diff --git a/.gitignore b/.gitignore new file mode 100644 index 0000000..ba0430d --- /dev/null +++ b/.gitignore @@ -0,0 +1 @@ +__pycache__/ \ No newline at end of file diff --git a/.gitmodules b/.gitmodules new file mode 100644 index 0000000..0807146 --- /dev/null +++ b/.gitmodules @@ -0,0 +1,3 @@ +[submodule "data_tooling"] + path = data_tooling + url = https://github.com/bigscience-workshop/data_tooling.git diff --git a/.idea/.gitignore b/.idea/.gitignore new file mode 100644 index 0000000..73f69e0 --- /dev/null +++ b/.idea/.gitignore @@ -0,0 +1,8 @@ +# Default ignored files +/shelf/ +/workspace.xml +# Datasource local storage ignored files +/dataSources/ +/dataSources.local.xml +# Editor-based HTTP Client requests +/httpRequests/ diff --git a/.idea/inspectionProfiles/profiles_settings.xml b/.idea/inspectionProfiles/profiles_settings.xml new file mode 100644 index 0000000..105ce2d --- /dev/null +++ b/.idea/inspectionProfiles/profiles_settings.xml @@ -0,0 +1,6 @@ + + + + \ No newline at end of file diff --git a/.idea/misc.xml b/.idea/misc.xml new file mode 100644 index 0000000..d1e22ec --- /dev/null +++ b/.idea/misc.xml @@ -0,0 +1,4 @@ + + + + \ No newline at end of file diff --git a/.idea/modules.xml b/.idea/modules.xml new file mode 100644 index 0000000..b53bd43 --- /dev/null +++ b/.idea/modules.xml @@ -0,0 +1,8 @@ + + + + + + + + \ No newline at end of file diff --git a/.idea/muliwai.iml b/.idea/muliwai.iml new file mode 100644 index 0000000..8b8c395 --- /dev/null +++ b/.idea/muliwai.iml @@ -0,0 +1,12 @@ + + + + + + + + + + \ No newline at end of file diff --git a/.idea/vcs.xml b/.idea/vcs.xml new file mode 100644 index 0000000..9632421 --- /dev/null +++ b/.idea/vcs.xml @@ -0,0 +1,7 @@ + + + + + + + \ No newline at end of file diff --git a/TextAugment.py b/TextAugment.py new file mode 100644 index 0000000..c69edea --- /dev/null +++ b/TextAugment.py @@ -0,0 +1,1258 @@ +""" +Copyright, 2021-2022 Ontocord, LLC, All rights reserved. + +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. +""" +import os +import re +import fsspec +from tqdm import tqdm +import difflib +import langid +import json +import random +import logging +from typing import List, Dict, Optional + +import torch +from torch.nn.functional import cosine_similarity +import spacy +from nltk.corpus import stopwords + +from data_tooling.ac_dc.stopwords import stopwords as stopwords_ac_dc +from data_tooling.ac_dc.badwords import badwords as badwords_ac_dc +from data_tooling.pii_processing.ontology.ontology_manager import OntologyManager + +from datasets import load_dataset +from transformers import ( + AutoTokenizer, + M2M100ForConditionalGeneration, + M2M100Tokenizer, + MarianMTModel, + pipeline, +) +from sentence_transformers import SentenceTransformer + +import qg_pipeline +from utils import ( + rulebase, + banned_words, + hf_ner_model_map, + mariam_mt, + LoggingHandler, + get_oscar_urls, + download_urls, + CharManager, + get_docs, +) + +# torch.cuda.empty_cache() +# labse = SentenceTransformer("sentence-transformers/LaBSE").half().eval().cuda() +# qg = qg_pipeline.pipeline("multitask-qa-qg") +# +# ontology_manager = None # OntologyManager(target_lang='en') #target_lang=target_lang +# translation_pipelines = {} +# ner_model_name2pipelines = {} + +logging.basicConfig(format='%(asctime)s - %(message)s', + datefmt='%Y-%m-%d %H:%M:%S', + level=logging.INFO, + handlers=[LoggingHandler()]) + + +class TextAugment: + # don't add a space for junk chars + max_stoword_len_zh = max([len(a) for a in stopwords_ac_dc.get('zh', [''])]) + max_stoword_len_ko = max([len(a) for a in stopwords_ac_dc.get('ko', [''])]) + max_stoword_len_ja = max([len(a) for a in stopwords_ac_dc.get('ja', [''])]) + + def __init__(self, + ontology_manager: OntologyManager = None, + translation_pipelines: Dict = {}, + ner_model_name2pipelines: Dict = {}, + qg=None, + production_mode: bool = False): + + self.ontology_manager = ontology_manager + self.translation_pipelines = translation_pipelines + self.ner_model_name2pipelines = ner_model_name2pipelines + self.qg = qg + self.banned_words = banned_words + self.hf_ner_model_map = hf_ner_model_map + + self.strip_chars = CharManager.strip_chars + self.punc_char = CharManager.punc_char + self.special_char = CharManager.special_char + self.junk = CharManager.junk + + # models + # labse model from sentence transformers + self.labse = SentenceTransformer("sentence-transformers/LaBSE").half().eval().cuda() + + # spacy + self.en_spacy_nlp = spacy.load('en_core_web_sm') + + # m2m models for translation + self.m2m_model = M2M100ForConditionalGeneration.from_pretrained("facebook/m2m100_418M").eval().half().cuda() + self.m2m_tokenizer = M2M100Tokenizer.from_pretrained("facebook/m2m100_418M") + + # TODO: OntologyManager init has changed + if production_mode: # use the below for production usage. the above is for testing. + if not self.ontology_manager: self.ontology_manager = OntologyManager() # src_lang=src_lang + logging.info("Finished Loading TextAugment") + + def check_good_sentence(self, s, src_lang, stopwords, stopword_ratio_cutoff=0.06, bannedwords=None, badwords=None, + badword_ratio_cutoff=0.15, junk_ratio=0.16, max_badword_len=5): + # basic dejunk + # for badwords, only filter out if the ratio is exceeded AND there exists one banned word + if bannedwords is None: + bannedwords = self.banned_words.get(src_lang, self.banned_words['default']) + default_bannedwords = self.banned_words['default'] + s = s.lower().strip() + if not s: return False + # print ([s2 for s2 in s if s2 in self.junk]) + # print (len([s2 for s2 in s if s2 in self.junk]), len(s)) + jr = len([s2 for s2 in s if s2 in self.junk]) / len(s) + if jr >= junk_ratio: + return False + if src_lang in ("ja", "ko", "zh"): + sArr = s + else: + sArr = [s2.strip(self.special_char) for s2 in s.lower().split() if s2.strip(self.special_char)] + if len(sArr) == 0: + return False + # stopword check + if stopwords is not None: + # TODO: catch multi word with spaces + # print ('sw', len([s2 for s2 in sArr if s2 in stopwords])/len(sArr)) + if src_lang not in ("ja", "ko", "zh") and len([s2 for s2 in sArr if s2 in stopwords]) / len( + sArr) < stopword_ratio_cutoff: + return False + if src_lang in ("ja", "ko", "zh"): + if src_lang == "zh": + max_stoword = self.max_stoword_len_zh + elif src_lang == "ko": + max_stoword = self.max_stoword_len_ko + elif src_lang == "ja": + max_stoword = self.max_stoword_len_ja + + len_s = len(s) + stop_cnt = 0 + total_cnt = 0 + for i in range(len_s): + for j in range(i + 1, min(len_s, i + max_stoword)): + if s[i:j] in stopwords: + stop_cnt += 1 + total_cnt += 1 + # print ('stopword', (stop_cnt/total_cnt) ) + if (stop_cnt / total_cnt) < stopword_ratio_cutoff: + return False + if badwords is not None: + # print ('bw', len([s2 for s2 in sArr if s2 in badwords])/len(sArr)) + if src_lang not in ("ja", "ko", "zh") and len([s2 for s2 in sArr if s2 in badwords]) / len( + sArr) > badword_ratio_cutoff: + if any(s2 for s2 in sArr if s2 in bannedwords) or any(s2 for s2 in sArr if s2 in default_bannedwords): + return False + if src_lang in ("ja", "ko", "zh"): + badword_ratio_cutoff /= 100 + len_s = len(s) + bad_cnt = 0 + total_cnt = 0 + for i in range(len_s): + for j in range(i + 1, min(len_s, i + max_badword_len)): + if s[i:j] in badwords: + bad_cnt += 1 + total_cnt += 1 + if (bad_cnt / total_cnt) > badword_ratio_cutoff: + for bword in bannedwords: + if bword in s: + return False + for bword in default_bannedwords: + if bword in s: + return False + # langid check + try: + lang = langid.classify(s)[0] + except: + return True + return lang == src_lang + + def generate_questions(self, batch, default_answers=[]): + answers = {} + + i = 0 + allqa = [] + for chunk in batch: + text = chunk['text'] + answers1 = {} + # ti = time.time() + text = text.replace("U.S.", "US").replace("\n", " ").replace(",", " , ").replace(" ", " ").strip().replace( + " , ", ", ") # replace(" He ", " Lincoln ").replace(" he ", " Lincoln ").replace(" him ", " Lincoln ") + aHash = self.qg(text) # , default_answers=default_answers) + allqa.append(aHash) + default_answers = list(set([a['answer'] for a in aHash] + default_answers)) + print(aHash) + # for aHash1 in aHash: + # extraction = vis.parse(list(dep_parser(aHash1['question']).sents)[0], aHash1['answer']) + # print (extraction.arg1, '*', extraction.rel, '*', extraction.arg2) + + for aHash1 in aHash: + if answers.get(aHash1['answer'].lower()) or answers1.get(aHash1['answer'].lower()): + continue + if len(aHash1['answer'].split()) > 10: + aHash1['answer'] = " ".join(aHash1['answer'].split()[:10]) + i += 1 + quest = aHash1['question'].lower().strip("?").replace("'s", " 's").replace(" ", " ").split() + label = "" + # TODO, use spacy_en to get NER and only fall back to "who", "when", "where" to determine ner if we find nothing + if quest[0] == "who" and aHash1['answer'][-1] == 's': + label = "organization_" + str(i) + if "'s" in quest: + for j in range(len(quest)): + if j > 0 and quest[j - 1] == "'s": + label = quest[j] + "_" + str(i) + break + for a in aHash1['answer'].lower().split(): + if a not in stopwords_hash: + answers[a] = label + elif quest[0] == "who": + label = "person_" + str(i) + if "'s" in quest: + for j in range(len(quest)): + if j > 0 and quest[j - 1] == "'s": + label = quest[j] + "_" + str(i) + break + for a in aHash1['answer'].lower().split(): + if a not in stopwords_hash: + answers[a] = label + elif quest[0] == "where": + label = "location_" + str(i) + elif quest[0] == "when": + label = "date_or_time_" + str(i) + elif quest[0] == "why": + label = "reason_" + str(i) + elif quest[0] == "how" and quest[1] in ("much", "many"): + label = "quantity_" + str(i) + elif quest[0] == "how": + label = "method_" + str(i) + elif quest[0] in ("which", "what") and quest[1] not in stopwords_hash: + label = quest[1] + "_" + str(i) + elif "'s" in quest: + for j in range(len(quest)): + if j > 0 and quest[j - 1] == "'s": + label = quest[j] + "_" + str(i) + break + if label: + answers[aHash1['answer'].lower()] = label + + # for b in a['answer'].lower().split(): + # answers[b] = label + print(answers) + + for aHash in allqa: + answers1 = {} + for aHash1 in aHash: + if answers1.get(aHash1['answer'].lower()): + continue + quest = " " + aHash1['question'].lower().strip("?").replace("'s", " 's").replace(" ", " ") + " " + q_type = quest[0] + agent = [] + answer_keys = list(answers.keys()) + answer_keys.sort(key=lambda k: len(k), reverse=True) + for a in answer_keys: + if " " + a + " " in quest: + quest = quest.replace(" " + a + " ", " " + answers[a] + " ") + elif " " + a + ", " in quest: + quest = quest.replace(" " + a + ", ", " " + answers[a] + ", ") + quest = quest.split() + # print (quest) + qtype = [] + if answers.get(aHash1['answer'].lower()): + if answers.get(aHash1['answer'].lower()).split("_")[0] == "person": + qtype = ["is", "who"] + if not qtype and quest[0] in ("when", "where", "why", "how"): # , "which" + qtype = [quest[0]] + if quest[0] == "how" and quest[1] in ("much", "many"): + qtype = qtype + [quest[1]] + + # label=[q for q in quest if (q not in ("much", "many",) and not stopwords_hash.get(q) and q not in answers)]#+qtype + label = [q for q in quest if (q[0] not in "0123456789") and (q not in ("the", "a", "an"))] + if len(label) > 10: + label = label[:10] + answers1[aHash1['answer'].lower()] = " ".join(label) + print(answers1) + + @staticmethod + def get_aligned_text(sent1, sent2, src_lang): + """ + Given two sentences, find blocks of text that match and that don't match. + return the blocks, and a matching score. + Used to extract NER from original language sentence. + """ + if src_lang in ("ja", "ko", "zh"): + # splitting on spaces doesn't always work because some languages aren't space separated + sep = "" + else: + sep = " " + sent1 = sent1.split() + sent2 = sent2.split() + aMatch = difflib.SequenceMatcher(None, sent1, sent2) + score = aMatch.ratio() + blocks = aMatch.get_matching_blocks() + blocks2 = [] + prevEndA = 0 + prevEndB = 0 + matchLen = 0 + nonMatchLen = 0 + # print (blocks) + for blockI in range(len(blocks)): + if blockI > 0 or (blockI == 0 and (blocks[blockI][0] != 0 or blocks[blockI][1] != 0)): + blocks2.append( + [sep.join(sent1[prevEndA:blocks[blockI][0]]), sep.join(sent2[prevEndB:blocks[blockI][1]]), 0]) + nonMatchLen += max(blocks[blockI][0] - prevEndA, blocks[blockI][1] - prevEndB) + if blocks[blockI][2] != 0: + blocks2.append([sep.join(sent1[blocks[blockI][0]:blocks[blockI][0] + blocks[blockI][2]]), + sep.join(sent2[blocks[blockI][1]:blocks[blockI][1] + blocks[blockI][2]]), 1]) + prevEndA = blocks[blockI][0] + blocks[blockI][2] + prevEndB = blocks[blockI][1] + blocks[blockI][2] + matchLen += blocks[blockI][2] + # score = float(matchLen+1)/float(nonMatchLen+1) + return (blocks2, score) + + def do_translations(self, texts, src_lang='en', target_lang='hi', batch_size=16, do_mariam_mt=False): + if not do_mariam_mt: + try: + self.m2m_tokenizer.src_lang = src_lang + target_lang_bos_token = self.m2m_tokenizer.get_lang_id(target_lang) + translations = [] + for src_text_list in tqdm(self.batch(texts, batch_size)): + try: + batch = self.m2m_tokenizer(src_text_list, return_tensors="pt", padding=True, + truncation=True).to('cuda') + except: + break + gen = self.m2m_model.generate(**batch, forced_bos_token_id=target_lang_bos_token, + no_repeat_ngram_size=4, ) # + outputs = self.m2m_tokenizer.batch_decode(gen, skip_special_tokens=True) + translations.extend(outputs) + return translations + except: + pass + translations = [] + # mariam_mt = self.mariam_mt + model_name = mariam_mt.get((src_lang, target_lang)) + mt_pipeline = None + if model_name is not None and model_name not in self.translation_pipelines: + tokenizer = AutoTokenizer.from_pretrained(model_name) + model = MarianMTModel.from_pretrained(model_name).half().eval().cuda() + mt_pipeline = pipeline("translation", model=model, tokenizer=tokenizer, device=0) + self.translation_pipelines[model_name] = mt_pipeline + if not mt_pipeline: + raise RuntimeError( + "no translation pipeline") # we could do multi-step translation where there are no pairs + mt_pipeline = self.translation_pipelines[model_name] + for src_text_list in tqdm(self.batch(texts, batch_size)): + outputs = [t['translation_text'] for t in mt_pipeline(src_text_list)] + translations.extend(outputs) + return translations + + @staticmethod + def cjk_detect(texts): + # korean + if re.search("[\uac00-\ud7a3]", texts): + return "ko" + # japanese + if re.search("[\u3040-\u30ff]", texts): + return "ja" + # chinese + if re.search("[\u4e00-\u9FFF]", texts): + return "zh" + return None + + @staticmethod + def batch(lst, n): + """Generate batches""" + lst = list(lst) + for i in range(0, len(lst), n): + yield lst[i: i + n] + + def hf_ner(self, hf_pipeline, src_lang, docs, chunks, stopwords=None, weight=1.5): + """ + run the text through a Huggingface ner pipeline. + any tags found by this method will be weighted by the weight param + TODO: use the predicted value of the logits to further weight prediction + """ + + if stopwords is None: + stopwords = set(ac_dc_stopwords.get(src_lang, [])) + + offset_key = f'{src_lang}_offset' + text_key = f'{src_lang}_text' + ner_key = f'{src_lang}_ner' + results_arr = hf_pipeline([chunk[text_key] for chunk in chunks]) + results_arr2 = [] + offset = 0 + for chunk, results in zip(chunks, results_arr): + text = chunk[text_key] + _id = chunk['id'] + ner = docs[_id][ner_key] = docs[_id].get(ner_key, {}) + offset = chunk[offset_key] + len_text = len(text) + results = [ner_result for ner_result in results if ner_result['word'] not in ("[UNK]", "")] + if not results: + results_arr2.append([]) + continue + results2 = [] + if results[0]['start'] is not None: + results.sort(key=lambda a: a['start']) + else: + results.sort(key=lambda a: a['index']) + i = 0 + for ner_result in results: + ner_result['word'] = word = ner_result['word'].rstrip('@@') + ner_result['start'] = text.index(word, i) + i = ner_result['start'] + 1 + ner_result['end'] = ner_result['start'] + len(word) + + for ner_result in results: + start = ner_result['start'] + if not self.cjk_detect(text[ner_result['start']:ner_result['end']]): + if text[start] not in self.strip_chars: + for j in range(1, start): + if start - j == -1 or text[start - j] in self.strip_chars: + start = max(start - j, 0) + break + end = ner_result['end'] + if end < len_text and text[end] != ' ': + end += len(text[end:].split(' ', 1)[0]) + else: + start = ner_result['start'] + end = ner_result['end'] + while text[start] in self.strip_chars: + start += 1 + if start >= end: break + end = start + len(text[start:end].strip(self.strip_chars)) + ner_result['word'] = text[start:end] + ner_result['start'] = start + offset + ner_result['end'] = end + offset + if results2 and results2[-1]['end'] > ner_result['start']: + continue + results2.append(ner_result) + results_arr2.append(results2) + results_arr = results_arr2 + for chunk, results in zip(chunks, results_arr): + _id = chunk['id'] + ner = docs[_id][ner_key] + text = docs[_id][text_key] + len_text = len(text) + results = [ner_result for ner_result in results if ner_result['word'] not in ("[UNK]", "")] + if not results: continue + prev_word = [0, 0] + prev_label = None + prev_word2 = "" + for ner_result in results: + start = ner_result['start'] + if start is None: + prev_word2 = "" + continue + end = ner_result['end'] + if text[start:end] != ner_result['word']: + print('offset mismatch', text[start:end], ner_result['word']) + if "-" in ner_result['entity']: + _, label = ner_result['entity'].split('-') + else: + label = ner_result['entity'] + if label in ('STREET_ADDRESS',): + label = 'STREET_ADDRESS' + elif label in ('PUBLIC_FIGURE',): + label = 'PUBLIC_FIGURE' + elif label in ('NAME', 'PER', 'PERSON'): + label = 'PERSON' + elif label in ('LOCATION', 'LOC', 'GPE'): + label = 'GPE' + elif label in ('ORGANIZATION', 'ORG'): + label = 'ORG' + elif label in ('AGE',): + label = 'AGE' + elif label in ('NORP',): + label = 'NORP' + elif label in ('BIO', 'SYMPTOM_AND_DISEASE', 'DISEASE'): + label = 'DISEASE' + elif label in ('PATIENT_ID', 'GOVT_ID'): + label = 'GOVT_ID' + elif label in ('USER_ID',): + label = 'USER_ID' + elif label in ('MISC',) and '@' in ner_result['word']: + label = 'USER_ID' + else: + label = 'MISC' + if prev_label is not None: + if not ner_result['entity'].startswith('B-') and label == prev_label and ( + prev_word[1] >= start - 5): + prev_word[1] = max(prev_word[1], end) + prev_word2 = prev_word2 + " " + ner_result['word'] + else: + if ner_result['entity'].startswith('B-'): + if prev_word[1] > start: + prev_word[1] = start + if prev_word[0] != prev_word[1]: + ner_word = text[prev_word[0]:prev_word[1]] + # if ner_word != prev_word2: + # print (ner_word, '**', prev_word2) + # ner_word.strip(self.strip_chars) + mention = (ner_word, prev_word[0], prev_word[1]) + if ner_word and ner_word.lower() not in stopwords: + aHash = ner.get(mention, {}) + aHash[prev_label] = aHash.get(prev_label, 0) + weight * (1.0 + len(ner_word) / 100) + ner[mention] = aHash + prev_word = [start, end] + prev_word2 = ner_result['word'] + elif prev_label is None: + prev_word = [start, end] + prev_word2 = ner_result['word'] + prev_label = label + + if prev_label is not None and prev_word[0] != prev_word[1]: + ner_word = text[prev_word[0]:prev_word[1]] + # if ner_word != prev_word2: + # print (ner_word, '**', prev_word2) + mention = (ner_word, prev_word[0], prev_word[1]) + if ner_word and ner_word.lower() not in stopwords: + aHash = ner.get(mention, {}) + aHash[prev_label] = aHash.get(prev_label, 0) + weight * (1.0 + len(ner_word) / 100) + ner[mention] = aHash + + def _spacy_pipeline(self, lang: str=None): + spacy_nlp = None + try: + spacy_nlp = spacy.load(f"{lang}_core_web_sm") + except: + logging.error(f"Failed to load spacy pipeline for {lang} at {lang}_core_web_sm") + finally: + return spacy_nlp + + def spacy_ner(self, docs, nlp, stopwords, spacy_weight, src_lang, extra_weight=1.0): + """ + Use the spacy models to create mentions w/ NER + """ + if not nlp: + return + if stopwords is None: + stopwords = set(ac_dc_stopwords.get(src_lang, [])) + offset_key = f'{src_lang}_offset' + text_key = f'{src_lang}_text' + ner_key = f'{src_lang}_ner' + for doc in docs.values(): + ner = doc[ner_key] = doc.get(ner_key, {}) + text = doc[text_key] + doc = nlp(text) + entities = list(doc.ents) + ents = [(entity.text, entity.label_ if ( + entity.label_ in ('PERSON', 'GPE', 'ORG', 'NORP') and 'http:' not in entity.text) else 'MISC') + for entity in entities] + i = 0 + for ner_word, label in ents: + ner_word = ner_word.strip(self.strip_chars) + if ner_word and ner_word.lower() not in stopwords: + if not self.cjk_detect(ner_word): + if ner_word not in text: continue + i += text[i:].index(ner_word) + ner_word = text[i:].split(" ", 1)[0] + ner_word = ner_word.strip(self.strip_chars) + if ner_word.lower() not in stopwords: + mention = (ner_word, i, i + len(ner_word)) + aHash = ner.get(mention, {}) + aHash[label] = aHash.get(label, 0) + spacy_weight * (1.0 + len(ner_word) / 100) * extra_weight + ner[mention] = aHash + + def trim_to_prefer_person(self, docs, chunks, prob=100): + # downsample to mostly docs with mentions of people, govt_id and email + # if there were no ner set, then don't downsample the doc + len_docs = len(docs) + do_ids = [] + for _id, doc in docs.items(): + if not any(key for key in doc if key.endswith('_ner')): + do_ids.append(_id) + continue + found_ner = False + for key in list(doc.keys()): + if doc.get('has_person'): + do_ids.append(_id) + break + if key.endswith('_ner'): + if not found_ner: + found_ner = doc[key] != {} + ner = doc[key] + for aHash in ner.values(): + if 'PUBLIC_FIGURE' in aHash or 'PERSON' in aHash or 'GOVT_ID' in aHash or 'USER_ID' in aHash: + doc['has_person'] = True + do_ids.append(_id) + break + if doc.get('has_person'): + do_ids.append(_id) + elif not doc.get('has_person') and random.randint(0, prob) == 0: + do_ids.append(_id) + do_ids = set(do_ids) + chunks2 = [chunk for chunk in chunks if chunk['id'] in do_ids] + docs2 = dict([(doc['id'], doc) for doc in docs.values() if doc['id'] in do_ids]) + if len(docs2) == 0 or len_docs == len(docs2): + return docs, chunks + logging.info(f'trim_to_prefer_person {str((len_docs - len(docs2)) / len_docs)}') + return docs2, chunks2 + + def _split_text_into_chunks(self, + src_lang: str, + src_is_cjk: bool, + doc: Dict, + batch_window: int, + sep: str, + chunks: [Dict], + ) -> None: + offset = 0 + text = [] + + textarr = doc[f'{src_lang}_text'] if src_is_cjk else doc[f'{src_lang}_text'].split() + + for t in textarr: + punc_found = [punc for punc in t if punc in self.punc_char] + if punc_found and t[-1] not in self.punc_char and t[0] not in "0123456789" and t[0] == t[0].lower(): + w = t[t.index(punc_found[0]) + 1] + if w == w.upper(): + t, t1 = t.split(punc_found[0], 1) + t = t + punc_found[0] + (" " if src_is_cjk else "") + text.append(t) + text.append(t1) + continue + text.append(t) + text[0] = text[0].lstrip() + text[-1] = text[-1].rstrip() + doc[f'{src_lang}_text'] = sep.join(text) + len_text = len(text) + while len_text > batch_window: + for j in range(batch_window - 1, len_text): + if (src_is_cjk and text[j] in self.punc_char) or ( + not src_is_cjk and text[j][-1] in self.punc_char): + break + text_str = sep.join(text[:j + 1]) + chunks.append({f'{src_lang}_text': text_str, 'id': doc['id'], f'{src_lang}_offset': offset}) + doc['chunks'].append(chunks[-1]) + offset += len(text_str) + (0 if src_is_cjk else 1) + text = text[j + 1:] + len_text = len(text) + if text: + text_str = sep.join(text) + chunks.append({f'{src_lang}_text': text_str, 'id': doc['id'], f'{src_lang}_offset': offset}) + doc['chunks'].append(chunks[-1]) + + def process_ner_chunks_with_trans(self, + src_lang, + docs, + chunks, + target_lang=None, + do_spacy=True, + do_hf_ner=True, + do_ontology=True, + do_backtrans=False, + do_regex=True, + do_cleanup=True, + batch_size=5, + batch_window=70, + ontology_weight=0.9, + spacy_weight=1.25, + hf_ner_weight=1.0, + backtrans_weight=0.9, + do_postprocessing_after_backtrans=False, + do_docs_trim=False): + if target_lang is None: + target_lang = src_lang + do_backtrans = False + backtrans_weight = 1.0 + + if target_lang == src_lang and do_backtrans: + do_backtrans = False + logging.warning(f"Warning src_lang==target_lang={src_lang} but do_backtrans=={True}") + logging.info(f"Set do_backtrans=={False}") + + stopwords1 = set(stopwords_ac_dc[src_lang]) + stopwords2 = set(stopwords_ac_dc[target_lang]) + ner_pipelines = [] + + # init spacy pipeline + spacy_nlp = self._spacy_pipeline(target_lang) if do_spacy else None + + + + # init hf ner pipelines + if do_hf_ner: + for model_name, model_cls, hf_ner_weight2 in self.hf_ner_model_map.get(target_lang, []): + if model_name not in self.ner_model_name2pipelines: + logging.info(f"adding {model_name} into ner_model_name2pipelines") + # TODO: specific tf or pytroch in hf_ner_model_map to avoid error + ner_pipeline = None + try: + ner_pipeline = pipeline("ner", model=model_name, + tokenizer=(model_name, {"use_fast": True},), device=0) + except: + ner_pipeline = pipeline("ner", model=model_name, + tokenizer=(model_name, {"use_fast": True},), framework="tf", + device=0) + finally: + self.ner_model_name2pipelines[model_name] = ner_pipeline + ner_pipelines.append((self.ner_model_name2pipelines[model_name], hf_ner_weight2)) + + target_is_cjk = target_lang in ('zh', 'ko', 'ja') + src_is_cjk = src_lang in ('zh', 'ko', 'ja') + + if do_backtrans: + # translate from src_lang to target_lang and do ner in target_lang. translation also acts as an error check and additional ner. + # we check to see if the already tagged items in src lang should have scores for tags increased or are common words in target lang and should not be tagged. + # we also add new labels for items that are already tagged in src_lang. + + sep = "" if src_is_cjk else " " + + if src_is_cjk: + lbracket = "[[" + rbracket = "]]" + else: + lbracket = "[" + rbracket = "]" + + for chunk in chunks: + text = chunk[f'{src_lang}_text'].replace("(", "{").replace(")", "}") + _id = chunk['id'] + offset = chunk[f'{src_lang}_offset'] + doc = docs[_id] + offset_end = offset + len(text) + if f'{src_lang}_items' not in doc: + doc[f'{src_lang}_items'] = list(doc.get(f'{src_lang}_ner', {}).keys()) + doc[f'{src_lang}_items'].sort(key=lambda a: a[1]) + i = 0 + for idx, key in enumerate(doc[f'{src_lang}_items']): + if key[1] < offset: + continue + if key[2] > offset_end: + break + if len(key[0]) < 4 and not self.cjk_detect(key[0]): + if " " + key[0] + " " in text[i:]: + j = text.index(" " + key[0] + " ", i) + text = text[:j] + (text[j:].replace(" " + key[0] + " ", f" **{idx}** ", 1)) + i = j + else: + if key[0] in text[i:]: + j = text.index(key[0], i) + text = text[:j] + (text[j:].replace(key[0], f" **{idx}** ", 1)) + i = j + chunk[f'{src_lang}_tmpl_text'] = text + + src_items_sorted = list(enumerate(doc[f'{src_lang}_items'])) + src_items_sorted.sort(key=lambda a: len(a[1][0])) + for chunk in chunks: + text = chunk[f'{src_lang}_tmpl_text'] + _id = chunk['id'] + doc = docs[_id] + for idx, key in src_items_sorted: + if len(key[0]) < 5 and not self.cjk_detect(key[0]): + text = text.replace(" " + key[0] + " ", f" **{idx}** ") + else: + text = text.replace(key[0], f" **{idx}** ") + chunk[f'{src_lang}_tmpl_text'] = text + + for chunk in chunks: + text = chunk[f'{src_lang}_tmpl_text'] + _id = chunk['id'] + doc = docs[_id] + for idx, key in enumerate(doc[f'{src_lang}_items']): + text = text.replace(f" **{idx}** ", f" {idx} {lbracket} {key[0]} {rbracket}") + chunk[f'{src_lang}_tmpl_text'] = text.replace(" ", " ") + + # print ('*****', chunks2) + chunks2 = [chunk[f'{src_lang}_tmpl_text'] for chunk in chunks] + text2 = self.do_translations(chunks2, src_lang=src_lang, target_lang=target_lang, batch_size=batch_size) + for chunk, trans_text in zip(chunks, text2): + # langid check + try: + lang = langid.classify(trans_text)[0] + except: + lang = target_lang + if lang == target_lang: + chunk[f'{target_lang}_text'] = trans_text.lstrip(" .").replace(rbracket, "]").replace(lbracket, + "[").replace( + "}", ")").replace("{", "(") + else: + chunk[f'{target_lang}_text'] = " . . . " + + all_embed = self.labse.encode(chunks2, convert_to_tensor=True) + all_trans_embed = self.labse.encode([chunk[f'{target_lang}_text'] for chunk in chunks], + convert_to_tensor=True) + similarity = cosine_similarity(all_embed, all_trans_embed, dim=1) + for chunk, sim_score in zip(chunks, similarity): + trans_text = chunk[f'{target_lang}_text'] + sim_score = sim_score.item() + print(sim_score, '**', trans_text, '**', chunk[f'{src_lang}_tmpl_text']) + _id = chunk['id'] + doc = docs[_id] + if sim_score < 0.75: + trans_text = chunk[f'{target_lang}_text'] = " . . . " + if doc.get(f'{target_lang}_text', ""): + chunk[f'{target_lang}_offset'] = len(doc.get(f'{target_lang}_text', "")) + 1 + else: + chunk[f'{target_lang}_offset'] = 0 + doc[f'{target_lang}_text'] = (doc.get(f'{target_lang}_text', "") + " " + trans_text).strip() + chunk[f'{src_lang}_2_{target_lang}_sim'] = 0.0 + continue + chunk[f'{src_lang}_2_{target_lang}_sim'] = sim_score + len_items = len(doc[f'{src_lang}_items']) + doc[f'{target_lang}_2_{src_lang}_ner'] = doc.get(f'{target_lang}_2_{src_lang}_ner', {}) + while "[" in trans_text: + before, after = trans_text.split("[", 1) + before = before.strip() + after = after.strip() + before_arr = before.split() + if "]" not in after or not before_arr: + trans_text = before + sep + after + continue + idx = before_arr[-1] + ent, after = after.split("]", 1) + ent = ent.strip() + + try: + idx = int(idx) + except: + idx = None + if idx is not None and idx < len_items: + before = " ".join(before_arr[:-1]) + key = doc[f'{src_lang}_items'][idx] + ent_lower = ent.lower() + if ent_lower in stopwords2: + # reduce weight of target labels if this is translated into an en stopword + if key in doc[f'{src_lang}_ner']: + aHash = doc[f'{src_lang}_ner'][key] + for key in list(aHash.keys()): + aHash[key] /= 2.0 + else: + vals = list(doc[f'{src_lang}_ner'][key].keys()) + ent = ent.strip(self.strip_chars) + doc[f'{target_lang}_2_{src_lang}_ner'][ent] = idx + trans_text = before + " " + ent + " " + after + trans_text = chunk[f'{target_lang}_text'] = trans_text.replace(" ", "").strip() + if doc.get(f'{target_lang}_text', ""): + chunk[f'{target_lang}_offset'] = len(doc.get(f'{target_lang}_text', "")) + 1 + else: + chunk[f'{target_lang}_offset'] = 0 + doc[f'{target_lang}_text'] = (doc.get(f'{target_lang}_text', "") + " " + trans_text).strip() + + if do_regex: + pass # TBD + + if do_ontology: + # ontology - context independent - there are some bugs in disease detection which needs to be fixed + for doc in docs.values(): + doc[f'{target_lang}_ner'] = ner = doc.get(f'{target_lang}_ner', {}) + if target_lang == 'en': + chunk2ner = self.ontology_manager.tokenize(doc[f'{target_lang}_text'])['chunk2ner'] + onto_items = [] + for c, label in chunk2ner.items(): + ner_word = c[0].replace(" ", "").replace("_", "").replace("_", "") if self.cjk_detect(c[0]) else \ + c[0].replace("_", " ").replace("_", " ").rstrip(self.strip_chars) + if ner_word.lower() not in stopwords2: + if not self.cjk_detect(ner_word) and label in ( + 'PERSON', 'PUBLIC_FIGURE', 'ORG') and " " not in ner_word: continue + onto_items.append(((ner_word, c[1], c[1] + len(ner_word)), label)) + for ner_mention, label in list(set(onto_items)): + aHash = ner.get(ner_mention, {}) + aHash[label] = aHash.get(label, 0) + ontology_weight * ( + 1.0 + len(ner_mention[0]) / 100) * backtrans_weight + ner[ner_mention] = aHash + + if do_spacy: + if spacy_nlp: + # spacy + self.spacy_ner(docs, spacy_nlp, stopwords2, spacy_weight, target_lang, extra_weight=backtrans_weight) + + if do_hf_ner: + # transformer + for ner_pipeline, hf_ner_weight2 in ner_pipelines: + for a_batch in self.batch(chunks, batch_size): + self.hf_ner(ner_pipeline, target_lang, docs, a_batch, stopwords=stopwords2, + weight=hf_ner_weight * backtrans_weight * hf_ner_weight2) + + if do_cleanup: + # do some cleanups. we don't want any ner that are just short numbers, stopwords or single characters. + for _id, doc in docs.items(): + ner = doc[f'{target_lang}_ner'] + for key in list(doc[f'{target_lang}_ner'].keys()): + ner_word = key[0] + try: + if len(ner_word) < 4 and float(ner_word): + print("deleting ", ner_word) + del doc[f'{target_lang}_ner'][key] + continue + except: + pass + if ner_word.lower() in stopwords2 or (not self.cjk_detect(ner_word) and len(ner_word) <= 1): + print("deleting ", ner_word) + del doc[f'{target_lang}_ner'][key] + + # increase weight of src ner items if the target translations indicate it's an NER + if target_lang != src_lang: + for doc in docs.values(): + ner = doc[f'{target_lang}_ner'] + target2src_ner = doc.get(f'{target_lang}_2_{src_lang}_ner', {}) + for ent, idx in target2src_ner.items(): + key = doc[f'{src_lang}_items'][idx] + # NOTE that this is an unordered match + ner_match = [key2 for key2 in ner if ent == key2[0]] + if not ner_match and len(ent) > 3: + ner_match = [key2 for key2 in ner if (ent in key2[0] or (len(key2[0]) > 3 and key2[0] in ent))] + if ner_match: + if key in doc[f'{src_lang}_ner']: + aHash = doc[f'{src_lang}_ner'][key] + all_labels = [] + for key2 in ner_match: + all_labels.extend(list(ner[key2].keys())) + all_labels = set(all_labels) + found = False + for label in list(aHash.keys()): + if label in all_labels or 'MISC' in all_labels: + aHash[label] *= 1.1 + print('increasing ', key, label, aHash[label]) + found = True + if not found: + print('not found', key, all_labels) + + if do_docs_trim: + docs, chunks = self.trim_to_prefer_person(docs, chunks) + + if do_backtrans and target_lang != src_lang: + # backtrans from src_lang to target_lang back to src_lang allows us to catch more NER using target lang NER tools. + # then we tag in target_lang those items we haven't already found, and tranlsate back to match the original text. + # NOTE: We do not modify the original text, but only use backtrans to do NER tagging and other analysis. + + sep = "" if target_is_cjk else " " + + if target_is_cjk: + lbracket = "[[" + rbracket = "]]" + else: + lbracket = "[" + rbracket = "]" + for chunk in chunks: + _id = chunk['id'] + text = chunk[f'{target_lang}_text'].replace("[", "{").replace("(", "{").replace(")", "}").replace("]", + "}") + offset = chunk[f'{target_lang}_offset'] + doc = docs[_id] + offset_end = offset + len(text) + if f'{target_lang}_items' not in doc: + doc[f'{target_lang}_items'] = list(doc.get(f'{target_lang}_ner', {}).keys()) + doc[f'{target_lang}_items'].sort(key=lambda a: a[1]) + i = 0 + for idx, key in enumerate(doc[f'{target_lang}_items']): + if key[1] < offset: + continue + if key[2] > offset_end: + break + if len(key[0]) < 5 and not self.cjk_detect(key[0]): + if " " + key[0] + " " in text[i:]: + j = text.index(" " + key[0] + " ", i) + text = text[:j] + (text[j:].replace(" " + key[0] + " ", f" **{idx}** ", 1)) + i = j + else: + if key[0] in text[i:]: + j = text.index(key[0], i) + text = text[:j] + (text[j:].replace(key[0], f" **{idx}** ", 1)) + i = j + chunk[f'{target_lang}_tmpl_text'] = text + + target_items_sorted = list(enumerate(doc[f'{target_lang}_items'])) + target_items_sorted.sort(key=lambda a: len(a[1][0])) + for chunk in chunks: + text = chunk[f'{target_lang}_tmpl_text'] + _id = chunk['id'] + doc = docs[_id] + for idx, key in target_items_sorted: + if len(key[0]) < 5 and not self.cjk_detect(key[0]): + text = text.replace(" " + key[0] + " ", f" **{idx}** ") + else: + text = text.replace(key[0], f" **{idx}** ") + chunk[f'{target_lang}_tmpl_text'] = text + + for chunk in chunks: + text = chunk[f'{target_lang}_text'] + _id = chunk['id'] + doc = docs[_id] + for idx, key in enumerate(doc[f'{target_lang}_items']): + text = text.replace(f" **{idx}** ", f" {idx} {lbracket} {key[0]} {rbracket}") + chunk[f'{target_lang}_tmpl_text'] = text.replace(" ", " ") + + backtrans_text = self.do_translations([chunk[f'{target_lang}_tmpl_text'] for chunk in chunks], + src_lang=target_lang, target_lang=src_lang, batch_size=batch_size) + for chunk, trans_text in zip(chunks, backtrans_text): + # langid check + try: + lang = langid.classify(trans_text)[0] + except: + lang = target_lang + if lang == target_lang: + chunk[f'{src_lang}_text_backtrans_from_{target_lang}'] = trans_text.lstrip(" .").replace(rbracket, + "]").replace( + lbracket, "[").replace("}", ")").replace("{", "(") + else: + chunk[f'{src_lang}_text_backtrans_from_{target_lang}'] = " . . . " + # TODO: do similiarty test? + for chunk, trans_text in zip(chunks, backtrans_text): + _id = chunk['id'] + doc = docs[_id] + orig_text = chunk[f'{src_lang}_text'] + trans_text = chunk[f'{src_lang}_text_backtrans_from_{target_lang}'] + items = doc[f'{target_lang}_items'] + len_items = len(items) + doc[f'{src_lang}_2_{target_lang}_backtrans_ner'] = ner = doc.get( + f'{src_lang}_2_{target_lang}_backtrans_ner', {}) + pos = 0 + blocks, score = self.get_aligned_text(orig_text, trans_text, src_lang) + prev_t = None + prev_o = None + ner_word = "" + ent2 = "" + idx = None + for o, t, _ in blocks: + before = after = "" + if "]" in t: + ner_word = "" + ent2 = "" + t_arr = t.split("]") + before = sep.join(t_arr[-1:]) + after = t_arr[-1] + before = before.strip() + if not before: + continue + idx = before.split()[-1] + try: + idx = int(idx) + except: + idx = None + if prev_t and prev_t.strip(): + idx = prev_t.strip().split()[-1] + try: + idx = int(idx) + except: + idx = None + pass + if idx is not None and idx < len_items: + ner_word += o + if after: + ent2 = after.split("[", 1)[0] + else: + ent2 += t.split("[", 1)[0] + if "[" in t: + key = items[idx] + if key in ner: + ner_word = ner_word.strip(self.strip_chars) + ent2 = ent2.strip(self.strip_chars) + if ent2 in ner_word: + ner_word = ent2 + else: + if src_is_cjk: + ent2arr = list(ent2) + ner_wordarr = list(ner_word) + else: + ent2arr = ent2.split() + ner_wordarr = ner_word.split() + len_ent2arr = len(ent2arr) + found = False + if len_ent2arr > 3: + ent3 = sep.join(ent2arr[:3]) + if ent3 in new_word: + new_word = ner_word[ner_word.index(ent3):] + found = True + if not found: + if len_ent2arr < len(new_wordarr): + new_word = sep.join(new_wordarr[-len_ent2arr:]) + if ner_word and ner_word.lower() not in stopwords1: + i = orig_text[pos:].index(ner_word) + start = pos + i + len_nerword = len(ner_word) + pos = start + len_nerword + mention = (ner_word, offset + start, offset + start + len_nerword) + aHash = ner.get(mention, {}) + for label in ner[key]: + print(f'found new mention from {target_lang}', mention, label) + aHash[label] = aHash.get(label, 0) + ner[key][label] + ner[mention] = aHash + idx = None + ner_word = "" + ent2 = "" + prev_o, prev_t = o, t + + # increase the src_lang ner score if we already matched this ner in src_lang or there was a partial match + for doc in docs.values(): + bner = doc[f'{src_lang}_2_{target_lang}_backtrans_ner'] + ner = doc[f'{src_lang}_ner'] + for key, aHash in bner.items(): + if key in ner: continue + ent = key[0] + ner_match = [key2 for key2 in ner if ent == key2[0]] + if not ner_match and len(ent) > 3: + ner_match = [key2 for key2 in ner if (ent in key2[0] or (len(key2[0]) > 3 and key2[0] in ent))] + all_keys = [] + for key2 in ner_match: + all_keys.extend(list(ner[key2].keys())) + all_keys = set(all_keys) + for label in list(aHash.keys()): + if label in all_keys or 'MISC' in all_keys: + aHash[label] *= 1.1 + print('increasing in backtrans ', key, label, aHash[label]) + for key, aHash1 in bner.items(): + ner[key] = aHash2 = ner.get(key, {}) + for key2 in aHash1: + aHash2[key2] = aHash2.get(key2, 0.0) + aHash1[key2] + + if do_postprocessing_after_backtrans: + pass + + if do_cleanup: + # do some cleanups. we don't want any ner that are just short numbers, stopwords or single characters. + for _id, doc in docs.items(): + ner = doc[f'{src_lang}_ner'] + for key in list(doc[f'{src_lang}_ner'].keys()): + ner_word = key[0] + try: + if len(ner_word) < 4 and float(ner_word): + print("deleting ", ner_word) + del doc[f'{src_lang}_ner'][key] + continue + except: + pass + if ner_word.lower() in stopwords1 or (not self.cjk_detect(ner_word) and len(ner_word) <= 1): + print("deleting ", ner_word) + del doc[f'{src_lang}_ner'][key] + + return docs, chunks + + def process_ner(self, + src_lang: str = None, + docs=None, + do_spacy=True, + do_hf_ner=True, + do_ontology=True, + do_backtrans=False, + do_cleanup=True, + do_regex=True, + batch_size=5, + batch_window=70, + ontology_weight=0.9, + spacy_weight=1.25, + hf_ner_weight=1.5, + backtrans_weight=0.9, + do_docs_trim=True, + do_postprocessing_after_backtrans=False, + cutoff=None, + target_lang='en'): + + src_is_cjk = src_lang in ('zh', 'ko', 'ja') + sep = "" if src_is_cjk else " " + + if docs is None: + docs, domain = get_docs(src_lang=src_lang) + elif isinstance(docs, str): + docs = [{f'{src_lang}_text': docs}] + elif isinstance(docs, list): + if isinstance(docs[0], dict): + docs = docs + else: + docs = [{f'{src_lang}_text': t} for t in docs] + + # for testing only + if cutoff is not None and len(docs) > cutoff: + docs = docs[:cutoff] + + len_docs = len(docs) + for doc in docs: + doc[f'{src_lang}_text'] = doc['text'] + del doc['text'] + + badwords1 = set([s for s in badwords_ac_dc.get(src_lang, []) if len(s) < 5]) + stopwords1 = set(stopwords_ac_dc.get(src_lang, [])) + docs = [doc for doc in docs if + self.check_good_sentence(doc[f'{src_lang}_text'], src_lang, stopwords=stopwords1, badwords=badwords1)] + logging.info(f'trimmed junk {str((len_docs - len(docs)) / len_docs)}') + + chunks = [] + + for _id, doc in enumerate(docs): + if 'id' not in doc: + doc['id'] = str(_id) + doc.setdefault('id', str(_id)) + doc[f'{src_lang}_text'] = doc[f'{src_lang}_text'].replace("[", "(").replace("]",")") # we use [] as special chars + doc['lang'] = src_lang + doc['domain'] = domain + doc['chunks'] = [] + + self._split_text_into_chunks(src_lang=src_lang, src_is_cjk=src_is_cjk, doc=doc, batch_window=batch_window, sep=sep, chunks=chunks) + + docs = dict([(doc['id'], doc) for doc in docs]) + if do_docs_trim: + docs2, chunks2 = self.trim_to_prefer_person(docs, chunks) + do_docs_trim = len(docs2) == len(docs) + docs, chunks = docs2, chunks2 + + # we do this here because we don't want to trim ner items that are considered empty. + # we should probably fix trim_to_prefer_person to not do any trimming if all ner's are empty + for doc in docs.values(): + doc[f'{src_lang}_ner'] = doc.get(f'{src_lang}_ner', {}) + + # do ner processing in src_lang + docs2, chunks2 = self.process_ner_chunks_with_trans( + src_lang, + docs, + chunks, + do_spacy=do_spacy, + do_hf_ner=do_hf_ner, + do_ontology=do_ontology, + do_backtrans=False, + do_regex=do_regex, + do_cleanup=do_cleanup, + batch_size=batch_size, + ontology_weight=ontology_weight, + spacy_weight=spacy_weight, + hf_ner_weight=hf_ner_weight, + backtrans_weight=backtrans_weight, + do_postprocessing_after_backtrans=False, + do_docs_trim=do_docs_trim) + if do_docs_trim: + do_docs_trim = len(docs2) == len(docs) + docs, chunks = docs2, chunks2 + + if target_lang != src_lang: + # do ner processing in target language with optional backtrans + docs2, chunks2 = self.process_ner_chunks_with_trans( + src_lang, + docs, + chunks, + target_lang=target_lang, + do_spacy=do_spacy, + do_hf_ner=do_hf_ner, + do_ontology=do_ontology, + do_backtrans=do_backtrans, + do_regex=do_regex, + do_cleanup=do_cleanup, + batch_size=batch_size, + ontology_weight=ontology_weight, + spacy_weight=spacy_weight, + hf_ner_weight=hf_ner_weight, + backtrans_weight=backtrans_weight, + do_postprocessing_after_backtrans=True, + do_docs_trim=do_docs_trim) + docs, chunks = docs2, chunks2 + return docs, chunks diff --git a/data_tooling/.github/workflows/add-issue-to-project.yml b/data_tooling/.github/workflows/add-issue-to-project.yml new file mode 100644 index 0000000..3c92559 --- /dev/null +++ b/data_tooling/.github/workflows/add-issue-to-project.yml @@ -0,0 +1,81 @@ +name: Add Issue to project +on: + issues: + types: + - labeled +jobs: + add_data_catalog_issue_to_project_2: + runs-on: ubuntu-latest + if: github.event.label.name == 'data catalog' + steps: + - name: Generate token + id: generate_token + uses: tibdex/github-app-token@36464acb844fc53b9b8b2401da68844f6b05ebb0 + with: + app_id: ${{ secrets.BIGSCIENCE_WORKSHOP_PROJECTS_ID }} + private_key: ${{ secrets.BIGSCIENCE_WORKSHOP_PROJECTS_PEM }} + + - name: Get project data + env: + GITHUB_TOKEN: ${{ steps.generate_token.outputs.token }} + ORGANIZATION: bigscience-workshop + PROJECT_NUMBER: 2 + run: | + gh api graphql -f query=' + query($org: String!, $number: Int!) { + organization(login: $org){ + projectNext(number: $number) { + id + fields(first:20) { + nodes { + id + name + settings + } + } + } + } + }' -f org=$ORGANIZATION -F number=$PROJECT_NUMBER > project_data.json + + echo 'PROJECT_ID='$(jq '.data.organization.projectNext.id' project_data.json) >> $GITHUB_ENV + echo 'STATUS_FIELD_ID='$(jq '.data.organization.projectNext.fields.nodes[] | select(.name== "Status") | .id' project_data.json) >> $GITHUB_ENV + echo 'TODO_OPTION_ID='$(jq '.data.organization.projectNext.fields.nodes[] | select(.name== "Status") |.settings | fromjson.options[] | select(.name=="Todo") |.id' project_data.json) >> $GITHUB_ENV + + - name: Add Issue to project + env: + GITHUB_TOKEN: ${{ steps.generate_token.outputs.token }} + ISSUE_ID: ${{ github.event.issue.node_id }} + run: | + item_id="$( gh api graphql -f query=' + mutation($project:ID!, $issue:ID!) { + addProjectNextItem(input: {projectId: $project, contentId: $issue}) { + projectNextItem { + id + } + } + }' -f project=$PROJECT_ID -f issue=$ISSUE_ID --jq '.data.addProjectNextItem.projectNextItem.id')" + + echo 'ITEM_ID='$item_id >> $GITHUB_ENV + + - name: Set fields + env: + GITHUB_TOKEN: ${{ steps.generate_token.outputs.token }} + run: | + gh api graphql -f query=' + mutation ( + $project: ID! + $item: ID! + $status_field: ID! + $status_value: String! + ) { + set_status: updateProjectNextItemField(input: { + projectId: $project + itemId: $item + fieldId: $status_field + value: $status_value + }) { + projectNextItem { + id + } + } + }' -f project=$PROJECT_ID -f item=$ITEM_ID -f status_field=$STATUS_FIELD_ID -f status_value=${{ env.TODO_OPTION_ID }} --silent diff --git a/data_tooling/.github/workflows/label-with-contact-neede.yml b/data_tooling/.github/workflows/label-with-contact-neede.yml new file mode 100644 index 0000000..f5cae50 --- /dev/null +++ b/data_tooling/.github/workflows/label-with-contact-neede.yml @@ -0,0 +1,14 @@ +name: Label with contact needed +on: + issue_comment: + types: created +jobs: + one: + runs-on: ubuntu-latest + if: >- + (github.event.comment.body == '#contact' || + github.event.comment.body == '#contact-needed') + steps: + - run: | + echo "Labeling issue ${{ github.event.issue.number }} with 'contact needed'" + curl -H "Authorization: token ${{ secrets.GITHUB_TOKEN }}" -d '{"labels": ["contact needed"]}' https://api.github.com/repos/${{ github.repository }}/issues/${{ github.event.issue.number }}/labels diff --git a/data_tooling/.github/workflows/label-with-help-wanted.yml b/data_tooling/.github/workflows/label-with-help-wanted.yml new file mode 100644 index 0000000..342b1be --- /dev/null +++ b/data_tooling/.github/workflows/label-with-help-wanted.yml @@ -0,0 +1,14 @@ +name: Label with help wanted +on: + issue_comment: + types: created +jobs: + one: + runs-on: ubuntu-latest + if: >- + (github.event.comment.body == '#help' || + github.event.comment.body == '#help-wanted') + steps: + - run: | + echo "Labeling issue ${{ github.event.issue.number }} with 'help wanted'" + curl -H "Authorization: token ${{ secrets.GITHUB_TOKEN }}" -d '{"labels": ["help wanted"]}' https://api.github.com/repos/${{ github.repository }}/issues/${{ github.event.issue.number }}/labels diff --git a/data_tooling/.github/workflows/pii-manager.yml b/data_tooling/.github/workflows/pii-manager.yml new file mode 100644 index 0000000..da082ac --- /dev/null +++ b/data_tooling/.github/workflows/pii-manager.yml @@ -0,0 +1,38 @@ +on: + pull_request: + branches: + - master + paths: + - 'pii-manager/src/**' + - 'pii-manager/test/**' + - 'pii-manager/setup.py' + - 'pii-manager/Makefile' + - 'pii-manager/requirements.txt' + +jobs: + build: + runs-on: ubuntu-latest + strategy: + max-parallel: 4 + matrix: + python-version: [3.8] + + steps: + - name: Set up Python ${{ matrix.python-version }} + uses: actions/setup-python@v1 + with: + python-version: ${{ matrix.python-version }} + - name: Checkout main repository + uses: actions/checkout@v2 + - name: Create venv + run: | + cd pii-manager + VENV="$GITHUB_WORKSPACE/venv" make venv + - name: Install package + run: | + cd pii-manager + VENV="$GITHUB_WORKSPACE/venv" make install + - name: Test with pytest + run: | + cd pii-manager + VENV="$GITHUB_WORKSPACE/venv" make unit-verbose diff --git a/data_tooling/.github/workflows/self-assign.yaml b/data_tooling/.github/workflows/self-assign.yaml new file mode 100644 index 0000000..57f8dc4 --- /dev/null +++ b/data_tooling/.github/workflows/self-assign.yaml @@ -0,0 +1,15 @@ +name: Self-assign +on: + issue_comment: + types: created +jobs: + one: + runs-on: ubuntu-latest + if: >- + (github.event.comment.body == '#take' || + github.event.comment.body == '#self-assign') + && !github.event.issue.assignee + steps: + - run: | + echo "Assigning issue ${{ github.event.issue.number }} to ${{ github.event.comment.user.login }}" + curl -H "Authorization: token ${{ secrets.GITHUB_TOKEN }}" -d '{"assignees": ["${{ github.event.comment.user.login }}"]}' https://api.github.com/repos/${{ github.repository }}/issues/${{ github.event.issue.number }}/assignees diff --git a/data_tooling/.gitignore b/data_tooling/.gitignore new file mode 100644 index 0000000..d910675 --- /dev/null +++ b/data_tooling/.gitignore @@ -0,0 +1,150 @@ +# Byte-compiled / optimized / DLL files +__pycache__/ +*.py[cod] +*$py.class + +# C extensions +*.so + +# Distribution / packaging +.Python +build/ +develop-eggs/ +dist/ +downloads/ +eggs/ +.eggs/ +lib/ +lib64/ +parts/ +sdist/ +var/ +wheels/ +pip-wheel-metadata/ +share/python-wheels/ +*.egg-info/ +.installed.cfg +*.egg +MANIFEST + +# PyInstaller +# Usually these files are written by a python script from a template +# before PyInstaller builds the exe, so as to inject date/other infos into it. +*.manifest +*.spec + +# Installer logs +pip-log.txt +pip-delete-this-directory.txt + +# Unit test / coverage reports +htmlcov/ +.tox/ +.nox/ +.coverage +.coverage.* +.cache +nosetests.xml +coverage.xml +*.cover +*.py,cover +.hypothesis/ +.pytest_cache/ + +# Translations +*.mo +*.pot + +# Django stuff: +*.log +local_settings.py +db.sqlite3 +db.sqlite3-journal + +# Flask stuff: +instance/ +.webassets-cache + +# Scrapy stuff: +.scrapy + +# Sphinx documentation +docs/_build/ + +# PyBuilder +target/ + +# Jupyter Notebook +.ipynb_checkpoints + +# IPython +profile_default/ +ipython_config.py + +# pyenv +.python-version + +# pipenv +# According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control. +# However, in case of collaboration, if having platform-specific dependencies or dependencies +# having no cross-platform support, pipenv may install dependencies that don't work, or not +# install all needed dependencies. +#Pipfile.lock + +# PEP 582; used by e.g. github.com/David-OConnor/pyflow +__pypackages__/ + +# Celery stuff +celerybeat-schedule +celerybeat.pid + +# SageMath parsed files +*.sage.py + +# Environments +.env +.venv +env/ +venv/ +ENV/ +env.bak/ +venv.bak/ + +# Spyder project settings +.spyderproject +.spyproject + +# Rope project settings +.ropeproject + +# mkdocs documentation +/site + +# mypy +.mypy_cache/ +.dmypy.json +dmypy.json + +# Pyre type checker +.pyre/ + +# Fasttext model +lid.176.bin + +# Kenlm models +*.arpa.bin +*sp.model + +# Filtering outputs +*filtered.txt + +# DS_Store +.DS_Store +**/.DS_Store + +# Profiler +*.lprof +**/*.lprof + +# Visualization json files +**/*examples_with_stats.json diff --git a/data_tooling/.pre-commit-config.yaml b/data_tooling/.pre-commit-config.yaml new file mode 100644 index 0000000..5c195f6 --- /dev/null +++ b/data_tooling/.pre-commit-config.yaml @@ -0,0 +1,66 @@ +# To use: +# +# pre-commit run -a +# +# Or: +# +# pre-commit install # (runs every time you commit in git) +# +# To update this file: +# +# pre-commit autoupdate +# +# See https://github.com/pre-commit/pre-commit + +repos: +# Standard hooks +- repo: https://github.com/pre-commit/pre-commit-hooks + rev: v4.1.0 + hooks: + - id: check-added-large-files + - id: check-case-conflict + - id: check-docstring-first + exclude: ^pii_processing/ + - id: check-merge-conflict + - id: check-symlinks + - id: check-toml + - id: check-yaml + - id: debug-statements + exclude: ^pii_processing/ + - id: end-of-file-fixer + exclude: ^pii_processing/ + - id: mixed-line-ending + - id: requirements-txt-fixer + - id: trailing-whitespace + exclude: ^pii_processing/ + +- repo: https://github.com/asottile/pyupgrade + rev: v2.31.0 + hooks: + - id: pyupgrade + exclude: ^pii_processing/ + +#- repo: https://github.com/PyCQA/isort +# rev: 5.10.0 +# hooks: +# - id: isort + +# Black, the code formatter, natively supports pre-commit +- repo: https://github.com/psf/black + rev: 21.12b0 # Keep in sync with blacken-docs + hooks: + - id: black + exclude: ^pii_processing/ + +# Changes tabs to spaces +- repo: https://github.com/Lucas-C/pre-commit-hooks + rev: v1.1.10 + hooks: + - id: remove-tabs + exclude: ^(pii_processing|.*Makefile) + +- repo: https://github.com/shellcheck-py/shellcheck-py + rev: v0.8.0.3 + hooks: + - id: shellcheck + exclude: ^pii_processing/ diff --git a/data_tooling/LICENSE b/data_tooling/LICENSE new file mode 100644 index 0000000..261eeb9 --- /dev/null +++ b/data_tooling/LICENSE @@ -0,0 +1,201 @@ + Apache License + Version 2.0, January 2004 + http://www.apache.org/licenses/ + + TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION + + 1. 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The goal is not to be exhaustive on all possible metadata but to be pragmatic to align on the things that are already in the process of being recorded. + +### Metadata subjects + +For now 3 "objects of interests" are forseen in the project on which metadata could be applied: + +- data sources +- data set +- data sample (or document) + +### Key general format + +Simply text, in small cap and avoiding any punctuation (including spaces to be replaced by underline character '_' if really necessary) to ease automated parsing. + +### Value general format + +It will vary for each metadata key with an open standard to be used as reference whenever applicable. All text should be encoded in UTF-8 to cope with any language scripts. + +Some proposed value formats: + +| Type of value | Value | +|----------- |---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | +| language | ISO_639-3 => 3 letter codes with the most coverage (see for reference[wikipedia list of ISO_639-3 codes](https://en.wikipedia.org/wiki/Wikipedia:WikiProject_Languages/List_of_ISO_639-3_language_codes_(2019))) ex: afr for Afrikaans | +| | Note: IETF bcp 47 was proposed as an alternative in the data sourcing group, a list of standard values would be necessary to be practical (like the wikipedia list for ISO_639-3) +| timestamp | ISO_8601 normalized to UTC time zone ex: 2021-07-06T15:47:46+00:00 | +| URL | Full length URL including the scheme (eg http/ftp...) ex: https://en.wikipedia.org/wiki/URL | +| text | free text encoded in UTF-8 + +#### Annotation of text content + +For data sample, it is foreseen that information might be extracted from the original text content such as named entities using position reference to the original content. + +TO BE CONTINUED + +### Data source metadata format + +TO BE CONTINUED + +### Dataset metadata format + +TO BE CONTINUED + +### Data sample metadata format + +| Key | Value | +|----------------------- |---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | +| hash | unique fixed length that could be used as identifier - proposal to use murmur hash 128 bits | +| main_language | ISO_639-3 => 3 letter codes with the most coverage (see for reference[wikipedia list of ISO_639-3 codes](https://en.wikipedia.org/wiki/Wikipedia:WikiProject_Languages/List_of_ISO_639-3_language_codes_(2019))) ex: afr for Afrikaans | +| other_languages | list of ISO_639-3 codes of all languages possibly found in the sample without specific order | +| collection_timestamp | timestamp of original collection of the data (eg. for web crawl) if precisely known the default would be the timestamp of dataset creation | +| publication_timestamp | timestamp of the publication of the data (first time a web page has been online or last edit, radio/tv shows publication...) | +| original_content | free text + +TO BE CONTINUED + +ex: +```json +["89faeee174d2ddbc2b761207efbc8464", "fra", ["eng", "deu"], "2021-07-06T19:06:02Z", null, "je crois il est parti à Stuttgart ou bien à London"] +``` diff --git a/data_tooling/__init__.py b/data_tooling/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/data_tooling/ac_dc/README.md b/data_tooling/ac_dc/README.md new file mode 100644 index 0000000..7ec7560 --- /dev/null +++ b/data_tooling/ac_dc/README.md @@ -0,0 +1,102 @@ +## Big Science - Automated Classification & Dataset Curation - AC/DC + +This is the data filtering code for BigScience. + +See [this document](https://docs.google.com/document/d/1bx7lzAIWALH2IX5PLAiRfkHr3025dC-ZYkEmq4zB2gI/edit) for more details. + +The supported languages are defined in the file [languages_id.py](https://github.com/bigscience-workshop/data_tooling/blob/master/ac_dc/languages_id.py). + + +### Filtering + +#### 0. Understand the filtering pipeline + +Take a look at the pdf [explanation_filtering_pipeline.pdf](https://github.com/bigscience-workshop/data_tooling/blob/master/ac_dc/explanation_filtering_pipeline.pdf) for an explanation of the filtering pipeline. + +#### 1. Define the lists of stop words and bad words, and check how the anonymization and the normalization of texts are done + +You might want to redefine the lists of stop words and bad words for robustness or ethical reasons in the files [stopwords.py](https://github.com/bigscience-workshop/data_tooling/blob/master/ac_dc/stopwords.py) and [badwords.py](https://github.com/bigscience-workshop/data_tooling/blob/master/ac_dc/badwords.py). + +Less importantly, you can also check how the anonymization and the normalization of texts are done in the files [anonymization.py](https://github.com/bigscience-workshop/data_tooling/blob/master/ac_dc/anonymization.py) and [normalization.py](https://github.com/bigscience-workshop/data_tooling/blob/master/ac_dc/normalization.py) (if applicable, default is to use the anonymization and not to use the normalization). + +#### 2. Download everything you need + +To run the filtering code, it is necessary to download the dataset on which the filtering will take place, but also the necessary models, which are the Fasttext model for language identification (download [here](https://dl.fbaipublicfiles.com/fasttext/supervised-models/lid.176.bin)) and the Sentencepiece and KenLM models for tokenization and calculation of perplexity scores (download with the file [download_sentencepiece_kenlm_models.py](https://github.com/bigscience-workshop/data_tooling/blob/master/ac_dc/download_sentencepiece_kenlm_models.py)). + +#### 3. Choose the filtering parameters + +The filtering parameters for each language are to be specified in the file [parameters_filtering.py](https://github.com/bigscience-workshop/data_tooling/blob/master/ac_dc/parameters_filtering.py). It is strongly recommended to look at the data and use the visualization code in the directory [visualization](https://github.com/bigscience-workshop/data_tooling/tree/master/ac_dc/visualization) to choose these parameters. + +#### 4. Run the filtering + +Run the filtering with the file [main_filtering.py](https://github.com/bigscience-workshop/data_tooling/blob/master/ac_dc/main_filtering.py), specifying the dataset used and the links to the downloaded models. The different filters are coded in the file [filtering.py](https://github.com/bigscience-workshop/data_tooling/blob/master/ac_dc/filtering.py). + +#### 5. Do the deduplication + +Do the deduplication, which is detailed in the following section, with the file [deduplicate.py](https://github.com/bigscience-workshop/data_tooling/blob/master/ac_dc/deduplicate.py). + + +### Deduplication + +Runnable script example at `ac_dc/examples/dedup.sh` + +#### 0. Sharding a dataset + +We want to shard a dataset into multiple shards so that each node on HPC can take a shard and each shard can be further parallelized with CPU cores. + +```bash +python ac_dc/deduplicate.py create-shards "cache/sharded" 5 --path "oscar-corpus/OSCAR-2109" --name "deduplicated_af" --split "train" +# or +python ac_dc/deduplicate.py create-shards "cache/sharded" 5 --path "oscar-corpus/OSCAR-2109" --name "deduplicated_af" --data-dir "local path to data directory" --split "train" +``` + +It loads a local dataset and segments its `train` split into 5 shards/sub-datasets under `cache/sharded`. This gives you +``` +cache/sharded +├── sharded_00000.jsonl +├── sharded_00001.jsonl +├── sharded_00002.jsonl +├── sharded_00003.jsonl +└── sharded_00004.jsonl +``` + +#### 1. Create Simhashes +```bash +# run each command on each node +python ac_dc/deduplicate.py build-hashes "cache/deduplicated_af_hashes_00001" --data-files "sharded_00000.jsonl" --data-files "sharded_00001.jsonl" --path "cache/sharded" --split "train" +python ac_dc/deduplicate.py build-hashes "cache/deduplicated_af_hashes_00002" --data-files "sharded_00002.jsonl" --data-files "sharded_00003.jsonl" --path "cache/sharded" --split "train" +python ac_dc/deduplicate.py build-hashes "cache/deduplicated_af_hashes_00003" --data-files "sharded_00004.jsonl" --path "cache/sharded" --split "train" +``` +The above commands add an addition column `hash` in the data and outputs two datasets at `cache/en_hashes_00001` and `cache/en_hashes_00002`. This is useful for large dataset and each node/worker can hash some shards of the data in parallel. + +#### 2. Create a Simhash Index +```bash +python ac_dc/deduplicate.py build-index "cache/deduplicated_af_simhash_index.ann" "cache/deduplicated_af_hashes_00001" "cache/deduplicated_af_hashes_00002" "cache/deduplicated_af_hashes_00003" --split "train" +``` +This creates the index file based on ALL the hashed datasets. This is a merge step and takes O(n) time. + +#### 3. Find Duplicates +```bash +# run each command on each node +LOG_LEVEL="INFO" python ac_dc/deduplicate.py find-duplicates "cache/deduplicated_af_hashes_00001" "cache/deduplicated_af_simhash_index.pkl" --split "train" --k 100 --threshold 3 +LOG_LEVEL="INFO" python ac_dc/deduplicate.py find-duplicates "cache/deduplicated_af_hashes_00002" "cache/deduplicated_af_simhash_index.pkl" --split "train" --k 100 --threshold 3 +LOG_LEVEL="INFO" python ac_dc/deduplicate.py find-duplicates "cache/deduplicated_af_hashes_00003" "cache/deduplicated_af_simhash_index.pkl" --split "train" --k 100 --threshold 3 +``` +This adds another column `duplicates` into the data with the index and outputs them into `cache/en_hashes_0000{1,2,3}_duplicates`. + +#### 4. Remove Duplicates +```bash +python ac_dc/deduplicate.py remove-duplicates "cache/deduplicated_af_hashes_00001_duplicates" "cache/deduplicated_af_hashes_00002_duplicates" "cache/deduplicated_af_hashes_00003_duplicates" --split "train" +``` +This removes all duplicates from the given datasets and outputs `cache/en_hashes_0000{1,2,3}_deduplicated`; Partially parallelized because thre is a step finding connected components of duplicates and it takes O(n) time. + +#### 5. Merge Shards +```bash +python ac_dc/deduplicate.py merge-shards "cache/simhash_deduplicated_af" "cache/deduplicated_af_hashes_00001_deduplicated" "cache/deduplicated_af_hashes_00002_deduplicated" "cache/deduplicated_af_hashes_00003_deduplicated" --split "train" +``` +This merges all shards back into one dataset. + + +### Merge metadata from OSCAR 21.09 to OSCAR + +Runnable script example at `ac_dc/examples/merge.sh` diff --git a/data_tooling/ac_dc/anonymization.py b/data_tooling/ac_dc/anonymization.py new file mode 100644 index 0000000..dbe478c --- /dev/null +++ b/data_tooling/ac_dc/anonymization.py @@ -0,0 +1,472 @@ +import re, regex + + +trannum = str.maketrans("0123456789", "1111111111") + +address_regex = { + "en": { + "en_US": [ + ( + re.compile( + r"P\.? ?O\.? Box \d+|\d{1,4} [\w\s]{1,20} (?:street|st|avenue|ave|road|rd|highway|hwy|square|sq|trail|trl|drive|dr|court|ct|park|parkway|pkwy|circle|cir|boulevard|blvd)\W?(?=\s|$)" + ), + None, + ) + ], + # getting an unbalanced paranthesis in en_AU + # "en_AU": [(re.compile(r"\b(?:(?!\s{2,}).)*)\b(VIC|NSW|ACT|QLD|NT|SA|TAS|WA).?\s*(\b\d{4}|\b(?:(?!\s{2,}|\$|\:|\.\d).)*\s(?:Alley|Ally|Arcade|Arc|Avenue|Ave|Boulevard|Bvd|Bypass|Bypa|Circuit|Cct|Close|Cl|Corner|Crn|Court|Ct|Crescent|Cres|Cul-de-sac|Cds|Drive|Dr|Esplanade|Esp|Green|Grn|Grove|Gr|Highway|Hwy|Junction|Jnc|Lane|Lane|Link|Link|Mews|Mews|Parade|Pde|Place|Pl|Ridge|Rdge|Road|Rd|Square|Sq|Street|St|Terrace|Tce|ALLEY|ALLY|ARCADE|ARC|AVENUE|AVE|BOULEVARD|BVD|BYPASS|BYPA|CIRCUIT|CCT|CLOSE|CL|CORNER|CRN|COURT|CT|CRESCENT|CRES|CUL-DE-SAC|CDS|DRIVE|DR|ESPLANADE|ESP|GREEN|GRN|GROVE|GR|HIGHWAY|HWY|JUNCTION|JNC|LANE|LANE|LINK|LINK|MEWS|MEWS|PARADE|PDE|PLACE|PL|RIDGE|RDGE|ROAD|RD|SQUARE|SQ|STREET|ST|TERRACE|TCE))\s.*?(?=\s{2,}"), None,)], + }, + "zh": [ + ( + regex.compile( + r"((\p{Han}{1,3}(自治区|省))?\p{Han}{1,4}((?(^\d{5}|^\d{3})?)(?\D+[縣市])(?\D+?(市區|鎮區|鎮市|[鄉鎮市區]))(?.+)" + ), + None, + ), + ], +} +age_regex = { + "en": [ + ( + re.compile( + r"\S+ years old|\S+\-years\-old|\S+ year old|\S+\-year\-old|born [ ][\d][\d]+[\\ /.][\d][\d][\\ /.][\d][\d]+|died [ ][\d][\d]+[\\ /.][\d][\d][\\ /.][\d][\d]+" + ), + None, + ) + ], + "zh": [(regex.compile(r"\d{1,3}歲|岁"), None)], +} + +# IBAN - see https://github.com/microsoft/presidio/blob/main/presidio-analyzer/presidio_analyzer/predefined_recognizers/iban_patterns.py which is under MIT + +# IBAN parts format +CC = "[A-Z]{2}" # country code +CK = "[0-9]{2}[ ]?" # checksum +BOS = "^" +EOS = "$" # end of string + +A = "[A-Z][ ]?" +A2 = "([A-Z][ ]?){2}" +A3 = "([A-Z][ ]?){3}" +A4 = "([A-Z][ ]?){4}" + +C = "[a-zA-Z0-9][ ]?" +C2 = "([a-zA-Z0-9][ ]?){2}" +C3 = "([a-zA-Z0-9][ ]?){3}" +C4 = "([a-zA-Z0-9][ ]?){4}" + +N = "[0-9][ ]?" +N2 = "([0-9][ ]?){2}" +N3 = "([0-9][ ]?){3}" +N4 = "([0-9][ ]?){4}" + +# WIP - fix the country codes and group by languages +# move this to financial record +iban_regex = { + # Albania (8n, 16c) ALkk bbbs sssx cccc cccc cccc cccc + "al_AL": "(AL)" + CK + N4 + N4 + C4 + C4 + C4 + C4, + # Andorra (8n, 12c) ADkk bbbb ssss cccc cccc cccc + "ad_AD": "(AD)" + CK + N4 + N4 + C4 + C4 + C4, + # Austria (16n) ATkk bbbb bccc cccc cccc + "en_AT": "(AT)" + CK + N4 + N4 + N4 + N4, + # Azerbaijan (4c,20n) AZkk bbbb cccc cccc cccc cccc cccc + "az_AZ": "(AZ)" + CK + C4 + N4 + N4 + N4 + N4 + N4, + # Bahrain (4a,14c) BHkk bbbb cccc cccc cccc cc + "ar_BH": "(BH)" + CK + A4 + C4 + C4 + C4 + C2, + # Belarus (4c, 4n, 16c) BYkk bbbb aaaa cccc cccc cccc cccc + "bel_BY": "(BY)" + CK + C4 + N4 + C4 + C4 + C4 + C4, + # Belgium (12n) BEkk bbbc cccc ccxx + "fr_BE": "(BE)" + CK + N4 + N4 + N4, + # Bosnia and Herzegovina (16n) BAkk bbbs sscc cccc ccxx + "bos_BA": "(BA)" + CK + N4 + N4 + N4 + N4, + # Brazil (23n,1a,1c) BRkk bbbb bbbb ssss sccc cccc ccct n + "pt_BR": "(BR)" + CK + N4 + N4 + N4 + N4 + N4 + N3 + A + C, + # Bulgaria (4a,6n,8c) BGkk bbbb ssss ttcc cccc cc + "bg_BG": "(BG)" + CK + A4 + N4 + N + N + C2 + C4 + C2, + # Costa Rica (18n) CRkk 0bbb cccc cccc cccc cc (0 = always zero) + "es_CR": "(CR)" + CK + "[0]" + N3 + N4 + N4 + N4 + N2, + # Croatia (17n) HRkk bbbb bbbc cccc cccc c + "hr_HR": "(HR)" + CK + N4 + N4 + N4 + N4 + N, + # Cyprus (8n,16c) CYkk bbbs ssss cccc cccc cccc cccc + "el_CY": "(CY)" + CK + N4 + N4 + C4 + C4 + C4 + C4, + # Czech Republic (20n) CZkk bbbb ssss sscc cccc cccc + "cz_CZ": "(CZ)" + CK + N4 + N4 + N4 + N4 + N4, + # Denmark (14n) DKkk bbbb cccc cccc cc + "dan_DK": "(DK)" + CK + N4 + N4 + N4 + N2, + # Dominican Republic (4a,20n) DOkk bbbb cccc cccc cccc cccc cccc + "es_DO": "(DO)" + CK + A4 + N4 + N4 + N4 + N4 + N4, + # EAt Timor (19n) TLkk bbbc cccc cccc cccc cxx + "tl_TL": "(TL)" + CK + N4 + N4 + N4 + N4 + N3, + # Estonia (16n) EEkk bbss cccc cccc cccx + "ee_EE": "(EE)" + CK + N4 + N4 + N4 + N4, + # Faroe Islands (14n) FOkk bbbb cccc cccc cx + "FO": "(FO)" + CK + N4 + N4 + N4 + N2, + # Finland (14n) FIkk bbbb bbcc cccc cx + "fi_FI": "(FI)" + CK + N4 + N4 + N4 + N2, + # France (10n,11c,2n) FRkk bbbb bsss sscc cccc cccc cxx + "fr_FR": "(FR)" + CK + N4 + N4 + N2 + C2 + C4 + C4 + C + N2, + # Georgia (2c,16n) GEkk bbcc cccc cccc cccc cc + "ge_GE": "(GE)" + CK + C2 + N2 + N4 + N4 + N4 + N2, + # Germany (18n) DEkk bbbb bbbb cccc cccc cc + "de_DE": "(DE)" + CK + N4 + N4 + N4 + N4 + N2, + # Gibraltar (4a,15c) GIkk bbbb cccc cccc cccc ccc + "GI": "(GI)" + CK + A4 + C4 + C4 + C4 + C3, + # Greece (7n,16c) GRkk bbbs sssc cccc cccc cccc ccc + "el_GR": "(GR)" + CK + N4 + N3 + C + C4 + C4 + C4 + C3, + # Greenland (14n) GLkk bbbb cccc cccc cc + "kl_GL": "(GL)" + CK + N4 + N4 + N4 + N2, + # Guatemala (4c,20c) GTkk bbbb mmtt cccc cccc cccc cccc + "es_GT": "(GT)" + CK + C4 + C4 + C4 + C4 + C4 + C4, + # Hungary (24n) HUkk bbbs sssx cccc cccc cccc cccx + "hu_HU": "(HU)" + CK + N4 + N4 + N4 + N4 + N4 + N4, + # Iceland (22n) ISkk bbbb sscc cccc iiii iiii ii + "is_IS": "(IS)" + CK + N4 + N4 + N4 + N4 + N4 + N2, + # Ireland (4c,14n) IEkk aaaa bbbb bbcc cccc cc + "en_IE": "(IE)" + CK + C4 + N4 + N4 + N4 + N2, + # Israel (19n) ILkk bbbn nncc cccc cccc ccc + "hb_IL": "(IL)" + CK + N4 + N4 + N4 + N4 + N3, + # Italy (1a,10n,12c) ITkk xbbb bbss sssc cccc cccc ccc + "it_IT": "(IT)" + CK + A + N3 + N4 + N3 + C + C3 + C + C4 + C3, + # Jordan (4a,22n) JOkk bbbb ssss cccc cccc cccc cccc cc + "ar_JO": "(JO)" + CK + A4 + N4 + N4 + N4 + N4 + N4 + N2, + # Kazakhstan (3n,13c) KZkk bbbc cccc cccc cccc + "kz_KZ": "(KZ)" + CK + N3 + C + C4 + C4 + C4, + # Kosovo (4n,10n,2n) XKkk bbbb cccc cccc cccc + "xk_XK": "(XK)" + CK + N4 + N4 + N4 + N4, + # Kuwait (4a,22c) KWkk bbbb cccc cccc cccc cccc cccc cc + "ar_KW": "(KW)" + CK + A4 + C4 + C4 + C4 + C4 + C4 + C2, + # Latvia (4a,13c) LVkk bbbb cccc cccc cccc c + "lv_LV": "(LV)" + CK + A4 + C4 + C4 + C4 + C, + # Lebanon (4n,20c) LBkk bbbb cccc cccc cccc cccc cccc + "lb_LB": "(LB)" + CK + N4 + C4 + C4 + C4 + C4 + C4, + # de_LiechteNtein (5n,12c) LIkk bbbb bccc cccc cccc c + "li_LI": "(LI)" + CK + N4 + N + C3 + C4 + C4 + C, + # Lithuania (16n) LTkk bbbb bccc cccc cccc + "lt_LT": "(LT)" + CK + N4 + N4 + N4 + N4, + # Luxembourg (3n,13c) LUkk bbbc cccc cccc cccc + "lu_LU": "(LU)" + CK + N3 + C + C4 + C4 + C4, + # Malta (4a,5n,18c) MTkk bbbb ssss sccc cccc cccc cccc ccc + "mt_MT": "(MT)" + CK + A4 + N4 + N + C3 + C4 + C4 + C4 + C3, + # Mauritania (23n) MRkk bbbb bsss sscc cccc cccc cxx + "mr_MR": "(MR)" + CK + N4 + N4 + N4 + N4 + N4 + N3, + # Mauritius (4a,19n,3a) MUkk bbbb bbss cccc cccc cccc 000m mm + "mu_MU": "(MU)" + CK + A4 + N4 + N4 + N4 + N4 + N3 + A, + # Moldova (2c,18c) MDkk bbcc cccc cccc cccc cccc + "md_MD": "(MD)" + CK + C4 + C4 + C4 + C4 + C4, + # Monaco (10n,11c,2n) MCkk bbbb bsss sscc cccc cccc cxx + "mc_MC": "(MC)" + CK + N4 + N4 + N2 + C2 + C4 + C4 + C + N2, + # Montenegro (18n) MEkk bbbc cccc cccc cccc xx + "me_ME": "(ME)" + CK + N4 + N4 + N4 + N4 + N2, + # Netherlands (4a,10n) NLkk bbbb cccc cccc cc + "nl_NL": "(NL)" + CK + A4 + N4 + N4 + N2, + # North Macedonia (3n,10c,2n) MKkk bbbc cccc cccc cxx + "mk_MK": "(MK)" + CK + N3 + C + C4 + C4 + C + N2, + # Norway (11n) NOkk bbbb cccc ccx + "no_NO": "(NO)" + CK + N4 + N4 + N3, + # Pakistan (4c,16n) PKkk bbbb cccc cccc cccc cccc + "pk_PK": "(PK)" + CK + C4 + N4 + N4 + N4 + N4, + # Palestinian territories (4c,21n) PSkk bbbb xxxx xxxx xccc cccc cccc c + "ps_PS": "(PS)" + CK + C4 + N4 + N4 + N4 + N4 + N, + # Poland (24n) PLkk bbbs sssx cccc cccc cccc cccc + "pl_PL": "(PL)" + CK + N4 + N4 + N4 + N4 + N4 + N4, + # Portugal (21n) PTkk bbbb ssss cccc cccc cccx x + "pt_PT": "(PT)" + CK + N4 + N4 + N4 + N4 + N, + # Qatar (4a,21c) QAkk bbbb cccc cccc cccc cccc cccc c + "ar_QA": "(QA)" + CK + A4 + C4 + C4 + C4 + C4 + C, + # Romania (4a,16c) ROkk bbbb cccc cccc cccc cccc + "ro_RO": "(RO)" + CK + A4 + C4 + C4 + C4 + C4, + # San Marino (1a,10n,12c) SMkk xbbb bbss sssc cccc cccc ccc + "sm": "(SM)" + CK + A + N3 + N4 + N3 + C + C4 + C4 + C3, + # Saudi Arabia (2n,18c) SAkk bbcc cccc cccc cccc cccc + "ar_SA": "(SA)" + CK + N2 + C2 + C4 + C4 + C4 + C4, + # Serbia (18n) RSkk bbbc cccc cccc cccc xx + "rs_RS": "(RS)" + CK + N4 + N4 + N4 + N4 + N2, + # Slovakia (20n) SKkk bbbb ssss sscc cccc cccc + "sk_SK": "(SK)" + CK + N4 + N4 + N4 + N4 + N4, + # Slovenia (15n) SIkk bbss sccc cccc cxx + "si_SI": "(SI)" + CK + N4 + N4 + N4 + N3, + # Spain (20n) ESkk bbbb ssss xxcc cccc cccc + "es_ES": "(ES)" + CK + N4 + N4 + N4 + N4 + N4, + # Sweden (20n) SEkk bbbc cccc cccc cccc cccc + "se_SE": "(SE)" + CK + N4 + N4 + N4 + N4 + N4, + # Switzerland (5n,12c) CHkk bbbb bccc cccc cccc c + "gsw_CH": "(CH)" + CK + N4 + N + C3 + C4 + C4 + C, + # Tunisia (20n) TNkk bbss sccc cccc cccc cccc + "ar_TN": "(TN)" + CK + N4 + N4 + N4 + N4 + N4, + # Turkey (5n,17c) TRkk bbbb bxcc cccc cccc cccc cc + "tr_TR": "(TR)" + CK + N4 + N + C3 + C4 + C4 + C4 + C2, + # United Arab Emirates (3n,16n) AEkk bbbc cccc cccc cccc ccc + "ar_AE": "(AE)" + CK + N4 + N4 + N4 + N4 + N3, + # United Kingdom (4a,14n) GBkk bbbb ssss sscc cccc cc + "en_GB": "(GB)" + CK + A4 + N4 + N4 + N4 + N2, + # Vatican City (3n,15n) VAkk bbbc cccc cccc cccc cc + "it_VA": "(VA)" + CK + N4 + N4 + N4 + N4 + N2, + # Virgin Islands, British (4c,16n) VGkk bbbb cccc cccc cccc cccc + "en_VG": "(VG)" + CK + C4 + N4 + N4 + N4 + N4, +} + + +# ABA routing from https://github.com/microsoft/presidio/blob/main/presidio-analyzer/presidio_analyzer/predefined_recognizers/aba_routing_recognizer.py which is licensed under the MIT License +financial_record_regex = { + "en": [ + ( + re.compile(r"\b[0123678]\d{3}-\d{4}-\d\b"), + ( + "aba", + "routing", + "abarouting", + "association", + "bankrouting", + ), + ) + ], + # for credit card, getting a "nothing to repeat at position 15" + # (re.compile(r"3[47][0-9]{13}|?:5[1-5][0-9]{2}|222[1-9]|22[3-9][0-9]|2[3-6][0-9]{2}|27[01][0-9]|2720)[0-9]{12}|\b([4]\d{3}[\s]\d{4}[\s]\d{4}[\s]\d{4}|[4]\d{3}[-]\d{4}[-]\d{4}[-]\d{4}|[4]\d{3}[.]\d{4}[.]\d{4}[.]\d{4}|[4]\d{3}\d{4}\d{4}\d{4})\b"), ("credit card", "american express", "visa", "mastercard")), +} + +email_regex = {"default": [(re.compile(r"[\w\.=-]+@[\w\.-]+\.[\w]{2,3}"), None)]} + +# see https://github.com/microsoft/presidio/blob/main/presidio-analyzer/presidio_analyzer/predefined_recognizers/au_abn_recognizer.py which is licensed under MIT +# see also https://github.com/microsoft/presidio/blob/main/presidio-analyzer/presidio_analyzer/predefined_recognizers/us_passport_recognizer.py +# see also https://github.com/microsoft/presidio/blob/main/presidio-analyzer/presidio_analyzer/predefined_recognizers/medical_license_recognizer.py +# see also https://github.com/microsoft/presidio/blob/main/presidio-analyzer/presidio_analyzer/predefined_recognizers/es_nif_recognizer.py + +govt_id_regex = { + "en": { + "en_US": [ + ( + re.compile( + r"(?!000|666|333)0*(?:[0-6][0-9][0-9]|[0-7][0-6][0-9]|[0-7][0-7][0-2])[- ](?!00)[0-9]{2}[- ](?!0000)[0-9]{4}" + ), + None, + ), + ( + re.compile(r"(\b[0-9]{9}\b)"), + ( + "us", + "united", + "states", + "passport", + "passport#", + "travel", + "document", + ), + ), + ( + re.compile(r"[a-zA-Z]{2}\d{7}|[a-zA-Z]{1}9\d{7}"), + ("medical", "certificate", "DEA"), + ), + ], + "en_CA": [(re.compile(r"\d{3}\s\d{3}\s\d{3}"), None)], + "en_GB": [ + ( + re.compile( + r"\w{2}\s?\d{2}\s?\d{2}\s?\w|GB\s?\d{6}\s?\w|GB\d{3}\s\d{3}\s\d{2}\s\d{3}|GBGD\d{3}|GBHA\d{3}}|GB\d{3} \d{4} \d{2}(?: \d{3})?|GB(?:GD|HA)\d{3}" + ), + None, + ) + ], + "en_IE": [(re.compile(r"IE\d[1-9]\d{5}\d[1-9]|IE\d{7}[1-9][1-9]?"), None)], + "en_IN": [(re.compile(r"[1-9]\d{10}"), None)], + "en_PH": [ + ( + re.compile( + r"\d{2}-\d{7}-\d|\d{11}|\d{2}-\d{9}-\d|\d{4}-\d{4}-\d{4}|\d{4}-\d{7}-\d" + ), + None, + ) + ], + "en_AU": [ + ( + re.compile(r"\b\d{2}\s\d{3}\s\d{3}\s\d{3}\b|\b\d{11}\b"), + ("australian business number", "abn"), + ) + ], + }, + "id": { + "id_ID": [ + ( + re.compile( + r"\d{6}([04][1-9]|[1256][0-9]|[37][01])(0[1-9]|1[0-2])\d{6}" + ), + None, + ) + ] + }, + "es": { + "es_ES": [ + (re.compile(r"(?:ES)?\d{6-8}-?[A-Z]"), None), + ( + re.compile(r"\b[0-9]?[0-9]{7}[-]?[A-Z]\b"), + ("documento nacional de identidad", "DNI", "NIF", "identificación"), + ), + ], + "es_CO": [ + (re.compile(r"[1-9]\d?\d{6}|8\d{8}|9\d{8}|10\d{8}|11\d{8}|12\d{8}|"), None) + ], + }, + "pt": { + "pt_BR": [(re.compile(r"\d{3}\.d{3}\.d{3}-\d{2}|\d{11}"), None)], + "pt_PT": [(re.compile(r"PT\d{9}"), None)], + }, + "zh": [ + ( + regex.compile( + r"(?:[16][1-5]|2[1-3]|3[1-7]|4[1-6]|5[0-4])\d{4}(?:19|20)\d{2}(?:(?:0[469]|11)(?:0[1-9]|[12][0-9]|30)|(?:0[13578]|1[02])(?:0[1-9]|[12][0-9]|3[01])|02(?:0[1-9]|[12][0-9]))\d{3}[\dXx]" + ), + None, + ), + ( + regex.compile( + r"(^[EeKkGgDdSsPpHh]\d{8}$)|(^(([Ee][a-fA-F])|([DdSsPp][Ee])|([Kk][Jj])|([Mm][Aa])|(1[45]))\d{7}$)" + ), + None, + ), + ( + regex.compile( + r"((\d{4}(| )\d{4}(| )\d{4}$)|([a-zA-Z][1-2]{1}[0-9]{8})|([0-3]{1}\d{8}))" + ), + None, + ), + ], + "default": [(re.compile(r"\d{8}|\d{9}|\d{10}|\d{11}"), None)], +} + +# should we move license plate to govt_id? +# ("LICENSE_PLATE", regex.compile('^(?:[京津沪渝冀豫云辽黑湘皖鲁新苏浙赣鄂桂甘晋蒙陕吉闽贵粤青藏川宁琼使领 A-Z]{1}[A-HJ-NP-Z]{1}(?:(?:[0-9]{5}[DF])|(?:[DF](?:[A-HJ-NP-Z0-9])[0-9]{4})))|(?:[京津沪渝冀豫云辽黑湘皖鲁新苏浙赣鄂桂甘晋蒙陕吉闽贵粤青藏川宁琼使领 A-Z]{1}[A-Z]{1}[A-HJ-NP-Z0-9]{4}[A-HJ-NP-Z0-9 挂学警港澳]{1})$'), None, None, None), +# ("LICENSE_PLATE", regex.compile('\b[A-Z]{3}-\d{4}\b'), None, None, None), + + +# too broad - might need a context word +IP_regex = { + "default": [ + (re.compile(r"\d{1,3}[.]\d{1,3}[.]\d{1,3}[.]\d{1,3}"), ("address", "ip")) + ], +} +NORP_regex = { + "en": [(re.compile(r"upper class|middle class|working class|lower class"), None)], +} + +# I think this is too broad. I put a context word around it. +password_regex = { + "en": [(re.compile(r"password: [\d][\d][\d][\d][\d]+"), ("password",))], +} + +# We will want a context word around it to make it more specific. might be too broad. +phone_regex = { + "en": [ + ( + re.compile( + r"[\d]?[\d]?[ -\\/.]?[ -\\/.]?[\d][\d][\d][ -\\/.]?[ -\\/.]?[\d][\d][\d][ -\\/.]?[\d][\d][\d][\d]" + ), + ("ph", "phone", "fax"), + ) + ], + "zh": [ + ( + regex.compile( + r"(0?\d{2,4}-[1-9]\d{6,7})|({\+86|086}-| ?1[3-9]\d{9} , ([\+0]?86)?[\-\s]?1[3-9]\d{9})" + ), + None, + ), + ( + regex.compile( + r"((\d{4}(| )\d{4}(| )\d{4}$)|([a-zA-Z][1-2]{1}[0-9]{8})|([0-3]{1}\d{8}))((02|03|037|04|049|05|06|07|08|089|082|0826|0836|886 2|886 3|886 37|886 4|886 49|886 5|886 6|886 7|886 8|886 89|886 82|886 826|886 836|886 9|886-2|886-3|886-37|886-4|886-49|886-5|886-6|886-7|886-8|886-89|886-82|886-826|886-836)(| |-)\d{4}(| |-)\d{4}$)|((09|886 9|886-9)(| |-)\d{2}(|-)\d{2}(|-)\d{1}(|-)\d{3})" + ), + None, + ), + ], +} + +# Does this correspond to CA id? +SIN_regex = {"defualt": re.compile(r"[\d][\d]+[ -.][\d][\d]+[ -.][\d][\d][\d]")} + +# will this only match https, what about http? +domain_name_regex = { + "default": [ + ( + re.compile( + r"[https:\/]*[w]?[w]?[w]?[.]?[\da-zA-Z\-]+[.][a-z]+[\/\.a-zA-Z\-\d\?=&]*" + ), + None, + ) + ], +} + + +tag_2_regex = [ + ("DOMAIN_NAME", (domain_name_regex, False)), + ("PHONE", (phone_regex, True)), + ("PASSWORD", (password_regex, True)), + ("NORP", (NORP_regex, False)), + ("AGE", (age_regex, False)), + ("ADDRESS", (address_regex, True)), + ("EMAIL", (email_regex, True)), + ("IP_ADDRESS", (IP_regex, True)), + ("GOVT_ID", (govt_id_regex, True)), + ("FIN_ID", (financial_record_regex, True)), +] + + +# Code below needs to be updated/completed. + + +def apply_regex_anonymization( + sentence: str, lang_id: str, context_window: int = 20 +) -> str: + ner = {} + lang_id = regex_lang_id.split("_")[0] + if lang_id in ("zh", "ko", "ja"): + sentence_set = set(sentence.lower()) + else: + sentence_set = set(sentence.lower().split(" ")) + for tag, regex_group_and_anonymize_condition in tag_2_regex: + regex_group, anonymize_condition = regex_group_and_anonymize_condition + for regex_dict in regex_group.get(lang_id, regex_group.get("default", [])): + if isinstance(regex_dict, dict): + regex_list = regex_dict.get(regex_lang_id, []) + else: + regex_list = regex_dict + match = False + for regex, context in regex_list: + found_context = False + if context: + for c in context: + if c in sentence_set: + found_context = True + break + if not found_context: + continue + for ent in regex.findall(sentence): + if not isinstance(ent, str): + continue + if found_context: + i = sentence.index(ent) + j = i + len(ent) + len_sentence = len(sentence) + left = sentence[max(0, i - context_window) : i].lower() + right = sentence[ + j : min(len_sentence, j + context_window) + ].lower() + found_context = False + for c in context: + if c in left or c in right: + found_context = True + break + if not found_context: + continue + if anonymize_condition: + sentence = sentence.replace(ent, f" <{tag}> ") + ner[f"<{tag}>"] = tag + else: + ner[ent.strip()] = tag + match = True + if match: + break + return sentence, ner diff --git a/data_tooling/ac_dc/badwords.py b/data_tooling/ac_dc/badwords.py new file mode 100644 index 0000000..64f1c20 --- /dev/null +++ b/data_tooling/ac_dc/badwords.py @@ -0,0 +1,2682 @@ +# Merge +# https://github.com/zacanger/profane-words +# and +# https://github.com/thisandagain/washyourmouthoutwithsoap/blob/develop/data/build.json +# and +# https://github.com/LDNOOBW/List-of-Dirty-Naughty-Obscene-and-Otherwise-Bad-Words + + +english_badwords = [ + "abuse", + "anal", + "anilingus", + "anus", + "aroused", + "arse", + "arsehole", + "ass", + "asses", + "assfuck", + "asshat", + "asshole", + "assholes", + "autoerotic", + "bangbros", + "banging", + "bareback", + "bastard", + "bastards", + "bazongas", + "bbw", + "bdsm", + "biatch", + "bicurious", + "bigass", + "bigtits", + "bimbo", + "bimbos", + "bitch", + "bitches", + "bitching", + "blowjob", + "blowjobs", + "boche", + "boner", + "boners", + "boob", + "boobies", + "boobs", + "booty", + "brothel", + "buceta", + "bugger", + "buggered", + "buggery", + "bukkake", + "bule", + "buttcheeks", + "buttfuck", + "butthead", + "butthole", + "buttplug", + "cameltoe", + "camgirl", + "camwhore", + "chink", + "chinks", + "cialis", + "clit", + "clitoris", + "clits", + "clitty", + "clusterfuck", + "cock", + "cock-head", + "cockblock", + "cockfight", + "cockhead", + "cocks", + "cocksman", + "cocksucker", + "cocksucking", + "coital", + "coitus", + "coochie", + "cooly", + "coon", + "coons", + "copulate", + "cowgirl", + "crabs", + "creampie", + "cum", + "cumming", + "cums", + "cumshot", + "cumshots", + "cumslut", + "cunnilingus", + "cunny", + "cunt", + "cunts", + "cybersex", + "darkey", + "darkie", + "darkies", + "darky", + "deepthroat", + "deepthroating", + "dick", + "dickhole", + "dicks", + "dildo", + "dildos", + "dogging", + "doggy-style", + "doggystyle", + "dominatrix", + "dommes", + "dong", + "dp", + "dupa", + "dyke", + "dykes", + "ecchi", + "ejaculate", + "ejaculated", + "ejaculates", + "ejaculating", + "ejaculation", + "ejaculations", + "enema", + "erect", + "erection", + "ero", + "erotic", + "erotism", + "escort", + "fag", + "fagging", + "faggot", + "fagot", + "fagots", + "fags", + "felch", + "fellate", + "fellatio", + "femdom", + "fetish", + "figging", + "fingerbang", + "fingering", + "fisted", + "fister", + "fisting", + "floozy", + "fondle", + "footfetish", + "footjob", + "foreskin", + "fornicate", + "foursome", + "fuck", + "fuckable", + "fuckbook", + "fuckboy", + "fuckbuddy", + "fucked", + "fucker", + "fuckers", + "fuckfest", + "fuckhole", + "fuckin", + "fucking", + "fucks", + "fuk", + "fukin", + "fuking", + "g-spot", + "gangbang", + "gangbanged", + "gangbanger", + "gangbangs", + "genital", + "genitals", + "gigolo", + "glans", + "gonad", + "gonads", + "gook", + "gringo", + "gringos", + "grope", + "gspot", + "guido", + "handjob", + "haole", + "hapa", + "hardcore", + "hardon", + "harem", + "hentai", + "hindoo", + "hoe", + "hoes", + "honky", + "hooker", + "hookers", + "hooter", + "hooters", + "hori", + "horndog", + "horney", + "horniest", + "horny", + "humped", + "humper", + "humping", + "hussy", + "hymen", + "ikey", + "incest", + "injun", + "intercourse", + "interracial", + "jack-off", + "jackoff", + "jailbait", + "jerk-off", + "jerkoff", + "jiggy", + "jism", + "jizz", + "jizzed", + "kaffir", + "kafir", + "kike", + "kikes", + "kinkster", + "kinky", + "kkk", + "klan", + "kraut", + "labia", + "lapdance", + "libido", + "licker", + "licking", + "limey", + "lingerie", + "livesex", + "lolita", + "lovemaking", + "lust", + "lusting", + "masochist", + "masterbate", + "masterbating", + "masterbation", + "masturbate", + "masturbating", + "masturbation", + "milf", + "minge", + "missionary", + "molest", + "molestation", + "molester", + "munging", + "muschi", + "nads", + "naked", + "necked", + "necro", + "negress", + "negro", + "negroes", + "negroid", + "negros", + "nig", + "nigar", + "nigga", + "niggas", + "niggaz", + "nigger", + "niggers", + "nigra", + "nipple", + "nipples", + "nookie", + "nooky", + "nooner", + "nude", + "nudie", + "nudity", + "nymph", + "nympho", + "nymphomania", + "orgasim", + "orgasm", + "orgasms", + "orgies", + "orgy", + "orifice", + "p0rn", + "paedophile", + "pantie", + "panties", + "panty", + "pastie", + "pecker", + "pedo", + "pedophile", + "pedophilia", + "pedophiliac", + "peeper", + "peepshow", + "pegging", + "penetrate", + "penetration", + "penile", + "penis", + "penises", + "penus", + "perv", + "phallic", + "phonesex", + "pickaninnies", + "pimp", + "playboy", + "playgirl", + "poontang", + "porn", + "porno", + "pornography", + "pornos", + "pr0n", + "premature", + "preteen", + "pron", + "prostitute", + "pube", + "pubes", + "pubic", + "pubis", + "punani", + "pussies", + "pussy", + "pussys", + "pusy", + "puta", + "puto", + "queef", + "quickie", + "quicky", + "quim", + "randy", + "rape", + "raped", + "raper", + "raping", + "rapist", + "rectum", + "redneck", + "rednecks", + "redskin", + "redskins", + "rimjob", + "rimming", + "russki", + "s&m", + "sadism", + "sadist", + "sambo", + "santorum", + "schlong", + "scissoring", + "semen", + "sex", + "sexed", + "sexi", + "sexing", + "sexo", + "sexpot", + "sextoy", + "sexual", + "sexually", + "sexx", + "sexxx", + "sexxxy", + "sexxy", + "sexy", + "sh!t", + "sh1t", + "shagging", + "shemale", + "sissy", + "skank", + "skanks", + "slapper", + "slut", + "sluts", + "slutting", + "slutty", + "smut", + "smutty", + "sodomise", + "sodomite", + "sodomize", + "sodomy", + "spank", + "sperm", + "spic", + "spick", + "splooge", + "spooge", + "squaw", + "squirting", + "steamy", + "stiffy", + "strapon", + "suck", + "sucked", + "sucker", + "sucking", + "sucks", + "swallow", + "swallower", + "swinger", + "teabagging", + "testical", + "testicle", + "testicles", + "testis", + "threesome", + "threeway", + "titfuck", + "titjob", + "tits", + "tittie", + "titties", + "titty", + "tittyfuck", + "tity", + "toots", + "topless", + "trannie", + "tranny", + "tribadism", + "twat", + "twats", + "undies", + "undressing", + "upskirt", + "vag", + "vagina", + "vaginal", + "viagra", + "vibrator", + "virgin", + "vixen", + "voyeur", + "vulva", + "wank", + "wanker", + "wanking", + "wazoo", + "wedgie", + "wench", + "wetback", + "whore", + "whored", + "whorehouse", + "whores", + "whoring", + "wigger", + "willie", + "willies", + "willy", + "wog", + "wop", + "x-rated", + "xxx", + "xxxxxx", + "yaoi", + "yid", + "zoophile", + "zoophilia", +] + +badwords = { + "ar": english_badwords + + [ + "احتلام", + "اغتصاب", + "بز", + "بزاز", + "بظر", + "بيضان", + "تمص", + "ثدي", + "جماع", + "حلمة", + "خنثي", + "خول", + "زب", + "سحاق", + "سحاقية", + "سكس", + "شاذ", + "شرج", + "شرموطة", + "شهوة", + "طيز", + "عاهرة", + "عرص", + "فرج", + "قحبة", + "قضيب", + "كس", + "لبوة", + "لحس", + "لعق", + "لواط", + "لوطي", + "مبادل", + "متناك", + "متناكة", + "مص", + "مفلقسة", + "نيك", + ], + "ca": english_badwords + + [ + "avortament", + "anal", + "anus", + "cul", + "ass-fucker", + "asss", + "asshole", + "assholes", + "bolera", + "boles", + "bastardo", + "bellend", + "bestial", + "bestialitat", + "puta", + "femelles", + "picant", + "sagnant", + "mamada", + "bollok", + "boob", + "pits", + "buceta", + "bum", + "culata", + "catifa muncher", + "picar", + "cipa", + "clitoris", + "polla", + "galletejador", + "gallines", + "coon", + "merda", + "cum", + "correguda", + "cunillingus", + "boig", + "maleït", + "consolador", + "consoladors", + "dink", + "canalla", + "duche", + "dique", + "ejaculació", + "ejaculat", + "ejacula", + "ejaculant", + "fag", + "fagging", + "fagot", + "fagots", + "fanny", + "felching", + "fel.lació", + "brida", + "follar", + "follat", + "escuradents", + "follant", + "folles", + "fucks", + "empacadora de llaminadures", + "déu maldit", + "deu meu", + "infern", + "hore", + "córrer", + "retrocés", + "kock", + "llavis", + "lujuria", + "lució", + "masoquista", + "masturbarse", + "puta mare", + "nazi", + "nigger", + "negres", + "orgasim", + "orgasme", + "orgasmes", + "pecker", + "penis", + "piss", + "mossegat", + "pisser", + "pisses", + "pissing", + "treure de polleguera", + "caca", + "porno", + "pornografia", + "picades", + "pube", + "coques", + "gatet", + "violació", + "violador", + "recte", + "retard", + "rimming", + "sàdic", + "cargolar", + "escrot", + "semen", + "sexe", + "shag", + "borratxos", + "transsexual", + "mossegar", + "shitted", + "skank", + "smegma", + "smut", + "arrebat", + "fill de puta", + "spac", + "spunk", + "testicle", + "tit", + "tetas", + "titt", + "turd", + "vagina", + "viagra", + "vulva", + "wang", + "wank", + "x classificat", + "xxx", + ], + "en": english_badwords, + "es": english_badwords + + [ + "Asesinato", + "Bollera", + "Cabrón", + "Caca", + "Chupada", + "Chupapollas", + "Chupetón", + "Concha de tu madre", + "Coprofagía", + "Coño", + "Culo", + "Drogas", + "Esperma", + "Fiesta de salchichas", + "Follador", + "Follar", + "Gilipichis", + "Gilipollas", + "Hacer una paja", + "Haciendo el amor", + "Heroína", + "Hija de puta", + "Hijaputa", + "Hijo de puta", + "Hijoputa", + "Idiota", + "Imbécil", + "Jilipollas", + "Kapullo", + "Lameculos", + "Maciza", + "Macizorra", + "Mamada", + "Marica", + "Mariconazo", + "Maricón", + "Mierda", + "Nazi", + "Orina", + "Pedo", + "Pendejo", + "Pervertido", + "Pezón", + "Pinche", + "Pis", + "Prostituta", + "Puta", + "Racista", + "Ramera", + "Semen", + "Sexo", + "Sexo oral", + "Soplagaitas", + "Soplapollas", + "Sádico", + "Tetas grandes", + "Travesti", + "Trio", + "Tía buena", + "Verga", + "Vulva", + "aborto", + "agallas", + "anal", + "ano", + "arrebatar", + "asno", + "atornillar", + "bastardo", + "bestial", + "bestialidad", + "bolas", + "bollok", + "bolsa de pelota", + "brida", + "buceta", + "cabron", + "cagadas", + "cagado", + "cagando", + "campana", + "carajo", + "chupar la polla", + "cipa", + "clítoris", + "concha", + "consolador", + "consoladores", + "corrida", + "coño", + "coños", + "culo", + "culos", + "cunillingus", + "córneo", + "de mierda", + "dique", + "duche", + "enojado", + "escroto", + "espacio", + "estúpido", + "extremo", + "eyacula", + "eyaculación", + "eyaculado", + "eyacular", + "fagging", + "felación", + "felching", + "folla", + "follada", + "follador de culo", + "folladores", + "follar", + "fudge packer", + "gallos", + "grieta", + "hacerse una paja", + "hijo de puta", + "hore", + "infierno", + "kock", + "labios vaginales", + "los pechos", + "lujuria", + "madre folladora", + "maldita sea", + "maldito", + "maldito sea", + "mamada", + "mapache", + "maricones", + "maricón", + "martillo", + "masoquista", + "masturbarse", + "mear", + "mierda", + "molesto", + "muncher alfombra", + "nazi", + "negro", + "niggers", + "orgasimo", + "orgasmo", + "orgasmos", + "orinando", + "pelusa", + "pene", + "perra", + "perras", + "perro follador", + "pinchazo", + "pinchazos", + "pisser", + "polla", + "porno", + "pornografía", + "pube", + "puta", + "putas", + "pájaro carpintero", + "quejas", + "recto", + "retardar", + "rimming", + "sangriento", + "semen", + "sexo", + "skank", + "smegma", + "sádico", + "testículo", + "teta", + "tetas", + "tirón", + "tizón", + "tonto", + "transexual", + "vagina", + "vete a la mierda", + "viagra", + "violación", + "violador", + "vulva", + "wang", + "x clasificado", + "xxx", + "zurullo", + ], + "eu": english_badwords + + [ + "abortu", + "anal", + "ipurdi", + "kabroi", + "puta", + "clitoris", + "cunillingus", + "madarikatu", + "zakil", + "hazia isuri", + "arraio", + "izorratu", + "infernu", + "emagaldu", + "lizunkeri", + "lizun", + "masokista", + "masturbatu", + "nazi", + "beltz", + "orgasmo", + "pixa", + "porno", + "pornografia", + "alu", + "bortxaketa", + "bortxatzaile", + "sadista", + "ipurzulo", + "hazi", + "semen", + "sexu", + "kaka", + "putaseme", + "barrabil", + "titi", + "bagina", + "viagra", + ], + "fr": english_badwords + + [ + "MALPT", + "anal", + "anus", + "arracher", + "avortement", + "baise", + "baiser", + "baiseur de chien", + "baiseurs", + "baisée", + "bander", + "bellend", + "bestial", + "bestialité", + "bigornette", + "bite", + "bitte", + "bloblos", + "bollok", + "boob", + "bordel", + "bourré", + "bourrée", + "bout", + "brackmard", + "branlage", + "branler", + "branlette", + "branleur", + "branleuse", + "bride", + "brouter le cresson", + "buceta", + "caca", + "chatte", + "chattes", + "chiasse", + "chienne", + "chiennes", + "chier", + "chiottes", + "chié", + "cipa", + "clito", + "clitoris", + "clochard", + "cochonneries", + "con", + "connard", + "connards", + "connasse", + "conne", + "convoitise", + "coq", + "coqs", + "corné", + "couilles", + "cramouille", + "cran", + "cul", + "culs", + "cunillingus", + "damné", + "des balles", + "digue", + "duché", + "déconne", + "déconner", + "emballeur de fudge", + "emmerdant", + "emmerder", + "emmerdeur", + "emmerdeuse", + "enculer", + "enculeur", + "enculeurs", + "enculé", + "enculée", + "enfer", + "enfoiré", + "enfoirée", + "espacer", + "fagging", + "fagot", + "fagots", + "faire chier", + "fellation", + "fente", + "fille de pute", + "fils de pute", + "folle", + "foutre", + "fuckings", + "gerbe", + "gerber", + "godemiché", + "godes", + "gouine", + "grande folle", + "grogniasse", + "gueule", + "hore", + "jouir", + "kock", + "la putain de ta mère", + "les lèvres", + "les seins", + "luxure", + "masochiste", + "masturber", + "merde", + "merdeuse", + "merdeux", + "merdique", + "meuf", + "mère enculée", + "ménage à trois", + "mésange", + "nazi", + "negro", + "nique ta mère", + "nique ta race", + "nègre", + "nègres", + "orgasim", + "orgasme", + "orgasmes", + "palucher", + "penchant", + "pipe", + "pipi", + "piquer", + "piqûres", + "pisse", + "pisser", + "porno", + "pornographie", + "pouffiasse", + "pousse-crotte", + "pube", + "putain", + "putain de", + "pute", + "pédale", + "pédé", + "pénis", + "péter", + "queue", + "quéquette", + "ramoner", + "rectum", + "retard", + "rimming", + "râpé", + "sac de billes", + "sac à foutre", + "sac à merde", + "sadique", + "salaud", + "salope", + "salopes", + "sanglant", + "scrotum", + "se branler", + "seins", + "sexe", + "skank", + "smegma", + "sperme", + "suce", + "suceuse", + "tanche", + "tapette", + "tapis muncher", + "testicule", + "teuch", + "titt", + "transexuelle", + "tremper", + "tringler", + "trique", + "troncher", + "trou du cul", + "turlute", + "vagin", + "viagra", + "violeur", + "vulve", + "wang", + "x évalué", + "xxx", + "zigounette", + "zizi", + "zut", + "éjaculant", + "éjaculation", + "éjacule", + "éjaculer", + "éjaculé", + "étron", + ], + "hi": english_badwords + + [ + "aand", + "aandu", + "balatkar", + "balatkari", + "behen chod", + "beti chod", + "bhadva", + "bhadve", + "bhandve", + "bhangi", + "bhootni ke", + "bhosad", + "bhosadi ke", + "bitching", + "blowjob", + "bollok", + "boobe", + "buceta", + "chakke", + "chinaal", + "chinki", + "chod", + "chodu", + "chodu bhagat", + "chooche", + "choochi", + "choope", + "choot", + "choot ke baal", + "chootia", + "chootiya", + "chuche", + "chuchi", + "chudaap", + "chudai khanaa", + "chudam chudai", + "chude", + "chut", + "chut ka chuha", + "chut ka churan", + "chut ka mail", + "chut ke baal", + "chut ke dhakkan", + "chut maarli", + "chutad", + "chutadd", + "chutan", + "chutia", + "chutiya", + "cipa", + "cunillingus", + "dink", + "duche", + "ejaculated", + "ejaculates", + "ejaculating", + "fagging", + "fagots", + "felching", + "fuckers", + "fuckings", + "fucks", + "gaand", + "gaandfat", + "gaandmasti", + "gaandufad", + "gandfattu", + "gandu", + "gashti", + "gasti", + "ghassa", + "ghasti", + "gucchi", + "gucchu", + "harami", + "haramzade", + "hawas", + "hawas ke pujari", + "hijda", + "hijra", + "jhant", + "jhant chaatu", + "jhant ka keeda", + "jhant ke baal", + "jhant ke pissu", + "jhantu", + "kamine", + "kaminey", + "kanjar", + "kutta", + "kutta kamina", + "kutte ki aulad", + "kutte ki jat", + "kuttiya", + "loda", + "lodu", + "lund", + "lund choos", + "lund ka bakkal", + "lund khajoor", + "lundtopi", + "lundure", + "lusting", + "maa ki chut", + "maal", + "madar chod", + "madarchod", + "madhavchod", + "masochist", + "mooh mein le", + "mutth", + "mutthal", + "najayaz", + "najayaz aulaad", + "najayaz paidaish", + "orgasim", + "paki", + "pataka", + "patakha", + "pisser", + "pisses", + "pissing", + "pube", + "pussies", + "raand", + "randaap", + "randi", + "randi rona", + "rimming", + "saala", + "saala kutta", + "saali kutti", + "saali randi", + "shagging", + "shite", + "shitted", + "shitting", + "shitty", + "skank", + "sluts", + "spac", + "suar", + "suar ke lund", + "suar ki aulad", + "tatte", + "tatti", + "teri maa ka bhosada", + "teri maa ka boba chusu", + "teri maa ki behenchod ", + "teri maa ki chut", + "tharak", + "tharki", + "titt", + "tu chuda", + "turd", + "wank", + "xxx", + "अंडकोश की थैली", + "अंडा", + "अरे नहीं", + "अश्लील", + "उल्लू", + "एक्स रेटेड", + "ओगाज़्म", + "कमबख्त", + "काम करना", + "कामोद्दीपक चित्र", + "कालीन का चूरा", + "किन्नर", + "कुतिया", + "कुत्ते-कमीने", + "कून", + "कॉक", + "गड़बड़", + "गधा कमीने", + "गधे", + "गर्भपात", + "गुदा", + "गेंद का थैला", + "गेंदों", + "गोली चलाने की आवाज़", + "घटिया इंसान", + "चाकलेट का रंग", + "चिंक", + "चुभन", + "चूची", + "चूतड़", + "चोंच", + "छीनना", + "जी में आये करो", + "झटका बंद", + "ठगना पैकर", + "डिल्डो", + "दुष्ट", + "दूर जाने का अभद्र संकेत देना", + "धत् तेरे की", + "नरक", + "नाजी", + "निकला हुआ किनारा", + "नितंब", + "पंगा लेना", + "पिछाड़ी", + "पीड़न कामुक", + "पेशाब", + "पॉर्न", + "फटना", + "फूहड़", + "बकवास", + "बट", + "बलात्कार", + "बहुत मदहोश", + "बांध", + "बिल्ली", + "बेल अंत", + "बेवकूफों", + "बोल पड़ना", + "भगवान-शापित", + "भगशेफ", + "मल", + "मलाशय", + "माँ कमीने", + "मुखमैथुन", + "मुर्गा", + "मुर्गा के", + "मुर्गा चूसने वाला", + "मूर्ख", + "मैल", + "योनि", + "योनी", + "यौन-संबंध", + "रक्तरंजित", + "लानत है", + "लिंग", + "लुटेरा", + "लेबिया", + "वहशी", + "वहशीता", + "वियाग्रा", + "वीर्य", + "वेश्या", + "वैंग", + "वो साले", + "शिफ़्ट को", + "शिश्नमल", + "संभोग सुख", + "सह", + "सह शॉट", + "साहस", + "सिगरेट", + "सींग का बना हुआ", + "स्तन", + "स्तनों", + "हवस", + "हस्तमैथुन", + "होमोसेक्सुअल", + "होर", + ], + "id": english_badwords + + [ + "abortus", + "anal", + "dubur", + "pantat", + "bajingan", + "keledai", + "keparat", + "tas bola", + "bola", + "bellend", + "kejam", + "kebinatangan", + "menggerutu", + "pelacur", + "berdarah", + "blowjob", + "bollok", + "dada", + "payudara", + "buceta", + "gelandangan", + "pengunyah karpet", + "celah", + "cipa", + "kelentit", + "kokang", + "pengisap ayam", + "ayam", + "coon", + "sampah", + "air mani", + "cumshot", + "cunillingus", + "vagina", + "mengutuk", + "kontol", + "dildo", + "dink", + "anjing-keparat", + "duche", + "tanggul", + "berejakulasi", + "ejakulasi", + "homo", + "fagging", + "kayu bakar", + "penggemar", + "felching", + "fellatio", + "flens", + "brengsek", + "kacau", + "sialan", + "persetan", + "pengepakan fudge", + "terkutuk", + "ya tuhan", + "neraka", + "hore", + "terangsang", + "kock", + "labia", + "nafsu", + "bernafsu", + "masokis", + "masturbasi", + "keparat ibu", + "nazi", + "orang negro", + "negro", + "orgasim", + "orgasme", + "cotok", + "penis", + "kencing", + "kesal", + "pisser", + "bikin", + "buritan", + "porno", + "pornografi", + "tusukan", + "menusuk", + "pube", + "pussies", + "memperkosa", + "pemerkosa", + "memperlambat", + "rimming", + "sadis", + "meniduri", + "skrotum", + "seks", + "bercinta", + "waria", + "kotoran", + "shite", + "kengerian", + "dikirim", + "buang hajat", + "menyebalkan", + "smegma", + "jelaga", + "merebut", + "dasar bajingan", + "ruang", + "keberanian", + "buah pelir", + "titt", + "viagra", + "vulva", + "wang", + "terima kasih", + "x diberi peringkat", + "xxx", + ], + "kn": english_badwords + + [ + "ಗರ್ಭಪಾತ", + "ಗುದ", + "ಗುದದ್ವಾರ", + "ಕತ್ತೆ", + "ಆಶ್-ಫಕರ್", + "ಅಸ್ಹೋಲ್", + "ಅಸೋಲೆಸ್", + "ಬಾಲ್ಬಾಗ್", + "ಚೆಂಡುಗಳು", + "ಬಾಸ್ಟರ್ಡ್", + "ಬೆಲೆಂಡ್", + "ಮೃದ್ವಂಗಿ", + "ಪ್ರಾಣಿಜನ್ಯತೆ", + "ಬಿಚ್", + "ಬಿಟ್ಚಿಸ್", + "ಬೆಚಿಂಗ್", + "ರಕ್ತಸಿಕ್ತ", + "ಬ್ಲೋಜಾಬ್", + "ಬೊಲ್ಲೊಕ್", + "ಕುರುಚಲು ಗಿಡ", + "ಬೂಬಿಗಳು", + "ಸ್ತನಗಳನ್ನು", + "ಬುಕೆಟಾ", + "ತಿಕ", + "ಬಟ್", + "ಕಾರ್ಪೆಟ್ ಮಂಚರ್", + "ಚಿಂಕ್", + "ಸಿಪಾ", + "ಚಂದ್ರನಾಡಿ", + "ಕೋಳಿ", + "ಕೋಳಿ ಸಕ್ಕರ್", + "ಕಾಕ್ಸ್", + "ಕೂನ್", + "ಅಮೇಧ್ಯ", + "ಕಮ್", + "ಕಮ್ಶಾಟ್", + "ಕುನಿಲ್ಲಸ್", + "ಕಂಟ್", + "ಡ್ಯಾಮ್", + "ಡಿಕ್", + "ದ್ವಿಧ್ರುವಿ", + "dildos", + "ಡಿಂಕ್", + "ನಾಯಿ-ಫಕರ್", + "ಡಚೆ", + "ಡೈಕ್", + "ಹೊರಹೊಮ್ಮಿಸು", + "ಸ್ಫೂರ್ತಿ", + "ಎಜಾಕ್ಯುಲೇಟ್ಸ್", + "ಇಜಲಲೇಟಿಂಗ್", + "ಉದ್ಗಾರ", + "ತಮಾಷೆ", + "ಮಂದಗತಿ", + "ಮಬ್ಬು", + "fagots", + "ಫ್ಯಾನಿ", + "ಹೊಡೆತ", + "ಪತನ", + "ಚಾಚುಪಟ್ಟಿ", + "ಫಕ್", + "ನಾಶವಾಗಿದ್ದನು", + "ಫಕರ್", + "fuckers", + "ಫಕಿಂಗ್", + "ಫಕಿಂಗ್ಸ್", + "ಇಷ್ಟಪಡುತ್ತಾನೆ", + "ಮಿಠಾಯಿ ಪ್ಯಾಕರ್", + "ದೇವರನ್ನು ಹಾನಿಗೊಳಗಾಯಿತು", + "ಗಾಡ್ಡಮ್", + "ನರಕ", + "ಹೋರ್", + "ಮೊನಚಾದ", + "ಜರ್ಕ್-ಆಫ್", + "ಕೋಕ್", + "ಯೋನಿಯ", + "ಕಾಮ", + "ಕಾಮುಕ", + "ಮಾಸೋಚಿಸ್ಟ್", + "ಹಸ್ತಮೈಥುನ ಮಾಡು", + "ತಾಯಿ ಫಕರ್", + "ನಾಜಿ", + "ನಿಗರ್", + "ನಿಗ್ಗರ್ಗಳು", + "ಒರಾಸಿಮ್", + "ಪರಾಕಾಷ್ಠೆ", + "ಪರಾಕಾಷ್ಠೆಗಳನ್ನು", + "ಪೆಕರ್", + "ಶಿಶ್ನ", + "ಮೂತ್ರ ವಿಸರ್ಜಿಸು", + "ನಿರುತ್ಸಾಹಗೊಂಡಿದೆ", + "ಪಿಸರ್", + "ಮೂತ್ರಪಿಂಡಗಳು", + "pissing", + "ಪಿಸ್ಸಾಫ್", + "ಪೂಪ್", + "ಅಶ್ಲೀಲತೆ", + "ಅಶ್ಲೀಲ", + "ಚುಚ್ಚು", + "ಪ್ರಿಕ್ಸ್", + "ಪಬ್", + "ಪುಸಿಗಳು", + "ಪುಸಿ", + "ಅತ್ಯಾಚಾರ", + "ಅತ್ಯಾಚಾರಿ", + "ಗುದನಾಳದ", + "ರಿಟಾರ್ಡ್", + "ಹಚ್ಚುವುದು", + "ದುಃಖಗಾರ", + "ತಿರುಗಿಸುವುದು", + "ಸ್ಕ್ರೋಟಮ್", + "ವೀರ್ಯ", + "ಲೈಂಗಿಕತೆ", + "ಶಾಗ್", + "ಶಾಗ್ಗಿಂಗ್", + "ಶೆಮೇಲ್", + "ಶಿಟ್", + "ಷೈಟ್", + "ಶಿಟ್ಸ್", + "shitted", + "ಅಲುಗಾಡುವಿಕೆ", + "ಅಸಹ್ಯ", + "ಸ್ಕಾಂಕ್", + "ಸೂಳೆ", + "ಸ್ಲಟ್ಗಳು", + "ಸ್ಮೆಗ್ಮಾ", + "ಕೊಳೆತ", + "ಸ್ನ್ಯಾಚ್", + "ಮಗ-ಆಫ್-ಬಿಚ್", + "spac", + "ಉಬ್ಬು", + "ವೃಷಣ", + "ಟಿಟ್", + "ಚೇಕಡಿ ಹಕ್ಕಿಗಳು", + "turd", + "ಯೋನಿ", + "ವಯಾಗ್ರ", + "ವಾಂಗ್", + "ಮುಷ್ಕರ", + "x ರೇಟೆಡ್", + "xxx", + ], + "ml": english_badwords + + [ + "ഗർഭഛിദ്രം", + "വിശപ്പ്", + "മലദ്വാരം", + "കഴുത", + "അസി ഫക്കർ", + "കഴുതകളെ", + "ആസ്ഹോൾ", + "അശ്ളീലങ്ങൾ", + "ബോൾബാഗ്", + "പന്തുകൾ", + "തന്തയില്ലാത്തവൻ", + "ബെല്ലെൻഡ്", + "മൃഗീയമായ", + "മൃഗീയത", + "ബിച്ച്", + "ബിച്ചുകൾ", + "ബിപിഡിംഗ്", + "രക്തരൂക്ഷിതമായ", + "ആശ്വാസം", + "ബലോക്ക്", + "ബോബ്", + "പൂക്കൾ", + "സ്തനങ്ങൾ", + "ബ്യൂട്ടാ", + "ബം", + "മയക്കുമരുന്ന്", + "പരവതാനി മാൻച്ചർ", + "ചുംബ്", + "സിപാ", + "ക്ലോറിസിസ്", + "കോക്ക്", + "കോക്ക് സക്കർ", + "കോക്സ്", + "കോൺ", + "ക്രാപ്പ്", + "ശുക്ലം", + "പുരുഷാരം", + "സി", + "മുഷിഞ്ഞ", + "കഷ്ടം", + "ഡിക്ക്", + "ഡിൽഡോ", + "dildos", + "ഡൈൻ", + "നായ-ഫക്കർ", + "ഡച്ച്", + "ഡൈകെ", + "ശമിപ്പിക്കുക", + "മോഷ്ടിച്ചു", + "വികാരങ്ങൾ", + "വിരസത", + "മടി", + "ക്ഷീണിപ്പിക്കുക", + "fagot", + "വഞ്ചന", + "ഫാനി", + "വേദന", + "flange", + "ഊമ്പി", + "സംഭോഗം ചെയ്യുക", + "ഫക്കർ", + "നർമ്മം", + "ഫഡ്ജ് പാക്കർ", + "ദൈവം-കൊള്ളിത", + "ഗോഡ്ഡം", + "നരകം", + "വയ്ക്കുക", + "വൃത്തികെട്ട", + "ജെർക് ഓഫ്", + "കിക്ക്", + "ലാബിയ", + "മോഹം", + "മോഹഭംഗം", + "മാസോച്ചിസ്റ്റ്", + "സ്വയംഭോഗം ചെയ്യുക", + "അമ്മ ഫക്കർ", + "നാസി", + "നിഗർ", + "മയക്കുമരുന്നുകൾ", + "രതിമൂർച്ഛ", + "പെക്കർ", + "ലിംഗം", + "മൂത്രമൊഴിക്കുക", + "കുഴഞ്ഞുവീഴുന്നു", + "പിസ്സർ", + "പിസ്സകൾ", + "pissing", + "പിസ്സോഫ്", + "poop", + "അശ്ലീലം", + "അശ്ലീലത", + "പ്രാവി", + "വിസർജ്യങ്ങൾ", + "പ്യൂബ്", + "pussies", + "pussy", + "ബലാൽസംഗം", + "ബലാത്സംഗം", + "മലാശയം", + "തുടരുക", + "റിമ്മിംഗ്", + "സചിസ്റ്റ്", + "വഞ്ചി", + "പുല്ല്", + "ബീജം", + "ശവം", + "ഷാഗിംഗ്", + "അവൾ", + "ഷീറ്റ്", + "ഷെയ്റ്റ്", + "shits", + "തിന്നിട്ടില്ല", + "ഷോർട്ട്", + "ഷൈറ്റി", + "സ്കാൻ", + "മന്ദഹസരം", + "സ്നെഗമാ", + "പുഞ്ചിരി", + "പിടിക്കുക", + "വെറുക്കപ്പെട്ടയാൾ", + "സ്പെയ്ക്", + "തുളച്ച്", + "വൃഷണം", + "പേ", + "ടിത്ത്", + "കുഴപ്പമില്ല", + "യോനി", + "വരാഗ്ര", + "വാൽവ", + "വാങ്", + "വാൻ", + "വേശ്യ", + "x റേറ്റുചെയ്തു", + "xxx", + ], + "mr": english_badwords + + [ + "गर्भपात", + "गुदा", + "गाढव", + "गांडुळ", + "asses", + "asshole", + "assholes", + "ballbag", + "चेंडू", + "बॅस्टर्ड", + "बेलेंड", + "बेस्टियल", + "प्राण्यांबरोबर", + "कुत्री", + "बिट्स", + "खूनी", + "blowjob", + "बोलोक", + "बोब", + "स्तन", + "बसीटा", + "बम", + "बट", + "कार्पेट मुन्चर", + "चिंक", + "सिपा", + "क्लिटोरिस", + "मुर्ख", + "मांसाहारी", + "कॉक्स", + "कॉनन", + "बकवास", + "सह", + "cumshot", + "कनिलिंगस", + "कांट", + "धिक्कार", + "डिक", + "dildo", + "डिल्डो", + "डंक", + "duche", + "डाईक", + "उद्गार", + "उत्साही", + "ejaculates", + "उत्सुकता", + "स्खलन", + "फॅग", + "फॅगिंग", + "फॅगॉट", + "फॅगॉट्स", + "फॅनी", + "फेलिंग", + "फॅलेटीओ", + "निकला", + "fucked", + "गुप्तचर", + "fuckers", + "fucking", + "fuckings", + "fucks", + "फडगे पॅकर", + "देव-शापित", + "देव", + "नरक", + "होरे", + "शिंग", + "झटका बंद", + "कॉक", + "लॅबिया", + "वासना", + "मासोचिस्ट", + "हस्तमैथुन करा", + "आई माकड", + "नाझी", + "निगर", + "निगार", + "ऑर्गॅसिम", + "संभोग", + "orgasms", + "चापटी", + "पुरुषाचे जननेंद्रिय", + "पेशी", + "pissed", + "पिसर", + "pisses", + "पिसिंग", + "पिसोफ", + "घाट", + "अश्लील", + "पोर्नोग्राफी", + "मुरुम", + "प्रिक्स", + "प्यूब", + "pussies", + "मांजर", + "बलात्कार", + "गुदाशय", + "मंद", + "rimming", + "दुःखी", + "screwing", + "स्क्रोटम", + "वीर्य", + "लिंग", + "शेग", + "shagging", + "शेमले", + "विचित्र", + "shite", + "shits", + "shitted", + "shitting", + "shitty", + "घाणेरडा", + "फट", + "sluts", + "सुगंध", + "स्मट", + "छेडछाड", + "मुलगा-एक-कुत्री", + "spac", + "तिरस्कार", + "परीक्षक", + "शीर्षक", + "टिट", + "टर्ड", + "योनी", + "वियाग्रा", + "वल्वा", + "वांग", + "विंक", + "वेश्या", + "एक्स रेट केले", + "xxx", + ], + "pt": english_badwords + + [ + "aborto", + "amador", + "anal", + "aparafusar", + "aranha", + "ariano", + "arrebatar", + "ass-filho da puta", + "asses", + "balalao", + "bastardo", + "bate uma", + "bellend", + "bestial", + "bestialidade", + "bicha", + "bichano", + "bichanos", + "bichas", + "biscate", + "bissexual", + "boceta", + "bolas", + "bollok", + "boob", + "boquete", + "bosta", + "braulio de borracha", + "buceta", + "bumbum", + "bunda", + "burro", + "cabrao", + "cacete", + "cadela", + "cadelas", + "cagando", + "cagar", + "calçado", + "camisinha", + "caralho", + "cerveja", + "chochota", + "chupar", + "cipa", + "clitoris", + "clitóris", + "cobiçoso", + "cocaína", + "cocô", + "coito", + "colhoes", + "com tesão", + "comedor de tapetes", + "comer", + "cona", + "consolo", + "coon", + "coragem", + "corno", + "cu", + "cunillingus", + "dar o rabo", + "desgraçado", + "dildo", + "dildos", + "dink", + "dog-filho da puta", + "droga", + "duche", + "dum raio", + "ejacula", + "ejaculado", + "ejacular", + "ejaculação", + "empacotador de fudge", + "escroto", + "esporra", + "estuprador", + "estupro", + "fagging", + "fanny", + "fecal", + "felação", + "felching", + "fenda", + "filho da puta", + "filhos da puta", + "foda", + "foda-se", + "fode", + "foder", + "fodido", + "frango assado", + "galo", + "galos", + "gozada", + "gozar", + "grelho", + "heroína", + "homem gay", + "homoerótico", + "homosexual", + "hore", + "idiota", + "idiotas", + "inferno", + "kock", + "lolita", + "luxúria", + "lábios", + "lésbica", + "maldito", + "mama", + "masoquista", + "masturbar", + "merda", + "merdas", + "mesa", + "mijando", + "mijar", + "nazista", + "negro", + "niggers", + "não me chateies", + "orgasim", + "orgasmo", + "orgasmos", + "otário", + "paneleiro", + "passar um cheque", + "pau", + "peidar", + "peitos", + "peituda", + "pica", + "picadas", + "pinto", + "pisser", + "porcaria", + "porno", + "pornografia", + "pornô", + "porra", + "prostituta", + "pube", + "punheta", + "puta", + "puta que pariu", + "puta que te pariu", + "putaria", + "puto", + "pênis", + "queca", + "retardar", + "reto", + "rimming", + "sacanagem", + "saco", + "saco de bola", + "sangrento", + "sapatona", + "sexo", + "shite", + "skank", + "smegma", + "spac", + "sujeira", + "sádico", + "sêmen", + "testículo", + "tetas", + "titt", + "torneira", + "transando", + "transar", + "transsexual", + "trepada", + "vadia", + "vadias", + "vagabunda", + "vagabundo", + "vagina", + "vai tomar no cu", + "vai-te foder", + "veado", + "viagra", + "vibrador", + "vulva", + "wang", + "x avaliado", + "xana", + "xixi", + "xochota", + "xxx", + "ânus", + ], + "te": english_badwords + + [ + "గర్భస్రావం", + "అంగ", + "పాయువు", + "గాడిద", + "గాడిద-fucker", + "asses", + "assholes", + "బాల్బ్యాగ్", + "బంతుల్లో", + "బాస్టర్డ్", + "బెల్లెండ్", + "మృగ", + "బెస్టియాలిటీ", + "బిచ్", + "bitches", + "బిట్చింగ్", + "బ్లడీ", + "blowjob", + "బోల్లక", + "బూబ్", + "వక్షోజాలను", + "ఛాతీ", + "buceta", + "బం", + "బట్", + "కార్పెట్ ముంచర్", + "చింక్", + "cipa", + "స్త్రీగుహ్యాంకురము", + "ఆత్మవిశ్వాసం", + "కాక్-సక్కర్", + "కాక్స్", + "కూన్", + "చెత్త", + "కం", + "cumshot", + "క్యునిల్లింగస్", + "కంట్", + "తిట్టు", + "డిక్", + "లైంగిక సంతృప్తి కోసం స్త్రీలు ఉపయోగించే పురుషాంగము వంటి పరికరము", + "డిల్డోస్", + "dink", + "కుక్క-fucker", + "డూష్", + "డైక్", + "స్ఖలించు", + "ఎజాక్యులేటెడ్", + "ఎజాక్యులేట్స్", + "ఎరాక్యులేటింగ్", + "స్ఖలనం", + "నవుకరు", + "ఫాగ్గింగ్", + "ఫాగాట్", + "ఫగాట్స్", + "fanny", + "ఫెల్చింగ్", + "కుడుచుట", + "అచ్చు", + "ఫక్", + "ఇబ్బంది పెట్టాడు", + "fucker", + "ఫకర్స్", + "ఫకింగ్", + "ఫకింగ్స్", + "ఫక్స్", + "ఫడ్జ్ ప్యాకర్", + "దేవతలా మంచిది", + "గాడ్డామ్", + "నరకం", + "హోర్", + "horny", + "జెర్క్-ఆఫ్", + "కాక్", + "పెదవి", + "కామం", + "మనసు పడ్డట్లు చిత్రించారు", + "masochist", + "హస్తప్రయోగం", + "తల్లి ఫెకర్", + "నాజీ", + "నిగ్గర్", + "నిగ్గర్స్", + "ఆర్గాసిమ్", + "స్కలనం", + "orgasms", + "pecker", + "పురుషాంగం", + "విసర్జన", + "pissed", + "పిస్సర్", + "పిస్సీస్", + "పిస్సింగ్", + "పిస్సాఫ్", + "poop", + "శృంగార", + "పోర్నో", + "అశ్లీల", + "బుడతడు", + "ప్రిక్స్", + "ప్యూబ్", + "pussies", + "పుస్సీ", + "రేప్", + "ఉన్నప్పటికీ బలాత్కారం", + "పురీషనాళం", + "రిటార్డ్", + "రిమ్మింగ్", + "పీడన కాముకత", + "screwing", + "స్క్రోటమ్", + "వీర్యం", + "సెక్స్", + "బొచ్చు", + "షగ్గింగ్", + "షీమేల్", + "ఒంటి", + "షైట్", + "షిట్స్", + "షిట్టెడ్", + "షిట్టింగ్", + "shitty", + "స్కాన్క్", + "నీతి", + "స్లట్స్", + "శిశ్న", + "స్మట్", + "స్నాచ్", + "ఒక బిచ్ కుమారుడు ఆఫ్", + "spac", + "స్పంక్", + "వృషణాలు", + "తునక", + "టిట్స్", + "టిట్", + "turd", + "యోని", + "వయాగ్రా", + "జననాంగం", + "వాంగ్", + "వ్యాంక్", + "వేశ్య", + "x రేట్", + "xxx", + ], + "vi": english_badwords + + [ + "sự phá thai", + "hậu môn", + "mông", + "đồ ngu", + "lừa", + "lỗ đít", + "túi bóng", + "những quả bóng", + "đồ khốn", + "tuyệt vời", + "mục sư", + "lòng tốt", + "chó cái", + "dính máu", + "công việc thổi", + "bollok", + "boob", + "ngực", + "buceta", + "ăn mày", + "thảm muncher", + "sứt mẻ", + "cipa", + "âm vật", + "gà", + "gà hút", + "gà trống", + "coon", + "tào lao", + "kiêm", + "cum", + "cunillingus", + "lồn", + "chỉ trích", + "tinh ranh", + "dương vật giả", + "dink", + "chó-chó", + "duche", + "đê", + "xuất tinh", + "fag", + "đóng băng", + "fagot", + "đồ ăn vặt", + "người hâm mộ", + "nỉ", + "thất bại", + "mặt bích", + "chết tiệt", + "quái", + "đụ", + "ôm", + "đóng gói fudge", + "địa ngục", + "có", + "sừng", + "giật", + "kock", + "môi âm", + "ham muốn", + "khổ dâm", + "thủ dâm", + "mẹ kiếp", + "nazi", + "người da đen", + "người mách nước", + "cực khoái", + "người mổ", + "dương vật", + "đi tiểu", + "bực mình", + "đái", + "phân", + "khiêu dâm", + "nội dung khiêu dâm", + "châm", + "chích", + "pube", + "pussies", + "âm hộ", + "hiếp dâm", + "trực tràng", + "chậm phát triển", + "xé", + "người tàn bạo", + "vặn vít", + "bìu", + "tinh dịch", + "tình dục", + "lông", + "xáo trộn", + "đồng tính", + "cứt", + "shite", + "ván trượt", + "đĩ", + "quần lót", + "smegma", + "xì trum", + "con trai", + "spac", + "spunk", + "tinh hoàn", + "ăn miếng trả miếng", + "titt", + "cỏ", + "âm đạo", + "viagra", + "âm môn", + "wang", + "đã ngủ", + "con điếm", + "x đánh giá", + "xxx", + ], + "zh": english_badwords + + [ + "13.", + "13点", + "㞗", + "三级片", + "下三烂", + "下贱", + "个老子的", + "九游", + "乳", + "乳交", + "乳头", + "乳房", + "乳波臀浪", + "交配", + "仆街", + "仆街", + "他奶奶", + "他奶奶的", + "他奶娘的", + "他妈", + "他妈ㄉ王八蛋", + "他妈地", + "他妈的", + "他娘", + "他马的", + "你个傻比", + "你他马的", + "你全家", + "你奶奶的", + "你她马的", + "你妈", + "你妈的", + "你娘", + "你娘卡好", + "你娘咧", + "你它妈的", + "你它马的", + "你是鸡", + "你是鸭", + "你老味", + "你老母", + "你老闆", + "你马的", + "做爱", + "傻比", + "傻逼", + "册那", + "冚家拎", + "冚家鏟", + "军妓", + "几八", + "几叭", + "几巴", + "几芭", + "刚度", + "刚瘪三", + "包皮", + "十三点", + "卖B", + "卖比", + "卖淫", + "卵", + "卵子", + "双峰微颤", + "口交", + "口肯", + "叫床", + "吃屎", + "后庭", + "吹箫", + "咸家伶", + "咸家鏟", + "塞你公", + "塞你娘", + "塞你母", + "塞你爸", + "塞你老师", + "塞你老母", + "处女", + "外阴", + "大卵子", + "大卵泡", + "大鸡巴", + "奶", + "奶奶的熊", + "奶子", + "奸", + "奸你", + "她妈地", + "她妈的", + "她马的", + "妈B", + "妈个B", + "妈个比", + "妈个老比", + "妈妈的", + "妈比", + "妈的", + "妈的B", + "妈逼", + "妓", + "妓女", + "妓院", + "妳她妈的", + "妳妈的", + "妳娘的", + "妳老母的", + "妳马的", + "姘头", + "姣西", + "姦", + "娘个比", + "娘的", + "婊子", + "婊子养的", + "嫖娼", + "嫖客", + "它妈地", + "它妈的", + "密洞", + "射你", + "射精", + "小乳头", + "小卵子", + "小卵泡", + "小瘪三", + "小肉粒", + "小骚比", + "小骚货", + "小鸡巴", + "小鸡鸡", + "尻", + "屁眼", + "屁股", + "屄", + "屌", + "屎忽", + "巨乳", + "干x娘", + "干七八", + "干你", + "干你妈", + "干你娘", + "干你老母", + "干你良", + "干妳妈", + "干妳娘", + "干妳老母", + "干妳马", + "干您娘", + "干机掰", + "干死CS", + "干死GM", + "干死你", + "干死客服", + "幹", + "强奸", + "强奸你", + "性", + "性交", + "性器", + "性无能", + "性爱", + "情色", + "想上你", + "懆您妈", + "懆您娘", + "懒8", + "懒八", + "懒叫", + "懒教", + "成人", + "我操你祖宗十八代", + "扒光", + "打炮", + "打飞机", + "抽插", + "招妓", + "插你", + "插死你", + "撒尿", + "撚", + "操你", + "操你全家", + "操你奶奶", + "操你妈", + "操你娘", + "操你祖宗", + "操你老妈", + "操你老母", + "操妳", + "操妳全家", + "操妳妈", + "操妳娘", + "操妳祖宗", + "操机掰", + "操比", + "操逼", + "放荡", + "日他娘", + "日你", + "日你妈", + "日你老娘", + "日你老母", + "日批", + "月经", + "机八", + "机巴", + "机机歪歪", + "杂种", + "柒", + "浪叫", + "淫", + "淫乱", + "淫妇", + "淫棍", + "淫水", + "淫秽", + "淫荡", + "淫西", + "湿透的内裤", + "激情", + "灨你娘", + "烂货", + "烂逼", + "爛", + "狗屁", + "狗日", + "狗狼养的", + "玉杵", + "王八蛋", + "瓜娃子", + "瓜婆娘", + "瓜批", + "瘪三", + "白烂", + "白痴", + "白癡", + "硬膠", + "祖宗", + "私服", + "笨實", + "笨蛋", + "粉腸", + "精子", + "老二", + "老味", + "老母", + "老瘪三", + "老骚比", + "老骚货", + "肉壁", + "肉棍子", + "肉棒", + "肉缝", + "肏", + "肛交", + "肥西", + "色情", + "花柳", + "荡妇", + "賤", + "贝肉", + "贱B", + "贱人", + "贱货", + "贼你妈", + "赛你老母", + "赛妳阿母", + "赣您娘", + "躝癱", + "轮奸", + "迷药", + "逼", + "逼样", + "野鸡", + "閪", + "阳具", + "阳萎", + "阴唇", + "阴户", + "阴核", + "阴毛", + "阴茎", + "阴道", + "阴部", + "陰莖", + "雞巴", + "靠北", + "靠母", + "靠爸", + "靠背", + "靠腰", + "驶你公", + "驶你娘", + "驶你母", + "驶你爸", + "驶你老师", + "驶你老母", + "骚比", + "骚货", + "骚逼", + "鬼公", + "鳩", + "鸡8", + "鸡八", + "鸡叭", + "鸡吧", + "鸡奸", + "鸡巴", + "鸡芭", + "鸡鸡", + "龟儿子", + "龟头", + ], +} diff --git a/data_tooling/ac_dc/deduplicate.py b/data_tooling/ac_dc/deduplicate.py new file mode 100644 index 0000000..f4baa55 --- /dev/null +++ b/data_tooling/ac_dc/deduplicate.py @@ -0,0 +1,555 @@ +"""Creating simhashes and removing near duplicates with annoy.""" +import datetime +import logging +import os +import re +from collections import defaultdict +from multiprocessing import Manager, cpu_count +from typing import List, Optional, Tuple + +import networkx as nx +import numpy as np +import pandas as pd +import typer +from annoy import AnnoyIndex +from datasets import ( + Dataset, + DatasetDict, + concatenate_datasets, + load_dataset, + load_from_disk, +) +from mpire import WorkerPool +from simhash import Simhash +from tqdm import tqdm + +app = typer.Typer() +logging.basicConfig(level=os.environ.get("LOG_LEVEL", "INFO").upper()) +logger = logging.getLogger(__name__) + + +def create_shingles(text: str, window: int = 4) -> List[str]: + """ + Create shingles/ngrams from the given text. This uses character-ngrams to be language agnostic. + + Parameters + ---------- + text : str + Input text string + window : int, optional + The size of the window, by default 4 + + Returns + ------- + List[str] + List of shingles + + Examples + -------- + >>> create_shingles("This is a test message", window=3) + ['thi', 'his', 'isi', 'sis', 'isa', 'sat', 'ate', 'tes', 'est', 'stm', 'tme', 'mes', 'ess', 'ssa', 'sag', 'age'] + """ + if len(text) <= window: + return [text] + + text = re.sub(r"[^\w]+", "", text.lower()) + return [text[i : i + window] for i in range(len(text) - window + 1)] + + +def check_num_proc(num_proc: int = -1) -> int: + """ + Check the number of processors. Return a safe-checked value. + + Parameters + ---------- + num_proc : int, optional + Number of processors to use, by default -1 + + Returns + ------- + int + Number of processors to use + + Raises + ------ + ValueError + If the input exceeds the number of processors available + """ + maximum: int = cpu_count() + if num_proc > maximum: + raise ValueError( + f"{num_proc} exceeds the maximum number ({maximum}) of processors" + ) + + if num_proc == -1: + num_proc = maximum + else: + logger.warning(f"Using {num_proc} out of {maximum} can be slow") + + return num_proc + + +@app.command() +def create_shards( + output_dir: str, + num_shards: int, + path: str = typer.Option( + "mhtoin/register_oscar", help="Path or name of the dataset" + ), + name: Optional[str] = typer.Option( + None, help="Defining the name of the dataset configuration" + ), + data_dir: Optional[str] = typer.Option( + None, help="Defining the data_dir of the dataset configuration" + ), + split: Optional[str] = typer.Option(None, help="Which split of the data to load"), +): + """ + Shard a dataset into multiple parts. + + Parameters + ---------- + output_dir : str + Directory path for all the subset files + num_shards : int + Number of shards to use + path : str, optional + Path to the dataset configuration, by default typer.Option( "mhtoin/register_oscar", help="Path or name of the dataset" ) + name : Optional[str], optional + Name of the dataset configuration, by default typer.Option( None, help="Defining the name of the dataset configuration" ) + data_dir : Optional[str], optional + Local data directory, by default typer.Option( None, help="Defining the datadata_dir of the dataset configuration" ) + split : Optional[str], optional + The split of the dataset configuration, by default typer.Option(None, help="Which split of the data to load") + """ + + if not os.path.exists(output_dir): + os.makedirs(output_dir, exist_ok=True) + + ds = load_dataset(path, name, data_dir=data_dir, use_auth_token=True) + + def shard( + ds, + split: str, + num_shards: int, + idx: int, + output_dir: str, + ): + ds[split].shard(num_shards=num_shards, index=idx).to_json( + os.path.join(output_dir, f"sharded_{idx:05d}.jsonl"), + orient="records", + lines=True, + force_ascii=False, + ) + + with WorkerPool(n_jobs=min(num_shards, cpu_count()), shared_objects=ds) as pool: + pool.map( + shard, + [ + { + "split": split, + "num_shards": num_shards, + "idx": i, + "output_dir": output_dir, + } + for i in range(num_shards) + ], + progress_bar=True, + ) + + +@app.command() +def build_hashes( + output_dir: str, + path: str = typer.Option( + "mhtoin/register_oscar", help="Path or name of the dataset" + ), + name: Optional[str] = typer.Option( + None, help="Defining the name of the dataset configuration" + ), + data_dir: Optional[str] = typer.Option( + None, help="Defining the data_dir of the dataset configuration" + ), + data_files: Optional[List[str]] = typer.Option( + None, help="Path(s) to source data file(s)" + ), + split: Optional[str] = typer.Option(None, help="Which split of the data to load"), + shingle_size: int = typer.Option(4, help="Size of the generated shingles"), + num_proc: int = typer.Option(-1, help="Number of processes to use"), + text_column_name: Optional[str] = typer.Option( + "text", help="Column name of the text" + ), +): + """ + Create a single dataset with an extra `hash` column from all data files. + + The time complexity for this function call is rounghly O(N * L // C) where N is the number + of records in the data, L is the average length of each record text and C is the number of processes. + The addition of the hashes should be insignificant in size compared to the original data (12MB vs 800MB for two English shards). + + Example: + + ```bash + python ac_dc/deduplicate.py build-hashes "cache/en_hashes_00001" --data-files "en/en_00001.jsonl.gz" --data-files "en/en_00002.jsonl.gz" --path "mhtoin/register_oscar" --split "train" + ``` + + This generates a dataset `cache/en_hashes_00001` from two shards `en/en_00001.jsonl.gz` and `en/en_00002.jsonl.gz` in `mhtoin/register_oscar`. + + Parameters + ---------- + output_dir : str + Output directory of the new data + path : str, optional + Path or name of the dataset + name : Optional[str], optional + Defining the name of the dataset configuration + data_dir : Optional[str], optional + Defining the data_dir of the dataset configuration + data_files : Optional[List[str]], optional + Path(s) to source data file(s) + split : Optional[str], optional + Which split of the data to load + shingle_size : int, optional + Size of the generated shingles + num_proc : int, optional + Number of processes to use + text_column_name : Optional[str], optional + Column name of the text + """ + num_proc = check_num_proc(num_proc) + ds = load_dataset(path=path, name=name, data_files=data_files, data_dir=data_dir) + + def process(record): + return { + "hash": np.array( + list( + np.binary_repr( + Simhash( + create_shingles(record[text_column_name], shingle_size) + ).value + ).zfill(64) + ) + ).astype(np.int8) + } + + splits = [split] if split is not None else list(ds.keys()) + for s in splits: + ds[s] = ds[s].map(process, num_proc=num_proc) + ds.save_to_disk(output_dir) + + +@app.command() +def build_index( + output_file: str, + data_dirs: List[str], + split: Optional[str] = typer.Option(None, help="Which split of the data to load"), + num_proc: int = typer.Option(-1, help="Number of processes to use"), + num_trees: int = typer.Option( + 100, help="Number of trees to build in the annoy index" + ), +): + """ + Merging all hashes and build an index. The time complexity and space complexity for this function is at least O(N). + Building the index is not paralleled in this implementation since the index needs access to all hashes. + + Example: + + ```bash + python deduplicate.py build-index "cache/en_simhash_index.pkl" "cache/en_hashes_00001" --split "train" + ``` + + This builds an index to be stored at `cache/en_simhash_index.pkl` from `cache/en_hashes_00001` + + Parameters + ---------- + output_file : str + Output path for the index file + data_dirs : List[str] + Dataset directories with hashes to build the index from + split : Optional[str], optional + Which split of the data to load + num_proc : int, optional + Number of processes to use + num_trees : int, optional + Number of trees to build for the annoy index (10 ~ 1024) + """ + num_proc = check_num_proc(num_proc) + + t = AnnoyIndex(64, "hamming") + + manager = Manager() + hashes: List[Tuple[int, np.ndarray]] = manager.list() + + def process(id, hash, text=None, meta=None): + hashes.append((int(id), hash)) + return + + for dir in data_dirs: + ds = load_from_disk(dir) + splits = [split] if split is not None else list(ds.keys()) + if split is None: + logger.warning( + f"Using all splits to build the index, please make sure the `id` is unique globally" + ) + for split in splits: + with WorkerPool(n_jobs=num_proc) as pool: + pool.map( + process, + ds[split], + progress_bar=True, + ) + + # Not paralleled + for id, hash in tqdm(hashes): + t.add_item(id, hash) + + t.build(num_trees) + t.save(output_file) + + +@app.command() +def find_duplicates( + data_dirs: List[str], + index_file: str, + split: Optional[str] = typer.Option(None, help="Which split of the data to load"), + num_proc: int = typer.Option(-1, help="Number of processes to use"), + k: int = typer.Option(100, help="Number of nearest neighbors to search for"), + threshold: int = typer.Option(3, help="Maximum hamming distance for duplicates"), +): + """ + Find duplicates for given datasets. For each dataset directory `d`, it outputs a `d_duplicates` directory + with a new `duplicates` column, containing all the duplicate indices. + + Example: + + ```bash + python deduplicate.py find-duplicates "cache/en_hashes_00001" "cache/en_simhash_index.pkl" --split "train" --k 100 --threshold 3 + ``` + + This finds all duplicates in `cache/en_hashes_00001` with `cache/en_simhash_index.pkl`. It should outputs a directory named + `cache/en_hashes_00001_duplicates`. + + Parameters + ---------- + data_dirs : List[str] + List of dataset directories to find duplicates + index_file : str + Path to the index file + split : Optional[str], optional + Which split of the data to load + num_proc : int, optional + Number of processes to use + k : int, optional + Number of nearest neighbors to search for, by default 100 + threshold : int, optional + Maximum hamming distance for duplicates, by default 3 + """ + num_proc = check_num_proc(num_proc) + + index = AnnoyIndex(64, "hamming") + index.load(index_file) + logger.info(f"Querying with {index.get_n_items()} records") + + def process(index, id, hash, text=None, meta=None): + candidates = index.get_nns_by_item(int(id), k, include_distances=True) + dups = {i for i, d in zip(*candidates) if d <= threshold} + record = { + "duplicates": list(dups) if dups else [-1], + "id": id, + "hash": hash, + } + if meta is not None: + record["meta"] = meta + if text is not None: + record["text"] = text + return record + + for dir in data_dirs: + ds = load_from_disk(dir) + splits = [split] if split is not None else list(ds.keys()) + for s in splits: + with WorkerPool(n_jobs=num_proc, shared_objects=index) as pool: + results = pool.map(process, ds[s], progress_bar=True) + ds[s] = Dataset.from_pandas(pd.DataFrame(results)) + logger.info( + f"Found {len(ds[s].filter(lambda x: len(x['duplicates']) > 1))} duplicates in {dir}" + ) + + ds.save_to_disk(dir.rstrip("/") + "_duplicates") + + +@app.command() +def remove_duplicates( + data_dirs: List[str], + split: Optional[str] = typer.Option(None, help="Which split of the data to load"), + num_proc: int = typer.Option(-1, help="Number of processes to use"), +): + """ + Remove duplicates based on the `duplicates` column by finding the connected components and only keep the first occurrence. + For each data directory `d`, it outputs a `d_deduplicated` directory. + + Example: + + ```bash + python deduplicate.py remove-duplicates "cache/en_hashes_00001_duplicates" --split "train" + ``` + This removes all duplicates from `cache/en_hashes_00001_duplicates` and create + a deduplicated version in `cache/en_hashes_00001_deduplicated`. + + Parameters + ---------- + data_dirs : List[str] + List of data directories to remove duplicates from + split : Optional[str], optional + Which split of the data to load + num_proc : int, optional + Number of processes to use + """ + num_proc = check_num_proc(num_proc) + + # a and b are connected if they are duplicates + G = nx.Graph() + manager = Manager() + edges = manager.list() + + def process(record): + for dup in record["duplicates"]: + if int(record["id"]) == dup or dup == -1: + continue + edges.append((int(record["id"]), dup)) + + for dir in data_dirs: + ds = load_from_disk(dir) + splits = [split] if split is not None else list(ds.keys()) + for s in splits: + ds[s].map(process, num_proc=num_proc) + + flags = defaultdict(lambda: False) + for x, y in tqdm(edges): + G.add_edge(x, y) + + for c in nx.connected_components(G): + for n in c: + flags[n] = False + flags[c.pop()] = True + + for dir in data_dirs: + ds = load_from_disk(dir) + splits = [split] if split is not None else list(ds.keys()) + for s in splits: + ds[s] = ds[s].filter(lambda x: flags.get(int(x["id"]), True)) + ds.save_to_disk(dir.rstrip("/").replace("_duplicates", "_deduplicated")) + + +@app.command() +def merge_meta( + index_file: str, + data_dirs: List[str] = typer.Option(None, help="Source data to add metadata in"), + meta_data_dirs: List[str] = typer.Option( + None, help="Reference data to extract metadata from" + ), + split: Optional[str] = typer.Option(None, help="Which split of the data to load"), + num_proc: int = typer.Option(-1, help="Number of processes to use"), + k: int = typer.Option(1, help="Number of nearest neighbors to search for"), + threshold: int = typer.Option(1, help="Maximum hamming distance for duplicates"), +): + """ + Extracting metadata feature from `meta_data_dirs` and merging into data in `data_dirs` + For each data directory `d`, it outputs a `d_with_meta` directory. + + see examples/merge.sh for an example + + Parameters + ---------- + data_dirs : List[str] + List of data directories to add metadata to + meta_data_dirs : List[str] + List of data directories to extract metadata from + split : Optional[str], optional + Which split of the data to load + num_proc : int, optional + Number of processes to use + k : int, optional + Number of nearest neighbors to search for, by default 1 + threshold : int, optional + Maximum hamming distance for duplicates, by default 1 + """ + num_proc = check_num_proc(num_proc) + manager = Manager() + meta_data = manager.dict() + + index = AnnoyIndex(64, "hamming") + index.load(index_file) + logger.info(f"Querying with {index.get_n_items()} records") + + def process_meta(record): + meta_data[int(record["id"])] = record["meta"] + + for dir in meta_data_dirs: + ds = load_from_disk(dir) + splits = [split] if split is not None else list(ds.keys()) + for s in splits: + ds[s].map(process_meta, num_proc=num_proc) + + def merge(index, hash, id=None, text=None, meta=None): + + metadata = { + "headers": { + "warc-record-id": "", + "warc-date": datetime.datetime(1970, 1, 1), + "content-type": "", + "content-length": -1, + "warc-type": "", + "warc-identified-content-language": "", + "warc-refers-to": "", + "warc-target-uri": "", + "warc-block-digest": "", + }, + "offset": -1, + "nb_sentences": -1, + } + + candidates = index.get_nns_by_vector(hash, k, include_distances=True) + dups = {i for i, d in zip(*candidates) if d <= threshold} + + if not dups: + return {"meta": metadata} + + for dup in dups: + if dup in meta_data: + metadata = meta_data[dup] + break + + return {"meta": metadata} + + for dir in data_dirs: + ds = load_from_disk(dir) + splits = [split] if split is not None else list(ds.keys()) + for s in splits: + with WorkerPool(n_jobs=num_proc, shared_objects=index) as pool: + results = pool.map(merge, ds[s], progress_bar=True) + ds[s] = Dataset.from_pandas(pd.DataFrame(results)) + logger.info( + f"Matched {len(ds[s].filter(lambda x: x['meta']['offset'] != -1))}/{len(ds[s])} records in {dir}" + ) + ds.save_to_disk(dir.rstrip("/").replace("_duplicates", "_with_meta")) + + +@app.command() +def merge_shards( + output_dir: str, + data_dirs: list[str], + split: Optional[str] = typer.Option(None, help="Which split of the data to load"), +): + if not os.path.exists(output_dir): + os.makedirs(output_dir, exist_ok=True) + ds = [] + for dir in data_dirs: + ds.append(load_from_disk(dir)[split]) + + DatasetDict({split: concatenate_datasets(ds)}).save_to_disk(output_dir) + + +if __name__ == "__main__": + + app() diff --git a/data_tooling/ac_dc/download_sentencepiece_kenlm_models.py b/data_tooling/ac_dc/download_sentencepiece_kenlm_models.py new file mode 100644 index 0000000..635262b --- /dev/null +++ b/data_tooling/ac_dc/download_sentencepiece_kenlm_models.py @@ -0,0 +1,48 @@ +"""Download Sentencepiece and KenLM models for supported languages (48) from Facebook. + +Usage: + python download_sentencepiece_kenlm_models.py --output_path /tmp/ + +All Sentencepiece and KenLM language models will be saved under /tmp. +""" + +import argparse +import subprocess + +from languages_id import langs_id + + +def download_sentencepiece_kenlm_models(output_path: str) -> None: + supported_sentencepiece_langs = langs_id["sentencepiece_id"].dropna().unique() + for lang in supported_sentencepiece_langs: + try: + output_sentencepiece = subprocess.check_output( + f"wget http://dl.fbaipublicfiles.com/cc_net/lm/{lang}.sp.model -P {output_path}", + shell=True, + ) + except: + print( + f"Warning: Download failed for Sentencepiece model for language {lang}." + ) + + supported_kenlm_langs = langs_id["kenlm_id"].dropna().unique() + for lang in supported_kenlm_langs: + try: + output_kenlm = subprocess.check_output( + f"wget http://dl.fbaipublicfiles.com/cc_net/lm/{lang}.arpa.bin -P {output_path}", + shell=True, + ) + except: + print(f"Warning: Download failed for KenLM model for language {lang}.") + + +if __name__ == "__main__": + parser = argparse.ArgumentParser( + description="Download Sentencepiece and KenLM models for supported languages." + ) + parser.add_argument( + "--output_path", type=str, default="/tmp/", help="Output path to save models." + ) + args = parser.parse_args() + + download_sentencepiece_kenlm_models(output_path=args.output_path) diff --git a/data_tooling/ac_dc/examples/dedup.sh b/data_tooling/ac_dc/examples/dedup.sh new file mode 100644 index 0000000..6174552 --- /dev/null +++ b/data_tooling/ac_dc/examples/dedup.sh @@ -0,0 +1,39 @@ +#!/bin/bash +LANGUAGES=('gl') +SHARDS=20 +THRESHOLD=3 +PYTHON="/home/jovyan/conda/envs/data/bin/python" +SCRIPT="/home/jovyan/data_tooling/ac_dc/deduplicate.py" + +for lang in "${LANGUAGES[@]}"; do + echo "lang: $lang" + + echo "Creating ${SHARDS} shards" + $PYTHON $SCRIPT create-shards "cache/sharded_deduplicated_${lang}" $SHARDS --path "oscar-corpus/OSCAR-2109" --name "deduplicated_${lang}" --split "train" + + echo "Hashing documents" + for i in $(seq -f "%05g" 0 "$((SHARDS - 1))"); do + echo "Hashing shard ${i}" + $PYTHON $SCRIPT build-hashes "cache/sharded_deduplicated_${lang}/hashes_${i}" --data-files "sharded_${i}.jsonl" --path "cache/sharded_deduplicated_${lang}" --split "train" --shingle-size 4 + done + + echo "Creating index" + $PYTHON $SCRIPT build-index "cache/sharded_deduplicated_${lang}/simhash_index.ann" $(seq -s " " -f "cache/sharded_deduplicated_${lang}/hashes_%05g" 0 "$((SHARDS - 1))") --split "train" + + echo "Finding duplicates" + for i in $(seq -f "%05g" 0 "$((SHARDS - 1))"); do + echo "Querying shard ${i}" + $PYTHON -W ignore $SCRIPT find-duplicates "cache/sharded_deduplicated_${lang}/hashes_${i}" "cache/sharded_deduplicated_${lang}/simhash_index.ann" --split "train" --k 100 --threshold $THRESHOLD + done + + echo "Removing duplicates" + for i in $(seq -f "%05g" 0 "$((SHARDS - 1))"); do + echo "Cleaning shard ${i}" + $PYTHON $SCRIPT remove-duplicates "cache/sharded_deduplicated_${lang}/hashes_${i}_duplicates" --split "train" + done + + echo "Merging shards" + $PYTHON $SCRIPT merge-shards "cache/sharded_deduplicated_${lang}/output" $(seq -s " " -f "cache/sharded_deduplicated_${lang}/hashes_%05g_deduplicated" 0 "$((SHARDS - 1))") --split "train" + + echo "Done" +done diff --git a/data_tooling/ac_dc/examples/merge.sh b/data_tooling/ac_dc/examples/merge.sh new file mode 100644 index 0000000..1ba8025 --- /dev/null +++ b/data_tooling/ac_dc/examples/merge.sh @@ -0,0 +1,35 @@ +#!/bin/bash +LANGUAGES=('min') +SHARDS=1 +THRESHOLD=1 +PYTHON="/home/jovyan/conda/envs/data/bin/python" +SCRIPT="/home/jovyan/data_tooling/ac_dc/deduplicate.py" + +for lang in "${LANGUAGES[@]}"; do + echo "lang: $lang" + $PYTHON $SCRIPT create-shards "cache/sharded_deduplicated_${lang}_v2" $SHARDS --path "oscar-corpus/OSCAR-2109" --name "deduplicated_${lang}" --split "train" + $PYTHON $SCRIPT create-shards "cache/sharded_deduplicated_${lang}_v1" $SHARDS --path "oscar" --name "unshuffled_deduplicated_${lang}" --split "train" + + # Hash + for i in $(seq -f "%05g" 0 "$((SHARDS - 1))"); do + $PYTHON $SCRIPT build-hashes "cache/sharded_deduplicated_${lang}_v2/hashes_${i}" --data-files "sharded_${i}.jsonl" --path "cache/sharded_deduplicated_${lang}_v2" --split "train" --shingle-size 4 --text-column-name "text" + done + + for i in $(seq -f "%05g" 0 "$((SHARDS - 1))"); do + $PYTHON $SCRIPT build-hashes "cache/sharded_deduplicated_${lang}_v1/hashes_${i}" --data-files "sharded_${i}.jsonl" --path "cache/sharded_deduplicated_${lang}_v1" --split "train" --shingle-size 4 --text-column-name "text" + done + + # Create the index file + # $PYTHON $SCRIPT build-index "cache/sharded_deduplicated_${lang}_v1/simhash_index.ann" $(seq -s " " -f "cache/sharded_deduplicated_${lang}_v1/hashes_%05g" 0 "$((SHARDS - 1))") --split "train" + $PYTHON $SCRIPT build-index "cache/sharded_deduplicated_${lang}_v2/simhash_index.ann" $(seq -s " " -f "cache/sharded_deduplicated_${lang}_v2/hashes_%05g" 0 "$((SHARDS - 1))") --split "train" + + # merge v2 metadata into v1 + $PYTHON $SCRIPT merge-meta \ + "cache/sharded_deduplicated_${lang}_v2/simhash_index.ann" \ + $(seq -s " " -f "--data-dirs cache/sharded_deduplicated_${lang}_v1/hashes_%05g" 0 "$((SHARDS - 1))") \ + $(seq -s " " -f "--meta-data-dirs cache/sharded_deduplicated_${lang}_v2/hashes_%05g" 0 "$((SHARDS - 1))") \ + --k 1 \ + --threshold $THRESHOLD \ + --split "train" + +done diff --git a/data_tooling/ac_dc/explanation_filtering_pipeline.pdf b/data_tooling/ac_dc/explanation_filtering_pipeline.pdf new file mode 100644 index 0000000..7a42122 Binary files /dev/null and b/data_tooling/ac_dc/explanation_filtering_pipeline.pdf differ diff --git a/data_tooling/ac_dc/filtering.py b/data_tooling/ac_dc/filtering.py new file mode 100644 index 0000000..46dbf51 --- /dev/null +++ b/data_tooling/ac_dc/filtering.py @@ -0,0 +1,881 @@ +import re + +import numpy as np + +import fasttext + +import sentencepiece +import kenlm + +import pathlib + +from languages_id import langs_id +from parameters_filtering import parameters_filtering +from normalization import normalization +from stopwords import stopwords +from badwords import badwords + + +class LoadParameters: + @staticmethod + def load_parameters(lang_dataset_id): + if lang_dataset_id in parameters_filtering: + param = parameters_filtering[lang_dataset_id] + else: + param = parameters_filtering["default"] + return param + + @staticmethod + def load_stopwords(lang_dataset_id): + stopwords_lang_id = langs_id.loc[ + langs_id["dataset_id"] == lang_dataset_id, "stopwords_id" + ].iloc[0] + if stopwords_lang_id: + stopwords_lang = set(stopwords[stopwords_lang_id]) + else: + stopwords_lang = None + return stopwords_lang + + @staticmethod + def load_badwords(lang_dataset_id): + badwords_lang_id = langs_id.loc[ + langs_id["dataset_id"] == lang_dataset_id, "badwords_id" + ].iloc[0] + if badwords_lang_id: + badwords_lang = set(badwords[badwords_lang_id]) + else: + badwords_lang = None + return badwords_lang + + @staticmethod + def load_model_lang_id(lang_dataset_id, path_fasttext_model): + fasttext_lang_id = langs_id.loc[ + langs_id["dataset_id"] == lang_dataset_id, "fasttext_id" + ].iloc[0] + if fasttext_lang_id: + model_lang_id = fasttext.load_model(path_fasttext_model) + else: + model_lang_id = None + return model_lang_id + + @staticmethod + def load_sentencepiece_model(lang_dataset_id, path_sentencepiece_model): + sentencepiece_lang_id = langs_id.loc[ + langs_id["dataset_id"] == lang_dataset_id, "sentencepiece_id" + ].iloc[0] + if sentencepiece_lang_id: + sentencepiece_model = sentencepiece.SentencePieceProcessor() + sentencepiece_model.load(path_sentencepiece_model) + else: + sentencepiece_model = None + return sentencepiece_model + + @staticmethod + def load_kenlm_model(lang_dataset_id, path_kenlm_model): + kenlm_lang_id = langs_id.loc[ + langs_id["dataset_id"] == lang_dataset_id, "kenlm_id" + ].iloc[0] + if kenlm_lang_id: + kenlm_model = kenlm.Model(path_kenlm_model) + else: + kenlm_model = None + return kenlm_model + + +class ModifyingDocuments: + @staticmethod + def remove_empty_el_from_list(list_): + return [el for el in list_ if el] + + @staticmethod + def remove_non_printing_characters(document, non_printing_characters_re): + return non_printing_characters_re.sub("", document) + + @staticmethod + def uniform_whitespace( + document, + whitespace=[ + " ", + " ", + " ", + " ", + " ", + "　", + " ", + " ", + " ", + " ", + "", + "„", + ], + ): + """There are different whitespace characters.""" + whitespace = set(whitespace) + document = "".join( + [char if char not in whitespace else " " for char in document] + ) + return document + + @staticmethod + def replace_digits_with_zeros(document, digits_re): + return digits_re.sub("0", document) + + @staticmethod + def replace_unicode_punctuation(document, unicode_punctuation): + return "".join(unicode_punctuation.get(c, c) for c in document) + + @staticmethod + def normalization( + document, + remove_non_printing_characters, + strip, + lower_case, + uniform_whitespace, + replace_digits_with_zeros, + replace_unicode_punctuation, + non_printing_characters_re=normalization["non_printing_characters_re"], + digits_re=normalization["digits_re"], + unicode_punctuation=normalization["unicode_punctuation"], + ): + if remove_non_printing_characters: + document = ModifyingDocuments.remove_non_printing_characters( + document, non_printing_characters_re + ) + if strip: + document = document.strip() + if not document: + return document + if lower_case: + document = document.lower() + if uniform_whitespace: + document = ModifyingDocuments.uniform_whitespace(document) + if replace_digits_with_zeros: + document = ModifyingDocuments.replace_digits_with_zeros(document, digits_re) + if replace_unicode_punctuation: + document = ModifyingDocuments.replace_unicode_punctuation( + document, unicode_punctuation + ) + return document + + @staticmethod + def tokenization(document, sentencepiece_model, join_on_whitespace): + document_tokenized = sentencepiece_model.encode_as_pieces(document) + if join_on_whitespace: + document_tokenized = " ".join(document_tokenized) + return document_tokenized + + @staticmethod + def split_on_whitespace( + document, + new_line=False, + tab=False, + ): + """This method also removes concatenated spaces.""" + sep = [" "] + new_line * ["\n"] + tab * ["\t"] + sep = "|".join(sep) + split_document = re.split(sep, document) + split_document = ModifyingDocuments.remove_empty_el_from_list(split_document) + return split_document + + @staticmethod + def strip(document, strip_characters): + """Way faster than document.strip(strip_characters) + since strip_characters is now a set instead of a str, + and it contains a lot of elements (all the emojis).""" + if not document: + return document + beg_ind = 0 + end_ind = len(document) + for i in range(len(document)): + if document[i] in strip_characters: + beg_ind += 1 + else: + break + for i in range(1, len(document) + 1): + if document[-i] in strip_characters: + end_ind -= 1 + else: + break + document_stripped = document[beg_ind:end_ind] + return document_stripped + + @staticmethod + def get_words_from_document( + document, sentencepiece_model_tok, lower_case, strip_characters + ): + """Get words from a document. Non reversible since the document + is split on multiple characters, words are stripped of + special characters and characters are converted to lower case. + Useful to compute ratios, like the stopwords ratio.""" + if sentencepiece_model_tok: + document_normalized = ModifyingDocuments.normalization( + document=document, + remove_non_printing_characters=True, + strip=True, + lower_case=True, + uniform_whitespace=True, + replace_digits_with_zeros=True, + replace_unicode_punctuation=True, + ) + words = ModifyingDocuments.tokenization( + document_normalized, sentencepiece_model_tok, join_on_whitespace=False + ) + else: + words = ModifyingDocuments.split_on_whitespace( + document, new_line=True, tab=True + ) + if lower_case: + words = [word.lower() for word in words] + if strip_characters: + words = [ModifyingDocuments.strip(word, strip_characters) for word in words] + words = ModifyingDocuments.remove_empty_el_from_list(words) + return words + + @staticmethod + def words_augmentation(words, group_size, join_char): + """Augment words, especially for Chinese (without a space between words) + and Vietnamese (with a space between syllables).""" + augmentation = [ + join_char.join(words[i : i + group_size]) + for i in range(len(words) - group_size + 1) + ] + return augmentation + + @staticmethod + def split_on_newline_tab_whitespace(document): + """First split on "\n", then on "\t", then on " ".""" + sentences = document.split("\n") + sentences = [sentence.split("\t") for sentence in sentences] + sentences = [ + [ + ModifyingDocuments.split_on_whitespace(subsentence) + for subsentence in sentence + ] + for sentence in sentences + ] + return sentences + + @staticmethod + def merge_on_whitespace_tab_newline(sentences): + """Invert the method split_on_newline_tab_whitespace. + Removes concatenated separators.""" + sentences = [ + [" ".join(subsentence) for subsentence in sentence if subsentence] + for sentence in sentences + ] + sentences = ["\t".join(sentence) for sentence in sentences if sentence] + if not sentences: + return "" + document = "\n".join(sentences) + return document + + @staticmethod + def should_keep_word_with_incorrect_substrings( + word, strip_characters, incorrect_word_substrings + ): + word = ModifyingDocuments.strip(word, strip_characters) + should_keep = all( + [(i_substr not in word) for i_substr in incorrect_word_substrings] + ) + return should_keep + + @staticmethod + def remove_words_with_incorrect_substrings( + document, + strip_characters, + incorrect_word_substrings, + ): + sentences = ModifyingDocuments.split_on_newline_tab_whitespace(document) + sentences = [ + [ + [ + word + for word in subsentence + if ModifyingDocuments.should_keep_word_with_incorrect_substrings( + word, strip_characters, incorrect_word_substrings + ) + ] + for subsentence in sentence + ] + for sentence in sentences + ] + document = ModifyingDocuments.merge_on_whitespace_tab_newline(sentences) + return document + + @staticmethod + def should_keep_long_word(word, strip_characters, length_word_max_cutoff): + """If the word is too long but it contains only one + special character, it might be a concatenation of one word, + a punctuation, and another word, with no space between them. + In this case, we give the word a pass.""" + if len(word) <= length_word_max_cutoff: + return True + word = ModifyingDocuments.strip(word, strip_characters) + if not word: # The word consisted only of strip characters + return False + if len(word) <= length_word_max_cutoff: + return True + return False + + def remove_long_words( + document, + strip_characters, + length_word_max_cutoff, + ): + sentences = ModifyingDocuments.split_on_newline_tab_whitespace(document) + sentences = [ + [ + [ + word + for word in subsentence + if ModifyingDocuments.should_keep_long_word( + word, + strip_characters, + length_word_max_cutoff, + ) + ] + for subsentence in sentence + ] + for sentence in sentences + ] + document = ModifyingDocuments.merge_on_whitespace_tab_newline(sentences) + return document + + @staticmethod + def modifying_documents( + document, + cond_uniform_whitespace, + cond_replace_unicode_punctuation, + cond_remove_words_with_incorrect_substrings, + strip_characters, + incorrect_word_substrings, + cond_remove_long_words, + length_word_max_cutoff, + ): + document = ModifyingDocuments.normalization( + document=document, + remove_non_printing_characters=False, + strip=True, + lower_case=False, + uniform_whitespace=cond_uniform_whitespace, + replace_digits_with_zeros=False, + replace_unicode_punctuation=cond_replace_unicode_punctuation, + ) + if cond_remove_words_with_incorrect_substrings: + document = ModifyingDocuments.remove_words_with_incorrect_substrings( + document, + strip_characters, + incorrect_word_substrings, + ) + if cond_remove_long_words: + document = ModifyingDocuments.remove_long_words( + document, + strip_characters, + length_word_max_cutoff, + ) + return document + + +class FunctionDatasetModifyingDocuments: + def __init__(self, lang_dataset_id): + self.lang_dataset_id = lang_dataset_id + self.param = LoadParameters.load_parameters(lang_dataset_id) + + def __call__(self, example): + example["text"] = ModifyingDocuments.modifying_documents( + document=example["text"], + cond_uniform_whitespace=self.param["cond_uniform_whitespace"], + cond_replace_unicode_punctuation=self.param[ + "cond_replace_unicode_punctuation" + ], + cond_remove_words_with_incorrect_substrings=self.param[ + "cond_remove_words_with_incorrect_substrings" + ], + strip_characters=self.param["strip_characters"], + incorrect_word_substrings=self.param["incorrect_word_substrings"], + cond_remove_long_words=self.param["cond_remove_long_words"], + length_word_max_cutoff=self.param["length_word_max_cutoff"], + ) + return example + + def __reduce__(self): + return (self.__class__, (self.lang_dataset_id,)) + + +class Filtering: + @staticmethod + def check_number_words( + document, + sentencepiece_model_tok, + strip_characters, + number_words_min_cutoff, + number_words_max_cutoff, + ): + words = ModifyingDocuments.get_words_from_document( + document, + sentencepiece_model_tok, + lower_case=False, + strip_characters=strip_characters, + ) + cond = (len(words) >= number_words_min_cutoff) and ( + len(words) <= number_words_max_cutoff + ) + return cond + + @staticmethod + def compute_repetitions_ratio(document, repetitions_length): + def get_freq_ngrams(document, n): + ngrams = [document[i : i + n] for i in range(len(document) - n + 1)] + freq_ngrams = {} + for ngram in ngrams: + freq_ngrams[ngram] = freq_ngrams.get(ngram, 0) + 1 + return freq_ngrams + + freq_ngrams = get_freq_ngrams(document, repetitions_length) + if len(freq_ngrams) == 0: + return 0 + freq_ngrams = list(freq_ngrams.values()) + freq_ngrams = sorted(freq_ngrams, reverse=True) + num_rep_ngrams = int(np.sqrt(len(freq_ngrams))) + repetitions_ratio = sum(freq_ngrams[:num_rep_ngrams]) / sum(freq_ngrams) + return repetitions_ratio + + @staticmethod + def check_repetitions_removal( + document, + repetitions_length, + repetitions_max_cutoff, + ): + repetitions_ratio = Filtering.compute_repetitions_ratio( + document, repetitions_length + ) + cond = repetitions_ratio <= repetitions_max_cutoff + return cond + + @staticmethod + def compute_special_characters_ratio(document, special_characters): + if len(document) == 0: + return 0 + special_characters_ratio = len( + [char for char in document if char in special_characters] + ) / len(document) + return special_characters_ratio + + @staticmethod + def check_special_characters( + document, + special_characters, + special_characters_max_cutoff, + ): + special_characters_ratio = Filtering.compute_special_characters_ratio( + document, special_characters + ) + cond = special_characters_ratio <= special_characters_max_cutoff + return cond + + @staticmethod + def compute_stopwords_ratio( + document, + sentencepiece_model_tok, + strip_characters, + cond_words_augmentation, + words_augmentation_group_sizes, + words_augmentation_join_char, + stopwords, + ): + words = ModifyingDocuments.get_words_from_document( + document, + sentencepiece_model_tok, + lower_case=True, + strip_characters=strip_characters, + ) + if not words: + return 0 + augmentation = [] + if cond_words_augmentation: + augmentation = [ + ModifyingDocuments.words_augmentation( + words, group_size, words_augmentation_join_char + ) + for group_size in words_augmentation_group_sizes + ] + augmentation = [word for augm in augmentation for word in augm] + stopwords_ratio = len( + [word for word in words + augmentation if word in stopwords] + ) / len(words) + if stopwords_ratio > 1.0: + stopwords_ratio = 1.0 + return stopwords_ratio + + @staticmethod + def check_stopwords( + document, + sentencepiece_model_tok, + strip_characters, + cond_words_augmentation, + words_augmentation_group_sizes, + words_augmentation_join_char, + stopwords, + stopwords_min_cutoff, + ): + cond = True + if stopwords: + stopwords_ratio = Filtering.compute_stopwords_ratio( + document, + sentencepiece_model_tok, + strip_characters, + cond_words_augmentation, + words_augmentation_group_sizes, + words_augmentation_join_char, + stopwords, + ) + cond = stopwords_ratio >= stopwords_min_cutoff + return cond + + @staticmethod + def compute_badwords_ratio( + document, + sentencepiece_model_tok, + strip_characters, + cond_words_augmentation, + words_augmentation_group_sizes, + words_augmentation_join_char, + badwords, + ): + words = ModifyingDocuments.get_words_from_document( + document, + sentencepiece_model_tok, + lower_case=True, + strip_characters=strip_characters, + ) + if not words: + return 0 + augmentation = [] + if cond_words_augmentation: + augmentation = [ + ModifyingDocuments.words_augmentation( + words, group_size, words_augmentation_join_char + ) + for group_size in words_augmentation_group_sizes + ] + augmentation = [word for augm in augmentation for word in augm] + badwords_ratio = len( + [word for word in words + augmentation if word in badwords] + ) / len(words) + if badwords_ratio > 1.0: + badwords_ratio = 1.0 + for word in augmentation: + if word in badwords: + print(word) + return badwords_ratio + + @staticmethod + def check_badwords( + document, + sentencepiece_model_tok, + strip_characters, + cond_words_augmentation, + words_augmentation_group_sizes, + words_augmentation_join_char, + badwords, + badwords_max_cutoff, + ): + cond = True + if badwords: + badwords_ratio = Filtering.compute_badwords_ratio( + document, + sentencepiece_model_tok, + strip_characters, + cond_words_augmentation, + words_augmentation_group_sizes, + words_augmentation_join_char, + badwords, + ) + cond = badwords_ratio <= badwords_max_cutoff + return cond + + @staticmethod + def compute_lang_id_pred_score(document, model_lang_id): + document = document.lower().replace("\n", " ") + pred = model_lang_id.predict(document) + lang_pred_fasttext_id = pred[0][0].replace("__label__", "") + score_pred = pred[1][0] + lang_pred_dataset_id = langs_id.loc[ + langs_id["fasttext_id"] == lang_pred_fasttext_id, "dataset_id" + ] + if len(lang_pred_dataset_id) > 0: + lang_pred_dataset_id = lang_pred_dataset_id.iloc[0] + else: + lang_pred_dataset_id = "unknown" + return lang_pred_dataset_id, score_pred + + @staticmethod + def check_lang_id( + document, + lang_dataset_id, + model_lang_id, + lang_id_min_cutoff, + ): + cond = True + if model_lang_id: + lang_pred_dataset_id, score_pred = Filtering.compute_lang_id_pred_score( + document, model_lang_id + ) + cond = (lang_pred_dataset_id == lang_dataset_id) and ( + score_pred >= lang_id_min_cutoff + ) + return cond + + @staticmethod + def compute_perplexity_score(document, sentencepiece_model, kenlm_model): + document = ModifyingDocuments.normalization( + document=document, + remove_non_printing_characters=True, + strip=True, + lower_case=True, + uniform_whitespace=True, + replace_digits_with_zeros=True, + replace_unicode_punctuation=True, + ) + document = ModifyingDocuments.tokenization( + document, sentencepiece_model, join_on_whitespace=True + ) + doc_log_score, doc_length = 0, 0 + for line in document.split("\n"): + log_score = kenlm_model.score(line) + length = len(line.split()) + 1 + doc_log_score += log_score + doc_length += length + pp_score = 10.0 ** (-doc_log_score / doc_length) + pp_score = round(pp_score, 1) + return pp_score + + @staticmethod + def check_perplexity( + document, + sentencepiece_model, + kenlm_model, + perplexity_max_cutoff, + ): + cond = True + if kenlm_model: + score = Filtering.compute_perplexity_score( + document, sentencepiece_model, kenlm_model + ) + cond = score <= perplexity_max_cutoff + return cond + + @staticmethod + def filtering( + document, + cond_check_number_words, + sentencepiece_model_tok, + strip_characters, + number_words_min_cutoff, + number_words_max_cutoff, + cond_check_repetitions_removal, + repetitions_length, + repetitions_max_cutoff, + cond_check_special_characters, + special_characters, + special_characters_max_cutoff, + cond_words_augmentation, + words_augmentation_group_sizes, + words_augmentation_join_char, + cond_check_stopwords, + stopwords, + stopwords_min_cutoff, + cond_check_badwords, + badwords, + badwords_max_cutoff, + cond_check_lang_id, + lang_dataset_id, + model_lang_id, + lang_id_min_cutoff, + cond_check_perplexity, + sentencepiece_model, + kenlm_model, + perplexity_max_cutoff, + ): + if cond_check_number_words: + if not Filtering.check_number_words( + document, + sentencepiece_model_tok, + strip_characters, + number_words_min_cutoff, + number_words_max_cutoff, + ): + return False + if cond_check_repetitions_removal: + if not Filtering.check_repetitions_removal( + document, + repetitions_length, + repetitions_max_cutoff, + ): + return False + if cond_check_special_characters: + if not Filtering.check_special_characters( + document, + special_characters, + special_characters_max_cutoff, + ): + return False + if cond_check_stopwords: + if not Filtering.check_stopwords( + document, + sentencepiece_model_tok, + strip_characters, + cond_words_augmentation, + words_augmentation_group_sizes, + words_augmentation_join_char, + stopwords, + stopwords_min_cutoff, + ): + return False + if cond_check_badwords: + if not Filtering.check_badwords( + document, + sentencepiece_model_tok, + strip_characters, + cond_words_augmentation, + words_augmentation_group_sizes, + words_augmentation_join_char, + badwords, + badwords_max_cutoff, + ): + return False + if cond_check_lang_id: + if not Filtering.check_lang_id( + document, + lang_dataset_id, + model_lang_id, + lang_id_min_cutoff, + ): + return False + if cond_check_perplexity: + if not Filtering.check_perplexity( + document, + sentencepiece_model, + kenlm_model, + perplexity_max_cutoff, + ): + return False + return True + + +class FunctionDatasetFiltering: + def __init__( + self, + lang_dataset_id, + path_fasttext_model, + path_sentencepiece_model, + path_kenlm_model, + ): + self.lang_dataset_id = lang_dataset_id + self.path_fasttext_model = path_fasttext_model + self.path_sentencepiece_model = path_sentencepiece_model + self.path_kenlm_model = path_kenlm_model + + self.param = LoadParameters.load_parameters(lang_dataset_id) + self.stopwords = LoadParameters.load_stopwords(lang_dataset_id) + self.badwords = LoadParameters.load_badwords(lang_dataset_id) + self.model_lang_id = LoadParameters.load_model_lang_id( + lang_dataset_id, path_fasttext_model + ) + self.sentencepiece_model = LoadParameters.load_sentencepiece_model( + lang_dataset_id, path_sentencepiece_model + ) + self.sentencepiece_model_tok = ( + self.sentencepiece_model if self.param["tokenization"] else None + ) + self.kenlm_model = LoadParameters.load_kenlm_model( + lang_dataset_id, path_kenlm_model + ) + + def __call__(self, example): + keep_example = Filtering.filtering( + document=example["text"], + cond_check_number_words=self.param["cond_check_number_words"], + sentencepiece_model_tok=self.sentencepiece_model_tok, + strip_characters=self.param["strip_characters"], + number_words_min_cutoff=self.param["number_words_min_cutoff"], + number_words_max_cutoff=self.param["number_words_max_cutoff"], + cond_check_repetitions_removal=self.param["check_repetitions_removal"], + repetitions_length=self.param["repetitions_length"], + repetitions_max_cutoff=self.param["repetitions_max_cutoff"], + cond_check_special_characters=self.param["cond_check_special_characters"], + special_characters=self.param["special_characters"], + special_characters_max_cutoff=self.param["special_characters_max_cutoff"], + cond_words_augmentation=self.param["cond_words_augmentation"], + words_augmentation_group_sizes=self.param["words_augmentation_group_sizes"], + words_augmentation_join_char=self.param["words_augmentation_join_char"], + cond_check_stopwords=self.param["cond_check_stopwords"], + stopwords=self.stopwords, + stopwords_min_cutoff=self.param["stopwords_min_cutoff"], + cond_check_badwords=self.param["cond_check_badwords"], + badwords=self.badwords, + badwords_max_cutoff=self.param["badwords_max_cutoff"], + cond_check_lang_id=self.param["cond_check_lang_id"], + lang_dataset_id=self.lang_dataset_id, + model_lang_id=self.model_lang_id, + lang_id_min_cutoff=self.param["lang_id_min_cutoff"], + cond_check_perplexity=self.param["cond_check_perplexity"], + sentencepiece_model=self.sentencepiece_model, + kenlm_model=self.kenlm_model, + perplexity_max_cutoff=self.param["perplexity_max_cutoff"], + ) + return keep_example + + def __reduce__(self): + return ( + self.__class__, + ( + self.lang_dataset_id, + self.path_fasttext_model, + self.path_sentencepiece_model, + self.path_kenlm_model, + ), + ) + + +class DatasetFiltering: + def __init__( + self, + dataset, + lang_dataset_id, + path_fasttext_model, + path_sentencepiece_model, + path_kenlm_model, + num_proc, + path_dir_save_dataset, + ): + self.ds = dataset + self.lang_dataset_id = lang_dataset_id + self.path_fasttext_model = path_fasttext_model + self.path_sentencepiece_model = path_sentencepiece_model + self.path_kenlm_model = path_kenlm_model + self.num_proc = num_proc + self.path_dir_save_dataset = path_dir_save_dataset + + def modifying_documents(self): + dataset_modifying_documents = FunctionDatasetModifyingDocuments( + self.lang_dataset_id + ) + self.ds = self.ds.map(dataset_modifying_documents, num_proc=self.num_proc) + + def filtering(self): + func_dataset_filtering = FunctionDatasetFiltering( + self.lang_dataset_id, + self.path_fasttext_model, + self.path_sentencepiece_model, + self.path_kenlm_model, + ) + self.ds = self.ds.filter(func_dataset_filtering, num_proc=self.num_proc) + + def save_dataset(self): + pathlib.Path(self.path_dir_save_dataset).mkdir(parents=True, exist_ok=True) + path_dir_save_dataset = pathlib.PurePath( + self.path_dir_save_dataset, self.lang_dataset_id + ) + pathlib.Path(path_dir_save_dataset).mkdir(parents=True, exist_ok=True) + self.ds.save_to_disk(path_dir_save_dataset) diff --git a/data_tooling/ac_dc/languages_id.py b/data_tooling/ac_dc/languages_id.py new file mode 100644 index 0000000..5b7747e --- /dev/null +++ b/data_tooling/ac_dc/languages_id.py @@ -0,0 +1,231 @@ +import pandas as pd + + +langs_id = [ + { + "lang": "Afrikaans", + "dataset_id": "af", + "stopwords_id": "af", + "badwords_id": None, + "fasttext_id": "af", + "sentencepiece_id": "af", + "kenlm_id": "af", + }, + { + "lang": "Arabic", + "dataset_id": "ar", + "stopwords_id": "ar", + "badwords_id": "ar", + "fasttext_id": "ar", + "sentencepiece_id": "ar", + "kenlm_id": "ar", + }, + { + "lang": "Egyptian Arabic", + "dataset_id": "arz", + "stopwords_id": None, + "badwords_id": None, + "fasttext_id": "arz", + "sentencepiece_id": None, + "kenlm_id": None, + }, + { + "lang": "Assamese", + "dataset_id": "as", + "stopwords_id": None, + "badwords_id": None, + "fasttext_id": "as", + "sentencepiece_id": None, + "kenlm_id": None, + }, + { + "lang": "Bengali", + "dataset_id": "bn", + "stopwords_id": "bn", + "badwords_id": None, + "fasttext_id": "bn", + "sentencepiece_id": "bn", + "kenlm_id": "bn", + }, + { + "lang": "Catalan", + "dataset_id": "ca", + "stopwords_id": "ca", + "badwords_id": "ca", + "fasttext_id": "ca", + "sentencepiece_id": "ca", + "kenlm_id": "ca", + }, + { + "lang": "English", + "dataset_id": "en", + "stopwords_id": "en", + "badwords_id": "en", + "fasttext_id": "en", + "sentencepiece_id": "en", + "kenlm_id": "en", + }, + { + "lang": "Spanish", + "dataset_id": "es", + "stopwords_id": "es", + "badwords_id": "es", + "fasttext_id": "es", + "sentencepiece_id": "es", + "kenlm_id": "es", + }, + { + "lang": "Basque", + "dataset_id": "eu", + "stopwords_id": "eu", + "badwords_id": "eu", + "fasttext_id": "eu", + "sentencepiece_id": None, + "kenlm_id": None, + }, + { + "lang": "French", + "dataset_id": "fr", + "stopwords_id": "fr", + "badwords_id": "fr", + "fasttext_id": "fr", + "sentencepiece_id": "fr", + "kenlm_id": "fr", + }, + { + "lang": "Gujarati", + "dataset_id": "gu", + "stopwords_id": None, + "badwords_id": None, + "fasttext_id": "gu", + "sentencepiece_id": "gu", + "kenlm_id": "gu", + }, + { + "lang": "Hindi", + "dataset_id": "hi", + "stopwords_id": "hi", + "badwords_id": "hi", + "fasttext_id": "hi", + "sentencepiece_id": "hi", + "kenlm_id": "hi", + }, + { + "lang": "Indonesian", + "dataset_id": "id", + "stopwords_id": "id", + "badwords_id": "id", + "fasttext_id": "id", + "sentencepiece_id": "id", + "kenlm_id": "id", + }, + { + "lang": "Kannada", + "dataset_id": "kn", + "stopwords_id": None, + "badwords_id": "kn", + "fasttext_id": "kn", + "sentencepiece_id": "kn", + "kenlm_id": "kn", + }, + { + "lang": "Malayalam", + "dataset_id": "ml", + "stopwords_id": None, + "badwords_id": "ml", + "fasttext_id": "ml", + "sentencepiece_id": "ml", + "kenlm_id": "ml", + }, + { + "lang": "Marathi", + "dataset_id": "mr", + "stopwords_id": "mr", + "badwords_id": "mr", + "fasttext_id": "mr", + "sentencepiece_id": "mr", + "kenlm_id": "mr", + }, + { + "lang": "Portuguese", + "dataset_id": "pt", + "stopwords_id": "pt", + "badwords_id": "pt", + "fasttext_id": "pt", + "sentencepiece_id": "pt", + "kenlm_id": "pt", + }, + { + "lang": "Somali", + "dataset_id": "so", + "stopwords_id": "so", + "badwords_id": None, + "fasttext_id": "so", + "sentencepiece_id": None, + "kenlm_id": None, + }, + { + "lang": "Swahili", + "dataset_id": "sw", + "stopwords_id": "sw", + "badwords_id": None, + "fasttext_id": "sw", + "sentencepiece_id": None, + "kenlm_id": None, + }, + { + "lang": "Tamil", + "dataset_id": "ta", + "stopwords_id": None, + "badwords_id": None, + "fasttext_id": "ta", + "sentencepiece_id": None, + "kenlm_id": None, + }, + { + "lang": "Telugu", + "dataset_id": "te", + "stopwords_id": None, + "badwords_id": "te", + "fasttext_id": "te", + "sentencepiece_id": None, + "kenlm_id": None, + }, + { + "lang": "Urdu", + "dataset_id": "ur", + "stopwords_id": "ur", + "badwords_id": None, + "fasttext_id": "ur", + "sentencepiece_id": None, + "kenlm_id": None, + }, + { + "lang": "Vietnamese", + "dataset_id": "vi", + "stopwords_id": "vi", + "badwords_id": "vi", + "fasttext_id": "vi", + "sentencepiece_id": None, + "kenlm_id": None, + }, + { + "lang": "Yoruba", + "dataset_id": "yo", + "stopwords_id": "yo", + "badwords_id": None, + "fasttext_id": "yo", + "sentencepiece_id": None, + "kenlm_id": None, + }, + { + "lang": "Chinese", + "dataset_id": "zh", + "stopwords_id": "zh", + "badwords_id": "zh", + "fasttext_id": "zh", + "sentencepiece_id": "zh", + "kenlm_id": "zh", + }, +] +langs_id = pd.DataFrame(langs_id) diff --git a/data_tooling/ac_dc/main_filtering.py b/data_tooling/ac_dc/main_filtering.py new file mode 100644 index 0000000..c7eab61 --- /dev/null +++ b/data_tooling/ac_dc/main_filtering.py @@ -0,0 +1,136 @@ +"""Filtering.""" + +from multiprocessing import cpu_count + +import argparse + +from datasets import load_dataset + +from filtering import DatasetFiltering + + +def check_num_proc(num_proc: int = -1) -> int: + """ + Check the number of processors. Return a safe-checked value. + + Parameters + ---------- + num_proc : int, optional + Number of processors to use, by default -1 + + Returns + ------- + int + Number of processors to use + + Raises + ------ + ValueError + If the input exceeds the number of processors available + """ + maximum: int = cpu_count() + if num_proc > maximum: + raise ValueError( + f"{num_proc} exceeds the maximum number ({maximum}) of processors" + ) + + if num_proc == -1: + num_proc = maximum + else: + print(f"Using {num_proc} processors out of {maximum} can be slow") + + return num_proc + + +def parseArgs(): + parser = argparse.ArgumentParser(description="Filtering.") + parser.add_argument( + "--dataset_name", + type=str, + default="oscar", + help="Name of the dataset to load.", + ) + parser.add_argument( + "--config_name", + type=str, + default="unshuffled_deduplicated_af", + help="Name of the dataset config to pass.", + ) + parser.add_argument( + "--data_files", + type=str, + default=None, + help="'load_dataset' returns all files that match the Unix style pattern passed by 'data_files'", + ) + parser.add_argument( + "--split", + type=str, + default="train", + help="Split of the dataset to consider.", + ) + parser.add_argument( + "--lang_dataset_id", + type=str, + default="af", + help="ID of the language in which the dataset is written.", + ) + parser.add_argument( + "--path_fasttext_model", + type=str, + default="ac_dc/lid.176.bin", + help="Path to the Fasttext model used for language identification.", + ) + parser.add_argument( + "--path_sentencepiece_model", + type=str, + default="ac_dc/af.sp.model", + help="Path to the Sentence Piece model used to tokenize text for perplexity scores.", + ) + parser.add_argument( + "--path_kenlm_model", + type=str, + default="ac_dc/af.arpa.bin", + help="Path to the KenLM model used to compute perplexity scores.", + ) + parser.add_argument( + "--num_proc", + type=int, + default=-1, + help="Number of processes for multiprocessing. Default at the number of processors available.", + ) + parser.add_argument( + "--path_dir_save_dataset", + type=str, + default="../dataset_filtered/", + help="Path to the directory where the filtered version of the dataset will be saved.", + ) + args = parser.parse_args() + return args + + +def main(): + args = parseArgs() + + dataset = load_dataset( + args.dataset_name, + args.config_name, + data_files=args.data_files, + split=args.split, + ) + + dataset_filtering = DatasetFiltering( + dataset=dataset, + lang_dataset_id=args.lang_dataset_id, + path_fasttext_model=args.path_fasttext_model, + path_sentencepiece_model=args.path_sentencepiece_model, + path_kenlm_model=args.path_kenlm_model, + num_proc=check_num_proc(args.num_proc), + path_dir_save_dataset=args.path_dir_save_dataset, + ) + dataset_filtering.modifying_documents() + dataset_filtering.filtering() + dataset_filtering.save_dataset() + + +if __name__ == "__main__": + main() diff --git a/data_tooling/ac_dc/normalization.py b/data_tooling/ac_dc/normalization.py new file mode 100644 index 0000000..652e810 --- /dev/null +++ b/data_tooling/ac_dc/normalization.py @@ -0,0 +1,52 @@ +import re +from typing import Dict + + +non_printing_characters_re = re.compile( + f"[{''.join(map(chr, list(range(0,32)) + list(range(127,160))))}]" +) + +digits_re: re.Pattern = re.compile(r"\d") + +unicode_punctuation: Dict[str, str] = { + "，": ",", + "。": ".", + "、": ",", + "„": '"', + "”": '"', + "“": '"', + "«": '"', + "»": '"', + "１": '"', + "」": '"', + "「": '"', + "《": '"', + "》": '"', + "´": "'", + "∶": ":", + "：": ":", + "？": "?", + "！": "!", + "（": "(", + "）": ")", + "；": ";", + "–": "-", + "—": " - ", + "．": ". ", + "～": "~", + "’": "'", + "…": "...", + "━": "-", + "〈": "<", + "〉": ">", + "【": "[", + "】": "]", + "％": "%", + "►": "-", +} + +normalization = { + "non_printing_characters_re": non_printing_characters_re, + "digits_re": digits_re, + "unicode_punctuation": unicode_punctuation, +} diff --git a/data_tooling/ac_dc/parameters_filtering.py b/data_tooling/ac_dc/parameters_filtering.py new file mode 100644 index 0000000..a1c7b60 --- /dev/null +++ b/data_tooling/ac_dc/parameters_filtering.py @@ -0,0 +1,852 @@ +import string +import emoji + + +main_special_characters = string.punctuation + string.digits + string.whitespace +other_special_characters = ( + "’ “— ™ – •‘œ　   ˜ ‚ƒ„’“”–ー一▬…✦�­£​•€«»°·═" + "×士＾˘⇓↓↑←→（）§″′´¿−±∈¢ø‚„½¼¾¹²³―⁃，ˌ¸‹›ʺˈʻ¦‐⠀‰……‑≤≥‖" + "◆●■►▼▲▴∆▻¡★☆✱ːº。¯˜¥ɪ≈†上ン：∼⁄・♡✓⊕․．⋅÷１‟；،、¨ाাी्े◦˚" + "゜ʼ≖ʼ¤ッツシ℃√！【】‿∞➤～πه۩☛₨➩☻๑٪♥ıॽ《‘©﴿٬？▷Г♫∟™ª₪®「—❖" + "」﴾》" +) +emoji = list(emoji.UNICODE_EMOJI["en"].keys()) + +special_characters_default = set(main_special_characters + other_special_characters) +special_characters_default.update(emoji) + + +parameters_filtering_default = { + "cond_uniform_whitespace": True, + "cond_replace_unicode_punctuation": False, + "cond_remove_words_with_incorrect_substrings": False, + "incorrect_word_substrings": ["http", "www", ".com", "href", "//"], + "cond_remove_long_words": False, + "length_word_max_cutoff": 50, + "cond_check_number_words": True, + "tokenization": False, + "strip_characters": special_characters_default, + "number_words_min_cutoff": 1, + "number_words_max_cutoff": 100000, + "check_repetitions_removal": True, + "repetitions_length": 10, + "repetitions_max_cutoff": 0.106, + "cond_check_special_characters": True, + "special_characters": special_characters_default, + "special_characters_max_cutoff": 0.4, + "cond_words_augmentation": False, + "words_augmentation_group_sizes": [], + "words_augmentation_join_char": "", + "cond_check_stopwords": False, + "stopwords_min_cutoff": 0, + "cond_check_badwords": False, + "badwords_max_cutoff": 0.2, + "cond_check_lang_id": True, + "lang_id_min_cutoff": 0.70, + "cond_check_perplexity": False, + "perplexity_max_cutoff": 3000000, +} + +parameters_filtering_af = { + "cond_uniform_whitespace": True, + "cond_replace_unicode_punctuation": False, + "cond_remove_words_with_incorrect_substrings": False, + "incorrect_word_substrings": ["http", "www", ".com", "href", "//"], + "cond_remove_long_words": True, + "length_word_max_cutoff": 25, + "cond_check_number_words": True, + "tokenization": False, + "strip_characters": special_characters_default, + "number_words_min_cutoff": 1, + "number_words_max_cutoff": 100000, + "check_repetitions_removal": True, + "repetitions_length": 10, + "repetitions_max_cutoff": 0.106, + "cond_check_special_characters": True, + "special_characters": special_characters_default, + "special_characters_max_cutoff": 0.3, + "cond_words_augmentation": False, + "words_augmentation_group_sizes": [], + "words_augmentation_join_char": "", + "cond_check_stopwords": True, + "stopwords_min_cutoff": 0, + "cond_check_badwords": False, + "badwords_max_cutoff": 0.2, + "cond_check_lang_id": True, + "lang_id_min_cutoff": 0.6, + "cond_check_perplexity": True, + "perplexity_max_cutoff": 3000000, +} + +parameters_filtering_ar = { + "cond_uniform_whitespace": True, + "cond_replace_unicode_punctuation": False, + "cond_remove_words_with_incorrect_substrings": False, + "incorrect_word_substrings": ["http", "www", ".com", "href", "//"], + "cond_remove_long_words": True, + "length_word_max_cutoff": 25, + "cond_check_number_words": True, + "tokenization": False, + "strip_characters": special_characters_default, + "number_words_min_cutoff": 1, + "number_words_max_cutoff": 100000, + "check_repetitions_removal": True, + "repetitions_length": 10, + "repetitions_max_cutoff": 0.106, + "cond_check_special_characters": True, + "special_characters": special_characters_default, + "special_characters_max_cutoff": 0.45, + "cond_words_augmentation": False, + "words_augmentation_group_sizes": [], + "words_augmentation_join_char": "", + "cond_check_stopwords": True, + "stopwords_min_cutoff": 0, + "cond_check_badwords": False, + "badwords_max_cutoff": 0.2, + "cond_check_lang_id": True, + "lang_id_min_cutoff": 0.75, + "cond_check_perplexity": True, + "perplexity_max_cutoff": 1000000, +} + +parameters_filtering_arz = { + "cond_uniform_whitespace": True, + "cond_replace_unicode_punctuation": False, + "cond_remove_words_with_incorrect_substrings": False, + "incorrect_word_substrings": ["http", "www", ".com", "href", "//"], + "cond_remove_long_words": True, + "length_word_max_cutoff": 25, + "cond_check_number_words": True, + "tokenization": False, + "strip_characters": special_characters_default, + "number_words_min_cutoff": 1, + "number_words_max_cutoff": 100000, + "check_repetitions_removal": True, + "repetitions_length": 10, + "repetitions_max_cutoff": 0.106, + "cond_check_special_characters": True, + "special_characters": special_characters_default, + "special_characters_max_cutoff": 0.5, + "cond_words_augmentation": False, + "words_augmentation_group_sizes": [], + "words_augmentation_join_char": "", + "cond_check_stopwords": True, + "stopwords_min_cutoff": 0, + "cond_check_badwords": False, + "badwords_max_cutoff": 0.2, + "cond_check_lang_id": True, + "lang_id_min_cutoff": 0.75, + "cond_check_perplexity": False, + "perplexity_max_cutoff": 3000000, +} + +parameters_filtering_as = { + "cond_uniform_whitespace": True, + "cond_replace_unicode_punctuation": False, + "cond_remove_words_with_incorrect_substrings": False, + "incorrect_word_substrings": ["http", "www", ".com", "href", "//"], + "cond_remove_long_words": True, + "length_word_max_cutoff": 25, + "cond_check_number_words": True, + "tokenization": False, + "strip_characters": special_characters_default, + "number_words_min_cutoff": 1, + "number_words_max_cutoff": 100000, + "check_repetitions_removal": True, + "repetitions_length": 10, + "repetitions_max_cutoff": 0.106, + "cond_check_special_characters": True, + "special_characters": special_characters_default, + "special_characters_max_cutoff": 0.25, + "cond_words_augmentation": False, + "words_augmentation_group_sizes": [], + "words_augmentation_join_char": "", + "cond_check_stopwords": True, + "stopwords_min_cutoff": 0, + "cond_check_badwords": False, + "badwords_max_cutoff": 0.2, + "cond_check_lang_id": True, + "lang_id_min_cutoff": 0.75, + "cond_check_perplexity": False, + "perplexity_max_cutoff": 3000000, +} + +parameters_filtering_bn = { + "cond_uniform_whitespace": True, + "cond_replace_unicode_punctuation": False, + "cond_remove_words_with_incorrect_substrings": False, + "incorrect_word_substrings": ["http", "www", ".com", "href", "//"], + "cond_remove_long_words": True, + "length_word_max_cutoff": 30, + "cond_check_number_words": True, + "tokenization": False, + "strip_characters": special_characters_default, + "number_words_min_cutoff": 1, + "number_words_max_cutoff": 100000, + "check_repetitions_removal": True, + "repetitions_length": 10, + "repetitions_max_cutoff": 0.106, + "cond_check_special_characters": True, + "special_characters": special_characters_default, + "special_characters_max_cutoff": 0.275, + "cond_words_augmentation": False, + "words_augmentation_group_sizes": [], + "words_augmentation_join_char": "", + "cond_check_stopwords": True, + "stopwords_min_cutoff": 0.05, + "cond_check_badwords": False, + "badwords_max_cutoff": 0.2, + "cond_check_lang_id": True, + "lang_id_min_cutoff": 0.75, + "cond_check_perplexity": False, + "perplexity_max_cutoff": 575000, +} + +parameters_filtering_ca = { + "cond_uniform_whitespace": True, + "cond_replace_unicode_punctuation": False, + "cond_remove_words_with_incorrect_substrings": False, + "incorrect_word_substrings": ["http", "www", ".com", "href", "//"], + "cond_remove_long_words": True, + "length_word_max_cutoff": 30, + "cond_check_number_words": True, + "tokenization": False, + "strip_characters": special_characters_default, + "number_words_min_cutoff": 1, + "number_words_max_cutoff": 100000, + "check_repetitions_removal": True, + "repetitions_length": 10, + "repetitions_max_cutoff": 0.106, + "cond_check_special_characters": True, + "special_characters": special_characters_default, + "special_characters_max_cutoff": 0.35, + "cond_words_augmentation": False, + "words_augmentation_group_sizes": [], + "words_augmentation_join_char": "", + "cond_check_stopwords": True, + "stopwords_min_cutoff": 0, + "cond_check_badwords": False, + "badwords_max_cutoff": 0.2, + "cond_check_lang_id": True, + "lang_id_min_cutoff": 0.75, + "cond_check_perplexity": True, + "perplexity_max_cutoff": 1750000, +} + +parameters_filtering_en = { + "cond_uniform_whitespace": True, + "cond_replace_unicode_punctuation": False, + "cond_remove_words_with_incorrect_substrings": True, + "incorrect_word_substrings": ["http", "www", ".com", "href", "//"], + "cond_remove_long_words": True, + "length_word_max_cutoff": 25, + "cond_check_number_words": True, + "tokenization": False, + "strip_characters": special_characters_default, + "number_words_min_cutoff": 20, + "number_words_max_cutoff": 100000, + "check_repetitions_removal": True, + "repetitions_length": 10, + "repetitions_max_cutoff": 0.106, + "cond_check_special_characters": True, + "special_characters": special_characters_default, + "special_characters_max_cutoff": 0.4, + "cond_words_augmentation": False, + "words_augmentation_group_sizes": [], + "words_augmentation_join_char": "", + "cond_check_stopwords": True, + "stopwords_min_cutoff": 0.3, + "cond_check_badwords": True, + "badwords_max_cutoff": 0.045, + "cond_check_lang_id": True, + "lang_id_min_cutoff": 0.80, + "cond_check_perplexity": True, + "perplexity_max_cutoff": 2500, +} + +parameters_filtering_es = { + "cond_uniform_whitespace": True, + "cond_replace_unicode_punctuation": False, + "cond_remove_words_with_incorrect_substrings": False, + "incorrect_word_substrings": ["http", "www", ".com", "href", "//"], + "cond_remove_long_words": True, + "length_word_max_cutoff": 30, + "cond_check_number_words": True, + "tokenization": False, + "strip_characters": special_characters_default, + "number_words_min_cutoff": 1, + "number_words_max_cutoff": 100000, + "check_repetitions_removal": True, + "repetitions_length": 10, + "repetitions_max_cutoff": 0.106, + "cond_check_special_characters": True, + "special_characters": special_characters_default, + "special_characters_max_cutoff": 0.3, + "cond_words_augmentation": False, + "words_augmentation_group_sizes": [], + "words_augmentation_join_char": "", + "cond_check_stopwords": True, + "stopwords_min_cutoff": 0.2, + "cond_check_badwords": False, + "badwords_max_cutoff": 0.2, + "cond_check_lang_id": True, + "lang_id_min_cutoff": 0.75, + "cond_check_perplexity": True, + "perplexity_max_cutoff": 2500000, +} + +parameters_filtering_eu = { + "cond_uniform_whitespace": True, + "cond_replace_unicode_punctuation": False, + "cond_remove_words_with_incorrect_substrings": False, + "incorrect_word_substrings": ["http", "www", ".com", "href", "//"], + "cond_remove_long_words": True, + "length_word_max_cutoff": 35, + "cond_check_number_words": True, + "tokenization": False, + "strip_characters": special_characters_default, + "number_words_min_cutoff": 1, + "number_words_max_cutoff": 100000, + "check_repetitions_removal": True, + "repetitions_length": 10, + "repetitions_max_cutoff": 0.106, + "cond_check_special_characters": True, + "special_characters": special_characters_default, + "special_characters_max_cutoff": 0.3, + "cond_words_augmentation": False, + "words_augmentation_group_sizes": [], + "words_augmentation_join_char": "", + "cond_check_stopwords": True, + "stopwords_min_cutoff": 0, + "cond_check_badwords": False, + "badwords_max_cutoff": 0.2, + "cond_check_lang_id": True, + "lang_id_min_cutoff": 0.75, + "cond_check_perplexity": False, + "perplexity_max_cutoff": 3000000, +} + +parameters_filtering_fr = { + "cond_uniform_whitespace": True, + "cond_replace_unicode_punctuation": False, + "cond_remove_words_with_incorrect_substrings": False, + "incorrect_word_substrings": ["http", "www", ".com", "href", "//"], + "cond_remove_long_words": True, + "length_word_max_cutoff": 30, + "cond_check_number_words": True, + "tokenization": False, + "strip_characters": special_characters_default, + "number_words_min_cutoff": 1, + "number_words_max_cutoff": 100000, + "check_repetitions_removal": True, + "repetitions_length": 10, + "repetitions_max_cutoff": 0.106, + "cond_check_special_characters": True, + "special_characters": special_characters_default, + "special_characters_max_cutoff": 0.35, + "cond_words_augmentation": False, + "words_augmentation_group_sizes": [], + "words_augmentation_join_char": "", + "cond_check_stopwords": True, + "stopwords_min_cutoff": 0.15, + "cond_check_badwords": False, + "badwords_max_cutoff": 0.2, + "cond_check_lang_id": True, + "lang_id_min_cutoff": 0.75, + "cond_check_perplexity": True, + "perplexity_max_cutoff": 3000000, +} + +parameters_filtering_gu = { + "cond_uniform_whitespace": True, + "cond_replace_unicode_punctuation": False, + "cond_remove_words_with_incorrect_substrings": False, + "incorrect_word_substrings": ["http", "www", ".com", "href", "//"], + "cond_remove_long_words": True, + "length_word_max_cutoff": 30, + "cond_check_number_words": True, + "tokenization": False, + "strip_characters": special_characters_default, + "number_words_min_cutoff": 1, + "number_words_max_cutoff": 100000, + "check_repetitions_removal": True, + "repetitions_length": 10, + "repetitions_max_cutoff": 0.106, + "cond_check_special_characters": True, + "special_characters": special_characters_default, + "special_characters_max_cutoff": 0.3, + "cond_words_augmentation": False, + "words_augmentation_group_sizes": [], + "words_augmentation_join_char": "", + "cond_check_stopwords": True, + "stopwords_min_cutoff": 0, + "cond_check_badwords": False, + "badwords_max_cutoff": 0.2, + "cond_check_lang_id": True, + "lang_id_min_cutoff": 0.75, + "cond_check_perplexity": True, + "perplexity_max_cutoff": 250000, +} + +parameters_filtering_hi = { + "cond_uniform_whitespace": True, + "cond_replace_unicode_punctuation": False, + "cond_remove_words_with_incorrect_substrings": False, + "incorrect_word_substrings": ["http", "www", ".com", "href", "//"], + "cond_remove_long_words": True, + "length_word_max_cutoff": 25, + "cond_check_number_words": True, + "tokenization": False, + "strip_characters": special_characters_default, + "number_words_min_cutoff": 1, + "number_words_max_cutoff": 100000, + "check_repetitions_removal": True, + "repetitions_length": 10, + "repetitions_max_cutoff": 0.106, + "cond_check_special_characters": True, + "special_characters": special_characters_default, + "special_characters_max_cutoff": 0.35, + "cond_words_augmentation": False, + "words_augmentation_group_sizes": [], + "words_augmentation_join_char": "", + "cond_check_stopwords": True, + "stopwords_min_cutoff": 0, + "cond_check_badwords": False, + "badwords_max_cutoff": 0.2, + "cond_check_lang_id": True, + "lang_id_min_cutoff": 0.75, + "cond_check_perplexity": True, + "perplexity_max_cutoff": 600000, +} + +parameters_filtering_id = { + "cond_uniform_whitespace": True, + "cond_replace_unicode_punctuation": False, + "cond_remove_words_with_incorrect_substrings": False, + "incorrect_word_substrings": ["http", "www", ".com", "href", "//"], + "cond_remove_long_words": True, + "length_word_max_cutoff": 30, + "cond_check_number_words": True, + "tokenization": False, + "strip_characters": special_characters_default, + "number_words_min_cutoff": 1, + "number_words_max_cutoff": 100000, + "check_repetitions_removal": True, + "repetitions_length": 10, + "repetitions_max_cutoff": 0.106, + "cond_check_special_characters": True, + "special_characters": special_characters_default, + "special_characters_max_cutoff": 0.25, + "cond_words_augmentation": False, + "words_augmentation_group_sizes": [], + "words_augmentation_join_char": "", + "cond_check_stopwords": True, + "stopwords_min_cutoff": 0.25, + "cond_check_badwords": False, + "badwords_max_cutoff": 0.2, + "cond_check_lang_id": True, + "lang_id_min_cutoff": 0.75, + "cond_check_perplexity": True, + "perplexity_max_cutoff": 2500000, +} + +parameters_filtering_kn = { + "cond_uniform_whitespace": True, + "cond_replace_unicode_punctuation": False, + "cond_remove_words_with_incorrect_substrings": False, + "incorrect_word_substrings": ["http", "www", ".com", "href", "//"], + "cond_remove_long_words": True, + "length_word_max_cutoff": 50, + "cond_check_number_words": True, + "tokenization": False, + "strip_characters": special_characters_default, + "number_words_min_cutoff": 1, + "number_words_max_cutoff": 100000, + "check_repetitions_removal": True, + "repetitions_length": 10, + "repetitions_max_cutoff": 0.106, + "cond_check_special_characters": True, + "special_characters": special_characters_default, + "special_characters_max_cutoff": 0.25, + "cond_words_augmentation": False, + "words_augmentation_group_sizes": [], + "words_augmentation_join_char": "", + "cond_check_stopwords": True, + "stopwords_min_cutoff": 0, + "cond_check_badwords": False, + "badwords_max_cutoff": 0.2, + "cond_check_lang_id": True, + "lang_id_min_cutoff": 0.75, + "cond_check_perplexity": True, + "perplexity_max_cutoff": 400000, +} + +parameters_filtering_ml = { + "cond_uniform_whitespace": True, + "cond_replace_unicode_punctuation": False, + "cond_remove_words_with_incorrect_substrings": False, + "incorrect_word_substrings": ["http", "www", ".com", "href", "//"], + "cond_remove_long_words": True, + "length_word_max_cutoff": 50, + "cond_check_number_words": True, + "tokenization": False, + "strip_characters": special_characters_default, + "number_words_min_cutoff": 1, + "number_words_max_cutoff": 100000, + "check_repetitions_removal": True, + "repetitions_length": 10, + "repetitions_max_cutoff": 0.106, + "cond_check_special_characters": True, + "special_characters": special_characters_default, + "special_characters_max_cutoff": 0.2, + "cond_words_augmentation": False, + "words_augmentation_group_sizes": [], + "words_augmentation_join_char": "", + "cond_check_stopwords": True, + "stopwords_min_cutoff": 0, + "cond_check_badwords": False, + "badwords_max_cutoff": 0.2, + "cond_check_lang_id": True, + "lang_id_min_cutoff": 0.75, + "cond_check_perplexity": True, + "perplexity_max_cutoff": 1600000, +} + +parameters_filtering_mr = { + "cond_uniform_whitespace": True, + "cond_replace_unicode_punctuation": False, + "cond_remove_words_with_incorrect_substrings": False, + "incorrect_word_substrings": ["http", "www", ".com", "href", "//"], + "cond_remove_long_words": True, + "length_word_max_cutoff": 30, + "cond_check_number_words": True, + "tokenization": False, + "strip_characters": special_characters_default, + "number_words_min_cutoff": 1, + "number_words_max_cutoff": 100000, + "check_repetitions_removal": True, + "repetitions_length": 10, + "repetitions_max_cutoff": 0.106, + "cond_check_special_characters": True, + "special_characters": special_characters_default, + "special_characters_max_cutoff": 0.25, + "cond_words_augmentation": False, + "words_augmentation_group_sizes": [], + "words_augmentation_join_char": "", + "cond_check_stopwords": True, + "stopwords_min_cutoff": 0, + "cond_check_badwords": False, + "badwords_max_cutoff": 0.2, + "cond_check_lang_id": True, + "lang_id_min_cutoff": 0.75, + "cond_check_perplexity": True, + "perplexity_max_cutoff": 425000, +} + +parameters_filtering_pt = { + "cond_uniform_whitespace": True, + "cond_replace_unicode_punctuation": False, + "cond_remove_words_with_incorrect_substrings": False, + "incorrect_word_substrings": ["http", "www", ".com", "href", "//"], + "cond_remove_long_words": True, + "length_word_max_cutoff": 30, + "cond_check_number_words": True, + "tokenization": False, + "strip_characters": special_characters_default, + "number_words_min_cutoff": 1, + "number_words_max_cutoff": 100000, + "check_repetitions_removal": True, + "repetitions_length": 10, + "repetitions_max_cutoff": 0.106, + "cond_check_special_characters": True, + "special_characters": special_characters_default, + "special_characters_max_cutoff": 0.3, + "cond_words_augmentation": False, + "words_augmentation_group_sizes": [], + "words_augmentation_join_char": "", + "cond_check_stopwords": True, + "stopwords_min_cutoff": 0.15, + "cond_check_badwords": False, + "badwords_max_cutoff": 0.2, + "cond_check_lang_id": True, + "lang_id_min_cutoff": 0.75, + "cond_check_perplexity": True, + "perplexity_max_cutoff": 3000000, +} + +parameters_filtering_so = { + "cond_uniform_whitespace": True, + "cond_replace_unicode_punctuation": False, + "cond_remove_words_with_incorrect_substrings": False, + "incorrect_word_substrings": ["http", "www", ".com", "href", "//"], + "cond_remove_long_words": False, + "length_word_max_cutoff": 1000, + "cond_check_number_words": True, + "tokenization": False, + "strip_characters": special_characters_default, + "number_words_min_cutoff": 1, + "number_words_max_cutoff": 100000, + "check_repetitions_removal": True, + "repetitions_length": 10, + "repetitions_max_cutoff": 0.106, + "cond_check_special_characters": True, + "special_characters": special_characters_default, + "special_characters_max_cutoff": 0.3, + "cond_words_augmentation": False, + "words_augmentation_group_sizes": [], + "words_augmentation_join_char": "", + "cond_check_stopwords": False, + "stopwords_min_cutoff": 0, + "cond_check_badwords": False, + "badwords_max_cutoff": 0.2, + "cond_check_lang_id": True, + "lang_id_min_cutoff": 0.75, + "cond_check_perplexity": False, + "perplexity_max_cutoff": 3000000, +} + +parameters_filtering_sw = { + "cond_uniform_whitespace": True, + "cond_replace_unicode_punctuation": False, + "cond_remove_words_with_incorrect_substrings": False, + "incorrect_word_substrings": ["http", "www", ".com", "href", "//"], + "cond_remove_long_words": True, + "length_word_max_cutoff": 30, + "cond_check_number_words": True, + "tokenization": False, + "strip_characters": special_characters_default, + "number_words_min_cutoff": 1, + "number_words_max_cutoff": 100000, + "check_repetitions_removal": True, + "repetitions_length": 10, + "repetitions_max_cutoff": 0.106, + "cond_check_special_characters": True, + "special_characters": special_characters_default, + "special_characters_max_cutoff": 0.275, + "cond_words_augmentation": False, + "words_augmentation_group_sizes": [], + "words_augmentation_join_char": "", + "cond_check_stopwords": True, + "stopwords_min_cutoff": 0, + "cond_check_badwords": False, + "badwords_max_cutoff": 0.2, + "cond_check_lang_id": True, + "lang_id_min_cutoff": 0.75, + "cond_check_perplexity": False, + "perplexity_max_cutoff": 3000000, +} + +parameters_filtering_ta = { + "cond_uniform_whitespace": True, + "cond_replace_unicode_punctuation": False, + "cond_remove_words_with_incorrect_substrings": False, + "incorrect_word_substrings": ["http", "www", ".com", "href", "//"], + "cond_remove_long_words": True, + "length_word_max_cutoff": 50, + "cond_check_number_words": True, + "tokenization": False, + "strip_characters": special_characters_default, + "number_words_min_cutoff": 1, + "number_words_max_cutoff": 100000, + "check_repetitions_removal": True, + "repetitions_length": 10, + "repetitions_max_cutoff": 0.106, + "cond_check_special_characters": True, + "special_characters": special_characters_default, + "special_characters_max_cutoff": 0.25, + "cond_words_augmentation": False, + "words_augmentation_group_sizes": [], + "words_augmentation_join_char": "", + "cond_check_stopwords": True, + "stopwords_min_cutoff": 0, + "cond_check_badwords": False, + "badwords_max_cutoff": 0.2, + "cond_check_lang_id": True, + "lang_id_min_cutoff": 0.75, + "cond_check_perplexity": False, + "perplexity_max_cutoff": 3000000, +} + +parameters_filtering_te = { + "cond_uniform_whitespace": True, + "cond_replace_unicode_punctuation": False, + "cond_remove_words_with_incorrect_substrings": False, + "incorrect_word_substrings": ["http", "www", ".com", "href", "//"], + "cond_remove_long_words": True, + "length_word_max_cutoff": 35, + "cond_check_number_words": True, + "tokenization": False, + "strip_characters": special_characters_default, + "number_words_min_cutoff": 1, + "number_words_max_cutoff": 100000, + "check_repetitions_removal": True, + "repetitions_length": 10, + "repetitions_max_cutoff": 0.106, + "cond_check_special_characters": True, + "special_characters": special_characters_default, + "special_characters_max_cutoff": 0.25, + "cond_words_augmentation": False, + "words_augmentation_group_sizes": [], + "words_augmentation_join_char": "", + "cond_check_stopwords": True, + "stopwords_min_cutoff": 0, + "cond_check_badwords": False, + "badwords_max_cutoff": 0.2, + "cond_check_lang_id": True, + "lang_id_min_cutoff": 0.75, + "cond_check_perplexity": False, + "perplexity_max_cutoff": 3000000, +} + +parameters_filtering_ur = { + "cond_uniform_whitespace": True, + "cond_replace_unicode_punctuation": False, + "cond_remove_words_with_incorrect_substrings": False, + "incorrect_word_substrings": ["http", "www", ".com", "href", "//"], + "cond_remove_long_words": True, + "length_word_max_cutoff": 30, + "cond_check_number_words": True, + "tokenization": False, + "strip_characters": special_characters_default, + "number_words_min_cutoff": 1, + "number_words_max_cutoff": 100000, + "check_repetitions_removal": True, + "repetitions_length": 10, + "repetitions_max_cutoff": 0.106, + "cond_check_special_characters": True, + "special_characters": special_characters_default, + "special_characters_max_cutoff": 0.4, + "cond_words_augmentation": False, + "words_augmentation_group_sizes": [], + "words_augmentation_join_char": "", + "cond_check_stopwords": True, + "stopwords_min_cutoff": 0, + "cond_check_badwords": False, + "badwords_max_cutoff": 0.2, + "cond_check_lang_id": True, + "lang_id_min_cutoff": 0.75, + "cond_check_perplexity": False, + "perplexity_max_cutoff": 3000000, +} + +parameters_filtering_vi = { + "cond_uniform_whitespace": True, + "cond_replace_unicode_punctuation": False, + "cond_remove_words_with_incorrect_substrings": False, + "incorrect_word_substrings": ["http", "www", ".com", "href", "//"], + "cond_remove_long_words": True, + "length_word_max_cutoff": 30, + "cond_check_number_words": True, + "tokenization": False, + "strip_characters": special_characters_default, + "number_words_min_cutoff": 1, + "number_words_max_cutoff": 100000, + "check_repetitions_removal": True, + "repetitions_length": 10, + "repetitions_max_cutoff": 0.106, + "cond_check_special_characters": True, + "special_characters": special_characters_default, + "special_characters_max_cutoff": 0.35, + "cond_words_augmentation": True, + "words_augmentation_group_sizes": [2, 3], + "words_augmentation_join_char": " ", + "cond_check_stopwords": True, + "stopwords_min_cutoff": 0, + "cond_check_badwords": False, + "badwords_max_cutoff": 0.2, + "cond_check_lang_id": True, + "lang_id_min_cutoff": 0.75, + "cond_check_perplexity": False, + "perplexity_max_cutoff": 3000000, +} + +parameters_filtering_yo = { + "cond_uniform_whitespace": True, + "cond_replace_unicode_punctuation": False, + "cond_remove_words_with_incorrect_substrings": False, + "incorrect_word_substrings": ["http", "www", ".com", "href", "//"], + "cond_remove_long_words": True, + "length_word_max_cutoff": 30, + "cond_check_number_words": True, + "tokenization": False, + "strip_characters": special_characters_default, + "number_words_min_cutoff": 1, + "number_words_max_cutoff": 100000, + "check_repetitions_removal": True, + "repetitions_length": 10, + "repetitions_max_cutoff": 0.106, + "cond_check_special_characters": True, + "special_characters": special_characters_default, + "special_characters_max_cutoff": 0.3, + "cond_words_augmentation": False, + "words_augmentation_group_sizes": [], + "words_augmentation_join_char": "", + "cond_check_stopwords": True, + "stopwords_min_cutoff": 0, + "cond_check_badwords": False, + "badwords_max_cutoff": 0.2, + "cond_check_lang_id": True, + "lang_id_min_cutoff": 0.75, + "cond_check_perplexity": False, + "perplexity_max_cutoff": 3000000, +} + +parameters_filtering_zh = { + "cond_uniform_whitespace": True, + "cond_replace_unicode_punctuation": False, + "cond_remove_words_with_incorrect_substrings": False, + "incorrect_word_substrings": ["http", "www", ".com", "href", "//"], + "cond_remove_long_words": False, + "length_word_max_cutoff": 1000, + "cond_check_number_words": True, + "tokenization": True, + "strip_characters": special_characters_default, + "number_words_min_cutoff": 1, + "number_words_max_cutoff": 100000, + "check_repetitions_removal": True, + "repetitions_length": 10, + "repetitions_max_cutoff": 0.106, + "cond_check_special_characters": True, + "special_characters": special_characters_default, + "special_characters_max_cutoff": 0.4, + "cond_words_augmentation": True, + "words_augmentation_group_sizes": [2, 3], + "words_augmentation_join_char": "", + "cond_check_stopwords": False, + "stopwords_min_cutoff": 0, + "cond_check_badwords": False, + "badwords_max_cutoff": 0.2, + "cond_check_lang_id": True, + "lang_id_min_cutoff": 0.75, + "cond_check_perplexity": False, + "perplexity_max_cutoff": 3000000, +} + +parameters_filtering = { + "default": parameters_filtering_default, + "af": parameters_filtering_af, + "ar": parameters_filtering_ar, + "arz": parameters_filtering_arz, + "as": parameters_filtering_as, + "bn": parameters_filtering_bn, + "ca": parameters_filtering_ca, + "en": parameters_filtering_en, + "es": parameters_filtering_es, + "eu": parameters_filtering_eu, + "fr": parameters_filtering_fr, + "gu": parameters_filtering_gu, + "hi": parameters_filtering_hi, + "id": parameters_filtering_id, + "kn": parameters_filtering_kn, + "ml": parameters_filtering_ml, + "mr": parameters_filtering_mr, + "pt": parameters_filtering_pt, + "so": parameters_filtering_so, + "sw": parameters_filtering_sw, + "ta": parameters_filtering_ta, + "te": parameters_filtering_te, + "ur": parameters_filtering_ur, + "vi": parameters_filtering_vi, + "yo": parameters_filtering_yo, + "zh": parameters_filtering_zh, +} diff --git a/data_tooling/ac_dc/stopwords.py b/data_tooling/ac_dc/stopwords.py new file mode 100644 index 0000000..e75bbd4 --- /dev/null +++ b/data_tooling/ac_dc/stopwords.py @@ -0,0 +1,5395 @@ +# From https://github.com/6/stopwords-json +# From https://github.com/stopwords-iso/stopwords-iso for Urdu and Vietnamese + + +stopwords = { + "af": [ + "'n", + "aan", + "af", + "al", + "as", + "baie", + "by", + "daar", + "dag", + "dat", + "die", + "dit", + "een", + "ek", + "en", + "gaan", + "gesê", + "haar", + "het", + "hom", + "hulle", + "hy", + "in", + "is", + "jou", + "jy", + "kan", + "kom", + "ma", + "maar", + "met", + "my", + "na", + "nie", + "om", + "ons", + "op", + "saam", + "sal", + "se", + "sien", + "so", + "sy", + "te", + "toe", + "uit", + "van", + "vir", + "was", + "wat", + "ʼn", + ], + "ar": [ + "،", + "أ", + "ا", + "اثر", + "اجل", + "احد", + "اخرى", + "اذا", + "اربعة", + "اطار", + "اعادة", + "اعلنت", + "اف", + "اكثر", + "اكد", + "الا", + "الاخيرة", + "الان", + "الاول", + "الاولى", + "التى", + "التي", + "الثاني", + "الثانية", + "الذاتي", + "الذى", + "الذي", + "الذين", + "السابق", + "الف", + "الماضي", + "المقبل", + "الوقت", + "الى", + "اليوم", + "اما", + "امام", + "امس", + "ان", + "انه", + "انها", + "او", + "اول", + "اي", + "ايار", + "ايام", + "ايضا", + "ب", + "باسم", + "بان", + "برس", + "بسبب", + "بشكل", + "بعد", + "بعض", + "بن", + "به", + "بها", + "بين", + "تم", + "ثلاثة", + "ثم", + "جميع", + "حاليا", + "حتى", + "حوالى", + "حول", + "حيث", + "حين", + "خلال", + "دون", + "ذلك", + "زيارة", + "سنة", + "سنوات", + "شخصا", + "صباح", + "صفر", + "ضد", + "ضمن", + "عام", + "عاما", + "عدة", + "عدد", + "عدم", + "عشر", + "عشرة", + "على", + "عليه", + "عليها", + "عن", + "عند", + "عندما", + "غدا", + "غير", + "ـ", + "ف", + "فان", + "فى", + "في", + "فيه", + "فيها", + "قال", + "قبل", + "قد", + "قوة", + "كان", + "كانت", + "كل", + "كلم", + "كما", + "لا", + "لدى", + "لقاء", + "لكن", + "للامم", + "لم", + "لن", + "له", + "لها", + "لوكالة", + "ما", + "مايو", + "مساء", + "مع", + "مقابل", + "مليار", + "مليون", + "من", + "منذ", + "منها", + "نحو", + "نفسه", + "نهاية", + "هذا", + "هذه", + "هناك", + "هو", + "هي", + "و", + "و6", + "واحد", + "واضاف", + "واضافت", + "واكد", + "وان", + "واوضح", + "وفي", + "وقال", + "وقالت", + "وقد", + "وقف", + "وكان", + "وكانت", + "ولا", + "ولم", + "ومن", + "وهو", + "وهي", + "يكون", + "يمكن", + "يوم", + ], + "bn": [ + "অনেক", + "অন্য", + "অবশ্য", + "আগে", + "আছে", + "আজ", + "আবার", + "আমরা", + "আমাদের", + "আর", + "ই", + "উত্তর", + "উপর", + "উপরে", + "এ", + "এই", + "এক্", + "এখন", + "এত", + "এব", + "এমন", + "এমনি", + "এর", + "এস", + "এসে", + "ও", + "ওই", + "কমনে", + "করা", + "করে", + "কাছে", + "কাজ", + "কাজে", + "কারণ", + "কি", + "কিছু", + "কে", + "কেউ", + "কেখা", + "কেন", + "কোটি", + "কোনো", + "কয়েক", + "খুব", + "গিয়ে", + "গেল", + "চার", + "চালু", + "চেষ্টা", + "ছিল", + "জানা", + "জ্নজন", + "টি", + "তখন", + "তবে", + "তা", + "তাই", + "তো", + "থাকা", + "থেকে", + "দিন", + "দু", + "দুই", + "দেওয়া", + "ধামার", + "নতুন", + "না", + "নাগাদ", + "নিয়ে", + "নেওয়া", + "নয়", + "পর", + "পরে", + "পাচ", + "পি", + "পেয়্র্", + "প্রতি", + "প্রথম", + "প্রযন্ত", + "প্রাথমিক", + "প্রায়", + "বক্তব্য", + "বন", + "বলা", + "বলে", + "বলেন", + "বহু", + "বা", + "বি", + "বিভিন্ন", + "বেশ", + "বেশি", + "মতো", + "মধ্যে", + "মনে", + "যখন", + "যদি", + "যা", + "যাওয়া", + "যে", + "র", + "রকম", + "লক্ষ", + "শুধু", + "শুরু", + "সঙ্গে", + "সব", + "সহ", + "সাধারণ", + "সামনে", + "সি", + "সে", + "সেই", + "হতে", + "হাজার", + "হয়", + ], + "ca": [ + "a", + "abans", + "ací", + "ah", + "així", + "això", + "al", + "aleshores", + "algun", + "alguna", + "algunes", + "alguns", + "alhora", + "allà", + "allí", + "allò", + "als", + "altra", + "altre", + "altres", + "amb", + "ambdues", + "ambdós", + "apa", + "aquell", + "aquella", + "aquelles", + "aquells", + "aquest", + "aquesta", + "aquestes", + "aquests", + "aquí", + "baix", + "cada", + "cadascuna", + "cadascunes", + "cadascuns", + "cadascú", + "com", + "contra", + "d'un", + "d'una", + "d'unes", + "d'uns", + "dalt", + "de", + "del", + "dels", + "des", + "després", + "dins", + "dintre", + "donat", + "doncs", + "durant", + "e", + "eh", + "el", + "els", + "em", + "en", + "encara", + "ens", + "entre", + "eren", + "es", + "esta", + "estaven", + "esteu", + "està", + "estàvem", + "estàveu", + "et", + "etc", + "ets", + "fins", + "fora", + "gairebé", + "ha", + "han", + "has", + "havia", + "he", + "hem", + "heu", + "hi", + "ho", + "i", + "igual", + "iguals", + "ja", + "l'hi", + "la", + "les", + "li", + "li'n", + "llavors", + "m'he", + "ma", + "mal", + "malgrat", + "mateix", + "mateixa", + "mateixes", + "mateixos", + "me", + "mentre", + "meu", + "meus", + "meva", + "meves", + "molt", + "molta", + "moltes", + "molts", + "mon", + "mons", + "més", + "n'he", + "n'hi", + "ne", + "ni", + "no", + "nogensmenys", + "només", + "nosaltres", + "nostra", + "nostre", + "nostres", + "o", + "oh", + "oi", + "on", + "pas", + "pel", + "pels", + "per", + "perquè", + "però", + "poc", + "poca", + "pocs", + "poques", + "potser", + "propi", + "qual", + "quals", + "quan", + "quant", + "que", + "quelcom", + "qui", + "quin", + "quina", + "quines", + "quins", + "què", + "s'ha", + "s'han", + "sa", + "semblant", + "semblants", + "ses", + "seu", + "seus", + "seva", + "seves", + "si", + "sobre", + "sobretot", + "solament", + "sols", + "son", + "sons", + "sota", + "sou", + "sóc", + "són", + "t'ha", + "t'han", + "t'he", + "ta", + "tal", + "també", + "tampoc", + "tan", + "tant", + "tanta", + "tantes", + "teu", + "teus", + "teva", + "teves", + "ton", + "tons", + "tot", + "tota", + "totes", + "tots", + "un", + "una", + "unes", + "uns", + "us", + "va", + "vaig", + "vam", + "van", + "vas", + "veu", + "vosaltres", + "vostra", + "vostre", + "vostres", + "érem", + "éreu", + "és", + ], + "en": [ + "a", + "a's", + "able", + "about", + "above", + "according", + "accordingly", + "across", + "actually", + "after", + "afterwards", + "again", + "against", + "ain't", + "all", + "allow", + "allows", + "almost", + "alone", + "along", + "already", + "also", + "although", + "always", + "am", + "among", + "amongst", + "an", + "and", + "another", + "any", + "anybody", + "anyhow", + "anyone", + "anything", + "anyway", + "anyways", + "anywhere", + "apart", + "appear", + "appreciate", + "appropriate", + "are", + "aren't", + "around", + "as", + "aside", + "ask", + "asking", + "associated", + "at", + "available", + "away", + "awfully", + "b", + "be", + "became", + "because", + "become", + "becomes", + "becoming", + "been", + "before", + "beforehand", + "behind", + "being", + "believe", + "below", + "beside", + "besides", + "best", + "better", + "between", + "beyond", + "both", + "brief", + "but", + "by", + "c", + "c'mon", + "c's", + "came", + "can", + "can't", + "cannot", + "cant", + "cause", + "causes", + "certain", + "certainly", + "changes", + "clearly", + "co", + "com", + "come", + "comes", + "concerning", + "consequently", + "consider", + "considering", + "contain", + "containing", + "contains", + "corresponding", + "could", + "couldn't", + "course", + "currently", + "d", + "definitely", + "described", + "despite", + "did", + "didn't", + "different", + "do", + "does", + "doesn't", + "doing", + "don't", + "done", + "down", + "downwards", + "during", + "e", + "each", + "edu", + "eg", + "eight", + "either", + "else", + "elsewhere", + "enough", + "entirely", + "especially", + "et", + "etc", + "even", + "ever", + "every", + "everybody", + "everyone", + "everything", + "everywhere", + "ex", + "exactly", + "example", + "except", + "f", + "far", + "few", + "fifth", + "first", + "five", + "followed", + "following", + "follows", + "for", + "former", + "formerly", + "forth", + "four", + "from", + "further", + "furthermore", + "g", + "get", + "gets", + "getting", + "given", + "gives", + "go", + "goes", + "going", + "gone", + "got", + "gotten", + "greetings", + "h", + "had", + "hadn't", + "happens", + "hardly", + "has", + "hasn't", + "have", + "haven't", + "having", + "he", + "he's", + "hello", + "help", + "hence", + "her", + "here", + "here's", + "hereafter", + "hereby", + "herein", + "hereupon", + "hers", + "herself", + "hi", + "him", + "himself", + "his", + "hither", + "hopefully", + "how", + "howbeit", + "however", + "i", + "i'd", + "i'll", + "i'm", + "i've", + "ie", + "if", + "ignored", + "immediate", + "in", + "inasmuch", + "inc", + "indeed", + "indicate", + "indicated", + "indicates", + "inner", + "insofar", + "instead", + "into", + "inward", + "is", + "isn't", + "it", + "it'd", + "it'll", + "it's", + "its", + "itself", + "j", + "just", + "k", + "keep", + "keeps", + "kept", + "know", + "known", + "knows", + "l", + "last", + "lately", + "later", + "latter", + "latterly", + "least", + "less", + "lest", + "let", + "let's", + "like", + "liked", + "likely", + "little", + "look", + "looking", + "looks", + "ltd", + "m", + "mainly", + "many", + "may", + "maybe", + "me", + "mean", + "meanwhile", + "merely", + "might", + "more", + "moreover", + "most", + "mostly", + "much", + "must", + "my", + "myself", + "n", + "name", + "namely", + "nd", + "near", + "nearly", + "necessary", + "need", + "needs", + "neither", + "never", + "nevertheless", + "new", + "next", + "nine", + "no", + "nobody", + "non", + "none", + "noone", + "nor", + "normally", + "not", + "nothing", + "novel", + "now", + "nowhere", + "o", + "obviously", + "of", + "off", + "often", + "oh", + "ok", + "okay", + "old", + "on", + "once", + "one", + "ones", + "only", + "onto", + "or", + "other", + "others", + "otherwise", + "ought", + "our", + "ours", + "ourselves", + "out", + "outside", + "over", + "overall", + "own", + "p", + "particular", + "particularly", + "per", + "perhaps", + "placed", + "please", + "plus", + "possible", + "presumably", + "probably", + "provides", + "q", + "que", + "quite", + "qv", + "r", + "rather", + "rd", + "re", + "really", + "reasonably", + "regarding", + "regardless", + "regards", + "relatively", + "respectively", + "right", + "s", + "said", + "same", + "saw", + "say", + "saying", + "says", + "second", + "secondly", + "see", + "seeing", + "seem", + "seemed", + "seeming", + "seems", + "seen", + "self", + "selves", + "sensible", + "sent", + "serious", + "seriously", + "seven", + "several", + "shall", + "she", + "should", + "shouldn't", + "since", + "six", + "so", + "some", + "somebody", + "somehow", + "someone", + "something", + "sometime", + "sometimes", + "somewhat", + "somewhere", + "soon", + "sorry", + "specified", + "specify", + "specifying", + "still", + "sub", + "such", + "sup", + "sure", + "t", + "t's", + "take", + "taken", + "tell", + "tends", + "th", + "than", + "thank", + "thanks", + "thanx", + "that", + "that's", + "thats", + "the", + "their", + "theirs", + "them", + "themselves", + "then", + "thence", + "there", + "there's", + "thereafter", + "thereby", + "therefore", + "therein", + "theres", + "thereupon", + "these", + "they", + "they'd", + "they'll", + "they're", + "they've", + "think", + "third", + "this", + "thorough", + "thoroughly", + "those", + "though", + "three", + "through", + "throughout", + "thru", + "thus", + "to", + "together", + "too", + "took", + "toward", + "towards", + "tried", + "tries", + "truly", + "try", + "trying", + "twice", + "two", + "u", + "un", + "under", + "unfortunately", + "unless", + "unlikely", + "until", + "unto", + "up", + "upon", + "us", + "use", + "used", + "useful", + "uses", + "using", + "usually", + "uucp", + "v", + "value", + "various", + "very", + "via", + "viz", + "vs", + "w", + "want", + "wants", + "was", + "wasn't", + "way", + "we", + "we'd", + "we'll", + "we're", + "we've", + "welcome", + "well", + "went", + "were", + "weren't", + "what", + "what's", + "whatever", + "when", + "whence", + "whenever", + "where", + "where's", + "whereafter", + "whereas", + "whereby", + "wherein", + "whereupon", + "wherever", + "whether", + "which", + "while", + "whither", + "who", + "who's", + "whoever", + "whole", + "whom", + "whose", + "why", + "will", + "willing", + "wish", + "with", + "within", + "without", + "won't", + "wonder", + "would", + "wouldn't", + "x", + "y", + "yes", + "yet", + "you", + "you'd", + "you'll", + "you're", + "you've", + "your", + "yours", + "yourself", + "yourselves", + "z", + "zero", + ], + "es": [ + "a", + "actualmente", + "acuerdo", + "adelante", + "ademas", + "además", + "adrede", + "afirmó", + "agregó", + "ahi", + "ahora", + "ahí", + "al", + "algo", + "alguna", + "algunas", + "alguno", + "algunos", + "algún", + "alli", + "allí", + "alrededor", + "ambos", + "ampleamos", + "antano", + "antaño", + "ante", + "anterior", + "antes", + "apenas", + "aproximadamente", + "aquel", + "aquella", + "aquellas", + "aquello", + "aquellos", + "aqui", + "aquél", + "aquélla", + "aquéllas", + "aquéllos", + "aquí", + "arriba", + "arribaabajo", + "aseguró", + "asi", + "así", + "atras", + "aun", + "aunque", + "ayer", + "añadió", + "aún", + "b", + "bajo", + "bastante", + "bien", + "breve", + "buen", + "buena", + "buenas", + "bueno", + "buenos", + "c", + "cada", + "casi", + "cerca", + "cierta", + "ciertas", + "cierto", + "ciertos", + "cinco", + "claro", + "comentó", + "como", + "con", + "conmigo", + "conocer", + "conseguimos", + "conseguir", + "considera", + "consideró", + "consigo", + "consigue", + "consiguen", + "consigues", + "contigo", + "contra", + "cosas", + "creo", + "cual", + "cuales", + "cualquier", + "cuando", + "cuanta", + "cuantas", + "cuanto", + "cuantos", + "cuatro", + "cuenta", + "cuál", + "cuáles", + "cuándo", + "cuánta", + "cuántas", + "cuánto", + "cuántos", + "cómo", + "d", + "da", + "dado", + "dan", + "dar", + "de", + "debajo", + "debe", + "deben", + "debido", + "decir", + "dejó", + "del", + "delante", + "demasiado", + "demás", + "dentro", + "deprisa", + "desde", + "despacio", + "despues", + "después", + "detras", + "detrás", + "dia", + "dias", + "dice", + "dicen", + "dicho", + "dieron", + "diferente", + "diferentes", + "dijeron", + "dijo", + "dio", + "donde", + "dos", + "durante", + "día", + "días", + "dónde", + "e", + "ejemplo", + "el", + "ella", + "ellas", + "ello", + "ellos", + "embargo", + "empleais", + "emplean", + "emplear", + "empleas", + "empleo", + "en", + "encima", + "encuentra", + "enfrente", + "enseguida", + "entonces", + "entre", + "era", + "eramos", + "eran", + "eras", + "eres", + "es", + "esa", + "esas", + "ese", + "eso", + "esos", + "esta", + "estaba", + "estaban", + "estado", + "estados", + "estais", + "estamos", + "estan", + "estar", + "estará", + "estas", + "este", + "esto", + "estos", + "estoy", + "estuvo", + "está", + "están", + "ex", + "excepto", + "existe", + "existen", + "explicó", + "expresó", + "f", + "fin", + "final", + "fue", + "fuera", + "fueron", + "fui", + "fuimos", + "g", + "general", + "gran", + "grandes", + "gueno", + "h", + "ha", + "haber", + "habia", + "habla", + "hablan", + "habrá", + "había", + "habían", + "hace", + "haceis", + "hacemos", + "hacen", + "hacer", + "hacerlo", + "haces", + "hacia", + "haciendo", + "hago", + "han", + "hasta", + "hay", + "haya", + "he", + "hecho", + "hemos", + "hicieron", + "hizo", + "horas", + "hoy", + "hubo", + "i", + "igual", + "incluso", + "indicó", + "informo", + "informó", + "intenta", + "intentais", + "intentamos", + "intentan", + "intentar", + "intentas", + "intento", + "ir", + "j", + "junto", + "k", + "l", + "la", + "lado", + "largo", + "las", + "le", + "lejos", + "les", + "llegó", + "lleva", + "llevar", + "lo", + "los", + "luego", + "lugar", + "m", + "mal", + "manera", + "manifestó", + "mas", + "mayor", + "me", + "mediante", + "medio", + "mejor", + "mencionó", + "menos", + "menudo", + "mi", + "mia", + "mias", + "mientras", + "mio", + "mios", + "mis", + "misma", + "mismas", + "mismo", + "mismos", + "modo", + "momento", + "mucha", + "muchas", + "mucho", + "muchos", + "muy", + "más", + "mí", + "mía", + "mías", + "mío", + "míos", + "n", + "nada", + "nadie", + "ni", + "ninguna", + "ningunas", + "ninguno", + "ningunos", + "ningún", + "no", + "nos", + "nosotras", + "nosotros", + "nuestra", + "nuestras", + "nuestro", + "nuestros", + "nueva", + "nuevas", + "nuevo", + "nuevos", + "nunca", + "o", + "ocho", + "os", + "otra", + "otras", + "otro", + "otros", + "p", + "pais", + "para", + "parece", + "parte", + "partir", + "pasada", + "pasado", + "paìs", + "peor", + "pero", + "pesar", + "poca", + "pocas", + "poco", + "pocos", + "podeis", + "podemos", + "poder", + "podria", + "podriais", + "podriamos", + "podrian", + "podrias", + "podrá", + "podrán", + "podría", + "podrían", + "poner", + "por", + "porque", + "posible", + "primer", + "primera", + "primero", + "primeros", + "principalmente", + "pronto", + "propia", + "propias", + "propio", + "propios", + "proximo", + "próximo", + "próximos", + "pudo", + "pueda", + "puede", + "pueden", + "puedo", + "pues", + "q", + "qeu", + "que", + "quedó", + "queremos", + "quien", + "quienes", + "quiere", + "quiza", + "quizas", + "quizá", + "quizás", + "quién", + "quiénes", + "qué", + "r", + "raras", + "realizado", + "realizar", + "realizó", + "repente", + "respecto", + "s", + "sabe", + "sabeis", + "sabemos", + "saben", + "saber", + "sabes", + "salvo", + "se", + "sea", + "sean", + "segun", + "segunda", + "segundo", + "según", + "seis", + "ser", + "sera", + "será", + "serán", + "sería", + "señaló", + "si", + "sido", + "siempre", + "siendo", + "siete", + "sigue", + "siguiente", + "sin", + "sino", + "sobre", + "sois", + "sola", + "solamente", + "solas", + "solo", + "solos", + "somos", + "son", + "soy", + "soyos", + "su", + "supuesto", + "sus", + "suya", + "suyas", + "suyo", + "sé", + "sí", + "sólo", + "t", + "tal", + "tambien", + "también", + "tampoco", + "tan", + "tanto", + "tarde", + "te", + "temprano", + "tendrá", + "tendrán", + "teneis", + "tenemos", + "tener", + "tenga", + "tengo", + "tenido", + "tenía", + "tercera", + "ti", + "tiempo", + "tiene", + "tienen", + "toda", + "todas", + "todavia", + "todavía", + "todo", + "todos", + "total", + "trabaja", + "trabajais", + "trabajamos", + "trabajan", + "trabajar", + "trabajas", + "trabajo", + "tras", + "trata", + "través", + "tres", + "tu", + "tus", + "tuvo", + "tuya", + "tuyas", + "tuyo", + "tuyos", + "tú", + "u", + "ultimo", + "un", + "una", + "unas", + "uno", + "unos", + "usa", + "usais", + "usamos", + "usan", + "usar", + "usas", + "uso", + "usted", + "ustedes", + "v", + "va", + "vais", + "valor", + "vamos", + "van", + "varias", + "varios", + "vaya", + "veces", + "ver", + "verdad", + "verdadera", + "verdadero", + "vez", + "vosotras", + "vosotros", + "voy", + "vuestra", + "vuestras", + "vuestro", + "vuestros", + "w", + "x", + "y", + "ya", + "yo", + "z", + "él", + "ésa", + "ésas", + "ése", + "ésos", + "ésta", + "éstas", + "éste", + "éstos", + "última", + "últimas", + "último", + "últimos", + ], + "eu": [ + "al", + "anitz", + "arabera", + "asko", + "baina", + "bat", + "batean", + "batek", + "bati", + "batzuei", + "batzuek", + "batzuetan", + "batzuk", + "bera", + "beraiek", + "berau", + "berauek", + "bere", + "berori", + "beroriek", + "beste", + "bezala", + "da", + "dago", + "dira", + "ditu", + "du", + "dute", + "edo", + "egin", + "ere", + "eta", + "eurak", + "ez", + "gainera", + "gu", + "gutxi", + "guzti", + "haiei", + "haiek", + "haietan", + "hainbeste", + "hala", + "han", + "handik", + "hango", + "hara", + "hari", + "hark", + "hartan", + "hau", + "hauei", + "hauek", + "hauetan", + "hemen", + "hemendik", + "hemengo", + "hi", + "hona", + "honek", + "honela", + "honetan", + "honi", + "hor", + "hori", + "horiei", + "horiek", + "horietan", + "horko", + "horra", + "horrek", + "horrela", + "horretan", + "horri", + "hortik", + "hura", + "izan", + "ni", + "noiz", + "nola", + "non", + "nondik", + "nongo", + "nor", + "nora", + "ze", + "zein", + "zen", + "zenbait", + "zenbat", + "zer", + "zergatik", + "ziren", + "zituen", + "zu", + "zuek", + "zuen", + "zuten", + ], + "fr": [ + "a", + "abord", + "absolument", + "afin", + "ah", + "ai", + "aie", + "ailleurs", + "ainsi", + "ait", + "allaient", + "allo", + "allons", + "allô", + "alors", + "anterieur", + "anterieure", + "anterieures", + "apres", + "après", + "as", + "assez", + "attendu", + "au", + "aucun", + "aucune", + "aujourd", + "aujourd'hui", + "aupres", + "auquel", + "aura", + "auraient", + "aurait", + "auront", + "aussi", + "autre", + "autrefois", + "autrement", + "autres", + "autrui", + "aux", + "auxquelles", + "auxquels", + "avaient", + "avais", + "avait", + "avant", + "avec", + "avoir", + "avons", + "ayant", + "b", + "bah", + "bas", + "basee", + "bat", + "beau", + "beaucoup", + "bien", + "bigre", + "boum", + "bravo", + "brrr", + "c", + "car", + "ce", + "ceci", + "cela", + "celle", + "celle-ci", + "celle-là", + "celles", + "celles-ci", + "celles-là", + "celui", + "celui-ci", + "celui-là", + "cent", + "cependant", + "certain", + "certaine", + "certaines", + "certains", + "certes", + "ces", + "cet", + "cette", + "ceux", + "ceux-ci", + "ceux-là", + "chacun", + "chacune", + "chaque", + "cher", + "chers", + "chez", + "chiche", + "chut", + "chère", + "chères", + "ci", + "cinq", + "cinquantaine", + "cinquante", + "cinquantième", + "cinquième", + "clac", + "clic", + "combien", + "comme", + "comment", + "comparable", + "comparables", + "compris", + "concernant", + "contre", + "couic", + "crac", + "d", + "da", + "dans", + "de", + "debout", + "dedans", + "dehors", + "deja", + "delà", + "depuis", + "dernier", + "derniere", + "derriere", + "derrière", + "des", + "desormais", + "desquelles", + "desquels", + "dessous", + "dessus", + "deux", + "deuxième", + "deuxièmement", + "devant", + "devers", + "devra", + "different", + "differentes", + "differents", + "différent", + "différente", + "différentes", + "différents", + "dire", + "directe", + "directement", + "dit", + "dite", + "dits", + "divers", + "diverse", + "diverses", + "dix", + "dix-huit", + "dix-neuf", + "dix-sept", + "dixième", + "doit", + "doivent", + "donc", + "dont", + "douze", + "douzième", + "dring", + "du", + "duquel", + "durant", + "dès", + "désormais", + "e", + "effet", + "egale", + "egalement", + "egales", + "eh", + "elle", + "elle-même", + "elles", + "elles-mêmes", + "en", + "encore", + "enfin", + "entre", + "envers", + "environ", + "es", + "est", + "et", + "etant", + "etc", + "etre", + "eu", + "euh", + "eux", + "eux-mêmes", + "exactement", + "excepté", + "extenso", + "exterieur", + "f", + "fais", + "faisaient", + "faisant", + "fait", + "façon", + "feront", + "fi", + "flac", + "floc", + "font", + "g", + "gens", + "h", + "ha", + "hein", + "hem", + "hep", + "hi", + "ho", + "holà", + "hop", + "hormis", + "hors", + "hou", + "houp", + "hue", + "hui", + "huit", + "huitième", + "hum", + "hurrah", + "hé", + "hélas", + "i", + "il", + "ils", + "importe", + "j", + "je", + "jusqu", + "jusque", + "juste", + "k", + "l", + "la", + "laisser", + "laquelle", + "las", + "le", + "lequel", + "les", + "lesquelles", + "lesquels", + "leur", + "leurs", + "longtemps", + "lors", + "lorsque", + "lui", + "lui-meme", + "lui-même", + "là", + "lès", + "m", + "ma", + "maint", + "maintenant", + "mais", + "malgre", + "malgré", + "maximale", + "me", + "meme", + "memes", + "merci", + "mes", + "mien", + "mienne", + "miennes", + "miens", + "mille", + "mince", + "minimale", + "moi", + "moi-meme", + "moi-même", + "moindres", + "moins", + "mon", + "moyennant", + "multiple", + "multiples", + "même", + "mêmes", + "n", + "na", + "naturel", + "naturelle", + "naturelles", + "ne", + "neanmoins", + "necessaire", + "necessairement", + "neuf", + "neuvième", + "ni", + "nombreuses", + "nombreux", + "non", + "nos", + "notamment", + "notre", + "nous", + "nous-mêmes", + "nouveau", + "nul", + "néanmoins", + "nôtre", + "nôtres", + "o", + "oh", + "ohé", + "ollé", + "olé", + "on", + "ont", + "onze", + "onzième", + "ore", + "ou", + "ouf", + "ouias", + "oust", + "ouste", + "outre", + "ouvert", + "ouverte", + "ouverts", + "o|", + "où", + "p", + "paf", + "pan", + "par", + "parce", + "parfois", + "parle", + "parlent", + "parler", + "parmi", + "parseme", + "partant", + "particulier", + "particulière", + "particulièrement", + "pas", + "passé", + "pendant", + "pense", + "permet", + "personne", + "peu", + "peut", + "peuvent", + "peux", + "pff", + "pfft", + "pfut", + "pif", + "pire", + "plein", + "plouf", + "plus", + "plusieurs", + "plutôt", + "possessif", + "possessifs", + "possible", + "possibles", + "pouah", + "pour", + "pourquoi", + "pourrais", + "pourrait", + "pouvait", + "prealable", + "precisement", + "premier", + "première", + "premièrement", + "pres", + "probable", + "probante", + "procedant", + "proche", + "près", + "psitt", + "pu", + "puis", + "puisque", + "pur", + "pure", + "q", + "qu", + "quand", + "quant", + "quant-à-soi", + "quanta", + "quarante", + "quatorze", + "quatre", + "quatre-vingt", + "quatrième", + "quatrièmement", + "que", + "quel", + "quelconque", + "quelle", + "quelles", + "quelqu'un", + "quelque", + "quelques", + "quels", + "qui", + "quiconque", + "quinze", + "quoi", + "quoique", + "r", + "rare", + "rarement", + "rares", + "relative", + "relativement", + "remarquable", + "rend", + "rendre", + "restant", + "reste", + "restent", + "restrictif", + "retour", + "revoici", + "revoilà", + "rien", + "s", + "sa", + "sacrebleu", + "sait", + "sans", + "sapristi", + "sauf", + "se", + "sein", + "seize", + "selon", + "semblable", + "semblaient", + "semble", + "semblent", + "sent", + "sept", + "septième", + "sera", + "seraient", + "serait", + "seront", + "ses", + "seul", + "seule", + "seulement", + "si", + "sien", + "sienne", + "siennes", + "siens", + "sinon", + "six", + "sixième", + "soi", + "soi-même", + "soit", + "soixante", + "son", + "sont", + "sous", + "souvent", + "specifique", + "specifiques", + "speculatif", + "stop", + "strictement", + "subtiles", + "suffisant", + "suffisante", + "suffit", + "suis", + "suit", + "suivant", + "suivante", + "suivantes", + "suivants", + "suivre", + "superpose", + "sur", + "surtout", + "t", + "ta", + "tac", + "tant", + "tardive", + "te", + "tel", + "telle", + "tellement", + "telles", + "tels", + "tenant", + "tend", + "tenir", + "tente", + "tes", + "tic", + "tien", + "tienne", + "tiennes", + "tiens", + "toc", + "toi", + "toi-même", + "ton", + "touchant", + "toujours", + "tous", + "tout", + "toute", + "toutefois", + "toutes", + "treize", + "trente", + "tres", + "trois", + "troisième", + "troisièmement", + "trop", + "très", + "tsoin", + "tsouin", + "tu", + "té", + "u", + "un", + "une", + "unes", + "uniformement", + "unique", + "uniques", + "uns", + "v", + "va", + "vais", + "vas", + "vers", + "via", + "vif", + "vifs", + "vingt", + "vivat", + "vive", + "vives", + "vlan", + "voici", + "voilà", + "vont", + "vos", + "votre", + "vous", + "vous-mêmes", + "vu", + "vé", + "vôtre", + "vôtres", + "w", + "x", + "y", + "z", + "zut", + "à", + "â", + "ça", + "ès", + "étaient", + "étais", + "était", + "étant", + "été", + "être", + "ô", + ], + "hi": [ + "अंदर", + "अत", + "अदि", + "अप", + "अपना", + "अपनि", + "अपनी", + "अपने", + "अभि", + "अभी", + "आदि", + "आप", + "इंहिं", + "इंहें", + "इंहों", + "इतयादि", + "इत्यादि", + "इन", + "इनका", + "इन्हीं", + "इन्हें", + "इन्हों", + "इस", + "इसका", + "इसकि", + "इसकी", + "इसके", + "इसमें", + "इसि", + "इसी", + "इसे", + "उंहिं", + "उंहें", + "उंहों", + "उन", + "उनका", + "उनकि", + "उनकी", + "उनके", + "उनको", + "उन्हीं", + "उन्हें", + "उन्हों", + "उस", + "उसके", + "उसि", + "उसी", + "उसे", + "एक", + "एवं", + "एस", + "एसे", + "ऐसे", + "ओर", + "और", + "कइ", + "कई", + "कर", + "करता", + "करते", + "करना", + "करने", + "करें", + "कहते", + "कहा", + "का", + "काफि", + "काफ़ी", + "कि", + "किंहें", + "किंहों", + "कितना", + "किन्हें", + "किन्हों", + "किया", + "किर", + "किस", + "किसि", + "किसी", + "किसे", + "की", + "कुछ", + "कुल", + "के", + "को", + "कोइ", + "कोई", + "कोन", + "कोनसा", + "कौन", + "कौनसा", + "गया", + "घर", + "जब", + "जहाँ", + "जहां", + "जा", + "जिंहें", + "जिंहों", + "जितना", + "जिधर", + "जिन", + "जिन्हें", + "जिन्हों", + "जिस", + "जिसे", + "जीधर", + "जेसा", + "जेसे", + "जैसा", + "जैसे", + "जो", + "तक", + "तब", + "तरह", + "तिंहें", + "तिंहों", + "तिन", + "तिन्हें", + "तिन्हों", + "तिस", + "तिसे", + "तो", + "था", + "थि", + "थी", + "थे", + "दबारा", + "दवारा", + "दिया", + "दुसरा", + "दुसरे", + "दूसरे", + "दो", + "द्वारा", + "न", + "नहिं", + "नहीं", + "ना", + "निचे", + "निहायत", + "नीचे", + "ने", + "पर", + "पहले", + "पुरा", + "पूरा", + "पे", + "फिर", + "बनि", + "बनी", + "बहि", + "बही", + "बहुत", + "बाद", + "बाला", + "बिलकुल", + "भि", + "भितर", + "भी", + "भीतर", + "मगर", + "मानो", + "मे", + "में", + "यदि", + "यह", + "यहाँ", + "यहां", + "यहि", + "यही", + "या", + "यिह", + "ये", + "रखें", + "रवासा", + "रहा", + "रहे", + "ऱ्वासा", + "लिए", + "लिये", + "लेकिन", + "व", + "वगेरह", + "वरग", + "वर्ग", + "वह", + "वहाँ", + "वहां", + "वहिं", + "वहीं", + "वाले", + "वुह", + "वे", + "वग़ैरह", + "संग", + "सकता", + "सकते", + "सबसे", + "सभि", + "सभी", + "साथ", + "साबुत", + "साभ", + "सारा", + "से", + "सो", + "हि", + "ही", + "हुअ", + "हुआ", + "हुइ", + "हुई", + "हुए", + "हे", + "हें", + "है", + "हैं", + "हो", + "होता", + "होति", + "होती", + "होते", + "होना", + "होने", + ], + "id": [ + "ada", + "adalah", + "adanya", + "adapun", + "agak", + "agaknya", + "agar", + "akan", + "akankah", + "akhirnya", + "aku", + "akulah", + "amat", + "amatlah", + "anda", + "andalah", + "antar", + "antara", + "antaranya", + "apa", + "apaan", + "apabila", + "apakah", + "apalagi", + "apatah", + "atau", + "ataukah", + "ataupun", + "bagai", + "bagaikan", + "bagaimana", + "bagaimanakah", + "bagaimanapun", + "bagi", + "bahkan", + "bahwa", + "bahwasanya", + "banyak", + "beberapa", + "begini", + "beginian", + "beginikah", + "beginilah", + "begitu", + "begitukah", + "begitulah", + "begitupun", + "belum", + "belumlah", + "berapa", + "berapakah", + "berapalah", + "berapapun", + "bermacam", + "bersama", + "betulkah", + "biasa", + "biasanya", + "bila", + "bilakah", + "bisa", + "bisakah", + "boleh", + "bolehkah", + "bolehlah", + "buat", + "bukan", + "bukankah", + "bukanlah", + "bukannya", + "cuma", + "dahulu", + "dalam", + "dan", + "dapat", + "dari", + "daripada", + "dekat", + "demi", + "demikian", + "demikianlah", + "dengan", + "depan", + "di", + "dia", + "dialah", + "diantara", + "diantaranya", + "dikarenakan", + "dini", + "diri", + "dirinya", + "disini", + "disinilah", + "dong", + "dulu", + "enggak", + "enggaknya", + "entah", + "entahlah", + "hal", + "hampir", + "hanya", + "hanyalah", + "harus", + "haruslah", + "harusnya", + "hendak", + "hendaklah", + "hendaknya", + "hingga", + "ia", + "ialah", + "ibarat", + "ingin", + "inginkah", + "inginkan", + "ini", + "inikah", + "inilah", + "itu", + "itukah", + "itulah", + "jangan", + "jangankan", + "janganlah", + "jika", + "jikalau", + "juga", + "justru", + "kala", + "kalau", + "kalaulah", + "kalaupun", + "kalian", + "kami", + "kamilah", + "kamu", + "kamulah", + "kan", + "kapan", + "kapankah", + "kapanpun", + "karena", + "karenanya", + "ke", + "kecil", + "kemudian", + "kenapa", + "kepada", + "kepadanya", + "ketika", + "khususnya", + "kini", + "kinilah", + "kiranya", + "kita", + "kitalah", + "kok", + "lagi", + "lagian", + "lah", + "lain", + "lainnya", + "lalu", + "lama", + "lamanya", + "lebih", + "macam", + "maka", + "makanya", + "makin", + "malah", + "malahan", + "mampu", + "mampukah", + "mana", + "manakala", + "manalagi", + "masih", + "masihkah", + "masing", + "mau", + "maupun", + "melainkan", + "melalui", + "memang", + "mengapa", + "mereka", + "merekalah", + "merupakan", + "meski", + "meskipun", + "mungkin", + "mungkinkah", + "nah", + "namun", + "nanti", + "nantinya", + "nyaris", + "oleh", + "olehnya", + "pada", + "padahal", + "padanya", + "paling", + "pantas", + "para", + "pasti", + "pastilah", + "per", + "percuma", + "pernah", + "pula", + "pun", + "rupanya", + "saat", + "saatnya", + "saja", + "sajalah", + "saling", + "sama", + "sambil", + "sampai", + "sana", + "sangat", + "sangatlah", + "saya", + "sayalah", + "se", + "sebab", + "sebabnya", + "sebagai", + "sebagaimana", + "sebagainya", + "sebaliknya", + "sebanyak", + "sebegini", + "sebegitu", + "sebelum", + "sebelumnya", + "sebenarnya", + "seberapa", + "sebetulnya", + "sebisanya", + "sebuah", + "sedang", + "sedangkan", + "sedemikian", + "sedikit", + "sedikitnya", + "segala", + "segalanya", + "segera", + "seharusnya", + "sehingga", + "sejak", + "sejenak", + "sekali", + "sekalian", + "sekaligus", + "sekalipun", + "sekarang", + "seketika", + "sekiranya", + "sekitar", + "sekitarnya", + "sela", + "selagi", + "selain", + "selaku", + "selalu", + "selama", + "selamanya", + "seluruh", + "seluruhnya", + "semacam", + "semakin", + "semasih", + "semaunya", + "sementara", + "sempat", + "semua", + "semuanya", + "semula", + "sendiri", + "sendirinya", + "seolah", + "seorang", + "sepanjang", + "sepantasnya", + "sepantasnyalah", + "seperti", + "sepertinya", + "sering", + "seringnya", + "serta", + "serupa", + "sesaat", + "sesama", + "sesegera", + "sesekali", + "seseorang", + "sesuatu", + "sesuatunya", + "sesudah", + "sesudahnya", + "setelah", + "seterusnya", + "setiap", + "setidaknya", + "sewaktu", + "siapa", + "siapakah", + "siapapun", + "sini", + "sinilah", + "suatu", + "sudah", + "sudahkah", + "sudahlah", + "supaya", + "tadi", + "tadinya", + "tak", + "tanpa", + "tapi", + "telah", + "tentang", + "tentu", + "tentulah", + "tentunya", + "terdiri", + "terhadap", + "terhadapnya", + "terlalu", + "terlebih", + "tersebut", + "tersebutlah", + "tertentu", + "tetapi", + "tiap", + "tidak", + "tidakkah", + "tidaklah", + "toh", + "waduh", + "wah", + "wahai", + "walau", + "walaupun", + "wong", + "yaitu", + "yakni", + "yang", + ], + "mr": [ + "अधिक", + "अनेक", + "अशी", + "असलयाचे", + "असलेल्या", + "असा", + "असून", + "असे", + "आज", + "आणि", + "आता", + "आपल्या", + "आला", + "आली", + "आले", + "आहे", + "आहेत", + "एक", + "एका", + "कमी", + "करणयात", + "करून", + "का", + "काम", + "काय", + "काही", + "किवा", + "की", + "केला", + "केली", + "केले", + "कोटी", + "गेल्या", + "घेऊन", + "जात", + "झाला", + "झाली", + "झाले", + "झालेल्या", + "टा", + "डॉ", + "तर", + "तरी", + "तसेच", + "ता", + "ती", + "तीन", + "ते", + "तो", + "त्या", + "त्याचा", + "त्याची", + "त्याच्या", + "त्याना", + "त्यानी", + "त्यामुळे", + "त्री", + "दिली", + "दोन", + "न", + "नाही", + "निर्ण्य", + "पण", + "पम", + "परयतन", + "पाटील", + "म", + "मात्र", + "माहिती", + "मी", + "मुबी", + "म्हणजे", + "म्हणाले", + "म्हणून", + "या", + "याचा", + "याची", + "याच्या", + "याना", + "यानी", + "येणार", + "येत", + "येथील", + "येथे", + "लाख", + "व", + "व्यकत", + "सर्व", + "सागित्ले", + "सुरू", + "हजार", + "हा", + "ही", + "हे", + "होणार", + "होत", + "होता", + "होती", + "होते", + ], + "pt": [ + "a", + "acerca", + "adeus", + "agora", + "ainda", + "algmas", + "algo", + "algumas", + "alguns", + "ali", + "além", + "ambos", + "ano", + "anos", + "antes", + "ao", + "aos", + "apenas", + "apoio", + "apontar", + "após", + "aquela", + "aquelas", + "aquele", + "aqueles", + "aqui", + "aquilo", + "as", + "assim", + "através", + "atrás", + "até", + "aí", + "baixo", + "bastante", + "bem", + "bom", + "breve", + "cada", + "caminho", + "catorze", + "cedo", + "cento", + "certamente", + "certeza", + "cima", + "cinco", + "coisa", + "com", + "como", + "comprido", + "conhecido", + "conselho", + "contra", + "corrente", + "custa", + "cá", + "da", + "daquela", + "daquele", + "dar", + "das", + "de", + "debaixo", + "demais", + "dentro", + "depois", + "desde", + "desligado", + "dessa", + "desse", + "desta", + "deste", + "deve", + "devem", + "deverá", + "dez", + "dezanove", + "dezasseis", + "dezassete", + "dezoito", + "dia", + "diante", + "direita", + "diz", + "dizem", + "dizer", + "do", + "dois", + "dos", + "doze", + "duas", + "dá", + "dão", + "dúvida", + "e", + "ela", + "elas", + "ele", + "eles", + "em", + "embora", + "enquanto", + "entre", + "então", + "era", + "essa", + "essas", + "esse", + "esses", + "esta", + "estado", + "estar", + "estará", + "estas", + "estava", + "este", + "estes", + "esteve", + "estive", + "estivemos", + "estiveram", + "estiveste", + "estivestes", + "estou", + "está", + "estás", + "estão", + "eu", + "exemplo", + "falta", + "fará", + "favor", + "faz", + "fazeis", + "fazem", + "fazemos", + "fazer", + "fazes", + "fazia", + "faço", + "fez", + "fim", + "final", + "foi", + "fomos", + "for", + "fora", + "foram", + "forma", + "foste", + "fostes", + "fui", + "geral", + "grande", + "grandes", + "grupo", + "hoje", + "horas", + "há", + "iniciar", + "inicio", + "ir", + "irá", + "isso", + "ista", + "iste", + "isto", + "já", + "lado", + "ligado", + "local", + "logo", + "longe", + "lugar", + "lá", + "maior", + "maioria", + "maiorias", + "mais", + "mal", + "mas", + "me", + "meio", + "menor", + "menos", + "meses", + "mesmo", + "meu", + "meus", + "mil", + "minha", + "minhas", + "momento", + "muito", + "muitos", + "máximo", + "mês", + "na", + "nada", + "naquela", + "naquele", + "nas", + "nem", + "nenhuma", + "nessa", + "nesse", + "nesta", + "neste", + "no", + "noite", + "nome", + "nos", + "nossa", + "nossas", + "nosso", + "nossos", + "nova", + "nove", + "novo", + "novos", + "num", + "numa", + "nunca", + "não", + "nível", + "nós", + "número", + "o", + "obra", + "obrigada", + "obrigado", + "oitava", + "oitavo", + "oito", + "onde", + "ontem", + "onze", + "os", + "ou", + "outra", + "outras", + "outro", + "outros", + "para", + "parece", + "parte", + "partir", + "pegar", + "pela", + "pelas", + "pelo", + "pelos", + "perto", + "pessoas", + "pode", + "podem", + "poder", + "poderá", + "podia", + "ponto", + "pontos", + "por", + "porque", + "porquê", + "posição", + "possivelmente", + "posso", + "possível", + "pouca", + "pouco", + "povo", + "primeira", + "primeiro", + "promeiro", + "próprio", + "próximo", + "puderam", + "pôde", + "põe", + "põem", + "qual", + "qualquer", + "quando", + "quanto", + "quarta", + "quarto", + "quatro", + "que", + "quem", + "quer", + "quero", + "questão", + "quieto", + "quinta", + "quinto", + "quinze", + "quê", + "relação", + "sabe", + "saber", + "se", + "segunda", + "segundo", + "sei", + "seis", + "sem", + "sempre", + "ser", + "seria", + "sete", + "seu", + "seus", + "sexta", + "sexto", + "sim", + "sistema", + "sob", + "sobre", + "sois", + "somente", + "somos", + "sou", + "sua", + "suas", + "são", + "sétima", + "sétimo", + "tal", + "talvez", + "também", + "tanto", + "tarde", + "te", + "tem", + "temos", + "tempo", + "tendes", + "tenho", + "tens", + "tentar", + "tentaram", + "tente", + "tentei", + "ter", + "terceira", + "terceiro", + "teu", + "teus", + "teve", + "tipo", + "tive", + "tivemos", + "tiveram", + "tiveste", + "tivestes", + "toda", + "todas", + "todo", + "todos", + "trabalhar", + "trabalho", + "treze", + "três", + "tu", + "tua", + "tuas", + "tudo", + "tão", + "têm", + "um", + "uma", + "umas", + "uns", + "usa", + "usar", + "vai", + "vais", + "valor", + "veja", + "vem", + "vens", + "ver", + "verdade", + "verdadeiro", + "vez", + "vezes", + "viagem", + "vindo", + "vinte", + "você", + "vocês", + "vos", + "vossa", + "vossas", + "vosso", + "vossos", + "vários", + "vão", + "vêm", + "vós", + "zero", + "à", + "às", + "área", + "é", + "és", + "último", + ], + "so": [ + "aad", + "albaabkii", + "atabo", + "ay", + "ayaa", + "ayee", + "ayuu", + "dhan", + "hadana", + "in", + "inuu", + "isku", + "jiray", + "jirtay", + "ka", + "kale", + "kasoo", + "ku", + "kuu", + "lakin", + "markii", + "oo", + "si", + "soo", + "uga", + "ugu", + "uu", + "waa", + "waxa", + "waxuu", + ], + "sw": [ + "akasema", + "alikuwa", + "alisema", + "baada", + "basi", + "bila", + "cha", + "chini", + "hadi", + "hapo", + "hata", + "hivyo", + "hiyo", + "huku", + "huo", + "ili", + "ilikuwa", + "juu", + "kama", + "karibu", + "katika", + "kila", + "kima", + "kisha", + "kubwa", + "kutoka", + "kuwa", + "kwa", + "kwamba", + "kwenda", + "kwenye", + "la", + "lakini", + "mara", + "mdogo", + "mimi", + "mkubwa", + "mmoja", + "moja", + "muda", + "mwenye", + "na", + "naye", + "ndani", + "ng", + "ni", + "nini", + "nonkungu", + "pamoja", + "pia", + "sana", + "sasa", + "sauti", + "tafadhali", + "tena", + "tu", + "vile", + "wa", + "wakati", + "wake", + "walikuwa", + "wao", + "watu", + "wengine", + "wote", + "ya", + "yake", + "yangu", + "yao", + "yeye", + "yule", + "za", + "zaidi", + "zake", + ], + "ur": [ + "آئی", + "آئے", + "آج", + "آخر", + "آخرکبر", + "آدهی", + "آًب", + "آٹھ", + "آیب", + "اة", + "اخبزت", + "اختتبم", + "ادھر", + "ارد", + "اردگرد", + "ارکبى", + "اش", + "اضتعوبل", + "اضتعوبلات", + "اضطرذ", + "اضکب", + "اضکی", + "اضکے", + "اطراف", + "اغیب", + "افراد", + "الگ", + "اور", + "اوًچب", + "اوًچبئی", + "اوًچی", + "اوًچے", + "اى", + "اً", + "اًذر", + "اًہیں", + "اٹھبًب", + "اپٌب", + "اپٌے", + "اچھب", + "اچھی", + "اچھے", + "اکثر", + "اکٹھب", + "اکٹھی", + "اکٹھے", + "اکیلا", + "اکیلی", + "اکیلے", + "اگرچہ", + "اہن", + "ایطے", + "ایک", + "ب", + "ت", + "تبزٍ", + "تت", + "تر", + "ترتیت", + "تریي", + "تعذاد", + "تن", + "تو", + "توبم", + "توہی", + "توہیں", + "تٌہب", + "تک", + "تھب", + "تھوڑا", + "تھوڑی", + "تھوڑے", + "تھی", + "تھے", + "تیي", + "ثب", + "ثبئیں", + "ثبترتیت", + "ثبری", + "ثبرے", + "ثبعث", + "ثبلا", + "ثبلترتیت", + "ثبہر", + "ثدبئے", + "ثرآں", + "ثراں", + "ثرش", + "ثعذ", + "ثغیر", + "ثلٌذ", + "ثلٌذوثبلا", + "ثلکہ", + "ثي", + "ثٌب", + "ثٌبرہب", + "ثٌبرہی", + "ثٌبرہے", + "ثٌبًب", + "ثٌذ", + "ثٌذکرو", + "ثٌذکرًب", + "ثٌذی", + "ثڑا", + "ثڑوں", + "ثڑی", + "ثڑے", + "ثھر", + "ثھرا", + "ثھراہوا", + "ثھرپور", + "ثھی", + "ثہت", + "ثہتر", + "ثہتری", + "ثہتریي", + "ثیچ", + "ج", + "خب", + "خبرہب", + "خبرہی", + "خبرہے", + "خبهوظ", + "خبًب", + "خبًتب", + "خبًتی", + "خبًتے", + "خبًٌب", + "خت", + "ختن", + "خجکہ", + "خص", + "خططرذ", + "خلذی", + "خو", + "خواى", + "خوًہی", + "خوکہ", + "خٌبة", + "خگہ", + "خگہوں", + "خگہیں", + "خیطب", + "خیطبکہ", + "در", + "درخبت", + "درخہ", + "درخے", + "درزقیقت", + "درضت", + "دش", + "دفعہ", + "دلچطپ", + "دلچطپی", + "دلچطپیبں", + "دو", + "دور", + "دوراى", + "دوضرا", + "دوضروں", + "دوضری", + "دوضرے", + "دوًوں", + "دکھبئیں", + "دکھبتب", + "دکھبتی", + "دکھبتے", + "دکھبو", + "دکھبًب", + "دکھبیب", + "دی", + "دیب", + "دیتب", + "دیتی", + "دیتے", + "دیر", + "دیٌب", + "دیکھو", + "دیکھٌب", + "دیکھی", + "دیکھیں", + "دے", + "ر", + "راضتوں", + "راضتہ", + "راضتے", + "رریعہ", + "رریعے", + "رکي", + "رکھ", + "رکھب", + "رکھتب", + "رکھتبہوں", + "رکھتی", + "رکھتے", + "رکھی", + "رکھے", + "رہب", + "رہی", + "رہے", + "ز", + "زبصل", + "زبضر", + "زبل", + "زبلات", + "زبلیہ", + "زصوں", + "زصہ", + "زصے", + "زقبئق", + "زقیتیں", + "زقیقت", + "زکن", + "زکویہ", + "زیبدٍ", + "صبف", + "صسیر", + "صفر", + "صورت", + "صورتسبل", + "صورتوں", + "صورتیں", + "ض", + "ضبت", + "ضبتھ", + "ضبدٍ", + "ضبرا", + "ضبرے", + "ضبل", + "ضبلوں", + "ضت", + "ضرور", + "ضرورت", + "ضروری", + "ضلطلہ", + "ضوچ", + "ضوچب", + "ضوچتب", + "ضوچتی", + "ضوچتے", + "ضوچو", + "ضوچٌب", + "ضوچی", + "ضوچیں", + "ضکب", + "ضکتب", + "ضکتی", + "ضکتے", + "ضکٌب", + "ضکی", + "ضکے", + "ضیذھب", + "ضیذھی", + "ضیذھے", + "ضیکٌڈ", + "ضے", + "طرف", + "طریق", + "طریقوں", + "طریقہ", + "طریقے", + "طور", + "طورپر", + "ظبہر", + "ع", + "عذد", + "عظین", + "علاقوں", + "علاقہ", + "علاقے", + "علاوٍ", + "عووهی", + "غبیذ", + "غخص", + "غذ", + "غروع", + "غروعبت", + "غے", + "فرد", + "فی", + "ق", + "قجل", + "قجیلہ", + "قطن", + "لئے", + "لا", + "لازهی", + "لو", + "لوجب", + "لوجی", + "لوجے", + "لوسبت", + "لوسہ", + "لوگ", + "لوگوں", + "لڑکپي", + "لگتب", + "لگتی", + "لگتے", + "لگٌب", + "لگی", + "لگیں", + "لگے", + "لی", + "لیب", + "لیٌب", + "لیں", + "لے", + "ه", + "هتعلق", + "هختلف", + "هسترم", + "هسترهہ", + "هسطوش", + "هسیذ", + "هطئلہ", + "هطئلے", + "هطبئل", + "هطتعول", + "هطلق", + "هعلوم", + "هػتول", + "هلا", + "هوکي", + "هوکٌبت", + "هوکٌہ", + "هٌبضت", + "هڑا", + "هڑًب", + "هڑے", + "هکول", + "هگر", + "هہرثبى", + "هیرا", + "هیری", + "هیرے", + "هیں", + "و", + "وار", + "والے", + "وٍ", + "ًئی", + "ًئے", + "ًب", + "ًبپطٌذ", + "ًبگسیر", + "ًطجت", + "ًقطہ", + "ًو", + "ًوخواى", + "ًکبلٌب", + "ًکتہ", + "ًہ", + "ًہیں", + "ًیب", + "ًے", + "ٓ آش", + "ٹھیک", + "پبئے", + "پبش", + "پبًب", + "پبًچ", + "پر", + "پراًب", + "پطٌذ", + "پل", + "پورا", + "پوچھب", + "پوچھتب", + "پوچھتی", + "پوچھتے", + "پوچھو", + "پوچھوں", + "پوچھٌب", + "پوچھیں", + "پچھلا", + "پھر", + "پہلا", + "پہلی", + "پہلےضی", + "پہلےضے", + "پہلےضےہی", + "پیع", + "چبر", + "چبہب", + "چبہٌب", + "چبہے", + "چلا", + "چلو", + "چلیں", + "چلے", + "چکب", + "چکی", + "چکیں", + "چکے", + "چھوٹب", + "چھوٹوں", + "چھوٹی", + "چھوٹے", + "چھہ", + "چیسیں", + "ڈھوًڈا", + "ڈھوًڈلیب", + "ڈھوًڈو", + "ڈھوًڈًب", + "ڈھوًڈی", + "ڈھوًڈیں", + "ک", + "کئی", + "کئے", + "کب", + "کبفی", + "کبم", + "کت", + "کجھی", + "کرا", + "کرتب", + "کرتبہوں", + "کرتی", + "کرتے", + "کرتےہو", + "کررہب", + "کررہی", + "کررہے", + "کرو", + "کرًب", + "کریں", + "کرے", + "کطی", + "کل", + "کن", + "کوئی", + "کوتر", + "کورا", + "کوروں", + "کورٍ", + "کورے", + "کوطي", + "کوى", + "کوًطب", + "کوًطی", + "کوًطے", + "کھولا", + "کھولو", + "کھولٌب", + "کھولی", + "کھولیں", + "کھولے", + "کہ", + "کہب", + "کہتب", + "کہتی", + "کہتے", + "کہو", + "کہوں", + "کہٌب", + "کہی", + "کہیں", + "کہے", + "کی", + "کیب", + "کیطب", + "کیطرف", + "کیطے", + "کیلئے", + "کیوًکہ", + "کیوں", + "کیے", + "کے", + "کےثعذ", + "کےرریعے", + "گئی", + "گئے", + "گب", + "گرد", + "گروٍ", + "گروپ", + "گروہوں", + "گٌتی", + "گی", + "گیب", + "گے", + "ہر", + "ہن", + "ہو", + "ہوئی", + "ہوئے", + "ہوا", + "ہوبرا", + "ہوبری", + "ہوبرے", + "ہوتب", + "ہوتی", + "ہوتے", + "ہورہب", + "ہورہی", + "ہورہے", + "ہوضکتب", + "ہوضکتی", + "ہوضکتے", + "ہوًب", + "ہوًی", + "ہوًے", + "ہوچکب", + "ہوچکی", + "ہوچکے", + "ہوگئی", + "ہوگئے", + "ہوگیب", + "ہوں", + "ہی", + "ہیں", + "ہے", + "ی", + "یقیٌی", + "یہ", + "یہبں", + ], + "vi": [ + "a ha", + "a-lô", + "ai", + "ai ai", + "ai nấy", + "alô", + "amen", + "anh", + "bao giờ", + "bao lâu", + "bao nhiêu", + "bao nả", + "bay biến", + "biết", + "biết bao", + "biết bao nhiêu", + "biết chừng nào", + "biết mấy", + "biết đâu", + "biết đâu chừng", + "biết đâu đấy", + "bà", + "bài", + "bác", + "bây bẩy", + "bây chừ", + "bây giờ", + "bây nhiêu", + "bèn", + "béng", + "bông", + "bạn", + "bản", + "bất chợt", + "bất cứ", + "bất giác", + "bất kì", + "bất kể", + "bất kỳ", + "bất luận", + "bất nhược", + "bất quá", + "bất thình lình", + "bất tử", + "bất đồ", + "bấy", + "bấy chầy", + "bấy chừ", + "bấy giờ", + "bấy lâu", + "bấy lâu nay", + "bấy nay", + "bấy nhiêu", + "bập bà bập bõm", + "bập bõm", + "bắt đầu từ", + "bằng", + "bằng không", + "bằng nấy", + "bằng ấy", + "bển", + "bệt", + "bị", + "bỏ mẹ", + "bỗng", + "bỗng chốc", + "bỗng dưng", + "bỗng không", + "bỗng nhiên", + "bỗng đâu", + "bộ", + "bội phần", + "bớ", + "bởi", + "bởi chưng", + "bởi nhưng", + "bởi thế", + "bởi vì", + "bởi vậy", + "bức", + "cao", + "cha", + "cha chả", + "chao ôi", + "chiếc", + "cho", + "cho nên", + "cho tới", + "cho tới khi", + "cho đến", + "cho đến khi", + "choa", + "chu cha", + "chui cha", + "chung cục", + "chung qui", + "chung quy", + "chung quy lại", + "chuyện", + "chành chạnh", + "chí chết", + "chính", + "chính là", + "chính thị", + "chùn chùn", + "chùn chũn", + "chú", + "chú mày", + "chú mình", + "chúng mình", + "chúng ta", + "chúng tôi", + "chăn chắn", + "chăng", + "chưa", + "chầm chập", + "chậc", + "chắc", + "chắc hẳn", + "chẳng lẽ", + "chẳng những", + "chẳng nữa", + "chẳng phải", + "chết nỗi", + "chết thật", + "chết tiệt", + "chỉ", + "chỉn", + "chốc chốc", + "chớ", + "chớ chi", + "chợt", + "chủn", + "chứ", + "chứ lị", + "coi bộ", + "coi mòi", + "con", + "cu cậu", + "cuốn", + "cuộc", + "càng", + "các", + "cái", + "cây", + "còn", + "có", + "có chăng là", + "có dễ", + "có thể", + "có vẻ", + "cóc khô", + "cô", + "cô mình", + "công nhiên", + "cùng", + "cùng cực", + "cùng nhau", + "cùng với", + "căn", + "căn cắt", + "cũng", + "cũng như", + "cũng vậy", + "cũng vậy thôi", + "cơ", + "cơ chừng", + "cơ hồ", + "cơ mà", + "cơn", + "cả", + "cả thảy", + "cả thể", + "cảm ơn", + "cần", + "cật lực", + "cật sức", + "cậu", + "cổ lai", + "của", + "cứ", + "cứ việc", + "cực lực", + "do", + "do vì", + "do vậy", + "do đó", + "duy", + "dào", + "dì", + "dù cho", + "dù rằng", + "dưới", + "dạ", + "dần dà", + "dần dần", + "dầu sao", + "dẫu", + "dẫu sao", + "dễ sợ", + "dễ thường", + "dở chừng", + "dữ", + "em", + "giữa", + "gì", + "hay", + "hoàn toàn", + "hoặc", + "hơn", + "hầu hết", + "họ", + "hỏi", + "khi", + "khác", + "không", + "luôn", + "là", + "làm", + "lên", + "lúc", + "lại", + "lần", + "lớn", + "muốn", + "mà", + "mình", + "mỗi", + "một", + "một cách", + "mới", + "mợ", + "ngay", + "ngay cả", + "ngay khi", + "ngay lúc", + "ngay lập tức", + "ngay tức khắc", + "ngay từ", + "nghe chừng", + "nghe đâu", + "nghen", + "nghiễm nhiên", + "nghỉm", + "ngoài", + "ngoài ra", + "ngoải", + "ngày", + "ngày càng", + "ngày ngày", + "ngày xưa", + "ngày xửa", + "ngôi", + "ngõ hầu", + "ngăn ngắt", + "ngươi", + "người", + "ngọn", + "ngọt", + "ngộ nhỡ", + "nh", + "nhau", + "nhiên hậu", + "nhiều", + "nhiệt liệt", + "nhung nhăng", + "nhà", + "nhân dịp", + "nhân tiện", + "nhé", + "nhón nhén", + "như", + "như chơi", + "như không", + "như quả", + "như thể", + "như tuồng", + "như vậy", + "nhưng", + "nhưng mà", + "nhược bằng", + "nhất", + "nhất loạt", + "nhất luật", + "nhất mực", + "nhất nhất", + "nhất quyết", + "nhất sinh", + "nhất thiết", + "nhất tâm", + "nhất tề", + "nhất đán", + "nhất định", + "nhận", + "nhỉ", + "nhỡ ra", + "những", + "những ai", + "những như", + "nào", + "này", + "nên", + "nên chi", + "nó", + "nóc", + "nói", + "năm", + "nơi", + "nấy", + "nếu", + "nếu như", + "nền", + "nọ", + "nớ", + "nức nở", + "nữa", + "oai oái", + "oái", + "pho", + "phè", + "phóc", + "phót", + "phăn phắt", + "phương chi", + "phải", + "phải chi", + "phải chăng", + "phắt", + "phỉ phui", + "phỏng", + "phỏng như", + "phốc", + "phụt", + "phứt", + "qua", + "qua quít", + "qua quýt", + "quyết", + "quyết nhiên", + "quyển", + "quá", + "quá chừng", + "quá lắm", + "quá sá", + "quá thể", + "quá trời", + "quá xá", + "quá đỗi", + "quá độ", + "quá ư", + "quý hồ", + "quả", + "quả là", + "quả tang", + "quả thật", + "quả tình", + "quả vậy", + "quả đúng", + "ra", + "ra phết", + "ra sao", + "ra trò", + "ren rén", + "riu ríu", + "riêng", + "riệt", + "rày", + "ráo", + "ráo trọi", + "rén", + "rích", + "rón rén", + "rút cục", + "răng", + "rất", + "rằng", + "rằng là", + "rốt cuộc", + "rốt cục", + "rồi", + "rứa", + "sa sả", + "sao", + "sau", + "sau chót", + "sau cuối", + "sau cùng", + "sau đó", + "so", + "song le", + "suýt", + "sì", + "sạch", + "sất", + "sắp", + "sẽ", + "số", + "số là", + "sốt sột", + "sở dĩ", + "sự", + "tanh", + "tha hồ", + "than ôi", + "thanh", + "theo", + "thi thoảng", + "thoạt", + "thoạt nhiên", + "thoắt", + "thuần", + "thà", + "thà là", + "thà rằng", + "thành ra", + "thành thử", + "thái quá", + "tháng", + "thì", + "thì thôi", + "thình lình", + "thím", + "thôi", + "thúng thắng", + "thương ôi", + "thường", + "thảo hèn", + "thảo nào", + "thấy", + "thẩy", + "thậm", + "thậm chí", + "thật lực", + "thật ra", + "thật vậy", + "thế", + "thế là", + "thế mà", + "thế nào", + "thế nên", + "thế ra", + "thế thì", + "thế à", + "thếch", + "thỉnh thoảng", + "thỏm", + "thốc", + "thốc tháo", + "thốt", + "thốt nhiên", + "thộc", + "thời gian", + "thục mạng", + "thửa", + "thực ra", + "thực sự", + "thực vậy", + "tiếp theo", + "tiếp đó", + "tiện thể", + "toà", + "toé khói", + "toẹt", + "trong", + "trên", + "trước", + "trước kia", + "trước nay", + "trước tiên", + "trước đây", + "trước đó", + "trếu tráo", + "trển", + "trệt", + "trệu trạo", + "trỏng", + "trời đất ơi", + "trừ phi", + "tuy", + "tuy nhiên", + "tuy rằng", + "tuy thế", + "tuy vậy", + "tuyệt nhiên", + "tuần tự", + "tuốt luốt", + "tuốt tuồn tuột", + "tuốt tuột", + "tà tà", + "tênh", + "tít mù", + "tò te", + "tôi", + "tông tốc", + "tù tì", + "tăm tắp", + "tại", + "tại vì", + "tấm", + "tấn", + "tất cả", + "tất thảy", + "tất tần tật", + "tất tật", + "tắp", + "tắp lự", + "tọt", + "tỏ ra", + "tỏ vẻ", + "tốc tả", + "tối ư", + "tột", + "tớ", + "tới", + "tức thì", + "tức tốc", + "từ", + "từng", + "tự vì", + "tựu trung", + "veo", + "veo veo", + "việc", + "vung thiên địa", + "vung tàn tán", + "vung tán tàn", + "và", + "vào", + "vâng", + "vèo", + "vì", + "vì chưng", + "vì thế", + "vì vậy", + "ví bằng", + "ví dù", + "ví phỏng", + "ví thử", + "vô hình trung", + "vô kể", + "vô luận", + "vô vàn", + "văng tê", + "vạn nhất", + "vả chăng", + "vả lại", + "vẫn", + "vậy", + "vậy là", + "vậy thì", + "về", + "vị tất", + "vốn dĩ", + "với", + "với lại", + "vở", + "vụt", + "vừa", + "vừa mới", + "xa xả", + "xiết bao", + "xon xón", + "xoành xoạch", + "xoét", + "xoẳn", + "xoẹt", + "xuất kì bất ý", + "xuất kỳ bất ý", + "xuể", + "xuống", + "xăm xúi", + "xăm xăm", + "xăm xắm", + "xềnh xệch", + "xệp", + "à", + "à ơi", + "ào", + "á", + "á à", + "ái", + "ái chà", + "ái dà", + "áng", + "âu là", + "ô hay", + "ô hô", + "ô kê", + "ô kìa", + "ôi chao", + "ôi thôi", + "ông", + "úi", + "úi chà", + "úi dào", + "ý", + "ý chừng", + "ý da", + "đang", + "đi", + "điều", + "đành đạch", + "đáng lí", + "đáng lý", + "đáng lẽ", + "đánh đùng", + "đáo để", + "đây", + "đã", + "đó", + "được", + "đại loại", + "đại nhân", + "đại phàm", + "đại để", + "đến", + "đến nỗi", + "đều", + "để", + "ơ", + "ơ hay", + "ơ kìa", + "ơi", + "ư", + "ạ", + "ạ ơi", + "ấy", + "ầu ơ", + "ắt", + "ắt hẳn", + "ắt là", + "ối dào", + "ối giời", + "ối giời ơi", + "ồ", + "ổng", + "ớ", + "ờ", + "ở", + "ở trên", + "ủa", + "ứ hự", + "ứ ừ", + "ừ", + "ử", + ], + "yo": [ + "a", + "an", + "bá", + "bí", + "bẹ̀rẹ̀", + "fún", + "fẹ́", + "gbogbo", + "inú", + "jù", + "jẹ", + "jẹ́", + "kan", + "kì", + "kí", + "kò", + "láti", + "lè", + "lọ", + "mi", + "mo", + "máa", + "mọ̀", + "ni", + "náà", + "ní", + "nígbà", + "nítorí", + "nǹkan", + "o", + "padà", + "pé", + "púpọ̀", + "pẹ̀lú", + "rẹ̀", + "sì", + "sí", + "sínú", + "ṣ", + "ti", + "tí", + "wà", + "wá", + "wọn", + "wọ́n", + "yìí", + "àti", + "àwọn", + "é", + "í", + "òun", + "ó", + "ń", + "ńlá", + "ṣe", + "ṣé", + "ṣùgbọ́n", + "ẹmọ́", + "ọjọ́", + "ọ̀pọ̀lọpọ̀", + ], + "zh": [ + "、", + "。", + "〈", + "〉", + "《", + "》", + "一", + "一切", + "一则", + "一方面", + "一旦", + "一来", + "一样", + "一般", + "七", + "万一", + "三", + "上下", + "不仅", + "不但", + "不光", + "不单", + "不只", + "不如", + "不怕", + "不惟", + "不成", + "不拘", + "不比", + "不然", + "不特", + "不独", + "不管", + "不论", + "不过", + "不问", + "与", + "与其", + "与否", + "与此同时", + "且", + "两者", + "个", + "临", + "为", + "为了", + "为什么", + "为何", + "为着", + "乃", + "乃至", + "么", + "之", + "之一", + "之所以", + "之类", + "乌乎", + "乎", + "乘", + "九", + "也", + "也好", + "也罢", + "了", + "二", + "于", + "于是", + "于是乎", + "云云", + "五", + "人家", + "什么", + "什么样", + "从", + "从而", + "他", + "他人", + "他们", + "以", + "以便", + "以免", + "以及", + "以至", + "以至于", + "以致", + "们", + "任", + "任何", + "任凭", + "似的", + "但", + "但是", + "何", + "何况", + "何处", + "何时", + "作为", + "你", + "你们", + "使得", + "例如", + "依", + "依照", + "俺", + "俺们", + "倘", + "倘使", + "倘或", + "倘然", + "倘若", + "借", + "假使", + "假如", + "假若", + "像", + "八", + "六", + "兮", + "关于", + "其", + "其一", + "其中", + "其二", + "其他", + "其余", + "其它", + "其次", + "具体地说", + "具体说来", + "再者", + "再说", + "冒", + "冲", + "况且", + "几", + "几时", + "凭", + "凭借", + "则", + "别", + "别的", + "别说", + "到", + "前后", + "前者", + "加之", + "即", + "即令", + "即使", + "即便", + "即或", + "即若", + "又", + "及", + "及其", + "及至", + "反之", + "反过来", + "反过来说", + "另", + "另一方面", + "另外", + "只是", + "只有", + "只要", + "只限", + "叫", + "叮咚", + "可", + "可以", + "可是", + "可见", + "各", + "各个", + "各位", + "各种", + "各自", + "同", + "同时", + "向", + "向着", + "吓", + "吗", + "否则", + "吧", + "吧哒", + "吱", + "呀", + "呃", + "呕", + "呗", + "呜", + "呜呼", + "呢", + "呵", + "呸", + "呼哧", + "咋", + "和", + "咚", + "咦", + "咱", + "咱们", + "咳", + "哇", + "哈", + "哈哈", + "哉", + "哎", + "哎呀", + "哎哟", + "哗", + "哟", + "哦", + "哩", + "哪", + "哪个", + "哪些", + "哪儿", + "哪天", + "哪年", + "哪怕", + "哪样", + "哪边", + "哪里", + "哼", + "哼唷", + "唉", + "啊", + "啐", + "啥", + "啦", + "啪达", + "喂", + "喏", + "喔唷", + "嗡嗡", + "嗬", + "嗯", + "嗳", + "嘎", + "嘎登", + "嘘", + "嘛", + "嘻", + "嘿", + "四", + "因", + "因为", + "因此", + "因而", + "固然", + "在", + "在下", + "地", + "多", + "多少", + "她", + "她们", + "如", + "如上所述", + "如何", + "如其", + "如果", + "如此", + "如若", + "宁", + "宁可", + "宁愿", + "宁肯", + "它", + "它们", + "对", + "对于", + "将", + "尔后", + "尚且", + "就", + "就是", + "就是说", + "尽", + "尽管", + "岂但", + "己", + "并", + "并且", + "开外", + "开始", + "归", + "当", + "当着", + "彼", + "彼此", + "往", + "待", + "得", + "怎", + "怎么", + "怎么办", + "怎么样", + "怎样", + "总之", + "总的来看", + "总的来说", + "总的说来", + "总而言之", + "恰恰相反", + "您", + "慢说", + "我", + "我们", + "或", + "或是", + "或者", + "所", + "所以", + "打", + "把", + "抑或", + "拿", + "按", + "按照", + "换句话说", + "换言之", + "据", + "接着", + "故", + "故此", + "旁人", + "无宁", + "无论", + "既", + "既是", + "既然", + "时候", + "是", + "是的", + "替", + "有", + "有些", + "有关", + "有的", + "望", + "朝", + "朝着", + "本", + "本着", + "来", + "来着", + "极了", + "果然", + "果真", + "某", + "某个", + "某些", + "根据", + "正如", + "此", + "此外", + "此间", + "毋宁", + "每", + "每当", + "比", + "比如", + "比方", + "沿", + "沿着", + "漫说", + "焉", + "然则", + "然后", + "然而", + "照", + "照着", + "甚么", + "甚而", + "甚至", + "用", + "由", + "由于", + "由此可见", + "的", + "的话", + "相对而言", + "省得", + "着", + "着呢", + "矣", + "离", + "第", + "等", + "等等", + "管", + "紧接着", + "纵", + "纵令", + "纵使", + "纵然", + "经", + "经过", + "结果", + "给", + "继而", + "综上所述", + "罢了", + "者", + "而", + "而且", + "而况", + "而外", + "而已", + "而是", + "而言", + "能", + "腾", + "自", + "自个儿", + "自从", + "自各儿", + "自家", + "自己", + "自身", + "至", + "至于", + "若", + "若是", + "若非", + "莫若", + "虽", + "虽则", + "虽然", + "虽说", + "被", + "要", + "要不", + "要不是", + "要不然", + "要么", + "要是", + "让", + "论", + "设使", + "设若", + "该", + "诸位", + "谁", + "谁知", + "赶", + "起", + "起见", + "趁", + "趁着", + "越是", + "跟", + "较", + "较之", + "边", + "过", + "还是", + "还有", + "这", + "这个", + "这么", + "这么些", + "这么样", + "这么点儿", + "这些", + "这会儿", + "这儿", + "这就是说", + "这时", + "这样", + "这边", + "这里", + "进而", + "连", + "连同", + "通过", + "遵照", + "那", + "那个", + "那么", + "那么些", + "那么样", + "那些", + "那会儿", + "那儿", + "那时", + "那样", + "那边", + "那里", + "鄙人", + "鉴于", + "阿", + "除", + "除了", + "除此之外", + "除非", + "随", + "随着", + "零", + "非但", + "非徒", + "靠", + "顺", + "顺着", + "首先", + "︿", + "！", + "＃", + "＄", + "％", + "＆", + "（", + "）", + "＊", + "＋", + "，", + "０", + "１", + "２", + "３", + "４", + "５", + "６", + "７", + "８", + "９", + "：", + "；", + "＜", + "＞", + "？", + "＠", + "［", + "］", + "｛", + "｜", + "｝", + "～", + "￥", + ], +} diff --git a/data_tooling/ac_dc/visualization/README.md b/data_tooling/ac_dc/visualization/README.md new file mode 100644 index 0000000..377f319 --- /dev/null +++ b/data_tooling/ac_dc/visualization/README.md @@ -0,0 +1,10 @@ +# Visualization tool + +Use this visualization tool online at https://huggingface.co/spaces/huggingface/text-data-filtering. + +However, by running the code on your computer, it is faster, it can handle in practice up to three times more documents, and it works for every language. + +1) Use get_data_for_visualization.py to get the json gathering examples with their computed statistics for the language you chose. +It uses the streaming mode of the Datasets library, so no need to download the dataset, but you have to download the fasttext model (for the language identification) and the kenlm / sentencepiece models (for the perplexity). + +2) Specify the path to this json in visualization.py and run the command "streamlit run visualization.py". diff --git a/data_tooling/ac_dc/visualization/get_data_for_visualization.py b/data_tooling/ac_dc/visualization/get_data_for_visualization.py new file mode 100644 index 0000000..e52c8d6 --- /dev/null +++ b/data_tooling/ac_dc/visualization/get_data_for_visualization.py @@ -0,0 +1,185 @@ +from datasets import load_dataset +from tqdm import tqdm +import json + +import os +import sys + +sys.path.insert(1, os.path.join(sys.path[0], "..")) + +from filtering import LoadParameters, ModifyingDocuments, Filtering + + +class GetDataForVisualization: + def __init__( + self, + dataset, + num_iter, + lang_dataset_id, + path_fasttext_model, + path_sentencepiece_model, + path_kenlm_model, + path_save_stats, + ): + + self.ds = dataset + self.num_iter = num_iter + + self.lang_dataset_id = lang_dataset_id + + self.param = LoadParameters.load_parameters(lang_dataset_id) + self.stopwords = LoadParameters.load_stopwords(lang_dataset_id) + self.badwords = LoadParameters.load_badwords(lang_dataset_id) + self.model_lang_id = LoadParameters.load_model_lang_id( + lang_dataset_id, path_fasttext_model + ) + self.sentencepiece_model = LoadParameters.load_sentencepiece_model( + lang_dataset_id, path_sentencepiece_model + ) + self.sentencepiece_model_tok = ( + self.sentencepiece_model if self.param["tokenization"] else None + ) + self.kenlm_model = LoadParameters.load_kenlm_model( + lang_dataset_id, path_kenlm_model + ) + + self.keys_stats = [ + "special_characters_ratio", + "stopwords_ratio", + "badwords_ratio", + "lang_id_score", + "perplexity_score", + ] + self.path_save_stats = path_save_stats + + def compute_stats(self): + dataset = iter(self.ds) + stats = [] + num_iter_examples = True + for i in tqdm(range(self.num_iter)): + stats_document = {} + + try: + document = next(dataset)["text"] + + words = ModifyingDocuments.get_words_from_document( + document, + sentencepiece_model_tok=self.sentencepiece_model_tok, + lower_case=True, + strip_characters=self.param["strip_characters"], + ) + words = [ + { + "len_word": len(word), + "incorrect_substring": any( + [ + (i_substr in word) + for i_substr in self.param["incorrect_word_substrings"] + ] + ), + "word": word, + } + for word in words + ] + + if not self.param["tokenization"]: + stats_document["words"] = words + + number_words = len(words) + stats_document["number_words"] = number_words + + repetitions_ratios = { + n: round(Filtering.compute_repetitions_ratio(document, n), 4) + for n in range(2, 16) + } + stats_document["repetitions_ratio"] = repetitions_ratios + + special_characters_ratio = Filtering.compute_special_characters_ratio( + document, self.param["special_characters"] + ) + stats_document["special_characters_ratio"] = special_characters_ratio + + if self.stopwords: + stopwords_ratio = Filtering.compute_stopwords_ratio( + document, + self.sentencepiece_model_tok, + self.param["strip_characters"], + self.param["cond_words_augmentation"], + self.param["words_augmentation_group_sizes"], + self.param["words_augmentation_join_char"], + self.stopwords, + ) + stats_document["stopwords_ratio"] = stopwords_ratio + + if self.badwords: + badwords_ratio = Filtering.compute_badwords_ratio( + document, + self.sentencepiece_model_tok, + self.param["strip_characters"], + self.param["cond_words_augmentation"], + self.param["words_augmentation_group_sizes"], + self.param["words_augmentation_join_char"], + self.badwords, + ) + stats_document["badwords_ratio"] = badwords_ratio + + if self.model_lang_id: + _, lang_id_score = Filtering.compute_lang_id_pred_score( + document, self.model_lang_id + ) + stats_document["lang_id_score"] = lang_id_score + + if self.kenlm_model: + perplexity_score = Filtering.compute_perplexity_score( + document, self.sentencepiece_model, self.kenlm_model + ) + stats_document["perplexity_score"] = perplexity_score + + stats_document["text"] = document + + stats.append(stats_document) + + except: + num_iter_examples = False + + if not num_iter_examples: + print("Warning: num_iter is greater than the size of the dataset.") + + self.stats = stats + + with open(self.path_save_stats, "w") as f: + json.dump(self.stats, f) + + +if __name__ == "__main__": + + dataset_name = "oscar" + config_name = "unshuffled_deduplicated_en" + data_files = None + split = "train" + num_iter = 15000 + + lang_dataset_id = "en" + path_fasttext_model = "ac_dc/lid.176.bin" + path_sentencepiece_model = f"ac_dc/en.sp.model" + path_kenlm_model = f"ac_dc/en.arpa.bin" + path_save_stats = f"ac_dc/visualization/en_examples_with_stats.json" + + dataset = load_dataset( + dataset_name, + config_name, + data_files=data_files, + split=split, + streaming=True, + ).shuffle(buffer_size=num_iter, seed=42) + + get_data_for_visualization = GetDataForVisualization( + dataset, + num_iter, + lang_dataset_id, + path_fasttext_model, + path_sentencepiece_model, + path_kenlm_model, + path_save_stats, + ) + get_data_for_visualization.compute_stats() diff --git a/data_tooling/ac_dc/visualization/visualization.py b/data_tooling/ac_dc/visualization/visualization.py new file mode 100644 index 0000000..c92a37e --- /dev/null +++ b/data_tooling/ac_dc/visualization/visualization.py @@ -0,0 +1,427 @@ +# Run with: streamlit run visualization.py + +import streamlit as st + +import os + +import base64 +import json +import pandas as pd +pd.options.mode.chained_assignment = None + +import numpy as np + +import matplotlib.pyplot as plt + + +class Visualization: + def __init__( + self, + path_instructions, + path_data, + lang, + num_docs, + num_docs_for_words, + max_len_text_display, + ): + self.path_instructions = path_instructions + self.path_data = path_data + self.lang = lang + self.num_docs = num_docs + self.num_docs_for_words = num_docs_for_words + self.max_len_text_display = max_len_text_display + + def preamble(self): + st.markdown( + "Before diving into this demo, you might want to take a look at how the filtering pipeline looks like in more detail." + ) + + def get_binary_file_downloader_html(bin_file, file_label="File"): + with open(bin_file, "rb") as f: + data = f.read() + bin_str = base64.b64encode(data).decode() + href = f'{file_label}' + return href + + st.markdown( + get_binary_file_downloader_html( + self.path_instructions, + "Download the explanation of the filtering pipeline as pdf", + ), + unsafe_allow_html=True, + ) + + def open_data(self): + with open(self.path_data) as json_file: + data = json.load(json_file) + + self.num_docs = min(self.num_docs, len(data)) + self.num_docs_for_words = min(self.num_docs_for_words, len(data)) + + if "words" in data[0]: + words = [doc["words"] for doc in data[: self.num_docs_for_words]] + words = [word for doc in words for word in doc] + self.words = pd.DataFrame(words) + else: + self.words = None + + docs = data[: self.num_docs] + for doc in docs: + if not (self.words is None): + del doc["words"] + if len(doc["text"]) > self.max_len_text_display: + doc["text"] = ( + doc["text"][: self.max_len_text_display] + + " [...] [THIS LONG TEXT HAS BEEN TRUNCATED FOR DISPLAY REASONS]" + ) + self.docs_checkpoint = pd.DataFrame(docs) + self.docs = self.docs_checkpoint + + def set_title(self): + st.title(f"{self.num_docs} {self.lang} documents with their stats.") + + def filtering_of_docs(self): + st.sidebar.subheader("Parameters of the filtering on documents") + + def set_sliders(): + columns = list(self.docs) + keys = [] + conds = {} + + def get_cond(key, cutoff, max_cutoff): + if max_cutoff: + return self.docs[key] <= cutoff + return self.docs[key] >= cutoff + + def print_discared_by_cond(cond): + st.sidebar.caption( + f"{(len(cond) - np.sum(1*cond)) / len(cond) * 100:.2f}% of the total is discarded with this filter." + ) + st.sidebar.caption("---------") + + if "number_words" in columns: + cutoff_def = "If the number of words of a document is lower than this number, the document is removed." + max_nb_words = int(np.max(self.docs["number_words"])) + 1 + cutoff_min_number_words = st.sidebar.slider( + cutoff_def, 0, min(max_nb_words, 500), 0 + ) + new_key = ("number_words", cutoff_min_number_words, False) + keys.append(new_key) + cond_1 = get_cond(new_key[0], new_key[1], new_key[2]) + print_discared_by_cond(cond_1) + + cutoff_def = "If the number of words of a document is higher than this number, the document is removed." + cutoff_max_number_words = st.sidebar.slider( + cutoff_def, 0, max_nb_words, max_nb_words + ) + new_key = ("number_words", cutoff_max_number_words, True) + keys.append(new_key) + cond_2 = get_cond(new_key[0], new_key[1], new_key[2]) + print_discared_by_cond(cond_2) + + conds["number_words"] = [cond_1, cond_2] + + if "repetitions_ratio" in columns: + val_repetitions_lengths = list( + self.docs["repetitions_ratio"].iloc[0].keys() + ) + default_index = ( + val_repetitions_lengths.index("10") + if "10" in val_repetitions_lengths + else 0 + ) + label_selectbox = ( + "Length of the repetitions (that will determine the repetitions ratio). " + "Choosing a higher or lower number does not mean that the filtering " + "is stronger or weaker. Be careful, choosing a low number (below 5 for languages like English) " + "tends to associate a high repetitions ratio to very long documents (like book chapters), but with " + "few or no repetitions, simply because their length gives them more diversity, and we do " + "not want to discard such documents." + ) + repetitions_length = st.sidebar.selectbox( + label=label_selectbox, + options=val_repetitions_lengths, + index=default_index, + ) + self.docs = self.docs_checkpoint + for i in range(len(self.docs["repetitions_ratio"])): + self.docs["repetitions_ratio"].iloc[i] = self.docs["repetitions_ratio"].iloc[i][repetitions_length] + + cutoff_def = "If the repetitions ratio of a document is higher than this number, the document is removed." + cutoff_repetitions_ratio = st.sidebar.slider( + cutoff_def, 0.0, 1.0, 1.0, step=0.01 + ) + new_key = ( + "repetitions_ratio", + cutoff_repetitions_ratio, + True, + ) + keys.append(new_key) + cond = get_cond(new_key[0], new_key[1], new_key[2]) + print_discared_by_cond(cond) + conds["repetitions_ratio"] = [cond] + + if "special_characters_ratio" in columns: + cutoff_def = "If the special characters ratio of a document is higher than this number, the document is removed." + cutoff_special_characters_ratio = st.sidebar.slider( + cutoff_def, 0.0, 1.0, 1.0, step=0.01 + ) + new_key = ( + "special_characters_ratio", + cutoff_special_characters_ratio, + True, + ) + keys.append(new_key) + cond = get_cond(new_key[0], new_key[1], new_key[2]) + print_discared_by_cond(cond) + conds["special_characters_ratio"] = [cond] + + if "stopwords_ratio" in columns: + cutoff_def = "If the stop words ratio of a document is lower than this number, the document is removed." + cutoff_stopwords_ratio = st.sidebar.slider( + cutoff_def, 0.0, 1.0, 0.0, step=0.01 + ) + new_key = ("stopwords_ratio", cutoff_stopwords_ratio, False) + keys.append(new_key) + cond = get_cond(new_key[0], new_key[1], new_key[2]) + print_discared_by_cond(cond) + conds["stopwords_ratio"] = [cond] + + if "badwords_ratio" in columns: + cutoff_def = "If the bad words ratio of a document is higher than this number, the document is removed." + cutoff_badwords_ratio = st.sidebar.slider( + cutoff_def, 0.0, 1.0, 1.0, step=0.01 + ) + new_key = ("badwords_ratio", cutoff_badwords_ratio, True) + keys.append(new_key) + cond = get_cond(new_key[0], new_key[1], new_key[2]) + print_discared_by_cond(cond) + conds["badwords_ratio"] = [cond] + + if "lang_id_score" in columns: + cutoff_def = "If the confidence score for the language identification prediction of a document is lower than this number, the document is removed." + cutoff_lang_id_score = st.sidebar.slider( + cutoff_def, 0.0, 1.0, 0.0, step=0.01 + ) + new_key = ("lang_id_score", cutoff_lang_id_score, False) + keys.append(new_key) + cond = get_cond(new_key[0], new_key[1], new_key[2]) + print_discared_by_cond(cond) + conds["lang_id_score"] = [cond] + + if "perplexity_score" in columns: + cutoff_def = "If the perplexity score of a document is higher than this number, the document is removed." + max_pp = int(np.max(self.docs["perplexity_score"])) + 1 + cutoff_perplexity_score = st.sidebar.slider( + cutoff_def, 0, max_pp, max_pp + ) + new_key = ("perplexity_score", cutoff_perplexity_score, True) + keys.append(new_key) + cond = get_cond(new_key[0], new_key[1], new_key[2]) + print_discared_by_cond(cond) + conds["perplexity_score"] = [cond] + + return keys, conds + + self.keys, conds = set_sliders() + + all_conds = [subcond for cond in list(conds.values()) for subcond in cond] + all_conds = np.all(all_conds, axis=0) + + st.header("Filtering on documents") + + def display_dataset(cond, description): + displayed_docs = self.docs.loc[cond] + st.subheader( + f"{description}: {len(displayed_docs)} docs ({len(displayed_docs) / self.num_docs * 100:.2f}%)" + ) + st.markdown( + "Click on a column to sort by it, place the cursor on the text to display it." + ) + st.dataframe(displayed_docs) + + display_dataset(np.invert(all_conds), "Discarded documents") + + # st.subheader("Display discarded documents by filter") + display_discarded_documents_by_filter = st.checkbox( + "Display discarded documents by filter" + ) + + if display_discarded_documents_by_filter: + columns = list(self.docs) + + if "number_words" in columns: + cond_filter = np.invert(np.all(conds["number_words"], axis=0)) + display_dataset( + cond_filter, + "Discarded documents for the filter on the number of words", + ) + + if "repetitions_ratio" in columns: + cond_filter = np.invert(np.all(conds["repetitions_ratio"], axis=0)) + display_dataset( + cond_filter, + "Discarded documents for the filter on the repetitions ratio", + ) + + if "special_characters_ratio" in columns: + cond_filter = np.invert( + np.all(conds["special_characters_ratio"], axis=0) + ) + display_dataset( + cond_filter, + "Discarded documents for the filter on the special characters ratio", + ) + + if "stopwords_ratio" in columns: + cond_filter = np.invert(np.all(conds["stopwords_ratio"], axis=0)) + display_dataset( + cond_filter, + "Discarded documents for the filter on the stop words ratio", + ) + + if "badwords_ratio" in columns: + cond_filter = np.invert(np.all(conds["badwords_ratio"], axis=0)) + display_dataset( + cond_filter, + "Discarded documents for the filter on the bad words ratio", + ) + + if "lang_id_score" in columns: + cond_filter = np.invert(np.all(conds["lang_id_score"], axis=0)) + display_dataset( + cond_filter, + "Discarded documents for the filter on the language identification confidence score", + ) + + if "perplexity_score" in columns: + cond_filter = np.invert(np.all(conds["perplexity_score"], axis=0)) + display_dataset( + cond_filter, + "Discarded documents for the filter on the perplexity score", + ) + + display_dataset(all_conds, "Retained documents") + + def filtering_of_words(self): + if not (self.words is None): + st.sidebar.subheader("Parameter of the filtering on words") + + cutoff_def = "If the length of a word is higher than this number, the word is removed." + max_len_word = min(int(np.max(self.words["len_word"])) + 1, 200) + cutoff_word = st.sidebar.slider(cutoff_def, 0, max_len_word, max_len_word) + + incorrect_substrings = st.sidebar.checkbox( + "Remove words with incorrect substrings." + ) + + cond_words = self.words["len_word"] <= cutoff_word + if incorrect_substrings: + cond_words = cond_words & np.invert(self.words["incorrect_substring"]) + + st.header("Filtering on words") + + st.markdown( + f"Since the number of words is way larger than the number of documents, " + f"we consider in this section words for the first {self.num_docs_for_words} documents only." + ) + + discarded_words = self.words.loc[np.invert(cond_words)] + st.subheader( + f"Discarded words: {len(discarded_words)} words ({len(discarded_words) / len(self.words) * 100:.2f}%)" + ) + st.markdown( + "Click on a column to sort by it, place the cursor on the text to display it." + ) + st.dataframe(discarded_words) + + retained_words = self.words.loc[cond_words] + st.subheader( + f"Retained words: {len(retained_words)} words ({len(retained_words) / len(self.words) * 100:.2f}%)" + ) + st.markdown( + "Click on a column to sort by it, place the cursor on the text to display it." + ) + st.dataframe(retained_words) + + def plot_distributions_filtering_parameters(self): + st.header("Distributions of the filtering parameters") + + display_distributions = st.checkbox("Display distributions") + + if display_distributions: + + def plot_hist(dataframe, key, num_bins=50): + st.subheader(" ".join(key.split("_"))) + hist_values = dataframe[key].values + max_range = np.max(hist_values) + hist_values = np.histogram( + hist_values, bins=num_bins, range=(0, max_range) + )[0] + st.bar_chart(hist_values) + st.markdown(f"Each bin is of size: {max_range/num_bins}.") + + for key in list({el[0]: None for el in self.keys}): + plot_hist(self.docs, key) + + if not (self.words is None): + plot_hist(self.words, "len_word") + + def plot_zipf_law(self): + if not (self.words is None): + st.header("Zipf's Law") + + display_zipf_law = st.checkbox("Display Zipf's Law") + + if display_zipf_law: + + freq_words = {} + for _, row in self.words.iterrows(): + freq_words[row["word"]] = freq_words.get(row["word"], 0) + 1 + freq_words = np.array(list(freq_words.values())) + freq_words = -np.sort(-freq_words) + + fig, ax = plt.subplots() + ax.loglog(freq_words) + ax.set_title("Zipf's Law") + ax.set_xlabel("$i$-th most frequent word") + ax.set_ylabel("frequency in the documents") + st.pyplot(fig) + + def download_data(self): + st.header("Download data") + + with open(self.path_data) as json_file: + btn = st.download_button( + label="Download data as json", + data=json_file, + file_name="data.json", + ) + + def visualization(self): + self.preamble() + self.open_data() + self.set_title() + self.filtering_of_docs() + self.filtering_of_words() + self.plot_distributions_filtering_parameters() + self.plot_zipf_law() + self.download_data() + + +path_instructions = "./ac_dc/explanation_filtering_pipeline.pdf" +path_data = "./ac_dc/visualization/en_examples_with_stats.json" +lang = "English" +num_docs = 15000 +num_docs_for_words = 1500 +max_len_text_display = 10000 + +visualization = Visualization( + path_instructions, + path_data, + lang, + num_docs, + num_docs_for_words, + max_len_text_display, +) +visualization.visualization() diff --git a/data_tooling/bertin/README.md b/data_tooling/bertin/README.md new file mode 100644 index 0000000..7b39067 --- /dev/null +++ b/data_tooling/bertin/README.md @@ -0,0 +1,488 @@ +# BERTIN-OSCAR + +This is a copy of https://huggingface.co/bertin-project/bertin-roberta-base-spanish/tree/main. + +## Orginal README.md + + +--- +language: es +license: cc-by-4.0 +tags: +- spanish +- roberta +pipeline_tag: fill-mask +widget: +- text: Fui a la librería a comprar un . +--- + +- [Version v1](https://huggingface.co/bertin-project/bertin-roberta-base-spanish/tree/v1) (default): July 26th, 2021 +- [Version v1-512](https://huggingface.co/bertin-project/bertin-roberta-base-spanish/tree/v1-512): July 26th, 2021 +- [Version beta](https://huggingface.co/bertin-project/bertin-roberta-base-spanish/tree/beta): July 15th, 2021 + +# BERTIN + +
+BERTIN logo +
+ +BERTIN is a series of BERT-based models for Spanish. The current model hub points to the best of all RoBERTa-base models trained from scratch on the Spanish portion of mC4 using [Flax](https://github.com/google/flax). All code and scripts are included. + +This is part of the +[Flax/Jax Community Week](https://discuss.huggingface.co/t/open-to-the-community-community-week-using-jax-flax-for-nlp-cv/7104), organized by [HuggingFace](https://huggingface.co/) and TPU usage sponsored by Google Cloud. + +The aim of this project was to pre-train a RoBERTa-base model from scratch during the Flax/JAX Community Event, in which Google Cloud provided free TPUv3-8 to do the training using Huggingface's Flax implementations of their library. + +# Motivation + +According to [Wikipedia](https://en.wikipedia.org/wiki/List_of_languages_by_total_number_of_speakers), Spanish is the second most-spoken language in the world by native speakers (>470 million speakers), only after Chinese, and the fourth including those who speak it as a second language. However, most NLP research is still mainly available in English. Relevant contributions like BERT, XLNet or GPT2 sometimes take years to be available in Spanish and, when they do, it is often via multilingual versions which are not as performant as the English alternative. + +At the time of the event there were no RoBERTa models available in Spanish. Therefore, releasing one such model was the primary goal of our project. During the Flax/JAX Community Event we released a beta version of our model, which was the first in the Spanish language. Thereafter, on the last day of the event, the Barcelona Supercomputing Center released their own [RoBERTa](https://arxiv.org/pdf/2107.07253.pdf) model. The precise timing suggests our work precipitated its publication, and such an increase in competition is a desired outcome of our project. We are grateful for their efforts to include BERTIN in their paper, as discussed further below, and recognize the value of their own contribution, which we also acknowledge in our experiments. + +Models in monolingual Spanish are hard to come by and, when they do, they are often trained on proprietary datasets and with massive resources. In practice, this means that many relevant algorithms and techniques remain exclusive to large technology companies and organizations. This motivated the second goal of our project, which is to bring training of large models like RoBERTa one step closer to smaller groups. We want to explore techniques that make training these architectures easier and faster, thus contributing to the democratization of large language models. + +## Spanish mC4 + +The dataset mC4 is a multilingual variant of the C4, the Colossal, Cleaned version of Common Crawl's web crawl corpus. While C4 was used to train the T5 text-to-text Transformer models, mC4 comprises natural text in 101 languages drawn from the public Common Crawl web-scrape and was used to train mT5, the multilingual version of T5. + +The Spanish portion of mC4 (mC4-es) contains about 416 million samples and 235 billion words in approximately 1TB of uncompressed data. + +```bash +$ zcat c4/multilingual/c4-es*.tfrecord*.json.gz | wc -l +416057992 +``` + +```bash +$ zcat c4/multilingual/c4-es*.tfrecord-*.json.gz | jq -r '.text | split(" ") | length' | paste -s -d+ - | bc +235303687795 +``` + +## Perplexity sampling + +The large amount of text in mC4-es makes training a language model within the time constraints of the Flax/JAX Community Event problematic. This motivated the exploration of sampling methods, with the goal of creating a subset of the dataset that would allow for the training of well-performing models with roughly one eighth of the data (~50M samples) and at approximately half the training steps. + +In order to efficiently build this subset of data, we decided to leverage a technique we call *perplexity sampling*, and whose origin can be traced to the construction of CCNet (Wenzek et al., 2020) and their high quality monolingual datasets from web-crawl data. In their work, they suggest the possibility of applying fast language models trained on high-quality data such as Wikipedia to filter out texts that deviate too much from correct expressions of a language (see Figure 1). They also released Kneser-Ney models (Ney et al., 1994) for 100 languages (Spanish included) as implemented in the KenLM library (Heafield, 2011) and trained on their respective Wikipedias. + +
+ +![Perplexity distributions by percentage CCNet corpus](./images/ccnet.png) + +Figure 1. Perplexity distributions by percentage CCNet corpus. +
+ +In this work, we tested the hypothesis that perplexity sampling might help +reduce training-data size and training times, while keeping the performance of +the final model. + +## Methodology + +In order to test our hypothesis, we first calculated the perplexity of each document in a random subset (roughly a quarter of the data) of mC4-es and extracted their distribution and quartiles (see Figure 2). + +
+ +![Perplexity distributions and quartiles (red lines) of 44M samples of mC4-es](./images/perp-p95.png) + +Figure 2. Perplexity distributions and quartiles (red lines) of 44M samples of mC4-es. +
+ +With the extracted perplexity percentiles, we created two functions to oversample the central quartiles with the idea of biasing against samples that are either too small (short, repetitive texts) or too long (potentially poor quality) (see Figure 3). + +The first function is a `Stepwise` that simply oversamples the central quartiles using quartile boundaries and a `factor` for the desired sampling frequency for each quartile, obviously giving larger frequencies for middle quartiles (oversampling Q2, Q3, subsampling Q1, Q4). +The second function weighted the perplexity distribution by a Gaussian-like function, to smooth out the sharp boundaries of the `Stepwise` function and give a better approximation to the desired underlying distribution (see Figure 4). + +We adjusted the `factor` parameter of the `Stepwise` function, and the `factor` and `width` parameter of the `Gaussian` function to roughly be able to sample 50M samples from the 416M in mC4-es (see Figure 4). For comparison, we also sampled randomly mC4-es up to 50M samples as well. In terms of sizes, we went down from 1TB of data to ~200GB. We released the code to sample from mC4 on the fly when streaming for any language under the dataset [`bertin-project/mc4-sampling`](https://huggingface.co/datasets/bertin-project/mc4-sampling). + +
+ +![Expected perplexity distributions of the sample mC4-es after applying the Stepwise function](./images/perp-resample-stepwise.png) + +Figure 3. Expected perplexity distributions of the sample mC4-es after applying the Stepwise function. + +
+ +
+ +![Expected perplexity distributions of the sample mC4-es after applying Gaussian function](./images/perp-resample-gaussian.png) + +Figure 4. Expected perplexity distributions of the sample mC4-es after applying Gaussian function. +
+ +Figure 5 shows the actual perplexity distributions of the generated 50M subsets for each of the executed subsampling procedures. All subsets can be easily accessed for reproducibility purposes using the [`bertin-project/mc4-es-sampled`](https://huggingface.co/datasets/bertin-project/mc4-es-sampled) dataset. We adjusted our subsampling parameters so that we would sample around 50M examples from the original train split in mC4. However, when these parameters were applied to the validation split they resulted in too few examples (~400k samples), Therefore, for validation purposes, we extracted 50k samples at each evaluation step from our own train dataset on the fly. Crucially, those elements were then excluded from training, so as not to validate on previously seen data. In the [`mc4-es-sampled`](https://huggingface.co/datasets/bertin-project/mc4-es-sampled) dataset, the train split contains the full 50M samples, while validation is retrieved as it is from the original mC4. + +```python +from datasets import load_dataset + +for config in ("random", "stepwise", "gaussian"): + mc4es = load_dataset( + "bertin-project/mc4-es-sampled", + config, + split="train", + streaming=True + ).shuffle(buffer_size=1000) + for sample in mc4es: + print(config, sample) + break +``` + +
+ +![Experimental perplexity distributions of the sampled mc4-es after applying Gaussian and Stepwise functions, and the Random control sample](./images/datasets-perp.png) + +Figure 5. Experimental perplexity distributions of the sampled mc4-es after applying Gaussian and Stepwise functions, and the Random control sample. +
+ +`Random` sampling displayed the same perplexity distribution of the underlying true distribution, as can be seen in Figure 6. + +
+ +![Experimental perplexity distribution of the sampled mc4-es after applying Random sampling](./images/datasets-random-comparison.png) + +Figure 6. Experimental perplexity distribution of the sampled mc4-es after applying Random sampling. +
+ +Although this is not a comprehensive analysis, we looked into the distribution of perplexity for the training corpus. A quick t-SNE graph seems to suggest the distribution is uniform for the different topics and clusters of documents. The [interactive plot](https://huggingface.co/bertin-project/bertin-roberta-base-spanish/raw/main/images/perplexity_colored_embeddings.html) was generated using [a distilled version of multilingual USE](https://huggingface.co/sentence-transformers/distiluse-base-multilingual-cased-v1) to embed a random subset of 20,000 examples and each example is colored based on its perplexity. This is important since, in principle, introducing a perplexity-biased sampling method could introduce undesired biases if perplexity happens to be correlated to some other quality of our data. The code required to replicate this plot is available at [`tsne_plot.py`](https://huggingface.co/bertin-project/bertin-roberta-base-spanish/blob/main/tsne_plot.py) script and the HTML file is located under [`images/perplexity_colored_embeddings.html`](https://huggingface.co/bertin-project/bertin-roberta-base-spanish/blob/main/images/perplexity_colored_embeddings.html). + +### Training details + +We then used the same setup and hyperparameters as [Liu et al. (2019)](https://arxiv.org/abs/1907.11692) but trained only for half the steps (250k) on a sequence length of 128. In particular, `Gaussian` and `Stepwise` trained for the 250k steps, while `Random` was stopped at 230k. `Stepwise` needed to be initially stopped at 180k to allow downstream tests (sequence length 128), but was later resumed and finished the 250k steps. At the time of tests for 512 sequence length it had reached 204k steps, improving performance substantially. + +Then, we continued training the most promising models for a few more steps (~50k) on sequence length 512 from the previous checkpoints on 128 sequence length at 230k steps. We tried two strategies for this, since it is not easy to find clear details about how to proceed in the literature. It turns out this decision had a big impact in the final performance. + +For `Random` sampling we trained with sequence length 512 during the last 25k steps of the 250k training steps, keeping the optimizer state intact. Results for this are underwhelming, as seen in Figure 7. + +
+ +![Training profile for Random sampling. Note the drop in performance after the change from 128 to 512 sequence length](./images/random_512.jpg) + +Figure 7. Training profile for Random sampling. Note the drop in performance after the change from 128 to 512 sequence length. +
+ +For `Gaussian` sampling we started a new optimizer after 230k steps with 128 sequence length, using a short warmup interval. Results are much better using this procedure. We do not have a graph since training needed to be restarted several times, however, final accuracy was 0.6873 compared to 0.5907 for `Random` (512), a difference much larger than that of their respective -128 models (0.6520 for `Random`, 0.6608 for `Gaussian`). Following the same procedure, `Stepwise` continues training on sequence length 512 with a MLM accuracy of 0.6744 at 31k steps. + +Batch size was 2048 (8 TPU cores x 256 batch size) for training with 128 sequence length, and 384 (8 x 48) for 512 sequence length, with no change in learning rate. Warmup steps for 512 was 500. + +## Results + +Please refer to the **evaluation** folder for training scripts for downstream tasks. + +Our first test, tagged [`beta`](https://huggingface.co/bertin-project/bertin-roberta-base-spanish/tree/beta) in this repository, refers to an initial experiment using `Stepwise` on 128 sequence length and trained for 210k steps with a small `factor` set to 10. The repository [`flax-community/bertin-roberta-large-spanish`](https://huggingface.co/flax-community/bertin-roberta-large-spanish) contains a nearly identical version but it is now discontinued). During the community event, the Barcelona Supercomputing Center (BSC) in association with the National Library of Spain released RoBERTa base and large models trained on 200M documents (570GB) of high quality data clean using 100 nodes with 48 CPU cores of MareNostrum 4 during 96h. At the end of the process they were left with 2TB of clean data at the document level that were further cleaned up to the final 570GB. This is an interesting contrast to our own resources (3 TPUv3-8 for 10 days to do cleaning, sampling, training, and evaluation) and makes for a valuable reference. The BSC team evaluated our early release of the model [`beta`](https://huggingface.co/bertin-project/bertin-roberta-base-spanish/tree/beta) and the results can be seen in Table 1. + +Our final models were trained on a different number of steps and sequence lengths and achieve different—higher—masked-word prediction accuracies. Despite these limitations it is interesting to see the results they obtained using the early version of our model. Note that some of the datasets used for evaluation by BSC are not freely available, therefore it is not possible to verify the figures. + +
+ +Table 1. Evaluation made by the Barcelona Supercomputing Center of their models and BERTIN (beta, sequence length 128), from their preprint(arXiv:2107.07253). + +| Dataset | Metric | RoBERTa-b | RoBERTa-l | BETO | mBERT | BERTIN (beta) | +|-------------|----------|-----------|-----------|--------|--------|--------| +| UD-POS | F1 |**0.9907** | 0.9901 | 0.9900 | 0.9886 | **0.9904** | +| Conll-NER | F1 | 0.8851 | 0.8772 | 0.8759 | 0.8691 | 0.8627 | +| Capitel-POS | F1 | 0.9846 | 0.9851 | 0.9836 | 0.9839 | 0.9826 | +| Capitel-NER | F1 | 0.8959 | 0.8998 | 0.8771 | 0.8810 | 0.8741 | +| STS | Combined | 0.8423 | 0.8420 | 0.8216 | 0.8249 | 0.7822 | +| MLDoc | Accuracy | 0.9595 | 0.9600 | 0.9650 | 0.9560 | **0.9673** | +| PAWS-X | F1 | 0.9035 | 0.9000 | 0.8915 | 0.9020 | 0.8820 | +| XNLI | Accuracy | 0.8016 | WIP | 0.8130 | 0.7876 | WIP | + +
+ +All of our models attained good accuracy values during training in the masked-language model task —in the range of 0.65— as can be seen in Table 2: + +
+ +Table 2. Accuracy for the different language models for the main masked-language model task. + +| Model | Accuracy | +|----------------------------------------------------|----------| +| [`bertin-project/bertin-roberta-base-spanish (beta)`](https://huggingface.co/bertin-project/bertin-roberta-base-spanish) | 0.6547 | +| [`bertin-project/bertin-base-random`](https://huggingface.co/bertin-project/bertin-base-random) | 0.6520 | +| [`bertin-project/bertin-base-stepwise`](https://huggingface.co/bertin-project/bertin-base-stepwise) | 0.6487 | +| [`bertin-project/bertin-base-gaussian`](https://huggingface.co/bertin-project/bertin-base-gaussian) | 0.6608 | +| [`bertin-project/bertin-base-random-exp-512seqlen`](https://huggingface.co/bertin-project/bertin-base-random-exp-512seqlen) | 0.5907 | +| [`bertin-project/bertin-base-stepwise-exp-512seqlen`](https://huggingface.co/bertin-project/bertin-base-stepwise-exp-512seqlen) | 0.6818 | +| [`bertin-project/bertin-base-gaussian-exp-512seqlen`](https://huggingface.co/bertin-project/bertin-base-gaussian-exp-512seqlen) | **0.6873** | + +
+ +### Downstream Tasks + +We are currently in the process of applying our language models to downstream tasks. +For simplicity, we will abbreviate the different models as follows: + +- **mBERT**: [`bert-base-multilingual-cased`](https://huggingface.co/bert-base-multilingual-cased) +- **BETO**: [`dccuchile/bert-base-spanish-wwm-cased`](https://huggingface.co/dccuchile/bert-base-spanish-wwm-cased) +- **BSC-BNE**: [`BSC-TeMU/roberta-base-bne`](https://huggingface.co/BSC-TeMU/roberta-base-bne) +- **Beta**: [`bertin-project/bertin-roberta-base-spanish`](https://huggingface.co/bertin-project/bertin-roberta-base-spanish) +- **Random**: [`bertin-project/bertin-base-random`](https://huggingface.co/bertin-project/bertin-base-random) +- **Stepwise**: [`bertin-project/bertin-base-stepwise`](https://huggingface.co/bertin-project/bertin-base-stepwise) +- **Gaussian**: [`bertin-project/bertin-base-gaussian`](https://huggingface.co/bertin-project/bertin-base-gaussian) +- **Random-512**: [`bertin-project/bertin-base-random-exp-512seqlen`](https://huggingface.co/bertin-project/bertin-base-random-exp-512seqlen) +- **Stepwise-512**: [`bertin-project/bertin-base-stepwise-exp-512seqlen`](https://huggingface.co/bertin-project/bertin-base-stepwise-exp-512seqlen) (WIP) +- **Gaussian-512**: [`bertin-project/bertin-base-gaussian-exp-512seqlen`](https://huggingface.co/bertin-project/bertin-base-gaussian-exp-512seqlen) + +
+ + +Table 3. Metrics for different downstream tasks, comparing our different models as well as other relevant BERT variations from the literature. Dataset for POS and NER is CoNLL 2002. POS and NER used max length 128 and batch size 16. Batch size for XNLI is 32 (max length 256). All models were fine-tuned for 5 epochs, with the exception of XNLI-256 that used 2 epochs. Stepwise used an older checkpoint with only 180.000 steps. + + +| Model | POS (F1/Acc) | NER (F1/Acc) | XNLI-256 (Acc) | +|--------------|----------------------|---------------------|----------------| +| mBERT | 0.9629 / 0.9687 | 0.8539 / 0.9779 | 0.7852 | +| BETO | 0.9642 / 0.9700 | 0.8579 / 0.9783 | **0.8186** | +| BSC-BNE | 0.9659 / 0.9707 | 0.8700 / 0.9807 | 0.8178 | +| Beta | 0.9638 / 0.9690 | 0.8725 / 0.9812 | 0.7791 | +| Random | 0.9656 / 0.9704 | 0.8704 / 0.9807 | 0.7745 | +| Stepwise | 0.9656 / 0.9707 | 0.8705 / 0.9809 | 0.7820 | +| Gaussian | 0.9662 / 0.9709 | **0.8792 / 0.9816** | 0.7942 | +| Random-512 | 0.9660 / 0.9707 | 0.8616 / 0.9803 | 0.7723 | +| Stepwise-512 | WIP | WIP | WIP | +| Gaussian-512 | **0.9662 / 0.9714** | **0.8764 / 0.9819** | 0.7878 | + +
+ +Table 4. Metrics for different downstream tasks, comparing our different models as well as other relevant BERT variations from the literature. Dataset for POS and NER is CoNLL 2002. POS, NER and PAWS-X used max length 512 and batch size 16. Batch size for XNLI is 16 too (max length 512). All models were fine-tuned for 5 epochs. Results marked with `*` indicate more than one run to guarantee convergence. + + +| Model | POS (F1/Acc) | NER (F1/Acc) | PAWS-X (Acc) | XNLI (Acc) | +|--------------|----------------------|---------------------|--------------|------------| +| mBERT | 0.9630 / 0.9689 | 0.8616 / 0.9790 | 0.8895* | 0.7606 | +| BETO | 0.9639 / 0.9693 | 0.8596 / 0.9790 | 0.8720* | **0.8012** | +| BSC-BNE | **0.9655 / 0.9706** | 0.8764 / 0.9818 | 0.8815* | 0.7771* | +| Beta | 0.9616 / 0.9669 | 0.8640 / 0.9799 | 0.8670* | 0.7751* | +| Random | 0.9651 / 0.9700 | 0.8638 / 0.9802 | 0.8800* | 0.7795 | +| Stepwise | 0.9647 / 0.9698 | 0.8749 / 0.9819 | 0.8685* | 0.7763 | +| Gaussian | 0.9644 / 0.9692 | **0.8779 / 0.9820** | 0.8875* | 0.7843 | +| Random-512 | 0.9636 / 0.9690 | 0.8664 / 0.9806 | 0.6735* | 0.7799 | +| Stepwise-512 | 0.9633 / 0.9684 | 0.8662 / 0.9811 | 0.8690 | 0.7695 | +| Gaussian-512 | 0.9646 / 0.9697 | 0.8707 / 0.9810 | **0.8965**\* | 0.7843 | + + + +In addition to the tasks above, we also trained the [`beta`](https://huggingface.co/bertin-project/bertin-roberta-base-spanish/tree/beta) model on the SQUAD dataset, achieving exact match 50.96 and F1 68.74 (sequence length 128). A full evaluation of this task is still pending. + +Results for PAWS-X seem surprising given the large differences in performance. However, this training was repeated to avoid failed runs and results seem consistent. A similar problem was found for XNLI-512, where many models reported a very poor 0.3333 accuracy on a first run (and even a second, in the case of BSC-BNE). This suggests training is a bit unstable for some datasets under these conditions. Increasing the batch size and number of epochs would be a natural attempt to fix this problem, however, this is not feasible within the project schedule. For example, runtime for XNLI-512 was ~19h per model and increasing the batch size without reducing sequence length is not feasible on a single GPU. + +We are also releasing the fine-tuned models for `Gaussian`-512 and making it our version [v1](https://huggingface.co/bertin-project/bertin-roberta-base-spanish/tree/v1) default to 128 sequence length since it experimentally shows better performance on fill-mask task, while also releasing the 512 sequence length version ([v1-512](https://huggingface.co/bertin-project/bertin-roberta-base-spanish/tree/v1-512) for fine-tuning. + +- POS: [`bertin-project/bertin-base-pos-conll2002-es`](https://huggingface.co/bertin-project/bertin-base-pos-conll2002-es/) +- NER: [`bertin-project/bertin-base-ner-conll2002-es`](https://huggingface.co/bertin-project/bertin-base-ner-conll2002-es/) +- PAWS-X: [`bertin-project/bertin-base-paws-x-es`](https://huggingface.co/bertin-project/bertin-base-paws-x-es) +- XNLI: [`bertin-project/bertin-base-xnli-es`](https://huggingface.co/bertin-project/bertin-base-xnli-es) + +## Bias and ethics + +While a rigorous analysis of our models and datasets for bias was out of the scope of our project (given the very tight schedule and our lack of experience on Flax/JAX), this issue has still played an important role in our motivation. Bias is often the result of applying massive, poorly-curated datasets during training of expensive architectures. This means that, even if problems are identified, there is little most can do about it at the root level since such training can be prohibitively expensive. We hope that, by facilitating competitive training with reduced times and datasets, we will help to enable the required iterations and refinements that these models will need as our understanding of biases improves. For example, it should be easier now to train a RoBERTa model from scratch using newer datasets specially designed to address bias. This is surely an exciting prospect, and we hope that this work will contribute in such challenges. + +Even if a rigorous analysis of bias is difficult, we should not use that excuse to disregard the issue in any project. Therefore, we have performed a basic analysis looking into possible shortcomings of our models. It is crucial to keep in mind that these models are publicly available and, as such, will end up being used in multiple real-world situations. These applications —some of them modern versions of phrenology— have a dramatic impact in the lives of people all over the world. We know Deep Learning models are in use today as [law assistants](https://www.wired.com/2017/04/courts-using-ai-sentence-criminals-must-stop-now/), in [law enforcement](https://www.washingtonpost.com/technology/2019/05/16/police-have-used-celebrity-lookalikes-distorted-images-boost-facial-recognition-results-research-finds/), as [exam-proctoring tools](https://www.wired.com/story/ai-college-exam-proctors-surveillance/) (also [this](https://www.eff.org/deeplinks/2020/09/students-are-pushing-back-against-proctoring-surveillance-apps)), for [recruitment](https://www.washingtonpost.com/technology/2019/10/22/ai-hiring-face-scanning-algorithm-increasingly-decides-whether-you-deserve-job/) (also [this](https://www.technologyreview.com/2021/07/21/1029860/disability-rights-employment-discrimination-ai-hiring/)) and even to [target minorities](https://www.insider.com/china-is-testing-ai-recognition-on-the-uighurs-bbc-2021-5). Therefore, it is our responsibility to fight bias when possible, and to be extremely clear about the limitations of our models, to discourage problematic use. + +### Bias examples (Spanish) + +Note that this analysis is slightly more difficult to do in Spanish since gender concordance reveals hints beyond masks. Note many suggestions seem grammatically incorrect in English, but with few exceptions —like “drive high”, which works in English but not in Spanish— they are all correct, even if uncommon. + +Results show that bias is apparent even in a quick and shallow analysis like this one. However, there are many instances where the results are more neutral than anticipated. For instance, the first option to “do the dishes” is the “son”, and “pink” is nowhere to be found in the color recommendations for a girl. Women seem to drive “high”, “fast”, “strong” and “well”, but “not a lot”. + +But before we get complacent, the model reminds us that the place of the woman is at "home" or "the bed" (!), while the man is free to roam the "streets", the "city" and even "Earth" (or "earth", both options are granted). + +Similar conclusions are derived from examples focusing on race and religion. Very matter-of-factly, the first suggestion always seems to be a repetition of the group ("Christians" **are** "Christians", after all), and other suggestions are rather neutral and tame. However, there are some worrisome proposals. For example, the fourth option for Jews is that they are "racist". Chinese people are both "intelligent" and "stupid", which actually hints to different forms of racism they encounter (so-called "positive" racism, such as claiming Asians are good at math, which can be insidious and [should not be taken lightly](https://www.health.harvard.edu/blog/anti-asian-racism-breaking-through-stereotypes-and-silence-2021041522414)). Predictions for Latin Americans also raise red flags, as they are linked to being "poor" and even "worse". + +The model also seems to suffer from geographical bias, producing words that are more common in Spain than other countries. For example, when filling the mask in "My <mask> is a Hyundai Accent", the word "coche" scores higher than "carro" (Spanish and Latin American words for car, respectively) while "auto", which is used in Argentina, doesn't appear in the top 5 choices. A more problematic example is seen with the word used for "taking" or "grabbing", when filling the mask in the sentence "I am late, I have to <mask> the bus". In Spain, the word "coger" is used, while in most countries in Latin America, the word "tomar" is used instead, while "coger" means "to have sex". The model choses "coger el autobús", which is a perfectly appropriate choice in the eyes of a person from Spain—it would translate to "take the bus", but inappropriate in most parts of Latin America, where it would mean "to have sex with the bus". Another example of geographical bias, can be observed by the preference of the model for the Spanish word for "drive", over its Latin American counterparts. Even when prompted with the words "carro" and "auto" (used in Latin America for "car"), the model chooses "conducir" (Spain) over "manejar" (Latin America) - however, "conducir" (Spain) scores higher when prompted with "coche" (Spain) than with "carro" and "auto" (Latin American), suggesting that the model has at least some basic understanding of the different ways of speaking Spanish in different parts of the world. + +On gender + +- Dile a tu **hijo** que hay que fregar los platos. + hijo — madre — jefe — pareja — suegra + +- Las mujeres conducen muy **alto**. + alto — rápido — poco — fuerte — bien + +- El lugar de la mujer está en la **casa**. + casa — cama — tierra — calle — vida + +- El lugar del hombre está en la **casa**. + calle — ciudad — Tierra — tierra — casa + +- Qué mal **vivir**, ¡tenía que ser mujer! + vivir — está — decirlo — hacer — escrito + +- Qué mal **vivir**, ¡tenía que ser hombre! + vivir — está — hecho — escrito — verlo + +- Como soy chica, mi color favorito es el **rojo**. + rojo — blanco — azul — verde — naranja + +On religion + +- La mayoría de los musulmanes son **musulmanes**. + musulmanes — árabes — cristianos — occidentales — (salto de línea) + +- La mayoría de los cristianos son **cristianos**. + cristianos — católicos — (salto de línea) — . — mujeres + +- La mayoría de los judíos son **judíos**. + judíos — blancos — argentinos — racistas — israelíes + +On race and origin + +- Los árabes son **árabes**. + árabes — musulmanes — iguales — dioses — cristianos + +- Los chinos son **chinos**. + chinos — asiáticos — inteligentes — negros — tontos + +- Los europeos son **europeos**. + europeos — alemanes — españoles — iguales — británicos + +- Los indios son **negros**. + negros — buenos — indios — todos — hombres + +- Los latinoamericanos son **mayoría**. + mayoría — iguales — pobres — latinoamericanos — peores + +Geographical bias + +- Mi **coche** es un Hyundai Accent. + coche — carro — vehículo — moto — padre + +- Llego tarde, tengo que **coger** el autobús. + coger — tomar — evitar — abandonar — utilizar + +- Para llegar a mi casa, tengo que **conducir** mi coche. + conducir — alquilar — llevar — coger — aparcar + +- Para llegar a mi casa, tengo que **llevar** mi carro. + llevar — comprar — tener — cargar — conducir + +- Para llegar a mi casa, tengo que **llevar** mi auto. + llevar — tener — conducir — coger — cargar + +### Bias examples (English translation) + +On gender + +- Tell your **son** to do the dishes. + son — mother — boss (male) — partner — mother in law + +- Women drive very **high**. + high (no drugs connotation) — fast — not a lot — strong — well + +- The place of the woman is at **home**. + house (home) — bed — earth — street — life + +- The place of the man is at the **street**. + street — city — Earth — earth — house (home) + +- Hard translation: What a bad way to <mask>, it had to be a woman! + Expecting sentences like: Awful driving, it had to be a woman! (Sadly common.) + live — is (“how bad it is”) — to say it — to do — written + +- (See previous example.) What a bad way to <mask>, it had to be a man! + live — is (“how bad it is”) — done — written — to see it (how unfortunate to see it) + +- Since I'm a girl, my favourite colour is **red**. + red — white — blue — green — orange + +On religion + +- Most Muslims are **Muslim**. + Muslim — Arab — Christian — Western — (new line) + +- Most Christians are **Christian**. + Christian — Catholic — (new line) — . — women + +- Most Jews are **Jews**. + Jews — white — Argentinian — racist — Israelis + +On race and origin + +- Arabs are **Arab**. + Arab — Muslim — the same — gods — Christian + +- Chinese are **Chinese**. + Chinese — Asian — intelligent — black — stupid + +- Europeans are **European**. + European — German — Spanish — the same — British + +- Indians are **black**. (Indians refers both to people from India or several Indigenous peoples, particularly from America.) + black — good — Indian — all — men + +- Latin Americans are **the majority**. + the majority — the same — poor — Latin Americans — worse + +Geographical bias + +- My **(Spain's word for) car** is a Hyundai Accent. + (Spain's word for) car — (Most of Latin America's word for) car — vehicle — motorbike — father + +- I am running late, I have to **take (in Spain) / have sex with (in Latin America)** the bus. + take (in Spain) / have sex with (in Latin America) — take (in Latin America) — avoid — leave — utilize + +- In order to get home, I have to **(Spain's word for) drive** my (Spain's word for) car. + (Spain's word for) drive — rent — bring — take — park + +- In order to get home, I have to **bring** my (most of Latin America's word for) car. + bring — buy — have — load — (Spain's word for) drive + +- In order to get home, I have to **bring** my (Argentina's and other parts of Latin America's word for) car. + bring — have — (Spain's word for) drive — take — load + +## Analysis + +The performance of our models has been, in general, very good. Even our beta model was able to achieve SOTA in MLDoc (and virtually tie in UD-POS) as evaluated by the Barcelona Supercomputing Center. In the main masked-language task our models reach values between 0.65 and 0.69, which foretells good results for downstream tasks. + +Our analysis of downstream tasks is not yet complete. It should be stressed that we have continued this fine-tuning in the same spirit of the project, that is, with smaller practicioners and budgets in mind. Therefore, our goal is not to achieve the highest possible metrics for each task, but rather train using sensible hyper parameters and training times, and compare the different models under these conditions. It is certainly possible that any of the models —ours or otherwise— could be carefully tuned to achieve better results at a given task, and it is a possibility that the best tuning might result in a new "winner" for that category. What we can claim is that, under typical training conditions, our models are remarkably performant. In particular, `Gaussian` sampling seems to produce more consistent models, taking the lead in four of the seven tasks analysed. + +The differences in performance for models trained using different data-sampling techniques are consistent. `Gaussian`-sampling is always first (with the exception of POS-512), while `Stepwise` is better than `Random` when trained during a similar number of steps. This proves that the sampling technique is, indeed, relevant. A more thorough statistical analysis is still required. + +As already mentioned in the [Training details](#training-details) section, the methodology used to extend sequence length during training is critical. The `Random`-sampling model took an important hit in performance in this process, while `Gaussian`-512 ended up with better metrics than than `Gaussian`-128, in both the main masked-language task and the downstream datasets. The key difference was that `Random` kept the optimizer intact while `Gaussian` used a fresh one. It is possible that this difference is related to the timing of the swap in sequence length, given that close to the end of training the optimizer will keep learning rates very low, perhaps too low for the adjustments needed after a change in sequence length. We believe this is an important topic of research, but our preliminary data suggests that using a new optimizer is a safe alternative when in doubt or if computational resources are scarce. + +# Lessons and next steps + +BERTIN Project has been a challenge for many reasons. Like many others in the Flax/JAX Community Event, ours is an impromptu team of people with little to no experience with Flax. Even if training a RoBERTa model sounds vaguely like a replication experiment, we anticipated difficulties ahead, and we were right to do so. + +New tools always require a period of adaptation in the working flow. For instance, lacking —to the best of our knowledge— a monitoring tool equivalent to `nvidia-smi` makes simple procedures like optimizing batch sizes become troublesome. Of course, we also needed to improvise the code adaptations required for our data sampling experiments. Moreover, this re-conceptualization of the project required that we run many training processes during the event. This is another reason why saving and restoring checkpoints was a must for our success —the other reason being our planned switch from 128 to 512 sequence length. However, such code was not available at the start of the Community Event. At some point code to save checkpoints was released, but not to restore and continue training from them (at least we are not aware of such update). In any case, writing this Flax code —with help from the fantastic and collaborative spirit of the event— was a valuable learning experience, and these modifications worked as expected when they were needed. + +The results we present in this project are very promising, and we believe they hold great value for the community as a whole. However, to fully make the most of our work, some next steps would be desirable. + +The most obvious step ahead is to replicate training on a "large" version of the model. This was not possible during the event due to our need of faster iterations. We should also explore in finer detail the impact of our proposed sampling methods. In particular, further experimentation is needed on the impact of the `Gaussian` parameters. If perplexity-based sampling were to become a common technique, it would be important to look carefully into possible biases this might introduce. Our preliminary data suggests this is not the case, but it would be a rewarding analysis nonetheless. Another intriguing possibility is to combine our sampling algorithm with other cleaning steps such as deduplication (Lee et al., 2021), as they seem to share a complementary philosophy. + +# Conclusions + +With roughly 10 days worth of access to 3 TPUv3-8, we have achieved remarkable results surpassing previous state of the art in a few tasks, and even improving document classification on models trained in massive supercomputers with very large, highly-curated, and in some cases private, datasets. + +The very big size of the datasets available looked enticing while formulating the project. However, it soon proved to be an important challenge given the time constraints. This led to a debate within the team and ended up reshaping our project and goals, now focusing on analysing this problem and how we could improve this situation for smaller teams like ours in the future. The subsampling techniques analysed in this report have shown great promise in this regard, and we hope to see other groups use them and improve them in the future. + +At a personal level, the experience has been incredible for all of us. We believe that these kind of events provide an amazing opportunity for small teams on low or non-existent budgets to learn how the big players in the field pre-train their models, certainly stirring the research community. The trade-off between learning and experimenting, and being beta-testers of libraries (Flax/JAX) and infrastructure (TPU VMs) is a marginal cost to pay compared to the benefits such access has to offer. + +Given our good results, on par with those of large corporations, we hope our work will inspire and set the basis for more small teams to play and experiment with language models on smaller subsets of huge datasets. + +## Team members + +- Javier de la Rosa ([versae](https://huggingface.co/versae)) +- Eduardo González ([edugp](https://huggingface.co/edugp)) +- Paulo Villegas ([paulo](https://huggingface.co/paulo)) +- Pablo González de Prado ([Pablogps](https://huggingface.co/Pablogps)) +- Manu Romero ([mrm8488](https://huggingface.co/)) +- María Grandury ([mariagrandury](https://huggingface.co/)) + +## Useful links + +- [Community Week timeline](https://discuss.huggingface.co/t/open-to-the-community-community-week-using-jax-flax-for-nlp-cv/7104#summary-timeline-calendar-6) +- [Community Week README](https://github.com/huggingface/transformers/blob/master/examples/research_projects/jax-projects/README.md) +- [Community Week thread](https://discuss.huggingface.co/t/bertin-pretrain-roberta-large-from-scratch-in-spanish/7125) +- [Community Week channel](https://discord.com/channels/858019234139602994/859113060068229190) +- [Masked Language Modelling example scripts](https://github.com/huggingface/transformers/tree/master/examples/flax/language-modeling) +- [Model Repository](https://huggingface.co/flax-community/bertin-roberta-large-spanish/) + +## References + +- Heafield, K. (2011). KenLM: faster and smaller language model queries. Proceedings of the EMNLP2011 Sixth Workshop on Statistical Machine Translation. + +- Lee, K., Ippolito, D., Nystrom, A., Zhang, C., Eck, D., Callison-Burch, C., & Carlini, N. (2021). Deduplicating Training Data Makes Language Models Better. arXiv preprint arXiv:2107.06499. + +- Liu, Y., Ott, M., Goyal, N., Du, J., Joshi, M., Chen, D., ... & Stoyanov, V. (2019). Roberta: A robustly optimized bert pretraining approach. arXiv preprint arXiv:1907.11692. + +- Ney, H., Essen, U., & Kneser, R. (1994). On structuring probabilistic dependences in stochastic language modelling. Computer Speech & Language, 8(1), 1-38. + +- Wenzek, G., Lachaux, M. A., Conneau, A., Chaudhary, V., Guzmán, F., Joulin, A., & Grave, E. (2019). Ccnet: Extracting high quality monolingual datasets from web crawl data. arXiv preprint arXiv:1911.00359. diff --git a/data_tooling/bertin/config.json b/data_tooling/bertin/config.json new file mode 100644 index 0000000..a66173d --- /dev/null +++ b/data_tooling/bertin/config.json @@ -0,0 +1,25 @@ +{ + "architectures": [ + "RobertaForMaskedLM" + ], + "attention_probs_dropout_prob": 0.1, + "bos_token_id": 0, + "eos_token_id": 2, + "gradient_checkpointing": false, + "hidden_act": "gelu", + "hidden_dropout_prob": 0.1, + "hidden_size": 768, + "initializer_range": 0.02, + "intermediate_size": 3072, + "layer_norm_eps": 1e-05, + "max_position_embeddings": 514, + "model_type": "roberta", + "num_attention_heads": 12, + "num_hidden_layers": 12, + "pad_token_id": 1, + "position_embedding_type": "absolute", + "transformers_version": "4.9.0.dev0", + "type_vocab_size": 1, + "use_cache": true, + "vocab_size": 50265 +} diff --git a/data_tooling/bertin/config.py b/data_tooling/bertin/config.py new file mode 100644 index 0000000..8243626 --- /dev/null +++ b/data_tooling/bertin/config.py @@ -0,0 +1,8 @@ +#!/usr/bin/env python +from transformers import RobertaConfig + +config = RobertaConfig.from_pretrained("roberta-large") +config.save_pretrained("./configs/large") + +config = RobertaConfig.from_pretrained("roberta-base") +config.save_pretrained("./configs/base") diff --git a/data_tooling/bertin/configs/base/config.json b/data_tooling/bertin/configs/base/config.json new file mode 100644 index 0000000..a854b05 --- /dev/null +++ b/data_tooling/bertin/configs/base/config.json @@ -0,0 +1,25 @@ +{ + "architectures": [ + "RobertaForMaskedLM" + ], + "attention_probs_dropout_prob": 0.1, + "bos_token_id": 0, + "eos_token_id": 2, + "gradient_checkpointing": false, + "hidden_act": "gelu", + "hidden_dropout_prob": 0.1, + "hidden_size": 768, + "initializer_range": 0.02, + "intermediate_size": 3072, + "layer_norm_eps": 1e-05, + "max_position_embeddings": 514, + "model_type": "roberta", + 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as jnp +from transformers import AutoTokenizer, FlaxRobertaForMaskedLM, RobertaForMaskedLM + + +def to_f32(t): + return jax.tree_map( + lambda x: x.astype(jnp.float32) if x.dtype == jnp.bfloat16 else x, t + ) + + +def main(): + # Saving extra files from config.json and tokenizer.json files + tokenizer = AutoTokenizer.from_pretrained("./") + tokenizer.save_pretrained("./") + + # Temporary saving bfloat16 Flax model into float32 + tmp = tempfile.mkdtemp() + flax_model = FlaxRobertaForMaskedLM.from_pretrained("./") + flax_model.params = to_f32(flax_model.params) + flax_model.save_pretrained(tmp) + # Converting float32 Flax to PyTorch + model = RobertaForMaskedLM.from_pretrained(tmp, from_flax=True) + model.save_pretrained("./", save_config=False) + + +if __name__ == "__main__": + main() diff --git a/data_tooling/bertin/evaluation/paws.yaml b/data_tooling/bertin/evaluation/paws.yaml new file mode 100644 index 0000000..b97f90e --- /dev/null +++ b/data_tooling/bertin/evaluation/paws.yaml @@ -0,0 +1,53 @@ +name: BERTIN PAWS-X es +project: bertin-eval +enitity: versae +program: run_glue.py +command: + - ${env} + - ${interpreter} + - ${program} + - ${args} +method: grid +metric: + name: eval/accuracy + goal: maximize +parameters: + model_name_or_path: + values: + - bertin-project/bertin-base-gaussian-exp-512seqlen + - bertin-project/bertin-base-stepwise-exp-512seqlen + - bertin-project/bertin-base-random-exp-512seqlen + - bertin-project/bertin-base-gaussian + - bertin-project/bertin-base-stepwise + - bertin-project/bertin-base-random + - bertin-project/bertin-roberta-base-spanish + - flax-community/bertin-roberta-large-spanish + - BSC-TeMU/roberta-base-bne + - dccuchile/bert-base-spanish-wwm-cased + - bert-base-multilingual-cased + num_train_epochs: + values: [5] + task_name: + value: paws-x + dataset_name: + value: paws-x + dataset_config_name: + value: es + output_dir: + value: ./outputs + overwrite_output_dir: + value: true + max_seq_length: + value: 512 + pad_to_max_length: + value: true + per_device_train_batch_size: + value: 16 + per_device_eval_batch_size: + value: 16 + save_total_limit: + value: 1 + do_train: + value: true + do_eval: + value: true diff --git a/data_tooling/bertin/evaluation/run_glue.py b/data_tooling/bertin/evaluation/run_glue.py new file mode 100644 index 0000000..a08cba2 --- /dev/null +++ b/data_tooling/bertin/evaluation/run_glue.py @@ -0,0 +1,683 @@ +#!/usr/bin/env python +# coding=utf-8 +# Copyright 2020 The HuggingFace Inc. team. All rights reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +""" Finetuning the library models for sequence classification on GLUE.""" +# You can also adapt this script on your own text classification task. Pointers for this are left as comments. + +import logging +import os +import random +import sys +from dataclasses import dataclass, field +from pathlib import Path +from typing import Optional + +import datasets +import numpy as np +import transformers +from datasets import load_dataset, load_metric +from transformers import ( + AutoConfig, + AutoModelForSequenceClassification, + AutoTokenizer, + DataCollatorWithPadding, + EvalPrediction, + HfArgumentParser, + PretrainedConfig, + Trainer, + TrainingArguments, + default_data_collator, + set_seed, +) +from transformers.trainer_utils import get_last_checkpoint +from transformers.utils import check_min_version +from transformers.utils.versions import require_version + +# Will error if the minimal version of Transformers is not installed. Remove at your own risks. +check_min_version("4.9.0.dev0") + +require_version( + "datasets>=1.8.0", + "To fix: pip install -r examples/pytorch/text-classification/requirements.txt", +) + +task_to_keys = { + "cola": ("sentence", None), + "mnli": ("premise", "hypothesis"), + "xnli": ("premise", "hypothesis"), + "mrpc": ("sentence1", "sentence2"), + "qnli": ("question", "sentence"), + "qqp": ("question1", "question2"), + "rte": ("sentence1", "sentence2"), + "sst2": ("sentence", None), + "stsb": ("sentence1", "sentence2"), + "wnli": ("sentence1", "sentence2"), + "paws-x": ("sentence1", "sentence2"), +} +task_to_metrics = { + "paws-x": "accuracy", + "xnli": "accuracy", +} + +logger = logging.getLogger(__name__) + + +@dataclass +class DataTrainingArguments: + """ + Arguments pertaining to what data we are going to input our model for training and eval. + + Using `HfArgumentParser` we can turn this class + into argparse arguments to be able to specify them on + the command line. + """ + + task_name: Optional[str] = field( + default=None, + metadata={ + "help": "The name of the task to train on: " + + ", ".join(task_to_keys.keys()) + }, + ) + dataset_name: Optional[str] = field( + default=None, + metadata={"help": "The name of the dataset to use (via the datasets library)."}, + ) + dataset_config_name: Optional[str] = field( + default=None, + metadata={ + "help": "The configuration name of the dataset to use (via the datasets library)." + }, + ) + max_seq_length: int = field( + default=128, + metadata={ + "help": "The maximum total input sequence length after tokenization. Sequences longer " + "than this will be truncated, sequences shorter will be padded." + }, + ) + overwrite_cache: bool = field( + default=False, + metadata={"help": "Overwrite the cached preprocessed datasets or not."}, + ) + pad_to_max_length: bool = field( + default=True, + metadata={ + "help": "Whether to pad all samples to `max_seq_length`. " + "If False, will pad the samples dynamically when batching to the maximum length in the batch." + }, + ) + max_train_samples: Optional[int] = field( + default=None, + metadata={ + "help": "For debugging purposes or quicker training, truncate the number of training examples to this " + "value if set." + }, + ) + max_eval_samples: Optional[int] = field( + default=None, + metadata={ + "help": "For debugging purposes or quicker training, truncate the number of evaluation examples to this " + "value if set." + }, + ) + max_predict_samples: Optional[int] = field( + default=None, + metadata={ + "help": "For debugging purposes or quicker training, truncate the number of prediction examples to this " + "value if set." + }, + ) + train_file: Optional[str] = field( + default=None, + metadata={"help": "A csv or a json file containing the training data."}, + ) + validation_file: Optional[str] = field( + default=None, + metadata={"help": "A csv or a json file containing the validation data."}, + ) + test_file: Optional[str] = field( + default=None, + metadata={"help": "A csv or a json file containing the test data."}, + ) + + def __post_init__(self): + if self.task_name is not None: + self.task_name = self.task_name.lower() + if self.task_name not in task_to_keys.keys(): + raise ValueError( + "Unknown task, you should pick one in " + + ",".join(task_to_keys.keys()) + ) + elif self.dataset_name is not None: + pass + elif self.train_file is None or self.validation_file is None: + raise ValueError( + "Need either a GLUE task, a training/validation file or a dataset name." + ) + else: + train_extension = self.train_file.split(".")[-1] + assert train_extension in [ + "csv", + "json", + ], "`train_file` should be a csv or a json file." + validation_extension = self.validation_file.split(".")[-1] + assert ( + validation_extension == train_extension + ), "`validation_file` should have the same extension (csv or json) as `train_file`." + + +@dataclass +class ModelArguments: + """ + Arguments pertaining to which model/config/tokenizer we are going to fine-tune from. + """ + + model_name_or_path: str = field( + metadata={ + "help": "Path to pretrained model or model identifier from huggingface.co/models" + } + ) + config_name: Optional[str] = field( + default=None, + metadata={ + "help": "Pretrained config name or path if not the same as model_name" + }, + ) + tokenizer_name: Optional[str] = field( + default=None, + metadata={ + "help": "Pretrained tokenizer name or path if not the same as model_name" + }, + ) + cache_dir: Optional[str] = field( + default=None, + metadata={ + "help": "Where do you want to store the pretrained models downloaded from huggingface.co" + }, + ) + use_fast_tokenizer: bool = field( + default=True, + metadata={ + "help": "Whether to use one of the fast tokenizer (backed by the tokenizers library) or not." + }, + ) + model_revision: str = field( + default="main", + metadata={ + "help": "The specific model version to use (can be a branch name, tag name or commit id)." + }, + ) + use_auth_token: bool = field( + default=False, + metadata={ + "help": "Will use the token generated when running `transformers-cli login` (necessary to use this script " + "with private models)." + }, + ) + + +def main(): + # See all possible arguments in src/transformers/training_args.py + # or by passing the --help flag to this script. + # We now keep distinct sets of args, for a cleaner separation of concerns. + + parser = HfArgumentParser( + (ModelArguments, DataTrainingArguments, TrainingArguments) + ) + if len(sys.argv) == 2 and sys.argv[1].endswith(".json"): + # If we pass only one argument to the script and it's the path to a json file, + # let's parse it to get our arguments. + model_args, data_args, training_args = parser.parse_json_file( + json_file=os.path.abspath(sys.argv[1]) + ) + else: + model_args, data_args, training_args = parser.parse_args_into_dataclasses() + + # Setup logging + logging.basicConfig( + format="%(asctime)s - %(levelname)s - %(name)s - %(message)s", + datefmt="%m/%d/%Y %H:%M:%S", + handlers=[logging.StreamHandler(sys.stdout)], + ) + + log_level = training_args.get_process_log_level() + logger.setLevel(log_level) + datasets.utils.logging.set_verbosity(log_level) + transformers.utils.logging.set_verbosity(log_level) + transformers.utils.logging.enable_default_handler() + transformers.utils.logging.enable_explicit_format() + + # Log on each process the small summary: + logger.warning( + f"Process rank: {training_args.local_rank}, device: {training_args.device}, n_gpu: {training_args.n_gpu}" + + f"distributed training: {bool(training_args.local_rank != -1)}, 16-bits training: {training_args.fp16}" + ) + logger.info(f"Training/evaluation parameters {training_args}") + + # Detecting last checkpoint. + last_checkpoint = None + run_name = f"{model_args.model_name_or_path}-{np.random.randint(1000):04d}" + training_args.output_dir = str(Path(training_args.output_dir) / run_name) + if ( + os.path.isdir(training_args.output_dir) + and training_args.do_train + and not training_args.overwrite_output_dir + ): + last_checkpoint = get_last_checkpoint(training_args.output_dir) + if last_checkpoint is None and len(os.listdir(training_args.output_dir)) > 0: + raise ValueError( + f"Output directory ({training_args.output_dir}) already exists and is not empty. " + "Use --overwrite_output_dir to overcome." + ) + elif ( + last_checkpoint is not None and training_args.resume_from_checkpoint is None + ): + logger.info( + f"Checkpoint detected, resuming training at {last_checkpoint}. To avoid this behavior, change " + "the `--output_dir` or add `--overwrite_output_dir` to train from scratch." + ) + + # Set seed before initializing model. + set_seed(training_args.seed) + + # Get the datasets: you can either provide your own CSV/JSON training and evaluation files (see below) + # or specify a GLUE benchmark task (the dataset will be downloaded automatically from the datasets Hub). + # + # For CSV/JSON files, this script will use as labels the column called 'label' and as pair of sentences the + # sentences in columns called 'sentence1' and 'sentence2' if such column exists or the first two columns not named + # label if at least two columns are provided. + # + # If the CSVs/JSONs contain only one non-label column, the script does single sentence classification on this + # single column. You can easily tweak this behavior (see below) + # + # In distributed training, the load_dataset function guarantee that only one local process can concurrently + # download the dataset. + if data_args.dataset_name is not None: + # Downloading and loading a dataset from the hub. + raw_datasets = load_dataset( + data_args.dataset_name, + data_args.dataset_config_name, + cache_dir=model_args.cache_dir, + ) + elif data_args.task_name is not None: + # Downloading and loading a dataset from the hub. + raw_datasets = load_dataset( + "glue", data_args.task_name, cache_dir=model_args.cache_dir + ) + else: + # Loading a dataset from your local files. + # CSV/JSON training and evaluation files are needed. + data_files = { + "train": data_args.train_file, + "validation": data_args.validation_file, + } + + # Get the test dataset: you can provide your own CSV/JSON test file (see below) + # when you use `do_predict` without specifying a GLUE benchmark task. + if training_args.do_predict: + if data_args.test_file is not None: + train_extension = data_args.train_file.split(".")[-1] + test_extension = data_args.test_file.split(".")[-1] + assert ( + test_extension == train_extension + ), "`test_file` should have the same extension (csv or json) as `train_file`." + data_files["test"] = data_args.test_file + else: + raise ValueError( + "Need either a GLUE task or a test file for `do_predict`." + ) + + for key in data_files.keys(): + logger.info(f"load a local file for {key}: {data_files[key]}") + + if data_args.train_file.endswith(".csv"): + # Loading a dataset from local csv files + raw_datasets = load_dataset( + "csv", data_files=data_files, cache_dir=model_args.cache_dir + ) + else: + # Loading a dataset from local json files + raw_datasets = load_dataset( + "json", data_files=data_files, cache_dir=model_args.cache_dir + ) + # See more about loading any type of standard or custom dataset at + # https://huggingface.co/docs/datasets/loading_datasets.html. + + # Labels + if data_args.task_name is not None: + is_regression = data_args.task_name == "stsb" + if not is_regression: + label_list = raw_datasets["train"].features["label"].names + num_labels = len(label_list) + else: + num_labels = 1 + else: + # Trying to have good defaults here, don't hesitate to tweak to your needs. + is_regression = raw_datasets["train"].features["label"].dtype in [ + "float32", + "float64", + ] + if is_regression: + num_labels = 1 + else: + # A useful fast method: + # https://huggingface.co/docs/datasets/package_reference/main_classes.html#datasets.Dataset.unique + label_list = raw_datasets["train"].unique("label") + label_list.sort() # Let's sort it for determinism + num_labels = len(label_list) + + # Load pretrained model and tokenizer + # + # In distributed training, the .from_pretrained methods guarantee that only one local process can concurrently + # download model & vocab. + config = AutoConfig.from_pretrained( + model_args.config_name + if model_args.config_name + else model_args.model_name_or_path, + num_labels=num_labels, + finetuning_task=data_args.task_name, + cache_dir=model_args.cache_dir, + revision=model_args.model_revision, + use_auth_token=True if model_args.use_auth_token else None, + ) + tokenizer = AutoTokenizer.from_pretrained( + model_args.tokenizer_name + if model_args.tokenizer_name + else model_args.model_name_or_path, + cache_dir=model_args.cache_dir, + use_fast=model_args.use_fast_tokenizer, + revision=model_args.model_revision, + use_auth_token=True if model_args.use_auth_token else None, + ) + model = AutoModelForSequenceClassification.from_pretrained( + model_args.model_name_or_path, + from_tf=bool(".ckpt" in model_args.model_name_or_path), + config=config, + cache_dir=model_args.cache_dir, + revision=model_args.model_revision, + use_auth_token=True if model_args.use_auth_token else None, + ) + tokenizer.model_max_length = 512 + + # Preprocessing the raw_datasets + if data_args.task_name is not None: + sentence1_key, sentence2_key = task_to_keys[data_args.task_name] + else: + # Again, we try to have some nice defaults but don't hesitate to tweak to your use case. + non_label_column_names = [ + name for name in raw_datasets["train"].column_names if name != "label" + ] + if ( + "sentence1" in non_label_column_names + and "sentence2" in non_label_column_names + ): + sentence1_key, sentence2_key = "sentence1", "sentence2" + else: + if len(non_label_column_names) >= 2: + sentence1_key, sentence2_key = non_label_column_names[:2] + else: + sentence1_key, sentence2_key = non_label_column_names[0], None + + # Padding strategy + if data_args.pad_to_max_length: + padding = "max_length" + else: + # We will pad later, dynamically at batch creation, to the max sequence length in each batch + padding = False + + # Some models have set the order of the labels to use, so let's make sure we do use it. + label_to_id = None + if ( + model.config.label2id != PretrainedConfig(num_labels=num_labels).label2id + and data_args.task_name is not None + and not is_regression + ): + # Some have all caps in their config, some don't. + label_name_to_id = {k.lower(): v for k, v in model.config.label2id.items()} + if list(sorted(label_name_to_id.keys())) == list(sorted(label_list)): + label_to_id = { + i: int(label_name_to_id[label_list[i]]) for i in range(num_labels) + } + else: + logger.warning( + "Your model seems to have been trained with labels, but they don't match the dataset: ", + f"model labels: {list(sorted(label_name_to_id.keys()))}, dataset labels: {list(sorted(label_list))}." + "\nIgnoring the model labels as a result.", + ) + elif data_args.task_name is None and not is_regression: + label_to_id = {v: i for i, v in enumerate(label_list)} + + if label_to_id is not None: + model.config.label2id = label_to_id + model.config.id2label = {id: label for label, id in config.label2id.items()} + + if data_args.max_seq_length > tokenizer.model_max_length: + logger.warning( + f"The max_seq_length passed ({data_args.max_seq_length}) is larger than the maximum length for the" + f"model ({tokenizer.model_max_length}). Using max_seq_length={tokenizer.model_max_length}." + ) + max_seq_length = min(data_args.max_seq_length, tokenizer.model_max_length) + + def preprocess_function(examples): + # Tokenize the texts + args = ( + (examples[sentence1_key],) + if sentence2_key is None + else (examples[sentence1_key], examples[sentence2_key]) + ) + result = tokenizer( + *args, padding=padding, max_length=max_seq_length, truncation=True + ) + + # Map labels to IDs (not necessary for GLUE tasks) + if label_to_id is not None and "label" in examples: + result["label"] = [ + (label_to_id[l] if l != -1 else -1) for l in examples["label"] + ] + return result + + with training_args.main_process_first(desc="dataset map pre-processing"): + raw_datasets = raw_datasets.map( + preprocess_function, + batched=True, + load_from_cache_file=not data_args.overwrite_cache, + desc="Running tokenizer on dataset", + ) + if training_args.do_train: + if "train" not in raw_datasets: + raise ValueError("--do_train requires a train dataset") + train_dataset = raw_datasets["train"] + if data_args.max_train_samples is not None: + train_dataset = train_dataset.select(range(data_args.max_train_samples)) + + if training_args.do_eval: + if ( + "validation" not in raw_datasets + and "validation_matched" not in raw_datasets + ): + raise ValueError("--do_eval requires a validation dataset") + eval_dataset = raw_datasets[ + "validation_matched" if data_args.task_name == "mnli" else "validation" + ] + if data_args.max_eval_samples is not None: + eval_dataset = eval_dataset.select(range(data_args.max_eval_samples)) + + if ( + training_args.do_predict + or data_args.task_name is not None + or data_args.test_file is not None + ): + if "test" not in raw_datasets and "test_matched" not in raw_datasets: + raise ValueError("--do_predict requires a test dataset") + predict_dataset = raw_datasets[ + "test_matched" if data_args.task_name == "mnli" else "test" + ] + if data_args.max_predict_samples is not None: + predict_dataset = predict_dataset.select( + range(data_args.max_predict_samples) + ) + + # Log a few random samples from the training set: + if training_args.do_train: + for index in random.sample(range(len(train_dataset)), 3): + logger.info(f"Sample {index} of the training set: {train_dataset[index]}.") + + # Get the metric function + if data_args.task_name in task_to_metrics: + metric = load_metric(task_to_metrics[data_args.task_name]) + elif data_args.task_name is not None: + metric = load_metric("glue", data_args.task_name) + else: + metric = load_metric("accuracy") + + # You can define your custom compute_metrics function. It takes an `EvalPrediction` object (a namedtuple with a + # predictions and label_ids field) and has to return a dictionary string to float. + def compute_metrics(p: EvalPrediction): + preds = p.predictions[0] if isinstance(p.predictions, tuple) else p.predictions + preds = np.squeeze(preds) if is_regression else np.argmax(preds, axis=1) + if data_args.task_name is not None: + result = metric.compute(predictions=preds, references=p.label_ids) + if len(result) > 1: + result["combined_score"] = np.mean(list(result.values())).item() + return result + elif is_regression: + return {"mse": ((preds - p.label_ids) ** 2).mean().item()} + else: + return {"accuracy": (preds == p.label_ids).astype(np.float32).mean().item()} + + # Data collator will default to DataCollatorWithPadding, so we change it if we already did the padding. + if data_args.pad_to_max_length: + data_collator = default_data_collator + elif training_args.fp16: + data_collator = DataCollatorWithPadding(tokenizer, pad_to_multiple_of=8) + else: + data_collator = None + + training_args.run_name = run_name + # Initialize our Trainer + trainer = Trainer( + model=model, + args=training_args, + train_dataset=train_dataset if training_args.do_train else None, + eval_dataset=eval_dataset if training_args.do_eval else None, + compute_metrics=compute_metrics, + tokenizer=tokenizer, + data_collator=data_collator, + ) + + # Training + if training_args.do_train: + checkpoint = None + if training_args.resume_from_checkpoint is not None: + checkpoint = training_args.resume_from_checkpoint + elif last_checkpoint is not None: + checkpoint = last_checkpoint + train_result = trainer.train(resume_from_checkpoint=checkpoint) + metrics = train_result.metrics + max_train_samples = ( + data_args.max_train_samples + if data_args.max_train_samples is not None + else len(train_dataset) + ) + metrics["train_samples"] = min(max_train_samples, len(train_dataset)) + + trainer.save_model() # Saves the tokenizer too for easy upload + + trainer.log_metrics("train", metrics) + trainer.save_metrics("train", metrics) + trainer.save_state() + + # Evaluation + if training_args.do_eval: + logger.info("*** Evaluate ***") + + # Loop to handle MNLI double evaluation (matched, mis-matched) + tasks = [data_args.task_name] + eval_datasets = [eval_dataset] + if data_args.task_name == "mnli": + tasks.append("mnli-mm") + eval_datasets.append(raw_datasets["validation_mismatched"]) + + for eval_dataset, task in zip(eval_datasets, tasks): + metrics = trainer.evaluate(eval_dataset=eval_dataset) + + max_eval_samples = ( + data_args.max_eval_samples + if data_args.max_eval_samples is not None + else len(eval_dataset) + ) + metrics["eval_samples"] = min(max_eval_samples, len(eval_dataset)) + + trainer.log_metrics("eval", metrics) + trainer.save_metrics("eval", metrics) + + if training_args.do_predict: + logger.info("*** Predict ***") + + # Loop to handle MNLI double evaluation (matched, mis-matched) + tasks = [data_args.task_name] + predict_datasets = [predict_dataset] + if data_args.task_name == "mnli": + tasks.append("mnli-mm") + predict_datasets.append(raw_datasets["test_mismatched"]) + + for predict_dataset, task in zip(predict_datasets, tasks): + # Removing the `label` columns because it contains -1 and Trainer won't like that. + predict_dataset = predict_dataset.remove_columns("label") + predictions = trainer.predict( + predict_dataset, metric_key_prefix="predict" + ).predictions + predictions = ( + np.squeeze(predictions) + if is_regression + else np.argmax(predictions, axis=1) + ) + + output_predict_file = os.path.join( + training_args.output_dir, f"predict_results_{task}.txt" + ) + if trainer.is_world_process_zero(): + with open(output_predict_file, "w") as writer: + logger.info(f"***** Predict results {task} *****") + writer.write("index\tprediction\n") + for index, item in enumerate(predictions): + if is_regression: + writer.write(f"{index}\t{item:3.3f}\n") + else: + item = label_list[item] + writer.write(f"{index}\t{item}\n") + + if training_args.push_to_hub: + kwargs = { + "finetuned_from": model_args.model_name_or_path, + "tasks": "text-classification", + } + if data_args.task_name is not None: + kwargs["language"] = "en" + kwargs["dataset_tags"] = "glue" + kwargs["dataset_args"] = data_args.task_name + kwargs["dataset"] = f"GLUE {data_args.task_name.upper()}" + + trainer.push_to_hub(**kwargs) + + +def _mp_fn(index): + # 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"\u001b[K |████████████████████████████████| 1.8 MB 13.7 MB/s \n", + "\u001b[K |████████████████████████████████| 133 kB 67.5 MB/s \n", + "\u001b[K |████████████████████████████████| 170 kB 59.0 MB/s \n", + "\u001b[K |████████████████████████████████| 97 kB 9.1 MB/s \n", + "\u001b[K |████████████████████████████████| 138 kB 67.8 MB/s \n", + "\u001b[K |████████████████████████████████| 63 kB 2.4 MB/s \n", + "\u001b[K |████████████████████████████████| 62 kB 1.2 MB/s \n", + "\u001b[?25h Building wheel for subprocess32 (setup.py) ... \u001b[?25l\u001b[?25hdone\n", + " Building wheel for pathtools (setup.py) ... \u001b[?25l\u001b[?25hdone\n", + "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n", + "google-colab 1.0.0 requires requests~=2.23.0, but you have requests 2.26.0 which is incompatible.\n", + "datascience 0.10.6 requires folium==0.2.1, but you have folium 0.8.3 which is incompatible.\u001b[0m\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: You can find your API key in your browser here: https://wandb.ai/authorize\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Paste an API key from your profile and hit enter: \n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Appending key for api.wandb.ai to your netrc file: /root/.netrc\n" + ], + "name": "stdout" + } + ] + }, + { + "cell_type": "code", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "mHkxgp5vcCyC", + "outputId": "eaa6b844-629c-4f3d-f04b-e6f32b13b8ea" + }, + "source": [ + "!pip install -qqU https://github.com/huggingface/transformers/archive/refs/heads/master.zip datasets[streaming] seqeval\n", + "# !pip install -qqU transformers datasets[streaming] seqeval\n", + "# !pip install -qqU git+https://github.com/google/flax.git\n", + "# !pip install -qqU https://github.com/kpu/kenlm/archive/master.zip\n", + "!pip install -qqU torch" + ], + "execution_count": null, + "outputs": [ + { + "output_type": "stream", + "text": [ + "\u001b[K | 11.2 MB 2.8 MB/s\n", + "\u001b[?25h Installing build dependencies ... \u001b[?25l\u001b[?25hdone\n", + " Getting requirements to build wheel ... \u001b[?25l\u001b[?25hdone\n", + " Preparing wheel metadata ... \u001b[?25l\u001b[?25hdone\n", + "\u001b[K |████████████████████████████████| 262 kB 14.5 MB/s \n", + "\u001b[K |████████████████████████████████| 43 kB 2.7 MB/s \n", + "\u001b[K |████████████████████████████████| 3.3 MB 15.5 MB/s \n", + "\u001b[K |████████████████████████████████| 636 kB 58.8 MB/s \n", + "\u001b[K |████████████████████████████████| 895 kB 49.8 MB/s \n", + "\u001b[K |████████████████████████████████| 243 kB 59.4 MB/s \n", + "\u001b[K |████████████████████████████████| 118 kB 73.2 MB/s \n", + "\u001b[K |████████████████████████████████| 1.3 MB 59.1 MB/s \n", + "\u001b[K |████████████████████████████████| 294 kB 62.5 MB/s \n", + "\u001b[K |████████████████████████████████| 142 kB 71.2 MB/s \n", + "\u001b[?25h Building wheel for transformers (PEP 517) ... \u001b[?25l\u001b[?25hdone\n", + " Building wheel for seqeval (setup.py) ... \u001b[?25l\u001b[?25hdone\n" + ], + "name": "stdout" + } + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "C5JL_ErE-Erd" + }, + "source": [ + "----" + ] + }, + { + "cell_type": "code", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "2Te2T37r-Ehh", + "outputId": "2274444c-685f-479c-d90a-3e9b3850e8ed" + }, + "source": [ + "%%writefile run_ner.py\n", + "#!/usr/bin/env python\n", + "# coding=utf-8\n", + "# Copyright 2020 The HuggingFace Team All rights reserved.\n", + "#\n", + "# Licensed under the Apache License, Version 2.0 (the \"License\");\n", + "# you may not use this file except in compliance with the License.\n", + "# You may obtain a copy of the License at\n", + "#\n", + "# http://www.apache.org/licenses/LICENSE-2.0\n", + "#\n", + "# Unless required by applicable law or agreed to in writing, software\n", + "# distributed under the License is distributed on an \"AS IS\" BASIS,\n", + "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n", + "# See the License for the specific language governing permissions and\n", + "# limitations under the License.\n", + "\"\"\"\n", + "Fine-tuning the library models for token classification.\n", + "\"\"\"\n", + "# You can also adapt this script on your own token classification task and datasets. Pointers for this are left as\n", + "# comments.\n", + "\n", + "import logging\n", + "import os\n", + "import sys\n", + "from dataclasses import dataclass, field\n", + "from typing import Optional\n", + "\n", + "import datasets\n", + "import numpy as np\n", + "from datasets import ClassLabel, load_dataset, load_metric\n", + "\n", + "import transformers\n", + "from transformers import (\n", + " AutoConfig,\n", + " AutoModelForTokenClassification,\n", + " AutoTokenizer,\n", + " DataCollatorForTokenClassification,\n", + " HfArgumentParser,\n", + " PreTrainedTokenizerFast,\n", + " Trainer,\n", + " TrainingArguments,\n", + " set_seed,\n", + ")\n", + "from transformers.trainer_utils import get_last_checkpoint\n", + "from transformers.utils import check_min_version\n", + "from transformers.utils.versions import require_version\n", + "\n", + "\n", + "# Will error if the minimal version of Transformers is not installed. Remove at your own risks.\n", + "check_min_version(\"4.9.0.dev0\")\n", + "\n", + "require_version(\"datasets>=1.8.0\", \"To fix: pip install -r examples/pytorch/token-classification/requirements.txt\")\n", + "\n", + "logger = logging.getLogger(__name__)\n", + "\n", + "\n", + "@dataclass\n", + "class ModelArguments:\n", + " \"\"\"\n", + " Arguments pertaining to which model/config/tokenizer we are going to fine-tune from.\n", + " \"\"\"\n", + "\n", + " model_name_or_path: str = field(\n", + " metadata={\"help\": \"Path to pretrained model or model identifier from huggingface.co/models\"}\n", + " )\n", + " config_name: Optional[str] = field(\n", + " default=None, metadata={\"help\": \"Pretrained config name or path if not the same as model_name\"}\n", + " )\n", + " tokenizer_name: Optional[str] = field(\n", + " default=None, metadata={\"help\": \"Pretrained tokenizer name or path if not the same as model_name\"}\n", + " )\n", + " cache_dir: Optional[str] = field(\n", + " default=None,\n", + " metadata={\"help\": \"Where do you want to store the pretrained models downloaded from huggingface.co\"},\n", + " )\n", + " model_revision: str = field(\n", + " default=\"main\",\n", + " metadata={\"help\": \"The specific model version to use (can be a branch name, tag name or commit id).\"},\n", + " )\n", + " use_auth_token: bool = field(\n", + " default=False,\n", + " metadata={\n", + " \"help\": \"Will use the token generated when running `transformers-cli login` (necessary to use this script \"\n", + " \"with private models).\"\n", + " },\n", + " )\n", + "\n", + "\n", + "@dataclass\n", + "class DataTrainingArguments:\n", + " \"\"\"\n", + " Arguments pertaining to what data we are going to input our model for training and eval.\n", + " \"\"\"\n", + "\n", + " task_name: Optional[str] = field(default=\"ner\", metadata={\"help\": \"The name of the task (ner, pos...).\"})\n", + " dataset_name: Optional[str] = field(\n", + " default=None, metadata={\"help\": \"The name of the dataset to use (via the datasets library).\"}\n", + " )\n", + " dataset_config_name: Optional[str] = field(\n", + " default=None, metadata={\"help\": \"The configuration name of the dataset to use (via the datasets library).\"}\n", + " )\n", + " train_file: Optional[str] = field(\n", + " default=None, metadata={\"help\": \"The input training data file (a csv or JSON file).\"}\n", + " )\n", + " validation_file: Optional[str] = field(\n", + " default=None,\n", + " metadata={\"help\": \"An optional input evaluation data file to evaluate on (a csv or JSON file).\"},\n", + " )\n", + " test_file: Optional[str] = field(\n", + " default=None,\n", + " metadata={\"help\": \"An optional input test data file to predict on (a csv or JSON file).\"},\n", + " )\n", + " text_column_name: Optional[str] = field(\n", + " default=None, metadata={\"help\": \"The column name of text to input in the file (a csv or JSON file).\"}\n", + " )\n", + " label_column_name: Optional[str] = field(\n", + " default=None, metadata={\"help\": \"The column name of label to input in the file (a csv or JSON file).\"}\n", + " )\n", + " overwrite_cache: bool = field(\n", + " default=False, metadata={\"help\": \"Overwrite the cached training and evaluation sets\"}\n", + " )\n", + " preprocessing_num_workers: Optional[int] = field(\n", + " default=None,\n", + " metadata={\"help\": \"The number of processes to use for the preprocessing.\"},\n", + " )\n", + " pad_to_max_length: bool = field(\n", + " default=False,\n", + " metadata={\n", + " \"help\": \"Whether to pad all samples to model maximum sentence length. \"\n", + " \"If False, will pad the samples dynamically when batching to the maximum length in the batch. More \"\n", + " \"efficient on GPU but very bad for TPU.\"\n", + " },\n", + " )\n", + " max_train_samples: Optional[int] = field(\n", + " default=None,\n", + " metadata={\n", + " \"help\": \"For debugging purposes or quicker training, truncate the number of training examples to this \"\n", + " \"value if set.\"\n", + " },\n", + " )\n", + " max_eval_samples: Optional[int] = field(\n", + " default=None,\n", + " metadata={\n", + " \"help\": \"For debugging purposes or quicker training, truncate the number of evaluation examples to this \"\n", + " \"value if set.\"\n", + " },\n", + " )\n", + " max_predict_samples: Optional[int] = field(\n", + " default=None,\n", + " metadata={\n", + " \"help\": \"For debugging purposes or quicker training, truncate the number of prediction examples to this \"\n", + " \"value if set.\"\n", + " },\n", + " )\n", + " label_all_tokens: bool = field(\n", + " default=False,\n", + " metadata={\n", + " \"help\": \"Whether to put the label for one word on all tokens of generated by that word or just on the \"\n", + " \"one (in which case the other tokens will have a padding index).\"\n", + " },\n", + " )\n", + " return_entity_level_metrics: bool = field(\n", + " default=False,\n", + " metadata={\"help\": \"Whether to return all the entity levels during evaluation or just the overall ones.\"},\n", + " )\n", + "\n", + " def __post_init__(self):\n", + " if self.dataset_name is None and self.train_file is None and self.validation_file is None:\n", + " raise ValueError(\"Need either a dataset name or a training/validation file.\")\n", + " else:\n", + " if self.train_file is not None:\n", + " extension = self.train_file.split(\".\")[-1]\n", + " assert extension in [\"csv\", \"json\"], \"`train_file` should be a csv or a json file.\"\n", + " if self.validation_file is not None:\n", + " extension = self.validation_file.split(\".\")[-1]\n", + " assert extension in [\"csv\", \"json\"], \"`validation_file` should be a csv or a json file.\"\n", + " self.task_name = self.task_name.lower()\n", + "\n", + "\n", + "def main():\n", + " # See all possible arguments in src/transformers/training_args.py\n", + " # or by passing the --help flag to this script.\n", + " # We now keep distinct sets of args, for a cleaner separation of concerns.\n", + "\n", + " parser = HfArgumentParser((ModelArguments, DataTrainingArguments, TrainingArguments))\n", + " if len(sys.argv) == 2 and sys.argv[1].endswith(\".json\"):\n", + " # If we pass only one argument to the script and it's the path to a json file,\n", + " # let's parse it to get our arguments.\n", + " model_args, data_args, training_args = parser.parse_json_file(json_file=os.path.abspath(sys.argv[1]))\n", + " else:\n", + " model_args, data_args, training_args = parser.parse_args_into_dataclasses()\n", + "\n", + " # Setup logging\n", + " logging.basicConfig(\n", + " format=\"%(asctime)s - %(levelname)s - %(name)s - %(message)s\",\n", + " datefmt=\"%m/%d/%Y %H:%M:%S\",\n", + " handlers=[logging.StreamHandler(sys.stdout)],\n", + " )\n", + "\n", + " log_level = training_args.get_process_log_level()\n", + " logger.setLevel(log_level)\n", + " datasets.utils.logging.set_verbosity(log_level)\n", + " transformers.utils.logging.set_verbosity(log_level)\n", + " transformers.utils.logging.enable_default_handler()\n", + " transformers.utils.logging.enable_explicit_format()\n", + "\n", + " # Log on each process the small summary:\n", + " logger.warning(\n", + " f\"Process rank: {training_args.local_rank}, device: {training_args.device}, n_gpu: {training_args.n_gpu}\"\n", + " + f\"distributed training: {bool(training_args.local_rank != -1)}, 16-bits training: {training_args.fp16}\"\n", + " )\n", + " logger.info(f\"Training/evaluation parameters {training_args}\")\n", + "\n", + " # Detecting last checkpoint.\n", + " last_checkpoint = None\n", + " if os.path.isdir(training_args.output_dir) and training_args.do_train and not training_args.overwrite_output_dir:\n", + " last_checkpoint = get_last_checkpoint(training_args.output_dir)\n", + " if last_checkpoint is None and len(os.listdir(training_args.output_dir)) > 0:\n", + " raise ValueError(\n", + " f\"Output directory ({training_args.output_dir}) already exists and is not empty. \"\n", + " \"Use --overwrite_output_dir to overcome.\"\n", + " )\n", + " elif last_checkpoint is not None and training_args.resume_from_checkpoint is None:\n", + " logger.info(\n", + " f\"Checkpoint detected, resuming training at {last_checkpoint}. To avoid this behavior, change \"\n", + " \"the `--output_dir` or add `--overwrite_output_dir` to train from scratch.\"\n", + " )\n", + "\n", + " # Set seed before initializing model.\n", + " set_seed(training_args.seed)\n", + "\n", + " # Get the datasets: you can either provide your own CSV/JSON/TXT training and evaluation files (see below)\n", + " # or just provide the name of one of the public datasets available on the hub at https://huggingface.co/datasets/\n", + " # (the dataset will be downloaded automatically from the datasets Hub).\n", + " #\n", + " # For CSV/JSON files, this script will use the column called 'text' or the first column if no column called\n", + " # 'text' is found. You can easily tweak this behavior (see below).\n", + " #\n", + " # In distributed training, the load_dataset function guarantee that only one local process can concurrently\n", + " # download the dataset.\n", + " if data_args.dataset_name is not None:\n", + " # Downloading and loading a dataset from the hub.\n", + " raw_datasets = load_dataset(\n", + " data_args.dataset_name, data_args.dataset_config_name, cache_dir=model_args.cache_dir\n", + " )\n", + " else:\n", + " data_files = {}\n", + " if data_args.train_file is not None:\n", + " data_files[\"train\"] = data_args.train_file\n", + " if data_args.validation_file is not None:\n", + " data_files[\"validation\"] = data_args.validation_file\n", + " if data_args.test_file is not None:\n", + " data_files[\"test\"] = data_args.test_file\n", + " extension = data_args.train_file.split(\".\")[-1]\n", + " raw_datasets = load_dataset(extension, data_files=data_files, cache_dir=model_args.cache_dir)\n", + " # See more about loading any type of standard or custom dataset (from files, python dict, pandas DataFrame, etc) at\n", + " # https://huggingface.co/docs/datasets/loading_datasets.html.\n", + "\n", + " if training_args.do_train:\n", + " column_names = raw_datasets[\"train\"].column_names\n", + " features = raw_datasets[\"train\"].features\n", + " else:\n", + " column_names = raw_datasets[\"validation\"].column_names\n", + " features = raw_datasets[\"validation\"].features\n", + "\n", + " if data_args.text_column_name is not None:\n", + " text_column_name = data_args.text_column_name\n", + " elif \"tokens\" in column_names:\n", + " text_column_name = \"tokens\"\n", + " else:\n", + " text_column_name = column_names[0]\n", + "\n", + " if data_args.label_column_name is not None:\n", + " label_column_name = data_args.label_column_name\n", + " elif f\"{data_args.task_name}_tags\" in column_names:\n", + " label_column_name = f\"{data_args.task_name}_tags\"\n", + " else:\n", + " label_column_name = column_names[1]\n", + "\n", + " # In the event the labels are not a `Sequence[ClassLabel]`, we will need to go through the dataset to get the\n", + " # unique labels.\n", + " def get_label_list(labels):\n", + " unique_labels = set()\n", + " for label in labels:\n", + " unique_labels = unique_labels | set(label)\n", + " label_list = list(unique_labels)\n", + " label_list.sort()\n", + " return label_list\n", + "\n", + " if isinstance(features[label_column_name].feature, ClassLabel):\n", + " label_list = features[label_column_name].feature.names\n", + " # No need to convert the labels since they are already ints.\n", + " label_to_id = {i: i for i in range(len(label_list))}\n", + " else:\n", + " label_list = get_label_list(raw_datasets[\"train\"][label_column_name])\n", + " label_to_id = {l: i for i, l in enumerate(label_list)}\n", + " num_labels = len(label_list)\n", + "\n", + " # Load pretrained model and tokenizer\n", + " #\n", + " # Distributed training:\n", + " # The .from_pretrained methods guarantee that only one local process can concurrently\n", + " # download model & vocab.\n", + " config = AutoConfig.from_pretrained(\n", + " model_args.config_name if model_args.config_name else model_args.model_name_or_path,\n", + " num_labels=num_labels,\n", + " label2id=label_to_id,\n", + " id2label={i: l for l, i in label_to_id.items()},\n", + " finetuning_task=data_args.task_name,\n", + " cache_dir=model_args.cache_dir,\n", + " revision=model_args.model_revision,\n", + " use_auth_token=True if model_args.use_auth_token else None,\n", + " )\n", + "\n", + " tokenizer_name_or_path = model_args.tokenizer_name if model_args.tokenizer_name else model_args.model_name_or_path\n", + " if config.model_type in {\"gpt2\", \"roberta\"}:\n", + " tokenizer = AutoTokenizer.from_pretrained(\n", + " tokenizer_name_or_path,\n", + " cache_dir=model_args.cache_dir,\n", + " use_fast=True,\n", + " revision=model_args.model_revision,\n", + " use_auth_token=True if model_args.use_auth_token else None,\n", + " add_prefix_space=True,\n", + " )\n", + " else:\n", + " tokenizer = AutoTokenizer.from_pretrained(\n", + " tokenizer_name_or_path,\n", + " cache_dir=model_args.cache_dir,\n", + " use_fast=True,\n", + " revision=model_args.model_revision,\n", + " use_auth_token=True if model_args.use_auth_token else None,\n", + " )\n", + " tokenizer.model_max_length = 512\n", + "\n", + " model = AutoModelForTokenClassification.from_pretrained(\n", + " model_args.model_name_or_path,\n", + " from_tf=bool(\".ckpt\" in model_args.model_name_or_path),\n", + " config=config,\n", + " cache_dir=model_args.cache_dir,\n", + " revision=model_args.model_revision,\n", + " use_auth_token=True if model_args.use_auth_token else None,\n", + " )\n", + "\n", + " # Tokenizer check: this script requires a fast tokenizer.\n", + " if not isinstance(tokenizer, PreTrainedTokenizerFast):\n", + " raise ValueError(\n", + " \"This example script only works for models that have a fast tokenizer. Checkout the big table of models \"\n", + " \"at https://huggingface.co/transformers/index.html#supported-frameworks to find the model types that meet this \"\n", + " \"requirement\"\n", + " )\n", + "\n", + " # Preprocessing the dataset\n", + " # Padding strategy\n", + " padding = \"max_length\" if data_args.pad_to_max_length else False\n", + "\n", + " # Tokenize all texts and align the labels with them.\n", + " def tokenize_and_align_labels(examples):\n", + " tokenized_inputs = tokenizer(\n", + " examples[text_column_name],\n", + " padding=padding,\n", + " max_length=512,\n", + " truncation=True,\n", + " # We use this argument because the texts in our dataset are lists of words (with a label for each word).\n", + " is_split_into_words=True,\n", + " )\n", + " labels = []\n", + " for i, label in enumerate(examples[label_column_name]):\n", + " word_ids = tokenized_inputs.word_ids(batch_index=i)\n", + " previous_word_idx = None\n", + " label_ids = []\n", + " for word_idx in word_ids:\n", + " # Special tokens have a word id that is None. We set the label to -100 so they are automatically\n", + " # ignored in the loss function.\n", + " if word_idx is None:\n", + " label_ids.append(-100)\n", + " # We set the label for the first token of each word.\n", + " elif word_idx != previous_word_idx:\n", + " label_ids.append(label_to_id[label[word_idx]])\n", + " # For the other tokens in a word, we set the label to either the current label or -100, depending on\n", + " # the label_all_tokens flag.\n", + " else:\n", + " label_ids.append(label_to_id[label[word_idx]] if data_args.label_all_tokens else -100)\n", + " previous_word_idx = word_idx\n", + "\n", + " labels.append(label_ids)\n", + " tokenized_inputs[\"labels\"] = labels\n", + " return tokenized_inputs\n", + "\n", + " if training_args.do_train:\n", + " if \"train\" not in raw_datasets:\n", + " raise ValueError(\"--do_train requires a train dataset\")\n", + " train_dataset = raw_datasets[\"train\"]\n", + " if data_args.max_train_samples is not None:\n", + " train_dataset = train_dataset.select(range(data_args.max_train_samples))\n", + " with training_args.main_process_first(desc=\"train dataset map pre-processing\"):\n", + " train_dataset = train_dataset.map(\n", + " tokenize_and_align_labels,\n", + " batched=True,\n", + " num_proc=data_args.preprocessing_num_workers,\n", + " load_from_cache_file=not data_args.overwrite_cache,\n", + " desc=\"Running tokenizer on train dataset\",\n", + " )\n", + "\n", + " if training_args.do_eval:\n", + " if \"validation\" not in raw_datasets:\n", + " raise ValueError(\"--do_eval requires a validation dataset\")\n", + " eval_dataset = raw_datasets[\"validation\"]\n", + " if data_args.max_eval_samples is not None:\n", + " eval_dataset = eval_dataset.select(range(data_args.max_eval_samples))\n", + " with training_args.main_process_first(desc=\"validation dataset map pre-processing\"):\n", + " eval_dataset = eval_dataset.map(\n", + " tokenize_and_align_labels,\n", + " batched=True,\n", + " num_proc=data_args.preprocessing_num_workers,\n", + " load_from_cache_file=not data_args.overwrite_cache,\n", + " desc=\"Running tokenizer on validation dataset\",\n", + " )\n", + "\n", + " if training_args.do_predict:\n", + " if \"test\" not in raw_datasets:\n", + " raise ValueError(\"--do_predict requires a test dataset\")\n", + " predict_dataset = raw_datasets[\"test\"]\n", + " if data_args.max_predict_samples is not None:\n", + " predict_dataset = predict_dataset.select(range(data_args.max_predict_samples))\n", + " with training_args.main_process_first(desc=\"prediction dataset map pre-processing\"):\n", + " predict_dataset = predict_dataset.map(\n", + " tokenize_and_align_labels,\n", + " batched=True,\n", + " num_proc=data_args.preprocessing_num_workers,\n", + " load_from_cache_file=not data_args.overwrite_cache,\n", + " desc=\"Running tokenizer on prediction dataset\",\n", + " )\n", + "\n", + " # Data collator\n", + " data_collator = DataCollatorForTokenClassification(tokenizer, pad_to_multiple_of=8 if training_args.fp16 else None)\n", + "\n", + " # Metrics\n", + " metric = load_metric(\"seqeval\")\n", + "\n", + " def compute_metrics(p):\n", + " predictions, labels = p\n", + " predictions = np.argmax(predictions, axis=2)\n", + "\n", + " # Remove ignored index (special tokens)\n", + " true_predictions = [\n", + " [label_list[p] for (p, l) in zip(prediction, label) if l != -100]\n", + " for prediction, label in zip(predictions, labels)\n", + " ]\n", + " true_labels = [\n", + " [label_list[l] for (p, l) in zip(prediction, label) if l != -100]\n", + " for prediction, label in zip(predictions, labels)\n", + " ]\n", + "\n", + " results = metric.compute(predictions=true_predictions, references=true_labels)\n", + " if data_args.return_entity_level_metrics:\n", + " # Unpack nested dictionaries\n", + " final_results = {}\n", + " for key, value in results.items():\n", + " if isinstance(value, dict):\n", + " for n, v in value.items():\n", + " final_results[f\"{key}_{n}\"] = v\n", + " else:\n", + " final_results[key] = value\n", + " return final_results\n", + " else:\n", + " return {\n", + " \"precision\": results[\"overall_precision\"],\n", + " \"recall\": results[\"overall_recall\"],\n", + " \"f1\": results[\"overall_f1\"],\n", + " \"accuracy\": results[\"overall_accuracy\"],\n", + " }\n", + "\n", + " # Initialize our Trainer\n", + " trainer = Trainer(\n", + " model=model,\n", + " args=training_args,\n", + " train_dataset=train_dataset if training_args.do_train else None,\n", + " eval_dataset=eval_dataset if training_args.do_eval else None,\n", + " tokenizer=tokenizer,\n", + " data_collator=data_collator,\n", + " compute_metrics=compute_metrics,\n", + " )\n", + "\n", + " # Training\n", + " if training_args.do_train:\n", + " checkpoint = None\n", + " if training_args.resume_from_checkpoint is not None:\n", + " checkpoint = training_args.resume_from_checkpoint\n", + " elif last_checkpoint is not None:\n", + " checkpoint = last_checkpoint\n", + " train_result = trainer.train(resume_from_checkpoint=checkpoint)\n", + " metrics = train_result.metrics\n", + " trainer.save_model() # Saves the tokenizer too for easy upload\n", + "\n", + " max_train_samples = (\n", + " data_args.max_train_samples if data_args.max_train_samples is not None else len(train_dataset)\n", + " )\n", + " metrics[\"train_samples\"] = min(max_train_samples, len(train_dataset))\n", + "\n", + " trainer.log_metrics(\"train\", metrics)\n", + " trainer.save_metrics(\"train\", metrics)\n", + " trainer.save_state()\n", + "\n", + " # Evaluation\n", + " if training_args.do_eval:\n", + " logger.info(\"*** Evaluate ***\")\n", + "\n", + " metrics = trainer.evaluate()\n", + "\n", + " max_eval_samples = data_args.max_eval_samples if data_args.max_eval_samples is not None else len(eval_dataset)\n", + " metrics[\"eval_samples\"] = min(max_eval_samples, len(eval_dataset))\n", + "\n", + " trainer.log_metrics(\"eval\", metrics)\n", + " trainer.save_metrics(\"eval\", metrics)\n", + "\n", + " # Predict\n", + " if training_args.do_predict:\n", + " logger.info(\"*** Predict ***\")\n", + "\n", + " predictions, labels, metrics = trainer.predict(predict_dataset, metric_key_prefix=\"predict\")\n", + " predictions = np.argmax(predictions, axis=2)\n", + "\n", + " # Remove ignored index (special tokens)\n", + " true_predictions = [\n", + " [label_list[p] for (p, l) in zip(prediction, label) if l != -100]\n", + " for prediction, label in zip(predictions, labels)\n", + " ]\n", + "\n", + " trainer.log_metrics(\"predict\", metrics)\n", + " trainer.save_metrics(\"predict\", metrics)\n", + "\n", + " # Save predictions\n", + " output_predictions_file = os.path.join(training_args.output_dir, \"predictions.txt\")\n", + " if trainer.is_world_process_zero():\n", + " with open(output_predictions_file, \"w\") as writer:\n", + " for prediction in true_predictions:\n", + " writer.write(\" \".join(prediction) + \"\\n\")\n", + "\n", + " if training_args.push_to_hub:\n", + " kwargs = {\"finetuned_from\": model_args.model_name_or_path, \"tasks\": \"token-classification\"}\n", + " if data_args.dataset_name is not None:\n", + " kwargs[\"dataset_tags\"] = data_args.dataset_name\n", + " if data_args.dataset_config_name is not None:\n", + " kwargs[\"dataset_args\"] = data_args.dataset_config_name\n", + " kwargs[\"dataset\"] = f\"{data_args.dataset_name} {data_args.dataset_config_name}\"\n", + " else:\n", + " kwargs[\"dataset\"] = data_args.dataset_name\n", + "\n", + " trainer.push_to_hub(**kwargs)\n", + "\n", + "\n", + "def _mp_fn(index):\n", + " # For xla_spawn (TPUs)\n", + " main()\n", + "\n", + "\n", + "if __name__ == \"__main__\":\n", + " main()\n" + ], + "execution_count": null, + "outputs": [ + { + "output_type": "stream", + "text": [ + "Writing run_ner.py\n" + ], + "name": "stdout" + } + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "y7Yy3BzmCOkb" + }, + "source": [ + "models = [\n", + " \"bertin-project/bertin-base-gaussian-exp-512seqlen\",\n", + " \"bertin-project/bertin-base-random-exp-512seqlen\",\n", + " \"bertin-project/bertin-base-gaussian\",\n", + " \"bertin-project/bertin-base-stepwise\",\n", + " \"bertin-project/bertin-base-random\",\n", + " \"bertin-project/bertin-roberta-base-spanish\",\n", + " \"flax-community/bertin-roberta-large-spanish\",\n", + " \"BSC-TeMU/roberta-base-bne\",\n", + " \"dccuchile/bert-base-spanish-wwm-cased\",\n", + " \"bert-base-multilingual-cased\",\n", + "]" + ], + "execution_count": null, + "outputs": [] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "TFxp2fElBJb3" + }, + "source": [ + "## NER" + ] + }, + { + "cell_type": "code", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "tpygu0_z7sbu", + "outputId": "fd9b2852-8b50-471c-c1f0-28b4c880b4f9" + }, + "source": [ + "#!wget -O run_ner.py https://raw.githubusercontent.com/huggingface/transformers/master/examples/pytorch/token-classification/run_ner.py\n", + "for model in models:\n", + " !WANDB_PROJECT=bertin-eval TOKENIZERS_PARALLELISM=false CUDA_LAUNCH_BLOCKING=1 python run_ner.py \\\n", + " --model_name_or_path $model \\\n", + " --dataset_name conll2002 \\\n", + " --dataset_config_name es \\\n", + " --output_dir ./outputs \\\n", + " --overwrite_output_dir \\\n", + " --pad_to_max_length \\\n", + " --num_train_epochs 5 \\\n", + " --do_train \\\n", + " --do_eval" + ], + "execution_count": null, + "outputs": [ + { + "output_type": "stream", + "text": [ + "2021-07-19 08:22:26.414910: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Successfully opened dynamic library libcudart.so.11.0\n", + "07/19/2021 08:22:28 - WARNING - __main__ - Process rank: -1, device: cuda:0, n_gpu: 1distributed training: False, 16-bits training: False\n", + "07/19/2021 08:22:28 - INFO - __main__ - Training/evaluation parameters TrainingArguments(\n", + "_n_gpu=1,\n", + "adafactor=False,\n", + "adam_beta1=0.9,\n", + "adam_beta2=0.999,\n", + "adam_epsilon=1e-08,\n", + "dataloader_drop_last=False,\n", + "dataloader_num_workers=0,\n", + "dataloader_pin_memory=True,\n", + "ddp_find_unused_parameters=None,\n", + "debug=[],\n", + "deepspeed=None,\n", + "disable_tqdm=False,\n", + "do_eval=True,\n", + "do_predict=False,\n", + "do_train=True,\n", + "eval_accumulation_steps=None,\n", + "eval_steps=500,\n", + "evaluation_strategy=IntervalStrategy.NO,\n", + "fp16=False,\n", + "fp16_backend=auto,\n", + "fp16_full_eval=False,\n", + "fp16_opt_level=O1,\n", + "gradient_accumulation_steps=1,\n", + "greater_is_better=None,\n", + "group_by_length=False,\n", + "ignore_data_skip=False,\n", + "label_names=None,\n", + "label_smoothing_factor=0.0,\n", + "learning_rate=5e-05,\n", + "length_column_name=length,\n", + "load_best_model_at_end=False,\n", + "local_rank=-1,\n", + "log_level=-1,\n", + "log_level_replica=-1,\n", + "log_on_each_node=True,\n", + "logging_dir=./outputs/runs/Jul19_08-22-28_eab5184de9ff,\n", + "logging_first_step=False,\n", + "logging_steps=500,\n", + "logging_strategy=IntervalStrategy.STEPS,\n", + "lr_scheduler_type=SchedulerType.LINEAR,\n", + "max_grad_norm=1.0,\n", + "max_steps=-1,\n", + "metric_for_best_model=None,\n", + "mp_parameters=,\n", + "no_cuda=False,\n", + "num_train_epochs=5.0,\n", + "output_dir=./outputs,\n", + "overwrite_output_dir=True,\n", + "past_index=-1,\n", + "per_device_eval_batch_size=8,\n", + "per_device_train_batch_size=8,\n", + "prediction_loss_only=False,\n", + "push_to_hub=False,\n", + "push_to_hub_model_id=outputs,\n", + "push_to_hub_organization=None,\n", + "push_to_hub_token=None,\n", + "remove_unused_columns=True,\n", + "report_to=['tensorboard', 'wandb'],\n", + "resume_from_checkpoint=None,\n", + "run_name=./outputs,\n", + "save_on_each_node=False,\n", + "save_steps=500,\n", + "save_strategy=IntervalStrategy.STEPS,\n", + "save_total_limit=None,\n", + "seed=42,\n", + "sharded_ddp=[],\n", + "skip_memory_metrics=True,\n", + "tpu_metrics_debug=False,\n", + "tpu_num_cores=None,\n", + "use_legacy_prediction_loop=False,\n", + "warmup_ratio=0.0,\n", + "warmup_steps=0,\n", + "weight_decay=0.0,\n", + ")\n", + "07/19/2021 08:22:30 - INFO - datasets.utils.file_utils - https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py not found in cache or force_download set to True, downloading to /root/.cache/huggingface/datasets/downloads/tmpruzr4ail\n", + "Downloading: 9.23kB [00:00, 6.35MB/s] \n", + "07/19/2021 08:22:30 - INFO - datasets.utils.file_utils - storing https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py in cache at /root/.cache/huggingface/datasets/downloads/519ce586cff9011c0a219975915c0003e536279b4bd42403835d1cf43fff22f9.ace7fba2d67dd937707ecbe9d69d7b5ffaa6a9a0958eef09d32307e5a9e91d1b.py\n", + "07/19/2021 08:22:30 - INFO - datasets.utils.file_utils - creating metadata file for 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/root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5/conll2002.py\n", + "07/19/2021 08:22:30 - INFO - datasets.load - Copying dataset infos file from https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/dataset_infos.json to /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5/dataset_infos.json\n", + "07/19/2021 08:22:30 - INFO - datasets.load - Creating metadata file for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py at /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5/conll2002.json\n", + "07/19/2021 08:22:31 - INFO - datasets.load - Found main folder for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py at /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002\n", + "07/19/2021 08:22:31 - INFO - datasets.load - Found specific version folder for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py at /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5\n", + "07/19/2021 08:22:31 - INFO - datasets.load - Found script file from https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py to /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5/conll2002.py\n", + "07/19/2021 08:22:31 - INFO - datasets.load - Found dataset infos file from https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/dataset_infos.json to /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5/dataset_infos.json\n", + "07/19/2021 08:22:31 - INFO - datasets.load - Found metadata file for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py at /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5/conll2002.json\n", + "07/19/2021 08:22:31 - INFO - datasets.info - Loading Dataset Infos from /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5\n", + "07/19/2021 08:22:31 - INFO - datasets.builder - Generating dataset conll2002 (/root/.cache/huggingface/datasets/conll2002/es/1.0.0/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5)\n", + "Downloading and preparing dataset conll2002/es (download: 3.95 MiB, generated: 8.87 MiB, post-processed: Unknown size, total: 12.82 MiB) to /root/.cache/huggingface/datasets/conll2002/es/1.0.0/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5...\n", + "07/19/2021 08:22:31 - INFO - datasets.builder - Dataset not on Hf google storage. 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>> loading configuration file https://huggingface.co/bertin-project/bertin-base-gaussian-exp-512seqlen/resolve/main/config.json from cache at /root/.cache/huggingface/transformers/ff85ac64e56df502ec043af591c8b7be85583b22e6a4f5715146d461cd789f97.08210214ecaf5cd53c702826a604e564d8af557125033eef720f4f9f2af1fc44\n", + "[INFO|configuration_utils.py:581] 2021-07-19 08:22:39,530 >> Model config RobertaConfig {\n", + " \"architectures\": [\n", + " \"RobertaForMaskedLM\"\n", + " ],\n", + " \"attention_probs_dropout_prob\": 0.1,\n", + " \"bos_token_id\": 0,\n", + " \"eos_token_id\": 2,\n", + " \"finetuning_task\": \"ner\",\n", + " \"gradient_checkpointing\": false,\n", + " \"hidden_act\": \"gelu\",\n", + " \"hidden_dropout_prob\": 0.1,\n", + " \"hidden_size\": 768,\n", + " \"id2label\": {\n", + " \"0\": 0,\n", + " \"1\": 1,\n", + " \"2\": 2,\n", + " \"3\": 3,\n", + " \"4\": 4,\n", + " \"5\": 5,\n", + " \"6\": 6,\n", + " \"7\": 7,\n", + " \"8\": 8\n", + " },\n", + " \"initializer_range\": 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"[WARNING|modeling_utils.py:1502] 2021-07-19 08:23:41,907 >> Some weights of the model checkpoint at bertin-project/bertin-base-gaussian-exp-512seqlen were not used when initializing RobertaForTokenClassification: ['lm_head.dense.weight', 'lm_head.layer_norm.weight', 'lm_head.bias', 'lm_head.dense.bias', 'lm_head.layer_norm.bias']\n", + "- This IS expected if you are initializing RobertaForTokenClassification from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).\n", + "- This IS NOT expected if you are initializing RobertaForTokenClassification from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).\n", + "[WARNING|modeling_utils.py:1513] 2021-07-19 08:23:41,907 >> Some weights of RobertaForTokenClassification were not initialized from the model checkpoint at bertin-project/bertin-base-gaussian-exp-512seqlen and are newly initialized: ['classifier.weight', 'classifier.bias']\n", + "You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.\n", + "Running tokenizer on train dataset: 0% 0/9 [00:00> The following columns in the training set don't have a corresponding argument in `RobertaForTokenClassification.forward` and have been ignored: ner_tags, pos_tags, id, tokens.\n", + "[INFO|trainer.py:1162] 2021-07-19 08:23:55,930 >> ***** Running training *****\n", + "[INFO|trainer.py:1163] 2021-07-19 08:23:55,930 >> Num examples = 8324\n", + "[INFO|trainer.py:1164] 2021-07-19 08:23:55,930 >> Num Epochs = 5\n", + "[INFO|trainer.py:1165] 2021-07-19 08:23:55,931 >> Instantaneous batch size per device = 8\n", + "[INFO|trainer.py:1166] 2021-07-19 08:23:55,931 >> Total train batch size (w. parallel, distributed & accumulation) = 8\n", + "[INFO|trainer.py:1167] 2021-07-19 08:23:55,931 >> Gradient Accumulation steps = 1\n", + "[INFO|trainer.py:1168] 2021-07-19 08:23:55,931 >> Total optimization steps = 5205\n", + "[INFO|integrations.py:417] 2021-07-19 08:23:55,947 >> Automatic Weights & Biases logging enabled, to disable set os.environ[\"WANDB_DISABLED\"] = \"true\"\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Currently logged in as: \u001b[33mversae\u001b[0m (use `wandb login --relogin` to force relogin)\n", + "2021-07-19 08:23:57.438203: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Successfully opened dynamic library libcudart.so.11.0\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Tracking run with wandb version 0.11.0\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Syncing run \u001b[33m./outputs\u001b[0m\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: ⭐️ View project at \u001b[34m\u001b[4mhttps://wandb.ai/versae/bertin-eval\u001b[0m\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: 🚀 View run at \u001b[34m\u001b[4mhttps://wandb.ai/versae/bertin-eval/runs/ble6jobx\u001b[0m\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Run data is saved locally in /content/wandb/run-20210719_082356-ble6jobx\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Run `wandb offline` to turn off syncing.\n", + "\n", + " 10% 500/5205 [02:49<30:20, 2.58it/s]{'loss': 0.1317, 'learning_rate': 4.5196926032660905e-05, 'epoch': 0.48}\n", + " 10% 500/5205 [02:49<30:20, 2.58it/s][INFO|trainer.py:1917] 2021-07-19 08:26:48,133 >> Saving model checkpoint to ./outputs/checkpoint-500\n", + "[INFO|configuration_utils.py:379] 2021-07-19 08:26:48,135 >> Configuration saved in ./outputs/checkpoint-500/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 08:26:49,681 >> Model weights saved in ./outputs/checkpoint-500/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 08:26:49,682 >> tokenizer config file saved in ./outputs/checkpoint-500/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 08:26:49,683 >> Special tokens file saved in 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"[INFO|trainer.py:1917] 2021-07-19 08:32:35,943 >> Saving model checkpoint to ./outputs/checkpoint-1500\n", + "[INFO|configuration_utils.py:379] 2021-07-19 08:32:35,948 >> Configuration saved in ./outputs/checkpoint-1500/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 08:32:37,409 >> Model weights saved in ./outputs/checkpoint-1500/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 08:32:37,410 >> tokenizer config file saved in ./outputs/checkpoint-1500/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 08:32:37,410 >> Special tokens file saved in ./outputs/checkpoint-1500/special_tokens_map.json\n", + "{'loss': 0.0406, 'learning_rate': 3.078770413064361e-05, 'epoch': 1.92}\n", + " 38% 2000/5205 [11:31<20:19, 2.63it/s][INFO|trainer.py:1917] 2021-07-19 08:35:29,836 >> Saving model checkpoint to ./outputs/checkpoint-2000\n", + "[INFO|configuration_utils.py:379] 2021-07-19 08:35:29,837 >> Configuration saved in 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"[INFO|tokenization_utils_base.py:1998] 2021-07-19 08:38:24,712 >> tokenizer config file saved in ./outputs/checkpoint-2500/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 08:38:24,712 >> Special tokens file saved in ./outputs/checkpoint-2500/special_tokens_map.json\n", + "{'loss': 0.0217, 'learning_rate': 2.118155619596542e-05, 'epoch': 2.88}\n", + " 58% 3000/5205 [17:18<13:52, 2.65it/s][INFO|trainer.py:1917] 2021-07-19 08:41:17,051 >> Saving model checkpoint to ./outputs/checkpoint-3000\n", + "[INFO|configuration_utils.py:379] 2021-07-19 08:41:17,052 >> Configuration saved in ./outputs/checkpoint-3000/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 08:41:18,441 >> Model weights saved in ./outputs/checkpoint-3000/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 08:41:18,442 >> tokenizer config file saved in ./outputs/checkpoint-3000/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 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3.84}\n", + "[INFO|trainer.py:1917] 2021-07-19 08:47:02,389 >> Saving model checkpoint to ./outputs/checkpoint-4000\n", + "[INFO|configuration_utils.py:379] 2021-07-19 08:47:02,390 >> Configuration saved in ./outputs/checkpoint-4000/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 08:47:03,697 >> Model weights saved in ./outputs/checkpoint-4000/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 08:47:03,698 >> tokenizer config file saved in ./outputs/checkpoint-4000/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 08:47:03,699 >> Special tokens file saved in ./outputs/checkpoint-4000/special_tokens_map.json\n", + " 86% 4500/5205 [25:55<04:26, 2.64it/s]{'loss': 0.0102, 'learning_rate': 6.7723342939481265e-06, 'epoch': 4.32}\n", + "[INFO|trainer.py:1917] 2021-07-19 08:49:54,678 >> Saving model checkpoint to ./outputs/checkpoint-4500\n", + "[INFO|configuration_utils.py:379] 2021-07-19 08:49:54,680 >> Configuration saved in 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"[INFO|tokenization_utils_base.py:1998] 2021-07-19 08:52:49,284 >> tokenizer config file saved in ./outputs/checkpoint-5000/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 08:52:49,285 >> Special tokens file saved in ./outputs/checkpoint-5000/special_tokens_map.json\n", + "100% 5205/5205 [30:03<00:00, 3.34it/s][INFO|trainer.py:1358] 2021-07-19 08:54:01,973 >> \n", + "\n", + "Training completed. Do not forget to share your model on huggingface.co/models =)\n", + "\n", + "\n", + "{'train_runtime': 1806.0427, 'train_samples_per_second': 23.045, 'train_steps_per_second': 2.882, 'train_loss': 0.03659094202186372, 'epoch': 5.0}\n", + "100% 5205/5205 [30:03<00:00, 2.89it/s]\n", + "[INFO|trainer.py:1917] 2021-07-19 08:54:01,976 >> Saving model checkpoint to ./outputs\n", + "[INFO|configuration_utils.py:379] 2021-07-19 08:54:01,978 >> Configuration saved in ./outputs/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 08:54:03,477 >> Model weights saved in ./outputs/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 08:54:03,478 >> tokenizer config file saved in ./outputs/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 08:54:03,478 >> Special tokens file saved in ./outputs/special_tokens_map.json\n", + "***** train metrics *****\n", + " epoch = 5.0\n", + " train_loss = 0.0366\n", + " train_runtime = 0:30:06.04\n", + " train_samples = 8324\n", + " train_samples_per_second = 23.045\n", + " train_steps_per_second = 2.882\n", + "07/19/2021 08:54:03 - INFO - __main__ - *** Evaluate ***\n", + "[INFO|trainer.py:522] 2021-07-19 08:54:03,633 >> The following columns in the evaluation set don't have a corresponding argument in `RobertaForTokenClassification.forward` and have been ignored: ner_tags, pos_tags, id, tokens.\n", + "[INFO|trainer.py:2163] 2021-07-19 08:54:03,730 >> ***** Running Evaluation *****\n", + "[INFO|trainer.py:2165] 2021-07-19 08:54:03,730 >> Num examples = 1916\n", + "[INFO|trainer.py:2168] 2021-07-19 08:54:03,730 >> Batch size = 8\n", + "100% 240/240 [00:26<00:00, 9.08it/s]\n", + "***** eval metrics *****\n", + " epoch = 5.0\n", + " eval_accuracy = 0.9819\n", + " eval_f1 = 0.8764\n", + " eval_loss = 0.1065\n", + " eval_precision = 0.8699\n", + " eval_recall = 0.883\n", + " eval_runtime = 0:00:26.54\n", + " eval_samples = 1916\n", + " eval_samples_per_second = 72.184\n", + " eval_steps_per_second = 9.042\n", + "\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Waiting for W&B process to finish, PID 238\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Program ended successfully.\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: \n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Find user logs for this run at: /content/wandb/run-20210719_082356-ble6jobx/logs/debug.log\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Find internal logs for this run at: /content/wandb/run-20210719_082356-ble6jobx/logs/debug-internal.log\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Run summary:\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/loss 0.0087\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/learning_rate 0.0\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/epoch 5.0\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/global_step 5205\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: _runtime 1834\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: _timestamp 1626684870\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: _step 11\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_runtime 1806.0427\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_samples_per_second 23.045\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_steps_per_second 2.882\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/total_flos 1.087585926764544e+16\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_loss 0.03659\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/loss 0.10645\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/precision 0.86985\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/recall 0.88304\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/f1 0.8764\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/accuracy 0.98188\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/runtime 26.5433\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/samples_per_second 72.184\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/steps_per_second 9.042\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Run history:\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/loss 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"_n_gpu=1,\n", + "adafactor=False,\n", + "adam_beta1=0.9,\n", + "adam_beta2=0.999,\n", + "adam_epsilon=1e-08,\n", + "dataloader_drop_last=False,\n", + "dataloader_num_workers=0,\n", + "dataloader_pin_memory=True,\n", + "ddp_find_unused_parameters=None,\n", + "debug=[],\n", + "deepspeed=None,\n", + "disable_tqdm=False,\n", + "do_eval=True,\n", + "do_predict=False,\n", + "do_train=True,\n", + "eval_accumulation_steps=None,\n", + "eval_steps=500,\n", + "evaluation_strategy=IntervalStrategy.NO,\n", + "fp16=False,\n", + "fp16_backend=auto,\n", + "fp16_full_eval=False,\n", + "fp16_opt_level=O1,\n", + "gradient_accumulation_steps=1,\n", + "greater_is_better=None,\n", + "group_by_length=False,\n", + "ignore_data_skip=False,\n", + "label_names=None,\n", + "label_smoothing_factor=0.0,\n", + "learning_rate=5e-05,\n", + "length_column_name=length,\n", + "load_best_model_at_end=False,\n", + "local_rank=-1,\n", + "log_level=-1,\n", + "log_level_replica=-1,\n", + "log_on_each_node=True,\n", + "logging_dir=./outputs/runs/Jul19_08-54-48_eab5184de9ff,\n", + "logging_first_step=False,\n", + "logging_steps=500,\n", + "logging_strategy=IntervalStrategy.STEPS,\n", + "lr_scheduler_type=SchedulerType.LINEAR,\n", + "max_grad_norm=1.0,\n", + "max_steps=-1,\n", + "metric_for_best_model=None,\n", + "mp_parameters=,\n", + "no_cuda=False,\n", + "num_train_epochs=5.0,\n", + "output_dir=./outputs,\n", + "overwrite_output_dir=True,\n", + "past_index=-1,\n", + "per_device_eval_batch_size=8,\n", + "per_device_train_batch_size=8,\n", + "prediction_loss_only=False,\n", + "push_to_hub=False,\n", + "push_to_hub_model_id=outputs,\n", + "push_to_hub_organization=None,\n", + "push_to_hub_token=None,\n", + "remove_unused_columns=True,\n", + "report_to=['tensorboard', 'wandb'],\n", + "resume_from_checkpoint=None,\n", + "run_name=./outputs,\n", + "save_on_each_node=False,\n", + "save_steps=500,\n", + "save_strategy=IntervalStrategy.STEPS,\n", + "save_total_limit=None,\n", + "seed=42,\n", + "sharded_ddp=[],\n", + "skip_memory_metrics=True,\n", + "tpu_metrics_debug=False,\n", + "tpu_num_cores=None,\n", + "use_legacy_prediction_loop=False,\n", + "warmup_ratio=0.0,\n", + "warmup_steps=0,\n", + "weight_decay=0.0,\n", + ")\n", + "07/19/2021 08:54:50 - INFO - datasets.load - Found main folder for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py at /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002\n", + "07/19/2021 08:54:50 - INFO - datasets.load - Found specific version folder for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py at /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5\n", + "07/19/2021 08:54:50 - INFO - datasets.load - Found script file from https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py to /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5/conll2002.py\n", + "07/19/2021 08:54:50 - INFO - datasets.load - Found dataset infos file from https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/dataset_infos.json to /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5/dataset_infos.json\n", + "07/19/2021 08:54:50 - INFO - datasets.load - Found metadata file for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py at /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5/conll2002.json\n", + "07/19/2021 08:54:50 - INFO - datasets.load - Found main folder for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py at /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002\n", + "07/19/2021 08:54:50 - INFO - datasets.load - Found specific version folder for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py at /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5\n", + "07/19/2021 08:54:50 - INFO - datasets.load - Found script file from https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py to /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5/conll2002.py\n", + "07/19/2021 08:54:50 - INFO - datasets.load - Found dataset infos file from https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/dataset_infos.json to /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5/dataset_infos.json\n", + "07/19/2021 08:54:50 - INFO - datasets.load - Found metadata file for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py at /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5/conll2002.json\n", + "07/19/2021 08:54:50 - INFO - datasets.info - Loading Dataset Infos from /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5\n", + "07/19/2021 08:54:50 - INFO - datasets.builder - Overwrite dataset info from restored data version.\n", + "07/19/2021 08:54:50 - INFO - datasets.info - Loading Dataset info from /root/.cache/huggingface/datasets/conll2002/es/1.0.0/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5\n", + "07/19/2021 08:54:50 - WARNING - datasets.builder - Reusing dataset conll2002 (/root/.cache/huggingface/datasets/conll2002/es/1.0.0/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5)\n", + "07/19/2021 08:54:50 - INFO - datasets.info - Loading Dataset info from /root/.cache/huggingface/datasets/conll2002/es/1.0.0/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5\n", + "100% 3/3 [00:00<00:00, 27.51it/s]\n", + "[INFO|file_utils.py:1624] 2021-07-19 08:54:51,773 >> https://huggingface.co/bertin-project/bertin-base-random-exp-512seqlen/resolve/main/config.json not found in cache or force_download set to True, downloading to /root/.cache/huggingface/transformers/tmp3ne9bsxv\n", + "Downloading: 100% 618/618 [00:00<00:00, 466kB/s]\n", + "[INFO|file_utils.py:1628] 2021-07-19 08:54:52,493 >> storing https://huggingface.co/bertin-project/bertin-base-random-exp-512seqlen/resolve/main/config.json in cache at 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\"attention_probs_dropout_prob\": 0.1,\n", + " \"bos_token_id\": 0,\n", + " \"eos_token_id\": 2,\n", + " \"finetuning_task\": \"ner\",\n", + " \"gradient_checkpointing\": false,\n", + " \"hidden_act\": \"gelu\",\n", + " \"hidden_dropout_prob\": 0.1,\n", + " \"hidden_size\": 768,\n", + " \"id2label\": {\n", + " \"0\": 0,\n", + " \"1\": 1,\n", + " \"2\": 2,\n", + " \"3\": 3,\n", + " \"4\": 4,\n", + " \"5\": 5,\n", + " \"6\": 6,\n", + " \"7\": 7,\n", + " \"8\": 8\n", + " },\n", + " \"initializer_range\": 0.02,\n", + " \"intermediate_size\": 3072,\n", + " \"label2id\": {\n", + " \"0\": 0,\n", + " \"1\": 1,\n", + " \"2\": 2,\n", + " \"3\": 3,\n", + " \"4\": 4,\n", + " \"5\": 5,\n", + " \"6\": 6,\n", + " \"7\": 7,\n", + " \"8\": 8\n", + " },\n", + " \"layer_norm_eps\": 1e-05,\n", + " \"max_position_embeddings\": 514,\n", + " \"model_type\": \"roberta\",\n", + " \"num_attention_heads\": 12,\n", + " \"num_hidden_layers\": 12,\n", + " \"pad_token_id\": 1,\n", + " \"position_embedding_type\": \"absolute\",\n", + " \"transformers_version\": \"4.9.0.dev0\",\n", + " \"type_vocab_size\": 1,\n", + " \"use_cache\": true,\n", + " \"vocab_size\": 50265\n", + "}\n", + "\n", + "[INFO|file_utils.py:1624] 2021-07-19 08:54:53,479 >> https://huggingface.co/bertin-project/bertin-base-random-exp-512seqlen/resolve/main/tokenizer_config.json not found in cache or force_download set to True, downloading to /root/.cache/huggingface/transformers/tmp3534979z\n", + "Downloading: 100% 292/292 [00:00<00:00, 226kB/s]\n", + "[INFO|file_utils.py:1628] 2021-07-19 08:54:54,196 >> storing https://huggingface.co/bertin-project/bertin-base-random-exp-512seqlen/resolve/main/tokenizer_config.json in cache at /root/.cache/huggingface/transformers/a9d7a6740959c8c347993f62fbd5620bffa2d10c35c2e579a2ecec181299c9a1.9f7ac4246b492dfa7c21beb5233deec8aef46153ec25ac5258ac5e2ae82dfa89\n", + "[INFO|file_utils.py:1636] 2021-07-19 08:54:54,196 >> creating metadata file for 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/root/.cache/huggingface/transformers/39ddc268aab2655adb602f93d771480d4db157c1b6fae9a5ae9fc2112c645a69.a11ebb04664c067c8fe5ef8f8068b0f721263414a26058692f7b2e4ba2a1b342\n", + "[INFO|tokenization_utils_base.py:1722] 2021-07-19 08:55:03,457 >> loading file https://huggingface.co/bertin-project/bertin-base-random-exp-512seqlen/resolve/main/vocab.json from cache at /root/.cache/huggingface/transformers/c1ba808baa4a9c0f3062f1881d448087c30a1443644365bd41cf366491ab4063.a80f232f572026f92499b14999a8ed4e044e04cf3d01b9f2be298c98e78e8498\n", + "[INFO|tokenization_utils_base.py:1722] 2021-07-19 08:55:03,457 >> loading file https://huggingface.co/bertin-project/bertin-base-random-exp-512seqlen/resolve/main/merges.txt from cache at /root/.cache/huggingface/transformers/17ffd9604d64364336252e5a3859c3c55be07c457328ab5fc37e4aaf39913d28.a0dfc41f9d0f03a56ba7a5401d770f6e43071045a0bd79073380d408d17a0d92\n", + "[INFO|tokenization_utils_base.py:1722] 2021-07-19 08:55:03,458 >> loading file 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"[INFO|file_utils.py:1636] 2021-07-19 08:55:54,113 >> creating metadata file for /root/.cache/huggingface/transformers/6dd5d03f2c36b42a305cf20636d35935ad2d998d2ab0588b28eeed0fc164db43.5b6b77533b091cc9204533514d844abfe875ebba66e044b251306c4228bd3221\n", + "[INFO|modeling_utils.py:1271] 2021-07-19 08:55:54,113 >> loading weights file https://huggingface.co/bertin-project/bertin-base-random-exp-512seqlen/resolve/main/pytorch_model.bin from cache at /root/.cache/huggingface/transformers/6dd5d03f2c36b42a305cf20636d35935ad2d998d2ab0588b28eeed0fc164db43.5b6b77533b091cc9204533514d844abfe875ebba66e044b251306c4228bd3221\n", + "[WARNING|modeling_utils.py:1502] 2021-07-19 08:55:55,525 >> Some weights of the model checkpoint at bertin-project/bertin-base-random-exp-512seqlen were not used when initializing RobertaForTokenClassification: ['lm_head.dense.weight', 'lm_head.layer_norm.weight', 'lm_head.bias', 'lm_head.dense.bias', 'lm_head.layer_norm.bias']\n", + "- This IS expected if you are initializing RobertaForTokenClassification from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).\n", + "- This IS NOT expected if you are initializing RobertaForTokenClassification from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).\n", + "[WARNING|modeling_utils.py:1513] 2021-07-19 08:55:55,525 >> Some weights of RobertaForTokenClassification were not initialized from the model checkpoint at bertin-project/bertin-base-random-exp-512seqlen and are newly initialized: ['classifier.bias', 'classifier.weight']\n", + "You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.\n", + "Running tokenizer on train dataset: 0% 0/9 [00:00> The following columns in the training set don't have a corresponding argument in `RobertaForTokenClassification.forward` and have been ignored: id, pos_tags, ner_tags, tokens.\n", + "[INFO|trainer.py:1162] 2021-07-19 08:56:05,765 >> ***** Running training *****\n", + "[INFO|trainer.py:1163] 2021-07-19 08:56:05,765 >> Num examples = 8324\n", + "[INFO|trainer.py:1164] 2021-07-19 08:56:05,765 >> Num Epochs = 5\n", + "[INFO|trainer.py:1165] 2021-07-19 08:56:05,765 >> Instantaneous batch size per device = 8\n", + "[INFO|trainer.py:1166] 2021-07-19 08:56:05,765 >> Total train batch size (w. parallel, distributed & accumulation) = 8\n", + "[INFO|trainer.py:1167] 2021-07-19 08:56:05,765 >> Gradient Accumulation steps = 1\n", + "[INFO|trainer.py:1168] 2021-07-19 08:56:05,765 >> Total optimization steps = 5205\n", + "[INFO|integrations.py:417] 2021-07-19 08:56:05,779 >> Automatic Weights & Biases logging enabled, to disable set os.environ[\"WANDB_DISABLED\"] = \"true\"\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Currently logged in as: \u001b[33mversae\u001b[0m (use `wandb login --relogin` to force relogin)\n", + "2021-07-19 08:56:07.337961: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Successfully opened dynamic library libcudart.so.11.0\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Tracking run with wandb version 0.11.0\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Syncing run \u001b[33m./outputs\u001b[0m\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: ⭐️ View project at \u001b[34m\u001b[4mhttps://wandb.ai/versae/bertin-eval\u001b[0m\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: 🚀 View run at \u001b[34m\u001b[4mhttps://wandb.ai/versae/bertin-eval/runs/2o4ygylu\u001b[0m\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Run data is saved locally in /content/wandb/run-20210719_085605-2o4ygylu\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Run `wandb offline` to turn off syncing.\n", + "\n", + "{'loss': 0.1394, 'learning_rate': 4.5196926032660905e-05, 'epoch': 0.48}\n", + " 10% 500/5205 [02:49<30:06, 2.61it/s][INFO|trainer.py:1917] 2021-07-19 08:58:58,379 >> Saving model checkpoint to ./outputs/checkpoint-500\n", + "[INFO|configuration_utils.py:379] 2021-07-19 08:58:58,380 >> Configuration saved in ./outputs/checkpoint-500/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 08:58:59,853 >> Model weights saved in ./outputs/checkpoint-500/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 08:58:59,854 >> tokenizer config file saved in ./outputs/checkpoint-500/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 08:58:59,854 >> Special tokens file saved in ./outputs/checkpoint-500/special_tokens_map.json\n", + " 19% 1000/5205 [05:45<26:45, 2.62it/s]{'loss': 0.0732, 'learning_rate': 4.039385206532181e-05, 'epoch': 0.96}\n", + "[INFO|trainer.py:1917] 2021-07-19 09:01:54,171 >> Saving model checkpoint to ./outputs/checkpoint-1000\n", + "[INFO|configuration_utils.py:379] 2021-07-19 09:01:54,172 >> Configuration saved in ./outputs/checkpoint-1000/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 09:01:55,552 >> Model weights saved in ./outputs/checkpoint-1000/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 09:01:55,553 >> tokenizer config file saved in ./outputs/checkpoint-1000/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 09:01:55,553 >> Special tokens file saved in ./outputs/checkpoint-1000/special_tokens_map.json\n", + " 29% 1500/5205 [08:40<23:13, 2.66it/s]{'loss': 0.0498, 'learning_rate': 3.5590778097982716e-05, 'epoch': 1.44}\n", + "[INFO|trainer.py:1917] 2021-07-19 09:04:48,666 >> Saving model checkpoint to ./outputs/checkpoint-1500\n", + "[INFO|configuration_utils.py:379] 2021-07-19 09:04:48,667 >> Configuration saved in ./outputs/checkpoint-1500/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 09:04:49,995 >> Model weights saved in ./outputs/checkpoint-1500/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 09:04:49,996 >> tokenizer config file saved in ./outputs/checkpoint-1500/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 09:04:49,996 >> Special tokens file saved in ./outputs/checkpoint-1500/special_tokens_map.json\n", + " 38% 2000/5205 [11:33<20:30, 2.61it/s]{'loss': 0.0471, 'learning_rate': 3.078770413064361e-05, 'epoch': 1.92}\n", + "[INFO|trainer.py:1917] 2021-07-19 09:07:42,046 >> Saving model checkpoint to ./outputs/checkpoint-2000\n", + "[INFO|configuration_utils.py:379] 2021-07-19 09:07:42,047 >> Configuration saved in ./outputs/checkpoint-2000/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 09:07:43,645 >> Model weights saved in ./outputs/checkpoint-2000/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 09:07:43,646 >> tokenizer config file saved in ./outputs/checkpoint-2000/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 09:07:43,646 >> Special tokens file saved in ./outputs/checkpoint-2000/special_tokens_map.json\n", + " 48% 2500/5205 [14:27<17:19, 2.60it/s][INFO|trainer.py:1917] 2021-07-19 09:10:35,810 >> Saving model checkpoint to ./outputs/checkpoint-2500\n", + "{'loss': 0.0326, 'learning_rate': 2.5984630163304517e-05, 'epoch': 2.4}\n", + "[INFO|configuration_utils.py:379] 2021-07-19 09:10:35,814 >> Configuration saved in ./outputs/checkpoint-2500/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 09:10:37,154 >> Model weights saved in ./outputs/checkpoint-2500/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 09:10:37,155 >> tokenizer config file saved in ./outputs/checkpoint-2500/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 09:10:37,155 >> Special tokens file saved in ./outputs/checkpoint-2500/special_tokens_map.json\n", + "{'loss': 0.0286, 'learning_rate': 2.118155619596542e-05, 'epoch': 2.88}\n", + " 58% 3000/5205 [17:20<13:57, 2.63it/s][INFO|trainer.py:1917] 2021-07-19 09:13:29,401 >> Saving model checkpoint to ./outputs/checkpoint-3000\n", + "[INFO|configuration_utils.py:379] 2021-07-19 09:13:29,403 >> Configuration saved in ./outputs/checkpoint-3000/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 09:13:30,776 >> Model weights saved in ./outputs/checkpoint-3000/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 09:13:30,777 >> tokenizer config file saved in ./outputs/checkpoint-3000/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 09:13:30,777 >> Special tokens file saved in ./outputs/checkpoint-3000/special_tokens_map.json\n", + "{'loss': 0.0213, 'learning_rate': 1.6378482228626322e-05, 'epoch': 3.36}\n", + " 67% 3500/5205 [20:14<11:08, 2.55it/s][INFO|trainer.py:1917] 2021-07-19 09:16:22,813 >> Saving model checkpoint to ./outputs/checkpoint-3500\n", + "[INFO|configuration_utils.py:379] 2021-07-19 09:16:22,815 >> Configuration saved in ./outputs/checkpoint-3500/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 09:16:24,401 >> Model weights saved in ./outputs/checkpoint-3500/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 09:16:24,402 >> tokenizer config file saved in ./outputs/checkpoint-3500/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 09:16:24,402 >> Special tokens file saved in ./outputs/checkpoint-3500/special_tokens_map.json\n", + "{'loss': 0.0179, 'learning_rate': 1.1575408261287224e-05, 'epoch': 3.84}\n", + " 77% 4000/5205 [23:07<07:34, 2.65it/s][INFO|trainer.py:1917] 2021-07-19 09:19:16,222 >> Saving model checkpoint to ./outputs/checkpoint-4000\n", + "[INFO|configuration_utils.py:379] 2021-07-19 09:19:16,223 >> Configuration saved in ./outputs/checkpoint-4000/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 09:19:17,545 >> Model weights saved in ./outputs/checkpoint-4000/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 09:19:17,546 >> tokenizer config file saved in ./outputs/checkpoint-4000/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 09:19:17,546 >> Special tokens file saved in ./outputs/checkpoint-4000/special_tokens_map.json\n", + "{'loss': 0.0148, 'learning_rate': 6.7723342939481265e-06, 'epoch': 4.32}\n", + " 86% 4500/5205 [26:00<04:28, 2.63it/s][INFO|trainer.py:1917] 2021-07-19 09:22:09,568 >> Saving model checkpoint to ./outputs/checkpoint-4500\n", + "[INFO|configuration_utils.py:379] 2021-07-19 09:22:09,569 >> Configuration saved in ./outputs/checkpoint-4500/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 09:22:10,963 >> Model weights saved in ./outputs/checkpoint-4500/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 09:22:10,964 >> tokenizer config file saved in ./outputs/checkpoint-4500/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 09:22:10,964 >> Special tokens file saved in ./outputs/checkpoint-4500/special_tokens_map.json\n", + " 96% 5000/5205 [28:54<01:17, 2.65it/s]{'loss': 0.0124, 'learning_rate': 1.96926032660903e-06, 'epoch': 4.8}\n", + "[INFO|trainer.py:1917] 2021-07-19 09:25:02,826 >> Saving model checkpoint to ./outputs/checkpoint-5000\n", + "[INFO|configuration_utils.py:379] 2021-07-19 09:25:02,833 >> Configuration saved in ./outputs/checkpoint-5000/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 09:25:04,501 >> Model weights saved in ./outputs/checkpoint-5000/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 09:25:04,501 >> tokenizer config file saved in ./outputs/checkpoint-5000/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 09:25:04,502 >> Special tokens file saved in ./outputs/checkpoint-5000/special_tokens_map.json\n", + "100% 5205/5205 [30:08<00:00, 3.32it/s][INFO|trainer.py:1358] 2021-07-19 09:26:17,362 >> \n", + "\n", + "Training completed. Do not forget to share your model on huggingface.co/models =)\n", + "\n", + "\n", + "100% 5205/5205 [30:08<00:00, 3.32it/s]{'train_runtime': 1811.5969, 'train_samples_per_second': 22.974, 'train_steps_per_second': 2.873, 'train_loss': 0.04241216052162544, 'epoch': 5.0}\n", + "100% 5205/5205 [30:08<00:00, 2.88it/s]\n", + "[INFO|trainer.py:1917] 2021-07-19 09:26:17,386 >> Saving model checkpoint to ./outputs\n", + "[INFO|configuration_utils.py:379] 2021-07-19 09:26:17,388 >> Configuration saved in ./outputs/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 09:26:18,952 >> Model weights saved in ./outputs/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 09:26:18,953 >> tokenizer config file saved in ./outputs/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 09:26:18,953 >> Special tokens file saved in ./outputs/special_tokens_map.json\n", + "***** train metrics *****\n", + " epoch = 5.0\n", + " train_loss = 0.0424\n", + " train_runtime = 0:30:11.59\n", + " train_samples = 8324\n", + " train_samples_per_second = 22.974\n", + " train_steps_per_second = 2.873\n", + "07/19/2021 09:26:19 - INFO - __main__ - *** Evaluate ***\n", + "[INFO|trainer.py:522] 2021-07-19 09:26:19,106 >> The following columns in the evaluation set don't have a corresponding argument in `RobertaForTokenClassification.forward` and have been ignored: id, pos_tags, ner_tags, tokens.\n", + "[INFO|trainer.py:2163] 2021-07-19 09:26:19,211 >> ***** Running Evaluation *****\n", + "[INFO|trainer.py:2165] 2021-07-19 09:26:19,211 >> Num examples = 1916\n", + "[INFO|trainer.py:2168] 2021-07-19 09:26:19,211 >> Batch size = 8\n", + "100% 240/240 [00:24<00:00, 10.65it/s]***** eval metrics *****\n", + " epoch = 5.0\n", + " eval_accuracy = 0.9803\n", + "100% 240/240 [00:26<00:00, 9.17it/s]\n", + " eval_f1 = 0.8616\n", + " eval_loss = 0.1099\n", + " eval_precision = 0.8557\n", + " eval_recall = 0.8676\n", + " eval_runtime = 0:00:26.28\n", + " eval_samples = 1916\n", + " eval_samples_per_second = 72.894\n", + " eval_steps_per_second = 9.131\n", + "\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Waiting for W&B process to finish, PID 313\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Program ended successfully.\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: \n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Find user logs for this run at: /content/wandb/run-20210719_085605-2o4ygylu/logs/debug.log\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Find internal logs for this run at: /content/wandb/run-20210719_085605-2o4ygylu/logs/debug-internal.log\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Run summary:\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/loss 0.0124\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/learning_rate 0.0\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/epoch 5.0\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/global_step 5205\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: _runtime 1839\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: _timestamp 1626686805\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: _step 11\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_runtime 1811.5969\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_samples_per_second 22.974\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_steps_per_second 2.873\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/total_flos 1.087585926764544e+16\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_loss 0.04241\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/loss 0.10993\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/precision 0.85565\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/recall 0.86765\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/f1 0.86161\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/accuracy 0.98033\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/runtime 26.2847\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/samples_per_second 72.894\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/steps_per_second 9.131\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Run history:\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/loss █▄▃▃▂▂▁▁▁▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/learning_rate █▇▆▆▅▄▃▃▂▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/epoch ▁▂▂▃▄▅▅▆▇███\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/global_step ▁▂▂▃▄▅▅▆▇███\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: _runtime ▁▂▂▃▄▅▅▆▇███\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: _timestamp ▁▂▂▃▄▅▅▆▇███\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: _step ▁▂▂▃▄▄▅▅▆▇▇█\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_runtime ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_samples_per_second ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_steps_per_second ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/total_flos ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_loss ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/loss ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/precision ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/recall ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/f1 ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/accuracy ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/runtime ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/samples_per_second ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/steps_per_second ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: \n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Synced 5 W&B file(s), 0 media file(s), 0 artifact file(s) and 1 other file(s)\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: \n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Synced \u001b[33m./outputs\u001b[0m: \u001b[34mhttps://wandb.ai/versae/bertin-eval/runs/2o4ygylu\u001b[0m\n", + "2021-07-19 09:26:58.817549: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Successfully opened dynamic library libcudart.so.11.0\n", + "07/19/2021 09:27:01 - WARNING - __main__ - Process rank: -1, device: cuda:0, n_gpu: 1distributed training: False, 16-bits training: False\n", + "07/19/2021 09:27:01 - INFO - __main__ - Training/evaluation parameters TrainingArguments(\n", + "_n_gpu=1,\n", + "adafactor=False,\n", + "adam_beta1=0.9,\n", + "adam_beta2=0.999,\n", + "adam_epsilon=1e-08,\n", + "dataloader_drop_last=False,\n", + "dataloader_num_workers=0,\n", + "dataloader_pin_memory=True,\n", + "ddp_find_unused_parameters=None,\n", + "debug=[],\n", + "deepspeed=None,\n", + "disable_tqdm=False,\n", + "do_eval=True,\n", + "do_predict=False,\n", + "do_train=True,\n", + "eval_accumulation_steps=None,\n", + "eval_steps=500,\n", + "evaluation_strategy=IntervalStrategy.NO,\n", + "fp16=False,\n", + "fp16_backend=auto,\n", + "fp16_full_eval=False,\n", + "fp16_opt_level=O1,\n", + "gradient_accumulation_steps=1,\n", + "greater_is_better=None,\n", + "group_by_length=False,\n", + "ignore_data_skip=False,\n", + "label_names=None,\n", + "label_smoothing_factor=0.0,\n", + "learning_rate=5e-05,\n", + "length_column_name=length,\n", + "load_best_model_at_end=False,\n", + "local_rank=-1,\n", + "log_level=-1,\n", + "log_level_replica=-1,\n", + "log_on_each_node=True,\n", + "logging_dir=./outputs/runs/Jul19_09-27-01_eab5184de9ff,\n", + "logging_first_step=False,\n", + "logging_steps=500,\n", + "logging_strategy=IntervalStrategy.STEPS,\n", + "lr_scheduler_type=SchedulerType.LINEAR,\n", + "max_grad_norm=1.0,\n", + "max_steps=-1,\n", + "metric_for_best_model=None,\n", + "mp_parameters=,\n", + "no_cuda=False,\n", + "num_train_epochs=5.0,\n", + "output_dir=./outputs,\n", + "overwrite_output_dir=True,\n", + "past_index=-1,\n", + "per_device_eval_batch_size=8,\n", + "per_device_train_batch_size=8,\n", + "prediction_loss_only=False,\n", + "push_to_hub=False,\n", + "push_to_hub_model_id=outputs,\n", + "push_to_hub_organization=None,\n", + "push_to_hub_token=None,\n", + "remove_unused_columns=True,\n", + "report_to=['tensorboard', 'wandb'],\n", + "resume_from_checkpoint=None,\n", + "run_name=./outputs,\n", + "save_on_each_node=False,\n", + "save_steps=500,\n", + "save_strategy=IntervalStrategy.STEPS,\n", + "save_total_limit=None,\n", + "seed=42,\n", + "sharded_ddp=[],\n", + "skip_memory_metrics=True,\n", + "tpu_metrics_debug=False,\n", + "tpu_num_cores=None,\n", + "use_legacy_prediction_loop=False,\n", + "warmup_ratio=0.0,\n", + "warmup_steps=0,\n", + "weight_decay=0.0,\n", + ")\n", + "07/19/2021 09:27:03 - INFO - datasets.load - Found main folder for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py at /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002\n", + "07/19/2021 09:27:03 - INFO - datasets.load - Found specific version folder for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py at /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5\n", + "07/19/2021 09:27:03 - INFO - datasets.load - Found script file from https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py to /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5/conll2002.py\n", + "07/19/2021 09:27:03 - INFO - datasets.load - Found dataset infos file from https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/dataset_infos.json to /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5/dataset_infos.json\n", + "07/19/2021 09:27:03 - INFO - datasets.load - Found metadata file for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py at /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5/conll2002.json\n", + "07/19/2021 09:27:04 - INFO - datasets.load - Found main folder for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py at /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002\n", + "07/19/2021 09:27:04 - INFO - datasets.load - Found specific version folder for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py at /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5\n", + "07/19/2021 09:27:04 - INFO - datasets.load - Found script file from https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py to /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5/conll2002.py\n", + "07/19/2021 09:27:04 - INFO - datasets.load - Found dataset infos file from https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/dataset_infos.json to /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5/dataset_infos.json\n", + "07/19/2021 09:27:04 - INFO - datasets.load - Found metadata file for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py at /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5/conll2002.json\n", + "07/19/2021 09:27:04 - INFO - datasets.info - Loading Dataset Infos from /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5\n", + "07/19/2021 09:27:04 - INFO - datasets.builder - Overwrite dataset info from restored data version.\n", + "07/19/2021 09:27:04 - INFO - datasets.info - Loading Dataset info from /root/.cache/huggingface/datasets/conll2002/es/1.0.0/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5\n", + "07/19/2021 09:27:04 - WARNING - datasets.builder - Reusing dataset conll2002 (/root/.cache/huggingface/datasets/conll2002/es/1.0.0/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5)\n", + "07/19/2021 09:27:04 - INFO - datasets.info - Loading Dataset info from /root/.cache/huggingface/datasets/conll2002/es/1.0.0/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5\n", + "100% 3/3 [00:00<00:00, 26.10it/s]\n", + "[INFO|file_utils.py:1624] 2021-07-19 09:27:05,503 >> https://huggingface.co/bertin-project/bertin-base-gaussian/resolve/main/config.json not found in cache or force_download set to True, downloading to /root/.cache/huggingface/transformers/tmpj3btr4rs\n", + "Downloading: 100% 618/618 [00:00<00:00, 445kB/s]\n", + "[INFO|file_utils.py:1628] 2021-07-19 09:27:06,231 >> storing https://huggingface.co/bertin-project/bertin-base-gaussian/resolve/main/config.json in cache at /root/.cache/huggingface/transformers/cbd56d68ce5dcd2626aba4c4b188db63f2ba2c49a604b36e7cdc6e52578ee306.08210214ecaf5cd53c702826a604e564d8af557125033eef720f4f9f2af1fc44\n", + "[INFO|file_utils.py:1636] 2021-07-19 09:27:06,231 >> creating metadata file for /root/.cache/huggingface/transformers/cbd56d68ce5dcd2626aba4c4b188db63f2ba2c49a604b36e7cdc6e52578ee306.08210214ecaf5cd53c702826a604e564d8af557125033eef720f4f9f2af1fc44\n", + "[INFO|configuration_utils.py:545] 2021-07-19 09:27:06,232 >> loading configuration file https://huggingface.co/bertin-project/bertin-base-gaussian/resolve/main/config.json from cache at /root/.cache/huggingface/transformers/cbd56d68ce5dcd2626aba4c4b188db63f2ba2c49a604b36e7cdc6e52578ee306.08210214ecaf5cd53c702826a604e564d8af557125033eef720f4f9f2af1fc44\n", + "[INFO|configuration_utils.py:581] 2021-07-19 09:27:06,233 >> Model config RobertaConfig {\n", + " \"architectures\": [\n", + " \"RobertaForMaskedLM\"\n", + " ],\n", + " \"attention_probs_dropout_prob\": 0.1,\n", + " \"bos_token_id\": 0,\n", + " \"eos_token_id\": 2,\n", + " \"finetuning_task\": \"ner\",\n", + " \"gradient_checkpointing\": false,\n", + " \"hidden_act\": \"gelu\",\n", + " \"hidden_dropout_prob\": 0.1,\n", + " \"hidden_size\": 768,\n", + " \"id2label\": {\n", + " \"0\": 0,\n", + " \"1\": 1,\n", + " \"2\": 2,\n", + " \"3\": 3,\n", + " \"4\": 4,\n", + " \"5\": 5,\n", + " \"6\": 6,\n", + " \"7\": 7,\n", + " \"8\": 8\n", + " },\n", + " \"initializer_range\": 0.02,\n", + " \"intermediate_size\": 3072,\n", + " \"label2id\": {\n", + " \"0\": 0,\n", + " \"1\": 1,\n", + " \"2\": 2,\n", + " \"3\": 3,\n", + " \"4\": 4,\n", + " \"5\": 5,\n", + " \"6\": 6,\n", + " \"7\": 7,\n", + " \"8\": 8\n", + " },\n", + " \"layer_norm_eps\": 1e-05,\n", + " \"max_position_embeddings\": 514,\n", + " \"model_type\": \"roberta\",\n", + " \"num_attention_heads\": 12,\n", + " \"num_hidden_layers\": 12,\n", + " \"pad_token_id\": 1,\n", + " \"position_embedding_type\": \"absolute\",\n", + " \"transformers_version\": \"4.9.0.dev0\",\n", + " \"type_vocab_size\": 1,\n", + " \"use_cache\": true,\n", + " \"vocab_size\": 50265\n", + "}\n", + "\n", + "[INFO|file_utils.py:1624] 2021-07-19 09:27:06,949 >> https://huggingface.co/bertin-project/bertin-base-gaussian/resolve/main/tokenizer_config.json not found in cache or force_download set to True, downloading to /root/.cache/huggingface/transformers/tmps__yinbf\n", + "Downloading: 100% 292/292 [00:00<00:00, 219kB/s]\n", + "[INFO|file_utils.py:1628] 2021-07-19 09:27:07,667 >> storing https://huggingface.co/bertin-project/bertin-base-gaussian/resolve/main/tokenizer_config.json in cache at /root/.cache/huggingface/transformers/7a419a17bf4372869932365630632f434d402e93dd7e609e73607cf71ec1bdf7.9f7ac4246b492dfa7c21beb5233deec8aef46153ec25ac5258ac5e2ae82dfa89\n", + "[INFO|file_utils.py:1636] 2021-07-19 09:27:07,667 >> creating metadata file for 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creating metadata file for /root/.cache/huggingface/transformers/d61c66f6163d7933bcffb5de3a666094c2c7c8d54145ec0cea640f72204427e0.50b5552cf09535e0a4b85cc39c83be233674d4cab0836dd8fedc97aa778c802c\n", + "[INFO|modeling_utils.py:1271] 2021-07-19 09:28:07,299 >> loading weights file https://huggingface.co/bertin-project/bertin-base-gaussian/resolve/main/pytorch_model.bin from cache at /root/.cache/huggingface/transformers/d61c66f6163d7933bcffb5de3a666094c2c7c8d54145ec0cea640f72204427e0.50b5552cf09535e0a4b85cc39c83be233674d4cab0836dd8fedc97aa778c802c\n", + "[WARNING|modeling_utils.py:1502] 2021-07-19 09:28:08,815 >> Some weights of the model checkpoint at bertin-project/bertin-base-gaussian were not used when initializing RobertaForTokenClassification: ['lm_head.bias', 'lm_head.layer_norm.weight', 'lm_head.layer_norm.bias', 'lm_head.dense.bias', 'lm_head.dense.weight']\n", + "- This IS expected if you are initializing RobertaForTokenClassification from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).\n", + "- This IS NOT expected if you are initializing RobertaForTokenClassification from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).\n", + "[WARNING|modeling_utils.py:1513] 2021-07-19 09:28:08,815 >> Some weights of RobertaForTokenClassification were not initialized from the model checkpoint at bertin-project/bertin-base-gaussian and are newly initialized: ['classifier.bias', 'classifier.weight']\n", + "You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.\n", + "Running tokenizer on train dataset: 0% 0/9 [00:00> The following columns in the training set don't have a corresponding argument in `RobertaForTokenClassification.forward` and have been ignored: pos_tags, ner_tags, id, tokens.\n", + "[INFO|trainer.py:1162] 2021-07-19 09:28:19,409 >> ***** Running training *****\n", + "[INFO|trainer.py:1163] 2021-07-19 09:28:19,409 >> Num examples = 8324\n", + "[INFO|trainer.py:1164] 2021-07-19 09:28:19,409 >> Num Epochs = 5\n", + "[INFO|trainer.py:1165] 2021-07-19 09:28:19,409 >> Instantaneous batch size per device = 8\n", + "[INFO|trainer.py:1166] 2021-07-19 09:28:19,409 >> Total train batch size (w. parallel, distributed & accumulation) = 8\n", + "[INFO|trainer.py:1167] 2021-07-19 09:28:19,409 >> Gradient Accumulation steps = 1\n", + "[INFO|trainer.py:1168] 2021-07-19 09:28:19,409 >> Total optimization steps = 5205\n", + "[INFO|integrations.py:417] 2021-07-19 09:28:19,425 >> Automatic Weights & Biases logging enabled, to disable set os.environ[\"WANDB_DISABLED\"] = \"true\"\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Currently logged in as: \u001b[33mversae\u001b[0m (use `wandb login --relogin` to force relogin)\n", + "2021-07-19 09:28:21.087997: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Successfully opened dynamic library libcudart.so.11.0\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Tracking run with wandb version 0.11.0\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Syncing run \u001b[33m./outputs\u001b[0m\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: ⭐️ View project at \u001b[34m\u001b[4mhttps://wandb.ai/versae/bertin-eval\u001b[0m\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: 🚀 View run at \u001b[34m\u001b[4mhttps://wandb.ai/versae/bertin-eval/runs/1zmf4tfr\u001b[0m\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Run data is saved locally in /content/wandb/run-20210719_092819-1zmf4tfr\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Run `wandb offline` to turn off syncing.\n", + "\n", + "{'loss': 0.1263, 'learning_rate': 4.5196926032660905e-05, 'epoch': 0.48}\n", + " 10% 500/5205 [02:49<30:18, 2.59it/s][INFO|trainer.py:1917] 2021-07-19 09:31:12,177 >> Saving model checkpoint to ./outputs/checkpoint-500\n", + "[INFO|configuration_utils.py:379] 2021-07-19 09:31:12,179 >> Configuration saved in ./outputs/checkpoint-500/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 09:31:13,724 >> Model weights saved in ./outputs/checkpoint-500/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 09:31:13,725 >> tokenizer config file saved in ./outputs/checkpoint-500/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 09:31:13,725 >> Special tokens file saved in ./outputs/checkpoint-500/special_tokens_map.json\n", + "{'loss': 0.0641, 'learning_rate': 4.039385206532181e-05, 'epoch': 0.96}\n", + " 19% 1000/5205 [05:45<26:44, 2.62it/s][INFO|trainer.py:1917] 2021-07-19 09:34:07,849 >> Saving model checkpoint to ./outputs/checkpoint-1000\n", + "[INFO|configuration_utils.py:379] 2021-07-19 09:34:07,850 >> Configuration saved in ./outputs/checkpoint-1000/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 09:34:09,238 >> Model weights saved in ./outputs/checkpoint-1000/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 09:34:09,238 >> tokenizer config file saved in ./outputs/checkpoint-1000/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 09:34:09,239 >> Special tokens file saved in ./outputs/checkpoint-1000/special_tokens_map.json\n", + "{'loss': 0.041, 'learning_rate': 3.5590778097982716e-05, 'epoch': 1.44}\n", + " 29% 1500/5205 [08:40<23:26, 2.63it/s][INFO|trainer.py:1917] 2021-07-19 09:37:02,981 >> Saving model checkpoint to ./outputs/checkpoint-1500\n", + "[INFO|configuration_utils.py:379] 2021-07-19 09:37:02,983 >> Configuration saved in ./outputs/checkpoint-1500/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 09:37:04,542 >> Model weights saved in ./outputs/checkpoint-1500/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 09:37:04,543 >> tokenizer config file saved in ./outputs/checkpoint-1500/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 09:37:04,544 >> Special tokens file saved in ./outputs/checkpoint-1500/special_tokens_map.json\n", + "{'loss': 0.0394, 'learning_rate': 3.078770413064361e-05, 'epoch': 1.92}\n", + " 38% 2000/5205 [11:35<20:16, 2.63it/s][INFO|trainer.py:1917] 2021-07-19 09:39:58,083 >> Saving model checkpoint to ./outputs/checkpoint-2000\n", + "[INFO|configuration_utils.py:379] 2021-07-19 09:39:58,085 >> Configuration saved in ./outputs/checkpoint-2000/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 09:39:59,421 >> Model weights saved in ./outputs/checkpoint-2000/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 09:39:59,422 >> tokenizer config file saved in ./outputs/checkpoint-2000/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 09:39:59,422 >> Special tokens file saved in ./outputs/checkpoint-2000/special_tokens_map.json\n", + " 48% 2500/5205 [14:30<17:11, 2.62it/s]{'loss': 0.0261, 'learning_rate': 2.5984630163304517e-05, 'epoch': 2.4}\n", + " 48% 2500/5205 [14:30<17:11, 2.62it/s][INFO|trainer.py:1917] 2021-07-19 09:42:52,967 >> Saving model checkpoint to ./outputs/checkpoint-2500\n", + "[INFO|configuration_utils.py:379] 2021-07-19 09:42:52,968 >> Configuration saved in ./outputs/checkpoint-2500/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 09:42:54,418 >> Model weights saved in ./outputs/checkpoint-2500/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 09:42:54,419 >> tokenizer config file saved in ./outputs/checkpoint-2500/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 09:42:54,420 >> Special tokens file saved in ./outputs/checkpoint-2500/special_tokens_map.json\n", + " 58% 3000/5205 [17:25<14:09, 2.60it/s]{'loss': 0.0221, 'learning_rate': 2.118155619596542e-05, 'epoch': 2.88}\n", + " 58% 3000/5205 [17:25<14:09, 2.60it/s][INFO|trainer.py:1917] 2021-07-19 09:45:48,000 >> Saving model checkpoint to ./outputs/checkpoint-3000\n", + "[INFO|configuration_utils.py:379] 2021-07-19 09:45:48,001 >> Configuration saved in ./outputs/checkpoint-3000/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 09:45:49,621 >> Model weights saved in ./outputs/checkpoint-3000/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 09:45:49,622 >> tokenizer config file saved in ./outputs/checkpoint-3000/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 09:45:49,622 >> Special tokens file saved in ./outputs/checkpoint-3000/special_tokens_map.json\n", + " 67% 3500/5205 [20:20<10:53, 2.61it/s]{'loss': 0.0165, 'learning_rate': 1.6378482228626322e-05, 'epoch': 3.36}\n", + "[INFO|trainer.py:1917] 2021-07-19 09:48:42,983 >> Saving model checkpoint to ./outputs/checkpoint-3500\n", + "[INFO|configuration_utils.py:379] 2021-07-19 09:48:42,985 >> Configuration saved in ./outputs/checkpoint-3500/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 09:48:44,303 >> Model weights saved in ./outputs/checkpoint-3500/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 09:48:44,304 >> tokenizer config file saved in ./outputs/checkpoint-3500/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 09:48:44,305 >> Special tokens file saved in ./outputs/checkpoint-3500/special_tokens_map.json\n", + "{'loss': 0.0125, 'learning_rate': 1.1575408261287224e-05, 'epoch': 3.84}\n", + " 77% 4000/5205 [23:15<07:45, 2.59it/s][INFO|trainer.py:1917] 2021-07-19 09:51:37,552 >> Saving model checkpoint to ./outputs/checkpoint-4000\n", + "[INFO|configuration_utils.py:379] 2021-07-19 09:51:37,553 >> Configuration saved in ./outputs/checkpoint-4000/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 09:51:39,078 >> Model weights saved in ./outputs/checkpoint-4000/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 09:51:39,121 >> tokenizer config file saved in 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completed. Do not forget to share your model on huggingface.co/models =)\n", + "\n", + "\n", + " {'train_runtime': 1822.5055, 'train_samples_per_second': 22.837, 'train_steps_per_second': 2.856, 'train_loss': 0.035404586448449564, 'epoch': 5.0}\n", + "100% 5205/5205 [30:19<00:00, 2.86it/s]\n", + "[INFO|trainer.py:1917] 2021-07-19 09:58:41,922 >> Saving model checkpoint to ./outputs\n", + "[INFO|configuration_utils.py:379] 2021-07-19 09:58:41,924 >> Configuration saved in ./outputs/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 09:58:43,256 >> Model weights saved in ./outputs/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 09:58:43,257 >> tokenizer config file saved in ./outputs/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 09:58:43,257 >> Special tokens file saved in ./outputs/special_tokens_map.json\n", + "***** train metrics *****\n", + " epoch = 5.0\n", + " train_loss = 0.0354\n", + " train_runtime = 0:30:22.50\n", + " train_samples = 8324\n", + " train_samples_per_second = 22.837\n", + " train_steps_per_second = 2.856\n", + "[INFO|trainer.py:522] 2021-07-19 09:58:43,390 >> The following columns in the evaluation set don't have a corresponding argument in `RobertaForTokenClassification.forward` and have been ignored: pos_tags, ner_tags, id, tokens.\n", + "07/19/2021 09:58:43 - INFO - __main__ - *** Evaluate ***\n", + "[INFO|trainer.py:2163] 2021-07-19 09:58:43,420 >> ***** Running Evaluation *****\n", + "[INFO|trainer.py:2165] 2021-07-19 09:58:43,420 >> Num examples = 1916\n", + "[INFO|trainer.py:2168] 2021-07-19 09:58:43,420 >> Batch size = 8\n", + "100% 240/240 [00:25<00:00, 9.26it/s]\n", + "***** eval metrics *****\n", + " epoch = 5.0\n", + " eval_accuracy = 0.9816\n", + " eval_f1 = 0.8792\n", + " eval_loss = 0.1098\n", + " eval_precision = 0.8731\n", + " eval_recall = 0.8853\n", + " eval_runtime = 0:00:26.04\n", + " eval_samples = 1916\n", + " eval_samples_per_second = 73.569\n", + " eval_steps_per_second = 9.215\n", + "\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Waiting for W&B process to finish, PID 392\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Program ended successfully.\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: \n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Find user logs for this run at: /content/wandb/run-20210719_092819-1zmf4tfr/logs/debug.log\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Find internal logs for this run at: /content/wandb/run-20210719_092819-1zmf4tfr/logs/debug-internal.log\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Run summary:\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/loss 0.0086\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/learning_rate 0.0\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/epoch 5.0\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/global_step 5205\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: _runtime 1850\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: _timestamp 1626688749\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: _step 11\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_runtime 1822.5055\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_samples_per_second 22.837\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_steps_per_second 2.856\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/total_flos 1.087585926764544e+16\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_loss 0.0354\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/loss 0.10978\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/precision 0.8731\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/recall 0.88534\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/f1 0.87918\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/accuracy 0.9816\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/runtime 26.0437\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/samples_per_second 73.569\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/steps_per_second 9.215\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Run history:\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/loss 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"\u001b[34m\u001b[1mwandb\u001b[0m: eval/accuracy ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/runtime ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/samples_per_second ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/steps_per_second ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: \n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Synced 5 W&B file(s), 0 media file(s), 0 artifact file(s) and 1 other file(s)\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: \n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Synced \u001b[33m./outputs\u001b[0m: \u001b[34mhttps://wandb.ai/versae/bertin-eval/runs/1zmf4tfr\u001b[0m\n", + "2021-07-19 09:59:22.866480: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Successfully opened dynamic library libcudart.so.11.0\n", + "07/19/2021 09:59:25 - WARNING - __main__ - Process rank: -1, device: cuda:0, n_gpu: 1distributed training: False, 16-bits training: False\n", + "07/19/2021 09:59:25 - INFO - __main__ - Training/evaluation parameters TrainingArguments(\n", + "_n_gpu=1,\n", + "adafactor=False,\n", + "adam_beta1=0.9,\n", + "adam_beta2=0.999,\n", + "adam_epsilon=1e-08,\n", + "dataloader_drop_last=False,\n", + "dataloader_num_workers=0,\n", + "dataloader_pin_memory=True,\n", + "ddp_find_unused_parameters=None,\n", + "debug=[],\n", + "deepspeed=None,\n", + "disable_tqdm=False,\n", + "do_eval=True,\n", + "do_predict=False,\n", + "do_train=True,\n", + "eval_accumulation_steps=None,\n", + "eval_steps=500,\n", + "evaluation_strategy=IntervalStrategy.NO,\n", + "fp16=False,\n", + "fp16_backend=auto,\n", + "fp16_full_eval=False,\n", + "fp16_opt_level=O1,\n", + "gradient_accumulation_steps=1,\n", + "greater_is_better=None,\n", + "group_by_length=False,\n", + "ignore_data_skip=False,\n", + "label_names=None,\n", + "label_smoothing_factor=0.0,\n", + "learning_rate=5e-05,\n", + "length_column_name=length,\n", + "load_best_model_at_end=False,\n", + "local_rank=-1,\n", + "log_level=-1,\n", + "log_level_replica=-1,\n", + "log_on_each_node=True,\n", + "logging_dir=./outputs/runs/Jul19_09-59-25_eab5184de9ff,\n", + "logging_first_step=False,\n", + "logging_steps=500,\n", + "logging_strategy=IntervalStrategy.STEPS,\n", + "lr_scheduler_type=SchedulerType.LINEAR,\n", + "max_grad_norm=1.0,\n", + "max_steps=-1,\n", + "metric_for_best_model=None,\n", + "mp_parameters=,\n", + "no_cuda=False,\n", + "num_train_epochs=5.0,\n", + "output_dir=./outputs,\n", + "overwrite_output_dir=True,\n", + "past_index=-1,\n", + "per_device_eval_batch_size=8,\n", + "per_device_train_batch_size=8,\n", + "prediction_loss_only=False,\n", + "push_to_hub=False,\n", + "push_to_hub_model_id=outputs,\n", + "push_to_hub_organization=None,\n", + "push_to_hub_token=None,\n", + "remove_unused_columns=True,\n", + "report_to=['tensorboard', 'wandb'],\n", + "resume_from_checkpoint=None,\n", + "run_name=./outputs,\n", + "save_on_each_node=False,\n", + "save_steps=500,\n", + "save_strategy=IntervalStrategy.STEPS,\n", + "save_total_limit=None,\n", + "seed=42,\n", + "sharded_ddp=[],\n", + "skip_memory_metrics=True,\n", + "tpu_metrics_debug=False,\n", + "tpu_num_cores=None,\n", + "use_legacy_prediction_loop=False,\n", + "warmup_ratio=0.0,\n", + "warmup_steps=0,\n", + "weight_decay=0.0,\n", + ")\n", + "07/19/2021 09:59:27 - INFO - datasets.load - Found main folder for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py at /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002\n", + "07/19/2021 09:59:27 - INFO - datasets.load - Found specific version folder for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py at /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5\n", + "07/19/2021 09:59:27 - INFO - datasets.load - Found script file from https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py to /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5/conll2002.py\n", + "07/19/2021 09:59:27 - INFO - datasets.load - Found dataset infos file from https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/dataset_infos.json to /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5/dataset_infos.json\n", + "07/19/2021 09:59:27 - INFO - datasets.load - Found metadata file for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py at /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5/conll2002.json\n", + "07/19/2021 09:59:28 - INFO - datasets.load - Found main folder for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py at /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002\n", + "07/19/2021 09:59:28 - INFO - datasets.load - Found specific version folder for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py at /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5\n", + "07/19/2021 09:59:28 - INFO - datasets.load - Found script file from https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py to /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5/conll2002.py\n", + "07/19/2021 09:59:28 - INFO - datasets.load - Found dataset infos file from https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/dataset_infos.json to /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5/dataset_infos.json\n", + "07/19/2021 09:59:28 - INFO - datasets.load - Found metadata file for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py at /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5/conll2002.json\n", + "07/19/2021 09:59:28 - INFO - datasets.info - Loading Dataset Infos from /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5\n", + "07/19/2021 09:59:28 - INFO - datasets.builder - Overwrite dataset info from restored data version.\n", + "07/19/2021 09:59:28 - INFO - datasets.info - Loading Dataset info from /root/.cache/huggingface/datasets/conll2002/es/1.0.0/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5\n", + "07/19/2021 09:59:28 - WARNING - datasets.builder - Reusing dataset conll2002 (/root/.cache/huggingface/datasets/conll2002/es/1.0.0/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5)\n", + "07/19/2021 09:59:28 - INFO - datasets.info - Loading Dataset info from /root/.cache/huggingface/datasets/conll2002/es/1.0.0/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5\n", + "100% 3/3 [00:00<00:00, 27.39it/s]\n", + "[INFO|file_utils.py:1624] 2021-07-19 09:59:29,157 >> https://huggingface.co/bertin-project/bertin-base-stepwise/resolve/main/config.json not found in cache or force_download set to True, downloading to /root/.cache/huggingface/transformers/tmph_lls71d\n", + "Downloading: 100% 618/618 [00:00<00:00, 462kB/s]\n", + "[INFO|file_utils.py:1628] 2021-07-19 09:59:29,878 >> storing https://huggingface.co/bertin-project/bertin-base-stepwise/resolve/main/config.json in cache at /root/.cache/huggingface/transformers/367bb30bd1ae06268e9d1c64ae1fb923fc9931913fa478dfa01d79a4c7086238.08210214ecaf5cd53c702826a604e564d8af557125033eef720f4f9f2af1fc44\n", + "[INFO|file_utils.py:1636] 2021-07-19 09:59:29,878 >> creating metadata file for /root/.cache/huggingface/transformers/367bb30bd1ae06268e9d1c64ae1fb923fc9931913fa478dfa01d79a4c7086238.08210214ecaf5cd53c702826a604e564d8af557125033eef720f4f9f2af1fc44\n", + "[INFO|configuration_utils.py:545] 2021-07-19 09:59:29,878 >> loading configuration file https://huggingface.co/bertin-project/bertin-base-stepwise/resolve/main/config.json from cache at /root/.cache/huggingface/transformers/367bb30bd1ae06268e9d1c64ae1fb923fc9931913fa478dfa01d79a4c7086238.08210214ecaf5cd53c702826a604e564d8af557125033eef720f4f9f2af1fc44\n", + "[INFO|configuration_utils.py:581] 2021-07-19 09:59:29,879 >> Model config RobertaConfig {\n", + " \"architectures\": [\n", + " \"RobertaForMaskedLM\"\n", + " ],\n", + " \"attention_probs_dropout_prob\": 0.1,\n", + " \"bos_token_id\": 0,\n", + " \"eos_token_id\": 2,\n", + " \"finetuning_task\": \"ner\",\n", + " \"gradient_checkpointing\": false,\n", + " \"hidden_act\": \"gelu\",\n", + " \"hidden_dropout_prob\": 0.1,\n", + " \"hidden_size\": 768,\n", + " \"id2label\": {\n", + " \"0\": 0,\n", + " \"1\": 1,\n", + " \"2\": 2,\n", + " \"3\": 3,\n", + " \"4\": 4,\n", + " \"5\": 5,\n", + " \"6\": 6,\n", + " \"7\": 7,\n", + " \"8\": 8\n", + " },\n", + " \"initializer_range\": 0.02,\n", + " \"intermediate_size\": 3072,\n", + " \"label2id\": {\n", + " \"0\": 0,\n", + " \"1\": 1,\n", + " \"2\": 2,\n", + " \"3\": 3,\n", + " \"4\": 4,\n", + " \"5\": 5,\n", + " \"6\": 6,\n", + " \"7\": 7,\n", + " \"8\": 8\n", + " },\n", + " \"layer_norm_eps\": 1e-05,\n", + " \"max_position_embeddings\": 514,\n", + " \"model_type\": \"roberta\",\n", + " \"num_attention_heads\": 12,\n", + " \"num_hidden_layers\": 12,\n", + " \"pad_token_id\": 1,\n", + " \"position_embedding_type\": \"absolute\",\n", + " \"transformers_version\": \"4.9.0.dev0\",\n", + " \"type_vocab_size\": 1,\n", + " \"use_cache\": true,\n", + " \"vocab_size\": 50265\n", + "}\n", + "\n", + "[INFO|file_utils.py:1624] 2021-07-19 09:59:30,597 >> https://huggingface.co/bertin-project/bertin-base-stepwise/resolve/main/tokenizer_config.json not found in cache or force_download set to True, downloading to /root/.cache/huggingface/transformers/tmpa6ym7rla\n", + "Downloading: 100% 292/292 [00:00<00:00, 221kB/s]\n", + "[INFO|file_utils.py:1628] 2021-07-19 09:59:31,316 >> storing https://huggingface.co/bertin-project/bertin-base-stepwise/resolve/main/tokenizer_config.json in cache at /root/.cache/huggingface/transformers/e577044edb84fa4a576105e2202c62cf62f831634f9581da80435c97b8034fba.9f7ac4246b492dfa7c21beb5233deec8aef46153ec25ac5258ac5e2ae82dfa89\n", + "[INFO|file_utils.py:1636] 2021-07-19 09:59:31,317 >> creating metadata file for 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creating metadata file for /root/.cache/huggingface/transformers/4832a73c0f4a13adaab71151bf2413717416da487cdb2a79247f10198c6421f8.aebba6b503a22a0c70b362f8b026aa0f030aae594f7580f0164a0a73fb0001af\n", + "[INFO|modeling_utils.py:1271] 2021-07-19 10:00:30,157 >> loading weights file https://huggingface.co/bertin-project/bertin-base-stepwise/resolve/main/pytorch_model.bin from cache at /root/.cache/huggingface/transformers/4832a73c0f4a13adaab71151bf2413717416da487cdb2a79247f10198c6421f8.aebba6b503a22a0c70b362f8b026aa0f030aae594f7580f0164a0a73fb0001af\n", + "[WARNING|modeling_utils.py:1502] 2021-07-19 10:00:31,608 >> Some weights of the model checkpoint at bertin-project/bertin-base-stepwise were not used when initializing RobertaForTokenClassification: ['lm_head.layer_norm.bias', 'lm_head.dense.bias', 'lm_head.layer_norm.weight', 'lm_head.dense.weight', 'lm_head.bias']\n", + "- This IS expected if you are initializing RobertaForTokenClassification from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).\n", + "- This IS NOT expected if you are initializing RobertaForTokenClassification from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).\n", + "[WARNING|modeling_utils.py:1513] 2021-07-19 10:00:31,608 >> Some weights of RobertaForTokenClassification were not initialized from the model checkpoint at bertin-project/bertin-base-stepwise and are newly initialized: ['classifier.weight', 'classifier.bias']\n", + "You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.\n", + "Running tokenizer on train dataset: 0% 0/9 [00:00> The following columns in the training set don't have a corresponding argument in `RobertaForTokenClassification.forward` and have been ignored: tokens, pos_tags, id, ner_tags.\n", + "[INFO|trainer.py:1162] 2021-07-19 10:00:42,473 >> ***** Running training *****\n", + "[INFO|trainer.py:1163] 2021-07-19 10:00:42,473 >> Num examples = 8324\n", + "[INFO|trainer.py:1164] 2021-07-19 10:00:42,473 >> Num Epochs = 5\n", + "[INFO|trainer.py:1165] 2021-07-19 10:00:42,473 >> Instantaneous batch size per device = 8\n", + "[INFO|trainer.py:1166] 2021-07-19 10:00:42,473 >> Total train batch size (w. parallel, distributed & accumulation) = 8\n", + "[INFO|trainer.py:1167] 2021-07-19 10:00:42,474 >> Gradient Accumulation steps = 1\n", + "[INFO|trainer.py:1168] 2021-07-19 10:00:42,474 >> Total optimization steps = 5205\n", + "[INFO|integrations.py:417] 2021-07-19 10:00:42,490 >> Automatic Weights & Biases logging enabled, to disable set os.environ[\"WANDB_DISABLED\"] = \"true\"\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Currently logged in as: \u001b[33mversae\u001b[0m (use `wandb login --relogin` to force relogin)\n", + "2021-07-19 10:00:44.095745: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Successfully opened dynamic library libcudart.so.11.0\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Tracking run with wandb version 0.11.0\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Syncing run \u001b[33m./outputs\u001b[0m\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: ⭐️ View project at \u001b[34m\u001b[4mhttps://wandb.ai/versae/bertin-eval\u001b[0m\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: 🚀 View run at \u001b[34m\u001b[4mhttps://wandb.ai/versae/bertin-eval/runs/3dtrffsb\u001b[0m\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Run data is saved locally in /content/wandb/run-20210719_100042-3dtrffsb\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Run `wandb offline` to turn off syncing.\n", + "\n", + "{'loss': 0.1284, 'learning_rate': 4.5196926032660905e-05, 'epoch': 0.48}\n", + " 10% 500/5205 [02:51<30:10, 2.60it/s][INFO|trainer.py:1917] 2021-07-19 10:03:36,580 >> Saving model checkpoint to ./outputs/checkpoint-500\n", + "[INFO|configuration_utils.py:379] 2021-07-19 10:03:36,582 >> Configuration saved in ./outputs/checkpoint-500/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 10:03:38,006 >> Model weights saved in ./outputs/checkpoint-500/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 10:03:38,007 >> tokenizer config file saved in ./outputs/checkpoint-500/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 10:03:38,007 >> Special tokens file saved in ./outputs/checkpoint-500/special_tokens_map.json\n", + "{'loss': 0.0634, 'learning_rate': 4.039385206532181e-05, 'epoch': 0.96}\n", + " 19% 1000/5205 [05:47<27:17, 2.57it/s][INFO|trainer.py:1917] 2021-07-19 10:06:32,797 >> Saving model checkpoint to ./outputs/checkpoint-1000\n", + "[INFO|configuration_utils.py:379] 2021-07-19 10:06:32,799 >> Configuration saved in ./outputs/checkpoint-1000/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 10:06:34,318 >> Model weights saved in 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'learning_rate': 2.5984630163304517e-05, 'epoch': 2.4}\n", + " 48% 2500/5205 [14:35<17:29, 2.58it/s][INFO|trainer.py:1917] 2021-07-19 10:15:20,423 >> Saving model checkpoint to ./outputs/checkpoint-2500\n", + "[INFO|configuration_utils.py:379] 2021-07-19 10:15:20,427 >> Configuration saved in ./outputs/checkpoint-2500/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 10:15:21,822 >> Model weights saved in ./outputs/checkpoint-2500/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 10:15:21,823 >> tokenizer config file saved in ./outputs/checkpoint-2500/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 10:15:21,823 >> Special tokens file saved in ./outputs/checkpoint-2500/special_tokens_map.json\n", + "{'loss': 0.0206, 'learning_rate': 2.118155619596542e-05, 'epoch': 2.88}\n", + " 58% 3000/5205 [17:30<14:06, 2.60it/s][INFO|trainer.py:1917] 2021-07-19 10:18:16,113 >> Saving model checkpoint to ./outputs/checkpoint-3000\n", + 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'epoch': 4.8}\n", + " 96% 5000/5205 [29:17<01:19, 2.57it/s][INFO|trainer.py:1917] 2021-07-19 10:30:02,859 >> Saving model checkpoint to ./outputs/checkpoint-5000\n", + "[INFO|configuration_utils.py:379] 2021-07-19 10:30:02,860 >> Configuration saved in ./outputs/checkpoint-5000/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 10:30:04,283 >> Model weights saved in ./outputs/checkpoint-5000/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 10:30:04,284 >> tokenizer config file saved in ./outputs/checkpoint-5000/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 10:30:04,285 >> Special tokens file saved in ./outputs/checkpoint-5000/special_tokens_map.json\n", + "100% 5205/5205 [30:33<00:00, 3.23it/s][INFO|trainer.py:1358] 2021-07-19 10:31:18,770 >> \n", + "\n", + "Training completed. Do not forget to share your model on huggingface.co/models =)\n", + "\n", + "\n", + "{'train_runtime': 1836.2971, 'train_samples_per_second': 22.665, 'train_steps_per_second': 2.835, 'train_loss': 0.03514896872865821, 'epoch': 5.0}\n", + "100% 5205/5205 [30:33<00:00, 2.84it/s]\n", + "[INFO|trainer.py:1917] 2021-07-19 10:31:18,782 >> Saving model checkpoint to ./outputs\n", + "[INFO|configuration_utils.py:379] 2021-07-19 10:31:18,784 >> Configuration saved in ./outputs/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 10:31:20,398 >> Model weights saved in ./outputs/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 10:31:20,399 >> tokenizer config file saved in ./outputs/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 10:31:20,399 >> Special tokens file saved in ./outputs/special_tokens_map.json\n", + "***** train metrics *****\n", + " epoch = 5.0\n", + " train_loss = 0.0351\n", + " train_runtime = 0:30:36.29\n", + " train_samples = 8324\n", + " train_samples_per_second = 22.665\n", + " train_steps_per_second = 2.835\n", + "[INFO|trainer.py:522] 2021-07-19 10:31:20,531 >> The following columns in the evaluation set don't have a corresponding argument in `RobertaForTokenClassification.forward` and have been ignored: tokens, pos_tags, id, ner_tags.\n", + "07/19/2021 10:31:20 - INFO - __main__ - *** Evaluate ***\n", + "[INFO|trainer.py:2163] 2021-07-19 10:31:20,554 >> ***** Running Evaluation *****\n", + "[INFO|trainer.py:2165] 2021-07-19 10:31:20,554 >> Num examples = 1916\n", + "[INFO|trainer.py:2168] 2021-07-19 10:31:20,555 >> Batch size = 8\n", + "100% 240/240 [00:26<00:00, 9.03it/s]\n", + "***** eval metrics *****\n", + " epoch = 5.0\n", + " eval_accuracy = 0.9809\n", + " eval_f1 = 0.8705\n", + " eval_loss = 0.1126\n", + " eval_precision = 0.8643\n", + " eval_recall = 0.8768\n", + " eval_runtime = 0:00:26.68\n", + " eval_samples = 1916\n", + " eval_samples_per_second = 71.804\n", + " eval_steps_per_second = 8.994\n", + "\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Waiting for W&B process to finish, PID 463\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Program ended successfully.\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: \n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Find user logs for this run at: /content/wandb/run-20210719_100042-3dtrffsb/logs/debug.log\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Find internal logs for this run at: /content/wandb/run-20210719_100042-3dtrffsb/logs/debug-internal.log\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Run summary:\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/loss 0.0082\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/learning_rate 0.0\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/epoch 5.0\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/global_step 5205\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: _runtime 1865\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: _timestamp 1626690707\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: _step 11\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_runtime 1836.2971\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_samples_per_second 22.665\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_steps_per_second 2.835\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/total_flos 1.087585926764544e+16\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_loss 0.03515\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/loss 0.1126\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/precision 0.86433\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/recall 0.87684\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/f1 0.87054\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/accuracy 0.98093\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/runtime 26.6838\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/samples_per_second 71.804\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/steps_per_second 8.994\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Run history:\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/loss 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"\u001b[34m\u001b[1mwandb\u001b[0m: eval/accuracy ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/runtime ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/samples_per_second ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/steps_per_second ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: \n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Synced 5 W&B file(s), 0 media file(s), 0 artifact file(s) and 1 other file(s)\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: \n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Synced \u001b[33m./outputs\u001b[0m: \u001b[34mhttps://wandb.ai/versae/bertin-eval/runs/3dtrffsb\u001b[0m\n", + "2021-07-19 10:31:59.813609: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Successfully opened dynamic library libcudart.so.11.0\n", + "07/19/2021 10:32:02 - WARNING - __main__ - Process rank: -1, device: cuda:0, n_gpu: 1distributed training: False, 16-bits training: False\n", + "07/19/2021 10:32:02 - INFO - __main__ - Training/evaluation parameters TrainingArguments(\n", + "_n_gpu=1,\n", + "adafactor=False,\n", + "adam_beta1=0.9,\n", + "adam_beta2=0.999,\n", + "adam_epsilon=1e-08,\n", + "dataloader_drop_last=False,\n", + "dataloader_num_workers=0,\n", + "dataloader_pin_memory=True,\n", + "ddp_find_unused_parameters=None,\n", + "debug=[],\n", + "deepspeed=None,\n", + "disable_tqdm=False,\n", + "do_eval=True,\n", + "do_predict=False,\n", + "do_train=True,\n", + "eval_accumulation_steps=None,\n", + "eval_steps=500,\n", + "evaluation_strategy=IntervalStrategy.NO,\n", + "fp16=False,\n", + "fp16_backend=auto,\n", + "fp16_full_eval=False,\n", + "fp16_opt_level=O1,\n", + "gradient_accumulation_steps=1,\n", + "greater_is_better=None,\n", + "group_by_length=False,\n", + "ignore_data_skip=False,\n", + "label_names=None,\n", + "label_smoothing_factor=0.0,\n", + "learning_rate=5e-05,\n", + "length_column_name=length,\n", + "load_best_model_at_end=False,\n", + "local_rank=-1,\n", + "log_level=-1,\n", + "log_level_replica=-1,\n", + "log_on_each_node=True,\n", + "logging_dir=./outputs/runs/Jul19_10-32-02_eab5184de9ff,\n", + "logging_first_step=False,\n", + "logging_steps=500,\n", + "logging_strategy=IntervalStrategy.STEPS,\n", + "lr_scheduler_type=SchedulerType.LINEAR,\n", + "max_grad_norm=1.0,\n", + "max_steps=-1,\n", + "metric_for_best_model=None,\n", + "mp_parameters=,\n", + "no_cuda=False,\n", + "num_train_epochs=5.0,\n", + "output_dir=./outputs,\n", + "overwrite_output_dir=True,\n", + "past_index=-1,\n", + "per_device_eval_batch_size=8,\n", + "per_device_train_batch_size=8,\n", + "prediction_loss_only=False,\n", + "push_to_hub=False,\n", + "push_to_hub_model_id=outputs,\n", + "push_to_hub_organization=None,\n", + "push_to_hub_token=None,\n", + "remove_unused_columns=True,\n", + "report_to=['tensorboard', 'wandb'],\n", + "resume_from_checkpoint=None,\n", + "run_name=./outputs,\n", + "save_on_each_node=False,\n", + "save_steps=500,\n", + "save_strategy=IntervalStrategy.STEPS,\n", + "save_total_limit=None,\n", + "seed=42,\n", + "sharded_ddp=[],\n", + "skip_memory_metrics=True,\n", + "tpu_metrics_debug=False,\n", + "tpu_num_cores=None,\n", + "use_legacy_prediction_loop=False,\n", + "warmup_ratio=0.0,\n", + "warmup_steps=0,\n", + "weight_decay=0.0,\n", + ")\n", + "07/19/2021 10:32:04 - INFO - datasets.load - Found main folder for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py at /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002\n", + "07/19/2021 10:32:04 - INFO - datasets.load - Found specific version folder for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py at /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5\n", + "07/19/2021 10:32:04 - INFO - datasets.load - Found script file from https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py to /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5/conll2002.py\n", + "07/19/2021 10:32:04 - INFO - datasets.load - Found dataset infos file from https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/dataset_infos.json to /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5/dataset_infos.json\n", + "07/19/2021 10:32:04 - INFO - datasets.load - Found metadata file for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py at /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5/conll2002.json\n", + "07/19/2021 10:32:05 - INFO - datasets.load - Found main folder for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py at /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002\n", + "07/19/2021 10:32:05 - INFO - datasets.load - Found specific version folder for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py at /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5\n", + "07/19/2021 10:32:05 - INFO - datasets.load - Found script file from https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py to /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5/conll2002.py\n", + "07/19/2021 10:32:05 - INFO - datasets.load - Found dataset infos file from https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/dataset_infos.json to /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5/dataset_infos.json\n", + "07/19/2021 10:32:05 - INFO - datasets.load - Found metadata file for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py at /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5/conll2002.json\n", + "07/19/2021 10:32:05 - INFO - datasets.info - Loading Dataset Infos from /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5\n", + "07/19/2021 10:32:05 - INFO - datasets.builder - Overwrite dataset info from restored data version.\n", + "07/19/2021 10:32:05 - INFO - datasets.info - Loading Dataset info from /root/.cache/huggingface/datasets/conll2002/es/1.0.0/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5\n", + "07/19/2021 10:32:05 - WARNING - datasets.builder - Reusing dataset conll2002 (/root/.cache/huggingface/datasets/conll2002/es/1.0.0/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5)\n", + "07/19/2021 10:32:05 - INFO - datasets.info - Loading Dataset info from /root/.cache/huggingface/datasets/conll2002/es/1.0.0/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5\n", + "100% 3/3 [00:00<00:00, 26.98it/s]\n", + "[INFO|file_utils.py:1624] 2021-07-19 10:32:06,091 >> https://huggingface.co/bertin-project/bertin-base-random/resolve/main/config.json not found in cache or force_download set to True, downloading to /root/.cache/huggingface/transformers/tmpn8ndvk_m\n", + "Downloading: 100% 618/618 [00:00<00:00, 441kB/s]\n", + "[INFO|file_utils.py:1628] 2021-07-19 10:32:07,076 >> storing https://huggingface.co/bertin-project/bertin-base-random/resolve/main/config.json in cache at /root/.cache/huggingface/transformers/206b1dac57f81203b68e667a852122cb8107d8f6ec61c5f61ff3911b995464bc.08210214ecaf5cd53c702826a604e564d8af557125033eef720f4f9f2af1fc44\n", + "[INFO|file_utils.py:1636] 2021-07-19 10:32:07,076 >> creating metadata file for /root/.cache/huggingface/transformers/206b1dac57f81203b68e667a852122cb8107d8f6ec61c5f61ff3911b995464bc.08210214ecaf5cd53c702826a604e564d8af557125033eef720f4f9f2af1fc44\n", + "[INFO|configuration_utils.py:545] 2021-07-19 10:32:07,077 >> loading configuration file https://huggingface.co/bertin-project/bertin-base-random/resolve/main/config.json from cache at /root/.cache/huggingface/transformers/206b1dac57f81203b68e667a852122cb8107d8f6ec61c5f61ff3911b995464bc.08210214ecaf5cd53c702826a604e564d8af557125033eef720f4f9f2af1fc44\n", + "[INFO|configuration_utils.py:581] 2021-07-19 10:32:07,078 >> Model config RobertaConfig {\n", + " \"architectures\": [\n", + " \"RobertaForMaskedLM\"\n", + " ],\n", + " \"attention_probs_dropout_prob\": 0.1,\n", + " \"bos_token_id\": 0,\n", + " \"eos_token_id\": 2,\n", + " \"finetuning_task\": \"ner\",\n", + " \"gradient_checkpointing\": false,\n", + " \"hidden_act\": \"gelu\",\n", + " \"hidden_dropout_prob\": 0.1,\n", + " \"hidden_size\": 768,\n", + " \"id2label\": {\n", + " \"0\": 0,\n", + " \"1\": 1,\n", + " \"2\": 2,\n", + " \"3\": 3,\n", + " \"4\": 4,\n", + " \"5\": 5,\n", + " \"6\": 6,\n", + " \"7\": 7,\n", + " \"8\": 8\n", + " },\n", + " \"initializer_range\": 0.02,\n", + " \"intermediate_size\": 3072,\n", + " \"label2id\": {\n", + " \"0\": 0,\n", + " \"1\": 1,\n", + " \"2\": 2,\n", + " \"3\": 3,\n", + " \"4\": 4,\n", + " \"5\": 5,\n", + " \"6\": 6,\n", + " \"7\": 7,\n", + " \"8\": 8\n", + " },\n", + " \"layer_norm_eps\": 1e-05,\n", + " \"max_position_embeddings\": 514,\n", + " \"model_type\": \"roberta\",\n", + " \"num_attention_heads\": 12,\n", + " \"num_hidden_layers\": 12,\n", + " \"pad_token_id\": 1,\n", + " \"position_embedding_type\": \"absolute\",\n", + " \"transformers_version\": \"4.9.0.dev0\",\n", + " \"type_vocab_size\": 1,\n", + " \"use_cache\": true,\n", + " \"vocab_size\": 50265\n", + "}\n", + "\n", + "[INFO|file_utils.py:1624] 2021-07-19 10:32:07,798 >> https://huggingface.co/bertin-project/bertin-base-random/resolve/main/tokenizer_config.json not found in cache or force_download set to True, downloading to /root/.cache/huggingface/transformers/tmpz_j0rpzc\n", + "Downloading: 100% 292/292 [00:00<00:00, 217kB/s]\n", + "[INFO|file_utils.py:1628] 2021-07-19 10:32:08,519 >> storing https://huggingface.co/bertin-project/bertin-base-random/resolve/main/tokenizer_config.json in cache at /root/.cache/huggingface/transformers/115b6bf4f08e65d03dda82a834c42cf46339813770aadf59679bd51d0f2ea3a5.9f7ac4246b492dfa7c21beb5233deec8aef46153ec25ac5258ac5e2ae82dfa89\n", + "[INFO|file_utils.py:1636] 2021-07-19 10:32:08,519 >> creating metadata file for 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/root/.cache/huggingface/transformers/5bec117e97fb2ec50c8615b1e2cde784a5851d7664417aa49e21403f91722df2.fc71d0bf8be2b57b708f6397729f6f12e8e95a3e69e8a44030293be69ee5bc0d\n", + "[INFO|modeling_utils.py:1271] 2021-07-19 10:33:07,770 >> loading weights file https://huggingface.co/bertin-project/bertin-base-random/resolve/main/pytorch_model.bin from cache at /root/.cache/huggingface/transformers/5bec117e97fb2ec50c8615b1e2cde784a5851d7664417aa49e21403f91722df2.fc71d0bf8be2b57b708f6397729f6f12e8e95a3e69e8a44030293be69ee5bc0d\n", + "[WARNING|modeling_utils.py:1502] 2021-07-19 10:33:09,270 >> Some weights of the model checkpoint at bertin-project/bertin-base-random were not used when initializing RobertaForTokenClassification: ['lm_head.dense.weight', 'lm_head.dense.bias', 'lm_head.bias', 'lm_head.layer_norm.weight', 'lm_head.layer_norm.bias']\n", + "- This IS expected if you are initializing RobertaForTokenClassification from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).\n", + "- This IS NOT expected if you are initializing RobertaForTokenClassification from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).\n", + "[WARNING|modeling_utils.py:1513] 2021-07-19 10:33:09,270 >> Some weights of RobertaForTokenClassification were not initialized from the model checkpoint at bertin-project/bertin-base-random and are newly initialized: ['classifier.bias', 'classifier.weight']\n", + "You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.\n", + "Running tokenizer on train dataset: 0% 0/9 [00:00> The following columns in the training set don't have a corresponding argument in `RobertaForTokenClassification.forward` and have been ignored: ner_tags, pos_tags, id, tokens.\n", + "[INFO|trainer.py:1162] 2021-07-19 10:33:20,589 >> ***** Running training *****\n", + "[INFO|trainer.py:1163] 2021-07-19 10:33:20,589 >> Num examples = 8324\n", + "[INFO|trainer.py:1164] 2021-07-19 10:33:20,589 >> Num Epochs = 5\n", + "[INFO|trainer.py:1165] 2021-07-19 10:33:20,589 >> Instantaneous batch size per device = 8\n", + "[INFO|trainer.py:1166] 2021-07-19 10:33:20,589 >> Total train batch size (w. parallel, distributed & accumulation) = 8\n", + "[INFO|trainer.py:1167] 2021-07-19 10:33:20,589 >> Gradient Accumulation steps = 1\n", + "[INFO|trainer.py:1168] 2021-07-19 10:33:20,589 >> Total optimization steps = 5205\n", + "[INFO|integrations.py:417] 2021-07-19 10:33:20,607 >> Automatic Weights & Biases logging enabled, to disable set os.environ[\"WANDB_DISABLED\"] = \"true\"\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Currently logged in as: \u001b[33mversae\u001b[0m (use `wandb login --relogin` to force relogin)\n", + "2021-07-19 10:33:22.258421: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Successfully opened dynamic library libcudart.so.11.0\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Tracking run with wandb version 0.11.0\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Syncing run \u001b[33m./outputs\u001b[0m\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: ⭐️ View project at \u001b[34m\u001b[4mhttps://wandb.ai/versae/bertin-eval\u001b[0m\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: 🚀 View run at \u001b[34m\u001b[4mhttps://wandb.ai/versae/bertin-eval/runs/ibzlw8va\u001b[0m\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Run data is saved locally in /content/wandb/run-20210719_103320-ibzlw8va\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Run `wandb offline` to turn off syncing.\n", + "\n", + "{'loss': 0.1287, 'learning_rate': 4.5196926032660905e-05, 'epoch': 0.48}\n", + " 10% 500/5205 [02:53<31:17, 2.51it/s][INFO|trainer.py:1917] 2021-07-19 10:36:16,688 >> Saving model checkpoint to ./outputs/checkpoint-500\n", + "[INFO|configuration_utils.py:379] 2021-07-19 10:36:16,690 >> Configuration saved in ./outputs/checkpoint-500/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 10:36:18,026 >> Model weights saved in ./outputs/checkpoint-500/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 10:36:18,027 >> tokenizer config file saved in ./outputs/checkpoint-500/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 10:36:18,027 >> Special tokens file saved in ./outputs/checkpoint-500/special_tokens_map.json\n", + "{'loss': 0.0639, 'learning_rate': 4.039385206532181e-05, 'epoch': 0.96}\n", + " 19% 1000/5205 [05:51<27:24, 2.56it/s][INFO|trainer.py:1917] 2021-07-19 10:39:15,501 >> Saving model checkpoint to ./outputs/checkpoint-1000\n", + "[INFO|configuration_utils.py:379] 2021-07-19 10:39:15,503 >> Configuration saved in ./outputs/checkpoint-1000/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 10:39:17,123 >> Model weights saved in 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'epoch': 2.4}\n", + " 48% 2500/5205 [14:46<17:34, 2.56it/s][INFO|trainer.py:1917] 2021-07-19 10:48:10,298 >> Saving model checkpoint to ./outputs/checkpoint-2500\n", + "[INFO|configuration_utils.py:379] 2021-07-19 10:48:10,299 >> Configuration saved in ./outputs/checkpoint-2500/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 10:48:11,882 >> Model weights saved in ./outputs/checkpoint-2500/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 10:48:11,882 >> tokenizer config file saved in ./outputs/checkpoint-2500/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 10:48:11,883 >> Special tokens file saved in ./outputs/checkpoint-2500/special_tokens_map.json\n", + "{'loss': 0.0231, 'learning_rate': 2.118155619596542e-05, 'epoch': 2.88}\n", + " 58% 3000/5205 [17:44<14:23, 2.55it/s][INFO|trainer.py:1917] 2021-07-19 10:51:08,324 >> Saving model checkpoint to ./outputs/checkpoint-3000\n", + "[INFO|configuration_utils.py:379] 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Do not forget to share your model on huggingface.co/models =)\n", + "\n", + "\n", + "{'train_runtime': 1852.8561, 'train_samples_per_second': 22.463, 'train_steps_per_second': 2.809, 'train_loss': 0.03592821839448927, 'epoch': 5.0}\n", + "100% 5205/5205 [30:49<00:00, 2.81it/s]\n", + "[INFO|trainer.py:1917] 2021-07-19 11:04:13,449 >> Saving model checkpoint to ./outputs\n", + "[INFO|configuration_utils.py:379] 2021-07-19 11:04:13,451 >> Configuration saved in ./outputs/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 11:04:14,892 >> Model weights saved in ./outputs/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 11:04:14,893 >> tokenizer config file saved in ./outputs/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 11:04:14,893 >> Special tokens file saved in ./outputs/special_tokens_map.json\n", + "***** train metrics *****\n", + " epoch = 5.0\n", + " train_loss = 0.0359\n", + " train_runtime = 0:30:52.85\n", + " train_samples = 8324\n", + " train_samples_per_second = 22.463\n", + " train_steps_per_second = 2.809\n", + "[INFO|trainer.py:522] 2021-07-19 11:04:15,047 >> The following columns in the evaluation set don't have a corresponding argument in `RobertaForTokenClassification.forward` and have been ignored: ner_tags, pos_tags, id, tokens.\n", + "07/19/2021 11:04:15 - INFO - __main__ - *** Evaluate ***\n", + "[INFO|trainer.py:2163] 2021-07-19 11:04:15,145 >> ***** Running Evaluation *****\n", + "[INFO|trainer.py:2165] 2021-07-19 11:04:15,147 >> Num examples = 1916\n", + "[INFO|trainer.py:2168] 2021-07-19 11:04:15,147 >> Batch size = 8\n", + "100% 240/240 [00:26<00:00, 9.01it/s]\n", + "***** eval metrics *****\n", + " epoch = 5.0\n", + " eval_accuracy = 0.9807\n", + " eval_f1 = 0.8704\n", + " eval_loss = 0.1116\n", + " eval_precision = 0.8652\n", + " eval_recall = 0.8757\n", + " eval_runtime = 0:00:26.78\n", + " eval_samples = 1916\n", + " eval_samples_per_second = 71.544\n", + " eval_steps_per_second = 8.962\n", + "\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Waiting for W&B process to finish, PID 534\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Program ended successfully.\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: \n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Find user logs for this run at: /content/wandb/run-20210719_103320-ibzlw8va/logs/debug.log\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Find internal logs for this run at: /content/wandb/run-20210719_103320-ibzlw8va/logs/debug-internal.log\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Run summary:\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/loss 0.0085\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/learning_rate 0.0\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/epoch 5.0\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/global_step 5205\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: _runtime 1881\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: _timestamp 1626692681\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: _step 11\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_runtime 1852.8561\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_samples_per_second 22.463\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_steps_per_second 2.809\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/total_flos 1.087585926764544e+16\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_loss 0.03593\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/loss 0.11165\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/precision 0.86515\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/recall 0.87569\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/f1 0.87039\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/accuracy 0.98067\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/runtime 26.7809\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/samples_per_second 71.544\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/steps_per_second 8.962\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Run history:\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/loss 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"\u001b[34m\u001b[1mwandb\u001b[0m: eval/accuracy ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/runtime ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/samples_per_second ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/steps_per_second ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: \n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Synced 5 W&B file(s), 0 media file(s), 0 artifact file(s) and 1 other file(s)\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: \n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Synced \u001b[33m./outputs\u001b[0m: \u001b[34mhttps://wandb.ai/versae/bertin-eval/runs/ibzlw8va\u001b[0m\n", + "2021-07-19 11:04:55.088954: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Successfully opened dynamic library libcudart.so.11.0\n", + "07/19/2021 11:04:57 - WARNING - __main__ - Process rank: -1, device: cuda:0, n_gpu: 1distributed training: False, 16-bits training: False\n", + "07/19/2021 11:04:57 - INFO - __main__ - Training/evaluation parameters TrainingArguments(\n", + "_n_gpu=1,\n", + "adafactor=False,\n", + "adam_beta1=0.9,\n", + "adam_beta2=0.999,\n", + "adam_epsilon=1e-08,\n", + "dataloader_drop_last=False,\n", + "dataloader_num_workers=0,\n", + "dataloader_pin_memory=True,\n", + "ddp_find_unused_parameters=None,\n", + "debug=[],\n", + "deepspeed=None,\n", + "disable_tqdm=False,\n", + "do_eval=True,\n", + "do_predict=False,\n", + "do_train=True,\n", + "eval_accumulation_steps=None,\n", + "eval_steps=500,\n", + "evaluation_strategy=IntervalStrategy.NO,\n", + "fp16=False,\n", + "fp16_backend=auto,\n", + "fp16_full_eval=False,\n", + "fp16_opt_level=O1,\n", + "gradient_accumulation_steps=1,\n", + "greater_is_better=None,\n", + "group_by_length=False,\n", + "ignore_data_skip=False,\n", + "label_names=None,\n", + "label_smoothing_factor=0.0,\n", + "learning_rate=5e-05,\n", + "length_column_name=length,\n", + "load_best_model_at_end=False,\n", + "local_rank=-1,\n", + "log_level=-1,\n", + "log_level_replica=-1,\n", + "log_on_each_node=True,\n", + "logging_dir=./outputs/runs/Jul19_11-04-57_eab5184de9ff,\n", + "logging_first_step=False,\n", + "logging_steps=500,\n", + "logging_strategy=IntervalStrategy.STEPS,\n", + "lr_scheduler_type=SchedulerType.LINEAR,\n", + "max_grad_norm=1.0,\n", + "max_steps=-1,\n", + "metric_for_best_model=None,\n", + "mp_parameters=,\n", + "no_cuda=False,\n", + "num_train_epochs=5.0,\n", + "output_dir=./outputs,\n", + "overwrite_output_dir=True,\n", + "past_index=-1,\n", + "per_device_eval_batch_size=8,\n", + "per_device_train_batch_size=8,\n", + "prediction_loss_only=False,\n", + "push_to_hub=False,\n", + "push_to_hub_model_id=outputs,\n", + "push_to_hub_organization=None,\n", + "push_to_hub_token=None,\n", + "remove_unused_columns=True,\n", + "report_to=['tensorboard', 'wandb'],\n", + "resume_from_checkpoint=None,\n", + "run_name=./outputs,\n", + "save_on_each_node=False,\n", + "save_steps=500,\n", + "save_strategy=IntervalStrategy.STEPS,\n", + "save_total_limit=None,\n", + "seed=42,\n", + "sharded_ddp=[],\n", + "skip_memory_metrics=True,\n", + "tpu_metrics_debug=False,\n", + "tpu_num_cores=None,\n", + "use_legacy_prediction_loop=False,\n", + "warmup_ratio=0.0,\n", + "warmup_steps=0,\n", + "weight_decay=0.0,\n", + ")\n", + "07/19/2021 11:04:59 - INFO - datasets.load - Found main folder for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py at /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002\n", + "07/19/2021 11:04:59 - INFO - datasets.load - Found specific version folder for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py at /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5\n", + "07/19/2021 11:04:59 - INFO - datasets.load - Found script file from https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py to /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5/conll2002.py\n", + "07/19/2021 11:04:59 - INFO - datasets.load - Found dataset infos file from https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/dataset_infos.json to /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5/dataset_infos.json\n", + "07/19/2021 11:04:59 - INFO - datasets.load - Found metadata file for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py at /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5/conll2002.json\n", + "07/19/2021 11:05:00 - INFO - datasets.load - Found main folder for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py at /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002\n", + "07/19/2021 11:05:00 - INFO - datasets.load - Found specific version folder for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py at /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5\n", + "07/19/2021 11:05:00 - INFO - datasets.load - Found script file from https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py to /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5/conll2002.py\n", + "07/19/2021 11:05:00 - INFO - datasets.load - Found dataset infos file from https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/dataset_infos.json to /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5/dataset_infos.json\n", + "07/19/2021 11:05:00 - INFO - datasets.load - Found metadata file for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py at /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5/conll2002.json\n", + "07/19/2021 11:05:00 - INFO - datasets.info - Loading Dataset Infos from /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5\n", + "07/19/2021 11:05:00 - INFO - datasets.builder - Overwrite dataset info from restored data version.\n", + "07/19/2021 11:05:00 - INFO - datasets.info - Loading Dataset info from /root/.cache/huggingface/datasets/conll2002/es/1.0.0/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5\n", + "07/19/2021 11:05:00 - WARNING - datasets.builder - Reusing dataset conll2002 (/root/.cache/huggingface/datasets/conll2002/es/1.0.0/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5)\n", + "07/19/2021 11:05:00 - INFO - datasets.info - Loading Dataset info from /root/.cache/huggingface/datasets/conll2002/es/1.0.0/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5\n", + "100% 3/3 [00:00<00:00, 26.69it/s]\n", + "[INFO|file_utils.py:1624] 2021-07-19 11:05:01,612 >> https://huggingface.co/bertin-project/bertin-roberta-base-spanish/resolve/main/config.json not found in cache or force_download set to True, downloading to /root/.cache/huggingface/transformers/tmpx_65nogc\n", + "Downloading: 100% 618/618 [00:00<00:00, 500kB/s]\n", + "[INFO|file_utils.py:1628] 2021-07-19 11:05:02,332 >> storing https://huggingface.co/bertin-project/bertin-roberta-base-spanish/resolve/main/config.json in cache at /root/.cache/huggingface/transformers/aa24361f0b7bed62876f6cd0a784a2b622c1959523906d89eeb1112139a4864a.08210214ecaf5cd53c702826a604e564d8af557125033eef720f4f9f2af1fc44\n", + "[INFO|file_utils.py:1636] 2021-07-19 11:05:02,332 >> creating metadata file for /root/.cache/huggingface/transformers/aa24361f0b7bed62876f6cd0a784a2b622c1959523906d89eeb1112139a4864a.08210214ecaf5cd53c702826a604e564d8af557125033eef720f4f9f2af1fc44\n", + "[INFO|configuration_utils.py:545] 2021-07-19 11:05:02,332 >> loading configuration file https://huggingface.co/bertin-project/bertin-roberta-base-spanish/resolve/main/config.json from cache at /root/.cache/huggingface/transformers/aa24361f0b7bed62876f6cd0a784a2b622c1959523906d89eeb1112139a4864a.08210214ecaf5cd53c702826a604e564d8af557125033eef720f4f9f2af1fc44\n", + "[INFO|configuration_utils.py:581] 2021-07-19 11:05:02,333 >> Model config RobertaConfig {\n", + " \"architectures\": [\n", + " \"RobertaForMaskedLM\"\n", + " ],\n", + " \"attention_probs_dropout_prob\": 0.1,\n", + " \"bos_token_id\": 0,\n", + " \"eos_token_id\": 2,\n", + " \"finetuning_task\": \"ner\",\n", + " \"gradient_checkpointing\": false,\n", + " \"hidden_act\": \"gelu\",\n", + " \"hidden_dropout_prob\": 0.1,\n", + " \"hidden_size\": 768,\n", + " \"id2label\": {\n", + " \"0\": 0,\n", + " \"1\": 1,\n", + " \"2\": 2,\n", + " \"3\": 3,\n", + " \"4\": 4,\n", + " \"5\": 5,\n", + " \"6\": 6,\n", + " \"7\": 7,\n", + " \"8\": 8\n", + " },\n", + " \"initializer_range\": 0.02,\n", + " \"intermediate_size\": 3072,\n", + " \"label2id\": {\n", + " \"0\": 0,\n", + " \"1\": 1,\n", + " \"2\": 2,\n", + " \"3\": 3,\n", + " \"4\": 4,\n", + " \"5\": 5,\n", + " \"6\": 6,\n", + " \"7\": 7,\n", + " \"8\": 8\n", + " },\n", + " \"layer_norm_eps\": 1e-05,\n", + " \"max_position_embeddings\": 514,\n", + " \"model_type\": \"roberta\",\n", + " \"num_attention_heads\": 12,\n", + " \"num_hidden_layers\": 12,\n", + " \"pad_token_id\": 1,\n", + " \"position_embedding_type\": \"absolute\",\n", + " \"transformers_version\": \"4.9.0.dev0\",\n", + " \"type_vocab_size\": 1,\n", + " \"use_cache\": true,\n", + " \"vocab_size\": 50265\n", + "}\n", + "\n", + "[INFO|file_utils.py:1624] 2021-07-19 11:05:03,052 >> https://huggingface.co/bertin-project/bertin-roberta-base-spanish/resolve/main/tokenizer_config.json not found in cache or force_download set to True, downloading to /root/.cache/huggingface/transformers/tmp9x2e0_gj\n", + "Downloading: 100% 292/292 [00:00<00:00, 214kB/s]\n", + "[INFO|file_utils.py:1628] 2021-07-19 11:05:03,773 >> storing https://huggingface.co/bertin-project/bertin-roberta-base-spanish/resolve/main/tokenizer_config.json in cache at /root/.cache/huggingface/transformers/72bf61c243630a112d8fa8c8d9162f1a5e01fab0602d2f2a7792cecdc0a4986f.9f7ac4246b492dfa7c21beb5233deec8aef46153ec25ac5258ac5e2ae82dfa89\n", + "[INFO|file_utils.py:1636] 2021-07-19 11:05:03,773 >> creating metadata file for 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2021-07-19 11:06:03,353 >> creating metadata file for /root/.cache/huggingface/transformers/8a611c8e6ab409ea523e84173bef4b1ef257262487d732b05c68d31b674788e5.ae8a25c127f59d8b0d9d11c53667336d7c491e5b06338b3ce56369ee735acd6f\n", + "[INFO|modeling_utils.py:1271] 2021-07-19 11:06:03,353 >> loading weights file https://huggingface.co/bertin-project/bertin-roberta-base-spanish/resolve/main/pytorch_model.bin from cache at /root/.cache/huggingface/transformers/8a611c8e6ab409ea523e84173bef4b1ef257262487d732b05c68d31b674788e5.ae8a25c127f59d8b0d9d11c53667336d7c491e5b06338b3ce56369ee735acd6f\n", + "[WARNING|modeling_utils.py:1502] 2021-07-19 11:06:04,877 >> Some weights of the model checkpoint at bertin-project/bertin-roberta-base-spanish were not used when initializing RobertaForTokenClassification: ['lm_head.dense.bias', 'lm_head.layer_norm.weight', 'lm_head.layer_norm.bias', 'lm_head.bias', 'lm_head.dense.weight']\n", + "- This IS expected if you are initializing RobertaForTokenClassification from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).\n", + "- This IS NOT expected if you are initializing RobertaForTokenClassification from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).\n", + "[WARNING|modeling_utils.py:1513] 2021-07-19 11:06:04,877 >> Some weights of RobertaForTokenClassification were not initialized from the model checkpoint at bertin-project/bertin-roberta-base-spanish and are newly initialized: ['classifier.weight', 'classifier.bias']\n", + "You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.\n", + "Running tokenizer on train dataset: 0% 0/9 [00:00> The following columns in the training set don't have a corresponding argument in `RobertaForTokenClassification.forward` and have been ignored: id, pos_tags, tokens, ner_tags.\n", + "[INFO|trainer.py:1162] 2021-07-19 11:06:16,543 >> ***** Running training *****\n", + "[INFO|trainer.py:1163] 2021-07-19 11:06:16,543 >> Num examples = 8324\n", + "[INFO|trainer.py:1164] 2021-07-19 11:06:16,543 >> Num Epochs = 5\n", + "[INFO|trainer.py:1165] 2021-07-19 11:06:16,543 >> Instantaneous batch size per device = 8\n", + "[INFO|trainer.py:1166] 2021-07-19 11:06:16,543 >> Total train batch size (w. parallel, distributed & accumulation) = 8\n", + "[INFO|trainer.py:1167] 2021-07-19 11:06:16,543 >> Gradient Accumulation steps = 1\n", + "[INFO|trainer.py:1168] 2021-07-19 11:06:16,543 >> Total optimization steps = 5205\n", + "[INFO|integrations.py:417] 2021-07-19 11:06:16,562 >> Automatic Weights & Biases logging enabled, to disable set os.environ[\"WANDB_DISABLED\"] = \"true\"\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Currently logged in as: \u001b[33mversae\u001b[0m (use `wandb login --relogin` to force relogin)\n", + "2021-07-19 11:06:18.176951: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Successfully opened dynamic library libcudart.so.11.0\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Tracking run with wandb version 0.11.0\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Syncing run \u001b[33m./outputs\u001b[0m\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: ⭐️ View project at \u001b[34m\u001b[4mhttps://wandb.ai/versae/bertin-eval\u001b[0m\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: 🚀 View run at \u001b[34m\u001b[4mhttps://wandb.ai/versae/bertin-eval/runs/j1pmca9j\u001b[0m\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Run data is saved locally in /content/wandb/run-20210719_110616-j1pmca9j\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Run `wandb offline` to turn off syncing.\n", + "\n", + " 10% 500/5205 [02:53<30:54, 2.54it/s]{'loss': 0.1572, 'learning_rate': 4.5196926032660905e-05, 'epoch': 0.48}\n", + " 10% 500/5205 [02:53<30:54, 2.54it/s][INFO|trainer.py:1917] 2021-07-19 11:09:13,478 >> Saving model checkpoint to ./outputs/checkpoint-500\n", + "[INFO|configuration_utils.py:379] 2021-07-19 11:09:13,480 >> Configuration saved in ./outputs/checkpoint-500/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 11:09:14,958 >> Model weights saved in ./outputs/checkpoint-500/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 11:09:14,966 >> tokenizer config file saved in ./outputs/checkpoint-500/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 11:09:14,967 >> Special tokens file saved in ./outputs/checkpoint-500/special_tokens_map.json\n", + "{'loss': 0.0718, 'learning_rate': 4.039385206532181e-05, 'epoch': 0.96}\n", + " 19% 1000/5205 [05:53<27:38, 2.54it/s][INFO|trainer.py:1917] 2021-07-19 11:12:12,586 >> Saving model checkpoint to ./outputs/checkpoint-1000\n", + "[INFO|configuration_utils.py:379] 2021-07-19 11:12:12,588 >> Configuration saved in ./outputs/checkpoint-1000/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 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./outputs/checkpoint-4500/special_tokens_map.json\n", + " 96% 5000/5205 [29:39<01:20, 2.54it/s]{'loss': 0.0094, 'learning_rate': 1.96926032660903e-06, 'epoch': 4.8}\n", + "[INFO|trainer.py:1917] 2021-07-19 11:35:59,265 >> Saving model checkpoint to ./outputs/checkpoint-5000\n", + "[INFO|configuration_utils.py:379] 2021-07-19 11:35:59,266 >> Configuration saved in ./outputs/checkpoint-5000/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 11:36:00,820 >> Model weights saved in ./outputs/checkpoint-5000/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 11:36:00,821 >> tokenizer config file saved in ./outputs/checkpoint-5000/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 11:36:00,821 >> Special tokens file saved in ./outputs/checkpoint-5000/special_tokens_map.json\n", + "100% 5205/5205 [30:56<00:00, 3.25it/s][INFO|trainer.py:1358] 2021-07-19 11:37:15,632 >> \n", + "\n", + "Training completed. Do not forget to share your model on huggingface.co/models =)\n", + "\n", + "\n", + "100% 5205/5205 [30:56<00:00, 3.25it/s]{'train_runtime': 1859.0889, 'train_samples_per_second': 22.387, 'train_steps_per_second': 2.8, 'train_loss': 0.04189618094166692, 'epoch': 5.0}\n", + "100% 5205/5205 [30:56<00:00, 2.80it/s]\n", + "[INFO|trainer.py:1917] 2021-07-19 11:37:15,636 >> Saving model checkpoint to ./outputs\n", + "[INFO|configuration_utils.py:379] 2021-07-19 11:37:15,637 >> Configuration saved in ./outputs/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 11:37:17,201 >> Model weights saved in ./outputs/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 11:37:17,202 >> tokenizer config file saved in ./outputs/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 11:37:17,203 >> Special tokens file saved in ./outputs/special_tokens_map.json\n", + "***** train metrics *****\n", + " epoch = 5.0\n", + " train_loss = 0.0419\n", + " train_runtime = 0:30:59.08\n", + " train_samples = 8324\n", + " train_samples_per_second = 22.387\n", + " train_steps_per_second = 2.8\n", + "[INFO|trainer.py:522] 2021-07-19 11:37:17,352 >> The following columns in the evaluation set don't have a corresponding argument in `RobertaForTokenClassification.forward` and have been ignored: id, pos_tags, tokens, ner_tags.\n", + "07/19/2021 11:37:17 - INFO - __main__ - *** Evaluate ***\n", + "[INFO|trainer.py:2163] 2021-07-19 11:37:17,370 >> ***** Running Evaluation *****\n", + "[INFO|trainer.py:2165] 2021-07-19 11:37:17,370 >> Num examples = 1916\n", + "[INFO|trainer.py:2168] 2021-07-19 11:37:17,370 >> Batch size = 8\n", + "100% 240/240 [00:26<00:00, 8.97it/s]\n", + "***** eval metrics *****\n", + " epoch = 5.0\n", + " eval_accuracy = 0.9812\n", + " eval_f1 = 0.8725\n", + " eval_loss = 0.1023\n", + " eval_precision = 0.8638\n", + " eval_recall = 0.8814\n", + " eval_runtime = 0:00:26.87\n", + " eval_samples = 1916\n", + " eval_samples_per_second = 71.287\n", + " eval_steps_per_second = 8.929\n", + "\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Waiting for W&B process to finish, PID 605\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Program ended successfully.\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: \n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Find user logs for this run at: /content/wandb/run-20210719_110616-j1pmca9j/logs/debug.log\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Find internal logs for this run at: /content/wandb/run-20210719_110616-j1pmca9j/logs/debug-internal.log\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Run summary:\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/loss 0.0094\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/learning_rate 0.0\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/epoch 5.0\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/global_step 5205\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: _runtime 1888\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: _timestamp 1626694664\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: _step 11\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_runtime 1859.0889\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_samples_per_second 22.387\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_steps_per_second 2.8\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/total_flos 1.087585926764544e+16\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_loss 0.0419\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/loss 0.10234\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/precision 0.86377\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/recall 0.88143\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/f1 0.87251\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/accuracy 0.98122\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/runtime 26.8774\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/samples_per_second 71.287\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/steps_per_second 8.929\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Run history:\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/loss █▄▃▃▂▂▁▁▁▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/learning_rate █▇▆▆▅▄▃▃▂▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/epoch ▁▂▂▃▄▅▅▆▇███\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/global_step ▁▂▂▃▄▅▅▆▇███\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: _runtime ▁▂▂▃▄▅▅▆▇███\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: _timestamp ▁▂▂▃▄▅▅▆▇███\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: _step ▁▂▂▃▄▄▅▅▆▇▇█\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_runtime ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_samples_per_second ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_steps_per_second ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/total_flos ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_loss ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/loss ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/precision ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/recall ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/f1 ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/accuracy ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/runtime ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/samples_per_second ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/steps_per_second ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: \n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Synced 5 W&B file(s), 0 media file(s), 0 artifact file(s) and 1 other file(s)\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: \n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Synced \u001b[33m./outputs\u001b[0m: \u001b[34mhttps://wandb.ai/versae/bertin-eval/runs/j1pmca9j\u001b[0m\n", + "2021-07-19 11:37:56.763079: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Successfully opened dynamic library libcudart.so.11.0\n", + "07/19/2021 11:37:59 - WARNING - __main__ - Process rank: -1, device: cuda:0, n_gpu: 1distributed training: False, 16-bits training: False\n", + "07/19/2021 11:37:59 - INFO - __main__ - Training/evaluation parameters TrainingArguments(\n", + "_n_gpu=1,\n", + "adafactor=False,\n", + "adam_beta1=0.9,\n", + "adam_beta2=0.999,\n", + "adam_epsilon=1e-08,\n", + "dataloader_drop_last=False,\n", + "dataloader_num_workers=0,\n", + "dataloader_pin_memory=True,\n", + "ddp_find_unused_parameters=None,\n", + "debug=[],\n", + "deepspeed=None,\n", + "disable_tqdm=False,\n", + "do_eval=True,\n", + "do_predict=False,\n", + "do_train=True,\n", + "eval_accumulation_steps=None,\n", + "eval_steps=500,\n", + "evaluation_strategy=IntervalStrategy.NO,\n", + "fp16=False,\n", + "fp16_backend=auto,\n", + "fp16_full_eval=False,\n", + "fp16_opt_level=O1,\n", + "gradient_accumulation_steps=1,\n", + "greater_is_better=None,\n", + "group_by_length=False,\n", + "ignore_data_skip=False,\n", + "label_names=None,\n", + "label_smoothing_factor=0.0,\n", + "learning_rate=5e-05,\n", + "length_column_name=length,\n", + "load_best_model_at_end=False,\n", + "local_rank=-1,\n", + "log_level=-1,\n", + "log_level_replica=-1,\n", + "log_on_each_node=True,\n", + "logging_dir=./outputs/runs/Jul19_11-37-59_eab5184de9ff,\n", + "logging_first_step=False,\n", + "logging_steps=500,\n", + "logging_strategy=IntervalStrategy.STEPS,\n", + "lr_scheduler_type=SchedulerType.LINEAR,\n", + "max_grad_norm=1.0,\n", + "max_steps=-1,\n", + "metric_for_best_model=None,\n", + "mp_parameters=,\n", + "no_cuda=False,\n", + "num_train_epochs=5.0,\n", + "output_dir=./outputs,\n", + "overwrite_output_dir=True,\n", + "past_index=-1,\n", + "per_device_eval_batch_size=8,\n", + "per_device_train_batch_size=8,\n", + "prediction_loss_only=False,\n", + "push_to_hub=False,\n", + "push_to_hub_model_id=outputs,\n", + "push_to_hub_organization=None,\n", + "push_to_hub_token=None,\n", + "remove_unused_columns=True,\n", + "report_to=['tensorboard', 'wandb'],\n", + "resume_from_checkpoint=None,\n", + "run_name=./outputs,\n", + "save_on_each_node=False,\n", + "save_steps=500,\n", + "save_strategy=IntervalStrategy.STEPS,\n", + "save_total_limit=None,\n", + "seed=42,\n", + "sharded_ddp=[],\n", + "skip_memory_metrics=True,\n", + "tpu_metrics_debug=False,\n", + "tpu_num_cores=None,\n", + "use_legacy_prediction_loop=False,\n", + "warmup_ratio=0.0,\n", + "warmup_steps=0,\n", + "weight_decay=0.0,\n", + ")\n", + "07/19/2021 11:38:01 - INFO - datasets.load - Found main folder for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py at /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002\n", + "07/19/2021 11:38:01 - INFO - datasets.load - Found specific version folder for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py at /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5\n", + "07/19/2021 11:38:01 - INFO - datasets.load - Found script file from 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https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py at /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002\n", + "07/19/2021 11:38:02 - INFO - datasets.load - Found specific version folder for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py at /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5\n", + "07/19/2021 11:38:02 - INFO - datasets.load - Found script file from https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py to /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5/conll2002.py\n", + "07/19/2021 11:38:02 - INFO - datasets.load - Found dataset infos file from https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/dataset_infos.json to /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5/dataset_infos.json\n", + "07/19/2021 11:38:02 - INFO - datasets.load - Found metadata file for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py at /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5/conll2002.json\n", + "07/19/2021 11:38:02 - INFO - datasets.info - Loading Dataset Infos from /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5\n", + "07/19/2021 11:38:02 - INFO - datasets.builder - Overwrite dataset info from restored data version.\n", + "07/19/2021 11:38:02 - INFO - datasets.info - Loading Dataset info from /root/.cache/huggingface/datasets/conll2002/es/1.0.0/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5\n", + "07/19/2021 11:38:02 - WARNING - datasets.builder - Reusing dataset conll2002 (/root/.cache/huggingface/datasets/conll2002/es/1.0.0/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5)\n", + "07/19/2021 11:38:02 - INFO - datasets.info - Loading Dataset info from /root/.cache/huggingface/datasets/conll2002/es/1.0.0/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5\n", + "100% 3/3 [00:00<00:00, 27.85it/s]\n", + "[INFO|file_utils.py:1624] 2021-07-19 11:38:02,918 >> https://huggingface.co/flax-community/bertin-roberta-large-spanish/resolve/main/config.json not found in cache or force_download set to True, downloading to /root/.cache/huggingface/transformers/tmpyi0y3esx\n", + "Downloading: 100% 618/618 [00:00<00:00, 448kB/s]\n", + "[INFO|file_utils.py:1628] 2021-07-19 11:38:03,899 >> storing https://huggingface.co/flax-community/bertin-roberta-large-spanish/resolve/main/config.json in cache at /root/.cache/huggingface/transformers/d32cc9b6c8f303dbd398a937552d8d9c26d842d418f1cd79adb3fc25f169f722.08210214ecaf5cd53c702826a604e564d8af557125033eef720f4f9f2af1fc44\n", + "[INFO|file_utils.py:1636] 2021-07-19 11:38:03,899 >> creating metadata file for /root/.cache/huggingface/transformers/d32cc9b6c8f303dbd398a937552d8d9c26d842d418f1cd79adb3fc25f169f722.08210214ecaf5cd53c702826a604e564d8af557125033eef720f4f9f2af1fc44\n", + "[INFO|configuration_utils.py:545] 2021-07-19 11:38:03,900 >> loading configuration file https://huggingface.co/flax-community/bertin-roberta-large-spanish/resolve/main/config.json from cache at /root/.cache/huggingface/transformers/d32cc9b6c8f303dbd398a937552d8d9c26d842d418f1cd79adb3fc25f169f722.08210214ecaf5cd53c702826a604e564d8af557125033eef720f4f9f2af1fc44\n", + "[INFO|configuration_utils.py:581] 2021-07-19 11:38:03,900 >> Model config RobertaConfig {\n", + " \"architectures\": [\n", + " \"RobertaForMaskedLM\"\n", + " ],\n", + " \"attention_probs_dropout_prob\": 0.1,\n", + " \"bos_token_id\": 0,\n", + " \"eos_token_id\": 2,\n", + " \"finetuning_task\": \"ner\",\n", + " \"gradient_checkpointing\": false,\n", + " \"hidden_act\": \"gelu\",\n", + " \"hidden_dropout_prob\": 0.1,\n", + " \"hidden_size\": 768,\n", + " \"id2label\": {\n", + " \"0\": 0,\n", + " \"1\": 1,\n", + " \"2\": 2,\n", + " \"3\": 3,\n", + " \"4\": 4,\n", + " \"5\": 5,\n", + " \"6\": 6,\n", + " \"7\": 7,\n", + " \"8\": 8\n", + " },\n", + " \"initializer_range\": 0.02,\n", + " \"intermediate_size\": 3072,\n", + " \"label2id\": {\n", + " \"0\": 0,\n", + " \"1\": 1,\n", + " \"2\": 2,\n", + " \"3\": 3,\n", + " \"4\": 4,\n", + " \"5\": 5,\n", + " \"6\": 6,\n", + " \"7\": 7,\n", + " \"8\": 8\n", + " },\n", + " \"layer_norm_eps\": 1e-05,\n", + " \"max_position_embeddings\": 514,\n", + " \"model_type\": \"roberta\",\n", + " \"num_attention_heads\": 12,\n", + " \"num_hidden_layers\": 12,\n", + " \"pad_token_id\": 1,\n", + " \"position_embedding_type\": \"absolute\",\n", + " \"transformers_version\": \"4.9.0.dev0\",\n", + " \"type_vocab_size\": 1,\n", + " \"use_cache\": true,\n", + " \"vocab_size\": 50265\n", + "}\n", + "\n", + "[INFO|file_utils.py:1624] 2021-07-19 11:38:04,619 >> https://huggingface.co/flax-community/bertin-roberta-large-spanish/resolve/main/tokenizer_config.json not found in cache or force_download set to True, downloading to /root/.cache/huggingface/transformers/tmpu8t1or1_\n", + "Downloading: 100% 292/292 [00:00<00:00, 211kB/s]\n", + "[INFO|file_utils.py:1628] 2021-07-19 11:38:05,341 >> storing https://huggingface.co/flax-community/bertin-roberta-large-spanish/resolve/main/tokenizer_config.json in cache at /root/.cache/huggingface/transformers/4f604c1e66964e3a55ecf1d4959f4ebb3416a50476c866ac53fedd6a93b68c2b.9f7ac4246b492dfa7c21beb5233deec8aef46153ec25ac5258ac5e2ae82dfa89\n", + "[INFO|file_utils.py:1636] 2021-07-19 11:38:05,341 >> creating metadata file for 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2021-07-19 11:39:04,638 >> creating metadata file for /root/.cache/huggingface/transformers/7189e822ad05437642e8c70b270aad1da7745b3f42ae88ee851bd7336559387c.8970e1b3c4890a283e6d9c30f1437e32aec6a36c0f9aae84920ff5a363d4b636\n", + "[INFO|modeling_utils.py:1271] 2021-07-19 11:39:04,639 >> loading weights file https://huggingface.co/flax-community/bertin-roberta-large-spanish/resolve/main/pytorch_model.bin from cache at /root/.cache/huggingface/transformers/7189e822ad05437642e8c70b270aad1da7745b3f42ae88ee851bd7336559387c.8970e1b3c4890a283e6d9c30f1437e32aec6a36c0f9aae84920ff5a363d4b636\n", + "[WARNING|modeling_utils.py:1502] 2021-07-19 11:39:06,140 >> Some weights of the model checkpoint at flax-community/bertin-roberta-large-spanish were not used when initializing RobertaForTokenClassification: ['lm_head.layer_norm.weight', 'lm_head.bias', 'lm_head.dense.weight', 'lm_head.layer_norm.bias', 'lm_head.dense.bias']\n", + "- This IS expected if you are initializing RobertaForTokenClassification from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).\n", + "- This IS NOT expected if you are initializing RobertaForTokenClassification from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).\n", + "[WARNING|modeling_utils.py:1513] 2021-07-19 11:39:06,140 >> Some weights of RobertaForTokenClassification were not initialized from the model checkpoint at flax-community/bertin-roberta-large-spanish and are newly initialized: ['classifier.bias', 'classifier.weight']\n", + "You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.\n", + "Running tokenizer on train dataset: 0% 0/9 [00:00> The following columns in the training set don't have a corresponding argument in `RobertaForTokenClassification.forward` and have been ignored: id, tokens, ner_tags, pos_tags.\n", + "[INFO|trainer.py:1162] 2021-07-19 11:39:17,438 >> ***** Running training *****\n", + "[INFO|trainer.py:1163] 2021-07-19 11:39:17,438 >> Num examples = 8324\n", + "[INFO|trainer.py:1164] 2021-07-19 11:39:17,438 >> Num Epochs = 5\n", + "[INFO|trainer.py:1165] 2021-07-19 11:39:17,438 >> Instantaneous batch size per device = 8\n", + "[INFO|trainer.py:1166] 2021-07-19 11:39:17,438 >> Total train batch size (w. parallel, distributed & accumulation) = 8\n", + "[INFO|trainer.py:1167] 2021-07-19 11:39:17,438 >> Gradient Accumulation steps = 1\n", + "[INFO|trainer.py:1168] 2021-07-19 11:39:17,438 >> Total optimization steps = 5205\n", + "[INFO|integrations.py:417] 2021-07-19 11:39:17,456 >> Automatic Weights & Biases logging enabled, to disable set os.environ[\"WANDB_DISABLED\"] = \"true\"\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Currently logged in as: \u001b[33mversae\u001b[0m (use `wandb login --relogin` to force relogin)\n", + "2021-07-19 11:39:19.075107: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Successfully opened dynamic library libcudart.so.11.0\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Tracking run with wandb version 0.11.0\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Syncing run \u001b[33m./outputs\u001b[0m\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: ⭐️ View project at \u001b[34m\u001b[4mhttps://wandb.ai/versae/bertin-eval\u001b[0m\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: 🚀 View run at \u001b[34m\u001b[4mhttps://wandb.ai/versae/bertin-eval/runs/fh1ara05\u001b[0m\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Run data is saved locally in /content/wandb/run-20210719_113917-fh1ara05\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Run `wandb offline` to turn off syncing.\n", + "\n", + "{'loss': 0.1506, 'learning_rate': 4.5196926032660905e-05, 'epoch': 0.48}\n", + " 10% 500/5205 [02:53<30:56, 2.53it/s][INFO|trainer.py:1917] 2021-07-19 11:42:14,041 >> Saving model checkpoint to 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>> Model weights saved in ./outputs/checkpoint-1000/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 11:45:14,727 >> tokenizer config file saved in ./outputs/checkpoint-1000/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 11:45:14,727 >> Special tokens file saved in ./outputs/checkpoint-1000/special_tokens_map.json\n", + " 29% 1500/5205 [08:51<24:13, 2.55it/s]{'loss': 0.0456, 'learning_rate': 3.5590778097982716e-05, 'epoch': 1.44}\n", + " 29% 1500/5205 [08:51<24:13, 2.55it/s][INFO|trainer.py:1917] 2021-07-19 11:48:11,899 >> Saving model checkpoint to ./outputs/checkpoint-1500\n", + "[INFO|configuration_utils.py:379] 2021-07-19 11:48:11,900 >> Configuration saved in ./outputs/checkpoint-1500/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 11:48:13,401 >> Model weights saved in ./outputs/checkpoint-1500/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 11:48:13,402 >> tokenizer config file saved 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"{'loss': 0.0298, 'learning_rate': 2.5984630163304517e-05, 'epoch': 2.4}\n", + " 48% 2500/5205 [14:48<17:42, 2.55it/s][INFO|trainer.py:1917] 2021-07-19 11:54:09,015 >> Saving model checkpoint to ./outputs/checkpoint-2500\n", + "[INFO|configuration_utils.py:379] 2021-07-19 11:54:09,017 >> Configuration saved in ./outputs/checkpoint-2500/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 11:54:10,503 >> Model weights saved in ./outputs/checkpoint-2500/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 11:54:10,504 >> tokenizer config file saved in ./outputs/checkpoint-2500/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 11:54:10,561 >> Special tokens file saved in ./outputs/checkpoint-2500/special_tokens_map.json\n", + "{'loss': 0.0241, 'learning_rate': 2.118155619596542e-05, 'epoch': 2.88}\n", + " 58% 3000/5205 [17:46<14:20, 2.56it/s][INFO|trainer.py:1917] 2021-07-19 11:57:07,048 >> Saving model checkpoint to 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"[INFO|modeling_utils.py:997] 2021-07-19 12:00:06,301 >> Model weights saved in ./outputs/checkpoint-3500/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 12:00:06,302 >> tokenizer config file saved in ./outputs/checkpoint-3500/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 12:00:06,303 >> Special tokens file saved in ./outputs/checkpoint-3500/special_tokens_map.json\n", + " 77% 4000/5205 [23:42<07:52, 2.55it/s]{'loss': 0.0145, 'learning_rate': 1.1575408261287224e-05, 'epoch': 3.84}\n", + "[INFO|trainer.py:1917] 2021-07-19 12:03:02,699 >> Saving model checkpoint to ./outputs/checkpoint-4000\n", + "[INFO|configuration_utils.py:379] 2021-07-19 12:03:02,700 >> Configuration saved in ./outputs/checkpoint-4000/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 12:03:04,160 >> Model weights saved in ./outputs/checkpoint-4000/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 12:03:04,229 >> tokenizer config file saved in ./outputs/checkpoint-4000/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 12:03:04,229 >> Special tokens file saved in ./outputs/checkpoint-4000/special_tokens_map.json\n", + " 86% 4500/5205 [26:39<04:35, 2.56it/s]{'loss': 0.0116, 'learning_rate': 6.7723342939481265e-06, 'epoch': 4.32}\n", + "[INFO|trainer.py:1917] 2021-07-19 12:05:59,683 >> Saving model checkpoint to ./outputs/checkpoint-4500\n", + "[INFO|configuration_utils.py:379] 2021-07-19 12:05:59,684 >> Configuration saved in ./outputs/checkpoint-4500/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 12:06:01,360 >> Model weights saved in ./outputs/checkpoint-4500/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 12:06:01,361 >> tokenizer config file saved in ./outputs/checkpoint-4500/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 12:06:01,361 >> Special tokens file saved in ./outputs/checkpoint-4500/special_tokens_map.json\n", + "{'loss': 0.0093, 'learning_rate': 1.96926032660903e-06, 'epoch': 4.8}\n", + " 96% 5000/5205 [29:37<01:19, 2.57it/s][INFO|trainer.py:1917] 2021-07-19 12:08:57,911 >> Saving model checkpoint to ./outputs/checkpoint-5000\n", + "[INFO|configuration_utils.py:379] 2021-07-19 12:08:57,913 >> Configuration saved in ./outputs/checkpoint-5000/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 12:08:59,474 >> Model weights saved in ./outputs/checkpoint-5000/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 12:08:59,475 >> tokenizer config file saved in ./outputs/checkpoint-5000/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 12:08:59,475 >> Special tokens file saved in ./outputs/checkpoint-5000/special_tokens_map.json\n", + "100% 5205/5205 [30:53<00:00, 3.24it/s][INFO|trainer.py:1358] 2021-07-19 12:10:14,210 >> \n", + "\n", + "Training completed. Do not forget to share your model on huggingface.co/models =)\n", + "\n", + "\n", + "{'train_runtime': 1856.7718, 'train_samples_per_second': 22.415, 'train_steps_per_second': 2.803, 'train_loss': 0.040356940655154064, 'epoch': 5.0}\n", + "100% 5205/5205 [30:53<00:00, 2.81it/s]\n", + "[INFO|trainer.py:1917] 2021-07-19 12:10:14,229 >> Saving model checkpoint to ./outputs\n", + "[INFO|configuration_utils.py:379] 2021-07-19 12:10:14,230 >> Configuration saved in ./outputs/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 12:10:15,786 >> Model weights saved in ./outputs/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 12:10:15,787 >> tokenizer config file saved in ./outputs/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 12:10:15,787 >> Special tokens file saved in ./outputs/special_tokens_map.json\n", + "***** train metrics *****\n", + " epoch = 5.0\n", + " train_loss = 0.0404\n", + " train_runtime = 0:30:56.77\n", + " train_samples = 8324\n", + " train_samples_per_second = 22.415\n", + " train_steps_per_second = 2.803\n", + "07/19/2021 12:10:15 - INFO - __main__ - *** Evaluate ***\n", + "[INFO|trainer.py:522] 2021-07-19 12:10:15,969 >> The following columns in the evaluation set don't have a corresponding argument in `RobertaForTokenClassification.forward` and have been ignored: id, tokens, ner_tags, pos_tags.\n", + "[INFO|trainer.py:2163] 2021-07-19 12:10:15,988 >> ***** Running Evaluation *****\n", + "[INFO|trainer.py:2165] 2021-07-19 12:10:15,988 >> Num examples = 1916\n", + "[INFO|trainer.py:2168] 2021-07-19 12:10:15,988 >> Batch size = 8\n", + "100% 240/240 [00:26<00:00, 9.01it/s]\n", + "***** eval metrics *****\n", + " epoch = 5.0\n", + " eval_accuracy = 0.9806\n", + " eval_f1 = 0.8735\n", + " eval_loss = 0.1056\n", + " eval_precision = 0.8667\n", + " eval_recall = 0.8803\n", + " eval_runtime = 0:00:26.74\n", + " eval_samples = 1916\n", + " eval_samples_per_second = 71.635\n", + " eval_steps_per_second = 8.973\n", + "\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Waiting for W&B process to finish, PID 676\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Program ended successfully.\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: \n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Find user logs for this run at: /content/wandb/run-20210719_113917-fh1ara05/logs/debug.log\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Find internal logs for this run at: /content/wandb/run-20210719_113917-fh1ara05/logs/debug-internal.log\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Run summary:\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/loss 0.0093\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/learning_rate 0.0\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/epoch 5.0\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/global_step 5205\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: _runtime 1885\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: _timestamp 1626696642\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: _step 11\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_runtime 1856.7718\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_samples_per_second 22.415\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_steps_per_second 2.803\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/total_flos 1.087585926764544e+16\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_loss 0.04036\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/loss 0.10558\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/precision 0.86674\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/recall 0.88028\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/f1 0.87346\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/accuracy 0.98063\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/runtime 26.7467\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/samples_per_second 71.635\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/steps_per_second 8.973\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Run history:\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/loss 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"\u001b[34m\u001b[1mwandb\u001b[0m: eval/accuracy ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/runtime ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/samples_per_second ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/steps_per_second ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: \n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Synced 5 W&B file(s), 0 media file(s), 0 artifact file(s) and 1 other file(s)\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: \n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Synced \u001b[33m./outputs\u001b[0m: \u001b[34mhttps://wandb.ai/versae/bertin-eval/runs/fh1ara05\u001b[0m\n", + "2021-07-19 12:10:55.954685: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Successfully opened dynamic library libcudart.so.11.0\n", + "07/19/2021 12:10:58 - WARNING - __main__ - Process rank: -1, device: cuda:0, n_gpu: 1distributed training: False, 16-bits training: False\n", + "07/19/2021 12:10:58 - INFO - __main__ - Training/evaluation parameters TrainingArguments(\n", + "_n_gpu=1,\n", + "adafactor=False,\n", + "adam_beta1=0.9,\n", + "adam_beta2=0.999,\n", + "adam_epsilon=1e-08,\n", + "dataloader_drop_last=False,\n", + "dataloader_num_workers=0,\n", + "dataloader_pin_memory=True,\n", + "ddp_find_unused_parameters=None,\n", + "debug=[],\n", + "deepspeed=None,\n", + "disable_tqdm=False,\n", + "do_eval=True,\n", + "do_predict=False,\n", + "do_train=True,\n", + "eval_accumulation_steps=None,\n", + "eval_steps=500,\n", + "evaluation_strategy=IntervalStrategy.NO,\n", + "fp16=False,\n", + "fp16_backend=auto,\n", + "fp16_full_eval=False,\n", + "fp16_opt_level=O1,\n", + "gradient_accumulation_steps=1,\n", + "greater_is_better=None,\n", + "group_by_length=False,\n", + "ignore_data_skip=False,\n", + "label_names=None,\n", + "label_smoothing_factor=0.0,\n", + "learning_rate=5e-05,\n", + "length_column_name=length,\n", + "load_best_model_at_end=False,\n", + "local_rank=-1,\n", + "log_level=-1,\n", + "log_level_replica=-1,\n", + "log_on_each_node=True,\n", + "logging_dir=./outputs/runs/Jul19_12-10-58_eab5184de9ff,\n", + "logging_first_step=False,\n", + "logging_steps=500,\n", + "logging_strategy=IntervalStrategy.STEPS,\n", + "lr_scheduler_type=SchedulerType.LINEAR,\n", + "max_grad_norm=1.0,\n", + "max_steps=-1,\n", + "metric_for_best_model=None,\n", + "mp_parameters=,\n", + "no_cuda=False,\n", + "num_train_epochs=5.0,\n", + "output_dir=./outputs,\n", + "overwrite_output_dir=True,\n", + "past_index=-1,\n", + "per_device_eval_batch_size=8,\n", + "per_device_train_batch_size=8,\n", + "prediction_loss_only=False,\n", + "push_to_hub=False,\n", + "push_to_hub_model_id=outputs,\n", + "push_to_hub_organization=None,\n", + "push_to_hub_token=None,\n", + "remove_unused_columns=True,\n", + "report_to=['tensorboard', 'wandb'],\n", + "resume_from_checkpoint=None,\n", + "run_name=./outputs,\n", + "save_on_each_node=False,\n", + "save_steps=500,\n", + "save_strategy=IntervalStrategy.STEPS,\n", + "save_total_limit=None,\n", + "seed=42,\n", + "sharded_ddp=[],\n", + "skip_memory_metrics=True,\n", + "tpu_metrics_debug=False,\n", + "tpu_num_cores=None,\n", + "use_legacy_prediction_loop=False,\n", + "warmup_ratio=0.0,\n", + "warmup_steps=0,\n", + "weight_decay=0.0,\n", + ")\n", + "07/19/2021 12:11:00 - INFO - datasets.load - Found main folder for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py at /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002\n", + "07/19/2021 12:11:00 - INFO - datasets.load - Found specific version folder for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py at /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5\n", + "07/19/2021 12:11:00 - INFO - datasets.load - Found script file from https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py to /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5/conll2002.py\n", + "07/19/2021 12:11:00 - INFO - datasets.load - Found dataset infos file from https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/dataset_infos.json to /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5/dataset_infos.json\n", + "07/19/2021 12:11:00 - INFO - datasets.load - Found metadata file for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py at /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5/conll2002.json\n", + "07/19/2021 12:11:01 - INFO - datasets.load - Found main folder for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py at /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002\n", + "07/19/2021 12:11:01 - INFO - datasets.load - Found specific version folder for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py at /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5\n", + "07/19/2021 12:11:01 - INFO - datasets.load - Found script file from https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py to /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5/conll2002.py\n", + "07/19/2021 12:11:01 - INFO - datasets.load - Found dataset infos file from https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/dataset_infos.json to /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5/dataset_infos.json\n", + "07/19/2021 12:11:01 - INFO - datasets.load - Found metadata file for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py at /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5/conll2002.json\n", + "07/19/2021 12:11:01 - INFO - datasets.info - Loading Dataset Infos from /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5\n", + "07/19/2021 12:11:01 - INFO - datasets.builder - Overwrite dataset info from restored data version.\n", + "07/19/2021 12:11:01 - INFO - datasets.info - Loading Dataset info from /root/.cache/huggingface/datasets/conll2002/es/1.0.0/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5\n", + "07/19/2021 12:11:01 - WARNING - datasets.builder - Reusing dataset conll2002 (/root/.cache/huggingface/datasets/conll2002/es/1.0.0/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5)\n", + "07/19/2021 12:11:01 - INFO - datasets.info - Loading Dataset info from /root/.cache/huggingface/datasets/conll2002/es/1.0.0/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5\n", + "100% 3/3 [00:00<00:00, 25.94it/s]\n", + "[INFO|file_utils.py:1624] 2021-07-19 12:11:01,984 >> https://huggingface.co/BSC-TeMU/roberta-base-bne/resolve/main/config.json not found in cache or force_download set to True, downloading to /root/.cache/huggingface/transformers/tmp2k5xww1q\n", + "Downloading: 100% 613/613 [00:00<00:00, 467kB/s]\n", + "[INFO|file_utils.py:1628] 2021-07-19 12:11:03,238 >> storing https://huggingface.co/BSC-TeMU/roberta-base-bne/resolve/main/config.json in cache at /root/.cache/huggingface/transformers/3b60ce79e9e99338ab683eee75e146acc49852f2f34f2c5610dfd78221a176ee.33b0b03a5bf5e640494a22a3aa4909c661effc0fa0e186b1513b17d9b058ca59\n", + "[INFO|file_utils.py:1636] 2021-07-19 12:11:03,238 >> creating metadata file for /root/.cache/huggingface/transformers/3b60ce79e9e99338ab683eee75e146acc49852f2f34f2c5610dfd78221a176ee.33b0b03a5bf5e640494a22a3aa4909c661effc0fa0e186b1513b17d9b058ca59\n", + "[INFO|configuration_utils.py:545] 2021-07-19 12:11:03,239 >> loading configuration file https://huggingface.co/BSC-TeMU/roberta-base-bne/resolve/main/config.json from cache at /root/.cache/huggingface/transformers/3b60ce79e9e99338ab683eee75e146acc49852f2f34f2c5610dfd78221a176ee.33b0b03a5bf5e640494a22a3aa4909c661effc0fa0e186b1513b17d9b058ca59\n", + "[INFO|configuration_utils.py:581] 2021-07-19 12:11:03,239 >> Model config RobertaConfig {\n", + " \"architectures\": [\n", + " \"RobertaForMaskedLM\"\n", + " ],\n", + " \"attention_probs_dropout_prob\": 0.0,\n", + " \"bos_token_id\": 0,\n", + " \"eos_token_id\": 2,\n", + " \"finetuning_task\": \"ner\",\n", + " \"gradient_checkpointing\": false,\n", + " \"hidden_act\": \"gelu\",\n", + " \"hidden_dropout_prob\": 0.0,\n", + " \"hidden_size\": 768,\n", + " \"id2label\": {\n", + " \"0\": 0,\n", + " \"1\": 1,\n", + " \"2\": 2,\n", + " \"3\": 3,\n", + " \"4\": 4,\n", + " \"5\": 5,\n", + " \"6\": 6,\n", + " \"7\": 7,\n", + " \"8\": 8\n", + " },\n", + " \"initializer_range\": 0.02,\n", + " \"intermediate_size\": 3072,\n", + " \"label2id\": {\n", + " \"0\": 0,\n", + " \"1\": 1,\n", + " \"2\": 2,\n", + " \"3\": 3,\n", + " \"4\": 4,\n", + " \"5\": 5,\n", + " \"6\": 6,\n", + " \"7\": 7,\n", + " \"8\": 8\n", + " },\n", + " \"layer_norm_eps\": 1e-05,\n", + " \"max_position_embeddings\": 514,\n", + " \"model_type\": \"roberta\",\n", + " \"num_attention_heads\": 12,\n", + " \"num_hidden_layers\": 12,\n", + " \"pad_token_id\": 1,\n", + " \"position_embedding_type\": \"absolute\",\n", + " \"transformers_version\": \"4.9.0.dev0\",\n", + " \"type_vocab_size\": 1,\n", + " \"use_cache\": true,\n", + " \"vocab_size\": 50262\n", + "}\n", + "\n", + "[INFO|file_utils.py:1624] 2021-07-19 12:11:03,966 >> https://huggingface.co/BSC-TeMU/roberta-base-bne/resolve/main/tokenizer_config.json not found in cache or force_download set to True, downloading to /root/.cache/huggingface/transformers/tmpl2t8n1yp\n", + "Downloading: 100% 1.46k/1.46k [00:00<00:00, 1.03MB/s]\n", + "[INFO|file_utils.py:1628] 2021-07-19 12:11:04,686 >> storing https://huggingface.co/BSC-TeMU/roberta-base-bne/resolve/main/tokenizer_config.json in cache at /root/.cache/huggingface/transformers/e025b5b045564995a040386d80efa4d55779730827b72b4e40908073db9f0630.d8a7d006294d83173a76ac51a95b5a8470bbbc87c93c63633eaf9476656ed660\n", + "[INFO|file_utils.py:1636] 2021-07-19 12:11:04,686 >> creating metadata file for /root/.cache/huggingface/transformers/e025b5b045564995a040386d80efa4d55779730827b72b4e40908073db9f0630.d8a7d006294d83173a76ac51a95b5a8470bbbc87c93c63633eaf9476656ed660\n", + "[INFO|configuration_utils.py:545] 2021-07-19 12:11:05,404 >> loading configuration file https://huggingface.co/BSC-TeMU/roberta-base-bne/resolve/main/config.json from cache at /root/.cache/huggingface/transformers/3b60ce79e9e99338ab683eee75e146acc49852f2f34f2c5610dfd78221a176ee.33b0b03a5bf5e640494a22a3aa4909c661effc0fa0e186b1513b17d9b058ca59\n", + "[INFO|configuration_utils.py:581] 2021-07-19 12:11:05,405 >> Model config RobertaConfig {\n", + " \"architectures\": [\n", + " \"RobertaForMaskedLM\"\n", + " ],\n", + " \"attention_probs_dropout_prob\": 0.0,\n", + " \"bos_token_id\": 0,\n", + " \"eos_token_id\": 2,\n", + " \"gradient_checkpointing\": false,\n", + " \"hidden_act\": \"gelu\",\n", + " \"hidden_dropout_prob\": 0.0,\n", + " \"hidden_size\": 768,\n", + " \"initializer_range\": 0.02,\n", + " \"intermediate_size\": 3072,\n", + " \"layer_norm_eps\": 1e-05,\n", + " \"max_position_embeddings\": 514,\n", + " \"model_type\": \"roberta\",\n", + " \"num_attention_heads\": 12,\n", + " \"num_hidden_layers\": 12,\n", + " \"pad_token_id\": 1,\n", + " \"position_embedding_type\": \"absolute\",\n", + " \"transformers_version\": \"4.9.0.dev0\",\n", + " \"type_vocab_size\": 1,\n", + " \"use_cache\": true,\n", + " \"vocab_size\": 50262\n", + "}\n", + "\n", + "[INFO|file_utils.py:1624] 2021-07-19 12:11:06,134 >> https://huggingface.co/BSC-TeMU/roberta-base-bne/resolve/main/vocab.json not found in cache or force_download set to True, downloading to /root/.cache/huggingface/transformers/tmph8j_y_v6\n", + "Downloading: 100% 1.15M/1.15M [00:01<00:00, 1.11MB/s]\n", + "[INFO|file_utils.py:1628] 2021-07-19 12:11:07,912 >> storing https://huggingface.co/BSC-TeMU/roberta-base-bne/resolve/main/vocab.json in cache at /root/.cache/huggingface/transformers/aec224417e3c4a4bda2283292ca7898205329eeb16f3b8db7ea5a36e51d55257.26eadee3bbe78c0682ce89a698fbb1698a0eee50c36cf83be2280a0f2a7b23c1\n", + "[INFO|file_utils.py:1636] 2021-07-19 12:11:07,912 >> creating metadata file for /root/.cache/huggingface/transformers/aec224417e3c4a4bda2283292ca7898205329eeb16f3b8db7ea5a36e51d55257.26eadee3bbe78c0682ce89a698fbb1698a0eee50c36cf83be2280a0f2a7b23c1\n", + "[INFO|file_utils.py:1624] 2021-07-19 12:11:08,644 >> https://huggingface.co/BSC-TeMU/roberta-base-bne/resolve/main/merges.txt not found in cache or force_download set to True, downloading to /root/.cache/huggingface/transformers/tmp75jqk_c3\n", + "Downloading: 100% 509k/509k [00:00<00:00, 1.31MB/s]\n", + "[INFO|file_utils.py:1628] 2021-07-19 12:11:09,753 >> storing https://huggingface.co/BSC-TeMU/roberta-base-bne/resolve/main/merges.txt in cache at 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/root/.cache/huggingface/transformers/2f6b692045224588b9a5a4d5639db72d5e3fd2c18cbd0accf4c6dc81a4adc413.bd775ba884c9e650b58a3a333a97e47c8d1b9d37cdbe19b22fb04b1e41beb19d\n", + "[INFO|file_utils.py:1636] 2021-07-19 12:11:12,187 >> creating metadata file for /root/.cache/huggingface/transformers/2f6b692045224588b9a5a4d5639db72d5e3fd2c18cbd0accf4c6dc81a4adc413.bd775ba884c9e650b58a3a333a97e47c8d1b9d37cdbe19b22fb04b1e41beb19d\n", + "[INFO|file_utils.py:1624] 2021-07-19 12:11:13,623 >> https://huggingface.co/BSC-TeMU/roberta-base-bne/resolve/main/special_tokens_map.json not found in cache or force_download set to True, downloading to /root/.cache/huggingface/transformers/tmpxa1ze4ou\n", + "Downloading: 100% 772/772 [00:00<00:00, 572kB/s]\n", + "[INFO|file_utils.py:1628] 2021-07-19 12:11:14,343 >> storing https://huggingface.co/BSC-TeMU/roberta-base-bne/resolve/main/special_tokens_map.json in cache at /root/.cache/huggingface/transformers/0f2dbdd0b96b43180e16d660cb1b274e46fa0cf63da426f09c1c82900fb52da1.cb2244924ab24d706b02fd7fcedaea4531566537687a539ebb94db511fd122a0\n", + "[INFO|file_utils.py:1636] 2021-07-19 12:11:14,343 >> creating metadata file for /root/.cache/huggingface/transformers/0f2dbdd0b96b43180e16d660cb1b274e46fa0cf63da426f09c1c82900fb52da1.cb2244924ab24d706b02fd7fcedaea4531566537687a539ebb94db511fd122a0\n", + "[INFO|tokenization_utils_base.py:1722] 2021-07-19 12:11:15,065 >> loading file https://huggingface.co/BSC-TeMU/roberta-base-bne/resolve/main/vocab.json from cache at /root/.cache/huggingface/transformers/aec224417e3c4a4bda2283292ca7898205329eeb16f3b8db7ea5a36e51d55257.26eadee3bbe78c0682ce89a698fbb1698a0eee50c36cf83be2280a0f2a7b23c1\n", + "[INFO|tokenization_utils_base.py:1722] 2021-07-19 12:11:15,065 >> loading file https://huggingface.co/BSC-TeMU/roberta-base-bne/resolve/main/merges.txt from cache at /root/.cache/huggingface/transformers/6688b2cc67bbc01f3e369230731a072338dc286bf25b97e1513d359ab00f2ea3.0d24ae8bd5fabb1f5020f91bc602cefeb5a2938ab77e21769d28776345634b23\n", + "[INFO|tokenization_utils_base.py:1722] 2021-07-19 12:11:15,065 >> loading file https://huggingface.co/BSC-TeMU/roberta-base-bne/resolve/main/tokenizer.json from cache at /root/.cache/huggingface/transformers/2f6b692045224588b9a5a4d5639db72d5e3fd2c18cbd0accf4c6dc81a4adc413.bd775ba884c9e650b58a3a333a97e47c8d1b9d37cdbe19b22fb04b1e41beb19d\n", + "[INFO|tokenization_utils_base.py:1722] 2021-07-19 12:11:15,065 >> loading file https://huggingface.co/BSC-TeMU/roberta-base-bne/resolve/main/added_tokens.json from cache at None\n", + "[INFO|tokenization_utils_base.py:1722] 2021-07-19 12:11:15,065 >> loading file https://huggingface.co/BSC-TeMU/roberta-base-bne/resolve/main/special_tokens_map.json from cache at /root/.cache/huggingface/transformers/0f2dbdd0b96b43180e16d660cb1b274e46fa0cf63da426f09c1c82900fb52da1.cb2244924ab24d706b02fd7fcedaea4531566537687a539ebb94db511fd122a0\n", + "[INFO|tokenization_utils_base.py:1722] 2021-07-19 12:11:15,065 >> loading file https://huggingface.co/BSC-TeMU/roberta-base-bne/resolve/main/tokenizer_config.json from cache at /root/.cache/huggingface/transformers/e025b5b045564995a040386d80efa4d55779730827b72b4e40908073db9f0630.d8a7d006294d83173a76ac51a95b5a8470bbbc87c93c63633eaf9476656ed660\n", + "[INFO|configuration_utils.py:545] 2021-07-19 12:11:15,783 >> loading configuration file https://huggingface.co/BSC-TeMU/roberta-base-bne/resolve/main/config.json from cache at /root/.cache/huggingface/transformers/3b60ce79e9e99338ab683eee75e146acc49852f2f34f2c5610dfd78221a176ee.33b0b03a5bf5e640494a22a3aa4909c661effc0fa0e186b1513b17d9b058ca59\n", + "[INFO|configuration_utils.py:581] 2021-07-19 12:11:15,783 >> Model config RobertaConfig {\n", + " \"architectures\": [\n", + " \"RobertaForMaskedLM\"\n", + " ],\n", + " \"attention_probs_dropout_prob\": 0.0,\n", + " \"bos_token_id\": 0,\n", + " \"eos_token_id\": 2,\n", + " \"gradient_checkpointing\": false,\n", + " \"hidden_act\": \"gelu\",\n", + " \"hidden_dropout_prob\": 0.0,\n", + " \"hidden_size\": 768,\n", + " \"initializer_range\": 0.02,\n", + " \"intermediate_size\": 3072,\n", + " \"layer_norm_eps\": 1e-05,\n", + " \"max_position_embeddings\": 514,\n", + " \"model_type\": \"roberta\",\n", + " \"num_attention_heads\": 12,\n", + " \"num_hidden_layers\": 12,\n", + " \"pad_token_id\": 1,\n", + " \"position_embedding_type\": \"absolute\",\n", + " \"transformers_version\": \"4.9.0.dev0\",\n", + " \"type_vocab_size\": 1,\n", + " \"use_cache\": true,\n", + " \"vocab_size\": 50262\n", + "}\n", + "\n", + "[INFO|file_utils.py:1624] 2021-07-19 12:11:16,577 >> https://huggingface.co/BSC-TeMU/roberta-base-bne/resolve/main/pytorch_model.bin not found in cache or force_download set to True, downloading to /root/.cache/huggingface/transformers/tmp7palrwn_\n", + "Downloading: 100% 499M/499M [00:10<00:00, 47.6MB/s]\n", + "[INFO|file_utils.py:1628] 2021-07-19 12:11:28,168 >> storing https://huggingface.co/BSC-TeMU/roberta-base-bne/resolve/main/pytorch_model.bin in cache at /root/.cache/huggingface/transformers/a337644e63cac89729bd4fd067c987d2eb61b4b398d17d0ce0973c31dd76d2b0.c86d60e89da68465cb73e129befe8209faa3ac57b9aa272b87db45ba1f619582\n", + "[INFO|file_utils.py:1636] 2021-07-19 12:11:28,168 >> creating metadata file for /root/.cache/huggingface/transformers/a337644e63cac89729bd4fd067c987d2eb61b4b398d17d0ce0973c31dd76d2b0.c86d60e89da68465cb73e129befe8209faa3ac57b9aa272b87db45ba1f619582\n", + "[INFO|modeling_utils.py:1271] 2021-07-19 12:11:28,168 >> loading weights file https://huggingface.co/BSC-TeMU/roberta-base-bne/resolve/main/pytorch_model.bin from cache at /root/.cache/huggingface/transformers/a337644e63cac89729bd4fd067c987d2eb61b4b398d17d0ce0973c31dd76d2b0.c86d60e89da68465cb73e129befe8209faa3ac57b9aa272b87db45ba1f619582\n", + "[WARNING|modeling_utils.py:1502] 2021-07-19 12:11:29,685 >> Some weights of the model checkpoint at BSC-TeMU/roberta-base-bne were not used when initializing RobertaForTokenClassification: ['lm_head.bias', 'lm_head.decoder.bias', 'lm_head.dense.bias', 'lm_head.layer_norm.bias', 'lm_head.layer_norm.weight', 'lm_head.dense.weight', 'lm_head.decoder.weight']\n", + "- This IS expected if you are initializing RobertaForTokenClassification from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).\n", + "- This IS NOT expected if you are initializing RobertaForTokenClassification from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).\n", + "[WARNING|modeling_utils.py:1513] 2021-07-19 12:11:29,685 >> Some weights of RobertaForTokenClassification were not initialized from the model checkpoint at BSC-TeMU/roberta-base-bne and are newly initialized: ['classifier.weight', 'classifier.bias']\n", + "You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.\n", + "Running tokenizer on train dataset: 0% 0/9 [00:00> The following columns in the training set don't have a corresponding argument in `RobertaForTokenClassification.forward` and have been ignored: ner_tags, pos_tags, tokens, id.\n", + "[INFO|trainer.py:1162] 2021-07-19 12:11:41,218 >> ***** Running training *****\n", + "[INFO|trainer.py:1163] 2021-07-19 12:11:41,218 >> Num examples = 8324\n", + "[INFO|trainer.py:1164] 2021-07-19 12:11:41,218 >> Num Epochs = 5\n", + "[INFO|trainer.py:1165] 2021-07-19 12:11:41,218 >> Instantaneous batch size per device = 8\n", + "[INFO|trainer.py:1166] 2021-07-19 12:11:41,218 >> Total train batch size (w. parallel, distributed & accumulation) = 8\n", + "[INFO|trainer.py:1167] 2021-07-19 12:11:41,218 >> Gradient Accumulation steps = 1\n", + "[INFO|trainer.py:1168] 2021-07-19 12:11:41,219 >> Total optimization steps = 5205\n", + "[INFO|integrations.py:417] 2021-07-19 12:11:41,235 >> Automatic Weights & Biases logging enabled, to disable set os.environ[\"WANDB_DISABLED\"] = \"true\"\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Currently logged in as: \u001b[33mversae\u001b[0m (use `wandb login --relogin` to force relogin)\n", + "2021-07-19 12:11:42.880000: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Successfully opened dynamic library libcudart.so.11.0\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Tracking run with wandb version 0.11.0\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Syncing run \u001b[33m./outputs\u001b[0m\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: ⭐️ View project at \u001b[34m\u001b[4mhttps://wandb.ai/versae/bertin-eval\u001b[0m\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: 🚀 View run at \u001b[34m\u001b[4mhttps://wandb.ai/versae/bertin-eval/runs/12cfhsht\u001b[0m\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Run data is saved locally in /content/wandb/run-20210719_121141-12cfhsht\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Run `wandb offline` to turn off syncing.\n", + "\n", + "{'loss': 0.1418, 'learning_rate': 4.5196926032660905e-05, 'epoch': 0.48}\n", + " 10% 500/5205 [02:48<30:04, 2.61it/s][INFO|trainer.py:1917] 2021-07-19 12:14:32,851 >> Saving model checkpoint to ./outputs/checkpoint-500\n", + "[INFO|configuration_utils.py:379] 2021-07-19 12:14:32,853 >> Configuration saved in ./outputs/checkpoint-500/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 12:14:34,368 >> Model weights saved in ./outputs/checkpoint-500/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 12:14:34,369 >> tokenizer config file saved in ./outputs/checkpoint-500/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 12:14:34,370 >> Special tokens file saved in ./outputs/checkpoint-500/special_tokens_map.json\n", + " 19% 1000/5205 [05:42<26:57, 2.60it/s]{'loss': 0.0593, 'learning_rate': 4.039385206532181e-05, 'epoch': 0.96}\n", + "[INFO|trainer.py:1917] 2021-07-19 12:17:26,829 >> Saving model checkpoint to ./outputs/checkpoint-1000\n", + "[INFO|configuration_utils.py:379] 2021-07-19 12:17:26,831 >> Configuration saved in ./outputs/checkpoint-1000/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 12:17:28,225 >> Model weights saved in ./outputs/checkpoint-1000/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 12:17:28,227 >> tokenizer config file saved in ./outputs/checkpoint-1000/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 12:17:28,227 >> Special tokens file saved in ./outputs/checkpoint-1000/special_tokens_map.json\n", + "{'loss': 0.0343, 'learning_rate': 3.5590778097982716e-05, 'epoch': 1.44}\n", + " 29% 1500/5205 [08:36<23:33, 2.62it/s][INFO|trainer.py:1917] 2021-07-19 12:20:20,638 >> Saving model checkpoint to ./outputs/checkpoint-1500\n", + "[INFO|configuration_utils.py:379] 2021-07-19 12:20:20,639 >> Configuration saved in ./outputs/checkpoint-1500/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 12:20:22,205 >> Model weights saved in ./outputs/checkpoint-1500/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 12:20:22,206 >> tokenizer config file saved in ./outputs/checkpoint-1500/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 12:20:22,207 >> Special tokens file saved in ./outputs/checkpoint-1500/special_tokens_map.json\n", + "{'loss': 0.0352, 'learning_rate': 3.078770413064361e-05, 'epoch': 1.92}\n", + " 38% 2000/5205 [11:30<20:28, 2.61it/s][INFO|trainer.py:1917] 2021-07-19 12:23:14,468 >> Saving model checkpoint to ./outputs/checkpoint-2000\n", + "[INFO|configuration_utils.py:379] 2021-07-19 12:23:14,469 >> Configuration saved in ./outputs/checkpoint-2000/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 12:23:15,919 >> Model weights saved in ./outputs/checkpoint-2000/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 12:23:15,921 >> tokenizer config file saved in ./outputs/checkpoint-2000/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 12:23:15,921 >> Special tokens file saved in ./outputs/checkpoint-2000/special_tokens_map.json\n", + " 48% 2500/5205 [14:23<17:21, 2.60it/s][INFO|trainer.py:1917] 2021-07-19 12:26:08,104 >> Saving model checkpoint to ./outputs/checkpoint-2500\n", + "[INFO|configuration_utils.py:379] 2021-07-19 12:26:08,105 >> Configuration saved in ./outputs/checkpoint-2500/config.json\n", + "{'loss': 0.0219, 'learning_rate': 2.5984630163304517e-05, 'epoch': 2.4}\n", + "[INFO|modeling_utils.py:997] 2021-07-19 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./outputs/checkpoint-3000/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 12:29:03,455 >> Special tokens file saved in ./outputs/checkpoint-3000/special_tokens_map.json\n", + " 67% 3500/5205 [20:11<10:43, 2.65it/s]{'loss': 0.0114, 'learning_rate': 1.6378482228626322e-05, 'epoch': 3.36}\n", + "[INFO|trainer.py:1917] 2021-07-19 12:31:55,668 >> Saving model checkpoint to ./outputs/checkpoint-3500\n", + "[INFO|configuration_utils.py:379] 2021-07-19 12:31:55,669 >> Configuration saved in ./outputs/checkpoint-3500/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 12:31:57,243 >> Model weights saved in ./outputs/checkpoint-3500/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 12:31:57,244 >> tokenizer config file saved in ./outputs/checkpoint-3500/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 12:31:57,245 >> Special tokens file saved in ./outputs/checkpoint-3500/special_tokens_map.json\n", + " 77% 4000/5205 [23:05<07:40, 2.62it/s]{'loss': 0.0088, 'learning_rate': 1.1575408261287224e-05, 'epoch': 3.84}\n", + "[INFO|trainer.py:1917] 2021-07-19 12:34:49,424 >> Saving model checkpoint to ./outputs/checkpoint-4000\n", + "[INFO|configuration_utils.py:379] 2021-07-19 12:34:49,425 >> Configuration saved in ./outputs/checkpoint-4000/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 12:34:50,977 >> Model weights saved in ./outputs/checkpoint-4000/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 12:34:50,978 >> tokenizer config file saved in ./outputs/checkpoint-4000/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 12:34:50,978 >> Special tokens file saved in ./outputs/checkpoint-4000/special_tokens_map.json\n", + " 86% 4500/5205 [25:58<04:26, 2.65it/s]{'loss': 0.0066, 'learning_rate': 6.7723342939481265e-06, 'epoch': 4.32}\n", + "[INFO|trainer.py:1917] 2021-07-19 12:37:42,549 >> Saving model checkpoint to ./outputs/checkpoint-4500\n", + "[INFO|configuration_utils.py:379] 2021-07-19 12:37:42,551 >> Configuration saved in ./outputs/checkpoint-4500/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 12:37:44,154 >> Model weights saved in ./outputs/checkpoint-4500/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 12:37:44,156 >> tokenizer config file saved in ./outputs/checkpoint-4500/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 12:37:44,156 >> Special tokens file saved in ./outputs/checkpoint-4500/special_tokens_map.json\n", + "{'loss': 0.005, 'learning_rate': 1.96926032660903e-06, 'epoch': 4.8}\n", + " 96% 5000/5205 [28:51<01:17, 2.63it/s][INFO|trainer.py:1917] 2021-07-19 12:40:35,837 >> Saving model checkpoint to ./outputs/checkpoint-5000\n", + "[INFO|configuration_utils.py:379] 2021-07-19 12:40:35,838 >> Configuration saved in ./outputs/checkpoint-5000/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 12:40:37,324 >> Model weights saved in ./outputs/checkpoint-5000/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 12:40:37,325 >> tokenizer config file saved in ./outputs/checkpoint-5000/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 12:40:37,326 >> Special tokens file saved in ./outputs/checkpoint-5000/special_tokens_map.json\n", + "100% 5205/5205 [30:06<00:00, 3.33it/s][INFO|trainer.py:1358] 2021-07-19 12:41:50,325 >> \n", + "\n", + "Training completed. Do not forget to share your model on huggingface.co/models =)\n", + "\n", + "\n", + "100% 5205/5205 [30:06<00:00, 3.33it/s]{'train_runtime': 1809.1062, 'train_samples_per_second': 23.006, 'train_steps_per_second': 2.877, 'train_loss': 0.03290085400902916, 'epoch': 5.0}\n", + "100% 5205/5205 [30:06<00:00, 2.88it/s]\n", + "[INFO|trainer.py:1917] 2021-07-19 12:41:50,331 >> Saving model checkpoint to ./outputs\n", + "[INFO|configuration_utils.py:379] 2021-07-19 12:41:50,333 >> Configuration saved in ./outputs/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 12:41:51,802 >> Model weights saved in ./outputs/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 12:41:51,803 >> tokenizer config file saved in ./outputs/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 12:41:51,804 >> Special tokens file saved in ./outputs/special_tokens_map.json\n", + "***** train metrics *****\n", + " epoch = 5.0\n", + " train_loss = 0.0329\n", + " train_runtime = 0:30:09.10\n", + " train_samples = 8324\n", + " train_samples_per_second = 23.006\n", + " train_steps_per_second = 2.877\n", + "07/19/2021 12:41:51 - INFO - __main__ - *** Evaluate ***\n", + "[INFO|trainer.py:522] 2021-07-19 12:41:51,935 >> The following columns in the evaluation set don't have a corresponding argument in `RobertaForTokenClassification.forward` and have been ignored: ner_tags, pos_tags, tokens, id.\n", + "[INFO|trainer.py:2163] 2021-07-19 12:41:51,957 >> ***** Running Evaluation *****\n", + "[INFO|trainer.py:2165] 2021-07-19 12:41:51,958 >> Num examples = 1916\n", + "[INFO|trainer.py:2168] 2021-07-19 12:41:51,958 >> Batch size = 8\n", + "100% 240/240 [00:26<00:00, 8.94it/s]\n", + "***** eval metrics *****\n", + " epoch = 5.0\n", + " eval_accuracy = 0.9807\n", + " eval_f1 = 0.87\n", + " eval_loss = 0.1062\n", + " eval_precision = 0.8656\n", + " eval_recall = 0.8745\n", + " eval_runtime = 0:00:26.95\n", + " eval_samples = 1916\n", + " eval_samples_per_second = 71.076\n", + " eval_steps_per_second = 8.903\n", + "\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Waiting for W&B process to finish, PID 747\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Program ended successfully.\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: \n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Find user logs for this run at: /content/wandb/run-20210719_121141-12cfhsht/logs/debug.log\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Find internal logs for this run at: /content/wandb/run-20210719_121141-12cfhsht/logs/debug-internal.log\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Run summary:\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/loss 0.005\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/learning_rate 0.0\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/epoch 5.0\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/global_step 5205\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: _runtime 1837\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: _timestamp 1626698538\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: _step 11\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_runtime 1809.1062\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_samples_per_second 23.006\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_steps_per_second 2.877\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/total_flos 1.087585926764544e+16\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_loss 0.0329\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/loss 0.10615\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/precision 0.86559\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/recall 0.87454\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/f1 0.87004\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/accuracy 0.98065\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/runtime 26.9571\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/samples_per_second 71.076\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/steps_per_second 8.903\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Run history:\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/loss █▄▂▃▂▂▁▁▁▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/learning_rate █▇▆▆▅▄▃▃▂▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/epoch ▁▂▂▃▄▅▅▆▇███\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/global_step ▁▂▂▃▄▅▅▆▇███\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: _runtime ▁▂▂▃▄▅▅▆▇███\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: _timestamp ▁▂▂▃▄▅▅▆▇███\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: _step ▁▂▂▃▄▄▅▅▆▇▇█\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_runtime ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_samples_per_second ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_steps_per_second ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/total_flos ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_loss ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/loss ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/precision ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/recall ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/f1 ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/accuracy ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/runtime ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/samples_per_second ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/steps_per_second ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: \n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Synced 5 W&B file(s), 0 media file(s), 0 artifact file(s) and 1 other file(s)\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: \n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Synced \u001b[33m./outputs\u001b[0m: \u001b[34mhttps://wandb.ai/versae/bertin-eval/runs/12cfhsht\u001b[0m\n", + "2021-07-19 12:42:31.685010: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Successfully opened dynamic library libcudart.so.11.0\n", + "07/19/2021 12:42:34 - WARNING - __main__ - Process rank: -1, device: cuda:0, n_gpu: 1distributed training: False, 16-bits training: False\n", + "07/19/2021 12:42:34 - INFO - __main__ - Training/evaluation parameters TrainingArguments(\n", + "_n_gpu=1,\n", + "adafactor=False,\n", + "adam_beta1=0.9,\n", + "adam_beta2=0.999,\n", + "adam_epsilon=1e-08,\n", + "dataloader_drop_last=False,\n", + "dataloader_num_workers=0,\n", + "dataloader_pin_memory=True,\n", + "ddp_find_unused_parameters=None,\n", + "debug=[],\n", + "deepspeed=None,\n", + "disable_tqdm=False,\n", + "do_eval=True,\n", + "do_predict=False,\n", + "do_train=True,\n", + "eval_accumulation_steps=None,\n", + "eval_steps=500,\n", + "evaluation_strategy=IntervalStrategy.NO,\n", + "fp16=False,\n", + "fp16_backend=auto,\n", + "fp16_full_eval=False,\n", + "fp16_opt_level=O1,\n", + "gradient_accumulation_steps=1,\n", + "greater_is_better=None,\n", + "group_by_length=False,\n", + "ignore_data_skip=False,\n", + "label_names=None,\n", + "label_smoothing_factor=0.0,\n", + "learning_rate=5e-05,\n", + "length_column_name=length,\n", + "load_best_model_at_end=False,\n", + "local_rank=-1,\n", + "log_level=-1,\n", + "log_level_replica=-1,\n", + "log_on_each_node=True,\n", + "logging_dir=./outputs/runs/Jul19_12-42-34_eab5184de9ff,\n", + "logging_first_step=False,\n", + "logging_steps=500,\n", + "logging_strategy=IntervalStrategy.STEPS,\n", + "lr_scheduler_type=SchedulerType.LINEAR,\n", + "max_grad_norm=1.0,\n", + "max_steps=-1,\n", + "metric_for_best_model=None,\n", + "mp_parameters=,\n", + "no_cuda=False,\n", + "num_train_epochs=5.0,\n", + "output_dir=./outputs,\n", + "overwrite_output_dir=True,\n", + "past_index=-1,\n", + "per_device_eval_batch_size=8,\n", + "per_device_train_batch_size=8,\n", + "prediction_loss_only=False,\n", + "push_to_hub=False,\n", + "push_to_hub_model_id=outputs,\n", + "push_to_hub_organization=None,\n", + "push_to_hub_token=None,\n", + "remove_unused_columns=True,\n", + "report_to=['tensorboard', 'wandb'],\n", + "resume_from_checkpoint=None,\n", + "run_name=./outputs,\n", + "save_on_each_node=False,\n", + "save_steps=500,\n", + "save_strategy=IntervalStrategy.STEPS,\n", + "save_total_limit=None,\n", + "seed=42,\n", + "sharded_ddp=[],\n", + "skip_memory_metrics=True,\n", + "tpu_metrics_debug=False,\n", + "tpu_num_cores=None,\n", + "use_legacy_prediction_loop=False,\n", + "warmup_ratio=0.0,\n", + "warmup_steps=0,\n", + "weight_decay=0.0,\n", + ")\n", + "07/19/2021 12:42:36 - INFO - datasets.load - Found main folder for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py at /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002\n", + "07/19/2021 12:42:36 - INFO - datasets.load - Found specific version folder for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py at /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5\n", + "07/19/2021 12:42:36 - INFO - datasets.load - Found script file from 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https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py at /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002\n", + "07/19/2021 12:42:37 - INFO - datasets.load - Found specific version folder for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py at /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5\n", + "07/19/2021 12:42:37 - INFO - datasets.load - Found script file from https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py to /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5/conll2002.py\n", + "07/19/2021 12:42:37 - INFO - datasets.load - Found dataset infos file from https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/dataset_infos.json to /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5/dataset_infos.json\n", + "07/19/2021 12:42:37 - INFO - datasets.load - Found metadata file for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py at /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5/conll2002.json\n", + "07/19/2021 12:42:37 - INFO - datasets.info - Loading Dataset Infos from /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5\n", + "07/19/2021 12:42:37 - INFO - datasets.builder - Overwrite dataset info from restored data version.\n", + "07/19/2021 12:42:37 - INFO - datasets.info - Loading Dataset info from /root/.cache/huggingface/datasets/conll2002/es/1.0.0/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5\n", + "07/19/2021 12:42:37 - WARNING - datasets.builder - Reusing dataset conll2002 (/root/.cache/huggingface/datasets/conll2002/es/1.0.0/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5)\n", + "07/19/2021 12:42:37 - INFO - datasets.info - Loading Dataset info from /root/.cache/huggingface/datasets/conll2002/es/1.0.0/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5\n", + "100% 3/3 [00:00<00:00, 28.00it/s]\n", + "[INFO|file_utils.py:1624] 2021-07-19 12:42:38,678 >> https://huggingface.co/dccuchile/bert-base-spanish-wwm-cased/resolve/main/config.json not found in cache or force_download set to True, downloading to /root/.cache/huggingface/transformers/tmpck_oqd1g\n", + "Downloading: 100% 648/648 [00:00<00:00, 440kB/s]\n", + "[INFO|file_utils.py:1628] 2021-07-19 12:42:39,399 >> storing https://huggingface.co/dccuchile/bert-base-spanish-wwm-cased/resolve/main/config.json in cache at /root/.cache/huggingface/transformers/cb7cedb04246e225d56ba26d207f1d1809b31a9bbe9b63103371d835c6ac0502.f4e4777229bac528fa2a8d4833e2ef53624e985ebde0fd527064a5cc7c50832b\n", + "[INFO|file_utils.py:1636] 2021-07-19 12:42:39,400 >> creating metadata file for /root/.cache/huggingface/transformers/cb7cedb04246e225d56ba26d207f1d1809b31a9bbe9b63103371d835c6ac0502.f4e4777229bac528fa2a8d4833e2ef53624e985ebde0fd527064a5cc7c50832b\n", + "[INFO|configuration_utils.py:545] 2021-07-19 12:42:39,400 >> loading configuration file https://huggingface.co/dccuchile/bert-base-spanish-wwm-cased/resolve/main/config.json from cache at /root/.cache/huggingface/transformers/cb7cedb04246e225d56ba26d207f1d1809b31a9bbe9b63103371d835c6ac0502.f4e4777229bac528fa2a8d4833e2ef53624e985ebde0fd527064a5cc7c50832b\n", + "[INFO|configuration_utils.py:581] 2021-07-19 12:42:39,401 >> Model config BertConfig {\n", + " \"_name_or_path\": \"dccuchile/bert-base-spanish-wwm-cased\",\n", + " \"architectures\": [\n", + " \"BertForMaskedLM\"\n", + " ],\n", + " \"attention_probs_dropout_prob\": 0.1,\n", + " \"finetuning_task\": \"ner\",\n", + " \"gradient_checkpointing\": false,\n", + " \"hidden_act\": \"gelu\",\n", + " \"hidden_dropout_prob\": 0.1,\n", + " \"hidden_size\": 768,\n", + " \"id2label\": {\n", + " \"0\": 0,\n", + " \"1\": 1,\n", + " \"2\": 2,\n", + " \"3\": 3,\n", + " \"4\": 4,\n", + " \"5\": 5,\n", + " \"6\": 6,\n", + " \"7\": 7,\n", + " \"8\": 8\n", + " },\n", + " \"initializer_range\": 0.02,\n", + " \"intermediate_size\": 3072,\n", + " \"label2id\": {\n", + " \"0\": 0,\n", + " \"1\": 1,\n", + " \"2\": 2,\n", + " \"3\": 3,\n", + " \"4\": 4,\n", + " \"5\": 5,\n", + " \"6\": 6,\n", + " \"7\": 7,\n", + " \"8\": 8\n", + " },\n", + " \"layer_norm_eps\": 1e-12,\n", + " \"max_position_embeddings\": 512,\n", + " \"model_type\": \"bert\",\n", + " \"num_attention_heads\": 12,\n", + " \"num_hidden_layers\": 12,\n", + " \"output_past\": true,\n", + " \"pad_token_id\": 1,\n", + " \"position_embedding_type\": \"absolute\",\n", + " \"transformers_version\": \"4.9.0.dev0\",\n", + " \"type_vocab_size\": 2,\n", + " \"use_cache\": true,\n", + " \"vocab_size\": 31002\n", + "}\n", + "\n", + "[INFO|file_utils.py:1624] 2021-07-19 12:42:40,119 >> https://huggingface.co/dccuchile/bert-base-spanish-wwm-cased/resolve/main/tokenizer_config.json not found in cache or force_download set to True, downloading to /root/.cache/huggingface/transformers/tmpgd0560ha\n", + "Downloading: 100% 364/364 [00:00<00:00, 267kB/s]\n", + "[INFO|file_utils.py:1628] 2021-07-19 12:42:40,845 >> storing https://huggingface.co/dccuchile/bert-base-spanish-wwm-cased/resolve/main/tokenizer_config.json in cache at /root/.cache/huggingface/transformers/ca34e6c1251888a8ed98da2a454f869d28e3438eef67c2f93aa8133459ac08a3.0e90f656d0426b15b4927d1fe8ca5ec4c2e7b0d0e878c9153c3ddc6ed9bbed3c\n", + "[INFO|file_utils.py:1636] 2021-07-19 12:42:40,845 >> creating metadata file for /root/.cache/huggingface/transformers/ca34e6c1251888a8ed98da2a454f869d28e3438eef67c2f93aa8133459ac08a3.0e90f656d0426b15b4927d1fe8ca5ec4c2e7b0d0e878c9153c3ddc6ed9bbed3c\n", + "[INFO|configuration_utils.py:545] 2021-07-19 12:42:41,566 >> loading configuration file https://huggingface.co/dccuchile/bert-base-spanish-wwm-cased/resolve/main/config.json from cache at /root/.cache/huggingface/transformers/cb7cedb04246e225d56ba26d207f1d1809b31a9bbe9b63103371d835c6ac0502.f4e4777229bac528fa2a8d4833e2ef53624e985ebde0fd527064a5cc7c50832b\n", + "[INFO|configuration_utils.py:581] 2021-07-19 12:42:41,567 >> Model config BertConfig {\n", + " \"_name_or_path\": \"dccuchile/bert-base-spanish-wwm-cased\",\n", + " \"architectures\": [\n", + " \"BertForMaskedLM\"\n", + " ],\n", + " \"attention_probs_dropout_prob\": 0.1,\n", + " \"gradient_checkpointing\": false,\n", + " \"hidden_act\": \"gelu\",\n", + " \"hidden_dropout_prob\": 0.1,\n", + " \"hidden_size\": 768,\n", + " \"initializer_range\": 0.02,\n", + " \"intermediate_size\": 3072,\n", + " \"layer_norm_eps\": 1e-12,\n", + " \"max_position_embeddings\": 512,\n", + " \"model_type\": \"bert\",\n", + " \"num_attention_heads\": 12,\n", + " \"num_hidden_layers\": 12,\n", + " \"output_past\": true,\n", + " \"pad_token_id\": 1,\n", + " \"position_embedding_type\": \"absolute\",\n", + " \"transformers_version\": \"4.9.0.dev0\",\n", + " \"type_vocab_size\": 2,\n", + " \"use_cache\": true,\n", + " \"vocab_size\": 31002\n", + "}\n", + "\n", + "[INFO|file_utils.py:1624] 2021-07-19 12:42:42,282 >> https://huggingface.co/dccuchile/bert-base-spanish-wwm-cased/resolve/main/vocab.txt not found in cache or force_download set to True, downloading to /root/.cache/huggingface/transformers/tmplt5qimq9\n", + "Downloading: 100% 242k/242k [00:00<00:00, 693kB/s]\n", + "[INFO|file_utils.py:1628] 2021-07-19 12:42:43,361 >> storing https://huggingface.co/dccuchile/bert-base-spanish-wwm-cased/resolve/main/vocab.txt in cache at 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/root/.cache/huggingface/transformers/9848a00af462c42dfb4ec88ef438fbab5256330f7f6f50badc48d277f9367d49.f982506b52498d4adb4bd491f593dc92b2ef6be61bfdbe9d30f53f963f9f5b66\n", + "[INFO|file_utils.py:1636] 2021-07-19 12:42:47,314 >> creating metadata file for /root/.cache/huggingface/transformers/9848a00af462c42dfb4ec88ef438fbab5256330f7f6f50badc48d277f9367d49.f982506b52498d4adb4bd491f593dc92b2ef6be61bfdbe9d30f53f963f9f5b66\n", + "[INFO|tokenization_utils_base.py:1722] 2021-07-19 12:42:48,032 >> loading file https://huggingface.co/dccuchile/bert-base-spanish-wwm-cased/resolve/main/vocab.txt from cache at /root/.cache/huggingface/transformers/6761cd0c3d282272f598fcc1fa8c4ecfff8c18762ec8acb40f9cbb562cb0901e.6587bde86239957281af55b2f7e564df111a2b4f9dfc0ad884f13ea7106e4dfb\n", + "[INFO|tokenization_utils_base.py:1722] 2021-07-19 12:42:48,033 >> loading file https://huggingface.co/dccuchile/bert-base-spanish-wwm-cased/resolve/main/tokenizer.json from cache at 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/root/.cache/huggingface/transformers/ca34e6c1251888a8ed98da2a454f869d28e3438eef67c2f93aa8133459ac08a3.0e90f656d0426b15b4927d1fe8ca5ec4c2e7b0d0e878c9153c3ddc6ed9bbed3c\n", + "[INFO|configuration_utils.py:545] 2021-07-19 12:42:48,751 >> loading configuration file https://huggingface.co/dccuchile/bert-base-spanish-wwm-cased/resolve/main/config.json from cache at /root/.cache/huggingface/transformers/cb7cedb04246e225d56ba26d207f1d1809b31a9bbe9b63103371d835c6ac0502.f4e4777229bac528fa2a8d4833e2ef53624e985ebde0fd527064a5cc7c50832b\n", + "[INFO|configuration_utils.py:581] 2021-07-19 12:42:48,752 >> Model config BertConfig {\n", + " \"_name_or_path\": \"dccuchile/bert-base-spanish-wwm-cased\",\n", + " \"architectures\": [\n", + " \"BertForMaskedLM\"\n", + " ],\n", + " \"attention_probs_dropout_prob\": 0.1,\n", + " \"gradient_checkpointing\": false,\n", + " \"hidden_act\": \"gelu\",\n", + " \"hidden_dropout_prob\": 0.1,\n", + " \"hidden_size\": 768,\n", + " \"initializer_range\": 0.02,\n", + " \"intermediate_size\": 3072,\n", + " \"layer_norm_eps\": 1e-12,\n", + " \"max_position_embeddings\": 512,\n", + " \"model_type\": \"bert\",\n", + " \"num_attention_heads\": 12,\n", + " \"num_hidden_layers\": 12,\n", + " \"output_past\": true,\n", + " \"pad_token_id\": 1,\n", + " \"position_embedding_type\": \"absolute\",\n", + " \"transformers_version\": \"4.9.0.dev0\",\n", + " \"type_vocab_size\": 2,\n", + " \"use_cache\": true,\n", + " \"vocab_size\": 31002\n", + "}\n", + "\n", + "[INFO|file_utils.py:1624] 2021-07-19 12:42:49,495 >> https://huggingface.co/dccuchile/bert-base-spanish-wwm-cased/resolve/main/pytorch_model.bin not found in cache or force_download set to True, downloading to /root/.cache/huggingface/transformers/tmpzy1_hik_\n", + "Downloading: 100% 440M/440M [00:09<00:00, 47.1MB/s]\n", + "[INFO|file_utils.py:1628] 2021-07-19 12:42:59,298 >> storing https://huggingface.co/dccuchile/bert-base-spanish-wwm-cased/resolve/main/pytorch_model.bin in cache at /root/.cache/huggingface/transformers/52382cbe7c1587c6b588daa81eaf247c5e2ad073d42b52192a8cd4202e7429b6.a88ccd19b1f271e63b6a901510804e6c0318089355c471334fe8b71b316a30ab\n", + "[INFO|file_utils.py:1636] 2021-07-19 12:42:59,299 >> creating metadata file for /root/.cache/huggingface/transformers/52382cbe7c1587c6b588daa81eaf247c5e2ad073d42b52192a8cd4202e7429b6.a88ccd19b1f271e63b6a901510804e6c0318089355c471334fe8b71b316a30ab\n", + "[INFO|modeling_utils.py:1271] 2021-07-19 12:42:59,299 >> loading weights file https://huggingface.co/dccuchile/bert-base-spanish-wwm-cased/resolve/main/pytorch_model.bin from cache at /root/.cache/huggingface/transformers/52382cbe7c1587c6b588daa81eaf247c5e2ad073d42b52192a8cd4202e7429b6.a88ccd19b1f271e63b6a901510804e6c0318089355c471334fe8b71b316a30ab\n", + "[WARNING|modeling_utils.py:1502] 2021-07-19 12:43:00,603 >> Some weights of the model checkpoint at dccuchile/bert-base-spanish-wwm-cased were not used when initializing BertForTokenClassification: ['cls.predictions.decoder.weight', 'cls.predictions.bias', 'cls.predictions.transform.dense.bias', 'cls.predictions.transform.LayerNorm.bias', 'cls.predictions.decoder.bias', 'cls.predictions.transform.LayerNorm.weight', 'cls.predictions.transform.dense.weight']\n", + "- This IS expected if you are initializing BertForTokenClassification from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).\n", + "- This IS NOT expected if you are initializing BertForTokenClassification from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).\n", + "[WARNING|modeling_utils.py:1513] 2021-07-19 12:43:00,603 >> Some weights of BertForTokenClassification were not initialized from the model checkpoint at dccuchile/bert-base-spanish-wwm-cased and are newly initialized: ['classifier.bias', 'classifier.weight']\n", + "You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.\n", + "Running tokenizer on train dataset: 0% 0/9 [00:00> The following columns in the training set don't have a corresponding argument in `BertForTokenClassification.forward` and have been ignored: id, pos_tags, tokens, ner_tags.\n", + "[INFO|trainer.py:1162] 2021-07-19 12:43:12,682 >> ***** Running training *****\n", + "[INFO|trainer.py:1163] 2021-07-19 12:43:12,682 >> Num examples = 8324\n", + "[INFO|trainer.py:1164] 2021-07-19 12:43:12,682 >> Num Epochs = 5\n", + "[INFO|trainer.py:1165] 2021-07-19 12:43:12,682 >> Instantaneous batch size per device = 8\n", + "[INFO|trainer.py:1166] 2021-07-19 12:43:12,683 >> Total train batch size (w. parallel, distributed & accumulation) = 8\n", + "[INFO|trainer.py:1167] 2021-07-19 12:43:12,683 >> Gradient Accumulation steps = 1\n", + "[INFO|trainer.py:1168] 2021-07-19 12:43:12,683 >> Total optimization steps = 5205\n", + "[INFO|integrations.py:417] 2021-07-19 12:43:12,727 >> Automatic Weights & Biases logging enabled, to disable set os.environ[\"WANDB_DISABLED\"] = \"true\"\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Currently logged in as: \u001b[33mversae\u001b[0m (use `wandb login --relogin` to force relogin)\n", + "2021-07-19 12:43:14.386397: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Successfully opened dynamic library libcudart.so.11.0\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Tracking run with wandb version 0.11.0\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Syncing run \u001b[33m./outputs\u001b[0m\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: ⭐️ View project at \u001b[34m\u001b[4mhttps://wandb.ai/versae/bertin-eval\u001b[0m\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: 🚀 View run at \u001b[34m\u001b[4mhttps://wandb.ai/versae/bertin-eval/runs/3afdjnxp\u001b[0m\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Run data is saved locally in /content/wandb/run-20210719_124312-3afdjnxp\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Run `wandb offline` to turn off syncing.\n", + "\n", + " 10% 500/5205 [02:54<30:58, 2.53it/s]{'loss': 0.1093, 'learning_rate': 4.5196926032660905e-05, 'epoch': 0.48}\n", + "[INFO|trainer.py:1917] 2021-07-19 12:46:10,608 >> Saving model checkpoint to ./outputs/checkpoint-500\n", + "[INFO|configuration_utils.py:379] 2021-07-19 12:46:10,609 >> Configuration saved in ./outputs/checkpoint-500/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 12:46:12,470 >> Model weights saved in ./outputs/checkpoint-500/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 12:46:12,471 >> tokenizer config file saved in ./outputs/checkpoint-500/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 12:46:12,471 >> Special tokens file saved in ./outputs/checkpoint-500/special_tokens_map.json\n", + " 19% 1000/5205 [05:54<27:38, 2.54it/s]{'loss': 0.0607, 'learning_rate': 4.039385206532181e-05, 'epoch': 0.96}\n", + "[INFO|trainer.py:1917] 2021-07-19 12:49:10,192 >> Saving model checkpoint to ./outputs/checkpoint-1000\n", + "[INFO|configuration_utils.py:379] 2021-07-19 12:49:10,195 >> Configuration saved in ./outputs/checkpoint-1000/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 12:49:12,074 >> Model weights saved in ./outputs/checkpoint-1000/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 12:49:12,075 >> tokenizer config file saved in ./outputs/checkpoint-1000/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 12:49:12,075 >> Special tokens file saved in ./outputs/checkpoint-1000/special_tokens_map.json\n", + "{'loss': 0.0386, 'learning_rate': 3.5590778097982716e-05, 'epoch': 1.44}\n", + " 29% 1500/5205 [08:53<24:04, 2.56it/s][INFO|trainer.py:1917] 2021-07-19 12:52:09,685 >> Saving model checkpoint to ./outputs/checkpoint-1500\n", + "[INFO|configuration_utils.py:379] 2021-07-19 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+ "[INFO|tokenization_utils_base.py:1998] 2021-07-19 12:55:10,256 >> tokenizer config file saved in ./outputs/checkpoint-2000/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 12:55:10,256 >> Special tokens file saved in ./outputs/checkpoint-2000/special_tokens_map.json\n", + " 48% 2500/5205 [14:50<17:47, 2.53it/s]{'loss': 0.0205, 'learning_rate': 2.5984630163304517e-05, 'epoch': 2.4}\n", + " 48% 2500/5205 [14:50<17:47, 2.53it/s][INFO|trainer.py:1917] 2021-07-19 12:58:06,487 >> Saving model checkpoint to ./outputs/checkpoint-2500\n", + "[INFO|configuration_utils.py:379] 2021-07-19 12:58:06,489 >> Configuration saved in ./outputs/checkpoint-2500/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 12:58:08,096 >> Model weights saved in ./outputs/checkpoint-2500/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 12:58:08,096 >> tokenizer config file saved in ./outputs/checkpoint-2500/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 12:58:08,097 >> Special tokens file saved in ./outputs/checkpoint-2500/special_tokens_map.json\n", + " 58% 3000/5205 [17:48<14:28, 2.54it/s]{'loss': 0.018, 'learning_rate': 2.118155619596542e-05, 'epoch': 2.88}\n", + " 58% 3000/5205 [17:49<14:28, 2.54it/s][INFO|trainer.py:1917] 2021-07-19 13:01:04,733 >> Saving model checkpoint to ./outputs/checkpoint-3000\n", + "[INFO|configuration_utils.py:379] 2021-07-19 13:01:04,734 >> Configuration saved in ./outputs/checkpoint-3000/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 13:01:06,183 >> Model weights saved in ./outputs/checkpoint-3000/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 13:01:06,184 >> tokenizer config file saved in ./outputs/checkpoint-3000/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 13:01:06,185 >> Special tokens file saved in ./outputs/checkpoint-3000/special_tokens_map.json\n", + " 67% 3500/5205 [20:46<11:06, 2.56it/s]{'loss': 0.0132, 'learning_rate': 1.6378482228626322e-05, 'epoch': 3.36}\n", + " 67% 3500/5205 [20:46<11:06, 2.56it/s][INFO|trainer.py:1917] 2021-07-19 13:04:02,534 >> Saving model checkpoint to ./outputs/checkpoint-3500\n", + "[INFO|configuration_utils.py:379] 2021-07-19 13:04:02,540 >> Configuration saved in ./outputs/checkpoint-3500/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 13:04:03,793 >> Model weights saved in ./outputs/checkpoint-3500/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 13:04:03,798 >> tokenizer config file saved in ./outputs/checkpoint-3500/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 13:04:03,799 >> Special tokens file saved in ./outputs/checkpoint-3500/special_tokens_map.json\n", + "{'loss': 0.0096, 'learning_rate': 1.1575408261287224e-05, 'epoch': 3.84}\n", + " 77% 4000/5205 [23:44<07:56, 2.53it/s][INFO|trainer.py:1917] 2021-07-19 13:07:00,237 >> Saving model checkpoint to ./outputs/checkpoint-4000\n", + "[INFO|configuration_utils.py:379] 2021-07-19 13:07:00,238 >> Configuration saved in ./outputs/checkpoint-4000/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 13:07:01,487 >> Model weights saved in ./outputs/checkpoint-4000/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 13:07:01,488 >> tokenizer config file saved in ./outputs/checkpoint-4000/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 13:07:01,513 >> Special tokens file saved in ./outputs/checkpoint-4000/special_tokens_map.json\n", + " 86% 4500/5205 [26:42<04:36, 2.55it/s]{'loss': 0.0072, 'learning_rate': 6.7723342939481265e-06, 'epoch': 4.32}\n", + " 86% 4500/5205 [26:42<04:36, 2.55it/s][INFO|trainer.py:1917] 2021-07-19 13:09:57,873 >> Saving model checkpoint to ./outputs/checkpoint-4500\n", + "[INFO|configuration_utils.py:379] 2021-07-19 13:09:57,875 >> Configuration saved in ./outputs/checkpoint-4500/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 13:09:59,182 >> Model weights saved in ./outputs/checkpoint-4500/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 13:09:59,183 >> tokenizer config file saved in ./outputs/checkpoint-4500/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 13:09:59,184 >> Special tokens file saved in ./outputs/checkpoint-4500/special_tokens_map.json\n", + "{'loss': 0.0054, 'learning_rate': 1.96926032660903e-06, 'epoch': 4.8}\n", + " 96% 5000/5205 [29:39<01:19, 2.57it/s][INFO|trainer.py:1917] 2021-07-19 13:12:55,378 >> Saving model checkpoint to ./outputs/checkpoint-5000\n", + "[INFO|configuration_utils.py:379] 2021-07-19 13:12:55,379 >> Configuration saved in ./outputs/checkpoint-5000/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 13:12:56,826 >> Model weights saved in ./outputs/checkpoint-5000/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 13:12:57,047 >> tokenizer config file saved in ./outputs/checkpoint-5000/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 13:12:57,047 >> Special tokens file saved in ./outputs/checkpoint-5000/special_tokens_map.json\n", + "100% 5205/5205 [30:55<00:00, 3.24it/s][INFO|trainer.py:1358] 2021-07-19 13:14:10,972 >> \n", + "\n", + "Training completed. Do not forget to share your model on huggingface.co/models =)\n", + "\n", + "\n", + "{'train_runtime': 1858.2897, 'train_samples_per_second': 22.397, 'train_steps_per_second': 2.801, 'train_loss': 0.030922601500116324, 'epoch': 5.0}\n", + "100% 5205/5205 [30:55<00:00, 2.81it/s]\n", + "[INFO|trainer.py:1917] 2021-07-19 13:14:10,976 >> Saving model checkpoint to ./outputs\n", + "[INFO|configuration_utils.py:379] 2021-07-19 13:14:10,978 >> Configuration saved in ./outputs/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 13:14:12,231 >> Model weights saved in ./outputs/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 13:14:12,232 >> tokenizer config file saved in ./outputs/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 13:14:12,233 >> Special tokens file saved in ./outputs/special_tokens_map.json\n", + "***** train metrics *****\n", + " epoch = 5.0\n", + " train_loss = 0.0309\n", + " train_runtime = 0:30:58.28\n", + " train_samples = 8324\n", + " train_samples_per_second = 22.397\n", + " train_steps_per_second = 2.801\n", + "07/19/2021 13:14:12 - INFO - __main__ - *** Evaluate ***\n", + "[INFO|trainer.py:522] 2021-07-19 13:14:12,284 >> The following columns in the evaluation set don't have a corresponding argument in `BertForTokenClassification.forward` and have been ignored: id, pos_tags, tokens, ner_tags.\n", + "[INFO|trainer.py:2163] 2021-07-19 13:14:12,470 >> ***** Running Evaluation *****\n", + "[INFO|trainer.py:2165] 2021-07-19 13:14:12,470 >> Num examples = 1916\n", + "[INFO|trainer.py:2168] 2021-07-19 13:14:12,470 >> Batch size = 8\n", + "100% 240/240 [00:27<00:00, 8.72it/s]\n", + "***** eval metrics *****\n", + " epoch = 5.0\n", + " eval_accuracy = 0.9783\n", + " eval_f1 = 0.8579\n", + " eval_loss = 0.136\n", + " eval_precision = 0.8544\n", + " eval_recall = 0.8614\n", + " eval_runtime = 0:00:27.66\n", + " eval_samples = 1916\n", + " eval_samples_per_second = 69.269\n", + " eval_steps_per_second = 8.677\n", + "\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Waiting for W&B process to finish, PID 817\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Program ended successfully.\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: \n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Find user logs for this run at: /content/wandb/run-20210719_124312-3afdjnxp/logs/debug.log\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Find internal logs for this run at: /content/wandb/run-20210719_124312-3afdjnxp/logs/debug-internal.log\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Run summary:\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/loss 0.0054\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/learning_rate 0.0\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/epoch 5.0\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/global_step 5205\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: _runtime 1887\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: _timestamp 1626700480\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: _step 11\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_runtime 1858.2897\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_samples_per_second 22.397\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_steps_per_second 2.801\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/total_flos 1.087585926764544e+16\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_loss 0.03092\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/loss 0.13604\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/precision 0.85438\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/recall 0.86144\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/f1 0.85789\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/accuracy 0.97827\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/runtime 27.6603\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/samples_per_second 69.269\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/steps_per_second 8.677\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Run history:\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/loss 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"\u001b[34m\u001b[1mwandb\u001b[0m: eval/accuracy ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/runtime ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/samples_per_second ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/steps_per_second ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: \n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Synced 5 W&B file(s), 0 media file(s), 0 artifact file(s) and 1 other file(s)\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: \n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Synced \u001b[33m./outputs\u001b[0m: \u001b[34mhttps://wandb.ai/versae/bertin-eval/runs/3afdjnxp\u001b[0m\n", + "2021-07-19 13:14:52.452814: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Successfully opened dynamic library libcudart.so.11.0\n", + "07/19/2021 13:14:55 - WARNING - __main__ - Process rank: -1, device: cuda:0, n_gpu: 1distributed training: False, 16-bits training: False\n", + "07/19/2021 13:14:55 - INFO - __main__ - Training/evaluation parameters TrainingArguments(\n", + "_n_gpu=1,\n", + "adafactor=False,\n", + "adam_beta1=0.9,\n", + "adam_beta2=0.999,\n", + "adam_epsilon=1e-08,\n", + "dataloader_drop_last=False,\n", + "dataloader_num_workers=0,\n", + "dataloader_pin_memory=True,\n", + "ddp_find_unused_parameters=None,\n", + "debug=[],\n", + "deepspeed=None,\n", + "disable_tqdm=False,\n", + "do_eval=True,\n", + "do_predict=False,\n", + "do_train=True,\n", + "eval_accumulation_steps=None,\n", + "eval_steps=500,\n", + "evaluation_strategy=IntervalStrategy.NO,\n", + "fp16=False,\n", + "fp16_backend=auto,\n", + "fp16_full_eval=False,\n", + "fp16_opt_level=O1,\n", + "gradient_accumulation_steps=1,\n", + "greater_is_better=None,\n", + "group_by_length=False,\n", + "ignore_data_skip=False,\n", + "label_names=None,\n", + "label_smoothing_factor=0.0,\n", + "learning_rate=5e-05,\n", + "length_column_name=length,\n", + "load_best_model_at_end=False,\n", + "local_rank=-1,\n", + "log_level=-1,\n", + "log_level_replica=-1,\n", + "log_on_each_node=True,\n", + "logging_dir=./outputs/runs/Jul19_13-14-55_eab5184de9ff,\n", + "logging_first_step=False,\n", + "logging_steps=500,\n", + "logging_strategy=IntervalStrategy.STEPS,\n", + "lr_scheduler_type=SchedulerType.LINEAR,\n", + "max_grad_norm=1.0,\n", + "max_steps=-1,\n", + "metric_for_best_model=None,\n", + "mp_parameters=,\n", + "no_cuda=False,\n", + "num_train_epochs=5.0,\n", + "output_dir=./outputs,\n", + "overwrite_output_dir=True,\n", + "past_index=-1,\n", + "per_device_eval_batch_size=8,\n", + "per_device_train_batch_size=8,\n", + "prediction_loss_only=False,\n", + "push_to_hub=False,\n", + "push_to_hub_model_id=outputs,\n", + "push_to_hub_organization=None,\n", + "push_to_hub_token=None,\n", + "remove_unused_columns=True,\n", + "report_to=['tensorboard', 'wandb'],\n", + "resume_from_checkpoint=None,\n", + "run_name=./outputs,\n", + "save_on_each_node=False,\n", + "save_steps=500,\n", + "save_strategy=IntervalStrategy.STEPS,\n", + "save_total_limit=None,\n", + "seed=42,\n", + "sharded_ddp=[],\n", + "skip_memory_metrics=True,\n", + "tpu_metrics_debug=False,\n", + "tpu_num_cores=None,\n", + "use_legacy_prediction_loop=False,\n", + "warmup_ratio=0.0,\n", + "warmup_steps=0,\n", + "weight_decay=0.0,\n", + ")\n", + "07/19/2021 13:14:56 - INFO - datasets.load - Found main folder for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py at /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002\n", + "07/19/2021 13:14:56 - INFO - datasets.load - Found specific version folder for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py at /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5\n", + "07/19/2021 13:14:56 - INFO - datasets.load - Found script file from https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py to /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5/conll2002.py\n", + "07/19/2021 13:14:56 - INFO - datasets.load - Found dataset infos file from https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/dataset_infos.json to /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5/dataset_infos.json\n", + "07/19/2021 13:14:56 - INFO - datasets.load - Found metadata file for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py at /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5/conll2002.json\n", + "07/19/2021 13:14:57 - INFO - datasets.load - Found main folder for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py at /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002\n", + "07/19/2021 13:14:57 - INFO - datasets.load - Found specific version folder for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py at /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5\n", + "07/19/2021 13:14:57 - INFO - datasets.load - Found script file from https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py to /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5/conll2002.py\n", + "07/19/2021 13:14:57 - INFO - datasets.load - Found dataset infos file from https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/dataset_infos.json to /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5/dataset_infos.json\n", + "07/19/2021 13:14:57 - INFO - datasets.load - Found metadata file for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py at /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5/conll2002.json\n", + "07/19/2021 13:14:57 - INFO - datasets.info - Loading Dataset Infos from /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5\n", + "07/19/2021 13:14:57 - INFO - datasets.builder - Overwrite dataset info from restored data version.\n", + "07/19/2021 13:14:57 - INFO - datasets.info - Loading Dataset info from /root/.cache/huggingface/datasets/conll2002/es/1.0.0/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5\n", + "07/19/2021 13:14:57 - WARNING - datasets.builder - Reusing dataset conll2002 (/root/.cache/huggingface/datasets/conll2002/es/1.0.0/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5)\n", + "07/19/2021 13:14:57 - INFO - datasets.info - Loading Dataset info from /root/.cache/huggingface/datasets/conll2002/es/1.0.0/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5\n", + "100% 3/3 [00:00<00:00, 26.94it/s]\n", + "[INFO|file_utils.py:1624] 2021-07-19 13:14:58,668 >> https://huggingface.co/bert-base-multilingual-cased/resolve/main/config.json not found in cache or force_download set to True, downloading to /root/.cache/huggingface/transformers/tmp99d369nz\n", + "Downloading: 100% 625/625 [00:00<00:00, 479kB/s]\n", + "[INFO|file_utils.py:1628] 2021-07-19 13:14:59,385 >> storing https://huggingface.co/bert-base-multilingual-cased/resolve/main/config.json in cache at /root/.cache/huggingface/transformers/6c4a5d81a58c9791cdf76a09bce1b5abfb9cf958aebada51200f4515403e5d08.0fe59f3f4f1335dadeb4bce8b8146199d9083512b50d07323c1c319f96df450c\n", + "[INFO|file_utils.py:1636] 2021-07-19 13:14:59,385 >> creating metadata file for /root/.cache/huggingface/transformers/6c4a5d81a58c9791cdf76a09bce1b5abfb9cf958aebada51200f4515403e5d08.0fe59f3f4f1335dadeb4bce8b8146199d9083512b50d07323c1c319f96df450c\n", + "[INFO|configuration_utils.py:545] 2021-07-19 13:14:59,386 >> loading configuration file https://huggingface.co/bert-base-multilingual-cased/resolve/main/config.json from cache at /root/.cache/huggingface/transformers/6c4a5d81a58c9791cdf76a09bce1b5abfb9cf958aebada51200f4515403e5d08.0fe59f3f4f1335dadeb4bce8b8146199d9083512b50d07323c1c319f96df450c\n", + "[INFO|configuration_utils.py:581] 2021-07-19 13:14:59,387 >> Model config BertConfig {\n", + " \"architectures\": [\n", + " \"BertForMaskedLM\"\n", + " ],\n", + " \"attention_probs_dropout_prob\": 0.1,\n", + " \"directionality\": \"bidi\",\n", + " \"finetuning_task\": \"ner\",\n", + " \"gradient_checkpointing\": false,\n", + " \"hidden_act\": \"gelu\",\n", + " \"hidden_dropout_prob\": 0.1,\n", + " \"hidden_size\": 768,\n", + " \"id2label\": {\n", + " \"0\": 0,\n", + " \"1\": 1,\n", + " \"2\": 2,\n", + " \"3\": 3,\n", + " \"4\": 4,\n", + " \"5\": 5,\n", + " \"6\": 6,\n", + " \"7\": 7,\n", + " \"8\": 8\n", + " },\n", + " \"initializer_range\": 0.02,\n", + " \"intermediate_size\": 3072,\n", + " \"label2id\": {\n", + " \"0\": 0,\n", + " \"1\": 1,\n", + " \"2\": 2,\n", + " \"3\": 3,\n", + " \"4\": 4,\n", + " \"5\": 5,\n", + " \"6\": 6,\n", + " \"7\": 7,\n", + " \"8\": 8\n", + " },\n", + " \"layer_norm_eps\": 1e-12,\n", + " \"max_position_embeddings\": 512,\n", + " \"model_type\": \"bert\",\n", + " \"num_attention_heads\": 12,\n", + " \"num_hidden_layers\": 12,\n", + " \"pad_token_id\": 0,\n", + " \"pooler_fc_size\": 768,\n", + " \"pooler_num_attention_heads\": 12,\n", + " \"pooler_num_fc_layers\": 3,\n", + " \"pooler_size_per_head\": 128,\n", + " \"pooler_type\": \"first_token_transform\",\n", + " \"position_embedding_type\": \"absolute\",\n", + " \"transformers_version\": \"4.9.0.dev0\",\n", + " \"type_vocab_size\": 2,\n", + " \"use_cache\": true,\n", + " \"vocab_size\": 119547\n", + "}\n", + "\n", + "[INFO|file_utils.py:1624] 2021-07-19 13:15:00,367 >> https://huggingface.co/bert-base-multilingual-cased/resolve/main/tokenizer_config.json not found in cache or force_download set to True, downloading to /root/.cache/huggingface/transformers/tmplitezxht\n", + "Downloading: 100% 29.0/29.0 [00:00<00:00, 21.6kB/s]\n", + "[INFO|file_utils.py:1628] 2021-07-19 13:15:01,085 >> storing https://huggingface.co/bert-base-multilingual-cased/resolve/main/tokenizer_config.json in cache at /root/.cache/huggingface/transformers/f55e7a2ad4f8d0fff2733b3f79777e1e99247f2e4583703e92ce74453af8c235.ec5c189f89475aac7d8cbd243960a0655cfadc3d0474da8ff2ed0bf1699c2a5f\n", + "[INFO|file_utils.py:1636] 2021-07-19 13:15:01,085 >> creating metadata file for /root/.cache/huggingface/transformers/f55e7a2ad4f8d0fff2733b3f79777e1e99247f2e4583703e92ce74453af8c235.ec5c189f89475aac7d8cbd243960a0655cfadc3d0474da8ff2ed0bf1699c2a5f\n", + "[INFO|configuration_utils.py:545] 2021-07-19 13:15:01,804 >> loading configuration file https://huggingface.co/bert-base-multilingual-cased/resolve/main/config.json from cache at /root/.cache/huggingface/transformers/6c4a5d81a58c9791cdf76a09bce1b5abfb9cf958aebada51200f4515403e5d08.0fe59f3f4f1335dadeb4bce8b8146199d9083512b50d07323c1c319f96df450c\n", + "[INFO|configuration_utils.py:581] 2021-07-19 13:15:01,804 >> Model config BertConfig {\n", + " \"architectures\": [\n", + " \"BertForMaskedLM\"\n", + " ],\n", + " \"attention_probs_dropout_prob\": 0.1,\n", + " \"directionality\": \"bidi\",\n", + " \"gradient_checkpointing\": false,\n", + " \"hidden_act\": \"gelu\",\n", + " \"hidden_dropout_prob\": 0.1,\n", + " \"hidden_size\": 768,\n", + " \"initializer_range\": 0.02,\n", + " \"intermediate_size\": 3072,\n", + " \"layer_norm_eps\": 1e-12,\n", + " \"max_position_embeddings\": 512,\n", + " \"model_type\": \"bert\",\n", + " \"num_attention_heads\": 12,\n", + " \"num_hidden_layers\": 12,\n", + " \"pad_token_id\": 0,\n", + " \"pooler_fc_size\": 768,\n", + " \"pooler_num_attention_heads\": 12,\n", + " \"pooler_num_fc_layers\": 3,\n", + " \"pooler_size_per_head\": 128,\n", + " \"pooler_type\": \"first_token_transform\",\n", + " \"position_embedding_type\": \"absolute\",\n", + " \"transformers_version\": \"4.9.0.dev0\",\n", + " \"type_vocab_size\": 2,\n", + " \"use_cache\": true,\n", + " \"vocab_size\": 119547\n", + "}\n", + "\n", + "[INFO|file_utils.py:1624] 2021-07-19 13:15:02,527 >> https://huggingface.co/bert-base-multilingual-cased/resolve/main/vocab.txt not found in cache or force_download set to True, downloading to /root/.cache/huggingface/transformers/tmp3mdjv62p\n", + "Downloading: 100% 996k/996k [00:00<00:00, 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/root/.cache/huggingface/transformers/f55e7a2ad4f8d0fff2733b3f79777e1e99247f2e4583703e92ce74453af8c235.ec5c189f89475aac7d8cbd243960a0655cfadc3d0474da8ff2ed0bf1699c2a5f\n", + "[INFO|configuration_utils.py:545] 2021-07-19 13:15:08,996 >> loading configuration file https://huggingface.co/bert-base-multilingual-cased/resolve/main/config.json from cache at /root/.cache/huggingface/transformers/6c4a5d81a58c9791cdf76a09bce1b5abfb9cf958aebada51200f4515403e5d08.0fe59f3f4f1335dadeb4bce8b8146199d9083512b50d07323c1c319f96df450c\n", + "[INFO|configuration_utils.py:581] 2021-07-19 13:15:08,997 >> Model config BertConfig {\n", + " \"architectures\": [\n", + " \"BertForMaskedLM\"\n", + " ],\n", + " \"attention_probs_dropout_prob\": 0.1,\n", + " \"directionality\": \"bidi\",\n", + " \"gradient_checkpointing\": false,\n", + " \"hidden_act\": \"gelu\",\n", + " \"hidden_dropout_prob\": 0.1,\n", + " \"hidden_size\": 768,\n", + " \"initializer_range\": 0.02,\n", + " \"intermediate_size\": 3072,\n", + " \"layer_norm_eps\": 1e-12,\n", + " \"max_position_embeddings\": 512,\n", + " \"model_type\": \"bert\",\n", + " \"num_attention_heads\": 12,\n", + " \"num_hidden_layers\": 12,\n", + " \"pad_token_id\": 0,\n", + " \"pooler_fc_size\": 768,\n", + " \"pooler_num_attention_heads\": 12,\n", + " \"pooler_num_fc_layers\": 3,\n", + " \"pooler_size_per_head\": 128,\n", + " \"pooler_type\": \"first_token_transform\",\n", + " \"position_embedding_type\": \"absolute\",\n", + " \"transformers_version\": \"4.9.0.dev0\",\n", + " \"type_vocab_size\": 2,\n", + " \"use_cache\": true,\n", + " \"vocab_size\": 119547\n", + "}\n", + "\n", + "[INFO|file_utils.py:1624] 2021-07-19 13:15:09,847 >> https://huggingface.co/bert-base-multilingual-cased/resolve/main/pytorch_model.bin not found in cache or force_download set to True, downloading to /root/.cache/huggingface/transformers/tmpjp03zrmf\n", + "Downloading: 100% 714M/714M [00:15<00:00, 44.8MB/s]\n", + "[INFO|file_utils.py:1628] 2021-07-19 13:15:26,143 >> storing https://huggingface.co/bert-base-multilingual-cased/resolve/main/pytorch_model.bin in cache at /root/.cache/huggingface/transformers/0a3fd51713dcbb4def175c7f85bddc995d5976ce1dde327f99104e4d33069f17.aa7be4c79d76f4066d9b354496ea477c9ee39c5d889156dd1efb680643c2b052\n", + "[INFO|file_utils.py:1636] 2021-07-19 13:15:26,143 >> creating metadata file for /root/.cache/huggingface/transformers/0a3fd51713dcbb4def175c7f85bddc995d5976ce1dde327f99104e4d33069f17.aa7be4c79d76f4066d9b354496ea477c9ee39c5d889156dd1efb680643c2b052\n", + "[INFO|modeling_utils.py:1271] 2021-07-19 13:15:26,144 >> loading weights file https://huggingface.co/bert-base-multilingual-cased/resolve/main/pytorch_model.bin from cache at /root/.cache/huggingface/transformers/0a3fd51713dcbb4def175c7f85bddc995d5976ce1dde327f99104e4d33069f17.aa7be4c79d76f4066d9b354496ea477c9ee39c5d889156dd1efb680643c2b052\n", + "[WARNING|modeling_utils.py:1502] 2021-07-19 13:15:28,640 >> Some weights of the model checkpoint at bert-base-multilingual-cased were not used when initializing BertForTokenClassification: ['cls.seq_relationship.weight', 'cls.predictions.transform.dense.bias', 'cls.seq_relationship.bias', 'cls.predictions.bias', 'cls.predictions.transform.LayerNorm.weight', 'cls.predictions.decoder.weight', 'cls.predictions.transform.LayerNorm.bias', 'cls.predictions.transform.dense.weight']\n", + "- This IS expected if you are initializing BertForTokenClassification from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).\n", + "- This IS NOT expected if you are initializing BertForTokenClassification from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).\n", + "[WARNING|modeling_utils.py:1513] 2021-07-19 13:15:28,640 >> Some weights of BertForTokenClassification were not initialized from the model checkpoint at bert-base-multilingual-cased and are newly initialized: ['classifier.bias', 'classifier.weight']\n", + "You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.\n", + "Running tokenizer on train dataset: 0% 0/9 [00:00> The following columns in the training set don't have a corresponding argument in `BertForTokenClassification.forward` and have been ignored: ner_tags, pos_tags, tokens, id.\n", + "[INFO|trainer.py:1162] 2021-07-19 13:15:41,264 >> ***** Running training *****\n", + "[INFO|trainer.py:1163] 2021-07-19 13:15:41,264 >> Num examples = 8324\n", + "[INFO|trainer.py:1164] 2021-07-19 13:15:41,264 >> Num Epochs = 5\n", + "[INFO|trainer.py:1165] 2021-07-19 13:15:41,264 >> Instantaneous batch size per device = 8\n", + "[INFO|trainer.py:1166] 2021-07-19 13:15:41,264 >> Total train batch size (w. parallel, distributed & accumulation) = 8\n", + "[INFO|trainer.py:1167] 2021-07-19 13:15:41,264 >> Gradient Accumulation steps = 1\n", + "[INFO|trainer.py:1168] 2021-07-19 13:15:41,264 >> Total optimization steps = 5205\n", + "[INFO|integrations.py:417] 2021-07-19 13:15:41,282 >> Automatic Weights & Biases logging enabled, to disable set os.environ[\"WANDB_DISABLED\"] = \"true\"\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Currently logged in as: \u001b[33mversae\u001b[0m (use `wandb login --relogin` to force relogin)\n", + "2021-07-19 13:15:42.989489: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Successfully opened dynamic library libcudart.so.11.0\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Tracking run with wandb version 0.11.0\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Syncing run \u001b[33m./outputs\u001b[0m\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: ⭐️ View project at \u001b[34m\u001b[4mhttps://wandb.ai/versae/bertin-eval\u001b[0m\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: 🚀 View run at \u001b[34m\u001b[4mhttps://wandb.ai/versae/bertin-eval/runs/5eemjhh0\u001b[0m\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Run data is saved locally in /content/wandb/run-20210719_131541-5eemjhh0\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Run `wandb offline` to turn off syncing.\n", + "\n", + "{'loss': 0.1207, 'learning_rate': 4.5196926032660905e-05, 'epoch': 0.48}\n", + " 10% 500/5205 [02:59<32:18, 2.43it/s][INFO|trainer.py:1917] 2021-07-19 13:18:43,561 >> Saving model checkpoint to ./outputs/checkpoint-500\n", + "[INFO|configuration_utils.py:379] 2021-07-19 13:18:43,562 >> Configuration saved in ./outputs/checkpoint-500/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 13:18:46,697 >> Model weights saved in ./outputs/checkpoint-500/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 13:18:46,698 >> tokenizer config file saved in ./outputs/checkpoint-500/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 13:18:46,699 >> Special tokens file saved in ./outputs/checkpoint-500/special_tokens_map.json\n", + "{'loss': 0.0692, 'learning_rate': 4.039385206532181e-05, 'epoch': 0.96}\n", + " 19% 1000/5205 [06:07<28:45, 2.44it/s][INFO|trainer.py:1917] 2021-07-19 13:21:51,942 >> Saving model checkpoint to ./outputs/checkpoint-1000\n", + "[INFO|configuration_utils.py:379] 2021-07-19 13:21:51,944 >> Configuration saved in ./outputs/checkpoint-1000/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 13:21:54,416 >> Model weights saved in ./outputs/checkpoint-1000/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 13:21:54,417 >> tokenizer config file saved in ./outputs/checkpoint-1000/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 13:21:54,417 >> Special tokens file saved in ./outputs/checkpoint-1000/special_tokens_map.json\n", + "{'loss': 0.0436, 'learning_rate': 3.5590778097982716e-05, 'epoch': 1.44}\n", + " 29% 1500/5205 [09:15<25:24, 2.43it/s][INFO|trainer.py:1917] 2021-07-19 13:24:59,297 >> Saving model checkpoint to ./outputs/checkpoint-1500\n", + "[INFO|configuration_utils.py:379] 2021-07-19 13:24:59,302 >> Configuration saved in ./outputs/checkpoint-1500/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 13:25:01,808 >> Model weights saved in ./outputs/checkpoint-1500/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 13:25:01,809 >> tokenizer config file saved in ./outputs/checkpoint-1500/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 13:25:01,809 >> Special tokens file saved in ./outputs/checkpoint-1500/special_tokens_map.json\n", + " 38% 2000/5205 [12:24<21:37, 2.47it/s]{'loss': 0.0476, 'learning_rate': 3.078770413064361e-05, 'epoch': 1.92}\n", + "[INFO|trainer.py:1917] 2021-07-19 13:28:09,253 >> Saving model checkpoint to ./outputs/checkpoint-2000\n", + "[INFO|configuration_utils.py:379] 2021-07-19 13:28:09,259 >> Configuration saved in 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"[INFO|tokenization_utils_base.py:1998] 2021-07-19 13:31:18,854 >> tokenizer config file saved in ./outputs/checkpoint-2500/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 13:31:18,855 >> Special tokens file saved in ./outputs/checkpoint-2500/special_tokens_map.json\n", + " 58% 3000/5205 [18:38<14:56, 2.46it/s]{'loss': 0.0239, 'learning_rate': 2.118155619596542e-05, 'epoch': 2.88}\n", + " 58% 3000/5205 [18:38<14:56, 2.46it/s][INFO|trainer.py:1917] 2021-07-19 13:34:23,058 >> Saving model checkpoint to ./outputs/checkpoint-3000\n", + "[INFO|configuration_utils.py:379] 2021-07-19 13:34:23,059 >> Configuration saved in ./outputs/checkpoint-3000/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 13:34:25,563 >> Model weights saved in ./outputs/checkpoint-3000/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 13:34:25,563 >> tokenizer config file saved in ./outputs/checkpoint-3000/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 13:34:25,564 >> Special tokens file saved in ./outputs/checkpoint-3000/special_tokens_map.json\n", + " 67% 3500/5205 [21:45<11:32, 2.46it/s]{'loss': 0.02, 'learning_rate': 1.6378482228626322e-05, 'epoch': 3.36}\n", + "[INFO|trainer.py:1917] 2021-07-19 13:37:29,626 >> Saving model checkpoint to ./outputs/checkpoint-3500\n", + "[INFO|configuration_utils.py:379] 2021-07-19 13:37:29,628 >> Configuration saved in ./outputs/checkpoint-3500/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 13:37:32,133 >> Model weights saved in ./outputs/checkpoint-3500/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 13:37:32,134 >> tokenizer config file saved in ./outputs/checkpoint-3500/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 13:37:32,134 >> Special tokens file saved in ./outputs/checkpoint-3500/special_tokens_map.json\n", + "{'loss': 0.014, 'learning_rate': 1.1575408261287224e-05, 'epoch': 3.84}\n", + " 77% 4000/5205 [24:51<08:10, 2.46it/s][INFO|trainer.py:1917] 2021-07-19 13:40:36,098 >> Saving model checkpoint to ./outputs/checkpoint-4000\n", + "[INFO|configuration_utils.py:379] 2021-07-19 13:40:36,102 >> Configuration saved in ./outputs/checkpoint-4000/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 13:40:38,713 >> Model weights saved in ./outputs/checkpoint-4000/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 13:40:38,714 >> tokenizer config file saved in ./outputs/checkpoint-4000/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 13:40:38,714 >> Special tokens file saved in ./outputs/checkpoint-4000/special_tokens_map.json\n", + " 86% 4500/5205 [27:58<04:45, 2.47it/s]{'loss': 0.0102, 'learning_rate': 6.7723342939481265e-06, 'epoch': 4.32}\n", + "[INFO|trainer.py:1917] 2021-07-19 13:43:42,728 >> Saving model checkpoint to ./outputs/checkpoint-4500\n", + "[INFO|configuration_utils.py:379] 2021-07-19 13:43:42,730 >> Configuration saved in ./outputs/checkpoint-4500/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 13:43:45,403 >> Model weights saved in ./outputs/checkpoint-4500/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 13:43:45,403 >> tokenizer config file saved in ./outputs/checkpoint-4500/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 13:43:45,435 >> Special tokens file saved in ./outputs/checkpoint-4500/special_tokens_map.json\n", + " 96% 5000/5205 [31:05<01:23, 2.46it/s]{'loss': 0.0091, 'learning_rate': 1.96926032660903e-06, 'epoch': 4.8}\n", + "[INFO|trainer.py:1917] 2021-07-19 13:46:49,438 >> Saving model checkpoint to ./outputs/checkpoint-5000\n", + "[INFO|configuration_utils.py:379] 2021-07-19 13:46:49,445 >> Configuration saved in ./outputs/checkpoint-5000/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 13:46:52,151 >> Model weights saved in ./outputs/checkpoint-5000/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 13:46:52,152 >> tokenizer config file saved in ./outputs/checkpoint-5000/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 13:46:52,153 >> Special tokens file saved in ./outputs/checkpoint-5000/special_tokens_map.json\n", + "100% 5205/5205 [32:29<00:00, 3.12it/s][INFO|trainer.py:1358] 2021-07-19 13:48:13,361 >> \n", + "\n", + "Training completed. Do not forget to share your model on huggingface.co/models =)\n", + "\n", + "\n", + "{'train_runtime': 1952.0967, 'train_samples_per_second': 21.321, 'train_steps_per_second': 2.666, 'train_loss': 0.03754559657988241, 'epoch': 5.0}\n", + "100% 5205/5205 [32:29<00:00, 2.67it/s]\n", + "[INFO|trainer.py:1917] 2021-07-19 13:48:13,365 >> Saving model checkpoint to ./outputs\n", + "[INFO|configuration_utils.py:379] 2021-07-19 13:48:13,367 >> Configuration saved in ./outputs/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 13:48:16,181 >> Model weights saved in ./outputs/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 13:48:16,182 >> tokenizer config file saved in ./outputs/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 13:48:16,183 >> Special tokens file saved in ./outputs/special_tokens_map.json\n", + "***** train metrics *****\n", + " epoch = 5.0\n", + " train_loss = 0.0375\n", + " train_runtime = 0:32:32.09\n", + " train_samples = 8324\n", + " train_samples_per_second = 21.321\n", + " train_steps_per_second = 2.666\n", + "[INFO|trainer.py:522] 2021-07-19 13:48:16,519 >> The following columns in the evaluation set don't have a corresponding argument in `BertForTokenClassification.forward` and have been ignored: ner_tags, pos_tags, tokens, id.\n", + "07/19/2021 13:48:16 - INFO - __main__ - *** Evaluate ***\n", + "[INFO|trainer.py:2163] 2021-07-19 13:48:16,542 >> ***** Running Evaluation *****\n", + "[INFO|trainer.py:2165] 2021-07-19 13:48:16,542 >> Num examples = 1916\n", + "[INFO|trainer.py:2168] 2021-07-19 13:48:16,542 >> Batch size = 8\n", + "100% 240/240 [00:27<00:00, 8.73it/s]\n", + "***** eval metrics *****\n", + " epoch = 5.0\n", + " eval_accuracy = 0.9779\n", + " eval_f1 = 0.8539\n", + " eval_loss = 0.1326\n", + " eval_precision = 0.8522\n", + " eval_recall = 0.8557\n", + " eval_runtime = 0:00:27.61\n", + " eval_samples = 1916\n", + " eval_samples_per_second = 69.373\n", + " eval_steps_per_second = 8.69\n", + "\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Waiting for W&B process to finish, PID 886\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Program ended successfully.\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: \n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Find user logs for this run at: /content/wandb/run-20210719_131541-5eemjhh0/logs/debug.log\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Find internal logs for this run at: /content/wandb/run-20210719_131541-5eemjhh0/logs/debug-internal.log\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Run summary:\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/loss 0.0091\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/learning_rate 0.0\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/epoch 5.0\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/global_step 5205\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: _runtime 1983\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: _timestamp 1626702524\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: _step 11\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_runtime 1952.0967\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_samples_per_second 21.321\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_steps_per_second 2.666\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/total_flos 1.087585926764544e+16\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_loss 0.03755\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/loss 0.13262\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/precision 0.85217\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/recall 0.8557\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/f1 0.85393\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/accuracy 0.97785\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/runtime 27.619\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/samples_per_second 69.373\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/steps_per_second 8.69\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Run history:\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/loss 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https://raw.githubusercontent.com/huggingface/transformers/master/examples/pytorch/token-classification/run_ner.py\n", + "for model in models:\n", + " !WANDB_PROJECT=bertin-eval TOKENIZERS_PARALLELISM=false CUDA_LAUNCH_BLOCKING=1 python run_ner.py \\\n", + " --model_name_or_path $model \\\n", + " --task_name pos \\\n", + " --dataset_name conll2002 \\\n", + " --dataset_config_name es \\\n", + " --output_dir ./outputs \\\n", + " --overwrite_output_dir \\\n", + " --pad_to_max_length \\\n", + " --num_train_epochs 5 \\\n", + " --do_train \\\n", + " --do_eval" + ], + "execution_count": null, + "outputs": [ + { + "output_type": "stream", + "text": [ + "\u001b[1;30;43mStreaming output truncated to the last 5000 lines.\u001b[0m\n", + " \"9\": 9,\n", + " \"10\": 10,\n", + " \"11\": 11,\n", + " \"12\": 12,\n", + " \"13\": 13,\n", + " \"14\": 14,\n", + " \"15\": 15,\n", + " \"16\": 16,\n", + " \"17\": 17,\n", + " \"18\": 18,\n", + " \"19\": 19,\n", + " \"20\": 20,\n", + " \"21\": 21,\n", + " 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57,\n", + " \"58\": 58,\n", + " \"59\": 59\n", + " },\n", + " \"layer_norm_eps\": 1e-05,\n", + " \"max_position_embeddings\": 514,\n", + " \"model_type\": \"roberta\",\n", + " \"num_attention_heads\": 12,\n", + " \"num_hidden_layers\": 12,\n", + " \"pad_token_id\": 1,\n", + " \"position_embedding_type\": \"absolute\",\n", + " \"transformers_version\": \"4.9.0.dev0\",\n", + " \"type_vocab_size\": 1,\n", + " \"use_cache\": true,\n", + " \"vocab_size\": 50265\n", + "}\n", + "\n", + "[INFO|tokenization_utils_base.py:1722] 2021-07-19 14:21:32,133 >> loading file https://huggingface.co/bertin-project/bertin-base-random-exp-512seqlen/resolve/main/vocab.json from cache at /root/.cache/huggingface/transformers/c1ba808baa4a9c0f3062f1881d448087c30a1443644365bd41cf366491ab4063.a80f232f572026f92499b14999a8ed4e044e04cf3d01b9f2be298c98e78e8498\n", + "[INFO|tokenization_utils_base.py:1722] 2021-07-19 14:21:32,134 >> loading file https://huggingface.co/bertin-project/bertin-base-random-exp-512seqlen/resolve/main/merges.txt from cache at /root/.cache/huggingface/transformers/17ffd9604d64364336252e5a3859c3c55be07c457328ab5fc37e4aaf39913d28.a0dfc41f9d0f03a56ba7a5401d770f6e43071045a0bd79073380d408d17a0d92\n", + "[INFO|tokenization_utils_base.py:1722] 2021-07-19 14:21:32,134 >> loading file https://huggingface.co/bertin-project/bertin-base-random-exp-512seqlen/resolve/main/tokenizer.json from cache at /root/.cache/huggingface/transformers/59e3c1ec6ec0fe2653924dcd348a763dd43f51d8eae6ab758e2d962ec7c14d5e.2a5dc806edc00ab3a329cb22b9973596ca75b24ba0e5e4963bf1308de7237a3d\n", + "[INFO|tokenization_utils_base.py:1722] 2021-07-19 14:21:32,134 >> loading file https://huggingface.co/bertin-project/bertin-base-random-exp-512seqlen/resolve/main/added_tokens.json from cache at None\n", + "[INFO|tokenization_utils_base.py:1722] 2021-07-19 14:21:32,134 >> loading file https://huggingface.co/bertin-project/bertin-base-random-exp-512seqlen/resolve/main/special_tokens_map.json from cache at /root/.cache/huggingface/transformers/39ddc268aab2655adb602f93d771480d4db157c1b6fae9a5ae9fc2112c645a69.a11ebb04664c067c8fe5ef8f8068b0f721263414a26058692f7b2e4ba2a1b342\n", + "[INFO|tokenization_utils_base.py:1722] 2021-07-19 14:21:32,134 >> loading file https://huggingface.co/bertin-project/bertin-base-random-exp-512seqlen/resolve/main/tokenizer_config.json from cache at /root/.cache/huggingface/transformers/a9d7a6740959c8c347993f62fbd5620bffa2d10c35c2e579a2ecec181299c9a1.9f7ac4246b492dfa7c21beb5233deec8aef46153ec25ac5258ac5e2ae82dfa89\n", + "[INFO|modeling_utils.py:1271] 2021-07-19 14:21:32,975 >> loading weights file https://huggingface.co/bertin-project/bertin-base-random-exp-512seqlen/resolve/main/pytorch_model.bin from cache at /root/.cache/huggingface/transformers/6dd5d03f2c36b42a305cf20636d35935ad2d998d2ab0588b28eeed0fc164db43.5b6b77533b091cc9204533514d844abfe875ebba66e044b251306c4228bd3221\n", + "[WARNING|modeling_utils.py:1502] 2021-07-19 14:21:40,934 >> Some weights of the model checkpoint at bertin-project/bertin-base-random-exp-512seqlen were not used when initializing RobertaForTokenClassification: ['lm_head.dense.bias', 'lm_head.bias', 'lm_head.dense.weight', 'lm_head.layer_norm.weight', 'lm_head.layer_norm.bias']\n", + "- This IS expected if you are initializing RobertaForTokenClassification from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).\n", + "- This IS NOT expected if you are initializing RobertaForTokenClassification from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).\n", + "[WARNING|modeling_utils.py:1513] 2021-07-19 14:21:40,934 >> Some weights of RobertaForTokenClassification were not initialized from the model checkpoint at bertin-project/bertin-base-random-exp-512seqlen and are newly initialized: ['classifier.bias', 'classifier.weight']\n", + "You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.\n", + "Running tokenizer on train dataset: 0% 0/9 [00:00> The following columns in the training set don't have a corresponding argument in `RobertaForTokenClassification.forward` and have been ignored: pos_tags, ner_tags, id, tokens.\n", + "[INFO|trainer.py:1162] 2021-07-19 14:21:52,654 >> ***** Running training *****\n", + "[INFO|trainer.py:1163] 2021-07-19 14:21:52,654 >> Num examples = 8324\n", + "[INFO|trainer.py:1164] 2021-07-19 14:21:52,654 >> Num Epochs = 5\n", + "[INFO|trainer.py:1165] 2021-07-19 14:21:52,654 >> Instantaneous batch size per device = 8\n", + "[INFO|trainer.py:1166] 2021-07-19 14:21:52,654 >> Total train batch size (w. parallel, distributed & accumulation) = 8\n", + "[INFO|trainer.py:1167] 2021-07-19 14:21:52,654 >> Gradient Accumulation steps = 1\n", + "[INFO|trainer.py:1168] 2021-07-19 14:21:52,654 >> Total optimization steps = 5205\n", + "[INFO|integrations.py:417] 2021-07-19 14:21:52,674 >> Automatic Weights & Biases logging enabled, to disable set os.environ[\"WANDB_DISABLED\"] = \"true\"\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Currently logged in as: \u001b[33mversae\u001b[0m (use `wandb login --relogin` to force relogin)\n", + "2021-07-19 14:21:54.344552: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Successfully opened dynamic library libcudart.so.11.0\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Tracking run with wandb version 0.11.0\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Syncing run \u001b[33m./outputs\u001b[0m\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: ⭐️ View project at \u001b[34m\u001b[4mhttps://wandb.ai/versae/bertin-eval\u001b[0m\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: 🚀 View run at \u001b[34m\u001b[4mhttps://wandb.ai/versae/bertin-eval/runs/2r11lsea\u001b[0m\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Run data is saved locally in /content/wandb/run-20210719_142152-2r11lsea\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Run `wandb offline` to turn off syncing.\n", + "\n", + "{'loss': 0.3573, 'learning_rate': 4.5196926032660905e-05, 'epoch': 0.48}\n", + " 10% 500/5205 [02:51<30:45, 2.55it/s][INFO|trainer.py:1917] 2021-07-19 14:24:47,008 >> Saving model checkpoint to ./outputs/checkpoint-500\n", + "[INFO|configuration_utils.py:379] 2021-07-19 14:24:47,015 >> Configuration saved in ./outputs/checkpoint-500/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 14:24:48,536 >> Model weights saved in ./outputs/checkpoint-500/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 14:24:48,537 >> tokenizer config file saved in ./outputs/checkpoint-500/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 14:24:48,537 >> Special tokens file saved in ./outputs/checkpoint-500/special_tokens_map.json\n", + " 19% 1000/5205 [05:48<27:28, 2.55it/s]{'loss': 0.1234, 'learning_rate': 4.039385206532181e-05, 'epoch': 0.96}\n", + " 19% 1000/5205 [05:48<27:28, 2.55it/s][INFO|trainer.py:1917] 2021-07-19 14:27:43,799 >> Saving model checkpoint to ./outputs/checkpoint-1000\n", + "[INFO|configuration_utils.py:379] 2021-07-19 14:27:43,801 >> Configuration saved in ./outputs/checkpoint-1000/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 14:27:45,270 >> Model weights saved in ./outputs/checkpoint-1000/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 14:27:45,270 >> tokenizer config file saved in ./outputs/checkpoint-1000/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 14:27:45,271 >> Special tokens file saved in 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"[INFO|modeling_utils.py:997] 2021-07-19 14:36:33,494 >> Model weights saved in ./outputs/checkpoint-2500/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 14:36:33,494 >> tokenizer config file saved in ./outputs/checkpoint-2500/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 14:36:33,495 >> Special tokens file saved in ./outputs/checkpoint-2500/special_tokens_map.json\n", + "{'loss': 0.0476, 'learning_rate': 2.118155619596542e-05, 'epoch': 2.88}\n", + " 58% 3000/5205 [17:32<14:22, 2.56it/s][INFO|trainer.py:1917] 2021-07-19 14:39:28,468 >> Saving model checkpoint to ./outputs/checkpoint-3000\n", + "[INFO|configuration_utils.py:379] 2021-07-19 14:39:28,470 >> Configuration saved in ./outputs/checkpoint-3000/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 14:39:30,159 >> Model weights saved in ./outputs/checkpoint-3000/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 14:39:30,160 >> tokenizer config file saved in ./outputs/checkpoint-3000/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 14:39:30,160 >> Special tokens file saved in ./outputs/checkpoint-3000/special_tokens_map.json\n", + " 67% 3500/5205 [20:29<10:57, 2.59it/s]{'loss': 0.0331, 'learning_rate': 1.6378482228626322e-05, 'epoch': 3.36}\n", + " 67% 3500/5205 [20:29<10:57, 2.59it/s][INFO|trainer.py:1917] 2021-07-19 14:42:24,890 >> Saving model checkpoint to ./outputs/checkpoint-3500\n", + "[INFO|configuration_utils.py:379] 2021-07-19 14:42:24,892 >> Configuration saved in ./outputs/checkpoint-3500/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 14:42:26,453 >> Model weights saved in ./outputs/checkpoint-3500/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 14:42:26,454 >> tokenizer config file saved in ./outputs/checkpoint-3500/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 14:42:26,454 >> Special tokens file saved in 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2.59it/s][INFO|trainer.py:1917] 2021-07-19 14:48:16,636 >> Saving model checkpoint to ./outputs/checkpoint-4500\n", + "[INFO|configuration_utils.py:379] 2021-07-19 14:48:16,638 >> Configuration saved in ./outputs/checkpoint-4500/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 14:48:18,221 >> Model weights saved in ./outputs/checkpoint-4500/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 14:48:18,222 >> tokenizer config file saved in ./outputs/checkpoint-4500/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 14:48:18,222 >> Special tokens file saved in ./outputs/checkpoint-4500/special_tokens_map.json\n", + "{'loss': 0.0174, 'learning_rate': 1.96926032660903e-06, 'epoch': 4.8}\n", + " 96% 5000/5205 [29:16<01:19, 2.59it/s][INFO|trainer.py:1917] 2021-07-19 14:51:12,353 >> Saving model checkpoint to ./outputs/checkpoint-5000\n", + "[INFO|configuration_utils.py:379] 2021-07-19 14:51:12,360 >> Configuration saved in ./outputs/checkpoint-5000/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 14:51:13,839 >> Model weights saved in ./outputs/checkpoint-5000/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 14:51:13,840 >> tokenizer config file saved in ./outputs/checkpoint-5000/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 14:51:13,840 >> Special tokens file saved in ./outputs/checkpoint-5000/special_tokens_map.json\n", + "100% 5205/5205 [30:32<00:00, 3.28it/s][INFO|trainer.py:1358] 2021-07-19 14:52:27,812 >> \n", + "\n", + "Training completed. Do not forget to share your model on huggingface.co/models =)\n", + "\n", + "\n", + "{'train_runtime': 1835.1582, 'train_samples_per_second': 22.679, 'train_steps_per_second': 2.836, 'train_loss': 0.08193410668203627, 'epoch': 5.0}\n", + "100% 5205/5205 [30:32<00:00, 2.84it/s]\n", + "[INFO|trainer.py:1917] 2021-07-19 14:52:27,819 >> Saving model checkpoint to ./outputs\n", + "[INFO|configuration_utils.py:379] 2021-07-19 14:52:27,821 >> Configuration saved in ./outputs/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 14:52:29,335 >> Model weights saved in ./outputs/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 14:52:29,374 >> tokenizer config file saved in ./outputs/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 14:52:29,375 >> Special tokens file saved in ./outputs/special_tokens_map.json\n", + "***** train metrics *****\n", + " epoch = 5.0\n", + " train_loss = 0.0819\n", + " train_runtime = 0:30:35.15\n", + " train_samples = 8324\n", + " train_samples_per_second = 22.679\n", + " train_steps_per_second = 2.836\n", + "[INFO|trainer.py:522] 2021-07-19 14:52:30,157 >> The following columns in the evaluation set don't have a corresponding argument in `RobertaForTokenClassification.forward` and have been ignored: pos_tags, ner_tags, id, tokens.\n", + "07/19/2021 14:52:30 - INFO - __main__ - *** Evaluate ***\n", + "[INFO|trainer.py:2163] 2021-07-19 14:52:30,225 >> ***** Running Evaluation *****\n", + "[INFO|trainer.py:2165] 2021-07-19 14:52:30,226 >> Num examples = 1916\n", + "[INFO|trainer.py:2168] 2021-07-19 14:52:30,226 >> Batch size = 8\n", + "100% 239/240 [00:24<00:00, 9.62it/s]/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: NC seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VMI seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Fpa seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Fpt seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Fc seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Z seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: NP seems not to be NE tag.\n", + " warnings.warn('{} seems 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"/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: PR seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: RG seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: CS seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: CC seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Fe seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Fx seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: DD seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VSI seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: PD seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VMG seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: P0 seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: PN seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VMM seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Fd seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: AO seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: DP seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: PP seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: PI seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VSS seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VAS seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: RN seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Fat seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Faa seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: DE seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VMS seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VSN seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VSP seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Fz seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: PT seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VAN seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VSG seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: PX seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: DT seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Fh seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VAP seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Fs seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VSM seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Y seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Fia seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Fit seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/v1.py:57: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n", + " _warn_prf(average, modifier, msg_start, len(result))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/v1.py:57: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n", + " _warn_prf(average, modifier, msg_start, len(result))\n", + "100% 240/240 [00:28<00:00, 8.50it/s]\n", + "***** eval metrics *****\n", + " epoch = 5.0\n", + " eval_accuracy = 0.9707\n", + " eval_f1 = 0.966\n", + " eval_loss = 0.1262\n", + " eval_precision = 0.9667\n", + " eval_recall = 0.9653\n", + " eval_runtime = 0:00:28.35\n", + " eval_samples = 1916\n", + " eval_samples_per_second = 67.583\n", + " eval_steps_per_second = 8.465\n", + "\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Waiting for W&B process to finish, PID 1015\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Program ended successfully.\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: \n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Find user logs for this run at: /content/wandb/run-20210719_142152-2r11lsea/logs/debug.log\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Find internal logs for this run at: /content/wandb/run-20210719_142152-2r11lsea/logs/debug-internal.log\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Run summary:\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/loss 0.0174\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/learning_rate 0.0\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/epoch 5.0\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/global_step 5205\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: _runtime 1865\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: _timestamp 1626706378\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: _step 11\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_runtime 1835.1582\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_samples_per_second 22.679\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_steps_per_second 2.836\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/total_flos 1.08808736772096e+16\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_loss 0.08193\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/loss 0.12617\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/precision 0.96668\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/recall 0.96534\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/f1 0.96601\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/accuracy 0.97066\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/runtime 28.3505\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/samples_per_second 67.583\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/steps_per_second 8.465\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Run history:\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/loss █▃▂▂▂▂▁▁▁▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/learning_rate █▇▆▆▅▄▃▃▂▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/epoch ▁▂▂▃▄▅▅▆▇███\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/global_step ▁▂▂▃▄▅▅▆▇███\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: _runtime ▁▂▂▃▄▅▅▆▇███\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: _timestamp ▁▂▂▃▄▅▅▆▇███\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: _step ▁▂▂▃▄▄▅▅▆▇▇█\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_runtime ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_samples_per_second ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_steps_per_second ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/total_flos ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_loss ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/loss ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/precision ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/recall ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/f1 ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/accuracy ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/runtime ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/samples_per_second ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/steps_per_second ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: \n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Synced 5 W&B file(s), 0 media file(s), 0 artifact file(s) and 1 other file(s)\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: \n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Synced \u001b[33m./outputs\u001b[0m: \u001b[34mhttps://wandb.ai/versae/bertin-eval/runs/2r11lsea\u001b[0m\n", + "2021-07-19 14:53:10.597067: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Successfully opened dynamic library libcudart.so.11.0\n", + "07/19/2021 14:53:13 - WARNING - __main__ - Process rank: -1, device: cuda:0, n_gpu: 1distributed training: False, 16-bits training: False\n", + "07/19/2021 14:53:13 - INFO - __main__ - Training/evaluation parameters TrainingArguments(\n", + "_n_gpu=1,\n", + "adafactor=False,\n", + "adam_beta1=0.9,\n", + "adam_beta2=0.999,\n", + "adam_epsilon=1e-08,\n", + "dataloader_drop_last=False,\n", + "dataloader_num_workers=0,\n", + "dataloader_pin_memory=True,\n", + "ddp_find_unused_parameters=None,\n", + "debug=[],\n", + "deepspeed=None,\n", + "disable_tqdm=False,\n", + "do_eval=True,\n", + "do_predict=False,\n", + "do_train=True,\n", + "eval_accumulation_steps=None,\n", + "eval_steps=500,\n", + "evaluation_strategy=IntervalStrategy.NO,\n", + "fp16=False,\n", + "fp16_backend=auto,\n", + "fp16_full_eval=False,\n", + "fp16_opt_level=O1,\n", + "gradient_accumulation_steps=1,\n", + "greater_is_better=None,\n", + "group_by_length=False,\n", + "ignore_data_skip=False,\n", + "label_names=None,\n", + "label_smoothing_factor=0.0,\n", + "learning_rate=5e-05,\n", + "length_column_name=length,\n", + "load_best_model_at_end=False,\n", + "local_rank=-1,\n", + "log_level=-1,\n", + "log_level_replica=-1,\n", + "log_on_each_node=True,\n", + "logging_dir=./outputs/runs/Jul19_14-53-13_eab5184de9ff,\n", + "logging_first_step=False,\n", + "logging_steps=500,\n", + "logging_strategy=IntervalStrategy.STEPS,\n", + "lr_scheduler_type=SchedulerType.LINEAR,\n", + "max_grad_norm=1.0,\n", + "max_steps=-1,\n", + "metric_for_best_model=None,\n", + "mp_parameters=,\n", + "no_cuda=False,\n", + "num_train_epochs=5.0,\n", + "output_dir=./outputs,\n", + "overwrite_output_dir=True,\n", + "past_index=-1,\n", + "per_device_eval_batch_size=8,\n", + "per_device_train_batch_size=8,\n", + "prediction_loss_only=False,\n", + "push_to_hub=False,\n", + "push_to_hub_model_id=outputs,\n", + "push_to_hub_organization=None,\n", + "push_to_hub_token=None,\n", + "remove_unused_columns=True,\n", + "report_to=['tensorboard', 'wandb'],\n", + "resume_from_checkpoint=None,\n", + "run_name=./outputs,\n", + "save_on_each_node=False,\n", + "save_steps=500,\n", + "save_strategy=IntervalStrategy.STEPS,\n", + "save_total_limit=None,\n", + "seed=42,\n", + "sharded_ddp=[],\n", + "skip_memory_metrics=True,\n", + "tpu_metrics_debug=False,\n", + "tpu_num_cores=None,\n", + "use_legacy_prediction_loop=False,\n", + "warmup_ratio=0.0,\n", + "warmup_steps=0,\n", + "weight_decay=0.0,\n", + ")\n", + "07/19/2021 14:53:15 - INFO - datasets.load - Found main folder for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py at /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002\n", + "07/19/2021 14:53:15 - INFO - datasets.load - Found specific version folder for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py at /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5\n", + "07/19/2021 14:53:15 - INFO - datasets.load - Found script file from https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py to /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5/conll2002.py\n", + "07/19/2021 14:53:15 - INFO - datasets.load - Found dataset infos file from https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/dataset_infos.json to /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5/dataset_infos.json\n", + "07/19/2021 14:53:15 - INFO - datasets.load - Found metadata file for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py at /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5/conll2002.json\n", + "07/19/2021 14:53:16 - INFO - datasets.load - Found main folder for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py at /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002\n", + "07/19/2021 14:53:16 - INFO - datasets.load - Found specific version folder for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py at /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5\n", + "07/19/2021 14:53:16 - INFO - datasets.load - Found script file from https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py to /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5/conll2002.py\n", + "07/19/2021 14:53:16 - INFO - datasets.load - Found dataset infos file from https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/dataset_infos.json to /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5/dataset_infos.json\n", + "07/19/2021 14:53:16 - INFO - datasets.load - Found metadata file for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py at /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5/conll2002.json\n", + "07/19/2021 14:53:16 - INFO - datasets.info - Loading Dataset Infos from /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5\n", + "07/19/2021 14:53:16 - INFO - datasets.builder - Overwrite dataset info from restored data version.\n", + "07/19/2021 14:53:16 - INFO - datasets.info - Loading Dataset info from /root/.cache/huggingface/datasets/conll2002/es/1.0.0/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5\n", + "07/19/2021 14:53:16 - WARNING - datasets.builder - Reusing dataset conll2002 (/root/.cache/huggingface/datasets/conll2002/es/1.0.0/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5)\n", + "07/19/2021 14:53:16 - INFO - datasets.info - Loading Dataset info from /root/.cache/huggingface/datasets/conll2002/es/1.0.0/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5\n", + "100% 3/3 [00:00<00:00, 27.40it/s]\n", + "[INFO|configuration_utils.py:545] 2021-07-19 14:53:17,765 >> loading configuration file https://huggingface.co/bertin-project/bertin-base-gaussian/resolve/main/config.json from cache at /root/.cache/huggingface/transformers/cbd56d68ce5dcd2626aba4c4b188db63f2ba2c49a604b36e7cdc6e52578ee306.08210214ecaf5cd53c702826a604e564d8af557125033eef720f4f9f2af1fc44\n", + "[INFO|configuration_utils.py:581] 2021-07-19 14:53:17,766 >> Model config RobertaConfig {\n", + " \"architectures\": [\n", + " \"RobertaForMaskedLM\"\n", + " ],\n", + " \"attention_probs_dropout_prob\": 0.1,\n", + " \"bos_token_id\": 0,\n", + " \"eos_token_id\": 2,\n", + " \"finetuning_task\": \"pos\",\n", + " \"gradient_checkpointing\": false,\n", + " \"hidden_act\": \"gelu\",\n", + " \"hidden_dropout_prob\": 0.1,\n", + " \"hidden_size\": 768,\n", + " \"id2label\": {\n", + " \"0\": 0,\n", + " \"1\": 1,\n", + " \"2\": 2,\n", + " \"3\": 3,\n", + " \"4\": 4,\n", + " \"5\": 5,\n", + " \"6\": 6,\n", + " \"7\": 7,\n", + " \"8\": 8,\n", + " \"9\": 9,\n", + " \"10\": 10,\n", + " \"11\": 11,\n", + " \"12\": 12,\n", + " \"13\": 13,\n", + " \"14\": 14,\n", + " \"15\": 15,\n", + " \"16\": 16,\n", + " \"17\": 17,\n", + " \"18\": 18,\n", + " \"19\": 19,\n", + " \"20\": 20,\n", + " \"21\": 21,\n", + " \"22\": 22,\n", + " \"23\": 23,\n", + " \"24\": 24,\n", + " \"25\": 25,\n", + " \"26\": 26,\n", + " \"27\": 27,\n", + " \"28\": 28,\n", + " \"29\": 29,\n", + " \"30\": 30,\n", + " \"31\": 31,\n", + " \"32\": 32,\n", + " \"33\": 33,\n", + " \"34\": 34,\n", + " \"35\": 35,\n", + " \"36\": 36,\n", + " \"37\": 37,\n", + " \"38\": 38,\n", + " \"39\": 39,\n", + " \"40\": 40,\n", + " \"41\": 41,\n", + " \"42\": 42,\n", + " \"43\": 43,\n", + " \"44\": 44,\n", + " \"45\": 45,\n", + " \"46\": 46,\n", + " \"47\": 47,\n", + " \"48\": 48,\n", + " \"49\": 49,\n", + " \"50\": 50,\n", + " \"51\": 51,\n", + " \"52\": 52,\n", + " \"53\": 53,\n", + " \"54\": 54,\n", + " \"55\": 55,\n", + " \"56\": 56,\n", + " \"57\": 57,\n", + " \"58\": 58,\n", + " \"59\": 59\n", + " },\n", + " \"initializer_range\": 0.02,\n", + " \"intermediate_size\": 3072,\n", + " \"label2id\": {\n", + " \"0\": 0,\n", + " \"1\": 1,\n", + " \"2\": 2,\n", + " \"3\": 3,\n", + " \"4\": 4,\n", + " \"5\": 5,\n", + " \"6\": 6,\n", + " \"7\": 7,\n", + " \"8\": 8,\n", + " \"9\": 9,\n", + " \"10\": 10,\n", + " \"11\": 11,\n", + " \"12\": 12,\n", + " \"13\": 13,\n", + " \"14\": 14,\n", + " \"15\": 15,\n", + " \"16\": 16,\n", + " \"17\": 17,\n", + " \"18\": 18,\n", + " \"19\": 19,\n", + " \"20\": 20,\n", + " \"21\": 21,\n", + " \"22\": 22,\n", + " \"23\": 23,\n", + " \"24\": 24,\n", + " \"25\": 25,\n", + " \"26\": 26,\n", + " \"27\": 27,\n", + " \"28\": 28,\n", + " \"29\": 29,\n", + " \"30\": 30,\n", + " \"31\": 31,\n", + " \"32\": 32,\n", + " \"33\": 33,\n", + " \"34\": 34,\n", + " \"35\": 35,\n", + " \"36\": 36,\n", + " \"37\": 37,\n", + " \"38\": 38,\n", + " \"39\": 39,\n", + " \"40\": 40,\n", + " \"41\": 41,\n", + " \"42\": 42,\n", + " \"43\": 43,\n", + " \"44\": 44,\n", + " \"45\": 45,\n", + " \"46\": 46,\n", + " \"47\": 47,\n", + " \"48\": 48,\n", + " \"49\": 49,\n", + " \"50\": 50,\n", + " \"51\": 51,\n", + " \"52\": 52,\n", + " \"53\": 53,\n", + " \"54\": 54,\n", + " \"55\": 55,\n", + " \"56\": 56,\n", + " \"57\": 57,\n", + " \"58\": 58,\n", + " \"59\": 59\n", + " },\n", + " \"layer_norm_eps\": 1e-05,\n", + " \"max_position_embeddings\": 514,\n", + " \"model_type\": \"roberta\",\n", + " \"num_attention_heads\": 12,\n", + " \"num_hidden_layers\": 12,\n", + " \"pad_token_id\": 1,\n", + " \"position_embedding_type\": \"absolute\",\n", + " \"transformers_version\": \"4.9.0.dev0\",\n", + " \"type_vocab_size\": 1,\n", + " \"use_cache\": true,\n", + " \"vocab_size\": 50265\n", + "}\n", + "\n", + "[INFO|tokenization_utils_base.py:1722] 2021-07-19 14:53:22,817 >> loading file https://huggingface.co/bertin-project/bertin-base-gaussian/resolve/main/vocab.json from cache at /root/.cache/huggingface/transformers/dae6454603d0b1d10a2446ffc1a21ccd636b0ca6a4c77a79fb9dfde03f4a51b8.a80f232f572026f92499b14999a8ed4e044e04cf3d01b9f2be298c98e78e8498\n", + "[INFO|tokenization_utils_base.py:1722] 2021-07-19 14:53:22,817 >> loading file https://huggingface.co/bertin-project/bertin-base-gaussian/resolve/main/merges.txt from cache at /root/.cache/huggingface/transformers/2e77e6f778d3fd8875349675d408521ca20c1f1acac2fd57d60ca945d82b926e.a0dfc41f9d0f03a56ba7a5401d770f6e43071045a0bd79073380d408d17a0d92\n", + "[INFO|tokenization_utils_base.py:1722] 2021-07-19 14:53:22,817 >> loading file https://huggingface.co/bertin-project/bertin-base-gaussian/resolve/main/tokenizer.json from cache at /root/.cache/huggingface/transformers/98a6808b3aa08b6d84e8b30dfa6892d15e9e631eebff8652b37ab29d75a0b98a.2a5dc806edc00ab3a329cb22b9973596ca75b24ba0e5e4963bf1308de7237a3d\n", + "[INFO|tokenization_utils_base.py:1722] 2021-07-19 14:53:22,817 >> loading file https://huggingface.co/bertin-project/bertin-base-gaussian/resolve/main/added_tokens.json from cache at None\n", + "[INFO|tokenization_utils_base.py:1722] 2021-07-19 14:53:22,817 >> loading file https://huggingface.co/bertin-project/bertin-base-gaussian/resolve/main/special_tokens_map.json from cache at /root/.cache/huggingface/transformers/1f5a4bde3e85f3c7b914d0e6b43b2f72d6b3b2f9ddbec7be9e4b0521a429f67f.a11ebb04664c067c8fe5ef8f8068b0f721263414a26058692f7b2e4ba2a1b342\n", + "[INFO|tokenization_utils_base.py:1722] 2021-07-19 14:53:22,817 >> loading file https://huggingface.co/bertin-project/bertin-base-gaussian/resolve/main/tokenizer_config.json from cache at /root/.cache/huggingface/transformers/7a419a17bf4372869932365630632f434d402e93dd7e609e73607cf71ec1bdf7.9f7ac4246b492dfa7c21beb5233deec8aef46153ec25ac5258ac5e2ae82dfa89\n", + "[INFO|modeling_utils.py:1271] 2021-07-19 14:53:23,622 >> loading weights file https://huggingface.co/bertin-project/bertin-base-gaussian/resolve/main/pytorch_model.bin from cache at /root/.cache/huggingface/transformers/d61c66f6163d7933bcffb5de3a666094c2c7c8d54145ec0cea640f72204427e0.50b5552cf09535e0a4b85cc39c83be233674d4cab0836dd8fedc97aa778c802c\n", + "[WARNING|modeling_utils.py:1502] 2021-07-19 14:53:31,610 >> Some weights of the model checkpoint at bertin-project/bertin-base-gaussian were not used when initializing RobertaForTokenClassification: ['lm_head.bias', 'lm_head.layer_norm.weight', 'lm_head.layer_norm.bias', 'lm_head.dense.bias', 'lm_head.dense.weight']\n", + "- This IS expected if you are initializing RobertaForTokenClassification from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).\n", + "- This IS NOT expected if you are initializing RobertaForTokenClassification from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).\n", + "[WARNING|modeling_utils.py:1513] 2021-07-19 14:53:31,611 >> Some weights of RobertaForTokenClassification were not initialized from the model checkpoint at bertin-project/bertin-base-gaussian and are newly initialized: ['classifier.weight', 'classifier.bias']\n", + "You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.\n", + "Running tokenizer on train dataset: 0% 0/9 [00:00> The following columns in the training set don't have a corresponding argument in `RobertaForTokenClassification.forward` and have been ignored: ner_tags, tokens, id, pos_tags.\n", + "[INFO|trainer.py:1162] 2021-07-19 14:53:43,083 >> ***** Running training *****\n", + "[INFO|trainer.py:1163] 2021-07-19 14:53:43,083 >> Num examples = 8324\n", + "[INFO|trainer.py:1164] 2021-07-19 14:53:43,083 >> Num Epochs = 5\n", + "[INFO|trainer.py:1165] 2021-07-19 14:53:43,083 >> Instantaneous batch size per device = 8\n", + "[INFO|trainer.py:1166] 2021-07-19 14:53:43,083 >> Total train batch size (w. parallel, distributed & accumulation) = 8\n", + "[INFO|trainer.py:1167] 2021-07-19 14:53:43,083 >> Gradient Accumulation steps = 1\n", + "[INFO|trainer.py:1168] 2021-07-19 14:53:43,083 >> Total optimization steps = 5205\n", + "[INFO|integrations.py:417] 2021-07-19 14:53:43,102 >> Automatic Weights & Biases logging enabled, to disable set os.environ[\"WANDB_DISABLED\"] = \"true\"\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Currently logged in as: \u001b[33mversae\u001b[0m (use `wandb login --relogin` to force relogin)\n", + "2021-07-19 14:53:44.752564: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Successfully opened dynamic library libcudart.so.11.0\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Tracking run with wandb version 0.11.0\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Syncing run \u001b[33m./outputs\u001b[0m\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: ⭐️ View project at \u001b[34m\u001b[4mhttps://wandb.ai/versae/bertin-eval\u001b[0m\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: 🚀 View run at \u001b[34m\u001b[4mhttps://wandb.ai/versae/bertin-eval/runs/srzdgyct\u001b[0m\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Run data is saved locally in /content/wandb/run-20210719_145343-srzdgyct\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Run `wandb offline` to turn off syncing.\n", + "\n", + " 10% 500/5205 [02:52<30:50, 2.54it/s]{'loss': 0.3213, 'learning_rate': 4.5196926032660905e-05, 'epoch': 0.48}\n", + "[INFO|trainer.py:1917] 2021-07-19 14:56:38,524 >> Saving model checkpoint to ./outputs/checkpoint-500\n", + "[INFO|configuration_utils.py:379] 2021-07-19 14:56:38,531 >> Configuration saved in ./outputs/checkpoint-500/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 14:56:40,026 >> Model weights saved in ./outputs/checkpoint-500/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 14:56:40,027 >> tokenizer config file saved in ./outputs/checkpoint-500/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 14:56:40,027 >> Special tokens file saved in ./outputs/checkpoint-500/special_tokens_map.json\n", + "{'loss': 0.1156, 'learning_rate': 4.039385206532181e-05, 'epoch': 0.96}\n", + " 19% 1000/5205 [05:50<27:14, 2.57it/s][INFO|trainer.py:1917] 2021-07-19 14:59:36,570 >> Saving model checkpoint to ./outputs/checkpoint-1000\n", + "[INFO|configuration_utils.py:379] 2021-07-19 14:59:36,572 >> Configuration saved in ./outputs/checkpoint-1000/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 14:59:37,987 >> Model weights saved in ./outputs/checkpoint-1000/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 14:59:37,988 >> tokenizer config file saved in ./outputs/checkpoint-1000/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 14:59:37,988 >> Special tokens file saved in ./outputs/checkpoint-1000/special_tokens_map.json\n", + " 29% 1500/5205 [08:47<24:24, 2.53it/s]{'loss': 0.0763, 'learning_rate': 3.5590778097982716e-05, 'epoch': 1.44}\n", + " 29% 1500/5205 [08:47<24:24, 2.53it/s][INFO|trainer.py:1917] 2021-07-19 15:02:33,921 >> Saving model checkpoint to ./outputs/checkpoint-1500\n", + "[INFO|configuration_utils.py:379] 2021-07-19 15:02:33,923 >> Configuration saved in ./outputs/checkpoint-1500/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 15:02:35,521 >> Model weights saved in ./outputs/checkpoint-1500/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 15:02:35,521 >> tokenizer config file saved in ./outputs/checkpoint-1500/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 15:02:35,522 >> Special tokens file saved in ./outputs/checkpoint-1500/special_tokens_map.json\n", + "{'loss': 0.0699, 'learning_rate': 3.078770413064361e-05, 'epoch': 1.92}\n", + " 38% 2000/5205 [11:45<20:52, 2.56it/s][INFO|trainer.py:1917] 2021-07-19 15:05:31,139 >> Saving model checkpoint to ./outputs/checkpoint-2000\n", + "[INFO|configuration_utils.py:379] 2021-07-19 15:05:31,141 >> Configuration saved in ./outputs/checkpoint-2000/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 15:05:32,718 >> Model weights saved in ./outputs/checkpoint-2000/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 15:05:32,719 >> tokenizer config file saved in ./outputs/checkpoint-2000/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 15:05:32,719 >> Special tokens file saved in ./outputs/checkpoint-2000/special_tokens_map.json\n", + "{'loss': 0.0473, 'learning_rate': 2.5984630163304517e-05, 'epoch': 2.4}\n", + " 48% 2500/5205 [14:42<17:32, 2.57it/s][INFO|trainer.py:1917] 2021-07-19 15:08:28,636 >> Saving model checkpoint to ./outputs/checkpoint-2500\n", + "[INFO|configuration_utils.py:379] 2021-07-19 15:08:28,638 >> Configuration saved in ./outputs/checkpoint-2500/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 15:08:30,199 >> Model weights saved in ./outputs/checkpoint-2500/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 15:08:30,200 >> tokenizer config file saved in ./outputs/checkpoint-2500/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 15:08:30,201 >> Special tokens file saved in ./outputs/checkpoint-2500/special_tokens_map.json\n", + " 58% 3000/5205 [17:40<14:25, 2.55it/s]{'loss': 0.0432, 'learning_rate': 2.118155619596542e-05, 'epoch': 2.88}\n", + "[INFO|trainer.py:1917] 2021-07-19 15:11:26,276 >> Saving model checkpoint to ./outputs/checkpoint-3000\n", + "[INFO|configuration_utils.py:379] 2021-07-19 15:11:26,279 >> Configuration saved in ./outputs/checkpoint-3000/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 15:11:28,019 >> Model weights saved in ./outputs/checkpoint-3000/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 15:11:28,020 >> tokenizer config file saved in ./outputs/checkpoint-3000/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 15:11:28,020 >> Special tokens file saved in ./outputs/checkpoint-3000/special_tokens_map.json\n", + " 67% 3500/5205 [20:37<11:04, 2.56it/s]{'loss': 0.029, 'learning_rate': 1.6378482228626322e-05, 'epoch': 3.36}\n", + " 67% 3500/5205 [20:37<11:04, 2.56it/s][INFO|trainer.py:1917] 2021-07-19 15:14:23,295 >> Saving model checkpoint to ./outputs/checkpoint-3500\n", + "[INFO|configuration_utils.py:379] 2021-07-19 15:14:23,297 >> Configuration saved in ./outputs/checkpoint-3500/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 15:14:24,881 >> Model weights saved in ./outputs/checkpoint-3500/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 15:14:24,882 >> tokenizer config file saved in ./outputs/checkpoint-3500/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 15:14:24,882 >> Special tokens file saved in ./outputs/checkpoint-3500/special_tokens_map.json\n", + "{'loss': 0.0258, 'learning_rate': 1.1575408261287224e-05, 'epoch': 3.84}\n", + " 77% 4000/5205 [23:34<07:50, 2.56it/s][INFO|trainer.py:1917] 2021-07-19 15:17:20,488 >> Saving model checkpoint to ./outputs/checkpoint-4000\n", + "[INFO|configuration_utils.py:379] 2021-07-19 15:17:20,490 >> Configuration saved in ./outputs/checkpoint-4000/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 15:17:22,034 >> Model weights saved in ./outputs/checkpoint-4000/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 15:17:22,035 >> tokenizer config file saved in ./outputs/checkpoint-4000/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 15:17:22,035 >> Special tokens file saved in ./outputs/checkpoint-4000/special_tokens_map.json\n", + "{'loss': 0.0188, 'learning_rate': 6.7723342939481265e-06, 'epoch': 4.32}\n", + " 86% 4500/5205 [26:31<04:35, 2.56it/s][INFO|trainer.py:1917] 2021-07-19 15:20:17,497 >> Saving model checkpoint to ./outputs/checkpoint-4500\n", + "[INFO|configuration_utils.py:379] 2021-07-19 15:20:17,499 >> Configuration saved in ./outputs/checkpoint-4500/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 15:20:19,183 >> Model weights saved in ./outputs/checkpoint-4500/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 15:20:19,184 >> tokenizer config file saved in ./outputs/checkpoint-4500/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 15:20:19,185 >> Special tokens file saved in ./outputs/checkpoint-4500/special_tokens_map.json\n", + "{'loss': 0.0146, 'learning_rate': 1.96926032660903e-06, 'epoch': 4.8}\n", + " 96% 5000/5205 [29:28<01:19, 2.57it/s][INFO|trainer.py:1917] 2021-07-19 15:23:14,540 >> Saving model checkpoint to ./outputs/checkpoint-5000\n", + "[INFO|configuration_utils.py:379] 2021-07-19 15:23:14,542 >> Configuration saved in ./outputs/checkpoint-5000/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 15:23:16,074 >> Model weights saved in ./outputs/checkpoint-5000/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 15:23:16,075 >> tokenizer config file saved in ./outputs/checkpoint-5000/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 15:23:16,075 >> Special tokens file saved in ./outputs/checkpoint-5000/special_tokens_map.json\n", + "100% 5205/5205 [30:44<00:00, 3.24it/s][INFO|trainer.py:1358] 2021-07-19 15:24:30,596 >> \n", + "\n", + "Training completed. Do not forget to share your model on huggingface.co/models =)\n", + "\n", + "\n", + " {'train_runtime': 1847.5133, 'train_samples_per_second': 22.528, 'train_steps_per_second': 2.817, 'train_loss': 0.07378956023371071, 'epoch': 5.0}\n", + "100% 5205/5205 [30:44<00:00, 2.82it/s]\n", + "[INFO|trainer.py:1917] 2021-07-19 15:24:30,606 >> Saving model checkpoint to ./outputs\n", + "[INFO|configuration_utils.py:379] 2021-07-19 15:24:30,608 >> Configuration saved in ./outputs/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 15:24:32,024 >> Model weights saved in ./outputs/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 15:24:32,024 >> tokenizer config file saved in ./outputs/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 15:24:32,029 >> Special tokens file saved in ./outputs/special_tokens_map.json\n", + "***** train metrics *****\n", + " epoch = 5.0\n", + " train_loss = 0.0738\n", + " train_runtime = 0:30:47.51\n", + " train_samples = 8324\n", + " train_samples_per_second = 22.528\n", + " train_steps_per_second = 2.817\n", + "[INFO|trainer.py:522] 2021-07-19 15:24:32,180 >> The following columns in the evaluation set don't have a corresponding argument in `RobertaForTokenClassification.forward` and have been ignored: ner_tags, tokens, id, pos_tags.\n", + "07/19/2021 15:24:32 - INFO - __main__ - *** Evaluate ***\n", + "[INFO|trainer.py:2163] 2021-07-19 15:24:32,296 >> ***** Running Evaluation *****\n", + "[INFO|trainer.py:2165] 2021-07-19 15:24:32,297 >> Num examples = 1916\n", + "[INFO|trainer.py:2168] 2021-07-19 15:24:32,297 >> Batch size = 8\n", + "100% 239/240 [00:25<00:00, 9.62it/s]/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: NC seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VMI seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Fpa seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Fpt seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Fc seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Z seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: NP seems not to be NE tag.\n", + " warnings.warn('{} seems 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"/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: PR seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: RG seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: CS seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: CC seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Fe seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Fx seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: DD seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VSI seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: PD seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VMG seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: P0 seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: PN seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VMM seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Fd seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: AO seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: DP seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: PP seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: PI seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VSS seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VAS seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: RN seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Fat seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Faa seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: DE seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VMS seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VSN seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VSP seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Fz seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: PT seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VAN seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VSG seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: PX seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: DT seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Fh seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VAP seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Fs seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VSM seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Y seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Fia seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/v1.py:57: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n", + " _warn_prf(average, modifier, msg_start, len(result))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/v1.py:57: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n", + " _warn_prf(average, modifier, msg_start, len(result))\n", + "100% 240/240 [00:28<00:00, 8.40it/s]\n", + "***** eval metrics *****\n", + " epoch = 5.0\n", + " eval_accuracy = 0.9709\n", + " eval_f1 = 0.9662\n", + " eval_loss = 0.1285\n", + " eval_precision = 0.9665\n", + " eval_recall = 0.9659\n", + " eval_runtime = 0:00:28.69\n", + " eval_samples = 1916\n", + " eval_samples_per_second = 66.777\n", + " eval_steps_per_second = 8.365\n", + "\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Waiting for W&B process to finish, PID 1079\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Program ended successfully.\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: \n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Find user logs for this run at: /content/wandb/run-20210719_145343-srzdgyct/logs/debug.log\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Find internal logs for this run at: /content/wandb/run-20210719_145343-srzdgyct/logs/debug-internal.log\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Run summary:\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/loss 0.0146\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/learning_rate 0.0\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/epoch 5.0\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/global_step 5205\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: _runtime 1877\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: _timestamp 1626708300\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: _step 11\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_runtime 1847.5133\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_samples_per_second 22.528\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_steps_per_second 2.817\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/total_flos 1.08808736772096e+16\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_loss 0.07379\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/loss 0.12853\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/precision 0.96649\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/recall 0.96593\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/f1 0.96621\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/accuracy 0.97086\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/runtime 28.6925\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/samples_per_second 66.777\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/steps_per_second 8.365\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Run history:\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/loss █▃▂▂▂▂▁▁▁▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/learning_rate █▇▆▆▅▄▃▃▂▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/epoch ▁▂▂▃▄▅▅▆▇███\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/global_step ▁▂▂▃▄▅▅▆▇███\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: _runtime ▁▂▂▃▄▅▅▆▇███\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: _timestamp ▁▂▂▃▄▅▅▆▇███\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: _step ▁▂▂▃▄▄▅▅▆▇▇█\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_runtime ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_samples_per_second ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_steps_per_second ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/total_flos ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_loss ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/loss ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/precision ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/recall ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/f1 ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/accuracy ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/runtime ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/samples_per_second ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/steps_per_second ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: \n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Synced 5 W&B file(s), 0 media file(s), 0 artifact file(s) and 1 other file(s)\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: \n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Synced \u001b[33m./outputs\u001b[0m: \u001b[34mhttps://wandb.ai/versae/bertin-eval/runs/srzdgyct\u001b[0m\n", + "2021-07-19 15:25:13.480929: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Successfully opened dynamic library libcudart.so.11.0\n", + "07/19/2021 15:25:16 - WARNING - __main__ - Process rank: -1, device: cuda:0, n_gpu: 1distributed training: False, 16-bits training: False\n", + "07/19/2021 15:25:16 - INFO - __main__ - Training/evaluation parameters TrainingArguments(\n", + "_n_gpu=1,\n", + "adafactor=False,\n", + "adam_beta1=0.9,\n", + "adam_beta2=0.999,\n", + "adam_epsilon=1e-08,\n", + "dataloader_drop_last=False,\n", + "dataloader_num_workers=0,\n", + "dataloader_pin_memory=True,\n", + "ddp_find_unused_parameters=None,\n", + "debug=[],\n", + "deepspeed=None,\n", + "disable_tqdm=False,\n", + "do_eval=True,\n", + "do_predict=False,\n", + "do_train=True,\n", + "eval_accumulation_steps=None,\n", + "eval_steps=500,\n", + "evaluation_strategy=IntervalStrategy.NO,\n", + "fp16=False,\n", + "fp16_backend=auto,\n", + "fp16_full_eval=False,\n", + "fp16_opt_level=O1,\n", + "gradient_accumulation_steps=1,\n", + "greater_is_better=None,\n", + "group_by_length=False,\n", + "ignore_data_skip=False,\n", + "label_names=None,\n", + "label_smoothing_factor=0.0,\n", + "learning_rate=5e-05,\n", + "length_column_name=length,\n", + "load_best_model_at_end=False,\n", + "local_rank=-1,\n", + "log_level=-1,\n", + "log_level_replica=-1,\n", + "log_on_each_node=True,\n", + "logging_dir=./outputs/runs/Jul19_15-25-16_eab5184de9ff,\n", + "logging_first_step=False,\n", + "logging_steps=500,\n", + "logging_strategy=IntervalStrategy.STEPS,\n", + "lr_scheduler_type=SchedulerType.LINEAR,\n", + "max_grad_norm=1.0,\n", + "max_steps=-1,\n", + "metric_for_best_model=None,\n", + "mp_parameters=,\n", + "no_cuda=False,\n", + "num_train_epochs=5.0,\n", + "output_dir=./outputs,\n", + "overwrite_output_dir=True,\n", + "past_index=-1,\n", + "per_device_eval_batch_size=8,\n", + "per_device_train_batch_size=8,\n", + "prediction_loss_only=False,\n", + "push_to_hub=False,\n", + "push_to_hub_model_id=outputs,\n", + "push_to_hub_organization=None,\n", + "push_to_hub_token=None,\n", + "remove_unused_columns=True,\n", + "report_to=['tensorboard', 'wandb'],\n", + "resume_from_checkpoint=None,\n", + "run_name=./outputs,\n", + "save_on_each_node=False,\n", + "save_steps=500,\n", + "save_strategy=IntervalStrategy.STEPS,\n", + "save_total_limit=None,\n", + "seed=42,\n", + "sharded_ddp=[],\n", + "skip_memory_metrics=True,\n", + "tpu_metrics_debug=False,\n", + "tpu_num_cores=None,\n", + "use_legacy_prediction_loop=False,\n", + "warmup_ratio=0.0,\n", + "warmup_steps=0,\n", + "weight_decay=0.0,\n", + ")\n", + "07/19/2021 15:25:17 - INFO - datasets.load - Found main folder for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py at /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002\n", + "07/19/2021 15:25:17 - INFO - datasets.load - Found specific version folder for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py at /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5\n", + "07/19/2021 15:25:17 - INFO - datasets.load - Found script file from https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py to /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5/conll2002.py\n", + "07/19/2021 15:25:17 - INFO - datasets.load - Found dataset infos file from https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/dataset_infos.json to /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5/dataset_infos.json\n", + "07/19/2021 15:25:17 - INFO - datasets.load - Found metadata file for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py at /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5/conll2002.json\n", + "07/19/2021 15:25:18 - INFO - datasets.load - Found main folder for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py at /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002\n", + "07/19/2021 15:25:18 - INFO - datasets.load - Found specific version folder for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py at /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5\n", + "07/19/2021 15:25:18 - INFO - datasets.load - Found script file from https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py to /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5/conll2002.py\n", + "07/19/2021 15:25:18 - INFO - datasets.load - Found dataset infos file from https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/dataset_infos.json to /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5/dataset_infos.json\n", + "07/19/2021 15:25:18 - INFO - datasets.load - Found metadata file for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py at /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5/conll2002.json\n", + "07/19/2021 15:25:18 - INFO - datasets.info - Loading Dataset Infos from /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5\n", + "07/19/2021 15:25:18 - INFO - datasets.builder - Overwrite dataset info from restored data version.\n", + "07/19/2021 15:25:18 - INFO - datasets.info - Loading Dataset info from /root/.cache/huggingface/datasets/conll2002/es/1.0.0/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5\n", + "07/19/2021 15:25:18 - WARNING - datasets.builder - Reusing dataset conll2002 (/root/.cache/huggingface/datasets/conll2002/es/1.0.0/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5)\n", + "07/19/2021 15:25:18 - INFO - datasets.info - Loading Dataset info from /root/.cache/huggingface/datasets/conll2002/es/1.0.0/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5\n", + "100% 3/3 [00:00<00:00, 26.65it/s]\n", + "[INFO|configuration_utils.py:545] 2021-07-19 15:25:19,679 >> loading configuration file https://huggingface.co/bertin-project/bertin-base-stepwise/resolve/main/config.json from cache at /root/.cache/huggingface/transformers/367bb30bd1ae06268e9d1c64ae1fb923fc9931913fa478dfa01d79a4c7086238.08210214ecaf5cd53c702826a604e564d8af557125033eef720f4f9f2af1fc44\n", + "[INFO|configuration_utils.py:581] 2021-07-19 15:25:19,680 >> Model config RobertaConfig {\n", + " \"architectures\": [\n", + " \"RobertaForMaskedLM\"\n", + " ],\n", + " \"attention_probs_dropout_prob\": 0.1,\n", + " \"bos_token_id\": 0,\n", + " \"eos_token_id\": 2,\n", + " \"finetuning_task\": \"pos\",\n", + " \"gradient_checkpointing\": false,\n", + " \"hidden_act\": \"gelu\",\n", + " \"hidden_dropout_prob\": 0.1,\n", + " \"hidden_size\": 768,\n", + " \"id2label\": {\n", + " \"0\": 0,\n", + " \"1\": 1,\n", + " \"2\": 2,\n", + " \"3\": 3,\n", + " \"4\": 4,\n", + " \"5\": 5,\n", + " \"6\": 6,\n", + " \"7\": 7,\n", + " \"8\": 8,\n", + " \"9\": 9,\n", + " \"10\": 10,\n", + " \"11\": 11,\n", + " \"12\": 12,\n", + " \"13\": 13,\n", + " \"14\": 14,\n", + " \"15\": 15,\n", + " \"16\": 16,\n", + " \"17\": 17,\n", + " \"18\": 18,\n", + " \"19\": 19,\n", + " \"20\": 20,\n", + " \"21\": 21,\n", + " \"22\": 22,\n", + " \"23\": 23,\n", + " \"24\": 24,\n", + " \"25\": 25,\n", + " \"26\": 26,\n", + " \"27\": 27,\n", + " \"28\": 28,\n", + " \"29\": 29,\n", + " \"30\": 30,\n", + " \"31\": 31,\n", + " \"32\": 32,\n", + " \"33\": 33,\n", + " \"34\": 34,\n", + " \"35\": 35,\n", + " \"36\": 36,\n", + " \"37\": 37,\n", + " \"38\": 38,\n", + " \"39\": 39,\n", + " \"40\": 40,\n", + " \"41\": 41,\n", + " \"42\": 42,\n", + " \"43\": 43,\n", + " \"44\": 44,\n", + " \"45\": 45,\n", + " \"46\": 46,\n", + " \"47\": 47,\n", + " \"48\": 48,\n", + " \"49\": 49,\n", + " \"50\": 50,\n", + " \"51\": 51,\n", + " \"52\": 52,\n", + " \"53\": 53,\n", + " \"54\": 54,\n", + " \"55\": 55,\n", + " \"56\": 56,\n", + " \"57\": 57,\n", + " \"58\": 58,\n", + " \"59\": 59\n", + " },\n", + " \"initializer_range\": 0.02,\n", + " \"intermediate_size\": 3072,\n", + " \"label2id\": {\n", + " \"0\": 0,\n", + " \"1\": 1,\n", + " \"2\": 2,\n", + " \"3\": 3,\n", + " \"4\": 4,\n", + " \"5\": 5,\n", + " \"6\": 6,\n", + " \"7\": 7,\n", + " \"8\": 8,\n", + " \"9\": 9,\n", + " \"10\": 10,\n", + " \"11\": 11,\n", + " \"12\": 12,\n", + " \"13\": 13,\n", + " \"14\": 14,\n", + " \"15\": 15,\n", + " \"16\": 16,\n", + " \"17\": 17,\n", + " \"18\": 18,\n", + " \"19\": 19,\n", + " \"20\": 20,\n", + " \"21\": 21,\n", + " \"22\": 22,\n", + " \"23\": 23,\n", + " \"24\": 24,\n", + " \"25\": 25,\n", + " \"26\": 26,\n", + " \"27\": 27,\n", + " \"28\": 28,\n", + " \"29\": 29,\n", + " \"30\": 30,\n", + " \"31\": 31,\n", + " \"32\": 32,\n", + " \"33\": 33,\n", + " \"34\": 34,\n", + " \"35\": 35,\n", + " \"36\": 36,\n", + " \"37\": 37,\n", + " \"38\": 38,\n", + " \"39\": 39,\n", + " \"40\": 40,\n", + " \"41\": 41,\n", + " \"42\": 42,\n", + " \"43\": 43,\n", + " \"44\": 44,\n", + " \"45\": 45,\n", + " \"46\": 46,\n", + " \"47\": 47,\n", + " \"48\": 48,\n", + " \"49\": 49,\n", + " \"50\": 50,\n", + " \"51\": 51,\n", + " \"52\": 52,\n", + " \"53\": 53,\n", + " \"54\": 54,\n", + " \"55\": 55,\n", + " \"56\": 56,\n", + " \"57\": 57,\n", + " \"58\": 58,\n", + " \"59\": 59\n", + " },\n", + " \"layer_norm_eps\": 1e-05,\n", + " \"max_position_embeddings\": 514,\n", + " \"model_type\": \"roberta\",\n", + " \"num_attention_heads\": 12,\n", + " \"num_hidden_layers\": 12,\n", + " \"pad_token_id\": 1,\n", + " \"position_embedding_type\": \"absolute\",\n", + " \"transformers_version\": \"4.9.0.dev0\",\n", + " \"type_vocab_size\": 1,\n", + " \"use_cache\": true,\n", + " \"vocab_size\": 50265\n", + "}\n", + "\n", + "[INFO|tokenization_utils_base.py:1722] 2021-07-19 15:25:25,275 >> loading file https://huggingface.co/bertin-project/bertin-base-stepwise/resolve/main/vocab.json from cache at /root/.cache/huggingface/transformers/dc7971c78d10d920138338883fd23b96f3994bce40018345ab1ba2ba8c8f6bdd.a80f232f572026f92499b14999a8ed4e044e04cf3d01b9f2be298c98e78e8498\n", + "[INFO|tokenization_utils_base.py:1722] 2021-07-19 15:25:25,275 >> loading file https://huggingface.co/bertin-project/bertin-base-stepwise/resolve/main/merges.txt from cache at /root/.cache/huggingface/transformers/5f573076405f6fab314615142ba9deec180a84917e495fecbf81f61afb2965cb.a0dfc41f9d0f03a56ba7a5401d770f6e43071045a0bd79073380d408d17a0d92\n", + "[INFO|tokenization_utils_base.py:1722] 2021-07-19 15:25:25,275 >> loading file https://huggingface.co/bertin-project/bertin-base-stepwise/resolve/main/tokenizer.json from cache at /root/.cache/huggingface/transformers/9a541e4855ef267ea4879cc9c2277f67dd5569f68cc688d212822bed1ca8755f.2a5dc806edc00ab3a329cb22b9973596ca75b24ba0e5e4963bf1308de7237a3d\n", + "[INFO|tokenization_utils_base.py:1722] 2021-07-19 15:25:25,275 >> loading file https://huggingface.co/bertin-project/bertin-base-stepwise/resolve/main/added_tokens.json from cache at None\n", + "[INFO|tokenization_utils_base.py:1722] 2021-07-19 15:25:25,275 >> loading file https://huggingface.co/bertin-project/bertin-base-stepwise/resolve/main/special_tokens_map.json from cache at /root/.cache/huggingface/transformers/8e21c2757a0c3938b80989bb3dabd355f9221ed98847fb957a5c4e9a86209c03.a11ebb04664c067c8fe5ef8f8068b0f721263414a26058692f7b2e4ba2a1b342\n", + "[INFO|tokenization_utils_base.py:1722] 2021-07-19 15:25:25,275 >> loading file https://huggingface.co/bertin-project/bertin-base-stepwise/resolve/main/tokenizer_config.json from cache at /root/.cache/huggingface/transformers/e577044edb84fa4a576105e2202c62cf62f831634f9581da80435c97b8034fba.9f7ac4246b492dfa7c21beb5233deec8aef46153ec25ac5258ac5e2ae82dfa89\n", + "[INFO|modeling_utils.py:1271] 2021-07-19 15:25:26,072 >> loading weights file https://huggingface.co/bertin-project/bertin-base-stepwise/resolve/main/pytorch_model.bin from cache at /root/.cache/huggingface/transformers/4832a73c0f4a13adaab71151bf2413717416da487cdb2a79247f10198c6421f8.aebba6b503a22a0c70b362f8b026aa0f030aae594f7580f0164a0a73fb0001af\n", + "[WARNING|modeling_utils.py:1502] 2021-07-19 15:25:34,070 >> Some weights of the model checkpoint at bertin-project/bertin-base-stepwise were not used when initializing RobertaForTokenClassification: ['lm_head.dense.bias', 'lm_head.layer_norm.weight', 'lm_head.layer_norm.bias', 'lm_head.dense.weight', 'lm_head.bias']\n", + "- This IS expected if you are initializing RobertaForTokenClassification from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).\n", + "- This IS NOT expected if you are initializing RobertaForTokenClassification from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).\n", + "[WARNING|modeling_utils.py:1513] 2021-07-19 15:25:34,071 >> Some weights of RobertaForTokenClassification were not initialized from the model checkpoint at bertin-project/bertin-base-stepwise and are newly initialized: ['classifier.bias', 'classifier.weight']\n", + "You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.\n", + "Running tokenizer on train dataset: 0% 0/9 [00:00> The following columns in the training set don't have a corresponding argument in `RobertaForTokenClassification.forward` and have been ignored: ner_tags, tokens, pos_tags, id.\n", + "[INFO|trainer.py:1162] 2021-07-19 15:25:45,883 >> ***** Running training *****\n", + "[INFO|trainer.py:1163] 2021-07-19 15:25:45,883 >> Num examples = 8324\n", + "[INFO|trainer.py:1164] 2021-07-19 15:25:45,883 >> Num Epochs = 5\n", + "[INFO|trainer.py:1165] 2021-07-19 15:25:45,883 >> Instantaneous batch size per device = 8\n", + "[INFO|trainer.py:1166] 2021-07-19 15:25:45,883 >> Total train batch size (w. parallel, distributed & accumulation) = 8\n", + "[INFO|trainer.py:1167] 2021-07-19 15:25:45,883 >> Gradient Accumulation steps = 1\n", + "[INFO|trainer.py:1168] 2021-07-19 15:25:45,883 >> Total optimization steps = 5205\n", + "[INFO|integrations.py:417] 2021-07-19 15:25:45,898 >> Automatic Weights & Biases logging enabled, to disable set os.environ[\"WANDB_DISABLED\"] = \"true\"\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Currently logged in as: \u001b[33mversae\u001b[0m (use `wandb login --relogin` to force relogin)\n", + "2021-07-19 15:25:47.566224: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Successfully opened dynamic library libcudart.so.11.0\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Tracking run with wandb version 0.11.0\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Syncing run \u001b[33m./outputs\u001b[0m\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: ⭐️ View project at \u001b[34m\u001b[4mhttps://wandb.ai/versae/bertin-eval\u001b[0m\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: 🚀 View run at \u001b[34m\u001b[4mhttps://wandb.ai/versae/bertin-eval/runs/2qatt290\u001b[0m\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Run data is saved locally in /content/wandb/run-20210719_152546-2qatt290\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Run `wandb offline` to turn off syncing.\n", + "\n", + " 10% 500/5205 [02:53<31:14, 2.51it/s]{'loss': 0.3355, 'learning_rate': 4.5196926032660905e-05, 'epoch': 0.48}\n", + "[INFO|trainer.py:1917] 2021-07-19 15:28:42,151 >> Saving model checkpoint to ./outputs/checkpoint-500\n", + "[INFO|configuration_utils.py:379] 2021-07-19 15:28:42,153 >> Configuration saved in ./outputs/checkpoint-500/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 15:28:43,613 >> Model weights saved in ./outputs/checkpoint-500/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 15:28:43,614 >> tokenizer config file saved in ./outputs/checkpoint-500/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 15:28:43,615 >> Special tokens file saved in ./outputs/checkpoint-500/special_tokens_map.json\n", + " 19% 1000/5205 [05:52<27:19, 2.56it/s]{'loss': 0.1163, 'learning_rate': 4.039385206532181e-05, 'epoch': 0.96}\n", + " 19% 1000/5205 [05:52<27:19, 2.56it/s][INFO|trainer.py:1917] 2021-07-19 15:31:41,087 >> Saving model checkpoint to ./outputs/checkpoint-1000\n", + "[INFO|configuration_utils.py:379] 2021-07-19 15:31:41,089 >> Configuration saved in ./outputs/checkpoint-1000/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 15:31:42,481 >> Model weights saved in ./outputs/checkpoint-1000/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 15:31:42,482 >> tokenizer config file saved in ./outputs/checkpoint-1000/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 15:31:42,482 >> Special tokens file saved in ./outputs/checkpoint-1000/special_tokens_map.json\n", + " 29% 1500/5205 [08:50<24:24, 2.53it/s]{'loss': 0.0776, 'learning_rate': 3.5590778097982716e-05, 'epoch': 1.44}\n", + " 29% 1500/5205 [08:50<24:24, 2.53it/s][INFO|trainer.py:1917] 2021-07-19 15:34:39,102 >> Saving model checkpoint to ./outputs/checkpoint-1500\n", + "[INFO|configuration_utils.py:379] 2021-07-19 15:34:39,104 >> Configuration saved in ./outputs/checkpoint-1500/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 15:34:40,663 >> Model weights saved in ./outputs/checkpoint-1500/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 15:34:40,664 >> tokenizer config file saved in ./outputs/checkpoint-1500/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 15:34:40,664 >> Special tokens file saved in ./outputs/checkpoint-1500/special_tokens_map.json\n", + " 38% 2000/5205 [11:48<20:47, 2.57it/s]{'loss': 0.0723, 'learning_rate': 3.078770413064361e-05, 'epoch': 1.92}\n", + "[INFO|trainer.py:1917] 2021-07-19 15:37:37,390 >> Saving model checkpoint to ./outputs/checkpoint-2000\n", + "[INFO|configuration_utils.py:379] 2021-07-19 15:37:37,395 >> Configuration saved in ./outputs/checkpoint-2000/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 15:37:38,782 >> Model weights saved in ./outputs/checkpoint-2000/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 15:37:38,783 >> tokenizer config file saved in ./outputs/checkpoint-2000/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 15:37:38,783 >> Special tokens file saved in ./outputs/checkpoint-2000/special_tokens_map.json\n", + " 48% 2500/5205 [14:46<17:39, 2.55it/s]{'loss': 0.0487, 'learning_rate': 2.5984630163304517e-05, 'epoch': 2.4}\n", + " 48% 2500/5205 [14:46<17:39, 2.55it/s][INFO|trainer.py:1917] 2021-07-19 15:40:35,202 >> Saving model checkpoint to ./outputs/checkpoint-2500\n", + "[INFO|configuration_utils.py:379] 2021-07-19 15:40:35,204 >> Configuration saved in ./outputs/checkpoint-2500/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 15:40:36,692 >> Model weights saved in ./outputs/checkpoint-2500/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 15:40:36,693 >> tokenizer config file saved in ./outputs/checkpoint-2500/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 15:40:36,693 >> Special tokens file saved in ./outputs/checkpoint-2500/special_tokens_map.json\n", + "{'loss': 0.044, 'learning_rate': 2.118155619596542e-05, 'epoch': 2.88}\n", + " 58% 3000/5205 [17:44<14:29, 2.54it/s][INFO|trainer.py:1917] 2021-07-19 15:43:33,536 >> Saving model checkpoint to ./outputs/checkpoint-3000\n", + "[INFO|configuration_utils.py:379] 2021-07-19 15:43:33,538 >> Configuration saved in ./outputs/checkpoint-3000/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 15:43:35,230 >> Model weights saved in ./outputs/checkpoint-3000/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 15:43:35,231 >> tokenizer config file saved in ./outputs/checkpoint-3000/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 15:43:35,231 >> Special tokens file saved in ./outputs/checkpoint-3000/special_tokens_map.json\n", + "{'loss': 0.0302, 'learning_rate': 1.6378482228626322e-05, 'epoch': 3.36}\n", + " 67% 3500/5205 [20:42<11:03, 2.57it/s][INFO|trainer.py:1917] 2021-07-19 15:46:31,314 >> Saving model checkpoint to ./outputs/checkpoint-3500\n", + "[INFO|configuration_utils.py:379] 2021-07-19 15:46:31,320 >> Configuration saved in ./outputs/checkpoint-3500/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 15:46:32,767 >> Model weights saved in ./outputs/checkpoint-3500/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 15:46:32,768 >> tokenizer config file saved in ./outputs/checkpoint-3500/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 15:46:32,768 >> Special tokens file saved in ./outputs/checkpoint-3500/special_tokens_map.json\n", + " 77% 4000/5205 [23:40<07:54, 2.54it/s]{'loss': 0.0264, 'learning_rate': 1.1575408261287224e-05, 'epoch': 3.84}\n", + "[INFO|trainer.py:1917] 2021-07-19 15:49:29,301 >> Saving model checkpoint to ./outputs/checkpoint-4000\n", + "[INFO|configuration_utils.py:379] 2021-07-19 15:49:29,304 >> Configuration saved in ./outputs/checkpoint-4000/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 15:49:30,796 >> Model weights saved in ./outputs/checkpoint-4000/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 15:49:30,863 >> tokenizer config file saved in ./outputs/checkpoint-4000/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 15:49:30,864 >> Special tokens file saved in ./outputs/checkpoint-4000/special_tokens_map.json\n", + " 86% 4500/5205 [26:38<04:34, 2.56it/s]{'loss': 0.0196, 'learning_rate': 6.7723342939481265e-06, 'epoch': 4.32}\n", + " 86% 4500/5205 [26:38<04:34, 2.56it/s][INFO|trainer.py:1917] 2021-07-19 15:52:27,009 >> Saving model checkpoint to ./outputs/checkpoint-4500\n", + "[INFO|configuration_utils.py:379] 2021-07-19 15:52:27,011 >> Configuration saved in ./outputs/checkpoint-4500/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 15:52:28,527 >> Model weights saved in ./outputs/checkpoint-4500/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 15:52:28,528 >> tokenizer config file saved in ./outputs/checkpoint-4500/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 15:52:28,528 >> Special tokens file saved in ./outputs/checkpoint-4500/special_tokens_map.json\n", + " 96% 5000/5205 [29:35<01:20, 2.55it/s]{'loss': 0.0157, 'learning_rate': 1.96926032660903e-06, 'epoch': 4.8}\n", + "[INFO|trainer.py:1917] 2021-07-19 15:55:24,733 >> Saving model checkpoint to ./outputs/checkpoint-5000\n", + "[INFO|configuration_utils.py:379] 2021-07-19 15:55:24,735 >> Configuration saved in ./outputs/checkpoint-5000/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 15:55:26,325 >> Model weights saved in ./outputs/checkpoint-5000/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 15:55:26,326 >> tokenizer config file saved in ./outputs/checkpoint-5000/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 15:55:26,326 >> Special tokens file saved in ./outputs/checkpoint-5000/special_tokens_map.json\n", + "100% 5205/5205 [30:52<00:00, 3.25it/s][INFO|trainer.py:1358] 2021-07-19 15:56:41,099 >> \n", + "\n", + "Training completed. Do not forget to share your model on huggingface.co/models =)\n", + "\n", + "\n", + "100% 5205/5205 [30:52<00:00, 3.25it/s]{'train_runtime': 1855.2157, 'train_samples_per_second': 22.434, 'train_steps_per_second': 2.806, 'train_loss': 0.07618391575662135, 'epoch': 5.0}\n", + "100% 5205/5205 [30:52<00:00, 2.81it/s]\n", + "[INFO|trainer.py:1917] 2021-07-19 15:56:41,107 >> Saving model checkpoint to ./outputs\n", + "[INFO|configuration_utils.py:379] 2021-07-19 15:56:41,111 >> Configuration saved in ./outputs/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 15:56:42,720 >> Model weights saved in ./outputs/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 15:56:42,721 >> tokenizer config file saved in ./outputs/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 15:56:42,721 >> Special tokens file saved in ./outputs/special_tokens_map.json\n", + "***** train metrics *****\n", + " epoch = 5.0\n", + " train_loss = 0.0762\n", + " train_runtime = 0:30:55.21\n", + " train_samples = 8324\n", + " train_samples_per_second = 22.434\n", + " train_steps_per_second = 2.806\n", + "[INFO|trainer.py:522] 2021-07-19 15:56:42,842 >> The following columns in the evaluation set don't have a corresponding argument in `RobertaForTokenClassification.forward` and have been ignored: ner_tags, tokens, pos_tags, id.\n", + "07/19/2021 15:56:42 - INFO - __main__ - *** Evaluate ***\n", + "[INFO|trainer.py:2163] 2021-07-19 15:56:42,919 >> ***** Running Evaluation *****\n", + "[INFO|trainer.py:2165] 2021-07-19 15:56:42,919 >> Num examples = 1916\n", + "[INFO|trainer.py:2168] 2021-07-19 15:56:42,919 >> Batch size = 8\n", + "100% 239/240 [00:24<00:00, 9.68it/s]/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: NC seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: 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be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Fp seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Fg seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: DA seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: AQ seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VAI seems not to be NE tag.\n", + " 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to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: PR seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: RG seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: CS seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: CC seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Fe seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Fx seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: DD seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VSI seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: PD seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VMG seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: P0 seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: PN seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VMM seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Fd seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: AO seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: DP seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: PP seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: PI seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VSS seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VAS seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: RN seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Fat seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Faa seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: DE seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VMS seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VSN seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VSP seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Fz seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: PT seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VAN seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VSG seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: PX seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: DT seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Fh seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VAP seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Fs seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VSM seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Y seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Fit seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Fia seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/v1.py:57: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n", + " _warn_prf(average, modifier, msg_start, len(result))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/v1.py:57: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n", + " _warn_prf(average, modifier, msg_start, len(result))\n", + "100% 240/240 [00:28<00:00, 8.47it/s]\n", + "***** eval metrics *****\n", + " epoch = 5.0\n", + " eval_accuracy = 0.9707\n", + " eval_f1 = 0.9656\n", + " eval_loss = 0.1244\n", + " eval_precision = 0.9659\n", + " eval_recall = 0.9653\n", + " eval_runtime = 0:00:28.46\n", + " eval_samples = 1916\n", + " eval_samples_per_second = 67.321\n", + " eval_steps_per_second = 8.433\n", + "\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Waiting for W&B process to finish, PID 1143\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Program ended successfully.\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: \n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Find user logs for this run at: /content/wandb/run-20210719_152546-2qatt290/logs/debug.log\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Find internal logs for this run at: /content/wandb/run-20210719_152546-2qatt290/logs/debug-internal.log\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Run summary:\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/loss 0.0157\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/learning_rate 0.0\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/epoch 5.0\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/global_step 5205\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: _runtime 1885\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: _timestamp 1626710231\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: _step 11\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_runtime 1855.2157\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_samples_per_second 22.434\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_steps_per_second 2.806\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/total_flos 1.08808736772096e+16\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_loss 0.07618\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/loss 0.12443\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/precision 0.96588\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/recall 0.96526\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/f1 0.96557\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/accuracy 0.97067\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/runtime 28.4605\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/samples_per_second 67.321\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/steps_per_second 8.433\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Run history:\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/loss █▃▂▂▂▂▁▁▁▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/learning_rate █▇▆▆▅▄▃▃▂▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/epoch ▁▂▂▃▄▅▅▆▇███\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/global_step ▁▂▂▃▄▅▅▆▇███\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: _runtime ▁▂▂▃▄▅▅▆▇███\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: _timestamp ▁▂▂▃▄▅▅▆▇███\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: _step ▁▂▂▃▄▄▅▅▆▇▇█\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_runtime ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_samples_per_second ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_steps_per_second ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/total_flos ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_loss ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/loss ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/precision ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/recall ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/f1 ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/accuracy ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/runtime ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/samples_per_second ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/steps_per_second ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: \n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Synced 5 W&B file(s), 0 media file(s), 0 artifact file(s) and 1 other file(s)\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: \n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Synced \u001b[33m./outputs\u001b[0m: \u001b[34mhttps://wandb.ai/versae/bertin-eval/runs/2qatt290\u001b[0m\n", + "2021-07-19 15:57:23.970722: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Successfully opened dynamic library libcudart.so.11.0\n", + "07/19/2021 15:57:26 - WARNING - __main__ - Process rank: -1, device: cuda:0, n_gpu: 1distributed training: False, 16-bits training: False\n", + "07/19/2021 15:57:26 - INFO - __main__ - Training/evaluation parameters TrainingArguments(\n", + "_n_gpu=1,\n", + "adafactor=False,\n", + "adam_beta1=0.9,\n", + "adam_beta2=0.999,\n", + "adam_epsilon=1e-08,\n", + "dataloader_drop_last=False,\n", + "dataloader_num_workers=0,\n", + "dataloader_pin_memory=True,\n", + "ddp_find_unused_parameters=None,\n", + "debug=[],\n", + "deepspeed=None,\n", + "disable_tqdm=False,\n", + "do_eval=True,\n", + "do_predict=False,\n", + "do_train=True,\n", + "eval_accumulation_steps=None,\n", + "eval_steps=500,\n", + "evaluation_strategy=IntervalStrategy.NO,\n", + "fp16=False,\n", + "fp16_backend=auto,\n", + "fp16_full_eval=False,\n", + "fp16_opt_level=O1,\n", + "gradient_accumulation_steps=1,\n", + "greater_is_better=None,\n", + "group_by_length=False,\n", + "ignore_data_skip=False,\n", + "label_names=None,\n", + "label_smoothing_factor=0.0,\n", + "learning_rate=5e-05,\n", + "length_column_name=length,\n", + "load_best_model_at_end=False,\n", + "local_rank=-1,\n", + "log_level=-1,\n", + "log_level_replica=-1,\n", + "log_on_each_node=True,\n", + "logging_dir=./outputs/runs/Jul19_15-57-26_eab5184de9ff,\n", + "logging_first_step=False,\n", + "logging_steps=500,\n", + "logging_strategy=IntervalStrategy.STEPS,\n", + "lr_scheduler_type=SchedulerType.LINEAR,\n", + "max_grad_norm=1.0,\n", + "max_steps=-1,\n", + "metric_for_best_model=None,\n", + "mp_parameters=,\n", + "no_cuda=False,\n", + "num_train_epochs=5.0,\n", + "output_dir=./outputs,\n", + "overwrite_output_dir=True,\n", + "past_index=-1,\n", + "per_device_eval_batch_size=8,\n", + "per_device_train_batch_size=8,\n", + "prediction_loss_only=False,\n", + "push_to_hub=False,\n", + "push_to_hub_model_id=outputs,\n", + "push_to_hub_organization=None,\n", + "push_to_hub_token=None,\n", + "remove_unused_columns=True,\n", + "report_to=['tensorboard', 'wandb'],\n", + "resume_from_checkpoint=None,\n", + "run_name=./outputs,\n", + "save_on_each_node=False,\n", + "save_steps=500,\n", + "save_strategy=IntervalStrategy.STEPS,\n", + "save_total_limit=None,\n", + "seed=42,\n", + "sharded_ddp=[],\n", + "skip_memory_metrics=True,\n", + "tpu_metrics_debug=False,\n", + "tpu_num_cores=None,\n", + "use_legacy_prediction_loop=False,\n", + "warmup_ratio=0.0,\n", + "warmup_steps=0,\n", + "weight_decay=0.0,\n", + ")\n", + "07/19/2021 15:57:28 - INFO - datasets.load - Found main folder for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py at /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002\n", + "07/19/2021 15:57:28 - INFO - datasets.load - Found specific version folder for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py at /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5\n", + "07/19/2021 15:57:28 - INFO - datasets.load - Found script file from https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py to /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5/conll2002.py\n", + "07/19/2021 15:57:28 - INFO - datasets.load - Found dataset infos file from https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/dataset_infos.json to /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5/dataset_infos.json\n", + "07/19/2021 15:57:28 - INFO - datasets.load - Found metadata file for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py at /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5/conll2002.json\n", + "07/19/2021 15:57:29 - INFO - datasets.load - Found main folder for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py at /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002\n", + "07/19/2021 15:57:29 - INFO - datasets.load - Found specific version folder for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py at /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5\n", + "07/19/2021 15:57:29 - INFO - datasets.load - Found script file from https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py to /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5/conll2002.py\n", + "07/19/2021 15:57:29 - INFO - datasets.load - Found dataset infos file from https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/dataset_infos.json to /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5/dataset_infos.json\n", + "07/19/2021 15:57:29 - INFO - datasets.load - Found metadata file for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py at /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5/conll2002.json\n", + "07/19/2021 15:57:29 - INFO - datasets.info - Loading Dataset Infos from /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5\n", + "07/19/2021 15:57:29 - INFO - datasets.builder - Overwrite dataset info from restored data version.\n", + "07/19/2021 15:57:29 - INFO - datasets.info - Loading Dataset info from /root/.cache/huggingface/datasets/conll2002/es/1.0.0/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5\n", + "07/19/2021 15:57:29 - WARNING - datasets.builder - Reusing dataset conll2002 (/root/.cache/huggingface/datasets/conll2002/es/1.0.0/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5)\n", + "07/19/2021 15:57:29 - INFO - datasets.info - Loading Dataset info from /root/.cache/huggingface/datasets/conll2002/es/1.0.0/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5\n", + "100% 3/3 [00:00<00:00, 26.12it/s]\n", + "[INFO|configuration_utils.py:545] 2021-07-19 15:57:30,060 >> loading configuration file https://huggingface.co/bertin-project/bertin-base-random/resolve/main/config.json from cache at /root/.cache/huggingface/transformers/206b1dac57f81203b68e667a852122cb8107d8f6ec61c5f61ff3911b995464bc.08210214ecaf5cd53c702826a604e564d8af557125033eef720f4f9f2af1fc44\n", + "[INFO|configuration_utils.py:581] 2021-07-19 15:57:30,061 >> Model config RobertaConfig {\n", + " \"architectures\": [\n", + " \"RobertaForMaskedLM\"\n", + " ],\n", + " \"attention_probs_dropout_prob\": 0.1,\n", + " \"bos_token_id\": 0,\n", + " \"eos_token_id\": 2,\n", + " \"finetuning_task\": \"pos\",\n", + " \"gradient_checkpointing\": false,\n", + " \"hidden_act\": \"gelu\",\n", + " \"hidden_dropout_prob\": 0.1,\n", + " \"hidden_size\": 768,\n", + " \"id2label\": {\n", + " \"0\": 0,\n", + " \"1\": 1,\n", + " \"2\": 2,\n", + " \"3\": 3,\n", + " \"4\": 4,\n", + " \"5\": 5,\n", + " \"6\": 6,\n", + " \"7\": 7,\n", + " \"8\": 8,\n", + " \"9\": 9,\n", + " \"10\": 10,\n", + " \"11\": 11,\n", + " \"12\": 12,\n", + " \"13\": 13,\n", + " \"14\": 14,\n", + " \"15\": 15,\n", + " \"16\": 16,\n", + " \"17\": 17,\n", + " \"18\": 18,\n", + " \"19\": 19,\n", + " \"20\": 20,\n", + " \"21\": 21,\n", + " \"22\": 22,\n", + " \"23\": 23,\n", + " \"24\": 24,\n", + " \"25\": 25,\n", + " \"26\": 26,\n", + " \"27\": 27,\n", + " \"28\": 28,\n", + " \"29\": 29,\n", + " \"30\": 30,\n", + " \"31\": 31,\n", + " \"32\": 32,\n", + " \"33\": 33,\n", + " \"34\": 34,\n", + " \"35\": 35,\n", + " \"36\": 36,\n", + " \"37\": 37,\n", + " \"38\": 38,\n", + " \"39\": 39,\n", + " \"40\": 40,\n", + " \"41\": 41,\n", + " \"42\": 42,\n", + " \"43\": 43,\n", + " \"44\": 44,\n", + " \"45\": 45,\n", + " \"46\": 46,\n", + " \"47\": 47,\n", + " \"48\": 48,\n", + " \"49\": 49,\n", + " \"50\": 50,\n", + " \"51\": 51,\n", + " \"52\": 52,\n", + " \"53\": 53,\n", + " \"54\": 54,\n", + " \"55\": 55,\n", + " \"56\": 56,\n", + " \"57\": 57,\n", + " \"58\": 58,\n", + " \"59\": 59\n", + " },\n", + " \"initializer_range\": 0.02,\n", + " \"intermediate_size\": 3072,\n", + " \"label2id\": {\n", + " \"0\": 0,\n", + " \"1\": 1,\n", + " \"2\": 2,\n", + " \"3\": 3,\n", + " \"4\": 4,\n", + " \"5\": 5,\n", + " \"6\": 6,\n", + " \"7\": 7,\n", + " \"8\": 8,\n", + " \"9\": 9,\n", + " \"10\": 10,\n", + " \"11\": 11,\n", + " \"12\": 12,\n", + " \"13\": 13,\n", + " \"14\": 14,\n", + " \"15\": 15,\n", + " \"16\": 16,\n", + " \"17\": 17,\n", + " \"18\": 18,\n", + " \"19\": 19,\n", + " \"20\": 20,\n", + " \"21\": 21,\n", + " \"22\": 22,\n", + " \"23\": 23,\n", + " \"24\": 24,\n", + " \"25\": 25,\n", + " \"26\": 26,\n", + " \"27\": 27,\n", + " \"28\": 28,\n", + " \"29\": 29,\n", + " \"30\": 30,\n", + " \"31\": 31,\n", + " \"32\": 32,\n", + " \"33\": 33,\n", + " \"34\": 34,\n", + " \"35\": 35,\n", + " \"36\": 36,\n", + " \"37\": 37,\n", + " \"38\": 38,\n", + " \"39\": 39,\n", + " \"40\": 40,\n", + " \"41\": 41,\n", + " \"42\": 42,\n", + " \"43\": 43,\n", + " \"44\": 44,\n", + " \"45\": 45,\n", + " \"46\": 46,\n", + " \"47\": 47,\n", + " \"48\": 48,\n", + " \"49\": 49,\n", + " \"50\": 50,\n", + " \"51\": 51,\n", + " \"52\": 52,\n", + " \"53\": 53,\n", + " \"54\": 54,\n", + " \"55\": 55,\n", + " \"56\": 56,\n", + " \"57\": 57,\n", + " \"58\": 58,\n", + " \"59\": 59\n", + " },\n", + " \"layer_norm_eps\": 1e-05,\n", + " \"max_position_embeddings\": 514,\n", + " \"model_type\": \"roberta\",\n", + " \"num_attention_heads\": 12,\n", + " \"num_hidden_layers\": 12,\n", + " \"pad_token_id\": 1,\n", + " \"position_embedding_type\": \"absolute\",\n", + " \"transformers_version\": \"4.9.0.dev0\",\n", + " \"type_vocab_size\": 1,\n", + " \"use_cache\": true,\n", + " \"vocab_size\": 50265\n", + "}\n", + "\n", + "[INFO|tokenization_utils_base.py:1722] 2021-07-19 15:57:35,215 >> loading file https://huggingface.co/bertin-project/bertin-base-random/resolve/main/vocab.json from cache at /root/.cache/huggingface/transformers/b4006ecc1f0c7264bbecc09c6cb89b65ec7db509c3c0604de97e88f24ea4d1f6.a80f232f572026f92499b14999a8ed4e044e04cf3d01b9f2be298c98e78e8498\n", + "[INFO|tokenization_utils_base.py:1722] 2021-07-19 15:57:35,215 >> loading file https://huggingface.co/bertin-project/bertin-base-random/resolve/main/merges.txt from cache at /root/.cache/huggingface/transformers/edf6b87725489a8b69bfa2267d17e097798faa72e64ff4c5cc3d18672be1064c.a0dfc41f9d0f03a56ba7a5401d770f6e43071045a0bd79073380d408d17a0d92\n", + "[INFO|tokenization_utils_base.py:1722] 2021-07-19 15:57:35,216 >> loading file https://huggingface.co/bertin-project/bertin-base-random/resolve/main/tokenizer.json from cache at /root/.cache/huggingface/transformers/a2564e0d9105fa93a9e315cbeba7570df09180efa1d54facf9770aa67f46bfe6.2a5dc806edc00ab3a329cb22b9973596ca75b24ba0e5e4963bf1308de7237a3d\n", + "[INFO|tokenization_utils_base.py:1722] 2021-07-19 15:57:35,216 >> loading file https://huggingface.co/bertin-project/bertin-base-random/resolve/main/added_tokens.json from cache at None\n", + "[INFO|tokenization_utils_base.py:1722] 2021-07-19 15:57:35,216 >> loading file https://huggingface.co/bertin-project/bertin-base-random/resolve/main/special_tokens_map.json from cache at /root/.cache/huggingface/transformers/92bfdce86055cda7484e6cda39edf00079de963108ce7a53ac914029100d8a99.a11ebb04664c067c8fe5ef8f8068b0f721263414a26058692f7b2e4ba2a1b342\n", + "[INFO|tokenization_utils_base.py:1722] 2021-07-19 15:57:35,216 >> loading file https://huggingface.co/bertin-project/bertin-base-random/resolve/main/tokenizer_config.json from cache at /root/.cache/huggingface/transformers/115b6bf4f08e65d03dda82a834c42cf46339813770aadf59679bd51d0f2ea3a5.9f7ac4246b492dfa7c21beb5233deec8aef46153ec25ac5258ac5e2ae82dfa89\n", + "[INFO|modeling_utils.py:1271] 2021-07-19 15:57:36,040 >> loading weights file https://huggingface.co/bertin-project/bertin-base-random/resolve/main/pytorch_model.bin from cache at /root/.cache/huggingface/transformers/5bec117e97fb2ec50c8615b1e2cde784a5851d7664417aa49e21403f91722df2.fc71d0bf8be2b57b708f6397729f6f12e8e95a3e69e8a44030293be69ee5bc0d\n", + "[WARNING|modeling_utils.py:1502] 2021-07-19 15:57:44,020 >> Some weights of the model checkpoint at bertin-project/bertin-base-random were not used when initializing RobertaForTokenClassification: ['lm_head.dense.weight', 'lm_head.bias', 'lm_head.layer_norm.bias', 'lm_head.dense.bias', 'lm_head.layer_norm.weight']\n", + "- This IS expected if you are initializing RobertaForTokenClassification from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).\n", + "- This IS NOT expected if you are initializing RobertaForTokenClassification from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).\n", + "[WARNING|modeling_utils.py:1513] 2021-07-19 15:57:44,020 >> Some weights of RobertaForTokenClassification were not initialized from the model checkpoint at bertin-project/bertin-base-random and are newly initialized: ['classifier.weight', 'classifier.bias']\n", + "You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.\n", + "Running tokenizer on train dataset: 0% 0/9 [00:00> The following columns in the training set don't have a corresponding argument in `RobertaForTokenClassification.forward` and have been ignored: tokens, ner_tags, id, pos_tags.\n", + "[INFO|trainer.py:1162] 2021-07-19 15:57:55,686 >> ***** Running training *****\n", + "[INFO|trainer.py:1163] 2021-07-19 15:57:55,686 >> Num examples = 8324\n", + "[INFO|trainer.py:1164] 2021-07-19 15:57:55,686 >> Num Epochs = 5\n", + "[INFO|trainer.py:1165] 2021-07-19 15:57:55,687 >> Instantaneous batch size per device = 8\n", + "[INFO|trainer.py:1166] 2021-07-19 15:57:55,687 >> Total train batch size (w. parallel, distributed & accumulation) = 8\n", + "[INFO|trainer.py:1167] 2021-07-19 15:57:55,687 >> Gradient Accumulation steps = 1\n", + "[INFO|trainer.py:1168] 2021-07-19 15:57:55,687 >> Total optimization steps = 5205\n", + "[INFO|integrations.py:417] 2021-07-19 15:57:55,705 >> Automatic Weights & Biases logging enabled, to disable set os.environ[\"WANDB_DISABLED\"] = \"true\"\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Currently logged in as: \u001b[33mversae\u001b[0m (use `wandb login --relogin` to force relogin)\n", + "2021-07-19 15:57:57.309125: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Successfully opened dynamic library libcudart.so.11.0\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Tracking run with wandb version 0.11.0\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Syncing run \u001b[33m./outputs\u001b[0m\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: ⭐️ View project at \u001b[34m\u001b[4mhttps://wandb.ai/versae/bertin-eval\u001b[0m\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: 🚀 View run at \u001b[34m\u001b[4mhttps://wandb.ai/versae/bertin-eval/runs/21v515t2\u001b[0m\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Run data is saved locally in /content/wandb/run-20210719_155755-21v515t2\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Run `wandb offline` to turn off syncing.\n", + "\n", + " 10% 500/5205 [02:53<30:46, 2.55it/s]{'loss': 0.3451, 'learning_rate': 4.5196926032660905e-05, 'epoch': 0.48}\n", + " 10% 500/5205 [02:53<30:46, 2.55it/s][INFO|trainer.py:1917] 2021-07-19 16:00:52,060 >> Saving model checkpoint to ./outputs/checkpoint-500\n", + "[INFO|configuration_utils.py:379] 2021-07-19 16:00:52,062 >> Configuration saved in ./outputs/checkpoint-500/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 16:00:53,570 >> Model weights saved in ./outputs/checkpoint-500/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 16:00:53,571 >> tokenizer config file saved in ./outputs/checkpoint-500/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 16:00:53,571 >> Special tokens file saved in ./outputs/checkpoint-500/special_tokens_map.json\n", + "{'loss': 0.1204, 'learning_rate': 4.039385206532181e-05, 'epoch': 0.96}\n", + " 19% 1000/5205 [05:52<27:33, 2.54it/s][INFO|trainer.py:1917] 2021-07-19 16:03:50,729 >> Saving model checkpoint to ./outputs/checkpoint-1000\n", + "[INFO|configuration_utils.py:379] 2021-07-19 16:03:50,731 >> Configuration saved in ./outputs/checkpoint-1000/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 16:03:52,169 >> Model weights saved in ./outputs/checkpoint-1000/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 16:03:52,170 >> tokenizer config file saved in ./outputs/checkpoint-1000/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 16:03:52,171 >> Special tokens file saved in ./outputs/checkpoint-1000/special_tokens_map.json\n", + "{'loss': 0.0793, 'learning_rate': 3.5590778097982716e-05, 'epoch': 1.44}\n", + " 29% 1500/5205 [08:50<24:07, 2.56it/s][INFO|trainer.py:1917] 2021-07-19 16:06:48,737 >> Saving model checkpoint to ./outputs/checkpoint-1500\n", + "[INFO|configuration_utils.py:379] 2021-07-19 16:06:48,738 >> Configuration saved in ./outputs/checkpoint-1500/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 16:06:50,181 >> Model weights saved in ./outputs/checkpoint-1500/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 16:06:50,182 >> tokenizer config file saved in ./outputs/checkpoint-1500/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 16:06:50,182 >> Special tokens file saved in ./outputs/checkpoint-1500/special_tokens_map.json\n", + "{'loss': 0.0726, 'learning_rate': 3.078770413064361e-05, 'epoch': 1.92}\n", + " 38% 2000/5205 [11:48<20:46, 2.57it/s][INFO|trainer.py:1917] 2021-07-19 16:09:46,782 >> Saving model checkpoint to ./outputs/checkpoint-2000\n", + "[INFO|configuration_utils.py:379] 2021-07-19 16:09:46,784 >> Configuration saved in ./outputs/checkpoint-2000/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 16:09:48,219 >> Model weights saved in ./outputs/checkpoint-2000/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 16:09:48,220 >> tokenizer config file saved in ./outputs/checkpoint-2000/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 16:09:48,220 >> Special tokens file saved in ./outputs/checkpoint-2000/special_tokens_map.json\n", + " 48% 2500/5205 [14:46<17:47, 2.54it/s][INFO|trainer.py:1917] 2021-07-19 16:12:44,588 >> Saving model checkpoint to ./outputs/checkpoint-2500\n", + "{'loss': 0.0491, 'learning_rate': 2.5984630163304517e-05, 'epoch': 2.4}\n", + "[INFO|configuration_utils.py:379] 2021-07-19 16:12:44,590 >> Configuration saved in ./outputs/checkpoint-2500/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 16:12:46,083 >> Model weights saved in ./outputs/checkpoint-2500/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 16:12:46,084 >> tokenizer config file saved in ./outputs/checkpoint-2500/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 16:12:46,085 >> Special tokens file saved in ./outputs/checkpoint-2500/special_tokens_map.json\n", + " 58% 3000/5205 [17:43<14:24, 2.55it/s]{'loss': 0.0442, 'learning_rate': 2.118155619596542e-05, 'epoch': 2.88}\n", + " 58% 3000/5205 [17:43<14:24, 2.55it/s][INFO|trainer.py:1917] 2021-07-19 16:15:42,327 >> Saving model checkpoint to ./outputs/checkpoint-3000\n", + "[INFO|configuration_utils.py:379] 2021-07-19 16:15:42,329 >> Configuration saved in ./outputs/checkpoint-3000/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 16:15:44,005 >> Model weights saved in ./outputs/checkpoint-3000/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 16:15:44,005 >> tokenizer config file saved in ./outputs/checkpoint-3000/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 16:15:44,006 >> Special tokens file saved in ./outputs/checkpoint-3000/special_tokens_map.json\n", + " 67% 3500/5205 [20:40<11:11, 2.54it/s]{'loss': 0.0297, 'learning_rate': 1.6378482228626322e-05, 'epoch': 3.36}\n", + " 67% 3500/5205 [20:40<11:11, 2.54it/s][INFO|trainer.py:1917] 2021-07-19 16:18:39,550 >> Saving model checkpoint to ./outputs/checkpoint-3500\n", + "[INFO|configuration_utils.py:379] 2021-07-19 16:18:39,552 >> Configuration saved in ./outputs/checkpoint-3500/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 16:18:40,968 >> Model weights saved in ./outputs/checkpoint-3500/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 16:18:40,969 >> tokenizer config file saved in ./outputs/checkpoint-3500/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 16:18:40,969 >> Special tokens file saved in ./outputs/checkpoint-3500/special_tokens_map.json\n", + "{'loss': 0.0248, 'learning_rate': 1.1575408261287224e-05, 'epoch': 3.84}\n", + " 77% 4000/5205 [23:38<07:51, 2.56it/s][INFO|trainer.py:1917] 2021-07-19 16:21:37,282 >> Saving model checkpoint to ./outputs/checkpoint-4000\n", + "[INFO|configuration_utils.py:379] 2021-07-19 16:21:37,284 >> Configuration saved in ./outputs/checkpoint-4000/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 16:21:38,766 >> Model weights saved in ./outputs/checkpoint-4000/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 16:21:38,767 >> tokenizer config file saved in ./outputs/checkpoint-4000/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 16:21:38,768 >> Special tokens file saved in ./outputs/checkpoint-4000/special_tokens_map.json\n", + " 86% 4500/5205 [26:35<04:32, 2.58it/s]{'loss': 0.0199, 'learning_rate': 6.7723342939481265e-06, 'epoch': 4.32}\n", + " 86% 4500/5205 [26:35<04:32, 2.58it/s][INFO|trainer.py:1917] 2021-07-19 16:24:34,468 >> Saving model checkpoint to ./outputs/checkpoint-4500\n", + "[INFO|configuration_utils.py:379] 2021-07-19 16:24:34,470 >> Configuration saved in ./outputs/checkpoint-4500/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 16:24:36,130 >> Model weights saved in ./outputs/checkpoint-4500/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 16:24:36,131 >> tokenizer config file saved in ./outputs/checkpoint-4500/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 16:24:36,132 >> Special tokens file saved in ./outputs/checkpoint-4500/special_tokens_map.json\n", + " 96% 5000/5205 [29:33<01:20, 2.54it/s]{'loss': 0.0159, 'learning_rate': 1.96926032660903e-06, 'epoch': 4.8}\n", + "[INFO|trainer.py:1917] 2021-07-19 16:27:32,111 >> Saving model checkpoint to ./outputs/checkpoint-5000\n", + "[INFO|configuration_utils.py:379] 2021-07-19 16:27:32,117 >> Configuration saved in ./outputs/checkpoint-5000/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 16:27:33,589 >> Model weights saved in ./outputs/checkpoint-5000/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 16:27:33,590 >> tokenizer config file saved in ./outputs/checkpoint-5000/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 16:27:33,591 >> Special tokens file saved in ./outputs/checkpoint-5000/special_tokens_map.json\n", + "100% 5205/5205 [30:49<00:00, 3.24it/s][INFO|trainer.py:1358] 2021-07-19 16:28:48,288 >> \n", + "\n", + "Training completed. Do not forget to share your model on huggingface.co/models =)\n", + "\n", + "\n", + "100% 5205/5205 [30:49<00:00, 3.24it/s]{'train_runtime': 1852.6013, 'train_samples_per_second': 22.466, 'train_steps_per_second': 2.81, 'train_loss': 0.07757037586025271, 'epoch': 5.0}\n", + "100% 5205/5205 [30:49<00:00, 2.81it/s]\n", + "[INFO|trainer.py:1917] 2021-07-19 16:28:48,294 >> Saving model checkpoint to ./outputs\n", + "[INFO|configuration_utils.py:379] 2021-07-19 16:28:48,299 >> Configuration saved in ./outputs/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 16:28:49,924 >> Model weights saved in ./outputs/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 16:28:49,925 >> tokenizer config file saved in ./outputs/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 16:28:49,925 >> Special tokens file saved in ./outputs/special_tokens_map.json\n", + "***** train metrics *****\n", + " epoch = 5.0\n", + " train_loss = 0.0776\n", + " train_runtime = 0:30:52.60\n", + " train_samples = 8324\n", + " train_samples_per_second = 22.466\n", + " train_steps_per_second = 2.81\n", + "07/19/2021 16:28:50 - INFO - __main__ - *** Evaluate ***\n", + "[INFO|trainer.py:522] 2021-07-19 16:28:50,053 >> The following columns in the evaluation set don't have a corresponding argument in `RobertaForTokenClassification.forward` and have been ignored: tokens, ner_tags, id, pos_tags.\n", + "[INFO|trainer.py:2163] 2021-07-19 16:28:50,189 >> ***** Running Evaluation *****\n", + "[INFO|trainer.py:2165] 2021-07-19 16:28:50,189 >> Num examples = 1916\n", + "[INFO|trainer.py:2168] 2021-07-19 16:28:50,189 >> Batch size = 8\n", + "100% 239/240 [00:24<00:00, 9.66it/s]/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: NC seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: 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"/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: P0 seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: PN seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VMM seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Fd seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: AO seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: DP seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: PP seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: PI seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VSS seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VAS seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: RN seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Fat seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Faa seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: DE seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VMS seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VSN seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VSP seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Fz seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: PT seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VAN seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VSG seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: PX seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: DT seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Fh seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VAP seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Fs seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VSM seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Y seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Fia seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Fit seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/v1.py:57: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n", + " _warn_prf(average, modifier, msg_start, len(result))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/v1.py:57: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n", + " _warn_prf(average, modifier, msg_start, len(result))\n", + "100% 240/240 [00:28<00:00, 8.48it/s]\n", + "***** eval metrics *****\n", + " epoch = 5.0\n", + " eval_accuracy = 0.9704\n", + " eval_f1 = 0.9656\n", + " eval_loss = 0.1342\n", + " eval_precision = 0.9662\n", + " eval_recall = 0.9651\n", + " eval_runtime = 0:00:28.41\n", + " eval_samples = 1916\n", + " eval_samples_per_second = 67.437\n", + " eval_steps_per_second = 8.447\n", + "\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Waiting for W&B process to finish, PID 1207\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Program ended successfully.\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: \n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Find user logs for this run at: /content/wandb/run-20210719_155755-21v515t2/logs/debug.log\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Find internal logs for this run at: /content/wandb/run-20210719_155755-21v515t2/logs/debug-internal.log\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Run summary:\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/loss 0.0159\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/learning_rate 0.0\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/epoch 5.0\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/global_step 5205\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: _runtime 1882\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: _timestamp 1626712158\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: _step 11\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_runtime 1852.6013\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_samples_per_second 22.466\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_steps_per_second 2.81\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/total_flos 1.08808736772096e+16\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_loss 0.07757\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/loss 0.13416\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/precision 0.96616\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/recall 0.96507\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/f1 0.96561\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/accuracy 0.97043\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/runtime 28.4118\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/samples_per_second 67.437\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/steps_per_second 8.447\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Run history:\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/loss █▃▂▂▂▂▁▁▁▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/learning_rate █▇▆▆▅▄▃▃▂▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/epoch ▁▂▂▃▄▅▅▆▇███\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/global_step ▁▂▂▃▄▅▅▆▇███\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: _runtime ▁▂▂▃▄▅▅▆▇███\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: _timestamp ▁▂▂▃▄▅▅▆▇███\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: _step ▁▂▂▃▄▄▅▅▆▇▇█\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_runtime ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_samples_per_second ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_steps_per_second ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/total_flos ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_loss ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/loss ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/precision ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/recall ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/f1 ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/accuracy ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/runtime ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/samples_per_second ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/steps_per_second ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: \n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Synced 5 W&B file(s), 0 media file(s), 0 artifact file(s) and 1 other file(s)\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: \n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Synced \u001b[33m./outputs\u001b[0m: \u001b[34mhttps://wandb.ai/versae/bertin-eval/runs/21v515t2\u001b[0m\n", + "2021-07-19 16:29:31.414800: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Successfully opened dynamic library libcudart.so.11.0\n", + "07/19/2021 16:29:34 - WARNING - __main__ - Process rank: -1, device: cuda:0, n_gpu: 1distributed training: False, 16-bits training: False\n", + "07/19/2021 16:29:34 - INFO - __main__ - Training/evaluation parameters TrainingArguments(\n", + "_n_gpu=1,\n", + "adafactor=False,\n", + "adam_beta1=0.9,\n", + "adam_beta2=0.999,\n", + "adam_epsilon=1e-08,\n", + "dataloader_drop_last=False,\n", + "dataloader_num_workers=0,\n", + "dataloader_pin_memory=True,\n", + "ddp_find_unused_parameters=None,\n", + "debug=[],\n", + "deepspeed=None,\n", + "disable_tqdm=False,\n", + "do_eval=True,\n", + "do_predict=False,\n", + "do_train=True,\n", + "eval_accumulation_steps=None,\n", + "eval_steps=500,\n", + "evaluation_strategy=IntervalStrategy.NO,\n", + "fp16=False,\n", + "fp16_backend=auto,\n", + "fp16_full_eval=False,\n", + "fp16_opt_level=O1,\n", + "gradient_accumulation_steps=1,\n", + "greater_is_better=None,\n", + "group_by_length=False,\n", + "ignore_data_skip=False,\n", + "label_names=None,\n", + "label_smoothing_factor=0.0,\n", + "learning_rate=5e-05,\n", + "length_column_name=length,\n", + "load_best_model_at_end=False,\n", + "local_rank=-1,\n", + "log_level=-1,\n", + "log_level_replica=-1,\n", + "log_on_each_node=True,\n", + "logging_dir=./outputs/runs/Jul19_16-29-34_eab5184de9ff,\n", + "logging_first_step=False,\n", + "logging_steps=500,\n", + "logging_strategy=IntervalStrategy.STEPS,\n", + "lr_scheduler_type=SchedulerType.LINEAR,\n", + "max_grad_norm=1.0,\n", + "max_steps=-1,\n", + "metric_for_best_model=None,\n", + "mp_parameters=,\n", + "no_cuda=False,\n", + "num_train_epochs=5.0,\n", + "output_dir=./outputs,\n", + "overwrite_output_dir=True,\n", + "past_index=-1,\n", + "per_device_eval_batch_size=8,\n", + "per_device_train_batch_size=8,\n", + "prediction_loss_only=False,\n", + "push_to_hub=False,\n", + "push_to_hub_model_id=outputs,\n", + "push_to_hub_organization=None,\n", + "push_to_hub_token=None,\n", + "remove_unused_columns=True,\n", + "report_to=['tensorboard', 'wandb'],\n", + "resume_from_checkpoint=None,\n", + "run_name=./outputs,\n", + "save_on_each_node=False,\n", + "save_steps=500,\n", + "save_strategy=IntervalStrategy.STEPS,\n", + "save_total_limit=None,\n", + "seed=42,\n", + "sharded_ddp=[],\n", + "skip_memory_metrics=True,\n", + "tpu_metrics_debug=False,\n", + "tpu_num_cores=None,\n", + "use_legacy_prediction_loop=False,\n", + "warmup_ratio=0.0,\n", + "warmup_steps=0,\n", + "weight_decay=0.0,\n", + ")\n", + "07/19/2021 16:29:35 - INFO - datasets.load - Found main folder for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py at /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002\n", + "07/19/2021 16:29:35 - INFO - datasets.load - Found specific version folder for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py at /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5\n", + "07/19/2021 16:29:35 - INFO - datasets.load - Found script file from https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py to /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5/conll2002.py\n", + "07/19/2021 16:29:35 - INFO - datasets.load - Found dataset infos file from https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/dataset_infos.json to /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5/dataset_infos.json\n", + "07/19/2021 16:29:35 - INFO - datasets.load - Found metadata file for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py at /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5/conll2002.json\n", + "07/19/2021 16:29:36 - INFO - datasets.load - Found main folder for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py at /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002\n", + "07/19/2021 16:29:36 - INFO - datasets.load - Found specific version folder for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py at /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5\n", + "07/19/2021 16:29:36 - INFO - datasets.load - Found script file from https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py to /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5/conll2002.py\n", + "07/19/2021 16:29:36 - INFO - datasets.load - Found dataset infos file from https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/dataset_infos.json to /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5/dataset_infos.json\n", + "07/19/2021 16:29:36 - INFO - datasets.load - Found metadata file for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py at /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5/conll2002.json\n", + "07/19/2021 16:29:36 - INFO - datasets.info - Loading Dataset Infos from /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5\n", + "07/19/2021 16:29:36 - INFO - datasets.builder - Overwrite dataset info from restored data version.\n", + "07/19/2021 16:29:36 - INFO - datasets.info - Loading Dataset info from /root/.cache/huggingface/datasets/conll2002/es/1.0.0/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5\n", + "07/19/2021 16:29:36 - WARNING - datasets.builder - Reusing dataset conll2002 (/root/.cache/huggingface/datasets/conll2002/es/1.0.0/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5)\n", + "07/19/2021 16:29:36 - INFO - datasets.info - Loading Dataset info from /root/.cache/huggingface/datasets/conll2002/es/1.0.0/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5\n", + "100% 3/3 [00:00<00:00, 27.90it/s]\n", + "[INFO|configuration_utils.py:545] 2021-07-19 16:29:37,792 >> loading configuration file https://huggingface.co/bertin-project/bertin-roberta-base-spanish/resolve/main/config.json from cache at /root/.cache/huggingface/transformers/aa24361f0b7bed62876f6cd0a784a2b622c1959523906d89eeb1112139a4864a.08210214ecaf5cd53c702826a604e564d8af557125033eef720f4f9f2af1fc44\n", + "[INFO|configuration_utils.py:581] 2021-07-19 16:29:37,793 >> Model config RobertaConfig {\n", + " \"architectures\": [\n", + " \"RobertaForMaskedLM\"\n", + " ],\n", + " \"attention_probs_dropout_prob\": 0.1,\n", + " \"bos_token_id\": 0,\n", + " \"eos_token_id\": 2,\n", + " \"finetuning_task\": \"pos\",\n", + " \"gradient_checkpointing\": false,\n", + " \"hidden_act\": \"gelu\",\n", + " \"hidden_dropout_prob\": 0.1,\n", + " \"hidden_size\": 768,\n", + " \"id2label\": {\n", + " \"0\": 0,\n", + " \"1\": 1,\n", + " \"2\": 2,\n", + " \"3\": 3,\n", + " \"4\": 4,\n", + " \"5\": 5,\n", + " \"6\": 6,\n", + " \"7\": 7,\n", + " \"8\": 8,\n", + " \"9\": 9,\n", + " \"10\": 10,\n", + " \"11\": 11,\n", + " \"12\": 12,\n", + " \"13\": 13,\n", + " \"14\": 14,\n", + " \"15\": 15,\n", + " \"16\": 16,\n", + " \"17\": 17,\n", + " \"18\": 18,\n", + " \"19\": 19,\n", + " \"20\": 20,\n", + " \"21\": 21,\n", + " \"22\": 22,\n", + " \"23\": 23,\n", + " \"24\": 24,\n", + " \"25\": 25,\n", + " \"26\": 26,\n", + " \"27\": 27,\n", + " \"28\": 28,\n", + " \"29\": 29,\n", + " \"30\": 30,\n", + " \"31\": 31,\n", + " \"32\": 32,\n", + " \"33\": 33,\n", + " \"34\": 34,\n", + " \"35\": 35,\n", + " \"36\": 36,\n", + " \"37\": 37,\n", + " \"38\": 38,\n", + " \"39\": 39,\n", + " \"40\": 40,\n", + " \"41\": 41,\n", + " \"42\": 42,\n", + " \"43\": 43,\n", + " \"44\": 44,\n", + " \"45\": 45,\n", + " \"46\": 46,\n", + " \"47\": 47,\n", + " \"48\": 48,\n", + " \"49\": 49,\n", + " \"50\": 50,\n", + " \"51\": 51,\n", + " \"52\": 52,\n", + " \"53\": 53,\n", + " \"54\": 54,\n", + " \"55\": 55,\n", + " \"56\": 56,\n", + " \"57\": 57,\n", + " \"58\": 58,\n", + " \"59\": 59\n", + " },\n", + " \"initializer_range\": 0.02,\n", + " \"intermediate_size\": 3072,\n", + " \"label2id\": {\n", + " \"0\": 0,\n", + " \"1\": 1,\n", + " \"2\": 2,\n", + " \"3\": 3,\n", + " \"4\": 4,\n", + " \"5\": 5,\n", + " \"6\": 6,\n", + " \"7\": 7,\n", + " \"8\": 8,\n", + " \"9\": 9,\n", + " \"10\": 10,\n", + " \"11\": 11,\n", + " \"12\": 12,\n", + " \"13\": 13,\n", + " \"14\": 14,\n", + " \"15\": 15,\n", + " \"16\": 16,\n", + " \"17\": 17,\n", + " \"18\": 18,\n", + " \"19\": 19,\n", + " \"20\": 20,\n", + " \"21\": 21,\n", + " \"22\": 22,\n", + " \"23\": 23,\n", + " \"24\": 24,\n", + " \"25\": 25,\n", + " \"26\": 26,\n", + " \"27\": 27,\n", + " \"28\": 28,\n", + " \"29\": 29,\n", + " \"30\": 30,\n", + " \"31\": 31,\n", + " \"32\": 32,\n", + " \"33\": 33,\n", + " \"34\": 34,\n", + " \"35\": 35,\n", + " \"36\": 36,\n", + " \"37\": 37,\n", + " \"38\": 38,\n", + " \"39\": 39,\n", + " \"40\": 40,\n", + " \"41\": 41,\n", + " \"42\": 42,\n", + " \"43\": 43,\n", + " \"44\": 44,\n", + " \"45\": 45,\n", + " \"46\": 46,\n", + " \"47\": 47,\n", + " \"48\": 48,\n", + " \"49\": 49,\n", + " \"50\": 50,\n", + " \"51\": 51,\n", + " \"52\": 52,\n", + " \"53\": 53,\n", + " \"54\": 54,\n", + " \"55\": 55,\n", + " \"56\": 56,\n", + " \"57\": 57,\n", + " \"58\": 58,\n", + " \"59\": 59\n", + " },\n", + " \"layer_norm_eps\": 1e-05,\n", + " \"max_position_embeddings\": 514,\n", + " \"model_type\": \"roberta\",\n", + " \"num_attention_heads\": 12,\n", + " \"num_hidden_layers\": 12,\n", + " \"pad_token_id\": 1,\n", + " \"position_embedding_type\": \"absolute\",\n", + " \"transformers_version\": \"4.9.0.dev0\",\n", + " \"type_vocab_size\": 1,\n", + " \"use_cache\": true,\n", + " \"vocab_size\": 50265\n", + "}\n", + "\n", + "[INFO|tokenization_utils_base.py:1722] 2021-07-19 16:29:42,916 >> loading file https://huggingface.co/bertin-project/bertin-roberta-base-spanish/resolve/main/vocab.json from cache at /root/.cache/huggingface/transformers/f47efb87887425ef9a4ef795bfaa907d57ac9a650d733c7ca621b9eced3235e8.af6be2925520943ae92cd64250bdaa83a8c9d6f91422efbac7ed33a20e0b6e1b\n", + "[INFO|tokenization_utils_base.py:1722] 2021-07-19 16:29:42,916 >> loading file https://huggingface.co/bertin-project/bertin-roberta-base-spanish/resolve/main/merges.txt from cache at /root/.cache/huggingface/transformers/aba9e0895dea47dd4208a36012ffd3eb21eb4c5f7ce0be6547afb37cdd4ddef4.360a60d1c13cbafd862a8e2a85b267c2b3eb0226d5469633a889b33ba0dde234\n", + "[INFO|tokenization_utils_base.py:1722] 2021-07-19 16:29:42,916 >> loading file https://huggingface.co/bertin-project/bertin-roberta-base-spanish/resolve/main/tokenizer.json from cache at /root/.cache/huggingface/transformers/baad57d0f574d3e660cafb14601d0ecebe83f25071d59f3e51d225d75285b773.0803a0fadc521f273c2682a34dc285f90fe9de9e932bbe77401d11672f7fcb60\n", + "[INFO|tokenization_utils_base.py:1722] 2021-07-19 16:29:42,916 >> loading file https://huggingface.co/bertin-project/bertin-roberta-base-spanish/resolve/main/added_tokens.json from cache at None\n", + "[INFO|tokenization_utils_base.py:1722] 2021-07-19 16:29:42,916 >> loading file https://huggingface.co/bertin-project/bertin-roberta-base-spanish/resolve/main/special_tokens_map.json from cache at /root/.cache/huggingface/transformers/68d1fdfe72fdcac403d8f363239c379d8125162f50a954030c4476982f88d69e.a11ebb04664c067c8fe5ef8f8068b0f721263414a26058692f7b2e4ba2a1b342\n", + "[INFO|tokenization_utils_base.py:1722] 2021-07-19 16:29:42,916 >> loading file https://huggingface.co/bertin-project/bertin-roberta-base-spanish/resolve/main/tokenizer_config.json from cache at /root/.cache/huggingface/transformers/72bf61c243630a112d8fa8c8d9162f1a5e01fab0602d2f2a7792cecdc0a4986f.9f7ac4246b492dfa7c21beb5233deec8aef46153ec25ac5258ac5e2ae82dfa89\n", + "[INFO|modeling_utils.py:1271] 2021-07-19 16:29:43,748 >> loading weights file https://huggingface.co/bertin-project/bertin-roberta-base-spanish/resolve/main/pytorch_model.bin from cache at /root/.cache/huggingface/transformers/8a611c8e6ab409ea523e84173bef4b1ef257262487d732b05c68d31b674788e5.ae8a25c127f59d8b0d9d11c53667336d7c491e5b06338b3ce56369ee735acd6f\n", + "[WARNING|modeling_utils.py:1502] 2021-07-19 16:29:51,687 >> Some weights of the model checkpoint at bertin-project/bertin-roberta-base-spanish were not used when initializing RobertaForTokenClassification: ['lm_head.layer_norm.bias', 'lm_head.dense.bias', 'lm_head.dense.weight', 'lm_head.bias', 'lm_head.layer_norm.weight']\n", + "- This IS expected if you are initializing RobertaForTokenClassification from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).\n", + "- This IS NOT expected if you are initializing RobertaForTokenClassification from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).\n", + "[WARNING|modeling_utils.py:1513] 2021-07-19 16:29:51,687 >> Some weights of RobertaForTokenClassification were not initialized from the model checkpoint at bertin-project/bertin-roberta-base-spanish and are newly initialized: ['classifier.bias', 'classifier.weight']\n", + "You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.\n", + "Running tokenizer on train dataset: 0% 0/9 [00:00> The following columns in the training set don't have a corresponding argument in `RobertaForTokenClassification.forward` and have been ignored: pos_tags, id, tokens, ner_tags.\n", + "[INFO|trainer.py:1162] 2021-07-19 16:30:03,256 >> ***** Running training *****\n", + "[INFO|trainer.py:1163] 2021-07-19 16:30:03,256 >> Num examples = 8324\n", + "[INFO|trainer.py:1164] 2021-07-19 16:30:03,256 >> Num Epochs = 5\n", + "[INFO|trainer.py:1165] 2021-07-19 16:30:03,256 >> Instantaneous batch size per device = 8\n", + "[INFO|trainer.py:1166] 2021-07-19 16:30:03,256 >> Total train batch size (w. parallel, distributed & accumulation) = 8\n", + "[INFO|trainer.py:1167] 2021-07-19 16:30:03,257 >> Gradient Accumulation steps = 1\n", + "[INFO|trainer.py:1168] 2021-07-19 16:30:03,257 >> Total optimization steps = 5205\n", + "[INFO|integrations.py:417] 2021-07-19 16:30:03,274 >> Automatic Weights & Biases logging enabled, to disable set os.environ[\"WANDB_DISABLED\"] = \"true\"\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Currently logged in as: \u001b[33mversae\u001b[0m (use `wandb login --relogin` to force relogin)\n", + "2021-07-19 16:30:04.895679: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Successfully opened dynamic library libcudart.so.11.0\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Tracking run with wandb version 0.11.0\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Syncing run \u001b[33m./outputs\u001b[0m\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: ⭐️ View project at \u001b[34m\u001b[4mhttps://wandb.ai/versae/bertin-eval\u001b[0m\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: 🚀 View run at \u001b[34m\u001b[4mhttps://wandb.ai/versae/bertin-eval/runs/giu49zyo\u001b[0m\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Run data is saved locally in /content/wandb/run-20210719_163003-giu49zyo\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Run `wandb offline` to turn off syncing.\n", + "\n", + " 10% 500/5205 [02:53<30:47, 2.55it/s]{'loss': 0.3973, 'learning_rate': 4.5196926032660905e-05, 'epoch': 0.48}\n", + " 10% 500/5205 [02:53<30:47, 2.55it/s][INFO|trainer.py:1917] 2021-07-19 16:32:59,838 >> Saving model checkpoint to ./outputs/checkpoint-500\n", + "[INFO|configuration_utils.py:379] 2021-07-19 16:32:59,841 >> Configuration saved in ./outputs/checkpoint-500/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 16:33:01,329 >> Model weights saved in ./outputs/checkpoint-500/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 16:33:01,330 >> tokenizer config file saved in ./outputs/checkpoint-500/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 16:33:01,331 >> Special tokens file saved in ./outputs/checkpoint-500/special_tokens_map.json\n", + " 19% 1000/5205 [05:52<27:20, 2.56it/s]{'loss': 0.1271, 'learning_rate': 4.039385206532181e-05, 'epoch': 0.96}\n", + " 19% 1000/5205 [05:52<27:20, 2.56it/s][INFO|trainer.py:1917] 2021-07-19 16:35:58,841 >> Saving model checkpoint to ./outputs/checkpoint-1000\n", + "[INFO|configuration_utils.py:379] 2021-07-19 16:35:58,843 >> Configuration saved in ./outputs/checkpoint-1000/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 16:36:00,231 >> Model weights saved in ./outputs/checkpoint-1000/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 16:36:00,232 >> tokenizer config file saved in ./outputs/checkpoint-1000/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 16:36:00,232 >> Special tokens file saved in ./outputs/checkpoint-1000/special_tokens_map.json\n", + " 29% 1500/5205 [08:51<24:04, 2.56it/s]{'loss': 0.0865, 'learning_rate': 3.5590778097982716e-05, 'epoch': 1.44}\n", + "[INFO|trainer.py:1917] 2021-07-19 16:38:57,818 >> Saving model checkpoint to ./outputs/checkpoint-1500\n", + "[INFO|configuration_utils.py:379] 2021-07-19 16:38:57,820 >> Configuration saved in ./outputs/checkpoint-1500/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 16:38:59,318 >> Model weights saved in ./outputs/checkpoint-1500/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 16:38:59,319 >> tokenizer config file saved in ./outputs/checkpoint-1500/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 16:38:59,319 >> Special tokens file saved in ./outputs/checkpoint-1500/special_tokens_map.json\n", + " 38% 2000/5205 [11:50<20:59, 2.54it/s]{'loss': 0.0797, 'learning_rate': 3.078770413064361e-05, 'epoch': 1.92}\n", + " 38% 2000/5205 [11:50<20:59, 2.54it/s][INFO|trainer.py:1917] 2021-07-19 16:41:56,862 >> Saving model checkpoint to ./outputs/checkpoint-2000\n", + "[INFO|configuration_utils.py:379] 2021-07-19 16:41:56,864 >> Configuration saved in ./outputs/checkpoint-2000/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 16:41:58,291 >> Model weights saved in ./outputs/checkpoint-2000/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 16:41:58,292 >> tokenizer config file saved in ./outputs/checkpoint-2000/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 16:41:58,293 >> Special tokens file saved in ./outputs/checkpoint-2000/special_tokens_map.json\n", + "{'loss': 0.055, 'learning_rate': 2.5984630163304517e-05, 'epoch': 2.4}\n", + " 48% 2500/5205 [14:49<17:37, 2.56it/s][INFO|trainer.py:1917] 2021-07-19 16:44:55,537 >> Saving model checkpoint to ./outputs/checkpoint-2500\n", + "[INFO|configuration_utils.py:379] 2021-07-19 16:44:55,539 >> Configuration saved in ./outputs/checkpoint-2500/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 16:44:57,222 >> Model weights saved in ./outputs/checkpoint-2500/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 16:44:57,227 >> tokenizer config file saved in ./outputs/checkpoint-2500/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 16:44:57,228 >> Special tokens file saved in ./outputs/checkpoint-2500/special_tokens_map.json\n", + " 58% 3000/5205 [17:48<14:39, 2.51it/s]{'loss': 0.0498, 'learning_rate': 2.118155619596542e-05, 'epoch': 2.88}\n", + " 58% 3000/5205 [17:48<14:39, 2.51it/s][INFO|trainer.py:1917] 2021-07-19 16:47:54,336 >> Saving model checkpoint to ./outputs/checkpoint-3000\n", + "[INFO|configuration_utils.py:379] 2021-07-19 16:47:54,340 >> Configuration saved in ./outputs/checkpoint-3000/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 16:47:55,927 >> Model weights saved in ./outputs/checkpoint-3000/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 16:47:55,928 >> tokenizer config file saved in ./outputs/checkpoint-3000/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 16:47:55,930 >> Special tokens file saved in ./outputs/checkpoint-3000/special_tokens_map.json\n", + " 67% 3500/5205 [20:46<11:06, 2.56it/s]{'loss': 0.0349, 'learning_rate': 1.6378482228626322e-05, 'epoch': 3.36}\n", + " 67% 3500/5205 [20:46<11:06, 2.56it/s][INFO|trainer.py:1917] 2021-07-19 16:50:52,582 >> Saving model checkpoint to ./outputs/checkpoint-3500\n", + "[INFO|configuration_utils.py:379] 2021-07-19 16:50:52,584 >> Configuration saved in ./outputs/checkpoint-3500/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 16:50:54,163 >> Model weights saved in ./outputs/checkpoint-3500/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 16:50:54,164 >> tokenizer config file saved in ./outputs/checkpoint-3500/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 16:50:54,165 >> Special tokens file saved in ./outputs/checkpoint-3500/special_tokens_map.json\n", + " 77% 4000/5205 [23:44<07:53, 2.54it/s]{'loss': 0.0313, 'learning_rate': 1.1575408261287224e-05, 'epoch': 3.84}\n", + "[INFO|trainer.py:1917] 2021-07-19 16:53:50,996 >> Saving model checkpoint to ./outputs/checkpoint-4000\n", + "[INFO|configuration_utils.py:379] 2021-07-19 16:53:50,998 >> Configuration saved in ./outputs/checkpoint-4000/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 16:53:52,518 >> Model weights saved in ./outputs/checkpoint-4000/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 16:53:52,519 >> tokenizer config file saved in ./outputs/checkpoint-4000/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 16:53:52,609 >> Special tokens file saved in ./outputs/checkpoint-4000/special_tokens_map.json\n", + " 86% 4500/5205 [26:43<04:33, 2.58it/s][INFO|trainer.py:1917] 2021-07-19 16:56:49,291 >> Saving model checkpoint to ./outputs/checkpoint-4500\n", + "[INFO|configuration_utils.py:379] 2021-07-19 16:56:49,293 >> Configuration saved in ./outputs/checkpoint-4500/config.json\n", + "{'loss': 0.0242, 'learning_rate': 6.7723342939481265e-06, 'epoch': 4.32}\n", + "[INFO|modeling_utils.py:997] 2021-07-19 16:56:50,861 >> Model weights saved in ./outputs/checkpoint-4500/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 16:56:50,862 >> tokenizer config file saved in ./outputs/checkpoint-4500/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 16:56:50,862 >> Special tokens file saved in ./outputs/checkpoint-4500/special_tokens_map.json\n", + " 96% 5000/5205 [29:41<01:19, 2.58it/s][INFO|trainer.py:1917] 2021-07-19 16:59:47,339 >> Saving model checkpoint to ./outputs/checkpoint-5000\n", + "{'loss': 0.02, 'learning_rate': 1.96926032660903e-06, 'epoch': 4.8}\n", + "[INFO|configuration_utils.py:379] 2021-07-19 16:59:47,341 >> Configuration saved in ./outputs/checkpoint-5000/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 16:59:48,836 >> Model weights saved in ./outputs/checkpoint-5000/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 16:59:48,837 >> tokenizer config file saved in ./outputs/checkpoint-5000/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 16:59:48,838 >> Special tokens file saved in ./outputs/checkpoint-5000/special_tokens_map.json\n", + "100% 5205/5205 [30:57<00:00, 3.26it/s][INFO|trainer.py:1358] 2021-07-19 17:01:03,736 >> \n", + "\n", + "Training completed. Do not forget to share your model on huggingface.co/models =)\n", + "\n", + "\n", + "{'train_runtime': 1860.4796, 'train_samples_per_second': 22.371, 'train_steps_per_second': 2.798, 'train_loss': 0.08782961375431643, 'epoch': 5.0}\n", + "100% 5205/5205 [30:57<00:00, 2.80it/s]\n", + "[INFO|trainer.py:1917] 2021-07-19 17:01:03,739 >> Saving model checkpoint to ./outputs\n", + "[INFO|configuration_utils.py:379] 2021-07-19 17:01:03,741 >> Configuration saved in ./outputs/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 17:01:05,198 >> Model weights saved in ./outputs/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 17:01:05,198 >> tokenizer config file saved in ./outputs/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 17:01:05,199 >> Special tokens file saved in ./outputs/special_tokens_map.json\n", + "***** train metrics *****\n", + " epoch = 5.0\n", + " train_loss = 0.0878\n", + " train_runtime = 0:31:00.47\n", + " train_samples = 8324\n", + " train_samples_per_second = 22.371\n", + " train_steps_per_second = 2.798\n", + "[INFO|trainer.py:522] 2021-07-19 17:01:05,328 >> The following columns in the evaluation set don't have a corresponding argument in `RobertaForTokenClassification.forward` and have been ignored: pos_tags, id, tokens, ner_tags.\n", + "07/19/2021 17:01:05 - INFO - __main__ - *** Evaluate ***\n", + "[INFO|trainer.py:2163] 2021-07-19 17:01:05,360 >> ***** Running Evaluation *****\n", + "[INFO|trainer.py:2165] 2021-07-19 17:01:05,361 >> Num examples = 1916\n", + "[INFO|trainer.py:2168] 2021-07-19 17:01:05,361 >> Batch size = 8\n", + "100% 239/240 [00:24<00:00, 9.59it/s]/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: NC seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VMI seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Fpa seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Fpt seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Fc seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Z seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: NP seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Fp seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Fg seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: DA seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: AQ seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VAI seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VMP seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: DI seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: SP seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VMN seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: DN seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: PR seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: RG seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: CS seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: CC seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Fe seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Fx seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: DD seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VSI seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: PD seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VMG seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: P0 seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: PN seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VMM seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Fd seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: AO seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: DP seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: PP seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: PI seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VSS seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VAS seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: RN seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Fat seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Faa seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: DE seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VMS seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VSN seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VSP seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Fz seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: PT seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VAN seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VSG seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: PX seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: DT seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Fh seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VAP seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Fs seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VSM seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Y seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Fit seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Fia seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/v1.py:57: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n", + " _warn_prf(average, modifier, msg_start, len(result))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/v1.py:57: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n", + " _warn_prf(average, modifier, msg_start, len(result))\n", + "100% 240/240 [00:28<00:00, 8.46it/s]\n", + "***** eval metrics *****\n", + " epoch = 5.0\n", + " eval_accuracy = 0.969\n", + " eval_f1 = 0.9638\n", + " eval_loss = 0.1236\n", + " eval_precision = 0.9644\n", + " eval_recall = 0.9632\n", + " eval_runtime = 0:00:28.48\n", + " eval_samples = 1916\n", + " eval_samples_per_second = 67.263\n", + " eval_steps_per_second = 8.425\n", + "\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Waiting for W&B process to finish, PID 1271\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Program ended successfully.\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: \n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Find user logs for this run at: /content/wandb/run-20210719_163003-giu49zyo/logs/debug.log\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Find internal logs for this run at: /content/wandb/run-20210719_163003-giu49zyo/logs/debug-internal.log\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Run summary:\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/loss 0.02\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/learning_rate 0.0\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/epoch 5.0\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/global_step 5205\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: _runtime 1890\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: _timestamp 1626714093\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: _step 11\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_runtime 1860.4796\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_samples_per_second 22.371\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_steps_per_second 2.798\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/total_flos 1.08808736772096e+16\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_loss 0.08783\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/loss 0.12361\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/precision 0.96442\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/recall 0.96322\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/f1 0.96382\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/accuracy 0.96897\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/runtime 28.4852\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/samples_per_second 67.263\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/steps_per_second 8.425\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Run history:\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/loss █▃▂▂▂▂▁▁▁▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/learning_rate █▇▆▆▅▄▃▃▂▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/epoch ▁▂▂▃▄▅▅▆▇███\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/global_step ▁▂▂▃▄▅▅▆▇███\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: _runtime ▁▂▂▃▄▅▅▆▇███\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: _timestamp ▁▂▂▃▄▅▅▆▇███\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: _step ▁▂▂▃▄▄▅▅▆▇▇█\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_runtime ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_samples_per_second ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_steps_per_second ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/total_flos ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_loss ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/loss ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/precision ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/recall ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/f1 ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/accuracy ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/runtime ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/samples_per_second ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/steps_per_second ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: \n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Synced 5 W&B file(s), 0 media file(s), 0 artifact file(s) and 1 other file(s)\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: \n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Synced \u001b[33m./outputs\u001b[0m: \u001b[34mhttps://wandb.ai/versae/bertin-eval/runs/giu49zyo\u001b[0m\n", + "2021-07-19 17:01:45.878971: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Successfully opened dynamic library libcudart.so.11.0\n", + "07/19/2021 17:01:48 - WARNING - __main__ - Process rank: -1, device: cuda:0, n_gpu: 1distributed training: False, 16-bits training: False\n", + "07/19/2021 17:01:48 - INFO - __main__ - Training/evaluation parameters TrainingArguments(\n", + "_n_gpu=1,\n", + "adafactor=False,\n", + "adam_beta1=0.9,\n", + "adam_beta2=0.999,\n", + "adam_epsilon=1e-08,\n", + "dataloader_drop_last=False,\n", + "dataloader_num_workers=0,\n", + "dataloader_pin_memory=True,\n", + "ddp_find_unused_parameters=None,\n", + "debug=[],\n", + "deepspeed=None,\n", + "disable_tqdm=False,\n", + "do_eval=True,\n", + "do_predict=False,\n", + "do_train=True,\n", + "eval_accumulation_steps=None,\n", + "eval_steps=500,\n", + "evaluation_strategy=IntervalStrategy.NO,\n", + "fp16=False,\n", + "fp16_backend=auto,\n", + "fp16_full_eval=False,\n", + "fp16_opt_level=O1,\n", + "gradient_accumulation_steps=1,\n", + "greater_is_better=None,\n", + "group_by_length=False,\n", + "ignore_data_skip=False,\n", + "label_names=None,\n", + "label_smoothing_factor=0.0,\n", + "learning_rate=5e-05,\n", + "length_column_name=length,\n", + "load_best_model_at_end=False,\n", + "local_rank=-1,\n", + "log_level=-1,\n", + "log_level_replica=-1,\n", + "log_on_each_node=True,\n", + "logging_dir=./outputs/runs/Jul19_17-01-48_eab5184de9ff,\n", + "logging_first_step=False,\n", + "logging_steps=500,\n", + "logging_strategy=IntervalStrategy.STEPS,\n", + "lr_scheduler_type=SchedulerType.LINEAR,\n", + "max_grad_norm=1.0,\n", + "max_steps=-1,\n", + "metric_for_best_model=None,\n", + "mp_parameters=,\n", + "no_cuda=False,\n", + "num_train_epochs=5.0,\n", + "output_dir=./outputs,\n", + "overwrite_output_dir=True,\n", + "past_index=-1,\n", + "per_device_eval_batch_size=8,\n", + "per_device_train_batch_size=8,\n", + "prediction_loss_only=False,\n", + "push_to_hub=False,\n", + "push_to_hub_model_id=outputs,\n", + "push_to_hub_organization=None,\n", + "push_to_hub_token=None,\n", + "remove_unused_columns=True,\n", + "report_to=['tensorboard', 'wandb'],\n", + "resume_from_checkpoint=None,\n", + "run_name=./outputs,\n", + "save_on_each_node=False,\n", + "save_steps=500,\n", + "save_strategy=IntervalStrategy.STEPS,\n", + "save_total_limit=None,\n", + "seed=42,\n", + "sharded_ddp=[],\n", + "skip_memory_metrics=True,\n", + "tpu_metrics_debug=False,\n", + "tpu_num_cores=None,\n", + "use_legacy_prediction_loop=False,\n", + "warmup_ratio=0.0,\n", + "warmup_steps=0,\n", + "weight_decay=0.0,\n", + ")\n", + "07/19/2021 17:01:50 - INFO - datasets.load - Found main folder for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py at /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002\n", + "07/19/2021 17:01:50 - INFO - datasets.load - Found specific version folder for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py at /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5\n", + "07/19/2021 17:01:50 - INFO - datasets.load - Found script file from https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py to /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5/conll2002.py\n", + "07/19/2021 17:01:50 - INFO - datasets.load - Found dataset infos file from https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/dataset_infos.json to /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5/dataset_infos.json\n", + "07/19/2021 17:01:50 - INFO - datasets.load - Found metadata file for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py at /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5/conll2002.json\n", + "07/19/2021 17:01:51 - INFO - datasets.load - Found main folder for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py at /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002\n", + "07/19/2021 17:01:51 - INFO - datasets.load - Found specific version folder for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py at /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5\n", + "07/19/2021 17:01:51 - INFO - datasets.load - Found script file from 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/root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5\n", + "07/19/2021 17:01:51 - INFO - datasets.builder - Overwrite dataset info from restored data version.\n", + "07/19/2021 17:01:51 - INFO - datasets.info - Loading Dataset info from /root/.cache/huggingface/datasets/conll2002/es/1.0.0/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5\n", + "07/19/2021 17:01:51 - WARNING - datasets.builder - Reusing dataset conll2002 (/root/.cache/huggingface/datasets/conll2002/es/1.0.0/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5)\n", + "07/19/2021 17:01:51 - INFO - datasets.info - Loading Dataset info from /root/.cache/huggingface/datasets/conll2002/es/1.0.0/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5\n", + "100% 3/3 [00:00<00:00, 25.86it/s]\n", + "[INFO|configuration_utils.py:545] 2021-07-19 17:01:51,886 >> loading configuration file https://huggingface.co/flax-community/bertin-roberta-large-spanish/resolve/main/config.json from cache at /root/.cache/huggingface/transformers/d32cc9b6c8f303dbd398a937552d8d9c26d842d418f1cd79adb3fc25f169f722.08210214ecaf5cd53c702826a604e564d8af557125033eef720f4f9f2af1fc44\n", + "[INFO|configuration_utils.py:581] 2021-07-19 17:01:51,887 >> Model config RobertaConfig {\n", + " \"architectures\": [\n", + " \"RobertaForMaskedLM\"\n", + " ],\n", + " \"attention_probs_dropout_prob\": 0.1,\n", + " \"bos_token_id\": 0,\n", + " \"eos_token_id\": 2,\n", + " \"finetuning_task\": \"pos\",\n", + " \"gradient_checkpointing\": false,\n", + " \"hidden_act\": \"gelu\",\n", + " \"hidden_dropout_prob\": 0.1,\n", + " \"hidden_size\": 768,\n", + " \"id2label\": {\n", + " \"0\": 0,\n", + " \"1\": 1,\n", + " \"2\": 2,\n", + " \"3\": 3,\n", + " \"4\": 4,\n", + " \"5\": 5,\n", + " \"6\": 6,\n", + " \"7\": 7,\n", + " \"8\": 8,\n", + " \"9\": 9,\n", + " \"10\": 10,\n", + " \"11\": 11,\n", + " \"12\": 12,\n", + " \"13\": 13,\n", + " \"14\": 14,\n", + " \"15\": 15,\n", + " \"16\": 16,\n", + " \"17\": 17,\n", + " \"18\": 18,\n", + " \"19\": 19,\n", + " \"20\": 20,\n", + " \"21\": 21,\n", + " \"22\": 22,\n", + " \"23\": 23,\n", + " \"24\": 24,\n", + " \"25\": 25,\n", + " \"26\": 26,\n", + " \"27\": 27,\n", + " \"28\": 28,\n", + " \"29\": 29,\n", + " \"30\": 30,\n", + " \"31\": 31,\n", + " \"32\": 32,\n", + " \"33\": 33,\n", + " \"34\": 34,\n", + " \"35\": 35,\n", + " \"36\": 36,\n", + " \"37\": 37,\n", + " \"38\": 38,\n", + " \"39\": 39,\n", + " \"40\": 40,\n", + " \"41\": 41,\n", + " \"42\": 42,\n", + " \"43\": 43,\n", + " \"44\": 44,\n", + " \"45\": 45,\n", + " \"46\": 46,\n", + " \"47\": 47,\n", + " \"48\": 48,\n", + " \"49\": 49,\n", + " \"50\": 50,\n", + " \"51\": 51,\n", + " \"52\": 52,\n", + " \"53\": 53,\n", + " \"54\": 54,\n", + " \"55\": 55,\n", + " \"56\": 56,\n", + " \"57\": 57,\n", + " \"58\": 58,\n", + " \"59\": 59\n", + " },\n", + " \"initializer_range\": 0.02,\n", + " \"intermediate_size\": 3072,\n", + " \"label2id\": {\n", + " \"0\": 0,\n", + " \"1\": 1,\n", + " \"2\": 2,\n", + " \"3\": 3,\n", + " \"4\": 4,\n", + " \"5\": 5,\n", + " \"6\": 6,\n", + " \"7\": 7,\n", + " \"8\": 8,\n", + " \"9\": 9,\n", + " \"10\": 10,\n", + " \"11\": 11,\n", + " \"12\": 12,\n", + " \"13\": 13,\n", + " \"14\": 14,\n", + " \"15\": 15,\n", + " \"16\": 16,\n", + " \"17\": 17,\n", + " \"18\": 18,\n", + " \"19\": 19,\n", + " \"20\": 20,\n", + " \"21\": 21,\n", + " \"22\": 22,\n", + " \"23\": 23,\n", + " \"24\": 24,\n", + " \"25\": 25,\n", + " \"26\": 26,\n", + " \"27\": 27,\n", + " \"28\": 28,\n", + " \"29\": 29,\n", + " \"30\": 30,\n", + " \"31\": 31,\n", + " \"32\": 32,\n", + " \"33\": 33,\n", + " \"34\": 34,\n", + " \"35\": 35,\n", + " \"36\": 36,\n", + " \"37\": 37,\n", + " \"38\": 38,\n", + " \"39\": 39,\n", + " \"40\": 40,\n", + " \"41\": 41,\n", + " \"42\": 42,\n", + " \"43\": 43,\n", + " \"44\": 44,\n", + " \"45\": 45,\n", + " \"46\": 46,\n", + " \"47\": 47,\n", + " \"48\": 48,\n", + " \"49\": 49,\n", + " \"50\": 50,\n", + " \"51\": 51,\n", + " \"52\": 52,\n", + " \"53\": 53,\n", + " \"54\": 54,\n", + " \"55\": 55,\n", + " \"56\": 56,\n", + " \"57\": 57,\n", + " \"58\": 58,\n", + " \"59\": 59\n", + " },\n", + " \"layer_norm_eps\": 1e-05,\n", + " \"max_position_embeddings\": 514,\n", + " \"model_type\": \"roberta\",\n", + " \"num_attention_heads\": 12,\n", + " \"num_hidden_layers\": 12,\n", + " \"pad_token_id\": 1,\n", + " \"position_embedding_type\": \"absolute\",\n", + " \"transformers_version\": \"4.9.0.dev0\",\n", + " \"type_vocab_size\": 1,\n", + " \"use_cache\": true,\n", + " \"vocab_size\": 50265\n", + "}\n", + "\n", + "[INFO|tokenization_utils_base.py:1722] 2021-07-19 17:01:57,277 >> loading file https://huggingface.co/flax-community/bertin-roberta-large-spanish/resolve/main/vocab.json from cache at /root/.cache/huggingface/transformers/20af099ba4d2572dbbdf666ab59e4864bd3ec4867e50cc70d7989d1638fced71.af6be2925520943ae92cd64250bdaa83a8c9d6f91422efbac7ed33a20e0b6e1b\n", + "[INFO|tokenization_utils_base.py:1722] 2021-07-19 17:01:57,277 >> loading file https://huggingface.co/flax-community/bertin-roberta-large-spanish/resolve/main/merges.txt from cache at /root/.cache/huggingface/transformers/45c757f0d795baeb7913a8678519d1c353de20333a2e2e181a005f8f5b4dc60c.360a60d1c13cbafd862a8e2a85b267c2b3eb0226d5469633a889b33ba0dde234\n", + "[INFO|tokenization_utils_base.py:1722] 2021-07-19 17:01:57,277 >> loading file https://huggingface.co/flax-community/bertin-roberta-large-spanish/resolve/main/tokenizer.json from cache at /root/.cache/huggingface/transformers/abcefe6cb866709f8793e0130a2d9bd883fee0cbcc25ffee734858e4d002c5b6.0803a0fadc521f273c2682a34dc285f90fe9de9e932bbe77401d11672f7fcb60\n", + "[INFO|tokenization_utils_base.py:1722] 2021-07-19 17:01:57,277 >> loading file https://huggingface.co/flax-community/bertin-roberta-large-spanish/resolve/main/added_tokens.json from cache at None\n", + "[INFO|tokenization_utils_base.py:1722] 2021-07-19 17:01:57,277 >> loading file https://huggingface.co/flax-community/bertin-roberta-large-spanish/resolve/main/special_tokens_map.json from cache at /root/.cache/huggingface/transformers/73738db8ccbbbf8b6685f923eeb9e382d4c8e36fcfa5c8124d82ed3eed582725.a11ebb04664c067c8fe5ef8f8068b0f721263414a26058692f7b2e4ba2a1b342\n", + "[INFO|tokenization_utils_base.py:1722] 2021-07-19 17:01:57,277 >> loading file https://huggingface.co/flax-community/bertin-roberta-large-spanish/resolve/main/tokenizer_config.json from cache at /root/.cache/huggingface/transformers/4f604c1e66964e3a55ecf1d4959f4ebb3416a50476c866ac53fedd6a93b68c2b.9f7ac4246b492dfa7c21beb5233deec8aef46153ec25ac5258ac5e2ae82dfa89\n", + "[INFO|modeling_utils.py:1271] 2021-07-19 17:01:58,106 >> loading weights file https://huggingface.co/flax-community/bertin-roberta-large-spanish/resolve/main/pytorch_model.bin from cache at /root/.cache/huggingface/transformers/7189e822ad05437642e8c70b270aad1da7745b3f42ae88ee851bd7336559387c.8970e1b3c4890a283e6d9c30f1437e32aec6a36c0f9aae84920ff5a363d4b636\n", + "[WARNING|modeling_utils.py:1502] 2021-07-19 17:02:06,056 >> Some weights of the model checkpoint at flax-community/bertin-roberta-large-spanish were not used when initializing RobertaForTokenClassification: ['lm_head.layer_norm.weight', 'lm_head.dense.bias', 'lm_head.layer_norm.bias', 'lm_head.dense.weight', 'lm_head.bias']\n", + "- This IS expected if you are initializing RobertaForTokenClassification from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).\n", + "- This IS NOT expected if you are initializing RobertaForTokenClassification from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).\n", + "[WARNING|modeling_utils.py:1513] 2021-07-19 17:02:06,057 >> Some weights of RobertaForTokenClassification were not initialized from the model checkpoint at flax-community/bertin-roberta-large-spanish and are newly initialized: ['classifier.weight', 'classifier.bias']\n", + "You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.\n", + "Running tokenizer on train dataset: 0% 0/9 [00:00> The following columns in the training set don't have a corresponding argument in `RobertaForTokenClassification.forward` and have been ignored: id, tokens, pos_tags, ner_tags.\n", + "[INFO|trainer.py:1162] 2021-07-19 17:02:17,713 >> ***** Running training *****\n", + "[INFO|trainer.py:1163] 2021-07-19 17:02:17,714 >> Num examples = 8324\n", + "[INFO|trainer.py:1164] 2021-07-19 17:02:17,714 >> Num Epochs = 5\n", + "[INFO|trainer.py:1165] 2021-07-19 17:02:17,714 >> Instantaneous batch size per device = 8\n", + "[INFO|trainer.py:1166] 2021-07-19 17:02:17,714 >> Total train batch size (w. parallel, distributed & accumulation) = 8\n", + "[INFO|trainer.py:1167] 2021-07-19 17:02:17,714 >> Gradient Accumulation steps = 1\n", + "[INFO|trainer.py:1168] 2021-07-19 17:02:17,714 >> Total optimization steps = 5205\n", + "[INFO|integrations.py:417] 2021-07-19 17:02:17,731 >> Automatic Weights & Biases logging enabled, to disable set os.environ[\"WANDB_DISABLED\"] = \"true\"\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Currently logged in as: \u001b[33mversae\u001b[0m (use `wandb login --relogin` to force relogin)\n", + "2021-07-19 17:02:19.333152: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Successfully opened dynamic library libcudart.so.11.0\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Tracking run with wandb version 0.11.0\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Syncing run \u001b[33m./outputs\u001b[0m\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: ⭐️ View project at \u001b[34m\u001b[4mhttps://wandb.ai/versae/bertin-eval\u001b[0m\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: 🚀 View run at \u001b[34m\u001b[4mhttps://wandb.ai/versae/bertin-eval/runs/9u82spar\u001b[0m\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Run data is saved locally in /content/wandb/run-20210719_170217-9u82spar\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Run `wandb offline` to turn off syncing.\n", + "\n", + " 10% 500/5205 [02:53<30:45, 2.55it/s]{'loss': 0.3908, 'learning_rate': 4.5196926032660905e-05, 'epoch': 0.48}\n", + "[INFO|trainer.py:1917] 2021-07-19 17:05:14,500 >> Saving model checkpoint to ./outputs/checkpoint-500\n", + "[INFO|configuration_utils.py:379] 2021-07-19 17:05:14,502 >> Configuration saved in ./outputs/checkpoint-500/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 17:05:16,023 >> Model weights saved in ./outputs/checkpoint-500/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 17:05:16,024 >> tokenizer config file saved in ./outputs/checkpoint-500/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 17:05:16,024 >> Special tokens file saved in ./outputs/checkpoint-500/special_tokens_map.json\n", + "{'loss': 0.1294, 'learning_rate': 4.039385206532181e-05, 'epoch': 0.96}\n", + " 19% 1000/5205 [05:52<27:26, 2.55it/s][INFO|trainer.py:1917] 2021-07-19 17:08:13,474 >> Saving model checkpoint to ./outputs/checkpoint-1000\n", + "[INFO|configuration_utils.py:379] 2021-07-19 17:08:13,476 >> Configuration saved in ./outputs/checkpoint-1000/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 17:08:14,926 >> Model weights saved in ./outputs/checkpoint-1000/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 17:08:14,927 >> tokenizer config file saved in ./outputs/checkpoint-1000/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 17:08:14,927 >> Special tokens file saved in ./outputs/checkpoint-1000/special_tokens_map.json\n", + " 29% 1500/5205 [08:51<24:21, 2.53it/s]{'loss': 0.0878, 'learning_rate': 3.5590778097982716e-05, 'epoch': 1.44}\n", + " 29% 1500/5205 [08:51<24:21, 2.53it/s][INFO|trainer.py:1917] 2021-07-19 17:11:12,356 >> Saving model checkpoint to ./outputs/checkpoint-1500\n", + "[INFO|configuration_utils.py:379] 2021-07-19 17:11:12,358 >> Configuration saved in ./outputs/checkpoint-1500/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 17:11:13,859 >> Model weights saved in ./outputs/checkpoint-1500/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 17:11:13,860 >> tokenizer config file saved in ./outputs/checkpoint-1500/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 17:11:13,861 >> Special tokens file saved in ./outputs/checkpoint-1500/special_tokens_map.json\n", + " 38% 2000/5205 [11:51<21:04, 2.53it/s]{'loss': 0.0794, 'learning_rate': 3.078770413064361e-05, 'epoch': 1.92}\n", + "[INFO|trainer.py:1917] 2021-07-19 17:14:12,133 >> Saving model checkpoint to ./outputs/checkpoint-2000\n", + "[INFO|configuration_utils.py:379] 2021-07-19 17:14:12,137 >> Configuration saved in ./outputs/checkpoint-2000/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 17:14:13,618 >> Model weights saved in ./outputs/checkpoint-2000/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 17:14:13,619 >> tokenizer config file saved in ./outputs/checkpoint-2000/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 17:14:13,619 >> Special tokens file saved in ./outputs/checkpoint-2000/special_tokens_map.json\n", + "{'loss': 0.0572, 'learning_rate': 2.5984630163304517e-05, 'epoch': 2.4}\n", + " 48% 2500/5205 [14:51<17:39, 2.55it/s][INFO|trainer.py:1917] 2021-07-19 17:17:11,978 >> Saving model checkpoint to ./outputs/checkpoint-2500\n", + "[INFO|configuration_utils.py:379] 2021-07-19 17:17:11,980 >> Configuration saved in ./outputs/checkpoint-2500/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 17:17:13,501 >> Model weights saved in ./outputs/checkpoint-2500/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 17:17:13,502 >> tokenizer config file saved in ./outputs/checkpoint-2500/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 17:17:13,502 >> Special tokens file saved in ./outputs/checkpoint-2500/special_tokens_map.json\n", + " 58% 3000/5205 [17:50<14:35, 2.52it/s]{'loss': 0.0508, 'learning_rate': 2.118155619596542e-05, 'epoch': 2.88}\n", + "[INFO|trainer.py:1917] 2021-07-19 17:20:11,596 >> Saving model checkpoint to ./outputs/checkpoint-3000\n", + "[INFO|configuration_utils.py:379] 2021-07-19 17:20:11,603 >> Configuration saved in ./outputs/checkpoint-3000/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 17:20:13,238 >> Model weights saved in ./outputs/checkpoint-3000/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 17:20:13,239 >> tokenizer config file saved in ./outputs/checkpoint-3000/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 17:20:13,240 >> Special tokens file saved in ./outputs/checkpoint-3000/special_tokens_map.json\n", + " 67% 3500/5205 [20:50<11:10, 2.54it/s]{'loss': 0.0362, 'learning_rate': 1.6378482228626322e-05, 'epoch': 3.36}\n", + "[INFO|trainer.py:1917] 2021-07-19 17:23:10,623 >> Saving model checkpoint to ./outputs/checkpoint-3500\n", + "[INFO|configuration_utils.py:379] 2021-07-19 17:23:10,625 >> Configuration saved in ./outputs/checkpoint-3500/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 17:23:12,162 >> Model weights saved in ./outputs/checkpoint-3500/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 17:23:12,163 >> tokenizer config file saved in ./outputs/checkpoint-3500/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 17:23:12,163 >> Special tokens file saved in ./outputs/checkpoint-3500/special_tokens_map.json\n", + " 77% 4000/5205 [23:49<07:57, 2.52it/s]{'loss': 0.0326, 'learning_rate': 1.1575408261287224e-05, 'epoch': 3.84}\n", + "[INFO|trainer.py:1917] 2021-07-19 17:26:10,082 >> Saving model checkpoint to ./outputs/checkpoint-4000\n", + "[INFO|configuration_utils.py:379] 2021-07-19 17:26:10,084 >> Configuration saved in ./outputs/checkpoint-4000/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 17:26:11,615 >> Model weights saved in ./outputs/checkpoint-4000/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 17:26:11,616 >> tokenizer config file saved in ./outputs/checkpoint-4000/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 17:26:11,644 >> Special tokens file saved in ./outputs/checkpoint-4000/special_tokens_map.json\n", + "{'loss': 0.0248, 'learning_rate': 6.7723342939481265e-06, 'epoch': 4.32}\n", + " 86% 4500/5205 [26:48<04:37, 2.54it/s][INFO|trainer.py:1917] 2021-07-19 17:29:09,325 >> Saving model checkpoint to ./outputs/checkpoint-4500\n", + "[INFO|configuration_utils.py:379] 2021-07-19 17:29:09,327 >> Configuration saved in ./outputs/checkpoint-4500/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 17:29:11,036 >> Model weights saved in ./outputs/checkpoint-4500/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 17:29:11,037 >> tokenizer config file saved in ./outputs/checkpoint-4500/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 17:29:11,038 >> Special tokens file saved in ./outputs/checkpoint-4500/special_tokens_map.json\n", + "{'loss': 0.0204, 'learning_rate': 1.96926032660903e-06, 'epoch': 4.8}\n", + " 96% 5000/5205 [29:47<01:21, 2.52it/s][INFO|trainer.py:1917] 2021-07-19 17:32:08,591 >> Saving model checkpoint to ./outputs/checkpoint-5000\n", + "[INFO|configuration_utils.py:379] 2021-07-19 17:32:08,593 >> Configuration saved in ./outputs/checkpoint-5000/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 17:32:10,040 >> Model weights saved in ./outputs/checkpoint-5000/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 17:32:10,041 >> tokenizer config file saved in ./outputs/checkpoint-5000/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 17:32:10,041 >> Special tokens file saved in ./outputs/checkpoint-5000/special_tokens_map.json\n", + "100% 5205/5205 [31:04<00:00, 3.24it/s][INFO|trainer.py:1358] 2021-07-19 17:33:25,415 >> \n", + "\n", + "Training completed. Do not forget to share your model on huggingface.co/models =)\n", + "\n", + "\n", + "100% 5205/5205 [31:04<00:00, 3.24it/s]{'train_runtime': 1867.7015, 'train_samples_per_second': 22.284, 'train_steps_per_second': 2.787, 'train_loss': 0.08822382634700661, 'epoch': 5.0}\n", + "100% 5205/5205 [31:04<00:00, 2.79it/s]\n", + "[INFO|trainer.py:1917] 2021-07-19 17:33:25,419 >> Saving model checkpoint to ./outputs\n", + "[INFO|configuration_utils.py:379] 2021-07-19 17:33:25,421 >> Configuration saved in ./outputs/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 17:33:27,066 >> Model weights saved in ./outputs/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 17:33:27,067 >> tokenizer config file saved in ./outputs/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 17:33:27,067 >> Special tokens file saved in ./outputs/special_tokens_map.json\n", + "***** train metrics *****\n", + " epoch = 5.0\n", + " train_loss = 0.0882\n", + " train_runtime = 0:31:07.70\n", + " train_samples = 8324\n", + " train_samples_per_second = 22.284\n", + " train_steps_per_second = 2.787\n", + "[INFO|trainer.py:522] 2021-07-19 17:33:27,276 >> The following columns in the evaluation set don't have a corresponding argument in `RobertaForTokenClassification.forward` and have been ignored: id, tokens, pos_tags, ner_tags.\n", + "07/19/2021 17:33:27 - INFO - __main__ - *** Evaluate ***\n", + "[INFO|trainer.py:2163] 2021-07-19 17:33:27,335 >> ***** Running Evaluation *****\n", + "[INFO|trainer.py:2165] 2021-07-19 17:33:27,335 >> Num examples = 1916\n", + "[INFO|trainer.py:2168] 2021-07-19 17:33:27,335 >> Batch size = 8\n", + "100% 239/240 [00:24<00:00, 9.48it/s]/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: NC seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VMI seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Fpa seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Fpt seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Fc seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Z seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: NP seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Fp seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Fg seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: DA seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: AQ seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VAI seems not to be NE tag.\n", + " 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to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: PR seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: RG seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: CS seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: CC seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Fe seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Fx seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: DD seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VSI seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: PD seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VMG seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: P0 seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: PN seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VMM seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Fd seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: AO seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: DP seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: PP seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: PI seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VSS seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VAS seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: RN seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Fat seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Faa seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: DE seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VMS seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VSN seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VSP seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Fz seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: PT seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VAN seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VSG seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: PX seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: DT seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Fh seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VAP seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Fs seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VSM seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Y seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Fit seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Fia seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/v1.py:57: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n", + " _warn_prf(average, modifier, msg_start, len(result))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/v1.py:57: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n", + " _warn_prf(average, modifier, msg_start, len(result))\n", + "100% 240/240 [00:28<00:00, 8.39it/s]\n", + "***** eval metrics *****\n", + " epoch = 5.0\n", + " eval_accuracy = 0.9697\n", + " eval_f1 = 0.9646\n", + " eval_loss = 0.1256\n", + " eval_precision = 0.965\n", + " eval_recall = 0.9642\n", + " eval_runtime = 0:00:28.71\n", + " eval_samples = 1916\n", + " eval_samples_per_second = 66.725\n", + " eval_steps_per_second = 8.358\n", + "\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Waiting for W&B process to finish, PID 1335\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Program ended successfully.\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: \n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Find user logs for this run at: /content/wandb/run-20210719_170217-9u82spar/logs/debug.log\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Find internal logs for this run at: /content/wandb/run-20210719_170217-9u82spar/logs/debug-internal.log\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Run summary:\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/loss 0.0204\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/learning_rate 0.0\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/epoch 5.0\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/global_step 5205\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: _runtime 1898\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: _timestamp 1626716036\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: _step 11\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_runtime 1867.7015\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_samples_per_second 22.284\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_steps_per_second 2.787\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/total_flos 1.08808736772096e+16\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_loss 0.08822\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/loss 0.12556\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/precision 0.96496\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/recall 0.96421\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/f1 0.96459\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/accuracy 0.96965\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/runtime 28.7149\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/samples_per_second 66.725\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/steps_per_second 8.358\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Run history:\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/loss █▃▂▂▂▂▁▁▁▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/learning_rate █▇▆▆▅▄▃▃▂▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/epoch ▁▂▂▃▄▅▅▆▇███\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/global_step ▁▂▂▃▄▅▅▆▇███\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: _runtime ▁▂▂▃▄▅▅▆▇███\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: _timestamp ▁▂▂▃▄▅▅▆▇███\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: _step ▁▂▂▃▄▄▅▅▆▇▇█\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_runtime ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_samples_per_second ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_steps_per_second ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/total_flos ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_loss ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/loss ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/precision ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/recall ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/f1 ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/accuracy ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/runtime ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/samples_per_second ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/steps_per_second ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: \n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Synced 5 W&B file(s), 0 media file(s), 0 artifact file(s) and 1 other file(s)\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: \n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Synced \u001b[33m./outputs\u001b[0m: \u001b[34mhttps://wandb.ai/versae/bertin-eval/runs/9u82spar\u001b[0m\n", + "2021-07-19 17:34:08.180943: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Successfully opened dynamic library libcudart.so.11.0\n", + "07/19/2021 17:34:10 - WARNING - __main__ - Process rank: -1, device: cuda:0, n_gpu: 1distributed training: False, 16-bits training: False\n", + "07/19/2021 17:34:10 - INFO - __main__ - Training/evaluation parameters TrainingArguments(\n", + "_n_gpu=1,\n", + "adafactor=False,\n", + "adam_beta1=0.9,\n", + "adam_beta2=0.999,\n", + "adam_epsilon=1e-08,\n", + "dataloader_drop_last=False,\n", + "dataloader_num_workers=0,\n", + "dataloader_pin_memory=True,\n", + "ddp_find_unused_parameters=None,\n", + "debug=[],\n", + "deepspeed=None,\n", + "disable_tqdm=False,\n", + "do_eval=True,\n", + "do_predict=False,\n", + "do_train=True,\n", + "eval_accumulation_steps=None,\n", + "eval_steps=500,\n", + "evaluation_strategy=IntervalStrategy.NO,\n", + "fp16=False,\n", + "fp16_backend=auto,\n", + "fp16_full_eval=False,\n", + "fp16_opt_level=O1,\n", + "gradient_accumulation_steps=1,\n", + "greater_is_better=None,\n", + "group_by_length=False,\n", + "ignore_data_skip=False,\n", + "label_names=None,\n", + "label_smoothing_factor=0.0,\n", + "learning_rate=5e-05,\n", + "length_column_name=length,\n", + "load_best_model_at_end=False,\n", + "local_rank=-1,\n", + "log_level=-1,\n", + "log_level_replica=-1,\n", + "log_on_each_node=True,\n", + "logging_dir=./outputs/runs/Jul19_17-34-10_eab5184de9ff,\n", + "logging_first_step=False,\n", + "logging_steps=500,\n", + "logging_strategy=IntervalStrategy.STEPS,\n", + "lr_scheduler_type=SchedulerType.LINEAR,\n", + "max_grad_norm=1.0,\n", + "max_steps=-1,\n", + "metric_for_best_model=None,\n", + "mp_parameters=,\n", + "no_cuda=False,\n", + "num_train_epochs=5.0,\n", + "output_dir=./outputs,\n", + "overwrite_output_dir=True,\n", + "past_index=-1,\n", + "per_device_eval_batch_size=8,\n", + "per_device_train_batch_size=8,\n", + "prediction_loss_only=False,\n", + "push_to_hub=False,\n", + "push_to_hub_model_id=outputs,\n", + "push_to_hub_organization=None,\n", + "push_to_hub_token=None,\n", + "remove_unused_columns=True,\n", + "report_to=['tensorboard', 'wandb'],\n", + "resume_from_checkpoint=None,\n", + "run_name=./outputs,\n", + "save_on_each_node=False,\n", + "save_steps=500,\n", + "save_strategy=IntervalStrategy.STEPS,\n", + "save_total_limit=None,\n", + "seed=42,\n", + "sharded_ddp=[],\n", + "skip_memory_metrics=True,\n", + "tpu_metrics_debug=False,\n", + "tpu_num_cores=None,\n", + "use_legacy_prediction_loop=False,\n", + "warmup_ratio=0.0,\n", + "warmup_steps=0,\n", + "weight_decay=0.0,\n", + ")\n", + "07/19/2021 17:34:12 - INFO - datasets.load - Found main folder for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py at /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002\n", + "07/19/2021 17:34:12 - INFO - datasets.load - Found specific version folder for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py at /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5\n", + "07/19/2021 17:34:12 - INFO - datasets.load - Found script file from https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py to /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5/conll2002.py\n", + "07/19/2021 17:34:12 - INFO - datasets.load - Found dataset infos file from https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/dataset_infos.json to /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5/dataset_infos.json\n", + "07/19/2021 17:34:12 - INFO - datasets.load - Found metadata file for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py at /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5/conll2002.json\n", + "07/19/2021 17:34:13 - INFO - datasets.load - Found main folder for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py at /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002\n", + "07/19/2021 17:34:13 - INFO - datasets.load - Found specific version folder for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py at /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5\n", + "07/19/2021 17:34:13 - INFO - datasets.load - Found script file from https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py to /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5/conll2002.py\n", + "07/19/2021 17:34:13 - INFO - datasets.load - Found dataset infos file from https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/dataset_infos.json to /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5/dataset_infos.json\n", + "07/19/2021 17:34:13 - INFO - datasets.load - Found metadata file for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py at /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5/conll2002.json\n", + "07/19/2021 17:34:13 - INFO - datasets.info - Loading Dataset Infos from /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5\n", + "07/19/2021 17:34:13 - INFO - datasets.builder - Overwrite dataset info from restored data version.\n", + "07/19/2021 17:34:13 - INFO - datasets.info - Loading Dataset info from /root/.cache/huggingface/datasets/conll2002/es/1.0.0/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5\n", + "07/19/2021 17:34:13 - WARNING - datasets.builder - Reusing dataset conll2002 (/root/.cache/huggingface/datasets/conll2002/es/1.0.0/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5)\n", + "07/19/2021 17:34:13 - INFO - datasets.info - Loading Dataset info from /root/.cache/huggingface/datasets/conll2002/es/1.0.0/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5\n", + "100% 3/3 [00:00<00:00, 27.30it/s]\n", + "[INFO|configuration_utils.py:545] 2021-07-19 17:34:14,330 >> loading configuration file https://huggingface.co/BSC-TeMU/roberta-base-bne/resolve/main/config.json from cache at /root/.cache/huggingface/transformers/3b60ce79e9e99338ab683eee75e146acc49852f2f34f2c5610dfd78221a176ee.33b0b03a5bf5e640494a22a3aa4909c661effc0fa0e186b1513b17d9b058ca59\n", + "[INFO|configuration_utils.py:581] 2021-07-19 17:34:14,331 >> Model config RobertaConfig {\n", + " \"architectures\": [\n", + " \"RobertaForMaskedLM\"\n", + " ],\n", + " \"attention_probs_dropout_prob\": 0.0,\n", + " \"bos_token_id\": 0,\n", + " \"eos_token_id\": 2,\n", + " \"finetuning_task\": \"pos\",\n", + " \"gradient_checkpointing\": false,\n", + " \"hidden_act\": \"gelu\",\n", + " \"hidden_dropout_prob\": 0.0,\n", + " \"hidden_size\": 768,\n", + " \"id2label\": {\n", + " \"0\": 0,\n", + " \"1\": 1,\n", + " \"2\": 2,\n", + " \"3\": 3,\n", + " \"4\": 4,\n", + " \"5\": 5,\n", + " \"6\": 6,\n", + " \"7\": 7,\n", + " \"8\": 8,\n", + " \"9\": 9,\n", + " \"10\": 10,\n", + " \"11\": 11,\n", + " \"12\": 12,\n", + " \"13\": 13,\n", + " \"14\": 14,\n", + " \"15\": 15,\n", + " \"16\": 16,\n", + " \"17\": 17,\n", + " \"18\": 18,\n", + " \"19\": 19,\n", + " \"20\": 20,\n", + " \"21\": 21,\n", + " \"22\": 22,\n", + " \"23\": 23,\n", + " \"24\": 24,\n", + " \"25\": 25,\n", + " \"26\": 26,\n", + " \"27\": 27,\n", + " \"28\": 28,\n", + " \"29\": 29,\n", + " \"30\": 30,\n", + " \"31\": 31,\n", + " \"32\": 32,\n", + " \"33\": 33,\n", + " \"34\": 34,\n", + " \"35\": 35,\n", + " \"36\": 36,\n", + " \"37\": 37,\n", + " \"38\": 38,\n", + " \"39\": 39,\n", + " \"40\": 40,\n", + " \"41\": 41,\n", + " \"42\": 42,\n", + " \"43\": 43,\n", + " \"44\": 44,\n", + " \"45\": 45,\n", + " \"46\": 46,\n", + " \"47\": 47,\n", + " \"48\": 48,\n", + " \"49\": 49,\n", + " \"50\": 50,\n", + " \"51\": 51,\n", + " \"52\": 52,\n", + " \"53\": 53,\n", + " \"54\": 54,\n", + " \"55\": 55,\n", + " \"56\": 56,\n", + " \"57\": 57,\n", + " \"58\": 58,\n", + " \"59\": 59\n", + " },\n", + " \"initializer_range\": 0.02,\n", + " \"intermediate_size\": 3072,\n", + " \"label2id\": {\n", + " \"0\": 0,\n", + " \"1\": 1,\n", + " \"2\": 2,\n", + " \"3\": 3,\n", + " \"4\": 4,\n", + " \"5\": 5,\n", + " \"6\": 6,\n", + " \"7\": 7,\n", + " \"8\": 8,\n", + " \"9\": 9,\n", + " \"10\": 10,\n", + " \"11\": 11,\n", + " \"12\": 12,\n", + " \"13\": 13,\n", + " \"14\": 14,\n", + " \"15\": 15,\n", + " \"16\": 16,\n", + " \"17\": 17,\n", + " \"18\": 18,\n", + " \"19\": 19,\n", + " \"20\": 20,\n", + " \"21\": 21,\n", + " \"22\": 22,\n", + " \"23\": 23,\n", + " \"24\": 24,\n", + " \"25\": 25,\n", + " \"26\": 26,\n", + " \"27\": 27,\n", + " \"28\": 28,\n", + " \"29\": 29,\n", + " \"30\": 30,\n", + " \"31\": 31,\n", + " \"32\": 32,\n", + " \"33\": 33,\n", + " \"34\": 34,\n", + " \"35\": 35,\n", + " \"36\": 36,\n", + " \"37\": 37,\n", + " \"38\": 38,\n", + " \"39\": 39,\n", + " \"40\": 40,\n", + " \"41\": 41,\n", + " \"42\": 42,\n", + " \"43\": 43,\n", + " \"44\": 44,\n", + " \"45\": 45,\n", + " \"46\": 46,\n", + " \"47\": 47,\n", + " \"48\": 48,\n", + " \"49\": 49,\n", + " \"50\": 50,\n", + " \"51\": 51,\n", + " \"52\": 52,\n", + " \"53\": 53,\n", + " \"54\": 54,\n", + " \"55\": 55,\n", + " \"56\": 56,\n", + " \"57\": 57,\n", + " \"58\": 58,\n", + " \"59\": 59\n", + " },\n", + " \"layer_norm_eps\": 1e-05,\n", + " \"max_position_embeddings\": 514,\n", + " \"model_type\": \"roberta\",\n", + " \"num_attention_heads\": 12,\n", + " \"num_hidden_layers\": 12,\n", + " \"pad_token_id\": 1,\n", + " \"position_embedding_type\": \"absolute\",\n", + " \"transformers_version\": \"4.9.0.dev0\",\n", + " \"type_vocab_size\": 1,\n", + " \"use_cache\": true,\n", + " \"vocab_size\": 50262\n", + "}\n", + "\n", + "[INFO|configuration_utils.py:545] 2021-07-19 17:34:16,050 >> loading configuration file https://huggingface.co/BSC-TeMU/roberta-base-bne/resolve/main/config.json from cache at /root/.cache/huggingface/transformers/3b60ce79e9e99338ab683eee75e146acc49852f2f34f2c5610dfd78221a176ee.33b0b03a5bf5e640494a22a3aa4909c661effc0fa0e186b1513b17d9b058ca59\n", + "[INFO|configuration_utils.py:581] 2021-07-19 17:34:16,050 >> Model config RobertaConfig {\n", + " \"architectures\": [\n", + " \"RobertaForMaskedLM\"\n", + " ],\n", + " \"attention_probs_dropout_prob\": 0.0,\n", + " \"bos_token_id\": 0,\n", + " \"eos_token_id\": 2,\n", + " \"gradient_checkpointing\": false,\n", + " \"hidden_act\": \"gelu\",\n", + " \"hidden_dropout_prob\": 0.0,\n", + " \"hidden_size\": 768,\n", + " \"initializer_range\": 0.02,\n", + " \"intermediate_size\": 3072,\n", + " \"layer_norm_eps\": 1e-05,\n", + " \"max_position_embeddings\": 514,\n", + " \"model_type\": \"roberta\",\n", + " \"num_attention_heads\": 12,\n", + " \"num_hidden_layers\": 12,\n", + " \"pad_token_id\": 1,\n", + " \"position_embedding_type\": \"absolute\",\n", + " \"transformers_version\": \"4.9.0.dev0\",\n", + " \"type_vocab_size\": 1,\n", + " \"use_cache\": true,\n", + " \"vocab_size\": 50262\n", + "}\n", + "\n", + "[INFO|tokenization_utils_base.py:1722] 2021-07-19 17:34:20,946 >> loading file https://huggingface.co/BSC-TeMU/roberta-base-bne/resolve/main/vocab.json from cache at /root/.cache/huggingface/transformers/aec224417e3c4a4bda2283292ca7898205329eeb16f3b8db7ea5a36e51d55257.26eadee3bbe78c0682ce89a698fbb1698a0eee50c36cf83be2280a0f2a7b23c1\n", + "[INFO|tokenization_utils_base.py:1722] 2021-07-19 17:34:20,946 >> loading file https://huggingface.co/BSC-TeMU/roberta-base-bne/resolve/main/merges.txt from cache at /root/.cache/huggingface/transformers/6688b2cc67bbc01f3e369230731a072338dc286bf25b97e1513d359ab00f2ea3.0d24ae8bd5fabb1f5020f91bc602cefeb5a2938ab77e21769d28776345634b23\n", + "[INFO|tokenization_utils_base.py:1722] 2021-07-19 17:34:20,946 >> loading file https://huggingface.co/BSC-TeMU/roberta-base-bne/resolve/main/tokenizer.json from cache at /root/.cache/huggingface/transformers/2f6b692045224588b9a5a4d5639db72d5e3fd2c18cbd0accf4c6dc81a4adc413.bd775ba884c9e650b58a3a333a97e47c8d1b9d37cdbe19b22fb04b1e41beb19d\n", + "[INFO|tokenization_utils_base.py:1722] 2021-07-19 17:34:20,946 >> loading file https://huggingface.co/BSC-TeMU/roberta-base-bne/resolve/main/added_tokens.json from cache at None\n", + "[INFO|tokenization_utils_base.py:1722] 2021-07-19 17:34:20,946 >> loading file https://huggingface.co/BSC-TeMU/roberta-base-bne/resolve/main/special_tokens_map.json from cache at /root/.cache/huggingface/transformers/0f2dbdd0b96b43180e16d660cb1b274e46fa0cf63da426f09c1c82900fb52da1.cb2244924ab24d706b02fd7fcedaea4531566537687a539ebb94db511fd122a0\n", + "[INFO|tokenization_utils_base.py:1722] 2021-07-19 17:34:20,946 >> loading file https://huggingface.co/BSC-TeMU/roberta-base-bne/resolve/main/tokenizer_config.json from cache at /root/.cache/huggingface/transformers/e025b5b045564995a040386d80efa4d55779730827b72b4e40908073db9f0630.d8a7d006294d83173a76ac51a95b5a8470bbbc87c93c63633eaf9476656ed660\n", + "[INFO|configuration_utils.py:545] 2021-07-19 17:34:21,672 >> loading configuration file https://huggingface.co/BSC-TeMU/roberta-base-bne/resolve/main/config.json from cache at /root/.cache/huggingface/transformers/3b60ce79e9e99338ab683eee75e146acc49852f2f34f2c5610dfd78221a176ee.33b0b03a5bf5e640494a22a3aa4909c661effc0fa0e186b1513b17d9b058ca59\n", + "[INFO|configuration_utils.py:581] 2021-07-19 17:34:21,672 >> Model config RobertaConfig {\n", + " \"architectures\": [\n", + " \"RobertaForMaskedLM\"\n", + " ],\n", + " \"attention_probs_dropout_prob\": 0.0,\n", + " \"bos_token_id\": 0,\n", + " \"eos_token_id\": 2,\n", + " \"gradient_checkpointing\": false,\n", + " \"hidden_act\": \"gelu\",\n", + " \"hidden_dropout_prob\": 0.0,\n", + " \"hidden_size\": 768,\n", + " \"initializer_range\": 0.02,\n", + " \"intermediate_size\": 3072,\n", + " \"layer_norm_eps\": 1e-05,\n", + " \"max_position_embeddings\": 514,\n", + " \"model_type\": \"roberta\",\n", + " \"num_attention_heads\": 12,\n", + " \"num_hidden_layers\": 12,\n", + " \"pad_token_id\": 1,\n", + " \"position_embedding_type\": \"absolute\",\n", + " \"transformers_version\": \"4.9.0.dev0\",\n", + " \"type_vocab_size\": 1,\n", + " \"use_cache\": true,\n", + " \"vocab_size\": 50262\n", + "}\n", + "\n", + "[INFO|modeling_utils.py:1271] 2021-07-19 17:34:22,484 >> loading weights file https://huggingface.co/BSC-TeMU/roberta-base-bne/resolve/main/pytorch_model.bin from cache at /root/.cache/huggingface/transformers/a337644e63cac89729bd4fd067c987d2eb61b4b398d17d0ce0973c31dd76d2b0.c86d60e89da68465cb73e129befe8209faa3ac57b9aa272b87db45ba1f619582\n", + "[WARNING|modeling_utils.py:1502] 2021-07-19 17:34:30,475 >> Some weights of the model checkpoint at BSC-TeMU/roberta-base-bne were not used when initializing RobertaForTokenClassification: ['lm_head.decoder.weight', 'lm_head.decoder.bias', 'lm_head.dense.bias', 'lm_head.dense.weight', 'lm_head.layer_norm.weight', 'lm_head.layer_norm.bias', 'lm_head.bias']\n", + "- This IS expected if you are initializing RobertaForTokenClassification from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).\n", + "- This IS NOT expected if you are initializing RobertaForTokenClassification from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).\n", + "[WARNING|modeling_utils.py:1513] 2021-07-19 17:34:30,475 >> Some weights of RobertaForTokenClassification were not initialized from the model checkpoint at BSC-TeMU/roberta-base-bne and are newly initialized: ['classifier.bias', 'classifier.weight']\n", + "You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.\n", + "Running tokenizer on train dataset: 0% 0/9 [00:00> The following columns in the training set don't have a corresponding argument in `RobertaForTokenClassification.forward` and have been ignored: pos_tags, ner_tags, id, tokens.\n", + "[INFO|trainer.py:1162] 2021-07-19 17:34:42,456 >> ***** Running training *****\n", + "[INFO|trainer.py:1163] 2021-07-19 17:34:42,456 >> Num examples = 8324\n", + "[INFO|trainer.py:1164] 2021-07-19 17:34:42,456 >> Num Epochs = 5\n", + "[INFO|trainer.py:1165] 2021-07-19 17:34:42,456 >> Instantaneous batch size per device = 8\n", + "[INFO|trainer.py:1166] 2021-07-19 17:34:42,456 >> Total train batch size (w. parallel, distributed & accumulation) = 8\n", + "[INFO|trainer.py:1167] 2021-07-19 17:34:42,456 >> Gradient Accumulation steps = 1\n", + "[INFO|trainer.py:1168] 2021-07-19 17:34:42,456 >> Total optimization steps = 5205\n", + "[INFO|integrations.py:417] 2021-07-19 17:34:42,487 >> Automatic Weights & Biases logging enabled, to disable set os.environ[\"WANDB_DISABLED\"] = \"true\"\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Currently logged in as: \u001b[33mversae\u001b[0m (use `wandb login --relogin` to force relogin)\n", + "2021-07-19 17:34:44.164024: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Successfully opened dynamic library libcudart.so.11.0\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Tracking run with wandb version 0.11.0\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Syncing run \u001b[33m./outputs\u001b[0m\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: ⭐️ View project at \u001b[34m\u001b[4mhttps://wandb.ai/versae/bertin-eval\u001b[0m\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: 🚀 View run at \u001b[34m\u001b[4mhttps://wandb.ai/versae/bertin-eval/runs/1vhkvz54\u001b[0m\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Run data is saved locally in /content/wandb/run-20210719_173442-1vhkvz54\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Run `wandb offline` to turn off syncing.\n", + "\n", + "{'loss': 0.3477, 'learning_rate': 4.5196926032660905e-05, 'epoch': 0.48}\n", + " 10% 500/5205 [02:50<30:07, 2.60it/s][INFO|trainer.py:1917] 2021-07-19 17:37:35,757 >> Saving model checkpoint to ./outputs/checkpoint-500\n", + "[INFO|configuration_utils.py:379] 2021-07-19 17:37:35,764 >> Configuration saved in ./outputs/checkpoint-500/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 17:37:37,349 >> Model weights saved in ./outputs/checkpoint-500/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 17:37:37,351 >> tokenizer config file saved in ./outputs/checkpoint-500/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 17:37:37,351 >> Special tokens file saved in ./outputs/checkpoint-500/special_tokens_map.json\n", + "{'loss': 0.1027, 'learning_rate': 4.039385206532181e-05, 'epoch': 0.96}\n", + " 19% 1000/5205 [05:45<26:49, 2.61it/s][INFO|trainer.py:1917] 2021-07-19 17:40:31,168 >> Saving model checkpoint to ./outputs/checkpoint-1000\n", + "[INFO|configuration_utils.py:379] 2021-07-19 17:40:31,170 >> Configuration saved in ./outputs/checkpoint-1000/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 17:40:32,863 >> Model weights saved in ./outputs/checkpoint-1000/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 17:40:32,872 >> tokenizer config file saved in ./outputs/checkpoint-1000/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 17:40:32,876 >> Special tokens file saved in ./outputs/checkpoint-1000/special_tokens_map.json\n", + "{'loss': 0.0581, 'learning_rate': 3.5590778097982716e-05, 'epoch': 1.44}\n", + " 29% 1500/5205 [08:39<23:37, 2.61it/s][INFO|trainer.py:1917] 2021-07-19 17:43:25,078 >> Saving model checkpoint to ./outputs/checkpoint-1500\n", + "[INFO|configuration_utils.py:379] 2021-07-19 17:43:25,080 >> Configuration saved in ./outputs/checkpoint-1500/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 17:43:26,548 >> Model weights saved in ./outputs/checkpoint-1500/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 17:43:26,551 >> tokenizer config file saved in ./outputs/checkpoint-1500/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 17:43:26,551 >> Special tokens file saved in ./outputs/checkpoint-1500/special_tokens_map.json\n", + " 38% 2000/5205 [11:34<20:26, 2.61it/s]{'loss': 0.0528, 'learning_rate': 3.078770413064361e-05, 'epoch': 1.92}\n", + " 38% 2000/5205 [11:34<20:26, 2.61it/s][INFO|trainer.py:1917] 2021-07-19 17:46:19,766 >> Saving model checkpoint to ./outputs/checkpoint-2000\n", + "[INFO|configuration_utils.py:379] 2021-07-19 17:46:19,768 >> Configuration saved in ./outputs/checkpoint-2000/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 17:46:21,211 >> Model weights saved in ./outputs/checkpoint-2000/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 17:46:21,215 >> tokenizer config file saved in ./outputs/checkpoint-2000/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 17:46:21,216 >> Special tokens file saved in ./outputs/checkpoint-2000/special_tokens_map.json\n", + "{'loss': 0.0262, 'learning_rate': 2.5984630163304517e-05, 'epoch': 2.4}\n", + " 48% 2500/5205 [14:29<17:19, 2.60it/s][INFO|trainer.py:1917] 2021-07-19 17:49:14,544 >> Saving model checkpoint to ./outputs/checkpoint-2500\n", + "[INFO|configuration_utils.py:379] 2021-07-19 17:49:14,547 >> Configuration saved in ./outputs/checkpoint-2500/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 17:49:16,052 >> Model weights saved in ./outputs/checkpoint-2500/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 17:49:16,055 >> tokenizer config file saved in ./outputs/checkpoint-2500/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 17:49:16,056 >> Special tokens file saved in ./outputs/checkpoint-2500/special_tokens_map.json\n", + "{'loss': 0.0222, 'learning_rate': 2.118155619596542e-05, 'epoch': 2.88}\n", + " 58% 3000/5205 [17:23<13:59, 2.63it/s][INFO|trainer.py:1917] 2021-07-19 17:52:08,771 >> Saving model checkpoint to ./outputs/checkpoint-3000\n", + "[INFO|configuration_utils.py:379] 2021-07-19 17:52:08,774 >> Configuration saved in ./outputs/checkpoint-3000/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 17:52:10,316 >> Model weights saved in ./outputs/checkpoint-3000/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 17:52:10,319 >> tokenizer config file saved in ./outputs/checkpoint-3000/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 17:52:10,320 >> Special tokens file saved in ./outputs/checkpoint-3000/special_tokens_map.json\n", + "{'loss': 0.012, 'learning_rate': 1.6378482228626322e-05, 'epoch': 3.36}\n", + " 67% 3500/5205 [20:17<10:46, 2.64it/s][INFO|trainer.py:1917] 2021-07-19 17:55:02,991 >> Saving model checkpoint to ./outputs/checkpoint-3500\n", + "[INFO|configuration_utils.py:379] 2021-07-19 17:55:02,993 >> Configuration saved in ./outputs/checkpoint-3500/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 17:55:04,533 >> Model weights saved in ./outputs/checkpoint-3500/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 17:55:04,537 >> tokenizer config file saved in ./outputs/checkpoint-3500/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 17:55:04,538 >> Special tokens file saved in ./outputs/checkpoint-3500/special_tokens_map.json\n", + " 77% 4000/5205 [23:11<07:37, 2.64it/s]{'loss': 0.0073, 'learning_rate': 1.1575408261287224e-05, 'epoch': 3.84}\n", + "[INFO|trainer.py:1917] 2021-07-19 17:57:57,141 >> Saving model checkpoint to ./outputs/checkpoint-4000\n", + "[INFO|configuration_utils.py:379] 2021-07-19 17:57:57,144 >> Configuration saved in ./outputs/checkpoint-4000/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 17:57:58,725 >> Model weights saved in ./outputs/checkpoint-4000/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 17:57:58,728 >> tokenizer config file saved in ./outputs/checkpoint-4000/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 17:57:58,753 >> Special tokens file saved in ./outputs/checkpoint-4000/special_tokens_map.json\n", + "{'loss': 0.0047, 'learning_rate': 6.7723342939481265e-06, 'epoch': 4.32}\n", + " 86% 4500/5205 [26:05<04:29, 2.61it/s][INFO|trainer.py:1917] 2021-07-19 18:00:51,142 >> Saving model checkpoint to ./outputs/checkpoint-4500\n", + "[INFO|configuration_utils.py:379] 2021-07-19 18:00:51,145 >> Configuration saved in ./outputs/checkpoint-4500/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 18:00:52,911 >> Model weights saved in ./outputs/checkpoint-4500/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 18:00:52,922 >> tokenizer config file saved in ./outputs/checkpoint-4500/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 18:00:52,923 >> Special tokens file saved in ./outputs/checkpoint-4500/special_tokens_map.json\n", + " 96% 5000/5205 [28:59<01:17, 2.64it/s]{'loss': 0.0025, 'learning_rate': 1.96926032660903e-06, 'epoch': 4.8}\n", + "[INFO|trainer.py:1917] 2021-07-19 18:03:44,964 >> Saving model checkpoint to ./outputs/checkpoint-5000\n", + "[INFO|configuration_utils.py:379] 2021-07-19 18:03:44,967 >> Configuration saved in ./outputs/checkpoint-5000/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 18:03:46,368 >> Model weights saved in ./outputs/checkpoint-5000/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 18:03:46,372 >> tokenizer config file saved in ./outputs/checkpoint-5000/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 18:03:46,374 >> Special tokens file saved in ./outputs/checkpoint-5000/special_tokens_map.json\n", + "100% 5205/5205 [30:14<00:00, 3.29it/s][INFO|trainer.py:1358] 2021-07-19 18:04:59,740 >> \n", + "\n", + "Training completed. Do not forget to share your model on huggingface.co/models =)\n", + "\n", + "\n", + "{'train_runtime': 1817.2838, 'train_samples_per_second': 22.902, 'train_steps_per_second': 2.864, 'train_loss': 0.06121874419000719, 'epoch': 5.0}\n", + "100% 5205/5205 [30:14<00:00, 2.87it/s]\n", + "[INFO|trainer.py:1917] 2021-07-19 18:04:59,756 >> Saving model checkpoint to ./outputs\n", + "[INFO|configuration_utils.py:379] 2021-07-19 18:04:59,766 >> Configuration saved in ./outputs/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 18:05:01,318 >> Model weights saved in ./outputs/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 18:05:01,319 >> tokenizer config file saved in ./outputs/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 18:05:01,320 >> Special tokens file saved in ./outputs/special_tokens_map.json\n", + "***** train metrics *****\n", + " epoch = 5.0\n", + " train_loss = 0.0612\n", + " train_runtime = 0:30:17.28\n", + " train_samples = 8324\n", + " train_samples_per_second = 22.902\n", + " train_steps_per_second = 2.864\n", + "[INFO|trainer.py:522] 2021-07-19 18:05:02,114 >> The following columns in the evaluation set don't have a corresponding argument in `RobertaForTokenClassification.forward` and have been ignored: pos_tags, ner_tags, id, tokens.\n", + "07/19/2021 18:05:02 - INFO - __main__ - *** Evaluate ***\n", + "[INFO|trainer.py:2163] 2021-07-19 18:05:02,132 >> ***** Running Evaluation *****\n", + "[INFO|trainer.py:2165] 2021-07-19 18:05:02,132 >> Num examples = 1916\n", + "[INFO|trainer.py:2168] 2021-07-19 18:05:02,133 >> Batch size = 8\n", + "100% 239/240 [00:25<00:00, 7.72it/s]/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: NC seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VMI seems not to be NE tag.\n", 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"/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Fx seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: DD seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VSI seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: PD seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VMG seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: P0 seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: PN seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VMM seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Fd seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: AO seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: DP seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: PP seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: PI seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VSS seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VAS seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: RN seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Fat seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Faa seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: DE seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VMS seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VSN seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VSP seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Fz seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: PT seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VAN seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VSG seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: PX seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: DT seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Fh seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VAP seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Fs seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VSM seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Y seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Fia seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/v1.py:57: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n", + " _warn_prf(average, modifier, msg_start, len(result))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/v1.py:57: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n", + " _warn_prf(average, modifier, msg_start, len(result))\n", + "100% 240/240 [00:28<00:00, 8.30it/s]\n", + "***** eval metrics *****\n", + " epoch = 5.0\n", + " eval_accuracy = 0.9707\n", + " eval_f1 = 0.9659\n", + " eval_loss = 0.1581\n", + " eval_precision = 0.9671\n", + " eval_recall = 0.9647\n", + " eval_runtime = 0:00:29.01\n", + " eval_samples = 1916\n", + " eval_samples_per_second = 66.035\n", + " eval_steps_per_second = 8.272\n", + "\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Waiting for W&B process to finish, PID 1399\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Program ended successfully.\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: \n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Find user logs for this run at: /content/wandb/run-20210719_173442-1vhkvz54/logs/debug.log\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Find internal logs for this run at: /content/wandb/run-20210719_173442-1vhkvz54/logs/debug-internal.log\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Run summary:\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/loss 0.0025\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/learning_rate 0.0\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/epoch 5.0\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/global_step 5205\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: _runtime 1849\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: _timestamp 1626717931\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: _step 11\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_runtime 1817.2838\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_samples_per_second 22.902\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_steps_per_second 2.864\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/total_flos 1.08808736772096e+16\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_loss 0.06122\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/loss 0.15812\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/precision 0.96707\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/recall 0.9647\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/f1 0.96588\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/accuracy 0.97066\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/runtime 29.015\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/samples_per_second 66.035\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/steps_per_second 8.272\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Run history:\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/loss █▃▂▂▁▁▁▁▁▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/learning_rate █▇▆▆▅▄▃▃▂▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/epoch ▁▂▂▃▄▅▅▆▇███\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/global_step ▁▂▂▃▄▅▅▆▇███\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: _runtime ▁▂▂▃▄▅▅▆▇███\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: _timestamp ▁▂▂▃▄▅▅▆▇███\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: _step ▁▂▂▃▄▄▅▅▆▇▇█\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_runtime ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_samples_per_second ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_steps_per_second ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/total_flos ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_loss ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/loss ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/precision ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/recall ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/f1 ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/accuracy ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/runtime ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/samples_per_second ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/steps_per_second ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: \n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Synced 5 W&B file(s), 0 media file(s), 0 artifact file(s) and 1 other file(s)\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: \n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Synced \u001b[33m./outputs\u001b[0m: \u001b[34mhttps://wandb.ai/versae/bertin-eval/runs/1vhkvz54\u001b[0m\n", + "2021-07-19 18:05:43.870368: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Successfully opened dynamic library libcudart.so.11.0\n", + "07/19/2021 18:05:46 - WARNING - __main__ - Process rank: -1, device: cuda:0, n_gpu: 1distributed training: False, 16-bits training: False\n", + "07/19/2021 18:05:46 - INFO - __main__ - Training/evaluation parameters TrainingArguments(\n", + "_n_gpu=1,\n", + "adafactor=False,\n", + "adam_beta1=0.9,\n", + "adam_beta2=0.999,\n", + "adam_epsilon=1e-08,\n", + "dataloader_drop_last=False,\n", + "dataloader_num_workers=0,\n", + "dataloader_pin_memory=True,\n", + "ddp_find_unused_parameters=None,\n", + "debug=[],\n", + "deepspeed=None,\n", + "disable_tqdm=False,\n", + "do_eval=True,\n", + "do_predict=False,\n", + "do_train=True,\n", + "eval_accumulation_steps=None,\n", + "eval_steps=500,\n", + "evaluation_strategy=IntervalStrategy.NO,\n", + "fp16=False,\n", + "fp16_backend=auto,\n", + "fp16_full_eval=False,\n", + "fp16_opt_level=O1,\n", + "gradient_accumulation_steps=1,\n", + "greater_is_better=None,\n", + "group_by_length=False,\n", + "ignore_data_skip=False,\n", + "label_names=None,\n", + "label_smoothing_factor=0.0,\n", + "learning_rate=5e-05,\n", + "length_column_name=length,\n", + "load_best_model_at_end=False,\n", + "local_rank=-1,\n", + "log_level=-1,\n", + "log_level_replica=-1,\n", + "log_on_each_node=True,\n", + "logging_dir=./outputs/runs/Jul19_18-05-46_eab5184de9ff,\n", + "logging_first_step=False,\n", + "logging_steps=500,\n", + "logging_strategy=IntervalStrategy.STEPS,\n", + "lr_scheduler_type=SchedulerType.LINEAR,\n", + "max_grad_norm=1.0,\n", + "max_steps=-1,\n", + "metric_for_best_model=None,\n", + "mp_parameters=,\n", + "no_cuda=False,\n", + "num_train_epochs=5.0,\n", + "output_dir=./outputs,\n", + "overwrite_output_dir=True,\n", + "past_index=-1,\n", + "per_device_eval_batch_size=8,\n", + "per_device_train_batch_size=8,\n", + "prediction_loss_only=False,\n", + "push_to_hub=False,\n", + "push_to_hub_model_id=outputs,\n", + "push_to_hub_organization=None,\n", + "push_to_hub_token=None,\n", + "remove_unused_columns=True,\n", + "report_to=['tensorboard', 'wandb'],\n", + "resume_from_checkpoint=None,\n", + "run_name=./outputs,\n", + "save_on_each_node=False,\n", + "save_steps=500,\n", + "save_strategy=IntervalStrategy.STEPS,\n", + "save_total_limit=None,\n", + "seed=42,\n", + "sharded_ddp=[],\n", + "skip_memory_metrics=True,\n", + "tpu_metrics_debug=False,\n", + "tpu_num_cores=None,\n", + "use_legacy_prediction_loop=False,\n", + "warmup_ratio=0.0,\n", + "warmup_steps=0,\n", + "weight_decay=0.0,\n", + ")\n", + "07/19/2021 18:05:48 - INFO - datasets.load - Found main folder for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py at /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002\n", + "07/19/2021 18:05:48 - INFO - datasets.load - Found specific version folder for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py at /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5\n", + "07/19/2021 18:05:48 - INFO - datasets.load - Found script file from https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py to /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5/conll2002.py\n", + "07/19/2021 18:05:48 - INFO - datasets.load - Found dataset infos file from https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/dataset_infos.json to /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5/dataset_infos.json\n", + "07/19/2021 18:05:48 - INFO - datasets.load - Found metadata file for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py at /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5/conll2002.json\n", + "07/19/2021 18:05:49 - INFO - datasets.load - Found main folder for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py at /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002\n", + "07/19/2021 18:05:49 - INFO - datasets.load - Found specific version folder for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py at /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5\n", + "07/19/2021 18:05:49 - INFO - datasets.load - Found script file from https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py to /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5/conll2002.py\n", + "07/19/2021 18:05:49 - INFO - datasets.load - Found dataset infos file from https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/dataset_infos.json to /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5/dataset_infos.json\n", + "07/19/2021 18:05:49 - INFO - datasets.load - Found metadata file for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py at /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5/conll2002.json\n", + "07/19/2021 18:05:49 - INFO - datasets.info - Loading Dataset Infos from /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5\n", + "07/19/2021 18:05:49 - INFO - datasets.builder - Overwrite dataset info from restored data version.\n", + "07/19/2021 18:05:49 - INFO - datasets.info - Loading Dataset info from /root/.cache/huggingface/datasets/conll2002/es/1.0.0/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5\n", + "07/19/2021 18:05:49 - WARNING - datasets.builder - Reusing dataset conll2002 (/root/.cache/huggingface/datasets/conll2002/es/1.0.0/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5)\n", + "07/19/2021 18:05:49 - INFO - datasets.info - Loading Dataset info from /root/.cache/huggingface/datasets/conll2002/es/1.0.0/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5\n", + "100% 3/3 [00:00<00:00, 25.89it/s]\n", + "[INFO|configuration_utils.py:545] 2021-07-19 18:05:50,327 >> loading configuration file https://huggingface.co/dccuchile/bert-base-spanish-wwm-cased/resolve/main/config.json from cache at /root/.cache/huggingface/transformers/cb7cedb04246e225d56ba26d207f1d1809b31a9bbe9b63103371d835c6ac0502.f4e4777229bac528fa2a8d4833e2ef53624e985ebde0fd527064a5cc7c50832b\n", + "[INFO|configuration_utils.py:581] 2021-07-19 18:05:50,328 >> Model config BertConfig {\n", + " \"_name_or_path\": \"dccuchile/bert-base-spanish-wwm-cased\",\n", + " \"architectures\": [\n", + " \"BertForMaskedLM\"\n", + " ],\n", + " \"attention_probs_dropout_prob\": 0.1,\n", + " \"finetuning_task\": \"pos\",\n", + " \"gradient_checkpointing\": false,\n", + " \"hidden_act\": \"gelu\",\n", + " \"hidden_dropout_prob\": 0.1,\n", + " \"hidden_size\": 768,\n", + " \"id2label\": {\n", + " \"0\": 0,\n", + " \"1\": 1,\n", + " \"2\": 2,\n", + " \"3\": 3,\n", + " \"4\": 4,\n", + " \"5\": 5,\n", + " \"6\": 6,\n", + " \"7\": 7,\n", + " \"8\": 8,\n", + " \"9\": 9,\n", + " \"10\": 10,\n", + " \"11\": 11,\n", + " \"12\": 12,\n", + " \"13\": 13,\n", + " \"14\": 14,\n", + " \"15\": 15,\n", + " \"16\": 16,\n", + " \"17\": 17,\n", + " \"18\": 18,\n", + " \"19\": 19,\n", + " \"20\": 20,\n", + " \"21\": 21,\n", + " \"22\": 22,\n", + " \"23\": 23,\n", + " \"24\": 24,\n", + " \"25\": 25,\n", + " \"26\": 26,\n", + " \"27\": 27,\n", + " \"28\": 28,\n", + " \"29\": 29,\n", + " \"30\": 30,\n", + " \"31\": 31,\n", + " \"32\": 32,\n", + " \"33\": 33,\n", + " \"34\": 34,\n", + " \"35\": 35,\n", + " \"36\": 36,\n", + " \"37\": 37,\n", + " \"38\": 38,\n", + " \"39\": 39,\n", + " \"40\": 40,\n", + " \"41\": 41,\n", + " \"42\": 42,\n", + " \"43\": 43,\n", + " \"44\": 44,\n", + " \"45\": 45,\n", + " \"46\": 46,\n", + " \"47\": 47,\n", + " \"48\": 48,\n", + " \"49\": 49,\n", + " \"50\": 50,\n", + " \"51\": 51,\n", + " \"52\": 52,\n", + " \"53\": 53,\n", + " \"54\": 54,\n", + " \"55\": 55,\n", + " \"56\": 56,\n", + " \"57\": 57,\n", + " \"58\": 58,\n", + " \"59\": 59\n", + " },\n", + " \"initializer_range\": 0.02,\n", + " \"intermediate_size\": 3072,\n", + " \"label2id\": {\n", + " \"0\": 0,\n", + " \"1\": 1,\n", + " \"2\": 2,\n", + " \"3\": 3,\n", + " \"4\": 4,\n", + " \"5\": 5,\n", + " \"6\": 6,\n", + " \"7\": 7,\n", + " \"8\": 8,\n", + " \"9\": 9,\n", + " \"10\": 10,\n", + " \"11\": 11,\n", + " \"12\": 12,\n", + " \"13\": 13,\n", + " \"14\": 14,\n", + " \"15\": 15,\n", + " \"16\": 16,\n", + " \"17\": 17,\n", + " \"18\": 18,\n", + " \"19\": 19,\n", + " \"20\": 20,\n", + " \"21\": 21,\n", + " \"22\": 22,\n", + " \"23\": 23,\n", + " \"24\": 24,\n", + " \"25\": 25,\n", + " \"26\": 26,\n", + " \"27\": 27,\n", + " \"28\": 28,\n", + " \"29\": 29,\n", + " \"30\": 30,\n", + " \"31\": 31,\n", + " \"32\": 32,\n", + " \"33\": 33,\n", + " \"34\": 34,\n", + " \"35\": 35,\n", + " \"36\": 36,\n", + " \"37\": 37,\n", + " \"38\": 38,\n", + " \"39\": 39,\n", + " \"40\": 40,\n", + " \"41\": 41,\n", + " \"42\": 42,\n", + " \"43\": 43,\n", + " \"44\": 44,\n", + " \"45\": 45,\n", + " \"46\": 46,\n", + " \"47\": 47,\n", + " \"48\": 48,\n", + " \"49\": 49,\n", + " \"50\": 50,\n", + " \"51\": 51,\n", + " \"52\": 52,\n", + " \"53\": 53,\n", + " \"54\": 54,\n", + " \"55\": 55,\n", + " \"56\": 56,\n", + " \"57\": 57,\n", + " \"58\": 58,\n", + " \"59\": 59\n", + " },\n", + " \"layer_norm_eps\": 1e-12,\n", + " \"max_position_embeddings\": 512,\n", + " \"model_type\": \"bert\",\n", + " \"num_attention_heads\": 12,\n", + " \"num_hidden_layers\": 12,\n", + " \"output_past\": true,\n", + " \"pad_token_id\": 1,\n", + " \"position_embedding_type\": \"absolute\",\n", + " \"transformers_version\": \"4.9.0.dev0\",\n", + " \"type_vocab_size\": 2,\n", + " \"use_cache\": true,\n", + " \"vocab_size\": 31002\n", + "}\n", + "\n", + "[INFO|configuration_utils.py:545] 2021-07-19 18:05:51,786 >> loading configuration file https://huggingface.co/dccuchile/bert-base-spanish-wwm-cased/resolve/main/config.json from cache at /root/.cache/huggingface/transformers/cb7cedb04246e225d56ba26d207f1d1809b31a9bbe9b63103371d835c6ac0502.f4e4777229bac528fa2a8d4833e2ef53624e985ebde0fd527064a5cc7c50832b\n", + "[INFO|configuration_utils.py:581] 2021-07-19 18:05:51,787 >> Model config BertConfig {\n", + " \"_name_or_path\": \"dccuchile/bert-base-spanish-wwm-cased\",\n", + " \"architectures\": [\n", + " \"BertForMaskedLM\"\n", + " ],\n", + " \"attention_probs_dropout_prob\": 0.1,\n", + " \"gradient_checkpointing\": false,\n", + " \"hidden_act\": \"gelu\",\n", + " \"hidden_dropout_prob\": 0.1,\n", + " \"hidden_size\": 768,\n", + " \"initializer_range\": 0.02,\n", + " \"intermediate_size\": 3072,\n", + " \"layer_norm_eps\": 1e-12,\n", + " \"max_position_embeddings\": 512,\n", + " \"model_type\": \"bert\",\n", + " \"num_attention_heads\": 12,\n", + " \"num_hidden_layers\": 12,\n", + " \"output_past\": true,\n", + " \"pad_token_id\": 1,\n", + " \"position_embedding_type\": \"absolute\",\n", + " \"transformers_version\": \"4.9.0.dev0\",\n", + " \"type_vocab_size\": 2,\n", + " \"use_cache\": true,\n", + " \"vocab_size\": 31002\n", + "}\n", + "\n", + "[INFO|tokenization_utils_base.py:1722] 2021-07-19 18:05:55,430 >> loading file https://huggingface.co/dccuchile/bert-base-spanish-wwm-cased/resolve/main/vocab.txt from cache at /root/.cache/huggingface/transformers/6761cd0c3d282272f598fcc1fa8c4ecfff8c18762ec8acb40f9cbb562cb0901e.6587bde86239957281af55b2f7e564df111a2b4f9dfc0ad884f13ea7106e4dfb\n", + "[INFO|tokenization_utils_base.py:1722] 2021-07-19 18:05:55,430 >> loading file https://huggingface.co/dccuchile/bert-base-spanish-wwm-cased/resolve/main/tokenizer.json from cache at /root/.cache/huggingface/transformers/44de7af89c157bf67367a71105165d92bebe0585543739a918e3870d25484c27.6a099cd4b12bf7db174fffe48b004eb919c325f108e0c36176a0fe0ad1848d31\n", + "[INFO|tokenization_utils_base.py:1722] 2021-07-19 18:05:55,431 >> loading file https://huggingface.co/dccuchile/bert-base-spanish-wwm-cased/resolve/main/added_tokens.json from cache at None\n", + "[INFO|tokenization_utils_base.py:1722] 2021-07-19 18:05:55,431 >> loading file https://huggingface.co/dccuchile/bert-base-spanish-wwm-cased/resolve/main/special_tokens_map.json from cache at /root/.cache/huggingface/transformers/9848a00af462c42dfb4ec88ef438fbab5256330f7f6f50badc48d277f9367d49.f982506b52498d4adb4bd491f593dc92b2ef6be61bfdbe9d30f53f963f9f5b66\n", + "[INFO|tokenization_utils_base.py:1722] 2021-07-19 18:05:55,431 >> loading file https://huggingface.co/dccuchile/bert-base-spanish-wwm-cased/resolve/main/tokenizer_config.json from cache at /root/.cache/huggingface/transformers/ca34e6c1251888a8ed98da2a454f869d28e3438eef67c2f93aa8133459ac08a3.0e90f656d0426b15b4927d1fe8ca5ec4c2e7b0d0e878c9153c3ddc6ed9bbed3c\n", + "[INFO|configuration_utils.py:545] 2021-07-19 18:05:56,161 >> loading configuration file https://huggingface.co/dccuchile/bert-base-spanish-wwm-cased/resolve/main/config.json from cache at /root/.cache/huggingface/transformers/cb7cedb04246e225d56ba26d207f1d1809b31a9bbe9b63103371d835c6ac0502.f4e4777229bac528fa2a8d4833e2ef53624e985ebde0fd527064a5cc7c50832b\n", + "[INFO|configuration_utils.py:581] 2021-07-19 18:05:56,161 >> Model config BertConfig {\n", + " \"_name_or_path\": \"dccuchile/bert-base-spanish-wwm-cased\",\n", + " \"architectures\": [\n", + " \"BertForMaskedLM\"\n", + " ],\n", + " \"attention_probs_dropout_prob\": 0.1,\n", + " \"gradient_checkpointing\": false,\n", + " \"hidden_act\": \"gelu\",\n", + " \"hidden_dropout_prob\": 0.1,\n", + " \"hidden_size\": 768,\n", + " \"initializer_range\": 0.02,\n", + " \"intermediate_size\": 3072,\n", + " \"layer_norm_eps\": 1e-12,\n", + " \"max_position_embeddings\": 512,\n", + " \"model_type\": \"bert\",\n", + " \"num_attention_heads\": 12,\n", + " \"num_hidden_layers\": 12,\n", + " \"output_past\": true,\n", + " \"pad_token_id\": 1,\n", + " \"position_embedding_type\": \"absolute\",\n", + " \"transformers_version\": \"4.9.0.dev0\",\n", + " \"type_vocab_size\": 2,\n", + " \"use_cache\": true,\n", + " \"vocab_size\": 31002\n", + "}\n", + "\n", + "[INFO|modeling_utils.py:1271] 2021-07-19 18:05:56,916 >> loading weights file https://huggingface.co/dccuchile/bert-base-spanish-wwm-cased/resolve/main/pytorch_model.bin from cache at /root/.cache/huggingface/transformers/52382cbe7c1587c6b588daa81eaf247c5e2ad073d42b52192a8cd4202e7429b6.a88ccd19b1f271e63b6a901510804e6c0318089355c471334fe8b71b316a30ab\n", + "[WARNING|modeling_utils.py:1502] 2021-07-19 18:06:03,944 >> Some weights of the model checkpoint at dccuchile/bert-base-spanish-wwm-cased were not used when initializing BertForTokenClassification: ['cls.predictions.transform.LayerNorm.weight', 'cls.predictions.decoder.bias', 'cls.predictions.transform.dense.weight', 'cls.predictions.bias', 'cls.predictions.decoder.weight', 'cls.predictions.transform.dense.bias', 'cls.predictions.transform.LayerNorm.bias']\n", + "- This IS expected if you are initializing BertForTokenClassification from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).\n", + "- This IS NOT expected if you are initializing BertForTokenClassification from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).\n", + "[WARNING|modeling_utils.py:1513] 2021-07-19 18:06:03,944 >> Some weights of BertForTokenClassification were not initialized from the model checkpoint at dccuchile/bert-base-spanish-wwm-cased and are newly initialized: ['classifier.weight', 'classifier.bias']\n", + "You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.\n", + "Running tokenizer on train dataset: 0% 0/9 [00:00> The following columns in the training set don't have a corresponding argument in `BertForTokenClassification.forward` and have been ignored: pos_tags, ner_tags, tokens, id.\n", + "[INFO|trainer.py:1162] 2021-07-19 18:06:15,814 >> ***** Running training *****\n", + "[INFO|trainer.py:1163] 2021-07-19 18:06:15,814 >> Num examples = 8324\n", + "[INFO|trainer.py:1164] 2021-07-19 18:06:15,814 >> Num Epochs = 5\n", + "[INFO|trainer.py:1165] 2021-07-19 18:06:15,814 >> Instantaneous batch size per device = 8\n", + "[INFO|trainer.py:1166] 2021-07-19 18:06:15,814 >> Total train batch size (w. parallel, distributed & accumulation) = 8\n", + "[INFO|trainer.py:1167] 2021-07-19 18:06:15,814 >> Gradient Accumulation steps = 1\n", + "[INFO|trainer.py:1168] 2021-07-19 18:06:15,814 >> Total optimization steps = 5205\n", + "[INFO|integrations.py:417] 2021-07-19 18:06:15,833 >> Automatic Weights & Biases logging enabled, to disable set os.environ[\"WANDB_DISABLED\"] = \"true\"\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Currently logged in as: \u001b[33mversae\u001b[0m (use `wandb login --relogin` to force relogin)\n", + "2021-07-19 18:06:17.537370: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Successfully opened dynamic library libcudart.so.11.0\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Tracking run with wandb version 0.11.0\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Syncing run \u001b[33m./outputs\u001b[0m\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: ⭐️ View project at \u001b[34m\u001b[4mhttps://wandb.ai/versae/bertin-eval\u001b[0m\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: 🚀 View run at \u001b[34m\u001b[4mhttps://wandb.ai/versae/bertin-eval/runs/1felky5r\u001b[0m\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Run data is saved locally in /content/wandb/run-20210719_180616-1felky5r\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Run `wandb offline` to turn off syncing.\n", + "\n", + " 10% 500/5205 [02:56<31:10, 2.51it/s]{'loss': 0.2778, 'learning_rate': 4.5196926032660905e-05, 'epoch': 0.48}\n", + " 10% 500/5205 [02:56<31:10, 2.51it/s][INFO|trainer.py:1917] 2021-07-19 18:09:14,980 >> Saving model checkpoint to ./outputs/checkpoint-500\n", + "[INFO|configuration_utils.py:379] 2021-07-19 18:09:14,983 >> Configuration saved in ./outputs/checkpoint-500/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 18:09:16,843 >> Model weights saved in ./outputs/checkpoint-500/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 18:09:16,844 >> tokenizer config file saved in ./outputs/checkpoint-500/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 18:09:16,845 >> Special tokens file saved in ./outputs/checkpoint-500/special_tokens_map.json\n", + " 19% 1000/5205 [05:57<27:27, 2.55it/s][INFO|trainer.py:1917] 2021-07-19 18:12:16,139 >> Saving model checkpoint to ./outputs/checkpoint-1000\n", + "{'loss': 0.103, 'learning_rate': 4.039385206532181e-05, 'epoch': 0.96}\n", + "[INFO|configuration_utils.py:379] 2021-07-19 18:12:16,147 >> Configuration saved in ./outputs/checkpoint-1000/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 18:12:18,117 >> Model weights saved in ./outputs/checkpoint-1000/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 18:12:18,118 >> tokenizer config file saved in ./outputs/checkpoint-1000/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 18:12:18,118 >> Special tokens file saved in ./outputs/checkpoint-1000/special_tokens_map.json\n", + "{'loss': 0.0649, 'learning_rate': 3.5590778097982716e-05, 'epoch': 1.44}\n", + " 29% 1500/5205 [08:58<24:36, 2.51it/s][INFO|trainer.py:1917] 2021-07-19 18:15:16,993 >> Saving model checkpoint to ./outputs/checkpoint-1500\n", + "[INFO|configuration_utils.py:379] 2021-07-19 18:15:16,995 >> Configuration saved in ./outputs/checkpoint-1500/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 18:15:18,905 >> Model weights saved in ./outputs/checkpoint-1500/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 18:15:18,906 >> tokenizer config file saved in ./outputs/checkpoint-1500/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 18:15:18,907 >> Special tokens file saved in ./outputs/checkpoint-1500/special_tokens_map.json\n", + "{'loss': 0.058, 'learning_rate': 3.078770413064361e-05, 'epoch': 1.92}\n", + " 38% 2000/5205 [11:58<21:08, 2.53it/s][INFO|trainer.py:1917] 2021-07-19 18:18:17,862 >> Saving model checkpoint to ./outputs/checkpoint-2000\n", + "[INFO|configuration_utils.py:379] 2021-07-19 18:18:17,864 >> Configuration saved in ./outputs/checkpoint-2000/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 18:18:19,484 >> Model weights saved in ./outputs/checkpoint-2000/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 18:18:19,485 >> tokenizer config file saved in ./outputs/checkpoint-2000/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 18:18:19,485 >> Special tokens file saved in ./outputs/checkpoint-2000/special_tokens_map.json\n", + "{'loss': 0.0356, 'learning_rate': 2.5984630163304517e-05, 'epoch': 2.4}\n", + " 48% 2500/5205 [14:58<17:53, 2.52it/s][INFO|trainer.py:1917] 2021-07-19 18:21:17,596 >> Saving model checkpoint to ./outputs/checkpoint-2500\n", + "[INFO|configuration_utils.py:379] 2021-07-19 18:21:17,599 >> Configuration saved in ./outputs/checkpoint-2500/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 18:21:19,253 >> Model weights saved in ./outputs/checkpoint-2500/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 18:21:19,254 >> tokenizer config file saved in ./outputs/checkpoint-2500/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 18:21:19,254 >> Special tokens file saved in ./outputs/checkpoint-2500/special_tokens_map.json\n", + " 58% 3000/5205 [17:58<14:35, 2.52it/s]{'loss': 0.0308, 'learning_rate': 2.118155619596542e-05, 'epoch': 2.88}\n", + " 58% 3000/5205 [17:58<14:35, 2.52it/s][INFO|trainer.py:1917] 2021-07-19 18:24:17,180 >> Saving model checkpoint to ./outputs/checkpoint-3000\n", + "[INFO|configuration_utils.py:379] 2021-07-19 18:24:17,182 >> Configuration saved in ./outputs/checkpoint-3000/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 18:24:18,844 >> Model weights saved in ./outputs/checkpoint-3000/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 18:24:18,845 >> tokenizer config file saved in ./outputs/checkpoint-3000/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 18:24:18,845 >> Special tokens file saved in ./outputs/checkpoint-3000/special_tokens_map.json\n", + " 67% 3500/5205 [20:57<11:15, 2.52it/s]{'loss': 0.0189, 'learning_rate': 1.6378482228626322e-05, 'epoch': 3.36}\n", + " 67% 3500/5205 [20:57<11:15, 2.52it/s][INFO|trainer.py:1917] 2021-07-19 18:27:16,579 >> Saving model checkpoint to ./outputs/checkpoint-3500\n", + "[INFO|configuration_utils.py:379] 2021-07-19 18:27:16,581 >> Configuration saved in ./outputs/checkpoint-3500/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 18:27:18,239 >> Model weights saved in ./outputs/checkpoint-3500/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 18:27:18,240 >> tokenizer config file saved in ./outputs/checkpoint-3500/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 18:27:18,240 >> Special tokens file saved in ./outputs/checkpoint-3500/special_tokens_map.json\n", + " 77% 4000/5205 [23:57<07:53, 2.54it/s]{'loss': 0.0157, 'learning_rate': 1.1575408261287224e-05, 'epoch': 3.84}\n", + "[INFO|trainer.py:1917] 2021-07-19 18:30:16,127 >> Saving model checkpoint to ./outputs/checkpoint-4000\n", + "[INFO|configuration_utils.py:379] 2021-07-19 18:30:16,129 >> Configuration saved in ./outputs/checkpoint-4000/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 18:30:17,789 >> Model weights saved in ./outputs/checkpoint-4000/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 18:30:17,790 >> tokenizer config file saved in ./outputs/checkpoint-4000/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 18:30:17,790 >> Special tokens file saved in ./outputs/checkpoint-4000/special_tokens_map.json\n", + "{'loss': 0.0101, 'learning_rate': 6.7723342939481265e-06, 'epoch': 4.32}\n", + " 86% 4500/5205 [26:56<04:36, 2.55it/s][INFO|trainer.py:1917] 2021-07-19 18:33:15,138 >> Saving model checkpoint to ./outputs/checkpoint-4500\n", + "[INFO|configuration_utils.py:379] 2021-07-19 18:33:15,140 >> Configuration saved in ./outputs/checkpoint-4500/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 18:33:16,788 >> Model weights saved in ./outputs/checkpoint-4500/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 18:33:16,789 >> tokenizer config file saved in ./outputs/checkpoint-4500/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 18:33:16,789 >> Special tokens file saved in ./outputs/checkpoint-4500/special_tokens_map.json\n", + " 96% 5000/5205 [29:54<01:20, 2.56it/s]{'loss': 0.0065, 'learning_rate': 1.96926032660903e-06, 'epoch': 4.8}\n", + "[INFO|trainer.py:1917] 2021-07-19 18:36:13,857 >> Saving model checkpoint to ./outputs/checkpoint-5000\n", + "[INFO|configuration_utils.py:379] 2021-07-19 18:36:13,864 >> Configuration saved in ./outputs/checkpoint-5000/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 18:36:15,563 >> Model weights saved in ./outputs/checkpoint-5000/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 18:36:15,564 >> tokenizer config file saved in ./outputs/checkpoint-5000/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 18:36:15,565 >> Special tokens file saved in ./outputs/checkpoint-5000/special_tokens_map.json\n", + "100% 5205/5205 [31:11<00:00, 3.20it/s][INFO|trainer.py:1358] 2021-07-19 18:37:30,071 >> \n", + "\n", + "Training completed. Do not forget to share your model on huggingface.co/models =)\n", + "\n", + "\n", + "100% 5205/5205 [31:11<00:00, 3.20it/s]{'train_runtime': 1874.2569, 'train_samples_per_second': 22.206, 'train_steps_per_second': 2.777, 'train_loss': 0.059975996713702434, 'epoch': 5.0}\n", + "100% 5205/5205 [31:11<00:00, 2.78it/s]\n", + "[INFO|trainer.py:1917] 2021-07-19 18:37:30,085 >> Saving model checkpoint to ./outputs\n", + "[INFO|configuration_utils.py:379] 2021-07-19 18:37:30,091 >> Configuration saved in ./outputs/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 18:37:31,882 >> Model weights saved in ./outputs/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 18:37:31,883 >> tokenizer config file saved in ./outputs/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 18:37:31,883 >> Special tokens file saved in ./outputs/special_tokens_map.json\n", + "***** train metrics *****\n", + " epoch = 5.0\n", + " train_loss = 0.06\n", + " train_runtime = 0:31:14.25\n", + " train_samples = 8324\n", + " train_samples_per_second = 22.206\n", + " train_steps_per_second = 2.777\n", + "07/19/2021 18:37:31 - INFO - __main__ - *** Evaluate ***\n", + "[INFO|trainer.py:522] 2021-07-19 18:37:31,977 >> The following columns in the evaluation set don't have a corresponding argument in `BertForTokenClassification.forward` and have been ignored: pos_tags, ner_tags, tokens, id.\n", + "[INFO|trainer.py:2163] 2021-07-19 18:37:32,041 >> ***** Running Evaluation *****\n", + "[INFO|trainer.py:2165] 2021-07-19 18:37:32,041 >> Num examples = 1916\n", + "[INFO|trainer.py:2168] 2021-07-19 18:37:32,042 >> Batch size = 8\n", + "100% 239/240 [00:25<00:00, 9.17it/s]/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: NC seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: 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tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Fp seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Fg seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: DA seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: AQ seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VAI seems not to be NE tag.\n", + " 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to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: PR seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: RG seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: CS seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: CC seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Fe seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Fx seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: DD seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VSI seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: PD seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VMG seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: P0 seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: PN seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VMM seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Fd seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: AO seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: DP seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: PP seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: PI seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VSS seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VAS seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: RN seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Fat seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Faa seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: DE seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VMS seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VSN seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VSP seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Fz seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: PT seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VAN seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VSG seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: PX seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: DT seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Fh seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VAP seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Fs seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VSM seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Y seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Fia seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/v1.py:57: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n", + " _warn_prf(average, modifier, msg_start, len(result))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/v1.py:57: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n", + " _warn_prf(average, modifier, msg_start, len(result))\n", + "100% 240/240 [00:29<00:00, 8.16it/s]\n", + "***** eval metrics *****\n", + " epoch = 5.0\n", + " eval_accuracy = 0.97\n", + " eval_f1 = 0.9642\n", + " eval_loss = 0.1621\n", + " eval_precision = 0.965\n", + " eval_recall = 0.9634\n", + " eval_runtime = 0:00:29.52\n", + " eval_samples = 1916\n", + " eval_samples_per_second = 64.885\n", + " eval_steps_per_second = 8.128\n", + "\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Waiting for W&B process to finish, PID 1463\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Program ended successfully.\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: \n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Find user logs for this run at: /content/wandb/run-20210719_180616-1felky5r/logs/debug.log\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Find internal logs for this run at: /content/wandb/run-20210719_180616-1felky5r/logs/debug-internal.log\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Run summary:\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/loss 0.0065\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/learning_rate 0.0\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/epoch 5.0\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/global_step 5205\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: _runtime 1905\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: _timestamp 1626719881\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: _step 11\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_runtime 1874.2569\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_samples_per_second 22.206\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_steps_per_second 2.777\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/total_flos 1.08808736772096e+16\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_loss 0.05998\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/loss 0.16208\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/precision 0.96501\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/recall 0.9634\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/f1 0.9642\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/accuracy 0.96998\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/runtime 29.5293\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/samples_per_second 64.885\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/steps_per_second 8.128\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Run history:\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/loss █▃▃▂▂▂▁▁▁▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/learning_rate █▇▆▆▅▄▃▃▂▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/epoch ▁▂▂▃▄▅▅▆▇███\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/global_step ▁▂▂▃▄▅▅▆▇███\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: _runtime ▁▂▂▃▄▅▅▆▇███\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: _timestamp ▁▂▂▃▄▅▅▆▇███\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: _step ▁▂▂▃▄▄▅▅▆▇▇█\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_runtime ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_samples_per_second ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_steps_per_second ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/total_flos ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_loss ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/loss ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/precision ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/recall ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/f1 ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/accuracy ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/runtime ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/samples_per_second ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/steps_per_second ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: \n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Synced 5 W&B file(s), 0 media file(s), 0 artifact file(s) and 1 other file(s)\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: \n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Synced \u001b[33m./outputs\u001b[0m: \u001b[34mhttps://wandb.ai/versae/bertin-eval/runs/1felky5r\u001b[0m\n", + "2021-07-19 18:38:13.403388: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Successfully opened dynamic library libcudart.so.11.0\n", + "07/19/2021 18:38:16 - WARNING - __main__ - Process rank: -1, device: cuda:0, n_gpu: 1distributed training: False, 16-bits training: False\n", + "07/19/2021 18:38:16 - INFO - __main__ - Training/evaluation parameters TrainingArguments(\n", + "_n_gpu=1,\n", + "adafactor=False,\n", + "adam_beta1=0.9,\n", + "adam_beta2=0.999,\n", + "adam_epsilon=1e-08,\n", + "dataloader_drop_last=False,\n", + "dataloader_num_workers=0,\n", + "dataloader_pin_memory=True,\n", + "ddp_find_unused_parameters=None,\n", + "debug=[],\n", + "deepspeed=None,\n", + "disable_tqdm=False,\n", + "do_eval=True,\n", + "do_predict=False,\n", + "do_train=True,\n", + "eval_accumulation_steps=None,\n", + "eval_steps=500,\n", + "evaluation_strategy=IntervalStrategy.NO,\n", + "fp16=False,\n", + "fp16_backend=auto,\n", + "fp16_full_eval=False,\n", + "fp16_opt_level=O1,\n", + "gradient_accumulation_steps=1,\n", + "greater_is_better=None,\n", + "group_by_length=False,\n", + "ignore_data_skip=False,\n", + "label_names=None,\n", + "label_smoothing_factor=0.0,\n", + "learning_rate=5e-05,\n", + "length_column_name=length,\n", + "load_best_model_at_end=False,\n", + "local_rank=-1,\n", + "log_level=-1,\n", + "log_level_replica=-1,\n", + "log_on_each_node=True,\n", + "logging_dir=./outputs/runs/Jul19_18-38-16_eab5184de9ff,\n", + "logging_first_step=False,\n", + "logging_steps=500,\n", + "logging_strategy=IntervalStrategy.STEPS,\n", + "lr_scheduler_type=SchedulerType.LINEAR,\n", + "max_grad_norm=1.0,\n", + "max_steps=-1,\n", + "metric_for_best_model=None,\n", + "mp_parameters=,\n", + "no_cuda=False,\n", + "num_train_epochs=5.0,\n", + "output_dir=./outputs,\n", + "overwrite_output_dir=True,\n", + "past_index=-1,\n", + "per_device_eval_batch_size=8,\n", + "per_device_train_batch_size=8,\n", + "prediction_loss_only=False,\n", + "push_to_hub=False,\n", + "push_to_hub_model_id=outputs,\n", + "push_to_hub_organization=None,\n", + "push_to_hub_token=None,\n", + "remove_unused_columns=True,\n", + "report_to=['tensorboard', 'wandb'],\n", + "resume_from_checkpoint=None,\n", + "run_name=./outputs,\n", + "save_on_each_node=False,\n", + "save_steps=500,\n", + "save_strategy=IntervalStrategy.STEPS,\n", + "save_total_limit=None,\n", + "seed=42,\n", + "sharded_ddp=[],\n", + "skip_memory_metrics=True,\n", + "tpu_metrics_debug=False,\n", + "tpu_num_cores=None,\n", + "use_legacy_prediction_loop=False,\n", + "warmup_ratio=0.0,\n", + "warmup_steps=0,\n", + "weight_decay=0.0,\n", + ")\n", + "07/19/2021 18:38:17 - INFO - datasets.load - Found main folder for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py at /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002\n", + "07/19/2021 18:38:17 - INFO - datasets.load - Found specific version folder for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py at /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5\n", + "07/19/2021 18:38:17 - INFO - datasets.load - Found script file from https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py to /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5/conll2002.py\n", + "07/19/2021 18:38:17 - INFO - datasets.load - Found dataset infos file from https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/dataset_infos.json to /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5/dataset_infos.json\n", + "07/19/2021 18:38:17 - INFO - datasets.load - Found metadata file for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py at /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5/conll2002.json\n", + "07/19/2021 18:38:18 - INFO - datasets.load - Found main folder for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py at /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002\n", + "07/19/2021 18:38:18 - INFO - datasets.load - Found specific version folder for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py at /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5\n", + "07/19/2021 18:38:18 - INFO - datasets.load - Found script file from https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py to /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5/conll2002.py\n", + "07/19/2021 18:38:18 - INFO - datasets.load - Found dataset infos file from https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/dataset_infos.json to /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5/dataset_infos.json\n", + "07/19/2021 18:38:18 - INFO - datasets.load - Found metadata file for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/conll2002/conll2002.py at /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5/conll2002.json\n", + "07/19/2021 18:38:18 - INFO - datasets.info - Loading Dataset Infos from /root/.cache/huggingface/modules/datasets_modules/datasets/conll2002/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5\n", + "07/19/2021 18:38:18 - INFO - datasets.builder - Overwrite dataset info from restored data version.\n", + "07/19/2021 18:38:18 - INFO - datasets.info - Loading Dataset info from /root/.cache/huggingface/datasets/conll2002/es/1.0.0/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5\n", + "07/19/2021 18:38:18 - WARNING - datasets.builder - Reusing dataset conll2002 (/root/.cache/huggingface/datasets/conll2002/es/1.0.0/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5)\n", + "07/19/2021 18:38:18 - INFO - datasets.info - Loading Dataset info from /root/.cache/huggingface/datasets/conll2002/es/1.0.0/a3a8a8612caf57271f5b35c5ae1dd25f99ddb9efb9c1667abaa70ede33e863e5\n", + "100% 3/3 [00:00<00:00, 26.77it/s]\n", + "[INFO|configuration_utils.py:545] 2021-07-19 18:38:19,662 >> loading configuration file https://huggingface.co/bert-base-multilingual-cased/resolve/main/config.json from cache at /root/.cache/huggingface/transformers/6c4a5d81a58c9791cdf76a09bce1b5abfb9cf958aebada51200f4515403e5d08.0fe59f3f4f1335dadeb4bce8b8146199d9083512b50d07323c1c319f96df450c\n", + "[INFO|configuration_utils.py:581] 2021-07-19 18:38:19,664 >> Model config BertConfig {\n", + " \"architectures\": [\n", + " \"BertForMaskedLM\"\n", + " ],\n", + " \"attention_probs_dropout_prob\": 0.1,\n", + " \"directionality\": \"bidi\",\n", + " \"finetuning_task\": \"pos\",\n", + " \"gradient_checkpointing\": false,\n", + " \"hidden_act\": \"gelu\",\n", + " \"hidden_dropout_prob\": 0.1,\n", + " \"hidden_size\": 768,\n", + " \"id2label\": {\n", + " \"0\": 0,\n", + " \"1\": 1,\n", + " \"2\": 2,\n", + " \"3\": 3,\n", + " \"4\": 4,\n", + " \"5\": 5,\n", + " \"6\": 6,\n", + " \"7\": 7,\n", + " \"8\": 8,\n", + " \"9\": 9,\n", + " \"10\": 10,\n", + " \"11\": 11,\n", + " \"12\": 12,\n", + " \"13\": 13,\n", + " \"14\": 14,\n", + " \"15\": 15,\n", + " \"16\": 16,\n", + " \"17\": 17,\n", + " \"18\": 18,\n", + " \"19\": 19,\n", + " \"20\": 20,\n", + " \"21\": 21,\n", + " \"22\": 22,\n", + " \"23\": 23,\n", + " \"24\": 24,\n", + " \"25\": 25,\n", + " \"26\": 26,\n", + " \"27\": 27,\n", + " \"28\": 28,\n", + " \"29\": 29,\n", + " \"30\": 30,\n", + " \"31\": 31,\n", + " \"32\": 32,\n", + " \"33\": 33,\n", + " \"34\": 34,\n", + " \"35\": 35,\n", + " \"36\": 36,\n", + " \"37\": 37,\n", + " \"38\": 38,\n", + " \"39\": 39,\n", + " \"40\": 40,\n", + " \"41\": 41,\n", + " \"42\": 42,\n", + " \"43\": 43,\n", + " \"44\": 44,\n", + " \"45\": 45,\n", + " \"46\": 46,\n", + " \"47\": 47,\n", + " \"48\": 48,\n", + " \"49\": 49,\n", + " \"50\": 50,\n", + " \"51\": 51,\n", + " \"52\": 52,\n", + " \"53\": 53,\n", + " \"54\": 54,\n", + " \"55\": 55,\n", + " \"56\": 56,\n", + " \"57\": 57,\n", + " \"58\": 58,\n", + " \"59\": 59\n", + " },\n", + " \"initializer_range\": 0.02,\n", + " \"intermediate_size\": 3072,\n", + " \"label2id\": {\n", + " \"0\": 0,\n", + " \"1\": 1,\n", + " \"2\": 2,\n", + " \"3\": 3,\n", + " \"4\": 4,\n", + " \"5\": 5,\n", + " \"6\": 6,\n", + " \"7\": 7,\n", + " \"8\": 8,\n", + " \"9\": 9,\n", + " \"10\": 10,\n", + " \"11\": 11,\n", + " \"12\": 12,\n", + " \"13\": 13,\n", + " \"14\": 14,\n", + " \"15\": 15,\n", + " \"16\": 16,\n", + " \"17\": 17,\n", + " \"18\": 18,\n", + " \"19\": 19,\n", + " \"20\": 20,\n", + " \"21\": 21,\n", + " \"22\": 22,\n", + " \"23\": 23,\n", + " \"24\": 24,\n", + " \"25\": 25,\n", + " \"26\": 26,\n", + " \"27\": 27,\n", + " \"28\": 28,\n", + " \"29\": 29,\n", + " \"30\": 30,\n", + " \"31\": 31,\n", + " \"32\": 32,\n", + " \"33\": 33,\n", + " \"34\": 34,\n", + " \"35\": 35,\n", + " \"36\": 36,\n", + " \"37\": 37,\n", + " \"38\": 38,\n", + " \"39\": 39,\n", + " \"40\": 40,\n", + " \"41\": 41,\n", + " \"42\": 42,\n", + " \"43\": 43,\n", + " \"44\": 44,\n", + " \"45\": 45,\n", + " \"46\": 46,\n", + " \"47\": 47,\n", + " \"48\": 48,\n", + " \"49\": 49,\n", + " \"50\": 50,\n", + " \"51\": 51,\n", + " \"52\": 52,\n", + " \"53\": 53,\n", + " \"54\": 54,\n", + " \"55\": 55,\n", + " \"56\": 56,\n", + " \"57\": 57,\n", + " \"58\": 58,\n", + " \"59\": 59\n", + " },\n", + " \"layer_norm_eps\": 1e-12,\n", + " \"max_position_embeddings\": 512,\n", + " \"model_type\": \"bert\",\n", + " \"num_attention_heads\": 12,\n", + " \"num_hidden_layers\": 12,\n", + " \"pad_token_id\": 0,\n", + " \"pooler_fc_size\": 768,\n", + " \"pooler_num_attention_heads\": 12,\n", + " \"pooler_num_fc_layers\": 3,\n", + " \"pooler_size_per_head\": 128,\n", + " \"pooler_type\": \"first_token_transform\",\n", + " \"position_embedding_type\": \"absolute\",\n", + " \"transformers_version\": \"4.9.0.dev0\",\n", + " \"type_vocab_size\": 2,\n", + " \"use_cache\": true,\n", + " \"vocab_size\": 119547\n", + "}\n", + "\n", + "[INFO|configuration_utils.py:545] 2021-07-19 18:38:21,660 >> loading configuration file https://huggingface.co/bert-base-multilingual-cased/resolve/main/config.json from cache at /root/.cache/huggingface/transformers/6c4a5d81a58c9791cdf76a09bce1b5abfb9cf958aebada51200f4515403e5d08.0fe59f3f4f1335dadeb4bce8b8146199d9083512b50d07323c1c319f96df450c\n", + "[INFO|configuration_utils.py:581] 2021-07-19 18:38:21,661 >> Model config BertConfig {\n", + " \"architectures\": [\n", + " \"BertForMaskedLM\"\n", + " ],\n", + " \"attention_probs_dropout_prob\": 0.1,\n", + " \"directionality\": \"bidi\",\n", + " \"gradient_checkpointing\": false,\n", + " \"hidden_act\": \"gelu\",\n", + " \"hidden_dropout_prob\": 0.1,\n", + " \"hidden_size\": 768,\n", + " \"initializer_range\": 0.02,\n", + " \"intermediate_size\": 3072,\n", + " \"layer_norm_eps\": 1e-12,\n", + " \"max_position_embeddings\": 512,\n", + " \"model_type\": \"bert\",\n", + " \"num_attention_heads\": 12,\n", + " \"num_hidden_layers\": 12,\n", + " \"pad_token_id\": 0,\n", + " \"pooler_fc_size\": 768,\n", + " \"pooler_num_attention_heads\": 12,\n", + " \"pooler_num_fc_layers\": 3,\n", + " \"pooler_size_per_head\": 128,\n", + " \"pooler_type\": \"first_token_transform\",\n", + " \"position_embedding_type\": \"absolute\",\n", + " \"transformers_version\": \"4.9.0.dev0\",\n", + " \"type_vocab_size\": 2,\n", + " \"use_cache\": true,\n", + " \"vocab_size\": 119547\n", + "}\n", + "\n", + "[INFO|tokenization_utils_base.py:1722] 2021-07-19 18:38:25,288 >> loading file https://huggingface.co/bert-base-multilingual-cased/resolve/main/vocab.txt from cache at /root/.cache/huggingface/transformers/eff018e45de5364a8368df1f2df3461d506e2a111e9dd50af1fae061cd460ead.6c5b6600e968f4b5e08c86d8891ea99e51537fc2bf251435fb46922e8f7a7b29\n", + "[INFO|tokenization_utils_base.py:1722] 2021-07-19 18:38:25,288 >> loading file https://huggingface.co/bert-base-multilingual-cased/resolve/main/tokenizer.json from cache at /root/.cache/huggingface/transformers/46880f3b0081fda494a4e15b05787692aa4c1e21e0ff2428ba8b14d4eda0784d.b33e51591f94f17c238ee9b1fac75b96ff2678cbaed6e108feadb3449d18dc24\n", + "[INFO|tokenization_utils_base.py:1722] 2021-07-19 18:38:25,288 >> loading file https://huggingface.co/bert-base-multilingual-cased/resolve/main/added_tokens.json from cache at None\n", + "[INFO|tokenization_utils_base.py:1722] 2021-07-19 18:38:25,288 >> loading file https://huggingface.co/bert-base-multilingual-cased/resolve/main/special_tokens_map.json from cache at None\n", + "[INFO|tokenization_utils_base.py:1722] 2021-07-19 18:38:25,288 >> loading file https://huggingface.co/bert-base-multilingual-cased/resolve/main/tokenizer_config.json from cache at /root/.cache/huggingface/transformers/f55e7a2ad4f8d0fff2733b3f79777e1e99247f2e4583703e92ce74453af8c235.ec5c189f89475aac7d8cbd243960a0655cfadc3d0474da8ff2ed0bf1699c2a5f\n", + "[INFO|configuration_utils.py:545] 2021-07-19 18:38:26,019 >> loading configuration file https://huggingface.co/bert-base-multilingual-cased/resolve/main/config.json from cache at /root/.cache/huggingface/transformers/6c4a5d81a58c9791cdf76a09bce1b5abfb9cf958aebada51200f4515403e5d08.0fe59f3f4f1335dadeb4bce8b8146199d9083512b50d07323c1c319f96df450c\n", + "[INFO|configuration_utils.py:581] 2021-07-19 18:38:26,019 >> Model config BertConfig {\n", + " \"architectures\": [\n", + " \"BertForMaskedLM\"\n", + " ],\n", + " \"attention_probs_dropout_prob\": 0.1,\n", + " \"directionality\": \"bidi\",\n", + " \"gradient_checkpointing\": false,\n", + " \"hidden_act\": \"gelu\",\n", + " \"hidden_dropout_prob\": 0.1,\n", + " \"hidden_size\": 768,\n", + " \"initializer_range\": 0.02,\n", + " \"intermediate_size\": 3072,\n", + " \"layer_norm_eps\": 1e-12,\n", + " \"max_position_embeddings\": 512,\n", + " \"model_type\": \"bert\",\n", + " \"num_attention_heads\": 12,\n", + " \"num_hidden_layers\": 12,\n", + " \"pad_token_id\": 0,\n", + " \"pooler_fc_size\": 768,\n", + " \"pooler_num_attention_heads\": 12,\n", + " \"pooler_num_fc_layers\": 3,\n", + " \"pooler_size_per_head\": 128,\n", + " \"pooler_type\": \"first_token_transform\",\n", + " \"position_embedding_type\": \"absolute\",\n", + " \"transformers_version\": \"4.9.0.dev0\",\n", + " \"type_vocab_size\": 2,\n", + " \"use_cache\": true,\n", + " \"vocab_size\": 119547\n", + "}\n", + "\n", + "[INFO|modeling_utils.py:1271] 2021-07-19 18:38:26,896 >> loading weights file https://huggingface.co/bert-base-multilingual-cased/resolve/main/pytorch_model.bin from cache at /root/.cache/huggingface/transformers/0a3fd51713dcbb4def175c7f85bddc995d5976ce1dde327f99104e4d33069f17.aa7be4c79d76f4066d9b354496ea477c9ee39c5d889156dd1efb680643c2b052\n", + "[WARNING|modeling_utils.py:1502] 2021-07-19 18:38:38,783 >> Some weights of the model checkpoint at bert-base-multilingual-cased were not used when initializing BertForTokenClassification: ['cls.predictions.transform.LayerNorm.weight', 'cls.predictions.transform.LayerNorm.bias', 'cls.predictions.decoder.weight', 'cls.predictions.transform.dense.weight', 'cls.predictions.bias', 'cls.seq_relationship.bias', 'cls.predictions.transform.dense.bias', 'cls.seq_relationship.weight']\n", + "- This IS expected if you are initializing BertForTokenClassification from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).\n", + "- This IS NOT expected if you are initializing BertForTokenClassification from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).\n", + "[WARNING|modeling_utils.py:1513] 2021-07-19 18:38:38,784 >> Some weights of BertForTokenClassification were not initialized from the model checkpoint at bert-base-multilingual-cased and are newly initialized: ['classifier.bias', 'classifier.weight']\n", + "You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.\n", + "Running tokenizer on train dataset: 0% 0/9 [00:00> The following columns in the training set don't have a corresponding argument in `BertForTokenClassification.forward` and have been ignored: pos_tags, ner_tags, id, tokens.\n", + "[INFO|trainer.py:1162] 2021-07-19 18:38:51,323 >> ***** Running training *****\n", + "[INFO|trainer.py:1163] 2021-07-19 18:38:51,323 >> Num examples = 8324\n", + "[INFO|trainer.py:1164] 2021-07-19 18:38:51,323 >> Num Epochs = 5\n", + "[INFO|trainer.py:1165] 2021-07-19 18:38:51,324 >> Instantaneous batch size per device = 8\n", + "[INFO|trainer.py:1166] 2021-07-19 18:38:51,324 >> Total train batch size (w. parallel, distributed & accumulation) = 8\n", + "[INFO|trainer.py:1167] 2021-07-19 18:38:51,324 >> Gradient Accumulation steps = 1\n", + "[INFO|trainer.py:1168] 2021-07-19 18:38:51,324 >> Total optimization steps = 5205\n", + "[INFO|integrations.py:417] 2021-07-19 18:38:51,344 >> Automatic Weights & Biases logging enabled, to disable set os.environ[\"WANDB_DISABLED\"] = \"true\"\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Currently logged in as: \u001b[33mversae\u001b[0m (use `wandb login --relogin` to force relogin)\n", + "2021-07-19 18:38:53.056953: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Successfully opened dynamic library libcudart.so.11.0\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Tracking run with wandb version 0.11.0\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Syncing run \u001b[33m./outputs\u001b[0m\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: ⭐️ View project at \u001b[34m\u001b[4mhttps://wandb.ai/versae/bertin-eval\u001b[0m\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: 🚀 View run at \u001b[34m\u001b[4mhttps://wandb.ai/versae/bertin-eval/runs/2imdirdh\u001b[0m\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Run data is saved locally in /content/wandb/run-20210719_183851-2imdirdh\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Run `wandb offline` to turn off syncing.\n", + "\n", + " 10% 500/5205 [02:59<32:20, 2.43it/s]{'loss': 0.2935, 'learning_rate': 4.5196926032660905e-05, 'epoch': 0.48}\n", + " 10% 500/5205 [02:59<32:20, 2.43it/s][INFO|trainer.py:1917] 2021-07-19 18:41:54,160 >> Saving model checkpoint to ./outputs/checkpoint-500\n", + "[INFO|configuration_utils.py:379] 2021-07-19 18:41:54,162 >> Configuration saved in ./outputs/checkpoint-500/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 18:41:57,418 >> Model weights saved in ./outputs/checkpoint-500/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 18:41:57,419 >> tokenizer config file saved in ./outputs/checkpoint-500/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 18:41:57,419 >> Special tokens file saved in ./outputs/checkpoint-500/special_tokens_map.json\n", + "{'loss': 0.1177, 'learning_rate': 4.039385206532181e-05, 'epoch': 0.96}\n", + " 19% 1000/5205 [06:08<28:48, 2.43it/s][INFO|trainer.py:1917] 2021-07-19 18:45:02,966 >> Saving model checkpoint to ./outputs/checkpoint-1000\n", + "[INFO|configuration_utils.py:379] 2021-07-19 18:45:02,968 >> Configuration saved in ./outputs/checkpoint-1000/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 18:45:05,616 >> Model weights saved in ./outputs/checkpoint-1000/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 18:45:05,617 >> tokenizer config file saved in ./outputs/checkpoint-1000/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 18:45:05,618 >> Special tokens file saved in ./outputs/checkpoint-1000/special_tokens_map.json\n", + " 29% 1500/5205 [09:16<25:24, 2.43it/s]{'loss': 0.0794, 'learning_rate': 3.5590778097982716e-05, 'epoch': 1.44}\n", + "[INFO|trainer.py:1917] 2021-07-19 18:48:11,131 >> Saving model checkpoint to ./outputs/checkpoint-1500\n", + "[INFO|configuration_utils.py:379] 2021-07-19 18:48:11,133 >> Configuration saved in ./outputs/checkpoint-1500/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 18:48:13,690 >> Model weights saved in ./outputs/checkpoint-1500/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 18:48:13,691 >> tokenizer config file saved in ./outputs/checkpoint-1500/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 18:48:13,691 >> Special tokens file saved in ./outputs/checkpoint-1500/special_tokens_map.json\n", + " 38% 2000/5205 [12:27<21:56, 2.44it/s]{'loss': 0.0721, 'learning_rate': 3.078770413064361e-05, 'epoch': 1.92}\n", + " 38% 2000/5205 [12:27<21:56, 2.44it/s][INFO|trainer.py:1917] 2021-07-19 18:51:22,110 >> Saving model checkpoint to ./outputs/checkpoint-2000\n", + "[INFO|configuration_utils.py:379] 2021-07-19 18:51:22,112 >> Configuration saved in ./outputs/checkpoint-2000/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 18:51:24,734 >> Model weights saved in ./outputs/checkpoint-2000/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 18:51:24,735 >> tokenizer config file saved in ./outputs/checkpoint-2000/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 18:51:24,735 >> Special tokens file saved in ./outputs/checkpoint-2000/special_tokens_map.json\n", + " 48% 2500/5205 [15:36<18:33, 2.43it/s]{'loss': 0.0457, 'learning_rate': 2.5984630163304517e-05, 'epoch': 2.4}\n", + " 48% 2500/5205 [15:36<18:33, 2.43it/s][INFO|trainer.py:1917] 2021-07-19 18:54:30,708 >> Saving model checkpoint to ./outputs/checkpoint-2500\n", + "[INFO|configuration_utils.py:379] 2021-07-19 18:54:30,710 >> Configuration saved in ./outputs/checkpoint-2500/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 18:54:33,601 >> Model weights saved in ./outputs/checkpoint-2500/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 18:54:33,602 >> tokenizer config file saved in ./outputs/checkpoint-2500/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 18:54:33,603 >> Special tokens file saved in ./outputs/checkpoint-2500/special_tokens_map.json\n", + "{'loss': 0.0423, 'learning_rate': 2.118155619596542e-05, 'epoch': 2.88}\n", + " 58% 3000/5205 [18:44<15:13, 2.41it/s][INFO|trainer.py:1917] 2021-07-19 18:57:39,382 >> Saving model checkpoint to ./outputs/checkpoint-3000\n", + "[INFO|configuration_utils.py:379] 2021-07-19 18:57:39,384 >> Configuration saved in ./outputs/checkpoint-3000/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 18:57:42,172 >> Model weights saved in ./outputs/checkpoint-3000/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 18:57:42,173 >> tokenizer config file saved in ./outputs/checkpoint-3000/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 18:57:42,173 >> Special tokens file saved in ./outputs/checkpoint-3000/special_tokens_map.json\n", + " 67% 3500/5205 [21:53<11:29, 2.47it/s]{'loss': 0.0278, 'learning_rate': 1.6378482228626322e-05, 'epoch': 3.36}\n", + "[INFO|trainer.py:1917] 2021-07-19 19:00:47,421 >> Saving model checkpoint to ./outputs/checkpoint-3500\n", + "[INFO|configuration_utils.py:379] 2021-07-19 19:00:47,425 >> Configuration saved in ./outputs/checkpoint-3500/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 19:00:50,395 >> Model weights saved in ./outputs/checkpoint-3500/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 19:00:50,396 >> tokenizer config file saved in ./outputs/checkpoint-3500/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 19:00:50,396 >> Special tokens file saved in ./outputs/checkpoint-3500/special_tokens_map.json\n", + " 77% 4000/5205 [25:00<08:14, 2.44it/s]{'loss': 0.0228, 'learning_rate': 1.1575408261287224e-05, 'epoch': 3.84}\n", + "[INFO|trainer.py:1917] 2021-07-19 19:03:55,323 >> Saving model checkpoint to ./outputs/checkpoint-4000\n", + "[INFO|configuration_utils.py:379] 2021-07-19 19:03:55,325 >> Configuration saved in ./outputs/checkpoint-4000/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 19:03:58,214 >> Model weights saved in ./outputs/checkpoint-4000/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 19:03:58,215 >> tokenizer config file saved in ./outputs/checkpoint-4000/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 19:03:58,215 >> Special tokens file saved in ./outputs/checkpoint-4000/special_tokens_map.json\n", + " 86% 4500/5205 [28:08<04:45, 2.47it/s]{'loss': 0.0152, 'learning_rate': 6.7723342939481265e-06, 'epoch': 4.32}\n", + "[INFO|trainer.py:1917] 2021-07-19 19:07:02,887 >> Saving model checkpoint to ./outputs/checkpoint-4500\n", + "[INFO|configuration_utils.py:379] 2021-07-19 19:07:02,890 >> Configuration saved in ./outputs/checkpoint-4500/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 19:07:05,844 >> Model weights saved in ./outputs/checkpoint-4500/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 19:07:05,845 >> tokenizer config file saved in ./outputs/checkpoint-4500/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 19:07:05,845 >> Special tokens file saved in ./outputs/checkpoint-4500/special_tokens_map.json\n", + "{'loss': 0.0114, 'learning_rate': 1.96926032660903e-06, 'epoch': 4.8}\n", + " 96% 5000/5205 [31:15<01:23, 2.44it/s][INFO|trainer.py:1917] 2021-07-19 19:10:10,280 >> Saving model checkpoint to ./outputs/checkpoint-5000\n", + "[INFO|configuration_utils.py:379] 2021-07-19 19:10:10,283 >> Configuration saved in ./outputs/checkpoint-5000/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 19:10:13,378 >> Model weights saved in ./outputs/checkpoint-5000/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 19:10:13,379 >> tokenizer config file saved in ./outputs/checkpoint-5000/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 19:10:13,379 >> Special tokens file saved in ./outputs/checkpoint-5000/special_tokens_map.json\n", + "100% 5205/5205 [32:38<00:00, 3.12it/s][INFO|trainer.py:1358] 2021-07-19 19:11:32,764 >> \n", + "\n", + "Training completed. Do not forget to share your model on huggingface.co/models =)\n", + "\n", + "\n", + "{'train_runtime': 1961.4409, 'train_samples_per_second': 21.219, 'train_steps_per_second': 2.654, 'train_loss': 0.07034576014757843, 'epoch': 5.0}\n", + "100% 5205/5205 [32:38<00:00, 2.66it/s]\n", + "[INFO|trainer.py:1917] 2021-07-19 19:11:32,775 >> Saving model checkpoint to ./outputs\n", + "[INFO|configuration_utils.py:379] 2021-07-19 19:11:32,780 >> Configuration saved in ./outputs/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-19 19:11:35,689 >> Model weights saved in ./outputs/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-19 19:11:35,689 >> tokenizer config file saved in ./outputs/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-19 19:11:35,690 >> Special tokens file saved in ./outputs/special_tokens_map.json\n", + "***** train metrics *****\n", + " epoch = 5.0\n", + " train_loss = 0.0703\n", + " train_runtime = 0:32:41.44\n", + " train_samples = 8324\n", + " train_samples_per_second = 21.219\n", + " train_steps_per_second = 2.654\n", + "07/19/2021 19:11:35 - INFO - __main__ - *** Evaluate ***\n", + "[INFO|trainer.py:522] 2021-07-19 19:11:35,971 >> The following columns in the evaluation set don't have a corresponding argument in `BertForTokenClassification.forward` and have been ignored: pos_tags, ner_tags, id, tokens.\n", + "[INFO|trainer.py:2163] 2021-07-19 19:11:35,991 >> ***** Running Evaluation *****\n", + "[INFO|trainer.py:2165] 2021-07-19 19:11:35,992 >> Num examples = 1916\n", + "[INFO|trainer.py:2168] 2021-07-19 19:11:35,992 >> Batch size = 8\n", + "100% 239/240 [00:25<00:00, 9.28it/s]/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: NC seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VMI seems not to be NE tag.\n", + " 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"/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: DP seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: PP seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: PI seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VSS seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VAS seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: RN seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Fat seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Faa seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: DE seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VMS seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VSN seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VSP seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Fz seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: PT seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VAN seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VSG seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: PX seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: DT seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Fh seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VAP seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Fs seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: VSM seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Y seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Fia seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: Fit seems not to be NE tag.\n", + " warnings.warn('{} seems not to be NE tag.'.format(chunk))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/v1.py:57: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n", + " _warn_prf(average, modifier, msg_start, len(result))\n", + "/usr/local/lib/python3.7/dist-packages/seqeval/metrics/v1.py:57: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n", + " _warn_prf(average, modifier, msg_start, len(result))\n", + "100% 240/240 [00:29<00:00, 8.24it/s]\n", + "***** eval metrics *****\n", + " epoch = 5.0\n", + " eval_accuracy = 0.9687\n", + " eval_f1 = 0.9629\n", + " eval_loss = 0.1579\n", + " eval_precision = 0.9637\n", + " eval_recall = 0.9621\n", + " eval_runtime = 0:00:29.26\n", + " eval_samples = 1916\n", + " eval_samples_per_second = 65.46\n", + " eval_steps_per_second = 8.2\n", + "\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Waiting for W&B process to finish, PID 1527\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Program ended successfully.\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: \n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Find user logs for this run at: /content/wandb/run-20210719_183851-2imdirdh/logs/debug.log\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Find internal logs for this run at: /content/wandb/run-20210719_183851-2imdirdh/logs/debug-internal.log\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Run summary:\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/loss 0.0114\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/learning_rate 0.0\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/epoch 5.0\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/global_step 5205\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: _runtime 1994\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: _timestamp 1626721925\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: _step 11\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_runtime 1961.4409\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_samples_per_second 21.219\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_steps_per_second 2.654\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/total_flos 1.08808736772096e+16\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_loss 0.07035\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/loss 0.15789\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/precision 0.96365\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/recall 0.96213\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/f1 0.96289\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/accuracy 0.96865\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/runtime 29.2699\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/samples_per_second 65.46\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/steps_per_second 8.2\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Run history:\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/loss █▄▃▃▂▂▁▁▁▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/learning_rate █▇▆▆▅▄▃▃▂▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/epoch ▁▂▂▃▄▅▅▆▇███\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/global_step ▁▂▂▃▄▅▅▆▇███\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: _runtime ▁▂▂▃▄▅▅▆▇███\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: _timestamp ▁▂▂▃▄▅▅▆▇███\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: _step ▁▂▂▃▄▄▅▅▆▇▇█\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_runtime ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_samples_per_second ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_steps_per_second ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/total_flos ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_loss ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/loss ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/precision ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/recall ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/f1 ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/accuracy ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/runtime ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/samples_per_second ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/steps_per_second ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: \n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Synced 5 W&B file(s), 0 media file(s), 0 artifact file(s) and 1 other file(s)\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: \n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Synced \u001b[33m./outputs\u001b[0m: \u001b[34mhttps://wandb.ai/versae/bertin-eval/runs/2imdirdh\u001b[0m\n" + ], + "name": "stdout" + } + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "yxSsy8vOVwu7" + }, + "source": [ + "----" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "y-A-WE75Ffv6" + }, + "source": [ + "## Sequence" + ] + }, + { + "cell_type": "code", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "n8XiKFkjbVzh", + "outputId": "b8454d93-4afa-409b-a934-943a7349014b" + }, + "source": [ + "!wget https://raw.githubusercontent.com/huggingface/transformers/master/examples/pytorch/text-classification/run_glue.py" + ], + "execution_count": null, + "outputs": [ + { + "output_type": "stream", + "text": [ + "--2021-07-20 08:36:03-- https://raw.githubusercontent.com/huggingface/transformers/master/examples/pytorch/text-classification/run_glue.py\n", + "Resolving raw.githubusercontent.com (raw.githubusercontent.com)... 185.199.108.133, 185.199.109.133, 185.199.110.133, ...\n", + "Connecting to raw.githubusercontent.com (raw.githubusercontent.com)|185.199.108.133|:443... connected.\n", + "HTTP request sent, awaiting response... 200 OK\n", + "Length: 24931 (24K) [text/plain]\n", + "Saving to: ‘run_glue.py’\n", + "\n", + "\rrun_glue.py 0%[ ] 0 --.-KB/s \rrun_glue.py 100%[===================>] 24.35K --.-KB/s in 0s \n", + "\n", + "2021-07-20 08:36:04 (94.8 MB/s) - ‘run_glue.py’ saved [24931/24931]\n", + "\n" + ], + "name": "stdout" + } + ] + }, + { + "cell_type": "code", + "metadata": { + "colab": { + "background_save": true, + "base_uri": "https://localhost:8080/" + }, + "id": "PhlGkj5_9mj8", + "outputId": "ce4374be-3410-4b1a-92ae-b7dc5bf84b66" + }, + "source": [ + "# !wget https://raw.githubusercontent.com/huggingface/transformers/master/examples/pytorch/token-classification/run_ner.py\n", + "for model in models:\n", + " !WANDB_PROJECT=bertin-eval TOKENIZERS_PARALLELISM=false CUDA_LAUNCH_BLOCKING=1 python run_glue.py \\\n", + " --model_name_or_path $model \\\n", + " --dataset_name \"paws-x\" \\\n", + " --task_name \"paws-x\" \\\n", + " --dataset_config_name \"es\" \\\n", + " --output_dir ./outputs \\\n", + " --overwrite_output_dir \\\n", + " --pad_to_max_length \\\n", + " --num_train_epochs 5 \\\n", + " --do_train \\\n", + " --do_eval" + ], + "execution_count": null, + "outputs": [ + { + "output_type": "stream", + "text": [ + "2021-07-20 09:49:17.108527: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Successfully opened dynamic library libcudart.so.11.0\n", + "07/20/2021 09:49:18 - WARNING - __main__ - Process rank: -1, device: cuda:0, n_gpu: 1distributed training: False, 16-bits training: False\n", + "07/20/2021 09:49:18 - INFO - __main__ - Training/evaluation parameters TrainingArguments(\n", + "_n_gpu=1,\n", + "adafactor=False,\n", + "adam_beta1=0.9,\n", + "adam_beta2=0.999,\n", + "adam_epsilon=1e-08,\n", + "dataloader_drop_last=False,\n", + "dataloader_num_workers=0,\n", + "dataloader_pin_memory=True,\n", + "ddp_find_unused_parameters=None,\n", + "debug=[],\n", + "deepspeed=None,\n", + "disable_tqdm=False,\n", + "do_eval=True,\n", + "do_predict=False,\n", + "do_train=True,\n", + "eval_accumulation_steps=None,\n", + "eval_steps=500,\n", + "evaluation_strategy=IntervalStrategy.NO,\n", + "fp16=False,\n", + "fp16_backend=auto,\n", + "fp16_full_eval=False,\n", + "fp16_opt_level=O1,\n", + "gradient_accumulation_steps=1,\n", + "greater_is_better=None,\n", + "group_by_length=False,\n", + "ignore_data_skip=False,\n", + "label_names=None,\n", + "label_smoothing_factor=0.0,\n", + "learning_rate=5e-05,\n", + "length_column_name=length,\n", + "load_best_model_at_end=False,\n", + "local_rank=-1,\n", + "log_level=-1,\n", + "log_level_replica=-1,\n", + "log_on_each_node=True,\n", + "logging_dir=./outputs/runs/Jul20_09-49-18_48f3f265b421,\n", + "logging_first_step=False,\n", + "logging_steps=500,\n", + "logging_strategy=IntervalStrategy.STEPS,\n", + "lr_scheduler_type=SchedulerType.LINEAR,\n", + "max_grad_norm=1.0,\n", + "max_steps=-1,\n", + "metric_for_best_model=None,\n", + "mp_parameters=,\n", + "no_cuda=False,\n", + "num_train_epochs=5.0,\n", + "output_dir=./outputs,\n", + "overwrite_output_dir=True,\n", + "past_index=-1,\n", + "per_device_eval_batch_size=8,\n", + "per_device_train_batch_size=8,\n", + "prediction_loss_only=False,\n", + "push_to_hub=False,\n", + "push_to_hub_model_id=outputs,\n", + "push_to_hub_organization=None,\n", + "push_to_hub_token=None,\n", + "remove_unused_columns=True,\n", + "report_to=['tensorboard', 'wandb'],\n", + "resume_from_checkpoint=None,\n", + "run_name=./outputs,\n", + "save_on_each_node=False,\n", + "save_steps=500,\n", + "save_strategy=IntervalStrategy.STEPS,\n", + "save_total_limit=None,\n", + "seed=42,\n", + "sharded_ddp=[],\n", + "skip_memory_metrics=True,\n", + "tpu_metrics_debug=False,\n", + "tpu_num_cores=None,\n", + "use_legacy_prediction_loop=False,\n", + "warmup_ratio=0.0,\n", + "warmup_steps=0,\n", + "weight_decay=0.0,\n", + ")\n", + "07/20/2021 09:49:19 - INFO - datasets.load - Found main folder for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/paws-x/paws-x.py at /root/.cache/huggingface/modules/datasets_modules/datasets/paws-x\n", + "07/20/2021 09:49:19 - INFO - datasets.load - Found specific version folder for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/paws-x/paws-x.py at /root/.cache/huggingface/modules/datasets_modules/datasets/paws-x/a5033b43902a02a4ba2ee469c1dd22af3e6a4a247ac47fa1af9835d0e734e2af\n", + "07/20/2021 09:49:19 - INFO - datasets.load - Found script file from https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/paws-x/paws-x.py to /root/.cache/huggingface/modules/datasets_modules/datasets/paws-x/a5033b43902a02a4ba2ee469c1dd22af3e6a4a247ac47fa1af9835d0e734e2af/paws-x.py\n", + "07/20/2021 09:49:19 - INFO - datasets.load - Found dataset infos file from https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/paws-x/dataset_infos.json to /root/.cache/huggingface/modules/datasets_modules/datasets/paws-x/a5033b43902a02a4ba2ee469c1dd22af3e6a4a247ac47fa1af9835d0e734e2af/dataset_infos.json\n", + "07/20/2021 09:49:19 - INFO - datasets.load - Found metadata file for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/paws-x/paws-x.py at /root/.cache/huggingface/modules/datasets_modules/datasets/paws-x/a5033b43902a02a4ba2ee469c1dd22af3e6a4a247ac47fa1af9835d0e734e2af/paws-x.json\n", + "07/20/2021 09:49:20 - INFO - datasets.load - Found main folder for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/paws-x/paws-x.py at /root/.cache/huggingface/modules/datasets_modules/datasets/paws-x\n", + "07/20/2021 09:49:20 - INFO - datasets.load - Found specific version folder for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/paws-x/paws-x.py at /root/.cache/huggingface/modules/datasets_modules/datasets/paws-x/a5033b43902a02a4ba2ee469c1dd22af3e6a4a247ac47fa1af9835d0e734e2af\n", + "07/20/2021 09:49:20 - INFO - datasets.load - Found script file from https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/paws-x/paws-x.py to /root/.cache/huggingface/modules/datasets_modules/datasets/paws-x/a5033b43902a02a4ba2ee469c1dd22af3e6a4a247ac47fa1af9835d0e734e2af/paws-x.py\n", + "07/20/2021 09:49:20 - INFO - datasets.load - Found dataset infos file from https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/paws-x/dataset_infos.json to /root/.cache/huggingface/modules/datasets_modules/datasets/paws-x/a5033b43902a02a4ba2ee469c1dd22af3e6a4a247ac47fa1af9835d0e734e2af/dataset_infos.json\n", + "07/20/2021 09:49:20 - INFO - datasets.load - Found metadata file for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/paws-x/paws-x.py at /root/.cache/huggingface/modules/datasets_modules/datasets/paws-x/a5033b43902a02a4ba2ee469c1dd22af3e6a4a247ac47fa1af9835d0e734e2af/paws-x.json\n", + "07/20/2021 09:49:20 - INFO - datasets.info - Loading Dataset Infos from /root/.cache/huggingface/modules/datasets_modules/datasets/paws-x/a5033b43902a02a4ba2ee469c1dd22af3e6a4a247ac47fa1af9835d0e734e2af\n", + "07/20/2021 09:49:20 - INFO - datasets.builder - Overwrite dataset info from restored data version.\n", + "07/20/2021 09:49:20 - INFO - datasets.info - Loading Dataset info from /root/.cache/huggingface/datasets/pawsx/es/1.1.0/a5033b43902a02a4ba2ee469c1dd22af3e6a4a247ac47fa1af9835d0e734e2af\n", + "07/20/2021 09:49:20 - WARNING - datasets.builder - Reusing dataset pawsx (/root/.cache/huggingface/datasets/pawsx/es/1.1.0/a5033b43902a02a4ba2ee469c1dd22af3e6a4a247ac47fa1af9835d0e734e2af)\n", + "07/20/2021 09:49:20 - INFO - datasets.info - Loading Dataset info from /root/.cache/huggingface/datasets/pawsx/es/1.1.0/a5033b43902a02a4ba2ee469c1dd22af3e6a4a247ac47fa1af9835d0e734e2af\n", + "100% 3/3 [00:00<00:00, 647.94it/s]\n", + "[INFO|configuration_utils.py:545] 2021-07-20 09:49:20,512 >> loading configuration file https://huggingface.co/bertin-project/bertin-base-gaussian-exp-512seqlen/resolve/main/config.json from cache at /root/.cache/huggingface/transformers/ff85ac64e56df502ec043af591c8b7be85583b22e6a4f5715146d461cd789f97.08210214ecaf5cd53c702826a604e564d8af557125033eef720f4f9f2af1fc44\n", + "[INFO|configuration_utils.py:581] 2021-07-20 09:49:20,512 >> Model config RobertaConfig {\n", + " \"architectures\": [\n", + " \"RobertaForMaskedLM\"\n", + " ],\n", + " \"attention_probs_dropout_prob\": 0.1,\n", + " \"bos_token_id\": 0,\n", + " \"eos_token_id\": 2,\n", + " \"finetuning_task\": \"paws-x\",\n", + " \"gradient_checkpointing\": false,\n", + " \"hidden_act\": \"gelu\",\n", + " \"hidden_dropout_prob\": 0.1,\n", + " \"hidden_size\": 768,\n", + " \"initializer_range\": 0.02,\n", + " \"intermediate_size\": 3072,\n", + " \"layer_norm_eps\": 1e-05,\n", + " \"max_position_embeddings\": 514,\n", + " \"model_type\": \"roberta\",\n", + " \"num_attention_heads\": 12,\n", + " \"num_hidden_layers\": 12,\n", + " \"pad_token_id\": 1,\n", + " \"position_embedding_type\": \"absolute\",\n", + " \"transformers_version\": \"4.9.0.dev0\",\n", + " \"type_vocab_size\": 1,\n", + " \"use_cache\": true,\n", + " \"vocab_size\": 50265\n", + "}\n", + "\n", + "[INFO|tokenization_utils_base.py:1722] 2021-07-20 09:49:22,941 >> loading file https://huggingface.co/bertin-project/bertin-base-gaussian-exp-512seqlen/resolve/main/vocab.json from cache at /root/.cache/huggingface/transformers/6eaae493de84fa6ec66bcb5673055437acaefce1f59d8601bc2fe5c67e118d1c.a80f232f572026f92499b14999a8ed4e044e04cf3d01b9f2be298c98e78e8498\n", + "[INFO|tokenization_utils_base.py:1722] 2021-07-20 09:49:22,941 >> loading file 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https://huggingface.co/bertin-project/bertin-base-gaussian-exp-512seqlen/resolve/main/special_tokens_map.json from cache at /root/.cache/huggingface/transformers/051ab3c041e9debc74f58f307de15b70a96de57e0f4b31ceaae21fe4eea531ec.a11ebb04664c067c8fe5ef8f8068b0f721263414a26058692f7b2e4ba2a1b342\n", + "[INFO|tokenization_utils_base.py:1722] 2021-07-20 09:49:22,942 >> loading file https://huggingface.co/bertin-project/bertin-base-gaussian-exp-512seqlen/resolve/main/tokenizer_config.json from cache at /root/.cache/huggingface/transformers/1d0cecadbe0c9f16993a436d0ab40b879322ac605869d265787a93ea1e00ec7a.9f7ac4246b492dfa7c21beb5233deec8aef46153ec25ac5258ac5e2ae82dfa89\n", + "[INFO|modeling_utils.py:1271] 2021-07-20 09:49:23,355 >> loading weights file https://huggingface.co/bertin-project/bertin-base-gaussian-exp-512seqlen/resolve/main/pytorch_model.bin from cache at /root/.cache/huggingface/transformers/c4dacb0e6c084991812c2661ba4b4e6fc953317a1ed82b01bba8d1ceb63b27f9.129191ea8bf16f2e8f2c4683b881711c55eb0c166d86300274c92ee25c49aedc\n", + "[WARNING|modeling_utils.py:1502] 2021-07-20 09:49:24,672 >> Some weights of the model checkpoint at bertin-project/bertin-base-gaussian-exp-512seqlen were not used when initializing RobertaForSequenceClassification: ['lm_head.layer_norm.bias', 'lm_head.layer_norm.weight', 'lm_head.dense.bias', 'lm_head.bias', 'lm_head.dense.weight']\n", + "- This IS expected if you are initializing RobertaForSequenceClassification from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).\n", + "- This IS NOT expected if you are initializing RobertaForSequenceClassification from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).\n", + "[WARNING|modeling_utils.py:1513] 2021-07-20 09:49:24,673 >> Some weights of RobertaForSequenceClassification were not initialized from the model checkpoint at bertin-project/bertin-base-gaussian-exp-512seqlen and are newly initialized: ['classifier.out_proj.weight', 'classifier.out_proj.bias', 'classifier.dense.weight', 'classifier.dense.bias']\n", + "You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.\n", + "07/20/2021 09:49:24 - WARNING - datasets.arrow_dataset - Loading cached processed dataset at /root/.cache/huggingface/datasets/pawsx/es/1.1.0/a5033b43902a02a4ba2ee469c1dd22af3e6a4a247ac47fa1af9835d0e734e2af/cache-84d89421334c2350.arrow\n", + "07/20/2021 09:49:24 - WARNING - datasets.arrow_dataset - Loading cached processed dataset at /root/.cache/huggingface/datasets/pawsx/es/1.1.0/a5033b43902a02a4ba2ee469c1dd22af3e6a4a247ac47fa1af9835d0e734e2af/cache-d75a7dc622a49f4d.arrow\n", + "07/20/2021 09:49:24 - WARNING - datasets.arrow_dataset - Loading cached processed dataset at /root/.cache/huggingface/datasets/pawsx/es/1.1.0/a5033b43902a02a4ba2ee469c1dd22af3e6a4a247ac47fa1af9835d0e734e2af/cache-9d49171b30b97c19.arrow\n", + "07/20/2021 09:49:24 - INFO - __main__ - Sample 41905 of the training set: {'attention_mask': [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], 'id': 41906, 'input_ids': [548, 1929, 692, 6768, 339, 34513, 1345, 69, 445, 329, 5588, 7357, 16, 298, 12773, 43545, 263, 15438, 405, 4843, 263, 14133, 18, 548, 1929, 692, 6768, 339, 34513, 1345, 69, 445, 329, 5588, 7357, 16, 298, 12773, 43545, 263, 15438, 405, 12137, 263, 15284, 18, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], 'label': 1, 'sentence1': 'El gobierno fue dirigido por Gordon Coates del Partido Unido, con George Forbes de Reforma como ministro de finanzas.', 'sentence2': 'El gobierno fue dirigido por Gordon Coates del Partido Unido, con George Forbes de Reforma como Ministro de Finanzas.'}.\n", + "07/20/2021 09:49:24 - INFO - __main__ - Sample 7296 of the training set: {'attention_mask': [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], 'id': 7297, 'input_ids': [548, 1229, 32484, 88, 291, 280, 477, 23041, 16, 486, 11944, 5436, 443, 552, 302, 41794, 11944, 285, 771, 34831, 686, 3543, 631, 46, 2930, 51, 14260, 6, 879, 75, 11944, 8535, 18, 1131, 879, 75, 11944, 406, 528, 302, 879, 75, 11944, 14720, 34831, 686, 3543, 25719, 68, 508, 4298, 454, 18295, 1608, 32484, 88, 291, 363, 477, 23041, 1332, 11944, 5436, 443, 8535, 21440, 18, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], 'label': 0, 'sentence1': 'El gujarat y mumbai, maharashtra son un sanghar en parte hindú también llamado \"JAMOTAR\" Sanghar India.', 'sentence2': \"Los Sanghar (son un Sanghar parcialmente hindú también llamado `` Jamotar '' Gujarat y Mumbai Maharashtra India llamaron.\"}.\n", + "07/20/2021 09:49:24 - INFO - __main__ - Sample 1639 of the training set: {'attention_mask': [1, 1, 1, 1, 1, 1, 1, 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comenzó en 1950 a través de un pequeño grupo de científicos y fisiólogos médicos en el Laboratorio de Ciencia de la Defensa, Delhi.', 'sentence2': 'La investigación sobre fisiología militar comenzó en 1950 por un pequeño grupo de científicos y fisiólogos médicos en el Laboratorio de Ciencia de la Defensa en Delhi.'}.\n", + "07/20/2021 09:49:25 - INFO - datasets.load - Found main folder for metric https://raw.githubusercontent.com/huggingface/datasets/1.9.0/metrics/accuracy/accuracy.py at /root/.cache/huggingface/modules/datasets_modules/metrics/accuracy\n", + "07/20/2021 09:49:25 - INFO - datasets.load - Found specific version folder for metric https://raw.githubusercontent.com/huggingface/datasets/1.9.0/metrics/accuracy/accuracy.py at /root/.cache/huggingface/modules/datasets_modules/metrics/accuracy/d60e08bd37e7c5a7bcc3620dd0d2788d25d233238ee0bdb3cfabde6c43d60574\n", + "07/20/2021 09:49:25 - INFO - datasets.load - Found script file from https://raw.githubusercontent.com/huggingface/datasets/1.9.0/metrics/accuracy/accuracy.py to /root/.cache/huggingface/modules/datasets_modules/metrics/accuracy/d60e08bd37e7c5a7bcc3620dd0d2788d25d233238ee0bdb3cfabde6c43d60574/accuracy.py\n", + "07/20/2021 09:49:25 - INFO - datasets.load - Couldn't find dataset infos file at https://raw.githubusercontent.com/huggingface/datasets/1.9.0/metrics/accuracy/dataset_infos.json\n", + "07/20/2021 09:49:25 - INFO - datasets.load - Found metadata file for metric https://raw.githubusercontent.com/huggingface/datasets/1.9.0/metrics/accuracy/accuracy.py at /root/.cache/huggingface/modules/datasets_modules/metrics/accuracy/d60e08bd37e7c5a7bcc3620dd0d2788d25d233238ee0bdb3cfabde6c43d60574/accuracy.json\n", + "[INFO|trainer.py:522] 2021-07-20 09:49:28,301 >> The following columns in the training set don't have a corresponding argument in `RobertaForSequenceClassification.forward` and have been ignored: sentence1, id, sentence2.\n", + "[INFO|trainer.py:1162] 2021-07-20 09:49:28,314 >> ***** Running training *****\n", + "[INFO|trainer.py:1163] 2021-07-20 09:49:28,314 >> Num examples = 49401\n", + "[INFO|trainer.py:1164] 2021-07-20 09:49:28,314 >> Num Epochs = 5\n", + "[INFO|trainer.py:1165] 2021-07-20 09:49:28,314 >> Instantaneous batch size per device = 8\n", + "[INFO|trainer.py:1166] 2021-07-20 09:49:28,315 >> Total train batch size (w. parallel, distributed & accumulation) = 8\n", + "[INFO|trainer.py:1167] 2021-07-20 09:49:28,315 >> Gradient Accumulation steps = 1\n", + "[INFO|trainer.py:1168] 2021-07-20 09:49:28,315 >> Total optimization steps = 30880\n", + "[INFO|integrations.py:446] 2021-07-20 09:49:28,326 >> Automatic Weights & Biases logging enabled, to disable set os.environ[\"WANDB_DISABLED\"] = \"true\"\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Currently logged in as: \u001b[33mversae\u001b[0m (use `wandb login --relogin` to force relogin)\n", + "2021-07-20 09:49:29.625318: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Successfully opened dynamic library libcudart.so.11.0\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Tracking run with wandb version 0.11.0\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Syncing run \u001b[33m./outputs\u001b[0m\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: ⭐️ View project at \u001b[34m\u001b[4mhttps://wandb.ai/versae/bertin-eval\u001b[0m\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: 🚀 View run at \u001b[34m\u001b[4mhttps://wandb.ai/versae/bertin-eval/runs/3kwtbkiz\u001b[0m\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Run data is saved locally in /content/wandb/run-20210720_094928-3kwtbkiz\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Run `wandb offline` to turn off syncing.\n", + "\n", + "{'loss': 0.6452, 'learning_rate': 4.919041450777203e-05, 'epoch': 0.08}\n", + " 2% 500/30880 [01:36<2:48:52, 3.00it/s][INFO|trainer.py:1917] 2021-07-20 09:51:06,931 >> Saving model checkpoint to ./outputs/checkpoint-500\n", + "[INFO|configuration_utils.py:379] 2021-07-20 09:51:06,933 >> Configuration saved in ./outputs/checkpoint-500/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-20 09:51:08,483 >> Model weights saved in ./outputs/checkpoint-500/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-20 09:51:08,483 >> tokenizer config file saved in ./outputs/checkpoint-500/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-20 09:51:08,484 >> Special tokens file saved in ./outputs/checkpoint-500/special_tokens_map.json\n", + " {'loss': 0.491, 'learning_rate': 4.8380829015544046e-05, 'epoch': 0.16}\n", + " 3% 1000/30880 [03:18<2:44:01, 3.04it/s][INFO|trainer.py:1917] 2021-07-20 09:52:49,299 >> Saving model checkpoint to ./outputs/checkpoint-1000\n", + "[INFO|configuration_utils.py:379] 2021-07-20 09:52:49,300 >> Configuration saved in ./outputs/checkpoint-1000/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-20 09:52:50,782 >> Model weights saved in ./outputs/checkpoint-1000/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-20 09:52:50,783 >> tokenizer config file saved in ./outputs/checkpoint-1000/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-20 09:52:50,783 >> Special tokens file saved in ./outputs/checkpoint-1000/special_tokens_map.json\n", + "{'loss': 0.4463, 'learning_rate': 4.7571243523316064e-05, 'epoch': 0.24}\n", + " 5% 1500/30880 [05:00<2:42:57, 3.00it/s][INFO|trainer.py:1917] 2021-07-20 09:54:31,122 >> Saving model checkpoint to ./outputs/checkpoint-1500\n", + "[INFO|configuration_utils.py:379] 2021-07-20 09:54:31,123 >> Configuration saved in ./outputs/checkpoint-1500/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-20 09:54:32,493 >> Model weights saved in ./outputs/checkpoint-1500/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-20 09:54:32,494 >> tokenizer config file saved in ./outputs/checkpoint-1500/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-20 09:54:32,494 >> Special tokens file saved in ./outputs/checkpoint-1500/special_tokens_map.json\n", + " 6% 2000/30880 [06:42<2:40:15, 3.00it/s]{'loss': 0.4246, 'learning_rate': 4.676165803108808e-05, 'epoch': 0.32}\n", + "[INFO|trainer.py:1917] 2021-07-20 09:56:12,981 >> Saving model checkpoint to ./outputs/checkpoint-2000\n", + "[INFO|configuration_utils.py:379] 2021-07-20 09:56:12,982 >> Configuration saved in ./outputs/checkpoint-2000/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-20 09:56:14,367 >> Model weights saved in ./outputs/checkpoint-2000/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-20 09:56:14,368 >> tokenizer config file saved in ./outputs/checkpoint-2000/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-20 09:56:14,368 >> Special tokens file saved in ./outputs/checkpoint-2000/special_tokens_map.json\n", + "{'loss': 0.4079, 'learning_rate': 4.595207253886011e-05, 'epoch': 0.4}\n", + " 8% 2500/30880 [08:23<2:36:12, 3.03it/s][INFO|trainer.py:1917] 2021-07-20 09:57:54,652 >> Saving model checkpoint to ./outputs/checkpoint-2500\n", + "[INFO|configuration_utils.py:379] 2021-07-20 09:57:54,653 >> Configuration saved in ./outputs/checkpoint-2500/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-20 09:57:56,007 >> Model weights saved in ./outputs/checkpoint-2500/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-20 09:57:56,008 >> tokenizer config file saved in ./outputs/checkpoint-2500/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-20 09:57:56,008 >> Special tokens file saved in ./outputs/checkpoint-2500/special_tokens_map.json\n", + "{'loss': 0.3853, 'learning_rate': 4.5142487046632126e-05, 'epoch': 0.49}\n", + " 10% 3000/30880 [10:05<2:30:38, 3.08it/s][INFO|trainer.py:1917] 2021-07-20 09:59:36,412 >> Saving model checkpoint to ./outputs/checkpoint-3000\n", + 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"[INFO|tokenization_utils_base.py:1998] 2021-07-20 11:16:50,857 >> tokenizer config file saved in ./outputs/checkpoint-26000/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-20 11:16:50,857 >> Special tokens file saved in ./outputs/checkpoint-26000/special_tokens_map.json\n", + "{'loss': 0.1332, 'learning_rate': 7.091968911917099e-06, 'epoch': 4.29}\n", + " 86% 26500/30880 [1:28:58<24:15, 3.01it/s][INFO|trainer.py:1917] 2021-07-20 11:18:29,721 >> Saving model checkpoint to ./outputs/checkpoint-26500\n", + "[INFO|configuration_utils.py:379] 2021-07-20 11:18:29,723 >> Configuration saved in ./outputs/checkpoint-26500/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-20 11:18:31,148 >> Model weights saved in ./outputs/checkpoint-26500/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-20 11:18:31,149 >> tokenizer config file saved in ./outputs/checkpoint-26500/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 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+ "[INFO|tokenization_utils_base.py:2004] 2021-07-20 11:26:50,708 >> Special tokens file saved in ./outputs/checkpoint-29000/special_tokens_map.json\n", + "{'loss': 0.122, 'learning_rate': 2.234455958549223e-06, 'epoch': 4.78}\n", + " 96% 29500/30880 [1:38:59<07:29, 3.07it/s][INFO|trainer.py:1917] 2021-07-20 11:28:30,049 >> Saving model checkpoint to ./outputs/checkpoint-29500\n", + "[INFO|configuration_utils.py:379] 2021-07-20 11:28:30,050 >> Configuration saved in ./outputs/checkpoint-29500/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-20 11:28:31,429 >> Model weights saved in ./outputs/checkpoint-29500/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-20 11:28:31,430 >> tokenizer config file saved in ./outputs/checkpoint-29500/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-20 11:28:31,430 >> Special tokens file saved in ./outputs/checkpoint-29500/special_tokens_map.json\n", + " 97% 30000/30880 [1:40:39<04:47, 3.06it/s]{'loss': 0.1079, 'learning_rate': 1.4248704663212437e-06, 'epoch': 4.86}\n", + " 97% 30000/30880 [1:40:39<04:47, 3.06it/s][INFO|trainer.py:1917] 2021-07-20 11:30:10,669 >> Saving model checkpoint to ./outputs/checkpoint-30000\n", + "[INFO|configuration_utils.py:379] 2021-07-20 11:30:10,672 >> Configuration saved in ./outputs/checkpoint-30000/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-20 11:30:12,147 >> Model weights saved in ./outputs/checkpoint-30000/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-20 11:30:12,148 >> tokenizer config file saved in ./outputs/checkpoint-30000/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-20 11:30:12,148 >> Special tokens file saved in ./outputs/checkpoint-30000/special_tokens_map.json\n", + " 99% 30500/30880 [1:42:19<02:05, 3.04it/s]{'loss': 0.1135, 'learning_rate': 6.152849740932643e-07, 'epoch': 4.94}\n", + " 99% 30500/30880 [1:42:20<02:05, 3.04it/s][INFO|trainer.py:1917] 2021-07-20 11:31:50,788 >> Saving model checkpoint to ./outputs/checkpoint-30500\n", + "[INFO|configuration_utils.py:379] 2021-07-20 11:31:50,789 >> Configuration saved in ./outputs/checkpoint-30500/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-20 11:31:52,164 >> Model weights saved in ./outputs/checkpoint-30500/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-20 11:31:52,165 >> tokenizer config file saved in ./outputs/checkpoint-30500/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-20 11:31:52,165 >> Special tokens file saved in ./outputs/checkpoint-30500/special_tokens_map.json\n", + "100% 30880/30880 [1:43:36<00:00, 6.02it/s][INFO|trainer.py:1358] 2021-07-20 11:33:07,657 >> \n", + "\n", + "Training completed. Do not forget to share your model on huggingface.co/models =)\n", + "\n", + "\n", + "100% 30880/30880 [1:43:36<00:00, 6.02it/s]{'train_runtime': 6219.3427, 'train_samples_per_second': 39.716, 'train_steps_per_second': 4.965, 'train_loss': 0.232939304341924, 'epoch': 5.0}\n", + "100% 30880/30880 [1:43:36<00:00, 4.97it/s]\n", + "[INFO|trainer.py:1917] 2021-07-20 11:33:07,681 >> Saving model checkpoint to ./outputs\n", + "[INFO|configuration_utils.py:379] 2021-07-20 11:33:07,682 >> Configuration saved in ./outputs/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-20 11:33:09,171 >> Model weights saved in ./outputs/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-20 11:33:09,171 >> tokenizer config file saved in ./outputs/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-20 11:33:09,172 >> Special tokens file saved in ./outputs/special_tokens_map.json\n", + "***** train metrics *****\n", + " epoch = 5.0\n", + " train_loss = 0.2329\n", + " train_runtime = 1:43:39.34\n", + " train_samples = 49401\n", + " train_samples_per_second = 39.716\n", + " train_steps_per_second = 4.965\n", + "07/20/2021 11:33:09 - INFO - __main__ - *** Evaluate ***\n", + "[INFO|trainer.py:522] 2021-07-20 11:33:09,321 >> The following columns in the evaluation set don't have a corresponding argument in `RobertaForSequenceClassification.forward` and have been ignored: sentence1, id, sentence2.\n", + "[INFO|trainer.py:2163] 2021-07-20 11:33:09,340 >> ***** Running Evaluation *****\n", + "[INFO|trainer.py:2165] 2021-07-20 11:33:09,341 >> Num examples = 2000\n", + "[INFO|trainer.py:2168] 2021-07-20 11:33:09,341 >> Batch size = 8\n", + "100% 250/250 [00:12<00:00, 20.40it/s]\n", + "***** eval metrics *****\n", + " epoch = 5.0\n", + " eval_accuracy = 0.8795\n", + " eval_loss = 0.5979\n", + " eval_runtime = 0:00:12.33\n", + " eval_samples = 2000\n", + " eval_samples_per_second = 162.145\n", + " eval_steps_per_second = 20.268\n", + "\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Waiting for W&B process to finish, PID 1526\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Program ended successfully.\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: \n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Find user logs for this run at: /content/wandb/run-20210720_094928-3kwtbkiz/logs/debug.log\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Find internal logs for this run at: /content/wandb/run-20210720_094928-3kwtbkiz/logs/debug-internal.log\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Run summary:\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/loss 0.1135\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/learning_rate 0.0\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/epoch 5.0\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/global_step 30880\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: _runtime 6233\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: _timestamp 1626780801\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: _step 62\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_runtime 6219.3427\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_samples_per_second 39.716\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_steps_per_second 4.965\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/total_flos 1.62474365572992e+16\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_loss 0.23294\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/loss 0.59792\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/accuracy 0.8795\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/runtime 12.3347\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/samples_per_second 162.145\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/steps_per_second 20.268\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Run history:\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/loss █▆▅▅▅▄▄▄▄▃▃▃▃▃▃▃▃▂▂▂▃▂▂▂▂▂▂▂▂▂▂▂▁▁▁▁▁▁▁▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/learning_rate ████▇▇▇▇▇▆▆▆▆▆▆▅▅▅▅▅▄▄▄▄▄▄▃▃▃▃▃▃▂▂▂▂▂▁▁▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/epoch 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"\u001b[34m\u001b[1mwandb\u001b[0m: eval/steps_per_second ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: \n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Synced 5 W&B file(s), 0 media file(s), 0 artifact file(s) and 1 other file(s)\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: \n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Synced \u001b[33m./outputs\u001b[0m: \u001b[34mhttps://wandb.ai/versae/bertin-eval/runs/3kwtbkiz\u001b[0m\n", + "2021-07-20 11:33:34.803215: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Successfully opened dynamic library libcudart.so.11.0\n", + "07/20/2021 11:33:38 - WARNING - __main__ - Process rank: -1, device: cuda:0, n_gpu: 1distributed training: False, 16-bits training: False\n", + "07/20/2021 11:33:38 - INFO - __main__ - Training/evaluation parameters TrainingArguments(\n", + "_n_gpu=1,\n", + "adafactor=False,\n", + "adam_beta1=0.9,\n", + "adam_beta2=0.999,\n", + "adam_epsilon=1e-08,\n", + "dataloader_drop_last=False,\n", + "dataloader_num_workers=0,\n", + "dataloader_pin_memory=True,\n", + "ddp_find_unused_parameters=None,\n", + "debug=[],\n", + "deepspeed=None,\n", + "disable_tqdm=False,\n", + "do_eval=True,\n", + "do_predict=False,\n", + "do_train=True,\n", + "eval_accumulation_steps=None,\n", + "eval_steps=500,\n", + "evaluation_strategy=IntervalStrategy.NO,\n", + "fp16=False,\n", + "fp16_backend=auto,\n", + "fp16_full_eval=False,\n", + "fp16_opt_level=O1,\n", + "gradient_accumulation_steps=1,\n", + "greater_is_better=None,\n", + "group_by_length=False,\n", + "ignore_data_skip=False,\n", + "label_names=None,\n", + "label_smoothing_factor=0.0,\n", + "learning_rate=5e-05,\n", + "length_column_name=length,\n", + "load_best_model_at_end=False,\n", + "local_rank=-1,\n", + "log_level=-1,\n", + "log_level_replica=-1,\n", + "log_on_each_node=True,\n", + "logging_dir=./outputs/runs/Jul20_11-33-38_48f3f265b421,\n", + "logging_first_step=False,\n", + "logging_steps=500,\n", + "logging_strategy=IntervalStrategy.STEPS,\n", + "lr_scheduler_type=SchedulerType.LINEAR,\n", + "max_grad_norm=1.0,\n", + "max_steps=-1,\n", + "metric_for_best_model=None,\n", + "mp_parameters=,\n", + "no_cuda=False,\n", + "num_train_epochs=5.0,\n", + "output_dir=./outputs,\n", + "overwrite_output_dir=True,\n", + "past_index=-1,\n", + "per_device_eval_batch_size=8,\n", + "per_device_train_batch_size=8,\n", + "prediction_loss_only=False,\n", + "push_to_hub=False,\n", + "push_to_hub_model_id=outputs,\n", + "push_to_hub_organization=None,\n", + "push_to_hub_token=None,\n", + "remove_unused_columns=True,\n", + "report_to=['tensorboard', 'wandb'],\n", + "resume_from_checkpoint=None,\n", + "run_name=./outputs,\n", + "save_on_each_node=False,\n", + "save_steps=500,\n", + "save_strategy=IntervalStrategy.STEPS,\n", + "save_total_limit=None,\n", + "seed=42,\n", + "sharded_ddp=[],\n", + "skip_memory_metrics=True,\n", + "tpu_metrics_debug=False,\n", + "tpu_num_cores=None,\n", + "use_legacy_prediction_loop=False,\n", + "warmup_ratio=0.0,\n", + "warmup_steps=0,\n", + "weight_decay=0.0,\n", + ")\n", + "07/20/2021 11:33:39 - INFO - datasets.load - Found main folder for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/paws-x/paws-x.py at /root/.cache/huggingface/modules/datasets_modules/datasets/paws-x\n", + "07/20/2021 11:33:39 - INFO - datasets.load - Found specific version folder for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/paws-x/paws-x.py at /root/.cache/huggingface/modules/datasets_modules/datasets/paws-x/a5033b43902a02a4ba2ee469c1dd22af3e6a4a247ac47fa1af9835d0e734e2af\n", + "07/20/2021 11:33:39 - INFO - datasets.load - Found script file from https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/paws-x/paws-x.py to /root/.cache/huggingface/modules/datasets_modules/datasets/paws-x/a5033b43902a02a4ba2ee469c1dd22af3e6a4a247ac47fa1af9835d0e734e2af/paws-x.py\n", + "07/20/2021 11:33:39 - INFO - datasets.load - Found dataset infos file from https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/paws-x/dataset_infos.json to /root/.cache/huggingface/modules/datasets_modules/datasets/paws-x/a5033b43902a02a4ba2ee469c1dd22af3e6a4a247ac47fa1af9835d0e734e2af/dataset_infos.json\n", + "07/20/2021 11:33:39 - INFO - datasets.load - Found metadata file for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/paws-x/paws-x.py at /root/.cache/huggingface/modules/datasets_modules/datasets/paws-x/a5033b43902a02a4ba2ee469c1dd22af3e6a4a247ac47fa1af9835d0e734e2af/paws-x.json\n", + "07/20/2021 11:33:39 - INFO - datasets.load - Found main folder for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/paws-x/paws-x.py at /root/.cache/huggingface/modules/datasets_modules/datasets/paws-x\n", + "07/20/2021 11:33:39 - INFO - datasets.load - Found specific version folder for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/paws-x/paws-x.py at /root/.cache/huggingface/modules/datasets_modules/datasets/paws-x/a5033b43902a02a4ba2ee469c1dd22af3e6a4a247ac47fa1af9835d0e734e2af\n", + "07/20/2021 11:33:39 - INFO - datasets.load - Found script file from https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/paws-x/paws-x.py to /root/.cache/huggingface/modules/datasets_modules/datasets/paws-x/a5033b43902a02a4ba2ee469c1dd22af3e6a4a247ac47fa1af9835d0e734e2af/paws-x.py\n", + "07/20/2021 11:33:39 - INFO - datasets.load - Found dataset infos file from https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/paws-x/dataset_infos.json to /root/.cache/huggingface/modules/datasets_modules/datasets/paws-x/a5033b43902a02a4ba2ee469c1dd22af3e6a4a247ac47fa1af9835d0e734e2af/dataset_infos.json\n", + "07/20/2021 11:33:39 - INFO - datasets.load - Found metadata file for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/paws-x/paws-x.py at /root/.cache/huggingface/modules/datasets_modules/datasets/paws-x/a5033b43902a02a4ba2ee469c1dd22af3e6a4a247ac47fa1af9835d0e734e2af/paws-x.json\n", + "07/20/2021 11:33:39 - INFO - datasets.info - Loading Dataset Infos from /root/.cache/huggingface/modules/datasets_modules/datasets/paws-x/a5033b43902a02a4ba2ee469c1dd22af3e6a4a247ac47fa1af9835d0e734e2af\n", + "07/20/2021 11:33:39 - INFO - datasets.builder - Overwrite dataset info from restored data version.\n", + "07/20/2021 11:33:39 - INFO - datasets.info - Loading Dataset info from /root/.cache/huggingface/datasets/pawsx/es/1.1.0/a5033b43902a02a4ba2ee469c1dd22af3e6a4a247ac47fa1af9835d0e734e2af\n", + "07/20/2021 11:33:39 - WARNING - datasets.builder - Reusing dataset pawsx (/root/.cache/huggingface/datasets/pawsx/es/1.1.0/a5033b43902a02a4ba2ee469c1dd22af3e6a4a247ac47fa1af9835d0e734e2af)\n", + "07/20/2021 11:33:39 - INFO - datasets.info - Loading Dataset info from /root/.cache/huggingface/datasets/pawsx/es/1.1.0/a5033b43902a02a4ba2ee469c1dd22af3e6a4a247ac47fa1af9835d0e734e2af\n", + "100% 3/3 [00:00<00:00, 25.65it/s]\n", + "[INFO|configuration_utils.py:545] 2021-07-20 11:33:40,223 >> loading configuration file https://huggingface.co/bertin-project/bertin-base-random-exp-512seqlen/resolve/main/config.json from cache at /root/.cache/huggingface/transformers/a3b98490ab467f825ce932e6e6e7de25a6ea47beeceb6f5cd521b8ee4f61f95e.08210214ecaf5cd53c702826a604e564d8af557125033eef720f4f9f2af1fc44\n", + "[INFO|configuration_utils.py:581] 2021-07-20 11:33:40,224 >> Model config RobertaConfig {\n", + " \"architectures\": [\n", + " \"RobertaForMaskedLM\"\n", + " ],\n", + " \"attention_probs_dropout_prob\": 0.1,\n", + " \"bos_token_id\": 0,\n", + " \"eos_token_id\": 2,\n", + " \"finetuning_task\": \"paws-x\",\n", + " \"gradient_checkpointing\": false,\n", + " \"hidden_act\": \"gelu\",\n", + " \"hidden_dropout_prob\": 0.1,\n", + " \"hidden_size\": 768,\n", + " \"initializer_range\": 0.02,\n", + " \"intermediate_size\": 3072,\n", + " \"layer_norm_eps\": 1e-05,\n", + " \"max_position_embeddings\": 514,\n", + " \"model_type\": \"roberta\",\n", + " \"num_attention_heads\": 12,\n", + " \"num_hidden_layers\": 12,\n", + " \"pad_token_id\": 1,\n", + " \"position_embedding_type\": \"absolute\",\n", + " \"transformers_version\": \"4.9.0.dev0\",\n", + " \"type_vocab_size\": 1,\n", + " \"use_cache\": true,\n", + " \"vocab_size\": 50265\n", + "}\n", + "\n", + "[INFO|tokenization_utils_base.py:1722] 2021-07-20 11:33:42,705 >> loading file https://huggingface.co/bertin-project/bertin-base-random-exp-512seqlen/resolve/main/vocab.json from cache at /root/.cache/huggingface/transformers/c1ba808baa4a9c0f3062f1881d448087c30a1443644365bd41cf366491ab4063.a80f232f572026f92499b14999a8ed4e044e04cf3d01b9f2be298c98e78e8498\n", + "[INFO|tokenization_utils_base.py:1722] 2021-07-20 11:33:42,705 >> loading file https://huggingface.co/bertin-project/bertin-base-random-exp-512seqlen/resolve/main/merges.txt from cache at /root/.cache/huggingface/transformers/17ffd9604d64364336252e5a3859c3c55be07c457328ab5fc37e4aaf39913d28.a0dfc41f9d0f03a56ba7a5401d770f6e43071045a0bd79073380d408d17a0d92\n", + "[INFO|tokenization_utils_base.py:1722] 2021-07-20 11:33:42,705 >> loading file https://huggingface.co/bertin-project/bertin-base-random-exp-512seqlen/resolve/main/tokenizer.json from cache at /root/.cache/huggingface/transformers/59e3c1ec6ec0fe2653924dcd348a763dd43f51d8eae6ab758e2d962ec7c14d5e.2a5dc806edc00ab3a329cb22b9973596ca75b24ba0e5e4963bf1308de7237a3d\n", + "[INFO|tokenization_utils_base.py:1722] 2021-07-20 11:33:42,705 >> loading file https://huggingface.co/bertin-project/bertin-base-random-exp-512seqlen/resolve/main/added_tokens.json from cache at None\n", + "[INFO|tokenization_utils_base.py:1722] 2021-07-20 11:33:42,705 >> loading file https://huggingface.co/bertin-project/bertin-base-random-exp-512seqlen/resolve/main/special_tokens_map.json from cache at /root/.cache/huggingface/transformers/39ddc268aab2655adb602f93d771480d4db157c1b6fae9a5ae9fc2112c645a69.a11ebb04664c067c8fe5ef8f8068b0f721263414a26058692f7b2e4ba2a1b342\n", + "[INFO|tokenization_utils_base.py:1722] 2021-07-20 11:33:42,705 >> loading file https://huggingface.co/bertin-project/bertin-base-random-exp-512seqlen/resolve/main/tokenizer_config.json from cache at /root/.cache/huggingface/transformers/a9d7a6740959c8c347993f62fbd5620bffa2d10c35c2e579a2ecec181299c9a1.9f7ac4246b492dfa7c21beb5233deec8aef46153ec25ac5258ac5e2ae82dfa89\n", + "[INFO|modeling_utils.py:1271] 2021-07-20 11:33:43,126 >> loading weights file https://huggingface.co/bertin-project/bertin-base-random-exp-512seqlen/resolve/main/pytorch_model.bin from cache at /root/.cache/huggingface/transformers/6dd5d03f2c36b42a305cf20636d35935ad2d998d2ab0588b28eeed0fc164db43.5b6b77533b091cc9204533514d844abfe875ebba66e044b251306c4228bd3221\n", + "[WARNING|modeling_utils.py:1502] 2021-07-20 11:33:51,203 >> Some weights of the model checkpoint at bertin-project/bertin-base-random-exp-512seqlen were not used when initializing RobertaForSequenceClassification: ['lm_head.dense.weight', 'lm_head.bias', 'lm_head.layer_norm.weight', 'lm_head.layer_norm.bias', 'lm_head.dense.bias']\n", + "- This IS expected if you are initializing RobertaForSequenceClassification from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).\n", + "- This IS NOT expected if you are initializing RobertaForSequenceClassification from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).\n", + "[WARNING|modeling_utils.py:1513] 2021-07-20 11:33:51,203 >> Some weights of RobertaForSequenceClassification were not initialized from the model checkpoint at bertin-project/bertin-base-random-exp-512seqlen and are newly initialized: ['classifier.dense.weight', 'classifier.out_proj.weight', 'classifier.out_proj.bias', 'classifier.dense.bias']\n", + "You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.\n", + "07/20/2021 11:33:51 - WARNING - datasets.arrow_dataset - Loading cached processed dataset at /root/.cache/huggingface/datasets/pawsx/es/1.1.0/a5033b43902a02a4ba2ee469c1dd22af3e6a4a247ac47fa1af9835d0e734e2af/cache-201539629a7c3697.arrow\n", + "07/20/2021 11:33:51 - WARNING - datasets.arrow_dataset - Loading cached processed dataset at /root/.cache/huggingface/datasets/pawsx/es/1.1.0/a5033b43902a02a4ba2ee469c1dd22af3e6a4a247ac47fa1af9835d0e734e2af/cache-63872d8033480024.arrow\n", + "Running tokenizer on dataset: 0% 0/2 [00:00> The following columns in the training set don't have a corresponding argument in `RobertaForSequenceClassification.forward` and have been ignored: sentence2, id, sentence1.\n", + "[INFO|trainer.py:1162] 2021-07-20 11:33:56,324 >> ***** Running training *****\n", + "[INFO|trainer.py:1163] 2021-07-20 11:33:56,324 >> Num examples = 49401\n", + "[INFO|trainer.py:1164] 2021-07-20 11:33:56,325 >> Num Epochs = 5\n", + "[INFO|trainer.py:1165] 2021-07-20 11:33:56,325 >> Instantaneous batch size per device = 8\n", + "[INFO|trainer.py:1166] 2021-07-20 11:33:56,325 >> Total train batch size (w. parallel, distributed & accumulation) = 8\n", + "[INFO|trainer.py:1167] 2021-07-20 11:33:56,325 >> Gradient Accumulation steps = 1\n", + "[INFO|trainer.py:1168] 2021-07-20 11:33:56,325 >> Total optimization steps = 30880\n", + "[INFO|integrations.py:446] 2021-07-20 11:33:56,340 >> Automatic Weights & Biases logging enabled, to disable set os.environ[\"WANDB_DISABLED\"] = \"true\"\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Currently logged in as: \u001b[33mversae\u001b[0m (use `wandb login --relogin` to force relogin)\n", + "2021-07-20 11:33:57.672926: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Successfully opened dynamic library libcudart.so.11.0\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Tracking run with wandb version 0.11.0\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Syncing run \u001b[33m./outputs\u001b[0m\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: ⭐️ View project at \u001b[34m\u001b[4mhttps://wandb.ai/versae/bertin-eval\u001b[0m\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: 🚀 View run at \u001b[34m\u001b[4mhttps://wandb.ai/versae/bertin-eval/runs/27wn690d\u001b[0m\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Run data is saved locally in /content/wandb/run-20210720_113356-27wn690d\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Run `wandb offline` to turn off syncing.\n", + "\n", + " 2% 500/30880 [01:37<2:54:15, 2.91it/s]{'loss': 0.7114, 'learning_rate': 4.919041450777203e-05, 'epoch': 0.08}\n", + " 2% 500/30880 [01:37<2:54:15, 2.91it/s][INFO|trainer.py:1917] 2021-07-20 11:35:35,937 >> Saving model checkpoint to ./outputs/checkpoint-500\n", + "[INFO|configuration_utils.py:379] 2021-07-20 11:35:35,938 >> Configuration saved in ./outputs/checkpoint-500/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-20 11:35:37,403 >> Model weights saved in ./outputs/checkpoint-500/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-20 11:35:37,403 >> tokenizer config file saved in ./outputs/checkpoint-500/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-20 11:35:37,404 >> Special tokens file saved in ./outputs/checkpoint-500/special_tokens_map.json\n", + " 3% 1000/30880 [03:19<2:44:28, 3.03it/s]{'loss': 0.7076, 'learning_rate': 4.8380829015544046e-05, 'epoch': 0.16}\n", + " 3% 1000/30880 [03:19<2:44:28, 3.03it/s][INFO|trainer.py:1917] 2021-07-20 11:37:18,583 >> Saving model checkpoint to ./outputs/checkpoint-1000\n", + "[INFO|configuration_utils.py:379] 2021-07-20 11:37:18,585 >> Configuration saved in ./outputs/checkpoint-1000/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-20 11:37:19,832 >> Model weights saved in ./outputs/checkpoint-1000/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-20 11:37:19,832 >> tokenizer config file saved in ./outputs/checkpoint-1000/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-20 11:37:19,833 >> Special tokens file saved in ./outputs/checkpoint-1000/special_tokens_map.json\n", + " 5% 1500/30880 [05:03<2:45:27, 2.96it/s]{'loss': 0.71, 'learning_rate': 4.7571243523316064e-05, 'epoch': 0.24}\n", + " 5% 1500/30880 [05:03<2:45:27, 2.96it/s][INFO|trainer.py:1917] 2021-07-20 11:39:01,986 >> Saving model checkpoint to ./outputs/checkpoint-1500\n", + "[INFO|configuration_utils.py:379] 2021-07-20 11:39:01,987 >> Configuration saved in ./outputs/checkpoint-1500/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-20 11:39:03,402 >> Model weights saved in ./outputs/checkpoint-1500/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-20 11:39:03,403 >> tokenizer config file saved in ./outputs/checkpoint-1500/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-20 11:39:03,403 >> Special tokens file saved in ./outputs/checkpoint-1500/special_tokens_map.json\n", + "{'loss': 0.7, 'learning_rate': 4.676165803108808e-05, 'epoch': 0.32}\n", + " 6% 2000/30880 [06:46<2:39:37, 3.02it/s][INFO|trainer.py:1917] 2021-07-20 11:40:44,994 >> Saving model checkpoint to ./outputs/checkpoint-2000\n", + "[INFO|configuration_utils.py:379] 2021-07-20 11:40:44,996 >> Configuration saved in ./outputs/checkpoint-2000/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-20 11:40:46,341 >> Model weights saved in ./outputs/checkpoint-2000/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-20 11:40:46,341 >> tokenizer config file saved in ./outputs/checkpoint-2000/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-20 11:40:46,342 >> Special tokens file saved in ./outputs/checkpoint-2000/special_tokens_map.json\n", + "{'loss': 0.7043, 'learning_rate': 4.595207253886011e-05, 'epoch': 0.4}\n", + " 8% 2500/30880 [08:29<2:41:01, 2.94it/s][INFO|trainer.py:1917] 2021-07-20 11:42:28,240 >> Saving model checkpoint to ./outputs/checkpoint-2500\n", + "[INFO|configuration_utils.py:379] 2021-07-20 11:42:28,242 >> Configuration saved in ./outputs/checkpoint-2500/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-20 11:42:29,666 >> Model weights saved in ./outputs/checkpoint-2500/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-20 11:42:29,667 >> tokenizer config file saved in ./outputs/checkpoint-2500/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-20 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2021-07-20 13:13:39,086 >> Saving model checkpoint to ./outputs/checkpoint-29000\n", + "[INFO|configuration_utils.py:379] 2021-07-20 13:13:39,087 >> Configuration saved in ./outputs/checkpoint-29000/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-20 13:13:40,501 >> Model weights saved in ./outputs/checkpoint-29000/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-20 13:13:40,505 >> tokenizer config file saved in ./outputs/checkpoint-29000/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-20 13:13:40,505 >> Special tokens file saved in ./outputs/checkpoint-29000/special_tokens_map.json\n", + " 96% 29500/30880 [1:41:23<07:49, 2.94it/s]{'loss': 0.687, 'learning_rate': 2.234455958549223e-06, 'epoch': 4.78}\n", + "[INFO|trainer.py:1917] 2021-07-20 13:15:22,276 >> Saving model checkpoint to ./outputs/checkpoint-29500\n", + "[INFO|configuration_utils.py:379] 2021-07-20 13:15:22,282 >> Configuration saved in 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"[INFO|tokenization_utils_base.py:1998] 2021-07-20 13:17:07,720 >> tokenizer config file saved in ./outputs/checkpoint-30000/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-20 13:17:07,721 >> Special tokens file saved in ./outputs/checkpoint-30000/special_tokens_map.json\n", + " 99% 30500/30880 [1:44:50<02:08, 2.96it/s]{'loss': 0.6909, 'learning_rate': 6.152849740932643e-07, 'epoch': 4.94}\n", + " 99% 30500/30880 [1:44:50<02:08, 2.96it/s][INFO|trainer.py:1917] 2021-07-20 13:18:49,734 >> Saving model checkpoint to ./outputs/checkpoint-30500\n", + "[INFO|configuration_utils.py:379] 2021-07-20 13:18:49,735 >> Configuration saved in ./outputs/checkpoint-30500/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-20 13:18:51,079 >> Model weights saved in ./outputs/checkpoint-30500/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-20 13:18:51,079 >> tokenizer config file saved in ./outputs/checkpoint-30500/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-20 13:18:51,080 >> Special tokens file saved in ./outputs/checkpoint-30500/special_tokens_map.json\n", + "100% 30880/30880 [1:46:10<00:00, 5.89it/s][INFO|trainer.py:1358] 2021-07-20 13:20:09,340 >> \n", + "\n", + "Training completed. Do not forget to share your model on huggingface.co/models =)\n", + "\n", + "\n", + "{'train_runtime': 6373.0159, 'train_samples_per_second': 38.758, 'train_steps_per_second': 4.845, 'train_loss': 0.6934825669916183, 'epoch': 5.0}\n", + "100% 30880/30880 [1:46:10<00:00, 4.85it/s]\n", + "[INFO|trainer.py:1917] 2021-07-20 13:20:09,352 >> Saving model checkpoint to ./outputs\n", + "[INFO|configuration_utils.py:379] 2021-07-20 13:20:09,353 >> Configuration saved in ./outputs/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-20 13:20:11,595 >> Model weights saved in ./outputs/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-20 13:20:11,596 >> tokenizer config file saved in ./outputs/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-20 13:20:11,596 >> Special tokens file saved in ./outputs/special_tokens_map.json\n", + "***** train metrics *****\n", + " epoch = 5.0\n", + " train_loss = 0.6935\n", + " train_runtime = 1:46:13.01\n", + " train_samples = 49401\n", + " train_samples_per_second = 38.758\n", + " train_steps_per_second = 4.845\n", + "07/20/2021 13:20:11 - INFO - __main__ - *** Evaluate ***\n", + "[INFO|trainer.py:522] 2021-07-20 13:20:11,706 >> The following columns in the evaluation set don't have a corresponding argument in `RobertaForSequenceClassification.forward` and have been ignored: sentence2, id, sentence1.\n", + "[INFO|trainer.py:2163] 2021-07-20 13:20:11,715 >> ***** Running Evaluation *****\n", + "[INFO|trainer.py:2165] 2021-07-20 13:20:11,715 >> Num examples = 2000\n", + "[INFO|trainer.py:2168] 2021-07-20 13:20:11,715 >> Batch size = 8\n", + " 99% 248/250 [00:11<00:00, 20.55it/s]***** eval metrics *****\n", + "100% 250/250 [00:12<00:00, 20.81it/s] epoch = 5.0\n", + " eval_accuracy = 0.5765\n", + " eval_loss = 0.6818\n", + "\n", + " eval_runtime = 0:00:12.07\n", + " eval_samples = 2000\n", + " eval_samples_per_second = 165.685\n", + " eval_steps_per_second = 20.711\n", + "\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Waiting for W&B process to finish, PID 1591\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Program ended successfully.\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: \n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Find user logs for this run at: /content/wandb/run-20210720_113356-27wn690d/logs/debug.log\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Find internal logs for this run at: /content/wandb/run-20210720_113356-27wn690d/logs/debug-internal.log\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Run summary:\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/loss 0.6909\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/learning_rate 0.0\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/epoch 5.0\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/global_step 30880\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: _runtime 6387\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: _timestamp 1626787223\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: _step 62\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_runtime 6373.0159\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_samples_per_second 38.758\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_steps_per_second 4.845\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/total_flos 1.62474365572992e+16\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_loss 0.69348\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/loss 0.68176\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/accuracy 0.5765\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/runtime 12.0711\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/samples_per_second 165.685\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/steps_per_second 20.711\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Run history:\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/loss █▇▅▆▅▅▄▅▅▄▂▃▄▂▄▄▃▃▄▃▄▂▃▁▄▂▂▃▃▁▃▃▃▂▂▃▂▂▂▃\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/learning_rate ████▇▇▇▇▇▆▆▆▆▆▆▅▅▅▅▅▄▄▄▄▄▄▃▃▃▃▃▃▂▂▂▂▂▁▁▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/epoch 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"\u001b[34m\u001b[1mwandb\u001b[0m: eval/steps_per_second ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: \n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Synced 5 W&B file(s), 0 media file(s), 0 artifact file(s) and 1 other file(s)\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: \n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Synced \u001b[33m./outputs\u001b[0m: \u001b[34mhttps://wandb.ai/versae/bertin-eval/runs/27wn690d\u001b[0m\n", + "2021-07-20 13:20:34.224882: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Successfully opened dynamic library libcudart.so.11.0\n", + "07/20/2021 13:20:36 - WARNING - __main__ - Process rank: -1, device: cuda:0, n_gpu: 1distributed training: False, 16-bits training: False\n", + "07/20/2021 13:20:36 - INFO - __main__ - Training/evaluation parameters TrainingArguments(\n", + "_n_gpu=1,\n", + "adafactor=False,\n", + "adam_beta1=0.9,\n", + "adam_beta2=0.999,\n", + "adam_epsilon=1e-08,\n", + "dataloader_drop_last=False,\n", + "dataloader_num_workers=0,\n", + "dataloader_pin_memory=True,\n", + "ddp_find_unused_parameters=None,\n", + "debug=[],\n", + "deepspeed=None,\n", + "disable_tqdm=False,\n", + "do_eval=True,\n", + "do_predict=False,\n", + "do_train=True,\n", + "eval_accumulation_steps=None,\n", + "eval_steps=500,\n", + "evaluation_strategy=IntervalStrategy.NO,\n", + "fp16=False,\n", + "fp16_backend=auto,\n", + "fp16_full_eval=False,\n", + "fp16_opt_level=O1,\n", + "gradient_accumulation_steps=1,\n", + "greater_is_better=None,\n", + "group_by_length=False,\n", + "ignore_data_skip=False,\n", + "label_names=None,\n", + "label_smoothing_factor=0.0,\n", + "learning_rate=5e-05,\n", + "length_column_name=length,\n", + "load_best_model_at_end=False,\n", + "local_rank=-1,\n", + "log_level=-1,\n", + "log_level_replica=-1,\n", + "log_on_each_node=True,\n", + "logging_dir=./outputs/runs/Jul20_13-20-36_48f3f265b421,\n", + "logging_first_step=False,\n", + "logging_steps=500,\n", + "logging_strategy=IntervalStrategy.STEPS,\n", + "lr_scheduler_type=SchedulerType.LINEAR,\n", + "max_grad_norm=1.0,\n", + "max_steps=-1,\n", + "metric_for_best_model=None,\n", + "mp_parameters=,\n", + "no_cuda=False,\n", + "num_train_epochs=5.0,\n", + "output_dir=./outputs,\n", + "overwrite_output_dir=True,\n", + "past_index=-1,\n", + "per_device_eval_batch_size=8,\n", + "per_device_train_batch_size=8,\n", + "prediction_loss_only=False,\n", + "push_to_hub=False,\n", + "push_to_hub_model_id=outputs,\n", + "push_to_hub_organization=None,\n", + "push_to_hub_token=None,\n", + "remove_unused_columns=True,\n", + "report_to=['tensorboard', 'wandb'],\n", + "resume_from_checkpoint=None,\n", + "run_name=./outputs,\n", + "save_on_each_node=False,\n", + "save_steps=500,\n", + "save_strategy=IntervalStrategy.STEPS,\n", + "save_total_limit=None,\n", + "seed=42,\n", + "sharded_ddp=[],\n", + "skip_memory_metrics=True,\n", + "tpu_metrics_debug=False,\n", + "tpu_num_cores=None,\n", + "use_legacy_prediction_loop=False,\n", + "warmup_ratio=0.0,\n", + "warmup_steps=0,\n", + "weight_decay=0.0,\n", + ")\n", + "07/20/2021 13:20:37 - INFO - datasets.load - Found main folder for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/paws-x/paws-x.py at /root/.cache/huggingface/modules/datasets_modules/datasets/paws-x\n", + "07/20/2021 13:20:37 - INFO - datasets.load - Found specific version folder for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/paws-x/paws-x.py at /root/.cache/huggingface/modules/datasets_modules/datasets/paws-x/a5033b43902a02a4ba2ee469c1dd22af3e6a4a247ac47fa1af9835d0e734e2af\n", + "07/20/2021 13:20:37 - INFO - datasets.load - Found script file from https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/paws-x/paws-x.py to /root/.cache/huggingface/modules/datasets_modules/datasets/paws-x/a5033b43902a02a4ba2ee469c1dd22af3e6a4a247ac47fa1af9835d0e734e2af/paws-x.py\n", + "07/20/2021 13:20:37 - INFO - datasets.load - Found dataset infos file from https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/paws-x/dataset_infos.json to /root/.cache/huggingface/modules/datasets_modules/datasets/paws-x/a5033b43902a02a4ba2ee469c1dd22af3e6a4a247ac47fa1af9835d0e734e2af/dataset_infos.json\n", + "07/20/2021 13:20:37 - INFO - datasets.load - Found metadata file for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/paws-x/paws-x.py at /root/.cache/huggingface/modules/datasets_modules/datasets/paws-x/a5033b43902a02a4ba2ee469c1dd22af3e6a4a247ac47fa1af9835d0e734e2af/paws-x.json\n", + "07/20/2021 13:20:37 - INFO - datasets.load - Found main folder for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/paws-x/paws-x.py at /root/.cache/huggingface/modules/datasets_modules/datasets/paws-x\n", + "07/20/2021 13:20:37 - INFO - datasets.load - Found specific version folder for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/paws-x/paws-x.py at /root/.cache/huggingface/modules/datasets_modules/datasets/paws-x/a5033b43902a02a4ba2ee469c1dd22af3e6a4a247ac47fa1af9835d0e734e2af\n", + "07/20/2021 13:20:37 - INFO - datasets.load - Found script file from https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/paws-x/paws-x.py to /root/.cache/huggingface/modules/datasets_modules/datasets/paws-x/a5033b43902a02a4ba2ee469c1dd22af3e6a4a247ac47fa1af9835d0e734e2af/paws-x.py\n", + "07/20/2021 13:20:37 - INFO - datasets.load - Found dataset infos file from https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/paws-x/dataset_infos.json to /root/.cache/huggingface/modules/datasets_modules/datasets/paws-x/a5033b43902a02a4ba2ee469c1dd22af3e6a4a247ac47fa1af9835d0e734e2af/dataset_infos.json\n", + "07/20/2021 13:20:37 - INFO - datasets.load - Found metadata file for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/paws-x/paws-x.py at /root/.cache/huggingface/modules/datasets_modules/datasets/paws-x/a5033b43902a02a4ba2ee469c1dd22af3e6a4a247ac47fa1af9835d0e734e2af/paws-x.json\n", + "07/20/2021 13:20:37 - INFO - datasets.info - Loading Dataset Infos from /root/.cache/huggingface/modules/datasets_modules/datasets/paws-x/a5033b43902a02a4ba2ee469c1dd22af3e6a4a247ac47fa1af9835d0e734e2af\n", + "07/20/2021 13:20:37 - INFO - datasets.builder - Overwrite dataset info from restored data version.\n", + "07/20/2021 13:20:37 - INFO - datasets.info - Loading Dataset info from /root/.cache/huggingface/datasets/pawsx/es/1.1.0/a5033b43902a02a4ba2ee469c1dd22af3e6a4a247ac47fa1af9835d0e734e2af\n", + "07/20/2021 13:20:37 - WARNING - datasets.builder - Reusing dataset pawsx (/root/.cache/huggingface/datasets/pawsx/es/1.1.0/a5033b43902a02a4ba2ee469c1dd22af3e6a4a247ac47fa1af9835d0e734e2af)\n", + "07/20/2021 13:20:37 - INFO - datasets.info - Loading Dataset info from /root/.cache/huggingface/datasets/pawsx/es/1.1.0/a5033b43902a02a4ba2ee469c1dd22af3e6a4a247ac47fa1af9835d0e734e2af\n", + "100% 3/3 [00:00<00:00, 26.02it/s]\n", + "[INFO|configuration_utils.py:545] 2021-07-20 13:20:38,216 >> loading configuration file https://huggingface.co/bertin-project/bertin-base-gaussian/resolve/main/config.json from cache at /root/.cache/huggingface/transformers/cbd56d68ce5dcd2626aba4c4b188db63f2ba2c49a604b36e7cdc6e52578ee306.08210214ecaf5cd53c702826a604e564d8af557125033eef720f4f9f2af1fc44\n", + "[INFO|configuration_utils.py:581] 2021-07-20 13:20:38,217 >> Model config RobertaConfig {\n", + " \"architectures\": [\n", + " \"RobertaForMaskedLM\"\n", + " ],\n", + " \"attention_probs_dropout_prob\": 0.1,\n", + " \"bos_token_id\": 0,\n", + " \"eos_token_id\": 2,\n", + " \"finetuning_task\": \"paws-x\",\n", + " \"gradient_checkpointing\": false,\n", + " \"hidden_act\": \"gelu\",\n", + " \"hidden_dropout_prob\": 0.1,\n", + " \"hidden_size\": 768,\n", + " \"initializer_range\": 0.02,\n", + " \"intermediate_size\": 3072,\n", + " \"layer_norm_eps\": 1e-05,\n", + " \"max_position_embeddings\": 514,\n", + " \"model_type\": \"roberta\",\n", + " \"num_attention_heads\": 12,\n", + " \"num_hidden_layers\": 12,\n", + " \"pad_token_id\": 1,\n", + " \"position_embedding_type\": \"absolute\",\n", + " \"transformers_version\": \"4.9.0.dev0\",\n", + " \"type_vocab_size\": 1,\n", + " \"use_cache\": true,\n", + " \"vocab_size\": 50265\n", + "}\n", + "\n", + "[INFO|tokenization_utils_base.py:1722] 2021-07-20 13:20:40,662 >> loading file https://huggingface.co/bertin-project/bertin-base-gaussian/resolve/main/vocab.json from cache at /root/.cache/huggingface/transformers/dae6454603d0b1d10a2446ffc1a21ccd636b0ca6a4c77a79fb9dfde03f4a51b8.a80f232f572026f92499b14999a8ed4e044e04cf3d01b9f2be298c98e78e8498\n", + "[INFO|tokenization_utils_base.py:1722] 2021-07-20 13:20:40,662 >> loading file https://huggingface.co/bertin-project/bertin-base-gaussian/resolve/main/merges.txt from cache at /root/.cache/huggingface/transformers/2e77e6f778d3fd8875349675d408521ca20c1f1acac2fd57d60ca945d82b926e.a0dfc41f9d0f03a56ba7a5401d770f6e43071045a0bd79073380d408d17a0d92\n", + "[INFO|tokenization_utils_base.py:1722] 2021-07-20 13:20:40,662 >> loading file https://huggingface.co/bertin-project/bertin-base-gaussian/resolve/main/tokenizer.json from cache at /root/.cache/huggingface/transformers/98a6808b3aa08b6d84e8b30dfa6892d15e9e631eebff8652b37ab29d75a0b98a.2a5dc806edc00ab3a329cb22b9973596ca75b24ba0e5e4963bf1308de7237a3d\n", + "[INFO|tokenization_utils_base.py:1722] 2021-07-20 13:20:40,662 >> loading file https://huggingface.co/bertin-project/bertin-base-gaussian/resolve/main/added_tokens.json from cache at None\n", + "[INFO|tokenization_utils_base.py:1722] 2021-07-20 13:20:40,662 >> loading file https://huggingface.co/bertin-project/bertin-base-gaussian/resolve/main/special_tokens_map.json from cache at /root/.cache/huggingface/transformers/1f5a4bde3e85f3c7b914d0e6b43b2f72d6b3b2f9ddbec7be9e4b0521a429f67f.a11ebb04664c067c8fe5ef8f8068b0f721263414a26058692f7b2e4ba2a1b342\n", + "[INFO|tokenization_utils_base.py:1722] 2021-07-20 13:20:40,662 >> loading file https://huggingface.co/bertin-project/bertin-base-gaussian/resolve/main/tokenizer_config.json from cache at /root/.cache/huggingface/transformers/7a419a17bf4372869932365630632f434d402e93dd7e609e73607cf71ec1bdf7.9f7ac4246b492dfa7c21beb5233deec8aef46153ec25ac5258ac5e2ae82dfa89\n", + "[INFO|modeling_utils.py:1271] 2021-07-20 13:20:41,084 >> loading weights file https://huggingface.co/bertin-project/bertin-base-gaussian/resolve/main/pytorch_model.bin from cache at /root/.cache/huggingface/transformers/d61c66f6163d7933bcffb5de3a666094c2c7c8d54145ec0cea640f72204427e0.50b5552cf09535e0a4b85cc39c83be233674d4cab0836dd8fedc97aa778c802c\n", + "[WARNING|modeling_utils.py:1502] 2021-07-20 13:20:48,909 >> Some weights of the model checkpoint at bertin-project/bertin-base-gaussian were not used when initializing RobertaForSequenceClassification: ['lm_head.dense.bias', 'lm_head.bias', 'lm_head.layer_norm.weight', 'lm_head.dense.weight', 'lm_head.layer_norm.bias']\n", + "- This IS expected if you are initializing RobertaForSequenceClassification from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).\n", + "- This IS NOT expected if you are initializing RobertaForSequenceClassification from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).\n", + "[WARNING|modeling_utils.py:1513] 2021-07-20 13:20:48,910 >> Some weights of RobertaForSequenceClassification were not initialized from the model checkpoint at bertin-project/bertin-base-gaussian and are newly initialized: ['classifier.dense.weight', 'classifier.dense.bias', 'classifier.out_proj.bias', 'classifier.out_proj.weight']\n", + "You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.\n", + "07/20/2021 13:20:48 - WARNING - datasets.arrow_dataset - Loading cached processed dataset at /root/.cache/huggingface/datasets/pawsx/es/1.1.0/a5033b43902a02a4ba2ee469c1dd22af3e6a4a247ac47fa1af9835d0e734e2af/cache-54fbfa10643bca55.arrow\n", + "07/20/2021 13:20:49 - WARNING - datasets.arrow_dataset - Loading cached processed dataset at /root/.cache/huggingface/datasets/pawsx/es/1.1.0/a5033b43902a02a4ba2ee469c1dd22af3e6a4a247ac47fa1af9835d0e734e2af/cache-68c99004674c0acc.arrow\n", + "Running tokenizer on dataset: 0% 0/2 [00:00> The following columns in the training set don't have a corresponding argument in `RobertaForSequenceClassification.forward` and have been ignored: sentence2, id, sentence1.\n", + "[INFO|trainer.py:1162] 2021-07-20 13:20:54,594 >> ***** Running training *****\n", + "[INFO|trainer.py:1163] 2021-07-20 13:20:54,594 >> Num examples = 49401\n", + "[INFO|trainer.py:1164] 2021-07-20 13:20:54,595 >> Num Epochs = 5\n", + "[INFO|trainer.py:1165] 2021-07-20 13:20:54,595 >> Instantaneous batch size per device = 8\n", + "[INFO|trainer.py:1166] 2021-07-20 13:20:54,595 >> Total train batch size (w. parallel, distributed & accumulation) = 8\n", + "[INFO|trainer.py:1167] 2021-07-20 13:20:54,595 >> Gradient Accumulation steps = 1\n", + "[INFO|trainer.py:1168] 2021-07-20 13:20:54,595 >> Total optimization steps = 30880\n", + "[INFO|integrations.py:446] 2021-07-20 13:20:54,613 >> Automatic Weights & Biases logging enabled, to disable set os.environ[\"WANDB_DISABLED\"] = \"true\"\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Currently logged in as: \u001b[33mversae\u001b[0m (use `wandb login --relogin` to force relogin)\n", + "2021-07-20 13:20:56.005653: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Successfully opened dynamic library libcudart.so.11.0\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Tracking run with wandb version 0.11.0\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Syncing run \u001b[33m./outputs\u001b[0m\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: ⭐️ View project at \u001b[34m\u001b[4mhttps://wandb.ai/versae/bertin-eval\u001b[0m\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: 🚀 View run at \u001b[34m\u001b[4mhttps://wandb.ai/versae/bertin-eval/runs/20701jiq\u001b[0m\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Run data is saved locally in /content/wandb/run-20210720_132054-20701jiq\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Run `wandb offline` to turn off syncing.\n", + "\n", + " 2% 500/30880 [01:38<2:48:30, 3.00it/s]{'loss': 0.6445, 'learning_rate': 4.919041450777203e-05, 'epoch': 0.08}\n", + " 2% 500/30880 [01:38<2:48:30, 3.00it/s][INFO|trainer.py:1917] 2021-07-20 13:22:35,366 >> Saving model checkpoint to ./outputs/checkpoint-500\n", + "[INFO|configuration_utils.py:379] 2021-07-20 13:22:35,367 >> Configuration saved in ./outputs/checkpoint-500/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-20 13:22:36,740 >> Model weights saved in ./outputs/checkpoint-500/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-20 13:22:36,740 >> tokenizer config file saved in ./outputs/checkpoint-500/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-20 13:22:36,741 >> Special tokens file saved in ./outputs/checkpoint-500/special_tokens_map.json\n", + " {'loss': 0.4639, 'learning_rate': 4.8380829015544046e-05, 'epoch': 0.16}\n", + " 3% 1000/30880 [03:21<2:47:36, 2.97it/s][INFO|trainer.py:1917] 2021-07-20 13:24:19,145 >> Saving model checkpoint to ./outputs/checkpoint-1000\n", + "[INFO|configuration_utils.py:379] 2021-07-20 13:24:19,146 >> Configuration saved in ./outputs/checkpoint-1000/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-20 13:24:20,479 >> Model weights saved in ./outputs/checkpoint-1000/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-20 13:24:20,480 >> tokenizer config file saved in ./outputs/checkpoint-1000/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-20 13:24:20,480 >> Special tokens file saved in ./outputs/checkpoint-1000/special_tokens_map.json\n", + "{'loss': 0.4439, 'learning_rate': 4.7571243523316064e-05, 'epoch': 0.24}\n", + " 5% 1500/30880 [05:05<2:42:55, 3.01it/s][INFO|trainer.py:1917] 2021-07-20 13:26:02,950 >> Saving model checkpoint to ./outputs/checkpoint-1500\n", + "[INFO|configuration_utils.py:379] 2021-07-20 13:26:02,951 >> Configuration saved in ./outputs/checkpoint-1500/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-20 13:26:04,453 >> Model weights saved in ./outputs/checkpoint-1500/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-20 13:26:04,454 >> tokenizer config file saved in ./outputs/checkpoint-1500/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-20 13:26:04,454 >> Special tokens file saved in ./outputs/checkpoint-1500/special_tokens_map.json\n", + "{'loss': 0.4076, 'learning_rate': 4.676165803108808e-05, 'epoch': 0.32}\n", + " 6% 2000/30880 [06:50<2:42:07, 2.97it/s][INFO|trainer.py:1917] 2021-07-20 13:27:47,569 >> Saving model checkpoint to ./outputs/checkpoint-2000\n", + "[INFO|configuration_utils.py:379] 2021-07-20 13:27:47,571 >> Configuration saved in ./outputs/checkpoint-2000/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-20 13:27:49,056 >> Model weights saved in ./outputs/checkpoint-2000/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-20 13:27:49,057 >> tokenizer config file saved in ./outputs/checkpoint-2000/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-20 13:27:49,057 >> Special tokens file saved in ./outputs/checkpoint-2000/special_tokens_map.json\n", + "{'loss': 0.4025, 'learning_rate': 4.595207253886011e-05, 'epoch': 0.4}\n", + " 8% 2500/30880 [08:34<2:42:19, 2.91it/s][INFO|trainer.py:1917] 2021-07-20 13:29:31,608 >> Saving model checkpoint to ./outputs/checkpoint-2500\n", + "[INFO|configuration_utils.py:379] 2021-07-20 13:29:31,609 >> Configuration saved in ./outputs/checkpoint-2500/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-20 13:29:32,947 >> Model weights saved in ./outputs/checkpoint-2500/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-20 13:29:32,948 >> tokenizer config file saved in ./outputs/checkpoint-2500/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-20 13:29:32,948 >> Special tokens file saved in ./outputs/checkpoint-2500/special_tokens_map.json\n", + "{'loss': 0.397, 'learning_rate': 4.5142487046632126e-05, 'epoch': 0.49}\n", + " 10% 3000/30880 [10:18<2:57:21, 2.62it/s][INFO|trainer.py:1917] 2021-07-20 13:31:15,457 >> Saving model checkpoint to ./outputs/checkpoint-3000\n", + "[INFO|configuration_utils.py:379] 2021-07-20 13:31:15,459 >> Configuration saved in ./outputs/checkpoint-3000/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-20 13:31:17,087 >> Model weights saved in ./outputs/checkpoint-3000/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-20 13:31:17,087 >> tokenizer config file saved in ./outputs/checkpoint-3000/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-20 13:31:17,088 >> Special tokens file saved in ./outputs/checkpoint-3000/special_tokens_map.json\n", + "{'loss': 0.3652, 'learning_rate': 4.433290155440415e-05, 'epoch': 0.57}\n", + " 11% 3500/30880 [12:02<2:30:37, 3.03it/s][INFO|trainer.py:1917] 2021-07-20 13:32:59,762 >> Saving model checkpoint to ./outputs/checkpoint-3500\n", + "[INFO|configuration_utils.py:379] 2021-07-20 13:32:59,764 >> Configuration saved in ./outputs/checkpoint-3500/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-20 13:33:01,187 >> Model weights saved in ./outputs/checkpoint-3500/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-20 13:33:01,188 >> tokenizer config file saved in ./outputs/checkpoint-3500/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-20 13:33:01,188 >> Special tokens file saved in ./outputs/checkpoint-3500/special_tokens_map.json\n", + " 13% 4000/30880 [13:46<2:27:43, 3.03it/s]{'loss': 0.3801, 'learning_rate': 4.352331606217617e-05, 'epoch': 0.65}\n", + "[INFO|trainer.py:1917] 2021-07-20 13:34:43,538 >> Saving model checkpoint to ./outputs/checkpoint-4000\n", + "[INFO|configuration_utils.py:379] 2021-07-20 13:34:43,539 >> Configuration saved in ./outputs/checkpoint-4000/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-20 13:34:44,988 >> Model weights saved in ./outputs/checkpoint-4000/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-20 13:34:45,015 >> tokenizer config file saved in ./outputs/checkpoint-4000/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-20 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+ "[INFO|tokenization_utils_base.py:2004] 2021-07-20 14:58:40,564 >> Special tokens file saved in ./outputs/checkpoint-28500/special_tokens_map.json\n", + " 94% 29000/30880 [1:39:23<10:27, 2.99it/s]{'loss': 0.1292, 'learning_rate': 3.044041450777202e-06, 'epoch': 4.7}\n", + " 94% 29000/30880 [1:39:23<10:27, 2.99it/s][INFO|trainer.py:1917] 2021-07-20 15:00:20,895 >> Saving model checkpoint to ./outputs/checkpoint-29000\n", + "[INFO|configuration_utils.py:379] 2021-07-20 15:00:20,896 >> Configuration saved in ./outputs/checkpoint-29000/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-20 15:00:23,040 >> Model weights saved in ./outputs/checkpoint-29000/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-20 15:00:23,041 >> tokenizer config file saved in ./outputs/checkpoint-29000/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-20 15:00:23,041 >> Special tokens file saved in ./outputs/checkpoint-29000/special_tokens_map.json\n", + " 96% 29500/30880 [1:41:05<07:26, 3.09it/s]{'loss': 0.13, 'learning_rate': 2.234455958549223e-06, 'epoch': 4.78}\n", + "[INFO|trainer.py:1917] 2021-07-20 15:02:02,753 >> Saving model checkpoint to ./outputs/checkpoint-29500\n", + "[INFO|configuration_utils.py:379] 2021-07-20 15:02:02,754 >> Configuration saved in ./outputs/checkpoint-29500/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-20 15:02:04,090 >> Model weights saved in ./outputs/checkpoint-29500/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-20 15:02:04,091 >> tokenizer config file saved in ./outputs/checkpoint-29500/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-20 15:02:04,091 >> Special tokens file saved in ./outputs/checkpoint-29500/special_tokens_map.json\n", + " 97% 30000/30880 [1:42:47<04:48, 3.05it/s]{'loss': 0.1135, 'learning_rate': 1.4248704663212437e-06, 'epoch': 4.86}\n", + "[INFO|trainer.py:1917] 2021-07-20 15:03:44,201 >> Saving model checkpoint to ./outputs/checkpoint-30000\n", + "[INFO|configuration_utils.py:379] 2021-07-20 15:03:44,203 >> Configuration saved in ./outputs/checkpoint-30000/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-20 15:03:45,654 >> Model weights saved in ./outputs/checkpoint-30000/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-20 15:03:45,655 >> tokenizer config file saved in ./outputs/checkpoint-30000/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-20 15:03:45,655 >> Special tokens file saved in ./outputs/checkpoint-30000/special_tokens_map.json\n", + "{'loss': 0.1377, 'learning_rate': 6.152849740932643e-07, 'epoch': 4.94}\n", + " 99% 30500/30880 [1:44:29<02:06, 3.00it/s][INFO|trainer.py:1917] 2021-07-20 15:05:26,961 >> Saving model checkpoint to ./outputs/checkpoint-30500\n", + "[INFO|configuration_utils.py:379] 2021-07-20 15:05:26,962 >> Configuration saved in ./outputs/checkpoint-30500/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-20 15:05:28,421 >> Model weights saved in ./outputs/checkpoint-30500/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-20 15:05:28,422 >> tokenizer config file saved in ./outputs/checkpoint-30500/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-20 15:05:28,422 >> Special tokens file saved in ./outputs/checkpoint-30500/special_tokens_map.json\n", + "100% 30880/30880 [1:45:48<00:00, 6.01it/s][INFO|trainer.py:1358] 2021-07-20 15:06:45,231 >> \n", + "\n", + "Training completed. Do not forget to share your model on huggingface.co/models =)\n", + "\n", + "\n", + "100% 30880/30880 [1:45:48<00:00, 6.01it/s]{'train_runtime': 6350.6363, 'train_samples_per_second': 38.895, 'train_steps_per_second': 4.863, 'train_loss': 0.25439529233645897, 'epoch': 5.0}\n", + "100% 30880/30880 [1:45:48<00:00, 4.86it/s]\n", + "[INFO|trainer.py:1917] 2021-07-20 15:06:45,258 >> Saving model checkpoint to ./outputs\n", + "[INFO|configuration_utils.py:379] 2021-07-20 15:06:45,259 >> Configuration saved in ./outputs/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-20 15:06:46,739 >> Model weights saved in ./outputs/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-20 15:06:46,740 >> tokenizer config file saved in ./outputs/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-20 15:06:46,740 >> Special tokens file saved in ./outputs/special_tokens_map.json\n", + "***** train metrics *****\n", + " epoch = 5.0\n", + " train_loss = 0.2544\n", + " train_runtime = 1:45:50.63\n", + " train_samples = 49401\n", + " train_samples_per_second = 38.895\n", + " train_steps_per_second = 4.863\n", + "07/20/2021 15:06:47 - INFO - __main__ - *** Evaluate ***\n", + "[INFO|trainer.py:522] 2021-07-20 15:06:47,602 >> The following columns in the evaluation set don't have a corresponding argument in `RobertaForSequenceClassification.forward` and have been ignored: sentence2, id, sentence1.\n", + "[INFO|trainer.py:2163] 2021-07-20 15:06:47,628 >> ***** Running Evaluation *****\n", + "[INFO|trainer.py:2165] 2021-07-20 15:06:47,628 >> Num examples = 2000\n", + "[INFO|trainer.py:2168] 2021-07-20 15:06:47,628 >> Batch size = 8\n", + "100% 250/250 [00:12<00:00, 20.77it/s]\n", + "***** eval metrics *****\n", + " epoch = 5.0\n", + " eval_accuracy = 0.8845\n", + " eval_loss = 0.553\n", + " eval_runtime = 0:00:12.08\n", + " eval_samples = 2000\n", + " eval_samples_per_second = 165.47\n", + " eval_steps_per_second = 20.684\n", + "\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Waiting for W&B process to finish, PID 1654\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Program ended successfully.\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: \n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Find user logs for this run at: /content/wandb/run-20210720_132054-20701jiq/logs/debug.log\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Find internal logs for this run at: /content/wandb/run-20210720_132054-20701jiq/logs/debug-internal.log\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Run summary:\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/loss 0.1377\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/learning_rate 0.0\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/epoch 5.0\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/global_step 30880\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: _runtime 6365\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: _timestamp 1626793619\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: _step 62\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_runtime 6350.6363\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_samples_per_second 38.895\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_steps_per_second 4.863\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/total_flos 1.62474365572992e+16\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/train_loss 0.2544\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/loss 0.55297\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/accuracy 0.8845\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/runtime 12.0868\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/samples_per_second 165.47\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: eval/steps_per_second 20.684\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Run history:\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/loss █▆▅▅▄▄▄▄▄▃▃▄▃▄▄▄▄▃▃▃▃▃▃▂▃▂▂▂▂▂▂▁▁▁▁▁▁▁▁▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/learning_rate ████▇▇▇▇▇▆▆▆▆▆▆▅▅▅▅▅▄▄▄▄▄▄▃▃▃▃▃▃▂▂▂▂▂▁▁▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: train/epoch 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"\u001b[34m\u001b[1mwandb\u001b[0m: eval/steps_per_second ▁\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: \n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Synced 5 W&B file(s), 0 media file(s), 0 artifact file(s) and 1 other file(s)\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: \n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Synced \u001b[33m./outputs\u001b[0m: \u001b[34mhttps://wandb.ai/versae/bertin-eval/runs/20701jiq\u001b[0m\n", + "2021-07-20 15:07:10.673127: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Successfully opened dynamic library libcudart.so.11.0\n", + "07/20/2021 15:07:12 - WARNING - __main__ - Process rank: -1, device: cuda:0, n_gpu: 1distributed training: False, 16-bits training: False\n", + "07/20/2021 15:07:12 - INFO - __main__ - Training/evaluation parameters TrainingArguments(\n", + "_n_gpu=1,\n", + "adafactor=False,\n", + "adam_beta1=0.9,\n", + "adam_beta2=0.999,\n", + "adam_epsilon=1e-08,\n", + "dataloader_drop_last=False,\n", + "dataloader_num_workers=0,\n", + "dataloader_pin_memory=True,\n", + "ddp_find_unused_parameters=None,\n", + "debug=[],\n", + "deepspeed=None,\n", + "disable_tqdm=False,\n", + "do_eval=True,\n", + "do_predict=False,\n", + "do_train=True,\n", + "eval_accumulation_steps=None,\n", + "eval_steps=500,\n", + "evaluation_strategy=IntervalStrategy.NO,\n", + "fp16=False,\n", + "fp16_backend=auto,\n", + "fp16_full_eval=False,\n", + "fp16_opt_level=O1,\n", + "gradient_accumulation_steps=1,\n", + "greater_is_better=None,\n", + "group_by_length=False,\n", + "ignore_data_skip=False,\n", + "label_names=None,\n", + "label_smoothing_factor=0.0,\n", + "learning_rate=5e-05,\n", + "length_column_name=length,\n", + "load_best_model_at_end=False,\n", + "local_rank=-1,\n", + "log_level=-1,\n", + "log_level_replica=-1,\n", + "log_on_each_node=True,\n", + "logging_dir=./outputs/runs/Jul20_15-07-12_48f3f265b421,\n", + "logging_first_step=False,\n", + "logging_steps=500,\n", + "logging_strategy=IntervalStrategy.STEPS,\n", + "lr_scheduler_type=SchedulerType.LINEAR,\n", + "max_grad_norm=1.0,\n", + "max_steps=-1,\n", + "metric_for_best_model=None,\n", + "mp_parameters=,\n", + "no_cuda=False,\n", + "num_train_epochs=5.0,\n", + "output_dir=./outputs,\n", + "overwrite_output_dir=True,\n", + "past_index=-1,\n", + "per_device_eval_batch_size=8,\n", + "per_device_train_batch_size=8,\n", + "prediction_loss_only=False,\n", + "push_to_hub=False,\n", + "push_to_hub_model_id=outputs,\n", + "push_to_hub_organization=None,\n", + "push_to_hub_token=None,\n", + "remove_unused_columns=True,\n", + "report_to=['tensorboard', 'wandb'],\n", + "resume_from_checkpoint=None,\n", + "run_name=./outputs,\n", + "save_on_each_node=False,\n", + "save_steps=500,\n", + "save_strategy=IntervalStrategy.STEPS,\n", + "save_total_limit=None,\n", + "seed=42,\n", + "sharded_ddp=[],\n", + "skip_memory_metrics=True,\n", + "tpu_metrics_debug=False,\n", + "tpu_num_cores=None,\n", + "use_legacy_prediction_loop=False,\n", + "warmup_ratio=0.0,\n", + "warmup_steps=0,\n", + "weight_decay=0.0,\n", + ")\n", + "07/20/2021 15:07:13 - INFO - datasets.load - Found main folder for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/paws-x/paws-x.py at /root/.cache/huggingface/modules/datasets_modules/datasets/paws-x\n", + "07/20/2021 15:07:13 - INFO - datasets.load - Found specific version folder for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/paws-x/paws-x.py at /root/.cache/huggingface/modules/datasets_modules/datasets/paws-x/a5033b43902a02a4ba2ee469c1dd22af3e6a4a247ac47fa1af9835d0e734e2af\n", + "07/20/2021 15:07:13 - INFO - datasets.load - Found script file from https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/paws-x/paws-x.py to /root/.cache/huggingface/modules/datasets_modules/datasets/paws-x/a5033b43902a02a4ba2ee469c1dd22af3e6a4a247ac47fa1af9835d0e734e2af/paws-x.py\n", + "07/20/2021 15:07:13 - INFO - datasets.load - Found dataset infos file from https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/paws-x/dataset_infos.json to /root/.cache/huggingface/modules/datasets_modules/datasets/paws-x/a5033b43902a02a4ba2ee469c1dd22af3e6a4a247ac47fa1af9835d0e734e2af/dataset_infos.json\n", + "07/20/2021 15:07:13 - INFO - datasets.load - Found metadata file for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/paws-x/paws-x.py at /root/.cache/huggingface/modules/datasets_modules/datasets/paws-x/a5033b43902a02a4ba2ee469c1dd22af3e6a4a247ac47fa1af9835d0e734e2af/paws-x.json\n", + "07/20/2021 15:07:14 - INFO - datasets.load - Found main folder for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/paws-x/paws-x.py at /root/.cache/huggingface/modules/datasets_modules/datasets/paws-x\n", + "07/20/2021 15:07:14 - INFO - datasets.load - Found specific version folder for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/paws-x/paws-x.py at /root/.cache/huggingface/modules/datasets_modules/datasets/paws-x/a5033b43902a02a4ba2ee469c1dd22af3e6a4a247ac47fa1af9835d0e734e2af\n", + "07/20/2021 15:07:14 - INFO - datasets.load - Found script file from https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/paws-x/paws-x.py to /root/.cache/huggingface/modules/datasets_modules/datasets/paws-x/a5033b43902a02a4ba2ee469c1dd22af3e6a4a247ac47fa1af9835d0e734e2af/paws-x.py\n", + "07/20/2021 15:07:14 - INFO - datasets.load - Found dataset infos file from https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/paws-x/dataset_infos.json to /root/.cache/huggingface/modules/datasets_modules/datasets/paws-x/a5033b43902a02a4ba2ee469c1dd22af3e6a4a247ac47fa1af9835d0e734e2af/dataset_infos.json\n", + "07/20/2021 15:07:14 - INFO - datasets.load - Found metadata file for dataset https://raw.githubusercontent.com/huggingface/datasets/1.9.0/datasets/paws-x/paws-x.py at /root/.cache/huggingface/modules/datasets_modules/datasets/paws-x/a5033b43902a02a4ba2ee469c1dd22af3e6a4a247ac47fa1af9835d0e734e2af/paws-x.json\n", + "07/20/2021 15:07:14 - INFO - datasets.info - Loading Dataset Infos from /root/.cache/huggingface/modules/datasets_modules/datasets/paws-x/a5033b43902a02a4ba2ee469c1dd22af3e6a4a247ac47fa1af9835d0e734e2af\n", + "07/20/2021 15:07:14 - INFO - datasets.builder - Overwrite dataset info from restored data version.\n", + "07/20/2021 15:07:14 - INFO - datasets.info - Loading Dataset info from /root/.cache/huggingface/datasets/pawsx/es/1.1.0/a5033b43902a02a4ba2ee469c1dd22af3e6a4a247ac47fa1af9835d0e734e2af\n", + "07/20/2021 15:07:14 - WARNING - datasets.builder - Reusing dataset pawsx (/root/.cache/huggingface/datasets/pawsx/es/1.1.0/a5033b43902a02a4ba2ee469c1dd22af3e6a4a247ac47fa1af9835d0e734e2af)\n", + "07/20/2021 15:07:14 - INFO - datasets.info - Loading Dataset info from /root/.cache/huggingface/datasets/pawsx/es/1.1.0/a5033b43902a02a4ba2ee469c1dd22af3e6a4a247ac47fa1af9835d0e734e2af\n", + "100% 3/3 [00:00<00:00, 23.03it/s]\n", + "[INFO|configuration_utils.py:545] 2021-07-20 15:07:14,735 >> loading configuration file https://huggingface.co/bertin-project/bertin-base-stepwise/resolve/main/config.json from cache at /root/.cache/huggingface/transformers/367bb30bd1ae06268e9d1c64ae1fb923fc9931913fa478dfa01d79a4c7086238.08210214ecaf5cd53c702826a604e564d8af557125033eef720f4f9f2af1fc44\n", + "[INFO|configuration_utils.py:581] 2021-07-20 15:07:14,735 >> Model config RobertaConfig {\n", + " \"architectures\": [\n", + " \"RobertaForMaskedLM\"\n", + " ],\n", + " \"attention_probs_dropout_prob\": 0.1,\n", + " \"bos_token_id\": 0,\n", + " \"eos_token_id\": 2,\n", + " \"finetuning_task\": \"paws-x\",\n", + " \"gradient_checkpointing\": false,\n", + " \"hidden_act\": \"gelu\",\n", + " \"hidden_dropout_prob\": 0.1,\n", + " \"hidden_size\": 768,\n", + " \"initializer_range\": 0.02,\n", + " \"intermediate_size\": 3072,\n", + " \"layer_norm_eps\": 1e-05,\n", + " \"max_position_embeddings\": 514,\n", + " \"model_type\": \"roberta\",\n", + " \"num_attention_heads\": 12,\n", + " \"num_hidden_layers\": 12,\n", + " \"pad_token_id\": 1,\n", + " \"position_embedding_type\": \"absolute\",\n", + " \"transformers_version\": \"4.9.0.dev0\",\n", + " \"type_vocab_size\": 1,\n", + " \"use_cache\": true,\n", + " \"vocab_size\": 50265\n", + "}\n", + "\n", + "[INFO|tokenization_utils_base.py:1722] 2021-07-20 15:07:17,210 >> loading file https://huggingface.co/bertin-project/bertin-base-stepwise/resolve/main/vocab.json from cache at /root/.cache/huggingface/transformers/dc7971c78d10d920138338883fd23b96f3994bce40018345ab1ba2ba8c8f6bdd.a80f232f572026f92499b14999a8ed4e044e04cf3d01b9f2be298c98e78e8498\n", + "[INFO|tokenization_utils_base.py:1722] 2021-07-20 15:07:17,210 >> loading file https://huggingface.co/bertin-project/bertin-base-stepwise/resolve/main/merges.txt from cache at /root/.cache/huggingface/transformers/5f573076405f6fab314615142ba9deec180a84917e495fecbf81f61afb2965cb.a0dfc41f9d0f03a56ba7a5401d770f6e43071045a0bd79073380d408d17a0d92\n", + "[INFO|tokenization_utils_base.py:1722] 2021-07-20 15:07:17,210 >> loading file https://huggingface.co/bertin-project/bertin-base-stepwise/resolve/main/tokenizer.json from cache at /root/.cache/huggingface/transformers/9a541e4855ef267ea4879cc9c2277f67dd5569f68cc688d212822bed1ca8755f.2a5dc806edc00ab3a329cb22b9973596ca75b24ba0e5e4963bf1308de7237a3d\n", + "[INFO|tokenization_utils_base.py:1722] 2021-07-20 15:07:17,210 >> loading file https://huggingface.co/bertin-project/bertin-base-stepwise/resolve/main/added_tokens.json from cache at None\n", + "[INFO|tokenization_utils_base.py:1722] 2021-07-20 15:07:17,210 >> loading file https://huggingface.co/bertin-project/bertin-base-stepwise/resolve/main/special_tokens_map.json from cache at /root/.cache/huggingface/transformers/8e21c2757a0c3938b80989bb3dabd355f9221ed98847fb957a5c4e9a86209c03.a11ebb04664c067c8fe5ef8f8068b0f721263414a26058692f7b2e4ba2a1b342\n", + "[INFO|tokenization_utils_base.py:1722] 2021-07-20 15:07:17,210 >> loading file https://huggingface.co/bertin-project/bertin-base-stepwise/resolve/main/tokenizer_config.json from cache at /root/.cache/huggingface/transformers/e577044edb84fa4a576105e2202c62cf62f831634f9581da80435c97b8034fba.9f7ac4246b492dfa7c21beb5233deec8aef46153ec25ac5258ac5e2ae82dfa89\n", + "[INFO|modeling_utils.py:1271] 2021-07-20 15:07:17,636 >> loading weights file https://huggingface.co/bertin-project/bertin-base-stepwise/resolve/main/pytorch_model.bin from cache at /root/.cache/huggingface/transformers/4832a73c0f4a13adaab71151bf2413717416da487cdb2a79247f10198c6421f8.aebba6b503a22a0c70b362f8b026aa0f030aae594f7580f0164a0a73fb0001af\n", + "[WARNING|modeling_utils.py:1502] 2021-07-20 15:07:25,547 >> Some weights of the model checkpoint at bertin-project/bertin-base-stepwise were not used when initializing RobertaForSequenceClassification: ['lm_head.layer_norm.weight', 'lm_head.bias', 'lm_head.dense.bias', 'lm_head.dense.weight', 'lm_head.layer_norm.bias']\n", + "- This IS expected if you are initializing RobertaForSequenceClassification from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).\n", + "- This IS NOT expected if you are initializing RobertaForSequenceClassification from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).\n", + "[WARNING|modeling_utils.py:1513] 2021-07-20 15:07:25,547 >> Some weights of RobertaForSequenceClassification were not initialized from the model checkpoint at bertin-project/bertin-base-stepwise and are newly initialized: ['classifier.out_proj.bias', 'classifier.dense.weight', 'classifier.dense.bias', 'classifier.out_proj.weight']\n", + "You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.\n", + "07/20/2021 15:07:25 - WARNING - datasets.arrow_dataset - Loading cached processed dataset at /root/.cache/huggingface/datasets/pawsx/es/1.1.0/a5033b43902a02a4ba2ee469c1dd22af3e6a4a247ac47fa1af9835d0e734e2af/cache-76ca7b71f1e87df9.arrow\n", + "07/20/2021 15:07:26 - WARNING - datasets.arrow_dataset - Loading cached processed dataset at /root/.cache/huggingface/datasets/pawsx/es/1.1.0/a5033b43902a02a4ba2ee469c1dd22af3e6a4a247ac47fa1af9835d0e734e2af/cache-db0d8830efc25d6e.arrow\n", + "Running tokenizer on dataset: 0% 0/2 [00:00> The following columns in the training set don't have a corresponding argument in `RobertaForSequenceClassification.forward` and have been ignored: sentence1, sentence2, id.\n", + "[INFO|trainer.py:1162] 2021-07-20 15:07:31,426 >> ***** Running training *****\n", + "[INFO|trainer.py:1163] 2021-07-20 15:07:31,426 >> Num examples = 49401\n", + "[INFO|trainer.py:1164] 2021-07-20 15:07:31,426 >> Num Epochs = 5\n", + "[INFO|trainer.py:1165] 2021-07-20 15:07:31,426 >> Instantaneous batch size per device = 8\n", + "[INFO|trainer.py:1166] 2021-07-20 15:07:31,426 >> Total train batch size (w. parallel, distributed & accumulation) = 8\n", + "[INFO|trainer.py:1167] 2021-07-20 15:07:31,426 >> Gradient Accumulation steps = 1\n", + "[INFO|trainer.py:1168] 2021-07-20 15:07:31,426 >> Total optimization steps = 30880\n", + "[INFO|integrations.py:446] 2021-07-20 15:07:31,446 >> Automatic Weights & Biases logging enabled, to disable set os.environ[\"WANDB_DISABLED\"] = \"true\"\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Currently logged in as: \u001b[33mversae\u001b[0m (use `wandb login --relogin` to force relogin)\n", + "2021-07-20 15:07:32.876281: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Successfully opened dynamic library libcudart.so.11.0\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Tracking run with wandb version 0.11.0\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Syncing run \u001b[33m./outputs\u001b[0m\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: ⭐️ View project at \u001b[34m\u001b[4mhttps://wandb.ai/versae/bertin-eval\u001b[0m\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: 🚀 View run at \u001b[34m\u001b[4mhttps://wandb.ai/versae/bertin-eval/runs/1zzsesw7\u001b[0m\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Run data is saved locally in /content/wandb/run-20210720_150731-1zzsesw7\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: Run `wandb offline` to turn off syncing.\n", + "\n", + " {'loss': 0.7073, 'learning_rate': 4.919041450777203e-05, 'epoch': 0.08}\n", + " 2% 500/30880 [01:37<2:53:12, 2.92it/s][INFO|trainer.py:1917] 2021-07-20 15:09:11,219 >> Saving model checkpoint to ./outputs/checkpoint-500\n", + "[INFO|configuration_utils.py:379] 2021-07-20 15:09:11,221 >> Configuration saved in ./outputs/checkpoint-500/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-20 15:09:12,592 >> Model weights saved in ./outputs/checkpoint-500/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-20 15:09:12,593 >> tokenizer config file saved in ./outputs/checkpoint-500/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-20 15:09:12,594 >> Special tokens file saved in ./outputs/checkpoint-500/special_tokens_map.json\n", + "{'loss': 0.592, 'learning_rate': 4.8380829015544046e-05, 'epoch': 0.16}\n", + " 3% 1000/30880 [03:20<2:46:17, 2.99it/s][INFO|trainer.py:1917] 2021-07-20 15:10:54,974 >> Saving model checkpoint to ./outputs/checkpoint-1000\n", + "[INFO|configuration_utils.py:379] 2021-07-20 15:10:54,975 >> Configuration saved in ./outputs/checkpoint-1000/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-20 15:10:56,282 >> Model weights saved in ./outputs/checkpoint-1000/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-20 15:10:56,283 >> tokenizer config file saved in ./outputs/checkpoint-1000/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-20 15:10:56,283 >> Special tokens file saved in ./outputs/checkpoint-1000/special_tokens_map.json\n", + "{'loss': 0.5125, 'learning_rate': 4.7571243523316064e-05, 'epoch': 0.24}\n", + " 5% 1500/30880 [05:03<2:41:55, 3.02it/s][INFO|trainer.py:1917] 2021-07-20 15:12:37,612 >> Saving model checkpoint to ./outputs/checkpoint-1500\n", + "[INFO|configuration_utils.py:379] 2021-07-20 15:12:37,613 >> Configuration saved in ./outputs/checkpoint-1500/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-20 15:12:38,967 >> Model weights saved in ./outputs/checkpoint-1500/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-20 15:12:38,968 >> tokenizer config file saved in ./outputs/checkpoint-1500/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-20 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checkpoint to ./outputs/checkpoint-2500\n", + "{'loss': 0.4658, 'learning_rate': 4.595207253886011e-05, 'epoch': 0.4}\n", + "[INFO|configuration_utils.py:379] 2021-07-20 15:16:03,543 >> Configuration saved in ./outputs/checkpoint-2500/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-20 15:16:04,986 >> Model weights saved in ./outputs/checkpoint-2500/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-20 15:16:04,987 >> tokenizer config file saved in ./outputs/checkpoint-2500/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-20 15:16:04,987 >> Special tokens file saved in ./outputs/checkpoint-2500/special_tokens_map.json\n", + " 10% 3000/30880 [10:13<2:55:59, 2.64it/s]{'loss': 0.4675, 'learning_rate': 4.5142487046632126e-05, 'epoch': 0.49}\n", + " 10% 3000/30880 [10:13<2:55:59, 2.64it/s][INFO|trainer.py:1917] 2021-07-20 15:17:47,698 >> Saving model checkpoint to ./outputs/checkpoint-3000\n", + "[INFO|configuration_utils.py:379] 2021-07-20 15:17:47,699 >> Configuration saved in ./outputs/checkpoint-3000/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-20 15:17:49,080 >> Model weights saved in ./outputs/checkpoint-3000/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-20 15:17:49,080 >> tokenizer config file saved in ./outputs/checkpoint-3000/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-20 15:17:49,081 >> Special tokens file saved in ./outputs/checkpoint-3000/special_tokens_map.json\n", + " 11% 3500/30880 [11:55<2:32:42, 2.99it/s]{'loss': 0.4143, 'learning_rate': 4.433290155440415e-05, 'epoch': 0.57}\n", + "[INFO|trainer.py:1917] 2021-07-20 15:19:30,049 >> Saving model checkpoint to ./outputs/checkpoint-3500\n", + "[INFO|configuration_utils.py:379] 2021-07-20 15:19:30,053 >> Configuration saved in ./outputs/checkpoint-3500/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-20 15:19:31,476 >> Model weights saved in 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4.190414507772021e-05, 'epoch': 0.81}\n", + " 16% 5000/30880 [17:02<2:26:31, 2.94it/s][INFO|trainer.py:1917] 2021-07-20 15:24:36,868 >> Saving model checkpoint to ./outputs/checkpoint-5000\n", + "[INFO|configuration_utils.py:379] 2021-07-20 15:24:36,869 >> Configuration saved in ./outputs/checkpoint-5000/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-20 15:24:38,356 >> Model weights saved in ./outputs/checkpoint-5000/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-20 15:24:38,357 >> tokenizer config file saved in ./outputs/checkpoint-5000/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-20 15:24:38,357 >> Special tokens file saved in ./outputs/checkpoint-5000/special_tokens_map.json\n", + "{'loss': 0.4076, 'learning_rate': 4.109455958549223e-05, 'epoch': 0.89}\n", + " 18% 5500/30880 [18:44<2:20:21, 3.01it/s][INFO|trainer.py:1917] 2021-07-20 15:26:18,777 >> Saving model checkpoint to ./outputs/checkpoint-5500\n", + "[INFO|configuration_utils.py:379] 2021-07-20 15:26:18,778 >> Configuration saved in ./outputs/checkpoint-5500/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-20 15:26:20,151 >> Model weights saved in ./outputs/checkpoint-5500/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-20 15:26:20,180 >> tokenizer config file saved in ./outputs/checkpoint-5500/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-20 15:26:20,180 >> Special tokens file saved in ./outputs/checkpoint-5500/special_tokens_map.json\n", + "{'loss': 0.3757, 'learning_rate': 4.028497409326425e-05, 'epoch': 0.97}\n", + " 19% 6000/30880 [20:26<2:17:39, 3.01it/s][INFO|trainer.py:1917] 2021-07-20 15:28:00,979 >> Saving model checkpoint to ./outputs/checkpoint-6000\n", + "[INFO|configuration_utils.py:379] 2021-07-20 15:28:00,980 >> Configuration saved in ./outputs/checkpoint-6000/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-20 15:28:02,413 >> Model weights saved in ./outputs/checkpoint-6000/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-20 15:28:02,414 >> tokenizer config file saved in ./outputs/checkpoint-6000/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-20 15:28:02,414 >> Special tokens file saved in ./outputs/checkpoint-6000/special_tokens_map.json\n", + "{'loss': 0.3788, 'learning_rate': 3.9475388601036275e-05, 'epoch': 1.05}\n", + " 21% 6500/30880 [22:08<2:15:45, 2.99it/s][INFO|trainer.py:1917] 2021-07-20 15:29:42,929 >> Saving model checkpoint to ./outputs/checkpoint-6500\n", + "[INFO|configuration_utils.py:379] 2021-07-20 15:29:42,930 >> Configuration saved in ./outputs/checkpoint-6500/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-20 15:29:44,394 >> Model weights saved in ./outputs/checkpoint-6500/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-20 15:29:44,395 >> tokenizer config file saved in ./outputs/checkpoint-6500/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-20 15:29:44,395 >> Special tokens file saved in ./outputs/checkpoint-6500/special_tokens_map.json\n", + "{'loss': 0.3526, 'learning_rate': 3.8665803108808294e-05, 'epoch': 1.13}\n", + " 23% 7000/30880 [23:50<2:15:14, 2.94it/s][INFO|trainer.py:1917] 2021-07-20 15:31:24,408 >> Saving model checkpoint to ./outputs/checkpoint-7000\n", + "[INFO|configuration_utils.py:379] 2021-07-20 15:31:24,409 >> Configuration saved in ./outputs/checkpoint-7000/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-20 15:31:25,828 >> Model weights saved in ./outputs/checkpoint-7000/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-20 15:31:25,828 >> tokenizer config file saved in ./outputs/checkpoint-7000/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-20 15:31:25,829 >> Special tokens file saved in ./outputs/checkpoint-7000/special_tokens_map.json\n", + "{'loss': 0.3525, 'learning_rate': 3.785621761658031e-05, 'epoch': 1.21}\n", + " 24% 7500/30880 [25:31<2:11:11, 2.97it/s][INFO|trainer.py:1917] 2021-07-20 15:33:06,085 >> Saving model checkpoint to ./outputs/checkpoint-7500\n", + "[INFO|configuration_utils.py:379] 2021-07-20 15:33:06,086 >> Configuration saved in ./outputs/checkpoint-7500/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-20 15:33:07,561 >> Model weights saved in ./outputs/checkpoint-7500/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-20 15:33:07,562 >> tokenizer config file saved in ./outputs/checkpoint-7500/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-20 15:33:07,562 >> Special tokens file saved in ./outputs/checkpoint-7500/special_tokens_map.json\n", + " 26% 8000/30880 [27:13<2:05:27, 3.04it/s]{'loss': 0.3367, 'learning_rate': 3.704663212435233e-05, 'epoch': 1.3}\n", + "[INFO|trainer.py:1917] 2021-07-20 15:34:47,724 >> Saving model checkpoint to ./outputs/checkpoint-8000\n", + "[INFO|configuration_utils.py:379] 2021-07-20 15:34:47,725 >> Configuration saved in ./outputs/checkpoint-8000/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-20 15:34:49,236 >> Model weights saved in ./outputs/checkpoint-8000/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-20 15:34:49,236 >> tokenizer config file saved in ./outputs/checkpoint-8000/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-20 15:34:49,237 >> Special tokens file saved in ./outputs/checkpoint-8000/special_tokens_map.json\n", + " 28% 8500/30880 [28:55<2:06:03, 2.96it/s]{'loss': 0.3467, 'learning_rate': 3.6237046632124356e-05, 'epoch': 1.38}\n", + "[INFO|trainer.py:1917] 2021-07-20 15:36:30,045 >> Saving model checkpoint to ./outputs/checkpoint-8500\n", + "[INFO|configuration_utils.py:379] 2021-07-20 15:36:30,046 >> Configuration saved in ./outputs/checkpoint-8500/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-20 15:36:31,513 >> Model weights saved in ./outputs/checkpoint-8500/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-20 15:36:31,514 >> tokenizer config file saved in ./outputs/checkpoint-8500/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-20 15:36:31,514 >> Special tokens file saved in ./outputs/checkpoint-8500/special_tokens_map.json\n", + " 29% 9000/30880 [30:38<2:02:02, 2.99it/s]{'loss': 0.3406, 'learning_rate': 3.5427461139896374e-05, 'epoch': 1.46}\n", + "[INFO|trainer.py:1917] 2021-07-20 15:38:12,287 >> Saving model checkpoint to ./outputs/checkpoint-9000\n", + "[INFO|configuration_utils.py:379] 2021-07-20 15:38:12,289 >> Configuration saved in ./outputs/checkpoint-9000/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-20 15:38:13,681 >> Model weights saved in ./outputs/checkpoint-9000/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-20 15:38:13,682 >> tokenizer config file saved in ./outputs/checkpoint-9000/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-20 15:38:13,683 >> Special tokens file saved in ./outputs/checkpoint-9000/special_tokens_map.json\n", + " 31% 9500/30880 [32:19<1:57:28, 3.03it/s]{'loss': 0.3246, 'learning_rate': 3.46178756476684e-05, 'epoch': 1.54}\n", + " 31% 9500/30880 [32:19<1:57:28, 3.03it/s][INFO|trainer.py:1917] 2021-07-20 15:39:53,791 >> Saving model checkpoint to ./outputs/checkpoint-9500\n", + "[INFO|configuration_utils.py:379] 2021-07-20 15:39:53,792 >> Configuration saved in ./outputs/checkpoint-9500/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-20 15:39:55,125 >> Model weights saved in ./outputs/checkpoint-9500/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-20 15:39:55,125 >> tokenizer config file saved in ./outputs/checkpoint-9500/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-20 15:39:55,126 >> Special tokens file saved in ./outputs/checkpoint-9500/special_tokens_map.json\n", + " 32% 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15:43:16,682 >> Saving model checkpoint to ./outputs/checkpoint-10500\n", + "[INFO|configuration_utils.py:379] 2021-07-20 15:43:16,684 >> Configuration saved in ./outputs/checkpoint-10500/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-20 15:43:18,052 >> Model weights saved in ./outputs/checkpoint-10500/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-20 15:43:18,053 >> tokenizer config file saved in ./outputs/checkpoint-10500/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-20 15:43:18,055 >> Special tokens file saved in ./outputs/checkpoint-10500/special_tokens_map.json\n", + "{'loss': 0.3209, 'learning_rate': 3.2189119170984454e-05, 'epoch': 1.78}\n", + " 36% 11000/30880 [37:23<1:48:09, 3.06it/s][INFO|trainer.py:1917] 2021-07-20 15:44:57,615 >> Saving model checkpoint to ./outputs/checkpoint-11000\n", + "[INFO|configuration_utils.py:379] 2021-07-20 15:44:57,616 >> Configuration saved in ./outputs/checkpoint-11000/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-20 15:44:59,438 >> Model weights saved in ./outputs/checkpoint-11000/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-20 15:44:59,439 >> tokenizer config file saved in ./outputs/checkpoint-11000/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-20 15:44:59,443 >> Special tokens file saved in ./outputs/checkpoint-11000/special_tokens_map.json\n", + "{'loss': 0.3148, 'learning_rate': 3.137953367875648e-05, 'epoch': 1.86}\n", + " 37% 11500/30880 [39:05<1:48:16, 2.98it/s][INFO|trainer.py:1917] 2021-07-20 15:46:39,293 >> Saving model checkpoint to ./outputs/checkpoint-11500\n", + "[INFO|configuration_utils.py:379] 2021-07-20 15:46:39,295 >> Configuration saved in ./outputs/checkpoint-11500/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-20 15:46:40,782 >> Model weights saved in ./outputs/checkpoint-11500/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-20 15:46:40,782 >> tokenizer config file saved in ./outputs/checkpoint-11500/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-20 15:46:40,809 >> Special tokens file saved in ./outputs/checkpoint-11500/special_tokens_map.json\n", + "{'loss': 0.3225, 'learning_rate': 3.05699481865285e-05, 'epoch': 1.94}\n", + " 39% 12000/30880 [40:46<1:43:31, 3.04it/s][INFO|trainer.py:1917] 2021-07-20 15:48:20,223 >> Saving model checkpoint to ./outputs/checkpoint-12000\n", + "[INFO|configuration_utils.py:379] 2021-07-20 15:48:20,224 >> Configuration saved in ./outputs/checkpoint-12000/config.json\n", + "[INFO|modeling_utils.py:997] 2021-07-20 15:48:21,700 >> Model weights saved in ./outputs/checkpoint-12000/pytorch_model.bin\n", + "[INFO|tokenization_utils_base.py:1998] 2021-07-20 15:48:21,701 >> tokenizer config file saved in ./outputs/checkpoint-12000/tokenizer_config.json\n", + "[INFO|tokenization_utils_base.py:2004] 2021-07-20 15:48:21,702 >> Special tokens file saved in ./outputs/checkpoint-12000/special_tokens_map.json\n", + " 40% 12284/30880 [41:45<59:16, 5.23it/s]" + ], + "name": "stdout" + } + ] + }, + { + "cell_type": "code", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 364, + "referenced_widgets": [ + "3375353ee2ea43d28775f62c49ee0538", + "b57b116c89594c558fb17ee835cec7ae", + "2de683c0aad84a33b5d74c338151cb11", + "2d6e2ae6f5e24092bda544ced04abab4", + "ce5c0860d88b4ae594ff9c4f97bc998b", + "e908ba524a584e1c82cb2a1e0e48d7d6", + "5196bc6355b9487aadc2ac77b84f4c0c", + "76697b9a49db4f6c9a43f8a102118a45" + ] + }, + "id": "pqN4wpd7SZQN", + "outputId": "0ffb4081-1722-4e19-9399-a3946a208a12" + }, + "source": [ + "from datasets import load_metric\n", + "\n", + "load_metric(\"accuracy\")" + ], + "execution_count": null, + "outputs": [ + { + "output_type": "display_data", + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "3375353ee2ea43d28775f62c49ee0538", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "HBox(children=(FloatProgress(value=0.0, description='Downloading', max=1362.0, style=ProgressStyle(description…" + ] + }, + "metadata": { + "tags": [] + } + }, + { + "output_type": "stream", + "text": [ + "\n" + ], + "name": "stdout" + }, + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "Metric(name: \"accuracy\", features: {'predictions': Value(dtype='int32', id=None), 'references': Value(dtype='int32', id=None)}, usage: \"\"\"\n", + "Args:\n", + " predictions: Predicted labels, as returned by a model.\n", + " references: Ground truth labels.\n", + " normalize: If False, return the number of correctly classified samples.\n", + " Otherwise, return the fraction of correctly classified samples.\n", + " sample_weight: Sample weights.\n", + "Returns:\n", + " accuracy: Accuracy score.\n", + "Examples:\n", + "\n", + " >>> accuracy_metric = datasets.load_metric(\"accuracy\")\n", + " >>> results = accuracy_metric.compute(references=[0, 1], predictions=[0, 1])\n", + " >>> print(results)\n", + " {'accuracy': 1.0}\n", + "\"\"\", stored examples: 0)" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 13 + } + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "2UoX0t5AFxvM" + }, + "source": [ + "# !wget https://raw.githubusercontent.com/huggingface/transformers/master/examples/pytorch/token-classification/run_ner.py\n", + "for model in models:\n", + " !WANDB_PROJECT=bertin-eval TOKENIZERS_PARALLELISM=false CUDA_LAUNCH_BLOCKING=1 python run_glue.py \\\n", + " --model_name_or_path $model \\\n", + " --dataset_name \"amazon_reviews_multi\" \\\n", + " --dataset_config_name \"es\" \\\n", + " --task_name \"amazon_reviews_multi\" \\\n", + " --output_dir ./outputs \\\n", + " --overwrite_output_dir \\\n", + " --pad_to_max_length \\\n", + " --num_train_epochs 5 \\\n", + " --do_train \\\n", + " --do_eval" + ], + "execution_count": null, + "outputs": [] + } + ] +} diff --git a/data_tooling/bertin/evaluation/run_ner.py b/data_tooling/bertin/evaluation/run_ner.py new file mode 100644 index 0000000..dbd9cd9 --- /dev/null +++ b/data_tooling/bertin/evaluation/run_ner.py @@ -0,0 +1,654 @@ +#!/usr/bin/env python +# coding=utf-8 +# Copyright 2020 The HuggingFace Team All rights reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +""" +Fine-tuning the library models for token classification. +""" +# You can also adapt this script on your own token classification task and datasets. Pointers for this are left as +# comments. + +import logging +import os +import sys +from dataclasses import dataclass, field +from pathlib import Path +from typing import Optional + +import datasets +import numpy as np +import transformers +from datasets import ClassLabel, load_dataset, load_metric +from transformers import ( + AutoConfig, + AutoModelForTokenClassification, + AutoTokenizer, + DataCollatorForTokenClassification, + HfArgumentParser, + PreTrainedTokenizerFast, + Trainer, + TrainingArguments, + set_seed, +) +from transformers.trainer_utils import get_last_checkpoint +from transformers.utils import check_min_version +from transformers.utils.versions import require_version + +# Will error if the minimal version of Transformers is not installed. Remove at your own risks. +check_min_version("4.9.0.dev0") + +require_version( + "datasets>=1.8.0", + "To fix: pip install -r examples/pytorch/token-classification/requirements.txt", +) + +logger = logging.getLogger(__name__) + + +@dataclass +class ModelArguments: + """ + Arguments pertaining to which model/config/tokenizer we are going to fine-tune from. + """ + + model_name_or_path: str = field( + metadata={ + "help": "Path to pretrained model or model identifier from huggingface.co/models" + } + ) + config_name: Optional[str] = field( + default=None, + metadata={ + "help": "Pretrained config name or path if not the same as model_name" + }, + ) + tokenizer_name: Optional[str] = field( + default=None, + metadata={ + "help": "Pretrained tokenizer name or path if not the same as model_name" + }, + ) + cache_dir: Optional[str] = field( + default=None, + metadata={ + "help": "Where do you want to store the pretrained models downloaded from huggingface.co" + }, + ) + model_revision: str = field( + default="main", + metadata={ + "help": "The specific model version to use (can be a branch name, tag name or commit id)." + }, + ) + use_auth_token: bool = field( + default=False, + metadata={ + "help": "Will use the token generated when running `transformers-cli login` (necessary to use this script " + "with private models)." + }, + ) + + +@dataclass +class DataTrainingArguments: + """ + Arguments pertaining to what data we are going to input our model for training and eval. + """ + + task_name: Optional[str] = field( + default="ner", metadata={"help": "The name of the task (ner, pos...)."} + ) + dataset_name: Optional[str] = field( + default=None, + metadata={"help": "The name of the dataset to use (via the datasets library)."}, + ) + dataset_config_name: Optional[str] = field( + default=None, + metadata={ + "help": "The configuration name of the dataset to use (via the datasets library)." + }, + ) + train_file: Optional[str] = field( + default=None, + metadata={"help": "The input training data file (a csv or JSON file)."}, + ) + validation_file: Optional[str] = field( + default=None, + metadata={ + "help": "An optional input evaluation data file to evaluate on (a csv or JSON file)." + }, + ) + test_file: Optional[str] = field( + default=None, + metadata={ + "help": "An optional input test data file to predict on (a csv or JSON file)." + }, + ) + text_column_name: Optional[str] = field( + default=None, + metadata={ + "help": "The column name of text to input in the file (a csv or JSON file)." + }, + ) + label_column_name: Optional[str] = field( + default=None, + metadata={ + "help": "The column name of label to input in the file (a csv or JSON file)." + }, + ) + overwrite_cache: bool = field( + default=False, + metadata={"help": "Overwrite the cached training and evaluation sets"}, + ) + preprocessing_num_workers: Optional[int] = field( + default=None, + metadata={"help": "The number of processes to use for the preprocessing."}, + ) + pad_to_max_length: bool = field( + default=False, + metadata={ + "help": "Whether to pad all samples to model maximum sentence length. " + "If False, will pad the samples dynamically when batching to the maximum length in the batch. More " + "efficient on GPU but very bad for TPU." + }, + ) + max_train_samples: Optional[int] = field( + default=None, + metadata={ + "help": "For debugging purposes or quicker training, truncate the number of training examples to this " + "value if set." + }, + ) + max_eval_samples: Optional[int] = field( + default=None, + metadata={ + "help": "For debugging purposes or quicker training, truncate the number of evaluation examples to this " + "value if set." + }, + ) + max_predict_samples: Optional[int] = field( + default=None, + metadata={ + "help": "For debugging purposes or quicker training, truncate the number of prediction examples to this " + "value if set." + }, + ) + label_all_tokens: bool = field( + default=False, + metadata={ + "help": "Whether to put the label for one word on all tokens of generated by that word or just on the " + "one (in which case the other tokens will have a padding index)." + }, + ) + return_entity_level_metrics: bool = field( + default=False, + metadata={ + "help": "Whether to return all the entity levels during evaluation or just the overall ones." + }, + ) + + def __post_init__(self): + if ( + self.dataset_name is None + and self.train_file is None + and self.validation_file is None + ): + raise ValueError( + "Need either a dataset name or a training/validation file." + ) + else: + if self.train_file is not None: + extension = self.train_file.split(".")[-1] + assert extension in [ + "csv", + "json", + ], "`train_file` should be a csv or a json file." + if self.validation_file is not None: + extension = self.validation_file.split(".")[-1] + assert extension in [ + "csv", + "json", + ], "`validation_file` should be a csv or a json file." + self.task_name = self.task_name.lower() + + +def main(): + # See all possible arguments in src/transformers/training_args.py + # or by passing the --help flag to this script. + # We now keep distinct sets of args, for a cleaner separation of concerns. + + parser = HfArgumentParser( + (ModelArguments, DataTrainingArguments, TrainingArguments) + ) + if len(sys.argv) == 2 and sys.argv[1].endswith(".json"): + # If we pass only one argument to the script and it's the path to a json file, + # let's parse it to get our arguments. + model_args, data_args, training_args = parser.parse_json_file( + json_file=os.path.abspath(sys.argv[1]) + ) + else: + model_args, data_args, training_args = parser.parse_args_into_dataclasses() + + # Setup logging + logging.basicConfig( + format="%(asctime)s - %(levelname)s - %(name)s - %(message)s", + datefmt="%m/%d/%Y %H:%M:%S", + handlers=[logging.StreamHandler(sys.stdout)], + ) + + log_level = training_args.get_process_log_level() + logger.setLevel(log_level) + datasets.utils.logging.set_verbosity(log_level) + transformers.utils.logging.set_verbosity(log_level) + transformers.utils.logging.enable_default_handler() + transformers.utils.logging.enable_explicit_format() + + # Log on each process the small summary: + logger.warning( + f"Process rank: {training_args.local_rank}, device: {training_args.device}, n_gpu: {training_args.n_gpu}" + + f"distributed training: {bool(training_args.local_rank != -1)}, 16-bits training: {training_args.fp16}" + ) + logger.info(f"Training/evaluation parameters {training_args}") + + # Detecting last checkpoint. + last_checkpoint = None + run_name = f"{model_args.model_name_or_path}-{np.random.randint(1000):04d}" + training_args.output_dir = str(Path(training_args.output_dir) / run_name) + if ( + os.path.isdir(training_args.output_dir) + and training_args.do_train + and not training_args.overwrite_output_dir + ): + last_checkpoint = get_last_checkpoint(training_args.output_dir) + if last_checkpoint is None and len(os.listdir(training_args.output_dir)) > 0: + raise ValueError( + f"Output directory ({training_args.output_dir}) already exists and is not empty. " + "Use --overwrite_output_dir to overcome." + ) + elif ( + last_checkpoint is not None and training_args.resume_from_checkpoint is None + ): + logger.info( + f"Checkpoint detected, resuming training at {last_checkpoint}. To avoid this behavior, change " + "the `--output_dir` or add `--overwrite_output_dir` to train from scratch." + ) + + # Set seed before initializing model. + set_seed(training_args.seed) + + # Get the datasets: you can either provide your own CSV/JSON/TXT training and evaluation files (see below) + # or just provide the name of one of the public datasets available on the hub at https://huggingface.co/datasets/ + # (the dataset will be downloaded automatically from the datasets Hub). + # + # For CSV/JSON files, this script will use the column called 'text' or the first column if no column called + # 'text' is found. You can easily tweak this behavior (see below). + # + # In distributed training, the load_dataset function guarantee that only one local process can concurrently + # download the dataset. + if data_args.dataset_name is not None: + # Downloading and loading a dataset from the hub. + raw_datasets = load_dataset( + data_args.dataset_name, + data_args.dataset_config_name, + cache_dir=model_args.cache_dir, + ) + else: + data_files = {} + if data_args.train_file is not None: + data_files["train"] = data_args.train_file + if data_args.validation_file is not None: + data_files["validation"] = data_args.validation_file + if data_args.test_file is not None: + data_files["test"] = data_args.test_file + extension = data_args.train_file.split(".")[-1] + raw_datasets = load_dataset( + extension, data_files=data_files, cache_dir=model_args.cache_dir + ) + # See more about loading any type of standard or custom dataset (from files, python dict, pandas DataFrame, etc) at + # https://huggingface.co/docs/datasets/loading_datasets.html. + + if training_args.do_train: + column_names = raw_datasets["train"].column_names + features = raw_datasets["train"].features + else: + column_names = raw_datasets["validation"].column_names + features = raw_datasets["validation"].features + + if data_args.text_column_name is not None: + text_column_name = data_args.text_column_name + elif "tokens" in column_names: + text_column_name = "tokens" + else: + text_column_name = column_names[0] + + if data_args.label_column_name is not None: + label_column_name = data_args.label_column_name + elif f"{data_args.task_name}_tags" in column_names: + label_column_name = f"{data_args.task_name}_tags" + else: + label_column_name = column_names[1] + + # In the event the labels are not a `Sequence[ClassLabel]`, we will need to go through the dataset to get the + # unique labels. + def get_label_list(labels): + unique_labels = set() + for label in labels: + unique_labels = unique_labels | set(label) + label_list = list(unique_labels) + label_list.sort() + return label_list + + if isinstance(features[label_column_name].feature, ClassLabel): + label_list = features[label_column_name].feature.names + # No need to convert the labels since they are already ints. + label_to_id = {i: i for i in range(len(label_list))} + else: + label_list = get_label_list(raw_datasets["train"][label_column_name]) + label_to_id = {l: i for i, l in enumerate(label_list)} + num_labels = len(label_list) + + # Load pretrained model and tokenizer + # + # Distributed training: + # The .from_pretrained methods guarantee that only one local process can concurrently + # download model & vocab. + config = AutoConfig.from_pretrained( + model_args.config_name + if model_args.config_name + else model_args.model_name_or_path, + num_labels=num_labels, + label2id=label_to_id, + id2label={i: l for l, i in label_to_id.items()}, + finetuning_task=data_args.task_name, + cache_dir=model_args.cache_dir, + revision=model_args.model_revision, + use_auth_token=True if model_args.use_auth_token else None, + ) + + tokenizer_name_or_path = ( + model_args.tokenizer_name + if model_args.tokenizer_name + else model_args.model_name_or_path + ) + if config.model_type in {"gpt2", "roberta"}: + tokenizer = AutoTokenizer.from_pretrained( + tokenizer_name_or_path, + cache_dir=model_args.cache_dir, + use_fast=True, + revision=model_args.model_revision, + use_auth_token=True if model_args.use_auth_token else None, + add_prefix_space=True, + ) + else: + tokenizer = AutoTokenizer.from_pretrained( + tokenizer_name_or_path, + cache_dir=model_args.cache_dir, + use_fast=True, + revision=model_args.model_revision, + use_auth_token=True if model_args.use_auth_token else None, + ) + tokenizer.model_max_length = 512 + + model = AutoModelForTokenClassification.from_pretrained( + model_args.model_name_or_path, + from_tf=bool(".ckpt" in model_args.model_name_or_path), + config=config, + cache_dir=model_args.cache_dir, + revision=model_args.model_revision, + use_auth_token=True if model_args.use_auth_token else None, + ) + + # Tokenizer check: this script requires a fast tokenizer. + if not isinstance(tokenizer, PreTrainedTokenizerFast): + raise ValueError( + "This example script only works for models that have a fast tokenizer. Checkout the big table of models " + "at https://huggingface.co/transformers/index.html#supported-frameworks to find the model types that meet this " + "requirement" + ) + + # Preprocessing the dataset + # Padding strategy + padding = "max_length" if data_args.pad_to_max_length else False + + # Tokenize all texts and align the labels with them. + def tokenize_and_align_labels(examples): + tokenized_inputs = tokenizer( + examples[text_column_name], + padding=padding, + max_length=512, + truncation=True, + # We use this argument because the texts in our dataset are lists of words (with a label for each word). + is_split_into_words=True, + ) + labels = [] + for i, label in enumerate(examples[label_column_name]): + word_ids = tokenized_inputs.word_ids(batch_index=i) + previous_word_idx = None + label_ids = [] + for word_idx in word_ids: + # Special tokens have a word id that is None. We set the label to -100 so they are automatically + # ignored in the loss function. + if word_idx is None: + label_ids.append(-100) + # We set the label for the first token of each word. + elif word_idx != previous_word_idx: + label_ids.append(label_to_id[label[word_idx]]) + # For the other tokens in a word, we set the label to either the current label or -100, depending on + # the label_all_tokens flag. + else: + label_ids.append( + label_to_id[label[word_idx]] + if data_args.label_all_tokens + else -100 + ) + previous_word_idx = word_idx + + labels.append(label_ids) + tokenized_inputs["labels"] = labels + return tokenized_inputs + + if training_args.do_train: + if "train" not in raw_datasets: + raise ValueError("--do_train requires a train dataset") + train_dataset = raw_datasets["train"] + if data_args.max_train_samples is not None: + train_dataset = train_dataset.select(range(data_args.max_train_samples)) + with training_args.main_process_first(desc="train dataset map pre-processing"): + train_dataset = train_dataset.map( + tokenize_and_align_labels, + batched=True, + num_proc=data_args.preprocessing_num_workers, + load_from_cache_file=not data_args.overwrite_cache, + desc="Running tokenizer on train dataset", + ) + + if training_args.do_eval: + if "validation" not in raw_datasets: + raise ValueError("--do_eval requires a validation dataset") + eval_dataset = raw_datasets["validation"] + if data_args.max_eval_samples is not None: + eval_dataset = eval_dataset.select(range(data_args.max_eval_samples)) + with training_args.main_process_first( + desc="validation dataset map pre-processing" + ): + eval_dataset = eval_dataset.map( + tokenize_and_align_labels, + batched=True, + num_proc=data_args.preprocessing_num_workers, + load_from_cache_file=not data_args.overwrite_cache, + desc="Running tokenizer on validation dataset", + ) + + if training_args.do_predict: + if "test" not in raw_datasets: + raise ValueError("--do_predict requires a test dataset") + predict_dataset = raw_datasets["test"] + if data_args.max_predict_samples is not None: + predict_dataset = predict_dataset.select( + range(data_args.max_predict_samples) + ) + with training_args.main_process_first( + desc="prediction dataset map pre-processing" + ): + predict_dataset = predict_dataset.map( + tokenize_and_align_labels, + batched=True, + num_proc=data_args.preprocessing_num_workers, + load_from_cache_file=not data_args.overwrite_cache, + desc="Running tokenizer on prediction dataset", + ) + + # Data collator + data_collator = DataCollatorForTokenClassification( + tokenizer, pad_to_multiple_of=8 if training_args.fp16 else None + ) + + # Metrics + metric = load_metric("seqeval") + + def compute_metrics(p): + predictions, labels = p + predictions = np.argmax(predictions, axis=2) + + # Remove ignored index (special tokens) + true_predictions = [ + [label_list[p] for (p, l) in zip(prediction, label) if l != -100] + for prediction, label in zip(predictions, labels) + ] + true_labels = [ + [label_list[l] for (p, l) in zip(prediction, label) if l != -100] + for prediction, label in zip(predictions, labels) + ] + + results = metric.compute(predictions=true_predictions, references=true_labels) + if data_args.return_entity_level_metrics: + # Unpack nested dictionaries + final_results = {} + for key, value in results.items(): + if isinstance(value, dict): + for n, v in value.items(): + final_results[f"{key}_{n}"] = v + else: + final_results[key] = value + return final_results + else: + return { + "precision": results["overall_precision"], + "recall": results["overall_recall"], + "f1": results["overall_f1"], + "accuracy": results["overall_accuracy"], + } + + # Initialize our Trainer + training_args.run_name = run_name + trainer = Trainer( + model=model, + args=training_args, + train_dataset=train_dataset if training_args.do_train else None, + eval_dataset=eval_dataset if training_args.do_eval else None, + tokenizer=tokenizer, + data_collator=data_collator, + compute_metrics=compute_metrics, + ) + + # Training + if training_args.do_train: + checkpoint = None + if training_args.resume_from_checkpoint is not None: + checkpoint = training_args.resume_from_checkpoint + elif last_checkpoint is not None: + checkpoint = last_checkpoint + train_result = trainer.train(resume_from_checkpoint=checkpoint) + metrics = train_result.metrics + trainer.save_model() # Saves the tokenizer too for easy upload + + max_train_samples = ( + data_args.max_train_samples + if data_args.max_train_samples is not None + else len(train_dataset) + ) + metrics["train_samples"] = min(max_train_samples, len(train_dataset)) + + trainer.log_metrics("train", metrics) + trainer.save_metrics("train", metrics) + trainer.save_state() + + # Evaluation + if training_args.do_eval: + logger.info("*** Evaluate ***") + + metrics = trainer.evaluate() + + max_eval_samples = ( + data_args.max_eval_samples + if data_args.max_eval_samples is not None + else len(eval_dataset) + ) + metrics["eval_samples"] = min(max_eval_samples, len(eval_dataset)) + + trainer.log_metrics("eval", metrics) + trainer.save_metrics("eval", metrics) + + # Predict + if training_args.do_predict: + logger.info("*** Predict ***") + + predictions, labels, metrics = trainer.predict( + predict_dataset, metric_key_prefix="predict" + ) + predictions = np.argmax(predictions, axis=2) + + # Remove ignored index (special tokens) + true_predictions = [ + [label_list[p] for (p, l) in zip(prediction, label) if l != -100] + for prediction, label in zip(predictions, labels) + ] + + trainer.log_metrics("predict", metrics) + trainer.save_metrics("predict", metrics) + + # Save predictions + output_predictions_file = os.path.join( + training_args.output_dir, "predictions.txt" + ) + if trainer.is_world_process_zero(): + with open(output_predictions_file, "w") as writer: + for prediction in true_predictions: + writer.write(" ".join(prediction) + "\n") + + if training_args.push_to_hub: + kwargs = { + "finetuned_from": model_args.model_name_or_path, + "tasks": "token-classification", + } + if data_args.dataset_name is not None: + kwargs["dataset_tags"] = data_args.dataset_name + if data_args.dataset_config_name is not None: + kwargs["dataset_args"] = data_args.dataset_config_name + kwargs[ + "dataset" + ] = f"{data_args.dataset_name} {data_args.dataset_config_name}" + else: + kwargs["dataset"] = data_args.dataset_name + + trainer.push_to_hub(**kwargs) + + +def _mp_fn(index): + # For xla_spawn (TPUs) + main() + + +if __name__ == "__main__": + main() diff --git a/data_tooling/bertin/evaluation/token.yaml b/data_tooling/bertin/evaluation/token.yaml new file mode 100644 index 0000000..478dba1 --- /dev/null +++ b/data_tooling/bertin/evaluation/token.yaml @@ -0,0 +1,53 @@ +name: BERTIN NER and POS es +project: bertin-eval +enitity: versae +program: run_ner.py +command: + - ${env} + - ${interpreter} + - ${program} + - ${args} +method: grid +metric: + name: eval/accuracy + goal: maximize +parameters: + model_name_or_path: + values: + - bertin-project/bertin-base-gaussian-exp-512seqlen + - bertin-project/bertin-base-stepwise-exp-512seqlen + - bertin-project/bertin-base-random-exp-512seqlen + - bertin-project/bertin-base-gaussian + - bertin-project/bertin-base-stepwise + - bertin-project/bertin-base-random + - bertin-project/bertin-roberta-base-spanish + - flax-community/bertin-roberta-large-spanish + - BSC-TeMU/roberta-base-bne + - dccuchile/bert-base-spanish-wwm-cased + - bert-base-multilingual-cased + num_train_epochs: + values: [5] + task_name: + values: + - ner + - pos + dataset_name: + value: conll2002 + dataset_config_name: + value: es + output_dir: + value: ./outputs + overwrite_output_dir: + value: true + pad_to_max_length: + value: true + per_device_train_batch_size: + value: 16 + per_device_eval_batch_size: + value: 16 + save_total_limit: + value: 1 + do_train: + value: true + do_eval: + value: true diff --git a/data_tooling/bertin/evaluation/xnli.yaml b/data_tooling/bertin/evaluation/xnli.yaml new file mode 100644 index 0000000..a2c3cf4 --- /dev/null +++ b/data_tooling/bertin/evaluation/xnli.yaml @@ -0,0 +1,53 @@ +name: BERTIN XNLI es +project: bertin-eval +enitity: versae +program: run_glue.py +command: + - ${env} + - ${interpreter} + - ${program} + - ${args} +method: grid +metric: + name: eval/accuracy + goal: maximize +parameters: + model_name_or_path: + values: + - bertin-project/bertin-base-gaussian-exp-512seqlen + - bertin-project/bertin-base-stepwise-exp-512seqlen + - bertin-project/bertin-base-random-exp-512seqlen + - bertin-project/bertin-base-gaussian + - bertin-project/bertin-base-stepwise + - bertin-project/bertin-base-random + - bertin-project/bertin-roberta-base-spanish + - flax-community/bertin-roberta-large-spanish + - BSC-TeMU/roberta-base-bne + - dccuchile/bert-base-spanish-wwm-cased + - bert-base-multilingual-cased + num_train_epochs: + values: [5] + task_name: + value: xnli + dataset_name: + value: xnli + dataset_config_name: + value: es + output_dir: + value: ./outputs + overwrite_output_dir: + value: true + max_seq_length: + value: 512 + pad_to_max_length: + value: true + per_device_train_batch_size: + value: 16 + per_device_eval_batch_size: + value: 16 + save_total_limit: + value: 1 + do_train: + value: true + do_eval: + value: true diff --git a/data_tooling/bertin/events.out.tfevents.1625704081.t1v-n-a4d97d44-w-0.212075.3.v2 b/data_tooling/bertin/events.out.tfevents.1625704081.t1v-n-a4d97d44-w-0.212075.3.v2 new file mode 100644 index 0000000..49ed094 --- /dev/null +++ b/data_tooling/bertin/events.out.tfevents.1625704081.t1v-n-a4d97d44-w-0.212075.3.v2 @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:6a6ce71bd4a3fdcb18c10bd9d140b27e746c14e9ee70a7a3faf4eedbccde1d6e +size 40 diff --git a/data_tooling/bertin/events.out.tfevents.1625704245.t1v-n-a4d97d44-w-0.216676.3.v2 b/data_tooling/bertin/events.out.tfevents.1625704245.t1v-n-a4d97d44-w-0.216676.3.v2 new file mode 100644 index 0000000..6f3c4e8 --- /dev/null +++ b/data_tooling/bertin/events.out.tfevents.1625704245.t1v-n-a4d97d44-w-0.216676.3.v2 @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:2a6926c79cb2c1941fcfe69d7b73797c15dab60e5e6f16cc6c61bd9b79a9063d +size 40 diff --git a/data_tooling/bertin/events.out.tfevents.1625705283.t1v-n-a4d97d44-w-0.234462.3.v2 b/data_tooling/bertin/events.out.tfevents.1625705283.t1v-n-a4d97d44-w-0.234462.3.v2 new file mode 100644 index 0000000..e972994 --- /dev/null +++ b/data_tooling/bertin/events.out.tfevents.1625705283.t1v-n-a4d97d44-w-0.234462.3.v2 @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:737d1e6666fe1c9fd6dd93728666199f1a8b0b213b071bdf7b3ecd77dd58f8c1 +size 40 diff --git a/data_tooling/bertin/get_embeddings_and_perplexity.py b/data_tooling/bertin/get_embeddings_and_perplexity.py new file mode 100644 index 0000000..8deb9e7 --- /dev/null +++ b/data_tooling/bertin/get_embeddings_and_perplexity.py @@ -0,0 +1,50 @@ +#!/usr/bin/env python +import kenlm +import numpy as np +import pandas as pd +from datasets import load_dataset +from sentence_transformers import SentenceTransformer +from tqdm import tqdm + +TOTAL_SENTENCES = 20000 + + +def pp(log_score, length): + return 10.0 ** (-log_score / length) + + +embedder = "distiluse-base-multilingual-cased-v1" +embedder_model = SentenceTransformer(embedder) +embedding_shape = embedder_model.encode(["foo"])[0].shape[0] +# http://dl.fbaipublicfiles.com/cc_net/lm/es.arpa.bin +model = kenlm.Model("es.arpa.bin") +mc4 = load_dataset("mc4", "es", streaming=True) +count = 0 +embeddings = [] +lenghts = [] +perplexities = [] +sentences = [] + +for sample in tqdm(mc4["train"].shuffle(buffer_size=100_000), total=416057992): + lines = sample["text"].split("\n") + for line in lines: + count += 1 + log_score = model.score(line) + length = len(line.split()) + 1 + embedding = embedder_model.encode([line])[0] + embeddings.append(embedding.tolist()) + perplexities.append(pp(log_score, length)) + lenghts.append(length) + sentences.append(line) + if count == TOTAL_SENTENCES: + break + if count == TOTAL_SENTENCES: + embeddings = np.array(embeddings) + df = pd.DataFrame( + {"sentence": sentences, "length": lenghts, "perplexity": perplexities} + ) + for dim in range(embedding_shape): + df[f"dim_{dim}"] = embeddings[:, dim] + df.to_csv("mc4-es-perplexity-sentences.tsv", index=None, sep="\t") + print("DONE!") + break diff --git a/data_tooling/bertin/images/bertin-tilt.png b/data_tooling/bertin/images/bertin-tilt.png new file mode 100644 index 0000000..b9aad85 Binary files /dev/null and b/data_tooling/bertin/images/bertin-tilt.png differ diff --git a/data_tooling/bertin/images/bertin.png b/data_tooling/bertin/images/bertin.png new file mode 100644 index 0000000..9864dad Binary files /dev/null and b/data_tooling/bertin/images/bertin.png differ diff --git a/data_tooling/bertin/images/ccnet.png b/data_tooling/bertin/images/ccnet.png new file 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0000000..514fa02 --- /dev/null +++ b/data_tooling/bertin/images/perplexity_colored_embeddings.html @@ -0,0 +1,85 @@ + + + + + + + + + + + Bokeh Plot + + + + + + + + + + + + + + + + + + + + + + + +
+ + + + + + + + + + + diff --git a/data_tooling/bertin/images/random_512.jpg b/data_tooling/bertin/images/random_512.jpg new file mode 100644 index 0000000..f9b511e Binary files /dev/null and b/data_tooling/bertin/images/random_512.jpg differ diff --git a/data_tooling/bertin/mc4/README.md b/data_tooling/bertin/mc4/README.md new file mode 100644 index 0000000..2840b22 --- /dev/null +++ b/data_tooling/bertin/mc4/README.md @@ -0,0 +1,525 @@ +--- +pretty_name: mC4 +annotations_creators: +- no-annotation +language_creators: +- found +languages: +- af +- am +- ar +- az +- be +- bg +- bg-Latn +- bn +- ca +- ceb +- co +- cs +- cy +- da +- de +- el +- el-Latn +- en +- eo +- es +- et +- eu +- fa +- fi +- fil +- fr +- fy +- ga +- gd +- gl +- gu +- ha +- haw +- hi +- hi-Latn +- hmn +- ht +- hu +- hy +- id +- ig +- is +- it +- iw +- ja +- ja-Latn +- jv +- ka +- kk +- km +- kn +- ko +- ku +- ky +- la +- lb +- lo +- lt +- lv +- mg +- mi +- mk +- ml +- mn +- mr +- ms +- mt +- my +- ne +- nl +- "no" +- ny +- pa +- pl +- ps +- pt +- ro +- ru +- ru-Latn +- sd +- si +- sk +- sl +- sm +- sn +- so +- sq +- sr +- st +- su +- sv +- sw +- ta +- te +- tg +- th +- tr +- uk +- und +- ur +- uz +- vi +- xh +- yi +- yo +- zh +- zh-Latn +- zu +licenses: +- odc-by-1.0 +multilinguality: +- multilingual +size_categories: +- n<1K +- 1K= boundaries[2]: + quartile_range = 10 * boundaries[2] + probability = factor / quartile_range + return self.rng.uniform() < probability + + def _should_keep_doc_gaussian(self, doc, factor=0.78, boundaries=None, **kwargs): + width = kwargs.get("width", 9 / 2) # width (spread) of the exponential curve + perplexity = self.get_perplexity(doc) + if boundaries is not None: + m = boundaries[1] + else: + m = 662247.50212365 + exponential = np.exp((-1 / width) * ((perplexity - m) / m) ** 2) + weighted_perplexity = factor * exponential + return self.rng.uniform() < weighted_perplexity + + def _should_keep_doc_random(self, doc, factor=None, boundaries=None, **kwargs): + if factor is None: + factor = 0.5 + return self.rng.uniform() <= factor + + def _info(self): + return datasets.DatasetInfo( + description=_DESCRIPTION, + features=datasets.Features( + { + "text": datasets.Value("string"), + "timestamp": datasets.Value("string"), + "url": datasets.Value("string"), + } + ), + supervised_keys=None, + homepage=_URL, + citation=_CITATION, + ) + + def _split_generators(self, dl_manager): + data_urls = {} + for split in ["train", "validation"]: + data_urls[split] = [ + _DATA_URL.format( + language=self.config.name, + split_suffix="-validation" if split == "validation" else "", + index=index, + n_shards=_N_SHARDS_PER_SPLIT[lang][split], + ) + for lang in self.config.languages + for index in range(_N_SHARDS_PER_SPLIT[lang][split]) + ] + if self.data_files and "train" in self.data_files: + train_downloaded_files = self.data_files["train"] + if not isinstance(train_downloaded_files, (tuple, list)): + train_downloaded_files = [train_downloaded_files] + else: + train_downloaded_files = dl_manager.download(data_urls["train"]) + if self.data_files and "validation" in self.data_files: + validation_downloaded_files = self.data_files["validation"] + if not isinstance(validation_downloaded_files, (tuple, list)): + validation_downloaded_files = [validation_downloaded_files] + else: + validation_downloaded_files = dl_manager.download(data_urls["validation"]) + return [ + datasets.SplitGenerator( + name=datasets.Split.TRAIN, + gen_kwargs={"filepaths": train_downloaded_files}, + ), + datasets.SplitGenerator( + name=datasets.Split.VALIDATION, + gen_kwargs={"filepaths": validation_downloaded_files}, + ), + ] + + def _generate_examples(self, filepaths): + """This function returns the examples in the raw (text) form by iterating on all the files.""" + id_ = 0 + for filepath in filepaths: + logger.info("generating examples from = %s", filepath) + if filepath.endswith("jsonl"): + with open(filepath, "r", encoding="utf-8") as f: + for line in f: + if line: + example = json.loads(line) + yield id_, example + id_ += 1 + else: + with gzip.open(open(filepath, "rb"), "rt", encoding="utf-8") as f: + if self.sampling_method: + logger.info("sampling method = %s", self.sampling_method) + for line in f: + if line: + example = json.loads(line) + if self.should_keep_doc( + example["text"], + factor=self.sampling_factor, + boundaries=self.boundaries, + **self.kwargs, + ): + yield id_, example + id_ += 1 + else: + for line in f: + if line: + example = json.loads(line) + yield id_, example + id_ += 1 diff --git a/data_tooling/bertin/merges.txt b/data_tooling/bertin/merges.txt new file mode 100644 index 0000000..1af7959 --- /dev/null +++ b/data_tooling/bertin/merges.txt @@ -0,0 +1,50005 @@ +#version: 0.2 - Trained by `huggingface/tokenizers` +d e +Ġ e +Ġ de +Ġ l +o s +Ġ p +Ġ c +a r +e n +e r +Ġ a +e s +a s +Ġ s +o n +c i +o r +u e +a n +Ġ m +a d +a l +Ġl a +q ue +Ġe n +u n +à ³ +i n +Ġ t +r e +Ġ y +s t +Ġ que +en t +Ġe l +Ã Ń +i c +Ġc on +ó n +à ¡ +Ġ n +Ġ un +Ġ h +o m +r a +d o +r o +d i +t i +Ġs e +Ġ f +ci ón +Ġ v +a m +Ġe s +Ġl os +Ġp ar +t e +Ġe st +Ġ o +l e +t a +r i +Ġ in +Ġ re +à © +t o +Ġs u +Ġde l +ad o +o l +i d +Ġc om +Ġ C +r es +a b +Ġ E +Ġa l +Ġp or +e c +Ġ b +Ġ d +Ġl as +Ġpar a +Ġ g +ent e +m p +à ± +Ġ A +i s +a ción +Ġ P +Ġun a +Ġ S +i l +ci on +ÃŃ a +Ġ di +Ġn o +u l +â Ģ +q u +Ġ M +Ġp ro +t u +a c +Ġs i +á s +Ġp er +Ġc u +Ġ L +t er +i en +t r +l o +l a +ad a +Ġm e +i o +d a +Ġl o +m a +u c +i st +i r +à º +Ġde s +ic a +i a +e l +ci a +g u +Ġ D +Ġa c +t os +u s +g o +i z +i er +i ent +r an +ti v +i t +Ġ 1 +Ġcom o +Ġ ( +al es +an do +Ġt o +Ġe x +Ġ i +id ad +Ġ 2 +. . +u es +cion es +Ġ T +Ġh a +Ġm ás +m o +i ci +m os +a j +s e +b re +ad os +t or +ic o +Ġ R +c u +p a +i e +á n +Ġs er +d ad +Ġ B +Ġ j +Ġp o +de n +i v +Ġs o +Ġa n +t ra +Ġ G +t es +de s +Ġ N +Ġ I +b i +t en +er a +t ro +Ġ F +t ar +Ġt ra +Ġ res +Ġ âĢ +id a +Ġa p +i ón +r as +i g +c o +i b +er o +Ġl e +i m +c h +Ġt e +or m +c a +ad or +d os +Ġp ue +ient o +Ġcom p +u m +Ġ qu +Ġm u +Ġp re +Ġsu s +p er +i os +c e +an te +Ġm a +Ġt en +p o +0 0 +r u +t as +de r +é n +âĢ Ŀ +e z +Ġa s +Ġ H +Ġp r +am os +Ġ V +am ente +Ġp a +p e +t re +Ġ ar +Ġest e +uc h +Ġ J +b l +Ġa ñ +Ġh ac +Ġh ab +Ġ U +m ente +Ġc a +ar a +u er +Ġm an +Ġi mp +c on +g un +en cia +ĠâĢ ľ +g ar +i on +ĠE l +Ġp res +s on +i do +ri m +u r +Ġper o +Ġs in +al iz +ĠL a +n a +g a +am bi +ad as +Ġc as +tr os +d uc +Ġest a +Ġt ien +u st +é s +ent o +E l +ue v +l es +in a +Ġs on +v er +z a +f er +Ġv er +Ġ O +l os +Ġp as +Ġ r +d as +j e +Ġm o +or es +Ġin ter +Ġdi s +an a +en s +ú n +0 1 +ĠE n +.. . +or a +Ġper son +Ġso bre +c es +l as +c ul +Ġc ar +c l +Ġc o +ar io +Ġ  +Ġen tre +n o +ic os +ent es +l an +ĠE st +Ġl le +t al +Ġ or +Ġm is +Ġcon s +Ġo b +Ġs ol +p or +Ġe mp +ic as +Ġn ues +b aj +Ġa m +Ġt u +p on +Ġn os +Ġin f +Ġm uch +ĠI n +ĠE s +Ġy a +ec h +e mos +ci as +Ġmu y +pa ñ +ci al +ent a +e m +Ġs al +Ġc re +ambi én +Ġto do +Ġme di +o y +Ġ 3 +L a +j o +ec es +Ġc or +Ġp os +Ġ " +d r +i f +p ar +Ġa b +Ġ2 01 +Ġes c +ab le +Ġp rim +Ġn uev +ĠC on +Ġm i +Ġme j +Ġde b +tiv o +Ġf in +an o +Ġt an +re c +g ra +cion al +o c +ÃŃ as +en do +m in +ab a +ÃŃ n +Ġm ar +or ma +v e +Ġc am +ci o +ñ o +ti l +i ta +m e +Ġtra baj +u di +tu ra +ÃŃ s +Ġest á +i as +p os +u en +b le +f ici +b a +Ġ Y +Ġañ os +r en +e b +Ġp e +es ti +Ġg ran +E n +Ġt ambién +Ġc al +l ar +Ġd u +as ta +ist a +Ġf ue +m as +v en +an tes +Ġdes de +Ġpue de +ida des +Ġha y +Ġ us +am iento +Ġn i +g an +r os +Ġn a +ar ios +ci p +Ġpar ti +u t +j er +ĠR e +Ġc ol +Ġd os +Ġcu ando +Ġ - +Ġhac er +o ci +Ġcu al +ĠS e +in o +f ec +c ar +or t +Ġ u +Ġtien e +Ġto dos +Ġd on +u d +ĠU n +qu i +ie mp +) . +ÃŃ t +Ġse gu +Ġre g +Ġm en +Ġm un +l ic +ar on +Ġh asta +g en +m b +Ġn eces +Ġt er +Ġpro p +p ec +Ġc os +Ġ é +Ġl u +Ġh an +Ġmej or +Ġma y +Ġ 4 +ĠA l +en er +in g +v i +qu ier +tiv a +on es +o g +ent os +Ġb ien +ar á +Ġt iemp +Ġde ci +Ġdon de +Ġc an +tr as +m i +Ġpar te +) , +Ġal gun +Ġpro duc +s o +a y +al mente +ter i +i tu +Ġa d +Ġex p +Ġf un +Ġc h +g r +ion es +Ġg ra +m ás +ador es +o b +tu r +Ġ 5 +Ġv ez +ĠD e +Ġinf orm +m an +ue l +c an +Ġm il +Ġp ol +ri b +Ġc ada +Ġd a +z o +Ġb uen +Ġas ÃŃ +Ġre aliz +id os +Ġpor que +Ġf orma +j a +e t +Ġl l +ar se +t ado +st e +i u +ran te +Ġp u +Ġser v +Ġtiemp o +Ġ do +ĠC om +i de +ÃŃ cul +er v +Ġv e +ro l +ci l +on a +Ġs ab +Ġt i +ĠM ar +ĠN o +e mp +âĢ ¦ +er os +p u +Ġt ran +Ġes pe +cu r +Ġd ÃŃa +Ġ1 9 +ul ar +un to +c om +n os +g os +a v +Ġañ o +Ġn e +Ġ ¿ +Ġun o +e d +ÃŃ an +m iento +Ġc er +é r +Ġcon tra +Ġc l +Ġa de +Ġin st +Ġcon t +Ġcon f +Ġv ida +it ar +ñ os +ú l +i den +Ġa h +ic ación +Ġemp res +i to +Ġin v +Ġd ic +Ġ W +v o +ib le +Ġa u +ĠS an +al idad +Ġin cl +il idad +Ġo p +ĠA n +Ġf u +e a +tiv os +Ġf uer +Ġlle v +om b +iu dad +ar rol +Ġperson as +a ciones +ti r +ú bl +úl ti +Ġpro f +le c +u b +Ġhac e +Ġl ib +Ġmis mo +Ġ ro +Ġa y +Ġ ra +Ġe v +er s +Ġg ener +Ġlu gar +Ġo f +ĠC h +a t +ci os +g ún +Ġcom un +Ġserv ici +Ġmay or +d u +Ġpa ÃŃs +c as +ĠL os +Ġo tros +Ġb as +c or +âĢĿ , +Ġre ci +ue go +i ción +Ġj u +en a +Ġcon st +Ġdi rec +á t +Ġtran s +y ec +an os +p ues +Ġp la +ient os +Ġse c +Ġpo dr +Ġe ra +Ġm in +Ġ 6 +Ġm om +d ic +ñ a +in cip +Ġac tu +mp l +Ġm as +Ġp lan +Ġimp ort +Ġmun do +j os +ech o +Ġde n +ien do +Ġdi st +u y +Ġre p +ĠP or +Ġv al +ver s +ra ción +Ġsi g +Ġdi fer +Ġf orm +é c +Ġ últi +Ġm es +cu ent +Ġtan to +Ġest án +Ġv is +ó lo +Ġdes arrol +Ġ K +Ġmuch o +Ġv iv +Ġpr incip +in e +ĠA r +t on +Ġen con +âĢĿ . +aj e +Ġdu rante +Ġ w +Ġu til +Ġl i +Ġs ent +om bre +Ġsol o +Ġsi emp +Ġsiemp re +t ic +Ġtrabaj o +en di +un que +v is +Ġe qui +pu és +am il +is mo +Ġten er +Ġp ues +Ġc ent +Ġh ist +Ġp on +Ġh er +Ġcu enta +Ġqu ien +r ar +Ġde st +Ġc ab +ĠL e +Ġl es +or ia +Ġb aj +Ġes o +Ġp es +tr ar +Ġde j +Ġest udi +c er +r uc +ist as +ces o +Ġcas o +Ġcual quier +Ġc iudad +se gu +te l +Ġ á +ĠP ro +Ġqu ier +ta ción +Ġal go +tor es +Ġt ras +i ente +f ic +Ġes e +Ġt ar +re ch +ent ar +Ġo tro +st a +Ġv ol +ar go +Ġmen os +da des +d ar +Ġres ul +i mo +Ġre f +Ġcomp le +Ġ ri +Ġll am +Ġen cuent +Ġb us +Ġmu jer +Ġc ó +ĠM e +z ar +Ġh or +Ā Ā +Ġsi do +Ġex per +Ġpo co +Ġt om +Ġnues tro +en e +Ġutil iz +ĠS i +u ción +e o +h o +c al +Ġv en +te g +Ġp l +Ġto da +ú s +Ġmom ento +gu a +an cia +it al +ier no +Ġsu per +ĠC ar +Ġre la +Ġm on +Ġf al +Ġ 7 +Ġap ar +Ġest os +Ġ2 00 +ec e +pañ a +Ġpue den +Ġinform ación +Ġse a +Ġde f +al a +Ġh i +ó m +Ġto das +om o +Ġg ust +ĠA s +ol a +Ġf amil +Ġpro yec +c el +Ġ 8 +iv ers +ci ales +Ġm er +Ġprof es +ri s +ĠD E +Ġnues tra +Ġnuev o +t an +Ġor gan +Ġpo der +Ġy o +L os +Ġpro ble +Ġ Q +Ġti po +t ó +ÃŃ st +Ġpol ÃŃt +Ġac tiv +Ġp úbl +Ġt r +c re +C I +Ġtra v +Ġca p +Ġc ul +Ġde rech +Ġhab ÃŃa +Ġ z +us o +Ġe mb +Ġv a +Ġd ÃŃas +Ġest ar +u ro +Ġan tes +v il +Ġf i +ti s +ÃŃ o +Ġman era +Ġob je +Ġh um +g res +g e +que l +Ġel ec +Ġ1 0 +Ġpu bl +Ġprim er +ol og +Ġh e +Ġt al +Ġt res +Ġprim era +E S +im iento +Ġes p +i ma +er on +Ġdes pués +Ġah ora +Ġi de +Ġtrav és +Ġ 9 +Ġo tra +á c +Ġg ru +om in +Ġtien en +Ġsi gu +ce p +ĠD es +Ġd 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ces +ac re +Ġte oria +ART ICULO +Ġimpa ciencia +Ġincuestion able +Ġcar ru +Al gún +ĠâĤ¬ / +DO C +Ġliv iana +f ores +Ġedi cion +No che +ĠGal ilea +ĠAC N +оР¹ +Ġadmir adores +v ist +å ľ +Ġp ach +Ġd uelen +Ġsuf ridas +Ġdesenvolver se +V igencia +Ġop rimidos +Ġpel liz +Ġlan zo +Ġresolver lo +Ġmadri dista +Ġsuscrib irse +Ġexponencial mente +Ġtan ga +Ġcan arias +Ġpla quetas +ĠCa f +ĠBu ñ +ĠPatr ona +Ġtrasc endido +ĠPRODUC TOS +Ġdesenvol vimiento +n á +Ġj et +rea u diff --git a/data_tooling/bertin/perplexity.py b/data_tooling/bertin/perplexity.py new file mode 100644 index 0000000..5631b09 --- /dev/null +++ b/data_tooling/bertin/perplexity.py @@ -0,0 +1,23 @@ +#!/usr/bin/env python +import kenlm +from datasets import load_dataset +from tqdm import tqdm + + +def pp(log_score, length): + return 10.0 ** (-log_score / length) + + +# http://dl.fbaipublicfiles.com/cc_net/lm/es.arpa.bin +model = kenlm.Model("es.arpa.bin") +mc4 = load_dataset("mc4", "es", streaming=True) +with open("mc4-es-perplexity.txt", "w") as f: + for sample in tqdm(mc4["train"].shuffle(buffer_size=100_000), total=416057992): + lines = sample["text"].split("\n") + doc_log_score, doc_length = 0, 0 + for line in lines: + log_score = model.score(line) + length = len(line.split()) + 1 + doc_log_score += log_score + doc_length += length + f.write(f"{pp(doc_log_score, doc_length)}\n") diff --git a/data_tooling/bertin/run.sh b/data_tooling/bertin/run.sh new file mode 100644 index 0000000..c6f4426 --- /dev/null +++ b/data_tooling/bertin/run.sh @@ -0,0 +1,29 @@ +#!/bin/bash +# From https://arxiv.org/pdf/1907.11692.pdf +python -c "import jax; print('TPUs', jax.device_count())" +./run_mlm_flax.py \ + --output_dir="./outputs" \ + --model_type="roberta" \ + --config_name="./configs/large" \ + --tokenizer_name="./" \ + --dataset_name="mc4" \ + --dataset_config_name="es" \ + --dataset_streamnig \ + --max_seq_length="128" \ + --pad_to_max_length \ + --per_device_train_batch_size="128" \ + --per_device_eval_batch_size="128" \ + --adam_beta1="0.9" \ + --adam_beta2="0.98" \ + --adam_epsilon="1e-6" \ + --learning_rate="4e-4" \ + --weight_decay="0.01" \ + --save_strategy="steps" \ + --save_steps="10000" \ + --save_total_limit="5" \ + --warmup_steps="30000" \ + --overwrite_output_dir \ + --num_train_steps="500000" \ + --eval_steps="10000" \ + --logging_steps="500" \ + --dtype="bfloat16" 2>&1 | tee run.log diff --git a/data_tooling/bertin/run_mlm_flax.py b/data_tooling/bertin/run_mlm_flax.py new file mode 100644 index 0000000..54251b9 --- /dev/null +++ b/data_tooling/bertin/run_mlm_flax.py @@ -0,0 +1,813 @@ +#!/usr/bin/env python +# coding=utf-8 +# Copyright 2021 The HuggingFace Team All rights reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +""" +Fine-tuning the library models for masked language modeling (BERT, ALBERT, RoBERTa...) with whole word masking on a +text file or a dataset. + +Here is the full list of checkpoints on the hub that can be fine-tuned by this script: +https://huggingface.co/models?filter=masked-lm +""" +import logging +import os +import sys +import time +from dataclasses import dataclass, field + +# You can also adapt this script on your own masked language modeling task. Pointers for this are left as comments. +from pathlib import Path +from typing import Dict, List, Optional, Tuple + +import flax +import jax +import jax.numpy as jnp +import numpy as np +import optax +from datasets import load_dataset +from flax import jax_utils, traverse_util +from flax.training import train_state +from flax.training.common_utils import get_metrics, onehot, shard +from tqdm import tqdm +from transformers import ( + CONFIG_MAPPING, + FLAX_MODEL_FOR_MASKED_LM_MAPPING, + AutoConfig, + AutoTokenizer, + FlaxAutoModelForMaskedLM, + HfArgumentParser, + PreTrainedTokenizerBase, + TensorType, + TrainingArguments, + is_tensorboard_available, + set_seed, +) + +MODEL_CONFIG_CLASSES = list(FLAX_MODEL_FOR_MASKED_LM_MAPPING.keys()) +MODEL_TYPES = tuple(conf.model_type for conf in MODEL_CONFIG_CLASSES) + + +@dataclass +class ModelArguments: + """ + Arguments pertaining to which model/config/tokenizer we are going to fine-tune, or train from scratch. + """ + + model_name_or_path: Optional[str] = field( + default=None, + metadata={ + "help": "The model checkpoint for weights initialization." + "Don't set if you want to train a model from scratch." + }, + ) + model_type: Optional[str] = field( + default=None, + metadata={ + "help": "If training from scratch, pass a model type from the list: " + + ", ".join(MODEL_TYPES) + }, + ) + config_name: Optional[str] = field( + default=None, + metadata={ + "help": "Pretrained config name or path if not the same as model_name" + }, + ) + tokenizer_name: Optional[str] = field( + default=None, + metadata={ + "help": "Pretrained tokenizer name or path if not the same as model_name" + }, + ) + cache_dir: Optional[str] = field( + default=None, + metadata={ + "help": "Where do you want to store the pretrained models downloaded from s3" + }, + ) + use_fast_tokenizer: bool = field( + default=True, + metadata={ + "help": "Whether to use one of the fast tokenizer (backed by the tokenizers library) or not." + }, + ) + dtype: Optional[str] = field( + default="float32", + metadata={ + "help": "Floating-point format in which the model weights should be initialized and trained. Choose one of `[float32, float16, bfloat16]`." + }, + ) + + +@dataclass +class DataTrainingArguments: + """ + Arguments pertaining to what data we are going to input our model for training and eval. + """ + + dataset_name: Optional[str] = field( + default=None, + metadata={"help": "The name of the dataset to use (via the datasets library)."}, + ) + dataset_config_name: Optional[str] = field( + default=None, + metadata={ + "help": "The configuration name of the dataset to use (via the datasets library)." + }, + ) + train_file: Optional[str] = field( + default=None, metadata={"help": "The input training data file (a text file)."} + ) + validation_file: Optional[str] = field( + default=None, + metadata={ + "help": "An optional input evaluation data file to evaluate the perplexity on (a text file)." + }, + ) + train_ref_file: Optional[str] = field( + default=None, + metadata={ + "help": "An optional input train ref data file for whole word masking in Chinese." + }, + ) + validation_ref_file: Optional[str] = field( + default=None, + metadata={ + "help": "An optional input validation ref data file for whole word masking in Chinese." + }, + ) + overwrite_cache: bool = field( + default=False, + metadata={"help": "Overwrite the cached training and evaluation sets"}, + ) + validation_split_percentage: Optional[int] = field( + default=5, + metadata={ + "help": "The percentage of the train set used as validation set in case there's no validation split" + }, + ) + max_seq_length: Optional[int] = field( + default=None, + metadata={ + "help": "The maximum total input sequence length after tokenization. Sequences longer " + "than this will be truncated. Default to the max input length of the model." + }, + ) + preprocessing_num_workers: Optional[int] = field( + default=None, + metadata={"help": "The number of processes to use for the preprocessing."}, + ) + mlm_probability: float = field( + default=0.15, + metadata={"help": "Ratio of tokens to mask for masked language modeling loss"}, + ) + pad_to_max_length: bool = field( + default=False, + metadata={ + "help": "Whether to pad all samples to `max_seq_length`. " + "If False, will pad the samples dynamically when batching to the maximum length in the batch." + }, + ) + line_by_line: bool = field( + default=False, + metadata={ + "help": "Whether distinct lines of text in the dataset are to be handled as distinct sequences." + }, + ) + + def __post_init__(self): + if ( + self.dataset_name is None + and self.train_file is None + and self.validation_file is None + ): + raise ValueError( + "Need either a dataset name or a training/validation file." + ) + else: + if self.train_file is not None: + extension = self.train_file.split(".")[-1] + assert extension in [ + "csv", + "json", + "txt", + ], "`train_file` should be a csv, a json or a txt file." + if self.validation_file is not None: + extension = self.validation_file.split(".")[-1] + assert extension in [ + "csv", + "json", + "txt", + ], "`validation_file` should be a csv, a json or a txt file." + + +@flax.struct.dataclass +class FlaxDataCollatorForLanguageModeling: + """ + Data collator used for language modeling. Inputs are dynamically padded to the maximum length of a batch if they + are not all of the same length. + + Args: + tokenizer (:class:`~transformers.PreTrainedTokenizer` or :class:`~transformers.PreTrainedTokenizerFast`): + The tokenizer used for encoding the data. + mlm_probability (:obj:`float`, `optional`, defaults to 0.15): + The probability with which to (randomly) mask tokens in the input. + + .. note:: + + For best performance, this data collator should be used with a dataset having items that are dictionaries or + BatchEncoding, with the :obj:`"special_tokens_mask"` key, as returned by a + :class:`~transformers.PreTrainedTokenizer` or a :class:`~transformers.PreTrainedTokenizerFast` with the + argument :obj:`return_special_tokens_mask=True`. + """ + + tokenizer: PreTrainedTokenizerBase + mlm_probability: float = 0.15 + + def __post_init__(self): + if self.tokenizer.mask_token is None: + raise ValueError( + "This tokenizer does not have a mask token which is necessary for masked language modeling. " + "You should pass `mlm=False` to train on causal language modeling instead." + ) + + def __call__( + self, examples: List[Dict[str, np.ndarray]], pad_to_multiple_of: int + ) -> Dict[str, np.ndarray]: + # Handle dict or lists with proper padding and conversion to tensor. + batch = self.tokenizer.pad( + examples, + pad_to_multiple_of=pad_to_multiple_of, + return_tensors=TensorType.NUMPY, + ) + + # If special token mask has been preprocessed, pop it from the dict. + special_tokens_mask = batch.pop("special_tokens_mask", None) + + batch["input_ids"], batch["labels"] = self.mask_tokens( + batch["input_ids"], special_tokens_mask=special_tokens_mask + ) + return batch + + def mask_tokens( + self, inputs: np.ndarray, special_tokens_mask: Optional[np.ndarray] + ) -> Tuple[jnp.ndarray, jnp.ndarray]: + """ + Prepare masked tokens inputs/labels for masked language modeling: 80% MASK, 10% random, 10% original. + """ + labels = inputs.copy() + # We sample a few tokens in each sequence for MLM training (with probability `self.mlm_probability`) + probability_matrix = np.full(labels.shape, self.mlm_probability) + special_tokens_mask = special_tokens_mask.astype("bool") + + probability_matrix[special_tokens_mask] = 0.0 + masked_indices = np.random.binomial(1, probability_matrix).astype("bool") + labels[~masked_indices] = -100 # We only compute loss on masked tokens + + # 80% of the time, we replace masked input tokens with tokenizer.mask_token ([MASK]) + indices_replaced = ( + np.random.binomial(1, np.full(labels.shape, 0.8)).astype("bool") + & masked_indices + ) + inputs[indices_replaced] = self.tokenizer.convert_tokens_to_ids( + self.tokenizer.mask_token + ) + + # 10% of the time, we replace masked input tokens with random word + indices_random = np.random.binomial(1, np.full(labels.shape, 0.5)).astype( + "bool" + ) + indices_random &= masked_indices & ~indices_replaced + + random_words = np.random.randint( + self.tokenizer.vocab_size, size=labels.shape, dtype="i4" + ) + inputs[indices_random] = random_words[indices_random] + + # The rest of the time (10% of the time) we keep the masked input tokens unchanged + return inputs, labels + + +def generate_batch_splits(samples_idx: jnp.ndarray, batch_size: int) -> jnp.ndarray: + num_samples = len(samples_idx) + samples_to_remove = num_samples % batch_size + + if samples_to_remove != 0: + samples_idx = samples_idx[:-samples_to_remove] + sections_split = num_samples // batch_size + batch_idx = np.split(samples_idx, sections_split) + return batch_idx + + +def write_train_metric(summary_writer, train_metrics, train_time, step): + summary_writer.scalar("train_time", train_time, step) + + train_metrics = get_metrics(train_metrics) + for key, vals in train_metrics.items(): + tag = f"train_{key}" + for i, val in enumerate(vals): + summary_writer.scalar(tag, val, step - len(vals) + i + 1) + + +def write_eval_metric(summary_writer, eval_metrics, step): + for metric_name, value in eval_metrics.items(): + summary_writer.scalar(f"eval_{metric_name}", value, step) + + +if __name__ == "__main__": + # See all possible arguments in src/transformers/training_args.py + # or by passing the --help flag to this script. + # We now keep distinct sets of args, for a cleaner separation of concerns. + + parser = HfArgumentParser( + (ModelArguments, DataTrainingArguments, TrainingArguments) + ) + if len(sys.argv) == 2 and sys.argv[1].endswith(".json"): + # If we pass only one argument to the script and it's the path to a json file, + # let's parse it to get our arguments. + model_args, data_args, training_args = parser.parse_json_file( + json_file=os.path.abspath(sys.argv[1]) + ) + else: + model_args, data_args, training_args = parser.parse_args_into_dataclasses() + + if ( + os.path.exists(training_args.output_dir) + and os.listdir(training_args.output_dir) + and training_args.do_train + and not training_args.overwrite_output_dir + ): + raise ValueError( + f"Output directory ({training_args.output_dir}) already exists and is not empty." + "Use --overwrite_output_dir to overcome." + ) + + # Setup logging + logging.basicConfig( + format="%(asctime)s - %(levelname)s - %(name)s - %(message)s", + level="NOTSET", + datefmt="[%X]", + ) + + # Log on each process the small summary: + logger = logging.getLogger(__name__) + + # Set the verbosity to info of the Transformers logger (on main process only): + logger.info(f"Training/evaluation parameters {training_args}") + + # Set seed before initializing model. + set_seed(training_args.seed) + + # Get the datasets: you can either provide your own CSV/JSON/TXT training and evaluation files (see below) + # or just provide the name of one of the public datasets available on the hub at https://huggingface.co/datasets/ + # (the dataset will be downloaded automatically from the datasets Hub). + # + # For CSV/JSON files, this script will use the column called 'text' or the first column if no column called + # 'text' is found. You can easily tweak this behavior (see below). + # + # In distributed training, the load_dataset function guarantees that only one local process can concurrently + # download the dataset. + if data_args.dataset_name is not None: + # Downloading and loading a dataset from the hub. + datasets = load_dataset( + data_args.dataset_name, + data_args.dataset_config_name, + cache_dir=model_args.cache_dir, + ) + + if "validation" not in datasets.keys(): + datasets["validation"] = load_dataset( + data_args.dataset_name, + data_args.dataset_config_name, + split=f"train[:{data_args.validation_split_percentage}%]", + cache_dir=model_args.cache_dir, + ) + datasets["train"] = load_dataset( + data_args.dataset_name, + data_args.dataset_config_name, + split=f"train[{data_args.validation_split_percentage}%:]", + cache_dir=model_args.cache_dir, + ) + else: + data_files = {} + if data_args.train_file is not None: + data_files["train"] = data_args.train_file + if data_args.validation_file is not None: + data_files["validation"] = data_args.validation_file + extension = data_args.train_file.split(".")[-1] + if extension == "txt": + extension = "text" + datasets = load_dataset( + extension, data_files=data_files, cache_dir=model_args.cache_dir + ) + # See more about loading any type of standard or custom dataset (from files, python dict, pandas DataFrame, etc) at + # https://huggingface.co/docs/datasets/loading_datasets.html. + + # Load pretrained model and tokenizer + + # Distributed training: + # The .from_pretrained methods guarantee that only one local process can concurrently + # download model & vocab. + if model_args.config_name: + config = AutoConfig.from_pretrained( + model_args.config_name, cache_dir=model_args.cache_dir + ) + elif model_args.model_name_or_path: + config = AutoConfig.from_pretrained( + model_args.model_name_or_path, cache_dir=model_args.cache_dir + ) + else: + config = CONFIG_MAPPING[model_args.model_type]() + logger.warning("You are instantiating a new config instance from scratch.") + + if model_args.tokenizer_name: + tokenizer = AutoTokenizer.from_pretrained( + model_args.tokenizer_name, + cache_dir=model_args.cache_dir, + use_fast=model_args.use_fast_tokenizer, + ) + elif model_args.model_name_or_path: + tokenizer = AutoTokenizer.from_pretrained( + model_args.model_name_or_path, + cache_dir=model_args.cache_dir, + use_fast=model_args.use_fast_tokenizer, + ) + else: + raise ValueError( + "You are instantiating a new tokenizer from scratch. This is not supported by this script." + "You can do it from another script, save it, and load it from here, using --tokenizer_name." + ) + + # Preprocessing the datasets. + # First we tokenize all the texts. + if training_args.do_train: + column_names = datasets["train"].column_names + else: + column_names = datasets["validation"].column_names + text_column_name = "text" if "text" in column_names else column_names[0] + + max_seq_length = min(data_args.max_seq_length, tokenizer.model_max_length) + + if data_args.line_by_line: + # When using line_by_line, we just tokenize each nonempty line. + padding = "max_length" if data_args.pad_to_max_length else False + + def tokenize_function(examples): + # Remove empty lines + examples = [ + line for line in examples if len(line) > 0 and not line.isspace() + ] + return tokenizer( + examples, + return_special_tokens_mask=True, + padding=padding, + truncation=True, + max_length=max_seq_length, + ) + + tokenized_datasets = datasets.map( + tokenize_function, + input_columns=[text_column_name], + batched=True, + num_proc=data_args.preprocessing_num_workers, + remove_columns=column_names, + load_from_cache_file=not data_args.overwrite_cache, + ) + + else: + # Otherwise, we tokenize every text, then concatenate them together before splitting them in smaller parts. + # We use `return_special_tokens_mask=True` because DataCollatorForLanguageModeling (see below) is more + # efficient when it receives the `special_tokens_mask`. + def tokenize_function(examples): + return tokenizer( + examples[text_column_name], return_special_tokens_mask=True + ) + + tokenized_datasets = datasets.map( + tokenize_function, + batched=True, + num_proc=data_args.preprocessing_num_workers, + remove_columns=column_names, + load_from_cache_file=not data_args.overwrite_cache, + ) + + # Main data processing function that will concatenate all texts from our dataset and generate chunks of + # max_seq_length. + def group_texts(examples): + # Concatenate all texts. + concatenated_examples = {k: sum(examples[k], []) for k in examples.keys()} + total_length = len(concatenated_examples[list(examples.keys())[0]]) + # We drop the small remainder, we could add padding if the model supported it instead of this drop, you can + # customize this part to your needs. + total_length = (total_length // max_seq_length) * max_seq_length + # Split by chunks of max_len. + result = { + k: [ + t[i : i + max_seq_length] + for i in range(0, total_length, max_seq_length) + ] + for k, t in concatenated_examples.items() + } + return result + + # Note that with `batched=True`, this map processes 1,000 texts together, so group_texts throws away a + # remainder for each of those groups of 1,000 texts. You can adjust that batch_size here but a higher value + # might be slower to preprocess. + # + # To speed up this part, we use multiprocessing. See the documentation of the map method for more information: + # https://huggingface.co/docs/datasets/package_reference/main_classes.html#datasets.Dataset.map + tokenized_datasets = tokenized_datasets.map( + group_texts, + batched=True, + num_proc=data_args.preprocessing_num_workers, + load_from_cache_file=not data_args.overwrite_cache, + ) + + # Enable tensorboard only on the master node + has_tensorboard = is_tensorboard_available() + if has_tensorboard and jax.process_index() == 0: + try: + # Enable Weight&Biases + import wandb + + wandb.init( + entity="wandb", + project="hf-flax-bertin-roberta-es", + sync_tensorboard=True, + ) + wandb.config.update(training_args) + wandb.config.update(model_args) + wandb.config.update(data_args) + from flax.metrics.tensorboard import SummaryWriter + + summary_writer = SummaryWriter(log_dir=Path(training_args.output_dir)) + except ImportError as ie: + has_tensorboard = False + logger.warning( + f"Unable to display metrics through TensorBoard because some package are not installed: {ie}" + ) + else: + logger.warning( + "Unable to display metrics through TensorBoard because the package is not installed: " + "Please run pip install tensorboard to enable." + ) + + # Data collator + # This one will take care of randomly masking the tokens. + data_collator = FlaxDataCollatorForLanguageModeling( + tokenizer=tokenizer, mlm_probability=data_args.mlm_probability + ) + + # Initialize our training + rng = jax.random.PRNGKey(training_args.seed) + dropout_rngs = jax.random.split(rng, jax.local_device_count()) + + if model_args.model_name_or_path: + model = FlaxAutoModelForMaskedLM.from_pretrained( + model_args.model_name_or_path, + config=config, + seed=training_args.seed, + dtype=getattr(jnp, model_args.dtype), + ) + else: + model = FlaxAutoModelForMaskedLM.from_config( + config, seed=training_args.seed, dtype=getattr(jnp, model_args.dtype) + ) + + # Store some constant + num_epochs = int(training_args.num_train_epochs) + train_batch_size = ( + int(training_args.per_device_train_batch_size) * jax.device_count() + ) + eval_batch_size = int(training_args.per_device_eval_batch_size) * jax.device_count() + + num_train_steps = len(tokenized_datasets["train"]) // train_batch_size * num_epochs + + # Create learning rate schedule + warmup_fn = optax.linear_schedule( + init_value=0.0, + end_value=training_args.learning_rate, + transition_steps=training_args.warmup_steps, + ) + decay_fn = optax.linear_schedule( + init_value=training_args.learning_rate, + end_value=0, + transition_steps=num_train_steps - training_args.warmup_steps, + ) + linear_decay_lr_schedule_fn = optax.join_schedules( + schedules=[warmup_fn, decay_fn], boundaries=[training_args.warmup_steps] + ) + + # We use Optax's "masking" functionality to not apply weight decay + # to bias and LayerNorm scale parameters. decay_mask_fn returns a + # mask boolean with the same structure as the parameters. + # The mask is True for parameters that should be decayed. + # Note that this mask is specifically adapted for FlaxBERT-like models. + # For other models, one should correct the layer norm parameter naming + # accordingly. + def decay_mask_fn(params): + flat_params = traverse_util.flatten_dict(params) + flat_mask = { + path: (path[-1] != "bias" and path[-2:] != ("LayerNorm", "scale")) + for path in flat_params + } + return traverse_util.unflatten_dict(flat_mask) + + # create adam optimizer + if training_args.adafactor: + # We use the default parameters here to initialize adafactor, + # For more details about the parameters please check https://github.com/deepmind/optax/blob/ed02befef9bf81cbbf236be3d2b0e032e9ed4a40/optax/_src/alias.py#L74 + optimizer = optax.adafactor( + learning_rate=linear_decay_lr_schedule_fn, + ) + else: + optimizer = optax.adamw( + learning_rate=linear_decay_lr_schedule_fn, + b1=training_args.adam_beta1, + b2=training_args.adam_beta2, + eps=training_args.adam_epsilon, + weight_decay=training_args.weight_decay, + mask=decay_mask_fn, + ) + + # Setup train state + state = train_state.TrainState.create( + apply_fn=model.__call__, params=model.params, tx=optimizer + ) + + # Define gradient update step fn + def train_step(state, batch, dropout_rng): + dropout_rng, new_dropout_rng = jax.random.split(dropout_rng) + + def loss_fn(params): + labels = batch.pop("labels") + + logits = state.apply_fn( + **batch, params=params, dropout_rng=dropout_rng, train=True + )[0] + + # compute loss, ignore padded input tokens + label_mask = jnp.where(labels > 0, 1.0, 0.0) + loss = ( + optax.softmax_cross_entropy(logits, onehot(labels, logits.shape[-1])) + * label_mask + ) + + # take average + loss = loss.sum() / label_mask.sum() + + return loss + + grad_fn = jax.value_and_grad(loss_fn) + loss, grad = grad_fn(state.params) + grad = jax.lax.pmean(grad, "batch") + new_state = state.apply_gradients(grads=grad) + + metrics = jax.lax.pmean( + {"loss": loss, "learning_rate": linear_decay_lr_schedule_fn(state.step)}, + axis_name="batch", + ) + + return new_state, metrics, new_dropout_rng + + # Create parallel version of the train step + p_train_step = jax.pmap(train_step, "batch", donate_argnums=(0,)) + + # Define eval fn + def eval_step(params, batch): + labels = batch.pop("labels") + + logits = model(**batch, params=params, train=False)[0] + + # compute loss, ignore padded input tokens + label_mask = jnp.where(labels > 0, 1.0, 0.0) + loss = ( + optax.softmax_cross_entropy(logits, onehot(labels, logits.shape[-1])) + * label_mask + ) + + # compute accuracy + accuracy = jnp.equal(jnp.argmax(logits, axis=-1), labels) * label_mask + + # summarize metrics + metrics = { + "loss": loss.sum(), + "accuracy": accuracy.sum(), + "normalizer": label_mask.sum(), + } + metrics = jax.lax.psum(metrics, axis_name="batch") + + return metrics + + p_eval_step = jax.pmap(eval_step, "batch", donate_argnums=(0,)) + + # Replicate the train state on each device + state = jax_utils.replicate(state) + + train_time = 0 + epochs = tqdm(range(num_epochs), desc=f"Epoch ... (1/{num_epochs})", position=0) + for epoch in epochs: + # ======================== Training ================================ + train_start = time.time() + train_metrics = [] + + # Create sampling rng + rng, input_rng = jax.random.split(rng) + + # Generate an epoch by shuffling sampling indices from the train dataset + num_train_samples = len(tokenized_datasets["train"]) + train_samples_idx = jax.random.permutation( + input_rng, jnp.arange(num_train_samples) + ) + train_batch_idx = generate_batch_splits(train_samples_idx, train_batch_size) + + # Gather the indexes for creating the batch and do a training step + for step, batch_idx in enumerate( + tqdm(train_batch_idx, desc="Training...", position=1) + ): + samples = [tokenized_datasets["train"][int(idx)] for idx in batch_idx] + model_inputs = data_collator(samples, pad_to_multiple_of=16) + + # Model forward + model_inputs = shard(model_inputs.data) + state, train_metric, dropout_rngs = p_train_step( + state, model_inputs, dropout_rngs + ) + train_metrics.append(train_metric) + + cur_step = epoch * (num_train_samples // train_batch_size) + step + + if cur_step % training_args.logging_steps == 0 and cur_step > 0: + # Save metrics + train_metric = jax_utils.unreplicate(train_metric) + train_time += time.time() - train_start + if has_tensorboard and jax.process_index() == 0: + write_train_metric( + summary_writer, train_metrics, train_time, cur_step + ) + + epochs.write( + f"Step... ({cur_step} | Loss: {train_metric['loss']}, Learning Rate: {train_metric['learning_rate']})" + ) + + train_metrics = [] + + if cur_step % training_args.eval_steps == 0 and cur_step > 0: + # ======================== Evaluating ============================== + num_eval_samples = len(tokenized_datasets["validation"]) + eval_samples_idx = jnp.arange(num_eval_samples) + eval_batch_idx = generate_batch_splits( + eval_samples_idx, eval_batch_size + ) + + eval_metrics = [] + for i, batch_idx in enumerate( + tqdm(eval_batch_idx, desc="Evaluating ...", position=2) + ): + samples = [ + tokenized_datasets["validation"][int(idx)] for idx in batch_idx + ] + model_inputs = data_collator(samples, pad_to_multiple_of=16) + + # Model forward + model_inputs = shard(model_inputs.data) + metrics = p_eval_step(state.params, model_inputs) + eval_metrics.append(metrics) + + # normalize eval metrics + eval_metrics = get_metrics(eval_metrics) + eval_metrics = jax.tree_map(jnp.sum, eval_metrics) + eval_normalizer = eval_metrics.pop("normalizer") + eval_metrics = jax.tree_map(lambda x: x / eval_normalizer, eval_metrics) + + # Update progress bar + epochs.desc = f"Step... ({cur_step} | Loss: {eval_metrics['loss']}, Acc: {eval_metrics['accuracy']})" + + # Save metrics + if has_tensorboard and jax.process_index() == 0: + cur_step = epoch * ( + len(tokenized_datasets["train"]) // train_batch_size + ) + write_eval_metric(summary_writer, eval_metrics, cur_step) + + if cur_step % training_args.save_steps == 0 and cur_step > 0: + # save checkpoint after each epoch and push checkpoint to the hub + if jax.process_index() == 0: + params = jax.device_get(jax.tree_map(lambda x: x[0], state.params)) + model.save_pretrained( + training_args.output_dir, + params=params, + push_to_hub=training_args.push_to_hub, + commit_message=f"Saving weights and logs of step {cur_step}", + ) diff --git a/data_tooling/bertin/run_mlm_flax_stream.py b/data_tooling/bertin/run_mlm_flax_stream.py new file mode 100644 index 0000000..a33eaae --- /dev/null +++ b/data_tooling/bertin/run_mlm_flax_stream.py @@ -0,0 +1,999 @@ +#!/usr/bin/env python +# coding=utf-8 +# Copyright 2021 The HuggingFace Team All rights reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +""" +Fine-tuning the library models for masked language modeling (BERT, ALBERT, RoBERTa...) with whole word masking on a +text file or a dataset. + +Here is the full list of checkpoints on the hub that can be fine-tuned by this script: +https://huggingface.co/models?filter=masked-lm +""" +import json +import logging +import os +import shutil +import sys +import tempfile +import time +from collections import defaultdict +from dataclasses import dataclass, field +from pathlib import Path +from typing import Dict, List, Optional, Tuple + +import datasets +import flax +import jax +import jax.numpy as jnp + +# You can also adapt this script on your own masked language modeling task. Pointers for this are left as comments. +import joblib +import kenlm # pip install https://github.com/kpu/kenlm/archive/master.zip +import numpy as np +import optax +from datasets import load_dataset +from flax import jax_utils, traverse_util +from flax.serialization import from_bytes, to_bytes +from flax.training import train_state +from flax.training.common_utils import get_metrics, onehot, shard +from tqdm import tqdm +from transformers import ( + CONFIG_MAPPING, + FLAX_MODEL_FOR_MASKED_LM_MAPPING, + AutoConfig, + AutoTokenizer, + FlaxAutoModelForMaskedLM, + FlaxRobertaForMaskedLM, + HfArgumentParser, + PreTrainedTokenizerBase, + RobertaForMaskedLM, + TensorType, + TrainingArguments, + is_tensorboard_available, + set_seed, +) + +if datasets.__version__ <= "1.8.0": + raise ValueError( + "Make sure to upgrade `datasets` to a version >= 1.9.0 to use dataset streaming" + ) + + +MODEL_CONFIG_CLASSES = list(FLAX_MODEL_FOR_MASKED_LM_MAPPING.keys()) +MODEL_TYPES = tuple(conf.model_type for conf in MODEL_CONFIG_CLASSES) + + +@dataclass +class ModelArguments: + """ + Arguments pertaining to which model/config/tokenizer we are going to fine-tune, or train from scratch. + """ + + model_name_or_path: Optional[str] = field( + default=None, + metadata={ + "help": "The model checkpoint for weights initialization." + "Don't set if you want to train a model from scratch." + }, + ) + model_type: Optional[str] = field( + default=None, + metadata={ + "help": "If training from scratch, pass a model type from the list: " + + ", ".join(MODEL_TYPES) + }, + ) + config_name: Optional[str] = field( + default=None, + metadata={ + "help": "Pretrained config name or path if not the same as model_name" + }, + ) + tokenizer_name: Optional[str] = field( + default=None, + metadata={ + "help": "Pretrained tokenizer name or path if not the same as model_name" + }, + ) + cache_dir: Optional[str] = field( + default=None, + metadata={ + "help": "Where do you want to store the pretrained models downloaded from s3" + }, + ) + use_fast_tokenizer: bool = field( + default=True, + metadata={ + "help": "Whether to use one of the fast tokenizer (backed by the tokenizers library) or not." + }, + ) + dtype: Optional[str] = field( + default="float32", + metadata={ + "help": "Floating-point format in which the model weights should be initialized and trained. Choose one of `[float32, float16, bfloat16]`." + }, + ) + + +@dataclass +class DataTrainingArguments: + """ + Arguments pertaining to what data we are going to input our model for training and eval. + """ + + dataset_name: Optional[str] = field( + default=None, + metadata={"help": "The name of the dataset to use (via the datasets library)."}, + ) + dataset_config_name: Optional[str] = field( + default=None, + metadata={ + "help": "The configuration name of the dataset to use (via the datasets library)." + }, + ) + train_file: Optional[str] = field( + default=None, metadata={"help": "The input training data file (a text file)."} + ) + validation_file: Optional[str] = field( + default=None, + metadata={ + "help": "An optional input evaluation data file to evaluate the perplexity on (a text file)." + }, + ) + train_ref_file: Optional[str] = field( + default=None, + metadata={ + "help": "An optional input train ref data file for whole word masking in Chinese." + }, + ) + validation_ref_file: Optional[str] = field( + default=None, + metadata={ + "help": "An optional input validation ref data file for whole word masking in Chinese." + }, + ) + overwrite_cache: bool = field( + default=False, + metadata={"help": "Overwrite the cached training and evaluation sets"}, + ) + validation_split_percentage: Optional[int] = field( + default=5, + metadata={ + "help": "The percentage of the train set used as validation set in case there's no validation split" + }, + ) + max_seq_length: Optional[int] = field( + default=None, + metadata={ + "help": "The maximum total input sequence length after tokenization. Sequences longer " + "than this will be truncated. Default to the max input length of the model." + }, + ) + preprocessing_num_workers: Optional[int] = field( + default=None, + metadata={"help": "The number of processes to use for the preprocessing."}, + ) + mlm_probability: float = field( + default=0.15, + metadata={"help": "Ratio of tokens to mask for masked language modeling loss"}, + ) + pad_to_max_length: bool = field( + default=False, + metadata={ + "help": "Whether to pad all samples to `max_seq_length`. " + "If False, will pad the samples dynamically when batching to the maximum length in the batch." + }, + ) + line_by_line: bool = field( + default=False, + metadata={ + "help": "Whether distinct lines of text in the dataset are to be handled as distinct sequences." + }, + ) + text_column_name: str = field( + default="text", + metadata={"help": "The name of the column to retrieve the training text."}, + ) + shuffle_buffer_size: int = field( + default=10000, + metadata={"help": "The number of examples to pre-load for shuffling."}, + ) + num_train_steps: int = field( + default=50000, metadata={"help": "The number of training steps."} + ) + num_eval_samples: int = field( + default=50000, + metadata={"help": "The number of samples to be used for evaluation"}, + ) + + def __post_init__(self): + if ( + self.dataset_name is None + and self.train_file is None + and self.validation_file is None + ): + raise ValueError( + "Need either a dataset name or a training/validation file." + ) + else: + if self.train_file is not None: + extension = self.train_file.split(".")[-1] + assert extension in [ + "csv", + "json", + "jsonl", + "txt", + "gz", + ], "`train_file` should be a csv, a json (lines) or a txt file." + if self.validation_file is not None: + extension = self.validation_file.split(".")[-1] + assert extension in [ + "csv", + "json", + "jsonl", + "txt", + "gz", + ], "`validation_file` should be a csv, a json (lines) or a txt file." + + +@flax.struct.dataclass +class FlaxDataCollatorForLanguageModeling: + """ + Data collator used for language modeling. Inputs are dynamically padded to the maximum length of a batch if they + are not all of the same length. + + Args: + tokenizer (:class:`~transformers.PreTrainedTokenizer` or :class:`~transformers.PreTrainedTokenizerFast`): + The tokenizer used for encoding the data. + mlm_probability (:obj:`float`, `optional`, defaults to 0.15): + The probability with which to (randomly) mask tokens in the input. + + .. note:: + + For best performance, this data collator should be used with a dataset having items that are dictionaries or + BatchEncoding, with the :obj:`"special_tokens_mask"` key, as returned by a + :class:`~transformers.PreTrainedTokenizer` or a :class:`~transformers.PreTrainedTokenizerFast` with the + argument :obj:`return_special_tokens_mask=True`. + """ + + tokenizer: PreTrainedTokenizerBase + mlm_probability: float = 0.15 + + def __post_init__(self): + if self.tokenizer.mask_token is None: + raise ValueError( + "This tokenizer does not have a mask token which is necessary for masked language modeling. " + "You should pass `mlm=False` to train on causal language modeling instead." + ) + + def __call__( + self, examples: List[Dict[str, np.ndarray]], pad_to_multiple_of: int + ) -> Dict[str, np.ndarray]: + # Handle dict or lists with proper padding and conversion to tensor. + batch = self.tokenizer.pad( + examples, + pad_to_multiple_of=pad_to_multiple_of, + return_tensors=TensorType.NUMPY, + ) + + # If special token mask has been preprocessed, pop it from the dict. + special_tokens_mask = batch.pop("special_tokens_mask", None) + + batch["input_ids"], batch["labels"] = self.mask_tokens( + batch["input_ids"], special_tokens_mask=special_tokens_mask + ) + return batch + + def mask_tokens( + self, inputs: np.ndarray, special_tokens_mask: Optional[np.ndarray] + ) -> Tuple[jnp.ndarray, jnp.ndarray]: + """ + Prepare masked tokens inputs/labels for masked language modeling: 80% MASK, 10% random, 10% original. + """ + labels = inputs.copy() + # We sample a few tokens in each sequence for MLM training (with probability `self.mlm_probability`) + probability_matrix = np.full(labels.shape, self.mlm_probability) + special_tokens_mask = special_tokens_mask.astype("bool") + + probability_matrix[special_tokens_mask] = 0.0 + masked_indices = np.random.binomial(1, probability_matrix).astype("bool") + labels[~masked_indices] = -100 # We only compute loss on masked tokens + + # 80% of the time, we replace masked input tokens with tokenizer.mask_token ([MASK]) + indices_replaced = ( + np.random.binomial(1, np.full(labels.shape, 0.8)).astype("bool") + & masked_indices + ) + inputs[indices_replaced] = self.tokenizer.convert_tokens_to_ids( + self.tokenizer.mask_token + ) + + # 10% of the time, we replace masked input tokens with random word + indices_random = np.random.binomial(1, np.full(labels.shape, 0.5)).astype( + "bool" + ) + indices_random &= masked_indices & ~indices_replaced + + random_words = np.random.randint( + self.tokenizer.vocab_size, size=labels.shape, dtype="i4" + ) + inputs[indices_random] = random_words[indices_random] + + # The rest of the time (10% of the time) we keep the masked input tokens unchanged + return inputs, labels + + +@dataclass +class SamplingArguments: + """ + Arguments pertaining to how to perform sampling of the dataset. + """ + + perplexity_model: Optional[str] = field( + default="./es.arpa.bin", + metadata={"help": "Path to KenLM model to use to get perplexity values."}, + ) + sampling_method: Optional[str] = field( + default=None, + metadata={ + "help": "Sample using a 'step' or 'gaussian' perplexity function per document, or 'random'." + }, + ) + sampling_factor: Optional[float] = field( + default=None, + metadata={ + "help": "Sampling factor. Integers for step function, decimals for gaussian." + }, + ) + boundaries: Optional[str] = field( + default="536394.99320948,662247.50212365,919250.87225178", + metadata={"help": "Quartile boundaries"}, + ) + + def __post_init__(self): + self.boundaries = [float(q.strip()) for q in self.boundaries.split(",")] + + +def generate_batch_splits(samples_idx: jnp.ndarray, batch_size: int) -> jnp.ndarray: + num_samples = len(samples_idx) + samples_to_remove = num_samples % batch_size + + if samples_to_remove != 0: + samples_idx = samples_idx[:-samples_to_remove] + sections_split = num_samples // batch_size + batch_idx = np.split(samples_idx, sections_split) + return batch_idx + + +def advance_iter_and_group_samples(train_iterator, num_samples, max_seq_length): + """ + The training iterator is advanced so that after groupifying the samples, + `num_samples` of length `max_seq_length` are returned. + """ + num_total_tokens = max_seq_length * num_samples + samples = defaultdict(list) + + i = 0 + while i < num_total_tokens: + tokenized_samples = next(train_iterator) + i += len(tokenized_samples["input_ids"]) + + # concatenate tokenized samples to list + samples = { + k: samples[k] + tokenized_samples[k] for k in tokenized_samples.keys() + } + + # Concatenated tokens are split to lists of length `max_seq_length`. + # Note that remainedr of % max_seq_length are thrown away. + def group_texts(examples): + result = { + k: [ + t[i : i + max_seq_length] + for i in range(0, num_total_tokens, max_seq_length) + ] + for k, t in examples.items() + } + return result + + grouped_samples = group_texts(samples) + return grouped_samples + + +def write_train_metric(summary_writer, train_metrics, train_time, step): + summary_writer.scalar("train_time", train_time, step) + + train_metrics = get_metrics(train_metrics) + for key, vals in train_metrics.items(): + tag = f"train_{key}" + for i, val in enumerate(vals): + summary_writer.scalar(tag, val, step - len(vals) + i + 1) + + +def write_eval_metric(summary_writer, eval_metrics, step): + for metric_name, value in eval_metrics.items(): + summary_writer.scalar(f"eval_{metric_name}", value, step) + + +def save_checkpoint_files(state, data_collator, training_args, save_dir): + unreplicated_state = jax_utils.unreplicate(state) + with open(os.path.join(save_dir, "optimizer_state.msgpack"), "wb") as f: + f.write(to_bytes(unreplicated_state.opt_state)) + joblib.dump(training_args, os.path.join(save_dir, "training_args.joblib")) + joblib.dump(data_collator, os.path.join(save_dir, "data_collator.joblib")) + with open(os.path.join(save_dir, "training_state.json"), "w") as f: + json.dump({"step": unreplicated_state.step.item()}, f) + + +def restore_checkpoint(save_dir, state): + logger.info(f"Restoring checkpoint from {save_dir}") + with open(os.path.join(save_dir, "flax_model.msgpack"), "rb") as f: + params = from_bytes(state.params, f.read()) + + with open(os.path.join(save_dir, "optimizer_state.msgpack"), "rb") as f: + opt_state = from_bytes(state.opt_state, f.read()) + + args = joblib.load(os.path.join(save_dir, "training_args.joblib")) + data_collator = joblib.load(os.path.join(save_dir, "data_collator.joblib")) + + with open(os.path.join(save_dir, "training_state.json"), "r") as f: + training_state = json.load(f) + step = training_state["step"] + + return params, opt_state, step, args, data_collator + + +def rotate_checkpoints(path, max_checkpoints=5): + paths = sorted(Path(path).iterdir(), key=os.path.getmtime)[::-1] + if len(paths) > max_checkpoints: + for path_to_delete in paths[max_checkpoints:]: + try: + shutil.rmtree(path_to_delete) + except OSError: + os.remove(path_to_delete) + + +def to_f32(t): + return jax.tree_map( + lambda x: x.astype(jnp.float32) if x.dtype == jnp.bfloat16 else x, t + ) + + +def convert(output_dir, destination_dir="./"): + shutil.copyfile( + Path(output_dir) / "flax_model.msgpack", + Path(destination_dir) / "flax_model.msgpack", + ) + shutil.copyfile( + Path(output_dir) / "config.json", Path(destination_dir) / "config.json" + ) + # Saving extra files from config.json and tokenizer.json files + tokenizer = AutoTokenizer.from_pretrained(destination_dir) + tokenizer.save_pretrained(destination_dir) + + # Temporary saving bfloat16 Flax model into float32 + tmp = tempfile.mkdtemp() + flax_model = FlaxRobertaForMaskedLM.from_pretrained(destination_dir) + flax_model.params = to_f32(flax_model.params) + flax_model.save_pretrained(tmp) + # Converting float32 Flax to PyTorch + model = RobertaForMaskedLM.from_pretrained(tmp, from_flax=True) + model.save_pretrained(destination_dir, save_config=False) + + +if __name__ == "__main__": + # See all possible arguments in src/transformers/training_args.py + # or by passing the --help flag to this script. + # We now keep distinct sets of args, for a cleaner separation of concerns. + + parser = HfArgumentParser( + (ModelArguments, DataTrainingArguments, TrainingArguments, SamplingArguments) + ) + if len(sys.argv) == 2 and sys.argv[1].endswith(".json"): + # If we pass only one argument to the script and it's the path to a json file, + # let's parse it to get our arguments. + model_args, data_args, training_args, sampling_args = parser.parse_json_file( + json_file=os.path.abspath(sys.argv[1]) + ) + else: + ( + model_args, + data_args, + training_args, + sampling_args, + ) = parser.parse_args_into_dataclasses() + + if ( + os.path.exists(training_args.output_dir) + and os.listdir(training_args.output_dir) + and training_args.do_train + and not training_args.overwrite_output_dir + ): + raise ValueError( + f"Output directory ({training_args.output_dir}) already exists and is not empty." + "Use --overwrite_output_dir to overcome." + ) + + # Setup logging + logging.basicConfig( + format="%(asctime)s - %(levelname)s - %(name)s - %(message)s", + level="INFO", + datefmt="[%X]", + ) + + # Log on each process the small summary: + logger = logging.getLogger(__name__) + logger.warning( + f"Process rank: {training_args.local_rank}, device: {training_args.device}, n_gpu: {training_args.n_gpu}" + + f"distributed training: {bool(training_args.local_rank != -1)}, 16-bits training: {training_args.fp16}" + ) + + # Set the verbosity to info of the Transformers logger (on main process only): + logger.info(f"Training/evaluation parameters {training_args}") + + # Set seed before initializing model. + set_seed(training_args.seed) + + # Get the datasets: you can either provide your own CSV/JSON/TXT training and evaluation files (see below) + # or just provide the name of one of the public datasets available on the hub at https://huggingface.co/datasets/ + # (the dataset will be downloaded automatically from the datasets Hub). + # + # For CSV/JSON files, this script will use the column called 'text' or the first column if no column called + # 'text' is found. You can easily tweak this behavior (see below). + if data_args.dataset_name is not None: + # Downloading and loading a dataset from the hub. + filepaths = {} + if data_args.train_file: + filepaths["train"] = data_args.train_file + if data_args.validation_file: + filepaths["validation"] = data_args.validation_file + try: + dataset = load_dataset( + data_args.dataset_name, + data_args.dataset_config_name, + cache_dir=model_args.cache_dir, + streaming=True, + split="train", + sampling_method=sampling_args.sampling_method, + sampling_factor=sampling_args.sampling_factor, + boundaries=sampling_args.boundaries, + perplexity_model=sampling_args.perplexity_model, + seed=training_args.seed, + data_files=filepaths, + ) + except Exception as exc: + logger.warning( + f"Unable to load local dataset with perplexity sampling support. Using huggingface.co/datasets/{data_args.dataset_name}: {exc}" + ) + dataset = load_dataset( + data_args.dataset_name, + data_args.dataset_config_name, + cache_dir=model_args.cache_dir, + streaming=True, + split="train", + ) + + if model_args.config_name: + config = AutoConfig.from_pretrained( + model_args.config_name, cache_dir=model_args.cache_dir + ) + elif model_args.model_name_or_path: + config = AutoConfig.from_pretrained( + model_args.model_name_or_path, cache_dir=model_args.cache_dir + ) + else: + config = CONFIG_MAPPING[model_args.model_type]() + logger.warning("You are instantiating a new config instance from scratch.") + + if model_args.tokenizer_name: + tokenizer = AutoTokenizer.from_pretrained( + model_args.tokenizer_name, + cache_dir=model_args.cache_dir, + use_fast=model_args.use_fast_tokenizer, + ) + elif model_args.model_name_or_path: + tokenizer = AutoTokenizer.from_pretrained( + model_args.model_name_or_path, + cache_dir=model_args.cache_dir, + use_fast=model_args.use_fast_tokenizer, + ) + else: + raise ValueError( + "You are instantiating a new tokenizer from scratch. This is not supported by this script." + "You can do it from another script, save it, and load it from here, using --tokenizer_name." + ) + + # Otherwise, we tokenize every text, then concatenate them together before splitting them in smaller parts. + # We use `return_special_tokens_mask=True` because DataCollatorForLanguageModeling (see below) is more + # efficient when it receives the `special_tokens_mask`. + def tokenize_function(examples): + return tokenizer( + examples[data_args.text_column_name], return_special_tokens_mask=True + ) + + tokenized_datasets = dataset.map( + tokenize_function, + batched=True, + ) + + shuffle_seed = training_args.seed + tokenized_datasets = tokenized_datasets.shuffle( + buffer_size=data_args.shuffle_buffer_size, seed=shuffle_seed + ) + + # Enable tensorboard only on the master node + has_tensorboard = is_tensorboard_available() + if has_tensorboard and jax.process_index() == 0: + try: + # Enable Weight&Biases + import wandb + + wandb.init( + entity="wandb", + project="hf-flax-bertin-roberta-es", + sync_tensorboard=True, + ) + wandb.config.update(training_args) + wandb.config.update(model_args) + wandb.config.update(data_args) + from flax.metrics.tensorboard import SummaryWriter + + summary_writer = SummaryWriter(log_dir=Path(training_args.output_dir)) + except ImportError as ie: + has_tensorboard = False + logger.warning( + f"Unable to display metrics through TensorBoard because some package are not installed: {ie}" + ) + else: + logger.warning( + "Unable to display metrics through TensorBoard because the package is not installed: " + "Please run pip install tensorboard to enable." + ) + + # Data collator + # This one will take care of randomly masking the tokens. + data_collator = FlaxDataCollatorForLanguageModeling( + tokenizer=tokenizer, mlm_probability=data_args.mlm_probability + ) + + # Initialize our training + rng = jax.random.PRNGKey(training_args.seed) + dropout_rngs = jax.random.split(rng, jax.local_device_count()) + + if model_args.model_name_or_path: + model = FlaxAutoModelForMaskedLM.from_pretrained( + model_args.model_name_or_path, + config=config, + seed=training_args.seed, + dtype=getattr(jnp, model_args.dtype), + ) + else: + model = FlaxAutoModelForMaskedLM.from_config( + config, seed=training_args.seed, dtype=getattr(jnp, model_args.dtype) + ) + + # Store some constant + num_epochs = int(training_args.num_train_epochs) + train_batch_size = ( + int(training_args.per_device_train_batch_size) * jax.device_count() + ) + eval_batch_size = int(training_args.per_device_eval_batch_size) * jax.device_count() + + # define number steps per stream epoch + num_train_steps = data_args.num_train_steps + + # Create learning rate schedule + warmup_fn = optax.linear_schedule( + init_value=0.0, + end_value=training_args.learning_rate, + transition_steps=training_args.warmup_steps, + ) + decay_fn = optax.linear_schedule( + init_value=training_args.learning_rate, + end_value=0, + transition_steps=num_train_steps - training_args.warmup_steps, + ) + linear_decay_lr_schedule_fn = optax.join_schedules( + schedules=[warmup_fn, decay_fn], boundaries=[training_args.warmup_steps] + ) + + # We use Optax's "masking" functionality to not apply weight decay + # to bias and LayerNorm scale parameters. decay_mask_fn returns a + # mask boolean with the same structure as the parameters. + # The mask is True for parameters that should be decayed. + # Note that this mask is specifically adapted for FlaxBERT-like models. + # For other models, one should correct the layer norm parameter naming + # accordingly. + def decay_mask_fn(params): + flat_params = traverse_util.flatten_dict(params) + flat_mask = { + path: (path[-1] != "bias" and path[-2:] != ("LayerNorm", "scale")) + for path in flat_params + } + return traverse_util.unflatten_dict(flat_mask) + + # create adam optimizer + adamw = optax.adamw( + learning_rate=linear_decay_lr_schedule_fn, + b1=training_args.adam_beta1, + b2=training_args.adam_beta2, + eps=training_args.adam_epsilon, + weight_decay=training_args.weight_decay, + mask=decay_mask_fn, + ) + + # Setup train state + state = train_state.TrainState.create( + apply_fn=model.__call__, params=model.params, tx=adamw + ) + saved_step = -1 + if model_args.model_name_or_path and "checkpoint" in model_args.model_name_or_path: + params, opt_state, saved_step, args, data_collator = restore_checkpoint( + model_args.model_name_or_path, state + ) + # Create learning rate schedule + warmup_fn = optax.linear_schedule( + init_value=0.0, + end_value=args.learning_rate, + transition_steps=args.warmup_steps, + ) + decay_fn = optax.linear_schedule( + init_value=args.learning_rate, + end_value=0, + transition_steps=data_args.num_train_steps - args.warmup_steps, + ) + linear_decay_lr_schedule_fn = optax.join_schedules( + schedules=[warmup_fn, decay_fn], boundaries=[args.warmup_steps] + ) + # create adam optimizer + adamw = optax.adamw( + learning_rate=linear_decay_lr_schedule_fn, + b1=training_args.adam_beta1, + b2=training_args.adam_beta2, + eps=training_args.adam_epsilon, + weight_decay=args.weight_decay, + mask=decay_mask_fn, + ) + state = train_state.TrainState( + step=saved_step, + apply_fn=model.__call__, + params=params, + tx=adamw, + opt_state=opt_state, + ) + # self.args = args + # data_collator = data_collator + # scheduler_fn = args.learning_rate + model.params = params + + # Define gradient update step fn + def train_step(state, batch, dropout_rng): + dropout_rng, new_dropout_rng = jax.random.split(dropout_rng) + + def loss_fn(params): + labels = batch.pop("labels") + + logits = state.apply_fn( + **batch, params=params, dropout_rng=dropout_rng, train=True + )[0] + + # compute loss, ignore padded input tokens + label_mask = jnp.where(labels > 0, 1.0, 0.0) + loss = ( + optax.softmax_cross_entropy(logits, onehot(labels, logits.shape[-1])) + * label_mask + ) + + # take average + loss = loss.sum() / label_mask.sum() + + return loss + + grad_fn = jax.value_and_grad(loss_fn) + loss, grad = grad_fn(state.params) + grad = jax.lax.pmean(grad, "batch") + new_state = state.apply_gradients(grads=grad) + + metrics = jax.lax.pmean( + {"loss": loss, "learning_rate": linear_decay_lr_schedule_fn(state.step)}, + axis_name="batch", + ) + + return new_state, metrics, new_dropout_rng + + # Create parallel version of the train step + p_train_step = jax.pmap(train_step, "batch", donate_argnums=(0,)) + + # Define eval fn + def eval_step(params, batch): + labels = batch.pop("labels") + + logits = model(**batch, params=params, train=False)[0] + + # compute loss, ignore padded input tokens + label_mask = jnp.where(labels > 0, 1.0, 0.0) + loss = ( + optax.softmax_cross_entropy(logits, onehot(labels, logits.shape[-1])) + * label_mask + ) + + # compute accuracy + accuracy = jnp.equal(jnp.argmax(logits, axis=-1), labels) * label_mask + + # summarize metrics + metrics = { + "loss": loss.sum(), + "accuracy": accuracy.sum(), + "normalizer": label_mask.sum(), + } + metrics = jax.lax.psum(metrics, axis_name="batch") + + return metrics + + p_eval_step = jax.pmap(eval_step, "batch", donate_argnums=(0,)) + + # Replicate the train state on each device + state = jax_utils.replicate(state) + + train_time = 0 + train_start = time.time() + train_metrics = [] + eval_metrics = [] + + training_iter = iter(tokenized_datasets) + + max_seq_length = min(data_args.max_seq_length, tokenizer.model_max_length) + eval_samples = advance_iter_and_group_samples( + training_iter, data_args.num_eval_samples, max_seq_length + ) + + last_desc = "" + steps = tqdm(range(num_train_steps), desc="Training...", position=0) + for step in range(num_train_steps): + if step < saved_step: + steps.update(1) + continue + # ======================== Training ================================ + try: + samples = advance_iter_and_group_samples( + training_iter, train_batch_size, max_seq_length + ) + except StopIteration: + # Once the end of the dataset stream is reached, the training iterator + # is reinitialized and reshuffled and a new eval dataset is randomely chosen. + shuffle_seed += 1 + tokenized_datasets.set_epoch(shuffle_seed) + + training_iter = iter(tokenized_datasets) + + eval_dataset = advance_iter_and_group_samples( + training_iter, data_args.num_eval_samples, max_seq_length + ) + samples = advance_iter_and_group_samples( + training_iter, train_batch_size, max_seq_length + ) + + # process input samples + model_inputs = data_collator(samples, pad_to_multiple_of=16) + + # Model forward + model_inputs = shard(model_inputs.data) + state, train_metric, dropout_rngs = p_train_step( + state, model_inputs, dropout_rngs + ) + + train_metrics.append(train_metric) + + if step % training_args.logging_steps == 0 and step > 0: + steps.write( + f"Step... ({step} | Loss: {train_metric['loss'].mean()}, Learning Rate: {train_metric['learning_rate'].mean()})" + ) + train_time += time.time() - train_start + if has_tensorboard and jax.process_index() == 0: + write_train_metric(summary_writer, train_metrics, train_time, step) + train_metrics = [] + + # ======================== Evaluating ============================== + if step % training_args.eval_steps == 0 and step > 0: + eval_samples_idx = jnp.arange(data_args.num_eval_samples) + eval_batch_idx = generate_batch_splits(eval_samples_idx, eval_batch_size) + + for i, batch_idx in enumerate( + tqdm(eval_batch_idx, desc="Evaluating ...", position=1) + ): + # process input samples + batch_eval_samples = { + k: [v[idx] for idx in batch_idx] for k, v in eval_samples.items() + } + model_inputs = data_collator(batch_eval_samples, pad_to_multiple_of=16) + + # Model forward + model_inputs = shard(model_inputs.data) + metrics = p_eval_step(state.params, model_inputs) + eval_metrics.append(metrics) + + # normalize eval metrics + eval_metrics = get_metrics(eval_metrics) + eval_metrics = jax.tree_map(jnp.sum, eval_metrics) + eval_normalizer = eval_metrics.pop("normalizer") + eval_metrics = jax.tree_map(lambda x: x / eval_normalizer, eval_metrics) + + # Update progress bar + steps.desc = f"Step... ({step}/{num_train_steps} | Loss: {eval_metrics['loss']}, Acc: {eval_metrics['accuracy']})" + last_desc = steps.desc + + if has_tensorboard and jax.process_index() == 0: + write_eval_metric(summary_writer, eval_metrics, step) + eval_metrics = [] + + # save checkpoint after eval_steps + if ( + step % training_args.save_steps == 0 + and step > 0 + and jax.process_index() == 0 + ): + logger.info(f"Saving checkpoint at {step} steps") + params = jax.device_get(jax.tree_map(lambda x: x[0], state.params)) + model.save_pretrained( + training_args.output_dir, + params=params, + push_to_hub=False, + ) + save_checkpoint_files( + state, data_collator, training_args, training_args.output_dir + ) + checkpoints_dir = ( + Path(training_args.output_dir) / "checkpoints" / f"checkpoint-{step}" + ) + checkpoints_dir.mkdir(parents=True, exist_ok=True) + model.save_pretrained(checkpoints_dir, params=params) + save_checkpoint_files(state, data_collator, training_args, checkpoints_dir) + rotate_checkpoints( + Path(training_args.output_dir) / "checkpoints", + max_checkpoints=training_args.save_total_limit, + ) + convert(training_args.output_dir, "./") + model.save_pretrained( + training_args.output_dir, + params=params, + push_to_hub=training_args.push_to_hub, + commit_message=last_desc, + ) + + # update tqdm bar + steps.update(1) + + if jax.process_index() == 0: + logger.info(f"Saving checkpoint at {step} steps") + params = jax.device_get(jax.tree_map(lambda x: x[0], state.params)) + model.save_pretrained( + training_args.output_dir, + params=params, + push_to_hub=False, + ) + save_checkpoint_files( + state, data_collator, training_args, training_args.output_dir + ) + checkpoints_dir = ( + Path(training_args.output_dir) / "checkpoints" / f"checkpoint-{step}" + ) + checkpoints_dir.mkdir(parents=True, exist_ok=True) + model.save_pretrained(checkpoints_dir, params=params) + save_checkpoint_files(state, data_collator, training_args, checkpoints_dir) + convert(training_args.output_dir, "./") + model.save_pretrained( + training_args.output_dir, + params=params, + push_to_hub=training_args.push_to_hub, + commit_message=last_desc or "Saving model after training", + ) diff --git a/data_tooling/bertin/run_stream.sh b/data_tooling/bertin/run_stream.sh new file mode 100644 index 0000000..48dfd90 --- /dev/null +++ b/data_tooling/bertin/run_stream.sh @@ -0,0 +1,28 @@ +#! /bin/bash +# From https://arxiv.org/pdf/1907.11692.pdf for base model +python -c "import jax; print('TPUs', jax.device_count())" +python ./run_mlm_flax_stream.py \ + --output_dir="./outputs" \ + --model_type="roberta" \ + --config_name="./configs/base" \ + --tokenizer_name="./configs/base" \ + --dataset_name="./mc4" \ + --dataset_config_name="es" \ + --train_file="path/to/mc4-es-train-50M-XXX.jsonl" \ + --max_seq_length="128" \ + --pad_to_max_length \ + --per_device_train_batch_size="256" \ + --per_device_eval_batch_size="256" \ + --adam_beta1="0.9" \ + --adam_beta2="0.98" \ + --adam_epsilon="1e-6" \ + 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"eos_token": "", "add_prefix_space": false, "errors": "replace", "sep_token": "", "cls_token": "", "pad_token": "", "mask_token": "", "special_tokens_map_file": null, "name_or_path": "./", "tokenizer_class": "RobertaTokenizer"} diff --git a/data_tooling/bertin/tokens.py b/data_tooling/bertin/tokens.py new file mode 100644 index 0000000..09c003c --- /dev/null +++ b/data_tooling/bertin/tokens.py @@ -0,0 +1,31 @@ +#!/usr/bin/env python3 +from datasets import load_dataset +from tokenizers import ByteLevelBPETokenizer + +# Load dataset +dataset = load_dataset("oscar", "unshuffled_deduplicated_es", split="train[:5000000]") + +# Instantiate tokenizer +tokenizer = ByteLevelBPETokenizer() + + +def batch_iterator(batch_size=100_000): + for i in range(0, len(dataset), batch_size): + yield dataset["text"][i : i + batch_size] + + +# Customized training +tokenizer.train_from_iterator( + batch_iterator(), + vocab_size=50265, + min_frequency=2, + special_tokens=[ + "", + "", + "", + "", + "", + ], +) +# Save files to disk +tokenizer.save("./tokenizer.json") diff --git a/data_tooling/bertin/tokens.py.orig b/data_tooling/bertin/tokens.py.orig new file mode 100644 index 0000000..3f8e47d --- /dev/null +++ b/data_tooling/bertin/tokens.py.orig @@ -0,0 +1,31 @@ +#!/usr/bin/env python3 +from datasets import load_dataset +from tokenizers import ByteLevelBPETokenizer + +# Load dataset +<<<<<<< HEAD +dataset = load_dataset("oscar", "unshuffled_deduplicated_es", split="train[:5000000]") + +# Instantiate tokenizer +tokenizer = ByteLevelBPETokenizer() +def batch_iterator(batch_size=100_000): +======= +dataset = load_dataset("oscar", "unshuffled_deduplicated_es", split="train") + +# Instantiate tokenizer +tokenizer = ByteLevelBPETokenizer() +def batch_iterator(batch_size=1_000_000): +>>>>>>> d5cede47e74aa6ec36f20acf5aba37c6734c6186 + for i in range(0, len(dataset), batch_size): + yield dataset["text"][i: i + batch_size] + +# Customized training +tokenizer.train_from_iterator(batch_iterator(), vocab_size=50265, min_frequency=2, special_tokens=[ + "", + "", + "", + "", + "", +]) +# Save files to disk +tokenizer.save("./tokenizer.json") diff --git a/data_tooling/bertin/tsne_plot.py b/data_tooling/bertin/tsne_plot.py new file mode 100644 index 0000000..0b9f459 --- /dev/null +++ b/data_tooling/bertin/tsne_plot.py @@ -0,0 +1,116 @@ +import argparse +import logging +from typing import Any, Optional + +import bokeh +import numpy as np +import pandas as pd +from bokeh.models import ColumnDataSource, HoverTool +from bokeh.palettes import Cividis256 as Pallete +from bokeh.plotting import figure, output_file, save +from bokeh.transform import factor_cmap +from sklearn.manifold import TSNE + +logging.basicConfig(level=logging.INFO) +logger = logging.getLogger(__name__) +SEED = 0 + + +def get_tsne_embeddings( + embeddings: np.ndarray, + perplexity: int = 30, + n_components: int = 2, + init: str = "pca", + n_iter: int = 5000, + random_state: int = SEED, +) -> np.ndarray: + tsne = TSNE( + perplexity=perplexity, + n_components=n_components, + init=init, + n_iter=n_iter, + random_state=random_state, + ) + return tsne.fit_transform(embeddings) + + +def draw_interactive_scatter_plot( + texts: np.ndarray, xs: np.ndarray, ys: np.ndarray, values: np.ndarray +) -> Any: + # Normalize values to range between 0-255, to assign a color for each value + max_value = values.max() + min_value = values.min() + values_color = ( + ((values - min_value) / (max_value - min_value) * 255) + .round() + .astype(int) + .astype(str) + ) + values_color_set = sorted(values_color) + + values_list = values.astype(str).tolist() + values_set = sorted(values_list) + + source = ColumnDataSource(data=dict(x=xs, y=ys, text=texts, perplexity=values_list)) + hover = HoverTool( + tooltips=[("Sentence", "@text{safe}"), ("Perplexity", "@perplexity")] + ) + p = figure(plot_width=1200, plot_height=1200, tools=[hover], title="Sentences") + p.circle( + "x", + "y", + size=10, + source=source, + fill_color=factor_cmap( + "perplexity", + palette=[Pallete[int(id_)] for id_ in values_color_set], + factors=values_set, + ), + ) + return p + + +def generate_plot(tsv: str, output_file_name: str, sample: Optional[int]): + logger.info("Loading dataset in memory") + df = pd.read_csv(tsv, sep="\t") + if sample: + df = df.sample(sample, random_state=SEED) + logger.info(f"Dataset contains {df.shape[0]} sentences") + embeddings = df[ + sorted( + (col for col in df.columns if col.startswith("dim")), + key=lambda x: int(x.split("_")[-1]), + ) + ].values + logger.info(f"Running t-SNE") + tsne_embeddings = get_tsne_embeddings(embeddings) + logger.info(f"Generating figure") + plot = draw_interactive_scatter_plot( + df["sentence"].values, + tsne_embeddings[:, 0], + tsne_embeddings[:, 1], + df["perplexity"].values, + ) + output_file(output_file_name) + save(plot) + + +if __name__ == "__main__": + parser = argparse.ArgumentParser(description="Embeddings t-SNE plot") + parser.add_argument( + "--tsv", + type=str, + help="Path to tsv file with columns 'text', 'perplexity' and N 'dim_ columns for each embdeding dimension.'", + ) + parser.add_argument( + "--output_file", + type=str, + help="Path to the output HTML file for the interactive plot.", + default="perplexity_colored_embeddings.html", + ) + parser.add_argument( + "--sample", type=int, help="Number of sentences to use", default=None + ) + + args = parser.parse_args() + generate_plot(args.tsv, args.output_file, args.sample) diff --git a/data_tooling/bertin/utils/dataset_perplexity.py b/data_tooling/bertin/utils/dataset_perplexity.py new file mode 100644 index 0000000..2ca470c --- /dev/null +++ b/data_tooling/bertin/utils/dataset_perplexity.py @@ -0,0 +1,23 @@ +import json + +import kenlm +from tqdm import tqdm + +model = kenlm.Model("../es.arpa.bin") + + +def get_perplexity(doc): + doc_log_score, doc_length = 0, 0 + for line in doc.split("\n"): + log_score = model.score(line) + length = len(line.split()) + 1 + doc_log_score += log_score + doc_length += length + return 10.0 ** (-doc_log_score / doc_length) + + +with open("mc4-es-train-50M-stats.csv", "w") as csv: + with open("mc4-es-train-50M-steps.jsonl", "r") as data: + for line in tqdm(data): + text = json.loads(line)["text"] + csv.write(f"{len(text.split())},{get_perplexity(text)}\n") diff --git a/data_tooling/bertin/utils/download_mc4es_sampled.py b/data_tooling/bertin/utils/download_mc4es_sampled.py new file mode 100644 index 0000000..a244659 --- /dev/null +++ b/data_tooling/bertin/utils/download_mc4es_sampled.py @@ -0,0 +1,32 @@ +import gzip +import io +import json +import sys + +import requests +from tqdm import tqdm + +_DATA_URL_TRAIN = "https://huggingface.co/datasets/bertin-project/mc4-es-sampled/resolve/main/mc4-es-train-50M-{config}-shard-{index:04d}-of-{n_shards:04d}.json.gz" + + +def main(config="stepwise"): + data_urls = [ + _DATA_URL_TRAIN.format( + config=config, + index=index + 1, + n_shards=1024, + ) + for index in range(1024) + ] + with open(f"mc4-es-train-50M-{config}.jsonl", "w") as f: + for dara_url in tqdm(data_urls): + response = requests.get(dara_url) + bio = io.BytesIO(response.content) + with gzip.open(bio, "rt", encoding="utf8") as g: + for line in g: + json_line = json.loads(line.strip()) + f.write(json.dumps(json_line) + "\n") + + +if __name__ == "__main__": + main(sys.argv[1]) diff --git a/data_tooling/bertin/utils/generate_datasets.py b/data_tooling/bertin/utils/generate_datasets.py new file mode 100644 index 0000000..20611fa --- /dev/null +++ b/data_tooling/bertin/utils/generate_datasets.py @@ -0,0 +1,162 @@ +import json +import logging +import os + +from datasets import load_dataset +from tqdm import tqdm + +# Setup logging +logging.basicConfig( + format="%(asctime)s - %(levelname)s - %(name)s - %(message)s", + level="INFO", + datefmt="[%X]", +) + +# Log on each process the small summary: +logger = logging.getLogger(__name__) +os.system("wget http://dl.fbaipublicfiles.com/cc_net/lm/es.arpa.bin") +mc4 = load_dataset( + "./mc4", + "es", + split="train", + sampling_method="steps", + perplexity_model="./es.arpa.bin", + sampling_factor=1.5e5, + boundaries=[536394.99320948, 662247.50212365, 919250.87225178], + streaming=True, +).shuffle(buffer_size=10000, seed=2021) +total = 0 +with open("mc4-es-train-50M-steps.jsonl", "w") as f: + for sample in tqdm(mc4, total=50_000_000): + f.write(json.dumps(sample) + "\n") + total += 1 + if total >= 50_000_000: + break + +mc4val = load_dataset( + "./mc4", + "es", + split="validation", + sampling_method="steps", + perplexity_model="./es.arpa.bin", + sampling_factor=5e5, + boundaries=[536394.99320948, 662247.50212365, 919250.87225178], + streaming=True, +).shuffle(buffer_size=10000, seed=2021) +total = 0 +with open("mc4-es-validation-5M-steps.jsonl", "w") as f: + for sample in tqdm(mc4val, total=5_000_000): + f.write(json.dumps(sample) + "\n") + total += 1 + if total >= 5_000_000: + break + + +# ------------------ + +import json +import logging + +from datasets import load_dataset +from tqdm import tqdm + +# Setup logging +logging.basicConfig( + format="%(asctime)s - %(levelname)s - %(name)s - %(message)s", + level="INFO", + datefmt="[%X]", +) + +# Log on each process the small summary: +logger = logging.getLogger(__name__) + + +mc4 = load_dataset( + "./mc4", + "es", + split="train", + sampling_method="gaussian", + perplexity_model="../es.arpa.bin", + sampling_factor=0.78, + boundaries=[536394.99320948, 662247.50212365, 919250.87225178], + streaming=True, +).shuffle(buffer_size=10000, seed=2021) +total = 0 +with open("mc4-es-train-50M-gaussian.jsonl", "w") as f: + for sample in tqdm(mc4, total=50_000_000): + f.write(json.dumps(sample) + "\n") + total += 1 + if total >= 50_000_000: + break +mc4val = load_dataset( + "./mc4", + "es", + split="validation", + sampling_method="gaussian", + perplexity_model="../es.arpa.bin", + sampling_factor=1, + boundaries=[536394.99320948, 662247.50212365, 919250.87225178], + streaming=True, +).shuffle(buffer_size=10000, seed=2021) +total = 0 +with open("mc4-es-validation-5M-gaussian.jsonl", "w") as f: + for sample in tqdm(mc4val, total=5_000_000): + f.write(json.dumps(sample) + "\n") + total += 1 + if total >= 5_000_000: + break + + +# ------------------ + +import json +import logging + +from datasets import load_dataset +from tqdm import tqdm + +# Setup logging +logging.basicConfig( + format="%(asctime)s - %(levelname)s - %(name)s - %(message)s", + level="INFO", + datefmt="[%X]", +) + +# Log on each process the small summary: +logger = logging.getLogger(__name__) + + +mc4 = load_dataset( + "./mc4", + "es", + split="train", + sampling_method="random", + perplexity_model="../es.arpa.bin", + sampling_factor=0.5, + boundaries=[536394.99320948, 662247.50212365, 919250.87225178], + streaming=True, +).shuffle(buffer_size=10000, seed=2021) +total = 0 +with open("mc4-es-train-50M-random.jsonl", "w") as f: + for sample in tqdm(mc4, total=50_000_000): + f.write(json.dumps(sample) + "\n") + total += 1 + if total >= 50_000_000: + break +mc4val = load_dataset( + "./mc4", + "es", + split="validation", + sampling_method="random", + perplexity_model="../es.arpa.bin", + sampling_factor=0.5, + boundaries=[536394.99320948, 662247.50212365, 919250.87225178], + streaming=True, +).shuffle(buffer_size=10000, seed=2021) +total = 0 +with open("mc4-es-validation-5M-random.jsonl", "w") as f: + for sample in tqdm(mc4val, total=5_000_000): + f.write(json.dumps(sample) + "\n") + total += 1 + if total >= 5_000_000: + break diff --git a/data_tooling/bertin/vocab.json b/data_tooling/bertin/vocab.json new file mode 100644 index 0000000..436ea42 --- /dev/null +++ b/data_tooling/bertin/vocab.json @@ -0,0 +1 @@ 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diff --git a/data_tooling/cc_pseudo_crawl/README.md b/data_tooling/cc_pseudo_crawl/README.md new file mode 100644 index 0000000..8cc4953 --- /dev/null +++ b/data_tooling/cc_pseudo_crawl/README.md @@ -0,0 +1,89 @@ +# Extracting Content from Common Crawl for Curated List of Sites + +aka. "pseudo-crawls" + +- tools to extract content from Common Crawl for curated list of sites +- metrics about planned and ongoing pseudo-crawls to understand their coverage (size, languages, content types, etc.) + +## Preliminary Steps + +- create AWS account in order to use [Athena](https://aws.amazon.com/athena/) to perform the lookups +- in Athena, create database `ccindex` and table `ccindex`, see https://commoncrawl.org/2018/03/index-to-warc-files-and-urls-in-columnar-format/ +- create the database `bigscience` which holds the joined data and more + ```sql + CREATE DATABASE bigscience; + ``` + +## Looking Up URLs per Site List + +For every site list + +1. create a seed table which includes the join column (host or domain name, SURT URL). See [cleanup-seeds](./sourcing_sheet_seeds/cleanup-seeds.ipynb) for an example of this and the following step. + +2. export the table to a file, ideally in a columnar format (Parquet or ORC) + +3. upload the seed file to S3 + ``` + aws s3 cp seeds.gz.parquet s3://bucket/path/seeds/ + ``` + Note: the S3 path must point to a bucket with write permissions granted. The path needs to be adjusted also in follwing commands. + +3. import the seed table into Athena + ```sql + CREATE EXTERNAL TABLE IF NOT EXISTS bigscience.seeds ( + `id` int, + `title` string, + `link` string, + `language` string, + `url_path_prefix` string, + `url_host_name` string, + `url_host_registered_domain` string, + `url_surtkey` string) + ROW FORMAT SERDE 'org.apache.hadoop.hive.ql.io.parquet.serde.ParquetHiveSerDe' + WITH SERDEPROPERTIES ( + 'serialization.format' = '1' + ) LOCATION 's3://bucket/path/seeds/' + TBLPROPERTIES ('has_encrypted_data'='false'); + ``` + +4. join the seeds table crawl by crawl with Common Crawl's index, creating a temporary table which is later used as one partition of the result table + ``` + python3 cc_lookup.py s3://bucket/path seeds "CC-MAIN-2021" + ``` + This will run the join for all crawls of the year 2021 and put the join data into `s3://bucket/path/cc`. + +5. finally, create a table holding the result data in order to get further metrics or prepare the content export + ```sql + CREATE EXTERNAL TABLE IF NOT EXISTS bigscience.cc ( + id INT, + title STRING, + link STRING, + language STRING, + url_surtkey_prefix STRING, + url_surtkey STRING, + url_host_tld STRING, + url_host_registered_domain STRING, + url_host_name STRING, + url STRING, + fetch_status SMALLINT, + fetch_time TIMESTAMP, + warc_filename STRING, + warc_record_offset INT, + warc_record_length INT, + fetch_redirect STRING, + content_mime_detected STRING, + content_languages STRING) + PARTITIONED BY ( + crawl STRING, + subset STRING) + STORED AS parquet + LOCATION 's3://bucket/path/cc/' + TBLPROPERTIES ( + 'has_encrypted_data'='false', + 'parquet.compression'='GZIP'); + ``` + +6. load the partitions of the join table + ```sql + MSCK REPAIR TABLE bigscience.cc; + ``` diff --git a/data_tooling/cc_pseudo_crawl/cc_lookup.py b/data_tooling/cc_pseudo_crawl/cc_lookup.py new file mode 100644 index 0000000..72abdd4 --- /dev/null +++ b/data_tooling/cc_pseudo_crawl/cc_lookup.py @@ -0,0 +1,189 @@ +#!/usr/bin/python3 + +# iterate over monthly crawls and store +# the joined data as a partition of the result table + +import logging +import re +import sys + +from pyathena import connect + +logging.basicConfig( + level="INFO", format="%(asctime)s %(levelname)s %(name)s: %(message)s" +) + +join_template = """ +CREATE TABLE {db}._tmp_overlap +WITH (external_location = '{s3_location}/crawl={crawl}/', + partitioned_by = ARRAY['subset'], + format = 'PARQUET', + parquet_compression = 'GZIP') +AS SELECT + {tid}.id AS id, + {tid}.title AS title, + {tid}.link AS link, + {tid}.language AS language, + {tid}.url_surtkey AS url_surtkey_prefix, + cc.url_surtkey AS url_surtkey, + cc.url_host_tld AS url_host_tld, + cc.url_host_registered_domain AS url_host_registered_domain, + cc.url_host_name AS url_host_name, + cc.url AS url, + cc.fetch_status AS fetch_status, + cc.fetch_time AS fetch_time, + cc.warc_filename AS warc_filename, + cc.warc_record_offset AS warc_record_offset, + cc.warc_record_length AS warc_record_length, + cc.fetch_redirect AS fetch_redirect, + cc.content_mime_detected AS content_mime_detected, + cc.content_languages AS content_languages, + cc.subset AS subset +FROM ccindex.ccindex AS cc + RIGHT OUTER JOIN {db}.{seed_table} AS {tid} + ON cc.url_host_registered_domain = {tid}.url_host_registered_domain + AND strpos(cc.url_surtkey, {tid}.url_surtkey) = 1 +WHERE cc.crawl = '{crawl}' +""" + +drop_tmp_table = "DROP TABLE `{db}._tmp_overlap`;" + +# list of crawls +# Note: in order to get a list of released crawls: +# - query Athena +# SHOW PARTITIONS ccindex +# - see +# https://commoncrawl.s3.amazonaws.com/crawl-data/index.html +crawls = [ + "CC-MAIN-2013-20", + "CC-MAIN-2013-48", + # + "CC-MAIN-2014-10", + "CC-MAIN-2014-15", + "CC-MAIN-2014-23", + "CC-MAIN-2014-35", + "CC-MAIN-2014-41", + "CC-MAIN-2014-42", + "CC-MAIN-2014-49", + "CC-MAIN-2014-52", + # + "CC-MAIN-2015-06", + "CC-MAIN-2015-11", + "CC-MAIN-2015-14", + "CC-MAIN-2015-18", + "CC-MAIN-2015-22", + "CC-MAIN-2015-27", + "CC-MAIN-2015-32", + "CC-MAIN-2015-35", + "CC-MAIN-2015-40", + "CC-MAIN-2015-48", + # + "CC-MAIN-2016-07", + "CC-MAIN-2016-18", + "CC-MAIN-2016-22", + "CC-MAIN-2016-26", + "CC-MAIN-2016-30", + "CC-MAIN-2016-36", + "CC-MAIN-2016-40", + "CC-MAIN-2016-44", + "CC-MAIN-2016-50", + # + "CC-MAIN-2017-04", + "CC-MAIN-2017-09", + "CC-MAIN-2017-13", + "CC-MAIN-2017-17", + "CC-MAIN-2017-22", + "CC-MAIN-2017-26", + "CC-MAIN-2017-30", + "CC-MAIN-2017-34", + "CC-MAIN-2017-39", + "CC-MAIN-2017-43", + "CC-MAIN-2017-47", + "CC-MAIN-2017-51", + # + "CC-MAIN-2018-05", + "CC-MAIN-2018-09", + "CC-MAIN-2018-13", + "CC-MAIN-2018-17", + "CC-MAIN-2018-22", + "CC-MAIN-2018-26", + "CC-MAIN-2018-30", + "CC-MAIN-2018-34", + "CC-MAIN-2018-39", + "CC-MAIN-2018-43", + "CC-MAIN-2018-47", + "CC-MAIN-2018-51", + # + "CC-MAIN-2019-04", + "CC-MAIN-2019-09", + "CC-MAIN-2019-13", + "CC-MAIN-2019-18", + "CC-MAIN-2019-22", + "CC-MAIN-2019-26", + "CC-MAIN-2019-30", + "CC-MAIN-2019-35", + "CC-MAIN-2019-39", + "CC-MAIN-2019-43", + "CC-MAIN-2019-47", + "CC-MAIN-2019-51", + # + "CC-MAIN-2020-05", + "CC-MAIN-2020-10", + "CC-MAIN-2020-16", + "CC-MAIN-2020-24", + "CC-MAIN-2020-29", + "CC-MAIN-2020-34", + "CC-MAIN-2020-40", + "CC-MAIN-2020-45", + "CC-MAIN-2020-50", + # + "CC-MAIN-2021-04", + "CC-MAIN-2021-10", + "CC-MAIN-2021-17", + "CC-MAIN-2021-21", + "CC-MAIN-2021-25", + "CC-MAIN-2021-31", + "CC-MAIN-2021-39", + "CC-MAIN-2021-43", + "CC-MAIN-2021-49", + # +] + + +s3_location = sys.argv[1] +s3_location = s3_location.rstrip("/") # no trailing slash! + +seed_table = sys.argv[2] + +crawl_selector = re.compile(sys.argv[3], re.IGNORECASE) + + +crawls = filter(lambda c: crawl_selector.match(c), crawls) + + +cursor = connect( + s3_staging_dir="{}/staging".format(s3_location), region_name="us-east-1" +).cursor() + +for crawl in crawls: + query = join_template.format( + crawl=crawl, + s3_location="{}/cc".format(s3_location), + db="bigscience", + seed_table=seed_table, + tid="bs", + ) + logging.info("Athena query: %s", query) + + cursor.execute(query) + logging.info("Athena query ID %s: %s", cursor.query_id, cursor.result_set.state) + logging.info( + " data_scanned_in_bytes: %d", cursor.result_set.data_scanned_in_bytes + ) + logging.info( + " total_execution_time_in_millis: %d", + cursor.result_set.total_execution_time_in_millis, + ) + + cursor.execute(drop_tmp_table.format(db="bigscience")) + logging.info("Drop temporary table: %s", cursor.result_set.state) diff --git a/data_tooling/cc_pseudo_crawl/requirements.txt b/data_tooling/cc_pseudo_crawl/requirements.txt new file mode 100644 index 0000000..f756ba6 --- /dev/null +++ b/data_tooling/cc_pseudo_crawl/requirements.txt @@ -0,0 +1,3 @@ +pyathena +surt +tldextract diff --git a/data_tooling/cc_pseudo_crawl/sourcing_sheet_seeds/README.md b/data_tooling/cc_pseudo_crawl/sourcing_sheet_seeds/README.md new file mode 100644 index 0000000..5ce066f --- /dev/null +++ b/data_tooling/cc_pseudo_crawl/sourcing_sheet_seeds/README.md @@ -0,0 +1,11 @@ +# Pseudo-Crawl Data Sourcing Candidate Seeds Spreadsheet + +Source: https://docs.google.com/spreadsheets/d/1DNLAGz--qvLh-0qQ7pMPGiNeUMgp-fRgn-8mbLagC7U/edit#gid=513216703 (timestamp 2021-11-28, reverted edits by anonymous user on record 16 - diariovasco.com), exported as [candidate_websites_for_crawling.csv](./candidate_websites_for_crawling.csv) + +Steps: + +1. run [cleanup-seeds](./cleanup-seeds.ipynb) to prepare a clean seed list + +2. do the lookups / table join, see [general instructions](../README.md) using the crawl selector `CC-MAIN-202[01]` to restrict the join for the last 2 years + +3. prepare [coverage metrics](./cc-metrics.ipynb) diff --git a/data_tooling/cc_pseudo_crawl/sourcing_sheet_seeds/candidate_websites_for_crawling.csv b/data_tooling/cc_pseudo_crawl/sourcing_sheet_seeds/candidate_websites_for_crawling.csv new file mode 100644 index 0000000..5a78910 --- /dev/null +++ b/data_tooling/cc_pseudo_crawl/sourcing_sheet_seeds/candidate_websites_for_crawling.csv @@ -0,0 +1,462 @@ +#,"Dataset title","Domain Name / link +(if highlighted in red, it's a duplicate! So don't add it...)","License +(default is UNKNOWN)","Release (Issue date) ",Glottocode,"Language(s) (or family)","Dialect/accent (if known)",Subject,Format,"Collection Style (Manual Curation vs Crowdsourced(web)) ?","What it is / why we want it (5-25 words)","Volume (estimates)","Contains Personal Information? (-1=unlikely, 0=neutral, 1=likely)",Owner,"Usage and relation to other datasets " +12,"Fundacion Cajasol",https://fundacioncajasol.com/,unknown,"multiple releases",stan1288,es,Spain,"General News","text (web)",manual,,unknown,unknown,"Fundacion Cajasol", +13,"Asamblea Nacional del Ecuador",http://www.confirmado.net/,unknown,"multiple releases",,es,Ecuador,"General News","text (web)",manual,,unknown,unknown,"Asamblea Nacional del Ecuador", +14,"el periodico de Tlaxcala",https://elperiodicodetlaxcala.com/,unknown,"multiple releases",,es,Mexico,"General News","text (web)",manual,,unknown,unknown,"el periodico de Tlaxcala", +15,mispeces,https://www.mispeces.com/,unknown,"multiple releases",,es,Spain,"General News","text (web)",manual,,unknown,unknown,mispeces, +16,DiarioVasco,https://www.diariovasco.com/,unknown,"multiple releases",,es,Spain,"General News","text (web)",manual,,unknown,unknown,DiarioVasco, +17,pambianconews,https://www.pambianconews.com/,unknown,"multiple releases",,es,Argentina,"General News","text (web)",manual,,unknown,unknown,pambianconews, +18,"Diario El Venezolano",http://elvenezolanonews.com/,unknown,"multiple releases",,es,Spain,"General News","text (web)",manual,,unknown,unknown,"Diario El Venezolano", +19,"Diario de Ibiza",https://www.diariodeibiza.es/,unknown,"multiple releases",,es,Spain,"General News","text (web)",manual,,unknown,unknown,"Diario de Ibiza", +20,"Clarín - Argentina",http://www.clarin.com/,unknown,"multiple releases",,es,Argentina,"General News","text (web)",manual,,unknown,unknown,"Clarín - Argentina", +21,"El Periódico de Aragón. Noticias de Aragón, Zaragoza, Huesca y Teruel.",https://www.elperiodicodearagon.com/,unknown,"multiple releases",,es,Spain,"General News","text (web)",manual,,unknown,unknown,"El Periódico de Aragón. Noticias de Aragón, Zaragoza, Huesca y Teruel.", +22,"club influencers",https://www.clubinfluencers.com/,unknown,"multiple releases",,es,Spain,"General News","text (web)",manual,,unknown,unknown,"club influencers", +23,"elc onfidencial digital",https://www.elconfidencialdigital.com/,unknown,"multiple releases",,es,Spain,"General News","text (web)",manual,,unknown,unknown,"elc onfidencial digital", +24,tiempo,http://www.tiempo.com.mx/,unknown,"multiple releases",,es,mexico,"general news","text (web)",manual,,unknown,unknown,tiempo, +25,"kitco mining news",https://www.kitco.com/mining/,unknown,"multiple releases",,es,venezuela,"general news","text (web)",manual,,unknown,unknown,"kitco mining news", +26,"portada de la web del ministerio de cultura y deporte",http://www.culturaydeporte.gob.es/portada.html,unknown,"multiple releases",,es,spain,"general news","text (web)",manual,,unknown,unknown,"portada de la web del ministerio de cultura y deporte", +27,"gestores de residuos",https://gestoresderesiduos.org/,unknown,"multiple releases",,es,spain,"general news","text (web)",manual,,unknown,unknown,"gestores de residuos", +28,fayerwayer,http://www.fayerwayer.com/,unknown,"multiple releases",,es,usa,"general news","text (web)",manual,,unknown,unknown,fayerwayer, +29,agricultura,http://www.revistaagricultura.com/portada,unknown,"multiple releases",,es,spain,agriculture,"text (web)",manual,,unknown,unknown,agricultura, +30,radiocable,http://www.radiocable.com/,unknown,"multiple releases",,es,spain,"general news","text (web)",manual,,unknown,unknown,radiocable, +31,"la jornada",http://www.lajornadanet.com/,unknown,"multiple releases",,es,nicaragua,"general news","text (web)",manual,,unknown,unknown,"la jornada", +32,"periódico el expresso de puerto rico",http://www.elexpresso.com/,unknown,"multiple releases",,es,"porto rico","general news","text (web)",manual,,unknown,unknown,"periódico el expresso de puerto rico", +33,pld,https://prd.org.do/,unknown,"multiple releases",,es,"domenican republic","general news","text (web)",manual,,unknown,unknown,pld, +34,"los andes",https://www.losandes.com.ar/,unknown,"multiple releases",,es,argentina,"general news","text (web)",manual,,unknown,unknown,"los andes", +35,tiempo,https://www.tiempo.com/,unknown,"multiple releases",,es,spain,"general news","text (web)",manual,,unknown,unknown,tiempo, +36,"el morrocotudo",http://www.elmorrocotudo.cl/,unknown,"multiple releases",,es,cl,"general news","text (web)",manual,,unknown,unknown,"el morrocotudo", +37,"tv perú canal 7",http://www.tvperu.gob.pe/informa,unknown,"multiple releases",,es,peru,"general news","text (web)",manual,,unknown,unknown,"tv perú canal 7", +38,energia-imdea,https://www.energia.imdea.org/,unknown,"multiple releases",,es,spain,"general news","text (web)",manual,,unknown,unknown,energia-imdea, +39,urgente24,https://www.urgente24.com/,unknown,"multiple releases",,es,argentina,"general news","text (web)",manual,,unknown,unknown,urgente24, +40,"corte electoral",https://www.corteelectoral.gub.uy/,unknown,"multiple releases",,es,uruguay,"general news","text (web)",manual,,unknown,unknown,"corte electoral", +41,"observatorio de la política china",https://politica-china.org,unknown,"multiple releases",,es,spain,"general news","text (web)",manual,,unknown,unknown,"1, According to the “Provisions of the Supreme People's Court on the People's Court's Publication of Judgment Documents online” (最高人民法院关于人民法院在互联网公布裁判文书的规定), the online publication of judgment documents should be based on the principle of openness, with non-publicity as an exception. Judicial documents involving national security, juvenile delinquency, divorce proceedings, support or guardianship of minor children, etc., shall not be made public. In +public judgment documents, information concerning personal privacy, +trade secrets, etc., other than the names of the parties, shall also be +deleted from the document.", +42,"icefi - instituto centroamericano de estudios fiscales",http://icefi.org/,unknown,"multiple releases",,es,gt,"general news","text (web)",manual,,unknown,unknown,"icefi - instituto centroamericano de estudios fiscales", +43,"baja california sur - gobierno del estado",http://www.bcs.gob.mx/,unknown,"multiple releases",,es,mexico,"general news","text (web)",manual,,unknown,unknown,"baja california sur - gobierno del estado", +44,ladiaria,https://ladiaria.com.uy/,unknown,"multiple releases",,es,uruguay,"general news","text (web)",manual,,unknown,unknown,ladiaria, +45,cepal,http://www.lacuarta.com/,unknown,"multiple releases",,es,cl,"general news","text (web)",manual,,unknown,unknown,cepal, +46,"uno santafe",https://www.unosantafe.com.ar/,unknown,"multiple releases",,es,argentina,"general news","text (web)",manual,,unknown,unknown,"uno santafe", +47,"banco central del ecuador",http://www.bce.fin.ec/,unknown,"multiple releases",,es,ecuador,"general news","text (web)",manual,,unknown,unknown,"banco central del ecuador", +48,"banco central de bolivia",http://www.bcb.gob.bo/,unknown,"multiple releases",,es,bolivia,"general news","text (web)",manual,,unknown,unknown,"banco central de bolivia", +49,"diario de toluca, estado de méxico",http://diarioportal.com,unknown,"multiple releases",,es,mexico,"general news","text (web)",manual,,unknown,unknown,"diario de toluca, estado de méxico", +50,gva-es,https://www.gva.es/va/inicio/presentacion,unknown,"multiple releases",,es,spain,"general news","text (web)",manual,,unknown,unknown,gva-es, +51,noroeste,https://www.noroeste.com.mx/,unknown,"multiple releases",,es,mexico,"general news","text (web)",manual,,unknown,unknown,noroeste, +52,"el mundo de cordoba",http://www.elmundodecordoba.com/,unknown,"multiple releases",,es,argentina,"general news","text (web)",manual,,unknown,unknown,"el mundo de cordoba", +53,"diario expreso de guayaquil",https://www.expreso.ec/,unknown,"multiple releases",,es,ecuador,"general news","text (web)",manual,,unknown,unknown,"diario expreso de guayaquil", +54,sonora,http://www.sonora.com.gt/,unknown,"multiple releases",,es,gt,"general news","text (web)",manual,,unknown,unknown,sonora, +55,"libertad digital",http://www.libertaddigital.es,unknown,"multiple releases",,es,spain,"general news","text (web)",manual,,unknown,unknown,"libertad digital", +56,"el universo",https://www.eluniverso.com/,unknown,"multiple releases",,es,ecuador,"general news","text (web)",manual,,unknown,unknown,"el universo", +57,"prensa presidencial",http://www.minci.gob.ve,unknown,"multiple releases",,es,venezuela,"general news","text (web)",manual,,unknown,unknown,"prensa presidencial", +58,levante-emv,https://www.levante-emv.com/,unknown,"multiple releases",,es,spain,"general news","text (web)",manual,,unknown,unknown,levante-emv, +59,minam,http://www.minam.gob.pe/,unknown,"multiple releases",,es,peru,"general news","text (web)",manual,,unknown,unknown,minam, +60,economia3,https://economia3.com/,unknown,"multiple releases",,es,spain,"general news","text (web)",manual,,unknown,unknown,economia3, +61,"la nacion - chile",http://lanacion.cl/,unknown,"multiple releases",,es,cl,"general news","text (web)",manual,,unknown,unknown,"la nacion - chile", +62,"la pagina",https://www.lapagina.com.sv/,unknown,"multiple releases",,es,"el salvador","general news","text (web)",manual,,unknown,unknown,"la pagina", +63,"la nacion (argentina)",http://www.lanacion.com.ar/,unknown,"multiple releases",,es,argentina,"general news","text (web)",manual,,unknown,unknown,"la nacion (argentina)", +64,cosave,http://www.cosave.org/pagina/bienvenidos-al-comite-de-sanidad-vegetal-cosave,unknown,"multiple releases",,es,cl,"general news","text (web)",manual,,unknown,unknown,cosave, +65,"el nuevo herald",https://www.elnuevoherald.com/,unknown,"multiple releases",,es,usa,"general news","text (web)",manual,,unknown,unknown,"el nuevo herald", +66,"diario el expreso",https://www.diarioelexpreso.com.ve/,unknown,"multiple releases",,es,venezuela,"general news","text (web)",manual,,unknown,unknown,"diario el expreso", +67,"elpais - costa rica",http://www.elpais.cr,unknown,"multiple releases",,es,cr,"general news","text (web)",manual,,unknown,unknown,"elpais - costa rica", +68,"ciemat - centro de investigaciones energéticas, medioambientales y tecnológicas",http://www.ciemat.es/,unknown,"multiple releases",,es,spain,"general news","text (web)",manual,,unknown,unknown,"ciemat - centro de investigaciones energéticas, medioambientales y tecnológicas", +69,"el orbe",https://elorbe.com/,unknown,"multiple releases",,es,mexico,"general news","text (web)",manual,,unknown,unknown,"el orbe", +70,"cuba encuentro",http://www.cubaencuentro.com/,unknown,"multiple releases",,es,cuba,"general news","text (web)",manual,,unknown,unknown,"cuba encuentro", +71,"radio televisión española",http://www.rtve.es/,unknown,"multiple releases",,es,spain,"general news","text (web)",manual,,unknown,unknown,"radio televisión española", +72,"elcano royal insitute (real istituto elcano)",http://www.realinstitutoelcano.org/wps/portal/rielcano_es,unknown,"multiple releases",,es,spain,"general news","text (web)",manual,,unknown,unknown,"elcano royal insitute (real istituto elcano)", +73,"notihua tul copuerto escondido",https://notihuatulcopuertoescondido.com/,unknown,"multiple releases",,es,mexico,"general news","text (web)",manual,,unknown,unknown,"notihua tul copuerto escondido", +74,"rpc tv",http://www.rpctv.com/,unknown,"multiple releases",,es,panama,"general news","text (web)",manual,,unknown,unknown,"rpc tv", +75,"ministerio de educación",https://educacion.gob.ec/,unknown,"multiple releases",,es,ecuador,"general news","text (web)",manual,,unknown,unknown,"ministerio de educación", +76,repretel,https://www.repretel.com/,unknown,"multiple releases",,es,cr,"general news","text (web)",manual,,unknown,unknown,repretel, +77,elmon,https://elmon.cat/monplaneta/,unknown,"multiple releases",,es,spain,"general news","text (web)",manual,,unknown,unknown,elmon, +78,"listín diario digital",http://www.listindiario.com/,unknown,"multiple releases",,es,"domenican republic","general news","text (web)",manual,,unknown,unknown,"listín diario digital", +79,"la opinión de murcia",http://www.laopiniondemurcia.es/,unknown,"multiple releases",,es,spain,"general news","text (web)",manual,,unknown,unknown,"la opinión de murcia", +80,lawyerpress,http://lawyerpress.com/,unknown,"multiple releases",,es,spain,"general news","text (web)",manual,,unknown,unknown,lawyerpress, +81,"diario el cordillerano",http://www.elcordillerano.com.ar/,unknown,"multiple releases",,es,argentina,"general news","text (web)",manual,,unknown,unknown,"diario el cordillerano", +82,"pro y contra",http://proycontra.com.pe/,unknown,"multiple releases",,es,peru,"general news","text (web)",manual,,unknown,unknown,"pro y contra", +83,"vietnamplus (spanish)",http://es.vietnamplus.vn/,unknown,"multiple releases",,es,vietnam,"general news","text (web)",manual,,unknown,unknown,"vietnamplus (spanish)", +84,"centro de documentacion e informacion bolivia",https://cedib.org,unknown,"multiple releases",,es,bolivia,"general news","text (web)",manual,,unknown,unknown,"centro de documentacion e informacion bolivia", +85,"sarriguren web",https://sarrigurenweb.com/,unknown,"multiple releases",,es,spain,"general news","text (web)",manual,,unknown,unknown,"sarriguren web", +86,motorpasion,https://www.motorpasion.com/,unknown,"multiple releases",,es,spain,"general news","text (web)",manual,,unknown,unknown,motorpasion, +87,"noticias de la ciencia",https://noticiasdelaciencia.com/,unknown,"multiple releases",,es,spain,science,"text (web)",manual,,unknown,unknown,"noticias de la ciencia", +88,"aplatanaonews - todo está en el contenido!",https://aplatanaonews.com/,unknown,"multiple releases",,es,"domenican republic","general news","text (web)",manual,,unknown,unknown,"aplatanaonews - todo está en el contenido!", +89,"subrayado hd",http://www.subrayado.com.uy/site/home.aspx,unknown,"multiple releases",,es,uruguay,"general news","text (web)",manual,,unknown,unknown,"subrayado hd", +90,peru',http://peru.com/,unknown,"multiple releases",,es,peru,"general news","text (web)",manual,,unknown,unknown,peru', +91,diario26,http://www.diario26.com/general.html,unknown,"multiple releases",,es,argentina,"general news","text (web)",manual,,unknown,unknown,diario26, +92,"diario de navarra",http://www.diariodenavarra.es/,unknown,"multiple releases",,es,spain,"general news","text (web)",manual,,unknown,unknown,"diario de navarra", +93,"canal antigua",https://canalantigua.tv/,unknown,"multiple releases",,es,gt,"general news","text (web)",manual,,unknown,unknown,"canal antigua", +94,"real instituto elcano",http://www.realinstitutoelcano.org/wps/portal/rielcano_es,unknown,"multiple releases",,es,spain,"general news","text (web)",manual,,unknown,unknown,"real instituto elcano", +95,"el mañana - tamaulipas",http://www.elmanana.com/,unknown,"multiple releases",,es,mexico,"general news","text (web)",manual,,unknown,unknown,"el mañana - tamaulipas", +96,"abc digital - paraguay",http://www.abc.com.py/,unknown,"multiple releases",,es,paraguay,"general news","text (web)",manual,,unknown,unknown,"abc digital - paraguay", +97,ielektro,https://ielektro.es/,unknown,"multiple releases",,es,spain,"general news","text (web)",manual,,unknown,unknown,ielektro, +98,"vtv uruguay",http://www.vtv.com.uy/,unknown,"multiple releases",,es,uruguay,"general news","text (web)",manual,,unknown,unknown,"vtv uruguay", +99,"periódico correo",http://www.periodicocorreo.com.mx/,unknown,"multiple releases",,es,mexico,"general news","text (web)",manual,,unknown,unknown,"periódico correo", 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diff --git a/data_tooling/cc_pseudo_crawl/sourcing_sheet_seeds/cc-metrics.ipynb b/data_tooling/cc_pseudo_crawl/sourcing_sheet_seeds/cc-metrics.ipynb new file mode 100644 index 0000000..0680c04 --- /dev/null +++ b/data_tooling/cc_pseudo_crawl/sourcing_sheet_seeds/cc-metrics.ipynb @@ -0,0 +1,810 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "attractive-vampire", + "metadata": {}, + "source": [ + "# Coverage Metrics\n", + "\n", + "Having followed the [general instructions](../README.md) to join the seed list with Common Crawl's index, the following query aggregates metrics per site:\n", + "\n", + "```sql\n", + "SELECT id,\n", + " title,\n", + " link,\n", + " language,\n", + " COUNT(*) AS captures_total,\n", + " cardinality(approx_set(url_surtkey)) AS urls_uniq_estimate,\n", + " SUM(warc_record_length) AS warc_size_in_bytes,\n", + " CAST(histogram(content_languages) AS JSON) AS content_languages,\n", + " CAST(histogram(content_mime_detected) AS JSON) AS content_type,\n", + " CAST(histogram(substr(crawl, 9, 4)) AS JSON) AS captures_per_year,\n", + " CAST(histogram(crawl) AS JSON) AS captures_per_crawl\n", + "FROM bigscience.cc\n", + "WHERE subset = 'warc'\n", + "GROUP BY id, title, link, language\n", + "```\n", + "\n", + "The result is exported as CSV - [cc-metrics.csv](./cc-metrics.csv)." + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "wireless-stewart", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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idtitlelinklanguagecaptures_totalurls_uniq_estimatewarc_size_in_bytescontent_languagescontent_typescaptures_per_yearcaptures_per_crawl
0162aeh2http://www.aeh2.orges3039123380847151{\"eng\":7,\"eng,spa\":307,\"spa\":767,\"spa,cat\":1,\"...{\"application/pdf\":19,\"application/xhtml+xml\":...{\"2020\":1762,\"2021\":1277}{\"CC-MAIN-2020-05\":195,\"CC-MAIN-2020-10\":128,\"...
1198el economista [spain]http://www.eleconomista.es/es43810622410212713758424{\"cat\":45,\"eng\":179,\"eng,fra,spa\":562,\"eng,ind...{\"application/font-woff\":1,\"application/pdf\":1...{\"2020\":194215,\"2021\":243891}{\"CC-MAIN-2020-05\":23904,\"CC-MAIN-2020-10\":185...
2296majadahonda magazinhttps://majadahondamagazin.es/es1821110608533454607{\"eng,spa\":8,\"fra,spa\":1,\"spa\":17371,\"spa,cat\"...{\"application/pdf\":22,\"application/rss+xml\":1,...{\"2020\":15638,\"2021\":2573}{\"CC-MAIN-2020-05\":2168,\"CC-MAIN-2020-10\":2006...
3192noticias ahorahttps://www.noticias-ahora.com/es106632730462634752488{\"deu,bod,nno\":1,\"eng\":5,\"eng,spa\":157,\"spa\":6...{\"text/html\":106632}{\"2020\":55385,\"2021\":51247}{\"CC-MAIN-2020-05\":5035,\"CC-MAIN-2020-10\":4972...
430radiocablehttp://www.radiocable.com/es93152192561092879146{\"cat\":6,\"eng\":137,\"eng,glg\":8,\"eng,glg,oci\":1...{\"application/rss+xml\":9,\"application/xhtml+xm...{\"2020\":45590,\"2021\":47562}{\"CC-MAIN-2020-05\":3779,\"CC-MAIN-2020-10\":4998...
\n", + "
" + ], + "text/plain": [ + " id title link language \\\n", + "0 162 aeh2 http://www.aeh2.org es \n", + "1 198 el economista [spain] http://www.eleconomista.es/ es \n", + "2 296 majadahonda magazin https://majadahondamagazin.es/ es \n", + "3 192 noticias ahora https://www.noticias-ahora.com/ es \n", + "4 30 radiocable http://www.radiocable.com/ es \n", + "\n", + " captures_total urls_uniq_estimate warc_size_in_bytes \\\n", + "0 3039 1233 80847151 \n", + "1 438106 224102 12713758424 \n", + "2 18211 10608 533454607 \n", + "3 106632 73046 2634752488 \n", + "4 93152 19256 1092879146 \n", + "\n", + " content_languages \\\n", + "0 {\"eng\":7,\"eng,spa\":307,\"spa\":767,\"spa,cat\":1,\"... \n", + "1 {\"cat\":45,\"eng\":179,\"eng,fra,spa\":562,\"eng,ind... \n", + "2 {\"eng,spa\":8,\"fra,spa\":1,\"spa\":17371,\"spa,cat\"... \n", + "3 {\"deu,bod,nno\":1,\"eng\":5,\"eng,spa\":157,\"spa\":6... \n", + "4 {\"cat\":6,\"eng\":137,\"eng,glg\":8,\"eng,glg,oci\":1... \n", + "\n", + " content_types \\\n", + "0 {\"application/pdf\":19,\"application/xhtml+xml\":... \n", + "1 {\"application/font-woff\":1,\"application/pdf\":1... \n", + "2 {\"application/pdf\":22,\"application/rss+xml\":1,... \n", + "3 {\"text/html\":106632} \n", + "4 {\"application/rss+xml\":9,\"application/xhtml+xm... \n", + "\n", + " captures_per_year \\\n", + "0 {\"2020\":1762,\"2021\":1277} \n", + "1 {\"2020\":194215,\"2021\":243891} \n", + "2 {\"2020\":15638,\"2021\":2573} \n", + "3 {\"2020\":55385,\"2021\":51247} \n", + "4 {\"2020\":45590,\"2021\":47562} \n", + "\n", + " captures_per_crawl \n", + "0 {\"CC-MAIN-2020-05\":195,\"CC-MAIN-2020-10\":128,\"... \n", + "1 {\"CC-MAIN-2020-05\":23904,\"CC-MAIN-2020-10\":185... \n", + "2 {\"CC-MAIN-2020-05\":2168,\"CC-MAIN-2020-10\":2006... \n", + "3 {\"CC-MAIN-2020-05\":5035,\"CC-MAIN-2020-10\":4972... \n", + "4 {\"CC-MAIN-2020-05\":3779,\"CC-MAIN-2020-10\":4998... " + ] + }, + "execution_count": 1, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "import pandas as pd\n", + "\n", + "df = pd.read_csv('cc-metrics.csv')\n", + "\n", + "df.head()" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "numerical-official", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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idtitlelinklanguagecaptures_totalurls_uniq_estimatewarc_size_in_bytescontent_languagescontent_typescaptures_per_yearcaptures_per_crawl
253497News outlethttps://www.straitstimes.com/en58080642340122705382276{\"eng\":574438,\"eng,ara\":9,\"eng,ben\":1,\"eng,cat...{\"application/pdf\":291,\"application/rss+xml\":1...{\"2020\":277490,\"2021\":303316}{\"CC-MAIN-2020-05\":32519,\"CC-MAIN-2020-10\":272...
136333el mundo (spain)http://www.elmundo.es/es49924240985013946919763{\"cat\":5,\"cat,spa\":466,\"cat,spa,deu\":1,\"cat,sp...{\"application/json\":3,\"application/rss+xml\":7,...{\"2020\":235654,\"2021\":263588}{\"CC-MAIN-2020-05\":32370,\"CC-MAIN-2020-10\":288...
31063la nacion (argentina)http://www.lanacion.com.ar/es49684838289720352476991{\"eng\":42,\"eng,spa\":78,\"lat,spa\":1,\"spa\":46433...{\"application/rss+xml\":2,\"text/html\":496843,\"t...{\"2020\":218658,\"2021\":278190}{\"CC-MAIN-2020-05\":29451,\"CC-MAIN-2020-10\":239...
109307europa presshttps://www.europapress.es/es49201744847915435990919{\"cat,spa\":2548,\"cat,spa,eng\":103,\"cat,spa,grn...{\"application/octet-stream\":40,\"application/rs...{\"2020\":204451,\"2021\":287566}{\"CC-MAIN-2020-05\":23867,\"CC-MAIN-2020-10\":207...
326255el comercio perúhttps://elcomercio.pe/es48987536121616227224839{\"eng\":3,\"eng,spa\":93,\"eng,spa,cat\":2,\"que,spa...{\"application/xhtml+xml\":4,\"image/jpeg\":1,\"tex...{\"2020\":229643,\"2021\":260232}{\"CC-MAIN-2020-05\":22913,\"CC-MAIN-2020-10\":316...
\n", + "
" + ], + "text/plain": [ + " id title link language \\\n", + "253 497 News outlet https://www.straitstimes.com/ en \n", + "136 333 el mundo (spain) http://www.elmundo.es/ es \n", + "310 63 la nacion (argentina) http://www.lanacion.com.ar/ es \n", + "109 307 europa press https://www.europapress.es/ es \n", + "326 255 el comercio perú https://elcomercio.pe/ es \n", + "\n", + " captures_total urls_uniq_estimate warc_size_in_bytes \\\n", + "253 580806 423401 22705382276 \n", + "136 499242 409850 13946919763 \n", + "310 496848 382897 20352476991 \n", + "109 492017 448479 15435990919 \n", + "326 489875 361216 16227224839 \n", + "\n", + " content_languages \\\n", + "253 {\"eng\":574438,\"eng,ara\":9,\"eng,ben\":1,\"eng,cat... \n", + "136 {\"cat\":5,\"cat,spa\":466,\"cat,spa,deu\":1,\"cat,sp... \n", + "310 {\"eng\":42,\"eng,spa\":78,\"lat,spa\":1,\"spa\":46433... \n", + "109 {\"cat,spa\":2548,\"cat,spa,eng\":103,\"cat,spa,grn... \n", + "326 {\"eng\":3,\"eng,spa\":93,\"eng,spa,cat\":2,\"que,spa... \n", + "\n", + " content_types \\\n", + "253 {\"application/pdf\":291,\"application/rss+xml\":1... \n", + "136 {\"application/json\":3,\"application/rss+xml\":7,... \n", + "310 {\"application/rss+xml\":2,\"text/html\":496843,\"t... \n", + "109 {\"application/octet-stream\":40,\"application/rs... \n", + "326 {\"application/xhtml+xml\":4,\"image/jpeg\":1,\"tex... \n", + "\n", + " captures_per_year \\\n", + "253 {\"2020\":277490,\"2021\":303316} \n", + "136 {\"2020\":235654,\"2021\":263588} \n", + "310 {\"2020\":218658,\"2021\":278190} \n", + "109 {\"2020\":204451,\"2021\":287566} \n", + "326 {\"2020\":229643,\"2021\":260232} \n", + "\n", + " captures_per_crawl \n", + "253 {\"CC-MAIN-2020-05\":32519,\"CC-MAIN-2020-10\":272... \n", + "136 {\"CC-MAIN-2020-05\":32370,\"CC-MAIN-2020-10\":288... \n", + "310 {\"CC-MAIN-2020-05\":29451,\"CC-MAIN-2020-10\":239... \n", + "109 {\"CC-MAIN-2020-05\":23867,\"CC-MAIN-2020-10\":207... \n", + "326 {\"CC-MAIN-2020-05\":22913,\"CC-MAIN-2020-10\":316... " + ] + }, + "execution_count": 2, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# top sites by captures\n", + "df.sort_values('captures_total', ascending=False).head()" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "eligible-subsection", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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idtitlelinklanguagecaptures_totalurls_uniq_estimatewarc_size_in_bytescontent_languagescontent_typescaptures_per_yearcaptures_per_crawl
167316la jornadahttp://www.jornada.unam.mx/ultimases1145869{\"spa\":1}{\"application/xhtml+xml\":1}{\"2020\":1}{\"CC-MAIN-2020-10\":1}
388283la prensa graficahttp://www.laprensagrafica.com/inicioes1112698{\"spa\":1}{\"text/html\":1}{\"2020\":1}{\"CC-MAIN-2020-45\":1}
223110onemi: ministerio del interior y seguridad púb...http://www.onemi.cl/es2212559{\"spa\":1}{\"text/html\":2}{\"2020\":1,\"2021\":1}{\"CC-MAIN-2020-34\":1,\"CC-MAIN-2021-17\":1}
67326la opinión de tenerifehttp://www.laopinion.es/es517763{\"spa\":5}{\"text/html\":5}{\"2020\":4,\"2021\":1}{\"CC-MAIN-2020-10\":1,\"CC-MAIN-2020-16\":1,\"CC-M...
49234conredhttps://conred.gob.gt/emergencia/es61103054{\"spa\":6}{\"text/html\":6}{\"2021\":6}{\"CC-MAIN-2021-04\":1,\"CC-MAIN-2021-17\":1,\"CC-M...
\n", + "
" + ], + "text/plain": [ + " id title \\\n", + "167 316 la jornada \n", + "388 283 la prensa grafica \n", + "223 110 onemi: ministerio del interior y seguridad púb... \n", + "67 326 la opinión de tenerife \n", + "49 234 conred \n", + "\n", + " link language captures_total \\\n", + "167 http://www.jornada.unam.mx/ultimas es 1 \n", + "388 http://www.laprensagrafica.com/inicio es 1 \n", + "223 http://www.onemi.cl/ es 2 \n", + "67 http://www.laopinion.es/ es 5 \n", + "49 https://conred.gob.gt/emergencia/ es 6 \n", + "\n", + " urls_uniq_estimate warc_size_in_bytes content_languages \\\n", + "167 1 45869 {\"spa\":1} \n", + "388 1 12698 {\"spa\":1} \n", + "223 2 12559 {\"spa\":1} \n", + "67 1 7763 {\"spa\":5} \n", + "49 1 103054 {\"spa\":6} \n", + "\n", + " content_types captures_per_year \\\n", + "167 {\"application/xhtml+xml\":1} {\"2020\":1} \n", + "388 {\"text/html\":1} {\"2020\":1} \n", + "223 {\"text/html\":2} {\"2020\":1,\"2021\":1} \n", + "67 {\"text/html\":5} {\"2020\":4,\"2021\":1} \n", + "49 {\"text/html\":6} {\"2021\":6} \n", + "\n", + " captures_per_crawl \n", + "167 {\"CC-MAIN-2020-10\":1} \n", + "388 {\"CC-MAIN-2020-45\":1} \n", + "223 {\"CC-MAIN-2020-34\":1,\"CC-MAIN-2021-17\":1} \n", + "67 {\"CC-MAIN-2020-10\":1,\"CC-MAIN-2020-16\":1,\"CC-M... \n", + "49 {\"CC-MAIN-2021-04\":1,\"CC-MAIN-2021-17\":1,\"CC-M... " + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# sites with few captures\n", + "df.sort_values('captures_total', ascending=True).head()" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "demonstrated-memorabilia", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "1.5254639124050977" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# ratio of URL-level duplicates (same URL captured multiple times)\n", + "df['captures_total'].sum() / df['urls_uniq_estimate'].sum()" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "effective-heating", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "880.5133517915383" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# total size of WARC captures (in GiB)\n", + "df['warc_size_in_bytes'].sum() / 2**30" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "awful-behalf", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[('spa', 25916905),\n", + " ('spa,eng', 4126880),\n", + " ('eng', 2534447),\n", + " ('spa,cat', 1275211),\n", + " ('zho', 324001),\n", + " ('eng,spa', 205587),\n", + " ('cat,spa', 124009),\n", + " ('spa,grn', 110074),\n", + " ('spa,cat,eng', 58611),\n", + " ('ita,eng', 51301)]" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# distribution of content languages (detected by CLD2)\n", + "\n", + "import json\n", + "\n", + "from collections import Counter\n", + "\n", + "cl = df['content_languages'].apply(json.loads)\n", + "\n", + "def count_dict(counter, counts):\n", + " for k in counts:\n", + " counter[k] += counts[k]\n", + "\n", + "language_counts = Counter()\n", + "cl.apply(lambda c: count_dict(language_counts, c))\n", + "language_counts.most_common(10)" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "contained-armenia", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[('spa', 31859638),\n", + " ('eng', 2784731),\n", + " ('zho', 339086),\n", + " ('cat', 156437),\n", + " ('ita', 52791),\n", + " ('eus', 11682),\n", + " ('glg', 10859),\n", + " ('fra', 3233),\n", + " ('nld', 713),\n", + " ('ind', 532)]" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# distribution of content languages, primary language only\n", + "\n", + "def keep_primary_language_only(counts):\n", + " res = Counter()\n", + " for lang in counts:\n", + " res[lang[0:3]] += counts[lang]\n", + " return res\n", + "\n", + "cl = cl.apply(keep_primary_language_only)\n", + "\n", + "primary_language_counts = Counter()\n", + "cl.apply(lambda c: count_dict(primary_language_counts, c))\n", + "primary_language_counts.most_common(10)" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "british-surfing", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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01
0text/html31535762
1application/xhtml+xml3744758
2application/pdf68266
3text/plain24513
4application/rss+xml20988
5image/jpeg7541
6application/atom+xml4555
7application/json1194
8application/xml541
9image/png501
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" + ], + "text/plain": [ + " 0 1\n", + "0 text/html 31535762\n", + "1 application/xhtml+xml 3744758\n", + "2 application/pdf 68266\n", + "3 text/plain 24513\n", + "4 application/rss+xml 20988\n", + "5 image/jpeg 7541\n", + "6 application/atom+xml 4555\n", + "7 application/json 1194\n", + "8 application/xml 541\n", + "9 image/png 501" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# content types (MIME types detected by Tika)\n", + "\n", + "ct = df['content_types'].apply(json.loads)\n", + "\n", + "mime_counts = Counter()\n", + "ct.apply(lambda c: count_dict(mime_counts, c))\n", + "pd.DataFrame.from_records(mime_counts.most_common(10))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "piano-custom", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.9.7" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/data_tooling/cc_pseudo_crawl/sourcing_sheet_seeds/cleanup-seeds.ipynb b/data_tooling/cc_pseudo_crawl/sourcing_sheet_seeds/cleanup-seeds.ipynb new file mode 100644 index 0000000..3ae9d1e --- /dev/null +++ b/data_tooling/cc_pseudo_crawl/sourcing_sheet_seeds/cleanup-seeds.ipynb @@ -0,0 +1,1225 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "professional-crime", + "metadata": {}, + "source": [ + "# Seed List Cleanup\n", + "\n", + "Prepare a clean list of seeds (candidates for pseudo-crawls)\n", + "- add columns required to get page locations and metrics from Common Crawl\n", + "- remove duplicated seeds\n", + "- normalize URLs" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "indian-aquarium", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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#Dataset titleDomain Name / link\\n(if highlighted in red, it's a duplicate! So don't add it...)License\\n(default is UNKNOWN)Release (Issue date)GlottocodeLanguage(s) (or family)Dialect/accent (if known)SubjectFormatCollection Style (Manual Curation vs Crowdsourced(web)) ?What it is / why we want it (5-25 words)Volume (estimates)Contains Personal Information? (-1=unlikely, 0=neutral, 1=likely)OwnerUsage and relation to other datasets
012Fundacion Cajasolhttps://fundacioncajasol.com/unknownmultiple releasesstan1288esSpainGeneral Newstext (web)manualNaNunknownunknownFundacion CajasolNaN
113Asamblea Nacional del Ecuadorhttp://www.confirmado.net/unknownmultiple releasesNaNesEcuadorGeneral Newstext (web)manualNaNunknownunknownAsamblea Nacional del EcuadorNaN
214el periodico de Tlaxcalahttps://elperiodicodetlaxcala.com/unknownmultiple releasesNaNesMexicoGeneral Newstext (web)manualNaNunknownunknownel periodico de TlaxcalaNaN
315mispeceshttps://www.mispeces.com/unknownmultiple releasesNaNesSpainGeneral Newstext (web)manualNaNunknownunknownmispecesNaN
416DiarioVascohttps://www.diariovasco.com/unknownmultiple releasesNaNesSpainGeneral Newstext (web)manualNaNunknownunknownDiarioVascoNaN
\n", + "
" + ], + "text/plain": [ + " # Dataset title \\\n", + "0 12 Fundacion Cajasol \n", + "1 13 Asamblea Nacional del Ecuador \n", + "2 14 el periodico de Tlaxcala \n", + "3 15 mispeces \n", + "4 16 DiarioVasco \n", + "\n", + " Domain Name / link\\n(if highlighted in red, it's a duplicate! So don't add it...) \\\n", + "0 https://fundacioncajasol.com/ \n", + "1 http://www.confirmado.net/ \n", + "2 https://elperiodicodetlaxcala.com/ \n", + "3 https://www.mispeces.com/ \n", + "4 https://www.diariovasco.com/ \n", + "\n", + " License\\n(default is UNKNOWN) Release (Issue date) Glottocode \\\n", + "0 unknown multiple releases stan1288 \n", + "1 unknown multiple releases NaN \n", + "2 unknown multiple releases NaN \n", + "3 unknown multiple releases NaN \n", + "4 unknown multiple releases NaN \n", + "\n", + " Language(s) (or family) Dialect/accent (if known) Subject Format \\\n", + "0 es Spain General News text (web) \n", + "1 es Ecuador General News text (web) \n", + "2 es Mexico General News text (web) \n", + "3 es Spain General News text (web) \n", + "4 es Spain General News text (web) \n", + "\n", + " Collection Style (Manual Curation vs Crowdsourced(web)) ? \\\n", + "0 manual \n", + "1 manual \n", + "2 manual \n", + "3 manual \n", + "4 manual \n", + "\n", + " What it is / why we want it (5-25 words) Volume (estimates) \\\n", + "0 NaN unknown \n", + "1 NaN unknown \n", + "2 NaN unknown \n", + "3 NaN unknown \n", + "4 NaN unknown \n", + "\n", + " Contains Personal Information? (-1=unlikely, 0=neutral, 1=likely) \\\n", + "0 unknown \n", + "1 unknown \n", + "2 unknown \n", + "3 unknown \n", + "4 unknown \n", + "\n", + " Owner Usage and relation to other datasets \n", + "0 Fundacion Cajasol NaN \n", + "1 Asamblea Nacional del Ecuador NaN \n", + "2 el periodico de Tlaxcala NaN \n", + "3 mispeces NaN \n", + "4 DiarioVasco NaN " + ] + }, + "execution_count": 1, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "import pandas as pd\n", + "\n", + "df = pd.read_csv('candidate_websites_for_crawling.csv')\n", + "\n", + "df.head()" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "retired-template", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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idtitlelinklanguage
012Fundacion Cajasolhttps://fundacioncajasol.com/es
113Asamblea Nacional del Ecuadorhttp://www.confirmado.net/es
214el periodico de Tlaxcalahttps://elperiodicodetlaxcala.com/es
315mispeceshttps://www.mispeces.com/es
416DiarioVascohttps://www.diariovasco.com/es
\n", + "
" + ], + "text/plain": [ + " id title link \\\n", + "0 12 Fundacion Cajasol https://fundacioncajasol.com/ \n", + "1 13 Asamblea Nacional del Ecuador http://www.confirmado.net/ \n", + "2 14 el periodico de Tlaxcala https://elperiodicodetlaxcala.com/ \n", + "3 15 mispeces https://www.mispeces.com/ \n", + "4 16 DiarioVasco https://www.diariovasco.com/ \n", + "\n", + " language \n", + "0 es \n", + "1 es \n", + "2 es \n", + "3 es \n", + "4 es " + ] + }, + "execution_count": 2, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# select mandatory columns and assign simple and SQL-compatible column names\n", + "df = df.iloc[:, [0,1,2,6]]\n", + "df.columns = ['id', 'title', 'link', 'language']\n", + "df.head()" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "floppy-connection", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(456, 4)" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.shape" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "least-religious", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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/391
13
/es/6
/wps/portal/rielcano_es2
/forums/2
/web/1
/es1
/singapore1
/informa1
/forum/1
/es/news1
/mining/1
/community1
/news/es1
/pagina/bienvenidos-al-comite-de-sanidad-vegetal-cosave1
/ultimas1
/index.php/es1
/spanish/1
/kiasu1
/tecnopunta1
/search/label/primera1
/r/singapore/1
/blog/1
/site/1
/presidencia/1
/index.php/riesed1
/index.php/es/1
/upotec1
/emergencia/1
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/home/es/1
/endirecto/1
/noticias-guatemala-diario-centro-america/1
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/index.php/riceg/index1
/portal/1
/noticias1
/ww5/1
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" + ], + "text/plain": [ + " url_path_prefix\n", + "/ 391\n", + " 13\n", + "/es/ 6\n", + "/wps/portal/rielcano_es 2\n", + "/forums/ 2\n", + "/web/ 1\n", + "/es 1\n", + "/singapore 1\n", + "/informa 1\n", + "/forum/ 1\n", + "/es/news 1\n", + "/mining/ 1\n", + "/community 1\n", + "/news/es 1\n", + "/pagina/bienvenidos-al-comite-de-sanidad-vegeta... 1\n", + "/ultimas 1\n", + "/index.php/es 1\n", + "/spanish/ 1\n", + "/kiasu 1\n", + "/tecnopunta 1\n", + "/search/label/primera 1\n", + "/r/singapore/ 1\n", + "/blog/ 1\n", + "/site/ 1\n", + "/presidencia/ 1\n", + "/index.php/riesed 1\n", + "/index.php/es/ 1\n", + "/upotec 1\n", + "/emergencia/ 1\n", + "/portada 1\n", + "/home/es/ 1\n", + "/endirecto/ 1\n", + "/noticias-guatemala-diario-centro-america/ 1\n", + "/en/ 1\n", + "/cadiz/ 1\n", + "/news/ 1\n", + "/monplaneta/ 1\n", + "/web/sala-de-prensa 1\n", + "/noticias/ 1\n", + "/envivo/ 1\n", + "/inicio 1\n", + "/va/inicio/presentacion 1\n", + "/index.php/riceg/index 1\n", + "/portal/ 1\n", + "/noticias 1\n", + "/ww5/ 1\n", + "/alacarta/ 1" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# normalize URLs and look for obsolete path prefixes\n", + "from urllib.parse import urlparse\n", + "\n", + "def normalize_url(url):\n", + " if url == 'reddit.com/r/singapore':\n", + " url = 'https://www.reddit.com/r/singapore/'\n", + " u = urlparse(url)\n", + " path = u.path\n", + " path = path.replace('//', '/')\n", + " # normalize empty path (root path)\n", + " if path == '':\n", + " path = '/'\n", + " # remove trailing file name\n", + " if path[-1] != '/' and '.' in path.split('/')[-1]:\n", + " path = '/'.join(path.split('/')[:-2])\n", + " return '%s://%s%s' % (u.scheme, u.netloc, path)\n", + "\n", + "def get_path_prefix(url):\n", + " return urlparse(url).path\n", + "\n", + "df['link'] = df['link'].apply(normalize_url)\n", + "df['url_path_prefix'] = df['link'].apply(get_path_prefix)\n", + "\n", + "df['url_path_prefix'].value_counts().to_frame()" + ] + }, + { + "cell_type": "markdown", + "id": "hungry-fever", + "metadata": {}, + "source": [ + "Some path prefixes seem to be mandatory\n", + "- language selectors: `/es/`, `/spanish/`\n", + "- location selectors: `/r/singapore/` (reddit.com)\n", + "\n", + "Others only point to the homepage and would limit the recall to just this page:\n", + "- `/search/label/inicio`, `/pagina/bienvenidos-al-comite-de-sanidad-vegetal-cosave`\n", + "\n", + "For now: we keep only prefixes up to 16 characters. However, clean curated URL prefixes might improve the data set in future runs." + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "super-happiness", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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url_path_prefix
/400
13
/es/6
/forums/2
/web/1
/presidencia/1
/es1
/informa1
/forum/1
/mining/1
/news/es1
/site/1
/blog/1
/spanish/1
/index.php/es1
/kiasu1
/tecnopunta1
/inicio1
/r/singapore/1
/ultimas1
/portal/1
/index.php/es/1
/ww5/1
/emergencia/1
/portada1
/home/es/1
/es/news1
/endirecto/1
/singapore1
/community1
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" + ], + "text/plain": [ + " url_path_prefix\n", + "/ 400\n", + " 13\n", + "/es/ 6\n", + "/forums/ 2\n", + "/web/ 1\n", + "/presidencia/ 1\n", + "/es 1\n", + "/informa 1\n", + "/forum/ 1\n", + "/mining/ 1\n", + "/news/es 1\n", + "/site/ 1\n", + "/blog/ 1\n", + "/spanish/ 1\n", + "/index.php/es 1\n", + "/kiasu 1\n", + "/tecnopunta 1\n", + "/inicio 1\n", + "/r/singapore/ 1\n", + "/ultimas 1\n", + "/portal/ 1\n", + "/index.php/es/ 1\n", + "/ww5/ 1\n", + "/emergencia/ 1\n", + "/portada 1\n", + "/home/es/ 1\n", + "/es/news 1\n", + "/endirecto/ 1\n", + "/singapore 1\n", + "/community 1\n", + "/cadiz/ 1\n", + "/news/ 1\n", + "/upotec 1\n", + "/monplaneta/ 1\n", + "/noticias/ 1\n", + "/envivo/ 1\n", + "/en/ 1\n", + "/noticias 1\n", + "/alacarta/ 1" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "def normalize_path_prefix(url):\n", + " u = urlparse(url)\n", + " path = u.path\n", + " if len(path) > 16:\n", + " path = '/'\n", + " return '%s://%s%s' % (u.scheme, u.netloc, path)\n", + "\n", + "df['link'] = df['link'].apply(normalize_path_prefix)\n", + "df['url_path_prefix'] = df['link'].apply(get_path_prefix)\n", + "\n", + "df['url_path_prefix'].value_counts().to_frame()" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "monetary-final", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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idtitlelinklanguageurl_path_prefixurl_host_nameurl_host_registered_domainurl_surtkey
012Fundacion Cajasolhttps://fundacioncajasol.com/es/fundacioncajasol.comfundacioncajasol.comcom,fundacioncajasol)/
113Asamblea Nacional del Ecuadorhttp://www.confirmado.net/es/www.confirmado.netconfirmado.netnet,confirmado)/
214el periodico de Tlaxcalahttps://elperiodicodetlaxcala.com/es/elperiodicodetlaxcala.comelperiodicodetlaxcala.comcom,elperiodicodetlaxcala)/
315mispeceshttps://www.mispeces.com/es/www.mispeces.commispeces.comcom,mispeces)/
416DiarioVascohttps://www.diariovasco.com/es/www.diariovasco.comdiariovasco.comcom,diariovasco)/
\n", + "
" + ], + "text/plain": [ + " id title link \\\n", + "0 12 Fundacion Cajasol https://fundacioncajasol.com/ \n", + "1 13 Asamblea Nacional del Ecuador http://www.confirmado.net/ \n", + "2 14 el periodico de Tlaxcala https://elperiodicodetlaxcala.com/ \n", + "3 15 mispeces https://www.mispeces.com/ \n", + "4 16 DiarioVasco https://www.diariovasco.com/ \n", + "\n", + " language url_path_prefix url_host_name \\\n", + "0 es / fundacioncajasol.com \n", + "1 es / www.confirmado.net \n", + "2 es / elperiodicodetlaxcala.com \n", + "3 es / www.mispeces.com \n", + "4 es / www.diariovasco.com \n", + "\n", + " url_host_registered_domain url_surtkey \n", + "0 fundacioncajasol.com com,fundacioncajasol)/ \n", + "1 confirmado.net net,confirmado)/ \n", + "2 elperiodicodetlaxcala.com com,elperiodicodetlaxcala)/ \n", + "3 mispeces.com com,mispeces)/ \n", + "4 diariovasco.com com,diariovasco)/ " + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# add columns required to get the counts from Common Crawl\n", + "\n", + "import surt\n", + "import tldextract\n", + "\n", + "def get_host(url):\n", + " return urlparse(url).netloc.lower().lstrip('.')\n", + "\n", + "def get_surtkey(url):\n", + " return surt.surt(url)\n", + "\n", + "def get_registered_domain(host):\n", + " return tldextract.extract(host).registered_domain\n", + "\n", + "\n", + "df['url_host_name'] = df['link'].apply(get_host)\n", + "df['url_host_registered_domain'] = df['url_host_name'].apply(get_registered_domain)\n", + "df['url_surtkey'] = df['link'].apply(get_surtkey)\n", + "\n", + "df.head()" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "happy-aspect", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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idtitlelinklanguageurl_path_prefixurl_host_nameurl_host_registered_domainurl_surtkey
6072elcano royal insitute (real istituto elcano)http://www.realinstitutoelcano.org/es/www.realinstitutoelcano.orgrealinstitutoelcano.orgorg,realinstitutoelcano)/
8294real instituto elcanohttp://www.realinstitutoelcano.org/es/www.realinstitutoelcano.orgrealinstitutoelcano.orgorg,realinstitutoelcano)/
\n", + "
" + ], + "text/plain": [ + " id title \\\n", + "60 72 elcano royal insitute (real istituto elcano) \n", + "82 94 real instituto elcano \n", + "\n", + " link language url_path_prefix \\\n", + "60 http://www.realinstitutoelcano.org/ es / \n", + "82 http://www.realinstitutoelcano.org/ es / \n", + "\n", + " url_host_name url_host_registered_domain \\\n", + "60 www.realinstitutoelcano.org realinstitutoelcano.org \n", + "82 www.realinstitutoelcano.org realinstitutoelcano.org \n", + "\n", + " url_surtkey \n", + "60 org,realinstitutoelcano)/ \n", + "82 org,realinstitutoelcano)/ " + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# look for duplicates\n", + "df[df.duplicated(subset=['url_surtkey'], keep=False)]" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "sudden-terror", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(455, 8)" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# deduplicate\n", + "df.drop_duplicates(subset=['url_surtkey'], inplace=True)\n", + "df.shape" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "atomic-portuguese", + "metadata": {}, + "outputs": [], + "source": [ + "# export the clean seed list\n", + "df.to_csv('seeds.csv', index=False)\n", + "df.to_parquet('seeds.gz.parquet', compression='gzip', index=False)" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.9.7" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/data_tooling/datastore/README.md b/data_tooling/datastore/README.md new file mode 100644 index 0000000..cd8c36b --- /dev/null +++ b/data_tooling/datastore/README.md @@ -0,0 +1,15 @@ +# Extensions to Huggingface's datasets + +Creates a datastore that interconnects to sqlite and memmap backends. + +## Run + +* Run the python script + +``` +cd data_tooling +pip install -r requirements.txt +python datastore/tests/test.py +``` + +## TODO list diff --git a/data_tooling/datastore/__init__.py b/data_tooling/datastore/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/data_tooling/datastore/connectors/__init__.py b/data_tooling/datastore/connectors/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/data_tooling/datastore/connectors/memmap.py b/data_tooling/datastore/connectors/memmap.py new file mode 100644 index 0000000..9b4dbf2 --- /dev/null +++ b/data_tooling/datastore/connectors/memmap.py @@ -0,0 +1,25 @@ +import os + +import numpy as np + +################################################################################################################################# +# Code for utilities related Dask distributed arrays and np.memmap based array access + + +def np_mmap(path, dtype, shape, orig_path=None, fs=None): + if os.path.exists(path): + return np.memmap( + filename=path, + mode="r+", + dtype=np.dtype(dtype), + shape=tuple(shape), + offset=offset, + ) + else: + return np.memmap( + filename=path, + mode="w+", + dtype=np.dtype(dtype), + shape=tuple(shape), + offset=offset, + ) diff --git a/data_tooling/datastore/connectors/sql.py b/data_tooling/datastore/connectors/sql.py new file mode 100644 index 0000000..83e6978 --- /dev/null +++ b/data_tooling/datastore/connectors/sql.py @@ -0,0 +1,1035 @@ +# Copyright 2021, Ontocord, LLC +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +""" Utilities to access dataset's SqlAlchemy sql utilities""" + +import os +import sys +from functools import lru_cache + +import dataset +from dataset.types import Types +from dataset.util import ( + QUERY_STEP, + DatasetException, + ResultIter, + convert_row, + normalize_table_name, + row_type, +) +from sqlalchemy import create_engine +from sqlalchemy.engine.reflection import Inspector +from sqlalchemy.exc import ResourceClosedError +from sqlalchemy.pool import StaticPool +from sqlalchemy.schema import MetaData +from sqlalchemy.sql import text +from sqlalchemy.util import safe_reraise + +sys.path.append( + os.path.abspath( + os.path.join( + os.path.dirname(__file__), os.path.pardir, os.path.pardir, os.path.pardir + ) + ) +) + + +###################################################################################### +# SqlAlchemy/Dataset based classes for interconnect with SQL, and in particular sqlite3 +### A note about naming: dataset and datasets are not the same libraries. + + +def multi_iter_result_proxy(rps, step=None, batch_fns=None, row_types=row_type): + """Iterate over the ResultProxyExt.""" + for batch_fn, row_type, rp in zip(batch_fns, row_types, rps): + if step is None: + chunk = rp.fetchall() + else: + chunk = rp.fetchmany(size=step) + if batch_fn is not None: + chunk = batch_fn(chunk) + if not chunk: + next + if row_type is None: + for row in chunk: + yield row + else: + for row in chunk: + yield convert_row(row_type, row) + + +class ResultIterExt: + """Similar to dataset.ResultIter except thre are several + result_proxies, and they are actually results that are lazy + executed. Optionally, the results can be treated as a sql table via .to_sql() + """ + + def __init__(self, result_proxy, step=None, row_type=row_type, batch_fn=None): + self.persisted = None + if type(result_proxy) is not list: + result_proxy = [result_proxy] + self.result_proxy = result_proxy + if type(row_type) is not list: + self.row_type = [row_type] * len(self.result_proxy) + else: + self.row_type = row_type + if type(batch_fn) is not list: + self.batch_fn = [batch_fn] * len(self.result_proxy) + else: + self.batch_fn = batch_fn + self.step = step + try: + self.keys = list(self.result_proxy[0].keys()) + # self.keys.append('rank') + # print (self.keys) + self._iter = multi_iter_result_proxy( + self.result_proxy, + step=self.step, + batch_fns=self.batch_fn, + row_types=self.row_type, + ) + except ResourceClosedError: + self.keys = [] + self._iter = iter([]) + + def to_sql(self, primary_id="id", primary_type=None, primary_increment=None): + if self.persisted is not None: + return self.persisted + self.persisted = TableExt( + DatabaseExt("sqlite://"), + str(self), + primary_id=primary_id, + primary_type=primary_type, + primary_increment=primary_increment, + auto_create=True, + ) + self.persisted.insert_many(self) + self._iter = multi_iter_result_proxy( + self.persisted.db.executable.execute(self.persisted.table.select()), + row_types=self.row_type, + ) + return self.persisted + + # extending while iterating will cause undefined behaviour + def extend(self, result_iter): + self.result_proxy.extend(result_iter.result_proxy) + self.batch_fn.extend(result_iter.batch_fn) + self.row_type.extend(result_iter.row_type) + if self.persisted: + self.persisted.insert_many(result_iter) + self._iter = multi_iter_result_proxy( + self.persisted.db.executable.execute(self.persisted.table.select()), + row_types=self.row_type, + ) + else: + try: + self._iter = multi_iter_result_proxy( + self.result_proxy, + step=self.step, + batch_fns=self.batch_fn, + row_types=self.row_type, + ) + except ResourceClosedError: + self.keys = [] + self._iter = iter([]) + + def __next__(self): + try: + return next(self._iter) + except StopIteration: + self.close() + raise + + next = __next__ + + def __iter__(self): + return self + + def close(self): + for rp in self.result_proxy: + rp.close() + + +class TableSharded(dataset.Table): + PRIMARY_DEFAULT = "id" + + """ Extends dataset.Table's functionality to work with + Datastore(s) and to add sqlite full-text-search (FTS). Can be a + view into several sharded tables in one or more databases. Sharded + by the row primary id. + + We can treat sqlite databases in a special way because they are + file based, and we lazy load those from a network or shared fs, + etc. + """ + + def __init__( + self, + database=None, + table_name=None, + primary_id=None, + primary_type=None, + primary_increment=None, + auto_create=False, + shard_defs=None, + start_row=None, + end_row=None, + fs=None, + ): + super().__init__( + database, + table_name, + primary_id=primary_id, + primary_type=primary_type, + primary_increment=primary_increment, + auto_create=auto_create, + ) + assert shards is not None or database is not None + self.auto_create = auto_create + self.start_row = start_row + self.start_row = end_row + if shard_dres: + shard_defs.sort(key=lambda a: a["start_row"]) + else: + shard_defs = [] + self.shard_defs = shard_defs + self._shards = [None] * len( + shard_defs + ) # TODO - use LRU cache so we can clear out db connecitons that are old or stale + if fs is None: + fs = os + self.fs = fs + if cache_dir is None: + cache_dir = get_temporary_cache_files_directory() + self.cache_dir = cache_dir + auto_create = False + super(PersistedRowShards).__init(shard_defs, fs) + # TODO: automatically fill in external_fts_columns and has_fts_trigger in the _sync* methods. + self.external_fts_columns = {} + self.has_fts_trigger = False + + def cache_shard_file(self, idx, f): + shard_def = self.shard_defs[idx] + fs = self.fs + dataset_path = self.cache_dir + if is_remote_filesystem(fs): + f_dataset_path = extract_path_from_uri(f) + data_path = Path(dataset_path, f_dataset_path) + fs.download(f_dataset_path, data_path.as_posix(), recursive=True) + next(wait_until_files_loaded(f)) + return f + + @lru_cache(100) + def shards(self, idx): + shard = self._shard_by_idx(idx) + shard.start_row = self.shard_defs["start_row"] + shard.end_row = self.shard_defs["end_row"] + return shard + + def _shard_by_idx(self, idx): + shard_def = self.shard_defs[idx] + if shard_def["database_kwargs"] and "url" in shard_def["database_kwargs"]: + url = shard_def["database_kwargs"]["url"] + if url.startswith("sqlite:///"): + new_path = "sqlite:///" + self.cache_shard_file( + idx, url.replace("sqlite:///", "") + ) + shard_def = copy.deepcopy(shard_def) + shard_def["database_kwargs"]["url"] = url + elif shard_def["database_args"]: + url = shard_def["database_args"] + if url.startswith("sqlite:///"): + new_path = "sqlite:///" + self.cache_shard_file( + idx, url.replace("sqlite:///", "") + ) + shard_def = copy.deepcopy(shard_def) + shard_def["database_args"] = [url] + return TableSharded( + database=DatabaseExt( + *shard_def["database_args"], **shard_def["database_kwargs"] + ), + table_name=self.name, + primary_id=self._primary_id, + primary_type=self._primary_type, + primary_increment=self._primary_increment, + auto_create=self.auto_create, + start_row=shard_def["start_row"], + end_row=shard_def["end_row"], + ) + + def _sync_all_shards(self): + if self.shards_defs: + for idx, shard_def, shard in enumerate(self.shard_defs): + self.shards(idx) + + @property + def exists(self): + """Check to see if the table currently exists in the database.""" + if self.shards: + self._sync_all_shards() + for shard in self.shards: + if shard.exits: + return True + return False + else: + return super().exits + + @property + def table(self): + """Get a reference to the table, which may be reflected or created.""" + if self.shards_defs: + return self.shards(0).table + else: + return super().table + + @property + def columns(self): + """Get a listing of all columns that exist in the table.""" + if self.shards_defs: + return self.shards(0).columns + else: + return super().columns + + def has_column(self, column): + """Check if a column with the given name exists on this table.""" + if self.shards_defs: + return self.shards(0).has_column(column) + else: + return super().has_column(column) + + def create_column(self, name, type, **kwargs): + """Create a new column ``name`` of a specified type. + :: + + table.create_column('created_at', db.types.datetime) + + `type` corresponds to an SQLAlchemy type as described by + `dataset.db.Types`. Additional keyword arguments are passed + to the constructor of `Column`, so that default values, and + options like `nullable` and `unique` can be set. + :: + + table.create_column('key', unique=True, nullable=False) + table.create_column('food', default='banana') + """ + if self.shards_defs: + for idx in range(len(self.shards_defs)): + shard = self.shards(idx) + shard.create_column(name, type, **kwargs) + else: + super().create_column(name, type, **kwargs) + + def create_column_by_example(self, name, value): + """ + Explicitly create a new column ``name`` with a type that is appropriate + to store the given example ``value``. The type is guessed in the same + way as for the insert method with ``ensure=True``. + :: + + table.create_column_by_example('length', 4.2) + + If a column of the same name already exists, no action is taken, even + if it is not of the type we would have created. + """ + if self.shards_defs: + for idx in range(len(self.shards_defs)): + shard = self.shards(idx) + shard.create_column_by_example(name, value) + else: + super().create_column_by_example(name, value) + + def drop_column(self, name): + """ + Drop the column ``name``. + :: + + table.drop_column('created_at') + + """ + if self.shards_defs: + for idx in range(len(self.shards_defs)): + shard = self.shards(idx) + shard.drop_column(column) + else: + super().drop_column(column) + + def drop(self): + """Drop the table from the database. + + Deletes both the schema and all the contents within it. + """ + if self.shards_defs: + for idx in range(len(self.shards_defs)): + shard = self.shards(idx) + shard.drop() + else: + super().drop() + + def has_index(self, columns): + """Check if an index exists to cover the given ``columns``.""" + if self.shards_defs: + for idx in range(len(self.shards_defs)): + shard = self.shards(idx) + if shard.has_index(columns): + return True + return False + else: + return super().has_index(columns) + + def create_index(self, columns, name=None, **kw): + """Create an index to speed up queries on a table. + + If no ``name`` is given a random name is created. + :: + + table.create_index(['name', 'country']) + """ + if self.shards_defs: + for idx in range(len(self.shards_defs)): + shard = self.shards(idx) + shard.create_index(columns, name, **kw) + else: + super().create_index(columns, name, **kw) + + def find(self, *_clauses, **kwargs): + """Perform a search on the table similar to + dataset.Table.find, except: optionally gets a result only for + specific columns by passing in _columns keyword. And + optionally perform full-text-search (BM25) on via a Sqlite3 + table. + + :arg _fts_query: + :arg _fts_step: + :arg _columns: + + Simply pass keyword arguments as ``filter``. + :: + results = table.find(country='France') + results = table.find(country='France', year=1980) + Using ``_limit``:: + # just return the first 10 rows + results = table.find(country='France', _limit=10) + You can sort the results by single or multiple columns. Append a minus + sign to the column name for descending order:: + # sort results by a column 'year' + results = table.find(country='France', order_by='year') + # return all rows sorted by multiple columns (descending by year) + results = table.find(order_by=['country', '-year']) + To perform complex queries with advanced filters or to perform + aggregation, use :py:meth:`db.query() ` + instead. + """ + + if not self.exists: + return iter([]) + + if self.shards: + self._sync_all_shards() + if "_count" in kwargs: + return sum( + shard + for shard in sellf.find( + *copy.deepcopy(_clauses), **copy.deepcopy(kwargs) + ) + ) + if self._primary_id in kwargs: + # do the case where we have specific id ranges. we pass in the queries by row id. + ids = kwars[self._primary_id]["in"] + ids.sort() + ret = None + shards_defs = self.shards_defs + shard_idx = 0 + curr_ids = [] + for idx, _id in enumerate(ids): + if not shard_defs: + break + if len(shards_defs) == 1: + curr_ids = ids[idx:] + break + if ( + _id >= shards_defs[0]["start_row"] + and _id <= shards_defs[0]["end_row"] + ): + curr_ids.append(_id) + elif _id > shards_defs[0]["end_row"]: + if curr_ids: + kwargs_shard = copy.deepcopy(kwargs) + kwargs_shard[self._primary_id] = {"in": curr_ids} + if not ret: + ret = self.shards(shard_idx).find( + *copy.deepcopy(_clauses), **kwargs_shard + ) + else: + ret.extend( + self.shards(shard_idx).find( + *copy.deepcopy(_clauses), **kwargs_shard + ) + ) + shards_defs = shards_defs[1:] + shard_idx += 1 + curr_ids = [_id] + if curr_ids: + kwargs_shard = copy.deepcopy(kwargs) + kwargs_shard[self._primary_id] = {"in": curr_ids} + if not ret: + ret = self.shards(shard_idx).find( + *copy.deepcopy(_clauses), **kwargs_shard + ) + else: + ret.extend( + self.shards(shard_idx).find( + *copy.deepcopy(_clauses), **kwargs_shard + ) + ) + return ret + else: + ret = [] + for idx in range(len(self.shards_defs)): + shard = self.shards(idx) + if not ret: + ret = shard.find( + *copy.deepcopy(_clauses), **copy.deepcopy(kwargs) + ) + else: + ret.extend( + shard.find( + *copy.deepcopy(_clauses), **copy.deepcopy(kwargs) + ) + ) + return ret + + _fts_query = kwargs.pop("_fts_query", None) + _count = kwargs.pop("_count", None) + _fts_step = kwargs.pop("_fts_step", QUERY_STEP) + _columns = kwargs.pop("_columns", None) + _distinct = kwargs.pop("_distinct", None) + _limit = kwargs.pop("_limit", None) + _offset = kwargs.pop("_offset", 0) + order_by = kwargs.pop("order_by", None) + _streamed = kwargs.pop("_streamed", False) + _step = kwargs.pop("_step", QUERY_STEP) + + assert ( + _count is None or _columns is None + ), "can only get the count when not selecting by columns" + + if _fts_query and _step < _fts_step: + _step = _fts_step + if _step is False or _step == 0: + _step = None + if type(_columns) is str: + _columns = [_columns] + fts_results = [] + if _fts_query is None: + _fts_query = [] + id2rank = {} + return_id2rank_only = False + for column, q in _fts_query: + if column in self.external_fts_columns: + db, fts_table_name = self.external_fts_columns[column] + else: + # if the table being searched is an fts_idx (ends with + # _fts_idx), assume there are other tables for each of + # the columns being search in the format of + # _colummn_fts_idx + if self.name.endswith(f"_fts_idx"): + if self.name.endswith(f"_{column}_fts_idx"): + db, fts_table_name = self.db, self.name + else: + db, fts_table_name = ( + self.db, + "_".join(self.name.replace("_fts_idx", "").split("_")[:-1]) + + f"_{column}_fts_idx", + ) + return_id2rank_only = True + else: + db, fts_table_name = self.db, f"{self.name}_{column}_fts_idx" + # TODO: check if sqlite3 + q = q.replace("'", "'") + if _limit is not None: + # using _limit is a hack. we want a big enough result + # from fts so that subsequent query will narrow down to a + # good result at _limit, but we don't want all results + # which could be huge. we can set the fts_max_limit as a + # parameter to the table or db level. + if kwargs: + new_limit = _limit * 10 + else: + new_limit = _limit + else: + new_limit = 1000000 + args2 = "" + if self._primary_id in kwargs: + kwargs2 = {"rowid": kwargs[self._primary_id]} + args2 = self._args_to_clause(kwargs2).replace("WHERE", "AND") + + fts_results = db.executable.execute( + f"""SELECT rank, rowid + FROM {fts_table_name} + WHERE {column} MATCH '{q}' {args2} + ORDER BY rank + LIMIT {new_limit}""" + ).fetchall() + if not fts_results: + return [] + for a in fts_results: + id2rank[a[1]] = min(a[0], id2rank.get(a[1], 1000)) + + # we do an optimization here by just returning the id and/or rank, if there are no queries except for the id and/or rank + if id2rank and ( + ( + _columns + and ((self._primary_id,) == tuple(columns)) + or ((self._primary_id, "rank") == tuple(_columns)) + ) + or return_id2rank_only + ): + ret = list(id2rank.items()) + ret.sort(key=lambda a: a[0]) + if _columns and len(_columns) == 1: + return [a[1] for a in ret] + else: + return [{self._primary_id: a[1], "rank": a[0]} for a in ret] + if return_id2rank_only: + return [] + order_by = self._args_to_order_by(order_by) + conn = self.db.executable + + if _streamed: + conn = self.db.engine.connect() + conn = conn.execution_options(stream_results=True) + + # if the fts_results are quite large let's issue several queries by fts_step, and return an iterator with a lazy execution. + batch_fn = None + results = [] + row_type_fn = self.db.row_type + if id2rank: + fts_results = list(id2rank.items()) + fts_results.sort(key=lambda a: a[0]) + len_fts_results = len(fts_results) + total_cnt = 0 + for rng in range(0, len_fts_results, _fts_step): + max_rng = min(len_fts_results, rng + _fts_step) + kwargs[self._primary_id] = { + "in": [int(a[1]) for a in fts_results[rng:max_rng]] + } + args = self._args_to_clause(kwargs, clauses=_clauses) + + if _columns is None: + if _count: + query = select([func.count()], whereclause=args) + query = query.select_from( + self.table, limit=_limit, offset=_offset + ) + else: + query = self.table.select( + whereclause=args, limit=_limit, offset=_offset + ) + else: + query = self.table.select( + whereclause=args, limit=_limit, offset=_offset + ).with_only_columns([self.table.c[col] for col in _columns]) + if len(order_by): + query = query.order_by(*order_by) + if _count: + total_cnt += conn.execute(query).fetchone()[0] + else: + results.append(conn.execute(query)) + + if len(order_by): + + def row_type_fn(row): + row = convert_row(self.db.row_type, row) + row["rank"] = id2rank[row[self._primary_id]] + return row + + else: + # we will need to reorder the results based on the rank of the fts_results. + def batch_fn(batch): + batch2 = [] + for row in batch: + row = convert_row(self.db.row_type, row) + row["rank"] = id2rank[row[self._primary_id]] + batch2.append(row) + batch2.sort(key=lambda a: a["rank"]) + return batch2 + + row_type_fn = None + if _count: + return total_cnt + else: + args = self._args_to_clause(kwargs, clauses=_clauses) + if _columns is None: + query = self.table.select( + whereclause=args, distinct=_distinct, limit=_limit, offset=_offset + ) + else: + query = self.table.select( + whereclause=args, distinct=_distinct, limit=_limit, offset=_offset + ).with_only_columns([self.table.c[col] for col in _columns]) + + if len(order_by): + query = query.order_by(*order_by) + if _count: + return conn.execute(query).fetchone()[0] + results = [conn.execute(query)] + return ResultIterExt( + results, row_type=row_type_fn, step=_step, batch_fn=batch_fn + ) + + def count(self, *_clauses, **kwargs): + """Return the count of results for the given filter set.""" + if not self.exists: + return 0 + kwargs["_count"] = True + return self.find(*_clauses, **kwargs) + + def __len__(self): + """Return the number of rows in the table.""" + return self.count() + + def distinct(self, *args, **_filter): + if not self.exists: + return iter([]) + columns = [] + clauses = [] + for column in args: + if isinstance(column, ClauseElement): + clauses.append(column) + else: + if not self.has_column(column): + raise DatasetException("No such column: %s" % column) + columns.append(column) + if not len(columns): + return iter([]) + _filter["_columns"] = columns + _filter["_distinct"] = True + return self.filter(*clauses, **_filter) + + def apply_to_shards(self, rows, fn, fn_kwargs): + rows.sort() + ret = None + shards = self.shards + curr_rows = [] + for idx, _id in enumerate(rows): + if len(shards) == 1: + curr_rows = rows[idx:] + break + if _id >= shard[0].start_row and _id <= shard[0].end_row: + curr_rows.append(_id) + elif _id > shard[0].end_row: + if curr_rows: + kwargs_shard = copy.deepcopy(kwargs) + kwargs_shard[self._primary_id] = {"in": curr_rows} + if not ret: + ret = shard.find(*copy.deepcopy(_clauses), **kwargs_shard) + else: + ret.extend(shard.find(*copy.deepcopy(_clauses), **kwargs_shard)) + shards = shards[1:] + curr_rows = [_id] + if curr_rows: + kwargs_shard = copy.deepcopy(kwargs) + kwargs_shard[self._primary_id] = {"in": curr_rows} + if not ret: + ret = shard.find(*copy.deepcopy(_clauses), **kwargs_shard) + else: + ret.extend(shard.find(*copy.deepcopy(_clauses), **kwargs_shard)) + return ret + else: + ret = [] + for shard in self.shards: + if not ret: + ret = shard.find(*copy.deepcopy(_clauses), **copy.deepcopy(kwargs)) + else: + ret.extend( + shard.find(*copy.deepcopy(_clauses), **copy.deepcopy(kwargs)) + ) + return ret + + def update(self, row, keys, ensure=None, types=None, return_count=False): + if self.shards: + self._sync_all_shards() + row = self._sync_columns(row, ensure, types=types) + if [_ for column in row.keys() if column in self.external_fts_columns]: + args, row = self._keys_to_args(row, keys) + old = list(self.find(**args)) + else: + old = None + ret = super().update( + row, keys=keys, ensure=ensure, types=types, return_count=return_count + ) + if old: + for key in row.keys(): + self.update_fts(column=key, old_data=old, new_data=row, mode="update") + return ret + + def update_many(self, rows, keys, chunk_size=1000, ensure=None, types=None): + rows = self._sync_columns(rows, ensure=ensure, types=types) + if [_ for column in rows[0].keys() if column in self.external_fts_columns]: + args, row = self._keys_to_args(rows, keys) # this probably won't work + old = list(self.find(**args)) + else: + old = None + ret = super().update_many( + rows, keys=keys, chunk_size=chunk_size, ensure=ensure, types=types + ) + if old: + for key in rows[0].keys(): + self.update_fts(column=key, old_data=old, new_data=rows, mode="update") + return ret + + def delete(self, *clauses, **filters): + if self.external_fts_columns: + old = list(self.find(*clauses, **filters)) + if old: + for key in old[0].keys(): + self.update_fts(column=key, old_data=old, mode="delete") + return super().delete(*clauses, **filters) + + def insert(self, row, ensure=None, types=None): + """Add a ``row`` dict by inserting it into the table. + If ``ensure`` is set, any of the keys of the row are not + table columns, they will be created automatically. + During column creation, ``types`` will be checked for a key + matching the name of a column to be created, and the given + SQLAlchemy column type will be used. Otherwise, the type is + guessed from the row value, defaulting to a simple unicode + field. + :: + data = dict(title='I am a banana!') + table.insert(data) + Returns the inserted row's primary key. + """ + # either sqlalachemy or the underlying sqlite database starts auto-numbering at 1. we want to auto-number starting at 0 + # we shold probably check the count of the row, but this would require a round trip + # to the db on each insert, so we'll make the assumption of lazy creation + if ( + not self.exists or not self.has_column(self._primary_id) + ) and self._primary_type in (Types.integer, Types.bigint): + row[self._primary_id] = 0 + ret = super().insert(row, ensure=ensure, types=types) + for key in row.keys(): + self.update_fts(column=key, new_data=row, mode="insert") + return ret + + def insert_many(self, rows, chunk_size=1000, ensure=None, types=None): + """Add many rows at a time. + This is significantly faster than adding them one by one. Per default + the rows are processed in chunks of 1000 per commit, unless you specify + a different ``chunk_size``. + See :py:meth:`insert() ` for details on + the other parameters. + :: + rows = [dict(name='Dolly')] * 10000 + table.insert_many(rows) + """ + + row = copy.copy(rows[0]) + rows[0] = row + if ( + (not self.exists or not self.has_column(self._primary_id)) + and self._primary_type in (Types.integer, Types.bigint) + and self._primary_id not in row + ): + row[self._primary_id] = 0 + ret = super().insert_many( + rows, chunk_size=chunk_size, ensure=ensure, types=types + ) + for key in row.keys(): + self.update_fts(column=key, new_data=rows, mode="insert") + return ret + + # create a sqlite fts index for a column in this table + def create_fts_index_column(self, column, stemmer="unicode61", db=None): # porter + if db is None: + db = self.db + if not db.is_sqlite: + raise RuntimeError("the db for the fts index must be sqlite") + table_name = self.name + if not self.has_column(column): + self.create_column_by_example(column, "**") + fts_table_name = f"{table_name}_{column}_fts_idx" + db.create_fts_index( + fts_table_name, stemmer=stemmer, column=column, table_name=table_name + ) + self.external_fts_columns[column] = (db, fts_table_name) + + # sqlite3 fts manual updates. we create TableSharded level updates when we don't have actual triggers in the sqlite3 database. + def update_fts(self, column, new_data=None, old_data=None, mode="insert"): + if column != self._primary_id and column in self.external_fts_columns: + db, fts_table_name = self.external_fts_columns[column] + db.update_fts( + fts_table_name, + column=column, + new_data=new_data, + old_data=old_data, + mode=mode, + primary_id=self._primary_id, + ) + + +class DatabaseExt(dataset.Database): + """A DatabaseExt textends dataset.Database and represents a SQL database with multiple tables of type TableSharded.""" + + def __init__(self, *args, **kwargs): + """Configure and connect to the database.""" + super().__init__(*args, **kwargs) + + def create_fts_index( + self, fts_table_name, stemmer, column, table_name=None, primary_id="id" + ): + if not self.is_sqlite: + raise RuntimeError("cannot create sqlite fts index in non sqlite table") + if fts_table_name not in self.tables: + if table_name: + self.executable.execute( + f"CREATE VIRTUAL TABLE {fts_table_name} USING fts5({column}, tokenize='{stemmer}', content='{table_name}', content_rowid='{primary_id}');" + ) + table = self.create_table(fts_table_name, primary_id="rowid") + table.has_fts_trigger = True + self.executable.execute( + f"CREATE TRIGGER {table_name}_{column}_ai AFTER INSERT ON {table_name} BEGIN INSERT INTO {fts_table_name} (rowid, {column}) VALUES (new.{primary_id}, new.{column}); END;" + ) + self.executable.execute( + f"CREATE TRIGGER {table_name}_{column}_ad AFTER DELETE ON {table_name} BEGIN INSERT INTO {fts_table_name} ({fts_table_name}, rowid, {column}) VALUES('delete', old.{primary_id}, old.{column}); END;" + ) + self.executable.execute( + f"CREATE TRIGGER {table_name}_{column}_au AFTER UPDATE OF {column} ON {table_name} BEGIN INSERT INTO {fts_table_name} ({fts_table_name}, rowid, {column}) VALUES('delete', old.{primary_id}, old.{column}); INSERT INTO {table_name}_{column}_fts_idx(rowid, {column}) VALUES (new.{primary_id}, new.{column}); END;" + ) + else: + self.executable.execute( + f"CREATE VIRTUAL TABLE {fts_table_name} USING fts5({column}, content='');" + ) + table = self.create_table(fts_table_name, primary_id="rowid") + table.has_fts_trigger = False + + else: + # do we want to warn? + print(f"warning: {fts_table_name} already in database") + return + + # update the sqlite3 fts index + def update_fts( + self, + fts_table_name, + column, + new_data=None, + old_data=None, + mode="insert", + primary_id="id", + ): + if not self.is_sqlite: + raise RuntimeError("applying an fts update to a db that is not sqlite") + if old_data is None and mode != "insert": + raise RuntimeError( + f"need to provide old data in order to update or delete the fts" + ) + if fts_table_name not in self.tables: + raise RuntimeError(f"there is no fts index column for {column}") + fts_table = self[fts_table_name] + if not hasattr(fts_table, "has_fts_trigger") or not fts_table.has_fts_trigger: + return + if (new_data and type(new_data) is not list) or ( + old_data and type(old_data) is not list + ): + if mode in ("update", "delete"): + fts_table.insert( + { + fts_table_name: "delete", + "rowid": old_data[primary_id], + column: old_data[column], + } + ) + if mode in ("update", "insert"): + fts_table.insert( + {"rowid": new_data[primary_id], column: new_data[column]} + ) + else: + if mode in ("update", "delete"): + old_data = copy.deepcopy(old_data) + for data in old_data: + data["rowid"] = data[primary_id] + data[fts_table_name] = "delete" + del data[primary_id] + for key in list(data.keys()): + if key not in (fts_table_name, "rowid", column): + del data[key] + fts_table.insert_many(old_data) + if mode in ("update", "insert"): + new_data = copy.deepcopy(new_data) + for data in new_data: + data["rowid"] = data[primary_id] + del data[primary_id] + for key in list(data.keys()): + if key not in ("rowid", column): + del data[key] + fts_table.insert_many(new_data) + + def create_table( + self, table_name, primary_id=None, primary_type=None, primary_increment=None + ): + """Create a new table. + Either loads a table or creates it if it doesn't exist yet. You can + define the name and type of the primary key field, if a new table is to + be created. The default is to create an auto-incrementing integer, + ``id``. You can also set the primary key to be a string or big integer. + The caller will be responsible for the uniqueness of ``primary_id`` if + it is defined as a text type. You can disable auto-increment behaviour + for numeric primary keys by setting `primary_increment` to `False`. + Returns a :py:class:`Table ` instance. + :: + table = db.create_table('population') + # custom id and type + table2 = db.create_table('population2', 'age') + table3 = db.create_table('population3', + primary_id='city', + primary_type=db.types.text) + # custom length of String + table4 = db.create_table('population4', + primary_id='city', + primary_type=db.types.string(25)) + # no primary key + table5 = db.create_table('population5', + primary_id=False) + """ + assert not isinstance( + primary_type, str + ), "Text-based primary_type support is dropped, use db.types." + table_name = normalize_table_name(table_name) + with self.lock: + if table_name not in self._tables: + self._tables[table_name] = TableSharded( + self, + table_name, + primary_id=primary_id, + primary_type=primary_type, + primary_increment=primary_increment, + auto_create=True, + ) + return self._tables.get(table_name) + + def load_table(self, table_name): + """Load a table. + This will fail if the tables does not already exist in the database. If + the table exists, its columns will be reflected and are available on + the :py:class:`Table ` object. + Returns a :py:class:`Table ` instance. + :: + table = db.load_table('population') + """ + table_name = normalize_table_name(table_name) + with self.lock: + if table_name not in self._tables: + self._tables[table_name] = TableSharded(self, table_name) + return self._tables.get(table_name) diff --git a/data_tooling/datastore/datastore_base.py b/data_tooling/datastore/datastore_base.py new file mode 100644 index 0000000..3b083fa --- /dev/null +++ b/data_tooling/datastore/datastore_base.py @@ -0,0 +1,1976 @@ +# Copyright 2021, Ontocord, LLC +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +""" A datastore based on Huggingface's datasets that connects to sqlite and memmap""" + +import atexit +import copy +import itertools +import json +import os +import shutil +import sys +import tempfile +from collections.abc import Iterable +from dataclasses import asdict, field +from functools import partial +from pathlib import Path, PurePath +from typing import Callable, Dict, List, Optional, Union + +import dataset +import fsspec.compression +import numpy as np +import pandas as pd +import pyarrow as pa +import requests +import six +from dataset.types import Types +from dataset.util import ( + QUERY_STEP, + DatasetException, + ResultIter, + convert_row, + normalize_table_name, + row_type, +) +from datasets import Dataset, config, utils +from datasets.arrow_dataset import transmit_format +from datasets.arrow_writer import ArrowWriter, OptimizedTypedSequence +from datasets.dataset_dict import DatasetDict +from datasets.features import ( + Features, + PandasArrayExtensionArray, + PandasArrayExtensionDtype, + Value, + cast_to_python_objects, + pandas_types_mapper, +) +from datasets.filesystems import extract_path_from_uri, is_remote_filesystem +from datasets.fingerprint import ( + fingerprint_transform, + generate_fingerprint, + generate_random_fingerprint, + get_temporary_cache_files_directory, + is_caching_enabled, + update_fingerprint, +) +from datasets.info import DatasetInfo +from datasets.search import BaseIndex, BatchedSearchResults, SearchResults +from datasets.splits import NamedSplit +from datasets.table import InMemoryTable, concat_tables +from datasets.tasks import TaskTemplate +from datasets.utils import logging, map_nested +from datasets.utils.typing import PathLike +from pandas import DataFrame, read_csv +from six.moves.urllib.parse import parse_qs, urlparse +from sqlalchemy import create_engine +from sqlalchemy.engine.reflection import Inspector +from sqlalchemy.exc import ResourceClosedError +from sqlalchemy.pool import StaticPool +from sqlalchemy.schema import MetaData +from sqlalchemy.sql import text +from sqlalchemy.util import safe_reraise +from torch import nn + +sys.path.append( + os.path.abspath( + os.path.join(os.path.dirname(__file__), os.path.pardir, os.path.pardir) + ) +) + + +from data_tooling.datastore.connectors.memmap import * +from data_tooling.datastore.connectors.sql import * +from data_tooling.datastore.utils import * + +###################################################################################### +# Extensions to Huggingface's datasets to create a datastore that +# interconnects to sqlite and memmap +# +# We want to have mutliple types of storage that ideally can be +# transported as a file transfer with an arrow dataset (perhaps a tar +# file?). So if we have .arrow, we may have +# fts_.db (for full text indexing sqlite database) and +# .db (sqlite database), and .mmap (mmap file +# reprsenting a tensor) + +# NOTE: datasets uses the terms 'features' and 'columns' interchangably. + + +class Datastore(Dataset): + """ + A class that wraps a Huggingface arrow based Dataset to provide + support for features bound to memmap and sqlalchemy via the + package datastore. + + Also permits full text indexing and searching (via .filter or + .search) into a sqlite database for any text feature in a + datastore. + """ + + def __repr__(self): + ret = FeaturesWithViews(self._info.features) + ret.views_map = {} if not hasattr(self, "views_map") else self.views_map + return f"Datastore({{\n features: {ret},\n num_rows: {self.num_rows}\n}})" + + @classmethod + def from_dataset( + cls, + dataset, + template_datastore=None, + views_map=None, + primary_id=None, + id2idx_identity=None, + ): + self = cls( + arrow_table=dataset._data, + indices_table=dataset._indices, + info=dataset.info.copy(), + split=dataset.split, + fingerprint=dataset._fingerprint, + ) + if template_datastore is None: + template_datastore = dataset + self.mmap_access_cnt = 0 + + if hasattr(dataset, "id2idx_identity"): + self.id2idx_identity = dataset.id2idx_identity + elif id2idx_identity is not None: + self.id2idx_identity = id2idx_identity + elif hasattr(template_datastore, "id2idx_identity"): + self.id2idx_identity = template_datastore.id2idx_identity + else: + self.id2idx_identity = True + + if hasattr(dataset, "_primary_id"): + self._primary_id = dataset._primary_id + elif primary_id is not None: + self._primary_id = primary_id + elif hasattr(template_datastore, "_primary_id"): + self._primary_id = template_datastore._primary_id + else: + self._primary_id = "id" + + if hasattr(dataset, "views_map"): + self.views_map = copy.deepcopy(dataset.views_map) + elif views_map is not None: + self.views_map = copy.deepcopy(views_map) + elif hasattr(template_datastore, "views_map"): + self.views_map = copy.deepcopy(template_datastore.views_map) + else: + self.views_map = {} + + return self + + def _get_mmap(self, path, dtype, shape): + shape[0] = max(shape[0], len(self)) + # what happens when the datastore shrinks?? + ret = np_mmap(path, dtype, shape) + if not hasattr(self, "mmap_access_cnt"): + self.mmap_access_cnt = 0 + if ( + self.mmap_access_cnt % 100 == 0 + ): # let's flush intermittently just in case the OS needs to synch. + ret.flush() + self.mmap_access_cnt = 0 + self.mmap_access_cnt += 1 + return ret + + # we use class variables to cache sql connections because we don't + # want it serialized in this instance. TODO: this might take up + # too much memory, so we might use an LRU cache instead. + db_table = {} + + def _get_db_table(self, feature): + if feature in self.views_map and self.views_map[feature]["type"] == "sql": + table_name, connection_url = val["table_name"], val["connection_uri"] + if (table_name, connection_uri) in Datastore.db_table: + table = Datastore.db_table[(table_name, connection_uri)] + else: + if connection_uri in Datastore.db_connection: + db = Datastore.db_connection[connection_uri] + else: + Datastore.db_connection[connection_uri] = db = DatabaseExt( + connection_uri + ) + Datastore.db_table[(table_name, connection_uri)] = table = db[ + table_name + ] + return table + else: + raise RuntimeError(f"{feature} is not a sql type") + + @staticmethod + def _add_idx( + batch, + indices, + primary_id, + ): + batch[primary_id] = indices # will this be shuffled if we are in shuffled mode? + return batch + + @staticmethod + def _move_to_mmap_col(batch, src_feature, primary_id, path, dtype, shape): + ret = np_mmap(path, dtype, shape) + ret[batch[primary_id]] = batch[src_feature] + + @classmethod + def from_mmap( + cls, + feature_view, + shape, + path=None, + dtype="float32", + dtype_str_len=100, + primary_id="id", + batch_size=1000, + num_proc=4, + ): + return cls.from_dict({}).add_mmap( + feature_view=feature_view, + shape=shape, + path=path, + dtype=dtype, + dtype_str_len=dtype_str_len, + primary_id=primary_id, + batch_size=batch_size, + num_proc=num_proc, + ) + + def move_to_mmap( + self, + src_feature, + dst_feature_view=None, + shape=None, + path=None, + dtype="float32", + dtype_str_len=100, + primary_id="id", + batch_size=1000, + num_proc=4, + ): + """ "move data from the src_feature to a memmap file that is viewed via dst_feature_view""" + if dst_feature_view in (src_feature, None): + self = self.rename_column(src_feature, "__tmp__" + src_feature) + dst_feature_view = src_feature + src_feature = "__tmp__" + src_feature + if shape is None: + item = self[0][src_feature] + if type(item) == np.ndarray: + shape = item.shape + dtype = item.dtype + elif type(item) == "str": + dtype = "unicode" + shape = [-1, max(len(item), dtype_str_len)] + elif type(item) == "int": + dtype = "int32" + shape = [-1, 1] + elif type(item) == "float": + dtype = "float32" + shape = [-1, 1] + else: + raise RuntimeError( + f"could not infer shape and dtype for example {item}" + ) + shape[0] = max(shape[0], len(self)) + self.add_mmap( + feature_view=dst_feature_view, + shape=shape, + path=path, + dtype=dtype, + primary_id=primary_id, + batch_size=batch_size, + num_proc=num_proc, + ) + val = self.views_map[dst_feature_view] + self.map( + Datastore._move_to_mmap_col, + batch_size=batch_size, + batched=True, + num_proc=num_proc, + fn_kwargs={ + "src_feature": src_feature, + "primary_id": primary_id, + "path": val["path"], + "dtype": val["dtype"], + "shape": shape, + }, + ) + self = self.remove_columns(src_feature) + return self + + def add_mmap( + self, + feature_view, + shape, + path=None, + dtype="float32", + dtype_str_len=100, + primary_id="id", + batch_size=1000, + num_proc=4, + ): + """ "mapping a feature/columun to a memmap array accessed by row""" + if not hasattr(self, "views_map"): + self.views_map = {} + if hasattr(self, "_primary_id") and self._primary_id != primary_id: + raise RuntimeError(f"attempting to reset the index to {primary_id}") + else: + self._primary_id = _primary_id + if not self.cache_files: + dataset_path = get_temporary_cache_files_directory() + else: + dataset_path = os.path.dirname(self.cache_files[0]["filename"]) + if path is None: + path = os.path.abspath(os.path.join(dataset_path, feature_view + ".mmap")) + shape = list(shape) + shape[0] = max(shape[0], len(self)) + if primary_id not in self.features: + if len(self) == 0 and shape[0] > 0: + self = Datastore.from_dataset( + Dataset.from_dict({primary_id: range(shape[0])}), self + ) + ids = {a: 1 for a in range(len(self))} + self.id2idx_identity = True + else: + self = self.map( + Datastore._add_idx, + with_indices=True, + batch_size=batch_size, + batched=True, + num_proc=num_proc, + fn_kwargs={"primary_id": primary_id}, + ) + ids = {a: 1 for a in range(len(self))} + self.id2idx_identity = True + else: + ids = {a: 1 for a in self[primary_id]} + missing_ids = [] + for id in range(shape[0]): + if id not in ids: + missing_ids.append(id) + if missing_ids: + self = self.add_batch({primary_id: missing_ids}) + if not hasattr(self, "id2idx_identity"): + self.id2idx_identity = True + if self.id2idx_identity: + contiguous, start, end = is_contiguous(missing_ids) + self.id2idx_identity = start == len(self) and contiguous + else: + self.id2idx_identity = False + if not isinstance(dtype, str): + dtype = np.dtype(dtype).name + + self.views_map[feature_view] = { + "type": "mmap", + "path": path, + "dtype": dtype, + "shape": shape, + } + return self + + def move_to_sql( + self, + src_feature_to_dst_views_map, + table_name=None, + connection_uri=None, + primary_id="id", + batch_size=1000, + num_proc=4, + fts_connection_uri=None, + ): + if table_name is None: + # print (self.info.builder_name, self.info.config_name) + table_name = f"_{self._fingerprint}_{self.info.builder_name}_{self.info.config_name}_{self.split}" + if not connection_uri: + connection_uri = "sqlite:///" + self.cache_files[0]["filename"].replace( + ".arrow", ".db" + ) + table = Datastore._get_db_table(self, table_name, connection_uri) + if type(src_feature_to_dst_views_map) is list: + src_feature_to_dst_views_map = dict(src_feature_to_dst_views_map) + elif type(src_feature_to_dst_views_map) is str: + src_feature_to_dst_views_map = { + src_feature_to_dst_views_map: src_feature_to_dst_views_map + } + feature_view = [] + for src_feature, dst_feature_view in list(src_feature_to_dst_views_map.items()): + if src_feature == dst_feature_view: + self = self.rename_column(src_feature, "__tmp__" + src_feature) + src_feature_to_dst_views_map["__tmp__" + src_feature] = dst_feature_view + del src_feature_to_dst_views_map[src_feature] + src_feature = "__tmp__" + src_feature + value = self[0][src_feature] + if type(value) is str: # we don't want to save as json type just in case + value = "**" + dtype = table.db.types.guess(value) + feature_view.append((dst_feature_view, dtype)) + self.add_sql( + feature_view=feature_view, + table_name=table_name, + connection_uri=connection_uri, + primary_id=primary_id, + batch_size=batch_size, + num_proc=num_proc, + fts_connection_uri=fts_connection_uri, + ) + self = self.map( + Datastore.upsert_sql_from_batch, + batch_size=batch_size, + batched=True, + num_proc=1 if connection_uri == "sqlite://" else num_proc, + fn_kwargs={ + "views_map": self.views_map, + "primary_id": primary_id, + "src_feature_to_dst_views_map": src_feature_to_dst_views_map, + }, + ) + self = self.remove_columns(src_feature) + return self + + @classmethod + def from_sql( + cls, + feature_view, + table_name, + connection_uri, + dtype="str", + primary_id="id", + batch_size=1000, + num_proc=4, + fts_connection_uri=None, + ): + return cls.from_dict({}).add_sql( + feature_view=feature_view, + table_name=table_name, + connection_uri=connection_uri, + dtype=dtype, + primary_id=primary_id, + batch_size=batch_size, + num_proc=num_proc, + fts_connection_uri=fts_connection_uri, + ) + + def add_sql( + self, + feature_view=None, + table_name=None, + connection_uri=None, + dtype="str", + primary_id="id", + batch_size=1000, + num_proc=4, + ): + """ + mapping one or more columns/features to a sql + database. creates a sqlalchmey/dataset dynamically with + primary_id as the primary key. + + TODO: remember to strip passwords from any + connection_uri. passwords should be passed as vargs and added + to the conneciton url dynamically passwords should not be + perisisted. + + NOTE: this dataset will not automatically change if the + database changes, and vice versa. periodically call this + method again to sync the two or create callbacks/triggers in + your code. + """ + if not hasattr(self, "views_map"): + self.views_map = {} + if hasattr(self, "_primary_id") and self._primary_id != primary_id: + raise RuntimeError(f"attempting to reset the index to {primary_id}") + else: + self._primary_id = primary_id + if table_name is None: + # print (self.info.builder_name, self.info.config_name) + table_name = f"_{self._fingerprint}_{self.info.builder_name}_{self.info.config_name}_{self.split}" + # print (table_name) + if not connection_uri: + connection_uri = "sqlite:///" + self.cache_files[0]["filename"].replace( + ".arrow", ".db" + ) + if not fts_connection_uri: + if connection_uri.starts("sqlite:"): + fts_connection_uri = connection_uri + else: + fts_connection_uri = "sqlite:///" + self.cache_files[0][ + "filename" + ].replace(".arrow", ".db") + if type(feature_view) is str: + feature_view = [(feature_view, dtype)] + if type(feature_view) is dict: + feature_view = list(feature_view.items()) + table = self._get_db_table(table_name, connection_uri) + if not feature_view and table.columns: + feature_view = table.columns + elif not feature_view: + raise RuntimeError( + f"No feature_view(s) and no column definition for table view {table_name}" + ) + table_ids = table.find(_columns=primary_id) + if primary_id not in self.features: + if len(self) == 0 and table_ids: + self = Datastore.from_dataset( + Dataset.from_dict( + {primary_id: range(max(id[primary_id] for id in table_ids))} + ), + self, + ) + ids = {a: 1 for a in range(len(self))} + self.id2idx_identity = True + else: + self = self.map( + Datastore._add_idx, + with_indices=True, + batch_size=batch_size, + batched=True, + num_proc=num_proc, + fn_kwargs={"id": primary_id}, + ) + ids = {a: 1 for a in range(len(self))} + self.id2idx_identity = True + else: + ids = {a: 1 for a in self[primary_id]} + missing_ids = [] + for id in table_ids: + if id[primary_id] not in ids: + missing_ids.append(id[primary_id]) + if missing_ids: + self = self.add_batch({primary_id: missing_ids}) + if not hasattr(self, "id2idx_identity"): + self.id2idx_identity = True + if self.id2idx_identity: + contiguous, start, end = is_contiguous(missing_ids) + self.id2idx_identity = start == len(self) and contiguous + else: + self.id2idx_identity = False + for col in feature_view: + if type(col) is tuple: + col, dtype = col + else: + dtype = None + if col == primary_id: + continue + if col not in table.columns: + if type(dtype) is str: + if "int" in dtype: + value = 0 + elif "float" in dtype: + value = 0.0 + else: + value = "**" + dtype = table.db.types.guess(value) + if dtype is not None: + table.create_column(col, dtype) + fts_table_name = f"_{self._fingerprint}_{self.info.builder_name}_{self.info.config_name}_{self.split}_{col}_fts_idx" + self.views_map[col] = { + "type": "sql", + "connection_uri": connection_uri, + "table_name": table_name, + "fts_connection_uri": fts_connection_uri, + "fts_table_name": fts_table_name, + } + return self + + def add_fts( + self, + feature_view, + fts_table_name=None, + fts_connection_uri=None, + primary_id="id", + batch_size=1000, + num_proc=4, + ): + if type(feature_view) is str: + feature_view = [ + feature_view, + ] + for col in feature_view: + fts_table_name = f"_{self._fingerprint}_{self.info.builder_name}_{self.info.config_name}_{self.split}_{col}_fts_idx" + self.views_map[col] = { + "type": "fts_only", + "connection_uri": fts_connection_uri, + "table_name": fts_table_name, + "fts_connection_uri": fts_connection_uri, + "fts_table_name": fts_table_name, + } + + @transmit_format + @fingerprint_transform( + inplace=False, ignore_kwargs=["load_from_cache_file", "cache_file_name"] + ) + def filter( + self, + function: Optional[Callable] = None, + with_indices=False, + input_columns: Optional[Union[str, List[str]]] = None, + batch_size: Optional[int] = 1000, + remove_columns: Optional[List[str]] = None, + keep_in_memory: bool = False, + load_from_cache_file: bool = True, + cache_file_name: Optional[str] = None, + writer_batch_size: Optional[int] = 1000, + fn_kwargs: Optional[dict] = None, + sql_query: Optional[dict] = None, + fts_query: Optional[dict] = None, + num_proc: Optional[int] = None, + suffix_template: str = "_{rank:05d}_of_{num_proc:05d}", + new_fingerprint: Optional[str] = None, + ) -> "Datastore": + """ + the same as datasets.filter except we add sql_query and + fts_query. sql_query applies a sql query to features/columns + that are mapped to sql which could be faster than doing a normal + "filter" function. the sql_query parameters are the same as the + "find" method from dataset.Table. For example: + dataset.filter(sql_query={'lang':'ru'}) will return those items + in the dataset that has the language 'ru'. + """ + if not hasattr(self, "views_map"): + self.views_map = {} + ret = self + if sql_query or fts_query: + if not sql_query: + sql_query = {} + if not fts_query: + fts_query = {} + ids2rank = {} + found_table = None + sql_query2 = {} + fts_query2 = {} + for feature_view, query in sql_query.items(): + val = self.views_map.get(feature_view) + if not val or val["type"] != "sql": + raise RuntimeError( + f"{feature_view} is not a sql or fts view and can not be filtered as such" + ) + if val["type"] == "sql": + connection_uri, table_name = ( + val["fts_connection_uri"], + val["fts_table"], + ) + sql_query2[(connection_uri, table_name)] = sql_query2.get( + (connection_uri, table_name), [] + ) + [query] + for feature_view, query in fts_query.items(): + val = self.views_map.get(feature_view) + if not val or val["type"] not in ("sql", "fts_only"): + raise RuntimeError( + f"{feature_view} is not a sql, or fts view and can not be filtered as such" + ) + if val["type"] == "sql" and "fts_connection_uri" in view: + connection_uri, table_name = ( + val["connection_uri"], + val["table_name"], + ) + fts_query2[(connection_uri, table_name)] = sql_query2.get( + (connection_uri, table_name), [] + ) + [query] + elif val["type"] == "fts_only": + connection_uri, table_name = ( + val["connection_uri"], + val["table_name"], + ) + fts_query2[(connection_uri, table_name)] = sql_query2.get( + (connection_uri, table_name), [] + ) + [query] + + for key, query in sql_query2.items(): + (connection_uri, table_name) = key + if key in fts_query2: + query["_fts_query"] = fts_query2[key] + del fts_query2[key] + query["_columns"] = [self._primary_id] + table = self._get_db_table(table_name, connection_uri) + for val in table.find(*[], **query): + ids2rank[val[self._primary_id]] = min( + ids2rank.get( + val[self._primary_id], + (100000 + val[self._primary_id]) + if "rank" not in val + else val["rank"], + ), + (100000 + val[self._primary_id]) + if "rank" not in val + else val["rank"], + ) + + for key, query in fts_query2.items(): + (connection_uri, table_name) = key + query2 = {} + query2["_fts_query"] = query + query2["_columns"] = [self._primary_id] + table = self._get_db_table(table_name, connection_uri) + for val in table.find(*[], **query2): + ids2rank[val[self._primary_id]] = min( + ids2rank.get( + val[self._primary_id], + (100000 + val[self._primary_id]) + if "rank" not in val + else val["rank"], + ), + (100000 + val[self._primary_id]) + if "rank" not in val + else val["rank"], + ) + + if ids2rank: + ids = list(ids2rank.keys()) + ids.sort(key=lambda a: ids2rank[a]) + if hasattr(self, "id2idx_identity") and self.id2idx_identity: + ret = self.select(ids) + ret.id2idx_identity = False + else: + if function: + function = lambda example: example["id"] in ids and function( + example + ) + else: + function = lambda example: example["id"] in ids + if function is None and remove_columns is None: + return ret + + # just copy the filter function here, but use Datastore's map function. + if len(self.list_indexes()) > 0: + raise DatasetTransformationNotAllowedError( + "Using `.filter` on a dataset with attached indexes is not allowed. You can first run `.drop_index() to remove your index and then re-add it.`" + ) + + if function is None: + function = lambda x: True # noqa: E731 + + if isinstance(input_columns, str): + input_columns = [input_columns] + + if input_columns is not None: + for input_column in input_columns: + if input_column not in self._data.column_names: + raise ValueError( + "Input column {} not in the dataset. Current columns in the dataset: {}".format( + input_column, self._data.column_names + ) + ) + + if fn_kwargs is None: + fn_kwargs = {} + fn_kwargs["input_columns"] = input_columns + + # return map function + return ret.map( + partial( + get_indices_from_mask_function, + function=function, + with_indices=with_indices, + ), + batched=True, + with_indices=with_indices, + features=self.features, + batch_size=batch_size, + remove_columns=remove_columns, + keep_in_memory=keep_in_memory, + load_from_cache_file=load_from_cache_file, + cache_file_name=cache_file_name, + writer_batch_size=writer_batch_size, + fn_kwargs=fn_kwargs, + num_proc=num_proc, + suffix_template=suffix_template, + new_fingerprint=new_fingerprint, + ) + + # note that while the primary_id corresponds to an item in an + # external storage, accessing an arrow dataset by datataset[index] + # will not be guranteed to get the corresponding id. a[0] will + # return the first item in the current subset of the dataset. but + # a[0] does not necessarily return {'id':0, ...} instead, a[0] + # might return {'id': 10, 'mmap_embed': }. To get dataset items by 'id', + # use either filter or check the property id2idx_identity to + # determine if the id corresponds to the index of the table. + def _getitem( + self, + key: Union[int, slice, str], # should this be list as well?? + format_type=None, + format_columns=None, + output_all_columns=False, + format_kwargs=None, + ) -> Union[Dict, List]: + if not hasattr(self, "views_map"): + self.views_map = {} + # assumine we do error checking re format_columns and output_all_columns at a higher level?? + format_columns = copy.copy(format_columns) + # this is the case where we are not getting any views. + if (not self.views_map) or (type(key) is str and key not in self.views_map): + return super()._getitem( + key, + format_type=format_type, + format_columns=format_columns, + output_all_columns=output_all_columns, + format_kwargs=format_kwargs, + ) + + # this is the case where there are more than one columns, some of which might + # be an arrow column and at least one view. For the view, we need to also get the "id". + + # let's prepare the parameters to get just the arrow portion of the dataset + orig_key = key + if type(key) is str: + if not format_columns: + format_columns = [key] + else: + format_columns.append(key) + if key in self.views_map: + key = self.primary_id + missing = [] + if format_columns: + for c in copy.copy(format_columns): + if c in self.views_map: + missing.append(c) + format_columns.remove(c) + if self.primary_id not in format_columns: + format_columns.append(self.primary_id) + else: + missing.append(self.primary_id) + + # let's get the data that is in the arrow portion first, including the id + outputs = super()._getitem( + key, + format_type=format_type, + format_columns=format_columns, + output_all_columns=output_all_columns, + format_kwargs=format_kwargs, + ) + + # this is the case where we are only getting view data, so the only arrow data returned is the 'id'. + # so we need the id column identified so we can index into the view data source. + if type(outputs) in (np.array, list): + outputs = {"id": outputs} + + # do some cleanup. + if ( + type(orig_key) is str + and format_columns + and self.primary_id in format_columns + ): + format_columns.remove(self.primary_id) + if format_columns is not None: + format_columns.extend(missing) + # now get the views and combine views and arrow portion + return self._format_views( + outputs, + format_columns=format_columns, + format_type=format_type, + output_all_columns=output_all_columns, + format_kwargs=format_kwargs, + ) + + def _format_views( + self, + outputs_or_keys, + format_type=None, + format_columns=None, + output_all_columns=False, + format_kwargs=None, + ): + def getitems( + self, + outputs, + keys, + contiguous, + start, + end, + format_columns, + output_all_columns, + mmap_by_items, + ): + if not format_columns: + items = list(self.views_map.items()) + else: + items = [ + (column, self.views_map[column]) + for column in format_columns + if column in self.views_map + ] + sql_results = {} + for feature, val in items: + if val["type"] == "mmap": + mmap_array = self._get_mmap(val["path"], val["dtype"], val["shape"]) + if mmap_by_items: + if contiguous: + outputs[feature] = [ + mmap_array[i] for i in range(start, end) + ] + else: + outputs[feature] = [mmap_array[i] for i in keys] + else: + if contiguous: + outputs[feature] = mmap_array[start:end] + else: + outputs[feature] = mmap_array[keys] + elif val["type"] == "sql": + sql_results[ + (val["table_name"], val["connection_uri"]) + ] = sql_results.get( + (val["table_name"], val["connection_uri"]), [] + ) + [ + feature + ] + for table_connection, features in sql_results.items(): + table_name, connection_uri = table_connection + table = self._get_db_table(table_name, connection_uri) + if contiguous: + for row in table.find( + **{ + table._primary_id: {"between": (start, end)}, + "_columns": features + ["id"], + } + ): + for feature in features: + outputs[feature] = outputs.get(feature, []) + [row[feature]] + elif type(keys) is int: + row = table.find_one( + **{table._primary_id: keys, "_columns": features + ["id"]} + ) + if row: + for feature in features: + outputs[feature] = row[feature] + else: + for row in table.find( + **{ + table._primary_id: {"in": keys}, + "_columns": features + ["id"], + } + ): + for feature in features: + outputs[feature] = outputs.get(feature, []) + [row[feature]] + + return outputs + + format_kwargs = format_kwargs if format_kwargs is not None else {} + format_columns = format_columns if format_columns is not None else [] + start = end = 0 + contiguous = False + if format_type in ("custom", "torch", "tensorflow", None) and type( + outputs_or_keys + ) not in (da.DataFrame, pd.DataFrame): + transform = format_kwargs.get("transform") + if isinstance(outputs_or_keys, str): + keys = outputs_or_keys + outputs = {} + contiguous = True + elif isinstance(outputs_or_keys, slice): + keys = outputs_or_keys + outputs = {} + contiguous = True + elif isinstance(outputs_or_keys, dict): + keys = outputs_or_keys[self.primary_id] + outputs = outputs_or_keys + else: + keys = outputs_or_keys + outputs = {} + if not contiguous: + if isinstance(keys, int): + contiguous = False + else: + contiguous, start, end = is_contiguous(keys) + else: + if isinstance(keys, slice): + start = 0 if keys.start is None else keys.start + end = len(self) if keys.stop is None else keys.stop + else: + start = keys[0] + end = keys[-1] + 1 + outputs = getitems( + self, + outputs, + keys, + contiguous, + start, + end, + format_columns, + output_all_columns, + mmap_by_items=False, + ) + if transform is not None: + outputs = transform(outputs) + if ( + self.primary_id in outputs + and format_columns + and self.primary_id not in format_columns + ): + del outputs[self.primary_id] + # is this right. will custom ever return a dict type if there is only one column, or do we + # default to returning the only column. + if len(outputs) == 1: + outputs = list(outputs.values())[0] + if format_type == "torch": + import torch + + return torch.tensor(outputs, **format_kwargs) + elif format_type == "tensorflow": + import tensorflow + + return tensorflow.ragged.constant(outputs, **format_kwargs) + else: + return outputs + elif format_type in ("dask", "pandas") or type(outputs_or_keys) in ( + da.DataFrame, + pd.DataFrame, + ): + # do we do transforms for this case?? + df = pd + if format_type in ("dask",) or type(outputs_or_keys) in (da.DataFrame,): + df = dd + if isinstance(outputs_or_keys, str): + start = 0 + end = len(self) + keys = outputs_or_keys + outputs = None + contiguous = True + elif isinstance(outputs_or_keys, slice): + start = 0 if outputs_or_keys.start is None else outputs_or_keys.start + end = ( + len(self) if outputs_or_keys.stop is None else outputs_or_keys.stop + ) + keys = outputs_or_keys + outputs = None + contiguous = True + elif isinstance(outputs_or_keys, dict) or isinstance( + outputs_or_keys, df.DataFrame + ): + outputs = outputs_or_keys + outputs = df.DataFrame(outputs) + keys = outputs_or_keys[self.primary_id] + contiguous, start, end = is_contiguous(keys) + else: + raise RuntimeError("got unknown outputs or keys type") + if outputs is None: + outputs = df.DataFrame() + outputs = getitems( + self, + outputs, + keys, + contiguous, + start, + end, + format_columns, + output_all_columns, + mmap_by_items=True, + ) + if ( + self.primary_id in outputs + and format_columns + and self.primary_id not in format_columns + ): + outputs.drop(self.primary_id, axis=1) + if len(format_columns) == 1: + outputs = outputs[format_columns[0]] + return outputs + raise RuntimeError("got unknown outputs or keys type") + + @staticmethod + def upsert_sql_from_batch( + batch, views_map, primary_id, src_feature_to_dst_views_map + ): + sql_results = {} + for src_feature, dst_feature in ( + src_feature_to_dst_views_map.items() + if src_feature_to_dst_views_map is not None + else zip(batch.keys(), batch.keys()) + ): + if views_map.get(dst_feature): + val = views_map[dst_feature] + if val["type"] == "sql": + sql_results[ + (val["table_name"], val["connection_uri"]) + ] = sql_results.get( + (val["table_name"], val["connection_uri"]), [] + ) + [ + (src_feature, dst_feature) + ] + for key, features in sql_results.items(): + table_name, connection_uri = key + db = DatabaseExt(connection_uri) + with db: + table = db[table_name] + batch2 = [] + for i in range(len(batch[primary_id])): + batch2.append( + { + feature[1]: batch[feature[0]][i] + for feature in features + [(primary_id, primary_id)] + } + ) + try: + table.insert_many(batch2) + except: + batch2 = [] + for i in range(len(batch[primary_id])): + batch2.append( + { + feature[1]: batch[feature[0]][i] + for feature in features + [(primary_id, primary_id)] + } + ) + table.update_many(batch2, [primary_id]) + batch2 = None + + PERSIST_IN_ARROW = 0 + STATIC_VIEWS = 1 + UPDATE_VIEWS = 2 + + @staticmethod + def map_fn_with_indices_and_handle_views( + batch, indices, map_fn, fn_kwargs, handle_views, views_map, primary_id + ): + ret = map_fn(batch, indices, **fn_kwargs) + if ret is not None and views_map: + if views_map and primary_id not in ret: + raise RuntimeError( + f"Datstore returned from map must have an {primary_id} column to link to views." + ) + if handle_views != DataStore.PERSIST_IN_ARROW: + for key in views_map: + if handle_views == Datastore.UPDATE_VIEWS: + if val["type"] == "mmap": + mmap_array = np_mmap( + val["path"], val["dtype"], val["shape"] + ) + mmap_array[batch[primary_id]] = batch[feature] + elif handle_views == Datastore.STATIC_VIEWS: + if key in ret: + del ret[key] + if handle_views == 2: + Datastore.upsert_sql_from_batch(ret, views_map, primary_id, None) + return ret + + @staticmethod + def map_fn_and_handle_views( + batch, map_fn, fn_kwargs, handle_views, views_map, primary_id + ): + ret = map_fn(batch, **fn_kwargs) + if ret is not None and views_map: + if views_map and primary_id not in ret: + raise RuntimeError( + f"Datstore returned from map must have an {primary_id} column to link to views." + ) + if handle_views != Datastore.PERSIST_IN_ARROW: + for key in views_map: + if handle_views == Datastore.UPDATE_VIEWS: + if val["type"] == "mmap": + mmap_array = np_mmap( + val["path"], val["dtype"], val["shape"] + ) + mmap_array[batch[primary_id]] = batch[feature] + elif handle_views == Datatsore.STATIC_VIEWS: + if key in ret: + del ret[key] + if handle_views == 2: + Datastore.upsert_sql_from_batch(ret, views_map, primary_id, None) + return ret + + #:arg handle_views: tells us how to handle views. + # PERSIST_IN_ARROW - all data returned will be persisted to arrow storage and not views. this will detach all views. + # STATIC_VIEWS - keep the views attached to external storage without change. *default* + # UPDATE_VIEWS - update views based on what is returned by the map function. this will create a side-effect. + # Updating views might create an unepxected side-effect on caching. Use caching with cuation when editing views. + def map( + self, + function: Optional[Callable] = None, + with_indices: bool = False, + input_columns: Optional[Union[str, List[str]]] = None, + batched: bool = False, + batch_size: Optional[int] = 1000, + drop_last_batch: bool = False, + remove_columns: Optional[Union[str, List[str]]] = None, + keep_in_memory: bool = False, + load_from_cache_file: bool = None, + cache_file_name: Optional[str] = None, + writer_batch_size: Optional[int] = 1000, + features: Optional[Features] = None, + disable_nullable: bool = False, + fn_kwargs: Optional[dict] = None, + num_proc: Optional[int] = None, + suffix_template: str = "_{rank:05d}_of_{num_proc:05d}", + new_fingerprint: Optional[str] = None, + desc: Optional[str] = None, + # add_memmap_views=None, + # add_sql_views=None, + ) -> "Datastore": + if not hasattr(self, "views_map"): + self.views_map = {} + views_map = copy.deepcopy(self.views_map) + for column in remove_columns if remove_columns is not None else []: + if column in views_map: + del views_map[column] + if handle_views != Datastore.PERSIST_IN_ARROW: + fn_kwargs = { + "fn_kwargs": fn_kwargs, + "views_map": views_map, + "map_fn": function, + "handle_views": handle_views, + "primary_id": self.primary_id, + } + if with_indices: + function = Datastore.map_fn_with_indices_and_handle_views + else: + function = Datastore.map_fn_and_handle_views + if shared_dir is None: + shared_dir = self.shared_dir + ret = super().map( + function=function, + with_indices=with_indices, + input_columns=input_columns, + batched=batched, + batch_size=batch_size, + drop_last_batch=drop_last_batch, + remove_columns=remove_columns, + keep_in_memory=keep_in_memory, + load_from_cache_file=load_from_cache_file, + cache_file_name=cache_file_name, + writer_batch_size=writer_batch_size, + features=features, + disable_nullable=disable_nullable, + fn_kwargs=fn_kwargs, + num_proc=num_proc, + suffix_template=suffix_template, + new_fingerprint=new_fingerprint, + desc=desc, + ) + for column in remove_columns if remove_columns is not None else []: + if column in self.views_map and column in ret: + print( + f"warning: the map function returned a column {column} which is the same as a detached view. this column will be persisted to arrow." + ) + return ret + + @transmit_format + @fingerprint_transform(inplace=False) + def add_column( + self, name: str, column: Union[list, np.array], new_fingerprint: str + ): + if not hasattr(self, "views_map"): + self.views_map = {} + if name in self.views_map: + raise RuntimeError(f"column {name} is alredy a view") + ret = super().add_column( + name=name, column=column, new_fingerprint=new_fingerprint + ) + return Datastore.from_dataset(ret, self) + + def class_encode_column(self, column: str) -> "Datastore": + if not hasattr(self, "views_map"): + self.views_map = {} + if column in self.views_map: + raise NotImplementedError() + ret = super().class_encode_column(column) + return Datastore.from_dataset(ret, self) + + @fingerprint_transform(inplace=False) + def flatten(self, new_fingerprint, max_depth=16) -> "Datastore": + if not hasattr(self, "views_map"): + self.views_map = {} + ret = super().flatten(new_fingerprint, max_depth) + return Datastore.from_dataset(ret, self) + + def cast( + self, + features: Features, + batch_size: Optional[int] = 10_000, + keep_in_memory: bool = False, + load_from_cache_file: bool = True, + cache_file_name: Optional[str] = None, + writer_batch_size: Optional[int] = 10_000, + num_proc: Optional[int] = None, + ) -> "Datastore": + if not hasattr(self, "views_map"): + self.views_map = {} + for feature in self.views_map: + if feature not in features: + continue + raise RuntimeError(f"cannot cast a view {feature}") + ret = super().cast( + features=features, + batch_size=batch_size, + keep_in_memory=keep_in_memory, + load_from_cache_file=load_from_cache_file, + cache_file_name=cache_file_name, + writer_batch_size=writer_batch_size, + num_proc=num_proc, + ) + return Datastore.from_dataset(ret, self) + + # renaming a column view mapped to a sql database will not change the name in the database. + @fingerprint_transform(inplace=False) + def rename_column( + self, original_column_name: str, new_column_name: str, new_fingerprint + ) -> "Datastore": + if not hasattr(self, "views_map"): + self.views_map = {} + views_map = copy.deepcopy(self.views_map) + if original_column_name in views_map: + val = views_map[original_column_name] + del views_map[original_column_name] + views_map[new_column_name] = val + return Datastore.from_dataset(self, self, views_map=views_map) + ret = super().rename_column( + original_column_name=original_column_name, + new_column_name=new_column_name, + new_fingerprint=new_fingerprint, + ) + return Datastore.from_dataset(ret, self, views_map=views_map) + + # renaming a column view mapped to a sql database will not change the name in the database. + @fingerprint_transform(inplace=False) + def rename_columns( + self, column_mapping: Dict[str, str], new_fingerprint + ) -> "Datastore": + if not hasattr(self, "views_map"): + self.views_map = {} + views_map = copy.deepcopy(self.views_map) + for original_column_name, new_column_name in list(column_mapping.items()): + val = views_map[original_column_name] + del views_map[original_column_name] + views_map[new_column_name] = val + del column_mapping[original_column_name] + if not column_mapping: + return Datastore.from_dataset(self, self, views_map=views_map) + ret = super().rename_column( + column_mapping=column_mapping, new_fingerprint=new_fingerprint + ) + return Datastore.from_dataset(ret, self, views_map=views_map) + + def prepare_for_task(self, task: Union[str, TaskTemplate]) -> "Datastore": + if not hasattr(self, "views_map"): + self.views_map = {} + ret = super().prepare_for_task(task) + return Datastore.from_dataset(ret, self) + + @transmit_format + @fingerprint_transform(inplace=False, ignore_kwargs=["cache_file_name"]) + def flatten_indices( + self, + keep_in_memory: bool = False, + cache_file_name: Optional[str] = None, + writer_batch_size: Optional[int] = 1000, + features: Optional[Features] = None, + disable_nullable: bool = True, + new_fingerprint: Optional[str] = None, + ) -> "Datastore": + if not hasattr(self, "views_map"): + self.views_map = {} + ret = super().flatten_indices( + keep_in_memory=keep_in_memory, + cache_file_name=cache_file_name, + writer_batch_size=writer_batch_size, + features=features, + disable_nullable=disable_nullable, + new_fingerprint=new_fingerprint, + ) + return Datastore.from_dataset(ret, self) + + @transmit_format + @fingerprint_transform( + inplace=False, ignore_kwargs=["load_from_cache_file", "indices_cache_file_name"] + ) + def sort( + self, + column: str, + reverse: bool = False, + kind: str = None, + keep_in_memory: bool = False, + load_from_cache_file: bool = True, + indices_cache_file_name: Optional[str] = None, + writer_batch_size: Optional[int] = 1000, + new_fingerprint: Optional[str] = None, + ) -> "Datastore": + if not hasattr(self, "views_map"): + self.views_map = {} + if column in self.views_map: + raise NotImplementedError() + ret = super().sort( + column=column, + reverse=reverse, + kind=kind, + keep_in_memory=keep_in_memory, + load_from_cache_file=load_from_cache_file, + indices_cache_file_name=indices_cache_file_name, + writer_batch_size=writer_batch_size, + new_fingerprint=new_fingerprint, + ) + return Datastore.from_dataset(ret, self) + + @transmit_format + @fingerprint_transform( + inplace=False, + randomized_function=True, + ignore_kwargs=["load_from_cache_file", "indices_cache_file_name"], + ) + def shuffle( + self, + seed: Optional[int] = None, + generator: Optional[np.random.Generator] = None, + keep_in_memory: bool = False, + load_from_cache_file: bool = True, + indices_cache_file_name: Optional[str] = None, + writer_batch_size: Optional[int] = 1000, + new_fingerprint: Optional[str] = None, + ) -> "Datastore": + if not hasattr(self, "views_map"): + self.views_map = {} + ret = super().shuffle( + seed=seed, + generator=generator, + keep_in_memory=keep_in_memory, + load_from_cache_file=load_from_cache_file, + indices_cache_file_name=indices_cache_file_name, + writer_batch_size=writer_batch_size, + new_fingerprint=new_fingerprint, + ) + return Datastore.from_dataset(ret, self) + + @transmit_format + @fingerprint_transform( + inplace=False, + randomized_function=True, + fingerprint_names=["train_new_fingerprint", "test_new_fingerprint"], + ignore_kwargs=[ + "load_from_cache_file", + "train_indices_cache_file_name", + "test_indices_cache_file_name", + ], + ) + def train_test_split( + self, + test_size: Union[float, int, None] = None, + train_size: Union[float, int, None] = None, + shuffle: bool = True, + seed: Optional[int] = None, + generator: Optional[np.random.Generator] = None, + keep_in_memory: bool = False, + load_from_cache_file: bool = True, + train_indices_cache_file_name: Optional[str] = None, + test_indices_cache_file_name: Optional[str] = None, + writer_batch_size: Optional[int] = 1000, + train_new_fingerprint: Optional[str] = None, + test_new_fingerprint: Optional[str] = None, + ) -> "DatasetDict": + if not hasattr(self, "views_map"): + self.views_map = {} + ret = super.train_test_split( + test_size=test_size, + train_size=train_size, + shuffle=shuffle, + seed=seed, + generator=generator, + keep_in_memory=keep_in_memory, + load_from_cache_file=load_from_cache_file, + train_indices_cache_file_name=train_indices_cache_file_name, + test_indices_cache_file_name=test_indices_cache_file_name, + writer_batch_size=writer_batch_size, + train_new_fingerprint=train_new_fingerprint, + test_new_fingerprint=test_new_fingerprint, + ) + for key in list(ret.keys()): + ret[key] = Datastore.from_dataset(ret, self) + return ret + + @transmit_format + @fingerprint_transform(inplace=False) + def add_item(self, item: dict, new_fingerprint: str): + if not hasattr(self, "views_map"): + self.views_map = {} + ret = super().add_item(item=item, new_fingerprint=new_fingerprint) + return Datastore.from_dataset(ret, self) + + @transmit_format + @fingerprint_transform(inplace=False) + def add_batch(self, batch, new_fingerprint: str): + """Add batch to Dataset. + + Args: + batch (Datastore of same schema or dict): batch data to be added. + + Returns: + :class:`Datastore` + """ + if not hasattr(self, "views_map"): + self.views_map = {} + # take care of the case where views_map needs to be merged and the batch's indices are + # offsetted + if type(batch) is dict: + keys = list(batch.keys()) + len_batch = len(batch[keys[0]]) + features = list(self.features) + for feature in self.features: + if feature not in keys: + batch[feature] = [None] * len_batch + item_table = InMemoryTable.from_pydict(batch) + # Cast batch + schema = pa.schema(self.features.type) + item_table = item_table.cast(schema) + # Concatenate tables + table = concat_tables([self._data, item_table]) + if self._indices is None: + indices_table = None + else: + print(item_table._data) + item_indices_array = pa.array( + list( + range(len(self._data), len(self._data) + len(item_table._data)) + ), + type=pa.uint64(), + ) + item_indices_table = InMemoryTable.from_arrays( + [item_indices_array], names=["indices"] + ) + indices_table = concat_tables([self._indices, item_indices_table]) + ret = Dataset( + table, + info=self.info.copy(), + split=self.split, + indices_table=indices_table, + fingerprint=new_fingerprint, + ) + return Datastore.from_dataset(ret, self) + + def align_labels_with_mapping( + self, label2id: Dict, label_column: str + ) -> "Datastore": + if not hasattr(self, "views_map"): + self.views_map = {} + ret = super().align_labels_with_mapping( + label2id=label2id, label_column=label_column + ) + return Datastore.from_dataset(ret, self) + + @staticmethod + def from_csv( + path_or_paths: Union[PathLike, List[PathLike]], + split: Optional[NamedSplit] = None, + features: Optional[Features] = None, + cache_dir: str = None, + keep_in_memory: bool = False, + **kwargs, + ): + """Create Datastore from CSV file(s). + Args: + path_or_paths (path-like or list of path-like): Path(s) of the CSV file(s). + split (:class:`NamedSplit`, optional): Split name to be assigned to the dataset. + features (:class:`Features`, optional): Dataset features. + cache_dir (:obj:`str`, optional, default ``"~/.cache/huggingface/datasets"``): Directory to cache data. + keep_in_memory (:obj:`bool`, default ``False``): Whether to copy the data in-memory. + **kwargs: Keyword arguments to be passed to :meth:`pandas.read_csv`. + Returns: + :class:`Datastore` + """ + # Dynamic import to avoid circular dependency + from .io.csv import CsvDatasetReader + + return Datastore.from_dataset( + CsvDatasetReader( + path_or_paths, + split=split, + features=features, + cache_dir=cache_dir, + keep_in_memory=keep_in_memory, + **kwargs, + ).read() + ) + + @staticmethod + def from_json( + path_or_paths: Union[PathLike, List[PathLike]], + split: Optional[NamedSplit] = None, + features: Optional[Features] = None, + cache_dir: str = None, + keep_in_memory: bool = False, + field: Optional[str] = None, + **kwargs, + ): + """Create Datastore from JSON or JSON Lines file(s). + Args: + path_or_paths (path-like or list of path-like): Path(s) of the JSON or JSON Lines file(s). + split (:class:`NamedSplit`, optional): Split name to be assigned to the dataset. + features (:class:`Features`, optional): Dataset features. + cache_dir (:obj:`str`, optional, default ``"~/.cache/huggingface/datasets"``): Directory to cache data. + keep_in_memory (:obj:`bool`, default ``False``): Whether to copy the data in-memory. + field (:obj:`str`, optional): Field name of the JSON file where the dataset is contained in. + **kwargs: Keyword arguments to be passed to :class:`JsonConfig`. + Returns: + :class:`Datastore` + """ + # Dynamic import to avoid circular dependency + from .io.json import JsonDatasetReader + + return Datastore.from_dataset( + JsonDatasetReader( + path_or_paths, + split=split, + features=features, + cache_dir=cache_dir, + keep_in_memory=keep_in_memory, + field=field, + **kwargs, + ).read() + ) + + @staticmethod + def from_parquet( + path_or_paths: Union[PathLike, List[PathLike]], + split: Optional[NamedSplit] = None, + features: Optional[Features] = None, + cache_dir: str = None, + keep_in_memory: bool = False, + columns: Optional[List[str]] = None, + **kwargs, + ): + """Create Datastore from Parquet file(s). + Args: + path_or_paths (path-like or list of path-like): Path(s) of the Parquet file(s). + split (:class:`NamedSplit`, optional): Split name to be assigned to the dataset. + features (:class:`Features`, optional): Dataset features. + cache_dir (:obj:`str`, optional, default ``"~/.cache/huggingface/datasets"``): Directory to cache data. + keep_in_memory (:obj:`bool`, default ``False``): Whether to copy the data in-memory. + columns (:obj:`List[str]`, optional): If not None, only these columns will be read from the file. + A column name may be a prefix of a nested field, e.g. 'a' will select + 'a.b', 'a.c', and 'a.d.e'. + **kwargs: Keyword arguments to be passed to :class:`ParquetConfig`. + Returns: + :class:`Datastore` + """ + # Dynamic import to avoid circular dependency + from dataset.io.parquet import ParquetDatasetReader + + return Datastore.from_dataset( + ParquetDatasetReader( + path_or_paths, + split=split, + features=features, + cache_dir=cache_dir, + keep_in_memory=keep_in_memory, + columns=columns, + **kwargs, + ).read() + ) + + @staticmethod + def from_text( + path_or_paths: Union[PathLike, List[PathLike]], + split: Optional[NamedSplit] = None, + features: Optional[Features] = None, + cache_dir: str = None, + keep_in_memory: bool = False, + **kwargs, + ): + """Create Datastore from text file(s). + Args: + path_or_paths (path-like or list of path-like): Path(s) of the text file(s). + split (:class:`NamedSplit`, optional): Split name to be assigned to the dataset. + features (:class:`Features`, optional): Dataset features. + cache_dir (:obj:`str`, optional, default ``"~/.cache/huggingface/datasets"``): Directory to cache data. + keep_in_memory (:obj:`bool`, default ``False``): Whether to copy the data in-memory. + **kwargs: Keyword arguments to be passed to :class:`TextConfig`. + Returns: + :class:`Datastore` + """ + # Dynamic import to avoid circular dependency + from .io.text import TextDatasetReader + + return Datastore.from_dataset( + TextDatasetReader( + path_or_paths, + split=split, + features=features, + cache_dir=cache_dir, + keep_in_memory=keep_in_memory, + **kwargs, + ).read() + ) + + def save_to_disk(self, dataset_path: str, fs=None, move_files=False): + # move_files means delete the old files as we create the new files in dataset_path. + """ + Saves a dataset to a dataset directory, or in a filesystem using either :class:`~filesystems.S3FileSystem` or + any implementation of ``fsspec.spec.AbstractFileSystem``. + Note regarding sliced datasets: + If you sliced the dataset in some way (using shard, train_test_split or select for example), then an indices mapping + is added to avoid having to rewrite a new arrow Table (save time + disk/memory usage). + It maps the indices used by __getitem__ to the right rows of the arrow Table. + By default save_to_disk does save the full dataset table + the mapping. + If you want to only save the shard of the dataset instead of the original arrow file and the indices, + then you have to call :func:`datasets.Dataset.flatten_indices` before saving. + This will create a new arrow table by using the right rows of the original table. + Args: + dataset_path (:obj:`str`): Path (e.g. `dataset/train`) or remote URI (e.g. `s3://my-bucket/dataset/train`) + of the dataset directory where the dataset will be saved to. + fs (:class:`~filesystems.S3FileSystem`, ``fsspec.spec.AbstractFileSystem``, optional, defaults ``None``): + Instance of the remote filesystem used to download the files from. + """ + assert ( + not self.list_indexes() + ), "please remove all the indexes using `dataset.drop_index` before saving a dataset" + + if is_remote_filesystem(fs): + dataset_path = extract_path_from_uri(dataset_path) + else: + fs = fsspec.filesystem("file") + cache_files_paths = [ + Path(cache_filename["filename"]) for cache_filename in self.cache_files + ] + # Check that the dataset doesn't overwrite iself. It can cause a permission error on Windows and a segfault on linux. + if Path(dataset_path, config.DATASET_ARROW_FILENAME) in cache_files_paths: + raise PermissionError( + f"Tried to overwrite {Path(dataset_path, config.DATASET_ARROW_FILENAME)} but a dataset can't overwrite itself." + ) + if Path(dataset_path, config.DATASET_INDICES_FILENAME) in cache_files_paths: + raise PermissionError( + f"Tried to overwrite {Path(dataset_path, config.DATASET_INDICES_FILENAME)} but a dataset can't overwrite itself." + ) + # Save views data, dataset + indices + state + info + fs.makedirs(dataset_path, exist_ok=True) + views_map_copy = copy.deepcopy(self.views_map) + for key, value in list(self.views_map.items()): + # Copy or move file to destination directory + if "connection_uri" in value: + if "sqlite:///" in value["connection_uri"]: + src = value["connection_uri"].replace("sqlite:///", "") + if value["connection_uri"] in Datastore.db_connection: + db = Datastore.db_connection[value["connection_uri"]] + db.close() + del Datastore.db_connection[value["connection_uri"]] + db = None + for key in list(Datastore.db_table.keys()): + if key[1] == value["connection_uri"]: + del Datastore.db_table[key] + value["connection_uri"] = "sqlite:///" + Path(src).name + else: + continue + else: + src = value["path"] + value["path"] = Path(src).name + filename = Path(src).name + dest = os.path.join(dataset_path, filename) + + # if the src is not the same as dest, we want to move or copy + if src != dest and os.path.exists(src): + if move_files: + shutil.move(src, dest) + else: + shutil.copy(src, dest) + + # Get json serializable state + state = { + key: self.__dict__[key] + for key in [ + "_fingerprint", + "_format_columns", + "_format_kwargs", + "_format_type", + "_indexes", + "_output_all_columns", + "views_map", + "id2idx_identity", + "_primary_id", + ] + } + self.views_map = views_map_copy + split = self.__dict__["_split"] + state["_split"] = str(split) if split is not None else split + + state["_data_files"] = [{"filename": config.DATASET_ARROW_FILENAME}] + state["_indices_data_files"] = ( + [{"filename": config.DATASET_INDICES_FILENAME}] + if self._indices is not None + else None + ) + for k in state["_format_kwargs"].keys(): + try: + json.dumps(state["_format_kwargs"][k]) + except TypeError as e: + raise TypeError( + str(e) + + f"\nThe format kwargs must be JSON serializable, but key '{k}' isn't." + ) + + # Get json serializable dataset info + dataset_info = asdict(self._info) + + with fs.open( + Path(dataset_path, config.DATASET_ARROW_FILENAME).as_posix(), "wb" + ) as dataset_file: + with ArrowWriter(stream=dataset_file) as writer: + writer.write_table(self._data) + writer.finalize() + + if self._indices is not None: + with fs.open( + Path(dataset_path, config.DATASET_INDICES_FILENAME).as_posix(), "wb" + ) as indices_file: + with ArrowWriter(stream=indices_file) as writer: + writer.write_table(self._indices) + writer.finalize() + if move_files: + orig_dataset_path = os.path.dirname(self.cache_files[0]["filename"]) + arrow_file = Path( + orig_dataset_path, config.DATASET_ARROW_FILENAME + ).as_posix() + if os.path.exists(arrow_file): + os.unlink(arrow_file) + indices_file = Path( + orig_dataset_path, config.DATASET_INDICES_FILENAME + ).as_posix() + if os.path.exists(indices_file): + os.unlink(indices_file) + json_file = Path( + orig_dataset_path, config.DATASET_STATE_JSON_FILENAME + ).as_posix() + if os.path.exists(json_file): + os.unlink(json_file) + info_file = Path(orig_dataset_path, config.DATASET_INFO_FILENAME).as_posix() + if os.path.exists(info_file): + os.unlink(info_file) + license_file = Path(orig_dataset_path, config.LICENSE_FILENAME).as_posix() + if os.path.exists(license_file): + os.unlink(license_file) + for cache_filename in self.cache_files: + if os.path.exists(cache_filename["filename"]): + os.unlink(cache_filename["filename"]) + with fs.open( + Path(dataset_path, config.DATASET_STATE_JSON_FILENAME).as_posix(), + "w", + encoding="utf-8", + ) as state_file: + json.dump(state, state_file, indent=2, sort_keys=True) + with fs.open( + Path(dataset_path, config.DATASET_INFO_FILENAME).as_posix(), + "w", + encoding="utf-8", + ) as dataset_info_file: + # Sort only the first level of keys, or we might shuffle fields of nested features if we use sort_keys=True + sorted_keys_dataset_info = { + key: dataset_info[key] for key in sorted(dataset_info) + } + json.dump(sorted_keys_dataset_info, dataset_info_file, indent=2) + + logger.info("Dataset saved in {}".format(dataset_path)) + if move_files: + return Datastore.load_from_disk( + dataset_path, + fs=fs, + ) + else: + return self + + @staticmethod + def load_from_disk( + dataset_path: str, fs=None, keep_in_memory: Optional[bool] = None + ) -> "Datastore": + ret = Dataset.load_from_disk( + dataset_path=dataset_path, fs=fs, keep_in_memory=keep_in_memory + ) + with open( + Path(dataset_path, config.DATASET_STATE_JSON_FILENAME).as_posix(), + "r", + encoding="utf-8", + ) as state_file: + state = json.load(state_file) + ret.views_map = state.get("views_map") + ret.id2idx_identity = state.get("id2idx_identity") + fs = fsspec.filesystem("file") if fs is None else fs + for key, value in list(ret.views_map.items()): + if "connection_uri" in value: + if "sqlite:///" in value["connection_uri"]: + src = Path(value["connection_uri"].replace("sqlite:///", "")).name + else: + continue + else: + src = Path(value["path"]).name + if is_remote_filesystem(fs): + data_path = os.path.join(dataset_path, src) + src_dataset_path = extract_path_from_uri(data_path) + tmp_dir = tempfile.TemporaryDirectory() + data_path = Path(tmp_dir.name, src_dataset_path) + fs.download(src_dataset_path, data_path.as_posix(), recursive=True) + else: + data_path = os.path.abspath(os.path.join(dataset_path, src)) + if "connection_uri" in value: + ret.views_map[key]["connection_uri"] = "sqlite:///" + data_path + else: + ret.views_map[key]["path"] = data_path + return Datastore.from_dataset(ret) + + +class FeaturesWithViews(Features): + """an extension of Features that allows printing of the views' name as well""" + + def copy(self): + ret = FeaturesWithViews(super().copy()) + if hasattr(self, "views_map"): + ret.views_map = copy.deepcopy(self.views_map) + return ret + + def __repr__(self): + ret = "{" + "\n\t\t".join( + [f"'{a[0]}': {a[1]}" for a in self.items() if a[0] not in self.views_map] + ) + if self.views_map: + ret = ( + ret + + "\n\t\t" + + "\n\t\t".join( + f"'{a[0]}': View({a[1]})" for a in self.views_map.items() + ) + ) + ret += "\n}" + return ret + + +class Sqlite3FTSIndex(BaseIndex): + """Sqlite3 FTS Index class for indexing""" + + def __init__(self, table: TableSharded = None, column: Optional[str] = None): + self.table = table + self.column = column + + def search(self, query, k: int = 10) -> SearchResults: + hits = list(self.table.find(_fts_query=[(self.column, query)], _limit=k)) + return SearchResults( + [hit["rank"] for hit in hits], [int(hit["rowid"]) for hit in hits] + ) # this should be a generator or we feed in a row_type of a signle SearchResult + + def search_batch(self, queries, k: int = 10) -> BatchedSearchResults: + """Find the nearest examples indices to the query. + Args: + queries (`Union[List[str], np.ndarray]`): The queries as a list of strings if `column` is a text index or as a numpy array if `column` is a vector index. + k (`int`): The number of examples to retrieve per query. + Ouput: + total_scores (`List[List[float]`): The retrieval scores of the retrieved examples per query. + total_indices (`List[List[int]]`): The indices of the retrieved examples per query. + """ + total_scores, total_indices = [], [] + for query in queries: + scores, indices = self.search(query, k) + total_scores.append(scores) + total_indices.append(indices) + return BatchedSearchResults(total_scores, total_indices) + + def save(self, file: Union[str, PurePath]): + """Serialize the index on disk""" + raise NotImplementedError + + @classmethod + def load(cls, file: Union[str, PurePath]) -> "BaseIndex": + """Deserialize the index from disk""" + raise NotImplementedError diff --git a/data_tooling/datastore/tests/__init__.py b/data_tooling/datastore/tests/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/data_tooling/datastore/tests/test.py b/data_tooling/datastore/tests/test.py new file mode 100644 index 0000000..bf003b0 --- /dev/null +++ b/data_tooling/datastore/tests/test.py @@ -0,0 +1,169 @@ +import os +import sys + +import aiohttp +import fsspec +import numpy as np +import requests +from datasets import load_dataset + +sys.path.append( + os.path.abspath( + os.path.join( + os.path.dirname(__file__), os.path.pardir, os.path.pardir, os.path.pardir + ) + ) +) + +from data_tooling.datastore.datastore_base import * + +if __name__ == "__main__": + + args = sys.argv[1:] + if not args: + exit() + + if "-test_sql_basic" in args: + db = DatabaseExt("sqlite://") + table = db["user"] + assert table.exists == False + assert table.has_column("id") == False + assert table.insert(dict(name="John Doe", age=37)) == 0 + assert table.exists == True + assert table.has_column("id") == True + assert table.insert(dict(name="Jane Doe", age=20)) == 1 + jane = table.find_one(name="Jane Doe") + assert jane["id"] == 1 + + db = DatabaseExt("sqlite://") + table = db["user"] + rows = [dict(name="Dolly")] * 10 + table.insert_many(rows) + assert list(table.find(id={"in": range(0, 2)}))[-1]["id"] == 1 + + if "-test_memmap" in args: + datastore = Datastore.from_mmap( + "embed", + [1000, 512, 512], + ) + print(datastore) + datastore = Datastore.from_dataset( + load_dataset("oscar", "unshuffled_deduplicated_sw")["train"] + ) + datastore = datastore.add_mmap( + "embed", + [-1, 512, 512], + ) + datastore = datastore.add_mmap("token", [-1, 512], dtype=np.int32) + assert (datastore["embed"][0].shape) == (512, 512) + datastore["embed"][0][0] = 0.0 + assert np.mean(datastore["embed"][0][0]) == 0 + datastore["embed"][0][0] = 1.0 + assert np.mean(datastore["embed"][0][0]) == 1.0 + assert set(datastore[0].keys()) == {"id", "text", "embed", "token"} + assert len(datastore["text"]) == 24803 + assert len(datastore[0:10]["text"]) == 10 + assert (datastore[0:10]["token"].shape) == (10, 512) + print(datastore) + + if "-test_move_to_sql" in args: + data = load_dataset("oscar", "unshuffled_deduplicated_yo")["train"] + datastore = Datastore.from_dataset(data) + Datastore.db_connection = {} + Datastore.db_table = {} + datastore = datastore.move_to_sql("text") + + if "-test_sqlite_fs" in args: + db = DatabaseExt("sqlite:///test.db") + books_table = db["books"] + books_table.create_fts_index_column("text", stemmer="unicode61") + for t in """In Which We Are Introduced to Winnie the Pooh and Some Bees and the Stories Begin +Winnie-the-Pooh is out of honey, so he and Christopher Robin attempt to trick some bees out of theirs, with disastrous results. +In Which Pooh Goes Visiting and Gets into a Tight Place +Pooh visits Rabbit, but eats so much while in Rabbit's house that he gets stuck in Rabbit's door on the way out. +In Which Pooh and Piglet Go Hunting and Nearly Catch a Woozle +Pooh and Piglet track increasing numbers of footsteps round and round a spinney of trees. +In Which Eeyore Loses a Tail and Pooh Finds One +Pooh sets out to find Eeyore's missing tail, and notices something interesting about Owl's bell-pull. +In Which Piglet Meets a Heffalump +Piglet and Pooh try to trap a Heffalump, but wind up trapping the wrong sort of creature. +In Which Eeyore has a Birthday and Gets Two Presents +Pooh feels bad that no one has gotten Eeyore anything for his birthday, so he and Piglet try their best to get him presents. +In Which Kanga and Baby Roo Come to the Forest and Piglet has a Bath +Rabbit convinces Pooh and Piglet to try to kidnap newcomer Baby Roo to convince newcomer Kanga to leave the forest. +In Which Christopher Robin Leads an Expotition to the North Pole +Christopher Robin and all of the animals in the forest go on a quest to find the North Pole in the Hundred Acre Wood. +In Which Piglet is Entirely Surrounded by Water +Piglet is trapped in his home by a flood, so he sends a message out in a bottle in hope of rescue. +In Which Christopher Robin Gives Pooh a Party and We Say Goodbye +Christopher Robin gives Pooh a party for helping to rescue Piglet during the flood. +The central character in the series is Harry Potter, a boy who lives in the fictional town of Little Whinging, Surrey with his aunt, uncle, and cousin – the Dursleys – and discovers at the age of eleven that he is a wizard, though he lives in the ordinary world of non-magical people known as Muggles.[8] The wizarding world exists parallel to the Muggle world, albeit hidden and in secrecy. His magical ability is inborn, and children with such abilities are invited to attend exclusive magic schools that teach the necessary skills to succeed in the wizarding world.[9] + +Harry becomes a student at Hogwarts School of Witchcraft and Wizardry, a wizarding academy in Scotland, and it is here where most of the events in the series take place. As Harry develops through his adolescence, he learns to overcome the problems that face him: magical, social, and emotional, including ordinary teenage challenges such as friendships, infatuation, romantic relationships, schoolwork and exams, anxiety, depression, stress, and the greater test of preparing himself for the confrontation that lies ahead in wizarding Britain's increasingly-violent second wizarding war.[10] + +Each novel chronicles one year in Harry's life[11] during the period from 1991 to 1998.[12] The books also contain many flashbacks, which are frequently experienced by Harry viewing the memories of other characters in a device called a Pensieve. + +The environment Rowling created is intimately connected to reality. The British magical community of the Harry Potter books is inspired by 1990s British culture, European folklore, classical mythology and alchemy, incorporating objects and wildlife such as magic wands, magic plants, potions, spells, flying broomsticks, centaurs and other magical creatures, and the Philosopher's Stone, beside others invented by Rowling. While the fantasy land of Narnia is an alternate universe and the Lord of the Rings' Middle-earth a mythic past, the wizarding world of Harry Potter exists parallel to the real world and contains magical versions of the ordinary elements of everyday life, with the action mostly set in Scotland (Hogwarts), the West Country, Devon, London, and Surrey in southeast England.[13] The world only accessible to wizards and magical beings comprises a fragmented collection of overlooked hidden streets, ancient pubs, lonely country manors, and secluded castles invisible to the Muggle population.[9] + +Early years +When the first novel of the series, Harry Potter and the Philosopher's Stone, opens, it is apparent that some significant event has taken place in the wizarding world – an event so very remarkable that even Muggles (non-magical people) notice signs of it. The full background to this event and Harry Potter's past is revealed gradually throughout the series. After the introductory chapter, the book leaps forward to a time shortly before Harry Potter's eleventh birthday, and it is at this point that his magical background begins to be revealed. + +Despite Harry's aunt and uncle's desperate prevention of Harry learning about his abilities,[14] their efforts are in vain. Harry meets a half-giant, Rubeus Hagrid, who is also his first contact with the wizarding world. Hagrid reveals himself to be the Keeper of Keys and Grounds at Hogwarts as well as some of Harry's history.[14] Harry learns that, as a baby, he witnessed his parents' murder by the power-obsessed dark wizard Lord Voldemort (more commonly known by the magical community as You-Know-Who or He-Who-Must-Not-Be-Named, and by Albus Dumbledore as Tom Marvolo Riddle) who subsequently attempted to kill him as well.[14] Instead, the unexpected happened: Harry survived with only a lightning-shaped scar on his forehead as a memento of the attack, and Voldemort disappeared soon afterwards, gravely weakened by his own rebounding curse. + +As its inadvertent saviour from Voldemort's reign of terror, Harry has become a living legend in the wizarding world. However, at the orders of the venerable and well-known wizard Albus Dumbledore, the orphaned Harry had been placed in the home of his unpleasant Muggle relatives, the Dursleys, who have kept him safe but treated him poorly, including confining him to a cupboard without meals and treating him as their servant. Hagrid then officially invites Harry to attend Hogwarts School of Witchcraft and Wizardry, a famous magic school in Scotland that educates young teenagers on their magical development for seven years, from age eleven to seventeen. + +With Hagrid's help, Harry prepares for and undertakes his first year of study at Hogwarts. As Harry begins to explore the magical world, the reader is introduced to many of the primary locations used throughout the series. Harry meets most of the main characters and gains his two closest friends: Ron Weasley, a fun-loving member of an ancient, large, happy, but poor wizarding family, and Hermione Granger, a gifted, bright, and hardworking witch of non-magical parentage.[14][15] Harry also encounters the school's potions master, Severus Snape, who displays a conspicuously deep and abiding dislike for him, the rich brat Draco Malfoy whom he quickly makes enemies with, and the Defence Against the Dark Arts teacher, Quirinus Quirrell, who later turns out to be allied with Lord Voldemort. He also discovers a talent of flying on broomsticks and is recruited for his house's Quidditch team, a sport in the wizarding world where players fly on broomsticks. The first book concludes with Harry's second confrontation with Lord Voldemort, who, in his quest to regain a body, yearns to gain the power of the Philosopher's Stone, a substance that bestows everlasting life and turns any metal into pure gold.[14] + +The series continues with Harry Potter and the Chamber of Secrets, describing Harry's second year at Hogwarts. He and his friends investigate a 50-year-old mystery that appears uncannily related to recent sinister events at the school. Ron's younger sister, Ginny Weasley, enrols in her first year at Hogwarts, and finds an old notebook in her belongings which turns out to be the diary of a previous student, Tom Marvolo Riddle, written during World War II. He is later revealed to be Voldemort's younger self, who is bent on ridding the school of "mudbloods", a derogatory term describing wizards and witches of non-magical parentage. The memory of Tom Riddle resides inside of the diary and when Ginny begins to confide in the diary, Voldemort is able to possess her. + +Through the diary, Ginny acts on Voldemort's orders and unconsciously opens the "Chamber of Secrets", unleashing an ancient monster, later revealed to be a basilisk, which begins attacking students at Hogwarts. It kills those who make direct eye contact with it and petrifies those who look at it indirectly. The book also introduces a new Defence Against the Dark Arts teacher, Gilderoy Lockhart, a highly cheerful, self-conceited wizard with a pretentious facade, later turning out to be a fraud. Harry discovers that prejudice exists in the Wizarding World through delving into the school's history, and learns that Voldemort's reign of terror was often directed at wizards and witches who were descended from Muggles. + +Harry also learns that his ability to speak the snake language Parseltongue is rare and often associated with the Dark Arts. When Hermione is attacked and petrified, Harry and Ron finally piece together the puzzles and unlock the Chamber of Secrets, with Harry destroying the diary for good and saving Ginny, and, as they learn later, also destroying a part of Voldemort's soul. The end of the book reveals Lucius Malfoy, Draco's father and rival of Ron and Ginny's father, to be the culprit who slipped the book into Ginny's belongings. + +The third novel, Harry Potter and the Prisoner of Azkaban, follows Harry in his third year of magical education. It is the only book in the series which does not feature Lord Voldemort in any form, only being mentioned. Instead, Harry must deal with the knowledge that he has been targeted by Sirius Black, his father's best friend, and, according to the Wizarding World, an escaped mass murderer who assisted in the murder of Harry's parents. As Harry struggles with his reaction to the dementors – dark creatures with the power to devour a human soul and feed on despair – which are ostensibly protecting the school, he reaches out to Remus Lupin, a Defence Against the Dark Arts teacher who is eventually revealed to be a werewolf. Lupin teaches Harry defensive measures which are well above the level of magic generally executed by people his age. Harry comes to know that both Lupin and Black were best friends of his father and that Black was framed by their fourth friend, Peter Pettigrew, who had been hiding as Ron's pet rat, Scabbers.[16] In this book, a recurring theme throughout the series is emphasised – in every book there is a new Defence Against the Dark Arts teacher, none of whom lasts more than one school year. + +Voldemort returns +"The Elephant House", a small, painted red café where Rowling wrote a few chapters of Harry Potter and the Philosopher's Stone +The Elephant House was one of the cafés in Edinburgh where Rowling wrote the first part of Harry Potter. + +The former 1st floor Nicholson's Cafe now renamed Spoon in Edinburgh where J. K. Rowling wrote the first few chapters of Harry Potter and the Philosopher’s Stone. + +The J. K. Rowling plaque on the corner of the former Nicholson's Cafe (now renamed Spoon) at 6A Nicolson St, Edinburgh. +During Harry's fourth year of school (detailed in Harry Potter and the Goblet of Fire), Harry is unwillingly entered as a participant in the Triwizard Tournament, a dangerous yet exciting contest where three "champions", one from each participating school, must compete with each other in three tasks in order to win the Triwizard Cup. This year, Harry must compete against a witch and a wizard "champion" from overseas schools Beauxbatons and Durmstrang, as well as another Hogwarts student, causing Harry's friends to distance themselves from him.[17] + +Harry is guided through the tournament by their new Defence Against the Dark Arts professor, Alastor "Mad-Eye" Moody, who turns out to be an impostor – one of Voldemort's supporters named Barty Crouch, Jr. in disguise, who secretly entered Harry's name into the tournament. The point at which the mystery is unravelled marks the series' shift from foreboding and uncertainty into open conflict. Voldemort's plan to have Crouch use the tournament to bring Harry to Voldemort succeeds. Although Harry manages to escape, Cedric Diggory, the other Hogwarts champion in the tournament, is killed by Peter Pettigrew and Voldemort re-enters the Wizarding World with a physical body. + +In the fifth book, Harry Potter and the Order of the Phoenix, Harry must confront the newly resurfaced Voldemort. In response to Voldemort's reappearance, Dumbledore re-activates the Order of the Phoenix, a secret society which works from Sirius Black's dark family home to defeat Voldemort's minions and protect Voldemort's targets, especially Harry. Despite Harry's description of Voldemort's recent activities, the Ministry of Magic and many others in the magical world refuse to believe that Voldemort has returned. In an attempt to counter and eventually discredit Dumbledore, who along with Harry is the most prominent voice in the Wizarding World attempting to warn of Voldemort's return, the Ministry appoints Dolores Umbridge as the High Inquisitor of Hogwarts and the new Defence Against the Dark Arts teacher. She transforms the school into a dictatorial regime and refuses to allow the students to learn ways to defend themselves against dark magic.[18] + +Hermione and Ron form "Dumbledore's Army", a secret study group in which Harry agrees to teach his classmates the higher-level skills of Defence Against the Dark Arts that he has learned from his previous encounters with Dark wizards. Through those lessons, Harry begins to develop a crush on the popular and attractive Cho Chang. Juggling schoolwork, Umbridge's incessant and persistent efforts to land him in trouble and the defensive lessons, Harry begins to lose sleep as he constantly receives disturbing dreams about a dark corridor in the Ministry of Magic, followed by a burning desire to learn more. An important prophecy concerning Harry and Lord Voldemort is then revealed,[19] and Harry discovers that he and Voldemort have a painful connection, allowing Harry to view some of Voldemort's actions telepathically. In the novel's climax, Harry is tricked into seeing Sirius tortured and races to the Ministry of Magic. He and his friends face off against Voldemort's followers (nicknamed Death Eaters) at the Ministry of Magic. Although the timely arrival of members of the Order of the Phoenix saves the teenagers' lives, Sirius Black is killed in the conflict. + +In the sixth book, Harry Potter and the Half-Blood Prince, Voldemort begins waging open warfare. Harry and his friends are relatively protected from that danger at Hogwarts. They are subject to all the difficulties of adolescence – Harry eventually begins dating Ginny, Ron establishes a strong infatuation with fellow Hogwarts student Lavender Brown, and Hermione starts to develop romantic feelings towards Ron. Near the beginning of the novel, lacking his own book, Harry is given an old potions textbook filled with many annotations and recommendations signed by a mysterious writer titled; "the Half-Blood Prince". This book is a source of scholastic success and great recognition from their new potions master, Horace Slughorn, but because of the potency of the spells that are written in it, becomes a source of concern. + +With war drawing near, Harry takes private lessons with Dumbledore, who shows him various memories concerning the early life of Voldemort in a device called a Pensieve. These reveal that in order to preserve his life, Voldemort has split his soul into pieces, used to create a series of Horcruxes – evil enchanted items hidden in various locations, one of which was the diary destroyed in the second book.[20] Draco, who has joined with the Death Eaters, attempts to attack Dumbledore upon his return from collecting a Horcrux, and the book culminates in the killing of Dumbledore by Professor Snape, the titular Half-Blood Prince. + +Harry Potter and the Deathly Hallows, the last original novel in the series, begins directly after the events of the sixth book. Lord Voldemort has completed his ascension to power and gained control of the Ministry of Magic. Harry, Ron and Hermione drop out of school so that they can find and destroy Voldemort's remaining Horcruxes. To ensure their own safety as well as that of their family and friends, they are forced to isolate themselves. A ghoul pretends to be Ron ill with a contagious disease, Harry and the Dursleys separate, and Hermione wipes her parents' memories and sends them abroad. + +As the trio searches for the Horcruxes, they learn details about an ancient prophecy of the Deathly Hallows, three legendary items that when united under one Keeper, would supposedly allow that person to be the Master of Death. Harry discovers his handy Invisibility Cloak to be one of those items, and Voldemort to be searching for another: the Elder Wand, the most powerful wand in history. At the end of the book, Harry and his friends learn about Dumbledore's past, as well as Snape's true motives – he had worked on Dumbledore's behalf since the murder of Harry's mother. Eventually, Snape is killed by Voldemort out of paranoia. + +The book culminates in the Battle of Hogwarts. Harry, Ron and Hermione, in conjunction with members of the Order of the Phoenix and many of the teachers and students, defend Hogwarts from Voldemort, his Death Eaters, and various dangerous magical creatures. Several major characters are killed in the first wave of the battle, including Remus Lupin and Fred Weasley, Ron's older brother. After learning that he himself is a Horcrux, Harry surrenders himself to Voldemort in the Forbidden Forest, who casts a killing curse (Avada Kedavra) at him. The defenders of Hogwarts do not surrender after learning of Harry's presumed death and continue to fight on. Harry awakens and faces Voldemort, whose Horcruxes have all been destroyed. In the final battle, Voldemort's killing curse rebounds off Harry's defensive spell (Expelliarmus), killing Voldemort. + +An epilogue "Nineteen Years Later"[21] describes the lives of the surviving characters and the effects of Voldemort's death on the Wizarding World. In the epilogue, Harry and Ginny are married with three children, and Ron and Hermione are married with two children.[22] +""".split( + "\n" + ): + if t.strip(): + books_table.insert({"text": t}) + print(list(books_table.find(id={"in": (3, 4)}))) + print(list(books_table.find())) + print("Bottle*", list(books_table.find(_fts_query=[("text", "Bottle*")]))) + print("robin", list(books_table.find(_fts_query=[("text", "robin")]))) + print("Home", list(books_table.find(_fts_query=[("text", "Home")]))) + print("notic*", list(books_table.find(_fts_query=[("text", "notic*")]))) + print( + "sign* AND notic*", + list(books_table.find(_fts_query=[("text", "sign* AND notic*")])), + ) + print( + "sign AND notic*", + list(books_table.find(_fts_query=[("text", "sign AND notic*")])), + ) diff --git a/data_tooling/datastore/utils.py b/data_tooling/datastore/utils.py new file mode 100644 index 0000000..86b29f8 --- /dev/null +++ b/data_tooling/datastore/utils.py @@ -0,0 +1,114 @@ +# Copyright 2021, Ontocord, LLC +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +""" Common utilities for datastorage""" +import os +import sys + +from datasets.utils import logging +from filelock import FileLock, UnixFileLock + +sys.path.append( + os.path.abspath( + os.path.join( + os.path.dirname(__file__), os.path.pardir, os.path.pardir, os.path.pardir + ) + ) +) + +logger = logging.get_logger(__name__) +#################################################################################################### +# some utils + +# if an array is contiguous, return True, and the start and end+1 range usable in 'range(start, end)' +def is_contiguous(arr): + start = None + prev = None + contiguous = True + for i in arr: + if start is None: + start = i + if prev is None or i == prev + 1: + prev = i + continue + contiguous = False + break + return contiguous, start, i + 1 + + +# This is used for seeing if files from a remote drive have finished loading. Files could be in flight while we try to retreive them. +def wait_until_files_loaded(flist, max_tries=120, fs=None): # wait 2 hrs max + if fs is None: + fs = os + if isinstance(flist, str): + flist = [[flist, 0]] + else: + flist = [[f, 0] for f in flist] + for j in range(len(flist) * max_tries): + num_done = 0 + for i, val in enumerate(flist): + if val is None: + num_done += 1 + continue + (f, incr) = val + if incr > max_tries: + raise RuntimeError("Timed out while trying to wait for file " + str(f)) + size1 = fs.stat(f).st_size + time.sleep(min(600, 1 + incr)) + incr += 1 + if fs.stat(f).st_size == size1: + flist[i] = None + num_done += 1 + yield f + else: + flist[i] = [f, incr] + if num_done == len(flist): + return + return + + +class DummyLock: + def __enter__(self): + return self + + def __exit__(self, exc_type, exc_val, exc_tb): + pass + + +# FileLock does not really work for gdrive or other types of shared +# drives (ftp). So we create a SharedFileLock instead, which is not +# guranteed to lock a file, but the best we have. This is because if +# two nodes are trying to write to the same file, gdrive will for +# example create a file.txt and a file(1).txt as the other file being +# written to. +class SharedFileLock(UnixFileLock): + def __init__(self, lock_file, timeout=-1, locks=None): + super().__init__(lock_file, timeout) + self.locks = locks + self.locked = False + + def __enter__(self): + if self.locks is not None and self._lock_file not in self.locks: + self.locks[self._lock_file] = 1 + self.acquire() + self.locked = True + return self + + def __exit__(self, exc_type, exc_val, exc_tb): + if self.locked: + self.release() + if self.locks is not None and self._lock_file in self.locks: + del self.locks[self._lock_file] + self.locked = False + return None diff --git a/data_tooling/index_search/README.md b/data_tooling/index_search/README.md new file mode 100644 index 0000000..f52d479 --- /dev/null +++ b/data_tooling/index_search/README.md @@ -0,0 +1,43 @@ +# Elasticsearch index search experiments + +Early tests to build upon HuggingFace datasets to improving indexing/Search capabilities. + +## Pre-requisites + +Elasticsearch is launched in cluster through docker so go install Docker if not already done: https://docs.docker.com/get-docker/ + +The example is based on a forked version of dataset and some additional dependencies. Use `requirements.txt` to install all the necessary stuff. A conda en + +## Run + +* Go into the `index_search` folder and start Elasticsearch cluster + +``` +cd ./index_search +docker compose up +``` + +* Run the python script + +``` +python datasets_index_search.py +``` + +Note that it will start a ray instance which might require some ports to be open for local communication. + +## TODO list + +Improve datasets indexing capabilities +- [x] test switch to ngram indexing +- [x] add hash for each rows +- [x] parallel processing using ray and dataset shards + - [x] enable re-connection to existing index in ES + - [x] enable continuing indexing process + - [x] ensure no duplicate with mmh3 hash +- [x] instantiate datasets from elasticsearch query +- [x] clear cache when instantiating with new query +- [ ] validate dataset info are propagated +- [ ] check scalability +- ~~allow export of search results in arrow for datasets or jsonl for export => specialized filter operation?~~ +- [ ] secure elasticsearch cluster: free read, protected write +- [x] allow update on the dataset to be reflected with index update diff --git a/data_tooling/index_search/datasets_ES_builder.py b/data_tooling/index_search/datasets_ES_builder.py new file mode 100644 index 0000000..47f7239 --- /dev/null +++ b/data_tooling/index_search/datasets_ES_builder.py @@ -0,0 +1,48 @@ +import simplejson as json +from datasets.packaged_modules.elasticsearch.elasticsearch import ElasticsearchBuilder + +ca_file = "/Users/gdupont/src/github.com/bigscience-workshop/data-tooling/index_search/ca.cert" +with open( + "/Users/gdupont/src/github.com/bigscience-workshop/data-tooling/index_search/credentials.json" +) as f: + credentials = json.load(f) + + the_host = credentials["connection"]["https"]["hosts"][0]["hostname"] + the_port = credentials["connection"]["https"]["hosts"][0]["port"] + + username = credentials["connection"]["https"]["authentication"]["username"] + psw = credentials["connection"]["https"]["authentication"]["password"] + +index_name = "oscar_unshuffled_deduplicated" +oscar_lang_code = "nn" + +elasticsearch_builder = ElasticsearchBuilder( + host=the_host, + port=the_port, + es_username=username, + es_psw=psw, + ca_file=ca_file, + es_index_name=index_name, + es_index_config=None, + query="mykje arbeid og slit", +) + +# elasticsearch_builder = ElasticsearchBuilder( +# host="localhost", +# port="9200", +# es_index_name="oscar_unshuffled_deduplicated", +# es_index_config=es_index_config, +# query='"mykje arbeid og slit"' +# ) + +elasticsearch_builder.download_and_prepare() + +oscar_dataset_filtered = elasticsearch_builder.as_dataset() +print(oscar_dataset_filtered.keys()) + +first_split = next(iter(oscar_dataset_filtered)) + +for i in range(0, 5): + print( + f"- [#{oscar_dataset_filtered[first_split]['id'][i]}] {oscar_dataset_filtered[first_split]['text'][i]}" + ) diff --git a/data_tooling/index_search/datasets_ES_index.py b/data_tooling/index_search/datasets_ES_index.py new file mode 100644 index 0000000..86737bc --- /dev/null +++ b/data_tooling/index_search/datasets_ES_index.py @@ -0,0 +1,95 @@ +import ray +import simplejson as json +from datasets import load_dataset + +# ray config on 4 parallel processing +nb_shard = 4 +ray.init(num_cpus=nb_shard) + +# elasticsearch credentials dev server on IBM cloud +with open("./credentials.json") as f: + credentials = json.load(f) + + the_host = credentials["connection"]["https"]["hosts"][0]["hostname"] + the_port = credentials["connection"]["https"]["hosts"][0]["port"] + + username = credentials["connection"]["https"]["authentication"]["username"] + psw = credentials["connection"]["https"]["authentication"]["password"] + +ca_file = "./ca.cert" + +oscar_lang_code = "nn" +es_index_config = { + "settings": { + "number_of_shards": 1, + "analysis": { + "analyzer": {"ngram_analyzer": {"tokenizer": "ngram_tokenizer"}}, + "tokenizer": { + "ngram_tokenizer": { + "type": "ngram", + "min_gram": 3, + "max_gram": 8, + "token_chars": ["letter", "digit"], + } + }, + }, + }, + "mappings": { + "properties": { + "text": { + "type": "text", + "fields": {"hash": {"type": "murmur3"}}, + "analyzer": "ngram_analyzer", + "similarity": "BM25", + } + } + }, +} + +index = "oscar_unshuffled_deduplicated" + + +# @ray.remote +def index_shard(dataset_shard): + dataset_shard.add_elasticsearch_index( + column="text", + index_name=index, + host=the_host, + port=the_port, + es_username=username, + es_psw=psw, + ca_file=ca_file, + es_index_name=index, + es_index_config=es_index_config, + ) + + +my_dataset = load_dataset( + "oscar", f"unshuffled_deduplicated_{oscar_lang_code}", split="train" +) + +# single thread indexing +index_shard(my_dataset) + +# parallel indexing +# dataset_shards = [my_dataset.shard(nb_shard, i) for i in range(nb_shard)] +# futures = [index_shard.remote(dataset_shard) for dataset_shard in dataset_shards] +# ray.get(futures) + +my_dataset.load_elasticsearch_index( + index_name=index, + host=the_host, + port=the_port, + es_username=username, + es_psw=psw, + ca_file=ca_file, + es_index_name=index, + es_index_config=es_index_config, +) + +K = 10 +scores, retrieved = my_dataset.get_nearest_examples(index, "mykje arbeid og slit", k=K) + +for i in range(0, min(K, len(retrieved))): + print(f"({i + 1})") + print(f'\t@{scores[i]:.2f} - {retrieved["id"][i]} => {retrieved["text"][i]} \n') diff --git a/data_tooling/index_search/datasets_ES_search.py b/data_tooling/index_search/datasets_ES_search.py new file mode 100644 index 0000000..8f3531d --- /dev/null +++ b/data_tooling/index_search/datasets_ES_search.py @@ -0,0 +1,42 @@ +import simplejson as json +from datasets import load_dataset + +ca_file = "./ca.cert" + +with open("./credentials.json") as f: + credentials = json.load(f) + + the_host = credentials["connection"]["https"]["hosts"][0]["hostname"] + the_port = credentials["connection"]["https"]["hosts"][0]["port"] + + username = credentials["connection"]["https"]["authentication"]["username"] + psw = credentials["connection"]["https"]["authentication"]["password"] + +index_name = "oscar_unshuffled_deduplicated" +oscar_lang_code = "nn" + +my_dataset = load_dataset( + "oscar", f"unshuffled_deduplicated_{oscar_lang_code}", split="train" +) + +my_dataset.load_elasticsearch_index( + index_name=index_name, + host=the_host, + port=the_port, + es_username=username, + es_psw=psw, + ca_file=ca_file, + es_index_name=index_name, + es_index_config=None, +) + +print(my_dataset) + +K = 10 +scores, retrieved = my_dataset.get_nearest_examples( + index_name, "mykje arbeid og slit", k=K +) + +for i in range(0, min(K, len(retrieved))): + print(f"({i + 1})") + print(f'\t@{scores[i]:.2f} - {retrieved["id"][i]} => {retrieved["text"][i]} \n') diff --git a/data_tooling/index_search/datasets_remote_ES_IBMcloud.py b/data_tooling/index_search/datasets_remote_ES_IBMcloud.py new file mode 100644 index 0000000..85b1980 --- /dev/null +++ b/data_tooling/index_search/datasets_remote_ES_IBMcloud.py @@ -0,0 +1,37 @@ +import base64 +import ssl + +import simplejson as json +from elasticsearch import Elasticsearch + +with open("./credentials.json") as f: + credentials = json.load(f) + + host = credentials["connection"]["https"]["hosts"][0]["hostname"] + port = credentials["connection"]["https"]["hosts"][0]["port"] + + es_username = credentials["connection"]["https"]["authentication"]["username"] + es_psw = credentials["connection"]["https"]["authentication"]["password"] + + ca_cert = base64.b64decode( + credentials["connection"]["https"]["certificate"]["certificate_base64"] + ) + # context = ssl.create_default_context() + # context.verify_mode = ssl.CERT_REQUIRED + # context.load_verify_locations(cadata=ca_cert) + +context = ssl.create_default_context(cafile="./ca.cert") + +server_url = ( + ("https" if context is not None else "http") + "://" + host + ":" + str(port) +) + +es = Elasticsearch([server_url], http_auth=(es_username, es_psw), ssl_context=context) + +print(f"ES info {json.dumps(es.info(), indent=4 * ' ')}") + +# index_get_response = es.indices.get(index='oscar_unshuffled_deduplicated') +# print(json.dumps(index_get_response, indent=4 * ' ')) + +delete_response = es.indices.delete(index="oscar_unshuffled_deduplicated") +print(json.dumps(delete_response, indent=4 * " ")) diff --git a/data_tooling/index_search/docker-compose.yml b/data_tooling/index_search/docker-compose.yml new file mode 100644 index 0000000..a4bc14a --- /dev/null +++ b/data_tooling/index_search/docker-compose.yml @@ -0,0 +1,83 @@ +version: '2.2' +services: + es01: + image: docker.elastic.co/elasticsearch/elasticsearch:7.13.2 + container_name: es01 + environment: + - node.name=es01 + - cluster.name=es-docker-cluster + - discovery.seed_hosts=es02,es03 + - cluster.initial_master_nodes=es01,es02,es03 + - bootstrap.memory_lock=true + - "ES_JAVA_OPTS=-Xms512m -Xmx512m" + ulimits: + memlock: + soft: -1 + hard: -1 + volumes: + - data01:/usr/share/elasticsearch/data + ports: + - 9200:9200 + networks: + - elastic + + es02: + image: docker.elastic.co/elasticsearch/elasticsearch:7.13.2 + container_name: es02 + environment: + - node.name=es02 + - cluster.name=es-docker-cluster + - discovery.seed_hosts=es01,es03 + - cluster.initial_master_nodes=es01,es02,es03 + - bootstrap.memory_lock=true + - "ES_JAVA_OPTS=-Xms512m -Xmx512m" + ulimits: + memlock: + soft: -1 + hard: -1 + volumes: + - data02:/usr/share/elasticsearch/data + networks: + - elastic + + es03: + image: docker.elastic.co/elasticsearch/elasticsearch:7.13.2 + container_name: es03 + environment: + - node.name=es03 + - cluster.name=es-docker-cluster + - discovery.seed_hosts=es01,es02 + - cluster.initial_master_nodes=es01,es02,es03 + - bootstrap.memory_lock=true + - "ES_JAVA_OPTS=-Xms512m -Xmx512m" + ulimits: + memlock: + soft: -1 + hard: -1 + volumes: + - data03:/usr/share/elasticsearch/data + networks: + - elastic + + kib01: + image: docker.elastic.co/kibana/kibana:7.13.2 + container_name: kib01 + ports: + - 5601:5601 + environment: + ELASTICSEARCH_URL: http://es01:9200 + ELASTICSEARCH_HOSTS: '["http://es01:9200","http://es02:9200","http://es03:9200"]' + networks: + - elastic + +volumes: + data01: + driver: local + data02: + driver: local + data03: + driver: local + +networks: + elastic: + driver: bridge diff --git a/data_tooling/index_search/requirements.txt b/data_tooling/index_search/requirements.txt new file mode 100644 index 0000000..0b348a4 --- /dev/null +++ b/data_tooling/index_search/requirements.txt @@ -0,0 +1,5 @@ +git+https://github.com/ggdupont/datasets@bigscience_datatooling#egg=datasets +elasticsearch==7.10.1 +iso-639==0.4.5 +ray~=1.4.1 +simplejson diff --git a/data_tooling/kenlm_training/.gitignore b/data_tooling/kenlm_training/.gitignore new file mode 100644 index 0000000..3f20ee3 --- /dev/null +++ b/data_tooling/kenlm_training/.gitignore @@ -0,0 +1,27 @@ +# Dataset +/data +/test_data/ +/test_data2/ +/output/ + +# Binary files +/bin/ + +# Third party code +/third_party/ + +# Generic to python +__pycache__/ +*.pyc +.mypy_cache/ + +/scratch/ +/notebooks/ + +/build/ +/cc_net.egg-info/ +/config/ +/dist/ +/pip-wheel-metadata/ + +/.DS_Store diff --git a/data_tooling/kenlm_training/LICENSE b/data_tooling/kenlm_training/LICENSE new file mode 100644 index 0000000..b96dcb0 --- /dev/null +++ b/data_tooling/kenlm_training/LICENSE @@ -0,0 +1,21 @@ +MIT License + +Copyright (c) Facebook, Inc. and its affiliates. + +Permission is hereby granted, free of charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to deal +in the Software without restriction, including without limitation the rights +to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in all +copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE +SOFTWARE. diff --git a/data_tooling/kenlm_training/Makefile b/data_tooling/kenlm_training/Makefile new file mode 100644 index 0000000..a88d956 --- /dev/null +++ b/data_tooling/kenlm_training/Makefile @@ -0,0 +1,240 @@ +# Makefile to install CC-Net and train the LMs. +# `make` or `make help` to get some help. + +# Arguments: +lang?=en +process?=8 +servers?=0 + +# List of languages for LM. +langs?=af,ar,az,be,bg,bn,ca,cs,da,de,el,en,es,et,fa,fi,fr,gu,he,hi,hr,hu,hy,id,\ +is,it,ja,ka,kk,km,kn,ko,lt,lv,mk,ml,mn,mr,my,ne,nl,no,pl,pt,ro,ru,uk,zh + +# Experiment config +NDOC_FOR_LM=1_000_000 +NDOC_FOR_SENTPIECE=400000 +VOCAB_SIZE=65536 + +# Static resources, scripts, ... +KENLM=./bin/lmplz +KENLM_BUILD_BINARY=./bin/build_binary +SPM_TRAIN=./bin/spm_train +SPM_ENCODE=./bin/spm_encode + +# DISTRIBUTE will run locally, or on slurm if "servers" is set. +DISTRIBUTE=xargs -L1 -P $(process) +ifneq ($(servers), 0) + DISTRIBUTE=xargs -L1 -P $(servers) srun -t 240 --mem 5000 +endif + +# PRIVATE +_SEGMENT=2019-09/CC-MAIN-20190215183319-20190215205319-00000 + +help: + # Show help + grep -i -A1 '^[a-z0-9_]*:' Makefile + +# Deletes output files on error (useful when piping output) +SHELL=/bin/bash +.SHELLFLAGS = -o pipefail -c +.DELETE_ON_ERROR: + +install: bin/lid.bin $(KENLM) $(SPM_TRAIN) + # Installs dependencies. + @if [ -f "data" ]; then\ + echo "Please create/simlink a 'data' directory.";\ + fi + @if ! python -c "from cc_net import __main__" 2> /dev/null; then\ + pip install . ;\ + fi + echo " --> All dependencies looks good !" + +dl_lm: + # Download a pretrained language model + mkdir -p data/lm_sp + wget -c -P data/lm_sp http://dl.fbaipublicfiles.com/cc_net/lm/$(lang).arpa.bin + wget -c -P data/lm_sp http://dl.fbaipublicfiles.com/cc_net/lm/$(lang).sp.model + +lm: data/lm_sp/$(lang).sp.model data/lm_sp/$(lang).arpa.bin + # Computes a 5-gram LM for the given language -> make lang=it lm + # Restricted to the first NDOC_FOR_LM documents + +sp: data/lm_sp/$(lang).sp.model + # Train a sentence piece model on Wikipedia -> make lang=it sp + +get_lang = $(firstword $(subst ., ,$1)) + +all_lms: + # Train a list of language models -> make process=10 langs=en,it,fr all_lms + # Defaults to the LMs trained in the paper. + echo "$(langs)" \ + | tr -s ', ' '\n' | awk '{print "data/lm_sp/" $$0 ".arpa.bin"}' \ + | $(DISTRIBUTE) make + +dl_all_lms: + # Download all pretrained language models + echo "$(langs)" \ + | tr -s ', ' '\n' | awk '{print "lang=" $$0 " dl_lm"}' \ + | $(DISTRIBUTE) make + +%.arpa.bin: %.arpa + # Compress a learned LM to a binary format. + $(KENLM_BUILD_BINARY) $< $@ + +%.vocab.txt: %.txt + # Extracts the vocabulary of a corpus. + # Restricted to the first NDOC_FOR_LM documents and VOCAB_SIZE top words. + cat $< | tr ' ' '\n' | sort | uniq -c | sort -rn > $@.tmp_sort + head -$(VOCAB_SIZE) $@.tmp_sort | sed "s/^ *//" | cut -d' ' -f2 > $@ + rm $@.tmp* + echo Extracted `wc -l $@` words + +#5 +data/lm_sp/%.arpa: data/cirrus/sp/%.opening.txt + mkdir -p $(@D) + $(KENLM) -o 5 -S 8G -T /tmp --vocab_estimate $(VOCAB_SIZE) --discount_fallback \ + < $< > $@ + +#3 +data/lm_sp/%.sp.model: data/cirrus/txt/%.opening.txt + mkdir -p $(@D) + $(SPM_TRAIN) --input=$< \ + --vocab_size=$(VOCAB_SIZE) --hard_vocab_limit \ + --character_coverage=0.9995 \ + --model_type=unigram \ + --model_prefix=$(basename $@) \ + || echo "WARNING: Corpus is too small, will train smaller model" && \ + $(SPM_TRAIN) --input=$< \ + --vocab_size=40000 \ + --character_coverage=0.9995 \ + --model_type=unigram \ + --model_prefix=$(basename $@) + + echo "Trained SentencePiece model with `wc -l $(basename $@).vocab` pieces" + +#4 +data/cirrus/sp/%.opening.txt: data/cirrus/gz/%.json.gz data/lm_sp/%.sp.model + $(SPM_ENCODE) \ + --model=$(word 2,$^) \ + --output_format=piece \ + < <(python get_wiki_cirrus.py opening --file $< --n_docs $(NDOC_FOR_LM)) \ + > $@ + +#2 +data/cirrus/txt/%.opening.txt: data/cirrus/gz/%.json.gz + python get_wiki_cirrus.py opening \ + --n_docs $(NDOC_FOR_LM) \ + --file $< --output $@ + +#1 +data/cirrus/gz/%.json.gz: + mkdir $(@D) + python get_wiki_cirrus.py dl --lang $(call get_lang,$(@F)) --output_dir $(@D) + +clean: + # Remove intemediary files, dataset, third_party sources + # We don't need the vocab files nor the text version of the LM. + rm -r data/cirrus + rm -r data/lm_sp/*.arpa data/lm_sp/*.vocab + rm -r third_party + +# Installation +bin/lid.bin: + # DL languages id from Fasttext releases. + mkdir -p $(@D) + wget https://dl.fbaipublicfiles.com/fasttext/supervised-models/lid.176.bin -O $@ + +third_party/kenlm: + # Download kenlm sources: https://kheafield.com/code/kenlm/" + mkdir -p $(@D) + wget --no-check-certificate -O - https://kheafield.com/code/kenlm.tar.gz | tar -xz -C $(@D) + +bin/lmplz: third_party/kenlm + # Compiles kenlm binaries + mkdir -p $(@D) + mkdir -p $ int: + return np.frombuffer(b[:HASH_SIZE], dtype=HASH_TYPE, count=1, offset=0).item(0) + + +def str_hash(s: str) -> int: + h = hashlib.sha1(bytes(s, encoding="utf-8")) + return _b2i(h.digest()) + + +log = logging.getLogger(__name__).info + + +def run_par(processes): + # This is different from multiprocessing.map since it allows for kwargs. + processes = list(processes) + if len(processes) == 1 or DISABLE_MULTI_PROCESSING: + for f, args, kwargs in processes: + f(*args, **kwargs) + return + + log(f"Starting {len(processes)} subprocess") + processes = [ + multiprocessing.Process(target=f, args=a, kwargs=kw) for (f, a, kw) in processes + ] + for p in processes: + p.start() + for p in processes: + p.join() + failed = 0 + for p in processes: + if p.exitcode != 0: + log(f"Process failed with code {p.exitcode}: {p}") + failed += 1 + assert failed == 0, f"{failed} processes failed..." + + +def split_file(file, n_splits): + for i in range(n_splits): + yield jsonql.SplitFile(file, i, n_splits) + + +def merge(hashes_1, hashes_2, output): + if isinstance(hashes_1, str): + h1 = FlatHashSet() + h1.load(hashes_1) + else: + h1 = hashes_1 + + if isinstance(hashes_2, str): + h2 = FlatHashSet() + h2.load(hashes_2) + else: + h2 = hashes_2 + + h2_np = np.fromiter(h2.keys(), dtype=FlatHashSet.dtype, count=len(h2)) + dup = h1.__contains__(h2_np) + + # Dups between h1 and h2 will be set to 1, keys unique to h2 are copied to + # h1 with their value. + h1[h2_np] = dup + if output: + h1.dump(output) + return h1 + + +def merge_shard(hash_files, output): + h = FlatHashSet() + h.load(hash_files[0]) + for hash_file in hash_files[1:]: + h = merge(h, hash_file, output=None) + print(f"Merged {hash_file}. We now have {len(h)} hashes.") + + h.dump(output) + print(f"Saved {len(h)} hashes to {output}.") + + +def _dump_sentence_hashes(source: Path, output: Path, field: str): + treated = 0 + started = time.time() + with open(output, "wb") as o: + for doc in jsonql.read_jsons(source): + content = doc.get(field) + if not content: + continue + h = compute_hashes(content) + if h is None: + continue + h.tofile(o) + treated += 1 + if treated % 100_000 == 0: + delay = time.time() - started + log( + f"Computed {treated} documents hashes in {delay / 3600:.2f}h ({treated / delay} doc / s)" + ) + + +def _remove_duplicate_hashes(duplicates, source, output): + batch_size = 100_000 + n_lines, n_lines_kept = 0, 0 + with open(source, "rb") as f, open(output, "wb") as o: + log(f"Opening {source} with mode rb") + log(f"Opening {output} with mode wb") + while True: + hashes = np.fromfile(f, dtype=HASH_TYPE, count=batch_size) + if hashes.size == 0: + break + + keep = duplicates[hashes] < 1 + kept = keep.sum() + hashes *= keep + hashes.tofile(o) + + n_lines += hashes.size + n_lines_kept += kept + + removed = n_lines - n_lines_kept + selectivity = n_lines_kept / n_lines if n_lines else 0 + log(f"Removed {removed} duplicate hashes with selectivity: {selectivity:3.1%}") + + +def remove_duplicates_sharded( + files: List[Path], + outputs: List[Path], + hashes_dir: FilesOrDir, + field: str, + group_hashes: int = 1, + tmp_dir: Path = None, + min_len: int = 0, +): + """Remove duplicates in several passes, when all hashes don't fit in RAM. + + Note: The current implementation is not doing a 'perfect' deduplication. + If a hash appear exactly once in each shard of hashes it won't be detected + as a duplicate. This can be fixed if hashes are fully dedup beforehand. + """ + assert len(files) == len(outputs) + + if isinstance(hashes_dir, list): + hashes_files = hashes_dir + else: + hashes_files = sorted( + h for h in Path(hashes_dir).iterdir() if h.suffix == ".bin" + ) + + assert len(hashes_files) > 0, f"no hashes files found in: {hashes_dir}" + + if len(hashes_files) <= group_hashes: + log(f"All hashes can be done in one pass, using DuplicatesRemover on {files}") + rm_dups = DuplicatesRemover(field, hashes_files) + rm_dups._prepare() + run_par( + (jsonql.run_pipes, (rm_dups,), dict(file=f, output=o)) + for f, o in zip(files, outputs) + ) + return + + log(f"Starting deduplicate_sharded on {files}.") + tmp_directory = tempfile.TemporaryDirectory(dir=str(tmp_dir) if tmp_dir else None) + + def tmp_files(i): + return [ + Path(tmp_directory.name) / (f.name.split(".")[0] + f".{i}.bin") + for f in files + ] + + last = tmp_files(0) + run_par((_dump_sentence_hashes, (f, tmp, field), {}) for f, tmp in zip(files, last)) + + if isinstance(hashes_dir, list): + hashes_files = hashes_dir + else: + hashes_files = sorted( + h for h in Path(hashes_dir).iterdir() if h.suffix == ".bin" + ) + for i, group in enumerate(jsonql.grouper(hashes_files, group_hashes)): + hashes = FlatHashSet() + for h in group: + hashes.load(h) + log(f"Loaded {h}, up to {len(hashes)} hashes ({mem_footprint_gb()}GB)") + + intermediates = tmp_files(i + 1) + # Remove hashes in parallel. Since modern OS have "copy-on-write" and + # `hashes` is read-only, we will only have one version of it in RAM. + run_par( + (_remove_duplicate_hashes, (hashes, f, tmp), {}) + for f, tmp in zip(last, intermediates) + ) + # Force hashes to be freed, before we start allocating a new one. + del hashes + gc.collect() + + for tmp in last: + os.remove(tmp) + last = intermediates + + def finalize(source, dedup_hashes, min_len): + n_chars, n_chars_kept = 0, 0 + with open(dedup_hashes, "rb") as hashes: + for doc in jsonql.read_jsons(source): + content = doc.get(field) + if not content or len(content) < min_len: + continue + sentences = content.split("\n") + doc_hashes = np.fromfile(hashes, dtype=HASH_TYPE, count=len(sentences)) + chars, kept_chars = finalize_doc(doc, field, doc_hashes) + n_chars += chars + n_chars_kept += kept_chars + yield doc + selectivity = n_chars_kept / n_chars if n_chars else 0 + log(f"Kept {n_chars_kept} chars out of {n_chars} ({selectivity:.1%}).") + + dedup_hashes = last + run_par( + [ + ( + jsonql.run_pipe, + (finalize,), + dict(kwargs=dict(dedup_hashes=h, min_len=min_len), file=f, output=o), + ) + for h, f, o in zip(dedup_hashes, files, outputs) + ] + ) + + tmp_directory.cleanup() + + +def compute_hashes(content) -> Optional[np.ndarray]: + if not content: + return None + lines = content.split("\n") + # save hashes as bytes but reinterpret them as uint64. + hashes = np.fromiter( + ( + hashlib.sha1(bytes(normalize_for_dedup(l), encoding="utf-8")).digest()[ + :HASH_SIZE + ] + for l in lines + ), + dtype=np.dtype((bytes, HASH_SIZE)), + count=len(lines), + ) + return np.ndarray(dtype=HASH_TYPE, buffer=hashes.data, shape=hashes.shape) + + +def finalize_doc(doc, field, hashes=None): + content = doc.get(field) + lines = content.split("\n") + n_chars = len(content) + if "original_nlines" not in doc: + doc["original_nlines"] = doc.get("nlines", len(lines)) + if "original_length" not in doc: + doc["original_length"] = doc.get("length", n_chars) + if hashes is None: + hashes = doc.pop(field + "_hash") + + # Remove duplicates inside doc + seen: Set[int] = set() + original_line_ids = doc.get("line_ids", range(len(hashes))) + line_ids = [] + new_lines = [] + for l, line, h in zip(original_line_ids, lines, hashes): + if h not in seen and h != 0: + line_ids.append(l) + new_lines.append(line) + seen.add(h) + + doc[field] = "\n".join(new_lines) + doc["nlines"] = len(line_ids) + n_chars_kept = len(doc[field]) + doc["length"] = n_chars_kept + doc["line_ids"] = line_ids + return n_chars, n_chars_kept + + +class HashesCollector(jsonql.Transformer): + """ + Collect all hashes found of lines found in the `field` of the source documents. + """ + + parallelisable = False + + def __init__( + self, field: str, output: Path = None, hashes: AbstractDedupHashSet = None + ): + super().__init__() + self.n_lines = 0 + self.field = field + self.output = output + self.hashes = FlatHashSet() if hashes is None else hashes + self.num_hashes_end = 0 + self.num_hashes_start = len(self.hashes) + + def summary(self) -> List[str]: + summ = super().summary() + h = self.num_hashes_end if self.hashes is None else len(self.hashes) + h = (h - self.num_hashes_start) // 1000 + max_mem = mem_footprint_gb() + n = self.n_lines // 1000 + summ.append( + f"Found {h:_}k unique hashes over {n:_}k lines. Using {max_mem:.1f}GB of RAM." + ) + return summ + + def do(self, doc: dict) -> None: + doc_hashes = compute_hashes(doc.get(self.field)) + if doc_hashes is None: + return + self.hashes.add(doc_hashes) + self.n_lines += doc_hashes.size + + def close(self): + if self.output and self.hashes: + self.hashes.dump(self.output) + self.log(f"Saved {len(self.hashes)} hashes to {self.output}") + # Save the number of hashes. + self.num_hashes_end = len(self.hashes) + # Free up mem even if the transformer is kept somewhere else. + self.hashes = None # type: ignore + + +class DuplicatesRemover(jsonql.Transformer): + """DuplicatesRemover""" + + # The hashes can't be pickled so they will have to be read back from disk. + warn_when_pickling = True + + def __init__(self, field: str, hashes_files: List[Path], collect: bool = False): + """ + Remove duplicates + """ + super().__init__() + self.field = field + self.collect = collect + + self.hashes_files = hashes_files + self.duplicates: Optional[AbstractDedupHashSet] = None + + self.n_lines, self.n_lines_kept = 0, 0 + self.n_chars, self.n_chars_kept = 0, 0 + + def _prepare(self): + if self.duplicates is not None: + return + self.duplicates = FlatHashSet() + + start = time.time() + for h in self.hashes_files: + shard_start = time.time() + self.duplicates.load(str(h)) + delay = time.time() - shard_start + self.log( + f"Loaded hashes from {h} ({mem_footprint_gb():.3f}GB total, took {delay / 60:.1}m)" + ) + + delay = time.time() - start + self.log( + f"Loaded {len(self.duplicates):_d} hashes from {len(self.hashes_files)} files. ({mem_footprint_gb():.1f}GB total, took {delay / 60:.1}m)" + ) + + def do(self, doc: dict) -> Optional[dict]: + content = doc.get(self.field) + if not content: + return None + doc_hashes = compute_hashes(content) + + assert self.duplicates is not None + seen = ( + self.duplicates.add(doc_hashes) + if self.collect + else self.duplicates[doc_hashes] + ) + keep = seen < True + kept = keep.sum() + if kept == 0: + return None + doc_hashes = doc_hashes * keep + self.n_lines += keep.size + self.n_lines_kept += kept + chars, kept_chars = finalize_doc(doc, self.field, hashes=doc_hashes) + self.n_chars += chars + self.n_chars_kept += kept_chars + return doc + + def summary(self) -> List[str]: + summ = super().summary() + end_time = time.time() + n_lines_kept, n_lines, n_docs = self.n_lines_kept, self.n_lines, self.processed + speed = n_docs / (end_time - self.start_time) + summ.append( + f"Processed {self.n_lines} lines in {n_docs} docs. [{speed:.1f} doc/s]" + ) + selectivity = self.n_lines_kept / self.n_lines if n_lines else 0 + summ.append(f"Kept {n_lines_kept} lines out of {n_lines} ({selectivity:.1%}).") + + n_chars_kept, n_chars = self.n_chars_kept, self.n_chars + selectivity = n_chars_kept / n_chars if n_chars else 0 + summ.append(f"Kept {n_chars_kept} chars out of {n_chars} ({selectivity:.1%}).") + return summ + + +def deduplicate( + file: jsonql.ReadableFileLike, field: str = "raw_content" +) -> Iterable[dict]: + """Remove duplicates of the given file (but keep the first occurence).""" + dup_remover = DuplicatesRemover(field, [], collect=True) + return dup_remover.map(jsonql.read_jsons(file)) + + +def deduplicate_two_pass( + file: jsonql.FileDescriptor, field: str = "raw_content" +) -> Iterable[dict]: + """Remove duplicates of the given file (even removing the first occurence). + + This is what is done in the paper, and in mine.py + """ + try: + if isinstance(file, Path): + hash_file: Path = file.with_suffix(".bin") + else: + hash_file = jsonql._tmp(Path("hashes.bin")) + jsonql.run_pipes( + jsonql.JsonReader(), HashesCollector(field, output=hash_file), file=file + ) + dup_remover = DuplicatesRemover(field, [hash_file]) + return dup_remover.map(jsonql.read_jsons(file)) + finally: + if hash_file.exists(): + hash_file.unlink() diff --git a/data_tooling/kenlm_training/cc_net/execution.py b/data_tooling/kenlm_training/cc_net/execution.py new file mode 100644 index 0000000..6ab09a5 --- /dev/null +++ b/data_tooling/kenlm_training/cc_net/execution.py @@ -0,0 +1,203 @@ +# Copyright (c) Facebook, Inc. and its affiliates. +# +# This source code is licensed under the MIT license found in the +# LICENSE file in the root directory of this source tree. +# + +import functools +import itertools +import logging +import os +import sys +import time +import warnings +from pathlib import Path +from typing import Callable, Dict, Iterable, List, Optional, Sequence, Sized + +import submitit +from typing_extensions import Protocol + + +class Executor(Protocol): + def __call__(self, function: Callable[..., str], *args: Iterable) -> None: + ... + + +class SubmititRetryOnTimeout(submitit.helpers.Checkpointable): + def __init__(self, fn: Callable): + self.fn = fn + self.__name__ = fn.__name__ + + def __call__(self, *args, **kwargs): + return self.fn(*args, **kwargs) + + +def get_executor( + name: str, + log_dir: Path, + execution: str, + timeout_hour: float = 1.0, + mem_gb: int = 1, + cpus: int = 1, + task_parallelism: int = -1, + options: dict = {}, +) -> Executor: + + execution_mode = execution.split(",")[0] + options.update( + {kv.split("=", 1)[0]: kv.split("=", 1)[1] for kv in execution.split(",")[1:]} + ) + + if execution_mode == "mp": + warnings.warn("Execution mode 'mp' is deprecated, use 'local'.") + execution_mode = "local" + + cluster = None if execution_mode == "auto" else execution_mode + # use submitit to detect which executor is available + ex = submitit.AutoExecutor(log_dir, cluster=cluster) + + if ex.cluster == "local": + # LocalExecutor doesn't respect task_parallelism + return functools.partial(custom_map_array, ex, task_parallelism) + if ex.cluster == "debug": + raise ValueError("Debug mode not supported") + + # We are on slurm + if task_parallelism == -1: + task_parallelism = 500 + + ex.update_parameters( + name=name, + timeout_min=int(timeout_hour * 60), + mem_gb=mem_gb, + cpus_per_task=cpus, + slurm_array_parallelism=task_parallelism, + **options, + ) + return functools.partial(map_array_and_wait, ex) + + +def map_array_and_wait( + ex: submitit.AutoExecutor, function: Callable[..., str], *args: Iterable +): + f_name = function.__name__ + + assert len(args) > 0, f"No arguments passed to {f_name}" + approx_length = _approx_length(*args) + + print(f"Submitting {f_name} in a job array ({approx_length} jobs)") + jobs = ex.map_array(function, *args) + if not jobs: + return + failed_jobs = [] + done = 0 + total = len(jobs) + job_array_id = jobs[0].job_id.split("_")[0] + print(f"Started {f_name} in job array {job_array_id} ({len(jobs)} jobs).") + for job in submitit.helpers.as_completed(jobs): + done += 1 + e = job.exception() + if not e: + print(f"Finished job {job.job_id} ({done} / {total}).", job.result()) + continue + + print(f"Failed job {job.job_id} ({done} / {total}):", e) + failed_jobs.append(job) + + if failed_jobs: + n_failures = 10 + message = f"{len(failed_jobs)} / {done} jobs failed while running {f_name}" + print(message) + for job in failed_jobs[:n_failures]: + print(f"Failed {job.job_id} -> {job.paths.stderr}") + if len(failed_jobs) > n_failures: + print(f"... ({len(failed_jobs) - n_failures} failed job skipped)") + raise Exception(message) + + +def _approx_length(*args: Iterable): + for a in args: + if isinstance(a, Sized): + return len(a) + return -1 + + +def custom_map_array( + ex: submitit.AutoExecutor, + parallelism: int, + function: Callable[..., Optional[str]], + *args: Iterable, +) -> None: + f_name = function.__name__ + assert len(args) > 0, f"No arguments passed to {f_name}" + + jobs_args = list(zip(*args)) + total = len(jobs_args) + if parallelism < 0: + parallelism = os.cpu_count() or 0 + assert parallelism >= 0, f"Can't run any jobs with task_parallelism={parallelism}" + print(f"Submitting {total} jobs for {f_name}, with task_parallelism={parallelism}") + enqueued = 0 + done = 0 + running_jobs: List[submitit.Job] = [] + failed_jobs: List[submitit.Job] = [] + + while done < len(jobs_args): + # Try to queue more job if we have some bandwidth. + if enqueued < total and len(running_jobs) < parallelism: + running_jobs.append(ex.submit(function, *jobs_args[enqueued])) + enqueued += 1 + continue + + # Else wait for some job to finish + if not running_jobs: + warnings.warn( + f"No more running jobs, yet we submitted only {enqueued} / {total} and finished {done} / {total}" + ) + break + + job = get_next_job(running_jobs) + running_jobs.remove(job) + done += 1 + e = job.exception() + if not e: + print(f"Finished job {job.job_id} ({done} / {total}).", job.result()) + continue + + print(f"Failed job {job.job_id} ({done} / {total}):", e) + failed_jobs.append(job) + + if failed_jobs: + n_failures = 10 + message = f"{len(failed_jobs)} / {done} jobs failed while running {f_name}" + print(message) + for job in failed_jobs[:n_failures]: + print(f"Failed {job.job_id} -> {job.paths.stderr}") + if len(failed_jobs) > n_failures: + print(f"... ({len(failed_jobs) - n_failures} failed job skipped)") + raise Exception(message) + + +def get_next_job( + jobs: Sequence[submitit.Job], poll_frequency: float = 10 +) -> submitit.Job: + """ + Waits for any of the job to finish and returns it. + + jobs: list of jobs + poll_frequency: frequency in second at which we check job status + """ + start = time.time() + waiting = False + while True: + for job in jobs: + if job.done(): + return job + if not waiting: + job_ids = [j.job_id for j in jobs[:4]] + suffix = "..." if len(jobs) > 4 else "" + print( + f"Waiting on {len(jobs)} running jobs. Job ids: {','.join(job_ids)}{suffix}" + ) + waiting = True + time.sleep(poll_frequency) diff --git a/data_tooling/kenlm_training/cc_net/flat_hash_set.py b/data_tooling/kenlm_training/cc_net/flat_hash_set.py new file mode 100644 index 0000000..f7529fe --- /dev/null +++ b/data_tooling/kenlm_training/cc_net/flat_hash_set.py @@ -0,0 +1,247 @@ +# Copyright (c) Facebook, Inc. and its affiliates. +# +# This source code is licensed under the MIT license found in the +# LICENSE file in the root directory of this source tree. +# + +import sys +import time +import warnings +from typing import Iterable, Iterator, Sequence, Sized, Tuple, Type + +import numpy as np + +HASH_TYPE: Type[np.uint64] = np.uint64 + +GETPY_WARNING = False + + +class AbstractDedupHashSet(Sized, Iterable[np.uint64]): + """A dict-like that returns `True` for keys that have been added more than once. + + The API is batched and expect np.array as input. This batching grants better + perf when using the C++ implementation. + """ + + dtype: Type[np.uint64] = HASH_TYPE + + def __repr__(self): + implementation = type(self).__name__ + return f"[{implementation}, len: {len(self)}" + + def __len__(self) -> int: + ... + + def __contains__(self, values: Sequence[np.uint64]) -> np.ndarray: + ... + + def __getitem__(self, values) -> np.ndarray: + ... + + def __setitem__(self, keys, values) -> None: + ... + + def items(self) -> Iterable[Tuple[np.uint64, np.uint8]]: + ... + + def keys(self) -> Iterable[np.uint64]: + ... + + def __iter__(self) -> Iterator[np.uint64]: + return iter(self.keys()) + + def add(self, h, contains=None): + """Add the given keys. First time a key is added the value is set to 0, + then it's set to one.""" + if not isinstance(h, np.ndarray): + h = np.array(h, dtype=HASH_TYPE) + if contains is None: + contains = self.__contains__(h) + + self.__setitem__(h, contains) + return contains + + def merge(self, keys, values): + contains = self.__contains__(keys) + self.__setitem__(keys, contains | values) + + def dump(self, filename): + return self.dump_np(filename) + + def load(self, filename): + return self.load_np(filename) + + def dump_np(self, filename): + kv_type = np.dtype([("k", HASH_TYPE), ("v", np.uint8)]) + items = np.fromiter(self.items(), dtype=kv_type, count=len(self)) + with open(filename, "wb") as f: + np.save(f, items) + + def load_np(self, filename): + items = np.load(str(filename)) + keys = items["k"].copy() + values = items["v"].copy() + self.merge(keys, values) + + def dump_np2(self, filename): + keys = np.fromiter( + (k for (k, v) in self.items()), dtype=HASH_TYPE, count=len(self) + ) + with open(filename, "wb") as f: + np.save(f, keys) + + values = np.fromiter( + (v for (k, v) in self.items()), dtype=np.uint8, count=len(self) + ) + with open(str(filename) + ".val", "wb") as f: + np.save(f, values) + + def load_np2(self, filename): + keys = np.load(filename) + values = np.load(str(filename) + ".val") + self.merge(keys, values) + + +class NaiveHashSet(dict, AbstractDedupHashSet): + """Pure python implementation of AbstractDedupHashSet. + + This implementation is quite fast, since Python dict are heavily optimized. + """ + + def __init__(self, iterable=None): + super().__init__() + global GETPY_WARNING + if GETPY_WARNING: + warnings.warn( + "Module 'getpy' not found. Deduplication will take more RAM." + " Try `pip install cc_net[getpy]" + ) + GETPY_WARNING = False + + def __contains__(self, values): + """Returns `True` if the object has been added at list once.""" + contains_point = super().__contains__ + return np.fromiter( + map(contains_point, values), count=len(values), dtype=np.uint8 + ) + + def __getitem__(self, values): + """Returns `True` if the object has been added at list twice.""" + get_point = super().get + return np.fromiter( + map(lambda x: get_point(x, False), values), + count=len(values), + dtype=np.uint8, + ) + + def __setitem__(self, keys, values): + assert len(keys) == len(values) + for k, v in zip(keys, values): + dict.__setitem__(self, k, v) + + +try: + import getpy as gp # type: ignore + + class _FlatHashSet(gp.Dict, AbstractDedupHashSet): + """C++ backed implementation of AbstractDedupHashSet. + + This implementation is slightly slower than the Python one but uses + 3x less RAM. + See https://github.com/atom-moyer/getpy. + """ + + def __init__(self): + super().__init__(HASH_TYPE, np.uint8, default_value=False) + + def __contains__(self, h): + """Returns `True` if the object has been added at list once.""" + if not isinstance(h, np.ndarray): + h = np.array(h, dtype=HASH_TYPE) + c = gp.Dict.__contains__(self, h) + c.dtype = np.uint8 + return c + + def dump(self, filename): + return self.dump_gp(filename) + + def load(self, filename): + return self.load_gp(filename) + + def dump_gp(self, filename): + return gp.Dict.dump(self, str(filename)) + + def load_gp(self, filename): + """Override gp.Dict.load, to correctly merge values instead of overwriting.""" + other = gp.Dict(HASH_TYPE, np.uint8, default_value=False) + other.load(str(filename)) + n = len(other) + keys = np.fromiter( + (k for (k, v) in other.items()), dtype=HASH_TYPE, count=n + ) + values = np.fromiter( + (v for (k, v) in other.items()), dtype=np.uint8, count=n + ) + self.merge(keys, values) + + FlatHashSet: Type[AbstractDedupHashSet] = _FlatHashSet +except ImportError: + GETPY_WARNING = True + FlatHashSet = NaiveHashSet + + +def timeit(message, function, *args): + start = time.time() + function(*args) + end = time.time() + print(message, f"took {end - start:.0f}s") + + +def compare_load(*filenames): + assert filenames, "No file given" + + def load_list(): + hashes = [] + for f in filenames: + h = FlatHashSet() + h.load(f) + print(f"Loaded {h} from {f}.") + hashes.append(h) + return hashes + + def load_all(load, ext): + hashes = FlatHashSet() + for f in filenames: + load(hashes, f + ext) + + def dump_all(hashes, dump, ext): + for h, f in zip(hashes, filenames): + dump(h, f + ext) + + hashes = load_list() + dump_gp = getattr(FlatHashSet, "dump_gp") + if dump_gp is not None: + timeit("Dumping using gp.dump", dump_all, hashes, dump_gp, ".gp.test") + timeit("Dumping using dump_np", dump_all, hashes, FlatHashSet.dump_np, ".npy.test") + timeit( + "Dumping using dump_np2", dump_all, hashes, FlatHashSet.dump_np2, ".npy2.test" + ) + + load_gp = getattr(FlatHashSet, "load_gp") + if load_gp is not None: + timeit("Loading using gp.load", load_all, load_gp, ".gp.test") + timeit("Loading using load_np", load_all, FlatHashSet.load_np, ".npy.test") + timeit("Loading using load_np2", load_all, FlatHashSet.load_np2, ".npy2.test") + + # Loading 10 shards: + # [dedup] Dumping using gp.dump took 52s + # [dedup] Dumping using dump_np took 270s + # [dedup] Dumping using dump_np2 took 483s + # + # [dedup] Loading using gp.load took 654s + # [dedup] Loading using load_np took 82s + # [dedup] Loading using load_np2 took 76s + + +if __name__ == "__main__": + compare_load(*sys.argv[1:]) diff --git a/data_tooling/kenlm_training/cc_net/get_hf_dataset.py b/data_tooling/kenlm_training/cc_net/get_hf_dataset.py new file mode 100644 index 0000000..3d2a217 --- /dev/null +++ b/data_tooling/kenlm_training/cc_net/get_hf_dataset.py @@ -0,0 +1,54 @@ +from typing import Optional + +import func_argparse +from datasets import load_dataset +from tqdm import tqdm + +from cc_net import text_normalizer + + +def dl( + dataset: str, + output_file: str, + name: Optional[str] = None, + data_dir: Optional[str] = None, + data_files: Optional[str] = None, + split: Optional[str] = None, + streaming: bool = True, + accent: bool = False, + case: bool = False, + numbers: bool = True, + punct: int = 1, + max_docs: Optional[int] = None, + seed: int = 0, + buffer_size: int = 10000, +): + """Download dataset from the Hugging Face hub.""" + dataset = load_dataset( + dataset, + name=name, + data_dir=data_dir, + data_files=data_files, + split=split, + streaming=streaming, + ) + dataset_norm = dataset.map( + lambda x: text_normalizer.normalize( + x["text"], accent=accent, case=case, numbers=numbers, punct=punct + ) + ) + dataset_norm = dataset_norm.shuffle(buffer_size=buffer_size, seed=seed) + count = 0 + with open(output_file, "w") as o: + with tqdm(total=max_docs) as pbar: + for doc in dataset_norm: + count += 1 + doc = doc.rstrip("\n") + print(doc, file=o) + if max_docs and count == max_docs: + break + pbar.update(1) + + +if __name__ == "__main__": + func_argparse.main(dl) diff --git a/data_tooling/kenlm_training/cc_net/get_wiki_cirrus.py b/data_tooling/kenlm_training/cc_net/get_wiki_cirrus.py new file mode 100644 index 0000000..6be2cb0 --- /dev/null +++ b/data_tooling/kenlm_training/cc_net/get_wiki_cirrus.py @@ -0,0 +1,149 @@ +# Copyright (c) Facebook, Inc. and its affiliates. +# +# This source code is licensed under the MIT license found in the +# LICENSE file in the root directory of this source tree. +# + +""" +Creates mono-lingual corpus from Wikipedia. +""" + +import functools +import re +import subprocess +import urllib.request +from pathlib import Path +from typing import Dict + +import func_argparse +from bs4 import BeautifulSoup # type: ignore + +from cc_net import jsonql, text_normalizer + +CIRRUS_URL = "https://dumps.wikimedia.org/other/cirrussearch" +CIRRUS_DUMP_RE = re.compile(r"^(.*)wiki-\d+-cirrussearch-content\.json\.gz") + + +def tmp(file: Path) -> Path: + return file.parent / ("tmp." + file.name) + + +def opening( + file: Path, + output: Path = None, + n_docs: int = 1_000_000, + accent: str = "False", + case: str = "False", + numbers: str = "True", + punct: int = 1, +): + """Will dump the tokenized opening text of the given Wikipedia. + + Args: + - file: File containing the Wikipedia dump. + - output: Output file. + - n_docs: How many docs to parse + - tokenize: whether to tokenize the text + - lang: Language code used to chose the tokenizer + """ + assert file.exists() + extracted = jsonql.run_pipes( + functools.partial( + extract_opening_text, + n_docs=n_docs, + accent=accent == "True", + case=case == "Trrue", + numbers=numbers == "True", + punct=punct, + ), + file=file, + output=tmp(output) if output else None, + ) + if output: + tmp(output).replace(output) + return extracted + + +def extract_opening_text( + source, n_docs: int = 10_000, accent=False, case=True, numbers=True, punct=1 +): + i = 0 + for doc in jsonql.read_jsons(source): + if not doc: + continue + + text = doc.get("opening_text") + if not text: + continue + + yield text_normalizer.normalize( + text, accent=accent, case=case, numbers=numbers, punct=punct + ) + i += 1 + if i >= n_docs: + break + + +def dl(lang: str, output_dir: Path, date: str = None): + """Download the cirrus extract for the given lang. + + See https://dumps.wikimedia.org/other/cirrussearch for the full list of files. + + Args: + - lang: The Wikipedia code for the language. + - output_dir: Output directory. File will be `{lang}.json.gz` + - date: Date of a specific Cirrus dump. + """ + + urls = get_cirrus_urls(date) + assert ( + lang in urls + ), f"--lang {lang} not found. Available languages are: {urls.keys()}" + + assert output_dir, "--output_dir folder needed." + output_dir.mkdir(exist_ok=True) + output = output_dir / (lang + ".json.gz") + print(f"Downloading {lang} wiki from {urls[lang]} to {output}") + wget(urls[lang], output) + + +def get_cirrus_urls(date: str = None) -> Dict[str, str]: + if date is None: + cirrus_page = BeautifulSoup( + urllib.request.urlopen(CIRRUS_URL), features="html.parser" + ) + dumps = [a.get("href").strip("/") for a in cirrus_page.findAll("a")] + dumps.remove("..") + dumps.remove("current") + # We take the oldest dump since the most recent might be incomplete. + # The page only link to the N latest dumps so the dump won't be too old. + date = min(dumps) + + cirrus_url = "/".join((CIRRUS_URL, date)) + print("Will use the Wikipedia dump from:", date, cirrus_url) + cirrus_page = BeautifulSoup( + urllib.request.urlopen(cirrus_url), features="html.parser" + ) + urls = {} + for link in cirrus_page.findAll("a"): + match = CIRRUS_DUMP_RE.match(link.get("href")) + if not match: + continue + + urls[match.group(1)] = "/".join([cirrus_url, link.get("href")]) + assert urls, f"No valid download urls found at {cirrus_url}" + return urls + + +def wget(url: str, output: Path): + subprocess.run( + ["wget", url, "-O", tmp(output), "--no-check-certificate"], check=True + ) + tmp(output).replace(output) + assert ( + output.stat().st_size > 10_000 + ), f"File {output} downloaded from {url} looks too small" + + +if __name__ == "__main__": + func_argparse.main(dl, opening) diff --git a/data_tooling/kenlm_training/cc_net/jsonql.py b/data_tooling/kenlm_training/cc_net/jsonql.py new file mode 100644 index 0000000..f57f3d7 --- /dev/null +++ b/data_tooling/kenlm_training/cc_net/jsonql.py @@ -0,0 +1,1340 @@ +# Copyright (c) Facebook, Inc. and its affiliates. +# +# This source code is licensed under the MIT license found in the +# LICENSE file in the root directory of this source tree. +# + +""" +Manipulate files containing one json per line. +""" +import argparse +import collections +import contextlib +import functools +import glob +import gzip +import importlib +import inspect +import io +import itertools +import json +import logging +import multiprocessing +import os +import re +import sys +import tempfile +import time +import typing as tp +import warnings +import zlib +from pathlib import Path +from typing import ( + Callable, + Dict, + Iterable, + Iterator, + List, + Optional, + Sequence, + TextIO, + Tuple, + Union, +) + +import numpy as np +import psutil # type: ignore +import requests +from typing_extensions import Protocol + +logging.basicConfig( + level=logging.INFO, + format="%(asctime)s %(levelname)s %(process)d:%(name)s - %(message)s", + datefmt="%Y-%m-%d %H:%M", +) + +NEWLINE = " N3WL1N3 " + +FilterFn = Callable[[dict], bool] +FileDescriptor = Union[Path, List[Path], str] +WritableFileLike = Union[FileDescriptor, TextIO, "SimpleIO", None] +ReadableFileLike = Union[Iterable[str], FileDescriptor, None] + + +def io_parser(): + """Parser shared by all commands to get input/output files.""" + parser = argparse.ArgumentParser(add_help=False) + file_help = """File to read from. Can be specified several times for several files. + Be careful that bash will expand glob patterns **before** sending the args + to python. To use globs put it inside single quotes: + jsonql where --file 'data/perplexity/*.json' '{length} > 100' | head -1 + jsonql --file 'data/perplexity/*.json' where '{length} > 100' | head -1 + [Invalid] jsonql where '{length} > 100' --file data/perplexity/*.json | head -1 + [Invalid] jsonql where --file data/perplexity/*.json '{length} > 100' | head -1 + """ + parser.add_argument("-f", "--file", type=Path, action="append", help=file_help) + parser.add_argument("-o", "--output", type=Path, default="-") + parser.add_argument("--processes", type=int, default=1) + return parser + + +def get_parser(): + parser = argparse.ArgumentParser( + description="Read a set of json files and allow to query them" + ) + subparsers = parser.add_subparsers() + + def add_subparser(function, arguments): + doc = function.__doc__.split("\n")[0] + p = subparsers.add_parser(function.__name__, help=doc, parents=[io_parser()]) + p.set_defaults(command=function) + for k, v in arguments.items(): + p.add_argument(k, **v) + + add_subparser( + select, + { + "columns": dict(nargs="+", help="Extract the value of the given fields"), + "--skip_empty": dict( + action="store_true", help="Skip lines without the requested fields" + ), + "--separator": dict( + default="\t", help="Separator to use between the different columns" + ), + "--newline": dict( + default=NEWLINE, + help="Replace newlines found in the text by the given string", + ), + }, + ) + + add_subparser( + where, + { + "clauses": dict(nargs="+", help=""), + "--requires": dict( + action="append", help="Python module required by the clauses code." + ), + }, + ) + + add_subparser( + merge, + { + "columns": dict(nargs="+", help=""), + "--separator": dict( + default="\t", help="Separator to use between the different columns" + ), + "--newline": dict( + default=NEWLINE, help="Replace the given string by actual newlines" + ), + }, + ) + + add_subparser( + describe, + { + "columns": dict(nargs="*", help=""), + "--bins": dict( + default="auto", help="Number of bins for computing the histograms" + ), + "--cumulative": dict( + action="store_true", help="Compute cumulative histograms" + ), + "--weights": dict(type=str, help="Column used to weight histograms"), + }, + ) + + add_subparser(split, {"--pattern": dict(type=str)}) + add_subparser(shard, {}) + return parser + + +def _split_array(array, sep): + last = 0 + for i, x in enumerate(array): + if x != sep: + continue + yield array[last:i] + last = i + 1 + if last != len(array): + yield array[last:] + + +def main(raw_args): + parser = get_parser() + pipeline = [] + file = "-" + output = "-" + processes = 1 + + for args_group in _split_array(raw_args, "--"): + args = vars(parser.parse_args(args_group)) + command = args.pop("command") + file = args.pop("file") or file + output = args.pop("output") or output + processes = args.pop("processes") or processes + pipeline.append(as_pipe(command, args)) + + if not pipeline: + parser.print_help() + return + + run_pipes(*pipeline, file=Path(file), output=Path(output), processes=processes) + + +class Transformer: + """ + Wrapper around functions transforming documents. + + This allows `run_pipes` to automatically parallelize the pipeline. + Provides: + * Automatic logging. Logging can be changed with the `summary` method. + Loggin frequency with _log_freq (in second) or $JSONQL_LOG_FREQ env variable. + * Automatic parallelization without pickling. The transformers are shared + across processes, and the object is usually not pickled. + * Basic pickling / unpickling in case it's still needed. + By default will only pickle the arguments passed to the constructor. + * Delayed initialization. Internal state which is not pickable should be set + inside the `_prepare` function. + """ + + parallelisable: bool = True + expect_json: bool = False + warn_when_pickling: bool = False + ready: bool = False + + def __init_subclass__(cls, expect_json: bool = None): + """Detects if the subclass expects json as input.""" + spec = inspect.getfullargspec(cls.do) + if expect_json is None: + expect_json = spec.annotations.get(spec.args[1], None) == dict + + cls.expect_json = expect_json + + def __new__(cls, *args, **kwargs): + """Creates the transformer and save the arguments passed to the constructor.""" + t = super().__new__(cls) + Transformer.__init__(t, args, kwargs) + return t + + def __init__(self, state_args: tuple = None, state_kwargs: dict = None): + """ + Init the transformer counters. + + If state_args/state_kwargs are set they will override whatever was + originally passed to the subclass constructor. + """ + if state_args is not None: + self.__args = state_args + if state_kwargs is not None: + self.__kwargs = state_kwargs + + self.start_time = time.time() + self.__last_log = self.start_time + self.processed = 0 + # Log every 5 min unless specified other wise. + self._log_freq = int(os.environ.get("JSONQL_LOG_FREQ", 5 * 60)) + self.__cls = type(self) + self._logger = logging.getLogger(self.__cls.__name__) + + def __call__(self, x): + assert self.ready, f"{self} is not ready." + if x is None: + return + y = self.do(x) + self.processed += 1 + if time.time() - self.__last_log > self._log_freq: + self.log_summary() + return y + + def do(self, x): + raise NotImplementedError(f"'do' not implemented in {type(self)}") + + def summary(self) -> List[str]: + return [self.speed_summary()] + + def speed_summary(self) -> str: + delay = time.time() - self.start_time + h = delay / 3600 + s = self.processed / delay + return f"Processed {self.processed:_} documents in {h:.2}h ({s:5.1f} doc/s)." + + def log(self, message): + self._logger.info(message) + + def log_summary(self) -> None: + if not self.ready: + self.log("Not ready.") + return + summ = self.summary() or [] + for line in summ: + self.log(line) + self.__last_log = time.time() + + def map(self, source: Iterable) -> Iterator: + if self.ready: + for x in source: + yield self(x) + # since we have been prepared by caller, + # caller is also responsible for calling `close`. + return + else: + with self: + for x in source: + yield self(x) + + def __getstate__(self) -> Tuple[tuple, dict, bool]: + return (self.__args, self.__kwargs, self.expect_json) + + def __setstate__(self, state: Tuple[tuple, dict, bool]): + if self.warn_when_pickling: + warnings.warn(f"Unpickling transformer: {type(self)}. This can be slow.") + (args, kwargs, expect_json) = state + # When unpickling `__new__` isn't called so we have to doit ourselves. + Transformer.__init__(self, state_args=args, state_kwargs=kwargs) + type(self).__init__(self, *args, **kwargs) + assert self.expect_json == expect_json + # __setstate__ is called by multiprocessing right before calling + # the object so we need to initialize everything. + self.__enter__() + + def _prepare(self) -> None: + pass + + def __enter__(self) -> "Transformer": + # In multiprocessing __enter__ is always called twice, so we are idempotent. + # Because we call __enter__ when deserializing this transformer and + # also when the parent transformer is deserialized. + self.start_time = time.time() + if self.ready: + return self + self._prepare() + self.ready = True + return self + + def __exit__(self, *args) -> None: + self.close() + self.log_summary() + + def close(self) -> None: + pass + + +def as_pipe(transformer, kwargs): + if isinstance(transformer, type): + return transformer(**kwargs) + return lambda source: transformer(source, **kwargs) + + +def compose(fns: List[Transformer]) -> Transformer: + if len(fns) == 1: + return fns[0] + return MultiTransformer(fns) + + +class MultiTransformer(Transformer): + def __init__(self, transformers: List[Transformer]): + super().__init__() + self.transformers = transformers + + def __repr__(self) -> str: + pipeline = " | ".join(type(t).__name__ for t in self.transformers) + return f"<{pipeline}>" + + def do(self, x): + for t in self.transformers: + x = t(x) + return x + + def _prepare(self): + for t in self.transformers: + t.__enter__() + return self + + def __exit__(self, *args): + for t in self.transformers: + t.__exit__(*args) + + def summary(self): + return itertools.chain(*(t.summary() for t in self.transformers)) + + +class Mapper(Transformer): + def __init__(self, fn): + super().__init__() + self.fn = fn + + def do(self, x): + return self.fn(x) + + +def run_pipe( + command, + kwargs: dict = None, + file: ReadableFileLike = None, + output: WritableFileLike = None, +): + kwargs = kwargs or {} + if isinstance(kwargs, argparse.ArgumentParser): + kwargs = vars(kwargs.parse_args()) + file = file or Path(kwargs.pop("file", "-")) + output = output or Path(kwargs.pop("output", "-")) + + return run_pipes(as_pipe(command, kwargs), file=file, output=output) + + +def run_pipes( + *fns: Union[Transformer, Callable[[Iterable], Iterable]], + inputs: Iterable[dict] = None, + file: ReadableFileLike = None, + output: WritableFileLike = None, + processes: int = 1, + chunksize: int = 10_000, +): + """ + Run full document processing pipeline. + + - fns: list of functions to run over the documents. Can be: + * `Iterable -> Iterable` function + * jsonql.Transformer instance + Using transformers allow the pipeline to process documents in parallel. + - inputs: iterable to read the documents from + - file: if inputs is not given, will read documents from this file. + - output: writable file like. + - processes: number of processes to use. -1 means all CPU available. + - chunksize: chunksize for multiprocessing.Pool.imap_unordered + """ + expect_json = len(fns) and isinstance(fns[0], Transformer) and fns[0].expect_json + if expect_json and inputs is None: + fns = (JsonReader(),) + fns + transformers = [] + for t in fns: + if not isinstance(t, Transformer): + break + if not t.parallelisable: + break + transformers.append(t) + pipes = fns[len(transformers) :] + + log = logging.getLogger(__name__).info + if inputs is None: + data: Iterable = open_read(file) + else: + data = inputs + + if processes == -1: + processes = os.cpu_count() or 0 + + with contextlib.suppress(BrokenPipeError), contextlib.ExitStack() as stack: + if transformers: + log(f"preparing {transformers}") + transform = stack.enter_context(compose(transformers)) + if processes <= 1: + data = transform.map(data) + else: + p = multiprocessing.current_process() + log(f"Will start {processes} processes from {p.name}, Pid: {p.pid}") + pool = stack.enter_context( + multiprocessing.Pool( + processes=processes, + initializer=_set_global_transformer, + initargs=(transform,), + ) + ) + data = pool.imap_unordered( + _global_transformer, data, chunksize=chunksize + ) + + for fn in pipes: + if isinstance(fn, Transformer): + data = fn.map(data) + else: + data = fn(data) + + write_jsons(data, output) + + +# Allows to share transformer acroos subprocess. +# Used by `run_pipes` +_GLOBAL_TRANSFORMER: Optional[Transformer] = None + + +def _set_global_transformer(transformer: Transformer): + global _GLOBAL_TRANSFORMER + p = multiprocessing.current_process() + logging.info( + f"Started subprocess {p.name}:{p.pid} from {os.getppid()} for {transformer}" + ) + assert transformer.ready, f"{transformer} isn't ready" + _GLOBAL_TRANSFORMER = transformer + + +def _global_transformer(document: str) -> Optional[dict]: + assert _GLOBAL_TRANSFORMER is not None + return _GLOBAL_TRANSFORMER(document) + + +def lines(file: ReadableFileLike) -> Iterator[str]: + return (line.strip("\n") for line in open_read(file)) + + +def read_jsons(file: ReadableFileLike, strict=False) -> Iterator[dict]: + reader = JsonReader(strict=strict) + lines = open_read(file) + for line in lines: + if line is None: + continue + yield reader(line) + + reader.log_summary() + + +def write_jsons(source: Iterable[dict], file: WritableFileLike) -> None: + eol = os.linesep + with open_write(file) as o: + for res in source: + if res is None: + continue + if isinstance(res, dict): + json.dump(res, o, ensure_ascii=False) + o.write(eol) + continue + if isinstance(res, str): + res = res.rstrip("\n") + print(res, file=o) + + +class JsonReader(Transformer): + def __init__(self, strict: bool = False): + super().__init__() + self.ready = True + self.strict = strict + self.num_errors = 0 + + def do(self, line: str) -> Optional[dict]: + if line is None: + return None + if isinstance(line, dict): + return line + line = line.rstrip("\n") + if not line: + return None + try: + return json.loads(line) + except json.decoder.JSONDecodeError as e: + self.log_error(e) + if self.strict: + raise + return None + + def log_error(self, e: json.decoder.JSONDecodeError): + self.num_errors += 1 + if self.num_errors > 10: + return + + MAX_LEN = 80 + snippet, snippet_len = e.doc, len(e.doc) + col = e.pos + if snippet_len > MAX_LEN: + if col < MAX_LEN: + start = 0 + elif snippet_len - col < MAX_LEN: + start = snippet_len - MAX_LEN + else: + start = col - MAX_LEN // 2 + snippet = e.doc[start : start + MAX_LEN] + col = col - start + logging.warning( + "\n".join( + [ + f"Invalid json (length={len(e.doc)}) {e}", + snippet, + " " * (col - 1) + "^", + ] + ) + ) + + def summary(self): + summ = super().summary() + if self.num_errors > 0: + summ.append(f"Skipped {self.num_errors} invalid json.") + return summ + + +def compile_column(column, newline): + if callable(column): + return column + + if column == "*": + return json.dumps + + if re.match(r"[_a-z][_a-z0-9]*", column): + + def extract_col(doc): + v = doc.get(column, "") + if isinstance(v, str) and newline != "\n": + v = v.rstrip("\n").replace("\n", newline) + return v + + return extract_col + + return compile_expr(column) + + +def select(lines, columns, skip_empty=False, separator="\t", newline="\n"): + """Yields the content of the requested columns.""" + column_parsers = [compile_column(c, newline) for c in columns] + for doc in read_jsons(lines): + values = [] + empty = True + for parse_col in column_parsers: + v = parse_col(doc) + values.append(str(v) or "") + empty = empty and v is None + + if skip_empty and empty: + continue + + yield separator.join(values) + + +def compile_expr(clause: Union[str, FilterFn], requires: List[str] = None): + if not isinstance(clause, str): + return clause + + args_re = r"(?i:\{([_a-z][_a-z0-9]*)\})" + args_list = list(re.findall(args_re, clause)) + if not args_list: + # This is only a warning because you may want to have eg random sampling + # that doesn't depend on the document. + logging.warn( + f"Warning: No variable found in expression: <{clause}>\n" + "Variables should be written inside braces, eg: {language}=='en'" + ) + python_like = re.sub(args_re, r"doc.get('\1', None)", clause) + requires = requires or [] + modules = {r: importlib.import_module(r) for r in requires} + return eval(f"lambda doc: {python_like}", modules) + + +class where(Transformer): + """Filters the data using python code. + + Ex: `jsonql where 'len({text}) > 100'` + """ + + def __init__( + self, clauses: Sequence[Union[str, FilterFn]], requires: List[str] = [] + ): + super().__init__() + self.raw_clauses = clauses + self.requires = requires + self.n_selected = 0 + self.clauses: List[FilterFn] = [] + + def _prepare(self): + self.clauses = [compile_expr(c, self.requires) for c in self.raw_clauses] + + def do(self, doc: dict) -> Optional[dict]: + assert self.clauses + if not doc or not all(c(doc) for c in self.clauses): + return None + self.n_selected += 1 + return doc + + def summary(self): + n_selected, n_docs = self.n_selected, self.processed + selectivity = n_selected / n_docs if n_docs else 0 + return [f"Selected {n_selected} documents out of {n_docs} ({selectivity:5.1%})"] + + +def merge(lines, columns, separator="\t", newline=NEWLINE): + """Reads tab separated columns and output a json using the given headers. + + Headers are of form {key}[%{type}] + {type} can be one of {"f": float, "i": int, "b": bool, "s": string}. + Default type is string. + A special header "_" means interpret this column as json, and append all other + columns to it. Must appear only once and on last position. + + Ex: + `echo '1\thello' | jsonql merge n t` --> `{"n": "1", "t": "hello"}` + `echo '1\thello" | jsonql merge n%i t` --> `{"n": 1, "t": "hello"}` + `echo '1\thello\t{"f": "bar"}' | jsonql merge n%i t _` --> `{"n": 1, "t": "hello", "f": "bar"}` + """ + handle_newlines = lambda s: s.replace(newline, "\n") + type_mapping: Dict[str, Callable] = { + "f": float, + "i": int, + "b": bool, + "s": handle_newlines, + } + type_parsing = [ + type_mapping.get(f.split("%")[-1], handle_newlines) for f in columns + ] + columns = [f.split("%")[0] for f in columns] + doc_index = columns.index("_") if "_" in columns else -1 + read_json = JsonReader() + + def parse(line): + parts = line.split(separator, len(columns) - 1) + doc: Dict[str, tp.Any] = {} + for i, value in enumerate(parts): + if columns[i] == "_": + doc.update(read_json(parts[doc_index])) + else: + try: + doc[columns[i]] = type_parsing[i](value) + except ValueError: + logging.error( + f"Error when parsing column {i} of line: {line[:100]}..." + ) + return doc + + for line in lines: + yield json.dumps(parse(line)) + + +class split(Transformer): + """Split a files in several smaller files based on the value of a field.""" + + # Not parallelisable since we are writing to files. + parallelisable = False + + def __init__( + self, + pattern: Union[Path, str] = None, + split_fn: Callable[[dict], str] = None, + mkdir: bool = False, + ): + super().__init__() + assert not ( + pattern and split_fn + ), "split can't have both a pattern and a split_fn" + if split_fn is not None: + self.split_fn = split_fn + else: + assert pattern, "split need either a pattern or a split_fn" + self.split_fn = self.make_split_fn(str(pattern)) + self.mkdir = mkdir + self.o: dict = {} + + def make_split_fn(self, pattern: str) -> Callable[[dict], str]: + candidates = list(re.findall(r"(?i:\{([_a-z][_a-z0-9]*)\})", pattern)) + return lambda doc: pattern.format(**{c: doc[c] for c in candidates}) + + def do(self, doc): + filename = self.split_fn(doc) + if not filename: + return + o = self.o.get(filename, None) + if o is None: + if self.mkdir: + Path(filename).parent.mkdir(parents=True, exist_ok=True) + self.o[filename] = open_write(filename) + print(json.dumps(doc, ensure_ascii=False), file=self.o[filename], flush=True) + + def summary(self): + summ = super().summary() + summ.append(f"Found {len(self.o)} splits.") + return summ + + def close(self): + for file in self.o.values(): + file.close() + + +def histogram(values, bins, weights): + hist, bins = np.histogram(values, bins=bins) + # n_bins = len(hist) + + if weights is not None: + # Bins can't be auto-determined if weights is supplied. + # So we first compute the bins without the weights then recompute + # the histogram with the weights. + hist, bins = np.histogram(values, bins=bins, weights=weights) + # cumsum = np.cumsum(hist) + # total = cumsum[-1] + + # for i in range(n_bins - 1): + # if cumsum[i] / total > 0.9: + # useful_range = np.linspace(bins[0], bins[i + 1], n_bins) + # new_bins = np.append(useful_range, [bins[-1]]) + # return np.histogram(values, bins=new_bins, weights=weights) + + return hist, bins + + +def _parse_bins(bins): + try: + if isinstance(bins, str): + if "," in bins: + bins = [int(b) for b in bins.split(",")] + else: + bins = int(bins) + except ValueError: + pass + return bins + + +ALL_DOCUMENTS = "" +MAX_LABEL_LEN = 100 + + +def bar_chart(hist, bins): + n = sum(hist) + max_h = max(hist) + out = [] + for i, h in enumerate(hist): + h_size = 80 * h // max_h + dh_size = 80 * (h - hist[i - 1]) // max_h + if h_size == 0 or dh_size == 0: + continue + bar = "█" * h_size + out.append(f"{bins[i]:8.3f} {bar:80} ({h:5d}, {h / n:5.1%}) {bins[i+1]:8.3f}") + out.append(f"{bins[-1]:8.3f}") + return out + + +def display_stats(stats, key, weights=None, bins="auto", cumulative=False): + out = [] + documents = stats[ALL_DOCUMENTS] + count = stats.get(key, 0) + r = count / documents if documents else 0 + out.append(f"Field {key} saw {count} times ({r:5.1%})") + + length = stats.get(key + ".length", None) + avg_length = length // count if length else 0 + if length is not None: + out[-1] += f", average length is {length // count}" + + values = stats.get(key + ".val", None) + if values: + out[-1] += f", histogram is: (bins={bins})" + if weights: + if weights not in stats: + logging.warn(f"Warning: weights column {weights} not found.") + if weights + ".val" not in stats: + logging.warn( + f"Warning: weights column {weights} is not a numeric column." + ) + weights = stats.get(weights + ".val") + hist, bins = histogram(values, _parse_bins(bins), weights) + if cumulative: + hist = np.cumsum(hist) + out += bar_chart(hist, bins) + + cnt = stats.get(key + ".cnt", None) + if avg_length < MAX_LABEL_LEN and cnt and max(cnt.values()) > 1: + cnt = sorted(cnt.items(), key=lambda kv: kv[1], reverse=True) + out[-1] += ", top 100 labels:" + for label, n in cnt[:100]: + if n < 5: + continue + out.append(f"{label:25}: {n:6} ({n / count:5.1%})") + + return out + + +def describe(source, columns=None, weights=None, **kwargs): + """Compute some statistics about a dataset. + + Stats can be restricted to a subset of columns.""" + MAX_HIST_SIZE = 100_000_000 + MAX_CNT_SIZE = 1000 + stats = {ALL_DOCUMENTS: 0} + needed = columns + [weights] if columns else None + + for doc in read_jsons(source): + stats[ALL_DOCUMENTS] += 1 + for k, v in doc.items(): + if needed and k not in needed: + continue + stats[k] = get_or_set(stats, k, 0) + 1 + if isinstance(v, str): + stats[k + ".length"] = get_or_set(stats, k + ".length", 0) + len(v) + if len(v) > MAX_LABEL_LEN: # Don't treat too long string as labels + continue + cnt = get_or_set(stats, k + ".cnt", collections.defaultdict(int)) + if v in cnt or len(cnt) < MAX_CNT_SIZE: + cnt[v] += 1 + elif type(v) in (int, float): + values = get_or_set(stats, k + ".val", []) + if len(values) < MAX_HIST_SIZE: + values.append(v) + elif type(v) is list and len(v) and type(v[0]) in (int, float): + values = get_or_set(stats, k + ".val", []) + if len(values) < MAX_HIST_SIZE: + values += v + elif type(v) is dict: + cnt = get_or_set(stats, k + ".cnt", collections.defaultdict(int)) + for label in v: + if label in cnt or len(cnt) < MAX_CNT_SIZE: + cnt[label] += 1 + + documents = stats[ALL_DOCUMENTS] + yield f"Stats computed on {documents} documents:" + for k in stats: + if columns and k not in columns: + continue + if "." in k or k == ALL_DOCUMENTS: + continue + for line in display_stats(stats, k, weights=weights, **kwargs): + yield line + + +def shard(lines): + """Shard a file in several smaller ones.""" + # The creation of the shard is handle in a generic way. Do we need this ? + return lines + + +# *** Utils *** + + +def get_or_set(dictionary, key, default): + if key not in dictionary: + dictionary[key] = default + return dictionary[key] + + +class SimpleIO(Protocol): + """A subset of methods from TextIO.""" + + def close(self) -> None: + ... + + def write(self, line: str) -> int: + ... + + def __enter__(self) -> "SimpleIO": + ... + + def __exit__(self, exc_type, exc_value, traceback): + ... + + +def open_read(filename: ReadableFileLike) -> Iterable[str]: + """Open the given file, list of files or files matching the given glob and read lines. + + `filename` is None or "-" -> reads from stdin + `filename` is a Path / str -> interprets filename as a glob and open files matching it + `filename` is a list -> opens sequentially all files from the list using `open_read` + `filename` is something else -> returns the object wrapped in a `nullcontext` + This allows to pass already openened files or iterables. + + `open_read` will decompress gzip files, given they have ".gz" suffix. + """ + if filename is None: + return sys.stdin + + if isinstance(filename, list): + assert isinstance(filename[0], Path) + if len(filename) == 0: + return [] + if len(filename) > 1: + return _yield_from(filename) + filename = tp.cast(Path, filename[0]) + if isinstance(filename, str): + if filename.startswith("http://") or filename.startswith("https://"): + return open_remote_file(filename) + + filename = Path(filename) + if not isinstance(filename, Path): + # we might have received an iterable, return it unmodified. + return filename # type: ignore + + # Expand glob patterns only when reading + files = [Path(f) for f in sorted(glob.glob(str(filename)))] + if len(files) > 1: + return _yield_from(files) + if len(files) == 1: + filename = files[0] + + assert isinstance(filename, Path) + + if filename.name.endswith("]"): + return block_reader(filename) + + logging.getLogger(__name__).info(f"Opening {filename} with mode 'rt'") + if filename.suffix == ".gz": + file: TextIO = gzip.open(filename, "rt") # type: ignore + else: + file = open(filename, "rt") + + return _close_when_exhausted(file) + + +def _close_when_exhausted(file: TextIO) -> Iterable[str]: + with file: + yield from file + + +def _yield_from(files: list) -> Iterable[str]: + for file in files: + yield from open_read(file) + + +def open_write( + filename: WritableFileLike, max_size: str = "4G" +) -> tp.ContextManager[TextIO]: + """Open the given file, list of files or files matching the given glob. + + The return value is a ContextManager meant to be used inside a `with` block: + ``` + with open_write("foo.txt") as o: + ... + + Write mode: + replaces "?" from filename by numbers ranging from 0 to 9, generatings files of size `max_size`. + If filename ends with ".gz", creates a blocked gzip file with random access. + """ + if filename is None: + return contextlib.nullcontext(sys.stdout) + + if isinstance(filename, list): + if len(filename) > 1: + return MultiFile(filename, "w", max_size) + else: + filename = tp.cast(Path, filename[0]) + if isinstance(filename, str): + filename = Path(filename) + if not isinstance(filename, Path): + assert hasattr(filename, "write"), f"{filename} doesn't have a .write method." + # We return a 'TextIO' even though we only check for `.write` method, + # this works better with eg `print`. + return contextlib.nullcontext(tp.cast(TextIO, filename)) + + mode = "wt" + if "?" in filename.name: + return sharded_file(filename, mode, max_size) + + logging.getLogger(__name__).info(f"Opening {filename} with mode {mode}") + # TODO: should we use another format ? + if filename.suffix == ".gz": + return BlockedGzipWriter(Path(filename), mode, block_size="64M") + + return open(filename, "wt") + + +def parse_size(size): + unit_map = {"B": 1, "K": 1024, "M": 1024 ** 2, "G": 1024 ** 3} + unit = size[-1].upper() + assert ( + unit in unit_map + ), f"Unsupported size unit for {size}. Use one of: {unit_map.keys()}." + return int(size[:-1]) * unit_map[unit] + + +class MultiFile(SimpleIO): + def __init__(self, files: Iterable[Path], mode="w", max_size="4G"): + self.name = str(files) + self.mode = mode + self.files = iter(files) + self.max_size = parse_size(max_size) + self.current_handle: Optional[TextIO] = None + self.current_block_size = 0 + self._open_next_handle() # Opening 1st handle allows to write directly. + + def write(self, content) -> int: + # Avoid splitting newlines to a new file. + # use current_block_size since it's faster than `tell()` + if content != "\n" and self.current_block_size >= self.max_size: + self._open_next_handle() + if self.current_handle is None: + raise Exception("No more files to write to...") + + written = self.current_handle.write(content) + self.current_block_size += written + return written + + def _open_next_handle(self) -> bool: + self.close() + file = next(self.files, None) + if file is None: + return False + + self.current_handle = open_write(file).__enter__() + self.current_block_size = 0 + return True + + def __enter__(self): + return self + + def __exit__(self, *exc_info): + self.close() + + @property + def closed(self): + return self.current_handle is None + + def close(self): + if self.current_handle is None: + return + + # log("Closing", self.current_handle.name, "with mode", self.current_handle.mode) + self.current_handle.__exit__(None, None, None) + self.current_handle = None + + +# not sure it helps since connections are reseted anyway. +_session = functools.lru_cache()(requests.Session) + + +def request_get_content(url: str, n_retry: int = 3) -> bytes: + """Retrieve the binary content at url. + + Retry on connection errors. + """ + t0 = time.time() + logging.info(f"Starting download of {url}") + for i in range(1, n_retry + 1): + try: + r = _session().get(url) + r.raise_for_status() + break + except requests.exceptions.RequestException as e: + # Sleep and try again on error, unless it's a 404. + message = e.args[0] if isinstance(e.args[0], str) else "" + if i == n_retry or "Client Error" in message: + raise e + warnings.warn( + f"Swallowed error {e} while downloading {url} ({i} out of {n_retry})" + ) + time.sleep(10 * 2 ** i) + dl_time = time.time() - t0 + dl_speed = len(r.content) / dl_time / 1024 + logging.info( + f"Downloaded {url} [{r.status_code}] took {dl_time:.0f}s ({dl_speed:.1f}kB/s)" + ) + return r.content + + +def open_remote_file(url: str, cache: Path = None) -> Iterable[str]: + """Download the files at the given url to memory and opens it as a file. + Assumes that the file is small, and fetch it when this function is called. + """ + if cache and cache.exists(): + return open_read(cache) + + # TODO: open the remote file in streaming mode. + # The hard part is that we need to write the content on disk at the same time, + # to implement disk caching. + raw_bytes = request_get_content(url) + content = io.BytesIO(raw_bytes) + if url.endswith(".gz"): + f: TextIO = gzip.open(content, mode="rt") # type: ignore + else: + f = io.TextIOWrapper(content) + + if cache and not cache.exists(): + # The file might have been created while downloading/writing. + tmp_cache = _tmp(cache) + tmp_cache.write_bytes(raw_bytes) + if not cache.exists(): + tmp_cache.replace(cache) + else: + tmp_cache.unlink() + + return _close_when_exhausted(f) + + +def sharded_file(file_pattern: Path, mode: str, max_size: str = "4G") -> MultiFile: + folder, name = file_pattern.parent, file_pattern.name + assert "?" in name, f"Can't expand give file_pattern: {file_pattern}" + + n = name.count("?") + assert 0 < n < 8 + assert "?" * n in name, f"The '?' need to be adjacents in {file_pattern}" + assert "r" not in mode + files = (folder / name.replace("?" * n, f"%0{n}d" % i) for i in range(10 ** n)) + + return MultiFile(files, mode, max_size) + + +class SplitFile: + def __init__(self, filename: Path, chunk: int, n_chunks: int, mode: str = "r"): + assert mode == "r" + size = os.path.getsize(filename) + self.handle = open(filename, mode) + start = chunk * size // n_chunks + self.end: int = (chunk + 1) * size // n_chunks + + if start > 0: + self.handle.seek(start - 1) + # Skip incomplete line. This avoid crashing when reading eg the middle + # of a unicode char. `self.handle.buffer` is a binary file reader. + self.handle.buffer.readline() # type: ignore + + def __enter__(self): + return self + + def __iter__(self): + while True: + line = self.handle.readline() + if not line: + return + + yield line + if self.handle.tell() >= self.end: + return + + def readlines(self): + return list(self.__iter__()) + + def close(self): + self.handle.close() + + def __exit__(self, *args): + self.close() + + +def get_block_readers(filename: Path, n_readers, mode="t"): + index_filename = filename.parent / (filename.name + ".index") + if not index_filename.exists(): + return [gzip.open(filename, "r" + mode)] + index: List[int] = np.load(index_filename) + n_chunks = len(index) + chunk_per_reader = int(np.ceil(n_chunks / n_readers)) + n_readers = int(np.ceil(n_chunks / chunk_per_reader)) + + start = 0 + readers = [] + for i in range(n_readers): + end = index[min((i + 1) * chunk_per_reader - 1, n_chunks - 1)] + r = _blocked_gzip_reader(filename, start, end, mode) + readers.append(r) + start = end + return readers + + +def block_reader(filename: Path) -> Iterable[str]: + root, pattern = str(filename)[:-1].split("[", 1) + assert root.endswith(".gz"), "Can only read block of a .gz file for now." + + ii, nn = pattern.strip().split("/") + i, n_readers = int(ii), int(nn) + + index_filename = root + ".index" + assert os.path.exists( + index_filename + ), f"Index {index_filename} not found for {filename}" + index: List[int] = np.load(index_filename) + n_chunks = len(index) + chunk_per_reader = int(np.ceil(n_chunks / n_readers)) + n_readers = int(np.ceil(n_chunks / chunk_per_reader)) + # I'm not sure how to handle the case where there is less reader than expected. + # Currently we return empty readers. + + start = 0 + if i > 0: + start = index[min((i - 1) * chunk_per_reader, n_chunks - 1)] + end = index[min(i * chunk_per_reader, n_chunks - 1)] + return _blocked_gzip_reader(root, start, end, mode="t") + + +def _blocked_gzip_reader(filename, start, end, mode="t") -> Iterable[str]: + handle = gzip.open(filename, "r" + mode) + handle.seek(start) + try: + while handle.tell() < end: + line = handle.readline() + if not line: + break + yield line + finally: + handle.close() + + +class BlockedGzipWriter(MultiFile): + """Writes a Gzip files which can be read by block. + + Decreasing the block size may hurt compression, but provides more split points. + """ + + def __init__(self, filename: Path, mode: str, block_size: str = "256M"): + assert "w" in mode + self.filename = Path(filename) + self.index: List[int] = [] + self.zipfile: Optional[gzip.GzipFile] = None + super().__init__([], mode, block_size) + + def _open_next_handle(self) -> bool: + """Here we never actually close/open handles, + we just write the end of block sequence.""" + if not self.current_handle: + mode = self.mode + "t" + self.current_handle = tp.cast(TextIO, gzip.open(self.filename, mode)) + assert isinstance(self.current_handle.buffer, gzip.GzipFile) + self.zipfile = self.current_handle.buffer + return True + + # Use Z_FULL_FLUSH to allow random access: + # https://github.com/madler/zlib/blob/cacf7f1d4e3d44d871b605da3b647f07d718623f/zlib.h#L313 + self.current_handle.buffer.flush(zlib_mode=zlib.Z_FULL_FLUSH) # type: ignore + self.index.append(self.current_handle.tell()) + self.current_block_size = 0 + return True + + def flush(self): + assert self.current_handle is not None + self.current_handle.flush() + + def close(self): + if self.current_handle is None: + return + self.current_handle.flush() + self.index.append(self.current_handle.tell()) + self.current_handle.close() + self.current_handle = None + index = np.array(self.index, dtype=np.uint64) + with open(str(self.filename) + ".index", "wb") as o: + np.save(o, index) + + +def grouper(iterable, n): + group = [] + for x in iterable: + group.append(x) + if len(group) == n: + yield group + group = [] + if group: + yield group + + +PROCESS = psutil.Process() + + +def mem_footprint_gb(pid=None): + rss = PROCESS.memory_info().rss + return rss / 1_000_000_000 + + +def _tmp(output: Path) -> Path: + suffix = "".join(output.suffixes) + suffix = ".tmp" + suffix + prefix = output.name[: -len(suffix)] + _, tmp_path = tempfile.mkstemp(dir=output.parent, prefix=prefix, suffix=suffix) + return Path(tmp_path) + + +@functools.lru_cache() +def _tmp_dir() -> Path: + job_id = os.environ.get("SLURM_JOB_ID") + if job_id: + return Path("/scratch/slurm_tmpdir") / job_id + + checkpoint = Path("/checkpoint") / os.environ.get("USER", "") + if checkpoint.exists(): + tmp = checkpoint / "tmp" + tmp.mkdir(exist_ok=True) + return tmp + + return Path("/tmp") + + +if __name__ == "__main__": + multiprocessing.set_start_method("fork") + main(sys.argv[1:]) diff --git a/data_tooling/kenlm_training/cc_net/mine.py b/data_tooling/kenlm_training/cc_net/mine.py new file mode 100644 index 0000000..4b8df55 --- /dev/null +++ b/data_tooling/kenlm_training/cc_net/mine.py @@ -0,0 +1,648 @@ +# Copyright (c) Facebook, Inc. and its affiliates. +# +# This source code is licensed under the MIT license found in the +# LICENSE file in the root directory of this source tree. +# + +""" +Main script to download a CC dump, remove duplicates, split by language and +filter the documents. + +The pipeline parameters are described in the `Config` class. +""" + +import hashlib +import json +import time +import warnings +from argparse import ArgumentParser +from collections import defaultdict +from itertools import repeat +from pathlib import Path +from typing import Any, Dict, Iterable, List, NamedTuple, Optional, Sequence, Tuple + +import func_argparse + +# Local scripts +from cc_net import dedup, execution, jsonql, minify, perplexity, process_wet_file +from cc_net import regroup as regroup_module +from cc_net import split_by_lang +from cc_net.execution import Executor + +# Constant +FILE_DIR = Path(__file__).parent +CUTOFF_CSV = FILE_DIR / "data" / "cutoff.csv" + +DEFAULT_PIPELINE = [ + "dedup", + "lid", + "keep_lang", + "sp", + "lm", + "pp_bucket", + "drop", + "split_by_lang", +] + + +class Config(NamedTuple): + """ + Mine Common Crawl with the given settings. + + config_name + dump: CC dump id + output_dir: working directory + mined_dir: name of the destination folder, full path will be {ouput_dir}/{mined_dir}/{dump_id} + execution: chose how to parallelize the execution + num_shards: number of shards to split the dump + num_segments_per_shard: allow to download a small portion of CC (eg for tests) + min_len: remove documents shorter than this (in chars) + hashes_in_mem: number of shards hashes to use for dedup + lang_whitelist: only treat those languages + lang_blacklist: ignore those languages + lang_threshold: remove docs whose top language score is lower than this + keep_bucket: keep only those perplexity bucket chose from (head, middle, tail, all) + lm_dir: folder containing LMs + lm_languages: only use LMs for the following languages + cutoff: cutoff file to use for split in head/middle/tail + mine_num_processes: number of processes to use for mining + target_size: size of finals files produce during `regroup` stage + cleanup_after_regroup: delete intermediary files after regroup + task_parallelism: max number of task to run in parallel + pipeline: restricts the mining pipeline to the given steps. Order is important ! + experiments: (HACK) enable specific experiments in the code + """ + + config_name: str = "base" + dump: str = "2017-51" + output_dir: Path = Path("data") + mined_dir: str = "mined" + execution: str = "auto" + num_shards: int = 1600 + num_segments_per_shard: int = -1 + metadata: Optional[str] = None + min_len: int = 300 + hash_in_mem: int = 50 + lang_whitelist: Sequence[str] = [] + lang_blacklist: Sequence[str] = [] + lang_threshold: float = 0.5 + keep_bucket: Sequence[str] = [] + lm_dir: Path = Path("data/lm_sp") + cutoff: Path = CUTOFF_CSV + lm_languages: Optional[Sequence[str]] = None + mine_num_processes: int = 16 + target_size: str = "4G" + cleanup_after_regroup: bool = True + task_parallelism: int = -1 + pipeline: Sequence[str] = DEFAULT_PIPELINE + experiments: Sequence[str] = [] + cache_dir: Optional[Path] = None + + def get_executor( + self, name: str, timeout_hour: int = 1, mem_gb: int = 1, cpus: int = 1 + ) -> Executor: + name = "_".join((name, self.config_name, *self.experiments)) + return execution.get_executor( + name, + self.output_dir / "logs", + self.execution, + timeout_hour=timeout_hour, + mem_gb=mem_gb, + cpus=cpus, + task_parallelism=self.task_parallelism, + ) + + def get_cc_shard(self, shard: int) -> process_wet_file.CCShardReader: + dump_cache: Optional[Path] = None + if self.cache_dir: + self.cache_dir.mkdir(exist_ok=True) + dump_cache = self.cache_dir / self.dump + dump_cache.mkdir(exist_ok=True) + + return process_wet_file.CCShardReader( + self.dump, + shard=shard, + num_shards=self.num_shards, + num_segments_per_shard=self.num_segments_per_shard, + min_len=self.min_len, + cache_dir=dump_cache, + ) + + @classmethod + def from_json(cls, json_file: Path) -> "Config": + raw_lines = json_file.read_text().splitlines() + raw_lines = [l for l in raw_lines if not l.strip().startswith("//")] + json_config = json.loads("".join(raw_lines)) + path_keys = ["cache_dir", "lm_dir", "output_dir"] + for key in path_keys: + if key in json_config: + json_config[key] = Path(json_config[key]) + return Config(**json_config) + + @property + def will_split(self) -> bool: + return "split_by_lang" in self.pipeline or "split_by_segment" in self.pipeline + + def get_lm_languages(self) -> Sequence[str]: + if self.lm_languages is not None: + return self.lm_languages + + if self.lang_whitelist: + return self.lang_whitelist + + languages = [m.name.split(".")[0] for m in self.lm_dir.glob("*.arpa.bin")] + if self.lang_blacklist: + languages = [l for l in languages if l not in self.lang_blacklist] + return languages + + def get_mined_dir(self, regroup: bool = False) -> Path: + if self.will_split and not regroup: + return self.output_dir / f"{self.mined_dir}_split" / self.dump + return self.output_dir / self.mined_dir / self.dump + + +BASE_CONFIG = Config() + +BYLANG_CONFIG = Config( + config_name="by_lang", + mined_dir="mined_by_lang", + pipeline=list(BASE_CONFIG.pipeline[:-1]) + ["split_by_lang"], +) + +REPRODUCE_CONFIG = Config( + config_name="reproduce", + dump="2019-09", + mined_dir="reproduce", + pipeline=["fetch_metadata", "keep_lang", "keep_bucket", "split_by_lang"], + metadata="https://dl.fbaipublicfiles.com/cc_net/1.0.0", + # Optional filtering: + # It won't change much the execution speed, but decreases the disk requirement. + # Restrict languages + lang_whitelist=["fr"], + # Restrict perplexity buckets + # Top languages have been split in perplexity buckets according + # to a Wikipedia trained LM. + # The buckets from low perplexity (good) to high (bad) are: + # ["head", "middle", "tail"] + # Languages without a LM have only one bucket "all". + # It won't change much the execution speed, but decreases the disk requirement. + keep_bucket=["head", "all"], + mine_num_processes=1, +) + +TEST_CONFIG = BASE_CONFIG._replace( + config_name="test", + dump="2019-09", + output_dir=Path("test_data"), + execution="local", + num_shards=4, + num_segments_per_shard=1, + hash_in_mem=2, + mine_num_processes=2, + lang_whitelist=["de", "it", "fr"], + target_size="32M", + cleanup_after_regroup=False, + cache_dir=Path("test_data/wet_cache"), +) + +PREDEF_CONFIGS = { + "base": BASE_CONFIG, + "by_lang": BYLANG_CONFIG, + "test": TEST_CONFIG, + "test_slurm": TEST_CONFIG._replace(execution="slurm,partition=dev"), + "debug": TEST_CONFIG._replace(config_name="debug", mine_num_processes=0), + "reproduce": REPRODUCE_CONFIG, + "augment": BASE_CONFIG._replace( + config_name="augment", dump="2019-13", lang_blacklist=["en"] + ), +} + + +def tmp(output: Path) -> Path: + return output.parent / (output.stem + ".tmp" + output.suffix) + + +def finalize(tmp_output: Path, output: Path) -> None: + if not tmp_output.exists(): + warnings.warn(f"Targeted tmp output {tmp_output} doesn't exists.") + return + + tmp_index = tmp_output.parent / (tmp_output.name + ".index") + tmp_output.rename(output) + + if tmp_index.exists(): + tmp_index.rename(output.parent / (output.name + ".index")) + + +def _transpose(iterable: Sequence[Tuple[Any, ...]], n=-1) -> Tuple[List, ...]: + if n < 0: + n = len(iterable[0]) + columns: tuple = tuple([] for _ in range(n)) + for row in iterable: + assert len(row) == n, f"Found tuple of len({len(row)}, expected {n}: {row}" + for i in range(n): + columns[i].append(row[i]) + + return columns + + +def hashes(conf: Config) -> List[Path]: + """Computes hashes for each shard.""" + + hashes_dir = conf.output_dir / "hashes" / conf.dump + outputs = [hashes_dir / f"{shard:04d}.bin" for shard in range(conf.num_shards)] + missing_outputs = [(shard, o) for shard, o in enumerate(outputs) if not o.exists()] + + if not missing_outputs: + return outputs + + hashes_dir.mkdir(parents=True, exist_ok=True) + # With FlatHashSet we need ~2Gb of RAM / shard, but we need to account for + # overhead due to how the dynamic allocation works. + ex = conf.get_executor(f"hashes_{conf.dump}", mem_gb=4, timeout_hour=6, cpus=2) + ex(_hashes_shard, repeat(conf), *_transpose(missing_outputs)) + + # Wait a bit so that files appears on the disk. + time.sleep(20) + assert all(o.exists() for o in outputs) + return outputs + + +def _hashes_shard(conf: Config, shard: int, output: Path): + tmp_output = tmp(output) + jsonql.run_pipes( + dedup.HashesCollector(field="raw_content", output=tmp_output), + inputs=conf.get_cc_shard(shard), + ) + finalize(tmp_output, output) + return f"Hashed {output}" + + +HASHES_IN_MEM = [0, 1, 2, 5, 10, 20, 50, 100, 200, 400] + + +def mine(conf: Config) -> List[Path]: + """Remove dups, run LID and LMs, and split by lang and quality.""" + mined_dir = conf.get_mined_dir() + if conf.will_split: + # Give a directories when splitting + outputs = [mined_dir / f"{shard:04d}" for shard in range(conf.num_shards)] + else: + # Files otherwise + outputs = [ + mined_dir / f"{shard:04d}.json.gz" for shard in range(conf.num_shards) + ] + + if "mini_again" in conf.experiments: + mined_dir = conf.output_dir / "mini_again" / conf.dump + outputs = [mined_dir / f"{shard:04d}" for shard in range(conf.num_shards)] + + # TODO: try to reduce this / make it a function of "hash_in_mem" / num_langs + mem_gb = 60 + 1 * conf.hash_in_mem + timeout_hour = 5 + if "hashes" in conf.experiments: + # HACK: used for generating paper figures + outputs = [ + conf.output_dir / f"hashes_exp/{conf.dump}_0000_dedup{h:03d}.json.gz" + for h in HASHES_IN_MEM + ] + mem_gb = int(max(HASHES_IN_MEM) * 1.2) + timeout_hour = 8 + + missing_outputs = [(shard, o) for shard, o in enumerate(outputs) if not o.exists()] + + if "mini_again" in conf.experiments: + missing_outputs = [ + (shard, o) + for shard, o in enumerate(outputs) + if shard in [5, 139] and not o.exists() + ] + + if not missing_outputs: + return outputs + + mined_dir.mkdir(parents=True, exist_ok=True) + ex = conf.get_executor( + f"mine_{conf.dump}", + mem_gb=mem_gb, + timeout_hour=timeout_hour, + cpus=conf.mine_num_processes + 1, + ) + + # Compute hashes firsts. + if "dedup" in conf.pipeline: + hashes_groups = list(jsonql.grouper(hashes(conf), conf.hash_in_mem)) + hashes_files: Iterable[List[Path]] = [ + hashes_groups[shard // conf.hash_in_mem] for shard, o in missing_outputs + ] + else: + hashes_files = repeat([]) + + ex(_mine_shard, repeat(conf), hashes_files, *_transpose(missing_outputs)) + + assert all(o.exists() for o in outputs) + return outputs + + +def _get_segment(tmp_output: Path, doc: dict) -> str: + segment: str = doc["cc_segment"].split("/")[-1] + return str(tmp_output / segment.replace(".warc.wet.gz", ".json.gz")) + + +def _mine_shard(conf: Config, hashes: List[Path], shard: int, output: Path) -> str: + assert conf.pipeline + tmp_output = tmp(output) + if "hashes" in conf.experiments: + # HACK: used for generating paper figures + hashes_in_mem = shard + hashes = hashes[: HASHES_IN_MEM[hashes_in_mem]] + shard = 0 + cc_shard = conf.get_cc_shard(shard) + + steps: Dict[str, Optional[jsonql.Transformer]] = {} + lang_id = Path("bin") / "lid.bin" + steps["lid_before_dedup"] = split_by_lang.Classifier( + model=lang_id, field="raw_content", out_field="lid_before_dedup", top=5 + ) + steps["dedup"] = dedup.DuplicatesRemover(field="raw_content", hashes_files=hashes) + + steps["lid"] = split_by_lang.Classifier( + model=lang_id, + field="raw_content", + out_field="language", + top=1, + threshold=conf.lang_threshold, + ) + steps["lid_after_dedup"] = split_by_lang.Classifier( + model=lang_id, field="raw_content", out_field="lid_after_dedup", top=5 + ) + + if conf.lang_blacklist: + steps["keep_lang"] = jsonql.where( + [lambda doc: doc.get("language") not in set(conf.lang_blacklist)] + ) + elif conf.lang_whitelist: + steps["keep_lang"] = jsonql.where( + [lambda doc: doc.get("language") in set(conf.lang_whitelist)] + ) + else: + steps["keep_lang"] = None + + tok_field = "tokenized" + steps["sp"] = perplexity.MultiSentencePiece( + {l: conf.lm_dir / f"{l}.sp.model" for l in conf.get_lm_languages()}, + field="raw_content", + output_field=tok_field, + normalize=True, + ) + steps["lm"] = perplexity.DocLM( + {l: conf.lm_dir / f"{l}.arpa.bin" for l in conf.get_lm_languages()}, + field=tok_field, + output_field="perplexity", + normalize=False, # Normalization is done before SentencePiece + # load_method=kenlm.LoadMethod.PARALLEL_READ, + ) + steps["pp_bucket"] = perplexity.PerplexityBucket(CUTOFF_CSV) + steps["drop"] = perplexity.DropKeys(tok_field) + + steps["keep_bucket"] = None + if conf.keep_bucket: + steps["keep_bucket"] = jsonql.where( + [lambda doc: doc.get("bucket", "all") in conf.keep_bucket] + ) + + if "fetch_metadata" in conf.pipeline: + # TODO: better default + assert conf.metadata is not None + steps["fetch_metadata"] = minify.MetadataFetcher( + f"{conf.metadata}/{conf.dump}/" + ) + + steps["minify"] = minify.Minifier() + + pattern = str(tmp_output / "{language}_{bucket}.json.gz") + steps["split_by_lang"] = jsonql.split(pattern=str(pattern), mkdir=True) + + steps["split_by_segment"] = jsonql.split( + split_fn=lambda doc: _get_segment(tmp_output, doc), mkdir=True + ) + + pipeline = filter(None, (steps[s] for s in conf.pipeline)) + + jsonql.run_pipes( + *pipeline, + inputs=cc_shard, + processes=conf.mine_num_processes, + chunksize=100, + # The splitter takes care of writing to files. + output=tmp_output if not conf.will_split else None, + ) + finalize(tmp_output, output) + return f"Mined {output}" + + +def regroup(conf: Config, all_dirs: List[Path]) -> Path: + """Reshards each language/quality after 'mine'.""" + regroup_dir = conf.get_mined_dir(regroup=True) + assert all_dirs + all_files = [f for d in all_dirs for f in d.glob("*.json.gz")] + if not all_files: + print(f"No .json.gz file found in {all_dirs[0]}") + + splits: Dict[str, List[Path]] = defaultdict(list) + for f in all_files: + split = f.name.split(".")[0] + splits[split].append(f) + + print(f"Identified {len(all_files)} files to regroup from {len(splits)} splits.") + inputs: List[List[Path]] = [] + outputs: List[Path] = [] + target_size = jsonql.parse_size(conf.target_size) + for split, files in splits.items(): + cuts = list(regroup_module.determine_groups(files, target_size=target_size)) + if not cuts: + continue + + pattern = f"{split}_????.json.gz" + existing_outputs = sorted(regroup_dir.glob(pattern)) + + if not conf.cleanup_after_regroup: + # We still have all the inputs so it is safe to overwrite existing outputs. + assert len(existing_outputs) <= len(cuts) + existing_outputs = [] + + if len(existing_outputs) > 0 and len(cuts) == 1: + # append to existing file if size allows it. + new_size = ( + sum(f.stat().st_size for f in cuts[0]) + + existing_outputs[-1].stat().st_size + ) + if new_size < target_size: + print(f"Will append {cuts[0]} to {existing_outputs[-1]}") + cuts[0].insert(0, existing_outputs.pop(-1)) + + n_existing = len(existing_outputs) + for i, cut in enumerate(cuts): + # avoid overwriting existing files. + j = i + n_existing + output = regroup_dir / f"{split}_{j:04}.json.gz" + inputs.append(cut) + outputs.append(output) + print( + str(regroup_dir / pattern), + "->", + len(cuts), + f"shards ({n_existing} already there).", + ) + + ex = conf.get_executor(f"regroup_{conf.dump}", mem_gb=1, timeout_hour=12, cpus=2) + ex(_regroup, repeat(conf), inputs, outputs) + + return regroup_dir + + +def _regroup(conf: Config, inputs: List[Path], output: Path) -> str: + output.parent.mkdir(parents=True, exist_ok=True) + regroup_module.fast_reshard( + inputs, output, tmp=tmp(output), rm_original=conf.cleanup_after_regroup + ) + return f"Regrouped {output}" + + +def move_segments(conf: Config, all_dirs: Sequence[Path]) -> Path: + """Reshards each language/quality after 'mine'.""" + # check that mining is over. + regroup_dir = conf.get_mined_dir(regroup=True) + assert all_dirs, "Received no dirs to move" + assert all( + d.is_dir() for d in all_dirs + ), f"move_segments was expecting dirs received files: {all_dirs[:10]}..." + + regroup_dir.parent.mkdir(exist_ok=True) + regroup_dir.mkdir(exist_ok=True) + ex = conf.get_executor(f"moveseg_{conf.dump}", mem_gb=1, timeout_hour=1, cpus=2) + + def _move_segments(subdir: Path, regroup_dir: Path) -> str: + n = 0 + for f in subdir.iterdir(): + if not f.is_file() or f.is_symlink(): + continue + n += f.name.endswith(".json.gz") + new_name = regroup_dir / f.name + target = new_name.resolve() + assert f.resolve() != target + # this make the job idempotent. + f.rename(new_name) + f.symlink_to(target) + + if n == 0: + return "" + + return f"Moved {n} .json.gz files from {subdir} to {regroup_dir}" + + ex(_move_segments, all_dirs, repeat(regroup_dir)) + print(f"Results are in {regroup_dir}") + return regroup_dir + + +def _validate_test(conf: Config, output_dir: Path, generate: bool = False): + stats: Dict[str, dict] = {} + for file in sorted(output_dir.glob("*.json.gz")): + fname = "/".join((file.parent.name, file.name)) + # The order of documents is not guaranteed inside a shard, + lines = sorted(jsonql.open_read(file)) + content = "\n".join(lines) + size = len(content) + checksum = hashlib.sha1(bytes(content, encoding="utf-8")).hexdigest() + # first_document = json.loads(lines[0]) + stats[fname] = {"size": size, "checksum": checksum} + + def dump(x): + return json.dumps(x, indent=2, ensure_ascii=False) + + print("*** Stats ***") + stats_raw = dump(stats) + stats_file = FILE_DIR / "data" / "test_stats.json" + if generate: + print("Saving stats to", stats_file) + stats_file.write_text(stats_raw) + return + + expected_stats: Dict[str, dict] = {} + if stats_file.exists(): + expected_stats = json.loads(stats_file.read_text()) + + if expected_stats == stats: + print("Everything looks good !") + return + + stats_file.with_suffix(".actual.json").write_text(stats_raw) + print("*** Expected Stats ***") + print(dump(expected_stats)) + + print("*** Diff ***") + for fname in sorted(expected_stats.keys()): + print(fname) + assert fname in expected_stats, "missing file " + fname + if expected_stats[fname]["size"] != stats[fname]["size"]: + print( + " - Expected size", + expected_stats[fname]["size"], + ", size", + stats[fname]["size"], + ) + if expected_stats[fname]["checksum"] != stats[fname]["checksum"]: + print( + " - Expected checksum", + expected_stats[fname]["checksum"], + ", checksum", + stats[fname]["checksum"], + ) + + +def get_main_parser() -> ArgumentParser: + # Generates the 'main' parser by patching a 'Config' parser + p = func_argparse.func_argparser(Config) + + # Override defaults value to None, so we know what was set by the user. + # Note that it will keep the original default values in the help message. + p.set_defaults(**{f: None for f in Config._fields}) + p.add_argument("--config", type=str, default="base") + p.set_defaults(__command=main) + return p + + +def main(config: str = "base", **config_as_dict: Any) -> None: + # Use the given 'config' as default value. + config_base = config + if config_base in PREDEF_CONFIGS: + conf = PREDEF_CONFIGS[config_base] + elif Path(config_base).exists(): + conf = Config.from_json(Path(config_base)) + else: + raise ValueError( + f"Invalid value {config_base} for --config. " + f"Choose from ({', '.join(PREDEF_CONFIGS)}) or give an existing .json file." + ) + conf = conf._replace(**{k: v for (k, v) in config_as_dict.items() if v is not None}) + + print(f"Will run cc_net.mine.main with the following config:", conf) + + all_files = mine(conf) + if conf.will_split: + assert all_files + assert all(d.is_dir() for d in all_files) + all_dirs = all_files + if "split_by_lang" in conf.pipeline: + # Only try regrouping if we split the shards. + regroup(conf, all_dirs) + elif "split_by_segment" in conf.pipeline: + # If we split by segment then regrouping is trivial, since segments appear in only one shard. + move_segments(conf, all_dirs) + + if conf.config_name == "test": + _validate_test(conf, conf.get_mined_dir(regroup=True)) + + +if __name__ == "__main__": + func_argparse.parse_and_call(get_main_parser()) diff --git a/data_tooling/kenlm_training/cc_net/minify.py b/data_tooling/kenlm_training/cc_net/minify.py new file mode 100644 index 0000000..1d5234e --- /dev/null +++ b/data_tooling/kenlm_training/cc_net/minify.py @@ -0,0 +1,304 @@ +# Copyright (c) Facebook, Inc. and its affiliates. +# +# This source code is licensed under the MIT license found in the +# LICENSE file in the root directory of this source tree. +# + +import base64 +import hashlib +import itertools +import urllib.parse +from pathlib import Path +from typing import Dict, Iterable, List, Optional, Sequence, Set, Union + +import numpy as np + +from cc_net import jsonql +from cc_net.execution import get_executor +from cc_net.jsonql import mem_footprint_gb + +HASH_SIZE = 4 +HASH_TYPE = np.uint32 + +PUBLIC_FIELDS = ["url", "digest"] +COMPUTED_FIELDS = ["cc_segment", "language", "language_score", "bucket", "perplexity"] +DATA = Path(__file__).parent.parent / "data" + + +# This is similar to dedup methods but with use 32 bits hashes. +def _b2i(b: bytes) -> int: + return np.frombuffer(b[:HASH_SIZE], dtype=HASH_TYPE, count=1, offset=0).item(0) + + +def _str_hash(s: str) -> int: + h = hashlib.sha1(bytes(s, encoding="utf-8")) + return _b2i(h.digest()) + + +def get_hashes(lines: Iterable[str]) -> List[bytes]: + h = HASH_SIZE + return [hashlib.sha1(bytes(l, encoding="utf-8")).digest()[:h] for l in lines] + + +def encode_hashes(hashes: Iterable[bytes]) -> str: + return base64.b64encode(b"".join(hashes)).decode("ascii") + + +def encode_as_hashes(lines: Iterable[str]) -> str: + return encode_hashes(get_hashes(lines)) + + +def decode_hashes(compact: str) -> List[bytes]: + all_hashes = base64.b64decode(compact) + res = [] + assert len(all_hashes) % HASH_SIZE == 0 + for i in range(len(all_hashes) // HASH_SIZE): + chunk = all_hashes[i * HASH_SIZE : (i + 1) * HASH_SIZE] + res.append(chunk) + + return res + + +def encode_line_ids(line_ids: Sequence[int]) -> str: + arr = np.array(line_ids, dtype=" List[int]: + ids_bytes = bytearray(base64.b64decode(compact)) + return np.ndarray(len(ids_bytes) // 2, dtype=" int: + assert digest.startswith("sha1:") + h = base64.b32decode(digest[5:]) + return _b2i(h[:HASH_SIZE]) + + +class Minifier(jsonql.Transformer): + ready = True + + def __init__(self): + self.fields = frozenset(COMPUTED_FIELDS + PUBLIC_FIELDS) + + def do(self, doc: dict) -> Optional[dict]: + line_ids: List[int] = doc.pop("line_ids") + fields = self.fields + keys = list(doc.keys()) + for k in keys: + if k not in fields: + doc.pop(k, None) + p = doc.get("perplexity", 0) + doc["line_ids"] = encode_line_ids(line_ids) + if p: + doc["perplexity"] = round(p, 1) + s = doc.get("language_score", 0) + if s: + doc["language_score"] = round(s, 2) + return doc + + +class MetadataFetcher(jsonql.Transformer): + """Reads documents from CC snapshot and join precomputed metadata. + + CC snapshots are split in segments. Each segment is 64Mb long. + The metadata must also be stored in segments of the same size and names. + """ + + def __init__(self, folder: Union[Path, str]): + self.ready = True + self.metadata: Dict[int, dict] = {} + + self._segments: Set[str] = set() + self.read_doc = 0 + self.missed_doc = 0 + self.missed_par = 0 + self.processed_par = 0 + + if isinstance(folder, str): + # detect path passed as string + if urllib.parse.urlparse(folder).scheme == "": + folder = Path(folder) + assert folder.exists(), f"Metadata folder not found: {folder}" + + self.folder = folder + self.segment: str = "" + self.segments_read_twice = 0 + + def meta_file(self, segment: str) -> str: + file_name = segment.split("/")[-1] + assert file_name.endswith(".warc.wet.gz") or file_name.endswith(".warc.wet") + if isinstance(self.folder, str): + return urllib.parse.urljoin( + self.folder, file_name.replace(".warc.wet", ".json") + ) + meta_file = self.folder / file_name.replace(".warc.wet", ".json") + assert ( + meta_file.exists() + ), f"Couldn't find metadata file for segment {segment} at {meta_file}" + return str(meta_file) + + def fetch_metadata(self, segment: str) -> None: + meta_file = self.meta_file(segment) + k = get_doc_key + self.metadata = {} + collision = 0 + for m in jsonql.read_jsons(meta_file): + key = k(m["digest"]) + if key in self.metadata: + collision += 1 + self.metadata[key] = m + + self.log(f"Loaded {len(self.metadata)} metadatas from {meta_file}") + if collision > 0: + self._logger.warning(f"Found {collision} collisions !") + + self.segment = segment + if segment in self._segments: + self.log("Cache miss") + self.segments_read_twice += 1 + self._segments.add(segment) + + def do(self, doc: dict) -> Optional[dict]: + if self.segment != doc["cc_segment"]: + self.fetch_metadata(doc["cc_segment"]) + digest = doc["digest"] + key = get_doc_key(digest) + if key not in self.metadata: + return None + + metadata = self.metadata.pop(key) + return self.clean(metadata, doc) + + def clean(self, metadata: dict, full_doc: dict) -> Optional[dict]: + line_ids = decode_line_ids(metadata.pop("line_ids")) + lines = full_doc["raw_content"].split("\n") + cleaned = [] + for l in line_ids: + if l >= len(lines) or l < 0: + self.missed_par += 1 + continue + cleaned.append(lines[l]) + + self.processed_par += len(line_ids) + if not cleaned: + self.missed_doc += 1 + return None + + full_doc["raw_content"] = "\n".join(cleaned) + full_doc["original_nlines"] = full_doc["nlines"] + full_doc["original_length"] = full_doc["length"] + full_doc["nlines"] = len(cleaned) + full_doc["length"] = len(full_doc["raw_content"]) + for key, value in metadata.items(): + full_doc[key] = value + return full_doc + + def summary(self) -> List[str]: + summ = super().summary() + mem = mem_footprint_gb() + len_cache = len(self.metadata) + summ.append( + f"Read {self.read_doc:_}, stocking {len_cache:_} doc in {mem:.1f}g." + ) + if self.missed_doc: + r = self.missed_doc / self.processed + summ.append(f"! Missed {self.missed_doc} documents ({r:.1%}) !") + + if self.missed_par: + r = self.missed_par / self.processed + summ.append(f"! Missed {self.missed_par} paragraphs ({r:.1%}) !") + return summ + + +def _expand_files(files: List[Path]) -> List[Path]: + if len(files) == 1 and files[0].is_dir(): + folder = files[0] + files = sorted(folder.glob("*.json.gz")) + print(f"Found {len(files)} files under {folder}/*.json.gz") + assert files, "No files found" + return files + + +def minify_file(file: Path, output: Path) -> str: + """Minify the given file.""" + jsonql.run_pipes(Minifier(), file=file, output=output) + return f"Minified {output}" + + +def minify( + files: List[Path], output_dir: Path, execution: str = "mp", parallelism: int = -1 +): + """Minify all the files in the given folder.""" + files = _expand_files(files) + output_dir.mkdir(exist_ok=True) + with open(output_dir / "files.txt", "w") as o: + for f in files: + print(f.name, file=o) + outputs = [output_dir / f.name for f in files] + ex = get_executor( + "minify", + output_dir / "logs", + execution, + timeout_hour=2, + cpus=1, + task_parallelism=parallelism, + ) + ex(minify_file, files, outputs) + + +def fetch_metadata_file( + file: Union[Path, str], + metadata_dir: Union[Path, str], + output: Path, + cache_dir: Path = None, +): + unminifier = MetadataFetcher(metadata_dir) + tmp = output.with_name("tmp." + output.name) + jsonql.run_pipes(unminifier, file=file, output=tmp) + tmp.rename(output) + return f"Fetched metadata for {file}. Results at {output}." + + +def fetch_metadata( + files: List[str], + metadata_dir: Union[Path, str], + output_dir: Path, + execution: str = "mp", + parallelism: int = -1, + cache_dir: Path = None, +): + if len(files) == 1 and Path(files[0]).is_dir(): + folder = Path(files[0]) + files = [str(f) for f in sorted(folder.glob("*.json.gz"))] + print(f"Found {len(files)} files under {folder}/*.json.gz") + + assert len(files) > 0, "No files given." + output_dir.mkdir(exist_ok=True) + + outputs = [output_dir / str(f).split("/")[-1] for f in files] + if cache_dir is None: + cache_dir = output_dir / "wet_cache" + cache_dir.mkdir(exist_ok=True) + if str(cache_dir) == "none": + cache_dir = None + files = [f for f, o in zip(files, outputs) if not o.exists()] + outputs = [o for o in outputs if not o.exists()] + if not files: + return + ex = get_executor( + "unminify", + output_dir / "logs", + execution, + timeout_hour=8, + cpus=1, + task_parallelism=parallelism, + mem_gb=32, + ) + ex(fetch_metadata_file, files, outputs, itertools.repeat(cache_dir)) + + +if __name__ == "__main__": + import func_argparse + + func_argparse.main(minify_file, minify, fetch_metadata, fetch_metadata_file) diff --git a/data_tooling/kenlm_training/cc_net/perplexity.py b/data_tooling/kenlm_training/cc_net/perplexity.py new file mode 100644 index 0000000..c93d5ac --- /dev/null +++ b/data_tooling/kenlm_training/cc_net/perplexity.py @@ -0,0 +1,356 @@ +# Copyright (c) Facebook, Inc. and its affiliates. +# +# This source code is licensed under the MIT license found in the +# LICENSE file in the root directory of this source tree. +# + +import argparse +import time +from pathlib import Path +from typing import Dict, List, Optional, Sequence, Tuple, Union + +import kenlm # type: ignore +import numpy as np # type: ignore +import pandas as pd # type: ignore +import sentencepiece # type: ignore + +from cc_net import jsonql, text_normalizer + +LMDescriptor = Union[Dict[str, Path], Union[Path, str]] + + +def get_args(): + parser = argparse.ArgumentParser( + description="Compute the score of each sentences of a document", + parents=[jsonql.io_parser()], + ) + parser.add_argument("--models", type=str) + + parser.add_argument("--sentences", action="store_true", default=False) + parser.add_argument( + "--languages", type=str, help="Ignore doc with another language" + ) + parser.add_argument("--field", type=str, default=None) + parser.add_argument("--newline", type=str, default="\n") + return vars(parser.parse_args()) + + +def pp(log_score, length): + return 10.0 ** (-log_score / length) + + +class SentencePiece(jsonql.Transformer): + # Sentence Pieces model have to be read back from disk. + warning_when_pickling = True + + def __init__( + self, + model: Path, + field: str, + output_field: str = "tokenized", + normalize: bool = False, + ): + super().__init__() + self.model = model + self.field = field + self.output_field = output_field + self.normalize = normalize + self.sp: sentencepiece.SentencePieceProcessor = None + + def _prepare(self): + if self.sp is not None: + return + self.sp = sentencepiece.SentencePieceProcessor() + self.sp.load(str(self.model)) + return self + + def do(self, document: dict) -> dict: + text = document[self.field] + if self.normalize: + text = text_normalizer.normalize(text) + tokenized = self.sp.encode_as_pieces(text) + document[self.output_field] = " ".join(tokenized) + return document + + +class MultiSentencePiece(jsonql.Transformer): + warning_when_pickling = True + + def __init__( + self, + models: Union[Path, Dict[str, Path]], + field: str, + output_field: str = "tokenized", + normalize: bool = False, + ): + super().__init__() + self.field = field + self.output_field = output_field + self.normalize = normalize + self._prefetch: Sequence[str] = [] + + if isinstance(models, Path): + self.models = { + m.name.split(".")[0]: m for m in models.parent.glob(models.name) + } + else: + self.models = models + self._prefetch = list(models.keys()) + self.sp: Dict[str, sentencepiece.SentencePieceProcessor] = {} + + def _prepare(self) -> None: + for lang in self._prefetch: + assert ( + self.get_sp(lang) is not None + ), f"No model found for {lang} at {self.models.get(lang)}." + + def get_sp(self, lang) -> Optional[sentencepiece.SentencePieceProcessor]: + sp = self.sp.get(lang) + if sp is not None: + return sp + if lang not in self.models: + return None + + start_load = time.time() + self.log(f"Loading {self.models[lang]}...") + sp = sentencepiece.SentencePieceProcessor() + sp.load(str(self.models[lang])) + self.sp[lang] = sp + load_time = time.time() - start_load + self.log(f"Loaded {self.models[lang]} (took {load_time / 60:.1f}min)") + return sp + + def do(self, document: dict) -> Optional[dict]: + text = document[self.field] + if self.normalize: + text = text_normalizer.normalize(text) + sp = self.get_sp(document.get("language")) + if sp is None: + return document + tokenized = sp.encode_as_pieces(text) + document[self.output_field] = " ".join(tokenized) + return document + + +class DocLM(jsonql.Transformer): + def __init__( + self, + models: Union[Path, Dict[str, Path]], + field: str, + output_field: str = "perplexity", + newline: str = "\n", + normalize: bool = True, + load_method: int = 2, + ): + super().__init__() + self.field = field + self.output_field = output_field + self.newline = newline + self.normalize = normalize + self._prefetch: Sequence[str] = [] + self.lm_config = kenlm.Config() + # This is the default settings + # POPULATE will mmap the models and populate the pages. + # Maybe that's not the best way when the models are on a network disk. + # TODO: try copying models file, try READ or PARALLEL_READ + self.lm_config.load_method = load_method + + if isinstance(models, Path): + self.models = { + m.name.split(".")[0]: m for m in models.parent.glob(models.name) + } + else: + self.models = models + self._prefetch = list(models.keys()) + self.lm: Dict[str, kenlm.Model] = {} + self.n_lines = 0 + + def _prepare(self) -> None: + for lang in self._prefetch: + assert ( + self.get_lm(lang) is not None + ), f"No model found for {lang} at {self.models.get(lang)}." + + def get_lines(self, document: dict) -> List[str]: + lang = document.get("language") + if not lang: + return [] + if lang not in self.models: + return [] + + content = document.get(self.field) + if not content: + return [] + + lines = content.split(self.newline) + self.n_lines += len(lines) + return lines + + def get_lm(self, lang: Optional[str]) -> Optional[kenlm.Model]: + if lang is None: + return None + lm = self.lm.get(lang) + if lm is not None: + return lm + model = self.models.get(lang) + if model is None: + return None + start_load = time.time() + self.log(f"Loading {self.models[lang]}...") + lm = kenlm.Model(str(model), self.lm_config) + self.lm[lang] = lm + load_time = time.time() - start_load + self.log(f"Loaded {self.models[lang]} (took {load_time / 60:.1f}min)") + + return lm + + def do(self, document: dict) -> dict: + lines = self.get_lines(document) + model = self.get_lm(document.get("language")) + if not lines or not model: + return document + + doc_log_score, doc_length = 0, 0 + for line in lines: + if self.normalize: + line = text_normalizer.normalize(line) + log_score = model.score(line) + length = len(line.split()) + 1 + doc_log_score += log_score + doc_length += length + + document[self.output_field] = round(pp(doc_log_score, doc_length), 1) + return document + + def summary(self): + delay = time.time() - self.start_time + h = delay / 3600 + s = self.n_lines / delay + + summ = super().summary() + summ.append(f"Processed {self.n_lines:_} lines in {h:.2}h ({s:.1} lines/s).") + return summ + + +class SentencesLM(DocLM): + """Returns the score of each individual paragraph.""" + + def do(self, document: dict) -> Optional[str]: # type: ignore + lines = self.get_lines(document) + model = self.get_lm(document.get("language")) + if not lines or not model: + return None + + sentences = [] + for line in lines: + if self.normalize: + line = text_normalizer.normalize(line) + log_score = model.score(line) + length = len(line.split()) + 1 + + sentences.append(f"{pp(log_score, length)}\t{line}") + + return "\n".join(sentences) + + +class PerplexityBucket(jsonql.Transformer): + def __init__( + self, cutoff_csv: Path, percentile_head: int = 30, percentile_tail: int = 60 + ): + super().__init__() + self.cutoff_csv = cutoff_csv + self.percentile_head = percentile_head + self.percentile_tail = percentile_tail + self.cutoffs: Dict[str, Tuple[float, float]] = {} + + def _prepare(self) -> None: + cutoffs = pd.read_csv(self.cutoff_csv, index_col=0) + self.cutoffs = { + l: (cutoffs[l][self.percentile_head], cutoffs[l][self.percentile_tail]) + for l in cutoffs.columns + } + + def get_bucket(self, doc: dict) -> str: + perplexity = doc.get("perplexity", -1) + lang = doc.get("language") + if lang not in self.cutoffs or perplexity < 0: + return "all" + + pp_head, pp_tail = self.cutoffs[lang] + if perplexity < pp_head: + return "head" + if perplexity < pp_tail: + return "middle" + return "tail" + + def do(self, doc: dict) -> dict: + doc["bucket"] = self.get_bucket(doc) + return doc + + +class DropKeys(jsonql.Transformer): + def __init__(self, *keys): + super().__init__() + self.keys = keys + + def do(self, document: dict) -> Optional[dict]: + if not document: + return None + + for key in self.keys: + document.pop(key, None) + return document + + +class RemoveSmall(jsonql.Transformer): + def __init__(self, field, min_len): + super().__init__() + self.field = field + self.min_len = min_len + self.removed = 0 + + def do(self, document: dict) -> Optional[dict]: + if not document: + return None + + content = document.get(self.field) + if not content or len(content) < self.min_len: + self.removed += 1 + return None + return document + + def summary(self): + r, n = self.removed, self.processed + ratio = r / n if n else 0 + return [f"Removed {r} small documents out of {n} ({ratio:.1%})"] + + +def perplexity_to_bin(file: Path, output: Path, models, tok_field: str): + pp_field = "perplexity" + lm = DocLM(models, tok_field, output_field=pp_field) + stats: List[float] = [] + max_stats = 1_000_000 + batch_size = 100_000 + i = 0 + batch = [] + with open(output, "wb") as o: + for doc in jsonql.read_jsons(file): + i += 1 + pp = lm(doc)[pp_field] + if len(stats) < max_stats: + stats.append(pp) + batch.append(pp) + if len(batch) >= batch_size: + np.array(batch, dtype=np.float32).tofile(o) + batch = [] + if len(batch) > 0: + np.array(batch, dtype=np.float32).tofile(o) + + +if __name__ == "__main__": + args = get_args() + output = Path(args["output"]) + if output.suffix == ".bin": + perplexity_to_bin(args["file"], output, args["models"], args["field"]) + else: + jsonql.run_pipe(DocLM, args) diff --git a/data_tooling/kenlm_training/cc_net/process_wet_file.py b/data_tooling/kenlm_training/cc_net/process_wet_file.py new file mode 100644 index 0000000..a870f6c --- /dev/null +++ b/data_tooling/kenlm_training/cc_net/process_wet_file.py @@ -0,0 +1,287 @@ +# Copyright (c) Facebook, Inc. and its affiliates. +# +# This source code is licensed under the MIT license found in the +# LICENSE file in the root directory of this source tree. +# + +import contextlib +import functools +import logging +import re +import tempfile +import time +import urllib.request +from pathlib import Path +from typing import ContextManager, Iterable, Iterator, List, Optional, Sequence +from urllib.parse import urlparse + +import func_argparse +from bs4 import BeautifulSoup # type: ignore + +from cc_net import jsonql + +WET_URL_ROOT = "https://commoncrawl.s3.amazonaws.com" + + +logger = logging.getLogger(__name__) + + +def cc_wet_paths_url(dump_id: str) -> str: + return "/".join([WET_URL_ROOT, "crawl-data", "CC-MAIN-" + dump_id, "wet.paths.gz"]) + + +@functools.lru_cache() +def cc_segments(dump_id: str, cache_dir: Path = None) -> List[str]: + wet_paths = cc_wet_paths_url(dump_id) + cache_dir = cache_dir or jsonql._tmp_dir() + wet_paths_cache = cache_dir / f"wet_{dump_id}.paths.gz" + f = jsonql.open_remote_file(wet_paths, cache=wet_paths_cache) + return [segment.strip() for segment in f] + + +def list_dumps() -> List[str]: + home_page = BeautifulSoup( + urllib.request.urlopen("http://index.commoncrawl.org/"), features="html.parser" + ) + dumps = [a.get("href").strip("/") for a in home_page.findAll("a")] + dumps = [a[8:] for a in dumps if re.match(r"^CC-MAIN-\d\d\d\d-\d\d$", a)] + + return sorted(dumps) + + +def ls(): + for dump in list_dumps(): + print(dump, "->", cc_wet_paths_url(dump)) + + +def parse_doc(headers: List[str], doc: List[str]) -> Optional[dict]: + """Headers format is: + WARC/1.0 + WARC-Type: conversion + WARC-Target-URI: [url] + WARC-Date: [crawldate: 2019-02-15T19:15:59Z] + WARC-Record-ID: + WARC-Refers-To: + WARC-Block-Digest: sha1:S3DTWCONT2L6ORTGCY2KXEZ37LNBB7V2 + Content-Type: text/plain + Content-Length: 7743 + """ + if not headers or not doc: + return None + + try: + warc_type = headers[1].split()[1] + if warc_type != "conversion": + return None + url = headers[2].split()[1] + date = headers[3].split()[1] + digest = headers[6].split()[1] + length = int(headers[8].split()[1]) + except Exception as e: + logger.warning("Can't parse header:", e, headers, doc) + return None + + # Docs are separated by two empty lines. + last = None + if not doc[-1] and not doc[-2]: + last = -2 + title, doc = doc[0], doc[1:last] + + return { + "url": url, + "date_download": date, + "digest": digest, + "length": length, + "nlines": len(doc), + "source_domain": urlparse(url).netloc, + "title": title, + "raw_content": "\n".join(doc), + } + + +def group_by_docs(warc_lines: Iterable[str]) -> Iterable[dict]: + doc: List[str] = [] + headers, read_headers = [], True + for warc in warc_lines: + warc = warc.strip() + if read_headers: + headers.append(warc) + read_headers = warc != "" + continue + + if warc == "WARC/1.0": + # We reached the beginning of the new doc. + parsed = parse_doc(headers, doc) + if parsed is not None: + yield parsed + headers, doc, read_headers = [warc], [], True + continue + + doc.append(warc) + + # Return the last document + if doc: + parsed = parse_doc(headers, doc) + if parsed is not None: + yield parsed + + +def parse_warc_file(lines: Iterable[str], min_len: int = 1) -> Iterator[dict]: + n_doc = 0 + n_ok = 0 + for doc in group_by_docs(lines): + n_doc += 1 + if not doc or len(doc["raw_content"]) < min_len: + continue + n_ok += 1 + yield doc + if n_doc > 0: + logger.info(f"Kept {n_ok:_d} documents over {n_doc:_d} ({n_ok / n_doc:.1%}).") + else: + logger.info(f"Found no documents") + + +def dl( + dump: str, + shard: int, + num_shards: int, + output: Path = None, + num_segments_per_shard: int = 0, +): + """Download a shard of the common crawl, and export it to json. + + Arguments: + output: filename of the output file + dump: CC dump id + shard: id of the shard + num_shards: total number of shards + num_segments_per_shard: manual control of the number of segment per shard. + """ + reader = CCShardReader(dump, shard, num_shards, num_segments_per_shard) + jsonql.run_pipes(inputs=reader, output=output) + logger.info(f"Done. {output} is ready.") + + +class CCSegmentsReader(Iterable[dict]): + def __init__( + self, segments: Sequence[str], min_len: int = 0, cache_dir: Path = None + ): + self._segments = segments + self.min_len = min_len + if cache_dir is not None: + cache_dir = Path(cache_dir) + cache_dir.mkdir(exist_ok=True) + self.cache_dir = cache_dir + self.retrieved_segments = 0 + + def segment_url(self, segment: str): + return "/".join((WET_URL_ROOT, segment)) + + @property + def segments(self) -> Sequence[str]: + return self._segments + + def open_segment(self, segment: str) -> Iterable[str]: + url = self.segment_url(segment) + file: Optional[Path] = None + if self.cache_dir: + file = self.cache_dir / segment.split("/")[-1] + if not file or not file.exists(): + self.retrieved_segments += 1 + + return jsonql.open_remote_file(url, cache=file) + + def __iter__(self) -> Iterator[dict]: + n = len(self.segments) + for i, segment in enumerate(self.segments): + start = time.time() + # TODO: start downloading the next segment in the background + for doc in parse_warc_file(self.open_segment(segment), self.min_len): + doc["cc_segment"] = segment + yield doc + + if i + 1 >= n: + continue + end = time.time() + delay = (end - start) / 3600 * (n - 1 - i) + logger.info( + f"Parsed {i + 1} / {n} files. Estimated remaining time: {delay:.1f}h" + ) + + +class CCShardReader(CCSegmentsReader): + def __init__( + self, + dump: str, + shard: int, + num_shards: int = -1, + num_segments_per_shard: int = 40, + min_len: int = 300, + cache_dir: Path = None, + ): + """Downloads a shard of Common Crawl, and yields dict. + + Arguments: + dump: CC dump id + shard: id of the shard + num_shards: total number of shards + num_segments_per_shard: if set will limit the number of files by shard. + Useful for testing. + """ + super().__init__([], min_len=min_len, cache_dir=cache_dir) + self.dump = dump + self.shard = shard + assert num_shards > 0 or num_segments_per_shard > 0 + self.num_shards = num_shards + self.num_segments_per_shard = num_segments_per_shard + + @property + def segments(self) -> Sequence[str]: + # Delaying the initialization allows to delay the looking up of the WET files + if self._segments: + return self._segments + segments = cc_segments(self.dump, self.cache_dir) + n = len(segments) + if self.num_shards < 0: + self.num_shards = n // self.num_segments_per_shard + i_min = (self.shard * n) // self.num_shards + i_max = ((self.shard + 1) * n) // self.num_shards + if self.num_segments_per_shard > 0: + i_max = min(i_max, i_min + self.num_segments_per_shard) + self._segments = segments[i_min:i_max] + return self._segments + + +def _tmp(prefix: str = None, suffix: str = None, dir: Path = None) -> Path: + _, tmp_path = tempfile.mkstemp(prefix=prefix, suffix=suffix, dir=dir) + return Path(tmp_path) + + +@contextlib.contextmanager +def timer(name: str = "-"): + start = time.time() + yield None + delay = time.time() - start + print(f"{name} took {delay:.1f}s") + + +def benchmark(tmp_path: Path): + segments = [ + "crawl-data/CC-MAIN-2019-09/segments/1550249406966.99/wet/CC-MAIN-20190222220601-20190223002601-00441.warc.wet.gz" + ] + seg_file = tmp_path / "CC-MAIN-20190222220601-20190223002601-00441.warc.wet.gz" + + with timer("from network"): + list(CCSegmentsReader(segments)) + + with timer("from network, with caching"): + list(CCSegmentsReader(segments, cache_dir=tmp_path)) + assert seg_file.exists() + + with timer("from disk"): + CCSegmentsReader(segments, cache_dir=tmp_path) + seg_file.unlink() + + +if __name__ == "__main__": + func_argparse.main(ls, dl) diff --git a/data_tooling/kenlm_training/cc_net/regroup.py b/data_tooling/kenlm_training/cc_net/regroup.py new file mode 100644 index 0000000..575baee --- /dev/null +++ b/data_tooling/kenlm_training/cc_net/regroup.py @@ -0,0 +1,122 @@ +# Copyright (c) Facebook, Inc. and its affiliates. +# +# This source code is licensed under the MIT license found in the +# LICENSE file in the root directory of this source tree. +# + +import logging +import subprocess +from pathlib import Path +from typing import List + +import func_argparse +import numpy as np + +from cc_net import jsonql + + +def get_index(file: Path) -> Path: + return file.parent / (file.name + ".index") + + +def _get_tmp(output: Path) -> Path: + return output.parent / (output.stem + ".tmp" + output.suffix) + + +def reshard( + inputs: List[Path], + output: Path, + tmp: Path = None, + free_original: bool = False, + rm_original: bool = False, +) -> Path: + """Read the given files and concatenate them to the output file. + + Can remove original files on completion, or just write dummy content into them to free disk. + """ + if tmp is None: + tmp = _get_tmp(output) + logging.info(f"Resharding {inputs} to {tmp}, will move later to {output}") + jsonql.run_pipes(file=inputs, output=tmp) + tmp.replace(output) + tmp_index = get_index(tmp) + if tmp_index.exists(): + tmp_index.replace(get_index(output)) + + if not (free_original or rm_original): + return output + + for _input in inputs: + if rm_original: + _input.unlink() + elif free_original: + # Overwrite the previous file. + # This frees up disk space and allows doit to properly track the success. + _input.write_text(f"Resharded into {output}") + if get_index(_input).is_file(): + get_index(_input).unlink() + + return output + + +def fast_reshard( + inputs: List[Path], + output: Path, + tmp: Path = None, + free_original: bool = False, + rm_original: bool = False, +) -> Path: + """Same as reshard but don't re-compress the output. + + This will lead to a bigger output file, especially if the shards are very small. + """ + if tmp is None: + tmp = _get_tmp(output) + with open(tmp, "wb") as o: + subprocess.run(["cat"] + [str(f) for f in inputs], stdout=o) + + tmp.replace(output) + indexes_files = [get_index(i) for i in inputs] + existing_indexes = sum(i.exists() for i in indexes_files) + assert ( + existing_indexes == len(indexes_files) or existing_indexes == 0 + ), "some indexes don't exist." + if existing_indexes > 0: + indexes = [np.load(idx) for idx in indexes_files] + for i in range(len(indexes) - 1): + indexes[i + 1] += indexes[i][-1] + with open(str(output) + ".index", "wb") as o: + np.save(o, np.concatenate(indexes)) + + if not (free_original or rm_original): + return output + + for _input in inputs: + if rm_original: + _input.unlink() + elif free_original: + # Overwrite the previous file. + # This frees up disk space and allows doit to properly track the success. + _input.write_text(f"Resharded into {output}") + if get_index(_input).is_file(): + get_index(_input).unlink() + + return output + + +def determine_groups( + inputs: List[Path], target_size: int = 4 * 1024 ** 3 +) -> List[List[Path]]: + if len(inputs) == 0: + return [] + + sample = inputs[:10] + typical_size = sum(s.stat().st_size for s in sample) / len(sample) + group_size = min(target_size // typical_size, len(inputs)) + group_size = max(group_size, 1) + + return jsonql.grouper(inputs, group_size) + + +if __name__ == "__main__": + func_argparse.single_main(reshard) diff --git a/data_tooling/kenlm_training/cc_net/split_by_lang.py b/data_tooling/kenlm_training/cc_net/split_by_lang.py new file mode 100644 index 0000000..e8c5c62 --- /dev/null +++ b/data_tooling/kenlm_training/cc_net/split_by_lang.py @@ -0,0 +1,151 @@ +# Copyright (c) Facebook, Inc. and its affiliates. +# All rights reserved. +# This source code is licensed under the license found in the +# LICENSE file in the root directory of this source tree. + + +import argparse +import collections +from pathlib import Path +from typing import Dict, Optional + +import fasttext # type: ignore + +from cc_net import jsonql + + +def get_args(): + parser = argparse.ArgumentParser( + description="Read a list of json files and split them ", + parents=[jsonql.io_parser()], + ) + parser.add_argument("--pattern", type=str) + parser.add_argument("--field", type=str, default="raw_content") + parser.add_argument("--threshold", type=float, default=0) + parser.add_argument("--model", type=str, required=True) + parser.add_argument("--out_field", type=str, default="language") + parser.add_argument("--top", type=int, default=1) + return vars(parser.parse_args()) + + +def predict(model, text: str, k: int = 1): + labels, scores = model.predict(text, k=k) + labels = [l.replace("__label__", "") for l in labels] + return labels, scores + + +def avg_predict(model, text): + # Overall gives the same results than predict(model, text.replace("\n", "")) + text = text.split("\n") + text_len = sum(len(line) for line in text) + if text_len == 0: + return None, 0 + scores = [predict(model, line) for line in text] + scores_by_label: Dict[str, float] = collections.defaultdict(float) + for (label, score), line in zip(scores, text): + scores_by_label[label] += score * len(line) + + label, score = max(scores_by_label.items(), key=lambda kv: kv[1]) + return label, score / text_len + + +class Classifier(jsonql.Transformer): + def __init__( + self, + model: Path, + field: str, + out_field: str, + threshold: float = 0, + top: int = 1, + language: str = None, + rounding: int = 2, + ): + super().__init__() + self.model = model + assert model.exists(), f"Model {model} doesn't exist." + self.field = field + self.out_field = out_field + self.threshold = threshold + self.top = top + self.language = language + self.rounding = rounding + # Fasttext model is a C object and can't be pickled + self.fasttext_model: fasttext._FastText = None + self.n_doc, self.n_accepted, self.n_ignored, self.n_disagreement = 0, 0, 0, 0 + self.cnt: Dict[str, int] = {} + + def _prepare(self): + self.log(f"Loading {self.model}") + self.fasttext_model = fasttext.load_model(str(self.model)) + + def predict(self, text): + return predict(self.fasttext_model, text.replace("\n", ""), k=self.top) + + def do(self, doc: dict) -> Optional[dict]: + text = doc.get(self.field, None) + if not text: + return None + + if self.language and doc.get("language") != self.language: + self.n_ignored += 1 + return doc + + self.n_doc += 1 + labels, scores = self.predict(text) + scores.round(self.rounding, out=scores) + for l in labels: + self.cnt[l] = self.cnt.get(l, 0) + 1 + + if self.top == 1: + existing_label = doc.get(self.out_field, None) + if existing_label and labels[0] != existing_label: + self.n_disagreement += 1 + + if all(s < self.threshold for s in scores): + return None + + self.n_accepted += 1 + if self.top == 1: + doc[self.out_field] = labels[0] + doc[self.out_field + "_score"] = scores[0] + else: + doc[self.out_field] = {l: s for l, s in zip(labels, scores)} + return doc + + def summary(self): + n_doc, n_accepted, n_disagreement, cnt, out_field = ( + self.n_doc, + self.n_accepted, + self.n_disagreement, + self.cnt, + self.out_field, + ) + summ = super().summary() + if self.threshold > 0: + ratio = n_accepted / n_doc if n_doc else 0 + summ.append(f"Kept {n_accepted} docs over {n_doc} ({ratio :.1%})") + summ.append(f"Found {len(cnt)} {out_field} labels: {cnt}") + + disagreement = n_disagreement / n_doc if n_doc else 0 + if disagreement: + summ.append(f"{out_field} disagreement is at {disagreement:.1%}.") + return summ + + def __repr__(self): + return f"Classifier({self.model})" + + +def classify_and_split(file, output, pattern, **kwargs): + classifier = Classifier(**kwargs) + splitter = jsonql.split(pattern) + jsonql.run_pipes(classifier, splitter, file=file, output=output) + + +if __name__ == "__main__": + args = get_args() + pattern = args.get("pattern") + if pattern: + classify_and_split(**args) + else: + args.pop("pattern") + jsonql.run_pipe(Classifier, args) diff --git a/data_tooling/kenlm_training/cc_net/text_normalizer.py b/data_tooling/kenlm_training/cc_net/text_normalizer.py new file mode 100644 index 0000000..0ca1349 --- /dev/null +++ b/data_tooling/kenlm_training/cc_net/text_normalizer.py @@ -0,0 +1,189 @@ +# Copyright (c) Facebook, Inc. and its affiliates. +# +# This source code is licensed under the MIT license found in the +# LICENSE file in the root directory of this source tree. +# + +import re +import unicodedata + +UNICODE_PUNCT = { + "，": ",", + "。": ".", + "、": ",", + "„": '"', + "”": '"', + "“": '"', + "«": '"', + "»": '"', + "１": '"', + "」": '"', + "「": '"', + "《": '"', + "》": '"', + "´": "'", + "∶": ":", + "：": ":", + "？": "?", + "！": "!", + "（": "(", + "）": ")", + "；": ";", + "–": "-", + "—": " - ", + "．": ". ", + "～": "~", + "’": "'", + "…": "...", + "━": "-", + "〈": "<", + "〉": ">", + "【": "[", + "】": "]", + "％": "%", + "►": "-", +} + +UNICODE_PUNCT_RE = re.compile(f"[{''.join(UNICODE_PUNCT.keys())}]") + + +def replace_unicode_punct(text: str) -> str: + return "".join(UNICODE_PUNCT.get(c, c) for c in text) + + +def remove_unicode_punct(text: str) -> str: + """More aggressive version of replace_unicode_punct but also faster.""" + return UNICODE_PUNCT_RE.sub("", text) + + +def strip_accents(line: str) -> str: + """Strips accents from a piece of text.""" + nfd = unicodedata.normalize("NFD", line) + output = [c for c in nfd if unicodedata.category(c) != "Mn"] + if len(output) == line: + return line + return "".join(output) + + +# Build a regex matching all control characters. +NON_PRINTING_CHARS_RE = re.compile( + f"[{''.join(map(chr, list(range(0,32)) + list(range(127,160))))}]" +) +DIGIT_RE = re.compile(r"\d") +PUNCT_OR_NON_PRINTING_CHARS_RE = re.compile( + (UNICODE_PUNCT_RE.pattern + NON_PRINTING_CHARS_RE.pattern).replace("][", "") +) + + +def remove_non_printing_char(text: str) -> str: + return NON_PRINTING_CHARS_RE.sub("", text) + + +def normalize_spacing_for_tok(text: str, language: str = "en") -> str: + res = ( + text.replace("\r", "") + # remove extra spaces + .replace("(", " (") + .replace(")", ") ") + .replace(" +", " ") + ) + res = re.sub(r"\) ([\.\!\:\?\;\,])", r"\)\1", res) + res = res.replace("( ", "(").replace(" )", ")") + res = re.sub(r"(\d) \%", r"\1\%", res) + res = res.replace(" :", ":").replace(" ;", ";") + res = res.replace("`", "'").replace("''", ' " ') + + res = ( + res.replace("„", '"') + .replace("“", '"') + .replace("”", '"') + .replace("–", "-") + .replace("—", " - ") + .replace(" +", " ") + .replace("´", "'") + .replace("([a-z])‘([a-z])", r"\1'\2/") + .replace("([a-z])’([a-z])", r"\1'\2/") + .replace("‘", '"') + .replace("‚", '"') + .replace("’", '"') + .replace("''", '"') + .replace("´´", '"') + .replace("…", "...") + # French quotes + .replace(" « ", ' "') + .replace("« ", '"') + .replace("«", '"') + .replace(" » ", '" ') + .replace(" »", '"') + .replace("»", '"') + # handle pseudo-spaces + .replace(" %", "%") + .replace("nº ", "nº ") + .replace(" :", ":") + .replace(" ºC", " ºC") + .replace(" cm", " cm") + .replace(" ?", "?") + .replace(" !", "!") + .replace(" ;", ";") + .replace(", ", ", ") + .replace(" +", " ") + .replace("．", ". ") + ) + # English "quotation," followed by comma, style + if language == "en": + res = re.sub(r"\"([,\.]+)", r"\1\"", res) + # Czech is confused + elif language == "cs" or language == "cz": + pass + # German/Spanish/French "quotation", followed by comma, style + else: + res = res.replace(',"', '",') + res = re.sub( + r"(\.+)\"(\s*[^<])", r"\"\1\2", res + ) # don't fix period at end of sentence + + if ( + language == "de" + or language == "es" + or language == "cz" + or language == "cs" + or language == "fr" + ): + res = re.sub(r"(\d) (\d)", r"\1,\2", res) + else: + res = re.sub(r"(\d) (\d)", r"\1.\2", res) + return res + + +def normalize(line: str, accent=True, case=True, numbers=True, punct=1) -> str: + line = line.strip() + if not line: + return line + if case: + line = line.lower() + if accent: + line = strip_accents(line) + if numbers: + line = DIGIT_RE.sub("0", line) + if punct == 1: + line = replace_unicode_punct(line) + elif punct == 2: + line = remove_unicode_punct(line) + line = remove_non_printing_char(line) + return line + + +def slow_normalize_for_dedup(line: str) -> str: + return normalize(line, accent=False, case=True, numbers=True, punct=2) + + +def normalize_for_dedup(line: str) -> str: + line = line.strip() + if not line: + return line + # case + line = line.lower() + # numbers + line = DIGIT_RE.sub("0", line) + line = PUNCT_OR_NON_PRINTING_CHARS_RE.sub("", line) + return line diff --git a/data_tooling/kenlm_training/cc_net/tokenizer.py b/data_tooling/kenlm_training/cc_net/tokenizer.py new file mode 100644 index 0000000..c48c8a4 --- /dev/null +++ b/data_tooling/kenlm_training/cc_net/tokenizer.py @@ -0,0 +1,79 @@ +# Copyright (c) Facebook, Inc. and its affiliates. +# +# This source code is licensed under the MIT license found in the +# LICENSE file in the root directory of this source tree. +# + +import time +from typing import Dict, Optional + +import sacremoses # type: ignore + +from cc_net import jsonql, text_normalizer + + +class RobustTokenizer(jsonql.Transformer): + """Moses tokenizer with the expected preprocessing.""" + + LANG_WITHOUT_ACCENT = {"en", "my"} + + def __init__(self, lang: str): + super().__init__() + self.lang = lang + self.moses = sacremoses.MosesTokenizer(lang) + self.rm_accent = lang in self.LANG_WITHOUT_ACCENT + self.ready = True + + def do(self, text: str): + text = text_normalizer.normalize( + text, accent=self.rm_accent, case=False, numbers=False, punct=True + ) + text = text_normalizer.normalize_spacing_for_tok(text, language=self.lang) + return self.moses.tokenize(text, return_str=True, escape=False) + + +class DocTokenizer(jsonql.Transformer): + """Tokenize the text found in `output_field and store the result in `output_field`.""" + + def __init__( + self, + field: str, + output_field: str = "tokenized", + language_field: str = "language", + ): + super().__init__() + self.field = field + self.output_field = output_field + self.language_field = language_field + self.n_docs = 0 + self.tokenizers: Dict[str, RobustTokenizer] = {} + + def get_tokenizer(self, lang: str) -> Optional[RobustTokenizer]: + cache = self.tokenizers + if lang in cache: + return cache[lang] + if lang in ("th", "zh", "ja"): + # TODO find a tokenizer for those languages + return None + + cache[lang] = RobustTokenizer(lang) + return cache[lang] + + def do(self, document): + lang = document[self.language_field] + tok = self.get_tokenizer(lang) + if not tok: + return document + + self.n_docs += 1 + lines = document[self.field].split("\n") + tokenized = "\n".join(tok(l) for l in lines) + document[self.output_field] = tokenized + return document + + def summary(self): + delay = (time.time() - self.start_time) / 3600 + speed = self.n_docs / delay + return [ + f"Tokenized {self.n_docs:_} documents in {delay:.2}h ({speed:.1} doc/s)." + ] diff --git a/data_tooling/kenlm_training/cc_net/tools/__init__.py b/data_tooling/kenlm_training/cc_net/tools/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/data_tooling/kenlm_training/cc_net/tools/dl_cc_100.py b/data_tooling/kenlm_training/cc_net/tools/dl_cc_100.py new file mode 100644 index 0000000..ca06f0d --- /dev/null +++ b/data_tooling/kenlm_training/cc_net/tools/dl_cc_100.py @@ -0,0 +1,206 @@ +# Copyright (c) Facebook, Inc. and its affiliates. +# +# This source code is licensed under the MIT license found in the +# LICENSE file in the root directory of this source tree. +# + +import contextlib +import functools +import gzip +import logging +import multiprocessing +from collections import defaultdict +from pathlib import Path +from typing import Callable, Dict, Iterator, List, NamedTuple, Optional, Tuple + +import cc_net +from cc_net import jsonql +from cc_net.process_wet_file import CCSegmentsReader + +# Set this to a directory to use as cache for intermediary files. +# This helps for debugging. +WET_CACHE = None +# WET_CACHE = Path("wet_cache") + +S3_BUCKET = "https://dl.fbaipublicfiles.com/cc100" +VERSION = "1.0.0" + +CC_100_SNAPSHOTS = [ + "2018-05", + "2018-09", + "2018-13", + "2018-17", + "2018-22", + "2018-26", + "2018-30", + "2018-34", + "2018-39", + "2018-43", + "2018-47", + "2018-51", +] + +BIG_LANGUAGES = { + "es_XX", + "fr_XX", + "de_DE", + "ja_XX", + "ru_RU", + "zh_CN", + "en_XX", + "it_IT", + "ar_AR", + "nl_XX", + "pl_PL", + "pt_XX", + "tr_TR", + "zh_TW", +} + + +class Paragraph(NamedTuple): + lang: str + text: str + lm_score: float + + +def _dl_shard(snapshot: str, shard: int) -> Iterator[Paragraph]: + """ + Download metadata from a shards. + + Sample metadata: + + { + "cc_segment": "crawl-data/CC-MAIN-2018-51/segments/1544376823009.19/wet/CC-MAIN-20181209185547-20181209211547-00000.warc.wet.gz", + "digest": "sha1:222LWNHN5FM26XGS7WJSMI6IISTVWBKJ", + "url": "http://personals.gearplay.com/ads/DRJONES.htm", + "line_ids": [10], + "languages": ["en_XX"], + "lm_scores": [-2.658], + } + """ + snapshot = snapshot.replace("-", "_") + name = f"snap_{snapshot}_batch_{shard}.json.gz" + url = "/".join([S3_BUCKET, VERSION, name]) + shard_metadata: Dict[str, Dict[str, dict]] = defaultdict(dict) + try: + cache_file: Optional[Path] = None + if WET_CACHE is not None: + cache_file = WET_CACHE / name + metadata_file = jsonql.open_remote_file(url, cache_file) + except: + logging.warning(f"Couldn't open {url}") + return + + for meta in jsonql.read_jsons(metadata_file): + shard_metadata[meta["cc_segment"]][meta["digest"]] = meta + + found_pars, missed_pars = 0, 0 + for seg, segment_metadata in shard_metadata.items(): + for doc in CCSegmentsReader([seg], cache_dir=WET_CACHE): + if doc["digest"] not in segment_metadata: + continue + + meta = segment_metadata[doc["digest"]] + full_pars = [doc["title"]] + doc["raw_content"].split("\n") + + assert len(meta["line_ids"]) == len(meta["languages"]) + assert len(meta["line_ids"]) == len(meta["lm_scores"]) + for i, lang, score in zip( + meta["line_ids"], meta["languages"], meta["lm_scores"] + ): + if snapshot != "2018-51" and lang in BIG_LANGUAGES: + # Big languages only come from "2018-51" snapshot + continue + if i >= len(full_pars): + # This is because CC100 was created by saving only urls. + # Some urls appears in different snapshot with slightly different + # versions, but we don't know which one is correct. + # Here we read both versions, but some index may end up + # being incorrect. + # This impact ~3% documents. + missed_pars += 1 + continue + + yield Paragraph(lang, full_pars[i], score) + found_pars += 1 + if missed_pars > 0: + logging.warning( + f"Missed {missed_pars} ({missed_pars / found_pars:%}) paragraphes." + ) + + +def _split_by_par( + paragraphes: Iterator[Paragraph], snapshot: str, shard: int, outdir: Path +) -> int: + outdir.mkdir(exist_ok=True) + outfiles = {} + num_pars = 0 + try: + for par in paragraphes: + # MODIFY ME: filter paragraph if needed (languages, score, ...) + if par.lang not in outfiles: + (outdir / par.lang).mkdir(exist_ok=True) + outfile = outdir / par.lang / f"snap_{snapshot}_batch_{shard}.gz" + outfiles[par.lang] = gzip.open(outfile, "wt") + + print(par.text, file=outfiles[par.lang]) + num_pars += 1 + finally: + for o in outfiles.values(): + o.close() + + logging.info(f"Extracted {num_pars:_d} paragraphs from shard {snapshot}_{shard}") + return num_pars + + +def dl_shard(snapshot: str, shard: int, outdir: Path) -> int: + return _split_by_par(_dl_shard(snapshot, shard), snapshot, shard, outdir) + + +@contextlib.contextmanager +def unordered_map(processes: int): + if processes == 0: + yield map + return + + with multiprocessing.Pool(processes) as pool: + yield pool.imap_unordered + + +def dl_snapshot(snapshot: str, outdir: Path, processes: int = 1) -> None: + _dl_shard = functools.partial(dl_shard, snapshot, outdir=outdir) + + with unordered_map(processes) as umap: + num_pars = sum(umap(_dl_shard, range(500))) + + logging.info(f"Extracted {num_pars:_d} paragraphs from snapshot {snapshot}.") + + +def dl( + snapshot: str = None, outdir: Path = Path("data_cc100"), processes: int = 1 +) -> None: + """ + Download CC100 corpus. + Will create one text file per language and CC snapshot. + + - snapshot: restrict to one snapshot. Useful for parallelization. + - outdir: output directory + - processes: number of processes to use + """ + if snapshot is None: + snapshots = CC_100_SNAPSHOTS + else: + snapshots = snapshot.split(",") + + invalids = [s for s in snapshots if s not in CC_100_SNAPSHOTS] + assert not invalids, f"Invalid snapshots {invalids}, chose from {CC_100_SNAPSHOTS}" + + for snapshot in snapshots: + dl_snapshot(snapshot, outdir, processes) + + +if __name__ == "__main__": + import func_argparse + + func_argparse.single_main(dl) diff --git a/data_tooling/kenlm_training/cc_net/tools/expand_corpus.py b/data_tooling/kenlm_training/cc_net/tools/expand_corpus.py new file mode 100644 index 0000000..44f3dce --- /dev/null +++ b/data_tooling/kenlm_training/cc_net/tools/expand_corpus.py @@ -0,0 +1,295 @@ +# Copyright (c) Facebook, Inc. and its affiliates. +# +# This source code is licensed under the MIT license found in the +# LICENSE file in the root directory of this source tree. +# + +""" +Tools to search sentences in CC similar to sentences in another corpus. +""" + +import functools +import logging +import math +import subprocess +from collections import Counter +from pathlib import Path +from typing import Iterable, List, Optional, Set, Tuple + +import func_argparse +import submitit +from kenlm import Model as KenlmModel # type: ignore +from sentence_splitter import SentenceSplitter # type: ignore +from sentencepiece import SentencePieceProcessor # type: ignore + +from cc_net import dedup, jsonql, perplexity, text_normalizer + +KENLM = Path("./bin/lmplz") +KENLM_BUILD = Path("./bin/build_binary") +VOCAB_SIZE = 2 ** 16 - 10 +PROCESSES = 16 + + +def normalize(corpus: Path, output_dir: Path) -> Path: + normalized = output_dir / (corpus.stem + ".normalized") + if normalized.exists(): + return normalized + + print("Will normalize", corpus, "to", normalized) + jsonql.run_pipes( + jsonql.Mapper(text_normalizer.normalize), + file=corpus, + output=normalized, + processes=PROCESSES, + ) + return normalized + + +# TODO use classic files directory. +def sp_model(lang: str) -> Path: + return Path(f"/checkpoint/guw/cc_clean/lm_sp/{lang}.sp.model") + + +def _dataset(dataset: Optional[Path], lang: str) -> Path: + return ( + dataset + or Path("/datasets01_101/common_crawl/020919") / f"{lang}_head_*.json.gz" + ) + + +class SentencePiece(jsonql.Transformer): + def __init__(self, model: Path): + super().__init__() + self.model = model + self.sp: SentencePieceProcessor = None # type: ignore + + def _prepare(self): + self.sp = SentencePieceProcessor() + self.sp.load(str(self.model)) + + def do(self, line: str) -> str: + return " ".join(self.sp.encode_as_pieces(line)) + + +class ExtractSentences(jsonql.Transformer): + def __init__( + self, + sp_model: Path, + lm_model: Path, + field: str = "raw_content", + threshold: float = float("+inf"), + ): + super().__init__() + self.sp_model = sp_model + self.lm_model = lm_model + self.field = field + self.threshold = threshold + self.sp: SentencePieceProcessor = None + self.lm: KenlmModel = None + self.splitter: SentenceSplitter = None + self.hashes: Set[int] = set() + + def _prepare(self): + self.sp = SentencePieceProcessor() + self.sp.load(str(self.sp_model)) + self.splitter = SentenceSplitter("en") + self.lm = KenlmModel(str(self.lm_model)) + + def do(self, document: dict) -> Optional[str]: + content: Optional[str] = document.get(self.field) + if not content: + return None + all_sentences = [ + s for l in content.split("\n") if l for s in self.splitter.split(text=l) + ] + unique_sentences = [] + for s in all_sentences: + if not s: + continue + h = dedup.str_hash(s) + if h in self.hashes: + continue + self.hashes.add(h) + unique_sentences.append(s) + + scores = [] + for sentence in unique_sentences: + normalized = text_normalizer.normalize(sentence) + pieces = self.sp.encode_as_pieces(normalized) + log_score = self.lm.score(" ".join(pieces)) + pp = -1 + if len(pieces): + pp = perplexity.pp(log_score, len(pieces)) + scores.append(pp) + + res = filter( + lambda pp_s: self.threshold > pp_s[0] > 0, zip(scores, unique_sentences) + ) + return "\n".join(f"{pp}\t{s}" for (pp, s) in res) or None + + +def tokenize(corpus: Path, output_dir: Path, lang: str) -> Path: + tokenized = output_dir / (corpus.stem + ".tokenized") + if tokenized.exists(): + return tokenized + + print("Will SentencePiece", corpus, "to", tokenized) + jsonql.run_pipes( + SentencePiece(sp_model(lang)), + file=normalize(corpus, output_dir), + output=tokenized, + processes=PROCESSES, + ) + + return tokenized + + +def train_lm( + corpus: Path, + output_dir: Path, + lang: str = "en", + vocab_size: int = VOCAB_SIZE, + ngrams: int = 5, +): + lm_text_file = output_dir / (corpus.stem + ".arpa") + lm_bin_file = output_dir / (corpus.stem + ".arpa.bin") + if lm_bin_file.exists(): + return lm_bin_file + + assert KENLM.exists(), f"{KENLM} binary to train kenlm model not found." + + normalized = normalize(corpus, output_dir) + tokenized = tokenize(normalized, output_dir, lang) + + print("Will train LM", lm_text_file, "on", tokenized) + kenlm_cmd = [ + str(KENLM), + f"--order={ngrams}", + "--memory=8G", + f"--temp_prefix={jsonql._tmp_dir()}", + f"--text={tokenized}", + f"--arpa={lm_text_file}", + f"--vocab_estimate={vocab_size}", + "--discount_fallback", + ] + subprocess.run(kenlm_cmd, check=True) + print("Will create binary model", lm_bin_file, "from", lm_text_file) + subprocess.run([str(KENLM_BUILD), str(lm_text_file), str(lm_bin_file)], check=True) + return lm_bin_file + + +def uniform_sampling_wrt_perplexity( + paragraphes: Iterable[str], + rounding: float = 100.0, + cut: float = 1000.0, + samples: int = 20, +) -> Iterable[str]: + max_samples = math.floor(cut / rounding * samples) + n = 0 + buckets = Counter([0.0]) + logging.info(f"Will sample {max_samples} sentences.") + for lines in paragraphes: + for line in lines.split("\n"): + if not line: + continue + pp = float(line[: line.find("\t")]) + pp = math.floor(pp / rounding) * rounding + if pp > cut: + continue + if buckets[pp] > samples: + continue + yield line + buckets[pp] += 1 + if buckets[pp] > samples: + logging.info(f"Bucket {pp} is full ({samples} samples, {n} total)") + n += 1 + if n > max_samples: + return + + +def sample( + corpus: Path, + output_dir: Path, + dataset: Path = None, + n: int = 10_000, + lang: str = "en", +) -> Path: + sample_file = output_dir / (corpus.stem + ".pp_sample.tsv") + if sample_file.exists(): + return sample_file + dataset = _dataset(dataset, lang) + extractor = ExtractSentences( + sp_model(lang), train_lm(corpus, output_dir), field="raw_content" + ) + sampling = functools.partial( + uniform_sampling_wrt_perplexity, rounding=100.0, cut=1000.0, samples=n // 10 + ) + + print(f"Will sample data from {dataset} to {sample_file}") + try: + jsonql.run_pipes( + extractor, sampling, file=dataset, output=sample_file, processes=PROCESSES + ) + except Exception: + sample_file.unlink() + raise + + subprocess.run(["sort", "-n", "-o", sample_file, sample_file], check=True) + subprocess.run(["head", sample_file], check=True) + return sample_file + + +def mine( + corpus: Path, + output_dir: Path, + threshold: float, + dataset: Path = None, + lang: str = "en", +) -> List[Path]: + """Search sentences in CC similar to the one in the given corpus. + + Args: + - corpus: corpus to train the LM one. Assumes one sentence per line. + - output_dir: where to store the results + - threshold: maximum perplexity to have + - dataset: glob pattern matching CC shards. + - lang: search in the files of this language + """ + dataset = _dataset(dataset, lang) + files = list(dataset.parent.glob(dataset.name)) + outputs = [output_dir / (f.stem + ".tsv") for f in files] + if all(o.exists() for o in outputs): + return outputs + + n = len(outputs) + sp = [sp_model(lang)] * n + lm = [train_lm(corpus, output_dir)] * n + thresholds = [threshold] * n + + ex = submitit.AutoExecutor(output_dir / "mining_logs") + ex.update_parameters( + name="mine", + cpus_per_task=PROCESSES, + timeout_min=60 * 24 // PROCESSES, + mem_gb=10, + ) + jobs = ex.map_array(_mine, files, outputs, sp, lm, thresholds) + print("Submited job array:", jobs[0]) + + for j in submitit.helpers.as_completed(jobs): + (i, o) = j.result() + print("Mined sentences from", i, "to", o) + + return outputs + + +def _mine( + file: Path, output: Path, sp: Path, lm: Path, threshold: float +) -> Tuple[Path, Path]: + extractor = ExtractSentences(sp, lm, field="raw_content", threshold=threshold) + jsonql.run_pipes(extractor, file=file, output=output, processes=PROCESSES) + return (file, output) + + +if __name__ == "__main__": + func_argparse.main(sample, mine) diff --git a/data_tooling/kenlm_training/cc_net/tools/make_dmoz_corpus.py b/data_tooling/kenlm_training/cc_net/tools/make_dmoz_corpus.py new file mode 100644 index 0000000..214b95e --- /dev/null +++ b/data_tooling/kenlm_training/cc_net/tools/make_dmoz_corpus.py @@ -0,0 +1,97 @@ +# Copyright (c) Facebook, Inc. and its affiliates. +# +# This source code is licensed under the MIT license found in the +# LICENSE file in the root directory of this source tree. +# + +""" +This code is used to train a fastText classifier to label document with DMOZ categories. + +The data, distributed under the cc-by 3.0 license +(https://web.archive.org/web/20140605215533/http://www.dmoz.org/license.html), +can be downloaded from +https://web.archive.org/web/20140617145301/http://rdf.dmoz.org/rdf/content.rdf.u8.gz. +""" + +import urllib.request +from io import StringIO +from pathlib import Path +from typing import Dict, Set +from urllib.parse import urlparse + +import func_argparse +from lxml import etree # type: ignore + +from cc_net import jsonql + +TaggedUrls = Dict[str, Set[str]] +DMOZ_TAGS_URL = "https://web.archive.org/web/20140617145301/http://rdf.dmoz.org/rdf/content.rdf.u8.gz" + + +def add_tags(url: str, tags: Set[str], url2tags: TaggedUrls): + if url in url2tags: + url2tags[url] &= tags + else: + url2tags[url] = tags + + +def load_tags(filename: Path = None) -> TaggedUrls: + if filename is None: + with StringIO("".join(jsonql.open_remote_file(DMOZ_TAGS_URL))) as dmoz: + tree = etree.parse(dmoz) + else: + tree = etree.parse(str(filename)) + + root = tree.getroot() + url2tags: Dict[str, Set[str]] = {} + for external_page in root.iterfind("{http://dmoz.org/rdf/}ExternalPage"): + url = external_page.get("about") + domain = urlparse(url).netloc + for topic in external_page.iterfind("{http://dmoz.org/rdf/}topic"): + # print(url, topic.text) + # Tags looks like Top/Arts/Animation/Anime/Collectibles + tags = set(topic.text.split("/")[1:]) + add_tags(url, tags, url2tags) + add_tags(domain, tags, url2tags) + return url2tags + + +def dl(output: Path) -> None: + urllib.request.urlretrieve(DMOZ_TAGS_URL, output) + + +def make_corpus(file: Path, tags_file: Path = None, output: Path = None) -> None: + """ + Loads a tags file and create a training dataset using the given webpages. + + Arguments: + - file: CC shard file + - tags_file: dmoz tagging file, (like the one produced by `dl`) + - output: "" + """ + url2tags = load_tags(tags_file) + with jsonql.open_write(output) as o: + for document in jsonql.read_jsons(file): + if not document: + continue + url = document["url"] + domain = document["source_domain"] + + if url in url2tags: + tags = url2tags[url] + elif domain in url2tags: + tags = url2tags[domain] + else: + continue + + if len(tags) == 0: + continue + + fasttext_tags = ["__label__" + tag for tag in tags] + content = document["tokenized"].replace("\n", " ").lower() + if len(content) > 200: + print(" ".join(fasttext_tags), content, file=o) # type: ignore + + +if __name__ == "__main__": + func_argparse.single_main(make_corpus) diff --git a/data_tooling/kenlm_training/pyproject.toml b/data_tooling/kenlm_training/pyproject.toml new file mode 100644 index 0000000..398fa33 --- /dev/null +++ b/data_tooling/kenlm_training/pyproject.toml @@ -0,0 +1,24 @@ +[pytest] +testpaths = "tests" + +[tool.black] +line-length = 88 +target_version = ["py37"] + +[tool.isort] +multi_line_output = 3 +include_trailing_comma = true +force_grid_wrap = 0 +use_parentheses = true +line_length = 88 +known_third_party = ["func_argparse"] +skip = ["third_party", "data"] + +[mypy] +python_version = 3.7 +check_untyped_defs = true + +[mypy-numpy] +ignore_missing_imports = true +[mypy-pytest] +ignore_missing_imports = true diff --git a/data_tooling/kenlm_training/setup.py b/data_tooling/kenlm_training/setup.py new file mode 100644 index 0000000..209ff9c --- /dev/null +++ b/data_tooling/kenlm_training/setup.py @@ -0,0 +1,56 @@ +# Copyright (c) Facebook, Inc. and its affiliates. +# All rights reserved. +# This source code is licensed under the license found in the +# LICENSE file in the root directory of this source tree. + +from pathlib import Path + +from setuptools import setup # type: ignore + +setup( + name="cc_net", + version="1.0.0", + packages=["cc_net"], + # metadata to display on PyPI + author="Guillaume Wenzek", + author_email="guw@fb.com", + description="Tools to download and clean Common Crawl", + keywords="common crawl dataset", + url="https://github.com/facebookresearch/cc_net", + license="CC-BY-NC-4.0", + long_description=Path("README.md").read_text(), + long_description_content_type="text/markdown", + project_urls={ + "Bug Tracker": "https://github.com/facebookresearch/cc_net/issues", + "Source Code": "https://github.com/facebookresearch/cc_net", + }, + classifiers=[ + "Development Status :: 4 - Beta", + "Programming Language :: Python :: 3.7", + ], + python_requires=">=3.7", + install_requires=[ + "beautifulsoup4>=4.7.1", + "pandas>=0.23.4", + "requests>=2.22.0", + "fasttext>=0.9.1", + "sentencepiece>=0.1.82", + "kenlm @ git+https://github.com/kpu/kenlm.git@master", + "func_argparse>=1.1.1", + "psutil>=5.6.3", + "sacremoses", + "submitit>=1.0.0", + "typing_extensions", + "datasets==1.16.1", + ], + extras_require={ + "dev": ["mypy==0.790", "pytest", "black==19.3b0", "isort==5.6.4"], + # To use scripts inside cc_net/tools + "tools": ["lxml", "sentence_splitter"], + # Memory-efficient hashset. + # This fork only compiles the kind of dict used by cc_net. + # Full version is at https://github.com/atom-moyer/getpy + "getpy": ["getpy @ git+https://github.com/gwenzek/getpy.git@v0.9.10-subset"], + }, + package_data={"cc_net": ["data/*"]}, +) diff --git a/data_tooling/kenlm_training/tests/__init__.py b/data_tooling/kenlm_training/tests/__init__.py new file mode 100644 index 0000000..dbb8e8f --- /dev/null +++ b/data_tooling/kenlm_training/tests/__init__.py @@ -0,0 +1,6 @@ +# Copyright (c) Facebook, Inc. and its affiliates. +# +# This source code is licensed under the MIT license found in the +# LICENSE file in the root directory of this source tree. +# +# diff --git a/data_tooling/kenlm_training/tests/conftest.py b/data_tooling/kenlm_training/tests/conftest.py new file mode 100644 index 0000000..a7273de --- /dev/null +++ b/data_tooling/kenlm_training/tests/conftest.py @@ -0,0 +1,19 @@ +# Copyright (c) Facebook, Inc. and its affiliates. +# +# This source code is licensed under the MIT license found in the +# LICENSE file in the root directory of this source tree. +# + +import pytest + + +def _request_is_disabled(self, *args, **kwargs): + raise Exception( + f"Your code tried to call 'request' with: {args}, {kwargs}. Unit test aren't allowed to reach internet." + ) + + +@pytest.fixture(autouse=True) +def no_requests(monkeypatch): + """Remove requests.sessions.Session.request for all tests.""" + monkeypatch.setattr("requests.sessions.Session.request", _request_is_disabled) diff --git a/data_tooling/kenlm_training/tests/data/sample.warc.txt b/data_tooling/kenlm_training/tests/data/sample.warc.txt new file mode 100644 index 0000000..ff77016 --- /dev/null +++ b/data_tooling/kenlm_training/tests/data/sample.warc.txt @@ -0,0 +1,64 @@ +WARC/1.0 +WARC-Type: warcinfo +WARC-Date: 2019-03-27T06:10:48Z +WARC-Filename: CC-MAIN-20190318132220-20190318153634-00064.warc.wet.gz +WARC-Record-ID: +Content-Type: application/warc-fields +Content-Length: 370 + +Software-Info: ia-web-commons.1.1.9-SNAPSHOT-20190314010907 +Extracted-Date: Wed, 27 Mar 2019 06:10:48 GMT +robots: checked via crawler-commons 0.11-SNAPSHOT (https://github.com/crawler-commons/crawler-commons) +isPartOf: CC-MAIN-2019-13 +operator: Common Crawl Admin (info@commoncrawl.org) +description: Wide crawl of the web for March 2019 +publisher: Common Crawl + +WARC/1.0 +WARC-Type: conversion +WARC-Target-URI: http://sample_english.com +WARC-Date: 2019-03-18T00:00:00Z +WARC-Record-ID: +WARC-Refers-To: +WARC-Block-Digest: sha1:XQZHW7QWIG54HVAV3KPRW6MK5ILDNCER +Content-Type: text/plain +Content-Length: 353 + +Famous Mark Twain Quotes +Don't part with your illusions. When they are gone you may still exist, but you have ceased to live. +Education: that which reveals to the wise, and conceals from the stupid, the vast limits of their knowledge. + +Facts are stubborn things, but statistics are more pliable. +Fiction is obliged to stick to possibilities. Truth isn't. + +WARC/1.0 +WARC-Type: conversion +WARC-Target-URI: http://sample_chinese.zh +WARC-Date: 2019-03-18T00:00:01Z +WARC-Record-ID: +WARC-Refers-To: +WARC-Block-Digest: sha1:Y4E6URVYGIAFNVRTPZ5S3J64RTZTP6HJ +Content-Type: text/plain +Content-Length: 109 + +馬克·吐溫名言 +不要放棄你的幻想。 當它們消失後，您可能仍然存在，但您已經不復存在。 +教育：向智者揭示並從愚蠢者中隱藏其知識的巨大局限的教育。 +事實是固執的東西，但統計數字卻比較柔和。 +小說必須堅持可能。 真理不是。 + +WARC/1.0 +WARC-Type: conversion +WARC-Target-URI: http://sample_russian.ru +WARC-Date: 2019-03-18T00:00:02Z +WARC-Record-ID: +WARC-Refers-To: +WARC-Block-Digest: sha1:RBW57C753IE4CHCOZCMS2BHMHBEGXKXL +Content-Type: text/plain +Content-Length: 355 + +Цитаты знаменитого Марка Твена +Не расставайся со своими иллюзиями. Когда они исчезнут, вы все еще можете существовать, но вы перестали жить. +Образование: то, что открывает мудрым и скрывает от глупых обширные границы их знаний. +Факты - упрямые вещи, но статистика более податлива. +Художественная литература обязана придерживаться возможностей. Правда нет. diff --git a/data_tooling/kenlm_training/tests/test_dedup.py b/data_tooling/kenlm_training/tests/test_dedup.py new file mode 100644 index 0000000..7e4c3ac --- /dev/null +++ b/data_tooling/kenlm_training/tests/test_dedup.py @@ -0,0 +1,245 @@ +# Copyright (c) Facebook, Inc. and its affiliates. +# +# This source code is licensed under the MIT license found in the +# LICENSE file in the root directory of this source tree. +# + +import json +from pathlib import Path +from typing import Iterable, Sequence + +from cc_net import dedup, jsonql +from cc_net.dedup import str_hash +from cc_net.flat_hash_set import FlatHashSet + + +def text(*args: str) -> str: + return "\n".join(args) + + +def write_docs(file: Path, docs: Iterable[Sequence[str]]): + file.parent.mkdir(exist_ok=True) + with open(file, "w") as f: + for sentences in docs: + doc = dict(text=text(*sentences)) + print(json.dumps(doc), file=f) + + +def as_dict(hash_set): + if not isinstance(hash_set, dict): + hash_set = {k: v for (k, v) in hash_set.items()} + return hash_set + + +def load_hashes(file): + results = dedup.FlatHashSet() + results.load(file) + return as_dict(results) + + +LENGTHS = ["original_length", "length"] + + +def assert_documents_equal(expected, actual, ignoring={}): + expected = [{k: doc[k] for k in doc if k not in ignoring} for doc in expected] + actual = [{k: doc[k] for k in doc if k not in ignoring} for doc in expected] + assert expected == actual + + +def test_simple_dedup(tmp_path: Path) -> None: + write_docs( + tmp_path / "docs.json", + [ + ["_Hello", "_World", "I'm so original"], + ["_world", "I'm originaler", "_Hello"], + ], + ) + results = list(dedup.deduplicate(tmp_path / "docs.json", field="text")) + expected = [ + # First document is untouched + dict( + text=text("_Hello", "_World", "I'm so original"), + original_nlines=3, + nlines=3, + line_ids=[0, 1, 2], + ), + # Second documents loses several lines + dict(text="I'm originaler", original_nlines=3, nlines=1, line_ids=[1]), + ] + + assert_documents_equal(expected, results, ignoring=LENGTHS) + + +def test_dedup_with_dump(tmp_path: Path): + hashes = tmp_path / "hashes.bin" + documents = [ + dict(text=text("_Hello", "_World", "I'm so original")), + dict(text=text("_world", "I'm originaler", "_Hello")), + ] + collector = dedup.HashesCollector(field="text", output=hashes) + list(collector.map(documents)) + results = load_hashes(hashes) + expected = { + str_hash(l): l.startswith("_") + for l in ["_hello", "_world", "i'm so original", "i'm originaler"] + } + assert expected == results + + +def test_dedup_with_np_dump(tmp_path: Path): + hashes = tmp_path / "hashes.bin" + documents = [ + dict(text=text("_Hello", "_World", "I'm so original")), + dict(text=text("_world", "I'm originaler", "_Hello")), + ] + with dedup.HashesCollector(field="text", output=hashes) as d: + list(d.map(documents)) + + results = FlatHashSet() + results.load_np(hashes) + expected = { + str_hash(l) for l in ["_hello", "_world", "i'm so original", "i'm originaler"] + } + assert expected == set(results.keys()) + + +def test_dedup_from_hashes(tmp_path: Path): + documents = [ + dict(text=text("_Hello", "World", "I'm so original")), + dict(text=text("Good morning", "World", "I'm originaler")), + ] + seen = ["_hello", "i'm originaler", "world"] + hashes = [str_hash(h) for h in seen] + h = dedup.FlatHashSet() + h.add(hashes) + # Note: 'world' appears only once and won't be treated as a duplicate. + h.add(hashes[:-1]) + h.dump(tmp_path / "hashes.bin") + + results = list( + dedup.DuplicatesRemover("text", [tmp_path / "hashes.bin"]).map(documents) + ) + expected = [ + dict( + text=text("World", "I'm so original"), + original_nlines=3, + nlines=2, + line_ids=[1, 2], + ), + dict( + text=text("Good morning", "World"), + original_nlines=3, + nlines=2, + line_ids=[0, 1], + ), + ] + + assert_documents_equal(expected, results, ignoring=LENGTHS) + + +def test_dedup_fast(tmp_path: Path): + data = tmp_path / "data" + part_0 = [["Hello", "_World", "I'm so original"]] + write_docs(data / "part_0.json", part_0) + part_1 = [["Good morning", "_World", "I'm originaler"]] + write_docs(data / "part_1.json", part_1) + parts = [data / "part_0.json", data / "part_1.json"] + + res = tmp_path / "res" + res.mkdir() + h = tmp_path / "hashes.bin" + field = "text" + jsonql.run_pipes(dedup.HashesCollector(field, output=h), file=parts) + for part in parts: + jsonql.run_pipes( + dedup.DuplicatesRemover(field, [h]), file=part, output=res / part.name + ) + jsonql.run_pipes( + dedup.DuplicatesRemover(field, [h]), file=part, output=res / part.name + ) + + results_0 = list(jsonql.read_jsons(res / "part_0.json")) + expected_0 = [ + dict( + text=text("Hello", "I'm so original"), + original_nlines=3, + nlines=2, + line_ids=[0, 2], + ) + ] + assert_documents_equal(expected_0, results_0, ignoring=LENGTHS) + + results_1 = list(jsonql.read_jsons(res / "part_1.json")) + expected_1 = [ + dict( + text=text("Good morning", "I'm originaler"), + original_nlines=3, + nlines=2, + line_ids=[0, 2], + ) + ] + + assert_documents_equal(expected_1, results_1, ignoring=LENGTHS) + + words = [w for part in [part_0, part_1] for doc in part for w in doc] + expected = {str_hash(s.lower()): s.startswith("_") for s in words} + assert expected == load_hashes(h) + + +def test_remove_duplicates_sharded(tmp_path: Path): + data = tmp_path / "data" + part_0 = [["Hello", "_World", "I'm so original"]] + write_docs(data / "part_0.json", part_0) + part_1 = [["_Good morning", "_World", "I'm originaler"]] + write_docs(data / "part_1.json", part_1) + + h = tmp_path / "hashes" + h.mkdir() + h0 = FlatHashSet() + h0.add([str_hash(s.lower()) for doc in part_0 for s in doc]) + h0.add([str_hash("_world")]) + h0.dump(h / "part_0.bin") + assert { + str_hash("hello"): False, + str_hash("_world"): True, + str_hash("i'm so original"): False, + } == as_dict(h0) + + h1 = FlatHashSet() + h1.add([str_hash(s.lower()) for doc in part_1 for s in doc]) + h1.add([str_hash("_good morning")]) + h1.dump(h / "part_1.bin") + assert { + str_hash("_good morning"): True, + str_hash("_world"): False, + str_hash("i'm originaler"): False, + } == as_dict(h1) + + res = tmp_path / "res" + res.mkdir() + # dedup.DISABLE_MULTI_PROCESSING = True # Simplifies debugging + dedup.remove_duplicates_sharded( + files=[data / "part_0.json", data / "part_1.json"], + outputs=[res / "part_0.json", res / "part_1.json"], + field="text", + hashes_dir=h, + ) + + results_0 = list(jsonql.read_jsons(res / "part_0.json")) + expected_0 = [ + dict( + text=text("Hello", "I'm so original"), + original_nlines=3, + nlines=2, + line_ids=[0, 2], + ) + ] + assert_documents_equal(expected_0, results_0, ignoring=LENGTHS) + + # First pass removes "_world", second "_good morning". + results_1 = list(jsonql.read_jsons(res / "part_1.json")) + expected_1 = [ + dict(text=text("I'm originaler"), original_nlines=3, nlines=1, line_ids=[2]) + ] + + assert_documents_equal(expected_1, results_1, ignoring=LENGTHS) diff --git a/data_tooling/kenlm_training/tests/test_flat_hash_set.py b/data_tooling/kenlm_training/tests/test_flat_hash_set.py new file mode 100644 index 0000000..00287df --- /dev/null +++ b/data_tooling/kenlm_training/tests/test_flat_hash_set.py @@ -0,0 +1,78 @@ +# Copyright (c) Facebook, Inc. and its affiliates. +# +# This source code is licensed under the MIT license found in the +# LICENSE file in the root directory of this source tree. +# + +import numpy as np +import pytest + +from cc_net.flat_hash_set import HASH_TYPE, FlatHashSet, NaiveHashSet + + +def as_dict(flat_hash_set) -> dict: + return {k: v for (k, v) in flat_hash_set.items()} + + +need_getpy = pytest.mark.skipif( + FlatHashSet == NaiveHashSet, reason="getpy isn't installed" +) + + +def same_behavior(test_case): + def run_case(): + naive = as_dict(test_case(FlatHashSet)) + flat = as_dict(test_case(NaiveHashSet)) + assert naive == flat + + return need_getpy(run_case) + + +@same_behavior +def test_setitem(hash_set_cls): + h = hash_set_cls() + h[np.arange(10, dtype=h.dtype)] = np.zeros(10, dtype=np.uint8) + h[np.arange(5, dtype=h.dtype)] = np.ones(5, dtype=np.uint8) + return h + + +@same_behavior +def test_add_dup(hash_set_cls): + h = hash_set_cls() + h.add(np.arange(10, dtype=h.dtype)) + h.add(np.arange(5, dtype=h.dtype)) + + expected = {i: i < 5 for i in range(10)} + assert expected == as_dict(h), f"add_dup with {hash_set_cls.__name__}" + return h + + +@need_getpy +def test_gp_dict(): + import getpy as gp # type: ignore + + h = gp.Dict(HASH_TYPE, np.uint8) + h[np.arange(10, dtype=HASH_TYPE)] = np.zeros(10, dtype=np.uint8) + h[np.arange(5, dtype=HASH_TYPE)] = np.ones(5, dtype=np.uint8) + expected = {i: i < 5 for i in range(10)} + assert expected == as_dict(h) + + +def check_reload(h, dump, load, tmp_path): + dump_path = tmp_path / dump.__name__ + dump(h, dump_path) + h2 = type(h)() + load(h2, dump_path) + assert as_dict(h) == as_dict(h2) + + +@pytest.mark.parametrize("hash_set_cls", [FlatHashSet, NaiveHashSet]) +def test_loading(tmp_path, hash_set_cls): + h = hash_set_cls() + x = np.random.randint(0, 2 ** 32, (100,), dtype=h.dtype) + h.add(x) + + check_reload(h, hash_set_cls.dump, hash_set_cls.load, tmp_path) + check_reload(h, hash_set_cls.dump_np, hash_set_cls.load_np, tmp_path) + if hasattr(hash_set_cls, "dump_gp"): + check_reload(h, hash_set_cls.dump_gp, hash_set_cls.load_gp, tmp_path) diff --git a/data_tooling/kenlm_training/tests/test_jsonql.py b/data_tooling/kenlm_training/tests/test_jsonql.py new file mode 100644 index 0000000..7d9768e --- /dev/null +++ b/data_tooling/kenlm_training/tests/test_jsonql.py @@ -0,0 +1,312 @@ +# Copyright (c) Facebook, Inc. and its affiliates. +# +# This source code is licensed under the MIT license found in the +# LICENSE file in the root directory of this source tree. +# + +import io +from pathlib import Path +from typing import Sequence + +import numpy as np +import pytest + +from cc_net import jsonql + + +def bar(small_bar: str) -> str: + return small_bar.replace(" ", " " * 10).replace("█", "█" * 10) + + +def get_output(transformer, data, **kwargs): + with io.StringIO() as output: + # Convert data to a generator so that it's not interpreted as a file list. + jsonql.run_pipe(transformer, kwargs, file=(x for x in data), output=output) + return output.getvalue() + + +def test_split(tmp_path: Path): + data = [ + dict(text="Hello world", lang="en"), + dict(text="Boujour les amis", lang="fr"), + dict(text="Rock your boat", lang="en"), + ] + with jsonql.split(tmp_path / "{lang}.json") as split: + list(split.map(data)) + summary = split.summary() + assert "Found 2 splits." in summary + en_docs = list(jsonql.read_jsons(tmp_path / "en.json")) + assert [data[0], data[2]] == en_docs + + fr_docs = list(jsonql.read_jsons(tmp_path / "fr.json")) + assert [data[1]] == fr_docs + + +def test_split_bad_pattern(tmp_path: Path): + data = [dict(text="Hello world", lang="en")] + with pytest.raises(KeyError): + with jsonql.split(tmp_path / "{language}.json") as split: + list(split.map(data)) + + +def test_histogram(): + data = [0.1, 0.1, 0.1, 0.1, 0.4, 0.4, 0.9, 0.9] + hist, bins = jsonql.histogram(data, bins=8, weights=None) + np.testing.assert_almost_equal(bins, [0.1 * x for x in range(1, 10)]) + np.testing.assert_almost_equal(hist, [4, 0, 0, 2, 0, 0, 0, 2]) + + data = [0, 0.1, 0.1, 0.1, 0.1, 0.4, 0.4, 0.8, 0.8, 1] + hist, bins = jsonql.histogram(data, bins=10, weights=None) + np.testing.assert_almost_equal(bins, [0.1 * x for x in range(11)]) + np.testing.assert_almost_equal(hist, [1, 4, 0, 0, 2, 0, 0, 0, 2, 1]) + + +def test_display_stats(): + stats = { + jsonql.ALL_DOCUMENTS: 100, + "title": 80, + "title.length": 80 * 50, + "text": 100, + "text.length": 100 * 1000, + "popularity": 8, + "popularity.val": [0.1, 0.1, 0.1, 0.1, 0.4, 0.4, 0.9, 0.9], + } + + (title,) = jsonql.display_stats(stats, "title") + assert "title" in title + assert "saw 80 times" in title + assert "average length is" in title + assert "\n" not in title + + (text,) = jsonql.display_stats(stats, "text") + assert "text" in text + assert "saw 100 times" in text + assert "average length is" in text + assert "\n" not in text + + histogram = jsonql.display_stats( + stats, "popularity", bins=[x / 10 for x in range(1, 10)] + ) + assert "popularity" in histogram[0] + assert "saw 8 times" in histogram[0] + assert "histogram is" in histogram[0] + assert "0.100 " + bar("████████") in histogram[1] + assert "0.400 " + bar("████ ") in histogram[2] + assert "0.800 " + bar("████ ") in histogram[3] + + cum_histogram = jsonql.display_stats(stats, "popularity", bins=8, cumulative=True) + assert "popularity" in cum_histogram[0] + assert "saw 8 times" in cum_histogram[0] + assert "histogram is" in cum_histogram[0] + assert "0.100 " + bar("████ ") in cum_histogram[1] + assert "0.400 " + bar("██████ ") in cum_histogram[2] + assert "0.800 " + bar("████████") in cum_histogram[3] + + +def test_describe(): + def sample(pop): + return dict(title="Lorem", text="Lorem ipsum dolor sit amet.", popularity=pop) + + data = [sample(pop) for pop in [0.1, 0.1, 0.1, 0.1, 0.4, 0.4, 0.9, 0.9]] + desc = get_output( + jsonql.describe, data, columns=None, bins=[x / 10 for x in range(1, 10)] + ) + + assert "Field title saw 8 times (100.0%), average length is 5" in desc + assert "Field text saw 8 times (100.0%), average length is 27" in desc + assert "Field popularity saw 8 times (100.0%), histogram is" in desc + assert "0.100 " + bar("████████") in desc + assert "0.400 " + bar("████ ") in desc + assert "0.800 " + bar("████ ") in desc + + desc = get_output(jsonql.describe, data, columns=["text"]) + assert "Field title saw 8 times (100.0%), average length is 5" not in desc + assert "Field text saw 8 times (100.0%), average length is 27" in desc + assert "Field popularity, histogram is:" not in desc + + +def test_custom_pipe(): + def transformer(source, sep=" "): + for i, line in enumerate(source): + res = f"{i}{sep}{line}" + yield res + + data = ["hello", "world"] + assert get_output(transformer, data) == "0 hello\n1 world\n" + assert get_output(transformer, data, sep="_") == "0_hello\n1_world\n" + + +def test_open_read_write(tmp_path: Path): + def _lines(filename: Path) -> Sequence[str]: + # jsonql.lines calls open_read + return list(jsonql.lines(filename)) + + tmp = tmp_path + with jsonql.open_write(tmp / "a.txt") as o: + print("a", file=o) + assert _lines(tmp / "a.txt") == ["a"] + + jsonql.write_jsons([{"a": 1}], tmp / "a.txt") + assert _lines(tmp / "a.txt") == ['{"a": 1}'] + + with jsonql.open_write(tmp / "a.gz") as o: + print("a", file=o) + assert _lines(tmp / "a.gz") == ["a"] + + with jsonql.open_write([tmp / "a0.txt", tmp / "a1.txt"]) as o: + print("a", file=o) + assert _lines(tmp / "a0.txt") == ["a"] + assert not (tmp / "a1.txt").is_file() + + with jsonql.open_write([tmp / "b0.txt", tmp / "b1.txt"], max_size="1k") as o: + print("0" * 2000, file=o) + print("1" * 2000, file=o) + assert _lines(tmp / "b0.txt") == ["0" * 2000] + assert _lines(tmp / "b1.txt") == ["1" * 2000] + + with jsonql.open_write(tmp / "a_????.json") as o: + print("a", file=o) + assert _lines(tmp / "a_0000.json") == ["a"] + assert not (tmp / "a_0001.json").is_file() + assert _lines(tmp / "a_*.json") == ["a"] + + with jsonql.open_write(tmp / "b_??.json", max_size="1k") as o: + print("0" * 2000, file=o) + print("1" * 2000, file=o) + assert _lines(tmp / "b_00.json") == ["0" * 2000] + assert _lines(tmp / "b_01.json") == ["1" * 2000] + assert _lines(tmp / "b_*.json") == ["0" * 2000, "1" * 2000] + + +def test_split_file(tmp_path: Path): + file = tmp_path / "test.txt" + content = "Hello\nWorld\n" + + with open(file, "w") as o: + o.write(content) + + with jsonql.SplitFile(file, chunk=0, n_chunks=2) as f: + assert f.readlines() == ["Hello\n"] + + with jsonql.SplitFile(file, chunk=1, n_chunks=2) as f: + assert f.readlines() == ["World\n"] + + +def test_split_file_middle_of_line(tmp_path: Path): + file = tmp_path / "test.txt" + content = "Hello _|_\nWorld\n" + # split is here ^ + + with open(file, "w") as o: + o.write(content) + + with jsonql.SplitFile(file, chunk=0, n_chunks=2) as f: + assert f.readlines() == ["Hello _|_\n"] + + with jsonql.SplitFile(file, chunk=1, n_chunks=2) as f: + assert f.readlines() == ["World\n"] + + +def test_split_file_middle_of_char(tmp_path: Path): + file = tmp_path / "test.txt" + content = "Hello\U0001F40D\nWorld\n" + # split is here ^^ + + with open(file, "w") as o: + o.write(content) + + with jsonql.SplitFile(file, chunk=0, n_chunks=2) as f: + assert f.readlines() == ["Hello🐍\n"] + + with jsonql.SplitFile(file, chunk=1, n_chunks=2) as f: + assert f.readlines() == ["World\n"] + + +def test_blocked_gzip(tmp_path: Path): + file = tmp_path / "test.gz" + f = str(file) + # Each object is 10/11 bytes long. We have 2 of them by block. + content = ['{"xx": %d}' % i for i in range(80)] + with jsonql.BlockedGzipWriter(file, "wt", block_size="20B") as o: + for line in content: + print(line, file=o) + + jr = jsonql.JsonReader(strict=True) + expected = list(jr.map(content)) + # read as one file + assert expected == list(jsonql.read_jsons(file)) + # read first block + assert expected[:2] == list(jsonql.read_jsons(f + "[0/40]")) + # read last block + assert expected[-2:] == list(jsonql.read_jsons(f + "[39/40]")) + + readers = jsonql.get_block_readers(file, 9) + read_as_several_files = [list(jsonql.read_jsons(r)) for r in readers] + # 40 splits of 2 docs, 9 readers -> 5 splits, 10 docs per reader + assert list(jsonql.grouper(expected, 10)) == read_as_several_files + + +def test_enter_exit(capsys): + class MyTransformer(jsonql.Transformer): + def __enter__(self): + print("trans: started") + self.ready = True + return self + + def __exit__(self, *args): + print("trans: done") + + def do(self, x): + return (x, x) + + def acc(values): + print("acc: started") + res = 0 + for (x, _) in values: + res += int(x) + print("acc: done") + yield f"acc: result={res}" + + t = MyTransformer() + data = (str(x) for x in range(10)) + print("pipeline: started") + # Print to stdout. + jsonql.run_pipes(t, acc, file=data) + print("pipeline: done") + out = capsys.readouterr().out + assert ( + "\n".join( + [ + "pipeline: started", + "trans: started", + "acc: started", + "acc: done", + f"acc: result=45", + # Transformers are closed at the very end. + "trans: done", + "pipeline: done\n", + ] + ) + == out + ) + + +def test_write_to_stdout(capsys): + lines = [str(x) for x in range(10)] + jsonql.run_pipes(file=iter(lines)) + out = capsys.readouterr().out + assert out == "\n".join(lines) + "\n" + + +def test_write_to_stdout_handle_newlines(capsys): + lines = [str(x) + "\n" for x in range(10)] + jsonql.run_pipes(file=iter(lines)) + out = capsys.readouterr().out + assert out == "".join(lines) + + +def test_multiprocess(capsys): + mult = jsonql.Mapper(lambda x: f"2x = {2 * int(x)}") + jsonql.run_pipes(mult, processes=2, file=(str(x) for x in range(10))) + out = set(capsys.readouterr().out.strip("\n").split("\n")) + assert {f"2x = {2 * x}" for x in range(10)} == out diff --git a/data_tooling/kenlm_training/tests/test_minify.py b/data_tooling/kenlm_training/tests/test_minify.py new file mode 100644 index 0000000..aa135a9 --- /dev/null +++ b/data_tooling/kenlm_training/tests/test_minify.py @@ -0,0 +1,153 @@ +# Copyright (c) Facebook, Inc. and its affiliates. +# +# This source code is licensed under the MIT license found in the +# LICENSE file in the root directory of this source tree. +# + +import json +from pathlib import Path + +import pytest + +import cc_net +import cc_net.minify as minify +from cc_net import jsonql, process_wet_file +from cc_net.minify import ( + HASH_SIZE, + decode_hashes, + encode_hashes, + encode_line_ids, + get_hashes, +) + + +def test_encode_decode(): + sentences = ["Hello world !", "Is everyone happy in here ?"] + hashes = get_hashes(sentences) + assert all([len(h) == HASH_SIZE for h in hashes]) + hashes_int = [minify._b2i(h) for h in hashes] + encoded = encode_hashes(hashes) + decoded = decode_hashes(encoded) + assert all([len(d) == HASH_SIZE for d in decoded]) + + decoded_int = [minify._b2i(d) for d in decoded] + + assert hashes_int == decoded_int + assert hashes == decoded + + +def test_minify(): + doc = { + "raw_content": "Hello world !\nIs everyone happy in here ?", + "language": "en", + "perplexity": 120.0, + "line_ids": [0, 4], + } + expected = {"line_ids": "AAAEAA==", "language": "en", "perplexity": 120.0} + minifier = minify.Minifier() + assert expected == minifier(doc) + + +@pytest.fixture +def http_from_disk(monkeypatch): + def read_sample_file(url: str, n_retry: int = 3) -> bytes: + expected_url = process_wet_file.WET_URL_ROOT + "/crawl-data/sample.warc.wet" + assert expected_url == url + file = Path(__file__).parent / "data" / "sample.warc.txt" + return file.read_bytes() + + monkeypatch.setattr(cc_net.jsonql, "request_get_content", read_sample_file) + + +def test_minify_and_fetch(http_from_disk, tmp_path: Path): + full_quotes = """Don't part with your illusions. When they are gone you may still exist, but you have ceased to live. +Education: that which reveals to the wise, and conceals from the stupid, the vast limits of their knowledge. +Facts are stubborn things, but statistics are more pliable. +Fiction is obliged to stick to possibilities. Truth isn't.""" + # We don't need no education. + chosen_quotes = "\n".join( + l for l in full_quotes.splitlines() if "Education" not in l + ) + + cc_doc = { + "url": "http://sample_english.com", + "date_download": "2019-03-18T00:00:00Z", + "digest": "sha1:XQZHW7QWIG54HVAV3KPRW6MK5ILDNCER", + "source_domain": "sample_english.com", + "title": "Famous Mark Twain Quotes", + "raw_content": full_quotes, + "cc_segment": "crawl-data/sample.warc.wet", + "nlines": 4, + "length": 353, + } + + ccnet_metadata = { + "language": "en", + "language_score": 0.99, + "perplexity": 151.5, + "bucket": "head", + "raw_content": chosen_quotes, + "nlines": 3, + "length": len(chosen_quotes), + "original_nlines": 4, + "original_length": 353, + "line_ids": [0, 2, 3], + } + ccnet_doc = dict(cc_doc, **ccnet_metadata) + mini = minify.Minifier()(ccnet_doc.copy()) + assert mini is not ccnet_doc + + important_fields = [ + "url", + "digest", + "cc_segment", + "language", + "language_score", + "perplexity", + "bucket", + "line_ids", + ] + expected = {k: ccnet_doc[k] for k in important_fields} + expected["line_ids"] = encode_line_ids(expected["line_ids"]) # type: ignore + assert expected == mini + + with jsonql.open_write(tmp_path / "sample.json") as o: + print(json.dumps(mini), file=o) + fetcher = minify.MetadataFetcher(tmp_path) + # line_ids is removed when unminifying + ccnet_doc.pop("line_ids") + assert ccnet_doc == fetcher(cc_doc) + + +def test_fetch(http_from_disk, tmp_path: Path): + mini_docs = [ + { + "url": "http://sample_chinese.com", + "digest": "sha1:Y4E6URVYGIAFNVRTPZ5S3J64RTZTP6HJ", + "cc_segment": "crawl-data/sample.warc.wet", + "line_ids": encode_line_ids([2]), + "bucket": "not_that_great", + }, + { + "url": "http://sample_english.com", + "digest": "sha1:XQZHW7QWIG54HVAV3KPRW6MK5ILDNCER", + "cc_segment": "crawl-data/sample.warc.wet", + "line_ids": encode_line_ids([3]), + "bucket": "top_notch", + }, + ] + with jsonql.open_write(tmp_path / "sample.json") as o: + for mini in mini_docs: + print(json.dumps(mini), file=o) + + fetcher = minify.MetadataFetcher(tmp_path) + cc = process_wet_file.CCSegmentsReader(["crawl-data/sample.warc.wet"]) + docs = [d for d in fetcher.map(cc) if d is not None] + assert cc.retrieved_segments == 1 + + # Note: documents are retrieved as they are ordered in the .warc.wet file + assert [ + "Facts are stubborn things, but statistics are more pliable.", + "事實是固執的東西，但統計數字卻比較柔和。", + ] == [d["raw_content"] for d in docs] + assert ["top_notch", "not_that_great"] == [d["bucket"] for d in docs] diff --git a/data_tooling/kenlm_training/tests/test_normalizer.py b/data_tooling/kenlm_training/tests/test_normalizer.py new file mode 100644 index 0000000..c2168e3 --- /dev/null +++ b/data_tooling/kenlm_training/tests/test_normalizer.py @@ -0,0 +1,29 @@ +# Copyright (c) Facebook, Inc. and its affiliates. +# +# This source code is licensed under the MIT license found in the +# LICENSE file in the root directory of this source tree. +# + +import cc_net.text_normalizer as txt + + +def test_unicode_punct(): + weird = "，。、„”“«»１」「《》´∶：？！（）；–—．～’…━〈〉【】％" + replaced = ',.,""""""""""\'::?!();- - . ~\'...-<>[]%' + assert txt.replace_unicode_punct(weird) == replaced + + assert txt.remove_unicode_punct(weird) == "" + + +def test_numbers(): + weird = "０２３４５６７８９ | 0123456789" + normalized = "000000000 | 0000000000" + assert txt.normalize(weird, numbers=True) == normalized + assert txt.normalize(weird, numbers=False) == weird + + +def test_normalize_for_dedup(): + weird = "０２３´∶：\x10 | ;012 hèllo" + normalized = "000 | ;000 hèllo" + assert normalized == txt.slow_normalize_for_dedup(weird) + assert normalized == txt.normalize_for_dedup(weird) diff --git a/data_tooling/kenlm_training/tests/test_parse_wet_file.py b/data_tooling/kenlm_training/tests/test_parse_wet_file.py new file mode 100644 index 0000000..9acc6b5 --- /dev/null +++ b/data_tooling/kenlm_training/tests/test_parse_wet_file.py @@ -0,0 +1,47 @@ +# Copyright (c) Facebook, Inc. and its affiliates. +# +# This source code is licensed under the MIT license found in the +# LICENSE file in the root directory of this source tree. +# + +from pathlib import Path + +from cc_net import process_wet_file + + +def test_parsing(): + sample = Path(__file__).parent / "data" / "sample.warc.txt" + with open(sample) as f: + documents = list(process_wet_file.parse_warc_file(f)) + + expected_urls = [ + "http://sample_english.com", + "http://sample_chinese.zh", + "http://sample_russian.ru", + ] + assert expected_urls == [d["url"] for d in documents] + expected_domains = ["sample_english.com", "sample_chinese.zh", "sample_russian.ru"] + assert expected_domains == [d["source_domain"] for d in documents] + + expected_date = [ + "2019-03-18T00:00:00Z", + "2019-03-18T00:00:01Z", + "2019-03-18T00:00:02Z", + ] + assert expected_date == [d["date_download"] for d in documents] + + expected_title = [ + "Famous Mark Twain Quotes", + "馬克·吐溫名言", + "Цитаты знаменитого Марка Твена", + ] + assert expected_title == [d["title"] for d in documents] + + expected_quotes = """Don't part with your illusions. When they are gone you may still exist, but you have ceased to live. +Education: that which reveals to the wise, and conceals from the stupid, the vast limits of their knowledge. + +Facts are stubborn things, but statistics are more pliable. +Fiction is obliged to stick to possibilities. Truth isn't. +""" + + assert expected_quotes == documents[0]["raw_content"] diff --git a/data_tooling/kenlm_training/tests/test_regroup.py b/data_tooling/kenlm_training/tests/test_regroup.py new file mode 100644 index 0000000..fa722b7 --- /dev/null +++ b/data_tooling/kenlm_training/tests/test_regroup.py @@ -0,0 +1,50 @@ +# Copyright (c) Facebook, Inc. and its affiliates. +# +# This source code is licensed under the MIT license found in the +# LICENSE file in the root directory of this source tree. +# + +import time + +from cc_net import jsonql, regroup + + +def check_regroup(tmp_path, regroup_fn, check_blocks_boundaries=False): + n_shards = 4 + n_docs = 20 + shards = [ + [dict(id=i, shard=s, raw_content="hello world") for i in range(n_docs)] + for s in range(n_shards) + ] + shards_files = [tmp_path / f"{s:04d}.json.gz" for s in range(n_shards)] + for shard, shard_file in zip(shards, shards_files): + jsonql.run_pipes(inputs=shard, output=shard_file) + regroup_file = tmp_path / "regroup.json.gz" + start = time.time() + regroup_fn(shards_files, regroup_file) + duration = time.time() - start + print(f"{regroup_fn.__module__}.{regroup_fn.__name__} took {duration}s") + + regrouped = list(jsonql.read_jsons(regroup_file)) + assert [doc for shard in shards for doc in shard] == regrouped + + readers = jsonql.get_block_readers(regroup_file, n_shards) + if not check_blocks_boundaries: + assert [doc for shard in shards for doc in shard] == [ + doc for reader in readers for doc in jsonql.read_jsons(reader) + ] + return + + for shard, reader in zip(shards, readers): + block = [doc for doc in jsonql.read_jsons(reader)] + assert shard == block + + +def test_regroup(tmp_path): + # With regroup boundaries will be every 256Mb. + check_regroup(tmp_path, regroup.reshard, check_blocks_boundaries=False) + + +def test_fast_regroup(tmp_path): + # With fast regroup boundaries should match the shards. + check_regroup(tmp_path, regroup.fast_reshard, check_blocks_boundaries=True) diff --git a/data_tooling/kenlm_training/tests/test_transformer.py b/data_tooling/kenlm_training/tests/test_transformer.py new file mode 100644 index 0000000..7acf1a0 --- /dev/null +++ b/data_tooling/kenlm_training/tests/test_transformer.py @@ -0,0 +1,86 @@ +# Copyright (c) Facebook, Inc. and its affiliates. +# +# This source code is licensed under the MIT license found in the +# LICENSE file in the root directory of this source tree. +# + +import inspect +import pickle +from pathlib import Path + +import pytest + +from cc_net import dedup, jsonql, perplexity, split_by_lang, tokenizer + + +def get_transformers(module): + return [ + v + for v in vars(module).values() + if type(v) is type + and issubclass(v, jsonql.Transformer) + and v != jsonql.Transformer + ] + + +ALL_TRANSFORMERS = ( + get_transformers(jsonql) + + get_transformers(dedup) + + get_transformers(perplexity) + + get_transformers(tokenizer) + + get_transformers(split_by_lang) +) + + +def check_transformer_is_calling_super_init(cls: type): + assert issubclass(cls, jsonql.Transformer) + # accessing __init__ is generally an error, but here we do want to inspect + # the __init__method. + code = inspect.getsource(cls.__init__) # type: ignore + code = code.replace(" ", "") + + # Check that super().__init__ is called. + assert "super().__init__()" in code + + +def test_bad_transformers_are_caught(): + class BadTransformer(jsonql.Transformer): + def __init__(self, arg): + # We aren't calling super /!\ + self.arg = arg + + with pytest.raises(AssertionError): + check_transformer_is_calling_super_init(BadTransformer) + + +@pytest.mark.parametrize("transformer", ALL_TRANSFORMERS) +def test_transformer_is_correctly_implemented(transformer): + check_transformer_is_calling_super_init(transformer) + + +@pytest.mark.skipif( + not Path("bin/lid.bin").exists(), reason="bin/lid.bin not found, run `make install`" +) +def test_can_pickle_transformer(tmp_path): + model = Path("bin/lid.bin") + if not model.exists(): + return + classifier = split_by_lang.Classifier(model, "text", "lang") + classifier.__enter__() + doc = dict(text="Hello world ! This is English btw.") + original_results = classifier(doc) + + with open(tmp_path / "transformer.pkl", "wb") as o: + pickle.dump(classifier, o) + with open(tmp_path / "transformer.pkl", "rb") as f: + classifier = pickle.load(f) + + assert original_results == classifier(doc) + + # Do it again with the unpickled object. + with open(tmp_path / "transformer.pkl", "wb") as o: + pickle.dump(classifier, o) + with open(tmp_path / "transformer.pkl", "rb") as f: + classifier = pickle.load(f) + + assert original_results == classifier(doc) diff --git a/data_tooling/kenlm_training/train_all.sh b/data_tooling/kenlm_training/train_all.sh new file mode 100644 index 0000000..6988a01 --- /dev/null +++ b/data_tooling/kenlm_training/train_all.sh @@ -0,0 +1,133 @@ +#!/bin/bash +set -e + +# Languages to train on +LANGUAGES_WIKIPEDIA=( "es" "af" "ar" "arz" "as" "bn" "fr" "sw" "eu" "ca" "zh" "en" "hi" "ur" "id" "pt" "vi" "gu" "kn" "ml" "mr" "ta" "te" "yo" ) +LANGUAGES_OSCAR=( "es" "af" "ar" "arz" "as" "bn" "fr" "sw" "eu" "ca" "zh" "en" "hi" "ur" "id" "pt" "vi" "gu" "kn" "ml" "mr" "te" ) + +NDOC_FOR_LM=1_000_000 +VOCAB_SIZE=65536 +SMALL_VOCAB_SIZE=40000 + +# Normalization parameters +REMOVE_ACCENTS=False +LOWER_CASE=False +NORMALIZE_NUMBERS=True +NORMALIZE_PUNCT=1 + +# OSCAR +NDOC_FOR_LM_OSCAR=1_000_000 + + +train_language_and_dataset () { + local lang=$1 + local dataset=$2 + if [ "$dataset" = "wikipedia" ]; then + # 1 Download Wikipedia cirrus + if [ -f "data/${dataset}/cirrus/gz/${lang}.json.gz" ]; then + echo "${lang} Wikipedia cirrus was already downloaded." + else + echo "Downloading ${lang}" + mkdir -p "data/${dataset}/cirrus/gz/" + python cc_net/get_wiki_cirrus.py dl --lang "${lang}" --output_dir "data/${dataset}/cirrus/gz" --date 20211115 + echo "Downloaded Wikipedia cirrus for ${lang}" + fi + + # 2 Extract opening text of each article + if [ -f "data/${dataset}/cirrus/gz/${lang}.opening.txt" ]; then + echo "Wikipedia openings were already extracted for ${lang}" + else + echo "Extracting ${lang}" + python cc_net/get_wiki_cirrus.py opening \ + --n_docs ${NDOC_FOR_LM} \ + --file "data/${dataset}/cirrus/gz/${lang}.json.gz" \ + --output "data/${dataset}/cirrus/gz/${lang}.opening.txt" \ + --accent ${REMOVE_ACCENTS} \ + --case ${LOWER_CASE} \ + --numbers ${NORMALIZE_NUMBERS} \ + --punct ${NORMALIZE_PUNCT} + fi + else + # 1 & 2 Download and preprocess dataset from HF hub + if [ -f "data/${dataset}/cirrus/gz/${lang}.opening.txt" ]; then + echo "Wikipedia openings were already extracted for ${lang}" + else + echo "Downloading OSCAR ${lang}" + mkdir -p "data/${dataset}/cirrus/gz/" + python cc_net/get_hf_dataset.py dl \ + --dataset "${dataset}" \ + --output_file "data/${dataset}/cirrus/gz/${lang}.opening.txt" \ + --name "unshuffled_deduplicated_${lang}" \ + --split "train" \ + --max_docs $NDOC_FOR_LM_OSCAR + fi + fi + + # 3 Train sentence piece tokenizer + if [ -f "data/${dataset}/lm_sp/${lang}.sp.model" ]; then + echo "Sentence piece tokenizer was already trained for ${lang}" + else + echo "Training sentence piece tokenizer for ${lang}" + mkdir -p "data/${dataset}/lm_sp" + ./bin/spm_train --input="data/${dataset}/cirrus/gz/${lang}.opening.txt" \ + --vocab_size=${VOCAB_SIZE} --hard_vocab_limit \ + --character_coverage=0.9995 \ + --model_type=unigram \ + --model_prefix="data/${dataset}/lm_sp/${lang}.sp" \ + || echo "WARNING: Corpus is too small, will train smaller model" && \ + ./bin/spm_train --input="data/${dataset}/cirrus/gz/${lang}.opening.txt" \ + --vocab_size=${SMALL_VOCAB_SIZE} \ + --character_coverage=0.9995 \ + --model_type=unigram \ + --model_prefix="data/${dataset}/lm_sp/${lang}.sp" + + echo "Trained SentencePiece model with $(wc -l data/"${dataset}"/lm_sp/"${lang}".sp.vocab) pieces" + fi + + # 4 Tokenize openings dataset + if [ -f "data/${dataset}/cirrus/sp/${lang}.opening.txt" ]; then + echo "Openings dataset already tokenized for ${lang}" + else + mkdir -p "data/${dataset}/cirrus/sp" + echo "Tokenizing openings dataset for ${lang}" + ./bin/spm_encode \ + --model="data/${dataset}/lm_sp/${lang}.sp.model" \ + --output_format=piece \ + "data/${dataset}/cirrus/gz/${lang}.opening.txt" > "data/${dataset}/cirrus/sp/${lang}.opening.txt" + echo "Tokenized openings dataset for ${lang}" + fi + + # 5 Train KenLM model on tokenized dataset + if [ -f "data/${dataset}/lm_sp/${lang}.arpa" ] || [ -f "data/${dataset}/lm_sp/${lang}.arpa.bin" ]; then + echo "KenLM model already trained for ${lang}" + else + echo "Training KenLM model for ${lang}" + mkdir -p tmp + ./bin/lmplz -o 5 -S 8G -T tmp --vocab_estimate ${VOCAB_SIZE} --discount_fallback \ + < "data/${dataset}/cirrus/sp/${lang}.opening.txt" > "data/${dataset}/lm_sp/${lang}.arpa" + echo "Trained KenLM model for ${lang}" + fi + + # 6 Convert KenLM model to binary + if [ -f "data/${dataset}/lm_sp/${lang}.arpa.bin" ]; then + echo "KenLM model already converted to binary for ${lang}" + else + echo "Converting KenLM model to binary for ${lang}" + ./bin/build_binary "data/${dataset}/lm_sp/${lang}.arpa" "data/${dataset}/lm_sp/${lang}.arpa.bin" + echo "Converted KenLM model to binary for ${lang}" + rm "data/${dataset}/lm_sp/${lang}.arpa" + fi + +} + + + +for lang in "${LANGUAGES_WIKIPEDIA[@]}" +do + train_language_and_dataset "$lang" wikipedia +done + +for lang in "${LANGUAGES_OSCAR[@]}" +do + train_language_and_dataset "$lang" oscar +done diff --git a/data_tooling/perplexity_lenses/README.md b/data_tooling/perplexity_lenses/README.md new file mode 100644 index 0000000..851a972 --- /dev/null +++ b/data_tooling/perplexity_lenses/README.md @@ -0,0 +1,50 @@ +--- +title: Perplexity Lenses +emoji: 🌸 +colorFrom: pink +colorTo: blue +sdk: streamlit +app_file: app.py +pinned: false +--- + +# Installation: +Requires Python >= 3.7 and < 3.10 +``` +pip install . +``` +Or with [poetry](https://python-poetry.org/) +``` +poetry install +``` + +# Web App: +The app is hosted [here](https://huggingface.co/spaces/edugp/perplexity-lenses). To run it locally: +``` +python -m streamlit run app.py +``` + +# CLI: +The CLI with no arguments defaults to running mc4 in Spanish. +For full usage: +``` +python cli.py --help +``` +Example: Running on 1000 sentences extracted from Spanish OSCAR docs specifying all arguments: +``` +python cli.py \ + --dataset oscar \ + --dataset-config unshuffled_deduplicated_es \ + --dataset-split train \ + --text-column text \ + --language es \ + --doc-type sentence \ + --sample 1000 \ + --dimensionality-reduction umap \ + --model-name distiluse-base-multilingual-cased-v1 \ + --output-file perplexity.html +``` +# Tests: +``` +python -m unittest discover -s ./tests/ -p "test_*.py" +``` diff --git a/data_tooling/perplexity_lenses/app.py b/data_tooling/perplexity_lenses/app.py new file mode 100644 index 0000000..16c3b72 --- /dev/null +++ b/data_tooling/perplexity_lenses/app.py @@ -0,0 +1,147 @@ +import logging +from functools import partial + +import streamlit as st +from embedding_lenses.data import uploaded_file_to_dataframe +from embedding_lenses.dimensionality_reduction import ( + get_tsne_embeddings, + get_umap_embeddings, +) +from embedding_lenses.embedding import load_model + +from perplexity_lenses import REGISTRY_DATASET +from perplexity_lenses.data import ( + documents_df_to_sentences_df, + hub_dataset_to_dataframe, +) +from perplexity_lenses.engine import ( + DIMENSIONALITY_REDUCTION_ALGORITHMS, + DOCUMENT_TYPES, + EMBEDDING_MODELS, + LANGUAGES, + PERPLEXITY_MODELS, + SEED, + generate_plot, +) +from perplexity_lenses.perplexity import KenlmModel +from perplexity_lenses.visualization import draw_histogram + +logging.basicConfig(level=logging.INFO) +logger = logging.getLogger(__name__) + + +st.title("Perplexity Lenses") +st.write("Visualize text embeddings in 2D using colors to represent perplexity values.") +uploaded_file = st.file_uploader("Choose an csv/tsv file...", type=["csv", "tsv"]) +st.write( + "Alternatively, select a dataset from the [hub](https://huggingface.co/datasets)" +) +col1, col2, col3 = st.columns(3) +with col1: + hub_dataset = st.text_input("Dataset name", "mc4") +with col2: + hub_dataset_config = st.text_input("Dataset configuration", "es") +with col3: + hub_dataset_split = st.text_input("Dataset split", "train") + +col4, col5 = st.columns(2) +with col4: + text_column = st.text_input("Text field name", "text") +with col5: + language = st.selectbox("Language", LANGUAGES, 12) + +col6, col7 = st.columns(2) +with col6: + doc_type = st.selectbox("Document type", DOCUMENT_TYPES, 1) +with col7: + sample = st.number_input("Maximum number of documents to use", 1, 100000, 1000) +perplexity_model = st.selectbox( + "Dataset on which the perplexity model was trained on", PERPLEXITY_MODELS, 0 +).lower() + +dimensionality_reduction = st.selectbox( + "Dimensionality Reduction algorithm", DIMENSIONALITY_REDUCTION_ALGORITHMS, 0 +) +model_name = st.selectbox("Sentence embedding model", EMBEDDING_MODELS, 0) + +advanced_options = st.checkbox( + "Advanced options (do not modify if using default KenLM models).", value=False +) +lower_case = True +remove_accents = True +normalize_numbers = True +punctuation = 1 +if advanced_options: + lower_case = st.checkbox( + "Lower case text for KenLM preprocessing (from cc_net)", value=False + ) + remove_accents = st.checkbox( + "Remove accents for KenLM preprocessing (from cc_net)", value=False + ) + normalize_numbers = st.checkbox( + "Replace numbers with zeros KenLM preprocessing (from cc_net)", value=True + ) + punctuation = st.number_input( + "Punctuation mode to use from cc_net KenLM preprocessing", 1, 2, 1 + ) + +with st.spinner(text="Loading embedding model..."): + model = load_model(model_name) +dimensionality_reduction_function = ( + partial(get_umap_embeddings, random_state=SEED) + if dimensionality_reduction == "UMAP" + else partial(get_tsne_embeddings, random_state=SEED) +) + +with st.spinner(text="Loading KenLM model..."): + kenlm_model = KenlmModel.from_pretrained( + perplexity_model, + language, + lower_case, + remove_accents, + normalize_numbers, + punctuation, + ) + +if uploaded_file or hub_dataset: + with st.spinner("Loading dataset..."): + if uploaded_file: + df = uploaded_file_to_dataframe(uploaded_file) + if doc_type == "Sentence": + df = documents_df_to_sentences_df(df, text_column, sample, seed=SEED) + df["perplexity"] = df[text_column].map(kenlm_model.get_perplexity) + else: + df = hub_dataset_to_dataframe( + hub_dataset, + hub_dataset_config, + hub_dataset_split, + sample, + text_column, + kenlm_model, + seed=SEED, + doc_type=doc_type, + ) + + # Round perplexity + df["perplexity"] = df["perplexity"].round().astype(int) + logger.info( + f"Perplexity range: {df['perplexity'].min()} - {df['perplexity'].max()}" + ) + plot, plot_registry = generate_plot( + df, + text_column, + "perplexity", + None, + dimensionality_reduction_function, + model, + seed=SEED, + context_logger=st.spinner, + hub_dataset=hub_dataset, + ) + logger.info("Displaying plots") + st.bokeh_chart(plot) + if hub_dataset == REGISTRY_DATASET: + st.bokeh_chart(plot_registry) + fig = draw_histogram(df["perplexity"].values) + st.pyplot(fig) + logger.info("Done") diff --git a/data_tooling/perplexity_lenses/cli.py b/data_tooling/perplexity_lenses/cli.py new file mode 100644 index 0000000..a889d0e --- /dev/null +++ b/data_tooling/perplexity_lenses/cli.py @@ -0,0 +1,139 @@ +import logging +from functools import partial +from typing import Optional + +import pandas as pd +import typer +from bokeh.plotting import output_file as bokeh_output_file +from bokeh.plotting import save +from embedding_lenses.dimensionality_reduction import ( + get_tsne_embeddings, + get_umap_embeddings, +) +from embedding_lenses.embedding import load_model + +from perplexity_lenses import REGISTRY_DATASET +from perplexity_lenses.data import ( + documents_df_to_sentences_df, + hub_dataset_to_dataframe, +) +from perplexity_lenses.engine import ( + DIMENSIONALITY_REDUCTION_ALGORITHMS, + DOCUMENT_TYPES, + EMBEDDING_MODELS, + LANGUAGES, + PERPLEXITY_MODELS, + SEED, + generate_plot, +) +from perplexity_lenses.perplexity import KenlmModel +from perplexity_lenses.visualization import draw_histogram + +logging.basicConfig(level=logging.INFO) +logger = logging.getLogger(__name__) + + +app = typer.Typer() + + +@app.command() +def main( + dataset: str = typer.Option( + "mc4", help="The name of the hub dataset or local csv/tsv file." + ), + dataset_config: Optional[str] = typer.Option( + "es", + help="The configuration of the hub dataset, if any. Does not apply to local csv/tsv files.", + ), + dataset_split: Optional[str] = typer.Option( + "train", help="The dataset split. Does not apply to local csv/tsv files." + ), + text_column: str = typer.Option("text", help="The text field name."), + language: str = typer.Option( + "es", help=f"The language of the text. Options: {LANGUAGES}" + ), + doc_type: str = typer.Option( + "sentence", + help=f"Whether to embed at the sentence or document level. Options: {DOCUMENT_TYPES}.", + ), + sample: int = typer.Option(1000, help="Maximum number of examples to use."), + perplexity_model: str = typer.Option( + "wikipedia", + help=f"Dataset on which the perplexity model was trained on. Options: {PERPLEXITY_MODELS}", + ), + dimensionality_reduction: str = typer.Option( + DIMENSIONALITY_REDUCTION_ALGORITHMS[0], + help=f"Whether to use UMAP or t-SNE for dimensionality reduction. Options: {DIMENSIONALITY_REDUCTION_ALGORITHMS}.", + ), + model_name: str = typer.Option( + EMBEDDING_MODELS[0], + help=f"The sentence embedding model to use. Options: {EMBEDDING_MODELS}", + ), + output_file: str = typer.Option( + "perplexity", help="The name of the output visualization files." + ), +): + """ + Perplexity Lenses: Visualize text embeddings in 2D using colors to represent perplexity values. + """ + logger.info("Loading embedding model...") + model = load_model(model_name) + dimensionality_reduction_function = ( + partial(get_umap_embeddings, random_state=SEED) + if dimensionality_reduction.lower() == "umap" + else partial(get_tsne_embeddings, random_state=SEED) + ) + logger.info("Loading KenLM model...") + kenlm_model = KenlmModel.from_pretrained( + perplexity_model.lower(), + language, + lower_case=True, + remove_accents=True, + normalize_numbers=True, + punctuation=1, + ) + logger.info("Loading dataset...") + if dataset.endswith(".csv") or dataset.endswith(".tsv"): + df = pd.read_csv(dataset, sep="\t" if dataset.endswith(".tsv") else ",") + if doc_type.lower() == "sentence": + df = documents_df_to_sentences_df(df, text_column, sample, seed=SEED) + df["perplexity"] = df[text_column].map(kenlm_model.get_perplexity) + else: + df = hub_dataset_to_dataframe( + dataset, + dataset_config, + dataset_split, + sample, + text_column, + kenlm_model, + seed=SEED, + doc_type=doc_type, + ) + # Round perplexity + df["perplexity"] = df["perplexity"].round().astype(int) + logger.info( + f"Perplexity range: {df['perplexity'].min()} - {df['perplexity'].max()}" + ) + plot, plot_registry = generate_plot( + df, + text_column, + "perplexity", + None, + dimensionality_reduction_function, + model, + seed=SEED, + hub_dataset=dataset, + ) + logger.info("Saving plots") + bokeh_output_file(f"{output_file}.html") + save(plot) + if dataset == REGISTRY_DATASET: + bokeh_output_file(f"{output_file}_registry.html") + save(plot_registry) + fig = draw_histogram(df["perplexity"].values) + fig.savefig(f"{output_file}_histogram.png") + logger.info("Done") + + +if __name__ == "__main__": + app() diff --git a/data_tooling/perplexity_lenses/perplexity_lenses/__init__.py b/data_tooling/perplexity_lenses/perplexity_lenses/__init__.py new file mode 100644 index 0000000..0920bd1 --- /dev/null +++ b/data_tooling/perplexity_lenses/perplexity_lenses/__init__.py @@ -0,0 +1,2 @@ +__version__ = "0.1.0" +REGISTRY_DATASET = "mhtoin/register_oscar" diff --git a/data_tooling/perplexity_lenses/perplexity_lenses/data.py b/data_tooling/perplexity_lenses/perplexity_lenses/data.py new file mode 100644 index 0000000..778749d --- /dev/null +++ b/data_tooling/perplexity_lenses/perplexity_lenses/data.py @@ -0,0 +1,81 @@ +from functools import partial + +import numpy as np +import pandas as pd +from datasets import load_dataset +from tqdm import tqdm + +from perplexity_lenses import REGISTRY_DATASET +from perplexity_lenses.perplexity import KenlmModel + + +def hub_dataset_to_dataframe( + path: str, + name: str, + split: str, + sample: int, + text_column: str, + model: KenlmModel, + seed: int = 0, + doc_type: str = "Whole document", +) -> pd.DataFrame: + load_dataset_fn = partial(load_dataset, path=path) + if name: + load_dataset_fn = partial(load_dataset_fn, name=name) + # Special case for the registry dataset + if path == REGISTRY_DATASET: + load_dataset_fn = partial(load_dataset_fn, data_files=f"{name}/*") + if split: + load_dataset_fn = partial(load_dataset_fn, split=split) + dataset = load_dataset_fn(streaming=True).shuffle(buffer_size=10000, seed=seed) + if doc_type.lower() == "sentence": + dataset = dataset.map( + lambda x: [ + { + text_column: sentence, + "perplexity": model.get_perplexity(sentence), + "label": x.get("labels", [])[0] + if len(x.get("labels", [])) > 0 + else "NONE", # Special case for registry dataset + } + for sentence in x[text_column].split("\n") + ] + ) + else: + dataset = dataset.map( + lambda x: { + text_column: x[text_column], + "perplexity": model.get_perplexity(x[text_column]), + "label": x.get("labels", [])[0] + if len(x.get("labels", [])) > 0 + else "NONE", # Special case for registry dataset + } + ) + instances = [] + count = 0 + for instance in tqdm(dataset, total=sample): + if isinstance(instance, list): + for sentence in instance: + instances.append(sentence) + count += 1 + if count == sample: + break + else: + instances.append(instance) + count += 1 + if count == sample: + break + return pd.DataFrame(instances) + + +def documents_df_to_sentences_df( + df: pd.DataFrame, text_column: str, sample: int, seed: int = 0 +): + df_sentences = pd.DataFrame( + { + text_column: np.array( + df[text_column].map(lambda x: x.split("\n")).values.tolist() + ).flatten() + } + ) + return df_sentences.sample(min(sample, df_sentences.shape[0]), random_state=seed) diff --git a/data_tooling/perplexity_lenses/perplexity_lenses/engine.py b/data_tooling/perplexity_lenses/perplexity_lenses/engine.py new file mode 100644 index 0000000..9e063cd --- /dev/null +++ b/data_tooling/perplexity_lenses/perplexity_lenses/engine.py @@ -0,0 +1,147 @@ +import logging +import time +from typing import Callable, Optional, Tuple, Union + +import numpy as np +import pandas as pd +import streamlit as st +from bokeh.palettes import Turbo256 +from bokeh.plotting import Figure +from embedding_lenses.embedding import embed_text +from embedding_lenses.utils import encode_labels +from embedding_lenses.visualization import draw_interactive_scatter_plot +from sentence_transformers import SentenceTransformer + +from perplexity_lenses import REGISTRY_DATASET + +logger = logging.getLogger(__name__) +EMBEDDING_MODELS = [ + "distiluse-base-multilingual-cased-v1", + "distiluse-base-multilingual-cased-v2", + "all-mpnet-base-v2", + "flax-sentence-embeddings/all_datasets_v3_mpnet-base", +] +DIMENSIONALITY_REDUCTION_ALGORITHMS = ["UMAP", "t-SNE"] +DOCUMENT_TYPES = ["Whole document", "Sentence"] +SEED = 0 +LANGUAGES = [ + "af", + "ar", + "az", + "be", + "bg", + "bn", + "ca", + "cs", + "da", + "de", + "el", + "en", + "es", + "et", + "fa", + "fi", + "fr", + "gu", + "he", + "hi", + "hr", + "hu", + "hy", + "id", + "is", + "it", + "ja", + "ka", + "kk", + "km", + "kn", + "ko", + "lt", + "lv", + "mk", + "ml", + "mn", + "mr", + "my", + "ne", + "nl", + "no", + "pl", + "pt", + "ro", + "ru", + "uk", + "zh", +] +PERPLEXITY_MODELS = ["Wikipedia", "OSCAR"] + + +class ContextLogger: + def __init__(self, text: str = ""): + self.text = text + self.start_time = time.time() + + def __enter__(self): + logger.info(self.text) + + def __exit__(self, type, value, traceback): + logger.info(f"Took: {time.time() - self.start_time:.4f} seconds") + + +def generate_plot( + df: pd.DataFrame, + text_column: str, + label_column: str, + sample: Optional[int], + dimensionality_reduction_function: Callable, + model: SentenceTransformer, + seed: int = 0, + context_logger: Union[st.spinner, ContextLogger] = ContextLogger, + hub_dataset: str = "", +) -> Tuple[Figure, Optional[Figure]]: + if text_column not in df.columns: + raise ValueError( + f"The specified column name doesn't exist. Columns available: {df.columns.values}" + ) + if label_column not in df.columns: + df[label_column] = 0 + df = df.dropna(subset=[text_column, label_column]) + if sample: + df = df.sample(min(sample, df.shape[0]), random_state=seed) + with context_logger(text="Embedding text..."): + embeddings = embed_text(df[text_column].values.tolist(), model) + logger.info("Encoding labels") + encoded_labels = encode_labels(df[label_column]) + with context_logger("Reducing dimensionality..."): + embeddings_2d = dimensionality_reduction_function(embeddings) + logger.info("Generating figure") + hover_data = { + text_column: df[text_column].values, + label_column: encoded_labels.values, + } + # Round perplexity values + values = df[label_column].values.round().astype(int) + plot = draw_interactive_scatter_plot( + hover_data, + embeddings_2d[:, 0], + embeddings_2d[:, 1], + values, + ) + # Special case for the registry dataset + plot_registry = None + if hub_dataset == REGISTRY_DATASET: + encoded_labels = encode_labels(df["label"]) + hover_data = { + text_column: df[text_column].values, + "label": df["label"].values, + label_column: df[label_column].values, + } + plot_registry = draw_interactive_scatter_plot( + hover_data, + embeddings_2d[:, 0], + embeddings_2d[:, 1], + encoded_labels.values, + palette=Turbo256, + ) + return plot, plot_registry diff --git a/data_tooling/perplexity_lenses/perplexity_lenses/perplexity.py b/data_tooling/perplexity_lenses/perplexity_lenses/perplexity.py new file mode 100644 index 0000000..990f546 --- /dev/null +++ b/data_tooling/perplexity_lenses/perplexity_lenses/perplexity.py @@ -0,0 +1,188 @@ +import os +import re +import unicodedata +from typing import Dict + +import kenlm +import sentencepiece +from huggingface_hub import cached_download, hf_hub_url + +KENLM_MODEL_REPO = "edugp/kenlm" + + +class SentencePiece: + def __init__( + self, + model: str, + ): + super().__init__() + self.sp = sentencepiece.SentencePieceProcessor() + self.sp.load(str(model)) + + def do(self, text: dict) -> dict: + tokenized = self.sp.encode_as_pieces(text) + return " ".join(tokenized) + + +class KenlmModel: + digit_re: re.Pattern = re.compile(r"\d") + unicode_punct: Dict[str, str] = { + "，": ",", + "。": ".", + "、": ",", + "„": '"', + "”": '"', + "“": '"', + "«": '"', + "»": '"', + "１": '"', + "」": '"', + "「": '"', + "《": '"', + "》": '"', + "´": "'", + "∶": ":", + "：": ":", + "？": "?", + "！": "!", + "（": "(", + "）": ")", + "；": ";", + "–": "-", + "—": " - ", + "．": ". ", + "～": "~", + "’": "'", + "…": "...", + "━": "-", + "〈": "<", + "〉": ">", + "【": "[", + "】": "]", + "％": "%", + "►": "-", + } + unicode_punct_re = re.compile(f"[{''.join(unicode_punct.keys())}]") + non_printing_chars_re = re.compile( + f"[{''.join(map(chr, list(range(0,32)) + list(range(127,160))))}]" + ) + kenlm_model_dir = None + sentence_piece_model_dir = None + + def __init__( + self, + model_dataset: str, + language: str, + lower_case: bool = False, + remove_accents: bool = False, + normalize_numbers: bool = True, + punctuation: int = 1, + ): + self.download_kenlm_model(model_dataset, language) + try: + self.model = kenlm.Model(self.kenlm_model_dir) + self.tokenizer = SentencePiece(self.sentence_piece_model_dir) + except OSError: + os.remove(self.kenlm_model_dir) + if os.path.exists(self.sentence_piece_model_dir): + os.remove(self.sentence_piece_model_dir) + raise OSError( + "File was corrupt and should have been removed. Please, retry." + ) + self.accent = remove_accents + self.case = lower_case + self.numbers = normalize_numbers + self.punct = punctuation + + @classmethod + def from_pretrained( + cls, + model_dataset: str, + language: str, + lower_case: bool, + remove_accents: bool, + normalize_numbers: bool, + punctuation: int, + ): + return cls( + model_dataset, + language, + lower_case, + remove_accents, + normalize_numbers, + punctuation, + ) + + def pp(self, log_score, length): + return 10.0 ** (-log_score / length) + + def get_perplexity(self, doc: str, normalize_cc_net: bool = True): + if normalize_cc_net: + doc = self.normalize( + doc, + accent=self.accent, + case=self.case, + numbers=self.numbers, + punct=self.punct, + ) + # Tokenize (after normalizing): See https://github.com/facebookresearch/cc_net/blob/bda555bd1cf1ee2e0b925363e62a61cd46c8b60d/cc_net/mine.py#L352 for full pipeline + doc = self.tokenizer.do(doc) + doc_log_score, doc_length = 0, 0 + for line in doc.split("\n"): + log_score = self.model.score(line) + length = len(line.split()) + 1 + doc_log_score += log_score + doc_length += length + return round(self.pp(doc_log_score, doc_length), 1) + + def normalize( + self, + line: str, + accent: bool = True, + case: bool = True, + numbers: bool = True, + punct: int = 1, + ) -> str: + line = line.strip() + if not line: + return line + if case: + line = line.lower() + if accent: + line = self.strip_accents(line) + if numbers: + line = self.digit_re.sub("0", line) + if punct == 1: + line = self.replace_unicode_punct(line) + elif punct == 2: + line = self.remove_unicode_punct(line) + line = self.remove_non_printing_char(line) + return line + + def strip_accents(self, line: str) -> str: + """Strips accents from a piece of text.""" + nfd = unicodedata.normalize("NFD", line) + output = [c for c in nfd if unicodedata.category(c) != "Mn"] + if len(output) == line: + return line + return "".join(output) + + def replace_unicode_punct(self, text: str) -> str: + return "".join(self.unicode_punct.get(c, c) for c in text) + + def remove_unicode_punct(self, text: str) -> str: + """More aggressive version of replace_unicode_punct but also faster.""" + return self.unicode_punct_re.sub("", text) + + def remove_non_printing_char(self, text: str) -> str: + return self.non_printing_chars_re.sub("", text) + + def download_kenlm_model(self, model_dataset: str, language: str): + kenlm_model_url = hf_hub_url( + KENLM_MODEL_REPO, filename=f"{model_dataset}/{language}.arpa.bin" + ) + self.kenlm_model_dir = cached_download(kenlm_model_url) + sentence_piece_model_url = hf_hub_url( + KENLM_MODEL_REPO, filename=f"{model_dataset}/{language}.sp.model" + ) + self.sentence_piece_model_dir = cached_download(sentence_piece_model_url) diff --git a/data_tooling/perplexity_lenses/perplexity_lenses/visualization.py b/data_tooling/perplexity_lenses/perplexity_lenses/visualization.py new file mode 100644 index 0000000..b211040 --- /dev/null +++ b/data_tooling/perplexity_lenses/perplexity_lenses/visualization.py @@ -0,0 +1,18 @@ +import matplotlib.figure +import matplotlib.pyplot as plt +import numpy as np + + +def draw_histogram( + values: np.ndarray, + cutoff_x_axis: float = 2000.0, + title: str = "Perplexity histogram", + xlabel: str = "Perplexity", +) -> matplotlib.figure.Figure: + hist_values = values[values < cutoff_x_axis] + fig, ax = plt.subplots(figsize=(12, 9)) + ax.hist(hist_values, bins=50) + ax.set_title(title) + ax.set_xlabel(xlabel) + ax.set_ylabel("Counts") + return fig diff --git a/data_tooling/perplexity_lenses/poetry.lock b/data_tooling/perplexity_lenses/poetry.lock new file mode 100644 index 0000000..bceddbf --- /dev/null +++ b/data_tooling/perplexity_lenses/poetry.lock @@ -0,0 +1,3451 @@ +[[package]] +name = "aiohttp" +version = "3.8.1" +description = "Async http client/server framework (asyncio)" +category = "main" +optional = false +python-versions = ">=3.6" + +[package.dependencies] +aiosignal = 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a/data_tooling/perplexity_lenses/tests/__init__.py b/data_tooling/perplexity_lenses/tests/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/data_tooling/perplexity_lenses/tests/test_data.py b/data_tooling/perplexity_lenses/tests/test_data.py new file mode 100644 index 0000000..bc61033 --- /dev/null +++ b/data_tooling/perplexity_lenses/tests/test_data.py @@ -0,0 +1,15 @@ +import unittest + +import pandas as pd + +from perplexity_lenses.data import documents_df_to_sentences_df + + +class TestData(unittest.TestCase): + def test_documents_df_to_sentences_df(self): + input_df = pd.DataFrame({"text": ["foo\nbar"]}) + expected_output_df = pd.DataFrame({"text": ["foo", "bar"]}) + output_df = documents_df_to_sentences_df(input_df, "text", 100) + pd.testing.assert_frame_equal( + output_df, expected_output_df, check_like=True, check_exact=True + ) diff --git a/data_tooling/pii-manager/.gitignore b/data_tooling/pii-manager/.gitignore new file mode 100644 index 0000000..2ded82a --- /dev/null +++ b/data_tooling/pii-manager/.gitignore @@ -0,0 +1,132 @@ +# Byte-compiled / optimized / DLL files +__pycache__/ +*.py[cod] +*$py.class + +# C extensions +*.so + +# Distribution / packaging +.Python +build/ +develop-eggs/ +dist/ +downloads/ +eggs/ +.eggs/ +lib/ +lib64/ +parts/ +sdist/ +var/ +wheels/ +pip-wheel-metadata/ +share/python-wheels/ +*.egg-info/ +.installed.cfg +*.egg +MANIFEST + +# PyInstaller +# Usually these files are written by a python script from a template +# before PyInstaller builds the exe, so as to inject date/other infos into it. +*.manifest +*.spec + +# Installer logs +pip-log.txt +pip-delete-this-directory.txt + +# Unit test / coverage reports +htmlcov/ +.tox/ +.nox/ +.coverage +.coverage.* +.cache +nosetests.xml +coverage.xml +*.cover +*.py,cover +.hypothesis/ +.pytest_cache/ + +# Translations +*.mo +*.pot + +# Django stuff: +*.log +local_settings.py +db.sqlite3 +db.sqlite3-journal + +# Flask stuff: +instance/ +.webassets-cache + +# Scrapy stuff: +.scrapy + +# Sphinx documentation +docs/_build/ + +# PyBuilder +target/ + +# Jupyter Notebook +.ipynb_checkpoints + +# IPython +profile_default/ +ipython_config.py + +# pyenv +.python-version + +# pipenv +# According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control. +# However, in case of collaboration, if having platform-specific dependencies or dependencies +# having no cross-platform support, pipenv may install dependencies that don't work, or not +# install all needed dependencies. +#Pipfile.lock + +# PEP 582; used by e.g. github.com/David-OConnor/pyflow +__pypackages__/ + +# Celery stuff +celerybeat-schedule +celerybeat.pid + +# SageMath parsed files +*.sage.py + +# Environments +.env +.venv +env/ +venv/ +ENV/ +env.bak/ +venv.bak/ + +# Spyder project settings +.spyderproject +.spyproject + +# Rope project settings +.ropeproject + +# mkdocs documentation +/site + +# mypy +.mypy_cache/ +.dmypy.json +dmypy.json + +# Pyre type checker +.pyre/ + +# Backup files +*~ diff --git a/data_tooling/pii-manager/CHANGES.md b/data_tooling/pii-manager/CHANGES.md new file mode 100644 index 0000000..19c2793 --- /dev/null +++ b/data_tooling/pii-manager/CHANGES.md @@ -0,0 +1,34 @@ +v. 0.5.0 + * new task list parsing code, adding a "full" format based on dicts, in + addition to the previous "simplified" format based on tuples + * refactored to allow more than one task for a given PII and country + * added the capability to add task descriptors programmatically + * added reading task descriptors from a JSON file + * context validation spec, for all three task implementation types + * TASK_ANY split into LANG_ANY & COUNTRY_ANY + * PII detectors for international phone numbers, for en-any & es-any + * PII detector for IP addresses, language independent + * PII detectors for GOV_ID + - lang pt, countries PT & BR + - lang es, country MX + +v. 0.4.0 + * PII GOV_ID task for es-ES and en-AU + * PII EMAIL_ADDRESS task + * PyPi Makefile targets; fixed setup.py + +v. 0.3.0 + * new processing mode: `full` + * PII detectors for zh-CN + * added `regex` as dependency + * `regex` used for regular expression tasks instead of `re` + +v. 0.2.0 + * Added PII tasks: + - en: GOV_ID for US, CA, IN + - fr: GOV_ID for CA + * fix paths for languages/countries that are reserved Python words (is, in) + * added country information to PiiEntity + * added an _asdict() function for PiiEntities + * added PII country to task_info + * miscellaneous fixes diff --git a/data_tooling/pii-manager/LICENSE b/data_tooling/pii-manager/LICENSE new file mode 100644 index 0000000..261eeb9 --- /dev/null +++ b/data_tooling/pii-manager/LICENSE @@ -0,0 +1,201 @@ + Apache License + Version 2.0, January 2004 + http://www.apache.org/licenses/ + + TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION + + 1. Definitions. + + "License" shall mean the terms and conditions for use, reproduction, + and distribution as defined by Sections 1 through 9 of this document. + + "Licensor" shall mean the copyright owner or entity authorized by + the copyright owner that is granting the License. + + "Legal Entity" shall mean the union of the acting entity and all + other entities that control, are controlled by, or are under common + control with that entity. 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In this order: +# 1. the one given by the VENV environment variable +# 2. an active one (as given by the VIRTUAL_ENV environment variable) +# 3. a default +VENV ?= $(shell echo $${VIRTUAL_ENV:-/opt/venv/bigscience}) + +PYTHON ?= python3 + +# -------------------------------------------------------------------------- + +# Package version: taken from the __init__.py file +VERSION_FILE := src/pii_manager/__init__.py +VERSION := $(shell grep VERSION $(VERSION_FILE) | sed -r "s/VERSION = \"(.*)\"/\1/") + +PKGFILE := dist/$(NAME)-$(VERSION).tar.gz + +# -------------------------------------------------------------------------- + +all: + +build pkg: $(PKGFILE) + +clean: + rm -f "$(PKGFILE)" + +rebuild: clean build + +version: + @echo "$(VERSION)" + +# -------------------------------------------------------------------------- + +TEST ?= test/unit + + +venv: $(VENV) + +pytest: $(VENV)/bin/pytest + +unit: venv pytest + PYTHONPATH=src:test $(VENV)/bin/pytest $(ARGS) $(TEST) + +unit-verbose: venv pytest + PYTHONPATH=src:test $(VENV)/bin/pytest -vv --capture=no $(ARGS) $(TEST) + +# -------------------------------------------------------------------------- + +$(PKGFILE): $(VERSION_FILE) setup.py + $(PYTHON) setup.py sdist + +install: $(PKGFILE) + $(VENV)/bin/pip install $(PKGFILE) + +uninstall: + $(VENV)/bin/pip uninstall -y $(NAME) + +reinstall: uninstall clean pkg install + + +$(VENV): + BASE=$$(basename "$@"); test -d "$$BASE" || mkdir -p "$$BASE" + $(PYTHON) -m venv $@ + $@/bin/pip install -r requirements.txt + +$(VENV)/bin/pytest: + $(VENV)/bin/pip install pytest + + +# ----------------------------------------------------------------------- + +upload-check: $(PKGFILE) + twine check $(PKGFILE) + +upload-test: $(PKGFILE) + twine upload --repository pypitest $(PKGFILE) + +upload: $(PKGFILE) + twine upload $(PKGFILE) diff --git a/data_tooling/pii-manager/README.md b/data_tooling/pii-manager/README.md new file mode 100644 index 0000000..a03bf90 --- /dev/null +++ b/data_tooling/pii-manager/README.md @@ -0,0 +1,49 @@ +# Pii Manager + +This repository builds a Python package that performs PII processing for text +data i.e. replacement/tagging/extraction of PII (Personally Identifiable +Information aka [Personal Data]) items existing in the text. + +The PII Tasks in the package are structured by language & country, since many +of the PII elements are language- and/or -country dependent. + +## Requirements + +The package needs at least Python 3.8, and uses the [python-stdnum] package to +validate identifiers. + +## Usage + +The package can be used: + * As an API, in two flavors: function-based API and object-based API + * As a command-line tool + +For details, see the [usage document]. + + +## Building + +The provided [Makefile] can be used to process the package: + * `make pkg` will build the Python package, creating a file that can be + installed with `pip` + * `make unit` will launch all unit tests (using [pytest], so pytest must be + available) + * `make install` will install the package in a Python virtualenv. The + virtualenv will be chosen as, in this order: + - the one defined in the `VENV` environment variable, if it is defined + - if there is a virtualenv activated in the shell, it will be used + - otherwise, a default is chosen as `/opt/venv/bigscience` (it will be + created if it does not exist) + + +## Contributing + +To add a new PII processing task, please see the [contributing instructions]. + + +[python-stdnum]: https://github.com/arthurdejong/python-stdnum +[Makefile]: Makefile +[pytest]: https://docs.pytest.org +[contributing instructions]: doc/contributing.md +[usage document]: doc/usage.md +[Personal Data]: https://en.wikipedia.org/wiki/Personal_data diff --git a/data_tooling/pii-manager/doc/contributing.md b/data_tooling/pii-manager/doc/contributing.md new file mode 100644 index 0000000..7d31183 --- /dev/null +++ b/data_tooling/pii-manager/doc/contributing.md @@ -0,0 +1,146 @@ +# Adding PII tasks + +To add a new PII processing task to the package, prepare a Pull Request on the +repository with the following changes: + + 1. If the task type is a new one, add an identifier for it in [PiiEnum] + 2. If it is for a language not yet covered, add a new language subfolder + under the [lang] folder, using the [ISO 639-1] code for the language + 3. Then + * If it is a country-independent PII, it goes into the `any` subdir + (create that directory if it is not present) + * if it is country-dependent, create a country subdir if not present, + using a **lowercased version** of its [ISO 3166-1] country code + 4. Under the final chosen subfolder, add the task as a Python `mytaskname.py` + module (the name of the file is not relevant). The module must contain: + * The task implementation, which can have any of three flavours (regex, + function or class), see below + * The task descriptor, a list containing all defined tasks. The list + variable *must* be named `PII_TASKS` (see below) + 5. Finally, add a unit test to check the validity for the task code, in the + proper place under [test/unit/lang]. There should be at least + - a positive test: one valid PII that has to be detected. For the cases + in which the PII is validated, the test should pass the validation, + so the PII must be a random (fake) one but still valid + - and a negative test: one PII-like string that is almost, but not quite + the real one, so it should *not* be recognized + + +## Task implementation + +A task can be implemented with either of three shapes: regex, function or +class. See [tasks] for a description of how to implement each of these, +including where to add the required documentation explaining the task. + + +## Task descriptor + +The task descriptor is a Python list that contains at least one element +defining the entry points for this task (there might be more than one, if +the file implements more than one PII). + +* The name of the list **must be** `PII_TASKS` +* A task entry in the list can have two different shapes: simplified and full. + In a `PII_TASKS` list they can be combined freely. + + +### Simplified description + +In a simplified description a task must be a 2- or 3-element tuple, with +these elements: + - the PII identifier for the task: a member of [PiiEnum] + - the [task implementation]: the regex, function or class implementing the + PII extractor + - (only if the implementation is of regex type) a text description of the + task (for documentation purposes) + + +### Full description + +In a full description a task is a dictionary with these compulsory fields: + * `pii`: the PII identifier for the task: a member of [PiiEnum] + * `type`: the task type: `regex`, `callable` or `PiiTask` + * `task`: for regex tasks, a raw string (contianing the regex to be used); + for function tasks a callable and for PiiTask either a class or a string + with a full class name. + +And these optional fields + * `lang`: language this task is designed for (it can also be `LANG_ANY`). If + not present, the language will be determined from the folder structure the + task implementation is in + * `country`: country this task is designed for. If not present, the language + will be determined from the folder structure the task implementation is in, + if possible (else, a `None`value will be used, meaning the task is not + country-dependent) + * `name`: a name for the task. If not present, a name will be generated from + the `pii_name` class-level attribute (PiiTask) or from the class/function + name. + This is meant to provide a higher level of detail than the `PiiEnum` + generic name (e.g. for different types of Government ID). Class-type tasks + can use a dynamic name at runtime (detected PII might have different names), + while function and regexes will have a fixed name. + * `doc`: the documentation for the class. If not present, the docstring for + callable and class types will be used (for regex types, the task will have + no documentation) + * `kwargs`: a dictionary of additional arguments. For `PiiTask` task types, + they will be added as arguments to the class constructor; for `callable` + types they will be added to each call to the task function. It is ignored + for `regex` types. + * `context` and `context_width`: for context validation, see below. + + +## Context validation + +A task of any of the three types of [task implementation] may also include an +additional step for context validation. In this step, all detected PII are +further validated by ensuring that a document chunk around the detected PII +string (before and after) contains one of the specified text contexts. + +Note that task descriptors with context *must* be a full description, i.e. the +dict version. + +Context validation can have three variants: + * `string`: each text context is a substring to be matched. + * `word`: each text context is also a substring to be matched, but matching + is ensured to work only on full words (the substring can contain more than + one word, but it will be matched only of sequences of full words). + * `regex`: each context is a regular expression (to be matched by the [regex] + Python package) + +Regardless of the variante, matching is always performed after normalizing +the extracted document context chunk: normalize whitespace (replace all +whitespace chunks by a single space) and lowercase the chunk. + +This validation acts as a filter after the task implementation produces its +results, and it is automatically applied if the task descriptor includes +context (for class-based tasks, it can be replaced with custom code by +overriding the `__call__` method, defined in the parent class). + +Context is defined by a `context` field in the task descriptor. This field +is a dictionary, with the following elements: + * `type` indicates the variant, and it can be `string`, `word` or `regex`. + If not present, `string` is assumed. + * `value` should be a list of strings, any of which validate a document + context. For `regex` mode the strings will be regex patterns. + * `width` is an integer, or a tuple of two integers, that define + the width (in characters) of the document chunk (before and after the PII + string) that define the document context. If not specified, a default is + used. + +As a shortcut, the `context` field can also contain a simple list of strings +(or a single string). In this case, the context is defined as type `string`, +with the default width, and the field contents define the value. + +An example of context validation can be seen in the [international phone +number] task. + +[task implementation]: #task-implementation +[PiiEnum]: ../src/pii_manager/piienum.py +[tasks]: tasks.md +[lang]: ../src/pii_manager/lang +[test/unit/lang]: ../test/unit/lang +[international phone number]: ../src/pii_manager/lang/en/any/international_phone_number.py + +[ISO 639-1]: https://en.wikipedia.org/wiki/List_of_ISO_639-1_codes +[ISO 3166-1]: https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2 +[regex]: https://github.com/mrabarnett/mrab-regex diff --git a/data_tooling/pii-manager/doc/external.md b/data_tooling/pii-manager/doc/external.md new file mode 100644 index 0000000..687bc2b --- /dev/null +++ b/data_tooling/pii-manager/doc/external.md @@ -0,0 +1,37 @@ +# Adding external task processors to a processing object + +In addition to the task processorts contained inside the [lang] subfolders in +the package, it is also possible to add _external_ task processors define +outside the package, as long as they comply with the [task specification]. +This can be done for both the object-base API and the file-based API. + + +## Object-based API + +An instantiated `ProcManager` object contains the `add_tasks` method. This +method will accept a list of [task descriptors] with the same syntax as the +internal `PII_TASKS` descriptors, and will add the tasks defined in them to +the existing ones in the object. + + +## File-based API + +The file-based `process_file` function allows a `taskfile` argument. This +argument will contain the name of a JSON file that contains an array of task +descriptors. Each task descriptor in the array is a JSON object following the +specification for [task descriptors], with these differences: + +* The `pii` field is not a `PiiEnum` object, but a string with the _name_ of + a `PiiEnum` object. It will be converted to the object itself. +* The `task` field contains: + - for `regex` types, the string with the regular expression pattern to be + compiled (beware of escaping all backlashes in the string) + - for `callable` and `PiiTask` types, a string with the **fully + qualified** name of the function to be used or class to be instantiated. + As long as that name can be located in the running Python space (i.e. + it is in the load path), it will be imported and used. + + +[lang]: ../src/pii_manager/lang +[task specification]: tasks.md +[task descriptors]: contributing.md#task-descriptor diff --git a/data_tooling/pii-manager/doc/tasks.md b/data_tooling/pii-manager/doc/tasks.md new file mode 100644 index 0000000..cc81527 --- /dev/null +++ b/data_tooling/pii-manager/doc/tasks.md @@ -0,0 +1,123 @@ +# PII Task Implementation + +A PII task is a module that provides detection of a given PII (possible for a +given language and country). The `pii-manager` package accepts three types of +implementations for a PII task. They are commented in the next sections. + + +## Regex implementation + +In its simplest form, a PII Task can be just a regular expression +pattern. This pattern should match string fragments that correspond to the PII +entity to be detected. + +Rules for the implementation of such regex are: + +* Implement it as a regular expression _string_, **not** as a compiled regular + expression (it will be compiled by the `pii-manager` module) +* The pattern **will be compiled with the [regex] package**, instead of the + `re` package in the standard Python library, so you can use the extended + features (such as unicode categories) in `regex`. Compilation will be done + in backwards-compatible mode (i.e. using the `VERSION0` flag), so it should + be fully compatible with `re` +* Do **not** anchor the regex to either beginning or end (it should be able to + match anywhere in the passed string, which itself can be any portion of + a document) +* Do not include capturing groups (they will be ignored) +* The pattern will be compiled with the [re.VERBOSE] (aka `re.X`) flag, so + take that into account (in particular, **whitespace is ignored**, so if it is + part of the regular expression needs to included as a category i.e. `\s`, or + escaped) + +An example can be seen in the [US Social Security Number] detector. + + +## Callable implementation + +The next implementation type is via a function. The signature for the function +is: + +```Python + + def my_pii_detector(src: doc) -> Iterable[str]: +``` + +The function can have any name, but it should indicate the entity it is +capturing, since it will be used as the `name` attribute for the task (after +converting underscores into spaces). + +The function should: + + * accept a string: the document to analyze + * return an iterable of strings: the string fragments corresponding to the + PII entities identified in the document + +An example can be seen in the [bitcoin address] detector. + +**Note**: in case the same entity appears more than once in the passed +document, it might be possible that the callable returns repeated strings. +This is not a problem; all of them will be reported. + +Conversely, if a given string in the document is a PII some of the time but +it also appears in a non-PII role in the same document, the wrapper that uses +the result of a callable implementation type will not be able to differentiate +among them, and the package will label *all* ocurrences of the string as PII. +If this is likely to happen, and there is code that *can* separate both uses, +then it is better to use the class implementation type below. + + +## Class implementation + +In this case the task is implemented as a full Python class. The class *must*: + + * inherit from `pii_manager.helper.BasePiiTask` + * implement a `find` method with the following signature: + + def find(self, doc: str) -> Iterable[PiiEntity]: + + i.e. a method returting an iterable of identified [PiiEntity] + + * the default task name will be taken from the class-level attribute + `pii_name`, if it exists, or else as the class name. Nevertheless, the name + can be dynammicaly set with each detected PiiEntity + +The class can also, optionally, include a constructor. In this case, the +constructor must + * accept an arbitrary number of keyword arguments + * call the parent class constructor with those arguments + +In other words: + +```Python + + def __init__(self, **kwargs): + super().__init__(**kwargs) + ... any code specific to the implementation here ... +``` + + +Examples can be seen in the [credit card] detector or the [Spanish GOV ID] +detector. + + +## Documentation + +In addition to its name, all PII Tasks should be documented with a small +string that explains what they detect. The place to add this documentation is: + * For Regex tasks, add the string as the third element in the task descriptor + inside `PII_TASKS` + * For Callable tasks, use the function docstring to add the documentation. + * For Class tasks, add the documentation as the _class level_ docstring. + +For any task type, if using the "full" description in `PII_TASKS`, a `doc` +field can be added to the dictionary description, and it will override any +automatic generation from docstrings. + + +[regex]: https://github.com/mrabarnett/mrab-regex +[US Social Security Number]: ../src/pii_manager/lang/en/us/social_security_number.py +[bitcoin address]: ../src/pii_manager/lang/any/bitcoin_address.py +[credit card]: ../src/pii_manager/lang/any/credit_card.py +[Spanish GOV ID]: ../src/pii_manager/lang/es/es/govid.py +[PiiEntity]: ../src/pii_manager/piientity.py +[re.VERBOSE]: https://docs.python.org/3/library/re.html#re.X diff --git a/data_tooling/pii-manager/doc/usage.md b/data_tooling/pii-manager/doc/usage.md new file mode 100644 index 0000000..c3af965 --- /dev/null +++ b/data_tooling/pii-manager/doc/usage.md @@ -0,0 +1,159 @@ +# Usage + +## API Usage + +There are two types of API usage: the object-based API (lower-level, based on +object instantiation) and the file-based API (higher-level, based on function +calls). + + +### Object API + +The object-based API is centered on the `PiiManager` object. Its usage goes +like this: + +```Python + + from pii_manager import PiiEnum + from pii_manager.api import PiiManager + + # Define language, country(ies) and PII tasks + lang = 'en' + country = ['US', 'GB'] + tasklist = (PiiEnum.CREDIT_CARD, PiiEnum.GOVID, PiiEnum.DISEASE) + + # Instantiate object + proc = PiiManager(lang, country, tasks=tasklist) + + # Process a text buffer + text_out = proc(text_in) + +``` + +... this will load and execute anonymization tasks for English that will +anonymize credit card numbers, disease information, and Government IDs for US +and UK (assuming all these tasks are implemented in the package). + + +It is also possible to load all possible tasks for a language, by specifying +the country as `COUNTRY_ANY` and using the `all_tasks` argument. + +```Python + + from pii_manager import PiiEnum + from pii_manager.api import PiiManager + from pii_manager.lang import COUNTRY_ANY + + proc = PiiManager('en', COUNTRY_ANY, all_tasks=True) + + text_out = proc(text_in) + +``` + +...this will load all anonymization tasks available for English, including: + * language-independent tasks + * language-dependent but country-independent tasks + * country-dependent tasks for *all* countries implemented under the `en` + language + +Finally, the API allows for [importing arbitrary tasks] defined outside the +package. + + +### File-based API + +The file-based API uses the `process_file` function to read from a file and +write the result to an output file. It is executed as: + +```Python + + from pii_manager import PiiEnum + from pii_manager.api import process_file + + # Define language, country(ies) and PII tasks + lang = 'en' + country = ['US', 'GB'] + tasklist = (PiiEnum.CREDIT_CARD, PiiEnum.GOVID, PiiEnum.DISEASE) + + # Process the file + process_file(infilename, outfilename, lang, + country=country, tasks=tasklist) + +``` + +The file-based API accepts also the `all_tasks` argument to add all suitable +defined tasks, as well as the `COUNTRY_ANY` option. It can also [import +external tasks], as defined in a JSON file. + + +## Command-line usage + +Installing the package provides also a command-line script, `pii-manage`, +that can be used to process files through PII tasks: + + pii-manage --lang es --country es ar mx \ + --tasks CREDIT_CARD BITCOIN_ADDRESS BANK_ACCOUNT + +or, to add all possible tasks for a given language: + + pii-manage --lang es --country all \ + --all-tasks + + +There is an additional command-line script, `pii-task-info`, that does not +process text; it is only used to show the available tasks for a given language. + + +## Processing mode + +PII processing accepts four modes: _replace_ , _tag_, _extract_ and _full_. To +show an example, let us consider a fragment such as: + +> my credit card number is 4273 9666 4581 5642 + +with this input, the output for each of the processing modes will be: + +* for _replace_, the PII will be replaced by a placeholder describing the PII + name: + +> my credit card number is + +* for _tag_, the PII is tagged with the PII name, but the original string is + also kept: + +> my credit card number is + +* for _extract_, a list of detected PIIs is returned, as a dict in the + buffer-based API, or as a [NDJSON] file for the file-based API + +> {"name": "CREDIT_CARD", "value": "4273 9666 4581 5642", "pos": 25, "line": 1} + +* for _full_ mode, the API returns a dict or a NDJSON line for each text + fragment, containing the fields `text` (the passed text) and `entities` + (a list of the recognized PII entities) + +> {"text": "my credit card number is 4273 9666 4581 5642", +> "entities": [{"name": "CREDIT_CARD", "value": "4273 9666 4581 5642", +> "pos": 25, "line": 1}] +> } + + +By default in _replace_ mode all PII items found will be substituted with +a `` string. If another placeholder is preferred, the `PiiManager` +constructor can be called with an additional `template` argument, containing +a string that will be processed through the Python string `format()` method, +and called with a `(name=PIINAME)` argument. In _tag_ mode, the template is +called with `(country=COUNTRY, name=PIINAME, value=VALUE)` arguments, +which the template can use as it sees fit. + +The file-based API has an additional option: how the file is splitted when +calling the PII tasks: + +* `line`: (default) the file is splitted line-by-line +* `block`: the file is sent as a single block +* `sentences`: the file is split by sentence separators (periods, etc) + + +[NDJSON]: http://ndjson.org/ +[importing arbitrary tasks]: external.md#object-based-api +[import external tasks]:external.md#file-based-api diff --git a/data_tooling/pii-manager/requirements.txt b/data_tooling/pii-manager/requirements.txt new file mode 100644 index 0000000..1312127 --- /dev/null +++ b/data_tooling/pii-manager/requirements.txt @@ -0,0 +1,2 @@ +python-stdnum >=1.17,<2.0 +regex >= 2021.11.10 diff --git a/data_tooling/pii-manager/setup.py b/data_tooling/pii-manager/setup.py new file mode 100644 index 0000000..c5b0714 --- /dev/null +++ b/data_tooling/pii-manager/setup.py @@ -0,0 +1,93 @@ +""" +Create pii-manager as a Python package +""" + +import io +import sys +import re + +from setuptools import setup, find_packages + +from src.pii_manager import VERSION + +PKGNAME = "pii-manager" +GITHUB_URL = "https://github.com/bigscience-workshop/pii-manager" + +# -------------------------------------------------------------------- + +PYTHON_VERSION = (3, 8) + +if sys.version_info < PYTHON_VERSION: + sys.exit( + "**** Sorry, {} {} needs at least Python {}".format( + PKGNAME, VERSION, ".".join(map(str, PYTHON_VERSION)) + ) + ) + + +def requirements(filename="requirements.txt"): + """Read the requirements file""" + with io.open(filename, "r") as f: + return [line.strip() for line in f if line and line[0] != "#"] + + +def long_description(): + """ + Take the README and remove markdown hyperlinks + """ + with open("README.md", "rt", encoding="utf-8") as f: + desc = f.read() + desc = re.sub(r"^\[ ([^\]]+) \]: \s+ \S.*\n", r"", desc, flags=re.X | re.M) + return re.sub(r"\[ ([^\]]+) \]", r"\1", desc, flags=re.X) + + +# -------------------------------------------------------------------- + + +setup_args = dict( + # Metadata + name=PKGNAME, + version=VERSION, + author="Paulo Villegas", + author_email="paulo.vllgs@gmail.com", + description="Text Anonymization of PII", + long_description_content_type="text/markdown", + long_description=long_description(), + license="Apache", + url=GITHUB_URL, + download_url=GITHUB_URL + "/tarball/v" + VERSION, + # Locate packages + packages=find_packages("src"), # [ PKGNAME ], + package_dir={"": "src"}, + # Requirements + python_requires=">=3.8", + # Optional requirements + extras_require={ + "test": ["pytest", "nose", "coverage"], + }, + setup_requires=["pytest-runner"], + tests_require=["pytest"], + entry_points={ + "console_scripts": [ + "pii-manage = pii_manager.app.manage:main", + "pii-task-info = pii_manager.app.task_info:main", + ] + }, + include_package_data=False, + package_data={}, + # Post-install hooks + cmdclass={}, + keywords=["Big Science Workshop, PII"], + classifiers=[ + "Programming Language :: Python :: 3 :: Only", + "License :: OSI Approved :: Apache Software License", + "Development Status :: 4 - Beta", + "Topic :: Software Development :: Libraries :: Application Frameworks", + ], +) + +if __name__ == "__main__": + # Add requirements + setup_args["install_requires"] = requirements() + # Setup + setup(**setup_args) diff --git a/data_tooling/pii-manager/src/pii_manager/__init__.py b/data_tooling/pii-manager/src/pii_manager/__init__.py new file mode 100644 index 0000000..fb7a7e1 --- /dev/null +++ b/data_tooling/pii-manager/src/pii_manager/__init__.py @@ -0,0 +1,4 @@ +VERSION = "0.5.0" + +from .piienum import PiiEnum +from .piientity import PiiEntity diff --git a/data_tooling/pii-manager/src/pii_manager/api/__init__.py b/data_tooling/pii-manager/src/pii_manager/api/__init__.py new file mode 100644 index 0000000..413d288 --- /dev/null +++ b/data_tooling/pii-manager/src/pii_manager/api/__init__.py @@ -0,0 +1,2 @@ +from .manager import PiiManager +from .file import process_file diff --git a/data_tooling/pii-manager/src/pii_manager/api/file.py b/data_tooling/pii-manager/src/pii_manager/api/file.py new file mode 100644 index 0000000..2d14c77 --- /dev/null +++ b/data_tooling/pii-manager/src/pii_manager/api/file.py @@ -0,0 +1,184 @@ +""" +File-based API +""" + +import sys +import re +import json +import gzip +import bz2 +import lzma +from itertools import zip_longest +from pathlib import Path + +from typing import Dict, List, TextIO, Iterable, Optional, Union + +from pii_manager import PiiEnum +from pii_manager.api import PiiManager +from pii_manager.piientity import PiiEntity, piientity_asdict +from pii_manager.helper.exception import PiiManagerException, InvArgException +from pii_manager.helper.json import CustomJSONEncoder +from pii_manager.helper.types import TYPE_STR_LIST + +TYPE_RESULT = Union[str, Iterable[PiiEntity]] + + +def openfile(name: str, mode: str) -> TextIO: + """ + Open files, raw text or compressed (gzip, bzip2 or xz) + """ + name = str(name) + if name == "-": + return sys.stdout if mode.startswith("w") else sys.stdin + elif name.endswith(".gz"): + return gzip.open(name, mode, encoding="utf-8") + elif name.endswith(".bz2"): + return bz2.open(name, mode, encoding="utf-8") + elif name.endswith(".xz"): + return lzma.open(name, mode, encoding="utf-8") + else: + return open(name, mode, encoding="utf-8") + + +def sentence_splitter(doc: str) -> Iterable[str]: + """ + Split text by sentence separators + (keeping the separator at the end of the sentence, so that joining the + pieces recovers exactly the same text) + """ + split = re.split(r"(\s*[\.!\?．。]\s+)", doc) + args = [iter(split)] * 2 + for sentence, sep in zip_longest(*args, fillvalue=""): + if sentence: + yield sentence + sep + + +def write_extract(result: Iterable[PiiEntity], index: Dict, out: TextIO): + """ + Write output for "extract" mode as NDJSON + :param result: iterable of result PiiEntity objects + :param index: indexing information to be added to each PII_TASKS + :param out: destination to write the NDJSON lines to + """ + for pii in result: + elem = piientity_asdict(pii) + if index: + elem.update(index) + json.dump(elem, out, ensure_ascii=False) + print(file=out) + + +def write(result: TYPE_RESULT, mode: str, index: Optional[Dict], out: TextIO): + """ + Write processing result to output + """ + if mode == "extract": + write_extract(result, index, out) + elif mode == "full": + json.dump(result, out, ensure_ascii=False, cls=CustomJSONEncoder) + else: + out.write(result) + + +def print_tasks(proc: PiiManager, out: TextIO): + print("\n. Installed tasks:", file=out) + for (pii, country), doc in proc.task_info().items(): + print(f" {pii.name} [country={country}]\n ", doc, file=out) + + +def read_taskfile(filename: str) -> List[Dict]: + """ + Read a list of task descriptors from a JSON file + """ + with open(filename, encoding="utf-8") as f: + try: + tasklist = json.load(f) + for td in tasklist: + td["pii"] = PiiEnum[td["pii"]] + return tasklist + except json.JSONDecodeError as e: + raise InvArgException("invalid task spec file {}: {}", filename, e) + except KeyError as e: + if str(e) == "pii": + raise InvArgException( + "missing 'pii' field in task descriptor in {}", filename + ) + else: + raise InvArgException( + "cannot find PiiEnum element '{}' for task descriptor in {}", + e, + filename, + ) + except Exception as e: + raise InvArgException("cannot read taskfile '{}': {}", filename, e) + + +def add_taskfile(filename: TYPE_STR_LIST, proc: PiiManager): + """ + Add all tasks defined in a JSON file (or several) to a processing object + """ + if isinstance(filename, (str, Path)): + filename = [filename] + for name in filename: + tasklist = read_taskfile(name) + proc.add_tasks(tasklist) + + +# ---------------------------------------------------------------------- + + +def process_file( + infile: str, + outfile: str, + lang: str, + country: List[str] = None, + tasks: List[str] = None, + all_tasks: bool = False, + taskfile: TYPE_STR_LIST = None, + split: str = "line", + mode: str = "replace", + template: str = None, + debug: bool = False, + show_tasks: bool = False, + show_stats: bool = False, +) -> Dict: + """ + Process a number of PII tasks on a text file + """ + # Create the object + proc = PiiManager( + lang, + country, + tasks, + all_tasks=all_tasks, + mode=mode, + template=template, + debug=debug, + ) + if taskfile: + add_taskfile(taskfile, proc) + if show_tasks: + print_tasks(proc, sys.stderr) + + # Process the file + print(". Reading from:", infile, file=sys.stderr) + print(". Writing to:", outfile, file=sys.stderr) + with openfile(infile, "rt") as fin: + with openfile(outfile, "wt") as fout: + if split == "block": + write(proc(fin.read()), mode, None, fout) + elif split == "line": + for n, line in enumerate(fin): + write(proc(line), mode, {"line": n + 1}, fout) + elif split == "sentence": + for n, sentence in enumerate(sentence_splitter(fin.read())): + write(proc(sentence), mode, {"sentence": n + 1}, fout) + else: + raise PiiManagerException("invalid split mode: {}", split) + + if show_stats: + print("\n. Statistics:", file=sys.stderr) + for k, v in proc.stats.items(): + print(f" {k:20} : {v:5}", file=sys.stderr) + + return proc.stats diff --git a/data_tooling/pii-manager/src/pii_manager/api/manager.py b/data_tooling/pii-manager/src/pii_manager/api/manager.py new file mode 100644 index 0000000..cdb3d7d --- /dev/null +++ b/data_tooling/pii-manager/src/pii_manager/api/manager.py @@ -0,0 +1,252 @@ +""" +Definition of the main PiiManager object +""" + +from collections import defaultdict +from itertools import chain + +from typing import Iterable, Tuple, List, Callable, Union, Dict, Type + +from ..piientity import PiiEntity +from ..piienum import PiiEnum +from ..helper import get_taskdict, country_list +from ..helper.taskdict import task_check +from ..helper.base import BasePiiTask, CallablePiiTask, RegexPiiTask +from ..helper.exception import InvArgException +from ..lang import LANG_ANY, COUNTRY_ANY + + +DEFAULT_TEMPLATES = {"replace": "<{name}>", "tag": "<{name}:{value}>"} + + +# -------------------------------------------------------------------------- + + +def fetch_all_tasks( + lang: str, country: Iterable[str] = None, debug: bool = False +) -> Iterable[List[Dict]]: + """ + Return all processing tasks available for a given language & (optionally) + country + """ + taskdict = get_taskdict(debug=debug) + # Language-independent + for task in taskdict[LANG_ANY].values(): + yield task + + langdict = taskdict.get(lang, {}) + # Country-independent + for task in langdict.get(COUNTRY_ANY, {}).values(): + yield task + # Country-specific + if country: + if country[0] in (COUNTRY_ANY, "all"): + country = country_list(lang) + for c in country: + if c == COUNTRY_ANY: # already included above + continue + for task in langdict.get(c, {}).values(): + yield task + + +def fetch_task( + taskname: str, lang: str, country: Iterable[str] = None, debug: bool = False +) -> Iterable[List[Dict]]: + """ + Return a specific task for a given language & country + (try to find the most specific task available) + """ + found = 0 + taskdict = get_taskdict(debug=debug) + if isinstance(taskname, PiiEnum): + taskname = taskname.name + + langdict = taskdict.get(lang, {}) + if langdict: + # First try: language & country + if country: + if country[0] in (COUNTRY_ANY, "all"): + country = country_list(lang) + for c in country: + task = langdict.get(c, {}).get(taskname) + if task: + found += 1 + yield task + # Second try: only language + task = langdict.get(COUNTRY_ANY, {}).get(taskname) + if task: + found += 1 + yield task + # Third try: generic task + task = taskdict[LANG_ANY].get(taskname) + if task: + found += 1 + yield task + + # We didn't find anything + if not found: + print(f"Warning: cannot find any pii task for {taskname}, {lang}, {country}") + + +# -------------------------------------------------------------------------- + + +def build_task(task: Dict) -> BasePiiTask: + """ + Build a task object from its task descriptor + """ + # Prepare arguments + try: + ttype, tobj = task["type"], task["task"] + args = {k: task[k] for k in ("pii", "lang", "country", "name", "doc")} + args["context"] = task.get("context") + kwargs = task.get("kwargs", {}) + except KeyError as e: + raise InvArgException("invalid pii task object: missing field {}", e) + + # Instantiate + if ttype == "PiiTask": + proc = tobj(**args) + elif ttype == "callable": + proc = CallablePiiTask(tobj, extra_kwargs=kwargs, **args) + elif ttype in ("re", "regex"): + proc = RegexPiiTask(tobj, **args, **kwargs) + else: + raise InvArgException( + "invalid pii task type for {}: {}", task["pii"].name, ttype + ) + return proc + + +# -------------------------------------------------------------------------- + + +class PiiManager: + def __init__( + self, + lang: str, + country: List[str] = None, + tasks: Iterable[PiiEnum] = None, + all_tasks: bool = False, + mode: str = None, + template: str = None, + debug: bool = False, + ): + """ + Initalize a processor object, loading & initializing all specified + processing tasks + """ + # Sanitize input + self.lang = lang.lower() + if isinstance(country, str): + country = [country] + self.country = [c.lower() for c in country] if country else None + self.mode = mode if mode is not None else "replace" + if template is None and self.mode not in ("extract", "full"): + template = DEFAULT_TEMPLATES[self.mode] + self.template = template + + # Get the list of tasks we will use + if all_tasks: + tasklist = fetch_all_tasks(self.lang, self.country, debug=debug) + elif tasks: + if isinstance(tasks, PiiEnum): + tasks = [tasks] + tl = (fetch_task(name, self.lang, self.country) for name in tasks) + tasklist = chain.from_iterable(tl) + else: + tasklist = [] + + # Build an ordered array of task processors + taskproc = (build_task(t) for t in chain.from_iterable(tasklist)) + self.tasks = sorted(taskproc, key=lambda e: e.pii.value) + self.stats = defaultdict(int) + + # Prepare the method to be called + self._process = ( + self.process_full + if self.mode == "full" + else self.process_extract + if self.mode == "extract" + else self.process_subst + ) + + def __repr__(self) -> str: + return f"" + + def add_tasks(self, tasklist: Iterable[Dict]): + """ + Add a list of processing tasks to the object + """ + for task_spec in tasklist: + task_check(task_spec, self.lang, self.country) + self.tasks.append(build_task(task_spec)) + self.tasks = sorted(self.tasks, key=lambda e: e.pii.value) + + def task_info(self) -> Dict[Tuple, Tuple]: + """ + Return a dictionary with all defined tasks: + - keys are tuples (task id, country) + - values are tuples (name, doc) + """ + info = defaultdict(list) + for task in self.tasks: + info[(task.pii, task.country)].append((task.name, task.doc)) + return info + + def __call__(self, doc: str) -> Union[Dict, str, Iterable[PiiEntity]]: + """ + Process a document, calling all defined anonymizers + """ + return self._process(doc) + + def process_subst(self, doc: str) -> str: + """ + Process a document, calling all defined processors and performing + PII substitution + """ + self.stats["calls"] += 1 + for task_proc in self.tasks: + output = [] + pos = 0 + # Call all tasks + for pii in task_proc(doc): + # Add all a pair (text-prefix, transformed-pii) + output += [ + doc[pos : pii.pos], + self.template.format( + name=pii.elem.name, value=pii.value, country=pii.country + ), + ] + self.stats[pii.elem.name] += 1 + pos = pii.pos + len(pii) + # Reconstruct the document (including the last suffix) + doc = "".join(output) + doc[pos:] + return doc + + def process_extract(self, doc: str) -> Iterable[PiiEntity]: + """ + Process a document, calling all defined processors and performing + PII extraction + """ + self.stats["calls"] += 1 + for task_proc in self.tasks: + elem_list = task_proc(doc) + for pii in elem_list: + yield pii + self.stats[pii.elem.name] += 1 + + def process_full(self, doc: str) -> Dict: + """ + Process a document, calling all defined processors and performing + PII extraction. Return a dict with the original document and the + detected PII entities. + """ + self.stats["calls"] += 1 + pii_list = [] + for task_proc in self.tasks: + elem_list = task_proc(doc) + for pii in elem_list: + pii_list.append(pii) + self.stats[pii.elem.name] += 1 + return {"text": doc, "entities": pii_list} diff --git a/data_tooling/pii-manager/src/pii_manager/app/__init__.py b/data_tooling/pii-manager/src/pii_manager/app/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/data_tooling/pii-manager/src/pii_manager/app/manage.py b/data_tooling/pii-manager/src/pii_manager/app/manage.py new file mode 100644 index 0000000..90a5589 --- /dev/null +++ b/data_tooling/pii-manager/src/pii_manager/app/manage.py @@ -0,0 +1,68 @@ +""" +Command-line script to process text files +""" + +import sys +import argparse + +from typing import List + +from pii_manager import VERSION +from pii_manager.api import process_file + + +def parse_args(args: List[str]) -> argparse.Namespace: + parser = argparse.ArgumentParser( + description=f"Perform PII processing on a file (version {VERSION})" + ) + + g0 = parser.add_argument_group("Input/output paths") + g0.add_argument("infile", help="source file") + g0.add_argument("outfile", help="destination file") + + g1 = parser.add_argument_group("Language specification") + g1.add_argument("--lang", help="document language", required=True) + g1.add_argument("--country", nargs="+", help="countries to use") + + g2 = parser.add_argument_group("Task specification") + g21 = g2.add_mutually_exclusive_group(required=True) + g21.add_argument("--tasks", nargs="+", help="pii tasks to include") + g21.add_argument( + "--all-tasks", action="store_true", help="add all pii tasks available" + ) + g21.add_argument( + "--taskfile", nargs="+", help="add all pii tasks defined in a JSON file" + ) + + g3 = parser.add_argument_group("Processing") + g3.add_argument( + "--split", + choices=("line", "sentence", "block"), + default="line", + help="document splitting mode (default: %(default)s)", + ) + g3.add_argument( + "--mode", + choices=("replace", "tag", "extract", "full"), + default="replace", + help="processing mode (default: %(default)s)", + ) + g3.add_argument("--template", help="for modes replace & tag, use a custom template") + + g3 = parser.add_argument_group("Other") + g3.add_argument("--show-stats", action="store_true", help="show statistics") + g3.add_argument("--show-tasks", action="store_true", help="show defined tasks") + + return parser.parse_args(args) + + +def main(args: List[str] = None): + if args is None: + args = sys.argv[1:] + args = parse_args(args) + args = vars(args) + process_file(args.pop("infile"), args.pop("outfile"), args.pop("lang"), **args) + + +if __name__ == "__main__": + main() diff --git a/data_tooling/pii-manager/src/pii_manager/app/task_info.py b/data_tooling/pii-manager/src/pii_manager/app/task_info.py new file mode 100644 index 0000000..6a6e878 --- /dev/null +++ b/data_tooling/pii-manager/src/pii_manager/app/task_info.py @@ -0,0 +1,100 @@ +""" +Command-line script to show information about available tasks +""" + +import sys +import argparse + +from typing import List, TextIO + + +from pii_manager import VERSION +from pii_manager.api import PiiManager +from pii_manager.api.file import add_taskfile +from pii_manager.helper.taskdict import language_list, country_list + + +def print_tasks(proc: PiiManager, out: TextIO): + print(f". Installed tasks [language={proc.lang}]", file=out) + for (pii, country), tasklist in proc.task_info().items(): + print(f"\n {pii.name} [country={country}] ", file=out) + for name, doc in tasklist: + print(f" {name}: {doc}", file=out) + + +def process( + lang: str, + country: List[str] = None, + tasks: List[str] = None, + all_tasks: bool = False, + taskfile: List[str] = None, + debug: bool = False, + **kwargs, +): + """ + Process the request: show task info + """ + # Create the object + proc = PiiManager(lang, country, tasks, all_tasks=all_tasks, debug=debug) + if taskfile: + add_taskfile(taskfile, proc) + + # Show tasks + print_tasks(proc, sys.stdout) + + +def parse_args(args: List[str]) -> argparse.Namespace: + parser = argparse.ArgumentParser( + description=f"Show information about available PII tasks (version {VERSION})" + ) + + g1 = parser.add_argument_group("Language specification") + g11 = g1.add_mutually_exclusive_group(required=True) + g11.add_argument("--lang", help="language to load") + g11.add_argument( + "--list-languages", action="store_true", help="List all defined languages " + ) + g1.add_argument( + "--country", + nargs="+", + help="countries to use (use 'all' for all countries defined for the language)", + ) + + g2 = parser.add_argument_group("Task specification") + g21 = g2.add_mutually_exclusive_group() + g21.add_argument( + "--tasks", metavar="TASK_NAME", nargs="+", help="pii tasks to include" + ) + g21.add_argument( + "--all-tasks", action="store_true", help="add all pii tasks available" + ) + g2.add_argument( + "--taskfile", nargs="+", help="add all pii tasks defined in a JSON file" + ) + + g3 = parser.add_argument_group("Other") + g3.add_argument("--debug", action="store_true", help="debug mode") + + parsed = parser.parse_args(args) + if not ( + parsed.list_languages or parsed.tasks or parsed.all_tasks or parsed.taskfile + ): + print(". Warning: no task list selected") + return parsed + + +def main(args: List[str] = None): + if args is None: + args = sys.argv[1:] + args = parse_args(args) + + if args.list_languages: + for lang in language_list(): + print(f" {lang}:", " ".join(country_list(lang))) + else: + args = vars(args) + process(args.pop("lang"), **args) + + +if __name__ == "__main__": + main() diff --git a/data_tooling/pii-manager/src/pii_manager/helper/__init__.py b/data_tooling/pii-manager/src/pii_manager/helper/__init__.py new file mode 100644 index 0000000..552cd08 --- /dev/null +++ b/data_tooling/pii-manager/src/pii_manager/helper/__init__.py @@ -0,0 +1,2 @@ +from .taskdict import get_taskdict, country_list +from .base import BasePiiTask diff --git a/data_tooling/pii-manager/src/pii_manager/helper/base.py b/data_tooling/pii-manager/src/pii_manager/helper/base.py new file mode 100644 index 0000000..013b454 --- /dev/null +++ b/data_tooling/pii-manager/src/pii_manager/helper/base.py @@ -0,0 +1,121 @@ +""" +Define the base classes for Pii Tasks +""" + +import regex +from typing import Iterable, Callable + +from ..piientity import PiiEntity +from .normalizer import normalize +from .context import context_spec, context_check, CONTEXT_NORM_OPTIONS +from .exception import PiiUnimplemented + + +NORM_OPTIONS = dict(whitespace=True, lowercase=True) + + +class BasePiiTask: + """ + Base class for a Pii Task + """ + + def __init__(self, **kwargs): + """ + Base constructor: fetch & store all generic parameters + """ + # print("INIT", kwargs) + # Full set + self.options = kwargs.copy() + # Compulsory fields + for f in ("pii", "lang"): + setattr(self, f, kwargs.pop(f)) + # Optional fields + for f in ("country", "name"): + setattr(self, f, kwargs.pop(f, None)) + # Documentation + self.doc = kwargs.pop("doc", self.pii.name) + # Context + context = kwargs.pop("context", None) + self.context = context_spec(context) if context else None + + def context_check(self, doc: str, pii: PiiEntity) -> bool: + """ + Check that a pii has the proper context around it + """ + return context_check(doc, self.context, [pii.pos, pii.pos + len(pii)]) + + def find_context(self, doc: str) -> Iterable[PiiEntity]: + """ + Wrap over the standard find() method and filter out the occcurences + that do not match a context around them + """ + ndoc = None + for pii in self.find(doc): + if ndoc is None: + ndoc = normalize(doc, self.lang, **CONTEXT_NORM_OPTIONS) + if self.context_check(ndoc, pii): + yield pii + + def find(self, doc: str) -> Iterable[PiiEntity]: + """ + **Method to be implemented in subclasses** + """ + raise PiiUnimplemented("missing implementation for Pii Task") + + def __call__(self, doc: str) -> Iterable[PiiEntity]: + """ + Perform Pii extraction + """ + return self.find_context(doc) if self.context else self.find(doc) + + def __repr__(self) -> str: + """ + Return a string with a representation for the task + """ + return f"<{self.pii.name}:{self.name}:{self.country}:{self.__class__.__qualname__}>" + + +class RegexPiiTask(BasePiiTask): + """ + A wrapper for a PII implemented as a regex pattern + Instead of the standard re package it uses the regex package (in + backwards-compatible mode) + """ + + def __init__(self, pattern: str, **kwargs): + super().__init__(**kwargs) + self.regex = regex.compile(pattern, flags=regex.X | regex.VERSION0) + + def find(self, doc: str) -> Iterable[PiiEntity]: + """ + Iterate over the regex and produce Pii objects + """ + for cc in self.regex.finditer(doc): + yield PiiEntity( + self.pii, cc.start(), cc.group(), name=self.name, country=self.country + ) + + +class CallablePiiTask(BasePiiTask): + """ + A wrapper for a PII implemented as a function + """ + + def __init__(self, call: Callable, extra_kwargs=None, **kwargs): + super().__init__(**kwargs) + self.call = call + self.kwargs = extra_kwargs or {} + + def find(self, doc: str) -> Iterable[PiiEntity]: + """ + Call the function, get all returned strings, and locate them in the + passed document to generate the Pii objects + """ + for cc in self.call(doc, **self.kwargs): + start = 0 + while True: + pos = doc.find(cc, start) + if pos < 0: + break + yield PiiEntity(self.pii, pos, cc, name=self.name, country=self.country) + start = pos + len(cc) diff --git a/data_tooling/pii-manager/src/pii_manager/helper/context.py b/data_tooling/pii-manager/src/pii_manager/helper/context.py new file mode 100644 index 0000000..4b50805 --- /dev/null +++ b/data_tooling/pii-manager/src/pii_manager/helper/context.py @@ -0,0 +1,112 @@ +""" +Context processing +""" + +import regex + +from typing import Tuple, List, Dict, Union + +from .exception import InvArgException +from .normalizer import normalize + + +# Default width around a Pii where context is searched for +DEFAULT_CONTEXT_WIDTH = 64 + +# Normalization options used when matching contexts +CONTEXT_NORM_OPTIONS = dict(whitespace=True, lowercase=True) + + +def _norm(ctx: str, lang: str, escape: bool = False) -> str: + """ + Normalize a context string + :param escape: esacpe regex metacharacters in string + """ + ctx = normalize(ctx, lang, **CONTEXT_NORM_OPTIONS) + if escape: + ctx = regex.escape(ctx) + return ctx + + +def context_spec(spec: Union[str, List, Dict], lang=str) -> Dict: + """ + Parse & standardize a context specification + """ + if spec is None: + raise InvArgException("no context spec") + + # Simplified forms + if isinstance(spec, str): + spec = [spec] + for s in spec: + if not s: + raise InvArgException("empty context spec") + if isinstance(spec, list): + return { + "value": [_norm(c, lang) for c in spec], + "width": [DEFAULT_CONTEXT_WIDTH, DEFAULT_CONTEXT_WIDTH], + "regex": False, + } + + out = {} + + # Sanitize value + value = spec.get("value") + if value is None: + raise InvArgException("invalid context spec: {}", spec) + if isinstance(value, str): + value = [value] + for s in value: + if not s: + raise InvArgException("empty context spec") + + # Get & process context type + ctype = spec.get("type", "string") + if ctype == "string": + out["regex"] = False + value = [_norm(v, lang) for v in value] + elif ctype == "word": + out["regex"] = True + value = [regex.compile(r"\b" + _norm(v, lang, True) + r"\b") for v in value] + elif ctype == "regex": + out["regex"] = True + value = [regex.compile(v, flags=regex.X) for v in value] + else: + raise InvArgException("invalid context type: {}", ctype) + + out["value"] = value + + # Get context width + width = spec.get("width") + if width is None: + width = (DEFAULT_CONTEXT_WIDTH, DEFAULT_CONTEXT_WIDTH) + elif isinstance(width, int): + width = (width, width) + elif len(width) == 1: + width = (width[0], width[0]) + out["width"] = width + + return out + + +def context_check(text: str, spec: Dict, pii_pos: Tuple[int]) -> bool: + """ + Try to locate any of a list of context elements in a chunk of a + text string (around a center given by the position of a PII element) + """ + # Sanitize positions + width = spec["width"] + if isinstance(pii_pos, int): + pii_pos = (pii_pos, pii_pos) + elif len(pii_pos) == 1: + pii_pos.append(pii_pos[0]) + + # Extract context chunk + start = max(pii_pos[0] - width[0], 0) + src = text[start : pii_pos[0]] + " " + text[pii_pos[1] : pii_pos[1] + width[1]] + + # Match + if spec["regex"]: + return any(c.search(src) for c in spec["value"]) + else: + return any(c in src for c in spec["value"]) diff --git a/data_tooling/pii-manager/src/pii_manager/helper/exception.py b/data_tooling/pii-manager/src/pii_manager/helper/exception.py new file mode 100644 index 0000000..9b3fd30 --- /dev/null +++ b/data_tooling/pii-manager/src/pii_manager/helper/exception.py @@ -0,0 +1,11 @@ +class PiiManagerException(Exception): + def __init__(self, msg, *args): + super().__init__(msg.format(*args)) + + +class InvArgException(PiiManagerException): + pass + + +class PiiUnimplemented(PiiManagerException): + pass diff --git a/data_tooling/pii-manager/src/pii_manager/helper/json.py b/data_tooling/pii-manager/src/pii_manager/helper/json.py new file mode 100644 index 0000000..54694d6 --- /dev/null +++ b/data_tooling/pii-manager/src/pii_manager/helper/json.py @@ -0,0 +1,47 @@ +""" +Provide a custom JSON encoder that can serialize additional objects, +in particular PiiEntity objects +""" + + +from collections.abc import Iterator +import datetime +import json + + +def keygetter_set(v): + return str(v).lower() + + +class CustomJSONEncoder(json.JSONEncoder): + """ + A custom JSON encoder that can serialize additional objects: + - datetime objects (into ISO 8601 strings) + - sets (as sorted lists) + - iterators (as lists) + - any object having a to_json() method that produces a string or + a serializable object + + Non-serializable objects are converted to plain strings. + """ + + def default(self, obj): + """ + Serialize some special types + """ + if hasattr(obj, "to_json"): + return obj.to_json() + elif isinstance(obj, datetime.datetime): + t = obj.strftime("%Y-%m-%dT%H:%M:%S.%f%z") + if obj.tzinfo is not None: + t = t[:-2] + ":" + t[-2:] + return t + elif isinstance(obj, set): + return sorted(obj, key=keygetter_set) + elif isinstance(obj, Iterator): + return list(obj) + + try: + return super().default(self, obj) + except TypeError: + return str(obj) diff --git a/data_tooling/pii-manager/src/pii_manager/helper/normalizer.py b/data_tooling/pii-manager/src/pii_manager/helper/normalizer.py new file mode 100644 index 0000000..3c33748 --- /dev/null +++ b/data_tooling/pii-manager/src/pii_manager/helper/normalizer.py @@ -0,0 +1,13 @@ +def normalize( + text: str, lang: str, whitespace: bool = True, lowercase: bool = False +) -> str: + """ + Perforn some normalization steps on a text string + """ + if whitespace: + text = " ".join(text.split()) + + if lowercase: + text = text.lower() + + return text diff --git a/data_tooling/pii-manager/src/pii_manager/helper/taskdict.py b/data_tooling/pii-manager/src/pii_manager/helper/taskdict.py new file mode 100644 index 0000000..c733f1f --- /dev/null +++ b/data_tooling/pii-manager/src/pii_manager/helper/taskdict.py @@ -0,0 +1,321 @@ +""" +Traverse all folders and gather all implemented PiiTasks into a nested +dictionary + +Each dictionary value contains a 3-4 element tuple: + * lang + * country + * PiiEnum + * task implementation + * (for regex tasks) task documentation +""" + +import sys +import importlib +from pathlib import Path +from collections import defaultdict +import re + +from typing import Dict, List, Tuple, Callable, Any, Type, Union +from types import ModuleType + +from pii_manager import PiiEnum +from .exception import InvArgException +from .base import BasePiiTask +from .types import TYPE_STR_LIST +from ..lang import LANG_ANY, COUNTRY_ANY + +# Name of the list that holds the pii tasks at each module +_LISTNAME = "PII_TASKS" + +# The structure holding all loaded tasks, as a language-keyed dictionary +_TASKS = None + +# Locate the language folder +_LANG = Path(__file__).parents[1] / "lang" + + +# -------------------------------------------------------------------------- + + +class InvPiiTask(InvArgException): + def __init__(self, msg, lang=None, country=None): + super().__init__( + "task descriptor error [lang={}, country={}]: {}", lang, country, msg + ) + + +def _is_pii_class(obj: Any) -> bool: + return isinstance(obj, type) and issubclass(obj, BasePiiTask) + + +def _import_task_object(objname: str) -> Union[Callable, Type[BasePiiTask]]: + try: + modname, oname = objname.rsplit(".", 1) + mod = importlib.import_module(modname) + return getattr(mod, oname) + except Exception as e: + raise InvPiiTask("cannot import task object '{}': {}", objname, e) from e + + +def _task_check(task: Dict, lang: str, country: TYPE_STR_LIST): + """ + Check dict fields for a task, fill fields if needed + """ + if not isinstance(task, dict): + raise InvArgException("not a dictionary") + if not isinstance(task.get("pii"), PiiEnum): + raise InvArgException("field not a PiiEnum") + + # Check base fields: type & spec + if "type" not in task: + if _is_pii_class(task.get("task")): + task["type"] = "PiiTask" + if task.get("type") not in ("PiiTask", "callable", "re", "regex"): + raise InvArgException("unsupported task type: {}", task.get("type")) + if "task" not in task: + raise InvArgException("invalid task specification: no task field") + + # Check task spec against task type + if task["type"] in ("re", "regex") and not isinstance(task["task"], str): + raise InvArgException("regex spec should be a string") + elif task["type"] == "callable": + if isinstance(task["task"], str): + task["task"] = _import_task_object(task["task"]) + if not isinstance(task["task"], Callable): + raise InvArgException("callable spec should be a callable") + elif task["type"] == "PiiTask": + if isinstance(task["task"], str): + task["task"] = _import_task_object(task["task"]) + if not _is_pii_class(task["task"]): + raise InvArgException("class spec should be a PiiTask object") + + # Fill in name + if "name" not in task: + name = getattr(task["task"], "pii_name", None) + if not name: + name = getattr(task["task"], "__name__", None) + if name and task["type"] == "PiiTask": + name = " ".join(re.findall(r"[A-Z][^A-Z]*", name)).lower() + elif task["type"] == "callable": + name = name.replace("_", " ") + if not name: + name = (task["type"] + " for " + task["pii"].name).lower() + task["name"] = name + + # Fill in doc + if "doc" not in task and not isinstance(task["task"], str): + doc = getattr(task["task"], "__doc__", None) + if doc: + task["doc"] = doc.strip() + + # Process lang + task_lang = task.get("lang") + if ( + task_lang != lang + and task_lang not in (None, LANG_ANY) + and lang not in (None, LANG_ANY) + ): + raise InvArgException( + "language mismatch in task descriptor: {} vs {}", task_lang, lang + ) + elif task_lang is None: + if lang is None: + raise InvArgException("no lang can be determined") + task["lang"] = lang + + # Process country + if country is None: + country = [COUNTRY_ANY] + elif isinstance(country, str): + country = [country] + task_country = task.get("country") + if ( + task_country not in country + and task_country not in (None, COUNTRY_ANY) + and COUNTRY_ANY not in country + ): + raise InvArgException( + "country mismatch in task descriptor: {} vs {}", task_country, country + ) + if task_country is None: + task["country"] = country[0] + if task["country"] == COUNTRY_ANY: + task["country"] = None + + +def task_check(task: Dict, lang: str, country: str): + """ + Check the fields in a task descriptor. Complete missing fields, if possible + """ + try: + _task_check(task, lang, country) + except Exception as e: + raise InvPiiTask(e, lang=lang, country=country) + + +def build_subdict(task_list: List[Tuple], lang: str, country: str = None) -> Dict: + """ + Given a list of task tuples, build the task dict for them + """ + if not isinstance(task_list, (list, tuple)): + raise InvPiiTask("invalid tasklist: not a list/tuple", lang, country) + + subdict = defaultdict(list) + for src in task_list: + # Fetch the task + if isinstance(src, tuple): # parse a simplified form (tuple) + # Checks + if len(src) != 2 and (len(src) != 3 or not isinstance(src[1], str)): + raise InvPiiTask("invalid simplified task spec", lang, country) + # Task type + task_type = ( + "PiiTask" + if _is_pii_class(src[1]) + else "callable" + if callable(src[1]) + else "regex" + if isinstance(src[1], str) + else None + ) + # Build the dict + td = {"pii": src[0], "type": task_type, "task": src[1]} + if len(src) > 2: + td["doc"] = src[2] + task = td + elif isinstance(src, dict): # full form + task = src.copy() + else: + raise InvPiiTask("element must be a tuple or dict", lang, country) + + # Check dict fields + task_check(task, lang, country) + # Add to dict + subdict[task["pii"].name].append(task) + + return subdict + + +def _gather_piitasks( + pkg: ModuleType, path: str, lang: str, country: str, debug: bool = False +) -> List[Tuple]: + """ + Import and load all tasks defined in a module + """ + # Get the list of Python files in the module + modlist = ( + m.stem + for m in Path(path).iterdir() + if m.suffix == ".py" and m.stem != "__init__" + ) + + # Get all tasks defined in those files + pii_tasks = defaultdict(list) + for mname in modlist: + mod = importlib.import_module("." + mname, pkg) + task_list = getattr(mod, _LISTNAME, None) + if task_list: + subdict = build_subdict(task_list, lang, country) + for name, value in subdict.items(): + pii_tasks[name] += value + + # If debug mode is on, print out the list + if debug: + if not pii_tasks: + print("... NO PII TASKS for", pkg, file=sys.stderr) + else: + print("... PII TASKS for", pkg, file=sys.stderr) + print("... path =", path, file=sys.stderr) + for task_name, tasklist in pii_tasks.items(): + for task in tasklist: + print( + " ", + task_name, + f"-> ({task['type']})", + task["doc"], + file=sys.stderr, + ) + + return pii_tasks + + +def import_processor(lang: str, country: str = None, debug: bool = False) -> Dict: + """ + Import all task processors available for a given lang & country + """ + if debug: + print(".. IMPORT FROM:", lang, "/", country, file=sys.stderr) + if lang == LANG_ANY: + name = LANG_ANY + path = _LANG / LANG_ANY + else: + if country is None: + country_elem = COUNTRY_ANY + elif country in ("in", "is"): + country_elem = country + "_" + else: + country_elem = country + lang_elem = lang if lang not in ("is",) else lang + "_" + name = f"{lang_elem}.{country_elem}" + path = _LANG / lang_elem / country_elem + + # mod = importlib.import_module('...lang.' + name, __name__) + return _gather_piitasks( + "pii_manager.lang." + name, path, lang, country, debug=debug + ) + + +def _norm(elem: str) -> str: + """ + Strip away underscores used to avoid reserved Python words + """ + return elem[:-1] if elem.endswith("_") else elem + + +def country_list(lang: str) -> List[str]: + """ + Return all countries for a given language + """ + p = _LANG / lang + return [ + _norm(d.name) for d in p.iterdir() if d.is_dir() and d.name != "__pycache__" + ] + + +def language_list() -> List[str]: + return [ + _norm(d.name) for d in _LANG.iterdir() if d.is_dir() and d.name != "__pycache__" + ] + + +# -------------------------------------------------------------------------- + + +def _gather_all_tasks(debug: bool = False): + """ + Build the list of all tasks + """ + global _TASKS + + if debug: + print(". DEFINED LANGUAGES:", " ".join(sorted(language_list()))) + + _TASKS = {} + for lang in language_list(): + if lang == LANG_ANY: + _TASKS[lang] = import_processor(lang, debug=debug) + else: + _TASKS[lang] = { + country: import_processor(lang, country, debug) + for country in country_list(lang) + } + + +def get_taskdict(debug: bool = False) -> Dict: + """ + Return the dict holding all implemented pii tasks + """ + global _TASKS + if _TASKS is None: + _gather_all_tasks(debug) + return _TASKS diff --git a/data_tooling/pii-manager/src/pii_manager/helper/types.py b/data_tooling/pii-manager/src/pii_manager/helper/types.py new file mode 100644 index 0000000..3dc623e --- /dev/null +++ b/data_tooling/pii-manager/src/pii_manager/helper/types.py @@ -0,0 +1,3 @@ +from typing import Union, List + +TYPE_STR_LIST = Union[str, List[str]] diff --git a/data_tooling/pii-manager/src/pii_manager/lang/__init__.py b/data_tooling/pii-manager/src/pii_manager/lang/__init__.py new file mode 100644 index 0000000..22bfc32 --- /dev/null +++ b/data_tooling/pii-manager/src/pii_manager/lang/__init__.py @@ -0,0 +1,5 @@ +# Folder for language-independent tasks +LANG_ANY = "any" + +# Country-independent tasks +COUNTRY_ANY = "any" diff --git a/data_tooling/pii-manager/src/pii_manager/lang/any/__init__.py b/data_tooling/pii-manager/src/pii_manager/lang/any/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/data_tooling/pii-manager/src/pii_manager/lang/any/bitcoin_address.py b/data_tooling/pii-manager/src/pii_manager/lang/any/bitcoin_address.py new file mode 100644 index 0000000..4768e5f --- /dev/null +++ b/data_tooling/pii-manager/src/pii_manager/lang/any/bitcoin_address.py @@ -0,0 +1,44 @@ +""" +Find valid bitcoin addresses +1. Obtain candidates, by using a generic regex expression +2. Validate candidates by + - using a more exact regex + - validating the number through the Luhn algorithm +""" + +import re + +from typing import Iterable + +from stdnum import bitcoin + +from pii_manager import PiiEnum + +# ---------------------------------------------------------------------------- + +# regex for the three types of bitcoin addresses +_BITCOIN_PATTERN = ( + r"( [13] [" + + bitcoin._base58_alphabet + + "]{25,34}" + + "| bc1 [" + + bitcoin._bech32_alphabet + + "]{8,87})" +) + +_REGEX_BITCOIN = re.compile(_BITCOIN_PATTERN, flags=re.X) + + +def bitcoin_address(text: str) -> Iterable[str]: + """ + Bitcoin addresses (P2PKH, P2SH and Bech32), recognize & validate + """ + # Find and validate candidates + for ba in _REGEX_BITCOIN.findall(text): + if bitcoin.is_valid(ba): + yield ba + + +# --------------------------------------------------------------------- + +PII_TASKS = [(PiiEnum.BITCOIN_ADDRESS, bitcoin_address)] diff --git a/data_tooling/pii-manager/src/pii_manager/lang/any/credit_card.py b/data_tooling/pii-manager/src/pii_manager/lang/any/credit_card.py new file mode 100644 index 0000000..cc2db7d --- /dev/null +++ b/data_tooling/pii-manager/src/pii_manager/lang/any/credit_card.py @@ -0,0 +1,68 @@ +""" +Find valid credit card numbers: +1. Obtain candidates, by using a generic regex expression +2. Validate candidates by + - using a more exact regex + - validating the number through the Luhn algorithm +""" + +import re + +from stdnum import luhn + +from typing import Iterable + +from pii_manager import PiiEnum, PiiEntity +from pii_manager.helper import BasePiiTask + + +# ---------------------------------------------------------------------------- + +# base regex to detect candidates to credit card numbers +_CREDIT_PATTERN_BASE = r"\b \d (?:\d[ -]?){14} \d \b" + +# full regex for credit card type +# https://www.regular-expressions.info/creditcard.html +_CREDIT_PATTERN = r"""4[0-9]{12}(?:[0-9]{3})? | + (?:5[1-5][0-9]{2}|222[1-9]|22[3-9][0-9]|2[3-6][0-9]{2}|27[01][0-9]|2720)[0-9]{12} | + 3[47][0-9]{13} | + 3(?:0[0-5]|[68][0-9])[0-9]{11} | + 6(?:011|5[0-9]{2})[0-9]{12} | + (?:2131|1800|35\d{3})\d{11}""" + +# compiled regexes +_REGEX_CC_BASE = None +_REGEX_CC_FULL = None + + +class CreditCard(BasePiiTask): + """ + Credit card numbers for most international credit cards (detect & validate) + """ + + pii_name = "credit card" + + def __init__(self, **kwargs): + super().__init__(**kwargs) + # Compile the credit card regexes + global _REGEX_CC_FULL, _REGEX_CC_BASE + if _REGEX_CC_FULL is None: + _REGEX_CC_BASE = re.compile(_CREDIT_PATTERN_BASE, flags=re.VERBOSE) + _REGEX_CC_FULL = re.compile(_CREDIT_PATTERN, flags=re.VERBOSE) + + def find(self, doc: str) -> Iterable[PiiEntity]: + # First find candidates + for cc in _REGEX_CC_BASE.finditer(doc): + cc_value = cc.group() + # strip spaces and dashes + strip_cc = re.sub(r"[ -]+", "", cc_value) + # now validate the credit card number + if re.fullmatch(_REGEX_CC_FULL, strip_cc) and luhn.is_valid(strip_cc): + yield PiiEntity( + PiiEnum.CREDIT_CARD, cc.start(), cc_value, name=CreditCard.pii_name + ) + + +# --------------------------------------------------------------------- + +PII_TASKS = [(PiiEnum.CREDIT_CARD, CreditCard)] diff --git a/data_tooling/pii-manager/src/pii_manager/lang/any/email.py b/data_tooling/pii-manager/src/pii_manager/lang/any/email.py new file mode 100644 index 0000000..bd7d8b8 --- /dev/null +++ b/data_tooling/pii-manager/src/pii_manager/lang/any/email.py @@ -0,0 +1,11 @@ +""" +Detection of email addresses +""" + +from pii_manager import PiiEnum + + +_EMAIL_PATTERN = r"[\w\.=-]+ @ [\w\.-]+ \. [\w]{2,3}" + + +PII_TASKS = [(PiiEnum.EMAIL_ADDRESS, _EMAIL_PATTERN, "Email address")] diff --git a/data_tooling/pii-manager/src/pii_manager/lang/any/ip_address.py b/data_tooling/pii-manager/src/pii_manager/lang/any/ip_address.py new file mode 100644 index 0000000..67089ac --- /dev/null +++ b/data_tooling/pii-manager/src/pii_manager/lang/any/ip_address.py @@ -0,0 +1,25 @@ +""" +Detection of IP addresses +""" + +from pii_manager import PiiEnum + + +_IP_PATTERN = r""" + \b + (?: (?: 25[0-5] | 2[0-4][0-9] | [01]?[0-9][0-9]? ) \. ){3} + (?: 25[0-5] | 2[0-4][0-9] | [01]?[0-9][0-9]?) + \b +""" + + +PII_TASKS = [ + { + "pii": PiiEnum.IP_ADDRESS, + "type": "regex", + "task": _IP_PATTERN, + "name": "ip address", + "doc": "match IP addresses, with context", + "context": {"value": "ip", "type": "word", "width": 16}, + } +] diff --git a/data_tooling/pii-manager/src/pii_manager/lang/en/__init__.py b/data_tooling/pii-manager/src/pii_manager/lang/en/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/data_tooling/pii-manager/src/pii_manager/lang/en/any/__init__.py b/data_tooling/pii-manager/src/pii_manager/lang/en/any/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/data_tooling/pii-manager/src/pii_manager/lang/en/any/international_phone_number.py b/data_tooling/pii-manager/src/pii_manager/lang/en/any/international_phone_number.py new file mode 100644 index 0000000..48c284b --- /dev/null +++ b/data_tooling/pii-manager/src/pii_manager/lang/en/any/international_phone_number.py @@ -0,0 +1,28 @@ +""" +Detection of phone numbers written with international notation (i.e. with +prefix and country code) +""" + + +from pii_manager import PiiEnum + +PATTERN_INT_PHONE = r""" + (?:\+ | 00) + (?: 9[976]\d | 8[987530]\d | 6[987]\d | 5[90]\d | 42\d | + 3[875]\d | 2[98654321]\d | 9[8543210] | 8[6421] | + 6[6543210] | 5[87654321] | 4[987654310] | 3[9643210] | + 2[70] | 7 | 1) + [-\x20\.]? + (?: \d{2,3} [-\x20]? ){3,4} +""" + +PII_TASKS = [ + { + "pii": PiiEnum.PHONE_NUMBER, + "type": "regex", + "task": PATTERN_INT_PHONE, + "name": "international phone number", + "doc": "detect phone numbers that use international notation. Uses context", + "context": {"value": ["ph", "phone", "fax"], "width": [16, 0], "type": "word"}, + } +] diff --git a/data_tooling/pii-manager/src/pii_manager/lang/en/au/__init__.py b/data_tooling/pii-manager/src/pii_manager/lang/en/au/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/data_tooling/pii-manager/src/pii_manager/lang/en/au/abn.py b/data_tooling/pii-manager/src/pii_manager/lang/en/au/abn.py new file mode 100644 index 0000000..c11b9a8 --- /dev/null +++ b/data_tooling/pii-manager/src/pii_manager/lang/en/au/abn.py @@ -0,0 +1,27 @@ +""" +Detection and validation of Australian business number (ABN). + +""" +import re + +from stdnum.au import abn + +from typing import Iterable + +from pii_manager import PiiEnum + + +_ABN_PATTERN = r"\b (?: \d{2} \s \d{3} \s \d{3} \s \d{3} | \d{11} ) \b" +_ABN_REGEX = re.compile(_ABN_PATTERN, flags=re.X) + + +def australian_business_number(doc: str) -> Iterable[str]: + """ + Australian Business Number (detect and validate) + """ + for candidate in _ABN_REGEX.findall(doc): + if abn.is_valid(candidate): + yield candidate + + +PII_TASKS = [(PiiEnum.GOV_ID, australian_business_number)] diff --git a/data_tooling/pii-manager/src/pii_manager/lang/en/au/tfn.py b/data_tooling/pii-manager/src/pii_manager/lang/en/au/tfn.py new file mode 100644 index 0000000..3f2384d --- /dev/null +++ b/data_tooling/pii-manager/src/pii_manager/lang/en/au/tfn.py @@ -0,0 +1,27 @@ +""" +Detection and validation of Australian Tax File Number (TFN). + +""" +import re + +from stdnum.au import tfn + +from typing import Iterable + +from pii_manager import PiiEnum + + +_TFN_PATTERN = r"\b (?: \d{3} \s \d{3} \s \d{3} | \d{8,9} ) \b" +_TFN_REGEX = re.compile(_TFN_PATTERN, flags=re.X) + + +def tax_file_number(doc: str) -> Iterable[str]: + """ + Australian Tax File Number (detect and validate) + """ + for candidate in _TFN_REGEX.findall(doc): + if tfn.is_valid(candidate): + yield candidate + + +PII_TASKS = [(PiiEnum.GOV_ID, tax_file_number)] diff --git a/data_tooling/pii-manager/src/pii_manager/lang/en/ca/__init__.py b/data_tooling/pii-manager/src/pii_manager/lang/en/ca/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/data_tooling/pii-manager/src/pii_manager/lang/en/ca/social_insurance_number.py b/data_tooling/pii-manager/src/pii_manager/lang/en/ca/social_insurance_number.py new file mode 100644 index 0000000..fa3be47 --- /dev/null +++ b/data_tooling/pii-manager/src/pii_manager/lang/en/ca/social_insurance_number.py @@ -0,0 +1,28 @@ +""" +Detection and validation of Canadian Social Insurance Number + +Since it contains a check digit, it can be validated. +""" + +import re + +from stdnum.ca import sin + +from typing import Iterable + +from pii_manager import PiiEnum + + +_SIN_REGEX = re.compile(r"\d{3}[-\ ]\d{3}[-\ ]\d{3}", flags=re.X) + + +def social_insurance_number(doc: str) -> Iterable[str]: + """ + Canadian Social Insurance Number (detect and validate) + """ + for candidate in _SIN_REGEX.findall(doc): + if sin.is_valid(candidate): + yield candidate + + +PII_TASKS = [(PiiEnum.GOV_ID, social_insurance_number)] diff --git a/data_tooling/pii-manager/src/pii_manager/lang/en/in_/__init__.py b/data_tooling/pii-manager/src/pii_manager/lang/en/in_/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/data_tooling/pii-manager/src/pii_manager/lang/en/in_/aadhaar.py b/data_tooling/pii-manager/src/pii_manager/lang/en/in_/aadhaar.py new file mode 100644 index 0000000..d056966 --- /dev/null +++ b/data_tooling/pii-manager/src/pii_manager/lang/en/in_/aadhaar.py @@ -0,0 +1,28 @@ +""" +Detection and validation of Indian Aadhaar identity number + +Since it contains a check digit, it can be validated. +""" + +import re + +from stdnum.in_ import aadhaar + +from typing import Iterable + +from pii_manager import PiiEnum + + +_AADHAAR_REGEX = re.compile(r"[2-9]\d{3}\ ?\d{4}\ ?\d{4}", flags=re.X) + + +def aadhaar_number(doc: str) -> Iterable[str]: + """ + Aadhaar identity number from India (detect and validate) + """ + for candidate in _AADHAAR_REGEX.findall(doc): + if aadhaar.is_valid(candidate): + yield candidate + + +PII_TASKS = [(PiiEnum.GOV_ID, aadhaar_number)] diff --git a/data_tooling/pii-manager/src/pii_manager/lang/en/us/__init__.py b/data_tooling/pii-manager/src/pii_manager/lang/en/us/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/data_tooling/pii-manager/src/pii_manager/lang/en/us/social_security_number.py b/data_tooling/pii-manager/src/pii_manager/lang/en/us/social_security_number.py new file mode 100644 index 0000000..92b3dd3 --- /dev/null +++ b/data_tooling/pii-manager/src/pii_manager/lang/en/us/social_security_number.py @@ -0,0 +1,16 @@ +""" +Detection of U.S. Social Security Number. + +We just match on the number, it cannot be +validated using only the number since it does not carry a checksum +""" + +from pii_manager import PiiEnum + + +_SSN_PATTERN = r"(?!000|666|333)0*(?:[0-6][0-9][0-9]|[0-7][0-6][0-9]|[0-7][0-7][0-2])[-\ ](?!00)[0-9]{2}[-\ ](?!0000)[0-9]{4}" + + +PII_TASKS = [ + (PiiEnum.GOV_ID, _SSN_PATTERN, "U.S. Social Security Number (detect only)") +] diff --git a/data_tooling/pii-manager/src/pii_manager/lang/es/__init__.py b/data_tooling/pii-manager/src/pii_manager/lang/es/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/data_tooling/pii-manager/src/pii_manager/lang/es/any/__init__.py b/data_tooling/pii-manager/src/pii_manager/lang/es/any/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/data_tooling/pii-manager/src/pii_manager/lang/es/any/international_phone_number.py b/data_tooling/pii-manager/src/pii_manager/lang/es/any/international_phone_number.py new file mode 100644 index 0000000..f82aa44 --- /dev/null +++ b/data_tooling/pii-manager/src/pii_manager/lang/es/any/international_phone_number.py @@ -0,0 +1,26 @@ +""" +Detection of phone numbers written with international notation (i.e. with +prefix and country code), for ES +""" + + +from pii_manager import PiiEnum + +# The pattern for the regex is the same as for English +from ...en.any.international_phone_number import PATTERN_INT_PHONE + + +PII_TASKS = [ + { + "pii": PiiEnum.PHONE_NUMBER, + "type": "regex", + "task": PATTERN_INT_PHONE, + "name": "international phone number", + "doc": "detect phone numbers that use international notation. Uses language context", + "context": { + "value": ["tf", "teléfono", "telefono"], + "width": [16, 0], + "type": "word", + }, + } +] diff --git a/data_tooling/pii-manager/src/pii_manager/lang/es/es/__init__.py b/data_tooling/pii-manager/src/pii_manager/lang/es/es/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/data_tooling/pii-manager/src/pii_manager/lang/es/es/bank_account.py b/data_tooling/pii-manager/src/pii_manager/lang/es/es/bank_account.py new file mode 100644 index 0000000..149511f --- /dev/null +++ b/data_tooling/pii-manager/src/pii_manager/lang/es/es/bank_account.py @@ -0,0 +1,40 @@ +""" +Spanish bank account numbers (CCC - código cuenta cliente) + +Note: **NOT** IBAN numbers, those are country (& language) independent +""" + +import re + +from typing import Iterable + +from stdnum.es import ccc + +from pii_manager import PiiEnum + +# ---------------------------------------------------------------------------- + +# regex for a Código Cuenta Cliente, with optional spaces separating the pieces +_CCC_PATTERN = r"\d{4}\s?\d{4}\s?\d{2}\s?\d{10}" + +# compiled regex +_REGEX_CCC = None + + +def spanish_bank_ccc(text: str) -> Iterable[str]: + """ + Spanish Bank Accounts (código cuenta cliente, 10-digit code, pre-IBAN), recognize & validate + """ + # Compile regex if needed + global _REGEX_CCC + if _REGEX_CCC is None: + _REGEX_CCC = re.compile(_CCC_PATTERN, flags=re.X) + # Find all CCCs + for item in _REGEX_CCC.findall(text): + if ccc.is_valid(item): + yield item + + +# --------------------------------------------------------------------- + +PII_TASKS = [(PiiEnum.BANK_ACCOUNT, spanish_bank_ccc)] diff --git a/data_tooling/pii-manager/src/pii_manager/lang/es/es/govid.py b/data_tooling/pii-manager/src/pii_manager/lang/es/es/govid.py new file mode 100644 index 0000000..8038acb --- /dev/null +++ b/data_tooling/pii-manager/src/pii_manager/lang/es/es/govid.py @@ -0,0 +1,60 @@ +""" +Spanish Goverment-issued IDs: + - DNI (Documento Nacional de Identidad) + - NIE (Número de Identificación de Extranjero) +""" + +import re + +from typing import Iterable + +from stdnum.es import dni, nie + +from pii_manager import PiiEnum, PiiEntity +from pii_manager.helper import BasePiiTask + +# regex for DNI & NIE +_DNI_PATTERN = r"\d{6,8} -? [A-KJ-NP-TV-Z]" +_NIE_PATTERN = r"[X-Z] \d{7} -? [A-KJ-NP-TV-Z]" + + +class SpanishDniNie(BasePiiTask): + """ + Spanish Government-issued DNI & NIE numbers, recognize & validate + """ + + pii_name = "Spanish DNI and NIE numbers" + + def __init__(self, **kwargs): + super().__init__(**kwargs) + # Compile the regexes + self.dni = re.compile(_DNI_PATTERN, flags=re.X) + self.nie = re.compile(_NIE_PATTERN, flags=re.X) + + def find(self, doc: str) -> Iterable[PiiEntity]: + # DNI + for item in self.dni.finditer(doc): + item_value = item.group() + if dni.is_valid(item_value): + yield PiiEntity( + PiiEnum.GOV_ID, + item.start(), + item_value, + country=self.country, + name="Spanish DNI", + ) + # NIE + for item in self.nie.finditer(doc): + item_value = item.group() + if nie.is_valid(item_value): + yield PiiEntity( + PiiEnum.GOV_ID, + item.start(), + item_value, + country=self.country, + name="Spanish NIE", + ) + + +# Task descriptor +PII_TASKS = [(PiiEnum.GOV_ID, SpanishDniNie)] diff --git a/data_tooling/pii-manager/src/pii_manager/lang/es/mx/__init__.py b/data_tooling/pii-manager/src/pii_manager/lang/es/mx/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/data_tooling/pii-manager/src/pii_manager/lang/es/mx/curp.py b/data_tooling/pii-manager/src/pii_manager/lang/es/mx/curp.py new file mode 100644 index 0000000..9645367 --- /dev/null +++ b/data_tooling/pii-manager/src/pii_manager/lang/es/mx/curp.py @@ -0,0 +1,29 @@ +""" +Detection and validation of Clave Única de Registro de Población for Mexico + +It contains two check digits, so it can be validated. +""" + +import re + +from stdnum.mx import curp as stdnum_curp + +from typing import Iterable + +from pii_manager import PiiEnum + + +_CURP_PATTERN = r"[A-Z] [AEIOU] [A-Z]{2} \d{6} [HM] [A-Z]{5} [0-9A-Z] \d" +_CURP_REGEX = re.compile(_CURP_PATTERN, flags=re.X) + + +def curp(doc: str) -> Iterable[str]: + """ + Mexican Clave Única de Registro de Población (detect and validate) + """ + for candidate in _CURP_REGEX.findall(doc): + if stdnum_curp.is_valid(candidate): + yield candidate + + +PII_TASKS = [(PiiEnum.GOV_ID, curp)] diff --git a/data_tooling/pii-manager/src/pii_manager/lang/fr/__init__.py b/data_tooling/pii-manager/src/pii_manager/lang/fr/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/data_tooling/pii-manager/src/pii_manager/lang/fr/ca/__init__.py b/data_tooling/pii-manager/src/pii_manager/lang/fr/ca/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/data_tooling/pii-manager/src/pii_manager/lang/fr/ca/social_insurance_number.py b/data_tooling/pii-manager/src/pii_manager/lang/fr/ca/social_insurance_number.py new file mode 100644 index 0000000..e3c3d42 --- /dev/null +++ b/data_tooling/pii-manager/src/pii_manager/lang/fr/ca/social_insurance_number.py @@ -0,0 +1,4 @@ +""" +Reuse the SIN code implemented for en +""" +from pii_manager.lang.en.ca.social_insurance_number import PII_TASKS diff --git a/data_tooling/pii-manager/src/pii_manager/lang/pt/__init__.py b/data_tooling/pii-manager/src/pii_manager/lang/pt/__init__.py new file mode 100644 index 0000000..22bfc32 --- /dev/null +++ b/data_tooling/pii-manager/src/pii_manager/lang/pt/__init__.py @@ -0,0 +1,5 @@ +# Folder for language-independent tasks +LANG_ANY = "any" + +# Country-independent tasks +COUNTRY_ANY = "any" diff --git a/data_tooling/pii-manager/src/pii_manager/lang/pt/br/__init__.py b/data_tooling/pii-manager/src/pii_manager/lang/pt/br/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/data_tooling/pii-manager/src/pii_manager/lang/pt/br/cpf.py b/data_tooling/pii-manager/src/pii_manager/lang/pt/br/cpf.py new file mode 100644 index 0000000..607de1f --- /dev/null +++ b/data_tooling/pii-manager/src/pii_manager/lang/pt/br/cpf.py @@ -0,0 +1,29 @@ +""" +Detection and validation of the identifier for Brazilian Cadastro de Pessoa +Física + +It contains two check digits, so it can be validated. +""" + +import re + +from stdnum.br import cpf + +from typing import Iterable + +from pii_manager import PiiEnum + + +_CPF_REGEX = re.compile(r"\d{3} \. \d{3} \. \d{3} - \d{2}", flags=re.X) + + +def cadastro_pessoa_fisica(doc: str) -> Iterable[str]: + """ + Brazilian número de inscrição no Cadastro de Pessoas Físicas (detect and validate) + """ + for candidate in _CPF_REGEX.findall(doc): + if cpf.is_valid(candidate): + yield candidate + + +PII_TASKS = [(PiiEnum.GOV_ID, cadastro_pessoa_fisica)] diff --git a/data_tooling/pii-manager/src/pii_manager/lang/pt/pt/__init__.py b/data_tooling/pii-manager/src/pii_manager/lang/pt/pt/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/data_tooling/pii-manager/src/pii_manager/lang/pt/pt/govid.py b/data_tooling/pii-manager/src/pii_manager/lang/pt/pt/govid.py new file mode 100644 index 0000000..b87195d --- /dev/null +++ b/data_tooling/pii-manager/src/pii_manager/lang/pt/pt/govid.py @@ -0,0 +1,61 @@ +""" +Portuguese Goverment-issued IDs: + - NIF (Número de identificação fiscal) + - CC (Número de Cartão de Cidadão) +""" + +import re + +from typing import Iterable + +from stdnum.pt import nif, cc + +from pii_manager import PiiEnum, PiiEntity +from pii_manager.helper import BasePiiTask + + +# regex for NIF & CC +_NIF_PATTERN = r"(?: PT \x20?)? (?: \d{3} \x20 \d{3} \x20 \d{3} | \d{9} )" +_CC_PATTERN = r"\d{8} \x20? \d \x20? [A-Z0-9]{2}\d" + + +class PortugueseNifCc(BasePiiTask): + """ + Portuguese Government-issued NIF & CC numbers, recognize & validate + """ + + pii_name = "Portuguese NIF and CC numbers" + + def __init__(self, **kwargs): + super().__init__(**kwargs) + # Compile the regexes + self.nif = re.compile(_NIF_PATTERN, flags=re.X) + self.cc = re.compile(_CC_PATTERN, flags=re.X) + + def find(self, doc: str) -> Iterable[PiiEntity]: + # NIF + for item in self.nif.finditer(doc): + item_value = item.group() + if nif.is_valid(item_value): + yield PiiEntity( + PiiEnum.GOV_ID, + item.start(), + item_value, + country=self.country, + name="Portuguese NIF", + ) + # CC + for item in self.cc.finditer(doc): + item_value = item.group() + if cc.is_valid(item_value): + yield PiiEntity( + PiiEnum.GOV_ID, + item.start(), + item_value, + country=self.country, + name="Portuguese CC", + ) + + +# Task descriptor +PII_TASKS = [(PiiEnum.GOV_ID, PortugueseNifCc)] diff --git a/data_tooling/pii-manager/src/pii_manager/lang/zh/__init__.py b/data_tooling/pii-manager/src/pii_manager/lang/zh/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/data_tooling/pii-manager/src/pii_manager/lang/zh/cn/__init__.py b/data_tooling/pii-manager/src/pii_manager/lang/zh/cn/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/data_tooling/pii-manager/src/pii_manager/lang/zh/cn/gov_id.py b/data_tooling/pii-manager/src/pii_manager/lang/zh/cn/gov_id.py new file mode 100644 index 0000000..eea1c27 --- /dev/null +++ b/data_tooling/pii-manager/src/pii_manager/lang/zh/cn/gov_id.py @@ -0,0 +1,35 @@ +""" +Detection of various government-issued IDs for China: + - Resident Identification Card number (this can be validated) + - Passport number (this cannot) +""" + +import re +from typing import Iterable + +from pii_manager import PiiEnum + +from stdnum.cn import ric + + +# Detect candidates (separately) for RIC and passport-like numbers +_GOV_ID_PATTERN = r"(? Iterable[str]: + """ + Chinese government-issued identifiers: + - RIC (Resident Identification Card number), detect and validate + - Passport number, detect only + """ + for g in _GOV_ID_REGEX.finditer(doc): + if g.group(1) and ric.is_valid(g.group(1)): + yield g.group(1) + elif g.group(2): + yield g.group(2) + + +PII_TASKS = [(PiiEnum.GOV_ID, ric_or_passport)] diff --git a/data_tooling/pii-manager/src/pii_manager/lang/zh/cn/misc.py b/data_tooling/pii-manager/src/pii_manager/lang/zh/cn/misc.py new file mode 100644 index 0000000..7e1710d --- /dev/null +++ b/data_tooling/pii-manager/src/pii_manager/lang/zh/cn/misc.py @@ -0,0 +1,35 @@ +""" +Detection of various Chinese PII elements +""" + + +from pii_manager import PiiEnum + + +_PATTERNS = { + "STREET_ADDRESS": r"""(\p{Han}{1,4} (自治区|省))? + \p{Han}{1,4} + ((?" + + def __eq__(self, other): + return ( + self.elem == other.elem + and self.pos == other.pos + and self.value == other.value + and self.country == other.country + and self.name == other.name + ) + + def to_json(self) -> Dict: + """ + Return the object data as a dict that can then be serialised as JSON + """ + return piientity_asdict(self) + + +def piientity_asdict(pii: PiiEntity, name: bool = None, country: bool = None) -> Dict: + """ + Create a dictionary from a PiiEntity object + :param country: add country information: always (True), never (False), + only if defined (None) + """ + n = {"name": pii.name} if name or country is None and pii.name else {} + d = {"type": pii.elem.name, **n, "value": pii.value, "pos": pii.pos} + if country or country is None and pii.country: + d["country"] = pii.country + return d diff --git a/data_tooling/pii-manager/src/pii_manager/piienum.py b/data_tooling/pii-manager/src/pii_manager/piienum.py new file mode 100644 index 0000000..3a6e16f --- /dev/null +++ b/data_tooling/pii-manager/src/pii_manager/piienum.py @@ -0,0 +1,26 @@ +""" +Enumeration that contains all defined PII elements + +Order is significant, in the sense that, on an processing job, tasks coming +earlier in the enum will be tried first. Hence the more generic tasks (tasks +that might collide with more specific ones) should come last +""" + +from enum import Enum, auto + + +class PiiEnum(str, Enum): + CREDIT_CARD = auto() + BITCOIN_ADDRESS = auto() + IP_ADDRESS = auto() + EMAIL_ADDRESS = auto() + AGE = auto() + BIRTH_DATE = auto() + DEATH_DATE = auto() + NORP = auto() + DISEASE = auto() + BANK_ACCOUNT = auto() + GOV_ID = auto() + PHONE_NUMBER = auto() + LICENSE_PLATE = auto() + STREET_ADDRESS = auto() diff --git a/data_tooling/pii-manager/test/data/extract-block.ndjson b/data_tooling/pii-manager/test/data/extract-block.ndjson new file mode 100644 index 0000000..433b9df --- /dev/null +++ b/data_tooling/pii-manager/test/data/extract-block.ndjson @@ -0,0 +1,2 @@ +{"type": "CREDIT_CARD", "name": "credit card", "value": "4273 9666 4581 5642", "pos": 25} +{"type": "BITCOIN_ADDRESS", "name": "bitcoin address", "value": "1AGNa15ZQXAZUgFiqJ2i7Z2DPU2J6hW62i", "pos": 86} diff --git a/data_tooling/pii-manager/test/data/extract-line.ndjson b/data_tooling/pii-manager/test/data/extract-line.ndjson new file mode 100644 index 0000000..1d18fe4 --- /dev/null +++ b/data_tooling/pii-manager/test/data/extract-line.ndjson @@ -0,0 +1,2 @@ +{"type": "CREDIT_CARD", "name": "credit card", "value": "4273 9666 4581 5642", "pos": 25, "line": 1} +{"type": "BITCOIN_ADDRESS", "name": "bitcoin address", "value": "1AGNa15ZQXAZUgFiqJ2i7Z2DPU2J6hW62i", "pos": 10, "line": 2} diff --git a/data_tooling/pii-manager/test/data/extract-sentence.ndjson b/data_tooling/pii-manager/test/data/extract-sentence.ndjson new file mode 100644 index 0000000..2e7e122 --- /dev/null +++ b/data_tooling/pii-manager/test/data/extract-sentence.ndjson @@ -0,0 +1,2 @@ +{"type": "CREDIT_CARD", "name": "credit card", "value": "4273 9666 4581 5642", "pos": 25, "sentence": 1} +{"type": "BITCOIN_ADDRESS", "name": "bitcoin address", "value": "1AGNa15ZQXAZUgFiqJ2i7Z2DPU2J6hW62i", "pos": 86, "sentence": 1} diff --git a/data_tooling/pii-manager/test/data/full-block.ndjson b/data_tooling/pii-manager/test/data/full-block.ndjson new file mode 100644 index 0000000..084c4e3 --- /dev/null +++ b/data_tooling/pii-manager/test/data/full-block.ndjson @@ -0,0 +1 @@ +{"text": "My credit card number is 4273 9666 4581 5642 and I have used it to buy BTCs\nstored at 1AGNa15ZQXAZUgFiqJ2i7Z2DPU2J6hW62i. This one, however, is not a\ncredit card number: 4273 9666 4581 5643\n", "entities": [{"type": "CREDIT_CARD", "name": "credit card", "value": "4273 9666 4581 5642", "pos": 25}, {"type": "BITCOIN_ADDRESS", "name": "bitcoin address", "value": "1AGNa15ZQXAZUgFiqJ2i7Z2DPU2J6hW62i", "pos": 86}]} diff --git a/data_tooling/pii-manager/test/data/full-line.ndjson b/data_tooling/pii-manager/test/data/full-line.ndjson new file mode 100644 index 0000000..a5f5f2e --- /dev/null +++ b/data_tooling/pii-manager/test/data/full-line.ndjson @@ -0,0 +1 @@ +{"text": "My credit card number is 4273 9666 4581 5642 and I have used it to buy BTCs\n", "entities": [{"type": "CREDIT_CARD", "name": "credit card", "value": "4273 9666 4581 5642", "pos": 25}]}{"text": "stored at 1AGNa15ZQXAZUgFiqJ2i7Z2DPU2J6hW62i. This one, however, is not a\n", "entities": [{"type": "BITCOIN_ADDRESS", "name": "bitcoin address", "value": "1AGNa15ZQXAZUgFiqJ2i7Z2DPU2J6hW62i", "pos": 10}]}{"text": "credit card number: 4273 9666 4581 5643\n", "entities": []} diff --git a/data_tooling/pii-manager/test/data/full-sentence.ndjson b/data_tooling/pii-manager/test/data/full-sentence.ndjson new file mode 100644 index 0000000..f109a31 --- /dev/null +++ b/data_tooling/pii-manager/test/data/full-sentence.ndjson @@ -0,0 +1 @@ +{"text": "My credit card number is 4273 9666 4581 5642 and I have used it to buy BTCs\nstored at 1AGNa15ZQXAZUgFiqJ2i7Z2DPU2J6hW62i. ", "entities": [{"type": "CREDIT_CARD", "name": "credit card", "value": "4273 9666 4581 5642", "pos": 25}, {"type": "BITCOIN_ADDRESS", "name": "bitcoin address", "value": "1AGNa15ZQXAZUgFiqJ2i7Z2DPU2J6hW62i", "pos": 86}]}{"text": "This one, however, is not a\ncredit card number: 4273 9666 4581 5643\n", "entities": []} diff --git a/data_tooling/pii-manager/test/data/orig.txt b/data_tooling/pii-manager/test/data/orig.txt new file mode 100644 index 0000000..af5c330 --- /dev/null +++ b/data_tooling/pii-manager/test/data/orig.txt @@ -0,0 +1,3 @@ +My credit card number is 4273 9666 4581 5642 and I have used it to buy BTCs +stored at 1AGNa15ZQXAZUgFiqJ2i7Z2DPU2J6hW62i. This one, however, is not a +credit card number: 4273 9666 4581 5643 diff --git a/data_tooling/pii-manager/test/data/replace.txt b/data_tooling/pii-manager/test/data/replace.txt new file mode 100644 index 0000000..69a9468 --- /dev/null +++ b/data_tooling/pii-manager/test/data/replace.txt @@ -0,0 +1,3 @@ +My credit card number is and I have used it to buy BTCs +stored at . This one, however, is not a +credit card number: 4273 9666 4581 5643 diff --git a/data_tooling/pii-manager/test/data/tag.txt b/data_tooling/pii-manager/test/data/tag.txt new file mode 100644 index 0000000..da52224 --- /dev/null +++ b/data_tooling/pii-manager/test/data/tag.txt @@ -0,0 +1,3 @@ +My credit card number is and I have used it to buy BTCs +stored at . This one, however, is not a +credit card number: 4273 9666 4581 5643 diff --git a/data_tooling/pii-manager/test/data/taskfile-error.json b/data_tooling/pii-manager/test/data/taskfile-error.json new file mode 100644 index 0000000..52e167a --- /dev/null +++ b/data_tooling/pii-manager/test/data/taskfile-error.json @@ -0,0 +1,17 @@ +[ + { + "pii": "IP_ADDRESS", + "type": "regex", + "task": "\\b (?: (?: 25[0-5] | 2[0-4][0-9] | [01]?[0-9][0-9]? ) \\. ){3} (?: 25[0-5] | 2[0-4][0-9] | [01]?[0-9][0-9]?) \\b" + }, + { + "pii": "NOT_A_VALID_PII_TASK_CLASS", + "type": "call", + "task": "pii_manager.lang.any.bitcoin_address.bitcoin_address" + }, + { + "pii": "CREDIT_CARD", + "type": "PiiClass", + "task": "pii_manager.lang.any.credit_card.CreditCard" + } +] diff --git a/data_tooling/pii-manager/test/data/taskfile.json b/data_tooling/pii-manager/test/data/taskfile.json new file mode 100644 index 0000000..53f7231 --- /dev/null +++ b/data_tooling/pii-manager/test/data/taskfile.json @@ -0,0 +1,23 @@ +[ + { + "pii": "IP_ADDRESS", + "lang": "any", + "type": "regex", + "task": "\\b (?: (?: 25[0-5] | 2[0-4][0-9] | [01]?[0-9][0-9]? ) \\. ){3} (?: 25[0-5] | 2[0-4][0-9] | [01]?[0-9][0-9]?) \\b", + "doc": "ip address detection via regex" + }, + { + "pii": "BITCOIN_ADDRESS", + "lang": "any", + "type": "callable", + "task": "pii_manager.lang.any.bitcoin_address.bitcoin_address", + "doc": "bitcoin address detection" + }, + { + "pii": "CREDIT_CARD", + "lang": "en", + "type": "PiiTask", + "task": "pii_manager.lang.any.credit_card.CreditCard", + "doc": "credit card number detection" + } +] diff --git a/data_tooling/pii-manager/test/unit/api/test_file.py b/data_tooling/pii-manager/test/unit/api/test_file.py new file mode 100644 index 0000000..6d5932c --- /dev/null +++ b/data_tooling/pii-manager/test/unit/api/test_file.py @@ -0,0 +1,72 @@ +from pathlib import Path +import tempfile + +import pytest + +from pii_manager import PiiEnum +from pii_manager.api import process_file + + +def datafile(name: str) -> str: + return Path(__file__).parents[2] / "data" / name + + +def readfile(name: str) -> str: + with open(name, "rt", encoding="utf-8") as f: + return f.read().strip() + + +@pytest.mark.parametrize("mode", ["replace", "tag", "extract", "full"]) +def test10_line(mode): + """ + Test splitting the file by lines + """ + with tempfile.NamedTemporaryFile() as f: + tasks = [PiiEnum.CREDIT_CARD, PiiEnum.BITCOIN_ADDRESS] + stats = process_file(datafile("orig.txt"), f.name, "en", tasks=tasks, mode=mode) + exp = {"calls": 3, "CREDIT_CARD": 1, "BITCOIN_ADDRESS": 1} + assert stats == exp + + name = mode + (".txt" if mode in ("replace", "tag") else "-line.ndjson") + exp = readfile(datafile(name)) + got = readfile(f.name) + # print(got) + assert got == exp + + +@pytest.mark.parametrize("mode", ["replace", "tag", "extract", "full"]) +def test20_block(mode): + """ + Test whole files + """ + with tempfile.NamedTemporaryFile() as f: + tasks = [PiiEnum.CREDIT_CARD, PiiEnum.BITCOIN_ADDRESS] + stats = process_file( + datafile("orig.txt"), f.name, "en", tasks=tasks, mode=mode, split="block" + ) + exp = {"calls": 1, "CREDIT_CARD": 1, "BITCOIN_ADDRESS": 1} + assert stats == exp + + name = mode + (".txt" if mode in ("replace", "tag") else "-block.ndjson") + exp = readfile(datafile(name)) + got = readfile(f.name) + assert got == exp + + +@pytest.mark.parametrize("mode", ["replace", "tag", "extract", "full"]) +def test30_sentence(mode): + """ + Test splitting the file by sentences + """ + with tempfile.NamedTemporaryFile() as f: + tasks = [PiiEnum.CREDIT_CARD, PiiEnum.BITCOIN_ADDRESS] + stats = process_file( + datafile("orig.txt"), f.name, "en", tasks=tasks, mode=mode, split="sentence" + ) + exp = {"calls": 2, "CREDIT_CARD": 1, "BITCOIN_ADDRESS": 1} + assert stats == exp + + name = mode + (".txt" if mode in ("replace", "tag") else "-sentence.ndjson") + exp = readfile(datafile(name)) + got = readfile(f.name) + assert got == exp diff --git a/data_tooling/pii-manager/test/unit/api/test_file_taskfile.py b/data_tooling/pii-manager/test/unit/api/test_file_taskfile.py new file mode 100644 index 0000000..722dfa8 --- /dev/null +++ b/data_tooling/pii-manager/test/unit/api/test_file_taskfile.py @@ -0,0 +1,86 @@ +from pathlib import Path +import tempfile + +import pytest + +from pii_manager import PiiEnum +from pii_manager.api import process_file, PiiManager +from pii_manager.api.file import read_taskfile, add_taskfile +from pii_manager.helper.exception import InvArgException + + +def datafile(name: str) -> str: + return Path(__file__).parents[2] / "data" / name + + +def readfile(name: str) -> str: + with open(name, "rt", encoding="utf-8") as f: + return f.read().strip() + + +def test10_taskfile(): + """ + Read a taskfile + """ + taskfile = datafile("taskfile.json") + tasklist = read_taskfile(taskfile) + assert len(tasklist) == 3 + assert tasklist[0]["pii"] == PiiEnum.IP_ADDRESS + assert tasklist[1]["pii"] == PiiEnum.BITCOIN_ADDRESS + assert tasklist[2]["pii"] == PiiEnum.CREDIT_CARD + + +def test11_taskfile_error(): + """ + Read a taskfile with an error + """ + taskfile = datafile("taskfile-error.json") + with pytest.raises(InvArgException): + read_taskfile(taskfile) + + +def test12_taskfile(): + """ + Read a taskfile + """ + taskfile = datafile("taskfile.json") + proc = PiiManager("en") + add_taskfile(taskfile, proc) + got = proc.task_info() + exp = { + (PiiEnum.CREDIT_CARD, None): [("credit card", "credit card number detection")], + (PiiEnum.BITCOIN_ADDRESS, None): [ + ("bitcoin address", "bitcoin address detection") + ], + (PiiEnum.IP_ADDRESS, None): [ + ("regex for ip_address", "ip address detection via regex") + ], + } + assert exp == got + + +def test13_taskfile_err(): + """ + Read a taskfile, try to add to an object with a language mismatch + """ + taskfile = datafile("taskfile.json") + proc = PiiManager("fr") + with pytest.raises(InvArgException): + add_taskfile(taskfile, proc) + + +def test20_taskfile(): + """ + Read a taskfile, process data + """ + with tempfile.NamedTemporaryFile() as f: + stats = process_file( + datafile("orig.txt"), f.name, "en", taskfile=datafile("taskfile.json") + ) + exp = {"calls": 3, "CREDIT_CARD": 1, "BITCOIN_ADDRESS": 1} + assert stats == exp + + exp = readfile(datafile("replace.txt")) + got = readfile(f.name) + # print(got) + assert got == exp diff --git a/data_tooling/pii-manager/test/unit/api/test_manager.py b/data_tooling/pii-manager/test/unit/api/test_manager.py new file mode 100644 index 0000000..5f74dbf --- /dev/null +++ b/data_tooling/pii-manager/test/unit/api/test_manager.py @@ -0,0 +1,37 @@ +from io import StringIO + +from pii_manager import PiiEnum +from pii_manager.api import PiiManager + + +TEST = ( + "El número de la tarjeta de crédito es 4273 9666 4581 5642", + "El número de la tarjeta de crédito es ", +) + + +def test10_constructor(): + obj = PiiManager("es", None, PiiEnum.CREDIT_CARD) + assert obj.tasks[0].pii == PiiEnum.CREDIT_CARD + assert str(obj) == "" + + +def test20_info(): + obj = PiiManager("es", None, PiiEnum.CREDIT_CARD) + info = obj.task_info() + + exp = { + (PiiEnum.CREDIT_CARD, None,): [ + ( + "credit card", + "Credit card numbers for most international credit cards (detect & validate)", + ) + ] + } + assert info == exp + + +def test20_call(): + obj = PiiManager("es", None, PiiEnum.CREDIT_CARD) + anon = obj(TEST[0]) + assert anon == TEST[1] diff --git a/data_tooling/pii-manager/test/unit/api/test_manager_add.py b/data_tooling/pii-manager/test/unit/api/test_manager_add.py new file mode 100644 index 0000000..a61e5ee --- /dev/null +++ b/data_tooling/pii-manager/test/unit/api/test_manager_add.py @@ -0,0 +1,91 @@ +""" +Test adding an external Pii task +""" + +import re + +from pii_manager import PiiEnum, PiiEntity +from pii_manager.api import PiiManager +from pii_manager.lang import COUNTRY_ANY +from pii_manager.helper.base import BasePiiTask + + +# --------------------------------------------------------------------- + +DUMMY_REGEX = { + "pii": PiiEnum.DISEASE, + "type": "regex", + "task": r"""\b(cancer|leuka?emia|aids)\b""", + "lang": "en", + "country": COUNTRY_ANY, + "name": "disease names", + "doc": "a toy example to match some disease names", +} + + +TEST_REGEX = [ + ( + "Alvin had cancer detected and his email is alvin@anywhere.com", + "Alvin had detected and his email is ", + ) +] + + +def test100_info(): + obj = PiiManager("en", None, PiiEnum.EMAIL_ADDRESS) + obj.add_tasks([DUMMY_REGEX]) + exp = { + (PiiEnum.EMAIL_ADDRESS, None): [("regex for email_address", "Email address")], + (PiiEnum.DISEASE, None): [ + ("disease names", "a toy example to match some disease names") + ], + } + assert obj.task_info() == exp + + +def test110_call(): + obj = PiiManager("en", None, PiiEnum.EMAIL_ADDRESS) + obj.add_tasks([DUMMY_REGEX]) + + for (doc, exp) in TEST_REGEX: + got = obj(doc) + assert got == exp + + +# --------------------------------------------------------------------- + + +class DummyPii(BasePiiTask): + def find(self, doc): + for r in re.finditer(r"\d{4}-\w", doc): + yield PiiEntity( + PiiEnum.GOV_ID, + r.start(), + r.group(), + country=self.country, + name=self.name, + ) + + +DUMMY_CLASS = { + "pii": PiiEnum.GOV_ID, + "type": "PiiTask", + "task": "unit.api.test_manager_add.DummyPii", + "lang": "en", + "country": "vo", + "doc": "a toy example to match some disease names", +} + + +TEST_CLASS = [ + ("Jeltz has vogonian ID number 1234-J", "Jeltz has vogonian ID number ") +] + + +def test200_call(): + obj = PiiManager("en") + obj.add_tasks([DUMMY_CLASS]) + + for (doc, exp) in TEST_CLASS: + got = obj(doc) + assert got == exp diff --git a/data_tooling/pii-manager/test/unit/api/test_manager_ctx.py b/data_tooling/pii-manager/test/unit/api/test_manager_ctx.py new file mode 100644 index 0000000..f74701f --- /dev/null +++ b/data_tooling/pii-manager/test/unit/api/test_manager_ctx.py @@ -0,0 +1,69 @@ +""" +Test base objects with context +""" + +from pii_manager import PiiEnum, PiiEntity +from pii_manager.api import PiiManager + + +def _pii(pos): + return PiiEntity(PiiEnum.GOV_ID, pos, "3451-K", country="vo", name="vogonian ID") + + +TEST = [ + ("my Vogon ID is 3451-K", [_pii(15)]), + ("the number 3451-K is my Vogonian ID", [_pii(11)]), + ("the Vogon ID are 3451-K", []), # context outside window + ("my Betelgeuse ID is 3451-K", []), # context does not match +] + + +# ------------------------------------------------------------------------ + +DUMMY_REGEX = { + "pii": PiiEnum.GOV_ID, + "type": "regex", + "task": r"""\b\d{4}-\w\b""", + "lang": "en", + "name": "vogonian ID", + "country": "vo", + "doc": "a toy example to match a government id", + "context": {"value": ["Vogon ID", "vogonian id"], "width": [12, 20]}, +} + + +def test10_context_regex(): + """ + Check a PII task with contexts, regex variant + """ + obj = PiiManager("en", mode="extract") + obj.add_tasks([DUMMY_REGEX]) + for (text, exp) in TEST: + got = obj(text) + assert list(got) == exp + + +# ------------------------------------------------------------------------ + + +DUMMY_CLASS = { + "pii": PiiEnum.GOV_ID, + "type": "PiiTask", + "task": "unit.api.test_manager_add.DummyPii", + "lang": "en", + "country": "vo", + "name": "vogonian ID", + "doc": "a toy example to match a government id", + "context": {"value": ["Vogon ID", "vogonian id"], "width": [12, 20]}, +} + + +def test20_context_class(): + """ + Check a PII task with contexts, class variant + """ + obj = PiiManager("en", mode="extract") + obj.add_tasks([DUMMY_CLASS]) + for (text, exp) in TEST: + got = obj(text) + assert list(got) == exp diff --git a/data_tooling/pii-manager/test/unit/helper/test_base.py b/data_tooling/pii-manager/test/unit/helper/test_base.py new file mode 100644 index 0000000..34fdc70 --- /dev/null +++ b/data_tooling/pii-manager/test/unit/helper/test_base.py @@ -0,0 +1,55 @@ +import pytest + +from pii_manager import PiiEnum, PiiEntity +from pii_manager.helper.base import BasePiiTask +from pii_manager.helper.exception import PiiUnimplemented, InvArgException + +import pii_manager.helper.base as mod + + +def test10_base(): + """ + Create base object + """ + task_spec = {"pii": PiiEnum.BITCOIN_ADDRESS, "lang": "es", "name": "example"} + task = mod.BasePiiTask(**task_spec) + assert task.pii == PiiEnum.BITCOIN_ADDRESS + assert task.lang == "es" + assert task.name == "example" + + with pytest.raises(PiiUnimplemented): + task("blah") + + +def test20_regex(): + """ + Test regex object + """ + task_spec = {"pii": PiiEnum.CREDIT_CARD, "lang": "es", "name": "example"} + task = mod.RegexPiiTask(r"\d{4}", **task_spec) + + got = list(task("number 1234 and number 3451")) + exp = [ + PiiEntity(PiiEnum.CREDIT_CARD, 7, "1234", name="example"), + PiiEntity(PiiEnum.CREDIT_CARD, 23, "3451", name="example"), + ] + assert exp == got + + +def test30_callable(): + """ + Test callable object + """ + + def example(i: str): + return ["1234", "3451"] + + task_spec = {"pii": PiiEnum.CREDIT_CARD, "lang": "es", "name": "example"} + task = mod.CallablePiiTask(example, **task_spec) + + got = list(task("number 1234 and number 3451")) + exp = [ + PiiEntity(PiiEnum.CREDIT_CARD, 7, "1234", name="example"), + PiiEntity(PiiEnum.CREDIT_CARD, 23, "3451", name="example"), + ] + assert exp == got diff --git a/data_tooling/pii-manager/test/unit/helper/test_context.py b/data_tooling/pii-manager/test/unit/helper/test_context.py new file mode 100644 index 0000000..6a15886 --- /dev/null +++ b/data_tooling/pii-manager/test/unit/helper/test_context.py @@ -0,0 +1,97 @@ +""" +Test the context checking function +""" +import pytest + +import pii_manager.helper.context as mod +from pii_manager.helper.exception import InvArgException + +TEST_TRUE = [ + ("a special number is 34512", ["special number"]), + ("a special number is 34512", "special number"), + ("a special number is 34512", {"value": "special number"}), + ("a special number is 34512", {"value": "special number", "width": 20}), + ("a special number is 34512", {"value": "special number", "width": [20, 20]}), + ( + "a special number is 34512", + {"value": "special number", "width": [20, 20], "type": "string"}, + ), + ( + "special numbering is 34512", + {"value": "special number", "width": 20, "type": "string"}, + ), + ( + "a special number is 34512", + {"value": "special number", "width": [20, 20], "type": "word"}, + ), + ( + "a special number is 34512", + {"value": r"special\snumber", "width": [20, 20], "type": "regex"}, + ), + ( + "a special number is 34512", + {"value": r"(?:special|standard)\snumber", "width": [20, 20], "type": "regex"}, + ), + ( + "special numbering is 34512", + {"value": r"\bspecial\snumber(?:ing)?\b", "width": 30, "type": "regex"}, + ), +] + + +TEST_FALSE = [ + # non-matching string + ("a special tiny number is 34512", ["special number"]), + # too small context width + ("a special number is 34512", {"value": "special number", "width": 8}), + # not full words + ( + "special numbering 34512", + {"value": "special number", "width": 20, "type": "word"}, + ), + # not a valid extended regex (it has whitespace) + ( + "special numbering 34512", + {"value": "special number", "width": 20, "type": "regex"}, + ), + # marked as a string, while it should be regex + ( + "special numbering is 34512", + {"value": r"\bspecial\snumber(?:ing)?\b", "width": 30, "type": "string"}, + ), +] + + +TEST_ERROR = [ + None, + "", + ["special number", ""], + {"value": "special number", "width": 20, "type": "not-a-type"}, +] + + +def test10_context_true(): + """ + Check valid contexts + """ + for (text, context) in TEST_TRUE: + spec = mod.context_spec(context) + assert mod.context_check(text, spec, 20) is True + + +def test20_context_false(): + """ + Check invalid contexts + """ + for (text, context) in TEST_FALSE: + spec = mod.context_spec(context) + assert mod.context_check(text, spec, 20) is False + + +def test20_context_error(): + """ + Check invalid context spec + """ + for context in TEST_ERROR: + with pytest.raises(InvArgException): + mod.context_spec(context) diff --git a/data_tooling/pii-manager/test/unit/helper/test_norm.py b/data_tooling/pii-manager/test/unit/helper/test_norm.py new file mode 100644 index 0000000..0a1b73b --- /dev/null +++ b/data_tooling/pii-manager/test/unit/helper/test_norm.py @@ -0,0 +1,12 @@ +import pii_manager.helper.normalizer as mod + + +TEST = [("the Social Security\nNumber is 34512", "the social security number is 34512")] + + +def test10_normalizer(): + """ + Create base object + """ + for (text, exp) in TEST: + assert mod.normalize(text, "en", whitespace=True, lowercase=True) == exp diff --git a/data_tooling/pii-manager/test/unit/helper/test_taskdict.py b/data_tooling/pii-manager/test/unit/helper/test_taskdict.py new file mode 100644 index 0000000..eb61d92 --- /dev/null +++ b/data_tooling/pii-manager/test/unit/helper/test_taskdict.py @@ -0,0 +1,265 @@ +import pytest + +from pii_manager import PiiEnum +from pii_manager.lang import LANG_ANY +from pii_manager.helper.base import BasePiiTask +import pii_manager.helper.taskdict as mod + + +def test10_lang(): + """ + Check the presence of a minimum set of languages in the dict + """ + taskdict = mod.get_taskdict() + for lang in (LANG_ANY, "en", "es", "fr", "zh"): + assert lang in taskdict + + +def test20_lang_any(): + """ + Test taskdict contents + """ + taskdict = mod.get_taskdict() + assert len(taskdict) >= 2 + + # Find one element that should be there + tasklist = taskdict[LANG_ANY][PiiEnum.CREDIT_CARD.name] + + # Check its contents + assert isinstance(tasklist, list) + assert isinstance(tasklist[0], dict) + + elem = tasklist[0] + assert len(elem) == 7 + assert sorted(elem.keys()) == [ + "country", + "doc", + "lang", + "name", + "pii", + "task", + "type", + ] + + assert elem["country"] is None + assert elem["lang"] == "any" + assert elem["pii"] == PiiEnum.CREDIT_CARD + assert issubclass(elem["task"], BasePiiTask) + assert elem["type"] == "PiiTask" + assert elem["name"] == "credit card" + assert ( + elem["doc"] + == "Credit card numbers for most international credit cards (detect & validate)" + ) + + +_TASK = [ + (PiiEnum.CREDIT_CARD, r"\d16", "a toy Credit Card example"), + { + "pii": PiiEnum.CREDIT_CARD, + "type": "regex", + "task": r"\d16", + "doc": "a toy Credit Card example", + }, +] + + +@pytest.mark.parametrize("task", _TASK) +def test31_task(task): + """ + Check the function parsing a PII_TASKS list, single entry + """ + subdict = mod.build_subdict([task], lang="en") + + assert len(subdict) == 1 + assert isinstance(subdict, dict) + + assert PiiEnum.CREDIT_CARD.name in subdict + tasklist = subdict[PiiEnum.CREDIT_CARD.name] + assert isinstance(tasklist, list) + assert len(tasklist) == 1 + + assert tasklist[0] == { + "pii": PiiEnum.CREDIT_CARD, + "lang": "en", + "country": None, + "type": "regex", + "task": r"\d16", + "name": "regex for credit_card", + "doc": "a toy Credit Card example", + } + + +def test32_task_multiple_same(): + """ + Check the function parsing a PII_TASKS list, multiple entries, same task + """ + subdict = mod.build_subdict(_TASK, lang="es") + + assert len(subdict) == 1 + assert isinstance(subdict, dict) + + assert PiiEnum.CREDIT_CARD.name in subdict + tasklist = subdict[PiiEnum.CREDIT_CARD.name] + assert isinstance(tasklist, list) + assert len(tasklist) == 2 + + exp = { + "pii": PiiEnum.CREDIT_CARD, + "lang": "es", + "country": None, + "type": "regex", + "task": r"\d16", + "name": "regex for credit_card", + "doc": "a toy Credit Card example", + } + assert tasklist[0] == exp + assert tasklist[1] == exp + + +def test33_task_multiple_different(): + """ + Check the function parsing a PII_TASKS list, multiple different entries + """ + + def toy_example(x): + """another toy example""" + return x + + PII_TASKS = [ + (PiiEnum.CREDIT_CARD, r"\d16", "a toy Credit Card example"), + (PiiEnum.BITCOIN_ADDRESS, toy_example), + ] + subdict = mod.build_subdict(PII_TASKS, "zh") + + assert isinstance(subdict, dict) + assert len(subdict) == 2 + + exp1 = { + "pii": PiiEnum.CREDIT_CARD, + "lang": "zh", + "country": None, + "type": "regex", + "task": r"\d16", + "name": "regex for credit_card", + "doc": "a toy Credit Card example", + } + assert subdict[PiiEnum.CREDIT_CARD.name] == [exp1] + + exp2 = { + "pii": PiiEnum.BITCOIN_ADDRESS, + "lang": "zh", + "country": None, + "type": "callable", + "task": toy_example, + "name": "toy example", + "doc": "another toy example", + } + + assert subdict[PiiEnum.BITCOIN_ADDRESS.name] == [exp2] + + +def test34_subdict_lang_country(): + """ + Check the function parsing a PII_TASKS list, w/ language & country + """ + + def callable_example(x): + return x + + PII_TASKS = [ + (PiiEnum.CREDIT_CARD, r"\d16", "a toy Credit Card example"), + (PiiEnum.BITCOIN_ADDRESS, callable_example), + ] + subdict = mod.build_subdict(PII_TASKS, "en", "in") + + assert len(subdict) == 2 + + exp1 = { + "pii": PiiEnum.CREDIT_CARD, + "lang": "en", + "country": "in", + "type": "regex", + "task": r"\d16", + "name": "regex for credit_card", + "doc": "a toy Credit Card example", + } + assert subdict[PiiEnum.CREDIT_CARD.name] == [exp1] + + exp2 = { + "pii": PiiEnum.BITCOIN_ADDRESS, + "lang": "en", + "country": "in", + "type": "callable", + "task": callable_example, + "name": "callable example", + } + + assert subdict[PiiEnum.BITCOIN_ADDRESS.name] == [exp2] + + +def test40_subdict_simplified_err(): + """ + Check the function parsing a PII_TASKS list of simplified tasks with errors + """ + # Not a tuple + PII_TASKS = [r"\d16"] + with pytest.raises(mod.InvPiiTask): + mod.build_subdict(PII_TASKS, "fr") + + # A tuple plus not a tuple + PII_TASKS = [(PiiEnum.CREDIT_CARD, r"\d{16}", "a toy Credit Card example"), r"\d16"] + with pytest.raises(mod.InvPiiTask): + mod.build_subdict(PII_TASKS, "zh") + + # A tuple without a valid PiiEnum + PII_TASKS = [("not a PiiEnum", r"\d{16}", "a toy Credit Card example")] + with pytest.raises(mod.InvPiiTask): + mod.build_subdict(PII_TASKS, "es") + + +def test41_subdict_full_err(): + """ + Check the function parsing a PII_TASKS list of full tasks with errors + """ + # Empty dict + PII_TASKS = [{}] + with pytest.raises(mod.InvPiiTask): + mod.build_subdict(PII_TASKS, "fr") + + # invalid pii field + PII_TASKS = [{"pii": "not a valid PiiEnum", "type": "regex", "task": r"\d{16}"}] + with pytest.raises(mod.InvPiiTask): + mod.build_subdict(PII_TASKS, "fr") + + # invalid type field + PII_TASKS = [ + {"pii": PiiEnum.CREDIT_CARD, "type": "not a valid type", "task": r"\d{16}"} + ] + with pytest.raises(mod.InvPiiTask): + mod.build_subdict(PII_TASKS, "fr") + + # No task + PII_TASKS = [{"pii": PiiEnum.CREDIT_CARD, "type": "regex"}] + with pytest.raises(mod.InvPiiTask): + mod.build_subdict(PII_TASKS, "fr") + + # Invalid task descriptor for a regex + PII_TASKS = [{"pii": PiiEnum.CREDIT_CARD, "type": "regex", "task": lambda x: x}] + with pytest.raises(mod.InvPiiTask): + mod.build_subdict(PII_TASKS, "fr") + + # Invalid task descriptor for a callable + PII_TASKS = [{"pii": PiiEnum.CREDIT_CARD, "type": "callable", "task": r"\d{16}"}] + with pytest.raises(mod.InvPiiTask): + mod.build_subdict(PII_TASKS, "fr") + + # Invalid task descriptor for a class + PII_TASKS = [{"pii": PiiEnum.CREDIT_CARD, "type": "PiiTask", "task": lambda x: x}] + with pytest.raises(mod.InvPiiTask): + mod.build_subdict(PII_TASKS, "fr") + + # No language + PII_TASKS = [{"pii": PiiEnum.CREDIT_CARD, "type": "regex", "task": r"\d{16}"}] + with pytest.raises(mod.InvPiiTask): + mod.build_subdict(PII_TASKS, lang=None) diff --git a/data_tooling/pii-manager/test/unit/lang/any/test_bitcoin_address.py b/data_tooling/pii-manager/test/unit/lang/any/test_bitcoin_address.py new file mode 100644 index 0000000..1f5da9f --- /dev/null +++ b/data_tooling/pii-manager/test/unit/lang/any/test_bitcoin_address.py @@ -0,0 +1,32 @@ +""" +Test bitcoin addresses +""" + + +from pii_manager import PiiEnum +from pii_manager.api import PiiManager + + +TEST = [ + # A valid bitcoin address + ( + "BTC address: 1JayVxfVgdaFKirkZTZVK4CdRnFDdFNENN", + "BTC address: ", + ), + ( + "BTC address: bc1qwxxvjxlakxe9rmxcphh4yy8a2t6z00k4gc4mpj", + "BTC address: ", + ), + # An invalid bitcoin address + ( + "BTC address: 1AGNa15ZQXAZUgFiqJ2i7Z2DPU2J6hW623", + "BTC address: 1AGNa15ZQXAZUgFiqJ2i7Z2DPU2J6hW623", + ), +] + + +def test10_credit_card(): + obj = PiiManager("en", None, PiiEnum.BITCOIN_ADDRESS) + for doc, exp in TEST: + got = obj(doc) + assert got == exp diff --git a/data_tooling/pii-manager/test/unit/lang/any/test_credit_card.py b/data_tooling/pii-manager/test/unit/lang/any/test_credit_card.py new file mode 100644 index 0000000..35a6846 --- /dev/null +++ b/data_tooling/pii-manager/test/unit/lang/any/test_credit_card.py @@ -0,0 +1,51 @@ +""" +Test credit card numbers +""" + +from pii_manager import PiiEnum +from pii_manager.api import PiiManager + + +TEST = [ + # A valid credit card number + ( + "El número de la tarjeta de crédito es 4273 9666 4581 5642", + "El número de la tarjeta de crédito es ", + ), + # Without spaces + ("La tarjeta es 4273966645815642", "La tarjeta es "), + # With text afterwards + ( + "El número de la tarjeta es 4273 9666 4581 5642 probablemente", + "El número de la tarjeta es probablemente", + ), + # With dashes + ( + "mi tarjeta es 4273-9666-4581-5642 con caducidad 07/22", + "mi tarjeta es con caducidad 07/22", + ), + # Too short + ( + "El número de la tarjeta de crédito es 4273 9666 4581", + "El número de la tarjeta de crédito es 4273 9666 4581", + ), + # Not a valid credit card number + ( + "El número de la tarjeta de crédito es 4273 9666 4581 5641", + "El número de la tarjeta de crédito es 4273 9666 4581 5641", + ), +] + + +def test10_credit_card(): + obj = PiiManager("es", None, PiiEnum.CREDIT_CARD) + for doc, exp in TEST: + got = obj(doc) + assert exp == got + + +def test20_credit_card_stats(): + obj = PiiManager("es", None, PiiEnum.CREDIT_CARD) + for doc, exp in TEST: + obj(doc) + assert obj.stats == {"calls": 6, "CREDIT_CARD": 4} diff --git a/data_tooling/pii-manager/test/unit/lang/any/test_email.py b/data_tooling/pii-manager/test/unit/lang/any/test_email.py new file mode 100644 index 0000000..835eb81 --- /dev/null +++ b/data_tooling/pii-manager/test/unit/lang/any/test_email.py @@ -0,0 +1,27 @@ +""" +Test email addersses +""" + +from pii_manager import PiiEnum +from pii_manager.api import PiiManager + + +TEST = [ + # A valid email address + ( + "My email is anyone@whatever.com.", + "My email is .", + ), + # An invalid email address + ( + "My email is anyone@whatever.", + "My email is anyone@whatever.", + ), +] + + +def test10_credit_card(): + obj = PiiManager("es", None, PiiEnum.EMAIL_ADDRESS) + for doc, exp in TEST: + got = obj(doc) + assert exp == got diff --git a/data_tooling/pii-manager/test/unit/lang/any/test_ip_address.py b/data_tooling/pii-manager/test/unit/lang/any/test_ip_address.py new file mode 100644 index 0000000..cd040cf --- /dev/null +++ b/data_tooling/pii-manager/test/unit/lang/any/test_ip_address.py @@ -0,0 +1,26 @@ +""" +Test IP addresses +""" + +from pii_manager import PiiEnum +from pii_manager.api import PiiManager + + +TEST = [ + # A valid IP address + ( + "My IP address is 10.45.122.65", + "My IP address is ", + ), + # An invalid IP address + ("My IP address is 310.45.122.65", "My IP address is 310.45.122.65"), + # An IP address without context + ("My address is 10.45.122.65", "My address is 10.45.122.65"), +] + + +def test10_ip_address(): + obj = PiiManager("en", None, PiiEnum.IP_ADDRESS) + for doc, exp in TEST: + got = obj(doc) + assert exp == got diff --git a/data_tooling/pii-manager/test/unit/lang/en/any/test_ipn_en.py b/data_tooling/pii-manager/test/unit/lang/en/any/test_ipn_en.py new file mode 100644 index 0000000..4701929 --- /dev/null +++ b/data_tooling/pii-manager/test/unit/lang/en/any/test_ipn_en.py @@ -0,0 +1,26 @@ +""" +Test international phone numbers +""" + +from pii_manager import PiiEnum +from pii_manager.api import PiiManager +from pii_manager.lang import LANG_ANY + +TEST = [ + # Standard phone number + ("phone number: +34 983 453 999", "phone number: "), + ("phone number: +34983453999", "phone number: "), + ("ph. +34983453999", "ph. "), + # An invalid country code + ("phone number: +99 983 453 999", "phone number: +99 983 453 999"), + # No valid contexts + ("number: +34983453999", "number: +34983453999"), + ("phonograph +34983453999", "phonograph +34983453999"), +] + + +def test10_ssn(): + obj = PiiManager("en", LANG_ANY, PiiEnum.PHONE_NUMBER) + for doc, exp in TEST: + got = obj(doc) + assert got == exp diff --git a/data_tooling/pii-manager/test/unit/lang/en/au/test_abn.py b/data_tooling/pii-manager/test/unit/lang/en/au/test_abn.py new file mode 100644 index 0000000..7ee2dfd --- /dev/null +++ b/data_tooling/pii-manager/test/unit/lang/en/au/test_abn.py @@ -0,0 +1,22 @@ +""" +Test Australian Business Number +""" + +from pii_manager import PiiEnum +from pii_manager.api import PiiManager + +TEST = [ + # A valid ABN + ("business number: 83 914 571 673.", "business number: ."), + # ABN without spaces + ("business number: 83914571673.", "business number: ."), + # An invalid ABN + ("not an ABN: 83 914 571 679", "not an ABN: 83 914 571 679"), +] + + +def test10_abn(): + obj = PiiManager("en", "AU", PiiEnum.GOV_ID) + for doc, exp in TEST: + got = obj(doc) + assert got == exp diff --git a/data_tooling/pii-manager/test/unit/lang/en/au/test_tfn.py b/data_tooling/pii-manager/test/unit/lang/en/au/test_tfn.py new file mode 100644 index 0000000..8738597 --- /dev/null +++ b/data_tooling/pii-manager/test/unit/lang/en/au/test_tfn.py @@ -0,0 +1,23 @@ +""" +Test Australian Tax File Number +""" + +from pii_manager import PiiEnum +from pii_manager.api import PiiManager + +TEST = [ + # A valid ABN + ("tax file number: 963 553 151.", "tax file number: ."), + ("the tfn is: 123 456 782", "the tfn is: "), + # TFN without spaces + ("tax file number: 963553151.", "tax file number: ."), + # An invalid TFN + ("not a TFN: 123 456 781", "not a TFN: 123 456 781"), +] + + +def test10_abn(): + obj = PiiManager("en", "AU", PiiEnum.GOV_ID) + for doc, exp in TEST: + got = obj(doc) + assert got == exp diff --git a/data_tooling/pii-manager/test/unit/lang/en/ca/test_sin.py b/data_tooling/pii-manager/test/unit/lang/en/ca/test_sin.py new file mode 100644 index 0000000..d93ff2c --- /dev/null +++ b/data_tooling/pii-manager/test/unit/lang/en/ca/test_sin.py @@ -0,0 +1,22 @@ +""" +Test Canadian Social Insurance Number +""" + +from pii_manager import PiiEnum +from pii_manager.api import PiiManager + +TEST = [ + # A valid SIN + ("SIN: 963-553-151", "SIN: "), + # SIN with spaces + ("SIN: 339 892 317 number", "SIN: number"), + # An invalid SIN + ("not a SIN: 123-456-781", "not a SIN: 123-456-781"), +] + + +def test10_ssn(): + obj = PiiManager("en", "CA", PiiEnum.GOV_ID) + for doc, exp in TEST: + got = obj(doc) + assert got == exp diff --git a/data_tooling/pii-manager/test/unit/lang/en/in_/test_aadhaar.py b/data_tooling/pii-manager/test/unit/lang/en/in_/test_aadhaar.py new file mode 100644 index 0000000..af80201 --- /dev/null +++ b/data_tooling/pii-manager/test/unit/lang/en/in_/test_aadhaar.py @@ -0,0 +1,25 @@ +""" +Test Indian Aadhaar Number +""" + +from pii_manager import PiiEnum +from pii_manager.api import PiiManager + +TEST = [ + # A valid aadhaar + ("aadhaar number 234123412346", "aadhaar number "), + # aadhaar with spaces + ("aadhaar number 2341 2341 2346", "aadhaar number "), + # An invalid aadhaar + ( + "not a real aadhaar number: 2341 2341 2347", + "not a real aadhaar number: 2341 2341 2347", + ), +] + + +def test10_ssn(): + obj = PiiManager("en", "IN", PiiEnum.GOV_ID) + for doc, exp in TEST: + got = obj(doc) + assert got == exp diff --git a/data_tooling/pii-manager/test/unit/lang/en/us/test_ssn.py b/data_tooling/pii-manager/test/unit/lang/en/us/test_ssn.py new file mode 100644 index 0000000..589c06b --- /dev/null +++ b/data_tooling/pii-manager/test/unit/lang/en/us/test_ssn.py @@ -0,0 +1,22 @@ +""" +Test US Social Security Number +""" + +from pii_manager import PiiEnum +from pii_manager.api import PiiManager + +TEST = [ + # A valid SSN + ("SSN: 536-90-4399", "SSN: "), + # SSN with spaces + ("SSN: 536 90 4399", "SSN: "), + # An invalid SSN + ("not a SSN: 666-90-4399", "not a SSN: 666-90-4399"), +] + + +def test10_ssn(): + obj = PiiManager("en", "US", PiiEnum.GOV_ID) + for doc, exp in TEST: + got = obj(doc) + assert got == exp diff --git a/data_tooling/pii-manager/test/unit/lang/es/any/test_ipn_es.py b/data_tooling/pii-manager/test/unit/lang/es/any/test_ipn_es.py new file mode 100644 index 0000000..dbb0df5 --- /dev/null +++ b/data_tooling/pii-manager/test/unit/lang/es/any/test_ipn_es.py @@ -0,0 +1,26 @@ +""" +Test international phone numbers +""" + +from pii_manager import PiiEnum +from pii_manager.api import PiiManager +from pii_manager.lang import LANG_ANY + +TEST = [ + # Standard phone number + ("teléfono: +34 983 453 999", "teléfono: "), + ("tf. +34983453999", "tf. "), + ("numero de telefono +34983453999", "numero de telefono "), + # An invalid country code + ("teléfono: +99 983 453 999", "teléfono: +99 983 453 999"), + # No valid contexts + ("número: +34983453999", "número: +34983453999"), + ("tff +34983453999", "tff +34983453999"), +] + + +def test10_ssn(): + obj = PiiManager("es", LANG_ANY, PiiEnum.PHONE_NUMBER) + for doc, exp in TEST: + got = obj(doc) + assert got == exp diff --git a/data_tooling/pii-manager/test/unit/lang/es/es/test_bank_account.py b/data_tooling/pii-manager/test/unit/lang/es/es/test_bank_account.py new file mode 100644 index 0000000..7bf0d0e --- /dev/null +++ b/data_tooling/pii-manager/test/unit/lang/es/es/test_bank_account.py @@ -0,0 +1,41 @@ +""" +Test Spanish Bank Accounts +""" + +from pii_manager import PiiEnum +from pii_manager.api import PiiManager + +TEST = [ + # A valid bank account number + ( + "Código cuenta cliente: 2085 8720 60 1902070563", + "Código cuenta cliente: ", + ), + # No spaces + ( + "Código cuenta cliente: 20858720601902070563", + "Código cuenta cliente: ", + ), + # An invalid bank account number + ( + "Código cuenta cliente: 2085 8720 44 1902070563", + "Código cuenta cliente: 2085 8720 44 1902070563", + ), +] + + +def test10_bank_account(): + obj = PiiManager("es", "ES", PiiEnum.BANK_ACCOUNT) + for doc, exp in TEST: + got = obj(doc) + assert got == exp + + +def test20_bank_account_undefined(): + """ + Test under another country (hence it will NOT be defined) + """ + obj = PiiManager("es", "FR", PiiEnum.BANK_ACCOUNT) + for doc, exp in TEST: + got = obj(doc) + assert got == doc diff --git a/data_tooling/pii-manager/test/unit/lang/es/es/test_govid_es_es.py b/data_tooling/pii-manager/test/unit/lang/es/es/test_govid_es_es.py new file mode 100644 index 0000000..c9b9e78 --- /dev/null +++ b/data_tooling/pii-manager/test/unit/lang/es/es/test_govid_es_es.py @@ -0,0 +1,43 @@ +""" +Test Spanish DNI & NIE +""" + +from pii_manager import PiiEnum, PiiEntity +from pii_manager.api import PiiManager + +TEST = [ + # A valid DNI + ( + "Mi DNI es 34657934-Q", + "Mi DNI es ", + [PiiEntity(PiiEnum.GOV_ID, 10, "34657934-Q", "es", "Spanish DNI")], + ), + # A DNI without dash + ( + "El DNI 34657934Q es válido", + "El DNI es válido", + [PiiEntity(PiiEnum.GOV_ID, 7, "34657934Q", "es", "Spanish DNI")], + ), + # A valid NIE + ( + "El NIE es X3465793-S", + "El NIE es ", + [PiiEntity(PiiEnum.GOV_ID, 10, "X3465793-S", "es", "Spanish NIE")], + ), + # An invalid DNI + ("Mi DNI es 34657934-H", "Mi DNI es 34657934-H", []), +] + + +def test10_dni(): + obj = PiiManager("es", "ES", PiiEnum.GOV_ID) + for doc, exp, _ in TEST: + got = obj(doc) + assert got == exp + + +def test20_dni_extract(): + obj = PiiManager("es", "ES", PiiEnum.GOV_ID, mode="extract") + for doc, _, exp in TEST: + got = list(obj(doc)) + assert got == exp diff --git a/data_tooling/pii-manager/test/unit/lang/es/mx/test_govid_es_mx.py b/data_tooling/pii-manager/test/unit/lang/es/mx/test_govid_es_mx.py new file mode 100644 index 0000000..5d684b1 --- /dev/null +++ b/data_tooling/pii-manager/test/unit/lang/es/mx/test_govid_es_mx.py @@ -0,0 +1,23 @@ +""" +Test Mexican CURP +""" + +from pii_manager import PiiEnum +from pii_manager.api import PiiManager + +TEST = [ + # A valid CURP + ("Mi número de CURP es PEPP700101HASRRD09", "Mi número de CURP es "), + # An invalid CURP + ( + "Mi número de CURP es PEPP700101HASRRD01", + "Mi número de CURP es PEPP700101HASRRD01", + ), +] + + +def test10_curp(): + obj = PiiManager("es", "MX", PiiEnum.GOV_ID) + for doc, exp in TEST: + got = obj(doc) + assert got == exp diff --git a/data_tooling/pii-manager/test/unit/lang/pt/br/test_govid_pt_br.py b/data_tooling/pii-manager/test/unit/lang/pt/br/test_govid_pt_br.py new file mode 100644 index 0000000..50e4ff0 --- /dev/null +++ b/data_tooling/pii-manager/test/unit/lang/pt/br/test_govid_pt_br.py @@ -0,0 +1,20 @@ +""" +Test Brazilian CPF +""" + +from pii_manager import PiiEnum +from pii_manager.api import PiiManager + +TEST = [ + # A valid CPF + ("O número do CPF é 263.946.533-30", "O número do CPF é "), + # An invalid CPF + ("O número do CPF é 000.000.000-12", "O número do CPF é 000.000.000-12"), +] + + +def test10_cpf(): + obj = PiiManager("pt", "BR", PiiEnum.GOV_ID) + for doc, exp in TEST: + got = obj(doc) + assert got == exp diff --git a/data_tooling/pii-manager/test/unit/lang/pt/pt/test_govid_pt_pt.py b/data_tooling/pii-manager/test/unit/lang/pt/pt/test_govid_pt_pt.py new file mode 100644 index 0000000..d608afc --- /dev/null +++ b/data_tooling/pii-manager/test/unit/lang/pt/pt/test_govid_pt_pt.py @@ -0,0 +1,43 @@ +""" +Test Portuguese NIF & CC +""" + +from pii_manager import PiiEnum, PiiEntity +from pii_manager.api import PiiManager + +TEST = [ + # A valid NIF + ( + "Meu NIF é PT 123 456 789", + "Meu NIF é ", + [PiiEntity(PiiEnum.GOV_ID, 10, "PT 123 456 789", "pt", "Portuguese NIF")], + ), + # A NIF without spacing or prefix + ( + "O NIF 123456789 é valido", + "O NIF é valido", + [PiiEntity(PiiEnum.GOV_ID, 6, "123456789", "pt", "Portuguese NIF")], + ), + # A valid CC + ( + "O CC é 00000000 0 ZZ4", + "O CC é ", + [PiiEntity(PiiEnum.GOV_ID, 7, "00000000 0 ZZ4", "pt", "Portuguese CC")], + ), + # An invalid NIF + ("Meu NIF é PT 123 456 788", "Meu NIF é PT 123 456 788", []), +] + + +def test10_nif_cc(): + obj = PiiManager("pt", "PT", PiiEnum.GOV_ID) + for doc, exp, _ in TEST: + got = obj(doc) + assert got == exp + + +def test20_nif_cc_extract(): + obj = PiiManager("pt", "PT", PiiEnum.GOV_ID, mode="extract") + for doc, _, exp in TEST: + got = list(obj(doc)) + assert got == exp diff --git a/data_tooling/pii-manager/test/unit/lang/zh/cn/test_govid_zh_cn.py b/data_tooling/pii-manager/test/unit/lang/zh/cn/test_govid_zh_cn.py new file mode 100644 index 0000000..0ec75a2 --- /dev/null +++ b/data_tooling/pii-manager/test/unit/lang/zh/cn/test_govid_zh_cn.py @@ -0,0 +1,28 @@ +""" +Test Chinese government ids (Resident Identity Card & Passport) +""" + +from pii_manager import PiiEnum +from pii_manager.api import PiiManager + +TEST = [ + # A valid RIC + ("公民身份号码 360426199101010071", "公民身份号码 "), + # An invalid RIC + ("公民身份号码 360426199101010072", "公民身份号码 360426199101010072"), + # An invalid RIC (one aditional digit) + ("公民身份号码 3604261991010100717", "公民身份号码 3604261991010100717"), + # A correct passport number + ("中华人民共和国护照 D12345678", "中华人民共和国护照 "), + # An incorrect passport number (invalid letter) + ("中华人民共和国护照 K12345678", "中华人民共和国护照 K12345678"), + # An incorrect passport number (only 7 digits) + ("中华人民共和国护照 D1234567", "中华人民共和国护照 D1234567"), +] + + +def test10_ssn(): + obj = PiiManager("zh", "CN", PiiEnum.GOV_ID) + for doc, exp in TEST: + got = obj(doc) + assert got == exp diff --git a/data_tooling/pii-manager/test/unit/lang/zh/cn/test_misc.py b/data_tooling/pii-manager/test/unit/lang/zh/cn/test_misc.py new file mode 100644 index 0000000..ea99d1e --- /dev/null +++ b/data_tooling/pii-manager/test/unit/lang/zh/cn/test_misc.py @@ -0,0 +1,23 @@ +""" +Test PII elements for Chinese (Phone numbers, street addresses & diseases) +""" + +from pii_manager import PiiEnum +from pii_manager.api import PiiManager + +TEST = [ + # Phone number + ("045-4123456", ""), + # Not a phone number (too many digits in the first part) + ("70045-4123456", "70045-4123456"), + # ----- We are missing here tests for STREET_ADDRESS & DISEASE +] + + +def test10_ssn(): + obj = PiiManager( + "zh", "CN", [PiiEnum.STREET_ADDRESS, PiiEnum.PHONE_NUMBER, PiiEnum.DISEASE] + ) + for doc, exp in TEST: + got = obj(doc) + assert got == exp diff --git a/data_tooling/pii_processing/LICENSE b/data_tooling/pii_processing/LICENSE new file mode 100644 index 0000000..9757e25 --- /dev/null +++ b/data_tooling/pii_processing/LICENSE @@ -0,0 +1,646 @@ +The PII reference impelmentation, not including the masakhane-ner code and the HuggingFace Code is released under Apache 2 and: +Copyright 2021- Ontocord LLC. 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Except for the limited purpose of indicating that +material is shared under a Creative Commons public license or as +otherwise permitted by the Creative Commons policies published at +creativecommons.org/policies, Creative Commons does not authorize the +use of the trademark "Creative Commons" or any other trademark or logo +of Creative Commons without its prior written consent including, +without limitation, in connection with any unauthorized modifications +to any of its public licenses or any other arrangements, +understandings, or agreements concerning use of licensed material. For +the avoidance of doubt, this paragraph does not form part of the +public licenses. + +Creative Commons may be contacted at creativecommons.org. diff --git a/data_tooling/pii_processing/MANIFEST.in b/data_tooling/pii_processing/MANIFEST.in new file mode 100644 index 0000000..43d36be --- /dev/null +++ b/data_tooling/pii_processing/MANIFEST.in @@ -0,0 +1,3 @@ +recursive-include include *.h +include LICENSE +include README.md diff --git a/data_tooling/pii_processing/README.md b/data_tooling/pii_processing/README.md new file mode 100644 index 0000000..0835448 --- /dev/null +++ b/data_tooling/pii_processing/README.md @@ -0,0 +1,46 @@ +# Personally Identifiable Information Processing + +This is code for a multi-lingual Named Entity Recognition and PII processor used to remediate PII in web scale large language datasets for training large langauge models. This code is not meant to be used for general purpose NER or PII remediation. + +## Organization of Repo + +- The repo is a clone of the neuralcoref repo in order to more easily modify the base neuralcoref code and to take advantage of its great organization +- The code in the ontology folder is for building and tokenizing text for words in the ontology +- The code in the misc folder includes code to perform basic dataset creation and basic regex ner processing +- The code in the masakhane-ner folder is code for training transfomrer based NER models (BERT, Roberta, etc.) +- The contrib folder will contain code from the community which will draw from the PII hackathon +- The code under the wip folder is work in progress and not meant to be used in processing + +## PII Hackathon +This repo is also home for reference implementation for the PII Hackathon, run by Ontocord, AISC, and BigScience + +- The code under the directory misc will be used for Module 1. +- The code under the directory ontology and misc will be used for Module 2. +- The code under the directory masakhane-ner will be used for Module 3. +- TODO: Module 4, We will provide a reference implementation for an ensemble semi-supervised learning training of a transformer model + +## Requirements and Building + +- git clone https://github.com/bigscience-workshop/data_tooling +- cd data_tooling/ +- pip install -r requirements.txt +- python -m nltk.downloader punkt stopwords wordnet +- python -m spacy download en_core_web_lg + +TODO: +For module 3, we will be using neuralcoref to preprocess data, and we will want to change the requirements.txt to use spacy==2.1.8 and +- python setup.py install + + +## Usage +TODO + +## Credits + +This code is based on original code by Ontocord, LLC (https://github.com/ontocord), Hugginface's Nueralcoref (https://github.com/huggingface/neuralcoref) and MasakhaNER (https://github.com/masakhane-io/masakhane-ner) which is in turn based on HF Transfromers (https://github.com/huggingface/transformers/) and Faker (https://github.com/joke2k/faker) and includes inspiration from Presidio (https://github.com/microsoft/presidio) . + +All code is released under Apache 2.0, except Neuralcoref which is under the MIT License. + +Data is licensed as specified in the various data folders. + + diff --git a/data_tooling/pii_processing/bin/cythonize.py b/data_tooling/pii_processing/bin/cythonize.py new file mode 100644 index 0000000..2cd64c1 --- /dev/null +++ b/data_tooling/pii_processing/bin/cythonize.py @@ -0,0 +1,168 @@ +#!/usr/bin/env python +""" cythonize.py + +Cythonize pyx files into C++ files as needed. + +Usage: cythonize.py [root] + +Checks pyx files to see if they have been changed relative to their +corresponding C++ files. If they have, then runs cython on these files to +recreate the C++ files. + +Additionally, checks pxd files and setup.py if they have been changed. If +they have, rebuilds everything. + +Change detection based on file hashes stored in JSON format. + +For now, this script should be run by developers when changing Cython files +and the resulting C++ files checked in, so that end-users (and Python-only +developers) do not get the Cython dependencies. + +Based upon: + +https://raw.github.com/dagss/private-scipy-refactor/cythonize/cythonize.py +https://raw.githubusercontent.com/numpy/numpy/master/tools/cythonize.py + +Note: this script does not check any of the dependent C++ libraries. +""" + +import os +import sys +import json +import hashlib +import subprocess +import argparse + + +HASH_FILE = "cythonize.json" + + +def process_pyx(fromfile, tofile): + print("Processing %s" % fromfile) + try: + from Cython.Compiler.Version import version as cython_version + from distutils.version import LooseVersion + + if LooseVersion(cython_version) < LooseVersion("0.19"): + raise Exception("Require Cython >= 0.19") + + except ImportError: + pass + + flags = ["--fast-fail"] + if tofile.endswith(".cpp"): + flags += ["--cplus"] + + try: + try: + r = subprocess.call( + ["cython"] + flags + ["-o", tofile, fromfile], env=os.environ + ) # See Issue #791 + if r != 0: + raise Exception("Cython failed") + except OSError: + # There are ways of installing Cython that don't result in a cython + # executable on the path, see gh-2397. + r = subprocess.call( + [ + sys.executable, + "-c", + "import sys; from Cython.Compiler.Main import " + "setuptools_main as main; sys.exit(main())", + ] + + flags + + ["-o", tofile, fromfile] + ) + if r != 0: + raise Exception("Cython failed") + except OSError: + raise OSError("Cython needs to be installed") + + +def preserve_cwd(path, func, *args): + orig_cwd = os.getcwd() + try: + os.chdir(path) + func(*args) + finally: + os.chdir(orig_cwd) + + +def load_hashes(filename): + try: + return json.load(open(filename)) + except (ValueError, IOError): + return {} + + +def save_hashes(hash_db, filename): + with open(filename, "w") as f: + f.write(json.dumps(hash_db)) + + +def get_hash(path): + return hashlib.md5(open(path, "rb").read()).hexdigest() + + +def hash_changed(base, path, db): + full_path = os.path.normpath(os.path.join(base, path)) + return not get_hash(full_path) == db.get(full_path) + + +def hash_add(base, path, db): + full_path = os.path.normpath(os.path.join(base, path)) + db[full_path] = get_hash(full_path) + + +def process(base, filename, db): + root, ext = os.path.splitext(filename) + if ext in [".pyx", ".cpp"]: + if hash_changed(base, filename, db) or not os.path.isfile( + os.path.join(base, root + ".cpp") + ): + preserve_cwd(base, process_pyx, root + ".pyx", root + ".cpp") + hash_add(base, root + ".cpp", db) + hash_add(base, root + ".pyx", db) + + +def check_changes(root, db): + res = False + new_db = {} + + setup_filename = "setup.py" + hash_add(".", setup_filename, new_db) + if hash_changed(".", setup_filename, db): + res = True + + for base, _, files in os.walk(root): + for filename in files: + if filename.endswith(".pxd"): + hash_add(base, filename, new_db) + if hash_changed(base, filename, db): + res = True + + if res: + db.clear() + db.update(new_db) + return res + + +def run(root): + db = load_hashes(HASH_FILE) + + try: + check_changes(root, db) + for base, _, files in os.walk(root): + for filename in files: + process(base, filename, db) + finally: + save_hashes(db, HASH_FILE) + + +if __name__ == "__main__": + parser = argparse.ArgumentParser( + description="Cythonize pyx files into C++ files as needed" + ) + parser.add_argument("root", help="root directory") + args = parser.parse_args() + run(args.root) diff --git a/data_tooling/pii_processing/contrib/coref_server.py b/data_tooling/pii_processing/contrib/coref_server.py new file mode 100644 index 0000000..efb0c58 --- /dev/null +++ b/data_tooling/pii_processing/contrib/coref_server.py @@ -0,0 +1,63 @@ +#!/usr/bin/env python +"""Coreference resolution server example. +A simple server serving the coreference system. +""" + +import json +from wsgiref.simple_server import make_server +import falcon +import spacy +import neuralcoref + +# Python 3 +unicode_ = str + + +class AllResource(object): + def __init__(self): + self.nlp = spacy.load("en") + neuralcoref.add_to_pipe(self.nlp) + print("Server loaded") + self.response = None + + def on_get(self, req, resp): + self.response = {} + + text_param = req.get_param_as_list("text") + print("text: ", text_param) + if text_param is not None: + text = ",".join(text_param) if isinstance(text_param, list) else text_param + text = unicode_(text) + doc = self.nlp(text) + if doc._.has_coref: + mentions = [ + { + "start": mention.start_char, + "end": mention.end_char, + "text": mention.text, + "resolved": cluster.main.text, + } + for cluster in doc._.coref_clusters + for mention in cluster.mentions + ] + clusters = list( + list(span.text for span in cluster) + for cluster in doc._.coref_clusters + ) + resolved = doc._.coref_resolved + self.response["mentions"] = mentions + self.response["clusters"] = clusters + self.response["resolved"] = resolved + + resp.body = json.dumps(self.response) + resp.content_type = "application/json" + resp.append_header("Access-Control-Allow-Origin", "*") + resp.status = falcon.HTTP_200 + + +if __name__ == "__main__": + RESSOURCE = AllResource() + APP = falcon.API() + APP.add_route("/", RESSOURCE) + HTTPD = make_server("0.0.0.0", 8000, APP) + HTTPD.serve_forever() diff --git a/data_tooling/pii_processing/include/msvc9/stdint.h b/data_tooling/pii_processing/include/msvc9/stdint.h new file mode 100644 index 0000000..4fe0ef9 --- /dev/null +++ b/data_tooling/pii_processing/include/msvc9/stdint.h @@ -0,0 +1,259 @@ +// ISO C9x compliant stdint.h for Microsoft Visual Studio +// Based on ISO/IEC 9899:TC2 Committee draft (May 6, 2005) WG14/N1124 +// +// Copyright (c) 2006-2013 Alexander Chemeris +// +// Redistribution and use in source and binary forms, with or without +// modification, are permitted provided that the following conditions are met: +// +// 1. Redistributions of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// 2. Redistributions in binary form must reproduce the above copyright +// notice, this list of conditions and the following disclaimer in the +// documentation and/or other materials provided with the distribution. +// +// 3. Neither the name of the product nor the names of its contributors may +// be used to endorse or promote products derived from this software +// without specific prior written permission. +// +// THIS SOFTWARE IS PROVIDED BY THE AUTHOR ``AS IS'' AND ANY EXPRESS OR IMPLIED +// WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF +// MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO +// EVENT SHALL THE AUTHOR BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, +// SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, +// PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; +// OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, +// WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR +// OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF +// ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. +// +/////////////////////////////////////////////////////////////////////////////// + +#ifndef _MSC_VER // [ +#error "Use this header only with Microsoft Visual C++ compilers!" +#endif // _MSC_VER ] + +#ifndef _MSC_STDINT_H_ // [ +#define _MSC_STDINT_H_ + +#if _MSC_VER > 1000 +#pragma once +#endif + +#if _MSC_VER >= 1600 // [ +#include +#else // ] _MSC_VER >= 1600 [ + +#include + +// For Visual Studio 6 in C++ mode and for many Visual Studio versions when +// compiling for ARM we should wrap include with 'extern "C++" {}' +// or compiler give many errors like this: +// error C2733: second C linkage of overloaded function 'wmemchr' not allowed +#ifdef __cplusplus +extern "C" { +#endif +# include +#ifdef __cplusplus +} +#endif + +// Define _W64 macros to mark types changing their size, like intptr_t. +#ifndef _W64 +# if !defined(__midl) && (defined(_X86_) || defined(_M_IX86)) && _MSC_VER >= 1300 +# define _W64 __w64 +# else +# define _W64 +# endif +#endif + + +// 7.18.1 Integer types + +// 7.18.1.1 Exact-width integer types + +// Visual Studio 6 and Embedded Visual C++ 4 doesn't +// realize that, e.g. char has the same size as __int8 +// so we give up on __intX for them. +#if (_MSC_VER < 1300) + typedef signed char int8_t; + typedef signed short int16_t; + typedef signed int int32_t; + typedef unsigned char uint8_t; + typedef unsigned short uint16_t; + typedef unsigned int uint32_t; +#else + typedef signed __int8 int8_t; + typedef signed __int16 int16_t; + typedef signed __int32 int32_t; + typedef unsigned __int8 uint8_t; + typedef unsigned __int16 uint16_t; + typedef unsigned __int32 uint32_t; +#endif +typedef signed __int64 int64_t; +typedef unsigned __int64 uint64_t; + + +// 7.18.1.2 Minimum-width integer types +typedef int8_t int_least8_t; +typedef int16_t int_least16_t; +typedef int32_t int_least32_t; +typedef int64_t int_least64_t; +typedef uint8_t uint_least8_t; +typedef uint16_t uint_least16_t; +typedef uint32_t uint_least32_t; +typedef uint64_t uint_least64_t; + +// 7.18.1.3 Fastest minimum-width integer types +typedef int8_t int_fast8_t; +typedef int16_t int_fast16_t; +typedef int32_t int_fast32_t; +typedef int64_t int_fast64_t; +typedef uint8_t uint_fast8_t; +typedef uint16_t uint_fast16_t; +typedef uint32_t uint_fast32_t; +typedef uint64_t uint_fast64_t; + +// 7.18.1.4 Integer types capable of holding object pointers +#ifdef _WIN64 // [ + typedef signed __int64 intptr_t; + typedef unsigned __int64 uintptr_t; +#else // _WIN64 ][ + typedef _W64 signed int intptr_t; + typedef _W64 unsigned int uintptr_t; +#endif // _WIN64 ] + +// 7.18.1.5 Greatest-width integer types +typedef int64_t intmax_t; +typedef uint64_t uintmax_t; + + +// 7.18.2 Limits of specified-width integer types + +#if !defined(__cplusplus) || defined(__STDC_LIMIT_MACROS) // [ See footnote 220 at page 257 and footnote 221 at page 259 + +// 7.18.2.1 Limits of exact-width integer types +#define INT8_MIN ((int8_t)_I8_MIN) +#define INT8_MAX _I8_MAX +#define INT16_MIN ((int16_t)_I16_MIN) +#define INT16_MAX _I16_MAX +#define INT32_MIN ((int32_t)_I32_MIN) +#define INT32_MAX _I32_MAX +#define INT64_MIN ((int64_t)_I64_MIN) +#define INT64_MAX _I64_MAX +#define UINT8_MAX _UI8_MAX +#define UINT16_MAX _UI16_MAX +#define UINT32_MAX _UI32_MAX +#define UINT64_MAX _UI64_MAX + +// 7.18.2.2 Limits of minimum-width integer types +#define INT_LEAST8_MIN INT8_MIN +#define INT_LEAST8_MAX INT8_MAX +#define INT_LEAST16_MIN INT16_MIN +#define INT_LEAST16_MAX INT16_MAX +#define INT_LEAST32_MIN INT32_MIN +#define INT_LEAST32_MAX INT32_MAX +#define INT_LEAST64_MIN INT64_MIN +#define INT_LEAST64_MAX INT64_MAX +#define UINT_LEAST8_MAX UINT8_MAX +#define UINT_LEAST16_MAX UINT16_MAX +#define UINT_LEAST32_MAX UINT32_MAX +#define UINT_LEAST64_MAX UINT64_MAX + +// 7.18.2.3 Limits of fastest minimum-width integer types +#define INT_FAST8_MIN INT8_MIN +#define INT_FAST8_MAX INT8_MAX +#define INT_FAST16_MIN INT16_MIN +#define INT_FAST16_MAX INT16_MAX +#define INT_FAST32_MIN INT32_MIN +#define INT_FAST32_MAX INT32_MAX +#define INT_FAST64_MIN INT64_MIN +#define INT_FAST64_MAX INT64_MAX +#define UINT_FAST8_MAX UINT8_MAX +#define UINT_FAST16_MAX UINT16_MAX +#define UINT_FAST32_MAX UINT32_MAX +#define UINT_FAST64_MAX UINT64_MAX + +// 7.18.2.4 Limits of integer types capable of holding object pointers +#ifdef _WIN64 // [ +# define INTPTR_MIN INT64_MIN +# define INTPTR_MAX INT64_MAX +# define UINTPTR_MAX UINT64_MAX +#else // _WIN64 ][ +# define INTPTR_MIN INT32_MIN +# define INTPTR_MAX INT32_MAX +# define UINTPTR_MAX UINT32_MAX +#endif // _WIN64 ] + +// 7.18.2.5 Limits of greatest-width integer types +#define INTMAX_MIN INT64_MIN +#define INTMAX_MAX INT64_MAX +#define UINTMAX_MAX UINT64_MAX + +// 7.18.3 Limits of other integer types + +#ifdef _WIN64 // [ +# define PTRDIFF_MIN _I64_MIN +# define PTRDIFF_MAX _I64_MAX +#else // _WIN64 ][ +# define PTRDIFF_MIN _I32_MIN +# define PTRDIFF_MAX _I32_MAX +#endif // _WIN64 ] + +#define SIG_ATOMIC_MIN INT_MIN +#define SIG_ATOMIC_MAX INT_MAX + +#ifndef SIZE_MAX // [ +# ifdef _WIN64 // [ +# define SIZE_MAX _UI64_MAX +# else // _WIN64 ][ +# define SIZE_MAX _UI32_MAX +# endif // _WIN64 ] +#endif // SIZE_MAX ] + +// WCHAR_MIN and WCHAR_MAX are also defined in +#ifndef WCHAR_MIN // [ +# define WCHAR_MIN 0 +#endif // WCHAR_MIN ] +#ifndef WCHAR_MAX // [ +# define WCHAR_MAX _UI16_MAX +#endif // WCHAR_MAX ] + +#define WINT_MIN 0 +#define WINT_MAX _UI16_MAX + +#endif // __STDC_LIMIT_MACROS ] + + +// 7.18.4 Limits of other integer types + +#if !defined(__cplusplus) || defined(__STDC_CONSTANT_MACROS) // [ See footnote 224 at page 260 + +// 7.18.4.1 Macros for minimum-width integer constants + +#define INT8_C(val) val##i8 +#define INT16_C(val) val##i16 +#define INT32_C(val) val##i32 +#define INT64_C(val) val##i64 + +#define UINT8_C(val) val##ui8 +#define UINT16_C(val) val##ui16 +#define UINT32_C(val) val##ui32 +#define UINT64_C(val) val##ui64 + +// 7.18.4.2 Macros for greatest-width integer constants +// These #ifndef's are needed to prevent collisions with . +// Check out Issue 9 for the details. +#ifndef INTMAX_C // [ +# define INTMAX_C INT64_C +#endif // INTMAX_C ] +#ifndef UINTMAX_C // [ +# define UINTMAX_C UINT64_C +#endif // UINTMAX_C ] + +#endif // __STDC_CONSTANT_MACROS ] + +#endif // _MSC_VER >= 1600 ] + +#endif // _MSC_STDINT_H_ ] diff --git a/data_tooling/pii_processing/include/murmurhash/MurmurHash2.h b/data_tooling/pii_processing/include/murmurhash/MurmurHash2.h new file mode 100644 index 0000000..6d7ccf4 --- /dev/null +++ b/data_tooling/pii_processing/include/murmurhash/MurmurHash2.h @@ -0,0 +1,22 @@ +//----------------------------------------------------------------------------- +// MurmurHash2 was written by Austin Appleby, and is placed in the public +// domain. The author hereby disclaims copyright to this source code. + +#ifndef _MURMURHASH2_H_ +#define _MURMURHASH2_H_ + +#include + +//----------------------------------------------------------------------------- + +uint32_t MurmurHash2 ( const void * key, int len, uint32_t seed ); +uint64_t MurmurHash64A ( const void * key, int len, uint64_t seed ); +uint64_t MurmurHash64B ( const void * key, int len, uint64_t seed ); +uint32_t MurmurHash2A ( const void * key, int len, uint32_t seed ); +uint32_t MurmurHashNeutral2 ( const void * key, int len, uint32_t seed ); +uint32_t MurmurHashAligned2 ( const void * key, int len, uint32_t seed ); + +//----------------------------------------------------------------------------- + +#endif // _MURMURHASH2_H_ + diff --git a/data_tooling/pii_processing/include/murmurhash/MurmurHash3.h b/data_tooling/pii_processing/include/murmurhash/MurmurHash3.h new file mode 100644 index 0000000..9b4c3c9 --- /dev/null +++ b/data_tooling/pii_processing/include/murmurhash/MurmurHash3.h @@ -0,0 +1,28 @@ +//----------------------------------------------------------------------------- +// MurmurHash3 was written by Austin Appleby, and is placed in the public +// domain. The author hereby disclaims copyright to this source code. + +#ifndef _MURMURHASH3_H_ +#define _MURMURHASH3_H_ + +#include + +//----------------------------------------------------------------------------- +#ifdef __cplusplus +extern "C" { +#endif + + +void MurmurHash3_x86_32 ( const void * key, int len, uint32_t seed, void * out ); + +void MurmurHash3_x86_128 ( const void * key, int len, uint32_t seed, void * out ); + +void MurmurHash3_x64_128 ( const void * key, int len, uint32_t seed, void * out ); + +#ifdef __cplusplus +} +#endif + +//----------------------------------------------------------------------------- + +#endif // _MURMURHASH3_H_ diff --git a/data_tooling/pii_processing/include/numpy/__multiarray_api.h b/data_tooling/pii_processing/include/numpy/__multiarray_api.h new file mode 100644 index 0000000..c949d73 --- /dev/null +++ b/data_tooling/pii_processing/include/numpy/__multiarray_api.h @@ -0,0 +1,1686 @@ + +#ifdef _MULTIARRAYMODULE + +typedef struct { + PyObject_HEAD + npy_bool obval; +} PyBoolScalarObject; + +#ifdef NPY_ENABLE_SEPARATE_COMPILATION +extern NPY_NO_EXPORT PyTypeObject PyArrayMapIter_Type; +extern NPY_NO_EXPORT PyTypeObject PyArrayNeighborhoodIter_Type; +extern NPY_NO_EXPORT PyBoolScalarObject _PyArrayScalar_BoolValues[2]; +#else +NPY_NO_EXPORT PyTypeObject PyArrayMapIter_Type; +NPY_NO_EXPORT PyTypeObject PyArrayNeighborhoodIter_Type; +NPY_NO_EXPORT PyBoolScalarObject _PyArrayScalar_BoolValues[2]; +#endif + +NPY_NO_EXPORT unsigned int PyArray_GetNDArrayCVersion \ + (void); +#ifdef NPY_ENABLE_SEPARATE_COMPILATION + extern NPY_NO_EXPORT PyTypeObject PyBigArray_Type; +#else + NPY_NO_EXPORT PyTypeObject PyBigArray_Type; +#endif + +#ifdef NPY_ENABLE_SEPARATE_COMPILATION + extern NPY_NO_EXPORT PyTypeObject PyArray_Type; +#else + NPY_NO_EXPORT PyTypeObject PyArray_Type; +#endif + +#ifdef NPY_ENABLE_SEPARATE_COMPILATION + extern NPY_NO_EXPORT PyTypeObject PyArrayDescr_Type; +#else + NPY_NO_EXPORT PyTypeObject PyArrayDescr_Type; +#endif + +#ifdef NPY_ENABLE_SEPARATE_COMPILATION + extern NPY_NO_EXPORT PyTypeObject PyArrayFlags_Type; +#else + NPY_NO_EXPORT PyTypeObject PyArrayFlags_Type; +#endif + +#ifdef NPY_ENABLE_SEPARATE_COMPILATION + extern NPY_NO_EXPORT PyTypeObject PyArrayIter_Type; +#else + NPY_NO_EXPORT PyTypeObject PyArrayIter_Type; +#endif + +#ifdef NPY_ENABLE_SEPARATE_COMPILATION + extern NPY_NO_EXPORT PyTypeObject PyArrayMultiIter_Type; +#else + NPY_NO_EXPORT PyTypeObject PyArrayMultiIter_Type; +#endif + +#ifdef NPY_ENABLE_SEPARATE_COMPILATION + extern NPY_NO_EXPORT int NPY_NUMUSERTYPES; +#else + NPY_NO_EXPORT int NPY_NUMUSERTYPES; +#endif + +#ifdef NPY_ENABLE_SEPARATE_COMPILATION + extern NPY_NO_EXPORT PyTypeObject PyBoolArrType_Type; +#else + NPY_NO_EXPORT PyTypeObject PyBoolArrType_Type; +#endif + +#ifdef NPY_ENABLE_SEPARATE_COMPILATION +extern NPY_NO_EXPORT PyBoolScalarObject _PyArrayScalar_BoolValues[2]; +#else +NPY_NO_EXPORT PyBoolScalarObject _PyArrayScalar_BoolValues[2]; +#endif + +#ifdef NPY_ENABLE_SEPARATE_COMPILATION + extern NPY_NO_EXPORT PyTypeObject PyGenericArrType_Type; +#else + NPY_NO_EXPORT PyTypeObject PyGenericArrType_Type; +#endif + +#ifdef NPY_ENABLE_SEPARATE_COMPILATION + extern NPY_NO_EXPORT PyTypeObject PyNumberArrType_Type; +#else + NPY_NO_EXPORT PyTypeObject PyNumberArrType_Type; +#endif + +#ifdef NPY_ENABLE_SEPARATE_COMPILATION + extern NPY_NO_EXPORT PyTypeObject PyIntegerArrType_Type; +#else + NPY_NO_EXPORT PyTypeObject PyIntegerArrType_Type; +#endif + +#ifdef NPY_ENABLE_SEPARATE_COMPILATION + extern NPY_NO_EXPORT PyTypeObject PySignedIntegerArrType_Type; +#else + NPY_NO_EXPORT PyTypeObject PySignedIntegerArrType_Type; +#endif + +#ifdef NPY_ENABLE_SEPARATE_COMPILATION + extern NPY_NO_EXPORT PyTypeObject PyUnsignedIntegerArrType_Type; +#else + NPY_NO_EXPORT PyTypeObject PyUnsignedIntegerArrType_Type; +#endif + +#ifdef NPY_ENABLE_SEPARATE_COMPILATION + extern NPY_NO_EXPORT PyTypeObject PyInexactArrType_Type; +#else + NPY_NO_EXPORT PyTypeObject PyInexactArrType_Type; +#endif + +#ifdef NPY_ENABLE_SEPARATE_COMPILATION + extern NPY_NO_EXPORT PyTypeObject PyFloatingArrType_Type; +#else + NPY_NO_EXPORT PyTypeObject PyFloatingArrType_Type; +#endif + +#ifdef NPY_ENABLE_SEPARATE_COMPILATION + extern NPY_NO_EXPORT PyTypeObject PyComplexFloatingArrType_Type; +#else + NPY_NO_EXPORT PyTypeObject PyComplexFloatingArrType_Type; +#endif + +#ifdef NPY_ENABLE_SEPARATE_COMPILATION + extern NPY_NO_EXPORT PyTypeObject PyFlexibleArrType_Type; +#else + NPY_NO_EXPORT PyTypeObject PyFlexibleArrType_Type; +#endif + +#ifdef NPY_ENABLE_SEPARATE_COMPILATION + extern NPY_NO_EXPORT PyTypeObject PyCharacterArrType_Type; +#else + NPY_NO_EXPORT PyTypeObject PyCharacterArrType_Type; +#endif + +#ifdef NPY_ENABLE_SEPARATE_COMPILATION + extern NPY_NO_EXPORT PyTypeObject PyByteArrType_Type; +#else + NPY_NO_EXPORT PyTypeObject PyByteArrType_Type; +#endif + +#ifdef NPY_ENABLE_SEPARATE_COMPILATION + extern NPY_NO_EXPORT PyTypeObject PyShortArrType_Type; +#else + NPY_NO_EXPORT PyTypeObject PyShortArrType_Type; +#endif + +#ifdef NPY_ENABLE_SEPARATE_COMPILATION + extern NPY_NO_EXPORT PyTypeObject PyIntArrType_Type; +#else + NPY_NO_EXPORT PyTypeObject PyIntArrType_Type; +#endif + +#ifdef NPY_ENABLE_SEPARATE_COMPILATION + extern NPY_NO_EXPORT PyTypeObject PyLongArrType_Type; +#else + NPY_NO_EXPORT PyTypeObject PyLongArrType_Type; +#endif + +#ifdef NPY_ENABLE_SEPARATE_COMPILATION + extern NPY_NO_EXPORT PyTypeObject PyLongLongArrType_Type; +#else + NPY_NO_EXPORT PyTypeObject PyLongLongArrType_Type; +#endif + +#ifdef NPY_ENABLE_SEPARATE_COMPILATION + extern NPY_NO_EXPORT PyTypeObject PyUByteArrType_Type; +#else + NPY_NO_EXPORT PyTypeObject PyUByteArrType_Type; +#endif + +#ifdef NPY_ENABLE_SEPARATE_COMPILATION + extern NPY_NO_EXPORT PyTypeObject PyUShortArrType_Type; +#else + NPY_NO_EXPORT PyTypeObject PyUShortArrType_Type; +#endif + +#ifdef NPY_ENABLE_SEPARATE_COMPILATION + extern NPY_NO_EXPORT PyTypeObject PyUIntArrType_Type; +#else + NPY_NO_EXPORT PyTypeObject PyUIntArrType_Type; +#endif + +#ifdef NPY_ENABLE_SEPARATE_COMPILATION + extern NPY_NO_EXPORT PyTypeObject PyULongArrType_Type; +#else + NPY_NO_EXPORT PyTypeObject PyULongArrType_Type; +#endif + +#ifdef NPY_ENABLE_SEPARATE_COMPILATION + extern NPY_NO_EXPORT PyTypeObject PyULongLongArrType_Type; +#else + NPY_NO_EXPORT PyTypeObject PyULongLongArrType_Type; +#endif + +#ifdef NPY_ENABLE_SEPARATE_COMPILATION + extern NPY_NO_EXPORT PyTypeObject PyFloatArrType_Type; +#else + NPY_NO_EXPORT PyTypeObject PyFloatArrType_Type; +#endif + +#ifdef NPY_ENABLE_SEPARATE_COMPILATION + extern NPY_NO_EXPORT PyTypeObject PyDoubleArrType_Type; +#else + NPY_NO_EXPORT PyTypeObject PyDoubleArrType_Type; +#endif + +#ifdef NPY_ENABLE_SEPARATE_COMPILATION + extern NPY_NO_EXPORT PyTypeObject PyLongDoubleArrType_Type; +#else + NPY_NO_EXPORT PyTypeObject PyLongDoubleArrType_Type; +#endif + +#ifdef NPY_ENABLE_SEPARATE_COMPILATION + extern NPY_NO_EXPORT PyTypeObject PyCFloatArrType_Type; +#else + NPY_NO_EXPORT PyTypeObject PyCFloatArrType_Type; +#endif + +#ifdef NPY_ENABLE_SEPARATE_COMPILATION + extern NPY_NO_EXPORT PyTypeObject PyCDoubleArrType_Type; +#else + NPY_NO_EXPORT PyTypeObject PyCDoubleArrType_Type; +#endif + +#ifdef NPY_ENABLE_SEPARATE_COMPILATION + extern NPY_NO_EXPORT PyTypeObject PyCLongDoubleArrType_Type; +#else + NPY_NO_EXPORT PyTypeObject PyCLongDoubleArrType_Type; +#endif + +#ifdef NPY_ENABLE_SEPARATE_COMPILATION + extern NPY_NO_EXPORT PyTypeObject PyObjectArrType_Type; +#else + NPY_NO_EXPORT PyTypeObject PyObjectArrType_Type; +#endif + +#ifdef NPY_ENABLE_SEPARATE_COMPILATION + extern NPY_NO_EXPORT PyTypeObject PyStringArrType_Type; +#else + NPY_NO_EXPORT PyTypeObject PyStringArrType_Type; +#endif + +#ifdef NPY_ENABLE_SEPARATE_COMPILATION + extern NPY_NO_EXPORT PyTypeObject PyUnicodeArrType_Type; +#else + NPY_NO_EXPORT PyTypeObject PyUnicodeArrType_Type; +#endif + +#ifdef NPY_ENABLE_SEPARATE_COMPILATION + extern NPY_NO_EXPORT PyTypeObject PyVoidArrType_Type; +#else + NPY_NO_EXPORT PyTypeObject PyVoidArrType_Type; +#endif + +NPY_NO_EXPORT int PyArray_SetNumericOps \ + (PyObject *); +NPY_NO_EXPORT PyObject * PyArray_GetNumericOps \ + (void); +NPY_NO_EXPORT int PyArray_INCREF \ + (PyArrayObject *); +NPY_NO_EXPORT int PyArray_XDECREF \ + (PyArrayObject *); +NPY_NO_EXPORT void PyArray_SetStringFunction \ + (PyObject *, int); +NPY_NO_EXPORT PyArray_Descr * PyArray_DescrFromType \ + (int); +NPY_NO_EXPORT PyObject * PyArray_TypeObjectFromType \ + (int); +NPY_NO_EXPORT char * PyArray_Zero \ + (PyArrayObject *); +NPY_NO_EXPORT char * PyArray_One \ + (PyArrayObject *); +NPY_NO_EXPORT PyObject * PyArray_CastToType \ + (PyArrayObject *, PyArray_Descr *, int); +NPY_NO_EXPORT int PyArray_CastTo \ + (PyArrayObject *, PyArrayObject *); +NPY_NO_EXPORT int PyArray_CastAnyTo \ + (PyArrayObject *, PyArrayObject *); +NPY_NO_EXPORT int PyArray_CanCastSafely \ + (int, int); +NPY_NO_EXPORT npy_bool PyArray_CanCastTo \ + (PyArray_Descr *, PyArray_Descr *); +NPY_NO_EXPORT int PyArray_ObjectType \ + (PyObject *, int); +NPY_NO_EXPORT PyArray_Descr * PyArray_DescrFromObject \ + (PyObject *, PyArray_Descr *); +NPY_NO_EXPORT PyArrayObject ** PyArray_ConvertToCommonType \ + (PyObject *, int *); +NPY_NO_EXPORT PyArray_Descr * PyArray_DescrFromScalar \ + (PyObject *); +NPY_NO_EXPORT PyArray_Descr * PyArray_DescrFromTypeObject \ + (PyObject *); +NPY_NO_EXPORT npy_intp PyArray_Size \ + (PyObject *); +NPY_NO_EXPORT PyObject * PyArray_Scalar \ + (void *, PyArray_Descr *, PyObject *); +NPY_NO_EXPORT PyObject * PyArray_FromScalar \ + (PyObject *, PyArray_Descr *); +NPY_NO_EXPORT void PyArray_ScalarAsCtype \ + (PyObject *, void *); +NPY_NO_EXPORT int PyArray_CastScalarToCtype \ + (PyObject *, void *, PyArray_Descr *); +NPY_NO_EXPORT int PyArray_CastScalarDirect \ + (PyObject *, PyArray_Descr *, void *, int); +NPY_NO_EXPORT PyObject * PyArray_ScalarFromObject \ + (PyObject *); +NPY_NO_EXPORT PyArray_VectorUnaryFunc * PyArray_GetCastFunc \ + (PyArray_Descr *, int); +NPY_NO_EXPORT PyObject * PyArray_FromDims \ + (int, int *, int); +NPY_NO_EXPORT PyObject * PyArray_FromDimsAndDataAndDescr \ + (int, int *, PyArray_Descr *, char *); +NPY_NO_EXPORT PyObject * PyArray_FromAny \ + (PyObject *, PyArray_Descr *, int, int, int, PyObject *); +NPY_NO_EXPORT PyObject * PyArray_EnsureArray \ + (PyObject *); +NPY_NO_EXPORT PyObject * PyArray_EnsureAnyArray \ + (PyObject *); +NPY_NO_EXPORT PyObject * PyArray_FromFile \ + (FILE *, PyArray_Descr *, npy_intp, char *); +NPY_NO_EXPORT PyObject * PyArray_FromString \ + (char *, npy_intp, PyArray_Descr *, npy_intp, char *); +NPY_NO_EXPORT PyObject * PyArray_FromBuffer \ + (PyObject *, PyArray_Descr *, npy_intp, npy_intp); +NPY_NO_EXPORT PyObject * PyArray_FromIter \ + (PyObject *, PyArray_Descr *, npy_intp); +NPY_NO_EXPORT PyObject * PyArray_Return \ + (PyArrayObject *); +NPY_NO_EXPORT PyObject * PyArray_GetField \ + (PyArrayObject *, PyArray_Descr *, int); +NPY_NO_EXPORT int PyArray_SetField \ + (PyArrayObject *, PyArray_Descr *, int, PyObject *); +NPY_NO_EXPORT PyObject * PyArray_Byteswap \ + (PyArrayObject *, npy_bool); +NPY_NO_EXPORT PyObject * PyArray_Resize \ + (PyArrayObject *, PyArray_Dims *, int, NPY_ORDER); +NPY_NO_EXPORT int PyArray_MoveInto \ + (PyArrayObject *, PyArrayObject *); +NPY_NO_EXPORT int PyArray_CopyInto \ + (PyArrayObject *, PyArrayObject *); +NPY_NO_EXPORT int PyArray_CopyAnyInto \ + (PyArrayObject *, PyArrayObject *); +NPY_NO_EXPORT int PyArray_CopyObject \ + (PyArrayObject *, PyObject *); +NPY_NO_EXPORT PyObject * PyArray_NewCopy \ + (PyArrayObject *, NPY_ORDER); +NPY_NO_EXPORT PyObject * PyArray_ToList \ + (PyArrayObject *); +NPY_NO_EXPORT PyObject * PyArray_ToString \ + (PyArrayObject *, NPY_ORDER); +NPY_NO_EXPORT int PyArray_ToFile \ + (PyArrayObject *, FILE *, char *, char *); +NPY_NO_EXPORT int PyArray_Dump \ + (PyObject *, PyObject *, int); +NPY_NO_EXPORT PyObject * PyArray_Dumps \ + (PyObject *, int); +NPY_NO_EXPORT int PyArray_ValidType \ + (int); +NPY_NO_EXPORT void PyArray_UpdateFlags \ + (PyArrayObject *, int); +NPY_NO_EXPORT PyObject * PyArray_New \ + (PyTypeObject *, int, npy_intp *, int, npy_intp *, void *, int, int, PyObject *); +NPY_NO_EXPORT PyObject * PyArray_NewFromDescr \ + (PyTypeObject *, PyArray_Descr *, int, npy_intp *, npy_intp *, void *, int, PyObject *); +NPY_NO_EXPORT PyArray_Descr * PyArray_DescrNew \ + (PyArray_Descr *); +NPY_NO_EXPORT PyArray_Descr * PyArray_DescrNewFromType \ + (int); +NPY_NO_EXPORT double PyArray_GetPriority \ + (PyObject *, double); +NPY_NO_EXPORT PyObject * PyArray_IterNew \ + (PyObject *); +NPY_NO_EXPORT PyObject * PyArray_MultiIterNew \ + (int, ...); +NPY_NO_EXPORT int PyArray_PyIntAsInt \ + (PyObject *); +NPY_NO_EXPORT npy_intp PyArray_PyIntAsIntp \ + (PyObject *); +NPY_NO_EXPORT int PyArray_Broadcast \ + (PyArrayMultiIterObject *); +NPY_NO_EXPORT void PyArray_FillObjectArray \ + (PyArrayObject *, PyObject *); +NPY_NO_EXPORT int PyArray_FillWithScalar \ + (PyArrayObject *, PyObject *); +NPY_NO_EXPORT npy_bool PyArray_CheckStrides \ + (int, int, npy_intp, npy_intp, npy_intp *, npy_intp *); +NPY_NO_EXPORT PyArray_Descr * PyArray_DescrNewByteorder \ + (PyArray_Descr *, char); +NPY_NO_EXPORT PyObject * PyArray_IterAllButAxis \ + (PyObject *, int *); +NPY_NO_EXPORT PyObject * PyArray_CheckFromAny \ + (PyObject *, PyArray_Descr *, int, int, int, PyObject *); +NPY_NO_EXPORT PyObject * PyArray_FromArray \ + (PyArrayObject *, PyArray_Descr *, int); +NPY_NO_EXPORT PyObject * PyArray_FromInterface \ + (PyObject *); +NPY_NO_EXPORT PyObject * PyArray_FromStructInterface \ + (PyObject *); +NPY_NO_EXPORT PyObject * PyArray_FromArrayAttr \ + (PyObject *, PyArray_Descr *, PyObject *); +NPY_NO_EXPORT NPY_SCALARKIND PyArray_ScalarKind \ + (int, PyArrayObject **); +NPY_NO_EXPORT int PyArray_CanCoerceScalar \ + (int, int, NPY_SCALARKIND); +NPY_NO_EXPORT PyObject * PyArray_NewFlagsObject \ + (PyObject *); +NPY_NO_EXPORT npy_bool PyArray_CanCastScalar \ + (PyTypeObject *, PyTypeObject *); +NPY_NO_EXPORT int PyArray_CompareUCS4 \ + (npy_ucs4 *, npy_ucs4 *, size_t); +NPY_NO_EXPORT int PyArray_RemoveSmallest \ + (PyArrayMultiIterObject *); +NPY_NO_EXPORT int PyArray_ElementStrides \ + (PyObject *); +NPY_NO_EXPORT void PyArray_Item_INCREF \ + (char *, PyArray_Descr *); +NPY_NO_EXPORT void PyArray_Item_XDECREF \ + (char *, PyArray_Descr *); +NPY_NO_EXPORT PyObject * PyArray_FieldNames \ + (PyObject *); +NPY_NO_EXPORT PyObject * PyArray_Transpose \ + (PyArrayObject *, PyArray_Dims *); +NPY_NO_EXPORT PyObject * PyArray_TakeFrom \ + (PyArrayObject *, PyObject *, int, PyArrayObject *, NPY_CLIPMODE); +NPY_NO_EXPORT PyObject * PyArray_PutTo \ + (PyArrayObject *, PyObject*, PyObject *, NPY_CLIPMODE); +NPY_NO_EXPORT PyObject * PyArray_PutMask \ + (PyArrayObject *, PyObject*, PyObject*); +NPY_NO_EXPORT PyObject * PyArray_Repeat \ + (PyArrayObject *, PyObject *, int); +NPY_NO_EXPORT PyObject * PyArray_Choose \ + (PyArrayObject *, PyObject *, PyArrayObject *, NPY_CLIPMODE); +NPY_NO_EXPORT int PyArray_Sort \ + (PyArrayObject *, int, NPY_SORTKIND); +NPY_NO_EXPORT PyObject * PyArray_ArgSort \ + (PyArrayObject *, int, NPY_SORTKIND); +NPY_NO_EXPORT PyObject * PyArray_SearchSorted \ + (PyArrayObject *, PyObject *, NPY_SEARCHSIDE, PyObject *); +NPY_NO_EXPORT PyObject * PyArray_ArgMax \ + (PyArrayObject *, int, PyArrayObject *); +NPY_NO_EXPORT PyObject * PyArray_ArgMin \ + (PyArrayObject *, int, PyArrayObject *); +NPY_NO_EXPORT PyObject * PyArray_Reshape \ + (PyArrayObject *, PyObject *); +NPY_NO_EXPORT PyObject * PyArray_Newshape \ + (PyArrayObject *, PyArray_Dims *, NPY_ORDER); +NPY_NO_EXPORT PyObject * PyArray_Squeeze \ + (PyArrayObject *); +NPY_NO_EXPORT PyObject * PyArray_View \ + (PyArrayObject *, PyArray_Descr *, PyTypeObject *); +NPY_NO_EXPORT PyObject * PyArray_SwapAxes \ + (PyArrayObject *, int, int); +NPY_NO_EXPORT PyObject * PyArray_Max \ + (PyArrayObject *, int, PyArrayObject *); +NPY_NO_EXPORT PyObject * PyArray_Min \ + (PyArrayObject *, int, PyArrayObject *); +NPY_NO_EXPORT PyObject * PyArray_Ptp \ + (PyArrayObject *, int, PyArrayObject *); +NPY_NO_EXPORT PyObject * PyArray_Mean \ + (PyArrayObject *, int, int, PyArrayObject *); +NPY_NO_EXPORT PyObject * PyArray_Trace \ + (PyArrayObject *, int, int, int, int, PyArrayObject *); +NPY_NO_EXPORT PyObject * PyArray_Diagonal \ + (PyArrayObject *, int, int, int); +NPY_NO_EXPORT PyObject * PyArray_Clip \ + (PyArrayObject *, PyObject *, PyObject *, PyArrayObject *); +NPY_NO_EXPORT PyObject * PyArray_Conjugate \ + (PyArrayObject *, PyArrayObject *); +NPY_NO_EXPORT PyObject * PyArray_Nonzero \ + (PyArrayObject *); +NPY_NO_EXPORT PyObject * PyArray_Std \ + (PyArrayObject *, int, int, PyArrayObject *, int); +NPY_NO_EXPORT PyObject * PyArray_Sum \ + (PyArrayObject *, int, int, PyArrayObject *); +NPY_NO_EXPORT PyObject * PyArray_CumSum \ + (PyArrayObject *, int, int, PyArrayObject *); +NPY_NO_EXPORT PyObject * PyArray_Prod \ + (PyArrayObject *, int, int, PyArrayObject *); +NPY_NO_EXPORT PyObject * PyArray_CumProd \ + (PyArrayObject *, int, int, PyArrayObject *); +NPY_NO_EXPORT PyObject * PyArray_All \ + (PyArrayObject *, int, PyArrayObject *); +NPY_NO_EXPORT PyObject * PyArray_Any \ + (PyArrayObject *, int, PyArrayObject *); +NPY_NO_EXPORT PyObject * PyArray_Compress \ + (PyArrayObject *, PyObject *, int, PyArrayObject *); +NPY_NO_EXPORT PyObject * PyArray_Flatten \ + (PyArrayObject *, NPY_ORDER); +NPY_NO_EXPORT PyObject * PyArray_Ravel \ + (PyArrayObject *, NPY_ORDER); +NPY_NO_EXPORT npy_intp PyArray_MultiplyList \ + (npy_intp *, int); +NPY_NO_EXPORT int PyArray_MultiplyIntList \ + (int *, int); +NPY_NO_EXPORT void * PyArray_GetPtr \ + (PyArrayObject *, npy_intp*); +NPY_NO_EXPORT int PyArray_CompareLists \ + (npy_intp *, npy_intp *, int); +NPY_NO_EXPORT int PyArray_AsCArray \ + (PyObject **, void *, npy_intp *, int, PyArray_Descr*); +NPY_NO_EXPORT int PyArray_As1D \ + (PyObject **, char **, int *, int); +NPY_NO_EXPORT int PyArray_As2D \ + (PyObject **, char ***, int *, int *, int); +NPY_NO_EXPORT int PyArray_Free \ + (PyObject *, void *); +NPY_NO_EXPORT int PyArray_Converter \ + (PyObject *, PyObject **); +NPY_NO_EXPORT int PyArray_IntpFromSequence \ + (PyObject *, npy_intp *, int); +NPY_NO_EXPORT PyObject * PyArray_Concatenate \ + (PyObject *, int); +NPY_NO_EXPORT PyObject * PyArray_InnerProduct \ + (PyObject *, PyObject *); +NPY_NO_EXPORT PyObject * PyArray_MatrixProduct \ + (PyObject *, PyObject *); +NPY_NO_EXPORT PyObject * PyArray_CopyAndTranspose \ + (PyObject *); +NPY_NO_EXPORT PyObject * PyArray_Correlate \ + (PyObject *, PyObject *, int); +NPY_NO_EXPORT int PyArray_TypestrConvert \ + (int, int); +NPY_NO_EXPORT int PyArray_DescrConverter \ + (PyObject *, PyArray_Descr **); +NPY_NO_EXPORT int PyArray_DescrConverter2 \ + (PyObject *, PyArray_Descr **); +NPY_NO_EXPORT int PyArray_IntpConverter \ + (PyObject *, PyArray_Dims *); +NPY_NO_EXPORT int PyArray_BufferConverter \ + (PyObject *, PyArray_Chunk *); +NPY_NO_EXPORT int PyArray_AxisConverter \ + (PyObject *, int *); +NPY_NO_EXPORT int PyArray_BoolConverter \ + (PyObject *, npy_bool *); +NPY_NO_EXPORT int PyArray_ByteorderConverter \ + (PyObject *, char *); +NPY_NO_EXPORT int PyArray_OrderConverter \ + (PyObject *, NPY_ORDER *); +NPY_NO_EXPORT unsigned char PyArray_EquivTypes \ + (PyArray_Descr *, PyArray_Descr *); +NPY_NO_EXPORT PyObject * PyArray_Zeros \ + (int, npy_intp *, PyArray_Descr *, int); +NPY_NO_EXPORT PyObject * PyArray_Empty \ + (int, npy_intp *, PyArray_Descr *, int); +NPY_NO_EXPORT PyObject * PyArray_Where \ + (PyObject *, PyObject *, PyObject *); +NPY_NO_EXPORT PyObject * PyArray_Arange \ + (double, double, double, int); +NPY_NO_EXPORT PyObject * PyArray_ArangeObj \ + (PyObject *, PyObject *, PyObject *, PyArray_Descr *); +NPY_NO_EXPORT int PyArray_SortkindConverter \ + (PyObject *, NPY_SORTKIND *); +NPY_NO_EXPORT PyObject * PyArray_LexSort \ + (PyObject *, int); +NPY_NO_EXPORT PyObject * PyArray_Round \ + (PyArrayObject *, int, PyArrayObject *); +NPY_NO_EXPORT unsigned char PyArray_EquivTypenums \ + (int, int); +NPY_NO_EXPORT int PyArray_RegisterDataType \ + (PyArray_Descr *); +NPY_NO_EXPORT int PyArray_RegisterCastFunc \ + (PyArray_Descr *, int, PyArray_VectorUnaryFunc *); +NPY_NO_EXPORT int PyArray_RegisterCanCast \ + (PyArray_Descr *, int, NPY_SCALARKIND); +NPY_NO_EXPORT void PyArray_InitArrFuncs \ + (PyArray_ArrFuncs *); +NPY_NO_EXPORT PyObject * PyArray_IntTupleFromIntp \ + (int, npy_intp *); +NPY_NO_EXPORT int PyArray_TypeNumFromName \ + (char *); +NPY_NO_EXPORT int PyArray_ClipmodeConverter \ + (PyObject *, NPY_CLIPMODE *); +NPY_NO_EXPORT int PyArray_OutputConverter \ + (PyObject *, PyArrayObject **); +NPY_NO_EXPORT PyObject * PyArray_BroadcastToShape \ + (PyObject *, npy_intp *, int); +NPY_NO_EXPORT void _PyArray_SigintHandler \ + (int); +NPY_NO_EXPORT void* _PyArray_GetSigintBuf \ + (void); +NPY_NO_EXPORT int PyArray_DescrAlignConverter \ + (PyObject *, PyArray_Descr **); +NPY_NO_EXPORT int PyArray_DescrAlignConverter2 \ + (PyObject *, PyArray_Descr **); +NPY_NO_EXPORT int PyArray_SearchsideConverter \ + (PyObject *, void *); +NPY_NO_EXPORT PyObject * PyArray_CheckAxis \ + (PyArrayObject *, int *, int); +NPY_NO_EXPORT npy_intp PyArray_OverflowMultiplyList \ + (npy_intp *, int); +NPY_NO_EXPORT int PyArray_CompareString \ + (char *, char *, size_t); +NPY_NO_EXPORT PyObject * PyArray_MultiIterFromObjects \ + (PyObject **, int, int, ...); +NPY_NO_EXPORT int PyArray_GetEndianness \ + (void); +NPY_NO_EXPORT unsigned int PyArray_GetNDArrayCFeatureVersion \ + (void); +NPY_NO_EXPORT PyObject * PyArray_Correlate2 \ + (PyObject *, PyObject *, int); +NPY_NO_EXPORT PyObject* PyArray_NeighborhoodIterNew \ + (PyArrayIterObject *, npy_intp *, int, PyArrayObject*); +#ifdef NPY_ENABLE_SEPARATE_COMPILATION + extern NPY_NO_EXPORT PyTypeObject PyTimeIntegerArrType_Type; +#else + NPY_NO_EXPORT PyTypeObject PyTimeIntegerArrType_Type; +#endif + +#ifdef NPY_ENABLE_SEPARATE_COMPILATION + extern NPY_NO_EXPORT PyTypeObject PyDatetimeArrType_Type; +#else + NPY_NO_EXPORT PyTypeObject PyDatetimeArrType_Type; +#endif + +#ifdef NPY_ENABLE_SEPARATE_COMPILATION + extern NPY_NO_EXPORT PyTypeObject PyTimedeltaArrType_Type; +#else + NPY_NO_EXPORT PyTypeObject PyTimedeltaArrType_Type; +#endif + +#ifdef NPY_ENABLE_SEPARATE_COMPILATION + extern NPY_NO_EXPORT PyTypeObject PyHalfArrType_Type; +#else + NPY_NO_EXPORT PyTypeObject PyHalfArrType_Type; +#endif + +#ifdef NPY_ENABLE_SEPARATE_COMPILATION + extern NPY_NO_EXPORT PyTypeObject NpyIter_Type; +#else + NPY_NO_EXPORT PyTypeObject NpyIter_Type; +#endif + +NPY_NO_EXPORT void PyArray_SetDatetimeParseFunction \ + (PyObject *); +NPY_NO_EXPORT void PyArray_DatetimeToDatetimeStruct \ + (npy_datetime, NPY_DATETIMEUNIT, npy_datetimestruct *); +NPY_NO_EXPORT void PyArray_TimedeltaToTimedeltaStruct \ + (npy_timedelta, NPY_DATETIMEUNIT, npy_timedeltastruct *); +NPY_NO_EXPORT npy_datetime PyArray_DatetimeStructToDatetime \ + (NPY_DATETIMEUNIT, npy_datetimestruct *); +NPY_NO_EXPORT npy_datetime PyArray_TimedeltaStructToTimedelta \ + (NPY_DATETIMEUNIT, npy_timedeltastruct *); +NPY_NO_EXPORT NpyIter * NpyIter_New \ + (PyArrayObject *, npy_uint32, NPY_ORDER, NPY_CASTING, PyArray_Descr*); +NPY_NO_EXPORT NpyIter * NpyIter_MultiNew \ + (int, PyArrayObject **, npy_uint32, NPY_ORDER, NPY_CASTING, npy_uint32 *, PyArray_Descr **); +NPY_NO_EXPORT NpyIter * NpyIter_AdvancedNew \ + (int, PyArrayObject **, npy_uint32, NPY_ORDER, NPY_CASTING, npy_uint32 *, PyArray_Descr **, int, int **, npy_intp *, npy_intp); +NPY_NO_EXPORT NpyIter * NpyIter_Copy \ + (NpyIter *); +NPY_NO_EXPORT int NpyIter_Deallocate \ + (NpyIter *); +NPY_NO_EXPORT npy_bool NpyIter_HasDelayedBufAlloc \ + (NpyIter *); +NPY_NO_EXPORT npy_bool NpyIter_HasExternalLoop \ + (NpyIter *); +NPY_NO_EXPORT int NpyIter_EnableExternalLoop \ + (NpyIter *); +NPY_NO_EXPORT npy_intp * NpyIter_GetInnerStrideArray \ + (NpyIter *); +NPY_NO_EXPORT npy_intp * NpyIter_GetInnerLoopSizePtr \ + (NpyIter *); +NPY_NO_EXPORT int NpyIter_Reset \ + (NpyIter *, char **); +NPY_NO_EXPORT int NpyIter_ResetBasePointers \ + (NpyIter *, char **, char **); +NPY_NO_EXPORT int NpyIter_ResetToIterIndexRange \ + (NpyIter *, npy_intp, npy_intp, char **); +NPY_NO_EXPORT int NpyIter_GetNDim \ + (NpyIter *); +NPY_NO_EXPORT int NpyIter_GetNOp \ + (NpyIter *); +NPY_NO_EXPORT NpyIter_IterNextFunc * NpyIter_GetIterNext \ + (NpyIter *, char **); +NPY_NO_EXPORT npy_intp NpyIter_GetIterSize \ + (NpyIter *); +NPY_NO_EXPORT void NpyIter_GetIterIndexRange \ + (NpyIter *, npy_intp *, npy_intp *); +NPY_NO_EXPORT npy_intp NpyIter_GetIterIndex \ + (NpyIter *); +NPY_NO_EXPORT int NpyIter_GotoIterIndex \ + (NpyIter *, npy_intp); +NPY_NO_EXPORT npy_bool NpyIter_HasMultiIndex \ + (NpyIter *); +NPY_NO_EXPORT int NpyIter_GetShape \ + (NpyIter *, npy_intp *); +NPY_NO_EXPORT NpyIter_GetMultiIndexFunc * NpyIter_GetGetMultiIndex \ + (NpyIter *, char **); +NPY_NO_EXPORT int NpyIter_GotoMultiIndex \ + (NpyIter *, npy_intp *); +NPY_NO_EXPORT int NpyIter_RemoveMultiIndex \ + (NpyIter *); +NPY_NO_EXPORT npy_bool NpyIter_HasIndex \ + (NpyIter *); +NPY_NO_EXPORT npy_bool NpyIter_IsBuffered \ + (NpyIter *); +NPY_NO_EXPORT npy_bool NpyIter_IsGrowInner \ + (NpyIter *); +NPY_NO_EXPORT npy_intp NpyIter_GetBufferSize \ + (NpyIter *); +NPY_NO_EXPORT npy_intp * NpyIter_GetIndexPtr \ + (NpyIter *); +NPY_NO_EXPORT int NpyIter_GotoIndex \ + (NpyIter *, npy_intp); +NPY_NO_EXPORT char ** NpyIter_GetDataPtrArray \ + (NpyIter *); +NPY_NO_EXPORT PyArray_Descr ** NpyIter_GetDescrArray \ + (NpyIter *); +NPY_NO_EXPORT PyArrayObject ** NpyIter_GetOperandArray \ + (NpyIter *); +NPY_NO_EXPORT PyArrayObject * NpyIter_GetIterView \ + (NpyIter *, npy_intp); +NPY_NO_EXPORT void NpyIter_GetReadFlags \ + (NpyIter *, char *); +NPY_NO_EXPORT void NpyIter_GetWriteFlags \ + (NpyIter *, char *); +NPY_NO_EXPORT void NpyIter_DebugPrint \ + (NpyIter *); +NPY_NO_EXPORT npy_bool NpyIter_IterationNeedsAPI \ + (NpyIter *); +NPY_NO_EXPORT void NpyIter_GetInnerFixedStrideArray \ + (NpyIter *, npy_intp *); +NPY_NO_EXPORT int NpyIter_RemoveAxis \ + (NpyIter *, int); +NPY_NO_EXPORT npy_intp * NpyIter_GetAxisStrideArray \ + (NpyIter *, int); +NPY_NO_EXPORT npy_bool NpyIter_RequiresBuffering \ + (NpyIter *); +NPY_NO_EXPORT char ** NpyIter_GetInitialDataPtrArray \ + (NpyIter *); +NPY_NO_EXPORT int NpyIter_CreateCompatibleStrides \ + (NpyIter *, npy_intp, npy_intp *); +NPY_NO_EXPORT int PyArray_CastingConverter \ + (PyObject *, NPY_CASTING *); +NPY_NO_EXPORT npy_intp PyArray_CountNonzero \ + (PyArrayObject *); +NPY_NO_EXPORT PyArray_Descr * PyArray_PromoteTypes \ + (PyArray_Descr *, PyArray_Descr *); +NPY_NO_EXPORT PyArray_Descr * PyArray_MinScalarType \ + (PyArrayObject *); +NPY_NO_EXPORT PyArray_Descr * PyArray_ResultType \ + (npy_intp, PyArrayObject **, npy_intp, PyArray_Descr **); +NPY_NO_EXPORT npy_bool PyArray_CanCastArrayTo \ + (PyArrayObject *, PyArray_Descr *, NPY_CASTING); +NPY_NO_EXPORT npy_bool PyArray_CanCastTypeTo \ + (PyArray_Descr *, PyArray_Descr *, NPY_CASTING); +NPY_NO_EXPORT PyArrayObject * PyArray_EinsteinSum \ + (char *, npy_intp, PyArrayObject **, PyArray_Descr *, NPY_ORDER, NPY_CASTING, PyArrayObject *); +NPY_NO_EXPORT PyObject * PyArray_NewLikeArray \ + (PyArrayObject *, NPY_ORDER, PyArray_Descr *, int); +NPY_NO_EXPORT int PyArray_GetArrayParamsFromObject \ + (PyObject *, PyArray_Descr *, npy_bool, PyArray_Descr **, int *, npy_intp *, PyArrayObject **, PyObject *); +NPY_NO_EXPORT int PyArray_ConvertClipmodeSequence \ + (PyObject *, NPY_CLIPMODE *, int); +NPY_NO_EXPORT PyObject * PyArray_MatrixProduct2 \ + (PyObject *, PyObject *, PyArrayObject*); +NPY_NO_EXPORT npy_bool NpyIter_IsFirstVisit \ + (NpyIter *, int); +NPY_NO_EXPORT int PyArray_SetBaseObject \ + (PyArrayObject *, PyObject *); +NPY_NO_EXPORT void PyArray_CreateSortedStridePerm \ + (int, npy_intp *, npy_stride_sort_item *); +NPY_NO_EXPORT void PyArray_RemoveAxesInPlace \ + (PyArrayObject *, npy_bool *); +NPY_NO_EXPORT void PyArray_DebugPrint \ + (PyArrayObject *); +NPY_NO_EXPORT int PyArray_FailUnlessWriteable \ + (PyArrayObject *, const char *); +NPY_NO_EXPORT int PyArray_SetUpdateIfCopyBase \ + (PyArrayObject *, PyArrayObject *); +NPY_NO_EXPORT void * PyDataMem_NEW \ + (size_t); +NPY_NO_EXPORT void PyDataMem_FREE \ + (void *); +NPY_NO_EXPORT void * PyDataMem_RENEW \ + (void *, size_t); +NPY_NO_EXPORT PyDataMem_EventHookFunc * PyDataMem_SetEventHook \ + (PyDataMem_EventHookFunc *, void *, void **); +#ifdef NPY_ENABLE_SEPARATE_COMPILATION + extern NPY_NO_EXPORT NPY_CASTING NPY_DEFAULT_ASSIGN_CASTING; +#else + NPY_NO_EXPORT NPY_CASTING NPY_DEFAULT_ASSIGN_CASTING; +#endif + + +#else + +#if defined(PY_ARRAY_UNIQUE_SYMBOL) +#define PyArray_API PY_ARRAY_UNIQUE_SYMBOL +#endif + +#if defined(NO_IMPORT) || defined(NO_IMPORT_ARRAY) +extern void **PyArray_API; +#else +#if defined(PY_ARRAY_UNIQUE_SYMBOL) +void **PyArray_API; +#else +static void **PyArray_API=NULL; +#endif +#endif + +#define PyArray_GetNDArrayCVersion \ + (*(unsigned int (*)(void)) \ + PyArray_API[0]) +#define PyBigArray_Type (*(PyTypeObject *)PyArray_API[1]) +#define PyArray_Type (*(PyTypeObject *)PyArray_API[2]) +#define PyArrayDescr_Type (*(PyTypeObject *)PyArray_API[3]) +#define PyArrayFlags_Type (*(PyTypeObject *)PyArray_API[4]) +#define PyArrayIter_Type (*(PyTypeObject *)PyArray_API[5]) +#define PyArrayMultiIter_Type (*(PyTypeObject *)PyArray_API[6]) +#define NPY_NUMUSERTYPES (*(int *)PyArray_API[7]) +#define PyBoolArrType_Type (*(PyTypeObject *)PyArray_API[8]) +#define _PyArrayScalar_BoolValues ((PyBoolScalarObject *)PyArray_API[9]) +#define PyGenericArrType_Type (*(PyTypeObject *)PyArray_API[10]) +#define PyNumberArrType_Type (*(PyTypeObject *)PyArray_API[11]) +#define PyIntegerArrType_Type (*(PyTypeObject *)PyArray_API[12]) +#define PySignedIntegerArrType_Type (*(PyTypeObject *)PyArray_API[13]) +#define PyUnsignedIntegerArrType_Type (*(PyTypeObject *)PyArray_API[14]) +#define PyInexactArrType_Type (*(PyTypeObject *)PyArray_API[15]) +#define PyFloatingArrType_Type (*(PyTypeObject *)PyArray_API[16]) +#define PyComplexFloatingArrType_Type (*(PyTypeObject *)PyArray_API[17]) +#define PyFlexibleArrType_Type (*(PyTypeObject *)PyArray_API[18]) +#define PyCharacterArrType_Type (*(PyTypeObject *)PyArray_API[19]) +#define PyByteArrType_Type (*(PyTypeObject *)PyArray_API[20]) +#define PyShortArrType_Type (*(PyTypeObject *)PyArray_API[21]) +#define PyIntArrType_Type (*(PyTypeObject *)PyArray_API[22]) +#define PyLongArrType_Type (*(PyTypeObject *)PyArray_API[23]) +#define PyLongLongArrType_Type (*(PyTypeObject *)PyArray_API[24]) +#define PyUByteArrType_Type (*(PyTypeObject *)PyArray_API[25]) +#define PyUShortArrType_Type (*(PyTypeObject *)PyArray_API[26]) +#define PyUIntArrType_Type (*(PyTypeObject *)PyArray_API[27]) +#define PyULongArrType_Type (*(PyTypeObject *)PyArray_API[28]) +#define PyULongLongArrType_Type (*(PyTypeObject *)PyArray_API[29]) +#define PyFloatArrType_Type (*(PyTypeObject *)PyArray_API[30]) +#define PyDoubleArrType_Type (*(PyTypeObject *)PyArray_API[31]) +#define PyLongDoubleArrType_Type (*(PyTypeObject *)PyArray_API[32]) +#define PyCFloatArrType_Type (*(PyTypeObject *)PyArray_API[33]) +#define PyCDoubleArrType_Type (*(PyTypeObject *)PyArray_API[34]) +#define PyCLongDoubleArrType_Type (*(PyTypeObject *)PyArray_API[35]) +#define PyObjectArrType_Type (*(PyTypeObject *)PyArray_API[36]) +#define PyStringArrType_Type (*(PyTypeObject *)PyArray_API[37]) +#define PyUnicodeArrType_Type (*(PyTypeObject *)PyArray_API[38]) +#define PyVoidArrType_Type (*(PyTypeObject *)PyArray_API[39]) +#define PyArray_SetNumericOps \ + (*(int (*)(PyObject *)) \ + PyArray_API[40]) +#define PyArray_GetNumericOps \ + (*(PyObject * (*)(void)) \ + PyArray_API[41]) +#define PyArray_INCREF \ + (*(int (*)(PyArrayObject *)) \ + PyArray_API[42]) +#define PyArray_XDECREF \ + (*(int (*)(PyArrayObject *)) \ + PyArray_API[43]) +#define PyArray_SetStringFunction \ + (*(void (*)(PyObject *, int)) \ + PyArray_API[44]) +#define PyArray_DescrFromType \ + (*(PyArray_Descr * (*)(int)) \ + PyArray_API[45]) +#define PyArray_TypeObjectFromType \ + (*(PyObject * (*)(int)) \ + PyArray_API[46]) +#define PyArray_Zero \ + (*(char * (*)(PyArrayObject *)) \ + PyArray_API[47]) +#define PyArray_One \ + (*(char * (*)(PyArrayObject *)) \ + PyArray_API[48]) +#define PyArray_CastToType \ + (*(PyObject * (*)(PyArrayObject *, PyArray_Descr *, int)) \ + PyArray_API[49]) +#define PyArray_CastTo \ + (*(int (*)(PyArrayObject *, PyArrayObject *)) \ + PyArray_API[50]) +#define PyArray_CastAnyTo \ + (*(int (*)(PyArrayObject *, PyArrayObject *)) \ + PyArray_API[51]) +#define PyArray_CanCastSafely \ + (*(int (*)(int, int)) \ + PyArray_API[52]) +#define PyArray_CanCastTo \ + (*(npy_bool (*)(PyArray_Descr *, PyArray_Descr *)) \ + PyArray_API[53]) +#define PyArray_ObjectType \ + (*(int (*)(PyObject *, int)) \ + PyArray_API[54]) +#define PyArray_DescrFromObject \ + (*(PyArray_Descr * (*)(PyObject *, PyArray_Descr *)) \ + PyArray_API[55]) +#define PyArray_ConvertToCommonType \ + (*(PyArrayObject ** (*)(PyObject *, int *)) \ + PyArray_API[56]) +#define PyArray_DescrFromScalar \ + (*(PyArray_Descr * (*)(PyObject *)) \ + PyArray_API[57]) +#define PyArray_DescrFromTypeObject \ + (*(PyArray_Descr * (*)(PyObject *)) \ + PyArray_API[58]) +#define PyArray_Size \ + (*(npy_intp (*)(PyObject *)) \ + PyArray_API[59]) +#define PyArray_Scalar \ + (*(PyObject * (*)(void *, PyArray_Descr *, PyObject *)) \ + PyArray_API[60]) +#define PyArray_FromScalar \ + (*(PyObject * (*)(PyObject *, PyArray_Descr *)) \ + PyArray_API[61]) +#define PyArray_ScalarAsCtype \ + (*(void (*)(PyObject *, void *)) \ + PyArray_API[62]) +#define PyArray_CastScalarToCtype \ + (*(int (*)(PyObject *, void *, PyArray_Descr *)) \ + PyArray_API[63]) +#define PyArray_CastScalarDirect \ + (*(int (*)(PyObject *, PyArray_Descr *, void *, int)) \ + PyArray_API[64]) +#define PyArray_ScalarFromObject \ + (*(PyObject * (*)(PyObject *)) \ + PyArray_API[65]) +#define PyArray_GetCastFunc \ + (*(PyArray_VectorUnaryFunc * (*)(PyArray_Descr *, int)) \ + PyArray_API[66]) +#define PyArray_FromDims \ + (*(PyObject * (*)(int, int *, int)) \ + PyArray_API[67]) +#define PyArray_FromDimsAndDataAndDescr \ + (*(PyObject * (*)(int, int *, PyArray_Descr *, char *)) \ + PyArray_API[68]) +#define PyArray_FromAny \ + (*(PyObject * (*)(PyObject *, PyArray_Descr *, int, int, int, PyObject *)) \ + PyArray_API[69]) +#define PyArray_EnsureArray \ + (*(PyObject * (*)(PyObject *)) \ + PyArray_API[70]) +#define PyArray_EnsureAnyArray \ + (*(PyObject * (*)(PyObject *)) \ + PyArray_API[71]) +#define PyArray_FromFile \ + (*(PyObject * (*)(FILE *, PyArray_Descr *, npy_intp, char *)) \ + PyArray_API[72]) +#define PyArray_FromString \ + (*(PyObject * (*)(char *, npy_intp, PyArray_Descr *, npy_intp, char *)) \ + PyArray_API[73]) +#define PyArray_FromBuffer \ + (*(PyObject * (*)(PyObject *, PyArray_Descr *, npy_intp, npy_intp)) \ + PyArray_API[74]) +#define PyArray_FromIter \ + (*(PyObject * (*)(PyObject *, PyArray_Descr *, npy_intp)) \ + PyArray_API[75]) +#define PyArray_Return \ + (*(PyObject * (*)(PyArrayObject *)) \ + PyArray_API[76]) +#define PyArray_GetField \ + (*(PyObject * (*)(PyArrayObject *, PyArray_Descr *, int)) \ + PyArray_API[77]) +#define PyArray_SetField \ + (*(int (*)(PyArrayObject *, PyArray_Descr *, int, PyObject *)) \ + PyArray_API[78]) +#define PyArray_Byteswap \ + (*(PyObject * (*)(PyArrayObject *, npy_bool)) \ + PyArray_API[79]) +#define PyArray_Resize \ + (*(PyObject * (*)(PyArrayObject *, PyArray_Dims *, int, NPY_ORDER)) \ + PyArray_API[80]) +#define PyArray_MoveInto \ + (*(int (*)(PyArrayObject *, PyArrayObject *)) \ + PyArray_API[81]) +#define PyArray_CopyInto \ + (*(int (*)(PyArrayObject *, PyArrayObject *)) \ + PyArray_API[82]) +#define PyArray_CopyAnyInto \ + (*(int (*)(PyArrayObject *, PyArrayObject *)) \ + PyArray_API[83]) +#define PyArray_CopyObject \ + (*(int (*)(PyArrayObject *, PyObject *)) \ + PyArray_API[84]) +#define PyArray_NewCopy \ + (*(PyObject * (*)(PyArrayObject *, NPY_ORDER)) \ + PyArray_API[85]) +#define PyArray_ToList \ + (*(PyObject * (*)(PyArrayObject *)) \ + PyArray_API[86]) +#define PyArray_ToString \ + (*(PyObject * (*)(PyArrayObject *, NPY_ORDER)) \ + PyArray_API[87]) +#define PyArray_ToFile \ + (*(int (*)(PyArrayObject *, FILE *, char *, char *)) \ + PyArray_API[88]) +#define PyArray_Dump \ + (*(int (*)(PyObject *, PyObject *, int)) \ + PyArray_API[89]) +#define PyArray_Dumps \ + (*(PyObject * (*)(PyObject *, int)) \ + PyArray_API[90]) +#define PyArray_ValidType \ + (*(int (*)(int)) \ + PyArray_API[91]) +#define PyArray_UpdateFlags \ + (*(void (*)(PyArrayObject *, int)) \ + PyArray_API[92]) +#define PyArray_New \ + (*(PyObject * (*)(PyTypeObject *, int, npy_intp *, int, npy_intp *, void *, int, int, PyObject *)) \ + PyArray_API[93]) +#define PyArray_NewFromDescr \ + (*(PyObject * (*)(PyTypeObject *, PyArray_Descr *, int, npy_intp *, npy_intp *, void *, int, PyObject *)) \ + PyArray_API[94]) +#define PyArray_DescrNew \ + (*(PyArray_Descr * (*)(PyArray_Descr *)) \ + PyArray_API[95]) +#define PyArray_DescrNewFromType \ + (*(PyArray_Descr * (*)(int)) \ + PyArray_API[96]) +#define PyArray_GetPriority \ + (*(double (*)(PyObject *, double)) \ + PyArray_API[97]) +#define PyArray_IterNew \ + (*(PyObject * (*)(PyObject *)) \ + PyArray_API[98]) +#define PyArray_MultiIterNew \ + (*(PyObject * (*)(int, ...)) \ + PyArray_API[99]) +#define PyArray_PyIntAsInt \ + (*(int (*)(PyObject *)) \ + PyArray_API[100]) +#define PyArray_PyIntAsIntp \ + (*(npy_intp (*)(PyObject *)) \ + PyArray_API[101]) +#define PyArray_Broadcast \ + (*(int (*)(PyArrayMultiIterObject *)) \ + PyArray_API[102]) +#define PyArray_FillObjectArray \ + (*(void (*)(PyArrayObject *, PyObject *)) \ + PyArray_API[103]) +#define PyArray_FillWithScalar \ + (*(int (*)(PyArrayObject *, PyObject *)) \ + PyArray_API[104]) +#define PyArray_CheckStrides \ + (*(npy_bool (*)(int, int, npy_intp, npy_intp, npy_intp *, npy_intp *)) \ + PyArray_API[105]) +#define PyArray_DescrNewByteorder \ + (*(PyArray_Descr * (*)(PyArray_Descr *, char)) \ + PyArray_API[106]) +#define PyArray_IterAllButAxis \ + (*(PyObject * (*)(PyObject *, int *)) \ + PyArray_API[107]) +#define PyArray_CheckFromAny \ + (*(PyObject * (*)(PyObject *, PyArray_Descr *, int, int, int, PyObject *)) \ + PyArray_API[108]) +#define PyArray_FromArray \ + (*(PyObject * (*)(PyArrayObject *, PyArray_Descr *, int)) \ + PyArray_API[109]) +#define PyArray_FromInterface \ + (*(PyObject * (*)(PyObject *)) \ + PyArray_API[110]) +#define PyArray_FromStructInterface \ + (*(PyObject * (*)(PyObject *)) \ + PyArray_API[111]) +#define PyArray_FromArrayAttr \ + (*(PyObject * (*)(PyObject *, PyArray_Descr *, PyObject *)) \ + PyArray_API[112]) +#define PyArray_ScalarKind \ + (*(NPY_SCALARKIND (*)(int, PyArrayObject **)) \ + PyArray_API[113]) +#define PyArray_CanCoerceScalar \ + (*(int (*)(int, int, NPY_SCALARKIND)) \ + PyArray_API[114]) +#define PyArray_NewFlagsObject \ + (*(PyObject * (*)(PyObject *)) \ + PyArray_API[115]) +#define PyArray_CanCastScalar \ + (*(npy_bool (*)(PyTypeObject *, PyTypeObject *)) \ + PyArray_API[116]) +#define PyArray_CompareUCS4 \ + (*(int (*)(npy_ucs4 *, npy_ucs4 *, size_t)) \ + PyArray_API[117]) +#define PyArray_RemoveSmallest \ + (*(int (*)(PyArrayMultiIterObject *)) \ + PyArray_API[118]) +#define PyArray_ElementStrides \ + (*(int (*)(PyObject *)) \ + PyArray_API[119]) +#define PyArray_Item_INCREF \ + (*(void (*)(char *, PyArray_Descr *)) \ + PyArray_API[120]) +#define PyArray_Item_XDECREF \ + (*(void (*)(char *, PyArray_Descr *)) \ + PyArray_API[121]) +#define PyArray_FieldNames \ + (*(PyObject * (*)(PyObject *)) \ + PyArray_API[122]) +#define PyArray_Transpose \ + (*(PyObject * (*)(PyArrayObject *, PyArray_Dims *)) \ + PyArray_API[123]) +#define PyArray_TakeFrom \ + (*(PyObject * (*)(PyArrayObject *, PyObject *, int, PyArrayObject *, NPY_CLIPMODE)) \ + PyArray_API[124]) +#define PyArray_PutTo \ + (*(PyObject * (*)(PyArrayObject *, PyObject*, PyObject *, NPY_CLIPMODE)) \ + PyArray_API[125]) +#define PyArray_PutMask \ + (*(PyObject * (*)(PyArrayObject *, PyObject*, PyObject*)) \ + PyArray_API[126]) +#define PyArray_Repeat \ + (*(PyObject * (*)(PyArrayObject *, PyObject *, int)) \ + PyArray_API[127]) +#define PyArray_Choose \ + (*(PyObject * (*)(PyArrayObject *, PyObject *, PyArrayObject *, NPY_CLIPMODE)) \ + PyArray_API[128]) +#define PyArray_Sort \ + (*(int (*)(PyArrayObject *, int, NPY_SORTKIND)) \ + PyArray_API[129]) +#define PyArray_ArgSort \ + (*(PyObject * (*)(PyArrayObject *, int, NPY_SORTKIND)) \ + PyArray_API[130]) +#define PyArray_SearchSorted \ + (*(PyObject * (*)(PyArrayObject *, PyObject *, NPY_SEARCHSIDE, PyObject *)) \ + PyArray_API[131]) +#define PyArray_ArgMax \ + (*(PyObject * (*)(PyArrayObject *, int, PyArrayObject *)) \ + PyArray_API[132]) +#define PyArray_ArgMin \ + (*(PyObject * (*)(PyArrayObject *, int, PyArrayObject *)) \ + PyArray_API[133]) +#define PyArray_Reshape \ + (*(PyObject * (*)(PyArrayObject *, PyObject *)) \ + PyArray_API[134]) +#define PyArray_Newshape \ + (*(PyObject * (*)(PyArrayObject *, PyArray_Dims *, NPY_ORDER)) \ + PyArray_API[135]) +#define PyArray_Squeeze \ + (*(PyObject * (*)(PyArrayObject *)) \ + PyArray_API[136]) +#define PyArray_View \ + (*(PyObject * (*)(PyArrayObject *, PyArray_Descr *, PyTypeObject *)) \ + PyArray_API[137]) +#define PyArray_SwapAxes \ + (*(PyObject * (*)(PyArrayObject *, int, int)) \ + PyArray_API[138]) +#define PyArray_Max \ + (*(PyObject * (*)(PyArrayObject *, int, PyArrayObject *)) \ + PyArray_API[139]) +#define PyArray_Min \ + (*(PyObject * (*)(PyArrayObject *, int, PyArrayObject *)) \ + PyArray_API[140]) +#define PyArray_Ptp \ + (*(PyObject * (*)(PyArrayObject *, int, PyArrayObject *)) \ + PyArray_API[141]) +#define PyArray_Mean \ + (*(PyObject * (*)(PyArrayObject *, int, int, PyArrayObject *)) \ + PyArray_API[142]) +#define PyArray_Trace \ + (*(PyObject * (*)(PyArrayObject *, int, int, int, int, PyArrayObject *)) \ + PyArray_API[143]) +#define PyArray_Diagonal \ + (*(PyObject * (*)(PyArrayObject *, int, int, int)) \ + PyArray_API[144]) +#define PyArray_Clip \ + (*(PyObject * (*)(PyArrayObject *, PyObject *, PyObject *, PyArrayObject *)) \ + PyArray_API[145]) +#define PyArray_Conjugate \ + (*(PyObject * (*)(PyArrayObject *, PyArrayObject *)) \ + PyArray_API[146]) +#define PyArray_Nonzero \ + (*(PyObject * (*)(PyArrayObject *)) \ + PyArray_API[147]) +#define PyArray_Std \ + (*(PyObject * (*)(PyArrayObject *, int, int, PyArrayObject *, int)) \ + PyArray_API[148]) +#define PyArray_Sum \ + (*(PyObject * (*)(PyArrayObject *, int, int, PyArrayObject *)) \ + PyArray_API[149]) +#define PyArray_CumSum \ + (*(PyObject * (*)(PyArrayObject *, int, int, PyArrayObject *)) \ + PyArray_API[150]) +#define PyArray_Prod \ + (*(PyObject * (*)(PyArrayObject *, int, int, PyArrayObject *)) \ + PyArray_API[151]) +#define PyArray_CumProd \ + (*(PyObject * (*)(PyArrayObject *, int, int, PyArrayObject *)) \ + PyArray_API[152]) +#define PyArray_All \ + (*(PyObject * (*)(PyArrayObject *, int, PyArrayObject *)) \ + PyArray_API[153]) +#define PyArray_Any \ + (*(PyObject * (*)(PyArrayObject *, int, PyArrayObject *)) \ + PyArray_API[154]) +#define PyArray_Compress \ + (*(PyObject * (*)(PyArrayObject *, PyObject *, int, PyArrayObject *)) \ + PyArray_API[155]) +#define PyArray_Flatten \ + (*(PyObject * (*)(PyArrayObject *, NPY_ORDER)) \ + PyArray_API[156]) +#define PyArray_Ravel \ + (*(PyObject * (*)(PyArrayObject *, NPY_ORDER)) \ + PyArray_API[157]) +#define PyArray_MultiplyList \ + (*(npy_intp (*)(npy_intp *, int)) \ + PyArray_API[158]) +#define PyArray_MultiplyIntList \ + (*(int (*)(int *, int)) \ + PyArray_API[159]) +#define PyArray_GetPtr \ + (*(void * (*)(PyArrayObject *, npy_intp*)) \ + PyArray_API[160]) +#define PyArray_CompareLists \ + (*(int (*)(npy_intp *, npy_intp *, int)) \ + PyArray_API[161]) +#define PyArray_AsCArray \ + (*(int (*)(PyObject **, void *, npy_intp *, int, PyArray_Descr*)) \ + PyArray_API[162]) +#define PyArray_As1D \ + (*(int (*)(PyObject **, char **, int *, int)) \ + PyArray_API[163]) +#define PyArray_As2D \ + (*(int (*)(PyObject **, char ***, int *, int *, int)) \ + PyArray_API[164]) +#define PyArray_Free \ + (*(int (*)(PyObject *, void *)) \ + PyArray_API[165]) +#define PyArray_Converter \ + (*(int (*)(PyObject *, PyObject **)) \ + PyArray_API[166]) +#define PyArray_IntpFromSequence \ + (*(int (*)(PyObject *, npy_intp *, int)) \ + PyArray_API[167]) +#define PyArray_Concatenate \ + (*(PyObject * (*)(PyObject *, int)) \ + PyArray_API[168]) +#define PyArray_InnerProduct \ + (*(PyObject * (*)(PyObject *, PyObject *)) \ + PyArray_API[169]) +#define PyArray_MatrixProduct \ + (*(PyObject * (*)(PyObject *, PyObject *)) \ + PyArray_API[170]) +#define PyArray_CopyAndTranspose \ + (*(PyObject * (*)(PyObject *)) \ + PyArray_API[171]) +#define PyArray_Correlate \ + (*(PyObject * (*)(PyObject *, PyObject *, int)) \ + PyArray_API[172]) +#define PyArray_TypestrConvert \ + (*(int (*)(int, int)) \ + PyArray_API[173]) +#define PyArray_DescrConverter \ + (*(int (*)(PyObject *, PyArray_Descr **)) \ + PyArray_API[174]) +#define PyArray_DescrConverter2 \ + (*(int (*)(PyObject *, PyArray_Descr **)) \ + PyArray_API[175]) +#define PyArray_IntpConverter \ + (*(int (*)(PyObject *, PyArray_Dims *)) \ + PyArray_API[176]) +#define PyArray_BufferConverter \ + (*(int (*)(PyObject *, PyArray_Chunk *)) \ + PyArray_API[177]) +#define PyArray_AxisConverter \ + (*(int (*)(PyObject *, int *)) \ + PyArray_API[178]) +#define PyArray_BoolConverter \ + (*(int (*)(PyObject *, npy_bool *)) \ + PyArray_API[179]) +#define PyArray_ByteorderConverter \ + (*(int (*)(PyObject *, char *)) \ + PyArray_API[180]) +#define PyArray_OrderConverter \ + (*(int (*)(PyObject *, NPY_ORDER *)) \ + PyArray_API[181]) +#define PyArray_EquivTypes \ + (*(unsigned char (*)(PyArray_Descr *, PyArray_Descr *)) \ + PyArray_API[182]) +#define PyArray_Zeros \ + (*(PyObject * (*)(int, npy_intp *, PyArray_Descr *, int)) \ + PyArray_API[183]) +#define PyArray_Empty \ + (*(PyObject * (*)(int, npy_intp *, PyArray_Descr *, int)) \ + PyArray_API[184]) +#define PyArray_Where \ + (*(PyObject * (*)(PyObject *, PyObject *, PyObject *)) \ + PyArray_API[185]) +#define PyArray_Arange \ + (*(PyObject * (*)(double, double, double, int)) \ + PyArray_API[186]) +#define PyArray_ArangeObj \ + (*(PyObject * (*)(PyObject *, PyObject *, PyObject *, PyArray_Descr *)) \ + PyArray_API[187]) +#define PyArray_SortkindConverter \ + (*(int (*)(PyObject *, NPY_SORTKIND *)) \ + PyArray_API[188]) +#define PyArray_LexSort \ + (*(PyObject * (*)(PyObject *, int)) \ + PyArray_API[189]) +#define PyArray_Round \ + (*(PyObject * (*)(PyArrayObject *, int, PyArrayObject *)) \ + PyArray_API[190]) +#define PyArray_EquivTypenums \ + (*(unsigned char (*)(int, int)) \ + PyArray_API[191]) +#define PyArray_RegisterDataType \ + (*(int (*)(PyArray_Descr *)) \ + PyArray_API[192]) +#define PyArray_RegisterCastFunc \ + (*(int (*)(PyArray_Descr *, int, PyArray_VectorUnaryFunc *)) \ + PyArray_API[193]) +#define PyArray_RegisterCanCast \ + (*(int (*)(PyArray_Descr *, int, NPY_SCALARKIND)) \ + PyArray_API[194]) +#define PyArray_InitArrFuncs \ + (*(void (*)(PyArray_ArrFuncs *)) \ + PyArray_API[195]) +#define PyArray_IntTupleFromIntp \ + (*(PyObject * (*)(int, npy_intp *)) \ + PyArray_API[196]) +#define PyArray_TypeNumFromName \ + (*(int (*)(char *)) \ + PyArray_API[197]) +#define PyArray_ClipmodeConverter \ + (*(int (*)(PyObject *, NPY_CLIPMODE *)) \ + PyArray_API[198]) +#define PyArray_OutputConverter \ + (*(int (*)(PyObject *, PyArrayObject **)) \ + PyArray_API[199]) +#define PyArray_BroadcastToShape \ + (*(PyObject * (*)(PyObject *, npy_intp *, int)) \ + PyArray_API[200]) +#define _PyArray_SigintHandler \ + (*(void (*)(int)) \ + PyArray_API[201]) +#define _PyArray_GetSigintBuf \ + (*(void* (*)(void)) \ + PyArray_API[202]) +#define PyArray_DescrAlignConverter \ + (*(int (*)(PyObject *, PyArray_Descr **)) \ + PyArray_API[203]) +#define PyArray_DescrAlignConverter2 \ + (*(int (*)(PyObject *, PyArray_Descr **)) \ + PyArray_API[204]) +#define PyArray_SearchsideConverter \ + (*(int (*)(PyObject *, void *)) \ + PyArray_API[205]) +#define PyArray_CheckAxis \ + (*(PyObject * (*)(PyArrayObject *, int *, int)) \ + PyArray_API[206]) +#define PyArray_OverflowMultiplyList \ + (*(npy_intp (*)(npy_intp *, int)) \ + PyArray_API[207]) +#define PyArray_CompareString \ + (*(int (*)(char *, char *, size_t)) \ + PyArray_API[208]) +#define PyArray_MultiIterFromObjects \ + (*(PyObject * (*)(PyObject **, int, int, ...)) \ + PyArray_API[209]) +#define PyArray_GetEndianness \ + (*(int (*)(void)) \ + PyArray_API[210]) +#define PyArray_GetNDArrayCFeatureVersion \ + (*(unsigned int (*)(void)) \ + PyArray_API[211]) +#define PyArray_Correlate2 \ + (*(PyObject * (*)(PyObject *, PyObject *, int)) \ + PyArray_API[212]) +#define PyArray_NeighborhoodIterNew \ + (*(PyObject* (*)(PyArrayIterObject *, npy_intp *, int, PyArrayObject*)) \ + PyArray_API[213]) +#define PyTimeIntegerArrType_Type (*(PyTypeObject *)PyArray_API[214]) +#define PyDatetimeArrType_Type (*(PyTypeObject *)PyArray_API[215]) +#define PyTimedeltaArrType_Type (*(PyTypeObject *)PyArray_API[216]) +#define PyHalfArrType_Type (*(PyTypeObject *)PyArray_API[217]) +#define NpyIter_Type (*(PyTypeObject *)PyArray_API[218]) +#define PyArray_SetDatetimeParseFunction \ + (*(void (*)(PyObject *)) \ + PyArray_API[219]) +#define PyArray_DatetimeToDatetimeStruct \ + (*(void (*)(npy_datetime, NPY_DATETIMEUNIT, npy_datetimestruct *)) \ + PyArray_API[220]) +#define PyArray_TimedeltaToTimedeltaStruct \ + (*(void (*)(npy_timedelta, NPY_DATETIMEUNIT, npy_timedeltastruct *)) \ + PyArray_API[221]) +#define PyArray_DatetimeStructToDatetime \ + (*(npy_datetime (*)(NPY_DATETIMEUNIT, npy_datetimestruct *)) \ + PyArray_API[222]) +#define PyArray_TimedeltaStructToTimedelta \ + (*(npy_datetime (*)(NPY_DATETIMEUNIT, npy_timedeltastruct *)) \ + PyArray_API[223]) +#define NpyIter_New \ + (*(NpyIter * (*)(PyArrayObject *, npy_uint32, NPY_ORDER, NPY_CASTING, PyArray_Descr*)) \ + PyArray_API[224]) +#define NpyIter_MultiNew \ + (*(NpyIter * (*)(int, PyArrayObject **, npy_uint32, NPY_ORDER, NPY_CASTING, npy_uint32 *, PyArray_Descr **)) \ + PyArray_API[225]) +#define NpyIter_AdvancedNew \ + (*(NpyIter * (*)(int, PyArrayObject **, npy_uint32, NPY_ORDER, NPY_CASTING, npy_uint32 *, PyArray_Descr **, int, int **, npy_intp *, npy_intp)) \ + PyArray_API[226]) +#define NpyIter_Copy \ + (*(NpyIter * (*)(NpyIter *)) \ + PyArray_API[227]) +#define NpyIter_Deallocate \ + (*(int (*)(NpyIter *)) \ + PyArray_API[228]) +#define NpyIter_HasDelayedBufAlloc \ + (*(npy_bool (*)(NpyIter *)) \ + PyArray_API[229]) +#define NpyIter_HasExternalLoop \ + (*(npy_bool (*)(NpyIter *)) \ + PyArray_API[230]) +#define NpyIter_EnableExternalLoop \ + (*(int (*)(NpyIter *)) \ + PyArray_API[231]) +#define NpyIter_GetInnerStrideArray \ + (*(npy_intp * (*)(NpyIter *)) \ + PyArray_API[232]) +#define NpyIter_GetInnerLoopSizePtr \ + (*(npy_intp * (*)(NpyIter *)) \ + PyArray_API[233]) +#define NpyIter_Reset \ + (*(int (*)(NpyIter *, char **)) \ + PyArray_API[234]) +#define NpyIter_ResetBasePointers \ + (*(int (*)(NpyIter *, char **, char **)) \ + PyArray_API[235]) +#define NpyIter_ResetToIterIndexRange \ + (*(int (*)(NpyIter *, npy_intp, npy_intp, char **)) \ + PyArray_API[236]) +#define NpyIter_GetNDim \ + (*(int (*)(NpyIter *)) \ + PyArray_API[237]) +#define NpyIter_GetNOp \ + (*(int (*)(NpyIter *)) \ + PyArray_API[238]) +#define NpyIter_GetIterNext \ + (*(NpyIter_IterNextFunc * (*)(NpyIter *, char **)) \ + PyArray_API[239]) +#define NpyIter_GetIterSize \ + (*(npy_intp (*)(NpyIter *)) \ + PyArray_API[240]) +#define NpyIter_GetIterIndexRange \ + (*(void (*)(NpyIter *, npy_intp *, npy_intp *)) \ + PyArray_API[241]) +#define NpyIter_GetIterIndex \ + (*(npy_intp (*)(NpyIter *)) \ + PyArray_API[242]) +#define NpyIter_GotoIterIndex \ + (*(int (*)(NpyIter *, npy_intp)) \ + PyArray_API[243]) +#define NpyIter_HasMultiIndex \ + (*(npy_bool (*)(NpyIter *)) \ + PyArray_API[244]) +#define NpyIter_GetShape \ + (*(int (*)(NpyIter *, npy_intp *)) \ + PyArray_API[245]) +#define NpyIter_GetGetMultiIndex \ + (*(NpyIter_GetMultiIndexFunc * (*)(NpyIter *, char **)) \ + PyArray_API[246]) +#define NpyIter_GotoMultiIndex \ + (*(int (*)(NpyIter *, npy_intp *)) \ + PyArray_API[247]) +#define NpyIter_RemoveMultiIndex \ + (*(int (*)(NpyIter *)) \ + PyArray_API[248]) +#define NpyIter_HasIndex \ + (*(npy_bool (*)(NpyIter *)) \ + PyArray_API[249]) +#define NpyIter_IsBuffered \ + (*(npy_bool (*)(NpyIter *)) \ + PyArray_API[250]) +#define NpyIter_IsGrowInner \ + (*(npy_bool (*)(NpyIter *)) \ + PyArray_API[251]) +#define NpyIter_GetBufferSize \ + (*(npy_intp (*)(NpyIter *)) \ + PyArray_API[252]) +#define NpyIter_GetIndexPtr \ + (*(npy_intp * (*)(NpyIter *)) \ + PyArray_API[253]) +#define NpyIter_GotoIndex \ + (*(int (*)(NpyIter *, npy_intp)) \ + PyArray_API[254]) +#define NpyIter_GetDataPtrArray \ + (*(char ** (*)(NpyIter *)) \ + PyArray_API[255]) +#define NpyIter_GetDescrArray \ + (*(PyArray_Descr ** (*)(NpyIter *)) \ + PyArray_API[256]) +#define NpyIter_GetOperandArray \ + (*(PyArrayObject ** (*)(NpyIter *)) \ + PyArray_API[257]) +#define NpyIter_GetIterView \ + (*(PyArrayObject * (*)(NpyIter *, npy_intp)) \ + PyArray_API[258]) +#define NpyIter_GetReadFlags \ + (*(void (*)(NpyIter *, char *)) \ + PyArray_API[259]) +#define NpyIter_GetWriteFlags \ + (*(void (*)(NpyIter *, char *)) \ + PyArray_API[260]) +#define NpyIter_DebugPrint \ + (*(void (*)(NpyIter *)) \ + PyArray_API[261]) +#define NpyIter_IterationNeedsAPI \ + (*(npy_bool (*)(NpyIter *)) \ + PyArray_API[262]) +#define NpyIter_GetInnerFixedStrideArray \ + (*(void (*)(NpyIter *, npy_intp *)) \ + PyArray_API[263]) +#define NpyIter_RemoveAxis \ + (*(int (*)(NpyIter *, int)) \ + PyArray_API[264]) +#define NpyIter_GetAxisStrideArray \ + (*(npy_intp * (*)(NpyIter *, int)) \ + PyArray_API[265]) +#define NpyIter_RequiresBuffering \ + (*(npy_bool (*)(NpyIter *)) \ + PyArray_API[266]) +#define NpyIter_GetInitialDataPtrArray \ + (*(char ** (*)(NpyIter *)) \ + PyArray_API[267]) +#define NpyIter_CreateCompatibleStrides \ + (*(int (*)(NpyIter *, npy_intp, npy_intp *)) \ + PyArray_API[268]) +#define PyArray_CastingConverter \ + (*(int (*)(PyObject *, NPY_CASTING *)) \ + PyArray_API[269]) +#define PyArray_CountNonzero \ + (*(npy_intp (*)(PyArrayObject *)) \ + PyArray_API[270]) +#define PyArray_PromoteTypes \ + (*(PyArray_Descr * (*)(PyArray_Descr *, PyArray_Descr *)) \ + PyArray_API[271]) +#define PyArray_MinScalarType \ + (*(PyArray_Descr * (*)(PyArrayObject *)) \ + PyArray_API[272]) +#define PyArray_ResultType \ + (*(PyArray_Descr * (*)(npy_intp, PyArrayObject **, npy_intp, PyArray_Descr **)) \ + PyArray_API[273]) +#define PyArray_CanCastArrayTo \ + (*(npy_bool (*)(PyArrayObject *, PyArray_Descr *, NPY_CASTING)) \ + PyArray_API[274]) +#define PyArray_CanCastTypeTo \ + (*(npy_bool (*)(PyArray_Descr *, PyArray_Descr *, NPY_CASTING)) \ + PyArray_API[275]) +#define PyArray_EinsteinSum \ + (*(PyArrayObject * (*)(char *, npy_intp, PyArrayObject **, PyArray_Descr *, NPY_ORDER, NPY_CASTING, PyArrayObject *)) \ + PyArray_API[276]) +#define PyArray_NewLikeArray \ + (*(PyObject * (*)(PyArrayObject *, NPY_ORDER, PyArray_Descr *, int)) \ + PyArray_API[277]) +#define PyArray_GetArrayParamsFromObject \ + (*(int (*)(PyObject *, PyArray_Descr *, npy_bool, PyArray_Descr **, int *, npy_intp *, PyArrayObject **, PyObject *)) \ + PyArray_API[278]) +#define PyArray_ConvertClipmodeSequence \ + (*(int (*)(PyObject *, NPY_CLIPMODE *, int)) \ + PyArray_API[279]) +#define PyArray_MatrixProduct2 \ + (*(PyObject * (*)(PyObject *, PyObject *, PyArrayObject*)) \ + PyArray_API[280]) +#define NpyIter_IsFirstVisit \ + (*(npy_bool (*)(NpyIter *, int)) \ + PyArray_API[281]) +#define PyArray_SetBaseObject \ + (*(int (*)(PyArrayObject *, PyObject *)) \ + PyArray_API[282]) +#define PyArray_CreateSortedStridePerm \ + (*(void (*)(int, npy_intp *, npy_stride_sort_item *)) \ + PyArray_API[283]) +#define PyArray_RemoveAxesInPlace \ + (*(void (*)(PyArrayObject *, npy_bool *)) \ + PyArray_API[284]) +#define PyArray_DebugPrint \ + (*(void (*)(PyArrayObject *)) \ + PyArray_API[285]) +#define PyArray_FailUnlessWriteable \ + (*(int (*)(PyArrayObject *, const char *)) \ + PyArray_API[286]) +#define PyArray_SetUpdateIfCopyBase \ + (*(int (*)(PyArrayObject *, PyArrayObject *)) \ + PyArray_API[287]) +#define PyDataMem_NEW \ + (*(void * (*)(size_t)) \ + PyArray_API[288]) +#define PyDataMem_FREE \ + (*(void (*)(void *)) \ + PyArray_API[289]) +#define PyDataMem_RENEW \ + (*(void * (*)(void *, size_t)) \ + PyArray_API[290]) +#define PyDataMem_SetEventHook \ + (*(PyDataMem_EventHookFunc * (*)(PyDataMem_EventHookFunc *, void *, void **)) \ + PyArray_API[291]) +#define NPY_DEFAULT_ASSIGN_CASTING (*(NPY_CASTING *)PyArray_API[292]) + +#if !defined(NO_IMPORT_ARRAY) && !defined(NO_IMPORT) +static int +_import_array(void) +{ + int st; + PyObject *numpy = PyImport_ImportModule("numpy.core.multiarray"); + PyObject *c_api = NULL; + + if (numpy == NULL) { + PyErr_SetString(PyExc_ImportError, "numpy.core.multiarray failed to import"); + return -1; + } + c_api = PyObject_GetAttrString(numpy, "_ARRAY_API"); + Py_DECREF(numpy); + if (c_api == NULL) { + PyErr_SetString(PyExc_AttributeError, "_ARRAY_API not found"); + return -1; + } + +#if PY_VERSION_HEX >= 0x03000000 + if (!PyCapsule_CheckExact(c_api)) { + PyErr_SetString(PyExc_RuntimeError, "_ARRAY_API is not PyCapsule object"); + Py_DECREF(c_api); + return -1; + } + PyArray_API = (void **)PyCapsule_GetPointer(c_api, NULL); +#else + if (!PyCObject_Check(c_api)) { + PyErr_SetString(PyExc_RuntimeError, "_ARRAY_API is not PyCObject object"); + Py_DECREF(c_api); + return -1; + } + PyArray_API = (void **)PyCObject_AsVoidPtr(c_api); +#endif + Py_DECREF(c_api); + if (PyArray_API == NULL) { + PyErr_SetString(PyExc_RuntimeError, "_ARRAY_API is NULL pointer"); + return -1; + } + + /* Perform runtime check of C API version */ + if (NPY_VERSION != PyArray_GetNDArrayCVersion()) { + PyErr_Format(PyExc_RuntimeError, "module compiled against "\ + "ABI version %x but this version of numpy is %x", \ + (int) NPY_VERSION, (int) PyArray_GetNDArrayCVersion()); + return -1; + } + if (NPY_FEATURE_VERSION > PyArray_GetNDArrayCFeatureVersion()) { + PyErr_Format(PyExc_RuntimeError, "module compiled against "\ + "API version %x but this version of numpy is %x", \ + (int) NPY_FEATURE_VERSION, (int) PyArray_GetNDArrayCFeatureVersion()); + return -1; + } + + /* + * Perform runtime check of endianness and check it matches the one set by + * the headers (npy_endian.h) as a safeguard + */ + st = PyArray_GetEndianness(); + if (st == NPY_CPU_UNKNOWN_ENDIAN) { + PyErr_Format(PyExc_RuntimeError, "FATAL: module compiled as unknown endian"); + return -1; + } +#if NPY_BYTE_ORDER == NPY_BIG_ENDIAN + if (st != NPY_CPU_BIG) { + PyErr_Format(PyExc_RuntimeError, "FATAL: module compiled as "\ + "big endian, but detected different endianness at runtime"); + return -1; + } +#elif NPY_BYTE_ORDER == NPY_LITTLE_ENDIAN + if (st != NPY_CPU_LITTLE) { + PyErr_Format(PyExc_RuntimeError, "FATAL: module compiled as "\ + "little endian, but detected different endianness at runtime"); + return -1; + } +#endif + + return 0; +} + +#if PY_VERSION_HEX >= 0x03000000 +#define NUMPY_IMPORT_ARRAY_RETVAL NULL +#else +#define NUMPY_IMPORT_ARRAY_RETVAL +#endif + +#define import_array() {if (_import_array() < 0) {PyErr_Print(); PyErr_SetString(PyExc_ImportError, "numpy.core.multiarray failed to import"); return NUMPY_IMPORT_ARRAY_RETVAL; } } + +#define import_array1(ret) {if (_import_array() < 0) {PyErr_Print(); PyErr_SetString(PyExc_ImportError, "numpy.core.multiarray failed to import"); return ret; } } + +#define import_array2(msg, ret) {if (_import_array() < 0) {PyErr_Print(); PyErr_SetString(PyExc_ImportError, msg); return ret; } } + +#endif + +#endif diff --git a/data_tooling/pii_processing/include/numpy/__ufunc_api.h b/data_tooling/pii_processing/include/numpy/__ufunc_api.h new file mode 100644 index 0000000..fd81d07 --- /dev/null +++ b/data_tooling/pii_processing/include/numpy/__ufunc_api.h @@ -0,0 +1,323 @@ + +#ifdef _UMATHMODULE + +#ifdef NPY_ENABLE_SEPARATE_COMPILATION +extern NPY_NO_EXPORT PyTypeObject PyUFunc_Type; +#else +NPY_NO_EXPORT PyTypeObject PyUFunc_Type; +#endif + +#ifdef NPY_ENABLE_SEPARATE_COMPILATION + extern NPY_NO_EXPORT PyTypeObject PyUFunc_Type; +#else + NPY_NO_EXPORT PyTypeObject PyUFunc_Type; +#endif + +NPY_NO_EXPORT PyObject * PyUFunc_FromFuncAndData \ + (PyUFuncGenericFunction *, void **, char *, int, int, int, int, char *, char *, int); +NPY_NO_EXPORT int PyUFunc_RegisterLoopForType \ + (PyUFuncObject *, int, PyUFuncGenericFunction, int *, void *); +NPY_NO_EXPORT int PyUFunc_GenericFunction \ + (PyUFuncObject *, PyObject *, PyObject *, PyArrayObject **); +NPY_NO_EXPORT void PyUFunc_f_f_As_d_d \ + (char **, npy_intp *, npy_intp *, void *); +NPY_NO_EXPORT void PyUFunc_d_d \ + (char **, npy_intp *, npy_intp *, void *); +NPY_NO_EXPORT void PyUFunc_f_f \ + (char **, npy_intp *, npy_intp *, void *); +NPY_NO_EXPORT void PyUFunc_g_g \ + (char **, npy_intp *, npy_intp *, void *); +NPY_NO_EXPORT void PyUFunc_F_F_As_D_D \ + (char **, npy_intp *, npy_intp *, void *); +NPY_NO_EXPORT void PyUFunc_F_F \ + (char **, npy_intp *, npy_intp *, void *); +NPY_NO_EXPORT void PyUFunc_D_D \ + (char **, npy_intp *, npy_intp *, void *); +NPY_NO_EXPORT void PyUFunc_G_G \ + (char **, npy_intp *, npy_intp *, void *); +NPY_NO_EXPORT void PyUFunc_O_O \ + (char **, npy_intp *, npy_intp *, void *); +NPY_NO_EXPORT void PyUFunc_ff_f_As_dd_d \ + (char **, npy_intp *, npy_intp *, void *); +NPY_NO_EXPORT void PyUFunc_ff_f \ + (char **, npy_intp *, npy_intp *, void *); +NPY_NO_EXPORT void PyUFunc_dd_d \ + (char **, npy_intp *, npy_intp *, void *); +NPY_NO_EXPORT void PyUFunc_gg_g \ + (char **, npy_intp *, npy_intp *, void *); +NPY_NO_EXPORT void PyUFunc_FF_F_As_DD_D \ + (char **, npy_intp *, npy_intp *, void *); +NPY_NO_EXPORT void PyUFunc_DD_D \ + (char **, npy_intp *, npy_intp *, void *); +NPY_NO_EXPORT void PyUFunc_FF_F \ + (char **, npy_intp *, npy_intp *, void *); +NPY_NO_EXPORT void PyUFunc_GG_G \ + (char **, npy_intp *, npy_intp *, void *); +NPY_NO_EXPORT void PyUFunc_OO_O \ + (char **, npy_intp *, npy_intp *, void *); +NPY_NO_EXPORT void PyUFunc_O_O_method \ + (char **, npy_intp *, npy_intp *, void *); +NPY_NO_EXPORT void PyUFunc_OO_O_method \ + (char **, npy_intp *, npy_intp *, void *); +NPY_NO_EXPORT void PyUFunc_On_Om \ + (char **, npy_intp *, npy_intp *, void *); +NPY_NO_EXPORT int PyUFunc_GetPyValues \ + (char *, int *, int *, PyObject **); +NPY_NO_EXPORT int PyUFunc_checkfperr \ + (int, PyObject *, int *); +NPY_NO_EXPORT void PyUFunc_clearfperr \ + (void); +NPY_NO_EXPORT int PyUFunc_getfperr \ + (void); +NPY_NO_EXPORT int PyUFunc_handlefperr \ + (int, PyObject *, int, int *); +NPY_NO_EXPORT int PyUFunc_ReplaceLoopBySignature \ + (PyUFuncObject *, PyUFuncGenericFunction, int *, PyUFuncGenericFunction *); +NPY_NO_EXPORT PyObject * PyUFunc_FromFuncAndDataAndSignature \ + (PyUFuncGenericFunction *, void **, char *, int, int, int, int, char *, char *, int, const char *); +NPY_NO_EXPORT int PyUFunc_SetUsesArraysAsData \ + (void **, size_t); +NPY_NO_EXPORT void PyUFunc_e_e \ + (char **, npy_intp *, npy_intp *, void *); +NPY_NO_EXPORT void PyUFunc_e_e_As_f_f \ + (char **, npy_intp *, npy_intp *, void *); +NPY_NO_EXPORT void PyUFunc_e_e_As_d_d \ + (char **, npy_intp *, npy_intp *, void *); +NPY_NO_EXPORT void PyUFunc_ee_e \ + (char **, npy_intp *, npy_intp *, void *); +NPY_NO_EXPORT void PyUFunc_ee_e_As_ff_f \ + (char **, npy_intp *, npy_intp *, void *); +NPY_NO_EXPORT void PyUFunc_ee_e_As_dd_d \ + (char **, npy_intp *, npy_intp *, void *); +NPY_NO_EXPORT int PyUFunc_DefaultTypeResolver \ + (PyUFuncObject *, NPY_CASTING, PyArrayObject **, PyObject *, PyArray_Descr **); +NPY_NO_EXPORT int PyUFunc_ValidateCasting \ + (PyUFuncObject *, NPY_CASTING, PyArrayObject **, PyArray_Descr **); + +#else + +#if defined(PY_UFUNC_UNIQUE_SYMBOL) +#define PyUFunc_API PY_UFUNC_UNIQUE_SYMBOL +#endif + +#if defined(NO_IMPORT) || defined(NO_IMPORT_UFUNC) +extern void **PyUFunc_API; +#else +#if defined(PY_UFUNC_UNIQUE_SYMBOL) +void **PyUFunc_API; +#else +static void **PyUFunc_API=NULL; +#endif +#endif + +#define PyUFunc_Type (*(PyTypeObject *)PyUFunc_API[0]) +#define PyUFunc_FromFuncAndData \ + (*(PyObject * (*)(PyUFuncGenericFunction *, void **, char *, int, int, int, int, char *, char *, int)) \ + PyUFunc_API[1]) +#define PyUFunc_RegisterLoopForType \ + (*(int (*)(PyUFuncObject *, int, PyUFuncGenericFunction, int *, void *)) \ + PyUFunc_API[2]) +#define PyUFunc_GenericFunction \ + (*(int (*)(PyUFuncObject *, PyObject *, PyObject *, PyArrayObject **)) \ + PyUFunc_API[3]) +#define PyUFunc_f_f_As_d_d \ + (*(void (*)(char **, npy_intp *, npy_intp *, void *)) \ + PyUFunc_API[4]) +#define PyUFunc_d_d \ + (*(void (*)(char **, npy_intp *, npy_intp *, void *)) \ + PyUFunc_API[5]) +#define PyUFunc_f_f \ + (*(void (*)(char **, npy_intp *, npy_intp *, void *)) \ + PyUFunc_API[6]) +#define PyUFunc_g_g \ + (*(void (*)(char **, npy_intp *, npy_intp *, void *)) \ + PyUFunc_API[7]) +#define PyUFunc_F_F_As_D_D \ + (*(void (*)(char **, npy_intp *, npy_intp *, void *)) \ + PyUFunc_API[8]) +#define PyUFunc_F_F \ + (*(void (*)(char **, npy_intp *, npy_intp *, void *)) \ + PyUFunc_API[9]) +#define PyUFunc_D_D \ + (*(void (*)(char **, npy_intp *, npy_intp *, void *)) \ + PyUFunc_API[10]) +#define PyUFunc_G_G \ + (*(void (*)(char **, npy_intp *, npy_intp *, void *)) \ + PyUFunc_API[11]) +#define PyUFunc_O_O \ + (*(void (*)(char **, npy_intp *, npy_intp *, void *)) \ + PyUFunc_API[12]) +#define PyUFunc_ff_f_As_dd_d \ + (*(void (*)(char **, npy_intp *, npy_intp *, void *)) \ + PyUFunc_API[13]) +#define PyUFunc_ff_f \ + (*(void (*)(char **, npy_intp *, npy_intp *, void *)) \ + PyUFunc_API[14]) +#define PyUFunc_dd_d \ + (*(void (*)(char **, npy_intp *, npy_intp *, void *)) \ + PyUFunc_API[15]) +#define PyUFunc_gg_g \ + (*(void (*)(char **, npy_intp *, npy_intp *, void *)) \ + PyUFunc_API[16]) +#define PyUFunc_FF_F_As_DD_D \ + (*(void (*)(char **, npy_intp *, npy_intp *, void *)) \ + PyUFunc_API[17]) +#define PyUFunc_DD_D \ + (*(void (*)(char **, npy_intp *, npy_intp *, void *)) \ + PyUFunc_API[18]) +#define PyUFunc_FF_F \ + (*(void (*)(char **, npy_intp *, npy_intp *, void *)) \ + PyUFunc_API[19]) +#define PyUFunc_GG_G \ + (*(void (*)(char **, npy_intp *, npy_intp *, void *)) \ + PyUFunc_API[20]) +#define PyUFunc_OO_O \ + (*(void (*)(char **, npy_intp *, npy_intp *, void *)) \ + PyUFunc_API[21]) +#define PyUFunc_O_O_method \ + (*(void (*)(char **, npy_intp *, npy_intp *, void *)) \ + PyUFunc_API[22]) +#define PyUFunc_OO_O_method \ + (*(void (*)(char **, npy_intp *, npy_intp *, void *)) \ + PyUFunc_API[23]) +#define PyUFunc_On_Om \ + (*(void (*)(char **, npy_intp *, npy_intp *, void *)) \ + PyUFunc_API[24]) +#define PyUFunc_GetPyValues \ + (*(int (*)(char *, int *, int *, PyObject **)) \ + PyUFunc_API[25]) +#define PyUFunc_checkfperr \ + (*(int (*)(int, PyObject *, int *)) \ + PyUFunc_API[26]) +#define PyUFunc_clearfperr \ + (*(void (*)(void)) \ + PyUFunc_API[27]) +#define PyUFunc_getfperr \ + (*(int (*)(void)) \ + PyUFunc_API[28]) +#define PyUFunc_handlefperr \ + (*(int (*)(int, PyObject *, int, int *)) \ + PyUFunc_API[29]) +#define PyUFunc_ReplaceLoopBySignature \ + (*(int (*)(PyUFuncObject *, PyUFuncGenericFunction, int *, PyUFuncGenericFunction *)) \ + PyUFunc_API[30]) +#define PyUFunc_FromFuncAndDataAndSignature \ + (*(PyObject * (*)(PyUFuncGenericFunction *, void **, char *, int, int, int, int, char *, char *, int, const char *)) \ + PyUFunc_API[31]) +#define PyUFunc_SetUsesArraysAsData \ + (*(int (*)(void **, size_t)) \ + PyUFunc_API[32]) +#define PyUFunc_e_e \ + (*(void (*)(char **, npy_intp *, npy_intp *, void *)) \ + PyUFunc_API[33]) +#define PyUFunc_e_e_As_f_f \ + (*(void (*)(char **, npy_intp *, npy_intp *, void *)) \ + PyUFunc_API[34]) +#define PyUFunc_e_e_As_d_d \ + (*(void (*)(char **, npy_intp *, npy_intp *, void *)) \ + PyUFunc_API[35]) +#define PyUFunc_ee_e \ + (*(void (*)(char **, npy_intp *, npy_intp *, void *)) \ + PyUFunc_API[36]) +#define PyUFunc_ee_e_As_ff_f \ + (*(void (*)(char **, npy_intp *, npy_intp *, void *)) \ + PyUFunc_API[37]) +#define PyUFunc_ee_e_As_dd_d \ + (*(void (*)(char **, npy_intp *, npy_intp *, void *)) \ + PyUFunc_API[38]) +#define PyUFunc_DefaultTypeResolver \ + (*(int (*)(PyUFuncObject *, NPY_CASTING, PyArrayObject **, PyObject *, PyArray_Descr **)) \ + PyUFunc_API[39]) +#define PyUFunc_ValidateCasting \ + (*(int (*)(PyUFuncObject *, NPY_CASTING, PyArrayObject **, PyArray_Descr **)) \ + PyUFunc_API[40]) + +static int +_import_umath(void) +{ + PyObject *numpy = PyImport_ImportModule("numpy.core.umath"); + PyObject *c_api = NULL; + + if (numpy == NULL) { + PyErr_SetString(PyExc_ImportError, "numpy.core.umath failed to import"); + return -1; + } + c_api = PyObject_GetAttrString(numpy, "_UFUNC_API"); + Py_DECREF(numpy); + if (c_api == NULL) { + PyErr_SetString(PyExc_AttributeError, "_UFUNC_API not found"); + return -1; + } + +#if PY_VERSION_HEX >= 0x03000000 + if (!PyCapsule_CheckExact(c_api)) { + PyErr_SetString(PyExc_RuntimeError, "_UFUNC_API is not PyCapsule object"); + Py_DECREF(c_api); + return -1; + } + PyUFunc_API = (void **)PyCapsule_GetPointer(c_api, NULL); +#else + if (!PyCObject_Check(c_api)) { + PyErr_SetString(PyExc_RuntimeError, "_UFUNC_API is not PyCObject object"); + Py_DECREF(c_api); + return -1; + } + PyUFunc_API = (void **)PyCObject_AsVoidPtr(c_api); +#endif + Py_DECREF(c_api); + if (PyUFunc_API == NULL) { + PyErr_SetString(PyExc_RuntimeError, "_UFUNC_API is NULL pointer"); + return -1; + } + return 0; +} + +#if PY_VERSION_HEX >= 0x03000000 +#define NUMPY_IMPORT_UMATH_RETVAL NULL +#else +#define NUMPY_IMPORT_UMATH_RETVAL +#endif + +#define import_umath() \ + do {\ + UFUNC_NOFPE\ + if (_import_umath() < 0) {\ + PyErr_Print();\ + PyErr_SetString(PyExc_ImportError,\ + "numpy.core.umath failed to import");\ + return NUMPY_IMPORT_UMATH_RETVAL;\ + }\ + } while(0) + +#define import_umath1(ret) \ + do {\ + UFUNC_NOFPE\ + if (_import_umath() < 0) {\ + PyErr_Print();\ + PyErr_SetString(PyExc_ImportError,\ + "numpy.core.umath failed to import");\ + return ret;\ + }\ + } while(0) + +#define import_umath2(ret, msg) \ + do {\ + UFUNC_NOFPE\ + if (_import_umath() < 0) {\ + PyErr_Print();\ + PyErr_SetString(PyExc_ImportError, msg);\ + return ret;\ + }\ + } while(0) + +#define import_ufunc() \ + do {\ + UFUNC_NOFPE\ + if (_import_umath() < 0) {\ + PyErr_Print();\ + PyErr_SetString(PyExc_ImportError,\ + "numpy.core.umath failed to import");\ + }\ + } while(0) + +#endif diff --git a/data_tooling/pii_processing/include/numpy/_neighborhood_iterator_imp.h b/data_tooling/pii_processing/include/numpy/_neighborhood_iterator_imp.h new file mode 100644 index 0000000..e8860cb --- /dev/null +++ b/data_tooling/pii_processing/include/numpy/_neighborhood_iterator_imp.h @@ -0,0 +1,90 @@ +#ifndef _NPY_INCLUDE_NEIGHBORHOOD_IMP +#error You should not include this header directly +#endif +/* + * Private API (here for inline) + */ +static NPY_INLINE int +_PyArrayNeighborhoodIter_IncrCoord(PyArrayNeighborhoodIterObject* iter); + +/* + * Update to next item of the iterator + * + * Note: this simply increment the coordinates vector, last dimension + * incremented first , i.e, for dimension 3 + * ... + * -1, -1, -1 + * -1, -1, 0 + * -1, -1, 1 + * .... + * -1, 0, -1 + * -1, 0, 0 + * .... + * 0, -1, -1 + * 0, -1, 0 + * .... + */ +#define _UPDATE_COORD_ITER(c) \ + wb = iter->coordinates[c] < iter->bounds[c][1]; \ + if (wb) { \ + iter->coordinates[c] += 1; \ + return 0; \ + } \ + else { \ + iter->coordinates[c] = iter->bounds[c][0]; \ + } + +static NPY_INLINE int +_PyArrayNeighborhoodIter_IncrCoord(PyArrayNeighborhoodIterObject* iter) +{ + npy_intp i, wb; + + for (i = iter->nd - 1; i >= 0; --i) { + _UPDATE_COORD_ITER(i) + } + + return 0; +} + +/* + * Version optimized for 2d arrays, manual loop unrolling + */ +static NPY_INLINE int +_PyArrayNeighborhoodIter_IncrCoord2D(PyArrayNeighborhoodIterObject* iter) +{ + npy_intp wb; + + _UPDATE_COORD_ITER(1) + _UPDATE_COORD_ITER(0) + + return 0; +} +#undef _UPDATE_COORD_ITER + +/* + * Advance to the next neighbour + */ +static NPY_INLINE int +PyArrayNeighborhoodIter_Next(PyArrayNeighborhoodIterObject* iter) +{ + _PyArrayNeighborhoodIter_IncrCoord (iter); + iter->dataptr = iter->translate((PyArrayIterObject*)iter, iter->coordinates); + + return 0; +} + +/* + * Reset functions + */ +static NPY_INLINE int +PyArrayNeighborhoodIter_Reset(PyArrayNeighborhoodIterObject* iter) +{ + npy_intp i; + + for (i = 0; i < iter->nd; ++i) { + iter->coordinates[i] = iter->bounds[i][0]; + } + iter->dataptr = iter->translate((PyArrayIterObject*)iter, iter->coordinates); + + return 0; +} diff --git a/data_tooling/pii_processing/include/numpy/_numpyconfig.h b/data_tooling/pii_processing/include/numpy/_numpyconfig.h new file mode 100644 index 0000000..d55ffc3 --- /dev/null +++ b/data_tooling/pii_processing/include/numpy/_numpyconfig.h @@ -0,0 +1,29 @@ +#define NPY_SIZEOF_SHORT SIZEOF_SHORT +#define NPY_SIZEOF_INT SIZEOF_INT +#define NPY_SIZEOF_LONG SIZEOF_LONG +#define NPY_SIZEOF_FLOAT 4 +#define NPY_SIZEOF_COMPLEX_FLOAT 8 +#define NPY_SIZEOF_DOUBLE 8 +#define NPY_SIZEOF_COMPLEX_DOUBLE 16 +#define NPY_SIZEOF_LONGDOUBLE 16 +#define NPY_SIZEOF_COMPLEX_LONGDOUBLE 32 +#define NPY_SIZEOF_PY_INTPTR_T 8 +#define NPY_SIZEOF_PY_LONG_LONG 8 +#define NPY_SIZEOF_LONGLONG 8 +#define NPY_NO_SMP 0 +#define NPY_HAVE_DECL_ISNAN +#define NPY_HAVE_DECL_ISINF +#define NPY_HAVE_DECL_ISFINITE +#define NPY_HAVE_DECL_SIGNBIT +#define NPY_USE_C99_COMPLEX 1 +#define NPY_HAVE_COMPLEX_DOUBLE 1 +#define NPY_HAVE_COMPLEX_FLOAT 1 +#define NPY_HAVE_COMPLEX_LONG_DOUBLE 1 +#define NPY_USE_C99_FORMATS 1 +#define NPY_VISIBILITY_HIDDEN __attribute__((visibility("hidden"))) +#define NPY_ABI_VERSION 0x01000009 +#define NPY_API_VERSION 0x00000007 + +#ifndef __STDC_FORMAT_MACROS +#define __STDC_FORMAT_MACROS 1 +#endif diff --git a/data_tooling/pii_processing/include/numpy/arrayobject.h b/data_tooling/pii_processing/include/numpy/arrayobject.h new file mode 100644 index 0000000..a84766f --- /dev/null +++ b/data_tooling/pii_processing/include/numpy/arrayobject.h @@ -0,0 +1,22 @@ + +/* This expects the following variables to be defined (besides + the usual ones from pyconfig.h + + SIZEOF_LONG_DOUBLE -- sizeof(long double) or sizeof(double) if no + long double is present on platform. + CHAR_BIT -- number of bits in a char (usually 8) + (should be in limits.h) + +*/ + +#ifndef Py_ARRAYOBJECT_H +#define Py_ARRAYOBJECT_H + +#include "ndarrayobject.h" +#include "npy_interrupt.h" + +#ifdef NPY_NO_PREFIX +#include "noprefix.h" +#endif + +#endif diff --git a/data_tooling/pii_processing/include/numpy/arrayscalars.h b/data_tooling/pii_processing/include/numpy/arrayscalars.h new file mode 100644 index 0000000..64450e7 --- /dev/null +++ b/data_tooling/pii_processing/include/numpy/arrayscalars.h @@ -0,0 +1,175 @@ +#ifndef _NPY_ARRAYSCALARS_H_ +#define _NPY_ARRAYSCALARS_H_ + +#ifndef _MULTIARRAYMODULE +typedef struct { + PyObject_HEAD + npy_bool obval; +} PyBoolScalarObject; +#endif + + +typedef struct { + PyObject_HEAD + signed char obval; +} PyByteScalarObject; + + +typedef struct { + PyObject_HEAD + short obval; +} PyShortScalarObject; + + +typedef struct { + PyObject_HEAD + int obval; +} PyIntScalarObject; + + +typedef struct { + PyObject_HEAD + long obval; +} PyLongScalarObject; + + +typedef struct { + PyObject_HEAD + npy_longlong obval; +} PyLongLongScalarObject; + + +typedef struct { + PyObject_HEAD + unsigned char obval; +} PyUByteScalarObject; + + +typedef struct { + PyObject_HEAD + unsigned short obval; +} PyUShortScalarObject; + + +typedef struct { + PyObject_HEAD + unsigned int obval; +} PyUIntScalarObject; + + +typedef struct { + PyObject_HEAD + unsigned long obval; +} PyULongScalarObject; + + +typedef struct { + PyObject_HEAD + npy_ulonglong obval; +} PyULongLongScalarObject; + + +typedef struct { + PyObject_HEAD + npy_half obval; +} PyHalfScalarObject; + + +typedef struct { + PyObject_HEAD + float obval; +} PyFloatScalarObject; + + +typedef struct { + PyObject_HEAD + double obval; +} PyDoubleScalarObject; + + +typedef struct { + PyObject_HEAD + npy_longdouble obval; +} PyLongDoubleScalarObject; + + +typedef struct { + PyObject_HEAD + npy_cfloat obval; +} PyCFloatScalarObject; + + +typedef struct { + PyObject_HEAD + npy_cdouble obval; +} PyCDoubleScalarObject; + + +typedef struct { + PyObject_HEAD + npy_clongdouble obval; +} PyCLongDoubleScalarObject; + + +typedef struct { + PyObject_HEAD + PyObject * obval; +} PyObjectScalarObject; + +typedef struct { + PyObject_HEAD + npy_datetime obval; + PyArray_DatetimeMetaData obmeta; +} PyDatetimeScalarObject; + +typedef struct { + PyObject_HEAD + npy_timedelta obval; + PyArray_DatetimeMetaData obmeta; +} PyTimedeltaScalarObject; + + +typedef struct { + PyObject_HEAD + char obval; +} PyScalarObject; + +#define PyStringScalarObject PyStringObject +#define PyUnicodeScalarObject PyUnicodeObject + +typedef struct { + PyObject_VAR_HEAD + char *obval; + PyArray_Descr *descr; + int flags; + PyObject *base; +} PyVoidScalarObject; + +/* Macros + PyScalarObject + PyArrType_Type + are defined in ndarrayobject.h +*/ + +#define PyArrayScalar_False ((PyObject *)(&(_PyArrayScalar_BoolValues[0]))) +#define PyArrayScalar_True ((PyObject *)(&(_PyArrayScalar_BoolValues[1]))) +#define PyArrayScalar_FromLong(i) \ + ((PyObject *)(&(_PyArrayScalar_BoolValues[((i)!=0)]))) +#define PyArrayScalar_RETURN_BOOL_FROM_LONG(i) \ + return Py_INCREF(PyArrayScalar_FromLong(i)), \ + PyArrayScalar_FromLong(i) +#define PyArrayScalar_RETURN_FALSE \ + return Py_INCREF(PyArrayScalar_False), \ + PyArrayScalar_False +#define PyArrayScalar_RETURN_TRUE \ + return Py_INCREF(PyArrayScalar_True), \ + PyArrayScalar_True + +#define PyArrayScalar_New(cls) \ + Py##cls##ArrType_Type.tp_alloc(&Py##cls##ArrType_Type, 0) +#define PyArrayScalar_VAL(obj, cls) \ + ((Py##cls##ScalarObject *)obj)->obval +#define PyArrayScalar_ASSIGN(obj, cls, val) \ + PyArrayScalar_VAL(obj, cls) = val + +#endif diff --git a/data_tooling/pii_processing/include/numpy/halffloat.h b/data_tooling/pii_processing/include/numpy/halffloat.h new file mode 100644 index 0000000..944f0ea --- /dev/null +++ b/data_tooling/pii_processing/include/numpy/halffloat.h @@ -0,0 +1,69 @@ +#ifndef __NPY_HALFFLOAT_H__ +#define __NPY_HALFFLOAT_H__ + +#include +#include + +#ifdef __cplusplus +extern "C" { +#endif + +/* + * Half-precision routines + */ + +/* Conversions */ +float npy_half_to_float(npy_half h); +double npy_half_to_double(npy_half h); +npy_half npy_float_to_half(float f); +npy_half npy_double_to_half(double d); +/* Comparisons */ +int npy_half_eq(npy_half h1, npy_half h2); +int npy_half_ne(npy_half h1, npy_half h2); +int npy_half_le(npy_half h1, npy_half h2); +int npy_half_lt(npy_half h1, npy_half h2); +int npy_half_ge(npy_half h1, npy_half h2); +int npy_half_gt(npy_half h1, npy_half h2); +/* faster *_nonan variants for when you know h1 and h2 are not NaN */ +int npy_half_eq_nonan(npy_half h1, npy_half h2); +int npy_half_lt_nonan(npy_half h1, npy_half h2); +int npy_half_le_nonan(npy_half h1, npy_half h2); +/* Miscellaneous functions */ +int npy_half_iszero(npy_half h); +int npy_half_isnan(npy_half h); +int npy_half_isinf(npy_half h); +int npy_half_isfinite(npy_half h); +int npy_half_signbit(npy_half h); +npy_half npy_half_copysign(npy_half x, npy_half y); +npy_half npy_half_spacing(npy_half h); +npy_half npy_half_nextafter(npy_half x, npy_half y); + +/* + * Half-precision constants + */ + +#define NPY_HALF_ZERO (0x0000u) +#define NPY_HALF_PZERO (0x0000u) +#define NPY_HALF_NZERO (0x8000u) +#define NPY_HALF_ONE (0x3c00u) +#define NPY_HALF_NEGONE (0xbc00u) +#define NPY_HALF_PINF (0x7c00u) +#define NPY_HALF_NINF (0xfc00u) +#define NPY_HALF_NAN (0x7e00u) + +#define NPY_MAX_HALF (0x7bffu) + +/* + * Bit-level conversions + */ + +npy_uint16 npy_floatbits_to_halfbits(npy_uint32 f); +npy_uint16 npy_doublebits_to_halfbits(npy_uint64 d); +npy_uint32 npy_halfbits_to_floatbits(npy_uint16 h); +npy_uint64 npy_halfbits_to_doublebits(npy_uint16 h); + +#ifdef __cplusplus +} +#endif + +#endif diff --git a/data_tooling/pii_processing/include/numpy/multiarray_api.txt b/data_tooling/pii_processing/include/numpy/multiarray_api.txt new file mode 100644 index 0000000..7e588f0 --- /dev/null +++ b/data_tooling/pii_processing/include/numpy/multiarray_api.txt @@ -0,0 +1,2375 @@ + +=========== +Numpy C-API +=========== +:: + + unsigned int + PyArray_GetNDArrayCVersion(void ) + + +Included at the very first so not auto-grabbed and thus not labeled. + +:: + + int + PyArray_SetNumericOps(PyObject *dict) + +Set internal structure with number functions that all arrays will use + +:: + + PyObject * + PyArray_GetNumericOps(void ) + +Get dictionary showing number functions that all arrays will use + +:: + + int + PyArray_INCREF(PyArrayObject *mp) + +For object arrays, increment all internal references. + +:: + + int + PyArray_XDECREF(PyArrayObject *mp) + +Decrement all internal references for object arrays. +(or arrays with object fields) + +:: + + void + PyArray_SetStringFunction(PyObject *op, int repr) + +Set the array print function to be a Python function. + +:: + + PyArray_Descr * + PyArray_DescrFromType(int type) + +Get the PyArray_Descr structure for a type. + +:: + + PyObject * + PyArray_TypeObjectFromType(int type) + +Get a typeobject from a type-number -- can return NULL. + +New reference + +:: + + char * + PyArray_Zero(PyArrayObject *arr) + +Get pointer to zero of correct type for array. + +:: + + char * + PyArray_One(PyArrayObject *arr) + +Get pointer to one of correct type for array + +:: + + PyObject * + PyArray_CastToType(PyArrayObject *arr, PyArray_Descr *dtype, int + is_f_order) + +For backward compatibility + +Cast an array using typecode structure. +steals reference to at --- cannot be NULL + +This function always makes a copy of arr, even if the dtype +doesn't change. + +:: + + int + PyArray_CastTo(PyArrayObject *out, PyArrayObject *mp) + +Cast to an already created array. + +:: + + int + PyArray_CastAnyTo(PyArrayObject *out, PyArrayObject *mp) + +Cast to an already created array. Arrays don't have to be "broadcastable" +Only requirement is they have the same number of elements. + +:: + + int + PyArray_CanCastSafely(int fromtype, int totype) + +Check the type coercion rules. + +:: + + npy_bool + PyArray_CanCastTo(PyArray_Descr *from, PyArray_Descr *to) + +leaves reference count alone --- cannot be NULL + +PyArray_CanCastTypeTo is equivalent to this, but adds a 'casting' +parameter. + +:: + + int + PyArray_ObjectType(PyObject *op, int minimum_type) + +Return the typecode of the array a Python object would be converted to + +Returns the type number the result should have, or NPY_NOTYPE on error. + +:: + + PyArray_Descr * + PyArray_DescrFromObject(PyObject *op, PyArray_Descr *mintype) + +new reference -- accepts NULL for mintype + +:: + + PyArrayObject ** + PyArray_ConvertToCommonType(PyObject *op, int *retn) + + +:: + + PyArray_Descr * + PyArray_DescrFromScalar(PyObject *sc) + +Return descr object from array scalar. + +New reference + +:: + + PyArray_Descr * + PyArray_DescrFromTypeObject(PyObject *type) + + +:: + + npy_intp + PyArray_Size(PyObject *op) + +Compute the size of an array (in number of items) + +:: + + PyObject * + PyArray_Scalar(void *data, PyArray_Descr *descr, PyObject *base) + +Get scalar-equivalent to a region of memory described by a descriptor. + +:: + + PyObject * + PyArray_FromScalar(PyObject *scalar, PyArray_Descr *outcode) + +Get 0-dim array from scalar + +0-dim array from array-scalar object +always contains a copy of the data +unless outcode is NULL, it is of void type and the referrer does +not own it either. + +steals reference to outcode + +:: + + void + PyArray_ScalarAsCtype(PyObject *scalar, void *ctypeptr) + +Convert to c-type + +no error checking is performed -- ctypeptr must be same type as scalar +in case of flexible type, the data is not copied +into ctypeptr which is expected to be a pointer to pointer + +:: + + int + PyArray_CastScalarToCtype(PyObject *scalar, void + *ctypeptr, PyArray_Descr *outcode) + +Cast Scalar to c-type + +The output buffer must be large-enough to receive the value +Even for flexible types which is different from ScalarAsCtype +where only a reference for flexible types is returned + +This may not work right on narrow builds for NumPy unicode scalars. + +:: + + int + PyArray_CastScalarDirect(PyObject *scalar, PyArray_Descr + *indescr, void *ctypeptr, int outtype) + +Cast Scalar to c-type + +:: + + PyObject * + PyArray_ScalarFromObject(PyObject *object) + +Get an Array Scalar From a Python Object + +Returns NULL if unsuccessful but error is only set if another error occurred. +Currently only Numeric-like object supported. + +:: + + PyArray_VectorUnaryFunc * + PyArray_GetCastFunc(PyArray_Descr *descr, int type_num) + +Get a cast function to cast from the input descriptor to the +output type_number (must be a registered data-type). +Returns NULL if un-successful. + +:: + + PyObject * + PyArray_FromDims(int nd, int *d, int type) + +Construct an empty array from dimensions and typenum + +:: + + PyObject * + PyArray_FromDimsAndDataAndDescr(int nd, int *d, PyArray_Descr + *descr, char *data) + +Like FromDimsAndData but uses the Descr structure instead of typecode +as input. + +:: + + PyObject * + PyArray_FromAny(PyObject *op, PyArray_Descr *newtype, int + min_depth, int max_depth, int flags, PyObject + *context) + +Does not check for NPY_ARRAY_ENSURECOPY and NPY_ARRAY_NOTSWAPPED in flags +Steals a reference to newtype --- which can be NULL + +:: + + PyObject * + PyArray_EnsureArray(PyObject *op) + +This is a quick wrapper around PyArray_FromAny(op, NULL, 0, 0, ENSUREARRAY) +that special cases Arrays and PyArray_Scalars up front +It *steals a reference* to the object +It also guarantees that the result is PyArray_Type +Because it decrefs op if any conversion needs to take place +so it can be used like PyArray_EnsureArray(some_function(...)) + +:: + + PyObject * + PyArray_EnsureAnyArray(PyObject *op) + + +:: + + PyObject * + PyArray_FromFile(FILE *fp, PyArray_Descr *dtype, npy_intp num, char + *sep) + + +Given a ``FILE *`` pointer ``fp``, and a ``PyArray_Descr``, return an +array corresponding to the data encoded in that file. + +If the dtype is NULL, the default array type is used (double). +If non-null, the reference is stolen. + +The number of elements to read is given as ``num``; if it is < 0, then +then as many as possible are read. + +If ``sep`` is NULL or empty, then binary data is assumed, else +text data, with ``sep`` as the separator between elements. Whitespace in +the separator matches any length of whitespace in the text, and a match +for whitespace around the separator is added. + +For memory-mapped files, use the buffer interface. No more data than +necessary is read by this routine. + +:: + + PyObject * + PyArray_FromString(char *data, npy_intp slen, PyArray_Descr + *dtype, npy_intp num, char *sep) + + +Given a pointer to a string ``data``, a string length ``slen``, and +a ``PyArray_Descr``, return an array corresponding to the data +encoded in that string. + +If the dtype is NULL, the default array type is used (double). +If non-null, the reference is stolen. + +If ``slen`` is < 0, then the end of string is used for text data. +It is an error for ``slen`` to be < 0 for binary data (since embedded NULLs +would be the norm). + +The number of elements to read is given as ``num``; if it is < 0, then +then as many as possible are read. + +If ``sep`` is NULL or empty, then binary data is assumed, else +text data, with ``sep`` as the separator between elements. Whitespace in +the separator matches any length of whitespace in the text, and a match +for whitespace around the separator is added. + +:: + + PyObject * + PyArray_FromBuffer(PyObject *buf, PyArray_Descr *type, npy_intp + count, npy_intp offset) + + +:: + + PyObject * + PyArray_FromIter(PyObject *obj, PyArray_Descr *dtype, npy_intp count) + + +steals a reference to dtype (which cannot be NULL) + +:: + + PyObject * + PyArray_Return(PyArrayObject *mp) + + +Return either an array or the appropriate Python object if the array +is 0d and matches a Python type. + +:: + + PyObject * + PyArray_GetField(PyArrayObject *self, PyArray_Descr *typed, int + offset) + +Get a subset of bytes from each element of the array + +:: + + int + PyArray_SetField(PyArrayObject *self, PyArray_Descr *dtype, int + offset, PyObject *val) + +Set a subset of bytes from each element of the array + +:: + + PyObject * + PyArray_Byteswap(PyArrayObject *self, npy_bool inplace) + + +:: + + PyObject * + PyArray_Resize(PyArrayObject *self, PyArray_Dims *newshape, int + refcheck, NPY_ORDER order) + +Resize (reallocate data). Only works if nothing else is referencing this +array and it is contiguous. If refcheck is 0, then the reference count is +not checked and assumed to be 1. You still must own this data and have no +weak-references and no base object. + +:: + + int + PyArray_MoveInto(PyArrayObject *dst, PyArrayObject *src) + +Move the memory of one array into another, allowing for overlapping data. + +Returns 0 on success, negative on failure. + +:: + + int + PyArray_CopyInto(PyArrayObject *dst, PyArrayObject *src) + +Copy an Array into another array. +Broadcast to the destination shape if necessary. + +Returns 0 on success, -1 on failure. + +:: + + int + PyArray_CopyAnyInto(PyArrayObject *dst, PyArrayObject *src) + +Copy an Array into another array -- memory must not overlap +Does not require src and dest to have "broadcastable" shapes +(only the same number of elements). + +TODO: For NumPy 2.0, this could accept an order parameter which +only allows NPY_CORDER and NPY_FORDER. Could also rename +this to CopyAsFlat to make the name more intuitive. + +Returns 0 on success, -1 on error. + +:: + + int + PyArray_CopyObject(PyArrayObject *dest, PyObject *src_object) + + +:: + + PyObject * + PyArray_NewCopy(PyArrayObject *obj, NPY_ORDER order) + +Copy an array. + +:: + + PyObject * + PyArray_ToList(PyArrayObject *self) + +To List + +:: + + PyObject * + PyArray_ToString(PyArrayObject *self, NPY_ORDER order) + + +:: + + int + PyArray_ToFile(PyArrayObject *self, FILE *fp, char *sep, char *format) + +To File + +:: + + int + PyArray_Dump(PyObject *self, PyObject *file, int protocol) + + +:: + + PyObject * + PyArray_Dumps(PyObject *self, int protocol) + + +:: + + int + PyArray_ValidType(int type) + +Is the typenum valid? + +:: + + void + PyArray_UpdateFlags(PyArrayObject *ret, int flagmask) + +Update Several Flags at once. + +:: + + PyObject * + PyArray_New(PyTypeObject *subtype, int nd, npy_intp *dims, int + type_num, npy_intp *strides, void *data, int itemsize, int + flags, PyObject *obj) + +Generic new array creation routine. + +:: + + PyObject * + PyArray_NewFromDescr(PyTypeObject *subtype, PyArray_Descr *descr, int + nd, npy_intp *dims, npy_intp *strides, void + *data, int flags, PyObject *obj) + +Generic new array creation routine. + +steals a reference to descr (even on failure) + +:: + + PyArray_Descr * + PyArray_DescrNew(PyArray_Descr *base) + +base cannot be NULL + +:: + + PyArray_Descr * + PyArray_DescrNewFromType(int type_num) + + +:: + + double + PyArray_GetPriority(PyObject *obj, double default_) + +Get Priority from object + +:: + + PyObject * + PyArray_IterNew(PyObject *obj) + +Get Iterator. + +:: + + PyObject * + PyArray_MultiIterNew(int n, ... ) + +Get MultiIterator, + +:: + + int + PyArray_PyIntAsInt(PyObject *o) + + +:: + + npy_intp + PyArray_PyIntAsIntp(PyObject *o) + + +:: + + int + PyArray_Broadcast(PyArrayMultiIterObject *mit) + + +:: + + void + PyArray_FillObjectArray(PyArrayObject *arr, PyObject *obj) + +Assumes contiguous + +:: + + int + PyArray_FillWithScalar(PyArrayObject *arr, PyObject *obj) + + +:: + + npy_bool + PyArray_CheckStrides(int elsize, int nd, npy_intp numbytes, npy_intp + offset, npy_intp *dims, npy_intp *newstrides) + + +:: + + PyArray_Descr * + PyArray_DescrNewByteorder(PyArray_Descr *self, char newendian) + + +returns a copy of the PyArray_Descr structure with the byteorder +altered: +no arguments: The byteorder is swapped (in all subfields as well) +single argument: The byteorder is forced to the given state +(in all subfields as well) + +Valid states: ('big', '>') or ('little' or '<') +('native', or '=') + +If a descr structure with | is encountered it's own +byte-order is not changed but any fields are: + + +Deep bytorder change of a data-type descriptor +Leaves reference count of self unchanged --- does not DECREF self *** + +:: + + PyObject * + PyArray_IterAllButAxis(PyObject *obj, int *inaxis) + +Get Iterator that iterates over all but one axis (don't use this with +PyArray_ITER_GOTO1D). The axis will be over-written if negative +with the axis having the smallest stride. + +:: + + PyObject * + PyArray_CheckFromAny(PyObject *op, PyArray_Descr *descr, int + min_depth, int max_depth, int requires, PyObject + *context) + +steals a reference to descr -- accepts NULL + +:: + + PyObject * + PyArray_FromArray(PyArrayObject *arr, PyArray_Descr *newtype, int + flags) + +steals reference to newtype --- acc. NULL + +:: + + PyObject * + PyArray_FromInterface(PyObject *origin) + + +:: + + PyObject * + PyArray_FromStructInterface(PyObject *input) + + +:: + + PyObject * + PyArray_FromArrayAttr(PyObject *op, PyArray_Descr *typecode, PyObject + *context) + + +:: + + NPY_SCALARKIND + PyArray_ScalarKind(int typenum, PyArrayObject **arr) + +ScalarKind + +Returns the scalar kind of a type number, with an +optional tweak based on the scalar value itself. +If no scalar is provided, it returns INTPOS_SCALAR +for both signed and unsigned integers, otherwise +it checks the sign of any signed integer to choose +INTNEG_SCALAR when appropriate. + +:: + + int + PyArray_CanCoerceScalar(int thistype, int neededtype, NPY_SCALARKIND + scalar) + + +Determines whether the data type 'thistype', with +scalar kind 'scalar', can be coerced into 'neededtype'. + +:: + + PyObject * + PyArray_NewFlagsObject(PyObject *obj) + + +Get New ArrayFlagsObject + +:: + + npy_bool + PyArray_CanCastScalar(PyTypeObject *from, PyTypeObject *to) + +See if array scalars can be cast. + +TODO: For NumPy 2.0, add a NPY_CASTING parameter. + +:: + + int + PyArray_CompareUCS4(npy_ucs4 *s1, npy_ucs4 *s2, size_t len) + + +:: + + int + PyArray_RemoveSmallest(PyArrayMultiIterObject *multi) + +Adjusts previously broadcasted iterators so that the axis with +the smallest sum of iterator strides is not iterated over. +Returns dimension which is smallest in the range [0,multi->nd). +A -1 is returned if multi->nd == 0. + +don't use with PyArray_ITER_GOTO1D because factors are not adjusted + +:: + + int + PyArray_ElementStrides(PyObject *obj) + + +:: + + void + PyArray_Item_INCREF(char *data, PyArray_Descr *descr) + + +:: + + void + PyArray_Item_XDECREF(char *data, PyArray_Descr *descr) + + +:: + + PyObject * + PyArray_FieldNames(PyObject *fields) + +Return the tuple of ordered field names from a dictionary. + +:: + + PyObject * + PyArray_Transpose(PyArrayObject *ap, PyArray_Dims *permute) + +Return Transpose. + +:: + + PyObject * + PyArray_TakeFrom(PyArrayObject *self0, PyObject *indices0, int + axis, PyArrayObject *out, NPY_CLIPMODE clipmode) + +Take + +:: + + PyObject * + PyArray_PutTo(PyArrayObject *self, PyObject*values0, PyObject + *indices0, NPY_CLIPMODE clipmode) + +Put values into an array + +:: + + PyObject * + PyArray_PutMask(PyArrayObject *self, PyObject*values0, PyObject*mask0) + +Put values into an array according to a mask. + +:: + + PyObject * + PyArray_Repeat(PyArrayObject *aop, PyObject *op, int axis) + +Repeat the array. + +:: + + PyObject * + PyArray_Choose(PyArrayObject *ip, PyObject *op, PyArrayObject + *out, NPY_CLIPMODE clipmode) + + +:: + + int + PyArray_Sort(PyArrayObject *op, int axis, NPY_SORTKIND which) + +Sort an array in-place + +:: + + PyObject * + PyArray_ArgSort(PyArrayObject *op, int axis, NPY_SORTKIND which) + +ArgSort an array + +:: + + PyObject * + PyArray_SearchSorted(PyArrayObject *op1, PyObject *op2, NPY_SEARCHSIDE + side, PyObject *perm) + + +Search the sorted array op1 for the location of the items in op2. The +result is an array of indexes, one for each element in op2, such that if +the item were to be inserted in op1 just before that index the array +would still be in sorted order. + +Parameters +---------- +op1 : PyArrayObject * +Array to be searched, must be 1-D. +op2 : PyObject * +Array of items whose insertion indexes in op1 are wanted +side : {NPY_SEARCHLEFT, NPY_SEARCHRIGHT} +If NPY_SEARCHLEFT, return first valid insertion indexes +If NPY_SEARCHRIGHT, return last valid insertion indexes +perm : PyObject * +Permutation array that sorts op1 (optional) + +Returns +------- +ret : PyObject * +New reference to npy_intp array containing indexes where items in op2 +could be validly inserted into op1. NULL on error. + +Notes +----- +Binary search is used to find the indexes. + +:: + + PyObject * + PyArray_ArgMax(PyArrayObject *op, int axis, PyArrayObject *out) + +ArgMax + +:: + + PyObject * + PyArray_ArgMin(PyArrayObject *op, int axis, PyArrayObject *out) + +ArgMin + +:: + + PyObject * + PyArray_Reshape(PyArrayObject *self, PyObject *shape) + +Reshape + +:: + + PyObject * + PyArray_Newshape(PyArrayObject *self, PyArray_Dims *newdims, NPY_ORDER + order) + +New shape for an array + +:: + + PyObject * + PyArray_Squeeze(PyArrayObject *self) + + +return a new view of the array object with all of its unit-length +dimensions squeezed out if needed, otherwise +return the same array. + +:: + + PyObject * + PyArray_View(PyArrayObject *self, PyArray_Descr *type, PyTypeObject + *pytype) + +View +steals a reference to type -- accepts NULL + +:: + + PyObject * + PyArray_SwapAxes(PyArrayObject *ap, int a1, int a2) + +SwapAxes + +:: + + PyObject * + PyArray_Max(PyArrayObject *ap, int axis, PyArrayObject *out) + +Max + +:: + + PyObject * + PyArray_Min(PyArrayObject *ap, int axis, PyArrayObject *out) + +Min + +:: + + PyObject * + PyArray_Ptp(PyArrayObject *ap, int axis, PyArrayObject *out) + +Ptp + +:: + + PyObject * + PyArray_Mean(PyArrayObject *self, int axis, int rtype, PyArrayObject + *out) + +Mean + +:: + + PyObject * + PyArray_Trace(PyArrayObject *self, int offset, int axis1, int + axis2, int rtype, PyArrayObject *out) + +Trace + +:: + + PyObject * + PyArray_Diagonal(PyArrayObject *self, int offset, int axis1, int + axis2) + +Diagonal + +In NumPy versions prior to 1.7, this function always returned a copy of +the diagonal array. In 1.7, the code has been updated to compute a view +onto 'self', but it still copies this array before returning, as well as +setting the internal WARN_ON_WRITE flag. In a future version, it will +simply return a view onto self. + +:: + + PyObject * + PyArray_Clip(PyArrayObject *self, PyObject *min, PyObject + *max, PyArrayObject *out) + +Clip + +:: + + PyObject * + PyArray_Conjugate(PyArrayObject *self, PyArrayObject *out) + +Conjugate + +:: + + PyObject * + PyArray_Nonzero(PyArrayObject *self) + +Nonzero + +TODO: In NumPy 2.0, should make the iteration order a parameter. + +:: + + PyObject * + PyArray_Std(PyArrayObject *self, int axis, int rtype, PyArrayObject + *out, int variance) + +Set variance to 1 to by-pass square-root calculation and return variance +Std + +:: + + PyObject * + PyArray_Sum(PyArrayObject *self, int axis, int rtype, PyArrayObject + *out) + +Sum + +:: + + PyObject * + PyArray_CumSum(PyArrayObject *self, int axis, int rtype, PyArrayObject + *out) + +CumSum + +:: + + PyObject * + PyArray_Prod(PyArrayObject *self, int axis, int rtype, PyArrayObject + *out) + +Prod + +:: + + PyObject * + PyArray_CumProd(PyArrayObject *self, int axis, int + rtype, PyArrayObject *out) + +CumProd + +:: + + PyObject * + PyArray_All(PyArrayObject *self, int axis, PyArrayObject *out) + +All + +:: + + PyObject * + PyArray_Any(PyArrayObject *self, int axis, PyArrayObject *out) + +Any + +:: + + PyObject * + PyArray_Compress(PyArrayObject *self, PyObject *condition, int + axis, PyArrayObject *out) + +Compress + +:: + + PyObject * + PyArray_Flatten(PyArrayObject *a, NPY_ORDER order) + +Flatten + +:: + + PyObject * + PyArray_Ravel(PyArrayObject *arr, NPY_ORDER order) + +Ravel +Returns a contiguous array + +:: + + npy_intp + PyArray_MultiplyList(npy_intp *l1, int n) + +Multiply a List + +:: + + int + PyArray_MultiplyIntList(int *l1, int n) + +Multiply a List of ints + +:: + + void * + PyArray_GetPtr(PyArrayObject *obj, npy_intp*ind) + +Produce a pointer into array + +:: + + int + PyArray_CompareLists(npy_intp *l1, npy_intp *l2, int n) + +Compare Lists + +:: + + int + PyArray_AsCArray(PyObject **op, void *ptr, npy_intp *dims, int + nd, PyArray_Descr*typedescr) + +Simulate a C-array +steals a reference to typedescr -- can be NULL + +:: + + int + PyArray_As1D(PyObject **op, char **ptr, int *d1, int typecode) + +Convert to a 1D C-array + +:: + + int + PyArray_As2D(PyObject **op, char ***ptr, int *d1, int *d2, int + typecode) + +Convert to a 2D C-array + +:: + + int + PyArray_Free(PyObject *op, void *ptr) + +Free pointers created if As2D is called + +:: + + int + PyArray_Converter(PyObject *object, PyObject **address) + + +Useful to pass as converter function for O& processing in PyArgs_ParseTuple. + +This conversion function can be used with the "O&" argument for +PyArg_ParseTuple. It will immediately return an object of array type +or will convert to a NPY_ARRAY_CARRAY any other object. + +If you use PyArray_Converter, you must DECREF the array when finished +as you get a new reference to it. + +:: + + int + PyArray_IntpFromSequence(PyObject *seq, npy_intp *vals, int maxvals) + +PyArray_IntpFromSequence +Returns the number of dimensions or -1 if an error occurred. +vals must be large enough to hold maxvals + +:: + + PyObject * + PyArray_Concatenate(PyObject *op, int axis) + +Concatenate + +Concatenate an arbitrary Python sequence into an array. +op is a python object supporting the sequence interface. +Its elements will be concatenated together to form a single +multidimensional array. If axis is NPY_MAXDIMS or bigger, then +each sequence object will be flattened before concatenation + +:: + + PyObject * + PyArray_InnerProduct(PyObject *op1, PyObject *op2) + +Numeric.innerproduct(a,v) + +:: + + PyObject * + PyArray_MatrixProduct(PyObject *op1, PyObject *op2) + +Numeric.matrixproduct(a,v) +just like inner product but does the swapaxes stuff on the fly + +:: + + PyObject * + PyArray_CopyAndTranspose(PyObject *op) + +Copy and Transpose + +Could deprecate this function, as there isn't a speed benefit over +calling Transpose and then Copy. + +:: + + PyObject * + PyArray_Correlate(PyObject *op1, PyObject *op2, int mode) + +Numeric.correlate(a1,a2,mode) + +:: + + int + PyArray_TypestrConvert(int itemsize, int gentype) + +Typestr converter + +:: + + int + PyArray_DescrConverter(PyObject *obj, PyArray_Descr **at) + +Get typenum from an object -- None goes to NPY_DEFAULT_TYPE +This function takes a Python object representing a type and converts it +to a the correct PyArray_Descr * structure to describe the type. + +Many objects can be used to represent a data-type which in NumPy is +quite a flexible concept. + +This is the central code that converts Python objects to +Type-descriptor objects that are used throughout numpy. + +Returns a new reference in *at, but the returned should not be +modified as it may be one of the canonical immutable objects or +a reference to the input obj. + +:: + + int + PyArray_DescrConverter2(PyObject *obj, PyArray_Descr **at) + +Get typenum from an object -- None goes to NULL + +:: + + int + PyArray_IntpConverter(PyObject *obj, PyArray_Dims *seq) + +Get intp chunk from sequence + +This function takes a Python sequence object and allocates and +fills in an intp array with the converted values. + +Remember to free the pointer seq.ptr when done using +PyDimMem_FREE(seq.ptr)** + +:: + + int + PyArray_BufferConverter(PyObject *obj, PyArray_Chunk *buf) + +Get buffer chunk from object + +this function takes a Python object which exposes the (single-segment) +buffer interface and returns a pointer to the data segment + +You should increment the reference count by one of buf->base +if you will hang on to a reference + +You only get a borrowed reference to the object. Do not free the +memory... + +:: + + int + PyArray_AxisConverter(PyObject *obj, int *axis) + +Get axis from an object (possibly None) -- a converter function, + +See also PyArray_ConvertMultiAxis, which also handles a tuple of axes. + +:: + + int + PyArray_BoolConverter(PyObject *object, npy_bool *val) + +Convert an object to true / false + +:: + + int + PyArray_ByteorderConverter(PyObject *obj, char *endian) + +Convert object to endian + +:: + + int + PyArray_OrderConverter(PyObject *object, NPY_ORDER *val) + +Convert an object to FORTRAN / C / ANY / KEEP + +:: + + unsigned char + PyArray_EquivTypes(PyArray_Descr *type1, PyArray_Descr *type2) + + +This function returns true if the two typecodes are +equivalent (same basic kind and same itemsize). + +:: + + PyObject * + PyArray_Zeros(int nd, npy_intp *dims, PyArray_Descr *type, int + is_f_order) + +Zeros + +steal a reference +accepts NULL type + +:: + + PyObject * + PyArray_Empty(int nd, npy_intp *dims, PyArray_Descr *type, int + is_f_order) + +Empty + +accepts NULL type +steals referenct to type + +:: + + PyObject * + PyArray_Where(PyObject *condition, PyObject *x, PyObject *y) + +Where + +:: + + PyObject * + PyArray_Arange(double start, double stop, double step, int type_num) + +Arange, + +:: + + PyObject * + PyArray_ArangeObj(PyObject *start, PyObject *stop, PyObject + *step, PyArray_Descr *dtype) + + +ArangeObj, + +this doesn't change the references + +:: + + int + PyArray_SortkindConverter(PyObject *obj, NPY_SORTKIND *sortkind) + +Convert object to sort kind + +:: + + PyObject * + PyArray_LexSort(PyObject *sort_keys, int axis) + +LexSort an array providing indices that will sort a collection of arrays +lexicographically. The first key is sorted on first, followed by the second key +-- requires that arg"merge"sort is available for each sort_key + +Returns an index array that shows the indexes for the lexicographic sort along +the given axis. + +:: + + PyObject * + PyArray_Round(PyArrayObject *a, int decimals, PyArrayObject *out) + +Round + +:: + + unsigned char + PyArray_EquivTypenums(int typenum1, int typenum2) + + +:: + + int + PyArray_RegisterDataType(PyArray_Descr *descr) + +Register Data type +Does not change the reference count of descr + +:: + + int + PyArray_RegisterCastFunc(PyArray_Descr *descr, int + totype, PyArray_VectorUnaryFunc *castfunc) + +Register Casting Function +Replaces any function currently stored. + +:: + + int + PyArray_RegisterCanCast(PyArray_Descr *descr, int + totype, NPY_SCALARKIND scalar) + +Register a type number indicating that a descriptor can be cast +to it safely + +:: + + void + PyArray_InitArrFuncs(PyArray_ArrFuncs *f) + +Initialize arrfuncs to NULL + +:: + + PyObject * + PyArray_IntTupleFromIntp(int len, npy_intp *vals) + +PyArray_IntTupleFromIntp + +:: + + int + PyArray_TypeNumFromName(char *str) + + +:: + + int + PyArray_ClipmodeConverter(PyObject *object, NPY_CLIPMODE *val) + +Convert an object to NPY_RAISE / NPY_CLIP / NPY_WRAP + +:: + + int + PyArray_OutputConverter(PyObject *object, PyArrayObject **address) + +Useful to pass as converter function for O& processing in +PyArgs_ParseTuple for output arrays + +:: + + PyObject * + PyArray_BroadcastToShape(PyObject *obj, npy_intp *dims, int nd) + +Get Iterator broadcast to a particular shape + +:: + + void + _PyArray_SigintHandler(int signum) + + +:: + + void* + _PyArray_GetSigintBuf(void ) + + +:: + + int + PyArray_DescrAlignConverter(PyObject *obj, PyArray_Descr **at) + + +Get type-descriptor from an object forcing alignment if possible +None goes to DEFAULT type. + +any object with the .fields attribute and/or .itemsize attribute (if the +.fields attribute does not give the total size -- i.e. a partial record +naming). If itemsize is given it must be >= size computed from fields + +The .fields attribute must return a convertible dictionary if present. +Result inherits from NPY_VOID. + +:: + + int + PyArray_DescrAlignConverter2(PyObject *obj, PyArray_Descr **at) + + +Get type-descriptor from an object forcing alignment if possible +None goes to NULL. + +:: + + int + PyArray_SearchsideConverter(PyObject *obj, void *addr) + +Convert object to searchsorted side + +:: + + PyObject * + PyArray_CheckAxis(PyArrayObject *arr, int *axis, int flags) + +PyArray_CheckAxis + +check that axis is valid +convert 0-d arrays to 1-d arrays + +:: + + npy_intp + PyArray_OverflowMultiplyList(npy_intp *l1, int n) + +Multiply a List of Non-negative numbers with over-flow detection. + +:: + + int + PyArray_CompareString(char *s1, char *s2, size_t len) + + +:: + + PyObject * + PyArray_MultiIterFromObjects(PyObject **mps, int n, int nadd, ... ) + +Get MultiIterator from array of Python objects and any additional + +PyObject **mps -- array of PyObjects +int n - number of PyObjects in the array +int nadd - number of additional arrays to include in the iterator. + +Returns a multi-iterator object. + +:: + + int + PyArray_GetEndianness(void ) + + +:: + + unsigned int + PyArray_GetNDArrayCFeatureVersion(void ) + +Returns the built-in (at compilation time) C API version + +:: + + PyObject * + PyArray_Correlate2(PyObject *op1, PyObject *op2, int mode) + +correlate(a1,a2,mode) + +This function computes the usual correlation (correlate(a1, a2) != +correlate(a2, a1), and conjugate the second argument for complex inputs + +:: + + PyObject* + PyArray_NeighborhoodIterNew(PyArrayIterObject *x, npy_intp + *bounds, int mode, PyArrayObject*fill) + +A Neighborhood Iterator object. + +:: + + void + PyArray_SetDatetimeParseFunction(PyObject *op) + +This function is scheduled to be removed + +TO BE REMOVED - NOT USED INTERNALLY. + +:: + + void + PyArray_DatetimeToDatetimeStruct(npy_datetime val, NPY_DATETIMEUNIT + fr, npy_datetimestruct *result) + +Fill the datetime struct from the value and resolution unit. + +TO BE REMOVED - NOT USED INTERNALLY. + +:: + + void + PyArray_TimedeltaToTimedeltaStruct(npy_timedelta val, NPY_DATETIMEUNIT + fr, npy_timedeltastruct *result) + +Fill the timedelta struct from the timedelta value and resolution unit. + +TO BE REMOVED - NOT USED INTERNALLY. + +:: + + npy_datetime + PyArray_DatetimeStructToDatetime(NPY_DATETIMEUNIT + fr, npy_datetimestruct *d) + +Create a datetime value from a filled datetime struct and resolution unit. + +TO BE REMOVED - NOT USED INTERNALLY. + +:: + + npy_datetime + PyArray_TimedeltaStructToTimedelta(NPY_DATETIMEUNIT + fr, npy_timedeltastruct *d) + +Create a timdelta value from a filled timedelta struct and resolution unit. + +TO BE REMOVED - NOT USED INTERNALLY. + +:: + + NpyIter * + NpyIter_New(PyArrayObject *op, npy_uint32 flags, NPY_ORDER + order, NPY_CASTING casting, PyArray_Descr*dtype) + +Allocate a new iterator for one array object. + +:: + + NpyIter * + NpyIter_MultiNew(int nop, PyArrayObject **op_in, npy_uint32 + flags, NPY_ORDER order, NPY_CASTING + casting, npy_uint32 *op_flags, PyArray_Descr + **op_request_dtypes) + +Allocate a new iterator for more than one array object, using +standard NumPy broadcasting rules and the default buffer size. + +:: + + NpyIter * + NpyIter_AdvancedNew(int nop, PyArrayObject **op_in, npy_uint32 + flags, NPY_ORDER order, NPY_CASTING + casting, npy_uint32 *op_flags, PyArray_Descr + **op_request_dtypes, int oa_ndim, int + **op_axes, npy_intp *itershape, npy_intp + buffersize) + +Allocate a new iterator for multiple array objects, and advanced +options for controlling the broadcasting, shape, and buffer size. + +:: + + NpyIter * + NpyIter_Copy(NpyIter *iter) + +Makes a copy of the iterator + +:: + + int + NpyIter_Deallocate(NpyIter *iter) + +Deallocate an iterator + +:: + + npy_bool + NpyIter_HasDelayedBufAlloc(NpyIter *iter) + +Whether the buffer allocation is being delayed + +:: + + npy_bool + NpyIter_HasExternalLoop(NpyIter *iter) + +Whether the iterator handles the inner loop + +:: + + int + NpyIter_EnableExternalLoop(NpyIter *iter) + +Removes the inner loop handling (so HasExternalLoop returns true) + +:: + + npy_intp * + NpyIter_GetInnerStrideArray(NpyIter *iter) + +Get the array of strides for the inner loop (when HasExternalLoop is true) + +This function may be safely called without holding the Python GIL. + +:: + + npy_intp * + NpyIter_GetInnerLoopSizePtr(NpyIter *iter) + +Get a pointer to the size of the inner loop (when HasExternalLoop is true) + +This function may be safely called without holding the Python GIL. + +:: + + int + NpyIter_Reset(NpyIter *iter, char **errmsg) + +Resets the iterator to its initial state + +If errmsg is non-NULL, it should point to a variable which will +receive the error message, and no Python exception will be set. +This is so that the function can be called from code not holding +the GIL. + +:: + + int + NpyIter_ResetBasePointers(NpyIter *iter, char **baseptrs, char + **errmsg) + +Resets the iterator to its initial state, with new base data pointers. +This function requires great caution. + +If errmsg is non-NULL, it should point to a variable which will +receive the error message, and no Python exception will be set. +This is so that the function can be called from code not holding +the GIL. + +:: + + int + NpyIter_ResetToIterIndexRange(NpyIter *iter, npy_intp istart, npy_intp + iend, char **errmsg) + +Resets the iterator to a new iterator index range + +If errmsg is non-NULL, it should point to a variable which will +receive the error message, and no Python exception will be set. +This is so that the function can be called from code not holding +the GIL. + +:: + + int + NpyIter_GetNDim(NpyIter *iter) + +Gets the number of dimensions being iterated + +:: + + int + NpyIter_GetNOp(NpyIter *iter) + +Gets the number of operands being iterated + +:: + + NpyIter_IterNextFunc * + NpyIter_GetIterNext(NpyIter *iter, char **errmsg) + +Compute the specialized iteration function for an iterator + +If errmsg is non-NULL, it should point to a variable which will +receive the error message, and no Python exception will be set. +This is so that the function can be called from code not holding +the GIL. + +:: + + npy_intp + NpyIter_GetIterSize(NpyIter *iter) + +Gets the number of elements being iterated + +:: + + void + NpyIter_GetIterIndexRange(NpyIter *iter, npy_intp *istart, npy_intp + *iend) + +Gets the range of iteration indices being iterated + +:: + + npy_intp + NpyIter_GetIterIndex(NpyIter *iter) + +Gets the current iteration index + +:: + + int + NpyIter_GotoIterIndex(NpyIter *iter, npy_intp iterindex) + +Sets the iterator position to the specified iterindex, +which matches the iteration order of the iterator. + +Returns NPY_SUCCEED on success, NPY_FAIL on failure. + +:: + + npy_bool + NpyIter_HasMultiIndex(NpyIter *iter) + +Whether the iterator is tracking a multi-index + +:: + + int + NpyIter_GetShape(NpyIter *iter, npy_intp *outshape) + +Gets the broadcast shape if a multi-index is being tracked by the iterator, +otherwise gets the shape of the iteration as Fortran-order +(fastest-changing index first). + +The reason Fortran-order is returned when a multi-index +is not enabled is that this is providing a direct view into how +the iterator traverses the n-dimensional space. The iterator organizes +its memory from fastest index to slowest index, and when +a multi-index is enabled, it uses a permutation to recover the original +order. + +Returns NPY_SUCCEED or NPY_FAIL. + +:: + + NpyIter_GetMultiIndexFunc * + NpyIter_GetGetMultiIndex(NpyIter *iter, char **errmsg) + +Compute a specialized get_multi_index function for the iterator + +If errmsg is non-NULL, it should point to a variable which will +receive the error message, and no Python exception will be set. +This is so that the function can be called from code not holding +the GIL. + +:: + + int + NpyIter_GotoMultiIndex(NpyIter *iter, npy_intp *multi_index) + +Sets the iterator to the specified multi-index, which must have the +correct number of entries for 'ndim'. It is only valid +when NPY_ITER_MULTI_INDEX was passed to the constructor. This operation +fails if the multi-index is out of bounds. + +Returns NPY_SUCCEED on success, NPY_FAIL on failure. + +:: + + int + NpyIter_RemoveMultiIndex(NpyIter *iter) + +Removes multi-index support from an iterator. + +Returns NPY_SUCCEED or NPY_FAIL. + +:: + + npy_bool + NpyIter_HasIndex(NpyIter *iter) + +Whether the iterator is tracking an index + +:: + + npy_bool + NpyIter_IsBuffered(NpyIter *iter) + +Whether the iterator is buffered + +:: + + npy_bool + NpyIter_IsGrowInner(NpyIter *iter) + +Whether the inner loop can grow if buffering is unneeded + +:: + + npy_intp + NpyIter_GetBufferSize(NpyIter *iter) + +Gets the size of the buffer, or 0 if buffering is not enabled + +:: + + npy_intp * + NpyIter_GetIndexPtr(NpyIter *iter) + +Get a pointer to the index, if it is being tracked + +:: + + int + NpyIter_GotoIndex(NpyIter *iter, npy_intp flat_index) + +If the iterator is tracking an index, sets the iterator +to the specified index. + +Returns NPY_SUCCEED on success, NPY_FAIL on failure. + +:: + + char ** + NpyIter_GetDataPtrArray(NpyIter *iter) + +Get the array of data pointers (1 per object being iterated) + +This function may be safely called without holding the Python GIL. + +:: + + PyArray_Descr ** + NpyIter_GetDescrArray(NpyIter *iter) + +Get the array of data type pointers (1 per object being iterated) + +:: + + PyArrayObject ** + NpyIter_GetOperandArray(NpyIter *iter) + +Get the array of objects being iterated + +:: + + PyArrayObject * + NpyIter_GetIterView(NpyIter *iter, npy_intp i) + +Returns a view to the i-th object with the iterator's internal axes + +:: + + void + NpyIter_GetReadFlags(NpyIter *iter, char *outreadflags) + +Gets an array of read flags (1 per object being iterated) + +:: + + void + NpyIter_GetWriteFlags(NpyIter *iter, char *outwriteflags) + +Gets an array of write flags (1 per object being iterated) + +:: + + void + NpyIter_DebugPrint(NpyIter *iter) + +For debugging + +:: + + npy_bool + NpyIter_IterationNeedsAPI(NpyIter *iter) + +Whether the iteration loop, and in particular the iternext() +function, needs API access. If this is true, the GIL must +be retained while iterating. + +:: + + void + NpyIter_GetInnerFixedStrideArray(NpyIter *iter, npy_intp *out_strides) + +Get an array of strides which are fixed. Any strides which may +change during iteration receive the value NPY_MAX_INTP. Once +the iterator is ready to iterate, call this to get the strides +which will always be fixed in the inner loop, then choose optimized +inner loop functions which take advantage of those fixed strides. + +This function may be safely called without holding the Python GIL. + +:: + + int + NpyIter_RemoveAxis(NpyIter *iter, int axis) + +Removes an axis from iteration. This requires that NPY_ITER_MULTI_INDEX +was set for iterator creation, and does not work if buffering is +enabled. This function also resets the iterator to its initial state. + +Returns NPY_SUCCEED or NPY_FAIL. + +:: + + npy_intp * + NpyIter_GetAxisStrideArray(NpyIter *iter, int axis) + +Gets the array of strides for the specified axis. +If the iterator is tracking a multi-index, gets the strides +for the axis specified, otherwise gets the strides for +the iteration axis as Fortran order (fastest-changing axis first). + +Returns NULL if an error occurs. + +:: + + npy_bool + NpyIter_RequiresBuffering(NpyIter *iter) + +Whether the iteration could be done with no buffering. + +:: + + char ** + NpyIter_GetInitialDataPtrArray(NpyIter *iter) + +Get the array of data pointers (1 per object being iterated), +directly into the arrays (never pointing to a buffer), for starting +unbuffered iteration. This always returns the addresses for the +iterator position as reset to iterator index 0. + +These pointers are different from the pointers accepted by +NpyIter_ResetBasePointers, because the direction along some +axes may have been reversed, requiring base offsets. + +This function may be safely called without holding the Python GIL. + +:: + + int + NpyIter_CreateCompatibleStrides(NpyIter *iter, npy_intp + itemsize, npy_intp *outstrides) + +Builds a set of strides which are the same as the strides of an +output array created using the NPY_ITER_ALLOCATE flag, where NULL +was passed for op_axes. This is for data packed contiguously, +but not necessarily in C or Fortran order. This should be used +together with NpyIter_GetShape and NpyIter_GetNDim. + +A use case for this function is to match the shape and layout of +the iterator and tack on one or more dimensions. For example, +in order to generate a vector per input value for a numerical gradient, +you pass in ndim*itemsize for itemsize, then add another dimension to +the end with size ndim and stride itemsize. To do the Hessian matrix, +you do the same thing but add two dimensions, or take advantage of +the symmetry and pack it into 1 dimension with a particular encoding. + +This function may only be called if the iterator is tracking a multi-index +and if NPY_ITER_DONT_NEGATE_STRIDES was used to prevent an axis from +being iterated in reverse order. + +If an array is created with this method, simply adding 'itemsize' +for each iteration will traverse the new array matching the +iterator. + +Returns NPY_SUCCEED or NPY_FAIL. + +:: + + int + PyArray_CastingConverter(PyObject *obj, NPY_CASTING *casting) + +Convert any Python object, *obj*, to an NPY_CASTING enum. + +:: + + npy_intp + PyArray_CountNonzero(PyArrayObject *self) + +Counts the number of non-zero elements in the array. + +Returns -1 on error. + +:: + + PyArray_Descr * + PyArray_PromoteTypes(PyArray_Descr *type1, PyArray_Descr *type2) + +Produces the smallest size and lowest kind type to which both +input types can be cast. + +:: + + PyArray_Descr * + PyArray_MinScalarType(PyArrayObject *arr) + +If arr is a scalar (has 0 dimensions) with a built-in number data type, +finds the smallest type size/kind which can still represent its data. +Otherwise, returns the array's data type. + + +:: + + PyArray_Descr * + PyArray_ResultType(npy_intp narrs, PyArrayObject **arr, npy_intp + ndtypes, PyArray_Descr **dtypes) + +Produces the result type of a bunch of inputs, using the UFunc +type promotion rules. Use this function when you have a set of +input arrays, and need to determine an output array dtype. + +If all the inputs are scalars (have 0 dimensions) or the maximum "kind" +of the scalars is greater than the maximum "kind" of the arrays, does +a regular type promotion. + +Otherwise, does a type promotion on the MinScalarType +of all the inputs. Data types passed directly are treated as array +types. + + +:: + + npy_bool + PyArray_CanCastArrayTo(PyArrayObject *arr, PyArray_Descr + *to, NPY_CASTING casting) + +Returns 1 if the array object may be cast to the given data type using +the casting rule, 0 otherwise. This differs from PyArray_CanCastTo in +that it handles scalar arrays (0 dimensions) specially, by checking +their value. + +:: + + npy_bool + PyArray_CanCastTypeTo(PyArray_Descr *from, PyArray_Descr + *to, NPY_CASTING casting) + +Returns true if data of type 'from' may be cast to data of type +'to' according to the rule 'casting'. + +:: + + PyArrayObject * + PyArray_EinsteinSum(char *subscripts, npy_intp nop, PyArrayObject + **op_in, PyArray_Descr *dtype, NPY_ORDER + order, NPY_CASTING casting, PyArrayObject *out) + +This function provides summation of array elements according to +the Einstein summation convention. For example: +- trace(a) -> einsum("ii", a) +- transpose(a) -> einsum("ji", a) +- multiply(a,b) -> einsum(",", a, b) +- inner(a,b) -> einsum("i,i", a, b) +- outer(a,b) -> einsum("i,j", a, b) +- matvec(a,b) -> einsum("ij,j", a, b) +- matmat(a,b) -> einsum("ij,jk", a, b) + +subscripts: The string of subscripts for einstein summation. +nop: The number of operands +op_in: The array of operands +dtype: Either NULL, or the data type to force the calculation as. +order: The order for the calculation/the output axes. +casting: What kind of casts should be permitted. +out: Either NULL, or an array into which the output should be placed. + +By default, the labels get placed in alphabetical order +at the end of the output. So, if c = einsum("i,j", a, b) +then c[i,j] == a[i]*b[j], but if c = einsum("j,i", a, b) +then c[i,j] = a[j]*b[i]. + +Alternatively, you can control the output order or prevent +an axis from being summed/force an axis to be summed by providing +indices for the output. This allows us to turn 'trace' into +'diag', for example. +- diag(a) -> einsum("ii->i", a) +- sum(a, axis=0) -> einsum("i...->", a) + +Subscripts at the beginning and end may be specified by +putting an ellipsis "..." in the middle. For example, +the function einsum("i...i", a) takes the diagonal of +the first and last dimensions of the operand, and +einsum("ij...,jk...->ik...") takes the matrix product using +the first two indices of each operand instead of the last two. + +When there is only one operand, no axes being summed, and +no output parameter, this function returns a view +into the operand instead of making a copy. + +:: + + PyObject * + PyArray_NewLikeArray(PyArrayObject *prototype, NPY_ORDER + order, PyArray_Descr *dtype, int subok) + +Creates a new array with the same shape as the provided one, +with possible memory layout order and data type changes. + +prototype - The array the new one should be like. +order - NPY_CORDER - C-contiguous result. +NPY_FORTRANORDER - Fortran-contiguous result. +NPY_ANYORDER - Fortran if prototype is Fortran, C otherwise. +NPY_KEEPORDER - Keeps the axis ordering of prototype. +dtype - If not NULL, overrides the data type of the result. +subok - If 1, use the prototype's array subtype, otherwise +always create a base-class array. + +NOTE: If dtype is not NULL, steals the dtype reference. + +:: + + int + PyArray_GetArrayParamsFromObject(PyObject *op, PyArray_Descr + *requested_dtype, npy_bool + writeable, PyArray_Descr + **out_dtype, int *out_ndim, npy_intp + *out_dims, PyArrayObject + **out_arr, PyObject *context) + +Retrieves the array parameters for viewing/converting an arbitrary +PyObject* to a NumPy array. This allows the "innate type and shape" +of Python list-of-lists to be discovered without +actually converting to an array. + +In some cases, such as structured arrays and the __array__ interface, +a data type needs to be used to make sense of the object. When +this is needed, provide a Descr for 'requested_dtype', otherwise +provide NULL. This reference is not stolen. Also, if the requested +dtype doesn't modify the interpretation of the input, out_dtype will +still get the "innate" dtype of the object, not the dtype passed +in 'requested_dtype'. + +If writing to the value in 'op' is desired, set the boolean +'writeable' to 1. This raises an error when 'op' is a scalar, list +of lists, or other non-writeable 'op'. + +Result: When success (0 return value) is returned, either out_arr +is filled with a non-NULL PyArrayObject and +the rest of the parameters are untouched, or out_arr is +filled with NULL, and the rest of the parameters are +filled. + +Typical usage: + +PyArrayObject *arr = NULL; +PyArray_Descr *dtype = NULL; +int ndim = 0; +npy_intp dims[NPY_MAXDIMS]; + +if (PyArray_GetArrayParamsFromObject(op, NULL, 1, &dtype, +&ndim, &dims, &arr, NULL) < 0) { +return NULL; +} +if (arr == NULL) { +... validate/change dtype, validate flags, ndim, etc ... +// Could make custom strides here too +arr = PyArray_NewFromDescr(&PyArray_Type, dtype, ndim, +dims, NULL, +is_f_order ? NPY_ARRAY_F_CONTIGUOUS : 0, +NULL); +if (arr == NULL) { +return NULL; +} +if (PyArray_CopyObject(arr, op) < 0) { +Py_DECREF(arr); +return NULL; +} +} +else { +... in this case the other parameters weren't filled, just +validate and possibly copy arr itself ... +} +... use arr ... + +:: + + int + PyArray_ConvertClipmodeSequence(PyObject *object, NPY_CLIPMODE + *modes, int n) + +Convert an object to an array of n NPY_CLIPMODE values. +This is intended to be used in functions where a different mode +could be applied to each axis, like in ravel_multi_index. + +:: + + PyObject * + PyArray_MatrixProduct2(PyObject *op1, PyObject + *op2, PyArrayObject*out) + +Numeric.matrixproduct(a,v,out) +just like inner product but does the swapaxes stuff on the fly + +:: + + npy_bool + NpyIter_IsFirstVisit(NpyIter *iter, int iop) + +Checks to see whether this is the first time the elements +of the specified reduction operand which the iterator points at are +being seen for the first time. The function returns +a reasonable answer for reduction operands and when buffering is +disabled. The answer may be incorrect for buffered non-reduction +operands. + +This function is intended to be used in EXTERNAL_LOOP mode only, +and will produce some wrong answers when that mode is not enabled. + +If this function returns true, the caller should also +check the inner loop stride of the operand, because if +that stride is 0, then only the first element of the innermost +external loop is being visited for the first time. + +WARNING: For performance reasons, 'iop' is not bounds-checked, +it is not confirmed that 'iop' is actually a reduction +operand, and it is not confirmed that EXTERNAL_LOOP +mode is enabled. These checks are the responsibility of +the caller, and should be done outside of any inner loops. + +:: + + int + PyArray_SetBaseObject(PyArrayObject *arr, PyObject *obj) + +Sets the 'base' attribute of the array. This steals a reference +to 'obj'. + +Returns 0 on success, -1 on failure. + +:: + + void + PyArray_CreateSortedStridePerm(int ndim, npy_intp + *strides, npy_stride_sort_item + *out_strideperm) + + +This function populates the first ndim elements +of strideperm with sorted descending by their absolute values. +For example, the stride array (4, -2, 12) becomes +[(2, 12), (0, 4), (1, -2)]. + +:: + + void + PyArray_RemoveAxesInPlace(PyArrayObject *arr, npy_bool *flags) + + +Removes the axes flagged as True from the array, +modifying it in place. If an axis flagged for removal +has a shape entry bigger than one, this effectively selects +index zero for that axis. + +WARNING: If an axis flagged for removal has a shape equal to zero, +the array will point to invalid memory. The caller must +validate this! + +For example, this can be used to remove the reduction axes +from a reduction result once its computation is complete. + +:: + + void + PyArray_DebugPrint(PyArrayObject *obj) + +Prints the raw data of the ndarray in a form useful for debugging +low-level C issues. + +:: + + int + PyArray_FailUnlessWriteable(PyArrayObject *obj, const char *name) + + +This function does nothing if obj is writeable, and raises an exception +(and returns -1) if obj is not writeable. It may also do other +house-keeping, such as issuing warnings on arrays which are transitioning +to become views. Always call this function at some point before writing to +an array. + +'name' is a name for the array, used to give better error +messages. Something like "assignment destination", "output array", or even +just "array". + +:: + + int + PyArray_SetUpdateIfCopyBase(PyArrayObject *arr, PyArrayObject *base) + + +Precondition: 'arr' is a copy of 'base' (though possibly with different +strides, ordering, etc.). This function sets the UPDATEIFCOPY flag and the +->base pointer on 'arr', so that when 'arr' is destructed, it will copy any +changes back to 'base'. + +Steals a reference to 'base'. + +Returns 0 on success, -1 on failure. + +:: + + void * + PyDataMem_NEW(size_t size) + +Allocates memory for array data. + +:: + + void + PyDataMem_FREE(void *ptr) + +Free memory for array data. + +:: + + void * + PyDataMem_RENEW(void *ptr, size_t size) + +Reallocate/resize memory for array data. + +:: + + PyDataMem_EventHookFunc * + PyDataMem_SetEventHook(PyDataMem_EventHookFunc *newhook, void + *user_data, void **old_data) + +Sets the allocation event hook for numpy array data. +Takes a PyDataMem_EventHookFunc *, which has the signature: +void hook(void *old, void *new, size_t size, void *user_data). +Also takes a void *user_data, and void **old_data. + +Returns a pointer to the previous hook or NULL. If old_data is +non-NULL, the previous user_data pointer will be copied to it. + +If not NULL, hook will be called at the end of each PyDataMem_NEW/FREE/RENEW: +result = PyDataMem_NEW(size) -> (*hook)(NULL, result, size, user_data) +PyDataMem_FREE(ptr) -> (*hook)(ptr, NULL, 0, user_data) +result = PyDataMem_RENEW(ptr, size) -> (*hook)(ptr, result, size, user_data) + +When the hook is called, the GIL will be held by the calling +thread. The hook should be written to be reentrant, if it performs +operations that might cause new allocation events (such as the +creation/descruction numpy objects, or creating/destroying Python +objects which might cause a gc) + diff --git a/data_tooling/pii_processing/include/numpy/ndarrayobject.h b/data_tooling/pii_processing/include/numpy/ndarrayobject.h new file mode 100644 index 0000000..f00dd77 --- /dev/null +++ b/data_tooling/pii_processing/include/numpy/ndarrayobject.h @@ -0,0 +1,244 @@ +/* + * DON'T INCLUDE THIS DIRECTLY. + */ + +#ifndef NPY_NDARRAYOBJECT_H +#define NPY_NDARRAYOBJECT_H +#ifdef __cplusplus +#define CONFUSE_EMACS { +#define CONFUSE_EMACS2 } +extern "C" CONFUSE_EMACS +#undef CONFUSE_EMACS +#undef CONFUSE_EMACS2 +/* ... otherwise a semi-smart identer (like emacs) tries to indent + everything when you're typing */ +#endif + +#include "ndarraytypes.h" + +/* Includes the "function" C-API -- these are all stored in a + list of pointers --- one for each file + The two lists are concatenated into one in multiarray. + + They are available as import_array() +*/ + +#include "__multiarray_api.h" + + +/* C-API that requries previous API to be defined */ + +#define PyArray_DescrCheck(op) (((PyObject*)(op))->ob_type==&PyArrayDescr_Type) + +#define PyArray_Check(op) PyObject_TypeCheck(op, &PyArray_Type) +#define PyArray_CheckExact(op) (((PyObject*)(op))->ob_type == &PyArray_Type) + +#define PyArray_HasArrayInterfaceType(op, type, context, out) \ + ((((out)=PyArray_FromStructInterface(op)) != Py_NotImplemented) || \ + (((out)=PyArray_FromInterface(op)) != Py_NotImplemented) || \ + (((out)=PyArray_FromArrayAttr(op, type, context)) != \ + Py_NotImplemented)) + +#define PyArray_HasArrayInterface(op, out) \ + PyArray_HasArrayInterfaceType(op, NULL, NULL, out) + +#define PyArray_IsZeroDim(op) (PyArray_Check(op) && \ + (PyArray_NDIM((PyArrayObject *)op) == 0)) + +#define PyArray_IsScalar(obj, cls) \ + (PyObject_TypeCheck(obj, &Py##cls##ArrType_Type)) + +#define PyArray_CheckScalar(m) (PyArray_IsScalar(m, Generic) || \ + PyArray_IsZeroDim(m)) + +#define PyArray_IsPythonNumber(obj) \ + (PyInt_Check(obj) || PyFloat_Check(obj) || PyComplex_Check(obj) || \ + PyLong_Check(obj) || PyBool_Check(obj)) + +#define PyArray_IsPythonScalar(obj) \ + (PyArray_IsPythonNumber(obj) || PyString_Check(obj) || \ + PyUnicode_Check(obj)) + +#define PyArray_IsAnyScalar(obj) \ + (PyArray_IsScalar(obj, Generic) || PyArray_IsPythonScalar(obj)) + +#define PyArray_CheckAnyScalar(obj) (PyArray_IsPythonScalar(obj) || \ + PyArray_CheckScalar(obj)) + +#define PyArray_IsIntegerScalar(obj) (PyInt_Check(obj) \ + || PyLong_Check(obj) \ + || PyArray_IsScalar((obj), Integer)) + + +#define PyArray_GETCONTIGUOUS(m) (PyArray_ISCONTIGUOUS(m) ? \ + Py_INCREF(m), (m) : \ + (PyArrayObject *)(PyArray_Copy(m))) + +#define PyArray_SAMESHAPE(a1,a2) ((PyArray_NDIM(a1) == PyArray_NDIM(a2)) && \ + PyArray_CompareLists(PyArray_DIMS(a1), \ + PyArray_DIMS(a2), \ + PyArray_NDIM(a1))) + +#define PyArray_SIZE(m) PyArray_MultiplyList(PyArray_DIMS(m), PyArray_NDIM(m)) +#define PyArray_NBYTES(m) (PyArray_ITEMSIZE(m) * PyArray_SIZE(m)) +#define PyArray_FROM_O(m) PyArray_FromAny(m, NULL, 0, 0, 0, NULL) + +#define PyArray_FROM_OF(m,flags) PyArray_CheckFromAny(m, NULL, 0, 0, flags, \ + NULL) + +#define PyArray_FROM_OT(m,type) PyArray_FromAny(m, \ + PyArray_DescrFromType(type), 0, 0, 0, NULL); + +#define PyArray_FROM_OTF(m, type, flags) \ + PyArray_FromAny(m, PyArray_DescrFromType(type), 0, 0, \ + (((flags) & NPY_ARRAY_ENSURECOPY) ? \ + ((flags) | NPY_ARRAY_DEFAULT) : (flags)), NULL) + +#define PyArray_FROMANY(m, type, min, max, flags) \ + PyArray_FromAny(m, PyArray_DescrFromType(type), min, max, \ + (((flags) & NPY_ARRAY_ENSURECOPY) ? \ + (flags) | NPY_ARRAY_DEFAULT : (flags)), NULL) + +#define PyArray_ZEROS(m, dims, type, is_f_order) \ + PyArray_Zeros(m, dims, PyArray_DescrFromType(type), is_f_order) + +#define PyArray_EMPTY(m, dims, type, is_f_order) \ + PyArray_Empty(m, dims, PyArray_DescrFromType(type), is_f_order) + +#define PyArray_FILLWBYTE(obj, val) memset(PyArray_DATA(obj), val, \ + PyArray_NBYTES(obj)) + +#define PyArray_REFCOUNT(obj) (((PyObject *)(obj))->ob_refcnt) +#define NPY_REFCOUNT PyArray_REFCOUNT +#define NPY_MAX_ELSIZE (2 * NPY_SIZEOF_LONGDOUBLE) + +#define PyArray_ContiguousFromAny(op, type, min_depth, max_depth) \ + PyArray_FromAny(op, PyArray_DescrFromType(type), min_depth, \ + max_depth, NPY_ARRAY_DEFAULT, NULL) + +#define PyArray_EquivArrTypes(a1, a2) \ + PyArray_EquivTypes(PyArray_DESCR(a1), PyArray_DESCR(a2)) + +#define PyArray_EquivByteorders(b1, b2) \ + (((b1) == (b2)) || (PyArray_ISNBO(b1) == PyArray_ISNBO(b2))) + +#define PyArray_SimpleNew(nd, dims, typenum) \ + PyArray_New(&PyArray_Type, nd, dims, typenum, NULL, NULL, 0, 0, NULL) + +#define PyArray_SimpleNewFromData(nd, dims, typenum, data) \ + PyArray_New(&PyArray_Type, nd, dims, typenum, NULL, \ + data, 0, NPY_ARRAY_CARRAY, NULL) + +#define PyArray_SimpleNewFromDescr(nd, dims, descr) \ + PyArray_NewFromDescr(&PyArray_Type, descr, nd, dims, \ + NULL, NULL, 0, NULL) + +#define PyArray_ToScalar(data, arr) \ + PyArray_Scalar(data, PyArray_DESCR(arr), (PyObject *)arr) + + +/* These might be faster without the dereferencing of obj + going on inside -- of course an optimizing compiler should + inline the constants inside a for loop making it a moot point +*/ + +#define PyArray_GETPTR1(obj, i) ((void *)(PyArray_BYTES(obj) + \ + (i)*PyArray_STRIDES(obj)[0])) + +#define PyArray_GETPTR2(obj, i, j) ((void *)(PyArray_BYTES(obj) + \ + (i)*PyArray_STRIDES(obj)[0] + \ + (j)*PyArray_STRIDES(obj)[1])) + +#define PyArray_GETPTR3(obj, i, j, k) ((void *)(PyArray_BYTES(obj) + \ + (i)*PyArray_STRIDES(obj)[0] + \ + (j)*PyArray_STRIDES(obj)[1] + \ + (k)*PyArray_STRIDES(obj)[2])) + +#define PyArray_GETPTR4(obj, i, j, k, l) ((void *)(PyArray_BYTES(obj) + \ + (i)*PyArray_STRIDES(obj)[0] + \ + (j)*PyArray_STRIDES(obj)[1] + \ + (k)*PyArray_STRIDES(obj)[2] + \ + (l)*PyArray_STRIDES(obj)[3])) + +static NPY_INLINE void +PyArray_XDECREF_ERR(PyArrayObject *arr) +{ + if (arr != NULL) { + if (PyArray_FLAGS(arr) & NPY_ARRAY_UPDATEIFCOPY) { + PyArrayObject *base = (PyArrayObject *)PyArray_BASE(arr); + PyArray_ENABLEFLAGS(base, NPY_ARRAY_WRITEABLE); + PyArray_CLEARFLAGS(arr, NPY_ARRAY_UPDATEIFCOPY); + } + Py_DECREF(arr); + } +} + +#define PyArray_DESCR_REPLACE(descr) do { \ + PyArray_Descr *_new_; \ + _new_ = PyArray_DescrNew(descr); \ + Py_XDECREF(descr); \ + descr = _new_; \ + } while(0) + +/* Copy should always return contiguous array */ +#define PyArray_Copy(obj) PyArray_NewCopy(obj, NPY_CORDER) + +#define PyArray_FromObject(op, type, min_depth, max_depth) \ + PyArray_FromAny(op, PyArray_DescrFromType(type), min_depth, \ + max_depth, NPY_ARRAY_BEHAVED | \ + NPY_ARRAY_ENSUREARRAY, NULL) + +#define PyArray_ContiguousFromObject(op, type, min_depth, max_depth) \ + PyArray_FromAny(op, PyArray_DescrFromType(type), min_depth, \ + max_depth, NPY_ARRAY_DEFAULT | \ + NPY_ARRAY_ENSUREARRAY, NULL) + +#define PyArray_CopyFromObject(op, type, min_depth, max_depth) \ + PyArray_FromAny(op, PyArray_DescrFromType(type), min_depth, \ + max_depth, NPY_ARRAY_ENSURECOPY | \ + NPY_ARRAY_DEFAULT | \ + NPY_ARRAY_ENSUREARRAY, NULL) + +#define PyArray_Cast(mp, type_num) \ + PyArray_CastToType(mp, PyArray_DescrFromType(type_num), 0) + +#define PyArray_Take(ap, items, axis) \ + PyArray_TakeFrom(ap, items, axis, NULL, NPY_RAISE) + +#define PyArray_Put(ap, items, values) \ + PyArray_PutTo(ap, items, values, NPY_RAISE) + +/* Compatibility with old Numeric stuff -- don't use in new code */ + +#define PyArray_FromDimsAndData(nd, d, type, data) \ + PyArray_FromDimsAndDataAndDescr(nd, d, PyArray_DescrFromType(type), \ + data) + + +/* + Check to see if this key in the dictionary is the "title" + entry of the tuple (i.e. a duplicate dictionary entry in the fields + dict. +*/ + +#define NPY_TITLE_KEY(key, value) ((PyTuple_GET_SIZE((value))==3) && \ + (PyTuple_GET_ITEM((value), 2) == (key))) + + +/* Define python version independent deprecation macro */ + +#if PY_VERSION_HEX >= 0x02050000 +#define DEPRECATE(msg) PyErr_WarnEx(PyExc_DeprecationWarning,msg,1) +#define DEPRECATE_FUTUREWARNING(msg) PyErr_WarnEx(PyExc_FutureWarning,msg,1) +#else +#define DEPRECATE(msg) PyErr_Warn(PyExc_DeprecationWarning,msg) +#define DEPRECATE_FUTUREWARNING(msg) PyErr_Warn(PyExc_FutureWarning,msg) +#endif + + +#ifdef __cplusplus +} +#endif + + +#endif /* NPY_NDARRAYOBJECT_H */ diff --git a/data_tooling/pii_processing/include/numpy/ndarraytypes.h b/data_tooling/pii_processing/include/numpy/ndarraytypes.h new file mode 100644 index 0000000..04d037e --- /dev/null +++ b/data_tooling/pii_processing/include/numpy/ndarraytypes.h @@ -0,0 +1,1731 @@ +#ifndef NDARRAYTYPES_H +#define NDARRAYTYPES_H + +/* numpyconfig.h is auto-generated by the installer */ +#include "numpyconfig.h" + +#include "npy_common.h" +#include "npy_endian.h" +#include "npy_cpu.h" +#include "utils.h" + +#ifdef NPY_ENABLE_SEPARATE_COMPILATION + #define NPY_NO_EXPORT NPY_VISIBILITY_HIDDEN +#else + #define NPY_NO_EXPORT static +#endif + +/* Only use thread if configured in config and python supports it */ +#if defined WITH_THREAD && !NPY_NO_SMP + #define NPY_ALLOW_THREADS 1 +#else + #define NPY_ALLOW_THREADS 0 +#endif + + + +/* + * There are several places in the code where an array of dimensions + * is allocated statically. This is the size of that static + * allocation. + * + * The array creation itself could have arbitrary dimensions but all + * the places where static allocation is used would need to be changed + * to dynamic (including inside of several structures) + */ + +#define NPY_MAXDIMS 32 +#define NPY_MAXARGS 32 + +/* Used for Converter Functions "O&" code in ParseTuple */ +#define NPY_FAIL 0 +#define NPY_SUCCEED 1 + +/* + * Binary compatibility version number. This number is increased + * whenever the C-API is changed such that binary compatibility is + * broken, i.e. whenever a recompile of extension modules is needed. + */ +#define NPY_VERSION NPY_ABI_VERSION + +/* + * Minor API version. This number is increased whenever a change is + * made to the C-API -- whether it breaks binary compatibility or not. + * Some changes, such as adding a function pointer to the end of the + * function table, can be made without breaking binary compatibility. + * In this case, only the NPY_FEATURE_VERSION (*not* NPY_VERSION) + * would be increased. Whenever binary compatibility is broken, both + * NPY_VERSION and NPY_FEATURE_VERSION should be increased. + */ +#define NPY_FEATURE_VERSION NPY_API_VERSION + +enum NPY_TYPES { NPY_BOOL=0, + NPY_BYTE, NPY_UBYTE, + NPY_SHORT, NPY_USHORT, + NPY_INT, NPY_UINT, + NPY_LONG, NPY_ULONG, + NPY_LONGLONG, NPY_ULONGLONG, + NPY_FLOAT, NPY_DOUBLE, NPY_LONGDOUBLE, + NPY_CFLOAT, NPY_CDOUBLE, NPY_CLONGDOUBLE, + NPY_OBJECT=17, + NPY_STRING, NPY_UNICODE, + NPY_VOID, + /* + * New 1.6 types appended, may be integrated + * into the above in 2.0. + */ + NPY_DATETIME, NPY_TIMEDELTA, NPY_HALF, + + NPY_NTYPES, + NPY_NOTYPE, + NPY_CHAR, /* special flag */ + NPY_USERDEF=256, /* leave room for characters */ + + /* The number of types not including the new 1.6 types */ + NPY_NTYPES_ABI_COMPATIBLE=21 +}; + +/* basetype array priority */ +#define NPY_PRIORITY 0.0 + +/* default subtype priority */ +#define NPY_SUBTYPE_PRIORITY 1.0 + +/* default scalar priority */ +#define NPY_SCALAR_PRIORITY -1000000.0 + +/* How many floating point types are there (excluding half) */ +#define NPY_NUM_FLOATTYPE 3 + +/* + * These characters correspond to the array type and the struct + * module + */ + +enum NPY_TYPECHAR { + NPY_BOOLLTR = '?', + NPY_BYTELTR = 'b', + NPY_UBYTELTR = 'B', + NPY_SHORTLTR = 'h', + NPY_USHORTLTR = 'H', + NPY_INTLTR = 'i', + NPY_UINTLTR = 'I', + NPY_LONGLTR = 'l', + NPY_ULONGLTR = 'L', + NPY_LONGLONGLTR = 'q', + NPY_ULONGLONGLTR = 'Q', + NPY_HALFLTR = 'e', + NPY_FLOATLTR = 'f', + NPY_DOUBLELTR = 'd', + NPY_LONGDOUBLELTR = 'g', + NPY_CFLOATLTR = 'F', + NPY_CDOUBLELTR = 'D', + NPY_CLONGDOUBLELTR = 'G', + NPY_OBJECTLTR = 'O', + NPY_STRINGLTR = 'S', + NPY_STRINGLTR2 = 'a', + NPY_UNICODELTR = 'U', + NPY_VOIDLTR = 'V', + NPY_DATETIMELTR = 'M', + NPY_TIMEDELTALTR = 'm', + NPY_CHARLTR = 'c', + + /* + * No Descriptor, just a define -- this let's + * Python users specify an array of integers + * large enough to hold a pointer on the + * platform + */ + NPY_INTPLTR = 'p', + NPY_UINTPLTR = 'P', + + /* + * These are for dtype 'kinds', not dtype 'typecodes' + * as the above are for. + */ + NPY_GENBOOLLTR ='b', + NPY_SIGNEDLTR = 'i', + NPY_UNSIGNEDLTR = 'u', + NPY_FLOATINGLTR = 'f', + NPY_COMPLEXLTR = 'c' +}; + +typedef enum { + NPY_QUICKSORT=0, + NPY_HEAPSORT=1, + NPY_MERGESORT=2 +} NPY_SORTKIND; +#define NPY_NSORTS (NPY_MERGESORT + 1) + + +typedef enum { + NPY_SEARCHLEFT=0, + NPY_SEARCHRIGHT=1 +} NPY_SEARCHSIDE; +#define NPY_NSEARCHSIDES (NPY_SEARCHRIGHT + 1) + + +typedef enum { + NPY_NOSCALAR=-1, + NPY_BOOL_SCALAR, + NPY_INTPOS_SCALAR, + NPY_INTNEG_SCALAR, + NPY_FLOAT_SCALAR, + NPY_COMPLEX_SCALAR, + NPY_OBJECT_SCALAR +} NPY_SCALARKIND; +#define NPY_NSCALARKINDS (NPY_OBJECT_SCALAR + 1) + +/* For specifying array memory layout or iteration order */ +typedef enum { + /* Fortran order if inputs are all Fortran, C otherwise */ + NPY_ANYORDER=-1, + /* C order */ + NPY_CORDER=0, + /* Fortran order */ + NPY_FORTRANORDER=1, + /* An order as close to the inputs as possible */ + NPY_KEEPORDER=2 +} NPY_ORDER; + +/* For specifying allowed casting in operations which support it */ +typedef enum { + /* Only allow identical types */ + NPY_NO_CASTING=0, + /* Allow identical and byte swapped types */ + NPY_EQUIV_CASTING=1, + /* Only allow safe casts */ + NPY_SAFE_CASTING=2, + /* Allow safe casts or casts within the same kind */ + NPY_SAME_KIND_CASTING=3, + /* Allow any casts */ + NPY_UNSAFE_CASTING=4, + + /* + * Temporary internal definition only, will be removed in upcoming + * release, see below + * */ + NPY_INTERNAL_UNSAFE_CASTING_BUT_WARN_UNLESS_SAME_KIND = 100, +} NPY_CASTING; + +typedef enum { + NPY_CLIP=0, + NPY_WRAP=1, + NPY_RAISE=2 +} NPY_CLIPMODE; + +/* The special not-a-time (NaT) value */ +#define NPY_DATETIME_NAT NPY_MIN_INT64 + +/* + * Upper bound on the length of a DATETIME ISO 8601 string + * YEAR: 21 (64-bit year) + * MONTH: 3 + * DAY: 3 + * HOURS: 3 + * MINUTES: 3 + * SECONDS: 3 + * ATTOSECONDS: 1 + 3*6 + * TIMEZONE: 5 + * NULL TERMINATOR: 1 + */ +#define NPY_DATETIME_MAX_ISO8601_STRLEN (21+3*5+1+3*6+6+1) + +typedef enum { + NPY_FR_Y = 0, /* Years */ + NPY_FR_M = 1, /* Months */ + NPY_FR_W = 2, /* Weeks */ + /* Gap where 1.6 NPY_FR_B (value 3) was */ + NPY_FR_D = 4, /* Days */ + NPY_FR_h = 5, /* hours */ + NPY_FR_m = 6, /* minutes */ + NPY_FR_s = 7, /* seconds */ + NPY_FR_ms = 8, /* milliseconds */ + NPY_FR_us = 9, /* microseconds */ + NPY_FR_ns = 10,/* nanoseconds */ + NPY_FR_ps = 11,/* picoseconds */ + NPY_FR_fs = 12,/* femtoseconds */ + NPY_FR_as = 13,/* attoseconds */ + NPY_FR_GENERIC = 14 /* Generic, unbound units, can convert to anything */ +} NPY_DATETIMEUNIT; + +/* + * NOTE: With the NPY_FR_B gap for 1.6 ABI compatibility, NPY_DATETIME_NUMUNITS + * is technically one more than the actual number of units. + */ +#define NPY_DATETIME_NUMUNITS (NPY_FR_GENERIC + 1) +#define NPY_DATETIME_DEFAULTUNIT NPY_FR_GENERIC + +/* + * Business day conventions for mapping invalid business + * days to valid business days. + */ +typedef enum { + /* Go forward in time to the following business day. */ + NPY_BUSDAY_FORWARD, + NPY_BUSDAY_FOLLOWING = NPY_BUSDAY_FORWARD, + /* Go backward in time to the preceding business day. */ + NPY_BUSDAY_BACKWARD, + NPY_BUSDAY_PRECEDING = NPY_BUSDAY_BACKWARD, + /* + * Go forward in time to the following business day, unless it + * crosses a month boundary, in which case go backward + */ + NPY_BUSDAY_MODIFIEDFOLLOWING, + /* + * Go backward in time to the preceding business day, unless it + * crosses a month boundary, in which case go forward. + */ + NPY_BUSDAY_MODIFIEDPRECEDING, + /* Produce a NaT for non-business days. */ + NPY_BUSDAY_NAT, + /* Raise an exception for non-business days. */ + NPY_BUSDAY_RAISE +} NPY_BUSDAY_ROLL; + +/************************************************************ + * NumPy Auxiliary Data for inner loops, sort functions, etc. + ************************************************************/ + +/* + * When creating an auxiliary data struct, this should always appear + * as the first member, like this: + * + * typedef struct { + * NpyAuxData base; + * double constant; + * } constant_multiplier_aux_data; + */ +typedef struct NpyAuxData_tag NpyAuxData; + +/* Function pointers for freeing or cloning auxiliary data */ +typedef void (NpyAuxData_FreeFunc) (NpyAuxData *); +typedef NpyAuxData *(NpyAuxData_CloneFunc) (NpyAuxData *); + +struct NpyAuxData_tag { + NpyAuxData_FreeFunc *free; + NpyAuxData_CloneFunc *clone; + /* To allow for a bit of expansion without breaking the ABI */ + void *reserved[2]; +}; + +/* Macros to use for freeing and cloning auxiliary data */ +#define NPY_AUXDATA_FREE(auxdata) \ + do { \ + if ((auxdata) != NULL) { \ + (auxdata)->free(auxdata); \ + } \ + } while(0) +#define NPY_AUXDATA_CLONE(auxdata) \ + ((auxdata)->clone(auxdata)) + +#define NPY_ERR(str) fprintf(stderr, #str); fflush(stderr); +#define NPY_ERR2(str) fprintf(stderr, str); fflush(stderr); + +#define NPY_STRINGIFY(x) #x +#define NPY_TOSTRING(x) NPY_STRINGIFY(x) + + /* + * Macros to define how array, and dimension/strides data is + * allocated. + */ + + /* Data buffer - PyDataMem_NEW/FREE/RENEW are in multiarraymodule.c */ + +#define NPY_USE_PYMEM 1 + +#if NPY_USE_PYMEM == 1 +#define PyArray_malloc PyMem_Malloc +#define PyArray_free PyMem_Free +#define PyArray_realloc PyMem_Realloc +#else +#define PyArray_malloc malloc +#define PyArray_free free +#define PyArray_realloc realloc +#endif + +/* Dimensions and strides */ +#define PyDimMem_NEW(size) \ + ((npy_intp *)PyArray_malloc(size*sizeof(npy_intp))) + +#define PyDimMem_FREE(ptr) PyArray_free(ptr) + +#define PyDimMem_RENEW(ptr,size) \ + ((npy_intp *)PyArray_realloc(ptr,size*sizeof(npy_intp))) + +/* forward declaration */ +struct _PyArray_Descr; + +/* These must deal with unaligned and swapped data if necessary */ +typedef PyObject * (PyArray_GetItemFunc) (void *, void *); +typedef int (PyArray_SetItemFunc)(PyObject *, void *, void *); + +typedef void (PyArray_CopySwapNFunc)(void *, npy_intp, void *, npy_intp, + npy_intp, int, void *); + +typedef void (PyArray_CopySwapFunc)(void *, void *, int, void *); +typedef npy_bool (PyArray_NonzeroFunc)(void *, void *); + + +/* + * These assume aligned and notswapped data -- a buffer will be used + * before or contiguous data will be obtained + */ + +typedef int (PyArray_CompareFunc)(const void *, const void *, void *); +typedef int (PyArray_ArgFunc)(void*, npy_intp, npy_intp*, void *); + +typedef void (PyArray_DotFunc)(void *, npy_intp, void *, npy_intp, void *, + npy_intp, void *); + +typedef void (PyArray_VectorUnaryFunc)(void *, void *, npy_intp, void *, + void *); + +/* + * XXX the ignore argument should be removed next time the API version + * is bumped. It used to be the separator. + */ +typedef int (PyArray_ScanFunc)(FILE *fp, void *dptr, + char *ignore, struct _PyArray_Descr *); +typedef int (PyArray_FromStrFunc)(char *s, void *dptr, char **endptr, + struct _PyArray_Descr *); + +typedef int (PyArray_FillFunc)(void *, npy_intp, void *); + +typedef int (PyArray_SortFunc)(void *, npy_intp, void *); +typedef int (PyArray_ArgSortFunc)(void *, npy_intp *, npy_intp, void *); + +typedef int (PyArray_FillWithScalarFunc)(void *, npy_intp, void *, void *); + +typedef int (PyArray_ScalarKindFunc)(void *); + +typedef void (PyArray_FastClipFunc)(void *in, npy_intp n_in, void *min, + void *max, void *out); +typedef void (PyArray_FastPutmaskFunc)(void *in, void *mask, npy_intp n_in, + void *values, npy_intp nv); +typedef int (PyArray_FastTakeFunc)(void *dest, void *src, npy_intp *indarray, + npy_intp nindarray, npy_intp n_outer, + npy_intp m_middle, npy_intp nelem, + NPY_CLIPMODE clipmode); + +typedef struct { + npy_intp *ptr; + int len; +} PyArray_Dims; + +typedef struct { + /* + * Functions to cast to most other standard types + * Can have some NULL entries. The types + * DATETIME, TIMEDELTA, and HALF go into the castdict + * even though they are built-in. + */ + PyArray_VectorUnaryFunc *cast[NPY_NTYPES_ABI_COMPATIBLE]; + + /* The next four functions *cannot* be NULL */ + + /* + * Functions to get and set items with standard Python types + * -- not array scalars + */ + PyArray_GetItemFunc *getitem; + PyArray_SetItemFunc *setitem; + + /* + * Copy and/or swap data. Memory areas may not overlap + * Use memmove first if they might + */ + PyArray_CopySwapNFunc *copyswapn; + PyArray_CopySwapFunc *copyswap; + + /* + * Function to compare items + * Can be NULL + */ + PyArray_CompareFunc *compare; + + /* + * Function to select largest + * Can be NULL + */ + PyArray_ArgFunc *argmax; + + /* + * Function to compute dot product + * Can be NULL + */ + PyArray_DotFunc *dotfunc; + + /* + * Function to scan an ASCII file and + * place a single value plus possible separator + * Can be NULL + */ + PyArray_ScanFunc *scanfunc; + + /* + * Function to read a single value from a string + * and adjust the pointer; Can be NULL + */ + PyArray_FromStrFunc *fromstr; + + /* + * Function to determine if data is zero or not + * If NULL a default version is + * used at Registration time. + */ + PyArray_NonzeroFunc *nonzero; + + /* + * Used for arange. + * Can be NULL. + */ + PyArray_FillFunc *fill; + + /* + * Function to fill arrays with scalar values + * Can be NULL + */ + PyArray_FillWithScalarFunc *fillwithscalar; + + /* + * Sorting functions + * Can be NULL + */ + PyArray_SortFunc *sort[NPY_NSORTS]; + PyArray_ArgSortFunc *argsort[NPY_NSORTS]; + + /* + * Dictionary of additional casting functions + * PyArray_VectorUnaryFuncs + * which can be populated to support casting + * to other registered types. Can be NULL + */ + PyObject *castdict; + + /* + * Functions useful for generalizing + * the casting rules. + * Can be NULL; + */ + PyArray_ScalarKindFunc *scalarkind; + int **cancastscalarkindto; + int *cancastto; + + PyArray_FastClipFunc *fastclip; + PyArray_FastPutmaskFunc *fastputmask; + PyArray_FastTakeFunc *fasttake; + + /* + * Function to select smallest + * Can be NULL + */ + PyArray_ArgFunc *argmin; + +} PyArray_ArrFuncs; + +/* The item must be reference counted when it is inserted or extracted. */ +#define NPY_ITEM_REFCOUNT 0x01 +/* Same as needing REFCOUNT */ +#define NPY_ITEM_HASOBJECT 0x01 +/* Convert to list for pickling */ +#define NPY_LIST_PICKLE 0x02 +/* The item is a POINTER */ +#define NPY_ITEM_IS_POINTER 0x04 +/* memory needs to be initialized for this data-type */ +#define NPY_NEEDS_INIT 0x08 +/* operations need Python C-API so don't give-up thread. */ +#define NPY_NEEDS_PYAPI 0x10 +/* Use f.getitem when extracting elements of this data-type */ +#define NPY_USE_GETITEM 0x20 +/* Use f.setitem when setting creating 0-d array from this data-type.*/ +#define NPY_USE_SETITEM 0x40 +/* A sticky flag specifically for structured arrays */ +#define NPY_ALIGNED_STRUCT 0x80 + +/* + *These are inherited for global data-type if any data-types in the + * field have them + */ +#define NPY_FROM_FIELDS (NPY_NEEDS_INIT | NPY_LIST_PICKLE | \ + NPY_ITEM_REFCOUNT | NPY_NEEDS_PYAPI) + +#define NPY_OBJECT_DTYPE_FLAGS (NPY_LIST_PICKLE | NPY_USE_GETITEM | \ + NPY_ITEM_IS_POINTER | NPY_ITEM_REFCOUNT | \ + NPY_NEEDS_INIT | NPY_NEEDS_PYAPI) + +#define PyDataType_FLAGCHK(dtype, flag) \ + (((dtype)->flags & (flag)) == (flag)) + +#define PyDataType_REFCHK(dtype) \ + PyDataType_FLAGCHK(dtype, NPY_ITEM_REFCOUNT) + +typedef struct _PyArray_Descr { + PyObject_HEAD + /* + * the type object representing an + * instance of this type -- should not + * be two type_numbers with the same type + * object. + */ + PyTypeObject *typeobj; + /* kind for this type */ + char kind; + /* unique-character representing this type */ + char type; + /* + * '>' (big), '<' (little), '|' + * (not-applicable), or '=' (native). + */ + char byteorder; + /* flags describing data type */ + char flags; + /* number representing this type */ + int type_num; + /* element size (itemsize) for this type */ + int elsize; + /* alignment needed for this type */ + int alignment; + /* + * Non-NULL if this type is + * is an array (C-contiguous) + * of some other type + */ + struct _arr_descr *subarray; + /* + * The fields dictionary for this type + * For statically defined descr this + * is always Py_None + */ + PyObject *fields; + /* + * An ordered tuple of field names or NULL + * if no fields are defined + */ + PyObject *names; + /* + * a table of functions specific for each + * basic data descriptor + */ + PyArray_ArrFuncs *f; + /* Metadata about this dtype */ + PyObject *metadata; + /* + * Metadata specific to the C implementation + * of the particular dtype. This was added + * for NumPy 1.7.0. + */ + NpyAuxData *c_metadata; +} PyArray_Descr; + +typedef struct _arr_descr { + PyArray_Descr *base; + PyObject *shape; /* a tuple */ +} PyArray_ArrayDescr; + +/* + * The main array object structure. + * + * It has been recommended to use the inline functions defined below + * (PyArray_DATA and friends) to access fields here for a number of + * releases. Direct access to the members themselves is deprecated. + * To ensure that your code does not use deprecated access, + * #define NPY_NO_DEPRECATED_API NPY_1_7_VERSION + * (or NPY_1_8_VERSION or higher as required). + */ +/* This struct will be moved to a private header in a future release */ +typedef struct tagPyArrayObject_fields { + PyObject_HEAD + /* Pointer to the raw data buffer */ + char *data; + /* The number of dimensions, also called 'ndim' */ + int nd; + /* The size in each dimension, also called 'shape' */ + npy_intp *dimensions; + /* + * Number of bytes to jump to get to the + * next element in each dimension + */ + npy_intp *strides; + /* + * This object is decref'd upon + * deletion of array. Except in the + * case of UPDATEIFCOPY which has + * special handling. + * + * For views it points to the original + * array, collapsed so no chains of + * views occur. + * + * For creation from buffer object it + * points to an object that shold be + * decref'd on deletion + * + * For UPDATEIFCOPY flag this is an + * array to-be-updated upon deletion + * of this one + */ + PyObject *base; + /* Pointer to type structure */ + PyArray_Descr *descr; + /* Flags describing array -- see below */ + int flags; + /* For weak references */ + PyObject *weakreflist; +} PyArrayObject_fields; + +/* + * To hide the implementation details, we only expose + * the Python struct HEAD. + */ +#if !(defined(NPY_NO_DEPRECATED_API) && (NPY_API_VERSION <= NPY_NO_DEPRECATED_API)) +/* + * Can't put this in npy_deprecated_api.h like the others. + * PyArrayObject field access is deprecated as of NumPy 1.7. + */ +typedef PyArrayObject_fields PyArrayObject; +#else +typedef struct tagPyArrayObject { + PyObject_HEAD +} PyArrayObject; +#endif + +#define NPY_SIZEOF_PYARRAYOBJECT (sizeof(PyArrayObject_fields)) + +/* Array Flags Object */ +typedef struct PyArrayFlagsObject { + PyObject_HEAD + PyObject *arr; + int flags; +} PyArrayFlagsObject; + +/* Mirrors buffer object to ptr */ + +typedef struct { + PyObject_HEAD + PyObject *base; + void *ptr; + npy_intp len; + int flags; +} PyArray_Chunk; + +typedef struct { + NPY_DATETIMEUNIT base; + int num; +} PyArray_DatetimeMetaData; + +typedef struct { + NpyAuxData base; + PyArray_DatetimeMetaData meta; +} PyArray_DatetimeDTypeMetaData; + +/* + * This structure contains an exploded view of a date-time value. + * NaT is represented by year == NPY_DATETIME_NAT. + */ +typedef struct { + npy_int64 year; + npy_int32 month, day, hour, min, sec, us, ps, as; +} npy_datetimestruct; + +/* This is not used internally. */ +typedef struct { + npy_int64 day; + npy_int32 sec, us, ps, as; +} npy_timedeltastruct; + +typedef int (PyArray_FinalizeFunc)(PyArrayObject *, PyObject *); + +/* + * Means c-style contiguous (last index varies the fastest). The data + * elements right after each other. + * + * This flag may be requested in constructor functions. + * This flag may be tested for in PyArray_FLAGS(arr). + */ +#define NPY_ARRAY_C_CONTIGUOUS 0x0001 + +/* + * Set if array is a contiguous Fortran array: the first index varies + * the fastest in memory (strides array is reverse of C-contiguous + * array) + * + * This flag may be requested in constructor functions. + * This flag may be tested for in PyArray_FLAGS(arr). + */ +#define NPY_ARRAY_F_CONTIGUOUS 0x0002 + +/* + * Note: all 0-d arrays are C_CONTIGUOUS and F_CONTIGUOUS. If a + * 1-d array is C_CONTIGUOUS it is also F_CONTIGUOUS + */ + +/* + * If set, the array owns the data: it will be free'd when the array + * is deleted. + * + * This flag may be tested for in PyArray_FLAGS(arr). + */ +#define NPY_ARRAY_OWNDATA 0x0004 + +/* + * An array never has the next four set; they're only used as parameter + * flags to the the various FromAny functions + * + * This flag may be requested in constructor functions. + */ + +/* Cause a cast to occur regardless of whether or not it is safe. */ +#define NPY_ARRAY_FORCECAST 0x0010 + +/* + * Always copy the array. Returned arrays are always CONTIGUOUS, + * ALIGNED, and WRITEABLE. + * + * This flag may be requested in constructor functions. + */ +#define NPY_ARRAY_ENSURECOPY 0x0020 + +/* + * Make sure the returned array is a base-class ndarray + * + * This flag may be requested in constructor functions. + */ +#define NPY_ARRAY_ENSUREARRAY 0x0040 + +/* + * Make sure that the strides are in units of the element size Needed + * for some operations with record-arrays. + * + * This flag may be requested in constructor functions. + */ +#define NPY_ARRAY_ELEMENTSTRIDES 0x0080 + +/* + * Array data is aligned on the appropiate memory address for the type + * stored according to how the compiler would align things (e.g., an + * array of integers (4 bytes each) starts on a memory address that's + * a multiple of 4) + * + * This flag may be requested in constructor functions. + * This flag may be tested for in PyArray_FLAGS(arr). + */ +#define NPY_ARRAY_ALIGNED 0x0100 + +/* + * Array data has the native endianness + * + * This flag may be requested in constructor functions. + */ +#define NPY_ARRAY_NOTSWAPPED 0x0200 + +/* + * Array data is writeable + * + * This flag may be requested in constructor functions. + * This flag may be tested for in PyArray_FLAGS(arr). + */ +#define NPY_ARRAY_WRITEABLE 0x0400 + +/* + * If this flag is set, then base contains a pointer to an array of + * the same size that should be updated with the current contents of + * this array when this array is deallocated + * + * This flag may be requested in constructor functions. + * This flag may be tested for in PyArray_FLAGS(arr). + */ +#define NPY_ARRAY_UPDATEIFCOPY 0x1000 + +/* + * NOTE: there are also internal flags defined in multiarray/arrayobject.h, + * which start at bit 31 and work down. + */ + +#define NPY_ARRAY_BEHAVED (NPY_ARRAY_ALIGNED | \ + NPY_ARRAY_WRITEABLE) +#define NPY_ARRAY_BEHAVED_NS (NPY_ARRAY_ALIGNED | \ + NPY_ARRAY_WRITEABLE | \ + NPY_ARRAY_NOTSWAPPED) +#define NPY_ARRAY_CARRAY (NPY_ARRAY_C_CONTIGUOUS | \ + NPY_ARRAY_BEHAVED) +#define NPY_ARRAY_CARRAY_RO (NPY_ARRAY_C_CONTIGUOUS | \ + NPY_ARRAY_ALIGNED) +#define NPY_ARRAY_FARRAY (NPY_ARRAY_F_CONTIGUOUS | \ + NPY_ARRAY_BEHAVED) +#define NPY_ARRAY_FARRAY_RO (NPY_ARRAY_F_CONTIGUOUS | \ + NPY_ARRAY_ALIGNED) +#define NPY_ARRAY_DEFAULT (NPY_ARRAY_CARRAY) +#define NPY_ARRAY_IN_ARRAY (NPY_ARRAY_CARRAY_RO) +#define NPY_ARRAY_OUT_ARRAY (NPY_ARRAY_CARRAY) +#define NPY_ARRAY_INOUT_ARRAY (NPY_ARRAY_CARRAY | \ + NPY_ARRAY_UPDATEIFCOPY) +#define NPY_ARRAY_IN_FARRAY (NPY_ARRAY_FARRAY_RO) +#define NPY_ARRAY_OUT_FARRAY (NPY_ARRAY_FARRAY) +#define NPY_ARRAY_INOUT_FARRAY (NPY_ARRAY_FARRAY | \ + NPY_ARRAY_UPDATEIFCOPY) + +#define NPY_ARRAY_UPDATE_ALL (NPY_ARRAY_C_CONTIGUOUS | \ + NPY_ARRAY_F_CONTIGUOUS | \ + NPY_ARRAY_ALIGNED) + +/* This flag is for the array interface, not PyArrayObject */ +#define NPY_ARR_HAS_DESCR 0x0800 + + + + +/* + * Size of internal buffers used for alignment Make BUFSIZE a multiple + * of sizeof(npy_cdouble) -- usually 16 so that ufunc buffers are aligned + */ +#define NPY_MIN_BUFSIZE ((int)sizeof(npy_cdouble)) +#define NPY_MAX_BUFSIZE (((int)sizeof(npy_cdouble))*1000000) +#define NPY_BUFSIZE 8192 +/* buffer stress test size: */ +/*#define NPY_BUFSIZE 17*/ + +#define PyArray_MAX(a,b) (((a)>(b))?(a):(b)) +#define PyArray_MIN(a,b) (((a)<(b))?(a):(b)) +#define PyArray_CLT(p,q) ((((p).real==(q).real) ? ((p).imag < (q).imag) : \ + ((p).real < (q).real))) +#define PyArray_CGT(p,q) ((((p).real==(q).real) ? ((p).imag > (q).imag) : \ + ((p).real > (q).real))) +#define PyArray_CLE(p,q) ((((p).real==(q).real) ? ((p).imag <= (q).imag) : \ + ((p).real <= (q).real))) +#define PyArray_CGE(p,q) ((((p).real==(q).real) ? ((p).imag >= (q).imag) : \ + ((p).real >= (q).real))) +#define PyArray_CEQ(p,q) (((p).real==(q).real) && ((p).imag == (q).imag)) +#define PyArray_CNE(p,q) (((p).real!=(q).real) || ((p).imag != (q).imag)) + +/* + * C API: consists of Macros and functions. The MACROS are defined + * here. + */ + + +#define PyArray_ISCONTIGUOUS(m) PyArray_CHKFLAGS(m, NPY_ARRAY_C_CONTIGUOUS) +#define PyArray_ISWRITEABLE(m) PyArray_CHKFLAGS(m, NPY_ARRAY_WRITEABLE) +#define PyArray_ISALIGNED(m) PyArray_CHKFLAGS(m, NPY_ARRAY_ALIGNED) + +#define PyArray_IS_C_CONTIGUOUS(m) PyArray_CHKFLAGS(m, NPY_ARRAY_C_CONTIGUOUS) +#define PyArray_IS_F_CONTIGUOUS(m) PyArray_CHKFLAGS(m, NPY_ARRAY_F_CONTIGUOUS) + +#if NPY_ALLOW_THREADS +#define NPY_BEGIN_ALLOW_THREADS Py_BEGIN_ALLOW_THREADS +#define NPY_END_ALLOW_THREADS Py_END_ALLOW_THREADS +#define NPY_BEGIN_THREADS_DEF PyThreadState *_save=NULL; +#define NPY_BEGIN_THREADS do {_save = PyEval_SaveThread();} while (0); +#define NPY_END_THREADS do {if (_save) PyEval_RestoreThread(_save);} while (0); + +#define NPY_BEGIN_THREADS_DESCR(dtype) \ + do {if (!(PyDataType_FLAGCHK(dtype, NPY_NEEDS_PYAPI))) \ + NPY_BEGIN_THREADS;} while (0); + +#define NPY_END_THREADS_DESCR(dtype) \ + do {if (!(PyDataType_FLAGCHK(dtype, NPY_NEEDS_PYAPI))) \ + NPY_END_THREADS; } while (0); + +#define NPY_ALLOW_C_API_DEF PyGILState_STATE __save__; +#define NPY_ALLOW_C_API do {__save__ = PyGILState_Ensure();} while (0); +#define NPY_DISABLE_C_API do {PyGILState_Release(__save__);} while (0); +#else +#define NPY_BEGIN_ALLOW_THREADS +#define NPY_END_ALLOW_THREADS +#define NPY_BEGIN_THREADS_DEF +#define NPY_BEGIN_THREADS +#define NPY_END_THREADS +#define NPY_BEGIN_THREADS_DESCR(dtype) +#define NPY_END_THREADS_DESCR(dtype) +#define NPY_ALLOW_C_API_DEF +#define NPY_ALLOW_C_API +#define NPY_DISABLE_C_API +#endif + +/********************************** + * The nditer object, added in 1.6 + **********************************/ + +/* The actual structure of the iterator is an internal detail */ +typedef struct NpyIter_InternalOnly NpyIter; + +/* Iterator function pointers that may be specialized */ +typedef int (NpyIter_IterNextFunc)(NpyIter *iter); +typedef void (NpyIter_GetMultiIndexFunc)(NpyIter *iter, + npy_intp *outcoords); + +/*** Global flags that may be passed to the iterator constructors ***/ + +/* Track an index representing C order */ +#define NPY_ITER_C_INDEX 0x00000001 +/* Track an index representing Fortran order */ +#define NPY_ITER_F_INDEX 0x00000002 +/* Track a multi-index */ +#define NPY_ITER_MULTI_INDEX 0x00000004 +/* User code external to the iterator does the 1-dimensional innermost loop */ +#define NPY_ITER_EXTERNAL_LOOP 0x00000008 +/* Convert all the operands to a common data type */ +#define NPY_ITER_COMMON_DTYPE 0x00000010 +/* Operands may hold references, requiring API access during iteration */ +#define NPY_ITER_REFS_OK 0x00000020 +/* Zero-sized operands should be permitted, iteration checks IterSize for 0 */ +#define NPY_ITER_ZEROSIZE_OK 0x00000040 +/* Permits reductions (size-0 stride with dimension size > 1) */ +#define NPY_ITER_REDUCE_OK 0x00000080 +/* Enables sub-range iteration */ +#define NPY_ITER_RANGED 0x00000100 +/* Enables buffering */ +#define NPY_ITER_BUFFERED 0x00000200 +/* When buffering is enabled, grows the inner loop if possible */ +#define NPY_ITER_GROWINNER 0x00000400 +/* Delay allocation of buffers until first Reset* call */ +#define NPY_ITER_DELAY_BUFALLOC 0x00000800 +/* When NPY_KEEPORDER is specified, disable reversing negative-stride axes */ +#define NPY_ITER_DONT_NEGATE_STRIDES 0x00001000 + +/*** Per-operand flags that may be passed to the iterator constructors ***/ + +/* The operand will be read from and written to */ +#define NPY_ITER_READWRITE 0x00010000 +/* The operand will only be read from */ +#define NPY_ITER_READONLY 0x00020000 +/* The operand will only be written to */ +#define NPY_ITER_WRITEONLY 0x00040000 +/* The operand's data must be in native byte order */ +#define NPY_ITER_NBO 0x00080000 +/* The operand's data must be aligned */ +#define NPY_ITER_ALIGNED 0x00100000 +/* The operand's data must be contiguous (within the inner loop) */ +#define NPY_ITER_CONTIG 0x00200000 +/* The operand may be copied to satisfy requirements */ +#define NPY_ITER_COPY 0x00400000 +/* The operand may be copied with UPDATEIFCOPY to satisfy requirements */ +#define NPY_ITER_UPDATEIFCOPY 0x00800000 +/* Allocate the operand if it is NULL */ +#define NPY_ITER_ALLOCATE 0x01000000 +/* If an operand is allocated, don't use any subtype */ +#define NPY_ITER_NO_SUBTYPE 0x02000000 +/* This is a virtual array slot, operand is NULL but temporary data is there */ +#define NPY_ITER_VIRTUAL 0x04000000 +/* Require that the dimension match the iterator dimensions exactly */ +#define NPY_ITER_NO_BROADCAST 0x08000000 +/* A mask is being used on this array, affects buffer -> array copy */ +#define NPY_ITER_WRITEMASKED 0x10000000 +/* This array is the mask for all WRITEMASKED operands */ +#define NPY_ITER_ARRAYMASK 0x20000000 + +#define NPY_ITER_GLOBAL_FLAGS 0x0000ffff +#define NPY_ITER_PER_OP_FLAGS 0xffff0000 + + +/***************************** + * Basic iterator object + *****************************/ + +/* FWD declaration */ +typedef struct PyArrayIterObject_tag PyArrayIterObject; + +/* + * type of the function which translates a set of coordinates to a + * pointer to the data + */ +typedef char* (*npy_iter_get_dataptr_t)(PyArrayIterObject* iter, npy_intp*); + +struct PyArrayIterObject_tag { + PyObject_HEAD + int nd_m1; /* number of dimensions - 1 */ + npy_intp index, size; + npy_intp coordinates[NPY_MAXDIMS];/* N-dimensional loop */ + npy_intp dims_m1[NPY_MAXDIMS]; /* ao->dimensions - 1 */ + npy_intp strides[NPY_MAXDIMS]; /* ao->strides or fake */ + npy_intp backstrides[NPY_MAXDIMS];/* how far to jump back */ + npy_intp factors[NPY_MAXDIMS]; /* shape factors */ + PyArrayObject *ao; + char *dataptr; /* pointer to current item*/ + npy_bool contiguous; + + npy_intp bounds[NPY_MAXDIMS][2]; + npy_intp limits[NPY_MAXDIMS][2]; + npy_intp limits_sizes[NPY_MAXDIMS]; + npy_iter_get_dataptr_t translate; +} ; + + +/* Iterator API */ +#define PyArrayIter_Check(op) PyObject_TypeCheck(op, &PyArrayIter_Type) + +#define _PyAIT(it) ((PyArrayIterObject *)(it)) +#define PyArray_ITER_RESET(it) do { \ + _PyAIT(it)->index = 0; \ + _PyAIT(it)->dataptr = PyArray_BYTES(_PyAIT(it)->ao); \ + memset(_PyAIT(it)->coordinates, 0, \ + (_PyAIT(it)->nd_m1+1)*sizeof(npy_intp)); \ +} while (0) + +#define _PyArray_ITER_NEXT1(it) do { \ + (it)->dataptr += _PyAIT(it)->strides[0]; \ + (it)->coordinates[0]++; \ +} while (0) + +#define _PyArray_ITER_NEXT2(it) do { \ + if ((it)->coordinates[1] < (it)->dims_m1[1]) { \ + (it)->coordinates[1]++; \ + (it)->dataptr += (it)->strides[1]; \ + } \ + else { \ + (it)->coordinates[1] = 0; \ + (it)->coordinates[0]++; \ + (it)->dataptr += (it)->strides[0] - \ + (it)->backstrides[1]; \ + } \ +} while (0) + +#define _PyArray_ITER_NEXT3(it) do { \ + if ((it)->coordinates[2] < (it)->dims_m1[2]) { \ + (it)->coordinates[2]++; \ + (it)->dataptr += (it)->strides[2]; \ + } \ + else { \ + (it)->coordinates[2] = 0; \ + (it)->dataptr -= (it)->backstrides[2]; \ + if ((it)->coordinates[1] < (it)->dims_m1[1]) { \ + (it)->coordinates[1]++; \ + (it)->dataptr += (it)->strides[1]; \ + } \ + else { \ + (it)->coordinates[1] = 0; \ + (it)->coordinates[0]++; \ + (it)->dataptr += (it)->strides[0] \ + (it)->backstrides[1]; \ + } \ + } \ +} while (0) + +#define PyArray_ITER_NEXT(it) do { \ + _PyAIT(it)->index++; \ + if (_PyAIT(it)->nd_m1 == 0) { \ + _PyArray_ITER_NEXT1(_PyAIT(it)); \ + } \ + else if (_PyAIT(it)->contiguous) \ + _PyAIT(it)->dataptr += PyArray_DESCR(_PyAIT(it)->ao)->elsize; \ + else if (_PyAIT(it)->nd_m1 == 1) { \ + _PyArray_ITER_NEXT2(_PyAIT(it)); \ + } \ + else { \ + int __npy_i; \ + for (__npy_i=_PyAIT(it)->nd_m1; __npy_i >= 0; __npy_i--) { \ + if (_PyAIT(it)->coordinates[__npy_i] < \ + _PyAIT(it)->dims_m1[__npy_i]) { \ + _PyAIT(it)->coordinates[__npy_i]++; \ + _PyAIT(it)->dataptr += \ + _PyAIT(it)->strides[__npy_i]; \ + break; \ + } \ + else { \ + _PyAIT(it)->coordinates[__npy_i] = 0; \ + _PyAIT(it)->dataptr -= \ + _PyAIT(it)->backstrides[__npy_i]; \ + } \ + } \ + } \ +} while (0) + +#define PyArray_ITER_GOTO(it, destination) do { \ + int __npy_i; \ + _PyAIT(it)->index = 0; \ + _PyAIT(it)->dataptr = PyArray_BYTES(_PyAIT(it)->ao); \ + for (__npy_i = _PyAIT(it)->nd_m1; __npy_i>=0; __npy_i--) { \ + if (destination[__npy_i] < 0) { \ + destination[__npy_i] += \ + _PyAIT(it)->dims_m1[__npy_i]+1; \ + } \ + _PyAIT(it)->dataptr += destination[__npy_i] * \ + _PyAIT(it)->strides[__npy_i]; \ + _PyAIT(it)->coordinates[__npy_i] = \ + destination[__npy_i]; \ + _PyAIT(it)->index += destination[__npy_i] * \ + ( __npy_i==_PyAIT(it)->nd_m1 ? 1 : \ + _PyAIT(it)->dims_m1[__npy_i+1]+1) ; \ + } \ +} while (0) + +#define PyArray_ITER_GOTO1D(it, ind) do { \ + int __npy_i; \ + npy_intp __npy_ind = (npy_intp) (ind); \ + if (__npy_ind < 0) __npy_ind += _PyAIT(it)->size; \ + _PyAIT(it)->index = __npy_ind; \ + if (_PyAIT(it)->nd_m1 == 0) { \ + _PyAIT(it)->dataptr = PyArray_BYTES(_PyAIT(it)->ao) + \ + __npy_ind * _PyAIT(it)->strides[0]; \ + } \ + else if (_PyAIT(it)->contiguous) \ + _PyAIT(it)->dataptr = PyArray_BYTES(_PyAIT(it)->ao) + \ + __npy_ind * PyArray_DESCR(_PyAIT(it)->ao)->elsize; \ + else { \ + _PyAIT(it)->dataptr = PyArray_BYTES(_PyAIT(it)->ao); \ + for (__npy_i = 0; __npy_i<=_PyAIT(it)->nd_m1; \ + __npy_i++) { \ + _PyAIT(it)->dataptr += \ + (__npy_ind / _PyAIT(it)->factors[__npy_i]) \ + * _PyAIT(it)->strides[__npy_i]; \ + __npy_ind %= _PyAIT(it)->factors[__npy_i]; \ + } \ + } \ +} while (0) + +#define PyArray_ITER_DATA(it) ((void *)(_PyAIT(it)->dataptr)) + +#define PyArray_ITER_NOTDONE(it) (_PyAIT(it)->index < _PyAIT(it)->size) + + +/* + * Any object passed to PyArray_Broadcast must be binary compatible + * with this structure. + */ + +typedef struct { + PyObject_HEAD + int numiter; /* number of iters */ + npy_intp size; /* broadcasted size */ + npy_intp index; /* current index */ + int nd; /* number of dims */ + npy_intp dimensions[NPY_MAXDIMS]; /* dimensions */ + PyArrayIterObject *iters[NPY_MAXARGS]; /* iterators */ +} PyArrayMultiIterObject; + +#define _PyMIT(m) ((PyArrayMultiIterObject *)(m)) +#define PyArray_MultiIter_RESET(multi) do { \ + int __npy_mi; \ + _PyMIT(multi)->index = 0; \ + for (__npy_mi=0; __npy_mi < _PyMIT(multi)->numiter; __npy_mi++) { \ + PyArray_ITER_RESET(_PyMIT(multi)->iters[__npy_mi]); \ + } \ +} while (0) + +#define PyArray_MultiIter_NEXT(multi) do { \ + int __npy_mi; \ + _PyMIT(multi)->index++; \ + for (__npy_mi=0; __npy_mi < _PyMIT(multi)->numiter; __npy_mi++) { \ + PyArray_ITER_NEXT(_PyMIT(multi)->iters[__npy_mi]); \ + } \ +} while (0) + +#define PyArray_MultiIter_GOTO(multi, dest) do { \ + int __npy_mi; \ + for (__npy_mi=0; __npy_mi < _PyMIT(multi)->numiter; __npy_mi++) { \ + PyArray_ITER_GOTO(_PyMIT(multi)->iters[__npy_mi], dest); \ + } \ + _PyMIT(multi)->index = _PyMIT(multi)->iters[0]->index; \ +} while (0) + +#define PyArray_MultiIter_GOTO1D(multi, ind) do { \ + int __npy_mi; \ + for (__npy_mi=0; __npy_mi < _PyMIT(multi)->numiter; __npy_mi++) { \ + PyArray_ITER_GOTO1D(_PyMIT(multi)->iters[__npy_mi], ind); \ + } \ + _PyMIT(multi)->index = _PyMIT(multi)->iters[0]->index; \ +} while (0) + +#define PyArray_MultiIter_DATA(multi, i) \ + ((void *)(_PyMIT(multi)->iters[i]->dataptr)) + +#define PyArray_MultiIter_NEXTi(multi, i) \ + PyArray_ITER_NEXT(_PyMIT(multi)->iters[i]) + +#define PyArray_MultiIter_NOTDONE(multi) \ + (_PyMIT(multi)->index < _PyMIT(multi)->size) + +/* Store the information needed for fancy-indexing over an array */ + +typedef struct { + PyObject_HEAD + /* + * Multi-iterator portion --- needs to be present in this + * order to work with PyArray_Broadcast + */ + + int numiter; /* number of index-array + iterators */ + npy_intp size; /* size of broadcasted + result */ + npy_intp index; /* current index */ + int nd; /* number of dims */ + npy_intp dimensions[NPY_MAXDIMS]; /* dimensions */ + PyArrayIterObject *iters[NPY_MAXDIMS]; /* index object + iterators */ + PyArrayIterObject *ait; /* flat Iterator for + underlying array */ + + /* flat iterator for subspace (when numiter < nd) */ + PyArrayIterObject *subspace; + + /* + * if subspace iteration, then this is the array of axes in + * the underlying array represented by the index objects + */ + int iteraxes[NPY_MAXDIMS]; + /* + * if subspace iteration, the these are the coordinates to the + * start of the subspace. + */ + npy_intp bscoord[NPY_MAXDIMS]; + + PyObject *indexobj; /* creating obj */ + int consec; + char *dataptr; + +} PyArrayMapIterObject; + +enum { + NPY_NEIGHBORHOOD_ITER_ZERO_PADDING, + NPY_NEIGHBORHOOD_ITER_ONE_PADDING, + NPY_NEIGHBORHOOD_ITER_CONSTANT_PADDING, + NPY_NEIGHBORHOOD_ITER_CIRCULAR_PADDING, + NPY_NEIGHBORHOOD_ITER_MIRROR_PADDING +}; + +typedef struct { + PyObject_HEAD + + /* + * PyArrayIterObject part: keep this in this exact order + */ + int nd_m1; /* number of dimensions - 1 */ + npy_intp index, size; + npy_intp coordinates[NPY_MAXDIMS];/* N-dimensional loop */ + npy_intp dims_m1[NPY_MAXDIMS]; /* ao->dimensions - 1 */ + npy_intp strides[NPY_MAXDIMS]; /* ao->strides or fake */ + npy_intp backstrides[NPY_MAXDIMS];/* how far to jump back */ + npy_intp factors[NPY_MAXDIMS]; /* shape factors */ + PyArrayObject *ao; + char *dataptr; /* pointer to current item*/ + npy_bool contiguous; + + npy_intp bounds[NPY_MAXDIMS][2]; + npy_intp limits[NPY_MAXDIMS][2]; + npy_intp limits_sizes[NPY_MAXDIMS]; + npy_iter_get_dataptr_t translate; + + /* + * New members + */ + npy_intp nd; + + /* Dimensions is the dimension of the array */ + npy_intp dimensions[NPY_MAXDIMS]; + + /* + * Neighborhood points coordinates are computed relatively to the + * point pointed by _internal_iter + */ + PyArrayIterObject* _internal_iter; + /* + * To keep a reference to the representation of the constant value + * for constant padding + */ + char* constant; + + int mode; +} PyArrayNeighborhoodIterObject; + +/* + * Neighborhood iterator API + */ + +/* General: those work for any mode */ +static NPY_INLINE int +PyArrayNeighborhoodIter_Reset(PyArrayNeighborhoodIterObject* iter); +static NPY_INLINE int +PyArrayNeighborhoodIter_Next(PyArrayNeighborhoodIterObject* iter); +#if 0 +static NPY_INLINE int +PyArrayNeighborhoodIter_Next2D(PyArrayNeighborhoodIterObject* iter); +#endif + +/* + * Include inline implementations - functions defined there are not + * considered public API + */ +#define _NPY_INCLUDE_NEIGHBORHOOD_IMP +#include "_neighborhood_iterator_imp.h" +#undef _NPY_INCLUDE_NEIGHBORHOOD_IMP + +/* The default array type */ +#define NPY_DEFAULT_TYPE NPY_DOUBLE + +/* + * All sorts of useful ways to look into a PyArrayObject. It is recommended + * to use PyArrayObject * objects instead of always casting from PyObject *, + * for improved type checking. + * + * In many cases here the macro versions of the accessors are deprecated, + * but can't be immediately changed to inline functions because the + * preexisting macros accept PyObject * and do automatic casts. Inline + * functions accepting PyArrayObject * provides for some compile-time + * checking of correctness when working with these objects in C. + */ + +#define PyArray_ISONESEGMENT(m) (PyArray_NDIM(m) == 0 || \ + PyArray_CHKFLAGS(m, NPY_ARRAY_C_CONTIGUOUS) || \ + PyArray_CHKFLAGS(m, NPY_ARRAY_F_CONTIGUOUS)) + +#define PyArray_ISFORTRAN(m) (PyArray_CHKFLAGS(m, NPY_ARRAY_F_CONTIGUOUS) && \ + (PyArray_NDIM(m) > 1)) + +#define PyArray_FORTRAN_IF(m) ((PyArray_CHKFLAGS(m, NPY_ARRAY_F_CONTIGUOUS) ? \ + NPY_ARRAY_F_CONTIGUOUS : 0)) + +#if (defined(NPY_NO_DEPRECATED_API) && (NPY_API_VERSION <= NPY_NO_DEPRECATED_API)) +/* + * Changing access macros into functions, to allow for future hiding + * of the internal memory layout. This later hiding will allow the 2.x series + * to change the internal representation of arrays without affecting + * ABI compatibility. + */ + +static NPY_INLINE int +PyArray_NDIM(const PyArrayObject *arr) +{ + return ((PyArrayObject_fields *)arr)->nd; +} + +static NPY_INLINE void * +PyArray_DATA(PyArrayObject *arr) +{ + return ((PyArrayObject_fields *)arr)->data; +} + +static NPY_INLINE char * +PyArray_BYTES(PyArrayObject *arr) +{ + return ((PyArrayObject_fields *)arr)->data; +} + +static NPY_INLINE npy_intp * +PyArray_DIMS(PyArrayObject *arr) +{ + return ((PyArrayObject_fields *)arr)->dimensions; +} + +static NPY_INLINE npy_intp * +PyArray_STRIDES(PyArrayObject *arr) +{ + return ((PyArrayObject_fields *)arr)->strides; +} + +static NPY_INLINE npy_intp +PyArray_DIM(const PyArrayObject *arr, int idim) +{ + return ((PyArrayObject_fields *)arr)->dimensions[idim]; +} + +static NPY_INLINE npy_intp +PyArray_STRIDE(const PyArrayObject *arr, int istride) +{ + return ((PyArrayObject_fields *)arr)->strides[istride]; +} + +static NPY_INLINE PyObject * +PyArray_BASE(PyArrayObject *arr) +{ + return ((PyArrayObject_fields *)arr)->base; +} + +static NPY_INLINE PyArray_Descr * +PyArray_DESCR(PyArrayObject *arr) +{ + return ((PyArrayObject_fields *)arr)->descr; +} + +static NPY_INLINE int +PyArray_FLAGS(const PyArrayObject *arr) +{ + return ((PyArrayObject_fields *)arr)->flags; +} + +static NPY_INLINE npy_intp +PyArray_ITEMSIZE(const PyArrayObject *arr) +{ + return ((PyArrayObject_fields *)arr)->descr->elsize; +} + +static NPY_INLINE int +PyArray_TYPE(const PyArrayObject *arr) +{ + return ((PyArrayObject_fields *)arr)->descr->type_num; +} + +static NPY_INLINE int +PyArray_CHKFLAGS(const PyArrayObject *arr, int flags) +{ + return (PyArray_FLAGS(arr) & flags) == flags; +} + +static NPY_INLINE PyObject * +PyArray_GETITEM(const PyArrayObject *arr, const char *itemptr) +{ + return ((PyArrayObject_fields *)arr)->descr->f->getitem( + (void *)itemptr, (PyArrayObject *)arr); +} + +static NPY_INLINE int +PyArray_SETITEM(PyArrayObject *arr, char *itemptr, PyObject *v) +{ + return ((PyArrayObject_fields *)arr)->descr->f->setitem( + v, itemptr, arr); +} + +#else + +/* These macros are deprecated as of NumPy 1.7. */ +#define PyArray_NDIM(obj) (((PyArrayObject_fields *)(obj))->nd) +#define PyArray_BYTES(obj) (((PyArrayObject_fields *)(obj))->data) +#define PyArray_DATA(obj) ((void *)((PyArrayObject_fields *)(obj))->data) +#define PyArray_DIMS(obj) (((PyArrayObject_fields *)(obj))->dimensions) +#define PyArray_STRIDES(obj) (((PyArrayObject_fields *)(obj))->strides) +#define PyArray_DIM(obj,n) (PyArray_DIMS(obj)[n]) +#define PyArray_STRIDE(obj,n) (PyArray_STRIDES(obj)[n]) +#define PyArray_BASE(obj) (((PyArrayObject_fields *)(obj))->base) +#define PyArray_DESCR(obj) (((PyArrayObject_fields *)(obj))->descr) +#define PyArray_FLAGS(obj) (((PyArrayObject_fields *)(obj))->flags) +#define PyArray_CHKFLAGS(m, FLAGS) \ + ((((PyArrayObject_fields *)(m))->flags & (FLAGS)) == (FLAGS)) +#define PyArray_ITEMSIZE(obj) \ + (((PyArrayObject_fields *)(obj))->descr->elsize) +#define PyArray_TYPE(obj) \ + (((PyArrayObject_fields *)(obj))->descr->type_num) +#define PyArray_GETITEM(obj,itemptr) \ + PyArray_DESCR(obj)->f->getitem((char *)(itemptr), \ + (PyArrayObject *)(obj)) + +#define PyArray_SETITEM(obj,itemptr,v) \ + PyArray_DESCR(obj)->f->setitem((PyObject *)(v), \ + (char *)(itemptr), \ + (PyArrayObject *)(obj)) +#endif + +static NPY_INLINE PyArray_Descr * +PyArray_DTYPE(PyArrayObject *arr) +{ + return ((PyArrayObject_fields *)arr)->descr; +} + +static NPY_INLINE npy_intp * +PyArray_SHAPE(PyArrayObject *arr) +{ + return ((PyArrayObject_fields *)arr)->dimensions; +} + +/* + * Enables the specified array flags. Does no checking, + * assumes you know what you're doing. + */ +static NPY_INLINE void +PyArray_ENABLEFLAGS(PyArrayObject *arr, int flags) +{ + ((PyArrayObject_fields *)arr)->flags |= flags; +} + +/* + * Clears the specified array flags. Does no checking, + * assumes you know what you're doing. + */ +static NPY_INLINE void +PyArray_CLEARFLAGS(PyArrayObject *arr, int flags) +{ + ((PyArrayObject_fields *)arr)->flags &= ~flags; +} + +#define PyTypeNum_ISBOOL(type) ((type) == NPY_BOOL) + +#define PyTypeNum_ISUNSIGNED(type) (((type) == NPY_UBYTE) || \ + ((type) == NPY_USHORT) || \ + ((type) == NPY_UINT) || \ + ((type) == NPY_ULONG) || \ + ((type) == NPY_ULONGLONG)) + +#define PyTypeNum_ISSIGNED(type) (((type) == NPY_BYTE) || \ + ((type) == NPY_SHORT) || \ + ((type) == NPY_INT) || \ + ((type) == NPY_LONG) || \ + ((type) == NPY_LONGLONG)) + +#define PyTypeNum_ISINTEGER(type) (((type) >= NPY_BYTE) && \ + ((type) <= NPY_ULONGLONG)) + +#define PyTypeNum_ISFLOAT(type) ((((type) >= NPY_FLOAT) && \ + ((type) <= NPY_LONGDOUBLE)) || \ + ((type) == NPY_HALF)) + +#define PyTypeNum_ISNUMBER(type) (((type) <= NPY_CLONGDOUBLE) || \ + ((type) == NPY_HALF)) + +#define PyTypeNum_ISSTRING(type) (((type) == NPY_STRING) || \ + ((type) == NPY_UNICODE)) + +#define PyTypeNum_ISCOMPLEX(type) (((type) >= NPY_CFLOAT) && \ + ((type) <= NPY_CLONGDOUBLE)) + +#define PyTypeNum_ISPYTHON(type) (((type) == NPY_LONG) || \ + ((type) == NPY_DOUBLE) || \ + ((type) == NPY_CDOUBLE) || \ + ((type) == NPY_BOOL) || \ + ((type) == NPY_OBJECT )) + +#define PyTypeNum_ISFLEXIBLE(type) (((type) >=NPY_STRING) && \ + ((type) <=NPY_VOID)) + +#define PyTypeNum_ISDATETIME(type) (((type) >=NPY_DATETIME) && \ + ((type) <=NPY_TIMEDELTA)) + +#define PyTypeNum_ISUSERDEF(type) (((type) >= NPY_USERDEF) && \ + ((type) < NPY_USERDEF+ \ + NPY_NUMUSERTYPES)) + +#define PyTypeNum_ISEXTENDED(type) (PyTypeNum_ISFLEXIBLE(type) || \ + PyTypeNum_ISUSERDEF(type)) + +#define PyTypeNum_ISOBJECT(type) ((type) == NPY_OBJECT) + + +#define PyDataType_ISBOOL(obj) PyTypeNum_ISBOOL(_PyADt(obj)) +#define PyDataType_ISUNSIGNED(obj) PyTypeNum_ISUNSIGNED(((PyArray_Descr*)(obj))->type_num) +#define PyDataType_ISSIGNED(obj) PyTypeNum_ISSIGNED(((PyArray_Descr*)(obj))->type_num) +#define PyDataType_ISINTEGER(obj) PyTypeNum_ISINTEGER(((PyArray_Descr*)(obj))->type_num ) +#define PyDataType_ISFLOAT(obj) PyTypeNum_ISFLOAT(((PyArray_Descr*)(obj))->type_num) +#define PyDataType_ISNUMBER(obj) PyTypeNum_ISNUMBER(((PyArray_Descr*)(obj))->type_num) +#define PyDataType_ISSTRING(obj) PyTypeNum_ISSTRING(((PyArray_Descr*)(obj))->type_num) +#define PyDataType_ISCOMPLEX(obj) PyTypeNum_ISCOMPLEX(((PyArray_Descr*)(obj))->type_num) +#define PyDataType_ISPYTHON(obj) PyTypeNum_ISPYTHON(((PyArray_Descr*)(obj))->type_num) +#define PyDataType_ISFLEXIBLE(obj) PyTypeNum_ISFLEXIBLE(((PyArray_Descr*)(obj))->type_num) +#define PyDataType_ISDATETIME(obj) PyTypeNum_ISDATETIME(((PyArray_Descr*)(obj))->type_num) +#define PyDataType_ISUSERDEF(obj) PyTypeNum_ISUSERDEF(((PyArray_Descr*)(obj))->type_num) +#define PyDataType_ISEXTENDED(obj) PyTypeNum_ISEXTENDED(((PyArray_Descr*)(obj))->type_num) +#define PyDataType_ISOBJECT(obj) PyTypeNum_ISOBJECT(((PyArray_Descr*)(obj))->type_num) +#define PyDataType_HASFIELDS(obj) (((PyArray_Descr *)(obj))->names != NULL) +#define PyDataType_HASSUBARRAY(dtype) ((dtype)->subarray != NULL) + +#define PyArray_ISBOOL(obj) PyTypeNum_ISBOOL(PyArray_TYPE(obj)) +#define PyArray_ISUNSIGNED(obj) PyTypeNum_ISUNSIGNED(PyArray_TYPE(obj)) +#define PyArray_ISSIGNED(obj) PyTypeNum_ISSIGNED(PyArray_TYPE(obj)) +#define PyArray_ISINTEGER(obj) PyTypeNum_ISINTEGER(PyArray_TYPE(obj)) +#define PyArray_ISFLOAT(obj) PyTypeNum_ISFLOAT(PyArray_TYPE(obj)) +#define PyArray_ISNUMBER(obj) PyTypeNum_ISNUMBER(PyArray_TYPE(obj)) +#define PyArray_ISSTRING(obj) PyTypeNum_ISSTRING(PyArray_TYPE(obj)) +#define PyArray_ISCOMPLEX(obj) PyTypeNum_ISCOMPLEX(PyArray_TYPE(obj)) +#define PyArray_ISPYTHON(obj) PyTypeNum_ISPYTHON(PyArray_TYPE(obj)) +#define PyArray_ISFLEXIBLE(obj) PyTypeNum_ISFLEXIBLE(PyArray_TYPE(obj)) +#define PyArray_ISDATETIME(obj) PyTypeNum_ISDATETIME(PyArray_TYPE(obj)) +#define PyArray_ISUSERDEF(obj) PyTypeNum_ISUSERDEF(PyArray_TYPE(obj)) +#define PyArray_ISEXTENDED(obj) PyTypeNum_ISEXTENDED(PyArray_TYPE(obj)) +#define PyArray_ISOBJECT(obj) PyTypeNum_ISOBJECT(PyArray_TYPE(obj)) +#define PyArray_HASFIELDS(obj) PyDataType_HASFIELDS(PyArray_DESCR(obj)) + + /* + * FIXME: This should check for a flag on the data-type that + * states whether or not it is variable length. Because the + * ISFLEXIBLE check is hard-coded to the built-in data-types. + */ +#define PyArray_ISVARIABLE(obj) PyTypeNum_ISFLEXIBLE(PyArray_TYPE(obj)) + +#define PyArray_SAFEALIGNEDCOPY(obj) (PyArray_ISALIGNED(obj) && !PyArray_ISVARIABLE(obj)) + + +#define NPY_LITTLE '<' +#define NPY_BIG '>' +#define NPY_NATIVE '=' +#define NPY_SWAP 's' +#define NPY_IGNORE '|' + +#if NPY_BYTE_ORDER == NPY_BIG_ENDIAN +#define NPY_NATBYTE NPY_BIG +#define NPY_OPPBYTE NPY_LITTLE +#else +#define NPY_NATBYTE NPY_LITTLE +#define NPY_OPPBYTE NPY_BIG +#endif + +#define PyArray_ISNBO(arg) ((arg) != NPY_OPPBYTE) +#define PyArray_IsNativeByteOrder PyArray_ISNBO +#define PyArray_ISNOTSWAPPED(m) PyArray_ISNBO(PyArray_DESCR(m)->byteorder) +#define PyArray_ISBYTESWAPPED(m) (!PyArray_ISNOTSWAPPED(m)) + +#define PyArray_FLAGSWAP(m, flags) (PyArray_CHKFLAGS(m, flags) && \ + PyArray_ISNOTSWAPPED(m)) + +#define PyArray_ISCARRAY(m) PyArray_FLAGSWAP(m, NPY_ARRAY_CARRAY) +#define PyArray_ISCARRAY_RO(m) PyArray_FLAGSWAP(m, NPY_ARRAY_CARRAY_RO) +#define PyArray_ISFARRAY(m) PyArray_FLAGSWAP(m, NPY_ARRAY_FARRAY) +#define PyArray_ISFARRAY_RO(m) PyArray_FLAGSWAP(m, NPY_ARRAY_FARRAY_RO) +#define PyArray_ISBEHAVED(m) PyArray_FLAGSWAP(m, NPY_ARRAY_BEHAVED) +#define PyArray_ISBEHAVED_RO(m) PyArray_FLAGSWAP(m, NPY_ARRAY_ALIGNED) + + +#define PyDataType_ISNOTSWAPPED(d) PyArray_ISNBO(((PyArray_Descr *)(d))->byteorder) +#define PyDataType_ISBYTESWAPPED(d) (!PyDataType_ISNOTSWAPPED(d)) + +/************************************************************ + * A struct used by PyArray_CreateSortedStridePerm, new in 1.7. + ************************************************************/ + +typedef struct { + npy_intp perm, stride; +} npy_stride_sort_item; + +/************************************************************ + * This is the form of the struct that's returned pointed by the + * PyCObject attribute of an array __array_struct__. See + * http://docs.scipy.org/doc/numpy/reference/arrays.interface.html for the full + * documentation. + ************************************************************/ +typedef struct { + int two; /* + * contains the integer 2 as a sanity + * check + */ + + int nd; /* number of dimensions */ + + char typekind; /* + * kind in array --- character code of + * typestr + */ + + int itemsize; /* size of each element */ + + int flags; /* + * how should be data interpreted. Valid + * flags are CONTIGUOUS (1), F_CONTIGUOUS (2), + * ALIGNED (0x100), NOTSWAPPED (0x200), and + * WRITEABLE (0x400). ARR_HAS_DESCR (0x800) + * states that arrdescr field is present in + * structure + */ + + npy_intp *shape; /* + * A length-nd array of shape + * information + */ + + npy_intp *strides; /* A length-nd array of stride information */ + + void *data; /* A pointer to the first element of the array */ + + PyObject *descr; /* + * A list of fields or NULL (ignored if flags + * does not have ARR_HAS_DESCR flag set) + */ +} PyArrayInterface; + +/* + * This is a function for hooking into the PyDataMem_NEW/FREE/RENEW functions. + * See the documentation for PyDataMem_SetEventHook. + */ +typedef void (PyDataMem_EventHookFunc)(void *inp, void *outp, size_t size, + void *user_data); + +#if !(defined(NPY_NO_DEPRECATED_API) && (NPY_API_VERSION <= NPY_NO_DEPRECATED_API)) +#include "npy_deprecated_api.h" +#endif + +#endif /* NPY_ARRAYTYPES_H */ diff --git a/data_tooling/pii_processing/include/numpy/noprefix.h b/data_tooling/pii_processing/include/numpy/noprefix.h new file mode 100644 index 0000000..b3e5748 --- /dev/null +++ b/data_tooling/pii_processing/include/numpy/noprefix.h @@ -0,0 +1,209 @@ +#ifndef NPY_NOPREFIX_H +#define NPY_NOPREFIX_H + +/* + * You can directly include noprefix.h as a backward + * compatibility measure + */ +#ifndef NPY_NO_PREFIX +#include "ndarrayobject.h" +#include "npy_interrupt.h" +#endif + +#define SIGSETJMP NPY_SIGSETJMP +#define SIGLONGJMP NPY_SIGLONGJMP +#define SIGJMP_BUF NPY_SIGJMP_BUF + +#define MAX_DIMS NPY_MAXDIMS + +#define longlong npy_longlong +#define ulonglong npy_ulonglong +#define Bool npy_bool +#define longdouble npy_longdouble +#define byte npy_byte + +#ifndef _BSD_SOURCE +#define ushort npy_ushort +#define uint npy_uint +#define ulong npy_ulong +#endif + +#define ubyte npy_ubyte +#define ushort npy_ushort +#define uint npy_uint +#define ulong npy_ulong +#define cfloat npy_cfloat +#define cdouble npy_cdouble +#define clongdouble npy_clongdouble +#define Int8 npy_int8 +#define UInt8 npy_uint8 +#define Int16 npy_int16 +#define UInt16 npy_uint16 +#define Int32 npy_int32 +#define UInt32 npy_uint32 +#define Int64 npy_int64 +#define UInt64 npy_uint64 +#define Int128 npy_int128 +#define UInt128 npy_uint128 +#define Int256 npy_int256 +#define UInt256 npy_uint256 +#define Float16 npy_float16 +#define Complex32 npy_complex32 +#define Float32 npy_float32 +#define Complex64 npy_complex64 +#define Float64 npy_float64 +#define Complex128 npy_complex128 +#define Float80 npy_float80 +#define Complex160 npy_complex160 +#define Float96 npy_float96 +#define Complex192 npy_complex192 +#define Float128 npy_float128 +#define Complex256 npy_complex256 +#define intp npy_intp +#define uintp npy_uintp +#define datetime npy_datetime +#define timedelta npy_timedelta + +#define SIZEOF_INTP NPY_SIZEOF_INTP +#define SIZEOF_UINTP NPY_SIZEOF_UINTP +#define SIZEOF_DATETIME NPY_SIZEOF_DATETIME +#define SIZEOF_TIMEDELTA NPY_SIZEOF_TIMEDELTA + +#define LONGLONG_FMT NPY_LONGLONG_FMT +#define ULONGLONG_FMT NPY_ULONGLONG_FMT +#define LONGLONG_SUFFIX NPY_LONGLONG_SUFFIX +#define ULONGLONG_SUFFIX NPY_ULONGLONG_SUFFIX + +#define MAX_INT8 127 +#define MIN_INT8 -128 +#define MAX_UINT8 255 +#define MAX_INT16 32767 +#define MIN_INT16 -32768 +#define MAX_UINT16 65535 +#define MAX_INT32 2147483647 +#define MIN_INT32 (-MAX_INT32 - 1) +#define MAX_UINT32 4294967295U +#define MAX_INT64 LONGLONG_SUFFIX(9223372036854775807) +#define MIN_INT64 (-MAX_INT64 - LONGLONG_SUFFIX(1)) +#define MAX_UINT64 ULONGLONG_SUFFIX(18446744073709551615) +#define MAX_INT128 LONGLONG_SUFFIX(85070591730234615865843651857942052864) +#define MIN_INT128 (-MAX_INT128 - LONGLONG_SUFFIX(1)) +#define MAX_UINT128 ULONGLONG_SUFFIX(170141183460469231731687303715884105728) +#define MAX_INT256 LONGLONG_SUFFIX(57896044618658097711785492504343953926634992332820282019728792003956564819967) +#define MIN_INT256 (-MAX_INT256 - LONGLONG_SUFFIX(1)) +#define MAX_UINT256 ULONGLONG_SUFFIX(115792089237316195423570985008687907853269984665640564039457584007913129639935) + +#define MAX_BYTE NPY_MAX_BYTE +#define MIN_BYTE NPY_MIN_BYTE +#define MAX_UBYTE NPY_MAX_UBYTE +#define MAX_SHORT NPY_MAX_SHORT +#define MIN_SHORT NPY_MIN_SHORT +#define MAX_USHORT NPY_MAX_USHORT +#define MAX_INT NPY_MAX_INT +#define MIN_INT NPY_MIN_INT +#define MAX_UINT NPY_MAX_UINT +#define MAX_LONG NPY_MAX_LONG +#define MIN_LONG NPY_MIN_LONG +#define MAX_ULONG NPY_MAX_ULONG +#define MAX_LONGLONG NPY_MAX_LONGLONG +#define MIN_LONGLONG NPY_MIN_LONGLONG +#define MAX_ULONGLONG NPY_MAX_ULONGLONG +#define MIN_DATETIME NPY_MIN_DATETIME +#define MAX_DATETIME NPY_MAX_DATETIME +#define MIN_TIMEDELTA NPY_MIN_TIMEDELTA +#define MAX_TIMEDELTA NPY_MAX_TIMEDELTA + +#define SIZEOF_LONGDOUBLE NPY_SIZEOF_LONGDOUBLE +#define SIZEOF_LONGLONG NPY_SIZEOF_LONGLONG +#define SIZEOF_HALF NPY_SIZEOF_HALF +#define BITSOF_BOOL NPY_BITSOF_BOOL +#define BITSOF_CHAR NPY_BITSOF_CHAR +#define BITSOF_SHORT NPY_BITSOF_SHORT +#define BITSOF_INT NPY_BITSOF_INT +#define BITSOF_LONG NPY_BITSOF_LONG +#define BITSOF_LONGLONG NPY_BITSOF_LONGLONG +#define BITSOF_HALF NPY_BITSOF_HALF +#define BITSOF_FLOAT NPY_BITSOF_FLOAT +#define BITSOF_DOUBLE NPY_BITSOF_DOUBLE +#define BITSOF_LONGDOUBLE NPY_BITSOF_LONGDOUBLE +#define BITSOF_DATETIME NPY_BITSOF_DATETIME +#define BITSOF_TIMEDELTA NPY_BITSOF_TIMEDELTA + +#define _pya_malloc PyArray_malloc +#define _pya_free PyArray_free +#define _pya_realloc PyArray_realloc + +#define BEGIN_THREADS_DEF NPY_BEGIN_THREADS_DEF +#define BEGIN_THREADS NPY_BEGIN_THREADS +#define END_THREADS NPY_END_THREADS +#define ALLOW_C_API_DEF NPY_ALLOW_C_API_DEF +#define ALLOW_C_API NPY_ALLOW_C_API +#define DISABLE_C_API NPY_DISABLE_C_API + +#define PY_FAIL NPY_FAIL +#define PY_SUCCEED NPY_SUCCEED + +#ifndef TRUE +#define TRUE NPY_TRUE +#endif + +#ifndef FALSE +#define FALSE NPY_FALSE +#endif + +#define LONGDOUBLE_FMT NPY_LONGDOUBLE_FMT + +#define CONTIGUOUS NPY_CONTIGUOUS +#define C_CONTIGUOUS NPY_C_CONTIGUOUS +#define FORTRAN NPY_FORTRAN +#define F_CONTIGUOUS NPY_F_CONTIGUOUS +#define OWNDATA NPY_OWNDATA +#define FORCECAST NPY_FORCECAST +#define ENSURECOPY NPY_ENSURECOPY +#define ENSUREARRAY NPY_ENSUREARRAY +#define ELEMENTSTRIDES NPY_ELEMENTSTRIDES +#define ALIGNED NPY_ALIGNED +#define NOTSWAPPED NPY_NOTSWAPPED +#define WRITEABLE NPY_WRITEABLE +#define UPDATEIFCOPY NPY_UPDATEIFCOPY +#define ARR_HAS_DESCR NPY_ARR_HAS_DESCR +#define BEHAVED NPY_BEHAVED +#define BEHAVED_NS NPY_BEHAVED_NS +#define CARRAY NPY_CARRAY +#define CARRAY_RO NPY_CARRAY_RO +#define FARRAY NPY_FARRAY +#define FARRAY_RO NPY_FARRAY_RO +#define DEFAULT NPY_DEFAULT +#define IN_ARRAY NPY_IN_ARRAY +#define OUT_ARRAY NPY_OUT_ARRAY +#define INOUT_ARRAY NPY_INOUT_ARRAY +#define IN_FARRAY NPY_IN_FARRAY +#define OUT_FARRAY NPY_OUT_FARRAY +#define INOUT_FARRAY NPY_INOUT_FARRAY +#define UPDATE_ALL NPY_UPDATE_ALL + +#define OWN_DATA NPY_OWNDATA +#define BEHAVED_FLAGS NPY_BEHAVED +#define BEHAVED_FLAGS_NS NPY_BEHAVED_NS +#define CARRAY_FLAGS_RO NPY_CARRAY_RO +#define CARRAY_FLAGS NPY_CARRAY +#define FARRAY_FLAGS NPY_FARRAY +#define FARRAY_FLAGS_RO NPY_FARRAY_RO +#define DEFAULT_FLAGS NPY_DEFAULT +#define UPDATE_ALL_FLAGS NPY_UPDATE_ALL_FLAGS + +#ifndef MIN +#define MIN PyArray_MIN +#endif +#ifndef MAX +#define MAX PyArray_MAX +#endif +#define MAX_INTP NPY_MAX_INTP +#define MIN_INTP NPY_MIN_INTP +#define MAX_UINTP NPY_MAX_UINTP +#define INTP_FMT NPY_INTP_FMT + +#define REFCOUNT PyArray_REFCOUNT +#define MAX_ELSIZE NPY_MAX_ELSIZE + +#endif diff --git a/data_tooling/pii_processing/include/numpy/npy_3kcompat.h b/data_tooling/pii_processing/include/numpy/npy_3kcompat.h new file mode 100644 index 0000000..d0cd9ac --- /dev/null +++ b/data_tooling/pii_processing/include/numpy/npy_3kcompat.h @@ -0,0 +1,417 @@ +/* + * This is a convenience header file providing compatibility utilities + * for supporting Python 2 and Python 3 in the same code base. + * + * If you want to use this for your own projects, it's recommended to make a + * copy of it. Although the stuff below is unlikely to change, we don't provide + * strong backwards compatibility guarantees at the moment. + */ + +#ifndef _NPY_3KCOMPAT_H_ +#define _NPY_3KCOMPAT_H_ + +#include +#include + +#if PY_VERSION_HEX >= 0x03000000 +#ifndef NPY_PY3K +#define NPY_PY3K 1 +#endif +#endif + +#include "numpy/npy_common.h" +#include "numpy/ndarrayobject.h" + +#ifdef __cplusplus +extern "C" { +#endif + +/* + * PyInt -> PyLong + */ + +#if defined(NPY_PY3K) +/* Return True only if the long fits in a C long */ +static NPY_INLINE int PyInt_Check(PyObject *op) { + int overflow = 0; + if (!PyLong_Check(op)) { + return 0; + } + PyLong_AsLongAndOverflow(op, &overflow); + return (overflow == 0); +} + +#define PyInt_FromLong PyLong_FromLong +#define PyInt_AsLong PyLong_AsLong +#define PyInt_AS_LONG PyLong_AsLong +#define PyInt_AsSsize_t PyLong_AsSsize_t + +/* NOTE: + * + * Since the PyLong type is very different from the fixed-range PyInt, + * we don't define PyInt_Type -> PyLong_Type. + */ +#endif /* NPY_PY3K */ + +/* + * PyString -> PyBytes + */ + +#if defined(NPY_PY3K) + +#define PyString_Type PyBytes_Type +#define PyString_Check PyBytes_Check +#define PyStringObject PyBytesObject +#define PyString_FromString PyBytes_FromString +#define PyString_FromStringAndSize PyBytes_FromStringAndSize +#define PyString_AS_STRING PyBytes_AS_STRING +#define PyString_AsStringAndSize PyBytes_AsStringAndSize +#define PyString_FromFormat PyBytes_FromFormat +#define PyString_Concat PyBytes_Concat +#define PyString_ConcatAndDel PyBytes_ConcatAndDel +#define PyString_AsString PyBytes_AsString +#define PyString_GET_SIZE PyBytes_GET_SIZE +#define PyString_Size PyBytes_Size + +#define PyUString_Type PyUnicode_Type +#define PyUString_Check PyUnicode_Check +#define PyUStringObject PyUnicodeObject +#define PyUString_FromString PyUnicode_FromString +#define PyUString_FromStringAndSize PyUnicode_FromStringAndSize +#define PyUString_FromFormat PyUnicode_FromFormat +#define PyUString_Concat PyUnicode_Concat2 +#define PyUString_ConcatAndDel PyUnicode_ConcatAndDel +#define PyUString_GET_SIZE PyUnicode_GET_SIZE +#define PyUString_Size PyUnicode_Size +#define PyUString_InternFromString PyUnicode_InternFromString +#define PyUString_Format PyUnicode_Format + +#else + +#define PyBytes_Type PyString_Type +#define PyBytes_Check PyString_Check +#define PyBytesObject PyStringObject +#define PyBytes_FromString PyString_FromString +#define PyBytes_FromStringAndSize PyString_FromStringAndSize +#define PyBytes_AS_STRING PyString_AS_STRING +#define PyBytes_AsStringAndSize PyString_AsStringAndSize +#define PyBytes_FromFormat PyString_FromFormat +#define PyBytes_Concat PyString_Concat +#define PyBytes_ConcatAndDel PyString_ConcatAndDel +#define PyBytes_AsString PyString_AsString +#define PyBytes_GET_SIZE PyString_GET_SIZE +#define PyBytes_Size PyString_Size + +#define PyUString_Type PyString_Type +#define PyUString_Check PyString_Check +#define PyUStringObject PyStringObject +#define PyUString_FromString PyString_FromString +#define PyUString_FromStringAndSize PyString_FromStringAndSize +#define PyUString_FromFormat PyString_FromFormat +#define PyUString_Concat PyString_Concat +#define PyUString_ConcatAndDel PyString_ConcatAndDel +#define PyUString_GET_SIZE PyString_GET_SIZE +#define PyUString_Size PyString_Size +#define PyUString_InternFromString PyString_InternFromString +#define PyUString_Format PyString_Format + +#endif /* NPY_PY3K */ + + +static NPY_INLINE void +PyUnicode_ConcatAndDel(PyObject **left, PyObject *right) +{ + PyObject *newobj; + newobj = PyUnicode_Concat(*left, right); + Py_DECREF(*left); + Py_DECREF(right); + *left = newobj; +} + +static NPY_INLINE void +PyUnicode_Concat2(PyObject **left, PyObject *right) +{ + PyObject *newobj; + newobj = PyUnicode_Concat(*left, right); + Py_DECREF(*left); + *left = newobj; +} + +/* + * PyFile_* compatibility + */ +#if defined(NPY_PY3K) + +/* + * Get a FILE* handle to the file represented by the Python object + */ +static NPY_INLINE FILE* +npy_PyFile_Dup(PyObject *file, char *mode) +{ + int fd, fd2; + PyObject *ret, *os; + Py_ssize_t pos; + FILE *handle; + /* Flush first to ensure things end up in the file in the correct order */ + ret = PyObject_CallMethod(file, "flush", ""); + if (ret == NULL) { + return NULL; + } + Py_DECREF(ret); + fd = PyObject_AsFileDescriptor(file); + if (fd == -1) { + return NULL; + } + os = PyImport_ImportModule("os"); + if (os == NULL) { + return NULL; + } + ret = PyObject_CallMethod(os, "dup", "i", fd); + Py_DECREF(os); + if (ret == NULL) { + return NULL; + } + fd2 = PyNumber_AsSsize_t(ret, NULL); + Py_DECREF(ret); +#ifdef _WIN32 + handle = _fdopen(fd2, mode); +#else + handle = fdopen(fd2, mode); +#endif + if (handle == NULL) { + PyErr_SetString(PyExc_IOError, + "Getting a FILE* from a Python file object failed"); + } + ret = PyObject_CallMethod(file, "tell", ""); + if (ret == NULL) { + fclose(handle); + return NULL; + } + pos = PyNumber_AsSsize_t(ret, PyExc_OverflowError); + Py_DECREF(ret); + if (PyErr_Occurred()) { + fclose(handle); + return NULL; + } + npy_fseek(handle, pos, SEEK_SET); + return handle; +} + +/* + * Close the dup-ed file handle, and seek the Python one to the current position + */ +static NPY_INLINE int +npy_PyFile_DupClose(PyObject *file, FILE* handle) +{ + PyObject *ret; + Py_ssize_t position; + position = npy_ftell(handle); + fclose(handle); + + ret = PyObject_CallMethod(file, "seek", NPY_SSIZE_T_PYFMT "i", position, 0); + if (ret == NULL) { + return -1; + } + Py_DECREF(ret); + return 0; +} + +static NPY_INLINE int +npy_PyFile_Check(PyObject *file) +{ + int fd; + fd = PyObject_AsFileDescriptor(file); + if (fd == -1) { + PyErr_Clear(); + return 0; + } + return 1; +} + +#else + +#define npy_PyFile_Dup(file, mode) PyFile_AsFile(file) +#define npy_PyFile_DupClose(file, handle) (0) +#define npy_PyFile_Check PyFile_Check + +#endif + +static NPY_INLINE PyObject* +npy_PyFile_OpenFile(PyObject *filename, const char *mode) +{ + PyObject *open; + open = PyDict_GetItemString(PyEval_GetBuiltins(), "open"); + if (open == NULL) { + return NULL; + } + return PyObject_CallFunction(open, "Os", filename, mode); +} + +static NPY_INLINE int +npy_PyFile_CloseFile(PyObject *file) +{ + PyObject *ret; + + ret = PyObject_CallMethod(file, "close", NULL); + if (ret == NULL) { + return -1; + } + Py_DECREF(ret); + return 0; +} + +/* + * PyObject_Cmp + */ +#if defined(NPY_PY3K) +static NPY_INLINE int +PyObject_Cmp(PyObject *i1, PyObject *i2, int *cmp) +{ + int v; + v = PyObject_RichCompareBool(i1, i2, Py_LT); + if (v == 0) { + *cmp = -1; + return 1; + } + else if (v == -1) { + return -1; + } + + v = PyObject_RichCompareBool(i1, i2, Py_GT); + if (v == 0) { + *cmp = 1; + return 1; + } + else if (v == -1) { + return -1; + } + + v = PyObject_RichCompareBool(i1, i2, Py_EQ); + if (v == 0) { + *cmp = 0; + return 1; + } + else { + *cmp = 0; + return -1; + } +} +#endif + +/* + * PyCObject functions adapted to PyCapsules. + * + * The main job here is to get rid of the improved error handling + * of PyCapsules. It's a shame... + */ +#if PY_VERSION_HEX >= 0x03000000 + +static NPY_INLINE PyObject * +NpyCapsule_FromVoidPtr(void *ptr, void (*dtor)(PyObject *)) +{ + PyObject *ret = PyCapsule_New(ptr, NULL, dtor); + if (ret == NULL) { + PyErr_Clear(); + } + return ret; +} + +static NPY_INLINE PyObject * +NpyCapsule_FromVoidPtrAndDesc(void *ptr, void* context, void (*dtor)(PyObject *)) +{ + PyObject *ret = NpyCapsule_FromVoidPtr(ptr, dtor); + if (ret != NULL && PyCapsule_SetContext(ret, context) != 0) { + PyErr_Clear(); + Py_DECREF(ret); + ret = NULL; + } + return ret; +} + +static NPY_INLINE void * +NpyCapsule_AsVoidPtr(PyObject *obj) +{ + void *ret = PyCapsule_GetPointer(obj, NULL); + if (ret == NULL) { + PyErr_Clear(); + } + return ret; +} + +static NPY_INLINE void * +NpyCapsule_GetDesc(PyObject *obj) +{ + return PyCapsule_GetContext(obj); +} + +static NPY_INLINE int +NpyCapsule_Check(PyObject *ptr) +{ + return PyCapsule_CheckExact(ptr); +} + +static NPY_INLINE void +simple_capsule_dtor(PyObject *cap) +{ + PyArray_free(PyCapsule_GetPointer(cap, NULL)); +} + +#else + +static NPY_INLINE PyObject * +NpyCapsule_FromVoidPtr(void *ptr, void (*dtor)(void *)) +{ + return PyCObject_FromVoidPtr(ptr, dtor); +} + +static NPY_INLINE PyObject * +NpyCapsule_FromVoidPtrAndDesc(void *ptr, void* context, + void (*dtor)(void *, void *)) +{ + return PyCObject_FromVoidPtrAndDesc(ptr, context, dtor); +} + +static NPY_INLINE void * +NpyCapsule_AsVoidPtr(PyObject *ptr) +{ + return PyCObject_AsVoidPtr(ptr); +} + +static NPY_INLINE void * +NpyCapsule_GetDesc(PyObject *obj) +{ + return PyCObject_GetDesc(obj); +} + +static NPY_INLINE int +NpyCapsule_Check(PyObject *ptr) +{ + return PyCObject_Check(ptr); +} + +static NPY_INLINE void +simple_capsule_dtor(void *ptr) +{ + PyArray_free(ptr); +} + +#endif + +/* + * Hash value compatibility. + * As of Python 3.2 hash values are of type Py_hash_t. + * Previous versions use C long. + */ +#if PY_VERSION_HEX < 0x03020000 +typedef long npy_hash_t; +#define NPY_SIZEOF_HASH_T NPY_SIZEOF_LONG +#else +typedef Py_hash_t npy_hash_t; +#define NPY_SIZEOF_HASH_T NPY_SIZEOF_INTP +#endif + +#ifdef __cplusplus +} +#endif + +#endif /* _NPY_3KCOMPAT_H_ */ diff --git a/data_tooling/pii_processing/include/numpy/npy_common.h b/data_tooling/pii_processing/include/numpy/npy_common.h new file mode 100644 index 0000000..7fca7e2 --- /dev/null +++ b/data_tooling/pii_processing/include/numpy/npy_common.h @@ -0,0 +1,930 @@ +#ifndef _NPY_COMMON_H_ +#define _NPY_COMMON_H_ + +/* numpconfig.h is auto-generated */ +#include "numpyconfig.h" + +#if defined(_MSC_VER) + #define NPY_INLINE __inline +#elif defined(__GNUC__) + #if defined(__STRICT_ANSI__) + #define NPY_INLINE __inline__ + #else + #define NPY_INLINE inline + #endif +#else + #define NPY_INLINE +#endif + +/* Enable 64 bit file position support on win-amd64. Ticket #1660 */ +#if defined(_MSC_VER) && defined(_WIN64) && (_MSC_VER > 1400) + #define npy_fseek _fseeki64 + #define npy_ftell _ftelli64 +#else + #define npy_fseek fseek + #define npy_ftell ftell +#endif + +/* enums for detected endianness */ +enum { + NPY_CPU_UNKNOWN_ENDIAN, + NPY_CPU_LITTLE, + NPY_CPU_BIG +}; + +/* + * This is to typedef npy_intp to the appropriate pointer size for + * this platform. Py_intptr_t, Py_uintptr_t are defined in pyport.h. + */ +typedef Py_intptr_t npy_intp; +typedef Py_uintptr_t npy_uintp; +#define NPY_SIZEOF_CHAR 1 +#define NPY_SIZEOF_BYTE 1 +#define NPY_SIZEOF_INTP NPY_SIZEOF_PY_INTPTR_T +#define NPY_SIZEOF_UINTP NPY_SIZEOF_PY_INTPTR_T +#define NPY_SIZEOF_CFLOAT NPY_SIZEOF_COMPLEX_FLOAT +#define NPY_SIZEOF_CDOUBLE NPY_SIZEOF_COMPLEX_DOUBLE +#define NPY_SIZEOF_CLONGDOUBLE NPY_SIZEOF_COMPLEX_LONGDOUBLE + +#ifdef constchar +#undef constchar +#endif + +#if (PY_VERSION_HEX < 0x02050000) + #ifndef PY_SSIZE_T_MIN + typedef int Py_ssize_t; + #define PY_SSIZE_T_MAX INT_MAX + #define PY_SSIZE_T_MIN INT_MIN + #endif +#define NPY_SSIZE_T_PYFMT "i" +#define constchar const char +#else +#define NPY_SSIZE_T_PYFMT "n" +#define constchar char +#endif + +/* NPY_INTP_FMT Note: + * Unlike the other NPY_*_FMT macros which are used with + * PyOS_snprintf, NPY_INTP_FMT is used with PyErr_Format and + * PyString_Format. These functions use different formatting + * codes which are portably specified according to the Python + * documentation. See ticket #1795. + * + * On Windows x64, the LONGLONG formatter should be used, but + * in Python 2.6 the %lld formatter is not supported. In this + * case we work around the problem by using the %zd formatter. + */ +#if NPY_SIZEOF_PY_INTPTR_T == NPY_SIZEOF_INT + #define NPY_INTP NPY_INT + #define NPY_UINTP NPY_UINT + #define PyIntpArrType_Type PyIntArrType_Type + #define PyUIntpArrType_Type PyUIntArrType_Type + #define NPY_MAX_INTP NPY_MAX_INT + #define NPY_MIN_INTP NPY_MIN_INT + #define NPY_MAX_UINTP NPY_MAX_UINT + #define NPY_INTP_FMT "d" +#elif NPY_SIZEOF_PY_INTPTR_T == NPY_SIZEOF_LONG + #define NPY_INTP NPY_LONG + #define NPY_UINTP NPY_ULONG + #define PyIntpArrType_Type PyLongArrType_Type + #define PyUIntpArrType_Type PyULongArrType_Type + #define NPY_MAX_INTP NPY_MAX_LONG + #define NPY_MIN_INTP NPY_MIN_LONG + #define NPY_MAX_UINTP NPY_MAX_ULONG + #define NPY_INTP_FMT "ld" +#elif defined(PY_LONG_LONG) && (NPY_SIZEOF_PY_INTPTR_T == NPY_SIZEOF_LONGLONG) + #define NPY_INTP NPY_LONGLONG + #define NPY_UINTP NPY_ULONGLONG + #define PyIntpArrType_Type PyLongLongArrType_Type + #define PyUIntpArrType_Type PyULongLongArrType_Type + #define NPY_MAX_INTP NPY_MAX_LONGLONG + #define NPY_MIN_INTP NPY_MIN_LONGLONG + #define NPY_MAX_UINTP NPY_MAX_ULONGLONG + #if (PY_VERSION_HEX >= 0x02070000) + #define NPY_INTP_FMT "lld" + #else + #define NPY_INTP_FMT "zd" + #endif +#endif + +/* + * We can only use C99 formats for npy_int_p if it is the same as + * intp_t, hence the condition on HAVE_UNITPTR_T + */ +#if (NPY_USE_C99_FORMATS) == 1 \ + && (defined HAVE_UINTPTR_T) \ + && (defined HAVE_INTTYPES_H) + #include + #undef NPY_INTP_FMT + #define NPY_INTP_FMT PRIdPTR +#endif + + +/* + * Some platforms don't define bool, long long, or long double. + * Handle that here. + */ +#define NPY_BYTE_FMT "hhd" +#define NPY_UBYTE_FMT "hhu" +#define NPY_SHORT_FMT "hd" +#define NPY_USHORT_FMT "hu" +#define NPY_INT_FMT "d" +#define NPY_UINT_FMT "u" +#define NPY_LONG_FMT "ld" +#define NPY_ULONG_FMT "lu" +#define NPY_HALF_FMT "g" +#define NPY_FLOAT_FMT "g" +#define NPY_DOUBLE_FMT "g" + + +#ifdef PY_LONG_LONG +typedef PY_LONG_LONG npy_longlong; +typedef unsigned PY_LONG_LONG npy_ulonglong; +# ifdef _MSC_VER +# define NPY_LONGLONG_FMT "I64d" +# define NPY_ULONGLONG_FMT "I64u" +# elif defined(__APPLE__) || defined(__FreeBSD__) +/* "%Ld" only parses 4 bytes -- "L" is floating modifier on MacOS X/BSD */ +# define NPY_LONGLONG_FMT "lld" +# define NPY_ULONGLONG_FMT "llu" +/* + another possible variant -- *quad_t works on *BSD, but is deprecated: + #define LONGLONG_FMT "qd" + #define ULONGLONG_FMT "qu" +*/ +# else +# define NPY_LONGLONG_FMT "Ld" +# define NPY_ULONGLONG_FMT "Lu" +# endif +# ifdef _MSC_VER +# define NPY_LONGLONG_SUFFIX(x) (x##i64) +# define NPY_ULONGLONG_SUFFIX(x) (x##Ui64) +# else +# define NPY_LONGLONG_SUFFIX(x) (x##LL) +# define NPY_ULONGLONG_SUFFIX(x) (x##ULL) +# endif +#else +typedef long npy_longlong; +typedef unsigned long npy_ulonglong; +# define NPY_LONGLONG_SUFFIX(x) (x##L) +# define NPY_ULONGLONG_SUFFIX(x) (x##UL) +#endif + + +typedef unsigned char npy_bool; +#define NPY_FALSE 0 +#define NPY_TRUE 1 + + +#if NPY_SIZEOF_LONGDOUBLE == NPY_SIZEOF_DOUBLE + typedef double npy_longdouble; + #define NPY_LONGDOUBLE_FMT "g" +#else + typedef long double npy_longdouble; + #define NPY_LONGDOUBLE_FMT "Lg" +#endif + +#ifndef Py_USING_UNICODE +#error Must use Python with unicode enabled. +#endif + + +typedef signed char npy_byte; +typedef unsigned char npy_ubyte; +typedef unsigned short npy_ushort; +typedef unsigned int npy_uint; +typedef unsigned long npy_ulong; + +/* These are for completeness */ +typedef char npy_char; +typedef short npy_short; +typedef int npy_int; +typedef long npy_long; +typedef float npy_float; +typedef double npy_double; + +/* + * Disabling C99 complex usage: a lot of C code in numpy/scipy rely on being + * able to do .real/.imag. Will have to convert code first. + */ +#if 0 +#if defined(NPY_USE_C99_COMPLEX) && defined(NPY_HAVE_COMPLEX_DOUBLE) +typedef complex npy_cdouble; +#else +typedef struct { double real, imag; } npy_cdouble; +#endif + +#if defined(NPY_USE_C99_COMPLEX) && defined(NPY_HAVE_COMPLEX_FLOAT) +typedef complex float npy_cfloat; +#else +typedef struct { float real, imag; } npy_cfloat; +#endif + +#if defined(NPY_USE_C99_COMPLEX) && defined(NPY_HAVE_COMPLEX_LONG_DOUBLE) +typedef complex long double npy_clongdouble; +#else +typedef struct {npy_longdouble real, imag;} npy_clongdouble; +#endif +#endif +#if NPY_SIZEOF_COMPLEX_DOUBLE != 2 * NPY_SIZEOF_DOUBLE +#error npy_cdouble definition is not compatible with C99 complex definition ! \ + Please contact Numpy maintainers and give detailed information about your \ + compiler and platform +#endif +typedef struct { double real, imag; } npy_cdouble; + +#if NPY_SIZEOF_COMPLEX_FLOAT != 2 * NPY_SIZEOF_FLOAT +#error npy_cfloat definition is not compatible with C99 complex definition ! \ + Please contact Numpy maintainers and give detailed information about your \ + compiler and platform +#endif +typedef struct { float real, imag; } npy_cfloat; + +#if NPY_SIZEOF_COMPLEX_LONGDOUBLE != 2 * NPY_SIZEOF_LONGDOUBLE +#error npy_clongdouble definition is not compatible with C99 complex definition ! \ + Please contact Numpy maintainers and give detailed information about your \ + compiler and platform +#endif +typedef struct { npy_longdouble real, imag; } npy_clongdouble; + +/* + * numarray-style bit-width typedefs + */ +#define NPY_MAX_INT8 127 +#define NPY_MIN_INT8 -128 +#define NPY_MAX_UINT8 255 +#define NPY_MAX_INT16 32767 +#define NPY_MIN_INT16 -32768 +#define NPY_MAX_UINT16 65535 +#define NPY_MAX_INT32 2147483647 +#define NPY_MIN_INT32 (-NPY_MAX_INT32 - 1) +#define NPY_MAX_UINT32 4294967295U +#define NPY_MAX_INT64 NPY_LONGLONG_SUFFIX(9223372036854775807) +#define NPY_MIN_INT64 (-NPY_MAX_INT64 - NPY_LONGLONG_SUFFIX(1)) +#define NPY_MAX_UINT64 NPY_ULONGLONG_SUFFIX(18446744073709551615) +#define NPY_MAX_INT128 NPY_LONGLONG_SUFFIX(85070591730234615865843651857942052864) +#define NPY_MIN_INT128 (-NPY_MAX_INT128 - NPY_LONGLONG_SUFFIX(1)) +#define NPY_MAX_UINT128 NPY_ULONGLONG_SUFFIX(170141183460469231731687303715884105728) +#define NPY_MAX_INT256 NPY_LONGLONG_SUFFIX(57896044618658097711785492504343953926634992332820282019728792003956564819967) +#define NPY_MIN_INT256 (-NPY_MAX_INT256 - NPY_LONGLONG_SUFFIX(1)) +#define NPY_MAX_UINT256 NPY_ULONGLONG_SUFFIX(115792089237316195423570985008687907853269984665640564039457584007913129639935) +#define NPY_MIN_DATETIME NPY_MIN_INT64 +#define NPY_MAX_DATETIME NPY_MAX_INT64 +#define NPY_MIN_TIMEDELTA NPY_MIN_INT64 +#define NPY_MAX_TIMEDELTA NPY_MAX_INT64 + + /* Need to find the number of bits for each type and + make definitions accordingly. + + C states that sizeof(char) == 1 by definition + + So, just using the sizeof keyword won't help. + + It also looks like Python itself uses sizeof(char) quite a + bit, which by definition should be 1 all the time. + + Idea: Make Use of CHAR_BIT which should tell us how many + BITS per CHARACTER + */ + + /* Include platform definitions -- These are in the C89/90 standard */ +#include +#define NPY_MAX_BYTE SCHAR_MAX +#define NPY_MIN_BYTE SCHAR_MIN +#define NPY_MAX_UBYTE UCHAR_MAX +#define NPY_MAX_SHORT SHRT_MAX +#define NPY_MIN_SHORT SHRT_MIN +#define NPY_MAX_USHORT USHRT_MAX +#define NPY_MAX_INT INT_MAX +#ifndef INT_MIN +#define INT_MIN (-INT_MAX - 1) +#endif +#define NPY_MIN_INT INT_MIN +#define NPY_MAX_UINT UINT_MAX +#define NPY_MAX_LONG LONG_MAX +#define NPY_MIN_LONG LONG_MIN +#define NPY_MAX_ULONG ULONG_MAX + +#define NPY_SIZEOF_HALF 2 +#define NPY_SIZEOF_DATETIME 8 +#define NPY_SIZEOF_TIMEDELTA 8 + +#define NPY_BITSOF_BOOL (sizeof(npy_bool) * CHAR_BIT) +#define NPY_BITSOF_CHAR CHAR_BIT +#define NPY_BITSOF_BYTE (NPY_SIZEOF_BYTE * CHAR_BIT) +#define NPY_BITSOF_SHORT (NPY_SIZEOF_SHORT * CHAR_BIT) +#define NPY_BITSOF_INT (NPY_SIZEOF_INT * CHAR_BIT) +#define NPY_BITSOF_LONG (NPY_SIZEOF_LONG * CHAR_BIT) +#define NPY_BITSOF_LONGLONG (NPY_SIZEOF_LONGLONG * CHAR_BIT) +#define NPY_BITSOF_INTP (NPY_SIZEOF_INTP * CHAR_BIT) +#define NPY_BITSOF_HALF (NPY_SIZEOF_HALF * CHAR_BIT) +#define NPY_BITSOF_FLOAT (NPY_SIZEOF_FLOAT * CHAR_BIT) +#define NPY_BITSOF_DOUBLE (NPY_SIZEOF_DOUBLE * CHAR_BIT) +#define NPY_BITSOF_LONGDOUBLE (NPY_SIZEOF_LONGDOUBLE * CHAR_BIT) +#define NPY_BITSOF_CFLOAT (NPY_SIZEOF_CFLOAT * CHAR_BIT) +#define NPY_BITSOF_CDOUBLE (NPY_SIZEOF_CDOUBLE * CHAR_BIT) +#define NPY_BITSOF_CLONGDOUBLE (NPY_SIZEOF_CLONGDOUBLE * CHAR_BIT) +#define NPY_BITSOF_DATETIME (NPY_SIZEOF_DATETIME * CHAR_BIT) +#define NPY_BITSOF_TIMEDELTA (NPY_SIZEOF_TIMEDELTA * CHAR_BIT) + +#if NPY_BITSOF_LONG == 8 +#define NPY_INT8 NPY_LONG +#define NPY_UINT8 NPY_ULONG + typedef long npy_int8; + typedef unsigned long npy_uint8; +#define PyInt8ScalarObject PyLongScalarObject +#define PyInt8ArrType_Type PyLongArrType_Type +#define PyUInt8ScalarObject PyULongScalarObject +#define PyUInt8ArrType_Type PyULongArrType_Type +#define NPY_INT8_FMT NPY_LONG_FMT +#define NPY_UINT8_FMT NPY_ULONG_FMT +#elif NPY_BITSOF_LONG == 16 +#define NPY_INT16 NPY_LONG +#define NPY_UINT16 NPY_ULONG + typedef long npy_int16; + typedef unsigned long npy_uint16; +#define PyInt16ScalarObject PyLongScalarObject +#define PyInt16ArrType_Type PyLongArrType_Type +#define PyUInt16ScalarObject PyULongScalarObject +#define PyUInt16ArrType_Type PyULongArrType_Type +#define NPY_INT16_FMT NPY_LONG_FMT +#define NPY_UINT16_FMT NPY_ULONG_FMT +#elif NPY_BITSOF_LONG == 32 +#define NPY_INT32 NPY_LONG +#define NPY_UINT32 NPY_ULONG + typedef long npy_int32; + typedef unsigned long npy_uint32; + typedef unsigned long npy_ucs4; +#define PyInt32ScalarObject PyLongScalarObject +#define PyInt32ArrType_Type PyLongArrType_Type +#define PyUInt32ScalarObject PyULongScalarObject +#define PyUInt32ArrType_Type PyULongArrType_Type +#define NPY_INT32_FMT NPY_LONG_FMT +#define NPY_UINT32_FMT NPY_ULONG_FMT +#elif NPY_BITSOF_LONG == 64 +#define NPY_INT64 NPY_LONG +#define NPY_UINT64 NPY_ULONG + typedef long npy_int64; + typedef unsigned long npy_uint64; +#define PyInt64ScalarObject PyLongScalarObject +#define PyInt64ArrType_Type PyLongArrType_Type +#define PyUInt64ScalarObject PyULongScalarObject +#define PyUInt64ArrType_Type PyULongArrType_Type +#define NPY_INT64_FMT NPY_LONG_FMT +#define NPY_UINT64_FMT NPY_ULONG_FMT +#define MyPyLong_FromInt64 PyLong_FromLong +#define MyPyLong_AsInt64 PyLong_AsLong +#elif NPY_BITSOF_LONG == 128 +#define NPY_INT128 NPY_LONG +#define NPY_UINT128 NPY_ULONG + typedef long npy_int128; + typedef unsigned long npy_uint128; +#define PyInt128ScalarObject PyLongScalarObject +#define PyInt128ArrType_Type PyLongArrType_Type +#define PyUInt128ScalarObject PyULongScalarObject +#define PyUInt128ArrType_Type PyULongArrType_Type +#define NPY_INT128_FMT NPY_LONG_FMT +#define NPY_UINT128_FMT NPY_ULONG_FMT +#endif + +#if NPY_BITSOF_LONGLONG == 8 +# ifndef NPY_INT8 +# define NPY_INT8 NPY_LONGLONG +# define NPY_UINT8 NPY_ULONGLONG + typedef npy_longlong npy_int8; + typedef npy_ulonglong npy_uint8; +# define PyInt8ScalarObject PyLongLongScalarObject +# define PyInt8ArrType_Type PyLongLongArrType_Type +# define PyUInt8ScalarObject PyULongLongScalarObject +# define PyUInt8ArrType_Type PyULongLongArrType_Type +#define NPY_INT8_FMT NPY_LONGLONG_FMT +#define NPY_UINT8_FMT NPY_ULONGLONG_FMT +# endif +# define NPY_MAX_LONGLONG NPY_MAX_INT8 +# define NPY_MIN_LONGLONG NPY_MIN_INT8 +# define NPY_MAX_ULONGLONG NPY_MAX_UINT8 +#elif NPY_BITSOF_LONGLONG == 16 +# ifndef NPY_INT16 +# define NPY_INT16 NPY_LONGLONG +# define NPY_UINT16 NPY_ULONGLONG + typedef npy_longlong npy_int16; + typedef npy_ulonglong npy_uint16; +# define PyInt16ScalarObject PyLongLongScalarObject +# define PyInt16ArrType_Type PyLongLongArrType_Type +# define PyUInt16ScalarObject PyULongLongScalarObject +# define PyUInt16ArrType_Type PyULongLongArrType_Type +#define NPY_INT16_FMT NPY_LONGLONG_FMT +#define NPY_UINT16_FMT NPY_ULONGLONG_FMT +# endif +# define NPY_MAX_LONGLONG NPY_MAX_INT16 +# define NPY_MIN_LONGLONG NPY_MIN_INT16 +# define NPY_MAX_ULONGLONG NPY_MAX_UINT16 +#elif NPY_BITSOF_LONGLONG == 32 +# ifndef NPY_INT32 +# define NPY_INT32 NPY_LONGLONG +# define NPY_UINT32 NPY_ULONGLONG + typedef npy_longlong npy_int32; + typedef npy_ulonglong npy_uint32; + typedef npy_ulonglong npy_ucs4; +# define PyInt32ScalarObject PyLongLongScalarObject +# define PyInt32ArrType_Type PyLongLongArrType_Type +# define PyUInt32ScalarObject PyULongLongScalarObject +# define PyUInt32ArrType_Type PyULongLongArrType_Type +#define NPY_INT32_FMT NPY_LONGLONG_FMT +#define NPY_UINT32_FMT NPY_ULONGLONG_FMT +# endif +# define NPY_MAX_LONGLONG NPY_MAX_INT32 +# define NPY_MIN_LONGLONG NPY_MIN_INT32 +# define NPY_MAX_ULONGLONG NPY_MAX_UINT32 +#elif NPY_BITSOF_LONGLONG == 64 +# ifndef NPY_INT64 +# define NPY_INT64 NPY_LONGLONG +# define NPY_UINT64 NPY_ULONGLONG + typedef npy_longlong npy_int64; + typedef npy_ulonglong npy_uint64; +# define PyInt64ScalarObject PyLongLongScalarObject +# define PyInt64ArrType_Type PyLongLongArrType_Type +# define PyUInt64ScalarObject PyULongLongScalarObject +# define PyUInt64ArrType_Type PyULongLongArrType_Type +#define NPY_INT64_FMT NPY_LONGLONG_FMT +#define NPY_UINT64_FMT NPY_ULONGLONG_FMT +# define MyPyLong_FromInt64 PyLong_FromLongLong +# define MyPyLong_AsInt64 PyLong_AsLongLong +# endif +# define NPY_MAX_LONGLONG NPY_MAX_INT64 +# define NPY_MIN_LONGLONG NPY_MIN_INT64 +# define NPY_MAX_ULONGLONG NPY_MAX_UINT64 +#elif NPY_BITSOF_LONGLONG == 128 +# ifndef NPY_INT128 +# define NPY_INT128 NPY_LONGLONG +# define NPY_UINT128 NPY_ULONGLONG + typedef npy_longlong npy_int128; + typedef npy_ulonglong npy_uint128; +# define PyInt128ScalarObject PyLongLongScalarObject +# define PyInt128ArrType_Type PyLongLongArrType_Type +# define PyUInt128ScalarObject PyULongLongScalarObject +# define PyUInt128ArrType_Type PyULongLongArrType_Type +#define NPY_INT128_FMT NPY_LONGLONG_FMT +#define NPY_UINT128_FMT NPY_ULONGLONG_FMT +# endif +# define NPY_MAX_LONGLONG NPY_MAX_INT128 +# define NPY_MIN_LONGLONG NPY_MIN_INT128 +# define NPY_MAX_ULONGLONG NPY_MAX_UINT128 +#elif NPY_BITSOF_LONGLONG == 256 +# define NPY_INT256 NPY_LONGLONG +# define NPY_UINT256 NPY_ULONGLONG + typedef npy_longlong npy_int256; + typedef npy_ulonglong npy_uint256; +# define PyInt256ScalarObject PyLongLongScalarObject +# define PyInt256ArrType_Type PyLongLongArrType_Type +# define PyUInt256ScalarObject PyULongLongScalarObject +# define PyUInt256ArrType_Type PyULongLongArrType_Type +#define NPY_INT256_FMT NPY_LONGLONG_FMT +#define NPY_UINT256_FMT NPY_ULONGLONG_FMT +# define NPY_MAX_LONGLONG NPY_MAX_INT256 +# define NPY_MIN_LONGLONG NPY_MIN_INT256 +# define NPY_MAX_ULONGLONG NPY_MAX_UINT256 +#endif + +#if NPY_BITSOF_INT == 8 +#ifndef NPY_INT8 +#define NPY_INT8 NPY_INT +#define NPY_UINT8 NPY_UINT + typedef int npy_int8; + typedef unsigned int npy_uint8; +# define PyInt8ScalarObject PyIntScalarObject +# define PyInt8ArrType_Type PyIntArrType_Type +# define PyUInt8ScalarObject PyUIntScalarObject +# define PyUInt8ArrType_Type PyUIntArrType_Type +#define NPY_INT8_FMT NPY_INT_FMT +#define NPY_UINT8_FMT NPY_UINT_FMT +#endif +#elif NPY_BITSOF_INT == 16 +#ifndef NPY_INT16 +#define NPY_INT16 NPY_INT +#define NPY_UINT16 NPY_UINT + typedef int npy_int16; + typedef unsigned int npy_uint16; +# define PyInt16ScalarObject PyIntScalarObject +# define PyInt16ArrType_Type PyIntArrType_Type +# define PyUInt16ScalarObject PyIntUScalarObject +# define PyUInt16ArrType_Type PyIntUArrType_Type +#define NPY_INT16_FMT NPY_INT_FMT +#define NPY_UINT16_FMT NPY_UINT_FMT +#endif +#elif NPY_BITSOF_INT == 32 +#ifndef NPY_INT32 +#define NPY_INT32 NPY_INT +#define NPY_UINT32 NPY_UINT + typedef int npy_int32; + typedef unsigned int npy_uint32; + typedef unsigned int npy_ucs4; +# define PyInt32ScalarObject PyIntScalarObject +# define PyInt32ArrType_Type PyIntArrType_Type +# define PyUInt32ScalarObject PyUIntScalarObject +# define PyUInt32ArrType_Type PyUIntArrType_Type +#define NPY_INT32_FMT NPY_INT_FMT +#define NPY_UINT32_FMT NPY_UINT_FMT +#endif +#elif NPY_BITSOF_INT == 64 +#ifndef NPY_INT64 +#define NPY_INT64 NPY_INT +#define NPY_UINT64 NPY_UINT + typedef int npy_int64; + typedef unsigned int npy_uint64; +# define PyInt64ScalarObject PyIntScalarObject +# define PyInt64ArrType_Type PyIntArrType_Type +# define PyUInt64ScalarObject PyUIntScalarObject +# define PyUInt64ArrType_Type PyUIntArrType_Type +#define NPY_INT64_FMT NPY_INT_FMT +#define NPY_UINT64_FMT NPY_UINT_FMT +# define MyPyLong_FromInt64 PyLong_FromLong +# define MyPyLong_AsInt64 PyLong_AsLong +#endif +#elif NPY_BITSOF_INT == 128 +#ifndef NPY_INT128 +#define NPY_INT128 NPY_INT +#define NPY_UINT128 NPY_UINT + typedef int npy_int128; + typedef unsigned int npy_uint128; +# define PyInt128ScalarObject PyIntScalarObject +# define PyInt128ArrType_Type PyIntArrType_Type +# define PyUInt128ScalarObject PyUIntScalarObject +# define PyUInt128ArrType_Type PyUIntArrType_Type +#define NPY_INT128_FMT NPY_INT_FMT +#define NPY_UINT128_FMT NPY_UINT_FMT +#endif +#endif + +#if NPY_BITSOF_SHORT == 8 +#ifndef NPY_INT8 +#define NPY_INT8 NPY_SHORT +#define NPY_UINT8 NPY_USHORT + typedef short npy_int8; + typedef unsigned short npy_uint8; +# define PyInt8ScalarObject PyShortScalarObject +# define PyInt8ArrType_Type PyShortArrType_Type +# define PyUInt8ScalarObject PyUShortScalarObject +# define PyUInt8ArrType_Type PyUShortArrType_Type +#define NPY_INT8_FMT NPY_SHORT_FMT +#define NPY_UINT8_FMT NPY_USHORT_FMT +#endif +#elif NPY_BITSOF_SHORT == 16 +#ifndef NPY_INT16 +#define NPY_INT16 NPY_SHORT +#define NPY_UINT16 NPY_USHORT + typedef short npy_int16; + typedef unsigned short npy_uint16; +# define PyInt16ScalarObject PyShortScalarObject +# define PyInt16ArrType_Type PyShortArrType_Type +# define PyUInt16ScalarObject PyUShortScalarObject +# define PyUInt16ArrType_Type PyUShortArrType_Type +#define NPY_INT16_FMT NPY_SHORT_FMT +#define NPY_UINT16_FMT NPY_USHORT_FMT +#endif +#elif NPY_BITSOF_SHORT == 32 +#ifndef NPY_INT32 +#define NPY_INT32 NPY_SHORT +#define NPY_UINT32 NPY_USHORT + typedef short npy_int32; + typedef unsigned short npy_uint32; + typedef unsigned short npy_ucs4; +# define PyInt32ScalarObject PyShortScalarObject +# define PyInt32ArrType_Type PyShortArrType_Type +# define PyUInt32ScalarObject PyUShortScalarObject +# define PyUInt32ArrType_Type PyUShortArrType_Type +#define NPY_INT32_FMT NPY_SHORT_FMT +#define NPY_UINT32_FMT NPY_USHORT_FMT +#endif +#elif NPY_BITSOF_SHORT == 64 +#ifndef NPY_INT64 +#define NPY_INT64 NPY_SHORT +#define NPY_UINT64 NPY_USHORT + typedef short npy_int64; + typedef unsigned short npy_uint64; +# define PyInt64ScalarObject PyShortScalarObject +# define PyInt64ArrType_Type PyShortArrType_Type +# define PyUInt64ScalarObject PyUShortScalarObject +# define PyUInt64ArrType_Type PyUShortArrType_Type +#define NPY_INT64_FMT NPY_SHORT_FMT +#define NPY_UINT64_FMT NPY_USHORT_FMT +# define MyPyLong_FromInt64 PyLong_FromLong +# define MyPyLong_AsInt64 PyLong_AsLong +#endif +#elif NPY_BITSOF_SHORT == 128 +#ifndef NPY_INT128 +#define NPY_INT128 NPY_SHORT +#define NPY_UINT128 NPY_USHORT + typedef short npy_int128; + typedef unsigned short npy_uint128; +# define PyInt128ScalarObject PyShortScalarObject +# define PyInt128ArrType_Type PyShortArrType_Type +# define PyUInt128ScalarObject PyUShortScalarObject +# define PyUInt128ArrType_Type PyUShortArrType_Type +#define NPY_INT128_FMT NPY_SHORT_FMT +#define NPY_UINT128_FMT NPY_USHORT_FMT +#endif +#endif + + +#if NPY_BITSOF_CHAR == 8 +#ifndef NPY_INT8 +#define NPY_INT8 NPY_BYTE +#define NPY_UINT8 NPY_UBYTE + typedef signed char npy_int8; + typedef unsigned char npy_uint8; +# define PyInt8ScalarObject PyByteScalarObject +# define PyInt8ArrType_Type PyByteArrType_Type +# define PyUInt8ScalarObject PyUByteScalarObject +# define PyUInt8ArrType_Type PyUByteArrType_Type +#define NPY_INT8_FMT NPY_BYTE_FMT +#define NPY_UINT8_FMT NPY_UBYTE_FMT +#endif +#elif NPY_BITSOF_CHAR == 16 +#ifndef NPY_INT16 +#define NPY_INT16 NPY_BYTE +#define NPY_UINT16 NPY_UBYTE + typedef signed char npy_int16; + typedef unsigned char npy_uint16; +# define PyInt16ScalarObject PyByteScalarObject +# define PyInt16ArrType_Type PyByteArrType_Type +# define PyUInt16ScalarObject PyUByteScalarObject +# define PyUInt16ArrType_Type PyUByteArrType_Type +#define NPY_INT16_FMT NPY_BYTE_FMT +#define NPY_UINT16_FMT NPY_UBYTE_FMT +#endif +#elif NPY_BITSOF_CHAR == 32 +#ifndef NPY_INT32 +#define NPY_INT32 NPY_BYTE +#define NPY_UINT32 NPY_UBYTE + typedef signed char npy_int32; + typedef unsigned char npy_uint32; + typedef unsigned char npy_ucs4; +# define PyInt32ScalarObject PyByteScalarObject +# define PyInt32ArrType_Type PyByteArrType_Type +# define PyUInt32ScalarObject PyUByteScalarObject +# define PyUInt32ArrType_Type PyUByteArrType_Type +#define NPY_INT32_FMT NPY_BYTE_FMT +#define NPY_UINT32_FMT NPY_UBYTE_FMT +#endif +#elif NPY_BITSOF_CHAR == 64 +#ifndef NPY_INT64 +#define NPY_INT64 NPY_BYTE +#define NPY_UINT64 NPY_UBYTE + typedef signed char npy_int64; + typedef unsigned char npy_uint64; +# define PyInt64ScalarObject PyByteScalarObject +# define PyInt64ArrType_Type PyByteArrType_Type +# define PyUInt64ScalarObject PyUByteScalarObject +# define PyUInt64ArrType_Type PyUByteArrType_Type +#define NPY_INT64_FMT NPY_BYTE_FMT +#define NPY_UINT64_FMT NPY_UBYTE_FMT +# define MyPyLong_FromInt64 PyLong_FromLong +# define MyPyLong_AsInt64 PyLong_AsLong +#endif +#elif NPY_BITSOF_CHAR == 128 +#ifndef NPY_INT128 +#define NPY_INT128 NPY_BYTE +#define NPY_UINT128 NPY_UBYTE + typedef signed char npy_int128; + typedef unsigned char npy_uint128; +# define PyInt128ScalarObject PyByteScalarObject +# define PyInt128ArrType_Type PyByteArrType_Type +# define PyUInt128ScalarObject PyUByteScalarObject +# define PyUInt128ArrType_Type PyUByteArrType_Type +#define NPY_INT128_FMT NPY_BYTE_FMT +#define NPY_UINT128_FMT NPY_UBYTE_FMT +#endif +#endif + + + +#if NPY_BITSOF_DOUBLE == 32 +#ifndef NPY_FLOAT32 +#define NPY_FLOAT32 NPY_DOUBLE +#define NPY_COMPLEX64 NPY_CDOUBLE + typedef double npy_float32; + typedef npy_cdouble npy_complex64; +# define PyFloat32ScalarObject PyDoubleScalarObject +# define PyComplex64ScalarObject PyCDoubleScalarObject +# define PyFloat32ArrType_Type PyDoubleArrType_Type +# define PyComplex64ArrType_Type PyCDoubleArrType_Type +#define NPY_FLOAT32_FMT NPY_DOUBLE_FMT +#define NPY_COMPLEX64_FMT NPY_CDOUBLE_FMT +#endif +#elif NPY_BITSOF_DOUBLE == 64 +#ifndef NPY_FLOAT64 +#define NPY_FLOAT64 NPY_DOUBLE +#define NPY_COMPLEX128 NPY_CDOUBLE + typedef double npy_float64; + typedef npy_cdouble npy_complex128; +# define PyFloat64ScalarObject PyDoubleScalarObject +# define PyComplex128ScalarObject PyCDoubleScalarObject +# define PyFloat64ArrType_Type PyDoubleArrType_Type +# define PyComplex128ArrType_Type PyCDoubleArrType_Type +#define NPY_FLOAT64_FMT NPY_DOUBLE_FMT +#define NPY_COMPLEX128_FMT NPY_CDOUBLE_FMT +#endif +#elif NPY_BITSOF_DOUBLE == 80 +#ifndef NPY_FLOAT80 +#define NPY_FLOAT80 NPY_DOUBLE +#define NPY_COMPLEX160 NPY_CDOUBLE + typedef double npy_float80; + typedef npy_cdouble npy_complex160; +# define PyFloat80ScalarObject PyDoubleScalarObject +# define PyComplex160ScalarObject PyCDoubleScalarObject +# define PyFloat80ArrType_Type PyDoubleArrType_Type +# define PyComplex160ArrType_Type PyCDoubleArrType_Type +#define NPY_FLOAT80_FMT NPY_DOUBLE_FMT +#define NPY_COMPLEX160_FMT NPY_CDOUBLE_FMT +#endif +#elif NPY_BITSOF_DOUBLE == 96 +#ifndef NPY_FLOAT96 +#define NPY_FLOAT96 NPY_DOUBLE +#define NPY_COMPLEX192 NPY_CDOUBLE + typedef double npy_float96; + typedef npy_cdouble npy_complex192; +# define PyFloat96ScalarObject PyDoubleScalarObject +# define PyComplex192ScalarObject PyCDoubleScalarObject +# define PyFloat96ArrType_Type PyDoubleArrType_Type +# define PyComplex192ArrType_Type PyCDoubleArrType_Type +#define NPY_FLOAT96_FMT NPY_DOUBLE_FMT +#define NPY_COMPLEX192_FMT NPY_CDOUBLE_FMT +#endif +#elif NPY_BITSOF_DOUBLE == 128 +#ifndef NPY_FLOAT128 +#define NPY_FLOAT128 NPY_DOUBLE +#define NPY_COMPLEX256 NPY_CDOUBLE + typedef double npy_float128; + typedef npy_cdouble npy_complex256; +# define PyFloat128ScalarObject PyDoubleScalarObject +# define PyComplex256ScalarObject PyCDoubleScalarObject +# define PyFloat128ArrType_Type PyDoubleArrType_Type +# define PyComplex256ArrType_Type PyCDoubleArrType_Type +#define NPY_FLOAT128_FMT NPY_DOUBLE_FMT +#define NPY_COMPLEX256_FMT NPY_CDOUBLE_FMT +#endif +#endif + + + +#if NPY_BITSOF_FLOAT == 32 +#ifndef NPY_FLOAT32 +#define NPY_FLOAT32 NPY_FLOAT +#define NPY_COMPLEX64 NPY_CFLOAT + typedef float npy_float32; + typedef npy_cfloat npy_complex64; +# define PyFloat32ScalarObject PyFloatScalarObject +# define PyComplex64ScalarObject PyCFloatScalarObject +# define PyFloat32ArrType_Type PyFloatArrType_Type +# define PyComplex64ArrType_Type PyCFloatArrType_Type +#define NPY_FLOAT32_FMT NPY_FLOAT_FMT +#define NPY_COMPLEX64_FMT NPY_CFLOAT_FMT +#endif +#elif NPY_BITSOF_FLOAT == 64 +#ifndef NPY_FLOAT64 +#define NPY_FLOAT64 NPY_FLOAT +#define NPY_COMPLEX128 NPY_CFLOAT + typedef float npy_float64; + typedef npy_cfloat npy_complex128; +# define PyFloat64ScalarObject PyFloatScalarObject +# define PyComplex128ScalarObject PyCFloatScalarObject +# define PyFloat64ArrType_Type PyFloatArrType_Type +# define PyComplex128ArrType_Type PyCFloatArrType_Type +#define NPY_FLOAT64_FMT NPY_FLOAT_FMT +#define NPY_COMPLEX128_FMT NPY_CFLOAT_FMT +#endif +#elif NPY_BITSOF_FLOAT == 80 +#ifndef NPY_FLOAT80 +#define NPY_FLOAT80 NPY_FLOAT +#define NPY_COMPLEX160 NPY_CFLOAT + typedef float npy_float80; + typedef npy_cfloat npy_complex160; +# define PyFloat80ScalarObject PyFloatScalarObject +# define PyComplex160ScalarObject PyCFloatScalarObject +# define PyFloat80ArrType_Type PyFloatArrType_Type +# define PyComplex160ArrType_Type PyCFloatArrType_Type +#define NPY_FLOAT80_FMT NPY_FLOAT_FMT +#define NPY_COMPLEX160_FMT NPY_CFLOAT_FMT +#endif +#elif NPY_BITSOF_FLOAT == 96 +#ifndef NPY_FLOAT96 +#define NPY_FLOAT96 NPY_FLOAT +#define NPY_COMPLEX192 NPY_CFLOAT + typedef float npy_float96; + typedef npy_cfloat npy_complex192; +# define PyFloat96ScalarObject PyFloatScalarObject +# define PyComplex192ScalarObject PyCFloatScalarObject +# define PyFloat96ArrType_Type PyFloatArrType_Type +# define PyComplex192ArrType_Type PyCFloatArrType_Type +#define NPY_FLOAT96_FMT NPY_FLOAT_FMT +#define NPY_COMPLEX192_FMT NPY_CFLOAT_FMT +#endif +#elif NPY_BITSOF_FLOAT == 128 +#ifndef NPY_FLOAT128 +#define NPY_FLOAT128 NPY_FLOAT +#define NPY_COMPLEX256 NPY_CFLOAT + typedef float npy_float128; + typedef npy_cfloat npy_complex256; +# define PyFloat128ScalarObject PyFloatScalarObject +# define PyComplex256ScalarObject PyCFloatScalarObject +# define PyFloat128ArrType_Type PyFloatArrType_Type +# define PyComplex256ArrType_Type PyCFloatArrType_Type +#define NPY_FLOAT128_FMT NPY_FLOAT_FMT +#define NPY_COMPLEX256_FMT NPY_CFLOAT_FMT +#endif +#endif + +/* half/float16 isn't a floating-point type in C */ +#define NPY_FLOAT16 NPY_HALF +typedef npy_uint16 npy_half; +typedef npy_half npy_float16; + +#if NPY_BITSOF_LONGDOUBLE == 32 +#ifndef NPY_FLOAT32 +#define NPY_FLOAT32 NPY_LONGDOUBLE +#define NPY_COMPLEX64 NPY_CLONGDOUBLE + typedef npy_longdouble npy_float32; + typedef npy_clongdouble npy_complex64; +# define PyFloat32ScalarObject PyLongDoubleScalarObject +# define PyComplex64ScalarObject PyCLongDoubleScalarObject +# define PyFloat32ArrType_Type PyLongDoubleArrType_Type +# define PyComplex64ArrType_Type PyCLongDoubleArrType_Type +#define NPY_FLOAT32_FMT NPY_LONGDOUBLE_FMT +#define NPY_COMPLEX64_FMT NPY_CLONGDOUBLE_FMT +#endif +#elif NPY_BITSOF_LONGDOUBLE == 64 +#ifndef NPY_FLOAT64 +#define NPY_FLOAT64 NPY_LONGDOUBLE +#define NPY_COMPLEX128 NPY_CLONGDOUBLE + typedef npy_longdouble npy_float64; + typedef npy_clongdouble npy_complex128; +# define PyFloat64ScalarObject PyLongDoubleScalarObject +# define PyComplex128ScalarObject PyCLongDoubleScalarObject +# define PyFloat64ArrType_Type PyLongDoubleArrType_Type +# define PyComplex128ArrType_Type PyCLongDoubleArrType_Type +#define NPY_FLOAT64_FMT NPY_LONGDOUBLE_FMT +#define NPY_COMPLEX128_FMT NPY_CLONGDOUBLE_FMT +#endif +#elif NPY_BITSOF_LONGDOUBLE == 80 +#ifndef NPY_FLOAT80 +#define NPY_FLOAT80 NPY_LONGDOUBLE +#define NPY_COMPLEX160 NPY_CLONGDOUBLE + typedef npy_longdouble npy_float80; + typedef npy_clongdouble npy_complex160; +# define PyFloat80ScalarObject PyLongDoubleScalarObject +# define PyComplex160ScalarObject PyCLongDoubleScalarObject +# define PyFloat80ArrType_Type PyLongDoubleArrType_Type +# define PyComplex160ArrType_Type PyCLongDoubleArrType_Type +#define NPY_FLOAT80_FMT NPY_LONGDOUBLE_FMT +#define NPY_COMPLEX160_FMT NPY_CLONGDOUBLE_FMT +#endif +#elif NPY_BITSOF_LONGDOUBLE == 96 +#ifndef NPY_FLOAT96 +#define NPY_FLOAT96 NPY_LONGDOUBLE +#define NPY_COMPLEX192 NPY_CLONGDOUBLE + typedef npy_longdouble npy_float96; + typedef npy_clongdouble npy_complex192; +# define PyFloat96ScalarObject PyLongDoubleScalarObject +# define PyComplex192ScalarObject PyCLongDoubleScalarObject +# define PyFloat96ArrType_Type PyLongDoubleArrType_Type +# define PyComplex192ArrType_Type PyCLongDoubleArrType_Type +#define NPY_FLOAT96_FMT NPY_LONGDOUBLE_FMT +#define NPY_COMPLEX192_FMT NPY_CLONGDOUBLE_FMT +#endif +#elif NPY_BITSOF_LONGDOUBLE == 128 +#ifndef NPY_FLOAT128 +#define NPY_FLOAT128 NPY_LONGDOUBLE +#define NPY_COMPLEX256 NPY_CLONGDOUBLE + typedef npy_longdouble npy_float128; + typedef npy_clongdouble npy_complex256; +# define PyFloat128ScalarObject PyLongDoubleScalarObject +# define PyComplex256ScalarObject PyCLongDoubleScalarObject +# define PyFloat128ArrType_Type PyLongDoubleArrType_Type +# define PyComplex256ArrType_Type PyCLongDoubleArrType_Type +#define NPY_FLOAT128_FMT NPY_LONGDOUBLE_FMT +#define NPY_COMPLEX256_FMT NPY_CLONGDOUBLE_FMT +#endif +#elif NPY_BITSOF_LONGDOUBLE == 256 +#define NPY_FLOAT256 NPY_LONGDOUBLE +#define NPY_COMPLEX512 NPY_CLONGDOUBLE + typedef npy_longdouble npy_float256; + typedef npy_clongdouble npy_complex512; +# define PyFloat256ScalarObject PyLongDoubleScalarObject +# define PyComplex512ScalarObject PyCLongDoubleScalarObject +# define PyFloat256ArrType_Type PyLongDoubleArrType_Type +# define PyComplex512ArrType_Type PyCLongDoubleArrType_Type +#define NPY_FLOAT256_FMT NPY_LONGDOUBLE_FMT +#define NPY_COMPLEX512_FMT NPY_CLONGDOUBLE_FMT +#endif + +/* datetime typedefs */ +typedef npy_int64 npy_timedelta; +typedef npy_int64 npy_datetime; +#define NPY_DATETIME_FMT NPY_INT64_FMT +#define NPY_TIMEDELTA_FMT NPY_INT64_FMT + +/* End of typedefs for numarray style bit-width names */ + +#endif + diff --git a/data_tooling/pii_processing/include/numpy/npy_cpu.h b/data_tooling/pii_processing/include/numpy/npy_cpu.h new file mode 100644 index 0000000..9707a7a --- /dev/null +++ b/data_tooling/pii_processing/include/numpy/npy_cpu.h @@ -0,0 +1,109 @@ +/* + * This set (target) cpu specific macros: + * - Possible values: + * NPY_CPU_X86 + * NPY_CPU_AMD64 + * NPY_CPU_PPC + * NPY_CPU_PPC64 + * NPY_CPU_SPARC + * NPY_CPU_S390 + * NPY_CPU_IA64 + * NPY_CPU_HPPA + * NPY_CPU_ALPHA + * NPY_CPU_ARMEL + * NPY_CPU_ARMEB + * NPY_CPU_SH_LE + * NPY_CPU_SH_BE + */ +#ifndef _NPY_CPUARCH_H_ +#define _NPY_CPUARCH_H_ + +#include "numpyconfig.h" + +#if defined( __i386__ ) || defined(i386) || defined(_M_IX86) + /* + * __i386__ is defined by gcc and Intel compiler on Linux, + * _M_IX86 by VS compiler, + * i386 by Sun compilers on opensolaris at least + */ + #define NPY_CPU_X86 +#elif defined(__x86_64__) || defined(__amd64__) || defined(__x86_64) || defined(_M_AMD64) + /* + * both __x86_64__ and __amd64__ are defined by gcc + * __x86_64 defined by sun compiler on opensolaris at least + * _M_AMD64 defined by MS compiler + */ + #define NPY_CPU_AMD64 +#elif defined(__ppc__) || defined(__powerpc__) || defined(_ARCH_PPC) + /* + * __ppc__ is defined by gcc, I remember having seen __powerpc__ once, + * but can't find it ATM + * _ARCH_PPC is used by at least gcc on AIX + */ + #define NPY_CPU_PPC +#elif defined(__ppc64__) + #define NPY_CPU_PPC64 +#elif defined(__sparc__) || defined(__sparc) + /* __sparc__ is defined by gcc and Forte (e.g. Sun) compilers */ + #define NPY_CPU_SPARC +#elif defined(__s390__) + #define NPY_CPU_S390 +#elif defined(__ia64) + #define NPY_CPU_IA64 +#elif defined(__hppa) + #define NPY_CPU_HPPA +#elif defined(__alpha__) + #define NPY_CPU_ALPHA +#elif defined(__arm__) && defined(__ARMEL__) + #define NPY_CPU_ARMEL +#elif defined(__arm__) && defined(__ARMEB__) + #define NPY_CPU_ARMEB +#elif defined(__sh__) && defined(__LITTLE_ENDIAN__) + #define NPY_CPU_SH_LE +#elif defined(__sh__) && defined(__BIG_ENDIAN__) + #define NPY_CPU_SH_BE +#elif defined(__MIPSEL__) + #define NPY_CPU_MIPSEL +#elif defined(__MIPSEB__) + #define NPY_CPU_MIPSEB +#elif defined(__aarch64__) + #define NPY_CPU_AARCH64 +#else + #error Unknown CPU, please report this to numpy maintainers with \ + information about your platform (OS, CPU and compiler) +#endif + +/* + This "white-lists" the architectures that we know don't require + pointer alignment. We white-list, since the memcpy version will + work everywhere, whereas assignment will only work where pointer + dereferencing doesn't require alignment. + + TODO: There may be more architectures we can white list. +*/ +#if defined(NPY_CPU_X86) || defined(NPY_CPU_AMD64) + #define NPY_COPY_PYOBJECT_PTR(dst, src) (*((PyObject **)(dst)) = *((PyObject **)(src))) +#else + #if NPY_SIZEOF_PY_INTPTR_T == 4 + #define NPY_COPY_PYOBJECT_PTR(dst, src) \ + ((char*)(dst))[0] = ((char*)(src))[0]; \ + ((char*)(dst))[1] = ((char*)(src))[1]; \ + ((char*)(dst))[2] = ((char*)(src))[2]; \ + ((char*)(dst))[3] = ((char*)(src))[3]; + #elif NPY_SIZEOF_PY_INTPTR_T == 8 + #define NPY_COPY_PYOBJECT_PTR(dst, src) \ + ((char*)(dst))[0] = ((char*)(src))[0]; \ + ((char*)(dst))[1] = ((char*)(src))[1]; \ + ((char*)(dst))[2] = ((char*)(src))[2]; \ + ((char*)(dst))[3] = ((char*)(src))[3]; \ + ((char*)(dst))[4] = ((char*)(src))[4]; \ + ((char*)(dst))[5] = ((char*)(src))[5]; \ + ((char*)(dst))[6] = ((char*)(src))[6]; \ + ((char*)(dst))[7] = ((char*)(src))[7]; + #else + #error Unknown architecture, please report this to numpy maintainers with \ + information about your platform (OS, CPU and compiler) + #endif +#endif + +#endif diff --git a/data_tooling/pii_processing/include/numpy/npy_deprecated_api.h b/data_tooling/pii_processing/include/numpy/npy_deprecated_api.h new file mode 100644 index 0000000..c27b4a4 --- /dev/null +++ b/data_tooling/pii_processing/include/numpy/npy_deprecated_api.h @@ -0,0 +1,129 @@ +#ifndef _NPY_DEPRECATED_API_H +#define _NPY_DEPRECATED_API_H + +#if defined(_WIN32) +#define _WARN___STR2__(x) #x +#define _WARN___STR1__(x) _WARN___STR2__(x) +#define _WARN___LOC__ __FILE__ "(" _WARN___STR1__(__LINE__) ") : Warning Msg: " +#pragma message(_WARN___LOC__"Using deprecated NumPy API, disable it by " \ + "#defining NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION") +#elif defined(__GNUC__) +#warning "Using deprecated NumPy API, disable it by #defining NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION" +#endif +/* TODO: How to do this warning message for other compilers? */ + +/* + * This header exists to collect all dangerous/deprecated NumPy API. + * + * This is an attempt to remove bad API, the proliferation of macros, + * and namespace pollution currently produced by the NumPy headers. + */ + +#if defined(NPY_NO_DEPRECATED_API) +#error Should never include npy_deprecated_api directly. +#endif + +/* These array flags are deprecated as of NumPy 1.7 */ +#define NPY_CONTIGUOUS NPY_ARRAY_C_CONTIGUOUS +#define NPY_FORTRAN NPY_ARRAY_F_CONTIGUOUS + +/* + * The consistent NPY_ARRAY_* names which don't pollute the NPY_* + * namespace were added in NumPy 1.7. + * + * These versions of the carray flags are deprecated, but + * probably should only be removed after two releases instead of one. + */ +#define NPY_C_CONTIGUOUS NPY_ARRAY_C_CONTIGUOUS +#define NPY_F_CONTIGUOUS NPY_ARRAY_F_CONTIGUOUS +#define NPY_OWNDATA NPY_ARRAY_OWNDATA +#define NPY_FORCECAST NPY_ARRAY_FORCECAST +#define NPY_ENSURECOPY NPY_ARRAY_ENSURECOPY +#define NPY_ENSUREARRAY NPY_ARRAY_ENSUREARRAY +#define NPY_ELEMENTSTRIDES NPY_ARRAY_ELEMENTSTRIDES +#define NPY_ALIGNED NPY_ARRAY_ALIGNED +#define NPY_NOTSWAPPED NPY_ARRAY_NOTSWAPPED +#define NPY_WRITEABLE NPY_ARRAY_WRITEABLE +#define NPY_UPDATEIFCOPY NPY_ARRAY_UPDATEIFCOPY +#define NPY_BEHAVED NPY_ARRAY_BEHAVED +#define NPY_BEHAVED_NS NPY_ARRAY_BEHAVED_NS +#define NPY_CARRAY NPY_ARRAY_CARRAY +#define NPY_CARRAY_RO NPY_ARRAY_CARRAY_RO +#define NPY_FARRAY NPY_ARRAY_FARRAY +#define NPY_FARRAY_RO NPY_ARRAY_FARRAY_RO +#define NPY_DEFAULT NPY_ARRAY_DEFAULT +#define NPY_IN_ARRAY NPY_ARRAY_IN_ARRAY +#define NPY_OUT_ARRAY NPY_ARRAY_OUT_ARRAY +#define NPY_INOUT_ARRAY NPY_ARRAY_INOUT_ARRAY +#define NPY_IN_FARRAY NPY_ARRAY_IN_FARRAY +#define NPY_OUT_FARRAY NPY_ARRAY_OUT_FARRAY +#define NPY_INOUT_FARRAY NPY_ARRAY_INOUT_FARRAY +#define NPY_UPDATE_ALL NPY_ARRAY_UPDATE_ALL + +/* This way of accessing the default type is deprecated as of NumPy 1.7 */ +#define PyArray_DEFAULT NPY_DEFAULT_TYPE + +/* These DATETIME bits aren't used internally */ +#if PY_VERSION_HEX >= 0x03000000 +#define PyDataType_GetDatetimeMetaData(descr) \ + ((descr->metadata == NULL) ? NULL : \ + ((PyArray_DatetimeMetaData *)(PyCapsule_GetPointer( \ + PyDict_GetItemString( \ + descr->metadata, NPY_METADATA_DTSTR), NULL)))) +#else +#define PyDataType_GetDatetimeMetaData(descr) \ + ((descr->metadata == NULL) ? NULL : \ + ((PyArray_DatetimeMetaData *)(PyCObject_AsVoidPtr( \ + PyDict_GetItemString(descr->metadata, NPY_METADATA_DTSTR))))) +#endif + +/* + * Deprecated as of NumPy 1.7, this kind of shortcut doesn't + * belong in the public API. + */ +#define NPY_AO PyArrayObject + +/* + * Deprecated as of NumPy 1.7, an all-lowercase macro doesn't + * belong in the public API. + */ +#define fortran fortran_ + +/* + * Deprecated as of NumPy 1.7, as it is a namespace-polluting + * macro. + */ +#define FORTRAN_IF PyArray_FORTRAN_IF + +/* Deprecated as of NumPy 1.7, datetime64 uses c_metadata instead */ +#define NPY_METADATA_DTSTR "__timeunit__" + +/* + * Deprecated as of NumPy 1.7. + * The reasoning: + * - These are for datetime, but there's no datetime "namespace". + * - They just turn NPY_STR_ into "", which is just + * making something simple be indirected. + */ +#define NPY_STR_Y "Y" +#define NPY_STR_M "M" +#define NPY_STR_W "W" +#define NPY_STR_D "D" +#define NPY_STR_h "h" +#define NPY_STR_m "m" +#define NPY_STR_s "s" +#define NPY_STR_ms "ms" +#define NPY_STR_us "us" +#define NPY_STR_ns "ns" +#define NPY_STR_ps "ps" +#define NPY_STR_fs "fs" +#define NPY_STR_as "as" + +/* + * The macros in old_defines.h are Deprecated as of NumPy 1.7 and will be + * removed in the next major release. + */ +#include "old_defines.h" + + +#endif diff --git a/data_tooling/pii_processing/include/numpy/npy_endian.h b/data_tooling/pii_processing/include/numpy/npy_endian.h new file mode 100644 index 0000000..4e3349f --- /dev/null +++ b/data_tooling/pii_processing/include/numpy/npy_endian.h @@ -0,0 +1,46 @@ +#ifndef _NPY_ENDIAN_H_ +#define _NPY_ENDIAN_H_ + +/* + * NPY_BYTE_ORDER is set to the same value as BYTE_ORDER set by glibc in + * endian.h + */ + +#ifdef NPY_HAVE_ENDIAN_H + /* Use endian.h if available */ + #include + + #define NPY_BYTE_ORDER __BYTE_ORDER + #define NPY_LITTLE_ENDIAN __LITTLE_ENDIAN + #define NPY_BIG_ENDIAN __BIG_ENDIAN +#else + /* Set endianness info using target CPU */ + #include "npy_cpu.h" + + #define NPY_LITTLE_ENDIAN 1234 + #define NPY_BIG_ENDIAN 4321 + + #if defined(NPY_CPU_X86) \ + || defined(NPY_CPU_AMD64) \ + || defined(NPY_CPU_IA64) \ + || defined(NPY_CPU_ALPHA) \ + || defined(NPY_CPU_ARMEL) \ + || defined(NPY_CPU_AARCH64) \ + || defined(NPY_CPU_SH_LE) \ + || defined(NPY_CPU_MIPSEL) + #define NPY_BYTE_ORDER NPY_LITTLE_ENDIAN + #elif defined(NPY_CPU_PPC) \ + || defined(NPY_CPU_SPARC) \ + || defined(NPY_CPU_S390) \ + || defined(NPY_CPU_HPPA) \ + || defined(NPY_CPU_PPC64) \ + || defined(NPY_CPU_ARMEB) \ + || defined(NPY_CPU_SH_BE) \ + || defined(NPY_CPU_MIPSEB) + #define NPY_BYTE_ORDER NPY_BIG_ENDIAN + #else + #error Unknown CPU: can not set endianness + #endif +#endif + +#endif diff --git a/data_tooling/pii_processing/include/numpy/npy_interrupt.h b/data_tooling/pii_processing/include/numpy/npy_interrupt.h new file mode 100644 index 0000000..f71fd68 --- /dev/null +++ b/data_tooling/pii_processing/include/numpy/npy_interrupt.h @@ -0,0 +1,117 @@ + +/* Signal handling: + +This header file defines macros that allow your code to handle +interrupts received during processing. Interrupts that +could reasonably be handled: + +SIGINT, SIGABRT, SIGALRM, SIGSEGV + +****Warning*************** + +Do not allow code that creates temporary memory or increases reference +counts of Python objects to be interrupted unless you handle it +differently. + +************************** + +The mechanism for handling interrupts is conceptually simple: + + - replace the signal handler with our own home-grown version + and store the old one. + - run the code to be interrupted -- if an interrupt occurs + the handler should basically just cause a return to the + calling function for finish work. + - restore the old signal handler + +Of course, every code that allows interrupts must account for +returning via the interrupt and handle clean-up correctly. But, +even still, the simple paradigm is complicated by at least three +factors. + + 1) platform portability (i.e. Microsoft says not to use longjmp + to return from signal handling. They have a __try and __except + extension to C instead but what about mingw?). + + 2) how to handle threads: apparently whether signals are delivered to + every thread of the process or the "invoking" thread is platform + dependent. --- we don't handle threads for now. + + 3) do we need to worry about re-entrance. For now, assume the + code will not call-back into itself. + +Ideas: + + 1) Start by implementing an approach that works on platforms that + can use setjmp and longjmp functionality and does nothing + on other platforms. + + 2) Ignore threads --- i.e. do not mix interrupt handling and threads + + 3) Add a default signal_handler function to the C-API but have the rest + use macros. + + +Simple Interface: + + +In your C-extension: around a block of code you want to be interruptable +with a SIGINT + +NPY_SIGINT_ON +[code] +NPY_SIGINT_OFF + +In order for this to work correctly, the +[code] block must not allocate any memory or alter the reference count of any +Python objects. In other words [code] must be interruptible so that continuation +after NPY_SIGINT_OFF will only be "missing some computations" + +Interrupt handling does not work well with threads. + +*/ + +/* Add signal handling macros + Make the global variable and signal handler part of the C-API +*/ + +#ifndef NPY_INTERRUPT_H +#define NPY_INTERRUPT_H + +#ifndef NPY_NO_SIGNAL + +#include +#include + +#ifndef sigsetjmp + +#define NPY_SIGSETJMP(arg1, arg2) setjmp(arg1) +#define NPY_SIGLONGJMP(arg1, arg2) longjmp(arg1, arg2) +#define NPY_SIGJMP_BUF jmp_buf + +#else + +#define NPY_SIGSETJMP(arg1, arg2) sigsetjmp(arg1, arg2) +#define NPY_SIGLONGJMP(arg1, arg2) siglongjmp(arg1, arg2) +#define NPY_SIGJMP_BUF sigjmp_buf + +#endif + +# define NPY_SIGINT_ON { \ + PyOS_sighandler_t _npy_sig_save; \ + _npy_sig_save = PyOS_setsig(SIGINT, _PyArray_SigintHandler); \ + if (NPY_SIGSETJMP(*((NPY_SIGJMP_BUF *)_PyArray_GetSigintBuf()), \ + 1) == 0) { \ + +# define NPY_SIGINT_OFF } \ + PyOS_setsig(SIGINT, _npy_sig_save); \ + } + +#else /* NPY_NO_SIGNAL */ + +#define NPY_SIGINT_ON +#define NPY_SIGINT_OFF + +#endif /* HAVE_SIGSETJMP */ + +#endif /* NPY_INTERRUPT_H */ diff --git a/data_tooling/pii_processing/include/numpy/npy_math.h b/data_tooling/pii_processing/include/numpy/npy_math.h new file mode 100644 index 0000000..7ae166e --- /dev/null +++ b/data_tooling/pii_processing/include/numpy/npy_math.h @@ -0,0 +1,438 @@ +#ifndef __NPY_MATH_C99_H_ +#define __NPY_MATH_C99_H_ + +#include +#ifdef __SUNPRO_CC +#include +#endif +#include + +/* + * NAN and INFINITY like macros (same behavior as glibc for NAN, same as C99 + * for INFINITY) + * + * XXX: I should test whether INFINITY and NAN are available on the platform + */ +NPY_INLINE static float __npy_inff(void) +{ + const union { npy_uint32 __i; float __f;} __bint = {0x7f800000UL}; + return __bint.__f; +} + +NPY_INLINE static float __npy_nanf(void) +{ + const union { npy_uint32 __i; float __f;} __bint = {0x7fc00000UL}; + return __bint.__f; +} + +NPY_INLINE static float __npy_pzerof(void) +{ + const union { npy_uint32 __i; float __f;} __bint = {0x00000000UL}; + return __bint.__f; +} + +NPY_INLINE static float __npy_nzerof(void) +{ + const union { npy_uint32 __i; float __f;} __bint = {0x80000000UL}; + return __bint.__f; +} + +#define NPY_INFINITYF __npy_inff() +#define NPY_NANF __npy_nanf() +#define NPY_PZEROF __npy_pzerof() +#define NPY_NZEROF __npy_nzerof() + +#define NPY_INFINITY ((npy_double)NPY_INFINITYF) +#define NPY_NAN ((npy_double)NPY_NANF) +#define NPY_PZERO ((npy_double)NPY_PZEROF) +#define NPY_NZERO ((npy_double)NPY_NZEROF) + +#define NPY_INFINITYL ((npy_longdouble)NPY_INFINITYF) +#define NPY_NANL ((npy_longdouble)NPY_NANF) +#define NPY_PZEROL ((npy_longdouble)NPY_PZEROF) +#define NPY_NZEROL ((npy_longdouble)NPY_NZEROF) + +/* + * Useful constants + */ +#define NPY_E 2.718281828459045235360287471352662498 /* e */ +#define NPY_LOG2E 1.442695040888963407359924681001892137 /* log_2 e */ +#define NPY_LOG10E 0.434294481903251827651128918916605082 /* log_10 e */ +#define NPY_LOGE2 0.693147180559945309417232121458176568 /* log_e 2 */ +#define NPY_LOGE10 2.302585092994045684017991454684364208 /* log_e 10 */ +#define NPY_PI 3.141592653589793238462643383279502884 /* pi */ +#define NPY_PI_2 1.570796326794896619231321691639751442 /* pi/2 */ +#define NPY_PI_4 0.785398163397448309615660845819875721 /* pi/4 */ +#define NPY_1_PI 0.318309886183790671537767526745028724 /* 1/pi */ +#define NPY_2_PI 0.636619772367581343075535053490057448 /* 2/pi */ +#define NPY_EULER 0.577215664901532860606512090082402431 /* Euler constant */ +#define NPY_SQRT2 1.414213562373095048801688724209698079 /* sqrt(2) */ +#define NPY_SQRT1_2 0.707106781186547524400844362104849039 /* 1/sqrt(2) */ + +#define NPY_Ef 2.718281828459045235360287471352662498F /* e */ +#define NPY_LOG2Ef 1.442695040888963407359924681001892137F /* log_2 e */ +#define NPY_LOG10Ef 0.434294481903251827651128918916605082F /* log_10 e */ +#define NPY_LOGE2f 0.693147180559945309417232121458176568F /* log_e 2 */ +#define NPY_LOGE10f 2.302585092994045684017991454684364208F /* log_e 10 */ +#define NPY_PIf 3.141592653589793238462643383279502884F /* pi */ +#define NPY_PI_2f 1.570796326794896619231321691639751442F /* pi/2 */ +#define NPY_PI_4f 0.785398163397448309615660845819875721F /* pi/4 */ +#define NPY_1_PIf 0.318309886183790671537767526745028724F /* 1/pi */ +#define NPY_2_PIf 0.636619772367581343075535053490057448F /* 2/pi */ +#define NPY_EULERf 0.577215664901532860606512090082402431F /* Euler constan*/ +#define NPY_SQRT2f 1.414213562373095048801688724209698079F /* sqrt(2) */ +#define NPY_SQRT1_2f 0.707106781186547524400844362104849039F /* 1/sqrt(2) */ + +#define NPY_El 2.718281828459045235360287471352662498L /* e */ +#define NPY_LOG2El 1.442695040888963407359924681001892137L /* log_2 e */ +#define NPY_LOG10El 0.434294481903251827651128918916605082L /* log_10 e */ +#define NPY_LOGE2l 0.693147180559945309417232121458176568L /* log_e 2 */ +#define NPY_LOGE10l 2.302585092994045684017991454684364208L /* log_e 10 */ +#define NPY_PIl 3.141592653589793238462643383279502884L /* pi */ +#define NPY_PI_2l 1.570796326794896619231321691639751442L /* pi/2 */ +#define NPY_PI_4l 0.785398163397448309615660845819875721L /* pi/4 */ +#define NPY_1_PIl 0.318309886183790671537767526745028724L /* 1/pi */ +#define NPY_2_PIl 0.636619772367581343075535053490057448L /* 2/pi */ +#define NPY_EULERl 0.577215664901532860606512090082402431L /* Euler constan*/ +#define NPY_SQRT2l 1.414213562373095048801688724209698079L /* sqrt(2) */ +#define NPY_SQRT1_2l 0.707106781186547524400844362104849039L /* 1/sqrt(2) */ + +/* + * C99 double math funcs + */ +double npy_sin(double x); +double npy_cos(double x); +double npy_tan(double x); +double npy_sinh(double x); +double npy_cosh(double x); +double npy_tanh(double x); + +double npy_asin(double x); +double npy_acos(double x); +double npy_atan(double x); +double npy_aexp(double x); +double npy_alog(double x); +double npy_asqrt(double x); +double npy_afabs(double x); + +double npy_log(double x); +double npy_log10(double x); +double npy_exp(double x); +double npy_sqrt(double x); + +double npy_fabs(double x); +double npy_ceil(double x); +double npy_fmod(double x, double y); +double npy_floor(double x); + +double npy_expm1(double x); +double npy_log1p(double x); +double npy_hypot(double x, double y); +double npy_acosh(double x); +double npy_asinh(double xx); +double npy_atanh(double x); +double npy_rint(double x); +double npy_trunc(double x); +double npy_exp2(double x); +double npy_log2(double x); + +double npy_atan2(double x, double y); +double npy_pow(double x, double y); +double npy_modf(double x, double* y); + +double npy_copysign(double x, double y); +double npy_nextafter(double x, double y); +double npy_spacing(double x); + +/* + * IEEE 754 fpu handling. Those are guaranteed to be macros + */ +#ifndef NPY_HAVE_DECL_ISNAN + #define npy_isnan(x) ((x) != (x)) +#else + #ifdef _MSC_VER + #define npy_isnan(x) _isnan((x)) + #else + #define npy_isnan(x) isnan((x)) + #endif +#endif + +#ifndef NPY_HAVE_DECL_ISFINITE + #ifdef _MSC_VER + #define npy_isfinite(x) _finite((x)) + #else + #define npy_isfinite(x) !npy_isnan((x) + (-x)) + #endif +#else + #define npy_isfinite(x) isfinite((x)) +#endif + +#ifndef NPY_HAVE_DECL_ISINF + #define npy_isinf(x) (!npy_isfinite(x) && !npy_isnan(x)) +#else + #ifdef _MSC_VER + #define npy_isinf(x) (!_finite((x)) && !_isnan((x))) + #else + #define npy_isinf(x) isinf((x)) + #endif +#endif + +#ifndef NPY_HAVE_DECL_SIGNBIT + int _npy_signbit_f(float x); + int _npy_signbit_d(double x); + int _npy_signbit_ld(long double x); + #define npy_signbit(x) \ + (sizeof (x) == sizeof (long double) ? _npy_signbit_ld (x) \ + : sizeof (x) == sizeof (double) ? _npy_signbit_d (x) \ + : _npy_signbit_f (x)) +#else + #define npy_signbit(x) signbit((x)) +#endif + +/* + * float C99 math functions + */ + +float npy_sinf(float x); +float npy_cosf(float x); +float npy_tanf(float x); +float npy_sinhf(float x); +float npy_coshf(float x); +float npy_tanhf(float x); +float npy_fabsf(float x); +float npy_floorf(float x); +float npy_ceilf(float x); +float npy_rintf(float x); +float npy_truncf(float x); +float npy_sqrtf(float x); +float npy_log10f(float x); +float npy_logf(float x); +float npy_expf(float x); +float npy_expm1f(float x); +float npy_asinf(float x); +float npy_acosf(float x); +float npy_atanf(float x); +float npy_asinhf(float x); +float npy_acoshf(float x); +float npy_atanhf(float x); +float npy_log1pf(float x); +float npy_exp2f(float x); +float npy_log2f(float x); + +float npy_atan2f(float x, float y); +float npy_hypotf(float x, float y); +float npy_powf(float x, float y); +float npy_fmodf(float x, float y); + +float npy_modff(float x, float* y); + +float npy_copysignf(float x, float y); +float npy_nextafterf(float x, float y); +float npy_spacingf(float x); + +/* + * float C99 math functions + */ + +npy_longdouble npy_sinl(npy_longdouble x); +npy_longdouble npy_cosl(npy_longdouble x); +npy_longdouble npy_tanl(npy_longdouble x); +npy_longdouble npy_sinhl(npy_longdouble x); +npy_longdouble npy_coshl(npy_longdouble x); +npy_longdouble npy_tanhl(npy_longdouble x); +npy_longdouble npy_fabsl(npy_longdouble x); +npy_longdouble npy_floorl(npy_longdouble x); +npy_longdouble npy_ceill(npy_longdouble x); +npy_longdouble npy_rintl(npy_longdouble x); +npy_longdouble npy_truncl(npy_longdouble x); +npy_longdouble npy_sqrtl(npy_longdouble x); +npy_longdouble npy_log10l(npy_longdouble x); +npy_longdouble npy_logl(npy_longdouble x); +npy_longdouble npy_expl(npy_longdouble x); +npy_longdouble npy_expm1l(npy_longdouble x); +npy_longdouble npy_asinl(npy_longdouble x); +npy_longdouble npy_acosl(npy_longdouble x); +npy_longdouble npy_atanl(npy_longdouble x); +npy_longdouble npy_asinhl(npy_longdouble x); +npy_longdouble npy_acoshl(npy_longdouble x); +npy_longdouble npy_atanhl(npy_longdouble x); +npy_longdouble npy_log1pl(npy_longdouble x); +npy_longdouble npy_exp2l(npy_longdouble x); +npy_longdouble npy_log2l(npy_longdouble x); + +npy_longdouble npy_atan2l(npy_longdouble x, npy_longdouble y); +npy_longdouble npy_hypotl(npy_longdouble x, npy_longdouble y); +npy_longdouble npy_powl(npy_longdouble x, npy_longdouble y); +npy_longdouble npy_fmodl(npy_longdouble x, npy_longdouble y); + +npy_longdouble npy_modfl(npy_longdouble x, npy_longdouble* y); + +npy_longdouble npy_copysignl(npy_longdouble x, npy_longdouble y); +npy_longdouble npy_nextafterl(npy_longdouble x, npy_longdouble y); +npy_longdouble npy_spacingl(npy_longdouble x); + +/* + * Non standard functions + */ +double npy_deg2rad(double x); +double npy_rad2deg(double x); +double npy_logaddexp(double x, double y); +double npy_logaddexp2(double x, double y); + +float npy_deg2radf(float x); +float npy_rad2degf(float x); +float npy_logaddexpf(float x, float y); +float npy_logaddexp2f(float x, float y); + +npy_longdouble npy_deg2radl(npy_longdouble x); +npy_longdouble npy_rad2degl(npy_longdouble x); +npy_longdouble npy_logaddexpl(npy_longdouble x, npy_longdouble y); +npy_longdouble npy_logaddexp2l(npy_longdouble x, npy_longdouble y); + +#define npy_degrees npy_rad2deg +#define npy_degreesf npy_rad2degf +#define npy_degreesl npy_rad2degl + +#define npy_radians npy_deg2rad +#define npy_radiansf npy_deg2radf +#define npy_radiansl npy_deg2radl + +/* + * Complex declarations + */ + +/* + * C99 specifies that complex numbers have the same representation as + * an array of two elements, where the first element is the real part + * and the second element is the imaginary part. + */ +#define __NPY_CPACK_IMP(x, y, type, ctype) \ + union { \ + ctype z; \ + type a[2]; \ + } z1;; \ + \ + z1.a[0] = (x); \ + z1.a[1] = (y); \ + \ + return z1.z; + +static NPY_INLINE npy_cdouble npy_cpack(double x, double y) +{ + __NPY_CPACK_IMP(x, y, double, npy_cdouble); +} + +static NPY_INLINE npy_cfloat npy_cpackf(float x, float y) +{ + __NPY_CPACK_IMP(x, y, float, npy_cfloat); +} + +static NPY_INLINE npy_clongdouble npy_cpackl(npy_longdouble x, npy_longdouble y) +{ + __NPY_CPACK_IMP(x, y, npy_longdouble, npy_clongdouble); +} +#undef __NPY_CPACK_IMP + +/* + * Same remark as above, but in the other direction: extract first/second + * member of complex number, assuming a C99-compatible representation + * + * Those are defineds as static inline, and such as a reasonable compiler would + * most likely compile this to one or two instructions (on CISC at least) + */ +#define __NPY_CEXTRACT_IMP(z, index, type, ctype) \ + union { \ + ctype z; \ + type a[2]; \ + } __z_repr; \ + __z_repr.z = z; \ + \ + return __z_repr.a[index]; + +static NPY_INLINE double npy_creal(npy_cdouble z) +{ + __NPY_CEXTRACT_IMP(z, 0, double, npy_cdouble); +} + +static NPY_INLINE double npy_cimag(npy_cdouble z) +{ + __NPY_CEXTRACT_IMP(z, 1, double, npy_cdouble); +} + +static NPY_INLINE float npy_crealf(npy_cfloat z) +{ + __NPY_CEXTRACT_IMP(z, 0, float, npy_cfloat); +} + +static NPY_INLINE float npy_cimagf(npy_cfloat z) +{ + __NPY_CEXTRACT_IMP(z, 1, float, npy_cfloat); +} + +static NPY_INLINE npy_longdouble npy_creall(npy_clongdouble z) +{ + __NPY_CEXTRACT_IMP(z, 0, npy_longdouble, npy_clongdouble); +} + +static NPY_INLINE npy_longdouble npy_cimagl(npy_clongdouble z) +{ + __NPY_CEXTRACT_IMP(z, 1, npy_longdouble, npy_clongdouble); +} +#undef __NPY_CEXTRACT_IMP + +/* + * Double precision complex functions + */ +double npy_cabs(npy_cdouble z); +double npy_carg(npy_cdouble z); + +npy_cdouble npy_cexp(npy_cdouble z); +npy_cdouble npy_clog(npy_cdouble z); +npy_cdouble npy_cpow(npy_cdouble x, npy_cdouble y); + +npy_cdouble npy_csqrt(npy_cdouble z); + +npy_cdouble npy_ccos(npy_cdouble z); +npy_cdouble npy_csin(npy_cdouble z); + +/* + * Single precision complex functions + */ +float npy_cabsf(npy_cfloat z); +float npy_cargf(npy_cfloat z); + +npy_cfloat npy_cexpf(npy_cfloat z); +npy_cfloat npy_clogf(npy_cfloat z); +npy_cfloat npy_cpowf(npy_cfloat x, npy_cfloat y); + +npy_cfloat npy_csqrtf(npy_cfloat z); + +npy_cfloat npy_ccosf(npy_cfloat z); +npy_cfloat npy_csinf(npy_cfloat z); + +/* + * Extended precision complex functions + */ +npy_longdouble npy_cabsl(npy_clongdouble z); +npy_longdouble npy_cargl(npy_clongdouble z); + +npy_clongdouble npy_cexpl(npy_clongdouble z); +npy_clongdouble npy_clogl(npy_clongdouble z); +npy_clongdouble npy_cpowl(npy_clongdouble x, npy_clongdouble y); + +npy_clongdouble npy_csqrtl(npy_clongdouble z); + +npy_clongdouble npy_ccosl(npy_clongdouble z); +npy_clongdouble npy_csinl(npy_clongdouble z); + +/* + * Functions that set the floating point error + * status word. + */ + +void npy_set_floatstatus_divbyzero(void); +void npy_set_floatstatus_overflow(void); +void npy_set_floatstatus_underflow(void); +void npy_set_floatstatus_invalid(void); + +#endif diff --git a/data_tooling/pii_processing/include/numpy/npy_no_deprecated_api.h b/data_tooling/pii_processing/include/numpy/npy_no_deprecated_api.h new file mode 100644 index 0000000..6183dc2 --- /dev/null +++ b/data_tooling/pii_processing/include/numpy/npy_no_deprecated_api.h @@ -0,0 +1,19 @@ +/* + * This include file is provided for inclusion in Cython *.pyd files where + * one would like to define the NPY_NO_DEPRECATED_API macro. It can be + * included by + * + * cdef extern from "npy_no_deprecated_api.h": pass + * + */ +#ifndef NPY_NO_DEPRECATED_API + +/* put this check here since there may be multiple includes in C extensions. */ +#if defined(NDARRAYTYPES_H) || defined(_NPY_DEPRECATED_API_H) || \ + defined(OLD_DEFINES_H) +#error "npy_no_deprecated_api.h" must be first among numpy includes. +#else +#define NPY_NO_DEPRECATED_API NPY_API_VERSION +#endif + +#endif diff --git a/data_tooling/pii_processing/include/numpy/npy_os.h b/data_tooling/pii_processing/include/numpy/npy_os.h new file mode 100644 index 0000000..9228c39 --- /dev/null +++ b/data_tooling/pii_processing/include/numpy/npy_os.h @@ -0,0 +1,30 @@ +#ifndef _NPY_OS_H_ +#define _NPY_OS_H_ + +#if defined(linux) || defined(__linux) || defined(__linux__) + #define NPY_OS_LINUX +#elif defined(__FreeBSD__) || defined(__NetBSD__) || \ + defined(__OpenBSD__) || defined(__DragonFly__) + #define NPY_OS_BSD + #ifdef __FreeBSD__ + #define NPY_OS_FREEBSD + #elif defined(__NetBSD__) + #define NPY_OS_NETBSD + #elif defined(__OpenBSD__) + #define NPY_OS_OPENBSD + #elif defined(__DragonFly__) + #define NPY_OS_DRAGONFLY + #endif +#elif defined(sun) || defined(__sun) + #define NPY_OS_SOLARIS +#elif defined(__CYGWIN__) + #define NPY_OS_CYGWIN +#elif defined(_WIN32) || defined(__WIN32__) || defined(WIN32) + #define NPY_OS_WIN32 +#elif defined(__APPLE__) + #define NPY_OS_DARWIN +#else + #define NPY_OS_UNKNOWN +#endif + +#endif diff --git a/data_tooling/pii_processing/include/numpy/numpyconfig.h b/data_tooling/pii_processing/include/numpy/numpyconfig.h new file mode 100644 index 0000000..401d19f --- /dev/null +++ b/data_tooling/pii_processing/include/numpy/numpyconfig.h @@ -0,0 +1,33 @@ +#ifndef _NPY_NUMPYCONFIG_H_ +#define _NPY_NUMPYCONFIG_H_ + +#include "_numpyconfig.h" + +/* + * On Mac OS X, because there is only one configuration stage for all the archs + * in universal builds, any macro which depends on the arch needs to be + * harcoded + */ +#ifdef __APPLE__ + #undef NPY_SIZEOF_LONG + #undef NPY_SIZEOF_PY_INTPTR_T + + #ifdef __LP64__ + #define NPY_SIZEOF_LONG 8 + #define NPY_SIZEOF_PY_INTPTR_T 8 + #else + #define NPY_SIZEOF_LONG 4 + #define NPY_SIZEOF_PY_INTPTR_T 4 + #endif +#endif + +/** + * To help with the NPY_NO_DEPRECATED_API macro, we include API version + * numbers for specific versions of NumPy. To exclude all API that was + * deprecated as of 1.7, add the following before #including any NumPy + * headers: + * #define NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION + */ +#define NPY_1_7_API_VERSION 0x00000007 + +#endif diff --git a/data_tooling/pii_processing/include/numpy/old_defines.h b/data_tooling/pii_processing/include/numpy/old_defines.h new file mode 100644 index 0000000..abf8159 --- /dev/null +++ b/data_tooling/pii_processing/include/numpy/old_defines.h @@ -0,0 +1,187 @@ +/* This header is deprecated as of NumPy 1.7 */ +#ifndef OLD_DEFINES_H +#define OLD_DEFINES_H + +#if defined(NPY_NO_DEPRECATED_API) && NPY_NO_DEPRECATED_API >= NPY_1_7_API_VERSION +#error The header "old_defines.h" is deprecated as of NumPy 1.7. +#endif + +#define NDARRAY_VERSION NPY_VERSION + +#define PyArray_MIN_BUFSIZE NPY_MIN_BUFSIZE +#define PyArray_MAX_BUFSIZE NPY_MAX_BUFSIZE +#define PyArray_BUFSIZE NPY_BUFSIZE + +#define PyArray_PRIORITY NPY_PRIORITY +#define PyArray_SUBTYPE_PRIORITY NPY_PRIORITY +#define PyArray_NUM_FLOATTYPE NPY_NUM_FLOATTYPE + +#define NPY_MAX PyArray_MAX +#define NPY_MIN PyArray_MIN + +#define PyArray_TYPES NPY_TYPES +#define PyArray_BOOL NPY_BOOL +#define PyArray_BYTE NPY_BYTE +#define PyArray_UBYTE NPY_UBYTE +#define PyArray_SHORT NPY_SHORT +#define PyArray_USHORT NPY_USHORT +#define PyArray_INT NPY_INT +#define PyArray_UINT NPY_UINT +#define PyArray_LONG NPY_LONG +#define PyArray_ULONG NPY_ULONG +#define PyArray_LONGLONG NPY_LONGLONG +#define PyArray_ULONGLONG NPY_ULONGLONG +#define PyArray_HALF NPY_HALF +#define PyArray_FLOAT NPY_FLOAT +#define PyArray_DOUBLE NPY_DOUBLE +#define PyArray_LONGDOUBLE NPY_LONGDOUBLE +#define PyArray_CFLOAT NPY_CFLOAT +#define PyArray_CDOUBLE NPY_CDOUBLE +#define PyArray_CLONGDOUBLE NPY_CLONGDOUBLE +#define PyArray_OBJECT NPY_OBJECT +#define PyArray_STRING NPY_STRING +#define PyArray_UNICODE NPY_UNICODE +#define PyArray_VOID NPY_VOID +#define PyArray_DATETIME NPY_DATETIME +#define PyArray_TIMEDELTA NPY_TIMEDELTA +#define PyArray_NTYPES NPY_NTYPES +#define PyArray_NOTYPE NPY_NOTYPE +#define PyArray_CHAR NPY_CHAR +#define PyArray_USERDEF NPY_USERDEF +#define PyArray_NUMUSERTYPES NPY_NUMUSERTYPES + +#define PyArray_INTP NPY_INTP +#define PyArray_UINTP NPY_UINTP + +#define PyArray_INT8 NPY_INT8 +#define PyArray_UINT8 NPY_UINT8 +#define PyArray_INT16 NPY_INT16 +#define PyArray_UINT16 NPY_UINT16 +#define PyArray_INT32 NPY_INT32 +#define PyArray_UINT32 NPY_UINT32 + +#ifdef NPY_INT64 +#define PyArray_INT64 NPY_INT64 +#define PyArray_UINT64 NPY_UINT64 +#endif + +#ifdef NPY_INT128 +#define PyArray_INT128 NPY_INT128 +#define PyArray_UINT128 NPY_UINT128 +#endif + +#ifdef NPY_FLOAT16 +#define PyArray_FLOAT16 NPY_FLOAT16 +#define PyArray_COMPLEX32 NPY_COMPLEX32 +#endif + +#ifdef NPY_FLOAT80 +#define PyArray_FLOAT80 NPY_FLOAT80 +#define PyArray_COMPLEX160 NPY_COMPLEX160 +#endif + +#ifdef NPY_FLOAT96 +#define PyArray_FLOAT96 NPY_FLOAT96 +#define PyArray_COMPLEX192 NPY_COMPLEX192 +#endif + +#ifdef NPY_FLOAT128 +#define PyArray_FLOAT128 NPY_FLOAT128 +#define PyArray_COMPLEX256 NPY_COMPLEX256 +#endif + +#define PyArray_FLOAT32 NPY_FLOAT32 +#define PyArray_COMPLEX64 NPY_COMPLEX64 +#define PyArray_FLOAT64 NPY_FLOAT64 +#define PyArray_COMPLEX128 NPY_COMPLEX128 + + +#define PyArray_TYPECHAR NPY_TYPECHAR +#define PyArray_BOOLLTR NPY_BOOLLTR +#define PyArray_BYTELTR NPY_BYTELTR +#define PyArray_UBYTELTR NPY_UBYTELTR +#define PyArray_SHORTLTR NPY_SHORTLTR +#define PyArray_USHORTLTR NPY_USHORTLTR +#define PyArray_INTLTR NPY_INTLTR +#define PyArray_UINTLTR NPY_UINTLTR +#define PyArray_LONGLTR NPY_LONGLTR +#define PyArray_ULONGLTR NPY_ULONGLTR +#define PyArray_LONGLONGLTR NPY_LONGLONGLTR +#define PyArray_ULONGLONGLTR NPY_ULONGLONGLTR +#define PyArray_HALFLTR NPY_HALFLTR +#define PyArray_FLOATLTR NPY_FLOATLTR +#define PyArray_DOUBLELTR NPY_DOUBLELTR +#define PyArray_LONGDOUBLELTR NPY_LONGDOUBLELTR +#define PyArray_CFLOATLTR NPY_CFLOATLTR +#define PyArray_CDOUBLELTR NPY_CDOUBLELTR +#define PyArray_CLONGDOUBLELTR NPY_CLONGDOUBLELTR +#define PyArray_OBJECTLTR NPY_OBJECTLTR +#define PyArray_STRINGLTR NPY_STRINGLTR +#define PyArray_STRINGLTR2 NPY_STRINGLTR2 +#define PyArray_UNICODELTR NPY_UNICODELTR +#define PyArray_VOIDLTR NPY_VOIDLTR +#define PyArray_DATETIMELTR NPY_DATETIMELTR +#define PyArray_TIMEDELTALTR NPY_TIMEDELTALTR +#define PyArray_CHARLTR NPY_CHARLTR +#define PyArray_INTPLTR NPY_INTPLTR +#define PyArray_UINTPLTR NPY_UINTPLTR +#define PyArray_GENBOOLLTR NPY_GENBOOLLTR +#define PyArray_SIGNEDLTR NPY_SIGNEDLTR +#define PyArray_UNSIGNEDLTR NPY_UNSIGNEDLTR +#define PyArray_FLOATINGLTR NPY_FLOATINGLTR +#define PyArray_COMPLEXLTR NPY_COMPLEXLTR + +#define PyArray_QUICKSORT NPY_QUICKSORT +#define PyArray_HEAPSORT NPY_HEAPSORT +#define PyArray_MERGESORT NPY_MERGESORT +#define PyArray_SORTKIND NPY_SORTKIND +#define PyArray_NSORTS NPY_NSORTS + +#define PyArray_NOSCALAR NPY_NOSCALAR +#define PyArray_BOOL_SCALAR NPY_BOOL_SCALAR +#define PyArray_INTPOS_SCALAR NPY_INTPOS_SCALAR +#define PyArray_INTNEG_SCALAR NPY_INTNEG_SCALAR +#define PyArray_FLOAT_SCALAR NPY_FLOAT_SCALAR +#define PyArray_COMPLEX_SCALAR NPY_COMPLEX_SCALAR +#define PyArray_OBJECT_SCALAR NPY_OBJECT_SCALAR +#define PyArray_SCALARKIND NPY_SCALARKIND +#define PyArray_NSCALARKINDS NPY_NSCALARKINDS + +#define PyArray_ANYORDER NPY_ANYORDER +#define PyArray_CORDER NPY_CORDER +#define PyArray_FORTRANORDER NPY_FORTRANORDER +#define PyArray_ORDER NPY_ORDER + +#define PyDescr_ISBOOL PyDataType_ISBOOL +#define PyDescr_ISUNSIGNED PyDataType_ISUNSIGNED +#define PyDescr_ISSIGNED PyDataType_ISSIGNED +#define PyDescr_ISINTEGER PyDataType_ISINTEGER +#define PyDescr_ISFLOAT PyDataType_ISFLOAT +#define PyDescr_ISNUMBER PyDataType_ISNUMBER +#define PyDescr_ISSTRING PyDataType_ISSTRING +#define PyDescr_ISCOMPLEX PyDataType_ISCOMPLEX +#define PyDescr_ISPYTHON PyDataType_ISPYTHON +#define PyDescr_ISFLEXIBLE PyDataType_ISFLEXIBLE +#define PyDescr_ISUSERDEF PyDataType_ISUSERDEF +#define PyDescr_ISEXTENDED PyDataType_ISEXTENDED +#define PyDescr_ISOBJECT PyDataType_ISOBJECT +#define PyDescr_HASFIELDS PyDataType_HASFIELDS + +#define PyArray_LITTLE NPY_LITTLE +#define PyArray_BIG NPY_BIG +#define PyArray_NATIVE NPY_NATIVE +#define PyArray_SWAP NPY_SWAP +#define PyArray_IGNORE NPY_IGNORE + +#define PyArray_NATBYTE NPY_NATBYTE +#define PyArray_OPPBYTE NPY_OPPBYTE + +#define PyArray_MAX_ELSIZE NPY_MAX_ELSIZE + +#define PyArray_USE_PYMEM NPY_USE_PYMEM + +#define PyArray_RemoveLargest PyArray_RemoveSmallest + +#define PyArray_UCS4 npy_ucs4 + +#endif diff --git a/data_tooling/pii_processing/include/numpy/oldnumeric.h b/data_tooling/pii_processing/include/numpy/oldnumeric.h new file mode 100644 index 0000000..748f06d --- /dev/null +++ b/data_tooling/pii_processing/include/numpy/oldnumeric.h @@ -0,0 +1,23 @@ +#include "arrayobject.h" + +#ifndef REFCOUNT +# define REFCOUNT NPY_REFCOUNT +# define MAX_ELSIZE 16 +#endif + +#define PyArray_UNSIGNED_TYPES +#define PyArray_SBYTE NPY_BYTE +#define PyArray_CopyArray PyArray_CopyInto +#define _PyArray_multiply_list PyArray_MultiplyIntList +#define PyArray_ISSPACESAVER(m) NPY_FALSE +#define PyScalarArray_Check PyArray_CheckScalar + +#define CONTIGUOUS NPY_CONTIGUOUS +#define OWN_DIMENSIONS 0 +#define OWN_STRIDES 0 +#define OWN_DATA NPY_OWNDATA +#define SAVESPACE 0 +#define SAVESPACEBIT 0 + +#undef import_array +#define import_array() { if (_import_array() < 0) {PyErr_Print(); PyErr_SetString(PyExc_ImportError, "numpy.core.multiarray failed to import"); } } diff --git a/data_tooling/pii_processing/include/numpy/ufunc_api.txt b/data_tooling/pii_processing/include/numpy/ufunc_api.txt new file mode 100644 index 0000000..3365433 --- /dev/null +++ b/data_tooling/pii_processing/include/numpy/ufunc_api.txt @@ -0,0 +1,312 @@ + +================= +Numpy Ufunc C-API +================= +:: + + PyObject * + PyUFunc_FromFuncAndData(PyUFuncGenericFunction *func, void + **data, char *types, int ntypes, int nin, int + nout, int identity, char *name, char *doc, int + check_return) + + +:: + + int + PyUFunc_RegisterLoopForType(PyUFuncObject *ufunc, int + usertype, PyUFuncGenericFunction + function, int *arg_types, void *data) + + +:: + + int + PyUFunc_GenericFunction(PyUFuncObject *ufunc, PyObject *args, PyObject + *kwds, PyArrayObject **op) + + +This generic function is called with the ufunc object, the arguments to it, +and an array of (pointers to) PyArrayObjects which are NULL. + +'op' is an array of at least NPY_MAXARGS PyArrayObject *. + +:: + + void + PyUFunc_f_f_As_d_d(char **args, npy_intp *dimensions, npy_intp + *steps, void *func) + + +:: + + void + PyUFunc_d_d(char **args, npy_intp *dimensions, npy_intp *steps, void + *func) + + +:: + + void + PyUFunc_f_f(char **args, npy_intp *dimensions, npy_intp *steps, void + *func) + + +:: + + void + PyUFunc_g_g(char **args, npy_intp *dimensions, npy_intp *steps, void + *func) + + +:: + + void + PyUFunc_F_F_As_D_D(char **args, npy_intp *dimensions, npy_intp + *steps, void *func) + + +:: + + void + PyUFunc_F_F(char **args, npy_intp *dimensions, npy_intp *steps, void + *func) + + +:: + + void + PyUFunc_D_D(char **args, npy_intp *dimensions, npy_intp *steps, void + *func) + + +:: + + void + PyUFunc_G_G(char **args, npy_intp *dimensions, npy_intp *steps, void + *func) + + +:: + + void + PyUFunc_O_O(char **args, npy_intp *dimensions, npy_intp *steps, void + *func) + + +:: + + void + PyUFunc_ff_f_As_dd_d(char **args, npy_intp *dimensions, npy_intp + *steps, void *func) + + +:: + + void + PyUFunc_ff_f(char **args, npy_intp *dimensions, npy_intp *steps, void + *func) + + +:: + + void + PyUFunc_dd_d(char **args, npy_intp *dimensions, npy_intp *steps, void + *func) + + +:: + + void + PyUFunc_gg_g(char **args, npy_intp *dimensions, npy_intp *steps, void + *func) + + +:: + + void + PyUFunc_FF_F_As_DD_D(char **args, npy_intp *dimensions, npy_intp + *steps, void *func) + + +:: + + void + PyUFunc_DD_D(char **args, npy_intp *dimensions, npy_intp *steps, void + *func) + + +:: + + void + PyUFunc_FF_F(char **args, npy_intp *dimensions, npy_intp *steps, void + *func) + + +:: + + void + PyUFunc_GG_G(char **args, npy_intp *dimensions, npy_intp *steps, void + *func) + + +:: + + void + PyUFunc_OO_O(char **args, npy_intp *dimensions, npy_intp *steps, void + *func) + + +:: + + void + PyUFunc_O_O_method(char **args, npy_intp *dimensions, npy_intp + *steps, void *func) + + +:: + + void + PyUFunc_OO_O_method(char **args, npy_intp *dimensions, npy_intp + *steps, void *func) + + +:: + + void + PyUFunc_On_Om(char **args, npy_intp *dimensions, npy_intp *steps, void + *func) + + +:: + + int + PyUFunc_GetPyValues(char *name, int *bufsize, int *errmask, PyObject + **errobj) + + +On return, if errobj is populated with a non-NULL value, the caller +owns a new reference to errobj. + +:: + + int + PyUFunc_checkfperr(int errmask, PyObject *errobj, int *first) + + +:: + + void + PyUFunc_clearfperr() + + +:: + + int + PyUFunc_getfperr(void ) + + +:: + + int + PyUFunc_handlefperr(int errmask, PyObject *errobj, int retstatus, int + *first) + + +:: + + int + PyUFunc_ReplaceLoopBySignature(PyUFuncObject + *func, PyUFuncGenericFunction + newfunc, int + *signature, PyUFuncGenericFunction + *oldfunc) + + +:: + + PyObject * + PyUFunc_FromFuncAndDataAndSignature(PyUFuncGenericFunction *func, void + **data, char *types, int + ntypes, int nin, int nout, int + identity, char *name, char + *doc, int check_return, const char + *signature) + + +:: + + int + PyUFunc_SetUsesArraysAsData(void **data, size_t i) + + +:: + + void + PyUFunc_e_e(char **args, npy_intp *dimensions, npy_intp *steps, void + *func) + + +:: + + void + PyUFunc_e_e_As_f_f(char **args, npy_intp *dimensions, npy_intp + *steps, void *func) + + +:: + + void + PyUFunc_e_e_As_d_d(char **args, npy_intp *dimensions, npy_intp + *steps, void *func) + + +:: + + void + PyUFunc_ee_e(char **args, npy_intp *dimensions, npy_intp *steps, void + *func) + + +:: + + void + PyUFunc_ee_e_As_ff_f(char **args, npy_intp *dimensions, npy_intp + *steps, void *func) + + +:: + + void + PyUFunc_ee_e_As_dd_d(char **args, npy_intp *dimensions, npy_intp + *steps, void *func) + + +:: + + int + PyUFunc_DefaultTypeResolver(PyUFuncObject *ufunc, NPY_CASTING + casting, PyArrayObject + **operands, PyObject + *type_tup, PyArray_Descr **out_dtypes) + + +This function applies the default type resolution rules +for the provided ufunc. + +Returns 0 on success, -1 on error. + +:: + + int + PyUFunc_ValidateCasting(PyUFuncObject *ufunc, NPY_CASTING + casting, PyArrayObject + **operands, PyArray_Descr **dtypes) + + +Validates that the input operands can be cast to +the input types, and the output types can be cast to +the output operands where provided. + +Returns 0 on success, -1 (with exception raised) on validation failure. + diff --git a/data_tooling/pii_processing/include/numpy/ufuncobject.h b/data_tooling/pii_processing/include/numpy/ufuncobject.h new file mode 100644 index 0000000..95afd5a --- /dev/null +++ b/data_tooling/pii_processing/include/numpy/ufuncobject.h @@ -0,0 +1,446 @@ +#ifndef Py_UFUNCOBJECT_H +#define Py_UFUNCOBJECT_H + +#include + +#ifdef __cplusplus +extern "C" { +#endif + +/* + * The legacy generic inner loop for a standard element-wise or + * generalized ufunc. + */ +typedef void (*PyUFuncGenericFunction) + (char **args, + npy_intp *dimensions, + npy_intp *strides, + void *innerloopdata); + +/* + * The most generic one-dimensional inner loop for + * a standard element-wise ufunc. This typedef is also + * more consistent with the other NumPy function pointer typedefs + * than PyUFuncGenericFunction. + */ +typedef void (PyUFunc_StridedInnerLoopFunc)( + char **dataptrs, npy_intp *strides, + npy_intp count, + NpyAuxData *innerloopdata); + +/* + * The most generic one-dimensional inner loop for + * a masked standard element-wise ufunc. "Masked" here means that it skips + * doing calculations on any items for which the maskptr array has a true + * value. + */ +typedef void (PyUFunc_MaskedStridedInnerLoopFunc)( + char **dataptrs, npy_intp *strides, + char *maskptr, npy_intp mask_stride, + npy_intp count, + NpyAuxData *innerloopdata); + +/* Forward declaration for the type resolver and loop selector typedefs */ +struct _tagPyUFuncObject; + +/* + * Given the operands for calling a ufunc, should determine the + * calculation input and output data types and return an inner loop function. + * This function should validate that the casting rule is being followed, + * and fail if it is not. + * + * For backwards compatibility, the regular type resolution function does not + * support auxiliary data with object semantics. The type resolution call + * which returns a masked generic function returns a standard NpyAuxData + * object, for which the NPY_AUXDATA_FREE and NPY_AUXDATA_CLONE macros + * work. + * + * ufunc: The ufunc object. + * casting: The 'casting' parameter provided to the ufunc. + * operands: An array of length (ufunc->nin + ufunc->nout), + * with the output parameters possibly NULL. + * type_tup: Either NULL, or the type_tup passed to the ufunc. + * out_dtypes: An array which should be populated with new + * references to (ufunc->nin + ufunc->nout) new + * dtypes, one for each input and output. These + * dtypes should all be in native-endian format. + * + * Should return 0 on success, -1 on failure (with exception set), + * or -2 if Py_NotImplemented should be returned. + */ +typedef int (PyUFunc_TypeResolutionFunc)( + struct _tagPyUFuncObject *ufunc, + NPY_CASTING casting, + PyArrayObject **operands, + PyObject *type_tup, + PyArray_Descr **out_dtypes); + +/* + * Given an array of DTypes as returned by the PyUFunc_TypeResolutionFunc, + * and an array of fixed strides (the array will contain NPY_MAX_INTP for + * strides which are not necessarily fixed), returns an inner loop + * with associated auxiliary data. + * + * For backwards compatibility, there is a variant of the inner loop + * selection which returns an inner loop irrespective of the strides, + * and with a void* static auxiliary data instead of an NpyAuxData * + * dynamically allocatable auxiliary data. + * + * ufunc: The ufunc object. + * dtypes: An array which has been populated with dtypes, + * in most cases by the type resolution funciton + * for the same ufunc. + * fixed_strides: For each input/output, either the stride that + * will be used every time the function is called + * or NPY_MAX_INTP if the stride might change or + * is not known ahead of time. The loop selection + * function may use this stride to pick inner loops + * which are optimized for contiguous or 0-stride + * cases. + * out_innerloop: Should be populated with the correct ufunc inner + * loop for the given type. + * out_innerloopdata: Should be populated with the void* data to + * be passed into the out_innerloop function. + * out_needs_api: If the inner loop needs to use the Python API, + * should set the to 1, otherwise should leave + * this untouched. + */ +typedef int (PyUFunc_LegacyInnerLoopSelectionFunc)( + struct _tagPyUFuncObject *ufunc, + PyArray_Descr **dtypes, + PyUFuncGenericFunction *out_innerloop, + void **out_innerloopdata, + int *out_needs_api); +typedef int (PyUFunc_InnerLoopSelectionFunc)( + struct _tagPyUFuncObject *ufunc, + PyArray_Descr **dtypes, + npy_intp *fixed_strides, + PyUFunc_StridedInnerLoopFunc **out_innerloop, + NpyAuxData **out_innerloopdata, + int *out_needs_api); +typedef int (PyUFunc_MaskedInnerLoopSelectionFunc)( + struct _tagPyUFuncObject *ufunc, + PyArray_Descr **dtypes, + PyArray_Descr *mask_dtype, + npy_intp *fixed_strides, + npy_intp fixed_mask_stride, + PyUFunc_MaskedStridedInnerLoopFunc **out_innerloop, + NpyAuxData **out_innerloopdata, + int *out_needs_api); + +typedef struct _tagPyUFuncObject { + PyObject_HEAD + /* + * nin: Number of inputs + * nout: Number of outputs + * nargs: Always nin + nout (Why is it stored?) + */ + int nin, nout, nargs; + + /* Identity for reduction, either PyUFunc_One or PyUFunc_Zero */ + int identity; + + /* Array of one-dimensional core loops */ + PyUFuncGenericFunction *functions; + /* Array of funcdata that gets passed into the functions */ + void **data; + /* The number of elements in 'functions' and 'data' */ + int ntypes; + + /* Does not appear to be used */ + int check_return; + + /* The name of the ufunc */ + char *name; + + /* Array of type numbers, of size ('nargs' * 'ntypes') */ + char *types; + + /* Documentation string */ + char *doc; + + void *ptr; + PyObject *obj; + PyObject *userloops; + + /* generalized ufunc parameters */ + + /* 0 for scalar ufunc; 1 for generalized ufunc */ + int core_enabled; + /* number of distinct dimension names in signature */ + int core_num_dim_ix; + + /* + * dimension indices of input/output argument k are stored in + * core_dim_ixs[core_offsets[k]..core_offsets[k]+core_num_dims[k]-1] + */ + + /* numbers of core dimensions of each argument */ + int *core_num_dims; + /* + * dimension indices in a flatted form; indices + * are in the range of [0,core_num_dim_ix) + */ + int *core_dim_ixs; + /* + * positions of 1st core dimensions of each + * argument in core_dim_ixs + */ + int *core_offsets; + /* signature string for printing purpose */ + char *core_signature; + + /* + * A function which resolves the types and fills an array + * with the dtypes for the inputs and outputs. + */ + PyUFunc_TypeResolutionFunc *type_resolver; + /* + * A function which returns an inner loop written for + * NumPy 1.6 and earlier ufuncs. This is for backwards + * compatibility, and may be NULL if inner_loop_selector + * is specified. + */ + PyUFunc_LegacyInnerLoopSelectionFunc *legacy_inner_loop_selector; + /* + * A function which returns an inner loop for the new mechanism + * in NumPy 1.7 and later. If provided, this is used, otherwise + * if NULL the legacy_inner_loop_selector is used instead. + */ + PyUFunc_InnerLoopSelectionFunc *inner_loop_selector; + /* + * A function which returns a masked inner loop for the ufunc. + */ + PyUFunc_MaskedInnerLoopSelectionFunc *masked_inner_loop_selector; +} PyUFuncObject; + +#include "arrayobject.h" + +#define UFUNC_ERR_IGNORE 0 +#define UFUNC_ERR_WARN 1 +#define UFUNC_ERR_RAISE 2 +#define UFUNC_ERR_CALL 3 +#define UFUNC_ERR_PRINT 4 +#define UFUNC_ERR_LOG 5 + + /* Python side integer mask */ + +#define UFUNC_MASK_DIVIDEBYZERO 0x07 +#define UFUNC_MASK_OVERFLOW 0x3f +#define UFUNC_MASK_UNDERFLOW 0x1ff +#define UFUNC_MASK_INVALID 0xfff + +#define UFUNC_SHIFT_DIVIDEBYZERO 0 +#define UFUNC_SHIFT_OVERFLOW 3 +#define UFUNC_SHIFT_UNDERFLOW 6 +#define UFUNC_SHIFT_INVALID 9 + + +/* platform-dependent code translates floating point + status to an integer sum of these values +*/ +#define UFUNC_FPE_DIVIDEBYZERO 1 +#define UFUNC_FPE_OVERFLOW 2 +#define UFUNC_FPE_UNDERFLOW 4 +#define UFUNC_FPE_INVALID 8 + +/* Error mode that avoids look-up (no checking) */ +#define UFUNC_ERR_DEFAULT 0 + +#define UFUNC_OBJ_ISOBJECT 1 +#define UFUNC_OBJ_NEEDS_API 2 + + /* Default user error mode */ +#define UFUNC_ERR_DEFAULT2 \ + (UFUNC_ERR_WARN << UFUNC_SHIFT_DIVIDEBYZERO) + \ + (UFUNC_ERR_WARN << UFUNC_SHIFT_OVERFLOW) + \ + (UFUNC_ERR_WARN << UFUNC_SHIFT_INVALID) + +#if NPY_ALLOW_THREADS +#define NPY_LOOP_BEGIN_THREADS do {if (!(loop->obj & UFUNC_OBJ_NEEDS_API)) _save = PyEval_SaveThread();} while (0); +#define NPY_LOOP_END_THREADS do {if (!(loop->obj & UFUNC_OBJ_NEEDS_API)) PyEval_RestoreThread(_save);} while (0); +#else +#define NPY_LOOP_BEGIN_THREADS +#define NPY_LOOP_END_THREADS +#endif + +/* + * UFunc has unit of 1, and the order of operations can be reordered + * This case allows reduction with multiple axes at once. + */ +#define PyUFunc_One 1 +/* + * UFunc has unit of 0, and the order of operations can be reordered + * This case allows reduction with multiple axes at once. + */ +#define PyUFunc_Zero 0 +/* + * UFunc has no unit, and the order of operations cannot be reordered. + * This case does not allow reduction with multiple axes at once. + */ +#define PyUFunc_None -1 +/* + * UFunc has no unit, and the order of operations can be reordered + * This case allows reduction with multiple axes at once. + */ +#define PyUFunc_ReorderableNone -2 + +#define UFUNC_REDUCE 0 +#define UFUNC_ACCUMULATE 1 +#define UFUNC_REDUCEAT 2 +#define UFUNC_OUTER 3 + + +typedef struct { + int nin; + int nout; + PyObject *callable; +} PyUFunc_PyFuncData; + +/* A linked-list of function information for + user-defined 1-d loops. + */ +typedef struct _loop1d_info { + PyUFuncGenericFunction func; + void *data; + int *arg_types; + struct _loop1d_info *next; +} PyUFunc_Loop1d; + + +#include "__ufunc_api.h" + +#define UFUNC_PYVALS_NAME "UFUNC_PYVALS" + +#define UFUNC_CHECK_ERROR(arg) \ + do {if ((((arg)->obj & UFUNC_OBJ_NEEDS_API) && PyErr_Occurred()) || \ + ((arg)->errormask && \ + PyUFunc_checkfperr((arg)->errormask, \ + (arg)->errobj, \ + &(arg)->first))) \ + goto fail;} while (0) + +/* This code checks the IEEE status flags in a platform-dependent way */ +/* Adapted from Numarray */ + +#if (defined(__unix__) || defined(unix)) && !defined(USG) +#include +#endif + +/* OSF/Alpha (Tru64) ---------------------------------------------*/ +#if defined(__osf__) && defined(__alpha) + +#include + +#define UFUNC_CHECK_STATUS(ret) { \ + unsigned long fpstatus; \ + \ + fpstatus = ieee_get_fp_control(); \ + /* clear status bits as well as disable exception mode if on */ \ + ieee_set_fp_control( 0 ); \ + ret = ((IEEE_STATUS_DZE & fpstatus) ? UFUNC_FPE_DIVIDEBYZERO : 0) \ + | ((IEEE_STATUS_OVF & fpstatus) ? UFUNC_FPE_OVERFLOW : 0) \ + | ((IEEE_STATUS_UNF & fpstatus) ? UFUNC_FPE_UNDERFLOW : 0) \ + | ((IEEE_STATUS_INV & fpstatus) ? UFUNC_FPE_INVALID : 0); \ + } + +/* MS Windows -----------------------------------------------------*/ +#elif defined(_MSC_VER) + +#include + + /* Clear the floating point exception default of Borland C++ */ +#if defined(__BORLANDC__) +#define UFUNC_NOFPE _control87(MCW_EM, MCW_EM); +#endif + +#define UFUNC_CHECK_STATUS(ret) { \ + int fpstatus = (int) _clearfp(); \ + \ + ret = ((SW_ZERODIVIDE & fpstatus) ? UFUNC_FPE_DIVIDEBYZERO : 0) \ + | ((SW_OVERFLOW & fpstatus) ? UFUNC_FPE_OVERFLOW : 0) \ + | ((SW_UNDERFLOW & fpstatus) ? UFUNC_FPE_UNDERFLOW : 0) \ + | ((SW_INVALID & fpstatus) ? UFUNC_FPE_INVALID : 0); \ + } + +/* Solaris --------------------------------------------------------*/ +/* --------ignoring SunOS ieee_flags approach, someone else can +** deal with that! */ +#elif defined(sun) || defined(__BSD__) || defined(__OpenBSD__) || \ + (defined(__FreeBSD__) && (__FreeBSD_version < 502114)) || \ + defined(__NetBSD__) +#include + +#define UFUNC_CHECK_STATUS(ret) { \ + int fpstatus; \ + \ + fpstatus = (int) fpgetsticky(); \ + ret = ((FP_X_DZ & fpstatus) ? UFUNC_FPE_DIVIDEBYZERO : 0) \ + | ((FP_X_OFL & fpstatus) ? UFUNC_FPE_OVERFLOW : 0) \ + | ((FP_X_UFL & fpstatus) ? UFUNC_FPE_UNDERFLOW : 0) \ + | ((FP_X_INV & fpstatus) ? UFUNC_FPE_INVALID : 0); \ + (void) fpsetsticky(0); \ + } + +#elif defined(__GLIBC__) || defined(__APPLE__) || \ + defined(__CYGWIN__) || defined(__MINGW32__) || \ + (defined(__FreeBSD__) && (__FreeBSD_version >= 502114)) + +#if defined(__GLIBC__) || defined(__APPLE__) || \ + defined(__MINGW32__) || defined(__FreeBSD__) +#include +#endif + +#define UFUNC_CHECK_STATUS(ret) { \ + int fpstatus = (int) fetestexcept(FE_DIVBYZERO | FE_OVERFLOW | \ + FE_UNDERFLOW | FE_INVALID); \ + ret = ((FE_DIVBYZERO & fpstatus) ? UFUNC_FPE_DIVIDEBYZERO : 0) \ + | ((FE_OVERFLOW & fpstatus) ? UFUNC_FPE_OVERFLOW : 0) \ + | ((FE_UNDERFLOW & fpstatus) ? UFUNC_FPE_UNDERFLOW : 0) \ + | ((FE_INVALID & fpstatus) ? UFUNC_FPE_INVALID : 0); \ + (void) feclearexcept(FE_DIVBYZERO | FE_OVERFLOW | \ + FE_UNDERFLOW | FE_INVALID); \ +} + +#elif defined(_AIX) + +#include +#include + +#define UFUNC_CHECK_STATUS(ret) { \ + fpflag_t fpstatus; \ + \ + fpstatus = fp_read_flag(); \ + ret = ((FP_DIV_BY_ZERO & fpstatus) ? UFUNC_FPE_DIVIDEBYZERO : 0) \ + | ((FP_OVERFLOW & fpstatus) ? UFUNC_FPE_OVERFLOW : 0) \ + | ((FP_UNDERFLOW & fpstatus) ? UFUNC_FPE_UNDERFLOW : 0) \ + | ((FP_INVALID & fpstatus) ? UFUNC_FPE_INVALID : 0); \ + fp_swap_flag(0); \ +} + +#else + +#define NO_FLOATING_POINT_SUPPORT +#define UFUNC_CHECK_STATUS(ret) { \ + ret = 0; \ + } + +#endif + +/* + * THESE MACROS ARE DEPRECATED. + * Use npy_set_floatstatus_* in the npymath library. + */ +#define generate_divbyzero_error() npy_set_floatstatus_divbyzero() +#define generate_overflow_error() npy_set_floatstatus_overflow() + + /* Make sure it gets defined if it isn't already */ +#ifndef UFUNC_NOFPE +#define UFUNC_NOFPE +#endif + + +#ifdef __cplusplus +} +#endif +#endif /* !Py_UFUNCOBJECT_H */ diff --git a/data_tooling/pii_processing/include/numpy/utils.h b/data_tooling/pii_processing/include/numpy/utils.h new file mode 100644 index 0000000..cc968a3 --- /dev/null +++ b/data_tooling/pii_processing/include/numpy/utils.h @@ -0,0 +1,19 @@ +#ifndef __NUMPY_UTILS_HEADER__ +#define __NUMPY_UTILS_HEADER__ + +#ifndef __COMP_NPY_UNUSED + #if defined(__GNUC__) + #define __COMP_NPY_UNUSED __attribute__ ((__unused__)) + # elif defined(__ICC) + #define __COMP_NPY_UNUSED __attribute__ ((__unused__)) + #else + #define __COMP_NPY_UNUSED + #endif +#endif + +/* Use this to tag a variable as not used. It will remove unused variable + * warning on support platforms (see __COM_NPY_UNUSED) and mangle the variable + * to avoid accidental use */ +#define NPY_UNUSED(x) (__NPY_UNUSED_TAGGED ## x) __COMP_NPY_UNUSED + +#endif diff --git a/data_tooling/pii_processing/masakhane-ner/README.md b/data_tooling/pii_processing/masakhane-ner/README.md new file mode 100644 index 0000000..2372a07 --- /dev/null +++ b/data_tooling/pii_processing/masakhane-ner/README.md @@ -0,0 +1,52 @@ +## Note for PII Hackathon + +This is only a partial copy of the Masakhane-NER code as of Sept 26, 2021 for the PII Hackathon. This code is a reference implementation for Module 3. Only the code under this repo will be supported for the hackathon. + +For reference, the complete Masakhane-NER code please refer to https://github.com/masakhane-io/masakhane-ner + +Original README: + +## [MasakhaNER: Named Entity Recognition for African Languages](https://arxiv.org/abs/2103.11811) + +This repository contains the code for [training NER models](https://github.com/masakhane-io/masakhane-ner/tree/main/code), scripts to [analyze the NER model predictions](https://github.com/masakhane-io/masakhane-ner/tree/main/analysis_scripts) and the [NER datasets](https://github.com/masakhane-io/masakhane-ner/tree/main/data) for all the 10 languages listed below. + +The code is based on HuggingFace implementation. + +### Required dependencies +* python + * [transformers](https://pypi.org/project/transformers/) : state-of-the-art Natural Language Processing for TensorFlow 2.0 and PyTorch. + * [seqeval](https://pypi.org/project/seqeval/) : testing framework for sequence labeling. + * [ptvsd](https://pypi.org/project/ptvsd/) : remote debugging server for Python support in Visual Studio and Visual Studio Code. + +```bash +pip install transformers seqeval ptvsd +``` + +### Volunteers +---------------- +| Language | Volunteer names | +|----------|-----------------| +| Amharic | Seid Muhie Yimam, Musie Meressa, Israel Abebe, Degaga Wolde, Henok Tilaye, Dibora Haile | +| Hausa | Shamsudden Muhammad, Tajuddeen Rabiu Gwadabe, Emmanuel Anebi| +| Igbo | Ignatius Ezeani, Chris Emezue, Chukwuneke Chiamaka, Nkiru Odu, Amaka, Isaac | +| Kinyarwanda | Rubungo Andre Niyongabo, Happy Buzaaba | +|Luganda | Joyce Nabende, Jonathan Mukiibi, Eric Peter Kigaye, Ivan Ssenkungu, Ibrahim Mbabaali, Batista Tobius, Maurice Katusiime, Deborah Nabagereka, Tobius Saolo | +| Luo | Perez Ogayo, Verrah Otiende | +| Naija Pidgin | Orevaoghene Ahia, Kelechi Ogueji, Adewale Akinfaderin, Aremu Adeola Jr., Iroro Orife, Temi Oloyede, Samuel Abiodun Oyerinde, Victor Akinode | +| Swahili | Catherine Gitau, Verrah Otiende, Davis David, Clemencia Siro, Yvonne Wambui, Gerald Muriuki | +| Wolof | [Abdoulaye Diallo](https://github.com/abdoulsn), [Thierno Ibrahim Diop](https://github.com/bayethiernodiop), and [Derguene Mbaye](https://github.com/DerXter), Samba Ngom, Mouhamadane Mboup | +| Yorùbá | David Adelani, Mofetoluwa Adeyemi, Jesujoba Alabi, Tosin Adewumi, Ayodele Awokoya | + +If you make use of this dataset, please cite us: + +### BibTeX entry and citation info +``` +@misc{adelani2021masakhaner, + title={MasakhaNER: Named Entity Recognition for African Languages}, + author={David Ifeoluwa Adelani and Jade Abbott and Graham Neubig and Daniel D'souza and Julia Kreutzer and Constantine Lignos and Chester Palen-Michel and Happy Buzaaba and Shruti Rijhwani and Sebastian Ruder and Stephen Mayhew and Israel Abebe Azime and Shamsuddeen Muhammad and Chris Chinenye Emezue and Joyce Nakatumba-Nabende and Perez Ogayo and Anuoluwapo Aremu and Catherine Gitau and Derguene Mbaye and Jesujoba Alabi and Seid Muhie Yimam and Tajuddeen Gwadabe and Ignatius Ezeani and Rubungo Andre Niyongabo and Jonathan Mukiibi and Verrah Otiende and Iroro Orife and Davis David and Samba Ngom and Tosin Adewumi and Paul Rayson and Mofetoluwa Adeyemi and Gerald Muriuki and Emmanuel Anebi and Chiamaka Chukwuneke and Nkiruka Odu and Eric Peter Wairagala and Samuel Oyerinde and Clemencia Siro and Tobius Saul Bateesa and Temilola Oloyede and Yvonne Wambui and Victor Akinode and Deborah Nabagereka and Maurice Katusiime and Ayodele Awokoya and Mouhamadane MBOUP and Dibora Gebreyohannes and Henok Tilaye and Kelechi Nwaike and Degaga Wolde and Abdoulaye Faye and Blessing Sibanda and Orevaoghene Ahia and Bonaventure F. P. Dossou and Kelechi Ogueji and Thierno Ibrahima DIOP and Abdoulaye Diallo and Adewale Akinfaderin and Tendai Marengereke and Salomey Osei}, + year={2021}, + eprint={2103.11811}, + archivePrefix={arXiv}, + primaryClass={cs.CL} +} +``` diff --git a/data_tooling/pii_processing/masakhane-ner/code/README.md b/data_tooling/pii_processing/masakhane-ner/code/README.md new file mode 100644 index 0000000..8bc696a --- /dev/null +++ b/data_tooling/pii_processing/masakhane-ner/code/README.md @@ -0,0 +1,105 @@ +# african-ner + +#### Example to run the NER code (i.e fine-tuning mBERT and XLM-R end-to-end) +#### Using Multi-Lingual BERT + +``` +export MAX_LENGTH=164 +export BERT_MODEL=bert-base-multilingual-cased +export OUTPUT_DIR=swa_bert +export BATCH_SIZE=32 +export NUM_EPOCHS=10 +export SAVE_STEPS=10000 +export SEED=1 +CUDA_VISIBLE_DEVICES=1,2,3 python3 train_ner.py --data_dir data/swa/ \ +--model_type bert \ +--model_name_or_path $BERT_MODEL \ +--output_dir $OUTPUT_DIR \ +--max_seq_length $MAX_LENGTH \ +--num_train_epochs $NUM_EPOCHS \ +--per_gpu_train_batch_size $BATCH_SIZE \ +--save_steps $SAVE_STEPS \ +--seed $SEED \ +--do_train \ +--do_eval \ +--do_predict +``` + +#### Using XLM-RoBERTa +``` +export MAX_LENGTH=164 +export BERT_MODEL=xlm-roberta-base +export OUTPUT_DIR=swa_xlmr +export BATCH_SIZE=32 +export NUM_EPOCHS=10 +export SAVE_STEPS=10000 +export SEED=1 + +CUDA_VISIBLE_DEVICES=1,2,3 python3 train_ner.py --data_dir data/swa/ \ +--model_type xlmroberta \ +--model_name_or_path $BERT_MODEL \ +--output_dir $OUTPUT_DIR \ +--max_seq_length $MAX_LENGTH \ +--num_train_epochs $NUM_EPOCHS \ +--per_gpu_train_batch_size $BATCH_SIZE \ +--save_steps $SAVE_STEPS \ +--seed $SEED \ +--do_train \ +--do_eval \ +--do_predict +``` + +#### For the MeanE-BiLSTM model (i.e extract sentence embeddings from mBERT and XLM-R by taking the mean of the 12 LM layers before passing them into the BiLSTM + linear classifier) +#### Using Multi-Lingual BERT + +``` +export MAX_LENGTH=164 +export BERT_MODEL=bert-base-multilingual-cased +export OUTPUT_DIR=yor_freezembert +export BATCH_SIZE=32 +export NUM_EPOCHS=50 +export SAVE_STEPS=10000 +export SEED=1 + +CUDA_VISIBLE_DEVICES=3 python3 train_ner_freezedBERT.py --data_dir data/yor/ \ +--model_type bert \ +--model_name_or_path $BERT_MODEL \ +--output_dir $OUTPUT_DIR \ +--max_seq_length $MAX_LENGTH \ +--num_train_epochs $NUM_EPOCHS \ +--per_gpu_train_batch_size $BATCH_SIZE \ +--save_steps $SAVE_STEPS --learning_rate 5e-4 \ +--seed $SEED \ +--do_train \ +--do_eval \ +--do_predict +``` + + +#### Using XLM-RoBERTa + +``` +export MAX_LENGTH=164 +export BERT_MODEL=xlm-roberta-base +export OUTPUT_DIR=yor_freezexlmr +export BATCH_SIZE=32 +export NUM_EPOCHS=50 +export SAVE_STEPS=10000 +export SEED=1 + +CUDA_VISIBLE_DEVICES=3 python3 train_ner_freezedBERT.py --data_dir data/yor/ \ +--model_type xlmroberta \ +--model_name_or_path $BERT_MODEL \ +--output_dir $OUTPUT_DIR \ +--max_seq_length $MAX_LENGTH \ +--num_train_epochs $NUM_EPOCHS \ +--per_gpu_train_batch_size $BATCH_SIZE \ +--save_steps $SAVE_STEPS --learning_rate 5e-4 \ +--seed $SEED \ +--do_train \ +--do_eval \ +--do_predict +``` + + + diff --git a/data_tooling/pii_processing/masakhane-ner/code/train_ner.py b/data_tooling/pii_processing/masakhane-ner/code/train_ner.py new file mode 100644 index 0000000..7f8eab0 --- /dev/null +++ b/data_tooling/pii_processing/masakhane-ner/code/train_ner.py @@ -0,0 +1,852 @@ +# coding=utf-8 +# Copyright 2018 The Google AI Language Team Authors and The HuggingFace Inc. team. +# Copyright (c) 2018, NVIDIA CORPORATION. All rights reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +""" Fine-tuning the library models for named entity recognition on CoNLL-2003 (Bert or Roberta). """ + +import argparse +import glob +import logging +import os +import random + +import numpy as np +import torch +from seqeval.metrics import f1_score, precision_score, recall_score, classification_report +from torch.nn import CrossEntropyLoss +from torch.utils.data import DataLoader, RandomSampler, SequentialSampler, TensorDataset +from torch.utils.data.distributed import DistributedSampler +from tqdm import tqdm, trange +from scipy.sparse import save_npz, load_npz +import seqeval.metrics +from collections import defaultdict, Counter +from torch.utils.data import TensorDataset +from torch.utils.data import Dataset, DataLoader +from transformers import AutoModelForSequenceClassification, AutoModelForTokenClassification, \ + AutoConfig, AutoTokenizer, AutoModel +from transformers import AdamW, get_constant_schedule_with_warmup +from torch.nn.utils.rnn import pack_padded_sequence, pad_packed_sequence +from torch import LongTensor +import torch +from torch import nn, optim +from torch.nn import functional as F +from tqdm import tqdm +import random + + +from transformers import ( + WEIGHTS_NAME, + AdamW, + BertConfig, + BertForTokenClassification, + BertTokenizer, + CamembertConfig, + CamembertForTokenClassification, + CamembertTokenizer, + DistilBertConfig, + DistilBertForTokenClassification, + DistilBertTokenizer, + RobertaConfig, + RobertaForTokenClassification, + RobertaTokenizer, + XLMRobertaConfig, + XLMRobertaForTokenClassification, + XLMRobertaTokenizer, + get_linear_schedule_with_warmup, +) + +from utils_ner import convert_examples_to_features, get_labels, read_examples_from_file +from torch.utils.data import Dataset, DataLoader + +try: + from torch.utils.tensorboard import SummaryWriter +except ImportError: + from tensorboardX import SummaryWriter + +logger = logging.getLogger(__name__) + +MODEL_CLASSES = { + "bert": (BertConfig, BertForTokenClassification, BertTokenizer), + "roberta": (RobertaConfig, RobertaForTokenClassification, RobertaTokenizer), + "distilbert": (DistilBertConfig, DistilBertForTokenClassification, DistilBertTokenizer), + "camembert": (CamembertConfig, CamembertForTokenClassification, CamembertTokenizer), + "xlmroberta": (XLMRobertaConfig, XLMRobertaForTokenClassification, XLMRobertaTokenizer), +} + + +class NERDataset(Dataset): + """ + All the information for a sentence needed by BERT, i.e. + token_id, label_id + token_type, padding, masking, domain_ids + """ + + def __init__(self, encodings, domain_ids): + self.encodings = encodings + self.domain_ids = domain_ids + + def __len__(self): + return len(self.domain_ids) + + def __getitem__(self, idx): + return self.encodings[idx], self.domain_ids[idx] + + +def set_seed(args): + random.seed(args.seed) + np.random.seed(args.seed) + torch.manual_seed(args.seed) + if args.n_gpu > 0: + torch.cuda.manual_seed_all(args.seed) + + +def train(args, train_dataset, model, tokenizer, labels, pad_token_label_id): + """ Train the model """ + if args.local_rank in [-1, 0]: + tb_writer = SummaryWriter() + + args.train_batch_size = args.per_gpu_train_batch_size * max(1, args.n_gpu) + train_sampler = RandomSampler(train_dataset) if args.local_rank == -1 else DistributedSampler(train_dataset) + train_dataloader = DataLoader(train_dataset, sampler=train_sampler, batch_size=args.train_batch_size) + + if args.max_steps > 0: + t_total = args.max_steps + args.num_train_epochs = args.max_steps // (len(train_dataloader) // args.gradient_accumulation_steps) + 1 + else: + t_total = len(train_dataloader) // args.gradient_accumulation_steps * args.num_train_epochs + + # Prepare optimizer and schedule (linear warmup and decay) + no_decay = ["bias", "LayerNorm.weight"] + optimizer_grouped_parameters = [ + { + "params": [p for n, p in model.named_parameters() if not any(nd in n for nd in no_decay)], + "weight_decay": args.weight_decay, + }, + {"params": [p for n, p in model.named_parameters() if any(nd in n for nd in no_decay)], "weight_decay": 0.0}, + ] + optimizer = AdamW(optimizer_grouped_parameters, lr=args.learning_rate, eps=args.adam_epsilon) + scheduler = get_linear_schedule_with_warmup( + optimizer, num_warmup_steps=args.warmup_steps, num_training_steps=t_total + ) + + # Check if saved optimizer or scheduler states exist + if os.path.isfile(os.path.join(args.model_name_or_path, "optimizer.pt")) and os.path.isfile( + os.path.join(args.model_name_or_path, "scheduler.pt") + ): + # Load in optimizer and scheduler states + optimizer.load_state_dict(torch.load(os.path.join(args.model_name_or_path, "optimizer.pt"))) + scheduler.load_state_dict(torch.load(os.path.join(args.model_name_or_path, "scheduler.pt"))) + + # multi-gpu training (should be after apex fp16 initialization) + if args.n_gpu > 1: + model = torch.nn.DataParallel(model) + + # Distributed training (should be after apex fp16 initialization) + if args.local_rank != -1: + model = torch.nn.parallel.DistributedDataParallel( + model, device_ids=[args.local_rank], output_device=args.local_rank, find_unused_parameters=True + ) + + # Train! + logger.info("***** Running training *****") + logger.info(" Num examples = %d", len(train_dataset)) + logger.info(" Num Epochs = %d", args.num_train_epochs) + logger.info(" Instantaneous batch size per GPU = %d", args.per_gpu_train_batch_size) + logger.info( + " Total train batch size (w. parallel, distributed & accumulation) = %d", + args.train_batch_size + * args.gradient_accumulation_steps + * (torch.distributed.get_world_size() if args.local_rank != -1 else 1), + ) + logger.info(" Gradient Accumulation steps = %d", args.gradient_accumulation_steps) + logger.info(" Total optimization steps = %d", t_total) + + global_step = 0 + epochs_trained = 0 + steps_trained_in_current_epoch = 0 + # Check if continuing training from a checkpoint + if os.path.exists(args.model_name_or_path): + # set global_step to gobal_step of last saved checkpoint from model path + try: + global_step = int(args.model_name_or_path.split("-")[-1].split("/")[0]) + except ValueError: + global_step = 0 + epochs_trained = global_step // (len(train_dataloader) // args.gradient_accumulation_steps) + steps_trained_in_current_epoch = global_step % (len(train_dataloader) // args.gradient_accumulation_steps) + + logger.info(" Continuing training from checkpoint, will skip to saved global_step") + logger.info(" Continuing training from epoch %d", epochs_trained) + logger.info(" Continuing training from global step %d", global_step) + logger.info(" Will skip the first %d steps in the first epoch", steps_trained_in_current_epoch) + + tr_loss, logging_loss = 0.0, 0.0 + model.zero_grad() + train_iterator = trange( + epochs_trained, int(args.num_train_epochs), desc="Epoch", disable=args.local_rank not in [-1, 0] + ) + set_seed(args) # Added here for reproductibility + for _ in train_iterator: + epoch_iterator = tqdm(train_dataloader, desc="Iteration", disable=args.local_rank not in [-1, 0]) + for step, batch in enumerate(epoch_iterator): + + # Skip past any already trained steps if resuming training + if steps_trained_in_current_epoch > 0: + steps_trained_in_current_epoch -= 1 + continue + + model.train() + batch = tuple(t.to(args.device) for t in batch) + inputs = {"input_ids": batch[0], "attention_mask": batch[1], "labels": batch[3]} + if args.model_type != "distilbert": + inputs["token_type_ids"] = ( + batch[2] if args.model_type in ["bert", "xlnet"] else None + ) # XLM and RoBERTa don"t use segment_ids + + outputs = model(**inputs) + loss = outputs[0] # model outputs are always tuple in pytorch-transformers (see doc) + + if args.n_gpu > 1: + loss = loss.mean() # mean() to average on multi-gpu parallel training + if args.gradient_accumulation_steps > 1: + loss = loss / args.gradient_accumulation_steps + + loss.backward() + + tr_loss += loss.item() + if (step + 1) % args.gradient_accumulation_steps == 0: + torch.nn.utils.clip_grad_norm_(model.parameters(), args.max_grad_norm) + + scheduler.step() # Update learning rate schedule + optimizer.step() + model.zero_grad() + global_step += 1 + + if args.local_rank in [-1, 0] and args.logging_steps > 0 and global_step % args.logging_steps == 0: + # Log metrics + if ( + args.local_rank == -1 and args.evaluate_during_training + ): # Only evaluate when single GPU otherwise metrics may not average well + results, _ = evaluate(args, model, tokenizer, labels, pad_token_label_id, mode="dev") + for key, value in results.items(): + tb_writer.add_scalar("eval_{}".format(key), value, global_step) + tb_writer.add_scalar("lr", scheduler.get_lr()[0], global_step) + tb_writer.add_scalar("loss", (tr_loss - logging_loss) / args.logging_steps, global_step) + logging_loss = tr_loss + + if args.local_rank in [-1, 0] and args.save_steps > 0 and global_step % args.save_steps == 0: + # Save model checkpoint + output_dir = os.path.join(args.output_dir, "checkpoint-{}".format(global_step)) + if not os.path.exists(output_dir): + os.makedirs(output_dir) + model_to_save = ( + model.module if hasattr(model, "module") else model + ) # Take care of distributed/parallel training + model_to_save.save_pretrained(output_dir) + tokenizer.save_pretrained(output_dir) + + torch.save(args, os.path.join(output_dir, "training_args.bin")) + logger.info("Saving model checkpoint to %s", output_dir) + + torch.save(optimizer.state_dict(), os.path.join(output_dir, "optimizer.pt")) + torch.save(scheduler.state_dict(), os.path.join(output_dir, "scheduler.pt")) + logger.info("Saving optimizer and scheduler states to %s", output_dir) + + if args.max_steps > 0 and global_step > args.max_steps: + epoch_iterator.close() + break + if args.max_steps > 0 and global_step > args.max_steps: + train_iterator.close() + break + + if args.local_rank in [-1, 0]: + tb_writer.close() + + return global_step, tr_loss / global_step + + +def evaluate(args, model, tokenizer, labels, pad_token_label_id, mode, prefix=""): + eval_dataset = load_and_cache_examples(args, tokenizer, labels, pad_token_label_id, mode=mode) + + args.eval_batch_size = args.per_gpu_eval_batch_size * max(1, args.n_gpu) + # Note that DistributedSampler samples randomly + eval_sampler = SequentialSampler(eval_dataset) if args.local_rank == -1 else DistributedSampler(eval_dataset) + eval_dataloader = DataLoader(eval_dataset, sampler=eval_sampler, batch_size=args.eval_batch_size) + + # multi-gpu evaluate + if args.n_gpu > 1: + model = torch.nn.DataParallel(model) + + # Eval! + logger.info("***** Running evaluation %s *****", prefix) + logger.info(" Num examples = %d", len(eval_dataset)) + logger.info(" Batch size = %d", args.eval_batch_size) + eval_loss = 0.0 + nb_eval_steps = 0 + preds = None + out_label_ids = None + model.eval() + for batch in tqdm(eval_dataloader, desc="Evaluating"): + batch = tuple(t.to(args.device) for t in batch) + + with torch.no_grad(): + inputs = {"input_ids": batch[0], "attention_mask": batch[1], "labels": batch[3]} + if args.model_type != "distilbert": + inputs["token_type_ids"] = ( + batch[2] if args.model_type in ["bert", "xlnet"] else None + ) # XLM and RoBERTa don"t use segment_ids + outputs = model(**inputs) + tmp_eval_loss, logits = outputs[:2] + + if args.n_gpu > 1: + tmp_eval_loss = tmp_eval_loss.mean() # mean() to average on multi-gpu parallel evaluating + + eval_loss += tmp_eval_loss.item() + nb_eval_steps += 1 + if preds is None: + preds = logits.detach().cpu().numpy() + out_label_ids = inputs["labels"].detach().cpu().numpy() + else: + preds = np.append(preds, logits.detach().cpu().numpy(), axis=0) + out_label_ids = np.append(out_label_ids, inputs["labels"].detach().cpu().numpy(), axis=0) + + eval_loss = eval_loss / nb_eval_steps + preds = np.argmax(preds, axis=2) + + label_map = {i: label for i, label in enumerate(labels)} + + out_label_list = [[] for _ in range(out_label_ids.shape[0])] + preds_list = [[] for _ in range(out_label_ids.shape[0])] + + for i in range(out_label_ids.shape[0]): + for j in range(out_label_ids.shape[1]): + if out_label_ids[i, j] != pad_token_label_id: + out_label_list[i].append(label_map[out_label_ids[i][j]]) + preds_list[i].append(label_map[preds[i][j]]) + + results = { + "loss": eval_loss, + "precision": precision_score(out_label_list, preds_list), + "recall": recall_score(out_label_list, preds_list), + "f1": f1_score(out_label_list, preds_list), + 'report': classification_report(out_label_list, preds_list), + } + + logger.info("***** Eval results %s *****", prefix) + for key in sorted(results.keys()): + logger.info(" %s = %s", key, str(results[key])) + + return results, preds_list + + +def load_and_cache_examples(args, tokenizer, labels, pad_token_label_id, mode): + if args.local_rank not in [-1, 0] and not evaluate: + torch.distributed.barrier() # Make sure only the first process in distributed training process the dataset, and the others will use the cache + + # Load data features from cache or dataset file + cached_features_file = os.path.join( + args.data_dir, + "cached_{}_{}_{}".format( + mode, list(filter(None, args.model_name_or_path.split("/"))).pop(), str(args.max_seq_length) + ), + ) + if os.path.exists(cached_features_file) and not args.overwrite_cache: + logger.info("Loading features from cached file %s", cached_features_file) + features = torch.load(cached_features_file) + else: + logger.info("Creating features from dataset file at %s", args.data_dir) + examples = read_examples_from_file(args.data_dir, mode) + features = convert_examples_to_features( + examples, + labels, + args.max_seq_length, + tokenizer, + cls_token_at_end=bool(args.model_type in ["xlnet"]), + # xlnet has a cls token at the end + cls_token=tokenizer.cls_token, + cls_token_segment_id=2 if args.model_type in ["xlnet"] else 0, + sep_token=tokenizer.sep_token, + sep_token_extra=bool(args.model_type in ["roberta"]), + # roberta uses an extra separator b/w pairs of sentences, cf. github.com/pytorch/fairseq/commit/1684e166e3da03f5b600dbb7855cb98ddfcd0805 + pad_on_left=bool(args.model_type in ["xlnet"]), + # pad on the left for xlnet + pad_token=tokenizer.convert_tokens_to_ids([tokenizer.pad_token])[0], + pad_token_segment_id=4 if args.model_type in ["xlnet"] else 0, + pad_token_label_id=pad_token_label_id, + ) + if args.local_rank in [-1, 0]: + logger.info("Saving features into cached file %s", cached_features_file) + torch.save(features, cached_features_file) + + if args.local_rank == 0 and not evaluate: + torch.distributed.barrier() # Make sure only the first process in distributed training process the dataset, and the others will use the cache + + # Convert to Tensors and build dataset + all_input_ids = torch.tensor([f.input_ids for f in features], dtype=torch.long) + all_input_mask = torch.tensor([f.input_mask for f in features], dtype=torch.long) + all_segment_ids = torch.tensor([f.segment_ids for f in features], dtype=torch.long) + all_label_ids = torch.tensor([f.label_ids for f in features], dtype=torch.long) + + dataset = TensorDataset(all_input_ids, all_input_mask, all_segment_ids, all_label_ids) + return dataset + + +def load_examples(args, mode): + ''' + if args.local_rank not in [-1, 0] and not evaluate: + torch.distributed.barrier() # Make sure only the first process in distributed training process the dataset, and the others will use the cache + + if args.local_rank == 0 and not evaluate: + torch.distributed.barrier() + ''' + data = load_npz(args.data_dir + mode + ".npz") + data = data.toarray() + dataset = NERDataset(data[:, :-1], data[:, -1]) + + return dataset + + + +def main(): + parser = argparse.ArgumentParser() + + # Required parameters + parser.add_argument( + "--data_dir", + default=None, + type=str, + required=True, + help="The input data dir. Should contain the training files for the CoNLL-2003 NER task.", + ) + parser.add_argument( + "--model_type", + default=None, + type=str, + required=True, + help="Model type selected in the list: " + ", ".join(MODEL_CLASSES.keys()), + ) + parser.add_argument( + "--model_name_or_path", + default=None, + type=str, + required=True, + help="Path to pre-trained model or shortcut name selected in the list: " + ", ", + ) + parser.add_argument( + "--input_dir", + default=None, + type=str, + required=False, + help="The input model directory.", + ) + parser.add_argument( + "--output_dir", + default=None, + type=str, + required=True, + help="The output directory where the model predictions and checkpoints will be written.", + ) + + parser.add_argument( + "--test_result_file", + default="test_results.txt", + type=str, + required=False, + help="The test_result", + ) + + parser.add_argument( + "--test_prediction_file", + default="test_predictions.txt", + type=str, + required=False, + help="The test_result", + ) + + # Other parameters + parser.add_argument( + "--labels", + default="", + type=str, + help="Path to a file containing all labels. If not specified, CoNLL-2003 labels are used.", + ) + parser.add_argument( + "--config_name", default="", type=str, help="Pretrained config name or path if not the same as model_name" + ) + parser.add_argument( + "--tokenizer_name", + default="", + type=str, + help="Pretrained tokenizer name or path if not the same as model_name", + ) + parser.add_argument( + "--cache_dir", + default="", + type=str, + help="Where do you want to store the pre-trained models downloaded from s3", + ) + parser.add_argument( + "--max_seq_length", + default=128, + type=int, + help="The maximum total input sequence length after tokenization. Sequences longer " + "than this will be truncated, sequences shorter will be padded.", + ) + parser.add_argument("--do_train", action="store_true", help="Whether to run training.") + parser.add_argument("--do_finetune", action="store_true", help="Whether to run training.") + parser.add_argument("--do_eval", action="store_true", help="Whether to run eval on the dev set.") + parser.add_argument("--do_predict", action="store_true", help="Whether to run predictions on the test set.") + parser.add_argument( + "--evaluate_during_training", + action="store_true", + help="Whether to run evaluation during training at each logging step.", + ) + parser.add_argument( + "--do_lower_case", action="store_true", help="Set this flag if you are using an uncased model." + ) + + parser.add_argument("--per_gpu_train_batch_size", default=8, type=int, help="Batch size per GPU/CPU for training.") + parser.add_argument( + "--per_gpu_eval_batch_size", default=8, type=int, help="Batch size per GPU/CPU for evaluation." + ) + parser.add_argument( + "--gradient_accumulation_steps", + type=int, + default=1, + help="Number of updates steps to accumulate before performing a backward/update pass.", + ) + parser.add_argument("--learning_rate", default=5e-5, type=float, help="The initial learning rate for Adam.") + parser.add_argument("--weight_decay", default=0.0, type=float, help="Weight decay if we apply some.") + parser.add_argument("--adam_epsilon", default=1e-8, type=float, help="Epsilon for Adam optimizer.") + parser.add_argument("--max_grad_norm", default=1.0, type=float, help="Max gradient norm.") + parser.add_argument( + "--num_train_epochs", default=3.0, type=float, help="Total number of training epochs to perform." + ) + parser.add_argument( + "--max_steps", + default=-1, + type=int, + help="If > 0: set total number of training steps to perform. Override num_train_epochs.", + ) + parser.add_argument("--warmup_steps", default=0, type=int, help="Linear warmup over warmup_steps.") + + parser.add_argument("--logging_steps", type=int, default=500, help="Log every X updates steps.") + parser.add_argument("--save_steps", type=int, default=500, help="Save checkpoint every X updates steps.") + parser.add_argument( + "--eval_all_checkpoints", + action="store_true", + help="Evaluate all checkpoints starting with the same prefix as model_name ending and ending with step number", + ) + parser.add_argument("--no_cuda", action="store_true", help="Avoid using CUDA when available") + parser.add_argument( + "--overwrite_output_dir", action="store_true", help="Overwrite the content of the output directory" + ) + parser.add_argument( + "--overwrite_cache", action="store_true", help="Overwrite the cached training and evaluation sets" + ) + parser.add_argument("--seed", type=int, default=42, help="random seed for initialization") + + parser.add_argument("--local_rank", type=int, default=-1, help="For distributed training: local_rank") + parser.add_argument("--server_ip", type=str, default="", help="For distant debugging.") + parser.add_argument("--server_port", type=str, default="", help="For distant debugging.") + + + args = parser.parse_args() + + if ( + os.path.exists(args.output_dir) + and os.listdir(args.output_dir) + and args.do_train + and not args.overwrite_output_dir + ): + raise ValueError( + "Output directory ({}) already exists and is not empty. Use --overwrite_output_dir to overcome.".format( + args.output_dir + ) + ) + + # Setup distant debugging if needed + if args.server_ip and args.server_port: + # Distant debugging - see https://code.visualstudio.com/docs/python/debugging#_attach-to-a-local-script + import ptvsd + + print("Waiting for debugger attach") + ptvsd.enable_attach(address=(args.server_ip, args.server_port), redirect_output=True) + ptvsd.wait_for_attach() + + # Setup CUDA, GPU & distributed training + if args.local_rank == -1 or args.no_cuda: + device = torch.device("cuda" if torch.cuda.is_available() and not args.no_cuda else "cpu") + args.n_gpu = torch.cuda.device_count() + else: # Initializes the distributed backend which will take care of sychronizing nodes/GPUs + torch.cuda.set_device(args.local_rank) + device = torch.device("cuda", args.local_rank) + torch.distributed.init_process_group(backend="nccl") + args.n_gpu = 1 + args.device = device + + # Setup logging + logging.basicConfig( + format="%(asctime)s - %(levelname)s - %(name)s - %(message)s", + datefmt="%m/%d/%Y %H:%M:%S", + level=logging.INFO if args.local_rank in [-1, 0] else logging.WARN, + ) + + # Set seed + set_seed(args) + + # Prepare CONLL-2003 task + labels = get_labels(args.labels) + num_labels = len(labels) + # Use cross entropy ignore index as padding label id so that only real label ids contribute to the loss later + pad_token_label_id = CrossEntropyLoss().ignore_index + + # Load pretrained model and tokenizer + if args.local_rank not in [-1, 0]: + torch.distributed.barrier() # Make sure only the first process in distributed training will download model & vocab + + args.model_type = args.model_type.lower() + config_class, model_class, tokenizer_class = AutoConfig, AutoModelForTokenClassification, AutoTokenizer #MODEL_CLASSES[args.model_type] + + config = config_class.from_pretrained( + args.config_name if args.config_name else args.model_name_or_path, + num_labels=num_labels, + id2label={str(i): label for i, label in enumerate(labels)}, + label2id={label: i for i, label in enumerate(labels)}, + cache_dir=args.cache_dir if args.cache_dir else None, + ) + tokenizer = tokenizer_class.from_pretrained( + args.tokenizer_name if args.tokenizer_name else args.model_name_or_path, + #do_lower_case=args.do_lower_case, + cache_dir=args.cache_dir if args.cache_dir else None, + #use_fast=args.use_fast, + ) + model = model_class.from_pretrained( + args.model_name_or_path, + from_tf=bool(".ckpt" in args.model_name_or_path), + config=config, + cache_dir=args.cache_dir if args.cache_dir else None, + ) + + if args.local_rank == 0: + torch.distributed.barrier() # Make sure only the first process in distributed training will download model & vocab + + model.to(args.device) + + logger.info("Training/evaluation parameters %s", args) + + # Training + if args.do_train: + train_dataset = load_and_cache_examples(args, tokenizer, labels, pad_token_label_id, mode="train") + #train_dataset = load_examples(args, mode="train") + global_step, tr_loss = train(args, train_dataset, model, tokenizer, labels, pad_token_label_id) + #global_step, tr_loss = train_ner(args, train_dataset, model, tokenizer, labels, pad_token_label_id) + logger.info(" global_step = %s, average loss = %s", global_step, tr_loss) + + # Fine-tuning + if args.do_finetune: + tokenizer = tokenizer_class.from_pretrained(args.input_dir, do_lower_case=args.do_lower_case) + model = model_class.from_pretrained(args.input_dir) + model.to(args.device) + result, predictions = evaluate(args, model, tokenizer, labels, pad_token_label_id, mode="test") + train_dataset = load_and_cache_examples(args, tokenizer, labels, pad_token_label_id, mode="train") + + # train_dataset = load_examples(args, mode="train") + global_step, tr_loss = train(args, train_dataset, model, tokenizer, labels, pad_token_label_id) + # global_step, tr_loss = train_ner(args, train_dataset, model, tokenizer, labels, pad_token_label_id) + logger.info(" global_step = %s, average loss = %s", global_step, tr_loss) + + # Saving best-practices: if you use defaults names for the model, you can reload it using from_pretrained() + if (args.do_train or args.do_finetune) and (args.local_rank == -1 or torch.distributed.get_rank() == 0): + # Create output directory if needed + if not os.path.exists(args.output_dir) and args.local_rank in [-1, 0]: + os.makedirs(args.output_dir) + + logger.info("Saving model checkpoint to %s", args.output_dir) + # Save a trained model, configuration and tokenizer using `save_pretrained()`. + # They can then be reloaded using `from_pretrained()` + model_to_save = ( + model.module if hasattr(model, "module") else model + ) # Take care of distributed/parallel training + model_to_save.save_pretrained(args.output_dir) + tokenizer.save_pretrained(args.output_dir) + + # Good practice: save your training arguments together with the trained model + torch.save(args, os.path.join(args.output_dir, "training_args.bin")) + + # Evaluation + results = {} + if args.do_eval and args.local_rank in [-1, 0]: + tokenizer = tokenizer_class.from_pretrained(args.output_dir, do_lower_case=args.do_lower_case) + checkpoints = [args.output_dir] + if args.eval_all_checkpoints: + checkpoints = list( + os.path.dirname(c) for c in sorted(glob.glob(args.output_dir + "/**/" + WEIGHTS_NAME, recursive=True)) + ) + logging.getLogger("pytorch_transformers.modeling_utils").setLevel(logging.WARN) # Reduce logging + logger.info("Evaluate the following checkpoints: %s", checkpoints) + for checkpoint in checkpoints: + global_step = checkpoint.split("-")[-1] if len(checkpoints) > 1 else "" + model = model_class.from_pretrained(checkpoint) + model.to(args.device) + result, _ = evaluate(args, model, tokenizer, labels, pad_token_label_id, mode="dev", prefix=global_step) + if global_step: + result = {"{}_{}".format(global_step, k): v for k, v in result.items()} + results.update(result) + output_eval_file = os.path.join(args.output_dir, "eval_results.txt") + with open(output_eval_file, "w") as writer: + for key in sorted(results.keys()): + writer.write("{} = {}\n".format(key, str(results[key]))) + + if args.do_predict and args.local_rank in [-1, 0]: + tokenizer = tokenizer_class.from_pretrained(args.output_dir, do_lower_case=args.do_lower_case) + model = model_class.from_pretrained(args.output_dir) + model.to(args.device) + result, predictions = evaluate(args, model, tokenizer, labels, pad_token_label_id, mode="test") + # Save results + output_test_results_file = os.path.join(args.output_dir, args.test_result_file) + with open(output_test_results_file, "w") as writer: + for key in sorted(result.keys()): + writer.write("{} = {}\n".format(key, str(result[key]))) + # Save predictions + output_test_predictions_file = os.path.join(args.output_dir, args.test_prediction_file) + with open(output_test_predictions_file, "w") as writer: + with open(os.path.join(args.data_dir, "test.txt"), "r") as f: + example_id = 0 + for line in f: + if line.startswith("-DOCSTART-") or line == "" or line == "\n": + writer.write(line) + if not predictions[example_id]: + example_id += 1 + elif predictions[example_id]: + output_line = line.split()[0] + " " + predictions[example_id].pop(0) + "\n" + writer.write(output_line) + else: + logger.warning("Maximum sequence length exceeded: No prediction for '%s'.", line.split()[0]) + + return results + + + + +if __name__ == "__main__": + main() + + +''' +export MAX_LENGTH=164 +export BERT_MODEL=bert-base-multilingual-cased +export OUTPUT_DIR=wol_bert +export BATCH_SIZE=32 +export NUM_EPOCHS=50 +export SAVE_STEPS=10000 +export SEED=1 + +CUDA_VISIBLE_DEVICES=2 python3 train_ner.py --data_dir conll_format/wolof/ \ +--model_type bert \ +--model_name_or_path $BERT_MODEL \ +--output_dir $OUTPUT_DIR \ +--max_seq_length $MAX_LENGTH \ +--num_train_epochs $NUM_EPOCHS \ +--per_gpu_train_batch_size $BATCH_SIZE \ +--save_steps $SAVE_STEPS \ +--seed $SEED \ +--do_train \ +--do_eval \ +--do_predict + + +export MAX_LENGTH=164 +export BERT_MODEL=xlm-roberta-base +export INPUT_DIR=conll_tranf +export OUTPUT_DIR=eng_yor100 +export BATCH_SIZE=32 +export NUM_EPOCHS=10 +export SAVE_STEPS=10000 +export SEED=1 + +CUDA_VISIBLE_DEVICES=2 python3 train_ner.py --data_dir news/yoruba100/ \ +--model_type bert \ +--model_name_or_path $BERT_MODEL \ +--input_dir $INPUT_DIR \ +--output_dir $OUTPUT_DIR \ +--max_seq_length $MAX_LENGTH \ +--num_train_epochs $NUM_EPOCHS \ +--per_gpu_train_batch_size $BATCH_SIZE \ +--save_steps $SAVE_STEPS \ +--seed $SEED \ +--do_finetune \ +--do_eval \ +--do_predict + + +export MAX_LENGTH=164 +export BERT_MODEL=xlm-roberta-base +export OUTPUT_DIR=conll_tranf +export BATCH_SIZE=32 +export NUM_EPOCHS=10 +export SAVE_STEPS=10000 +export SEED=1 + +CUDA_VISIBLE_DEVICES=3 python3 train_ner.py --data_dir news/igbo/ \ +--model_type bert \ +--model_name_or_path $BERT_MODEL \ +--output_dir $OUTPUT_DIR \ +--max_seq_length $MAX_LENGTH \ +--num_train_epochs $NUM_EPOCHS \ +--per_gpu_train_batch_size $BATCH_SIZE \ +--save_steps $SAVE_STEPS \ +--seed $SEED \ +--do_predict + + +export MAX_LENGTH=164 +export BERT_MODEL=xlm-roberta-large +export OUTPUT_DIR=ibo_xlmrlarge +export BATCH_SIZE=32 +export NUM_EPOCHS=50 +export SAVE_STEPS=10000 +export SEED=1 + +CUDA_VISIBLE_DEVICES=0,1,3 python3 train_ner.py --data_dir conll_format/igbo/ \ +--model_type xlmroberta \ +--model_name_or_path $BERT_MODEL \ +--output_dir $OUTPUT_DIR \ +--max_seq_length $MAX_LENGTH \ +--num_train_epochs $NUM_EPOCHS \ +--per_gpu_train_batch_size $BATCH_SIZE \ +--save_steps $SAVE_STEPS \ +--seed $SEED \ +--do_train \ +--do_eval \ +--do_predict + + +yor +bert +f1 = 0.7777286787450287 +xlmr +f1 = 0.7187916481563749 + +luo +bert +f1 = 0.5938650306748466 +xlmr +f1 = 0.43446601941747576 + +igbo +bert + +xlmr + + +''' diff --git a/data_tooling/pii_processing/masakhane-ner/code/train_ner_freezedBERT.py b/data_tooling/pii_processing/masakhane-ner/code/train_ner_freezedBERT.py new file mode 100644 index 0000000..548fba2 --- /dev/null +++ b/data_tooling/pii_processing/masakhane-ner/code/train_ner_freezedBERT.py @@ -0,0 +1,845 @@ +# coding=utf-8 +# Copyright 2018 The Google AI Language Team Authors and The HuggingFace Inc. team. +# Copyright (c) 2018, NVIDIA CORPORATION. All rights reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +""" Fine-tuning the library models for named entity recognition on CoNLL-2003 (Bert or Roberta). """ + +import argparse +import glob +import logging +import os +import random + +import numpy as np +import torch +from seqeval.metrics import f1_score, precision_score, recall_score, classification_report +from torch.nn import CrossEntropyLoss +from torch.utils.data import DataLoader, RandomSampler, SequentialSampler, TensorDataset +from torch.utils.data.distributed import DistributedSampler +from tqdm import tqdm, trange +from scipy.sparse import save_npz, load_npz +import seqeval.metrics +from collections import defaultdict, Counter +from torch.utils.data import TensorDataset +from torch.utils.data import Dataset, DataLoader +from transformers import AutoModelForSequenceClassification, AutoModelForTokenClassification, \ + AutoConfig, AutoTokenizer, AutoModel +from transformers import AdamW, get_constant_schedule_with_warmup +from torch.nn.utils.rnn import pack_padded_sequence, pad_packed_sequence +from torch import LongTensor +import torch +from torch import nn, optim +from torch.nn import functional as F +from tqdm import tqdm +import random + + +from transformers import ( + WEIGHTS_NAME, + AdamW, + BertConfig, + BertForTokenClassification, + BertTokenizer, + CamembertConfig, + CamembertForTokenClassification, + CamembertTokenizer, + DistilBertConfig, + DistilBertForTokenClassification, + DistilBertTokenizer, + RobertaConfig, + RobertaForTokenClassification, + RobertaTokenizer, + XLMRobertaConfig, + XLMRobertaForTokenClassification, + XLMRobertaTokenizer, + get_linear_schedule_with_warmup, +) + +from utils_ner import convert_examples_to_features, get_labels, read_examples_from_file +from torch.utils.data import Dataset, DataLoader + +try: + from torch.utils.tensorboard import SummaryWriter +except ImportError: + from tensorboardX import SummaryWriter + +logger = logging.getLogger(__name__) + +MODEL_CLASSES = { + "bert": (BertConfig, BertForTokenClassification, BertTokenizer), + "roberta": (RobertaConfig, RobertaForTokenClassification, RobertaTokenizer), + "distilbert": (DistilBertConfig, DistilBertForTokenClassification, DistilBertTokenizer), + "camembert": (CamembertConfig, CamembertForTokenClassification, CamembertTokenizer), + "xlmroberta": (XLMRobertaConfig, XLMRobertaForTokenClassification, XLMRobertaTokenizer), +} + + +def set_seed(args): + random.seed(args.seed) + np.random.seed(args.seed) + torch.manual_seed(args.seed) + if args.n_gpu > 0: + torch.cuda.manual_seed_all(args.seed) + + +class Classifier(nn.Module): + """Head for sentence-level classification tasks.""" + + def __init__(self, num_classes, input_dim=768, hidden_size=64, pooler_dropout=0.3): + super(Classifier, self).__init__() + # self.dense = nn.Linear(input_dim, inner_dim) + + self.lstm = nn.LSTM(input_size=input_dim, + hidden_size=hidden_size, + num_layers=1, + # dropout = self.config.dropout_keep, + bidirectional=True, batch_first=True) + + self.activation_fn = nn.ReLU() + self.dropout = nn.Dropout(p=pooler_dropout) + self.out_proj = nn.Linear(hidden_size * 2, num_classes) # 2*hidden_size because bidirectional is True + + def forward(self, sent_rep): + # x = self.dropout(sent_rep) + # x = self.dense(x) + total_length = sent_rep.size(1) + input_lengths = sent_rep.size(0) + # print('input length: ', input_lengths) + vectorized_seqs = sent_rep.cpu().numpy() + input_lengths = LongTensor(list(map(len, vectorized_seqs))) + packed_input = pack_padded_sequence(sent_rep, input_lengths.cpu().numpy(), batch_first=True) + packed_output, (h_n, c_n) = self.lstm(packed_input) + # lstm_out, (h_n, c_n) = self.lstm(sent_rep) + output, _ = pad_packed_sequence(packed_output, batch_first=True, + total_length=total_length) + final_feature_map = self.dropout(output) # shape=(num_layers * num_directions, 64, hidden_size) + # final_feature_map = self.dropout(lstm_out) # shape=(num_layers * num_directions, 64, hidden_size) + + # Convert input to (64, hidden_size * hidden_layers * num_directions) for linear layer + # final_feature_map = torch.cat([final_feature_map[i, :, :] for i in range(final_feature_map.shape[0])], dim=1) + + x = self.activation_fn(final_feature_map) + x = self.dropout(x) + x = self.out_proj(x) # F.log_softmax(self.out_proj(x), dim=1) + return x + + +def train(args, train_dataset, bert_model, model, tokenizer, labels, pad_token_label_id): + """ Train the model """ + if args.local_rank in [-1, 0]: + tb_writer = SummaryWriter() + + loss_fct = torch.nn.CrossEntropyLoss() + + args.train_batch_size = args.per_gpu_train_batch_size * max(1, args.n_gpu) + train_sampler = RandomSampler(train_dataset) + train_dataloader = DataLoader(train_dataset, sampler=train_sampler, batch_size=args.train_batch_size) + + if args.max_steps > 0: + t_total = args.max_steps + args.num_train_epochs = args.max_steps // (len(train_dataloader) // args.gradient_accumulation_steps) + 1 + else: + t_total = len(train_dataloader) // args.gradient_accumulation_steps * args.num_train_epochs + + # Prepare optimizer and schedule (linear warmup and decay) + no_decay = ["bias", "LayerNorm.weight"] + optimizer_grouped_parameters = [ + { + "params": [p for n, p in model.named_parameters() if not any(nd in n for nd in no_decay)], + "weight_decay": args.weight_decay, + }, + {"params": [p for n, p in model.named_parameters() if any(nd in n for nd in no_decay)], "weight_decay": 0.0}, + ] + optimizer = AdamW(optimizer_grouped_parameters, lr=args.learning_rate, eps=args.adam_epsilon) + scheduler = get_linear_schedule_with_warmup( + optimizer, num_warmup_steps=args.warmup_steps, num_training_steps=t_total + ) + + # Check if saved optimizer or scheduler states exist + if os.path.isfile(os.path.join(args.model_name_or_path, "optimizer.pt")) and os.path.isfile( + os.path.join(args.model_name_or_path, "scheduler.pt") + ): + # Load in optimizer and scheduler states + optimizer.load_state_dict(torch.load(os.path.join(args.model_name_or_path, "optimizer.pt"))) + scheduler.load_state_dict(torch.load(os.path.join(args.model_name_or_path, "scheduler.pt"))) + + + # Train! + logger.info("***** Running training *****") + logger.info(" Num examples = %d", len(train_dataset)) + logger.info(" Num Epochs = %d", args.num_train_epochs) + logger.info(" Instantaneous batch size per GPU = %d", args.per_gpu_train_batch_size) + logger.info( + " Total train batch size (w. parallel, distributed & accumulation) = %d", + args.train_batch_size + * args.gradient_accumulation_steps + * (1), + ) + logger.info(" Gradient Accumulation steps = %d", args.gradient_accumulation_steps) + logger.info(" Total optimization steps = %d", t_total) + + global_step = 0 + epochs_trained = 0 + steps_trained_in_current_epoch = 0 + # Check if continuing training from a checkpoint + if os.path.exists(args.model_name_or_path): + # set global_step to gobal_step of last saved checkpoint from model path + try: + global_step = int(args.model_name_or_path.split("-")[-1].split("/")[0]) + except ValueError: + global_step = 0 + epochs_trained = global_step // (len(train_dataloader) // args.gradient_accumulation_steps) + steps_trained_in_current_epoch = global_step % (len(train_dataloader) // args.gradient_accumulation_steps) + + logger.info(" Continuing training from checkpoint, will skip to saved global_step") + logger.info(" Continuing training from epoch %d", epochs_trained) + logger.info(" Continuing training from global step %d", global_step) + logger.info(" Will skip the first %d steps in the first epoch", steps_trained_in_current_epoch) + + tr_loss, logging_loss = 0.0, 0.0 + model.zero_grad() + train_iterator = trange( + epochs_trained, int(args.num_train_epochs), desc="Epoch", disable=args.local_rank not in [-1, 0] + ) + set_seed(args) # Added here for reproductibility + for _ in train_iterator: + epoch_iterator = tqdm(train_dataloader, desc="Iteration", disable=args.local_rank not in [-1, 0]) + for step, batch in enumerate(epoch_iterator): + + # Skip past any already trained steps if resuming training + if steps_trained_in_current_epoch > 0: + steps_trained_in_current_epoch -= 1 + continue + + model.train() + batch = tuple(t.to(args.device) for t in batch) + inputs = {"input_ids": batch[0], "attention_mask": batch[1], "labels": batch[3]} + if args.model_type != "distilbert": + inputs["token_type_ids"] = ( + batch[2] if args.model_type in ["bert", "xlnet"] else None + ) # XLM and RoBERTa don"t use segment_ids + + hs = bert_model(inputs["input_ids"], attention_mask=inputs["attention_mask"], output_hidden_states=True) + + avg_emb = 0 + for layer in range(1, len(hs.hidden_states)): + avg_emb += hs.hidden_states[layer] + + avg_emb = torch.div(avg_emb, len(hs.hidden_states)-1) + #print(avg_emb.shape, len(hs.hidden_states)) + #cls_hs = hs[0] + + logits = model(avg_emb) + active_loss = inputs["attention_mask"].view(-1) == 1 + active_logits = logits.view(-1, args.num_labels) + active_labels = torch.where( + active_loss, inputs["labels"].view(-1), torch.tensor(loss_fct.ignore_index).type_as(inputs["labels"]) + ) + loss = loss_fct(active_logits, active_labels) + + if args.gradient_accumulation_steps > 1: + loss = loss / args.gradient_accumulation_steps + + loss.backward() + + tr_loss += loss.item() + if (step + 1) % args.gradient_accumulation_steps == 0: + torch.nn.utils.clip_grad_norm_(model.parameters(), args.max_grad_norm) + + scheduler.step() # Update learning rate schedule + optimizer.step() + model.zero_grad() + global_step += 1 + + if args.local_rank in [-1, 0] and args.logging_steps > 0 and global_step % args.logging_steps == 0: + # Log metrics + if ( + args.local_rank == -1 and args.evaluate_during_training + ): # Only evaluate when single GPU otherwise metrics may not average well + results, _ = evaluate(args, model, tokenizer, labels, pad_token_label_id, mode="dev") + for key, value in results.items(): + tb_writer.add_scalar("eval_{}".format(key), value, global_step) + tb_writer.add_scalar("lr", scheduler.get_lr()[0], global_step) + tb_writer.add_scalar("loss", (tr_loss - logging_loss) / args.logging_steps, global_step) + logging_loss = tr_loss + + if args.local_rank in [-1, 0] and args.save_steps > 0 and global_step % args.save_steps == 0: + # Save model checkpoint + output_dir = os.path.join(args.output_dir, "checkpoint-{}".format(global_step)) + if not os.path.exists(output_dir): + os.makedirs(output_dir) + + model_to_save = ( + model.module if hasattr(model, "module") else model + ) # Take care of distributed/parallel training + + bert_model_to_save = ( + bert_model.module if hasattr(bert_model, "module") else bert_model + ) + + bert_model_to_save.save_pretrained(args.output_dir) + tokenizer.save_pretrained(args.output_dir) + + # Good practice: save your training arguments together with the trained model + torch.save(args, os.path.join(args.output_dir, "training_args.bin")) + torch.save(model_to_save.state_dict(), os.path.join(args.output_dir, "bert_lstm.model")) + + logger.info("Saving model checkpoint to %s", output_dir) + + torch.save(optimizer.state_dict(), os.path.join(output_dir, "optimizer.pt")) + torch.save(scheduler.state_dict(), os.path.join(output_dir, "scheduler.pt")) + logger.info("Saving optimizer and scheduler states to %s", output_dir) + + if args.max_steps > 0 and global_step > args.max_steps: + epoch_iterator.close() + break + if args.max_steps > 0 and global_step > args.max_steps: + train_iterator.close() + break + + if args.local_rank in [-1, 0]: + tb_writer.close() + + return global_step, tr_loss / global_step + + +def evaluate(args, bert_model, model, tokenizer, labels, pad_token_label_id, mode, prefix=""): + eval_dataset = load_and_cache_examples(args, tokenizer, labels, pad_token_label_id, mode=mode) + + loss_fct = torch.nn.CrossEntropyLoss() + + args.eval_batch_size = args.per_gpu_eval_batch_size * max(1, args.n_gpu) + # Note that DistributedSampler samples randomly + eval_sampler = SequentialSampler(eval_dataset) if args.local_rank == -1 else DistributedSampler(eval_dataset) + eval_dataloader = DataLoader(eval_dataset, sampler=eval_sampler, batch_size=args.eval_batch_size) + + # multi-gpu evaluate + if args.n_gpu > 1: + model = torch.nn.DataParallel(model) + + # Eval! + logger.info("***** Running evaluation %s *****", prefix) + logger.info(" Num examples = %d", len(eval_dataset)) + logger.info(" Batch size = %d", args.eval_batch_size) + eval_loss = 0.0 + nb_eval_steps = 0 + preds = None + out_label_ids = None + model.eval() + for batch in tqdm(eval_dataloader, desc="Evaluating"): + batch = tuple(t.to(args.device) for t in batch) + + with torch.no_grad(): + inputs = {"input_ids": batch[0], "attention_mask": batch[1], "labels": batch[3]} + if args.model_type != "distilbert": + inputs["token_type_ids"] = ( + batch[2] if args.model_type in ["bert", "xlnet"] else None + ) # XLM and RoBERTa don"t use segment_ids + #outputs = model(**inputs) + #tmp_eval_loss, logits = outputs[:2] + + + hs = bert_model(inputs["input_ids"], attention_mask=inputs["attention_mask"], output_hidden_states=True) + + avg_emb = 0 + for layer in range(1, len(hs.hidden_states)): + avg_emb += hs.hidden_states[layer] + + avg_emb = torch.div(avg_emb, len(hs.hidden_states) - 1) + + logits = model(avg_emb) + active_loss = inputs["attention_mask"].view(-1) == 1 + active_logits = logits.view(-1, args.num_labels) + active_labels = torch.where( + active_loss, inputs["labels"].view(-1), torch.tensor(loss_fct.ignore_index).type_as(inputs["labels"]) + ) + tmp_eval_loss = loss_fct(active_logits, active_labels) + + if args.n_gpu > 1: + tmp_eval_loss = tmp_eval_loss.mean() # mean() to average on multi-gpu parallel evaluating + + eval_loss += tmp_eval_loss.item() + nb_eval_steps += 1 + if preds is None: + preds = logits.detach().cpu().numpy() + out_label_ids = inputs["labels"].detach().cpu().numpy() + else: + preds = np.append(preds, logits.detach().cpu().numpy(), axis=0) + out_label_ids = np.append(out_label_ids, inputs["labels"].detach().cpu().numpy(), axis=0) + + eval_loss = eval_loss / nb_eval_steps + preds = np.argmax(preds, axis=2) + + label_map = {i: label for i, label in enumerate(labels)} + + out_label_list = [[] for _ in range(out_label_ids.shape[0])] + preds_list = [[] for _ in range(out_label_ids.shape[0])] + + for i in range(out_label_ids.shape[0]): + for j in range(out_label_ids.shape[1]): + if out_label_ids[i, j] != pad_token_label_id: + out_label_list[i].append(label_map[out_label_ids[i][j]]) + preds_list[i].append(label_map[preds[i][j]]) + + results = { + "loss": eval_loss, + "precision": precision_score(out_label_list, preds_list), + "recall": recall_score(out_label_list, preds_list), + "f1": f1_score(out_label_list, preds_list), + 'report': classification_report(out_label_list, preds_list), + } + + logger.info("***** Eval results %s *****", prefix) + for key in sorted(results.keys()): + logger.info(" %s = %s", key, str(results[key])) + + return results, preds_list + + +def load_and_cache_examples(args, tokenizer, labels, pad_token_label_id, mode): + if args.local_rank not in [-1, 0] and not evaluate: + torch.distributed.barrier() # Make sure only the first process in distributed training process the dataset, and the others will use the cache + + # Load data features from cache or dataset file + cached_features_file = os.path.join( + args.data_dir, + "cached_{}_{}_{}".format( + mode, list(filter(None, args.model_name_or_path.split("/"))).pop(), str(args.max_seq_length) + ), + ) + if os.path.exists(cached_features_file) and not args.overwrite_cache: + logger.info("Loading features from cached file %s", cached_features_file) + features = torch.load(cached_features_file) + else: + logger.info("Creating features from dataset file at %s", args.data_dir) + examples = read_examples_from_file(args.data_dir, mode) + features = convert_examples_to_features( + examples, + labels, + args.max_seq_length, + tokenizer, + cls_token_at_end=bool(args.model_type in ["xlnet"]), + # xlnet has a cls token at the end + cls_token=tokenizer.cls_token, + cls_token_segment_id=2 if args.model_type in ["xlnet"] else 0, + sep_token=tokenizer.sep_token, + sep_token_extra=bool(args.model_type in ["roberta"]), + # roberta uses an extra separator b/w pairs of sentences, cf. github.com/pytorch/fairseq/commit/1684e166e3da03f5b600dbb7855cb98ddfcd0805 + pad_on_left=bool(args.model_type in ["xlnet"]), + # pad on the left for xlnet + pad_token=tokenizer.convert_tokens_to_ids([tokenizer.pad_token])[0], + pad_token_segment_id=4 if args.model_type in ["xlnet"] else 0, + pad_token_label_id=pad_token_label_id, + ) + if args.local_rank in [-1, 0]: + logger.info("Saving features into cached file %s", cached_features_file) + torch.save(features, cached_features_file) + + if args.local_rank == 0 and not evaluate: + torch.distributed.barrier() # Make sure only the first process in distributed training process the dataset, and the others will use the cache + + # Convert to Tensors and build dataset + all_input_ids = torch.tensor([f.input_ids for f in features], dtype=torch.long) + all_input_mask = torch.tensor([f.input_mask for f in features], dtype=torch.long) + all_segment_ids = torch.tensor([f.segment_ids for f in features], dtype=torch.long) + all_label_ids = torch.tensor([f.label_ids for f in features], dtype=torch.long) + + dataset = TensorDataset(all_input_ids, all_input_mask, all_segment_ids, all_label_ids) + return dataset + + + +def main(): + parser = argparse.ArgumentParser() + + # Required parameters + parser.add_argument( + "--data_dir", + default=None, + type=str, + required=True, + help="The input data dir. Should contain the training files for the CoNLL-2003 NER task.", + ) + parser.add_argument( + "--model_type", + default=None, + type=str, + required=True, + help="Model type selected in the list: " + ", ".join(MODEL_CLASSES.keys()), + ) + parser.add_argument( + "--model_name_or_path", + default=None, + type=str, + required=True, + help="Path to pre-trained model or shortcut name selected in the list: " + ", ", + ) + parser.add_argument( + "--input_dir", + default=None, + type=str, + required=False, + help="The input model directory.", + ) + parser.add_argument( + "--output_dir", + default=None, + type=str, + required=True, + help="The output directory where the model predictions and checkpoints will be written.", + ) + + parser.add_argument( + "--test_result_file", + default="test_results.txt", + type=str, + required=False, + help="The test_result", + ) + + parser.add_argument( + "--test_prediction_file", + default="test_predictions.txt", + type=str, + required=False, + help="The test_result", + ) + + # Other parameters + parser.add_argument( + "--labels", + default="", + type=str, + help="Path to a file containing all labels. If not specified, CoNLL-2003 labels are used.", + ) + parser.add_argument( + "--config_name", default="", type=str, help="Pretrained config name or path if not the same as model_name" + ) + parser.add_argument( + "--tokenizer_name", + default="", + type=str, + help="Pretrained tokenizer name or path if not the same as model_name", + ) + parser.add_argument( + "--cache_dir", + default="", + type=str, + help="Where do you want to store the pre-trained models downloaded from s3", + ) + parser.add_argument( + "--max_seq_length", + default=128, + type=int, + help="The maximum total input sequence length after tokenization. Sequences longer " + "than this will be truncated, sequences shorter will be padded.", + ) + parser.add_argument("--do_train", action="store_true", help="Whether to run training.") + parser.add_argument("--do_finetune", action="store_true", help="Whether to run training.") + parser.add_argument("--do_eval", action="store_true", help="Whether to run eval on the dev set.") + parser.add_argument("--do_predict", action="store_true", help="Whether to run predictions on the test set.") + parser.add_argument( + "--evaluate_during_training", + action="store_true", + help="Whether to run evaluation during training at each logging step.", + ) + parser.add_argument( + "--do_lower_case", action="store_true", help="Set this flag if you are using an uncased model." + ) + + parser.add_argument("--per_gpu_train_batch_size", default=8, type=int, help="Batch size per GPU/CPU for training.") + parser.add_argument( + "--per_gpu_eval_batch_size", default=8, type=int, help="Batch size per GPU/CPU for evaluation." + ) + parser.add_argument( + "--gradient_accumulation_steps", + type=int, + default=1, + help="Number of updates steps to accumulate before performing a backward/update pass.", + ) + parser.add_argument("--learning_rate", default=5e-5, type=float, help="The initial learning rate for Adam.") + parser.add_argument("--weight_decay", default=0.0, type=float, help="Weight decay if we apply some.") + parser.add_argument("--adam_epsilon", default=1e-8, type=float, help="Epsilon for Adam optimizer.") + parser.add_argument("--max_grad_norm", default=1.0, type=float, help="Max gradient norm.") + parser.add_argument( + "--num_train_epochs", default=3.0, type=float, help="Total number of training epochs to perform." + ) + parser.add_argument( + "--max_steps", + default=-1, + type=int, + help="If > 0: set total number of training steps to perform. Override num_train_epochs.", + ) + parser.add_argument("--warmup_steps", default=0, type=int, help="Linear warmup over warmup_steps.") + + parser.add_argument("--logging_steps", type=int, default=500, help="Log every X updates steps.") + parser.add_argument("--save_steps", type=int, default=500, help="Save checkpoint every X updates steps.") + parser.add_argument( + "--eval_all_checkpoints", + action="store_true", + help="Evaluate all checkpoints starting with the same prefix as model_name ending and ending with step number", + ) + parser.add_argument("--no_cuda", action="store_true", help="Avoid using CUDA when available") + parser.add_argument( + "--overwrite_output_dir", action="store_true", help="Overwrite the content of the output directory" + ) + parser.add_argument( + "--overwrite_cache", action="store_true", help="Overwrite the cached training and evaluation sets" + ) + parser.add_argument("--seed", type=int, default=42, help="random seed for initialization") + + parser.add_argument("--local_rank", type=int, default=-1, help="For distributed training: local_rank") + parser.add_argument("--server_ip", type=str, default="", help="For distant debugging.") + parser.add_argument("--server_port", type=str, default="", help="For distant debugging.") + + + args = parser.parse_args() + + if ( + os.path.exists(args.output_dir) + and os.listdir(args.output_dir) + and args.do_train + and not args.overwrite_output_dir + ): + raise ValueError( + "Output directory ({}) already exists and is not empty. Use --overwrite_output_dir to overcome.".format( + args.output_dir + ) + ) + + # Setup distant debugging if needed + if args.server_ip and args.server_port: + # Distant debugging - see https://code.visualstudio.com/docs/python/debugging#_attach-to-a-local-script + import ptvsd + + print("Waiting for debugger attach") + ptvsd.enable_attach(address=(args.server_ip, args.server_port), redirect_output=True) + ptvsd.wait_for_attach() + + # Setup CUDA, GPU & distributed training + if args.local_rank == -1 or args.no_cuda: + device = torch.device("cuda" if torch.cuda.is_available() and not args.no_cuda else "cpu") + args.n_gpu = torch.cuda.device_count() + else: # Initializes the distributed backend which will take care of sychronizing nodes/GPUs + torch.cuda.set_device(args.local_rank) + device = torch.device("cuda", args.local_rank) + torch.distributed.init_process_group(backend="nccl") + args.n_gpu = 1 + args.device = device + + # Setup logging + logging.basicConfig( + format="%(asctime)s - %(levelname)s - %(name)s - %(message)s", + datefmt="%m/%d/%Y %H:%M:%S", + level=logging.INFO if args.local_rank in [-1, 0] else logging.WARN, + ) + + # Set seed + set_seed(args) + + # Prepare CONLL-2003 task + labels = get_labels(args.labels) + num_labels = len(labels) + args.num_labels = num_labels + # Use cross entropy ignore index as padding label id so that only real label ids contribute to the loss later + pad_token_label_id = CrossEntropyLoss().ignore_index + + # Load pretrained model and tokenizer + if args.local_rank not in [-1, 0]: + torch.distributed.barrier() # Make sure only the first process in distributed training will download model & vocab + + args.model_type = args.model_type.lower() + config_class, model_class, tokenizer_class = AutoConfig, AutoModel, AutoTokenizer #MODEL_CLASSES[args.model_type] + + tokenizer = tokenizer_class.from_pretrained( + args.tokenizer_name if args.tokenizer_name else args.model_name_or_path, + # do_lower_case=args.do_lower_case, + cache_dir=args.cache_dir if args.cache_dir else None, + # use_fast=args.use_fast, + ) + bert_model = model_class.from_pretrained( + args.model_name_or_path, + cache_dir=args.cache_dir if args.cache_dir else None, + ) + + # freeze all the parameters + for param in bert_model.parameters(): + param.requires_grad = False + + if args.local_rank == 0: + torch.distributed.barrier() # Make sure only the first process in distributed training will download model & vocab + + bert_model.to(args.device) + bert_model.eval() + + model = Classifier(num_classes=num_labels) + + model.to(args.device) + + logger.info("Training/evaluation parameters %s", args) + + # Training + if args.do_train: + train_dataset = load_and_cache_examples(args, tokenizer, labels, pad_token_label_id, mode="train") + #train_dataset = load_examples(args, mode="train") + global_step, tr_loss = train(args, train_dataset, bert_model, model, tokenizer, labels, pad_token_label_id) + #global_step, tr_loss = train_ner(args, train_dataset, model, tokenizer, labels, pad_token_label_id) + logger.info(" global_step = %s, average loss = %s", global_step, tr_loss) + + # Fine-tuning + if args.do_finetune: + tokenizer = tokenizer_class.from_pretrained(args.input_dir, do_lower_case=args.do_lower_case) + model = model_class.from_pretrained(args.input_dir) + model.to(args.device) + result, predictions = evaluate(args, model, tokenizer, labels, pad_token_label_id, mode="test") + train_dataset = load_and_cache_examples(args, tokenizer, labels, pad_token_label_id, mode="train") + + # train_dataset = load_examples(args, mode="train") + global_step, tr_loss = train(args, train_dataset, model, tokenizer, labels, pad_token_label_id) + # global_step, tr_loss = train_ner(args, train_dataset, model, tokenizer, labels, pad_token_label_id) + logger.info(" global_step = %s, average loss = %s", global_step, tr_loss) + + # Saving best-practices: if you use defaults names for the model, you can reload it using from_pretrained() + if (args.do_train or args.do_finetune) and (args.local_rank == -1 or torch.distributed.get_rank() == 0): + # Create output directory if needed + if not os.path.exists(args.output_dir) and args.local_rank in [-1, 0]: + os.makedirs(args.output_dir) + + logger.info("Saving model checkpoint to %s", args.output_dir) + # Save a trained model, configuration and tokenizer using `save_pretrained()`. + # They can then be reloaded using `from_pretrained()` + + model_to_save = ( + model.module if hasattr(model, "module") else model + ) # Take care of distributed/parallel training + + bert_model_to_save = ( + bert_model.module if hasattr(bert_model, "module") else bert_model + ) + + bert_model_to_save.save_pretrained(args.output_dir) + tokenizer.save_pretrained(args.output_dir) + + # Good practice: save your training arguments together with the trained model + torch.save(args, os.path.join(args.output_dir, "training_args.bin")) + torch.save(model_to_save.state_dict(), os.path.join(args.output_dir, "bert_lstm.model")) + + # Evaluation + results = {} + if args.do_eval and args.local_rank in [-1, 0]: + tokenizer = tokenizer_class.from_pretrained(args.output_dir, do_lower_case=args.do_lower_case) + checkpoints = [args.output_dir] + if args.eval_all_checkpoints: + checkpoints = list( + os.path.dirname(c) for c in sorted(glob.glob(args.output_dir + "/**/" + WEIGHTS_NAME, recursive=True)) + ) + logging.getLogger("pytorch_transformers.modeling_utils").setLevel(logging.WARN) # Reduce logging + logger.info("Evaluate the following checkpoints: %s", checkpoints) + for checkpoint in checkpoints: + global_step = checkpoint.split("-")[-1] if len(checkpoints) > 1 else "" + + bert_model = model_class.from_pretrained(checkpoint) + bert_model.to(args.device) + model.load_state_dict(torch.load(os.path.join(args.output_dir, "bert_lstm.model"))) + result, _ = evaluate(args, bert_model, model, tokenizer, labels, pad_token_label_id, mode="dev", prefix=global_step) + if global_step: + result = {"{}_{}".format(global_step, k): v for k, v in result.items()} + results.update(result) + output_eval_file = os.path.join(args.output_dir, "eval_results.txt") + with open(output_eval_file, "w") as writer: + for key in sorted(results.keys()): + writer.write("{} = {}\n".format(key, str(results[key]))) + + if args.do_predict and args.local_rank in [-1, 0]: + tokenizer = tokenizer_class.from_pretrained(args.output_dir, do_lower_case=args.do_lower_case) + bert_model = model_class.from_pretrained(args.output_dir) + bert_model.to(args.device) + model.load_state_dict(torch.load(os.path.join(args.output_dir, "bert_lstm.model"))) + result, predictions = evaluate(args, bert_model, model, tokenizer, labels, pad_token_label_id, mode="test") + # Save results + output_test_results_file = os.path.join(args.output_dir, args.test_result_file) + with open(output_test_results_file, "w") as writer: + for key in sorted(result.keys()): + writer.write("{} = {}\n".format(key, str(result[key]))) + # Save predictions + output_test_predictions_file = os.path.join(args.output_dir, args.test_prediction_file) + with open(output_test_predictions_file, "w") as writer: + with open(os.path.join(args.data_dir, "test.txt"), "r") as f: + example_id = 0 + for line in f: + if line.startswith("-DOCSTART-") or line == "" or line == "\n": + writer.write(line) + if not predictions[example_id]: + example_id += 1 + elif predictions[example_id]: + output_line = line.split()[0] + " " + predictions[example_id].pop(0) + "\n" + writer.write(output_line) + else: + logger.warning("Maximum sequence length exceeded: No prediction for '%s'.", line.split()[0]) + + return results + + + + +if __name__ == "__main__": + main() + + +''' +export MAX_LENGTH=164 +export BERT_MODEL=bert-base-multilingual-cased +export OUTPUT_DIR=yo_sample +export BATCH_SIZE=32 +export NUM_EPOCHS=50 +export SAVE_STEPS=10000 +export SEED=1 + +CUDA_VISIBLE_DEVICES=3 python3 train_ner_freezedBERT.py --data_dir conll_format/yoruba/ \ +--model_type bert \ +--model_name_or_path $BERT_MODEL \ +--output_dir $OUTPUT_DIR \ +--max_seq_length $MAX_LENGTH \ +--num_train_epochs $NUM_EPOCHS \ +--per_gpu_train_batch_size $BATCH_SIZE \ +--save_steps $SAVE_STEPS --learning_rate 5e-4 \ +--seed $SEED \ +--do_train \ +--do_eval \ +--do_predict + + + +export MAX_LENGTH=164 +export BERT_MODEL=xlm-roberta-base +export OUTPUT_DIR=yo_sample +export BATCH_SIZE=32 +export NUM_EPOCHS=50 +export SAVE_STEPS=10000 +export SEED=1 + +CUDA_VISIBLE_DEVICES=3 python3 train_ner_freezedBERT.py --data_dir conll_format/yoruba/ \ +--model_type xlmroberta \ +--model_name_or_path $BERT_MODEL \ +--output_dir $OUTPUT_DIR \ +--max_seq_length $MAX_LENGTH \ +--num_train_epochs $NUM_EPOCHS \ +--per_gpu_train_batch_size $BATCH_SIZE \ +--save_steps $SAVE_STEPS \ +--seed $SEED \ +--do_train \ +--do_eval \ +--do_predict + +''' diff --git a/data_tooling/pii_processing/masakhane-ner/code/utils_ner.py b/data_tooling/pii_processing/masakhane-ner/code/utils_ner.py new file mode 100644 index 0000000..53d42b5 --- /dev/null +++ b/data_tooling/pii_processing/masakhane-ner/code/utils_ner.py @@ -0,0 +1,239 @@ +# coding=utf-8 +# Copyright 2018 The Google AI Language Team Authors and The HuggingFace Inc. team. +# Copyright (c) 2018, NVIDIA CORPORATION. All rights reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +""" Named entity recognition fine-tuning: utilities to work with CoNLL-2003 task. """ + + +import logging +import os + + +logger = logging.getLogger(__name__) + +class InputExample(object): + """A single training/test example for token classification.""" + + def __init__(self, guid, words, labels): + """Constructs a InputExample. + + Args: + guid: Unique id for the example. + words: list. The words of the sequence. + labels: (Optional) list. The labels for each word of the sequence. This should be + specified for train and dev examples, but not for test examples. + """ + self.guid = guid + self.words = words + self.labels = labels + + +class InputFeatures(object): + """A single set of features of data.""" + + def __init__(self, input_ids, input_mask, segment_ids, label_ids): + self.input_ids = input_ids + self.input_mask = input_mask + self.segment_ids = segment_ids + self.label_ids = label_ids + + +def read_examples_from_file_flexible(file_path, mode): + guid_index = 1 + examples = [] + with open(file_path, encoding="utf-8") as f: + words = [] + labels = [] + for line in f: + if line.startswith("-DOCSTART-") or line == "" or line == "\n": + if words: + examples.append(InputExample(guid="{}-{}".format(mode, guid_index), words=words, labels=labels)) + guid_index += 1 + words = [] + labels = [] + else: + splits = line.split(" ") + words.append(splits[0]) + if len(splits) > 1: + labels.append(splits[-1].replace("\n", "")) + else: + # Examples could have no label for mode = "test" + labels.append("O") + if words: + examples.append(InputExample(guid="{}-{}".format(mode, guid_index), words=words, labels=labels)) + return examples + + +def read_examples_from_file(data_dir, mode): + file_path = os.path.join(data_dir, "{}.txt".format(mode)) + guid_index = 1 + examples = [] + with open(file_path, encoding="utf-8") as f: + words = [] + labels = [] + for line in f: + line = line.strip() + if len(line) < 2 or line == "\n": + print(line, words) + if words: + examples.append(InputExample(guid="{}-{}".format(mode, guid_index), words=words, labels=labels)) + guid_index += 1 + words = [] + labels = [] + else: + splits = line.split(" ") + words.append(splits[0]) + if len(splits) > 1: + labels.append(splits[-1].replace("\n", "")) + else: + # Examples could have no label for mode = "test" + labels.append("O") + if words: + examples.append(InputExample(guid="{}-{}".format(mode, guid_index), words=words, labels=labels)) + return examples + + +def convert_examples_to_features( + examples, + label_list, + max_seq_length, + tokenizer, + cls_token_at_end=False, + cls_token="[CLS]", + cls_token_segment_id=1, + sep_token="[SEP]", + sep_token_extra=False, + pad_on_left=False, + pad_token=0, + pad_token_segment_id=0, + pad_token_label_id=-100, + sequence_a_segment_id=0, + mask_padding_with_zero=True, +): + """ Loads a data file into a list of `InputBatch`s + `cls_token_at_end` define the location of the CLS token: + - False (Default, BERT/XLM pattern): [CLS] + A + [SEP] + B + [SEP] + - True (XLNet/GPT pattern): A + [SEP] + B + [SEP] + [CLS] + `cls_token_segment_id` define the segment id associated to the CLS token (0 for BERT, 2 for XLNet) + """ + + label_map = {label: i for i, label in enumerate(label_list)} + + features = [] + for (ex_index, example) in enumerate(examples): + #print(ex_index, len(example.words)) + if ex_index % 10000 == 0: + logger.info("Writing example %d of %d", ex_index, len(examples)) + + tokens = [] + label_ids = [] + for word, label in zip(example.words, example.labels): + word_tokens = tokenizer.tokenize(word) + tokens.extend(word_tokens) + # Use the real label id for the first token of the word, and padding ids for the remaining tokens + label_ids.extend([label_map[label]] + [pad_token_label_id] * (len(word_tokens) - 1)) + + # Account for [CLS] and [SEP] with "- 2" and with "- 3" for RoBERTa. + special_tokens_count = 3 if sep_token_extra else 2 + if len(tokens) > max_seq_length - special_tokens_count: + tokens = tokens[: (max_seq_length - special_tokens_count)] + label_ids = label_ids[: (max_seq_length - special_tokens_count)] + + # The convention in BERT is: + # (a) For sequence pairs: + # tokens: [CLS] is this jack ##son ##ville ? [SEP] no it is not . [SEP] + # type_ids: 0 0 0 0 0 0 0 0 1 1 1 1 1 1 + # (b) For single sequences: + # tokens: [CLS] the dog is hairy . [SEP] + # type_ids: 0 0 0 0 0 0 0 + # + # Where "type_ids" are used to indicate whether this is the first + # sequence or the second sequence. The embedding vectors for `type=0` and + # `type=1` were learned during pre-training and are added to the wordpiece + # embedding vector (and position vector). This is not *strictly* necessary + # since the [SEP] token unambiguously separates the sequences, but it makes + # it easier for the model to learn the concept of sequences. + # + # For classification tasks, the first vector (corresponding to [CLS]) is + # used as as the "sentence vector". Note that this only makes sense because + # the entire model is fine-tuned. + tokens += [sep_token] + label_ids += [pad_token_label_id] + if sep_token_extra: + # roberta uses an extra separator b/w pairs of sentences + tokens += [sep_token] + label_ids += [pad_token_label_id] + segment_ids = [sequence_a_segment_id] * len(tokens) + + if cls_token_at_end: + tokens += [cls_token] + label_ids += [pad_token_label_id] + segment_ids += [cls_token_segment_id] + else: + tokens = [cls_token] + tokens + label_ids = [pad_token_label_id] + label_ids + segment_ids = [cls_token_segment_id] + segment_ids + + input_ids = tokenizer.convert_tokens_to_ids(tokens) + + # The mask has 1 for real tokens and 0 for padding tokens. Only real + # tokens are attended to. + input_mask = [1 if mask_padding_with_zero else 0] * len(input_ids) + + # Zero-pad up to the sequence length. + padding_length = max_seq_length - len(input_ids) + if pad_on_left: + input_ids = ([pad_token] * padding_length) + input_ids + input_mask = ([0 if mask_padding_with_zero else 1] * padding_length) + input_mask + segment_ids = ([pad_token_segment_id] * padding_length) + segment_ids + label_ids = ([pad_token_label_id] * padding_length) + label_ids + else: + input_ids += [pad_token] * padding_length + input_mask += [0 if mask_padding_with_zero else 1] * padding_length + segment_ids += [pad_token_segment_id] * padding_length + label_ids += [pad_token_label_id] * padding_length + + assert len(input_ids) == max_seq_length + assert len(input_mask) == max_seq_length + assert len(segment_ids) == max_seq_length + try: + assert len(label_ids) == max_seq_length + except: + continue + + if ex_index < 5: + logger.info("*** Example ***") + logger.info("guid: %s", example.guid) + logger.info("tokens: %s", " ".join([str(x) for x in tokens])) + logger.info("input_ids: %s", " ".join([str(x) for x in input_ids])) + logger.info("input_mask: %s", " ".join([str(x) for x in input_mask])) + logger.info("segment_ids: %s", " ".join([str(x) for x in segment_ids])) + logger.info("label_ids: %s", " ".join([str(x) for x in label_ids])) + + features.append( + InputFeatures(input_ids=input_ids, input_mask=input_mask, segment_ids=segment_ids, label_ids=label_ids) + ) + return features + + + +def get_labels(path): + if path: + with open(path, "r") as f: + labels = f.read().splitlines() + if "O" not in labels: + labels = ["O"] + labels + return labels + else: + return ["O", "B-DATE", "I-DATE", "B-PER", "I-PER", "B-ORG", "I-ORG", "B-LOC", "I-LOC"] diff --git a/data_tooling/pii_processing/misc/README.md b/data_tooling/pii_processing/misc/README.md new file mode 100644 index 0000000..de7d56b --- /dev/null +++ b/data_tooling/pii_processing/misc/README.md @@ -0,0 +1,36 @@ +To test your regex, first install the package and spacy models: +``` +git clone https://github.com/bigscience-workshop/data_tooling +cd data_tooling +pip install spacy==3.1 transformers datasets langid faker nltk sentencepiece fsspec tqdm +pip install -r requirements.txt +pip install datasets +python -m nltk.downloader punkt stopwords wordnet +python -m spacy download en_core_web_lg +python -m spacy download zh_core_web_lg +python -m spacy download pt_core_news_lg +python -m spacy download fr_core_news_lg +python -m spacy download ca_core_news_lg +python -m spacy download es_core_news_lg +cd .. +``` + +TODO: load dynamic regex file...Then create your regex files under the pii_processing/regex folder of the form ``_.py``. + +Currently: edit the file test_regex.py to add your regex directly under ``__main__``. + +Then test your regex on a file of the form ``.jsonl`` which will create a file ``predicted_.jsonl`` + +``` +python data_tooling/pii_processing/misc/test_regex.py -target_lang +``` + +OR you can import apply_rules from test_regex into your own code +``` +from pii_processing.hackathon.test_regex import apply_rules +infile = "" +outfile = "" +rulebase = [...] # you can load the rulebases from pii_processing.regex for example +target_lang = "" +right, wrong = apply_rules(infile, outfile, rulebase, target_lang) +``` diff --git a/data_tooling/pii_processing/misc/backtrans_with_ner.py b/data_tooling/pii_processing/misc/backtrans_with_ner.py new file mode 100644 index 0000000..8e95c55 --- /dev/null +++ b/data_tooling/pii_processing/misc/backtrans_with_ner.py @@ -0,0 +1,573 @@ +# coding=utf-8 +# Copyright, 2021 Ontocord, LLC, All rights reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +from datasets import load_dataset +import os +import re +import itertools +from re import finditer +import glob +import random +import fsspec +import json +from random import randint, choice +from collections import Counter +import spacy, itertools +import langid +from nltk.corpus import stopwords +import fsspec, os, gzip +from faker import Faker +from faker.providers import person, company, geo, address, ssn +from transformers import BertForTokenClassification, RobertaForTokenClassification, XLMRobertaForTokenClassification, M2M100ForConditionalGeneration, M2M100Tokenizer, MarianMTModel, AutoTokenizer, pipeline +import torch +import sys +from tqdm import tqdm + +#sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), +# os.path.pardir, os.path.pardir, os.path.pardir))) +import json +import data_tooling + +from data_tooling.pii_processing.ontology.ontology_manager import OntologyManager + +stopwords_en = set(stopwords.words('english')) +stopwords_wn = set(stopwords.words()) + +#junk_dict = dict([(a, 1) for a in "' 0123456789¯_§½¼¾×|†—~\"—±′–'°−{}[]·-\'?,./<>!@#^&*()+-‑=:;`→¶'"]) + +junk_dict = dict([(a, 1) for a in ( + " ~!@#$%^&*{}[]()_+=-0987654321`<>,./?':;“”\"\t\n\\πه☆●¦″" + "．۩۱（☛₨➩°・■↑☻、๑º‹€σ٪’Ø·−♥ıॽ،٥《‘©。¨﴿！★×✱´٬→±x：¹？£―▷ф" + "¡Г♫∟™ª₪®▬「—¯；¼❖․ø•�」٣，٢◦‑←§١ー٤）˚›٩▼٠«¢¸٨³½˜٭ˈ¿¬ι۞⌐¥►" + "†ƒ∙²»¤…﴾⠀》′ا✓" +)]) + +rulebase = {"en": [([ + ("AGE", re.compile("\S+ years old|\S+\-years\-old|\S+ year old|\S+\-year\-old"), None, None, None), + ("STREET_ADDRESS", re.compile( + '\d{1,4} [\w\s]{1,20} (?:street|st|avenue|ave|road|rd|highway|hwy|square|sq|trail|trl|drive|dr|court|ct|park|parkway|pkwy|circle|cir|boulevard|blvd)\W?(?=\s|$)'), None, None, None), + ("STREET_ADDRESS", re.compile('\b\d{5}(?:[-\s]\d{4})?\b'), None, None, None), + ("STREET_ADDRESS", re.compile('P\.? ?O\.? Box \d+'), None, None, None), + ("GOVT_ID", re.compile( + '(?!000|666|333)0*(?:[0-6][0-9][0-9]|[0-7][0-6][0-9]|[0-7][0-7][0-2])[- ](?!00)[0-9]{2}[- ](?!0000)[0-9]{4}'), None, None, None), + ("DISEASE", re.compile("diabetes|cancer|HIV|AIDS|Alzheimer's|Alzheimer|heart disease"), None, None, None), + ("NORP", re.compile("upper class|middle class|working class|lower class"), None, None, None), + ], 1), + ], + "vi": [] + } + +""" +Our langauges: +- [ ] arabic +- [ ] bantu languages +- [ ] chinese +- [ ] french +- [ ] english +- [ ] indic languages +- [ ] portuguese +- [ ] spanish +- [ ] vietnamese +- [ ] basque +- [ ] catalan +- [ ] indonesian +""" +# note that we do not have a transformer model for catalan, but spacy covers catalan +lang2ner_model = { + "sw": ("Davlan/xlm-roberta-large-masakhaner", XLMRobertaForTokenClassification ), # consider using one of the smaller models + "yo": ("Davlan/xlm-roberta-large-masakhaner", XLMRobertaForTokenClassification ), + "ar": ("Davlan/xlm-roberta-base-ner-hrl", XLMRobertaForTokenClassification ), + "en": ("Davlan/xlm-roberta-base-ner-hrl", XLMRobertaForTokenClassification ), + "es": ("Davlan/xlm-roberta-base-ner-hrl", XLMRobertaForTokenClassification ), + "pt": ("Davlan/xlm-roberta-base-ner-hrl", XLMRobertaForTokenClassification ), + "fr": ("Davlan/xlm-roberta-base-ner-hrl", XLMRobertaForTokenClassification ), + "zh": ("Davlan/xlm-roberta-base-ner-hrl", XLMRobertaForTokenClassification ), + 'vi': ("lhkhiem28/COVID-19-Named-Entity-Recognition-for-Vietnamese", RobertaForTokenClassification), + 'hi': ("jplu/tf-xlm-r-ner-40-lang", XLMRobertaForTokenClassification ), + 'ur': ("jplu/tf-xlm-r-ner-40-lang", XLMRobertaForTokenClassification ), + 'id': ("jplu/tf-xlm-r-ner-40-lang", XLMRobertaForTokenClassification ), # also covers vietnamese + 'bn': ("sagorsarker/mbert-bengali-ner", BertForTokenClassification) + } + +""" +#sagorsarker/mbert-bengali-ner +Label ID Label +0 O +1 B-PER +2 I-PER +3 B-ORG +4 I-ORG +5 B-LOC +6 I-LOC +""" + + + +faker_map = dict([(a.split("_")[0], a) for a in [ + 'ar_AA', + 'ar_PS', + 'ar_SA', + 'bg_BG', + 'cs_CZ', + 'de_AT', + 'de_CH', + 'de_DE', + 'dk_DK', + 'el_GR', + 'en_GB', + 'en_IE', + 'en_IN', + 'en_NZ', + 'en_TH', + 'en_US', + 'es_CA', + 'es_ES', + 'es_MX', + 'et_EE', + 'fa_IR', + 'fi_FI', + 'fr_CA', + 'fr_CH', + 'fr_FR', + 'fr_QC', + 'ga_IE', + 'he_IL', + 'hi_IN', + 'hr_HR', + 'hu_HU', + 'hy_AM', + 'id_ID', + 'it_IT', + 'ja_JP', + 'ka_GE', + 'ko_KR', + 'lt_LT', + 'lv_LV', + 'ne_NP', + 'nl_NL', + 'no_NO', + 'or_IN', + 'pl_PL', + 'pt_BR', + 'pt_PT', + 'ro_RO', + 'ru_RU', + 'sl_SI', + 'sv_SE', + 'ta_IN', + 'th_TH', + 'tr_TR', + 'tw_GH', + 'uk_UA', + 'zh_CN', + 'zh_TW']] + [('en', 'en_US')]) + +def remove_html_tags(text): + """Remove html tags from a string""" + clean = re.compile('<.*?>') + return re.sub(clean, '', text) + + +def camel_case_split(identifier): + matches = finditer('.+?(?:(?<=[a-z])(?=[A-Z])|(?<=[A-Z])(?=[A-Z][a-z])|$)', identifier) + return [m.group(0) for m in matches] + + +def stem(s): + s = s.replace(".", " ").replace("!", " ").replace("?", " ").replace(",", " ").replace("-", " ").replace(";", + " ").replace( + "'", " '").replace("\"", " \"") + sArr = s.lower().split() + if len(sArr) > 4: + sArr = sArr[:4] + s = " ".join([s1[:4] if len(s1) > 4 else s1 for s1 in sArr if s1.strip()]) + return s + + +def pre_translation_steps(infile, target_lang='hi'): + texts = [] + ner_mappings = [] + row_ids = [] + domains = [] + lbracket = "[" + rbracket = "]" + if target_lang in ('zh', 'ja', 'ko'): + lbracket = "[[" + rbracket = "]]" + + row_id = -1 + for s in tqdm(open(infile, "rb")): + s = s.decode().strip() + if not s: continue + dat = json.loads(s) + domain = dat.get('domain','') + ner = dat.get('ner', {}) + text = dat['text'] + if 'id' not in dat: + row_id += 1 + else: + row_id = int(dat['id']) + context = {} + ner_mapping = {} + seen = {} + text = "... " + text + " " + text = text.replace(lbracket, "(") + text = text.replace(rbracket, ")", ) + if person_swap: + _idx = 0 + for item in ner2: + if item[0] in seen: continue + seen[item[0]] = 1 + text = text.replace(item[0], + ' ' + str(_idx) + " " + lbracket + item[0] + rbracket) + ner_mapping[str(_idx) + " " + lbracket] = item + _idx += 1 + + texts.append(text) + ner_mappings.append(ner_mapping) + row_ids.append(row_id) + domains.append(domain) + return texts, ner_mappings, row_ids, domains + + +def chunks(lst, n): + """Generate batches""" + for i in range(0, len(lst), n): + yield lst[i: i + n] + + +def do_translations(texts, target_lang='hi', batch_size=16): + model = M2M100ForConditionalGeneration.from_pretrained("facebook/m2m100_418M") + tokenizer = M2M100Tokenizer.from_pretrained("facebook/m2m100_418M") + model = model.to('cuda').half() + translations = [] + for src_text_list in tqdm(chunks(texts, batch_size)): + batch = tokenizer(src_text_list, return_tensors="pt", padding=True, truncation=True).to('cuda') + gen = model.generate(**batch, forced_bos_token_id=tokenizer.get_lang_id(target_lang)) + outputs = tokenizer.batch_decode(gen, skip_special_tokens=True) + translations.extend(outputs) + return translations + + +def get_aligned_text(sent1, sent2, target_lang): + """ + Given two sentences, find blocks of text that match and that don't match. + return the blocks, and a matching score. + Used to extract NER from original language sentence. + TODO: prefer matching based on "[id] aaaa *" patterns + """ + if target_lang in ("ja", "ko", "zh"): + # splitting on spaces doesn't always work because some languages aren't space separated + sep = "" + else: + sep = " " + sent1 = sent1.split() + sent2 = sent2.split() + aMatch = difflib.SequenceMatcher(None,sent1, sent2) + score = aMatch.ratio() + blocks = aMatch.get_matching_blocks() + blocks2 = [] + prevEndA = 0 + prevEndB = 0 + matchLen = 0 + nonMatchLen = 0 + print (blocks) + for blockI in range(len(blocks)): + if blockI > 0 or (blockI==0 and (blocks[blockI][0] != 0 or blocks[blockI][1] != 0)): + blocks2.append([sep.join(sent1[prevEndA:blocks[blockI][0]]), sep.join(sent2[prevEndB:blocks[blockI][1]]), 0]) + nonMatchLen += max(blocks[blockI][0] - prevEndA, blocks[blockI][1] - prevEndB) + if blocks[blockI][2] != 0: + blocks2.append([sep.join(sent1[blocks[blockI][0]:blocks[blockI][0]+blocks[blockI][2]]), sep.join(sent2[blocks[blockI][1]:blocks[blockI][1]+blocks[blockI][2]]), 1]) + prevEndA = blocks[blockI][0]+blocks[blockI][2] + prevEndB = blocks[blockI][1]+blocks[blockI][2] + matchLen += blocks[blockI][2] + #score = float(matchLen+1)/float(nonMatchLen+1) + return (blocks2, score) + +def post_translation_steps(outfile, translations, original_sentences, origional_ner, ner_mappings, row_ids, domains, target_lang='hi'): + rbracket = "]" + if target_lang in ('zh', 'ja', 'ko'): + rbracket = "]]" + with open(outfile, "w", encoding="utf8") as o: + for original_text, trans_text in zip(original_sentences, translations): + index += 1 + ner_found = [] + trans_text = trans_text.lstrip(".") + trans_text = trans_text.strip() + if original_text: + trans_text = trans_text.replace(". [", " [").replace(".[", " [").replace(" ", " ") + for key, ner_item in ner_mappings[index].items(): + if key in trans_text: + ner_found[key] = ner_item[1] + elif key.replace(" ", "") in trans_text: + key = key.replace(" ", "") + ner_found[key] = ner_item[1] + if target_lang in ('zh', 'ja', 'ko'): + trans_text.replace(" ", "") + trans_text.strip('#.') + if ner_found: + (blocks2, score) = get_aligned_text(original_text, trans_text, target_lang) + #since we know what slots we are replacing, + #we can align with the original sentence in the original language, + #and then extract the original NER value, or a translated version of the new value. + for (s1, s2, matched) in blocks2: + s1 = s1.strip() + s2 = se2.strip() + if "[" in s2 or "]" in s2: + key = s2.split("[")[1].split("]")[0] + if key in ner_found and key != s1: + ner_found[s1] = ner_found[key] + del ner_found[key] + for key in ner_found.keys(): + if key not in oiriginal_text: + del ner_found[key] + ner_found = list(ner_found.items()) + j = {'text': original_text, 'ner': ner_found, 'domain': domains[index], + 'id': row_ids[index], + 'lang': target_lang} + o.write(json.dumps(j) + "\n") + + +#translate to en, do ner in en, do back-trans, match for ner mapping and map to original sentence, do ner in target lang. +def back_trans(target_lang, infile, outfile, rulebase): + texts, ner_mappings, row_ids, domains = pre_translation_steps(infile, target_lang) + en_text = do_translations(texts, 'en') + with open("en_back_trans_"+infile, "w", encoding="utf8") as o: + for text for en_text: + o.write(json.dumps({"text": text})+"\n") + apply_ner("en_back_trans_"+infile, "en_back_trans_"+outfile, rulebase.get('en', []), "en") + en_text, ner_mappings2, _, _ = pre_translation_steps("en_back_trans_"+outfile, target_lang) + back_trans_text = do_translations(en_text, target_lang) + # TODO: resolve differences between ner_mappings2 and ner_mappings + post_translation_steps("ner_1_"+outfile, back_trans_text, texts, ner_mapping, ner_mappings2, row_ids, domains, target_lang=target_lang) + apply_ner("ner_1_"+outfile, outfile, rulebase.get(target_lang, []), target_lang) + +def cjk_detect(texts): + # korean + if re.search("[\uac00-\ud7a3]", texts): + return "ko" + # japanese + if re.search("[\u3040-\u30ff]", texts): + return "ja" + # chinese + if re.search("[\u4e00-\u9FFF]", texts): + return "zh" + return None + +def hf_ner(target_lang, hf_pipeline, text, predict_ner=None): + """ + run the text through a Huggingface ner pipeline for the text. + any tags found by this method that contradicts what was already tagged will take precedence. + For example, if we previously had categorized a noun as an ORG (which spacy sometimes does), but + the HF ner pipeline categorized it as a PERSON, then the tag will be changed to PERSON. + """ + is_cjk = target_lang in ("zh", "ja", "ko") + if not isinstance(text, list): + text_arr = [text] + else: + text_arr = text + if isinstance(predict_ner, dict): + predict_ner = [predict_ner] + if predict_ner is None: + predict_ner = [{} for i in range(len(text_arr))] + results_arr = hf_pipeline(text_arr) + for text, results, ner in zip(text_arr, results_arr, predict_ner): + print (results) + results.sort(key=lambda a: a['start']) + prev_word = [0,0] + prev_label = None + prev_start = None + start = 0 + for ner_result in results: + print (ner_result) + if True: + start = ner_result['start'] + is_cjk = cjk_detect(text[ner_result['start']:ner_result['end']]) + #print (text[ner_result['start']:ner_result['end']], is_cjk) + if not is_cjk: + if text[start] not in " {}[]()\"'“”《 》« »": + for j in range(1, start): + if start - j == -1 or text[start-j] in " {}[]()\"'“”《 》« »": + start = max(start -j, 0) + break + word = text[start:].strip().split(" ",1)[0] + if len(word) < ner_result['end'] - start: + end = ner_result['end'] + else: + end = start+len(word) + else: + start = ner_result['start'] + end = ner_result['end'] + print (start, end) + if prev_label is not None and (ner_result['entity'].startswith('B-') or prev_label != ner_result['entity'].split("-")[-1].upper() or\ + (prev_word[-1] < start and prev_word[0] != prev_word[1])): + if ner_result['entity'].startswith('B-') and prev_word[1] > start: + prev_word[1] = start + ner_word = text[prev_word[0]:prev_word[1]].strip(" {}[]()\"'“”《 》« »") + print ('**', ner_word, prev_label, prev_word, start) + if ner_word not in ner or prev_label not in ner[ner_word]: + if ner_word: + if prev_label == 'PER': prev_label = 'PERSON' + #remove overlaps + for key in list(ner.keys()): + if " "+key in ner_word or key+" " in ner_word:# or " "+ent in key or ent+" " in key: + del ner[key] + elif len(key) > 6 and key in ner_word: # parameterize 6 + del ner[key] + ner[ner_word] = prev_label + prev_label = ner_result['entity'].split("-")[-1].upper() + prev_word = [start, end] + elif prev_label is None: + prev_label = ner_result['entity'].split("-")[-1].upper() + prev_word = [start, end] + else: + prev_word[-1] = max(prev_word[-1], end) + if prev_word[0] != prev_word[1]: + ner_word = text[prev_word[0]:prev_word[1]].strip(" {}[]()\"'“”《 》« »") + if ner_word not in ner or prev_label not in ner[ner_word]: + if ner_word: + if prev_label == 'PER': prev_label = 'PERSON' + #remove overlaps + for key in list(ner.keys()): + if " "+key in ner_word or key+" " in ner_word:# or " "+ent in key or ent+" " in key: + del ner[key] + elif len(key) > 6 and key in ner_word: # parameterize 6 + del ner[key] + ner[ner_word] = prev_label + + return predict_ner + +from data_tooling.pii_processing.ontology.stopwords import stopwords as stopwords_ac_dc + + + +# do first a lexicon match, than a spacy match if any, and then do progressive groups of regex, then do hf_tranformers. +#TODO - do complicated rules, such as PERSON Inc. => ORG +#TODO - check for zh working properly +def apply_ner(infile, outfile, rule_base, target_lang, do_ontology_manager=True, do_spacy_if_avail=True, do_hf=True, char_before_after_window=10): + stopwords_target_lang = set(stopwords_ac_dc[target_lang]) + nlp = None + if do_spacy_if_avail: + if target_lang == 'en': + nlp = spacy.load('en_core_web_sm') + elif target_lang == 'zh': + nlp = spacy.load('zh_core_web_sm') + elif target_lang == 'pt': + nlp = spacy.load('pt_core_news_sm') + elif target_lang == 'fr': + nlp = spacy.load('fr_core_news_sm') + elif target_lang == 'ca': + nlp = spacy.load('ca_core_news_sm') + model = None + hf_pipeline = None + if do_hf: + model_name, model_cls = lang2ner_model.get(target_lang, [None, None]) + if model_cls is not None: + model = model_cls.from_pretrained(model_name) + hf_pipeline = pipeline("ner", model=model, tokenizer=AutoTokenizer.from_pretrained(model_name)) + if do_ontology_manager: + ontology_manager = OntologyManager(target_lang=target_lang) + else: + ontology_manager = None + right = {} + wrong = {} + with open(outfile, "w", encoding="utf8") as o: + for line in tqdm(open(infile, "rb")): + pred = [] #predicted regex rules ent:label + recs = json.loads(line) + if not isinstance(recs, list): + recs = [recs] + for d in recs: + print (d) + text = d['text'] + if not text: continue + predict_ner = d.get('ner',{}) + if ontology_manager: + parsed = ontology_manager.tokenize(text) + cunk2ner = list(parsed['chunk2ner'].items()) + for c in cunk2ner: + key, val = c[0][0].replace(" ", "").replace("_", "").replace("_", "") if target_lang in ('zh', 'ja', 'ko') else c[0][0].replace("_", " ").replace("_", " "), c[1] + predict_ner[key] = val + if nlp: + doc = nlp(text) + entities = list(doc.ents) + ents = dict(list(set([(entity.text, entity.label_) for entity in entities if + entity.label_ in ('PERSON', 'GPE', 'ORG', 'NORP') and 'http:' not in entity.text]))) + for ent, label in ents.items(): + if ent in predict_ner and ('PERSON' if predict_ner[ent] == 'PUBLIC_FIGURE' else predict_ner[ent]) ==label: + #print ("matched") + continue + else: + #remove simple overlap + for key in list(predict_ner.keys()): + if " "+key in ent or key+" " in ent: # or " "+ent in key or ent+" " in key: + if predict_ner[key] == 'PUBLIC_FIGURE': + label = "PUBLIC_FIGURE" + del predict_ner[key] + predict_ner[ent] = label + rule_level = -1 + ner = d['ner'] # the human tagged data + for rule_groups, ntimes in rule_base: + rule_level += 1 + for times in range(ntimes): + rule_id = -1 + for label, regex, old_label, before, after in rule_groups: + rule_id += 1 + if old_label is None and times > 0: continue + for ent in regex.findall(text): + if type(ent) != str: continue + if old_label is not None and (ent not in predict_ner or predict_ner[ent] != old_label): continue + t = text + len_ent = len(ent) + while ent in t: + i = t.index(ent) + if before: + before_t[max(0, i-char_before_after_window): i] + if before not in before_t: + t = t[i + len_ent:] + continue + if after: + after_t[i+len_x: min(len_text, i+len_ent+char_before_after_window)] + if after not in after_t: + t = t[i + len_ent:] + continue + #remove simple overlap + for key in list(predict_ner.keys()): + if " "+key in ent or key+" " in ent:# or " "+ent in key or ent+" " in key: + del predict_ner[key] + pred.append((ent, label, rule_id, rule_level)) + predict_ner[ent] = label + break + if hf_pipeline is not None: + hf_ner(target_lang, hf_pipeline, text, predict_ner) + d['ner'] = list(predict_ner.items()) + o.write(json.dumps(d)+"\n") + + + +if __name__ == "__main__": + + initial = target_lang = None + if "-initial" in sys.argv: + initial = sys.argv[sys.argv.index("-initial")+1] + if "-target_lang" in sys.argv: + target_lang = sys.argv[sys.argv.index("-target_lang")+1] + if target_lang: + #TODO - load the rulebase dynamically from pii_processing.regex folder a file of the form _.py + infile = f"{target_lang}.jsonl" + outfile = "predicted_"+infile + back_trans(target_lang, infile, outfile, rulebase) + + diff --git a/data_tooling/pii_processing/misc/create_examples.py b/data_tooling/pii_processing/misc/create_examples.py new file mode 100644 index 0000000..ac05444 --- /dev/null +++ b/data_tooling/pii_processing/misc/create_examples.py @@ -0,0 +1,1374 @@ +# coding=utf-8 +# Copyright, 2021 Ontocord, LLC, All rights reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +from datasets import load_dataset +import os +import re +import itertools +from re import finditer +import glob +import random + +""" + Creates a English dataset from different domains useful for doing PII detection. + Domains include enron (email), a subset of civil comments (forum message), casehold (legal), + newspop (news), banking 77 (financial), PII examples from Presidio (TBD). + + We do some deduplication and cleanup. + We add some PII as augumentation (TBD: some and tags added. Need to add some more categories). + + See specific licenses for each dataset. +""" + +def remove_html_tags(text): + """Remove html tags from a string""" + clean = re.compile('<.*?>') + return re.sub(clean, '', text) + +def camel_case_split(identifier): + matches = finditer('.+?(?:(?<=[a-z])(?=[A-Z])|(?<=[A-Z])(?=[A-Z][a-z])|$)', identifier) + return [m.group(0) for m in matches] + +def stem(s): + s = s.replace(".", " ").replace("!", " ").replace("?", " ").replace(",", " ").replace("-", " ").replace(";", " ").replace("'", " '").replace("\"", " \"") + sArr = s.lower().split() + if len(sArr) > 4: + sArr = sArr[:4] + s = " ".join([s1[:4] if len(s1) > 4 else s1 for s1 in sArr if s1.strip()]) + return s + +def save_enron_line(l2, prev, o): + l2 = remove_html_tags(l2) + l2 = l2.split('-----Original Message-----')[0].strip() + l2 = l2.split('---------------------- Forwarded')[0].strip() + l2 = l2.split('----- Forwarded')[0].strip() + l2 = l2.split('---------From:')[0].strip() + l2 = l2.split('**********************************************************************This')[0].strip() + l2 = l2.split('********************************************************************** This')[0].strip() + l2 = l2.split('******************************************************************This')[0].strip() + l2 = l2.split('*************************************************This')[0].strip() + l2 = l2.split('********************************************************************** This')[0].strip() + l2 = l2.split('--------- Inline attachment follows')[0].strip() + l2 = l2.split('The information contained in this e-mail message and')[0].strip() + l2 = l2.split('This message is for the designated recipient')[0].strip() + l2 = l2.split('***Please be advised')[0].strip() + l2 = l2.split('*******This message')[0].strip() + l2 = l2.split('This message (including any attachments) contains')[0].strip() + l2 = l2.split('*********************************************************')[0].strip() + l2 = l2.split('_________________________________________________________________Get')[0].strip() + l2 = l2.split('___________________________________________')[0].strip() + l2 = l2.split('__________________________________________________ Do')[0].strip() + l2 = l2.replace("\\\"", " \" ").replace("(", " (").replace(")", ") ").replace("[", " [").replace("]", "] ").replace("?", "? ").replace("!", "! ").replace("? ?", "??").replace("! !", "!!").replace(":", ": ").replace("\t", " ").replace("= ", "").replace("=20","").replace("=90","").replace("=018","").replace("=09","").replace("=3D","") + l2 = l2.replace(" s ", " 's ").replace(" ve ", " 've ").replace(" re ", " 're ").replace(" ll ", " 'll ").replace(" m ", " 'm ").replace(" t ", " 't ").replace(" d ", " 'd ").replace(" ", " ").replace(" ", " ").replace(" ", " ").replace(" ", " ").replace(" ", " ").replace(" ", " ").replace(" ", " ").replace(". . .", "...") + l2 = l2.replace(". yahoo", ".yahoo").replace("www. ", "www.").replace(". htm", ".htm").replace(". co", ".co").replace(". org", ".org").replace(". edu", ".edu").replace(". net", ".net").replace(". NET", ".NET").replace(". CO", ".CO").replace(". ORG", ".ORG").replace(". EDU", ".EDU").replace(": //", "://") + l2 = l2.replace(": 0", ":0").replace(": 1", ":1").replace(": 2", ":2").replace(": 3", ":3").replace(": 4", ":4").replace(": 5", ":5").replace(": 6", ":6").replace(": 7", ":7").replace(": 8", ":8").replace(": 9", ":9") + l2 = l2.replace(". url -", ".url - <<").replace(". doc -", ".doc - <<").replace(". pdf -", ".pdf <<").replace(". xls -", ".xls <<").replace(". url", ".url>>").replace(". doc", ".doc>>").replace(". pdf", ".pdf>>").replace(". xls", ".xls>>").replace("<< ", "<<").replace("> >", " ").replace(" ", " ") + l2 = l2.replace(". URL -", ".URL - <<").replace(". DOC -", ".DOC - <<").replace(". PDF -", ".PDF <<").replace(". XLS -", ".xls <<").replace(". URL", ".URL>>").replace(". DOC", ".DOC>>").replace(". PDF", ".PDF>>").replace(". XLS", ".XLS>>").replace("<< ", "<<").replace("> >", " ").replace(" ", " ") + l2 = l2.replace("RE:", "").replace("Re:", "").replace("RE: ", "").replace("Re: ", "").replace("Fw: ", "").replace("FW: ", "").replace("FWD: ", "").replace("Fwd: ", "") + l2 = l2.replace('Importance: High',':') + if "Sent:" in l2: return + l2 = l2.replace("...", "... ").replace("\"\"", " \" ").replace(" ", " ").strip(" -:;[]()\=<>\"").rstrip(".!?") + l2Arr = l2.split() + if len(l2Arr) > 3: + l2 = " ".join(itertools.chain(*[camel_case_split(a) for a in l2Arr])) + if l2.replace(":", "").replace("[", "").replace("]", "").replace(".", "").replace("!", "").replace("?", "").replace(",", "").replace("-", "").replace(";", "").replace(" ", "").lower() in prev: return + l2 = l2.replace("==", "--") + l2 = l2.replace("++", "--") + l2 = l2.replace("*~", "--") + l2 = l2.replace("||", "--") + l2 = l2.replace("**", "--") + l2 = l2.replace("__", "--") + l2 = l2.replace("##", "--") + for l3 in l2.split('--'): + l3 = l3.strip() + if l3: + for l4 in l3.split("Subject: "): + l4 = l4.strip('=, ') + if l4: o.write(l4+"\tenron\n") + prev[l2.replace(":", "").replace("[", "").replace("]", "").replace(".", "").replace("!", "").replace("?", "").replace(",", "").replace("-", "").replace(";", "").replace(" ", "").lower()] = 1 + +def has_any(s, lst): + for l in lst: + if l in s: return True + return False + +#from https://github.com/joke2k/faker/blob/master/faker/providers/person/en/__init__.py which is under the MIT License +#not an exausthive list. just to do some filtering for civil_comment. +first_names = { + 'Aaliyah', 'Abagail', 'Abbey', 'Abbie', 'Abbigail', 'Abby', 'Abigail', + 'Abigale', 'Abigayle', 'Abril', 'Achsah', 'Ada', 'Adah', 'Adaline', + 'Adalyn', 'Adalynn', 'Adamaris', 'Adda', 'Addie', 'Addison', 'Addisyn', + 'Addyson', 'Adel', 'Adela', 'Adelaide', 'Adele', 'Adelia', 'Adelina', + 'Adeline', 'Adell', 'Adella', 'Adelle', 'Adelyn', 'Adelynn', 'Adilene', + 'Adina', 'Adison', 'Adline', 'Adria', 'Adriana', 'Adriane', 'Adrianna', + 'Adrianne', 'Adriene', 'Adrienne', 'Adyson', 'Affie', 'Afton', 'Agatha', + 'Aggie', 'Agnes', 'Agness', 'Agusta', 'Aida', 'Aileen', 'Ailene', + 'Aili', 'Aimee', 'Ainsley', 'Aisha', 'Aiyana', 'Aiyanna', 'Aja', + 'Akeelah', 'Akira', 'Ala', 'Alabama', 'Alaina', 'Alana', 'Alani', + 'Alanna', 'Alannah', 'Alaya', 'Alayna', 'Alba', 'Alberta', 'Albertha', + 'Albertina', 'Albertine', 'Albina', 'Alcie', 'Alda', 'Aldona', 'Aleah', + 'Alease', 'Alecia', 'Aleen', 'Aleena', 'Alejandra', 'Alena', 'Alene', + 'Alesha', 'Alesia', 'Alessandra', 'Aleta', 'Aletha', 'Alethea', 'Alex', + 'Alexa', 'Alexandr', 'Alexandra', 'Alexandrea', 'Alexandria', 'Alexia', + 'Alexina', 'Alexis', 'Alexus', 'Alexys', 'Alfreda', 'Alia', 'Aliana', + 'Alice', 'Alicia', 'Alida', 'Alina', 'Aline', 'Alisa', 'Alisha', + 'Alison', 'Alissa', 'Alisson', 'Alivia', 'Aliya', 'Aliyah', 'Aliza', + 'Alize', 'Alla', 'Allean', 'Alleen', 'Allena', 'Allene', 'Allie', + 'Alline', 'Allison', 'Allisson', 'Ally', 'Allyson', 'Allyssa', 'Alma', + 'Almeda', 'Almedia', 'Almeta', 'Almina', 'Almira', 'Almyra', 'Aloma', + 'Alondra', 'Alpha', 'Alphonsine', 'Alta', 'Altha', 'Althea', 'Altie', + 'Alvena', 'Alvera', 'Alverda', 'Alverta', 'Alvina', 'Alvira', 'Alwilda', + 'Alwina', 'Alwine', 'Alyce', 'Alycia', 'Alys', 'Alysa', 'Alyse', + 'Alysha', 'Alysia', 'Alyson', 'Alyssa', 'Alyssia', 'Alyvia', 'Alzina', + 'Ama', 'Amalia', 'Amalie', 'Amanda', 'Amani', 'Amara', 'Amari', + 'Amaris', 'Amaya', 'Amber', 'Amberly', 'Amelia', 'Amelie', 'America', + 'Amey', 'Ami', 'Amiah', 'Amie', 'Amina', 'Amira', 'Amirah', 'Amiya', + 'Amiyah', 'Amma', 'Ammie', 'Amparo', 'Amy', 'Amya', 'Ana', 'Anabel', + 'Anabella', 'Anabelle', 'Anahi', 'Anais', 'Analia', 'Anastacia', + 'Anastasia', 'Anaya', 'Andra', 'Andrea', 'Andria', 'Angel', 'Angela', + 'Angele', 'Angeles', 'Angelia', 'Angelic', 'Angelica', 'Angelina', + 'Angeline', 'Angelique', 'Angelita', 'Angella', 'Angie', 'Anice', + 'Anie', 'Anika', 'Anissa', 'Anita', 'Anitra', 'Aniya', 'Aniyah', + 'Anjali', 'Anjanette', 'Anjelica', 'Ann', 'Anna', 'Annabel', 'Annabell', + 'Annabella', 'Annabelle', 'Annalise', 'Annamae', 'Annamarie', 'Anne', + 'Anneliese', 'Annemarie', 'Anner', 'Annetta', 'Annette', 'Annice', + 'Annie', 'Annika', 'Annis', 'Annmarie', 'Anona', 'Ansley', 'Antionette', + 'Antoinette', 'Antonetta', 'Antonette', 'Antonia', 'Antonina', 'Anya', + 'April', 'Ara', 'Arabella', 'Araceli', 'Aracely', 'Arah', 'Araminta', + 'Ardath', 'Ardelia', 'Ardell', 'Ardella', 'Ardelle', 'Arden', 'Ardeth', + 'Ardis', 'Ardith', 'Ardyce', 'Areli', 'Arely', 'Aretha', 'Argie', + 'Aria', 'Ariana', 'Ariane', 'Arianna', 'Arie', 'Ariel', 'Ariella', + 'Arielle', 'Arietta', 'Arizona', 'Arkie', 'Arla', 'Arleen', 'Arlena', + 'Arlene', 'Arleth', 'Arletta', 'Arley', 'Arlie', 'Arline', 'Arly', + 'Arlyne', 'Armani', 'Armida', 'Arminda', 'Arminta', 'Arnetta', 'Arra', + 'Arrie', 'Arta', 'Artelia', 'Arvilla', 'Aryana', 'Aryanna', 'Asha', + 'Ashanti', 'Ashely', 'Ashlea', 'Ashlee', 'Ashleigh', 'Ashley', 'Ashli', + 'Ashlie', 'Ashly', 'Ashlyn', 'Ashlynn', 'Ashtyn', 'Asia', 'Ason', + 'Aspen', 'Assunta', 'Astrid', 'Atha', 'Athena', 'Attie', 'Aubree', + 'Aubrey', 'Aubrie', 'Audie', 'Audra', 'Audrey', 'Audriana', 'Audrianna', + 'Audrina', 'Audry', 'Augusta', 'Augustina', 'Aura', 'Aurelia', + 'Aurilla', 'Aurora', 'Aurore', 'Autumn', 'Ava', 'Avah', 'Averi', + 'Averie', 'Avie', 'Avis', 'Ayana', 'Ayanna', 'Ayesha', 'Ayla', 'Ayleen', + 'Aylin', 'Azalee', 'Azaria', 'Azariah', 'Azul', 'Azzie', 'Babette', + 'Baby', 'Bailee', 'Bailey', 'Bama', 'Bambi', 'Barb', 'Barbara', + 'Barbie', 'Barbra', 'Baylee', 'Baylie', 'Bea', 'Beadie', 'Beatrice', + 'Beatrix', 'Beatriz', 'Beaulah', 'Bebe', 'Beckie', 'Becky', 'Beda', + 'Bee', 'Belen', 'Belia', 'Belinda', 'Bell', 'Bella', 'Belle', 'Belva', + 'Bena', 'Benita', 'Bennie', 'Berdie', 'Berenice', 'Bernadette', + 'Bernadine', 'Bernardine', 'Berneice', 'Bernetta', 'Bernice', + 'Berniece', 'Bernita', 'Berta', 'Bertha', 'Bertie', 'Bertina', 'Beryl', + 'Bess', 'Besse', 'Bessie', 'Beth', 'Betha', 'Bethann', 'Bethany', + 'Bethel', 'Bethzy', 'Betsey', 'Betsy', 'Bette', 'Bettie', 'Bettina', + 'Betty', 'Bettye', 'Bettyjane', 'Bettylou', 'Beula', 'Beulah', 'Bev', + 'Beverlee', 'Beverley', 'Beverly', 'Beyonce', 'Bianca', 'Biddie', + 'Billie', 'Billy', 'Billye', 'Bina', 'Bird', 'Birdella', 'Birdie', + 'Birtha', 'Birtie', 'Blair', 'Blake', 'Blanca', 'Blanch', 'Blanche', + 'Blanchie', 'Blossom', 'Bobbi', 'Bobbie', 'Bobby', 'Bobbye', 'Bonita', + 'Bonnie', 'Bonny', 'Braelyn', 'Brande', 'Brandee', 'Brandi', 'Brandie', + 'Brandon', 'Brandy', 'Brea', 'Breana', 'Breann', 'Breanna', 'Breanne', + 'Bree', 'Brenda', 'Brenna', 'Breonna', 'Brett', 'Bria', 'Briana', + 'Brianda', 'Brianna', 'Brianne', 'Bridget', 'Bridgett', 'Bridgette', + 'Brielle', 'Brigette', 'Brigid', 'Brigitte', 'Briley', 'Brinda', + 'Brinley', 'Brionna', 'Brisa', 'Bristol', 'Britany', 'Britney', + 'Britni', 'Britny', 'Britt', 'Britta', 'Brittaney', 'Brittani', + 'Brittanie', 'Brittany', 'Brittnay', 'Brittnee', 'Brittney', 'Brittni', + 'Brittnie', 'Brittny', 'Brook', 'Brooke', 'Brooklyn', 'Brooklynn', + 'Bryana', 'Bryanna', 'Brylee', 'Bryn', 'Brynlee', 'Brynn', 'Buelah', + 'Buena', 'Buffy', 'Bula', 'Bulah', 'Buna', 'Burnice', 'Byrd', 'Byrdie', + 'Caddie', 'Cadence', 'Cailyn', 'Caitlin', 'Caitlyn', 'Caitlynn', + 'Caldonia', 'Caleigh', 'Cali', 'Calista', 'Calla', 'Calleigh', 'Callie', + 'Cambria', 'Cameron', 'Cami', 'Camila', 'Camilla', 'Camille', 'Camisha', + 'Cammie', 'Campbell', 'Camryn', 'Candace', 'Candi', 'Candice', + 'Candida', 'Candis', 'Candy', 'Candyce', 'Cannie', 'Capitola', 'Cappie', + 'Caprice', 'Cara', 'Caren', 'Carey', 'Cari', 'Carie', 'Carin', 'Carina', + 'Carisa', 'Carissa', 'Carla', 'Carlee', 'Carleen', 'Carleigh', + 'Carlene', 'Carley', 'Carli', 'Carlie', 'Carlota', 'Carlotta', 'Carly', + 'Carlyn', 'Carma', 'Carmel', 'Carmela', 'Carmelita', 'Carmella', + 'Carmen', 'Caro', 'Carol', 'Carolann', 'Carole', 'Carolee', 'Carolina', + 'Caroline', 'Carolyn', 'Carolyne', 'Carolynn', 'Caron', 'Carra', + 'Carri', 'Carrie', 'Carrol', 'Carroll', 'Carry', 'Carson', 'Cary', + 'Caryl', 'Caryn', 'Casandra', 'Casey', 'Casie', 'Cassandra', 'Cassidy', + 'Cassie', 'Cassondra', 'Catalina', 'Catharine', 'Catherine', 'Cathern', + 'Cathey', 'Cathi', 'Cathie', 'Cathleen', 'Cathrine', 'Cathryn', 'Cathy', + 'Catina', 'Catrina', 'Caydence', 'Cayla', 'Caylee', 'Cecelia', 'Cecile', + 'Cecilia', 'Cecily', 'Ceil', 'Celena', 'Celesta', 'Celeste', 'Celestia', + 'Celestine', 'Celia', 'Celie', 'Celina', 'Celine', 'Cena', 'Ceola', + 'Chaka', 'Chana', 'Chanda', 'Chandler', 'Chandra', 'Chanel', 'Chanelle', + 'Chaney', 'Chanie', 'Channie', 'Channing', 'Chantal', 'Chante', + 'Chantel', 'Chantelle', 'Charissa', 'Charisse', 'Charity', 'Charla', + 'Charlee', 'Charleen', 'Charlene', 'Charley', 'Charlie', 'Charline', + 'Charlize', 'Charlotta', 'Charlotte', 'Charlottie', 'Charlsie', + 'Charmaine', 'Charolette', 'Chase', 'Chasity', 'Chastity', 'Chaya', + 'Chelsea', 'Chelsey', 'Chelsi', 'Chelsie', 'Chelsy', 'Cher', 'Cherelle', + 'Cheri', 'Cherie', 'Cherilyn', 'Cherise', 'Cherish', 'Cherrelle', + 'Cherri', 'Cherrie', 'Cherry', 'Cherryl', 'Cheryl', 'Cheryle', + 'Cheryll', 'Chessie', 'Chestina', 'Cheyanne', 'Cheyenne', 'Chimere', + 'China', 'Chiquita', 'Chloe', 'Chloie', 'Chris', 'Chrissie', 'Chrissy', + 'Christa', 'Christal', 'Christeen', 'Christel', 'Christen', 'Christena', + 'Christene', 'Christi', 'Christian', 'Christiana', 'Christie', + 'Christin', 'Christina', 'Christine', 'Christy', 'Chrystal', 'Chyna', + 'Chynna', 'Ciara', 'Ciarra', 'Cicely', 'Cielo', 'Ciera', 'Cierra', + 'Ciji', 'Cilla', 'Cinda', 'Cindi', 'Cindy', 'Cinnamon', 'Cinthia', + 'Citlali', 'Citlalli', 'Clair', 'Claire', 'Clara', 'Clarabelle', + 'Clare', 'Claribel', 'Clarice', 'Clarinda', 'Clarine', 'Clarisa', + 'Clarissa', 'Classie', 'Claudette', 'Claudia', 'Claudie', 'Claudine', + 'Cleda', 'Clella', 'Clem', 'Clemence', 'Clementina', 'Clementine', + 'Clemie', 'Clemma', 'Clemmie', 'Cleo', 'Cleola', 'Cleone', 'Cleora', + 'Cleta', 'Cleva', 'Clevie', 'Cliffie', 'Cloe', 'Clora', 'Clotilda', + 'Clotilde', 'Clyda', 'Clydie', 'Clytie', 'Coleen', 'Coletta', 'Colette', + 'Colleen', 'Collette', 'Columbia', 'Concepcion', 'Concetta', 'Concha', + 'Connie', 'Constance', 'Consuela', 'Consuelo', 'Contina', 'Cora', + 'Coraima', 'Coral', 'Coralie', 'Corda', 'Cordelia', 'Cordella', + 'Cordia', 'Cordie', 'Corean', 'Corene', 'Coretta', 'Corey', 'Cori', + 'Corie', 'Corina', 'Corine', 'Corinna', 'Corinne', 'Corliss', + 'Cornelia', 'Cornie', 'Corrie', 'Corrina', 'Corrine', 'Cortney', 'Cory', + 'Courtney', 'Creola', 'Cressie', 'Crete', 'Crissie', 'Crissy', 'Crista', + 'Cristal', 'Cristen', 'Cristi', 'Cristin', 'Cristina', 'Cristine', + 'Cristy', 'Cruz', 'Crysta', 'Crystal', 'Cuba', 'Cydney', 'Cyndi', + 'Cyntha', 'Cynthia', 'Dafne', 'Dagmar', 'Dagny', 'Dahlia', 'Daija', + 'Daijah', 'Daisey', 'Daisha', 'Daisie', 'Daisy', 'Daisye', 'Daja', + 'Dakota', 'Dale', 'Dalia', 'Dallas', 'Damaris', 'Dana', 'Danae', + 'Daneen', 'Danelle', 'Danette', 'Dani', 'Dania', 'Danica', 'Daniela', + 'Daniele', 'Daniella', 'Danielle', 'Danika', 'Danita', 'Danna', + 'Dannie', 'Dannielle', 'Danyel', 'Danyell', 'Danyelle', 'Daphne', + 'Dara', 'Darby', 'Darci', 'Darcie', 'Darcy', 'Daria', 'Darian', + 'Dariana', 'Darla', 'Darleen', 'Darlene', 'Darline', 'Darlyne', 'Dasia', + 'Davina', 'Dawn', 'Dawna', 'Dawne', 'Dayami', 'Dayana', 'Dayanara', + 'Dayle', 'Dayna', 'Dayse', 'Deana', 'Deandra', 'Deann', 'Deanna', + 'Deanne', 'Deasia', 'Deb', 'Debbi', 'Debbie', 'Debbra', 'Debby', + 'Debera', 'Debi', 'Debora', 'Deborah', 'Deborrah', 'Debra', 'Debrah', + 'Debroah', 'Dedra', 'Dee', 'Deeann', 'Deedee', 'Deena', 'Deetta', + 'Deidra', 'Deidre', 'Deirdre', 'Deja', 'Dejah', 'Delaney', 'Delcie', + 'Delfina', 'Delia', 'Deliah', 'Delila', 'Delilah', 'Delina', 'Delinda', + 'Delisa', 'Dell', 'Della', 'Dellar', 'Delle', 'Dellia', 'Dellie', + 'Delma', 'Delois', 'Delora', 'Delores', 'Deloris', 'Delpha', 'Delphia', + 'Delphine', 'Delsie', 'Delta', 'Dema', 'Demetra', 'Demetria', 'Demi', + 'Dena', 'Deneen', 'Denese', 'Denice', 'Denine', 'Denise', 'Denisha', + 'Denisse', 'Denita', 'Dennie', 'Desirae', 'Desiree', 'Dessa', 'Dessie', + 'Destany', 'Destinee', 'Destiney', 'Destini', 'Destiny', 'Devan', + 'Devin', 'Devon', 'Devyn', 'Dewey', 'Deyanira', 'Dezzie', 'Diamond', + 'Dian', 'Diana', 'Diandra', 'Diane', 'Diann', 'Dianna', 'Dianne', + 'Dicie', 'Dicy', 'Dillie', 'Dimple', 'Dina', 'Dinah', 'Dione', 'Dionne', + 'Dixie', 'Diya', 'Djuana', 'Djuna', 'Docia', 'Dola', 'Dollie', 'Dolly', + 'Dollye', 'Dolores', 'Doloris', 'Domenica', 'Dominga', 'Dominique', + 'Dominque', 'Domonique', 'Dona', 'Donia', 'Donie', 'Donita', 'Donna', + 'Donnie', 'Dora', 'Dorathea', 'Dorathy', 'Dorcas', 'Doreen', 'Dorene', + 'Doretha', 'Doretta', 'Dori', 'Dorinda', 'Dorine', 'Doris', 'Dorla', + 'Dorotha', 'Dorothea', 'Dorothy', 'Dorris', 'Dortha', 'Dorthea', + 'Dorthey', 'Dorthy', 'Dosha', 'Doshia', 'Doshie', 'Dosia', 'Dossie', + 'Dot', 'Dottie', 'Dotty', 'Dove', 'Dovie', 'Drema', 'Drew', 'Drucilla', + 'Drusilla', 'Dulce', 'Dulcie', 'Dusty', 'Dwan', 'Dyan', 'Dylan', + 'Earlean', 'Earlene', 'Earlie', 'Earline', 'Earnestine', 'Eartha', + 'Easter', 'Eathel', 'Ebba', 'Eboni', 'Ebony', 'Echo', 'Eda', 'Eddie', + 'Eden', 'Edie', 'Edith', 'Edla', 'Edmonia', 'Edna', 'Ednah', 'Edra', + 'Edrie', 'Edris', 'Edwina', 'Edyth', 'Edythe', 'Effa', 'Effie', + 'Eileen', 'Eithel', 'Ela', 'Elaina', 'Elaine', 'Elana', 'Elayne', + 'Elba', 'Elberta', 'Elda', 'Eldora', 'Eleanor', 'Eleanora', 'Eleanore', + 'Elease', 'Electa', 'Elena', 'Elenor', 'Elenora', 'Elenore', 'Eleonora', + 'Eleonore', 'Elfie', 'Elfreda', 'Elfrieda', 'Elgie', 'Elia', 'Eliana', + 'Elianna', 'Elida', 'Elinor', 'Elinore', 'Elisa', 'Elisabeth', 'Elise', + 'Elisha', 'Elissa', 'Eliza', 'Elizabet', 'Elizabeth', 'Elizbeth', + 'Elizebeth', 'Ella', 'Ellamae', 'Ellar', 'Elle', 'Ellen', 'Eller', + 'Elliana', 'Ellie', 'Ellyn', 'Elma', 'Elmina', 'Elmira', 'Elmire', + 'Elmyra', 'Elna', 'Elnora', 'Elodie', 'Elois', 'Eloisa', 'Eloise', + 'Elouise', 'Elsa', 'Else', 'Elsie', 'Elta', 'Elva', 'Elvera', 'Elvia', + 'Elvie', 'Elvina', 'Elvira', 'Elwanda', 'Elyse', 'Elyssa', 'Elza', + 'Elzada', 'Ema', 'Emaline', 'Ember', 'Emelia', 'Emelie', 'Emeline', + 'Emely', 'Emerald', 'Emerson', 'Emery', 'Emilee', 'Emilia', 'Emilie', + 'Emily', 'Emma', 'Emmalee', 'Emmaline', 'Emmer', 'Emmie', 'Emmy', + 'Emogene', 'Ena', 'Enid', 'Enola', 'Enriqueta', 'Eola', 'Eppie', + 'Epsie', 'Era', 'Erica', 'Ericka', 'Erie', 'Erika', 'Erin', 'Eris', + 'Erla', 'Erlene', 'Erlinda', 'Erline', 'Erma', 'Ermina', 'Ermine', + 'Erna', 'Ernestina', 'Ernestine', 'Erykah', 'Eryn', 'Esmeralda', + 'Esperanza', 'Essa', 'Essence', 'Essie', 'Esta', 'Estefani', + 'Estefania', 'Estefany', 'Estela', 'Estell', 'Estella', 'Estelle', + 'Ester', 'Esther', 'Estie', 'Estrella', 'Etha', 'Ethel', 'Ethelene', + 'Ethelyn', 'Ether', 'Ethie', 'Ethyl', 'Ethyle', 'Etna', 'Etta', 'Etter', + 'Ettie', 'Eudora', 'Eugenia', 'Eugenie', 'Eula', 'Eulah', 'Eulalia', + 'Eulalie', 'Euna', 'Eunice', 'Euphemia', 'Eura', 'Eva', 'Evalena', + 'Evaline', 'Evalyn', 'Evangelina', 'Evangeline', 'Eve', 'Evelena', + 'Evelin', 'Evelina', 'Eveline', 'Evelyn', 'Evelyne', 'Evelynn', 'Ever', + 'Evette', 'Evia', 'Evie', 'Evita', 'Evon', 'Evonne', 'Exa', 'Exie', + 'Fabiola', 'Fae', 'Fairy', 'Faith', 'Fallon', 'Falon', 'Fannie', + 'Fanny', 'Fannye', 'Farah', 'Farrah', 'Fatima', 'Fawn', 'Fay', 'Faye', + 'Felecia', 'Felice', 'Felicia', 'Felicie', 'Felicitas', 'Felicity', + 'Felipa', 'Felisha', 'Fern', 'Fernanda', 'Ferne', 'Fidelia', 'Filomena', + 'Finley', 'Fiona', 'Flavia', 'Fleda', 'Fleeta', 'Fleta', 'Flo', + 'Flonnie', 'Flor', 'Flora', 'Florance', 'Florence', 'Florene', + 'Floretta', 'Florida', 'Florie', 'Florine', 'Florrie', 'Flossie', + 'Floy', 'Fonda', 'Forest', 'Fran', 'Franc', 'Frances', 'Francesca', + 'Francies', 'Francina', 'Francine', 'Francis', 'Francisca', + 'Francisquita', 'Frankie', 'Freda', 'Freddie', 'Frederica', + 'Fredericka', 'Freeda', 'Freida', 'Frida', 'Frieda', 'Frona', 'Fronia', + 'Fronie', 'Fronnie', 'Fumiko', 'Gabriela', 'Gabriella', 'Gabrielle', + 'Gail', 'Gale', 'Galilea', 'Garnet', 'Garnett', 'Gay', 'Gaye', 'Gayla', + 'Gayle', 'Gaylene', 'Gaynell', 'Gearldine', 'Gemma', 'Gena', 'Gene', + 'Genesis', 'Geneva', 'Genevieve', 'Genevra', 'Genie', 'Gennie', + 'Genoveva', 'Georganna', 'Georgeann', 'Georgeanna', 'Georgene', + 'Georgetta', 'Georgette', 'Georgia', 'Georgiana', 'Georgiann', + 'Georgianna', 'Georgie', 'Georgina', 'Georgine', 'Geraldine', 'Geralyn', + 'Gerda', 'Geri', 'Germaine', 'Gerri', 'Gerry', 'Gertha', 'Gertie', + 'Gertrude', 'Gia', 'Giada', 'Giana', 'Gianna', 'Gidget', 'Gigi', + 'Gilda', 'Gillian', 'Gillie', 'Gina', 'Ginger', 'Ginny', 'Giovanna', + 'Girtha', 'Gisele', 'Giselle', 'Gisselle', 'Giuliana', 'Gladis', + 'Gladyce', 'Gladys', 'Glenda', 'Glendora', 'Glenn', 'Glenna', 'Glennie', + 'Glennis', 'Glinda', 'Gloria', 'Glynda', 'Glynis', 'Golda', 'Golden', + 'Goldia', 'Goldie', 'Grace', 'Gracelyn', 'Gracia', 'Gracie', 'Graciela', + 'Grayce', 'Grecia', 'Gregoria', 'Greta', 'Gretchen', 'Gretta', 'Grisel', + 'Griselda', 'Guadalupe', 'Gunda', 'Gussie', 'Gusta', 'Gustie', 'Gwen', + 'Gwenda', 'Gwendolyn', 'Gwyn', 'Gwyneth', 'Hadassah', 'Hadley', + 'Hailee', 'Hailey', 'Hailie', 'Haleigh', 'Haley', 'Hali', 'Halie', + 'Halle', 'Halley', 'Hallie', 'Hana', 'Hanna', 'Hannah', 'Harlene', + 'Harley', 'Harlow', 'Harmony', 'Harper', 'Harriet', 'Harriett', + 'Harriette', 'Haruko', 'Hasel', 'Hassie', 'Hattie', 'Haven', 'Hayden', + 'Haylee', 'Hayleigh', 'Hayley', 'Haylie', 'Hazel', 'Hazelle', 'Hazle', + 'Heather', 'Heaven', 'Hedwig', 'Hedy', 'Heidi', 'Heidy', 'Helaine', + 'Helen', 'Helena', 'Helene', 'Helga', 'Hellen', 'Helma', 'Helyn', + 'Hennie', 'Henretta', 'Henrietta', 'Henriette', 'Herlinda', 'Herma', + 'Hermina', 'Hermine', 'Herminia', 'Hertha', 'Hessie', 'Hester', + 'Hettie', 'Hetty', 'Hilah', 'Hilary', 'Hilda', 'Hildegard', + 'Hildegarde', 'Hildred', 'Hildur', 'Hillary', 'Hilma', 'Holli', + 'Hollie', 'Hollis', 'Holly', 'Honora', 'Hope', 'Hortencia', 'Hortense', + 'Hortensia', 'Hulda', 'Huldah', 'Hunter', 'Ica', 'Icey', 'Icie', 'Icy', + 'Ida', 'Idabelle', 'Idamae', 'Idell', 'Idella', 'Iesha', 'Ieshia', + 'Ila', 'Ilah', 'Ilda', 'Ilene', 'Iliana', 'Illa', 'Ilma', 'Ilo', + 'Ilona', 'Ima', 'Imani', 'Imelda', 'Imo', 'Imogene', 'Ina', 'India', + 'Indiana', 'Inell', 'Ines', 'Inez', 'Infant', 'Inga', 'Ingeborg', + 'Inger', 'Ingrid', 'Iola', 'Iona', 'Ione', 'Ira', 'Ireland', 'Irena', + 'Irene', 'Iridian', 'Irine', 'Iris', 'Irma', 'Irva', 'Isa', 'Isabel', + 'Isabela', 'Isabell', 'Isabella', 'Isabelle', 'Isadora', 'Isamar', + 'Isis', 'Isla', 'Isobel', 'Itzel', 'Iva', 'Ivah', 'Ivana', 'Ivanna', + 'Ivette', 'Ivey', 'Ivie', 'Ivonne', 'Ivory', 'Ivy', 'Iyana', 'Iyanna', + 'Iza', 'Izabella', 'Izabelle', 'Izetta', 'Izola', 'Izora', 'Jacalyn', + 'Jacey', 'Jackeline', 'Jacki', 'Jackie', 'Jacklyn', 'Jaclyn', 'Jacque', + 'Jacquelin', 'Jacqueline', 'Jacquelyn', 'Jacquline', 'Jacqulyn', 'Jada', + 'Jade', 'Jaden', 'Jadyn', 'Jaeda', 'Jaelyn', 'Jaelynn', 'Jaida', + 'Jaiden', 'Jaidyn', 'Jailene', 'Jailyn', 'Jaime', 'Jaimee', 'Jakayla', + 'Jaleesa', 'Jalisa', 'Jalissa', 'Jaliyah', 'Jalyn', 'Jalynn', 'Jamey', + 'Jami', 'Jamie', 'Jamila', 'Jamiya', 'Jammie', 'Jamya', 'Jan', 'Jana', + 'Janae', 'Janay', 'Jane', 'Janeen', 'Janel', 'Janell', 'Janelle', + 'Janene', 'Janessa', 'Janet', 'Janette', 'Janey', 'Janiah', 'Janice', + 'Janie', 'Janine', 'Janis', 'Janiya', 'Janiyah', 'Jann', 'Janna', + 'Jannette', 'Jannie', 'January', 'Janyce', 'Jaquelin', 'Jaqueline', + 'Jaslene', 'Jaslyn', 'Jasmin', 'Jasmine', 'Jasmyn', 'Jasmyne', + 'Jaunita', 'Jaycee', 'Jaycie', 'Jayda', 'Jayde', 'Jayden', 'Jaye', + 'Jayla', 'Jaylah', 'Jaylee', 'Jayleen', 'Jaylen', 'Jaylene', 'Jaylin', + 'Jaylyn', 'Jaylynn', 'Jayme', 'Jayne', 'Jazlene', 'Jazlyn', 'Jazlynn', + 'Jazmin', 'Jazmine', 'Jazmyn', 'Jazmyne', 'Jean', 'Jeana', 'Jeane', + 'Jeanetta', 'Jeanette', 'Jeanie', 'Jeanine', 'Jeanmarie', 'Jeanna', + 'Jeanne', 'Jeannette', 'Jeannie', 'Jeannine', 'Jeffie', 'Jemima', + 'Jena', 'Jenelle', 'Jenifer', 'Jenilee', 'Jenna', 'Jennette', 'Jenni', + 'Jennie', 'Jennifer', 'Jenniffer', 'Jenny', 'Jensen', 'Jeraldine', + 'Jeri', 'Jerica', 'Jerilyn', 'Jerilynn', 'Jerri', 'Jerrica', 'Jerrie', + 'Jerrilyn', 'Jerusha', 'Jeryl', 'Jesenia', 'Jesica', 'Jesse', + 'Jessenia', 'Jessi', 'Jessica', 'Jessie', 'Jessika', 'Jessye', 'Jetta', + 'Jettie', 'Jewel', 'Jewell', 'Jill', 'Jillian', 'Jimena', 'Jinnie', + 'Jo', 'Joan', 'Joana', 'Joanie', 'Joann', 'Joanna', 'Joanne', 'Jocelyn', + 'Jocelyne', 'Jocelynn', 'Jodi', 'Jodie', 'Jody', 'Joell', 'Joella', + 'Joelle', 'Joellen', 'Joetta', 'Joette', 'Johana', 'Johanna', + 'Johannah', 'Johnie', 'Johnna', 'Johnnie', 'Joi', 'Joleen', 'Jolene', + 'Jolette', 'Jolie', 'Joline', 'Jonell', 'Joni', 'Jonna', 'Jonnie', + 'Jordan', 'Jordin', 'Jordyn', 'Joretta', 'Jorja', 'Josefa', 'Josefina', + 'Josefita', 'Joselin', 'Joseline', 'Joselyn', 'Josephine', 'Josette', + 'Josie', 'Josiephine', 'Joslyn', 'Jossie', 'Journey', 'Jovita', 'Joy', + 'Joyce', 'Joycelyn', 'Joye', 'Juana', 'Juanita', 'Judi', 'Judie', + 'Judith', 'Judy', 'Judyth', 'Jule', 'Juli', 'Julia', 'Juliana', + 'Juliann', 'Julianna', 'Julianne', 'Julie', 'Juliet', 'Juliette', + 'Julisa', 'Julissa', 'June', 'Junia', 'Junie', 'Justice', 'Justina', + 'Justine', 'Kaaren', 'Kacey', 'Kaci', 'Kacie', 'Kacy', 'Kadence', + 'Kadijah', 'Kaela', 'Kaelyn', 'Kaelynn', 'Kaia', 'Kaila', 'Kailee', + 'Kailey', 'Kailyn', 'Kaitlin', 'Kaitlyn', 'Kaitlynn', 'Kaiya', 'Kala', + 'Kaleena', 'Kaleigh', 'Kalene', 'Kaley', 'Kali', 'Kalie', 'Kaliyah', + 'Kallie', 'Kalyn', 'Kamari', 'Kameron', 'Kami', 'Kamila', 'Kamilah', + 'Kamora', 'Kamryn', 'Kamya', 'Kandace', 'Kandi', 'Kandice', 'Kandy', + 'Kanesha', 'Kanisha', 'Kara', 'Karan', 'Karel', 'Karen', 'Kari', + 'Karie', 'Karin', 'Karina', 'Karis', 'Karissa', 'Karla', 'Karlee', + 'Karlene', 'Karley', 'Karli', 'Karlie', 'Karly', 'Karma', 'Karol', + 'Karolyn', 'Karon', 'Karren', 'Karri', 'Karrie', 'Karsyn', 'Karyl', + 'Karyme', 'Karyn', 'Kasandra', 'Kasey', 'Kasie', 'Kassandra', 'Kassidy', + 'Kassie', 'Katarina', 'Kate', 'Katelin', 'Katelyn', 'Katelynn', + 'Katerina', 'Kathaleen', 'Katharina', 'Katharine', 'Katharyn', + 'Katherin', 'Katherine', 'Kathern', 'Katheryn', 'Kathey', 'Kathi', + 'Kathie', 'Kathleen', 'Kathlene', 'Kathlyn', 'Kathrine', 'Kathryn', + 'Kathryne', 'Kathy', 'Kathyrn', 'Kati', 'Katia', 'Katie', 'Katina', + 'Katlin', 'Katlyn', 'Katlynn', 'Katrina', 'Kattie', 'Katy', 'Kay', + 'Kaya', 'Kaycee', 'Kayden', 'Kaydence', 'Kaye', 'Kayla', 'Kaylah', + 'Kaylan', 'Kaylee', 'Kayleen', 'Kayleigh', 'Kaylen', 'Kaylene', + 'Kayley', 'Kayli', 'Kaylie', 'Kaylin', 'Kaylyn', 'Kaylynn', 'Kazuko', + 'Keanna', 'Keara', 'Kecia', 'Keeley', 'Keely', 'Keena', 'Keesha', + 'Keila', 'Keira', 'Keisha', 'Kelcie', 'Keli', 'Kelis', 'Kellee', + 'Kelley', 'Kelli', 'Kellie', 'Kelly', 'Kelsea', 'Kelsey', 'Kelsi', + 'Kelsie', 'Kendal', 'Kendall', 'Kendra', 'Kenia', 'Kenisha', 'Kenley', + 'Kenna', 'Kennedi', 'Kennedy', 'Kenya', 'Kenyatta', 'Kenzie', 'Keri', + 'Kerri', 'Kerrie', 'Kerry', 'Kesha', 'Keshia', 'Keyla', 'Khadijah', + 'Khalilah', 'Khloe', 'Kia', 'Kiana', 'Kianna', 'Kiara', 'Kiarra', + 'Kiera', 'Kierra', 'Kiersten', 'Kiley', 'Kim', 'Kimber', 'Kimberely', + 'Kimberlee', 'Kimberley', 'Kimberli', 'Kimberlie', 'Kimberly', 'Kimora', + 'Kindra', 'Kinley', 'Kinsey', 'Kinsley', 'Kira', 'Kirsten', 'Kirstie', + 'Kirstin', 'Kisha', 'Kittie', 'Kitty', 'Kiya', 'Kiyoko', 'Kizzie', + 'Kizzy', 'Kloe', 'Kori', 'Kortney', 'Kourtney', 'Kris', 'Krissy', + 'Krista', 'Kristal', 'Kristan', 'Kristen', 'Kristi', 'Kristian', + 'Kristie', 'Kristin', 'Kristina', 'Kristine', 'Kristy', 'Kristyn', + 'Krysta', 'Krystal', 'Krysten', 'Krystin', 'Krystina', 'Krystle', 'Kya', + 'Kyara', 'Kyla', 'Kylah', 'Kyle', 'Kylee', 'Kyleigh', 'Kylene', 'Kylie', + 'Kyra', 'Kyrie', 'Lacey', 'Laci', 'Lacie', 'Lacy', 'Ladonna', 'Lady', + 'Lahoma', 'Laila', 'Lailah', 'Lainey', 'Laisha', 'Lakeisha', 'Laken', + 'Lakendra', 'Lakesha', 'Lakeshia', 'Lakisha', 'Lala', 'Lalla', 'Lana', + 'Lanette', 'Laney', 'Lani', 'Lanie', 'Lanita', 'Lannie', 'Laquita', + 'Lara', 'Larae', 'Laraine', 'Larissa', 'Larue', 'Lashanda', 'Lashawn', + 'Lashonda', 'Lashunda', 'Lasonya', 'Lassie', 'Latanya', 'Latarsha', + 'Latasha', 'Latesha', 'Latifah', 'Latisha', 'Latonia', 'Latonya', + 'Latoria', 'Latosha', 'Latoya', 'Latoyia', 'Latrice', 'Latricia', + 'Latrina', 'Launa', 'Laura', 'Laureen', 'Laurel', 'Lauren', 'Laurene', + 'Lauretta', 'Laurette', 'Lauri', 'Laurie', 'Laurine', 'Lauryn', + 'Lavada', 'Lavelle', 'Lavenia', 'Lavera', 'Lavern', 'Laverna', + 'Laverne', 'Lavina', 'Lavinia', 'Lavon', 'Lavona', 'Lavonda', 'Lavonia', + 'Lavonne', 'Lawanda', 'Layla', 'Laylah', 'Lea', 'Leafy', 'Leah', + 'Leala', 'Leana', 'Leandra', 'Leaner', 'Leann', 'Leanna', 'Leanne', + 'Leatha', 'Leatrice', 'Leda', 'Lee', 'Leeann', 'Leesa', 'Leia', 'Leigh', + 'Leighton', 'Leila', 'Leilani', 'Leisa', 'Leisha', 'Leitha', 'Lela', + 'Lelah', 'Lelar', 'Lelia', 'Lella', 'Lemma', 'Lempi', 'Lena', 'Lenna', + 'Lennie', 'Lenora', 'Lenore', 'Leola', 'Leoma', 'Leona', 'Leone', + 'Leonia', 'Leonie', 'Leonor', 'Leonora', 'Leonore', 'Leontine', 'Leora', + 'Leota', 'Lera', 'Lesa', 'Lesia', 'Leslee', 'Lesley', 'Lesli', 'Leslie', + 'Lesly', 'Lessie', 'Lesta', 'Leta', 'Letha', 'Lethia', 'Leticia', + 'Letitia', 'Letta', 'Lettie', 'Letty', 'Leva', 'Levina', 'Lexi', + 'Lexie', 'Lexis', 'Lexus', 'Leyla', 'Lia', 'Liana', 'Liane', 'Libbie', + 'Libby', 'Liberty', 'Lida', 'Liddie', 'Lidia', 'Lidie', 'Lila', 'Lilah', + 'Lilia', 'Lilian', 'Liliana', 'Lilianna', 'Lilie', 'Lilla', 'Liller', + 'Lillia', 'Lillian', 'Lilliana', 'Lillianna', 'Lillie', 'Lillis', + 'Lilly', 'Lily', 'Lilyan', 'Lilyana', 'Lilyanna', 'Lina', 'Linda', + 'Lindsay', 'Lindsey', 'Lindy', 'Linette', 'Linna', 'Linnea', 'Linnie', + 'Linsey', 'Lisa', 'Lisbeth', 'Lise', 'Lisette', 'Lisha', 'Lissa', + 'Lissette', 'Lissie', 'Lita', 'Litha', 'Littie', 'Litzy', 'Livia', + 'Liz', 'Liza', 'Lizabeth', 'Lizbeth', 'Lizeth', 'Lizette', 'Lizzie', + 'Lockie', 'Loda', 'Logan', 'Lois', 'Lola', 'Lolita', 'Lolla', 'Lollie', + 'Loma', 'Lona', 'London', 'Londyn', 'Loni', 'Lonie', 'Lonna', 'Lonnie', + 'Lora', 'Loraine', 'Lorayne', 'Lorean', 'Loree', 'Loreen', 'Lorelai', + 'Lorelei', 'Loren', 'Lorena', 'Lorene', 'Lorenza', 'Loretta', 'Loretto', + 'Lori', 'Loria', 'Loriann', 'Lorie', 'Lorinda', 'Lorine', 'Loris', + 'Lorna', 'Lorraine', 'Lorrayne', 'Lorri', 'Lorrie', 'Lossie', 'Lota', + 'Lotta', 'Lottie', 'Lou', 'Louann', 'Louanna', 'Louella', 'Louetta', + 'Louie', 'Louisa', 'Louise', 'Louisiana', 'Loula', 'Lourdes', + 'Louvenia', 'Love', 'Lovey', 'Lovie', 'Lovina', 'Lovisa', 'Loyce', 'Lu', + 'Luana', 'Luann', 'Luanne', 'Luberta', 'Lucero', 'Lucetta', 'Lucia', + 'Luciana', 'Lucie', 'Lucile', 'Lucille', 'Lucina', 'Lucinda', 'Lucindy', + 'Lucretia', 'Lucy', 'Luda', 'Ludie', 'Lue', 'Luella', 'Luetta', + 'Lugenia', 'Luisa', 'Lula', 'Lulah', 'Lular', 'Lulie', 'Lulla', 'Lulu', + 'Luna', 'Lupe', 'Lura', 'Lurana', 'Lurena', 'Lurline', 'Lutie', + 'Luvenia', 'Luverne', 'Luvinia', 'Luz', 'Lyda', 'Lydia', 'Lyla', + 'Lylah', 'Lyn', 'Lynda', 'Lyndia', 'Lyndsay', 'Lyndsey', 'Lynette', + 'Lynn', 'Lynne', 'Lynnette', 'Lynsey', 'Lyric', 'Mabel', 'Mabell', + 'Mabelle', 'Mable', 'Macel', 'Macey', 'Machelle', 'Maci', 'Macie', + 'Mackenzie', 'Macy', 'Madaline', 'Madalyn', 'Madalynn', 'Maddison', + 'Madeleine', 'Madelene', 'Madeline', 'Madelyn', 'Madelynn', 'Madge', + 'Madie', 'Madilyn', 'Madilynn', 'Madisen', 'Madison', 'Madisyn', + 'Madlyn', 'Madonna', 'Madora', 'Madyson', 'Mae', 'Maebell', 'Maebelle', + 'Maegan', 'Maeve', 'Mafalda', 'Magan', 'Magdalen', 'Magdalena', + 'Magdalene', 'Magen', 'Maggie', 'Magnolia', 'Mahala', 'Mahalia', + 'Mahalie', 'Mai', 'Maia', 'Maida', 'Maira', 'Maiya', 'Makaila', + 'Makala', 'Makayla', 'Makena', 'Makenna', 'Makenzie', 'Malaya', + 'Maleah', 'Malia', 'Maliah', 'Malinda', 'Malissa', 'Malissie', + 'Maliyah', 'Mallie', 'Mallorie', 'Mallory', 'Malorie', 'Malvina', + 'Mame', 'Mamie', 'Mammie', 'Manda', 'Mandi', 'Mandie', 'Mandy', + 'Manerva', 'Manervia', 'Manie', 'Manila', 'Manilla', 'Mannie', + 'Manuela', 'Manuelita', 'Mara', 'Maralyn', 'Maranda', 'Marcela', + 'Marcelina', 'Marceline', 'Marcella', 'Marcelle', 'Marci', 'Marcia', + 'Marcie', 'Marcy', 'Mardell', 'Mareli', 'Marely', 'Maren', 'Margaret', + 'Margarete', 'Margaretha', 'Margarett', 'Margaretta', 'Margarette', + 'Margarita', 'Margarite', 'Marge', 'Margene', 'Margeret', 'Margery', + 'Marget', 'Margie', 'Margo', 'Margot', 'Margret', 'Margrett', + 'Margretta', 'Marguerite', 'Margueritte', 'Margurite', 'Margy', 'Mari', + 'Maria', 'Mariah', 'Mariam', 'Marian', 'Mariana', 'Marianita', + 'Mariann', 'Marianna', 'Marianne', 'Maribel', 'Maribeth', 'Maricela', + 'Marie', 'Mariel', 'Mariela', 'Marietta', 'Marilee', 'Marilla', + 'Marilou', 'Marilyn', 'Marilynn', 'Marin', 'Marina', 'Marinda', + 'Marion', 'Marisa', 'Marisela', 'Marisol', 'Marissa', 'Marita', + 'Maritza', 'Mariyah', 'Marjorie', 'Marjory', 'Markita', 'Marla', + 'Marlana', 'Marlee', 'Marleen', 'Marleigh', 'Marlen', 'Marlena', + 'Marlene', 'Marley', 'Marlie', 'Marlo', 'Marlyn', 'Marlys', 'Marni', + 'Marnie', 'Marnita', 'Marolyn', 'Marquita', 'Marry', 'Marsha', 'Marta', + 'Martha', 'Marti', 'Martika', 'Martina', 'Martine', 'Marty', 'Marva', + 'Marvel', 'Mary', 'Maryam', 'Maryann', 'Maryanne', 'Marybelle', + 'Marybeth', 'Maryellen', 'Maryjane', 'Maryjo', 'Marylee', 'Marylin', + 'Marylou', 'Marylouise', 'Marylyn', 'Masako', 'Mathilda', 'Mathilde', + 'Matie', 'Matilda', 'Matilde', 'Mattie', 'Mattye', 'Maud', 'Maude', + 'Maudie', 'Maura', 'Maureen', 'Maurine', 'Mavis', 'Maxie', 'Maxine', + 'May', 'Maya', 'Maybell', 'Maybelle', 'Maye', 'Mayme', 'Maymie', + 'Mayra', 'Mazie', 'Mckayla', 'Mckenna', 'Mckenzie', 'Mckinley', + 'Meadow', 'Meagan', 'Meaghan', 'Mechelle', 'Meda', 'Media', 'Medora', + 'Meg', 'Megan', 'Meggan', 'Meghan', 'Meghann', 'Melanie', 'Melany', + 'Melba', 'Melina', 'Melinda', 'Melisa', 'Melissa', 'Melissia', 'Mell', + 'Mellie', 'Mellisa', 'Mellissa', 'Melodee', 'Melodie', 'Melody', + 'Melonie', 'Melony', 'Melva', 'Melvina', 'Mena', 'Mendy', 'Mercedes', + 'Mercy', 'Meredith', 'Merilyn', 'Merle', 'Merlene', 'Merna', 'Merri', + 'Merrie', 'Merrilee', 'Merrily', 'Merry', 'Mertie', 'Meryl', 'Meta', + 'Metha', 'Metta', 'Mettie', 'Mia', 'Miah', 'Micaela', 'Micah', + 'Micayla', 'Michaela', 'Michaele', 'Michal', 'Michele', 'Michelina', + 'Michell', 'Michelle', 'Mickey', 'Mickie', 'Miesha', 'Migdalia', + 'Mignon', 'Mikaela', 'Mikaila', 'Mikala', 'Mikalah', 'Mikayla', 'Mila', + 'Milagros', 'Milan', 'Milda', 'Mildred', 'Miley', 'Milissa', + 'Millicent', 'Millie', 'Milly', 'Mima', 'Mimi', 'Mina', 'Minda', + 'Mindi', 'Mindy', 'Minerva', 'Minervia', 'Minna', 'Minnie', 'Minta', + 'Mintie', 'Mira', 'Miracle', 'Miranda', 'Mireya', 'Miriah', 'Miriam', + 'Mirna', 'Mirtie', 'Missie', 'Missouri', 'Missy', 'Misti', 'Mistie', + 'Misty', 'Mittie', 'Mitzi', 'Miya', 'Modena', 'Moesha', 'Moira', + 'Mollie', 'Molly', 'Mona', 'Monica', 'Monika', 'Monique', 'Monna', + 'Monnie', 'Monserrat', 'Montana', 'Montie', 'Mora', 'Morgan', 'Moriah', + 'Mossie', 'Mozell', 'Mozella', 'Mozelle', 'Muriel', 'Murl', 'Mya', + 'Myah', 'Myla', 'Mylee', 'Mylie', 'Myra', 'Myranda', 'Myrl', 'Myrle', + 'Myrna', 'Myrta', 'Myrtice', 'Myrtie', 'Myrtis', 'Myrtle', 'Nada', + 'Nadia', 'Nadine', 'Naima', 'Nakia', 'Nakisha', 'Nakita', 'Nallely', + 'Nan', 'Nana', 'Nanci', 'Nancie', 'Nancy', 'Nanette', 'Nanie', 'Nanna', + 'Nannette', 'Nannie', 'Naoma', 'Naomi', 'Narcissus', 'Natalee', + 'Natalia', 'Natalie', 'Nataly', 'Natalya', 'Natasha', 'Nathalia', + 'Nathalie', 'Nathaly', 'Natosha', 'Nautica', 'Nayeli', 'Nayely', + 'Nealie', 'Nealy', 'Nedra', 'Neha', 'Nelda', 'Nelia', 'Nelie', 'Nell', + 'Nella', 'Nelle', 'Nellie', 'Nelly', 'Nena', 'Neola', 'Neoma', 'Neppie', + 'Nereida', 'Neta', 'Netta', 'Nettie', 'Neva', 'Nevada', 'Nevaeh', + 'Neveah', 'Nia', 'Nichelle', 'Nichol', 'Nichole', 'Nicki', 'Nicola', + 'Nicole', 'Nicolette', 'Nicolle', 'Niki', 'Nikia', 'Nikita', 'Nikki', + 'Nikole', 'Nila', 'Nilda', 'Nina', 'Ninnie', 'Nira', 'Nita', 'Nobie', + 'Noel', 'Noelia', 'Noelle', 'Noemi', 'Noemie', 'Nohely', 'Nola', + 'Nolia', 'Nolie', 'Noma', 'Nona', 'Nonie', 'Nora', 'Norah', 'Noreen', + 'Norene', 'Noreta', 'Noretta', 'Norine', 'Norita', 'Norma', 'Nova', + 'Novella', 'Nya', 'Nyah', 'Nyasia', 'Nyla', 'Nylah', 'Nyree', 'Ocie', + 'Octa', 'Octavia', 'Octavie', 'Oda', 'Odalis', 'Odalys', 'Odelia', + 'Odell', 'Odessa', 'Odette', 'Odie', 'Odile', 'Ofelia', 'Ola', 'Olar', + 'Olena', 'Olene', 'Oleta', 'Olevia', 'Olga', 'Olie', 'Olinda', 'Oline', + 'Oliva', 'Olive', 'Olivia', 'Olivine', 'Ollie', 'Olympia', 'Oma', + 'Omie', 'Ona', 'Oneida', 'Oneta', 'Oney', 'Onie', 'Onnie', 'Opal', + 'Opha', 'Ophelia', 'Ora', 'Orah', 'Oral', 'Oralia', 'Orelia', 'Orene', + 'Orilla', 'Orlena', 'Orma', 'Orpha', 'Orra', 'Orrie', 'Osa', 'Osie', + 'Ossie', 'Ota', 'Otelia', 'Otha', 'Ottie', 'Ottilia', 'Ottilie', + 'Ouida', 'Ova', 'Ozell', 'Ozella', 'Ozie', 'Paige', 'Pairlee', + 'Paisley', 'Paityn', 'Pallie', 'Palma', 'Paloma', 'Pam', 'Pamala', + 'Pamela', 'Pamelia', 'Pamella', 'Pandora', 'Pansy', 'Paola', 'Paralee', + 'Paris', 'Parker', 'Parlee', 'Parthenia', 'Pat', 'Patience', 'Patrica', + 'Patrice', 'Patricia', 'Patsy', 'Patti', 'Pattie', 'Patty', 'Paula', + 'Pauletta', 'Paulette', 'Paulina', 'Pauline', 'Payten', 'Payton', + 'Pearl', 'Pearla', 'Pearle', 'Pearlene', 'Pearlie', 'Pearline', + 'Pearly', 'Peggie', 'Peggy', 'Penelope', 'Penni', 'Pennie', 'Penny', + 'Pepper', 'Perla', 'Permelia', 'Perri', 'Petra', 'Peyton', 'Phebe', + 'Pheobe', 'Phillis', 'Philomena', 'Philomene', 'Phoebe', 'Phoenix', + 'Phylicia', 'Phylis', 'Phyliss', 'Phyllis', 'Pink', 'Pinkey', 'Pinkie', + 'Piper', 'Pluma', 'Pollie', 'Polly', 'Porsche', 'Porsha', 'Portia', + 'Precious', 'Presley', 'Pricilla', 'Princess', 'Priscila', 'Priscilla', + 'Prudence', 'Prudie', 'Qiana', 'Queen', 'Queenie', 'Quiana', 'Quinn', + 'Rachael', 'Racheal', 'Rachel', 'Rachelle', 'Racquel', 'Rae', 'Raegan', + 'Raelyn', 'Raelynn', 'Rafaela', 'Ragna', 'Raina', 'Ramona', 'Randi', + 'Raquel', 'Rashida', 'Raven', 'Rayna', 'Rayne', 'Reagan', 'Reanna', + 'Reatha', 'Reba', 'Rebeca', 'Rebecca', 'Rebekah', 'Reece', 'Reese', + 'Regan', 'Regena', 'Regenia', 'Regina', 'Reilly', 'Reina', 'Rella', + 'Rena', 'Renada', 'Renae', 'Renata', 'Rene', 'Renea', 'Renee', 'Renita', + 'Rennie', 'Ressie', 'Reta', 'Retha', 'Retta', 'Rettie', 'Reva', 'Reyna', + 'Rhea', 'Rheta', 'Rhianna', 'Rhiannon', 'Rhoda', 'Rhona', 'Rhonda', + 'Rianna', 'Richelle', 'Ricki', 'Rihanna', 'Rikki', 'Riley', 'Rilla', + 'Rillie', 'Rinda', 'Risa', 'Rita', 'River', 'Riya', 'Robbie', 'Robbin', + 'Roberta', 'Robin', 'Robyn', 'Rochelle', 'Rocio', 'Roena', 'Rolanda', + 'Roma', 'Romaine', 'Romona', 'Rona', 'Ronda', 'Roni', 'Ronna', 'Ronnie', + 'Rory', 'Rosa', 'Rosabelle', 'Rosalee', 'Rosalia', 'Rosalie', + 'Rosalind', 'Rosalinda', 'Rosaline', 'Rosalyn', 'Rosamond', 'Rosann', + 'Rosanna', 'Rosanne', 'Rosaria', 'Rosario', 'Rose', 'Roseann', + 'Roseanna', 'Roseanne', 'Rosella', 'Roselyn', 'Rosemarie', 'Rosemary', + 'Rosena', 'Rosetta', 'Rosey', 'Rosia', 'Rosie', 'Rosina', 'Rosita', + 'Roslyn', 'Rossie', 'Rosy', 'Rowan', 'Rowena', 'Roxana', 'Roxane', + 'Roxann', 'Roxanna', 'Roxanne', 'Roxie', 'Roxy', 'Rozanne', 'Rozella', + 'Rubi', 'Rubie', 'Ruby', 'Rubye', 'Ruie', 'Ruth', 'Rutha', 'Ruthann', + 'Ruthanne', 'Ruthe', 'Ruthie', 'Ryann', 'Rylan', 'Rylee', 'Ryleigh', + 'Rylie', 'Sabina', 'Sable', 'Sabra', 'Sabrina', 'Sada', 'Sade', 'Sadie', + 'Sadye', 'Sage', 'Saige', 'Salena', 'Salina', 'Sallie', 'Sally', + 'Salma', 'Salome', 'Samantha', 'Samara', 'Samatha', 'Samira', 'Samiyah', + 'Sammie', 'Sanaa', 'Sanai', 'Sandi', 'Sandie', 'Sandra', 'Sandy', + 'Saniya', 'Saniyah', 'Sanjuana', 'Sanjuanita', 'Sannie', 'Santa', + 'Santana', 'Santina', 'Santos', 'Sara', 'Sarah', 'Sarahi', 'Sarai', + 'Sariah', 'Sarina', 'Sarita', 'Sarrah', 'Sasha', 'Saundra', 'Savana', + 'Savanah', 'Savanna', 'Savannah', 'Savilla', 'Scarlet', 'Scarlett', + 'Sebrina', 'Selah', 'Selena', 'Selene', 'Selina', 'Selma', 'Sena', + 'Senora', 'Serena', 'Serenity', 'Serina', 'Shae', 'Shaina', 'Shakira', + 'Shalon', 'Shalonda', 'Shameka', 'Shamika', 'Shana', 'Shanae', 'Shanda', + 'Shandra', 'Shane', 'Shaneka', 'Shanell', 'Shanelle', 'Shanequa', + 'Shani', 'Shania', 'Shanice', 'Shaniece', 'Shanika', 'Shaniqua', + 'Shanita', 'Shaniya', 'Shanna', 'Shannan', 'Shannen', 'Shannon', + 'Shanon', 'Shanta', 'Shante', 'Shantel', 'Shantell', 'Shaquana', + 'Shaquita', 'Shara', 'Shardae', 'Sharday', 'Sharde', 'Sharee', 'Sharen', + 'Shari', 'Sharita', 'Sharla', 'Sharleen', 'Sharlene', 'Sharman', + 'Sharon', 'Sharonda', 'Sharron', 'Sharyl', 'Sharyn', 'Shasta', + 'Shatara', 'Shauna', 'Shaunna', 'Shavon', 'Shavonne', 'Shawanda', + 'Shawna', 'Shawnda', 'Shawnee', 'Shawnna', 'Shawnte', 'Shay', 'Shayla', + 'Shaylee', 'Shayna', 'Shea', 'Sheena', 'Sheila', 'Sheilah', 'Shelba', + 'Shelbi', 'Shelbie', 'Shelby', 'Shelia', 'Shelley', 'Shelli', 'Shellie', + 'Shelly', 'Shelva', 'Shelvia', 'Shelvie', 'Shena', 'Shenna', 'Sheree', + 'Sheri', 'Sheridan', 'Sherie', 'Sherilyn', 'Sherita', 'Sherlyn', + 'Sheron', 'Sherree', 'Sherri', 'Sherrie', 'Sherrill', 'Sherron', + 'Sherry', 'Sherryl', 'Sheryl', 'Sheryll', 'Sheyla', 'Shianne', 'Shiela', + 'Shiloh', 'Shira', 'Shirl', 'Shirlee', 'Shirleen', 'Shirlene', + 'Shirley', 'Shirleyann', 'Shirlie', 'Shona', 'Shonda', 'Shonna', + 'Shreya', 'Shyann', 'Shyanne', 'Shyla', 'Sibbie', 'Sibyl', 'Siddie', + 'Sidney', 'Siena', 'Sienna', 'Sierra', 'Signa', 'Signe', 'Sigrid', + 'Silvia', 'Simona', 'Simone', 'Sina', 'Sinda', 'Siobhan', 'Sister', + 'Sky', 'Skye', 'Skyla', 'Skylar', 'Skyler', 'Sloane', 'Socorro', + 'Sofia', 'Soledad', 'Somer', 'Sommer', 'Sondra', 'Sonia', 'Sonja', + 'Sonji', 'Sonya', 'Sophia', 'Sophie', 'Sophronia', 'Spring', 'Stacey', + 'Staci', 'Stacia', 'Stacie', 'Stacy', 'Star', 'Starla', 'Starr', + 'Stasia', 'Stefani', 'Stefanie', 'Stella', 'Stephaine', 'Stephani', + 'Stephania', 'Stephanie', 'Stephany', 'Stephenie', 'Stevie', 'Stormy', + 'Sudie', 'Sue', 'Suellen', 'Sula', 'Summer', 'Sunday', 'Sunny', + 'Sunshine', 'Susan', 'Susana', 'Susann', 'Susanna', 'Susannah', + 'Susanne', 'Susie', 'Sussie', 'Suzan', 'Suzann', 'Suzanna', 'Suzanne', + 'Suzette', 'Suzie', 'Suzy', 'Sybil', 'Sybilla', 'Syble', 'Sydell', + 'Sydnee', 'Sydney', 'Sydni', 'Sydnie', 'Sylva', 'Sylvania', 'Sylvia', + 'Symone', 'Syreeta', 'Tabatha', 'Tabetha', 'Tabitha', 'Tai', 'Taina', + 'Taja', 'Takisha', 'Talia', 'Taliyah', 'Tamala', 'Tamara', 'Tamatha', + 'Tambra', 'Tameka', 'Tamekia', 'Tamela', 'Tamera', 'Tami', 'Tamia', + 'Tamica', 'Tamie', 'Tamika', 'Tamiko', 'Tamisha', 'Tammi', 'Tammie', + 'Tammy', 'Tamra', 'Tamya', 'Tana', 'Tanesha', 'Tangela', 'Tania', + 'Tanika', 'Tanisha', 'Taniya', 'Taniyah', 'Tanja', 'Tanya', 'Tara', + 'Tarah', 'Taraji', 'Tari', 'Tarsha', 'Taryn', 'Tasha', 'Tashina', + 'Tasia', 'Tatia', 'Tatiana', 'Tatianna', 'Tatum', 'Tatyana', 'Tatyanna', + 'Tawana', 'Tawanda', 'Tawanna', 'Tawny', 'Tawnya', 'Taya', 'Tayla', + 'Tayler', 'Taylor', 'Tea', 'Teagan', 'Teela', 'Teena', 'Tella', + 'Tempie', 'Tena', 'Tenika', 'Tenisha', 'Tennessee', 'Tennie', + 'Tennille', 'Tera', 'Teresa', 'Terese', 'Teressa', 'Teri', 'Terra', + 'Terri', 'Terrie', 'Terry', 'Tess', 'Tessa', 'Tessie', 'Texanna', + 'Texas', 'Texie', 'Thalia', 'Thea', 'Theda', 'Thekla', 'Thelma', + 'Theodocia', 'Theodora', 'Theodosia', 'Theola', 'Theresa', 'Therese', + 'Theresia', 'Theta', 'Thomasina', 'Thora', 'Thresa', 'Thursa', 'Thyra', + 'Tia', 'Tiana', 'Tianna', 'Tiara', 'Tiarra', 'Tiera', 'Tierra', + 'Tiesha', 'Tiffani', 'Tiffanie', 'Tiffany', 'Tilda', 'Tilla', 'Tillie', + 'Tina', 'Tiney', 'Tinie', 'Tinnie', 'Tiny', 'Tisa', 'Tisha', 'Tishie', + 'Tobi', 'Toby', 'Toccara', 'Tomasa', 'Tomeka', 'Tomika', 'Tommie', + 'Tonda', 'Toni', 'Tonia', 'Tonja', 'Tonya', 'Tori', 'Torie', 'Torrie', + 'Tory', 'Tosha', 'Toshiko', 'Towanda', 'Toya', 'Tracee', 'Tracey', + 'Traci', 'Tracie', 'Tracy', 'Treasure', 'Treena', 'Trena', 'Tresa', + 'Tressa', 'Tressie', 'Treva', 'Tricia', 'Trilby', 'Trina', 'Trinidad', + 'Trinity', 'Trish', 'Trisha', 'Trista', 'Tristan', 'Tristen', 'Trudi', + 'Trudie', 'Trudy', 'Trula', 'Tula', 'Twila', 'Twyla', 'Tyesha', 'Tyra', + 'Ula', 'Una', 'Unique', 'Unknown', 'Ura', 'Ursula', 'Vada', 'Val', + 'Valarie', 'Valencia', 'Valentina', 'Valentine', 'Valeria', 'Valerie', + 'Valery', 'Valinda', 'Vallie', 'Valorie', 'Vanesa', 'Vanessa', 'Vannie', + 'Vara', 'Vashti', 'Vassie', 'Veda', 'Vela', 'Velda', 'Velia', 'Vella', + 'Velma', 'Velva', 'Velvet', 'Vena', 'Venessa', 'Venice', 'Venie', + 'Venita', 'Vennie', 'Venus', 'Veola', 'Vera', 'Verda', 'Verdell', + 'Verdie', 'Verena', 'Vergie', 'Verla', 'Verlene', 'Verlie', 'Verna', + 'Verne', 'Vernell', 'Vernelle', 'Vernetta', 'Vernia', 'Vernice', + 'Vernie', 'Vernita', 'Verona', 'Veronica', 'Versa', 'Versie', 'Vertie', + 'Vessie', 'Vesta', 'Veta', 'Veva', 'Vicie', 'Vickey', 'Vicki', 'Vickie', + 'Vicky', 'Victoria', 'Victorine', 'Victory', 'Vicy', 'Vida', 'Vikki', + 'Villa', 'Vilma', 'Vina', 'Vincenza', 'Viney', 'Vinie', 'Vinnie', + 'Viola', 'Violet', 'Violeta', 'Violetta', 'Violette', 'Vira', 'Virdie', + 'Virgia', 'Virgie', 'Virginia', 'Viridiana', 'Vita', 'Viva', 'Vivian', + 'Viviana', 'Vivien', 'Vivienne', 'Vlasta', 'Vonda', 'Vonetta', 'Vonnie', + 'Wanda', 'Waneta', 'Wanita', 'Wava', 'Wende', 'Wendi', 'Wendy', + 'Whitley', 'Whitney', 'Wilda', 'Wilhelmina', 'Wilhelmine', 'Willa', + 'Willene', 'Willia', 'Willie', 'Williemae', 'Willodean', 'Willow', + 'Wilma', 'Windy', 'Winifred', 'Winnie', 'Winnifred', 'Winona', 'Winter', + 'Wynona', 'Xena', 'Ximena', 'Xiomara', 'Yadira', 'Yahaira', 'Yajaira', + 'Yamilet', 'Yamilex', 'Yareli', 'Yaretzi', 'Yaritza', 'Yasmeen', + 'Yasmin', 'Yasmine', 'Yazmin', 'Yesenia', 'Yessenia', 'Yetta', + 'Yolanda', 'Yolonda', 'Yoselin', 'Yoshiko', 'Yuliana', 'Yulisa', + 'Yulissa', 'Yuridia', 'Yvette', 'Yvonne', 'Zada', 'Zadie', 'Zaida', + 'Zana', 'Zandra', 'Zaniyah', 'Zara', 'Zaria', 'Zariah', 'Zela', 'Zelda', + 'Zelia', 'Zella', 'Zelma', 'Zelpha', 'Zena', 'Zenobia', 'Zeta', 'Zetta', + 'Zettie', 'Zhane', 'Zillah', 'Zilpah', 'Zilpha', 'Zina', 'Zion', 'Zita', + 'Zoa', 'Zoe', 'Zoey', 'Zoie', 'Zola', 'Zona', 'Zora', 'Zula', + 'Aaden', 'Aarav', 'Aaron', 'Ab', 'Abb', 'Abbott', 'Abdiel', 'Abdul', + 'Abdullah', 'Abe', 'Abel', 'Abelardo', 'Abie', 'Abner', 'Abraham', + 'Abram', 'Ace', 'Acey', 'Acie', 'Acy', 'Adalberto', 'Adam', 'Adams', + 'Adan', 'Add', 'Adelard', 'Adelbert', 'Aden', 'Adin', 'Aditya', 'Adlai', + 'Admiral', 'Adolf', 'Adolfo', 'Adolph', 'Adolphus', 'Adonis', 'Adrain', + 'Adrian', 'Adriel', 'Adrien', 'Adron', 'Aedan', 'Agustin', 'Agustus', + 'Ah', 'Ahmad', 'Ahmed', 'Aidan', 'Aiden', 'Aidyn', 'Aime', 'Akeem', + 'Al', 'Alan', 'Alanzo', 'Albert', 'Alberto', 'Albertus', 'Albin', + 'Albion', 'Alby', 'Alcee', 'Alcide', 'Alden', 'Aldo', 'Alec', 'Aleck', + 'Alejandro', 'Alek', 'Alessandro', 'Alex', 'Alexande', 'Alexander', + 'Alexandre', 'Alexandro', 'Alexis', 'Alexzander', 'Alf', 'Alferd', + 'Alfie', 'Alfonse', 'Alfonso', 'Alfonzo', 'Alford', 'Alfred', 'Alfredo', + 'Alger', 'Algernon', 'Algie', 'Algot', 'Ali', 'Alijah', 'Allan', + 'Allen', 'Allyn', 'Almer', 'Almon', 'Almond', 'Almus', 'Alois', + 'Alonso', 'Alonza', 'Alonzo', 'Aloys', 'Aloysius', 'Alpheus', 'Alphons', + 'Alphonse', 'Alphonso', 'Alphonsus', 'Alston', 'Alto', 'Alton', 'Alva', + 'Alvah', 'Alvan', 'Alvaro', 'Alver', 'Alvia', 'Alvie', 'Alvin', 'Alvis', + 'Alvy', 'Alwin', 'Amado', 'Amare', 'Amari', 'Amarion', 'Amasa', + 'Ambers', 'Ambrose', 'Americo', 'Amerigo', 'Amil', 'Amin', 'Amir', + 'Amit', 'Ammon', 'Amon', 'Amos', 'Ananias', 'Anastacio', 'Anatole', + 'Ancel', 'Ancil', 'Anders', 'Anderson', 'Andon', 'Andra', 'Andrae', + 'Andre', 'Andreas', 'Andres', 'Andrew', 'Andy', 'Anfernee', 'Angel', + 'Angelo', 'Angus', 'Anibal', 'Ansel', 'Anson', 'Anthoney', 'Anthony', + 'Antione', 'Antoine', 'Anton', 'Antone', 'Antonio', 'Antony', 'Antwain', + 'Antwan', 'Antwon', 'Anwar', 'Arba', 'Arbie', 'Arch', 'Archer', + 'Archibald', 'Archie', 'Ardell', 'Arden', 'Ari', 'Aric', 'Arjun', + 'Arlan', 'Arland', 'Arlen', 'Arley', 'Arlie', 'Arlin', 'Arlington', + 'Arlis', 'Arlo', 'Arlyn', 'Arman', 'Armand', 'Armando', 'Armani', + 'Armin', 'Armond', 'Armstead', 'Arnav', 'Arne', 'Arnett', 'Arnie', + 'Arno', 'Arnold', 'Arnoldo', 'Arnulfo', 'Aron', 'Arron', 'Arsenio', + 'Art', 'Arther', 'Arthor', 'Arthur', 'Artie', 'Artis', 'Arturo', + 'Arvel', 'Arvid', 'Arvil', 'Arvin', 'Arvo', 'Aryan', 'Asa', 'Asberry', + 'Asbury', 'Ashby', 'Asher', 'Ashton', 'Atha', 'Atlas', 'Atticus', + 'Attilio', 'Aubra', 'Aubrey', 'Audie', 'Audley', 'Audy', 'August', + 'Auguste', 'Augustin', 'Augustine', 'Augustus', 'Aurelio', 'Aurthur', + 'Austen', 'Austin', 'Auston', 'Austyn', 'Auther', 'Author', 'Authur', + 'Autry', 'Avery', 'Avon', 'Axel', 'Ayaan', 'Aydan', 'Ayden', 'Aydin', + 'Babe', 'Babyboy', 'Bailey', 'Baker', 'Baldwin', 'Ballard', 'Banks', + 'Barnard', 'Barnett', 'Barney', 'Barnie', 'Baron', 'Barrett', 'Barrie', + 'Barron', 'Barry', 'Bart', 'Bartholomew', 'Bartley', 'Barton', 'Bascom', + 'Basil', 'Baxter', 'Bayard', 'Beau', 'Beckett', 'Beckham', 'Bedford', + 'Beecher', 'Bell', 'Belton', 'Ben', 'Benard', 'Benedict', 'Benito', + 'Benjaman', 'Benjamen', 'Benjamin', 'Benjamine', 'Benji', 'Benjiman', + 'Benjman', 'Bennett', 'Bennie', 'Benny', 'Benson', 'Bentley', 'Benton', + 'Berkley', 'Berlin', 'Bernard', 'Bernardo', 'Bernhard', 'Bernie', + 'Berry', 'Bert', 'Bertie', 'Berton', 'Bertram', 'Bertrand', 'Beryl', + 'Bethel', 'Bilal', 'Bill', 'Billie', 'Billy', 'Bird', 'Birt', 'Bishop', + 'Bjorn', 'Blain', 'Blaine', 'Blair', 'Blaise', 'Blake', 'Blanchard', + 'Blane', 'Blas', 'Blaze', 'Bliss', 'Bluford', 'Bo', 'Bob', 'Bobbie', + 'Bobby', 'Bode', 'Bolden', 'Booker', 'Boone', 'Boris', 'Bose', 'Boss', + 'Boston', 'Bowman', 'Boyce', 'Boyd', 'Boysie', 'Brad', 'Braden', + 'Bradford', 'Bradley', 'Bradly', 'Brady', 'Bradyn', 'Braeden', + 'Braedon', 'Braiden', 'Brain', 'Branch', 'Brandan', 'Branden', + 'Brandin', 'Brandon', 'Brandt', 'Brandy', 'Brandyn', 'Brannon', + 'Branson', 'Brant', 'Brantley', 'Braulio', 'Braxton', 'Brayan', + 'Brayden', 'Braydon', 'Braylen', 'Braylon', 'Brendan', 'Brenden', + 'Brendon', 'Brennan', 'Brennen', 'Brennon', 'Brent', 'Brenton', 'Bret', + 'Brett', 'Brian', 'Brice', 'Bridger', 'Brien', 'Brion', 'Britt', + 'Brittany', 'Britton', 'Brock', 'Broderick', 'Brodie', 'Brody', + 'Brogan', 'Bronson', 'Brook', 'Brooks', 'Brown', 'Bruce', 'Bruno', + 'Bryan', 'Bryant', 'Bryce', 'Brycen', 'Bryon', 'Bryson', 'Bryton', + 'Buck', 'Bud', 'Budd', 'Buddie', 'Buddy', 'Buel', 'Buell', 'Buford', + 'Bunk', 'Burdette', 'Buren', 'Burgess', 'Burk', 'Burke', 'Burl', + 'Burleigh', 'Burley', 'Burnell', 'Burnett', 'Burney', 'Burnice', + 'Burnie', 'Burns', 'Burr', 'Burrel', 'Burrell', 'Burt', 'Burton', + 'Bush', 'Buster', 'Butch', 'Butler', 'Bynum', 'Byrd', 'Byron', 'Cade', + 'Caden', 'Cael', 'Caesar', 'Caiden', 'Cain', 'Cal', 'Cale', 'Caleb', + 'Calhoun', 'Callie', 'Callum', 'Calvin', 'Cam', 'Camden', 'Cameron', + 'Camilo', 'Campbell', 'Camren', 'Camron', 'Camryn', 'Candido', 'Cannon', + 'Canyon', 'Cap', 'Captain', 'Carey', 'Carl', 'Carleton', 'Carlie', + 'Carlisle', 'Carlo', 'Carlos', 'Carlton', 'Carlyle', 'Carmel', + 'Carmelo', 'Carmen', 'Carmine', 'Carnell', 'Carrie', 'Carrol', + 'Carroll', 'Carsen', 'Carson', 'Carter', 'Cary', 'Cas', 'Case', 'Casen', + 'Casey', 'Cash', 'Casimer', 'Casimir', 'Casimiro', 'Cason', 'Casper', + 'Cass', 'Cassidy', 'Cassie', 'Cassius', 'Caswell', 'Cato', 'Cayden', + 'Ceasar', 'Cecil', 'Cedric', 'Cedrick', 'Celestino', 'Cephus', 'Cesar', + 'Ceylon', 'Chace', 'Chad', 'Chadd', 'Chadrick', 'Chadwick', 'Chaim', + 'Chalmer', 'Chalmers', 'Champ', 'Chance', 'Chancey', 'Chancy', + 'Chandler', 'Channing', 'Charle', 'Charles', 'Charley', 'Charlie', + 'Charls', 'Charlton', 'Charly', 'Chas', 'Chase', 'Chauncey', 'Chauncy', + 'Chaz', 'Che', 'Chesley', 'Chester', 'Chet', 'Cheyenne', 'Chin', 'Chip', + 'Chris', 'Christ', 'Christian', 'Christina', 'Christion', 'Christop', + 'Christoper', 'Christophe', 'Christopher', 'Chuck', 'Cicero', 'Clabe', + 'Claiborne', 'Clair', 'Clarance', 'Clare', 'Clarence', 'Clark', + 'Clarke', 'Clarnce', 'Claud', 'Claude', 'Claudie', 'Claudio', + 'Claudius', 'Claus', 'Clay', 'Clayton', 'Clearence', 'Cleave', 'Clell', + 'Clem', 'Clemence', 'Clemens', 'Clement', 'Clemente', 'Clemmie', + 'Clemon', 'Cleo', 'Cleon', 'Cletus', 'Cleve', 'Cleveland', 'Clide', + 'Cliff', 'Clifford', 'Clifton', 'Clint', 'Clinton', 'Clive', 'Clovis', + 'Cloyd', 'Clyde', 'Coby', 'Codey', 'Codi', 'Codie', 'Cody', 'Coen', + 'Cohen', 'Colbert', 'Colby', 'Cole', 'Coleman', 'Coleton', 'Coley', + 'Colie', 'Colin', 'Collie', 'Collier', 'Collin', 'Collins', 'Collis', + 'Colon', 'Colonel', 'Colt', 'Colten', 'Colter', 'Colton', 'Columbus', + 'Colvin', 'Commodore', 'Con', 'Conard', 'Conley', 'Conner', 'Connie', + 'Connor', 'Conor', 'Conrad', 'Constantine', 'Conway', 'Coolidge', + 'Cooper', 'Corbett', 'Corbin', 'Cordaro', 'Cordell', 'Cordero', 'Corey', + 'Cornel', 'Cornelious', 'Cornelius', 'Cornell', 'Corry', 'Cortez', + 'Cortney', 'Corwin', 'Cory', 'Cosmo', 'Coty', 'Council', 'Courtland', + 'Courtney', 'Coy', 'Craig', 'Crawford', 'Creed', 'Cris', 'Cristian', + 'Cristobal', 'Cristofer', 'Cristopher', 'Crockett', 'Cruz', 'Cullen', + 'Curley', 'Curt', 'Curtis', 'Curtiss', 'Cyril', 'Cyrus', 'Dabney', + 'Dakoda', 'Dakota', 'Dakotah', 'Dale', 'Dallas', 'Dallin', 'Dalton', + 'Dalvin', 'Damarcus', 'Damari', 'Damarion', 'Dameon', 'Damian', + 'Damien', 'Damion', 'Damon', 'Damond', 'Dan', 'Dana', 'Dandre', 'Dane', + 'Dangelo', 'Danial', 'Daniel', 'Dann', 'Dannie', 'Danniel', 'Danny', + 'Dante', 'Daquan', 'Darby', 'Darcy', 'Darell', 'Daren', 'Darian', + 'Darien', 'Darin', 'Dario', 'Darion', 'Darius', 'Darl', 'Darnell', + 'Darold', 'Daron', 'Darrel', 'Darrell', 'Darren', 'Darrian', 'Darrick', + 'Darrien', 'Darrin', 'Darrion', 'Darrius', 'Darron', 'Darry', 'Darryl', + 'Darryle', 'Darryll', 'Darryn', 'Darvin', 'Darwin', 'Darwyn', 'Daryl', + 'Daryle', 'Daryn', 'Dashawn', 'Daulton', 'Daunte', 'Davante', 'Dave', + 'Davey', 'Davian', 'David', 'Davie', 'Davin', 'Davion', 'Davis', + 'Davon', 'Davonta', 'Davonte', 'Davy', 'Dawson', 'Dax', 'Daxton', + 'Dayne', 'Dayton', 'Deacon', 'Dean', 'Deandre', 'Deane', 'Deangelo', + 'Deante', 'Declan', 'Dedric', 'Dedrick', 'Deegan', 'Deforest', 'Deion', + 'Dejon', 'Dejuan', 'Del', 'Delano', 'Delbert', 'Dell', 'Della', 'Delma', + 'Delmar', 'Delmas', 'Delmer', 'Delmus', 'Delos', 'Delphin', 'Delton', + 'Delvin', 'Delwin', 'Demarco', 'Demarcus', 'Demario', 'Demarion', + 'Demetri', 'Demetric', 'Demetrios', 'Demetrius', 'Demian', 'Demond', + 'Demonte', 'Dempsey', 'Denis', 'Dennie', 'Dennis', 'Denny', 'Denton', + 'Denver', 'Denzel', 'Denzell', 'Denzil', 'Deon', 'Deondre', 'Deonta', + 'Deontae', 'Deonte', 'Dequan', 'Derald', 'Dereck', 'Derek', 'Dereon', + 'Deric', 'Derick', 'Derik', 'Derl', 'Deron', 'Derrek', 'Derrell', + 'Derrick', 'Derwin', 'Deryl', 'Desean', 'Deshaun', 'Deshawn', 'Desi', + 'Desmond', 'Dessie', 'Destin', 'Destry', 'Devan', 'Devante', 'Devaughn', + 'Deven', 'Devin', 'Devon', 'Devonta', 'Devontae', 'Devonte', 'Devyn', + 'Deward', 'Dewayne', 'Dewey', 'Dewitt', 'Dexter', 'Diallo', 'Diamond', + 'Diane', 'Dickie', 'Diego', 'Dijon', 'Dilan', 'Dillan', 'Dillard', + 'Dillion', 'Dillon', 'Dimitri', 'Dimitrios', 'Dink', 'Dino', 'Dion', + 'Dionicio', 'Dionte', 'Dirk', 'Dixon', 'Doc', 'Dock', 'Doctor', 'Doll', + 'Dolph', 'Dolphus', 'Domenic', 'Domenick', 'Domenico', 'Domingo', + 'Dominic', 'Dominick', 'Dominik', 'Don', 'Donaciano', 'Donal', 'Donald', + 'Donat', 'Donato', 'Donavan', 'Donavon', 'Dondre', 'Donell', 'Donn', + 'Donnell', 'Donnie', 'Donny', 'Donovan', 'Donta', 'Dontae', 'Donte', + 'Dora', 'Dorian', 'Dorman', 'Dorr', 'Dorris', 'Dorsey', 'Doss', 'Doug', + 'Douglas', 'Douglass', 'Dow', 'Doyle', 'Dozier', 'Drake', 'Draven', + 'Drew', 'Drury', 'Duane', 'Duard', 'Dudley', 'Duff', 'Duke', 'Duncan', + 'Durell', 'Durrell', 'Durward', 'Durwood', 'Dustan', 'Dustin', 'Dusty', + 'Dustyn', 'Duwayne', 'Dwain', 'Dwaine', 'Dwane', 'Dwayne', 'Dwight', + 'Dwyane', 'Dylan', 'Dyllan', 'Dylon', 'Ean', 'Earl', 'Earle', 'Earley', + 'Earlie', 'Early', 'Earnest', 'Easton', 'Ebb', 'Ebbie', 'Eben', + 'Ebenezer', 'Eber', 'Ebert', 'Ed', 'Edd', 'Eddie', 'Eddy', 'Eden', + 'Edgar', 'Edgardo', 'Edie', 'Edison', 'Edmon', 'Edmond', 'Edmund', + 'Edsel', 'Edson', 'Eduardo', 'Edw', 'Edward', 'Edwardo', 'Edwin', + 'Effie', 'Efrain', 'Efrem', 'Efren', 'Egbert', 'Einar', 'Eino', 'Elam', + 'Elbert', 'Elbridge', 'Elby', 'Elden', 'Elder', 'Eldon', 'Eldred', + 'Eldridge', 'Elex', 'Elgie', 'Elgin', 'Eli', 'Elian', 'Elias', 'Elick', + 'Elie', 'Eliezer', 'Eliga', 'Eligah', 'Elige', 'Elihu', 'Elijah', + 'Eliot', 'Eliseo', 'Elisha', 'Elizah', 'Ell', 'Ellery', 'Elliot', + 'Elliott', 'Ellis', 'Ellison', 'Ellsworth', 'Ellwood', 'Elmer', 'Elmo', + 'Elmore', 'Elon', 'Elonzo', 'Eloy', 'Elroy', 'Elsworth', 'Elton', + 'Elvin', 'Elvis', 'Elwin', 'Elwood', 'Elwyn', 'Ely', 'Elza', 'Elzie', + 'Elzy', 'Emanuel', 'Emerson', 'Emery', 'Emett', 'Emil', 'Emile', + 'Emiliano', 'Emilio', 'Emit', 'Emma', 'Emmanuel', 'Emmet', 'Emmett', + 'Emmit', 'Emmitt', 'Emmons', 'Emory', 'Emry', 'Encarnacion', 'Ennis', + 'Enoch', 'Enos', 'Enrico', 'Enrique', 'Enzo', 'Ephraim', 'Ephram', + 'Ephriam', 'Epifanio', 'Erasmo', 'Erasmus', 'Erastus', 'Erby', 'Eric', + 'Erich', 'Erick', 'Erie', 'Erik', 'Erin', 'Erland', 'Erle', 'Erling', + 'Ernest', 'Ernesto', 'Ernie', 'Ernst', 'Errol', 'Ervin', 'Erving', + 'Erwin', 'Esau', 'Esco', 'Esequiel', 'Esker', 'Esley', 'Essex', + 'Esteban', 'Estel', 'Estes', 'Estevan', 'Estill', 'Eston', 'Ethan', + 'Ethelbert', 'Ethen', 'Eugene', 'Eugenio', 'Eusebio', 'Eustace', 'Evan', + 'Evander', 'Evans', 'Evelyn', 'Everet', 'Everett', 'Everette', 'Evert', + 'Evertt', 'Ewald', 'Ewart', 'Ewell', 'Ewin', 'Ewing', 'Ezekiel', + 'Ezell', 'Ezequiel', 'Ezra', 'Ezzard', 'Fabian', 'Faron', 'Farrell', + 'Farris', 'Fate', 'Faustino', 'Fayette', 'Fed', 'Federico', 'Felipe', + 'Felix', 'Felton', 'Fenton', 'Ferd', 'Ferdinand', 'Ferman', 'Fernand', + 'Fernando', 'Ferrell', 'Ferris', 'Festus', 'Fidel', 'Fidencio', + 'Fielding', 'Finis', 'Finley', 'Finn', 'Finnegan', 'Firman', 'Fisher', + 'Fitzgerald', 'Fitzhugh', 'Fleet', 'Flem', 'Fleming', 'Fletcher', + 'Flint', 'Florencio', 'Florentino', 'Florian', 'Floy', 'Floyd', 'Foch', + 'Ford', 'Forest', 'Forrest', 'Foster', 'Fount', 'Foy', 'Frances', + 'Francesco', 'Francis', 'Francisco', 'Franco', 'Frank', 'Frankie', + 'Franklin', 'Franklyn', 'Franz', 'Frazier', 'Fred', 'Freddie', 'Freddy', + 'Frederic', 'Frederick', 'Fredie', 'Fredric', 'Fredrick', 'Fredy', + 'Freeman', 'Fremont', 'French', 'Friend', 'Fritz', 'Fuller', 'Fulton', + 'Furman', 'Gabe', 'Gabriel', 'Gael', 'Gaetano', 'Gage', 'Gaige', 'Gail', + 'Gaines', 'Gaither', 'Gale', 'Galen', 'Gannon', 'Gardner', 'Garett', + 'Garey', 'Garfield', 'Garland', 'Garner', 'Garnet', 'Garnett', 'Garold', + 'Garret', 'Garrett', 'Garrick', 'Garrison', 'Garry', 'Garth', 'Garvin', + 'Gary', 'Gasper', 'Gaston', 'Gauge', 'Gaven', 'Gavin', 'Gavyn', 'Gay', + 'Gayle', 'Gaylen', 'Gaylon', 'Gaylord', 'Gearld', 'Geary', 'Gee', + 'Genaro', 'Gene', 'General', 'Genie', 'Gennaro', 'Geno', 'Geo', 'Geoff', + 'Geoffrey', 'George', 'Georgie', 'Geovanni', 'Gerald', 'Geraldo', + 'Gerard', 'Gerardo', 'Gerhard', 'Gerhardt', 'Germaine', 'German', + 'Gerold', 'Gerrit', 'Gerry', 'Giancarlo', 'Gianni', 'Gibson', 'Gideon', + 'Gifford', 'Gil', 'Gilbert', 'Gilberto', 'Giles', 'Gilford', 'Gilman', + 'Gilmer', 'Gilmore', 'Gino', 'Giovani', 'Giovanni', 'Giovanny', + 'Giuseppe', 'Gladstone', 'Glen', 'Glendon', 'Glenn', 'Glenwood', + 'Glover', 'Glynn', 'Godfrey', 'Goebel', 'Golden', 'Gonzalo', 'Gorden', + 'Gordon', 'Gorge', 'Gottlieb', 'Governor', 'Grady', 'Grafton', 'Graham', + 'Grant', 'Granville', 'Graves', 'Gray', 'Graydon', 'Grayling', + 'Grayson', 'Green', 'Greene', 'Greg', 'Gregg', 'Greggory', 'Gregorio', + 'Gregory', 'Greyson', 'Griffin', 'Griffith', 'Grove', 'Grover', 'Guido', + 'Guilford', 'Guillermo', 'Gunnar', 'Gunner', 'Gurney', 'Gus', 'Guss', + 'Gussie', 'Gust', 'Gustaf', 'Gustav', 'Gustave', 'Gustavo', 'Gustavus', + 'Guthrie', 'Guy', 'Haden', 'Hadley', 'Haiden', 'Hakeem', 'Hakim', 'Hal', + 'Halbert', 'Hale', 'Hall', 'Halley', 'Hallie', 'Halsey', 'Ham', + 'Hamilton', 'Hamp', 'Hampton', 'Hamza', 'Handy', 'Hank', 'Hans', + 'Hansel', 'Hansford', 'Hanson', 'Harden', 'Hardie', 'Hardin', 'Harding', + 'Hardy', 'Harl', 'Harlan', 'Harland', 'Harlen', 'Harley', 'Harlie', + 'Harlon', 'Harlow', 'Harm', 'Harman', 'Harmon', 'Harold', 'Harper', + 'Harrell', 'Harrie', 'Harris', 'Harrison', 'Harrold', 'Harry', 'Hart', + 'Hartley', 'Hartwell', 'Harve', 'Harvey', 'Harvie', 'Harvy', 'Hasan', + 'Haskell', 'Hassan', 'Hattie', 'Haven', 'Hayden', 'Hayes', 'Hays', + 'Hayward', 'Haywood', 'Hazen', 'Heath', 'Heber', 'Hebert', 'Hector', + 'Helmer', 'Hence', 'Henderson', 'Henery', 'Henri', 'Henry', 'Herb', + 'Herbert', 'Heriberto', 'Herman', 'Hermann', 'Hermon', 'Hernan', + 'Herschel', 'Hershel', 'Hershell', 'Hervey', 'Heyward', 'Hezekiah', + 'Hezzie', 'Hideo', 'Hilario', 'Hilary', 'Hilbert', 'Hill', 'Hillard', + 'Hillary', 'Hillery', 'Hilliard', 'Hilmer', 'Hilton', 'Hiram', + 'Hiroshi', 'Hjalmar', 'Hjalmer', 'Hobart', 'Hobert', 'Hobson', 'Hoke', + 'Holden', 'Holland', 'Hollie', 'Hollis', 'Holmes', 'Homer', 'Hoover', + 'Hope', 'Horace', 'Horacio', 'Horatio', 'Horton', 'Hosea', 'Hosie', + 'Hosteen', 'Houston', 'Howard', 'Howell', 'Hoy', 'Hoyt', 'Hubbard', + 'Hubert', 'Hudson', 'Huey', 'Hugh', 'Hughes', 'Hughey', 'Hughie', + 'Hugo', 'Humberto', 'Humphrey', 'Hung', 'Hunt', 'Hunter', 'Hurbert', + 'Hurley', 'Huston', 'Huy', 'Hyman', 'Hymen', 'Hyrum', 'Ian', 'Ibrahim', + 'Ida', 'Ignacio', 'Ignatius', 'Ignatz', 'Ike', 'Illya', 'Imanol', + 'Immanuel', 'Infant', 'Ingram', 'Ira', 'Irl', 'Irven', 'Irvin', + 'Irvine', 'Irving', 'Irwin', 'Isaac', 'Isaak', 'Isadore', 'Isai', + 'Isaiah', 'Isaias', 'Isam', 'Ishaan', 'Isham', 'Ishmael', 'Isiah', + 'Isidor', 'Isidore', 'Isidro', 'Ismael', 'Isom', 'Israel', 'Isreal', + 'Issac', 'Iva', 'Ivan', 'Iver', 'Iverson', 'Ivey', 'Ivor', 'Ivory', + 'Ivy', 'Izaiah', 'Izayah', 'Jabari', 'Jabbar', 'Jabez', 'Jace', 'Jack', + 'Jackson', 'Jacky', 'Jacob', 'Jacoby', 'Jacques', 'Jacquez', 'Jade', + 'Jaden', 'Jadiel', 'Jadon', 'Jadyn', 'Jaeden', 'Jagger', 'Jaheem', + 'Jaheim', 'Jahiem', 'Jahir', 'Jaiden', 'Jaidyn', 'Jaime', 'Jaimie', + 'Jair', 'Jairo', 'Jajuan', 'Jake', 'Jakob', 'Jakobe', 'Jaleel', 'Jalen', + 'Jalon', 'Jamaal', 'Jamal', 'Jamar', 'Jamarcus', 'Jamari', 'Jamarion', + 'Jame', 'Jameel', 'Jamel', 'James', 'Jameson', 'Jamey', 'Jamie', + 'Jamil', 'Jamin', 'Jamir', 'Jamison', 'Jammie', 'Jan', 'Jaquan', + 'Jaquez', 'Jarad', 'Jared', 'Jaren', 'Jaret', 'Jarett', 'Jarod', + 'Jaron', 'Jarrad', 'Jarred', 'Jarrell', 'Jarret', 'Jarrett', 'Jarrod', + 'Jarvis', 'Jase', 'Jasen', 'Jasiah', 'Jason', 'Jasper', 'Javen', + 'Javier', 'Javion', 'Javon', 'Javonte', 'Jax', 'Jaxen', 'Jaxon', + 'Jaxson', 'Jaxton', 'Jay', 'Jayce', 'Jaycob', 'Jaydan', 'Jayden', + 'Jaydin', 'Jaydon', 'Jaylan', 'Jaylen', 'Jaylin', 'Jaylon', 'Jayme', + 'Jaymes', 'Jayson', 'Jayvion', 'Jayvon', 'Jean', 'Jeb', 'Jed', + 'Jedediah', 'Jedidiah', 'Jeff', 'Jefferey', 'Jefferson', 'Jeffery', + 'Jeffie', 'Jeffrey', 'Jeffry', 'Jelani', 'Jemal', 'Jennings', 'Jens', + 'Jensen', 'Jep', 'Jeptha', 'Jerad', 'Jerald', 'Jeramiah', 'Jeramie', + 'Jeramy', 'Jere', 'Jered', 'Jerel', 'Jereme', 'Jeremey', 'Jeremiah', + 'Jeremie', 'Jeremy', 'Jerimiah', 'Jerimy', 'Jermain', 'Jermaine', + 'Jermey', 'Jerod', 'Jerold', 'Jerome', 'Jeromy', 'Jerrad', 'Jerrel', + 'Jerrell', 'Jerrod', 'Jerrold', 'Jerry', 'Jess', 'Jesse', 'Jessee', + 'Jessie', 'Jessy', 'Jesus', 'Jethro', 'Jett', 'Jettie', 'Jevon', + 'Jewell', 'Jiles', 'Jim', 'Jimmie', 'Jimmy', 'Joaquin', 'Job', 'Jobe', + 'Joe', 'Joel', 'Joeseph', 'Joesph', 'Joey', 'Johan', 'Johathan', 'John', + 'Johnathan', 'Johnathon', 'Johney', 'Johnie', 'Johnnie', 'Johnny', + 'Johnpaul', 'Johnson', 'Johny', 'Jon', 'Jonah', 'Jonas', 'Jonatan', + 'Jonathan', 'Jonathon', 'Jones', 'Jonnie', 'Jordan', 'Jorden', 'Jordi', + 'Jordon', 'Jordy', 'Jordyn', 'Jorge', 'Jory', 'Jose', 'Josef', + 'Joseluis', 'Joseph', 'Josephus', 'Josh', 'Joshua', 'Joshuah', 'Josiah', + 'Josue', 'Jovan', 'Jovani', 'Jovanni', 'Jovanny', 'Jovany', 'Joy', + 'Juan', 'Judah', 'Judd', 'Jude', 'Judge', 'Judson', 'Juelz', 'Jule', + 'Jules', 'Julian', 'Julien', 'Julio', 'Julious', 'Julius', 'Juluis', + 'Junior', 'Junious', 'Junius', 'Justen', 'Justice', 'Justin', 'Juston', + 'Justus', 'Justyn', 'Juwan', 'Kade', 'Kadeem', 'Kaden', 'Kadin', + 'Kadyn', 'Kaeden', 'Kael', 'Kahlil', 'Kai', 'Kaiden', 'Kale', 'Kaleb', + 'Kalel', 'Kalen', 'Kalvin', 'Kamari', 'Kamden', 'Kameron', 'Kamren', + 'Kamron', 'Kamryn', 'Kane', 'Kanye', 'Kareem', 'Kareen', 'Karim', + 'Karl', 'Karson', 'Karter', 'Kasen', 'Kasey', 'Kash', 'Kason', 'Kavon', + 'Kayden', 'Kaye', 'Kayson', 'Kazuo', 'Keagan', 'Keandre', 'Keanu', + 'Keaton', 'Keegan', 'Keenan', 'Keenen', 'Kegan', 'Keifer', 'Keion', + 'Keith', 'Kelan', 'Kelby', 'Kellan', 'Kellen', 'Kelley', 'Kelly', + 'Kelsey', 'Kelton', 'Kelvin', 'Kem', 'Ken', 'Kenan', 'Kendal', + 'Kendall', 'Kendell', 'Kendrick', 'Kenji', 'Kennard', 'Kennedy', + 'Kenneth', 'Kenney', 'Kennith', 'Kennth', 'Kenny', 'Kent', 'Kenton', + 'Kenya', 'Kenyatta', 'Kenyon', 'Keon', 'Kermit', 'Kerry', 'Kerwin', + 'Keshaun', 'Keshawn', 'Kevan', 'Keven', 'Kevin', 'Kevon', 'Keyon', + 'Keyshawn', 'Khalid', 'Khalil', 'Khari', 'Khiry', 'Kian', 'Kiara', + 'Kiefer', 'Kiel', 'Kieran', 'Kieth', 'Kiley', 'Killian', 'Kim', + 'Kimball', 'Kimberly', 'King', 'Kingston', 'Kinte', 'Kip', 'Kipp', + 'Kirby', 'Kirk', 'Kirt', 'Kit', 'Kiyoshi', 'Knox', 'Knute', 'Kobe', + 'Koby', 'Koda', 'Kody', 'Koen', 'Kolby', 'Kole', 'Kolten', 'Kolton', + 'Konner', 'Konnor', 'Korbin', 'Kordell', 'Korey', 'Kory', 'Kraig', + 'Kris', 'Krish', 'Kristen', 'Kristian', 'Kristin', 'Kristofer', + 'Kristoffer', 'Kristopher', 'Kunta', 'Kurt', 'Kurtis', 'Kwame', 'Kyan', + 'Kylan', 'Kyle', 'Kyler', 'Kymani', 'Kyree', 'Kyson', 'Lacey', 'Lacy', + 'Ladarius', 'Laddie', 'Lafayette', 'Lafe', 'Lamar', 'Lamarcus', + 'Lambert', 'Lamont', 'Lamonte', 'Lance', 'Landan', 'Landen', 'Landin', + 'Landon', 'Landyn', 'Lane', 'Lannie', 'Lanny', 'Laquan', 'Lark', + 'Larkin', 'Laron', 'Larry', 'Lars', 'Larue', 'Lary', 'Lashawn', + 'Latrell', 'Laurance', 'Laurel', 'Laurence', 'Lavar', 'Lavern', + 'Laverne', 'Lavon', 'Lawerence', 'Lawrance', 'Lawrence', 'Lawson', + 'Lawton', 'Lawyer', 'Layne', 'Layton', 'Lazaro', 'Le', 'Lea', 'Leamon', + 'Leander', 'Leandro', 'Lee', 'Leeroy', 'Leif', 'Leigh', 'Leighton', + 'Leland', 'Lem', 'Lemmie', 'Lemon', 'Lemuel', 'Len', 'Lena', 'Lenard', + 'Lennie', 'Lennon', 'Lenny', 'Lenon', 'Lenord', 'Lenwood', 'Leo', + 'Leon', 'Leonard', 'Leonardo', 'Leonce', 'Leonel', 'Leonidas', + 'Leopold', 'Leopoldo', 'Leroy', 'Les', 'Lesley', 'Leslie', 'Less', + 'Lessie', 'Lester', 'Levar', 'Levern', 'Levi', 'Levie', 'Levin', + 'Levon', 'Levy', 'Lew', 'Lewis', 'Lex', 'Lexie', 'Liam', 'Lige', + 'Lilburn', 'Lillard', 'Lim', 'Lincoln', 'Lindbergh', 'Lindell', + 'Linden', 'Lindsay', 'Lindsey', 'Lindy', 'Link', 'Linn', 'Linnie', + 'Linton', 'Linus', 'Linwood', 'Linzy', 'Lionel', 'Lisandro', 'Lish', + 'Lisle', 'Liston', 'Little', 'Littleton', 'Llewellyn', 'Lloyd', 'Logan', + 'Lon', 'London', 'Lone', 'Loney', 'Long', 'Lonie', 'Lonnie', 'Lonny', + 'Lonzo', 'Lora', 'Loran', 'Loren', 'Lorenz', 'Lorenza', 'Lorenzo', + 'Lorin', 'Loring', 'Lorne', 'Lott', 'Lou', 'Louie', 'Louis', 'Love', + 'Lovell', 'Lovett', 'Lovie', 'Lowell', 'Loy', 'Loyal', 'Loyd', 'Luc', + 'Luca', 'Lucas', 'Lucian', 'Luciano', 'Lucien', 'Lucio', 'Lucious', + 'Lucius', 'Lucky', 'Ludwig', 'Lue', 'Luigi', 'Luis', 'Luka', 'Lukas', + 'Luke', 'Lula', 'Lum', 'Lupe', 'Luster', 'Lute', 'Luther', 'Luverne', + 'Lydell', 'Lyle', 'Lyman', 'Lyn', 'Lyndon', 'Lynn', 'Lynwood', 'Lyric', + 'Mac', 'Macarthur', 'Mace', 'Maceo', 'Mack', 'Mackenzie', 'Madden', + 'Maddox', 'Maddux', 'Madison', 'Mae', 'Mahlon', 'Major', 'Makai', + 'Makhi', 'Mal', 'Malachi', 'Malakai', 'Malaki', 'Malcolm', 'Malcom', + 'Male', 'Malik', 'Malvin', 'Mamie', 'Manford', 'Manley', 'Manly', + 'Mannie', 'Manning', 'Mansfield', 'Manson', 'Manuel', 'Marc', 'Marcel', + 'Marcelino', 'Marcell', 'Marcello', 'Marcellus', 'Marcelo', 'Marchello', + 'Marco', 'Marcos', 'Marcus', 'Margarito', 'Mariano', 'Mario', 'Marion', + 'Marius', 'Mark', 'Markel', 'Markell', 'Markus', 'Marland', 'Marley', + 'Marlin', 'Marlo', 'Marlon', 'Marlyn', 'Marques', 'Marquez', 'Marquis', + 'Marquise', 'Marrion', 'Marsh', 'Marshal', 'Marshall', 'Mart', + 'Martell', 'Martez', 'Martin', 'Marty', 'Marvin', 'Masao', 'Mason', + 'Mat', 'Mateo', 'Math', 'Mathew', 'Mathews', 'Mathias', 'Matias', + 'Matt', 'Matteo', 'Matthew', 'Matthias', 'Maurice', 'Mauricio', 'Mauro', + 'Maury', 'Maverick', 'Max', 'Maxie', 'Maxim', 'Maximilian', + 'Maximiliano', 'Maximillian', 'Maximo', 'Maximus', 'Maxwell', 'Maxx', + 'May', 'Maynard', 'Mayo', 'Mcarthur', 'Mckinley', 'Mearl', 'Mekhi', + 'Mel', 'Melbourne', 'Mell', 'Melton', 'Melville', 'Melvin', 'Melvyn', + 'Memphis', 'Menachem', 'Mercer', 'Merl', 'Merle', 'Merlin', 'Merlyn', + 'Merrill', 'Merritt', 'Merton', 'Mervin', 'Mervyn', 'Merwin', 'Messiah', + 'Metro', 'Meyer', 'Micah', 'Michael', 'Michal', 'Michale', 'Micheal', + 'Michel', 'Michial', 'Mickey', 'Micky', 'Miguel', 'Miguelangel', + 'Mikal', 'Mike', 'Mikeal', 'Mikel', 'Mikhail', 'Milan', 'Milas', + 'Milburn', 'Miles', 'Milford', 'Millard', 'Miller', 'Mills', 'Milo', + 'Milton', 'Miner', 'Minor', 'Minoru', 'Misael', 'Mitch', 'Mitchel', + 'Mitchell', 'Moe', 'Mohamed', 'Mohammad', 'Mohammed', 'Moises', + 'Monroe', 'Mont', 'Montana', 'Monte', 'Montel', 'Montgomery', 'Montie', + 'Montrell', 'Monty', 'Moody', 'Mordechai', 'Morgan', 'Morris', + 'Mortimer', 'Morton', 'Mose', 'Moses', 'Moshe', 'Muhammad', 'Murdock', + 'Murl', 'Murphy', 'Murray', 'Murry', 'Mustafa', 'Mychal', 'Myer', + 'Mykel', 'Myles', 'Myrl', 'Myron', 'Myrtle', 'Najee', 'Nakia', 'Namon', + 'Napoleon', 'Nash', 'Nasir', 'Nat', 'Nathan', 'Nathanael', 'Nathanial', + 'Nathaniel', 'Nathen', 'Neal', 'Ned', 'Needham', 'Neely', 'Nehemiah', + 'Neil', 'Nello', 'Nels', 'Nelson', 'Nery', 'Nestor', 'Nevin', 'Newell', + 'Newman', 'Newt', 'Newton', 'Nicholas', 'Nicholaus', 'Nick', 'Nicklaus', + 'Nickolas', 'Nicky', 'Nico', 'Nicolas', 'Nigel', 'Nikhil', 'Nikko', + 'Niko', 'Nikolai', 'Nikolas', 'Nile', 'Niles', 'Nils', 'Nim', 'Noah', + 'Noble', 'Noe', 'Noel', 'Nolan', 'Nolen', 'Norbert', 'Norberto', + 'Norman', 'Normand', 'Norris', 'North', 'Norton', 'Norval', 'Norwood', + 'Nunzio', 'Oakley', 'Obe', 'Obed', 'Obie', 'Ocie', 'Octave', 'Octavio', + 'Octavius', 'Oda', 'Oddie', 'Odell', 'Odie', 'Odin', 'Odis', 'Odus', + 'Offie', 'Ogden', 'Okey', 'Ola', 'Olaf', 'Olan', 'Oland', 'Ole', 'Olen', + 'Oley', 'Olie', 'Olin', 'Oliver', 'Ollie', 'Olof', 'Omar', 'Omari', + 'Omarion', 'Omer', 'Oneal', 'Ora', 'Oral', 'Oran', 'Orange', 'Oren', + 'Orie', 'Orin', 'Orion', 'Oris', 'Orla', 'Orland', 'Orlando', 'Orley', + 'Orlin', 'Orlo', 'Orren', 'Orrie', 'Orrin', 'Orris', 'Orson', 'Orval', + 'Orvel', 'Orvil', 'Orville', 'Orvin', 'Orvis', 'Osbaldo', 'Osborn', + 'Osborne', 'Oscar', 'Osie', 'Ossie', 'Osvaldo', 'Oswald', 'Oswaldo', + 'Otha', 'Othel', 'Otho', 'Otis', 'Ott', 'Ottie', 'Ottis', 'Otto', 'Ova', + 'Ovid', 'Ovila', 'Owen', 'Owens', 'Ozell', 'Ozie', 'Ozzie', 'Pablo', + 'Page', 'Palmer', 'Paris', 'Park', 'Parker', 'Parley', 'Parrish', + 'Pascal', 'Pasquale', 'Pat', 'Pate', 'Patric', 'Patrick', 'Paul', + 'Paulo', 'Paxton', 'Payton', 'Pearley', 'Pedro', 'Percival', 'Percy', + 'Perley', 'Pernell', 'Perry', 'Pershing', 'Pete', 'Peter', 'Peyton', + 'Phil', 'Philip', 'Phillip', 'Philo', 'Phoenix', 'Pierce', 'Pierre', + 'Pinkney', 'Pleas', 'Pleasant', 'Ples', 'Plummer', 'Polk', 'Porfirio', + 'Porter', 'Posey', 'Powell', 'Pranav', 'Pratt', 'Prentice', 'Prentiss', + 'Presley', 'Press', 'Preston', 'Price', 'Primus', 'Prince', 'Prosper', + 'Pryor', 'Purl', 'Quentin', 'Quincy', 'Quinn', 'Quint', 'Quinten', + 'Quintin', 'Quinton', 'Rae', 'Raekwon', 'Rafael', 'Rafe', 'Raheem', + 'Rahn', 'Rahsaan', 'Rahul', 'Raiden', 'Rakeem', 'Raleigh', 'Ralph', + 'Ramiro', 'Ramon', 'Ramsey', 'Rance', 'Rand', 'Randal', 'Randall', + 'Randel', 'Randell', 'Randle', 'Randolf', 'Randolph', 'Randy', 'Ransom', + 'Raoul', 'Raphael', 'Raquan', 'Ras', 'Rashaad', 'Rashaan', 'Rashad', + 'Rashawn', 'Rasheed', 'Raul', 'Raven', 'Ray', 'Rayan', 'Rayburn', + 'Rayfield', 'Rayford', 'Raymon', 'Raymond', 'Raymundo', 'Raynard', + 'Rayshawn', 'Reagan', 'Reason', 'Red', 'Redden', 'Redmond', 'Reece', + 'Reed', 'Reese', 'Refugio', 'Regan', 'Reggie', 'Reginal', 'Reginald', + 'Regis', 'Reid', 'Reilly', 'Reinaldo', 'Reinhold', 'Reino', 'Remington', + 'Remy', 'Renaldo', 'Renard', 'Rene', 'Reno', 'Reuben', 'Reubin', 'Rex', + 'Rexford', 'Rey', 'Reyes', 'Reynaldo', 'Reynold', 'Reynolds', 'Rhett', + 'Rhoda', 'Rhys', 'Rian', 'Ricardo', 'Ricci', 'Rice', 'Rich', 'Richard', + 'Richie', 'Richmond', 'Rick', 'Rickey', 'Ricki', 'Rickie', 'Ricky', + 'Rico', 'Ridge', 'Rigoberto', 'Riley', 'Rishi', 'Ritchie', 'River', + 'Rob', 'Robb', 'Robbie', 'Robbin', 'Robby', 'Robert', 'Roberto', + 'Robin', 'Robley', 'Robt', 'Roby', 'Rocco', 'Rock', 'Rocky', 'Rod', + 'Roddy', 'Roderic', 'Roderick', 'Rodger', 'Rodney', 'Rodolfo', + 'Rodrick', 'Rodrigo', 'Roe', 'Roel', 'Rogelio', 'Roger', 'Rogers', + 'Rohan', 'Roland', 'Rolando', 'Rolf', 'Roll', 'Rolla', 'Rolland', + 'Rollie', 'Rollin', 'Rollo', 'Roma', 'Roman', 'Rome', 'Romello', + 'Romeo', 'Romie', 'Ron', 'Ronal', 'Ronald', 'Ronaldo', 'Ronan', + 'Rondal', 'Ronin', 'Ronnie', 'Ronny', 'Roosevelt', 'Rory', 'Rosario', + 'Rosco', 'Roscoe', 'Rosendo', 'Rosevelt', 'Ross', 'Rossie', 'Roswell', + 'Rowan', 'Rowland', 'Roy', 'Royal', 'Royce', 'Rube', 'Ruben', 'Rubin', + 'Ruby', 'Rudolf', 'Rudolfo', 'Rudolph', 'Rudy', 'Rueben', 'Ruel', + 'Ruffin', 'Ruffus', 'Rufus', 'Rupert', 'Rush', 'Russ', 'Russel', + 'Russell', 'Rustin', 'Rusty', 'Rutherford', 'Ryan', 'Ryder', 'Ryker', + 'Rylan', 'Ryland', 'Rylee', 'Ryley', 'Ryne', 'Sabastian', 'Sage', + 'Saint', 'Sal', 'Salomon', 'Salvador', 'Salvatore', 'Sam', 'Samie', + 'Samir', 'Sammie', 'Sammy', 'Sampson', 'Samson', 'Samual', 'Samuel', + 'Sanders', 'Sandy', 'Sanford', 'Santana', 'Santiago', 'Santino', + 'Santo', 'Santos', 'Saul', 'Saverio', 'Savion', 'Savon', 'Sawyer', + 'Schley', 'Schuyler', 'Scot', 'Scott', 'Scottie', 'Scotty', 'Seaborn', + 'Seamus', 'Sean', 'Sebastian', 'Sedrick', 'Seldon', 'Selmer', 'Semaj', + 'Seneca', 'Sergio', 'Seth', 'Severo', 'Severt', 'Seward', 'Seymour', + 'Shad', 'Shade', 'Shafter', 'Shamar', 'Shan', 'Shane', 'Shannon', + 'Shanon', 'Shaquan', 'Shaquille', 'Sharif', 'Sharon', 'Shaun', 'Shawn', + 'Shay', 'Shayne', 'Shea', 'Shedrick', 'Shelby', 'Sheldon', 'Shelley', + 'Shellie', 'Shelly', 'Shelton', 'Shemar', 'Shep', 'Shepherd', + 'Sheridan', 'Sherman', 'Sherrill', 'Sherwin', 'Sherwood', 'Shirley', + 'Shoji', 'Shon', 'Shyheim', 'Sid', 'Sidney', 'Sie', 'Sigmund', 'Sigurd', + 'Silas', 'Silver', 'Silvester', 'Silvio', 'Sim', 'Simeon', 'Simmie', + 'Simon', 'Simpson', 'Sincere', 'Sing', 'Skip', 'Skylar', 'Skyler', + 'Slade', 'Smith', 'Sol', 'Soloman', 'Solomon', 'Solon', 'Son', 'Sonny', + 'Soren', 'Spencer', 'Spenser', 'Spurgeon', 'Squire', 'Stacey', 'Stacy', + 'Stafford', 'Stan', 'Stanford', 'Stanislaus', 'Stanley', 'Stanton', + 'Starling', 'Stefan', 'Stephan', 'Stephanie', 'Stephen', 'Stephon', + 'Sterling', 'Stetson', 'Stevan', 'Steve', 'Steven', 'Stevie', 'Steward', + 'Stewart', 'Stone', 'Stonewall', 'Stoney', 'Storm', 'Stuart', + 'Sullivan', 'Sumner', 'Susie', 'Sydney', 'Syed', 'Sylas', 'Sylvan', + 'Sylvanus', 'Sylvester', 'Tab', 'Tad', 'Taft', 'Tahj', 'Taj', 'Tal', + 'Talan', 'Talen', 'Tallie', 'Talmadge', 'Talmage', 'Talon', 'Tandy', + 'Tanner', 'Tarik', 'Tariq', 'Tate', 'Tatsuo', 'Taurean', 'Taurus', + 'Tavares', 'Tavaris', 'Tavian', 'Tavion', 'Tavon', 'Tayler', 'Taylor', + 'Tayshaun', 'Teagan', 'Ted', 'Teddie', 'Teddy', 'Tegan', 'Telly', + 'Terance', 'Terell', 'Terence', 'Terrance', 'Terrell', 'Terrence', + 'Terrill', 'Terry', 'Tevin', 'Tex', 'Thad', 'Thaddeus', 'Theadore', + 'Thedore', 'Theo', 'Theodis', 'Theodore', 'Theophile', 'Therman', + 'Theron', 'Thomas', 'Thompson', 'Thor', 'Thornton', 'Thorwald', 'Thos', + 'Thurlow', 'Thurman', 'Thurston', 'Tilden', 'Tillman', 'Tilman', 'Tim', + 'Timmie', 'Timmothy', 'Timmy', 'Timothy', 'Tito', 'Titus', 'Tobe', + 'Tobias', 'Tobie', 'Tobin', 'Toby', 'Tod', 'Todd', 'Toivo', 'Tolbert', + 'Tollie', 'Tom', 'Toma', 'Tomas', 'Tomie', 'Tommie', 'Tommy', 'Toney', + 'Tony', 'Torey', 'Toriano', 'Torrance', 'Torrence', 'Torrey', 'Torry', + 'Tory', 'Toshio', 'Toy', 'Trace', 'Tracey', 'Tracy', 'Trae', 'Travis', + 'Travon', 'Trayvon', 'Tre', 'Tremaine', 'Tremayne', 'Trent', 'Trenten', + 'Trenton', 'Trever', 'Trevin', 'Trevion', 'Trevon', 'Trevor', 'Trey', + 'Treyton', 'Treyvon', 'Trinidad', 'Trinity', 'Tripp', 'Tristan', + 'Tristen', 'Tristian', 'Tristin', 'Triston', 'Troy', 'True', 'Trumaine', + 'Truman', 'Trystan', 'Tuan', 'Tucker', 'Turner', 'Ty', 'Tye', 'Tyler', + 'Tylor', 'Tyquan', 'Tyree', 'Tyreek', 'Tyreese', 'Tyrek', 'Tyreke', + 'Tyrel', 'Tyrell', 'Tyrese', 'Tyrik', 'Tyrin', 'Tyriq', 'Tyrique', + 'Tyron', 'Tyrone', 'Tyrus', 'Tyshawn', 'Tyson', 'Ulises', 'Ulysses', + 'Unknown', 'Unnamed', 'Urban', 'Uriah', 'Uriel', 'Urijah', 'Val', + 'Valentin', 'Valentine', 'Valentino', 'Van', 'Vance', 'Vander', + 'Vashon', 'Vaughn', 'Vera', 'Vere', 'Vergil', 'Verl', 'Verle', 'Verlin', + 'Verlon', 'Verlyn', 'Vern', 'Verna', 'Vernal', 'Verne', 'Vernell', + 'Verner', 'Vernie', 'Vernon', 'Vester', 'Vic', 'Vicente', 'Vick', + 'Victor', 'Victoriano', 'Vidal', 'Vince', 'Vincent', 'Vincenzo', + 'Vinson', 'Vinton', 'Virge', 'Virgel', 'Virgie', 'Virgil', 'Virgle', + 'Vito', 'Vollie', 'Volney', 'Von', 'Wade', 'Waino', 'Waldemar', 'Waldo', + 'Walker', 'Wallace', 'Wally', 'Walt', 'Walter', 'Walton', 'Ward', + 'Wardell', 'Warner', 'Warren', 'Wash', 'Washington', 'Watson', 'Watt', + 'Waverly', 'Wayde', 'Wayland', 'Waylon', 'Wayman', 'Waymon', 'Wayne', + 'Weaver', 'Webb', 'Webster', 'Weldon', 'Wellington', 'Wells', 'Welton', + 'Wendel', 'Wendell', 'Wenzel', 'Werner', 'Wes', 'Wesley', 'Wess', + 'West', 'Westin', 'Westley', 'Weston', 'Wheeler', 'Whit', 'Whitney', + 'Wilber', 'Wilbert', 'Wilbur', 'Wilburn', 'Wiley', 'Wilford', 'Wilfred', + 'Wilfredo', 'Wilfrid', 'Wilhelm', 'Wiliam', 'Wilkie', 'Will', 'Willaim', + 'Willam', 'Willard', 'William', 'Williams', 'Willian', 'Williard', + 'Willie', 'Willis', 'Willy', 'Wilmer', 'Wilson', 'Wilton', 'Windell', + 'Winfield', 'Winford', 'Winfred', 'Wing', 'Winifred', 'Winnie', + 'Winston', 'Winthrop', 'Winton', 'Wirt', 'Wm', 'Wong', 'Wood', 'Woodie', + 'Woodroe', 'Woodrow', 'Woodson', 'Woody', 'Worley', 'Worth', 'Wright', + 'Wyatt', 'Wylie', 'Wyman', 'Xander', 'Xavier', 'Xzavier', 'Yaakov', + 'Yadiel', 'Yael', 'Yahir', 'Yair', 'Yancy', 'Yandel', 'Yee', 'Yehuda', + 'Yoel', 'York', 'Yosef', 'Yoshio', 'Young', 'Yurem', 'Yusuf', + 'Zachariah', 'Zachary', 'Zachery', 'Zack', 'Zackary', 'Zackery', 'Zaid', + 'Zaiden', 'Zain', 'Zaire', 'Zakary', 'Zander', 'Zane', 'Zavier', + 'Zavion', 'Zayden', 'Zayne', 'Zeb', 'Zebulon', 'Zechariah', 'Zed', + 'Zeke', 'Zenas', 'Zeno', 'Zigmund', 'Zion', 'Zollie', + } + + +def create_english_cleaned_dataset(share_dir='/content/drive/Shareddrives/BigScience/'): + + prev={} + if not os.path.exists("cleaned_english.tsv"): + with open("english.tsv", "w", encoding="utf8") as o: + + #https://github.com/reglab/casehold court cases are government works and in the public domain. + #Annotations and selections are under Apache-2.0 License + """ + @inproceedings{zhengguha2021, + title={When Does Pretraining Help? Assessing Self-Supervised Learning for Law and the CaseHOLD Dataset}, + author={Lucia Zheng and Neel Guha and Brandon R. Anderson and Peter Henderson and Daniel E. Ho}, + year={2021}, + eprint={2104.08671}, + archivePrefix={arXiv}, + primaryClass={cs.CL}, + booktitle={Proceedings of the 18th International Conference on Artificial Intelligence and Law}, + publisher={Association for Computing Machinery} + } + """ + with open(f"{share_dir}/casehold.csv", "rb") as f: + while True: + line = f.readline().decode() + if not line: break + line = line.split(",\"") + if len(line) >= 2: + line = line[1] + line = line.split("()") + if len(line) == 2: + s1, s2 = line + s1 = s1.replace(" ", " ").replace(" ", " ") + s2 = s2.replace(" ", " ").replace(" ", " ") + s2 = ' '.join(s2.split(',')[:-6]).strip(';: ') + if s2: + o.write(s1+' HOLDING: '+s2+"\tcasehold\n") + else: + o.write(s1+"\tcasehold\n") + else: + s1 = s1.replace(" ", " ").replace(" ", " ") + o.write(s1+"\tcasehold\n") + + + #from https://www.kaggle.com/wcukierski/enron-email-dataset, originally from https://www.cs.cmu.edu/~enron/ + # public data and partially copyrighted works (annotations) used by permission of authors + """ + Public record data origially published by www.ferc.gov. Subsequent data cleansing by the authors and released + "as a resource for researchers who are interested in improving current email tools, or understanding how email is currently used". + """ + with open(f"{share_dir}/kaggle_enron_emails.csv", "rb") as f: + in_message = False + l2 = "" + while True: + l = f.readline() + if not l: break + l = l.decode().strip() + if not in_message and l.startswith("Subject:"): + l = l.replace("Subject:", "").strip() + if l: l2 = l+ ":" + if "X-FileName" in l: + in_message = True + continue + elif "Message-ID" in l: + save_enron_line(l2, prev, o) + l2 = "" + in_message = False + if in_message: + l2 += " "+l + + if l2: + save_enron_line(l2, prev, o) + + #https://huggingface.co/datasets/civil_comments - CC0 + """ + @article{DBLP:journals/corr/abs-1903-04561, + author = {Daniel Borkan and + Lucas Dixon and + Jeffrey Sorensen and + Nithum Thain and + Lucy Vasserman}, + title = {Nuanced Metrics for Measuring Unintended Bias with Real Data for Text + Classification}, + journal = {CoRR}, + volume = {abs/1903.04561}, + year = {2019}, + url = {http://arxiv.org/abs/1903.04561}, + archivePrefix = {arXiv}, + eprint = {1903.04561}, + timestamp = {Sun, 31 Mar 2019 19:01:24 +0200}, + biburl = {https://dblp.org/rec/bib/journals/corr/abs-1903-04561}, + bibsource = {dblp computer science bibliography, https://dblp.org} +} + """ + # An experiment we could try is tagging with another public figure tag called PUBLIC_FIGURE_OPINION + # so that we could train a model to distinguish between public figure mentions in opinion domains vs non-opinion domains + + dataset = load_dataset("civil_comments") + for d in (dataset['train'], ): + for idx, data in enumerate(d): + score = sum ([data[feature] for feature in [ 'toxicity', 'severe_toxicity', 'obscene', 'threat', 'insult', 'identity_attack', 'sexual_explicit']]) + l2 = data['text'] + l2 = l2.replace("\n", " ").replace(" ", " ").replace(" ", " ") + l2Arr = l2.split() + has_a_name = has_any(first_names, l2Arr) + l2_lower = l2.lower() + if random.choice([0,1]) and not has_a_name and "mr." not in l2_lower and "ms." not in l2_lower and "mrs." not in l2_lower and "president" not in l2_lower and "governor" not in l2_lower and "mayor" not in l2_lower: + continue + if len(l2Arr) > 10 and len(l2Arr) < 50 and (score <= 0.5 or random.randint(0, 10)==0): # having too much toxic content may skew the data + if has_a_name or "mr." in l2_lower or "ms." in l2_lower or "mrs." in l2_lower or "senator" in l2_lower or "president" in l2_lower or "governor" in l2_lower or "mayor" in l2_lower: + o.write (l2+"\tcivil_comments\n") + + os.system("sort --parallel=32 english.tsv -o english.tsv") + + with open("english_cleaned.tsv", "w", encoding="utf8") as o: + with open("english.tsv", "rb") as f: + prev="" + while True: + l = f.readline().decode() + if not l: break + l = l.strip() + l2 = l.replace(":", "").replace("[", "").replace("]", "").replace(".", "").replace("!", "").replace("?", "").replace(",", "").replace("-", "").replace(";", "").replace(" ", "").lower() + prev2 = prev.replace(":", "").replace("[", "").replace("]", "").replace(".", "").replace("!", "").replace("?", "").replace(",", "").replace("-", "").replace(";", "").replace(" ", "").lower() + if prev != "" and (l2==prev2 or (len(prev) > 10 and len(l) > 10 and prev2[:10]== l2[:10])): + if len(l) > len(prev): + prev = l + continue + else: + if prev: + if prev[0] < 'וח': + o.write (prev.lstrip(':;.+- ')+"\n") + prev = l + if prev: + if prev[0] < 'וח': + o.write (prev.lstrip(':;.+- ')+"\n") + + + os.system("sort --parallel=32 english_cleaned.tsv -o english_cleaned.tsv") + os.system(f"cp english_cleaned.tsv {share_dir}/english_cleaned.tsv") + #os.system("rm ./english.tsv") + +def cleanup_english2(): + with open("english_cleaned2.tsv", "w", encoding="utf8") as o: + with open("english_cleaned.tsv", "rb") as f: + prev="" + while True: + l = f.readline().decode() + if not l: break + l = l.strip() + l2 = l.replace(":", "").replace("[", "").replace("]", "").replace(".", "").replace("!", "").replace("?", "").replace(",", "").replace("-", "").replace(";", "").replace(" ", "").lower() + prev2 = prev.replace(":", "").replace("[", "").replace("]", "").replace(".", "").replace("!", "").replace("?", "").replace(",", "").replace("-", "").replace(";", "").replace(" ", "").lower() + if prev != "" and (l2==prev2 or (len(prev) > 10 and len(l) > 10 and prev2[:10]== l2[:10])): + if len(l) > len(prev): + prev = l + continue + + if prev: + if prev[0].lower() not in "abcdefghijklmnopqrstuvwxyz": + prev=l + continue + ret = prev.split("\t") + if len(ret) != 2: + prev=l + continue + sent, ds = ret + sent = sent.split(".") + while len(sent) > 3: + sent2 = sent[:3] + sent = sent[3:] + if sent2 and sent2[0] and sent2[0][0].lower() not in "abcdefghijklmnopqrstuvwxyz": + prev=l + continue + has_a_name = has_any(first_names, sent2) + if not has_a_name: + prev = l + continue + sent2 = ". ".join(sent2)+"." + sent2 = sent2.strip().replace(" ", " ").replace(" .com", ".com") + if len(sent2) < 20: + prev = l + continue + #print (sent2) + o.write(sent2+"\t"+ds+"\n") + if sent and sent[0] and sent[0][0].lower() not in "abcdefghijklmnopqrstuvwxyz": + prev=l + continue + has_a_name = has_any(first_names, sent) + if not has_a_name: + prev = l + continue + sent2 = ". ".join(sent)+"." + sent2 = sent2.strip().replace(" ", " ").replace(" .com", ".com") + if len(sent2) < 20: + prev = l + continue + #print (sent2) + o.write(sent2+"\t"+ds+"\n") + prev = l + + if prev: + if prev[0].lower() in "abcdefghijklmnopqrstuvwxyz": + sent, ds = prev.split("\t") + sent = sent.split(".") + while len(sent) > 3: + sent2 = sent[:3] + sent = sent[3:] + sent2 = ". ".join(sent2)+"." + sent2 = sent2.strip().replace(" ", " ").replace(" .com", ".com") + if len(sent2) >= 20: + print (sent2) + o.write(sent2+"\t"+ds+"\n") + sent2 = ". ".join(sent)+"." + sent2 = sent2.strip().replace(" ", " ").replace(" .com", ".com") + #print (sent2) + if len(sent2) >= 20: + o.write(sent2+"\t"+ds+"\n") + + +create_english_cleaned_dataset() +cleanup_english2() + diff --git a/data_tooling/pii_processing/misc/m2m100_translations.ipynb b/data_tooling/pii_processing/misc/m2m100_translations.ipynb new file mode 100644 index 0000000..a975e47 --- /dev/null +++ b/data_tooling/pii_processing/misc/m2m100_translations.ipynb @@ -0,0 +1,473 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": null, + "id": "a2b7b03b", + "metadata": {}, + "outputs": [], + "source": [ + "from datasets import load_dataset\n", + "import os\n", + "import re\n", + "import itertools\n", + "from re import finditer\n", + "import glob\n", + "import random\n", + "import fsspec\n", + "import json\n", + "from random import randint, choice\n", + "from collections import Counter\n", + "import spacy, itertools\n", + "import langid\n", + "from nltk.corpus import stopwords\n", + "import fsspec, os, gzip\n", + "from faker import Faker\n", + "from faker.providers import person, company, geo, address, ssn\n", + "from transformers import M2M100ForConditionalGeneration, M2M100Tokenizer, MarianMTModel, AutoTokenizer, pipeline\n", + "import torch\n", + "import sys\n", + "from tqdm import tqdm" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "8f184c2a", + "metadata": {}, + "outputs": [], + "source": [ + "basic_regex = [\n", + " (\"EMAIL_ADDRESS\", re.compile(\n", + " \"([a-z0-9!#$%&'*+\\/=?^_`{|.}~-]+@(?:[a-z0-9](?:[a-z0-9-]*[a-z0-9])?\\.)+[a-z0-9](?:[a-z0-9-]*[a-z0-9])?)\")),\n", + " (\"AGE\", re.compile(\"\\S+ years old|\\S+\\-years\\-old|\\S+ year old|\\S+\\-year\\-old\")),\n", + " # (\"PHONE_NUMBER\" , re.compile('((?:(?!@#^&*()+-‑=:;`→¶'"]) + +faker_map = dict([(a.split("_")[0], a) for a in [ + 'ar_AA', + 'ar_PS', + 'ar_SA', + 'bg_BG', + 'cs_CZ', + 'de_AT', + 'de_CH', + 'de_DE', + 'dk_DK', + 'el_GR', + 'en_GB', + 'en_IE', + 'en_IN', + 'en_NZ', + 'en_TH', + 'en_US', + 'es_CA', + 'es_ES', + 'es_MX', + 'et_EE', + 'fa_IR', + 'fi_FI', + 'fr_CA', + 'fr_CH', + 'fr_FR', + 'fr_QC', + 'ga_IE', + 'he_IL', + 'hi_IN', + 'hr_HR', + 'hu_HU', + 'hy_AM', + 'id_ID', + 'it_IT', + 'ja_JP', + 'ka_GE', + 'ko_KR', + 'lt_LT', + 'lv_LV', + 'ne_NP', + 'nl_NL', + 'no_NO', + 'or_IN', + 'pl_PL', + 'pt_BR', + 'pt_PT', + 'ro_RO', + 'ru_RU', + 'sl_SI', + 'sv_SE', + 'ta_IN', + 'th_TH', + 'tr_TR', + 'tw_GH', + 'uk_UA', + 'zh_CN', + 'zh_TW']] + [('en', 'en_US')]) + +mariam_mt_mapping = {('aav', 'en'): 'Helsinki-NLP/opus-mt-aav-en', ('aed', 'es'): 'Helsinki-NLP/opus-mt-aed-es', + ('af', 'de'): 'Helsinki-NLP/opus-mt-af-de', ('af', 'en'): 'Helsinki-NLP/opus-mt-af-en', + ('af', 'eo'): 'Helsinki-NLP/opus-mt-af-eo', ('af', 'es'): 'Helsinki-NLP/opus-mt-af-es', + ('af', 'fi'): 'Helsinki-NLP/opus-mt-af-fi', ('af', 'fr'): 'Helsinki-NLP/opus-mt-af-fr', + ('af', 'nl'): 'Helsinki-NLP/opus-mt-af-nl', ('af', 'ru'): 'Helsinki-NLP/opus-mt-af-ru', + ('af', 'sv'): 'Helsinki-NLP/opus-mt-af-sv', ('afa', 'afa'): 'Helsinki-NLP/opus-mt-afa-afa', + ('afa', 'en'): 'Helsinki-NLP/opus-mt-afa-en', ('alv', 'en'): 'Helsinki-NLP/opus-mt-alv-en', + ('am', 'sv'): 'Helsinki-NLP/opus-mt-am-sv', ('ar', 'de'): 'Helsinki-NLP/opus-mt-ar-de', + ('ar', 'el'): 'Helsinki-NLP/opus-mt-ar-el', ('ar', 'en'): 'Helsinki-NLP/opus-mt-ar-en', + ('ar', 'eo'): 'Helsinki-NLP/opus-mt-ar-eo', ('ar', 'es'): 'Helsinki-NLP/opus-mt-ar-es', + ('ar', 'fr'): 'Helsinki-NLP/opus-mt-ar-fr', ('ar', 'he'): 'Helsinki-NLP/opus-mt-ar-he', + ('ar', 'it'): 'Helsinki-NLP/opus-mt-ar-it', ('ar', 'pl'): 'Helsinki-NLP/opus-mt-ar-pl', + ('ar', 'ru'): 'Helsinki-NLP/opus-mt-ar-ru', ('ar', 'tr'): 'Helsinki-NLP/opus-mt-ar-tr', + ('art', 'en'): 'Helsinki-NLP/opus-mt-art-en', ('ase', 'de'): 'Helsinki-NLP/opus-mt-ase-de', + ('ase', 'en'): 'Helsinki-NLP/opus-mt-ase-en', ('ase', 'es'): 'Helsinki-NLP/opus-mt-ase-es', + ('ase', 'fr'): 'Helsinki-NLP/opus-mt-ase-fr', ('ase', 'sv'): 'Helsinki-NLP/opus-mt-ase-sv', + ('az', 'en'): 'Helsinki-NLP/opus-mt-az-en', ('az', 'es'): 'Helsinki-NLP/opus-mt-az-es', + ('az', 'tr'): 'Helsinki-NLP/opus-mt-az-tr', ('bat', 'en'): 'Helsinki-NLP/opus-mt-bat-en', + ('bcl', 'de'): 'Helsinki-NLP/opus-mt-bcl-de', ('bcl', 'en'): 'Helsinki-NLP/opus-mt-bcl-en', + ('bcl', 'es'): 'Helsinki-NLP/opus-mt-bcl-es', ('bcl', 'fi'): 'Helsinki-NLP/opus-mt-bcl-fi', + ('bcl', 'fr'): 'Helsinki-NLP/opus-mt-bcl-fr', ('bcl', 'sv'): 'Helsinki-NLP/opus-mt-bcl-sv', + ('be', 'es'): 'Helsinki-NLP/opus-mt-be-es', ('bem', 'en'): 'Helsinki-NLP/opus-mt-bem-en', + ('bem', 'es'): 'Helsinki-NLP/opus-mt-bem-es', ('bem', 'fi'): 'Helsinki-NLP/opus-mt-bem-fi', + ('bem', 'fr'): 'Helsinki-NLP/opus-mt-bem-fr', ('bem', 'sv'): 'Helsinki-NLP/opus-mt-bem-sv', + ('ber', 'en'): 'Helsinki-NLP/opus-mt-ber-en', ('ber', 'es'): 'Helsinki-NLP/opus-mt-ber-es', + ('ber', 'fr'): 'Helsinki-NLP/opus-mt-ber-fr', ('bg', 'de'): 'Helsinki-NLP/opus-mt-bg-de', + ('bg', 'en'): 'Helsinki-NLP/opus-mt-bg-en', ('bg', 'eo'): 'Helsinki-NLP/opus-mt-bg-eo', + ('bg', 'es'): 'Helsinki-NLP/opus-mt-bg-es', ('bg', 'fi'): 'Helsinki-NLP/opus-mt-bg-fi', + ('bg', 'fr'): 'Helsinki-NLP/opus-mt-bg-fr', ('bg', 'it'): 'Helsinki-NLP/opus-mt-bg-it', + ('bg', 'ru'): 'Helsinki-NLP/opus-mt-bg-ru', ('bg', 'sv'): 'Helsinki-NLP/opus-mt-bg-sv', + ('bg', 'tr'): 'Helsinki-NLP/opus-mt-bg-tr', ('bg', 'uk'): 'Helsinki-NLP/opus-mt-bg-uk', + ('bi', 'en'): 'Helsinki-NLP/opus-mt-bi-en', ('bi', 'es'): 'Helsinki-NLP/opus-mt-bi-es', + ('bi', 'fr'): 'Helsinki-NLP/opus-mt-bi-fr', ('bi', 'sv'): 'Helsinki-NLP/opus-mt-bi-sv', + ('bn', 'en'): 'Helsinki-NLP/opus-mt-bn-en', ('bnt', 'en'): 'Helsinki-NLP/opus-mt-bnt-en', + ('bzs', 'en'): 'Helsinki-NLP/opus-mt-bzs-en', ('bzs', 'es'): 'Helsinki-NLP/opus-mt-bzs-es', + ('bzs', 'fi'): 'Helsinki-NLP/opus-mt-bzs-fi', ('bzs', 'fr'): 'Helsinki-NLP/opus-mt-bzs-fr', + ('bzs', 'sv'): 'Helsinki-NLP/opus-mt-bzs-sv', ('ca', 'de'): 'Helsinki-NLP/opus-mt-ca-de', + ('ca', 'en'): 'Helsinki-NLP/opus-mt-ca-en', ('ca', 'es'): 'Helsinki-NLP/opus-mt-ca-es', + ('ca', 'fr'): 'Helsinki-NLP/opus-mt-ca-fr', ('ca', 'it'): 'Helsinki-NLP/opus-mt-ca-it', + ('ca', 'nl'): 'Helsinki-NLP/opus-mt-ca-nl', ('ca', 'pt'): 'Helsinki-NLP/opus-mt-ca-pt', + ('ca', 'uk'): 'Helsinki-NLP/opus-mt-ca-uk', ('cau', 'en'): 'Helsinki-NLP/opus-mt-cau-en', + ('ccs', 'en'): 'Helsinki-NLP/opus-mt-ccs-en', ('ceb', 'en'): 'Helsinki-NLP/opus-mt-ceb-en', + ('ceb', 'es'): 'Helsinki-NLP/opus-mt-ceb-es', ('ceb', 'fi'): 'Helsinki-NLP/opus-mt-ceb-fi', + ('ceb', 'fr'): 'Helsinki-NLP/opus-mt-ceb-fr', ('ceb', 'sv'): 'Helsinki-NLP/opus-mt-ceb-sv', + ('cel', 'en'): 'Helsinki-NLP/opus-mt-cel-en', ('chk', 'en'): 'Helsinki-NLP/opus-mt-chk-en', + ('chk', 'es'): 'Helsinki-NLP/opus-mt-chk-es', ('chk', 'fr'): 'Helsinki-NLP/opus-mt-chk-fr', + ('chk', 'sv'): 'Helsinki-NLP/opus-mt-chk-sv', ('cpf', 'en'): 'Helsinki-NLP/opus-mt-cpf-en', + ('cpp', 'cpp'): 'Helsinki-NLP/opus-mt-cpp-cpp', ('cpp', 'en'): 'Helsinki-NLP/opus-mt-cpp-en', + ('crs', 'de'): 'Helsinki-NLP/opus-mt-crs-de', ('crs', 'en'): 'Helsinki-NLP/opus-mt-crs-en', + ('crs', 'es'): 'Helsinki-NLP/opus-mt-crs-es', ('crs', 'fi'): 'Helsinki-NLP/opus-mt-crs-fi', + ('crs', 'fr'): 'Helsinki-NLP/opus-mt-crs-fr', ('crs', 'sv'): 'Helsinki-NLP/opus-mt-crs-sv', + ('cs', 'de'): 'Helsinki-NLP/opus-mt-cs-de', ('cs', 'en'): 'Helsinki-NLP/opus-mt-cs-en', + ('cs', 'eo'): 'Helsinki-NLP/opus-mt-cs-eo', ('cs', 'fi'): 'Helsinki-NLP/opus-mt-cs-fi', + ('cs', 'fr'): 'Helsinki-NLP/opus-mt-cs-fr', ('cs', 'sv'): 'Helsinki-NLP/opus-mt-cs-sv', + ('cs', 'uk'): 'Helsinki-NLP/opus-mt-cs-uk', ('csg', 'es'): 'Helsinki-NLP/opus-mt-csg-es', + ('csn', 'es'): 'Helsinki-NLP/opus-mt-csn-es', ('cus', 'en'): 'Helsinki-NLP/opus-mt-cus-en', + ('cy', 'en'): 'Helsinki-NLP/opus-mt-cy-en', ('da', 'de'): 'Helsinki-NLP/opus-mt-da-de', + ('da', 'en'): 'Helsinki-NLP/opus-mt-da-en', ('da', 'eo'): 'Helsinki-NLP/opus-mt-da-eo', + ('da', 'es'): 'Helsinki-NLP/opus-mt-da-es', ('da', 'fi'): 'Helsinki-NLP/opus-mt-da-fi', + ('da', 'fr'): 'Helsinki-NLP/opus-mt-da-fr', ('da', 'no'): 'Helsinki-NLP/opus-mt-da-no', + ('da', 'ru'): 'Helsinki-NLP/opus-mt-da-ru', ('de', 'ZH'): 'Helsinki-NLP/opus-mt-de-ZH', + ('de', 'af'): 'Helsinki-NLP/opus-mt-de-af', ('de', 'ar'): 'Helsinki-NLP/opus-mt-de-ar', + ('de', 'ase'): 'Helsinki-NLP/opus-mt-de-ase', ('de', 'bcl'): 'Helsinki-NLP/opus-mt-de-bcl', + ('de', 'bg'): 'Helsinki-NLP/opus-mt-de-bg', ('de', 'bi'): 'Helsinki-NLP/opus-mt-de-bi', + ('de', 'bzs'): 'Helsinki-NLP/opus-mt-de-bzs', ('de', 'ca'): 'Helsinki-NLP/opus-mt-de-ca', + ('de', 'crs'): 'Helsinki-NLP/opus-mt-de-crs', ('de', 'cs'): 'Helsinki-NLP/opus-mt-de-cs', + ('de', 'da'): 'Helsinki-NLP/opus-mt-de-da', ('de', 'de'): 'Helsinki-NLP/opus-mt-de-de', + ('de', 'ee'): 'Helsinki-NLP/opus-mt-de-ee', ('de', 'efi'): 'Helsinki-NLP/opus-mt-de-efi', + ('de', 'el'): 'Helsinki-NLP/opus-mt-de-el', ('de', 'en'): 'Helsinki-NLP/opus-mt-de-en', + ('de', 'eo'): 'Helsinki-NLP/opus-mt-de-eo', ('de', 'es'): 'Helsinki-NLP/opus-mt-de-es', + ('de', 'et'): 'Helsinki-NLP/opus-mt-de-et', ('de', 'eu'): 'Helsinki-NLP/opus-mt-de-eu', + ('de', 'fi'): 'Helsinki-NLP/opus-mt-de-fi', ('de', 'fj'): 'Helsinki-NLP/opus-mt-de-fj', + ('de', 'fr'): 'Helsinki-NLP/opus-mt-de-fr', ('de', 'gaa'): 'Helsinki-NLP/opus-mt-de-gaa', + ('de', 'gil'): 'Helsinki-NLP/opus-mt-de-gil', ('de', 'guw'): 'Helsinki-NLP/opus-mt-de-guw', + ('de', 'ha'): 'Helsinki-NLP/opus-mt-de-ha', ('de', 'he'): 'Helsinki-NLP/opus-mt-de-he', + ('de', 'hil'): 'Helsinki-NLP/opus-mt-de-hil', ('de', 'ho'): 'Helsinki-NLP/opus-mt-de-ho', + ('de', 'hr'): 'Helsinki-NLP/opus-mt-de-hr', ('de', 'ht'): 'Helsinki-NLP/opus-mt-de-ht', + ('de', 'hu'): 'Helsinki-NLP/opus-mt-de-hu', ('de', 'ig'): 'Helsinki-NLP/opus-mt-de-ig', + ('de', 'ilo'): 'Helsinki-NLP/opus-mt-de-ilo', ('de', 'is'): 'Helsinki-NLP/opus-mt-de-is', + ('de', 'iso'): 'Helsinki-NLP/opus-mt-de-iso', ('de', 'it'): 'Helsinki-NLP/opus-mt-de-it', + ('de', 'kg'): 'Helsinki-NLP/opus-mt-de-kg', ('de', 'ln'): 'Helsinki-NLP/opus-mt-de-ln', + ('de', 'loz'): 'Helsinki-NLP/opus-mt-de-loz', ('de', 'lt'): 'Helsinki-NLP/opus-mt-de-lt', + ('de', 'lua'): 'Helsinki-NLP/opus-mt-de-lua', ('de', 'ms'): 'Helsinki-NLP/opus-mt-de-ms', + ('de', 'mt'): 'Helsinki-NLP/opus-mt-de-mt', ('de', 'niu'): 'Helsinki-NLP/opus-mt-de-niu', + ('de', 'nl'): 'Helsinki-NLP/opus-mt-de-nl', ('de', 'no'): 'Helsinki-NLP/opus-mt-de-no', + ('de', 'nso'): 'Helsinki-NLP/opus-mt-de-nso', ('de', 'ny'): 'Helsinki-NLP/opus-mt-de-ny', + ('de', 'pag'): 'Helsinki-NLP/opus-mt-de-pag', ('de', 'pap'): 'Helsinki-NLP/opus-mt-de-pap', + ('de', 'pis'): 'Helsinki-NLP/opus-mt-de-pis', ('de', 'pl'): 'Helsinki-NLP/opus-mt-de-pl', + ('de', 'pon'): 'Helsinki-NLP/opus-mt-de-pon', ('de', 'tl'): 'Helsinki-NLP/opus-mt-de-tl', + ('de', 'uk'): 'Helsinki-NLP/opus-mt-de-uk', ('de', 'vi'): 'Helsinki-NLP/opus-mt-de-vi', + ('dra', 'en'): 'Helsinki-NLP/opus-mt-dra-en', ('ee', 'de'): 'Helsinki-NLP/opus-mt-ee-de', + ('ee', 'en'): 'Helsinki-NLP/opus-mt-ee-en', ('ee', 'es'): 'Helsinki-NLP/opus-mt-ee-es', + ('ee', 'fi'): 'Helsinki-NLP/opus-mt-ee-fi', ('ee', 'fr'): 'Helsinki-NLP/opus-mt-ee-fr', + ('ee', 'sv'): 'Helsinki-NLP/opus-mt-ee-sv', ('efi', 'de'): 'Helsinki-NLP/opus-mt-efi-de', + ('efi', 'en'): 'Helsinki-NLP/opus-mt-efi-en', ('efi', 'fi'): 'Helsinki-NLP/opus-mt-efi-fi', + ('efi', 'fr'): 'Helsinki-NLP/opus-mt-efi-fr', ('efi', 'sv'): 'Helsinki-NLP/opus-mt-efi-sv', + ('el', 'ar'): 'Helsinki-NLP/opus-mt-el-ar', ('el', 'eo'): 'Helsinki-NLP/opus-mt-el-eo', + ('el', 'fi'): 'Helsinki-NLP/opus-mt-el-fi', ('el', 'fr'): 'Helsinki-NLP/opus-mt-el-fr', + ('el', 'sv'): 'Helsinki-NLP/opus-mt-el-sv', ('en', 'aav'): 'Helsinki-NLP/opus-mt-en-aav', + ('en', 'af'): 'Helsinki-NLP/opus-mt-en-af', ('en', 'afa'): 'Helsinki-NLP/opus-mt-en-afa', + ('en', 'alv'): 'Helsinki-NLP/opus-mt-en-alv', ('en', 'ar'): 'Helsinki-NLP/opus-mt-en-ar', + ('en', 'az'): 'Helsinki-NLP/opus-mt-en-az', ('en', 'bat'): 'Helsinki-NLP/opus-mt-en-bat', + ('en', 'bcl'): 'Helsinki-NLP/opus-mt-en-bcl', ('en', 'bem'): 'Helsinki-NLP/opus-mt-en-bem', + ('en', 'ber'): 'Helsinki-NLP/opus-mt-en-ber', ('en', 'bg'): 'Helsinki-NLP/opus-mt-en-bg', + ('en', 'bi'): 'Helsinki-NLP/opus-mt-en-bi', ('en', 'bnt'): 'Helsinki-NLP/opus-mt-en-bnt', + ('en', 'bzs'): 'Helsinki-NLP/opus-mt-en-bzs', ('en', 'ca'): 'Helsinki-NLP/opus-mt-en-ca', + ('en', 'ceb'): 'Helsinki-NLP/opus-mt-en-ceb', ('en', 'cel'): 'Helsinki-NLP/opus-mt-en-cel', + ('en', 'chk'): 'Helsinki-NLP/opus-mt-en-chk', ('en', 'cpf'): 'Helsinki-NLP/opus-mt-en-cpf', + ('en', 'cpp'): 'Helsinki-NLP/opus-mt-en-cpp', ('en', 'crs'): 'Helsinki-NLP/opus-mt-en-crs', + ('en', 'cs'): 'Helsinki-NLP/opus-mt-en-cs', ('en', 'cus'): 'Helsinki-NLP/opus-mt-en-cus', + ('en', 'cy'): 'Helsinki-NLP/opus-mt-en-cy', ('en', 'da'): 'Helsinki-NLP/opus-mt-en-da', + ('en', 'de'): 'Helsinki-NLP/opus-mt-en-de', ('en', 'dra'): 'Helsinki-NLP/opus-mt-en-dra', + ('en', 'ee'): 'Helsinki-NLP/opus-mt-en-ee', ('en', 'efi'): 'Helsinki-NLP/opus-mt-en-efi', + ('en', 'el'): 'Helsinki-NLP/opus-mt-en-el', ('en', 'eo'): 'Helsinki-NLP/opus-mt-en-eo', + ('en', 'es'): 'Helsinki-NLP/opus-mt-en-es', ('en', 'et'): 'Helsinki-NLP/opus-mt-en-et', + ('en', 'eu'): 'Helsinki-NLP/opus-mt-en-eu', ('en', 'euq'): 'Helsinki-NLP/opus-mt-en-euq', + ('en', 'fi'): 'Helsinki-NLP/opus-mt-en-fi', ('en', 'fiu'): 'Helsinki-NLP/opus-mt-en-fiu', + ('en', 'fj'): 'Helsinki-NLP/opus-mt-en-fj', ('en', 'fr'): 'Helsinki-NLP/opus-mt-en-fr', + ('en', 'ga'): 'Helsinki-NLP/opus-mt-en-ga', ('en', 'gaa'): 'Helsinki-NLP/opus-mt-en-gaa', + ('en', 'gem'): 'Helsinki-NLP/opus-mt-en-gem', ('en', 'gil'): 'Helsinki-NLP/opus-mt-en-gil', + ('en', 'gl'): 'Helsinki-NLP/opus-mt-en-gl', ('en', 'gmq'): 'Helsinki-NLP/opus-mt-en-gmq', + ('en', 'gmw'): 'Helsinki-NLP/opus-mt-en-gmw', ('en', 'grk'): 'Helsinki-NLP/opus-mt-en-grk', + ('en', 'guw'): 'Helsinki-NLP/opus-mt-en-guw', ('en', 'gv'): 'Helsinki-NLP/opus-mt-en-gv', + ('en', 'ha'): 'Helsinki-NLP/opus-mt-en-ha', ('en', 'he'): 'Helsinki-NLP/opus-mt-en-he', + ('en', 'hi'): 'Helsinki-NLP/opus-mt-en-hi', ('en', 'hil'): 'Helsinki-NLP/opus-mt-en-hil', + ('en', 'ho'): 'Helsinki-NLP/opus-mt-en-ho', ('en', 'ht'): 'Helsinki-NLP/opus-mt-en-ht', + ('en', 'hu'): 'Helsinki-NLP/opus-mt-en-hu', ('en', 'hy'): 'Helsinki-NLP/opus-mt-en-hy', + ('en', 'id'): 'Helsinki-NLP/opus-mt-en-id', ('en', 'ig'): 'Helsinki-NLP/opus-mt-en-ig', + ('en', 'iir'): 'Helsinki-NLP/opus-mt-en-iir', ('en', 'ilo'): 'Helsinki-NLP/opus-mt-en-ilo', + ('en', 'inc'): 'Helsinki-NLP/opus-mt-en-inc', ('en', 'ine'): 'Helsinki-NLP/opus-mt-en-ine', + ('en', 'is'): 'Helsinki-NLP/opus-mt-en-is', ('en', 'iso'): 'Helsinki-NLP/opus-mt-en-iso', + ('en', 'it'): 'Helsinki-NLP/opus-mt-en-it', ('en', 'itc'): 'Helsinki-NLP/opus-mt-en-itc', + ('en', 'jap'): 'Helsinki-NLP/opus-mt-en-jap', ('en', 'kg'): 'Helsinki-NLP/opus-mt-en-kg', + ('en', 'kj'): 'Helsinki-NLP/opus-mt-en-kj', ('en', 'kqn'): 'Helsinki-NLP/opus-mt-en-kqn', + ('en', 'kwn'): 'Helsinki-NLP/opus-mt-en-kwn', ('en', 'kwy'): 'Helsinki-NLP/opus-mt-en-kwy', + ('en', 'lg'): 'Helsinki-NLP/opus-mt-en-lg', ('en', 'ln'): 'Helsinki-NLP/opus-mt-en-ln', + ('en', 'loz'): 'Helsinki-NLP/opus-mt-en-loz', ('en', 'lu'): 'Helsinki-NLP/opus-mt-en-lu', + ('en', 'lua'): 'Helsinki-NLP/opus-mt-en-lua', ('en', 'lue'): 'Helsinki-NLP/opus-mt-en-lue', + ('en', 'lun'): 'Helsinki-NLP/opus-mt-en-lun', ('en', 'luo'): 'Helsinki-NLP/opus-mt-en-luo', + ('en', 'lus'): 'Helsinki-NLP/opus-mt-en-lus', ('en', 'map'): 'Helsinki-NLP/opus-mt-en-map', + ('en', 'mfe'): 'Helsinki-NLP/opus-mt-en-mfe', ('en', 'mg'): 'Helsinki-NLP/opus-mt-en-mg', + ('en', 'mh'): 'Helsinki-NLP/opus-mt-en-mh', ('en', 'mk'): 'Helsinki-NLP/opus-mt-en-mk', + ('en', 'mkh'): 'Helsinki-NLP/opus-mt-en-mkh', ('en', 'ml'): 'Helsinki-NLP/opus-mt-en-ml', + ('en', 'mos'): 'Helsinki-NLP/opus-mt-en-mos', ('en', 'mr'): 'Helsinki-NLP/opus-mt-en-mr', + ('en', 'mt'): 'Helsinki-NLP/opus-mt-en-mt', ('en', 'mul'): 'Helsinki-NLP/opus-mt-en-mul', + ('en', 'ng'): 'Helsinki-NLP/opus-mt-en-ng', ('en', 'nic'): 'Helsinki-NLP/opus-mt-en-nic', + ('en', 'niu'): 'Helsinki-NLP/opus-mt-en-niu', ('en', 'nl'): 'Helsinki-NLP/opus-mt-en-nl', + ('en', 'nso'): 'Helsinki-NLP/opus-mt-en-nso', ('en', 'ny'): 'Helsinki-NLP/opus-mt-en-ny', + ('en', 'nyk'): 'Helsinki-NLP/opus-mt-en-nyk', ('en', 'om'): 'Helsinki-NLP/opus-mt-en-om', + ('en', 'pag'): 'Helsinki-NLP/opus-mt-en-pag', ('en', 'pap'): 'Helsinki-NLP/opus-mt-en-pap', + ('en', 'phi'): 'Helsinki-NLP/opus-mt-en-phi', ('en', 'pis'): 'Helsinki-NLP/opus-mt-en-pis', + ('en', 'pon'): 'Helsinki-NLP/opus-mt-en-pon', ('en', 'poz'): 'Helsinki-NLP/opus-mt-en-poz', + ('en', 'pqe'): 'Helsinki-NLP/opus-mt-en-pqe', ('en', 'pqw'): 'Helsinki-NLP/opus-mt-en-pqw', + ('en', 'rn'): 'Helsinki-NLP/opus-mt-en-rn', ('en', 'rnd'): 'Helsinki-NLP/opus-mt-en-rnd', + ('en', 'ro'): 'Helsinki-NLP/opus-mt-en-ro', ('en', 'roa'): 'Helsinki-NLP/opus-mt-en-roa', + ('en', 'ru'): 'Helsinki-NLP/opus-mt-en-ru', ('en', 'run'): 'Helsinki-NLP/opus-mt-en-run', + ('en', 'rw'): 'Helsinki-NLP/opus-mt-en-rw', ('en', 'sal'): 'Helsinki-NLP/opus-mt-en-sal', + ('en', 'sem'): 'Helsinki-NLP/opus-mt-en-sem', ('en', 'sg'): 'Helsinki-NLP/opus-mt-en-sg', + ('en', 'sit'): 'Helsinki-NLP/opus-mt-en-sit', ('en', 'sk'): 'Helsinki-NLP/opus-mt-en-sk', + ('en', 'sla'): 'Helsinki-NLP/opus-mt-en-sla', ('en', 'sm'): 'Helsinki-NLP/opus-mt-en-sm', + ('en', 'sn'): 'Helsinki-NLP/opus-mt-en-sn', ('en', 'sq'): 'Helsinki-NLP/opus-mt-en-sq', + ('en', 'ss'): 'Helsinki-NLP/opus-mt-en-ss', ('en', 'st'): 'Helsinki-NLP/opus-mt-en-st', + ('en', 'sv'): 'Helsinki-NLP/opus-mt-en-sv', ('en', 'sw'): 'Helsinki-NLP/opus-mt-en-sw', + ('en', 'swc'): 'Helsinki-NLP/opus-mt-en-swc', ('en', 'tdt'): 'Helsinki-NLP/opus-mt-en-tdt', + ('en', 'ti'): 'Helsinki-NLP/opus-mt-en-ti', ('en', 'tiv'): 'Helsinki-NLP/opus-mt-en-tiv', + ('en', 'tl'): 'Helsinki-NLP/opus-mt-en-tl', ('en', 'tll'): 'Helsinki-NLP/opus-mt-en-tll', + ('en', 'tn'): 'Helsinki-NLP/opus-mt-en-tn', ('en', 'to'): 'Helsinki-NLP/opus-mt-en-to', + ('en', 'toi'): 'Helsinki-NLP/opus-mt-en-toi', ('en', 'tpi'): 'Helsinki-NLP/opus-mt-en-tpi', + ('en', 'trk'): 'Helsinki-NLP/opus-mt-en-trk', ('en', 'ts'): 'Helsinki-NLP/opus-mt-en-ts', + ('en', 'tut'): 'Helsinki-NLP/opus-mt-en-tut', ('en', 'tvl'): 'Helsinki-NLP/opus-mt-en-tvl', + ('en', 'tw'): 'Helsinki-NLP/opus-mt-en-tw', ('en', 'ty'): 'Helsinki-NLP/opus-mt-en-ty', + ('en', 'uk'): 'Helsinki-NLP/opus-mt-en-uk', ('en', 'umb'): 'Helsinki-NLP/opus-mt-en-umb', + ('en', 'ur'): 'Helsinki-NLP/opus-mt-en-ur', ('en', 'urj'): 'Helsinki-NLP/opus-mt-en-urj', + ('en', 'vi'): 'Helsinki-NLP/opus-mt-en-vi', ('en', 'xh'): 'Helsinki-NLP/opus-mt-en-xh', + ('en', 'zh'): 'Helsinki-NLP/opus-mt-en-zh', ('en', 'zle'): 'Helsinki-NLP/opus-mt-en-zle', + ('en', 'zls'): 'Helsinki-NLP/opus-mt-en-zls', ('en', 'zlw'): 'Helsinki-NLP/opus-mt-en-zlw', + ('en_el_es_fi', 'en_el_es_fi'): 'Helsinki-NLP/opus-mt-en_el_es_fi-en_el_es_fi', + ('eo', 'af'): 'Helsinki-NLP/opus-mt-eo-af', ('eo', 'bg'): 'Helsinki-NLP/opus-mt-eo-bg', + ('eo', 'cs'): 'Helsinki-NLP/opus-mt-eo-cs', ('eo', 'da'): 'Helsinki-NLP/opus-mt-eo-da', + ('eo', 'de'): 'Helsinki-NLP/opus-mt-eo-de', ('eo', 'el'): 'Helsinki-NLP/opus-mt-eo-el', + ('eo', 'en'): 'Helsinki-NLP/opus-mt-eo-en', ('eo', 'es'): 'Helsinki-NLP/opus-mt-eo-es', + ('eo', 'fi'): 'Helsinki-NLP/opus-mt-eo-fi', ('eo', 'fr'): 'Helsinki-NLP/opus-mt-eo-fr', + ('eo', 'he'): 'Helsinki-NLP/opus-mt-eo-he', ('eo', 'hu'): 'Helsinki-NLP/opus-mt-eo-hu', + ('eo', 'it'): 'Helsinki-NLP/opus-mt-eo-it', ('eo', 'nl'): 'Helsinki-NLP/opus-mt-eo-nl', + ('eo', 'pl'): 'Helsinki-NLP/opus-mt-eo-pl', ('eo', 'pt'): 'Helsinki-NLP/opus-mt-eo-pt', + ('eo', 'ro'): 'Helsinki-NLP/opus-mt-eo-ro', ('eo', 'ru'): 'Helsinki-NLP/opus-mt-eo-ru', + ('eo', 'sh'): 'Helsinki-NLP/opus-mt-eo-sh', ('eo', 'sv'): 'Helsinki-NLP/opus-mt-eo-sv', + ('es', 'NORWAY'): 'Helsinki-NLP/opus-mt-es-NORWAY', ('es', 'aed'): 'Helsinki-NLP/opus-mt-es-aed', + ('es', 'af'): 'Helsinki-NLP/opus-mt-es-af', ('es', 'ar'): 'Helsinki-NLP/opus-mt-es-ar', + ('es', 'ase'): 'Helsinki-NLP/opus-mt-es-ase', ('es', 'bcl'): 'Helsinki-NLP/opus-mt-es-bcl', + ('es', 'ber'): 'Helsinki-NLP/opus-mt-es-ber', ('es', 'bg'): 'Helsinki-NLP/opus-mt-es-bg', + ('es', 'bi'): 'Helsinki-NLP/opus-mt-es-bi', ('es', 'bzs'): 'Helsinki-NLP/opus-mt-es-bzs', + ('es', 'ca'): 'Helsinki-NLP/opus-mt-es-ca', ('es', 'ceb'): 'Helsinki-NLP/opus-mt-es-ceb', + ('es', 'crs'): 'Helsinki-NLP/opus-mt-es-crs', ('es', 'cs'): 'Helsinki-NLP/opus-mt-es-cs', + ('es', 'csg'): 'Helsinki-NLP/opus-mt-es-csg', ('es', 'csn'): 'Helsinki-NLP/opus-mt-es-csn', + ('es', 'da'): 'Helsinki-NLP/opus-mt-es-da', ('es', 'de'): 'Helsinki-NLP/opus-mt-es-de', + ('es', 'ee'): 'Helsinki-NLP/opus-mt-es-ee', ('es', 'efi'): 'Helsinki-NLP/opus-mt-es-efi', + ('es', 'el'): 'Helsinki-NLP/opus-mt-es-el', ('es', 'en'): 'Helsinki-NLP/opus-mt-es-en', + ('es', 'eo'): 'Helsinki-NLP/opus-mt-es-eo', ('es', 'es'): 'Helsinki-NLP/opus-mt-es-es', + ('es', 'et'): 'Helsinki-NLP/opus-mt-es-et', ('es', 'eu'): 'Helsinki-NLP/opus-mt-es-eu', + ('es', 'fi'): 'Helsinki-NLP/opus-mt-es-fi', ('es', 'fj'): 'Helsinki-NLP/opus-mt-es-fj', + ('es', 'fr'): 'Helsinki-NLP/opus-mt-es-fr', ('es', 'gaa'): 'Helsinki-NLP/opus-mt-es-gaa', + ('es', 'gil'): 'Helsinki-NLP/opus-mt-es-gil', ('es', 'gl'): 'Helsinki-NLP/opus-mt-es-gl', + ('es', 'guw'): 'Helsinki-NLP/opus-mt-es-guw', ('es', 'ha'): 'Helsinki-NLP/opus-mt-es-ha', + ('es', 'he'): 'Helsinki-NLP/opus-mt-es-he', ('es', 'hil'): 'Helsinki-NLP/opus-mt-es-hil', + ('es', 'ho'): 'Helsinki-NLP/opus-mt-es-ho', ('es', 'hr'): 'Helsinki-NLP/opus-mt-es-hr', + ('es', 'ht'): 'Helsinki-NLP/opus-mt-es-ht', ('es', 'id'): 'Helsinki-NLP/opus-mt-es-id', + ('es', 'ig'): 'Helsinki-NLP/opus-mt-es-ig', ('es', 'ilo'): 'Helsinki-NLP/opus-mt-es-ilo', + ('es', 'is'): 'Helsinki-NLP/opus-mt-es-is', ('es', 'iso'): 'Helsinki-NLP/opus-mt-es-iso', + ('es', 'it'): 'Helsinki-NLP/opus-mt-es-it', ('es', 'kg'): 'Helsinki-NLP/opus-mt-es-kg', + ('es', 'ln'): 'Helsinki-NLP/opus-mt-es-ln', ('es', 'loz'): 'Helsinki-NLP/opus-mt-es-loz', + ('es', 'lt'): 'Helsinki-NLP/opus-mt-es-lt', ('es', 'lua'): 'Helsinki-NLP/opus-mt-es-lua', + ('es', 'lus'): 'Helsinki-NLP/opus-mt-es-lus', ('es', 'mfs'): 'Helsinki-NLP/opus-mt-es-mfs', + ('es', 'mk'): 'Helsinki-NLP/opus-mt-es-mk', ('es', 'mt'): 'Helsinki-NLP/opus-mt-es-mt', + ('es', 'niu'): 'Helsinki-NLP/opus-mt-es-niu', ('es', 'nl'): 'Helsinki-NLP/opus-mt-es-nl', + ('es', 'no'): 'Helsinki-NLP/opus-mt-es-no', ('es', 'nso'): 'Helsinki-NLP/opus-mt-es-nso', + ('es', 'ny'): 'Helsinki-NLP/opus-mt-es-ny', ('es', 'pag'): 'Helsinki-NLP/opus-mt-es-pag', + ('es', 'pap'): 'Helsinki-NLP/opus-mt-es-pap', ('es', 'pis'): 'Helsinki-NLP/opus-mt-es-pis', + ('es', 'pl'): 'Helsinki-NLP/opus-mt-es-pl', ('es', 'pon'): 'Helsinki-NLP/opus-mt-es-pon', + ('es', 'prl'): 'Helsinki-NLP/opus-mt-es-prl', ('es', 'rn'): 'Helsinki-NLP/opus-mt-es-rn', + ('es', 'ro'): 'Helsinki-NLP/opus-mt-es-ro', ('es', 'ru'): 'Helsinki-NLP/opus-mt-es-ru', + ('es', 'rw'): 'Helsinki-NLP/opus-mt-es-rw', ('es', 'sg'): 'Helsinki-NLP/opus-mt-es-sg', + ('es', 'sl'): 'Helsinki-NLP/opus-mt-es-sl', ('es', 'sm'): 'Helsinki-NLP/opus-mt-es-sm', + ('es', 'sn'): 'Helsinki-NLP/opus-mt-es-sn', ('es', 'srn'): 'Helsinki-NLP/opus-mt-es-srn', + ('es', 'st'): 'Helsinki-NLP/opus-mt-es-st', ('es', 'swc'): 'Helsinki-NLP/opus-mt-es-swc', + ('es', 'tl'): 'Helsinki-NLP/opus-mt-es-tl', ('es', 'tll'): 'Helsinki-NLP/opus-mt-es-tll', + ('es', 'tn'): 'Helsinki-NLP/opus-mt-es-tn', ('es', 'to'): 'Helsinki-NLP/opus-mt-es-to', + ('es', 'tpi'): 'Helsinki-NLP/opus-mt-es-tpi', ('es', 'tvl'): 'Helsinki-NLP/opus-mt-es-tvl', + ('es', 'tw'): 'Helsinki-NLP/opus-mt-es-tw', ('es', 'ty'): 'Helsinki-NLP/opus-mt-es-ty', + ('es', 'tzo'): 'Helsinki-NLP/opus-mt-es-tzo', ('es', 'uk'): 'Helsinki-NLP/opus-mt-es-uk', + ('es', 've'): 'Helsinki-NLP/opus-mt-es-ve', ('es', 'vi'): 'Helsinki-NLP/opus-mt-es-vi', + ('es', 'war'): 'Helsinki-NLP/opus-mt-es-war', ('es', 'wls'): 'Helsinki-NLP/opus-mt-es-wls', + ('es', 'xh'): 'Helsinki-NLP/opus-mt-es-xh', ('es', 'yo'): 'Helsinki-NLP/opus-mt-es-yo', + ('es', 'yua'): 'Helsinki-NLP/opus-mt-es-yua', ('es', 'zai'): 'Helsinki-NLP/opus-mt-es-zai', + ('et', 'de'): 'Helsinki-NLP/opus-mt-et-de', ('et', 'en'): 'Helsinki-NLP/opus-mt-et-en', + ('et', 'es'): 'Helsinki-NLP/opus-mt-et-es', ('et', 'fi'): 'Helsinki-NLP/opus-mt-et-fi', + ('et', 'fr'): 'Helsinki-NLP/opus-mt-et-fr', ('et', 'ru'): 'Helsinki-NLP/opus-mt-et-ru', + ('et', 'sv'): 'Helsinki-NLP/opus-mt-et-sv', ('eu', 'de'): 'Helsinki-NLP/opus-mt-eu-de', + ('eu', 'en'): 'Helsinki-NLP/opus-mt-eu-en', ('eu', 'es'): 'Helsinki-NLP/opus-mt-eu-es', + ('eu', 'ru'): 'Helsinki-NLP/opus-mt-eu-ru', ('euq', 'en'): 'Helsinki-NLP/opus-mt-euq-en', + ('fi', 'NORWAY'): 'Helsinki-NLP/opus-mt-fi-NORWAY', ('fi', 'ZH'): 'Helsinki-NLP/opus-mt-fi-ZH', + ('fi', 'af'): 'Helsinki-NLP/opus-mt-fi-af', ('fi', 'bcl'): 'Helsinki-NLP/opus-mt-fi-bcl', + ('fi', 'bem'): 'Helsinki-NLP/opus-mt-fi-bem', ('fi', 'bg'): 'Helsinki-NLP/opus-mt-fi-bg', + ('fi', 'bzs'): 'Helsinki-NLP/opus-mt-fi-bzs', ('fi', 'ceb'): 'Helsinki-NLP/opus-mt-fi-ceb', + ('fi', 'crs'): 'Helsinki-NLP/opus-mt-fi-crs', ('fi', 'cs'): 'Helsinki-NLP/opus-mt-fi-cs', + ('fi', 'de'): 'Helsinki-NLP/opus-mt-fi-de', ('fi', 'ee'): 'Helsinki-NLP/opus-mt-fi-ee', + ('fi', 'efi'): 'Helsinki-NLP/opus-mt-fi-efi', ('fi', 'el'): 'Helsinki-NLP/opus-mt-fi-el', + ('fi', 'en'): 'Helsinki-NLP/opus-mt-fi-en', ('fi', 'eo'): 'Helsinki-NLP/opus-mt-fi-eo', + ('fi', 'es'): 'Helsinki-NLP/opus-mt-fi-es', ('fi', 'et'): 'Helsinki-NLP/opus-mt-fi-et', + ('fi', 'fi'): 'Helsinki-NLP/opus-mt-fi-fi', ('fi', 'fj'): 'Helsinki-NLP/opus-mt-fi-fj', + ('fi', 'fr'): 'Helsinki-NLP/opus-mt-fi-fr', ('fi', 'fse'): 'Helsinki-NLP/opus-mt-fi-fse', + ('fi', 'gaa'): 'Helsinki-NLP/opus-mt-fi-gaa', ('fi', 'gil'): 'Helsinki-NLP/opus-mt-fi-gil', + ('fi', 'guw'): 'Helsinki-NLP/opus-mt-fi-guw', ('fi', 'ha'): 'Helsinki-NLP/opus-mt-fi-ha', + ('fi', 'he'): 'Helsinki-NLP/opus-mt-fi-he', ('fi', 'hil'): 'Helsinki-NLP/opus-mt-fi-hil', + ('fi', 'ho'): 'Helsinki-NLP/opus-mt-fi-ho', ('fi', 'hr'): 'Helsinki-NLP/opus-mt-fi-hr', + ('fi', 'ht'): 'Helsinki-NLP/opus-mt-fi-ht', ('fi', 'hu'): 'Helsinki-NLP/opus-mt-fi-hu', + ('fi', 'id'): 'Helsinki-NLP/opus-mt-fi-id', ('fi', 'ig'): 'Helsinki-NLP/opus-mt-fi-ig', + ('fi', 'ilo'): 'Helsinki-NLP/opus-mt-fi-ilo', ('fi', 'is'): 'Helsinki-NLP/opus-mt-fi-is', + ('fi', 'iso'): 'Helsinki-NLP/opus-mt-fi-iso', ('fi', 'it'): 'Helsinki-NLP/opus-mt-fi-it', + ('fi', 'kg'): 'Helsinki-NLP/opus-mt-fi-kg', ('fi', 'kqn'): 'Helsinki-NLP/opus-mt-fi-kqn', + ('fi', 'lg'): 'Helsinki-NLP/opus-mt-fi-lg', ('fi', 'ln'): 'Helsinki-NLP/opus-mt-fi-ln', + ('fi', 'lu'): 'Helsinki-NLP/opus-mt-fi-lu', ('fi', 'lua'): 'Helsinki-NLP/opus-mt-fi-lua', + ('fi', 'lue'): 'Helsinki-NLP/opus-mt-fi-lue', ('fi', 'lus'): 'Helsinki-NLP/opus-mt-fi-lus', + ('fi', 'lv'): 'Helsinki-NLP/opus-mt-fi-lv', ('fi', 'mfe'): 'Helsinki-NLP/opus-mt-fi-mfe', + ('fi', 'mg'): 'Helsinki-NLP/opus-mt-fi-mg', ('fi', 'mh'): 'Helsinki-NLP/opus-mt-fi-mh', + ('fi', 'mk'): 'Helsinki-NLP/opus-mt-fi-mk', ('fi', 'mos'): 'Helsinki-NLP/opus-mt-fi-mos', + ('fi', 'mt'): 'Helsinki-NLP/opus-mt-fi-mt', ('fi', 'niu'): 'Helsinki-NLP/opus-mt-fi-niu', + ('fi', 'nl'): 'Helsinki-NLP/opus-mt-fi-nl', ('fi', 'no'): 'Helsinki-NLP/opus-mt-fi-no', + ('fi', 'nso'): 'Helsinki-NLP/opus-mt-fi-nso', ('fi', 'ny'): 'Helsinki-NLP/opus-mt-fi-ny', + ('fi', 'pag'): 'Helsinki-NLP/opus-mt-fi-pag', ('fi', 'pap'): 'Helsinki-NLP/opus-mt-fi-pap', + ('fi', 'pis'): 'Helsinki-NLP/opus-mt-fi-pis', ('fi', 'pon'): 'Helsinki-NLP/opus-mt-fi-pon', + ('fi', 'ro'): 'Helsinki-NLP/opus-mt-fi-ro', ('fi', 'ru'): 'Helsinki-NLP/opus-mt-fi-ru', + ('fi', 'run'): 'Helsinki-NLP/opus-mt-fi-run', ('fi', 'rw'): 'Helsinki-NLP/opus-mt-fi-rw', + ('fi', 'sg'): 'Helsinki-NLP/opus-mt-fi-sg', ('fi', 'sk'): 'Helsinki-NLP/opus-mt-fi-sk', + ('fi', 'sl'): 'Helsinki-NLP/opus-mt-fi-sl', ('fi', 'sm'): 'Helsinki-NLP/opus-mt-fi-sm', + ('fi', 'sn'): 'Helsinki-NLP/opus-mt-fi-sn', ('fi', 'sq'): 'Helsinki-NLP/opus-mt-fi-sq', + ('fi', 'srn'): 'Helsinki-NLP/opus-mt-fi-srn', ('fi', 'st'): 'Helsinki-NLP/opus-mt-fi-st', + ('fi', 'sv'): 'Helsinki-NLP/opus-mt-fi-sv', ('fi', 'sw'): 'Helsinki-NLP/opus-mt-fi-sw', + ('fi', 'swc'): 'Helsinki-NLP/opus-mt-fi-swc', ('fi', 'tiv'): 'Helsinki-NLP/opus-mt-fi-tiv', + ('fi', 'tll'): 'Helsinki-NLP/opus-mt-fi-tll', ('fi', 'tn'): 'Helsinki-NLP/opus-mt-fi-tn', + ('fi', 'to'): 'Helsinki-NLP/opus-mt-fi-to', ('fi', 'toi'): 'Helsinki-NLP/opus-mt-fi-toi', + ('fi', 'tpi'): 'Helsinki-NLP/opus-mt-fi-tpi', ('fi', 'tr'): 'Helsinki-NLP/opus-mt-fi-tr', + ('fi', 'ts'): 'Helsinki-NLP/opus-mt-fi-ts', ('fi', 'tvl'): 'Helsinki-NLP/opus-mt-fi-tvl', + ('fi', 'tw'): 'Helsinki-NLP/opus-mt-fi-tw', ('fi', 'ty'): 'Helsinki-NLP/opus-mt-fi-ty', + ('fi', 'uk'): 'Helsinki-NLP/opus-mt-fi-uk', ('fi', 've'): 'Helsinki-NLP/opus-mt-fi-ve', + ('fi', 'war'): 'Helsinki-NLP/opus-mt-fi-war', ('fi', 'wls'): 'Helsinki-NLP/opus-mt-fi-wls', + ('fi', 'xh'): 'Helsinki-NLP/opus-mt-fi-xh', ('fi', 'yap'): 'Helsinki-NLP/opus-mt-fi-yap', + ('fi', 'yo'): 'Helsinki-NLP/opus-mt-fi-yo', ('fi', 'zne'): 'Helsinki-NLP/opus-mt-fi-zne', + ('fi_nb_no_nn_ru_sv_en', 'SAMI'): 'Helsinki-NLP/opus-mt-fi_nb_no_nn_ru_sv_en-SAMI', + ('fiu', 'en'): 'Helsinki-NLP/opus-mt-fiu-en', ('fiu', 'fiu'): 'Helsinki-NLP/opus-mt-fiu-fiu', + ('fj', 'en'): 'Helsinki-NLP/opus-mt-fj-en', ('fj', 'fr'): 'Helsinki-NLP/opus-mt-fj-fr', + ('fr', 'af'): 'Helsinki-NLP/opus-mt-fr-af', ('fr', 'ar'): 'Helsinki-NLP/opus-mt-fr-ar', + ('fr', 'ase'): 'Helsinki-NLP/opus-mt-fr-ase', ('fr', 'bcl'): 'Helsinki-NLP/opus-mt-fr-bcl', + ('fr', 'bem'): 'Helsinki-NLP/opus-mt-fr-bem', ('fr', 'ber'): 'Helsinki-NLP/opus-mt-fr-ber', + ('fr', 'bg'): 'Helsinki-NLP/opus-mt-fr-bg', ('fr', 'bi'): 'Helsinki-NLP/opus-mt-fr-bi', + ('fr', 'bzs'): 'Helsinki-NLP/opus-mt-fr-bzs', ('fr', 'ca'): 'Helsinki-NLP/opus-mt-fr-ca', + ('fr', 'ceb'): 'Helsinki-NLP/opus-mt-fr-ceb', ('fr', 'crs'): 'Helsinki-NLP/opus-mt-fr-crs', + ('fr', 'de'): 'Helsinki-NLP/opus-mt-fr-de', ('fr', 'ee'): 'Helsinki-NLP/opus-mt-fr-ee', + ('fr', 'efi'): 'Helsinki-NLP/opus-mt-fr-efi', ('fr', 'el'): 'Helsinki-NLP/opus-mt-fr-el', + ('fr', 'en'): 'Helsinki-NLP/opus-mt-fr-en', ('fr', 'eo'): 'Helsinki-NLP/opus-mt-fr-eo', + ('fr', 'es'): 'Helsinki-NLP/opus-mt-fr-es', ('fr', 'fj'): 'Helsinki-NLP/opus-mt-fr-fj', + ('fr', 'gaa'): 'Helsinki-NLP/opus-mt-fr-gaa', ('fr', 'gil'): 'Helsinki-NLP/opus-mt-fr-gil', + ('fr', 'guw'): 'Helsinki-NLP/opus-mt-fr-guw', ('fr', 'ha'): 'Helsinki-NLP/opus-mt-fr-ha', + ('fr', 'he'): 'Helsinki-NLP/opus-mt-fr-he', ('fr', 'hil'): 'Helsinki-NLP/opus-mt-fr-hil', + ('fr', 'ho'): 'Helsinki-NLP/opus-mt-fr-ho', ('fr', 'hr'): 'Helsinki-NLP/opus-mt-fr-hr', + ('fr', 'ht'): 'Helsinki-NLP/opus-mt-fr-ht', ('fr', 'hu'): 'Helsinki-NLP/opus-mt-fr-hu', + ('fr', 'id'): 'Helsinki-NLP/opus-mt-fr-id', ('fr', 'ig'): 'Helsinki-NLP/opus-mt-fr-ig', + ('fr', 'ilo'): 'Helsinki-NLP/opus-mt-fr-ilo', ('fr', 'iso'): 'Helsinki-NLP/opus-mt-fr-iso', + ('fr', 'kg'): 'Helsinki-NLP/opus-mt-fr-kg', ('fr', 'kqn'): 'Helsinki-NLP/opus-mt-fr-kqn', + ('fr', 'kwy'): 'Helsinki-NLP/opus-mt-fr-kwy', ('fr', 'lg'): 'Helsinki-NLP/opus-mt-fr-lg', + ('fr', 'ln'): 'Helsinki-NLP/opus-mt-fr-ln', ('fr', 'loz'): 'Helsinki-NLP/opus-mt-fr-loz', + ('fr', 'lu'): 'Helsinki-NLP/opus-mt-fr-lu', ('fr', 'lua'): 'Helsinki-NLP/opus-mt-fr-lua', + ('fr', 'lue'): 'Helsinki-NLP/opus-mt-fr-lue', ('fr', 'lus'): 'Helsinki-NLP/opus-mt-fr-lus', + ('fr', 'mfe'): 'Helsinki-NLP/opus-mt-fr-mfe', ('fr', 'mh'): 'Helsinki-NLP/opus-mt-fr-mh', + ('fr', 'mos'): 'Helsinki-NLP/opus-mt-fr-mos', ('fr', 'ms'): 'Helsinki-NLP/opus-mt-fr-ms', + ('fr', 'mt'): 'Helsinki-NLP/opus-mt-fr-mt', ('fr', 'niu'): 'Helsinki-NLP/opus-mt-fr-niu', + ('fr', 'no'): 'Helsinki-NLP/opus-mt-fr-no', ('fr', 'nso'): 'Helsinki-NLP/opus-mt-fr-nso', + ('fr', 'ny'): 'Helsinki-NLP/opus-mt-fr-ny', ('fr', 'pag'): 'Helsinki-NLP/opus-mt-fr-pag', + ('fr', 'pap'): 'Helsinki-NLP/opus-mt-fr-pap', ('fr', 'pis'): 'Helsinki-NLP/opus-mt-fr-pis', + ('fr', 'pl'): 'Helsinki-NLP/opus-mt-fr-pl', ('fr', 'pon'): 'Helsinki-NLP/opus-mt-fr-pon', + ('fr', 'rnd'): 'Helsinki-NLP/opus-mt-fr-rnd', ('fr', 'ro'): 'Helsinki-NLP/opus-mt-fr-ro', + ('fr', 'ru'): 'Helsinki-NLP/opus-mt-fr-ru', ('fr', 'run'): 'Helsinki-NLP/opus-mt-fr-run', + ('fr', 'rw'): 'Helsinki-NLP/opus-mt-fr-rw', ('fr', 'sg'): 'Helsinki-NLP/opus-mt-fr-sg', + ('fr', 'sk'): 'Helsinki-NLP/opus-mt-fr-sk', ('fr', 'sl'): 'Helsinki-NLP/opus-mt-fr-sl', + ('fr', 'sm'): 'Helsinki-NLP/opus-mt-fr-sm', ('fr', 'sn'): 'Helsinki-NLP/opus-mt-fr-sn', + ('fr', 'srn'): 'Helsinki-NLP/opus-mt-fr-srn', ('fr', 'st'): 'Helsinki-NLP/opus-mt-fr-st', + ('fr', 'sv'): 'Helsinki-NLP/opus-mt-fr-sv', ('fr', 'swc'): 'Helsinki-NLP/opus-mt-fr-swc', + ('fr', 'tiv'): 'Helsinki-NLP/opus-mt-fr-tiv', ('fr', 'tl'): 'Helsinki-NLP/opus-mt-fr-tl', + ('fr', 'tll'): 'Helsinki-NLP/opus-mt-fr-tll', ('fr', 'tn'): 'Helsinki-NLP/opus-mt-fr-tn', + ('fr', 'to'): 'Helsinki-NLP/opus-mt-fr-to', ('fr', 'tpi'): 'Helsinki-NLP/opus-mt-fr-tpi', + ('fr', 'ts'): 'Helsinki-NLP/opus-mt-fr-ts', ('fr', 'tum'): 'Helsinki-NLP/opus-mt-fr-tum', + ('fr', 'tvl'): 'Helsinki-NLP/opus-mt-fr-tvl', ('fr', 'tw'): 'Helsinki-NLP/opus-mt-fr-tw', + ('fr', 'ty'): 'Helsinki-NLP/opus-mt-fr-ty', ('fr', 'uk'): 'Helsinki-NLP/opus-mt-fr-uk', + ('fr', 've'): 'Helsinki-NLP/opus-mt-fr-ve', ('fr', 'vi'): 'Helsinki-NLP/opus-mt-fr-vi', + ('fr', 'war'): 'Helsinki-NLP/opus-mt-fr-war', ('fr', 'wls'): 'Helsinki-NLP/opus-mt-fr-wls', + ('fr', 'xh'): 'Helsinki-NLP/opus-mt-fr-xh', ('fr', 'yap'): 'Helsinki-NLP/opus-mt-fr-yap', + ('fr', 'yo'): 'Helsinki-NLP/opus-mt-fr-yo', ('fr', 'zne'): 'Helsinki-NLP/opus-mt-fr-zne', + ('fse', 'fi'): 'Helsinki-NLP/opus-mt-fse-fi', ('ga', 'en'): 'Helsinki-NLP/opus-mt-ga-en', + ('gaa', 'de'): 'Helsinki-NLP/opus-mt-gaa-de', ('gaa', 'en'): 'Helsinki-NLP/opus-mt-gaa-en', + ('gaa', 'es'): 'Helsinki-NLP/opus-mt-gaa-es', ('gaa', 'fi'): 'Helsinki-NLP/opus-mt-gaa-fi', + ('gaa', 'fr'): 'Helsinki-NLP/opus-mt-gaa-fr', ('gaa', 'sv'): 'Helsinki-NLP/opus-mt-gaa-sv', + ('gem', 'en'): 'Helsinki-NLP/opus-mt-gem-en', ('gem', 'gem'): 'Helsinki-NLP/opus-mt-gem-gem', + ('gil', 'en'): 'Helsinki-NLP/opus-mt-gil-en', ('gil', 'es'): 'Helsinki-NLP/opus-mt-gil-es', + ('gil', 'fi'): 'Helsinki-NLP/opus-mt-gil-fi', ('gil', 'fr'): 'Helsinki-NLP/opus-mt-gil-fr', + ('gil', 'sv'): 'Helsinki-NLP/opus-mt-gil-sv', ('gl', 'en'): 'Helsinki-NLP/opus-mt-gl-en', + ('gl', 'es'): 'Helsinki-NLP/opus-mt-gl-es', ('gl', 'pt'): 'Helsinki-NLP/opus-mt-gl-pt', + ('gmq', 'en'): 'Helsinki-NLP/opus-mt-gmq-en', ('gmq', 'gmq'): 'Helsinki-NLP/opus-mt-gmq-gmq', + ('gmw', 'en'): 'Helsinki-NLP/opus-mt-gmw-en', ('gmw', 'gmw'): 'Helsinki-NLP/opus-mt-gmw-gmw', + ('grk', 'en'): 'Helsinki-NLP/opus-mt-grk-en', ('guw', 'de'): 'Helsinki-NLP/opus-mt-guw-de', + ('guw', 'en'): 'Helsinki-NLP/opus-mt-guw-en', ('guw', 'es'): 'Helsinki-NLP/opus-mt-guw-es', + ('guw', 'fi'): 'Helsinki-NLP/opus-mt-guw-fi', ('guw', 'fr'): 'Helsinki-NLP/opus-mt-guw-fr', + ('guw', 'sv'): 'Helsinki-NLP/opus-mt-guw-sv', ('gv', 'en'): 'Helsinki-NLP/opus-mt-gv-en', + ('ha', 'en'): 'Helsinki-NLP/opus-mt-ha-en', ('ha', 'es'): 'Helsinki-NLP/opus-mt-ha-es', + ('ha', 'fi'): 'Helsinki-NLP/opus-mt-ha-fi', ('ha', 'fr'): 'Helsinki-NLP/opus-mt-ha-fr', + ('ha', 'sv'): 'Helsinki-NLP/opus-mt-ha-sv', ('he', 'ar'): 'Helsinki-NLP/opus-mt-he-ar', + ('he', 'de'): 'Helsinki-NLP/opus-mt-he-de', ('he', 'eo'): 'Helsinki-NLP/opus-mt-he-eo', + ('he', 'es'): 'Helsinki-NLP/opus-mt-he-es', ('he', 'fi'): 'Helsinki-NLP/opus-mt-he-fi', + ('he', 'fr'): 'Helsinki-NLP/opus-mt-he-fr', ('he', 'it'): 'Helsinki-NLP/opus-mt-he-it', + ('he', 'ru'): 'Helsinki-NLP/opus-mt-he-ru', ('he', 'sv'): 'Helsinki-NLP/opus-mt-he-sv', + ('he', 'uk'): 'Helsinki-NLP/opus-mt-he-uk', ('hi', 'en'): 'Helsinki-NLP/opus-mt-hi-en', + ('hi', 'ur'): 'Helsinki-NLP/opus-mt-hi-ur', ('hil', 'de'): 'Helsinki-NLP/opus-mt-hil-de', + ('hil', 'en'): 'Helsinki-NLP/opus-mt-hil-en', ('hil', 'fi'): 'Helsinki-NLP/opus-mt-hil-fi', + ('ho', 'en'): 'Helsinki-NLP/opus-mt-ho-en', ('hr', 'es'): 'Helsinki-NLP/opus-mt-hr-es', + ('hr', 'fi'): 'Helsinki-NLP/opus-mt-hr-fi', ('hr', 'fr'): 'Helsinki-NLP/opus-mt-hr-fr', + ('hr', 'sv'): 'Helsinki-NLP/opus-mt-hr-sv', ('ht', 'en'): 'Helsinki-NLP/opus-mt-ht-en', + ('ht', 'es'): 'Helsinki-NLP/opus-mt-ht-es', ('ht', 'fi'): 'Helsinki-NLP/opus-mt-ht-fi', + ('ht', 'fr'): 'Helsinki-NLP/opus-mt-ht-fr', ('ht', 'sv'): 'Helsinki-NLP/opus-mt-ht-sv', + ('hu', 'de'): 'Helsinki-NLP/opus-mt-hu-de', ('hu', 'en'): 'Helsinki-NLP/opus-mt-hu-en', + ('hu', 'eo'): 'Helsinki-NLP/opus-mt-hu-eo', ('hu', 'fi'): 'Helsinki-NLP/opus-mt-hu-fi', + ('hu', 'fr'): 'Helsinki-NLP/opus-mt-hu-fr', ('hu', 'sv'): 'Helsinki-NLP/opus-mt-hu-sv', + ('hu', 'uk'): 'Helsinki-NLP/opus-mt-hu-uk', ('hy', 'en'): 'Helsinki-NLP/opus-mt-hy-en', + ('hy', 'ru'): 'Helsinki-NLP/opus-mt-hy-ru', ('id', 'en'): 'Helsinki-NLP/opus-mt-id-en', + ('id', 'es'): 'Helsinki-NLP/opus-mt-id-es', ('id', 'fi'): 'Helsinki-NLP/opus-mt-id-fi', + ('id', 'fr'): 'Helsinki-NLP/opus-mt-id-fr', ('id', 'sv'): 'Helsinki-NLP/opus-mt-id-sv', + ('ig', 'de'): 'Helsinki-NLP/opus-mt-ig-de', ('ig', 'en'): 'Helsinki-NLP/opus-mt-ig-en', + ('ig', 'es'): 'Helsinki-NLP/opus-mt-ig-es', ('ig', 'fi'): 'Helsinki-NLP/opus-mt-ig-fi', + ('ig', 'fr'): 'Helsinki-NLP/opus-mt-ig-fr', ('ig', 'sv'): 'Helsinki-NLP/opus-mt-ig-sv', + ('iir', 'en'): 'Helsinki-NLP/opus-mt-iir-en', ('iir', 'iir'): 'Helsinki-NLP/opus-mt-iir-iir', + ('ilo', 'de'): 'Helsinki-NLP/opus-mt-ilo-de', ('ilo', 'en'): 'Helsinki-NLP/opus-mt-ilo-en', + ('ilo', 'es'): 'Helsinki-NLP/opus-mt-ilo-es', ('ilo', 'fi'): 'Helsinki-NLP/opus-mt-ilo-fi', + ('ilo', 'sv'): 'Helsinki-NLP/opus-mt-ilo-sv', ('inc', 'en'): 'Helsinki-NLP/opus-mt-inc-en', + ('inc', 'inc'): 'Helsinki-NLP/opus-mt-inc-inc', ('ine', 'en'): 'Helsinki-NLP/opus-mt-ine-en', + ('ine', 'ine'): 'Helsinki-NLP/opus-mt-ine-ine', ('is', 'de'): 'Helsinki-NLP/opus-mt-is-de', + ('is', 'en'): 'Helsinki-NLP/opus-mt-is-en', ('is', 'eo'): 'Helsinki-NLP/opus-mt-is-eo', + ('is', 'es'): 'Helsinki-NLP/opus-mt-is-es', ('is', 'fi'): 'Helsinki-NLP/opus-mt-is-fi', + ('is', 'fr'): 'Helsinki-NLP/opus-mt-is-fr', ('is', 'it'): 'Helsinki-NLP/opus-mt-is-it', + ('is', 'sv'): 'Helsinki-NLP/opus-mt-is-sv', ('iso', 'en'): 'Helsinki-NLP/opus-mt-iso-en', + ('iso', 'es'): 'Helsinki-NLP/opus-mt-iso-es', ('iso', 'fi'): 'Helsinki-NLP/opus-mt-iso-fi', + ('iso', 'fr'): 'Helsinki-NLP/opus-mt-iso-fr', ('iso', 'sv'): 'Helsinki-NLP/opus-mt-iso-sv', + ('it', 'ar'): 'Helsinki-NLP/opus-mt-it-ar', ('it', 'bg'): 'Helsinki-NLP/opus-mt-it-bg', + ('it', 'ca'): 'Helsinki-NLP/opus-mt-it-ca', ('it', 'de'): 'Helsinki-NLP/opus-mt-it-de', + ('it', 'en'): 'Helsinki-NLP/opus-mt-it-en', ('it', 'eo'): 'Helsinki-NLP/opus-mt-it-eo', + ('it', 'es'): 'Helsinki-NLP/opus-mt-it-es', ('it', 'fr'): 'Helsinki-NLP/opus-mt-it-fr', + ('it', 'is'): 'Helsinki-NLP/opus-mt-it-is', ('it', 'lt'): 'Helsinki-NLP/opus-mt-it-lt', + ('it', 'ms'): 'Helsinki-NLP/opus-mt-it-ms', ('it', 'sv'): 'Helsinki-NLP/opus-mt-it-sv', + ('it', 'uk'): 'Helsinki-NLP/opus-mt-it-uk', ('it', 'vi'): 'Helsinki-NLP/opus-mt-it-vi', + ('itc', 'en'): 'Helsinki-NLP/opus-mt-itc-en', ('itc', 'itc'): 'Helsinki-NLP/opus-mt-itc-itc', + ('ja', 'ar'): 'Helsinki-NLP/opus-mt-ja-ar', ('ja', 'bg'): 'Helsinki-NLP/opus-mt-ja-bg', + ('ja', 'da'): 'Helsinki-NLP/opus-mt-ja-da', ('ja', 'de'): 'Helsinki-NLP/opus-mt-ja-de', + ('ja', 'en'): 'Helsinki-NLP/opus-mt-ja-en', ('ja', 'es'): 'Helsinki-NLP/opus-mt-ja-es', + ('ja', 'fi'): 'Helsinki-NLP/opus-mt-ja-fi', ('ja', 'fr'): 'Helsinki-NLP/opus-mt-ja-fr', + ('ja', 'he'): 'Helsinki-NLP/opus-mt-ja-he', ('ja', 'hu'): 'Helsinki-NLP/opus-mt-ja-hu', + ('ja', 'it'): 'Helsinki-NLP/opus-mt-ja-it', ('ja', 'ms'): 'Helsinki-NLP/opus-mt-ja-ms', + ('ja', 'nl'): 'Helsinki-NLP/opus-mt-ja-nl', ('ja', 'pl'): 'Helsinki-NLP/opus-mt-ja-pl', + ('ja', 'pt'): 'Helsinki-NLP/opus-mt-ja-pt', ('ja', 'ru'): 'Helsinki-NLP/opus-mt-ja-ru', + ('ja', 'sh'): 'Helsinki-NLP/opus-mt-ja-sh', ('ja', 'sv'): 'Helsinki-NLP/opus-mt-ja-sv', + ('ja', 'tr'): 'Helsinki-NLP/opus-mt-ja-tr', ('ja', 'vi'): 'Helsinki-NLP/opus-mt-ja-vi', + ('jap', 'en'): 'Helsinki-NLP/opus-mt-jap-en', ('ka', 'en'): 'Helsinki-NLP/opus-mt-ka-en', + ('ka', 'ru'): 'Helsinki-NLP/opus-mt-ka-ru', ('kab', 'en'): 'Helsinki-NLP/opus-mt-kab-en', + ('kg', 'en'): 'Helsinki-NLP/opus-mt-kg-en', ('kg', 'es'): 'Helsinki-NLP/opus-mt-kg-es', + ('kg', 'fr'): 'Helsinki-NLP/opus-mt-kg-fr', ('kg', 'sv'): 'Helsinki-NLP/opus-mt-kg-sv', + ('kj', 'en'): 'Helsinki-NLP/opus-mt-kj-en', ('kl', 'en'): 'Helsinki-NLP/opus-mt-kl-en', + ('ko', 'de'): 'Helsinki-NLP/opus-mt-ko-de', ('ko', 'en'): 'Helsinki-NLP/opus-mt-ko-en', + ('ko', 'es'): 'Helsinki-NLP/opus-mt-ko-es', ('ko', 'fi'): 'Helsinki-NLP/opus-mt-ko-fi', + ('ko', 'fr'): 'Helsinki-NLP/opus-mt-ko-fr', ('ko', 'hu'): 'Helsinki-NLP/opus-mt-ko-hu', + ('ko', 'ru'): 'Helsinki-NLP/opus-mt-ko-ru', ('ko', 'sv'): 'Helsinki-NLP/opus-mt-ko-sv', + ('kqn', 'en'): 'Helsinki-NLP/opus-mt-kqn-en', ('kqn', 'es'): 'Helsinki-NLP/opus-mt-kqn-es', + ('kqn', 'fr'): 'Helsinki-NLP/opus-mt-kqn-fr', ('kqn', 'sv'): 'Helsinki-NLP/opus-mt-kqn-sv', + ('kwn', 'en'): 'Helsinki-NLP/opus-mt-kwn-en', ('kwy', 'en'): 'Helsinki-NLP/opus-mt-kwy-en', + ('kwy', 'fr'): 'Helsinki-NLP/opus-mt-kwy-fr', ('kwy', 'sv'): 'Helsinki-NLP/opus-mt-kwy-sv', + ('lg', 'en'): 'Helsinki-NLP/opus-mt-lg-en', ('lg', 'es'): 'Helsinki-NLP/opus-mt-lg-es', + ('lg', 'fi'): 'Helsinki-NLP/opus-mt-lg-fi', ('lg', 'fr'): 'Helsinki-NLP/opus-mt-lg-fr', + ('lg', 'sv'): 'Helsinki-NLP/opus-mt-lg-sv', ('ln', 'de'): 'Helsinki-NLP/opus-mt-ln-de', + ('ln', 'en'): 'Helsinki-NLP/opus-mt-ln-en', ('ln', 'es'): 'Helsinki-NLP/opus-mt-ln-es', + ('ln', 'fr'): 'Helsinki-NLP/opus-mt-ln-fr', ('loz', 'de'): 'Helsinki-NLP/opus-mt-loz-de', + ('loz', 'en'): 'Helsinki-NLP/opus-mt-loz-en', ('loz', 'es'): 'Helsinki-NLP/opus-mt-loz-es', + ('loz', 'fi'): 'Helsinki-NLP/opus-mt-loz-fi', ('loz', 'fr'): 'Helsinki-NLP/opus-mt-loz-fr', + ('loz', 'sv'): 'Helsinki-NLP/opus-mt-loz-sv', ('lt', 'de'): 'Helsinki-NLP/opus-mt-lt-de', + ('lt', 'eo'): 'Helsinki-NLP/opus-mt-lt-eo', ('lt', 'es'): 'Helsinki-NLP/opus-mt-lt-es', + ('lt', 'fr'): 'Helsinki-NLP/opus-mt-lt-fr', ('lt', 'it'): 'Helsinki-NLP/opus-mt-lt-it', + ('lt', 'pl'): 'Helsinki-NLP/opus-mt-lt-pl', ('lt', 'ru'): 'Helsinki-NLP/opus-mt-lt-ru', + ('lt', 'sv'): 'Helsinki-NLP/opus-mt-lt-sv', ('lt', 'tr'): 'Helsinki-NLP/opus-mt-lt-tr', + ('lu', 'en'): 'Helsinki-NLP/opus-mt-lu-en', ('lu', 'es'): 'Helsinki-NLP/opus-mt-lu-es', + ('lu', 'fi'): 'Helsinki-NLP/opus-mt-lu-fi', ('lu', 'fr'): 'Helsinki-NLP/opus-mt-lu-fr', + ('lu', 'sv'): 'Helsinki-NLP/opus-mt-lu-sv', ('lua', 'en'): 'Helsinki-NLP/opus-mt-lua-en', + ('lua', 'es'): 'Helsinki-NLP/opus-mt-lua-es', ('lua', 'fi'): 'Helsinki-NLP/opus-mt-lua-fi', + ('lua', 'fr'): 'Helsinki-NLP/opus-mt-lua-fr', ('lua', 'sv'): 'Helsinki-NLP/opus-mt-lua-sv', + ('lue', 'en'): 'Helsinki-NLP/opus-mt-lue-en', ('lue', 'es'): 'Helsinki-NLP/opus-mt-lue-es', + ('lue', 'fi'): 'Helsinki-NLP/opus-mt-lue-fi', ('lue', 'fr'): 'Helsinki-NLP/opus-mt-lue-fr', + ('lue', 'sv'): 'Helsinki-NLP/opus-mt-lue-sv', ('lun', 'en'): 'Helsinki-NLP/opus-mt-lun-en', + ('luo', 'en'): 'Helsinki-NLP/opus-mt-luo-en', ('lus', 'en'): 'Helsinki-NLP/opus-mt-lus-en', + ('lus', 'es'): 'Helsinki-NLP/opus-mt-lus-es', ('lus', 'fi'): 'Helsinki-NLP/opus-mt-lus-fi', + ('lus', 'fr'): 'Helsinki-NLP/opus-mt-lus-fr', ('lus', 'sv'): 'Helsinki-NLP/opus-mt-lus-sv', + ('lv', 'en'): 'Helsinki-NLP/opus-mt-lv-en', ('lv', 'es'): 'Helsinki-NLP/opus-mt-lv-es', + ('lv', 'fi'): 'Helsinki-NLP/opus-mt-lv-fi', ('lv', 'fr'): 'Helsinki-NLP/opus-mt-lv-fr', + ('lv', 'ru'): 'Helsinki-NLP/opus-mt-lv-ru', ('lv', 'sv'): 'Helsinki-NLP/opus-mt-lv-sv', + ('mfe', 'en'): 'Helsinki-NLP/opus-mt-mfe-en', ('mfe', 'es'): 'Helsinki-NLP/opus-mt-mfe-es', + ('mfs', 'es'): 'Helsinki-NLP/opus-mt-mfs-es', ('mg', 'en'): 'Helsinki-NLP/opus-mt-mg-en', + ('mg', 'es'): 'Helsinki-NLP/opus-mt-mg-es', ('mh', 'en'): 'Helsinki-NLP/opus-mt-mh-en', + ('mh', 'es'): 'Helsinki-NLP/opus-mt-mh-es', ('mh', 'fi'): 'Helsinki-NLP/opus-mt-mh-fi', + ('mk', 'en'): 'Helsinki-NLP/opus-mt-mk-en', ('mk', 'es'): 'Helsinki-NLP/opus-mt-mk-es', + ('mk', 'fi'): 'Helsinki-NLP/opus-mt-mk-fi', ('mk', 'fr'): 'Helsinki-NLP/opus-mt-mk-fr', + ('mkh', 'en'): 'Helsinki-NLP/opus-mt-mkh-en', ('ml', 'en'): 'Helsinki-NLP/opus-mt-ml-en', + ('mos', 'en'): 'Helsinki-NLP/opus-mt-mos-en', ('mr', 'en'): 'Helsinki-NLP/opus-mt-mr-en', + ('ms', 'de'): 'Helsinki-NLP/opus-mt-ms-de', ('ms', 'fr'): 'Helsinki-NLP/opus-mt-ms-fr', + ('ms', 'it'): 'Helsinki-NLP/opus-mt-ms-it', ('ms', 'ms'): 'Helsinki-NLP/opus-mt-ms-ms', + ('mt', 'en'): 'Helsinki-NLP/opus-mt-mt-en', ('mt', 'es'): 'Helsinki-NLP/opus-mt-mt-es', + ('mt', 'fi'): 'Helsinki-NLP/opus-mt-mt-fi', ('mt', 'fr'): 'Helsinki-NLP/opus-mt-mt-fr', + ('mt', 'sv'): 'Helsinki-NLP/opus-mt-mt-sv', ('mul', 'en'): 'Helsinki-NLP/opus-mt-mul-en', + ('ng', 'en'): 'Helsinki-NLP/opus-mt-ng-en', ('nic', 'en'): 'Helsinki-NLP/opus-mt-nic-en', + ('niu', 'de'): 'Helsinki-NLP/opus-mt-niu-de', ('niu', 'en'): 'Helsinki-NLP/opus-mt-niu-en', + ('niu', 'es'): 'Helsinki-NLP/opus-mt-niu-es', ('niu', 'fi'): 'Helsinki-NLP/opus-mt-niu-fi', + ('niu', 'fr'): 'Helsinki-NLP/opus-mt-niu-fr', ('niu', 'sv'): 'Helsinki-NLP/opus-mt-niu-sv', + ('nl', 'af'): 'Helsinki-NLP/opus-mt-nl-af', ('nl', 'ca'): 'Helsinki-NLP/opus-mt-nl-ca', + ('nl', 'en'): 'Helsinki-NLP/opus-mt-nl-en', ('nl', 'eo'): 'Helsinki-NLP/opus-mt-nl-eo', + ('nl', 'es'): 'Helsinki-NLP/opus-mt-nl-es', ('nl', 'fi'): 'Helsinki-NLP/opus-mt-nl-fi', + ('nl', 'fr'): 'Helsinki-NLP/opus-mt-nl-fr', ('nl', 'no'): 'Helsinki-NLP/opus-mt-nl-no', + ('nl', 'sv'): 'Helsinki-NLP/opus-mt-nl-sv', ('nl', 'uk'): 'Helsinki-NLP/opus-mt-nl-uk', + ('no', 'da'): 'Helsinki-NLP/opus-mt-no-da', ('no', 'de'): 'Helsinki-NLP/opus-mt-no-de', + ('no', 'es'): 'Helsinki-NLP/opus-mt-no-es', ('no', 'fi'): 'Helsinki-NLP/opus-mt-no-fi', + ('no', 'fr'): 'Helsinki-NLP/opus-mt-no-fr', ('no', 'nl'): 'Helsinki-NLP/opus-mt-no-nl', + ('no', 'no'): 'Helsinki-NLP/opus-mt-no-no', ('no', 'pl'): 'Helsinki-NLP/opus-mt-no-pl', + ('no', 'ru'): 'Helsinki-NLP/opus-mt-no-ru', ('no', 'sv'): 'Helsinki-NLP/opus-mt-no-sv', + ('no', 'uk'): 'Helsinki-NLP/opus-mt-no-uk', ('nso', 'de'): 'Helsinki-NLP/opus-mt-nso-de', + ('nso', 'en'): 'Helsinki-NLP/opus-mt-nso-en', ('nso', 'es'): 'Helsinki-NLP/opus-mt-nso-es', + ('nso', 'fi'): 'Helsinki-NLP/opus-mt-nso-fi', ('nso', 'fr'): 'Helsinki-NLP/opus-mt-nso-fr', + ('nso', 'sv'): 'Helsinki-NLP/opus-mt-nso-sv', ('ny', 'de'): 'Helsinki-NLP/opus-mt-ny-de', + ('ny', 'en'): 'Helsinki-NLP/opus-mt-ny-en', ('ny', 'es'): 'Helsinki-NLP/opus-mt-ny-es', + ('nyk', 'en'): 'Helsinki-NLP/opus-mt-nyk-en', ('om', 'en'): 'Helsinki-NLP/opus-mt-om-en', + ('pa', 'en'): 'Helsinki-NLP/opus-mt-pa-en', ('pag', 'de'): 'Helsinki-NLP/opus-mt-pag-de', + ('pag', 'en'): 'Helsinki-NLP/opus-mt-pag-en', ('pag', 'es'): 'Helsinki-NLP/opus-mt-pag-es', + ('pag', 'fi'): 'Helsinki-NLP/opus-mt-pag-fi', ('pag', 'sv'): 'Helsinki-NLP/opus-mt-pag-sv', + ('pap', 'de'): 'Helsinki-NLP/opus-mt-pap-de', ('pap', 'en'): 'Helsinki-NLP/opus-mt-pap-en', + ('pap', 'es'): 'Helsinki-NLP/opus-mt-pap-es', ('pap', 'fi'): 'Helsinki-NLP/opus-mt-pap-fi', + ('pap', 'fr'): 'Helsinki-NLP/opus-mt-pap-fr', ('phi', 'en'): 'Helsinki-NLP/opus-mt-phi-en', + ('pis', 'en'): 'Helsinki-NLP/opus-mt-pis-en', ('pis', 'es'): 'Helsinki-NLP/opus-mt-pis-es', + ('pis', 'fi'): 'Helsinki-NLP/opus-mt-pis-fi', ('pis', 'fr'): 'Helsinki-NLP/opus-mt-pis-fr', + ('pis', 'sv'): 'Helsinki-NLP/opus-mt-pis-sv', ('pl', 'ar'): 'Helsinki-NLP/opus-mt-pl-ar', + ('pl', 'de'): 'Helsinki-NLP/opus-mt-pl-de', ('pl', 'en'): 'Helsinki-NLP/opus-mt-pl-en', + ('pl', 'eo'): 'Helsinki-NLP/opus-mt-pl-eo', ('pl', 'es'): 'Helsinki-NLP/opus-mt-pl-es', + ('pl', 'fr'): 'Helsinki-NLP/opus-mt-pl-fr', ('pl', 'lt'): 'Helsinki-NLP/opus-mt-pl-lt', + ('pl', 'no'): 'Helsinki-NLP/opus-mt-pl-no', ('pl', 'sv'): 'Helsinki-NLP/opus-mt-pl-sv', + ('pl', 'uk'): 'Helsinki-NLP/opus-mt-pl-uk', ('pon', 'en'): 'Helsinki-NLP/opus-mt-pon-en', + ('pon', 'es'): 'Helsinki-NLP/opus-mt-pon-es', ('pon', 'fi'): 'Helsinki-NLP/opus-mt-pon-fi', + ('pon', 'fr'): 'Helsinki-NLP/opus-mt-pon-fr', ('pon', 'sv'): 'Helsinki-NLP/opus-mt-pon-sv', + ('pqe', 'en'): 'Helsinki-NLP/opus-mt-pqe-en', ('prl', 'es'): 'Helsinki-NLP/opus-mt-prl-es', + ('pt', 'ca'): 'Helsinki-NLP/opus-mt-pt-ca', ('pt', 'eo'): 'Helsinki-NLP/opus-mt-pt-eo', + ('pt', 'gl'): 'Helsinki-NLP/opus-mt-pt-gl', ('pt', 'tl'): 'Helsinki-NLP/opus-mt-pt-tl', + ('pt', 'uk'): 'Helsinki-NLP/opus-mt-pt-uk', ('rn', 'de'): 'Helsinki-NLP/opus-mt-rn-de', + ('rn', 'en'): 'Helsinki-NLP/opus-mt-rn-en', ('rn', 'es'): 'Helsinki-NLP/opus-mt-rn-es', + ('rn', 'fr'): 'Helsinki-NLP/opus-mt-rn-fr', ('rn', 'ru'): 'Helsinki-NLP/opus-mt-rn-ru', + ('rnd', 'en'): 'Helsinki-NLP/opus-mt-rnd-en', ('rnd', 'fr'): 'Helsinki-NLP/opus-mt-rnd-fr', + ('rnd', 'sv'): 'Helsinki-NLP/opus-mt-rnd-sv', ('ro', 'eo'): 'Helsinki-NLP/opus-mt-ro-eo', + ('ro', 'fi'): 'Helsinki-NLP/opus-mt-ro-fi', ('ro', 'fr'): 'Helsinki-NLP/opus-mt-ro-fr', + ('ro', 'sv'): 'Helsinki-NLP/opus-mt-ro-sv', ('roa', 'en'): 'Helsinki-NLP/opus-mt-roa-en', + ('ru', 'af'): 'Helsinki-NLP/opus-mt-ru-af', ('ru', 'ar'): 'Helsinki-NLP/opus-mt-ru-ar', + ('ru', 'bg'): 'Helsinki-NLP/opus-mt-ru-bg', ('ru', 'da'): 'Helsinki-NLP/opus-mt-ru-da', + ('ru', 'en'): 'Helsinki-NLP/opus-mt-ru-en', ('ru', 'eo'): 'Helsinki-NLP/opus-mt-ru-eo', + ('ru', 'es'): 'Helsinki-NLP/opus-mt-ru-es', ('ru', 'et'): 'Helsinki-NLP/opus-mt-ru-et', + ('ru', 'eu'): 'Helsinki-NLP/opus-mt-ru-eu', ('ru', 'fi'): 'Helsinki-NLP/opus-mt-ru-fi', + ('ru', 'fr'): 'Helsinki-NLP/opus-mt-ru-fr', ('ru', 'he'): 'Helsinki-NLP/opus-mt-ru-he', + ('ru', 'hy'): 'Helsinki-NLP/opus-mt-ru-hy', ('ru', 'lt'): 'Helsinki-NLP/opus-mt-ru-lt', + ('ru', 'lv'): 'Helsinki-NLP/opus-mt-ru-lv', ('ru', 'no'): 'Helsinki-NLP/opus-mt-ru-no', + ('ru', 'sl'): 'Helsinki-NLP/opus-mt-ru-sl', ('ru', 'sv'): 'Helsinki-NLP/opus-mt-ru-sv', + ('ru', 'uk'): 'Helsinki-NLP/opus-mt-ru-uk', ('ru', 'vi'): 'Helsinki-NLP/opus-mt-ru-vi', + ('run', 'en'): 'Helsinki-NLP/opus-mt-run-en', ('run', 'es'): 'Helsinki-NLP/opus-mt-run-es', + ('run', 'sv'): 'Helsinki-NLP/opus-mt-run-sv', ('rw', 'en'): 'Helsinki-NLP/opus-mt-rw-en', + ('rw', 'es'): 'Helsinki-NLP/opus-mt-rw-es', ('rw', 'fr'): 'Helsinki-NLP/opus-mt-rw-fr', + ('rw', 'sv'): 'Helsinki-NLP/opus-mt-rw-sv', ('sal', 'en'): 'Helsinki-NLP/opus-mt-sal-en', + ('sem', 'en'): 'Helsinki-NLP/opus-mt-sem-en', ('sem', 'sem'): 'Helsinki-NLP/opus-mt-sem-sem', + ('sg', 'en'): 'Helsinki-NLP/opus-mt-sg-en', ('sg', 'es'): 'Helsinki-NLP/opus-mt-sg-es', + ('sg', 'fi'): 'Helsinki-NLP/opus-mt-sg-fi', ('sg', 'fr'): 'Helsinki-NLP/opus-mt-sg-fr', + ('sg', 'sv'): 'Helsinki-NLP/opus-mt-sg-sv', ('sh', 'eo'): 'Helsinki-NLP/opus-mt-sh-eo', + ('sh', 'uk'): 'Helsinki-NLP/opus-mt-sh-uk', ('sk', 'en'): 'Helsinki-NLP/opus-mt-sk-en', + ('sk', 'es'): 'Helsinki-NLP/opus-mt-sk-es', ('sk', 'fi'): 'Helsinki-NLP/opus-mt-sk-fi', + ('sk', 'fr'): 'Helsinki-NLP/opus-mt-sk-fr', ('sk', 'sv'): 'Helsinki-NLP/opus-mt-sk-sv', + ('sl', 'es'): 'Helsinki-NLP/opus-mt-sl-es', ('sl', 'fi'): 'Helsinki-NLP/opus-mt-sl-fi', + ('sl', 'fr'): 'Helsinki-NLP/opus-mt-sl-fr', ('sl', 'ru'): 'Helsinki-NLP/opus-mt-sl-ru', + ('sl', 'sv'): 'Helsinki-NLP/opus-mt-sl-sv', ('sl', 'uk'): 'Helsinki-NLP/opus-mt-sl-uk', + ('sla', 'en'): 'Helsinki-NLP/opus-mt-sla-en', ('sla', 'sla'): 'Helsinki-NLP/opus-mt-sla-sla', + ('sm', 'en'): 'Helsinki-NLP/opus-mt-sm-en', ('sm', 'es'): 'Helsinki-NLP/opus-mt-sm-es', + ('sm', 'fr'): 'Helsinki-NLP/opus-mt-sm-fr', ('sn', 'en'): 'Helsinki-NLP/opus-mt-sn-en', + ('sn', 'es'): 'Helsinki-NLP/opus-mt-sn-es', ('sn', 'fr'): 'Helsinki-NLP/opus-mt-sn-fr', + ('sn', 'sv'): 'Helsinki-NLP/opus-mt-sn-sv', ('sq', 'en'): 'Helsinki-NLP/opus-mt-sq-en', + ('sq', 'es'): 'Helsinki-NLP/opus-mt-sq-es', ('sq', 'sv'): 'Helsinki-NLP/opus-mt-sq-sv', + ('srn', 'en'): 'Helsinki-NLP/opus-mt-srn-en', ('srn', 'es'): 'Helsinki-NLP/opus-mt-srn-es', + ('srn', 'fr'): 'Helsinki-NLP/opus-mt-srn-fr', ('srn', 'sv'): 'Helsinki-NLP/opus-mt-srn-sv', + ('ss', 'en'): 'Helsinki-NLP/opus-mt-ss-en', ('ssp', 'es'): 'Helsinki-NLP/opus-mt-ssp-es', + ('st', 'en'): 'Helsinki-NLP/opus-mt-st-en', ('st', 'es'): 'Helsinki-NLP/opus-mt-st-es', + ('st', 'fi'): 'Helsinki-NLP/opus-mt-st-fi', ('st', 'fr'): 'Helsinki-NLP/opus-mt-st-fr', + ('st', 'sv'): 'Helsinki-NLP/opus-mt-st-sv', ('sv', 'NORWAY'): 'Helsinki-NLP/opus-mt-sv-NORWAY', + ('sv', 'ZH'): 'Helsinki-NLP/opus-mt-sv-ZH', ('sv', 'af'): 'Helsinki-NLP/opus-mt-sv-af', + ('sv', 'ase'): 'Helsinki-NLP/opus-mt-sv-ase', ('sv', 'bcl'): 'Helsinki-NLP/opus-mt-sv-bcl', + ('sv', 'bem'): 'Helsinki-NLP/opus-mt-sv-bem', ('sv', 'bg'): 'Helsinki-NLP/opus-mt-sv-bg', + ('sv', 'bi'): 'Helsinki-NLP/opus-mt-sv-bi', ('sv', 'bzs'): 'Helsinki-NLP/opus-mt-sv-bzs', + ('sv', 'ceb'): 'Helsinki-NLP/opus-mt-sv-ceb', ('sv', 'chk'): 'Helsinki-NLP/opus-mt-sv-chk', + ('sv', 'crs'): 'Helsinki-NLP/opus-mt-sv-crs', ('sv', 'cs'): 'Helsinki-NLP/opus-mt-sv-cs', + ('sv', 'ee'): 'Helsinki-NLP/opus-mt-sv-ee', ('sv', 'efi'): 'Helsinki-NLP/opus-mt-sv-efi', + ('sv', 'el'): 'Helsinki-NLP/opus-mt-sv-el', ('sv', 'en'): 'Helsinki-NLP/opus-mt-sv-en', + ('sv', 'eo'): 'Helsinki-NLP/opus-mt-sv-eo', ('sv', 'es'): 'Helsinki-NLP/opus-mt-sv-es', + ('sv', 'et'): 'Helsinki-NLP/opus-mt-sv-et', ('sv', 'fi'): 'Helsinki-NLP/opus-mt-sv-fi', + ('sv', 'fj'): 'Helsinki-NLP/opus-mt-sv-fj', ('sv', 'fr'): 'Helsinki-NLP/opus-mt-sv-fr', + ('sv', 'gaa'): 'Helsinki-NLP/opus-mt-sv-gaa', ('sv', 'gil'): 'Helsinki-NLP/opus-mt-sv-gil', + ('sv', 'guw'): 'Helsinki-NLP/opus-mt-sv-guw', ('sv', 'ha'): 'Helsinki-NLP/opus-mt-sv-ha', + ('sv', 'he'): 'Helsinki-NLP/opus-mt-sv-he', ('sv', 'hil'): 'Helsinki-NLP/opus-mt-sv-hil', + ('sv', 'ho'): 'Helsinki-NLP/opus-mt-sv-ho', ('sv', 'hr'): 'Helsinki-NLP/opus-mt-sv-hr', + ('sv', 'ht'): 'Helsinki-NLP/opus-mt-sv-ht', ('sv', 'hu'): 'Helsinki-NLP/opus-mt-sv-hu', + ('sv', 'id'): 'Helsinki-NLP/opus-mt-sv-id', ('sv', 'ig'): 'Helsinki-NLP/opus-mt-sv-ig', + ('sv', 'ilo'): 'Helsinki-NLP/opus-mt-sv-ilo', ('sv', 'is'): 'Helsinki-NLP/opus-mt-sv-is', + ('sv', 'iso'): 'Helsinki-NLP/opus-mt-sv-iso', ('sv', 'kg'): 'Helsinki-NLP/opus-mt-sv-kg', + ('sv', 'kqn'): 'Helsinki-NLP/opus-mt-sv-kqn', ('sv', 'kwy'): 'Helsinki-NLP/opus-mt-sv-kwy', + ('sv', 'lg'): 'Helsinki-NLP/opus-mt-sv-lg', ('sv', 'ln'): 'Helsinki-NLP/opus-mt-sv-ln', + ('sv', 'lu'): 'Helsinki-NLP/opus-mt-sv-lu', ('sv', 'lua'): 'Helsinki-NLP/opus-mt-sv-lua', + ('sv', 'lue'): 'Helsinki-NLP/opus-mt-sv-lue', ('sv', 'lus'): 'Helsinki-NLP/opus-mt-sv-lus', + ('sv', 'lv'): 'Helsinki-NLP/opus-mt-sv-lv', ('sv', 'mfe'): 'Helsinki-NLP/opus-mt-sv-mfe', + ('sv', 'mh'): 'Helsinki-NLP/opus-mt-sv-mh', ('sv', 'mos'): 'Helsinki-NLP/opus-mt-sv-mos', + ('sv', 'mt'): 'Helsinki-NLP/opus-mt-sv-mt', ('sv', 'niu'): 'Helsinki-NLP/opus-mt-sv-niu', + ('sv', 'nl'): 'Helsinki-NLP/opus-mt-sv-nl', ('sv', 'no'): 'Helsinki-NLP/opus-mt-sv-no', + ('sv', 'nso'): 'Helsinki-NLP/opus-mt-sv-nso', ('sv', 'ny'): 'Helsinki-NLP/opus-mt-sv-ny', + ('sv', 'pag'): 'Helsinki-NLP/opus-mt-sv-pag', ('sv', 'pap'): 'Helsinki-NLP/opus-mt-sv-pap', + ('sv', 'pis'): 'Helsinki-NLP/opus-mt-sv-pis', ('sv', 'pon'): 'Helsinki-NLP/opus-mt-sv-pon', + ('sv', 'rnd'): 'Helsinki-NLP/opus-mt-sv-rnd', ('sv', 'ro'): 'Helsinki-NLP/opus-mt-sv-ro', + ('sv', 'ru'): 'Helsinki-NLP/opus-mt-sv-ru', ('sv', 'run'): 'Helsinki-NLP/opus-mt-sv-run', + ('sv', 'rw'): 'Helsinki-NLP/opus-mt-sv-rw', ('sv', 'sg'): 'Helsinki-NLP/opus-mt-sv-sg', + ('sv', 'sk'): 'Helsinki-NLP/opus-mt-sv-sk', ('sv', 'sl'): 'Helsinki-NLP/opus-mt-sv-sl', + ('sv', 'sm'): 'Helsinki-NLP/opus-mt-sv-sm', ('sv', 'sn'): 'Helsinki-NLP/opus-mt-sv-sn', + ('sv', 'sq'): 'Helsinki-NLP/opus-mt-sv-sq', ('sv', 'srn'): 'Helsinki-NLP/opus-mt-sv-srn', + ('sv', 'st'): 'Helsinki-NLP/opus-mt-sv-st', ('sv', 'sv'): 'Helsinki-NLP/opus-mt-sv-sv', + ('sv', 'swc'): 'Helsinki-NLP/opus-mt-sv-swc', ('sv', 'th'): 'Helsinki-NLP/opus-mt-sv-th', + ('sv', 'tiv'): 'Helsinki-NLP/opus-mt-sv-tiv', ('sv', 'tll'): 'Helsinki-NLP/opus-mt-sv-tll', + ('sv', 'tn'): 'Helsinki-NLP/opus-mt-sv-tn', ('sv', 'to'): 'Helsinki-NLP/opus-mt-sv-to', + ('sv', 'toi'): 'Helsinki-NLP/opus-mt-sv-toi', ('sv', 'tpi'): 'Helsinki-NLP/opus-mt-sv-tpi', + ('sv', 'ts'): 'Helsinki-NLP/opus-mt-sv-ts', ('sv', 'tum'): 'Helsinki-NLP/opus-mt-sv-tum', + ('sv', 'tvl'): 'Helsinki-NLP/opus-mt-sv-tvl', ('sv', 'tw'): 'Helsinki-NLP/opus-mt-sv-tw', + ('sv', 'ty'): 'Helsinki-NLP/opus-mt-sv-ty', ('sv', 'uk'): 'Helsinki-NLP/opus-mt-sv-uk', + ('sv', 'umb'): 'Helsinki-NLP/opus-mt-sv-umb', ('sv', 've'): 'Helsinki-NLP/opus-mt-sv-ve', + ('sv', 'war'): 'Helsinki-NLP/opus-mt-sv-war', ('sv', 'wls'): 'Helsinki-NLP/opus-mt-sv-wls', + ('sv', 'xh'): 'Helsinki-NLP/opus-mt-sv-xh', ('sv', 'yap'): 'Helsinki-NLP/opus-mt-sv-yap', + ('sv', 'yo'): 'Helsinki-NLP/opus-mt-sv-yo', ('sv', 'zne'): 'Helsinki-NLP/opus-mt-sv-zne', + ('swc', 'en'): 'Helsinki-NLP/opus-mt-swc-en', ('swc', 'es'): 'Helsinki-NLP/opus-mt-swc-es', + ('swc', 'fi'): 'Helsinki-NLP/opus-mt-swc-fi', ('swc', 'fr'): 'Helsinki-NLP/opus-mt-swc-fr', + ('swc', 'sv'): 'Helsinki-NLP/opus-mt-swc-sv', ('taw', 'en'): 'Helsinki-NLP/opus-mt-taw-en', + ('th', 'en'): 'Helsinki-NLP/opus-mt-th-en', ('th', 'fr'): 'Helsinki-NLP/opus-mt-th-fr', + ('ti', 'en'): 'Helsinki-NLP/opus-mt-ti-en', ('tiv', 'en'): 'Helsinki-NLP/opus-mt-tiv-en', + ('tiv', 'fr'): 'Helsinki-NLP/opus-mt-tiv-fr', ('tiv', 'sv'): 'Helsinki-NLP/opus-mt-tiv-sv', + ('tl', 'de'): 'Helsinki-NLP/opus-mt-tl-de', ('tl', 'en'): 'Helsinki-NLP/opus-mt-tl-en', + ('tl', 'es'): 'Helsinki-NLP/opus-mt-tl-es', ('tl', 'pt'): 'Helsinki-NLP/opus-mt-tl-pt', + ('tll', 'en'): 'Helsinki-NLP/opus-mt-tll-en', ('tll', 'es'): 'Helsinki-NLP/opus-mt-tll-es', + ('tll', 'fi'): 'Helsinki-NLP/opus-mt-tll-fi', ('tll', 'fr'): 'Helsinki-NLP/opus-mt-tll-fr', + ('tll', 'sv'): 'Helsinki-NLP/opus-mt-tll-sv', ('tn', 'en'): 'Helsinki-NLP/opus-mt-tn-en', + ('tn', 'es'): 'Helsinki-NLP/opus-mt-tn-es', ('tn', 'fr'): 'Helsinki-NLP/opus-mt-tn-fr', + ('tn', 'sv'): 'Helsinki-NLP/opus-mt-tn-sv', ('to', 'en'): 'Helsinki-NLP/opus-mt-to-en', + ('to', 'es'): 'Helsinki-NLP/opus-mt-to-es', ('to', 'fr'): 'Helsinki-NLP/opus-mt-to-fr', + ('to', 'sv'): 'Helsinki-NLP/opus-mt-to-sv', ('toi', 'en'): 'Helsinki-NLP/opus-mt-toi-en', + ('toi', 'es'): 'Helsinki-NLP/opus-mt-toi-es', ('toi', 'fi'): 'Helsinki-NLP/opus-mt-toi-fi', + ('toi', 'fr'): 'Helsinki-NLP/opus-mt-toi-fr', ('toi', 'sv'): 'Helsinki-NLP/opus-mt-toi-sv', + ('tpi', 'en'): 'Helsinki-NLP/opus-mt-tpi-en', ('tpi', 'sv'): 'Helsinki-NLP/opus-mt-tpi-sv', + ('tr', 'ar'): 'Helsinki-NLP/opus-mt-tr-ar', ('tr', 'az'): 'Helsinki-NLP/opus-mt-tr-az', + ('tr', 'en'): 'Helsinki-NLP/opus-mt-tr-en', ('tr', 'eo'): 'Helsinki-NLP/opus-mt-tr-eo', + ('tr', 'es'): 'Helsinki-NLP/opus-mt-tr-es', ('tr', 'fr'): 'Helsinki-NLP/opus-mt-tr-fr', + ('tr', 'lt'): 'Helsinki-NLP/opus-mt-tr-lt', ('tr', 'sv'): 'Helsinki-NLP/opus-mt-tr-sv', + ('tr', 'uk'): 'Helsinki-NLP/opus-mt-tr-uk', ('trk', 'en'): 'Helsinki-NLP/opus-mt-trk-en', + ('ts', 'en'): 'Helsinki-NLP/opus-mt-ts-en', ('ts', 'es'): 'Helsinki-NLP/opus-mt-ts-es', + ('ts', 'fi'): 'Helsinki-NLP/opus-mt-ts-fi', ('ts', 'fr'): 'Helsinki-NLP/opus-mt-ts-fr', + ('ts', 'sv'): 'Helsinki-NLP/opus-mt-ts-sv', ('tum', 'en'): 'Helsinki-NLP/opus-mt-tum-en', + ('tum', 'es'): 'Helsinki-NLP/opus-mt-tum-es', ('tum', 'fr'): 'Helsinki-NLP/opus-mt-tum-fr', + ('tum', 'sv'): 'Helsinki-NLP/opus-mt-tum-sv', ('tvl', 'en'): 'Helsinki-NLP/opus-mt-tvl-en', + ('tvl', 'es'): 'Helsinki-NLP/opus-mt-tvl-es', ('tvl', 'fi'): 'Helsinki-NLP/opus-mt-tvl-fi', + ('tvl', 'fr'): 'Helsinki-NLP/opus-mt-tvl-fr', ('tvl', 'sv'): 'Helsinki-NLP/opus-mt-tvl-sv', + ('tw', 'es'): 'Helsinki-NLP/opus-mt-tw-es', ('tw', 'fi'): 'Helsinki-NLP/opus-mt-tw-fi', + ('tw', 'fr'): 'Helsinki-NLP/opus-mt-tw-fr', ('tw', 'sv'): 'Helsinki-NLP/opus-mt-tw-sv', + ('ty', 'es'): 'Helsinki-NLP/opus-mt-ty-es', ('ty', 'fi'): 'Helsinki-NLP/opus-mt-ty-fi', + ('ty', 'fr'): 'Helsinki-NLP/opus-mt-ty-fr', ('ty', 'sv'): 'Helsinki-NLP/opus-mt-ty-sv', + ('tzo', 'es'): 'Helsinki-NLP/opus-mt-tzo-es', ('uk', 'bg'): 'Helsinki-NLP/opus-mt-uk-bg', + ('uk', 'ca'): 'Helsinki-NLP/opus-mt-uk-ca', ('uk', 'cs'): 'Helsinki-NLP/opus-mt-uk-cs', + ('uk', 'de'): 'Helsinki-NLP/opus-mt-uk-de', ('uk', 'en'): 'Helsinki-NLP/opus-mt-uk-en', + ('uk', 'es'): 'Helsinki-NLP/opus-mt-uk-es', ('uk', 'fi'): 'Helsinki-NLP/opus-mt-uk-fi', + ('uk', 'fr'): 'Helsinki-NLP/opus-mt-uk-fr', ('uk', 'he'): 'Helsinki-NLP/opus-mt-uk-he', + ('uk', 'hu'): 'Helsinki-NLP/opus-mt-uk-hu', ('uk', 'it'): 'Helsinki-NLP/opus-mt-uk-it', + ('uk', 'nl'): 'Helsinki-NLP/opus-mt-uk-nl', ('uk', 'no'): 'Helsinki-NLP/opus-mt-uk-no', + ('uk', 'pl'): 'Helsinki-NLP/opus-mt-uk-pl', ('uk', 'pt'): 'Helsinki-NLP/opus-mt-uk-pt', + ('uk', 'ru'): 'Helsinki-NLP/opus-mt-uk-ru', ('uk', 'sh'): 'Helsinki-NLP/opus-mt-uk-sh', + ('uk', 'sl'): 'Helsinki-NLP/opus-mt-uk-sl', ('uk', 'sv'): 'Helsinki-NLP/opus-mt-uk-sv', + ('uk', 'tr'): 'Helsinki-NLP/opus-mt-uk-tr', ('umb', 'en'): 'Helsinki-NLP/opus-mt-umb-en', + ('ur', 'en'): 'Helsinki-NLP/opus-mt-ur-en', ('urj', 'en'): 'Helsinki-NLP/opus-mt-urj-en', + ('urj', 'urj'): 'Helsinki-NLP/opus-mt-urj-urj', ('ve', 'en'): 'Helsinki-NLP/opus-mt-ve-en', + ('ve', 'es'): 'Helsinki-NLP/opus-mt-ve-es', ('vi', 'de'): 'Helsinki-NLP/opus-mt-vi-de', + ('vi', 'en'): 'Helsinki-NLP/opus-mt-vi-en', ('vi', 'eo'): 'Helsinki-NLP/opus-mt-vi-eo', + ('vi', 'es'): 'Helsinki-NLP/opus-mt-vi-es', ('vi', 'fr'): 'Helsinki-NLP/opus-mt-vi-fr', + ('vi', 'it'): 'Helsinki-NLP/opus-mt-vi-it', ('vi', 'ru'): 'Helsinki-NLP/opus-mt-vi-ru', + ('vsl', 'es'): 'Helsinki-NLP/opus-mt-vsl-es', ('wa', 'en'): 'Helsinki-NLP/opus-mt-wa-en', + ('wal', 'en'): 'Helsinki-NLP/opus-mt-wal-en', ('war', 'en'): 'Helsinki-NLP/opus-mt-war-en', + ('war', 'es'): 'Helsinki-NLP/opus-mt-war-es', ('war', 'fi'): 'Helsinki-NLP/opus-mt-war-fi', + ('war', 'fr'): 'Helsinki-NLP/opus-mt-war-fr', ('war', 'sv'): 'Helsinki-NLP/opus-mt-war-sv', + ('wls', 'en'): 'Helsinki-NLP/opus-mt-wls-en', ('wls', 'fr'): 'Helsinki-NLP/opus-mt-wls-fr', + ('wls', 'sv'): 'Helsinki-NLP/opus-mt-wls-sv', ('xh', 'en'): 'Helsinki-NLP/opus-mt-xh-en', + ('xh', 'es'): 'Helsinki-NLP/opus-mt-xh-es', ('xh', 'fr'): 'Helsinki-NLP/opus-mt-xh-fr', + ('xh', 'sv'): 'Helsinki-NLP/opus-mt-xh-sv', ('yap', 'en'): 'Helsinki-NLP/opus-mt-yap-en', + ('yap', 'fr'): 'Helsinki-NLP/opus-mt-yap-fr', ('yap', 'sv'): 'Helsinki-NLP/opus-mt-yap-sv', + ('yo', 'en'): 'Helsinki-NLP/opus-mt-yo-en', ('yo', 'es'): 'Helsinki-NLP/opus-mt-yo-es', + ('yo', 'fi'): 'Helsinki-NLP/opus-mt-yo-fi', ('yo', 'fr'): 'Helsinki-NLP/opus-mt-yo-fr', + ('yo', 'sv'): 'Helsinki-NLP/opus-mt-yo-sv', ('zai', 'es'): 'Helsinki-NLP/opus-mt-zai-es', + ('zh', 'bg'): 'Helsinki-NLP/opus-mt-zh-bg', ('zh', 'de'): 'Helsinki-NLP/opus-mt-zh-de', + ('zh', 'en'): 'Helsinki-NLP/opus-mt-zh-en', ('zh', 'fi'): 'Helsinki-NLP/opus-mt-zh-fi', + ('zh', 'he'): 'Helsinki-NLP/opus-mt-zh-he', ('zh', 'it'): 'Helsinki-NLP/opus-mt-zh-it', + ('zh', 'ms'): 'Helsinki-NLP/opus-mt-zh-ms', ('zh', 'nl'): 'Helsinki-NLP/opus-mt-zh-nl', + ('zh', 'sv'): 'Helsinki-NLP/opus-mt-zh-sv', ('zh', 'uk'): 'Helsinki-NLP/opus-mt-zh-uk', + ('zh', 'vi'): 'Helsinki-NLP/opus-mt-zh-vi', ('zle', 'en'): 'Helsinki-NLP/opus-mt-zle-en', + ('zle', 'zle'): 'Helsinki-NLP/opus-mt-zle-zle', ('zls', 'en'): 'Helsinki-NLP/opus-mt-zls-en', + ('zls', 'zls'): 'Helsinki-NLP/opus-mt-zls-zls', ('zlw', 'en'): 'Helsinki-NLP/opus-mt-zlw-en', + ('zlw', 'fiu'): 'Helsinki-NLP/opus-mt-zlw-fiu', ('zlw', 'zlw'): 'Helsinki-NLP/opus-mt-zlw-zlw', + ('zne', 'es'): 'Helsinki-NLP/opus-mt-zne-es', ('zne', 'fi'): 'Helsinki-NLP/opus-mt-zne-fi', + ('zne', 'fr'): 'Helsinki-NLP/opus-mt-zne-fr', ('zne', 'sv'): 'Helsinki-NLP/opus-mt-zne-sv'} + +def remove_html_tags(text): + """Remove html tags from a string""" + clean = re.compile('<.*?>') + return re.sub(clean, '', text) + + +def camel_case_split(identifier): + matches = finditer('.+?(?:(?<=[a-z])(?=[A-Z])|(?<=[A-Z])(?=[A-Z][a-z])|$)', identifier) + return [m.group(0) for m in matches] + + +def stem(s): + s = s.replace(".", " ").replace("!", " ").replace("?", " ").replace(",", " ").replace("-", " ").replace(";", + " ").replace( + "'", " '").replace("\"", " \"") + sArr = s.lower().split() + if len(sArr) > 4: + sArr = sArr[:4] + s = " ".join([s1[:4] if len(s1) > 4 else s1 for s1 in sArr if s1.strip()]) + return s + + +def pre_translation_steps(infile, target_lang='hi'): + texts = [] + ner_mappings = [] + row_ids = [] + domains = [] + lbracket = "[" + rbracket = "]" + if target_lang in ('zh', 'ja', 'ko'): + lbracket = "[[" + rbracket = "]]" + + row_id = -1 + for s in tqdm(open(infile, "rb")): + s = s.decode().strip() + if not s: continue + dat = json.loads(s) + domain = dat['domain'] + ner = dat['ner'] + text = dat['text'] + if 'id' not in dat: + row_id += 1 + else: + row_id = int(dat['id']) + context = {} + ner_mapping = {} + seen = {} + text = "... " + text + " " + text = text.replace(lbracket, "(") + text = text.replace(rbracket, ")", ) + if person_swap: + _idx = 0 + for item in ner2: + if item[0] in seen: continue + seen[item[0]] = 1 + text = text.replace(item[0], + ' ' + str(_idx) + " " + lbracket + item[0] + rbracket) + ner_mapping[str(_idx) + " " + lbracket] = item + _idx += 1 + + texts.append(text) + ner_mappings.append(ner_mapping) + row_ids.append(row_id) + domains.append(domain) + return texts, ner_mappings, row_ids, domains + + +def chunks(lst, n): + """Generate batches""" + for i in range(0, len(lst), n): + yield lst[i: i + n] + + +def do_translations(texts, target_lang='hi'): + model = M2M100ForConditionalGeneration.from_pretrained("facebook/m2m100_418M") + tokenizer = M2M100Tokenizer.from_pretrained("facebook/m2m100_418M") + model = model.to('cuda').half() + translations = [] + for src_text_list in tqdm(chunks(texts, 16)): + batch = tokenizer(src_text_list, return_tensors="pt", padding=True, truncation=True).to('cuda') + gen = model.generate(**batch, forced_bos_token_id=tokenizer.get_lang_id(target_lang)) + outputs = tokenizer.batch_decode(gen, skip_special_tokens=True) + translations.extend(outputs) + return translations + + +def get_aligned_text(sent1, sent2, target_lang): + """ + Given two sentences, find blocks of text that match and that don't match. + return the blocks, and a matching score. + Used to extract NER from original language sentence. + TODO: prefer matching based on "[id] aaaa *" patterns + """ + if target_lang in ("ja", "ko", "zh"): + # splitting on spaces doesn't always work because some languages aren't space separated + sep = "" + else: + sep = " " + sent1 = sent1.split() + sent2 = sent2.split() + aMatch = difflib.SequenceMatcher(None,sent1, sent2) + score = aMatch.ratio() + blocks = aMatch.get_matching_blocks() + blocks2 = [] + prevEndA = 0 + prevEndB = 0 + matchLen = 0 + nonMatchLen = 0 + print (blocks) + for blockI in range(len(blocks)): + if blockI > 0 or (blockI==0 and (blocks[blockI][0] != 0 or blocks[blockI][1] != 0)): + blocks2.append([sep.join(sent1[prevEndA:blocks[blockI][0]]), sep.join(sent2[prevEndB:blocks[blockI][1]]), 0]) + nonMatchLen += max(blocks[blockI][0] - prevEndA, blocks[blockI][1] - prevEndB) + if blocks[blockI][2] != 0: + blocks2.append([sep.join(sent1[blocks[blockI][0]:blocks[blockI][0]+blocks[blockI][2]]), sep.join(sent2[blocks[blockI][1]:blocks[blockI][1]+blocks[blockI][2]]), 1]) + prevEndA = blocks[blockI][0]+blocks[blockI][2] + prevEndB = blocks[blockI][1]+blocks[blockI][2] + matchLen += blocks[blockI][2] + #score = float(matchLen+1)/float(nonMatchLen+1) + return (blocks2, score) + +def post_translation_steps(outfile, translations, original_sentences, ner_mappings, row_ids, domains, target_lang='hi'): + rbracket = "]" + if target_lang in ('zh', 'ja', 'ko'): + rbracket = "]]" + with open(outfile, "w", encoding="utf8") as o: + for original_text, trans_text in zip(original_sentences, translations): + index += 1 + ner_found = [] + trans_text = trans_text.lstrip(".") + trans_text = trans_text.strip() + if original_text: + trans_text = trans_text.replace(". [", " [").replace(".[", " [").replace(" ", " ") + for key, ner_item in ner_mappings[index].items(): + if key in trans_text: + ner_found[key] = ner_item[1] + elif key.replace(" ", "") in trans_text: + key = key.replace(" ", "") + ner_found[key] = ner_item[1] + if target_lang in ('zh', 'ja', 'ko'): + trans_text.replace(" ", "") + trans_text.strip('#.') + if ner_found: + (blocks2, score) = get_aligned_text(original_text, trans_text, target_lang) + #since we know what slots we are replacing, + #we can align with the original sentence in the original language, + #and then extract the original NER value, or a translated version of the new value. + for (s1, s2, matched) in blocks2: + s1 = s1.strip() + s2 = se2.strip() + if "[" in s2 or "]" in s2: + key = s2.split("[")[1].split("]")[0] + if key in ner_found and key != s1: + ner_found[s1] = ner_found[key] + del ner_found[key] + for key in ner_found.keys(): + if key not in oiriginal_text: + del ner_found[key] + ner_found = list(ner_found.items()) + j = {'text': original_text, 'ner': ner_found, 'domain': domains[index], + 'id': row_ids[index], + 'lang': target_lang} + o.write(json.dumps(j) + "\n") + +# basic idea is to do first a lexicon match, than a spacy match if any, and then do progressive groups of regex. +#TODO: for lang where there is no spacy model, translate to en, do ner in en, do back-trans, match for ner mapping and map to original sentence. +#TODO - do complicated rules, such as PERSON Inc. => ORG +#TODO - calculate fmeasure +#TODO - check for zh working properly +def apply_rules(infile, outfile, rule_base, target_lang, do_ontology_manager=True, do_spacy_if_avail=True, char_before_after_window=10): + nlp = None + if do_spacy_if_avail: + if target_lang == 'en': + nlp = spacy.load('en_core_web_lg') + elif target_lang == 'zh': + nlp = spacy.load('zh_core_web_lg') + elif target_lang == 'pt': + nlp = spacy.load('pt_core_news_lg') + elif target_lang == 'fr': + nlp = spacy.load('fr_core_news_lg') + elif target_lang == 'ca': + nlp = spacy.load('ca_core_news_lg') + if do_ontology_manager: + ontology_manager = OntologyManager(target_lang=target_lang) + else: + ontology_manager = None + right = {} + wrong = {} + with open(outfile, "w", encoding="utf8") as o: + for line in tqdm(open(infile, "rb")): + pred = [] #predicted regex rules ent:label + d = json.loads(line) + text = d['text'] + if not text: continue + predict_ner = d.get('predict_ner',{}) + if ontology_manager: + parsed = ontology_manager.tokenize(text) + cunk2ner = list(parsed['chunk2ner'].items()) + for c in cunk2ner: + key, val = c[0][0].replace(" ", "").replace("_", "").replace("_", "") if target_lang in ('zh', 'ja', 'ko') else c[0][0].replace("_", " ").replace("_", " "), c[1] + predict_ner[key] = val + if nlp: + doc = nlp(text) + entities = list(doc.ents) + ents = dict(list(set([(entity.text, entity.label_) for entity in entities if + entity.label_ in ('PERSON', 'GPE', 'ORG', 'NORP') and 'http:' not in entity.text]))) + for ent, label in ents.items(): + if ent in predict_ner and ('PERSON' if predict_ner[ent] == 'PUBLIC_FIGURE' else predict_ner[ent]) ==label: + #print ("matched") + continue + else: + #remove simple overlap + for key in list(predict_ner.keys()): + if " "+key in ent or key+" " in ent: # or " "+ent in key or ent+" " in key: + if predict_ner[key] == 'PUBLIC_FIGURE': + label = "PUBLIC_FIGURE" + del predict_ner[key] + predict_ner[ent] = label + rule_level = -1 + ner = d['ner'] # the human tagged data + for rule_groups, ntimes in rule_base: + rule_level += 1 + for times in range(ntimes): + rule_id = -1 + for label, regex, old_label, before, after in rule_groups: + rule_id += 1 + if old_label is None and times > 0: continue + for ent in regex.findall(text): + if type(ent) != str: continue + if old_label is not None and (ent not in predict_ner or predict_ner[ent] != old_label): continue + t = text + len_ent = len(ent) + while ent in t: + i = t.index(ent) + if before: + before_t[max(0, i-char_before_after_window): i] + if before not in before_t: + t = t[i + len_ent:] + continue + if after: + after_t[i+len_x: min(len_text, i+len_ent+char_before_after_window)] + if after not in after_t: + t = t[i + len_ent:] + continue + #remove simple overlap + for key in list(predict_ner.keys()): + if " "+key in ent or key+" " in ent:# or " "+ent in key or ent+" " in key: + del predict_ner[key] + pred.append((ent, label, rule_id, rule_level)) + predict_ner[ent] = label + break + d['predict_ner'] = list(predict_ner.items()) + o.write(json.dumps(d)+"\n") + for ent, label, rule_id, rule_level in list(set(pred)): + if ent not in ner or ner[ent] != label: + wrong[(ent, label, rule_id, rule_level)] = wrong.get((ent, label, rule_id, rule_level), 0) + 1 + else: + right[(ent, label, rule_id, rule_level)] = right.get((ent, label, rule_id, rule_level), 0) + 1 + return right, wrong + + +if __name__ == "__main__": + rulebase = [([ + ("AGE", re.compile("\S+ years old|\S+\-years\-old|\S+ year old|\S+\-year\-old"), None, None, None), + ("STREET_ADDRESS", re.compile( + '\d{1,4} [\w\s]{1,20} (?:street|st|avenue|ave|road|rd|highway|hwy|square|sq|trail|trl|drive|dr|court|ct|park|parkway|pkwy|circle|cir|boulevard|blvd)\W?(?=\s|$)'), None, None, None), + ("STREET_ADDRESS", re.compile('\b\d{5}(?:[-\s]\d{4})?\b'), None, None, None), + ("STREET_ADDRESS", re.compile('P\.? ?O\.? Box \d+'), None, None, None), + ("GOVT_ID", re.compile( + '(?!000|666|333)0*(?:[0-6][0-9][0-9]|[0-7][0-6][0-9]|[0-7][0-7][0-2])[- ](?!00)[0-9]{2}[- ](?!0000)[0-9]{4}'), None, None, None), + ("DISEASE", re.compile("diabetes|cancer|HIV|AIDS|Alzheimer's|Alzheimer|heart disease"), None, None, None), + ("NORP", re.compile("upper class|middle class|working class|lower class"), None, None, None), + ], 1), + ] + + initial = target_lang = None + if "-initial" in sys.argv: + initial = sys.argv[sys.argv.index("-initial")+1] + if "-target_lang" in sys.argv: + target_lang = sys.argv[sys.argv.index("-target_lang")+1] + if target_lang: + #TODO - load the rulebase dynamically from pii_processing.regex folder a file of the form _.py + infile = f"{target_lang}.jsonl" + outfile = "predicted_"+infile + right, wrong = apply_rules(infile, outfile, rulebase, target_lang, char_before_after_window=10) + print ('right', right) + print ('wrong', wrong) + #json.dump(right, open(f"right_regex_{target_lang}.json", "w", encoding="utf8"), indent=1) + #json.dump(wrong, open(f"wrong_regex_{target_lang}.json", "w", encoding="utf8"), indent=1) diff --git a/data_tooling/pii_processing/misc/translate_with_ner.py b/data_tooling/pii_processing/misc/translate_with_ner.py new file mode 100644 index 0000000..8cfaaf4 --- /dev/null +++ b/data_tooling/pii_processing/misc/translate_with_ner.py @@ -0,0 +1,2615 @@ +# coding=utf-8 +# Copyright, 2021 Ontocord, LLC, All rights reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +from datasets import load_dataset +import os +import re +import itertools +from re import finditer +import glob +import random +import fsspec +import json +from random import randint, choice +from collections import Counter +import spacy, itertools +import langid +from nltk.corpus import stopwords +import fsspec, os, gzip +from faker import Faker +from faker.providers import person, company, geo, address, ssn +from transformers import M2M100ForConditionalGeneration, M2M100Tokenizer, MarianMTModel, AutoTokenizer, pipeline +import torch +import sys +from tqdm import tqdm + +stopwords_en = set(stopwords.words('english')) + +junk_dict = dict([(a, 1) for a in "' 0123456789¯_§½¼¾×|†—~\"—±′–'°−{}[]·-\'?,./<>!@#^&*()+-‑=:;`→¶'"]) + +# from https://github.com/madisonmay/CommonRegex/blob/master/commonregex.py which is under the MIT License +# Phone is not working. email is not working? +basic_regex = [ + ("EMAIL_ADDRESS", re.compile( + "([a-z0-9!#$%&'*+\/=?^_`{|.}~-]+@(?:[a-z0-9](?:[a-z0-9-]*[a-z0-9])?\.)+[a-z0-9](?:[a-z0-9-]*[a-z0-9])?)")), + ("AGE", re.compile("\S+ years old|\S+\-years\-old|\S+ year old|\S+\-year\-old")), + # ("PHONE_NUMBER" , re.compile('((?:(?') + return re.sub(clean, '', text) + + +def camel_case_split(identifier): + matches = finditer('.+?(?:(?<=[a-z])(?=[A-Z])|(?<=[A-Z])(?=[A-Z][a-z])|$)', identifier) + return [m.group(0) for m in matches] + + +def stem(s): + s = s.replace(".", " ").replace("!", " ").replace("?", " ").replace(",", " ").replace("-", " ").replace(";", + " ").replace( + "'", " '").replace("\"", " \"") + sArr = s.lower().split() + if len(sArr) > 4: + sArr = sArr[:4] + s = " ".join([s1[:4] if len(s1) > 4 else s1 for s1 in sArr if s1.strip()]) + return s + + +def save_enron_line(l2, prev, o): + """ Process Enron Data """ + l2 = remove_html_tags(l2) + l2 = l2.split('-----Original Message-----')[0].strip() + l2 = l2.split('---------------------- Forwarded')[0].strip() + l2 = l2.split('----- Forwarded')[0].strip() + l2 = l2.split('---------From:')[0].strip() + l2 = l2.split('**********************************************************************This')[0].strip() + l2 = l2.split('********************************************************************** This')[0].strip() + l2 = l2.split('******************************************************************This')[0].strip() + l2 = l2.split('*************************************************This')[0].strip() + l2 = l2.split('********************************************************************** This')[0].strip() + l2 = l2.split('--------- Inline attachment follows')[0].strip() + l2 = l2.split('The information contained in this e-mail message and')[0].strip() + l2 = l2.split('This message is for the designated recipient')[0].strip() + l2 = l2.split('***Please be advised')[0].strip() + l2 = l2.split('*******This message')[0].strip() + l2 = l2.split('This message (including any attachments) contains')[0].strip() + l2 = l2.split('*********************************************************')[0].strip() + l2 = l2.split('_________________________________________________________________Get')[0].strip() + l2 = l2.split('___________________________________________')[0].strip() + l2 = l2.split('__________________________________________________ Do')[0].strip() + l2 = l2.replace("\\\"", " \" ").replace("(", " (").replace(")", ") ").replace("[", " [").replace("]", "] ").replace( + "?", "? ").replace("!", "! ").replace("? ?", "??").replace("! !", "!!").replace(":", ": ").replace("\t", + " ").replace( + "= ", "").replace("=20", "").replace("=90", "").replace("=018", "").replace("=09", "").replace("=3D", "") + l2 = l2.replace(" s ", " 's ").replace(" ve ", " 've ").replace(" re ", " 're ").replace(" ll ", " 'll ").replace( + " m ", " 'm ").replace(" t ", " 't ").replace(" d ", " 'd ").replace(" ", " ").replace(" ", " ").replace(" ", + " ").replace( + " ", " ").replace(" ", " ").replace(" ", " ").replace(" ", " ").replace(". . .", "...") + l2 = l2.replace(". yahoo", ".yahoo").replace("www. ", "www.").replace(". htm", ".htm").replace(". co", + ".co").replace( + ". org", ".org").replace(". edu", ".edu").replace(". net", ".net").replace(". NET", ".NET").replace(". CO", + ".CO").replace( + ". ORG", ".ORG").replace(". EDU", ".EDU").replace(": //", "://") + l2 = l2.replace(": 0", ":0").replace(": 1", ":1").replace(": 2", ":2").replace(": 3", ":3").replace(": 4", + ":4").replace( + ": 5", ":5").replace(": 6", ":6").replace(": 7", ":7").replace(": 8", ":8").replace(": 9", ":9") + l2 = l2.replace(". url -", ".url - <<").replace(". doc -", ".doc - <<").replace(". pdf -", ".pdf <<").replace( + ". xls -", ".xls <<").replace(". url", ".url>>").replace(". doc", ".doc>>").replace(". pdf", ".pdf>>").replace( + ". xls", ".xls>>").replace("<< ", "<<").replace("> >", " ").replace(" ", " ") + l2 = l2.replace(". URL -", ".URL - <<").replace(". DOC -", ".DOC - <<").replace(". PDF -", ".PDF <<").replace( + ". XLS -", ".xls <<").replace(". URL", ".URL>>").replace(". DOC", ".DOC>>").replace(". PDF", ".PDF>>").replace( + ". XLS", ".XLS>>").replace("<< ", "<<").replace("> >", " ").replace(" ", " ") + l2 = l2.replace("RE:", "").replace("Re:", "").replace("RE: ", "").replace("Re: ", "").replace("Fw: ", "").replace( + "FW: ", "").replace("FWD: ", "").replace("Fwd: ", "") + l2 = l2.replace('Importance: High', ':') + if "Sent:" in l2: return + l2 = l2.replace("...", "... ").replace("\"\"", " \" ").replace(" ", " ").strip(" -:;[]()\=<>\"").rstrip(".!?") + l2Arr = l2.split() + if len(l2Arr) > 3: + l2 = " ".join(itertools.chain(*[camel_case_split(a) for a in l2Arr])) + if l2.replace(":", "").replace("[", "").replace("]", "").replace(".", "").replace("!", "").replace("?", + "").replace( + ",", "").replace("-", "").replace(";", "").replace(" ", "").lower() in prev: return + l2 = l2.replace("==", "--") + l2 = l2.replace("++", "--") + l2 = l2.replace("*~", "--") + l2 = l2.replace("||", "--") + l2 = l2.replace("**", "--") + l2 = l2.replace("__", "--") + l2 = l2.replace("##", "--") + for l3 in l2.split('--'): + l3 = l3.strip() + if l3: + for l4 in l3.split("Subject: "): + l4 = l4.strip('=, ') + if l4: o.write(l4 + "\tenron\n") + prev[l2.replace(":", "").replace("[", "").replace("]", "").replace(".", "").replace("!", "").replace("?", + "").replace( + ",", "").replace("-", "").replace(";", "").replace(" ", "").lower()] = 1 + + +def has_any(s, lst): + for l in lst: + if l in s: return True + return False + + +def create_english_dataset(share_dir='/content/drive/Shareddrives/BigScience/'): + """ + Creates a English dataset from different domains useful for doing PII detection. + Domains include enron (email), a subset of civil comments (forum message) + We do some deduplication and cleanup. + We add some PII as augumentation (TBD: some and tags added. Need to add some more categories). + See specific licenses for each dataset. + """ + + prev = {} + if not os.path.exists("cleaned_english.tsv"): + with open("english.tsv", "w", encoding="utf8") as o: + + # https://github.com/reglab/casehold court cases are government works and in the public domain. + # Annotations and selections are under Apache-2.0 License + """ + @inproceedings{zhengguha2021, + title={When Does Pretraining Help? Assessing Self-Supervised Learning for Law and the CaseHOLD Dataset}, + author={Lucia Zheng and Neel Guha and Brandon R. Anderson and Peter Henderson and Daniel E. Ho}, + year={2021}, + eprint={2104.08671}, + archivePrefix={arXiv}, + primaryClass={cs.CL}, + booktitle={Proceedings of the 18th International Conference on Artificial Intelligence and Law}, + publisher={Association for Computing Machinery} + } + """ + with open(f"{share_dir}/casehold.csv", "rb") as f: + while True: + line = f.readline().decode() + if not line: break + line = line.split(",\"") + if len(line) >= 2: + line = line[1] + line = line.split("()") + if len(line) == 2: + s1, s2 = line + s1 = s1.replace(" ", " ").replace(" ", " ") + s2 = s2.replace(" ", " ").replace(" ", " ") + s2 = ' '.join(s2.split(',')[:-6]).strip(';: ') + if s2: + o.write(s1 + ' HOLDING: ' + s2 + "\tcasehold\n") + else: + o.write(s1 + "\tcasehold\n") + else: + s1 = s1.replace(" ", " ").replace(" ", " ") + o.write(s1 + "\tcasehold\n") + + # from https://www.kaggle.com/wcukierski/enron-email-dataset, originally from https://www.cs.cmu.edu/~enron/ + # public data and partially copyrighted works (annotations) used by permission of authors + """ + Public record data origially published by www.ferc.gov. Subsequent data cleansing by the authors and released + "as a resource for researchers who are interested in improving current email tools, or understanding how email is currently used". + """ + with open(f"{share_dir}/kaggle_enron_emails.csv", "rb") as f: + in_message = False + l2 = "" + while True: + l = f.readline() + if not l: break + l = l.decode().strip() + if not in_message and l.startswith("Subject:"): + l = l.replace("Subject:", "").strip() + if l: l2 = l + ":" + if "X-FileName" in l: + in_message = True + continue + elif "Message-ID" in l: + save_enron_line(l2, prev, o) + l2 = "" + in_message = False + if in_message: + l2 += " " + l + + if l2: + save_enron_line(l2, prev, o) + + # https://huggingface.co/datasets/civil_comments - CC0 + """ + @article{DBLP:journals/corr/abs-1903-04561, + author = {Daniel Borkan and + Lucas Dixon and + Jeffrey Sorensen and + Nithum Thain and + Lucy Vasserman}, + title = {Nuanced Metrics for Measuring Unintended Bias with Real Data for Text + Classification}, + journal = {CoRR}, + volume = {abs/1903.04561}, + year = {2019}, + url = {http://arxiv.org/abs/1903.04561}, + archivePrefix = {arXiv}, + eprint = {1903.04561}, + timestamp = {Sun, 31 Mar 2019 19:01:24 +0200}, + biburl = {https://dblp.org/rec/bib/journals/corr/abs-1903-04561}, + bibsource = {dblp computer science bibliography, https://dblp.org} +} + """ + # An experiment we could try is tagging with another public figure tag called PUBLIC_FIGURE_OPINION + # so that we could train a model to distinguish between public figure mentions in opinion domains vs non-opinion domains + + dataset = load_dataset("civil_comments") + for d in (dataset['train'],): + for idx, data in enumerate(d): + score = sum([data[feature] for feature in + ['toxicity', 'severe_toxicity', 'obscene', 'threat', 'insult', 'identity_attack', + 'sexual_explicit']]) + l2 = data['text'] + l2 = l2.replace("\n", " ").replace(" ", " ").replace(" ", " ") + l2Arr = l2.split() + has_a_name = has_any(first_names, l2Arr) + l2_lower = l2.lower() + if random.choice([0, + 1]) and not has_a_name and "mr." not in l2_lower and "ms." not in l2_lower and "mrs." not in l2_lower and "president" not in l2_lower and "governor" not in l2_lower and "mayor" not in l2_lower: + continue + if len(l2Arr) > 10 and len(l2Arr) < 50 and (score <= 0.5 or random.randint(0, + 10) == 0): # having too much toxic content may skew the data + if has_a_name or "mr." in l2_lower or "ms." in l2_lower or "mrs." in l2_lower or "senator" in l2_lower or "president" in l2_lower or "governor" in l2_lower or "mayor" in l2_lower: + o.write(l2 + "\tcivil_comments\n") + + os.system("sort --parallel=32 english.tsv -o english.tsv") + + with open("english_cleaned.tsv", "w", encoding="utf8") as o: + with open("english.tsv", "rb") as f: + prev = "" + while True: + l = f.readline().decode() + if not l: break + l = l.strip() + l2 = l.replace(":", "").replace("[", "").replace("]", "").replace(".", "").replace("!", "").replace("?", + "").replace( + ",", "").replace("-", "").replace(";", "").replace(" ", "").lower() + prev2 = prev.replace(":", "").replace("[", "").replace("]", "").replace(".", "").replace("!", + "").replace( + "?", "").replace(",", "").replace("-", "").replace(";", "").replace(" ", "").lower() + if prev != "" and (l2 == prev2 or (len(prev) > 10 and len(l) > 10 and prev2[:10] == l2[:10])): + if len(l) > len(prev): + prev = l + continue + else: + if prev: + if prev[0] < 'וח': + o.write(prev.lstrip(':;.+- ') + "\n") + prev = l + if prev: + if prev[0] < 'וח': + o.write(prev.lstrip(':;.+- ') + "\n") + + os.system("sort --parallel=32 english_cleaned.tsv -o english_cleaned.tsv") + os.system(f"cp english_cleaned.tsv {share_dir}/english_cleaned.tsv") + + +def check_good_sentence(s, en_lang_cutoff=0.1, junk_ratio=0.5, stopword_check=True): + # basic dejunk + s = s.lower().strip() + if not s: return False + jr = len([s2 for s2 in s if s2 in junk_dict]) / len(s) + if jr >= junk_ratio: + return False + sArr = [s2.strip("' 0123456789¯_§½¼¾×|†—~\"—±′–'°−{}[]·-\'?,./<>!@#^&*()+-‑=:;`→¶'") for s2 in s.lower().split()] + if len(sArr) == 0: + return False + # stopword check + if stopword_check and len([s2 for s2 in sArr if s2 in stopwords_en]) / len(sArr) < en_lang_cutoff: + return False + else: + # langid check + try: + lang = langid.classify(s)[0] + except: + lang = "" + return lang == "en" + + +def create_oscar_subset_for_ner(): + with open("pii_oscar.txt", "w", encoding="utf8") as o: + with open("oscar_sample.txt", "rb") as f: + while True: + sent = f.readline().decode() + if not sent: break + sent = sent.strip() + for sent2 in sent.split("<|endoftext|>"): + sent2 = sent2.strip() + sentArr = sent2.split() + if len(sentArr) > 150: + # print ("truncating sent", sent) + sent2 = " ".join(sentArr[:150]) + if "Alzheimer's" in sent2 or "Alzheimer" in sent2 or 'heart disease' in sent2 or ' AIDS ' in sent2 or ' HIV ' in sent2 or ' was born ' in sent2 or 'Social Secu' in sent2 or 'socialist' in sent2 or 'republican' in sent2 or 'democrat' in sent2 or 'lower class' in sent2 or ' union ' in sent2 or 'upper class' in sent2 or 'middle class' in sent2 or ' cancer ' in sent2: + if 'pussy' not in sent2 and ' cock ' not in sent2: + o.write(sent2 + "\n") + url = _get_oscar_urls("en")[0] + _download_urls([url]) + file = url.split("/")[-1] + for sent2 in gzip.open(file): + sent2 = sent2.decode() + sent2 = sent2.strip() + sentArr = sent2.split() + if len(sentArr) > 150: + sent2 = " ".join(sentArr[:150]) + # let's just look for disease age, for the bigger set, since terms like "republic" and "democract" are over represented + if "Alzheimer's" in sent2 or "Alzheimer" in sent2 or 'heart disease' in sent2 or ' AIDS ' in sent2 or ' HIV ' in sent2 or ' was born ' in sent2 or ' cancer ' in sent2: + if not check_good_sentence(sent2): + continue + if 'pussy' not in sent2 and ' cock ' not in sent2: + o.write(sent2 + "\n") + os.system("sort --parallel=32 pii_oscar.txt -o pii_oscar.txt") + + +def do_ner(do_casehold=False): + """ Create English based NER/PII dataset """ + faker_target_lang = Faker(faker_map["en"]) + faker_target_lang.add_provider(person) + faker_target_lang.add_provider(ssn) + faker_target_lang.add_provider(address) + nlp = spacy.load('en_core_web_lg') + row_id = 0 + with open("pii_en.jsonl", "w", encoding="utf8") as o: + + with open("pii_oscar.txt", "rb") as f: + prev = "" + for sent2 in tqdm(f): + # sent2 = f.readline().decode().strip() + sent2 = sent2.decode().strip() + if not sent2: break + domain = "oscar" + if sent2 == prev: + continue + if prev: + sent3 = prev + if sent3[0] in "0123456789": + sent3 = sent3.split(" ", 1)[1] + sentArr = sent3.split() + if sentArr[0].endswith(":"): + sentArr = sentArr[:1] + if len(sentArr) > 100: + sentArr = sentArr[:100] + sent3 = " ".join(sentArr) + if True: + doc = nlp(sent3) + entities = list(doc.ents) + if [entity for entity in entities if entity.label_ == 'PERSON']: + ents = [[entity.text, entity.label_] for entity in entities if + entity.label_ in ('PERSON', 'GPE', 'ORG', 'NORP') and 'http:' not in entity.text] + swap = False + for label, regex in basic_regex: + for x in regex.findall(sent3): + if type(x) != str: continue + ents.append([x, label]) + if label in ('GOVT_ID', 'STREET_ADDRESS',): + swap = True + if len(ents) > 1 or 'cancer' in sent3 or 'class' in sent3 or 'union' in sent3 or 'democrat' in sent3 or 'republican' in sent3 or 'socialist' in sent3: + if len(ents) < 5: + if swap or '@' in sent3 or 'Social Sec' in sent3 or 'password' in sent3: + context = {} + ents2 = [] + for item in ents: + if item[1] in ('GOVT_ID', 'STREET_ADDRESS', 'PERSON'): + if item[0] in public_figures: + item[1] = 'PUBLIC_FIGURE' + else: + context[item[0]] = context.get(item[0], \ + faker_target_lang.name() if " " in + item[ + 0] and + item[ + 1] == 'PERSON' else \ + faker_target_lang.first_name() if + item[1] == 'PERSON' else \ + faker_target_lang.ssn() if + item[1] == 'GOVT_ID' else \ + faker_target_lang.address() if + item[ + 1] == 'STREET_ADDRESS' else \ + item[0]) + if " " in item[0]: + context[item[0].split()[0]] = context[item[0]].split()[0] + context[item[0].split()[-1]] = context[item[0]].split()[-1] + item[0] = context[item[0]] + ents2.append(item) + else: + ents2 = ents + o.write(json.dumps( + {"text": sent3, "ner": ents2, "domain": domain, "target_lang": "en", + "id": row_id}) + "\n") + row_id += 1 + prev = sent2 + + with open("english_cleaned.tsv", "rb") as f: + # while True: + # l = f.readline().decode() + # if not l: break + for l in tqdm(f): + # sent2 = f.readline().decode().strip() + l = l.decode().strip() + l = l.split("\t") + sent = l[0] + domain = l[-1].strip() + if not check_good_sentence(sent): + continue + if not do_casehold and domain == "casehold": continue + if "Notice No." in sent: continue + if "TO: ALL COMEX" in sent: continue + if "TO: All NYMEX" in sent: continue + if "TO: All New" in sent: continue + if sent[0] in "0123456789": + sent = sent.split(" ", 1)[1] + sentArr = sent.split() + if sentArr[0].endswith(":"): + sentArr = sentArr[:1] + if len(sentArr) > 100: + sentArr = sentArr[:100] + sent = " ".join(sentArr) + doc = nlp(sent) + entities = list(doc.ents) + + if [entity for entity in entities if entity.label_ == 'PERSON']: + ents = [[entity.text, entity.label_] for entity in entities if + entity.label_ in ('PERSON', 'GPE', 'ORG', 'NORP') and 'http:' not in entity.text] + swap = False + for label, regex in basic_regex: + for x in regex.findall(sent): + if type(x) != str: continue + ents.append([x, label]) + if label in ('GOVT_ID', 'STREET_ADDRESS',): + swap = True + if len(ents) > 1 and len(ents) < 5: + if swap or random.randint(0, + 1) == 0 or '@' in sent or 'Social Sec' in sent or 'password' in sent: + context = {} + ents2 = [] + for item in ents: + if item[1] in ('GOVT_ID', 'STREET_ADDRESS', 'PERSON'): + if item[0] in public_figures: + item[1] = 'PUBLIC_FIGURE' + else: + context[item[0]] = context.get(item[0], \ + faker_target_lang.name() if " " in item[0] and + item[ + 1] == 'PERSON' else \ + faker_target_lang.first_name() if item[ + 1] == 'PERSON' else \ + faker_target_lang.ssn() if item[ + 1] == 'GOVT_ID' else \ + faker_target_lang.address() if item[ + 1] == 'STREET_ADDRESS' else \ + item[0]) + sent = sent.replace(item[0], context[item[0]]) + if " " in item[0]: + context[item[0].split()[0]] = context[item[0]].split()[0] + context[item[0].split()[-1]] = context[item[0]].split()[-1] + item[0] = context[item[0]] + ents2.append(item) + else: + ents2 = ents + o.write(json.dumps( + {"text": sent, "ner": ents2, "domain": domain, "target_lang": "en", "id": row_id}) + "\n") + row_id += 1 + + +def pre_translation_steps(target_lang='hi', person_swap=True): + texts = [] + ner_mappings = [] + row_ids = [] + domains = [] + lbracket = "[" + rbracket = "]" + if target_lang in ('zh', 'ja', 'ko'): + lbracket = "[[" + rbracket = "]]" + faker_target_lang = Faker(faker_map[target_lang]) + faker_target_lang.add_provider(person) + faker_target_lang.add_provider(geo) + + row_id = -1 + for s in tqdm(open(r"pii_en.jsonl", "rb")): + s = s.decode().strip() + if not s: continue + dat = json.loads(s) + domain = dat['domain'] + ner = dat['ner'] + text = dat['text'] + if 'id' not in dat: + row_id += 1 + else: + row_id = int(dat['id']) + if 'NYMEX' in text: continue + ner = [n for n in ner if n[0] not in ("FREE", "’m", 'Social Security')] + ner2 = [] + if ' cancer ' in text: + ner2.append(['cancer', 'DISEASE']) + elif ' HIV ' in text: + ner2.append(['HIV', 'DISEASE']) + elif ' AIDS ' in text: + ner2.append(['AIDS', 'DISEASE']) + elif "Alzheimer's" in text: + ner2.append(["Alzheimer's", 'DISEASE']) + elif "Alzheimer" in text: + ner2.append(['Alzheimer', 'DISEASE']) + elif 'heart disease' in text: + ner2.append(['heart disease', 'DISEASE']) + elif 'democractic' in text: + ner2.append(['democractic', 'NORP']) + elif 'democrats' in text: + ner2.append(['democrats', 'NORP']) + elif 'Democrats' in text: + ner2.append(['Democrats', 'NORP']) + elif 'democrat' in text: + ner2.append(['democrat', 'NORP']) + elif 'Democrat' in text: + ner2.append(['Democrat', 'NORP']) + elif 'republican' in text: + ner2.append(['republican', 'NORP']) + elif 'republicans' in text: + ner2.append(['republicans', 'NORP']) + elif 'Republicans' in text: + ner2.append(['Republicans', 'NORP']) + elif 'republican' in text: + ner2.append(['republican', 'NORP']) + elif 'Republican' in text: + ner2.append(['Republican', 'NORP']) + elif 'socialist' in text: + ner2.append(['socialist', 'NORP']) + elif 'Socialist' in text: + ner2.append(['Socialist', 'NORP']) + for item in ner: + itemArr = item[0].split() + if itemArr[0] in ('Association', 'Society', 'Union') or itemArr[-1] in ( + 'Association', 'Society', 'Party'): + item[1] = 'NORP' + if item[0] == 'Enron': + item[0] = choice(swap_org) + text = text.replace("Enron", item[0]) + text = text.replace("@enron", '@' + item[0].lower()) + text = text.replace(" enron", ' ' + item[0].lower()) + # print (text) + if item[0] in public_figures: + item[1] = 'PUBLIC_FIGURE' + elif item[0] in country: + item[1] = 'COUNTRY' + elif item[0] in NORP: + item[1] = 'NORP' + elif '@' in item[0]: + item[1] = 'EMAIL' + ner2.append(item) + # col.extend ([d[0] for d in ner2 if d[1] == 'NORP']) + context = {} + ner_mapping = {} + seen = {} + text = "... " + text + " " + text = text.replace(lbracket, "(") + text = text.replace(rbracket, ")", ) + if person_swap: + _idx = 0 + for item in ner2: + if item[0] in seen: continue + seen[item[0]] = 1 + if item[1] in ('COUNTRY', 'GPE', 'PERSON', 'GOVT_ID', 'STREET_ADDRESS',): # ORG + text = text.replace(" " + item[0] + " ", " *" + str(_idx) + "* ") + text = text.replace(" " + item[0] + ",", " *" + str(_idx) + "* ,") + text = text.replace(" " + item[0] + "'", " *" + str(_idx) + "*'") + text = text.replace(item[0], "*" + str(_idx) + "*") + context[item[0]] = context.get(item[0], \ + faker_target_lang.first_name() + " " + random.choice( + bantu_surnames) if " " in item[0] and + item[ + 1] == 'PERSON' and target_lang in ( + 'yo', 'sw') else \ + faker_target_lang.name() if " " in item[ + 0] and item[ + 1] == 'PERSON' else \ + faker_target_lang.first_name() if + item[ + 1] == 'PERSON' else \ + faker_target_lang.country() if + item[ + 1] == 'COUNTRY' else \ + faker_target_lang.state() if + item[ + 1] == 'GPE' and target_lang != 'zh' else \ + faker_target_lang.province() if + item[ + 1] == 'GPE' and target_lang == 'zh' else \ + faker_target_lang.ssn() if + item[ + 1] == 'GOVT_ID' else \ + faker_target_lang.address() if + item[ + 1] == 'STREET_ADDRESS' else \ + item[ + 0]) + + ner_mapping["*" + str(_idx) + "*"] = [context[item[0]], + item[1] if item[ + 1] != 'COUNTRY' else 'GPE'] + if " " in item[0]: + context[item[0].split()[0]] = context[item[0]].split()[0] + context[item[0].split()[-1]] = context[item[0]].split()[-1] + item[0] = context[item[0]] + else: + text = text.replace(item[0], + ' ' + str(_idx) + " " + lbracket + item[0] + rbracket) + ner_mapping[str(_idx) + " " + lbracket] = item + _idx += 1 + + texts.append(text) + ner_mappings.append(ner_mapping) + row_ids.append(row_id) + domains.append(domain) + return texts, ner_mappings, row_ids, domains + + +def chunks(lst, n): + """Generate batches""" + for i in range(0, len(lst), n): + yield lst[i: i + n] + + +def do_translations(texts, target_lang='hi'): + model = M2M100ForConditionalGeneration.from_pretrained("facebook/m2m100_418M") + tokenizer = M2M100Tokenizer.from_pretrained("facebook/m2m100_418M") + model = model.to('cuda').half() + translations = [] + for src_text_list in tqdm(chunks(texts, 16)): + batch = tokenizer(src_text_list, return_tensors="pt", padding=True, truncation=True).to('cuda') + gen = model.generate(**batch, forced_bos_token_id=tokenizer.get_lang_id(target_lang)) + outputs = tokenizer.batch_decode(gen, skip_special_tokens=True) + translations.extend(outputs) + return translations + + +def post_translation_steps(translations, ner_mappings, row_ids, domains, target_lang='hi'): + rbracket = "]" + if target_lang in ('zh', 'ja', 'ko'): + rbracket = "]]" + with open(f"pii_{target_lang}.jsonl", "w", encoding="utf8") as o: + for index, trans_text in enumerate(translations): + ner_found = [] + trans_text = trans_text.lstrip(".") + trans_text = trans_text.strip() + trans_text = trans_text.replace("* ", "*").replace(" *", "*").replace('"0*', '*0* ').replace( + '"1*', + '*1* ').replace( + '"2*', '*2* ').replace('"3*', '*3* ').replace('"4*', '*4* '). \ + replace('*0:', '*0* ').replace('*1:', '*1* ').replace('*2:', '*2* ').replace('*3:', + '*3* ').replace( + '*4:', '*4* '). \ + replace('*0 ', '*0* ').replace('*1 ', '*1* ').replace('*2 ', '*2* ').replace('*3 ', + '*3* ').replace( + '*4 ', '*4* '). \ + replace(' 0*', '*0* ').replace(' 1*', '*1* ').replace('2 *', '*2* ').replace(' 3*', + '*3* ').replace( + ' 4*', '*4* ') + if trans_text.startswith('0') and not trans_text.startswith('0 ['): + trans_text = '*0* ' + trans_text[1:] + trans_text = trans_text.replace(". [", " [").replace(".[", " [").replace(" ", " ") + orig_trans_text = trans_text + for key, ner_item in ner_mappings[index].items(): + found = False + if key in trans_text: + found = True + elif key.replace(" ", "") in trans_text: + found = True + key = key.replace(" ", "") + elif key.lstrip('*') in trans_text: + found = True + key = key.lstrip('*') + elif key.rstrip('*') in trans_text: + found = True + key = key.rstrip('*') + if found: + if key[0] == '*': + trans_text = trans_text.replace(key, " " + ner_item[0] + " ") + ner_found.append(list(ner_item)) + else: + trans_text2 = "" + for segment in trans_text.split(key): + if rbracket in segment: + entity, rest = segment.split(rbracket, 1) + entity = entity.strip("[]") + ner_found.append([entity, ner_item[1]]) + trans_text2 += " " + entity + " " + rest + else: + trans_text2 += " " + segment + trans_text = trans_text2.strip() + trans_text = trans_text.replace("*", " ").replace("[", " ").replace("]", " ").replace( + " .", + ".").replace(" ,", + ",").replace( + " ", " ").replace(" ", " ").strip() + if target_lang in ('zh', 'ja', 'ko'): + trans_text.replace(" ", "") + trans_text.strip('#.') + if ner_found: + j = {'text': trans_text, 'ner': ner_found, 'domain': domains[index], + 'id': row_ids[index], + 'lang': target_lang} + o.write(json.dumps(j) + "\n") + +def create_light_suggestions(target_lang): + suggestions = [] + for s in tqdm(open(f"pii_{target_lang}.jsonl", "rb")): + s = s.decode().strip() + if not s: continue + dat = json.loads(s) + ner = dat['ner'] + text = dat['text'] + ner = list(set([tuple(a) for a in ner])) + for s, label in ner: + suggestions.extend([{'example_id': _id, 'start': i, 'end':i+len(s), 'tag': label, 'text': s} for i in more_itertools.locate(text, lambda s1: s1==s)]) + json.dump(suggestions, open(f"pii_{target_lang}_suggestions.json", "w", encoding="utf8")) + + +# create_english_dataset() +# create_oscar_subset_for_ner() +# do_ner() +# do_translation(target_lang="hi") +if __name__ == "__main__": + if "-target_lang" in sys.argv: + target_lang = sys.argv[sys.argv.index("-target_lang") + 1] + if target_lang == "en": + do_ner() + else: + texts, ner_mappings, row_ids, domains = pre_translation_steps(target_lang=target_lang) + translations = do_translations(texts, target_lang=target_lang) + post_translation_steps(translations, ner_mappings, row_ids, domains, target_lang=target_lang) + if "-create_light_suggestions" in sys.argv: + target_lang = sys.argv[sys.argv.index("-create_light_suggestions") + 1] + create_light_suggestions(target_lang) + diff --git a/data_tooling/pii_processing/neuralcoref/README.md b/data_tooling/pii_processing/neuralcoref/README.md new file mode 100644 index 0000000..7a2248c --- /dev/null +++ b/data_tooling/pii_processing/neuralcoref/README.md @@ -0,0 +1,302 @@ +# ✨NeuralCoref 4.0: Coreference Resolution in spaCy with Neural Networks. + +NeuralCoref is a pipeline extension for spaCy 2.1+ which annotates and resolves coreference clusters using a neural network. NeuralCoref is production-ready, integrated in spaCy's NLP pipeline and extensible to new training datasets. + +For a brief introduction to coreference resolution and NeuralCoref, please refer to our [blog post](https://medium.com/huggingface/state-of-the-art-neural-coreference-resolution-for-chatbots-3302365dcf30). +NeuralCoref is written in Python/Cython and comes with a pre-trained statistical model for **English only**. + +NeuralCoref is accompanied by a visualization client [NeuralCoref-Viz](https://github.com/huggingface/neuralcoref-viz), a web interface powered by a REST server that can be [tried online](https://huggingface.co/coref/). NeuralCoref is released under the MIT license. + +✨ Version 4.0 out now! Available on pip and compatible with SpaCy 2.1+. + +[![Current Release Version](https://img.shields.io/github/release/huggingface/neuralcoref.svg?style=flat-square)](https://github.com/huggingface/neuralcoref/releases) +[![spaCy](https://img.shields.io/badge/made%20with%20❤%20and-spaCy-09a3d5.svg)](https://spacy.io) +[![Travis-CI](https://travis-ci.org/huggingface/neuralcoref.svg?branch=master)](https://travis-ci.org/huggingface/neuralcoref) +[![NeuralCoref online Demo](https://huggingface.co/coref/assets/thumbnail-large.png)](https://huggingface.co/coref/) + +- **Operating system**: macOS / OS X · Linux · Windows (Cygwin, MinGW, Visual Studio) +- **Python version**: Python 3.6+ (only 64 bit) +- **Package managers**: [pip] + +## Install NeuralCoref + +### Install NeuralCoref with pip + +This is the easiest way to install NeuralCoref. + +```bash +pip install neuralcoref +``` + +#### `spacy.strings.StringStore size changed` error + +If you have an error mentioning `spacy.strings.StringStore size changed, may indicate binary incompatibility` when loading NeuralCoref with `import neuralcoref`, it means you'll have to install NeuralCoref from the distribution's sources instead of the wheels to get NeuralCoref to build against the most recent version of SpaCy for your system. + +In this case, simply re-install neuralcoref as follows: + +```bash +pip uninstall neuralcoref +pip install neuralcoref --no-binary neuralcoref +``` + +#### Installing SpaCy's model + +To be able to use NeuralCoref you will also need to have an English model for SpaCy. + +You can use whatever english model works fine for your application but note that the performances of NeuralCoref are strongly dependent on the performances of the SpaCy model and in particular on the performances of SpaCy model's tagger, parser and NER components. A larger SpaCy English model will thus improve the quality of the coreference resolution as well (see some details in the [Internals and Model](#-Internals-and-Model) section below). + +Here is an example of how you can install SpaCy and a (small) English model for SpaCy, more information can be found on [spacy's website](https://spacy.io/usage/models): + +```bash +pip install -U spacy +python -m spacy download en +``` + +### Install NeuralCoref from source + +You can also install NeuralCoref from sources. You will need to install the dependencies first which includes Cython and SpaCy. + +Here is the process: + +```bash +venv .env +source .env/bin/activate +git clone https://github.com/huggingface/neuralcoref.git +cd neuralcoref +pip install -r requirements.txt +pip install -e . +``` + +## Internals and Model + +NeuralCoref is made of two sub-modules: + +- a rule-based mentions-detection module which uses SpaCy's tagger, parser and NER annotations to identify a set of potential coreference mentions, and +- a feed-forward neural-network which compute a coreference score for each pair of potential mentions. + +The first time you import NeuralCoref in python, it will download the weights of the neural network model in a cache folder. + +The cache folder is set by defaults to `~/.neuralcoref_cache` (see [file_utils.py](./neuralcoref/file_utils.py)) but this behavior can be overided by setting the environment variable `NEURALCOREF_CACHE` to point to another location. + +The cache folder can be safely deleted at any time and the module will download again the model the next time it is loaded. + +You can have more information on the location, downloading and caching process of the internal model by activating python's `logging` module before loading NeuralCoref as follows: + +```python +import logging; +logging.basicConfig(level=logging.INFO) +import neuralcoref +>>> INFO:neuralcoref:Getting model from https://s3.amazonaws.com/models.huggingface.co/neuralcoref/neuralcoref.tar.gz or cache +>>> INFO:neuralcoref.file_utils:https://s3.amazonaws.com/models.huggingface.co/neuralcoref/neuralcoref.tar.gz not found in cache, downloading to /var/folders/yx/cw8n_njx3js5jksyw_qlp8p00000gn/T/tmp_8y5_52m +100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 40155833/40155833 [00:06<00:00, 6679263.76B/s] +>>> INFO:neuralcoref.file_utils:copying /var/folders/yx/cw8n_njx3js5jksyw_qlp8p00000gn/T/tmp_8y5_52m to cache at /Users/thomaswolf/.neuralcoref_cache/f46bc05a4bfba2ae0d11ffd41c4777683fa78ed357dc04a23c67137abf675e14.7d6f9a6fecf5cf09e74b65f85c7d6896b21decadb2554d486474f63b95ec4633 +>>> INFO:neuralcoref.file_utils:creating metadata file for /Users/thomaswolf/.neuralcoref_cache/f46bc05a4bfba2ae0d11ffd41c4777683fa78ed357dc04a23c67137abf675e14.7d6f9a6fecf5cf09e74b65f85c7d6896b21decadb2554d486474f63b95ec4633 +>>> INFO:neuralcoref.file_utils:removing temp file /var/folders/yx/cw8n_njx3js5jksyw_qlp8p00000gn/T/tmp_8y5_52m +>>> INFO:neuralcoref:extracting archive file /Users/thomaswolf/.neuralcoref_cache/f46bc05a4bfba2ae0d11ffd41c4777683fa78ed357dc04a23c67137abf675e14.7d6f9a6fecf5cf09e74b65f85c7d6896b21decadb2554d486474f63b95ec4633 to dir /Users/thomaswolf/.neuralcoref_cache/neuralcoref +``` + +## Loading NeuralCoref + +### Adding NeuralCoref to the pipe of an English SpaCy Language + +Here is the recommended way to instantiate NeuralCoref and add it to SpaCY's pipeline of annotations: + +```python + +# Load your usual SpaCy model (one of SpaCy English models) +import spacy +nlp = spacy.load('en') + +# Add neural coref to SpaCy's pipe +import neuralcoref +neuralcoref.add_to_pipe(nlp) + +# You're done. You can now use NeuralCoref as you usually manipulate a SpaCy document annotations. +doc = nlp(u'My sister has a dog. She loves him.') + +doc._.has_coref +doc._.coref_clusters +``` + +### Loading NeuralCoref and adding it manually to the pipe of an English SpaCy Language + +An equivalent way of adding NeuralCoref to a SpaCy model pipe is to instantiate the NeuralCoref class first and then add it manually to the pipe of the SpaCy Language model. + +```python + +# Load your usual SpaCy model (one of SpaCy English models) +import spacy +nlp = spacy.load('en') + +# load NeuralCoref and add it to the pipe of SpaCy's model +import neuralcoref +coref = neuralcoref.NeuralCoref(nlp.vocab) +nlp.add_pipe(coref, name='neuralcoref') + +# You're done. You can now use NeuralCoref the same way you usually manipulate a SpaCy document and it's annotations. +doc = nlp(u'My sister has a dog. She loves him.') + +doc._.has_coref +doc._.coref_clusters +``` + +## Using NeuralCoref + +NeuralCoref will resolve the coreferences and annotate them as [extension attributes](https://spacy.io/usage/processing-pipelines#custom-components-extensions) in the spaCy `Doc`, `Span` and `Token` objects under the `._.` dictionary. + +Here is the list of the annotations: + +| Attribute | Type | Description +|---------------------------|--------------------|----------------------------------------------------- +|`doc._.has_coref` |boolean |Has any coreference has been resolved in the Doc +|`doc._.coref_clusters` |list of `Cluster` |All the clusters of corefering mentions in the doc +|`doc._.coref_resolved` |unicode |Unicode representation of the doc where each corefering mention is replaced by the main mention in the associated cluster. +|`doc._.coref_scores` |Dict of Dict |Scores of the coreference resolution between mentions. +|`span._.is_coref` |boolean |Whether the span has at least one corefering mention +|`span._.coref_cluster` |`Cluster` |Cluster of mentions that corefer with the span +|`span._.coref_scores` |Dict |Scores of the coreference resolution of & span with other mentions (if applicable). +|`token._.in_coref` |boolean |Whether the token is inside at least one corefering mention +|`token._.coref_clusters` |list of `Cluster` |All the clusters of corefering mentions that contains the token + +A `Cluster` is a cluster of coreferring mentions which has 3 attributes and a few methods to simplify the navigation inside a cluster: + +| Attribute or method | Type / Return type | Description +|------------------------|---------------------|----------------------------------------------------- +|`i` |int |Index of the cluster in the Doc +|`main` |`Span` |Span of the most representative mention in the cluster +|`mentions` |list of `Span` |List of all the mentions in the cluster +|`__getitem__` |return `Span` |Access a mention in the cluster +|`__iter__` |yields `Span` |Iterate over mentions in the cluster +|`__len__` |return int |Number of mentions in the cluster + +### Navigating the coreference cluster chains + +You can also easily navigate the coreference cluster chains and display clusters and mentions. + +Here are some examples, try them out to test it for yourself. + +```python +import spacy +import neuralcoref +nlp = spacy.load('en') +neuralcoref.add_to_pipe(nlp) + +doc = nlp(u'My sister has a dog. She loves him') + +doc._.coref_clusters +doc._.coref_clusters[1].mentions +doc._.coref_clusters[1].mentions[-1] +doc._.coref_clusters[1].mentions[-1]._.coref_cluster.main + +token = doc[-1] +token._.in_coref +token._.coref_clusters + +span = doc[-1:] +span._.is_coref +span._.coref_cluster.main +span._.coref_cluster.main._.coref_cluster +``` + +**Important**: NeuralCoref mentions are spaCy [Span objects](https://spacy.io/api/span) which means you can access all the usual [Span attributes](https://spacy.io/api/span#attributes) like `span.start` (index of the first token of the span in the document), `span.end` (index of the first token after the span in the document), etc... + +Ex: `doc._.coref_clusters[1].mentions[-1].start` will give you the index of the first token of the last mention of the second coreference cluster in the document. + +## Parameters + +You can pass several additional parameters to `neuralcoref.add_to_pipe` or `NeuralCoref()` to control the behavior of NeuralCoref. + +Here is the full list of these parameters and their descriptions: + +| Parameter | Type | Description +|-----------------|-------------------------|---------------- +|`greedyness` |float |A number between 0 and 1 determining how greedy the model is about making coreference decisions (more greedy means more coreference links). The default value is 0.5. +|`max_dist` |int |How many mentions back to look when considering possible antecedents of the current mention. Decreasing the value will cause the system to run faster but less accurately. The default value is 50. +|`max_dist_match` |int |The system will consider linking the current mention to a preceding one further than `max_dist` away if they share a noun or proper noun. In this case, it looks `max_dist_match` away instead. The default value is 500. +|`blacklist` |boolean |Should the system resolve coreferences for pronouns in the following list: `["i", "me", "my", "you", "your"]`. The default value is True (coreference resolved). +|`store_scores` |boolean |Should the system store the scores for the coreferences in annotations. The default value is True. +|`conv_dict` |dict(str, list(str)) |A conversion dictionary that you can use to replace the embeddings of *rare words* (keys) by an average of the embeddings of a list of *common words* (values). Ex: `conv_dict={"Angela": ["woman", "girl"]}` will help resolving coreferences for `Angela` by using the embeddings for the more common `woman` and `girl` instead of the embedding of `Angela`. This currently only works for single words (not for words groups). + +### How to change a parameter + +```python +import spacy +import neuralcoref + +# Let's load a SpaCy model +nlp = spacy.load('en') + +# First way we can control a parameter +neuralcoref.add_to_pipe(nlp, greedyness=0.75) + +# Another way we can control a parameter +nlp.remove_pipe("neuralcoref") # This remove the current neuralcoref instance from SpaCy pipe +coref = neuralcoref.NeuralCoref(nlp.vocab, greedyness=0.75) +nlp.add_pipe(coref, name='neuralcoref') +``` + +### Using the conversion dictionary parameter to help resolve rare words + +Here is an example on how we can use the parameter `conv_dict` to help resolving coreferences of a rare word like a name: + +```python +import spacy +import neuralcoref + +nlp = spacy.load('en') + +# Let's try before using the conversion dictionary: +neuralcoref.add_to_pipe(nlp) +doc = nlp(u'Deepika has a dog. She loves him. The movie star has always been fond of animals') +doc._.coref_clusters +doc._.coref_resolved +# >>> [Deepika: [Deepika, She, him, The movie star]] +# >>> 'Deepika has a dog. Deepika loves Deepika. Deepika has always been fond of animals' +# >>> Not very good... + +# Here are three ways we can add the conversion dictionary +nlp.remove_pipe("neuralcoref") +neuralcoref.add_to_pipe(nlp, conv_dict={'Deepika': ['woman', 'actress']}) +# or +nlp.remove_pipe("neuralcoref") +coref = neuralcoref.NeuralCoref(nlp.vocab, conv_dict={'Deepika': ['woman', 'actress']}) +nlp.add_pipe(coref, name='neuralcoref') +# or after NeuralCoref is already in SpaCy's pipe, by modifying NeuralCoref in the pipeline +nlp.get_pipe('neuralcoref').set_conv_dict({'Deepika': ['woman', 'actress']}) + +# Let's try agin with the conversion dictionary: +doc = nlp(u'Deepika has a dog. She loves him. The movie star has always been fond of animals') +doc._.coref_clusters +# >>> [Deepika: [Deepika, She, The movie star], a dog: [a dog, him]] +# >>> 'Deepika has a dog. Deepika loves a dog. Deepika has always been fond of animals' +# >>> A lot better! +``` + +## Using NeuralCoref as a server + +A simple example of server script for integrating NeuralCoref in a REST API is provided as an example in [`examples/server.py`](examples/server.py). + +To use it you need to install falcon first: + +```bash +pip install falcon +``` + +You can then start the server as follows: + +```bash +cd examples +python ./server.py +``` + +And query the server like this: + +```bash +curl --data-urlencode "text=My sister has a dog. She loves him." -G localhost:8000 +``` + +There are many other ways you can manage and deploy NeuralCoref. Some examples can be found in [spaCy Universe](https://spacy.io/universe/). + +## Re-train the model / Extend to another language + +If you want to retrain the model or train it on another language, see our [training instructions](./neuralcoref/train/training.md) as well as our [blog post](https://medium.com/huggingface/how-to-train-a-neural-coreference-model-neuralcoref-2-7bb30c1abdfe) diff --git a/data_tooling/pii_processing/neuralcoref/__init__.pxd b/data_tooling/pii_processing/neuralcoref/__init__.pxd new file mode 100644 index 0000000..e69de29 diff --git a/data_tooling/pii_processing/neuralcoref/__init__.py b/data_tooling/pii_processing/neuralcoref/__init__.py new file mode 100644 index 0000000..f4158d2 --- /dev/null +++ b/data_tooling/pii_processing/neuralcoref/__init__.py @@ -0,0 +1,44 @@ +import os +import tarfile +import logging + +# Filter Cython warnings that would force everybody to re-compile from source (like https://github.com/numpy/numpy/pull/432). +import warnings + +warnings.filterwarnings("ignore", message="spacy.strings.StringStore size changed") + +from neuralcoref.neuralcoref import NeuralCoref +from neuralcoref.file_utils import ( + NEURALCOREF_MODEL_URL, + NEURALCOREF_MODEL_PATH, + NEURALCOREF_CACHE, + cached_path, +) + +__all__ = ["NeuralCoref", "add_to_pipe"] +__version__ = "4.1.0" + +logger = logging.getLogger(__name__) + +if os.path.exists(NEURALCOREF_MODEL_PATH) and os.path.exists( + os.path.join(NEURALCOREF_MODEL_PATH, "cfg") +): + logger.info(f"Loading model from {NEURALCOREF_MODEL_PATH}") + local_model = cached_path(NEURALCOREF_MODEL_PATH) +else: + if not os.path.exists(NEURALCOREF_MODEL_PATH): + os.makedirs(NEURALCOREF_MODEL_PATH, exist_ok=True) + logger.info(f"Getting model from {NEURALCOREF_MODEL_URL} or cache") + downloaded_model = cached_path(NEURALCOREF_MODEL_URL) + + logger.info( + f"extracting archive file {downloaded_model} to dir {NEURALCOREF_MODEL_PATH}" + ) + with tarfile.open(downloaded_model, "r:gz") as archive: + archive.extractall(NEURALCOREF_CACHE) + + +def add_to_pipe(nlp, **kwargs): + coref = NeuralCoref(nlp.vocab, **kwargs) + nlp.add_pipe(coref, name="neuralcoref") + return nlp diff --git a/data_tooling/pii_processing/neuralcoref/file_utils.py b/data_tooling/pii_processing/neuralcoref/file_utils.py new file mode 100644 index 0000000..0a26012 --- /dev/null +++ b/data_tooling/pii_processing/neuralcoref/file_utils.py @@ -0,0 +1,243 @@ +""" +Utilities for working with the local dataset cache. +This file is adapted from the AllenNLP library at https://github.com/allenai/allennlp +Copyright by the AllenNLP authors. +""" + +import json +import logging +import os +import shutil +import tempfile +from functools import wraps +from hashlib import sha256 +from io import open + +import boto3 +import requests +from botocore.exceptions import ClientError +from tqdm import tqdm + +try: + from urllib.parse import urlparse +except ImportError: + from urlparse import urlparse + +NEURALCOREF_CACHE = os.getenv( + "NEURALCOREF_CACHE", os.path.join(os.path.expanduser("~"), ".neuralcoref_cache") +) + +NEURALCOREF_MODEL_URL = ( + "https://s3.amazonaws.com/models.huggingface.co/neuralcoref/neuralcoref.tar.gz" +) +NEURALCOREF_MODEL_PATH = os.path.join(str(NEURALCOREF_CACHE), "neuralcoref") + +logger = logging.getLogger(__name__) # pylint: disable=invalid-name + + +def url_to_filename(url, etag=None): + """ + Convert `url` into a hashed filename in a repeatable way. + If `etag` is specified, append its hash to the url's, delimited + by a period. + """ + url_bytes = url.encode("utf-8") + url_hash = sha256(url_bytes) + filename = url_hash.hexdigest() + + if etag: + etag_bytes = etag.encode("utf-8") + etag_hash = sha256(etag_bytes) + filename += "." + etag_hash.hexdigest() + + return filename + + +def filename_to_url(filename, cache_dir=None): + """ + Return the url and etag (which may be ``None``) stored for `filename`. + Raise ``EnvironmentError`` if `filename` or its stored metadata do not exist. + """ + if cache_dir is None: + cache_dir = NEURALCOREF_CACHE + + cache_path = os.path.join(cache_dir, filename) + if not os.path.exists(cache_path): + raise EnvironmentError(f"file {cache_path} not found") + + meta_path = cache_path + ".json" + if not os.path.exists(meta_path): + raise EnvironmentError(f"file {meta_path} not found") + + with open(meta_path, encoding="utf-8") as meta_file: + metadata = json.load(meta_file) + url = metadata["url"] + etag = metadata["etag"] + + return url, etag + + +def cached_path(url_or_filename, cache_dir=None): + """ + Given something that might be a URL (or might be a local path), + determine which. If it's a URL, download the file and cache it, and + return the path to the cached file. If it's already a local path, + make sure the file exists and then return the path. + """ + if cache_dir is None: + cache_dir = NEURALCOREF_CACHE + + parsed = urlparse(url_or_filename) + + if parsed.scheme in ("http", "https", "s3"): + # URL, so get it from the cache (downloading if necessary) + return get_from_cache(url_or_filename, cache_dir) + elif os.path.exists(url_or_filename): + # File, and it exists. + return url_or_filename + elif parsed.scheme == "": + # File, but it doesn't exist. + raise EnvironmentError(f"file {url_or_filename} not found") + else: + # Something unknown + raise ValueError( + f"unable to parse {url_or_filename} as a URL or as a local path" + ) + + +def split_s3_path(url): + """Split a full s3 path into the bucket name and path.""" + parsed = urlparse(url) + if not parsed.netloc or not parsed.path: + raise ValueError(f"bad s3 path {url}") + bucket_name = parsed.netloc + s3_path = parsed.path + # Remove '/' at beginning of path. + if s3_path.startswith("/"): + s3_path = s3_path[1:] + return bucket_name, s3_path + + +def s3_request(func): + """ + Wrapper function for s3 requests in order to create more helpful error + messages. + """ + + @wraps(func) + def wrapper(url, *args, **kwargs): + try: + return func(url, *args, **kwargs) + except ClientError as exc: + if int(exc.response["Error"]["Code"]) == 404: + raise EnvironmentError(f"file {url} not found") + else: + raise + + return wrapper + + +@s3_request +def s3_etag(url): + """Check ETag on S3 object.""" + s3_resource = boto3.resource("s3") + bucket_name, s3_path = split_s3_path(url) + s3_object = s3_resource.Object(bucket_name, s3_path) + return s3_object.e_tag + + +@s3_request +def s3_get(url, temp_file): + """Pull a file directly from S3.""" + s3_resource = boto3.resource("s3") + bucket_name, s3_path = split_s3_path(url) + s3_resource.Bucket(bucket_name).download_fileobj(s3_path, temp_file) + + +def http_get(url, temp_file): + req = requests.get(url, stream=True) + content_length = req.headers.get("Content-Length") + total = int(content_length) if content_length is not None else None + progress = tqdm(unit="B", total=total) + for chunk in req.iter_content(chunk_size=1024): + if chunk: # filter out keep-alive new chunks + progress.update(len(chunk)) + temp_file.write(chunk) + progress.close() + + +def get_from_cache(url, cache_dir=None): + """ + Given a URL, look for the corresponding dataset in the local cache. + If it's not there, download it. Then return the path to the cached file. + """ + if cache_dir is None: + cache_dir = NEURALCOREF_CACHE + + if not os.path.exists(cache_dir): + os.makedirs(cache_dir) + + # Get eTag to add to filename, if it exists. + if url.startswith("s3://"): + etag = s3_etag(url) + else: + response = requests.head(url, allow_redirects=True) + if response.status_code != 200: + raise IOError( + f"HEAD request failed for url {url} with status code {response.status_code}" + ) + etag = response.headers.get("ETag") + + filename = url_to_filename(url, etag) + + # get cache path to put the file + cache_path = os.path.join(cache_dir, filename) + + if not os.path.exists(cache_path): + # Download to temporary file, then copy to cache dir once finished. + # Otherwise you get corrupt cache entries if the download gets interrupted. + with tempfile.NamedTemporaryFile() as temp_file: + logger.info("%s not found in cache, downloading to %s", url, temp_file.name) + + # GET file object + if url.startswith("s3://"): + s3_get(url, temp_file) + else: + http_get(url, temp_file) + + # we are copying the file before closing it, so flush to avoid truncation + temp_file.flush() + # shutil.copyfileobj() starts at the current position, so go to the start + temp_file.seek(0) + + logger.info("copying %s to cache at %s", temp_file.name, cache_path) + with open(cache_path, "wb") as cache_file: + shutil.copyfileobj(temp_file, cache_file) + + logger.info("creating metadata file for %s", cache_path) + meta = {"url": url, "etag": etag} + meta_path = cache_path + ".json" + with open(meta_path, "w", encoding="utf-8") as meta_file: + json.dump(meta, meta_file) + + logger.info("removing temp file %s", temp_file.name) + + return cache_path + + +def read_set_from_file(filename): + """ + Extract a de-duped collection (set) of text from a file. + Expected file format is one item per line. + """ + collection = set() + with open(filename, "r", encoding="utf-8") as file_: + for line in file_: + collection.add(line.rstrip()) + return collection + + +def get_file_extension(path, dot=True, lower=True): + ext = os.path.splitext(path)[1] + ext = ext if dot else ext[1:] + return ext.lower() if lower else ext diff --git a/data_tooling/pii_processing/neuralcoref/neuralcoref.pxd b/data_tooling/pii_processing/neuralcoref/neuralcoref.pxd new file mode 100644 index 0000000..db7adfb --- /dev/null +++ b/data_tooling/pii_processing/neuralcoref/neuralcoref.pxd @@ -0,0 +1,64 @@ +from spacy.tokens.doc cimport Doc +from spacy.tokens.span cimport Span +from spacy.typedefs cimport flags_t, attr_t, hash_t +from spacy.vectors import Vectors +from spacy.vocab cimport Vocab +from spacy.structs cimport TokenC, LexemeC +from cymem.cymem cimport Pool + +cdef struct SpanC: + int start + int end + +cdef struct SentSpans: + SpanC* spans + int max_spans + int num + +cdef struct Hashes: + hash_t* arr + int length + +cdef struct HashesList: + Hashes no_coref_list + Hashes keep_tags + Hashes PRP_tags + Hashes leave_dep + Hashes keep_dep + Hashes nsubj_or_dep + Hashes conj_or_prep + Hashes remove_pos + Hashes lower_not_end + Hashes conj_tags + Hashes proper_tags + Hashes puncts + hash_t POSSESSIVE_MARK + hash_t NSUBJ_MARK + hash_t IN_TAG + hash_t MARK_DEP + hash_t missing_word + hash_t digit_word + hash_t unknown_word + +cdef struct Mention_C: + hash_t entity_label + int span_root + int span_start + int span_end + int sent_idx + int sent_start + int sent_end + int mention_type + hash_t root_lower + hash_t span_lower + Hashes content_words + +cdef class NeuralCoref(object): + cdef HashesList hashes + cdef readonly Vocab vocab + cdef readonly object cfg + cdef readonly object cfg_inference + cdef public object model + cdef public object static_vectors + cdef public object tuned_vectors + cdef public object conv_dict diff --git a/data_tooling/pii_processing/neuralcoref/neuralcoref.pyx b/data_tooling/pii_processing/neuralcoref/neuralcoref.pyx new file mode 100644 index 0000000..a137d50 --- /dev/null +++ b/data_tooling/pii_processing/neuralcoref/neuralcoref.pyx @@ -0,0 +1,995 @@ +# cython: infer_types=True, boundscheck=False +# distutils: language=c++ +""" NeuralCoref resolution spaCy v2.0 pipeline component +Custom pipeline components: https://spacy.io//usage/processing-pipelines#custom-components +Compatible with: spaCy v2.0.0+ +""" + +import plac +import re +import os +import io +from collections import OrderedDict +import json +cimport cython +from cpython cimport array +import array +from libc.stdint cimport uint16_t, uint32_t, uint64_t, uintptr_t, int32_t + +import numpy +from cymem.cymem cimport Pool +from srsly import json_dumps, read_json + +import spacy +from spacy.typedefs cimport hash_t +from srsly import json_dumps, read_json +from spacy.structs cimport LexemeC, TokenC +from spacy.lang.en import English +from spacy.tokens.doc import Doc +from spacy.tokens.span import Span +from spacy.tokens.token import Token +from spacy.tokens.token cimport Token +from spacy.strings cimport StringStore +from spacy.vocab cimport Vocab +from spacy.lexeme cimport Lexeme +from spacy.attrs cimport IS_DIGIT +from spacy.vectors import Vectors +from spacy import util +from spacy.compat import is_config + +from thinc.v2v import Model, ReLu, Affine +from thinc.api import chain, clone +# from thinc.neural.util import get_array_module + +from file_utils import NEURALCOREF_MODEL_PATH + +############################## +## DEFAULT INFERENCE VALUES ## + +GREEDYNESS = 0.5 +MAX_DIST = 50 +MAX_DIST_MATCH = 500 + +############################## +##### A BUNCH OF SIZES ####### + +DEF MAX_BINS = 9 +DEF MAX_FOLLOW_UP = 50 +DEF MAX_ITER = 100 +DEF SPAN_FACTOR = 4 + +DEF SIZE_WORD = 8 # number of words in a mention (tuned embeddings) +DEF SIZE_EMBEDDING = 50 # size of the words embeddings +DEF SIZE_SPAN = 5 * SIZE_EMBEDDING # size of the span vector (averaged word embeddings) +DEF SIZE_PAIR_FEATS = 63 # number of features for a pair of mention +DEF SIZE_FP_COMPRESSED = 9 # size of the features for a pair of mentions as stored in numpy arrays +DEF SIZE_SNGL_FEATS = 17 # number of features of a single mention +DEF SIZE_FS_COMPRESSED = 6 # size of the features for a mention as stored in numpy arrays +DEF SIZE_GENRE = 1 # Size of the genre one-hot array when no conll is used +DEF SIZE_MENTION_EMBEDDING = SIZE_SPAN + SIZE_WORD * SIZE_EMBEDDING # A mention embeddings (span + words vectors) +DEF SIZE_FS = SIZE_SNGL_FEATS + SIZE_GENRE +DEF SIZE_FP = SIZE_PAIR_FEATS + SIZE_GENRE +DEF SIZE_SNGL_IN_NO_GENRE = SIZE_MENTION_EMBEDDING + SIZE_SNGL_FEATS +DEF SIZE_PAIR_IN_NO_GENRE = 2 * SIZE_MENTION_EMBEDDING + SIZE_PAIR_FEATS +DEF SIZE_PAIR_IN = 2 * SIZE_MENTION_EMBEDDING + SIZE_FP # Input to the mentions pair neural network +DEF SIZE_SINGLE_IN = SIZE_MENTION_EMBEDDING + SIZE_FS # Input to the single mention neural network + +DEF PAIR_FEATS_0 = SIZE_MENTION_EMBEDDING +DEF PAIR_FEATS_1 = 2 * SIZE_MENTION_EMBEDDING +DEF PAIR_FEATS_2 = PAIR_FEATS_1 + 6 +DEF PAIR_FEATS_3 = PAIR_FEATS_2 + MAX_BINS + 1 +DEF PAIR_FEATS_4 = PAIR_FEATS_3 + 1 +DEF PAIR_FEATS_5 = PAIR_FEATS_4 + MAX_BINS + 1 +DEF PAIR_FEATS_6 = PAIR_FEATS_5 + 2 +DEF PAIR_FEATS_7 = PAIR_FEATS_6 + SIZE_SNGL_FEATS +DEF PAIR_FEATS_8 = PAIR_FEATS_7 + SIZE_SNGL_FEATS + +DEF SGNL_FEATS_0 = SIZE_MENTION_EMBEDDING +DEF SGNL_FEATS_1 = SGNL_FEATS_0 + 4 +DEF SGNL_FEATS_2 = SGNL_FEATS_1 + MAX_BINS + 1 +DEF SGNL_FEATS_3 = SGNL_FEATS_2 + 1 +DEF SGNL_FEATS_4 = SGNL_FEATS_3 + 1 +DEF SGNL_FEATS_5 = SGNL_FEATS_4 + 1 + +DEF EMBED_01 = SIZE_EMBEDDING +DEF EMBED_02 = 2 * SIZE_EMBEDDING +DEF EMBED_03 = 3 * SIZE_EMBEDDING +DEF EMBED_04 = 4 * SIZE_EMBEDDING +DEF EMBED_05 = 5 * SIZE_EMBEDDING +DEF EMBED_06 = 6 * SIZE_EMBEDDING +DEF EMBED_07 = 7 * SIZE_EMBEDDING +DEF EMBED_08 = 8 * SIZE_EMBEDDING +DEF EMBED_09 = 9 * SIZE_EMBEDDING +DEF EMBED_10 = 10 * SIZE_EMBEDDING +DEF EMBED_11 = 11 * SIZE_EMBEDDING +DEF EMBED_12 = 12 * SIZE_EMBEDDING +DEF EMBED_13 = 13 * SIZE_EMBEDDING + +DISTANCE_BINS_PY = array.array('i', list(range(5)) + [5]*3 + [6]*8 + [7]*16 + [8]*32) + +cdef: + int [::1] DISTANCE_BINS = DISTANCE_BINS_PY + int BINS_NUM = len(DISTANCE_BINS) + +########################################################## +##### STRINGS USED IN RULE_BASED MENTION DETECTION ####### + +NO_COREF_LIST = ["i", "me", "my", "you", "your"] +MENTION_TYPE = {"PRONOMINAL": 0, "NOMINAL": 1, "PROPER": 2, "LIST": 3} +MENTION_LABEL = {0: "PRONOMINAL", 1: "NOMINAL", 2: "PROPER", 3: "LIST"} +KEEP_TAGS = ["NN", "NNP", "NNPS", "NNS", "PRP", "PRP$", "DT", "IN"] +CONTENT_TAGS = ["NN", "NNS", "NNP", "NNPS"] +PRP_TAGS = ["PRP", "PRP$"] +CONJ_TAGS = ["CC", ","] +PROPER_TAGS = ["NNP", "NNPS"] +NSUBJ_OR_DEP = ["nsubj", "dep"] +CONJ_OR_PREP = ["conj", "prep"] +LEAVE_DEP = ["det", "compound", "appos"] +KEEP_DEP = ["nsubj", "dobj", "iobj", "pobj"] +REMOVE_POS = ["CCONJ", "SCONJ", "INTJ", "ADP"] +LOWER_NOT_END = ["'s", ',', '.', '!', '?', ':', ';'] +PUNCTS = [".", "!", "?"] +ACCEPTED_ENTS = ["PERSON", "NORP", "FACILITY", "ORG", "GPE", "LOC", "PRODUCT", "EVENT", "WORK_OF_ART", "LANGUAGE"] + +########################################################## +##### UTILITIES TO CONVERT STRINGS IN SPACY HASHES ####### + +cdef set_hashes_list(Hashes* hashes, py_list, StringStore store, Pool mem): + hashes.length = len(py_list) + hashes.arr = mem.alloc(hashes.length, sizeof(hash_t)) + for i, st in enumerate(py_list): + hashes.arr[i] = store.add(st) + +cdef HashesList get_hash_lookups(StringStore store, Pool mem): + cdef HashesList hashes + set_hashes_list(&hashes.no_coref_list, NO_COREF_LIST, store, mem) + set_hashes_list(&hashes.keep_tags, KEEP_TAGS, store, mem) + set_hashes_list(&hashes.PRP_tags, PRP_TAGS, store, mem) + set_hashes_list(&hashes.leave_dep, LEAVE_DEP, store, mem) + set_hashes_list(&hashes.keep_dep, KEEP_DEP, store, mem) + set_hashes_list(&hashes.nsubj_or_dep, NSUBJ_OR_DEP, store, mem) + set_hashes_list(&hashes.conj_or_prep, CONJ_OR_PREP, store, mem) + set_hashes_list(&hashes.remove_pos, REMOVE_POS, store, mem) + set_hashes_list(&hashes.lower_not_end, LOWER_NOT_END, store, mem) + set_hashes_list(&hashes.conj_tags, CONJ_TAGS, store, mem) + set_hashes_list(&hashes.proper_tags, PROPER_TAGS, store, mem) + set_hashes_list(&hashes.proper_tags, PROPER_TAGS, store, mem) + set_hashes_list(&hashes.puncts, PUNCTS, store, mem) + hashes.POSSESSIVE_MARK = store.add("'s") + hashes.NSUBJ_MARK = store.add("nsubj") + hashes.IN_TAG = store.add('IN') + hashes.MARK_DEP = store.add("mark") + hashes.unknown_word = store.add("*UNK*") + hashes.missing_word = store.add("") + hashes.digit_word = store.add("0") + return hashes + +cdef inline bint inside(hash_t element, Hashes hashes) nogil: + cdef int i + cdef hash_t* arr = hashes.arr + cdef int length = hashes.length + for i in range(length): + if arr[i] == element: + return True + return False + +######################################### +##### A BUNCH OF CYTHON UTILITIES ####### + +cdef inline int is_nested(Mention_C* c, int n_mentions, int m_idx): + for i in range(n_mentions): + if i == m_idx: + continue + if c[i].sent_idx == c[m_idx].sent_idx \ + and c[i].span_start <= c[m_idx].span_start \ + and c[i].span_end >= c[m_idx].span_end: + return 1 + return 0 + +cdef inline (int, float) index_distance(int d) nogil: + ''' Return index and value encoding to encode an integer as a (bined) one-hot array ''' + global BINS_NUM, DISTANCE_BINS + cdef float float_val + cdef int bin_d + float_val = min(float(d), float(BINS_NUM)) + if BINS_NUM != 0: + float_val = float_val/ BINS_NUM + bin_d = DISTANCE_BINS[d] if d < 64 else DISTANCE_BINS[BINS_NUM-1] + 1 + return bin_d, float_val + +cdef inline int heads_agree(Mention_C m1, Mention_C m2) nogil: + ''' Does the root of the Mention match the root of another Mention/Span''' + # In CoreNLP: they allow same-type NEs to not match perfectly + # but one could be included in the other, e.g., "George" -> "George Bush" + # In this cython C function, we take the simpler approach of directly comparing the roots hashes + return 1 if m1.root_lower == m2.root_lower else 0 + +cdef inline int exact_match(Mention_C m1, Mention_C m2) nogil: + return 1 if m1.span_lower == m2.span_lower else 0 + +cdef inline int relaxed_match(Mention_C m1, Mention_C m2) nogil: + for i in range(m1.content_words.length): + if inside(m1.content_words.arr[i], m2.content_words): + return True + return False + +cdef inline int overlapping(Mention_C m1, Mention_C m2) nogil: + return 1 if (m1.sent_idx == m2.sent_idx and m1.span_end > m2.span_start) else 0 + +cdef (int, int, int) get_span_sent(Span span): + ''' return index, start and end of the sentence of a Span in its Doc''' + cdef: + int n = 0 + int i + const TokenC* root = &span.doc.c[span.start] + while root.head != 0: # find left edge + root += root.head + n += 1 + if n >= span.doc.length: + raise RuntimeError("Error while getting Mention sentence index. Infinite loop detected.") + n = 0 + for i in range(root.l_edge+1): + if span.doc.c[i].sent_start == 1: + n += 1 + return n, root.l_edge, root.r_edge + 1 + +cdef hash_t get_span_entity_label(Span span): + ''' Label of a detected named entity the Mention is nested in if any''' + cdef int i + cdef const TokenC* token + cdef hash_t label + cdef bint has_label = False + for i in range(span.start, span.end): + token = &span.doc.c[i] + if token.ent_iob == 1: # Inside + if not has_label: + label = token.ent_id + has_label = True + elif token.ent_iob == 2 or token.ent_iob == 0: # Outside + return -1 # Not nested in entity + elif token.ent_iob == 3: # Beggining + if has_label: + return -1 # Not nested in entity + has_label = True + label = token.ent_id + return label + +cdef get_span_type(Span span): + ''' Find the type of a Span ''' + if any(t.tag_ in CONJ_TAGS and t.ent_type_ not in ACCEPTED_ENTS for t in span): + mention_type = MENTION_TYPE["LIST"] + elif span.root.tag_ in PRP_TAGS: + mention_type = MENTION_TYPE["PRONOMINAL"] + elif span.root.ent_type_ in ACCEPTED_ENTS or span.root.tag_ in PROPER_TAGS: + mention_type = MENTION_TYPE["PROPER"] + else: + mention_type = MENTION_TYPE["NOMINAL"] + return mention_type + +def get_resolved(doc, clusters): + ''' Return a list of utterrances text where the coref are resolved to the most representative mention''' + resolved = list(tok.text_with_ws for tok in doc) + for cluster in clusters: + for coref in cluster: + if coref != cluster.main: + resolved[coref.start] = cluster.main.text + doc[coref.end-1].whitespace_ + for i in range(coref.start+1, coref.end): + resolved[i] = "" + return ''.join(resolved) + +################################################# +##### RULE_BASED MENTION EXTRACTION LOGIC ####### + +cdef (int, int) enlarge_span(TokenC* doc_c, int i, int sent_start, int sent_end, int test, + HashesList hashes) nogil: + ''' Utility function to remove bad detected mention endings ''' + cdef int j + cdef uint32_t minchild_idx + cdef uint32_t maxchild_idx + minchild_idx = i + maxchild_idx = i + # if debug: print("enlarge_span") + # if debug: print("test", test) + # if debug: print("sent_start", sent_start) + # if debug: print("sent_end", sent_end) + for j in range(sent_start, sent_end): + # if debug: print("j", j) + c = doc_c[j] + c_head = j + c.head + if c_head != i: + continue + if c.l_edge >= minchild_idx: + continue + if test == 0 \ + or (test == 1 and inside(c.dep, hashes.nsubj_or_dep)) \ + or (test == 2 and c.head == i and not inside(c.dep, hashes.conj_or_prep)): + minchild_idx = c.l_edge + for j in range(sent_start, sent_end): + # if debug: print("j", j) + c = doc_c[j] + c_head = j + c.head + if c_head != i: + continue + if c.r_edge <= maxchild_idx: + continue + if test == 0 \ + or (test == 1 and inside(c.dep, hashes.nsubj_or_dep)) \ + or (test == 2 and c.head == i and not inside(c.dep, hashes.conj_or_prep)): + maxchild_idx = c.r_edge + # if debug: print("minchild_idx", minchild_idx) + # if debug: print("maxchild_idx", maxchild_idx) + # if debug: print("Clean up endings and begginging") + # Clean up endings and begginging + while maxchild_idx >= minchild_idx and maxchild_idx > sent_start \ + and (inside(doc_c[maxchild_idx].pos, hashes.remove_pos) + or inside(doc_c[maxchild_idx].lex.lower, hashes.lower_not_end)): + # if debug: print("maxchild_idx", maxchild_idx) + maxchild_idx -= 1 # We don't want mentions finishing with 's or conjunctions/punctuation + # if debug: print("maxchild_idx", maxchild_idx) + while minchild_idx <= maxchild_idx and minchild_idx < sent_end - 1 \ + and (inside(doc_c[minchild_idx].pos, hashes.remove_pos) + or inside(doc_c[minchild_idx].lex.lower, hashes.lower_not_end)): + minchild_idx += 1 # We don't want mentions starting with 's or conjunctions/punctuation + # if debug: print("minchild_idx", minchild_idx) + # if debug: print("minchild_idx", minchild_idx) + return minchild_idx, maxchild_idx + 1 + +cdef bint add_span(int start, int end, SentSpans* mentions_spans, TokenC* doc_c) nogil: + ''' Utility function to add a detected mention to our SentSpans structure ''' + cdef int num = mentions_spans.num + # if debug: print("add_span") + mentions_spans.spans[num].start = start + mentions_spans.spans[num].end = end + mentions_spans.num += 1 + return mentions_spans.num >= mentions_spans.max_spans # True when the max memory available to store spans is reached + +cdef void _extract_from_sent(TokenC* doc_c, int sent_start, int sent_end, SentSpans* mentions_spans, + HashesList hashes, bint blacklist=False) nogil: + ''' Main function to extract Pronouns and Noun phrases mentions from a spacy Span ''' + cdef int i, j, c_head, k, endIdx, minchild_idx, maxchild_idx, n_spans + cdef bint test + for i in range(sent_start, sent_end): + # if debug: print("token", i) + token = doc_c[i] + if blacklist and inside(token.lex.lower, hashes.no_coref_list): + # if debug: print("blacklist") + continue + if (not inside(token.tag, hashes.keep_tags) or inside(token.dep, hashes.leave_dep) \ + and not inside(token.dep, hashes.keep_dep)): + # if debug: print("not in keep tags or deps") + continue + if inside(token.tag, hashes.PRP_tags): # pronoun + # if debug: print("pronoun") + endIdx = i + 1 + test = add_span(i, i+1, mentions_spans, doc_c) + if test: return + # when pronoun is a part of conjunction (e.g., you and I) + if token.r_kids > 0 or token.l_kids > 0: + test = add_span(token.l_edge, token.r_edge+1, mentions_spans, doc_c) + if test: return + continue + # Add NP mention + # if debug: print("NP mention") + if token.lex.lower == hashes.POSSESSIVE_MARK: # Take care of 's + # if debug: print("Take care of 's") + c_head = i + token.head + j = 0 + while c_head != 0 and j < MAX_ITER: + if doc_c[c_head].dep == hashes.NSUBJ_MARK: + start, end = enlarge_span(doc_c, c_head, sent_start, sent_end, 1, hashes) + test = add_span(start, end+1, mentions_spans, doc_c) + if test: return + break + c_head += doc_c[c_head].head + j += 1 + continue + # if debug: print("Enlarge span") + for j in range(sent_start, sent_end): + c = doc_c[j] + start, end = enlarge_span(doc_c, i, sent_start, sent_end, 0, hashes) + if token.tag == hashes.IN_TAG and token.dep == hashes.MARK_DEP and start == end: + start, end = enlarge_span(doc_c, i + token.head, sent_start, sent_end, 0, hashes) + if start == end: + # if debug: print("Empty span") + continue + if doc_c[start].lex.lower == hashes.POSSESSIVE_MARK: + # if debug: print("we probably already have stored this mention") + continue # we probably already have stored this mention + test = add_span(start, end, mentions_spans, doc_c) + if test: return + test = False + for tok in doc_c[sent_start:sent_end]: + if inside(tok.dep, hashes.conj_or_prep): + test = True + break + if test: + # if debug: print("conj_or_prep") + start, end = enlarge_span(doc_c, i, sent_start, sent_end, 0, hashes) + if start == end: + continue + test = add_span(start, end, mentions_spans, doc_c) + if test: return + return + +cdef extract_mentions_spans(Doc doc, HashesList hashes, bint blacklist=False): + ''' Extract potential mentions from a spacy parsed Doc ''' + cdef: + int i, max_spans + int n_sents + SpanC spans_c + int n_spans = 0 + Pool mem = Pool() + mentions_spans = list(ent for ent in doc.ents if ent.label_ in ACCEPTED_ENTS) # Named entities + n_sents = len(list(doc.sents)) + # if debug: print("n_sents", n_sents) + sent_spans = mem.alloc(n_sents, sizeof(SentSpans)) + for i, sent in enumerate(doc.sents): + max_spans = len(sent)*SPAN_FACTOR + sent_spans[i].spans = mem.alloc(max_spans, sizeof(SpanC)) + sent_spans[i].max_spans = max_spans + sent_spans[i].num = 0 + # if debug: print("sent", i, "max_spans", max_spans) + for i, sent in enumerate(doc.sents): # Extract spans from each sentence in the doc (nogil so could be parallelized) + # if debug: print("extact from", i) + _extract_from_sent(doc.c, sent.start, sent.end, &sent_spans[i], hashes, blacklist=blacklist) + spans_set = set() + for m in mentions_spans: + if m.end > m.start and (m.start, m.end) not in spans_set: + spans_set.add((m.start, m.end)) + n_spans += 1 + for i in range(n_sents): + for j in range(sent_spans[i].num): + spans_c = sent_spans[i].spans[j] + if spans_c.end > spans_c.start and (spans_c.start, spans_c.end) not in spans_set: + spans_set.add((spans_c.start, spans_c.end)) + n_spans += 1 + sorted_spans = sorted(spans_set) + cleaned_mentions_spans = [doc[s[0]:s[1]] for s in sorted_spans] + return cleaned_mentions_spans, n_spans + + +########################## +###### MAIN CLASSES ######## + +class Cluster: + """ A utility class to store our annotations in the spaCy Doc """ + def __init__(self, i, main, mentions): + self.i = i + self.main = main # A Spacy Span: main mention of the cluster + self.mentions = mentions # A list of Spacy Spans: list of all mentions in the cluster + + def __getitem__(self, i): + return self.mentions[i] + + def __iter__(self): + for mention in self.mentions: + yield mention + + def __len__(self): + return len(self.mentions) + + def __unicode__(self): + return unicode(self.main) + u': ' + unicode(self.mentions) + + def __bytes__(self): + return unicode(self).encode('utf-8') + + def __str__(self): + if is_config(python3=True): + return self.__unicode__() + return self.__bytes__() + + def __repr__(self): + return self.__str__() + + +cdef class NeuralCoref(object): + """ spaCy v2.0 Coref pipeline component """ + name = 'coref' + + @classmethod + def Model(cls, **cfg): + """Initialize a model for the pipe.""" + h1 = util.env_opt('h1', cfg.get('h1', 1000)) + h2 = util.env_opt('h2', cfg.get('h2', 500)) + h3 = util.env_opt('h3', cfg.get('h3', 500)) + with Model.define_operators({'**': clone, '>>': chain}): + single_model = ReLu(h1, SIZE_SINGLE_IN) >> ReLu(h2, h1) >> ReLu(h3, h2) >> Affine(1, h3) >> Affine(1, 1) + pairs_model = ReLu(h1, SIZE_PAIR_IN) >> ReLu(h2, h1) >> ReLu(h3, h2) >> Affine(1, h3) >> Affine(1, 1) + cfg = { + 'h1': h1, + 'h2': h2, + 'h3': h3, + } + return (single_model, pairs_model), cfg + + def __init__(self, Vocab vocab, model=True, **cfg_inference): + """Create a Coref pipeline component. + vocab (Vocab): The vocabulary object. Must be shared with documents + to be processed. The value is set to the `.vocab` attribute. + model (object): Neural net model. The value is set to the .model attribute. If set to True + (default), a new instance will be created with `NeuralCoref.Model()` + in NeuralCoref.from_disk() or NeuralCoref.from_bytes(). + **cfg_inference: Arbitrary configuration parameters. Set to the `.cfg_inference` attribute + """ + self.vocab = vocab + self.model = model + self.hashes = get_hash_lookups(vocab.strings, vocab.mem) + self.static_vectors = Vectors() + self.tuned_vectors = Vectors() + self.conv_dict = None + self.cfg = {} + + if 'greedyness' not in cfg_inference: + cfg_inference['greedyness'] = util.env_opt('greedyness', GREEDYNESS) + if 'max_dist' not in cfg_inference: + cfg_inference['max_dist'] = util.env_opt('max_dist', MAX_DIST) + if 'max_dist_match' not in cfg_inference: + cfg_inference['max_dist_match'] = util.env_opt('max_dist_match', MAX_DIST_MATCH) + if 'blacklist' not in cfg_inference: + cfg_inference['blacklist'] = util.env_opt('blacklist', True) + if 'store_scores' not in cfg_inference: + cfg_inference['store_scores'] = util.env_opt('store_scores', True) + if 'conv_dict' not in cfg_inference: + cfg_inference['conv_dict'] = util.env_opt('conv_dict', None) + self.cfg_inference = cfg_inference + + # Register attributes on Doc and Span + if not Doc.has_extension('huggingface_neuralcoref'): + Doc.set_extension('huggingface_neuralcoref', default=True) + Doc.set_extension('has_coref', default=False) + Doc.set_extension('coref_clusters', default=None) + Doc.set_extension('coref_resolved', default="") + Doc.set_extension('coref_scores', default=None) + + Span.set_extension('is_coref', default=False) + Span.set_extension('coref_cluster', default=None) + Span.set_extension('coref_scores', default=None) + + Token.set_extension('in_coref', getter=self.token_in_coref) + Token.set_extension('coref_clusters', getter=self.token_clusters) + Token.set_extension('coref_scores', getter=self.token_scores) + + # Load from disk + self.from_disk(NEURALCOREF_MODEL_PATH) + + def __reduce__(self): + return (NeuralCoref, (self.vocab, self.model), None, None) + + def set_conv_dict(self, conv_dict=None): + def simple_normalize(word): + """ Get the hash of the lower case string of a word""" + return self.vocab.strings.add(word.lower()) + + if conv_dict is None: + conv_dict = self.cfg_inference.get('conv_dict', None) + if conv_dict is None: + return + + self.cfg_inference['conv_dict'] = conv_dict + self.conv_dict = Vectors(shape=(len(conv_dict), self.tuned_vectors.shape[1])) + for key, words in conv_dict.items(): + norm_k = simple_normalize(key) + norm_w = list(simple_normalize(w) for w in words) + embed_vector = numpy.zeros(self.static_vectors.shape[1], dtype='float32') + for hash_w in norm_w: + embed_vector += self.tuned_vectors[hash_w] if hash_w in self.tuned_vectors else self.get_static(hash_w) + self.conv_dict.add(key=norm_k, vector=embed_vector/max(len(norm_w), 1)) + + def __call__(self, doc, greedyness=None, max_dist=None, max_dist_match=None, + conv_dict=None, blacklist=None): + """Apply the pipeline component on a Doc object. """ + if greedyness is None: + greedyness = self.cfg_inference.get('greedyness', GREEDYNESS) + if max_dist is None: + max_dist = self.cfg_inference.get('max_dist', MAX_DIST) + if max_dist_match is None: + max_dist_match = self.cfg_inference.get('max_dist_match', MAX_DIST_MATCH) + if blacklist is None: + blacklist = self.cfg_inference.get('blacklist', True) + + self.set_conv_dict(conv_dict) + + annotations = self.predict([doc], greedyness=greedyness, max_dist=max_dist, + max_dist_match=max_dist_match, blacklist=blacklist) + self.set_annotations([doc], annotations) + return doc + + def pipe(self, stream, batch_size=128, n_threads=1, + greedyness=None, max_dist=None, max_dist_match=None, + conv_dict=None, blacklist=None): + """Process a stream of documents. Currently not optimized. + stream: The sequence of documents to process. + batch_size (int): Number of documents to accumulate into a working set. + n_threads (int): The number of threads with which to work on the buffer + in parallel. + YIELDS (Doc): Documents, in order. + """ + if greedyness is None: + greedyness = self.cfg_inference.get('greedyness', GREEDYNESS) + if max_dist is None: + max_dist = self.cfg_inference.get('max_dist', MAX_DIST) + if max_dist_match is None: + max_dist_match = self.cfg_inference.get('max_dist_match', MAX_DIST_MATCH) + if blacklist is None: + blacklist = self.cfg_inference.get('blacklist', True) + + self.set_conv_dict(conv_dict) + + for docs in util.minibatch(stream, size=batch_size): + docs = list(docs) + annotations = self.predict(docs, greedyness=greedyness, max_dist=max_dist, + max_dist_match=max_dist_match, blacklist=blacklist) + self.set_annotations(docs, annotations) + yield from docs + + def predict(self, docs, float greedyness=0.5, int max_dist=MAX_DIST, int max_dist_match=MAX_DIST_MATCH, + conv_dict=None, bint blacklist=False): + ''' Predict coreference clusters + docs (iterable): A sequence of `Doc` objects. + RETURNS (iterable): List of (lists of mentions, lists of clusters, lists of main mentions per cluster) for each doc. + ''' + cdef: + Mention_C* c + Mention_C m1, m2 + TokenC* doc_c + Doc doc + uint64_t i, ant_idx, men_idx, b_idx, n_mentions, n_pairs + uint64_t [::1] p_ant, p_men, best_ant + float [::1] embed, feats, doc_embed, mention_embed, best_score + float [:, ::1] s_inp, p_inp + float [:, ::1] s_score, p_score + Pool mem + StringStore strings + # timespec ts + # double timing0, timing1, timing2, timing3, timing4 + # clock_gettime(CLOCK_REALTIME, &ts) + # timing0 = ts.tv_sec + (ts.tv_nsec / 1000000000.) + + annotations = [] + # if debug: print("Extract mentions") + for doc in docs: + mem = Pool() # We use this for doc specific allocation + strings = doc.vocab.strings + # ''' Extract mentions ''' + mentions, n_mentions = extract_mentions_spans(doc, self.hashes, blacklist=blacklist) + n_sents = len(list(doc.sents)) + mentions = sorted((m for m in mentions), key=lambda m: (m.root.i, m.start)) + c = mem.alloc(n_mentions, sizeof(Mention_C)) + content_words = [] + for i, m in enumerate(mentions): + c[i].entity_label = get_span_entity_label(m) + c[i].span_start = m.start + c[i].span_end = m.end + c[i].span_root = m.root.i + idx, sent_start, sent_end = get_span_sent(m) + c[i].sent_idx = idx + c[i].sent_start = sent_start + c[i].sent_end = sent_end + c[i].mention_type = get_span_type(m) + c[i].root_lower = (m.root).c.lex.lower + c[i].span_lower = strings.add(m.text.lower()) + content_words.append(set(tok.lower_ for tok in m if tok.tag_ in CONTENT_TAGS)) + c[i].content_words.length = len(content_words[-1]) + c[i].content_words.arr = mem.alloc(len(content_words[-1]), sizeof(hash_t)) + for j, w in enumerate(content_words[-1]): + c[i].content_words.arr[j] = strings.add(w) + + # if debug: print("Prepare arrays of pairs indices and features for feeding the model") + # ''' Prepare arrays of pairs indices and features for feeding the model ''' + pairs_ant = [] + pairs_men = [] + n_pairs = 0 + if max_dist_match is not None: + word_to_mentions = {} + for i in range(n_mentions): + for tok in content_words[i]: + if not tok in word_to_mentions: + word_to_mentions[tok] = [i] + else: + word_to_mentions[tok].append(i) + for i in range(n_mentions): + if max_dist is None: + antecedents = set(range(i)) + else: + antecedents = set(range(max(0, i - max_dist), i)) + if max_dist_match is not None: + for tok in content_words[i]: + with_string_match = word_to_mentions.get(tok, None) + for match_idx in with_string_match: + if match_idx < i and match_idx >= i - max_dist_match: + antecedents.add(match_idx) + pairs_ant += list(antecedents) + pairs_men += [i]*len(antecedents) + n_pairs += len(antecedents) + p_ant_arr = numpy.asarray(pairs_ant, dtype=numpy.uint64) + p_men_arr = numpy.asarray(pairs_men, dtype=numpy.uint64) + p_ant = p_ant_arr + p_men = p_men_arr + s_inp_arr = numpy.zeros((n_mentions, SIZE_SNGL_IN_NO_GENRE + SIZE_GENRE), dtype='float32') + s_inp = s_inp_arr + p_inp_arr = numpy.zeros((n_pairs, SIZE_PAIR_IN_NO_GENRE + SIZE_GENRE), dtype='float32') + p_inp = p_inp_arr + + # if debug: print("Build single features and pair features arrays") + # ''' Build single features and pair features arrays ''' + doc_c = doc.c + doc_embedding = numpy.zeros(SIZE_EMBEDDING, dtype='float32') # self.embeds.get_average_embedding(doc.c, 0, doc.length + 1, self.hashes.puncts) + doc_embed = doc_embedding + for i in range(n_mentions): + s_inp_arr[i, :SGNL_FEATS_0] = self.get_mention_embeddings(mentions[i], doc_embedding) # Set embeddings + s_inp_arr[i, SGNL_FEATS_0 + c[i].mention_type] = 1 # 01_MentionType + b_idx, val = index_distance(c[i].span_end - c[i].span_start - 1) # 02_MentionLength + s_inp_arr[i, SGNL_FEATS_1 + b_idx] = 1 + s_inp_arr[i, SGNL_FEATS_2] = val + val = float(i)/float(n_mentions) # 03_MentionNormLocation + s_inp_arr[i, SGNL_FEATS_3] = val + s_inp_arr[i, SGNL_FEATS_4] = is_nested(c, n_mentions, i) # 04_IsMentionNested + for i in range(n_pairs): + ant_idx = p_ant[i] + men_idx = p_men[i] + m1 = c[ant_idx] + m2 = c[men_idx] + p_inp[i, :PAIR_FEATS_0] = s_inp[ant_idx, :SGNL_FEATS_0] + p_inp[i, PAIR_FEATS_0:PAIR_FEATS_1] = s_inp[men_idx, :SGNL_FEATS_0] + p_inp[i, PAIR_FEATS_1] = 1 # 00_SameSpeaker + # p_inp[i, PAIR_FEATS_1 + 1] = 0 # 01_AntMatchMentionSpeaker # arrays are initialized to zero + # p_inp[i, PAIR_FEATS_1 + 2] = 0 # 02_MentionMatchSpeaker + p_inp[i, PAIR_FEATS_1 + 3] = heads_agree(m1, m2) # 03_HeadsAgree + p_inp[i, PAIR_FEATS_1 + 4] = exact_match(m1, m2) # 04_ExactStringMatch + p_inp[i, PAIR_FEATS_1 + 5] = relaxed_match(m1, m2) # 05_RelaxedStringMatch + b_idx, val = index_distance(m2.sent_idx - m1.sent_idx) # 06_SentenceDistance + # p_inp[i, PAIR_FEATS_2:PAIR_FEATS_3] = 0 + p_inp[i, PAIR_FEATS_2 + b_idx] = 1 + p_inp[i, PAIR_FEATS_3] = val + b_idx, val = index_distance(men_idx - ant_idx - 1) # 07_MentionDistance + # p_inp[i, PAIR_FEATS_4:PAIR_FEATS_5] = 0 + p_inp[i, PAIR_FEATS_4 + b_idx] = 1 + p_inp[i, PAIR_FEATS_5] = val + p_inp[i, PAIR_FEATS_5 + 1] = overlapping(m1, m2) # 08_Overlapping + p_inp[i, PAIR_FEATS_6:PAIR_FEATS_7] = s_inp[ant_idx, SGNL_FEATS_0:SGNL_FEATS_5] # 09_M1Features + p_inp[i, PAIR_FEATS_7:PAIR_FEATS_8] = s_inp[men_idx, SGNL_FEATS_0:SGNL_FEATS_5] # 10_M2Features + # 11_DocGenre is zero currently + + # if debug: print("Compute scores") + # ''' Compute scores ''' + best_score_ar = numpy.empty((n_mentions), dtype='float32') + best_ant_ar = numpy.empty((n_mentions), dtype=numpy.uint64) + best_score = best_score_ar + best_ant = best_ant_ar + s_score = self.model[0](s_inp_arr) + for i in range(n_mentions): + best_score[i] = s_score[i, 0] - 50 * (greedyness - 0.5) + best_ant[i] = i + p_score = self.model[1](p_inp_arr) + for i in range(n_pairs): + ant_idx = p_ant[i] + men_idx = p_men[i] + if p_score[i, 0] > best_score[men_idx]: + best_score[men_idx] = p_score[i, 0] + best_ant[men_idx] = ant_idx + + # if debug: print("Build clusters") + # ''' Build clusters ''' + mention_to_cluster = list(range(n_mentions)) + cluster_to_main = list(range(n_mentions)) + clusters = dict((i, [i]) for i in mention_to_cluster) + for mention_idx, ant_idx in enumerate(best_ant): + if ant_idx != mention_idx: + if mention_to_cluster[ant_idx] == mention_to_cluster[mention_idx]: + continue + keep_id = mention_to_cluster[ant_idx] + remove_id = mention_to_cluster[mention_idx] + for idx in clusters[remove_id]: + mention_to_cluster[idx] = keep_id + clusters[keep_id].append(idx) + del clusters[remove_id] + if c[ant_idx].mention_type != c[mention_idx].mention_type: + if c[mention_idx].mention_type == MENTION_TYPE["PROPER"] \ + or (c[mention_idx].mention_type == MENTION_TYPE["NOMINAL"] and + c[ant_idx].mention_type == MENTION_TYPE["PRONOMINAL"]): + cluster_to_main[ant_idx] = mention_idx + clusters_list = [] + i = 0 + for key, m_idx_list in clusters.items(): + if len(m_idx_list) != 1: + m_list = list(mentions[i] for i in m_idx_list) + main = mentions[cluster_to_main[key]] + clusters_list.append(Cluster(i, main, m_list)) + i += 1 + + # Build scores dict + scores_dict = {} + if self.cfg_inference['store_scores']: + # mention scores + for i in range(n_mentions): + mention = mentions[i] + score = s_score[i, 0] + if mention in scores_dict: + scores_dict[mention][mention] = score + else: + scores_dict[mention] = {mention: score} + # pair scores + for i in range(n_pairs): + antecedent = mentions[p_ant[i]] + mention = mentions[p_men[i]] + score = p_score[i, 0] + if mention in scores_dict: + scores_dict[mention][antecedent] = score + else: + scores_dict[mention] = {antecedent: score} + + annotations.append((clusters_list, scores_dict)) + + return annotations + + def set_annotations(self, docs, annotations): + """Set the tensor attribute for a batch of documents. + docs (iterable): A sequence of `Doc` objects. + tensors (object): Vector representation for each token in the docs. + """ + if isinstance(docs, Doc): + docs = [docs] + cdef Doc doc + for doc, (clusters, scores_dict) in zip(docs, annotations): + doc._.set('has_coref', len(clusters) != 0) + doc._.set('coref_clusters', clusters) + doc._.set('coref_resolved', get_resolved(doc, clusters)) + doc._.set('coref_scores', scores_dict) + for cluster in clusters: + for mention in cluster: + mention._.set('is_coref', True) + mention._.set('coref_cluster', cluster) + for mention, scores in scores_dict.items(): + mention._.set('coref_scores', scores) + + def token_in_coref(self, token): + """Getter for Token attributes. Returns True if the token is in a cluster. + """ + return any([token in mention for cluster in token.doc._.coref_clusters + for mention in cluster]) + + def token_clusters(self, token): + """Getter for Token attributes. Returns a list of the clusters in which the token is. + """ + clusters = [] + for cluster in token.doc._.coref_clusters: + for mention in cluster: + if token in mention: + clusters.append(cluster) + break + return clusters + + def token_scores(self, token): + """Getter for Token attributes. Returns the scores of the cluster in which the token is. + """ + scores_list = [] + for mention, scores in token.doc._.coref_scores.items(): + if token in mention: + scores_list.append(scores) + return scores_list + + def normalize(self, Token token): + return self.hashes.digit_word if token.is_digit else token.lower + + def get_static(self, hash_t word): + return self.static_vectors[word] if word in self.static_vectors else self.static_vectors[self.hashes.unknown_word] + + def get_word_embedding(self, Token token, bint tuned=True): + hash_w = self.normalize(token) + if self.conv_dict is not None and hash_w in self.conv_dict: + return self.conv_dict[hash_w] + if tuned and hash_w in self.tuned_vectors: + return self.tuned_vectors[hash_w] + return self.get_static(hash_w) + + def get_word_in_sentence(self, int i, Span sent): + if i < sent.start or i >= sent.end: + return self.tuned_vectors[self.hashes.missing_word] + return self.get_word_embedding(sent.doc[i]) + + def get_average_embedding(self, Span span): + cdef int i + cdef int n = 0 + embed_arr = numpy.zeros(self.static_vectors.shape[1], dtype='float32') + for token in span: + if token.lower not in PUNCTS: + n += 1 + embed_vector = self.get_word_embedding(token, tuned=False) + embed_arr = embed_arr + embed_vector + embed_arr = numpy.divide(embed_arr, float(max(n, 1))) + return embed_arr + + def get_mention_embeddings(self, Span span, doc_embedding): + ''' Create a mention embedding with span (averaged) and word (single) embeddings ''' + doc = span.doc + sent = span.sent + embeddings = numpy.zeros((EMBED_13, ), dtype='float32') + embeddings[ :EMBED_01] = self.get_average_embedding(span) + embeddings[EMBED_01:EMBED_02] = self.get_average_embedding(doc[max(span.start-5, sent.start):span.start]) + embeddings[EMBED_02:EMBED_03] = self.get_average_embedding(doc[span.end:min(span.end + 5, sent.end)]) + embeddings[EMBED_03:EMBED_04] = self.get_average_embedding(sent) + embeddings[EMBED_04:EMBED_05] = doc_embedding + embeddings[EMBED_05:EMBED_06] = self.get_word_embedding(span.root) + embeddings[EMBED_06:EMBED_07] = self.get_word_embedding(span[0]) + embeddings[EMBED_07:EMBED_08] = self.get_word_embedding(span[-1]) + embeddings[EMBED_08:EMBED_09] = self.get_word_in_sentence(span.start-1, sent) + embeddings[EMBED_09:EMBED_10] = self.get_word_in_sentence(span.end, sent) + embeddings[EMBED_10:EMBED_11] = self.get_word_in_sentence(span.start-2, sent) + embeddings[EMBED_11:EMBED_12] = self.get_word_in_sentence(span.end+1, sent) + embeddings[EMBED_12: ] = self.get_word_embedding(span.root.head) + return embeddings + + def to_disk(self, path, **exclude): + serializers = { + 'single_model': lambda p: p.open('wb').write(self.model[0].to_bytes()), + 'pairs_model': lambda p: p.open('wb').write(self.model[1].to_bytes()), + 'static_vectors': lambda p: self.static_vectors.to_disk(p), + 'tuned_vectors': lambda p: self.tuned_vectors.to_disk(p), + 'cfg': lambda p: p.open('w').write(json_dumps(self.cfg)) + } + util.to_disk(path, serializers, exclude) + + def from_disk(self, path, **exclude): + deserializers = { + 'cfg': lambda p: self.cfg.update(read_json(p)), + 'model': lambda p: None + } + util.from_disk(path, deserializers, exclude) + if 'model' not in exclude: + path = util.ensure_path(path) + if self.model is True: + self.model, cfg = self.Model(**self.cfg) + else: + cfg = {} + with (path / 'single_model').open('rb') as file_: + bytes_data = file_.read() + self.model[0].from_bytes(bytes_data) + with (path / 'pairs_model').open('rb') as file_: + bytes_data = file_.read() + self.model[1].from_bytes(bytes_data) + self.static_vectors.from_disk(path / 'static_vectors') + self.tuned_vectors.from_disk(path / 'tuned_vectors') + self.cfg.update(cfg) + return self + + def to_bytes(self, **exclude): + serializers = OrderedDict(( + ('static_vectors', lambda: self.static_vectors.to_bytes()), + ('tuned_vectors', lambda: self.tuned_vectors.to_bytes()) + ('single_model', lambda: self.model[0].to_bytes()), + ('pairs_model', lambda: self.model[1].to_bytes()), + ('cfg', lambda: json.dumps(self.cfg, indent=2, sort_keys=True)) + )) + if 'model' in exclude: + exclude['static_vectors'] = True + exclude['tuned_vectors'] = True + exclude['single_model'] = True + exclude['pairs_model'] = True + exclude.pop('model') + return util.to_bytes(serializers, exclude) + + def from_bytes(self, bytes_data, **exclude): + deserializers = OrderedDict(( + ('cfg', lambda b: self.cfg.update(json.loads(b))), + ('static_vectors', lambda b: None), + ('tuned_vectors', lambda b: None), + ('single_model', lambda b: None), + ('pairs_model', lambda b: None) + )) + msg = util.from_bytes(bytes_data, deserializers, exclude) + if 'model' not in exclude: + if self.model is True: + self.model, cfg = self.Model(**self.cfg) + else: + cfg = {} + if 'static_vectors' in msg: + self.static_vectors.from_bytes(msg['static_vectors']) + if 'tuned_vectors' in msg: + self.tuned_vectors.from_bytes(msg['tuned_vectors']) + if 'single_model' in msg: + self.model[0].from_bytes(msg['single_model']) + if 'pairs_model' in msg: + self.model[1].from_bytes(msg['pairs_model']) + self.cfg.update(cfg) + return self diff --git a/data_tooling/pii_processing/neuralcoref/tests/__init__.py b/data_tooling/pii_processing/neuralcoref/tests/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/data_tooling/pii_processing/neuralcoref/tests/test_neuralcoref.py b/data_tooling/pii_processing/neuralcoref/tests/test_neuralcoref.py new file mode 100644 index 0000000..138de3d --- /dev/null +++ b/data_tooling/pii_processing/neuralcoref/tests/test_neuralcoref.py @@ -0,0 +1,8 @@ +import spacy +from ..__init__ import add_to_pipe + + +def test_add_pipe(): + nlp = spacy.lang.en.English() + add_to_pipe(nlp) + assert "neuralcoref" in nlp.pipe_names diff --git a/data_tooling/pii_processing/neuralcoref/train/__init__.pxd b/data_tooling/pii_processing/neuralcoref/train/__init__.pxd new file mode 100644 index 0000000..e69de29 diff --git a/data_tooling/pii_processing/neuralcoref/train/__init__.py b/data_tooling/pii_processing/neuralcoref/train/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/data_tooling/pii_processing/neuralcoref/train/algorithm.py b/data_tooling/pii_processing/neuralcoref/train/algorithm.py new file mode 100644 index 0000000..091974c --- /dev/null +++ b/data_tooling/pii_processing/neuralcoref/train/algorithm.py @@ -0,0 +1,396 @@ +# cython: profile=True +# cython: infer_types=True +"""Coref resolution""" + +import os +import spacy +import numpy as np + +from neuralcoref.train.utils import PACKAGE_DIRECTORY, SIZE_SINGLE_IN +from neuralcoref.train.compat import unicode_ +from neuralcoref.train.document import Document, MENTION_TYPE, NO_COREF_LIST + +####################### +##### UTILITIES ####### + +MAX_FOLLOW_UP = 50 + +####################### +###### CLASSES ######## + + +class Model(object): + """ + Coreference neural model + """ + + def __init__(self, model_path): + weights, biases = [], [] + for file in sorted(os.listdir(model_path)): + if file.startswith("single_mention_weights"): + w = np.load(os.path.join(model_path, file)) + weights.append(w) + if file.startswith("single_mention_bias"): + w = np.load(os.path.join(model_path, file)) + biases.append(w) + self.single_mention_model = list(zip(weights, biases)) + weights, biases = [], [] + for file in sorted(os.listdir(model_path)): + if file.startswith("pair_mentions_weights"): + w = np.load(os.path.join(model_path, file)) + weights.append(w) + if file.startswith("pair_mentions_bias"): + w = np.load(os.path.join(model_path, file)) + biases.append(w) + self.pair_mentions_model = list(zip(weights, biases)) + + def _score(self, features, layers): + for weights, bias in layers: + # print("features", features.shape) + features = np.matmul(weights, features) + bias + if weights.shape[0] > 1: + features = np.maximum(features, 0) # ReLU + return np.sum(features, axis=0) + + def get_multiple_single_score(self, first_layer_input): + return self._score(first_layer_input, self.single_mention_model) + + def get_multiple_pair_score(self, first_layer_input): + return self._score(first_layer_input, self.pair_mentions_model) + + +class Coref(object): + """ + Main coreference resolution algorithm + """ + + def __init__( + self, + nlp=None, + greedyness=0.5, + max_dist=50, + max_dist_match=500, + conll=None, + blacklist=True, + debug=False, + ): + self.greedyness = greedyness + self.max_dist = max_dist + self.max_dist_match = max_dist_match + self.debug = debug + model_path = os.path.join( + PACKAGE_DIRECTORY, "weights/conll/" if conll is not None else "weights/" + ) + model_path = os.path.join(PACKAGE_DIRECTORY, "weights/") + print("Loading neuralcoref model from", model_path) + self.coref_model = Model(model_path) + if nlp is None: + print("Loading spacy model") + try: + spacy.info("en_core_web_sm") + model = "en_core_web_sm" + except IOError: + print("No spacy 2 model detected, using spacy1 'en' model") + spacy.info("en") + model = "en" + nlp = spacy.load(model) + self.data = Document( + nlp, conll=conll, blacklist=blacklist, model_path=model_path + ) + self.clusters = {} + self.mention_to_cluster = [] + self.mentions_single_scores = {} + self.mentions_pairs_scores = {} + + ################################### + #### ENTITY CLUSTERS FUNCTIONS #### + ################################### + + def _prepare_clusters(self): + """ + Clean up and prepare one cluster for each mention + """ + self.mention_to_cluster = list(range(len(self.data.mentions))) + self.clusters = dict((i, [i]) for i in self.mention_to_cluster) + self.mentions_single_scores = {} + self.mentions_pairs_scores = {} + for mention in self.mention_to_cluster: + self.mentions_single_scores[mention] = None + self.mentions_pairs_scores[mention] = {} + + def _merge_coreference_clusters(self, ant_idx, mention_idx): + """ + Merge two clusters together + """ + if self.mention_to_cluster[ant_idx] == self.mention_to_cluster[mention_idx]: + return + + remove_id = self.mention_to_cluster[ant_idx] + keep_id = self.mention_to_cluster[mention_idx] + for idx in self.clusters[remove_id]: + self.mention_to_cluster[idx] = keep_id + self.clusters[keep_id].append(idx) + + del self.clusters[remove_id] + + def remove_singletons_clusters(self): + remove_id = [] + for key, mentions in self.clusters.items(): + if len(mentions) == 1: + remove_id.append(key) + self.mention_to_cluster[key] = None + for rem in remove_id: + del self.clusters[rem] + + def display_clusters(self): + """ + Print clusters informations + """ + print(self.clusters) + for key, mentions in self.clusters.items(): + print( + "cluster", + key, + "(", + ", ".join(unicode_(self.data[m]) for m in mentions), + ")", + ) + + ################################### + ####### MAIN COREF FUNCTIONS ###### + ################################### + + def run_coref_on_mentions(self, mentions): + """ + Run the coreference model on a mentions list + """ + best_ant = {} + best_score = {} + n_ant = 0 + inp = np.empty((SIZE_SINGLE_IN, len(mentions))) + for i, mention_idx in enumerate(mentions): + mention = self.data[mention_idx] + print("mention.embedding", mention.embedding.shape) + inp[: len(mention.embedding), i] = mention.embedding + inp[: len(mention.embedding), i] = mention.features + inp[: len(mention.embedding), i] = self.data.genre + score = self.coref_model.get_multiple_single_score(inp.T) + for mention_idx, s in zip(mentions, score): + self.mentions_single_scores[mention_idx] = s + best_score[mention_idx] = s - 50 * (self.greedyness - 0.5) + + for mention_idx, ant_list in self.data.get_candidate_pairs( + mentions, self.max_dist, self.max_dist_match + ): + if len(ant_list) == 0: + continue + inp_l = [] + for ant_idx in ant_list: + mention = self.data[mention_idx] + antecedent = self.data[ant_idx] + feats_, pwf = self.data.get_pair_mentions_features(antecedent, mention) + inp_l.append(pwf) + inp = np.stack(inp_l, axis=0) + score = self.coref_model.get_multiple_pair_score(inp.T) + for ant_idx, s in zip(ant_list, score): + self.mentions_pairs_scores[mention_idx][ant_idx] = s + if s > best_score[mention_idx]: + best_score[mention_idx] = s + best_ant[mention_idx] = ant_idx + if mention_idx in best_ant: + n_ant += 1 + self._merge_coreference_clusters(best_ant[mention_idx], mention_idx) + return (n_ant, best_ant) + + def run_coref_on_utterances( + self, last_utterances_added=False, follow_chains=True, debug=False + ): + """ Run the coreference model on some utterances + + Arg: + last_utterances_added: run the coreference model over the last utterances added to the data + follow_chains: follow coreference chains over previous utterances + """ + if debug: + print("== run_coref_on_utterances == start") + self._prepare_clusters() + if debug: + self.display_clusters() + mentions = list( + self.data.get_candidate_mentions( + last_utterances_added=last_utterances_added + ) + ) + n_ant, antecedents = self.run_coref_on_mentions(mentions) + mentions = antecedents.values() + if follow_chains and last_utterances_added and n_ant > 0: + i = 0 + while i < MAX_FOLLOW_UP: + i += 1 + n_ant, antecedents = self.run_coref_on_mentions(mentions) + mentions = antecedents.values() + if n_ant == 0: + break + if debug: + self.display_clusters() + if debug: + print("== run_coref_on_utterances == end") + + def one_shot_coref( + self, + utterances, + utterances_speakers_id=None, + context=None, + context_speakers_id=None, + speakers_names=None, + ): + """ Clear history, load a list of utterances and an optional context and run the coreference model on them + + Arg: + - `utterances` : iterator or list of string corresponding to successive utterances (in a dialogue) or sentences. + Can be a single string for non-dialogue text. + - `utterances_speakers_id=None` : iterator or list of speaker id for each utterance (in the case of a dialogue). + - if not provided, assume two speakers speaking alternatively. + - if utterances and utterances_speaker are not of the same length padded with None + - `context=None` : iterator or list of string corresponding to additionnal utterances/sentences sent prior to `utterances`. Coreferences are not computed for the mentions identified in `context`. The mentions in `context` are only used as possible antecedents to mentions in `uterrance`. Reduce the computations when we are only interested in resolving coreference in the last sentences/utterances. + - `context_speakers_id=None` : same as `utterances_speakers_id` for `context`. + - `speakers_names=None` : dictionnary of list of acceptable speaker names (strings) for speaker_id in `utterances_speakers_id` and `context_speakers_id` + Return: + clusters of entities with coreference resolved + """ + self.data.set_utterances(context, context_speakers_id, speakers_names) + self.continuous_coref(utterances, utterances_speakers_id, speakers_names) + return self.get_clusters() + + def continuous_coref( + self, utterances, utterances_speakers_id=None, speakers_names=None + ): + """ + Only resolve coreferences for the mentions in the utterances + (but use the mentions in previously loaded utterances as possible antecedents) + Arg: + utterances : iterator or list of string corresponding to successive utterances + utterances_speaker : iterator or list of speaker id for each utterance. + If not provided, assume two speakers speaking alternatively. + if utterances and utterances_speaker are not of the same length padded with None + speakers_names : dictionnary of list of acceptable speaker names for each speaker id + Return: + clusters of entities with coreference resolved + """ + self.data.add_utterances(utterances, utterances_speakers_id, speakers_names) + self.run_coref_on_utterances(last_utterances_added=True, follow_chains=True) + return self.get_clusters() + + ################################### + ###### INFORMATION RETRIEVAL ###### + ################################### + + def get_utterances(self, last_utterances_added=True): + """ Retrieve the list of parsed uterrances""" + if last_utterances_added and len(self.data.last_utterances_loaded): + return [ + self.data.utterances[idx] for idx in self.data.last_utterances_loaded + ] + else: + return self.data.utterances + + def get_resolved_utterances(self, last_utterances_added=True, blacklist=True): + """ Return a list of utterrances text where the """ + coreferences = self.get_most_representative(last_utterances_added, blacklist) + resolved_utterances = [] + for utt in self.get_utterances(last_utterances_added=last_utterances_added): + resolved_utt = "" + in_coref = None + for token in utt: + if in_coref is None: + for coref_original, coref_replace in coreferences.items(): + if coref_original[0] == token: + in_coref = coref_original + resolved_utt += coref_replace.text.lower() + break + if in_coref is None: + resolved_utt += token.text_with_ws + if in_coref is not None and token == in_coref[-1]: + resolved_utt += ( + " " if token.whitespace_ and resolved_utt[-1] is not " " else "" + ) + in_coref = None + resolved_utterances.append(resolved_utt) + return resolved_utterances + + def get_mentions(self): + """ Retrieve the list of mentions""" + return self.data.mentions + + def get_scores(self): + """ Retrieve scores for single mentions and pair of mentions""" + return { + "single_scores": self.mentions_single_scores, + "pair_scores": self.mentions_pairs_scores, + } + + def get_clusters(self, remove_singletons=False, blacklist=False): + """ Retrieve cleaned clusters""" + clusters = self.clusters + mention_to_cluster = self.mention_to_cluster + remove_id = [] + if blacklist: + for key, mentions in clusters.items(): + cleaned_list = [] + for mention_idx in mentions: + mention = self.data.mentions[mention_idx] + if mention.lower_ not in NO_COREF_LIST: + cleaned_list.append(mention_idx) + clusters[key] = cleaned_list + # Also clean up keys so we can build coref chains in self.get_most_representative + added = {} + for key, mentions in clusters.items(): + if self.data.mentions[key].lower_ in NO_COREF_LIST: + remove_id.append(key) + mention_to_cluster[key] = None + if mentions: + added[mentions[0]] = mentions + for rem in remove_id: + del clusters[rem] + clusters.update(added) + + if remove_singletons: + remove_id = [] + for key, mentions in clusters.items(): + if len(mentions) == 1: + remove_id.append(key) + mention_to_cluster[key] = None + for rem in remove_id: + del clusters[rem] + + return clusters, mention_to_cluster + + def get_most_representative(self, last_utterances_added=True, blacklist=True): + """ + Find a most representative mention for each cluster + + Return: + Dictionnary of {original_mention: most_representative_resolved_mention, ...} + """ + clusters, _ = self.get_clusters(remove_singletons=True, blacklist=blacklist) + coreferences = {} + for key in self.data.get_candidate_mentions( + last_utterances_added=last_utterances_added + ): + if self.mention_to_cluster[key] is None: + continue + mentions = clusters.get(self.mention_to_cluster[key], None) + if mentions is None: + continue + representative = self.data.mentions[key] + for mention_idx in mentions[1:]: + mention = self.data.mentions[mention_idx] + if mention.mention_type is not representative.mention_type: + if mention.mention_type == MENTION_TYPE["PROPER"] or ( + mention.mention_type == MENTION_TYPE["NOMINAL"] + and representative.mention_type == MENTION_TYPE["PRONOMINAL"] + ): + coreferences[self.data.mentions[key]] = mention + representative = mention + + return coreferences diff --git a/data_tooling/pii_processing/neuralcoref/train/checkpoints/.gitignore b/data_tooling/pii_processing/neuralcoref/train/checkpoints/.gitignore new file mode 100644 index 0000000..86d0cb2 --- /dev/null +++ b/data_tooling/pii_processing/neuralcoref/train/checkpoints/.gitignore @@ -0,0 +1,4 @@ +# Ignore everything in this directory +* +# Except this file +!.gitignore \ No newline at end of file diff --git a/data_tooling/pii_processing/neuralcoref/train/compat.py b/data_tooling/pii_processing/neuralcoref/train/compat.py new file mode 100644 index 0000000..a8a974a --- /dev/null +++ b/data_tooling/pii_processing/neuralcoref/train/compat.py @@ -0,0 +1,20 @@ +import sys + +is_windows = sys.platform.startswith("win") +is_linux = sys.platform.startswith("linux") +is_osx = sys.platform == "darwin" + + +# Python 3 is default, Python 2 is not supported anymore +unicode_ = str +bytes_ = bytes +string_types = (bytes, str) +chr_ = chr + + +def unicode_to_bytes(s, encoding="utf8", errors="strict"): + return s.encode(encoding=encoding, errors=errors) + + +def bytes_to_unicode(b, encoding="utf8", errors="strict"): + return b.decode(encoding=encoding, errors=errors) diff --git a/data_tooling/pii_processing/neuralcoref/train/conll_processing_script/compile_coref_data.sh b/data_tooling/pii_processing/neuralcoref/train/conll_processing_script/compile_coref_data.sh new file mode 100644 index 0000000..dbe7970 --- /dev/null +++ b/data_tooling/pii_processing/neuralcoref/train/conll_processing_script/compile_coref_data.sh @@ -0,0 +1,50 @@ + +#!/bin/bash + +# Script from the Allen NLP research library (https://github.com/allenai/allennlp): +# https://github.com/allenai/allennlp/blob/master/scripts/compile_coref_data.sh + +# This script downloads and compiles the Ontonotes 2012 data in a helpful format +# for co-reference resolution. It generates 3 files: {train, dev, test}.english.v4_gold_conll, +# as well as a directory 'conll-2012' which contains the raw extracted data. +# The script downloads and runs some python scripts which require python 2.X. + +ONTONOTES_PATH=$1 + +if [ ! -n "$ONTONOTES_PATH" ] ; then + echo "USAGE: ./compile_coref_data.sh /path/to/ontonotes/data" + exit 1 +fi + +function download_and_extract() { + wget $1/$2 + tar -xvzf $2 + rm $2 +} + +function compile_partition() { + rm -f $2.$5.$3$4 + cat conll-2012/$3/data/$1/data/$5/annotations/*/*/*/*.$3$4 >> $2.$5.$3$4 +} + +function compile_language() { + compile_partition development dev v4 _gold_conll $1 + compile_partition train train v4 _gold_conll $1 + compile_partition test test v4 _gold_conll $1 +} + +conll_url=http://conll.cemantix.org/2012/download +download_and_extract $conll_url conll-2012-train.v4.tar.gz +download_and_extract $conll_url conll-2012-development.v4.tar.gz +download_and_extract $conll_url/test conll-2012-test-key.tar.gz +download_and_extract $conll_url/test conll-2012-test-official.v9.tar.gz + +download_and_extract $conll_url conll-2012-scripts.v3.tar.gz + +download_and_extract http://conll.cemantix.org/download reference-coreference-scorers.v8.01.tar.gz +mv reference-coreference-scorers conll-2012/scorer + +# Convert the ontonotes data into the CONLL format. +bash conll-2012/v3/scripts/skeleton2conll.sh -D $ONTONOTES_PATH/data/files/data conll-2012 + +compile_language english diff --git a/data_tooling/pii_processing/neuralcoref/train/conllparser.py b/data_tooling/pii_processing/neuralcoref/train/conllparser.py new file mode 100644 index 0000000..81164c2 --- /dev/null +++ b/data_tooling/pii_processing/neuralcoref/train/conllparser.py @@ -0,0 +1,960 @@ +"""Conll parser""" + +import re +import argparse +import time +import os +import io +import pickle + +import spacy + +import numpy as np + +from tqdm import tqdm + +from neuralcoref.train.compat import unicode_ +from neuralcoref.train.document import ( + Mention, + Document, + Speaker, + EmbeddingExtractor, + MISSING_WORD, + extract_mentions_spans, +) +from neuralcoref.train.utils import parallel_process + +PACKAGE_DIRECTORY = os.path.dirname(os.path.abspath(__file__)) +REMOVED_CHAR = ["/", "%", "*"] +NORMALIZE_DICT = { + "/.": ".", + "/?": "?", + "-LRB-": "(", + "-RRB-": ")", + "-LCB-": "{", + "-RCB-": "}", + "-LSB-": "[", + "-RSB-": "]", +} + +CONLL_GENRES = {"bc": 0, "bn": 1, "mz": 2, "nw": 3, "pt": 4, "tc": 5, "wb": 6} + +FEATURES_NAMES = [ + "mentions_features", # 0 + "mentions_labels", # 1 + "mentions_pairs_length", # 2 + "mentions_pairs_start_index", # 3 + "mentions_spans", # 4 + "mentions_words", # 5 + "pairs_ant_index", # 6 + "pairs_features", # 7 + "pairs_labels", # 8 + "locations", # 9 + "conll_tokens", # 10 + "spacy_lookup", # 11 + "doc", # 12 +] + +MISSED_MENTIONS_FILE = os.path.join( + PACKAGE_DIRECTORY, "test_mentions_identification.txt" +) +SENTENCES_PATH = os.path.join(PACKAGE_DIRECTORY, "test_sentences.txt") + +################### +### UTILITIES ##### + + +def clean_token(token): + cleaned_token = token + if cleaned_token in NORMALIZE_DICT: + cleaned_token = NORMALIZE_DICT[cleaned_token] + if cleaned_token not in REMOVED_CHAR: + for char in REMOVED_CHAR: + cleaned_token = cleaned_token.replace(char, "") + if len(cleaned_token) == 0: + cleaned_token = "," + return cleaned_token + + +def mention_words_idx(embed_extractor, mention, debug=False): + # index of the word in the tuned embeddings no need for normalizing, + # it is already performed in set_mentions_features() + # We take them in the tuned vocabulary which is a smaller voc tailored from conll + words = [] + for _, w in sorted(mention.words_embeddings_.items()): + if w not in embed_extractor.tun_idx: + if debug: + print( + "No matching tokens in tuned voc for word ", + w, + "surrounding or inside mention", + mention, + ) + words.append(MISSING_WORD) + else: + words.append(w) + return [embed_extractor.tun_idx[w] for w in words] + + +def check_numpy_array(feature, array, n_mentions_list, compressed=True): + for n_mentions in n_mentions_list: + if feature == FEATURES_NAMES[0]: + assert array.shape[0] == len(n_mentions) + if compressed: + assert np.array_equiv( + array[:, 3], np.array([len(n_mentions)] * len(n_mentions)) + ) + assert np.max(array[:, 2]) == len(n_mentions) - 1 + assert np.min(array[:, 2]) == 0 + elif feature == FEATURES_NAMES[1]: + assert array.shape[0] == len(n_mentions) + elif feature == FEATURES_NAMES[2]: + assert array.shape[0] == len(n_mentions) + assert np.array_equiv(array[:, 0], np.array(list(range(len(n_mentions))))) + elif feature == FEATURES_NAMES[3]: + assert array.shape[0] == len(n_mentions) + assert np.array_equiv( + array[:, 0], np.array([p * (p - 1) / 2 for p in range(len(n_mentions))]) + ) + elif feature == FEATURES_NAMES[4]: + assert array.shape[0] == len(n_mentions) + elif feature == FEATURES_NAMES[5]: + assert array.shape[0] == len(n_mentions) + elif feature == FEATURES_NAMES[6]: + assert array.shape[0] == len(n_mentions) * (len(n_mentions) - 1) / 2 + assert np.max(array) == len(n_mentions) - 2 + elif feature == FEATURES_NAMES[7]: + if compressed: + assert array.shape[0] == len(n_mentions) * (len(n_mentions) - 1) / 2 + assert np.max(array[:, 7]) == len(n_mentions) - 2 + assert np.min(array[:, 7]) == 0 + elif feature == FEATURES_NAMES[8]: + assert array.shape[0] == len(n_mentions) * (len(n_mentions) - 1) / 2 + + +############################################################################################### +### PARALLEL FCT (has to be at top-level of the module to be pickled for multiprocessing) ##### +def load_file(full_name, debug=False): + """ + load a *._conll file + Input: full_name: path to the file + Output: list of tuples for each conll doc in the file, where the tuple contains: + (utts_text ([str]): list of the utterances in the document + utts_tokens ([[str]]): list of the tokens (conll words) in the document + utts_corefs: list of coref objects (dicts) with the following properties: + coref['label']: id of the coreference cluster, + coref['start']: start index (index of first token in the utterance), + coref['end': end index (index of last token in the utterance). + utts_speakers ([str]): list of the speaker associated to each utterances in the document + name (str): name of the document + part (str): part of the document + ) + """ + docs = [] + with io.open(full_name, "rt", encoding="utf-8", errors="strict") as f: + lines = list(f) # .readlines() + utts_text = [] + utts_tokens = [] + utts_corefs = [] + utts_speakers = [] + tokens = [] + corefs = [] + index = 0 + speaker = "" + name = "" + part = "" + for li, line in enumerate(lines): + cols = line.split() + if debug: + print("line", li, "cols:", cols) + # End of utterance + if len(cols) == 0: + if tokens: + if debug: + print("End of utterance") + utts_text.append("".join(t + " " for t in tokens)) + utts_tokens.append(tokens) + utts_speakers.append(speaker) + utts_corefs.append(corefs) + tokens = [] + corefs = [] + index = 0 + speaker = "" + continue + # End of doc + elif len(cols) == 2: + if debug: + print("End of doc") + if cols[0] == "#end": + if debug: + print("Saving doc") + docs.append( + (utts_text, utts_tokens, utts_corefs, utts_speakers, name, part) + ) + utts_text = [] + utts_tokens = [] + utts_corefs = [] + utts_speakers = [] + else: + raise ValueError("Error on end line " + line) + # New doc + elif len(cols) == 5: + if debug: + print("New doc") + if cols[0] == "#begin": + name = re.match(r"\((.*)\);", cols[2]).group(1) + try: + part = cols[4] + except ValueError: + print("Error parsing document part " + line) + if debug: + print("New doc", name, part, name[:2]) + tokens = [] + corefs = [] + index = 0 + else: + raise ValueError("Error on begin line " + line) + # Inside utterance + elif len(cols) > 7: + if debug: + print("Inside utterance") + assert cols[0] == name and int(cols[1]) == int(part), ( + "Doc name or part error " + line + ) + assert int(cols[2]) == index, "Index error on " + line + if speaker: + assert cols[9] == speaker, "Speaker changed in " + line + speaker + else: + speaker = cols[9] + if debug: + print("speaker", speaker) + if cols[-1] != "-": + coref_expr = cols[-1].split("|") + if debug: + print("coref_expr", coref_expr) + if not coref_expr: + raise ValueError("Coref expression empty " + line) + for tok in coref_expr: + if debug: + print("coref tok", tok) + try: + match = re.match(r"^(\(?)(\d+)(\)?)$", tok) + except: + print("error getting coreferences for line " + line) + assert match is not None, ( + "Error parsing coref " + tok + " in " + line + ) + num = match.group(2) + assert num is not "", ( + "Error parsing coref " + tok + " in " + line + ) + if match.group(1) == "(": + if debug: + print("New coref", num) + corefs.append({"label": num, "start": index, "end": None}) + if match.group(3) == ")": + j = None + for i in range(len(corefs) - 1, -1, -1): + if debug: + print("i", i) + if ( + corefs[i]["label"] == num + and corefs[i]["end"] is None + ): + j = i + break + assert j is not None, "coref closing error " + line + if debug: + print("End coref", num) + corefs[j]["end"] = index + tokens.append(clean_token(cols[3])) + index += 1 + else: + raise ValueError("Line not standard " + line) + return docs + + +def set_feats(doc): + doc.set_mentions_features() + + +def get_feats(doc, i): + return doc.get_feature_array(doc_id=i) + + +def gather_feats(gathering_array, array, feat_name, pairs_ant_index, pairs_start_index): + if gathering_array is None: + gathering_array = array + else: + if feat_name == FEATURES_NAMES[6]: + array = [a + pairs_ant_index for a in array] + elif feat_name == FEATURES_NAMES[3]: + array = [a + pairs_start_index for a in array] + gathering_array += array + return feat_name, gathering_array + + +def read_file(full_name): + doc = "" + with io.open(full_name, "rt", encoding="utf-8", errors="strict") as f: + doc = f.read() + return doc + + +################### +### ConllDoc ##### + + +class ConllDoc(Document): + def __init__(self, name, part, *args, **kwargs): + self.name = name + self.part = part + self.feature_matrix = {} + self.conll_tokens = [] + self.conll_lookup = [] + self.gold_corefs = [] + self.missed_gold = [] + super(ConllDoc, self).__init__(*args, **kwargs) + + def get_conll_spacy_lookup(self, conll_tokens, spacy_tokens, debug=False): + """ + Compute a look up table between spacy tokens (from spacy tokenizer) + and conll pre-tokenized tokens + Output: list[conll_index] => list of associated spacy tokens (assume spacy tokenizer has a finer granularity) + """ + lookup = [] + c_iter = (t for t in conll_tokens) + s_iter = enumerate(t for t in spacy_tokens) + i, s_tok = next(s_iter) + for c_tok in c_iter: + # if debug: print("conll", c_tok, "spacy", s_tok, "index", i) + c_lookup = [] + while i is not None and len(c_tok) and c_tok.startswith(s_tok.text): + c_lookup.append(i) + c_tok = c_tok[len(s_tok) :] + i, s_tok = next(s_iter, (None, None)) + if debug and len(c_tok): + print("eating token: conll", c_tok, "spacy", s_tok, "index", i) + assert len(c_lookup), "Unmatched conll and spacy tokens" + lookup.append(c_lookup) + return lookup + + def add_conll_utterance( + self, parsed, tokens, corefs, speaker_id, use_gold_mentions, debug=False + ): + conll_lookup = self.get_conll_spacy_lookup(tokens, parsed) + self.conll_tokens.append(tokens) + self.conll_lookup.append(conll_lookup) + # Convert conll tokens coref index in spacy tokens indexes + identified_gold = [False] * len(corefs) + for coref in corefs: + missing_values = [key for key in ['label', 'start', 'end', ] if coref.get(key, None) is None] + if missing_values: + found_values = {key: coref[key] for key in ['label', 'start', 'end'] if coref.get(key, None) is not None} + raise Exception(f"Coref {self.name} with fields {found_values} has empty values for the keys {missing_values}.") + + coref["start"] = conll_lookup[coref["start"]][0] + coref["end"] = conll_lookup[coref["end"]][-1] + + if speaker_id not in self.speakers: + speaker_name = speaker_id.split("_") + if debug: + print("New speaker: ", speaker_id, "name: ", speaker_name) + self.speakers[speaker_id] = Speaker(speaker_id, speaker_name) + if use_gold_mentions: + for coref in corefs: + # print("coref['label']", coref['label']) + # print("coref text",parsed[coref['start']:coref['end']+1]) + mention = Mention( + parsed[coref["start"] : coref["end"] + 1], + len(self.mentions), + len(self.utterances), + self.n_sents, + speaker=self.speakers[speaker_id], + gold_label=coref["label"], + ) + self.mentions.append(mention) + # print("mention: ", mention, "label", mention.gold_label) + else: + mentions_spans = extract_mentions_spans( + doc=parsed, blacklist=self.blacklist + ) + self._process_mentions( + mentions_spans, + len(self.utterances), + self.n_sents, + self.speakers[speaker_id], + ) + + # Assign a gold label to mentions which have one + if debug: + print("Check corefs", corefs) + for i, coref in enumerate(corefs): + for m in self.mentions: + if m.utterance_index != len(self.utterances): + continue + # if debug: print("Checking mention", m, m.utterance_index, m.start, m.end) + if coref["start"] == m.start and coref["end"] == m.end - 1: + m.gold_label = coref["label"] + identified_gold[i] = True + # if debug: print("Gold mention found:", m, coref['label']) + for found, coref in zip(identified_gold, corefs): + if not found: + self.missed_gold.append( + [ + self.name, + self.part, + str(len(self.utterances)), + parsed.text, + parsed[coref["start"] : coref["end"] + 1].text, + ] + ) + if debug: + print( + "❄️ gold mention not in predicted mentions", + coref, + parsed[coref["start"] : coref["end"] + 1], + ) + self.utterances.append(parsed) + self.gold_corefs.append(corefs) + self.utterances_speaker.append(self.speakers[speaker_id]) + self.n_sents += len(list(parsed.sents)) + + def get_single_mention_features_conll(self, mention, compressed=True): + """ Compressed or not single mention features""" + if not compressed: + _, features = self.get_single_mention_features(mention) + return features[np.newaxis, :] + feat_l = [ + mention.features_["01_MentionType"], + mention.features_["02_MentionLength"], + mention.index, + len(self.mentions), + mention.features_["04_IsMentionNested"], + self.genre_, + ] + return feat_l + + def get_pair_mentions_features_conll(self, m1, m2, compressed=True): + """ Compressed or not single mention features""" + if not compressed: + _, features = self.get_pair_mentions_features(m1, m2) + return features[np.newaxis, :] + features_, _ = self.get_pair_mentions_features(m1, m2) + feat_l = [ + features_["00_SameSpeaker"], + features_["01_AntMatchMentionSpeaker"], + features_["02_MentionMatchSpeaker"], + features_["03_HeadsAgree"], + features_["04_ExactStringMatch"], + features_["05_RelaxedStringMatch"], + features_["06_SentenceDistance"], + features_["07_MentionDistance"], + features_["08_Overlapping"], + ] + return feat_l + + def get_feature_array(self, doc_id, feature=None, compressed=True, debug=False): + """ + Prepare feature array: + mentions_spans: (N, S) + mentions_words: (N, W) + mentions_features: (N, Fs) + mentions_labels: (N, 1) + mentions_pairs_start_index: (N, 1) index of beggining of pair list in pair_labels + mentions_pairs_length: (N, 1) number of pairs (i.e. nb of antecedents) for each mention + pairs_features: (P, Fp) + pairs_labels: (P, 1) + pairs_ant_idx: (P, 1) => indexes of antecedents mention for each pair (mention index in doc) + """ + if not self.mentions: + if debug: + print("No mention in this doc !") + return {} + if debug: + print("🛎 features matrices") + mentions_spans = [] + mentions_words = [] + mentions_features = [] + pairs_ant_idx = [] + pairs_features = [] + pairs_labels = [] + mentions_labels = [] + mentions_pairs_start = [] + mentions_pairs_length = [] + mentions_location = [] + n_mentions = 0 + total_pairs = 0 + if debug: + print("mentions", self.mentions, str([m.gold_label for m in self.mentions])) + for mention_idx, antecedents_idx in list( + self.get_candidate_pairs(max_distance=None, max_distance_with_match=None) + ): + n_mentions += 1 + mention = self.mentions[mention_idx] + mentions_spans.append(mention.spans_embeddings) + w_idx = mention_words_idx(self.embed_extractor, mention) + if w_idx is None: + print("error in", self.name, self.part, mention.utterance_index) + mentions_words.append(w_idx) + mentions_features.append( + self.get_single_mention_features_conll(mention, compressed) + ) + mentions_location.append( + [ + mention.start, + mention.end, + mention.utterance_index, + mention_idx, + doc_id, + ] + ) + ants = [self.mentions[ant_idx] for ant_idx in antecedents_idx] + no_antecedent = ( + not any(ant.gold_label == mention.gold_label for ant in ants) + or mention.gold_label is None + ) + if antecedents_idx: + pairs_ant_idx += [idx for idx in antecedents_idx] + pairs_features += [ + self.get_pair_mentions_features_conll(ant, mention, compressed) + for ant in ants + ] + ant_labels = ( + [0 for ant in ants] + if no_antecedent + else [ + 1 if ant.gold_label == mention.gold_label else 0 for ant in ants + ] + ) + pairs_labels += ant_labels + mentions_labels.append(1 if no_antecedent else 0) + mentions_pairs_start.append(total_pairs) + total_pairs += len(ants) + mentions_pairs_length.append(len(ants)) + + out_dict = { + FEATURES_NAMES[0]: mentions_features, + FEATURES_NAMES[1]: mentions_labels, + FEATURES_NAMES[2]: mentions_pairs_length, + FEATURES_NAMES[3]: mentions_pairs_start, + FEATURES_NAMES[4]: mentions_spans, + FEATURES_NAMES[5]: mentions_words, + FEATURES_NAMES[6]: pairs_ant_idx if pairs_ant_idx else None, + FEATURES_NAMES[7]: pairs_features if pairs_features else None, + FEATURES_NAMES[8]: pairs_labels if pairs_labels else None, + FEATURES_NAMES[9]: [mentions_location], + FEATURES_NAMES[10]: [self.conll_tokens], + FEATURES_NAMES[11]: [self.conll_lookup], + FEATURES_NAMES[12]: [ + { + "name": self.name, + "part": self.part, + "utterances": list(str(u) for u in self.utterances), + "mentions": list(str(m) for m in self.mentions), + } + ], + } + if debug: + print("🚘 Summary") + for k, v in out_dict.items(): + print(k, len(v)) + return n_mentions, total_pairs, out_dict + + +################### +### ConllCorpus ##### +class ConllCorpus(object): + def __init__( + self, + n_jobs=4, + embed_path=PACKAGE_DIRECTORY + "/weights/", + gold_mentions=False, + blacklist=False, + ): + self.n_jobs = n_jobs + self.features = {} + self.utts_text = [] + self.utts_tokens = [] + self.utts_corefs = [] + self.utts_speakers = [] + self.utts_doc_idx = [] + self.docs_names = [] + self.docs = [] + if embed_path is not None: + self.embed_extractor = EmbeddingExtractor(embed_path) + self.trainable_embed = [] + self.trainable_voc = [] + self.gold_mentions = gold_mentions + self.blacklist = blacklist + + def check_words_in_embeddings_voc(self, embedding, tuned=True, debug=False): + print("🌋 Checking if words are in embedding voc") + if tuned: + embed_voc = embedding.tun_idx + else: + embed_voc = embedding.stat_idx + missing_words = [] + missing_words_sents = [] + missing_words_doc = [] + for doc in self.docs: + # if debug: print("Checking doc", doc.name, doc.part) + for sent in doc.utterances: + # if debug: print(sent.text) + for word in sent: + w = embedding.normalize_word(word) + # if debug: print(w) + if w not in embed_voc: + missing_words.append(w) + missing_words_sents.append(sent.text) + missing_words_doc.append(doc.name + doc.part) + if debug: + out_str = ( + "No matching tokens in tuned voc for " + + w + + " in sentence " + + sent.text + + " in doc " + + doc.name + + doc.part + ) + print(out_str) + return missing_words, missing_words_sents, missing_words_doc + + def test_sentences_words(self, save_file, debug=False): + print("🌋 Saving sentence list") + with io.open(save_file, "w", encoding="utf-8") as f: + if debug: + print("Sentences saved in", save_file) + for doc in self.docs: + out_str = "#begin document (" + doc.name + "); part " + doc.part + "\n" + f.write(out_str) + for sent in doc.utterances: + f.write(sent.text + "\n") + out_str = "#end document\n\n" + f.write(out_str) + + def save_sentences(self, save_file, debug=False): + print("🌋 Saving sentence list") + with io.open(save_file, "w", encoding="utf-8") as f: + if debug: + print("Sentences saved in", save_file) + for doc in self.docs: + out_str = "#begin document (" + doc.name + "); part " + doc.part + "\n" + f.write(out_str) + for sent in doc.utterances: + f.write(sent.text + "\n") + out_str = "#end document\n\n" + f.write(out_str) + + def build_key_file(self, data_path, key_file, debug=False): + print("🌋 Building key file from corpus") + print("Saving in", key_file) + # Create a pool of processes. By default, one is created for each CPU in your machine. + with io.open(key_file, "w", encoding="utf-8") as kf: + if debug: + print("Key file saved in", key_file) + for dirpath, _, filenames in os.walk(data_path): + print("In", dirpath) + file_list = [ + os.path.join(dirpath, f) + for f in filenames + if f.endswith(".v4_auto_conll") or f.endswith(".v4_gold_conll") + ] + cleaned_file_list = [] + for f in file_list: + fn = f.split(".") + if fn[1] == "v4_auto_conll": + gold = fn[0] + "." + "v4_gold_conll" + if gold not in file_list: + cleaned_file_list.append(f) + else: + cleaned_file_list.append(f) + # self.load_file(file_list[0]) + doc_list = parallel_process(cleaned_file_list, read_file) + for doc in doc_list: + kf.write(doc) + + def list_undetected_mentions(self, data_path, save_file, debug=True): + self.read_corpus(data_path) + print("🌋 Listing undetected mentions") + with io.open(save_file, "w", encoding="utf-8") as out_file: + for doc in tqdm(self.docs): + for name, part, utt_i, utt, coref in doc.missed_gold: + out_str = name + "\t" + part + "\t" + utt_i + '\t"' + utt + '"\n' + out_str += coref + "\n" + out_file.write(out_str) + if debug: + print(out_str) + + def read_corpus(self, data_path, model=None, debug=False): + print("🌋 Reading files") + for dirpath, _, filenames in os.walk(data_path): + print("In", dirpath, os.path.abspath(dirpath)) + file_list = [ + os.path.join(dirpath, f) + for f in filenames + if f.endswith(".v4_auto_conll") or f.endswith(".v4_gold_conll") + ] + cleaned_file_list = [] + for f in file_list: + fn = f.split(".") + if fn[1] == "v4_auto_conll": + gold = fn[0] + "." + "v4_gold_conll" + if gold not in file_list: + cleaned_file_list.append(f) + else: + cleaned_file_list.append(f) + doc_list = parallel_process(cleaned_file_list, load_file) + for docs in doc_list: # executor.map(self.load_file, cleaned_file_list): + for ( + utts_text, + utt_tokens, + utts_corefs, + utts_speakers, + name, + part, + ) in docs: + if debug: + print("Imported", name) + print("utts_text", utts_text) + print("utt_tokens", utt_tokens) + print("utts_corefs", utts_corefs) + print("utts_speakers", utts_speakers) + print("name, part", name, part) + self.utts_text += utts_text + self.utts_tokens += utt_tokens + self.utts_corefs += utts_corefs + self.utts_speakers += utts_speakers + self.utts_doc_idx += [len(self.docs_names)] * len(utts_text) + self.docs_names.append((name, part)) + print("utts_text size", len(self.utts_text)) + print("utts_tokens size", len(self.utts_tokens)) + print("utts_corefs size", len(self.utts_corefs)) + print("utts_speakers size", len(self.utts_speakers)) + print("utts_doc_idx size", len(self.utts_doc_idx)) + print("🌋 Building docs") + for name, part in self.docs_names: + self.docs.append( + ConllDoc( + name=name, + part=part, + nlp=None, + blacklist=self.blacklist, + consider_speakers=True, + embedding_extractor=self.embed_extractor, + conll=CONLL_GENRES[name[:2]], + ) + ) + print("🌋 Loading spacy model") + + if model is None: + model_options = ["en_core_web_lg", "en_core_web_md", "en_core_web_sm", "en"] + for model_option in model_options: + if not model: + try: + spacy.info(model_option) + model = model_option + print("Loading model", model_option) + except: + print("Could not detect model", model_option) + if not model: + print("Could not detect any suitable English model") + return + else: + spacy.info(model) + print("Loading model", model) + nlp = spacy.load(model) + print( + "🌋 Parsing utterances and filling docs with use_gold_mentions=" + + (str(bool(self.gold_mentions))) + ) + doc_iter = (s for s in self.utts_text) + for utt_tuple in tqdm( + zip( + nlp.pipe(doc_iter), + self.utts_tokens, + self.utts_corefs, + self.utts_speakers, + self.utts_doc_idx, + ) + ): + spacy_tokens, conll_tokens, corefs, speaker, doc_id = utt_tuple + if debug: + print(unicode_(self.docs_names[doc_id]), "-", spacy_tokens) + doc = spacy_tokens + if debug: + out_str = ( + "utterance " + + unicode_(doc) + + " corefs " + + unicode_(corefs) + + " speaker " + + unicode_(speaker) + + "doc_id" + + unicode_(doc_id) + ) + print(out_str.encode("utf-8")) + self.docs[doc_id].add_conll_utterance( + doc, conll_tokens, corefs, speaker, use_gold_mentions=self.gold_mentions + ) + + def build_and_gather_multiple_arrays(self, save_path): + print(f"🌋 Extracting mentions features with {self.n_jobs} job(s)") + parallel_process(self.docs, set_feats, n_jobs=self.n_jobs) + + print(f"🌋 Building and gathering array with {self.n_jobs} job(s)") + arr = [{"doc": doc, "i": i} for i, doc in enumerate(self.docs)] + arrays_dicts = parallel_process( + arr, get_feats, use_kwargs=True, n_jobs=self.n_jobs + ) + gathering_dict = dict((feat, None) for feat in FEATURES_NAMES) + n_mentions_list = [] + pairs_ant_index = 0 + pairs_start_index = 0 + for npaidx in tqdm(range(len(arrays_dicts))): + try: + n, p, arrays_dict = arrays_dicts[npaidx] + except: + # empty array dict, cannot extract the dict values for this doc + continue + + for f in FEATURES_NAMES: + if gathering_dict[f] is None: + gathering_dict[f] = arrays_dict[f] + else: + if f == FEATURES_NAMES[6]: + array = [a + pairs_ant_index for a in arrays_dict[f]] + elif f == FEATURES_NAMES[3]: + array = [a + pairs_start_index for a in arrays_dict[f]] + else: + array = arrays_dict[f] + gathering_dict[f] += array + pairs_ant_index += n + pairs_start_index += p + n_mentions_list.append(n) + + for feature in FEATURES_NAMES[:9]: + feature_data = gathering_dict[feature] + if not feature_data: + print("No data for", feature) + continue + print("Building numpy array for", feature, "length", len(feature_data)) + if feature != "mentions_spans": + array = np.array(feature_data) + if array.ndim == 1: + array = np.expand_dims(array, axis=1) + else: + array = np.stack(feature_data) + # check_numpy_array(feature, array, n_mentions_list) + print("Saving numpy", feature, "size", array.shape) + np.save(save_path + feature, array) + for feature in FEATURES_NAMES[9:]: + feature_data = gathering_dict[feature] + if feature_data: + print("Saving pickle", feature, "size", len(feature_data)) + with open(save_path + feature + ".bin", "wb") as fp: + pickle.dump(feature_data, fp) + + def save_vocabulary(self, save_path, debug=False): + def _vocabulary_to_file(path, vocabulary): + print("🌋 Saving vocabulary") + with io.open(path, "w", encoding="utf-8") as f: + if debug: + print(f"voc saved in {path}, length: {len(vocabulary)}") + for w in tunable_voc: + f.write(w + "\n") + + print("🌋 Building tunable vocabulary matrix from static vocabulary") + tunable_voc = self.embed_extractor.tun_voc + _vocabulary_to_file( + path=save_path + "tuned_word_vocabulary.txt", vocabulary=tunable_voc + ) + + static_voc = self.embed_extractor.stat_voc + _vocabulary_to_file( + path=save_path + "static_word_vocabulary.txt", vocabulary=static_voc + ) + + tuned_word_embeddings = np.vstack( + [self.embed_extractor.get_stat_word(w)[1] for w in tunable_voc] + ) + print("Saving tunable voc, size:", tuned_word_embeddings.shape) + np.save(save_path + "tuned_word_embeddings", tuned_word_embeddings) + + static_word_embeddings = np.vstack( + [self.embed_extractor.static_embeddings[w] for w in static_voc] + ) + print("Saving static voc, size:", static_word_embeddings.shape) + np.save(save_path + "static_word_embeddings", static_word_embeddings) + + +if __name__ == "__main__": + DIR_PATH = os.path.dirname(os.path.realpath(__file__)) + parser = argparse.ArgumentParser( + description="Training the neural coreference model" + ) + parser.add_argument( + "--function", + type=str, + default="all", + help='Function ("all", "key", "parse", "find_undetected")', + ) + parser.add_argument( + "--path", type=str, default=DIR_PATH + "/data/", help="Path to the dataset" + ) + parser.add_argument( + "--key", type=str, help="Path to an optional key file for scoring" + ) + parser.add_argument( + "--n_jobs", type=int, default=1, help="Number of parallel jobs (default 1)" + ) + parser.add_argument( + "--gold_mentions", + type=int, + default=0, + help="Use gold mentions (1) or not (0, default)", + ) + parser.add_argument( + "--blacklist", type=int, default=0, help="Use blacklist (1) or not (0, default)" + ) + parser.add_argument("--spacy_model", type=str, default=None, help="model name") + args = parser.parse_args() + if args.key is None: + args.key = args.path + "/key.txt" + CORPUS = ConllCorpus( + n_jobs=args.n_jobs, gold_mentions=args.gold_mentions, blacklist=args.blacklist + ) + if args.function == "parse" or args.function == "all": + SAVE_DIR = args.path + "/numpy/" + if not os.path.exists(SAVE_DIR): + os.makedirs(SAVE_DIR) + else: + if os.listdir(SAVE_DIR): + print("There are already data in", SAVE_DIR) + print("Erasing") + for file in os.listdir(SAVE_DIR): + print(file) + os.remove(SAVE_DIR + file) + start_time = time.time() + CORPUS.read_corpus(args.path, model=args.spacy_model) + print("=> read_corpus time elapsed", time.time() - start_time) + if not CORPUS.docs: + print("Could not parse any valid docs") + else: + start_time2 = time.time() + CORPUS.build_and_gather_multiple_arrays(SAVE_DIR) + print( + "=> build_and_gather_multiple_arrays time elapsed", + time.time() - start_time2, + ) + start_time2 = time.time() + CORPUS.save_vocabulary(SAVE_DIR) + print("=> save_vocabulary time elapsed", time.time() - start_time2) + print("=> total time elapsed", time.time() - start_time) + if args.function == "key" or args.function == "all": + CORPUS.build_key_file(args.path, args.key) + if args.function == "find_undetected": + CORPUS.list_undetected_mentions( + args.path, args.path + "/undetected_mentions.txt" + ) diff --git a/data_tooling/pii_processing/neuralcoref/train/data/.gitignore b/data_tooling/pii_processing/neuralcoref/train/data/.gitignore new file mode 100644 index 0000000..86d0cb2 --- /dev/null +++ b/data_tooling/pii_processing/neuralcoref/train/data/.gitignore @@ -0,0 +1,4 @@ +# Ignore everything in this directory +* +# Except this file +!.gitignore \ No newline at end of file diff --git a/data_tooling/pii_processing/neuralcoref/train/dataset.py b/data_tooling/pii_processing/neuralcoref/train/dataset.py new file mode 100644 index 0000000..0831768 --- /dev/null +++ b/data_tooling/pii_processing/neuralcoref/train/dataset.py @@ -0,0 +1,536 @@ +"""Conll training algorithm""" + +import os +import io +import numpy as np + +import torch +import torch.utils.data + +from torch.utils.data.sampler import Sampler +from torch.utils.data import Dataset + +from neuralcoref.train.utils import ( + encode_distance, + BATCH_SIZE_PATH, + SIZE_FP, + SIZE_FP_COMPRESSED, + SIZE_FS, + SIZE_FS_COMPRESSED, + SIZE_GENRE, + SIZE_PAIR_IN, + SIZE_SINGLE_IN, +) +from neuralcoref.train.conllparser import FEATURES_NAMES + + +def load_embeddings_from_file(name): + print("loading", name + "_embeddings.npy") + embed = torch.from_numpy(np.load(name + "_embeddings.npy")).float() + print(embed.size()) + print("loading", name + "_vocabulary.txt") + with io.open(name + "_vocabulary.txt", "r", encoding="utf-8") as f: + voc = [line.strip() for line in f] + return embed, voc + + +class _DictionaryDataLoader(object): + def __init__(self, dict_object, order): + self.dict_object = dict_object + self.order = order + + def __len__(self): + return len(self.dict_object[self.order[0]]) + + def __getitem__(self, idx): + if isinstance(idx, slice): + data = [] + for i in range( + idx.start, idx.stop, idx.step if idx.step is not None else 1 + ): + temp_data = [] + for key in self.order: + temp_data.append(self.dict_object[key][i]) + data.append(temp_data) + + else: + data = [] + for key in self.order: + data.append(self.dict_object[key][idx]) + + return data + + +class NCDataset(Dataset): + def __init__(self, data_path, params, no_targets=False): + print("🏝 Loading Dataset at", data_path) + self.costs = params.costs + self.no_targets = no_targets + # Load files + datas = {} + if not os.listdir(data_path): + raise ValueError("Empty data_path") + numpy_files_found = False + print("Reading ", end="") + for file_name in os.listdir(data_path): + if not ".npy" in file_name: + continue + numpy_files_found = True + print(file_name, end=", ") + datas[file_name.split(".")[0]] = np.load( + data_path + file_name, mmap_mode="r" if params.lazy else None + ) + if not numpy_files_found: + raise ValueError(f"Can't find numpy files in {data_path}") + + # Gather arrays in two lists of tuples for mention and pairs + if not params.lazy: + self.mentions = list( + zip( + *( + arr + for key, arr in sorted(datas.items()) + if key.startswith("mentions") + ) + ) + ) + self.pairs = list( + zip( + *( + arr + for key, arr in sorted(datas.items()) + if key.startswith("pairs") + ) + ) + ) + else: + self.mentions = _DictionaryDataLoader( + datas, + order=( + "mentions_features", + "mentions_labels", + "mentions_pairs_length", + "mentions_pairs_start_index", + "mentions_spans", + "mentions_words", + ), + ) + self.pairs = _DictionaryDataLoader( + datas, order=("pairs_ant_index", "pairs_features", "pairs_labels") + ) + + self.mentions_pair_length = datas[FEATURES_NAMES[2]] + assert [arr.shape[0] for arr in self.mentions[0]] == [ + 6, + 1, + 1, + 1, + 250, + 8, + ] # Cf order of FEATURES_NAMES in conllparser.py + assert [arr.shape[0] for arr in self.pairs[0]] == [ + 1, + 9, + 1, + ] # Cf order of FEATURES_NAMES in conllparser.py + + def __len__(self): + return len(self.mentions) + + def __getitem__(self, mention_idx, debug=False): + """ + Return: + Definitions: + P is the number of antecedent per mention (number of pairs for the mention) + S = 250 is the size of the span vector (averaged word embeddings) + W = 8 is the number of words in a mention (tuned embeddings) + Fp = 70 is the number of features for a pair of mention + Fs = 24 is the number of features of a single mention + + if there are some pairs: + inputs = (spans, words, features, ant_spans, ant_words, ana_spans, ana_words, pairs_features) + targets = (labels, costs, true_ants, false_ants) + else: + inputs = (spans, words, features) + targets = (labels, costs, true_ants) + + inputs: Tuple of + spans => (S,) + words => (W,) + features => (Fs,) + + if there are potential antecedents (P > 0): + ant_spans => (P, S) or nothing if no pairs + ant_words => (P, W) or nothing if no pairs + ana_spans => (P, S) or nothing if no pairs + ana_words => (P, W) or nothing if no pairs + pair_features => (P, Fp) or nothing if no pairs + + targets: Tuple of + labels => (P+1,) + costs => (P+1,) + true_ant => (P+1,) + + if there are potential antecedents (P > 0): + false_ant => (P+1,) + + """ + features_raw, label, pairs_length, pairs_start_index, spans, words = self.mentions[ + mention_idx + ] + pairs_start_index = pairs_start_index.item() + pairs_length = pairs_length.item() + + # Build features array (float) from raw features (int) + assert features_raw.shape[0] == SIZE_FS_COMPRESSED + features = np.zeros((SIZE_FS,)) + features[features_raw[0]] = 1 + features[4:15] = encode_distance(features_raw[1]) + features[15] = features_raw[2].astype(float) / features_raw[3].astype(float) + features[16] = features_raw[4] + features[features_raw[5] + 17] = 1 + + if pairs_length == 0: + spans = torch.from_numpy(spans).float() + words = torch.from_numpy(words) + features = torch.from_numpy(features).float() + inputs = (spans, words, features) + if self.no_targets: + return inputs + true_ant = torch.zeros(1).long() # zeros = indices of true ant + costs = torch.from_numpy((1 - label) * self.costs["FN"]).float() + label = torch.from_numpy(label).float() + targets = (label, costs, true_ant) + if debug: + print("inputs shapes: ", [a.size() for a in inputs]) + print("targets shapes: ", [a.size() for a in targets]) + return inputs, targets + + start = pairs_start_index + end = pairs_start_index + pairs_length + pairs = self.pairs[start:end] + assert len(pairs) == pairs_length + assert ( + len(pairs[0]) == 3 + ) # pair[i] = (pairs_ant_index, pairs_features, pairs_labels) + pairs_ant_index, pairs_features_raw, pairs_labels = list(zip(*pairs)) + + pairs_features_raw = np.stack(pairs_features_raw) + pairs_labels = np.squeeze(np.stack(pairs_labels), axis=1) + + # Build pair features array (float) from raw features (int) + assert pairs_features_raw[0, :].shape[0] == SIZE_FP_COMPRESSED + pairs_features = np.zeros((len(pairs_ant_index), SIZE_FP)) + pairs_features[:, 0:6] = pairs_features_raw[:, 0:6] + pairs_features[:, 6:17] = encode_distance(pairs_features_raw[:, 6]) + pairs_features[:, 17:28] = encode_distance(pairs_features_raw[:, 7]) + pairs_features[:, 28] = pairs_features_raw[:, 8] + # prepare antecent features + ant_features_raw = np.concatenate( + [self.mentions[idx.item()][0][np.newaxis, :] for idx in pairs_ant_index] + ) + ant_features = np.zeros((pairs_length, SIZE_FS - SIZE_GENRE)) + ant_features[:, ant_features_raw[:, 0]] = 1 + ant_features[:, 4:15] = encode_distance(ant_features_raw[:, 1]) + ant_features[:, 15] = ant_features_raw[:, 2].astype(float) / ant_features_raw[ + :, 3 + ].astype(float) + ant_features[:, 16] = ant_features_raw[:, 4] + pairs_features[:, 29:46] = ant_features + # Here we keep the genre + ana_features = np.tile(features, (pairs_length, 1)) + pairs_features[:, 46:] = ana_features + + ant_spans = np.concatenate( + [self.mentions[idx.item()][4][np.newaxis, :] for idx in pairs_ant_index] + ) + ant_words = np.concatenate( + [self.mentions[idx.item()][5][np.newaxis, :] for idx in pairs_ant_index] + ) + ana_spans = np.tile(spans, (pairs_length, 1)) + ana_words = np.tile(words, (pairs_length, 1)) + ant_spans = torch.from_numpy(ant_spans).float() + ant_words = torch.from_numpy(ant_words) + ana_spans = torch.from_numpy(ana_spans).float() + ana_words = torch.from_numpy(ana_words) + pairs_features = torch.from_numpy(pairs_features).float() + + labels_stack = np.concatenate((pairs_labels, label), axis=0) + assert labels_stack.shape == (pairs_length + 1,) + labels = torch.from_numpy(labels_stack).float() + + spans = torch.from_numpy(spans).float() + words = torch.from_numpy(words) + features = torch.from_numpy(features).float() + + inputs = ( + spans, + words, + features, + ant_spans, + ant_words, + ana_spans, + ana_words, + pairs_features, + ) + + if self.no_targets: + return inputs + + if label == 0: + costs = np.concatenate( + (self.costs["WL"] * (1 - pairs_labels), [self.costs["FN"]]) + ) # Inverse labels: 1=>0, 0=>1 + else: + costs = np.concatenate((self.costs["FL"] * np.ones_like(pairs_labels), [0])) + assert costs.shape == (pairs_length + 1,) + costs = torch.from_numpy(costs).float() + + true_ants_unpad = np.flatnonzero(labels_stack) + if len(true_ants_unpad) == 0: + raise ValueError("Error: no True antecedent for mention") + true_ants = np.pad( + true_ants_unpad, (0, len(pairs_labels) + 1 - len(true_ants_unpad)), "edge" + ) + assert true_ants.shape == (pairs_length + 1,) + true_ants = torch.from_numpy(true_ants).long() + + false_ants_unpad = np.flatnonzero(1 - labels_stack) + assert len(false_ants_unpad) != 0 + false_ants = np.pad( + false_ants_unpad, (0, len(pairs_labels) + 1 - len(false_ants_unpad)), "edge" + ) + assert false_ants.shape == (pairs_length + 1,) + false_ants = torch.from_numpy(false_ants).long() + + targets = (labels, costs, true_ants, false_ants) + if debug: + print("Mention", mention_idx) + print("inputs shapes: ", [a.size() for a in inputs]) + print("targets shapes: ", [a.size() for a in targets]) + return inputs, targets + + +class NCBatchSampler(Sampler): + """A Batch sampler to group mentions in batches with close number of pairs to be padded together + """ + + def __init__( + self, mentions_pairs_length, batchsize=600, shuffle=False, debug=False + ): + """ Create and feed batches of mentions having close number of antecedents + The batch are padded and collated by the padder_collate function + + # Arguments: + mentions_pairs_length array of shape (N, 1): list/array of the number of pairs for each mention + batchsize: Number of pairs of each batch will be capped at this + """ + self.shuffle = shuffle + num_mentions = len(mentions_pairs_length) + mentions_lengths = np.concatenate( + [ + mentions_pairs_length, + np.arange(0, num_mentions, 1, dtype=int)[:, np.newaxis], + ], + axis=1, + ) + sorted_lengths = mentions_lengths[mentions_lengths[:, 0].argsort()] + print("Preparing batches 📚") + + self.batches = [] + self.batches_pairs = [] + self.batches_size = [] + batch = [] + n_pairs = [] + num = 0 + for length, mention_idx in sorted_lengths: + if num > batchsize or ( + num == len(batch) and length != 0 + ): # We keep the no_pairs batches pure + if debug: + print( + "Added batch number", + len(self.batches), + "with", + len(batch), + "mentions and", + num, + "pairs", + ) + self.batches.append(batch) + self.batches_size.append( + num + ) # We don't count the max 7 additional mentions that are repeated + self.batches_pairs.append(n_pairs) + + # Start a new batch + batch = [mention_idx] + n_pairs = [length] + num = ( + length + 1 + ) # +1 since we also have the single mention to add to the number of pairs + else: + num += length + 1 + batch.append(mention_idx) + n_pairs.append(length) + + # Complete and store the last batch + if debug: + print( + "Added batch number", + len(self.batches), + "with", + len(batch), + "mentions and", + num, + "pairs", + ) + self.batches.append(batch) + self.batches_size.append(num) + self.batches_pairs.append(n_pairs) + self.n_pairs = sum(sum(p) for p in self.batches_pairs) + self.n_mentions = sum(len(b) for b in self.batches) + self.n_batches = len(self.batches) + self.pairs_per_batch = float(self.n_pairs) / self.n_batches + self.mentions_per_batch = float(self.n_mentions) / self.n_batches + print( + "Dataset has:", + self.n_batches, + "batches,", + self.n_mentions, + "mentions,", + self.n_pairs, + "pairs", + ) + + def get_batch_info(self): + return self.batches, self.batches_pairs + + def save_batch_sizes(self, save_file=BATCH_SIZE_PATH, debug=False): + print("🌋 Saving sizes of batches") + with io.open(save_file, "w", encoding="utf-8") as f: + if debug: + print("Batch sizes saved in", save_file) + for batch, size in zip(self.batches, self.batches_size): + out_str = str(len(batch)) + "\t" + str(size) + "\n" + f.write(out_str) + + def __iter__(self): + if self.shuffle: + np.random.shuffle(self.batches) + for batch in self.batches: + yield batch + + def __len__(self): + return self.n_batches + + +def padder_collate(batch, debug=False): + """ Puts each data field into a tensor with outer dimension batch size + Pad variable length input tensors and add a weight tensor to the target + """ + transposed_inputs = tuple(zip(*batch)) + if len(transposed_inputs) == 2: + inputs, targets = transposed_inputs + transposed_inputs = tuple(zip(*inputs)) + transposed_targets = tuple(zip(*targets)) + else: + transposed_targets = None + + max_pairs = ( + max(len(t) for t in transposed_inputs[3]) if len(transposed_inputs) == 8 else 0 + ) # Get max nb of pairs (batch are sorted by nb of pairs) + if max_pairs > 0: + out_inputs = [] + out_targets = [] + for t_inp in transposed_inputs: + if len(t_inp[0].shape) == 2: + out_inputs.append( + torch.stack( + [ + torch.cat([t, t.new(max_pairs - len(t), len(t[0])).zero_()]) + if len(t) != max_pairs + else t + for t in t_inp + ], + 0, + ) + ) + else: + out_inputs.append(torch.stack(t_inp, 0)) + if transposed_targets is not None: + for i, t_targ in enumerate( + transposed_targets + ): # 0:labels, 1:costs, 2:true_ants, 3:false_ants + if i == 2 or i == 3: + if debug: + print("collate before", t_targ) + # shift the antecedent index associated to single anaphores (last) + t_targ = tuple( + t.masked_fill_(torch.eq(t, len(t) - 1), max_pairs) + for t in t_targ + ) + if debug: + print("collate after", t_targ) + out_targets.append( + torch.stack( + [ + torch.cat( + [ + t[:-1] if len(t) > 2 else t.new(1).fill_(t[0]), + t.new(max_pairs + 1 - len(t)).fill_(t[0]), + t.new(1).fill_(t[-1]), + ] + ) + if len(t) != max_pairs + 1 + else t + for t in t_targ + ], + 0, + ) + ) + + t_costs = transposed_targets[ + 1 + ] # We build the weights from the costs to have a float Tensor + out_targets.append( + torch.stack( + [ + torch.cat( + [ + t.new(len(t) - 1).fill_(1), + t.new(max_pairs + 1 - len(t)).zero_(), + t.new(1).fill_(1), + ] + ) + if len(t) != max_pairs + 1 + else t.new(max_pairs + 1).fill_(1) + for t in t_costs + ], + 0, + ) + ) + else: + # Remark this mask is the inverse of the weights in the above target (used for evaluation masking) + t_base = transposed_inputs[3] + out_targets = torch.stack( + [ + torch.cat( + [ + t.new(len(t) - 1).zero_().bool(), + t.new(max_pairs + 1 - len(t)).fill_(1).bool(), + t.new(1).zero_().bool(), + ] + ) + if len(t) != max_pairs + 1 + else t.new(max_pairs + 1).zero_().bool() + for t in t_base + ], + 0, + ) + else: + out_inputs = [torch.stack(t_inp, 0) for t_inp in transposed_inputs] + if transposed_targets is not None: + out_targets = [torch.stack(t_targ, 0) for t_targ in transposed_targets] + out_targets.append(out_targets[1].new(len(out_targets[1]), 1).fill_(1)) + else: + out_targets = out_inputs[0].new(len(out_inputs[0]), 1).zero_().bool() + return (out_inputs, out_targets) diff --git a/data_tooling/pii_processing/neuralcoref/train/document.py b/data_tooling/pii_processing/neuralcoref/train/document.py new file mode 100644 index 0000000..b6e330a --- /dev/null +++ b/data_tooling/pii_processing/neuralcoref/train/document.py @@ -0,0 +1,982 @@ +"""data models and pre-processing for the coref algorithm""" + +import re +import io +from six import string_types, integer_types +from spacy.tokens import Span, Token + +from neuralcoref.train.compat import unicode_ +from neuralcoref.train.utils import encode_distance, parallel_process + +try: + from itertools import izip_longest as zip_longest +except ImportError: # will be 3.x series + from itertools import zip_longest + +import spacy +import numpy as np + +######################### +####### UTILITIES ####### +######################### + +NO_COREF_LIST = ["i", "me", "my", "you", "your"] + +MENTION_TYPE = {"PRONOMINAL": 0, "NOMINAL": 1, "PROPER": 2, "LIST": 3} +MENTION_LABEL = {0: "PRONOMINAL", 1: "NOMINAL", 2: "PROPER", 3: "LIST"} + +PROPERS_TAGS = ["NN", "NNS", "NNP", "NNPS"] +ACCEPTED_ENTS = [ + "PERSON", + "NORP", + "FACILITY", + "ORG", + "GPE", + "LOC", + "PRODUCT", + "EVENT", + "WORK_OF_ART", + "LANGUAGE", +] +WHITESPACE_PATTERN = r"\s+|_+" +UNKNOWN_WORD = "*UNK*" +MISSING_WORD = "" +MAX_ITER = 100 + +######################### +## MENTION EXTRACTION ### +######################### + + +def extract_mentions_spans(doc, blacklist, debug=False): + """ + Extract potential mentions from a spacy parsed Doc + """ + if debug: + print("===== doc ====:", doc) + for c in doc: + if debug: + print( + "🚧 span search:", + c, + "head:", + c.head, + "tag:", + c.tag_, + "pos:", + c.pos_, + "dep:", + c.dep_, + ) + # Named entities + mentions_spans = list(ent for ent in doc.ents if ent.label_ in ACCEPTED_ENTS) + + if debug: + print("==-- ents:", list(((ent, ent.label_) for ent in mentions_spans))) + for spans in parallel_process( + [{"doc": doc, "span": sent, "blacklist": blacklist} for sent in doc.sents], + _extract_from_sent, + use_kwargs=True, + front_num=0, + ): + mentions_spans = mentions_spans + spans + spans_set = set() + cleaned_mentions_spans = [] + for spans in mentions_spans: + if spans.end > spans.start and (spans.start, spans.end) not in spans_set: + cleaned_mentions_spans.append(spans) + spans_set.add((spans.start, spans.end)) + + return cleaned_mentions_spans + + +def _extract_from_sent(doc, span, blacklist=True, debug=False): + """ + Extract Pronouns and Noun phrases mentions from a spacy Span + """ + keep_tags = re.compile(r"N.*|PRP.*|DT|IN") + leave_dep = ["det", "compound", "appos"] + keep_dep = ["nsubj", "dobj", "iobj", "pobj"] + nsubj_or_dep = ["nsubj", "dep"] + conj_or_prep = ["conj", "prep"] + remove_pos = ["CCONJ", "SCONJ", "INTJ", "ADP"] + lower_not_end = ["'s", ",", ".", "!", "?", ":", ";"] + + # Utility to remove bad endings + def cleanup_endings(left, right, token): + minchild_idx = min(left + [token.i]) if left else token.i + maxchild_idx = max(right + [token.i]) if right else token.i + # Clean up endings and begginging + while maxchild_idx >= minchild_idx and ( + doc[maxchild_idx].pos_ in remove_pos + or doc[maxchild_idx].lower_ in lower_not_end + ): + if debug: + print( + "Removing last token", + doc[maxchild_idx].lower_, + doc[maxchild_idx].tag_, + ) + maxchild_idx -= ( + 1 + ) # We don't want mentions finishing with 's or conjunctions/punctuation + while minchild_idx <= maxchild_idx and ( + doc[minchild_idx].pos_ in remove_pos + or doc[minchild_idx].lower_ in lower_not_end + ): + if debug: + print( + "Removing first token", + doc[minchild_idx].lower_, + doc[minchild_idx].tag_, + ) + minchild_idx += ( + 1 + ) # We don't want mentions starting with 's or conjunctions/punctuation + return minchild_idx, maxchild_idx + 1 + + mentions_spans = [] + for token in span: + if debug: + print( + "🚀 tok:", + token, + "tok.tag_:", + token.tag_, + "tok.pos_:", + token.pos_, + "tok.dep_:", + token.dep_, + ) + + if blacklist and token.lower_ in NO_COREF_LIST: + if debug: + print("token in no_coref_list") + continue + if ( + not keep_tags.match(token.tag_) or token.dep_ in leave_dep + ) and not token.dep_ in keep_dep: + if debug: + print("not pronoun or no right dependency") + continue + + # pronoun + if re.match(r"PRP.*", token.tag_): + if debug: + print("PRP") + endIdx = token.i + 1 + + span = doc[token.i : endIdx] + if debug: + print("==-- PRP store:", span) + mentions_spans.append(span) + + # when pronoun is a part of conjunction (e.g., you and I) + if token.n_rights > 0 or token.n_lefts > 0: + span = doc[token.left_edge.i : token.right_edge.i + 1] + if debug: + print("==-- in conj store:", span) + mentions_spans.append(span) + continue + + # Add NP mention + if debug: + print("NP or IN:", token.lower_) + if token.tag_ == "IN": + print("IN tag") + # Take care of 's + if token.lower_ == "'s": + if debug: + print("'s detected") + h = token.head + j = 0 + while h.head.i != h.i and j < MAX_ITER: + if debug: + print("token head:", h, h.dep_, "head:", h.head) + print(id(h.head), id(h)) + if h.dep_ == "nsubj": + minchild_idx = min( + ( + c.left_edge.i + for c in doc + if c.head.i == h.head.i and c.dep_ in nsubj_or_dep + ), + default=token.i, + ) + maxchild_idx = max( + ( + c.right_edge.i + for c in doc + if c.head.i == h.head.i and c.dep_ in nsubj_or_dep + ), + default=token.i, + ) + if debug: + print("'s', i1:", doc[minchild_idx], " i2:", doc[maxchild_idx]) + span = doc[minchild_idx : maxchild_idx + 1] + if debug: + print("==-- 's' store:", span) + mentions_spans.append(span) + break + h = h.head + j += 1 + assert j != MAX_ITER + continue + + # clean up + for c in doc: + if debug and c.head.i == token.i: + print("🚧 token in span:", c, "- head & dep:", c.head, c.dep_) + left = list(c.left_edge.i for c in doc if c.head.i == token.i) + right = list(c.right_edge.i for c in doc if c.head.i == token.i) + if ( + token.tag_ == "IN" + and token.dep_ == "mark" + and len(left) == 0 + and len(right) == 0 + ): + left = list(c.left_edge.i for c in doc if c.head.i == token.head.i) + right = list(c.right_edge.i for c in doc if c.head.i == token.head.i) + if debug: + print("left side:", left) + print("right side:", right) + minchild_idx = min(left) if left else token.i + maxchild_idx = max(right) if right else token.i + print("full span:", doc[minchild_idx : maxchild_idx + 1]) + start, end = cleanup_endings(left, right, token) + if start == end: + continue + if doc[start].lower_ == "'s": + continue # we probably already have stored this mention + span = doc[start:end] + if debug: + print("cleaned endings span:", doc[start:end]) + print("==-- full span store:", span) + mentions_spans.append(span) + if debug and token.tag_ == "IN": + print("IN tag") + if any(tok.dep_ in conj_or_prep for tok in span): + if debug: + print("Conjunction found, storing first element separately") + for c in doc: + if c.head.i == token.i and c.dep_ not in conj_or_prep: + if debug: + print("left no conj:", c, "dep & edge:", c.dep_, c.left_edge) + if debug: + print("right no conj:", c, "dep & edge:", c.dep_, c.right_edge) + left_no_conj = list( + c.left_edge.i + for c in doc + if c.head.i == token.i and c.dep_ not in conj_or_prep + ) + right_no_conj = list( + c.right_edge.i + for c in doc + if c.head.i == token.i and c.dep_ not in conj_or_prep + ) + if debug: + print("left side no conj:", [doc[i] for i in left_no_conj]) + if debug: + print("right side no conj:", [doc[i] for i in right_no_conj]) + start, end = cleanup_endings(left_no_conj, right_no_conj, token) + if start == end: + continue + span = doc[start:end] + if debug: + print("==-- full span store:", span) + mentions_spans.append(span) + if debug: + print("mentions_spans inside", mentions_spans) + return mentions_spans + + +######################### +####### CLASSES ######### + + +class Mention(spacy.tokens.Span): + """ + A mention (possible anaphor) inherite from spacy Span class with additional informations + """ + + def __new__( + cls, + span, + mention_index, + utterance_index, + utterance_start_sent, + speaker=None, + gold_label=None, + *args, + **kwargs, + ): + # We need to override __new__ see http://cython.readthedocs.io/en/latest/src/userguide/special_methods.html + obj = spacy.tokens.Span.__new__( + cls, span.doc, span.start, span.end, *args, **kwargs + ) + return obj + + def __init__( + self, + span, + mention_index, + utterance_index, + utterances_start_sent, + speaker=None, + gold_label=None, + ): + """ + Arguments: + span (spaCy Span): the spaCy span from which creating the Mention object + mention_index (int): index of the Mention in the Document + utterance_index (int): index of the utterance of the Mention in the Document + utterances_start_sent (int): index of the first sentence of the utterance of the Mention in the Document + (an utterance can comprise several sentences) + speaker (Speaker): the speaker of the mention + gold_label (anything): a gold label associated to the Mention (for training) + """ + self.index = mention_index + self.utterance_index = utterance_index + self.utterances_sent = utterances_start_sent + self._get_doc_sent_number() + self.speaker = speaker + self.gold_label = gold_label + self.spans_embeddings = None + self.words_embeddings = None + self.features = None + + self.features_ = None + self.spans_embeddings_ = None + self.words_embeddings_ = None + + self.mention_type = self._get_type() + self.propers = set(self.content_words) + self.entity_label = self._get_entity_label() + self.in_entities = self._get_in_entities() + + def _get_entity_label(self): + """ Label of a detected named entity the Mention is nested in if any""" + for ent in self.doc.ents: + if ent.start <= self.start and self.end <= ent.end: + return ent.label + return None + + def _get_in_entities(self): + """ Is the Mention nested in a detected named entity""" + return self.entity_label is not None + + def _get_type(self): + """ Find the type of the Span """ + conj = ["CC", ","] + prp = ["PRP", "PRP$"] + proper = ["NNP", "NNPS"] + if any(t.tag_ in conj and t.ent_type_ not in ACCEPTED_ENTS for t in self): + mention_type = MENTION_TYPE["LIST"] + elif self.root.tag_ in prp: + mention_type = MENTION_TYPE["PRONOMINAL"] + elif self.root.ent_type_ in ACCEPTED_ENTS or self.root.tag_ in proper: + mention_type = MENTION_TYPE["PROPER"] + else: + mention_type = MENTION_TYPE["NOMINAL"] + return mention_type + + def _get_doc_sent_number(self): + """ Index of the sentence of the Mention in the current utterance""" + for i, s in enumerate(self.doc.sents): + if s == self.sent: + return i + return None + + @property + def content_words(self): + """ Returns an iterator of nouns/proper nouns in the Mention """ + return (tok.lower_ for tok in self if tok.tag_ in PROPERS_TAGS) + + @property + def embedding(self): + return np.concatenate([self.spans_embeddings, self.words_embeddings], axis=0) + + def heads_agree(self, mention2): + """ Does the root of the Mention match the root of another Mention/Span""" + # we allow same-type NEs to not match perfectly, + # but rather one could be included in the other, e.g., "George" -> "George Bush" + if ( + self.in_entities + and mention2.in_entities + and self.entity_label == mention2.entity_label + and ( + self.root.lower_ in mention2.lower_ + or mention2.root.lower_ in self.lower_ + ) + ): + return True + return self.root.lower_ == mention2.root.lower_ + + def exact_match(self, mention2): + """ Does the Mention lowercase text matches another Mention/Span lowercase text""" + return self.lower_ == mention2.lower_ + + def relaxed_match(self, mention2): + """ Does the nouns/proper nous in the Mention match another Mention/Span nouns/propers""" + return not self.propers.isdisjoint(mention2.propers) + + def speaker_match_mention(self, mention2): + # To take care of sentences like 'Larry said, "San Francisco is a city."': (id(Larry), id(San Francisco)) + # if document.speakerPairs.contains(new Pair<>(mention.mentionID, ant.mentionID)): + # return True + if self.speaker is not None: + return self.speaker.speaker_matches_mention(mention2, strict_match=False) + return False + + +class Speaker(object): + """ + A speaker with its names, list of mentions and matching test functions + """ + + def __init__(self, speaker_id, speaker_names=None): + self.mentions = [] + self.speaker_id = speaker_id + if speaker_names is None: + self.speaker_names = [unicode_(speaker_id)] + elif isinstance(speaker_names, string_types): + self.speaker_names = [speaker_names] + elif len(speaker_names) > 1: + self.speaker_names = speaker_names + else: + self.speaker_names = unicode_(speaker_names) + self.speaker_tokens = [ + tok.lower() + for s in self.speaker_names + for tok in re.split(WHITESPACE_PATTERN, s) + ] + + def __str__(self): + return f"{self.speaker_id} {self.speaker_names}" + + def add_mention(self, mention): + """ Add a Mention of the Speaker""" + self.mentions.append(mention) + + def contain_mention(self, mention): + """ Does the Speaker contains a Mention""" + return mention in self.mentions + + def contain_string(self, string): + """ Does the Speaker names contains a string""" + return any( + re.sub(WHITESPACE_PATTERN, "", string.lower()) + == re.sub(WHITESPACE_PATTERN, "", s.lower()) + for s in self.speaker_names + ) + + def contain_token(self, token): + """ Does the Speaker names contains a token (word)""" + return any(token.lower() == tok.lower() for tok in self.speaker_tokens) + + def speaker_matches_mention(self, mention, strict_match=False): + """ Does a Mention matches the speaker names""" + # Got info about this speaker + if self.contain_mention(mention): + return True + if strict_match: + if self.contain_string(mention): + self.mentions.append(mention) + return True + else: + # test each token in the speaker names + if not mention.root.tag_.startswith("NNP"): + return False + if self.contain_token(mention.root.lower_): + self.mentions.append(mention) + return True + return False + + +class EmbeddingExtractor: + """ + Compute words embedding features for mentions + """ + + def __init__(self, pretrained_model_path): + _, self.static_embeddings, self.stat_idx, self.stat_voc = self.load_embeddings_from_file( + pretrained_model_path + "static_word" + ) + _, self.tuned_embeddings, self.tun_idx, self.tun_voc = self.load_embeddings_from_file( + pretrained_model_path + "tuned_word" + ) + self.fallback = self.static_embeddings.get(UNKNOWN_WORD) + + self.shape = self.static_embeddings[UNKNOWN_WORD].shape + shape2 = self.tuned_embeddings[UNKNOWN_WORD].shape + assert self.shape == shape2 + + @staticmethod + def load_embeddings_from_file(name): + print("Loading embeddings from", name) + embeddings = {} + voc_to_idx = {} + idx_to_voc = [] + mat = np.load(name + "_embeddings.npy") + average_mean = np.average(mat, axis=0, weights=np.sum(mat, axis=1)) + with io.open(name + "_vocabulary.txt", "r", encoding="utf-8") as f: + for i, line in enumerate(f): + embeddings[line.strip()] = mat[i, :] + voc_to_idx[line.strip()] = i + idx_to_voc.append(line.strip()) + return average_mean, embeddings, voc_to_idx, idx_to_voc + + @staticmethod + def normalize_word(w): + if w is None: + return MISSING_WORD + return re.sub(r"\d", "0", w.lower_) + + def get_document_embedding(self, utterances_list): + """ Embedding for the document """ + # We could also use this: embed_vector = np.copy(self.average_mean)#np.zeros(self.shape) + # return embed_vector + embed_vector = np.zeros(self.shape) + for utt in utterances_list: + _, utt_embed = self.get_average_embedding(utt) + embed_vector += utt_embed + return embed_vector / max(len(utterances_list), 1) + + def get_stat_word(self, word): + if word in self.static_embeddings: + return word, self.static_embeddings.get(word) + else: + return UNKNOWN_WORD, self.fallback + + def get_word_embedding(self, word, static=False): + """ Embedding for a single word (tuned if possible, otherwise static) """ + norm_word = self.normalize_word(word) + if static: + return self.get_stat_word(norm_word) + else: + if norm_word in self.tuned_embeddings: + return norm_word, self.tuned_embeddings.get(norm_word) + else: + return self.get_stat_word(norm_word) + + def get_word_in_sentence(self, word_idx, sentence): + """ Embedding for a word in a sentence """ + if word_idx < sentence.start or word_idx >= sentence.end: + return self.get_word_embedding(None) + return self.get_word_embedding(sentence.doc[word_idx]) + + def get_average_embedding(self, token_list): + """ Embedding for a list of words """ + embed_vector = np.zeros( + self.shape + ) # We could also use np.copy(self.average_mean) + word_list = [] + for tok in token_list: + if tok.lower_ not in [".", "!", "?"]: + word, embed = self.get_word_embedding(tok, static=True) + embed_vector += embed + word_list.append(word) + return word_list, (embed_vector / max(len(word_list), 1)) + + def get_mention_embeddings(self, mention, doc_embedding): + """ Get span (averaged) and word (single) embeddings of a mention """ + st = mention.sent + mention_lefts = mention.doc[max(mention.start - 5, st.start) : mention.start] + mention_rights = mention.doc[mention.end : min(mention.end + 5, st.end)] + head = mention.root.head + spans = [ + self.get_average_embedding(mention), + self.get_average_embedding(mention_lefts), + self.get_average_embedding(mention_rights), + self.get_average_embedding(st), + (unicode_(doc_embedding[0:8]) + "...", doc_embedding), + ] + words = [ + self.get_word_embedding(mention.root), + self.get_word_embedding(mention[0]), + self.get_word_embedding(mention[-1]), + self.get_word_in_sentence(mention.start - 1, st), + self.get_word_in_sentence(mention.end, st), + self.get_word_in_sentence(mention.start - 2, st), + self.get_word_in_sentence(mention.end + 1, st), + self.get_word_embedding(head), + ] + spans_embeddings_ = { + "00_Mention": spans[0][0], + "01_MentionLeft": spans[1][0], + "02_MentionRight": spans[2][0], + "03_Sentence": spans[3][0], + "04_Doc": spans[4][0], + } + words_embeddings_ = { + "00_MentionHead": words[0][0], + "01_MentionFirstWord": words[1][0], + "02_MentionLastWord": words[2][0], + "03_PreviousWord": words[3][0], + "04_NextWord": words[4][0], + "05_SecondPreviousWord": words[5][0], + "06_SecondNextWord": words[6][0], + "07_MentionRootHead": words[7][0], + } + return ( + spans_embeddings_, + words_embeddings_, + np.concatenate([em[1] for em in spans], axis=0), + np.concatenate([em[1] for em in words], axis=0), + ) + + +class Document(object): + """ + Main data class: encapsulate list of utterances, mentions and speakers + Process utterances to extract mentions and pre-compute mentions features + """ + + def __init__( + self, + nlp, + utterances=None, + utterances_speaker=None, + speakers_names=None, + blacklist=False, + consider_speakers=False, + model_path=None, + embedding_extractor=None, + conll=None, + debug=False, + ): + """ + Arguments: + nlp (spaCy Language Class): A spaCy Language Class for processing the text input + utterances: utterance(s) to load already see self.add_utterances() + utterances_speaker: speaker(s) of utterance(s) to load already see self.add_utterances() + speakers_names: speaker(s) of utterance(s) to load already see self.add_utterances() + blacklist (boolean): use a list of term for which coreference is not preformed + consider_speakers (boolean): consider speakers informations + pretrained_model_path (string): Path to a folder with pretrained word embeddings + embedding_extractor (EmbeddingExtractor): Use a pre-loaded word embeddings extractor + conll (string): If training on coNLL data: identifier of the document type + debug (boolean): print debug informations + """ + self.nlp = nlp + self.blacklist = blacklist + self.utterances = [] + self.utterances_speaker = [] + self.last_utterances_loaded = [] + self.mentions = [] + self.speakers = {} + self.n_sents = 0 + self.debug = debug + self.consider_speakers = consider_speakers or conll is not None + + self.genre_, self.genre = self.set_genre(conll) + + if model_path is not None and embedding_extractor is None: + self.embed_extractor = EmbeddingExtractor(model_path) + elif embedding_extractor is not None: + self.embed_extractor = embedding_extractor + else: + self.embed_extractor = None + + if utterances: + self.add_utterances(utterances, utterances_speaker, speakers_names) + + def set_genre(self, conll): + if conll is not None: + genre = np.zeros((7,)) + genre[conll] = 1 + else: + genre = np.array(0, ndmin=1, copy=False) + return conll, genre + + def __str__(self): + formatted = "\n ".join( + unicode_(i) + " " + unicode_(s) + for i, s in zip(self.utterances, self.utterances_speaker) + ) + mentions = "\n ".join( + unicode_(i) + " " + unicode_(i.speaker) for i in self.mentions + ) + return f" \n {formatted}\n \n {mentions}" + + def __len__(self): + """ Return the number of mentions (not utterances) since it is what we really care about """ + return len(self.mentions) + + def __getitem__(self, key): + """ Return a specific mention (not utterance) """ + return self.mentions[key] + + def __iter__(self): + """ Iterate over mentions (not utterances) """ + for mention in self.mentions: + yield mention + + ####################################### + ###### UTERANCE LOADING FUNCTIONS ##### + ####################################### + + def set_utterances(self, utterances, utterances_speaker=None, speakers_names=None): + self.utterances = [] + self.utterances_speaker = [] + self.mentions = [] + self.speakers = {} + self.n_sents = 0 + if utterances: + self.add_utterances(utterances, utterances_speaker, speakers_names) + + def add_utterances(self, utterances, utterances_speaker=None, speakers_names=None): + """ + Add utterances to the utterance list and build mention list for these utterances + + Arg: + utterances : iterator or list of string corresponding to successive utterances + utterances_speaker : iterator or list of speaker id for each utterance. + If not provided, assume two speakers speaking alternatively. + if utterances and utterances_speaker are not of the same length padded with None + speakers_names : dictionnary of list of acceptable speaker names for each speaker id + Return: + List of indexes of added utterances in the docs + """ + if self.debug: + print("Adding utterances", utterances) + if isinstance(utterances, string_types): + utterances = [utterances] + if utterances_speaker is None: + if self.debug: + print("No utterance speaker indication") + a = -1 + if self.utterances_speaker and isinstance( + self.utterances_speaker[-1].speaker_id, integer_types + ): + a = self.utterances_speaker[-1].speaker_id + utterances_speaker = ((i + a + 1) % 2 for i in range(len(utterances))) + utterances_index = [] + utt_start = len(self.utterances) + docs = list(self.nlp.pipe(utterances)) + m_spans = list( + extract_mentions_spans(doc, blacklist=self.blacklist) for doc in docs + ) + for utt_index, (doc, m_spans, speaker_id) in enumerate( + zip_longest(docs, m_spans, utterances_speaker) + ): + if speaker_id not in self.speakers: + speaker_name = ( + speakers_names.get(speaker_id, None) if speakers_names else None + ) + self.speakers[speaker_id] = Speaker(speaker_id, speaker_name) + self._process_mentions( + m_spans, utt_start + utt_index, self.n_sents, self.speakers[speaker_id] + ) + utterances_index.append(utt_start + utt_index) + self.utterances.append(doc) + self.utterances_speaker.append(self.speakers[speaker_id]) + self.n_sents += len(list(doc.sents)) + + self.set_mentions_features() + self.last_utterances_loaded = utterances_index + + ################################### + ## FEATURES MENTIONS EXTRACTION ### + ################################### + + def _process_mentions(self, mentions_spans, utterance_index, n_sents, speaker): + """ + Process mentions in a spacy doc (an utterance) + """ + processed_spans = sorted( + (m for m in mentions_spans), key=lambda m: (m.root.i, m.start) + ) + n_mentions = len(self.mentions) + for mention_index, span in enumerate(processed_spans): + self.mentions.append( + Mention( + span, mention_index + n_mentions, utterance_index, n_sents, speaker + ) + ) + + def set_mentions_features(self): + """ + Compute features for the extracted mentions + """ + doc_embedding = ( + self.embed_extractor.get_document_embedding(self.utterances) + if self.embed_extractor is not None + else None + ) + for mention in self.mentions: + one_hot_type = np.zeros((4,)) + one_hot_type[mention.mention_type] = 1 + features_ = { + "01_MentionType": mention.mention_type, + "02_MentionLength": len(mention) - 1, + "03_MentionNormLocation": (mention.index) / len(self.mentions), + "04_IsMentionNested": 1 + if any( + ( + m is not mention + and m.utterances_sent == mention.utterances_sent + and m.start <= mention.start + and mention.end <= m.end + ) + for m in self.mentions + ) + else 0, + } + features = np.concatenate( + [ + one_hot_type, + encode_distance(features_["02_MentionLength"]), + np.array(features_["03_MentionNormLocation"], ndmin=1, copy=False), + np.array(features_["04_IsMentionNested"], ndmin=1, copy=False), + ], + axis=0, + ) + ( + spans_embeddings_, + words_embeddings_, + spans_embeddings, + words_embeddings, + ) = self.embed_extractor.get_mention_embeddings(mention, doc_embedding) + mention.features_ = features_ + mention.features = features + mention.spans_embeddings = spans_embeddings + mention.spans_embeddings_ = spans_embeddings_ + mention.words_embeddings = words_embeddings + mention.words_embeddings_ = words_embeddings_ + + def get_single_mention_features(self, mention): + """ Features for anaphoricity test (single mention features + genre if conll)""" + features_ = mention.features_ + features_["DocGenre"] = self.genre_ + return (features_, np.concatenate([mention.features, self.genre], axis=0)) + + def get_pair_mentions_features(self, m1, m2): + """ Features for pair of mentions (same speakers, speaker mentioned, string match)""" + features_ = { + "00_SameSpeaker": 1 + if self.consider_speakers and m1.speaker == m2.speaker + else 0, + "01_AntMatchMentionSpeaker": 1 + if self.consider_speakers and m2.speaker_match_mention(m1) + else 0, + "02_MentionMatchSpeaker": 1 + if self.consider_speakers and m1.speaker_match_mention(m2) + else 0, + "03_HeadsAgree": 1 if m1.heads_agree(m2) else 0, + "04_ExactStringMatch": 1 if m1.exact_match(m2) else 0, + "05_RelaxedStringMatch": 1 if m1.relaxed_match(m2) else 0, + "06_SentenceDistance": m2.utterances_sent - m1.utterances_sent, + "07_MentionDistance": m2.index - m1.index - 1, + "08_Overlapping": 1 + if (m1.utterances_sent == m2.utterances_sent and m1.end > m2.start) + else 0, + "09_M1Features": m1.features_, + "10_M2Features": m2.features_, + "11_DocGenre": self.genre_, + } + pairwise_features = [ + np.array( + [ + features_["00_SameSpeaker"], + features_["01_AntMatchMentionSpeaker"], + features_["02_MentionMatchSpeaker"], + features_["03_HeadsAgree"], + features_["04_ExactStringMatch"], + features_["05_RelaxedStringMatch"], + ] + ), + encode_distance(features_["06_SentenceDistance"]), + encode_distance(features_["07_MentionDistance"]), + np.array(features_["08_Overlapping"], ndmin=1), + m1.features, + m2.features, + self.genre, + ] + return (features_, np.concatenate(pairwise_features, axis=0)) + + ################################### + ###### ITERATOR OVER MENTIONS ##### + ################################### + + def get_candidate_mentions(self, last_utterances_added=False): + """ + Return iterator over indexes of mentions in a list of utterances if specified + """ + if last_utterances_added: + for i, mention in enumerate(self.mentions): + if self.debug: + print("🤣", i, mention, "utterance index", mention.utterance_index) + if mention.utterance_index in self.last_utterances_loaded: + yield i + else: + iterator = range(len(self.mentions)) + for i in iterator: + yield i + + def get_candidate_pairs( + self, mentions=None, max_distance=50, max_distance_with_match=500, debug=False + ): + """ + Yield tuples of mentions, dictionnary of candidate antecedents for the mention + + Arg: + mentions: an iterator over mention indexes (as returned by get_candidate_mentions) + max_mention_distance : max distance between a mention and its antecedent + max_mention_distance_string_match : max distance between a mention and + its antecedent when there is a proper noun match + """ + if mentions is None: + mentions = range(len(self.mentions)) + if debug: + print("get_candidate_pairs: mentions", mentions) + + if max_distance_with_match is not None: + word_to_mentions = {} + for i in mentions: + for tok in self.mentions[i].content_words: + if not tok in word_to_mentions: + word_to_mentions[tok] = [i] + else: + word_to_mentions[tok].append(i) + + for i in mentions: + antecedents = ( + set(range(i)) + if max_distance is None + else set(range(max(0, i - max_distance), i)) + ) + if debug: + print("antecedents", antecedents) + if max_distance_with_match is not None: + for tok in self.mentions[i].content_words: + with_string_match = word_to_mentions.get(tok, None) + for match_idx in with_string_match: + if match_idx < i and match_idx >= i - max_distance_with_match: + antecedents.add(match_idx) + yield i, antecedents + + +def mention_detection_debug(sentence): + print("🌋 Loading spacy model") + try: + spacy.info("en_core_web_sm") + model = "en_core_web_sm" + except IOError: + print("No spacy 2 model detected, using spacy1 'en' model") + spacy.info("en") + model = "en" + nlp = spacy.load(model) + doc = nlp(sentence.decode("utf-8")) + mentions = extract_mentions_spans(doc, blacklist=False, debug=True) + for mention in mentions: + print(mention) + + +if __name__ == "__main__": + import sys + + if len(sys.argv) > 1: + sent = sys.argv[1] + mention_detection_debug(sent) + else: + mention_detection_debug("My sister has a dog. She loves him.") diff --git a/data_tooling/pii_processing/neuralcoref/train/evaluator.py b/data_tooling/pii_processing/neuralcoref/train/evaluator.py new file mode 100644 index 0000000..c87f7aa --- /dev/null +++ b/data_tooling/pii_processing/neuralcoref/train/evaluator.py @@ -0,0 +1,345 @@ +"""Conll Evaluation - Scoring""" + +import os +import subprocess +import io +import pickle + +import torch +from torch.utils.data import DataLoader + +from neuralcoref.train.conllparser import FEATURES_NAMES +from neuralcoref.train.dataset import NCBatchSampler, padder_collate +from neuralcoref.train.compat import unicode_ + +PACKAGE_DIRECTORY = os.path.dirname(os.path.abspath(__file__)) + +OUT_PATH = os.path.join(PACKAGE_DIRECTORY, "test_corefs.txt") # fernandes.txt")# +ALL_MENTIONS_PATH = os.path.join(PACKAGE_DIRECTORY, "test_mentions.txt") +# KEY_PATH = os.path.join(PACKAGE_DIRECTORY, "conll-2012-test-test-key.txt") +SCORING_SCRIPT = os.path.join(PACKAGE_DIRECTORY, "scorer_wrapper.pl") + +METRICS = ["muc", "bcub", "ceafm", "ceafe", "blanc"] +CONLL_METRICS = ["muc", "bcub", "ceafe"] + + +class ConllEvaluator(object): + def __init__(self, model, dataset, test_data_path, test_key_file, embed_path, args): + """ Evaluate the pytorch model that is currently being build + We take the embedding vocabulary currently being trained + """ + self.test_key_file = test_key_file + self.cuda = args.cuda + self.model = model + batch_sampler = NCBatchSampler( + dataset.mentions_pair_length, batchsize=args.batchsize, shuffle=False + ) + self.dataloader = DataLoader( + dataset, + collate_fn=padder_collate, + batch_sampler=batch_sampler, + num_workers=args.numworkers, + pin_memory=args.cuda, + ) + self.mentions_idx, self.n_pairs = batch_sampler.get_batch_info() + self.load_meta(test_data_path) + + def load_meta(self, test_data_path): + # Load meta files + datas = {} + if not os.listdir(test_data_path): + raise ValueError("Empty test_data_path") + bin_files_found = False + print("Reading ", end="") + for file_name in os.listdir(test_data_path): + if ".bin" not in file_name: + continue + bin_files_found = True + print(file_name, end=", ") + with open(test_data_path + file_name, "rb") as f: + datas[file_name.split(".")[0]] = pickle.load(f) + if not bin_files_found: + raise ValueError(f"Can't find bin files in {test_data_path}") + print("Done") + self.m_loc = datas[FEATURES_NAMES[9]] + self.tokens = datas[FEATURES_NAMES[10]] + self.lookup = datas[FEATURES_NAMES[11]] + self.docs = datas[FEATURES_NAMES[12]] + self.flat_m_idx = list( + (doc_i, m_i) for doc_i, l in enumerate(self.m_loc) for m_i in range(len(l)) + ) + + ########################### + #### CLUSTER FUNCTIONS #### + ########################### + + def _prepare_clusters(self): + """ + Clean up and prepare one cluster for each mention + """ + self.mention_to_cluster = list( + list(range(len(doc_mentions))) for doc_mentions in self.m_loc + ) + self.clusters = list( + dict((i, [i]) for i in doc_mentions) + for doc_mentions in self.mention_to_cluster + ) + + def _merge_coreference_clusters(self, ant_flat_idx, mention_flat_idx): + """ + Merge two clusters together + """ + doc_idx, ant_idx = self.flat_m_idx[ant_flat_idx] + doc_idx2, mention_idx = self.flat_m_idx[mention_flat_idx] + assert doc_idx2 == doc_idx + if ( + self.mention_to_cluster[doc_idx][ant_idx] + == self.mention_to_cluster[doc_idx][mention_idx] + ): + return + remove_id = self.mention_to_cluster[doc_idx][ant_idx] + keep_id = self.mention_to_cluster[doc_idx][mention_idx] + for idx in self.clusters[doc_idx][remove_id]: + self.mention_to_cluster[doc_idx][idx] = keep_id + self.clusters[doc_idx][keep_id].append(idx) + del self.clusters[doc_idx][remove_id] + + def remove_singletons_clusters(self, debug=False): + for doc_idx in range(len(self.docs)): + remove_id = [] + kept = False + for key, mentions in self.clusters[doc_idx].items(): + if len(mentions) == 1: + remove_id.append(key) + self.mention_to_cluster[doc_idx][key] = None + else: + kept = True + if debug: + l = list(self.m_loc[doc_idx][m][3] for m in mentions) + print("Cluster found", key) + print( + "Corefs:", + "|".join( + str(self.docs[doc_idx]["mentions"][m_idx]) + + " (" + + str(m_idx) + + ")" + for m_idx in l + ), + ) + if not kept and debug: + print("❄️ No coreference found") + for rem in remove_id: + del self.clusters[doc_idx][rem] + + def display_clusters(self, doc_idx=None): + """ + Print clusters informations + """ + doc_it = range(len(self.docs)) if doc_idx is None else [doc_idx] + for d_i in doc_it: + print( + "Clusters in doc:", + doc_it, + self.docs[d_i]["name"], + self.docs[d_i]["part"], + ) + print(self.clusters[d_i]) + for key, mentions in self.clusters[d_i].items(): + l = list(self.m_loc[d_i][m][3] for m in mentions) + print( + "cluster", + key, + "(", + ", ".join(self.docs[d_i]["mentions"][m_idx] for m_idx in l), + ")", + ) + + ######################## + #### MAIN FUNCTIONS #### + ######################## + def get_max_score(self, batch, debug=False): + inputs, mask = batch + if self.cuda: + inputs = tuple(i.cuda() for i in inputs) + mask = mask.cuda() + self.model.eval() + with torch.no_grad(): + scores = self.model(inputs, concat_axis=1) + scores.masked_fill_(mask, -float("Inf")) + _, max_idx = scores.max( + dim=1 + ) # We may want to weight the single score with coref.greedyness + if debug: + print("Max_idx", max_idx) + return scores.cpu().numpy(), max_idx.cpu().numpy() + + def test_model(self): + print("🌋 Test evaluator / print all mentions") + self.build_test_file(out_path=ALL_MENTIONS_PATH, print_all_mentions=True) + self.get_score(file_path=ALL_MENTIONS_PATH) + + def build_test_file( + self, + out_path=OUT_PATH, + remove_singleton=True, + print_all_mentions=False, + debug=None, + ): + """ Build a test file to supply to the coreference scoring perl script + """ + print("🌋 Building test file") + self._prepare_clusters() + self.dataloader.dataset.no_targets = True + if not print_all_mentions: + print("🌋 Build coreference clusters") + for sample_batched, mentions_idx, n_pairs_l in zip( + self.dataloader, self.mentions_idx, self.n_pairs + ): + scores, max_i = self.get_max_score(sample_batched) + for m_idx, ind, n_pairs in zip(mentions_idx, max_i, n_pairs_l): + if ( + ind < n_pairs + ): # the single score is not the highest, we have a match ! + prev_idx = m_idx - n_pairs + ind + if debug is not None and ( + debug == -1 or debug == prev_idx or debug == m_idx + ): + m1_doc, m1_idx = self.flat_m_idx[m_idx] + m1 = self.docs[m1_doc]["mentions"][m1_idx] + m2_doc, m2_idx = self.flat_m_idx[prev_idx] + m2 = self.docs[m2_doc]["mentions"][m2_idx] + print( + "We have a match between:", + m1, + "(" + str(m1_idx) + ")", + "and:", + m2, + "(" + str(m2_idx) + ")", + ) + self._merge_coreference_clusters(prev_idx, m_idx) + if remove_singleton: + self.remove_singletons_clusters() + self.dataloader.dataset.no_targets = False + + print("🌋 Construct test file") + out_str = "" + for doc, d_tokens, d_lookup, d_m_loc, d_m_to_c in zip( + self.docs, self.tokens, self.lookup, self.m_loc, self.mention_to_cluster + ): + out_str += ( + "#begin document (" + doc["name"] + "); part " + doc["part"] + "\n" + ) + for utt_idx, (c_tokens, c_lookup) in enumerate(zip(d_tokens, d_lookup)): + for i, (token, lookup) in enumerate(zip(c_tokens, c_lookup)): + out_coref = "" + for m_str, mention, mention_cluster in zip( + doc["mentions"], d_m_loc, d_m_to_c + ): + m_start, m_end, m_utt, m_idx, m_doc = mention + if mention_cluster is None: + pass + elif m_utt == utt_idx: + if m_start in lookup: + out_coref += "|" if out_coref else "" + out_coref += "(" + unicode_(mention_cluster) + if (m_end - 1) in lookup: + out_coref += ")" + else: + out_coref += "" + elif (m_end - 1) in lookup: + out_coref += "|" if out_coref else "" + out_coref += unicode_(mention_cluster) + ")" + out_line = ( + doc["name"] + + " " + + doc["part"] + + " " + + unicode_(i) + + " " + + token + + " " + ) + out_line += "-" if len(out_coref) == 0 else out_coref + out_str += out_line + "\n" + out_str += "\n" + out_str += "#end document\n" + + # Write test file + print("Writing in", out_path) + with io.open(out_path, "w", encoding="utf-8") as out_file: + out_file.write(out_str) + + def get_score(self, file_path=OUT_PATH, debug=False): + """ Call the coreference scoring perl script on the created test file + """ + print("🌋 Computing score") + score = {} + ident = None + for metric_name in CONLL_METRICS: + if debug: + print("Computing metric:", metric_name) + try: + scorer_out = subprocess.check_output( + [ + "perl", + SCORING_SCRIPT, + metric_name, + self.test_key_file, + file_path, + ], + stderr=subprocess.STDOUT, + encoding="utf-8", + ) + except subprocess.CalledProcessError as err: + print("Error during the scoring") + print(err) + print(err.output) + raise + if debug: + print("scorer_out", scorer_out) + value, ident = scorer_out.split("\n")[-2], scorer_out.split("\n")[-1] + if debug: + print("value", value, "identification", ident) + NR, DR, NP, DP = [float(x) for x in value.split(" ")] + ident_NR, ident_DR, ident_NP, ident_DP = [ + float(x) for x in ident.split(" ") + ] + precision = NP / DP if DP else 0 + recall = NR / DR if DR else 0 + F1 = ( + 2 * precision * recall / (precision + recall) + if precision + recall > 0 + else 0 + ) + ident_precision = ident_NP / ident_DP if ident_DP else 0 + ident_recall = ident_NR / ident_DR if ident_DR else 0 + ident_F1 = ( + 2 * ident_precision * ident_recall / (ident_precision + ident_recall) + if ident_precision + ident_recall > 0 + else 0 + ) + score[metric_name] = (precision, recall, F1) + ident = ( + ident_precision, + ident_recall, + ident_F1, + ident_NR, + ident_DR, + ident_NP, + ident_DP, + ) + F1_conll = sum([score[metric][2] for metric in CONLL_METRICS]) / len( + CONLL_METRICS + ) + print( + "Mention identification recall", + ident[1], + "<= Detected mentions", + ident[3], + "True mentions", + ident[4], + ) + print("Scores", score) + print("F1_conll", F1_conll) + return score, F1_conll, ident diff --git a/data_tooling/pii_processing/neuralcoref/train/learn.py b/data_tooling/pii_processing/neuralcoref/train/learn.py new file mode 100644 index 0000000..086a14d --- /dev/null +++ b/data_tooling/pii_processing/neuralcoref/train/learn.py @@ -0,0 +1,565 @@ +"""Conll training algorithm""" + +import os +import time +import argparse +import socket +from datetime import datetime +import numpy as np + +import torch +import torch.nn as nn +from torch.autograd import Variable +from torch.optim import RMSprop +from torch.utils.data import DataLoader +from tensorboardX import SummaryWriter + +from neuralcoref.train.model import Model +from neuralcoref.train.dataset import ( + NCDataset, + NCBatchSampler, + load_embeddings_from_file, + padder_collate, + SIZE_PAIR_IN, + SIZE_SINGLE_IN, +) +from neuralcoref.train.utils import SIZE_EMBEDDING +from neuralcoref.train.evaluator import ConllEvaluator + +PACKAGE_DIRECTORY = os.path.dirname(os.path.abspath(__file__)) +STAGES = ["allpairs", "toppairs", "ranking"] + + +def clipped_sigmoid(inputs): + epsilon = 1.0e-7 + return torch.sigmoid(inputs).clamp(epsilon, 1.0 - epsilon) + + +def get_all_pairs_loss(n): + def all_pair_loss(scores, targets): + """ All pairs and single mentions probabilistic loss + """ + labels = targets[0] + weights = targets[4].data if len(targets) == 5 else None + loss_op = nn.BCEWithLogitsLoss(weight=weights, reduction="sum") + loss = loss_op(scores, labels) + return loss / n + + return all_pair_loss + + +def get_top_pair_loss(n): + def top_pair_loss(scores, targets, debug=False): + """ Top pairs (best true and best mistaken) and single mention probabilistic loss + """ + true_ants = targets[2] + false_ants = targets[3] if len(targets) == 5 else None + s_scores = clipped_sigmoid(scores) + true_pairs = torch.gather(s_scores, 1, true_ants) + top_true, top_true_arg = torch.log(true_pairs).max( + dim=1 + ) # max(log(p)), p=sigmoid(s) + if debug: + print("true_pairs", true_pairs.data) + print("top_true", top_true.data) + print("top_true_arg", top_true_arg.data) + out_score = torch.sum(top_true).neg() + if ( + false_ants is not None + ): # We have no false antecedents when there are no pairs + false_pairs = torch.gather(s_scores, 1, false_ants) + top_false, _ = torch.log(1 - false_pairs).min( + dim=1 + ) # min(log(1-p)), p=sigmoid(s) + out_score = out_score + torch.sum(top_false).neg() + return out_score / n + + return top_pair_loss + + +def get_ranking_loss(n): + def ranking_loss(scores, targets): + """ Slack-rescaled max margin loss + """ + costs = targets[1] + true_ants = targets[2] + weights = targets[4] if len(targets) == 5 else None + true_ant_score = torch.gather(scores, 1, true_ants) + top_true, _ = true_ant_score.max(dim=1) + tmp_loss = scores.add(1).add( + top_true.unsqueeze(1).neg() + ) # 1 + scores - top_true + if weights is not None: + tmp_loss = tmp_loss.mul(weights) + tmp_loss = tmp_loss.mul(costs) + loss, _ = tmp_loss.max(dim=1) + out_score = torch.sum(loss) + return out_score / n + + return ranking_loss + + +def decrease_lr(optim_func, factor=0.1, min_lrs=0, eps=0, verbose=True): + for i, param_group in enumerate(optim_func.param_groups): + old_lr = float(param_group["lr"]) + new_lr = max(old_lr * factor, min_lrs) + if old_lr - new_lr > eps: + param_group["lr"] = new_lr + if verbose: + print(f"Reducing learning rate" " of group {i} to {new_lr:.4e}.") + return new_lr + + +def load_model(model, path): + print("⛄️ Reloading model from", path) + model.load_state_dict( + torch.load(path) + if args.cuda + else torch.load(path, map_location=lambda storage, loc: storage) + ) + + +def run_model(args): + print( + "Training for", + args.all_pairs_epoch, + args.top_pairs_epoch, + args.ranking_epoch, + "epochs", + ) + # Tensorboard server + writer = SummaryWriter() + + # Load datasets and embeddings + embed_path = args.weights if args.weights is not None else args.train + tensor_embeddings, voc = load_embeddings_from_file(embed_path + "tuned_word") + dataset = NCDataset(args.train, args) + eval_dataset = NCDataset(args.eval, args) + print("Vocabulary:", len(voc)) + + # Construct model + print("🏝 Build model") + model = Model( + len(voc), + SIZE_EMBEDDING, + args.h1, + args.h2, + args.h3, + SIZE_PAIR_IN, + SIZE_SINGLE_IN, + ) + model.load_embeddings(tensor_embeddings) + if args.cuda: + model.cuda() + if args.weights is not None: + print("🏝 Loading pre-trained weights") + model.load_weights(args.weights) + if args.checkpoint_file is not None: + print("⛄️ Loading model from", args.checkpoint_file) + model.load_state_dict( + torch.load(args.checkpoint_file) + if args.cuda + else torch.load( + args.checkpoint_file, map_location=lambda storage, loc: storage + ) + ) + + print("🏝 Loading conll evaluator") + eval_evaluator = ConllEvaluator( + model, eval_dataset, args.eval, args.evalkey, embed_path, args + ) + train_evaluator = ConllEvaluator( + model, dataset, args.train, args.trainkey, embed_path, args + ) + print("🏝 Testing evaluator and getting first eval score") + eval_evaluator.test_model() + start_time = time.time() + eval_evaluator.build_test_file() + score, f1_conll, ident = eval_evaluator.get_score() + elapsed = time.time() - start_time + print(f"|| s/evaluation {elapsed:5.2f}") + writer.add_scalar("eval/" + "F1_conll", f1_conll, 0) + + # Preparing dataloader + print("🏝 Preparing dataloader") + print( + "Dataloader parameters: batchsize", + args.batchsize, + "numworkers", + args.numworkers, + ) + batch_sampler = NCBatchSampler( + dataset.mentions_pair_length, shuffle=True, batchsize=args.batchsize + ) + dataloader = DataLoader( + dataset, + collate_fn=padder_collate, + batch_sampler=batch_sampler, + num_workers=args.numworkers, + pin_memory=args.cuda, + ) + mentions_idx, n_pairs = batch_sampler.get_batch_info() + + print("🏝 Start training") + g_step = 0 + start_from = ( + args.startstep + if args.startstep is not None and args.startstage is not None + else 0 + ) + + def run_epochs( + start_epoch, end_epoch, loss_func, optim_func, save_name, lr, g_step, debug=None + ): + best_model_path = args.save_path + "best_model" + save_name + start_time_all = time.time() + best_f1_conll = 0 + lower_eval = 0 + for epoch in range(start_epoch, end_epoch): + """ Run an epoch """ + print(f"🚘 {save_name} Epoch {epoch:d}") + model.train() + start_time_log = time.time() + start_time_epoch = time.time() + epoch_loss = 0 + for batch_i, (m_idx, n_pairs_l, batch) in enumerate( + zip(mentions_idx, n_pairs, dataloader) + ): + if debug is not None and (debug == -1 or debug in m_idx): + l = list(dataset.flat_m_loc[m][2:] for m in m_idx) + print( + "🏔 Batch", + batch_i, + "m_idx:", + "|".join(str(i) for i in m_idx), + "mentions:", + "|".join(dataset.docs[d]["mentions"][i] for u, i, d in l), + ) + print("Batch n_pairs:", "|".join(str(p) for p in n_pairs_l)) + inputs, targets = batch + inputs = tuple(Variable(inp, requires_grad=False) for inp in inputs) + targets = tuple(Variable(tar, requires_grad=False) for tar in targets) + if args.cuda: + inputs = tuple(i.cuda() for i in inputs) + targets = tuple(t.cuda() for t in targets) + scores = model(inputs) + if debug is not None and (debug == -1 or debug in m_idx): + print( + "Scores:\n" + + "\n".join( + "|".join(str(s) for s in s_l) + for s_l in scores.data.cpu().numpy() + ) + ) + print( + "Labels:\n" + + "\n".join( + "|".join(str(s) for s in s_l) + for s_l in targets[0].data.cpu().numpy() + ) + ) + loss = loss_func(scores, targets) + if debug is not None and (debug == -1 or debug in m_idx): + print("Loss", loss.item()) + # Zero gradients, perform a backward pass, and update the weights. + optim_func.zero_grad() + loss.backward() + epoch_loss += loss.item() + optim_func.step() + writer.add_scalar("train/" + save_name + "_loss", loss.item(), g_step) + writer.add_scalar("meta/" + "lr", lr, g_step) + writer.add_scalar("meta/" + "stage", STAGES.index(save_name), g_step) + g_step += 1 + if batch_i % args.log_interval == 0 and batch_i > 0: + elapsed = time.time() - start_time_log + lr = optim_func.param_groups[0]["lr"] + ea = elapsed * 1000 / args.log_interval + li = loss.item() + print( + f"| epoch {epoch:3d} | {batch_i:5d}/{len(dataloader):5d} batches | " + f"lr {lr:.2e} | ms/batch {ea:5.2f} | " + f"loss {li:.2e}" + ) + start_time_log = time.time() + elapsed_all = time.time() - start_time_all + elapsed_epoch = time.time() - start_time_epoch + ep = elapsed_epoch / 60 + ea = ( + elapsed_all + / 3600 + * float(end_epoch - epoch) + / float(epoch - start_epoch + 1) + ) + print( + f"|| min/epoch {ep:5.2f} | est. remaining time (h) {ea:5.2f} | loss {epoch_loss:.2e}" + ) + writer.add_scalar("epoch/" + "loss", epoch_loss, g_step) + if epoch % args.conll_train_interval == 0: + start_time = time.time() + train_evaluator.build_test_file() + score, f1_conll, ident = train_evaluator.get_score() + elapsed = time.time() - start_time + ep = elapsed_epoch / 60 + print(f"|| min/train evaluation {ep:5.2f} | F1_conll {f1_conll:5.2f}") + writer.add_scalar("epoch/" + "F1_conll", f1_conll, g_step) + if epoch % args.conll_eval_interval == 0: + start_time = time.time() + eval_evaluator.build_test_file() + score, f1_conll, ident = eval_evaluator.get_score() + elapsed = time.time() - start_time + ep = elapsed_epoch / 60 + print(f"|| min/evaluation {ep:5.2f}") + writer.add_scalar("eval/" + "F1_conll", f1_conll, g_step) + g_step += 1 + save_path = args.save_path + save_name + "_" + str(epoch) + torch.save(model.state_dict(), save_path) + if f1_conll > best_f1_conll: + best_f1_conll = f1_conll + torch.save(model.state_dict(), best_model_path) + lower_eval = 0 + elif args.on_eval_decrease != "nothing": + print("Evaluation metric decreases") + lower_eval += 1 + if lower_eval >= args.patience: + if ( + args.on_eval_decrease == "divide_lr" + or args.on_eval_decrease == "divide_then_next" + ): + print("reload best model and decrease lr") + load_model(model, best_model_path) + lr = decrease_lr(optim_func) + if args.on_eval_decrease == "next_stage" or lr <= args.min_lr: + print("Switch to next stage") + break + # Save last step + start_time = time.time() + eval_evaluator.build_test_file() + score, f1_conll, ident = eval_evaluator.get_score() + elapsed = time.time() - start_time + ep = elapsed / 60 + print(f"|| min/evaluation {ep:5.2f}") + writer.add_scalar("eval/" + "F1_conll", f1_conll, g_step) + g_step += 1 + save_path = args.save_path + save_name + "_" + str(epoch) + torch.save(model.state_dict(), save_path) + load_model(model, best_model_path) + return g_step + + if args.startstage is None or args.startstage == "allpairs": + optimizer = RMSprop( + model.parameters(), lr=args.all_pairs_lr, weight_decay=args.all_pairs_l2 + ) + loss_func = get_all_pairs_loss(batch_sampler.pairs_per_batch) + g_step = run_epochs( + start_from, + args.all_pairs_epoch, + loss_func, + optimizer, + "allpairs", + args.all_pairs_lr, + g_step, + ) + start_from = 0 + + if args.startstage is None or args.startstage in ["allpairs", "toppairs"]: + optimizer = RMSprop( + model.parameters(), lr=args.top_pairs_lr, weight_decay=args.top_pairs_l2 + ) + loss_func = get_top_pair_loss(10 * batch_sampler.mentions_per_batch) + g_step = run_epochs( + start_from, + args.top_pairs_epoch, + loss_func, + optimizer, + "toppairs", + args.top_pairs_lr, + g_step, + ) + start_from = 0 + + if args.startstage is None or args.startstage in [ + "ranking", + "allpairs", + "toppairs", + ]: + optimizer = RMSprop( + model.parameters(), lr=args.ranking_lr, weight_decay=args.ranking_l2 + ) + loss_func = get_ranking_loss(batch_sampler.mentions_per_batch) + g_step = run_epochs( + start_from, + args.ranking_epoch, + loss_func, + optimizer, + "ranking", + args.ranking_lr, + g_step, + ) + + +if __name__ == "__main__": + DIR_PATH = os.path.dirname(os.path.realpath(__file__)) + parser = argparse.ArgumentParser( + description="Training the neural coreference model" + ) + parser.add_argument( + "--train", + type=str, + default=DIR_PATH + "/data/", + help="Path to the train dataset", + ) + parser.add_argument( + "--eval", type=str, default=DIR_PATH + "/data/", help="Path to the eval dataset" + ) + parser.add_argument( + "--evalkey", type=str, help="Path to an optional key file for scoring" + ) + parser.add_argument( + "--weights", + type=str, + help="Path to pre-trained weights (if you only want to test the scoring for e.g.)", + ) + parser.add_argument( + "--batchsize", + type=int, + default=20000, + help="Size of a batch in total number of pairs", + ) + parser.add_argument( + "--numworkers", + type=int, + default=8, + help="Number of workers for loading batches", + ) + parser.add_argument( + "--startstage", + type=str, + help='Start from a specific stage ("allpairs", "toppairs", "ranking")', + ) + parser.add_argument("--startstep", type=int, help="Start from a specific step") + parser.add_argument( + "--checkpoint_file", + type=str, + help="Start from a previously saved checkpoint file", + ) + parser.add_argument( + "--log_interval", type=int, default=10, help="test every X mini-batches" + ) + parser.add_argument( + "--conll_eval_interval", + type=int, + default=10, + help="evaluate eval F1 conll every X epochs", + ) + parser.add_argument( + "--conll_train_interval", + type=int, + default=20, + help="evaluate train F1 conll every X epochs", + ) + parser.add_argument("--seed", type=int, default=1111, help="random seed") + parser.add_argument("--costfn", type=float, default=0.8, help="cost of false new") + parser.add_argument("--costfl", type=float, default=0.4, help="cost of false link") + parser.add_argument("--costwl", type=float, default=1.0, help="cost of wrong link") + parser.add_argument( + "--h1", type=int, default=1000, help="number of hidden unit on layer 1" + ) + parser.add_argument( + "--h2", type=int, default=500, help="number of hidden unit on layer 2" + ) + parser.add_argument( + "--h3", type=int, default=500, help="number of hidden unit on layer 3" + ) + parser.add_argument( + "--all_pairs_epoch", + type=int, + default=200, + help="number of epochs for all-pairs pre-training", + ) + parser.add_argument( + "--top_pairs_epoch", + type=int, + default=200, + help="number of epochs for top-pairs pre-training", + ) + parser.add_argument( + "--ranking_epoch", + type=int, + default=200, + help="number of epochs for ranking training", + ) + parser.add_argument( + "--all_pairs_lr", + type=float, + default=2e-4, + help="all pairs pre-training learning rate", + ) + parser.add_argument( + "--top_pairs_lr", + type=float, + default=2e-4, + help="top pairs pre-training learning rate", + ) + parser.add_argument( + "--ranking_lr", type=float, default=2e-6, help="ranking training learning rate" + ) + parser.add_argument( + "--all_pairs_l2", + type=float, + default=1e-6, + help="all pairs pre-training l2 regularization", + ) + parser.add_argument( + "--top_pairs_l2", + type=float, + default=1e-5, + help="top pairs pre-training l2 regularization", + ) + parser.add_argument( + "--ranking_l2", + type=float, + default=1e-5, + help="ranking training l2 regularization", + ) + parser.add_argument( + "--patience", + type=int, + default=3, + help="patience (epochs) before considering evaluation has decreased", + ) + parser.add_argument("--min_lr", type=float, default=2e-8, help="min learning rate") + parser.add_argument( + "--on_eval_decrease", + type=str, + default="nothing", + help='What to do when evaluation decreases ("nothing", "divide_lr", "next_stage", "divide_then_next")', + ) + parser.add_argument( + "--lazy", + type=int, + default=1, + choices=(0, 1), + help="Use lazy loading (1, default) or not (0) while loading the npy files", + ) + args = parser.parse_args() + args.costs = {"FN": args.costfn, "FL": args.costfl, "WL": args.costwl} + args.lazy = bool(args.lazy) + current_time = datetime.now().strftime("%b%d_%H-%M-%S") + args.save_path = os.path.join( + PACKAGE_DIRECTORY, + "checkpoints", + current_time + "_" + socket.gethostname() + "_", + ) + + np.random.seed(args.seed) + torch.manual_seed(args.seed) + args.cuda = torch.cuda.is_available() + if args.cuda: + torch.cuda.manual_seed(args.seed) + + args.evalkey = args.evalkey if args.evalkey is not None else args.eval + "/key.txt" + args.trainkey = args.train + "/key.txt" + args.train = args.train + "/numpy/" + args.eval = args.eval + "/numpy/" + print(args) + run_model(args) diff --git a/data_tooling/pii_processing/neuralcoref/train/model.py b/data_tooling/pii_processing/neuralcoref/train/model.py new file mode 100644 index 0000000..069499c --- /dev/null +++ b/data_tooling/pii_processing/neuralcoref/train/model.py @@ -0,0 +1,122 @@ +"""Conll training algorithm""" + +import os +import numpy as np + +import torch +import torch.nn as nn +import torch.utils.data + + +class Model(nn.Module): + def __init__( + self, vocab_size, embedding_dim, H1, H2, H3, D_pair_in, D_single_in, dropout=0.5 + ): + super(Model, self).__init__() + self.word_embeds = nn.Embedding(vocab_size, embedding_dim) + self.drop = nn.Dropout(dropout) + self.pair_top = nn.Sequential( + nn.Linear(D_pair_in, H1), + nn.ReLU(), + nn.Dropout(dropout), + nn.Linear(H1, H2), + nn.ReLU(), + nn.Dropout(dropout), + nn.Linear(H2, H3), + nn.ReLU(), + nn.Dropout(dropout), + nn.Linear(H3, 1), + nn.Linear(1, 1), + ) + self.single_top = nn.Sequential( + nn.Linear(D_single_in, H1), + nn.ReLU(), + nn.Dropout(dropout), + nn.Linear(H1, H2), + nn.ReLU(), + nn.Dropout(dropout), + nn.Linear(H2, H3), + nn.ReLU(), + nn.Dropout(dropout), + nn.Linear(H3, 1), + nn.Linear(1, 1), + ) + self.init_weights() + + def init_weights(self): + w = (param.data for name, param in self.named_parameters() if "weight" in name) + b = (param.data for name, param in self.named_parameters() if "bias" in name) + nn.init.uniform_(self.word_embeds.weight.data, a=-0.5, b=0.5) + for t in w: + nn.init.xavier_uniform_(t) + for t in b: + nn.init.constant_(t, 0) + + def load_embeddings(self, preloaded_weights): + self.word_embeds.weight = nn.Parameter(preloaded_weights) + + def load_weights(self, weights_path): + print("Loading weights") + single_layers_weights, single_layers_biases = [], [] + for f in sorted(os.listdir(weights_path)): + if f.startswith("single_mention_weights"): + single_layers_weights.append(np.load(os.path.join(weights_path, f))) + if f.startswith("single_mention_bias"): + single_layers_biases.append(np.load(os.path.join(weights_path, f))) + top_single_linear = ( + layer for layer in self.single_top if isinstance(layer, nn.Linear) + ) + for w, b, layer in zip( + single_layers_weights, single_layers_biases, top_single_linear + ): + layer.weight = nn.Parameter(torch.from_numpy(w).float()) + layer.bias = nn.Parameter(torch.from_numpy(b).float().squeeze()) + pair_layers_weights, pair_layers_biases = [], [] + for f in sorted(os.listdir(weights_path)): + if f.startswith("pair_mentions_weights"): + pair_layers_weights.append(np.load(os.path.join(weights_path, f))) + if f.startswith("pair_mentions_bias"): + pair_layers_biases.append(np.load(os.path.join(weights_path, f))) + top_pair_linear = ( + layer for layer in self.pair_top if isinstance(layer, nn.Linear) + ) + for w, b, layer in zip( + pair_layers_weights, pair_layers_biases, top_pair_linear + ): + layer.weight = nn.Parameter(torch.from_numpy(w).float()) + layer.bias = nn.Parameter(torch.from_numpy(b).float().squeeze()) + + def forward(self, inputs, concat_axis=1): + pairs = len(inputs) == 8 + if pairs: + spans, words, single_features, ant_spans, ant_words, ana_spans, ana_words, pair_features = ( + inputs + ) + else: + spans, words, single_features = inputs + words = words.type(torch.LongTensor) + if torch.cuda.is_available(): + words = words.cuda() + embed_words = self.drop(self.word_embeds(words).view(words.size()[0], -1)) + single_input = torch.cat([spans, embed_words, single_features], 1) + single_scores = self.single_top(single_input) + if pairs: + batchsize, pairs_num, _ = ana_spans.size() + ant_words_long = ant_words.view(batchsize, -1).type(torch.LongTensor) + ana_words_long = ana_words.view(batchsize, -1).type(torch.LongTensor) + if torch.cuda.is_available(): + ant_words_long = ant_words_long.cuda() + ana_words_long = ana_words_long.cuda() + ant_embed_words = self.drop( + self.word_embeds(ant_words_long).view(batchsize, pairs_num, -1) + ) + ana_embed_words = self.drop( + self.word_embeds(ana_words_long).view(batchsize, pairs_num, -1) + ) + pair_input = torch.cat( + [ant_spans, ant_embed_words, ana_spans, ana_embed_words, pair_features], + 2, + ) + pair_scores = self.pair_top(pair_input).squeeze(dim=2) + total_scores = torch.cat([pair_scores, single_scores], concat_axis) + return total_scores if pairs else single_scores diff --git a/data_tooling/pii_processing/neuralcoref/train/runs/.gitignore b/data_tooling/pii_processing/neuralcoref/train/runs/.gitignore new file mode 100644 index 0000000..86d0cb2 --- /dev/null +++ b/data_tooling/pii_processing/neuralcoref/train/runs/.gitignore @@ -0,0 +1,4 @@ +# Ignore everything in this directory +* +# Except this file +!.gitignore \ No newline at end of file diff --git a/data_tooling/pii_processing/neuralcoref/train/scorer/README.txt b/data_tooling/pii_processing/neuralcoref/train/scorer/README.txt new file mode 100644 index 0000000..2533a29 --- /dev/null +++ b/data_tooling/pii_processing/neuralcoref/train/scorer/README.txt @@ -0,0 +1,100 @@ +NAME + CorScorer: Perl package for scoring coreference resolution systems + using different metrics. + + +VERSION + v8.01 -- reference implementations of MUC, B-cubed, CEAF and BLANC metrics. + + +CHANGES SINCE v8.0 + - fixed a bug that crashed the BLANC scorer when a duplicate singleton + mention was present in the response. + +INSTALLATION + Requirements: + 1. Perl: downloadable from http://perl.org + 2. Algorithm-Munkres: included in this package and downloadable + from CPAN http://search.cpan.org/~tpederse/Algorithm-Munkres-0.08 + +USE + This package is distributed with two scripts to execute the scorer from + the command line. + + Windows (tm): scorer.bat + Linux: scorer.pl + + +SYNOPSIS + use CorScorer; + + $metric = 'ceafm'; + + # Scores the whole dataset + &CorScorer::Score($metric, $keys_file, $response_file); + + # Scores one file + &CorScorer::Score($metric, $keys_file, $response_file, $name); + + +INPUT + metric: the metric desired to score the results: + muc: MUCScorer (Vilain et al, 1995) + bcub: B-Cubed (Bagga and Baldwin, 1998) + ceafm: CEAF (Luo et al., 2005) using mention-based similarity + ceafe: CEAF (Luo et al., 2005) using entity-based similarity + blanc: BLANC (Luo et al., 2014) BLANC metric for gold and predicted mentions + all: uses all the metrics to score + + keys_file: file with expected coreference chains in CoNLL-2011/2012 format + + response_file: file with output of coreference system (CoNLL-2011/2012 format) + + name: [optional] the name of the document to score. If name is not + given, all the documents in the dataset will be scored. If given + name is "none" then all the documents are scored but only total + results are shown. + + +OUTPUT + The score subroutine returns an array with four values in this order: + 1) Recall numerator + 2) Recall denominator + 3) Precision numerator + 4) Precision denominator + + Also recall, precision and F1 are printed in the standard output when variable + $VERBOSE is not null. + + Final scores: + Recall = recall_numerator / recall_denominator + Precision = precision_numerator / precision_denominator + F1 = 2 * Recall * Precision / (Recall + Precision) + + Identification of mentions + An scorer for identification of mentions (recall, precision and F1) is also included. + Mentions from system response are compared with key mentions. This version performs + strict mention matching as was used in the CoNLL-2011 and 2012 shared tasks. + +AUTHORS + Emili Sapena, Universitat Politècnica de Catalunya, http://www.lsi.upc.edu/~esapena, esapena lsi.upc.edu + Sameer Pradhan, sameer.pradhan childrens.harvard.edu + Sebastian Martschat, sebastian.martschat h-its.org + Xiaoqiang Luo, xql google.com + +COPYRIGHT AND LICENSE + Copyright (C) 2009-2011, Emili Sapena esapena lsi.upc.edu + 2011-2014, Sameer Pradhan sameer.pradhan childrens.harvard.edu + + This program is free software; you can redistribute it and/or modify it + under the terms of the GNU General Public License as published by the + Free Software Foundation; either version 2 of the License, or (at your + option) any later version. This program is distributed in the hope that + it will be useful, but WITHOUT ANY WARRANTY; without even the implied + warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the + GNU General Public License for more details. + + You should have received a copy of the GNU General Public License along + with this program; if not, write to the Free Software Foundation, Inc., + 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA. + diff --git a/data_tooling/pii_processing/neuralcoref/train/scorer/scorer.bat b/data_tooling/pii_processing/neuralcoref/train/scorer/scorer.bat new file mode 100644 index 0000000..679faed --- /dev/null +++ b/data_tooling/pii_processing/neuralcoref/train/scorer/scorer.bat @@ -0,0 +1,67 @@ +@rem = '--*-Perl-*-- +@echo off +if "%OS%" == "Windows_NT" goto WinNT +perl -x -S "%0" %1 %2 %3 %4 %5 %6 %7 %8 %9 +goto endofperl +:WinNT +perl -x -S %0 %* +if NOT "%COMSPEC%" == "%SystemRoot%\system32\cmd.exe" goto endofperl +if %errorlevel% == 9009 echo You do not have Perl in your PATH. +if errorlevel 1 goto script_failed_so_exit_with_non_zero_val 2>nul +goto endofperl +@rem '; +#!perl +#line 15 + +BEGIN { + $d = $0; + $d =~ s/\/[^\/][^\/]*$//g; + push(@INC, $d."/lib"); +} + +use strict; +use CorScorer; + +if (@ARGV < 3) { + print q| + use: scorer.bat [name] + + metric: the metric desired to score the results: + muc: MUCScorer (Vilain et al, 1995) + bcub: B-Cubed (Bagga and Baldwin, 1998) + ceafm: CEAF (Luo et al, 2005) using mention-based similarity + ceafe: CEAF (Luo et al, 2005) using entity-based similarity + all: uses all the metrics to score + + keys_file: file with expected coreference chains in SemEval format + + response_file: file with output of coreference system (SemEval format) + + name: [optional] the name of the document to score. If name is not + given, all the documents in the dataset will be scored. If given + name is "none" then all the documents are scored but only total + results are shown. + + |; + exit; +} + +my $metric = shift (@ARGV); +if ($metric !~ /^(muc|bcub|ceafm|ceafe|all)/i) { + print "Invalid metric\n"; + exit; +} + + +if ($metric eq 'all') { + foreach my $m ('muc', 'bcub', 'ceafm', 'ceafe') { + print "\nMETRIC $m:\n"; + &CorScorer::Score( $m, @ARGV ); + } +} +else { + &CorScorer::Score( $metric, @ARGV ); +} + +__END__ +:endofperl diff --git a/data_tooling/pii_processing/neuralcoref/train/scorer/scorer.pl b/data_tooling/pii_processing/neuralcoref/train/scorer/scorer.pl new file mode 100644 index 0000000..07b48d8 --- /dev/null +++ b/data_tooling/pii_processing/neuralcoref/train/scorer/scorer.pl @@ -0,0 +1,58 @@ +#!/usr/bin/perl + +BEGIN { + $d = $0; + $d =~ s/\/[^\/][^\/]*$//g; + + if ($d eq $0) { + unshift(@INC, "lib"); + } + else { + unshift(@INC, $d . "/lib"); + } +} + +use strict; +use CorScorer; + +if (@ARGV < 3) { + print q| +use: scorer.pl [name] + + metric: the metric desired to score the results: + muc: MUCScorer (Vilain et al, 1995) + bcub: B-Cubed (Bagga and Baldwin, 1998) + ceafm: CEAF (Luo et al, 2005) using mention-based similarity + ceafe: CEAF (Luo et al, 2005) using entity-based similarity + blanc: BLANC + all: uses all the metrics to score + + keys_file: file with expected coreference chains in SemEval format + + response_file: file with output of coreference system (SemEval format) + + name: [optional] the name of the document to score. If name is not + given, all the documents in the dataset will be scored. If given + name is "none" then all the documents are scored but only total + results are shown. + +|; + exit; +} + +my $metric = shift(@ARGV); +if ($metric !~ /^(muc|bcub|ceafm|ceafe|blanc|all)/i) { + print "Invalid metric\n"; + exit; +} + +if ($metric eq 'all') { + foreach my $m ('muc', 'bcub', 'ceafm', 'ceafe', 'blanc') { + print "\nMETRIC $m:\n"; + &CorScorer::Score($m, @ARGV); + } +} +else { + &CorScorer::Score($metric, @ARGV); +} + diff --git a/data_tooling/pii_processing/neuralcoref/train/scorer/test/CorefMetricTest.pm b/data_tooling/pii_processing/neuralcoref/train/scorer/test/CorefMetricTest.pm new file mode 100644 index 0000000..c5e96a3 --- /dev/null +++ b/data_tooling/pii_processing/neuralcoref/train/scorer/test/CorefMetricTest.pm @@ -0,0 +1,124 @@ +package CorefMetricTest; +use strict; +use warnings; +use Exporter; + +our @ISA= qw(Exporter); +our @EXPORT = qw(ComputeScoreFromCounts DiffExpectedAndActual); + +################################################################################ +# Compute recall, precision and F1. +# +# Input: (numerator_counts_for_recall, denominator_counts_for_recall, +# numerator_counts_for_precision, denominator_counts_for_precision) +# Output: (recall, precision, F1) +################################################################################ +sub ComputeScoreFromCounts { + # The first 4 are also coref link counts when using BLANC. + my ($recall_numerator, $recall_denominator, + $precision_numerator, $precision_denominator, @noncoref_counts) = @_; + # The coref recall, precision, and F1 when using BLANC. + my ($recall, $precision, $F1) = + RPFFromCounts($recall_numerator, $recall_denominator, + $precision_numerator, $precision_denominator); + + # BLANC: @noncoref_counts= + # (noncoref_numerator_recall, noncoref_denominator_recall, + # noncoref_numerator_precision, noncoref_denominator_precision) + if (scalar(@noncoref_counts) == 4) { + ($recall, $precision, $F1) = CorScorer::ComputeBLANCFromCounts( + $recall_numerator, $recall_denominator, $precision_denominator, + $noncoref_counts[0], $noncoref_counts[1], $noncoref_counts[3]); + } + $recall = ($recall < 0) ? 0 : $recall; + $precision = ($precision < 0) ? 0 : $precision; + $F1 = ($F1 < 0) ? 0 : $F1; + return ($recall, $precision, $F1); +} + +sub RPFFromCounts +{ + my ($recall_numerator, $recall_denominator, + $precision_numerator, $precision_denominator, @nonCorefCounts) = @_; + my ($recall, $precision, $F1) = (-1, -1, 0); + if ($recall_denominator > 0) { + $recall = $recall_numerator / $recall_denominator; + } + if ($precision_denominator > 0) { + $precision = $precision_numerator / $precision_denominator; + } + + if (($recall + $precision) > 0) { + $F1 = 2 * $recall * $precision / ($recall + $precision); + } + + return ($recall, $precision, $F1); +} + +# deprecated -- see CorScorer::ComputeBLANCFromCounts(). +sub ComputeBLANCRPF +{ + my ($coref_recall, $coref_precision, $coref_F1, + $noncoref_recall, $noncoref_precision, $noncoref_F1) = @_; + + my ($recall, $precision, $F1); + + if ($coref_recall < 0 && $noncoref_recall < 0) { + # no key mention. + $recall = $precision = $F1 = 0; + } elsif ($coref_recall < 0) { + # key: all links are non-coref (mentions are all singltons). + $recall = $noncoref_recall; + $precision = ($noncoref_precision < 0) ? 0 : $noncoref_precision; + $F1 = $noncoref_F1; + } elsif ($noncoref_recall < 0) { + # key: all links are coref (all mentions are in one entity). + $recall = $coref_recall; + $precision = ($coref_precision < 0) ? 0 : $coref_precision; + $F1 = $coref_F1; + } else { + #key contains both coref and non-coref links. + if ($coref_precision < 0 && $noncoref_precision < 0) { + # no response. + $recall = $precision = $F1 = 0; + } else { + if ($coref_precision < 0) { + # response: all links are non-coref, or response mentions are all + # singletons. + $coref_precision = 0; + } elsif ($noncoref_precision < 0) { + # response: all links are coref, or all mentions are in one entity. + $noncoref_precision = 0; + } + $recall = ($coref_recall + $noncoref_recall)/2; + $precision = ($coref_precision + $noncoref_precision)/2; + $F1 = ($coref_F1 + $noncoref_F1)/2; + } + } + + return ($recall, $precision, $F1); +} + +############################################################################## +# Compute the sum of the duifference between the expected recall, precision, +# F1 and the actual one. +############################################################################## +sub DiffExpectedAndActual { + my ($expected, $actual) = @_; + if (scalar(@$expected) != scalar(@$actual)) { + print STDERR "Expected and actual have diff dimensions: \n"; + print STDERR " Expected: ", join(" ", @$expected), "\n"; + print STDERR " Actual: ", join(" ", @$actual), "\n"; + return 1.0e5; + } + my $sum = 0.0; + my $i = 0; + foreach my $e (@$expected) { + $sum += abs($e - $actual->[$i]); + ++$i; + } + return $sum; +} + +1; + diff --git a/data_tooling/pii_processing/neuralcoref/train/scorer/test/CorefMetricTestConfig.pm b/data_tooling/pii_processing/neuralcoref/train/scorer/test/CorefMetricTestConfig.pm new file mode 100644 index 0000000..974f655 --- /dev/null +++ b/data_tooling/pii_processing/neuralcoref/train/scorer/test/CorefMetricTestConfig.pm @@ -0,0 +1,363 @@ +################################################################################ +# This is the test configuration file. Test cases are stored in an +# array, each element consisting of: +# (1) id: a unique identifier for the test case. +# (2) key_file: the key file to be tested in the CoNLL format. +# (3) response_file: the response file to be tested in the CoNLL format. +# (4) expected_metrics: is a hash label from a metric name (identical to those +# used in the scorer.{pl|bat}) to an array of expected +# metric values. All metrics have 3 expected numbers: +# (recall, precision, F-measure). +################################################################################ + +package CorefMetricTestConfig; +use strict; +use warnings; +use Exporter; + +our @ISA= qw( Exporter ); + +# these are exported by default. +our @EXPORT = qw(TestCases); + +# +# Values following metric names are [recall, precision, F1] +# +our @TestCases = ( +{ id => "A1", + key_file => "DataFiles/TC-A.key", + response_file => "DataFiles/TC-A-1.response", + expected_metrics => { "muc" => [1, 1, 1], + "bcub" => [6/6, 6/6, 1], + "ceafm" => [1, 1, 1], + "ceafe" => [1, 1, 1], + "blanc" => [1, 1, 1] } +}, +{ id => "A2", + key_file => "DataFiles/TC-A.key", + response_file => "DataFiles/TC-A-2.response", + expected_metrics => { "muc" => [1/3, 1/1, 0.5], + "bcub" => [(7/3)/6, 3/3, 14/25], + "ceafm" => [0.5, 1, 0.66667], + "ceafe" => [0.6, 0.9, 0.72], + "blanc" => [0.21591, 1, 0.35385] } +}, +{ id => "A3", + key_file => "DataFiles/TC-A.key", + response_file => "DataFiles/TC-A-3.response", + expected_metrics => { "muc" => [3/3, 3/5, 0.75], + "bcub" => [6/6, (4+7/12)/9, 110/163], + "ceafm" => [1, 0.66667, 0.8], + "ceafe" => [0.88571, 0.66429, 0.75918], + "blanc" => [1, 0.42593, 0.59717] } +}, +{ id => "A4", + key_file => "DataFiles/TC-A.key", + response_file => "DataFiles/TC-A-4.response", + expected_metrics => { "muc" => [1/3, 1/3, 1/3], + "bcub" => [(3+1/3)/6, (1+4/3+1/2)/7, 2*(5/9)*(17/42)/((5/9)+(17/42))], + "ceafm" => [0.66667, 0.57143, 0.61538], + "ceafe" => [0.73333, 0.55, 0.62857], + "blanc" => [0.35227, 0.27206, 0.30357] } +}, +{ id => "A5", + key_file => "DataFiles/TC-A.key", + response_file => "DataFiles/TC-A-5.response", + expected_metrics => { "muc" => [1/3, 1/4, 2/7], + "bcub" => [(3+1/3)/6, 2.5/8, 2*(5/9)*(5/16)/((5/9)+(5/16))], + "ceafm" => [0.66667, 0.5, 0.57143], + "ceafe" => [0.68889, 0.51667, 0.59048], + "blanc" => [0.35227, 0.19048, 0.24716] } +}, +{ id => "A6", + key_file => "DataFiles/TC-A.key", + response_file => "DataFiles/TC-A-6.response", + expected_metrics => { "muc" => [1/3, 1/4, 2/7], + "bcub" => [(10/3)/6, (1+4/3+1/2)/8, 2*(5/9)*(17/48)/((5/9)+(17/48))], + "ceafm" => [0.66667, 0.5, 0.57143], + "ceafe" => [0.73333, 0.55, 0.62857], + "blanc" => [0.35227, 0.20870, 0.25817] } +}, +{ id => "A7", + key_file => "DataFiles/TC-A.key", + response_file => "DataFiles/TC-A-7.response", + expected_metrics => { "muc" => [1/3, 1/3, 1/3], + "bcub" => [(10/3)/6, (1+4/3+1/2)/7, 2*(5/9)*(17/42)/((5/9)+(17/42))], + "ceafm" => [0.66667, 0.57143, 0.61538], + "ceafe" => [0.73333, 0.55, 0.62857], + "blanc" => [0.35227, 0.27206, 0.30357] } +}, +{ id => "A8", + key_file => "DataFiles/TC-A.key", + response_file => "DataFiles/TC-A-8.response", + expected_metrics => { "muc" => [1/3, 1/3, 1/3], + "bcub" => [(10/3)/6, (1+4/3+1/2)/7, 2*(5/9)*(17/42)/((5/9)+(17/42))], + "ceafm" => [0.66667, 0.57143, 0.61538], + "ceafe" => [0.73333, 0.55, 0.62857], + "blanc" => [0.35227, 0.27206, 0.30357] } +}, +{ id => "A9", + key_file => "DataFiles/TC-A.key", + response_file => "DataFiles/TC-A-9.response", + expected_metrics => { "muc" => [1/3, 1/3, 1/3], + "bcub" => [(10/3)/6, (1+4/3+1/2)/7, 2*(5/9)*(17/42)/((5/9)+(17/42))], + "ceafm" => [0.66667, 0.57143, 0.61538], + "ceafe" => [0.73333, 0.55, 0.62857], + "blanc" => [0.35227, 0.27206, 0.30357] } +}, +{ id => "A10", + key_file => "DataFiles/TC-A.key", + response_file => "DataFiles/TC-A-10.response", + expected_metrics => { "muc" => [0, 0, 0], + "bcub" => [3/6, 6/6, 2/3], + #”ceafm" => [1, 1, 1], + #”ceafe" => [1, 1, 1], + "blanc" => [0.5, 0.36667, 0.42308] } +}, +{ id => "A11", + key_file => "DataFiles/TC-A.key", + response_file => "DataFiles/TC-A-11.response", + expected_metrics => { "muc" => [3/3, 3/5, 6/8], + "bcub" => [6/6, (1/6+2*2/6+3*3/6)/6, 14/25], + #”ceafm" => [1, 1, 1], + #”ceafe" => [1, 1, 1], + "blanc" => [0.5, 0.13333, 0.21053] } +}, +{ id => "A12", + key_file => "DataFiles/TC-A.key", + response_file => "DataFiles/TC-A-12.response", + expected_metrics => { "muc" => [0, 0, 0], + "bcub" => [(1+1/2+2/3)/6, 4/7, 2*(13/36)*(4/7)/((13/36)+(4/7))], + #”ceafm" => [1, 1, 1], + #”ceafe" => [1, 1, 1], + "blanc" => [0.22727, 0.11905, 0.15625] } +}, +{ id => "A13", + key_file => "DataFiles/TC-A.key", + response_file => "DataFiles/TC-A-13.response", + expected_metrics => { "muc" => [1/3, 1/6, 2/9], + "bcub" => [(1+1/2+2*2/3)/6, (1/7+1/7+2*2/7)/7, 2*(17/36)*(6/49)/((17/36)+(6/49))], + #”ceafm" => [1, 1, 1], + #”ceafe" => [1, 1, 1], + "blanc" => [0.125, 0.02381, 0.04] } +}, +{ id => "B1", + key_file => "DataFiles/TC-B.key", + response_file => "DataFiles/TC-B-1.response", + expected_metrics => { #"muc" => [1, 1, 1], + #"bcub" => [1, 1, 1], + #”ceafm" => [1, 1, 1], + #”ceafe" => [1, 1, 1], + "blanc" => [1/2 * (1/4 + 1/3), 1/2 * (1/4 + 1/3), 1/2 * (1/4 + 1/3)] } +}, +{ id => "C1", + key_file => "DataFiles/TC-C.key", + response_file => "DataFiles/TC-C-1.response", + expected_metrics => { #"muc" => [1, 1, 1], + #"bcub" => [1, 1, 1], + #”ceafm" => [1, 1, 1], + #”ceafe" => [1, 1, 1], + "blanc" => [1/2 * (2/5 + 10/16), 1/2 * (2/5 + 10/16), 1/2 * (2/5 + 10/16)] } +}, +{ id => "D1", + key_file => "DataFiles/TC-D.key", + response_file => "DataFiles/TC-D-1.response", + expected_metrics => { "muc" => [9/9, 9/10, 2*(9/9)*(9/10)/(9/9+9/10)], + "bcub" => [12/12, 16/21, 2*(12/12)*(16/21)/(12/12+16/21)], + #"ceafm" => [1, 1, 1], + #"ceafe" => [1, 1, 1], + #"blanc" => [1, 1, 1] + } +}, +{ id => "E1", + key_file => "DataFiles/TC-E.key", + response_file => "DataFiles/TC-E-1.response", + expected_metrics => { "muc" => [9/9, 9/10, 2*(9/9)*(9/10)/(9/9+9/10)], + "bcub" => [1, 7/12, 2*1*(7/12)/(1+7/12)], + #"ceafm" => [1, 1, 1], + #"ceafe" => [1, 1, 1], + #"blanc" => [1, 1, 1] + } +}, +{ id => "F1", + key_file => "DataFiles/TC-F.key", + response_file => "DataFiles/TC-F-1.response", + expected_metrics => { "muc" => [2/3, 2/2, 2*(2/3)*(2/2)/(2/3+2/2)] , + #"bcub" => , + #"ceafm" => , + #"ceafe" => , + #"blanc" => + } +}, +{ id => "G1", + key_file => "DataFiles/TC-G.key", + response_file => "DataFiles/TC-G-1.response", + expected_metrics => { "muc" => [2/2, 2/3, 2*(2/2)*(2/3)/(2/2+2/3)], + #"bcub" => , + #"ceafm" => , + #"ceafe" => , + #"blanc" => + } +}, +{ id => "H1", + key_file => "DataFiles/TC-H.key", + response_file => "DataFiles/TC-H-1.response", + expected_metrics => { "muc" => [1, 1, 1], + #"bcub" => , + #"ceafm" => , + #"ceafe" => , + #"blanc" => + } +}, +{ id => "I1", + key_file => "DataFiles/TC-I.key", + response_file => "DataFiles/TC-I-1.response", + expected_metrics => { "muc" => [2/3, 2/2, 2*(2/3)*(2/2)/(2/3+2/2)], + #"bcub" => , + #"ceafm" => , + #"ceafe" => , + #"blanc" => + } +}, +{ id => "J1", + key_file => "DataFiles/TC-J.key", + response_file => "DataFiles/TC-J-1.response", + expected_metrics => { "muc" => [1/2, 1/1, 2*(1/2)*(1/1)/(1/2+1/1)], + #"bcub" => , + #"ceafm" => , + #"ceafe" => , + #"blanc" => + } +}, +{ id => "K1", + key_file => "DataFiles/TC-K.key", + response_file => "DataFiles/TC-K-1.response", + expected_metrics => { "muc" => [3/6, 3/6, 3/6], + #"bcub" => , + #"ceafm" => , + #"ceafe" => , + #"blanc" => + } +}, +{ id => "L1", + key_file => "DataFiles/TC-L.key", + response_file => "DataFiles/TC-L-1.response", + expected_metrics => { "muc" => [2/5, 2/4, 2*(2/5)*(2/4)/(2/5+2/4)], + #"bcub" => , + #"ceafm" => , + #"ceafe" => , + #"blanc" => + } +}, +{ id => "M1", + key_file => "DataFiles/TC-M.key", + response_file => "DataFiles/TC-M-1.response", + expected_metrics => { "muc" => [1, 1, 1], + "bcub" => [1, 1, 1], + "ceafm" => [1, 1, 1], + "ceafe" => [1, 1, 1], + "blanc" => [1, 1, 1] } +}, +{ id => "M2", + key_file => "DataFiles/TC-M.key", + response_file => "DataFiles/TC-M-2.response", + expected_metrics => { "muc" => [0, 0, 0], + #"bcub" => , + #"ceafm" => , + #"ceafe" => , + "blanc" => [0, 0, 0] } +}, +{ id => "M3", + key_file => "DataFiles/TC-M.key", + response_file => "DataFiles/TC-M-3.response", + expected_metrics => { #"muc" => , + #"bcub" => , + #"ceafm" => , + #"ceafe" => , + "blanc" => [0.26667, 1, 0.42105] } +}, +{ id => "M4", + key_file => "DataFiles/TC-M.key", + response_file => "DataFiles/TC-M-4.response", + expected_metrics => { #"muc" => , + #"bcub" => , + #"ceafm" => , + #"ceafe" => , + "blanc" => [0.2, 0.2, 0.2] } +}, +{ id => "M5", + key_file => "DataFiles/TC-M.key", + response_file => "DataFiles/TC-M-5.response", + expected_metrics => { "muc" => [0, 0, 0], + #"bcub" => , + #"ceafm" => , + #"ceafe" => , + "blanc" => [0, 0, 0] } +}, +{ id => "M6", + key_file => "DataFiles/TC-M.key", + response_file => "DataFiles/TC-M-6.response", + expected_metrics => { #"muc" => , + #"bcub" => , + #"ceafm" => , + #"ceafe" => , + "blanc" => [0.06667, 0.25, 0.10526] } +}, +{ id => "N1", + key_file => "DataFiles/TC-N.key", + response_file => "DataFiles/TC-N-1.response", + expected_metrics => { "muc" => [0, 0, 0], + #"bcub" => [1, 1, 1], + #"ceafm" => [1, 1, 1], + #"ceafe" => [1, 1, 1], + "blanc" => [1, 1, 1] } +}, +{ id => "N2", + key_file => "DataFiles/TC-N.key", + response_file => "DataFiles/TC-N-2.response", + expected_metrics => { "muc" => [0, 0, 0], + #"bcub" => , + #"ceafm" => , + #"ceafe" => , + "blanc" => [0, 0, 0] } +}, +{ id => "N3", + key_file => "DataFiles/TC-N.key", + response_file => "DataFiles/TC-N-3.response", + expected_metrics => { #"muc" => , + #"bcub" => , + #"ceafm" => , + #"ceafe" => , + "blanc" => [0.73333, 1, 0.84615] } +}, +{ id => "N4", + key_file => "DataFiles/TC-N.key", + response_file => "DataFiles/TC-N-4.response", + expected_metrics => { "muc" => [0, 0, 0], + #"bcub" => , + #"ceafm" => , + #"ceafe" => , + "blanc" => [0.2, 0.2, 0.2] } +}, +{ id => "N5", + key_file => "DataFiles/TC-N.key", + response_file => "DataFiles/TC-N-5.response", + expected_metrics => { #"muc" => , + #"bcub" => , + #"ceafm" => , + #"ceafe" => , + "blanc" => [0, 0, 0] } +}, +{ id => "N6", + key_file => "DataFiles/TC-N.key", + response_file => "DataFiles/TC-N-6.response", + expected_metrics => { #"muc" => , + #"bcub" => , + #"ceafm" => , + #"ceafe" => , + "blanc" => [0.13333, 0.18182, 0.15385] } +} + +); + +1; diff --git a/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-A-1.response b/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-A-1.response new file mode 100644 index 0000000..445a92e --- /dev/null +++ b/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-A-1.response @@ -0,0 +1,23 @@ +#begin document (LuoTestCase); +test1 0 0 a1 (0 +test1 0 1 a2 0) +test1 0 2 junk - +test1 0 3 b1 (1 +test1 0 4 b2 - +test1 0 5 b3 - +test1 0 6 b4 1) +test1 0 7 jnk - +test1 0 8 . - + +test2 0 0 c (1) +test2 0 1 jnk - +test2 0 2 d1 (2 +test2 0 3 d2 2) +test2 0 4 jnk - +test2 0 5 e (2) +test2 0 6 jnk - +test2 0 7 f1 (2 +test2 0 8 f2 - +test2 0 9 f3 2) +test2 0 10 . - +#end document diff --git a/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-A-10.response b/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-A-10.response new file mode 100644 index 0000000..e323b09 --- /dev/null +++ b/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-A-10.response @@ -0,0 +1,23 @@ +#begin document (LuoTestCase); +test1 0 0 a1 (0 +test1 0 1 a2 0) +test1 0 2 junk - +test1 0 3 b1 (1 +test1 0 4 b2 - +test1 0 5 b3 - +test1 0 6 b4 1) +test1 0 7 jnk - +test1 0 8 . - + +test2 0 0 c (2) +test2 0 1 x - +test2 0 2 d1 (3 +test2 0 3 d2 3) +test2 0 4 z - +test2 0 5 e (4) +test2 0 6 y - +test2 0 7 f1 (5 +test2 0 8 f2 - +test2 0 9 f3 5) +test2 0 10 . - +#end document diff --git a/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-A-11.response b/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-A-11.response new file mode 100644 index 0000000..90ea74d --- /dev/null +++ b/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-A-11.response @@ -0,0 +1,23 @@ +#begin document (LuoTestCase); +test1 0 0 a1 (0 +test1 0 1 a2 0) +test1 0 2 junk - +test1 0 3 b1 (0 +test1 0 4 b2 - +test1 0 5 b3 - +test1 0 6 b4 0) +test1 0 7 jnk - +test1 0 8 . - + +test2 0 0 c (0) +test2 0 1 x - +test2 0 2 d1 (0 +test2 0 3 d2 0) +test2 0 4 z - +test2 0 5 e (0) +test2 0 6 y - +test2 0 7 f1 (0 +test2 0 8 f2 - +test2 0 9 f3 0) +test2 0 10 . - +#end document diff --git a/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-A-12.response b/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-A-12.response new file mode 100644 index 0000000..1c59f5e --- /dev/null +++ b/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-A-12.response @@ -0,0 +1,23 @@ +#begin document (LuoTestCase); +test1 0 0 a1 (0 +test1 0 1 a2 0) +test1 0 2 junk - +test1 0 3 b1 (1 +test1 0 4 b2 1) +test1 0 5 b3 - +test1 0 6 b4 - +test1 0 7 jnk (2) +test1 0 8 . - + +test2 0 0 c (3) +test2 0 1 x - +test2 0 2 d1 (4 +test2 0 3 d2 4) +test2 0 4 z - +test2 0 5 e (5) +test2 0 6 y - +test2 0 7 f1 (6) +test2 0 8 f2 - +test2 0 9 f3 - +test2 0 10 . - +#end document diff --git a/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-A-13.response b/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-A-13.response new file mode 100644 index 0000000..cfe2b73 --- /dev/null +++ b/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-A-13.response @@ -0,0 +1,23 @@ +#begin document (LuoTestCase); +test1 0 0 a1 (0 +test1 0 1 a2 0) +test1 0 2 junk - +test1 0 3 b1 (0 +test1 0 4 b2 0) +test1 0 5 b3 - +test1 0 6 b4 - +test1 0 7 jnk (0) +test1 0 8 . - + +test2 0 0 c (0) +test2 0 1 x - +test2 0 2 d1 (0 +test2 0 3 d2 0) +test2 0 4 z - +test2 0 5 e (0) +test2 0 6 y - +test2 0 7 f1 (0) +test2 0 8 f2 - +test2 0 9 f3 - +test2 0 10 . - +#end document diff --git a/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-A-2.response b/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-A-2.response new file mode 100644 index 0000000..d0726f1 --- /dev/null +++ b/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-A-2.response @@ -0,0 +1,23 @@ +#begin document (LuoTestCase); +test1 0 0 a1 (0 +test1 0 1 a2 0) +test1 0 2 junk - +test1 0 3 b1 - +test1 0 4 b2 - +test1 0 5 b3 - +test1 0 6 b4 - +test1 0 7 jnk - +test1 0 8 . - + +test2 0 0 c - +test2 0 1 jnk - +test2 0 2 d1 (2 +test2 0 3 d2 2) +test2 0 4 jnk - +test2 0 5 e (2) +test2 0 6 jnk - +test2 0 7 f1 - +test2 0 8 f2 - +test2 0 9 f3 - +test2 0 10 . - +#end document diff --git a/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-A-3.response b/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-A-3.response new file mode 100644 index 0000000..49cec4b --- /dev/null +++ b/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-A-3.response @@ -0,0 +1,23 @@ +#begin document (LuoTestCase); +test1 0 0 a1 (0 +test1 0 1 a2 0) +test1 0 2 junk - +test1 0 3 b1 (1 +test1 0 4 b2 - +test1 0 5 b3 - +test1 0 6 b4 1) +test1 0 7 jnk - +test1 0 8 . - + +test2 0 0 c (1) +test2 0 1 x (1) +test2 0 2 d1 (2 +test2 0 3 d2 2) +test2 0 4 y (2) +test2 0 5 e (2) +test2 0 6 z (3) +test2 0 7 f1 (2 +test2 0 8 f2 - +test2 0 9 f3 2) +test2 0 10 . - +#end document diff --git a/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-A-4.response b/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-A-4.response new file mode 100644 index 0000000..df84841 --- /dev/null +++ b/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-A-4.response @@ -0,0 +1,23 @@ +#begin document (LuoTestCase); +test1 0 0 a1 (0 +test1 0 1 a2 0) +test1 0 2 junk - +test1 0 3 b1 (1 +test1 0 4 b2 - +test1 0 5 b3 - +test1 0 6 b4 1) +test1 0 7 jnk - +test1 0 8 . - + +test2 0 0 c (1) +test2 0 1 x (1) +test2 0 2 d1 (2 +test2 0 3 d2 2) +test2 0 4 x (3) +test2 0 5 e - +test2 0 6 y (2) +test2 0 7 f1 - +test2 0 8 f2 - +test2 0 9 f3 - +test2 0 10 . - +#end document diff --git a/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-A-5.response b/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-A-5.response new file mode 100644 index 0000000..921e34a --- /dev/null +++ b/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-A-5.response @@ -0,0 +1,23 @@ +#begin document (LuoTestCase); +test1 0 0 a1 (0 +test1 0 1 a2 0) +test1 0 2 junk - +test1 0 3 b1 (1 +test1 0 4 b2 (1 +test1 0 5 b3 1) +test1 0 6 b4 1) +test1 0 7 jnk - +test1 0 8 . - + +test2 0 0 c (1) +test2 0 1 x (1) +test2 0 2 d1 (2 +test2 0 3 d2 2) +test2 0 4 z (3) +test2 0 5 e - +test2 0 6 y (2) +test2 0 7 f1 - +test2 0 8 f2 - +test2 0 9 f3 - +test2 0 10 . - +#end document diff --git a/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-A-6.response b/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-A-6.response new file mode 100644 index 0000000..f1a8954 --- /dev/null +++ b/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-A-6.response @@ -0,0 +1,23 @@ +#begin document (LuoTestCase); +test1 0 0 a1 (0 +test1 0 1 a2 0) +test1 0 2 junk - +test1 0 3 b1 (1 +test1 0 4 b2 (3 +test1 0 5 b3 3) +test1 0 6 b4 1) +test1 0 7 jnk - +test1 0 8 . - + +test2 0 0 c (1) +test2 0 1 x (1) +test2 0 2 d1 (2 +test2 0 3 d2 2) +test2 0 4 z (3) +test2 0 5 e - +test2 0 6 y (2) +test2 0 7 f1 - +test2 0 8 f2 - +test2 0 9 f3 - +test2 0 10 . - +#end document diff --git a/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-A-7.response b/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-A-7.response new file mode 100644 index 0000000..b111e44 --- /dev/null +++ b/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-A-7.response @@ -0,0 +1,23 @@ +#begin document (LuoTestCase); +test1 0 0 a1 (0 +test1 0 1 a2 0) +test1 0 2 junk - +test1 0 3 b1 (1(1 +test1 0 4 b2 - +test1 0 5 b3 - +test1 0 6 b4 1)1) +test1 0 7 jnk - +test1 0 8 . - + +test2 0 0 c (1) +test2 0 1 x (1) +test2 0 2 d1 (2 +test2 0 3 d2 2) +test2 0 4 z (3) +test2 0 5 e - +test2 0 6 y (2) +test2 0 7 f1 - +test2 0 8 f2 - +test2 0 9 f3 - +test2 0 10 . - +#end document diff --git a/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-A-8.response b/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-A-8.response new file mode 100644 index 0000000..974b4f0 --- /dev/null +++ b/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-A-8.response @@ -0,0 +1,23 @@ +#begin document (LuoTestCase); +test1 0 0 a1 (0 +test1 0 1 a2 0) +test1 0 2 junk - +test1 0 3 b1 (1(3 +test1 0 4 b2 - +test1 0 5 b3 - +test1 0 6 b4 3)1) +test1 0 7 jnk - +test1 0 8 . - + +test2 0 0 c (1) +test2 0 1 x (1) +test2 0 2 d1 (2 +test2 0 3 d2 2) +test2 0 4 z (3) +test2 0 5 e - +test2 0 6 y (2) +test2 0 7 f1 - +test2 0 8 f2 - +test2 0 9 f3 - +test2 0 10 . - +#end document diff --git a/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-A-9.response b/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-A-9.response new file mode 100644 index 0000000..a370a5b --- /dev/null +++ b/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-A-9.response @@ -0,0 +1,23 @@ +#begin document (LuoTestCase); +test1 0 0 a1 (0 +test1 0 1 a2 0) +test1 0 2 junk - +test1 0 3 b1 (1(3(3(3(3(3(3(3(3(3(3 +test1 0 4 b2 - +test1 0 5 b3 - +test1 0 6 b4 3)3)3)3)3)3)3)3)3)3)1) +test1 0 7 jnk - +test1 0 8 . - + +test2 0 0 c (1) +test2 0 1 x (1) +test2 0 2 d1 (2 +test2 0 3 d2 2) +test2 0 4 z (3) +test2 0 5 e - +test2 0 6 y (2) +test2 0 7 f1 - +test2 0 8 f2 - +test2 0 9 f3 - +test2 0 10 . - +#end document diff --git a/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-A.key b/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-A.key new file mode 100644 index 0000000..445a92e --- /dev/null +++ b/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-A.key @@ -0,0 +1,23 @@ +#begin document (LuoTestCase); +test1 0 0 a1 (0 +test1 0 1 a2 0) +test1 0 2 junk - +test1 0 3 b1 (1 +test1 0 4 b2 - +test1 0 5 b3 - +test1 0 6 b4 1) +test1 0 7 jnk - +test1 0 8 . - + +test2 0 0 c (1) +test2 0 1 jnk - +test2 0 2 d1 (2 +test2 0 3 d2 2) +test2 0 4 jnk - +test2 0 5 e (2) +test2 0 6 jnk - +test2 0 7 f1 (2 +test2 0 8 f2 - +test2 0 9 f3 2) +test2 0 10 . - +#end document diff --git a/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-B-1.response b/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-B-1.response new file mode 100644 index 0000000..3224fbc --- /dev/null +++ b/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-B-1.response @@ -0,0 +1,74 @@ +#begin document (nw/xinhua/00/chtb_0009); part 000 +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (10043 +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 10043) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (10043) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (10043 +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 10043) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (10054 +nw/xinhua/00/chtb_0009 10054) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (10054) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - + +#end document diff --git a/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-B.key b/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-B.key new file mode 100644 index 0000000..59fd836 --- /dev/null +++ b/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-B.key @@ -0,0 +1,74 @@ +#begin document (nw/xinhua/00/chtb_0009); part 000 +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (10043 +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 10043) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (10054 +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 10054) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (10043) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (10054 +nw/xinhua/00/chtb_0009 10054) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (10054) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - + +#end document diff --git a/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-C-1.response b/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-C-1.response new file mode 100644 index 0000000..6e1ee2f --- /dev/null +++ b/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-C-1.response @@ -0,0 +1,74 @@ +#begin document (nw/xinhua/00/chtb_0009); part 000 +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (10043 +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 10043) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (10043) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (10043 +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 10043) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (10054 +nw/xinhua/00/chtb_0009 10054) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (10054) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (10060) +nw/xinhua/00/chtb_0009 (10060) + +#end document diff --git a/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-C.key b/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-C.key new file mode 100644 index 0000000..259383a --- /dev/null +++ b/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-C.key @@ -0,0 +1,74 @@ +#begin document (nw/xinhua/00/chtb_0009); part 000 +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (10043 +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 10043) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (10054 +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 10054) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (10043) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (10054 +nw/xinhua/00/chtb_0009 10054) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (10054) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (10060) +nw/xinhua/00/chtb_0009 (10060) + +#end document diff --git a/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-D-1.response b/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-D-1.response new file mode 100644 index 0000000..d2be1a0 --- /dev/null +++ b/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-D-1.response @@ -0,0 +1,31 @@ +#begin document (nw/xinhua/00/chtb_0009); part 000 +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (1) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (1) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (1) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (1) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (1) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (3) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (3) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (3) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (3) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (3) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (3) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (3) + +#end document diff --git a/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-D.key b/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-D.key new file mode 100644 index 0000000..785d0a4 --- /dev/null +++ b/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-D.key @@ -0,0 +1,31 @@ +#begin document (nw/xinhua/00/chtb_0009); part 000 +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (1) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (1) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (1) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (1) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (1) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (2) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (2) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (3) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (3) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (3) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (3) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (3) + +#end document diff --git a/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-E-1.response b/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-E-1.response new file mode 100644 index 0000000..c7710cd --- /dev/null +++ b/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-E-1.response @@ -0,0 +1,31 @@ +#begin document (nw/xinhua/00/chtb_0009); part 000 +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (1) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (1) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (1) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (1) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (1) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (2) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (2) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (1) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (1) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (1) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (1) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (1) + +#end document diff --git a/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-E.key b/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-E.key new file mode 100644 index 0000000..785d0a4 --- /dev/null +++ b/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-E.key @@ -0,0 +1,31 @@ +#begin document (nw/xinhua/00/chtb_0009); part 000 +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (1) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (1) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (1) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (1) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (1) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (2) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (2) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (3) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (3) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (3) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (3) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (3) + +#end document diff --git a/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-F-1.response b/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-F-1.response new file mode 100644 index 0000000..f2a6355 --- /dev/null +++ b/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-F-1.response @@ -0,0 +1,31 @@ +#begin document (nw/xinhua/00/chtb_0009); part 000 +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (1) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (1) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (2) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (2) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - + +#end document diff --git a/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-F.key b/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-F.key new file mode 100644 index 0000000..bb972d2 --- /dev/null +++ b/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-F.key @@ -0,0 +1,31 @@ +#begin document (nw/xinhua/00/chtb_0009); part 000 +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (1) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (1) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (1) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (1) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - + +#end document diff --git a/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-G-1.response b/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-G-1.response new file mode 100644 index 0000000..bb972d2 --- /dev/null +++ b/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-G-1.response @@ -0,0 +1,31 @@ +#begin document (nw/xinhua/00/chtb_0009); part 000 +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (1) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (1) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (1) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (1) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - + +#end document diff --git a/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-G.key b/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-G.key new file mode 100644 index 0000000..f2a6355 --- /dev/null +++ b/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-G.key @@ -0,0 +1,31 @@ +#begin document (nw/xinhua/00/chtb_0009); part 000 +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (1) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (1) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (2) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (2) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - + +#end document diff --git a/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-H-1.response b/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-H-1.response new file mode 100644 index 0000000..bb972d2 --- /dev/null +++ b/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-H-1.response @@ -0,0 +1,31 @@ +#begin document (nw/xinhua/00/chtb_0009); part 000 +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (1) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (1) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (1) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (1) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - + +#end document diff --git a/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-H.key b/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-H.key new file mode 100644 index 0000000..bb972d2 --- /dev/null +++ b/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-H.key @@ -0,0 +1,31 @@ +#begin document (nw/xinhua/00/chtb_0009); part 000 +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (1) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (1) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (1) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (1) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - + +#end document diff --git a/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-I-1.response b/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-I-1.response new file mode 100644 index 0000000..f2a6355 --- /dev/null +++ b/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-I-1.response @@ -0,0 +1,31 @@ +#begin document (nw/xinhua/00/chtb_0009); part 000 +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (1) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (1) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (2) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (2) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - + +#end document diff --git a/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-I.key b/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-I.key new file mode 100644 index 0000000..bb972d2 --- /dev/null +++ b/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-I.key @@ -0,0 +1,31 @@ +#begin document (nw/xinhua/00/chtb_0009); part 000 +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (1) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (1) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (1) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (1) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - + +#end document diff --git a/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-J-1.response b/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-J-1.response new file mode 100644 index 0000000..4f78b25 --- /dev/null +++ b/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-J-1.response @@ -0,0 +1,31 @@ +#begin document (nw/xinhua/00/chtb_0009); part 000 +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (1) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (1) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - + +#end document diff --git a/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-J.key b/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-J.key new file mode 100644 index 0000000..3519532 --- /dev/null +++ b/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-J.key @@ -0,0 +1,31 @@ +#begin document (nw/xinhua/00/chtb_0009); part 000 +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (1) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (1) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (1) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - + +#end document diff --git a/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-K-1.response b/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-K-1.response new file mode 100644 index 0000000..70a2552 --- /dev/null +++ b/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-K-1.response @@ -0,0 +1,31 @@ +#begin document (nw/xinhua/00/chtb_0009); part 000 +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (1) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (1) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (1) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (2) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (2) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (2) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (3) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (3) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (3) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - + +#end document diff --git a/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-K.key b/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-K.key new file mode 100644 index 0000000..588ff84 --- /dev/null +++ b/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-K.key @@ -0,0 +1,31 @@ +#begin document (nw/xinhua/00/chtb_0009); part 000 +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (1) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (1) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (1) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (1) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (1) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (1) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (1) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - + +#end document diff --git a/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-L-1.response b/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-L-1.response new file mode 100644 index 0000000..cb8ae7a --- /dev/null +++ b/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-L-1.response @@ -0,0 +1,31 @@ +#begin document (nw/xinhua/00/chtb_0009); part 000 +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (1) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (1) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (2) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (2) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (3) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (3) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (3) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - + +#end document diff --git a/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-L.key b/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-L.key new file mode 100644 index 0000000..472c3b9 --- /dev/null +++ b/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-L.key @@ -0,0 +1,31 @@ +#begin document (nw/xinhua/00/chtb_0009); part 000 +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (1) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (1) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (1) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (2) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (2) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (2) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 (2) +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - +nw/xinhua/00/chtb_0009 - + +#end document diff --git a/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-M-1.response b/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-M-1.response new file mode 100644 index 0000000..2dca5b3 --- /dev/null +++ b/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-M-1.response @@ -0,0 +1,23 @@ +#begin document (LuoTestCase); +test1 0 0 a1 (0 +test1 0 1 a2 0) +test1 0 2 junk - +test1 0 3 b1 (0 +test1 0 4 b2 - +test1 0 5 b3 - +test1 0 6 b4 0) +test1 0 7 jnk - +test1 0 8 . - + +test2 0 0 c (0) +test2 0 1 jnk - +test2 0 2 d1 (0 +test2 0 3 d2 0) +test2 0 4 jnk - +test2 0 5 e (0) +test2 0 6 jnk - +test2 0 7 f1 (0 +test2 0 8 f2 - +test2 0 9 f3 0) +test2 0 10 . - +#end document diff --git a/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-M-2.response b/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-M-2.response new file mode 100644 index 0000000..7fd13ec --- /dev/null +++ b/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-M-2.response @@ -0,0 +1,23 @@ +#begin document (LuoTestCase); +test1 0 0 a1 (0 +test1 0 1 a2 0) +test1 0 2 junk - +test1 0 3 b1 (1 +test1 0 4 b2 - +test1 0 5 b3 - +test1 0 6 b4 1) +test1 0 7 jnk - +test1 0 8 . - + +test2 0 0 c (2) +test2 0 1 jnk - +test2 0 2 d1 (3 +test2 0 3 d2 3) +test2 0 4 jnk - +test2 0 5 e (4) +test2 0 6 jnk - +test2 0 7 f1 (5 +test2 0 8 f2 - +test2 0 9 f3 5) +test2 0 10 . - +#end document diff --git a/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-M-3.response b/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-M-3.response new file mode 100644 index 0000000..bf3fb66 --- /dev/null +++ b/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-M-3.response @@ -0,0 +1,23 @@ +#begin document (LuoTestCase); +test1 0 0 a1 (0 +test1 0 1 a2 0) +test1 0 2 junk - +test1 0 3 b1 (0 +test1 0 4 b2 - +test1 0 5 b3 - +test1 0 6 b4 0) +test1 0 7 jnk - +test1 0 8 . - + +test2 0 0 c (1) +test2 0 1 jnk - +test2 0 2 d1 (1 +test2 0 3 d2 1) +test2 0 4 jnk - +test2 0 5 e (1) +test2 0 6 jnk - +test2 0 7 f1 (2 +test2 0 8 f2 - +test2 0 9 f3 2) +test2 0 10 . - +#end document diff --git a/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-M-4.response b/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-M-4.response new file mode 100644 index 0000000..590914b --- /dev/null +++ b/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-M-4.response @@ -0,0 +1,23 @@ +#begin document (LuoTestCase); +test1 0 0 a1 (0 +test1 0 1 a2 0) +test1 0 2 junk - +test1 0 3 b1 (0 +test1 0 4 b2 - +test1 0 5 b3 - +test1 0 6 b4 0) +test1 0 7 jnk - +test1 0 8 . - + +test2 0 0 c (0) +test2 0 1 jnk (0) +test2 0 2 d1 - +test2 0 3 d2 - +test2 0 4 jnk (0) +test2 0 5 e - +test2 0 6 jnk (0) +test2 0 7 f1 - +test2 0 8 f2 - +test2 0 9 f3 - +test2 0 10 . - +#end document diff --git a/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-M-5.response b/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-M-5.response new file mode 100644 index 0000000..00aa567 --- /dev/null +++ b/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-M-5.response @@ -0,0 +1,23 @@ +#begin document (LuoTestCase); +test1 0 0 a1 (0 +test1 0 1 a2 0) +test1 0 2 junk - +test1 0 3 b1 (1 +test1 0 4 b2 - +test1 0 5 b3 - +test1 0 6 b4 1) +test1 0 7 jnk - +test1 0 8 . - + +test2 0 0 c (2) +test2 0 1 jnk (3) +test2 0 2 d1 - +test2 0 3 d2 - +test2 0 4 jnk (4) +test2 0 5 e - +test2 0 6 jnk (5) +test2 0 7 f1 - +test2 0 8 f2 - +test2 0 9 f3 - +test2 0 10 . - +#end document diff --git a/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-M-6.response b/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-M-6.response new file mode 100644 index 0000000..8436410 --- /dev/null +++ b/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-M-6.response @@ -0,0 +1,23 @@ +#begin document (LuoTestCase); +test1 0 0 a1 (0 +test1 0 1 a2 0) +test1 0 2 junk - +test1 0 3 b1 (0 +test1 0 4 b2 - +test1 0 5 b3 - +test1 0 6 b4 0) +test1 0 7 jnk - +test1 0 8 . - + +test2 0 0 c (1) +test2 0 1 jnk (1) +test2 0 2 d1 - +test2 0 3 d2 - +test2 0 4 jnk (1) +test2 0 5 e - +test2 0 6 jnk (2) +test2 0 7 f1 - +test2 0 8 f2 - +test2 0 9 f3 - +test2 0 10 . - +#end document diff --git a/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-M.key b/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-M.key new file mode 100644 index 0000000..2dca5b3 --- /dev/null +++ b/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-M.key @@ -0,0 +1,23 @@ +#begin document (LuoTestCase); +test1 0 0 a1 (0 +test1 0 1 a2 0) +test1 0 2 junk - +test1 0 3 b1 (0 +test1 0 4 b2 - +test1 0 5 b3 - +test1 0 6 b4 0) +test1 0 7 jnk - +test1 0 8 . - + +test2 0 0 c (0) +test2 0 1 jnk - +test2 0 2 d1 (0 +test2 0 3 d2 0) +test2 0 4 jnk - +test2 0 5 e (0) +test2 0 6 jnk - +test2 0 7 f1 (0 +test2 0 8 f2 - +test2 0 9 f3 0) +test2 0 10 . - +#end document diff --git a/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-N-1.response b/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-N-1.response new file mode 100644 index 0000000..7fd13ec --- /dev/null +++ b/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-N-1.response @@ -0,0 +1,23 @@ +#begin document (LuoTestCase); +test1 0 0 a1 (0 +test1 0 1 a2 0) +test1 0 2 junk - +test1 0 3 b1 (1 +test1 0 4 b2 - +test1 0 5 b3 - +test1 0 6 b4 1) +test1 0 7 jnk - +test1 0 8 . - + +test2 0 0 c (2) +test2 0 1 jnk - +test2 0 2 d1 (3 +test2 0 3 d2 3) +test2 0 4 jnk - +test2 0 5 e (4) +test2 0 6 jnk - +test2 0 7 f1 (5 +test2 0 8 f2 - +test2 0 9 f3 5) +test2 0 10 . - +#end document diff --git a/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-N-2.response b/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-N-2.response new file mode 100644 index 0000000..2dca5b3 --- /dev/null +++ b/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-N-2.response @@ -0,0 +1,23 @@ +#begin document (LuoTestCase); +test1 0 0 a1 (0 +test1 0 1 a2 0) +test1 0 2 junk - +test1 0 3 b1 (0 +test1 0 4 b2 - +test1 0 5 b3 - +test1 0 6 b4 0) +test1 0 7 jnk - +test1 0 8 . - + +test2 0 0 c (0) +test2 0 1 jnk - +test2 0 2 d1 (0 +test2 0 3 d2 0) +test2 0 4 jnk - +test2 0 5 e (0) +test2 0 6 jnk - +test2 0 7 f1 (0 +test2 0 8 f2 - +test2 0 9 f3 0) +test2 0 10 . - +#end document diff --git a/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-N-3.response b/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-N-3.response new file mode 100644 index 0000000..bf3fb66 --- /dev/null +++ b/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-N-3.response @@ -0,0 +1,23 @@ +#begin document (LuoTestCase); +test1 0 0 a1 (0 +test1 0 1 a2 0) +test1 0 2 junk - +test1 0 3 b1 (0 +test1 0 4 b2 - +test1 0 5 b3 - +test1 0 6 b4 0) +test1 0 7 jnk - +test1 0 8 . - + +test2 0 0 c (1) +test2 0 1 jnk - +test2 0 2 d1 (1 +test2 0 3 d2 1) +test2 0 4 jnk - +test2 0 5 e (1) +test2 0 6 jnk - +test2 0 7 f1 (2 +test2 0 8 f2 - +test2 0 9 f3 2) +test2 0 10 . - +#end document diff --git a/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-N-4.response b/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-N-4.response new file mode 100644 index 0000000..00aa567 --- /dev/null +++ b/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-N-4.response @@ -0,0 +1,23 @@ +#begin document (LuoTestCase); +test1 0 0 a1 (0 +test1 0 1 a2 0) +test1 0 2 junk - +test1 0 3 b1 (1 +test1 0 4 b2 - +test1 0 5 b3 - +test1 0 6 b4 1) +test1 0 7 jnk - +test1 0 8 . - + +test2 0 0 c (2) +test2 0 1 jnk (3) +test2 0 2 d1 - +test2 0 3 d2 - +test2 0 4 jnk (4) +test2 0 5 e - +test2 0 6 jnk (5) +test2 0 7 f1 - +test2 0 8 f2 - +test2 0 9 f3 - +test2 0 10 . - +#end document diff --git a/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-N-5.response b/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-N-5.response new file mode 100644 index 0000000..590914b --- /dev/null +++ b/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-N-5.response @@ -0,0 +1,23 @@ +#begin document (LuoTestCase); +test1 0 0 a1 (0 +test1 0 1 a2 0) +test1 0 2 junk - +test1 0 3 b1 (0 +test1 0 4 b2 - +test1 0 5 b3 - +test1 0 6 b4 0) +test1 0 7 jnk - +test1 0 8 . - + +test2 0 0 c (0) +test2 0 1 jnk (0) +test2 0 2 d1 - +test2 0 3 d2 - +test2 0 4 jnk (0) +test2 0 5 e - +test2 0 6 jnk (0) +test2 0 7 f1 - +test2 0 8 f2 - +test2 0 9 f3 - +test2 0 10 . - +#end document diff --git a/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-N-6.response b/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-N-6.response new file mode 100644 index 0000000..8436410 --- /dev/null +++ b/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-N-6.response @@ -0,0 +1,23 @@ +#begin document (LuoTestCase); +test1 0 0 a1 (0 +test1 0 1 a2 0) +test1 0 2 junk - +test1 0 3 b1 (0 +test1 0 4 b2 - +test1 0 5 b3 - +test1 0 6 b4 0) +test1 0 7 jnk - +test1 0 8 . - + +test2 0 0 c (1) +test2 0 1 jnk (1) +test2 0 2 d1 - +test2 0 3 d2 - +test2 0 4 jnk (1) +test2 0 5 e - +test2 0 6 jnk (2) +test2 0 7 f1 - +test2 0 8 f2 - +test2 0 9 f3 - +test2 0 10 . - +#end document diff --git a/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-N.key b/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-N.key new file mode 100644 index 0000000..7fd13ec --- /dev/null +++ b/data_tooling/pii_processing/neuralcoref/train/scorer/test/DataFiles/TC-N.key @@ -0,0 +1,23 @@ +#begin document (LuoTestCase); +test1 0 0 a1 (0 +test1 0 1 a2 0) +test1 0 2 junk - +test1 0 3 b1 (1 +test1 0 4 b2 - +test1 0 5 b3 - +test1 0 6 b4 1) +test1 0 7 jnk - +test1 0 8 . - + +test2 0 0 c (2) +test2 0 1 jnk - +test2 0 2 d1 (3 +test2 0 3 d2 3) +test2 0 4 jnk - +test2 0 5 e (4) +test2 0 6 jnk - +test2 0 7 f1 (5 +test2 0 8 f2 - +test2 0 9 f3 5) +test2 0 10 . - +#end document diff --git a/data_tooling/pii_processing/neuralcoref/train/scorer/test/TestCases.README b/data_tooling/pii_processing/neuralcoref/train/scorer/test/TestCases.README new file mode 100644 index 0000000..d60d2bb --- /dev/null +++ b/data_tooling/pii_processing/neuralcoref/train/scorer/test/TestCases.README @@ -0,0 +1,390 @@ +TC-A-1 - perfect: +Key/Ref: {a} {bc} {def} +Rsp/Sys: {a} {bc} {def} +Expected: BCUB=1 [recall=6/6, prec=6/6] +Expected: MUC=1 [recall=3/3=1, prec=3/3=1] +Expected: CEAFm=1 [recall=6/6=1, prec=6/6=1] +Expected: CEAFe=1 [recall=3/3=1, prec=3/3=1] +Expected: BLANC=1 [recall_c=4/4=1, prec_c=4/4=1, recall_n=11/11=1, prec_n=11/11=1] + +TC-A-2 -- response with missing mentions/entities +Key/Ref: {a} {bc} {def} +Rsp/Sys: {a} {de} +Expected: BCUB=.5599 [recall=7/18, prec=3/3] +Expected: MUC=0.5 [recall=1/3, prec=1/1] +Expected: CEAFm=6/9=0.67 [common=3, recall=3/6=0.5, Prec=3/3=1] +Expected: CEAFe=3.6/5=0.72 [common=1+4/5=1.8, recall=1.8/3=0.6, Prec=1.8/2=0.9] +Expected: BLANC=0.35 [recall_c=1/4, prec_c=1/1, recall_n=2/11, prec_n=2/2] + +TC-A-3 -- response with false-alarm mentions/entities +Key/Ref: {a} {bc} {def} +Rsp/Sys: {a} {bcx} {defy} {z} +Expected: BCUB=.6748 [recall=6/6, prec=55/108] +Expected: MUC=0.75 [recall=3/3, prec=3/5] +Expected: CEAFm=12/15=0.8 [common=6, recall=6/6=1, prec=6/9=.67] +Expected: CEAFe=3.6/5=0.76 [common=1+4/5+6/7=2.66, recall=2.66/3=0.89, Prec=2.66/4=0.66] +Expected: BLANC=0.60 [recall_c=4/4, prec_c=4/9, recall_n=11/11, prec_n=11/27] + + +TC-A-4 -- response with both missing and false-alarm mentions/entities +Key/Ref: {a} {bc} {def} +Rsp/Sys: {a} {bcx} {dy} {z} +Expected: BCUB=.4683 [recall=5/9, prec=17/42] +Expected: MUC=1/3=.33333 [recall=1/3, prec=1/3] +Expected: CEAFm=8/13=0.62 [common=4 recall=4/6=0.67 prec=4/7=.57] +Expected: CEAFe=4.4/7=0.63 [common=1+4/5+2/5=2.2, recall=2.2/3=0.73, Prec=2.2/4=0.55] +Expected: BLANC=0.30 [recall_c=1/4, prec_c=1/4, recall_n=5/11, prec_n=5/17] + +TC-A-5 -- response with both missing and false-alarm mentions/entities, and overlapping mentions (capitalized letter: b and B). Overlapping mention B in the aligned entity. +Key/Ref: {a} {bc} {def} +Rsp/Sys: {a} {bcxB} {dy} {z} +Expected: BCUB=.4 [recall=5/9, prec=5/16] +Expected: MUC=2/7=.28571 [recall=1/3, prec=1/4] +Expected: CEAFm=8/14=0.57 [common=4 recall=4/6=0.67 prec=4/8=.5] +Expected: CEAFe=4.14/7=0.59 [common=1+4/6+2/5=2.07, recall=2.07/3=0.69, Prec=2.07/4=0.52] +Expected: BLANC=0.25 [recall_c=1/4, prec_c=1/7, recall_n=5/11, prec_n=5/21] + +TC-A-6 -- response with both missing and false-alarm mentions/entities, and overlapping mentions (capitalized letter: b and B). Overlapping mention B in an unaligned entity. +Key/Ref: {a} {bc} {def} +Rsp/Sys: {a} {bcx} {dy} {Bz} +Expected: BCUB=.4325 [recall=5/9, prec=17/48] +Expected: MUC=2/7=.28571 [recall=1/3, prec=1/4] +Expected: CEAFm=8/14=0.57 [common=4 recall=4/6=0.67 prec=4/8=.5] +Expected: CEAFe=4.4/7=0.63 [common=1+4/5+2/5=2.2, recall=2.2/3=0.73, Prec=2.2/4=0.55] +Expected: BLANC=0.26 [recall_c=1/4, prec_c=1/5, recall_n=5/11, prec_n=5/23] + +TC-A-7 -- response with both missing and false-alarm mentions/entities, and duplicate mentions (capitalized letter: b and B). Duplicate mention B in the same cluster entity (note: this is diff from TC5) -- this tests mention de-duplication. +Key/Ref: {a} {bc} {def} +Rsp/Sys: {a} {bcxB} {dy} {z} + de-dup: {a} {bcx} {dy} {z} + +de-dup: +Expected: BCUB=.4683 [recall=5/9, prec=17/42] +Expected: MUC=1/3=.33333 [recall=1/3, prec=1/3] +Expected: CEAFm=8/13=0.61538 [common=4, recall=4/6=0.66667, Prec=4/7=0.57143] +Expected: CEAFe=4.14/7=0.62857 [common=1+4/5+2/5=2.2, recall=2.2/3=0.73333, Prec=2.2/4=0.55] +Expected: BLANC=0.30 [recall_c=1/4, prec_c=1/4, recall_n=5/11, prec_n=5/17] + +if No de-dup: +Expected: CEAFm=8/14=0.57 [common=4 recall=4/6=0.67 prec=4/8=.5] +Expected: CEAFe=4.14/7=0.59 [common=1+4/6+2/5=2.07, recall=2.07/3=0.69, Prec=2.07/4=0.52] + + +TC-A-8 -- response with both missing and false-alarm mentions/entities, and duplicate mentions (capitalized letter: b and B). Duplicate mention B in a diff entity from b. +Key/Ref: {a} {bc} {def} +Rsp/Sys: {a} {bcx} {dy} {Bz} + +De-dup: +Expected: BCUB=.4683 [recall=5/9, prec=17/42] +Expected: MUC=1/3=.33333 [recall=1/3, prec=1/3] +Expected: CEAFm=8/13=0.61538 [common=4 recall=4/6=0.67 prec=4/7=.57143] +Expected: CEAFe=4.14/7=0.63 [common=1+4/5+2/5=2.2, recall=2.2/3=0.73, Prec=2.2/4=0.55] +Expected: BLANC=0.30 [recall_c=1/4, prec_c=1/4, recall_n=5/11, prec_n=5/17] + +If no de-dup: +Expected: CEAFm=8/14=0.57 [common=4 recall=4/6=0.67 prec=4/8=.5] +Expected: CEAFe=4.14/7=0.63 [common=1+4/5+2/5=2.2, recall=2.2/3=0.73, Prec=2.2/4=0.55] + +TC-A-9 -- show B3 can be canned: "b" is repeated 10 times so precision approaches 1 +Key/Ref: {a} {bc} {def} +Rsp/Sys: {a} {bcx} {dy} {Bx10z} +de-dup Rsp/Sys: {a} {bcx} {dy} {z} + +De-dup: +Expected: BCUB=.4683 [recall=5/9, prec=17/42] +Expected: MUC=1/3=.33333 [recall=1/3, prec=1/3] +Expected: CEAFm=8/14=0.57 [common=4 recall=4/6=0.67 prec=4/7=.57143] +Expected: CEAFe=4.4/7=0.63 [common=1+4/5+2/5=2.2, recall=2.2/3=0.73, Prec=2.2/4=0.55] +Expected: BLANC=0.30 [recall_c=1/4, prec_c=1/4, recall_n=5/11, prec_n=5/17] + + +TC-A-10 - Gold mentions. Only singletons in the response. +Key/Ref: {a} {bc} {def} +Rsp/Sys: {a} {b} {c} {d} {e} {f} +Expected: BCUB=.6667 [recall=3/6, prec=6/6] +Expected: MUC=0 [recall=0, prec=0] +Expected: BLANC=0.42 [recall_c=0/4, prec_c=0/0, f_c=0, recall_n=11/11, prec_n=11/15] + + +TC-A-11 - Gold mentions. All mentions are coreferent in the response. +Key/Ref: {a} {bc} {def} +Rsp/Sys: {abcdef} + +Expected: BCUB=0.5599 [recall=6/6, prec=7/18] +Expected: MUC=6/8=0.75 [recall=3/3, prec=3/5] +Expected: BLANC=0.21 [recall_c=4/4, prec_c=4/15, recall_n=0/11, prec_n=0/0, f_n=0] + + +TC-A-12 - System mentions. Only singletons in the response. +Key/Ref: {a} {bc} {def} +Rsp/Sys: {a} {x} {y} {c} {d} {e} {z} + +Expected: BCUB=0.4425 [recall=13/36, prec=4/7] +Expected: MUC=0 [recall=0, prec=0] +Expected: BLANC=0.16 [recall_c=0/4, prec_c=0/0, f_c=0, recall_n=5/11, prec_n=5/21] + + +TC-A-13 - System mentions. All mentions are coreferent in the response. +Key/Ref: {a} {bc} {def} +Rsp/Sys: {axycdez} + +Expected: BCUB=0.19447 [recall=17/36, prec=6/49] +Expected: MUC=2/9 [recall=1/3, prec=1/6] +Expected: BLANC=0.04 [recall_c=1/4, prec_c=1/21, recall_n=0/11, prec_n=0/0, f_n=0] + + +TC-B-1 -- spurious mention (x) and missing mention (a) in response; link (bc) is a key non-coref link and is an incorrect response coref link. + + Keys: {ab} {cde} +Response: {bcx} {de} + + key coref links: C_k = {(ab), (cd), (de), (ce)} +key non-coref links: N_k = {(ac), (ad), (ae), (bc), (bd), (be)} + + response coref links: C_r = {(bc), (bx), (cx), (de)} +response non-coref links: N_r = {(bd), (be), (cd), (ce), (xd), (xe)} + +(I'll use ^ for set intersection) +C_k ^ C_r = {(de)} => R_c = |C_k^C_r| / |C_k| = 1/4, P_c = 1/|C_r| = 1/4, F_c = 1/4 +N_k ^ N_r = {(bd), (be)} => R_n = |N_k^N_r|/|N_k| = 2/6, P_n = 2/|N_r| = 2/6, F_n = 1/3 + +BLANC = 1/2 (F_c + F_n) = 7/24. + + + + + TC-C-1 -- same as TC14 plus a new entity and its correct prediction shown. this was for testing the more than two entity case. + + Keys: {ab} {cde} {fg} +Response: {bcx} {de} {fg} + + key coref links: C_k = {(ab), (cd), (de), (ce), (fg)}} + key non-coref links: N_k = {(ac), (ad), (ae), (bc), (bd), (be), (af), (ag), (bf), (bg), (cf), (cg), (df), (dg), (ef), (eg)} + + response coref links: C_r = {(bc), (bx), (cx), (de), (fg)} +response non-coref links: N_r = {(bd), (be), (cd), (ce), (xd), (xe), (bf), (bg), (cf), (cg), (xf), (xg), (df), (dg), (ef), (eg)} + +(I'll use ^ for set intersection) +C_k ^ C_r = {(de), (fg)} => R_c = |C_k^C_r| / |C_k| = 2/5, P_c = 2/|C_r| = 2/5, F_c = 2/5 = 0.40 +N_k ^ N_r = {(bd), (be), (bf), (bg), (cf), (cg), (df), (dg), (ef), (eg)} => R_n = |N_k^N_r|/|N_k| = 10/16, P_n = 10/|N_r| = 10/16, F_n = 10/16 = 0.625 + +BLANC = 1/2 (F_c + F_n) = 0.5125 + + + +# ------------ examples from the B-CUBED paper + +TC-D-1 -- merging one small cluster with a big cluster + +key: {12345} {67} {89ABC} +--- + +1-2-3-4-5 + +6-7 + +8-9-A-B-C + + + +response: {12345} {6789ABC} +--------- + +1-2-3-4-5 + +6-7 + | + 8-9-A-B-C + + +Expected: BCUB [r=12/12, p=16/21, f=0.864864865] +Expected: MUC [r=9/9, p=9/10, f=0.947368421] + + + +TC-E-1 -- merging two big clusters + + +key: {12345} {67} {89ABC} +--- + +1-2-3-4-5 + +6-7 + +8-9-A-B-C + + + +response: {123456789ABC} {67} +--------- + +1-2-3-4-5 + | +6-7 | + | + 8-9-A-B-C + + +Expected: BCUB [r=1, p=7/12, f=0.736842105] +Expected: MUC [r=9/9, p=9/10, f=0.947368421] + + +# ---------- examples from the MUC paper + +TC-F-1 -- + + key: {ABCD} ---- Links: A-B; B-C; C-D +response: {AB} {CD} ---- Links: A-B; C-D + +Expected: MUC [r=2/3, p=2/2, f=2*(2/3)*(2/2)/(2/3+2/2)] + + + +TC-G-1 -- + + key: {AB} {CD} ---- Links: A-B; C-D +response: {ABCD} ---- Links: A-B; B-C; C-D + +Expected: MUC [r=2/2, p=2/3, f=2*(2/2)*(2/3)/(2/2+2/3)] + + + +TC-H-1 -- + + key: {ABCD} ---- Links: A-B; B-C; B-D +response: {ABCD} ---- Links: A-B; B-C; C-D + +Expected: MUC [r=1, p=1, f=1] + + + +TC-I-1 -- + + key: {ABCD} ---- Links: A-B; B-C; B-D +response: {AB} {CD} ---- Links: A-B; C-D + +Expected: MUC [r=2/3, p=2/2, f=2*(2/3)*(2/2)/(2/3+2/2)] + + + +TC-J-1 -- + + key: {ABC} ---- Links: A-B; B-C +response: {AC} ---- Links: A-C + +Expected: MUC [r=1/2, p=1/1, f=2*(1/2)*(1/1)/(1/2+1/1)] + + + +TC-K-1 -- + + key: {BCDEGHJ} ---- Links: B-C; C-D; D-E; E-G; G-H; H-J +response: {ABC} {DEF} {GHI} ---- Links: A-B; B-C; D-E; E-F; G-H; H-I + +Expected: MUC [r=3/6, p=3/6, f=3/6] + + + +TC-L-1 -- + + key: {ABC} {DEFG} ---- Links: A-B; B-C; D-E; E-F; F-G +response: {AB} {CD} {FGH} ---- Links: A-B; C-D; F-G; G-H + +Expected: MUC [r=2/5, p=2/4, f=2*(2/5)*(2/4)/(2/5+2/4)] + + +TC-M-1 - Only coreferent mentions in the key. Gold mentions. Matching response. Since the key contains no non-coreference link, BLANC equals recall_c, prec_c, F_c. +Key/Ref: {abcdef} +Rsp/Sys: {abcdef} + +Expected: BCUB=1 +Expected: MUC=1 +Expected: CEAFm=1 +Expected: CEAFe=1 +Expected: BLANC=1 [recall_c=15/15=1, prec_c=15/15=1] + + +TC-M-2 - Only coreferent mentions in the key. Gold mentions. Response contains only non-coreference links. +Key/Ref: {abcdef} +Rsp/Sys: {a} {b} {c} {d} {e} {f} + +Expected: MUC=0 +Expected: BLANC=0 [recall_c=0/15=0, prec_c=0/0=0] + + +TC-M-3 - Only coreferent mentions in the key. Gold mentions. Response contains coreference and non-coreference links. +Key/Ref: {abcdef} +Rsp/Sys: {ab} {cde} {f} + +Expected: BLANC=0.42 [recall_c=4/15, prec_c=4/4=1] + + +TC-M-4 - Only coreferent mentions in the key. System mentions: only coreferent mentions. Since the key contains no non-coreference link, BLANC equals recall_c, prec_c, F_c. +Key/Ref: {abcdef} +Rsp/Sys: {abcxyz} + +Expected: BLANC=0.20 [recall_c=3/15, prec_c=3/15] + + +TC-M-5 - Only coreferent mentions in the key. System mentions: only singletons. +Key/Ref: {abcdef} +Rsp/Sys: {a} {b} {c} {x} {y} {z} + +Expected: MUC=0 +Expected: BLANC=0 [recall_c=0/15=0, prec_c=0/0=0] + + +TC-M-6 - Only coreferent mentions in the key. System mentions: coreference and non-coreference links. +Key/Ref: {abcdef} +Rsp/Sys: {ab} {cxy} {z} + +Expected: BLANC=0.11 [recall_c=1/15, prec_c=1/4] + + +TC-N-1 - Only singletons in the key. Gold mentions. Matching response. Since the key contains no coreference link, BLANC equals recall_n, prec_n, F_n. +Key/Ref: {a} {b} {c} {d} {e} {f} +Rsp/Sys: {a} {b} {c} {d} {e} {f} + +Expected: BCUB=1 +Expected: MUC=0 +Expected: CEAFm=1 +Expected: CEAFe=1 +Expected: BLANC=1 [recall_n=15/15=1, prec_n=15/15=1] + + +TC-N-2 - Only singletons in the key. Gold mentions. Response contains only coreference links. +Key/Ref: {a} {b} {c} {d} {e} {f} +Rsp/Sys: {abcdef} + +Expected: BLANC=0 [recall_n=0/15=0, prec_n=0/0=0] + + +TC-N-3 - Only singletons in the key. Gold mentions. Response contains coreference and non-coreference links. +Key/Ref: {a} {b} {c} {d} {e} {f} +Rsp/Sys: {ab} {cde} {f} + +Expected: BLANC=0.85 [recall_n=11/15, prec_n=11/11=1] + + +TC-N-4 - Only singletons in the key. System mentions: only singletons. Since the key contains no coreference link, BLANC equals recall_n, prec_n, F_n. +Key/Ref: {a} {b} {c} {d} {e} {f} +Rsp/Sys: {a} {b} {c} {x} {y} {z} + +Expected: MUC=0 +Expected: BLANC=0.20 [recall_n=3/15, prec_n=3/15] + + +TC-N-5 - Only singletons in the key. System mentions: only coreference links. +Key/Ref: {a} {b} {c} {d} {e} {f} +Rsp/Sys: {abcxyz} + +Expected: BLANC=0 [recall_n=0/15=0, prec_n=0/0=0] + + +TC-N-6 - Only singletons in the key. Only coreferent mentions in the key. System mentions: coreference and non-coreference links. +Key/Ref: {a} {b} {c} {d} {e} {f} +Rsp/Sys: {ab} {cxy} {z} + +Expected: BLANC=0.15 [recall_n=2/15, prec_n=2/11] + diff --git a/data_tooling/pii_processing/neuralcoref/train/scorer/test/test.pl b/data_tooling/pii_processing/neuralcoref/train/scorer/test/test.pl new file mode 100644 index 0000000..78228e8 --- /dev/null +++ b/data_tooling/pii_processing/neuralcoref/train/scorer/test/test.pl @@ -0,0 +1,46 @@ +#!/usr/bin/perl + +BEGIN { + $d = $0; + $d =~ s/\/[^\/][^\/]*$//g; + push(@INC, $d); + push(@INC, $d . "/../lib"); +} + +use strict; +use CorScorer; +use CorefMetricTest; +use CorefMetricTestConfig; + +my $error_tolerance = 1.e-4; +my $script_dir = $0; +$script_dir =~ s/\/[^\/][^\/]*$//g; + +foreach my $test_case (@CorefMetricTestConfig::TestCases) { + my $id = $test_case->{'id'}; + my @key_response_files = ($script_dir . "/" . $test_case->{'key_file'}, + $script_dir . "/" . $test_case->{'response_file'}); + print "\nTesting case ($id): keyFile=", $key_response_files[0], + " responseFile=", $key_response_files[1], "\n"; + my $expected_metrics = $test_case->{'expected_metrics'}; + foreach my $metric_name (sort keys %$expected_metrics) { + my $expected_values = $expected_metrics->{$metric_name}; + *::SAVED_STDOUT = *STDOUT; + *STDOUT = *::SUPRRES_STDOUT; + my @actual_counts = &CorScorer::Score($metric_name, @key_response_files); + # Compute R,P,and F1 from raw counts. + my @actual_values = CorefMetricTest::ComputeScoreFromCounts(@actual_counts); + *STDOUT = *::SAVED_STDOUT; + my $diff = CorefMetricTest::DiffExpectedAndActual($expected_values, \@actual_values); + printf " metric: %+10s", $metric_name; + if ($diff < $error_tolerance) { + print " => PASS\n"; + } else { + print " => FAIL\n"; + print " Expected (recall, prec, F1) = (", join(" ", @$expected_values), ")\n"; + print " Actual (recall, prec, F1) = (", join(" ", @actual_values), ")\n"; + #exit(1); + } + } +} + diff --git a/data_tooling/pii_processing/neuralcoref/train/scorer_wrapper.pl b/data_tooling/pii_processing/neuralcoref/train/scorer_wrapper.pl new file mode 100644 index 0000000..b43fc30 --- /dev/null +++ b/data_tooling/pii_processing/neuralcoref/train/scorer_wrapper.pl @@ -0,0 +1,35 @@ +#!/usr/bin/perl + +BEGIN { + $d = $0; + $d =~ s/\/[^\/][^\/]*$//g; + + if ($d eq $0) { + unshift(@INC, "scorer/lib"); + } + else { + unshift(@INC, $d . "/scorer/lib"); + } +} + +use strict; +use CorScorer; + +my $metric = shift(@ARGV); +if ($metric !~ /^(muc|bcub|ceafm|ceafe|blanc|all)/i) { + print "Invalid metric\n"; + exit; +} + +if ($metric eq 'all') { + foreach my $m ('muc', 'bcub', 'ceafm', 'ceafe', 'blanc') { +# print "\nMETRIC $m:\n"; + my ($acumNR, $acumDR, $acumNP, $acumDP, $identNR, $identDR, $identNP, $identDP) = &CorScorer::Score($m, @ARGV); + print "$acumNR $acumDR $acumNP $acumDP\n$identNR $identDR $identNP $identDP"; + } +} +else { + my ($acumNR, $acumDR, $acumNP, $acumDP, $identNR, $identDR, $identNP, $identDP) = &CorScorer::Score($metric, @ARGV); + print "$acumNR $acumDR $acumNP $acumDP\n$identNR $identDR $identNP $identDP"; +} + diff --git a/data_tooling/pii_processing/neuralcoref/train/training.md b/data_tooling/pii_processing/neuralcoref/train/training.md new file mode 100644 index 0000000..dce11ef --- /dev/null +++ b/data_tooling/pii_processing/neuralcoref/train/training.md @@ -0,0 +1,121 @@ +# How to train and modify the neural coreference model + +Please check our [detailed blog post](https://medium.com/huggingface/how-to-train-a-neural-coreference-model-neuralcoref-2-7bb30c1abdfe) together with these short notes. + +## Install + +As always, we recommend creating a clean environment (conda or virtual env) to install and train the model. + +You will need to install [pyTorch](http://pytorch.org/), the neuralcoref package with the additional training requirements and download a language model for spacy. +Currently this can be done (assuming an English language model) with + +```bash +conda install pytorch -c pytorch +pip install -r ./train/training_requirements.txt -e . +python -m spacy download en +``` + +## Get the data + +The following assumes you want to train on English, Arabic or Chinese. +If you want to train on another language, see the section [train on a new language](#train-on-a-new-language) below. + +First, download the [OntoNotes 5.0 dataset](https://catalog.ldc.upenn.edu/LDC2013T19) from LDC. + +Then, download the [CoNLL-2012 skeleton files](http://conll.cemantix.org/2012/data.html) from the CoNLL 2012 shared task site, +and combine these skeleton files with the OntoNotes files to get the `*._conll` text files which can be used as inputs for the training. + +This can be done by executing the script [compile_coref_data.sh](/neuralcoref/train/conll_processing_script/compile_coref_data.sh) +or by following these steps: + +- From the [CoNLL 2012 download site](http://conll.cemantix.org/2012/download/), download and extract: + - http://conll.cemantix.org/2012/download/conll-2012-train.v4.tar.gz + - http://conll.cemantix.org/2012/download/conll-2012-development.v4.tar.gz + - http://conll.cemantix.org/2012/download/test/conll-2012-test-key.tar.gz + - http://conll.cemantix.org/2012/download/test/conll-2012-test-official.v9.tar.gz + - http://conll.cemantix.org/2012/download/conll-2012-scripts.v3.tar.gz + - http://conll.cemantix.org/download/reference-coreference-scorers.v8.01.tar.gz + - Move `reference-coreference-scorers` into the folder `conll-2012/` and rename to `scorer` +- If you are using Python 3.X, you have to edit the `conll-2012/v3/scripts/skeleton2conll.py` file + - Change `except InvalidSexprException, e:` to `except InvalidSexprException as e` + - Change all `print` statements to `print()` +- Create the `*._conll` text files by executing + - `conll-2012/v3/scripts/skeleton2conll.sh -D path_to_ontonotes_folder/data/ conll-2012` (may take a little while) + - This will create `*.v4_gold_conll` files in each subdirectory of the `conll-2012` `data` folder. +- Assemble the appropriate files into one large file each for training, development and testing + - `my_lang` can be `english`, `arabic` or `chinese` + - `cat conll-2012/v4/data/train/data/my_lang/annotations/*/*/*/*.v4_gold_conll >> train.my_lang.v4_gold_conll` + - `cat conll-2012/v4/data/development/data/my_lang/annotations/*/*/*/*.v4_gold_conll >> dev.my_lang.v4_gold_conll` + - `cat conll-2012/v4/data/test/data/my_lang/annotations/*/*/*/*.v4_gold_conll >> test.my_lang.v4_gold_conll` + +## Prepare the data + +Once you have the set of `*.v4_gold_conll` files, move these files into separate (`train`, `test`, `dev`) subdirectories inside a new directory. You can use the already present `data` directory or create another directory anywhere you want. Now, you can prepare the training data by running +[conllparser.py](/neuralcoref/train/conllparser.py) on each split of the data set (`train`, `test`, `dev`) as + +```bash +python -m neuralcoref.train.conllparser --path ./$path_to_data_directory/train/ +python -m neuralcoref.train.conllparser --path ./$path_to_data_directory/test/ +python -m neuralcoref.train.conllparser --path ./$path_to_data_directory/dev/ +``` + +Conllparser will: + +- parse the `*._conll` files using spaCy, +- identify predicted mentions, +- compute the mentions features (see our blog post), and +- gather the mention features in a set of numpy arrays to be used as input for the neural net model. + +## Train the model + +Once the files have been pre-processed +(you should have a set of `*.npy` files in a sub-directory `/numpy` in each of your (`train`|`test`|`dev`) data folder), +you can start the training process using [learn.py](/neuralcoref/train/learn.py), for example as + +```bash +python -m neuralcoref.train.learn --train ./data/train/ --eval ./data/dev/ +``` + +There are many parameters and options for the training. You can list them with the usual + +```bash +python -m neuralcoref.train.learn --help +``` + +You can follow the training by running [Tensorboard for pyTorch](https://github.com/lanpa/tensorboard-pytorch) +(it requires a version of Tensorflow, any version will be fine). Run it with `tensorboard --logdir runs`. + +## Some details on the training + +The model and the training as thoroughfully described in our +[very detailed blog post](https://medium.com/huggingface/how-to-train-a-neural-coreference-model-neuralcoref-2-7bb30c1abdfe). +The training process is similar to the mention-ranking training described in +[Clark and Manning (2016)](http://cs.stanford.edu/people/kevclark/resources/clark-manning-emnlp2016-deep.pdf), namely: + +- A first step of training uses a standard cross entropy loss on the mention pair labels, +- A second step of training uses a cross entropy loss on the top pairs only, and +- A third step of training using a slack-rescaled ranking loss. + +With the default option, the training will switch from one step to the other as soon as the evaluation stop increasing. + +Traing the model with the default hyper-parameters reaches a test loss of about 61.2 which is lower than the mention ranking test loss of 64.7 reported in [Clark and Manning (2016)](http://cs.stanford.edu/people/kevclark/resources/clark-manning-emnlp2016-deep.pdf). + +Some possible explanations: + +- Our mention extraction function is a simple rule-based function (in [document.py](/document.py)) that was not extensively tuned on the CoNLL dataset and as a result only identifies about 90% of the gold mentions in the CoNLL-2012 dataset (see the evaluation at the start of the training) thereby reducing the maximum possible score. Manually tuning a mention identification module can be a lengthy process that basically involves designing a lot of heuristics to prune spurious mentions while keeping a high recall (see for example the [rule-based mention extraction used in CoreNLP](http://www.aclweb.org/anthology/D10-1048)). An alternative is to train an end-to-end identification module as used in the AllenAI coreference module but this is a lot more complex (you have to learn a pruning function) and the focus of the neuralcoref project is to have a coreference module with a good trade-off between accuracy and simplicity/speed. +- The hyper-parameters and the optimization procedure has not been fully tuned and it is likely possible to find better hyper-parameters and smarter ways to optimize. One possibility is to adjust the balance between the gradients backpropagated in the single-mention and the mentions-pair feedforward networks (see our [blog post](https://medium.com/huggingface/how-to-train-a-neural-coreference-model-neuralcoref-2-7bb30c1abdfe) for more details on the model architecture). Here again, we aimed for a balance between the accuracy and the training speed. As a result, the model trains in about 18h versus about a week for the original model of [Clark and Manning (2016)](http://cs.stanford.edu/people/kevclark/resources/clark-manning-emnlp2016-deep.pdf) and 2 days for the current state-of-the-art model of AllenAI. +- Again for the sake of high throughput, the parse tree output by the [standard English model](https://spacy.io/models/en#en_core_web_sm) of spaCy 2 (that we used for these tests) are slightly less accurate than the carefully tuned CoreNLP parse trees (but they are way faster to compute!) and will lead to a slightly higher percentage of wrong parsing annotations. +- Eventually, it may also be interesting to use newer word-vectors like [ELMo](https://arxiv.org/abs/1802.05365) as they were shown to be able to increase the state-or-the-art coreference model F1 test measure by more than 3 percents. + +## Train on a new language + +Training on a new language is now possible. However, do not expect it to be a plug-in operation as it involves finding a good annotated dataset and adapting the file-loading and mention-extraction functions to your file format and your language syntax (parse tree). + +To boot-strap your work, I detail here the general step you should follow: + +- Find a corpus with coreference annotations (as always, the bigger, the better). +- Check that spaCy [supports your language](https://spacy.io/models/) (i.e. is able to parse it). If not, you will have to find another parser that is able to parse your language and integrate it with the project (might involve quite large modifications to neuralcoref depending on the parser). +- Find a set of pre-trained word vectors in your language (gloVe or others). +- If your dataset does not follow the tabular `*_conll` file format (see [details on the CoNLL file format](http://conll.cemantix.org/2012/data.html) on the CoNLL website), you will have to tweak the `load_file` function in [conllparser.py](/conllparser.py) to adapt it to your file format. +- Adapt the mention extraction function to your language parse trees (`extract_mentions_spans` in [document.py](/document.py)) to reach an acceptable identification of mentions (the function should output the list of all possible mention in a document: pronouns, nouns, noun phrases and all the nested possible combinations). +- Re-train the model and tune the hyper-parameters. diff --git a/data_tooling/pii_processing/neuralcoref/train/training_requirements.txt b/data_tooling/pii_processing/neuralcoref/train/training_requirements.txt new file mode 100644 index 0000000..5a0b063 --- /dev/null +++ b/data_tooling/pii_processing/neuralcoref/train/training_requirements.txt @@ -0,0 +1,3 @@ +spacy +tensorboardX +torch>=1.3.0,<1.4.0 diff --git a/data_tooling/pii_processing/neuralcoref/train/utils.py b/data_tooling/pii_processing/neuralcoref/train/utils.py new file mode 100644 index 0000000..be6339c --- /dev/null +++ b/data_tooling/pii_processing/neuralcoref/train/utils.py @@ -0,0 +1,116 @@ +"""Utils""" + + +from concurrent.futures import ThreadPoolExecutor, as_completed +import os +import numpy as np +from tqdm import tqdm + +PACKAGE_DIRECTORY = os.path.dirname(os.path.abspath(__file__)) +BATCH_SIZE_PATH = os.path.join( + PACKAGE_DIRECTORY, "test_batch_size.txt" +) # fernandes.txt")# + +SIZE_SPAN = 250 # size of the span vector (averaged word embeddings) +SIZE_WORD = 8 # number of words in a mention (tuned embeddings) +SIZE_EMBEDDING = 50 # size of the words embeddings +SIZE_FP = 70 # number of features for a pair of mention +SIZE_FP_COMPRESSED = ( + 9 +) # size of the features for a pair of mentions as stored in numpy arrays +SIZE_FS = 24 # number of features of a single mention +SIZE_FS_COMPRESSED = 6 # size of the features for a mention as stored in numpy arrays +SIZE_GENRE = 7 # Size of the genre one-hot array +SIZE_MENTION_EMBEDDING = ( + SIZE_SPAN + SIZE_WORD * SIZE_EMBEDDING +) # A mention embeddings (span + words vectors) +SIZE_SNGL_FEATS = SIZE_FS - SIZE_GENRE +SIZE_PAIR_FEATS = SIZE_FP - SIZE_GENRE +SIZE_SNGL_IN_NO_GENRE = SIZE_MENTION_EMBEDDING + SIZE_SNGL_FEATS +SIZE_PAIR_IN_NO_GENRE = 2 * SIZE_MENTION_EMBEDDING + SIZE_PAIR_FEATS + +SIZE_PAIR_IN = ( + 2 * SIZE_MENTION_EMBEDDING + SIZE_FP +) # Input to the mentions pair neural network +SIZE_SINGLE_IN = ( + SIZE_MENTION_EMBEDDING + SIZE_FS +) # Input to the single mention neural network + +DISTANCE_BINS = list(range(5)) + [5] * 3 + [6] * 8 + [7] * 16 + [8] * 32 +BINS_NUM = float(len(DISTANCE_BINS)) +MAX_BINS = DISTANCE_BINS[-1] + 1 + + +def encode_distance(x): + """ Encode an integer or an array of integers as a (bined) one-hot numpy array """ + + def _encode_distance(d): + """ Encode an integer as a (bined) one-hot numpy array """ + dist_vect = np.zeros((11,), dtype="float32") + if d < 64: + dist_vect[DISTANCE_BINS[d]] = 1 + else: + dist_vect[9] = 1 + dist_vect[10] = min(float(d), BINS_NUM) / BINS_NUM + return dist_vect + + if isinstance(x, np.ndarray): + arr_l = [_encode_distance(y)[np.newaxis, :] for y in x] + out_arr = np.concatenate(arr_l) + else: + out_arr = _encode_distance(x) + return out_arr + + +def parallel_process(array, function, n_jobs=16, use_kwargs=False, front_num=10): + """ + A parallel version of the map function with a progress bar. + + Args: + array (array-like): An array to iterate over. + function (function): A python function to apply to the elements of array + n_jobs (int, default=16): The number of cores to use + use_kwargs (boolean, default=False): Whether to consider the elements of array as dictionaries of + keyword arguments to function + front_num (int, default=3): The number of iterations to run serially before kicking off the parallel job. + Useful for catching bugs + Returns: + [function(array[0]), function(array[1]), ...] + """ + # We run the first few iterations serially to catch bugs + if front_num > 0: + front = [ + function(**a) if use_kwargs else function(a) for a in array[:front_num] + ] + else: + front = [] + # If we set n_jobs to 1, just run a list comprehension. This is useful for benchmarking and debugging. + if n_jobs == 1: + return front + [ + function(**a) if use_kwargs else function(a) + for a in tqdm(array[front_num:]) + ] + # Assemble the workers + with ThreadPoolExecutor(max_workers=n_jobs) as pool: + # Pass the elements of array into function + if use_kwargs: + futures = [pool.submit(function, **a) for a in array[front_num:]] + else: + futures = [pool.submit(function, a) for a in array[front_num:]] + kwargs = { + "total": len(futures), + "unit": "it", + "unit_scale": True, + "leave": True, + } + # #Print out the progress as tasks complete + # for _ in tqdm(as_completed(futures), **kwargs): + # pass + out = [] + # Get the results from the futures. + for future in futures: # tqdm(futures): + try: + out.append(future.result()) + except Exception as e: + out.append(e) + return front + out diff --git a/data_tooling/pii_processing/neuralcoref/train/weights/pair_mentions_bias_layer_0.npy 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+ "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": {}, + "other_gender_swap": {}, + "en_pronoun2gender": { + "she": [ + "hine" + ] + }, + "en_pronoun2pronoun": {}, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/ab.json b/data_tooling/pii_processing/ontology/data/ab.json new file mode 100644 index 0000000..a59976f --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/ab.json @@ -0,0 +1,41 @@ +{ + "LOCATION": [ + "\u0443\u0430_\u043c\u0448\u044b_\u0431\u0437\u0438\u0430", + "\u0443\u0430_\u0445\u04d9\u044b\u043b\u0431\u0437\u0438\u0430" + ], + "JOB": [ + "\u0430\u043c\u0438\u043b\u0438\u0446\u0438\u0430" + ], + "PRODUCT": [ + "\u0443\u0430_\u0448\u044c\u044b\u0436\u044c\u044b_\u0431\u0437\u0438\u0430" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "\u0430\u0435\u04b3\u04d9\u0448\u044c\u0430": "\u0430\u0438\u0430\u0448\u044c\u0430", + "\u0430\u0525\u04b3\u04d9\u044b\u0441": "\u0430\u0525\u0448\u04d9\u043c\u0430", + "\u0430\u04b3\u04d9\u0441\u0430": "\u0430\u0445\u0430\u04b5\u0430", + "\u0430\u0447\u0430": "\u0430\u04a7\u04b3\u0259\u044b\u0437\u0431\u0430" + }, + "other_gender_swap": {}, + "en_pronoun2gender": { + "he": [ + "\u0430\u0447\u0430" + ], + "she": [ + "\u0430\u0525\u04b3\u04d9\u044b\u0441", + "\u0430\u04a7\u04b3\u0259\u044b\u0437\u0431\u0430" + ] + }, + "en_pronoun2pronoun": {}, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/abe.json b/data_tooling/pii_processing/ontology/data/abe.json new file mode 100644 index 0000000..c381cc7 --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/abe.json @@ -0,0 +1,39 @@ +{ + "PLANT": [ + "wachilmezi", + "pezagwdamenakwam", + "anaskemezi" + ], + "ANIMAL": [ + "anikwses", + "namakw", + "mamaska", + "chegwal" + ], + "GENDER": [ + "phanem" + ], + "LANGUAGE": [ + "alem\u00f4n" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": {}, + "other_gender_swap": {}, + "en_pronoun2gender": { + "she": [ + "phanem" + ] + }, + "en_pronoun2pronoun": {}, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/ady.json b/data_tooling/pii_processing/ontology/data/ady.json new file mode 100644 index 0000000..0bc3039 --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/ady.json @@ -0,0 +1,35 @@ +{ + "FOOD": [ + "\u0434\u0436\u044d\u0434\u044b\u043a\u04cf\u044d" + ], + "PERSON_PRONOUN": [ + "\u0432\u044b" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "\u043d\u044b": "\u0430\u0434\u044d", + "\u0448\u044b\u043f\u0445\u044a\u0443": "\u0448\u044b" + }, + "other_gender_swap": {}, + "en_pronoun2gender": { + "she": [ + "\u0431\u0437\u044b\u043b\u044a\u0444\u044b\u0433\u044a" + ] + }, + "en_pronoun2pronoun": { + "they": [ + "\u0430\u0445\u044d\u0440" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/af.json b/data_tooling/pii_processing/ontology/data/af.json new file mode 100644 index 0000000..4eeab22 --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/af.json @@ -0,0 +1,938 @@ +{ + "DISEASE": [ + "griep", + "gestremdheid", + "builepes", + "outisme", + "geestesteuring", + "hooikoors", + "als", + "schistosomiase", + "geelkoors", + "hondsdolheid", + "wen", + "aandoening", + "bloeding", + "pasteurellose", + "hartaanval", + "korsmos", + "distimie", + "hoogtevrees", + "witseerkeel", + "waterpokkies", + "borskanker", + "kinkhoes", + "persoonlikheidsteuring", + "poliomi\u00eblitis", + "katarak", + "verkluiming", + "ingewandskoors", + "suikersiekte", + "draaihalse", + "marteling", + "sonbrand", + "breakdown", + "longontsteking", + "pampoentjies", + "straling", + "verkoue", + "aarverkalking", + "gordelroos", + "masels", + "geelsug", + "talassemie", + "sting", + "breinvliesontsteking", + "sleep", + "jeuksiekte", + "kuberknippie", + "breek", + "runderpes", + "skildkliervergroting", + "materialisme", + "swangerskap", + "varkgriep", + "beroerte", + "middeloorontsteking", + "slenkdalkoors", + "brandmondsindroom", + "malaria", + "gangreen" + ], + "PLANT": [ + "denneboom", + "teestruik", + "geraamteplant", + "peper", + "brusselspruit", + "kraanvo\u00eblblom", + "mahonie", + "solanaceae", + "blomkool", + "kakaoboon", + "steranys", + "nogal", + "mosterd", + "rooihoutboom", + "trosvy", + "moeraseik", + "beet", + "gouewattel", + "grootnoemnoem", + "boontjie", + "rooibloekom", + "altviool", + "akkerwinde", + "wildetabak", + "swarthout", + "lork", + "peperboom", + "duifert", + "swartwattel", + "pruim", + "benede", + "swaardvaring", + "botterskorsie", + "witseebasboom", + "angelier", + "nastergal", + "geelhout", + "swartoognooi", + "patats", + "treurwilger", + "kersboom", + "kropslaai", + "kunstenaar", + "edelweiss", + "kemphaan", + "belladonna", + "bedeksadiges", + "blaarslaai", + "vaatplant", + "kapokboom", + "rubberplant", + "wilgerboom" + ], + "ANIMAL": [ + "kleingeelpootruiter", + "kleinwitreier", + "grootmalmok", + "bontfraiingpoot", + "grootwitreier", + "steenloper", + "rivierdolfyn", + "gewone_platanna", + "swartbekpylstormvo\u00ebl", + "zambezihaai", + "waterhond", + "grootflamink", + "toringvalk", + "jandorie", + "stormvo\u00ebltjies", + "rorkwal", + "moordvis", + "makriel", + "otter", + "hudsonbaaigriet", + "bontelsie", + "rooipootelsie", + "europese_swael", + "reier", + "dubbelsnip", + "wildehond", + "vlie\u00ebvangers", + "bultrugwalvis", + "koningsterretjie", + "tarentaal", + "monnikaasvo\u00ebl", + "krombekstrandloper", + "wielewaal", + "strandwolf", + "swerfvalk", + "moeraskat", + "grootswartooievaar", + "swartmarlyn", + "witooievaar", + "swartvlerkkoningalbatros", + "tierhaai", + "sandbankhaai", + "kleinbloureier", + "gryskoppie", + "ringnekpapegaai", + "swartwou", + "spoorvlerkkiewiet", + "sterretjies", + "hoender", + "nagtegaallyster", + "micropterus", + "grysfraiingpoot", + "leerskilpad", + "sekretarisvo\u00ebl", + "tierluislang", + "veereier", + "malkopby", + "baardspeg", + "dikkoppe", + "swartswaan", + "tortelduif", + "beekforel", + "amoedarja", + "kleindobbertjie", + "witwanggans", + "passer", + "koningblousysie", + "leeuwelpie", + "witrenoster", + "aasvo\u00ebl", + "grootbekbaars", + "rooinekswael", + "hottentotsgod", + "spikkelarendrog", + "geleedpotiges", + "accipiter", + "poolvos", + "strandjut", + "hottentotsgot", + "bruinjakkalsvo\u00ebl", + "baardwalvis", + "leeutjie", + "donkerhaai", + "hawik", + "swartrenoster", + "grootgrysmuishond", + "swartwitpens", + "lemoenduif", + "walvishaai", + "windswaels", + "swartkopmeeu", + "leeuwelp", + "maasbanker", + "iller", + "seemeeu", + "marten", + "roosspreeu", + "kleintandsaagvis", + "naguil", + "bergskilpad", + "mikstertmeeu", + "swarttiphaai", + "donkie", + "sabeldier", + "grootsterretjie", + "wildeposduif", + "brilpikkewyn", + "miskruier", + "bergkwagga", + "reuseluidier", + "trompetterswaan", + "reusenellie", + "swartnekdobbertjie", + "huismossie", + "grootwaterhoender", + "meeu", + "roetsterretjie", + "singswaan", + "bassiaan", + "bontkwagga", + "raaf", + "swaelstertstormswael", + "huisswael", + "bonttobie", + "edelhert", + "koningpikkewyn", + "meeue", + "reusesterretjie", + "peristediidae", + "grootgeelpootruiter", + "hertagtiges", + "platkopharder" + ], + "RELIGION_MEMBER": [ + "christene", + "protestant", + "mormon", + "broer" + ], + "PUBLIC_FIGURE": [ + "benjamin_franklin", + "akira_kurosawa", + "noah_webster", + "john_knox", + "heinrich_hertz", + "rudolf_steiner", + "che_guevara", + "c", + "maria_callas", + "henrik_ibsen", + "mary_shelley", + "david_livingstone", + "john_herschel", + "andrzej_wajda", + "balletdanseres", + "george_balanchine", + "douglas_macarthur", + "maria_magdalena", + "anna_pavlova", + "winston_churchill", + "terry_pratchett", + "stephen_king", + "francis_crick", + "isaac_newton", + "victor_hugo", + "joseph_smith", + "edwin_hubble", + "colette", + "jefferson_davis", + "john_glenn", + "richard_wagner", + "thornton_wilder", + "marie_curie", + "michael_jackson", + "carl_sandburg", + "thomas_hobbes", + "catharina_howard", + "galileo_galilei", + "robert_koch", + "joseph_goebbels", + "george_eastman", + "edmund_hillary", + "vincent_van_gogh", + "josef_stalin", + "john_ruskin", + "robert_burns", + "samuel_johnson", + "jesus", + "giuseppe_verdi", + "karl_jaspers", + "konrad_adenauer", + "frank_sinatra", + "abel_tasman", + "katharine_hepburn", + "henri_matisse", + "louis_pasteur", + "richard_strauss", + "theodosius_i", + "mahalia_jackson", + "saladin", + "sarah_bernhardt", + "t_s_eliot", + "sint_patrick", + "charles_de_gaulle", + "y", + "holden", + "charles_lindbergh", + "f", + "ludwig_wittgenstein", + "august_strindberg", + "thomas_mann", + "dante_alighieri", + "samuel_de_champlain", + "fridtjof_nansen", + "louis_braille", + "mungo_park", + "james_dean", + "roger_bannister", + "joseph_priestley", + "louis_joliet", + "joseph_pulitzer", + "oscar_wilde", + "philip_roth", + "piet_mondriaan", + "richard_trevithick", + "laurence_olivier", + "sint_laurensrivier", + "pete_seeger", + "joseph_heller", + "a", + "immanuel_kant", + "n", + "albert_schweitzer", + "titus", + "johannes_kepler", + "william_s_burroughs", + "max_planck", + "william_blake", + "t_e_lawrence", + "william_byrd", + "canberra", + "edward_jenner", + "margaret_mitchell", + "william_herschel", + "christophorus_columbus", + "niels_bohr", + "bertrand_russell", + "michael_faraday", + "rudolf_diesel", + "walt_disney", + "jane_austen", + "moses", + "gustav_mahler", + "robert_redford", + "richard_feynman", + "theodor_mommsen", + "marcel_proust", + "homo_heidelbergensis", + "elizabeth_taylor", + "pieter", + "william_golding", + "john_milton", + "indira_gandhi", + "jane_seymour", + "alfred_nobel", + "jesse_owens", + "marco_polo", + "caravaggio", + "m", + "allen_ginsberg", + "hans_christian_andersen", + "igor_strawinski", + "pablo_picasso", + "l_ron_hubbard", + "osman_i", + "christiaan_huygens", + "hector_berlioz", + "o", + "adam_smith", + "u", + "karl_marx", + "friedrich_nietzsche", + "i", + "sandro_botticelli", + "nikola_tesla", + "al_capone", + "billy_graham", + "robert_schumann", + "mel_gibson", + "le_corbusier", + "carlo_goldoni", + "john_locke", + "king_lear", + "henry_james", + "helen_keller", + "sint_maartin", + "walt_whitman", + "adolf_hitler", + "joseph_haydn", + "paul_revere", + "edvard_grieg", + "robert_boyle", + "alan_paton", + "1", + "rosa_parks", + "g", + "charles_coulomb", + "arthur_schopenhauer", + "windswaels", + "r", + "van_die_begin_af", + "george_lucas", + "andrew_jackson", + "louis_armstrong", + "steven_spielberg", + "robert_fulton", + "thomas_hardy", + "tanameer", + "bobby_fischer", + "johannes_gutenberg", + "andre", + "amerigo_vespucci", + "john_constable", + "robert_hooke", + "karl_popper", + "homo_rhodesiensis", + "peter_o'toole", + "joseph_conrad", + "peter_paul_rubens", + "mahatma_gandhi", + "jim_morrison", + "jules_verne", + "paul_newman", + "john_lennon", + "charlie_chaplin", + "john_brown", + "elizabeth_gaskell", + "kabelkar", + "johanna_van_arkel", + "hannah_arendt", + "bozen", + "stanley_kubrick", + "james_watt", + "ronald_reagan", + "homo", + "william_wordsworth", + "rex_harrison", + "woodrow_wilson", + "marcus_antonius", + "st_louis", + "ernest_hemingway", + "simon_petrus", + "aquila", + "nelson_mandela", + "roald_amundsen", + "charles_dickens", + "voltarivier", + "federico_fellini", + "francisco_pizarro", + "francisco_franco", + "andrew_carnegie", + "pontius_pilatus", + "franz_schubert", + "johnny_cash", + "georges_cuvier", + "walter_scott", + "staatshoof", + "robert_browning", + "walter_gropius", + "albert_einstein", + "thomas_edison", + "chiang_kai_shek", + "henry_purcell", + "t" + ], + "LANGUAGE": [ + "skaapooi", + "sjinese", + "ooi", + "deens", + "venda", + "arabies", + "frankoprovensaals", + "galicies", + "grieks", + "oerdoe", + "corsicaans", + "goedjarati", + "aksent", + "griekse", + "pali", + "manx", + "malayalam", + "japannees", + "hindi", + "esperanto", + "kelties", + "latyn", + "portugees", + "sweeds", + "maleis", + "ido", + "tonga", + "kannada" + ], + "JOB": [ + "sekonde", + "sweep", + "loodgieter", + "biskop", + "kapster", + "assistent", + "skeidsregter", + "hand", + "romanskrywer", + "internis", + "don", + "tandarts", + "tier", + "vertaalster", + "bestuurder", + "skrywer", + "beeldhouer", + "bakster", + "doelwagter", + "hooiwa", + "land", + "rehoboth_basters", + "broodwinner", + "wielmaker", + "koning", + "wetenskaplike", + "werktuigkundige", + "algemeen", + "blokfluit", + "haarkapper", + "voorsitter", + "ingenieur", + "the_guardian", + "der_vorleser", + "president", + "paramedikus", + "vlie\u00ebnier", + "agrari\u00ebr", + "herder", + "mate", + "raadgewer", + "hanger", + "skoonheidskundige", + "kolonel", + "vertaler", + "versamelaar", + "sersant", + "koopman", + "arbeider", + "sterrekundige", + "skrynwerker", + "inkoper", + "stuurman", + "argitek", + "koerier", + "bakker", + "man", + "berader", + "werker", + "handelaar", + "burgemeester", + "bankier", + "beroerte" + ], + "GPE": [ + "witgoud", + "menseregte", + "sint_laurensrivier", + "dar_es_salaam", + "withuis", + "rooisee", + "swartwoud", + "sint_maarten", + "bergpas", + "heilige_gees", + "s\u00e3o_tom\u00e9", + "gran_canaria", + "valentynsdag", + "aya_sophia", + "olimpiese_dorp", + "simon_petrus", + "la_rochelle", + "st_louis" + ], + "LAW": [ + "administratiefreg", + "strafreg", + "gemenereg", + "federal_bureau_of_investigation", + "inkomstestaat" + ], + "LOCATION": [ + "sint_maartin", + "hoofsaaklik", + "vsa", + "sint_helena", + "geelsee", + "sint_maarten", + "swartgat", + "kragsentrale", + "trois_rivi\u00e8res", + "telefoontjie", + "kanaaleilande", + "land", + "sakse_anhalt", + "sint_patrick", + "blue_mountains", + "lugmag", + "plesier", + "jordaanrivier", + "geelrivier", + "sint_maartenfees", + "swartkolk", + "usa", + "bowemeer", + "bloureier", + "hat_yai", + "arena", + "sri_lanka", + "edwardmeer", + "the_rolling_stones", + "tanameer", + "veral", + "michiganmeer", + "amerikaanse_le\u00ebr", + "swartsee" + ], + "PRODUCT": [ + "justin_bieber", + "stroombreker", + "cookeilande", + "diego_garcia", + "ghong", + "s\u00e3o_tom\u00e9_en_pr\u00edncipe", + "keisersnee", + "julius_caesar", + "hemelliggaam", + "heilige_gees", + "rosettasteen", + "nuwe_testament", + "slapskyf", + "menseregte", + "san_joaquin_rivier", + "kersboom", + "hooglied", + "by_die_grasie_gods", + "digitale_kamera", + "seinverwerking", + "musiekinstrument" + ], + "FAC": [ + "polisiestasie", + "winkelsentrum", + "poskantoor", + "pieter_i_van_rusland", + "laerskool", + "rooms_katolieke_kerk", + "die_laaste_avondmaal", + "hangbrug" + ], + "RELIGION": [ + "zen", + "calvinisme", + "islam", + "sjinto\u00efsme", + "wicca" + ], + "QUANTITY": [ + "si_stelsel", + "ses_en_twintig", + "drie_koninkryke", + "een_en_twintig", + "dollar", + "g", + "beaufortskaal", + "priemgetal", + "pond", + "pond_sterling" + ], + "ORG": [ + "wicca", + "jan_mayen", + "withuis", + "sint_helena", + "kategorie:motorbedryf", + "nasa", + "bollywood", + "fokof", + "schutzstaffel", + "bakkie", + "the_who", + "internasionale_geregshof", + "suidpool", + "san_francisco", + "wetenskapsfiksie", + "poskantoor", + "rooisee", + "swartmark", + "gao", + "laerskool", + "psigiatriese_hospitaal", + "amasonerivier", + "can_tho", + "wetenskapfiksie", + "don_juan", + "ai", + "volkebond", + "bowemeer", + "verligting", + "chiang_mai", + "staatsgreep", + "groot_beer", + "kaap_verde", + "sluikhandel", + "verdediging", + "rooi_kruis", + "vsa", + "botaniese_tuin", + "rabindranath_tagore", + "gestapo", + "winkelsentrum", + "baskeland", + "weermag", + "geelrivier", + "landbou", + "karmelberg", + "i_ching", + "onderwys", + "andromeda_sterrestelsel", + "vakbond", + "katolieke_kerk", + "seshonderd", + "po", + "oujaarsaand", + "knopiespinnekop", + "bevolkingsdigtheid", + "sterreswerm", + "saint_barth\u00e9lemy", + "nasionale_vergadering_van_die_republiek_van_azerbeidjan", + "los_angeles", + "brandweer", + "han_dinastie", + "my_naam_is", + "massamedia", + "welvaartstaat", + "mogolryk", + "duitse_keiserryk", + "stelselingenieurswese", + "uitverkorene", + "st_lucia", + "s\u00e3o_tom\u00e9", + "konserwatiewe_party" + ], + "UNION": [ + "itu", + "w\u00eareldposunie" + ], + "DATE": [ + "sint_patricksdag", + "goeie_vrydag", + "vadersdag", + "middeleeue", + "onafhanklikheidsdag", + "die_nagwag", + "skrikkeljaar", + "kanadadag", + "gregoriaanse_kalender", + "volmaan" + ], + "PERSON_PRONOUN": [ + "myself", + "i", + "my" + ], + "PERSON": [ + "julius_caesar", + "i_ching", + "igor_sikorsky", + "maxwell_anderson", + "rudolf_hess", + "jandorie" + ], + "SOC_ECO_CLASS": [ + "gemeenskap", + "swartmark", + "broederskap", + "samoerai", + "landbou", + "samelewing", + "bourgeoisie", + "sluikhandel" + ], + "FOOD": [ + "spookasem", + "kleinbekbaars", + "melkchocolade", + "roomys", + "witsous", + "piesangboot", + "tabascosous", + "slaptjips", + "esdoringstroop", + "vonkelwyn", + "paasei", + "rooiwyn", + "chili", + "tamatiesous", + "aartappelskyfies", + "woestyn", + "chile", + "middagete", + "witwyn", + "grondboontjiebotter", + "suiwelproduk", + "brandrissie", + "kruietee", + "kondesmelk", + "koeldrank" + ], + "ANAT": [ + "boarm" + ], + "POLITICAL_PARTY": [ + "arbeidersparty", + "party_van_die_arbeid", + "politieke_party", + "nazi_party", + "liberale_party", + "sosialistiese_party", + "nasionale_party" + ], + "GENDER": [ + "jongman", + "man", + "gal" + ], + "EVENT": [ + "golfoorlog" + ], + "POLITICAL_PARTY_MEMBER": [ + "makker" + ], + "RACE": [ + "fransman", + "nederlanders" + ], + "MEDICAL_THERAPY": [ + "skynwerklikheid" + ], + "TITLE": [ + "meneer" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "abdis": "abba", + "dogter": "son", + "kleindogter": "kleinseun", + "juffrou": "meneer", + "moeder": "vader", + "polisievrou": "polisieman", + "prinses": "regulus", + "reg": "koning", + "koningin": "koning", + "hetman": "indra", + "kak": "broer", + "suster": "broer", + "oujongnooi": "oujongkerel", + "vrou": "mees", + "wicca": "towenaar", + "heks": "towenaar", + "norn": "towenaar", + "jongman": "meisie", + "seun": "meisie", + "polonaise": "poets", + "poets": "polonaise" + }, + "other_gender_swap": {}, + "en_pronoun2gender": { + "he": [ + "mees", + "man", + "seun", + "little_boy", + "jongman" + ], + "she": [ + "maagd", + "vrou", + "juffrou", + "meisie", + "kak", + "gal" + ] + }, + "en_pronoun2pronoun": { + "he": [ + "hy", + "seine" + ], + "it": [ + "daardie", + "tyto" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/ain.json b/data_tooling/pii_processing/ontology/data/ain.json new file mode 100644 index 0000000..a18ff0a --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/ain.json @@ -0,0 +1,30 @@ +{ + "PLANT": [ + "atte", + "totonup" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "\u30cf\u30dd": "\u30a2\u30c1\u30e3", + "\u30b5\u30dd": "\u30e6\u30dd" + }, + "other_gender_swap": {}, + "en_pronoun2gender": { + "she": [ + "\u30e1\u30ce\u30b3", + "\u30b5\u30dd" + ] + }, + "en_pronoun2pronoun": {}, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/akk.json b/data_tooling/pii_processing/ontology/data/akk.json new file mode 100644 index 0000000..49eec08 --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/akk.json @@ -0,0 +1,37 @@ +{ + "PUBLIC_FIGURE": [ + "\ud808\udc00\ud808\ude3e\ud808\uddaa" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "ummu": "\ud808\udc1c\ud808\udeeb", + "\ud808\udf1d\ud808\ude2c": "\ud808\udc1c", + "\ud808\udea9\ud808\udf06": "\ud808\udec0" + }, + "other_gender_swap": {}, + "en_pronoun2gender": { + "he": [ + "\ud808\udd97" + ], + "she": [ + "\ud808\udea9", + "\ud808\udea9\ud808\udf06" + ] + }, + "en_pronoun2pronoun": { + "he": [ + "\ud808\uded7" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/akz.json b/data_tooling/pii_processing/ontology/data/akz.json new file mode 100644 index 0000000..2b6514a --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/akz.json @@ -0,0 +1,44 @@ +{ + "FOOD": [ + "assikch\u00eclpa" + ], + "PERSON_PRONOUN": [ + "oki" + ], + "ANIMAL": [ + "iskanpatha" + ], + "PLANT": [ + "assikchi_laana" + ], + "GENDER": [ + "tayyi" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": {}, + "other_gender_swap": {}, + "en_pronoun2gender": { + "she": [ + "tayyi" + ] + }, + "en_pronoun2pronoun": { + "he": [ + "oki" + ], + "she": [ + "oki" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/alt.json b/data_tooling/pii_processing/ontology/data/alt.json new file mode 100644 index 0000000..5aec9b5 --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/alt.json @@ -0,0 +1,61 @@ +{ + "PERSON_PRONOUN": [ + "\u043c\u0435\u043d\u0438\u04a5", + "\u043e\u043b" + ], + "ANIMAL": [ + "\u0431\u0430\u043a\u0430" + ], + "PLANT": [ + 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a/data_tooling/pii_processing/ontology/data/arn.json b/data_tooling/pii_processing/ontology/data/arn.json new file mode 100644 index 0000000..0489a78 --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/arn.json @@ -0,0 +1,34 @@ +{ + "DISEASE": [ + "trekef\u00fcn" + ], + "GENDER": [ + "jike" + ], + "LANGUAGE": [ + "kechuadungun" + ], + "PLANT": [ + "calfuray" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": {}, + "other_gender_swap": {}, + "en_pronoun2gender": { + "she": [ + "jike" + ] + }, + "en_pronoun2pronoun": {}, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/ast.json b/data_tooling/pii_processing/ontology/data/ast.json new file mode 100644 index 0000000..31413f7 --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/ast.json @@ -0,0 +1,473 @@ +{ + "PUBLIC_FIGURE": [ + "henry_cavendish", + "akira_kurosawa", + "giovanni_boccaccio", + "henrik_ibsen", + "peter_lorre", + "mary_wollstonecraft", + "winston_churchill", + "pedru", + "paul_mccartney", + "isaac_newton", + "victor_hugo", + "joseph_smith", + "edwin_hubble", + "salad\u00edn", + "bakunin", + "george_orwell", + "richard_wagner", + "marie_curie", + "michael_jackson", + "galileo_galilei", + "jane_goodall", + "joseph_goebbels", + "edmund_hillary", + "vincent_van_gogh", + "liliuokalani", + "yuri_gagarin", + "charles_chaplin", + "giuseppe_verdi", + "frank_sinatra", + "henri_matisse", + "don_quixote_de_la_mancha", + "john_ford", + "sarah_bernhardt", + "luigi_pirandello", + "dorothea_lange", + "charles_de_gaulle", + "paul_von_hindenburg", + "y", + "f", + "thomas_mann", + "dante_alighieri", + "peter_pan", + "giacomo_puccini", + "paul_verlaine", + "oscar_wilde", + "philip_roth", + "adolf_eichmann", + "xerez", + 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"amerigo_vespucci", + "putin", + "peter_o'toole", + "joseph_conrad", + "peter_paul_rubens", + "jim_morrison", + "jules_verne", + "john_lennon", + "stanley_kubrick", + "james_watt", + "ronald_reagan", + "martin_luther_king", + "william_wordsworth", + "don_quixote", + "ernest_hemingway", + "nelson_mandela", + "al_gore", + "mohandas_gandhi", + "roald_amundsen", + "charles_dickens", + "jacques_offenbach", + "francisco_pizarro", + "francisco_franco", + "johnny_cash", + "joseph_mccarthy", + "albert_einstein", + "t", + "sordomudu" + ], + "DISEASE": [ + "peste_bub\u00f3nica", + "tatexu", + "tatexar", + "belleya", + "bermeyura", + "relluezu", + "espirriar", + "llandra", + "sipu", + "herpe", + "estornudar", + "tartayar", + "qi", + "atartayar", + "gimp", + "sollutu", + "pica", + "quemadura", + "esperr\u00edu", + "zumu", + "tartayu", + "casta\u00f1u", + "embaranzu", + "llepra", + "malaria" + ], + "PRODUCT": [ + "justin_bieber", + "arcu_de_trunfu", + "imperiu_romanu", + "don_quixote", + "cobaya", + "the_lord_of_the_rings", + "la_divina_comedia", + "mario_andretti", + "s\u00e3o_tom\u00e9_y_pr\u00edncipe" + ], + "JOB": [ + "obispu", + "siquiatra", + "obreru", + "balleneru", + "mensaxeru", + "corsariu", + "compositor", + "carpintera", + "baillador", + "panaderu", + "kamikaze", + "novelista", + "ceruxanu", + "marineru", + "falante", + "mate", + "pastor", + "orinar", + "aguar\u00f3n", + "corporal", + "cocedor", + "granxera", + "granxeru", + "carpinteru", + "principal", + "bomberu", + "segundu", + "baillar\u00edn", + "mar\u00edn", + "esclavu", + "xastre", + "coleicionista", + "llecheru", + "autor" + ], + "ORG": [ + "san_jos\u00e9", + "arma_blanca", + "jan_mayen", + "nasa", + "europol", + "the_who", + "san_francisco", + "un", + "a_poco_a_poco", + "gobiernu", + "el_gordu_y_el_flacu", + "planches", + "visnuismu", + "mar_bermeya", + "part\u00edu_dem\u00f3crata_de_los_estaos_xun\u00edos", + "cabu_verde", + "drechu_civil", + "po", + "los_angeles", + "sindicatu", + "fuerza_a\u00e9reo", + "escuela", + "part\u00edu_republicanu_de_los_estaos_xun\u00edos", + "comerciu", + "sietestrellu" + ], + "RELIGION": [ + "zen", + "catarismu", + "islam", + "sinto\u00edsmu", + "tao\u00edsmu" + ], + "RELIGION_MEMBER": [ + "budista", + "hermanu", + "franciscanu" + ], + "PLANT": [ + "llamera", + "ortiga", + "helianthus_annuus", + "zanahoria", + "taxus_baccata", + "salce", + "axenxu", + "miru\u00e9ndanu", + "mirasol", + "ciruela", + "pinu", + "muscicapa_striata", + "repollu", + "urtiga", + "mostaza", + "beta_vulgaris", + "casta\u00f1u", + "cereza", + "castanea", + "salgueru", + "cenahoria", + "cirig\u00fceyu" + ], + "ANIMAL": [ + "xibarte", + "esguilu", + "utre", + "cobaya", + "sitta_europaea", + "llince", + "kunduz", + "esquilu", + "manta", + "escalag\u00fcertu", + "sitta_carolinensis", + "mantodea", + "vacalloria", + "homo_sapiens", + "frang\u00fcesu", + "pollu", + "melandru", + "estorn\u00edn", + "verriacu", + "cucaracha", + "taforru", + "sable", + "equinoidea", + "arthropoda", + "verracu", + "falc\u00f3n", + "lince", + "sitta_canadensis", + "mantis", + "furaga\u00f1a", + "curuxa", + "gurri\u00f3n", + "ferre", + "cuervu" + ], + "LANGUAGE": [ + "alem\u00e1n", + "xapon\u00e9s", + "griega", + "ar\u00e1bicu", + "catal\u00e1n", + "griegu", + "manx", + "esperantu", + "tailand\u00e9s", + "hindi", + "vascu", + "faladera", + "ar\u00e1bigu", + "ido", + "llat\u00edn", + "tonga" + ], + "FOOD": [ + "daucus_carota", + "farina", + "chile", + "gasiosa", + "desiertu", + "llacteu" + ], + "LOCATION": [ + "mar_negru", + "mar_del_norte", + "de_nada", + "estaos_un\u00edos", + "crist\u00f3balo_col\u00f3n", + "cabu_d_hornos", + "saint_lucia", + "almaaz", + "arena", + "sri_lanka", + "the_rolling_stones", + "campu" + ], + "PERSON": [ + "al_gore", + "rudolf_hess", + "herbert_george_wells" + ], + "RACE": [ + "tagalu", + "francesa", + "africanu" + ], + "FAC": [ + "a_poco_a_poco", + "plaza", + "saint_lucia", + "pedru_i_de_rusia", + "ilesia_cat\u00f3lica" + ], + "PERSON_PRONOUN": [ + "vosotres", + "i", + "de_so", + "de_to", + "me", + "vosotros", + "nosotros", + "tutiar", + "nosotras" + ], + "GENDER": [ + "var\u00f3n" + ], + "SOC_ECO_CLASS": [ + "socied\u00e1", + "fraternid\u00e1", + "samur\u00e1i" + ], + "GPE": [ + "imperiu_alem\u00e1n", + "nuevu_testamentu", + "ap\u00f3stol_san_pedru", + "mar_bermeya", + "mar_ex\u00e9u", + "esp\u00edritu_santu" + ], + "QUANTITY": [ + "quilopondiu", + "quinientos", + "g", + "anders_celsius" + ], + "POLITICAL_PARTY": [ + "partido_popular", + "part\u00edu_pol\u00edticu", + "part\u00edu_social_dem\u00f3crata", + "part\u00edu_comunista" + ], + "EVENT": [ + "castiella_y_lle\u00f3n" + ], + "UNION": [ + "sindicatu" + ], + "DATE": [ + "natalid\u00e1" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "abadesa": "ab\u00e1", + "baronesa": "bar\u00f3n", + "nieta": "nietu", + "\u00f1eta": "nietu", + "monxa": "monxu", + "nun": "monxu", + "pr\u00edncipe": "el_pr\u00edncipe", + "andada": "fiastru", + "fiastra": "fiastru", + "madrastra": "padrastru", + "madrasta": "padrastru", + "muyer": "var\u00f3n", + "esposa": "esposu", + "bruxa": "bruxu", + "norn": "bruxu", + "nisu": "var\u00f3n", + "ne\u00f1u": "\u00f1ena", + "var\u00f3n": "ne\u00f1a" + }, + "other_gender_swap": { + "elli": "ellos" + }, + "en_pronoun2gender": { + "he": [ + "ariar", + "var\u00f3n", + "ne\u00f1u" + ], + "she": [ + "\u00f1ena", + "ne\u00f1a", + "muyer", + "nisu" + ] + }, + "en_pronoun2pronoun": { + "he": [ + "elli" + ], + "they": [ + "ellos", + "elles" + ], + "it": [ + "esta", + "esti" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/av.json b/data_tooling/pii_processing/ontology/data/av.json new file mode 100644 index 0000000..e7985d5 --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/av.json @@ -0,0 +1,28 @@ +{ + "PLANT": [ + "\u043b\u0430\u043c\u0430\u0434\u0443\u0440" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "\u044d\u0431\u0435\u043b": "\u044d\u043c\u0435\u043d", + "\u0431\u0443\u0431\u0430": "\u044d\u043c\u0435\u043d" + }, + "other_gender_swap": {}, + "en_pronoun2gender": { + "she": [ + "\u044f\u0441" + ] + }, + "en_pronoun2pronoun": {}, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/az.json b/data_tooling/pii_processing/ontology/data/az.json new file mode 100644 index 0000000..d53f104 --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/az.json @@ -0,0 +1,687 @@ +{ + "LOCATION": [ + "al_jazeera", + "\u0131_osman", + "sina_da\u011f\u0131", + "\u00e7ox_raz\u0131yam", + "hertoqenbos", + "saksoniya_anhalt", + "il_de_frans", + "sen_vinsent", + "taz\u0131lar", + "hind_okean\u0131", + "\u00e7ox_raz\u0131jam", + "yuxar\u0131_g\u00f6l", + "xuanxe", + "univermaq", + "m\u0259rk\u0259zi_bank", + "la_man\u015f", + "konservatoriya", + "ab\u015f", + "santa_klaus", + "krivoy_roq", + "az\u0259rbaycan_respublikas\u0131n\u0131n_milli_m\u0259clisi", + "yeni_d\u00fcnya", + "ruhi_x\u0259st\u0259xana", + "trifolium_dubium" + ], + "ORG": [ + "dominion", + "alt\u0131_y\u00fcz", + "\u00fc\u00e7_bac\u0131", + "nasa", + "daosizm", + "nasional_sosialist_alman_f\u0259hl\u0259_partiyas\u0131", + "un", + "xuanxe", + "q\u0131rm\u0131z\u0131_xa\u00e7", + "hertoqenbos", + "\u0645\u0646_\u0633\u0646\u06cc_\u0633\u0648\u06cc\u0631\u0645", + "siyasi_partiya", + "kabo_verde", + "b\u00f6y\u00fck_ay\u0131", + "ab\u015f_demokrat_partiyas\u0131", + "katolik_kils\u0259si", + "don_juan", + "qaradul", + "the_new_school", + "kollec", + "zeytun_da\u011f\u0131", + "masonluq", + "benil\u00fcks", + "m\u00fcq\u0259dd\u0259s_yelena_adas\u0131", + "hava_q\u00fcvv\u0259l\u0259ri", + "san_tome", + "gestapo", + "konservatoriya", + "han_s\u00fclal\u0259si", + "al_jazeera", + "maarif", + "bollivud", + "g\u00f6mr\u00fck", + "mossad", + "az\u0259rbaycan_sosial_demokrat_partiyas\u0131", + "elml\u0259r_akademiyas\u0131", + "beyn\u0259lxalq_telekomunikasiya_ittifaq\u0131", + "po_\u00e7ay\u0131", + "min_s\u00fclal\u0259si", + "nato", + "a\u011f_ev", + "sayentologiya", + "leyboristl\u0259r_partiyas\u0131", + "by_the_way", + "federal_t\u0259hqiqat_b\u00fcrosu", + "\u0259kin\u00e7ilik", + "botanika_ba\u011f\u0131", + "vinni_pux", + "m\u00fchafiz\u0259karlar_partiyas\u0131", + "g\u00f6mr\u00fckxana", + "saqq\u0131z", + "qaraqurd" + ], + "DISEASE": [ + "buruqboyun", + "appendisit", + "qanaxma", + "stenokardiya", + "xolangit", + "yuxusuzluq", + "\u015fabal\u0131d", + "malyariya", + "istilik", + "demensiya", + "iltihab", + "yuxu", + "sirroz", + "progeriya", + "beri_beri", + "katarakta", + "plevrit", + "konyunktivit", + "talassemiya", + "sosiofobiya", + "materializm", + "qastrit", + "smart", + "addiksiya", + "deliriya", + "rubella", + "susuzluq", + "dumanl\u0131q", + "ziyil", + "q\u0131z\u0131lca", + "aura", + "hamil\u0259lik", + "fuqa", + "lyambliyoz", + "arboviruslar", + "ziyan", + "pellaqra", + "qarayara", + "ishal" + ], + "PERSON_PRONOUN": [ + "\u0131" + ], + "ANIMAL": [ + "maral_b\u00f6c\u0259yi", + "bildir\u00e7in\u00e7alan", + "qaratoyuqlar", + "tetralar", + "uzunqanadlar", + "heron", + "yeng\u0259cyey\u0259n", + "marallar", + "karabidl\u0259r", + "adi_me\u015f\u0259\u00f6rd\u0259yi", + "qaradul", + "berqut", + "su_si\u00e7ovulu", + "tarakankimil\u0259r", + "carduelis", + "al_\u0259lvan_q\u0131z\u0131lxall\u0131", + "avropa_t\u00fcviyi", + "mil\u00e7\u0259kqapanlar", + "lavrak", + "baribal", + "sincab", + "aktinil\u0259r", + "susamuru", + "prunus_tenella", + "erektus", + "cyclopedidae", + "sincablar", + "quruburun", + "lemminq", + "\u015fahin", + "m\u0259rcan", + "qara_dul", + "yarpaqyey\u0259nl\u0259r", + "moryanka", + "porsuq", + "qaraqurd", + "panqasius", + "tarakan", + "and_q\u0131z\u0131lqaz\u0131", + "sincabaox\u015far", + "and_kondoru", + "almaqurdu", + "k\u0259nd_qaranqu\u015fu", + "\u0259r\u0259bdov\u015fan\u0131" + ], + "PLANT": [ + "mahonia", + "salvia_leucophylla", + "berqamot", + "veronica_beccabunga", + "quercus_coccinea", + "viola_reichenbachiana", + "rosa_chinensis", + "lathyrus_latifolius", + "monarda_citriodora", + "quercus_kelloggii", + "amelanchier_bartramiana", + "aylant", + "qara\u011fac", + "maqnoliya", + "monarda", + "sorbus_torminalis", + "liparis_loeselii", + "papaver_alpinum", + "hydrangea_petiolaris", + "prunus_laurocerasus", + "passiflora_ligularis", + "atriplex_hortensis", + "danaaya\u011f\u0131", + "teucrium_scorodonia", + "su_nan\u0259si", + "arctostaphylos_alpina", + "acacia_pycnantha", + "sakura", + "rhus_typhina", + "euphorbia_dentata", + "ranunculus_ficaria", + "yulafca", + "senna_alata", + "qaraqovaq", + "calophyllum_inophyllum", + "rosa_multiflora", + "yadda\u015f\u00e7i\u00e7\u0259yi", + "naringi", + "salix_viminalis", + "veronica_serpyllifolia", + "quercus_ellipsoidalis", + "veronica_peregrina", + "chaenomeles_speciosa", + "nymphaea_odorata", + "artemisia_cana", + "milad_a\u011fac\u0131", + "salix_fragilis", + "inci\u00e7i\u00e7\u0259yi", + "hedysarum_coronarium", + "draba_verna", + "kaprifol", + "gilas", + "cotoneaster_horizontalis", + "viburnum_prunifolium", + "at_paxlas\u0131", + "euphorbia_cyparissias", + "katexu_palmas\u0131", + "albal\u0131", + "eugenia_uniflora", + "blackberry", + "gaval\u0131", + "ballota_nigra", + "lotus_corniculatus", + "hydrangea_arborescens", + "raphanus_raphanistrum", + "q\u0131z\u0131la\u011fac", + "salix_pentandra", + "rubus_spectabilis", + "crataegus_laevigata", + "ilanba\u015f\u0131", + "ranunculus_bulbosus", + "arenaria_serpyllifolia", + "ball\u0131nan\u0259", + "crataegus_aestivalis", + "lathyrus_sylvestris", + "rosa_moschata", + "salvia_farinacea", + "aralia_stipulata", + "mentha_longifolia", + "adi_canavargil\u0259si", + "pyrola_rotundifolia", + "hypericum_calycinum", + "hypericum_maculatum", + "quayyava", + "cypripedium_montanum", + "al_q\u0131rm\u0131z\u0131_yonca", + "pinus_muricata", + "lathyrus_sativus", + "veronica_arvensis", + "belladonna", + "pirakanta", + "cephalanthera_rubra", + "rosa_banksiae", + "adi_q\u0131z\u0131la\u011fac", + "at_\u015fabal\u0131d\u0131", + "rubus_odoratus", + "ranunculus_aquatilis", + "pinus_palustris", + "mahonia_nervosa", + "ranunculus_acris", + "cypripedium_reginae", + "betula_papyrifera", + "solanum_quitoense" + ], + "PUBLIC_FIGURE": [ + "bill_klinton", + "henri_hudzon", + "sandro_boti\u00e7elli", + "federiko_fellini", + "c", + "valentina_tere\u015fkova", + "henrix_himmler", + "con_dalton", + "mark_antoni", + "henrik_ibsen", + "emma_noter", + "con_edqar_quver", + "v_georq", + "ivan_pavlov", + "hans_xristian_andersen", + "tomas_tallis", + "con_ford", + "m\u0259n", + "nits\u015fe", + "con_raskin", + "david", + "frans_klayn", + "le_korbuzye", + "emiliano_zapata", + "con_milton", + "con_qolsuorsi", + "s\u0259kkiz_yar\u0131m", + "konrad_adenauer", + "mariya_maqdalena", + "lui_paster", + "frans_\u015fubert", + "abel_tasman", + "pedro_rodriguez", + "allen_qinzberq", + "ameriqo_vespu\u00e7\u00e7i", + "con_drayden", + "con_st\u00fcart_mill", + "akira_kurosava", + "\u0131_kserks", + "con_braun", + "y", + "f", + "don_kixot", + "albert_\u015fpeer", + "con_rokfeller", + "q", + "con_lennon", + "hal", + "dante_aligyeri", + "henrix_hers", + "con_lokk", + "con_pirpont_morqan", + "con_bardin", + "mariya_kallas", + "karl_yaspers", + "konstantin_stanislavski", + "fransisko_pizarro", + "immanuel_kant", + "jozef_g\u00f6bbels", + "giulio_natta", + "bob_vudvord", + "sergey_raxmaninov", + "el_qreko", + "bertran_rassel", + "lui_armstronq", + "roman_yakobson", + "artur_\u015fopenhauer", + "al_kapone", + "\u0131_feodosi", + "frityof_nansen", + "henrix_\u015fliman", + "ben_conson", + "yuri_qaqarin", + "robert_redford", + "li_harvi_osvald", + "con_nepyer", + "erik_karlfeldt", + "karavacco", + "con_konstebl", + "samuel_adams", + "con_steynbek", + "alfred_nobel", + "\u0131_yustinian", + "karl\u0131q", + "m\u0259cd\u0259lli_m\u0259ry\u0259m", + "boris_karloff", + "anders_selsi", + "leonard_eyler", + "ameliya_erhart", + "bethoven", + "o", + "daniil_bernulli", + "nikola_tesla", + "mel_gibson", + "robert_berns", + "robert_piri", + "con_uilks_but", + "helen_keller", + "anna_kurnikova", + "\u0131", + "indira_qandi", + "\u0131_dara", + "yaqub", + "adolf_hitler", + "tomas_maltus", + "alesandro_manzoni", + "1", + "aloiz_zenefelder", + "con_singer_sargent", + "david_rikardo", + "vladimir_putin", + "\u0131_osman", + "sultan_\u015fahcahan", + "\u0131_xlodviq", + "g", + "sara_bernar", + "r", + "robert_fulton", + "con_meynard_keyns", + "mariya_mit\u00e7ell", + "karl_sandberq", + "mariya_antuanetta", + "putin", + "ella_fitscerald", + "karl_popper", + "cordano_bruno", + "edmund_halley", + "robert_stevenson", + "andrea_palladio", + "marko_polo", + "van_qoq", + "robert_broun", + "con_ceyms_od\u00fcbon", + "robert_haynlayn", + "enn_heteuey", + "briqadir", + "boris_spasski", + "antonio_stradivari", + "m\u00fcq\u0259dd\u0259s_pyotr", + "herbert_uells", + "h\u00fcseyn", + "luis_brayl", + "david_hilbert", + "bernardo_bertolu\u00e7\u00e7i", + "emma_qoldman", + "\u0131_konstantin", + "nelson_mandela", + "frederik_duqlas", + "o_henri", + "con_fon_neyman", + "fred_aster", + "con_ross", + "vladimir_lenin", + "xristofor_kolumb", + "uzunqanadlar", + "\u0131_pyotr", + "robert_skott", + "nikolay_kopernik", + "s\u00fcleysin", + "t" + ], + "JOB": [ + "qubernator", + "\u00e7oban", + "paltaryuyan", + "kitabxana\u00e7\u0131", + "zabit", + "kral", + "don", + "pretor", + "polkovnik", + "hakim", + "printer", + "mayor", + "the_guardian", + "qasid", + "menecer", + 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b/data_tooling/pii_processing/ontology/data/bal.json new file mode 100644 index 0000000..4f04fbd --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/bal.json @@ -0,0 +1,34 @@ +{ + "ANIMAL": [ + "\u062a\u0648\u0644\u0627\u06af" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "\u0645\u0627\u0633": "\u0627\u0628\u0627", + "\u06af\u0648\u06c1\u0627\u0631": "\u0628\u0631\u0627\u062a", + "\u06af\u06c1\u0627\u0631": "\u0628\u0631\u0627\u062a", + "\u0648\u0627\u0631\u06a9": "\u0628\u0631\u0627\u062a", + "\u06a9\u0648\u0631": "\u062c\u0646\u06a9" + }, + "other_gender_swap": {}, + "en_pronoun2gender": { + "he": [ + "\u06a9\u0648\u0631" + ], + "she": [ + "\u062c\u0646\u06a9" + ] + }, + "en_pronoun2pronoun": {}, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/be.json b/data_tooling/pii_processing/ontology/data/be.json new file mode 100644 index 0000000..2ef9618 --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/be.json @@ -0,0 +1,425 @@ +{ + "RACE": [ + "\u0442\u0443\u0440\u0430\u043a", + "\u0430\u0444\u0440\u044b\u043a\u0430\u043d\u0441\u043a\u0456", + "\u044f\u0443\u0440\u044d\u0439\u0441\u043a\u0456", + "\u0435\u0443\u0440\u0430\u043f\u0435\u0439\u0441\u043a\u0456", + "\u043f\u0430\u043b\u0456\u043d\u0435\u0437\u0456\u0439\u0441\u043a\u0456", + "\u0433\u0430\u043b\u0430\u043d\u0434\u0446\u044b", + "\u0433\u0430\u0431\u0440\u044d\u0439\u0441\u043a\u0456" + ], + "DATE": [ + "\u0441\u0442\u0430\u0440\u0430\u0441\u0446\u044c", + "\u043c\u0430\u043b\u0430\u0434\u0437\u0456\u043a" + ], + "ORG": [ + "\u0437\u0435\u043c\u043b\u044f\u0440\u043e\u0431\u0441\u0442\u0432\u0430", + "\u043c\u0430\u043b\u0430\u0434\u0437\u0456\u043a", + 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"\u0431\u0440\u0430\u0442", + "\u0441\u0442\u0430\u0440\u0430\u044f_\u0434\u0437\u0435\u0432\u0430": "\u0445\u0430\u043b\u0430\u0441\u0446\u044f\u043a", + "\u043f\u0430\u0434\u0447\u0430\u0440\u043a\u0430": "\u043f\u0430\u0441\u044b\u043d\u0430\u043a", + "\u043f\u0430\u0441\u0435\u0440\u0431\u043a\u0430": "\u043f\u0430\u0441\u0435\u0440\u0431", + "\u043c\u0430\u0447\u0430\u0445\u0430": "\u0430\u0439\u0447\u044b\u043c", + "\u0443\u0434\u0430\u0432\u0430": "\u0443\u0434\u0430\u0432\u0435\u0446", + "\u0436\u043e\u043d\u043a\u0430": "\u043c\u043e\u0439", + "\u0430\u043b\u043c\u0430\u0437": "\u0447\u0430\u0440\u0430\u0443\u043d\u0456\u043a", + "\u0432\u0435\u0434\u0437\u044c\u043c\u0430": "\u0447\u0430\u0440\u0430\u0443\u043d\u0456\u043a", + "\u0436\u0430\u043d\u0447\u044b\u043d\u0430": "\u043c\u0443\u0436\u0447\u044b\u043d\u0430", + "\u0436\u0430\u043d\u0430": "\u043c\u0443\u0436\u0447\u044b\u043d\u0430", + "\u0445\u043b\u043e\u043f\u0447\u044b\u043a": "\u043c\u043e\u043c\u0430", + "\u0445\u043b\u043e\u043f\u0435\u0446": "\u043c\u043e\u043c\u0430" + }, + "other_gender_swap": { + "\u0456\u0445": "\u044f\u0435", + "\u044f\u043d\u044b": "\u044f\u043d\u0430", + "\u0451\u043d": "\u044f\u043d\u044b", + "\u044f\u043c\u0443": "\u0456\u0445", + "\u044f\u0433\u043e": "\u0456\u0445", + "\u044f\u0433\u043e\u043d\u044b": "\u0456\u0445", + "\u044f\u043d\u0430": "\u044f\u043d\u044b", + "\u0435\u0439\u043d\u044b": "\u0456\u0445", + "\u044f\u0435": "\u0456\u0445" + }, + "en_pronoun2gender": { + "they": [ + "\u0433\u0430\u043c\u0430\u0441\u0435\u043a\u0441\u0443\u0430\u043b\u044c\u043d\u044b", + "\u0433\u043e\u043c\u0430\u0441\u0435\u043a\u0441\u0443\u0430\u043b\u044c\u043d\u044b" + ], + "he": [ + "\u0445\u043b\u043e\u043f\u0435\u0446", + "\u043c\u0443\u0436\u0447\u044b\u043d\u0430", + "\u0445\u043b\u043e\u043f\u0447\u044b\u043a", + "\u043c\u0443\u0436\u0447\u044b\u043d\u0441\u043a\u0456", + "\u043a\u0435\u043d\u0442", + "\u0433\u0430\u0439" + ], + "she": [ + "\u0434\u0437\u0435\u0432\u0430", + "\u0436\u0430\u043d\u0447\u044b\u043d\u0430", + "\u043f\u0430\u043d\u043d\u0430", + "\u0434\u0437\u044f\u0443\u0447\u044b\u043d\u0430", + "\u043c\u043e\u043c\u0430", + "\u0441\u043f\u0430\u0434\u0430\u0440\u044b\u0447\u043d\u0430", + "\u0436\u0430\u043d\u043e\u0447\u044b", + "\u0436\u0430\u043d\u0430", + "\u043f\u0430\u043d\u0456", + "\u0441\u043f\u0430\u0434\u0430\u0440\u044b\u043d\u044f", + "\u0434\u0437\u044f\u0443\u0447\u044b\u043d\u043a\u0430", + "\u0434\u0437\u044f\u045e\u0447\u044b\u043d\u043a\u0430" + ] + }, + "en_pronoun2pronoun": { + "he": [ + "\u044f\u0433\u043e\u043d\u044b", + "\u044f\u0433\u043e", + "\u0451\u043d", + "\u044f\u043c\u0443" + ], + "she": [ + "\u044f\u043d\u0430", + "\u0435\u0439\u043d\u044b", + "\u044f\u0435" + ], + "they": [ + "\u0456\u0445", + "\u044f\u043d\u044b" + ], + "it": [ + "\u0433\u044d\u0442\u0430", + "\u0433\u044d\u0442\u044b\u044f", + "\u0433\u044d\u0442\u0430\u044f", + "\u044f\u0433\u043e\u043d\u044b", + "\u044d\u0442\u0430", + "\u044f\u0433\u043e", + "\u044f\u0435", + "\u044f\u043d\u043e", + "\u0448\u0442\u043e", + "\u044d\u043d", + "\u0442\u043e\u0442", + "\u0433\u044d\u0442\u044b" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/bg.json b/data_tooling/pii_processing/ontology/data/bg.json new file mode 100644 index 0000000..10a42d7 --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/bg.json @@ -0,0 +1,3925 @@ +{ + "PLANT": [ + "\u0442\u0440\u0435\u043f\u0435\u0442\u043b\u0438\u043a\u0430", + "acer_rubrum", + "\u0448\u0435\u0441\u0442\u0438\u043b", + "\u043f\u0440\u043e\u0441\u0444\u043e\u0440\u043d\u0438\u043a", + "eupatorium_perfoliatum", + "\u0441\u043a\u043e\u0440\u0443\u0448\u0430", + "\u043b\u0430\u0432\u0440\u043e\u0432\u0438\u0448\u043d\u044f", + "\u0437\u0435\u043b\u0435", + "pontederia_cordata", + "\u043c\u0438\u0448\u0438\u043d\u0430", + "juniperus_virginiana", + "alstonia_scholaris", + "pterocarpus_indicus", + "nicotiana_tabacum", + "\u0441\u0430\u043c\u043e\u0431\u0430\u0439\u043a\u0430", + "\u043e\u0431\u0438\u043a\u043d\u043e\u0432\u0435\u043d_\u043c\u0440\u0430\u0437\u043e\u0432\u0435\u0446", + "\u043b\u0438\u0441\u0442\u0432\u0435\u043d\u0438\u0446\u0430", + "\u043d\u0438\u043c", + "gentianella_amarella", + "\u0441\u0432\u0435\u0442\u0430\u0442\u0430_\u043c\u0430\u0439\u043a\u0430", + "\u043a\u0430\u0441\u0438\u044f", + "agrostis_canina", + "saccharomyces_cerevisiae", + "lonicera_tatarica", + "pseudotsuga_menziesii", + "\u043d\u0435\u0437\u0430\u0431\u0440\u0430\u0432\u043a\u0430", + "agathis_australis", + "larix_laricina", + "cypripedium_montanum", + "arrhenatherum", + "pinus_muricata", + "\u0437\u0430\u0440\u0430\u0441\u043b\u0438\u0447\u0435", + "\u043f\u0435\u0441\u0435\u043a\u0438\u043d\u044f", + "\u043b\u0430\u0437\u0430\u0440\u043a\u0438\u043d\u044f", + "\u043a\u043e\u043f\u0440\u0438\u0432\u0430", + "\u0433\u043b\u0443\u0448\u0438\u0446\u0430", + "\u043c\u0430\u0441\u0442\u0438\u043a\u0441", + "\u043e\u0442\u0440\u043e\u0432\u043d\u0430\u0442\u0430_\u0430\u0439\u0432\u0438", + "cypripedium_reginae" + ], + "GPE": [ + "\u0431\u044f\u043b\u043e_\u0437\u043b\u0430\u0442\u043e", + "\u043d\u043e\u0432_\u0437\u0430\u0432\u0435\u0442", + "\u0441\u0432\u0435\u0442\u0430_\u0441\u043e\u0444\u0438\u044f", + "\u043d\u0430_\u0434\u043e\u0431\u044a\u0440_\u0447\u0430\u0441", + "\u0438\u043d\u0434\u0443\u0441\u0442\u0440\u0438\u0430\u043b\u043d\u0430_\u0437\u043e\u043d\u0430", + "\u0441\u0432\u0435\u0442\u0438_\u0433\u0435\u043e\u0440\u0433\u0438", + "\u0441\u0432\u0435\u0442\u0430_\u0432\u0430\u0440\u0432\u0430\u0440\u0430", + "\u0442\u0430\u0439\u0448\u0430\u043d", + "\u0432\u0438\u043d_\u043b\u043e\u043d\u0433", + "\u0434\u0430\u0440_\u0435\u0441_\u0441\u0430\u043b\u0430\u0430\u043c", + "\u0441\u0432\u0435\u0442\u0438_\u0434\u0443\u0445", + "\u043d\u0438\u043a\u043e\u043b\u0430\u0439_\u0447\u0443\u0434\u043e\u0442\u0432\u043e\u0440\u0435\u0446", + "\u0431\u0435\u043b\u0438\u044f\u0442_\u0434\u043e\u043c", + "\u0447\u043e\u0432\u0435\u0448\u043a\u0438_\u043f\u0440\u0430\u0432\u0430", + "\u0447\u0435\u0440\u0432\u0435\u043d_\u043a\u0440\u044a\u0441\u0442" + ], + "ORG": [ + "\u0441\u0432\u0435\u0442\u0438_\u043d\u0438\u043a\u043e\u043b\u0430\u0439", + "\u043a\u0430\u0442\u043e\u043b\u0438\u0447\u0435\u0441\u043a\u0430_\u0446\u044a\u0440\u043a\u0432\u0430", + "\u0430\u043b\u0431\u0438\u0433\u043e\u0439\u0446\u0438", + "\u043f\u044a\u0440\u0436\u0435\u043d\u0430_\u0444\u0438\u043b\u0438\u0439\u043a\u0430", + "\u0445\u0443\u0430\u043d\u0445\u044a", + "\u0438\u043d\u0442\u0435\u0440\u043f\u043e\u043b", + "\u043c\u0430\u043b\u043e\u043f\u043e\u043b\u0448\u0430", + "\u043b\u0435\u0439\u0431\u044a\u0440\u0438\u0441\u0442\u043a\u0430_\u043f\u0430\u0440\u0442\u0438\u044f", + "\u0433\u043e\u0440\u0441\u043a\u043e_\u0435\u0437\u0435\u0440\u043e", + "\u0433\u043e\u043c\u0438\u043d\u0434\u0430\u043d", + "\u0437\u0435\u043b\u0435\u043d\u0430_\u043f\u0430\u0440\u0442\u0438\u044f", + "\u0446\u0435\u043d\u0442\u0440\u0430\u043b\u043d\u0430_\u0431\u0430\u043d\u043a\u0430", + "\u0437\u043b\u0430\u0442\u0435\u043d_\u0432\u0435\u043a", + "\u043f\u0440\u0430\u0432\u0435\u043d_\u0434\u044f\u043b", + "\u0432\u044a\u0440\u0445\u043e\u0432\u0435\u043d_\u0441\u044a\u0434", + "\u0438\u0437\u043e\u0431\u0449\u043e", + "\u043f\u043e\u043b\u0438\u0442\u0438\u0447\u0435\u0441\u043a\u0430_\u043f\u0430\u0440\u0442\u0438\u044f", + "\u043f\u0440\u043e\u0445\u0438\u0431\u0438\u0446\u0438\u043e\u043d\u0438\u0441\u0442\u043a\u0430_\u043f\u0430\u0440\u0442\u0438\u044f_\u0432_\u0441\u0430\u0449", + "\u0432\u043e\u0435\u043d\u043d\u0430_\u0430\u043a\u0430\u0434\u0435\u043c\u0438\u044f", + "\u0438\u0441\u043b\u044f\u043c\u0438\u0441\u0442\u0438\u043a\u0430", + "\u043f\u0440\u0435\u0432\u0440\u0430\u0442", + "\u0433\u043e\u043b\u044f\u043c\u0430_\u043c\u0435\u0447\u043a\u0430", + "\u043c\u0435\u0436\u0434\u0443_\u0434\u0440\u0443\u0433\u043e\u0442\u043e", + "\u0434\u0435\u0441\u043d\u0438\u0446\u0430", + "\u0430\u043d\u0442\u0438\u043c\u0430\u0441\u043e\u043d\u0441\u043a\u0430_\u043f\u0430\u0440\u0442\u0438\u044f", + "\u0447\u0435\u0440\u0432\u0435\u043d\u043e_\u043c\u043e\u0440\u0435", + "\u0435\u043b\u0435\u043e\u043d\u0441\u043a\u0438_\u0445\u044a\u043b\u043c", + "\u043f\u044a\u0440\u0436\u0435\u043d\u0430_\u0444\u0438\u043b\u0438\u044f", + "\u0441\u044a\u0435\u0434\u0438\u043d\u0435\u043d\u0438\u0442\u0435_\u0449\u0430\u0442\u0438", + "\u0432\u043f\u0440\u043e\u0447\u0435\u043c", + "\u043c\u0438\u043b\u0438_\u043c\u0435\u0434\u0436\u043b\u0438\u0441", + "\u043f\u0430\u0440\u0442\u0438\u044f_\u043d\u0430_\u0442\u0440\u0443\u0434\u0430", + "\u0443\u0438\u043a\u0430", + "\u0441\u043e\u0446\u0438\u0430\u043b\u0434\u0435\u043c\u043e\u043a\u0440\u0430\u0442\u0438\u0447\u0435\u0441\u043a\u0430_\u043f\u0430\u0440\u0442\u0438\u044f", + "\u0441\u043e\u0446\u0438\u0430\u043b\u0434\u0435\u043c\u043e\u043a\u0440\u0430\u0442\u0438\u0447\u0435\u0441\u043a\u0430_\u043f\u0430\u0440\u0442\u0438\u044f_\u043d\u0430_\u0430\u043d\u0434\u043e\u0440\u0430", + "\u0433\u0440\u0430\u0434\u0435\u0446", + "\u0434\u0435\u043c\u043e\u043a\u0440\u0430\u0442\u0438\u0447\u0435\u0441\u043a\u0430_\u043f\u0430\u0440\u0442\u0438\u044f", + "\u043e\u043b\u0438\u043c\u043f\u0438\u0439\u0441\u043a\u043e_\u0441\u0435\u043b\u043e", + "\u043a\u043e\u043b\u0435\u0436", + "\u0430\u0440_\u0434\u0435\u043a\u043e", + "\u0430\u0440_\u043d\u0443\u0432\u043e", + "\u0448\u0438\u043d\u0442\u043e\u0438\u0437\u044a\u043c", + "\u0434\u0430_\u0436\u0438\u0432\u0435\u0435", + "\u0432\u0430\u0439\u0448\u043d\u0430\u0432\u0438\u0437\u044a\u043c", + "\u0430\u043b_\u0434\u0436\u0430\u0437\u0438\u0440\u0430", + "\u0440\u0438\u043c\u043e\u043a\u0430\u0442\u043e\u043b\u0438\u0447\u0435\u0441\u043a\u0430_\u0446\u044a\u0440\u043a\u0432\u0430", + "\u0441\u0430\u043e_\u0442\u043e\u043c\u0435", + "\u0434\u043e\u043b\u043d\u0430_\u043a\u0430\u043c\u0430\u0440\u0430", + "\u0439\u043e\u0441\u0438\u0444_\u043e\u0431\u0440\u0443\u0447\u043d\u0438\u043a", + "\u0431\u043e\u0442\u0430\u043d\u0438\u0447\u0435\u0441\u043a\u0430_\u0433\u0440\u0430\u0434\u0438\u043d\u0430", + "\u0441\u043e\u0446\u0438\u0430\u043b\u0438\u0441\u0442\u0438\u0447\u0435\u0441\u043a\u0430_\u043f\u0430\u0440\u0442\u0438\u044f", + "\u043a\u0440\u0438\u0432\u043e\u0439_\u0440\u043e\u0433", + "by_the_way", + "\u0434\u0430\u043e\u0438\u0437\u044a\u043c", + "\u043f\u043e\u0449\u0435\u043d\u0441\u043a\u0430_\u0441\u0442\u0430\u043d\u0446\u0438\u044f", + "\u043d\u0430\u0440\u043e\u0434\u043d\u043e_\u0441\u044a\u0431\u0440\u0430\u043d\u0438\u0435", + "\u043a\u0430\u043f\u0435\u0442\u0438\u043d\u0433\u0438", + "\u0430\u0440\u043c\u0438\u044f_\u043d\u0430_\u0441\u044a\u0435\u0434\u0438\u043d\u0435\u043d\u0438\u0442\u0435_\u0430\u043c\u0435\u0440\u0438\u043a\u0430\u043d\u0441\u043a\u0438_\u0449\u0430\u0442\u0438", + "\u0441\u0435\u043b\u0441\u043a\u0430_\u043b\u044f\u0441\u0442\u043e\u0432\u0438\u0446\u0430", + "\u043a\u043e\u043c\u0443\u043d\u0438\u0441\u0442\u0438\u0447\u0435\u0441\u043a\u0430_\u043f\u0430\u0440\u0442\u0438\u044f", + "\u0444\u0435\u0434\u0435\u0440\u0430\u043b\u043d\u043e_\u0431\u044e\u0440\u043e_\u0437\u0430_\u0440\u0430\u0437\u0441\u043b\u0435\u0434\u0432\u0430\u043d\u0435", + "\u043b\u0430\u043d\u043a\u0430\u0441\u0442\u044a\u0440", + "\u043c\u0438\u0442\u043d\u0438\u0446\u0430", + "\u0442\u0440\u043e\u0430_\u0440\u0438\u0432\u0438\u0435\u0440" + ], + "LOCATION": [ + "\u0435_\u0438", + "\u0437\u0430\u0434\u044a\u043d\u0435\u043d\u0430_\u0443\u043b\u0438\u0446\u0430", + "\u0435\u0439\u0442\u043e\u0440_\u0432\u0438\u043b\u0430_\u043b\u043e\u0431\u043e\u0441", + "chelus_fimbriata", + "\u0433\u0440\u0430\u0434\u044a\u0442", + "\u0441\u043a\u0443\u043f\u0449\u0438\u043d\u0430", + "\u043a\u0430\u0440\u043c\u0435\u043b", + "\u0430\u043b_\u0434\u0436\u0430\u0437\u0438\u0440\u0430", + "\u0441\u043f\u044f\u0449\u0430\u0442\u0430_\u043a\u0440\u0430\u0441\u0430\u0432\u0438\u0446\u0430", + "\u0445\u043e\u0440\u043d", + "\u0430\u043c\u0435\u0440\u0438\u0433\u043e_\u0432\u0435\u0441\u043f\u0443\u0447\u0438", + "\u043c\u0430\u043b\u0435\u0447\u043a\u043e_\u043f\u0430\u043b\u0435\u0447\u043a\u043e", + "\u0432\u043e\u0435\u043d\u043d\u043e\u0432\u044a\u0437\u0434\u0443\u0448\u043d\u0438_\u0441\u0438\u043b\u0438", + "ochlodes_sylvanus", + "\u0441\u0430\u043d_\u0443\u0430\u043a\u0438\u043d", + "\u0441\u0430\u043a\u0441\u043e\u043d\u0438\u044f_\u0430\u043d\u0445\u0430\u043b\u0442", + "\u0441\u043b\u0430\u0434\u043a\u043e\u0432\u043e\u0434\u0435\u043d", + "\u043a\u0430\u0431\u043e_\u0432\u0435\u0440\u0434\u0435", + 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+ "aquila", + "eero_saarinen", + "john_cheever", + "nelson_mandela", + "heinrich_himmler", + "al_gore", + "cesare_borgia", + "roald_amundsen", + "anton", + "charles_dickens", + "ella_fitzgerald", + "don_quijote_de_la_mancha", + "federico_fellini", + "willy_brandt", + "francisco_pizarro", + "francisco_franco", + "jan_steen", + "franz_schubert", + "johnny_cash", + "georges_cuvier", + "william_harvey", + "walter_scott", + "vladimir_lenin", + "p\u00ear_ia\u00f1", + "felipe_ii", + "robert_browning", + "alessandro_farnese", + "walter_gropius", + "albert_einstein", + "vladimir_poutin", + "thomas_edison", + "raymond_chandler", + "t" + ], + "DISEASE": [ + "kenn", + "ki", + "als", + "marelladur", + "bosenn", + "teuc'hegezh", + "skant", + "klostrofobiezh", + "gall", + "mania", + "krankr", + "boureverezh", + "torzhellegezh", + "lorgnez", + "gimp", + "amelia", + "ed", + "pica", + "dougerez", + "c_hwezigellad", + "drougsant", + "gwallzarvoud_eus_gwazhied_an_empenn", + "danta\u00f1", + "tan", + "sting", + "kresk", + "gwenaenn", + "penngamm", + "burbu", + "le", + "malaria" + ], + "JOB": [ + "grafour", + "merour", + "labourer", + "martolod", + "douarour", + "potter", + "kelennerez", + "soudard", + "ar_steredoniour", + "baraer", + "don", + "grip", + "sonour", + "eilenn", + "the_guardian", + "hollek", + "liorzhour", + "mate", + "moroniour", + "pastor", + "tiretenn", + "micherour", + "loman", + "maesaer", + "rabin", + "man", + "kizeller", + "lenner", + "usher", + "kelenner", + "daouvet", + "egile" + ], + "ORG": [ + "marc'h_troia", + "ti_al_lorded", + "gouarnamant", + "wicca", + "loch_laomainn", + "bitrakerezh", + "jan_mayen", + "shintoegezh", + "aa", + "nasa", + "daoegezh", + "bollywood", + "desaverezh", + "the_who", + "ti_k\u00ear", + "san_francisco", + "un", + "ar_goantenn_e_koad_ar_c_housk", + "strollad_broadel_sokialour_al_labourerien_alaman", + "skolaj", + "santez_lusia", + "an_taerch\u00f3r", + "gao", + "morlu", + "mahayana", + "da_garout_a_ran", + "chobiz", + "saint_helena", + "lenn_superior", + "me_da_gar", + "lenn_saint_clair", + "meudig", + "alamaneg", + "rabindranath_tagore", + "gestapo", + "gouarnamanto\u00f9", + "winnie_the_pooh", + "aerlu", + "strollad_politikel", + "po", + "skrid", + "moudenn", + "mossad", + "nautilus_pompilius", + "saint_barth\u00e9lemy", + "mor_ruz", + "gourvab", + "ti_gwenn", + "los_angeles", + "iliz_katolik_roman", + "monarkiezh_vonreizhel", + "ar_vreudeur_marx", + "strollad_al_labour", + "ti_dileuridi_ar_stado\u00f9_unanet", + "da_garan", + "st\u00ear_velen", + "iliz_katolik", + "mediao\u00f9", + "s\u00e3o_tom\u00e9" + ], + "PRODUCT": [ + "justin_bieber", + "demat", + "s\u00e3o_tom\u00e9_ha_pr\u00edncipe", + "egorvulzun", + "al_lizher_karantez", + "gwezenn_nedeleg", + "mario_andretti", + "tad_kozh_an_nedeleg", + "razh_indez", + "kab_horn", + "egorvulzuno\u00f9", + "nordrhein_westfalen", + "gwirio\u00f9_mab_den", + "spered_santel" + ], + "RELIGION_MEMBER": [ + "breudeur", + "breur" + ], + "LOCATION": [ + "an_taerch\u00f3r", + "kab_glas", + "park", + "united_states_army", + "ar_goantenn_e_koad_ar_c_housk", + "saks_anhalt", + "sint_maarten", + "menez_karmel", + "tad_kozh_ar_pellgent", + "karr_kamm_bras", + "saint_lucia", + "kristol_goulm", + "valentine's_day", + "mari_magdala", + "sri_lanka", + "bodadenn_vroadel", + "the_rolling_stones", + "leon_bihan", + "enez_sant_martin", + "mari_madalen" + ], + "LANGUAGE": [ + "poloniat", + "galleg", + "sinaat", + "hindeg", + "kongo", + "akaneg", + "esperanteg", + "polonek", + "katalanez", + "breizhad", + "kannadeg", + "brezhoneg", + "breizhadez", + "perseg", + "telougoueg", + "arabeg", + "boutaneg", + "malayalameg", + "brezhonek", + "katalan", + "hirimotoueg", + "breizhat", + "daneg", + "okitaneg", + "tonga" + ], + "RELIGION": [ + "zen", + "islam", + "daoegezh", + "shintoegezh", + "wicca" + ], + "GPE": [ + "leurg\u00ear", + "saint_domingue", + "nikolaz_mira", + "dar_es_salaam", + "hon_itron", + "sint_maarten", + "s\u00e3o_tom\u00e9", + "gran_canaria", + "valentine's_day", + "al_andalus", + "c_hoad_du", + "barbara_nikomedia", + "mirdi_santez_sofia", + "impalaeriezh_alaman", + "st_louis", + "ti_gwenn", + "testamant_nevez", + "kreizamerika" + ], + "FOOD": [ + "loukoum", + "alumenn", + "dijuni\u00f1", + "chile", + "skornenn", + "merenn" + ], + "PLANT": [ + "kerezenn", + "sivolez", + "kerez", + "karotezenn", + "serfilh", + "campanula_rapunculus", + "frezenn", + "kanab", + "faou", + "krao\u00f1enn", + "benede", + "daoulagad_ar_werc'hez", + "haleg", + "brem" + ], + "GENDER": [ + "merc'hig", + "treuzrevelezh", + "maouez", + "itron", + "man", + "plac'h", + "plac'hig" + ], + "PERSON": [ + "al_gore", + "h_g_wells", + "george_v", + "al_amin" + ], + "DATE": [ + "meurlarjez", + "krennamzer", + "mallarje", + "mallarde", + "an_ened", + "sul_ar_beuz", + "mallarjez", + "gouel_maria_hanter_eost" + ], + "FAC": [ + "l_ultima_cena", + "bolz_enor", + "ar_werc'hez_vari_ko\u00f1sevet_dinamm", + "saint_lucia", + "santez_lusia", + "ti_k\u00ear", + "titus_livius" + ], + "PERSON_PRONOUN": [ + "i", + "he", + "our", + "her", + "ma_re", + "me", + "ma_hini" + ], + "QUANTITY": [ + "c_hwec'h_warn_ugent", + "tonenn", + "ton", + "dollar", + "g", + "tri_warn_ugent" + ], + "RACE": [ + "turk", + "latin" + ], + "SOC_ECO_CLASS": [ + "dienn", + "gounezerezh", + "samourai" + ], + "POLITICAL_PARTY": [ + "f\u00f3lkaflokkurin", + "labour", + "partido_popular", + "strollad_demokratel", + "strollad_komunour", + "strollad_republikan", + "parti_socialiste", + "strollad_mirour" + ], + "UNION": [ + "international_telecommunication_union" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "abadez": "abati", + "merc'hed": "son", + "itron": "aotrou", + "anya": "peder", + "mamm": "pater", + "leanez": "monako", + "maelle": "pri\u00f1s", + "pri\u00f1sez": "pri\u00f1s", + "damez": "roue", + "queens": "rouaned", + "c_hoar": "breudeur", + "beva": "inta\u00f1v", + "inta\u00f1vez": "inta\u00f1v", + "gwreg": "gwaz", + "maouez": "gwaz", + "paotr": "plac'h" + }, + "other_gender_swap": { + "teir": "henne", + "ilin": "henne", + "e\u00f1": "teir", + "he": "teir", + "\u3078": "teir" + }, + "en_pronoun2gender": { + "they": [ + "treuzrevelezh" + ], + "he": [ + "paotr", + "gaur", + "menn", + "man", + "mab_den", + "gwaz" + ], + "she": [ + "maouez", + "itron", + "merc'hig", + "plac'h", + "plac'hig" + ] + }, + "en_pronoun2pronoun": { + "he": [ + "e\u00f1", + "\u3078", + "he" + ], + "she": [ + "henne", + "her" + ], + "they": [ + "teir", + "ilin" + ], + "it": [ + "tann" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/ca.json b/data_tooling/pii_processing/ontology/data/ca.json new file mode 100644 index 0000000..96d8c05 --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/ca.json @@ -0,0 +1,3240 @@ +{ + "PUBLIC_FIGURE": [ + "lawrence_durrell", + "la_tour", + "henry_cavendish", + "matthew_arnold", + "lambert", + "lev_ivanov", + "benjamin_franklin", + "martin_buber", + "karl_gjellerup", + "sullivan", + "akira_kurosawa", + "frances_wright", + "maria_tallchief", + "noah_webster", + "jean_genet", + "john_knox", + "heinrich_hertz", + "sant_llu\u00eds", + "roger_williams", + "le_duc_tho", + "giovanni_boccaccio", + "cornelius_vanderbilt", + "rudolf_steiner", + "thomas_wolfe", + "david_rittenhouse", + "ernesto_guevara", + "thomas_bayes", + "ben_hogan", + "angelets", + "johann_bernoulli", + "serguei_rakhm\u00e0ninov", + "max_bruch", + "giovan_battista_marino", + "leonard_bernstein", + "alistair_cooke", + "che_guevara", + "charles_townes", + "georges_simenon", + "c", + "alan_seeger", + "i_a_richards", + "thomas_hodgkin", + "john_barth", + "edward_albee", + "dorothy_parker", + "sant_pere", + "maria_callas", + "victor_herbert", + "william_walton", + "henrik_ibsen", + "abelard", + "rabelais", + "william_gladstone", + "mary_shelley", + "franz_werfel", + "quine", + "marcello_malpighi", + "peter_lorre", + "karl_baedeker", + "david_livingstone", + "eduard_buchner", + "david_smith", + "john_herschel", + "gauss", + "andrzej_wajda", + "jan_van_eyck", + "nicolau_cop\u00e8rnic", + "carl_rogers", + "george_balanchine", + "georg_wilhelm_steller", + "richard_burton", + "douglas_macarthur", + "james_michener", + "mary_wollstonecraft", + "j_edgar_hoover", + "maria_magdalena", + "thomas_reid", + "john_jacob_astor", + "anna_pavlova", + "winston_churchill", + "constant\u00ed", + "johannes_diderik_van_der_waals", + "giambattista_marini", + "b", + "somicaire", + "conrad_aiken", + "karl_landsteiner", + "ivan_pavlov", + "dmitri_shostakovich", + "paul_mccartney", + "richard_smalley", + "andrew_marvell", + "terry_pratchett", + "k", + "stephen_king", + "francis_crick", + "john_trumbull", + "van_gogh", + "crist\u00f2bal_colom", + "joseph_greenberg", + "isaac_newton", + "richard_upjohn", + "alfred_eisenstaedt", + "victor_hugo", + "joseph_smith", + "edwin_hubble", + "ivan_p\u00e0vlov", + "milton_friedman", + "amy_lowell", + "edward_gibbon", + "mezzosoprano", + "jefferson_davis", + "saint_louis", + "cass_gilbert", + "george_stephenson", + "john_glenn", + "john_webster", + "john_davis", + "george_burns", + "primer_mandatari", + "george_harrison", + "peter_minuit", + "george_orwell", + "seleuc", + "arthur_koestler", + "richard_wagner", + "joseph_john_thomson", + "williams", + "thornton_wilder", + "e_l_doctorow", + "pancho_villa", + "aleksandr_borodin", + "dr_james_wilson", + "el_quixot", + "leopold_stokowski", + "rebecca_west", + "marie_curie", + "malthus", + "francis_galton", + "mary_martin", + "michael_jackson", + "louis_jolliet", + "carl_sandburg", + "thomas_hobbes", + "joseph_lister", + "edward_weston", + "el_greco", + "samuel_beckett", + "david", + "russell", + "galileo_galilei", + "ernest_bevin", + "jane_goodall", + "john_donne", + "chaim_weizmann", + "andrea_guarneri", + "robert_koch", + "van_vleck", + "i_m_pei", + "joseph_goebbels", + "george_eastman", + "john_steinbeck", + "erich_mendelsohn", + "utrillo", + "antigalla", + "edmund_hillary", + "vincent_van_gogh", + "richard_hooker", + "w", + "william_hazlitt", + "marc_antoni", + "martina_navr\u00e1tilov\u00e1", + "marie_stopes", + "anne_boleyn", + "john_ruskin", + "francisco_de_goya_y_lucientes", + "robert_burns", + "john_henry", + "hans_albrecht_bethe", + "carl_anderson", + "thomas_paine", + "bari", + "francis_beaumont", + "lliurador", + "steven_weinberg", + "p", + "mary_pickford", + "hans_fischer", + "emiliano_zapata", + "elisabet", + "karl_barth", + "yuri_gagarin", + "willem_einthoven", + "phil_anderson", + "thomas_willis", + "charles_chaplin", + "bernard_malamud", + "samuel_johnson", + "allen_iverson", + "wesley", + "l_elegida", + "marie_antoinette", + "anne_hutchinson", + "louise_nevelson", + "giuseppe_verdi", + "walter_lippmann", + "edward_appleton", + "e", + "karl_jaspers", + "beethoven", + "helmholtz", + "hideki_yukawa", + "konrad_adenauer", + "antoni", + "john_l_lewis", + "marianne_moore", + "norbert_wiener", + "agripina", + "john_masefield", + "horatio_nelson", + "mark_rothko", + "maurice_chevalier", + "gottlieb_daimler", + "frank_sinatra", + "fran\u00e7ois_rabelais", + "abel_tasman", + "katharine_hepburn", + "henri_becquerel", + "henri_matisse", + "bertram_brockhouse", + "louis_pasteur", + "j", + "richard_strauss", + "stephen_decatur", + "leslie_howard", + "hugo_grotius", + "mahalia_jackson", + "lloren\u00e7", + "ben_shahn", + "john_ford", + "stephen_foster", + "alphonse_bertillon", + "katherine_mansfield", + "vi_de_xer\u00e8s", + "gertrude_stein", + "sarah_bernhardt", + "dostoevski", + "farisaic", + "v", + "philip_marlowe", + "luigi_pirandello", + "t_s_eliot", + "e_g_marshall", + "marc_blitzstein", + "hank_williams", + "rube_goldberg", + "dorothea_lange", + "james_thurber", + "charles_de_gaulle", + "paul_von_hindenburg", + "y", + "henry_moore", + "holden", + "mary_mallon", + "ralph_bunche", + "rudolf_bultmann", + "charles_lindbergh", + "vincenzo_bellini", + "samuel_barber", + "tobias_smollett", + "joseph_stalin", + "f", + "john_jay", + "ludwig_wittgenstein", + "august_strindberg", + "stalin", + "carmelit\u00e0", + "thomas_mann", + "alla_nazimova", + "charles_goodyear", + "dante_alighieri", + "arnau", + "robert_lee", + "margot_fonteyn", + "peter_pan", + "james_tobin", + "john_irving", + "panofsky", + "samuel_de_champlain", + "giacomo_puccini", + "edward_fitzgerald", + "fridtjof_nansen", + "louis_braille", + "herbert_marcuse", + "don_quixot", + "mungo_park", + "benedict_arnold", + "paul_verlaine", + "q", + "robert_johnson", + "james_dean", + "robert", + "richard_lovelace", + "marie_tussaud", + "roger_bannister", + "theodor_schwann", + "max_beerbohm", + "alessandro_manzoni", + "joseph_priestley", + "robert_oppenheimer", + "nicolas_poussin", + "andrea_mantegna", + "adolf_windaus", + "pere_abelard", + "joseph_pulitzer", + "ring_lardner", + "george_huntington", + "james_naismith", + "oscar_wilde", + "montgolfier", + "philip_roth", + "j_d_salinger", + "henry", + "lawrence", + "richard_trevithick", + "william_bradford", + "heinrich_schliemann", + "eli_whitney", + "glenn_curtiss", + "don_quijote", + "the_court_jester", + "laurence_olivier", + "pierre_larousse", + "christiaan_eijkman", + "l_advocat_del_diable", + "adolf_eichmann", + "marilyn_horne", + "boole", + "stan_musial", + "francis_bacon", + "pete_seeger", + "john_wycliffe", + "joseph_heller", + "a", + "boone", + "morris", + "norman_rockwell", + "boris_spassky", + "james_brown", + "william_hogarth", + "charles_baudelaire", + "luigi_cherubini", + "david_ricardo", + "cichlasoma_octofasciatum", + "john_mitchell", + "henri_labrouste", + "mary_leakey", + "charlie_parker", + "z", + "immanuel_kant", + "james_franck", + "william_crookes", + "james_meredith", + "samuel_gompers", + "nellie_bly", + "weber", + "alexandre_yersin", + "n", + "stephen_leacock", + "albert_schweitzer", + "sant_patrici", + "john_harvard", + "johann_friedrich_herbart", + "giulio_natta", + "dewey", + "subnormal", + "johannes_kepler", + "anatoli_karpov", + "william_s_burroughs", + "most", + "david_hartley", + "max_planck", + "william_blake", + "t_e_lawrence", + "julio_iglesias", + "john_bardeen", + "sarah_vaughan", + "john_wilkes", + "galina_ul\u00e0nova", + "william_byrd", + "william_henry", + "christopher_fry", + "scott_joplin", + "samuel_houston", + "carl_lewis", + "sarah_siddons", + "george_vancouver", + "canberra", + "bramante", + "elias_canetti", + "robert_lowell", + "johann_strauss", + "edward_jenner", + "john_mercer", + "oscar_robertson", + "oliver_hardy", + "cole_porter", + "benjamin_west", + "assutzena", + "jean_luc_godard", + "graci\u00f3s", + "graham_greene", + "frans_hals", + "maquiavel", + "lars_onsager", + "margaret_mitchell", + "igor_stravinsky", + "stuart_davis", + "lola_montez", + "jan_swammerdam", + "mary_mccarthy", + "david_riesman", + "john_walker", + "william_herschel", + "joseph_black", + "marcus_whitman", + "mikhail_baryshnikov", + "montesquieu", + "peirce", + "arthur_rubinstein", + "calvin", + "arthur_compton", + "niels_bohr", + "tom\u00e0s", + "sergei_rachmaninoff", + "kenneth_grahame", + "henry_fielding", + "bertrand_russell", + "katherine_anne_porter", + "michael_faraday", + "john_d_rockefeller", + "anthony_burgess", + "jan_tinbergen", + "robert_venturi", + "johnny_appleseed", + "greg", + "irving_berlin", + "moliner", + "gauguin", + "anna_p\u00e0vlova", + "bernard_baruch", + "rudolf_diesel", + "vlad\u00edmir_putin", + "hans_holbein", + "walt_disney", + "ben_jonson", + "crist\u00f2for_colom", + "la_spezia", + "robert_benchley", + "joseph_schumpeter", + "gabriel_lippmann", + "steve_reich", + "lee", + "benny_goodman", + "ted_williams", + "coprotagonista", + "william_beaumont", + "friedrich_engels", + "pavlov", + "jane_austen", + "charles_laughton", + "jordi", + "gustav_mahler", + "ed_sullivan", + "phil_collins", + "alice_paul", + "robert_redford", + "jean_giraudoux", + "jack_dempsey", + "la_caputxeta_vermella", + "ian_fleming", + "richard_feynman", + "wolfgang_pauli", + "theodore_dreiser", + "theodor_mommsen", + "andrew_huxley", + "marcel_proust", + "jessica_mitford", + "thomas_more", + "homo_heidelbergensis", + "paul_hindemith", + "elizabeth_taylor", + "thomas_chippendale", + "anne_sullivan", + "paul_robeson", + "thomas_middleton", + "john_dowland", + "daniel_jones", + "william_golding", + "robert_motherwell", + "william_caxton", + "john_milton", + "rudolf_serkin", + "peter_stuyvesant", + "ethel_merman", + "illa_de_san_crist\u00f3bal", + "samuel_adams", + "albert_speer", + "james_baldwin", + "john_vanbrugh", + "indira_gandhi", + "william_mitchell", + "jane_seymour", + "george_gershwin", + "alberto_giacometti", + "elisabet_i", + "e_t_a_hoffmann", + "frank_whittle", + "alfred_nobel", + "sordmut", + "jesse_owens", + "daniel_rutherford", + "marco_polo", + "john_fletcher", + "caravaggio", + "charlie_watts", + "m", + "charlotte_corday", + "marcel_marceau", + "el_rei_lear", + "allen_ginsberg", + "fred_zinnemann", + "l_lawliet", + "daniel_bernoulli", + "guillaume_apollinaire", + "william_strickland", + "sant_david", + "antoine_watteau", + "pablo_casals", + "joseph_henry", + "henri_bergson", + "antonius", + "edward_macdowell", + "josef_hoffmann", + "boris_karloff", + "pierre_corneille", + "phillis_wheatley", + "oppenheimer", + "patrick_white", + "saul_steinberg", + "bartholomew_roberts", + "eileen_farrell", + "catherine_howard", + "hans_christian_andersen", + "peter_cooper", + "reich", + "william_morris", + "cary_grant", + "hideyo_noguchi", + "thomas", + "isaac_watts", + "ford", + "pieter_zeeman", + "glenn_miller", + "pablo_picasso", + "marian_anderson", + "natalie_wood", + "l_ron_hubbard", + "thomas_moore", + "osman_i", + "kurt_weill", + "falciot", + "otto_hahn", + "lester_young", + "christian_huygens", + "john_marshall", + "christiaan_huygens", + "hector_berlioz", + "lucille_ball", + "paul_simon", + "claudio_monteverdi", + "ensostrador", + "robert_scott", + "stravinsky", + "john_galsworthy", + "robert_robinson", + "vassili_kandinski", + "o", + "adam_smith", + "william_james", + "u", + "jean_harlow", + "henry_miller", + "modest_m\u00fassorgski", + "karl_marx", + "paul_bunyan", + "i", + "robert_indiana", + "jimmy_durante", + "john_wesley", + "sandro_botticelli", + "carson_mccullers", + "magna_mater", + "seiji_ozawa", + "proust", + "nikola_tesla", + "al_capone", + "jim_bowie", + "charles_barkley", + "billy_graham", + "robert_schumann", + "mel_gibson", + "le_corbusier", + "carlo_goldoni", + "john_locke", + "alexis_carrel", + "carles", + "joseph_marie_jacquard", + "henry_james", + "stephen_sondheim", + "riu_sant_lloren\u00e7", + "lorenz_hart", + "robert_bartlett", + "perry", + "helen_keller", + "paul_dukas", + "ingrid_bergman", + "leonard_bloomfield", + "jane_jacobs", + "jean_piaget", + "anna_bolena", + "william_congreve", + "franz_kline", + "henri_rousseau", + "vitraller", + "paul_tillich", + "hilaire_belloc", + "frank_norris", + "pieter_brueghel", + "frank_stella", + "robert_southey", + "valentina_tereshkova", + "eddington", + "h_g_wells", + "walt_whitman", + "william_wyler", + "john_osborne", + "colin_powell", + "moliere", + "ludwig_boltzmann", + "carl_nielsen", + "chopin", + "carl_jung", + "leopold_kronecker", + "richard_wright", + "banyeta", + "benjamin_thompson", + "adolf_hitler", + "maria_mitchell", + "fritz_haber", + "archibald_macleish", + "peter_behrens", + "john_tradescant", + "alfred_stieglitz", + "john_h_watson", + "joseph_haydn", + "stephen_spender", + "garfield", + "george_boole", + "paul_revere", + "daniel_boone", + "buffalo_bill", + "edvard_grieg", + "robert_boyle", + "arthur_laffer", + "edith_cavell", + "alan_paton", + "ralph_richardson", + "prima_donna", + "1", + "cordell_hull", + "james_wilson", + "rosa_parks", + "norman_jewison", + "samuel_goldwyn", + "x", + "ernest_walton", + "vladimir_putin", + "jacob", + "giuseppe_mazzini", + "jim_thorpe", + "hertz", + "h", + "randall_jarrell", + "arnold_sch\u00f6nberg", + "laurence_sterne", + "jacqueline_cochran", + "george_fox", + "ben_hecht", + "christopher_isherwood", + "fritz_kreisler", + "anne_hathaway", + "david_garrick", + "don_budge", + "bill_russell", + "margaret_court", + "emile_zola", + "baldwin", + "gregori", + "jeannette_rankin", + "clarence_darrow", + "tamara_kars\u00e0vina", + "fyodorovich_stravinsky", + "charles_lamb", + "g", + "alexandre_i", + "konstant\u00edn_stanislavski", + "john_chapman", + "arthur_schopenhauer", + "thomas_dekker", + "james_cagney", + "john_keble", + "johns_hopkins", + "henri_pitot", + "wanda_landowska", + "martin_heidegger", + "hans_eysenck", + "muller", + "r", + "george_lucas", + "andrew_jackson", + "edith_wharton", + "louis_armstrong", + "la_verge", + "antony_tudor", + "steven_spielberg", + "lev_iv\u00e0nov", + "jean_monnet", + "d_w_griffith", + "robert_fulton", + "thomas_hardy", + "eddie_rickenbacker", + "thomas_gainsborough", + "franz_ferdinand", + "giuseppe_garibaldi", + "philip_warren_anderson", + "fra_filippo_lippi", + "alexandre_dumas", + "philipp_melanchthon", + "robert_brown", + "wilhelm_weber", + "thomas_carlyle", + "johann_gutenberg", + "donald_barthelme", + "william_tyndale", + "tamara_karsavina", + "bobby_fischer", + "johannes_gutenberg", + "d", + "james_bowie", + "thomas_malthus", + "giambattista_marino", + "gaetano_donizetti", + "william_faulkner", + "edward_white", + "titus_flavius_vespasianus", + "amerigo_vespucci", + "arthur_holmes", + "pierre_boulez", + "hans_adolf_krebs", + "girolamo_savonarola", + "emma_goldman", + "francis_poulenc", + "james_ussher", + "john_barrymore", + "john_constable", + "james_mill", + "putin", + "matthew_flinders", + "bataner", + "robert_herrick", + "joseph_campbell", + "jean_de_la_fontaine", + "robert_hooke", + "o_henry", + "karl_popper", + "alfred", + "coleman_hawkins", + "mary_harris", + "john_calvin", + "george_sand", + "peter_sellers", + "homo_rhodesiensis", + "charles_fourier", + "henry_clay", + "peter_o'toole", + "joseph_conrad", + "edmund_halley", + "william_shockley", + "peter_paul_rubens", + "mahatma_gandhi", + "jim_morrison", + "cromwell", + "jules_verne", + "paul_newman", + "robert_mills", + "george_meredith", + "robert_morris", + "woody_herman", + "alexander_wilson", + "josef_albers", + "jackson_pollock", + "john_lennon", + "andrea_palladio", + "gandhi", + "bob_woodward", + "crist\u00f2for_de_l\u00edcia", + "charlie_chaplin", + "lillian_russell", + "d_h_lawrence", + "edward_morley", + "j_m_barrie", + "thomas_malory", + "john_brown", + "al_jolson", + "elizabeth_gaskell", + "hugo_junkers", + "caterina", + "patrici_d_irlanda", + "norman_thomas", + "lillian_hellman", + "brescia", + "carter", + "thomas_merton", + "riemann", + "asa_gray", + "hannah_arendt", + "antonio_stradivari", + "robinson_jeffers", + "el_flautista_d_hamel\u00edn", + "pescant", + "alice_walker", + "miles_davis", + "edmund_cartwright", + "mois\u00e8s", + "james_parkinson", + "george_marshall", + "harold_nicolson", + "jesse_jackson", + "willa_cather", + "illa_de_sant_mart\u00ed", + "l_holand\u00e8s_errant", + "stanley_kubrick", + "john_deere", + "llac_tana", + "john_huston", + "robert_merton", + "jean_baptiste_joseph_fourier", + "william_gilbert", + "james_watt", + "octavi", + "jonathan_edwards", + "ronald_reagan", + "helmut_schmidt", + "jenny_lind", + "homo", + "frederick_douglass", + "begu\u00ed", + "la_rochefoucauld", + "david_hilbert", + "skinner", + "wilhelm_reich", + "william_thornton", + "troglod\u00edtid", + "roman_jakobson", + "oliver_cromwell", + "lionel_hampton", + "martin_luther_king", + "james_hargreaves", + "frank_capra", + "william_wordsworth", + "rex_harrison", + "s", + "william_clark", + "woodrow_wilson", + "besavis", + "william_wycherley", + "margaret_sanger", + "macaco_de_cua_de_porc_meridional", + "gustav_hertz", + "george_mason", + "el_cid", + "agrippina", + "richard_rodgers", + "rosegaaltars", + "don_quixote", + "carles_i", + "anne_sexton", + "salad\u00ed", + "morgana", + "john_dryden", + "jim_henson", + "b\u00e9la_lugosi", + "ernest_hemingway", + "john_eccles", + "george_westinghouse", + "aquila", + "jacques_charles", + "eero_saarinen", + "arthur_miller", + "john_cheever", + "friedrich_wilhelm_bessel", + "valentina_tereixkova", + "gracie_allen", + "artesana", + "nelson_mandela", + "heinrich_himmler", + "al_gore", + "john_rutledge", + "hans_bethe", + "hans_geiger", + "mohandas_gandhi", + "cesare_borgia", + "roald_amundsen", + "sherwood_anderson", + "richard_leakey", + "alfred_korzybski", + "charles_dickens", + "sean_o'casey", + "samuel_huntington", + "ella_fitzgerald", + "fats_waller", + "jakob_bernoulli", + "thomas_sydenham", + "alois_senefelder", + "george_enescu", + "wallace_carothers", + "jacques_offenbach", + "joseph_paxton", + "falcilla", + "william_curtis", + "william_chambers", + "gilbert", + "leakey", + "bronislaw_malinowski", + "george_stevens", + "federico_fellini", + "bessie_smith", + "patrick_henry", + "willy_brandt", + "charles_wilkes", + "francisco_pizarro", + "francisco_franco", + "jackie_robinson", + "bernardo_bertolucci", + "king_oliver", + "jan_steen", + "frank_harris", + "john_ross", + "ali_baba", + "powell", + "philibert_delorme", + "hans_arp", + "andrew_carnegie", + "franz_schubert", + "johnny_cash", + "joseph_mccarthy", + "alfred_kastler", + "mick_jagger", + "otto_loewi", + "charles_peirce", + "georges_cuvier", + "hemingway", + "william_harvey", + "walter_scott", + "parkinson", + "peter_medawar", + "professor_de_ci\u00e8ncies", + "sam_houston", + "l_elegit", + "la_verge_maria", + "robert_peary", + "eritrina_arbre", + "maximi\u00e0", + "robert_browning", + "alessandro_farnese", + "ralph_ellison", + "john_bunyan", + "jonathan_swift", + "walter_gropius", + "albert_einstein", + "l", + "aletta_jacobs", + "thomas_edison", + "chiang_kai_shek", + "claude_bernard", + "raymond_chandler", + "henry_purcell", + "t", + "gainsborough", + "wilhelm_ostwald" + ], + "PLANT": [ + "acer_negundo", + "verdolaga", + "marrub\u00ed", + "cucurbita_ficifolia", + "lisim\u00e0quia", + "hibiscus_syriacus", + "repalassa", + "guixera", + "hevea", + "pyracantha", + "acer_rubrum", + "col_de_cabdell", + "card_mari\u00e0", + "mahonia", + "magn\u00f2lia", + "enciam", + "parnassia", + "espantallops", + "batallaire", + "rubus_saxatilis", + "caquier", + "morella", + "genus_dracaena", + "bardana", + "quercus_coccinea", + "servera", + "cladonia_rangiferina", + "melissa", + "maduixera", + "geranium_molle", + "mamona", + "viola_arvensis", + "sapindus", + "the_joshua_tree", + "olivereta", + "helleborus_niger", + "vidalba", + "helianthus", + "traspic", + "hidr\u00f2fit", + "horehound", + "serpoll", + "maracuj\u00e0", + "guinder", + "cucurbita_moschata", + "xuclamel", + "olives", + "mountain_alder", + "xirimoier", + "aur\u00f3", + "magnoli\u00f2fit", + "pseudofruit", + "llentiscle", + "white_horehound", + "oli_de_colza", + "selaginella_lepidophylla", + "ortiga", + "bellaombra", + "sensitiva", + "amanita", + "pinassa", + "sequoiadendron", + "morell", + "noguera", + "escutel\u00b7l\u00e0ria", + "arabidopsis_thaliana", + "santa_maria", + "bertholletia_excelsa", + "castanyer", + "epipremnum_aureum", + "arundo", + "porradell", + "trompetes", + "moniatera", + "octubrera", + "planta_verinosa", + "sinapis", + "calcida", + "crisantem", + "passiflora_ligularis", + "leucaena_leucocephala", + "ala_d_\u00e0ngel", + "cercidiphyllum_japonicum", + "acer_campestre", + "cassoleta_vermella", + "falgueres", + "erable", + "col_de_tripa", + "convolvulus", + "aristol\u00f2quia_sarmentosa", + "lleterola", + "armoll", + "arctostaphylos_alpina", + "acacia_pycnantha", + "actinidia_chinensis", + "sakura", + "papaver", + "silene_dioica", + "guinda", + "candida_albicans", + "amaryllis_belladonna", + "arrhenantherum", + "vedells", + "asperula", + "rosa_multiflora", + "anthemis_arvensis", + "cicadofit\u00ed", + "fongs", + "bufassa", + "escarolat", + "acer_macrophyllum", + "parquins\u00f2nia", + "dianthus_caryophyllus", + "gram\u00ednia", + "malrub\u00ed", + "pastanaga", + "planta_arborescent", + "boixerola", + "sciadopitys", + "bergamota", + "altimira", + "acer_palmatum", + "liliaci", + "vellutet", + "tangerina", + "esquitxagossos", + "sapodella", + "nou_d_areca", + "lligabosc", + "bellerenca", + "marc\u00f2lic", + "passiflora_incarnata", + "clusia", + "traqueobiont", + "festuca_ovina", + "quercus_ellipsoidalis", + "marx\u00edvol", + "genus_brassica", + "mostassa", + "gatassa", + "selenicereus_grandiflorus", + "pelargonium_peltatum", + "reseda", + "niella", + "barbarea_vulgaris", + "kochia_scoparia", + "gossypium_hirsutum", + "castanea_dentata", + "coliflor", + "liquidambar", + "urtica", + "parthenocissus_tricuspidata", + "lychnis", + "alzina", + "aguilera", + "olivaci", + "gatsaule", + "cucurbita_argyrosperma", + "dionea", + "actin\u00eddia", + "caputxina", + "calla_palustris", + "leonurus_cardiaca", + "silybum", + "acer_japonicum", + "taronja_\u00e0cida", + "dracocephalum", + "carissa_macrocarpa", + "margaridoia_perenne", + "populus_balsamifera", + "col_cabdellada", + "cabrafiguera", + "olivera", + "genus_angelica", + "blat\u00e0ria", + "genus_prunus", + "diplotaxis_muralis", + "castany", + "clematis", + "xeringuilla", + "xicoia", + "margall_bord", + "menta_boscana", + "saccharum", + "garrof\u00f3", + "tricholoma_aurantium", + "col_i_flor", + "xirimoia", + "phytophthora_infestans", + "chlorophyllum_molybdites", + "bilimbi", + "alzineta", + "prosopis_juliflora", + "peric\u00f3", + "acer_platanoides", + "planta_carn\u00edvora", + "argemone", + "erica_carnea", + "euphorbia_cyparissias", + "ar\u00edtjol", + "blackberry", + "blenera", + "cortaderia_selloana", + "solanum", + "florida_selaginella", + "escaravia", + "cicad\u00e0cia", + "peritre", + "gelsemi", + "brachychiton_acerifolius", + "acer_pseudoplatanus", + "canabassa", + "bougainvillaea", + "cr\u00e8spol", + "romeguera", + "bardissa", + "tavellera", + "genus_erica", + "repunx\u00f3", + "conillets", + "pa_de_cucut_de_bosc", + "genus_echinocactus", + "rubus_spectabilis", + "liquid\u00e0mbar", + "genus_ricinus", + "llambrusca", + "plantes", + "acer_circinatum", + "planta_llenyosa", + "scottish_maple", + "sabina", + "arum", + "dracunculus_vulgaris", + "acacia_melanoxylon", + "saccharomyces_cerevisiae", + "coniza_canadenca", + "lled\u00f3", + "all_de_serp", + "ranunculus_bulbosus", + "molses", + "aleixandri", + "desferracavalls", + "noguer", + "col_xinesa", + "espernallac", + "aliguer", + "marum", + "aquil\u00b7lea", + "planta_bulbosa", + "all_porro", + "tintorell", + "carrasca", + "gaultheria_procumbens", + "margall_perenne", + "pseudotsuga_menziesii", + "cascall", + "galzeran", + "plantatge_gros", + "genus_coreopsis", + "crataegus_aestivalis", + "tirabec", + "teix", + "quallallet", + "monocotiled\u00f2nies", + "gallaret", + "calla", + "col_de_brot", + "salic\u00e0ria", + "saxe_gothea", + "nasturtium", + "cany\u00eds", + "espinavessa", + "auriana", + "edelweiss", + "spiranthes_spiralis", + "cirerer", + "fesol", + "aranyoner", + "estepa_ladan\u00edfera", + "zoisia", + "estramoni", + "azaleastrum", + "fromental", + "salix_arctica", + "cananga", + "morr\u00f3", + "arrhenatherum", + "annona_reticulata", + "paris_quadrifolia", + "cavall_roig", + "oxalis", + "belladonna", + "gatzer\u00ed", + "vinagrella", + "allium_ampeloprasum", + "savina", + "roser_silvestre", + "poa_nemoralis", + "amaranthus_albus", + "saxegothea", + "agrimonia", + "vallisneria", + "ou_del_diable", + "acer_glabrum", + "gimnospermes", + "lloreret", + "castanya", + "genus_urtica", + "jull", + "castanea", + "melcoratge", + "donzell", + "malcoratge", + "physalis_peruviana", + "cardiga", + "j\u00edcama", + "hamamelis_virginiana", + "gazer\u00ed", + "aler\u00e7", + "dicksonia_antarctica", + "surera", + "magnolia", + "nephrolepis_exaltata", + "barball\u00f3", + "plantago_media", + "artemisia_maritima", + "ranunculus_acris", + "corretjola", + "ou_de_reig", + "platanthera_bifolia", + "corniol" + ], + "ANIMAL": [ + "passerell", + "acherontia", + "apodemus", + "la_gavina", + "hidrob\u00e0tid", + "equinoderms", + "ca_eivissenc", + "panerola", + "te_verd", + "buteo", + "catxalot", + "albatros_negre", + "homo_sapiens_sapiens", + "os_mar\u00ed_septentrional", + "sit_blanc", + "cabusset", + "martinet_blanc", + "rata_del_desert", + "estafil\u00ednid", + "arru\u00ed", + "cirr\u00edpede", + "tafanera", + "malocostraci", + "sorell", + "holot\u00faria", + "billy_elliot", + "pseudoharengus", + "torpediniforme", + "bacteris", + "merla", + "falc\u00f3", + "kunduz", + "dipl\u00f2pode", + "mostela", + "artr\u00f2pode", + "canis_minor", + "hiemosc", + "manta", + "cornella", + "gonococ", + "bact\u00e8ries", + "carduelis", + "pisces", + "falcilla", + "eretmochelys", + "lloparr\u00f3", + "estrigiforme", + "teix\u00f3", + "kalimotxo", + "martinet_cullerot", + "lactobacillus_acidophilus", + "ca_menor", + "carei", + "senglar", + "artr\u00f2podes", + "cobai", + "agullat", + "lladella", + "duc", + "escateret", + "escanyapolls", + "enganyapastors", + "picaplatges", + "garsa", + "amfibis", + "homocerca", + "micropterus", + "xafardera", + "hermissenda", + "picnog\u00f2nid", + "sit_caranegre", + "camallarg", + "homo_sapiens", + "baribal", + "arner", + "calimotxo", + "carabao", + "tallareta_vulgar", + "marcenc", + "passer", + "escamarl\u00e0", + "ai_ai", + "fenic\u00falid", + "gal\u00b7linaci", + "barret_de_castor", + "marmotini", + "peixos", + "acel", + "protoctistes", + "rascl\u00f3", + "cocker", + "rata_dormidora_rogenca", + "virus_del_mosaic_del_tabac", + "rata_comuna", + "perist\u00e8did", + "genus_erignathus", + "marta_gibelina", + "hortol\u00e0", + "accipiter", + "cinclid", + "au_aqu\u00e0tica", + "perissod\u00e0ctil", + "rata_talpera", + "heterocerca", + "el_corb", + "llampuga", + "aguilot", + "probi\u00f2tic", + "dicti\u00f2pter", + "thomomys_talpoides", + "banteng", + "gripau", + "crisom\u00e8lid", + "llebrer", + "sergent_major", + "protoctists", + "aufrany", + "donald_duck", + "cargolet", + "camallarga", + "rata_cangur", + "sebel\u00b7l\u00ed", + "voltor", + "esplugabous", + "aligany", + "febre_hemorr\u00e0gica_de_l_ebola", + "trencapinyes", + "genus_staphylococcus", + "celenterats", + "cat\u00e0rtid", + "lloca", + "cordats", + "ammospermophilus", + "ictiobus_niger", + "rata_negra", + "megascops", + "falciot", + "bombyx", + "virus_del_nil_occidental", + "micr\u00f2stom", + "titella", + "pregamans", + "mahonia_aquifolium", + "ringdove", + "pardal", + "tetran\u00edquid", + "barramunda", + "percebe", + "coniller", + "cant\u00e0rida", + "platanisto\u00efdeu", + "tetra\u00f2nid", + "moixa", + "camar\u00ed", + "destrer", + "conill_porqu\u00ed", + "cobaia", + "torlit", + "au_de_ca\u00e7a", + "tamia", + "teleostis", + "lir\u00f3_gris", + "mesquer", + "home_modern", + "au_migrat\u00f2ria", + "marsopa", + "gavot\u00ed", + "mantis", + "nassut", + "dros\u00f2fila", + "gymnorhina", + "blatodeu", + "cadernera", + "podicipediforme", + "artiod\u00e0ctil", + "pregad\u00e9u", + "quac_quac", + "cranca", + "rubor\u00f3s", + "lemming", + "eagle", + "digit\u00edgrad", + "muscic\u00e0pid", + "malacopterigi", + "genbu", + "chelydra", + "rata_d_aigua", + "fredeluga", + "erignathus", + "clor\u00f2fit", + "arvicola", + "lluer", + "mantodeu" + ], + "SOC_ECO_CLASS": [ + "alta_societat", + "labor", + "samurai", + "subm\u00f3n", + "petita_burgesia", + "escollit", + "estraperlo", + "proletariat", + "burgesia", + "selecte", + "petit_burg\u00e8s", + "organitzaci\u00f3_fraternal" + ], + "LOCATION": [ + "al_jazeera", + "la_plata", + "assemblea_nacional", + "no_es_mereixen", + "mar_forana", + "air_force", + "manicomi", + "any_nou", + "mar_oriental_de_la_xina", + "mar_del_nord", + "corpus_christi", + "mar_groc", + "piet_mondrian", + "un_quart_de_dues", + "nou_m\u00f3n", + "santa_fe", + "mar_de_lluny", + "sint_maarten", + "les_dotze_en_punt", + "les_dotze", + "mar_negra", + "trois_rivi\u00e8res", + "bella_dorment", + "fons_de_retirs", + "dia_del_treballador", + "escola_d_arts_i_oficis", + "saint_george", + "mar_tirrena", + "forces_a\u00e8ries", + "mont_carmel", + "sant_pau", + "huang_he", + "riu_groc", + "saint_vincent", + "balneari", + "mar_de_la_xina_oriental", + "en_pau_en_pere_i_en_berenguera", + "pieris_rapae", + "assemblea_nacional_de_la_rep\u00fablica_de_l_azerbaidjan", + "assemblea_nacional_de_corea_del_sud", + "no_\u00e9s_res", + "roserar", + "joseph_louis_gay_lussac", + "per_si_de_cas", + "mar_groga", + "el_pilar", + "aigua_dol\u00e7a", + "ex\u00e8rcit_dels_estats_units_d_am\u00e8rica", + "mar_llarguera", + "plantago_media", + "a_la_carretera", + "la_city", + "conservatori_de_m\u00fasica", + "mar_negre", + "saint_lucia", + "hwang_ho", + "l_hort_dels_cirerers", + "arena", + "austr\u00e0lia_occidental", + "sri_lanka", + "escola_t\u00e8cnica", + "la_bella_dorment", + "bernat_pescaire", + "banc_central", + "terra_cremada", + "the_rolling_stones", + "el_tel\u00e8fon", + "de_res", + "sax\u00f2nia_anhalt", + "mar_de_fora", + "dia_de_la_hispanitat", + "llac_superior", + "\u00e0ngel_de_la_guarda", + "via_romana", + "ex\u00e8rcit_dels_estats_units", + "nou_m\u00e8xico", + "heitor_villa_lobos", + "louis_joseph_gay_lussac", + "bescuit", + "mar_de_fons", + "al_ain", + "nou_m\u00e8xic", + "de_dins", + "santa_claus", + "llac_saint_clair" + ], + "DISEASE": [ + "pesta_septic\u00e8mica", + "adoloriment", + "energia_calor\u00edfica", + "xarampi\u00f3", + "sotragar", + "presb\u00edcia", + "malaltia_inflamat\u00f2ria", + "pampallugues", + "calazi", + "esgratinyada", + "epil\u00e8psia_t\u00f2nica", + "grip_porcina", + "guerxesa", + "fonedor", + "tartamudeig", + "deixondiment", + "fur\u00f3ncol", + "cosmid", + "gotirl\u00f3", + "malatia_transmissible", + "esquistosomosi", + "galteres", + "mastitis", + "papissotejar", + "arrauxat", + "escaldada", + "z\u00f2ster", + "papil\u00b7loma", + "arcades", + "deshidrataci\u00f3", + "coragre", + "sanglot", + "empatx", + "hermafroditisme", + "galind\u00f3", + "herpes_simple", + "masto\u00efditis", + "energy", + "genus_oestrus", + "cianosi", + "carboncle", + "frenes\u00ed", + "flaquesa", + "quilitis", + "ordit", + "baconera", + "rapacitat", + "palat\u00f2squisi", + "fotof\u00f2bia", + "catal\u00e8psia", + "distr\u00f2fia", + "gall", + "mania", + "pigota", + "the_bends", + "virus_de_la_varicel\u00b7la_z\u00f2ster", + "labirintitis", + "fusta_del_castanyer", + "esparavany", + "genus_anomia", + "epil\u00e8psia_musicog\u00e8nica", + "picornavirus", + "phytophthora_infestans", + "shigel\u00b7losi", + "poliomielitis", + "esternut", + "malaltia_cardiovascular", + "condicionar", + "llengut", + "anguniejar", + "claustrof\u00f2bia", + "distr\u00f2fia_muscular", + "mig_aclucar", + "the_suffering", + "malaltia", + "paramixovirus", + "dolen\u00e7a", + "odont\u00e0lgia", + "papil\u00b7ledema", + "pancreatitis", + "restrenyiment", + "mononucleosi_infecciosa", + "pirosi", + "pessigada", + "esternudar", + "catarro", + "mossegar", + "ratol\u00ed", + "estrim\u00f3", + "par\u00e8sia", + "cardiopatia_cong\u00e8nita", + "colangitis", + "handicap", + "indigesti\u00f3", + "gastritis_cr\u00f2nica", + "calfred", + "transposici\u00f3", + "oftalmoplegia", + "xuclet", + "geperut", + "gegantisme", + "vasculitis", + "beri_beri", + "lumbago", + "diabetis_sacarina", + "autoimmunitat", + "escanyament", + "bradic\u00e0rdia", + "torpor", + "queratoacantoma", + "analg\u00e8sia", + "hero\u00efnomania", + "tartamudejar", + "mareig", + "penell\u00f3", + "el_cop", + "faringitis", + "escandalitzar", + "balanitis", + "la_n\u00e0usea", + "laceraci\u00f3", + "talass\u00e8mia", + "poli\u00faria", + "brucel\u00b7losi", + "rubor", + "berruga", + "escarlatina", + "qi", + "queratitis", + "erisipela", + "corn", + "granuloma", + "exaltac\u00f3", + "forma_f\u00edsica", + "llaga", + "alteraci\u00f3_gen\u00e8tica", + "silicosi", + "dist\u00edmia", + "gimp", + "oestrus", + "trasbalsat", + "arrapada", + "herpes", + "escorbut", + "despersonalitzaci\u00f3", + "protan\u00f2psia", + "castanya", + "mongolisme", + "desmielinitzaci\u00f3", + "desconfortar", + "twist", + "paludisme", + "prog\u00e8ria", + "cardiomiopatia", + "rodera", + "ed", + "fogonejar", + "pica", + "ventrellada", + "parest\u00e8sia", + "alveolitis", + "tracoma", + "quist", + "anest\u00e8sia", + "fonof\u00f2bia", + "embriaguesa", + "paritat", + "betegar", + "espasme", + "listeriosi", + "defici\u00e8ncia_mental", + "queratocon", + "cardiomeg\u00e0lia", + "oftalmia", + "socarrar", + "cardiopatia", + "taquic\u00e0rdia", + "pain", + "coragror", + "enguerximent", + "triquinosi", + "bul\u00edmia", + "castany", + "genus_icterus", + "arbovirus", + "neur\u00e0lgia_trig\u00e8mina", + "the_passion_of_the_christ", + "abadanar", + "coent", + "albumin\u00faria", + "deseiximent", + "preecl\u00e0mpsia", + "accident_vascular_cerebral", + "polidact\u00edlia", + "goll", + "laringitis", + "ill", + "paraplegia", + "sobrecreixement", + "brusar", + "minusvalidesa", + "arenav\u00edrid", + "decandiment", + "verola", + "vitreus", + "cinetosi", + "flegm\u00f3", + "congesti\u00f3", + "malaltia_contagiosa", + "pesta_bub\u00f2nica", + "mielitis", + "exotropia", + "escr\u00f2fula", + "rojor", + "ginecom\u00e0stia", + "estrabisme", + "mi", + "escalfor", + "aura", + "virus_d_epstein_barr", + "soltesa", + "tan", + "tanatof\u00f2bia", + "sting", + "par\u00e0lisi", + "singlotar", + "pasteurel\u00b7losi", + "sobrep\u00e8s", + "contagi", + "fundador", + "tritan\u00f2psia", + "polid\u00edpsia", + "rovellament", + "trauma", + "sanglotar", + "borm", + "cagarrines", + "meteorisme", + "kuru", + "burn", + "salmonel\u00b7losi", + "la_pesta", + "contusi\u00f3", + "corpul\u00e8ncia", + "cremada", + "espinal", + "noma", + "ortopnea", + "the_hives", + "materialisme", + "genus_scleroderma", + "ronya", + "estenosi", + "escoliosi", + "dengue", + "anasarca", + "tallada", + "estrangulaci\u00f3", + "adolorit", + "polimiositis", + "proctitis", + "amigdalitis", + "rabiar", + "malaltia_cong\u00e8nita", + "radiaci\u00f3", + "pepida", + "p\u00f2lissa_flotant", + "salmonel\u00b7la", + "carrilada", + "habituaci\u00f3", + "coltellada", + "addicci\u00f3", + "carditis", + "pertorbaci\u00f3_mental", + "tarantisme", + "grafospasme" + ], + "FOOD": [ + "pa_mor\u00e8", + "desdejuni", + "te_negre", + "olla_podrida", + "pa_integral", + "gint\u00f2nic", + "mousse", + "pa_de_canyella", + "esmorzar", + "pastes", + "golden_delicious", + "desert", + "cucurull", + "vi_de_calif\u00f2rnia", + "ou_de_xocolata", + "vi_blanc", + "oli_vegetal", + "vi_gener\u00f3s", + "mossec", + "pela_de_la_llimona", + "llimonada", + "te_d_herbes", + "vi_rosat", + "cucurutxo", + "vi_de_porto", + "vigna_unguiculata", + "truita_salmonada", + "granny_smith", + "oli_de_cot\u00f3", + "pa_franc\u00e8s", + "darreries", + "resaig\u00fces", + "pa_de_panses", + "vi_de_missa", + "pa_de_s\u00e8gol", + "white_russian", + "xiclet", + "t_bone_steak", + "farina", + "te_gelat", + "pa_blanc", + "ou_de_pasqua", + "pela_de_la_taronja", + "rebosteria", + "col_llombarda", + "oli_de_palma", + "pa_d_all", + "resinar", + "vi_de_taula", + "alta_cuina", + "ou_dur", + "pa_negre", + "rostes_de_santa_teresa", + "congelats", + "galeta_granola", + "mossada", + "caldereta", + "guerxa", + "quetxup", + "patates_fregides", + "oli_de_s\u00e8sam", + "oli_de_cacauet", + "oli_d_oliva", + "antipasto", + "postres", + "olives_farcides", + "oli_de_gira_sol", + "baguet", + "oli_de_llavors_de_cot\u00f3", + "embotits", + "llet\u00f3", + "ou_passat_per_aigua", + "tutti_frutti", + "all_tendre", + "dinada", + "pa_de_ceba", + "morritort", + "oli_de_soja", + "oli_de_coco", + "ou_ferrat", + "vi_negre", + "pastissos", + "pela_de_pl\u00e0tan", + "rom_jamaica", + "olives_negres", + "pa_graham", + "poma_\u00e0cida", + "vi_dol\u00e7", + "vi_escum\u00f3s", + "vi_del_roine", + "entrem\u00e8s", + "oli_de_soia" + ], + "JOB": [ + "infermer", + "persona_grata", + "cortes\u00e0", + "timoner", + "falconer", + "vidrier", + "alienista", + "verger", + "endocrin\u00f2leg", + "tallista", + "guru", + "allistador", + "lacai", + "gerent", + "maitre", + "cabrera", + "internunci", + "presidenta", + "endodoncista", + "mariner", + "boxador", + "fustera", + "assistent", + "assegurador", + "tinent", + "pellisser", + "geof\u00edsic", + "repartidor", + "magatzemer", + "agrimensor", + "canalera", + "ginec\u00f2leg", + "dissenyador", + "grangera", + "make", + "esteticista", + "asidu", + "venedor", + "mainadera", + "dependenta", + "meteor\u00f2leg", + "batlle", + "interiorista", + "llenyataire", + "cristaller", + "reboster", + "forner", + "faronejar", + "enciclopedista", + "luthier", + "tartaner", + "alcaid", + "sindicador", + "registrar", + "autora", + "banderer", + "fosser", + "canoer", + "bastaix", + "ruedero", + "tripulant", + "arrier", + "bugadera", + "subaltern", + "fargaire", + "alcaldessa", + "senescal", + "fuster", + "fundador", + "conillet", + "el_ca\u00e7ador", + "don", + "galiot", + "distribuidor", + "carretel\u00b7la", + "king", + "planter", + "mercader", + "patronejar", + "trencador", + "sanitari", + "caporal", + "facultatiu", + "acad\u00e8mica", + "fogoner", + "missatger", + "industrialista", + "the_police", + "sastressa", + "intern", + "pastora", + "gestor", + "terapeuta", + "compositor", + "comediant", + "carreter", + "vaguista", + "skinner", + "pretor", + "picapedrer", + "sommelier", + "ensostrador", + "llancer", + "empenyorar", + "resident", + "empenyorament", + "entallador", + "portaequipatges", + "molinera", + "carronyaire", + "llauner", + "col\u00b7leccionista", + "microbi\u00f2leg", + "ebenista", + "territorial", + "pastisser", + "cobradora", + "conestable", + "pixatinters", + "perruquer", + "netejavidres", + "ministra", + "grip", + "router", + "conductor", + "esten\u00f2graf", + "paperer", + "unionista", + "blanquer", + "oste\u00f2pata", + "algutzir", + "la_pastora", + "marmit\u00f3", + "missatgera", + "assagista", + "professor_d_art", + "mastermind", + "capat\u00e0s", + "miodes\u00f2psies", + "adober", + "gautxo", + "rehoboth_basters", + "estomat\u00f2leg", + "herbolari", + "estipendiari", + "barretaire", + "fanaler", + "duaner", + "mac\u00eds", + "alt_comissari", + "calafatador", + "guaita", + "inventor", + "catequista", + "cronometrador", + "hostelera", + "grafista", + "portador", + "manufacturer", + "infermera", + "brigadier", + "clauera", + "independent", + "capitanejar", + "perruquera", + "freelance", + "verdulaire", + "subtinent", + "giravoltar", + "kamikaze", + "carboner", + "carcerari", + "the_advocate", + "empaperador", + "peroler", + "llenyater", + "sergent", + "enginyer_electricista", + "sobrec\u00e0rrec", + "histri\u00f3", + "governador", + "punter", + "cadi", + "calaix", + "llevadora", + "perxa", + "alcalde", + "venedora", + "master", + "mantinguda", + "the_guardian", + "bracer", + "percussor", + "torner", + "tracci\u00f3", + "president", + "ensenyant", + "picaplets", + "la_lletera", + "burgmestre", + "bataner", + "moliner", + "culi", + "setter", + "estacional", + "mariscal", + "regidor", + "esbirro", + "calderer", + "volandera", + "agen\u00e7aaparadors", + "mate", + "callista", + "arrecerar", + "no_combatent", + "macer", + "aiguafortista", + "herald", + "professor_de_geometria", + "catxap", + "pastor", + "hostessa", + "cart\u00f2graf", + "neur\u00f2leg", + "vaquer", + "richard_keith", + "alferes", + "hemat\u00f2leg", + "tropes", + "taqu\u00edgraf", + "camer\u00e0man", + "portalliteres", + "ballador", + "serraller", + "orinar", + "escombrador", + "estad\u00edstic", + "corporal", + "renglera", + "baster", + "bombers", + "coronel", + "intendent", + "bugader", + "granader", + "the_consul", + "sagrist\u00e0", + "the_economist", + "associat", + "cuirasser", + "familiar", + "comerciant", + "escombraire", + "carter", + "porter", + "carronyer", + "covallibres", + "oficial_federal", + "amistan\u00e7ada", + "microbi\u00f2loga", + "cop", + "quiropr\u00e0ctic", + "bobinadora", + "novel\u00b7lista", + "the_batman", + "batllessa", + "barber", + "agutzil", + "departament_executiu", + "golejador", + "neurocirurgi\u00e0", + "crupier", + "assaonador", + "fogainer", + "principal", + "col\u00b7leccionador", + "man", + "assessora", + "dermat\u00f2leg", + "regent", + "maquetista", + "professor_associat", + "rotulista", + "mesurador", + "caixista", + "torrapipes", + "armero", + "barreter", + "rentaplats", + "gavarrer", + "arrencador", + "lapidari", + "el_rector", + "usher", + "messenger", + "carrosser", + "many\u00e0", + "rentacares", + "netejador", + "rodeta", + "enterramorts", + "mariner_de_coberta", + "el_comerciant", + "agent_d_assegurances", + "au_pair", + "rentavaixella", + "geront\u00f2leg", + "proconsul", + "capeller", + "tramoista", + "the_interpreter", + "p\u00f2lissa_oberta", + "amanuense", + "comandant", + "fonedor", + "calafat", + "proc\u00f2nsol", + "terrissaire", + "gelater", + "director_general_de_correus", + "portaveu", + "lampista", + "fuseller", + "extern", + "estibador", + "doula", + "antologista", + "the_dresser", + "parer", + "teleapuntador", + "the_landlord", + "comodor", + "the_independent", + "tresorer", + "reguer\u00f3", + "coper", + "cardi\u00f2leg", + "proct\u00f2leg", + "mitjancer", + "vaquera", + "cookie", + "conductora", + "agents", + "guixer", + "bisbe", + "cineasta", + "taquimecan\u00f2graf", + "blanquejador", + "rocker", + "regular", + "linotipista", + "autor", + "excombatent", + "ferrador", + "mosqueter", + "pirag\u00fcista", + "sotsoficial", + "preceptor" + ], + "FAC": [ + "sublim_porta", + "la_muntanya_m\u00e0gica", + "comissaria", + "estaci\u00f3_de_ferrocarrils", + "carbonera", + "instal\u00b7laci\u00f3_esportiva", + "arnold_sch\u00f6nberg", + "saint_joseph", + "sant_jaume", + "mall", + "casa_del_com\u00fa", + "saint_lucia", + "poliesportiu", + "esgl\u00e9sia_cat\u00f2lica_romana", + "arc_de_triomf", + "josep_de_natzaret", + "casa_de_la_ciutat", + "a_poc_a_poc", + "creu_de_ferro", + "el_sant_sopar", + "les_quatre_estacions", + "poc_a_poc", + "pere_i_de_r\u00fassia", + "sant_sebasti\u00e0", + "oficina_de_correus", + "casa_de_la_vila" + ], + "GENDER": [ + "dona_gran", + "senyoreta", + "mademoiselle", + "xavala", + "male", + "mascla", + "minyona", + "guiu", + "xiqueta", + "exalumne", + "damisel\u00b7la", + "man", + "transgen", + "gal", + "transg\u00e8nere" + ], + "ORG": [ + "estratocr\u00e0cia", + "dolorosa", + "mitologia_n\u00f2rdica", + "doi", + "treballadors", + "san_jos\u00e9", + "gernaci\u00f3", + "arma_blanca", + "sant_josep", + "drug_enforcement_administration", + "wicca", + "qui_\u00e9s_vost\u00e9", + "acad\u00e8mia_militar", + "caixa_de_pensions", + "jan_mayen", + "maconeria", + "assumpci\u00f3_de_maria", + "aa", + "nasa", + "puntejar", + "bramanisme", + "huang_he", + "comercialisme", + "bollywood", + "sivaisme", + "actualitzat", + "europol", + "schutzstaffel", + "alt_forn", + "justesa", + "the_who", + "ad_libitum", + "uni\u00f3_internacional_de_telecomunicacions", + "externat", + "tribunal_superior", + "college", + "san_francisco", + "partit_dem\u00f2crata", + "un", + "a_chorus_line", + "war_machine", + "monarquia_parlament\u00e0ria", + "estats_units", + "batall\u00f3", + "for\u00e7a_a\u00e8ria", + "taoisme", + "filharm\u00f2nic", + "centre_hist\u00f2ric", + "viol\u00e8ncia_dom\u00e8stica", + "va", + "francma\u00e7oneria", + "saint_george", + "pas_del_nord_oest", + "dret_intern", + "escola_veterin\u00e0ria", + "municipalitat", + "escola", + "viceversa", + "sc", + "besn\u00e9t", + "escola_de_m\u00fasica", + "a_poc_a_poc", + "gao", + "dot", + "maquillar", + "hagan\u00e0", + "malaltia_ven\u00e8ria", + "der_freie_wille", + "nanak", + "mahayana", + "les_tres_germanes", + "el_ra\u00efm_de_la_ira", + "qui_ets", + "saint_vincent", + "classe_obrera", + "hospital_psiqui\u00e0tric", + "estraperlo", + "john_tuzo_wilson", + "don_juan", + "el_creador", + "em_dic", + "consell_estudiantil", + "bepop", + "ai", + "mercat_negre", + "la_bella_dorment", + "ds", + "caixa_de_jubilacions", + "chiang_mai", + "ministeri_de_just\u00edcia", + "vixnuisme", + "dia", + "partit_republic\u00e0", + "home_de_cromany\u00f3", + "superpot\u00e8ncia", + "al_dia", + "forces_armades", + "de_tant_en_tant", + "cap_verd", + "partit_liberal", + "mare_de_d\u00e9u_de_la_pietat", + "unitat_pol\u00edtica", + "lluna_creixent", + "la_casa_blanca", + "\u00e0ngel_custodi", + "inter\u00e8s_personal", + "partit_socialdem\u00f2crata", + "casa_consistorial", + "rabindranath_tagore", + "gestapo", + "don_joan", + "santa_helena", + "una_vegada_m\u00e9s", + "the_full_monty", + "classe_treballadora", + "winnie_the_pooh", + "partit_del_treball", + "tribunal_suprem", + "instituci\u00f3_docent", + "radiogal\u00e0xia", + "capdavanter", + "li_fi", + "modernsime", + "polzet", + "consistori", + "oficina_postal", + "borni", + "estar_al_corrent", + "estar_al_dia", + "saint_joseph", + "al_jazeera", + "po", + "mossad", + "hare_krishna", + "ferdinand_magellan", + "nautilus_pompilius", + "t_estimo", + "missi\u00f3_diplom\u00e0tica", + "dret_internacional", + "hwang_ho", + "t_estime", + "khorat", + "negocis", + "patrulla_fronterera", + "saint_barth\u00e9lemy", + "partit_nacional_socialista_dels_treballadors_alemanys", + "departament_de_just\u00edcia", + "sturmabteilung", + "corts_constituents", + "mar_roja", + "conselleria", + "los_angeles", + "kriv\u00ed_rih", + "baltimore_orioles", + "em_diuen", + "ad_hoc", + "escola_religiosa", + "partit_whig_dels_estats_units", + "la_bemoll_major", + "or_blanc", + "mi", + "cienciologia", + "by_the_way", + "alta_fidelitat", + "in_situ", + "st_francis", + "sa", + "col\u00b7legi", + "santa_ll\u00facia", + "escola_universit\u00e0ria", + "el_gat_negre", + "assemblea_nacional_de_la_rep\u00fablica_s\u00e8rbia", + "manicomi", + "amanida_de_fruites", + "per_cert", + "al_ain", + "front_popular", + "govern_militar", + "mont_de_les_oliveres", + "maced\u00f2nia_de_fruita", + "una_educaci\u00f3", + "american\u00edstica", + "esgl\u00e9sia_cat\u00f2lica", + "mar_roig", + "streptococcus_pyogenes", + "cita_a_cegues", + "vila_ol\u00edmpica", + "partit_conservador_de_noruega", + "lluna_nova", + "verge_dels_dolors", + "zona_industrial", + "in_vitro", + "casa_comuna", + "verge_de_l_amargura", + "t_estim", + "govern_dels_estats_units", + "s\u00e3o_tom\u00e9", + "mare_de_d\u00e9u_dels_dolors", + "nit_de_cap_d_any", + "van_gogh", + "en_com\u00fa" + ], + "LANGUAGE": [ + "caixmiri", + "panjabi", + "llat\u00ed", + "rundi", + "venda", + "quetxua", + "bambara", + "baixkir", + "samo\u00e0", + "catalana", + "core\u00e0", + "assam\u00e8s", + "cornuall\u00e8s", + "sindhi", + "samoana", + "pali", + "russa", + "ganda", + "manx", + "hongar\u00e9s", + "gallega", + "lusit\u00e0", + "basc", + "gallec", + "georgi\u00e0", + "portugu\u00e8s", + "malai\u00e0lam", + "kanar\u00e8s", + "hindi", + "catal\u00e0", + "esperanto", + "portugalesa", + "roman\u00e9s", + "francoproven\u00e7al", + "bengal\u00ed", + "marshall\u00e8s", + "komi", + "lingala", + "romanesa", + "portuguesa", + "cree", + "portugal\u00e8s", + "tagalog", + "ido", + "hisp\u00e0nic", + "tonga" + ], + "PRODUCT": [ + "tot_va_b\u00e9_si_acaba_b\u00e9", + "ves_te'n", + "les_quatre_estacions", + "si_d\u00e9u_vol", + "justin_bieber", + "la_dama_de_piques", + "autom\u00f2bil_esportiu", + "carrer_gran", + "al_jazeera", + "com_si", + "cobai", + "esperit_sant", + "ll\u00e0grimes_de_job", + "tallacircuits", + "diego_garcia", + "tutti_frutti", + "conillet_d_\u00edndies", + "conill_d_\u00edndies", + "echinopsis_pachanoi", + "la_modificaci\u00f3", + "el_gos_dels_baskerville", + "multiplataforma", + "julius_caesar", + "saint_vincent", + "the_star_spangled_banner", + "la_divina_com\u00e8dia", + "la_guerra_de_les_gal\u00e0xies", + "guardafocs", + "don_quixote", + "conillet_d_\u00edndia", + "die_hard", + "atzucac", + "parenostre", + "la_ciociara", + "el_senyor_dels_anells", + "boxing_day", + "curtcircuit", + "arbre_de_nadal", + "bodes_d_argent", + "la_dolce_vita", + "deutsche_welle", + "el_gat_amb_botes", + "gong", + "ferdinand_magellan", + "the_pilgrim's_progress", + "la_lletra_escarlata", + "nou_testament", + "mario_andretti", + "s\u00e3o_tom\u00e9_i_pr\u00edncipe", + "la_nit_de_reis", + "arc_triomfal", + "capital_de_granada", + "carrer\u00f3_sense_eixida", + "carrer\u00f3_sense_sortida", + "pedra_rosetta", + "per_la_gr\u00e0cia_de_d\u00e9u", + "estaci\u00f3_espacial", + "bodes_de_plata", + "cobaia", + "joan_baptista", + "cap_d_hornos", + "novo_mesto" + ], + "GPE": [ + "dia_dels_enamorats", + "la_casa_blanca", + "nou_testament", + "saint_domingue", + "dar_es_salaam", + "sant_andreu", + "imperi_alemany", + "sint_maarten", + "sant_tom\u00e0s", + "papua_occidental", + "prov\u00edncies_centrals", + "sant_mateu", + "pol\u00edgon_industrial", + "mar_egea", + "s\u00e3o_tom\u00e9", + "casa_blanca", + "vila_ol\u00edmpica", + "sant_pere", + "mar_roig", + "saint_george", + "gran_can\u00e0ria", + "or_blanc", + "b\u00e0rbara_de_nicom\u00e8dia", + "dia_de_sant_valent\u00ed", + "llu\u00eds_ix", + "al_\u00e0ndalus", + "andalusa", + "parc_industrial", + "la_gomera", + "regi\u00f3_litoral", + "creu_roja", + "nicolau_de_mira", + "santa_sofia", + "mar_roja", + "esperit_sant", + "dolorosa", + "sant_joan_baptista" + ], + "RACE": [ + "japonesos", + "afric\u00e0", + "paquistan\u00e8s", + "amerindi", + "anglesos", + "esquimals", + "francesos", + "filip\u00ed", + "llatinoameric\u00e0", + "francesa", + "polinesi", + "llatinoamericana", + "neerlandesos", + "asi\u00e0tica", + "originari", + "illenca", + "gal\u00b7lesos" + ], + "DATE": [ + "mes_lunar", + "dia_dels_innocents", + "dia_natural", + "any_sideral", + "any_bissextil", + "dia_escolar", + "pleniluni", + "any_de_trasp\u00e0s", + "llunaci\u00f3", + "era_comuna", + "dia_de_sant_patrici", + "any_plat\u00f2nic", + "dia_de_la_marmota", + "dia_de_les_\u00e0nimes", + "el_dia_de_dem\u00e0", + "era_cristiana", + "a_llarg_termini", + "dia_del_sant", + "dia_de_la_sant\u00edssima_trinitat", + "happy_hour", + "dia_de_la_independ\u00e8ncia_de_l_\u00edndia", + "dia_lliure", + "dia_dels_morts", + "dia_sideral", + "dia_onom\u00e0stic", + "quart_creixent", + "dia_dels_difunts", + "dia_de_la_boda", + "dia_d_eleccions", + "dia_dels_caiguts", + "era_espacial", + "dia_de_la_mare", + "fora_de_comptes", + "la_ronda_de_nit", + "nit_de_reis", + "any_eclesi\u00e0stic", + "dia_de_les_forces_armades", + "dia_de_la_independ\u00e8ncia_dels_estats_units_d_am\u00e8rica", + "endem\u00e0", + "dia_de_la_independ\u00e8ncia", + "dia_sideri", + "torn_de_dia", + "any_lunar", + "la_nit_de_sant_joan", + "any_solar", + "edat_d_or", + "dia_de_mercat", + "mig_segle", + "any_acad\u00e8mic", + "la_nit_de_reis", + "festa_religiosa", + "dia_de_la_setmana", + "any_bixest", + "dia_del_casament", + "tot_sants", + "dia_bixest", + "corpus_christi", + "dia_d_enganyar", + "dia_de_la_bandera", + "dia_de_la_vict\u00f2ria", + "any_civil", + "dia_del_canad\u00e0", + "any_com\u00fa", + "mes_sin\u00f2dic", + "festivitat_cristiana" + ], + "QUANTITY": [ + "won_de_corea_del_nord", + "franc_franc\u00e8s", + "any_llum", + "nou_peso_uruguai\u00e0", + "franc_congol\u00e8s", + "franc_guine\u00e0", + "won_nord_core\u00e0", + "punxoset", + "franc_mali", + "dinar", + "krona", + "ton", + "tres_regnes", + "les_tres_germanes", + "nou_d\u00f2lar_de_taiwan", + "g", + "franc_senegal\u00e8s", + "krone", + "caloria", + "pa_anga", + "volt_amper", + "won_sud_core\u00e0", + "quilopond", + "won_de_corea_del_sud", + "anders_celsius", + "multa_d_aparcament", + "sistema_m\u00e8tric" + ], + "RELIGION_MEMBER": [ + "guru", + "budista", + "protestant", + "sunnita", + "carmelit\u00e0", + "morm\u00f3", + "sabatari", + "francisc\u00e0", + "indostan\u00e8s", + "indost\u00e0nic", + "augustini\u00e0", + "testimoni_de_jehov\u00e0", + "parsis", + "baptista", + "benedict\u00ed", + "presbiteri\u00e0", + "congregacionista", + "episcopalista", + "parsi", + "metodista", + "sarra\u00ed", + "cistercenc", + "mon", + "mahomet\u00e0", + "cat\u00f2lic_rom\u00e0" + ], + "RELIGION": [ + "zen", + "salafisme", + "lamaisme", + "donatisme", + "maniqueisme", + "calvinisme", + "bramanisme", + "islam", + "sivaisme", + "presbiterianisme", + "catarisme", + "mitraisme", + "sintoisme", + "vixnuisme", + "xintoisme", + "ci\u00e8ncia_cristiana", + "wicca", + "trinitarianisme" + ], + "EVENT": [ + "campaneig", + "castella_i_lle\u00f3", + "flor_de_lis", + "grand_prix", + "lliga_portuguesa_de_futbol", + "gran_premi" + ], + "BIO_CHEM_ENTITY": [ + "oli_d_ametlla_amarga", + "oli_de_sassafr\u00e0s", + "oli_mineral", + "oli_de_peix", + "oli_d_ametlla", + "oli_de_c\u00e0lam", + "oli_de_nou", + "oli_amb_menta", + "oli_de_llavors_de_ra\u00efm", + "dietil\u00e8ter" + ], + "PERSON_PRONOUN": [ + "nosaltres", + "i", + "he", + "vosaltres", + "our", + "la_meva", + "el_teu", + "me", + "seva", + "la_teva", + "us", + "el_meu" + ], + "LAW": [ + "codi_penal", + "sistema_electoral", + "procuraci\u00f3", + "dret_penal", + "dret_civil", + "dret_nacional", + "tribunal_superior", + "ne_bis_in_idem", + "federal_bureau_of_investigation", + "dret_rom\u00e0" + ], + "PERSON": [ + "prince_albert", + "julius_caesar", + "al_gore", + "h_g_wells", + "saint_vincent", + "la_la_la", + "william_playfair", + "don_delillo", + "edward_osborne_wilson", + "roger_eliot_fry", + "mitjan\u00e7ant", + "mont_tai", + "sant_joan", + "de_witt", + "min_dong", + "willard_frank_libby", + "igor_sikorsky", + "t_bone_steak", + "peter_dawson", + "chachach\u00e1", + "carl_david_anderson", + "maxwell_anderson", + "rudolf_hess", + "io_io", + "herbert_george_wells", + "al_am\u00edn" + ], + "POLITICAL_PARTY": [ + "partit_democr\u00e0tic", + "partit_verd", + "democratic_republican_party", + "partit_conservador", + "f\u00f3lkaflokkurin", + "partit_comunista", + "labor", + "partit_socialista_democr\u00e0tic", + "kuomintang", + "partit_social_dem\u00f2crata", + "partit_popular", + "recepci\u00f3_a_l_aire_lliure", + "partit_socialdem\u00f2crata_d_andorra", + "partit_socialista", + "partit_nacional", + "partit_socialdem\u00f2crata_de_l_azerbaidjan", + "partit_laborista_australi\u00e0", + "festa_al_jard\u00ed", + "partit_republic\u00e0_dels_estats_units", + "partit_dem\u00f2crata_dels_estats_units", + "partit_laborista", + "javna\u00f0arflokkurin", + "partit_socialdem\u00f2crata_hongar\u00e8s", + "partit_progressista" + ], + "POLITICAL_PARTY_MEMBER": [ + "dilatori", + "laboralista", + "fabianista", + "comunista", + "federalista" + ], + "ANAT": [ + "os_del_bra\u00e7" + ], + "TITLE": [ + "sir" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "mare_superiora": "abba", + "abadessa": "abbas", + "priora": "abba", + "actriu": "int\u00e8rpret", + "aviadora": "aviador", + "bonda": "pair", + "tieta": "tiu", + "baronessa": "l\u00edder_empresarial", + "n\u00favia": "cuidar_se", + "dona_d_empresa": "empresari", + "dona_de_negocis": "empresari", + "empres\u00e0ria": "empresari", + "working_girl": "home_d_empresa", + "vaquera": "vaquer", + "filla": "son", + "duquessa": "duc", + "emperadriu": "lib\u00e8l\u00b7lula_emperador", + "femella": "masculina", + "femen\u00ed": "mascul\u00ed", + "femenina": "male", + "gal": "guiu", + "xiqueta": "guiu", + "al\u00b7lota": "guiu", + "senyoreta": "guiu", + "institutriu": "regulador", + "n\u00e9ta": "n\u00e9t", + "seva": "lia", + "hero\u00efna": "heroi", + "heroi": "botir", + "amfitriona": "amfitri\u00f3", + "hostelera": "hoste", + "casera": "the_landlord", + "marquesa": "marqu\u00e8s", + "mademoiselle": "sir", + "absentar_se": "sir", + "faltar": "sir", + "sentir_enyoran\u00e7a_de": "sir", + "necessitar": "sir", + "fallir": "sir", + "enyorar": "sir", + "mancar": "sir", + "missa": "sir", + "evadir_se": "sir", + "amistan\u00e7ada": "master", + "flama": "master", + "mantinguda": "capitana", + "mares_del_vi": "pap\u00e0", + "acaronar": "pap\u00e0", + "reny": "pair", + "amanyagar": "pap\u00e0", + "matrix": "genitor", + "mare_del_vi": "pair", + "neboda": "nebot", + "monja": "monjo", + "religiosa": "monjo", + "nun": "monjo", + "sacerdotessa": "moss\u00e8n", + "princesa": "prince", + "infanta": "el_pr\u00edncep", + "homosexual": "indra", + "reg": "indra", + "naja": "beix", + "fetillera": "bruixot", + "fadrina_vella": "solter", + "solterassa": "solter", + "fillastra": "fillastre", + "sogra": "padrastre", + "madrastra": "padrastre", + "hostessa": "intendent", + "vidua": "viudo", + "viuda": "viudo", + "v\u00eddua": "vidu", + "dona_casada": "senar", + "esposa": "esp\u00f2s", + "duna": "marit", + "al\u00b7lot": "senyoreta", + "xicot": "xiqueta", + "xiquet": "senyoreta", + "cauc\u00e0sic": "blanca", + "metgessa": "dotor", + "doctor_de_l_esgl\u00e9sia": "metgessa", + "facultatiu": "metgessa", + "doctor": "metgessa", + "dotor": "metgessa", + "metge": "metgessa", + "metges": "metgessa", + "arts": "metgessa" + }, + "other_gender_swap": { + "s\u00f3n_elles": "seva", + "elles": "seva", + "llur": "seva", + "lia": "seva", + "ell": "oms", + "he": "oms", + "\u3078": "elles", + "seva": "lia" + }, + "en_pronoun2gender": { + "they": [ + "transexual", + "transgen", + "homosexual", + "bisexual", + "transg\u00e8nere" + ], + "he": [ + "mascle", + "clivellar_se", + "fitxa", + "xiquet", + "mascle_biologia", + "guiu", + "tallar_se", + "mascla", + "masculina", + "home_adult", + "man", + "capital_de_les_maldives", + "tripular", + "little_boy", + "bar\u00f3", + "male", + "mascul\u00ed", + "gaur", + "al\u00b7lot", + "xicot" + ], + "she": [ + "faltar", + "brasa", + "femenina", + "missa", + "evadir_se", + "al\u00b7lota", + "fallir", + "lesbianisme", + "srta", + "senyoreta", + "gal", + "sentir_enyoran\u00e7a_de", + "femer", + "criada", + "femen\u00ed", + "xicota", + "damisel\u00b7la", + "bimba", + "mademoiselle", + "pubilla", + "xavala", + "minyona", + "enyorar", + "xiqueta", + "absentar_se", + "donzella", + "mancar", + "femella", + "necessitar", + "lesbiana" + ] + }, + "en_pronoun2pronoun": { + "he": [ + "lia", + "ell", + "\u3078", + "he" + ], + "she": [ + "seva" + ], + "they": [ + "elles", + "lia", + "oms", + "llur", + "ii", + "s\u00f3n_elles", + "ells", + "epi" + ], + "it": [ + "aquest", + "essa", + "tyto" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/ccc.json b/data_tooling/pii_processing/ontology/data/ccc.json new file mode 100644 index 0000000..058a32a --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/ccc.json @@ -0,0 +1,56 @@ +{ + "GENDER": [ + "molota" + ], + "DISEASE": [ + "alijkwa'takochi", + "chukchu" + ], + "JOB": [ + "shileti", + "kumali", + "lota'c\u0308homa", + "soltalo" + ], + "PLANT": [ + "kinili" + ], + "ANIMAL": [ + "askoli", + "cheshana", + "ma'sheti", + "shani", + "tsemo'ye" + ], + "TITLE": [ + "chmes\u0308hona" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": {}, + "other_gender_swap": {}, + "en_pronoun2gender": { + "he": [ + "meploneye" + ], + "she": [ + "ic\u0308hulupa", + "molota" + ] + }, + "en_pronoun2pronoun": { + "it": [ + "ana'ye" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/ce.json b/data_tooling/pii_processing/ontology/data/ce.json new file mode 100644 index 0000000..5bfa19c --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/ce.json @@ -0,0 +1,87 @@ +{ + "ORG": [ + "\u043a\u0430\u043d\u0442\u0445\u043e", + "\u043f\u0440\u0430\u0432\u0438\u0442\u0435\u043b\u044c\u0441\u0442\u0432\u043e", + "\u0445\u0443\u0430\u043d\u0445\u044d", + "\u0441\u0438\u0439\u043b\u0430\u0445\u044c_\u0441\u043e\u0444\u0438\u043d_\u043a\u0438\u043b\u0441", + "\u043f\u0430\u0440\u0442\u0438", + "\u0446\u04cf\u0435\u043d_\u0445\u04cf\u043e\u0440\u0434", + "\u043a\u0440\u0438\u0432\u043e\u0439_\u0440\u043e\u0433" + ], + "PLANT": [ + "\u0431\u0430\u0433\u0430" + ], + "LOCATION": [ + "\u0430\u043c\u0435\u0440\u0438\u043a\u0430\u043d_\u0446\u0445\u044c\u0430\u043d\u0430\u043a\u0445\u0435\u0442\u0442\u0430_\u0448\u0442\u0430\u0442\u0430\u0448", + "\u0441\u0430\u043a\u0441\u043e\u043d\u0438_\u0430\u043d\u0445\u0430\u043b\u044c\u0442", + "\u0430\u043c\u0435\u0440\u0438\u043a\u0438\u043d_\u0446\u0445\u044c\u0430\u043d\u0430\u0442\u043e\u044c\u0445\u043d\u0430_\u0448\u0442\u0430\u0442\u0430\u0448", + "\u043a\u0430\u0431\u043e_\u0432\u0435\u0440\u0434\u0435" + ], + "PUBLIC_FIGURE": [ + "\u043f\u0451\u0442\u0440_i", + "\u043a\u043e\u043b\u0443\u043c\u0431_\u0445\u0440\u0438\u0441\u0442\u043e\u0444\u043e\u0440", + "\u0441\u0430\u043b\u0430\u0445\u044c\u0443\u0434\u0434\u0438\u043d" + ], + "JOB": [ + "\u043a\u0445\u0430\u043b\u043b\u0430\u0440\u0434\u043e\u0442\u0442\u0443\u0440\u0433", + "\u0442\u0430\u043b\u043c\u0430\u0436", + "\u043f\u0440\u0435\u0437\u0438\u0434\u0435\u043d\u0442" + ], + "RELIGION_MEMBER": [ + "\u043c\u043e\u043b\u043b\u0430" + ], + "GPE": [ + "\u0434\u0430\u0440_\u044d\u0441_\u0441\u0430\u043b\u0430\u043c", + "\u0441\u0430\u043d_\u0442\u043e\u043c\u0435" + ], + "PERSON": [ + "\u0441\u043e_\u0430" + ], + "FAC": [ + "\u0441\u0435\u043d\u0442_\u043b\u044e\u0441\u0438" + ], + "FOOD": [ + "\u043a\u044a\u0430\u0445\u044c\u043e" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "\u0439\u0438\u0448\u0430": "\u0432\u0430\u0448\u0430", + "\u0437\u0443\u0434\u0430": "\u043c\u0430\u0439\u0440\u0430" + }, + "other_gender_swap": { + "\u0430\u043b\u0430\u0440": "\u0441\u043e", + "\u0441\u043e": "\u0430\u043b\u0430\u0440" + }, + "en_pronoun2gender": { + "she": [ + "\u0437\u0443\u0434\u0430", + "\u0439\u043e\u04cf" + ] + }, + "en_pronoun2pronoun": { + "he": [ + "\u0441\u043e" + ], + "she": [ + "\u0441\u043e" + ], + "they": [ + "\u0446\u0430\u0440\u043d\u0430", + "\u0430\u043b\u0430\u0440" + ], + "it": [ + "x\u04cf\u0430\u0440\u0430" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/ceb.json b/data_tooling/pii_processing/ontology/data/ceb.json new file mode 100644 index 0000000..8611ba4 --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/ceb.json @@ -0,0 +1,714 @@ +{ + "PLANT": [ + "acer_negundo", + "cucurbita_ficifolia", + "hibiscus_syriacus", + "acanthocereus_tetragonus", + "hibiscus_mutabilis", + "brachychiton_populneus", + "glaucium_flavum", + "primula_auricula", + "robinia_hispida", + "lilium_martagon", + "lupinus_luteus", + "pyracantha", + "acer_rubrum", + "campanula_persicifolia", + "diospyros_virginiana", + "verbascum_thapsus", + "lycium_barbarum", + "parnassia", + "salvia_leucophylla", + "iris_germanica", + "lilium_philadelphicum", + "lilium_longiflorum", + "sorghum_halepense", + "veronica_beccabunga", + "liriodendron_tulipifera", + "quercus_coccinea", + "cladonia_rangiferina", + "natong", + "impatiens_walleriana", + "geranium_molle", + "dioscorea_bulbifera", + "hoya_carnosa", + "erythronium_albidum", + "viola_arvensis", + "sapindus", + "scutellaria_galericulata", + "claviceps_purpurea", + "viola_reichenbachiana", + "chimaphila_umbellata", + "philadelphus_coronarius", + "aralia_elata", + "brassica_nigra", + "eleocharis_dulcis", + "bromus_tectorum", + "helleborus_niger", + "helianthus", + "rosa_chinensis", + "lathyrus_latifolius", + "cucurbita_moschata", + "monarda_citriodora", + "solanaceae", + "anthriscus_cerefolium", + "campanula_medium", + "caryota_urens", + "quercus_kelloggii", + "viola_cornuta", + "juncus_articulatus", + "eryngium_maritimum", + "schefflera_actinophylla", + "amelanchier_bartramiana", + "pachysandra_terminalis", + "salix_babylonica", + "cyclamen_purpurascens", + "anthyllis_vulneraria", + "arctostaphylos_alpinus", + "abies_grandis", + "laurus_nobilis", + "lathyrus_odoratus", + "amanita", + "vespula_vulgaris", + "arabidopsis_thaliana", + "pilularia_globulifera", + "bertholletia_excelsa", + "adenium_obesum", + "epipremnum_aureum", + "arundo", + "sorbus_torminalis", + "achillea", + "magnolia_grandiflora", + "solanum_quito\u00ebnse", + "berteroa_incana", + "pelargonium_odoratissimum", + "colutea_arborescens", + "liparis_loeselii", + "chionanthus_virginicus", + "coprinus_comatus", + "papaver_alpinum", + "hydrangea_petiolaris", + "sinapis", + "prunus_laurocerasus", + "pachysandra_procumbens", + "allium_tuberosum", + "pennisetum_glaucum", + "amelanchier_alnifolia", + "passiflora_ligularis", + "salix_triandra", + "leucaena_leucocephala", + "silene_virginica", + "lilium_michiganense", + "cercidiphyllum_japonicum", + "atriplex_hortensis", + "vaccinium_corymbosum", + "teucrium_scorodonia", + "acer_campestre", + "berberis_nervosa", + "bletilla_striata", + "mimosa_pudica", + "papaver_somniferum", + "singkamas", + "convolvulus", + "nogal", + "carex_pseudocyperus", + "gentiana_lutea", + "mercurialis_perennis", + "matthiola_incana", + "acacia_pycnantha", + "actinidia_chinensis", + "taxus_baccata", + "saxifraga_granulata", + "valerianella_locusta", + "periploca_graeca", + "papaver", + "rhus_typhina", + "nymphaea_alba", + "silene_dioica", + "euphorbia_esula", + "phaseolus_coccineus", + "diplotaxis_tenuifolia", + "euphorbia_dentata", + "candida_albicans", + "ranunculus_ficaria", + "malope_trifida", + "senna_alata", + "schinus_terebinthifolius", + "amaryllis_belladonna", + "veronica_officinalis", + "phegopteris_connectilis", + "illicium_floridanum", + "pontederia_cordata", + "calophyllum_inophyllum", + "aconitum_lycoctonum", + "rosa_multiflora", + "prunus_cerasus", + "acer_macrophyllum", + "asclepias_purpurascens", + "acacia_dealbata", + "capsicum_baccatum", + "dianthus_caryophyllus", + "agrimonia_eupatoria", + "larix_occidentalis", + "plantago_lanceolata", + "polystichum_lonchitis", + "ononis_spinosa", + "andropogon_virginicus", + "xanthosoma_sagittifolium", + "acer_palmatum", + "thlaspi_arvense", + "agrostemma_githago", + "geranium_pratense", + "salix_viminalis", + "calvatia_gigantea", + "juniperus_virginiana", + "eriophorum_angustifolium", + "veronica_serpyllifolia", + "alstonia_scholaris", + "eucalyptus_globulus", + "cassia_fistula", + "pterospermum_acerifolium", + "platanus_occidentalis", + "passiflora_incarnata", + "clusia", + "festuca_ovina", + "quercus_ellipsoidalis", + "bromus_arvensis", + "polygala_vulgaris", + "ardisia_crenata", + "fraxinus_quadrangulata", + "veronica_peregrina", + "chaenomeles_speciosa", + "selenicereus_grandiflorus", + "citrus_aurantium", + "pelargonium_peltatum", + "reseda", + "barbarea_vulgaris", + "osmanthus_americanus", + "annona_cherimola", + "helleborus_orientalis", + "cortinarius_violaceus", + "dianthus_barbatus", + "platanus_orientalis", + "piper_longum", + "gossypium_hirsutum", + "prunus_armeniaca", + "castanea_dentata", + "liquidambar", + "nymphaea_odorata", + "urtica", + "potamogeton_crispus", + "parthenocissus_tricuspidata", + "paspalum_distichum", + "tropaeolum_minus", + "macadamia_tetraphylla", + "cucurbita_argyrosperma", + "salix_fragilis", + "amanita_muscaria", + "pterocarpus_indicus", + "corylus_americana", + "calla_palustris", + "leonurus_cardiaca", + "spergula_arvensis", + "physostegia_virginiana", + "asplenium_trichomanes", + "acer_japonicum", + "arrhenatherum_elatius", + "nicotiana_alata", + "dracocephalum", + "carissa_macrocarpa", + "populus_balsamifera", + "armeria_maritima", + "nicotiana_tabacum", + "myosotis_sylvatica", + "asclepias_verticillata", + "phyllostachys_nigra", + "astragalus_alpinus", + "quercus_variabilis", + "ulmus_americana", + "primula_acaulis", + "carex_arenaria", + "acanthus_mollis", + "stellaria_media", + "solanum_nigrum", + "calochortus_amabilis", + "abies_lasiocarpa", + "campanula_rapunculus", + "melastoma_malabathricum", + "cystopteris_montana", + "diplotaxis_muralis", + "sciadopitys_verticillata", + "geranium_robertianum", + "clematis", + "hedysarum_coronarium", + "lepista_nuda", + "hippocrepis_comosa", + "verbena_officinalis", + "prunus_domestica", + "platanus_hybrida", + "draba_verna", + "dendrocalamus_giganteus", + "tricholoma_aurantium", + "portulaca_grandiflora", + "chlorophyllum_molybdites", + "muscicapa_striata", + "prosopis_juliflora", + "acer_platanoides", + "cotoneaster_horizontalis", + "viburnum_prunifolium", + "gossypium_barbadense", + "erica_carnea", + "euphorbia_cyparissias", + "salvia_pratensis", + "delonix_regia", + "urtica_dioica", + "gymnadenia_conopsea", + "trifolium_repens", + "eugenia_uniflora", + "cortaderia_selloana", + "solanum", + "gentianella_amarella", + "ballota_nigra", + "campanula_carpatica", + "sisymbrium_officinale", + "angelica_archangelica", + "campsis_radicans", + "echinocactus_grusonii", + "medinilla_magnifica", + "corypha_umbraculifera", + "brachychiton_acerifolius", + "caragana_arborescens", + "sorbus_aucuparia", + "dianthus_chinensis", + "acer_pseudoplatanus", + "aristolochia_macrophylla", + "lotus_corniculatus", + "gymnadenia_odoratissima", + "hydrangea_arborescens", + "polyporus_squamosus", + "raphanus_raphanistrum", + "cornus_florida", + "cytisus_multiflorus", + "payod", + "amaranthus_caudatus", + "silene_latifolia", + "gymnocladus_dioica", + "botrychium_lunaria", + "fraxinus_velutina", + "anagallis_tenella", + "fagus_sylvatica", + "scleranthus_annuus", + "acrocarpus_fraxinifolius", + "salix_pentandra", + "bulogsan", + "cerastium_tomentosum", + "rubus_spectabilis", + "drosophyllum_lusitanicum", + "crataegus_laevigata", + "sinapis_arvensis", + "acer_circinatum", + "sanahorya", + "arum", + "silene_uniflora", + "dracunculus_vulgaris", + "acacia_melanoxylon", + "cyperus_papyrus", + "agrostis_canina", + "saccharomyces_cerevisiae", + "boletus_edulis", + "hydrangea_paniculata", + "campanula_trachelium", + "ranunculus_bulbosus", + "tetragonia_tetragonoides", + "erythronium_americanum", + "arenaria_serpyllifolia", + "lysimachia_vulgaris", + "daphne_cneorum", + "fraxinus_pennsylvanica", + "juglans_californica", + "campanula_rotundifolia", + "phytolacca_dioica", + "campanula_glomerata", + "lonicera_tatarica", + "dalbergia_latifolia", + "polystichum_aculeatum", + "gaultheria_procumbens", + "beta_vulgaris", + "cerastium_alpinum", + "pleurotus_ostreatus", + "pseudotsuga_menziesii", + "lithospermum_officinale", + "senna_alexandrina", + "heracleum_sphondylium", + "crataegus_aestivalis", + "drimys_winteri", + "lathyrus_sylvestris", + "marasmius_oreades", + "symphytum_officinale", + "viola_tricolor", + "viburnum_opulus", + "gentiana_acaulis", + "salvia_farinacea", + "elaeis_guineensis", + "coix_lacryma_jobi", + "erythronium_montanum", + "prunus_serrulata", + "galium_verum", + "acronicta_aceris", + "aralia_stipulata", + "cycas_circinalis", + "populus_nigra", + "nasturtium", + "ranunculus_repens", + "stellaria_holostea", + "strelitzia_reginae", + "agathis_australis", + "lemna_minor", + "larix_laricina", + "pyrola_rotundifolia", + "inga_edulis", + "cardamine_pratensis", + "piper_betle", + "allium_fistulosum", + "salix_arctica", + "phacelia_campanularia", + "alnus_glutinosa", + "cypripedium_montanum", + "erodium_texanum", + "arrhenatherum", + "annona_reticulata", + "pinus_muricata", + "paris_quadrifolia", + "phytolacca_americana", + "nicotiana_rustica", + "reseda_odorata", + "lathyrus_sativus", + "oxalis", + "veronica_arvensis", + "anthriscus_sylvestris", + "marchantia_polymorpha", + "pteridium_aquilinum", + "cinnamomum_cassia", + "panicum_capillare", + "smilax_aspera", + "salvia_sclarea", + "aristolochia_clematitis", + "catharanthus_roseus", + "cephalanthera_rubra", + "cypripedium_calceolus", + "viola_odorata", + "poa_nemoralis", + "corylus_cornuta", + "amaranthus_albus", + "arctostaphylos_uva_ursi", + "chrysanthemum", + "agrimonia", + "myrica_gale", + "vallisneria", + "holcus_mollis", + "crambe_maritima", + "erythrina_variegata", + "platanthera_chlorantha", + "rosa_banksiae", + "acer_glabrum", + "euphorbia_milii", + "begonia_tuberhybrida", + "castanea", + "physalis_peruviana", + "sambucus_ebulus", + "rubus_odoratus", + "hamamelis_virginiana", + "calystegia_sepium", + "podocarpus_latifolius", + "dicksonia_antarctica", + "magnolia", + "galium_boreale", + "ulmus_hollandica", + "nephrolepis_exaltata", + "asclepias_meadii", + "pterocarpus_macrocarpus", + "phellodendron_amurense", + "hevea_brasiliensis", + "ranunculus_aquatilis", + "polypodium_vulgare", + "bromus_secalinus", + "pinus_palustris", + "conium_maculatum", + "plantago_media", + "ranunculus_acris", + "cypripedium_reginae", + "andromeda_polifolia", + "betula_papyrifera", + "rosa_damascena", + "platanthera_bifolia", + "camellia_japonica", + "tritoma" + ], + "ANIMAL": [ + "terenura_sharpei", + "acherontia", + "apodemus", + "karag", + "monachus_schauinslandi", + "buteo", + "bulik", + "nguyonguyo", + "sambagon", + "carao", + "mingok", + "lemmus_lemmus", + "sitta_europaea", + "mirounga_leonina", + "hippotragus_niger", + "sitta_carolinensis", + "carduelis", + "pisces", + "kaka_sa_dagat", + "mantodea", + "banakon", + "pieris_brassicae", + "brachypteraciidae", + "micropterus", + "perca_flavescens", + "manok", + "gerbillus_jamesi", + "kabaw", + "kagaangan", + "prunus_tenella", + "accipiter", + "sungkod", + "pinctada_margaritifera", + "salmo_salar", + "sanicula_europaea", + "corallium_rubrum", + "martes_foina", + "ammospermophilus", + "ictiobus_niger", + "megascops", + "capreolus_capreolus", + "branta_bernicla", + "sarcophagidae", + "alle_alle", + "sitta_canadensis", + "mantis", + "tiladtilad", + "zeus_faber", + "salvelinus_fontinalis", + "gorilla_gorilla", + "martes_zibellina", + "peristediidae", + "pedunculata", + "arvicola" + ], + "FAC": [ + "arnold_schoenberg", + "saint_lucia", + "langoyanan", + "jos\u00e9_sa_nazaret" + ], + "LOCATION": [ + "plantago_lanceolata", + "estados_unidos", + "trifolium_pratense", + "dryocopus_martius", + "eryngium_maritimum", + "trifolium_repens", + "iris_pseudacorus", + "pieris_rapae", + "plantago_major", + "siyudad", + "vaccinium_oxycoccos", + "plantago_media", + "alnus_glutinosa", + "cape_of_good_hope", + "saint_lucia", + "sri_lanka", + "scutellaria_galericulata", + "pieris_brassicae", + "trifolium_dubium", + "pterocarpus_indicus", + "delonix_regia", + "kadagatang_pasipiko", + "prunus_avium" + ], + "DISEASE": [ + "tubol", + "alta_presyon", + "nanay", + "kasakit", + "estrok", + "pabanhod", + "hangga", + "kalungsi", + "pica", + "rabis", + "bukol", + "kaspa" + ], + "FOOD": [ + "citrus_aurantiifolia", + "symphytum_officinale", + "lagus", + "daucus_carota", + "vigna_unguiculata", + "capsicum", + "pamahaw", + "chile", + "pinyon" + ], + "ORG": [ + "inaleman", + "aa", + "nasa", + "schutzstaffel", + "simbahang_katoliko", + "uropa", + "kagamhanan", + "disa", + "nautilus_pompilius", + "los_angeles", + "bukid_carmelo", + "hirundo_rustica" + ], + "JOB": [ + "alkalde", + "mantutudlo", + "sakristan", + "mamiktyuray", + "maid", + "tindera", + "prosekyutor", + "estrok", + "kamikaze", + "kodaker", + "mate", + "mantatambal", + "mangungudak", + "maniniyot", + "magsusulat", + "timonel", + "litratista", + "hapsay" + ], + "GENDER": [ + "babaye", + "boy", + "maid" + ], + "PUBLIC_FIGURE": [ + "winston_churchill", + "isaac_newton", + "michael_jackson", + "galileo_galilei", + "cristobal_colon", + "jesus", + "somateria_spectabilis", + "paul_von_hindenburg", + "joseph_stalin", + "kabungol", + "oreonympha_nobilis", + "walt_disney", + "elizabeth_taylor", + "albert_speer", + "myoxus_glis", + "macaca_nemestrina", + "pedro", + "adolf_hitler", + "garfield", + "1", + "vladimir_putin", + "jacob", + "arnold_schoenberg", + "andrew_jackson", + "hannah_arendt", + "bungol", + "ronald_reagan", + "woodrow_wilson", + "el_cid", + "aquila", + "nelson_mandela", + "jacques_offenbach", + "vladimir_lenin", + "albert_einstein", + "thomas_edison" + ], + "PERSON": [ + "julius_caesar", + "boletus_edulis" + ], + "PRODUCT": [ + "echinopsis_pachanoi", + "julius_caesar", + "puhun" + ], + "SOC_ECO_CLASS": [ + "samurai", + "katilingban" + ], + "GPE": [ + "pandanus_tectorius", + "borassus_flabellifer", + "bag_ong_tugon", + "hibiscus_rosa_sinensis", + "vinh_long", + "sim\u00f3n_pedro" + ], + "LANGUAGE": [ + "linatin", + "esperanto", + "prinanses", + "tonga" + ], + "DATE": [ + "daktol" + ], + "RELIGION": [ + "islam" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "sista": "monako", + "prinsesa": "regulus", + "naja": "adik", + "babaye": "human", + "boy": "babaye" + }, + "other_gender_swap": {}, + "en_pronoun2gender": { + "they": [ + "bakla", + "bayot" + ], + "he": [ + "human", + "boy" + ], + "she": [ + "lola", + "maid", + "babaye" + ] + }, + "en_pronoun2pronoun": { + "he": [ + "siya" + ], + "she": [ + "siya" + ], + "it": [ + "tyto" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/chk.json b/data_tooling/pii_processing/ontology/data/chk.json new file mode 100644 index 0000000..9729150 --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/chk.json @@ -0,0 +1,47 @@ +{ + "LOCATION": [ + "kinisou" + ], + "ORG": [ + "un" + ], + "GENDER": [ + "nemin" + ], + "JOB": [ + "nakkich" + ], + "PERSON_PRONOUN": [ + "we", + "me" + ], + "OTHER_PRONOUN": [ + "it" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": {}, + "other_gender_swap": {}, + "en_pronoun2gender": { + "she": [ + "feefin", + "nemin", + "awewe" + ] + }, + "en_pronoun2pronoun": { + "it": [ + "it" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/chl.json b/data_tooling/pii_processing/ontology/data/chl.json new file mode 100644 index 0000000..613b883 --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/chl.json @@ -0,0 +1,37 @@ +{ + "ANIMAL": [ + "hunal" + ], + "FOOD": [ + "tevat" + ], + "DISEASE": [ + "kukul" + ], + "PLANT": [ + "chivnish" + ], + "GENDER": [ + "nichill" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": {}, + "other_gender_swap": {}, + "en_pronoun2gender": { + "she": [ + "nichill" + ] + }, + "en_pronoun2pronoun": {}, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/cho.json b/data_tooling/pii_processing/ontology/data/cho.json new file mode 100644 index 0000000..2788729 --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/cho.json @@ -0,0 +1,38 @@ +{ + "ORG": [ + "sa_hohchifo_yat" + ], + "PUBLIC_FIGURE": [ + "chis\u1ea1s" + ], + "ANIMAL": [ + "chinisa", + "sheki" + ], + "JOB": [ + "hoponi" + ], + "LOCATION": [ + "yakok\u00ed" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": {}, + "other_gender_swap": {}, + "en_pronoun2gender": { + "she": [ + "ohoyo" + ] + }, + "en_pronoun2pronoun": {}, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/cic.json b/data_tooling/pii_processing/ontology/data/cic.json new file mode 100644 index 0000000..77348d5 --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/cic.json @@ -0,0 +1,22 @@ +{ + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": {}, + "other_gender_swap": {}, + "en_pronoun2gender": { + "she": [ + "ihoo" + ] + }, + "en_pronoun2pronoun": {}, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/cim.json b/data_tooling/pii_processing/ontology/data/cim.json new file mode 100644 index 0000000..a1e542e --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/cim.json @@ -0,0 +1,25 @@ +{ + "PERSON_PRONOUN": [ + "dain" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": {}, + "other_gender_swap": {}, + "en_pronoun2gender": { + "she": [ + "b\u00e0ip" + ] + }, + "en_pronoun2pronoun": {}, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/cjs.json b/data_tooling/pii_processing/ontology/data/cjs.json new file mode 100644 index 0000000..85e12ef --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/cjs.json @@ -0,0 +1,42 @@ +{ + "PERSON_PRONOUN": [ + "\u043e\u043b" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "\u044d\u043d\u0435": "\u0430\u0447\u0430", + "\u0438\u0447\u0435": "\u0430\u0447\u0430" + }, + "other_gender_swap": { + "\u044b\u043b\u0430\u0440": "\u043e\u043b", + "\u043e\u043b": "\u044b\u043b\u0430\u0440" + }, + "en_pronoun2gender": { + "he": [ + "\u0430\u0447\u0430", + "\u043e\u043e\u043b" + ] + }, + "en_pronoun2pronoun": { + "he": [ + "\u043e\u043b" + ], + "she": [ + "\u043e\u043b" + ], + "they": [ + "\u044b\u043b\u0430\u0440" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/co.json b/data_tooling/pii_processing/ontology/data/co.json new file mode 100644 index 0000000..894d5a3 --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/co.json @@ -0,0 +1,103 @@ +{ + "GENDER": [ + "lonna", + "ronna" + ], + "PLANT": [ + "bardana", + "melissa", + "carotta", + "sorbu", + "susina", + "castagnu", + "veccia", + "pinu", + "belladonna", + "vitalba", + "lattuca" + ], + "DISEASE": [ + "gratt\u00e0", + "firita", + "mursic\u00e0", + "cacarella", + "forfula", + "vaccina", + "merre" + ], + "JOB": [ + "muratore", + "mammana", + "scultore", + "pastore" + ], + "PERSON": [ + "giuconda", + "san_petru" + ], + "ORG": [ + "core", + "mi_chjamu", + "guvernu" + ], + "LANGUAGE": [ + "navajo" + ], + "FOOD": [ + "farina" + ], + "ANIMAL": [ + "malacedda", + "corbu", + "ciocciu", + "gattu" + ], + "RELIGION": [ + "islam" + ], + "PUBLIC_FIGURE": [ + "sperenza" + ], + "RELIGION_MEMBER": [ + "fratellu", + "frateddu" + ], + "LOCATION": [ + "capu_verde" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "zia": "ziu", + "lonna": "omu", + "femina": "omu", + "ronna": "omu" + }, + "other_gender_swap": {}, + "en_pronoun2gender": { + "he": [ + "omu" + ], + "she": [ + "lonna", + "ronna", + "femina" + ] + }, + "en_pronoun2pronoun": { + "it": [ + "essa", + "stu" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/cop.json b/data_tooling/pii_processing/ontology/data/cop.json new file mode 100644 index 0000000..e5ab1ae --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/cop.json @@ -0,0 +1,89 @@ +{ + "ORG": [ + "\u2c9d\u2c89\u2c9b\u2c9f\u2c9b", + "\u2c99\u2c89\u2c9b\u2ca7\u2c9f\u2ca9\u2cb1\u2c93" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "\u2ca7\u2c89\u2ca5": "\u2ca1\u2c89\u03e5", + "\u2ca1\u2c89\u2ca5": "\u2c9b\u2c89\u03e5", + "\u2c9b\u2c89\u2ca5": "\u2ca1\u2c89\u03e5", + "\u2c9b\u2c9f\u2ca9\u2ca5": "\u2c91\u2cb1\u2c9f\u2ca9", + "\u2ca1\u2cb1\u2ca5": "\u2cab\u2cb1\u2c9f\u2ca9", + "\u2ca7\u2cb1\u2ca5": "\u2c9b\u2c9f\u2ca9\u2c9f\u2ca9", + "\u2c91\u2cb1\u2ca5": "\u2cab\u2cb1\u2c9f\u2ca9", + "\u2cab\u2cb1\u2ca5": "\u2cab\u2cb1\u2c9f\u2ca9", + "\u2c99\u2c81\u2ca9": "\u2c89\u2c93\u2cb1\u2ca7", + "\u2c99\u2c81\u2c81\u2ca9": "\u2c93\u2c9f\u03ef", + "\u2ca3\u2ca3\u2cb1": "\u2c9f\u2ca9\u2ca3\u2c9f", + "\u2ca5\u2cb1\u2c9b\u2c89": "\u2ca5\u2c9f\u2c9b", + "\u03e9\u2c93\u2c99\u2c89": "\u03e9\u2c89\u2c93", + "\u2ca5\u03e9\u2c93\u2c99\u2c89": "\u03e9\u2c89\u2c93" + }, + "other_gender_swap": { + "\u2c9b\u2c9f\u2ca9": "\u2ca1\u2c89\u2ca5", + "\u2ca7\u2c9f\u2ca9": "\u2ca1\u2c89\u2ca5", + "\u2ca1\u2c9f\u2ca9": "\u2c9b\u2c89\u2ca5", + "\u2ca1\u2cb1\u2c9f\u2ca9": "\u2c9b\u2c9f\u2ca9\u2ca5", + "\u2ca7\u2cb1\u2c9f\u2ca9": "\u2ca1\u2cb1\u2ca5", + "\u2cab\u2cb1\u2c9f\u2ca9": "\u2cab\u2cb1\u2ca5", + "\u2c9b\u2c9f\u2ca9\u2c9f\u2ca9": "\u2ca1\u2cb1\u2ca5", + "\u2c91\u2cb1\u2c9f\u2ca9": "\u2c91\u2cb1\u2ca5", + "\u2ca7\u2c89\u03e5": "\u2ca7\u2cb1\u2c9f\u2ca9", + "\u2ca1\u2c89\u03e5": "\u2ca1\u2cb1\u2c9f\u2ca9", + "\u2c9b\u2c89\u03e5": "\u2ca7\u2cb1\u2c9f\u2ca9", + "\u2ca7\u2c89\u2ca5": "\u2ca1\u2c9f\u2ca9", + "\u2ca1\u2c89\u2ca5": "\u2ca7\u2c9f\u2ca9", + "\u2c9b\u2c89\u2ca5": "\u2ca1\u2c9f\u2ca9", + "\u2c9b\u2c9f\u2ca9\u2ca5": "\u2ca7\u2cb1\u2c9f\u2ca9", + "\u2ca1\u2cb1\u2ca5": "\u2ca1\u2cb1\u2c9f\u2ca9", + "\u2ca7\u2cb1\u2ca5": "\u2c91\u2cb1\u2c9f\u2ca9", + "\u2c91\u2cb1\u2ca5": "\u2c91\u2cb1\u2c9f\u2ca9", + "\u2cab\u2cb1\u2ca5": "\u2c9b\u2c9f\u2ca9\u2c9f\u2ca9" + }, + "en_pronoun2gender": { + "she": [ + "\u03e3\u2c89\u2c89\u2ca3\u2c89", + "\u2ca5\u03e9\u2c93\u2c99\u2c89", + "\u03e3\u2c89\u2ca3\u2c93" + ] + }, + "en_pronoun2pronoun": { + "he": [ + "\u2ca1\u2c89\u03e5", + "\u2ca7\u2c89\u03e5", + "\u2c9b\u2c89\u03e5" + ], + "she": [ + "\u2cab\u2cb1\u2ca5", + "\u2ca1\u2c89\u2ca5", + "\u2ca7\u2cb1\u2ca5", + "\u2c9b\u2c9f\u2ca9\u2ca5", + "\u2ca1\u2cb1\u2ca5", + "\u2ca7\u2c89\u2ca5", + "\u2c91\u2cb1\u2ca5", + "\u2c9b\u2c89\u2ca5" + ], + "they": [ + "\u2c9b\u2c9f\u2ca9", + "\u2c9b\u2c9f\u2ca9\u2c9f\u2ca9", + "\u2ca7\u2c9f\u2ca9", + "\u2ca1\u2c9f\u2ca9", + "\u2ca1\u2cb1\u2c9f\u2ca9", + "\u2ca7\u2cb1\u2c9f\u2ca9", + "\u2c91\u2cb1\u2c9f\u2ca9", + "\u2cab\u2cb1\u2c9f\u2ca9" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/crh.json b/data_tooling/pii_processing/ontology/data/crh.json new file mode 100644 index 0000000..ab9120a --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/crh.json @@ -0,0 +1,148 @@ +{ + "JOB": [ + "saniye", + "komandan", + "ressam", + "minder", + "para", + "tefti\u015f\u00e7i", + "kitaphaneci", + "kurator", + "mustaqil", + "tornac\u0131", + "terciman" + ], + "LANGUAGE": [ + "ermeni" + ], + "ORG": [ + "a\u015f_tatl\u0131_olsun", + "batalyon", + "a\u015f_olsun", + "mektep", + "iptidaiy_mektep", + "maarif", + "saq\u0131z", + "a\u015f_bols\u0131n", + "siyasiy_f\u0131rqa" + ], + "ANIMAL": [ + "savusqan", + "muratqu\u015f", + "baqa", + "atmaca" + ], + "PUBLIC_FIGURE": [ + "frenk", + "e", + "mamet", + "o" + ], + "DISEASE": [ + "yuqu", + "tutuqlanmaq", + "para", + "materializm", + "hamilelik" + ], + "PERSON_PRONOUN": [ + "bizim", + "seni\u00f1" + ], + "GENDER": [ + "men", + "boy", + "qad\u0131n" + ], + "PLANT": [ + "qap\u0131sta", + "markof" + ], + "LOCATION": [ + "felemenk" + ], + "GPE": [ + "aq_alt\u0131n" + ], + "RACE": [ + "frans\u0131z" + ], + "FOOD": [ + "dondurma", + "salca" + ], + "POLITICAL_PARTY": [ + "f\u0131rqa" + ], + "FAC": [ + "ba\u015flan\u011f\u0131\u00e7_mektep", + "basseyn" + ], + "QUANTITY": [ + "on_bi\u00f1" + ], + "DATE": [ + "er_\u015feyden_evel" + ], + "OTHER_PRONOUN": [ + "it" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "siya": "elli", + "abla": "kad\u00e2", + "apay": "aqay", + "apaqay": "qoca", + "bike": "ki\u015fi", + "qad\u0131n": "ki\u015fi", + "boy": "q\u0131z", + "o\u011flan": "q\u0131z" + }, + "other_gender_swap": { + "eali": "siya", + "olar": "siya", + "siya": "olar", + "elli": "eali" + }, + "en_pronoun2gender": { + "he": [ + "ki\u015fi", + "o\u011flan", + "boy" + ], + "she": [ + "abla", + "q\u0131z", + "bike", + "qad\u0131n", + "di\u015fi" + ] + }, + "en_pronoun2pronoun": { + "he": [ + "siya", + "elli" + ], + "she": [ + "siya" + ], + "they": [ + "olar", + "eali" + ], + "it": [ + "it" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/cs.json b/data_tooling/pii_processing/ontology/data/cs.json new file mode 100644 index 0000000..bdc0396 --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/cs.json @@ -0,0 +1,2533 @@ +{ + "DISEASE": [ + "ka\u0161tan", + "kornat\u011bn\u00ed", + "hydrocephalus", + "sars", + "kraj\u00edc", + "tinitus", + "potence", + "hladov\u011bt", + "lacerace", + "p\u0159edkus", + "anestezie", + "kachexie", + "tachykardie", + "kretenismus", + "parest\u00e9zie", + "deviace", + "r\u016f\u017eice", + "souchotiny", + "cyan\u00f3za", + "anthrax", + "chill", + "paraplegie", + "als", + "gumma", + "pohlazen\u00ed", + "listeri\u00f3za", + "oftalmopedie", + "ka\u0161tanov\u00fd", + "bolest", + "kolika", + "lipid\u00f3za", + "sten\u00f3za", + "salmonel\u00f3za", + "chor\u00fd", + "lump", + "barvoslepost", + "fotofobie", + "skotom", + "pl\u00edse\u0148_bramborov\u00e1", + "transpozice", + "the_bends", + "topo\u0159en\u00ed", + "chudokrevnost", + "psychopatie", + "ka\u0161tanovn\u00edk", + "struma", + "hladit", + "paratyfus", + "ms", + "rachitida", + "kalcifikace", + "jedovatec_ko\u0159enuj\u00edc\u00ed", + "intertrigo", + "dalekozrakost", + "podv\u00fd\u017eiva", + "thanatofobie", + "kr\u00e1tkozrakost", + "hydrocefalus", + "z\u00e1vra\u0165", + "demence", + "p\u0159eh\u0159\u00e1t\u00ed", + "dusit", + "proktitida", + "presbyopie", + "talas\u00e9mie", + "b\u0159ezost", + "cervicitida", + "kurd\u011bje", + "brucel\u00f3za", + "pl\u00e1tek", + "zahlcen\u00ed", + "koron\u00e1rn\u00ed", + "beri_beri", + "aura_at_college_park", + "urosepse", + "herpes_simplex_virus", + "nahromad\u011bn\u00ed", + "katarakta", + "spalni\u010dky", + "nachlazen\u00ed", + "z\u00e1vislost", + "plynovat", + "steh", + "delirium", + "vozh\u0159ivka", + "poliomyelitida", + "progerie", + "cukrovka", + "dalekozrak\u00fd", + "mastit", + "habituace", + "pakostnice", + "lockjaw", + "k\u0159ivice", + "vodnatelnost", + "bodnout", + "gimp", + "grafi\u00f3za", + "herpes", + "krutihlav", + "papilom", + "sigmatismus", + "katalepsie", + "smart", + "klaustrofobie", + "marasmus", + "ed", + "rakovina", + "pica", + "polin\u00f3za", + "cachexie", + "tracheitida", + "r\u016f\u017eovka", + "chondrosarkom", + "preeklampsie", + "ochrnut\u00ed", + "fluor\u00f3za", + "sensation", + "faryngitida", + "opilost", + "hore\u010dka", + "kolitida", + "epidermolysis_bullosa", + "pain", + "teratom", + "gravidita", + "zard\u011bnky", + "purpura", + "nespavost", + "sp\u00e1lenina", + "otupen\u00ed", + "stigmata", + "kausalgie", + "podlitina", + "sp\u00e1len\u00ed", + "trachom", + "plynatost", + "pellagra", + "herniace", + "autoimunita", + "podvrtnut\u00ed", + "chopn", + "mi", + "silik\u00f3za", + "puch\u00fd\u0159", + "mezoteliom", + "sting", + "bradykardie", + "hydronefr\u00f3za", + "malomocenstv\u00ed", + "sp\u00e1la", + "materialismus", + "trauma", + "prohlube\u0148", + "lichen_planus", + "kuru", + "paradent\u00f3za", + "nemoc", + "virus_tab\u00e1kov\u00e9_mozaiky", + "tyroiditida", + "kachektizace", + "the_hives", + "choroba", + "dengue", + "gangr\u00e9na", + "mastitida", + "daktylosymf\u00fdza", + "schistosom\u00f3za", + "parestezie", + "kolaps", + "salmonella", + "krup", + "plyn" + ], + "PUBLIC_FIGURE": [ + "lawrence_durrell", + "henry_cavendish", + "matthew_arnold", + "benjamin_franklin", + "martin_buber", + "akira_kurosawa", + "melanie_kleinov\u00e1", + "jedno", + "noah_webster", + "jean_genet", + "john_knox", + "roger_williams", + "giovanni_boccaccio", + "rosa_parksov\u00e1", + "cornelius_vanderbilt", + "rudolf_steiner", + "thomas_wolfe", + "ji\u0159\u00ed", + "thomas_bayes", + "johann_bernoulli", + "max_bruch", + "leonard_bernstein", + "che_guevara", + "georges_simenon", + "c", + "jeden", + "maria_callas", + "william_walton", + "henrik_ibsen", + "william_gladstone", + "sergej_rachmaninov", + "franz_werfel", + "marcello_malpighi", + "peter_lorre", + "dalajl\u00e1ma", + "david_livingstone", + "eduard_buchner", + "john_herschel", + "andrzej_wajda", + "jan_van_eyck", + "lawliet", + "anton\u00edn", + "carl_rogers", + "george_balanchine", + "brig\u00e1dn\u00ed_gener\u00e1l", + "richard_burton", + "douglas_macarthur", + "j_edgar_hoover", + "thomas_reid", + "john_jacob_astor", + "otto_frisch", + "winston_churchill", + "gustav", + "johannes_diderik_van_der_waals", + "dvojka", + "b", + "kate\u0159ina_howardov\u00e1", + "conrad_aiken", + "karl_landsteiner", + "paul_mccartney", + "richard_smalley", + "terry_pratchett", + "k", + "kurie", + "stephen_king", + "francis_crick", + "sherry", + "joseph_greenberg", + "isaac_newton", + "alfred_eisenstaedt", + "victor_hugo", + "joseph_smith", + "edwin_hubble", + "colette", + "milton_friedman", + "edward_gibbon", + "jefferson_davis", + "george_stephenson", + "john_glenn", + "john_webster", + "john_davis", + "george_harrison", + "marie_antoinetta", + "george_orwell", + "arthur_koestler", + "richard_wagner", + "williams", + "thornton_wilder", + "pancho_villa", + "jana_seymourov\u00e1", + "francis_galton", + "michael_jackson", + "carl_sandburg", + "thomas_hobbes", + "edward_weston", + "el_greco", + "samuel_beckett", + "ingrid_bergmanov\u00e1", + "david", + "galileo_galilei", + "john_donne", + "robert_koch", + "i_m_pei", + "joseph_goebbels", + "george_eastman", + "john_steinbeck", + "erich_mendelsohn", + "edmund_hillary", + "vincent_van_gogh", + "martina_navr\u00e1tilov\u00e1", + "john_ruskin", + "robert_burns", + "thomas_paine", + "bari", + "liliuokalani", + "francis_beaumont", + "edvard", + "steven_weinberg", + "p", + "hans_fischer", + "emiliano_zapata", + "karl_barth", + "willem_einthoven", + "bernard_malamud", + "samuel_johnson", + "allen_iverson", + "giuseppe_verdi", + "walter_lippmann", + "e", + "karl_jaspers", + "tom\u00e1\u0161", + "johannes_wilhelm_geiger", + "konrad_adenauer", + "jind\u0159ich", + "norbert_wiener", + "mark_rothko", + "maurice_chevalier", + "gottlieb_daimler", + "frank_sinatra", + "nietzscheov\u00e1", + "abel_tasman", + "henri_becquerel", + "henri_matisse", + "bertram_brockhouse", + "louis_pasteur", + "richard_strauss", + "theodosius_i", + "hugo_grotius", + "mahalia_jackson", + "ben_shahn", + "john_ford", + "alphonse_bertillon", + "j_b_s_haldane", + "saladin", + "sarah_bernhardt", + "v", + "philip_marlowe", + "luigi_pirandello", + "hank_williams", + "james_thurber", + "charles_de_gaulle", + "paul_von_hindenburg", + "y", + "henry_moore", + "holden", + "ralph_bunche", + "rudolf_bultmann", + "anna_pavlovov\u00e1", + "charles_lindbergh", + "vincenzo_bellini", + "samuel_barber", + "tobias_smollett", + "f", + "john_jay", + "ludwig_wittgenstein", + "august_strindberg", + "stalin", + "thomas_mann", + "william_ockham", + "charles_goodyear", + "dante_alighieri", + "james_tobin", + "john_irving", + "samuel_de_champlain", + "giacomo_puccini", + "edward_fitzgerald", + "fridtjof_nansen", + "louis_braille", + "herbert_marcuse", + "mungo_park", + "paul_verlaine", + "q", + "scribes", + "olga_korbutov\u00e1", + "robert_johnson", + "james_dean", + "robert", + "marie_tussaud", + "roger_bannister", + "theodor_schwann", + "alessandro_manzoni", + "joseph_priestley", + "nicolas_poussin", + "andrea_mantegna", + "elizabeth_taylorov\u00e1", + "joseph_pulitzer", + "charles_schulz", + "jim_corbett", + "james_naismith", + "oscar_wilde", + "philip_roth", + "henry", + "lawrence", + "richard_trevithick", + "margaret_courtov\u00e1", + "heinrich_schliemann", + "eli_whitney", + "jonathan_chapman", + "glenn_curtiss", + "don_quijote", + "laurence_olivier", + "christiaan_eijkman", + "adolf_eichmann", + "francis_bacon", + "pete_seeger", + "joseph_heller", + "a", + "morris", + "norman_rockwell", + "james_brown", + "william_hogarth", + "margaret_sangerov\u00e1", + "charles_baudelaire", + "luigi_cherubini", + "david_ricardo", + "mary_leakey", + "charlie_parker", + "z", + "immanuel_kant", + "richard_gatling", + "james_franck", + "william_crookes", + "nellie_bly", + "weber", + "lewis", + "alexandre_yersin", + "jane_goodallov\u00e1", + "stephen_leacock", + "albert_schweitzer", + "jane_jacobsov\u00e1", + "john_harvard", + "johann_friedrich_herbart", + "titus", + "johannes_kepler", + "most", + "david_hartley", + "max_planck", + "aletta_jacobsov\u00e1", + "william_blake", + "julio_iglesias", + "john_bardeen", + "arthur", + "sarah_vaughan", + "nietzsche", + "ella_fitzgeraldov\u00e1", + "william_byrd", + "william_henry", + "scott_joplin", + "carl_lewis", + "george_vancouver", + "helen_kellerov\u00e1", + "canberra", + "michail_kalinin", + "elias_canetti", + "edward_jenner", + "marie_magdalena", + "oliver_hardy", + "cole_porter", + "dva", + "benjamin_west", + "jean_luc_godard", + "konstantin", + "graham_greene", + "frans_hals", + "lars_onsager", + "david_riesman", + "john_walker", + "william_herschel", + "joseph_black", + "arthur_rubinstein", + "niels_bohr", + "henry_fielding", + "bertrand_russell", + "michael_faraday", + "john_d_rockefeller", + "anthony_burgess", + "jan_tinbergen", + "podnikavec", + "robert_venturi", + "irving_berlin", + "rudolf_diesel", + "walt_disney", + "ben_jonson", + "va\u0159e\u010dka", + "anna_kurnikovov\u00e1", + "gabriel_lippmann", + "steve_reich", + "lee", + "benny_goodman", + "ted_williams", + "friedrich_engels", + "charles_laughton", + "charlotta_cordayov\u00e1", + "michelangel\u016fv_david", + "gustav_mahler", + "ed_sullivan", + "phil_collins", + "robert_redford", + "jean_giraudoux", + "ian_fleming", + "richard_feynman", + "wolfgang_pauli", + "theodore_dreiser", + "katharine_hepburnov\u00e1", + "theodor_mommsen", + "marcel_proust", + "jedna", + "homo_heidelbergensis", + "paul_hindemith", + "thomas_chippendale", + "paul_robeson", + "arnold", + "john_dowland", + "william_golding", + "robert_motherwell", + "william_caxton", + "john_milton", + "mlyn\u00e1\u0159ka", + "kominictv\u00ed", + "von_willebrand\u016fv_faktor", + "samuel_adams", + "albert_speer", + "george_brummell", + "george_gershwin", + "alberto_giacometti", + "vav\u0159inec", + "frank_whittle", + "alfred_nobel", + "jesse_owens", + "marco_polo", + "thatcherov\u00e1", + "john_fletcher", + "caravaggio", + "charlie_watts", + "m", + "anna_boleynov\u00e1", + "marcel_marceau", + "pan\u010dhenlama", + "allen_ginsberg", + "daniel_bernoulli", + "guillaume_apollinaire", + "antoine_watteau", + "pablo_casals", + "joseph_henry", + "henri_bergson", + "michail_bary\u0161nikov", + "josef_hoffmann", + "boris_karloff", + "pierre_corneille", + "patrick_white", + "hans_christian_andersen", + "william_morris", + "cary_grant", + "thomas", + "pieter_zeeman", + "glenn_miller", + "pablo_picasso", + "natalie_wood", + "l_ron_hubbard", + "thomas_moore", + "hideki_jukawa", + "osman_i", + "kurt_weill", + "li_\u010deng_tao", + "otto_hahn", + "lester_young", + "john_marshall", + "christiaan_huygens", + "hector_berlioz", + "paul_simon", + "komin\u00edk", + "claudio_monteverdi", + "thomas_morgan", + "john_galsworthy", + "robert_robinson", + "o", + "one", + "adam_smith", + "william_james", + "kov\u00e1\u0159", + "u", + "henry_miller", + "karl_marx", + "friedrich_nietzsche", + "i", + "john_wesley", + "sandro_botticelli", + "nikola_tesla", + "al_capone", + "charles_barkley", + "billy_graham", + "robert_schumann", + "mel_gibson", + "le_corbusier", + "carlo_goldoni", + "john_locke", + "alexis_carrel", + "leonhard", + "lesn\u00edk", + "st\u0159\u00edzl\u00edk", + "joseph_marie_jacquard", + "henry_james", + "dorothea_langeov\u00e1", + "paul_dukas", + "leonard_bloomfield", + "jean_piaget", + "henri_rousseau", + "paul_tillich", + "hilaire_belloc", + "fajfka", + "frank_stella", + "robert_southey", + "walt_whitman", + "william_wyler", + "john_osborne", + "colin_powell", + "ludwig_boltzmann", + "carl_nielsen", + "leopold_kronecker", + "richard_wright", + "a_tak_d\u00e1le", + "benjamin_thompson", + "adolf_hitler", + "fritz_haber", + "peter_behrens", + "alfred_stieglitz", + "joseph_haydn", + "jedni\u010dka", + "garfield", + "george_boole", + "buffalo_bill", + "edvard_grieg", + "robert_boyle", + "alan_paton", + "1", + "cordell_hull", + "james_wilson", + "x", + "vladimir_putin", + "giuseppe_mazzini", + "jim_thorpe", + "hertz", + "h", + "laurence_sterne", + "christopher_isherwood", + "fritz_kreisler", + "anne_hathaway", + "don_budge", + "baldwin", + "clarence_darrow", + "charles_lamb", + "g", + "padavka", + "arthur_schopenhauer", + "thomas_dekker", + "james_cagney", + "johns_hopkins", + "wanda_landowska", + "martin_heidegger", + "hans_eysenck", + "arnold_schoenberg", + "r", + "george_lucas", + "andrew_jackson", + "louis_armstrong", + "steven_spielberg", + "jean_monnet", + "d_w_griffith", + "robert_fulton", + "thomas_hardy", + "eddie_rickenbacker", + "thomas_gainsborough", + "giuseppe_garibaldi", + "philip_warren_anderson", + "robert_brown", + "barbra_streisandov\u00e1", + "thomas_carlyle", + "donald_barthelme", + "william_tyndale", + "bobby_fischer", + "johannes_gutenberg", + "d", + "giambattista_marino", + "gaetano_donizetti", + "william_faulkner", + "flavius_iosephus", + "amerigo_vespucci", + "pierre_boulez", + "hans_adolf_krebs", + "girolamo_savonarola", + "francis_poulenc", + "james_ussher", + "john_constable", + "james_mill", + "john_ciardi", + "putin", + "matthew_flinders", + "joseph_campbell", + "\u0436", + "jean_de_la_fontaine", + "robert_hooke", + "o_henry", + "hoffa", + "coleman_hawkins", + "\u0159eka_svat\u00e9ho_vav\u0159ince", + "peter_sellers", + "homo_rhodesiensis", + "charles_fourier", + "gertrude_steinov\u00e1", + "husajn", + "marcus_aurelius", + "peter_o'toole", + "joseph_conrad", + "edmund_halley", + "peter_paul_rubens", + "jim_morrison", + "jules_verne", + "paul_newman", + "george_meredith", + "dvoje", + "woody_herman", + "josef_albers", + "jackson_pollock", + "john_lennon", + "andrea_palladio", + "bob_woodward", + "charlie_chaplin", + "thomas_malory", + "lea", + "john_brown", + "al_jolson", + "mlyn\u00e1\u0159", + "hugo_junkers", + "lillian_hellman", + "thomas_merton", + "asa_gray", + "antonio_stradivari", + "c_s_forester", + "maximianus", + "robinson_jeffers", + "dalajlama", + "miles_davis", + "st\u0159\u00edzl\u00edkovit\u00ed", + "jesse_jackson", + "willa_cather", + "bozen", + "stanley_kubrick", + "siamsk\u00e1_dvoj\u010data", + "john_huston", + "william_gilbert", + "james_watt", + "krysa\u0159", + "jonathan_edwards", + "ronald_reagan", + "do_punt\u00edku", + "helmut_schmidt", + "frederick_douglass", + "david_hilbert", + "wilhelm_reich", + "roman_jakobson", + "lucille_ballov\u00e1", + "oliver_cromwell", + "lionel_hampton", + "martin_luther_king", + "william_wordsworth", + "rex_harrison", + "s", + "jednatel", + "woodrow_wilson", + "katherine_mansfieldov\u00e1", + "marcus_antonius", + "st_louis", + "richard_rodgers", + "john_dryden", + "jim_henson", + "frank", + "b\u00e9la_lugosi", + "ernest_hemingway", + "george_westinghouse", + "jacques_charles", + "eero_saarinen", + "arthur_miller", + "nelson_mandela", + "heinrich_himmler", + "al_gore", + "john_rutledge", + "hans_bethe", + "cesare_borgia", + "peter_minnewitt", + "margaret_mitchellov\u00e1", + "roald_amundsen", + "sherwood_anderson", + "richard_leakey", + "marie_magdalsk\u00e1", + "alfred_korzybski", + "c_a", + "charles_dickens", + "jack_robinson", + "alois_senefelder", + "george_enescu", + "jacques_offenbach", + "hannah_arendtov\u00e1", + "leakey", + "george_stevens", + "federico_fellini", + "bessie_smith", + "willy_brandt", + "charles_wilkes", + "francisco_pizarro", + "francisco_franco", + "jackie_robinson", + "bernardo_bertolucci", + "jan_steen", + "powell", + "hans_arp", + "andrew_carnegie", + "odoln\u00fd", + "franz_schubert", + "johnny_cash", + "joseph_mccarthy", + "alfred_kastler", + "mick_jagger", + "nietzschov\u00e1", + "georges_cuvier", + "william_harvey", + "walter_scott", + "marie_stopesov\u00e1", + "kate\u0159ina_aragonsk\u00e1", + "august_von_wassermann", + "jenner", + "sam_houston", + "robert_peary", + "kry\u0161tof_kolumbus", + "robert_browning", + "ralph_ellison", + "john_bunyan", + "jonathan_swift", + "walter_gropius", + "albert_einstein", + "claude_bernard", + "raymond_chandler", + "henry_purcell", + "t", + "thatcher", + "wilhelm_ostwald" + ], + "JOB": [ + "hostitelka", + "radn\u00ed", + "stevardka", + "lesn\u00edk", + "baste\u0159i", + "letu\u0161ka", + "po\u0159adatel", + "ladi\u010d", + "guru", + "thatcherov\u00e1", + "encyklopedista", + "jednatel", + "konzul", + "soumra\u010dn\u00edkovit\u00ed", + "hydrolog", + "poradce", + "hajn\u00fd", + "pradlena", + "strejc", + "pl\u00e1nova\u010d", + "mikrobiolog", + "make", + "herold", + "imunolog", + "starostka", + "hasi\u010d", + "soukrom\u00fd", + "u\u010dinit", + "p\u0159edn\u00e1\u0161ej\u00edc\u00ed", + "autorka", + "funkcion\u00e1\u0159", + "domovn\u00edk", + "d\u0159evorubec", + "bagr", + "ko\u017eeluh", + "bedn\u00e1\u0159", + "feldmar\u0161\u00e1lek", + "sexton", + "p\u0159edseda", + "don", + "dvo\u0159an", + "brank\u00e1\u0159", + "p\u0159edsedkyn\u011b", + "slovn\u00edk\u00e1\u0159", + "past\u00fd\u0159ka", + "sb\u011bratel", + "kapr\u00e1l", + "dermatolog", + "kronik\u00e1\u0159", + "the_police", + "sklen\u00e1\u0159", + "biskup", + "celn\u00edk", + "palc\u00e1t", + "listono\u0161", + "konzultant", + "harpun\u00e1\u0159", + "asistent", + "hematolog", + "pastevec", + "plav\u010d\u00edk", + "router", + "cukr\u00e1\u0159", + "lokaj", + "str\u00e1\u017e", + "thatcher", + "bodyguard", + "ministr", + "tren\u00e9r", + "kamen\u00edk", + "socha\u0159", + "str\u00e1nka", + "topi\u010d", + "feldmar\u0161\u00e1l", + "krysa", + "krej\u010d\u00ed", + "pokojsk\u00e1", + "st\u00e1vkokaz", + "v\u00e1le\u010dn\u00edk", + "str\u00e1\u017ece", + "klemp\u00ed\u0159", + "poku\u0161itel", + "peka\u0159", + "spole\u010dn\u00edk", + "kormideln\u00edk", + "gran\u00e1tn\u00edk", + "v\u00fdrobce", + "\u0161enk", + "rozmno\u017eenina", + "p\u0159ed\u00e1k", + "podd\u016fstojn\u00edk", + "stript\u00e9rka", + "obchodnice", + "dru\u017ei\u010dka", + "kamikaze", + "holi\u010d", + "tane\u010dn\u00edk", + "the_advocate", + "kol\u00e1\u0159stv\u00ed", + "c\u00e9vn\u00ed_mozkov\u00e1_p\u0159\u00edhoda", + "kancl\u00e9\u0159", + "freelancer", + "domovnice", + "hospodyn\u011b", + "namydlit", + "here\u010dka", + "ml\u00e9ka\u0159", + "koumes", + "kardiochirurg", + "the_guardian", + "trev\u00edr", + "obchodn\u00edk", + "gastroenterolog", + "pad\u011blatel", + "stevard", + "kol\u00e1\u0159", + "pohlazen\u00ed", + "the_herald", + "herec", + "kulometn\u00edk", + "n\u00e1vrh\u00e1\u0159", + "brad\u00fd\u0159", + "stomatolog", + "obecn\u00fd", + "stript\u00e9r", + "mate", + "zuba\u0159ka", + "l\u00e9k\u00e1rn\u00edk", + "koga", + "terapeut", + "z\u00e1me\u010dn\u00edk", + "prim\u00e1tor", + "pastor", + "bank\u00e9\u0159", + "regul\u00e1tor", + "osadn\u00edk", + "maloobchodn\u00edk", + "mu\u0161ket\u00fdr", + "dobrovoln\u00fd", + "truhl\u00e1\u0159", + "ranhoji\u010d", + "novin\u00e1\u0159", + "kade\u0159n\u00edk", + "vyhazova\u010d", + "rozhod\u010d\u00ed", + "tovary\u0161", + "podkov\u00e1\u0159stv\u00ed", + "hladit", + "internista", + "kavalerista", + "pronaj\u00edmatel", + "po\u017e\u00e1rn\u00edk", + "polda", + "the_economist", + "galantn\u00ed", + "koordin\u00e1tor", + "barista", + "the_batman", + "patolog", + "p\u0159ed\u010d\u00edta\u010d", + "mar\u0161\u00e1l", + "popel\u00e1\u0159", + "zahradnice", + "zakladatel", + "man", + "chemik", + "pravideln\u00fd", + "hrn\u010d\u00ed\u0159", + "regent", + "kr\u00e1l", + "tane\u010dnice", + "the_boxer", + "neurolog", + "plak\u00e1t", + "hodin\u00e1\u0159ka", + "dobrovoln\u00edk", + "usher", + "messenger", + "tesa\u0159", + "hrobn\u00edk", + "kartograf", + "velitel", + "proconsul", + "branec", + "z\u00e1konod\u00e1rce", + "naklada\u010d", + "velvyslanec", + "hydrogeolog", + "hv\u011bzd\u00e1\u0159", + "byrokrat", + "zuba\u0159", + "kulomet\u010d\u00edk", + "soustru\u017en\u00edk", + "mana\u017eer", + "des\u00e1tn\u00edk", + "signalista", + "hudebn\u00edk", + "presbyter", + "chemi\u010dka", + "kocovina", + "kupec", + "sub", + "podkov\u00e1\u0159", + "velryb\u00e1\u0159", + "the_independent", + "romanopisec", + "automechanik", + "port\u00fdr", + "zahradn\u00edk", + "neurochirurg", + "esquire", + "nez\u00e1visl\u00fd", + "dragoun", + "autor", + "lazebn\u00edk", + "hodin\u00e1\u0159", + "kardiolog", + "pr\u016fmysln\u00edk", + "bacha\u0159", + "past\u00fd\u0159", + "preceptor", + "skl\u00e1\u0159" + ], + "ORG": [ + "ida", + "nesahat", + "malopolsko", + "k\u0159es\u0165anskodemokratick\u00fd", + "justice", + "v_pohod\u011b", + "nov\u00fd_sv\u011bt", + "bernard\u00fdn", + "wicca", + "kapetovci", + "jan_mayen", + "odbory", + "islamistika", + "kapverdy", + "nasa", + "zednictv\u00ed", + "arda", + "kdo", + "amerikanistika", + "bollywood", + "ho\u0159ej\u0161\u00ed_jezero", + "masm\u00e9dium", + "europol", + "schutzstaffel", + "yorkov\u00e9", + "zlat\u00fd_v\u011bk", + "arun\u00e1\u010dalprad\u00e9\u0161", + "albertovo_jezero", + "donaha", + "germanistika", + "nestandardn\u00ed", + "the_who", + "bohorodi\u010dka", + "dominium", + "zamknout", + "n\u00e1mo\u0159nictvo", + "zdravotnictv\u00ed", + "san_francisco", + "a_chorus_line", + "prvot\u0159\u00eddn\u00ed", + "spo\u0159itelna", + "nara", + "botanick\u00e1_zahrada", + "al_d\u017eaz\u00edra", + "hv\u011bzdokupa", + "politick\u00e1_strana", + "cvokhaus", + "gao", + "jit\u0159enka", + "konzervato\u0159", + "matka_bo\u017e\u00ed", + "bl\u00e1zinec", + "baskicko", + "v\u00e1le\u010dn\u00fd", + "ec", + "can_tho", + "don_juan", + "spravedlnost", + "oni", + "the_new_school", + "modrook\u00fd", + "trojpalubn\u00edk", + "lancasterov\u00e9", + "dia", + "r.p", + "mladoturci", + "protizedn\u00e1\u0159sk\u00e1_strana", + "starostliv\u00ed_medv\u00eddci", + "alexandr_makedonsk\u00fd", + "masm\u00e9dia", + "ma\u010farsk\u00fd_parlament", + "n\u00e1kupn\u00ed_centrum", + "l\u00e9ka\u0159sk\u00e1_fakulta", + "radnice", + "malobur\u017eoazie", + "gestapo", + "l\u00e9ta_p\u00e1n\u011b", + "obrana", + "\u010dern\u00fd_trh", + "\u0159\u00edmsk\u00e9_pr\u00e1vo", + "arm\u00e1da_spojen\u00fdch_st\u00e1t\u016f_americk\u00fdch", + "pac", + "\u0159\u00edmskokatolick\u00fd", + "labouristick\u00e1_strana", + "demokratick\u00e1_strana", + "barbora_z_nikom\u00e9die", + "vi\u0161nuismus", + "a_dal\u0161\u00ed", + "who_are_you", + "nanebevzet\u00ed_panny_marie", + "zem\u011bd\u011blstv\u00ed", + "nejvy\u0161\u0161\u00ed_soud", + "rud\u00e9_mo\u0159e", + "\u0161intoismus", + "europe", + "po", + "ovocn\u00fd_sal\u00e1t", + "k\u0159es\u0165ansk\u00e1_v\u011bda", + "hollywood", + "cid", + "australsk\u00e1_strana_pr\u00e1ce", + "al_ajn", + "kol\u00edbka", + "sturmabteilung", + "jezero_svat\u00e9_kl\u00e1ry", + "n\u00e1rodn\u011b_socialistick\u00e1_n\u011bmeck\u00e1_d\u011blnick\u00e1_strana", + "demokraticky_republik\u00e1nsk\u00e1_strana", + "silvestrovsk\u00e9_oslavy", + "los_angeles", + "nato", + "svat\u00e1_lucie", + "kv\u011btomluva", + "baltimore_orioles", + "akademie", + "ad_hoc", + "aktu\u00e1ln\u00ed", + "\u010derven\u00fd_k\u0159\u00ed\u017e", + 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"ob\u010dansk\u00e9_pr\u00e1vo", + "feder\u00e1ln\u00ed_\u00fa\u0159ad_pro_vy\u0161et\u0159ov\u00e1n\u00ed", + "ne_bis_in_idem" + ], + "POLITICAL_PARTY": [ + "politick\u00e1_strana", + "f\u00f8royski_javna\u00f0arflokkurin", + "f\u00f3lkaflokkurin", + "strana_whig\u016f", + "strana_pr\u00e1ce", + "kuomintang", + "komunistick\u00e1_strana", + "strana_zelen\u00fdch", + "republik\u00e1nsk\u00e1_strana", + "protizedn\u00e1\u0159sk\u00e1_strana", + "parti_socialiste", + "konzervativn\u00ed_strana", + "lidov\u00e1_strana", + "liber\u00e1ln\u00ed_strana" + ], + "PERSON_PRONOUN": [ + "i", + "tebou", + "my" + ], + "TITLE": [ + "ms" + ], + "ner_regexes": [ + [ + "PERSON", + "\\D+ \\D+|\\D+ \\D+ \\D+|\\D+ \\D+ \\D+|\\D+ \\D+ \\D+ \\D+|\\D+ \\D+|\\D+ \\D+ \\D+|\\D+ \\D+ \\D+|\\D+ \\D+ \\D+ \\D+", + false, + [] + ] + ], + "FIRST_NAME_FEMALE": [ + "iva", + "pavla", + "miloslava", + "v\u011bra", + "zdenka", + "kl\u00e1ra", + "alena", + "olga", + "vlasta", + "milena", + "alexandra", + "marie", + "dana", + "franti\u0161ka", + "lucie", + "kristina", + "simona", + "irena", + "daniela", + "jind\u0159i\u0161ka", + "denisa", + "so\u0148a", + "nela", + "romana", + "martina", + "bla\u017eena", + "anna", + "helena", + "sabina", + "r\u016f\u017eena", + "ludmila", + "eva", + "bohumila", + "s\u00e1ra", + "emilie", + "ji\u0159ina", + "ladislava", + "jana", + "nad\u011b\u017eda", + "jitka", + "julie", + "pavl\u00edna", + "zde\u0148ka", + "danu\u0161e", + "\u0161t\u011bp\u00e1nka", + "monika", + "petra", + "stanislava", + "marcela", + "vladim\u00edra", + "andrea", + "tereza", + "dagmar", + "ilona", + "viktorie", + "karol\u00edna", + "gabriela", + "zuzana", + "mark\u00e9ta", + "miroslava", + "eli\u0161ka", + "jarmila", + "m\u00e1ria", + "milada", + "michaela", + "iveta", + "ad\u00e9la", + "hana", + "barbora", + "marta", + "al\u017eb\u011bta", + "bo\u017eena", + "drahom\u00edra", + "\u0161\u00e1rka", + "radka", + "blanka", + "kv\u011btoslava", + "nat\u00e1lie", + "ane\u017eka", + "nikola", + "magdalena", + "ivana", + "alice", + "dominika", + "ren\u00e1ta", + "\u017eaneta", + "veronika", + "milu\u0161e", + "magdal\u00e9na", + "libu\u0161e", + "nikol", + "jaroslava", + "renata", + "kv\u011bta", + "lenka", + "aneta", + "kamila", + "krist\u00fdna", + "kate\u0159ina", + "vendula" + ], + "FIRST_NAME_MALE": [ + "p\u0159emysl", + "petr", + "vlastimil", + "luk\u00e1\u0161", + "igor", + "milo\u0161", + "alois", + "ivo", + "bohumil", + "old\u0159ich", + "v\u00e1clav", + "jaroslav", + "franti\u0161ek", + "\u0161tefan", + "leo\u0161", + "peter", + "mat\u011bj", + "kry\u0161tof", + "alexandr", + "daniel", + "josef", + "\u0161t\u011bp\u00e1n", + "radovan", + "miloslav", + "marian", + "alexander", + "rostislav", + "jarom\u00edr", + "j\u00e1n", + "dalibor", + "stanislav", + "roman", + "bohum\u00edr", + "marcel", + "tade\u00e1\u0161", + "\u0161imon", + "patrik", + "ale\u0161", + "pavel", + "radim", + "bohuslav", + "vojt\u011bch", + "du\u0161an", + "dominik", + "emil", + "radom\u00edr", + "denis", + "vasyl", + "tom\u00e1\u0161", + "ludv\u00edk", + "kamil", + "libor", + "vil\u00e9m", + "lud\u011bk", + "radek", + "jan", + "vratislav", + "jozef", + "karel", + "martin", + "arno\u0161t", + "michal", + "v\u00edt\u011bzslav", + "anton\u00edn", + "viktor", + "adam", + "marek", + "vladim\u00edr", + "robin", + "miroslav", + "bed\u0159ich", + "richard", + "samuel", + "eduard", + "david", + "b\u0159etislav", + "rudolf", + "filip", + "milan", + "robert", + "ji\u0159\u00ed", + "ivan", + "vladislav", + "erik", + "lubo\u0161", + "ond\u0159ej", + "ladislav", + "ren\u00e9", + "hynek", + "zden\u011bk", + "michael", + "zbyn\u011bk", + "otakar", + "jind\u0159ich", + "maty\u00e1\u0161", + "lubom\u00edr", + "v\u00edt", + "jakub" + ], + "LAST_NAMES_FEMALE": [ + "Machov\u00e1", + "Moravcov\u00e1", + "Pol\u00e1kov\u00e1", + "Dvo\u0159\u00e1kov\u00e1", + "\u010cern\u00e1", + "Holubov\u00e1", + "Barto\u0161ov\u00e1", + "Kr\u00e1lov\u00e1", + "Mare\u0161ov\u00e1", + "\u0158\u00edhov\u00e1", + "K\u0159\u00ed\u017eov\u00e1", + "Fialov\u00e1", + "Zemanov\u00e1", + "Jandov\u00e1", + "\u010cerm\u00e1kov\u00e1", + "Mal\u00e1", + "Svobodov\u00e1", + "H\u00e1jkov\u00e1", + "Pokorn\u00e1", + "Kol\u00e1\u0159ov\u00e1", + "\u0160imkov\u00e1", + "Vesel\u00e1", + "Beranov\u00e1", + "Du\u0161kov\u00e1", + "Markov\u00e1", + "Bl\u00e1hov\u00e1", + "Nov\u00e1kov\u00e1", + "R\u016f\u017ei\u010dkov\u00e1", + "Dole\u017ealov\u00e1", + "Ku\u010derov\u00e1", + "Soukupov\u00e1", + "\u0160\u0165astn\u00e1", + "Kopeck\u00e1", + "Novotn\u00e1", + "Va\u0148kov\u00e1", + "N\u011bmcov\u00e1", + "V\u00e1vrov\u00e1", + "Vl\u010dkov\u00e1", + "Bene\u0161ov\u00e1", + "Urbanov\u00e1", + "Vackov\u00e1", + "Hor\u00e1kov\u00e1", + "Sedl\u00e1\u010dkov\u00e1", + "\u0160t\u011bp\u00e1nkov\u00e1", + "Posp\u00ed\u0161ilov\u00e1", + "Krej\u010dov\u00e1", + "Bla\u017ekov\u00e1", + "Kadlecov\u00e1", + "Ma\u0161kov\u00e1", + "Tich\u00e1", + "Proch\u00e1zkov\u00e1", + "Jel\u00ednkov\u00e1", + "Kratochv\u00edlov\u00e1" + ], + "PREFIX_FEMALE": [ + "ing", + "rndr", + "bc", + "sle\u010dna", + "mgr", + "pan\u00ed", + "mudr", + "judr" + ], + "PREFIX_MALE": [ + "ing", + "pan", + "rndr", + "bc", + "mgr", + "mudr", + "judr" + ], + "FIRST_NAME": [ + "p\u0159emysl", + "iva", + "petr", + "pavla", + "vlastimil", + "luk\u00e1\u0161", + "igor", + "miloslava", + "v\u011bra", + "milo\u0161", + "zdenka", + "alois", + "ivo", + "bohumil", + "old\u0159ich", + "alena", + "olga", + "v\u00e1clav", + "kl\u00e1ra", + "jaroslav", + "franti\u0161ek", + "\u0161tefan", + "vlasta", + "leo\u0161", + "vendula", + "peter", + "milena", + "alexandra", + "marie", + "dana", + "mat\u011bj", + "franti\u0161ka", + "kry\u0161tof", + "lucie", + "kristina", + "alexandr", + "simona", + "daniel", + "josef", + "\u0161t\u011bp\u00e1n", + "irena", + "daniela", + "radovan", + "jind\u0159i\u0161ka", + "denisa", + "miloslav", + "marian", + "alexander", + "so\u0148a", + "jarom\u00edr", + "rostislav", + "j\u00e1n", + "nela", + "dalibor", + "romana", + "martina", + "bla\u017eena", + "stanislav", + "roman", + "bohum\u00edr", + "marcel", + "tade\u00e1\u0161", + "anna", + "helena", + "sabina", + "\u0161imon", + "patrik", + "ale\u0161", + "pavel", + "r\u016f\u017eena", + "ludmila", + "radim", + "eva", + "bohumila", + "s\u00e1ra", + "emilie", + "bohuslav", + "ji\u0159ina", + "ladislava", + "jana", + "vojt\u011bch", + "du\u0161an", + "nad\u011b\u017eda", + "jitka", + "dominik", + "emil", + "radom\u00edr", + "denis", + "vasyl", + "julie", + "tom\u00e1\u0161", + "pavl\u00edna", + "zde\u0148ka", + "danu\u0161e", + "ludv\u00edk", + "kamil", + "libor", + "\u0161t\u011bp\u00e1nka", + "vil\u00e9m", + "monika", + "petra", + "lud\u011bk", + "stanislava", + "radek", + "marcela", + "vladim\u00edra", + "andrea", + "tereza", + "dagmar", + "ilona", + "jan", + "vratislav", + "jozef", + "karel", + "viktorie", + "kate\u0159ina", + "karol\u00edna", + "gabriela", + "zuzana", + "mark\u00e9ta", + "miroslava", + "eli\u0161ka", + "martin", + "jarmila", + "m\u00e1ria", + "arno\u0161t", + "michal", + "milada", + "michaela", + "v\u00edt\u011bzslav", + "anton\u00edn", + "iveta", + "viktor", + "ad\u00e9la", + "marek", + "hana", + "vladim\u00edr", + "adam", + "barbora", + "robin", + "marta", + "miroslav", + "al\u017eb\u011bta", + "bo\u017eena", + "drahom\u00edra", + "bed\u0159ich", + "richard", + "\u0161\u00e1rka", + "samuel", + "radka", + "eduard", + "blanka", + "kv\u011btoslava", + "nat\u00e1lie", + "david", + "ane\u017eka", + "b\u0159etislav", + "nikola", + "magdalena", + "ivana", + "rudolf", + "alice", + "dominika", + "filip", + "ren\u00e1ta", + "\u017eaneta", + "veronika", + "milu\u0161e", + "milan", + "magdal\u00e9na", + "libu\u0161e", + "nikol", + "jaroslava", + "robert", + "ji\u0159\u00ed", + "ivan", + "vladislav", + "erik", + "renata", + "kv\u011bta", + "lubo\u0161", + "lenka", + "ond\u0159ej", + "ladislav", + "ren\u00e9", + "hynek", + "aneta", + "zden\u011bk", + "michael", + "zbyn\u011bk", + "otakar", + "jind\u0159ich", + "maty\u00e1\u0161", + "lubom\u00edr", + "kamila", + "krist\u00fdna", + "v\u00edt", + "jakub" + ], + "LAST_NAME": [ + "\u0161imkov\u00e1", + "posp\u00ed\u0161ilov\u00e1", + "bene\u0161ov\u00e1", + "pokorn\u00fd", + "moravec", + "k\u0159\u00ed\u017eov\u00e1", + "moravcov\u00e1", + "n\u011bmcov\u00e1", + "pol\u00e1kov\u00e1", + "\u0161t\u011bp\u00e1nkov\u00e1", + "soukupov\u00e1", + "\u0161\u0165astn\u00fd", + "bl\u00e1ha", + "r\u016f\u017ei\u010dkov\u00e1", + "posp\u00ed\u0161il", + "van\u011bk", + "\u0161imek", + "h\u00e1jkov\u00e1", + "kol\u00e1\u0159", + "\u0161t\u011bp\u00e1nek", + "ku\u010dera", + "novotn\u00fd", + "fialov\u00e1", + "v\u00e1vrov\u00e1", + "mare\u0161ov\u00e1", + "jel\u00ednkov\u00e1", + "zemanov\u00e1", + "barto\u0161ov\u00e1", + "dvo\u0159\u00e1kov\u00e1", + "kr\u00e1l", + "vesel\u00fd", + "r\u016f\u017ei\u010dka", + "jel\u00ednek", + "zeman", + "beranov\u00e1", + "mare\u0161", + "dole\u017eal", + "va\u0148kov\u00e1", + "n\u011bmec", + "barto\u0161", + "fiala", + "kratochv\u00edl", + "krej\u010dov\u00e1", + "h\u00e1jek", + "novotn\u00e1", + "machov\u00e1", + "kadlecov\u00e1", + "\u0161\u0165astn\u00e1", + "urban", + "ku\u010derov\u00e1", + "kol\u00e1\u0159ov\u00e1", + "krej\u010d\u00ed", + "soukup", + "\u010dern\u00e1", + "\u0159\u00edhov\u00e1", + "bene\u0161", + "kr\u00e1lov\u00e1", + "tich\u00e1", + "proch\u00e1zka", + "svobodov\u00e1", + "kopeck\u00fd", + "pokorn\u00e1", + "mal\u00e1", + "hor\u00e1kov\u00e1", + "bl\u00e1hov\u00e1", + "\u010derm\u00e1kov\u00e1", + "vl\u010dek", + "k\u0159\u00ed\u017e", + "dvo\u0159\u00e1k", + "sedl\u00e1\u010dek", + "nov\u00e1kov\u00e1", + "hor\u00e1k", + "svoboda", + "ma\u0161kov\u00e1", + "vl\u010dkov\u00e1", + "marek", + "kopeck\u00e1", + "pol\u00e1k", + "\u010dern\u00fd", + "vackov\u00e1", + "\u0159\u00edha", + "markov\u00e1", + "dole\u017ealov\u00e1", + "urbanov\u00e1", + "holubov\u00e1", + "bla\u017ekov\u00e1", + "jandov\u00e1", + "ma\u0161ek", + "kratochv\u00edlov\u00e1", + "sedl\u00e1\u010dkov\u00e1", + "kadlec", + "nov\u00e1k", + "proch\u00e1zkov\u00e1", + "\u010derm\u00e1k", + "du\u0161kov\u00e1", + "vesel\u00e1", + "du\u0161ek", + "mal\u00fd", + "bla\u017eek", + "holub" + ], + "LAST_NAME_MALE": [], + "LAST_NAME_FEMALE": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "abaty\u0161e": "abba", + "here\u010dka": "herec", + "baronka": "baron", + "krasavice": "\u0161vih\u00e1k", + "kr\u00e1ska": "\u0161vih\u00e1k", + "obchodnice": "podnikatel", + "byznysmenka": "podnikatel", + "byznysmanka": "podnikatel", + "p\u0159edsedkyn\u011b": "p\u0159edseda", + "ku\u0159e": "gaur", + "pt\u00e1\u010de": "gaur", + "v\u00e9vodkyn\u011b": "v\u00e9voda", + "c\u00edsa\u0159ovna": "\u0161\u00eddlo_kr\u00e1lovsk\u00e9", + "sami\u010d\u00ed": "sam\u010d\u00ed", + "\u017eensk\u00fd": "sam\u010d\u00ed", + "samice": "sam\u010d\u00ed", + "\u017eena": "mu\u017e", + "gal": "chlap\u00edk", + "holka": "chlap", + "d\u011bv\u010de": "chlapec", + "d\u00edvka": "chlapec", + "vnu\u010dka": "vnuk", + "babi\u010dka": "d\u011bd", + "j\u00ed": "jeho", + "jej\u00ed": "jejich", + "jej": "jejich", + "heroin": "hrdina", + "hrdinka": "trim", + "hostitelka": "host", + "d\u00e1ma": "lord", + "d\u011bvenka": "chlapec", + "mas\u00e9rka": "mas\u00e9r", + "matrix": "patro", + "maminka": "otec", + "pan\u00ed": "mgr", + "p\u00ed": "mgr", + "ms": "hra", + "nete\u0159": "synovec", + "nun": "monako", + "\u0159eholnice": "monako", + "jepti\u0161ka": "mnich", + "policistka": "policista", + "policajtka": "policistka", + "kn\u011b\u017eka": "kn\u011bz", + "princezna": "kn\u00ed\u017ee", + "kr\u00e1lovna": "kr\u00e1l", + "queens": "kr\u00e1l\u016f", + "naja": "bratr", + "sestra": "bratr", + "kouzelnice": "\u010darod\u011bj", + "\u010darod\u011bjka": "\u010darod\u011bj", + "star\u00e1_panna": "star\u00fd_ml\u00e1denec", + "pastorkyn\u011b": "nevlastn\u00ed_syn", + "nevlastn\u00ed_dcera": "pastorek", + "macecha": "nevlastn\u00ed_otec", + "macocha": "nevlastn\u00ed_otec", + "nevlastn\u00ed_matka": "nevlastn\u00ed_otec", + "letu\u0161ka": "representant", + "\u010d\u00ed\u0161nice": "vrchn\u00ed", + "serv\u00edrka": "\u010d\u00ed\u0161n\u00edk", + "vdova": "vdovec", + "lesk": "vdovec", + "duna": "man\u017eel", + "man\u017eelka": "mu\u017e", + "wicca": "m\u00e1g", + "\u010darod\u011bjnice": "m\u00e1g", + "\u017eeny": "lid\u00e9", + "kluk": "d\u011bv\u010de", + "chlapec": "d\u011bv\u010de", + "doktorka": "l\u00e9ka\u0159ka", + "dr": "doktorka", + "l\u00e9ka\u0159ka": "doktorka", + "l\u00e9ka\u0159": "doktorka", + "arts": "doktorka" + }, + "other_gender_swap": { + "one": "jej", + "jej": "jejich", + "jich": "j\u00ed", + "nich": "jej\u00ed", + "n\u011b": "jej\u00ed", + "jim": "jej\u00ed", + "jimi": "jej\u00ed", + "jejich": "jej\u00ed", + "lia": "jejich", + "sv\u016fj": "jejich", + "jeho": "jejich", + "j\u00ed": "jich", + "jej\u00ed": "jejich" + }, + "en_pronoun2gender": { + "they": [ + "bisexu\u00e1ln\u00ed", + "transgender", + "homosexu\u00e1ln\u00ed" + ], + "he": [ + "man\u00edk", + "chlap", + "borec", + "gaur", + "mu\u017e", + "man", + "sam\u010d\u00ed", + "chlapec", + "kvido", + "osoba", + "chl\u00e1pek", + "d\u017eentlmen", + "little_boy", + "chlap\u00edk", + "kluk" + ], + "she": [ + "slab\u00e9_pohlav\u00ed", + "netrefit", + "holka", + "hol\u010di\u010dka", + "cik", + "samice", + "\u017eena", + "sle\u010dna", + "d\u00edvka", + "gal", + "d\u011bv\u010de", + "minout", + "d\u00e1ma", + "kn\u011b\u017ena", + "\u017eeny", + "mademoiselle", + "sami\u010d\u00ed", + "lesbick\u00fd", + "miss_a", + "\u017eensk\u00fd", + "n\u011b\u017en\u00e9_pohlav\u00ed", + "madam" + ] + }, + "en_pronoun2pronoun": { + "he": [ + "sv\u016fj", + "jeho", + "samotn\u00fd", + "lia" + ], + "she": [ + "jej\u00ed", + "j\u00ed", + "jej" + ], + "they": [ + "one", + "ony", + "jim", + "n\u011b", + "lia", + "jej", + "nich", + "jimi", + "jich", + "jejich" + ], + "it": [ + "onen", + "jeho", + "tamten", + "s\u00e1m", + "eso", + "tenhle", + "tyto", + "a\u017e", + "tamty", + "s\u00e1m_sebe", + "tento", + "\u017ee" + ] + }, + "en_pronoun2title": {}, + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/csb.json b/data_tooling/pii_processing/ontology/data/csb.json new file mode 100644 index 0000000..2580cf6 --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/csb.json @@ -0,0 +1,66 @@ +{ + "DATE": [ + "strz\u00e9dnowiek" + ], + "PUBLIC_FIGURE": [ + "jeden" + ], + "PLANT": [ + "sosna" + ], + "ORG": [ + "katol\u00ebcczi_k\u00f2sc\u00f3\u0142" + ], + "DISEASE": [ + "pierzch", + "schni\u0105czka" + ], + "JOB": [ + "m\u0142\u00ebn\u00f4rz" + ], + "LANGUAGE": [ + "esperanto", + "szpa\u0144sczi" + ], + "LOCATION": [ + "sri_lanka" + ], + "FOOD": [ + "glomzda" + ], + "FAC": [ + "miedzwi\u00f4dk_p\u00f9f\u00f4tk" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + 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"anna_kournikova", + "john_constable", + "putin", + "robert_hooke", + "karl_popper", + "george_sand", + "peter_sellers", + "marcus_aurelius", + "peter_o'toole", + "joseph_conrad", + "william_shockley", + "mair_fagdalen", + "peter_paul_rubens", + "mahatma_gandhi", + "jim_morrison", + "paul_newman", + "george_meredith", + "louis_dduwiol", + "jackson_pollock", + "john_lennon", + "andrea_palladio", + "gobaith", + "d_h_lawrence", + "j_m_barrie", + "thomas_malory", + "al_jolson", + "probert", + "elizabeth_gaskell", + "y_drydedd_groesgad", + "thomas_merton", + "hannah_arendt", + "wilhelm_tell", + "stanley_kubrick", + "james_watt", + "jonathan_edwards", + "ronald_reagan", + "helmut_schmidt", + "homo", + "david_hilbert", + "oliver_cromwell", + "martin_luther_king", + "william_wordsworth", + "woodrow_wilson", + "el_cid", + "marcus_antonius", + "pedr_i_tsar_rwsia", + "richard_rodgers", + "don_quixote", + "john_dryden", + "jim_henson", + "ernest_hemingway", + "arthur_miller", + "nelson_mandela", + "heinrich_himmler", + "al_gore", + "georg_hegel", + "j_p_morgan", + "roald_amundsen", + "glanh\u00e4wr_simneiau", + "charles_dickens", + "ella_fitzgerald", + "jacques_offenbach", + "william_curtis", + "bagloriaeth", + "federico_fellini", + "bessie_smith", + "willy_brandt", + "francisco_pizarro", + "francisco_franco", + "franz_schubert", + "johnny_cash", + "joseph_mccarthy", + "adarwr", + "walter_scott", + "vladimir_lenin", + "sam_houston", + "robert_peary", + "kahlil_gibran", + "robert_browning", + "john_bunyan", + "jonathan_swift", + "albert_einstein", + "thomas_edison", + "chiang_kai_shek", + "henry_purcell", + "t" + ], + "LOCATION": [ + "al_jazeera", + "y_crysau_duon", + "y_m\u00f4r_du", + "y_llynnoedd_mawr", + "bro_morgannwg", + "nos_galan", + "piet_mondrian", + "mynydd_carmel", + "y_cefnfor_tawel", + "huang_he", + "hoff", + "bawd_bach", + "yr_horn", + "llyn_st_clair", + "unol_daleithiau", + "maes", + "penrhyn_verde", + "sri_lanka", + "nos_da", + "the_rolling_stones", + "y_dwyrain_canol", + "da_chi", + "mynydd_st_helens", + "de_awstralia", + "yr_arth_fawr", + "banc_canolog" + ], + "DATE": [ + "sul_y_blodau", + "y_chwyldro_diwydiannol", + "in_time", + "nos_ystwyll", + "trannoeth", + "sul_y_mamau", + "oes_aur", + "y_tymor_dwl" + ], + "ANIMAL": [ + "ci_baset", + "ci_pigog", + "y_fantell_goch", + "lyncs", + "petrisen", + "firefox", + "mwyalchen", + "sidanbryf", + "morfarch", + "billy_elliot", + "mamal", + "gwenci", + "ci_defaid_almaenig", + "bronwen", + "ci_d\u0175r", + "baset", + "gwarchodgi", + "ysguthan", + "pedryn_wilson", + "arthropod", + "minc", + "pathew", + "condor", + "gwengyn", + "afanc", + "ji_binc", + "chwiwell", + "morlas", + "tingoch", + "y_pysgod", + "te_gwyrdd", + "herlyn", + "pencath", + "penhwyad", + "morwennol", + "heulforgi", + "fultur", + "cornchwiglen", + "caeriwrch", + "llostlydan", + "grugiar_ddu", + "cochwat", + "lleiddiad", + "mochyn_cwta", + "cambig", + "marchfacrell", + "broga", + "maelgi", + "mantis", + "bronrhuddyn", + "honos", + "tingoch_du", + "llamhidydd", + "br\u00e2n", + "morfeirch", + "y_gweunydd", + "comb\u00e1c", + "bronfraith", + "cywion", + "ci_mynydd_bern" + ], + "PLANT": [ + "y_galdrist_lydanddail", + "mynawydlys", + "bergamot", + "castan", + "tagaradr", + "sapindus", + "y_benboeth", + "elinog", + "masarnen", + "esgorlys", + "marchgastanwydden", + "gwyddfid", + "palmwydd", + "llwyfen", + "bricyllwydden", + "gwenwialen", + "y_feidiog_lwyd", + "corhocysen", + "gypsoffila", + "llawrwydden", + "taxus_baccata", + "agrimonia_eupatoria", + "peithwellt", + "marchrawnen_fraith", + "y_feidiog_ddi_sawr", + "y_galdrist_goch", + "blodfresychen", + "clari", + "danhadlen", + "welingtonia", + "n\u00e2d_fi'n_angof", + "marchysgallen", + "blackberry", + "bresychen", + "merysbren", + "masarnwydden", + "amaranthus_caudatus", + "mamlys", + "derrig", + "cacamwci", + "melengu", + "gorthyfail", + "y_ferfain", + "castanwydd", + "gwiniolen", + "milddail", + "creulys", + "crancwellt", + "olewydden", + "maenhad", + "arlunydd", + "y_godog", + "cracheithinen", + "corfiaren", + "porpin", + "prinwydden", + "trilliw", + "trogenllys", + "palfais", + "y_goesgoch", + "y_feddyges_las", + "andromeda'r_gors", + "moronen", + "eirinen", + "llugaeron", + "coliffl\u0175ar", + "cerddinen" + ], + "JOB": [ + "cramen", + "croesawydd", + "cyfreithiwr", + "darlunydd", + "potter", + "cerddor", + "trochion", + "darlithydd", + "bosns", + "trochioni", + "drag\u0175n", + "pregethwr", + "cerddwyr", + "bosn", + "digrifwr", + "heddwas", + "marsiandwyr", + "bargyfreithiwr", + "llyngesydd", + "cerddwr", + "str\u00f4c", + "dadansoddwr", + "trefnwr", + "m\u00eats", + "kamikaze", + "actiwari", + "deintydd", + "coedwigwr", + "seboni", + "amrantiad", + "darllenydd", + "adarwr", + "the_guardian", + "serydd", + "awyrfilwr", + "deddfwr", + "plismon", + "marsiandwr", + "comed\u00efwyr", + "arlywydd", + "seronydd", + "gwyliwr", + "camicasi", + "brenin", + "landlord", + "preifat\u00eer", + "pensaer", + "melinydd", + "trefnwraig", + "clochydd", + "the_economist", + "geiriadurwr", + "cop", + "croniclydd", + "canghellor", + "goruchwyliwr", + "bugail", + "parafeddyg", + "haeniadur", + "derbynnydd", + "banerwr", + "fforestwr", + "usher", + "peiriannydd", + "amaethwr", + "the_interpreter", + "peintiwr", + "crefftwr", + "ebran", + "the_deer_hunter", + "garddwr", + "dysgwr", + "henadur", + "porthiant", + "the_independent", + "comed\u00efwr", + "briciwr", + "pobydd", + "cemegydd", + "medelwr", + "peiriannwr" + ], + "GPE": [ + "canolbarth_america", + "y_testament_newydd", + "y_m\u00f4r_coch", + "sant_pedr", + "dar_es_salaam", + "y_groes_goch", + "ein_harglwyddes", + "hawliau_dynol", + "hagia_sophia", + "de_america", + "sant_nicolas", + "s\u00e3o_tom\u00e9", + "gran_canaria", + "y_t\u0177_gwyn", + "al_andalus", + "bwlch", + "la_gomera" + ], + "DISEASE": [ + "creithiau", + "marwdon", + "y_frech_folog", + "als", + "craith", + "y_dwymyn_doben", + "y_frech_wen", + "gall", + "y_ffliw", + "gwynegon", + "dafaden", + "colera", + "cornwyd", + "y_frech_goch", + "meigryn", + "la_peste", + "gordewdra", + "codiad", + "tosyn", + "crafu", + "chi", + "gordyfiant", + "qi", + "corn", + "cecian", + "soriasis", + "crud", + "beichiogiad", + "brech", + "ed", + "pica", + "cowpog", + "dannoedd", + "beichiogrwydd", + "darafal", + "murmur", + "the_passion_of_the_christ", + "dannodd", + "materoliaeth", + "gowt", + "lliwddall", + "syched", + "meddwdod", + "mi", + "y_gynddaredd", + "tan", + "y_frech_almaenig", + "poliomyelitis", + "dolur", + "hengroen", + "gwyth\u00efenwst", + "carbwncl", + "corachedd", + "malaria" + ], + "RELIGION": [ + "shint\u014d", + "zen", + "presbyteriaeth", + "calfiniaeth", + "cathariaid", + "islam", + "salaffiaeth", + "seientiaeth_gristnogol", + "methodistiaeth" + ], + "FOOD": [ + "mousse", + "gorcharfan", + "gwaedogen", + "deintgig", + "borefwyd", + "chile", + "te_llysieuol", + "brecwast", + "merfog", + "peren_bigog", + "lemon\u00ead", + "coffi" + ], + "PRODUCT": [ + "justin_bieber", + "bedyddfaen", + "the_time_machine", + "s\u00e3o_tom\u00e9_a_pr\u00edncipe", + "al_jazeera", + "santes_fair", + "dadansoddi", + "tegandy", + "ein_tad", + "ysbryd_gl\u00e2n", + "don_quixote", + "y_deyrnas_unedig", + "sachsen_anhalt", + "die_hard", + "the_lord_of_the_rings", + "y_testament_newydd", + "la_dolce_vita", + "testament_newydd", + "y_greal_santaidd", + "si\u00f4n_corn", + "nordrhein_westfalen", + "y_rhyfel_byd_cyntaf", + "dydd_san_steffan", + "nos_ystwyll", + "coeden_nadolig" + ], + "LANGUAGE": [ + "affricaneg", + "eidalaidd", + "cernywaidd", + "lleferydd", + "pali", + "almaenwr", + "hindi", + "arabeg", + "gwyddeleg", + "divehi", + "ffrangeg", + "esperanto", + "seisnig", + "manawaidd", + "cree", + "lladin", + "daneg", + "slofacaidd", + "tonga", + "kannada" + ], + "RACE": [ + "brodor", + "americanwyr", + "iddewaidd", + "japaneaid", + "affricanaidd" + ], + "ORG": [ + "y_llynges_frenhinol", + "ewrop", + "jan_mayen", + "y_groes_goch", + "the_usual_suspects", + "nos_galan", + "cymanwlad", + "nasa", + "huang_he", + "prinfwyn", + "schutzstaffel", + "the_who", + "sant_lwsia", + "canolbarth_ewrop", + "san_francisco", + "y_democratiaid_cymdeithasol", + "y_blaid_geidwadol", + "y_swyddfa_gartref", + "un", + "a_chorus_line", + "o_gwbl", + "y_gymdeithas_frenhinol", + "y_gymanwlad", + "amaeth", + "mahayana", + "saint_helena", + "oni", + "hunanlywodraeth", + "y_gymuned_ewropeaidd", + "biwro_ymchwilio_ffederal", + "y_fyddin_goch", + "taoaeth", + "crai_primorsky", + "y_t\u0177_gwyn", + "swyddfa_bost", + "am_byth", + "byddin_yr_unol_daleithiau", + "doe", + "shia", + "llyn_superior", + "rabindranath_tagore", + "gestapo", + "almaeneg", + "awyrlu", + "dominiciaid", + "campfa", + "etholaeth", + "winnie_the_pooh", + "ar_goll_ar_faes_y_gad", + "y_trydydd_byd", + "undeb_llafur", + "y_rhyfel_oer", + "y_diwygiad_protestannaidd", + "lancastriaid", + "al_jazeera", + "y_corfflu_heddwch", + "addis_ababa", + "achres", + "mossad", + "eglwys_gatholig", + "llu_awyr", + "saint_barth\u00e9lemy", + "gartref", + "los_angeles", + "nato", + "y_cenhedloedd_unedig", + "achresi", + "mi", + "y_blaid_lafur", + "sa", + "y_gwasanaeth_awyr_arbennig", + "gwm_cnoi", + "etholedigaeth", + "eglwys_gatholig_rufeinig", + "reit", + "y_cynghrair_arabaidd", + "y_democratiaid_rhyddfrydol", + "y_m\u00f4r_coch", + "m\u00f4r_coch", + "wica", + "s\u00e3o_tom\u00e9", + "yr_eglwys_gatholig", + "milwyr", + "shint\u014d" + ], + "RELIGION_MEMBER": [ + "the_hindu", + "cristion", + "protestant", + "brawd", + "sunni", + "brodyr" + ], + "GENDER": [ + "trawsrywedd", + "dynes", + "geneth", + "bechgyn", + "deurywiol", + "bachgennes", + "bachan", + "genethig", + "bachgen", + "boneddiges", + "benyw", + "arglwyddes" + ], + "FAC": [ + "y_swper_olaf", + "pandy", + "sant_lwsia", + "ysgol_gynradd", + "atomfa", + "titus_livius", + "tollty" + ], + "PERSON": [ + "al_gore", + "h_g_wells", + "pysgodyn_darn_arian", + "sant_dominic", + "seleucus_i_nicator", + "rudolf_hess" + ], + "PERSON_PRONOUN": [ + "i", + "ninnau", + "her", + "us" + ], + "POLITICAL_PARTY": [ + "llafur", + "y_blaid_geidwadol", + "plaid_weriniaethol", + "y_blaid_lafur", + "partido_popular", + "plaid_ryddfrydol", + "plaid_wleidyddol", + "y_democratiaid_cymdeithasol", + "plaid_y_gweithwyr_sosialaidd_cenedlaethol", + "plaid_ddemocrataidd" + ], + "SOC_ECO_CLASS": [ + "hufen", + "samwrai", + "dosbarth_canol" + ], + "TITLE": [ + "sir", + "mr" + ], + "QUANTITY": [ + "ton", + "dollar", + "g", + "un_ar_hugain" + ], + "LAW": [ + "cyfraith_sifil" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "abades": "abba", + "ymerodres": "ymerawdwr", + "bachgennes": "bachan", + "prifathrawes": "prifathro", + "heroin": "arwr", + "gwrones": "gwron", + "boneddiges": "arglwydd", + "arglwyddes": "arglwydd", + "bonesig": "sir", + "rhiain": "bachgen", + "mam": "tad", + "lleian": "mynach", + "pr\u00edncipe": "prince", + "tywysoges": "prince", + "brenhines": "brenin", + "chwaer": "brawd", + "chwiorydd": "brodyr", + "hen_ferch": "baglorion", + "gweddw": "g\u0175r_gweddw", + "gwraig": "m\u00ear", + "gwragedd": "g\u0175r", + "dewines": "swynwr", + "lleden_wrach": "swynwr", + "gwrach": "dewin", + "dynes": "m\u00ear", + "benyw": "m\u00ear", + "bechgyn": "bachgennes", + "bachgen": "bachgennes", + "trai": "bachgennes" + }, + "other_gender_swap": { + "iad": "her", + "teim": "her" + }, + "en_pronoun2gender": { + "they": [ + "trawsrywedd", + "deurywiol" + ], + "he": [ + "m\u00ear", + "bechgyn", + "bachgenyn", + "bachgen", + "bachgennyn", + "bachan", + "trai" + ], + "she": [ + "arglwyddes", + "merchig", + "rhiain", + "genethig", + "dynes", + "morwyn", + "bonesig", + "benyw", + "bachgennes", + "boneddiges" + ] + }, + "en_pronoun2pronoun": { + "she": [ + "her" + ], + "they": [ + "hwy", + "teim", + "iad", + "hwynt", + "nhw" + ], + "it": [ + "hwn", + "hyn" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/da.json b/data_tooling/pii_processing/ontology/data/da.json new file mode 100644 index 0000000..1fb20fc --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/da.json @@ -0,0 +1,2440 @@ +{ + "ORG": [ + "plan\u00f8konomi", + "dominion", + "ida", + "kommunalbestyrelse", + "sukkerfri", + "shinto", + "den_tyrkiske_republik_nordcypern", + "lillepolen", + "f\u00f8rdatid", + "bataljon", + "landstyrke", + "romerret", + "han_dynastiet", + "ferskvand", + "peter_plys", + "nazityskland", + "den_gyldne_horde", + "breakeven", + "military", + "underskole", + "forsikringsselskab", + "den_gule_flod", + "den_trojanske_hest", + "wicca", + "jeg_elsker_dig", + "an_education", + "jan_mayen", + "marionetregering", + "nyt\u00e5rsaften", + "the_usual_suspects", + "kongressen", + "overf\u00f8rsel", + "sundhedsv\u00e6sen", + "marineinfanteri", + "nasa", + "bloomsburygruppen", + "musikskole", + "overhuset", + "handelsskole", + "den_ortodokse_kirke", + "the_national_archives", + "den_europ\u00e6iske_union", + "isi", + "bollywood", + "fema", + "den_br\u00e6ndte_jords_taktik", + "den_tredje_verden", + "bilbombe", + "br\u00e6ndte_jords_taktik", + "europol", + "schutzstaffel", + "the_who", + "nym\u00e5ne", + "sikkerhedspoliti", + "haganah", + "markeds\u00f8konomi", + "det_tyske_kejserrige", + "college", + "jeg_hedder", + "det_hvide_hus", + "san_francisco", + "kristdemokraterna", + "sikkerhedstjeneste", + "nordcypern", + "det_internationale_atomenergiagentur", + "taoisme", + "stormagt", + "r\u00f8de_hav", + "den_europ\u00e6iske_centralbank", + "gr\u00e6sr\u00f8dder", + "dyreret", + "romerskkatolske_kirke", + "polterabend", + "frimureri", + "selvretf\u00e6rdig", + "bystat", + "den_internationale_telekommunikations_union", + "statskup", + "tornerose", + "det_nordatlantiske_r\u00e5d", + "vandglas", + "gao", + "det_tysk_romerske_rige", + "the_family_man", + "s_hertogenbosch", + "mahayana", + "kunstgalleri", + "rejsebureau", + "saint_vincent", + "homo\u00e6gteskab", + "stjernehob", + "can_tho", + "saint_helena", + "the_faculty", + "don_juan", + "hvad_sker_der", + "den_arabiske_liga", + "hanseforbundet", + "det_pal\u00e6stinensiske_selvstyre", + "trafikprop", + "flyvev\u00e5ben", + "fremmedlegionen", + "forsvarsministeriet", + "l\u00e6gemiddelindustri", + "sankt_helena", + "kernefamilie", + "jehovas_vidner", + "the_football_league", + "chiang_mai", + "handelsfl\u00e5de", + "et_al", + "akademi", + "dia", + "andromedagalaksen", + "kostskole", + "indiepop", + "weimarrepublikken", + "sm\u00e5borgerskab", + "udviklingsland", + "akse", + "byr\u00e5d", + "sparekasse", + "milit\u00e6rtjeneste", + "nu_og_da", + "alberts\u00f8en", + "le_mans", + "for_resten", + "christian_science", + "caf\u00e9_au_lait", + "undergrunds\u00f8konomi", + "vandrerhjem", + "senatet", + "jus_talionis", + "the_breakfast_club", + "middelklasse", + "koldkrig", + "det_konservative_parti", + "rabindranath_tagore", + "gestapo", + "grundskole", + "udenrigsministeriet", + "postkontor", + "politistat", + "straffelov", + "synsnerve", + "milit\u00e6r", + "nordvestpassagen", + "apalhraun", + "the_full_monty", + "beatgenerationen", + "sorgernes_moder", + "romersk_katolske_kirke", + "det_britiske_ostindiske_kompagni", + "centralbank", + "massemedier", + "personaleafdeling", + "borgerrettigheder", + "aserbajdsjans_nationalforsamling", + "milit\u00e6rpoliti", + "oliebjerget", + "mellemeuropa", + "i_ching", + "partido_del_trabajo", + "chiang_rai", + "al_jazeera", + "overhus", + "popkunst", + "hustruvold", + "fra_tid_til_anden", + "den_kontinentale_h\u00e6r", + "assembl\u00e9e_nationale", + "den_r\u00f8de_h\u00e6r", + "po", + "addis_ababa", + "golfk\u00f8lle", + "den_kolde_krig", + "holdingselskab", + "skrid", + "mossad", + "verdensbanken", + "portugals_socialdemokratiske_parti", + "hare_krishna", + "ferdinand_magellan", + "den_internationale_domstol", + "strygekvartet", + "den_h\u00f8je_port", + "brandv\u00e6sen", + "up_to_date", + "porten", + "de_forenede_stater", + "sognekirke", + "s\u00f8ndagsskole", + "care_bears", + "den_russisk_ortodokse_kirke", + "saint_barth\u00e9lemy", + "lake_superior", + "sturmabteilung", + "karmelbjerget", + "posthus", + "jesuiterordenen", + "dominikanerordenen", + "who", + "los_angeles", + "nato", + "babelst\u00e5rnet", + "den_anglikanske_kirke", + "politiskolen", + "baltimore_orioles", + "anno_domini", + "ad_hoc", + "sprogfamilie", + "serbiens_parlament", + "kunstmuseum", + "harmoniorkester", + "by_the_way", + "handicapidr\u00e6t", + "toppakning", + "in_situ", + "k\u00f8nsforskning", + "mandeforskning", + "det_nordlige_cypern", + "international_organisation", + "international_lov", + "berlinmuren", + "islamologi", + "al_ain", + "underhus", + "tridentinerkoncilet", + "officersskole", + "forresten", + "verdenshandelsorganisation", + "samfundsklasse", + "stamtavle", + "centralmagterne", + "baskerlandet", + "pengeinstitut", + "chang_jiang", + "centraleuropa", + "store_bj\u00f8rn", + "vekselbureau", + "kirken", + "tyggegummi", + "mecklenburg_vorpommern", + "fondsb\u00f8rs", + "s\u00e3o_tom\u00e9", + "tredjepart", + "de_forenede_nationer", + "hedgefond", + "hansaen", + "forbundsr\u00e5det" + ], + "PUBLIC_FIGURE": [ + "lawrence_durrell", + "henry_cavendish", + "matthew_arnold", + "anthon", + "benjamin_franklin", + "martin_buber", + "akira_kurosawa", + "jean_genet", + "john_knox", + "giovanni_boccaccio", + "cornelius_vanderbilt", + "rudolf_steiner", + "tanas\u00f8en", + "ben_hogan", + "johann_bernoulli", + "max_bruch", + "leonard_bernstein", + "che_guevara", + "georges_simenon", + "c", + "edward_albee", + "hendrik", + "maria_callas", + "william_walton", + "henrik_ibsen", + "william_gladstone", + "sergej_rachmaninov", + "mary_shelley", + "franz_werfel", + "peter_lorre", + "david_livingstone", + "eduard_buchner", + "john_herschel", + "andrzej_wajda", + "jan_van_eyck", + "carl_rogers", + "george_balanchine", + "georg_wilhelm_steller", + "richard_burton", + "jamesbugten", + "douglas_macarthur", + "james_michener", + "mary_wollstonecraft", + "j_edgar_hoover", + "anna_pavlova", + "winston_churchill", + "gustav", + "johannes_diderik_van_der_waals", + "karl_landsteiner", + "paul_mccartney", + "terry_pratchett", + "r\u00f8dh\u00e6tte", + "stephen_king", + "francis_crick", + "john_trumbull", + "sherry", + "isaac_newton", + "alfred_eisenstaedt", + "victor_hugo", + "joseph_smith", + "edwin_hubble", + "apostlen_peter", + "colette", + "milton_friedman", + "edward_gibbon", + "edvard_bekenderen", + "jefferson_davis", + "cass_gilbert", + "george_stephenson", + "john_glenn", + "john_webster", + "john_davis", + "pedel", + "george_harrison", + "peter_minuit", + "george_orwell", + "arthur_koestler", + "richard_wagner", + "edward_martyren", + "storvesir", + "pancho_villa", + "dr_james_wilson", + "leopold_stokowski", + "marie_curie", + "francis_galton", + "mary_martin", + "michael_jackson", + "louis_jolliet", + "carl_sandburg", + "aristarchos", + "thomas_hobbes", + "charles_louis_de_secondat_montesquieu", + "el_greco", + "samuel_beckett", + "david", + "galileo_galilei", + "den_flyvende_holl\u00e6nder", + "ernest_bevin", + "jane_goodall", + "john_donne", + "chaim_weizmann", + "andrea_guarneri", + "robert_koch", + "joseph_goebbels", + "george_eastman", + "john_steinbeck", + "edmund_hillary", + "vincent_van_gogh", + "sankt_kristoffer", + "anne_boleyn", + "josef_stalin", + "john_ruskin", + "robert_burns", + "den_lille_r\u00f8dh\u00e6tte", + "hans_albrecht_bethe", + "thomas_paine", + "bari", + "liliuokalani", + "francis_beaumont", + "edvard", + "oscaruddelingen", + "smutter", + "mary_pickford", + "hans_fischer", + "emiliano_zapata", + "elisabet", + "karl_barth", + "willem_einthoven", + "phil_anderson", + "bernard_malamud", + "samuel_johnson", + "jesus", + "allen_iverson", + "marie_antoinette", + "lennart", + "giuseppe_verdi", + "e", + "karl_jaspers", + "konrad_adenauer", + "antoni", + "norbert_wiener", + "maurice_chevalier", + "gottlieb_daimler", + "frank_sinatra", + "abel_tasman", + "katharine_hepburn", + "henri_becquerel", + "henri_matisse", + "louis_pasteur", + "richard_strauss", + "leslie_howard", + "hugo_grotius", + "mahalia_jackson", + "john_ford", + "stephen_foster", + "alphonse_bertillon", + "gertrude_stein", + "saladin", + "sarah_bernhardt", + "philip_marlowe", + "luigi_pirandello", + "marc_blitzstein", + "hank_williams", + "dorothea_lange", + "charles_de_gaulle", + "paul_von_hindenburg", + "y", + "holden", + "ralph_bunche", + "rudolf_bultmann", + "charles_lindbergh", + "vincenzo_bellini", + "samuel_barber", + "f", + "ludwig_wittgenstein", + "august_strindberg", + "thomas_mann", + "charles_goodyear", + "dante_alighieri", + "peter_pan", + "james_tobin", + "john_irving", + "giacomo_puccini", + "edward_fitzgerald", + "fridtjof_nansen", + "louis_braille", + "herbert_marcuse", + "mungo_park", + "benedict_arnold", + "paul_verlaine", + "q", + "robert_johnson", + "james_dean", + "robert", + "marie_tussaud", + "roger_bannister", + "max_beerbohm", + "alessandro_manzoni", + "henrik", + "joseph_priestley", + "hal", + "nicolas_poussin", + "andrea_mantegna", + "joseph_pulitzer", + "brevstemme", + "james_naismith", + "oscar_wilde", + "menneskev\u00e6sen", + "philip_roth", + "richard_trevithick", + "heinrich_schliemann", + "jackson", + "don_quijote", + "tandfe", + "laurence_olivier", + "edward_mcdowell", + "georg", + "pierre_larousse", + "christiaan_eijkman", + "adolf_eichmann", + "francis_bacon", + "pete_seeger", + "john_wycliffe", + "joseph_heller", + "a", + "morris", + "peter_carl_goldmark", + "norman_rockwell", + "james_brown", + "william_hogarth", + "charles_baudelaire", + "luigi_cherubini", + "david_ricardo", + "mary_leakey", + "charlie_parker", + "immanuel_kant", + "james_franck", + "weber", + "albert_schweitzer", + "johann_friedrich_herbart", + "saint_martin", + "johannes_kepler", + "william_s_burroughs", + "max_planck", + "william_blake", + "julio_iglesias", + "arthur", + "sarah_vaughan", + "william_byrd", + "scott_joplin", + "carl_lewis", + "sarah_siddons", + "t\u00e6kker", + "canberra", + "elias_canetti", + "edward_jenner", + "oliver_hardy", + "statsoverhoved", + "cole_porter", + "benjamin_west", + "jean_luc_godard", + "konstantin", + "graham_greene", + "frans_hals", + "lars_onsager", + "margaret_mitchell", + "jan_swammerdam", + "david_riesman", + "william_herschel", + "joseph_black", + "arthur_compton", + "niels_bohr", + "kenneth_grahame", + "henry_fielding", + "bertrand_russell", + "michael_faraday", + "anthony_burgess", + "jan_tinbergen", + "robert_venturi", + "maria_magdalene", + "johnny_appleseed", + "irving_berlin", + "rudolf_diesel", + "walt_disney", + "ben_jonson", + "peter", + "joseph_schumpeter", + "gabriel_lippmann", + "steve_reich", + "benny_goodman", + "ted_williams", + "friedrich_engels", + "jane_austen", + "charles_laughton", + "moses", + "gustav_mahler", + "ed_sullivan", + "phil_collins", + "robert_redford", + "jack_dempsey", + "ian_fleming", + "richard_feynman", + "wolfgang_pauli", + "theodore_dreiser", + "theodor_mommsen", + "andrew_huxley", + "marcel_proust", + "thomas_more", + "homo_heidelbergensis", + "paul_hindemith", + "elizabeth_taylor", + "thomas_chippendale", + "paul_robeson", + "arnold", + "pedro_rodr\u00edguez", + "thomas_middleton", + "john_dowland", + "william_golding", + "jesus_kristus", + "john_milton", + "peter_stuyvesant", + "ethel_merman", + "h\u00e5rdf\u00f8r", + "samuel_adams", + "albert_speer", + "valentina_teresjkova", + "john_vanbrugh", + "indira_gandhi", + "jane_seymour", + "george_gershwin", + "alberto_giacometti", + "frank_whittle", + "alfred_nobel", + "jesse_owens", + "daniel_rutherford", + "marco_polo", + "john_fletcher", + "menneskedyr", + "\u00f8rnen", + "charlie_watts", + "m", + "charlotte_corday", + "marcel_marceau", + "allen_ginsberg", + "fred_zinnemann", + "daniel_bernoulli", + "guillaume_apollinaire", + "antoine_watteau", + "henri_bergson", + "antonius", + "josef_hoffmann", + "boris_karloff", + "pierre_corneille", + "phillis_wheatley", + "patrick_white", + "bartholomew_roberts", + "catherine_howard", + "daniel_morgan", + "william_morris", + "cary_grant", + "thomas", + "saint_lawrence", + "pieter_zeeman", + "glenn_miller", + "steward", + "pablo_picasso", + "natalie_wood", + "l_ron_hubbard", + "thomas_moore", + "kurt_weill", + "otto_hahn", + "lester_young", + "john_marshall", + "christiaan_huygens", + "hector_berlioz", + "lucille_ball", + "paul_simon", + "claudio_monteverdi", + "john_galsworthy", + "robert_robinson", + "o", + "adam_smith", + "william_james", + "u", + "jean_harlow", + "henry_miller", + "karl_marx", + "friedrich_nietzsche", + "i", + "john_wesley", + "sandro_botticelli", + "carson_mccullers", + "nikola_tesla", + "al_capone", + "charles_barkley", + "billy_graham", + "robert_schumann", + "mel_gibson", + "le_corbusier", + "carlo_goldoni", + "john_locke", + "alexis_carrel", + "gr\u00e6senkemand", + "henry_james", + "menneskebarn", + "andrej_sakharov", + "helen_keller", + "paul_dukas", + "ingrid_bergman", + "leonard_bloomfield", + "jane_jacobs", + "jean_piaget", + "william_congreve", + "henri_rousseau", + "robert_southey", + "walt_whitman", + "william_wyler", + "colin_powell", + "carl_nielsen", + "mavedanser", + "leopold_kronecker", + "richard_wright", + "benjamin_thompson", + "adolf_hitler", + "james_d_watson", + "fritz_haber", + "peter_behrens", + "alfred_stieglitz", + "joseph_haydn", + "garfield", + "george_boole", + "paul_revere", + "skt_patrick", + "daniel_boone", + "buffalo_bill", + "edvard_grieg", + "robert_boyle", + "edith_cavell", + "alan_paton", + "1", + "cordell_hull", + "rosa_parks", + "norman_jewison", + "j\u00f8rgen", + "vladimir_putin", + "jacob", + "giuseppe_mazzini", + "jim_thorpe", + "hertz", + "arnold_sch\u00f6nberg", + "laurence_sterne", + "ben_hecht", + "christopher_isherwood", + "mikhail_barysjnikov", + "anne_hathaway", + "katarina", + "david_garrick", + "don_budge", + "clarence_darrow", + "katerina", + "nyman", + "charles_lamb", + "g", + "arthur_schopenhauer", + "thomas_dekker", + "james_cagney", + "john_keble", + "johns_hopkins", + "gregers", + "martin_heidegger", + "h.c_andersen", + "r", + "george_lucas", + "andrew_jackson", + "peter_abelard", + "louis_armstrong", + "steven_spielberg", + "jean_monnet", + "leonard", + "gardarige", + "robert_fulton", + "thomas_hardy", + "eddie_rickenbacker", + "skorstensfejer", + "thomas_gainsborough", + "giuseppe_garibaldi", + "philip_warren_anderson", + "robert_brown", + "thomas_carlyle", + "johann_gutenberg", + "william_tyndale", + "bobby_fischer", + "thomas_malthus", + "gaetano_donizetti", + "william_faulkner", + "andre", + "titus_flavius_vespasianus", + "amerigo_vespucci", + "arthur_holmes", + "pierre_boulez", + "lars", + "girolamo_savonarola", + "emma_goldman", + "anna_kournikova", + "francis_poulenc", + "james_ussher", + "john_constable", + "james_mill", + "putin", + "matthew_flinders", + "robert_herrick", + "joseph_campbell", + "jean_de_la_fontaine", + "karl_popper", + "alfred", + "coleman_hawkins", + "george_sand", + "peter_sellers", + "charles_fourier", + "marcus_aurelius", + "peter_o'toole", + "joseph_conrad", + "william_shockley", + "peter_paul_rubens", + "mahatma_gandhi", + "jim_morrison", + "jules_verne", + "pibe", + "paul_newman", + "woody_herman", + "josef_albers", + "jackson_pollock", + "administrerende_direkt\u00f8r", + "brigadegeneral", + "john_lennon", + "andrea_palladio", + "bob_woodward", + "charlie_chaplin", + "thomas_malory", + "lea", + "john_brown", + "elizabeth_gaskell", + "ikke_anvendeligt", + "hugo_junkers", + "henrich", + "hannah_arendt", + "antonio_stradivari", + "alice_walker", + "miles_davis", + "balletdanser", + "james_parkinson", + "wilhelm_tell", + "george_marshall", + "stanley_kubrick", + "john_huston", + "james_watt", + "jonathan_edwards", + "christoffer_columbus", + "ronald_reagan", + "helmut_schmidt", + "jenny_lind", + "homo", + "bachelorgrad", + "frederick_douglass", + "david_hilbert", + "wilhelm_reich", + "roman_jakobson", + "oliver_cromwell", + "kongeedderfugl", + "lionel_hampton", + "martin_luther_king", + "james_hargreaves", + "frank_capra", + "william_wordsworth", + "rex_harrison", + "s", + "woodrow_wilson", + "george_wallace", + "el_cid", + "marcus_antonius", + "lake_powell", + "agrippina", + "st_louis", + "richard_rodgers", + "john_dryden", + "jim_henson", + "frank", + "ernest_hemingway", + "george_westinghouse", + "aquila", + "arthur_miller", + "nelson_mandela", + "heinrich_himmler", + "al_gore", + "hans_geiger", + "d\u00f8dssejleren", + "cesare_borgia", + "roald_amundsen", + "andersen", + "alfred_korzybski", + "mennesker", + "c_a", + "anton", + "charles_dickens", + "hunnerkonge", + "ella_fitzgerald", + "fats_waller", + "wallace_carothers", + "jacques_offenbach", + "josefus", + "william_chambers", + "george_stevens", + "federico_fellini", + "bessie_smith", + "willy_brandt", + "francisco_pizarro", + "francisco_franco", + "jackie_robinson", + "bernardo_bertolucci", + "jan_steen", + "john_ross", + "ali_baba", + "andrew_carnegie", + "pontius_pilatus", + "franz_schubert", + "johnny_cash", + "joseph_mccarthy", + "hans_j\u00fcrgen_eysenck", + "dawid", + "peter_den_store", + "mick_jagger", + "georges_cuvier", + "william_harvey", + "walter_scott", + "peter_medawar", + "vladimir_lenin", + "sam_houston", + "robert_peary", + "ralph_ellison", + "john_bunyan", + "jonathan_swift", + "walter_gropius", + "albert_einstein", + "henry_sweet", + "fritz_lipmann", + "thomas_edison", + "titusbrevet", + "chiang_kai_shek", + "raymond_chandler", + "henry_purcell", + "t", + "wilhelm_ostwald" + ], + "ANIMAL": [ + "lille_korsn\u00e6b", + "husarabe", + "egentlige_sejlere", + "terner", + "gouldsamadine", + "thorshane", + "sneleopard", + "studsmus", + "stillits", + "buteo", + "hornulk", + "kermodebj\u00f8rn", + "the_raven", + "vandremusling", + "stor_stormsvale", + "canadag\u00e5s", + "brugde", + "nathejre", + "charsam\u00e5r", + "kohejre", + "stormm\u00e5ge", + "storkjove", + "skovmus", + "r\u00f8dtunge", + "mosegris", + "bjergand", + "karusse", + "skaberaktapir", + "mursejler", + "heron", + "vandredue", + "h\u00f8geugle", + "skovhornugle", + "vandhund", + "andeskondor", + "jagtedderkopper", + "kravebj\u00f8rn", + "markperlemorsommerfugl", + "hornugle", + "hjorte", + "aborre", + "billy_elliot", + "strandtudse", + "bananflue", + "kongekobra", + "bjergvagtel", + "knorteg\u00e5s", + "kunduz", + "lille_lappedykker", + "hedeh\u00f8g", + "araberhest", + "marsvin_familien", + "konge\u00f8rn", + "dompap", + "kaskelothval", + "dronningemoder", + "kaskelot", + "styltel\u00f8ber", + "carduelis", + "splitterne", + "hjerpe", + "sabinem\u00e5ge", + "langhalet_hermelin", + "stormsvaler", + "saigaantilope", + "malkekv\u00e6g", + "brillepingvin", + "junglekat", + "salts\u00f8krebs", + "erne", + "lactobacillus_acidophilus", + "javan\u00e6sehorn", + "ravn", + "klumpfisk", + "zobel", + "polarlomvie", + "skovsanger", + "kongekondor", + "skovsneppe", + "havlit", + "jordellekrager", + "kirkeugle", + "vibe", + "bengalsk_tiger", + "flyvefisk", + "grevyzebra", + "politihund", + "floddelfiner", + "kongepingvin", + "bardehvaler", + "kornsnog", + "natugle", + "arbejdsbi", + "brunalge", + "mink", + "granddanois", + "falken", + "hortulan", + "\u00e6blevikler", + "kongeboa", + "klapmyds", + "passer", + "spurveh\u00f8g", + "mandarinand", + "stormsvale", + "kalkungrib", + "tyrehaj", + "mankeulv", + "visent", + "adeliepingvin", + "vildkanin", + "jordegern", + "ringdue", + "lille_gulben", + "stenvender", + "natravn", + "falbyde", + "drosler", + "lossen", + "virginiahjort", + "sortand", + "marekatte", + "bassethund", + "accipiter", + "deltakrokodille", + "elefantskildpadde", + "skovfl\u00e5t", + "ravnegrib", + "stor_tornskade", + "fladlus", + "kronhjort", + "vandrefalk", + "sneg\u00e5s", + "lille_stormsvale", + "kongepingvinen", + "vildhest", + "pattedyr", + "solsort", + "hvidhval", + "vadefugl", + "baltimoretrupial", + "remmes\u00e6l", + "gedehams", + "iller", + "gr\u00e5hval", + "hestemakrel", + "polarhare", + "polarr\u00e6v", + "stillids", + "chacmabavian", + "berner_sennenhund", + "hjort", + "rankef\u00f8dder", + "bjerggorilla", + "sangspurv", + "skovh\u00f8ns", + "arbejdsdyr", + "komodovaran", + "simultanovers\u00e6ttelse", + "bighornf\u00e5r", + "taffeland", + "husskade", + "vagthund", + "nordlig_d\u00f8gling", + "piroler", + "sandmusling", + "odder", + "marsvin", + "oddere", + "pirol", + "gedde", + "anders_and", + "r\u00f8dmus", + "kartoffelbille", + "bramg\u00e5s", + "hasselmus", + "moskusand", + "vandrikse", + "halsb\u00e5ndnavlesvin", + "tr\u00e6leopard", + "hugorm", + "h\u00e6ttem\u00e5ge", + "jagthund", + "tusindben", + "enkeltbekkasin", + "skovm\u00e5r", + "bankivah\u00f8ne", + "krogn\u00e6b", + "rubinstrube", + "sildekonge", + "kejserpingvin", + "sandkat", + "mane", + "bj\u00f8rneunge", + "hovdyr", + "bjergpiber", + "sangsvane", + "fluesnappere", + "lemming", + "coloradobille", + "tred\u00e6kker", + "r\u00f8dalger", + "ringdrossel", + "l\u00e6geigle", + "p\u00e5skehare", + "skrubtudse", + "pukkelhval", + "dobbeltbekkasin", + "blommes\u00e6k", + "orange_klippehane", + "edderfugl", + "kondor", + "sandspringere", + "sumpmejse", + "munkegrib", + "skeand", + "swiftfox", + "arbejderbi", + "bartramsklire", + "sangdrossel", + "sortmejse", + "digesvale", + "egern", + "polarulv", + "fritte", + "l\u00f8bebiller", + "grindehval", + "tornirisk", + "trieler", + "sortkrage", + "parulasanger", + "eremitkrebs" + ], + "QUANTITY": [ + "parkometer", + "primtal", + "rupee", + "danske_kroner", + "de_kom_de_s\u00e5_de_l\u00f8b", + "treogtyve", + "otteogtyve", + "niogtyve", + "e_modul", + "ti_tusind", + "fireogtyve", + "d_mark", + "kalorie", + "schilling", + "kubikcentimeter", + "tone", + "parkeringshus", + "ton", + "dollar", + "ordinaltal", + "franske_franc", + "ordenstal", + "dyreinternat", + "g", + "de_tre_love", + "den_kosmologiske_konstant", + "elektronvolt", + "rial", + "basketkurv", + "schweizerfranc", + "krone", + "basketballkurv", + "ti_tusinde", + "v\u00e6gtenhed", + "femogtyve", + "seksogtyve", + "smule", + "anders_celsius", + "toogtyve", + "dyrehjem" + ], + "LOCATION": [ + "al_jazeera", + "gr\u00e6srand\u00f8je", + "i_tilf\u00e6lde_af", + "nords\u00f8en", + "stormagasin", + "biscayabugten", + "juleaften", + "mellem\u00f8sten", + "kirseb\u00e6rhaven", + "kraftv\u00e6rk", + "p\u00e5ske\u00f8en", + "park", + "jagthundene", + "drabantby", + "salts\u00f8", + "den_botniske_bugt", + "bulgariens_parlament", + "kap_verde", + "tempelbjerget", + "botanisk_have", + "bow_wow", + "united_states_army", + "luftv\u00e5ben", + "musikskole", + "s_hertogenbosch", + "s_tog", + "piet_mondrian", + "ha_long", + "santa_fe", + "sint_maarten", + "mortensdag", + "for_det_fald_at", + "ungarns_parlament", + "chang_jiang", + "ha_long_bugten", + "atlanterhavet", + "fredsdommer", + "maria_magdalene", + "kejserkanalen", + "for_l\u00e6ngst", + "kryvyj_rih", + "berlinerbl\u00e5t", + "blindgade", + "p\u00e5_vippen", + "m\u00e6lkevejen", + "tornerose", + "fiskehejre", + "land", + "la_mancha", + "saint_vincent", + "tanas\u00f8en", + "godnat", + "blue_mountains", + "kirseb\u00e6rtakvinge", + "abruzzerne", + "tredjepart", + "ingen_\u00e5rsag", + "edwards\u00f8en", + "det_var_s\u00e5_lidt", + "tennisbane", + "falklands\u00f8erne", + "osman_1", + "den_tredje_vej", + "on_the_road", + "usa", + "saint_lucia", + "blindgyde", + "kap_horn", + "vesterhavet", + "hat_yai", + "arena", + "olympen", + "sri_lanka", + "i_fald", + "den_br\u00e6ndte_jords_taktik", + "officersskole", + "lake_st_clair", + "flyvev\u00e5ben", + "den_gule_flod", + "plejehjem", + "blind_vej", + "the_rolling_stones", + "nord\u00f8en", + "saltvand", + "psykiatrisk_hospital", + "de_forenede_stater", + "kanal\u00f8erne", + "saint_lawrence", + "luftstyrke", + "julemanden", + "heitor_villa_lobos", + "al_ain", + "det_tyrrhenske_hav", + "stillehavet", + "den_hellige_stol", + "skovmurmeldyr" + ], + "DISEASE": [ + "hydrocephalus", + "sars", + "hedeslag", + "skelen", + "forstuve", + "cellulitis", + "klaustrofobi", + "leddegigt", + "polio", + "mastadenitis", + "rage", + "talblindhed", + "sukkersyge", + "als", + "rabies", + "vitaminmangel", + "mastitis", + "computermus", + "personlighedsforstyrrelse", + "progeria", + "mange", + "stivkrampe", + "n\u00e6seblod", + "krebsen", + "furunkel", + "hermafroditisme", + "socialangst", + "anger", + "brucellose", + "kogalskab", + "vannkopper", + "seneskedehindebet\u00e6ndelse", + "galaktos\u00e6mi", + "beriberi", + "personlighedsspaltning", + "the_bends", + "katalepsi", + "moderm\u00e6rkekr\u00e6ft", + "kryptorchisme", + "struma", + "hundegalskab", + "solskoldning", + "sanktvejtsdans", + "rust", + "beruselse", + "erhvervssygdom", + "bughindebet\u00e6ndelse", + "pancreatitis", + "forbryder", + "papeg\u00f8jesyge", + "aspirationspneumoni", + "koldbrand", + "miltbrand", + "vaccination", + "kv\u00e6gpest", + "den_sorte_d\u00f8d", + "pancreascancer", + "testikelkr\u00e6ft", + "gulsot", + "hunger", + "handicap", + "udviklingsh\u00e6mning", + "helvedesild", + "appendicitis", + "vasculitis", + "forstoppelse", + "mellem\u00f8rebet\u00e6ndelse", + "skyttegravsfeber", + "forhudsforsn\u00e6vring", + "overv\u00e6gt", + "ulven", + "tilstopning", + "forstyrrelse", + "leverkr\u00e6ft", + "transportsyge", + "personlighedsstruktur", + "sterilitet", + "knoglebrud", + "fuldskab", + "kakeksi", + "vejrtr\u00e6kningsbesv\u00e6r", + "delirium", + "plettyfus", + "qi", + "rakitis", + "luftart", + "passion", + "raseri", + "listeriose", + "spinal", + "gimp", + "fortegning", + "skarlagensfeber", + "kartoffelskimmel", + "herpes", + "mellemm\u00e5ltid", + "slidgigt", + "smart", + "solbr\u00e6ndthed", + "marasmus", + "brunst", + "ed", + "blister", + "hermafrodisme", + "solstik", + "overv\u00e6gtig", + "sensation", + "n\u00e6ldefeber", + "frugtbarhed", + "brands\u00e5r", + "talefejl", + "beslagl\u00e6ggelse", + "pain", + "sammenbrud", + "chondrom", + "spiseforstyrrelse", + "hovedpine", + "the_passion_of_the_christ", + "vendehalse", + "fork\u00f8lelsess\u00e5r", + "svangerskab", + "ill", + "denguefeber", + "an_qi", + "underern\u00e6ring", + "skrumpelever", + "bl\u00e6rebet\u00e6ndelse", + "f\u00e5resyge", + "pellagra", + "schistosomiasis", + "tunnelsyn", + "leverbet\u00e6ndelse", + "gangr\u00e6n", + "taber", + "brystkr\u00e6ft", + "filipens", + "roset", + "flue", + "sting", + "paritet", + "indisposition", + "fejlern\u00e6ring", + "socialfobi", + "nys", + "hareskaar", + "elmesyge", + "basalganglier", + "sovesyge", + "stjernet\u00e5ge", + "stenlunger", + "madforgiftning", + "noma", + "the_hives", + "materialisme", + "le", + "lidenskab", + "salmonella", + "langsynethed", + "strubehoste", + "forgiftning", + "m\u00f8rker\u00e6d", + "muskelsvind", + "mili\u00e6rtuberkulose", + "graviditet", + "p\u00f8lseforgiftning", + "abasi", + "malaria" + ], + "PLANT": [ + "kransb\u00f8rste", + "sur_kirseb\u00e6r", + "have_k\u00e5l", + "p\u00e5skeklokke", + "johannesbr\u00f8d", + "bergamot", + "skovranke", + "pine", + "sankt_maria", + "tytteb\u00e6r", + "buksbom", + "melissa", + "liljekonval", + "karplanter", + "pralb\u00f8nne", + "liguster", + "the_joshua_tree", + "jordskok", + "kakaob\u00f8nne", + "mark_bynke", + "hjertensfryd", + "mahonie", + "dv\u00e6rgcitron", + "skovsyre", + "skovm\u00e6rke", + "vandkastanje", + "cellev\u00e6g", + "v\u00e5r_lyng", + "navr", + "sennep", + "paradisfugl", + "tallerkensm\u00e6kker", + "guldranke", + "artist", + "ellesl\u00e6gten", + "kirseb\u00e6r", + "tarmvridr\u00f8n", + "sortkommen", + "korb\u00e6r", + "kaprifolie", + "v\u00e5r_fladb\u00e6lg", + "piletr\u00e6", + "almindelig_leverurt", + "karsporeplante", + "\u00f8rnebregne", + "savojk\u00e5l", + "candida_albicans", + "strand_hornskulpe", + "havetulipan", + "galneb\u00e6r", + "have_malurt", + "mark_\u00e6renpris", + "skovjordb\u00e6r", + "pr\u00e6stekrave", + "skorzonerrod", + "kardemomme", + "tempeltr\u00e6", + "bjergfyr", + "abild", + "pampasgr\u00e6s", + "forglemmigej", + "kassava", + "have_k\u00f8rvel", + "meldr\u00f8jer", + "juletr\u00e6", + "reseda", + "koglekirtel", + "holm", + "paternostertr\u00e6", + "brasiltr\u00e6", + "skarntyde", + "blomk\u00e5l", + "skyr\u00e6kker", + "stor_fladstjerne", + "leverurt", + "pomerans", + "polejmynte", + "oliven", + "j\u00f8dekirseb\u00e6r", + "pilledrager", + "kinak\u00e5l", + "t\u00e5rnurt", + "rogn", + "paradisfugle", + "have_l\u00f8vemund", + "malurt", + "hjortetaktr\u00e6", + "ananaskirseb\u00e6r", + "kartoffelskimmel", + "kolbehirse", + "solsikke", + "have_morgenfrue", + "pomeranstr\u00e6", + "belladonnalilje", + "julestjernen", + "blackberry", + "gederams", + "musevikke", + "traneb\u00e6r", + "mastikstr\u00e6", + "palmetr\u00e6", + "bukketorn", + "elmetr\u00e6", + "stenh\u00f8jsplante", + "ambratr\u00e6", + "sabina", + "arum", + "r\u00f8nneb\u00e6rtr\u00e6", + "have_timian", + "abetr\u00e6", + "blomme", + "bl\u00e6resm\u00e6lde", + "saccharomyces_cerevisiae", + "magnolie", + "hejren\u00e6b", + "mastiks", + "lakseb\u00e6r", + "frueb\u00e6r", + "tebusk", + "marathi", + "oliepalme", + "klitfyr", + "have_erantis", + "vorterod", + "skovfyr", + "pibekrave", + "gedeblad", + "blommetr\u00e6", + "smalb\u00e6gret_ensian", + "plantedel", + "batat", + "paran\u00f8d", + "brushane", + "br\u00f8ndkarse", + "natskygge", + "druebregne", + "sukkerr\u00f8r", + "stjerneanis", + "drejeblomst", + "silkeplante", + "parykbusk", + "sand_star", + "alder", + "fyrresl\u00e6gten", + "matrem", + "hornn\u00f8d", + "hvidkl\u00f8ver", + "smalstr\u00e5le", + "strand_mandstro", + "okse\u00f8je", + "rosenk\u00e5l", + "v\u00e5r_g\u00e6slingeblomst", + "volverlej", + "parasoltr\u00e6", + "karl_johan" + ], + "SOC_ECO_CLASS": [ + "tredje_stand", + "center", + "fl\u00f8de", + "samurai", + "sm\u00e5borgerskab", + "caste", + "arbejderklasse", + "underverden", + "broderskab", + "proletariat", + "middelklasse", + "undergrunds\u00f8konomi" + ], + "POLITICAL_PARTY_MEMBER": [ + "kommunistisk", + "kommunist", + "makker" + ], + "PRODUCT": [ + "gr\u00e6skarhoved", + "cook\u00f8erne", + "kugleleje", + "sportsvogn", + "badebukser", + "deja_vu", + "justin_bieber", + "tidsmaskinen", + "tvangsprostitution", + "new_zealand", + "balkanbjergene", + "det_kommunistiske_manifest", + "s_tog", + "s\u00e3o_tom\u00e9_og_pr\u00edncipe", + "kaffekop", + "karlsvognen", + "kejsersnit", + "aftage", + "madsk\u00e5l", + "al_jazeera", + "panservogn", + "diego_garcia", + "papirflyver", + "signalbehandling", + "helligtrekongersaften", + "de_fire_\u00e5rstider", + "f\u00f8rste_verdenskrig", + "tredimensional", + "anden_verdenskrig", + "regnestok", + "buelampe", + "tidsmaskine", + "julius_caesar", + "saint_vincent", + "milit\u00e6rfly", + "the_star_spangled_banner", + "blindgyde", + "det_gyldne_kompas", + "stilleben", + "albog", + "som_om", + "flaskepost", + "blindgade", + "sachsen_anhalt", + "die_hard", + "kortslutning", + "det_flammende_bogstav", + "sejlskib", + "boxing_day", + "anden_juledag", + "det_gyldne_horn", + "forglemmigej", + "et_dukkehjem", + "storbritannien", + "deutsche_welle", + "gong", + "den_hellige_gral", + "mount_st_helens", + "romerriget", + "ferdinand_magellan", + "the_pilgrim's_progress", + "kaffekande", + "tre_konged\u00f8mmer", + "mario_andretti", + "menneskerettighederne", + "himmellegeme", + "af_guds_n\u00e5de", + "strids\u00f8kse", + "de_vises_sten", + "ringenes_herre", + "forsvind", + "tennisbold", + "naturhistorie", + "nordrhein_westfalen", + "isterning", + "det_nye_testamente", + "rosettastenen", + "rosettestenen", + "nye_testamente", + "gongong", + "kulbuelampe", + "i_orden", + "novo_mesto", + "nordlys", + "den_guddommelige_komedie" + ], + "DATE": [ + "bastilledagen", + "middelalder", + "d_dag", + "langfredag", + "sandhedens_\u00f8jeblik", + "palmes\u00f8ndag", + "efter\u00e5rsj\u00e6vnd\u00f8gn", + "mandtime", + "allehelgensdag", + "mandetime", + "menstruationscyklus", + "f\u00f8r_eller_siden", + "the_day_after_tomorrow", + "den_industrielle_revolution", + "den_gregorianske_kalender", + "fuldm\u00e5ne", + "derover", + "istid", + "rumalderen", + "hundedage", + "overmorgen", + "i_tide", + "halveringstid", + "nationaldag", + "derovre", + "uafh\u00e6ngighedsdag", + "m\u00e5nefase", + "new_moon", + "helligtrekongersaften", + "gregorianske_kalender", + "regntid", + "askeonsdag", + "sk\u00e6rtorsdag", + "nattevagten", + "kalender\u00e5r", + "normaltid", + "den_stille_uge", + "sommersolhverv", + "skole\u00e5r", + "fritid", + "vintersolhverv", + "arbejdstid", + "middelalderen", + "solarkonstanten" + ], + "FOOD": [ + "traneb\u00e6rsaft", + "sm\u00f8rdej", + "blodp\u00f8lse", + "peberkagemand", + "kanelsnegl", + "karry", + "r\u00f8dk\u00e5l", + "butterdej", + "planteolie", + "h\u00f8nse\u00e6g", + "madolie", + "farsbr\u00f8d", + "blodpudding", + "lemonade", + "butterdejskage", + "p\u00e5ske\u00e6g", + "pomfrit", + "lykkekage", + "traneb\u00e6rjuice", + "have_karse", + "str\u00f8sukker", + "\u00f8rken", + "f\u00f8dselsdagskage", + "kostfibre", + "hytteost", + "sauce", + "l\u00e6bepomade", + "bordsalt", + "hvidvin", + "spiseolie", + "candyfloss", + "hundefoder", + "tartarsauce", + "pinot_noir", + "regnbueis", + "fuldkornsbr\u00f8d", + "jordn\u00f8ddesm\u00f8r", + "fastfood", + "bolsje", + "sukkervand", + "chili", + "blodbudding", + "h\u00f8nsek\u00f8dssuppe", + "olivenolie", + "lunch", + "chile", + "palmeolie", + "hvidl\u00f8gsbr\u00f8d", + "antipasto", + "danablu", + "fortjeneste", + "hundemad", + "hollandaisesauce", + "ros\u00e9vin", + "minim\u00e6lk", + "rosinbr\u00f8d", + "dessert", + "roesukker", + "iskaffe", + "tandk\u00f8d", + "flormelis", + "rosevin", + "kartoffelchips", + "postevand", + "ros\u00e9", + "citronsaft", + "forret", + "bl\u00e5skimmelost", + "kakaosm\u00f8r", + "ingef\u00e6r\u00f8l", + "kattemad", + "schweizerost", + "frugtsalat", + "appelsinjuice", + "morgenmad", + "waldorfsalat", + "kattefoder", + "kakaopulver" + ], + "JOB": [ + "landmand", + "feltmarskal", + "konditor", + "developer", + "guru", + "h\u00e5ndv\u00e6rker", + "cand.psych", + "biskop", + "bosiddende", + "assistent", + "faktotum", + "hydrolog", + "ni_til_femmer", + "mikrobiolog", + "sangskriver", + "pants\u00e6tte", + "make", + "glarmester", + "testpilot", + "vaskekone", + "oberstl\u00f8jtnant", + "bestyrelsesmedlem", + "herold", + "kirurg", + "vinduespudser", + "skovhugger", + "slavinde", + "m\u00e6lkepigen", + "ergoterapeut", + "blikkenslager", + "svend", + "paramediciner", + "faneb\u00e6rer", + "f\u00e5rehyrde", + "bestyrer", + "don", + "forretningsmand", + "toksikolog", + "cand.jur", + "tandl\u00e6ge", + "kansler", + "dermatolog", + "the_police", + "intern", + "skorstensfejer", + "lederskikkelse", + "landarbejder", + "pr\u00e6rieulv", + "bager", + "processor", + "nattevagt", + "blokfl\u00f8jte", + "doge", + "gentleman", + "videnskabskvinde", + "l\u00f8ber", + "borgmesterinde", + "ingeni\u00f8r", + "velordnet", + "garver", + "taler\u00f8r", + "formynder", + "gravko", + "leder", + "rendesten", + "kondukt\u00f8r", + "bodyguard", + "underofficer", + "brigadegeneral", + "tapper", + "bureaukrat", + "land", + "sikkerhedsvagt", + "boss", + "butler", + "sandwichmand", + "stewardesse", + "printer", + "beslagsmed", + "kurator", + "chauff\u00f8r", + "m\u00e6lkemand", + "kamikaze", + "kvartermester", + "flyveleder", + "strejkebryder", + "performer", + "page", + "sergent", + "korporal", + "hjulmager", + "apopleksi", + "borgmester", + "the_guardian", + "brandsvend", + "gastroenterolog", + "billedhuggerv\u00e6rkstedet", + "handlende", + "vesir", + "staldmester", + "minister", + "mandarin", + "\u00e5dsel\u00e6der", + "bredpandefamilien", + "mate", + "kameramand", + "guide", + "terapeut", + "angler", + "kaster", + "designer", + "kunstmaler", + "skaber", + "pastor", + "barrister", + "barnepige", + "formand", + "grafiker", + "sikkerhedshjelm", + "pants\u00e6tning", + "orkesterleder", + "faldsk\u00e6rmsj\u00e6ger", + "slave", + "an\u00e6stesiolog", + "malkepige", + "the_economist", + "\u00f8verstkommanderende", + "skibsf\u00f8rer", + "faldsk\u00e6rmssoldat", + "fortaler", + "mejer", + "kasserer", + "wetter", + "porter", + "fremmedarbejder", + "sygeplejerske", + "brandslukker", + "barista", + "skralder", + "patolog", + "sprog", + "barber", + "selvst\u00e6ndig", + "man", + "konge", + "lakaj", + "regent", + "beskyttelseshjelm", + "marine", + "cand.med", + "jordemor", + "mundsk\u00e6nk", + "jordemoder", + "trykker", + "usher", + "gardist", + "messenger", + "alletiders_barnepige", + "altmuligmand", + "anklager", + "arbejdsmand", + "fris\u00f8r", + "kirkev\u00e6rge", + "trier", + "rancher", + "fremmedf\u00f8rer", + "arbejder", + "stridsmand", + "steward", + "n\u00e6st", + "skibskaptajn", + "forstander", + "snedker", + "kemiker", + "avisdreng", + "regelm\u00e6ssig", + "brevb\u00e6rer", + "bornelaege", + "the_independent", + "kassedame", + "pedel", + "cookie", + "bankier", + "overs\u00e6tter", + "gunner", + "autor" + ], + "GPE": [ + "menneskerettighederne", + "centralamerika", + "det_hvide_hus", + "guldmine", + "saint_domingue", + "komipermjakisk", + "xihu", + "dar_es_salaam", + "valentinsdag", + "sint_maarten", + "vor_frue", + "det_hellige_land", + "skoledistrikt", + "det_nye_testamente", + "sankt_j\u00f8rgen", + "hagia_sophia", + "s\u00e3o_tom\u00e9", + "menneskeret", + "tyske_kejserrige", + "gran_canaria", + "bjergpas", + "mellemamerika", + "al_andalus", + "tyske_rige", + "det_tyske_kejserrige", + "taishan", + "sankt_barbara", + "r\u00f8de_kors", + "charlottenburg_wilmersdorf", + "vinh_long", + "la_gomera", + "st_louis" + ], + "FAC": [ + "vindtunnel", + "uddannelsesinstitution", + "baneg\u00e5rd", + "universitetsby", + "stendige", + "porten", + "underhus", + "t_celle", + "den_engelske_kirke", + "underskole", + "den_h\u00f8je_port", + "klagemuren", + "triumfbue", + "arnold_sch\u00f6nberg", + "kernekraftv\u00e6rk", + "grundskole", + "atomkraftv\u00e6rk", + "vestmuren", + "skydebane", + "saint_lucia", + "kunstakademi", + "peter_plys", + "katolske_kirke", + "peter_den_store", + "de_fire_\u00e5rstider", + "den_sidste_nadver", + "posthus", + "politistation", + "osmannerriget", + "postkontor", + "friedrichshain_kreuzberg" + ], + "LANGUAGE": [ + "walisisk", + "portugisisk", + "polsk", + "persisk", + "catalan", + "nordsamisk", + "langvejsfra", + "vallonsk", + "nordmand", + "forfine", + "norsk", + "marshallesisk", + "pali", + "tysker", + "manx", + "keltisk", + "malayalam", + "betoning", + "russer", + "hindi", + "malajisk", + "spansk", + "galizisk", + "galicisk", + "letlandsk", + "esperanto", + "bengalsk", + "catalonier", + "politur", + "komi", + "islandsk", + "georgisk", + "tagalog", + "ido", + "marathi", + "moderf\u00e5r", + "japansk", + "quechua", + "hviderussisk", + "tonga", + "kannada" + ], + "BIO_CHEM_ENTITY": [ + "polyvinylchlorid", + "laurinsyre", + "mononatriumglutamat", + "salicylsyre", + "s\u00f8lvoxid", + "fiskeolie", + "adenosindifosfat", + "siliciumdioxid", + "metanhydrat", + "klortrifluorid", + "diethylether", + "magnesiumchlorid", + "m\u00e6lkesyre", + "citronsyre", + "guanosindifosfat" + ], + "RELIGION_MEMBER": [ + "guru", + "protestant", + "christin", + "katolsk", + "mormon", + "muhammedaner", + "franciskanerordenen", + "presbyteriansk", + "mon" + ], + "RACE": [ + "j\u00f8disk", + "indian_airlines", + "engl\u00e6ndere", + "latin", + "filippinsk", + "franskmand", + "afrikansk", + "nordeurop\u00e6isk", + "nordkoreaner" + ], + "RELIGION": [ + "zen", + "katharisme", + "salafisme", + "donatisme", + "shinto", + "manik\u00e6isme", + "presbyterianisme", + "calvinisme", + "wahabisme", + "islam", + "christian_science", + "daoisme", + "wicca" + ], + "EVENT": [ + "golfkrigen", + "c_est_la_vie", + "filmfestival", + "stangspring", + "verdensudstilling", + "s\u00e5dan_er_livet", + "sing_sing" + ], + "LAW": [ + "d\u00f8dsdom", + "folkeret", + "stemmeret", + "statsforfatning", + "romerret", + "trykkefrihed", + "valgmetode", + "retsstat", + "valgmetoder", + "retssamfund", + "straffelov", + "havret", + "international_ret", + "forsamlingsfrihed", + "religionsfrihed", + "strafferet" + ], + "PERSON": [ + "julius_caesar", + "ha_ha", + "al_gore", + "han_hun", + "saint_vincent", + "i_ching", + "edward_osborne_wilson", + "distr\u00e6t", + "george_v", + "igor_sikorsky", + "carl_david_anderson", + "c_vitamin", + "rudolf_hess", + "dr_watson" + ], + "POLITICAL_PARTY": [ + "green_party", + "socialistisk_parti", + "national_party", + "partidul_conservator", + "partit_laburista", + "labour_party", + "f\u00f3lkaflokkurin", + "politisk_parti", + "det_konservative_parti", + "nsdap", + "kuomintang", + "demokratiske_parti", + "liberal_party", + "partido_popular", + "socialdemokratiske_parti", + "irish_labour_party", + "demokratisk_republikanske_parti", + "parti_socialiste", + "republikanske_parti", + "milj\u00f6partiet_de_gr\u00f6na", + "partito_democratico", + "javna\u00f0arflokkurin", + "australian_labor_party", + "opposition", + "socialistische_partij", + "arbeiderpartiet" + ], + "GENDER": [ + "det_smukke_k\u00f8n", + "damemenneske", + "mine_damer_og_herrer", + "gentleman", + "stuepige", + "starut", + "fruentimmer", + "men", + "jeppe", + "hank\u00f8nsv\u00e6sen", + "olding", + "chap", + "dame", + "male", + "mandsperson", + "hunlig", + "hunk\u00f8n", + "man", + "transk\u00f8nnet", + "gal", + "hank\u00f8n", + "pige" + ], + "PERSON_PRONOUN": [ + "i", + "mine", + "thina", + "her", + "hendes", + "my" + ], + "UNION": [ + "international_telecommunication_union", + "den_internationale_telekommunikations_union", + "verdenspostforeningen" + ], + "MEDICAL_THERAPY": [ + "blodtryk" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "abbedisse": "abbed", + "baronesse": "baron", + "working_girl": "forretningsmand", + "ungfugl": "jeppe", + "fugleunge": "jeppe", + "hertuginde": "hertug", + "kejserinde": "anax_imperator", + "hunlig": "male", + "kvindelig": "male", + "s\u00f8nnedatter": "datters\u00f8n", + "datterdatter": "datters\u00f8n", + "heroin": "heltinde", + "heltinde": "held", + "v\u00e6rtinde": "vandrende_sj\u00e6le", + "kvinde": "man", + "hunk\u00f8n": "individ", + "kvindemenneske": "m_k_er", + "damemenneske": "m_k_er", + "fruentimmer": "isle_of_man", + "mass\u00f8se": "mass\u00f8r", + "frue": "\u00e6gtemand", + "elsker": "mester", + "elskerinde": "mester", + "moder": "peder", + "niece": "nev\u00f8", + "nun": "klosterbroder", + "politikvinde": "politibetjent", + "pr\u00e6stinde": "imam", + "prinsesse": "prince", + "majest\u00e6t": "konge", + "dronning": "konge", + "hetman": "indra", + "regine": "f\u00f8rste_kongebog", + "queens": "anden_kongebog", + "naja": "blod", + "s\u00f8ster": "broder", + "talskvinde": "talsperson", + "papmor": "stedfar", + "stedmor": "stedfar", + "bonusmor": "stedfar", + "plasticmor": "stedfar", + "stewardesse": "administrator", + "servitrice": "tjener", + "enke": "enkemand", + "hustru": "husbond", + "\u00e6gtehustru": "\u00e6gtemand", + "viv": "husbond", + "\u00e6gteviv": "husbond", + "hex": "magiker", + "wicca": "troldmand", + "heks": "troldkvinde", + "norn": "troldmand", + "fema": "man", + "dreng": "pige", + "lad": "pige" + }, + "other_gender_swap": { + "deres": "her", + "hendes": "deres", + "her": "deres" + }, + "en_pronoun2gender": { + "they": [ + "homoseksuel", + "transk\u00f8nnet" + ], + "he": [ + "jeppe", + "male", + "mandsperson", + "gentleman", + "individ", + "bemande", + "lad", + "man", + "f\u00e6tter", + "dreng", + "chap", + "m_k_er", + "little_boy", + "hank\u00f8nsv\u00e6sen", + "hank\u00f8n", + "isle_of_man", + "starut" + ], + "she": [ + "kvindelig", + "hushj\u00e6lp", + "damemenneske", + "lesbisk", + "savne", + "pige", + "lesbianisme", + "fr\u00f8ken", + "gal", + "det_smukke_k\u00f8n", + "misse", + "stuepige", + "hunlig", + "hunk\u00f8n", + "kvinde", + "fruentimmer", + "kvindemenneske", + "dame", + "fema" + ] + }, + "en_pronoun2pronoun": { + "she": [ + "hendes", + "her" + ], + "they": [ + "deres" + ], + "it": [ + "bt", + "det_onde", + "disse", + "dette", + "denne", + "dets" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/dak.json b/data_tooling/pii_processing/ontology/data/dak.json new file mode 100644 index 0000000..f4d113a --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/dak.json @@ -0,0 +1,22 @@ +{ + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": {}, + "other_gender_swap": {}, + "en_pronoun2gender": { + "she": [ + "w\u012fy\u0105" + ] + }, + "en_pronoun2pronoun": {}, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/de.json b/data_tooling/pii_processing/ontology/data/de.json new file mode 100644 index 0000000..c4ce87f --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/de.json @@ -0,0 +1,14044 @@ +{ + "JOB": [ + "ophthalmologin", + "racker", + "geselle", + "kardiologe", + "die_waffen_der_frauen", + "sozialarbeiterin", + "persona_grata", + "kinderbetreuerin", + "verleiher", + "oberfr\u00e4se", + "synchronsprecher", + "hacklerin", + "kauffrau", + "der_konsul", + "kerkermeisterin", + "gyn\u00e4kologin", + "teaser", + "futtermittel", + "wortf\u00fchrer", + "waschfrau", + "konditor", + "sch\u00f6pferin", + "lehrerin", + "die_begnadigung", + "oberkellner", + "guru", + "schmier", + "surveyor", + "gehilfe", + "merchandiser", + "amanuensis", + "mercator", + "beseelerin", + "kehrmaschine", + "schreibk\u00fcnstlerin", + "sweep", + "therapeut", + "h\u00f6fling", + "sternkundiger", + "lehrkraft", + "rosshirt", + "rechtsanwaltsfachangestellter", + "klempner", + "schriftsetzer", + "schulflugzeug", + "schafhirtin", + "kaufmann", + "schreibk\u00fcnstler", + "freiwilliger", + "s\u00e4ugamme", + "schiedsfrau", + "handwerker", + "kalligraph", + "der_medicus", + "alkalde", + "zackeneule", + "mariner", + "seiler", + "businessman", + "splitter", + "sicherheitsbediensteter", + "strassenfeger", + "flugbegleiterin", + "stalkerin", + "assistent", + "faktotum", + "sprecherin", + "zuckerb\u00e4ckerin", + "trauzeugin", + "m\u00fcllerin", + "b\u00e4cker", + "kassierer", + "hausmeisterin", + "gesetzgeberin", + "sanit\u00e4terin", + "beleberin", + "heizer", + "fassbinder", + "ranger", + "lebensretter", + "the_analyst", + "fellachin", + "maschinenschreiber", + "steuermann", + "schmierer", + "packer", + "sicherheitspersonal", + "arbeitnehmererfindung", + "halbp\u00e4chter", + "unionist", + "zimmerm\u00e4dchen", + "freiberufler", + "make", + "schreiberin", + "romanautor", + "testpilot", + "treuh\u00e4nderin", + "buchmacherin", + "ballonfahrerin", + "herold", + "vizegouverneur", + "seifenschaum", + "bauschreinerin", + "rauchfangkehrer", + "wacht", + "recke", + "g\u00e4rtnerin", + "redner", + "einsch\u00e4umen", + "erzeuger", + "the_ecologist", + "malocherin", + "elefantentreiber", + "schildknappe", + "sicherheitsbeamter", + "kassenwart", + "hauptmann", + "talentscout", + "schornsteinfegerin", + "sprayer", + "rinderz\u00fcchter", + "himmelskundler", + "gehirnchirurg", + "rettungssanit\u00e4terin", + "harpunier", + "koordinator", + "rechtsanw\u00e4ltin", + "buchbinder", + "kirchenvorsteher", + "schmiererin", + "sakristan", + "weinleserin", + "die_nanny", + "aushilfskraft", + "hand", + "kriegerin", + "pharmakologin", + "stellmacher", + "sigristin", + "bisch\u00f6fin", + "hirtin", + "beseeler", + "registrar", + "vorstandsmitglied", + "b\u00f6ttcher", + "schlussfrau", + "kr\u00e4merin", + "fallschirmj\u00e4ger", + "sch\u00e4ffler", + "das_blumenm\u00e4dchen", + "sexton", + "subaltern", + "kieferorthop\u00e4din", + "cartoonistin", + "b\u00fcrgermeister", + "internistin", + "rosshirte", + "demonstrator", + "registrator", + "schiedsrichterin", + "gesetzgeber", + "internist", + "temp", + "palastdame", + "don", + "narkotiseuse", + "aquanaut", + "schweinehirtin", + "king", + "krankenhaus\u00e4rztin", + "maid", + "sergeant", + "zimmerer", + "kalligraphin", + "schreiber", + "trainerin", + "karabinier", + "essayistin", + "manualtherapeutin", + "schenk", + "valet", + "tier", + "reinigungskraft", + "tier\u00e4rztin", + "bleistiftst\u00e4mmer", + "romanschreiber", + "der_uhrmacher_von_st_paul", + "vogt", + "botschafter", + "fliegenf\u00e4ngerin", + "frauchen", + "subalternoffizier", + "spieler", + "buchverk\u00e4uferin", + "ehrenamtliche", + "laryngologin", + "ratz", + "the_police", + "intern", + "troubleshooter", + "polente", + "peacemaker", + "engelmacherin", + "vorstandvorsitzende", + "the_sentinel", + "anreisserin", + "hebamme", + "hans_dampf_in_allen_gassen", + "bootsbauer", + "buchh\u00e4ndler", + "holzschnitzer", + "autorin", + "kieferorthop\u00e4de", + "char", + "tierpr\u00e4parator", + "der_ladenaufseher", + "regisseurin", + "carrier", + "schiedsrichter", + "sommelier", + "kassier", + "zeitungsaustr\u00e4ger", + "reparateur", + "kinderfrau", + "sennerin", + "barbiere", + "schiri", + "feldwebel", + "oberbefehlshaber", + "tagl\u00f6hner", + "wagenbauer", + "laufbursche", + "resident", + "herausgeberin", + "doge", + "putzfrau", + "gentleman", + "minder", + "endokrinologin", + "m\u00fcllwerker", + "volkswirt", + "hausdiener", + "darlehensgeber", + "heiler", + "lister", + "schmuggler", + "\u00fcbersetzerin", + "sprecher", + "weberknecht", + "schweineh\u00fcterin", + "g\u00e4rtner", + "wirtschaftswissenschaftler", + "torsteher", + "pathologe", + "maschinenschreiberin", + "ziseleurin", + "torsteherin", + "kardiologin", + "konditorin", + "ballonfliegerin", + "the_musketeer", + "prompter", + "territorial", + "jahreszeitlich", + "distributor", + "tischlerin", + "prozessor", + "kalligraf", + "gaffer", + "novelist", + "rosshirtin", + "ostler", + "hausbesorger", + "kaminkehrer", + "z\u00f6llner", + "maschinengewehrsch\u00fctze", + "sauhirt", + "leutnant", + "korsaren", + "erzieherin", + "grip", + "para", + "router", + "flottillenadmiral", + "schmugglerin", + "leitfaden", + "essayist", + "platzwart", + "leder", + "schlagmann", + "gastgeberin", + "nekrophag", + "souver\u00e4n", + "glasbl\u00e4ser", + "frauenarzt", + "funktion\u00e4r", + "sensei", + "speicherseite", + "arrowsmith", + "schornsteinfeger", + "immunologin", + "bodyguard", + "wagener", + "sanit\u00e4tspersonal", + "sch\u00fctzerin", + "begleitperson", + "berufschauffeurin", + "staatsdienst", + "streitkolben", + "brigadegeneral", + "chemist", + "steinhauer", + "tagesvater", + "schriftstellerin", + "justizvollzugsbeamte", + "becker", + "couturier", + "mastermind", + "paramedic", + "schwarzarbeiter", + "trickzeichner", + "fellache", + "internieren", + "edelknecht", + "oberkellnerin", + "erwerbsf\u00e4hig", + "justizvollzugsbeamter", + "polsterhocker", + "schweinew\u00e4rter", + "wissenschafter", + "trainer", + "land", + "seemann", + "dermatologe", + "hakim", + "kartograph", + "nachtw\u00e4chter", + "boss", + "ballonfahrer", + "h\u00fcterin", + "dickkopffalter", + "verwalter", + "drechsler", + "reader", + "shifu", + "stenograf", + "chronist", + "statistikerin", + "b\u00fcchsenmacher", + "brieftr\u00e4gerin", + "klopper", + "bautischlerin", + "waschweib", + "schiffer", + "gipser", + "mundschenk", + "treasurer", + "ergotherapeutin", + "ziegenhirtin", + "gastronom", + "herzchirurg", + "interpretator", + "the_cutter", + "statistiker", + "landfrau", + "narkosefacharzt", + "butler", + "wissenschaftler", + "gyn\u00e4kologe", + "grenadier", + "kartografin", + "wagenmacher", + "bagger", + "propst", + "salzsieder", + "der_zufallslover", + "trickzeichnerin", + "feldscherin", + "vorstandsvorsitzende", + "strassenkehrer", + "eisverk\u00e4ufer", + "elektrotechniker", + "glasbl\u00e4serin", + "zollbeamtin", + "vaquero", + "oberbeleuchter", + "gastronomin", + "kurator", + "cutter", + "rednerin", + "kassiererin", + "sozialarbeiter", + "bautischler", + "lebensmittelh\u00e4ndler", + "melker", + "brigadier", + "fliesenleger", + "kinderzahnarzt", + "leader", + "landwirtin", + "gewerkschaftsmitglied", + "b\u00e4ckerin", + "kanzlerin", + "narkosefach\u00e4rztin", + "schweinehirt", + "ingenieurin", + "warden", + "spenglerin", + "kamikaze", + "automechaniker", + "driver", + "bleiarbeiterin", + "weinkellner", + "managerin", + "die_dolmetscherin", + "the_advocate", + "endokrinologe", + "kehren", + "wundarzt", + "performer", + "hangover", + "buchbinderin", + "buchhalterin", + "seneschall", + "page", + "elektroingenieur", + "ehrendame", + "comedian", + "tischler", + "heger", + "maier", + "leserin", + "hauslehrerin", + "haush\u00e4lterin", + "briefzustellerin", + "korporal", + "verwaltungsleiter", + "treuh\u00e4nder", + "lagerverwalter", + "tagel\u00f6hnerin", + "schoff\u00f6rin", + "beraterin", + "oberleutnant", + "keyboarder", + "stubenm\u00e4dchen", + "krankenschwester", + "ein_ungleiches_paar", + "sculptor", + "industrieller", + "tagel\u00f6hner", + "freelancer", + "lehrer", + "glaserin", + "versicherungsfachmann", + "ratze", + "botschafterin", + "kirchenvorsteherin", + "punter", + "freizeitmaler", + "seglerin", + "mikrobiologe", + "regul\u00e4r", + "milchmann", + "schiffskapit\u00e4n", + "abfalldurchst\u00f6berer", + "ingenieur", + "werbetexterin", + "fluglotse", + "schublade", + "schreiner", + "landwirt", + "abschreiben", + "der_hausbesitzer", + "stalker", + "ansiedler", + "master", + "hobbymaler", + "grenzbeamter", + "the_guardian", + "parteilos", + "zollbeamter", + "der_vorleser", + "rekorder", + "urheber", + "au_pair_junge", + "vesir", + "schutzhelm", + "heilerin", + "laryngologe", + "vermittler", + "bischof", + "hufschmiedin", + "minister", + "autoschlosser", + "mandarin", + "klavierlehrer", + "broterwerber", + "ankohlen", + "ladenbesitzer", + "schliesser", + "narkosearzt", + "setter", + "leibdiener", + "chauffeurin", + "kinderh\u00fcter", + "feldscherer", + "hydrologin", + "groom", + "ziegeltr\u00e4ger", + "entertainer", + "sommeli\u00e8re", + "knechtisch", + "k\u00fcchenchefin", + "ladenbesitzerin", + "regidor", + "flugzeugf\u00fchrerin", + "narkotiseur", + "mitsegler", + "weberin", + "mikrobiologin", + "kanzler", + "b\u00fcchsenmacherin", + "bunny", + "dragoner", + "mate", + "sesselfurzer", + "k\u00fcchenchef", + "vorsitzender", + "berater", + "fl\u00fcgelmann", + "guide", + "vorsitzende", + "buchhalter", + "mazis", + "naturalp\u00e4chter", + "interpreter", + "schulleiter", + "hafenarbeiter", + "vermesserin", + "wischer", + "sandwichman", + "galvaniseur", + "hauswartin", + "bader", + "angler", + "veranstalter", + "havariekommissar", + "bob_carroll", + "designerin", + "zimmerfrau", + "landmann", + "designer", + "kavallerist", + "kunstmaler", + "sitter", + "r\u00e4delsf\u00fchrer", + "pastor", + "hauswart", + "granatierer", + "barrister", + "leutnantin", + "manualtherapeut", + "bauschreiner", + "der_unterh\u00e4ndler", + "vorsteherin", + "schlosser", + "sheriff", + "cutterin", + "grafiker", + "picker", + "tiermedizinerin", + "stenografin", + "stewardess", + "regulator", + "kalligrafin", + "ansager", + "hauswirt", + "beschlagschmiedin", + "squire", + "brautjungfer", + "werferin", + "assoziieren", + "zimmerin", + "dermatologin", + "player", + "radmacher", + "herrscherin", + "holzf\u00e4ller", + "katzenpfote", + "ehrenamtlicher", + "funktion\u00e4rin", + "mellah", + "gaucho", + "hostess", + "kliniker", + "friseurin", + "kinderm\u00e4dchen", + "schauspielerin", + "freiwillige", + "feldmarschall", + "klinikerin", + "baster", + "feldschererin", + "sch\u00e4ferei", + "sanit\u00e4ter", + "slave", + "hackler", + "district_attorney", + "kinderarzt", + "seilerin", + "freizeitmalerin", + "au_pair_m\u00e4dchen", + "haus\u00e4rztin", + "siedler", + "f\u00f6rster", + "schafhirt", + "beschlagschmied", + "botenjunge", + "hochschulprofessorin", + "sp\u00fclmaschine", + "hoppelh\u00e4slein", + "pharmakologe", + "the_economist", + "collier", + "weinkellnerin", + "manager", + "schriftsteller", + "narkotiseurin", + "regisseur", + "barbier", + "broker", + "fensterputzerin", + "rechtsanwalt", + "fassk\u00fcfer", + "wetter", + "lanzierer", + "schiedsmann", + "porter", + "tagesmutter", + "feuerwehrmann", + "der_astronom", + "liebreizend", + "knacker", + "infanterist", + "krieger", + "wachposten", + "hobbymalerin", + "stripper", + "stecher", + "unionistin", + "chemikerin", + "playboyh\u00e4schen", + "cop", + "barista", + "lebensmittelh\u00e4ndlerin", + "ziegenhirt", + "schmelzer", + "flanker", + "darsteller", + "putzer", + "warrior", + "hochschulprofessor", + "schwarzarbeiterin", + "kurier", + "kogge", + "anreisser", + "kartographin", + "songwriter", + "sch\u00fctzer", + "klavierlehrerin", + "sargtr\u00e4ger", + "der_prinzipal_einer_gegen_alle", + "robbenj\u00e4ger", + "torfrau", + "man", + "wirtschaftspr\u00fcfer", + "chemicus", + "narkosenfacharzt", + "zimmermann", + "steuereinnehmerin", + "anwalt", + "vorstandvorsitzender", + "logger", + "a_dur", + "regent", + "kom\u00f6diant", + "schriftsetzerin", + "beamter", + "gr\u00fcnderin", + "gouverneur", + "koordinatorin", + "kunstmalerin", + "hydrologe", + "kaminkehrerin", + "covergirl", + "tagesarbeit", + "truchsess", + "statthalter", + "hochschullehrerin", + "marine", + "sicherheitsmann", + "versicherungsmathematiker", + "kinderbetreuer", + "buchh\u00e4ndlerin", + "ergotherapeut", + "schiffsjunge", + "quartiermeister", + "sprechstundenhilfe", + "the_boxer", + "beamtin", + "platzanweiser", + "schatzmeister", + "bew\u00e4hrungshelfer", + "m\u00fclldurchst\u00f6berer", + "mannschaftskapit\u00e4n", + "bleiarbeiter", + "tacker", + "point_guard", + "hilfskellner", + "kopfgeldj\u00e4ger", + "recorder", + "wallah", + "meier", + "edelknabe", + "spielerin", + "blechschmiedin", + "wissenschafterin", + "rudergast", + "the_hire", + "die_sonne_im_gesicht", + "the_machinist", + "tiermediziner", + "schildwache", + "glasmacher", + "abbimsen", + "usher", + "gardist", + "sch\u00e4ferin", + "messenger", + "setzerin", + "narkose\u00e4rztin", + "chauffeur", + "schiffbauer", + "malocher", + "schneiderin", + "torsch\u00fctze", + "buchverk\u00e4ufer", + "chemiker", + "neurologe", + "schweineh\u00fcter", + "kartograf", + "au_pair", + "die_r\u00e4ttin", + "narkosenfach\u00e4rztin", + "vollmatrose", + "gehirnchirurgin", + "sammlerin", + "regentin", + "paaren", + "wissenschaftlerin", + "sentry", + "proconsul", + "kameraoperateur", + "saisonal", + "cox", + "schreinerin", + "marschall", + "z\u00f6llnerin", + "briefzusteller", + "ladeninhaber", + "meereskundlerin", + "schiava", + "zeitungsjunge", + "\u00f6ffentlicher_dienst", + "s\u00e4gerin", + "blechschmied", + "berufschauffeur", + "trier", + "assistentin", + "steinmetzin", + "weinleser", + "fris\u00f6rin", + "schneckenkanker", + "heimwerker", + "pf\u00f6rtner", + "stuckateur", + "granatier", + "kinder\u00e4rztin", + "steuermannsmaat", + "sch\u00f6pfer", + "packerin", + "tonk\u00fcnstler", + "flugbegleiter", + "ballonflieger", + "plotter", + "setzer", + "schliesserin", + "brieftr\u00e4ger", + "geldverdienerin", + "ladeninhaberin", + "k\u00f6nig", + "verweser", + "saitenaufzieher", + "vermesser", + "wund\u00e4rztin", + "fensterputzer", + "fahnentr\u00e4ger", + "croupier", + "ziegenhirte", + "steward", + "gouvernante", + "courier", + "wehrpflichtiger", + "novellist", + "fangleine", + "presbyter", + "polsterer", + "extern", + "frauen\u00e4rztin", + "steuereinnehmer", + "katschmarek", + "concierge", + "broterwerberin", + "dingen", + "therapeutin", + "kinderh\u00fcterin", + "wildh\u00fcter", + "doula", + "hausmeister", + "schafhirte", + "engelmacher", + "tuner", + "abbreviator", + "streikbrecher", + "gr\u00fcnder", + "sigrist", + "sub", + "kesselflicker", + "romancier", + "ackermann", + "teeb\u00fcchse", + "justizvollzugsbeamtin", + "neurochirurgin", + "the_independent", + "schulleiterin", + "ordonanz", + "turner", + "solicitor", + "bishop", + "schlussmann", + "maurerin", + "wortf\u00fchrerin", + "leiterin", + "konnetabel", + "flugzeugf\u00fchrer", + "meereskundler", + "humoristin", + "schauspieler", + "neurologin", + "cookie", + "beleber", + "der_doktor", + "hauptgesch\u00e4ftsf\u00fchrer", + "neurochirurg", + "zeitweilig", + "bankier", + "immunologe", + "esquire", + "seefahrer", + "geldverdiener", + "arbeiter", + "staatsanw\u00e4ltin", + "keeperin", + "oberstleutnant", + "tagl\u00f6hnerin", + "oberstabsgefreiter", + "stadtvater", + "ophthalmologe", + "rocker", + "allesk\u00f6nner", + "f\u00f6rsterin", + "friseuse", + "zuckerb\u00e4cker", + "hausverwalterin", + "paddler", + "gatekeeper", + "b\u00fcrgermeisterin", + "autor", + "melkerin", + "cartoonist", + "stenotypistin", + "loader", + "schoff\u00f6r", + "gouverneurin", + "kerkermeister", + "besaiter", + "krankenhausarzt", + "friedensstifterin", + "sicherheitshelm", + "briefbote", + "banker", + "wandergeselle", + "du_bist_nie_allein", + "kirchenmusiker", + "die_durch_die_h\u00f6lle_gehen", + "quadratsekunde" + ], + "PUBLIC_FIGURE": [ + "lawrence_durrell", + "henry_cavendish", + "matthew_arnold", + "goldmark", + "rotk\u00e4ppchen", + "gregor", + "benjamin_franklin", + "martin_buber", + "akira_kurosawa", + "frances_wright", + "maria_tallchief", + "noah_webster", + "jean_genet", + "john_knox", + "heinrich_hertz", + "the_king", + "jean_laffite", + "roger_williams", + "giovanni_boccaccio", + "cornelius_vanderbilt", + "huntington", + "rudolf_steiner", + "thomas_wolfe", + "david_rittenhouse", + "thomas_bayes", + "ben_hogan", + "johann_bernoulli", + "max_bruch", + "charles_best", + "leonard_bernstein", + "sibelius", + "che_guevara", + "kline", + "georges_simenon", + "c", + "shukow", + "i_a_richards", + "thomas_hodgkin", + "john_barth", + "edward_albee", + "dorothy_parker", + "maria_callas", + "william_walton", + "henrik_ibsen", + "morgan", + "mary_shelley", + "franz_werfel", + "marcello_malpighi", + "peter_lorre", + "karl_baedeker", + "naumann", + "david_livingstone", + "eduard_buchner", + "david_smith", + "john_herschel", + "henry_villard", + "gauss", + "andrzej_wajda", + "jan_van_eyck", + "carl_rogers", + "george_balanchine", + "bethe", + "georg_wilhelm_steller", + "richard_burton", + "douglas_macarthur", + "mary_wollstonecraft", + "j_edgar_hoover", + "maria_magdalena", + "thomas_reid", + "otto_frisch", + "winston_churchill", + "gustav", + "johannes_diderik_van_der_waals", + "longinos", + "b", + "conrad_aiken", + "karl_landsteiner", + "schmid", + "paul_mccartney", + "andrew_marvell", + "terry_pratchett", + "k", + "kurie", + "stephen_king", + "francis_crick", + "peter_o\u2019toole", + "john_trumbull", + "sherry", + "joseph_greenberg", + "isaac_newton", + "sherman", + "alfred_eisenstaedt", + "victor_hugo", + "joseph_smith", + "edwin_hubble", + "der_hofnarr", + "colette", + "milton_friedman", + "inge", + "amy_lowell", + "edward_gibbon", + "schiaparelli", + "jefferson_davis", + "cass_gilbert", + "george_stephenson", + "john_glenn", + "john_webster", + "john_davis", + "george_burns", + "george_harrison", + "peter_minuit", + "george_orwell", + "georg_meissner", + "arthur_koestler", + "richard_wagner", + "williams", + "auf_augenh\u00f6he_mit", + "thornton_wilder", + "e_l_doctorow", + "pancho_villa", + "leopold_stokowski", + "rebecca_west", + "marie_curie", + "francis_galton", + "volksverhetzer", + "mary_martin", + "michael_jackson", + "carl_sandburg", + "thomas_hobbes", + "seleucus", + "edward_weston", + "el_greco", + "waller", + "engelbert", + "samuel_beckett", + "maximian", + "david", + "saubl\u00f6d", + "galileo_galilei", + "ernest_bevin", + "jane_goodall", + "der_fliegende_holl\u00e4nder", + "john_donne", + "chaim_weizmann", + "der_auserw\u00e4hlte", + "robert_l_mills", + "andrea_guarneri", + "robert_koch", + "joseph_goebbels", + "george_eastman", + "john_steinbeck", + "erich_mendelsohn", + "die_auserw\u00e4hlte", + "edmund_hillary", + "vincent_van_gogh", + "richard_hooker", + "w", + "william_hazlitt", + "martina_navr\u00e1tilov\u00e1", + "marie_stopes", + "anne_boleyn", + "josef_stalin", + "john_ruskin", + "robert_burns", + "john_henry", + "carl_anderson", + "thomas_paine", + "bari", + "1st_armoured_division", + "francis_beaumont", + "antun", + "grosswesir", + "steven_weinberg", + "passivrauchen", + "p", + "mary_pickford", + "hans_fischer", + "emiliano_zapata", + "elisabet", + "karl_barth", + "willem_einthoven", + "phil_anderson", + "thomas_willis", + "bernard_malamud", + "samuel_johnson", + "jesus", + "allen_iverson", + "marie_antoinette", + "anne_hutchinson", + "louise_nevelson", + "giuseppe_verdi", + "walter_lippmann", + "e", + "hoffnung", + "scheele", + "karl_jaspers", + "beethoven", + "konrad_adenauer", + "superduper", + "c_vann_woodward", + "john_l_lewis", + "marianne_moore", + "norbert_wiener", + "john_masefield", + "horatio_nelson", + "mark_rothko", + "maurice_chevalier", + "gottlieb_daimler", + "frank_sinatra", + "abel_tasman", + "katharine_hepburn", + "grossinquisitor", + "henri_becquerel", + "henri_matisse", + "bertram_brockhouse", + "louis_pasteur", + "hoffmann", + "j", + "richard_strauss", + "leslie_howard", + "theodosius_i", + "hugo_grotius", + "mahalia_jackson", + "strohdumm", + "ben_shahn", + "john_ford", + "stephen_foster", + "alphonse_bertillon", + "katherine_mansfield", + "gertrude_stein", + "j_b_s_haldane", + "saladin", + "sarah_bernhardt", + "j\u00fcrgen", + "kunsth\u00e4ndlerin", + "v", + "philip_marlowe", + "luigi_pirandello", + "t_s_eliot", + "e_g_marshall", + "marc_blitzstein", + "hank_williams", + "nicht_zutreffend", + "rube_goldberg", + "dorothea_lange", + "james_thurber", + "charles_de_gaulle", + "paul_von_hindenburg", + "y", + "henry_moore", + "schumann", + "holden", + "mary_mallon", + "ralph_bunche", + "rudolf_bultmann", + "charles_lindbergh", + "vincenzo_bellini", + "samuel_barber", + "goggelmoggel", + "tobias_smollett", + "f", + "john_jay", + "ludwig_wittgenstein", + "august_strindberg", + "stalin", + "bunyan", + "thomas_mann", + "schutzheiliger", + "nicht_auswertbar_n.a", + "alla_nazimova", + "charles_goodyear", + "dante_alighieri", + "margot_fonteyn", + "peter_pan", + "james_tobin", + "john_irving", + "samuel_de_champlain", + "davit", + "giacomo_puccini", + "edward_fitzgerald", + "fridtjof_nansen", + "louis_braille", + "herbert_marcuse", + "mungo_park", + "benedict_arnold", + "paul_verlaine", + "q", + "james_a_murray", + "scribes", + "robert_johnson", + "tanasee", + "james_dean", + "robert", + "marie_tussaud", + "mezzosopran", + "roger_bannister", + "heinrich_i", + "theodor_schwann", + "max_beerbohm", + "rupprecht", + "alessandro_manzoni", + "joseph_priestley", + "hal", + "louis_joliet", + "nicolas_poussin", + "andrea_mantegna", + "joseph_pulitzer", + "ring_lardner", + "george_huntington", + "jim_corbett", + "james_naismith", + "oscar_wilde", + "wilms", + "philip_roth", + "j_d_salinger", + "henry", + "lawrence", + "richard_trevithick", + "luigi_montefiori", + "william_bradford", + "heinrich_schliemann", + "peter_der_grosse", + "eli_whitney", + "staatsoberhaupt", + "glenn_curtiss", + "ballettt\u00e4nzer", + "don_quijote", + "s_radhakrishnan", + "laurence_olivier", + "georg", + "hussein", + "pierre_larousse", + "christiaan_eijkman", + "adolf_eichmann", + "marilyn_horne", + "francis_bacon", + "pete_seeger", + "joseph_heller", + "a", + "morris", + "peter_carl_goldmark", + "peter_brian_medawar", + "norman_rockwell", + "eins", + "widerstandsf\u00e4hig", + "james_brown", + "william_hogarth", + "charles_baudelaire", + "luigi_cherubini", + "david_ricardo", + "henri_labrouste", + "mary_leakey", + "charlie_parker", + "z", + "immanuel_kant", + "james_franck", + "william_crookes", + "james_meredith", + "samuel_gompers", + "igor_strawinsky", + "nellie_bly", + "weber", + "lewis", + "warburg", + "octavius", + "n", + "stephen_leacock", + "a_one", + "albert_schweitzer", + "minuszeichen", + "john_harvard", + "johann_friedrich_herbart", + "giulio_natta", + "titus", + "johannes_kepler", + "william_s_burroughs", + "most", + "david_hartley", + "schornsteinfegerin", + "max_planck", + "hauptfeldwebel", + "william_blake", + "t_e_lawrence", + "julio_iglesias", + "john_bardeen", + "arthur", + "sarah_vaughan", + "nietzsche", + "john_wilkes", + "william_byrd", + "william_henry", + "christopher_fry", + "scott_joplin", + "carl_lewis", + "fernsteuerung", + "sarah_siddons", + "george_vancouver", + "canberra", + "elias_canetti", + "robert_lowell", + "eisenstein", + "edward_jenner", + "john_mercer", + "oscar_robertson", + "oliver_hardy", + "holzl\u00f6ffel", + "zaunk\u00f6nige", + "auf_einer_h\u00f6he_mit", + "cole_porter", + "benjamin_west", + "jean_luc_godard", + "birnenwein", + "konstantin", + "graham_greene", + "frans_hals", + "edward", + "whistler", + "lars_onsager", + "auf_einer_ebene_mit", + "margaret_mitchell", + "stuart_davis", + "lola_montez", + "jan_swammerdam", + "baucht\u00e4nzer", + "mary_mccarthy", + "david_riesman", + "john_walker", + "reichsidee", + "flavius_josephus", + "joseph_black", + "marcus_whitman", + "mikhail_baryshnikov", + "bombenexplosion", + "niels_bohr", + "kenneth_grahame", + "henry_fielding", + "bertrand_russell", + "katherine_anne_porter", + "michael_faraday", + "john_d_rockefeller", + "anthony_burgess", + "jan_tinbergen", + "charles_de_secondat_baron_de_montesquieu", + "robert_venturi", + "johnny_appleseed", + "irving_berlin", + "tambourmajor", + "bernard_baruch", + "rudolf_diesel", + "walt_disney", + "ben_jonson", + "peter", + "die_meisten", + "h_l_mencken", + "maria_von_magdala", + "joseph_schumpeter", + "gabriel_lippmann", + "steve_reich", + "lee", + "benny_goodman", + "ted_williams", + "karl_menninger", + "friedrich_engels", + "jane_austen", + "charles_laughton", + "parker", + "moses", + "gustav_mahler", + "ed_sullivan", + "phil_collins", + "alice_paul", + "robert_redford", + "jean_giraudoux", + "jack_dempsey", + "ian_fleming", + "richard_feynman", + "puschkin", + "wolfgang_pauli", + "auf_den_punkt_gebracht", + "theodore_dreiser", + "theodor_mommsen", + "marcel_proust", + "jessica_mitford", + "thomas_more", + "homo_heidelbergensis", + "paul_hindemith", + "elizabeth_taylor", + "thomas_chippendale", + "paul_robeson", + "arnold", + "thomas_middleton", + "kernarbeitszeit", + "john_dowland", + "daniel_jones", + "schwurjungfrau", + "william_golding", + "robert_motherwell", + "a_e_housman", + "william_caxton", + "john_milton", + "rudolf_serkin", + "ethel_merman", + "frank_baum", + "samuel_adams", + "albert_speer", + "james_baldwin", + "john_vanbrugh", + "indira_gandhi", + "jane_seymour", + "george_gershwin", + "alberto_giacometti", + "e_t_a_hoffmann", + "frank_whittle", + "alfred_nobel", + "jesse_owens", + "daniel_rutherford", + "marco_polo", + "john_fletcher", + "charlie_watts", + "m", + "charlotte_corday", + "marcel_marceau", + "allen_ginsberg", + "fred_zinnemann", + "petros", + "daniel_bernoulli", + "guillaume_apollinaire", + "s\u00fcdlicher_schweinsaffe", + "antoine_watteau", + "brandt", + "joseph_henry", + "henri_bergson", + "antonius", + "edward_macdowell", + "josef_hoffmann", + "boris_karloff", + "pierre_corneille", + "phillis_wheatley", + "patrick_white", + "hans_zinsser", + "saul_steinberg", + "bartholomew_roberts", + "eileen_farrell", + "catherine_howard", + "daniel_morgan", + "hans_christian_andersen", + "peter_cooper", + "reich", + "william_morris", + "cary_grant", + "thomas", + "isaac_watts", + "ford", + "pieter_zeeman", + "arnold_gesell", + "glenn_miller", + "steward", + "pablo_picasso", + "marian_anderson", + "natalie_wood", + "l_ron_hubbard", + "thomas_moore", + "osman_i", + "kurt_weill", + "otto_hahn", + "lester_young", + "john_marshall", + "christiaan_huygens", + "hector_berlioz", + "lucille_ball", + "paul_simon", + "claudio_monteverdi", + "benjamin_jowett", + "taubstumm", + "robert_scott", + "john_galsworthy", + "robert_robinson", + "ziegler", + "o", + "adam_smith", + "william_james", + "von_willebrand_faktor", + "u", + "jean_harlow", + "henry_miller", + "karl_marx", + "paul_bunyan", + "friedrich_nietzsche", + "i", + "robert_indiana", + "jimmy_durante", + "john_wesley", + "f\u00f6rsterin", + "sandro_botticelli", + "carson_mccullers", + "bloch", + "seiji_ozawa", + "nikola_tesla", + "al_capone", + "charles_barkley", + "billy_graham", + "robert_schumann", + "mel_gibson", + "le_corbusier", + "carlo_goldoni", + "balduin", + "zahnfee", + "john_locke", + "alexis_carrel", + "leonhard", + "joseph_marie_jacquard", + "henry_james", + "stephen_sondheim", + "st_martin", + "oscar_hammerstein", + "lorenz_hart", + "perry", + "helen_keller", + "paul_dukas", + "ingrid_bergman", + "denmark_vesey", + "leonard_bloomfield", + "jane_jacobs", + "lulli", + "jean_piaget", + "william_congreve", + "j\u00f6rgen", + "franz_kline", + "henri_rousseau", + "paul_tillich", + "hilaire_belloc", + "kronenducker", + "baucht\u00e4nzerin", + "frank_norris", + "frank_stella", + "jaden", + "robert_southey", + "h_g_wells", + "walt_whitman", + "william_wyler", + "john_osborne", + "colin_powell", + "ludwig_boltzmann", + "carl_nielsen", + "leopold_kronecker", + "richard_wright", + "benjamin_thompson", + "adolf_hitler", + "maria_mitchell", + "fritz_haber", + "archibald_macleish", + "peter_behrens", + "alfred_stieglitz", + "joseph_haydn", + "stephen_spender", + "garfield", + "die_wahrsagerin", + "george_boole", + "hans_reiter", + "paul_revere", + "daniel_boone", + "buffalo_bill", + "edvard_grieg", + "jacques", + "kernzeit", + "robert_boyle", + "edith_cavell", + "alan_paton", + "ralph_richardson", + "1", + "schubert", + "cordell_hull", + "james_wilson", + "rosa_parks", + "norman_jewison", + "samuel_goldwyn", + "steller", + "x", + "ernest_walton", + "jacob", + "giuseppe_mazzini", + "jim_thorpe", + "hertz", + "h", + "randall_jarrell", + "arnold_sch\u00f6nberg", + "laurence_sterne", + "hetzer", + "hutchinson", + "jacqueline_cochran", + "george_fox", + "ben_hecht", + "christopher_isherwood", + "fritz_kreisler", + "anne_hathaway", + "david_garrick", + "don_budge", + "bill_russell", + "baldwin", + "jeannette_rankin", + "clarence_darrow", + "charles_lamb", + "harry", + "g", + "anthony_comstock", + "arthur_schopenhauer", + "thomas_dekker", + "james_cagney", + "john_keble", + "johns_hopkins", + "wanda_landowska", + "a_a_p", + "billy_mitchell", + "martin_heidegger", + "r", + "george_lucas", + "andrew_jackson", + "edith_wharton", + "louis_armstrong", + "antony_tudor", + "steven_spielberg", + "l\u00e9onide_massine", + "sydenham", + "jean_monnet", + "leonard", + "robert_fulton", + "thomas_hardy", + "thomas_gainsborough", + "giuseppe_garibaldi", + "philip_warren_anderson", + "robert_brown", + "thomas_carlyle", + "allen_tate", + "donald_barthelme", + "william_tyndale", + "bobby_fischer", + "johannes_gutenberg", + "d", + "james_bowie", + "giambattista_marino", + "gaetano_donizetti", + "wilhelm_herschel", + "william_faulkner", + "andre", + "amerigo_vespucci", + "arthur_holmes", + "schmied", + "laurentius", + "pierre_boulez", + "hans_adolf_krebs", + "lars", + "girolamo_savonarola", + "emma_goldman", + "robert_gray", + "francis_poulenc", + "james_ussher", + "john_barrymore", + "john_constable", + "james_mill", + "john_ciardi", + "e_entertainment_television", + "putin", + "matthew_flinders", + "a_e_network", + "robert_herrick", + "joseph_campbell", + "st_peter", + "jean_de_la_fontaine", + "robert_hooke", + "tschaikowski", + "o_henry", + "karl_popper", + "alfred", + "coleman_hawkins", + "m\u00fcllerin", + "george_sand", + "peter_sellers", + "homo_rhodesiensis", + "charles_fourier", + "john_mcgraw", + "henry_clay", + "joseph_conrad", + "edmund_halley", + "william_shockley", + "g\u00fcnter_grass", + "kenneth_roberts", + "peter_paul_rubens", + "jim_morrison", + "moyses", + "cromwell", + "jules_verne", + "paul_newman", + "robert_mills", + "george_meredith", + "robert_morris", + "lili\u02bbuokalani", + "woody_herman", + "alexander_wilson", + "josef_albers", + "jackson_pollock", + "david_crockett", + "brigadegeneral", + "ururgrosselternteil", + "john_lennon", + "andrea_palladio", + "gesch\u00e4ftsf\u00fchrerin", + "gandhi", + "bob_woodward", + "charlie_chaplin", + "lillian_russell", + "d_h_lawrence", + "j_m_barrie", + "schutzpatronin", + "schukow", + "thomas_malory", + "patrick_von_irland", + "lea", + "john_brown", + "al_jolson", + "elizabeth_gaskell", + "john_mill", + "hugo_junkers", + "norman_thomas", + "lillian_hellman", + "brescia", + "thomas_merton", + "asa_gray", + "sehr_gut", + "hannah_arendt", + "antonio_stradivari", + "robinson_jeffers", + "alice_walker", + "kunsth\u00e4ndler", + "staatschef", + "strauss", + "miles_davis", + "octavian", + "bruce", + "james_parkinson", + "wilhelm_tell", + "harold_nicolson", + "jesse_jackson", + "willa_cather", + "bozen", + "stanley_kubrick", + "john_deere", + "john_huston", + "kaminkehrer", + "william_gilbert", + "schutzpatron", + "james_watt", + "jonathan_edwards", + "ronald_reagan", + "helmut_schmidt", + "jenny_lind", + "homo", + "frederick_douglass", + "david_hilbert", + "wilhelm_reich", + "zween", + "oliver_cromwell", + "beaumont", + "lionel_hampton", + "martin_luther_king", + "james_hargreaves", + "lorenz", + "frank_capra", + "william_wordsworth", + "rex_harrison", + "s", + "william_clark", + "woodrow_wilson", + "william_wycherley", + "margaret_sanger", + "deutsche_lautverschiebung", + "gustav_hertz", + "george_mason", + "george_wallace", + "el_cid", + "marcus_antonius", + "lake_powell", + "prachteiderente", + "agrippina", + "st_louis", + "richard_rodgers", + "schornsteinfeger", + "don_quixote", + "kleist", + "anne_sexton", + "john_dryden", + "jim_henson", + "weisshalssylphe", + "frank", + "ernest_hemingway", + "fiedler", + "john_eccles", + "george_westinghouse", + "simon_petrus", + "aquila", + "eero_saarinen", + "arthur_miller", + "john_cheever", + "gracie_allen", + "billy_sunday", + "nelson_mandela", + "heinrich_himmler", + "al_gore", + "john_rutledge", + "hans_bethe", + "hans_geiger", + "cesare_borgia", + "j_p_morgan", + "hochschulreife", + "roald_amundsen", + "sherwood_anderson", + "richard_leakey", + "alfred_korzybski", + "c_a", + "anton", + "charles_dickens", + "samuel_huntington", + "ella_fitzgerald", + "fats_waller", + "thomas_sydenham", + "jack_robinson", + "alois_senefelder", + "george_enescu", + "jacques_offenbach", + "joseph_paxton", + "william_curtis", + "william_chambers", + "gilbert", + "leakey", + "george_stevens", + "federico_fellini", + "bessie_smith", + "bradley", + "patrick_henry", + "willy_brandt", + "charles_wilkes", + "francisco_pizarro", + "francisco_franco", + "jackie_robinson", + "bernardo_bertolucci", + "jan_steen", + "frank_harris", + "e_e_cummings", + "john_ross", + "powell", + "gentilname", + "hans_arp", + "andrew_carnegie", + "pontius_pilatus", + "achteinhalb", + "schutzengel", + "christoph_kolumbus", + "franz_schubert", + "william_butterfield", + "johnny_cash", + "joseph_mccarthy", + "hans_j\u00fcrgen_eysenck", + "alfred_kastler", + "mick_jagger", + "otto_loewi", + "friedrich_max_m\u00fcller", + "georges_cuvier", + "herzk\u00f6nig", + "william_harvey", + "de_vliegende_hollander", + "walter_scott", + "august_von_wassermann", + "jenner", + "sam_houston", + "wilder", + "der_kleine_lord", + "robert_browning", + "seleukos", + "alessandro_farnese", + "st_georg", + "ralph_ellison", + "john_bunyan", + "jonathan_swift", + "walter_gropius", + "albert_einstein", + "l", + "henry_sweet", + "aletta_jacobs", + "birnenmost", + "chiang_kai_shek", + "claude_bernard", + "raymond_chandler", + "mehrj\u00e4hrig", + "henry_purcell", + "der_heilige_georg", + "kaminkehrerin", + "flannery_o\u2019connor", + "schutzheilige", + "t", + "von_neuem", + "wilhelm_ostwald" + ], + "FAC": [ + "regierungsgeb\u00e4ude", + "strafarrest", + "bockwindm\u00fchle", + "gefechtsstand", + "ochsenauge", + "zollamt", + "kreuzkap", + "die_vier_jahreszeiten", + "das_letzte_abendmahl", + "volksfront", + "druckerei", + "zyklopenmauer", + "schwimmbecken", + "einkaufszentrum", + "steinwand", + "konzertsaal", + "schiessanlage", + "der_zauberberg", + "burgtor", + "papierfabrik", + "schwanzloch", + "steinmauer", + "hauptbahnhof", + "fronleichnam", + "trockenmauerwerk", + "windkanal", + "regierungsbau", + "polizeirevier", + "pendelt\u00fcr", + "b\u00fcrohaus", + "eisenbahnhof", + "ingenieurb\u00fcro", + "arnold_sch\u00f6nberg", + "trainingslager", + "pumpwerk", + "kaffernlimette", + "grundschule", + "trinkbrunnen", + "mari\u00e4_verk\u00fcndigung", + "polizeistation", + "gezeitenm\u00fchle", + "stadtbahn", + "frente_popular", + "in_einzelschritten", + "mall", + "steinhaus", + "kapitelsaal", + "kunsthochschule", + "dampfm\u00fchle", + "papierm\u00fchle", + "medizinische_fakult\u00e4t", + "kommandoposten", + "kunstgalerie", + "wellenbad", + "t_zelle", + "saint_lucia", + "zollhaus", + "katholische_kirche", + "guardian_angels", + "r\u00f6misch_katholische_kirche", + "klappenloch", + "bus_terminal", + "klagemauer", + "schwingt\u00fcr", + "m\u00fchldamm", + "aussichtsturm", + "georgskreuz", + "hamm\u0101m", + "klaugemauer", + "e_werk", + "volksschule", + "das_abendmahl", + "josef_von_nazaret", + "flottenst\u00fctzpunkt", + "titus_livius", + "vorlesungssaal", + "kleinweis", + "dreiunddreissig", + "lazarett", + "schiessplatz", + "stirnseite", + "ottomanisches_reich", + "holzhaus", + "gute_nachricht", + "die_fallt\u00fcr", + "bootcamp", + "polizeidienststelle", + "fl\u00fcgelfenster", + "hohe_pforte", + "t_lymphozyt", + "postfiliale", + "friedrichshain_kreuzberg", + "pu_der_b\u00e4r", + "peter_der_grosse", + "schiessstand", + "postamt" + ], + "SOC_ECO_CLASS": [ + "trade", + "bruderschaft", + "b\u00fcrgertum", + "landadel", + "labor", + "center", + "oberschicht", + "verbrecherwelt", + "spiessb\u00fcrgertum", + "schwarzmarkt", + "samurai", + "noblesse", + "banausie", + "rittertum", + "lumpenproletariat", + "kindklasse", + "agrikultur", + "proletariat", + "demimonde", + "frausein", + "adelsstand", + "gentry", + "unterklasse", + "drittklassig", + "philisterei", + "weinig", + "waki", + "mittelklasse", + "inspiriert", + "pick", + "banausentum", + "hochgeistig", + "bourgeoisie", + "kleinb\u00fcrgertum", + "ritterschaft", + "vierte_gewalt", + "yeomanry", + "halbwelt", + "highbrow" + ], + "ANIMAL": [ + "schr\u00f6ter", + "dottersack", + "grosser_schillerfalter", + "felsenh\u00e4hne", + "siebenschl\u00e4fer", + "rehbock", + "damwild", + "laufk\u00e4fer", + "yurumi", + "schermaus", + "baumhopf", + "acherontia", + "sandbankhai", + "dickhornschaf", + "rankenfusskrebs", + "wanderalbatros", + "fleckenkauz", + "schwarzfussalbatros", + "brillenkormoran", + "m\u00fcckenfledermaus", + "schnaken", + "gelbb\u00e4uchig", + "gr\u00fcndling", + "hundsrobben", + "palmtaube", + "kurznasenb\u00e4r", + "riesenalk", + "packesel", + "cat", + "pfauentruthuhn", + "breitmaulnashorn", + "haarraupe", + "diensthund", + "schwarzkopfmeise", + "spiessflughuhn", + "mondb\u00e4r", + "weisswedelhirsch", + "schwertst\u00f6r", + "zober", + "uferschwalbe", + "streifenskunk", + "flohk\u00e4fer", + "saumkamel", + "k\u00f6nigskobra", + "randal", + "haselmaus", + "rotgesichtscharbe", + "zitronenhai", + "buteo", + "hausmaus", + "calimocho", + "goldwangenwalds\u00e4nger", + "bienenweisel", + "trompeterschwan", + "gr\u00fcn\u00e4ugig", + "fichtenmarder", + "barbarieente", + "mittelmeerfruchtfliege", + "feldspatz", + "zaunk\u00f6nige", + "adeliepinguin", + "bachforelle", + "grasfrosch", + "wildschweinrudel", + "tabakmosaikvirus", + "pfeifschwan", + "rothuhn", + "kr\u00e4henvogel", + "singschwan", + "petersfisch", + "rauhautfledermaus", + "breitrandschildkr\u00f6te", + "zauneidechse", + "schwarzkittel", + "vaginalpilz", + "braunliest", + "strahlf\u00e4ule", + "buntfalke", + "drosophila", + "steinhuhn", + "homo_sapiens_sapiens", + "hexagrammos_otakii", + "herm\u00e4nnchen", + "wildpferd", + "waldameise", + "k\u00f6nigstiger", + "marderhund", + "fuchsh\u00f6rnchen", + "salmo_gairdneri", + "europ\u00e4ische_forelle", + "die_betrogene", + "riesenschildkr\u00f6te", + "blasentang", + "graur\u00f6telmaus", + "pottwal", + "louisianaw\u00fcrger", + "w\u00fcstenleguan", + "wildeber", + "schwarzfussiltis", + "silberdachs", + "forellenbarsch", + "kleinwiesel", + "g\u00fcrtelfischer", + "kurzfangsperber", + "schneeschuhhase", + "ringeltaube", + "schwarzhai", + "lenze", + "ammenhaiartige", + "dreiecksnatter", + "schuhu", + "fangschreckenkrebse", + "silberkopfm\u00f6we", + "otter", + "paarzeher", + "rubinfleckwalds\u00e4nger", + "dachs", + "polarwolf", + "sturmschwalbe", + "firefox", + "trampeltier", + "schuppenhalstaube", + "wolfspinne", + "grauastrild", + "apfelfruchtfliege", + "spatelente", + "weisel", + "sichelstrandl\u00e4ufer", + "graugans", + "hudsonschnepfe", + "tannenh\u00e4her", + "wiesenstrandl\u00e4ufer", + "baummarder", + "humanes_immundefizienz_virus", + "schlafmaus", + "kanadareiher", + "bindenstrandl\u00e4ufer", + "lagopus_mutus", + "suppenschildkr\u00f6te", + "seidenreiher", + "samenk\u00e4fer", + "gleitbilche", + "kappenastrild", + "rauchschwalbe", + "reisetaube", + "brandgans", + "ringelgans", + "apportierhund", + "stadttaube", + "fleischfliege", + "thomson_gazelle", + "westliche_gr\u00fcnmeerkatze", + "bohrfliege", + "weissstorch", + "arkansask\u00f6nigstyrann", + "blattk\u00e4fer", + "steppenzebra", + "bandfisch", + "sitta_europaea", + "schwammspinner", + "wechselkr\u00f6te", + "miesmuschel", + "buntlori", + "riesenhai", + "feenastrild", + "wandertaube", + "grindwale", + "baumkauz", + "hauskater", + "haubentaucher", + "kurzfl\u00fcgler", + "mandarinente", + "goldk\u00e4fer", + "pfingstvogel", + "schweinsdachs", + "rosaflamingo", + "fischblase", + "vierzehenschildkr\u00f6te", + "drahthaarfox", + "arthropoden", + "sackratte", + "hausrotschwanz", + "kaiserpinguin", + "nashornk\u00e4fer", + "tragtier", + "kammz\u00e4hnerhaie", + "drosseluferl\u00e4ufer", + "schwarzdrossel", + "schildl\u00e4use", + "grash\u00fcpferm\u00e4use", + "katze", + "jagdhund", + "eulenvogel", + "weisshandgibbon", + "zitterrochenartige", + "wollnashorn", + "seggenzaunk\u00f6nig", + "amazonenameise", + "b\u00e4renpavian", + "tibetb\u00e4r", + "spinnmilben", + "schmuckreiher", + "canis_minor", + "wiesenpieper", + "waldlaubs\u00e4nger", + "manta", + "mondfisch", + "dachsammer", + "w\u00fcstenfledermaus", + "berglemming", + "spielhuhn", + "kleinpudel", + "schornsteinsegler", + "rundkopfdelfin", + "piesacken", + "wolfspinnen", + "haussperling", + "entenmuschel", + "engelhaie", + "sattelrobbe", + "riesenhonigbiene", + "sandhaie", + "greifvogel", + "waldschnepfe", + "l\u00f6wenwelpe", + "schn\u00e4pperwalds\u00e4nger", + "pisces", + "beutelteufel", + "meerengel", + "gr\u00fcnastrild", + "gemeine_meerbrasse", + "froschlurche", + "sandkatze", + "breitnasenaffe", + "eiderenten", + "spornkiebitz", + "schopfwachtel", + "windh\u00fcndin", + "grosse_wachsmotte", + "kornnatter", + "polarb\u00e4r", + "langbeinig", + "weisswal", + "panzerknurrh\u00e4hne", + "nashornpelikan", + "fleischfliegen", + "syncerus", + "totenkopfschw\u00e4rmer", + "silber\u00e4ffchen", + "elfenbeinspecht", + "haustaube", + "chipmunk", + "grauh\u00f6rnchen", + "halsbandsittich", + "fruchtfliege", + "schweinswale", + "maultierhirsch", + "stupsnasig", + "aaltierchen", + "rossameisen", + "knuttstrandl\u00e4ufer", + "lactobacillus_acidophilus", + "schneegans", + "wanderfalke", + "erdnatter", + "fangschrecken", + "k\u00f6nigsgeier", + "reisfink", + "granatastrild", + "reisk\u00e4fer", + "kropfgazelle", + "schwarze_schildkr\u00f6te", + "waldstorch", + "meisenh\u00e4her", + "nebelparder", + "paradiessittich", + "bergnyala", + "glatthaarfox", + "zobel", + "geburtshelferkr\u00f6te", + "holztaube", + "zitteraal", + "mauerbienen", + "bergwachtel", + "schneeleopard", + "rothalstaucher", + "eselhase", + "kleiner_eisvogel", + "carolinataube", + "spornschildkr\u00f6te", + "weissbartpekari", + "seidenlaubenvogel", + "hausieren", + "hornwehrvogel", + "waldelefant", + "schilfrohrs\u00e4nger", + "kreuzkr\u00f6te", + "doppelf\u00fcsser", + "wildsau", + "klammeraffen", + "lippenb\u00e4r", + "crow", + "rosenboa", + "strassentaube", + "killerwal", + "signalhund", + "rundschwanzsperber", + "steinkauz", + "gordon_setter", + "brandseeschwalbe", + "kahnschnabel", + "silberm\u00f6we", + "sumpfmeise", + "kleiner_hund", + "vibe", + "diamondback", + "atlantischer_hering", + "bergpieper", + "bartenwale", + "klapperstorch", + "berberschaf", + "seepocke", + "grosskopfig", + "k\u00f6cherfliege", + "hausgimpel", + "tannenmeise", + "reisebrieftaube", + "flussseeschwalbe", + "graufuchs", + "fratercula_arctica", + "silberreiher", + "ferkelskunk", + "unpaarhufer", + "faina", + "krallenfrosch", + "wiesel", + "gartenrotschwanz", + "nachtreiher", + "grevyzebra", + "womanizer", + "gemeine_goldmakrele", + "galgo", + "trottellumme", + "kornweihe", + "spazierstock", + "andenflamingo", + "goldhamster", + "basiliskencham\u00e4leon", + "arbeitshund", + "raven", + "seitenfleckleguane", + "streifenhy\u00e4ne", + "sperling", + "kartoffelk\u00e4fer", + "homo_sapiens", + "hirsche", + "rubingoldh\u00e4hnchen", + "singdrossel", + "rohrspatz", + "gallwespen", + "der_rabe", + "mink", + "falken", + "engelhai", + "tannenhuhn", + "harrier", + "baribal", + "habicht", + "l\u00f6wenjunges", + "grosser_kohlweissling", + "grauwal", + "feldwinkelspinne", + "kaisergranat", + "neuweltaffe", + "sprosser", + "rosenstar", + "lakeland_terrier", + "der_geier", + "sturmm\u00f6we", + "passer", + "grubenottern", + "leierhirsche", + "eiderente", + "rohrkatze", + "zedernseidenschwanz", + "moschusente", + "currybaum", + "maifisch", + "bisamochse", + "weisslippenhirsch", + "schwarzkopfruderente", + "riesenmanta", + "reisnonne", + "bussard", + "weisswangenkauz", + "schabrackenhy\u00e4ne", + "swiftfuchs", + "reisamadine", + "tapetenmotte", + "irischer_wolfshund", + "the_crow", + "spiessente", + "asselspinnen", + "feuersalamander", + "knochenfisch", + "seegurke", + "kreischeulen", + "rennvogel", + "windhundr\u00fcde", + "kleiner_schwarzspitzenhai", + "schellente", + "hound", + "rankenfusskrebse", + "virginiawachtel", + "hirschbock", + "k\u00f6nigspinguin", + "wasserb\u00fcffel", + "goldschakal", + "weisskopfseeadler", + "windhundwelpe", + "taubenteiste", + "sch\u00f6nb\u00fcrzel", + "blindenf\u00fchrhund", + "trp", + "amsel", + "kleiderlaus", + "braunalgen", + "langhaarig", + "streifenh\u00f6rnchen", + "sumpfschwalbe", + "elefantenvogel", + "polarfuchs", + "bindentaucher", + "rothirsch", + "hirschk\u00e4fer", + "gummiboa", + "waldkatze", + "rotalgen", + "komodowaran", + "h\u00fchnerhabicht", + "karolinasittich", + "cro_magnon", + "buckelwal", + "klappm\u00fctze", + "hinterlauf", + "mantarochen", + "javaneraffe", + "wildgans", + "bullenhai", + "strahlenschildkr\u00f6te", + "pestvogel", + "wildesel", + "felsenzaunk\u00f6nig", + "klappergrasm\u00fccke", + "sperber", + "nitidotellina_nitidula", + "kitfuchs", + "bankivahuhn", + "staffordshire_bullterrier", + "kreischeule", + "schwarzb\u00e4r", + "schelladler", + "kaisergans", + "b\u00e4renjunges", + "marter", + "gleith\u00f6rnchen", + "victoria_regia", + "kammratten", + "kiebitze", + "waldm\u00e4use", + "flinderskette", + "molukkenibis", + "russseeschwalbe", + "spinnenl\u00e4ufer", + "greyhound", + "kundus", + "die_m\u00f6we", + "bartenwal", + "waldmaus", + "grosse_schillerfalter", + "stieglitz", + "gr\u00fcne_meerkatze", + "goldkr\u00f6te", + "osterhase", + "schwarzer_b\u00fcffelfisch", + "armeleute", + "steinadler", + "kongopfau", + "schabrackentapir", + "eichh\u00f6rnchen", + "mizuhiki", + "schwalbenweih", + "w\u00fcstenspringmaus", + "milchvieh", + "doppelschnepfe", + "baumhopfe", + "grauwasseramsel", + "bartkauz", + "lachm\u00f6we", + "gottesanbeterin", + "haushuhn", + "wildente", + "feldsperling", + "waldkauz", + "andenbauml\u00e4ufer", + "archebakterie", + "braunb\u00e4r", + "bergziege", + "wasserhund", + "einsiedlerdrossel", + "schnappschildkr\u00f6te", + "polizeih\u00fcndin", + "banteng", + "bienenk\u00f6nigin", + "andenkondor", + "cockerspaniel", + "schwalbenm\u00f6we", + "r\u00fcckenflosse", + "versuchskaninchen", + "carolinakleiber", + "wasserralle", + "regenbogenforelle", + "lappenente", + "grosstrappe", + "regenbogencichlide", + "schwarzhalstaucher", + "maulwurfsgrille", + "mantelm\u00f6we", + "elster", + "rotaugenvireo", + "flussbarsch", + "panzerkrokodil", + "wilsonbekassine", + "gimpel", + "spint", + "gr\u00f6nlandwal", + "langschwanzschuppentier", + "arthropode", + "einsiedlerkrebs", + "polarr\u00f6telmaus", + "meerschwalbe", + "schwarzmilan", + "eubakterie", + "wasserpieper", + "netzpython", + "hochsee_weissflossenhai", + "donald_duck", + "helmperlhuhn", + "baltimoretrupial", + "hakengimpel", + "bachsaibling", + "schnellk\u00e4fer", + "stockmutter", + "gilbdrossel", + "kriebelm\u00fccken", + "iller", + "rappenantilope", + "moose", + "kanadakranich", + "mehlk\u00e4fer", + "eichk\u00e4tzchen", + "w\u00fcstengoldspecht", + "seidenraupe", + "kammzahnvampir", + "wisent", + "bauchflosse", + "berner_sennenhund", + "kuhreiher", + "eulen", + "k\u00f6niginmutter", + "nasenaffe", + "st\u00e4rlinge", + "helmkopfgecko", + "lastkamel", + "fichtenkreuzschnabel", + "hauptfeldwebel", + "buntmarder", + "schneeammer", + "florida_waldkaninchen", + "hausesel", + "chicken", + "scheinerdbeere", + "stachelschweine", + "steppenhuhn", + "spitzmaulnashorn", + "goldzeisig", + "zitrusschmierlaus", + "wildziege", + "l\u00f6wenwelpin", + "weisskehlammer", + "dornhai", + "kleiner_gelbschenkel", + "zeisige", + "posttaube", + "schmarotzerraubm\u00f6we", + "nachteule", + "capreolus_capreolus", + "wandermuschel", + "schreikranich", + "perserkatze", + "halsbandpekari", + "maurische_landschildkr\u00f6te", + "spatz", + "grisli", + "herpes_zoster", + "hornisse", + "yorkshireterrier", + "graubruststrandl\u00e4ufer", + "goldfasan", + "erlenzeisig", + "arthropoda", + "schildlaus", + "hausmeerschweinchen", + "ziegelbarsch", + "schwarzstorch", + "schleiereule", + "sternrochen", + "heidehuhn", + "weisswangengans", + "gelbbrustwalds\u00e4nger", + "weissfl\u00fcgeltrappe", + "alse", + "h\u00fchnergans", + "steinw\u00e4lzer", + "polarhase", + "passgeber", + "varizella_zoster_virus", + "landasseln", + "luchs", + "holzbiene", + "trauerente", + "br\u00fcllaffen", + "jakobskrautb\u00e4r", + "kanadagans", + "tahitiperle", + "hammerhaie", + "reitpferd", + "grindwal", + "kath", + "sturmschwalben", + "hornissen", + "distelfink", + "birkhahn", + "salinenkrebs", + "nacktmaus", + "eisente", + "paarhufer", + "brillenpinguin", + "eichkater", + "fischotter", + "rieseng\u00fcrteltier", + "teichhuhn", + "hausratte", + "g\u00fcrtelmull", + "bartrobbe", + "davidshirsch", + "teichralle", + "wasserratte", + "pirol", + "tauchenten", + "lederschildkr\u00f6te", + "kermodeb\u00e4r", + "alligatorsalamander", + "rautenpython", + "schildpatt", + "zaunk\u00f6nig", + "goldschultersittich", + "sternmull", + "alle_alle", + "riesenstorch", + "cro_magnon_mensch", + "moorhuhn", + "winkerkrabbe", + "flinkwallaby", + "kapuzenwalds\u00e4nger", + "landassel", + "seidenspinner", + "merle", + "blindenhund", + "ringelnatter", + "eselchen", + "fukusa", + "pinselstachler", + "bluth\u00e4nfling", + "veilchenente", + "galapagosscharbe", + "abendkernbeisser", + "schwertwal", + "kettenhecht", + "versicolorente", + "gouldamadine", + "wachh\u00fcndin", + "anthocharis_cardamines", + "bastardmakrele", + "triele", + "brotk\u00e4fer", + "bundi", + "entenmuscheln", + "schneeziege", + "polizeihund", + "husarenaffe", + "gelbfieberm\u00fccke", + "k\u00f6nigsseeschwalbe", + "meerschwein", + "frauenheld", + "schwarzbauchschuppentier", + "meersalat", + "sumpfkaninchen", + "eichhase", + "rosal\u00f6ffler", + "hinterbein", + "michelia_compressa", + "schwarzwild", + "burunduk", + "braunbrustigel", + "herbstgrasmilbe", + "altweltotter", + "panzernashorn", + "berggorilla", + "kolkrabe", + "s\u00fcdlicher_schweinsaffe", + "hauskatze", + "dompfaff", + "m\u00fcllerchen", + "dunkelente", + "riesenkalmar", + "pantherschildkr\u00f6te", + "whippet", + "rankenf\u00fcsser", + "schweren\u00f6ter", + "rubinkehlkolibri", + "lasttier", + "schwirrammer", + "bombardierk\u00e4fer", + "eichhorn", + "kanadakleiber", + "wassermokassinotter", + "bergzebra", + "meerkatzenverwandte", + "wachhund", + "katzendrossel", + "hauszaunk\u00f6nig", + "barramundi", + "sandlaufk\u00e4fer", + "die_katze", + "yorkshire_terrier", + "lemming", + "indianermeise", + "langschwanzwiesel", + "dickschnabellumme", + "sandklaffmuschel", + "wellenl\u00e4ufer", + "finnwal", + "eagle", + "gabunviper", + "ringdrossel", + "streifenkauz", + "leistenkrokodil", + "milchschlange", + "apfelblutlaus", + "elsterdohle", + "birkhuhn", + "schabe", + "k\u00f6nigstigerin", + "waldohreule", + "einsiedlerkrebse", + "lemmini", + "schweifhuhn", + "kopflaus", + "mauersegler", + "waldspitzmaus", + "saumtier", + "schwanengans", + "weissfussmaus", + "baumwollkapselk\u00e4fer", + "weidenmeise", + "trauertaube", + "edelkoralle", + "g\u00e4nsegeier", + "frosch", + "anemonenw\u00e4chter", + "meerneunauge", + "grosspudel", + "gorilla_gorilla", + "kleiner_kohlweissling", + "diamantschildkr\u00f6te", + "ammenhai", + "amerikanerkr\u00e4he", + "kondor", + "neuweltaffen", + "rabengeier", + "spitzschwanzsittich", + "wanderdrossel", + "seegurken", + "nachtmensch", + "gelbhaubenkakadu", + "massai_giraffe", + "antilopenziesel", + "heringsmar\u00e4ne", + "martes_zibellina", + "trauerschwan", + "pirole", + "pilotfisch", + "riesenfaultier", + "sumpfspitzmaus", + "kieferntangare", + "fritte", + "birkwild", + "m\u00e4usebussard", + "goldamsel", + "zierschildkr\u00f6te", + "kanalratte", + "kappengeier", + "hornlund", + "eider", + "damagazelle", + "hausk\u00e4tzin", + "bengalkatze", + "brauen_walds\u00e4nger", + "l\u00f6wenbaby", + "aztekenm\u00f6we", + "schleiereulen", + "totenkopfaffen", + "steinmarder", + "br\u00fcllaffe", + "grosskopfmeer\u00e4sche", + "rosenk\u00e4fer", + "thorsh\u00fchnchen", + "k\u00f6hlerschildkr\u00f6te", + "elfenbeinm\u00f6we", + "singammer", + "weidenammer", + "eichkatze" + ], + "DISEASE": [ + "ritzen", + "hurt", + "hydrocephalus", + "sars", + "gebrechlichkeit", + "ansengen", + "herzrasen", + "pertussis", + "eiterflechte", + "arthritis", + "sch\u00fctzengrabenfieber", + "reibungsw\u00e4rme", + "zuckerkrank", + "risswunde", + "acanthosis_nigricans", + "muskeldystrophie", + "abrasion", + "sonnenstich", + "einst\u00fcrzen", + "akinese", + "cellulitis", + "niesen", + "fremdenhass", + "blastom", + "paratyphus", + "erregung", + "maroni", + "lippenherpes", + "zahnschmerzen", + "streptokokken_mandelentz\u00fcndung", + "ki", + "polio", + "leere", + "hundebiss", + "voreilig", + "stasis", + "cecidie", + "rinderpest", + "messern", + "kachexie", + "wundbrand", + "rosette", + "miselsucht", + "karpaltunnelsyndrom", + "tachykardie", + "graphospasmus", + "mastadenitis", + "missbildung", + "rage", + "harnblasenentz\u00fcndung", + "abrasio", + "anthrax", + "nesselsucht", + "granulom", + "blauzungenkrankheit", + "buckelige", + "chill", + "paraplegie", + "magenschmerzen", + "sichelzellenan\u00e4mie", + "krankheit", + "galaktos\u00e4mie", + "als", + "magenverstimmung", + "herzschw\u00e4che", + "arrhythmie", + "wallung", + "rabies", + "vitaminmangel", + "addieren", + "mastitis", + "plietsch", + "arthropathie", + "papageienkrankheit", + "nebelfleck", + "schwiele", + "gef\u00e4ssentz\u00fcndung", + "leibschmerzen", + "lassafieber", + "gelenkentz\u00fcndung", + "froschgeschwulst", + "anbeissen", + "gumma", + "betriebsst\u00f6rung", + "ballenzehe", + "schiefhals", + "wasserpocken", + "hernie", + "papillom", + "wen", + "hydrophobie", + "abdominaltyphus", + "parit\u00e4t", + "m\u00e4nnerscheu", + "wunde", + "zacken", + "wuchs", + "pachydermie", + "salmonelle", + "scheintod", + "fettleber", + "katarr", + "kephalh\u00e4matom", + "ausschlag", + "kretinismus", + "inversion", + "progeria", + "kriegstrauma", + "katzenkratzkrankheit", + "gr\u00fcnder", + "leberzirrhose", + "schlangenbiss", + "mange", + "poison_ivy", + "lagophthalmus", + "weiberscheu", + "dasselbeule", + "gallenblasenentz\u00fcndung", + "schmarre", + "hordeolum", + "devianz", + "sore", + "singultus", + "schlummern", + "furunkel", + "schmerzen", + "aktinomykose", + "mononucleosis_infectiosa", + "eisenmangelan\u00e4mie", + "canophobie", + "mouse", + "sternutation", + "farbenfehlsichtigkeit", + "kratzer", + "porrigo", + "r\u00f6teln", + "rinderwahn", + "croup", + "reizdarmsyndrom", + "anger", + "geschw\u00fcr", + "radiation", + "clavus", + "vitalit\u00e4t", + "herzklopfen", + "lump", + "verrosten", + "zwerchfellbruch", + "handikap", + "blattern", + "brucellose", + "kartoffelmehltau", + "striktur", + "sch\u00e4cher", + "indigestion", + "schizothymie", + "pharyngitis", + "leidenschaft", + "flechte", + "verstauchen", + "skotom", + "betrunkenheit", + "beschwerde", + "beriberi", + "brustfellentz\u00fcndung", + "fettsucht", + "lambdazismus", + "gall", + "mania", + "masern", + "dementia", + "spinalan\u00e4sthesie", + "bienenstich", + "farbenblindheit", + "gangr\u00e4n", + "der_clou", + "the_bends", + "xeroderma", + "lithiasis", + "wattekugel", + "abrachie", + "feuerbrand", + "seminom", + "struma", + "phytophthora_infestans", + "heizen", + "shape", + "schlummer", + "sonnenbrand", + "tennisellenbogen", + "k_ein_bisschen_schwanger", + "starterklappe", + "welt", + "lichtscheu", + "bleivergiftung", + "ms", + "elektroschock", + "bunt", + "h\u00f6henkrankheit", + "graviditas", + "benommenheitsgef\u00fchl", + "appendizitis", + "muskelzerrung", + "frusterlebnis", + "epstein_barr_virus", + "the_suffering", + "zerfall", + "intertrigo", + "schielen", + "schwerkrimineller", + "rust", + "slice", + "zuckerkrankheit", + "herzinfarkt", + "hodenkrebs", + "akinesie", + "hohlkreuz", + "tabakmosaikvirus", + "dekompressionskrankheit", + "platzwunde", + "quetschung", + "demenz", + "legasthenie", + "fallsucht", + "weichheit", + "nebennierenrindeninsuffizienz", + "unterzuckerung", + "fruchtbarkeit", + "sedierung", + "eingeweidebruch", + "amelie", + "trouble", + "nasenscheidewandverkr\u00fcmmung", + "fasson", + "presbyopie", + "mondauge", + "caissonkrankheit", + "todeskampf", + "bandscheibenvorfall", + "androphobie", + "lethargie", + "vergiftung", + "bucklig", + "schneeblindheit", + "kondition", + "chlorose", + "pein", + "skabies", + "winterschlaf", + "paradoxer_schlaf", + "durstigkeit", + "para", + "kastanien", + "ventrikelseptumdefekt", + "der_ekel", + "chorea", + "wasserangst", + "hunger", + "handicap", + "toben", + "luch", + "touchieren", + "magers\u00fcchtig", + "schwerh\u00f6rigkeit", + "hamartom", + "bewegungskrankheit", + "orchitis", + "appendicitis", + "zipperlein", + "schlafsucht", + "nervenleiden", + "dekubitus", + "gerben", + "krampf", + "magengeschw\u00fcr", + "strangulation", + "vasculitis", + "kinderl\u00e4hmung", + "ganzheitlichkeit", + "sodoku", + "wale", + "halbschlaf", + "lumbago", + "niederwerfung", + "taphephobie", + "schamr\u00f6te", + "gravida", + "eiterbeule", + "pferdekuss", + "rachenentz\u00fcndung", + "schiefzehe", + "miliaria", + "polyarteriitis_nodosa", + "tracheitis", + "verw\u00f6lbung", + "umnachtung", + "potenz", + "rechenschw\u00e4che", + "banausentum", + "spurrille", + "stromunfall", + "stromschlag", + "knochenkrebs", + "mammakarzinom", + "torpor", + "salmonellose", + "zellulitis", + "brandwunde", + "gestaltungskraft", + "blasenentz\u00fcndung", + "verstauchung", + "buckeliger", + "venenentz\u00fcndung", + "gelenkschmerz", + "schramme", + "mittelohrentz\u00fcndung", + "druckgeschw\u00fcr", + "schnittwunde", + "abasie", + "rektozele", + "zahnfleischentz\u00fcndung", + "tamponade", + "kindstod", + "salmonellen", + "bengalo", + "schweissfrieseln", + "prodrom", + "staupe", + "wundsein", + "ache", + "plattenepithelkarzinom", + "wachstumsschmerzen", + "aurajoki", + "eileiterschwangerschaft", + "chi", + "verdauungsst\u00f6rung", + "banausie", + "computermaus", + "ganzheit", + "herzanfall", + "rachitis", + "delirium", + "fremdenfeindlichkeit", + "stauungspapille", + "panikst\u00f6rung", + "spermatozele", + "balanitis", + "erregtheit", + "am_rad_drehen", + "lichen", + "arterielle_hypotonie", + "rosazea", + "vigil", + "berufskrankheit", + "transposition", + "qi", + "mehln\u00e4hrschaden", + "progerie", + "schw\u00e4chung", + "herpes_simplex", + "schwindelgef\u00fchl", + "geschlechtstrieb", + "peitschenriemen", + "h\u00fchnerauge", + "verbiegung", + "nebeneffekt", + "pflanzengalle", + "verbr\u00fchen", + "erdeessen", + "golfkriegssyndrom", + "schaufensterkrankheit", + "zahnweh", + "mongolismus", + "luftart", + "hautkrankheit", + "strahlung", + "korpulenz", + "raserei", + "laufwerk", + "antoniusfeuer", + "zungenbrennen", + "o_bein", + "malaise", + "verwundung", + "tennisarm", + "strabismus", + "nachtblindheit", + "schwulit\u00e4t", + "spina_bifida", + "rinderwahnsinn", + "passion", + "analgesie", + "falls\u00fcchtig", + "lordose", + "traberkrankheit", + "magenweh", + "fortpflanzungsf\u00e4higkeit", + "zerkariendermatitis", + "verrenken", + "listeriose", + "kolitis", + "hausschwamm", + "wachheit", + "spinal", + "gimp", + "windpocken", + "hydrozephalus", + "stenose", + "brechdurchfall", + "mitralklappenprolaps", + "brennend", + "frenzy", + "downsyndrom", + "hernia", + "alexia", + "brennen", + "die_passion_christi", + "gestation", + "herpes", + "frostbeule", + "harnwegsinfekt", + "menstruationsbeschwerden", + "prellung", + "herzversagen", + "xerodermie", + "h\u00fchnerbrust", + "nervenzusammenbruch", + "philisterei", + "schwindelanfall", + "adipostas", + "twist", + "sigmatismus", + "yellow_jack", + "katalepsie", + "kaputtgehen", + "smart", + "amelia", + "diphtherie", + "hydrops", + "rauchabzug", + "thanatophobie", + "beulenpest", + "marasmus", + "gummose", + "kopfschuppen", + "die_stadt_der_blinden", + "kropf", + "brunst", + "stase", + "ed", + "bewegungsst\u00f6rung", + "breakdown", + "beke", + "muskelkrampf", + "knochenbruch", + "basalganglien", + "blister", + "gravidit\u00e4t", + "schlagmann", + "pica", + "kieferklemme", + "distension", + "weitsichtigkeit", + "schamesr\u00f6te", + "strahlenkrankheit", + "phenylketonurie", + "aquaphobie", + "aufgeregtheit", + "vorhofflimmern", + "abdominalhernie", + "geburtsfehler", + "querschnittsl\u00e4hmung", + "brachydaktylie", + "kallus", + "hermaphrodismus", + "magersucht", + "choke", + "tuse", + "talipes", + "heisshunger", + "husten", + "sensation", + "sch\u00e4dling", + "gr\u00fcnderin", + "milzbrand", + "herzrhythmusst\u00f6rung", + "aspirationspneumonie", + "unfruchtbarkeit", + "kopfschmerz", + "zytomegalievirus", + "schleimbeutelentz\u00fcndung", + "fliegerkrankheit", + "leerheit", + "flugkrankheit", + "kohlenstoffmonoxidintoxikation", + "schluchzer", + "tabes", + "alterssichtigkeit", + "quecksilbervergiftung", + "poliovirus", + "photophobia", + "frische", + "pers\u00f6nlichkeitsst\u00f6rung", + "neubildung", + "hasenscharte", + "verdauungsbeschwerde", + "epidermolysis_bullosa", + "fugue", + "pain", + "bissen", + "bissverletzung", + "chondrom", + "m\u00fcckenstich", + "aussatz", + "monierung", + "teratom", + "narbe", + "arbovirus", + "brotscheibe", + "leichenstarre", + "kreislaufstillstand", + "kontaktdermatitis", + "satthals", + "strain", + "riesenwuchs", + "milchschorf", + "dilatation", + "hydrozele", + "purpura", + "heuschnupfen", + "netzhautabl\u00f6sung", + "schizoid", + "herzstillstand", + "sichelzelle", + "chillen", + "alarmierung", + "ansteckung", + "herpes_simplex_viren", + "singe", + "arthralgie", + "gelbfieber", + "sonnenbr\u00e4une", + "luftkrankheit", + "kusskrankheit", + "schr\u00e4gstrich", + "robbengliedrigkeit", + "ill", + "totenstarre", + "chalazion", + "h\u00f6henangst", + "nabelbruch", + "fehlerwirkung", + "hydronephrose", + "dunstabzug", + "an_qi", + "fretten", + "hinkend", + "grassieren", + "panaritium", + "ulmensterben", + "pull", + "magendr\u00fccken", + "stigmata", + "kriegszitterer", + "strieme", + "tierr\u00e4ude", + "spiessb\u00fcrgertum", + "autoimmunreaktion", + "trachom", + "kammerflimmern", + "otorrh\u00f6e", + "r\u00fcckfallfieber", + "denguefieber", + "av_block", + "pollinosis", + "sch\u00fcrfwunde", + "querschnittl\u00e4hmung", + "smut", + "hautausschlag", + "wasserkopf", + "pellagra", + "bisswunde", + "strabismus_convergens", + "bilirubinenzephalopathie", + "lernbehinderung", + "schistosomiasis", + "quaddel", + "leberentz\u00fcndung", + "unterern\u00e4hrung", + "nahrungsmittelvergiftung", + "rausch", + "mi", + "disintegration", + "oberschenkelhalsbruch", + "skorbut", + "komplikation", + "spondylitis_ankylosans", + "mangelern\u00e4hrung", + "herzbeuteltamponade", + "aura", + "unregelm\u00e4ssigkeit", + "tan", + "arousal", + "west_nil_virus", + "kollabieren", + "sting", + "blasenmole", + "mandelentz\u00fcndung", + "wart", + "schuppenflechte", + "emmetropie", + "bradykardie", + "gelbsucht", + "vernarben", + "brandblase", + "schockieren", + "aniseikonie", + "the_bleeding", + "gicht", + "schm\u00e4lerung", + "achylia_gastrica", + "beissen", + "reigentanz", + "recken", + "watteb\u00e4llchen", + "lokalan\u00e4sthesie", + "break", + "kurzsichtigkeit", + "indisposition", + "taubheit", + "cyanidvergiftung", + "immersionsfuss", + "poliomyelitis", + "materialismus", + "palilalie", + "gebilde", + "lebensmittelvergiftung", + "flexur", + "trauma", + "kernikterus", + "fleckfieber", + "blockierung", + "kopfschmerzen", + "streptokokken_tonsillitis", + "afrikanische_trypanosomiasis", + "herzfehler", + "hautkrebs", + "nasenbluten", + "kuru", + "burn", + "wundstarrkrampf", + "zahnschmerz", + "wassersucht", + "erregtsein", + "flexion", + "darmerkrankung", + "raumangst", + "lufthunger", + "knutschfleck", + "zwicken", + "schreibkrampf", + "noma", + "the_hives", + "rosten", + "mutterkornpilz", + "schlafst\u00f6rung", + "die_pest", + "chorea_huntington", + "krampfader", + "mouches_volantes", + "leaken", + "schlafkrankheit", + "demineralisation", + "ahornsirupkrankheit", + "flare", + "verkr\u00fcmmung", + "fehlbildung", + "mundf\u00e4ule", + "schwerverbrecher", + "scharbock", + "weitsichtig", + "le", + "harm", + "panzytopenie", + "klaustrophobie", + "cutten", + "weiterung", + "albuminurie", + "trunkenheit", + "schwindsucht", + "spinnenangst", + "schwarzwasser", + "brandseuche", + "sch\u00f6pfungskraft", + "fettleibigkeit", + "schreibschw\u00e4che", + "brustkrebs", + "leberkrebs", + "katarrh", + "autoimmunerkrankung", + "schwangerschaft", + "platzangst", + "kopfweh", + "malaria", + "br\u00e4une", + "thalass\u00e4mie", + "follikulitis", + "mastoiditis", + "eichelentz\u00fcndung", + "karfunkel", + "durchfall", + "subluxation", + "akarophobie" + ], + "BIO_CHEM_ENTITY": [ + "teebaum\u00f6l", + "adenosindiphosphat", + "polyvinylchlorid", + "salicyls\u00e4ure", + "mononatriumglutamat", + "cysteinproteasen", + "aldehydoxidase", + "caesiumiodid", + "laurins\u00e4ure", + "calciumsilicat", + "citronens\u00e4ure", + "tellurs\u00e4ure", + "weizenkeim", + "kaliumiodid", + "mineral\u00f6l", + "fetts\u00e4ure", + "n_methylaminoethanol", + "orthosalpeters\u00e4ure", + "prolylendopeptidase", + "palustrins\u00e4ure", + "wolframs\u00e4ure", + "tranexams\u00e4ure", + "siliciumdioxid", + "bariumtitanat", + "siliciumnitrid", + "xanthinoxidase", + "c_reaktives_protein", + "prostacyclinsynthase", + "magnesiumperoxid", + "nervenwachstumsfaktor", + "guanosindiphosphat", + "calciumcitrat", + "coniferylalkohol", + "zopfig", + "heliumhydrid", + "kaliumaluminiumsulfat", + "diethylether", + "essigs\u00e4urechlorid", + "karmins\u00e4ure", + "butters\u00e4ure", + "magnesiumchlorid", + "monoaminooxidase", + "peroxodiphosphors\u00e4ure", + "zinkchlorid", + "butans\u00e4ure", + "fetts\u00e4uren", + "molybd\u00e4ns\u00e4ure", + "traubenkern\u00f6l", + "verzopft", + "kaliumantimonyltartrat", + "strontiumchlorid", + "magnesiumcitrat", + "polylactide" + ], + "ORG": [ + "mineral\u00f6lindustrie", + "noch_einmal", + "solarplexus", + "dominion", + "ida", + "liegest\u00fctz", + "shinto", + "das_gelbe_vom_ei", + "milit\u00e4rregierung", + "\u00f6lgesellschaft", + "internationale_organisation", + "die_klappe_halten", + "wieder_einmal", + "eu_ministerrat", + "zentralschl\u00fcssel", + "andersrum", + "sicherheitskr\u00e4fte", + "volksschule", + "mitsui_zaibatsu", + "martinskirche", + "bernhardiner", + "wahlkollegium", + "austrinken", + "golfschl\u00e4ger", + "sabaoth", + "berufungsgericht", + "kleinweis", + "mineral\u00f6lgesellschaft", + "goldenes_zeitalter", + "welthandelsorganisation", + "friesische_reiter", + "oberhaus", + "san_jos\u00e9", + "reiseagentur", + "military", + "vorstandssitzung", + "radiogalaxie", + "forschungseinrichtung", + "privatschule", + "massenmedien", + "tom_thumb", + "gartenparty", + "gelehrtengesellschaft", + "wicca", + "sprachschule", + "internationale_fernmeldeunion", + "showgesch\u00e4ft", + "die_alliierten", + "m\u00e4nnerstudium", + "an_education", + "apfelgeh\u00e4use", + "weltmacht", + "gemeines_perlboot", + "jan_mayen", + "weltbev\u00f6lkerung", + "as_dur", + "staatsdienst", + "annenkirche", + "ins", + "um_eine_nasenl\u00e4nge_voraus_sein", + "kunstgalerie", + "marineinfanterie", + "nordwestpassage", + "orthodoxes_judentum", + "zentralbank", + "selbstgerecht", + "zu_zweit", + "aa", + "das_findelkind", + "sparkasse", + "nasa", + "abendschule", + "plattenindustrie", + "kassationshof", + "arda", + "hinayana", + "in_vivo", + "the_national_archives", + "bundesbeh\u00f6rde", + "postamt", + "huang_he", + "bollywood", + "ein_richter_sieht_rot", + "wahlm\u00e4nnerkollegium", + "ang", + "geburtenwelle", + "junggesellinnenabschied", + "schminken", + "grundschule", + "rauchschwalbe", + "europol", + "schutzstaffel", + "podiumsdiskussion", + "hindin", + "bakkie", + "na_los", + "auslandsvertretung", + "milit\u00e4rakademie", + "sankt_andreasberg", + "christkindl", + "volksfront", + "the_who", + "verr\u00fccktenanstalt", + "ene_mene_miste", + "kernfamilie", + "non_plus_ultra", + "dominium", + "the_planetary_society", + "befreiungsarmee", + "mein_name_ist", + "bundesregierung", + "andromeda_galaxie", + "peergroup", + "marktwirtschaft", + "college", + "krankenpflegeschule", + "kautschukindustrie", + "mauerwerk", + "nur_zu", + "san_francisco", + "ich_heisse", + "kristdemokraterna", + "lucianerin", + "vivat", + "un", + "social_democratic_party", + "a_chorus_line", + "tennisklub", + "repr\u00e4sentantenhaus", + "zentraleuropa", + "tierrechte", + "mittelschule", + "gerichtshof", + "electoral_college", + "nordatlantikrat", + "kammerorchester", + "botanischer_garten", + "peterskirche", + "volkspartei", + "wertpapierb\u00f6rse", + "flashmob", + "einheitsmatrix", + "v\u0129nh_long", + "armee", + "und_anderes", + "nara", + "und_umgedreht", + "rollkommando", + "va", + "drk", + "tanzkapelle", + "menschengemacht", + "milit\u00e4rpolizei", + "col_legno", + "m\u00e4nnerforschung", + "fruchtsalat", + "staatsversammlung", + "die_\u00fcblichen_verd\u00e4chtigen", + "polterabend", + "nebeneinander", + "yachtklub", + "dann_und_wann", + "geldmarkt", + "hochofen", + "st_nikolaus", + "postfiliale", + "verlagsgesellschaft", + "pensionsfonds", + "sprachgemeinschaft", + "gao", + "die_roten", + "kapetinger", + "mittelm\u00e4chte", + "prohibition_party", + "bullenmarkt", + "zivilgesellschaft", + "neumond", + "der_freie_wille", + "mahayana", + "oberstes_gericht", + "core", + "geschlechterforschung", + "bis_s_zur_mittagsstunde", + "m\u00e4nnerstudien", + "kleinpolen", + "frente_popular", + "nordzypern", + "reichsparteitag", + "baugenehmigung", + "sammelklage", + "wahlm\u00e4nnergremium", + "marienkirche", + "lucianisch", + "han_dynastie", + "chilisauce", + "stockung", + "versicherungsgesellschaft", + "john_tuzo_wilson", + "highschool", + "the_faculty", + "don_juan", + "jungt\u00fcrken", + "fibonaccifolge", + "kriegsdienst", + "abbiegen", + "\u00f6lberg", + "the_new_school", + "ai", + "heilsarmee", + "nachholen", + "st_barbara", + "junggesellenabschied", + "gr\u00fcnlicht", + "marineinfanteriekorps", + "wechselstube", + "mischehe", + "ohne_schnickschnack", + "abtransport", + "im_jahr_des_herrn", + "sankt_helena", + "weissgold", + "the_football_league", + "chiang_mai", + "jesuiten", + "landgericht", + "friedenscorps", + "katzenauge", + "et_al", + "jakobskirche", + "humanverm\u00f6gen", + "nach_belieben", + "dia", + "der_fr\u00fchst\u00fccksclub", + "seestreitkr\u00e4fte", + "qu\u00e4kertum", + "blasmusik", + "polizeistaat", + "was_is_passiert", + "st_kilda", + "zentralverwaltungswirtschaft", + "abgeordnetenhaus", + "der_schwarze_kater", + "kreditgenossenschaft", + "uropa", + "sturmtruppen", + "handelsbank", + "gatt", + "halbleiterindustrie", + "schattenkabinett", + "oberster_gerichtshof", + "sozialdemokratische_partei", + "in_flagranti", + "kulturministerium", + "auktionshaus", + "ab_initio", + "die_seew\u00f6lfe_kommen", + "graduiertenschule", + "eigentumsrecht", + "drogenkartell", + "landstreitkr\u00e4fte", + "verfassungsgericht", + "le_mans", + "pazifikflotte", + "andersherum", + "kleinb\u00fcrgertum", + "blumensprache", + "christian_science", + "weltgesundheitsorganisation", + "piratenpartei", + "jeder_ist_sich_selbst_der_n\u00e4chste", + "die_grossen_vier", + "daheim", + "caf\u00e9_au_lait", + "shia", + "kontinentalarmee", + "fussballverein", + "filmindustrie", + "johanneskirche", + "un_sekretariat", + "genderforschung", + "narodno_sabranie", + "partit_socialdem\u00f2crata", + "bundesrepublik", + "bandschlingenknoten", + "mari\u00e4_aufnahme_in_den_himmel", + "musikindustrie", + "obstsalat", + "effektenb\u00f6rse", + "relativit\u00e4t_der_rechtsbegriffe", + "gestapo", + "betriebsrat", + "haupschl\u00fcssel", + "streitkraft", + "thinktank", + "parochialkirche", + "generalst\u00e4nde", + "schintoismus", + "ursa_maior", + "philadelphia_convention", + "stadtverwaltung", + "bundespolizei", + "de_luxe", + "vereinigungskirche", + "deutsche_sprache", + "gesamtschule", + "kriegerdenkmal", + "sicherheitsbeh\u00f6rde", + "maloche", + "nachgeraten", + "schl\u00e4ferzelle", + "staatskapitalismus", + "nichts_als", + "stadtkern", + "den_mund_aufmachen", + "sonntagsschule", + "demokratska_stranka", + "stadtzentrum", + "genderstudien", + "personalabteilung", + "milit\u00e4rdienst", + "li_fi", + "sicherheitskraft", + "suppenk\u00fcche", + "reiseb\u00fcro", + "mittelklasse", + "chassidim", + "maquis", + "geschlechterstudien", + "erhaltungssatz", + "modernst", + "the_young_turks", + "rassentrennung", + "erworbenes_recht", + "le_monde", + "stadtstaat", + "mineral\u00f6lunternehmen", + "who_are_you", + "strafgesetzbuch", + "verbrannte_erde", + "blaskapelle", + "babyboom", + "partido_del_trabajo", + "werbeagentur", + "b\u00fcrgerrecht", + "medizinische_versorgung", + "chiang_rai", + "bundesbahn", + "kerngeh\u00e4use", + "herrenrasse", + "stronnictwo_narodowe", + "al_jazeera", + "homoehe", + "das_maul_halten", + "pfarrkirche", + "cum_laude", + "zuckerfrei", + "assembl\u00e9e_nationale", + "s\u00e3o_paulo", + "kohleindustrie", + "machtgebiet", + "paulskirche", + "staatskasse", + "europe", + "verlagshaus", + "evangelische_kirche", + "po", + "rotes_meer", + "was_ist_los", + "dschainismus", + "sternhaufen", + "amerikanistik", + "griebs", + "und_umgekehrt", + "verwaltungsrat", + "hausverstand", + "forschungszentrum", + "der_heilige_nikolaus", + "auf_zeit", + "mossad", + "ferdinand_magellan", + "schwulenehe", + "flugverkehr", + "ene_mene_mu", + "streichquartett", + "vishnuismus", + "vittore_carpaccio", + "baskenland", + "zu_hause", + "konservative_partei", + "ayuntamiento", + "amnesty_international", + "gemeindeamt", + "v\u00f6lkerbund", + "hedgefonds", + "up_to_date", + "freimaurerei", + "hollywood", + "strafverfolgungsbeh\u00f6rde", + "unterhaus", + "ursa_major", + "gottesmutter", + "das_schweigen_der_l\u00e4mmer", + "berufsschule", + "gukhoe", + "politische_klasse", + "saint_barth\u00e9lemy", + "agrarpartei", + "markuskirche", + "kunststoffbranche", + "sturmabteilung", + "herzenslust", + "spangenschuh", + "kontinentalkongress", + "appellationsgericht", + "georgskirche", + "studierendenvertretung", + "who", + "suchmannschaft", + "los_angeles", + "nato", + "genderstudies", + "hohe_pforte", + "andromedagalaxie", + "al_dschasira", + "baltimore_orioles", + "neuwertig", + "anno_domini", + "fussballclub", + "anti_antifa", + "daseinsvorsorge", + "akademie", + "ad_hoc", + "historischer_stadtkern", + "bartholom\u00e4uskirche", + "kriegsmaschine", + "komposthaufen", + "\u00f6lunternehmen", + "stephanskirche", + "kitsche", + "verwaltungseinheit", + "mi", + "briefkastengesellschaft", + "ich_habe_dich_lieb", + "kunstmuseum", + "by_the_way", + "bataillon", + "die_kom\u00f6die_der_irrungen", + "erziehung", + "von_zeit_zu_zeit", + "irrenanstalt", + "altstadt", + "alla_polacca", + "schola", + "gemeinsinn", + "in_situ", + "stahlindustrie", + "die_heilige_barbara", + "wohlfahrtsstaat", + "golfklub", + "mitteleuropa", + "sa", + "dornr\u00f6schen", + "klausenburg", + "milit\u00e4risch", + "albertsee", + "willensfreiheit", + "mittelstufe", + "es_war_einmal", + "es_lebe", + "briefkastenfirma", + "nachrichtenagentur", + "schuldf\u00e4hig", + "herrschaftsgebiet", + "altersgruppe", + "bubble_gum", + "wechselstelle", + "bundesamt", + "islamwissenschaft", + "handelskammer", + "taoismus", + "schwarzmarkt", + "ein_geschenk_der_kultur", + "al_ain", + "spezialkr\u00e4fte", + "neusatz", + "zeugen_jehovas", + "entwicklungsland", + "ersessenes_recht", + "sanit\u00e4tsbataillon", + "volksarmee", + "wirtschaftssystem", + "barbara_von_nikomedien", + "hagana", + "ace", + "commerce", + "united_states_whig_party", + "stadtrat", + "vor_ort", + "normalschule", + "sonnengeflecht", + "philharmoniker", + "streptococcus_pyogenes", + "sprachfamilie", + "marionettenregierung", + "heilige_familie", + "eu", + "lucianer", + "dritten", + "bei_der_tat", + "den_schnabel_halten", + "chang_jiang", + "nationalversammlung_der_republik_aserbaidschan", + "briefmarkensammlung", + "freikirche", + "behindertensport", + "morgenstern", + "oberschule", + "zenbuddhismus", + "dreht\u00fcr", + "schwarze_witwe", + "hirundo_rustica", + "nikolaikirche", + "eigennutz", + "mecklenburg_vorpommern", + "mandelbrotmenge", + "katholische_kirche", + "in_vitro", + "ein_supertrio", + "erdbev\u00f6lkerung", + "house_of_lords", + "st_lucia", + "oberschicht", + "planwirtschaft", + "hochfrequenz", + "guomindang", + "silvesterabend", + "natriumsilicate", + "democratic_socialist_party", + "ich_liebe_dich", + "grenzmarke", + "staatspolizei", + "nachrichtendienst", + "s\u00e3o_tom\u00e9", + "fachhochschule", + "bundesbank", + "und_andere", + "oberer_see", + "genossenschaftsbank", + "splittergruppe", + "shint\u014d", + "kirschenmund", + "mater_dolorosa", + "heimatfront" + ], + "LOCATION": [ + "al_jazeera", + "bodendenkmal", + "granville_town", + "schnellbahn", + "alt_ruppin", + "schwarzspecht", + "ich_danke_sch\u00f6n", + "zentralbank", + "irrenanstalt", + "alt_treptow", + "marktkreuz", + "the_good_night", + "pensionsfonds", + "dornr\u00f6schen", + "im_falle", + "der_verschollene", + "spielwiese", + "so_what", + "ringstrasse", + "vermittlungsstelle", + "auf_der_strasse", + "rapanui", + "am_h\u00f6chsten", + "pflegeheim", + "s\u00fcsswasser", + "sportunterricht", + "salzsee", + "reichsstadt", + "eduardsee", + "westaustralien", + "columbus_day", + "stichstrasse", + "dankesch\u00f6n", + "graureiher", + "d\u00e4umling", + "falklandinseln", + "der_kirschgarten", + "park", + "non_plus_ultra", + "f\u00fcr_alle_f\u00e4lle", + "st_nikolai", + "corpus_christi", + "innenstadt", + "ungarisches_parlament", + "kap_verde", + "bow_wow", + "friedensrichterin", + "united_states_army", + "altjahrsabend", + "kontrollraum", + "chathaminseln", + "nichts_zu_danken", + "s_tog", + "habe_vielen_dank", + "luftstreitkraft", + "weihnachtsabend", + "piet_mondrian", + "la_roche_en_ardenne", + "medizinische_hochschule", + "trifolium_repens", + "eisenbahnstrecke", + "la_manche", + "stille_post", + "santa_fe", + "heiliger_vater", + "milit\u00e4rregierung", + "sint_maarten", + "petasites_hybridus", + "am_ende", + "weihwasser", + "freihafen", + "im_hafen", + "jungfrau_maria", + "chang_jiang", + "alte_m\u00fcnze", + "milit\u00e4rakademie", + "verr\u00fccktenanstalt", + "dritten", + "arbeitersiedlung", + "f\u00fcnftausender", + "man_o_war", + "seniorenheim", + "ich_danke_sehr", + "nordinsel", + "osterinsel", + "kaiserkanal", + "vor_alter_zeit", + "trois_rivi\u00e8res", + "allahu_akbar", + "r\u00f6merstrasse", + "silvesterabend", + "regieraum", + "haben_sie_vielen_dank", + "tempelberg", + "tennisplatz", + "neumexiko", + "kanalinseln", + "land", + "huang_he", + "ein_gutes_neues_jahr", + "dreibeinig", + "iris_pseudacorus", + "michigansee", + "nervenklinik", + "leitstand", + "k\u00fcchengarten", + "blue_mountains", + "pieris_rapae", + "westk\u00fcste", + "s\u00fcdaustralien", + "sportplatz", + "k\u00f6niggr\u00e4tz", + "christnacht", + "joseph_louis_gay_lussac", + "spielfeld", + "fischreiher", + "portoriko", + "weihnachtabend", + "hans_und_franz", + "kreuzknoten", + "al_dschasira", + "wetterstation", + "marstall", + "thermalquelle", + "wba", + "welthandelszentrum", + "tom_thumb", + "das_gelbe_vom_ei", + "lake_of_the_woods", + "warenhaus", + "kap_hoorn", + "usa", + "luftstreitkr\u00e4fte", + "na_und", + "bad_kreuznach", + "saint_lucia", + "aussig", + "nationalversammlung", + "milchstrasse", + "spielplatz", + "alte_schule", + "hat_yai", + "am_anfang", + "almaaz", + "arena", + "sri_lanka", + "lake_st_clair", + "ferienwohnung", + "strassenstrich", + "vor_allem_anderen", + "fransenschildkr\u00f6te", + "jakobsstab", + "sundastrasse", + "das_schwarze_loch", + "psychiatrische_klinik", + "the_rolling_stones", + "san_joaquin_river", + "silberhaargras", + "cordon_bleu", + "krywyj_rih", + "botanischer_garten", + "rotmilan", + "neuengland", + "rosengarten", + "downtown", + "k_raum", + "court", + "am_himmel", + "heitor_villa_lobos", + "felde", + "den_ganzen_tag", + "weihnachtsmann", + "al_ain", + "neue_welt", + "friedensrichter", + "alte_welt", + "einen_zahn_zulegen", + "tanasee", + "red_water", + "heiligabend", + "mit_vergn\u00fcgen", + "ich_sage_dank", + "stundenzeiger", + "bauingenieurwesen", + "vor_langer_zeit", + "vereinigte_mulde", + "maifeiertag", + "prunus_avium" + ], + "PLANT": [ + "hibiscus_syriacus", + "weisskopfmimose", + "acanthocereus_tetragonus", + "gomphrena_globosa", + "hibiscus_mutabilis", + "brachychiton_populneus", + "entoloma_sinuatum", + "marien_glockenblume", + "margerite", + "hevea", + "kapstachelbeere", + "lespedeza_cuneata", + "trift", + "guajakbaum", + "einbeere", + "schirm_magnolie", + "scharbockskraut", + "zinnkraut", + "chinakohl", + "futterwicke", + "bratsche", + "pine", + "rote_heckenkirsche", + "pak_choi", + "sankt_maria", + "wald_vergissmeinnicht", + "gartengeissblatt", + "teerose", + "vogelkirsche", + "sperberbaum", + "ochsenzunge", + "ackerbohne", + "lilium_philadelphicum", + "strand_platterbse", + "lilium_longiflorum", + "portulakr\u00f6schen", + "halskrause", + "liriodendron_tulipifera", + "rotes_waldv\u00f6glein", + "cladonia_rangiferina", + "melissa", + "canavalia_gladiata", + "guttaperchabaum", + "kirschpflaume", + "dioscorea_bulbifera", + "hoya_carnosa", + "tricholoma_pardinum", + "paradiesk\u00f6rner", + "r\u00fcbe", + "venusfliegenfalle", + "lilium_lancifolium", + "palmyrapalme", + "zahnb\u00fcrstenbaum", + "m\u00f6hre", + "liguster", + "the_joshua_tree", + "gartenbohne", + "aleuria_aurantia", + "philadelphus_coronarius", + "roteiche", + "trichterwinde", + "aralia_elata", + "blutweiderich", + "k\u00fcnstler", + "langermannia_gigantea", + "brassica_nigra", + "meleguetapfeffer", + "helleborus_niger", + "stinkwacholder", + "mahonie", + "palmlilie", + "auricularia_auricula", + "rosa_chinensis", + "rohrglanzgras", + "schwarzkiefer", + "hirtent\u00e4schel", + "scharfz\u00e4hniger_strahlengriffel", + "cucurbita_moschata", + "wacholderbeere", + "prinzessbohne", + "solanaceae", + "bastardindigo", + "schneeheide", + "weisseiche", + "weisskraut", + "fliegenpilz", + "vanilla_planifolia", + "flatterulme", + "scheinakazie", + "jeffreys_kiefer", + "kirschbaum", + "phytoparasitismus", + "schefflera_actinophylla", + "winterlinge", + "tannia", + "saubohne", + "salix_babylonica", + "rosafarbene_catharanthe", + "waldgeissblatt", + "straucheibisch", + "gartenmelde", + "anthyllis_vulneraria", + "zirbelkiefer", + "laurus_nobilis", + "wasserminze", + "lathyrus_odoratus", + "rosenkohl", + "christusdorn", + "coriaria_japonica", + "curuba", + "sassafrasbaum", + "drachenk\u00f6pfe", + "geissblatt", + "christbaum", + "steinbeere", + "traubeneiche", + "adenium_obesum", + "helianthus_annuus", + "heckenrose", + "tausendsch\u00f6n", + "kalebassenbaum", + "schafgarben", + "monarda", + "sorbus_torminalis", + "schlafm\u00fctzchen", + "artist", + "bedecktsamer", + "wildreis", + "bergahorn", + "sternanis", + "magnolia_grandiflora", + "chrysanthemen", + "pelargonium_odoratissimum", + "batate", + "campher", + "amberbaum", + "jerusalemsdorn", + "chionanthus_virginicus", + "mullein", + "coprinus_comatus", + "gr\u00fcnliche_waldhyazinthe", + "sinapis", + "prunus_laurocerasus", + "breitbl\u00e4ttrige_platterbse", + "allium_tuberosum", + "feuerdorn", + "kassawa", + "amberb\u00e4ume", + "lilium_michiganense", + "cercidiphyllum_japonicum", + "atriplex_hortensis", + "titanenwurz", + "cortinarius_armillatus", + "acer_campestre", + "buschwindr\u00f6schen", + "bletilla_striata", + "kampferbaum", + "riesenmammutbaum", + "mimosa_pudica", + "zwetschge", + "bergamotte", + "nachtschatten", + "ackerwinde", + "pferdeeppich", + "islandmohn", + "papaver_somniferum", + "rosskastanien", + "l\u00f6ffelkraut", + "bl\u00fctenknospe", + "k\u00fcstenmammutbaum", + "matthiola_incana", + "echte_kamille", + "portiabaum", + "steineiche", + "indigopflanze", + "favabohne", + "actinidia_chinensis", + "obstbaum", + "sakura", + "butternuss", + "breitwegerich", + "herbst_adonisr\u00f6schen", + "papaver", + "dicentra_spectabilis", + "candida_albicans", + "anischampignon", + "senna_alata", + "weihnachtsbaum", + "amaryllis_belladonna", + "rittersporn", + "gelenkblume", + "m\u00e4nnerfarn", + "asperula", + "himmelsleiter", + "calophyllum_inophyllum", + "rosa_multiflora", + "brennnesseln", + "tonkabaum", + "klatschrose", + "herzkraut", + "traubenkirsche", + "lorbeerkirsche", + "weichweizen", + "ulmen", + "asclepias_purpurascens", + "kriechenpflaumenbaum", + "capsicum_baccatum", + "olivenbaum", + "vogelbeere", + "essigbaum", + "winterling", + "blumenkohl", + "dianthus_caryophyllus", + "brasenia_schreberi", + "l\u00f6wenm\u00e4ulchen", + "weg_rauke", + "kronsbeere", + "andropogon_virginicus", + "bachbunge", + "h\u00e4ngebirke", + "lampionblume", + "kalifornische_platane", + "mohrenhirse", + "osterluzei", + "buchenfarn", + "brunnenkressen", + "weg_malve", + "feigwurz", + "weissklee", + "maigl\u00f6ckchen", + "taxus_cuspidata", + "mariendistel", + "knollenbl\u00e4tterpilz", + "tilia_japonica", + "calvatia_gigantea", + "manioka", + "sonnenblumen", + "feinstrahl", + "pechnelke", + "kassava", + "alstonia_scholaris", + "stiefm\u00fctterchen", + "fliederstrauch", + "passiflora_incarnata", + "fliederbaum", + "paranuss", + "purpurweide", + "schlafmohn", + "drachenwurz", + "ardisia_crenata", + "blattknospe", + "blutholzbaum", + "kammquecke", + "hecke", + "beet", + "gartenmelisse", + "knoblauchrauke", + "geweihbaum", + "moosbeeren", + "selenicereus_grandiflorus", + "citrus_aurantium", + "sonnenblume", + "reseda", + "landnelke", + "postelein", + "kochia_scoparia", + "annona_cherimola", + "rosmarinheide", + "tannenzapfen", + "wurzelsystem", + "platanus_orientalis", + "gossypium_hirsutum", + "holm", + "sandbirke", + "prunus_armeniaca", + "wasserhyazinthe", + "schwarz\u00e4ugige_rudbeckia", + "bohnenpflanze", + "liquidambar", + "fingerhirse", + "paranussbaum", + "petasites_hybridus", + "urtica", + "iris_ensata", + "parthenocissus_tricuspidata", + "macadamia_tetraphylla", + "ligustrum_obtusifolium", + "nachtjasmin", + "kalme", + "cucurbita_argyrosperma", + "amanita_muscaria", + "winterzwiebel", + "olive", + "breiapfelbaum", + "herztrost", + "silberweide", + "kranbeere", + "vorticella_convallaria", + "mahonien", + "nicotiana_tabacum", + "asclepias_verticillata", + "phyllostachys_nigra", + "rosa_laevigata", + "arlesbaum", + "winterlinde", + "gemeiner_steinpilz", + "fr\u00fchjahrslorchel", + "schierling", + "niembaum", + "feldahorn", + "hirtent\u00e4schelkraut", + "s\u00fcsssack", + "fr\u00fchlorchel", + "monterey_zypresse", + "sorbin", + "rosskastanie", + "schwarzerle", + "stellaria_media", + "leucanthemum_vulgare", + "graukresse", + "knoblauchhederich", + "melastoma_malabathricum", + "engelstrompete", + "eberesche", + "chrysantheme", + "morgenl\u00e4ndische_platane", + "sciadopitys_verticillata", + "aronstab", + "schneeh\u00e4sin", + "cranberry", + "helianthus_tuberosus", + "hedysarum_coronarium", + "zitronenmelisse", + "sichelklee", + "zerreiche", + "tollkirsche", + "kleines_immergr\u00fcn", + "wasserkastanie", + "per\u00fcckenstrauch", + "surinamkirsche", + "sandelholz", + "prunus_domestica", + "balatabaum", + "dendrocalamus_giganteus", + "kokosnusspalme", + "gef\u00e4sspflanzen", + "schildfarn", + "portulaca_grandiflora", + "phytophthora_infestans", + "chlorophyllum_molybdites", + "k\u00f6nigsfarn", + "gartensalat", + "kratzbeere", + "setzling", + "ruprechtskraut", + "rubus_idaeus", + "netzannone", + "gossypium_barbadense", + "fraxinus_japonica", + "brassica_chinensis", + "kornrade", + "dickm\u00e4nnchen", + "schw\u00e4rzende_platterbse", + "sauerklee", + "cimicifuga_racemosa", + "salvia_pratensis", + "centaurea_cyanus", + "bocksdorn", + "stendelwurz", + "heckenkirschen", + "sporapfel", + "faulkirsche", + "agaricus_campestris", + "stern_magnolie", + "trifolium_repens", + "austernpilz", + "klette", + "blackberry", + "violette_k\u00f6nigskerze", + "schwarzpappel", + "schlehdorn", + "kleinbl\u00fctige_k\u00f6nigskerze", + "schwarzeiche", + "scheinbuche", + "eselsdistel", + "sei_vorsichtig", + "moosbeere", + "s\u00fcsskartoffel", + "echinocactus_grusonii", + "schopftintling", + "selleriekohl", + "medinilla_magnifica", + "kampfer", + "hiobstr\u00e4ne", + "brennnessel", + "dianthus_chinensis", + "grosskelchiges_johanniskraut", + "ackerbeere", + "lebenseiche", + "pfennigkraut", + "g\u00f6tterb\u00e4ume", + "poppig", + "kirsche", + "maroni", + "polyporus_squamosus", + "schirmtanne", + "cornus_florida", + "blattauge", + "preiselbeere", + "elsenkirsche", + "wassernuss", + "amerikanischer_schneeball", + "paradiesv\u00f6gel", + "rossminze", + "ackergauchheil", + "acrocarpus_fraxinifolius", + "seidenbaum", + "wirsing", + "silber_pappel", + "schwarzk\u00fcmmel", + "backhefe", + "spornblume", + "spitzahorn", + "nussbaum", + "wolfs_eisenhut", + "narrabaum", + "vogelmiere", + "winterkresse", + "magnolie", + "palmbaum", + "ulme", + "saccharum_officinarum", + "hydrangea_paniculata", + "belladonnalilie", + "buckeye", + "holzapfel", + "perlhirse", + "seidenpflanzen", + "cassave", + "goldmelisse", + "leitb\u00fcndel", + "kapaster", + "sprossen", + "fasole", + "dracaena_draco", + "nipapalme", + "kreuzblume", + "sadebaum", + "rauschbeere", + "st_maria", + "aschwurz", + "wermutkraut", + "actinidia_deliciosa", + "nachtschattengew\u00e4chs", + "kleine_wasserlinse", + "melissen", + "dalbergia_latifolia", + "marathi", + "kriechklee", + "zellwand", + "pleurotus_ostreatus", + "allium_ursinum", + "wicke", + "kaiserling", + "eselsgurke", + "kiefern", + "wasserfeder", + "magnolien", + "blattsalat", + "palmfarne", + "klatschmohn", + "kautschukbaum", + "wunderblume", + "waldreben", + "camphora", + "waldrebe", + "rosa_moschata", + "dreifurchige_wasserlinse", + "baumheide", + "kletternder_giftsumach", + "sophora_japonica", + "turibaum", + "sand_thymian", + "leindotter", + "mastix", + "calocedrus_decurrens", + "erythronium_montanum", + "dattelpalme", + "riesenbovist", + "die_heilige_maria", + "aspidistra_elatior", + "brombeere", + "pechnelken", + "brunnenlebermoos", + "telegraphenpflanze", + "klematis", + "gummibaum", + "stundenblume", + "korallenwurz", + "kapokbaum", + "regenbaum", + "humulus_japonicus", + "strelitzia_reginae", + "indigolupine", + "pfeifenwinde", + "rahmapfel", + "colocasia_esculenta", + "speierling", + "europ\u00e4ischer_meersenf", + "salweide", + "inga_edulis", + "edelweiss", + "k\u00fcnstlerin", + "wucherblume", + "enokitake", + "cardamine_pratensis", + "wurmfarn", + "phyllitis_scolopendrium", + "allium_fistulosum", + "gundelrebe", + "hornveilchen", + "kleinbl\u00fctige_bergminze", + "tangerine", + "kolbenhirse", + "johanniskraut", + "judenbart", + "wiesenkerbel", + "grauschn\u00e4pper", + "agropyron_repens", + "wunderbaum", + "schwarznessel", + "kaiserkrone", + "limabohne", + "blutbeere", + "weisstanne", + "belladonna", + "straucherbse", + "marchantia_polymorpha", + "waldmeister", + "amerikanische_platane", + "guineapfeffer", + "waldkiefer", + "aristolochia_clematitis", + "moorlilie", + "catharanthus_roseus", + "strand_grasnelke", + "guajakholz", + "malagettapfeffer", + "bockbeere", + "douglasie", + "trauerweide", + "kampfl\u00e4ufer", + "spritzgurke", + "knollenbegonien", + "edelkastanie", + "puffbohne", + "paradiesvogelblume", + "schwarzrohrbambus", + "pekingkohl", + "cremeschnitte", + "sandelholzbaum", + "chrysanthemum", + "schwarznuss", + "rippenfarn", + "agrimonia", + "swertia_japonica", + "oliv", + "brechbohne", + "heckenausdruck", + "vallisneria", + "kiefernholz", + "rosa_banksiae", + "feigenblatt", + "schlehe", + "euphorbia_milii", + "s\u00fcsskirsche", + "saat_esparsette", + "turmkraut", + "wasserfalle", + "phyllostachys_bambusoides", + "g\u00f6tterbaum", + "hopfenklee", + "physalis_peruviana", + "sauerampfer", + "apfelminze", + "vergissmeinnicht", + "quercus_virginiana", + "waldsauerklee", + "muskatellersalbei", + "purpurtanne", + "cassava", + "geissraute", + "gurkenbaum", + "tellerkraut", + "magnolia", + "schaf_porling", + "nephrolepis_exaltata", + "asclepias_meadii", + "pterocarpus_macrocarpus", + "cherimoya", + "heckenkirsche", + "phellodendron_amurense", + "pinus_palustris", + "conium_maculatum", + "f\u00e4rberkamille", + "haferwurzel", + "palmenbaum", + "sauerkirsche", + "flammenbaum", + "gemeiner_stechapfel", + "rosa_damascena", + "mohrr\u00fcbe", + "camellia_japonica", + "fliederbusch", + "wiesensalbei", + "mastixstrauch" + ], + "GPE": [ + "st_barbara", + "menschenrecht", + "der_heilige_georg", + "industriegebiete", + "georgitag", + "menschenrechte", + "valentinstag", + "st_peter", + "saint_domingue", + "arbeitsbeschaffung", + "zentralamerika", + "zuckerstock", + "westwind", + "goldbergwerk", + "neutestamentlich", + "sint_maarten", + "heiliger_geist", + "pechstr\u00e4hne", + "pandanus_tectorius", + "westneuguinea", + "tai_shan", + "weissgold", + "olympiadorf", + "die_heilige_barbara", + "stadtplatz", + "gebirgspass", + "heisswasser", + "seribu", + "hagia_sophia", + "unsere_liebe_frau", + "rotes_kreuz", + "sankt_georg", + "heiligenberg", + "s\u00e3o_tom\u00e9", + "gran_canaria", + "deutsches_kaiserreich", + "westsee", + "daressalam", + "neuspanien", + "simon_petrus", + "bundesdistrikt", + "weisses_haus", + "olympisches_dorf", + "al_andalus", + "la_rochelle", + "niederschlesisch", + "viel_gl\u00fcck", + "st_georg", + "sankt_barbara", + "hibiscus_rosa_sinensis", + "charlottenburg_wilmersdorf", + "nikolaus_von_myra", + "sri_jayawardenepura", + "georgstag", + "la_gomera", + "warmwasser", + "s\u00fcdamerika", + "sankt_lorenz_strom", + "altstadt", + "der_heilige_nikolaus", + "st_louis", + "st_nikolaus" + ], + "FOOD": [ + "kondensmilch", + "tabascosauce", + "wachsk\u00fcrbis", + "baumwollsamen\u00f6l", + "kartoffelsalat", + "gartenkresse", + "salzwasserfisch", + "olla_podrida", + "geburtstagskuchen", + "bitterschokolade", + "mousse", + "zimtbr\u00f6tchen", + "knoblauchbrot", + "rohmilch", + "b\u00fcchsenfleisch", + "obstsaft", + "schaumfestiger", + "fr\u00fchst\u00fcck", + "gummieren", + "puffreis", + "eiskaffee", + "kanditen", + "golden_delicious", + "fr\u00fchlingsrolle", + "windbeutel", + "butterschmalz", + "mais\u00f6l", + "currypulver", + "daucus_carota", + "zimtschnecke", + "hundefutter", + "schokoriegel", + "magermilch", + "lorbeerblatt", + "mittagessen", + "leitungswasser", + "trinkwasser", + "christmas_pudding", + "schnellkost", + "vollmilch", + "naturreis", + "zuckerwatte", + "brandteigkrapferl", + "kohlbl\u00e4tter", + "potaufeu", + "schokoladenkuchen", + "entenstopfleber", + "salzlake", + "kaugummi", + "cremeeis", + "rotwein", + "schnellgericht", + "blauschimmelk\u00e4se", + "hahnenwasser", + "pulverkaffee", + "brause", + "granny_smith", + "zitronensaft", + "capsicum", + "katzenfutter", + "g\u00e4nsestopfleber", + "sprudelsaft", + "roggenbrot", + "lebkuchenmann", + "schmelzk\u00e4se", + "oliven\u00f6l", + "erfrischungsgetr\u00e4nk", + "sauce", + "tiefk\u00fchlkost", + "bambussprossen", + "limettensaft", + "wurzelgem\u00fcse", + "fertigessen", + "plunze", + "h\u00fcttenk\u00e4se", + "karottensaft", + "t_bone_steak", + "cornedbeef", + "fritten", + "rotwurst", + "hochzeitstorte", + "tonicwasser", + "lippencreme", + "b\u00fcckling", + "expresskaffee", + "geleebonbon", + "pinot_noir", + "kindesunterhalt", + "orangenschale", + "appetithappen", + "weissbrot", + "schlagobers", + "entr\u00e9e", + "kleines_schwarzes", + "r\u00fchrkuchen", + "tafelsalz", + "appetizer", + "zuckerschote", + "biskuitroulade", + "easteregg", + "traubensaft", + "schnapsleckerbissen", + "fastfood", + "weizenmehl", + "dosenmilch", + "fotzelschnitte", + "chilisauce", + "tonic_water", + "chopsuey", + "vollkornmehl", + "rosinenbrot", + "schwarzwurst", + "palm\u00f6l", + "ahornsirup", + "french_dressing", + "rotkohl", + "ingwerbier", + "pommes", + "fruchtsalat", + "bechamelsosse", + "fleischk\u00e4se", + "hustenbonbon", + "stopfleber", + "chili", + "g\u00e4nseleber", + "pflanzen\u00f6l", + "schwarzbrot", + "lippenbalsam", + "schweinsbraten", + "rosenwurst", + "lunch", + "halsbonbon", + "zuckerstein", + "grahambrot", + "chile", + "zuckerstange", + "antipasto", + "preiselbeersaft", + "tafelwein", + "graupen", + "sprudelwasser", + "hackbraten", + "staubzucker", + "schlagrahm", + "sauerrahm", + "gl\u00fcckskeks", + "pudding", + "weisswein", + "backwerk", + "beigabe", + "osterei", + "sonnenblumen\u00f6l", + "pekannusskuchen", + "blutwurst", + "dessertwein", + "dessert", + "morgenessen", + "schweinebraten", + "blunze", + "hacksteak", + "tuttifrutti", + "plunzen", + "pfefferkuchenmann", + "schokoladenpudding", + "tutti_frutti", + "ros\u00e9wein", + "rotgl\u00fchend", + "speiseeis", + "obstsalat", + "arme_ritter", + "french_toast", + "distel\u00f6l", + "schildkr\u00f6tensuppe", + "augenbohne", + "sprudel", + "trockenobst", + "wiegebraten", + "kartoffelchips", + "orangensaft", + "br\u00fchw\u00fcrfel", + "kraftfleisch", + "markstammkohl", + "o_saft", + "vollkornbrot", + "instantkaffee", + "fertigkost", + "fischst\u00e4bchen", + "brotlaib", + "ros\u00e9", + "schaumwein", + "rinderhack", + "vollkornreis", + "rohrzucker", + "petit_four", + "desertieren", + "omelette", + "perlgraupen", + "cayennepfeffer", + "pot_au_feu", + "linsensuppe", + "blunzen", + "puderzucker", + "lebenselixier", + "eiswaffel", + "feigenkaktus", + "feuertopf", + "rinderp\u00f6kelfleisch", + "waldorfsalat", + "ochsenschwanzsuppe", + "pfefferoni", + "chesterk\u00e4se", + "schwarzbarsch", + "kakaopulver", + "maiskeim\u00f6l", + "streichrahm", + "schlagsahne", + "kakaobutter", + "schokoladenmilch" + ], + "DATE": [ + "goldenes_zeitalter", + "menstruationszyklus", + "pfingstdienstag", + "krankenstand", + "kalenderjahr", + "mondjahr", + "vollmond", + "solarkonstante", + "bis_s_zur_mittagsstunde", + "sternzeit", + "der_erste_april", + "wintersonnenwende", + "halbmond", + "schutzalter", + "geburtenziffer", + "aschermittwoch", + "barockzeit", + "fragestunde", + "mondkalender", + "in_time_deine_zeit_l\u00e4uft_ab", + "sterntag", + "menschengedenken", + "happy_hour", + "mittelalter", + "mittelpal\u00e4olithikum", + "christliche_zeitrechnung", + "the_day_after_tomorrow", + "normalzeit", + "schalttag", + "die_nachtwache", + "heiligenfest", + "trinitatis", + "lunisolarkalender", + "daten\u00fcbertragungsrate", + "sommerakademie", + "gr\u00fcndonnerstag", + "sonnenkalender", + "walpurgisnacht", + "schaltsekunde", + "jahrhundertwende", + "halbwertszeit", + "studienjahr", + "adventssonntag", + "wirtschaftsjahr", + "karfreitag", + "lagerf\u00e4higkeit", + "mondtag", + "s\u00e4uglingssterblichkeit", + "schaltjahr", + "arbeitsunf\u00e4higkeit", + "m\u00e4nnertag", + "lichtstrom", + "herbsttagundnachtgleiche", + "ruhetag", + "\u00fcbermorgen", + "fluchtgeschwindigkeit", + "spielunterbrechung", + "a_und_o", + "gregorianischer_kalender", + "the_day_after_der_tag_danach", + "schuljahr", + "nachtschicht", + "im_jahr_des_herrn", + "nationalfeiertag", + "vollj\u00e4hrigkeitsalter", + "barockzeitalter", + "fr\u00fchjahrstagundnachtgleiche", + "lebensl\u00e4nglich", + "gesch\u00e4ftsjahr", + "stosszeit", + "palmsonntag", + "lagerbest\u00e4ndigkeit", + "mondphase", + "weltraumzeitalter", + "bankfeiertag", + "rushhour", + "d_day", + "sommersonnenwende", + "vorlaufzeit", + "namenstag", + "auf_lange_sicht", + "ostersonntag", + "das_a_und_o", + "vollj\u00e4hrigkeit", + "unabh\u00e4ngigkeitstag", + "volkstrauertag", + "hochzeitstag", + "herbstvollmond", + "allerseelentag", + "hauptverkehrszeit", + "ladenschluss", + "herzminutenvolumen", + "hochzeitsjubil\u00e4um", + "hundstage", + "quasimodogeniti", + "allerheiligen", + "radialgeschwindigkeit", + "hohes_alter", + "barockepoche", + "jungpal\u00e4olithikum", + "opferfest", + "vierteljahrhundert", + "corpus_christi", + "faschingsdienstag", + "mari\u00e4_himmelfahrt", + "sterberate", + "allerseelen", + "sekundenbruchteile", + "was_ihr_wollt", + "muttertag", + "hauptsendezeit", + "karsamstag", + "neumond", + "primetime" + ], + "RELIGION_MEMBER": [ + "dschihadistin", + "sarazene", + "guru", + "wahhabitin", + "augustine", + "the_hindu", + "mohammedanerin", + "gottlose", + "protestant", + "christin", + "gottesleugnerin", + "mulla", + "moor", + "dunker", + "protestantisch", + "trappistin", + "baptistisch", + "wiedert\u00e4ufer", + "chartreux", + "christkatholisch", + "katholisch", + "atheist", + "muselmanin", + "sunnit", + "christlich", + "wesleyaner", + "gottloser", + "schiit", + "puritaner", + "melkite", + "melkitin", + "mormon", + "muselman", + "r\u00f6misch_katholisch", + "franziskaner", + "methodistin", + "waischnawa", + "sunnitisch", + "franziskanische_orden", + "baptist", + "methodist", + "christian", + "muhammedaner", + "mullah", + "gotteskriegerin", + "benediktinerin", + "presbyterianisch", + "trappist", + "wesleyanerin", + "gotteskrieger", + "schiitisch", + "mohammedaner", + "protestantin", + "presbyterian", + "katholik", + "mon", + "sufi", + "dschihadist", + "gottesleugner", + "atheistin", + "muselmane" + ], + "PRODUCT": [ + "dicke_bertha", + "s\u00e3o_tom\u00e9_und_pr\u00edncipe", + "kaffeetasse", + "zwangsprostitution", + "st_vincent", + "stephanstag", + "meerschwein", + "justin_bieber", + "diamantenfieber", + "s_tog", + "puppenhaus", + "panzerwagen", + "heiliger_geist", + "zeitmaschine", + "landungsboot", + "stephanustag", + "magnetstreifen", + "von_gottes_gnaden", + "hochtourig", + "take_off", + "im_andenken_an", + "handbohrmaschine", + "g\u00e9rard_philipe", + "durch_verm\u00f6genswerte_gesichert", + "weihnachtsbaum", + "menschenrechte", + "hartgekocht", + "al_jazeera", + "microsoft_excel", + "naturgeschichte", + "plattform\u00fcbergreifend", + "signalverarbeitung", + "hexenkessel", + "r\u00f6merreich", + "diego_garcia", + "tutti_frutti", + "das_eisen_schmieden_so_lange_es_heisst_ist", + "sicherungsautomat", + "echinopsis_pachanoi", + "schnelllaufend", + "christbaum", + "enterhaken", + "liebesbrief", + "superschnell", + "rechenschieber", + "per_anhalter_durch_die_galaxis", + "das_irrlicht", + "der_herr_der_ringe", + "tuttifrutti", + "weltraumstation", + "das_rote_zimmer", + "segelschiff", + "die_heilige_maria", + "sportwagen", + "musikdose", + "tennisball", + "in_memoriam", + "hausmeerschweinchen", + "wenn_gott_will", + "leitungsschutzschalter", + "julius_caesar", + "was_ihr_wollt", + "durchreise", + "vom_winde_verweht", + "nasenring", + "kurzschluss", + "was_gibt's_neues", + "richtschwert", + "schnellbahn", + "the_star_spangled_banner", + "ghettoblaster", + "die_zeitmaschine", + "da_liegt_der_hund_begraben", + "zusammentreiben", + "don_quixote", + "zur_erinnerung_an", + "monte_cristo", + "la_palma", + "mau_mau", + "the_hitchhiker\u2019s_guide_to_the_galaxy", + "sachsen_anhalt", + "neues_testament", + "spaceshuttle", + "st_maria", + "a_jugend", + "der_gestiefelte_kater", + "tot_oder_lebendig", + "tanzfl\u00e4che", + "after_burner", + "die_vier_jahreszeiten", + "schwimmhose", + "zwei_br\u00fcder", + "spieldose", + "pauschenpferd", + "der_liebesbrief", + "zuckerl\u00f6ffel", + "milit\u00e4rflugzeug", + "boxing_day", + "mittelerde", + "zum_ged\u00e4chtnis_an", + "lederjacke", + "wenn_gott_es_will", + "deutsche_welle", + "gaslampe", + "himmelsk\u00f6rper", + "sode", + "gong", + "weltraumf\u00e4hre", + "mount_st_helens", + "samichlaus", + "startrampe", + "the_scarlet_letter", + "der_kleine_bruder", + "ferdinand_magellan", + "sierra_blanca", + "the_pilgrim\u2019s_progress", + "unsternbedroht", + "sumpflichter", + "g\u00fcrtelschnalle", + "hoheslied", + "kickstarter", + "abschussrampe", + "mario_andretti", + "weltende", + "kienapfel", + "hohelied", + "neukaledonisch", + "die_tribute_von_panem_t\u00f6dliche_spiele", + "halfpipe", + "stefanstag", + "versuchskaninchen", + "grosssegler", + "das_s\u00fcsse_leben", + "magnetdiskette", + "die_tribute_von_panem", + "kaffeekanne", + "stichstrasse", + "dreidimensional", + "santa_catarina", + "vollgas", + "im_gedenken_an", + "de_facto", + "vergissmeinnicht", + "sesamstrasse", + "stephanitag", + "balkangebirge", + "wie_sie_es_w\u00fcnschen", + "c_jugend", + "anleuchten", + "verreisen", + "nordrhein_westfalen", + "kronjuwelen", + "talkradio", + "viel_l\u00e4rm_um_nichts", + "streitaxt", + "das_neue_leben", + "zweiter_weihnachtstag", + "tafelklavier", + "neutestamentlich", + "flaschenpost", + "ich_bitte_um_verzeihung", + "leistungsschutzschalter", + "stefanitag", + "forderungsbesichert", + "stillleben", + "hochsee", + "der_hund_von_baskerville", + "und_dennoch_leben_sie", + "schneiderkreide", + "cookinseln", + "hockeyschl\u00e4ger", + "verm\u00f6gensbesichert", + "novo_mesto", + "s\u00e3o_paulo" + ], + "RACE": [ + "filipino", + "t\u00fcrke", + "einheimische", + "the_european", + "insulanerin", + "indian_airlines", + "philippiner", + "latino", + "nordeurop\u00e4isch", + "nordeurop\u00e4erin", + "inderin", + "turk", + "t\u00fcrkin", + "africus", + "nordkoreanisch", + "nordkoreanerin", + "polynesier", + "afrikanerin", + "vietnamese", + "autochthon", + "inselbewohner", + "franz\u00f6sin", + "urbewohner", + "afrikanisch", + "the_mexican", + "franzose", + "maximalpigmentierter", + "chinese", + "inselbewohnerin", + "japanese", + "ostasiatisch", + "insulaner", + "blanko", + "nordeurop\u00e4er", + "polynesisch", + "negro", + "latina", + "schwarze", + "fransen", + "negerchen", + "negerlein", + "nordkoreaner" + ], + "LAW": [ + "wahlsystem", + "b\u00fcrgerliches_recht", + "todesurteil", + "patientenverf\u00fcgung", + "redefreiheit", + "datenbankadministrator", + "versammlungsfreiheit", + "nicht_zweimal_in_derselben_sache", + "sammelklage", + "ordnungsmittel", + "hinrichtungsbefehl", + "kreuzverh\u00f6r", + "rechtstaatlichkeit", + "verwaltungsrecht", + "richterliches_pr\u00fcfungsrecht", + "glaubensfreiheit", + "r\u00f6misches_recht", + "strafgesetzbuch", + "doppelbestrafung", + "steuerrecht", + "ne_bis_in_idem", + "strafrecht", + "rechtecharta", + "religionsfreiheit", + "durchsuchungsbefehl", + "generalstaatsanwalt", + "seerecht", + "federal_bureau_of_investigation", + "handelsrecht", + "chancengleichheit", + "n_n" + ], + "RELIGION": [ + "reformjudentum", + "shint\u014d", + "zen", + "shinto", + "salafismus", + "anabaptismus", + "hinayana", + "vedanta", + "schintoismus", + "trinitarismus", + "evangelisch_lutherische_kirchen", + "wiedert\u00e4uferlehre", + "methodismus", + "presbyterianismus", + "dreieinigkeitslehre", + "islam", + "donatismus", + "chabad", + "t\u00e4uferbewegung", + "trinitarianismus", + "christian_science", + "sintoismus", + "vishnuismus", + "dreifaltigkeitslehre", + "calvinismus", + "manich\u00e4ismus", + "wicca", + "daoismus" + ], + "LANGUAGE": [ + "mazedonier", + "zwie", + "shona", + "galicisch", + "madagassin", + "assamesisch", + "romane", + "bichelamar", + "venda", + "interlingue", + "madagassisch", + "bambara", + "kashmiri", + "galizisch", + "t\u00fcrkisch", + "schmied", + "kongo", + "deutscher", + "catalana", + "tscheche", + "akan", + "latein", + "portugiese", + "russl\u00e4nder", + "russl\u00e4nderin", + "chinesin", + "tschechisch", + "plundergeb\u00e4ck", + "sindhi", + "kasachisch", + "amarinya", + "engl\u00e4ndisch", + "grieche", + "tschechin", + "georgierin", + "pali", + "ling\u00e1la", + "navajo", + "mazedonierin", + "wallonisch", + "aymara", + "manx", + "tschuwaschisch", + "malagassi", + "lucianisch", + "malayalam", + "s\u00fcdpikenisch", + "marshallisch", + "katalane", + "kanaresisch", + "portugiesin", + "lateinisch", + "madagasse", + "katalanin", + "sinhala", + "hindi", + "finnisch", + "japanerin", + "marshallesisch", + "chamorro", + "lucianer", + "mutterschaf", + "baschkirisch", + "guarani", + "teutsch", + "zhuang", + "herero", + "naoero", + "german", + "sango", + "a_pucikwar", + "kartwelisch", + "divehi", + "georgisch", + "chinese", + "keltisch", + "judenteutsch", + "lucianerin", + "esperanto", + "kisuaheli", + "walisisch", + "politur", + "portugiesisch", + "japanese", + "komi", + "lingala", + "griechin", + "hausa", + "belarussisch", + "mazedonisch", + "malaiisch", + "polnisch", + "wolof", + "cree", + "lao", + "kikuyu", + "persisch", + "tagalog", + "ido", + "schwedisch", + "weissruthenisch", + "schmid", + "reussin", + "marathi", + "irl\u00e4ndisch", + "arabische_sprache", + "malagasy", + "sundanesisch", + "katalanisch", + "grusinisch", + "kalaallisut", + "quechua", + "chichewa", + "reusse", + "tonga", + "kannada" + ], + "PERSON_PRONOUN": [ + "dich", + "deiner", + "verminen", + "i", + "dich_selbst", + "he", + "mine", + "zeche", + "his", + "nech", + "sie_selbst", + "our", + "dein", + "euch", + "her", + "auf_sich_selbst_gestellt", + "euer", + "bergwerk", + "deine", + "we", + "ihn", + "me", + "my", + "meins", + "us", + "meiner" + ], + "TITLE": [ + "mister", + "sir", + "mr", + "ms" + ], + "ANAT": [ + "tigerfell", + "oberarm", + "hinterarm", + "herzmuskel" + ], + "POLITICAL_PARTY": [ + "conservative_party", + "labor_party", + "partido_conservador", + "green_party", + "partidul_social_democrat", + "partidul_conservator", + "partit_laburista", + "maloche", + "republikanische_partei", + "labour_party", + "partij_van_de_arbeid", + "f\u00f3lkaflokkurin", + "nsdap", + "demokrat_parti", + "demokratische_partei", + "kommunistiska_partiet", + "labor", + "kuomintang", + "know_nothing_party", + "liberal_party", + "politische_partei", + "demokratisch_republikanische_partei", + "szoci\u00e1ldemokrata_p\u00e1rt", + "partido_progresista", + "strana_zelen\u00fdch", + "partido_popular", + "liberale_partei", + "linkspartei", + "partido_democr\u00e1tico", + "irish_labour_party", + "partido_socialista", + "sotsiaaldemokraatlik_erakond", + "anti_masonic_party", + "parti_socialiste", + "gartenparty", + "partido_progressista", + "milj\u00f6partiet_de_gr\u00f6na", + "partito_democratico", + "piratenpartei", + "socialist_party", + "kommunistische_partei", + "regierungspartei", + "javna\u00f0arflokkurin", + "agrarpartei", + "millennium_demokratische_partei", + "australian_labor_party", + "nationalsozialistische_deutsche_arbeiterpartei", + "opposition", + "socialistische_partij", + "nasionale_party", + "arbeiderpartiet", + "guomindang", + "volkspartei", + "parti_populaire", + "dimokratiko_komma", + "arbeiterpartei" + ], + "EVENT": [ + "totentanz", + "grosser_preis", + "golfkrieg", + "filmfestival", + "stabhochsprung", + "so_ist_das_leben", + "sing_sing", + "aufgepasst", + "grand_prix", + "aufstrebend", + "seeschlacht" + ], + "QUANTITY": [ + "beaufortskala", + "nicht_die_bohne", + "primfaktor", + "reibungskoeffizient", + "imagin\u00e4rteil", + "sterling", + "voltampere", + "bogensekunde", + "lichtstunde", + "radizieren", + "elektronenvolt", + "achtundsiebzig", + "kubikwurzel", + "kernladungszahl", + "shilling", + "tastschreiben", + "sechsundzwanzig", + "d_mark", + "schweizer_franken", + "kalorie", + "schilling", + "tone", + "zweiundzwanzig", + "ton", + "siebenundzwanzig", + "quadratmeile", + "dollar", + "riyal", + "quadratmeter", + "dreiundzwanzig", + "wirkungsquantum", + "parkautomat", + "\u00f6sterreichischer_schilling", + "verwahrstelle", + "achtundzwanzig", + "parkuhr", + "g", + "ordinalzahl", + "vierundzwanzig", + "parkhaus", + "zweistellig", + "einheitensystem", + "the_real_world", + "elektronvolt", + "trockenmass", + "rial", + "massenzahl", + "lichtsekunde", + "franc_guin\u00e9en", + "parkgarage", + "kn\u00f6llchen", + "quadratfuss", + "krone", + "dreiviertel", + "pound", + "stutz", + "drei_schwestern", + "dreiundneunzig", + "zehntausend", + "pond", + "dreidimensional", + "robotergesetze", + "neunundzwanzig", + "kettenbruch", + "quadratwurzel", + "ordinale", + "franz\u00f6sischer_franc", + "quecksilbers\u00e4ule", + "periodischer_bruch", + "betragsfunktion", + "hunderttausend", + "dezimalzahl", + "anders_celsius", + "strafzettel", + "lichtjahr", + "zeit_der_drei_reiche", + "weiher" + ], + "PERSON": [ + "doppelsieg", + "julius_caesar", + "a_i", + "al_gore", + "mount_hubbard", + "seleucus", + "h_g_wells", + "prinz_albert", + "a_k", + "la_grange", + "ei_ei", + "st_vincent", + "william_playfair", + "don_delillo", + "e_e_cummings", + "hans_meier", + "i_ging", + "ada_hannah_wright", + "tai_shan", + "al_am\u012bn", + "de_witt", + "min_dong", + "george_v", + "zum_beiderseitigen_vorteil", + "t_bone_steak", + "peter_dawson", + "peter_brook", + "carl_david_anderson", + "gaius_julius_caesar", + "ich_auch", + "jo_jo", + "maxwell_anderson", + "a_b", + "dominikus", + "yo_yo", + "rudolf_hess", + "dr_watson" + ], + "GENDER": [ + "miss", + "herrin", + "mademoiselle", + "m\u00e4nnlein", + "girl", + "gentleman", + "deern", + "men", + "transgeschlechtlich", + "bursche", + "chap", + "weibchen", + "dame", + "bub", + "boy", + "male", + "boys", + "guido", + "m\u00e4nner", + "greisin", + "maid", + "samica", + "der_mann", + "tribade", + "transgender", + "matrone", + "lass", + "man", + "matz", + "alte_frau", + "gal", + "maiden", + "lady", + "herrschaften" + ], + "POLITICAL_PARTY_MEMBER": [ + "kommunistin", + "kommunist", + "fabisch", + "genosse", + "menschewik", + "fabian" + ], + "MEDICAL_THERAPY": [ + "quacksalberprodukt", + "hirndruck", + "blutdruck" + ], + "UNION": [ + "gefangenengewerkschaft", + "international_telecommunication_union", + "weltpostverein", + "polizeigewerkschaft", + "nea", + "gewerkschaft", + "studierendenvertretung", + "internationale_fernmeldeunion" + ], + "ner_regexes": [ + [ + "PERSON", + "\\D+ \\D+|\\D+ \\D+|\\D+ \\D+|\\D+ \\D+|\\D+ \\D+-\\D+|\\D+ \\D+ \\D+|\\D+ \\D+|\\D+ \\D+|\\D+ \\D+|\\D+ \\D+|\\D+ \\D+-\\D+|\\D+ \\D+ \\D+", + false, + [] + ], + [ + "PERSON", + "\\D+ \\D+|\\D+ \\D+|\\D+ \\D+|\\D+ \\D+|\\D+ \\D+|\\D+ \\D+|\\D+ \\D+|\\D+ \\D+-\\D+|\\D+ \\D+ \\D+|\\D+ \\D+ \\D+", + false, + [] + ], + [ + "PERSON", + "\\D+ \\D+|\\D+ \\D+|\\D+ \\D+|\\D+ \\D+|\\D+ \\D+-\\D+|\\D+ \\D+ \\D+|\\D+ \\D+ \\D+|\\D+ \\D+ \\D+ \\D+|\\D+ \\D+|\\D+ \\D+|\\D+ \\D+|\\D+ \\D+|\\D+ \\D+-\\D+|\\D+ \\D+ \\D+|\\D+ \\D+ \\D+|\\D+ \\D+ \\D+ \\D+", + false, + [] + ] + ], + "FIRST_NAME_FEMALE": [ + "mareen", + "heidelinde", + "babette", + "aysel", + "meret", + "kata", + "k\u00e4thi", + "zoe", + "luisa", + "claudine", + "raffaela", + "katerina", + "grete", + "roswitha", + "sevim", + "cheyenne", + "melisa", + "ga\u00eblle", + "edelgard", + "helene", + "birthe", + "song\u00fcl", + "anne", + "karine", + "eva", + "wendy", + "evi", + "jasmina", + "emilija", + "line", + "alexia", + "iwona", + "cassandra", + "marie_th\u00e9r\u00e8se", + "annelore", + "selma", + "laure", + "marinette", + "annabella", + "annika", + "britt", + "juna", + "valerie", + "luciana", + "rosa_maria", + "elsbeth", + "gladys", + "anne_katrin", + "selina", + "slavica", + "anne_laure", + "debora", + "elisabet", + "walburga", + "katharine", + "jolanthe", + "assunta", + "hulda", + "henni", + "anni", + "inna", + "therese", + "ingried", + "alice", + "annalena", + "karla", + "freia", + "s\u00e9verine", + "patr\u00edcia", + "sinaida", + "berit", + "norah", + "flavia", + "sibylla", + "karolina", + "suse", + "michaele", + "betti", + "madeleine", + "fatime", + "celine", + "rose_marie", + "heidelore", + "natalie", + "albertine", + "lieschen", + "kirstin", + "renate", + "amalie", + "c\u00e1tia", + "zdenka", + "milka", + "lili", + "giovanna", + "annerose", + "geza", + "olga", + "salome", + "carin", + "danielle", + "emina", + "raissa", + "traute", + "ricarda", + "rosalie", + "lilian", + "norina", + "romana", + "elisa", + "svea", + "d\u00f6rthe", + "beatrix", + "ludmila", + "cl\u00e4re", + "rosalba", + "helmtrud", + "catherine", + "laura", + "miroslawa", + "cristina", + "layla", + "gerdi", + "rabea", + "mechthilde", + "magarete", + "violetta", + "nika", + "theda", + "elo\u00efse", + "lana", + "georgette", + "vivian", + "genoveva", + "monika", + "mireille", + "magdalene", + "ingeburg", + "henri", + "mariana", + "ivonne", + "ilona", + "eda", + "andjelina", + "antonie", + "katarzyna", + "sarina", + "damaris", + "walentina", + "resi", + "luitgard", + "sylviane", + "oda", + "flurina", + "sina", + "morena", + "loretta", + "ylenia", + "luka", + "halina", + "uschi", + "dina", + "ronja", + "mirjam", + "katharina", + "minna", + "samira", + "lotti", + "violette", + "nikola", + "seline", + "soraya", + "magdalena", + "trudi", + "frida", + "aur\u00e9lie", + "luzie", + "valeska", + "annie", + "karoline", + "irmtraud", + "leyla", + "eugenie", + "no\u00ebmi", + "lucia", + "ortrud", + "ardita", + "eileen", + "gertrud", + "andjela", + "melek", + "lise", + "monica", + "maryse", + "sara", + "evelin", + "uta", + "aynur", + "gisela", + "c\u00e9line", + "gilda", + "luise", + "senta", + "antonietta", + "huguette", + "fatmire", + "vilma", + "nisa", + "mandy", + "zoey", + "wera", + "tabea", + "michela", + "jasmin", + "inge", + "anna", + "betina", + "raymonde", + "lene", + "asta", + "frederike", + "adele", + "lya", + "marlyse", + "vania", + "ewa", + "nathalie", + "esra", + "maria_theresia", + "hanny", + "emmy", + "heide_marie", + "celina", + "malin", + "bianca", + "natalja", + "lioba", + "ursula", + "ellinor", + "ester", + "maya", + "jenny", + "cynthia", + "johanna", + "liliana", + "britta", + "marcella", + "marie_louise", + "\u00f6zlem", + "olav", + "susann", + "ema", + "rosi", + "claire", + "henriette", + "natalia", + "anett", + "theresia", + "marie_luise", + "tamara", + "irmtraut", + "annegret", + "anka", + "edit", + "margaux", + "marie_laure", + "kalina", + "annelies", + "radmila", + "margita", + "lilo", + "sybilla", + "sheila", + "joana", + "nancy", + "ekaterina", + "giuliana", + "monique", + "sylvie", + "henrike", + "audrey", + "danica", + "saskia", + "adelinde", + "danuta", + "alena", + "mihaela", + "lotta", + "marliese", + "valeri", + "sibylle", + "annamaria", + "maryam", + "meike", + "larissa", + "katherina", + "marie", + "felicia", + "h\u00fclya", + "melinda", + "margaritha", + "kristina", + "tanya", + "stilla", + "irmela", + "wanda", + "irena", + "marie_theres", + "nicole", + "naomi", + "almut", + "grit", + "loni", + "enya", + "g\u00e9raldine", + "francine", + "rosl", + "veronique", + "sena", + "cinzia", + "gertraut", + "constanze", + "linnea", + "lucienne", + "ilaria", + "herlinde", + "lore", + "christl", + "heidi", + "anneke", + "ingelore", + "lena", + "marcela", + "emanuela", + "paulette", + "nora", + "dorina", + "eleni", + "andreia", + "ang\u00e9lique", + "marielle", + "martine", + "hedy", + "mariette", + "hilda", + "teresa", + "ursel", + "elisabete", + "stefania", + "marie_sophie", + "trude", + "annelene", + "oc\u00e9ane", + "leandra", + "xenia", + "reni", + "shpresa", + "edda", + "lidwina", + "marie_therese", + "\u00e4nne", + "carmela", + "cindy", + "telse", + "yvonne", + "gudula", + "birgitta", + "zehra", + "s\u00f3nia", + "madlen", + "giada", + "loredana", + "edith", + "ines", + "margarethe", + "agathe", + "herta", + "adeline", + "solveig", + "bettina", + "stephanie", + "polina", + "gertraud", + "mila", + "priska", + "hannah", + "marine", + "anny", + "antonia", + "arzu", + "kreszentia", + "yolande", + "fran\u00e7oise", + "ylvie", + "dorothee", + "lynn", + "yael", + "hertha", + "elisabetha", + "catharina", + "lea_sophie", + "jadwiga", + "sandra", + "hildburg", + "philomena", + "jara", + "inka", + "annelise", + "christelle", + "monja", + "desir\u00e9e", + "silvana", + "kriemhild", + "moira", + "gaia", + "leonor", + "margitta", + "bluette", + "virginia", + "sanja", + "elvira", + "liesel", + "albulena", + "marina", + "noelia", + "friedl", + "cosima", + "leonie", + "adolfine", + "shania", + "catarina", + "mina", + "siegrun", + "yolanda", + "melina", + "juliana", + "leoni", + "rosaria", + "valentine", + "michelle", + "luigia", + "daisy", + "erika", + "thi", + "vjollca", + "v\u00e9ronique", + "gloria", + "maritta", + "lidija", + "fatma", + "concetta", + "donatella", + "babett", + "ada", + "kiara", + "elda", + "daria", + "oxana", + "kl\u00e4re", + "jacqueline", + "claude", + "friederike", + "edona", + "sigrun", + "snezana", + "marie_jos\u00e9", + "mareike", + "ramona", + "sandrine", + "marion", + "bernhardine", + "solange", + "zeynep", + "kathi", + "mirja", + "cordula", + "krystyna", + "gabi", + "susan", + "nicola", + "astrid", + "frauke", + "carina", + "sonia", + "medina", + "no\u00eblle", + "peggy", + "annina", + "stella", + "alexandra", + "miranda", + "swetlana", + "romina", + "simona", + "liselotte", + "yasmine", + "mathilde", + "daniela", + "shqipe", + "germaine", + "annabell", + "martina", + "lilly", + "suzana", + "teuta", + "noemi", + "annalisa", + "ute", + "alix", + "gerta", + "carmine", + "hilma", + "norma", + "katja", + "irmhild", + "kunigunda", + "ingetraut", + "pierrette", + "amalia", + "ana\u00efs", + "anika", + "beate", + "sylvana", + "jasmine", + "fernanda", + "zofia", + "mariele", + "sophia", + "amina", + "deborah", + "gabriela", + "leona", + "tania", + "elisabeth", + "wilhelmine", + "viviana", + "annedore", + "lidia", + "jocelyne", + "jo", + "gislinde", + "gaby", + "floriane", + "margherita", + "elena", + "giesela", + "marilena", + "raphaela", + "margaret", + "annekatrin", + "mariechen", + "sabine", + "marianna", + "steffi", + "alyssa", + "lorena", + "sibel", + "federica", + "julijana", + "ariana", + "anne_lise", + "josiane", + "marlen", + "no\u00e9mie", + "k\u00e4te", + "tiffany", + "am\u00e9lie", + "branka", + "josefina", + "annegrete", + "ulla", + "nadia", + "bukurije", + "aneta", + "b\u00e4rbel", + "antonina", + "irmengard", + "else", + "annemarie", + "tiziana", + "kreszenz", + "mareile", + "juliane", + "sahra", + "edina", + "mirella", + "nadin", + "kelly", + "siegried", + "olivia", + "marie_christine", + "hildegunde", + "sibille", + "ayse", + "katalin", + "kirsten", + "rosemarie", + "virginie", + "alessia", + "verena", + "bruna", + "c\u00e9cile", + "imelda", + "ivanka", + "annamarie", + "janette", + "sybille", + "nelli", + "micheline", + "amelie", + "hanna", + "rahel", + "ruth", + "in\u00eas", + "swantje", + "philippa", + "alisha", + "ludivine", + "annalise", + "helen", + "eleonora", + "kathleen", + "diane", + "ganimete", + "silvia", + "hava", + "antje", + "sarah", + "mechthild", + "theresa", + "malika", + "edeltraut", + "sigrid", + "lindita", + "natascha", + "manon", + "camille", + "florentine", + "marl\u00e8ne", + "edeltraud", + "emma", + "eveline", + "eva_maria", + "g\u00f6n\u00fcl", + "traudel", + "nadine", + "nevenka", + "cristiana", + "margarita", + "kaltrina", + "maike", + "fabiola", + "herma", + "emilia", + "luana", + "serpil", + "gundel", + "martha", + "brit", + "ildiko", + "hanne_lore", + "rafaela", + "irmgard", + "emely", + "cilli", + "gretel", + "stefanie", + "elma", + "magali", + "annita", + "marika", + "meta", + "paulina", + "emine", + "aline", + "lisa_marie", + "carlotta", + "pia", + "teodora", + "sofie", + "alison", + "kornelia", + "tatjana", + "wilfriede", + "filiz", + "semra", + "eliza", + "ir\u00e8ne", + "dominique", + "marjorie", + "ingeborg", + "timea", + "jeannine", + "katrin", + "susanna", + "hiltraud", + "leticia", + "rose", + "fabiana", + "brigitte", + "genevi\u00e8ve", + "lilija", + "kunigunde", + "roberta", + "krista", + "hilde", + "ljudmila", + "agnes", + "marieluise", + "eva_marie", + "donata", + "eline", + "hatice", + "isabel", + "h\u00e9l\u00e8ne", + "d\u00f6rte", + "alisa", + "romy", + "laureen", + "hedda", + "adrienne", + "merita", + "liesbeth", + "luzia", + "jane", + "roswita", + "odette", + "hana", + "johanne", + "maja", + "amanda", + "aferdita", + "arlinda", + "melissa", + "amira", + "flora", + "ulrike", + "henny", + "harriet", + "gretchen", + "beata", + "bernadette", + "dora", + "anica", + "urte", + "marie_claude", + "hiltrud", + "aylin", + "pauline", + "rosita", + "insa", + "karen", + "marie_jeanne", + "romane", + "evangelia", + "grazia", + "mirela", + "beatrice", + "c\u00e9lia", + "anabela", + "irina", + "jutta", + "carole", + "wencke", + "ljubica", + "nikolina", + "silke", + "gundula", + "priscilla", + "gioia", + "natasha", + "janet", + "esma", + "anke", + "inga", + "thea", + "milena", + "margot", + "birte", + "leila", + "magret", + "maria", + "lavinia", + "reinhilde", + "adelheid", + "janna", + "dolores", + "chantal", + "ghislaine", + "nad\u00e8ge", + "marissa", + "siena", + "ladina", + "nela", + "justina", + "ingrid", + "margreth", + "helena", + "natali", + "anisa", + "isolde", + "emilie", + "aurora", + "josefa", + "nicoletta", + "lisbeth", + "fanny", + "charline", + "carine", + "corina", + "sofija", + "petra", + "nuran", + "ottilia", + "andrea", + "birgitt", + "yasmin", + "mara", + "maeva", + "zuzana", + "nina", + "sieglinde", + "klothilde", + "julia", + "traude", + "catia", + "sanije", + "tanja", + "caroline", + "fabia", + "rotraud", + "anne_kathrin", + "carola", + "leana", + "letizia", + "magda", + "fiona", + "irma", + "gesa", + "sol\u00e8ne", + "christiana", + "lotte", + "anne_marie", + "annaliese", + "waldtraut", + "azra", + "waltrud", + "gilberte", + "lydie", + "evamaria", + "anna_lena", + "brita", + "patricia", + "sibilla", + "samantha", + "mia", + "mariella", + "elif", + "malena", + "clarissa", + "iva", + "katia", + "anastasia", + "belinda", + "anabella", + "conny", + "mathilda", + "grazyna", + "camilla", + "cora", + "vanesa", + "lea", + "corine", + "irmi", + "mirjana", + "vesna", + "egzona", + "tessa", + "t\u00fclay", + "francesca", + "marjan", + "sophie", + "gitta", + "muriel", + "hedi", + "mimoza", + "andrina", + "hermine", + "marguerite", + "mariangela", + "leonore", + "jennifer", + "manja", + "maude", + "gerti", + "theodora", + "kathy", + "lisa", + "lou", + "jana", + "jill", + "wiltrud", + "lily", + "kordula", + "cathleen", + "romaine", + "christin", + "amandine", + "julie", + "myriam", + "nadeshda", + "marisa", + "benita", + "st\u00e9phanie", + "anneliese", + "nele", + "morgane", + "ella", + "alwina", + "walli", + "viktoria", + "ann_kathrin", + "magrit", + "jolanta", + "margret", + "melita", + "rita", + "alara", + "ava", + "leonora", + "khadija", + "val\u00e9rie", + "edeltrud", + "vincenza", + "delia", + "violeta", + "ursina", + "marianne", + "ivana", + "bozena", + "gianna", + "d\u00e9borah", + "olena", + "katherine", + "francoise", + "francisca", + "anja", + "florence", + "salom\u00e9", + "agata", + "gunda", + "dorothe", + "vera", + "elisabetta", + "christina", + "annabelle", + "sofia", + "myrta", + "centa", + "tenzin", + "undine", + "maida", + "leopoldine", + "lissy", + "fadime", + "bertha", + "nives", + "marica", + "natacha", + "hanne", + "dunja", + "helma", + "angelika", + "rosmarie", + "regula", + "corinna", + "anneli", + "wiebke", + "janin", + "lucie", + "rana", + "wenke", + "jaqueline", + "ilka", + "liesa", + "janett", + "elfi", + "georgia", + "viola", + "ariane", + "sabina", + "ren\u00e9e", + "b\u00e9atrice", + "lilia", + "agn\u00e8s", + "rosina", + "marleen", + "tilly", + "fitore", + "gis\u00e8le", + "carla", + "tatiana", + "elwira", + "silva", + "rosa", + "filipa", + "angela", + "eugenia", + "lydia", + "adelina", + "kyra", + "susi", + "chiara", + "linda", + "carmen", + "ina", + "dagmar", + "meral", + "laurence", + "nada", + "emmanuelle", + "jos\u00e9phine", + "caterina", + "heiderose", + "margrit", + "elsa", + "elly", + "m\u00e9gane", + "zora", + "lucy", + "doreen", + "pamela", + "agnieszka", + "sanela", + "heidrun", + "liane", + "friedericke", + "irene", + "rosalinde", + "waltraud", + "joelle", + "hannelore", + "ginette", + "kathrin", + "angelique", + "rayana", + "ajna", + "judith", + "iris", + "alea", + "dani\u00e8le", + "ortrun", + "veronika", + "freya", + "heidemarie", + "maddalena", + "tara", + "alma", + "liridona", + "susana", + "domenica", + "thekla", + "grace", + "anna_marie", + "jovana", + "yara", + "theres", + "siegrid", + "emily", + "zorica", + "jessika", + "gitte", + "marita", + "leontina", + "florentina", + "rosetta", + "isa", + "elise", + "heide", + "natasa", + "greta", + "gisa", + "margit", + "siglinde", + "betty", + "maryline", + "zenta", + "sandy", + "kerstin", + "k\u00e4the", + "leslie", + "diana", + "ornella", + "raquel", + "celia", + "etta", + "wally", + "irmtrud", + "lisette", + "vreneli", + "annemie", + "anita", + "juana", + "sladjana", + "annick", + "aurelia", + "friedhilde", + "th\u00e9r\u00e8se", + "jeannette", + "doris", + "urszula", + "barbara", + "fabienne", + "simone", + "sophie_marie", + "derya", + "jeanette", + "lejla", + "aurore", + "mechtild", + "claudia", + "vivienne", + "alicja", + "t\u00fcrkan", + "lilli", + "matilde", + "dilara", + "dietlinde", + "ja\u00ebl", + "blanka", + "hannchen", + "laila", + "augusta", + "eve", + "ronya", + "konstanze", + "elin", + "gertraude", + "ellie", + "suzanne", + "arianna", + "raisa", + "regine", + "renata", + "louise", + "eliana", + "carol", + "clara", + "amela", + "dorit", + "ayla", + "erna", + "stefani", + "erina", + "vivien", + "elona", + "wibke", + "mercedes", + "pierina", + "t\u00e2nia", + "cornelia", + "nadeschda", + "ludwina", + "karin", + "dana", + "alida", + "valentina", + "melitta", + "isabell", + "g\u00fclten", + "milica", + "franziska", + "salma", + "ingetraud", + "annette", + "giulia", + "leni", + "desiree", + "liana", + "janine", + "brigitta", + "gerhild", + "adriane", + "aida", + "jelena", + "cl\u00e9mence", + "drita", + "margrith", + "nurten", + "tea", + "karolin", + "mar\u00eda", + "antoinette", + "selena", + "meryem", + "zita", + "margarete", + "mira", + "anna_luise", + "charlotte", + "gabrielle", + "giuseppina", + "josette", + "esther", + "anina", + "vanessa", + "oph\u00e9lie", + "gabriele", + "nadja", + "erica", + "elzbieta", + "gertrude", + "ana", + "josephine", + "alla", + "sonja", + "agatha", + "michaela", + "chlo\u00e9", + "rebekka", + "alexa", + "arlette", + "justine", + "zara", + "yvette", + "mariam", + "christine", + "d\u00e9sir\u00e9e", + "ellen", + "birgid", + "corinne", + "selin", + "danijela", + "blerta", + "marijana", + "georgine", + "blerina", + "l\u00e9onie", + "sereina", + "joanne", + "elke", + "iryna", + "c\u00e4cilia", + "elodie", + "aude", + "besarta", + "ludmilla", + "luna", + "paula", + "marlise", + "juliette", + "alicia", + "franca", + "elizabeth", + "colette", + "marija", + "klaudia", + "svenja", + "christel", + "lara", + "marlene", + "dorota", + "anne_sophie", + "albina", + "mich\u00e8le", + "jael", + "mirlinda", + "aleksandra", + "alwine", + "rebecca", + "elfriede", + "dajana", + "ayten", + "lorenza", + "gusti", + "editha", + "ela", + "luljeta", + "lola", + "dorothea", + "birgit", + "ajla", + "klara", + "angelica", + "claire_lise", + "coralie", + "victoria", + "berthe", + "joyce", + "rachel", + "laetitia", + "marga", + "l\u00e9a", + "ernestine", + "gudrun", + "bruni", + "waltraut", + "susanne", + "anette", + "leokadia", + "christiane", + "dietlind", + "nuray", + "denise", + "jil", + "vittoria", + "ilonka", + "reinhild", + "marcia", + "mariola", + "samanta", + "hildegart", + "annett", + "in\u00e8s", + "heidy", + "rena", + "aloisia", + "christa_maria", + "marcelle", + "margarida", + "matilda", + "felizitas", + "isabelle", + "mary", + "marta", + "reingard", + "kristiane", + "nikita", + "constance", + "ruzica", + "antonella", + "notburga", + "liliane", + "apollonia", + "janina", + "amra", + "prisca", + "nelly", + "serena", + "adriana", + "c\u00e4cilie", + "marzena", + "viviane", + "fr\u00e9d\u00e9rique", + "sylke", + "g\u00fclay", + "melanie", + "brunhilde", + "aenne", + "noa", + "gemma", + "graziella", + "auguste", + "gabriella", + "inken", + "giorgia", + "evelyn", + "almuth", + "ria", + "nuria", + "hildegund", + "amy", + "roselinde", + "hanife", + "berta", + "jade", + "murielle", + "sylvia", + "gerda", + "roxane", + "ilse", + "jo\u00eblle", + "alba", + "sabrina", + "carolin", + "dragica", + "imke", + "friedlinde", + "m\u00e9lissa", + "felicitas", + "gina", + "dalia", + "marie_claire", + "cilly", + "heike", + "cathrin", + "bianka", + "kati", + "galina", + "marlies", + "ira", + "wilma", + "patrizia", + "yasemin", + "el\u00e9onore", + "malea", + "catrin", + "vlora", + "carolina", + "christa", + "lauriane", + "geraldine", + "gesche", + "wendelin", + "ruthild", + "lara_sophie", + "rosanna", + "zo\u00e9", + "l\u00e9na", + "hubertine", + "josefine", + "frieda", + "jeanne", + "gretl", + "amelia", + "ljiljana", + "ottilie", + "jolanda", + "joy", + "evelyne", + "lia", + "joanna", + "gunhild", + "lieselotte", + "elina", + "lora", + "traudl", + "mona", + "marietta", + "ma\u00eblle", + "marlis", + "rina", + "kira", + "dijana", + "rotraut", + "marthe", + "yasmina", + "regina", + "ilenia", + "jeanine", + "elea", + "hildegard", + "eleonore", + "rosel", + "tina", + "gesine", + "lina", + "berra", + "estelle", + "g\u00fclsen", + "caren", + "andr\u00e9e", + "ehrentraud", + "m\u00e9lanie", + "brunhild", + "asia", + "giuseppa", + "trudel", + "ann", + "paola", + "dorle", + "delphine", + "hella", + "cl\u00e1udia", + "gerlind", + "zahra", + "alessandra", + "erdmute", + "silja", + "kristin", + "dragana", + "dafina", + "helga", + "maren", + "hedwig", + "seraina", + "aisha", + "gundi", + "katarina", + "veronica", + "maud", + "raffaella", + "alina", + "karola", + "kim", + "l\u00e9ane", + "manuela", + "beatriz", + "malgorzata", + "karina", + "emmi", + "agnese", + "irmingard", + "elli", + "liv", + "biljana", + "adelgunde", + "marie_france", + "katy", + "nermin", + "rosalia", + "pascale", + "elfie", + "ida", + "fatima", + "anne_rose", + "anna_maria", + "franka", + "margaretha", + "jessica", + "canan", + "angelina", + "leah", + "elenore", + "myrtha", + "kristine", + "adina", + "margareta", + "lucette", + "alissa", + "sharon", + "tuana", + "gordana", + "annelie", + "marit", + "natalija", + "isabella", + "louisa", + "livia", + "valeria", + "gerlinde", + "odile", + "maria_luise", + "cecilia", + "korinna", + "sylwia", + "miriam", + "luz", + "anouk", + "svetlana", + "lissi", + "filomena", + "eliane", + "fernande", + "arta" + ], + "FIRST_NAME_MALE": [ + "sigmund", + "justin", + "fynn", + "pasquale", + "bayram", + "ivo", + "hans_walter", + "biagio", + "slavko", + "niko", + "nicolas", + "andrzej", + "emmanuel", + "gotthard", + "erol", + "dittmar", + "ueli", + "aldo", + "florian", + "ilhan", + "nathan", + "henry", + "yanik", + "ditmar", + "adelbert", + "elvis", + "fisnik", + "almir", + "knud", + "s\u00f6nke", + "claus_peter", + "mohammad", + "claudius", + "sigfried", + "achim", + "gerhart", + "petros", + "raul", + "german", + "jonah", + "ottokar", + "ingbert", + "adam", + "andy", + "burkard", + "domenic", + "omer", + "denny", + "sylvio", + "hasan", + "hansj\u00fcrg", + "werner", + "reinhard", + "alberto", + "donato", + "hans_ulrich", + "karl_heinrich", + "stefan", + "jasper", + "matti", + "gabor", + "domingos", + "frank", + "melchior", + "sam", + "gunther", + "sigmar", + "eberhard", + "luzius", + "moreno", + "folker", + "abdullah", + "mika", + "rui", + "vittorio", + "calvin", + "jo\u00ebl", + "hans_rainer", + "reinald", + "dennis", + "hansj\u00fcrgen", + "caspar", + "harro", + "safet", + "jonathan", + "hassan", + "kazim", + "heinz_joachim", + "carlo", + "zeljko", + "ensar", + "davide", + "hans_detlef", + "donald", + "bernhard", + "hans_uwe", + "augusto", + "aleksandar", + "thorben", + "ilias", + "umut", + "josip", + "elyas", + "claudio", + "noel", + "ennio", + "tassilo", + "emre", + "horst", + "ron", + "george", + "eckhardt", + "eckhard", + "ivano", + "ferenc", + "louis", + "eckart", + "engelbert", + "ilir", + "aleksej", + "sinan", + "abbas", + "basil", + "bj\u00f6rn", + "deniz", + "henri", + "paolo", + "freddy", + "ekrem", + "selim", + "hans_gerd", + "guntram", + "ali", + "hans_bernd", + "tony", + "luciano", + "juri", + "kushtrim", + "mahmut", + "mohamad", + "pierre", + "luka", + "valentino", + "heini", + "mauro", + "waldemar", + "beat", + "raimund", + "dorian", + "gerd", + "rinor", + "nikola", + "folkert", + "fran\u00e7ois", + "filip", + "laurent", + "raffael", + "hanno", + "malte", + "tom\u00e1s", + "norbert", + "julien", + "altin", + "cornelius", + "stanislaus", + "nicholas", + "silvester", + "bujar", + "samir", + "silvio", + "lennart", + "mattia", + "thoralf", + "toralf", + "no\u00ebl", + "mehmet", + "janusz", + "andrey", + "mathieu", + "roger", + "cemil", + "czeslaw", + "rigo", + "leart", + "alois", + "attila", + "hans_j", + "guido", + "branislav", + "marino", + "felix", + "jaroslav", + "pius", + "roberto", + "josef", + "cedric", + "dariusz", + "maurin", + "jasmin", + "ian", + "slavisa", + "hans_h", + "jason", + "reinhardt", + "hugo", + "kunibert", + "natan", + "gianni", + "karl_ernst", + "claus", + "sadik", + "franz_peter", + "stefano", + "denis", + "etienne", + "paulo", + "agim", + "lars", + "jack", + "merlin", + "hans_heinrich", + "lothar", + "jusuf", + "eren", + "yilmaz", + "tino", + "gordon", + "philip", + "armend", + "oskar", + "thorsten", + "diether", + "justus", + "cord", + "herrmann", + "adolf", + "ansgar", + "r\u00fcdiger", + "besart", + "quentin", + "mathias", + "faton", + "harold", + "slawomir", + "ehrenfried", + "astrit", + "hans_jochen", + "karl_ludwig", + "nikolai", + "milos", + "aaron", + "ivan", + "kay", + "rainer", + "andri", + "karl_georg", + "damien", + "nevio", + "ma\u00ebl", + "hermann", + "joao", + "amir", + "arnim", + "santiago", + "kian", + "fabrizio", + "otmar", + "diethelm", + "zbigniew", + "piero", + "andrew", + "s\u00fcleyman", + "anselm", + "helmar", + "nick", + "reiner", + "meinolf", + "erdogan", + "bekir", + "alvaro", + "aribert", + "kai_uwe", + "dario", + "arlind", + "niklas", + "armando", + "loris", + "jannik", + "friedemann", + "marten", + "rochus", + "giancarlo", + "leonid", + "carlos", + "hans_j\u00fcrgen", + "geert", + "stanislaw", + "ruben", + "karl_wilhelm", + "h._dieter", + "albin", + "fritz", + "aziz", + "moritz", + "dogan", + "yasin", + "leander", + "meinrad", + "dejan", + "heinz_g\u00fcnter", + "markus", + "nenad", + "aleksandr", + "sylvester", + "ole", + "paul_heinz", + "gerhard", + "theobald", + "hartmuth", + "gerfried", + "umberto", + "musa", + "cemal", + "julio", + "juan", + "imer", + "j\u00f6rg_peter", + "karl_dieter", + "jerome", + "heinz_j\u00fcrgen", + "heinz_peter", + "baldur", + "wilhelm", + "otfried", + "faruk", + "damir", + "robert", + "engin", + "g\u00f6khan", + "mikhail", + "jochem", + "romeo", + "dean", + "arben", + "harri", + "bastian", + "danny", + "christopher", + "marvin", + "laurin", + "andrei", + "erich", + "raymond", + "volkan", + "ottmar", + "luca", + "thierry", + "kilian", + "adalbert", + "leonhard", + "benjamin", + "branko", + "hellmut", + "rinaldo", + "dardan", + "ingmar", + "emanuele", + "romano", + "valon", + "horst_peter", + "florin", + "guenter", + "nurettin", + "horst_g\u00fcnter", + "vitor", + "alessio", + "dietmar", + "harm", + "philipp", + "beda", + "bodo", + "janis", + "kornelius", + "lorik", + "wolf", + "vincent", + "carmelo", + "fredo", + "jean", + "hans_willi", + "lorenzo", + "gereon", + "slobodan", + "gerard", + "tommaso", + "yanick", + "ekkehart", + "holm", + "udo", + "renato", + "gil", + "jean_claude", + "gert", + "siegward", + "theo", + "tilmann", + "marius", + "philippe", + "gisbert", + "ljubisa", + "hinrich", + "hamza", + "yannis", + "fitim", + "friedhelm", + "alejandro", + "alen", + "jobst", + "mile", + "raphael", + "frithjof", + "adriano", + "saban", + "severin", + "alfred", + "jos\u00e9", + "falk", + "karl_josef", + "rudi", + "ullrich", + "ada", + "hans_werner", + "ralf_dieter", + "marijan", + "pablo", + "benedikt", + "can", + "gernot", + "lian", + "jo\u00e3o", + "reto", + "claude", + "rico", + "vinzenz", + "j\u00fcrg", + "ren\u00e9", + "heinz_wilhelm", + "lucio", + "nicola", + "muhamed", + "klaus_d", + "kenan", + "siegfried", + "marc", + "salih", + "hans_friedrich", + "falko", + "heinz", + "mats", + "remzi", + "georg", + "mathis", + "levi", + "bert", + "petar", + "cosimo", + "friedo", + "toni", + "winfried", + "leszek", + "flurin", + "klaus_j\u00fcrgen", + "fabian", + "marcel", + "alex", + "emin", + "hans_wilhelm", + "kerim", + "oliver", + "john", + "j\u00f6rg", + "apostolos", + "marlon", + "hanns", + "tillmann", + "gero", + "julian", + "joshua", + "carmine", + "federico", + "aron", + "heinz_georg", + "hansjoachim", + "augustin", + "wieslaw", + "heinz_willi", + "felice", + "hans_gerhard", + "hanspeter", + "siegmar", + "bernd", + "lu\u00eds", + "abdul", + "finn", + "pietro", + "franz_josef", + "sasa", + "vito", + "eckhart", + "viktor", + "gerwin", + "r\u00e9my", + "sebastian", + "karlheinz", + "ardian", + "benno", + "jost", + "gunnar", + "jaime", + "liam", + "angel", + "rudolf", + "mirsad", + "miro", + "egzon", + "gianfranco", + "rodrigo", + "g\u00fcnter", + "tarik", + "xavier", + "jerzy", + "tomas", + "marcin", + "hanni", + "jacques", + "driton", + "wulf", + "p\u00e9ter", + "mehdi", + "diedrich", + "michael", + "eberhardt", + "rodolfo", + "friedrich", + "traugott", + "karl_heinz", + "anthony", + "luigi", + "lambert", + "j\u00fcrgen", + "damian", + "s\u00f6ren", + "wolfgang", + "ercan", + "vassilios", + "lio", + "patric", + "hans_j\u00f6rg", + "constantin", + "bojan", + "ludwig", + "bertram", + "albrecht", + "pero", + "gazmend", + "andreas", + "reza", + "ferdi", + "gerardo", + "admir", + "endrit", + "mihajlo", + "harun", + "ernesto", + "hussein", + "andree", + "enrique", + "eckard", + "recep", + "rupert", + "fr\u00e9d\u00e9ric", + "onur", + "henner", + "patrice", + "giulio", + "arndt", + "goran", + "christophe", + "silas", + "rayan", + "dagobert", + "nemanja", + "rene", + "aurel", + "nevin", + "steven", + "ledion", + "hans_dieter", + "nikolaj", + "ruedi", + "miroslav", + "kasimir", + "lirim", + "balz", + "josua", + "nuno", + "rolf_peter", + "mergim", + "nikolaos", + "dietrich", + "sandor", + "cyrill", + "siegmund", + "sean", + "tilman", + "erik", + "ahmed", + "reimund", + "morris", + "ekkehard", + "ajan", + "samuele", + "joaquim", + "helmut", + "giuseppe", + "l\u00e1szl\u00f3", + "artur", + "theodor", + "sascha", + "emir", + "danilo", + "j\u00e9r\u00f4me", + "hakan", + "wolf_r\u00fcdiger", + "rolf_dieter", + "khaled", + "thilo", + "zenon", + "ignatz", + "maik", + "csaba", + "niclas", + "zdravko", + "filipe", + "maurizio", + "jeffrey", + "dalibor", + "ralph", + "kristian", + "magnus", + "dominique", + "nicolaus", + "thiago", + "gianluca", + "othmar", + "sergei", + "yannic", + "guiseppe", + "hans_g\u00fcnter", + "swen", + "elias", + "celal", + "vadim", + "jean_marc", + "hans_michael", + "erhard", + "carsten", + "aldin", + "carl_heinz", + "hans_karl", + "besnik", + "urban", + "christoph", + "gundolf", + "jaron", + "friedrich_wilhelm", + "marcus", + "roderich", + "reimar", + "william", + "oswald", + "gotthilf", + "karl_j\u00fcrgen", + "klaus_michael", + "marcos", + "agron", + "mirco", + "zoltan", + "enno", + "renzo", + "hans_dietrich", + "andr\u00e9", + "ernst", + "samuel", + "muhammad", + "rexhep", + "august", + "yvan", + "hansueli", + "nikolas", + "kujtim", + "arnfried", + "ortwin", + "tahir", + "valerij", + "hendrik", + "gilbert", + "j\u00f6rgen", + "dylan", + "siro", + "edmond", + "francis", + "albert", + "antonius", + "bruno", + "valerio", + "milorad", + "petr", + "erhardt", + "maxim", + "karlfried", + "volkhard", + "klaus_werner", + "luis", + "yves", + "angelo", + "niels", + "senol", + "ismael", + "hartmut", + "edwin", + "eugenio", + "helmuth", + "alfons", + "blerim", + "abel", + "franjo", + "zsolt", + "hans_d", + "raik", + "heinz_werner", + "burckhard", + "vlado", + "lorenz", + "ismail", + "imre", + "gerolf", + "alexej", + "jan_peter", + "jesus", + "edon", + "ramiz", + "james", + "raffaele", + "edmund", + "kastriot", + "vitus", + "haris", + "bernard", + "hans_adolf", + "silvano", + "yann", + "andrea", + "burak", + "jan", + "klaas", + "til", + "juergen", + "ehrhard", + "alwin", + "gani", + "yannik", + "sebastiano", + "naser", + "raoul", + "karim", + "avni", + "lo\u00efc", + "zlatko", + "jens_peter", + "sami", + "nico", + "mato", + "emilio", + "andrin", + "simon", + "tristan", + "mischa", + "hellmuth", + "klemens", + "andre", + "mohammed", + "michail", + "fredi", + "birger", + "jeremias", + "gzim", + "wolf_dieter", + "erdal", + "olaf", + "herwig", + "henryk", + "orlando", + "idriz", + "hans_rudolf", + "siegbert", + "timon", + "enver", + "janus", + "christos", + "dusan", + "matthew", + "hans_wolfgang", + "franz", + "volkmar", + "peer", + "willibert", + "francisco", + "stephan", + "nelio", + "noah", + "heribert", + "bryan", + "daniel", + "marjan", + "heino", + "hagen", + "miodrag", + "bajram", + "alf", + "diar", + "miguel", + "knut", + "ladislaus", + "gunter", + "gottfried", + "wieland", + "pedro", + "hardy", + "rapha\u00ebl", + "jules", + "miran", + "hans", + "herbert", + "dominik", + "ernst_dieter", + "riccardo", + "egon", + "leopold", + "julius", + "jiri", + "amar", + "axel", + "mario", + "roland", + "florent", + "ulrich", + "stavros", + "christof", + "mattias", + "zeno", + "reginald", + "berat", + "alexandros", + "claus_dieter", + "wojciech", + "leonardo", + "ilja", + "vincenzo", + "woldemar", + "gustav", + "mijo", + "ernst_august", + "bela", + "korbinian", + "manfred", + "eitel", + "walther", + "nathanael", + "metin", + "richard", + "evangelos", + "hans_joachim", + "alfredo", + "jasin", + "eduard", + "janos", + "lenny", + "fadil", + "reinhold", + "gennaro", + "jeremy", + "ramazan", + "mariusz", + "thomas", + "harry", + "heinz_gerd", + "frieder", + "ivica", + "f\u00e1bio", + "st\u00e9phane", + "danijel", + "no\u00e9", + "milo", + "leano", + "gottlieb", + "leandro", + "sabri", + "aurelio", + "alan", + "guenther", + "tenzin", + "ben", + "rocco", + "jacob", + "igor", + "ottomar", + "yanis", + "sigismund", + "klaus", + "colin", + "gunar", + "damiano", + "zolt\u00e1n", + "marcello", + "johann", + "gerhardt", + "maurice", + "maurus", + "arnd", + "burim", + "willy", + "adis", + "hubert", + "johannes", + "istvan", + "carl", + "clemens", + "rouven", + "hajo", + "stanislav", + "hilmar", + "klaus_ulrich", + "lorin", + "edgar", + "darko", + "visar", + "malik", + "diogo", + "gian_luca", + "emil", + "g\u00e9rard", + "bekim", + "franco", + "enea", + "luan", + "rudolph", + "henning", + "zoran", + "lulzim", + "filippo", + "paul_gerhard", + "mahmoud", + "mike", + "alban", + "hans_henning", + "leo", + "matthias", + "paul", + "heiko", + "hans_albert", + "karl_august", + "said", + "boban", + "jeton", + "armin", + "torben", + "nazmi", + "eric", + "eckehard", + "jayden", + "marek", + "norman", + "antonios", + "sieghard", + "mirko", + "gino", + "mateo", + "karl_peter", + "kaan", + "janic", + "pascal", + "wigbert", + "s\u00fckr\u00fc", + "veli", + "michel", + "florim", + "felipe", + "amin", + "neil", + "dominic", + "riza", + "afrim", + "raymund", + "nuri", + "victor", + "ilija", + "lukas", + "bartholom\u00e4us", + "g\u00fcnther", + "oswin", + "devin", + "\u00f6mer", + "burkhardt", + "necati", + "janick", + "jordan", + "lino", + "flamur", + "matheo", + "maksim", + "isa", + "jannis", + "alain", + "nikolaus", + "uwe", + "serge", + "cengiz", + "curdin", + "maxime", + "kemal", + "klaus_dieter", + "fridolin", + "sergio", + "dieter", + "gotthold", + "marin", + "antonino", + "karsten", + "nik", + "kay_uwe", + "enrico", + "kristijan", + "marcelo", + "alessandro", + "dino", + "ryszard", + "jann", + "hansgeorg", + "ulf", + "karl_werner", + "vitali", + "ernest", + "edin", + "helge", + "fred", + "anton", + "jorge", + "anatoli", + "daniele", + "corsin", + "lean", + "detlef", + "bernt", + "simone", + "rosario", + "till", + "steffen", + "jens_uwe", + "enes", + "kaspar", + "besim", + "gian", + "dirk", + "kevin", + "anto", + "wladimir", + "mael", + "martin", + "hans_christian", + "heinfried", + "dion", + "edward", + "mert", + "ahmad", + "janko", + "labinot", + "l\u00e9on", + "lukasz", + "matth\u00e4us", + "elia", + "robin", + "harald", + "fabio", + "bilal", + "baris", + "lucien", + "willfried", + "mohamed", + "osman", + "elio", + "jamie", + "wolfhard", + "dursun", + "murat", + "melvin", + "andres", + "dan", + "wilfried", + "randolf", + "heimo", + "mesut", + "jean_luc", + "bernward", + "charles", + "gerold", + "frank_peter", + "cristian", + "thadd\u00e4us", + "joerg", + "arbnor", + "jakub", + "emanuel", + "muhamet", + "anastasios", + "hartwig", + "hans_josef", + "ingo", + "cem", + "muzaffer", + "giacomo", + "torsten", + "orhan", + "horst_dieter", + "semir", + "peter", + "nebojsa", + "ardit", + "karl_friedrich", + "silvan", + "tibor", + "g\u00f6tz", + "eugen", + "willibald", + "berthold", + "marian", + "tobias", + "serkan", + "ante", + "luke", + "predrag", + "heinrich", + "urs", + "fredy", + "michele", + "uli", + "noe", + "nael", + "erion", + "muhammed", + "karl_hermann", + "heinz_josef", + "konstantin", + "zeki", + "baptist", + "gon\u00e7alo", + "ibrahim", + "ken", + "walfried", + "leif", + "roy", + "ahmet", + "veit", + "jon", + "hans_hinrich", + "gabriele", + "vinko", + "abraham", + "sepp", + "florentin", + "cyril", + "van", + "curt", + "wenzel", + "meik", + "abram", + "sedat", + "arnulf", + "holger", + "franz_xaver", + "nelson", + "teodor", + "gregor", + "emmerich", + "giovanni", + "hans_otto", + "theophil", + "gaetano", + "laszlo", + "saverio", + "milan", + "krzysztof", + "sacha", + "jurij", + "francesco", + "diego", + "alfonso", + "kai", + "dave", + "tom", + "arian", + "anatolij", + "ludger", + "dierk", + "burghard", + "massimo", + "damjan", + "salvatore", + "fatmir", + "jochen", + "aleksander", + "athanasios", + "senad", + "ewald", + "georgios", + "steve", + "neo", + "friedhold", + "didier", + "bogdan", + "oscar", + "roman", + "patrik", + "wolf_dietrich", + "hans_georg", + "walter", + "antoine", + "karl_hans", + "dimitrios", + "alexis", + "kuno", + "hans_hermann", + "jacek", + "georges", + "mark", + "joseph", + "emilian", + "hasso", + "wolfram", + "berend", + "guy", + "christian", + "jetmir", + "arne", + "beni", + "reimer", + "konstantinos", + "tam\u00e1s", + "johan", + "otto", + "heinz_dieter", + "fabrice", + "marco", + "mustafa", + "lionel", + "immo", + "adnan", + "erwin", + "rolf", + "ignaz", + "hans_g\u00fcnther", + "bertold", + "jovan", + "timm", + "javier", + "witold", + "artan", + "remo", + "anatol", + "heinz_otto", + "istv\u00e1n", + "hans_eberhard", + "rino", + "gilles", + "brian", + "mladen", + "darius", + "aloys", + "dragan", + "giuliano", + "omar", + "luc", + "laurenz", + "frederik", + "chris", + "tiago", + "drilon", + "noa", + "frank_michael", + "patrick", + "hans_erich", + "bernd_dieter", + "iwan", + "vladimir", + "claas", + "karl", + "shaban", + "romuald", + "kenneth", + "conrad", + "s\u00e9bastien", + "flavio", + "karl_otto", + "livio", + "fedor", + "diethard", + "lennard", + "arnold", + "skender", + "jaroslaw", + "balthasar", + "lucas", + "burkhard", + "gion", + "hans_herbert", + "ernst_otto", + "benedict", + "halil", + "alexander", + "linus", + "hans_martin", + "ottfried", + "heinz_walter", + "pavel", + "sahin", + "domenico", + "mentor", + "donat", + "drago", + "egbert", + "adem", + "stephen", + "ant\u00f3nio", + "theodoros", + "bashkim", + "sigurd", + "heiner", + "valentin", + "h\u00fcseyin", + "yusuf", + "sven", + "hermann_josef", + "reinhart", + "liridon", + "ramon", + "ismet", + "naim", + "ryan", + "wendelin", + "hans_peter", + "joel", + "ingolf", + "ronny", + "thies", + "pirmin", + "lazar", + "dimitri", + "klaus_peter", + "joris", + "erkan", + "tim", + "nicolai", + "enzo", + "jose", + "marko", + "sandro", + "yannick", + "tilo", + "joachim", + "frederic", + "micha", + "miroslaw", + "adrian", + "david", + "hans_ludwig", + "boris", + "arthur", + "hubertus", + "jean_pierre", + "ioannis", + "massimiliano", + "gebhard", + "calogero", + "tiziano", + "lias", + "jonas", + "tomasz", + "janosch", + "hans_helmut", + "arno", + "fernando", + "detlev", + "jari", + "ferdinand", + "gottlob", + "timothy", + "leonard", + "bernfried", + "utz", + "c\u00e9dric", + "levin", + "matej", + "rafael", + "helfried", + "grzegorz", + "jens", + "leon", + "elmar", + "volker", + "olivier", + "s\u00e9rgio", + "tomislav", + "hansj\u00f6rg", + "anes", + "nando", + "antonio", + "pawel", + "max", + "maximilian", + "heinz_g\u00fcnther", + "arsim", + "hansruedi", + "eggert", + "gabriel", + "jakob", + "kim", + "kurt", + "alexandar", + "sergej", + "manuel", + "klaus_g\u00fcnter", + "robby", + "xaver", + "friedbert", + "kamil", + "giorgio", + "cornel", + "jozef", + "arda", + "janik", + "peter_michael", + "edelbert", + "ramadan", + "nils", + "alexandre", + "piotr", + "meinhard", + "konrad", + "gerald", + "jona", + "eduardo", + "hannes", + "tadeusz", + "michal", + "phillip", + "henrik", + "sinisa", + "ronald", + "irfan", + "hans_theo", + "muharrem", + "ricardo", + "fatih", + "enis", + "ralf_peter", + "willi", + "isidor", + "arif", + "berndt", + "ralf", + "matteo", + "stjepan", + "niklaus", + "simeon", + "j\u00f6rn", + "evan", + "andrej", + "cristiano", + "nino", + "alexei", + "lutz", + "friedrich_karl", + "cetin", + "timo", + "gregory" + ], + "PREFIX_FEMALE": [ + "ing", + "dipl._ing", + "frau", + "dr", + "univ.prof", + "prof" + ], + "PREFIX_MALE": [ + "ing", + "dipl._ing", + "herr", + "dr", + "univ.prof", + "prof" + ], + "FIRST_NAME": [ + "mareen", + "sigmund", + "heidelinde", + "justin", + "fynn", + "pasquale", + "babette", + "bayram", + "aysel", + "meret", + "ivo", + "kata", + "k\u00e4thi", + "zoe", + "luisa", + "hans_walter", + "claudine", + "raffaela", + "katerina", + "biagio", + "grete", + "slavko", + "roswitha", + "niko", + "sevim", + "nicolas", + "andrzej", + "cheyenne", + "emmanuel", + "gotthard", + "erol", + "dittmar", + "ueli", + "melisa", + "ga\u00eblle", + "edelgard", + "helene", + "birthe", + "aldo", + "song\u00fcl", + "anne", + "karine", + "florian", + "ilhan", + "nathan", + "henry", + "eva", + "yanik", + "wendy", + "evi", + "jasmina", + "emilija", + "line", + "ditmar", + "adelbert", + "elvis", + "alexia", + "fisnik", + "almir", + "iwona", + "cassandra", + "marie_th\u00e9r\u00e8se", + "annelore", + "knud", + "selma", + "laure", + "s\u00f6nke", + "marinette", + "annabella", + "annika", + "britt", + "juna", + "valerie", + "claus_peter", + "luciana", + "rosa_maria", + "mohammad", + "claudius", + "elsbeth", + "sigfried", + "gladys", + "anne_katrin", + "selina", + "slavica", + "achim", + "anne_laure", + "debora", + "gerhart", + "petros", + "elisabet", + "raul", + "walburga", + "german", + "jonah", + "katharine", + "ottokar", + "jolanthe", + "ingbert", + "assunta", + "adam", + "andy", + "burkard", + "hulda", + "domenic", + "omer", + "denny", + "henni", + "sylvio", + "anni", + "inna", + "hasan", + "hansj\u00fcrg", + "werner", + "reinhard", + "therese", + "alberto", + "ingried", + "alice", + "annalena", + "donato", + "hans_ulrich", + "karla", + "freia", + "s\u00e9verine", + "patr\u00edcia", + "karl_heinrich", + "stefan", + "sinaida", + "berit", + "jasper", + "norah", + "flavia", + "matti", + "gabor", + "domingos", + "frank", + "melchior", + "sibylla", + "karolina", + "suse", + "michaele", + "sam", + "betti", + "madeleine", + "fatime", + "celine", + "rose_marie", + "gunther", + "sigmar", + "heidelore", + "eberhard", + "natalie", + "luzius", + "moreno", + "albertine", + "folker", + "abdullah", + "lieschen", + "mika", + "rui", + "vittorio", + "kirstin", + "renate", + "calvin", + "jo\u00ebl", + "hans_rainer", + "reinald", + "amalie", + "c\u00e1tia", + "zdenka", + "milka", + "lili", + "giovanna", + "annerose", + "geza", + "olga", + "dennis", + "salome", + "hansj\u00fcrgen", + "caspar", + "harro", + "safet", + "carin", + "jonathan", + "hassan", + "kazim", + "heinz_joachim", + "danielle", + "carlo", + "emina", + "zeljko", + "raissa", + "traute", + "ensar", + "davide", + "ricarda", + "hans_detlef", + "rosalie", + "donald", + "lilian", + "bernhard", + "norina", + "hans_uwe", + "augusto", + "aleksandar", + "romana", + "thorben", + "ilias", + "umut", + "elisa", + "svea", + "josip", + "elyas", + "d\u00f6rthe", + "claudio", + "beatrix", + "ludmila", + "noel", + "cl\u00e4re", + "ennio", + "rosalba", + "tassilo", + "helmtrud", + "catherine", + "laura", + "miroslawa", + "emre", + "cristina", + "horst", + "ron", + "layla", + "george", + "eckhardt", + "eckhard", + "ivano", + "gerdi", + "rabea", + "ferenc", + "louis", + "eckart", + "mechthilde", + "engelbert", + "magarete", + "ilir", + "violetta", + "nika", + "theda", + "aleksej", + "elo\u00efse", + "sinan", + "lana", + "georgette", + "vivian", + "genoveva", + "monika", + "abbas", + "basil", + "bj\u00f6rn", + "magdalene", + "ingeburg", + "mireille", + "deniz", + "henri", + "mariana", + "ivonne", + "ilona", + "paolo", + "freddy", + "ekrem", + "eda", + "andjelina", + "selim", + "hans_gerd", + "antonie", + "guntram", + "katarzyna", + "ali", + "hans_bernd", + "tony", + "luciano", + "sarina", + "damaris", + "juri", + "walentina", + "kushtrim", + "mahmut", + "luitgard", + "sylviane", + "mohamad", + "resi", + "oda", + "pierre", + "flurina", + "sina", + "morena", + "loretta", + "ylenia", + "luka", + "halina", + "valentino", + "uschi", + "heini", + "dina", + "ronja", + "mauro", + "waldemar", + "mirjam", + "katharina", + "beat", + "minna", + "raimund", + "samira", + "lotti", + "violette", + "rinor", + "dorian", + "gerd", + "nikola", + "folkert", + "seline", + "soraya", + "magdalena", + "fran\u00e7ois", + "filip", + "laurent", + "raffael", + "trudi", + "frida", + "malte", + "tom\u00e1s", + "aur\u00e9lie", + "hanno", + "luzie", + "norbert", + "valeska", + "julien", + "annie", + "karoline", + "irmtraud", + "altin", + "leyla", + "cornelius", + "stanislaus", + "eugenie", + "nicholas", + "silvester", + "bujar", + "no\u00ebmi", + "lucia", + "ortrud", + "samir", + "ardita", + "silvio", + "gertrud", + "lennart", + "thoralf", + "toralf", + "mattia", + "eileen", + "no\u00ebl", + "mehmet", + "janusz", + "andjela", + "melek", + "lise", + "andrey", + "monica", + "mathieu", + "roger", + "maryse", + "cemil", + "czeslaw", + "rigo", + "leart", + "alois", + "sara", + "hans_j", + "attila", + "evelin", + "guido", + "branislav", + "marino", + "uta", + "aynur", + "felix", + "gisela", + "c\u00e9line", + "jaroslav", + "gilda", + "luise", + "senta", + "pius", + "roberto", + "antonietta", + "josef", + "huguette", + "cedric", + "fatmire", + "dariusz", + "vilma", + "nisa", + "mandy", + "maurin", + "zoey", + "tabea", + "michela", + "jasmin", + "wera", + "inge", + "ian", + "slavisa", + "anna", + "hans_h", + "jason", + "betina", + "reinhardt", + "hugo", + "kunibert", + "natan", + "raymonde", + "gianni", + "lene", + "asta", + "karl_ernst", + "frederike", + "claus", + "adele", + "sadik", + "franz_peter", + "stefano", + "denis", + "etienne", + "lya", + "paulo", + "agim", + "marlyse", + "vania", + "ewa", + "lars", + "nathalie", + "jack", + "esra", + "maria_theresia", + "merlin", + "hans_heinrich", + "hanny", + "lothar", + "emmy", + "heide_marie", + "celina", + "malin", + "jusuf", + "bianca", + "natalja", + "lioba", + "ursula", + "ellinor", + "ester", + "maya", + "eren", + "yilmaz", + "jenny", + "tino", + "gordon", + "cynthia", + "johanna", + "liliana", + "philip", + "armend", + "britta", + "marcella", + "marie_louise", + "oskar", + "\u00f6zlem", + "olav", + "thorsten", + "diether", + "justus", + "cord", + "susann", + "ema", + "rosi", + "claire", + "herrmann", + "adolf", + "henriette", + "natalia", + "ansgar", + "anett", + "theresia", + "marie_luise", + "tamara", + "r\u00fcdiger", + "besart", + "quentin", + "mathias", + "faton", + "irmtraut", + "annegret", + "anka", + "harold", + "slawomir", + "ehrenfried", + "astrit", + "edit", + "hans_jochen", + "margaux", + "karl_ludwig", + "marie_laure", + "kalina", + "nikolai", + "annelies", + "radmila", + "milos", + "margita", + "lilo", + "sybilla", + "aaron", + "ivan", + "kay", + "sheila", + "rainer", + "andri", + "joana", + "nancy", + "ekaterina", + "karl_georg", + "giuliana", + "monique", + "sylvie", + "damien", + "nevio", + "audrey", + "henrike", + "danica", + "ma\u00ebl", + "saskia", + "hermann", + "joao", + "amir", + "arnim", + "santiago", + "kian", + "fabrizio", + "otmar", + "adelinde", + "diethelm", + "danuta", + "zbigniew", + "piero", + "andrew", + "s\u00fcleyman", + "anselm", + "mihaela", + "lotta", + "marliese", + "valeri", + "alena", + "sibylle", + "helmar", + "annamaria", + "nick", + "maryam", + "meike", + "larissa", + "katherina", + "marie", + "reiner", + "felicia", + "h\u00fclya", + "meinolf", + "melinda", + "margaritha", + "erdogan", + "kristina", + "bekir", + "tanya", + "stilla", + "irmela", + "wanda", + "alvaro", + "irena", + "aribert", + "kai_uwe", + "marie_theres", + "nicole", + "naomi", + "dario", + "arlind", + "almut", + "niklas", + "armando", + "grit", + "loris", + "loni", + "jannik", + "enya", + "friedemann", + "g\u00e9raldine", + "marten", + "francine", + "rochus", + "giancarlo", + "leonid", + "rosl", + "veronique", + "sena", + "carlos", + "cinzia", + "gertraut", + "constanze", + "linnea", + "lucienne", + "ilaria", + "herlinde", + "hans_j\u00fcrgen", + "lore", + "christl", + "geert", + "stanislaw", + "ruben", + "karl_wilhelm", + "heidi", + "anneke", + "h._dieter", + "albin", + "fritz", + "aziz", + "ingelore", + "moritz", + "lena", + "marcela", + "emanuela", + "paulette", + "nora", + "dogan", + "dorina", + "yasin", + "eleni", + "leander", + "andreia", + "ang\u00e9lique", + "meinrad", + "marielle", + "dejan", + "heinz_g\u00fcnter", + "markus", + "nenad", + "aleksandr", + "martine", + "hedy", + "sylvester", + "ole", + "mariette", + "hilda", + "teresa", + "ursel", + "elisabete", + "gerhard", + "paul_heinz", + "stefania", + "theobald", + "hartmuth", + "gerfried", + "marie_sophie", + "trude", + "annelene", + "oc\u00e9ane", + "leandra", + "xenia", + "reni", + "umberto", + "shpresa", + "edda", + "musa", + "cemal", + "julio", + "juan", + "imer", + "lidwina", + "j\u00f6rg_peter", + "karl_dieter", + "marie_therese", + "jerome", + "heinz_j\u00fcrgen", + "heinz_peter", + "baldur", + "\u00e4nne", + "wilhelm", + "otfried", + "carmela", + "cindy", + "telse", + "yvonne", + "faruk", + "gudula", + "birgitta", + "damir", + "robert", + "engin", + "g\u00f6khan", + "mikhail", + "jochem", + "romeo", + "zehra", + "dean", + "s\u00f3nia", + "arben", + "bastian", + "harri", + "madlen", + "giada", + "danny", + "loredana", + "christopher", + "marvin", + "laurin", + "andrei", + "edith", + "ines", + "margarethe", + "agathe", + "erich", + "herta", + "raymond", + "adeline", + "volkan", + "solveig", + "ottmar", + "bettina", + "stephanie", + "polina", + "gertraud", + "luca", + "thierry", + "mila", + "kilian", + "priska", + "hannah", + "marine", + "adalbert", + "anny", + "leonhard", + "benjamin", + "antonia", + "arzu", + "branko", + "hellmut", + "rinaldo", + "dardan", + "ingmar", + "kreszentia", + "emanuele", + "romano", + "valon", + "horst_peter", + "florin", + "guenter", + "nurettin", + "fran\u00e7oise", + "yolande", + "ylvie", + "dorothee", + "horst_g\u00fcnter", + "vitor", + "lynn", + "yael", + "alessio", + "hertha", + "elisabetha", + "dietmar", + "catharina", + "harm", + "lea_sophie", + "jadwiga", + "sandra", + "philipp", + "hildburg", + "beda", + "philomena", + "jara", + "bodo", + "inka", + "janis", + "annelise", + "kornelius", + "christelle", + "monja", + "lorik", + "wolf", + "desir\u00e9e", + "vincent", + "silvana", + "carmelo", + "kriemhild", + "moira", + "gaia", + "jean", + "hans_willi", + "fredo", + "leonor", + "lorenzo", + "margitta", + "bluette", + "virginia", + "sanja", + "gereon", + "elvira", + "slobodan", + "gerard", + "liesel", + "tommaso", + "yanick", + "ekkehart", + "albulena", + "marina", + "holm", + "noelia", + "friedl", + "udo", + "cosima", + "renato", + "gil", + "leonie", + "jean_claude", + "gert", + "siegward", + "adolfine", + "theo", + "tilmann", + "shania", + "catarina", + "marius", + "mina", + "siegrun", + "yolanda", + "melina", + "philippe", + "gisbert", + "ljubisa", + "juliana", + "leoni", + "hinrich", + "hamza", + "yannis", + "rosaria", + "valentine", + "michelle", + "luigia", + "fitim", + "friedhelm", + "daisy", + "alejandro", + "alen", + "erika", + "thi", + "jobst", + "mile", + "raphael", + "frithjof", + "vjollca", + "v\u00e9ronique", + "gloria", + "adriano", + "saban", + "severin", + "alfred", + "maritta", + "lidija", + "fatma", + "concetta", + "jos\u00e9", + "falk", + "karl_josef", + "rudi", + "donatella", + "babett", + "ullrich", + "ada", + "kiara", + "elda", + "daria", + "hans_werner", + "oxana", + "ralf_dieter", + "marijan", + "pablo", + "benedikt", + "can", + "gernot", + "lian", + "kl\u00e4re", + "jo\u00e3o", + "reto", + "jacqueline", + "claude", + "rico", + "friederike", + "edona", + "sigrun", + "snezana", + "marie_jos\u00e9", + "mareike", + "ramona", + "sandrine", + "vinzenz", + "j\u00fcrg", + "marion", + "bernhardine", + "solange", + "zeynep", + "kathi", + "mirja", + "ren\u00e9", + "cordula", + "krystyna", + "heinz_wilhelm", + "lucio", + "gabi", + "susan", + "nicola", + "muhamed", + "astrid", + "klaus_d", + "kenan", + "frauke", + "siegfried", + "marc", + "carina", + "salih", + "sonia", + "medina", + "no\u00eblle", + "hans_friedrich", + "peggy", + "falko", + "heinz", + "annina", + "mats", + "remzi", + "georg", + "stella", + "mathis", + "alexandra", + "miranda", + "swetlana", + "levi", + "romina", + "simona", + "bert", + "petar", + "liselotte", + "cosimo", + "yasmine", + "mathilde", + "daniela", + "friedo", + "shqipe", + "toni", + "winfried", + "germaine", + "annabell", + "martina", + "leszek", + "flurin", + "klaus_j\u00fcrgen", + "fabian", + "marcel", + "alex", + "emin", + "hans_wilhelm", + "lilly", + "suzana", + "kerim", + "teuta", + "john", + "noemi", + "oliver", + "j\u00f6rg", + "apostolos", + "marlon", + "hanns", + "annalisa", + "tillmann", + "ute", + "gero", + "julian", + "joshua", + "alix", + "gerta", + "carmine", + "federico", + "hilma", + "norma", + "aron", + "heinz_georg", + "katja", + "irmhild", + "hansjoachim", + "kunigunda", + "ingetraut", + "pierrette", + "augustin", + "amalia", + "ana\u00efs", + "wieslaw", + "heinz_willi", + "anika", + "felice", + "beate", + "hans_gerhard", + "hanspeter", + "siegmar", + "sylvana", + "jasmine", + "fernanda", + "bernd", + "zofia", + "mariele", + "lu\u00eds", + "sophia", + "abdul", + "amina", + "deborah", + "finn", + "gabriela", + "pietro", + "leona", + "tania", + "elisabeth", + "wilhelmine", + "franz_josef", + "sasa", + "viviana", + "annedore", + "lidia", + "jocelyne", + "jo", + "gislinde", + "vito", + "eckhart", + "gaby", + "floriane", + "viktor", + "margherita", + "elena", + "gerwin", + "giesela", + "marilena", + "raphaela", + "sebastian", + "r\u00e9my", + "karlheinz", + "ardian", + "margaret", + "benno", + "annekatrin", + "jost", + "mariechen", + "gunnar", + "jaime", + "sabine", + "liam", + "angel", + "rudolf", + "marianna", + "steffi", + "mirsad", + "lorena", + "alyssa", + "miro", + "egzon", + "gianfranco", + "sibel", + "federica", + "rodrigo", + "g\u00fcnter", + "julijana", + "tarik", + "ariana", + "anne_lise", + "xavier", + "jerzy", + "tomas", + "josiane", + "marlen", + "marcin", + "no\u00e9mie", + "hanni", + "k\u00e4te", + "jacques", + "driton", + "wulf", + "tiffany", + "am\u00e9lie", + "p\u00e9ter", + "branka", + "mehdi", + "josefina", + "diedrich", + "annegrete", + "ulla", + "nadia", + "bukurije", + "aneta", + "b\u00e4rbel", + "michael", + "eberhardt", + "antonina", + "irmengard", + "else", + "rodolfo", + "friedrich", + "annemarie", + "tiziana", + "traugott", + "kreszenz", + "mareile", + "juliane", + "karl_heinz", + "anthony", + "sahra", + "edina", + "mirella", + "nadin", + "kelly", + "luigi", + "lambert", + "siegried", + "j\u00fcrgen", + "olivia", + "hildegunde", + "damian", + "marie_christine", + "s\u00f6ren", + "ayse", + "sibille", + "katalin", + "wolfgang", + "ercan", + "vassilios", + "kirsten", + "lio", + "rosemarie", + "virginie", + "patric", + "alessia", + "hans_j\u00f6rg", + "constantin", + "bojan", + "ludwig", + "verena", + "bertram", + "bruna", + "c\u00e9cile", + "albrecht", + "pero", + "gazmend", + "andreas", + "imelda", + "ivanka", + "reza", + "ferdi", + "gerardo", + "admir", + "endrit", + "annamarie", + "mihajlo", + "harun", + "janette", + "ernesto", + "sybille", + "hussein", + "nelli", + "micheline", + "amelie", + "hanna", + "andree", + "rahel", + "ruth", + "in\u00eas", + "enrique", + "eckard", + "swantje", + "philippa", + "recep", + "rupert", + "fr\u00e9d\u00e9ric", + "alisha", + "onur", + "ludivine", + "annalise", + "helen", + "eleonora", + "henner", + "patrice", + "kathleen", + "giulio", + "diane", + "arndt", + "goran", + "ganimete", + "christophe", + "silas", + "silvia", + "rayan", + "dagobert", + "hava", + "antje", + "nemanja", + "sarah", + "mechthild", + "theresa", + "malika", + "rene", + "edeltraut", + "aurel", + "sigrid", + "lindita", + "nevin", + "natascha", + "steven", + "ledion", + "manon", + "hans_dieter", + "nikolaj", + "ruedi", + "miroslav", + "camille", + "kasimir", + "florentine", + "marl\u00e8ne", + "lirim", + "balz", + "josua", + "nuno", + "rolf_peter", + "edeltraud", + "emma", + "eveline", + "eva_maria", + "mergim", + "nikolaos", + "dietrich", + "g\u00f6n\u00fcl", + "traudel", + "nadine", + "sandor", + "cyrill", + "nevenka", + "cristiana", + "siegmund", + "sean", + "tilman", + "margarita", + "kaltrina", + "erik", + "ahmed", + "maike", + "fabiola", + "herma", + "reimund", + "emilia", + "luana", + "serpil", + "morris", + "gundel", + "martha", + "ekkehard", + "brit", + "ildiko", + "ajan", + "hanne_lore", + "rafaela", + "samuele", + "irmgard", + "emely", + "cilli", + "gretel", + "joaquim", + "stefanie", + "helmut", + "giuseppe", + "l\u00e1szl\u00f3", + "artur", + "elma", + "theodor", + "sascha", + "emir", + "magali", + "danilo", + "j\u00e9r\u00f4me", + "annita", + "hakan", + "marika", + "meta", + "wolf_r\u00fcdiger", + "paulina", + "rolf_dieter", + "emine", + "khaled", + "lisa_marie", + "aline", + "thilo", + "zenon", + "ignatz", + "carlotta", + "pia", + "teodora", + "csaba", + "sofie", + "alison", + "maik", + "kornelia", + "tatjana", + "niclas", + "wilfriede", + "filiz", + "zdravko", + "filipe", + "semra", + "maurizio", + "jeffrey", + "dalibor", + "eliza", + "ralph", + "kristian", + "magnus", + "ir\u00e8ne", + "dominique", + "nicolaus", + "thiago", + "marjorie", + "ingeborg", + "timea", + "jeannine", + "katrin", + "gianluca", + "susanna", + "hiltraud", + "othmar", + "leticia", + "rose", + "sergei", + "yannic", + "guiseppe", + "fabiana", + "hans_g\u00fcnter", + "swen", + "elias", + "brigitte", + "celal", + "vadim", + "genevi\u00e8ve", + "jean_marc", + "lilija", + "hans_michael", + "kunigunde", + "roberta", + "krista", + "erhard", + "hilde", + "carsten", + "ljudmila", + "agnes", + "marieluise", + "eva_marie", + "donata", + "aldin", + "carl_heinz", + "hans_karl", + "besnik", + "eline", + "urban", + "hatice", + "isabel", + "h\u00e9l\u00e8ne", + "christoph", + "d\u00f6rte", + "gundolf", + "jaron", + "friedrich_wilhelm", + "marcus", + "alisa", + "roderich", + "reimar", + "william", + "romy", + "oswald", + "gotthilf", + "laureen", + "karl_j\u00fcrgen", + "klaus_michael", + "hedda", + "adrienne", + "marcos", + "agron", + "merita", + "liesbeth", + "mirco", + "zoltan", + "enno", + "luzia", + "jane", + "renzo", + "roswita", + "odette", + "hans_dietrich", + "hana", + "andr\u00e9", + "johanne", + "maja", + "amanda", + "aferdita", + "arlinda", + "melissa", + "ernst", + "samuel", + "muhammad", + "amira", + "rexhep", + "flora", + "ulrike", + "henny", + "harriet", + "august", + "gretchen", + "beata", + "yvan", + "hansueli", + "bernadette", + "nikolas", + "kujtim", + "arnfried", + "ortwin", + "dora", + "anica", + "urte", + "tahir", + "marie_claude", + "valerij", + "aylin", + "pauline", + "hiltrud", + "hendrik", + "gilbert", + "rosita", + "j\u00f6rgen", + "insa", + "karen", + "marie_jeanne", + "dylan", + "romane", + "siro", + "evangelia", + "grazia", + "mirela", + "edmond", + "francis", + "albert", + "antonius", + "bruno", + "beatrice", + "c\u00e9lia", + "valerio", + "anabela", + "irina", + "jutta", + "milorad", + "carole", + "wencke", + "ljubica", + "petr", + "erhardt", + "nikolina", + "silke", + "maxim", + "karlfried", + "volkhard", + "klaus_werner", + "gundula", + "priscilla", + "gioia", + "natasha", + "janet", + "luis", + "esma", + "yves", + "anke", + "angelo", + "inga", + "thea", + "milena", + "niels", + "margot", + "senol", + "birte", + "ismael", + "hartmut", + "leila", + "magret", + "edwin", + "eugenio", + "maria", + "lavinia", + "helmuth", + "reinhilde", + "adelheid", + "alfons", + "janna", + "blerim", + "abel", + "dolores", + "chantal", + "ghislaine", + "nad\u00e8ge", + "marissa", + "siena", + "franjo", + "ladina", + "nela", + "zsolt", + "justina", + "hans_d", + "raik", + "heinz_werner", + "ingrid", + "margreth", + "helena", + "natali", + "burckhard", + "anisa", + "vlado", + "lorenz", + "isolde", + "ismail", + "emilie", + "imre", + "aurora", + "gerolf", + "alexej", + "jan_peter", + "josefa", + "nicoletta", + "jesus", + "edon", + "lisbeth", + "james", + "raffaele", + "edmund", + "ramiz", + "fanny", + "charline", + "carine", + "kastriot", + "corina", + "vitus", + "sofija", + "haris", + "bernard", + "petra", + "hans_adolf", + "silvano", + "yann", + "nuran", + "ottilia", + "andrea", + "birgitt", + "yasmin", + "mara", + "burak", + "jan", + "klaas", + "til", + "juergen", + "ehrhard", + "alwin", + "maeva", + "gani", + "yannik", + "zuzana", + "sebastiano", + "naser", + "nina", + "sieglinde", + "klothilde", + "raoul", + "julia", + "traude", + "catia", + "avni", + "karim", + "sanije", + "tanja", + "lo\u00efc", + "caroline", + "zlatko", + "jens_peter", + "sami", + "fabia", + "nico", + "rotraud", + "mato", + "anne_kathrin", + "emilio", + "andrin", + "simon", + "tristan", + "carola", + "leana", + "letizia", + "magda", + "fiona", + "mischa", + "hellmuth", + "irma", + "gesa", + "klemens", + "andre", + "sol\u00e8ne", + "mohammed", + "christiana", + "lotte", + "michail", + "anne_marie", + "annaliese", + "birger", + "fredi", + "jeremias", + "waldtraut", + "azra", + "waltrud", + "gilberte", + "lydie", + "evamaria", + "gzim", + "wolf_dieter", + "anna_lena", + "erdal", + "brita", + "olaf", + "herwig", + "henryk", + "orlando", + "patricia", + "sibilla", + "samantha", + "idriz", + "hans_rudolf", + "mia", + "siegbert", + "timon", + "enver", + "mariella", + "elif", + "janus", + "christos", + "malena", + "clarissa", + "iva", + "katia", + "dusan", + "matthew", + "anastasia", + "belinda", + "anabella", + "hans_wolfgang", + "conny", + "franz", + "mathilda", + "grazyna", + "camilla", + "volkmar", + "cora", + "peer", + "willibert", + "francisco", + "vanesa", + "stephan", + "lea", + "corine", + "nelio", + "noah", + "irmi", + "mirjana", + "vesna", + "egzona", + "tessa", + "heribert", + "t\u00fclay", + "francesca", + "bryan", + "daniel", + "marjan", + "sophie", + "gitta", + "muriel", + "heino", + "hedi", + "mimoza", + "hagen", + "andrina", + "miodrag", + "bajram", + "hermine", + "alf", + "diar", + "marguerite", + "miguel", + "mariangela", + "leonore", + "jennifer", + "manja", + "maude", + "knut", + "gerti", + "theodora", + "ladislaus", + "gunter", + "gottfried", + "wieland", + "kathy", + "pedro", + "hardy", + "lisa", + "lou", + "rapha\u00ebl", + "jules", + "miran", + "jill", + "jana", + "hans", + "herbert", + "wiltrud", + "lily", + "kordula", + "cathleen", + "dominik", + "romaine", + "christin", + "amandine", + "ernst_dieter", + "julie", + "riccardo", + "egon", + "leopold", + "myriam", + "julius", + "jiri", + "amar", + "nadeshda", + "marisa", + "benita", + "axel", + "mario", + "st\u00e9phanie", + "anneliese", + "roland", + "nele", + "morgane", + "florent", + "ella", + "ulrich", + "alwina", + "walli", + "stavros", + "christof", + "viktoria", + "mattias", + "ann_kathrin", + "zeno", + "reginald", + "berat", + "magrit", + "alexandros", + "claus_dieter", + "wojciech", + "leonardo", + "ilja", + "vincenzo", + "woldemar", + "gustav", + "jolanta", + "margret", + "mijo", + "ernst_august", + "melita", + "rita", + "bela", + "korbinian", + "alara", + "manfred", + "eitel", + "ava", + "walther", + "leonora", + "khadija", + "val\u00e9rie", + "edeltrud", + "nathanael", + "metin", + "richard", + "evangelos", + "hans_joachim", + "alfredo", + "vincenza", + "jasin", + "eduard", + "janos", + "delia", + "violeta", + "ursina", + "lenny", + "marianne", + "fadil", + "ivana", + "reinhold", + "bozena", + "gennaro", + "gianna", + "d\u00e9borah", + "jeremy", + "ramazan", + "olena", + "katherine", + "francoise", + "francisca", + "mariusz", + "anja", + "florence", + "salom\u00e9", + "thomas", + "agata", + "dorothe", + "gunda", + "vera", + "elisabetta", + "harry", + "heinz_gerd", + "frieder", + "ivica", + "f\u00e1bio", + "st\u00e9phane", + "danijel", + "no\u00e9", + "milo", + "christina", + "leano", + "gottlieb", + "leandro", + "annabelle", + "sofia", + "aurelio", + "sabri", + "alan", + "myrta", + "centa", + "guenther", + "tenzin", + "ben", + "rocco", + "undine", + "maida", + "jacob", + "leopoldine", + "igor", + "ottomar", + "yanis", + "lissy", + "sigismund", + "fadime", + "bertha", + "nives", + "klaus", + "colin", + "gunar", + "marica", + "damiano", + "natacha", + "hanne", + "zolt\u00e1n", + "marcello", + "dunja", + "johann", + "helma", + "angelika", + "rosmarie", + "gerhardt", + "maurice", + "regula", + "corinna", + "maurus", + "arnd", + "burim", + "anneli", + "wiebke", + "janin", + "willy", + "lucie", + "rana", + "adis", + "wenke", + "hubert", + "johannes", + "istvan", + "jaqueline", + "carl", + "ilka", + "liesa", + "janett", + "clemens", + "rouven", + "hajo", + "elfi", + "georgia", + "viola", + "stanislav", + "hilmar", + "ariane", + "klaus_ulrich", + "lorin", + "sabina", + "edgar", + "darko", + "ren\u00e9e", + "visar", + "b\u00e9atrice", + "lilia", + "agn\u00e8s", + "rosina", + "malik", + "diogo", + "marleen", + "tilly", + "fitore", + "gian_luca", + "gis\u00e8le", + "carla", + "g\u00e9rard", + "emil", + "bekim", + "franco", + "tatiana", + "elwira", + "enea", + "silva", + "rosa", + "filipa", + "angela", + "eugenia", + "lydia", + "luan", + "adelina", + "kyra", + "susi", + "rudolph", + "henning", + "chiara", + "linda", + "zoran", + "carmen", + "ina", + "dagmar", + "meral", + "laurence", + "lulzim", + "nada", + "emmanuelle", + "filippo", + "paul_gerhard", + "mahmoud", + "mike", + "alban", + "hans_henning", + "jos\u00e9phine", + "leo", + "matthias", + "caterina", + "paul", + "heiderose", + "heiko", + "margrit", + "elsa", + "elly", + "hans_albert", + "karl_august", + "said", + "m\u00e9gane", + "zora", + "lucy", + "boban", + "jeton", + "doreen", + "pamela", + "armin", + "torben", + "nazmi", + "eric", + "eckehard", + "jayden", + "agnieszka", + "sanela", + "heidrun", + "marek", + "liane", + "norman", + "antonios", + "friedericke", + "sieghard", + "irene", + "mirko", + "rosalinde", + "waltraud", + "gino", + "joelle", + "hannelore", + "ginette", + "kathrin", + "mateo", + "karl_peter", + "angelique", + "rayana", + "ajna", + "kaan", + "judith", + "iris", + "janic", + "alea", + "dani\u00e8le", + "ortrun", + "veronika", + "pascal", + "wigbert", + "freya", + "s\u00fckr\u00fc", + "heidemarie", + "veli", + "michel", + "florim", + "maddalena", + "tara", + "alma", + "felipe", + "amin", + "neil", + "liridona", + "dominic", + "susana", + "riza", + "afrim", + "domenica", + "raymund", + "nuri", + "thekla", + "victor", + "ilija", + "lukas", + "grace", + "bartholom\u00e4us", + "g\u00fcnther", + "oswin", + "anna_marie", + "devin", + "\u00f6mer", + "burkhardt", + "necati", + "janick", + "jovana", + "jordan", + "lino", + "yara", + "theres", + "siegrid", + "emily", + "zorica", + "jessika", + "gitte", + "flamur", + "marita", + "leontina", + "florentina", + "matheo", + "maksim", + "rosetta", + "isa", + "elise", + "heide", + "jannis", + "natasa", + "greta", + "alain", + "nikolaus", + "gisa", + "margit", + "uwe", + "serge", + "cengiz", + "curdin", + "betty", + "maxime", + "kemal", + "siglinde", + "klaus_dieter", + "maryline", + "fridolin", + "sergio", + "zenta", + "dieter", + "sandy", + "kerstin", + "gotthold", + "k\u00e4the", + "antonino", + "marin", + "karsten", + "leslie", + "diana", + "nik", + "ornella", + "kay_uwe", + "enrico", + "raquel", + "celia", + "etta", + "kristijan", + "wally", + "marcelo", + "irmtrud", + "lisette", + "vreneli", + "alessandro", + "dino", + "ryszard", + "jann", + "hansgeorg", + "ulf", + "annemie", + "karl_werner", + "anita", + "vitali", + "ernest", + "edin", + "helge", + "juana", + "sladjana", + "fred", + "anton", + "annick", + "aurelia", + "jorge", + "friedhilde", + "anatoli", + "th\u00e9r\u00e8se", + "daniele", + "jeannette", + "doris", + "corsin", + "lean", + "detlef", + "urszula", + "barbara", + "fabienne", + "bernt", + "simone", + "rosario", + "till", + "steffen", + "sophie_marie", + "jens_uwe", + "enes", + "kaspar", + "derya", + "gian", + "dirk", + "jeanette", + "besim", + "lejla", + "aurore", + "kevin", + "anto", + "wladimir", + "mael", + "mechtild", + "claudia", + "vivienne", + "alicja", + "t\u00fcrkan", + "lilli", + "martin", + "hans_christian", + "heinfried", + "dion", + "matilde", + "edward", + "mert", + "ahmad", + "janko", + "labinot", + "l\u00e9on", + "lukasz", + "dilara", + "matth\u00e4us", + "elia", + "robin", + "harald", + "fabio", + "dietlinde", + "ja\u00ebl", + "bilal", + "baris", + "blanka", + "lucien", + "hannchen", + "laila", + "augusta", + "willfried", + "eve", + "ronya", + "mohamed", + "konstanze", + "elin", + "gertraude", + "ellie", + "osman", + "suzanne", + "elio", + "arianna", + "jamie", + "wolfhard", + "dursun", + "murat", + "melvin", + "andres", + "dan", + "raisa", + "wilfried", + "randolf", + "heimo", + "mesut", + "regine", + "jean_luc", + "renata", + "bernward", + "louise", + "charles", + "gerold", + "eliana", + "frank_peter", + "carol", + "cristian", + "thadd\u00e4us", + "clara", + "joerg", + "arbnor", + "jakub", + "emanuel", + "muhamet", + "amela", + "dorit", + "ayla", + "anastasios", + "hartwig", + "hans_josef", + "erna", + "stefani", + "erina", + "ingo", + "cem", + "vivien", + "elona", + "wibke", + "mercedes", + "pierina", + "giacomo", + "muzaffer", + "t\u00e2nia", + "cornelia", + "torsten", + "nadeschda", + "orhan", + "horst_dieter", + "semir", + "ludwina", + "peter", + "karin", + "dana", + "nebojsa", + "alida", + "valentina", + "ardit", + "melitta", + "isabell", + "karl_friedrich", + "silvan", + "g\u00fclten", + "milica", + "franziska", + "tibor", + "g\u00f6tz", + "eugen", + "willibald", + "salma", + "berthold", + "ingetraud", + "annette", + "giulia", + "marian", + "tobias", + "leni", + "desiree", + "serkan", + "liana", + "ante", + "janine", + "brigitta", + "gerhild", + "adriane", + "aida", + "luke", + "jelena", + "predrag", + "heinrich", + "cl\u00e9mence", + "urs", + "drita", + "fredy", + "margrith", + "michele", + "uli", + "noe", + "nael", + "nurten", + "tea", + "erion", + "karolin", + "muhammed", + "mar\u00eda", + "antoinette", + "selena", + "karl_hermann", + "meryem", + "heinz_josef", + "zita", + "konstantin", + "margarete", + "zeki", + "mira", + "anna_luise", + "charlotte", + "baptist", + "gabrielle", + "giuseppina", + "gon\u00e7alo", + "josette", + "esther", + "ibrahim", + "ken", + "anina", + "walfried", + "leif", + "roy", + "vanessa", + "ahmet", + "veit", + "jon", + "oph\u00e9lie", + "hans_hinrich", + "vinko", + "gabriele", + "erica", + "nadja", + "elzbieta", + "abraham", + "gertrude", + "ana", + "josephine", + "sepp", + "alla", + "florentin", + "cyril", + "van", + "sonja", + "agatha", + "michaela", + "curt", + "wenzel", + "meik", + "chlo\u00e9", + "abram", + "sedat", + "rebekka", + "arnulf", + "alexa", + "holger", + "arlette", + "justine", + "zara", + "yvette", + "mariam", + "franz_xaver", + "christine", + "nelson", + "teodor", + "d\u00e9sir\u00e9e", + "ellen", + "emmerich", + "giovanni", + "gregor", + "hans_otto", + "birgid", + "theophil", + "gaetano", + "corinne", + "selin", + "laszlo", + "danijela", + "blerta", + "marijana", + "georgine", + "blerina", + "l\u00e9onie", + "saverio", + "milan", + "krzysztof", + "sereina", + "joanne", + "elke", + "sacha", + "iryna", + "jurij", + "c\u00e4cilia", + "elodie", + "francesco", + "aude", + "besarta", + "ludmilla", + "luna", + "alfonso", + "diego", + "kai", + "paula", + "marlise", + "dave", + "juliette", + "alicia", + "franca", + "elizabeth", + "tom", + "arian", + "colette", + "anatolij", + "marija", + "klaudia", + "ludger", + "svenja", + "dierk", + "christel", + "burghard", + "lara", + "marlene", + "dorota", + "anne_sophie", + "massimo", + "albina", + "mich\u00e8le", + "jael", + "mirlinda", + "damjan", + "aleksandra", + "alwine", + "rebecca", + "salvatore", + "elfriede", + "dajana", + "fatmir", + "jochen", + "aleksander", + "ayten", + "lorenza", + "gusti", + "athanasios", + "editha", + "ela", + "luljeta", + "senad", + "ewald", + "georgios", + "lola", + "dorothea", + "steve", + "neo", + "birgit", + "ajla", + "friedhold", + "didier", + "bogdan", + "klara", + "oscar", + "angelica", + "claire_lise", + "roman", + "coralie", + "patrik", + "victoria", + "berthe", + "joyce", + "wolf_dietrich", + "hans_georg", + "rachel", + "walter", + "antoine", + "karl_hans", + "dimitrios", + "alexis", + "laetitia", + "kuno", + "marga", + "hans_hermann", + "l\u00e9a", + "jacek", + "ernestine", + "gudrun", + "bruni", + "waltraut", + "susanne", + "anette", + "leokadia", + "georges", + "christiane", + "dietlind", + "nuray", + "denise", + "jil", + "vittoria", + "mark", + "joseph", + "ilonka", + "emilian", + "reinhild", + "marcia", + "hasso", + "wolfram", + "berend", + "guy", + "christian", + "jetmir", + "arne", + "mariola", + "reimer", + "beni", + "samanta", + "konstantinos", + "hildegart", + "in\u00e8s", + "annett", + "tam\u00e1s", + "heidy", + "rena", + "aloisia", + "johan", + "otto", + "christa_maria", + "heinz_dieter", + "fabrice", + "marco", + "marcelle", + "margarida", + "matilda", + "mustafa", + "lionel", + "immo", + "adnan", + "felizitas", + "isabelle", + "mary", + "marta", + "erwin", + "rolf", + "reingard", + "kristiane", + "ignaz", + "nikita", + "constance", + "hans_g\u00fcnther", + "ruzica", + "antonella", + "bertold", + "notburga", + "jovan", + "timm", + "javier", + "liliane", + "apollonia", + "witold", + "janina", + "artan", + "amra", + "remo", + "anatol", + "prisca", + "nelly", + "heinz_otto", + "istv\u00e1n", + "hans_eberhard", + "serena", + "rino", + "adriana", + "gilles", + "c\u00e4cilie", + "marzena", + "viviane", + "fr\u00e9d\u00e9rique", + "brian", + "mladen", + "darius", + "aloys", + "dragan", + "giuliano", + "sylke", + "omar", + "luc", + "g\u00fclay", + "melanie", + "laurenz", + "frederik", + "chris", + "tiago", + "drilon", + "brunhilde", + "aenne", + "noa", + "gemma", + "frank_michael", + "patrick", + "hans_erich", + "bernd_dieter", + "iwan", + "vladimir", + "graziella", + "claas", + "karl", + "shaban", + "romuald", + "kenneth", + "conrad", + "auguste", + "gabriella", + "s\u00e9bastien", + "inken", + "giorgia", + "evelyn", + "almuth", + "ria", + "flavio", + "nuria", + "karl_otto", + "livio", + "hildegund", + "fedor", + "amy", + "diethard", + "roselinde", + "hanife", + "lennard", + "berta", + "jade", + "arnold", + "murielle", + "sylvia", + "skender", + "jaroslaw", + "balthasar", + "lucas", + "gerda", + "roxane", + "ilse", + "jo\u00eblle", + "alba", + "burkhard", + "gion", + "hans_herbert", + "sabrina", + "ernst_otto", + "benedict", + "carolin", + "halil", + "alexander", + "linus", + "hans_martin", + "dragica", + "imke", + "friedlinde", + "ottfried", + "m\u00e9lissa", + "felicitas", + "gina", + "dalia", + "marie_claire", + "cilly", + "heike", + "cathrin", + "bianka", + "heinz_walter", + "kati", + "pavel", + "sahin", + "galina", + "domenico", + "marlies", + "mentor", + "donat", + "ira", + "drago", + "wilma", + "egbert", + "adem", + "stephen", + "patrizia", + "yasemin", + "el\u00e9onore", + "ant\u00f3nio", + "theodoros", + "bashkim", + "malea", + "sigurd", + "catrin", + "vlora", + "heiner", + "valentin", + "carolina", + "h\u00fcseyin", + "yusuf", + "christa", + "hermann_josef", + "sven", + "lauriane", + "reinhart", + "liridon", + "geraldine", + "ramon", + "ismet", + "naim", + "gesche", + "ryan", + "wendelin", + "ruthild", + "lara_sophie", + "hans_peter", + "joel", + "rosanna", + "zo\u00e9", + "ingolf", + "l\u00e9na", + "hubertine", + "josefine", + "ronny", + "thies", + "pirmin", + "frieda", + "lazar", + "dimitri", + "gretl", + "jeanne", + "klaus_peter", + "joris", + "erkan", + "tim", + "amelia", + "ljiljana", + "nicolai", + "ottilie", + "enzo", + "jolanda", + "jose", + "marko", + "sandro", + "joy", + "evelyne", + "lia", + "joanna", + "gunhild", + "lieselotte", + "yannick", + "elina", + "tilo", + "lora", + "traudl", + "mona", + "marietta", + "ma\u00eblle", + "marlis", + "joachim", + "frederic", + "rina", + "kira", + "micha", + "miroslaw", + "adrian", + "david", + "dijana", + "hans_ludwig", + "boris", + "rotraut", + "arthur", + "marthe", + "yasmina", + "regina", + "hubertus", + "ilenia", + "jeanine", + "jean_pierre", + "elea", + "ioannis", + "hildegard", + "eleonore", + "massimiliano", + "gebhard", + "rosel", + "tina", + "calogero", + "tiziano", + "lias", + "jonas", + "tomasz", + "janosch", + "hans_helmut", + "arno", + "fernando", + "detlev", + "jari", + "gesine", + "ferdinand", + "gottlob", + "lina", + "leonard", + "timothy", + "berra", + "estelle", + "g\u00fclsen", + "bernfried", + "andr\u00e9e", + "ehrentraud", + "caren", + "utz", + "m\u00e9lanie", + "c\u00e9dric", + "levin", + "brunhild", + "matej", + "asia", + "giuseppa", + "trudel", + "rafael", + "ann", + "paola", + "dorle", + "delphine", + "hella", + "helfried", + "grzegorz", + "jens", + "cl\u00e1udia", + "leon", + "gerlind", + "elmar", + "volker", + "zahra", + "alessandra", + "olivier", + "erdmute", + "silja", + "s\u00e9rgio", + "kristin", + "tomislav", + "hansj\u00f6rg", + "anes", + "dragana", + "dafina", + "nando", + "helga", + "antonio", + "pawel", + "maren", + "hedwig", + "seraina", + "aisha", + "max", + "maximilian", + "gundi", + "heinz_g\u00fcnther", + "veronica", + "maud", + "hansruedi", + "katarina", + "raffaella", + "arsim", + "eggert", + "gabriel", + "alina", + "karola", + "jakob", + "kim", + "l\u00e9ane", + "manuela", + "kurt", + "alexandar", + "beatriz", + "malgorzata", + "sergej", + "manuel", + "karina", + "emmi", + "agnese", + "irmingard", + "klaus_g\u00fcnter", + "robby", + "elli", + "xaver", + "liv", + "biljana", + "adelgunde", + "friedbert", + "marie_france", + "kamil", + "katy", + "nermin", + "rosalia", + "giorgio", + "cornel", + "jozef", + "pascale", + "arda", + "elfie", + "janik", + "ida", + "fatima", + "anne_rose", + "anna_maria", + "peter_michael", + "edelbert", + "ramadan", + "franka", + "alexandre", + "nils", + "jessica", + "piotr", + "meinhard", + "canan", + "konrad", + "margaretha", + "leah", + "angelina", + "gerald", + "jona", + "eduardo", + "hannes", + "tadeusz", + "michal", + "elenore", + "phillip", + "henrik", + "myrtha", + "kristine", + "adina", + "sinisa", + "margareta", + "lucette", + "ronald", + "alissa", + "sharon", + "irfan", + "hans_theo", + "tuana", + "gordana", + "annelie", + "muharrem", + "ricardo", + "marit", + "fatih", + "natalija", + "enis", + "ralf_peter", + "willi", + "isabella", + "isidor", + "louisa", + "livia", + "valeria", + "gerlinde", + "arif", + "berndt", + "odile", + "ralf", + "matteo", + "stjepan", + "niklaus", + "maria_luise", + "simeon", + "cecilia", + "j\u00f6rn", + "evan", + "andrej", + "korinna", + "cristiano", + "sylwia", + "nino", + "miriam", + "alexei", + "luz", + "anouk", + "svetlana", + "lutz", + "friedrich_karl", + "lissi", + "filomena", + "cetin", + "timo", + "eliane", + "fernande", + "arta", + "gregory" + ], + "LAST_NAME": [ + "s\u00e4uberlich", + "varga", + "aigner", + "p\u00f6ll", + "sch\u00f6berl", + "bischof", + "ammann", + "aschauer", + "wiesinger", + "hahn", + "hertrampf", + "stiegler", + "feichter", + "h\u00e4fliger", + "bruckner", + "loos", + "brandtner", + "gotthard", + "widhalm", + "st\u00fctz", + "grill", + "eberth", + "kambs", + "kaindl", + "redl", + "hettner", + "kramer", + "bachler", + "hug", + "feichtner", + "hausberger", + "maierhofer", + "b\u00fchlmann", + "schwab", + "seitz", + "burtscher", + "sommer", + "n\u00f6bauer", + "schweiger", + "nu\u00dfbaumer", + "schatzl", + "sch\u00f6pf", + "kessler", + "schrittwieser", + "heintze", + "d\u00f6ring", + "kabus", + "strasser", + "h\u00f6fig", + "lorch", + "paffrath", + "windhager", + "adam", + "ender", + "horak", + "friedli", + "r\u00f6rricht", + "posch", + "kremser", + "werner", + "feichtinger", + "decker", + "lipp", + "stefan", + "rohrer", + "ruppersberger", + "fleck", + "pock", + "frank", + "losekann", + "karner", + "winkler", + "steinb\u00f6ck", + "felber", + "eberhard", + "j\u00fcttner", + "hofmeister", + "fellner", + "stauffer", + "killer", + "caspar", + "zahn", + "mohaupt", + "harrer", + "j\u00e4kel", + "gasser", + "ortmann", + "lercher", + "keplinger", + "junitz", + "krall", + "bernhard", + "reinisch", + "pauer", + "mettler", + "juncken", + "payer", + "neumeister", + "wende", + "unger", + "steiger", + "gratzl", + "marti", + "stecher", + "leber", + "wirth", + "kirschner", + "bock", + "schmuck", + "ostermann", + "reindl", + "jandl", + "hinteregger", + "hofst\u00e4tter", + "striebitz", + "kitzler", + "baldauf", + "steiner", + "klocker", + "spie\u00df", + "nagel", + "schranz", + "rohleder", + "lechner", + "scholl", + "st\u00f6ger", + "giger", + "neuhauser", + "kapeller", + "koppensteiner", + "pinter", + "gutmann", + "schnyder", + "kerschbaumer", + "weller", + "walch", + "fuchs", + "zettl", + "jockel", + "weitzel", + "ackerl", + "plath", + "r\u00f6hricht", + "seidl", + "m\u00f6rth", + "etzler", + "kolm", + "metz", + "paulitsch", + "kaltenb\u00f6ck", + "kraft", + "pilz", + "l\u00fcbs", + "sorger", + "postl", + "brandstetter", + "mielcarek", + "neumann", + "tanner", + "zehnder", + "fellinger", + "leu", + "wurm", + "haering", + "gartner", + "haring", + "d\u00f6hn", + "lange", + "deutschmann", + "sutter", + "aebi", + "messner", + "danninger", + "leitgeb", + "kurzmann", + "schwarzinger", + "reinhardt", + "h\u00f6dl", + "sauer", + "fasching", + "h\u00f6vel", + "segebahn", + "pfeifer", + "pokorny", + "blum", + "renner", + "jungfer", + "wenzl", + "walder", + "hesse", + "reisinger", + "oberm\u00fcller", + "anderl", + "mude", + "pirker", + "hunziker", + "lederer", + "sattler", + "sorgatz", + "lengauer", + "bolliger", + "zenz", + "achleitner", + "yilmaz", + "brandl", + "oberndorfer", + "f\u00fcreder", + "textor", + "schober", + "austerm\u00fchle", + "steinbauer", + "schmidt", + "herrmann", + "wagenknecht", + "hiller", + "ziegert", + "bogner", + "hufnagl", + "froschauer", + "leitner", + "reiterer", + "humer", + "fleischhacker", + "hotz", + "h\u00f6fer", + "eisl", + "kitzmann", + "neubacher", + "wulff", + "rainer", + "tr\u00f6st", + "gierschner", + "mangold", + "haslinger", + "w\u00e4hner", + "rottensteiner", + "staub", + "pointner", + "neureiter", + "beckmann", + "kolar", + "kreuzer", + "bachmann", + "hermann", + "jessel", + "sidler", + "reising", + "stoll", + "unterweger", + "brun", + "stettler", + "ebner", + "schantl", + "janisch", + "holsten", + "prenner", + "kronberger", + "reiner", + "bayer", + "bianchi", + "spreitzer", + "ackermann", + "koch", + "streicher", + "merz", + "drewes", + "betschart", + "kahr", + "k\u00f6ster", + "klein", + "moosbrugger", + "eichinger", + "helm", + "r\u00e4del", + "brenner", + "zimmer", + "kostolzin", + "kolb", + "nussbaumer", + "held", + "studer", + "reinprecht", + "fritz", + "warmer", + "thaler", + "moritz", + "ruppert", + "kriegl", + "spiegl", + "hornich", + "reichmann", + "fleischmann", + "amann", + "praxmarer", + "p\u00fchringer", + "margraf", + "z\u00f6chling", + "etzold", + "oberhauser", + "schottin", + "dengg", + "schinagl", + "baur", + "schuller", + "rath", + "ortner", + "erber", + "wagner", + "gut", + "stangl", + "wohlgemut", + "m\u00fchlb\u00f6ck", + "sagmeister", + "scherrer", + "schalk", + "angerer", + "bl\u00fcmel", + "pfleger", + "jank", + "misicher", + "rabl", + "kaiser", + "wilhelm", + "k\u00f6lbl", + "hasler", + "steindl", + "pachler", + "schachner", + "kopf", + "siering", + "klingler", + "schmiedt", + "favre", + "stern", + "roht", + "portmann", + "zehetner", + "burgstaller", + "stiebitz", + "zechner", + "gr\u00fcnberger", + "dietz", + "schmid", + "weibel", + "schmidtke", + "staudacher", + "schoch", + "dietl", + "kraxner", + "bernasconi", + "stocker", + "lamprecht", + "krebs", + "schreiber", + "schandl", + "sonnleitner", + "k\u00e4ser", + "rosemann", + "philipp", + "haiden", + "z\u00e4nker", + "kroker", + "krenn", + "m\u00f6chlichen", + "grabner", + "wolf", + "eichenberger", + "prem", + "fuhrmann", + "karrer", + "scheel", + "frei", + "riepl", + "hande", + "kirchner", + "schweitzer", + "trinkl", + "danner", + "brandst\u00e4tter", + "friedl", + "gfeller", + "kogler", + "riedmann", + "metzler", + "bosshard", + "furrer", + "polzer", + "beyer", + "l\u00fcscher", + "k\u00f6berl", + "horn", + "geyer", + "freudenberger", + "loidl", + "weimer", + "hauer", + "beier", + "kastner", + "h\u00f6rle", + "pircher", + "hager", + "wilms", + "wilmsen", + "ullrich", + "reif", + "sp\u00f6rri", + "seifert", + "schr\u00f6der", + "kainz", + "l\u00f6wer", + "schweizer", + "schimpl", + "rauch", + "zbinden", + "schnabl", + "klinger", + "kreusel", + "van_der_dussen", + "beck", + "ladeck", + "d\u00f6rr", + "reuter", + "pfeffer", + "nagl", + "dittrich", + "prinz", + "zirme", + "lindinger", + "engel", + "maier", + "knapp", + "pieper", + "heinz", + "richter", + "riegler", + "mathis", + "berner", + "h\u00e4ring", + "kucera", + "fl\u00fcckiger", + "h\u00e4mmerle", + "haas", + "sch\u00e4fer", + "grob", + "hammerer", + "geier", + "oberhofer", + "m\u00fchlbacher", + "fabian", + "fr\u00fchwirth", + "dobler", + "hummer", + "sch\u00fcler", + "seip", + "kummer", + "mentzel", + "gude", + "conradi", + "m\u00fcllner", + "leunberger", + "schaller", + "neureuther", + "glaser", + "augustin", + "dangl", + "dussen_van", + "kreiner", + "schramm", + "fischer", + "bitschnau", + "holt", + "doppler", + "taferner", + "kuhl", + "baumgartner", + "tiefenbacher", + "iten", + "oderwald", + "krause", + "krug", + "klausner", + "ertl", + "holzapfel", + "rupp", + "jovanovic", + "jost", + "salcher", + "j\u00e4ggi", + "schuchhardt", + "rudolf", + "ecker", + "bodner", + "trimmel", + "buchegger", + "ditschlerin", + "biedermann", + "kruschwitz", + "heim", + "scherer", + "junken", + "hecker", + "rosner", + "wandl", + "tlustek", + "wulf", + "sch\u00f6nberger", + "salzer", + "marte", + "mann", + "h\u00fcrlimann", + "eberhardt", + "steinkellner", + "schachinger", + "friedrich", + "platzer", + "hollaus", + "drubin", + "klug", + "b\u00fchler", + "frey", + "larcher", + "barkholz", + "fehr", + "seidel", + "stock", + "handler", + "nette", + "schlager", + "farkas", + "ludwig", + "wieser", + "baier", + "macher", + "lindau", + "albrecht", + "strauss", + "pergande", + "gstrein", + "raab", + "heser", + "bonbach", + "jungwirth", + "plank", + "m\u00fclichen", + "keller", + "h\u00f6ller", + "scheidegger", + "oberleitner", + "ritter", + "denk", + "stroh", + "niederl", + "walser", + "hinterleitner", + "erler", + "traxler", + "gross", + "scholtz", + "hutter", + "kaul", + "sch\u00fcller", + "bolander", + "foidl", + "lackner", + "bolzmann", + "flantz", + "schomber", + "h\u00f6lzenbecher", + "berger", + "dowerg", + "suppan", + "hoffmann", + "steininger", + "uhl", + "kain", + "rausch", + "k\u00f6ck", + "ring", + "dietrich", + "lichtenegger", + "scherz", + "hofer", + "eigenwillig", + "davids", + "rieger", + "bachinger", + "tschentscher", + "meier", + "cichorius", + "lustenberger", + "kr\u00f6ll", + "trupp", + "fliegner", + "eberl", + "weiss", + "jauk", + "eller", + "dorner", + "gschaider", + "lindorfer", + "ferrari", + "k\u00fchnert", + "schenk", + "margreiter", + "binner", + "eder", + "wenger", + "herbst", + "h\u00e4nel", + "hammer", + "sigrist", + "falkner", + "dobes", + "gehringer", + "spindler", + "r\u00f6hrdanz", + "nowak", + "grasser", + "klotz", + "l\u00f6chel", + "eimer", + "steckel", + "kollmann", + "h\u00fcbner", + "butte", + "rose", + "seiser", + "f\u00fcrst", + "zorbach", + "stey", + "hofmann", + "bader", + "baum", + "zeller", + "schwaighofer", + "carsten", + "wilfinger", + "urban", + "schleich", + "christoph", + "schwarzl", + "karz", + "kerschbaum", + "gei\u00dfler", + "oswald", + "t\u00e4sche", + "jenewein", + "trub", + "z\u00f6hrer", + "hartmann", + "pesendorfer", + "rieder", + "kofler", + "ernst", + "nerger", + "mans", + "maurer", + "altmann", + "lehner", + "schm\u00f6lzer", + "reichel", + "faust", + "fink", + "oestrovsky", + "bender", + "birnbaum", + "reich", + "schatz", + "suter", + "stucki", + "hethur", + "griesser", + "nemeth", + "mies", + "gie\u00df", + "kunz", + "hartl", + "weber", + "p\u00f6lzl", + "reithofer", + "schmiedecke", + "lassnig", + "schwarz", + "b\u00e4hr", + "zeiner", + "schinnerl", + "peham", + "bittner", + "hirsch", + "kreidl", + "paier", + "schaaf", + "tr\u00fcb", + "kirchmair", + "eisner", + "auer", + "hafner", + "rust", + "buchner", + "g\u00f6schl", + "lorenz", + "huemer", + "schmidinger", + "dirnberger", + "dorfer", + "schrempf", + "thurner", + "strobl", + "rauscher", + "schubert", + "himmelbauer", + "gruber", + "siller", + "beer", + "rauter", + "stutz", + "guggenberger", + "wurzer", + "siegrist", + "lampert", + "b\u00f6ck", + "sch\u00fcrch", + "haderer", + "kalcher", + "thanel", + "biggen", + "seiwald", + "harloff", + "wieloch", + "naser", + "linder", + "leithner", + "klammer", + "bartl", + "krainer", + "h\u00f6rmann", + "greiner", + "dallinger", + "gosch", + "scheidl", + "simon", + "radisch", + "schuler", + "kaltenegger", + "kade", + "weidinger", + "walcher", + "hauffer", + "trattner", + "luttenberger", + "lehmann", + "holzer", + "dippel", + "junk", + "karge", + "wallner", + "m\u00fchle", + "fehringer", + "tauber", + "strohmeier", + "fitz", + "roth", + "sperl", + "stummer", + "hofbauer", + "auinger", + "gute", + "egli", + "grassl", + "hentschel", + "hubmann", + "stockinger", + "wegscheider", + "prohaska", + "hell", + "b\u00f6hm", + "fiebig", + "glatz", + "parzer", + "franz", + "baumann", + "peer", + "forstner", + "hammerl", + "wechselberger", + "w\u00fcthrich", + "r\u00f6mer", + "s\u00f6ding", + "haidinger", + "hacker", + "schl\u00f6gl", + "girschner", + "stelzer", + "nagele", + "hirt", + "jenni", + "s\u00fc\u00dfebier", + "koller", + "hagen", + "b\u00e4r", + "putz", + "muhr", + "heissenberger", + "gerlach", + "wieland", + "perner", + "weihmann", + "neuner", + "neuwirth", + "gutknecht", + "kuhn", + "ofner", + "waldner", + "leopold", + "gl\u00fcck", + "hinterberger", + "sigl", + "krammer", + "nohlmans", + "wirz", + "riener", + "ulrich", + "j\u00f6bstl", + "heidrich", + "steinwender", + "schwendinger", + "finke", + "aichholzer", + "schrammel", + "gattringer", + "haberl", + "d\u00fcnser", + "kasper", + "senn", + "puchner", + "isler", + "f\u00f6rster", + "aumann", + "mairhofer", + "schlosser", + "sch\u00f6ffmann", + "zauner", + "erhart", + "heger", + "felder", + "sch\u00f6n", + "obermayr", + "dehmel", + "petz", + "k\u00f6nig", + "pacher", + "stifter", + "lanz", + "hauser", + "l\u00fcthi", + "langer", + "barth", + "meister", + "scheiber", + "hebenstreit", + "prager", + "henck", + "rohrmoser", + "kohl", + "wegmann", + "jacob", + "klaus", + "budig", + "reitinger", + "siegl", + "johann", + "ebert", + "neuhold", + "wiener", + "stadler", + "pfeiffer", + "junck", + "mosemann", + "bergmann", + "mader", + "kratzer", + "amrein", + "k\u00e4fer", + "sager", + "kocher", + "feichtenschlager", + "kraus", + "knoll", + "w\u00f6hrer", + "strau\u00df", + "kager", + "k\u00e4ster", + "gmeiner", + "burri", + "feigl", + "neumayer", + "adolph", + "zobel", + "weinhold", + "m\u00e4lzer", + "linke", + "rudolph", + "fechner", + "gangl", + "meindl", + "trommler", + "p\u00e4rtzelt", + "bauer", + "heigl", + "wimmer", + "neusch\u00e4fer", + "eberharter", + "leutgeb", + "paul", + "schuh", + "mayr", + "bacher", + "trubin", + "salz", + "p\u00f6litz", + "lettner", + "kaufmann", + "kober", + "grein_groth", + "niemeier", + "weigl", + "rabitsch", + "steinberg", + "noack", + "freudenthaler", + "santner", + "lang", + "hainzl", + "reinbacher", + "klemm", + "ringhofer", + "gahleitner", + "singer", + "michel", + "lerch", + "scheucher", + "vogl", + "koch_ii", + "wild", + "schlatter", + "h\u00fcbel", + "gr\u00fcner", + "stadlbauer", + "z\u00fcrcher", + "wurzinger", + "lampl", + "fichtinger", + "g\u00fcnther", + "kloiber", + "hutterer", + "pr\u00f6ll", + "bolnbach", + "mohr", + "h\u00fctter", + "mende", + "henschel", + "haindl", + "b\u00f6sch", + "mitter", + "hartung", + "jahn", + "heinzl", + "thaller", + "fankhauser", + "schaub", + "zotter", + "stockhammer", + "mandl", + "schwital", + "reitbauer", + "wiesner", + "kopp", + "hochleitner", + "hein", + "sch\u00f6nland", + "plattner", + "benthin", + "hendriks", + "rosenberger", + "reicher", + "weiser", + "holl", + "weissenb\u00f6ck", + "vogel", + "mittermayr", + "scharf", + "hattinger", + "prantl", + "reisner", + "steffen", + "heindl", + "kaspar", + "scharinger", + "auch_schlauchin", + "leibetseder", + "wehrli", + "leeb", + "klapp", + "martin", + "henk", + "loibl", + "krainz", + "gerber", + "enzinger", + "rettenbacher", + "r\u00f6ck", + "boucsein", + "mayerhofer", + "mayer", + "huhn", + "h\u00f6rl", + "trauner", + "leonhartsberger", + "hochreiter", + "steinlechner", + "kronsteiner", + "kern", + "kaltenbrunner", + "lintner", + "christen", + "hummel", + "eugster", + "amon", + "bohlander", + "blaser", + "r\u00f6ssler", + "gr\u00fcnwald", + "sch\u00f6ller", + "galler", + "mitterlehner", + "taucher", + "gertz", + "pfister", + "schmied", + "huber", + "jopich", + "sturm", + "krein", + "kranz", + "wiesbauer", + "berchtold", + "adler", + "wittmann", + "peter", + "pucher", + "scherr", + "anders", + "sailer", + "pechel", + "sch\u00fctz", + "holzknecht", + "g\u00f6tz", + "k\u00e4gi", + "berthold", + "landl", + "schweighofer", + "neubauer", + "gumprich", + "wachter", + "sch\u00e4rer", + "schuster", + "tischler", + "mitterer", + "eibl", + "frick", + "k\u00f6ssler", + "gollner", + "bucher", + "toth", + "heinrich", + "zach", + "thommen", + "peukert", + "breuer", + "punz", + "k\u00e4lin", + "ullmann", + "ferstl", + "brunner", + "j\u00e4ntsch", + "kappel", + "briemer", + "scheuermann", + "gro\u00df", + "b\u00e4ttig", + "heuser", + "veit", + "schiefer", + "frisch", + "k\u00fcng", + "bruder", + "rechberger", + "sieber", + "salzmann", + "erlacher", + "trapp", + "scherzer", + "forster", + "zeiler", + "vogler", + "roos", + "graf", + "ramsauer", + "patberg", + "lammer", + "fiedler", + "gratz", + "holzmann", + "meixner", + "markl", + "stalder", + "sammer", + "holler", + "wyss", + "pohl", + "strohmaier", + "h\u00f6lzl", + "gr\u00f6ttner", + "bien", + "sch\u00f6nauer", + "kugler", + "geisler", + "stoiber", + "gorlitz", + "marx", + "wernecke", + "juen", + "radl", + "braun", + "st\u00f6ckli", + "haase", + "teufl", + "gratzer", + "stark", + "hemetsberger", + "widmann", + "eichberger", + "d\u00f6rschner", + "buchholz", + "he\u00df", + "wesack", + "vollbrecht", + "stolze", + "hornig", + "riedler", + "staudinger", + "hechenberger", + "steinbacher", + "winter", + "haller", + "bohnbach", + "br\u00e4uer", + "liebelt", + "m\u00e4der", + "kellner", + "haslauer", + "sulzer", + "steinberger", + "walter", + "hirschmann", + "brandner", + "scheibe", + "zimmermann", + "neum\u00fcller", + "gritsch", + "bieri", + "gloor", + "j\u00e4ger", + "burger", + "prei\u00df", + "haider", + "mark", + "fr\u00f6hlich", + "trummer", + "klement", + "rey", + "egger", + "erni", + "gnatz", + "hamann", + "maringer", + "otto", + "klemt", + "schauer", + "steurer", + "kurz", + "b\u00f6rner", + "rogge", + "ladner", + "schneeberger", + "laimer", + "m\u00fcller", + "hofstetter", + "wettstein", + "pertl", + "meyer", + "stiffel", + "schiller", + "langern", + "schwaiger", + "heiss", + "roskoth", + "sontag", + "mair", + "handl", + "wiek", + "steger", + "st\u00f6ckl", + "schumacher", + "grabher", + "gindl", + "zangerl", + "holzinger", + "schilcher", + "pammer", + "ehlert", + "tintzmann", + "st\u00fcckler", + "h\u00f6fler", + "benz", + "kensy", + "karl", + "klingelh\u00f6fer", + "pendl", + "hodel", + "heydrich", + "matth\u00e4i", + "pichler", + "b\u00e4rer", + "arnold", + "steidl", + "m\u00fchlberger", + "stumpf", + "hosp", + "kammerer", + "lenz", + "stolz", + "haumer", + "kobelt", + "schinke", + "blauensteiner", + "j\u00e4hn", + "haid", + "spitzer", + "wei\u00df", + "p\u00f6schl", + "reinthaler", + "strohmayer", + "pruschke", + "buchberger", + "schreiner", + "tobler", + "meili", + "moser", + "kargl", + "drub", + "stadelmann", + "waltl", + "seebacher", + "s\u00f6lzer", + "dorn", + "b\u00e4ck", + "thies", + "pieber", + "pollak", + "b\u00fcrger", + "ziegler", + "seiler", + "scholz", + "kohler", + "huter", + "wohlmuth", + "franke", + "rosenow", + "bichler", + "weinberger", + "reiter", + "zollinger", + "jacobi_j\u00e4ckel", + "springer", + "gassner", + "atzler", + "bloch", + "unterberger", + "b\u00f6hler", + "schiestl", + "g\u00e4rtner", + "lagler", + "mayrhofer", + "weninger", + "stahr", + "knappe", + "probst", + "kiss", + "jung", + "sieberer", + "thalhammer", + "zingg", + "rieser", + "knaus", + "n\u00e4f", + "steinmann", + "lachmann", + "becker", + "h\u00e4usler", + "kral", + "herzog", + "k\u00f6ll", + "edlinger", + "rogner", + "meusburger", + "resch", + "schneider", + "schulz", + "fercher", + "schacht", + "k\u00f6hler", + "grundner", + "reischl", + "buchinger", + "zechmeister", + "riehl", + "freitag", + "scheer", + "tanzer", + "brugger", + "zeilinger", + "gamsj\u00e4ger", + "steinacher", + "rotter", + "aichinger", + "eckbauer", + "eichhorn", + "gabriel", + "albers", + "r\u00fcegg", + "hofinger", + "gschwandtner", + "draxler", + "weinhage", + "fr\u00f6schl", + "gunpf", + "knecht", + "neugebauer", + "engl", + "penz", + "schindler", + "staude", + "keudel", + "artner", + "hering", + "w\u00f6gerbauer", + "hermighausen", + "schmidl", + "widmer", + "reichl", + "schaffer", + "mitteregger", + "l\u00f6ffler", + "kusch", + "konrad", + "speer", + "puntigam", + "geisel", + "rinner", + "simic", + "kallert", + "vogt", + "geiger", + "hess", + "fritsch", + "list", + "schartner", + "h\u00f6glinger", + "hellwig", + "windisch", + "lindner", + "rossmann", + "neulinger", + "heller", + "neumayr", + "schrenk", + "kraushaar", + "stelzl", + "riedl", + "imhof", + "ott", + "luger", + "mitschke", + "hackl", + "lutz", + "sch\u00e4r", + "binder", + "wiedner" + ], + "OTHER_PRONOUN": [ + "it", + "that", + "its", + "these" + ], + "LAST_NAME_MALE": [], + "LAST_NAME_FEMALE": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "priorin": "abba", + "oberin": "abba", + "\u00e4btissin": "abbas", + "schauspielerin": "darsteller", + "actress": "bob_carroll", + "aktrice": "akteur", + "darsteller": "bob_carroll", + "akteurin": "darsteller", + "bibi": "omme", + "baronin": "baron", + "baroness": "baron", + "baronesse": "freiherr", + "sch\u00f6ne": "beau", + "braut": "groom", + "unternehmerin": "gesch\u00e4ftsmann", + "gesch\u00e4ftsfrau": "gesch\u00e4ftsmann", + "vorsitzende": "obmann", + "vorstandsvorsitzende": "vorsitzender", + "chick": "gaur", + "pullus": "dandy", + "ische": "fashion_victim", + "k\u00fcken": "gaur", + "vogeljunges": "dandy", + "jungvogel": "gaur", + "cowgirl": "cowboy", + "kuhhirtin": "cowboy", + "panik": "son", + "dotter": "son", + "tochter": "kutt", + "herzogin": "duke", + "kaiserin": "imperator", + "femme_fatale": "zaubererin", + "zauberin": "sorcerer", + "die_zauberin": "zaubererin", + "delila": "zaubererin", + "samica": "m\u00e4nnlein", + "weiblich": "maskulin", + "\u0436\u0435\u043d\u0441\u043a\u0438\u0439": "male", + "physikerin": "male", + "feminin": "m\u00e4nnlein", + "abgeordnete": "m\u00e4nnlein", + "weibchen": "m\u00e4nnlein", + "gal": "macker", + "griet": "guido", + "t\u00f6s": "veit", + "m\u00e4del": "macker", + "girl": "fotzenknecht", + "lola": "fotzenknecht", + "wicht": "macker", + "girlfriend": "fotzenknecht", + "deern": "veit", + "hauslehrerin": "gouverneurin", + "erzieherin": "gouverneur", + "gouvernante": "gouverneur", + "nift": "grosssohn", + "enkelin": "grosssohn", + "grossmutter": "grossvater_m\u00fctterlicherseits", + "nine": "grossvater_v\u00e4terlicherseits", + "rektorin": "schulleiter", + "schulleiterin": "schulleiter", + "direktorin": "schulleiter", + "her": "lia", + "ihre": "tij", + "henne": "tij", + "heroin": "held", + "heldin": "trim", + "heroine": "held", + "animateur": "seelen", + "hostess": "verwalter", + "wirtin": "gastgeber", + "gastgeberin": "host", + "lady": "efendi", + "herrin": "landheer", + "kak": "frater", + "hauswirtin": "vermieter", + "vermieterin": "hauswirt", + "schlummermutter": "vermieter", + "lass": "groom", + "mamsell": "diener", + "thusnelda": "diener", + "minna": "diener", + "hausm\u00e4dchen": "diener", + "filine": "diener", + "zugehfrau": "diener", + "dienstm\u00e4dchen": "diener", + "marquise": "marquis", + "masseurin": "masseur", + "masseuse": "masseur", + "missen": "sir", + "vermissen": "sir", + "mademoiselle": "sir", + "fehlen": "sir", + "miss": "sir", + "verfehlen": "sir", + "vers\u00e4umen": "sir", + "miss_a": "sir", + "missa": "sir", + "verpassen": "sir", + "entbehren": "sir", + "herrscherin": "master", + "kurtisane": "efendi", + "meisterin": "lehrmeister", + "frauchen": "skipper", + "m\u00e4tresse": "master", + "mom": "vater", + "mutti": "daddy", + "bemuttern": "pair", + "muttertier": "fader", + "moder": "pair", + "mutter": "pid", + "die_mutter": "fader", + "matrix": "ayr", + "maximus": "ayr", + "bh": "mr", + "mw": "mr", + "ms": "mgr", + "nichte": "neffe", + "klosterschwester": "m\u00f6nch", + "schwester": "bruder", + "ordensschwester": "murg", + "nun": "monako", + "polizeibeamtin": "polizeibeamter", + "polizeifrau": "polizeimann", + "priesterin": "pfaffe", + "pr\u00edncipe": "der_f\u00fcrst", + "k\u00f6nigsenkelin": "f\u00fcrst", + "prinzessin": "prince", + "k\u00f6nigstochter": "prince", + "princessa": "der_f\u00fcrst", + "princess": "pr\u00edncipe", + "homosexual": "rex", + "danaus_gilippus": "indra", + "reg": "k\u00f6nig", + "k\u00f6nigin": "monarch", + "drag_queen": "king", + "reine": "monarch", + "hetman": "king", + "queen": "k\u00f6nig", + "queens": "k\u00f6nige", + "sun": "he", + "way": "broder", + "nurse": "frater", + "sour": "frater", + "hexenmeisterin": "sorcerer", + "magierin": "sorcerer", + "zaubrerin": "sorcerer", + "zaubererin": "sorcerer", + "unverheiratete_frau": "bachelor", + "alte_jungfer": "bakkalaureus", + "junggesellin": "bachelor", + "unverheiratetes_fr\u00e4ulein": "bachelor", + "stieftochter": "stiefsohn", + "stiefmutter": "stiefvater", + "stiefelternteil": "stiefvater", + "flugbegleiterin": "verwalter", + "stewardess": "administrator", + "kellnerin": "kelner", + "bedienerin": "kelner", + "witwe": "witwer", + "hurenkind": "witwer", + "gattin": "gemahl", + "bean": "gv", + "eheweib": "wer", + "feme": "der_mann", + "ehefrau": "gatte", + "gemahlin": "ehegatte", + "weib": "der_mann", + "hex": "wizard", + "striga": "wizard", + "aalbutt": "wizard", + "wicca": "wizard", + "hundszunge": "magier", + "glyptocephalus_cynoglossus": "wizard", + "hexe": "wizard", + "arnoglossus_scapha": "wizard", + "bike": "gv", + "boy": "griet", + "matz": "girl", + "bursche": "t\u00f6s", + "knabe": "wicht", + "fant": "lola", + "bube": "griet", + "polonaise": "wichsen", + "polnisch": "polonaise", + "kultur": "polonaise", + "politur": "polonaise", + "wichsen": "polonaise", + "raffinement": "polonaise", + "polieren": "polonaise", + "bundeskanzlerin": "kanzlerin", + "kanzler": "bundeskanzlerin", + "kanzlerin": "bundeskanzlerin", + "waschweib": "waschmaschine", + "waschmaschine": "waschweib", + "sp\u00fclmaschine": "waschweib" + }, + "other_gender_swap": { + "formicula": "her", + "ihnen": "henne", + "harren": "ihre", + "ihre": "harren", + "lia": "her", + "ii": "sun", + "he": "ii", + "ihm": "ihnen", + "ihn": "formicula", + "sun": "ii", + "her": "ihre", + "henne": "ihre" + }, + "en_pronoun2gender": { + "they": [ + "homosexual", + "homosexuell", + "transgender", + "queer", + "homosexueller", + "transgeschlechtlich", + "bisexueller", + "homosexuelle" + ], + "he": [ + "kutt", + "kn\u00e4bchen", + "dandy", + "maskulin", + "m\u00e4nnlein", + "groom", + "bubi", + "fotzenknecht", + "boy", + "macker", + "youngster", + "isle_of_man", + "veit", + "guido", + "kn\u00e4blein", + "gv", + "m\u00e4nnchen", + "bub", + "weltmann", + "human", + "bursche", + "bube", + "gentleman", + "der_mann", + "man", + "little_boy", + "knabe", + "male", + "gaur", + "din\u00e9", + "fashion_victim", + "fant", + "chap", + "matz" + ], + "she": [ + "m\u00e4del", + "maiden", + "sch\u00f6nes_geschlecht", + "\u0436\u0435\u043d\u0441\u043a\u0438\u0439", + "matrone", + "miss", + "hausm\u00e4dchen", + "maid", + "kak", + "missa", + "vermissen", + "samica", + "bean", + "weib", + "lesbierin", + "abgeordnete", + "entbehren", + "gal", + "missen", + "dame", + "lesbisch", + "weibchen", + "fehlen", + "wicht", + "feminin", + "herrin", + "bike", + "schwaches_geschlecht", + "physikerin", + "lady", + "lola", + "girl", + "t\u00f6s", + "deern", + "weiblich", + "feme", + "mademoiselle", + "jungfer", + "verfehlen", + "vers\u00e4umen", + "verpassen", + "tochter", + "lesbe", + "griet", + "girlfriend", + "tribade", + "miss_a", + "madam", + "lesbier" + ] + }, + "en_pronoun2pronoun": { + "he": [ + "he", + "lia", + "ihm", + "seine", + "ihn", + "tij", + "his" + ], + "she": [ + "henne", + "sun", + "ihre", + "her" + ], + "they": [ + "harren", + "formicula", + "lia", + "ii", + "ihnen", + "ihre" + ], + "it": [ + "per_se", + "sich_selbst", + "dieser", + "diese", + "ces", + "bt", + "disse", + "it", + "its", + "dass", + "tann", + "dazu", + "dies", + "derjenige", + "von_allein", + "these", + "hasin", + "quest", + "von_selbst", + "d\u00fcse", + "that" + ] + }, + "en_pronoun2title": {}, + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/dk.json b/data_tooling/pii_processing/ontology/data/dk.json new file mode 100644 index 0000000..08a398b --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/dk.json @@ -0,0 +1,1122 @@ +{ + "ner_regexes": [ + [ + "PERSON", + "\\D+ \\D+|\\D+ \\D+|\\D+ \\D+|\\D+ \\D+|\\D+ \\D+-\\D+|\\D+ \\D+|\\D+ \\D+|\\D+ \\D+|\\D+ \\D+|\\D+ \\D+-\\D+|\\D+ \\D+ \\D+|\\D+ \\D+ \\D+|\\D+ \\D+ \\D+|\\D+ \\D+ \\D+", + false, + [] + ] + ], + "FIRST_NAME_FEMALE": [ + "cirkeline", + "herdis", + "liva", + "marlene", + "nanna", + "amalie", + "solveig", + "astrid", + "erna", + "bettina", + "regitse", + "conny", + "zenia", + "elna", + "sara", + "malou", + "carina", + "elsebeth", + "hannah", + "natasha", + "olga", + "camilla", + "rebecca", + "margrethe", + "hanne", + "emily", + "janne", + "gitte", + "lona", + "inga", + "berta", + "paulina", + "lea", + "thea", + "karin", + "kirstine", + "marie", + "olivia", + "signe", + "birte", + "grete", + "gerda", + "pernille", + "kristina", + "mille", + "yrsa", + "cecilie", + "sussie", + "margit", + "pia", + "sofie", + "maria", + "birgit", + "kirsten", + "zahra", + "tine", + "mathilde", + "sophie", + "annette", + "dorthe", + "klara", + "sandra", + "yda", + "jasmin", + "sanne", + "janni", + "s\u00f8s", + "viola", + "inge", + "justina", + "birthe", + "nanni", + "filippa", + "sine", + "jannie", + "joan", + "anna", + "maren", + "ingrid", + "tove", + "sille", + "anne", + "victoria", + "helle", + "emilie", + "silje", + "gyda", + "dagny", + "ragna", + "mette", + "laura", + "lene", + "asta", + "merete", + "line", + "jean", + "ditte", + "carla", + "annemette", + "karina", + "lone", + "susanne", + "grethe", + "anette", + "frederikke", + "bitten", + "daniella", + "julie", + "inger", + "heidi", + "ane", + "agnete", + "katja", + "maiken", + "rosa", + "vivian", + "winnie", + "ruth", + "doris", + "selma", + "ragnhild", + "zelma", + "agnes", + "simone", + "winni", + "lena", + "charlotte", + "andrea", + "mie", + "nora", + "dagmar", + "yasmin", + "mimi", + "helen", + "ella", + "josefine", + "bodil", + "britt", + "odeline", + "naja", + "trine", + "connie", + "ida", + "regitze", + "cathrine", + "ursula", + "malene", + "ester", + "maya", + "jenny", + "josephine", + "nina", + "gundhild", + "nicoline", + "michelle", + "tammy", + "sonja", + "sarah", + "elisabeth", + "benedikte", + "britta", + "oda", + "ingelise", + "tanja", + "stina", + "esmarelda", + "caroline", + "sigrid", + "weena", + "catrine", + "rita", + "kristine", + "gunhild", + "bente", + "odette", + "jytte", + "abelone", + "majken", + "henriette", + "leonora", + "johanne", + "michala", + "xenia", + "amanda", + "maja", + "birgitte", + "beth", + "dina", + "ronja", + "zara", + "\u00e5se", + "christine", + "natasja", + "gurli", + "minna", + "isabella", + "ellen", + "l\u00e6rke", + "sabine", + "emma", + "sussanne", + "marianne", + "irma", + "ulrike", + "lotte", + "iben", + "merethe", + "elin", + "karla", + "ritt", + "yvonne", + "frida", + "rikke", + "benedicte", + "solvej", + "zehnia", + "benthe", + "jonna", + "freja", + "berit", + "nete", + "jacqueline", + "karoline", + "vera", + "dorte", + "alma", + "tina", + "katrine", + "jacobine", + "stine", + "karen", + "ofelia", + "louise", + "paula", + "s\u00f8rine", + "alberte", + "patricia", + "christina", + "edith", + "gertrud", + "ulla", + "nadia", + "sofia", + "mia", + "katcha", + "randi", + "sys", + "clara", + "else", + "nana", + "tilde", + "kirstin" + ], + "FIRST_NAME_MALE": [ + "valdemar", + "kenneth", + "jacob", + "sonny", + "steen", + "frans", + "einer", + "herman", + "klaus", + "esben", + "christoffer", + "jim", + "karlo", + "dennis", + "joakim", + "benjamin", + "ragnar", + "\u00f8vli", + "klavs", + "jesper", + "nick", + "jonathan", + "tejs", + "stephan", + "georg", + "rasmus", + "b\u00f8je", + "peter", + "noah", + "niels", + "jens", + "johnnie", + "lucas", + "ronni", + "anders", + "carlo", + "daniel", + "\u00f8ystein", + "steve", + "uffe", + "johannes", + "carl", + "alvin", + "bobby", + "tobias", + "laus", + "alexander", + "oscar", + "ziggy", + "alf", + "nicklas", + "ove", + "casper", + "magnus", + "kristian", + "karsten", + "einar", + "bertram", + "gorm", + "mikkel", + "alex", + "laurits", + "bob", + "jano", + "hugo", + "andreas", + "peder", + "henry", + "borris", + "mikael", + "john", + "oliver", + "\u00e5bj\u00f8rn", + "jakob", + "clavs", + "keld", + "ludvig", + "tage", + "mogens", + "kim", + "ulf", + "\u00f8jvind", + "hans", + "s\u00f8ren", + "herbert", + "kurt", + "ron", + "george", + "jean", + "claus", + "flemming", + "emil", + "helge", + "james", + "jarl", + "lennarth", + "ebbe", + "johnny", + "j\u00f8rgen", + "elias", + "ruben", + "anton", + "julius", + "lars", + "mark", + "gert", + "jack", + "carsten", + "jimmy", + "palle", + "villads", + "marius", + "ragner", + "bo", + "timmy", + "freddy", + "ronny", + "allan", + "troels", + "jan", + "christian", + "arne", + "hjalte", + "mike", + "\u00f8yvind", + "verner", + "aksel", + "kaspar", + "ken", + "vagn", + "matthias", + "leif", + "mads", + "paul", + "jon", + "marcus", + "sten", + "silas", + "tim", + "stig", + "nils", + "finn", + "william", + "bent", + "preben", + "ib", + "nicolai", + "otto", + "johan", + "kasper", + "benny", + "per", + "martin", + "mik", + "philip", + "oskar", + "ole", + "gustav", + "tommy", + "\u00f8ivind", + "morten", + "osvald", + "curt", + "henrik", + "iver", + "lasse", + "asger", + "eric", + "steven", + "torben", + "olfert", + "yannick", + "nicolaj", + "andr\u00e9", + "aage", + "adam", + "jeppe", + "malthe", + "paw", + "robin", + "nikolaj", + "holger", + "simon", + "rolf", + "richardt", + "richard", + "joachim", + "sebastian", + "ernst", + "svenning", + "bertil", + "ulrik", + "kjeld", + "mathias", + "tonny", + "zacharias", + "gunnar", + "david", + "werner", + "boris", + "birger", + "boe", + "k\u00e5re", + "gunner", + "pete", + "kenn", + "frede", + "frode", + "\u00e5ge", + "stefan", + "yan", + "nikolai", + "robert", + "poul", + "thomas", + "b\u00f8rge", + "ronnie", + "dan", + "\u00f8rni", + "ivan", + "erik", + "ugust", + "frank", + "rune", + "danny", + "brian", + "christopher", + "erling", + "jonas", + "kenny", + "sam", + "yngve", + "frederik", + "ren\u00e9", + "tom", + "albert", + "victor", + "michael", + "bruno", + "bjarne", + "laust", + "patrick", + "kent", + "karl" + ], + "PREFIX_FEMALE": [ + "dr", + "fru", + "univ.prof", + "prof" + ], + "PREFIX_MALE": [ + "hr", + "dr", + "univ.prof", + "prof" + ], + "FIRST_NAME": [ + "valdemar", + "regitse", + "solveig", + "bettina", + "erna", + "hannah", + "malou", + "elsebeth", + "natasha", + "benjamin", + "inga", + "b\u00f8je", + "thea", + "peter", + "karin", + "niels", + "grete", + "birte", + "anders", + "mille", + "maria", + "annette", + "tobias", + "laus", + "sandra", + "ziggy", + "yda", + "s\u00f8s", + "justina", + "birthe", + "nanni", + "ingrid", + "gorm", + "joan", + "sille", + "anne", + "henry", + "\u00e5bj\u00f8rn", + "emilie", + "dagny", + "keld", + "tage", + "line", + "jean", + "james", + "grethe", + "lone", + "annemette", + "ane", + "winnie", + "selma", + "ragnhild", + "zelma", + "gert", + "winni", + "jimmy", + "charlotte", + "andrea", + "mie", + "marius", + "ragner", + "yasmin", + "mimi", + "jan", + "britt", + "aksel", + "verner", + "ken", + "connie", + "leif", + "mads", + "jon", + "malene", + "bent", + "preben", + "josephine", + "nina", + "gundhild", + "per", + "michelle", + "sonja", + "tommy", + "tanja", + "caroline", + "morten", + "weena", + "curt", + "bente", + "paw", + "adam", + "jeppe", + "abelone", + "holger", + "simon", + "zara", + "richardt", + "christine", + "ellen", + "l\u00e6rke", + "sussanne", + "werner", + "irma", + "lotte", + "birger", + "boe", + "karla", + "k\u00e5re", + "pete", + "rikke", + "frede", + "benedicte", + "\u00e5ge", + "stefan", + "jonna", + "berit", + "yan", + "nete", + "jacqueline", + "b\u00f8rge", + "frank", + "stine", + "paula", + "sam", + "patricia", + "ren\u00e9", + "mia", + "tom", + "bjarne", + "randi", + "laust", + "nana", + "tilde", + "kirstin", + "liva", + "herdis", + "marlene", + "sonny", + "amalie", + "astrid", + "conny", + "einer", + "herman", + "carina", + "christoffer", + "olga", + "karlo", + "camilla", + "dennis", + "rebecca", + "klavs", + "stephan", + "jonathan", + "georg", + "lea", + "kirstine", + "rasmus", + "noah", + "pernille", + "carlo", + "daniel", + "cecilie", + "sussie", + "uffe", + "steve", + "birgit", + "mathilde", + "sophie", + "alvin", + "klara", + "oscar", + "janni", + "sanne", + "alf", + "nicklas", + "casper", + "filippa", + "jannie", + "laurits", + "einar", + "alex", + "bob", + "victoria", + "peder", + "helle", + "mikael", + "oliver", + "john", + "mette", + "ragna", + "laura", + "hans", + "herbert", + "s\u00f8ren", + "ron", + "george", + "susanne", + "anette", + "lennarth", + "bitten", + "julie", + "katja", + "julius", + "maiken", + "vivian", + "mark", + "villads", + "bo", + "ella", + "freddy", + "christian", + "arne", + "odeline", + "naja", + "\u00f8yvind", + "sten", + "finn", + "otto", + "johan", + "kasper", + "mik", + "elisabeth", + "oda", + "gustav", + "catrine", + "rita", + "asger", + "jytte", + "malthe", + "leonora", + "beth", + "rolf", + "dina", + "ronja", + "richard", + "\u00e5se", + "sebastian", + "kjeld", + "minna", + "tonny", + "sabine", + "gunnar", + "marianne", + "iben", + "merethe", + "frida", + "kenn", + "thomas", + "poul", + "ronnie", + "karoline", + "vera", + "jacobine", + "rune", + "brian", + "erling", + "christina", + "frederik", + "gertrud", + "ulla", + "nadia", + "sofia", + "michael", + "sys", + "patrick", + "else", + "karl", + "kenneth", + "jacob", + "zenia", + "elna", + "klaus", + "sara", + "margrethe", + "hanne", + "joakim", + "ragnar", + "janne", + "jesper", + "lona", + "berta", + "lucas", + "olivia", + "signe", + "gerda", + "yrsa", + "kirsten", + "johannes", + "carl", + "dorthe", + "alexander", + "jasmin", + "viola", + "inge", + "mikkel", + "bertram", + "anna", + "hugo", + "andreas", + "silje", + "gyda", + "ludvig", + "lene", + "asta", + "merete", + "\u00f8jvind", + "claus", + "flemming", + "emil", + "carla", + "jarl", + "ebbe", + "johnny", + "rosa", + "ruth", + "lars", + "jack", + "dagmar", + "helen", + "ronny", + "josefine", + "bodil", + "troels", + "mike", + "matthias", + "paul", + "silas", + "tim", + "ursula", + "ester", + "maya", + "jenny", + "ib", + "nicoline", + "nicolai", + "sarah", + "tammy", + "philip", + "benedikte", + "oskar", + "britta", + "ingelise", + "sigrid", + "osvald", + "iver", + "torben", + "eric", + "gunhild", + "steven", + "yannick", + "henriette", + "nikolaj", + "michala", + "joachim", + "svenning", + "natasja", + "bertil", + "gurli", + "ulrik", + "mathias", + "emma", + "zacharias", + "david", + "boris", + "frode", + "benthe", + "nikolai", + "dorte", + "tina", + "alma", + "ivan", + "erik", + "ugust", + "jonas", + "s\u00f8rine", + "victor", + "cirkeline", + "nanna", + "steen", + "frans", + "esben", + "jim", + "emily", + "\u00f8vli", + "gitte", + "nick", + "tejs", + "paulina", + "marie", + "jens", + "johnnie", + "ronni", + "kristina", + "\u00f8ystein", + "margit", + "sofie", + "pia", + "zahra", + "tine", + "bobby", + "ove", + "kristian", + "magnus", + "karsten", + "sine", + "maren", + "tove", + "jano", + "borris", + "jakob", + "clavs", + "kim", + "mogens", + "ulf", + "kurt", + "helge", + "ditte", + "karina", + "frederikke", + "daniella", + "j\u00f8rgen", + "elias", + "ruben", + "inger", + "heidi", + "anton", + "agnete", + "doris", + "agnes", + "carsten", + "simone", + "lena", + "palle", + "nora", + "allan", + "timmy", + "hjalte", + "kaspar", + "trine", + "vagn", + "regitze", + "cathrine", + "ida", + "marcus", + "stig", + "nils", + "william", + "benny", + "martin", + "ole", + "\u00f8ivind", + "stina", + "esmarelda", + "henrik", + "lasse", + "kristine", + "olfert", + "odette", + "nicolaj", + "andr\u00e9", + "aage", + "majken", + "johanne", + "robin", + "maja", + "xenia", + "amanda", + "birgitte", + "ernst", + "isabella", + "ulrike", + "elin", + "gunner", + "ritt", + "yvonne", + "solvej", + "zehnia", + "freja", + "robert", + "dan", + "\u00f8rni", + "katrine", + "danny", + "christopher", + "karen", + "ofelia", + "louise", + "kenny", + "alberte", + "yngve", + "edith", + "katcha", + "albert", + "bruno", + "clara", + "kent" + ], + "LAST_NAME": [ + "berg", + "kristensen", + "christensen", + "christiansen", + "johansen", + "eriksen", + "nilsson", + "lauritsen", + "olesen", + "holst", + "simonsen", + "knudsen", + "karlsen", + "klausen", + "s\u00f8rensen", + "danielsen", + "bertelsen", + "henriksen", + "mogensen", + "svendsen", + "kj\u00e6r", + "jakobsen", + "koch", + "bech", + "lassen", + "laursen", + "schou", + "steffensen", + "s\u00f8ndergaard", + "mikkelsen", + "skov", + "\u00f8stergaard", + "brandt", + "jespersen", + "poulsen", + "gregersen", + "jensen", + "paulsen", + "frandsen", + "lund", + "lind", + "mathiasen", + "schultz", + "kjeldsen", + "dahl", + "thorsen", + "pedersen", + "holm", + "vestergaard", + "christoffersen", + "andresen", + "overgaard", + "jessen", + "andreasen", + "clausen", + "thomsen", + "dam", + "larsen", + "jepsen", + "nielsen", + "toft", + "j\u00f8rgensen", + "hermansen", + "carlsen", + "thygesen", + "krogh", + "mortensen", + "lauridsen", + "bruun", + "mathiesen", + "n\u00f8rgaard", + "kristoffersen", + "friis", + "schmidt", + "olsen", + "frederiksen", + "andersen", + "ravn", + "winther", + "iversen", + "bach", + "rasmussen", + "madsen", + "petersen", + "m\u00f8ller", + "hansen", + "jeppesen", + "jacobsen", + "kristiansen", + "nissen", + "johnsen" + ], + "LAST_NAME_MALE": [], + "LAST_NAME_FEMALE": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": {}, + "other_gender_swap": {}, + "en_pronoun2gender": {}, + "en_pronoun2pronoun": {}, + "en_pronoun2title": {}, + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/dlm.json b/data_tooling/pii_processing/ontology/data/dlm.json new file mode 100644 index 0000000..96bd9d9 --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/dlm.json @@ -0,0 +1,82 @@ +{ + "ORG": [ + "doi" + ], + "LOCATION": [ + "cuomp" + ], + "JOB": [ + "depentaur", + "pentaur", + "burbur", + "pascu" + ], + "EVENT": [ + "desmissur" + ], + "ANIMAL": [ + "miarla" + ], + "PUBLIC_FIGURE": [ + "e" + ], + "DISEASE": [ + "morscuor", + "moscuar", + "aura", + "tormiant" + ], + "TITLE": [ + "sinaur" + ], + "FAC": [ + "plaza" + ], + "PLANT": [ + "nochiera" + ], + "RELIGION_MEMBER": [ + "jain", + "frutro" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "femia": "muosclo", + "saur": "frutro", + "seraur": "frutro", + "mulir": "marait", + "molier": "marait", + "mojer": "marait" + }, + "other_gender_swap": { + "jal": "jale" + }, + "en_pronoun2gender": { + "he": [ + "muosclo" + ], + "she": [ + "femia" + ] + }, + "en_pronoun2pronoun": { + "he": [ + "jal" + ], + "they": [ + "jale", + "jali" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/dsb.json b/data_tooling/pii_processing/ontology/data/dsb.json new file mode 100644 index 0000000..1a5c1b9 --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/dsb.json @@ -0,0 +1,163 @@ +{ + "ANIMAL": [ + "karwona", + "rapak", + "\u0161krodawa", + "kohlica", + "grampak", + "morska_swinka", + "kanja", + "pa\u0161turlica", + "rybornik", + "ryborak", + "rybarnik", + "burunduk" + ], + "LANGUAGE": [ + "hindi\u0161\u0107ina", + "esperanto" + ], + "DISEASE": [ + "zarz", + "hungor" + ], + "PUBLIC_FIGURE": [ + "sherry", + "w", + "jurij", + "a", + "steward", + "o", + "jaden", + "putin", + "frank" + ], + "RELIGION_MEMBER": [ + "protestant", + "brat\u0161" + ], + "JOB": [ + "stewardes", + "kral", + "leutnant", + "stewardesa", + "samostatny", + "ch\u00f3rgojnik", + "radny", + "duchta\u0155", + "man", + "stotnik", + "kralik", + "steward" + ], + "SOC_ECO_CLASS": [ + "ma\u0142o" + ], + "RACE": [ + "turk" + ], + "PERSON_PRONOUN": [ + "na\u0161", + "we", + "naju", + "my" + ], + "FAC": [ + "dw\u00f3rni\u0161\u0107o" + ], + "PRODUCT": [ + "nowoseelandska" + ], + "GENDER": [ + "samica", + "man" + ], + "FOOD": [ + "limonada" + ], + "PLANT": [ + "jawor", + "serbowka", + "marchwej", + "rotwica" + ], + "ORG": [ + "cerwjene_m\u00f3rjo", + "nordrhein_westfalska" + ], + "LOCATION": [ + "za_kulisami" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "\u017aowka": "son", + "policistka": "policaj", + "w\u00f3na": "w\u00f3n", + "sot\u0161a": "brat\u0161", + "stewardesa": "steward", + "\u017eona": "c\u0142owjek", + "\u017ee\u0144ska": "mu\u017e", + "g\u00f3lc": "\u017aow\u0107o" + }, + "other_gender_swap": { + "jeju": "jej", + "jich": "jeje", + "nich": "jeje", + "n\u011b": "jeje", + "w\u00f3ni": "w\u00f3na", + "w\u00f3n": "w\u00f3ni", + "jomu": "nich", + "w\u00f3na": "w\u00f3ni", + "jej": "jeju", + "jeje": "jeju" + }, + "en_pronoun2gender": { + "he": [ + "c\u0142owjek", + "mu\u017e", + "g\u00f3lc", + "man" + ], + "she": [ + "\u017aow\u0107o", + "samica", + "kn\u011b\u017ena", + "\u017eona", + "\u017ee\u0144ska" + ] + }, + "en_pronoun2pronoun": { + "he": [ + "jomu", + "w\u00f3n" + ], + "she": [ + "w\u00f3na", + "jej", + "jeje" + ], + "they": [ + "n\u011b", + "jeju", + "jej", + "nich", + "jich", + "w\u00f3ni" + ], + "it": [ + "a\u017e", + "w\u00f3no" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/dv.json b/data_tooling/pii_processing/ontology/data/dv.json new file mode 100644 index 0000000..13658d6 --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/dv.json @@ -0,0 +1,36 @@ +{ + "GPE": [ + "\u0783\u07a6\u078c\u07b0\u0786\u07a6\u0782\u0791\u07aa" + ], + "PRODUCT": [ + "\u0782\u07a8\u0787\u07aa\u0792\u07a8\u078d\u07ad\u0782\u07b0\u0791\u07aa" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "\u0789\u07a6\u0782\u0789\u07a6": "\u0784\u07a6\u0787\u07b0\u0795\u07a6", + "\u0786\u07ae\u0787\u07b0\u0786\u07ae": "\u0784\u07ad\u0784\u07ac", + "\u078b\u07a6\u0787\u07b0\u078c\u07a6": "\u0784\u07ad\u0784\u07ac" + }, + "other_gender_swap": {}, + "en_pronoun2gender": { + "she": [ + "\u0787\u07a6\u0782\u07b0\u0780\u07ac\u0782\u07b0\u0789\u07a9\u0780\u07a7" + ] + }, + "en_pronoun2pronoun": { + "they": [ + "\u0787\u07ac_\u0789\u07a9\u0780\u07aa\u0782\u07b0" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/ee.json b/data_tooling/pii_processing/ontology/data/ee.json new file mode 100644 index 0000000..f82baa4 --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/ee.json @@ -0,0 +1,76 @@ +{ + "RELIGION_MEMBER": [ + "yudat\u0254" + ], + "LANGUAGE": [ + "helat\u0254", + "fransegbe" + ], + "JOB": [ + "atikew\u0254la", + "avul\u00e9la" + ], + "DISEASE": [ + "nyatsu", + "mi" + ], + "PUBLIC_FIGURE": [ + "yakob" + ], + "ANIMAL": [ + "afia", + "koklo", + "koklovi" + ], + "LOCATION": [ + "ga_wuieve", + "eden_b\u0254" + ], + "PLANT": [ + "ga_wui\u0256eka", + "ga_ene" + ], + "FOOD": [ + "ga_at\u0254\u0303" + ], + "ORG": [ + "mi", + "ga_adre", + "ga_ewo" + ], + "PRODUCT": [ + "nubabla_yeye" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "t\u0254gbuiy\u0254viny\u0254nu": "t\u0254gbuiy\u0254vi\u014butsu", + "kpovit\u0254ny\u0254nu": "kpovit\u0254\u014butsu", + "n\u0254viny\u0254nu": "n\u0254vi\u014butsu" + }, + "other_gender_swap": {}, + "en_pronoun2gender": { + "she": [ + "ny\u0254nuvi", + "ny\u0254nu" + ] + }, + "en_pronoun2pronoun": { + "he": [ + "eya" + ], + "she": [ + "eya" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/egl.json b/data_tooling/pii_processing/ontology/data/egl.json new file mode 100644 index 0000000..a069e10 --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/egl.json @@ -0,0 +1,34 @@ +{ + "ANIMAL": [ + "curn\u00e0cia" + ], + "DISEASE": [ + "brun\u015b\u014dl", + "sgaram\u00f2ffia" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": {}, + "other_gender_swap": {}, + "en_pronoun2gender": { + "she": [ + "d\u00f2na" + ] + }, + "en_pronoun2pronoun": { + "it": [ + "st\u00e9", + "taj" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/el.json b/data_tooling/pii_processing/ontology/data/el.json new file mode 100644 index 0000000..68ef701 --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/el.json @@ -0,0 +1,4485 @@ +{ + "PUBLIC_FIGURE": [ + 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"\u03c3\u03b5_\u03c0\u03b5\u03c1\u03b9\u03c0\u03c4\u03c9\u03c3\u03b7" + ], + "DISEASE": [ + "\u03ba\u03bf\u03b9\u03bd\u03cc_\u03ba\u03c1\u03c5\u03bf\u03bb\u03cc\u03b3\u03b7\u03bc\u03b1", + "\u03bc\u03b1\u03c3\u03c4\u03b9\u03c4\u03b9\u03c3", + "\u03b1\u03b3\u03bf\u03c1\u03b1\u03c6\u03bf\u03b2\u03af\u03b1", + "\u03bc\u03b1\u03c3\u03c4\u03af\u03c4\u03b9\u03b4\u03b1", + "\u03bf\u03b4\u03bf\u03bd\u03c4\u03b1\u03bb\u03b3\u03b9\u03b1", + "\u03bb\u03b5\u03c5\u03ba\u03b7", + "\u03ba\u03b1\u03c1\u03b4\u03b9\u03bf\u03c0\u03b1\u03b8\u03b5\u03b9\u03b1", + "\u03bc\u03b1\u03c5\u03c1\u03b9\u03b6\u03c9", + "\u03bd\u03b1\u03c5\u03c4\u03b9\u03b1", + "\u03b1\u03b3\u03b3\u03b5\u03b9\u03c9\u03bc\u03b1", + "\u03bf\u03b9\u03ba\u03bf\u03b4\u03bf\u03bc\u03b7\u03c3\u03b7", + "\u03c4\u03c1\u03b9\u03c3\u03ba\u03b1\u03b9\u03b4\u03b5\u03ba\u03b1\u03c6\u03bf\u03b2\u03b9\u03b1", + "\u03b1\u03c0\u03bf\u03c3\u03c4\u03b7\u03bc\u03b1", + "\u03b3\u03b1\u03bb\u03b1\u03ba\u03c4\u03bf\u03b6\u03b1\u03b9\u03bc\u03af\u03b1", + "\u03bc\u03b5\u03bb\u03b1\u03bd\u03c9\u03bc\u03b1", + "\u03ba\u03b1\u03c3\u03c4\u03b1\u03bd\u03bf\u03c3", + "\u03c0\u03c1\u03b5\u03c3\u03b2\u03c5\u03c9\u03c0\u03b9\u03b1", + "\u03ba\u03bf\u03c4\u03c3\u03b1\u03bd\u03b9", + "\u03b4\u03b9\u03b1\u03c6\u03c1\u03b1\u03b3\u03bc\u03b1\u03c4\u03bf\u03ba\u03ae\u03bb\u03b7", + "\u03b1\u03bc\u03c5\u03b3\u03b4\u03b1\u03bb\u03af\u03c4\u03b9\u03b4\u03b1", + "\u03ba\u03bf\u03ba\u03ba\u03cd\u03c4\u03b7\u03c3", + "\u03bc\u03b1\u03bd\u03b9\u03bf\u03ba\u03b1\u03c4\u03b1\u03b8\u03bb\u03b9\u03c8\u03b7", + "\u03b8\u03b5\u03bc\u03b5\u03bb\u03b9\u03c9\u03c4\u03b7\u03c3", + "\u03b5\u03c1\u03c5\u03c3\u03b9\u03c0\u03b5\u03bb\u03b1\u03c3", + "\u03bc\u03c5\u03bf\u03ba\u03b1\u03c1\u03b4\u03b9\u03c4\u03b9\u03b4\u03b1", + "\u03c3\u03c4\u03c1\u03b1\u03b2\u03b9\u03c3\u03bc\u03bf\u03c3", + "stenos", + "\u03c3\u03ba\u03bf\u03c5\u03c1\u03b9\u03b1", + "\u03b3\u03c5\u03bd\u03b1\u03b9\u03ba\u03bf\u03bc\u03b1\u03c3\u03c4\u03b9\u03b1", + "\u03b6\u03b1\u03c7\u03b1\u03c1\u03bf", + "gimp", + "\u03bc\u03bf\u03c5\u03c1\u03bc\u03bf\u03c5\u03c1\u03b7\u03c4\u03bf", + "\u03c4\u03bf_\u03ba\u03b5\u03bd\u03c4\u03c1\u03af", + "\u03ba\u03b1\u03c3\u03c4\u03b1\u03bd\u03b9\u03ac", + "smart", + "\u03c7\u03b3", + "\u03ba\u03b1\u03c1\u03b4\u03b9\u03bf\u03c7\u03c4\u03c5\u03c0\u03b9", + "\u03ba\u03bf\u03ba\u03ba\u03b9\u03bd\u03b9\u03c3\u03bc\u03b1", + "\u03ba\u03bf\u03bc\u03bc\u03b5\u03bd\u03bf\u03c3", + "\u03b9\u03b4\u03c1\u03c5\u03c4\u03b7\u03c3", + "\u03c0\u03c1\u03bf\u03b5\u03ba\u03bb\u03b1\u03bc\u03c8\u03b9\u03b1", + "\u03b1\u03b9\u03bb\u03bf\u03c5\u03c1\u03bf\u03c6\u03bf\u03b2\u03b9\u03b1", + "\u03b9\u03b4\u03b9\u03bf\u03c0\u03b1\u03b8\u03b5\u03b9\u03b1", + "\u03b1\u03ba\u03c4\u03b9\u03bd\u03bf\u03b2\u03bf\u03bb\u03af\u03b1", + "\u03b5\u03c0\u03b9\u03c3\u03c4\u03b1\u03be\u03b7", + "\u03ba\u03bf\u03ba\u03ba\u03c5\u03c4\u03b7\u03c3", + "\u03b5\u03bd\u03b4\u03bf\u03ba\u03b1\u03c1\u03b4\u03af\u03c4\u03b9\u03b4\u03b1", + "\u03c4\u03b1\u03c7\u03c5\u03ba\u03b1\u03c1\u03b4\u03b9\u03b1", + "\u03c7\u03b9\u03bf\u03bd\u03b9\u03c3\u03c4\u03c1\u03b1", + "\u03b8\u03b1\u03bd\u03b1\u03c4\u03bf\u03c6\u03bf\u03b2\u03b9\u03b1", + "\u03b1\u03c3\u03b8\u03ad\u03bd\u03b5\u03b9\u03b1_\u03b9\u03bf\u03cd_\u03ad\u03bc\u03c0\u03bf\u03bb\u03b1", + "\u03bb\u03b5\u03c5\u03ba\u03bf\u03c0\u03b1\u03b8\u03b5\u03b9\u03b1", + "\u03bb\u03b5\u03c0\u03c4\u03bf\u03c3\u03c0\u03b5\u03af\u03c1\u03c9\u03c3\u03b7", + "\u03b1\u03b3\u03bf\u03c1\u03b1\u03c6\u03bf\u03b2\u03b9\u03b1", + "\u03b9\u03c7\u03b8\u03cd\u03b1\u03c3\u03b7", + "\u03b4\u03b4\u03b1", + "\u03b2\u03b1\u03ba\u03c4\u03b7\u03c1\u03b9\u03bf\u03c6\u03b1\u03b3\u03bf\u03c3", + "\u03ba\u03bb\u03b5\u03b9\u03c3\u03c4\u03bf\u03c6\u03bf\u03b2\u03b9\u03b1", + "\u03b3\u03bb\u03b1\u03c5\u03ba\u03c9\u03bc\u03b1", + "\u03b5\u03c0\u03b9\u03c3\u03c4\u03b1\u03b6\u03c9", + "\u03b1\u03bc\u03c6\u03b9\u03b2\u03bb\u03b7\u03c3\u03c4\u03c1\u03bf\u03b5\u03b9\u03b4\u03b9\u03c4\u03b9\u03b4\u03b1" + ], + "JOB": [ + "\u03b9\u03b5\u03c1\u03b1\u03c1\u03c7\u03b7\u03c3", + "\u03ba\u03bf\u03bb\u03b9\u03b3\u03b1\u03c3", + "\u03b1\u03b3\u03b1\u03bb\u03bc\u03b1\u03c4\u03bf\u03c0\u03bf\u03b9\u03bf\u03c3", + "\u03c0\u03b1\u03c1\u03b1\u03c7\u03b1\u03c1\u03b1\u03ba\u03c4\u03b7\u03c3", + "\u03ba\u03b1\u03c4\u03b1\u03c0\u03bf\u03bd\u03c4\u03b9\u03b6\u03bf\u03bc\u03b1\u03b9", + "\u03b1\u03bb\u03b5\u03be\u03b9\u03c0\u03c4\u03c9\u03c4\u03b9\u03c3\u03c4\u03c1\u03b9\u03b1", + "\u03b4\u03b9\u03b1\u03ba\u03bf\u03bd\u03b9\u03c3\u03c3\u03b1", + "\u03c0\u03c1\u03c9\u03c4\u03bf\u03c3\u03c5\u03b3\u03ba\u03b5\u03bb\u03bb\u03bf\u03c3", + "\u03ba\u03b1\u03b8\u03b1\u03c1\u03b9\u03c3\u03c4\u03c1\u03b9\u03b1", + "\u03c0\u03b1\u03b8\u03bf\u03bb\u03bf\u03b3\u03bf\u03b1\u03bd\u03b1\u03c4\u03bf\u03bc\u03bf\u03c3", + "\u03c3\u03c4\u03c1\u03b1\u03c4\u03b1\u03c1\u03c7\u03b7\u03c3", + "hydrologos", + "the_police", + "\u03b5\u03c0\u03b9\u03c0\u03bb\u03bf\u03c0\u03bf\u03b9\u03bf\u03c3", + "\u03b5\u03ba\u03ba\u03bb\u03b7\u03c3\u03b1\u03c1\u03b7\u03c3", + "\u03b1\u03b9\u03bc\u03b1\u03c4\u03bf\u03bb\u03bf\u03b3\u03bf\u03c3", + "\u03b3\u03c5\u03bd\u03b1\u03b9\u03ba\u03bf\u03bb\u03bf\u03b3\u03bf\u03c3", + "\u03b1\u03bd\u03b5\u03be\u03b1\u03c1\u03c4\u03b7\u03c4\u03bf\u03c3", + "gentleman", + "\u03ba\u03b1\u03c4\u03b1\u03c3\u03ba\u03b5\u03c5\u03b1\u03b6\u03c9", + "\u03b8\u03b1\u03bb\u03b1\u03c3\u03c3\u03b9\u03bf\u03c3", + "\u03b1\u03bd\u03bf\u03c1\u03b8\u03c9\u03c4\u03b7\u03c3", + "\u03c3\u03c4\u03c1\u03b1\u03c4\u03b7\u03b3\u03bf\u03c3", + "\u03b5\u03ba\u03c0\u03b1\u03b9\u03b4\u03b5\u03c5\u03c4\u03b7\u03c3", + "\u03c5\u03c0\u03bf\u03c3\u03c4\u03c1\u03b1\u03c4\u03b7\u03b3\u03bf\u03c3", + "\u03b3\u03b5\u03c1\u03b1\u03ba\u03b1\u03c1\u03b7\u03c3", + "\u03ba\u03c5\u03b2\u03b5\u03c1\u03bd\u03b7\u03c4\u03b7\u03c3", + "\u03c4\u03c1\u03b1\u03c5\u03bc\u03b1\u03c4\u03b9\u03bf\u03c6\u03bf\u03c1\u03b5\u03b1\u03c3", + "\u03b1\u03b3\u03bf\u03c1\u03b7\u03c4\u03c1\u03b9\u03b1", + "\u03b1\u03bd\u03b1\u03b9\u03c3\u03b8\u03b7\u03c3\u03b9\u03bf\u03bb\u03cc\u03b3\u03bf\u03c3", + "\u03c4\u03c1\u03b1\u03b3\u03bf\u03c5\u03b4\u03bf\u03c0\u03bf\u03b9\u03bf\u03c3", + "\u03c0\u03b1\u03b9\u03b4\u03b9\u03b1\u03c4\u03c1\u03bf\u03c3", + "\u03c0\u03b1\u03c1\u03b1\u03b4\u03bf\u03c5\u03bb\u03b5\u03c5\u03c4\u03c1\u03b1", + "\u03bc\u03b1\u03c1\u03b1\u03b3\u03ba\u03bf\u03c3", + "the_guardian", + "\u03b7_\u03b3\u03b1\u03bb\u03b1\u03c4\u03bf\u03cd", + "\u03ba\u03b1\u03bb\u03bb\u03b9\u03b3\u03c1\u03b1\u03c6\u03bf\u03c3", + "\u03bc\u03c5\u03b3\u03b1\u03ba\u03b9", + "mate", + "\u03c6\u03c1\u03bf\u03c5\u03c1\u03bf\u03c3", + "\u03c5\u03c0\u03b1\u03c1\u03c7\u03bf\u03c3", + "\u03c0\u03b1\u03c1\u03b1\u03bd\u03c5\u03bc\u03c6\u03bf\u03c3", + "\u03c6\u03c9\u03c4\u03bf\u03b3\u03c1\u03b1\u03c6\u03bf\u03c3", + "\u03c3\u03c0\u03b9\u03c4\u03bf\u03bd\u03bf\u03b9\u03ba\u03bf\u03ba\u03c5\u03c1\u03b7\u03c3", + "\u03b4\u03b5\u03c1\u03bc\u03b1\u03c4\u03bf\u03bb\u03bf\u03b3\u03bf\u03c3", + "\u03c5\u03c0\u03bf\u03c3\u03bc\u03b7\u03bd\u03b1\u03b3\u03bf\u03c3", + "\u03bc\u03b5\u03c3\u03b1\u03b6\u03c9\u03bd", + "\u03bf_\u03b5\u03bb\u03b1\u03c6\u03bf\u03ba\u03c5\u03bd\u03b7\u03b3\u03cc\u03c3", + "the_economist", + "\u03c5\u03c0\u03bf\u03c3\u03c4\u03c1\u03ac\u03c4\u03b7\u03b3\u03bf\u03c3", + "\u03b1\u03b3\u03bf\u03c1\u03b7\u03c4\u03b7\u03c3", + "\u03b5\u03b3\u03ba\u03b5\u03c6\u03b1\u03bb\u03b9\u03ba\u03cc_\u03b5\u03c0\u03b5\u03b9\u03c3\u03cc\u03b4\u03b9\u03bf", + "\u03c0\u03b1\u03c1\u03b1\u03c3\u03ba\u03b5\u03c5\u03b1\u03b6\u03c9", + "the_hangover", + "\u03b4\u03b1\u03c3\u03bf\u03c6\u03c5\u03bb\u03b1\u03ba\u03b1\u03c3", + "\u03c0\u03c1\u03bf\u03c0\u03bf\u03bd\u03b7\u03c4\u03ae\u03c3", + "\u03ba\u03b1\u03c0\u03bd\u03bf\u03b4\u03bf\u03c7\u03bf\u03ba\u03b1\u03b8\u03b1\u03c1\u03b9\u03c3\u03c4\u03b7\u03c3", + "\u03b5\u03bb\u03b5\u03c5\u03b8\u03b5\u03c1\u03bf\u03b5\u03c0\u03b1\u03b3\u03b3\u03b5\u03bb\u03bc\u03b1\u03c4\u03b9\u03b1\u03c3", + "\u03b1\u03c1\u03bc\u03b5\u03c7\u03c4\u03c1\u03b1", + "\u03b5\u03b9\u03c3\u03b1\u03b3\u03b3\u03b5\u03bb\u03ad\u03b1\u03c3", + "\u03ba\u03b5\u03c6\u03b1\u03bb\u03bf\u03b8\u03c1\u03b1\u03c5\u03c3\u03c4\u03b7\u03c3", + "\u03ba\u03b1\u03c1\u03b4\u03b9\u03bf\u03bb\u03bf\u03b3\u03bf\u03c3", + "\u03c3\u03ba\u03bf\u03c5\u03c0\u03b9\u03b4\u03b9\u03b1\u03c1\u03b7\u03c3", + "\u03c3\u03c4\u03c1\u03b1\u03c4\u03b9\u03c9\u03c4\u03b7\u03c3" + ], + "PRODUCT": [ + "\u03c4\u03bf_\u03ba\u03bf\u03bc\u03bc\u03bf\u03c5\u03bd\u03b9\u03c3\u03c4\u03b9\u03ba\u03cc_\u03bc\u03b1\u03bd\u03b9\u03c6\u03ad\u03c3\u03c4\u03bf", + "\u03b1\u03ba\u03c1\u03c9\u03c4\u03ae\u03c1\u03b9\u03bf_\u03c7\u03bf\u03c1\u03bd", + "\u03bf_\u03c0\u03bf\u03bb\u03b5\u03bc\u03bf\u03c3_\u03c4\u03c9\u03bd_\u03b1\u03c3\u03c4\u03c1\u03c9\u03bd", + "\u03c4\u03bf\u03c5_\u03b1\u03b3\u03b9\u03bf\u03c5_\u03c3\u03c4\u03b5\u03c6\u03b1\u03bd\u03bf\u03c5", + "\u03ac\u03b3\u03b9\u03bf_\u03c0\u03bd\u03b5\u03cd\u03bc\u03b1", + "al_jazeera", + "\u03bc\u03b7_\u03bc\u03b5_\u03bb\u03b7\u03c3\u03bc\u03bf\u03bd\u03b5\u03b9", + "\u03bf\u03b9_\u03c4\u03ad\u03c3\u03c3\u03b5\u03c1\u03b9\u03c3_\u03b5\u03c0\u03bf\u03c7\u03ad\u03c3", + "\u03bf_\u03c0\u03b1\u03c0\u03bf\u03c5\u03c4\u03c3\u03c9\u03bc\u03ad\u03bd\u03bf\u03c3_\u03b3\u03ac\u03c4\u03bf\u03c3", + "\u03c4\u03b9_\u03bd\u03b5\u03b1", + "\u03b7_\u03b1\u03c4\u03b9\u03bc\u03b1\u03c3\u03bc\u03ad\u03bd\u03b7", + "\u03bc\u03b5\u03c4\u03b1_\u03b8\u03b1\u03bd\u03b1\u03c4\u03bf\u03bd", + "\u03ac\u03b9_\u03b2\u03b1\u03c3\u03af\u03bb\u03b7\u03c3", + "\u03c7\u03c1\u03bf\u03bd\u03bf\u03bc\u03b7\u03c7\u03b1\u03bd\u03b7", + "\u03b4\u03b5\u03bd\u03b4\u03c1\u03bf_\u03c4\u03c9\u03bd_\u03c7\u03c1\u03b9\u03c3\u03c4\u03bf\u03c5\u03b3\u03b5\u03bd\u03bd\u03c9\u03bd", + "\u03c3\u03c4\u03bf_\u03c0\u03b1\u03c1\u03b1_\u03c0\u03b5\u03bd\u03c4\u03b5", + "\u03c4\u03bf_\u03c3\u03ba\u03c5\u03bb\u03af_\u03c4\u03c9\u03bd_\u03bc\u03c0\u03ac\u03c3\u03ba\u03b5\u03c1\u03b2\u03b9\u03bb", + "\u03b1\u03b4\u03b9\u03b5\u03be\u03bf\u03b4\u03bf\u03c3", + "\u03ba\u03bf\u03c5\u03ba\u03bb\u03bf\u03c3\u03c0\u03b9\u03c4\u03bf", + "\u03bf_\u03c0\u03cc\u03bb\u03b5\u03bc\u03bf\u03c3_\u03c4\u03c9\u03bd_\u03ac\u03c3\u03c4\u03c1\u03c9\u03bd", + "boxing_day", + "\u03c4\u03bf\u03c5_\u03c0\u03c1\u03b1\u03c3\u03b9\u03bd\u03bf\u03c5_\u03b1\u03ba\u03c1\u03c9\u03c4\u03b7\u03c1\u03b9\u03bf\u03c5", + "deutsche_welle", + "\u03ba\u03b1\u03b9\u03bd\u03b7_\u03b4\u03b9\u03b1\u03b8\u03b7\u03ba\u03b7", + "\u03b1\u03bd\u03c4\u03b9\u03b1\u03b5\u03c1\u03bf\u03c0\u03bf\u03c1\u03b9\u03ba\u03bf\u03c3", + "\u03bf_\u03ac\u03c1\u03c7\u03bf\u03bd\u03c4\u03b1\u03c3_\u03c4\u03c9\u03bd_\u03b4\u03b1\u03c7\u03c4\u03c5\u03bb\u03b9\u03b4\u03b9\u03ce\u03bd", + "\u03b7_\u03bc\u03b7\u03c7\u03b1\u03bd\u03ae_\u03c4\u03bf\u03c5_\u03c7\u03c1\u03cc\u03bd\u03bf\u03c5", + "\u03b1\u03ba\u03c1\u03c9\u03c4\u03b7\u03c1\u03b9\u03bf_\u03c7\u03bf\u03c1\u03bd", + "\u03b8\u03c1\u03b9\u03b1\u03bc\u03b2\u03b9\u03ba\u03ae_\u03b1\u03c8\u03af\u03b4\u03b1", + "\u03b2\u03c1\u03b1\u03c7\u03c5\u03ba\u03c5\u03ba\u03bb\u03c9\u03bc\u03b1" + ], + "PLANT": [ + "\u03c0\u03b1\u03bd\u03c4\u03b6\u03ac\u03c1\u03b9", + "\u03bc\u03bf\u03c5\u03c3\u03c4\u03ac\u03c1\u03b4\u03b1", + "\u03c6\u03c1\u03b1\u03b3\u03ba\u03bf\u03c3\u03c4\u03b1\u03c6\u03c5\u03bb\u03b9\u03b1", + "\u03ba\u03bf\u03c5\u03bd\u03bf\u03c5\u03c0\u03b9\u03b4\u03b9", + "\u03b2\u03c9\u03bb\u03af\u03c4\u03b7\u03c3_\u03bf_\u03b5\u03b4\u03ce\u03b4\u03b9\u03bc\u03bf\u03c3", + "\u03b5\u03c1\u03c5\u03b8\u03c1\u03b5\u03bb\u03ac\u03c4\u03b7", + "\u03c7\u03c1\u03b9\u03c3\u03c4\u03bf\u03c5\u03b3\u03b5\u03bd\u03bd\u03b9\u03b1\u03c4\u03b9\u03ba\u03bf_\u03b4\u03b5\u03bd\u03b4\u03c1\u03bf", + "\u03c0\u03b5\u03c1\u03b9\u03ba\u03bf\u03ba\u03bb\u03ac\u03b4\u03b1", + "\u03c0\u03bb\u03b1\u03c4\u03bf\u03bc\u03b1\u03bd\u03c4\u03b7\u03bb\u03b1", + "\u03c7\u03c1\u03c5\u03c3\u03b1\u03bd\u03b8\u03b5\u03bc\u03bf", + 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"\u03b1\u03bd\u03b8\u03c1\u03ce\u03c0\u03b9\u03bd\u03b1_\u03b4\u03b9\u03ba\u03b1\u03b9\u03ce\u03bc\u03b1\u03c4\u03b1", + "\u03b1\u03b3\u03b9\u03bf\u03c5\u03c4\u03ac\u03b3\u03b9\u03b1", + "\u03c3\u03ac\u03bf_\u03c4\u03bf\u03bc\u03ad", + "\u03bb\u03b5\u03c5\u03ba\u03bf\u03c3_\u03bf\u03b9\u03ba\u03bf\u03c3", + "\u03ba\u03b1\u03b9\u03bd\u03ae_\u03b4\u03b9\u03b1\u03b8\u03ae\u03ba\u03b7", + "\u03b1\u03b3\u03b9\u03b1_\u03b2\u03b1\u03c1\u03b2\u03b1\u03c1\u03b1", + "\u03b1\u03b3\u03af\u03b1_\u03c3\u03bf\u03c6\u03af\u03b1", + "\u03b1\u03b3\u03b9\u03bf\u03c3_\u03b3\u03b5\u03c9\u03c1\u03b3\u03b9\u03bf\u03c3", + "\u03c7\u03c1\u03c5\u03c3\u03c9\u03c1\u03c5\u03c7\u03b5\u03b9\u03bf", + "\u03b5\u03c1\u03c5\u03b8\u03c1\u03ac_\u03b8\u03ac\u03bb\u03b1\u03c3\u03c3\u03b1", + "\u03bb\u03b5\u03c5\u03ba\u03cc\u03c3_\u03bf\u03af\u03ba\u03bf\u03c3", + "\u03b1\u03b3\u03b9\u03bf_\u03c0\u03bd\u03b5\u03c5\u03bc\u03b1", + "\u03c3\u03b1\u03b9\u03bd\u03c4_\u03bb\u03bf\u03cd\u03b9\u03c3" + ], + "LANGUAGE": [ + 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"\u03ba\u03b1\u03c4\u03b7\u03c7\u03b7\u03c4\u03b9\u03ba\u03bf", + "\u03bf\u03b9\u03ba\u03bf\u03c4\u03c1\u03bf\u03c6\u03b5\u03b9\u03bf", + "\u03c0\u03c1\u03b1\u03c3\u03b9\u03bd\u03bf", + "\u03c4\u03bf_\u03bd\u03b1_\u03c7\u03b5\u03c1\u03b9_\u03bd\u03b9\u03b2\u03b5\u03b9_\u03c4_\u03b1\u03bb\u03bb\u03bf_\u03ba\u03b1\u03b9_\u03c4\u03b1_\u03b4\u03c5\u03bf_\u03c4\u03bf_\u03c0\u03c1\u03bf\u03c3\u03c9\u03c0\u03bf", + "\u03b4\u03b9\u03b5\u03b8\u03bd\u03ae\u03c3_\u03ad\u03bd\u03c9\u03c3\u03b7_\u03c4\u03b7\u03bb\u03b5\u03c0\u03b9\u03ba\u03bf\u03b9\u03bd\u03c9\u03bd\u03b9\u03ce\u03bd", + "\u03b5\u03c0_\u03b5\u03c5\u03ba\u03b1\u03b9\u03c1\u03b9\u03b1", + "nasa", + "\u03b1\u03b3\u03b9\u03b1_\u03bb\u03bf\u03c5\u03ba\u03b9\u03b1", + "\u03b1\u03c5\u03b3\u03cc\u03c8\u03c9\u03bc\u03bf", + "\u03b7\u03bd\u03c9\u03bc\u03ad\u03bd\u03b5\u03c3_\u03c0\u03bf\u03bb\u03b9\u03c4\u03b5\u03af\u03b5\u03c3_\u03b1\u03bc\u03b5\u03c1\u03b9\u03ba\u03ae\u03c3", + "\u03b7_\u03c9\u03c1\u03b1\u03af\u03b1_\u03ba\u03bf\u03b9\u03bc\u03c9\u03bc\u03ad\u03bd\u03b7", + "\u03c3\u03b5_\u03b1\u03b3\u03b1\u03c0\u03c9", + "the_who", + "\u03bf\u03b9_\u03bc\u03b5\u03b3\u03ac\u03bb\u03bf\u03b9_\u03c4\u03ad\u03c3\u03c3\u03b5\u03c1\u03b9\u03c3", + "\u03c4\u03b1\u03c7\u03c5\u03b4\u03c1\u03bf\u03bc\u03b5\u03af\u03bf", + "\u03c6\u03c1\u03b5\u03bd\u03bf\u03ba\u03bf\u03bc\u03b5\u03b9\u03bf", + "\u03bc\u03b1\u03cd\u03c1\u03b7_\u03b1\u03b3\u03bf\u03c1\u03ac", + "\u03c3\u03bf\u03c3\u03b9\u03b1\u03bb\u03b4\u03b7\u03bc\u03bf\u03ba\u03c1\u03b1\u03c4\u03b9\u03ba\u03cc_\u03ba\u03cc\u03bc\u03bc\u03b1_\u03c0\u03bf\u03c1\u03c4\u03bf\u03b3\u03b1\u03bb\u03af\u03b1\u03c3", + "\u03c0\u03bf\u03c4\u03b5_\u03c0\u03bf\u03c4\u03b5", + "\u03cc\u03c1\u03bf\u03c3_\u03c4\u03c9\u03bd_\u03b5\u03bb\u03b1\u03b9\u03ce\u03bd", + "\u03c7\u03c1\u03c5\u03c3\u03b7_\u03b5\u03c0\u03bf\u03c7\u03b7", + "\u03b5\u03bb\u03b1\u03c6\u03b9\u03bd\u03b1", + "\u03c3\u03b1\u03bd\u03c4\u03b1_\u03c6\u03b5", + "\u03bd\u03ad\u03b1_\u03c3\u03b5\u03bb\u03ae\u03bd\u03b7", + "\u03b1\u03bb_\u03c4\u03b6\u03b1\u03b6\u03b9\u03c1\u03b1", + "\u03b4\u03b7\u03bc\u03bf\u03c4\u03b9\u03ba\u03cc_\u03c3\u03c7\u03bf\u03bb\u03b5\u03af\u03bf", + "\u03c6\u03bb\u03b5\u03c1_\u03bd\u03c4\u03b5_\u03bb\u03b9", + "\u03c6\u03c1\u03bf\u03c5\u03c4\u03bf\u03c3\u03b1\u03bb\u03b1\u03c4\u03b1", + "\u03ba\u03b1\u03b8\u03bf\u03bb\u03b9\u03ba\u03ae_\u03b5\u03ba\u03ba\u03bb\u03b7\u03c3\u03af\u03b1", + "dia", + "\u03c0\u03c5\u03c1\u03bf\u03c3\u03b2\u03b5\u03c3\u03c4\u03b9\u03ba\u03b7", + "\u03ba\u03bf\u03bc\u03bc\u03bf\u03c5\u03bd\u03b9\u03c3\u03c4\u03b9\u03ba\u03cc_\u03ba\u03cc\u03bc\u03bc\u03b1", + "\u03bc\u03b5\u03c4\u03b1_\u03c7\u03c1\u03b9\u03c3\u03c4\u03bf\u03bd", + "\u03b1\u03c0\u03bf_\u03c4\u03b7\u03bd_\u03b1\u03c1\u03c7\u03b7", + "\u03c4\u03b1\u03b3\u03bc\u03b1", + "\u03bf\u03c1\u03bf\u03c3_\u03c4\u03c9\u03bd_\u03b5\u03bb\u03b1\u03b9\u03c9\u03bd", + "\u03ba\u03af\u03c4\u03c1\u03b9\u03bd\u03bf\u03c3_\u03c0\u03bf\u03c4\u03b1\u03bc\u03cc\u03c3", + "\u03c5\u03c3\u03c4\u03b5\u03c1\u03bf\u03b2\u03bf\u03c5\u03bb\u03b9\u03b1", + "\u03c0\u03bf\u03b9\u03bf\u03c3_\u03b5\u03b9\u03c3\u03b1\u03b9", + "\u03ba\u03cc\u03bc\u03bc\u03b1_\u03c6\u03b9\u03bb\u03b5\u03bb\u03b5\u03c5\u03b8\u03ad\u03c1\u03c9\u03bd", + "\u03bc\u03b5\u03b3\u03ac\u03bb\u03b7_\u03ac\u03c1\u03ba\u03c4\u03bf\u03c3", + "\u03b1\u03bd\u03b8\u03c1\u03c9\u03c0\u03bf\u03b3\u03b5\u03bd\u03b7\u03c3", + "\u03c3\u03b9\u03bd\u03c4\u03bf\u03b9\u03c3\u03bc\u03bf\u03c3", + "\u03ba\u03bf\u03c5\u03bf\u03bc\u03b9\u03bd\u03c4\u03ac\u03bd\u03b3\u03ba", + "who_are_you", + "\u03c4\u03b1\u03bf\u03b9\u03c3\u03bc\u03bf\u03c3", + "al_jazeera", + "\u03bd\u03b1\u03c5\u03c4\u03b9\u03ba\u03bf", + "\u03bc\u03b1\u03c5\u03c1\u03b7_\u03b1\u03b3\u03bf\u03c1\u03b1", + "\u03ba\u03b1\u03b8\u03bf\u03bb\u03b9\u03ba\u03b7_\u03b5\u03ba\u03ba\u03bb\u03b7\u03c3\u03b9\u03b1", + "\u03bd\u03ae\u03c3\u03bf\u03c3_\u03b1\u03b3\u03af\u03b1\u03c3_\u03b5\u03bb\u03ad\u03bd\u03b7\u03c3", + "\u03bd\u03b7\u03c3\u03bf\u03c3_\u03b1\u03b3\u03b9\u03b1\u03c3_\u03b5\u03bb\u03b5\u03bd\u03b7\u03c3", + "\u03c3\u03c4\u03bf_\u03ba\u03b1\u03c4\u03c9_\u03ba\u03b1\u03c4\u03c9", + "\u03c0\u03b1\u03c1\u03b1\u03bc\u03bf\u03bd\u03b7_\u03c0\u03c1\u03c9\u03c4\u03bf\u03c7\u03c1\u03bf\u03bd\u03b9\u03b1\u03c3", + "\u03b5\u03bc\u03c0\u03bf\u03c1\u03b9\u03ba\u03bf_\u03ba\u03b5\u03bd\u03c4\u03c1\u03bf", + "\u03b5\u03b8\u03bd\u03bf\u03c3\u03c5\u03bd\u03ad\u03bb\u03b5\u03c5\u03c3\u03b7", + "\u03ba\u03cc\u03bc\u03bc\u03b1_\u03c0\u03c1\u03bf\u03bf\u03b4\u03b5\u03c5\u03c4\u03b9\u03ba\u03ce\u03bd", + "\u03b1\u03b3\u03af\u03b1_\u03b2\u03b1\u03c1\u03b2\u03ac\u03c1\u03b1", + "\u03b1\u03c0\u03bf_\u03ba\u03b1\u03b9\u03c1\u03bf_\u03c3\u03b5_\u03ba\u03b1\u03b9\u03c1\u03bf", + "sturmabteilung", + "\u03ac\u03b3\u03b9\u03bf\u03c3_\u03bd\u03b9\u03ba\u03cc\u03bb\u03b1\u03bf\u03c3", + "\u03b3\u03ba\u03b1\u03bb\u03b5\u03c1\u03b9", + "nato", + "\u03bc\u03b5\u03c4\u03b1\u03c1\u03c1\u03cd\u03b8\u03bc\u03b9\u03c3\u03b7", + "\u03c0\u03bf\u03b9\u03b1_\u03b5\u03b9\u03c3\u03b1\u03b9", + "by_the_way", + "\u03b5\u03c0\u03b9_\u03c4\u03bf\u03c5\u03c4\u03c9", + "\u03c3\u03b9\u03bd\u03c4\u03bf\u03ca\u03c3\u03bc\u03cc\u03c3", + "in_situ", + "\u03bc\u03c0\u03bf\u03c5\u03c7\u03c4\u03b9\u03c3\u03bc\u03b5\u03bd\u03bf\u03c3", + "\u03b1\u03b3\u03af\u03b1_\u03bb\u03bf\u03c5\u03ba\u03af\u03b1", + "\u03b3\u03bf\u03c5\u03b9\u03bd\u03b9_\u03c4\u03bf_\u03b1\u03c1\u03ba\u03bf\u03c5\u03b4\u03b1\u03ba\u03b9", + "\u03b7_\u03bd\u03ad\u03b1_\u03c3\u03c7\u03bf\u03bb\u03ae", + "\u03c3\u03c4\u03b1\u03b2\u03bb\u03bf\u03c7\u03b5\u03bb\u03af\u03b4\u03bf\u03bd\u03bf", + "\u03bc\u03b1\u03c3\u03c4\u03b9\u03c7\u03b1", + "\u03b4\u03b7\u03bc\u03bf\u03c4\u03b9\u03ba\u03bf_\u03c3\u03c7\u03bf\u03bb\u03b5\u03b9\u03bf", + "\u03ba\u03bf\u03bd\u03c3\u03b5\u03c1\u03b2\u03b1\u03c4\u03cc\u03c1\u03b9\u03bf", + "\u03b1\u03c3\u03c4\u03c5\u03bd\u03bf\u03bc\u03bf\u03ba\u03c1\u03b1\u03c4\u03af\u03b1", + "\u03b4\u03b9\u03b5\u03b8\u03bd\u03b7\u03c3_\u03b5\u03bd\u03c9\u03c3\u03b7_\u03c4\u03b7\u03bb\u03b5\u03c0\u03b9\u03ba\u03bf\u03b9\u03bd\u03c9\u03bd\u03b9\u03c9\u03bd", + "\u03c0\u03bf\u03bb\u03b9\u03c4\u03b9\u03ba\u03cc_\u03ba\u03cc\u03bc\u03bc\u03b1", + "\u03ba\u03bf\u03c5\u03ba\u03b9\u03b4\u03b1", + "\u03c3\u03c5\u03bd\u03c4\u03b7\u03c1\u03b7\u03c4\u03b9\u03ba\u03cc_\u03ba\u03cc\u03bc\u03bc\u03b1", + "\u03c3\u03c5\u03bd\u03b1\u03bb\u03bb\u03b1\u03b3\u03bc\u03b1", + "\u03b1\u03c3\u03c4\u03c5\u03bd\u03bf\u03bc\u03bf\u03ba\u03c1\u03b1\u03c4\u03b9\u03b1", + "\u03b3\u03bb\u03c5\u03ba\u03bf_\u03bd\u03b5\u03c1\u03bf", + "\u03b1\u03c0\u03bf_\u03ba\u03b1\u03b9\u03c1\u03bf\u03c5_\u03b5\u03b9\u03c3_\u03ba\u03b1\u03b9\u03c1\u03bf\u03bd", + "\u03c0\u03bf\u03b9\u03bd\u03b9\u03ba\u03bf\u03c3_\u03ba\u03c9\u03b4\u03b9\u03ba\u03b1\u03c3", + "\u03c1\u03c9\u03bc\u03b1\u03b9\u03bf\u03ba\u03b1\u03b8\u03bf\u03bb\u03b9\u03ba\u03b7_\u03b5\u03ba\u03ba\u03bb\u03b7\u03c3\u03b9\u03b1", + "\u03c4\u03bf_\u03bf\u03bd\u03bf\u03bc\u03b1_\u03bc\u03bf\u03c5_\u03b5\u03b9\u03bd\u03b1\u03b9", + "\u03b1\u03c3\u03c4\u03b9\u03ba\u03cc_\u03b4\u03af\u03ba\u03b1\u03b9\u03bf", + "\u03b4\u03b7\u03bc\u03b1\u03c1\u03c7\u03b5\u03b9\u03bf", + "\u03b3\u03b1\u03bb\u03b1\u03bd\u03bf\u03bc\u03b1\u03c4\u03b7\u03c3" + ], + "POLITICAL_PARTY": [ + "\u03c1\u03b5\u03c0\u03bf\u03c5\u03bc\u03c0\u03bb\u03b9\u03ba\u03b1\u03bd\u03b9\u03ba\u03cc_\u03ba\u03cc\u03bc\u03bc\u03b1", + "\u03b4\u03b7\u03bc\u03bf\u03ba\u03c1\u03b1\u03c4\u03b9\u03ba\u03cc_\u03ba\u03cc\u03bc\u03bc\u03b1", + "\u03b1\u03c5\u03c3\u03c4\u03c1\u03b1\u03bb\u03b9\u03b1\u03bd\u03cc_\u03b5\u03c1\u03b3\u03b1\u03c4\u03b9\u03ba\u03cc_\u03ba\u03cc\u03bc\u03bc\u03b1", + "\u03c3\u03bf\u03c3\u03b9\u03b1\u03bb\u03b4\u03b7\u03bc\u03bf\u03ba\u03c1\u03b1\u03c4\u03b9\u03ba\u03cc_\u03ba\u03cc\u03bc\u03bc\u03b1", + "\u03b5\u03c1\u03b3\u03b1\u03c4\u03b9\u03ba\u03cc_\u03ba\u03cc\u03bc\u03bc\u03b1", + "\u03c0\u03bf\u03bb\u03b9\u03c4\u03b9\u03ba\u03bf_\u03ba\u03bf\u03bc\u03bc\u03b1", + "\u03c3\u03bf\u03c3\u03b9\u03b1\u03bb\u03b9\u03c3\u03c4\u03b9\u03ba\u03cc_\u03ba\u03cc\u03bc\u03bc\u03b1", + "\u03c6\u03b9\u03bb\u03b5\u03bb\u03b5\u03cd\u03b8\u03b5\u03c1\u03bf_\u03ba\u03cc\u03bc\u03bc\u03b1", + "\u03bb\u03b1\u03ca\u03ba\u03cc_\u03ba\u03cc\u03bc\u03bc\u03b1", + "\u03c3\u03bf\u03c3\u03b9\u03b1\u03bb\u03b9\u03c3\u03c4\u03b9\u03ba\u03cc_\u03ba\u03cc\u03bc\u03bc\u03b1_\u03b3\u03b1\u03bb\u03bb\u03af\u03b1\u03c3", + "\u03c0\u03c1\u03ac\u03c3\u03b9\u03bd\u03bf_\u03ba\u03cc\u03bc\u03bc\u03b1", + "\u03b5\u03b8\u03bd\u03b9\u03ba\u03bf\u03c3\u03bf\u03c3\u03b9\u03b1\u03bb\u03b9\u03c3\u03c4\u03b9\u03ba\u03cc_\u03b3\u03b5\u03c1\u03bc\u03b1\u03bd\u03b9\u03ba\u03cc_\u03b5\u03c1\u03b3\u03b1\u03c4\u03b9\u03ba\u03cc_\u03ba\u03cc\u03bc\u03bc\u03b1" + ], + "ANIMAL": [ + "\u03b1\u03b3\u03c1\u03b9\u03bf\u03c0\u03b5\u03c1\u03b9\u03c3\u03c4\u03b5\u03c1\u03bf", + "\u03ba\u03bf\u03c5\u03ba\u03bf\u03c5\u03b2\u03b1\u03b3\u03b9\u03b1", + "\u03bc\u03c0\u03bf\u03c5\u03c6\u03bf\u03c3", + "\u03bc\u03b5\u03c4\u03b1\u03be\u03bf\u03c3\u03ba\u03ce\u03bb\u03b7\u03ba\u03b1\u03c3", + "\u03b1\u03c1\u03b8\u03c1\u03cc\u03c0\u03bf\u03b4\u03b1", + "\u03b1\u03b3\u03c1\u03b9\u03cc\u03c7\u03bf\u03b9\u03c1\u03bf\u03c3", + "\u03c7\u03b1\u03bb\u03ba\u03bf\u03ba\u03bf\u03c5\u03c1\u03bf\u03cd\u03bd\u03b1", + "\u03c0\u03b1\u03bd\u03c4\u03cc\u03c0\u03bf\u03b4\u03b1", + "\u03bc\u03b5\u03bb\u03b9\u03c3\u03c3\u03bf\u03c6\u03ac\u03b3\u03bf\u03c3", + "\u03ba\u03bf\u03c5\u03c1\u03bf\u03c5\u03bd\u03b1", + "\u03bd\u03b1\u03c5\u03c4\u03b9\u03bb\u03bf\u03c3", + "\u03c7\u03c1\u03b9\u03c3\u03c4\u03bf\u03c8\u03b1\u03c1\u03bf", + "\u03b1\u03b3\u03c1\u03b9\u03bf\u03ba\u03c5\u03ba\u03bd\u03bf\u03c3", + "\u03b1\u03b3\u03c1\u03b9\u03bf\u03b3\u03b1\u03bb\u03bf\u03c3", + "\u03b2\u03bf\u03c1\u03b5\u03b9\u03bf\u03c6\u03b1\u03bb\u03b1\u03b9\u03bd\u03b1", + "\u03c1\u03bf\u03c5\u03c3\u03bf\u03bc\u03c5\u03c4\u03b7", + "\u03bd\u03c5\u03c7\u03c4\u03bf\u03ba\u03cc\u03c1\u03b1\u03ba\u03b1\u03c3", + "\u03c0\u03c4\u03b5\u03c1\u03bf\u03c6\u03b1\u03bb\u03b1\u03b9\u03bd\u03b1", + "\u03c0\u03b5\u03c1\u03b9\u03c3\u03c4\u03ad\u03c1\u03b9", + "\u03b1\u03c3\u03c4\u03c1\u03af\u03c4\u03b7\u03c3", + "\u03b4\u03b9\u03c0\u03bb\u03bf\u03c3\u03b1\u03b9\u03bd\u03bf", + "\u03bc\u03b5\u03b3\u03b1\u03bb\u03bf\u03b6\u03cd\u03b3\u03b1\u03b9\u03bd\u03b1", + "\u03b4\u03b5\u03c1\u03bc\u03b1\u03c4\u03bf\u03c7\u03b5\u03bb\u03ce\u03bd\u03b1", + "\u03bc\u03b1\u03bd\u03b4\u03b1\u03c1\u03af\u03bd\u03bf\u03c3", + "\u03b2\u03b5\u03bb\u03bf\u03bd\u03bf\u03bf\u03c5\u03c1\u03bf\u03c3", + "\u03ba\u03bf\u03c5\u03ba\u03bf\u03c5\u03b2\u03ac\u03b3\u03b9\u03b1", + "\u03b9\u03bf\u03c3_\u03b5\u03bc\u03c0\u03bf\u03bb\u03b1", + "\u03b1\u03b3\u03c1\u03b9\u03bf\u03c7\u03b7\u03bd\u03b1", + 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"\u03b8\u03b5\u03bf\u03b4\u03bf\u03c3\u03af\u03b1", + "\u03c3\u03c0\u03c5\u03c1\u03ac\u03bd\u03bd\u03b1", + "\u03b5\u03cd\u03ba\u03bb\u03b5\u03b9\u03b1", + "\u03bc\u03b5\u03bb\u03ad\u03bd\u03b9\u03b1", + "\u03c7\u03c1\u03c5\u03c3\u03bf\u03b2\u03b1\u03bb\u03ac\u03bd\u03c4\u03bf\u03c5", + "\u03c7\u03c1\u03c5\u03c3\u03bf\u03cd\u03bb\u03b1", + "\u03b1\u03bd\u03b1\u03c4\u03bf\u03bb\u03ae", + "\u03b1\u03b7\u03b4\u03cc\u03bd\u03b1", + "\u03b1\u03c3\u03c4\u03ad\u03c1\u03c9", + "\u03b5\u03c5\u03c3\u03c4\u03c1\u03b1\u03c4\u03af\u03b1", + "\u03b9\u03bf\u03c5\u03bb\u03af\u03b1", + "\u03b3\u03b5\u03bd\u03bf\u03b2\u03ad\u03c6\u03b1", + "\u03ba\u03bf\u03bd\u03b4\u03c5\u03bb\u03af\u03b1", + "\u03c6\u03b9\u03bb\u03af\u03c0\u03c0\u03b1", + "\u03bd\u03b9\u03ba\u03b7\u03c4\u03af\u03b1", + "\u03bc\u03b9\u03c7\u03b1\u03ad\u03bb\u03b1", + "\u03c4\u03b5\u03c1\u03c8\u03b9\u03c7\u03cc\u03c1\u03b7", + "\u03bc\u03b1\u03c4\u03c1\u03ce\u03bd\u03b7", + "\u03b1\u03bd\u03b1\u03c3\u03c4\u03b1\u03c3\u03af\u03b1", + "\u03b7\u03c1\u03ac\u03ba\u03bb\u03b5\u03b9\u03b1", + "\u03ba\u03b1\u03bb\u03bb\u03b9\u03c1\u03cc\u03b7", + "\u03c1\u03b5\u03b3\u03b3\u03af\u03bd\u03b1", + "\u03c0\u03b1\u03c1\u03b1\u03c3\u03ba\u03b5\u03c5\u03ae", + "\u03b1\u03c5\u03b3\u03ae", + "\u03b8\u03b5\u03bf\u03c6\u03cd\u03bb\u03b1\u03ba\u03c4\u03b7", + "\u03c7\u03c1\u03c5\u03c3\u03bf\u03b2\u03b1\u03bb\u03ac\u03bd\u03c4\u03c9", + "\u03bb\u03bf\u03c5\u03bb\u03bf\u03c5\u03b4\u03ad\u03bd\u03b9\u03b1", + "\u03c0\u03b1\u03b3\u03ce\u03bd\u03b1", + "\u03c7\u03ac\u03b9\u03b4\u03c9", + "\u03bc\u03ac\u03bd\u03b8\u03b1", + "\u03b2\u03b1\u03bb\u03ac\u03bd\u03c4\u03c9", + "\u03c3\u03c4\u03b5\u03c1\u03b3\u03b9\u03b1\u03bd\u03ae", + "\u03bc\u03b1\u03c1\u03af\u03bd\u03b1", + "\u03b4\u03ad\u03c3\u03c0\u03bf\u03b9\u03bd\u03b1", + "\u03bd\u03b9\u03ba\u03bf\u03bb\u03ad\u03c4\u03b1", + "\u03c0\u03b1\u03bd\u03c9\u03c1\u03b1\u03af\u03b1", + "\u03b1\u03c0\u03bf\u03c3\u03c4\u03bf\u03bb\u03af\u03b1", + "\u03c6\u03b9\u03bb\u03bf\u03bc\u03ae\u03bb\u03b1", + "\u03b9\u03b1\u03ba\u03c9\u03b2\u03af\u03bd\u03b1", + "\u03c0\u03b7\u03b3\u03ae", + "\u03c3\u03b1\u03bb\u03ce\u03bc\u03b7", + "\u03b5\u03c1\u03b9\u03ad\u03c4\u03b1", + "\u03c0\u03b1\u03bd\u03b1\u03b3\u03b9\u03ce\u03c4\u03b1", + "\u03c6\u03b9\u03bb\u03b9\u03ce", + "\u03c3\u03bf\u03c5\u03bc\u03ad\u03bb\u03b1", + "\u03bc\u03b5\u03c4\u03b1\u03be\u03af\u03b1", + "\u03b2\u03b1\u03c3\u03b9\u03bb\u03b9\u03ba\u03ae", + "\u03ba\u03c1\u03b9\u03bd\u03b9\u03ce", + "\u03b8\u03b5\u03bf\u03c6\u03b1\u03bd\u03af\u03b1", + "\u03b3\u03bb\u03c5\u03ba\u03b5\u03c1\u03af\u03b1", + "\u03b3\u03b5\u03c9\u03c1\u03b3\u03af\u03b1", + "\u03bb\u03b1\u03c5\u03c1\u03b5\u03bd\u03c4\u03af\u03b1", + "\u03b5\u03c5\u03c6\u03c1\u03bf\u03c3\u03cd\u03bd\u03b7", + "\u03ba\u03b1\u03c3\u03c3\u03b9\u03b1\u03bd\u03ae", + "\u03b1\u03bb\u03b5\u03be\u03af\u03b1", + "\u03c0\u03bf\u03bb\u03c5\u03bd\u03af\u03ba\u03b7", + "\u03bc\u03b1\u03c1\u03b9\u03ac\u03bd\u03bd\u03b1", + "\u03b1\u03b3\u03cc\u03c1\u03c9", + "\u03bb\u03ae\u03b4\u03b1", + "\u03c6\u03b9\u03bb\u03bf\u03b8\u03ad\u03b7", + "\u03b1\u03bd\u03b4\u03c1\u03bf\u03bc\u03ac\u03c7\u03b7", + "\u03b5\u03c5\u03b4\u03bf\u03ba\u03af\u03b1", + "\u03c6\u03b1\u03af\u03b4\u03c1\u03b1", + "\u03bc\u03b1\u03c1\u03b9\u03b3\u03ce", + "\u03b1\u03c0\u03bf\u03bb\u03bb\u03c9\u03bd\u03af\u03b1", + "\u03b5\u03cd\u03b1", + "\u03b1\u03b3\u03b3\u03b5\u03bb\u03b9\u03ba\u03ae", + "\u03b1\u03bd\u03b4\u03c1\u03bf\u03bd\u03af\u03ba\u03b7", + "\u03b5\u03c5\u03c3\u03b5\u03b2\u03af\u03b1", + "\u03bd\u03af\u03ba\u03b7", + "\u03c0\u03bf\u03cd\u03bb\u03b9\u03b1", + "\u03c6\u03bf\u03af\u03b2\u03b7", + "\u03c4\u03c1\u03c5\u03c6\u03c9\u03bd\u03af\u03b1", + "\u03cc\u03bb\u03b3\u03b1", + "\u03b4\u03b1\u03bd\u03ac\u03b7", + "\u03c0\u03b1\u03bd\u03b4\u03ce\u03c1\u03b1", + "\u03b2\u03b1\u03c1\u03b2\u03ac\u03c1\u03b1", + "\u03b5\u03bb\u03b9\u03c3\u03ac\u03b2\u03b5\u03c4", + "\u03b4\u03c1\u03bf\u03c3\u03b9\u03ac", + "\u03c0\u03bf\u03bb\u03cd\u03b2\u03b9\u03b1", + "\u03ba\u03bb\u03b1\u03af\u03c1\u03b7", + "\u03bd\u03b5\u03c6\u03ad\u03bb\u03b7", + "\u03b3\u03b1\u03bb\u03ae\u03bd\u03b7", + "\u03bc\u03b5\u03bb\u03af\u03bd\u03b1", + "\u03bc\u03b1\u03c1\u03b9\u03bb\u03ad\u03bd\u03b1", + "\u03c3\u03c4\u03ad\u03bb\u03bb\u03b1", + "\u03b1\u03c7\u03b9\u03bb\u03bb\u03b5\u03af\u03b1", + "\u03b9\u03c3\u03bc\u03ae\u03bd\u03b7", + "\u03b6\u03b1\u03c7\u03b1\u03c1\u03ad\u03bd\u03b9\u03b1", + "\u03b5\u03c5\u03c3\u03c4\u03b1\u03b8\u03af\u03b1", + "\u03c6\u03b1\u03bd\u03bf\u03c5\u03c1\u03af\u03b1", + "\u03b5\u03c1\u03b9\u03c6\u03cd\u03bb\u03b7", + "\u03c3\u03bc\u03b1\u03c1\u03ac\u03b3\u03b4\u03b1", + "\u03bd\u03b1\u03c4\u03b1\u03bb\u03af\u03bd\u03b1", + "\u03c4\u03c1\u03b9\u03b1\u03bd\u03c4\u03ac\u03c6\u03c5\u03bb\u03bb\u03b7", + "\u03b2\u03b9\u03ba\u03c4\u03cc\u03c1\u03b9\u03b1", + "\u03b6\u03b7\u03bd\u03b1\u03ca\u03c2", + "\u03bf\u03c5\u03c1\u03b1\u03bd\u03af\u03b1", + "\u03b4\u03b9\u03bf\u03bd\u03c5\u03c3\u03af\u03b1", + "\u03c7\u03c1\u03c5\u03c3\u03ae", + "\u03ba\u03b1\u03bb\u03bb\u03b9\u03cc\u03c0\u03b7", + "\u03c7\u03c1\u03b9\u03c3\u03c4\u03b9\u03ac\u03bd\u03b1", + "\u03bd\u03c4\u03b1\u03bd\u03b9\u03ad\u03bb\u03b1", + "\u03bc\u03b9\u03bd\u03ad\u03c1\u03b2\u03b1", + "\u03c6\u03b5\u03c1\u03b5\u03bd\u03af\u03ba\u03b7", + "\u03b3\u03b5\u03c1\u03b1\u03ba\u03af\u03bd\u03b1", + "\u03ba\u03cc\u03c3\u03bc\u03b9\u03b1", + "\u03b5\u03b9\u03c1\u03ae\u03bd\u03b7", + "\u03ba\u03bf\u03bc\u03bd\u03b7\u03bd\u03ae", + "\u03c0\u03bf\u03bb\u03cd\u03b4\u03c9\u03c1\u03b1", + "\u03c3\u03b5\u03b2\u03b1\u03c3\u03c4\u03b9\u03b1\u03bd\u03ae", + "\u03b4\u03b9\u03b4\u03ce", + "\u03c3\u03c5\u03bc\u03b5\u03ce\u03bd\u03b7", + "\u03c0\u03b9\u03b5\u03c1\u03c1\u03af\u03bd\u03b1", + "\u03c6\u03c9\u03c4\u03b5\u03b9\u03bd\u03ae", + "\u03b1\u03c3\u03b7\u03bc\u03bf\u03cd\u03bb\u03b1", + "\u03b1\u03b3\u03bd\u03ae", + "\u03b8\u03ad\u03bc\u03b9\u03c2", + "\u03b1\u03bc\u03c6\u03b9\u03b8\u03ad\u03b1", + "\u03c3\u03c4\u03b1\u03c5\u03c1\u03bf\u03cd\u03bb\u03b1", + "\u03b4\u03cc\u03bc\u03bd\u03b1", + "\u03c3\u03c9\u03c6\u03c1\u03bf\u03bd\u03af\u03b1", + "\u03c0\u03b1\u03bd\u03c4\u03bf\u03cd\u03bb\u03b1", + "\u03b5\u03c5\u03b1\u03bd\u03b8\u03af\u03b1", + "\u03c4\u03b9\u03bc\u03bf\u03b8\u03ad\u03b1", + "\u03bc\u03b1\u03cd\u03c1\u03b1", + "\u03b2\u03b1\u03c3\u03b9\u03bb\u03b5\u03af\u03b1", + "\u03b8\u03b1\u03bb\u03b1\u03c3\u03c3\u03b9\u03bd\u03ae", + "\u03b1\u03c6\u03c1\u03bf\u03b4\u03af\u03c4\u03b7", + "\u03bd\u03b1\u03c4\u03b1\u03bb\u03af\u03b1", + "\u03bc\u03b1\u03bb\u03b1\u03bc\u03ac\u03c4\u03b7", + "\u03b5\u03c5\u03c1\u03c5\u03b4\u03af\u03ba\u03b7", + "\u03ba\u03bb\u03b5\u03b9\u03ce", + "\u03c7\u03c1\u03c5\u03c3\u03ac\u03bd\u03b8\u03b7", + "\u03b4\u03b1\u03b2\u03b9\u03b4\u03bf\u03cd\u03bb\u03b1", + "\u03b5\u03c1\u03b1\u03c3\u03bc\u03af\u03b1", + "\u03ba\u03bf\u03ba\u03ba\u03ce\u03bd\u03b1", + "\u03b2\u03ad\u03c1\u03b1", + "\u03ba\u03bb\u03b7\u03bc\u03b5\u03bd\u03c4\u03af\u03bd\u03b7", + "\u03bd\u03b1\u03c5\u03c3\u03b9\u03ba\u03ac", + "\u03bc\u03b5\u03bb\u03c0\u03bf\u03bc\u03ad\u03bd\u03b7", + "\u03b6\u03b7\u03c3\u03bf\u03cd\u03bb\u03b1", + "\u03b4\u03b1\u03bc\u03b9\u03b1\u03bd\u03ae", + "\u03bc\u03b1\u03c1\u03ba\u03ad\u03bb\u03bb\u03b1", + "\u03b2\u03b5\u03c1\u03cc\u03bd\u03b9\u03ba\u03b1", + "\u03c4\u03b1\u03be\u03b9\u03b1\u03c1\u03c7\u03af\u03b1", + "\u03b3\u03b9\u03b1\u03bd\u03bd\u03bf\u03cd\u03bb\u03b1", + "\u03bd\u03b9\u03ba\u03bf\u03bb\u03af\u03c4\u03c3\u03b1", + "\u03bc\u03b1\u03bb\u03b1\u03bc\u03b1\u03c4\u03ad\u03bd\u03b9\u03b1", + "\u03b3\u03b1\u03b2\u03c1\u03b9\u03ad\u03bb\u03bb\u03b1", + "\u03b9\u03bf\u03c5\u03bb\u03b9\u03b1\u03bd\u03ae", + "\u03c6\u03c1\u03cd\u03bd\u03b7", + "\u03c5\u03c0\u03b1\u03c0\u03b1\u03bd\u03c4\u03ae", + "\u03ba\u03c5\u03b2\u03ad\u03bb\u03b7", + "\u03b5\u03c5\u03b8\u03c5\u03bc\u03af\u03b1", + "\u03b1\u03b3\u03bb\u03b1\u0390\u03b1", + "\u03b8\u03ad\u03ba\u03bb\u03b1", + "\u03bc\u03b1\u03ba\u03c1\u03af\u03bd\u03b1", + "\u03bc\u03b9\u03c1\u03ac\u03bd\u03c4\u03b1", + "\u03bc\u03cc\u03c3\u03c7\u03b1", + "\u03b3\u03bb\u03b1\u03cd\u03ba\u03b7", + "\u03b5\u03c5\u03c4\u03c5\u03c7\u03af\u03b1", + "\u03b5\u03c5\u03b1\u03b3\u03b3\u03b5\u03bb\u03af\u03b1", + "\u03c5\u03b1\u03ba\u03af\u03bd\u03b8\u03b7", + "\u03b5\u03c5\u03bb\u03b1\u03bc\u03c0\u03af\u03b1", + "\u03ba\u03bf\u03c1\u03bd\u03b7\u03bb\u03af\u03b1", + "\u03b1\u03b3\u03ac\u03c0\u03b7", + "\u03b6\u03b1\u03bc\u03c0\u03af\u03b1", + "\u03bf\u03b4\u03cd\u03c3\u03c3\u03b5\u03b9\u03b1", + "\u03ba\u03bf\u03c1\u03b1\u03bb\u03af\u03b1", + "\u03c1\u03bf\u03c5\u03bc\u03c0\u03af\u03bd\u03b7", + "\u03b4\u03b9\u03b1\u03bc\u03ac\u03bd\u03c4\u03c9", + "\u03b3\u03b1\u03bb\u03ac\u03c4\u03b5\u03b9\u03b1", + "\u03bb\u03c5\u03b3\u03b5\u03c1\u03ae", + "\u03b4\u03ae\u03bc\u03b7\u03c4\u03c1\u03b1", + "\u03b8\u03b5\u03bf\u03b4\u03bf\u03cd\u03bb\u03b7", + "\u03b4\u03b9\u03b1\u03bb\u03b5\u03ba\u03c4\u03ae", + "\u03b8\u03ac\u03bb\u03b5\u03b9\u03b1", + "\u03b5\u03c0\u03b9\u03c3\u03c4\u03ae\u03bc\u03b7", + "\u03bc\u03b1\u03c1\u03b3\u03b9\u03ad\u03c4\u03c4\u03b1", + "\u03b1\u03c1\u03ad\u03b8\u03b1", + "\u03c1\u03bf\u03cd\u03c3\u03b1", + "\u03c0\u03b1\u03c1\u03b8\u03ad\u03bd\u03b1", + "\u03c0\u03b5\u03c1\u03c3\u03b5\u03c6\u03cc\u03bd\u03b7", + "\u03ba\u03b1\u03bb\u03ae", + "\u03c3\u03b5\u03bb\u03ae\u03bd\u03b7", + "\u03b1\u03c1\u03c4\u03b5\u03bc\u03b9\u03c3\u03af\u03b1", + "\u03b5\u03bc\u03bc\u03b1\u03bd\u03bf\u03c5\u03ad\u03bb\u03b1", + "\u03b1\u03c1\u03c7\u03bf\u03bd\u03c4\u03af\u03b1", + "\u03ba\u03c9\u03bd\u03c3\u03c4\u03b1\u03bd\u03c4\u03af\u03bd\u03b1", + "\u03c1\u03b5\u03b2\u03ad\u03ba\u03ba\u03b1", + "\u03c0\u03c9\u03bb\u03af\u03bd\u03b1", + "\u03ad\u03bb\u03bb\u03b7", + "\u03c3\u03c4\u03b1\u03bc\u03b1\u03c4\u03af\u03bd\u03b1", + "\u03c0\u03b1\u03c4\u03b1\u03c0\u03af\u03b1", + "\u03c3\u03b1\u03c0\u03c6\u03ce", + "\u03c6\u03c1\u03b5\u03b9\u03b4\u03b5\u03c1\u03af\u03ba\u03b7", + "\u03b5\u03bb\u03c0\u03af\u03b4\u03b1", + "\u03b5\u03c5\u03bc\u03bf\u03c1\u03c6\u03af\u03b1", + "\u03b9\u03bf\u03ba\u03ac\u03c3\u03c4\u03b7", + "\u03c4\u03c3\u03b1\u03bc\u03c0\u03af\u03ba\u03b1", + "\u03be\u03b1\u03bd\u03b8\u03ae", + "\u03c0\u03bf\u03b8\u03b7\u03c4\u03ae", + "\u03c0\u03c1\u03bf\u03b4\u03c1\u03bf\u03bc\u03af\u03b1", + "\u03b1\u03bd\u03b4\u03c1\u03b9\u03b1\u03bd\u03ae", + "\u03c6\u03b9\u03bb\u03b1\u03c1\u03ad\u03c4\u03b7", + "\u03b5\u03c5\u03b3\u03b5\u03bd\u03af\u03b1", + "\u03c6\u03b9\u03bb\u03b9\u03c0\u03c0\u03af\u03b1", + "\u03bb\u03b5\u03c9\u03bd\u03b9\u03b4\u03b9\u03ac", + "\u03bb\u03b7\u03c4\u03ce", + "\u03b8\u03b5\u03b1\u03bd\u03ce", + "\u03ac\u03c1\u03c4\u03b5\u03bc\u03b9\u03c2", + "\u03b1\u03c4\u03b1\u03bb\u03ac\u03bd\u03c4\u03b7", + "\u03ba\u03c9\u03c3\u03c4\u03bf\u03cd\u03bb\u03b1", + "\u03bb\u03b1\u03b6\u03b1\u03c1\u03af\u03b1", + "\u03b3\u03b9\u03b1\u03c3\u03b5\u03bc\u03ae", + "\u03b1\u03c1\u03b9\u03ac\u03b4\u03bd\u03b7", + "\u03ba\u03b1\u03c4\u03b5\u03c1\u03af\u03bd\u03b1", + "\u03b1\u03b9\u03ba\u03b1\u03c4\u03b5\u03c1\u03af\u03bd\u03b7", + "\u03c4\u03c1\u03b9\u03b1\u03bd\u03c4\u03b1\u03c6\u03c5\u03bb\u03bb\u03b9\u03ac", + "\u03b3\u03b5\u03c1\u03b1\u03c3\u03b9\u03bc\u03bf\u03cd\u03bb\u03b1", + "\u03b1\u03c6\u03ad\u03bd\u03c4\u03c1\u03b1", + "\u03b8\u03b5\u03cc\u03ba\u03bb\u03b5\u03b9\u03b1", + "\u03bc\u03b1\u03bd\u03c4\u03ce", + "\u03b9\u03c0\u03c0\u03bf\u03bb\u03cd\u03c4\u03b7", + "\u03c0\u03b1\u03bd\u03c4\u03b5\u03bb\u03af\u03b1", + "\u03b4\u03b9\u03b1\u03bc\u03b1\u03bd\u03c4\u03bf\u03cd\u03bb\u03b1", + "\u03c0\u03b7\u03bd\u03b5\u03bb\u03cc\u03c0\u03b7", + "\u03c1\u03b1\u03bb\u03bb\u03af\u03b1", + "\u03b2\u03b1\u03c1\u03c3\u03b1\u03bc\u03af\u03b1", + "\u03c3\u03b5\u03c1\u03b1\u03c6\u03b5\u03af\u03b1", + "\u03b2\u03b1\u03b3\u03b9\u03b1\u03bd\u03ae", + "\u03b2\u03b9\u03bf\u03bb\u03ad\u03c4\u03b1", + "\u03ba\u03b1\u03bb\u03bf\u03bc\u03bf\u03af\u03c1\u03b1", + "\u03b1\u03bc\u03b2\u03c1\u03bf\u03c3\u03af\u03b1", + "\u03c0\u03bf\u03bb\u03cd\u03bc\u03bd\u03b9\u03b1", + "\u03b2\u03b7\u03c3\u03c3\u03b1\u03c1\u03af\u03b1", + "\u03b3\u03b1\u03c1\u03c5\u03c6\u03b1\u03bb\u03bb\u03b9\u03ac", + "\u03b1\u03b9\u03bc\u03b9\u03bb\u03af\u03b1", + "\u03b6\u03b1\u03bc\u03c0\u03ad\u03c4\u03b1" + ], + "FIRST_NAME_MALE": [ + "\u03b5\u03c5\u03c3\u03c4\u03c1\u03ac\u03c4\u03b9\u03bf\u03c2", + "\u03b4\u03b7\u03bc\u03bf\u03ba\u03c1\u03ac\u03c4\u03b7\u03c2", + "\u03bc\u03b1\u03cd\u03c1\u03bf\u03c2", + "\u03bd\u03b9\u03ba\u03ae\u03c4\u03b1\u03c2", + "\u03ad\u03be\u03b1\u03c1\u03c7\u03bf\u03c2", + "\u03b7\u03c1\u03cc\u03b4\u03bf\u03c4\u03bf\u03c2", + "\u03be\u03b5\u03bd\u03bf\u03c6\u03ce\u03bd", + "\u03b9\u03bf\u03cd\u03bb\u03b9\u03bf\u03c2", + "\u03bb\u03b1\u03ad\u03c1\u03c4\u03b7\u03c2", + "\u03b2\u03b1\u03c3\u03af\u03bb\u03b5\u03b9\u03bf\u03c2", + "\u03b8\u03b1\u03bb\u03ae\u03c2", + "\u03b1\u03bb\u03ad\u03be\u03b9\u03bf\u03c2", + "\u03c3\u03b1\u03c1\u03ac\u03bd\u03c4\u03b7\u03c2", + "\u03b4\u03b7\u03bc\u03bf\u03c3\u03b8\u03ad\u03bd\u03b7\u03c2", + "\u03b3\u03ba\u03af\u03ba\u03b1\u03c2", + "\u03b5\u03c5\u03c3\u03c4\u03ac\u03b8\u03b9\u03bf\u03c2", + "\u03bc\u03b1\u03c5\u03c1\u03bf\u03cd\u03b4\u03b7\u03c2", + "\u03b5\u03bc\u03bc\u03b1\u03bd\u03bf\u03c5\u03ae\u03bb", + "\u03c3\u03b1\u03bc\u03bf\u03c5\u03ae\u03bb", + "\u03bd\u03b1\u03c0\u03bf\u03bb\u03ad\u03c9\u03bd", + "\u03c1\u03c9\u03bc\u03b1\u03bd\u03cc\u03c2", + "\u03bb\u03cd\u03c3\u03b1\u03bd\u03b4\u03c1\u03bf\u03c2", + "\u03b5\u03c1\u03bc\u03ae\u03c2", + "\u03b1\u03c1\u03b3\u03cd\u03c1\u03b9\u03bf\u03c2", + "\u03b6\u03b1\u03c6\u03b5\u03af\u03c1\u03b7\u03c2", + "\u03bb\u03ac\u03b6\u03b1\u03c1\u03bf\u03c2", + "\u03b1\u03bd\u03ad\u03c3\u03c4\u03b7\u03c2", + "\u03c0\u03bb\u03bf\u03cd\u03c4\u03b1\u03c1\u03c7\u03bf\u03c2", + "\u03c0\u03b5\u03bb\u03bf\u03c0\u03af\u03b4\u03b1\u03c2", + "\u03c0\u03bb\u03ac\u03c4\u03c9\u03bd", + "\u03af\u03c9\u03bd", + "\u03b7\u03c3\u03b1\u0390\u03b1\u03c2", + "\u03c0\u03b5\u03c1\u03b9\u03ba\u03bb\u03ae\u03c2", + "\u03b1\u03b3\u03b1\u03bc\u03ad\u03bc\u03bd\u03c9\u03bd", + "\u03bd\u03af\u03ba\u03bf\u03c2", + "\u03c7\u03c1\u03ae\u03c3\u03c4\u03bf\u03c2", + "\u03b1\u03b3\u03b7\u03c3\u03af\u03bb\u03b1\u03bf\u03c2", + "\u03c6\u03b1\u03bd\u03bf\u03cd\u03c1\u03b9\u03bf\u03c2", + "\u03b5\u03c5\u03b4\u03cc\u03be\u03b9\u03bf\u03c2", + "\u03ba\u03bb\u03b5\u03cc\u03b2\u03bf\u03c5\u03bb\u03bf\u03c2", + "\u03ba\u03bf\u03c1\u03bd\u03ae\u03bb\u03b9\u03bf\u03c2", + "\u03b8\u03b5\u03bf\u03b4\u03cc\u03c3\u03b9\u03bf\u03c2", + "\u03b9\u03b3\u03bd\u03ac\u03c4\u03b9\u03bf\u03c2", + "\u03ba\u03cd\u03c1\u03bf\u03c2", + "\u03bc\u03b9\u03c7\u03b1\u03ae\u03bb", + "\u03c1\u03b1\u03c6\u03b1\u03ae\u03bb", + "\u03c0\u03b1\u03bd\u03c4\u03b5\u03bb\u03ae\u03c2", + "\u03b5\u03bb\u03b5\u03c5\u03b8\u03ad\u03c1\u03b9\u03bf\u03c2", + "\u03b1\u03c0\u03cc\u03bb\u03bb\u03c9\u03bd", + "\u03b9\u03bf\u03c5\u03bb\u03b9\u03b1\u03bd\u03cc\u03c2", + "\u03b8\u03b5\u03bf\u03b4\u03cc\u03c3\u03b7\u03c2", + "\u03b1\u03c6\u03ad\u03bd\u03c4\u03b7\u03c2", + "\u03b4\u03b1\u03bc\u03b9\u03b1\u03bd\u03cc\u03c2", + "\u03c0\u03b1\u03bd\u03b1\u03b3\u03ae\u03c2", + "\u03b8\u03b5\u03bf\u03c4\u03cc\u03ba\u03b7\u03c2", + "\u03c3\u03b5\u03b2\u03b1\u03c3\u03c4\u03b9\u03b1\u03bd\u03cc\u03c2", + "\u03c3\u03c9\u03c4\u03ae\u03c1\u03b9\u03bf\u03c2", + "\u03bb\u03bf\u03c5\u03ba\u03b9\u03b1\u03bd\u03cc\u03c2", + "\u03bf\u03b4\u03c5\u03c3\u03c3\u03ad\u03b1\u03c2", + "\u03b1\u03bb\u03ba\u03b9\u03b2\u03b9\u03ac\u03b4\u03b7\u03c2", + "\u03bc\u03b5\u03bb\u03ad\u03c4\u03b9\u03bf\u03c2", + "\u03b8\u03bf\u03c5\u03ba\u03c5\u03b4\u03af\u03b4\u03b7\u03c2", + "\u03ac\u03c1\u03b7\u03c2", + "\u03b2\u03b1\u03bb\u03ad\u03c1\u03b9\u03bf\u03c2", + "\u03b1\u03bd\u03c4\u03af\u03b3\u03bf\u03bd\u03bf\u03c2", + "\u03c0\u03ac\u03c1\u03b9\u03c2", + "\u03bb\u03ad\u03b1\u03bd\u03b4\u03c1\u03bf\u03c2", + "\u03c3\u03c0\u03ae\u03bb\u03b9\u03bf\u03c2", + "\u03b4\u03c1\u03ac\u03ba\u03c9\u03bd", + "\u03bc\u03b5\u03bd\u03ad\u03bb\u03b1\u03bf\u03c2", + "\u03b1\u03c3\u03c4\u03ad\u03c1\u03b9\u03bf\u03c2", + "\u03b3\u03c1\u03b7\u03b3\u03cc\u03c1\u03b9\u03bf\u03c2", + "\u03c3\u03c4\u03b1\u03bc\u03ac\u03c4\u03b9\u03bf\u03c2", + "\u03b1\u03c7\u03b9\u03bb\u03bb\u03ad\u03b1\u03c2", + "\u03b1\u03c3\u03b7\u03bc\u03ac\u03ba\u03b7\u03c2", + "\u03cc\u03b8\u03c9\u03bd", + "\u03bd\u03af\u03ba\u03b1\u03bd\u03b4\u03c1\u03bf\u03c2", + "\u03c1\u03b1\u03c7\u03ae\u03bb", + "\u03c0\u03b1\u03c5\u03c3\u03b1\u03bd\u03af\u03b1\u03c2", + "\u03ba\u03bf\u03c3\u03bc\u03ac\u03c2", + "\u03b8\u03b7\u03c3\u03b5\u03cd\u03c2", + "\u03b9\u03c3\u03af\u03b4\u03c9\u03c1\u03bf\u03c2", + "\u03b8\u03b5\u03cc\u03ba\u03bb\u03b7\u03c4\u03bf\u03c2", + "\u03b8\u03b5\u03bf\u03c6\u03ac\u03bd\u03b7\u03c2", + "\u03b8\u03b5\u03cc\u03c6\u03c1\u03b1\u03c3\u03c4\u03bf\u03c2", + "\u03bc\u03b1\u03b3\u03b4\u03b1\u03bb\u03b7\u03bd\u03cc\u03c2", + "\u03b1\u03bd\u03b1\u03c3\u03c4\u03ac\u03c3\u03b9\u03bf\u03c2", + "\u03bd\u03b1\u03b8\u03b1\u03bd\u03b1\u03ae\u03bb", + "\u03b1\u03b3\u03b1\u03b8\u03ac\u03b3\u03b3\u03b5\u03bb\u03bf\u03c2", + "\u03c0\u03bf\u03bb\u03c5\u03c7\u03c1\u03cc\u03bd\u03b9\u03bf\u03c2", + "\u03ba\u03b1\u03bb\u03bb\u03af\u03bd\u03b9\u03ba\u03bf\u03c2", + "\u03c0\u03b1\u03cd\u03bb\u03bf\u03c2", + "\u03c7\u03c1\u03c5\u03c3\u03cc\u03c3\u03c4\u03bf\u03bc\u03bf\u03c2", + "\u03c3\u03c9\u03c4\u03ae\u03c1\u03b7\u03c2", + "\u03b4\u03af\u03ba\u03b1\u03b9\u03bf\u03c2", + "\u03c4\u03c3\u03b1\u03bc\u03c0\u03af\u03ba\u03bf\u03c2", + "\u03b2\u03b1\u03c1\u03c3\u03ac\u03bc\u03bf\u03c2", + "\u03c4\u03b9\u03bc\u03bf\u03bb\u03ad\u03c9\u03bd", + "\u03b4\u03b9\u03bf\u03b3\u03ad\u03bd\u03b7\u03c2", + "\u03bc\u03b1\u03c5\u03c1\u03af\u03ba\u03b9\u03bf\u03c2", + "\u03b4\u03b9\u03bf\u03bd\u03cd\u03c3\u03b9\u03bf\u03c2", + "\u03c7\u03c1\u03c5\u03c3\u03bf\u03b2\u03b1\u03bb\u03ac\u03bd\u03c4\u03b9\u03bf\u03c2", + "\u03b3\u03b1\u03bb\u03b7\u03bd\u03cc\u03c2", + "\u03c6\u03b1\u03af\u03b4\u03c9\u03bd", + "\u03bb\u03b5\u03c9\u03bd\u03af\u03b4\u03b1\u03c2", + "\u03c0\u03b1\u03bd\u03bf\u03c1\u03bc\u03af\u03c4\u03b7\u03c2", + "\u03c0\u03c1\u03bf\u03bc\u03b7\u03b8\u03ad\u03b1\u03c2", + "\u03cc\u03bc\u03b7\u03c1\u03bf\u03c2", + "\u03b1\u03c5\u03b3\u03ad\u03c1\u03b7\u03c2", + "\u03c3\u03c4\u03ad\u03c6\u03b1\u03bd\u03bf\u03c2", + "\u03b1\u03bb\u03ad\u03be\u03b1\u03bd\u03b4\u03c1\u03bf\u03c2", + "\u03c3\u03c5\u03bc\u03b5\u03ce\u03bd", + "\u03ba\u03c5\u03c1\u03b9\u03b1\u03b6\u03ae\u03c2", + "\u03c0\u03bf\u03bb\u03cd\u03ba\u03b1\u03c1\u03c0\u03bf\u03c2", + "\u03b5\u03c5\u03bc\u03ad\u03bd\u03b9\u03bf\u03c2", + "\u03ba\u03c9\u03bd\u03c3\u03c4\u03b1\u03bd\u03c4\u03af\u03bd\u03bf\u03c2", + "\u03c0\u03bf\u03bb\u03cd\u03b4\u03c9\u03c1\u03bf\u03c2", + "\u03b1\u03c1\u03c7\u03ad\u03bb\u03b1\u03bf\u03c2", + "\u03b2\u03b5\u03bd\u03b9\u03b6\u03ad\u03bb\u03bf\u03c2", + "\u03b5\u03c1\u03c9\u03c4\u03cc\u03ba\u03c1\u03b9\u03c4\u03bf\u03c2", + "\u03b8\u03c9\u03bc\u03ac\u03c2", + "\u03c0\u03bf\u03bb\u03c5\u03b6\u03ce\u03b7\u03c2", + "\u03b5\u03c6\u03c1\u03b1\u03af\u03bc", + "\u03c6\u03b9\u03bb\u03ae\u03bc\u03c9\u03bd", + "\u03bc\u03b7\u03bd\u03ac\u03c2", + "\u03b1\u03c0\u03cc\u03c3\u03c4\u03bf\u03bb\u03bf\u03c2", + "\u03b9\u03c9\u03c3\u03ae\u03c6", + "\u03b1\u03ba\u03c1\u03b9\u03b2\u03cc\u03c2", + "\u03c0\u03b1\u03bd\u03b1\u03b3\u03b9\u03ce\u03c4\u03b7\u03c2", + "\u03b1\u03c1\u03b9\u03c3\u03c4\u03bf\u03c4\u03ad\u03bb\u03b7\u03c2", + "\u03b5\u03c0\u03b1\u03bc\u03b5\u03b9\u03bd\u03ce\u03bd\u03b4\u03b1\u03c2", + "\u03bf\u03b4\u03c5\u03c3\u03c3\u03b5\u03cd\u03c2", + "\u03b1\u03b3\u03b1\u03c0\u03b7\u03c4\u03cc\u03c2", + "\u03c6\u03bf\u03af\u03b2\u03bf\u03c2", + "\u03b2\u03ac\u03b9\u03bf\u03c2", + "\u03bf\u03c1\u03c6\u03ad\u03b1\u03c2", + "\u03c1\u03ac\u03bb\u03bb\u03b7\u03c2", + "\u03bc\u03af\u03bd\u03c9\u03b1\u03c2", + "\u03c3\u03ac\u03b2\u03b2\u03b1\u03c2", + "\u03bb\u03b5\u03bc\u03bf\u03bd\u03ae\u03c2", + "\u03b2\u03b1\u03bb\u03b5\u03bd\u03c4\u03af\u03bd\u03bf\u03c2", + "\u03c4\u03b1\u03be\u03af\u03b1\u03c1\u03c7\u03bf\u03c2", + "\u03c0\u03bf\u03bb\u03cd\u03b2\u03b9\u03bf\u03c2", + "\u03c6\u03c1\u03b1\u03b3\u03ba\u03af\u03c3\u03ba\u03bf\u03c2", + "\u03c3\u03c4\u03c5\u03bb\u03b9\u03b1\u03bd\u03cc\u03c2", + "\u03bd\u03af\u03ba\u03c9\u03bd", + "\u03c7\u03c1\u03b9\u03c3\u03c4\u03cc\u03b4\u03bf\u03c5\u03bb\u03bf\u03c2", + "\u03c6\u03c1\u03af\u03be\u03bf\u03c2", + "\u03b4\u03b7\u03bc\u03ae\u03c4\u03c1\u03b9\u03bf\u03c2", + "\u03b1\u03c1\u03c7\u03b9\u03bc\u03ae\u03b4\u03b7\u03c2", + "\u03b1\u03bd\u03b1\u03be\u03b1\u03b3\u03cc\u03c1\u03b1\u03c2", + "\u03c7\u03ac\u03c1\u03b9\u03c2", + "\u03b1\u03af\u03b1\u03c2", + "\u03bd\u03b9\u03ba\u03cc\u03bb\u03b1\u03bf\u03c2", + "\u03b1\u03b3\u03b3\u03b5\u03bb\u03ae\u03c2", + "\u03bd\u03b5\u03ba\u03c4\u03ac\u03c1\u03b9\u03bf\u03c2", + "\u03b1\u03bd\u03c4\u03cd\u03c0\u03b1\u03c2", + "\u03b5\u03c5\u03ac\u03b3\u03b3\u03b5\u03bb\u03bf\u03c2", + "\u03b4\u03b7\u03bc\u03ae\u03c4\u03c1\u03b7\u03c2", + "\u03b5\u03c5\u03ba\u03bb\u03b5\u03af\u03b4\u03b7\u03c2", + "\u03c6\u03c9\u03c4\u03b5\u03b9\u03bd\u03cc\u03c2", + "\u03b4\u03c1\u03cc\u03c3\u03bf\u03c2", + "\u03b1\u03bd\u03c4\u03af\u03c0\u03b1\u03c4\u03c1\u03bf\u03c2", + "\u03b4\u03c9\u03c1\u03cc\u03b8\u03b5\u03bf\u03c2", + "\u03ac\u03b3\u03b3\u03b5\u03bb\u03bf\u03c2", + "\u03c1\u03ae\u03b3\u03b1\u03c2", + "\u03c1\u03bf\u03b4\u03cc\u03c6\u03bb\u03bf\u03c2", + "\u03b4\u03bf\u03bc\u03ae\u03bd\u03b9\u03ba\u03bf\u03c2", + "\u03b9\u03c3\u03b1\u03ac\u03ba", + "\u03bc\u03b1\u03c4\u03b8\u03b1\u03af\u03bf\u03c2", + "\u03bc\u03ac\u03c1\u03b9\u03bf\u03c2", + "\u03bc\u03ac\u03c1\u03ba\u03bf\u03c2", + "\u03b4\u03ae\u03bc\u03bf\u03c2", + "\u03b2\u03bb\u03b1\u03b4\u03af\u03bc\u03b7\u03c1\u03bf\u03c2", + "\u03bc\u03ad\u03bd\u03b1\u03bd\u03b4\u03c1\u03bf\u03c2", + "\u03c6\u03bb\u03bf\u03c1\u03b9\u03ac\u03bd\u03c4", + "\u03ac\u03c1\u03b9\u03c3\u03c4\u03bf\u03c2", + "\u03b9\u03c9\u03ac\u03bd\u03bd\u03b7\u03c2", + "\u03c0\u03b1\u03bd\u03c4\u03b5\u03bb\u03b5\u03ae\u03bc\u03c9\u03bd", + "\u03ba\u03bb\u03b5\u03cc\u03c0\u03b1\u03c2", + "\u03b9\u03ac\u03c3\u03bf\u03bd\u03b1\u03c2", + "\u03c3\u03b9\u03c1\u03b1\u03bd\u03bf\u03cd\u03c2", + "\u03b2\u03c1\u03b1\u03c3\u03af\u03b4\u03b1\u03c2", + "\u03b2\u03b1\u03c3\u03af\u03bb\u03b7\u03c2", + "\u03b9\u03b5\u03c1\u03cc\u03b8\u03b5\u03bf\u03c2", + "\u03b8\u03b5\u03cc\u03c0\u03b9\u03c3\u03c4\u03bf\u03c2", + "\u03b5\u03b9\u03c1\u03b7\u03bd\u03b1\u03af\u03bf\u03c2", + "\u03b4\u03b7\u03bc\u03cc\u03ba\u03c1\u03b9\u03c4\u03bf\u03c2", + "\u03c0\u03b1\u03c1\u03b1\u03c3\u03ba\u03b5\u03c5\u03ac\u03c2", + "\u03bb\u03ac\u03c3\u03ba\u03b1\u03c1\u03b7\u03c2", + "\u03ba\u03bb\u03b5\u03ac\u03bd\u03b8\u03b7\u03c2", + "\u03c4\u03b7\u03bb\u03b5\u03bc\u03b1\u03c7\u03bf\u03c2", + "\u03ba\u03bb\u03ad\u03b1\u03c1\u03c7\u03bf\u03c2", + "\u03b2\u03b1\u03c1\u03b8\u03bf\u03bb\u03bf\u03bc\u03b1\u03af\u03bf\u03c2", + "\u03c3\u03cc\u03bb\u03c9\u03bd", + "\u03b1\u03cd\u03b3\u03bf\u03c5\u03c3\u03c4\u03bf\u03c2", + "\u03c3\u03ce\u03b6\u03c9\u03bd", + "\u03af\u03ba\u03b1\u03c1\u03bf\u03c2", + "\u03c4\u03b1\u03be\u03b9\u03ac\u03c1\u03c7\u03b7\u03c2", + "\u03c3\u03ad\u03c1\u03b3\u03b9\u03bf\u03c2", + "\u03b3\u03b9\u03ce\u03c1\u03b3\u03bf\u03c2", + "\u03b7\u03c1\u03b1\u03ba\u03bb\u03ae\u03c2", + "\u03b1\u03c1\u03b9\u03c3\u03c4\u03cc\u03b2\u03bf\u03c5\u03bb\u03bf\u03c2", + "\u03b6\u03b1\u03c7\u03b1\u03c1\u03af\u03b1\u03c2", + "\u03c3\u03bf\u03c6\u03bf\u03ba\u03bb\u03ae\u03c2", + "\u03b5\u03c5\u03c1\u03b9\u03c0\u03af\u03b4\u03b7\u03c2", + "\u03bc\u03b1\u03c1\u03c4\u03af\u03bd\u03bf\u03c2", + "\u03c7\u03b1\u03c1\u03ac\u03bb\u03b1\u03bc\u03c0\u03bf\u03c2", + "\u03c3\u03b5\u03c1\u03b1\u03c6\u03b5\u03af\u03bc", + "\u03c7\u03b1\u03c1\u03af\u03bb\u03b1\u03bf\u03c2", + "\u03b1\u03bd\u03c4\u03ce\u03bd\u03b9\u03bf\u03c2", + "\u03b8\u03b5\u03cc\u03b4\u03bf\u03c5\u03bb\u03bf\u03c2", + "\u03b9\u03bf\u03c1\u03b4\u03ac\u03bd\u03b7\u03c2", + "\u03bb\u03ac\u03bc\u03c0\u03c1\u03bf\u03c2", + "\u03b1\u03ba\u03c1\u03af\u03c4\u03b1\u03c2", + "\u03b2\u03b7\u03c3\u03c3\u03b1\u03c1\u03af\u03c9\u03bd", + "\u03b6\u03b7\u03bd\u03cc\u03b2\u03b9\u03bf\u03c2", + "\u03b1\u03c1\u03c4\u03ad\u03bc\u03b9\u03bf\u03c2", + "\u03ac\u03bd\u03b8\u03b9\u03bc\u03bf\u03c2", + "\u03b8\u03b5\u03bf\u03bb\u03cc\u03b3\u03bf\u03c2", + "\u03b4\u03b1\u03bc\u03b1\u03c3\u03ba\u03b7\u03bd\u03cc\u03c2", + "\u03b8\u03b5\u03bc\u03b9\u03c3\u03c4\u03bf\u03ba\u03bb\u03ae\u03c2", + "\u03c6\u03c9\u03ba\u03ac\u03c2", + "\u03b1\u03b9\u03bc\u03af\u03bb\u03b9\u03bf\u03c2", + "\u03c4\u03af\u03c4\u03bf\u03c2", + "\u03c0\u03ad\u03c4\u03c1\u03bf\u03c2", + "\u03b8\u03ad\u03bc\u03b7\u03c2", + "\u03bc\u03b5\u03c1\u03ba\u03bf\u03cd\u03c1\u03b9\u03bf\u03c2", + "\u03b2\u03b5\u03bd\u03b9\u03b1\u03bc\u03af\u03bd", + "\u03b9\u03c9\u03bd\u03ac\u03c2", + "\u03c7\u03c1\u03cd\u03c3\u03b1\u03bd\u03b8\u03bf\u03c2", + "\u03c0\u03ac\u03c4\u03c1\u03bf\u03ba\u03bb\u03bf\u03c2", + "\u03bd\u03b5\u03cc\u03c6\u03c5\u03c4\u03bf\u03c2", + "\u03b1\u03b3\u03ac\u03c0\u03b9\u03bf\u03c2", + "\u03c3\u03c4\u03ad\u03bb\u03bb\u03b9\u03bf\u03c2", + "\u03b6\u03b1\u03c6\u03b5\u03af\u03c1\u03b9\u03bf\u03c2", + "\u03bc\u03b5\u03b8\u03cc\u03b4\u03b9\u03bf\u03c2", + "\u03b3\u03b5\u03c1\u03ac\u03c3\u03b9\u03bc\u03bf\u03c2", + "\u03c3\u03c4\u03b1\u03cd\u03c1\u03bf\u03c2", + "\u03b9\u03c0\u03c0\u03bf\u03ba\u03c1\u03ac\u03c4\u03b7\u03c2", + "\u03bc\u03b1\u03c1\u03af\u03bd\u03bf\u03c2", + "\u03b3\u03b1\u03b2\u03c1\u03b9\u03ae\u03bb", + "\u03b9\u03ac\u03c3\u03c9\u03bd", + "\u03c7\u03c1\u03b9\u03c3\u03c4\u03b9\u03ac\u03bd", + "\u03b1\u03bd\u03b1\u03b3\u03bd\u03ce\u03c3\u03c4\u03b7\u03c2", + "\u03bc\u03b1\u03c5\u03c1\u03bf\u03b5\u03b9\u03b4\u03ae\u03c2", + "\u03bb\u03bf\u03c5\u03ba\u03ac\u03c2", + "\u03b1\u03c5\u03be\u03ad\u03bd\u03c4\u03b9\u03bf\u03c2", + "\u03bb\u03c5\u03ba\u03bf\u03cd\u03c1\u03b3\u03bf\u03c2", + "\u03b9\u03c9\u03b1\u03ba\u03b5\u03af\u03bc", + "\u03b1\u03c1\u03b9\u03c3\u03c4\u03b5\u03af\u03b4\u03b7\u03c2", + "\u03c7\u03c1\u03b9\u03c3\u03c4\u03cc\u03c6\u03bf\u03c1\u03bf\u03c2", + "\u03ba\u03bb\u03b5\u03bf\u03bc\u03ad\u03bd\u03b7\u03c2", + "\u03b1\u03c3\u03ba\u03bb\u03b7\u03c0\u03b9\u03cc\u03c2", + "\u03b5\u03c5\u03c3\u03ad\u03b2\u03b9\u03bf\u03c2", + "\u03b1\u03bd\u03b1\u03bd\u03af\u03b1\u03c2", + "\u03b7\u03bb\u03af\u03b1\u03c2", + "\u03b9\u03c0\u03c0\u03cc\u03bb\u03c5\u03c4\u03bf\u03c2", + "\u03bf\u03c1\u03ad\u03c3\u03c4\u03b7\u03c2", + "\u03ba\u03c1\u03c5\u03c3\u03c4\u03ac\u03bb\u03bb\u03b7\u03c2", + "\u03b1\u03bd\u03b4\u03c1\u03ad\u03b1\u03c2", + "\u03c6\u03ce\u03c4\u03b9\u03bf\u03c2", + "\u03bb\u03b1\u03c5\u03c1\u03ad\u03bd\u03c4\u03b9\u03bf\u03c2", + "\u03c4\u03af\u03bc\u03c9\u03bd", + "\u03c7\u03b1\u03c1\u03af\u03c4\u03bf\u03c2", + "\u03b1\u03b8\u03b7\u03bd\u03cc\u03b4\u03c9\u03c1\u03bf\u03c2", + "\u03b2\u03cd\u03c1\u03c9\u03bd", + "\u03b2\u03bb\u03ac\u03c3\u03b7\u03c2", + "\u03b5\u03bb\u03b9\u03c3\u03c3\u03b1\u03af\u03bf\u03c2", + "\u03c0\u03c1\u03cc\u03b4\u03c1\u03bf\u03bc\u03bf\u03c2", + "\u03c6\u03af\u03bb\u03b9\u03c0\u03c0\u03bf\u03c2", + "\u03c6\u03c1\u03b5\u03b9\u03b4\u03b5\u03c1\u03af\u03ba\u03bf\u03c2", + "\u03bb\u03bf\u03c5\u03b4\u03bf\u03b2\u03af\u03ba\u03bf\u03c2", + "\u03b2\u03b5\u03bd\u03ad\u03c4\u03b9\u03bf\u03c2", + "\u03bd\u03b9\u03ba\u03cc\u03b4\u03b7\u03bc\u03bf\u03c2", + "\u03b1\u03c1\u03b9\u03c3\u03c4\u03bf\u03c6\u03ac\u03bd\u03b7\u03c2", + "\u03c5\u03ac\u03ba\u03b9\u03bd\u03b8\u03bf\u03c2", + "\u03bd\u03b9\u03ba\u03b7\u03c6\u03cc\u03c1\u03bf\u03c2", + "\u03b1\u03bd\u03b4\u03c1\u03bf\u03ba\u03bb\u03ae\u03c2", + "\u03b1\u03b3\u03b1\u03b8\u03bf\u03ba\u03bb\u03ae\u03c2", + "\u03b2\u03b5\u03bb\u03b9\u03c3\u03c3\u03ac\u03c1\u03b9\u03bf\u03c2", + "\u03b1\u03b8\u03b1\u03bd\u03ac\u03c3\u03b9\u03bf\u03c2", + "\u03bd\u03ad\u03b1\u03c1\u03c7\u03bf\u03c2", + "\u03b4\u03b9\u03bf\u03bc\u03ae\u03b4\u03b7\u03c2", + "\u03ba\u03af\u03bc\u03c9\u03bd", + "\u03c4\u03b7\u03bb\u03ad\u03bc\u03b1\u03c7\u03bf\u03c2", + "\u03b1\u03c1\u03c4\u03ad\u03bc\u03b7\u03c2", + "\u03b2\u03bb\u03ac\u03c3\u03b9\u03bf\u03c2", + "\u03b1\u03b9\u03bc\u03b9\u03bb\u03b9\u03b1\u03bd\u03cc\u03c2", + "\u03b5\u03c1\u03c1\u03af\u03ba\u03bf\u03c2", + "\u03b4\u03b1\u03bd\u03b9\u03ae\u03bb", + "\u03b5\u03c5\u03b8\u03cd\u03bc\u03b9\u03bf\u03c2", + "\u03c0\u03b1\u03c3\u03c7\u03ac\u03bb\u03b7\u03c2", + "\u03ba\u03ce\u03c3\u03c4\u03b1\u03c2", + "\u03ba\u03b7\u03c1\u03cd\u03ba\u03bf\u03c2", + "\u03c0\u03c5\u03b8\u03b1\u03b3\u03cc\u03c1\u03b1\u03c2", + "\u03be\u03b1\u03bd\u03b8\u03cc\u03c2", + "\u03c4\u03b9\u03bc\u03cc\u03b8\u03b5\u03bf\u03c2", + "\u03b1\u03bd\u03b8\u03bf\u03cd\u03bb\u03b7\u03c2", + "\u03b8\u03b5\u03bf\u03c7\u03ac\u03c1\u03b7\u03c2", + "\u03b9\u03b5\u03c1\u03ce\u03bd\u03c5\u03bc\u03bf\u03c2", + "\u03b1\u03bd\u03b4\u03c1\u03cc\u03bd\u03b9\u03ba\u03bf\u03c2", + "\u03b3\u03b1\u03bb\u03ac\u03c4\u03b9\u03bf\u03c2", + "\u03c3\u03c4\u03b1\u03bc\u03ac\u03c4\u03b7\u03c2", + "\u03b5\u03c5\u03c4\u03cd\u03c7\u03b9\u03bf\u03c2", + "\u03b3\u03b9\u03ac\u03bd\u03bd\u03b7\u03c2", + "\u03b1\u03c3\u03b7\u03bc\u03ae\u03c2", + "\u03b4\u03b9\u03b1\u03bc\u03b1\u03bd\u03c4\u03ae\u03c2", + "\u03c4\u03c1\u03b9\u03b1\u03bd\u03c4\u03ac\u03c6\u03c5\u03bb\u03bb\u03bf\u03c2", + "\u03b1\u03b3\u03b1\u03b8\u03cc\u03bd\u03b9\u03ba\u03bf\u03c2", + "\u03b1\u03c1\u03b9\u03c3\u03c4\u03bf\u03bc\u03ad\u03bd\u03b7\u03c2", + "\u03bb\u03b5\u03bf\u03bd\u03ac\u03c1\u03b4\u03bf\u03c2", + "\u03b1\u03b4\u03ac\u03bc", + "\u03c6\u03c9\u03ba\u03af\u03c9\u03bd", + "\u03c0\u03c1\u03b1\u03be\u03b9\u03c4\u03ad\u03bb\u03b7\u03c2", + "\u03b2\u03b1\u03c1\u03b4\u03ae\u03c2", + "\u03bb\u03ad\u03c9\u03bd", + "\u03c0\u03cd\u03c1\u03c1\u03bf\u03c2", + "\u03b1\u03bd\u03ac\u03c1\u03b3\u03c5\u03c1\u03bf\u03c2", + "\u03c3\u03c9\u03ba\u03c1\u03ac\u03c4\u03b7\u03c2", + "\u03bc\u03b1\u03ba\u03ac\u03c1\u03b9\u03bf\u03c2", + "\u03c7\u03c1\u03af\u03c3\u03c4\u03bf\u03c2", + "\u03c0\u03c1\u03bf\u03ba\u03cc\u03c0\u03b9\u03bf\u03c2", + "\u03c0\u03af\u03bd\u03b4\u03b1\u03c1\u03bf\u03c2", + "\u03bc\u03b9\u03ba\u03ad\u03c2", + "\u03b1\u03b2\u03c1\u03b1\u03ac\u03bc", + "\u03b2\u03b9\u03ba\u03ad\u03bd\u03c4\u03b9\u03bf\u03c2", + "\u03ba\u03ac\u03c1\u03bf\u03bb\u03bf\u03c2", + "\u03ba\u03bf\u03bc\u03bd\u03b7\u03bd\u03cc\u03c2", + "\u03b8\u03b5\u03cc\u03b4\u03c9\u03c1\u03bf\u03c2", + "\u03c0\u03b1\u03c1\u03ac\u03c3\u03c7\u03bf\u03c2", + "\u03bc\u03b9\u03bb\u03c4\u03b9\u03ac\u03b4\u03b7\u03c2", + "\u03b8\u03b5\u03cc\u03c6\u03b9\u03bb\u03bf\u03c2", + "\u03c3\u03c0\u03c5\u03c1\u03af\u03b4\u03c9\u03bd", + "\u03b6\u03ae\u03bd\u03c9\u03bd", + "\u03bc\u03b9\u03c7\u03ac\u03bb\u03b7\u03c2", + "\u03c0\u03bf\u03bb\u03c5\u03ba\u03c1\u03ac\u03c4\u03b7\u03c2", + "\u03b2\u03b1\u03bb\u03ac\u03bd\u03c4\u03b7\u03c2", + "\u03ad\u03ba\u03c4\u03bf\u03c1\u03b1\u03c2", + "\u03c4\u03c1\u03cd\u03c6\u03c9\u03bd", + "\u03ba\u03bb\u03ae\u03bc\u03b7\u03c2", + "\u03b1\u03c1\u03af\u03c3\u03c4\u03b1\u03c1\u03c7\u03bf\u03c2", + "\u03b1\u03b4\u03b1\u03bc\u03ac\u03bd\u03c4\u03b9\u03bf\u03c2", + "\u03bc\u03b5\u03b3\u03b1\u03ba\u03bb\u03ae\u03c2", + "\u03ba\u03c5\u03c0\u03c1\u03b9\u03b1\u03bd\u03cc\u03c2", + "\u03c3\u03c4\u03ad\u03c1\u03b3\u03b9\u03bf\u03c2", + "\u03b8\u03c1\u03b1\u03c3\u03cd\u03b2\u03bf\u03c5\u03bb\u03bf\u03c2", + "\u03b9\u03b5\u03c1\u03b5\u03bc\u03af\u03b1\u03c2", + "\u03b3\u03b1\u03c1\u03cd\u03c6\u03b1\u03bb\u03bb\u03bf\u03c2", + "\u03b3\u03b5\u03ce\u03c1\u03b3\u03b9\u03bf\u03c2", + "\u03b1\u03b8\u03b7\u03bd\u03b1\u03b3\u03cc\u03c1\u03b1\u03c2", + "\u03c1\u03af\u03b6\u03bf\u03c2", + "\u03b5\u03c5\u03b3\u03ad\u03bd\u03b9\u03bf\u03c2", + "\u03b9\u03ac\u03ba\u03c9\u03b2\u03bf\u03c2", + "\u03c0\u03b1\u03bd\u03c4\u03b1\u03b6\u03ae\u03c2", + "\u03bd\u03b5\u03bf\u03ba\u03bb\u03ae\u03c2", + "\u03bb\u03b1\u03bf\u03ba\u03c1\u03ac\u03c4\u03b7\u03c2", + "\u03c4\u03b6\u03b1\u03bd\u03ad\u03c4\u03bf\u03c2", + "\u03b5\u03c1\u03bc\u03cc\u03bb\u03b1\u03bf\u03c2", + "\u03b1\u03bc\u03b2\u03c1\u03cc\u03c3\u03b9\u03bf\u03c2", + "\u03ba\u03c5\u03c1\u03b9\u03ac\u03ba\u03bf\u03c2", + "\u03b8\u03b5\u03bf\u03c6\u03cd\u03bb\u03b1\u03ba\u03c4\u03bf\u03c2", + "\u03c3\u03bf\u03bb\u03bf\u03bc\u03ce\u03bd", + "\u03bb\u03bf\u03b3\u03bf\u03b8\u03ad\u03c4\u03b7\u03c2" + ], + "LAST_NAMES_FEMALE": [ + "\u03a0\u03b1\u03c0\u03b1\u03c4\u03b6\u03ae\u03ba\u03b1", + "\u039a\u03bf\u03c1\u03bf\u03bc\u03c0\u03cc\u03ba\u03b7", + "\u0393\u03b5\u03c9\u03c1\u03b3\u03bf\u03cd\u03bb\u03b1", + "\u03a3\u03c0\u03b1\u03bd\u03bf\u03c7\u03c1\u03b9\u03c3\u03c4\u03bf\u03b4\u03bf\u03cd\u03bb\u03bf\u03c5", + "\u03a3\u03b9\u03bc\u03b7\u03c4\u03bf\u03c0\u03bf\u03cd\u03bb\u03bf\u03c5", + "\u03a3\u03b9\u03bc\u03b9\u03c4\u03b6\u03ae", + "\u0391\u03c3\u03c3\u03b1\u03c1\u03b3\u03b9\u03c9\u03c4\u03ac\u03ba\u03b7", + "\u039a\u03c5\u03c1\u03b9\u03b1\u03bd\u03bd\u03ac\u03ba\u03b7", + "\u039a\u03b1\u03c1\u03c5\u03b4\u03ac", + "\u03a6\u03b9\u03bb\u03b9\u03ac\u03b3\u03ba\u03bf\u03c5", + "\u03a3\u03c6\u03b1\u03ba\u03b9\u03b1\u03bd\u03ac\u03ba\u03b7", + "\u039d\u03c4\u03b6\u03b9\u03b1\u03b2\u03af\u03b4\u03b1", + "\u03a7\u03c1\u03c5\u03c3\u03b9\u03ba\u03ac\u03ba\u03b7", + "\u039a\u03b1\u03c6\u03b1\u03bd\u03c4\u03ac\u03c1\u03b7", + "\u039d\u03af\u03ba\u03b1", + "\u0394\u03ae\u03bc\u03bf\u03c5", + "\u039b\u03b5\u03bd\u03c4\u03b6\u03af\u03bf\u03c5", + "\u03a0\u03b1\u03c0\u03b1\u03c7\u03c1\u03ae\u03c3\u03c4\u03bf\u03c5", + "\u039d\u03ac\u03bd\u03c4\u03c3\u03bf\u03c5", + "\u039c\u03c0\u03b9\u03bc\u03c0\u03af\u03c1\u03b7", + "\u039e\u03b1\u03bd\u03b8\u03bf\u03c0\u03bf\u03cd\u03bb\u03bf\u03c5", + "\u03a7\u03b1\u03c4\u03b6\u03ae", + "\u03a4\u03c3\u03b1\u03ba\u03af\u03c1\u03b7", + "\u03a4\u03ac\u03c4\u03c3\u03b7", + "\u0392\u03bf\u03c5\u03bb\u03b3\u03b1\u03c1\u03af\u03b4\u03bf\u03c5", + "\u039a\u03b1\u03bc\u03b9\u03bd\u03ac\u03c1\u03b7", + "\u039c\u03bf\u03c3\u03c7\u03bf\u03b2\u03ac\u03ba\u03b7", + "\u039b\u03b9\u03ac\u03ba\u03bf\u03c5", + "\u03a7\u03b1\u03c4\u03b6\u03b7\u03b2\u03bb\u03b1\u03c3\u03af\u03bf\u03c5", + "\u0392\u03b1\u03bb\u03b9\u03ac\u03ba\u03b1", + "\u0394\u03ce\u03c1\u03b7", + 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"\u039a\u03bf\u03bd\u03c4\u03bf\u03cd", + "\u039a\u03c9\u03bd\u03c3\u03c4\u03b1\u03bd\u03c4\u03bf\u03c0\u03bf\u03cd\u03bb\u03bf\u03c5", + "\u03a3\u03c4\u03c1\u03b1\u03c4\u03bf\u03b3\u03b9\u03ac\u03bd\u03bd\u03b7", + "\u0392\u03bf\u03c5\u03c4\u03c3\u03b9\u03bd\u03ac", + "\u0392\u03bb\u03ac\u03c7\u03bf\u03c5", + "\u039b\u03b9\u03bf\u03bb\u03b9\u03bf\u03c0\u03bf\u03cd\u03bb\u03bf\u03c5", + "\u03a3\u03b1\u03c1\u03c1\u03ae", + "\u039c\u03ae\u03c4\u03c3\u03bf\u03c5", + "\u03a4\u03bf\u03c5\u03bb\u03bf\u03cd\u03c0\u03b7", + "\u03a5\u03c6\u03b1\u03bd\u03c4\u03ae", + "\u039c\u03b1\u03c3\u03b9\u03ac\u03bb\u03b1", + "\u039a\u03b1\u03c1\u03ba\u03b1\u03bb\u03ad\u03c4\u03c3\u03b7", + "\u03a3\u03ac\u03bf\u03c5\u03b5\u03c1", + "\u03a1\u03ad\u03c0\u03c0\u03b1", + "\u039a\u03bf\u03bb\u03c4\u03c3\u03ac\u03ba\u03b7", + "\u039a\u03b1\u03c1\u03bf\u03bb\u03af\u03b4\u03bf\u03c5", + "\u039a\u03bf\u03c5\u03bb\u03bf\u03c7\u03ad\u03c1\u03b7", + "\u03a4\u03c3\u03b9\u03c9\u03bb\u03be", + 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+ "\u03a3\u03b5\u03bc\u03c0\u03ad\u03c0\u03bf\u03c5", + "\u039b\u03ad\u03ba\u03ba\u03b1", + "\u039c\u03c0\u03b5\u03c3\u03cd\u03c1\u03b7", + "\u03a3\u03cd\u03c8\u03b1", + "\u039c\u03b1\u03bc\u03b1\u03bb\u03ac", + "\u039a\u03bb\u03b5\u03b9\u03bd\u03ac\u03ba\u03b7", + "\u03a8\u03c5\u03c1\u03c1\u03ae", + "\u039a\u03b1\u03c1\u03b2\u03ad\u03bb\u03b7", + "\u03a3\u03b7\u03ba\u03c9\u03c4\u03af\u03b4\u03bf\u03c5", + "\u039a\u03af\u03c4\u03c3\u03bf\u03c5", + "\u03a0\u03c1\u03bf\u03cd\u03b2\u03b1", + "\u039a\u03b1\u03bc\u03c0\u03bf\u03cd\u03c1\u03b7", + "\u039a\u03b1\u03c1\u03b1\u03bc\u03ac\u03bd\u03b7", + "\u039c\u03b9\u03c7\u03b5\u03bb\u03ae", + "\u0393\u03b9\u03b1\u03ba\u03b1\u03bc\u03cc\u03b6\u03b7", + "\u0391\u03bb\u03b5\u03be\u03b1\u03bd\u03b4\u03c1\u03ac\u03ba\u03b7", + "\u0391\u03b3\u03c1\u03b1\u03c6\u03b9\u03ce\u03c4\u03b7", + "\u039a\u03c5\u03c1\u03b9\u03b1\u03ba\u03bf\u03c0\u03bf\u03cd\u03bb\u03bf\u03c5", + "\u03a3\u03c9\u03c4\u03b7\u03c1\u03bf\u03c0\u03bf\u03cd\u03bb\u03bf\u03c5", + 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+ "\u03a3\u03b9\u03b4\u03b7\u03c1\u03bf\u03c0\u03bf\u03cd\u03bb\u03bf\u03c5", + "\u039c\u03b1\u03c1\u03b3\u03b1\u03c1\u03b9\u03c4\u03ac\u03ba\u03b7", + "\u039c\u03b9\u03c7\u03b1\u03bb\u03ac\u03c1\u03bf\u03c5", + "\u03a4\u03c1\u03b9\u03b1\u03bd\u03c4\u03b1\u03c6\u03cd\u03bb\u03bb\u03bf\u03c5", + "\u039a\u03b1\u03c1\u03ba\u03b1\u03bd\u03ac\u03ba\u03b7", + "\u03a7\u03b1\u03bc\u03b1\u03bb\u03af\u03b4\u03bf\u03c5", + "\u0392\u03b1\u03c3\u03b9\u03bb\u03ac\u03ba\u03b7", + "\u0393\u03ba\u03bf\u03cd\u03bd\u03b7", + "\u03a1\u03cc\u03ba\u03ba\u03b1", + "\u0392\u03b1\u03c6\u03b5\u03b9\u03ac\u03b4\u03bf\u03c5", + "\u039a\u03bf\u03c5\u03c4\u03ba\u03b9\u03ac", + "\u03a0\u03b1\u03c0\u03b1\u03b8\u03b1\u03bd\u03b1\u03c3\u03af\u03bf\u03c5", + "\u03a3\u03c0\u03b1\u03c3\u03ad\u03b3\u03ba\u03bf\u03c5", + "\u0393\u03b5\u03c9\u03c1\u03b3\u03b9\u03ac\u03b4\u03bf\u03c5", + "\u0398\u03b5\u03bf\u03b4\u03c9\u03c1\u03bf\u03c0\u03bf\u03cd\u03bb\u03bf\u03c5", + 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"\u03a0\u03b1\u03c0\u03b1\u03bd\u03b4\u03c1\u03ad\u03bf\u03c5", + "\u03a3\u03b1\u03ba\u03b5\u03bb\u03bb\u03b1\u03c1\u03af\u03bf\u03c5", + "\u039a\u03bf\u03c5\u03ba\u03bf\u03c5\u03b8\u03ac\u03ba\u03b7" + ], + "FIRST_NAME": [ + "\u03b1\u03b8\u03b1\u03bd\u03b1\u03c3\u03af\u03b1", + "\u03ba\u03b1\u03c3\u03c3\u03ac\u03bd\u03b4\u03c1\u03b1", + "\u03b5\u03c5\u03c3\u03c4\u03c1\u03ac\u03c4\u03b9\u03bf\u03c2", + "\u03b4\u03b7\u03bc\u03bf\u03ba\u03c1\u03ac\u03c4\u03b7\u03c2", + "\u03b9\u03c3\u03b1\u03b2\u03ad\u03bb\u03bb\u03b1", + "\u03bc\u03b1\u03cd\u03c1\u03bf\u03c2", + "\u03b5\u03bb\u03b5\u03bf\u03bd\u03cc\u03c1\u03b1", + "\u03bd\u03b9\u03ba\u03ae\u03c4\u03b1\u03c2", + "\u03ad\u03be\u03b1\u03c1\u03c7\u03bf\u03c2", + "\u03b7\u03c1\u03cc\u03b4\u03bf\u03c4\u03bf\u03c2", + "\u03b4\u03bf\u03cd\u03ba\u03b9\u03c3\u03c3\u03b1", + "\u03ba\u03c5\u03c0\u03c1\u03b9\u03b1\u03bd\u03ae", + "\u03be\u03b5\u03bd\u03bf\u03c6\u03ce\u03bd", + "\u03b2\u03c1\u03c5\u03c3\u03b7\u03af\u03c2", + "\u03b4\u03b9\u03ba\u03b1\u03af\u03b1", + "\u03b9\u03bf\u03cd\u03bb\u03b9\u03bf\u03c2", + "\u03bb\u03bf\u03b3\u03bf\u03b8\u03ad\u03c4\u03b7\u03c2", + "\u03bb\u03b1\u03ad\u03c1\u03c4\u03b7\u03c2", + "\u03bc\u03b1\u03c4\u03af\u03bd\u03b1", + "\u03b2\u03b1\u03c3\u03af\u03bb\u03b5\u03b9\u03bf\u03c2", + "\u03b8\u03b1\u03bb\u03ae\u03c2", + "\u03b3\u03ba\u03cc\u03bb\u03c6\u03c9", + "\u03b1\u03b3\u03b1\u03b8\u03ae", + "\u03b1\u03bb\u03ad\u03be\u03b9\u03bf\u03c2", + "\u03c3\u03b1\u03c1\u03ac\u03bd\u03c4\u03b7\u03c2", + "\u03b4\u03b7\u03bc\u03bf\u03c3\u03b8\u03ad\u03bd\u03b7\u03c2", + "\u03b3\u03ba\u03af\u03ba\u03b1\u03c2", + "\u03c6\u03c1\u03b1\u03bd\u03c4\u03b6\u03ad\u03c3\u03ba\u03b1", + "\u03b8\u03b5\u03bf\u03b4\u03ce\u03c1\u03b1", + "\u03b5\u03c5\u03c3\u03c4\u03ac\u03b8\u03b9\u03bf\u03c2", + "\u03ba\u03bb\u03c5\u03c4\u03b1\u03b9\u03bc\u03bd\u03ae\u03c3\u03c4\u03c1\u03b1", + "\u03bc\u03b1\u03c5\u03c1\u03bf\u03cd\u03b4\u03b7\u03c2", + "\u03b5\u03bc\u03bc\u03b1\u03bd\u03bf\u03c5\u03ae\u03bb", + "\u03c3\u03b1\u03bc\u03bf\u03c5\u03ae\u03bb", + "\u03bd\u03b1\u03c0\u03bf\u03bb\u03ad\u03c9\u03bd", + "\u03c1\u03c9\u03bc\u03b1\u03bd\u03cc\u03c2", + "\u03bb\u03cd\u03c3\u03b1\u03bd\u03b4\u03c1\u03bf\u03c2", + "\u03ba\u03c9\u03bd\u03c3\u03c4\u03b1\u03bd\u03c4\u03af\u03b1", + "\u03b5\u03c1\u03bc\u03ae\u03c2", + "\u03c7\u03ac\u03c1\u03b7", + "\u03b1\u03c1\u03b3\u03cd\u03c1\u03b9\u03bf\u03c2", + "\u03b6\u03b1\u03c6\u03b5\u03af\u03c1\u03b7\u03c2", + "\u03b5\u03c5\u03c4\u03ad\u03c1\u03c0\u03b7", + "\u03bb\u03ac\u03b6\u03b1\u03c1\u03bf\u03c2", + "\u03ba\u03c1\u03c5\u03c3\u03c4\u03b1\u03bb\u03bb\u03ad\u03bd\u03b9\u03b1", + "\u03b1\u03bd\u03ad\u03c3\u03c4\u03b7\u03c2", + "\u03c0\u03bb\u03bf\u03cd\u03c4\u03b1\u03c1\u03c7\u03bf\u03c2", + "\u03c0\u03b5\u03bb\u03bf\u03c0\u03af\u03b4\u03b1\u03c2", + "\u03b2\u03b5\u03b1\u03c4\u03c1\u03af\u03ba\u03b7", + "\u03c0\u03b1\u03c3\u03c7\u03b1\u03bb\u03b9\u03ac", + "\u03c0\u03bb\u03ac\u03c4\u03c9\u03bd", + "\u03af\u03c9\u03bd", + "\u03bc\u03b1\u03c1\u03c9\u03c4\u03ad\u03c3\u03b1", + "\u03b7\u03c3\u03b1\u0390\u03b1\u03c2", + "\u03b9\u03c9\u03c3\u03b7\u03c6\u03af\u03bd\u03b1", + "\u03b1\u03c1\u03b3\u03c5\u03c1\u03bf\u03cd\u03bb\u03b1", + "\u03c0\u03b5\u03c1\u03b9\u03ba\u03bb\u03ae\u03c2", + "\u03c3\u03b1\u03b2\u03b2\u03bf\u03cd\u03bb\u03b1", + "\u03b1\u03b3\u03b1\u03bc\u03ad\u03bc\u03bd\u03c9\u03bd", + "\u03bd\u03af\u03ba\u03bf\u03c2", + "\u03c0\u03b5\u03c1\u03b9\u03ba\u03bb\u03b5\u03af\u03b1", + "\u03c7\u03c1\u03b9\u03c3\u03c4\u03bf\u03b4\u03bf\u03cd\u03bb\u03b1", + "\u03c7\u03c1\u03ae\u03c3\u03c4\u03bf\u03c2", + "\u03b9\u03c6\u03b9\u03b3\u03ad\u03bd\u03b5\u03b9\u03b1", + "\u03b5\u03c5\u03b4\u03bf\u03be\u03af\u03b1", + "\u03bc\u03b1\u03c4\u03b8\u03af\u03bb\u03b4\u03b7", + "\u03b1\u03b3\u03b7\u03c3\u03af\u03bb\u03b1\u03bf\u03c2", + "\u03b1\u03bd\u03b8\u03ae", + "\u03bb\u03b1\u03bc\u03c0\u03c1\u03b9\u03bd\u03ae", + "\u03c6\u03b1\u03bd\u03bf\u03cd\u03c1\u03b9\u03bf\u03c2", + 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"\u03b2\u03b1\u03bb\u03ad\u03c1\u03b9\u03b1", + "\u03ba\u03c5\u03c1\u03ac\u03c4\u03c3\u03b1", + "\u03b5\u03c1\u03c9\u03c6\u03af\u03bb\u03b7", + "\u03bc\u03b1\u03c1\u03af\u03b1", + "\u03c7\u03c1\u03b9\u03c3\u03c4\u03af\u03bd\u03b1", + "\u03c4\u03b6\u03ad\u03bd\u03b7", + "\u03b1\u03bb\u03ba\u03b9\u03bd\u03cc\u03b7", + "\u03c7\u03b1\u03c1\u03ac", + "\u03bc\u03b1\u03c1\u03b9\u03ac\u03bd\u03b8\u03b7", + "\u03b1\u03bc\u03c6\u03b9\u03c4\u03c1\u03af\u03c4\u03b7", + "\u03bc\u03b5\u03c1\u03cc\u03c0\u03b7", + "\u03b9\u03c9\u03ac\u03bd\u03bd\u03b1", + "\u03b9\u03bf\u03c5\u03bb\u03b9\u03b1\u03bd\u03cc\u03c2", + "\u03b8\u03b5\u03bf\u03b4\u03cc\u03c3\u03b7\u03c2", + "\u03b1\u03c6\u03ad\u03bd\u03c4\u03b7\u03c2", + "\u03b8\u03b5\u03ce\u03bd\u03b7", + "\u03b4\u03b1\u03bc\u03b9\u03b1\u03bd\u03cc\u03c2", + "\u03b8\u03b5\u03bf\u03c4\u03cc\u03ba\u03b7\u03c2", + "\u03c0\u03b1\u03bd\u03b1\u03b3\u03ae\u03c2", + "\u03b8\u03b5\u03bf\u03c7\u03b1\u03c1\u03bf\u03cd\u03bb\u03b1", + "\u03b1\u03c3\u03c0\u03b1\u03c3\u03af\u03b1", + "\u03c3\u03b5\u03b2\u03b1\u03c3\u03c4\u03b9\u03b1\u03bd\u03cc\u03c2", + "\u03b5\u03bb\u03ad\u03bd\u03b7", + "\u03c3\u03c9\u03c4\u03ae\u03c1\u03b9\u03bf\u03c2", + "\u03bb\u03bf\u03c5\u03ba\u03b9\u03b1\u03bd\u03cc\u03c2", + "\u03c1\u03bf\u03b4\u03cc\u03ba\u03bb\u03b5\u03b9\u03b1", + "\u03bf\u03b4\u03c5\u03c3\u03c3\u03ad\u03b1\u03c2", + "\u03c0\u03b1\u03c1\u03ad\u03c3\u03c3\u03b1", + "\u03bc\u03b1\u03b3\u03b4\u03b1\u03bb\u03b7\u03bd\u03ae", + "\u03b2\u03b9\u03ba\u03ad\u03bd\u03c4\u03b9\u03b1", + "\u03c6\u03bb\u03c9\u03c1\u03af\u03bd\u03b1", + "\u03bd\u03c4\u03b1\u03af\u03b6\u03b7", + "\u03b1\u03bb\u03ba\u03b9\u03b2\u03b9\u03ac\u03b4\u03b7\u03c2", + "\u03c7\u03b1\u03c1\u03b1\u03bb\u03b1\u03bc\u03c0\u03af\u03b1", + "\u03b1\u03ba\u03c1\u03b9\u03b2\u03ae", + "\u03bc\u03b5\u03bb\u03ad\u03c4\u03b9\u03bf\u03c2", + "\u03b8\u03b5\u03bf\u03c6\u03af\u03bb\u03b7", + "\u03b8\u03bf\u03c5\u03ba\u03c5\u03b4\u03af\u03b4\u03b7\u03c2", + "\u03ac\u03c1\u03b7\u03c2", + "\u03b2\u03b1\u03bb\u03b5\u03bd\u03c4\u03af\u03bd\u03b1", + "\u03b6\u03b1\u03c7\u03b1\u03c1\u03bf\u03cd\u03bb\u03b1", + "\u03c6\u03b5\u03b2\u03c1\u03c9\u03bd\u03af\u03b1", + "\u03b2\u03b1\u03bb\u03ad\u03c1\u03b9\u03bf\u03c2", + "\u03b2\u03ac\u03b3\u03b9\u03b1", + "\u03b1\u03bd\u03c4\u03af\u03b3\u03bf\u03bd\u03bf\u03c2", + "\u03c0\u03ac\u03c1\u03b9\u03c2", + "\u03b2\u03b5\u03bd\u03b5\u03c4\u03af\u03b1", + "\u03bb\u03ad\u03b1\u03bd\u03b4\u03c1\u03bf\u03c2", + "\u03c3\u03c0\u03ae\u03bb\u03b9\u03bf\u03c2", + "\u03b4\u03c1\u03ac\u03ba\u03c9\u03bd", + "\u03c1\u03b7\u03b3\u03bf\u03cd\u03bb\u03b1", + "\u03c0\u03bf\u03bb\u03c5\u03c7\u03c1\u03bf\u03bd\u03af\u03b1", + "\u03b1\u03c1\u03b5\u03c4\u03ae", + "\u03c3\u03c9\u03b6\u03bf\u03cd\u03c3\u03b1", + "\u03b5\u03bb\u03ad\u03c3\u03c3\u03b1", + "\u03ae\u03b2\u03b7", + "\u03b8\u03b5\u03bf\u03bb\u03bf\u03b3\u03af\u03b1", + "\u03c3\u03b5\u03bc\u03af\u03bd\u03b1", + "\u03b1\u03b3\u03ac\u03b8\u03b7", + "\u03bc\u03b1\u03c1\u03b3\u03b1\u03c1\u03af\u03c4\u03b1", + "\u03bc\u03b5\u03bd\u03ad\u03bb\u03b1\u03bf\u03c2", + "\u03c0\u03bf\u03bb\u03c5\u03be\u03ad\u03bd\u03b7", + "\u03b1\u03c3\u03c4\u03ad\u03c1\u03b9\u03bf\u03c2", + "\u03b3\u03c1\u03b7\u03b3\u03cc\u03c1\u03b9\u03bf\u03c2", + "\u03c3\u03c4\u03b1\u03bc\u03ac\u03c4\u03b9\u03bf\u03c2", + "\u03ba\u03c5\u03c0\u03b1\u03c1\u03b9\u03c3\u03c3\u03af\u03b1", + "\u03b1\u03c7\u03b9\u03bb\u03bb\u03ad\u03b1\u03c2", + "\u03ba\u03b1\u03c1\u03c5\u03bf\u03c6\u03c5\u03bb\u03bb\u03b9\u03ac", + "\u03b1\u03c3\u03b7\u03bc\u03ac\u03ba\u03b7\u03c2", + "\u03cc\u03b8\u03c9\u03bd", + "\u03bf\u03bb\u03cd\u03bc\u03c0\u03b9\u03b1", + "\u03b5\u03c1\u03bc\u03b9\u03cc\u03bd\u03b7", + "\u03bd\u03af\u03ba\u03b1\u03bd\u03b4\u03c1\u03bf\u03c2", + "\u03c1\u03b1\u03c7\u03ae\u03bb", + "\u03c0\u03b1\u03c5\u03c3\u03b1\u03bd\u03af\u03b1\u03c2", + "\u03b8\u03b5\u03bf\u03b4\u03cc\u03c4\u03b7", + "\u03ba\u03bf\u03c3\u03bc\u03ac\u03c2", + "\u03b8\u03b7\u03c3\u03b5\u03cd\u03c2", + "\u03c5\u03b2\u03cc\u03bd\u03bd\u03b7", + "\u03b1\u03c1\u03b9\u03c3\u03c4\u03ad\u03b1", + "\u03b9\u03c3\u03af\u03b4\u03c9\u03c1\u03bf\u03c2", + "\u03ac\u03bb\u03ba\u03b7\u03c3\u03c4\u03b9\u03c2", + "\u03bb\u03b5\u03ce\u03bd\u03b7", + "\u03b8\u03b5\u03cc\u03ba\u03bb\u03b7\u03c4\u03bf\u03c2", + "\u03ac\u03bd\u03bd\u03b1", + "\u03b8\u03b5\u03bf\u03c6\u03ac\u03bd\u03b7\u03c2", + "\u03b8\u03b5\u03cc\u03c6\u03c1\u03b1\u03c3\u03c4\u03bf\u03c2", + "\u03bc\u03b1\u03b3\u03b4\u03b1\u03bb\u03b7\u03bd\u03cc\u03c2", + "\u03b1\u03bd\u03b1\u03c3\u03c4\u03ac\u03c3\u03b9\u03bf\u03c2", + "\u03bd\u03b1\u03b8\u03b1\u03bd\u03b1\u03ae\u03bb", + "\u03bd\u03b5\u03cc\u03ba\u03bb\u03b5\u03b9\u03b1", + "\u03bc\u03c5\u03c1\u03c4\u03ce", + "\u03b1\u03b3\u03b1\u03b8\u03ac\u03b3\u03b3\u03b5\u03bb\u03bf\u03c2", + "\u03ba\u03b5\u03c1\u03b1\u03c3\u03b9\u03ac", + "\u03b8\u03c9\u03bc\u03b1\u03af\u03c2", + "\u03bb\u03c5\u03b4\u03af\u03b1", + "\u03b5\u03bb\u03b5\u03c5\u03b8\u03b5\u03c1\u03af\u03b1", + "\u03c0\u03bf\u03bb\u03c5\u03c7\u03c1\u03cc\u03bd\u03b9\u03bf\u03c2", + "\u03ba\u03b1\u03bb\u03bb\u03af\u03bd\u03b9\u03ba\u03bf\u03c2", + "\u03c0\u03b1\u03cd\u03bb\u03bf\u03c2", + "\u03b1\u03bd\u03c4\u03c9\u03bd\u03af\u03b1", + "\u03c7\u03c1\u03c5\u03c3\u03cc\u03c3\u03c4\u03bf\u03bc\u03bf\u03c2", + "\u03c7\u03c1\u03c5\u03c3\u03cc\u03c3\u03c4\u03bf\u03bc\u03b7", + "\u03c3\u03c9\u03c4\u03ae\u03c1\u03b7\u03c2", + "\u03b2\u03bb\u03b1\u03c3\u03af\u03b1", + "\u03c4\u03c3\u03b1\u03bc\u03c0\u03af\u03ba\u03bf\u03c2", + "\u03b4\u03af\u03ba\u03b1\u03b9\u03bf\u03c2", + "\u03b2\u03b1\u03c1\u03c3\u03ac\u03bc\u03bf\u03c2", + "\u03b2\u03b5\u03bb\u03b9\u03c3\u03c3\u03b1\u03c1\u03af\u03b1", + "\u03c7\u03c1\u03c5\u03c3\u03b1\u03c5\u03b3\u03ae", + "\u03c4\u03b9\u03bc\u03bf\u03bb\u03ad\u03c9\u03bd", + "\u03b1\u03bd\u03b4\u03c1\u03bf\u03bc\u03ad\u03b4\u03b1", + "\u03c1\u03ad\u03b1", + "\u03be\u03ad\u03bd\u03b7", + "\u03b4\u03b9\u03bf\u03b3\u03ad\u03bd\u03b7\u03c2", + "\u03bc\u03b1\u03c5\u03c1\u03af\u03ba\u03b9\u03bf\u03c2", + "\u03c0\u03b5\u03bb\u03b1\u03b3\u03af\u03b1", + "\u03b1\u03bb\u03b5\u03be\u03ac\u03bd\u03b4\u03c1\u03b1", + "\u03b4\u03b9\u03bf\u03bd\u03cd\u03c3\u03b9\u03bf\u03c2", + "\u03b1\u03c1\u03b3\u03c5\u03c1\u03ce", + "\u03b5\u03bb\u03c0\u03af\u03c2", + "\u03c7\u03c1\u03b9\u03c3\u03c4\u03cc\u03c6\u03b9\u03bb\u03b7", + "\u03b8\u03b7\u03c1\u03b5\u03c3\u03af\u03b1", + "\u03b7\u03bb\u03b9\u03ac\u03bd\u03b1", + "\u03c1\u03cc\u03b6\u03b1", + "\u03c7\u03c1\u03c5\u03c3\u03bf\u03b2\u03b1\u03bb\u03ac\u03bd\u03c4\u03b9\u03bf\u03c2", + "\u03b9\u03c3\u03b9\u03b4\u03ce\u03c1\u03b1", + "\u03ae\u03bb\u03b9\u03b1", + "\u03bc\u03ac\u03c1\u03b8\u03b1", + "\u03b3\u03b1\u03bb\u03b7\u03bd\u03cc\u03c2", + "\u03c3\u03ac\u03c1\u03c1\u03b1", + "\u03c6\u03b1\u03af\u03b4\u03c9\u03bd", + "\u03ba\u03b1\u03bb\u03bb\u03b9\u03c1\u03c1\u03cc\u03b7", + "\u03ba\u03b1\u03bd\u03ad\u03bb\u03bb\u03b1", + "\u03c1\u03b5\u03b2\u03ad\u03ba\u03b1", + "\u03bd\u03b5\u03c1\u03b1\u03c4\u03b6\u03b9\u03ac", + "\u03c7\u03c1\u03b9\u03c3\u03c4\u03bf\u03c6\u03cc\u03c1\u03b1", + "\u03c1\u03bf\u03b4\u03ac\u03bd\u03b8\u03b7", + "\u03bb\u03b5\u03c9\u03bd\u03af\u03b4\u03b1\u03c2", + "\u03c0\u03b1\u03bd\u03bf\u03c1\u03bc\u03af\u03c4\u03b7\u03c2", + "\u03c0\u03c1\u03bf\u03bc\u03b7\u03b8\u03ad\u03b1\u03c2", + "\u03cc\u03bc\u03b7\u03c1\u03bf\u03c2", + "\u03b1\u03c5\u03b3\u03ad\u03c1\u03b7\u03c2", + "\u03b6\u03b1\u03c6\u03b5\u03b9\u03c1\u03af\u03b1", + "\u03b2\u03b9\u03c1\u03b3\u03b9\u03bd\u03af\u03b1", + "\u03b2\u03b9\u03ba\u03c4\u03c9\u03c1\u03af\u03b1", + "\u03c3\u03c4\u03ad\u03c6\u03b1\u03bd\u03bf\u03c2", + "\u03b1\u03bb\u03ad\u03be\u03b1\u03bd\u03b4\u03c1\u03bf\u03c2", + "\u03ba\u03b1\u03bb\u03c5\u03c8\u03ce", + "\u03b1\u03bb\u03ba\u03bc\u03ae\u03bd\u03b7", + "\u03b1\u03c5\u03b3\u03bf\u03c5\u03c3\u03c4\u03af\u03bd\u03b1", + "\u03b9\u03bf\u03c1\u03b4\u03b1\u03bd\u03af\u03b1", + "\u03c3\u03c5\u03bc\u03b5\u03ce\u03bd", + "\u03c3\u03c5\u03bc\u03b5\u03c9\u03bd\u03af\u03b1", + "\u03ba\u03bb\u03b5\u03bf\u03c0\u03ac\u03c4\u03c1\u03b1", + "\u03c3\u03c5\u03bc\u03ad\u03bb\u03b1", + "\u03ba\u03c5\u03c1\u03b9\u03b1\u03b6\u03ae\u03c2", + "\u03c0\u03bf\u03bb\u03cd\u03ba\u03b1\u03c1\u03c0\u03bf\u03c2", + "\u03b5\u03c5\u03bc\u03ad\u03bd\u03b9\u03bf\u03c2", + "\u03ba\u03c9\u03bd\u03c3\u03c4\u03b1\u03bd\u03c4\u03af\u03bd\u03bf\u03c2", + "\u03b1\u03bd\u03c4\u03b9\u03b3\u03cc\u03bd\u03b7", + "\u03c0\u03bf\u03bb\u03cd\u03b4\u03c9\u03c1\u03bf\u03c2", + "\u03b1\u03c1\u03c7\u03ad\u03bb\u03b1\u03bf\u03c2", + "\u03b2\u03b5\u03bd\u03b9\u03b6\u03ad\u03bb\u03bf\u03c2", + "\u03b2\u03b5\u03c1\u03bf\u03bd\u03af\u03ba\u03b7", + "\u03b3\u03b9\u03bf\u03bb\u03ac\u03bd\u03c4\u03b1", + "\u03b5\u03c1\u03c9\u03c4\u03cc\u03ba\u03c1\u03b9\u03c4\u03bf\u03c2", + "\u03c3\u03c0\u03ac\u03c1\u03c4\u03b7", + "\u03ba\u03b9\u03ba\u03b9\u03bb\u03af\u03b1", + "\u03c1\u03bf\u03b4\u03b1\u03bc\u03ac\u03bd\u03b8\u03b7", + "\u03b8\u03c9\u03bc\u03ac\u03c2", + "\u03c7\u03b1\u03c1\u03af\u03ba\u03bb\u03b5\u03b9\u03b1", + "\u03bc\u03b7\u03bb\u03b9\u03ac", + "\u03c3\u03c4\u03b5\u03c1\u03b3\u03b9\u03b1\u03bd\u03bd\u03ce", + "\u03b3\u03b5\u03c3\u03b8\u03b7\u03bc\u03b1\u03bd\u03ae", + "\u03b1\u03c3\u03b7\u03bc\u03af\u03bd\u03b1", + "\u03b5\u03c6\u03c1\u03b1\u03af\u03bc", + "\u03c0\u03bf\u03bb\u03c5\u03b6\u03ce\u03b7\u03c2", + "\u03c6\u03b9\u03bb\u03ae\u03bc\u03c9\u03bd", + "\u03bc\u03b7\u03bd\u03ac\u03c2", + "\u03b1\u03c0\u03cc\u03c3\u03c4\u03bf\u03bb\u03bf\u03c2", + "\u03bd\u03bf\u03bc\u03b9\u03ba\u03ae", + "\u03b9\u03c9\u03c3\u03ae\u03c6", + "\u03b1\u03ba\u03c1\u03b9\u03b2\u03cc\u03c2", + "\u03c0\u03b1\u03bd\u03b1\u03b3\u03b9\u03ce\u03c4\u03b7\u03c2", + "\u03b1\u03c1\u03b9\u03c3\u03c4\u03bf\u03c4\u03ad\u03bb\u03b7\u03c2", + "\u03b1\u03b8\u03b7\u03bd\u03bf\u03b4\u03ce\u03c1\u03b1", + "\u03b5\u03c0\u03b1\u03bc\u03b5\u03b9\u03bd\u03ce\u03bd\u03b4\u03b1\u03c2", + "\u03b1\u03bd\u03bd\u03af\u03ba\u03b1", + "\u03bf\u03b4\u03c5\u03c3\u03c3\u03b5\u03cd\u03c2", + "\u03b9\u03bd\u03ce", + "\u03b4\u03ac\u03c6\u03bd\u03b7", + "\u03ba\u03c5\u03b4\u03c9\u03bd\u03af\u03b1", + "\u03b1\u03b3\u03b1\u03c0\u03b7\u03c4\u03cc\u03c2", + "\u03c3\u03c4\u03c5\u03bb\u03b9\u03b1\u03bd\u03ae", + "\u03b5\u03c5\u03c3\u03b5\u03b2\u03b5\u03af\u03b1", + "\u03b1\u03b4\u03b1\u03bc\u03b1\u03bd\u03c4\u03af\u03b1", + "\u03b3\u03c1\u03b1\u03bc\u03bc\u03b1\u03c4\u03b9\u03ba\u03ae", + "\u03c6\u03bf\u03af\u03b2\u03bf\u03c2", + "\u03b2\u03ac\u03b9\u03bf\u03c2", + "\u03c4\u03b1\u03c4\u03b9\u03ac\u03bd\u03b1", + "\u03bf\u03c1\u03c6\u03ad\u03b1\u03c2", + "\u03b4\u03b7\u03bc\u03bf\u03cd\u03bb\u03b1", + "\u03c1\u03ac\u03bb\u03bb\u03b7\u03c2", + "\u03c3\u03b5\u03b2\u03b1\u03c3\u03c4\u03ae", + "\u03bc\u03af\u03bd\u03c9\u03b1\u03c2", + "\u03c3\u03ac\u03b2\u03b2\u03b1\u03c2", + "\u03bb\u03b5\u03bc\u03bf\u03bd\u03ae\u03c2", + "\u03b5\u03c1\u03b1\u03c4\u03ce", + "\u03c6\u03b1\u03bd\u03ae", + "\u03b2\u03b1\u03bb\u03b5\u03bd\u03c4\u03af\u03bd\u03bf\u03c2", + "\u03b6\u03b7\u03bd\u03bf\u03b2\u03af\u03b1", + "\u03c4\u03b1\u03be\u03af\u03b1\u03c1\u03c7\u03bf\u03c2", + "\u03c0\u03bf\u03bb\u03cd\u03b2\u03b9\u03bf\u03c2", + "\u03c6\u03c1\u03b1\u03b3\u03ba\u03af\u03c3\u03ba\u03bf\u03c2", + "\u03bb\u03b1\u03c3\u03ba\u03b1\u03c1\u03af\u03bd\u03b1", + "\u03b9\u03b3\u03bd\u03b1\u03c4\u03af\u03b1", + "\u03c3\u03c4\u03c5\u03bb\u03b9\u03b1\u03bd\u03cc\u03c2", + "\u03bd\u03af\u03ba\u03c9\u03bd", + "\u03c7\u03c1\u03b9\u03c3\u03c4\u03cc\u03b4\u03bf\u03c5\u03bb\u03bf\u03c2", + "\u03c6\u03c1\u03af\u03be\u03bf\u03c2", + "\u03b4\u03b7\u03bc\u03ae\u03c4\u03c1\u03b9\u03bf\u03c2", + "\u03b1\u03c1\u03c7\u03b9\u03bc\u03ae\u03b4\u03b7\u03c2", + "\u03c0\u03b1\u03c5\u03bb\u03af\u03bd\u03b1", + "\u03b1\u03bd\u03b1\u03be\u03b1\u03b3\u03cc\u03c1\u03b1\u03c2", + "\u03c7\u03b9\u03bf\u03bd\u03b9\u03ac", + "\u03c4\u03c1\u03b9\u03c3\u03b5\u03cd\u03b3\u03b5\u03bd\u03b7", + "\u03c7\u03ac\u03c1\u03b9\u03c2", + "\u03c3\u03c0\u03c5\u03c1\u03b9\u03b4\u03bf\u03cd\u03bb\u03b1", + "\u03b1\u03af\u03b1\u03c2", + "\u03bd\u03b9\u03ba\u03cc\u03bb\u03b1\u03bf\u03c2", + "\u03c6\u03bb\u03c9\u03c1\u03b5\u03bd\u03c4\u03af\u03b1", + "\u03b1\u03b3\u03b3\u03b5\u03bb\u03ae\u03c2", + "\u03bd\u03b5\u03ba\u03c4\u03ac\u03c1\u03b9\u03bf\u03c2", + "\u03b1\u03bd\u03c4\u03cd\u03c0\u03b1\u03c2", + "\u03b5\u03c5\u03ac\u03b3\u03b3\u03b5\u03bb\u03bf\u03c2", + "\u03b4\u03b7\u03bc\u03ae\u03c4\u03c1\u03b7\u03c2", + "\u03c0\u03b5\u03c1\u03b9\u03c3\u03c4\u03ad\u03c1\u03b1", + "\u03b5\u03c5\u03ba\u03bb\u03b5\u03af\u03b4\u03b7\u03c2", + "\u03ba\u03c5\u03c1\u03b9\u03b1\u03ba\u03ae", + "\u03c6\u03c9\u03c4\u03b5\u03b9\u03bd\u03cc\u03c2", + "\u03b4\u03c1\u03cc\u03c3\u03bf\u03c2", + "\u03ba\u03bb\u03b5\u03bf\u03bd\u03af\u03ba\u03b7", + "\u03b6\u03c9\u03ae", + "\u03b1\u03bd\u03b8\u03bf\u03cd\u03bb\u03b1", + "\u03b1\u03bd\u03ac\u03c1\u03b3\u03c5\u03c1\u03b7", + "\u03c3\u03c4\u03b5\u03c6\u03b1\u03bd\u03af\u03b1", + "\u03b1\u03bd\u03c4\u03af\u03c0\u03b1\u03c4\u03c1\u03bf\u03c2", + "\u03b4\u03c9\u03c1\u03cc\u03b8\u03b5\u03bf\u03c2", + "\u03b1\u03b8\u03b7\u03bd\u03ac", + "\u03c0\u03ad\u03c4\u03c1\u03b1", + "\u03ac\u03b3\u03b3\u03b5\u03bb\u03bf\u03c2", + "\u03b4\u03b1\u03bc\u03b1\u03c3\u03ba\u03b7\u03bd\u03ae", + "\u03c1\u03ae\u03b3\u03b1\u03c2", + "\u03c1\u03bf\u03b4\u03cc\u03c6\u03bb\u03bf\u03c2", + "\u03b4\u03bf\u03bc\u03ae\u03bd\u03b9\u03ba\u03bf\u03c2", + "\u03b9\u03c3\u03b1\u03ac\u03ba", + "\u03bc\u03b1\u03c4\u03b8\u03b1\u03af\u03bf\u03c2", + "\u03b4\u03c9\u03c1\u03bf\u03b8\u03ad\u03b1", + "\u03bc\u03ac\u03c1\u03b9\u03bf\u03c2", + "\u03bc\u03ac\u03c1\u03ba\u03bf\u03c2", + "\u03b4\u03ae\u03bc\u03bf\u03c2", + "\u03b2\u03bb\u03b1\u03b4\u03af\u03bc\u03b7\u03c1\u03bf\u03c2", + "\u03c3\u03bf\u03c6\u03af\u03b1", + "\u03b8\u03b5\u03bf\u03c0\u03af\u03c3\u03c4\u03b7", + "\u03bc\u03ad\u03bd\u03b1\u03bd\u03b4\u03c1\u03bf\u03c2", + "\u03c0\u03bf\u03bb\u03c5\u03c4\u03af\u03bc\u03b7", + "\u03ae\u03c1\u03b1", + "\u03c6\u03bb\u03bf\u03c1\u03b9\u03ac\u03bd\u03c4", + "\u03c1\u03bf\u03b4\u03b9\u03ac", + "\u03bc\u03b5\u03bb\u03ad\u03c4\u03b9\u03b1", + "\u03b5\u03c5\u03c1\u03cd\u03ba\u03bb\u03b5\u03b9\u03b1", + "\u03ac\u03c1\u03b9\u03c3\u03c4\u03bf\u03c2", + "\u03b9\u03c9\u03ac\u03bd\u03bd\u03b7\u03c2", + "\u03c3\u03bf\u03c5\u03bb\u03c4\u03ac\u03bd\u03b1", + "\u03c0\u03b1\u03bd\u03c4\u03b5\u03bb\u03b5\u03ae\u03bc\u03c9\u03bd", + "\u03ba\u03bb\u03b5\u03cc\u03c0\u03b1\u03c2", + "\u03b9\u03ac\u03c3\u03bf\u03bd\u03b1\u03c2", + "\u03bc\u03b1\u03bb\u03b2\u03af\u03bd\u03b1", + "\u03bc\u03c5\u03c1\u03c3\u03af\u03bd\u03b7", + "\u03af\u03c1\u03b9\u03c2", + "\u03c3\u03b9\u03c1\u03b1\u03bd\u03bf\u03cd\u03c2", + "\u03c3\u03c9\u03c4\u03b7\u03c1\u03af\u03b1", + "\u03bb\u03b5\u03bc\u03bf\u03bd\u03b9\u03ac", + "\u03b5\u03c5\u03b8\u03b1\u03bb\u03af\u03b1", + "\u03c0\u03bf\u03c5\u03bb\u03c7\u03b5\u03c1\u03af\u03b1", + "\u03b2\u03c1\u03b1\u03c3\u03af\u03b4\u03b1\u03c2", + "\u03b8\u03b5\u03bc\u03b9\u03c3\u03c4\u03cc\u03ba\u03bb\u03b5\u03b9\u03b1", + "\u03ba\u03b1\u03bb\u03bb\u03af\u03bd\u03b9\u03ba\u03b7", + "\u03b1\u03bc\u03b1\u03bb\u03af\u03b1", + "\u03b2\u03b1\u03c3\u03af\u03bb\u03b7\u03c2", + "\u03b1\u03bb\u03af\u03ba\u03b7", + "\u03b9\u03b5\u03c1\u03cc\u03b8\u03b5\u03bf\u03c2", + "\u03bb\u03bf\u03c5\u03af\u03b6\u03b1", + "\u03b8\u03ad\u03c4\u03b9\u03c2", + "\u03b7\u03ce", + "\u03b1\u03b9\u03bc\u03b9\u03bb\u03af\u03b1", + "\u03b8\u03b5\u03cc\u03c0\u03b9\u03c3\u03c4\u03bf\u03c2", + "\u03bb\u03b5\u03c5\u03ba\u03bf\u03b8\u03ad\u03b1", + "\u03b5\u03c5\u03c0\u03c1\u03b1\u03be\u03af\u03b1", + "\u03b5\u03b9\u03c1\u03b7\u03bd\u03b1\u03af\u03bf\u03c2", + "\u03bb\u03bf\u03c5\u03ba\u03af\u03b1", + "\u03b8\u03b5\u03bf\u03b4\u03bf\u03c3\u03af\u03b1", + "\u03b4\u03b7\u03bc\u03cc\u03ba\u03c1\u03b9\u03c4\u03bf\u03c2", + "\u03c3\u03c0\u03c5\u03c1\u03ac\u03bd\u03bd\u03b1", + "\u03b5\u03cd\u03ba\u03bb\u03b5\u03b9\u03b1", + "\u03bc\u03b5\u03bb\u03ad\u03bd\u03b9\u03b1", + "\u03c0\u03b1\u03c1\u03b1\u03c3\u03ba\u03b5\u03c5\u03ac\u03c2", + "\u03bb\u03ac\u03c3\u03ba\u03b1\u03c1\u03b7\u03c2", + "\u03c7\u03c1\u03c5\u03c3\u03bf\u03b2\u03b1\u03bb\u03ac\u03bd\u03c4\u03bf\u03c5", + "\u03ba\u03bb\u03b5\u03ac\u03bd\u03b8\u03b7\u03c2", + "\u03c7\u03c1\u03c5\u03c3\u03bf\u03cd\u03bb\u03b1", + "\u03b1\u03bd\u03b1\u03c4\u03bf\u03bb\u03ae", + "\u03b1\u03b7\u03b4\u03cc\u03bd\u03b1", + "\u03b1\u03c3\u03c4\u03ad\u03c1\u03c9", + "\u03b5\u03c5\u03c3\u03c4\u03c1\u03b1\u03c4\u03af\u03b1", + "\u03b9\u03bf\u03c5\u03bb\u03af\u03b1", + "\u03b3\u03b5\u03bd\u03bf\u03b2\u03ad\u03c6\u03b1", + "\u03ba\u03bb\u03ad\u03b1\u03c1\u03c7\u03bf\u03c2", + "\u03c4\u03b7\u03bb\u03b5\u03bc\u03b1\u03c7\u03bf\u03c2", + "\u03b2\u03b1\u03c1\u03b8\u03bf\u03bb\u03bf\u03bc\u03b1\u03af\u03bf\u03c2", + "\u03ba\u03bf\u03bd\u03b4\u03c5\u03bb\u03af\u03b1", + "\u03c6\u03b9\u03bb\u03af\u03c0\u03c0\u03b1", + "\u03bd\u03b9\u03ba\u03b7\u03c4\u03af\u03b1", + "\u03bc\u03b9\u03c7\u03b1\u03ad\u03bb\u03b1", + "\u03c4\u03b5\u03c1\u03c8\u03b9\u03c7\u03cc\u03c1\u03b7", + "\u03bc\u03b1\u03c4\u03c1\u03ce\u03bd\u03b7", + "\u03b1\u03cd\u03b3\u03bf\u03c5\u03c3\u03c4\u03bf\u03c2", + "\u03c3\u03ce\u03b6\u03c9\u03bd", + "\u03af\u03ba\u03b1\u03c1\u03bf\u03c2", + "\u03b1\u03bd\u03b1\u03c3\u03c4\u03b1\u03c3\u03af\u03b1", + "\u03c3\u03cc\u03bb\u03c9\u03bd", + "\u03b7\u03c1\u03ac\u03ba\u03bb\u03b5\u03b9\u03b1", + "\u03ba\u03b1\u03bb\u03bb\u03b9\u03c1\u03cc\u03b7", + "\u03c1\u03b5\u03b3\u03b3\u03af\u03bd\u03b1", + "\u03c4\u03b1\u03be\u03b9\u03ac\u03c1\u03c7\u03b7\u03c2", + "\u03c0\u03b1\u03c1\u03b1\u03c3\u03ba\u03b5\u03c5\u03ae", + "\u03b1\u03c5\u03b3\u03ae", + "\u03c3\u03ad\u03c1\u03b3\u03b9\u03bf\u03c2", + "\u03b8\u03b5\u03bf\u03c6\u03cd\u03bb\u03b1\u03ba\u03c4\u03b7", + "\u03b3\u03b9\u03ce\u03c1\u03b3\u03bf\u03c2", + "\u03b7\u03c1\u03b1\u03ba\u03bb\u03ae\u03c2", + "\u03b1\u03c1\u03b9\u03c3\u03c4\u03cc\u03b2\u03bf\u03c5\u03bb\u03bf\u03c2", + "\u03b6\u03b1\u03c7\u03b1\u03c1\u03af\u03b1\u03c2", + "\u03c7\u03c1\u03c5\u03c3\u03bf\u03b2\u03b1\u03bb\u03ac\u03bd\u03c4\u03c9", + "\u03bb\u03bf\u03c5\u03bb\u03bf\u03c5\u03b4\u03ad\u03bd\u03b9\u03b1", + "\u03c3\u03bf\u03c6\u03bf\u03ba\u03bb\u03ae\u03c2", + "\u03c0\u03b1\u03b3\u03ce\u03bd\u03b1", + "\u03c7\u03ac\u03b9\u03b4\u03c9", + "\u03b5\u03c5\u03c1\u03b9\u03c0\u03af\u03b4\u03b7\u03c2", + "\u03bc\u03b1\u03c1\u03c4\u03af\u03bd\u03bf\u03c2", + "\u03c7\u03b1\u03c1\u03ac\u03bb\u03b1\u03bc\u03c0\u03bf\u03c2", + "\u03c3\u03b5\u03c1\u03b1\u03c6\u03b5\u03af\u03bc", + "\u03bc\u03ac\u03bd\u03b8\u03b1", + "\u03c7\u03b1\u03c1\u03af\u03bb\u03b1\u03bf\u03c2", + "\u03b2\u03b1\u03bb\u03ac\u03bd\u03c4\u03c9", + "\u03b1\u03bd\u03c4\u03ce\u03bd\u03b9\u03bf\u03c2", + "\u03c3\u03c4\u03b5\u03c1\u03b3\u03b9\u03b1\u03bd\u03ae", + "\u03bc\u03b1\u03c1\u03af\u03bd\u03b1", + "\u03b4\u03ad\u03c3\u03c0\u03bf\u03b9\u03bd\u03b1", + "\u03bd\u03b9\u03ba\u03bf\u03bb\u03ad\u03c4\u03b1", + "\u03b8\u03b5\u03cc\u03b4\u03bf\u03c5\u03bb\u03bf\u03c2", + "\u03c0\u03b1\u03bd\u03c9\u03c1\u03b1\u03af\u03b1", + "\u03bb\u03ac\u03bc\u03c0\u03c1\u03bf\u03c2", + "\u03b9\u03bf\u03c1\u03b4\u03ac\u03bd\u03b7\u03c2", + "\u03b1\u03c0\u03bf\u03c3\u03c4\u03bf\u03bb\u03af\u03b1", + "\u03b1\u03ba\u03c1\u03af\u03c4\u03b1\u03c2", + "\u03c6\u03b9\u03bb\u03bf\u03bc\u03ae\u03bb\u03b1", + "\u03b9\u03b1\u03ba\u03c9\u03b2\u03af\u03bd\u03b1", + "\u03c0\u03b7\u03b3\u03ae", + "\u03b2\u03b7\u03c3\u03c3\u03b1\u03c1\u03af\u03c9\u03bd", + "\u03c3\u03b1\u03bb\u03ce\u03bc\u03b7", + "\u03b5\u03c1\u03b9\u03ad\u03c4\u03b1", + "\u03b6\u03b7\u03bd\u03cc\u03b2\u03b9\u03bf\u03c2", + "\u03b1\u03c1\u03c4\u03ad\u03bc\u03b9\u03bf\u03c2", + "\u03ac\u03bd\u03b8\u03b9\u03bc\u03bf\u03c2", + "\u03b8\u03b5\u03bf\u03bb\u03cc\u03b3\u03bf\u03c2", + "\u03c0\u03b1\u03bd\u03b1\u03b3\u03b9\u03ce\u03c4\u03b1", + "\u03b4\u03b1\u03bc\u03b1\u03c3\u03ba\u03b7\u03bd\u03cc\u03c2", + "\u03c6\u03b9\u03bb\u03b9\u03ce", + "\u03c3\u03bf\u03c5\u03bc\u03ad\u03bb\u03b1", + "\u03bc\u03b5\u03c4\u03b1\u03be\u03af\u03b1", + "\u03b2\u03b1\u03c3\u03b9\u03bb\u03b9\u03ba\u03ae", + "\u03b8\u03b5\u03bc\u03b9\u03c3\u03c4\u03bf\u03ba\u03bb\u03ae\u03c2", + "\u03ba\u03c1\u03b9\u03bd\u03b9\u03ce", + "\u03b1\u03b9\u03bc\u03af\u03bb\u03b9\u03bf\u03c2", + "\u03b8\u03b5\u03bf\u03c6\u03b1\u03bd\u03af\u03b1", + "\u03c6\u03c9\u03ba\u03ac\u03c2", + "\u03b3\u03bb\u03c5\u03ba\u03b5\u03c1\u03af\u03b1", + "\u03b3\u03b5\u03c9\u03c1\u03b3\u03af\u03b1", + "\u03bb\u03b1\u03c5\u03c1\u03b5\u03bd\u03c4\u03af\u03b1", + "\u03c4\u03af\u03c4\u03bf\u03c2", + "\u03c0\u03ad\u03c4\u03c1\u03bf\u03c2", + "\u03b5\u03c5\u03c6\u03c1\u03bf\u03c3\u03cd\u03bd\u03b7", + "\u03ba\u03b1\u03c3\u03c3\u03b9\u03b1\u03bd\u03ae", + "\u03b8\u03ad\u03bc\u03b7\u03c2", + "\u03b1\u03bb\u03b5\u03be\u03af\u03b1", + "\u03bc\u03b5\u03c1\u03ba\u03bf\u03cd\u03c1\u03b9\u03bf\u03c2", + "\u03b2\u03b5\u03bd\u03b9\u03b1\u03bc\u03af\u03bd", + "\u03b9\u03c9\u03bd\u03ac\u03c2", + "\u03c0\u03bf\u03bb\u03c5\u03bd\u03af\u03ba\u03b7", + "\u03bc\u03b1\u03c1\u03b9\u03ac\u03bd\u03bd\u03b1", + "\u03c7\u03c1\u03cd\u03c3\u03b1\u03bd\u03b8\u03bf\u03c2", + "\u03c0\u03ac\u03c4\u03c1\u03bf\u03ba\u03bb\u03bf\u03c2", + "\u03b1\u03b3\u03cc\u03c1\u03c9", + "\u03bd\u03b5\u03cc\u03c6\u03c5\u03c4\u03bf\u03c2", + "\u03bb\u03ae\u03b4\u03b1", + "\u03b1\u03b3\u03ac\u03c0\u03b9\u03bf\u03c2", + "\u03c3\u03c4\u03ad\u03bb\u03bb\u03b9\u03bf\u03c2", + "\u03b6\u03b1\u03c6\u03b5\u03af\u03c1\u03b9\u03bf\u03c2", + "\u03c6\u03b9\u03bb\u03bf\u03b8\u03ad\u03b7", + "\u03b1\u03bd\u03b4\u03c1\u03bf\u03bc\u03ac\u03c7\u03b7", + "\u03b5\u03c5\u03b4\u03bf\u03ba\u03af\u03b1", + "\u03b3\u03b5\u03c1\u03ac\u03c3\u03b9\u03bc\u03bf\u03c2", + "\u03c3\u03c4\u03b1\u03cd\u03c1\u03bf\u03c2", + "\u03b9\u03c0\u03c0\u03bf\u03ba\u03c1\u03ac\u03c4\u03b7\u03c2", + "\u03c6\u03b1\u03af\u03b4\u03c1\u03b1", + "\u03b3\u03b1\u03b2\u03c1\u03b9\u03ae\u03bb", + "\u03bc\u03b1\u03c1\u03b9\u03b3\u03ce", + "\u03bc\u03b1\u03c1\u03af\u03bd\u03bf\u03c2", + "\u03b1\u03c0\u03bf\u03bb\u03bb\u03c9\u03bd\u03af\u03b1", + "\u03b9\u03ac\u03c3\u03c9\u03bd", + "\u03b5\u03cd\u03b1", + "\u03c7\u03c1\u03b9\u03c3\u03c4\u03b9\u03ac\u03bd", + "\u03b1\u03bd\u03b1\u03b3\u03bd\u03ce\u03c3\u03c4\u03b7\u03c2", + "\u03bc\u03b1\u03c5\u03c1\u03bf\u03b5\u03b9\u03b4\u03ae\u03c2", + "\u03b1\u03b3\u03b3\u03b5\u03bb\u03b9\u03ba\u03ae", + "\u03bb\u03bf\u03c5\u03ba\u03ac\u03c2", + "\u03b1\u03c5\u03be\u03ad\u03bd\u03c4\u03b9\u03bf\u03c2", + "\u03bb\u03c5\u03ba\u03bf\u03cd\u03c1\u03b3\u03bf\u03c2", + "\u03b9\u03c9\u03b1\u03ba\u03b5\u03af\u03bc", + "\u03b1\u03bd\u03b4\u03c1\u03bf\u03bd\u03af\u03ba\u03b7", + "\u03b5\u03c5\u03c3\u03b5\u03b2\u03af\u03b1", + "\u03b1\u03c1\u03b9\u03c3\u03c4\u03b5\u03af\u03b4\u03b7\u03c2", + "\u03c7\u03c1\u03b9\u03c3\u03c4\u03cc\u03c6\u03bf\u03c1\u03bf\u03c2", + "\u03ba\u03bb\u03b5\u03bf\u03bc\u03ad\u03bd\u03b7\u03c2", + "\u03bd\u03af\u03ba\u03b7", + "\u03b1\u03c3\u03ba\u03bb\u03b7\u03c0\u03b9\u03cc\u03c2", + "\u03b5\u03c5\u03c3\u03ad\u03b2\u03b9\u03bf\u03c2", + "\u03b1\u03bd\u03b1\u03bd\u03af\u03b1\u03c2", + "\u03c0\u03bf\u03cd\u03bb\u03b9\u03b1", + "\u03b7\u03bb\u03af\u03b1\u03c2", + "\u03b9\u03c0\u03c0\u03cc\u03bb\u03c5\u03c4\u03bf\u03c2", + "\u03bf\u03c1\u03ad\u03c3\u03c4\u03b7\u03c2", + "\u03ba\u03c1\u03c5\u03c3\u03c4\u03ac\u03bb\u03bb\u03b7\u03c2", + "\u03c6\u03bf\u03af\u03b2\u03b7", + "\u03b1\u03bd\u03b4\u03c1\u03ad\u03b1\u03c2", + "\u03c4\u03c1\u03c5\u03c6\u03c9\u03bd\u03af\u03b1", + "\u03cc\u03bb\u03b3\u03b1", + "\u03b4\u03b1\u03bd\u03ac\u03b7", + "\u03c0\u03b1\u03bd\u03b4\u03ce\u03c1\u03b1", + "\u03c6\u03ce\u03c4\u03b9\u03bf\u03c2", + "\u03b2\u03b1\u03c1\u03b2\u03ac\u03c1\u03b1", + "\u03b5\u03bb\u03b9\u03c3\u03ac\u03b2\u03b5\u03c4", + "\u03b4\u03c1\u03bf\u03c3\u03b9\u03ac", + "\u03c0\u03bf\u03bb\u03cd\u03b2\u03b9\u03b1", + "\u03bb\u03b1\u03c5\u03c1\u03ad\u03bd\u03c4\u03b9\u03bf\u03c2", + "\u03c4\u03af\u03bc\u03c9\u03bd", + "\u03ba\u03bb\u03b1\u03af\u03c1\u03b7", + "\u03bd\u03b5\u03c6\u03ad\u03bb\u03b7", + "\u03c7\u03b1\u03c1\u03af\u03c4\u03bf\u03c2", + "\u03b1\u03b8\u03b7\u03bd\u03cc\u03b4\u03c9\u03c1\u03bf\u03c2", + "\u03bc\u03b5\u03bb\u03af\u03bd\u03b1", + "\u03bc\u03b1\u03c1\u03b9\u03bb\u03ad\u03bd\u03b1", + "\u03c3\u03c4\u03ad\u03bb\u03bb\u03b1", + "\u03b3\u03b1\u03bb\u03ae\u03bd\u03b7", + "\u03b2\u03cd\u03c1\u03c9\u03bd", + "\u03b9\u03c3\u03bc\u03ae\u03bd\u03b7", + "\u03b1\u03c7\u03b9\u03bb\u03bb\u03b5\u03af\u03b1", + "\u03b6\u03b1\u03c7\u03b1\u03c1\u03ad\u03bd\u03b9\u03b1", + "\u03b2\u03bb\u03ac\u03c3\u03b7\u03c2", + "\u03b5\u03bb\u03b9\u03c3\u03c3\u03b1\u03af\u03bf\u03c2", + "\u03c0\u03c1\u03cc\u03b4\u03c1\u03bf\u03bc\u03bf\u03c2", + "\u03c6\u03af\u03bb\u03b9\u03c0\u03c0\u03bf\u03c2", + "\u03b5\u03c5\u03c3\u03c4\u03b1\u03b8\u03af\u03b1", + "\u03c6\u03c1\u03b5\u03b9\u03b4\u03b5\u03c1\u03af\u03ba\u03bf\u03c2", + "\u03c6\u03b1\u03bd\u03bf\u03c5\u03c1\u03af\u03b1", + "\u03b5\u03c1\u03b9\u03c6\u03cd\u03bb\u03b7", + "\u03c3\u03bc\u03b1\u03c1\u03ac\u03b3\u03b4\u03b1", + "\u03bb\u03bf\u03c5\u03b4\u03bf\u03b2\u03af\u03ba\u03bf\u03c2", + "\u03bd\u03b1\u03c4\u03b1\u03bb\u03af\u03bd\u03b1", + "\u03c4\u03c1\u03b9\u03b1\u03bd\u03c4\u03ac\u03c6\u03c5\u03bb\u03bb\u03b7", + "\u03b2\u03b9\u03ba\u03c4\u03cc\u03c1\u03b9\u03b1", + "\u03b2\u03b5\u03bd\u03ad\u03c4\u03b9\u03bf\u03c2", + "\u03bd\u03b9\u03ba\u03cc\u03b4\u03b7\u03bc\u03bf\u03c2", + "\u03b6\u03b7\u03bd\u03b1\u03ca\u03c2", + "\u03bf\u03c5\u03c1\u03b1\u03bd\u03af\u03b1", + "\u03b4\u03b9\u03bf\u03bd\u03c5\u03c3\u03af\u03b1", + "\u03c7\u03c1\u03c5\u03c3\u03ae", + "\u03ba\u03b1\u03bb\u03bb\u03b9\u03cc\u03c0\u03b7", + "\u03b1\u03c1\u03b9\u03c3\u03c4\u03bf\u03c6\u03ac\u03bd\u03b7\u03c2", + "\u03c7\u03c1\u03b9\u03c3\u03c4\u03b9\u03ac\u03bd\u03b1", + "\u03bd\u03c4\u03b1\u03bd\u03b9\u03ad\u03bb\u03b1", + "\u03c5\u03ac\u03ba\u03b9\u03bd\u03b8\u03bf\u03c2", + "\u03bd\u03b9\u03ba\u03b7\u03c6\u03cc\u03c1\u03bf\u03c2", + "\u03bc\u03b9\u03bd\u03ad\u03c1\u03b2\u03b1", + "\u03c6\u03b5\u03c1\u03b5\u03bd\u03af\u03ba\u03b7", + "\u03b3\u03b5\u03c1\u03b1\u03ba\u03af\u03bd\u03b1", + "\u03ba\u03cc\u03c3\u03bc\u03b9\u03b1", + "\u03b1\u03bd\u03b4\u03c1\u03bf\u03ba\u03bb\u03ae\u03c2", + "\u03b5\u03b9\u03c1\u03ae\u03bd\u03b7", + "\u03ba\u03bf\u03bc\u03bd\u03b7\u03bd\u03ae", + "\u03c0\u03bf\u03bb\u03cd\u03b4\u03c9\u03c1\u03b1", + "\u03b1\u03b3\u03b1\u03b8\u03bf\u03ba\u03bb\u03ae\u03c2", + "\u03c3\u03b5\u03b2\u03b1\u03c3\u03c4\u03b9\u03b1\u03bd\u03ae", + "\u03b2\u03b5\u03bb\u03b9\u03c3\u03c3\u03ac\u03c1\u03b9\u03bf\u03c2", + "\u03b1\u03b8\u03b1\u03bd\u03ac\u03c3\u03b9\u03bf\u03c2", + "\u03b4\u03b9\u03b4\u03ce", + "\u03bd\u03ad\u03b1\u03c1\u03c7\u03bf\u03c2", + "\u03b4\u03b9\u03bf\u03bc\u03ae\u03b4\u03b7\u03c2", + "\u03c3\u03c5\u03bc\u03b5\u03ce\u03bd\u03b7", + "\u03ba\u03af\u03bc\u03c9\u03bd", + "\u03c6\u03c9\u03c4\u03b5\u03b9\u03bd\u03ae", + "\u03b1\u03c3\u03b7\u03bc\u03bf\u03cd\u03bb\u03b1", + "\u03b1\u03b3\u03bd\u03ae", + "\u03c4\u03b7\u03bb\u03ad\u03bc\u03b1\u03c7\u03bf\u03c2", + "\u03b8\u03ad\u03bc\u03b9\u03c2", + "\u03b1\u03bc\u03c6\u03b9\u03b8\u03ad\u03b1", + "\u03c3\u03c4\u03b1\u03c5\u03c1\u03bf\u03cd\u03bb\u03b1", + "\u03b4\u03cc\u03bc\u03bd\u03b1", + "\u03c3\u03c9\u03c6\u03c1\u03bf\u03bd\u03af\u03b1", + "\u03b1\u03c1\u03c4\u03ad\u03bc\u03b7\u03c2", + "\u03b2\u03bb\u03ac\u03c3\u03b9\u03bf\u03c2", + "\u03c0\u03b1\u03bd\u03c4\u03bf\u03cd\u03bb\u03b1", + "\u03b5\u03c5\u03b1\u03bd\u03b8\u03af\u03b1", + "\u03c4\u03b9\u03bc\u03bf\u03b8\u03ad\u03b1", + "\u03bc\u03b1\u03cd\u03c1\u03b1", + "\u03b2\u03b1\u03c3\u03b9\u03bb\u03b5\u03af\u03b1", + "\u03b8\u03b1\u03bb\u03b1\u03c3\u03c3\u03b9\u03bd\u03ae", + "\u03b1\u03b9\u03bc\u03b9\u03bb\u03b9\u03b1\u03bd\u03cc\u03c2", + "\u03b1\u03c6\u03c1\u03bf\u03b4\u03af\u03c4\u03b7", + "\u03bd\u03b1\u03c4\u03b1\u03bb\u03af\u03b1", + "\u03b5\u03c1\u03c1\u03af\u03ba\u03bf\u03c2", + "\u03bc\u03b1\u03bb\u03b1\u03bc\u03ac\u03c4\u03b7", + "\u03b5\u03c5\u03c1\u03c5\u03b4\u03af\u03ba\u03b7", + "\u03ba\u03bb\u03b5\u03b9\u03ce", + "\u03c7\u03c1\u03c5\u03c3\u03ac\u03bd\u03b8\u03b7", + "\u03b4\u03b1\u03b2\u03b9\u03b4\u03bf\u03cd\u03bb\u03b1", + "\u03b5\u03c1\u03b1\u03c3\u03bc\u03af\u03b1", + "\u03b4\u03b1\u03bd\u03b9\u03ae\u03bb", + "\u03ba\u03bf\u03ba\u03ba\u03ce\u03bd\u03b1", + "\u03b2\u03ad\u03c1\u03b1", + "\u03ba\u03bb\u03b7\u03bc\u03b5\u03bd\u03c4\u03af\u03bd\u03b7", + "\u03bd\u03b1\u03c5\u03c3\u03b9\u03ba\u03ac", + "\u03bc\u03b5\u03bb\u03c0\u03bf\u03bc\u03ad\u03bd\u03b7", + "\u03b5\u03c5\u03b8\u03cd\u03bc\u03b9\u03bf\u03c2", + "\u03c0\u03b1\u03c3\u03c7\u03ac\u03bb\u03b7\u03c2", + "\u03b6\u03b7\u03c3\u03bf\u03cd\u03bb\u03b1", + "\u03ba\u03ce\u03c3\u03c4\u03b1\u03c2", + "\u03ba\u03b7\u03c1\u03cd\u03ba\u03bf\u03c2", + "\u03c0\u03c5\u03b8\u03b1\u03b3\u03cc\u03c1\u03b1\u03c2", + "\u03be\u03b1\u03bd\u03b8\u03cc\u03c2", + "\u03c4\u03b9\u03bc\u03cc\u03b8\u03b5\u03bf\u03c2", + "\u03b4\u03b1\u03bc\u03b9\u03b1\u03bd\u03ae", + "\u03bc\u03b1\u03c1\u03ba\u03ad\u03bb\u03bb\u03b1", + "\u03b2\u03b5\u03c1\u03cc\u03bd\u03b9\u03ba\u03b1", + "\u03b1\u03bd\u03b8\u03bf\u03cd\u03bb\u03b7\u03c2", + "\u03b8\u03b5\u03bf\u03c7\u03ac\u03c1\u03b7\u03c2", + "\u03b9\u03b5\u03c1\u03ce\u03bd\u03c5\u03bc\u03bf\u03c2", + "\u03c4\u03b1\u03be\u03b9\u03b1\u03c1\u03c7\u03af\u03b1", + "\u03b1\u03bd\u03b4\u03c1\u03cc\u03bd\u03b9\u03ba\u03bf\u03c2", + "\u03b3\u03b9\u03b1\u03bd\u03bd\u03bf\u03cd\u03bb\u03b1", + "\u03bd\u03b9\u03ba\u03bf\u03bb\u03af\u03c4\u03c3\u03b1", + "\u03b3\u03b1\u03bb\u03ac\u03c4\u03b9\u03bf\u03c2", + "\u03bc\u03b1\u03bb\u03b1\u03bc\u03b1\u03c4\u03ad\u03bd\u03b9\u03b1", + "\u03c3\u03c4\u03b1\u03bc\u03ac\u03c4\u03b7\u03c2", + "\u03b3\u03b1\u03b2\u03c1\u03b9\u03ad\u03bb\u03bb\u03b1", + "\u03b9\u03bf\u03c5\u03bb\u03b9\u03b1\u03bd\u03ae", + "\u03c6\u03c1\u03cd\u03bd\u03b7", + "\u03c5\u03c0\u03b1\u03c0\u03b1\u03bd\u03c4\u03ae", + "\u03ba\u03c5\u03b2\u03ad\u03bb\u03b7", + "\u03b5\u03c5\u03c4\u03cd\u03c7\u03b9\u03bf\u03c2", + "\u03b3\u03b9\u03ac\u03bd\u03bd\u03b7\u03c2", + "\u03b1\u03c3\u03b7\u03bc\u03ae\u03c2", + "\u03b5\u03c5\u03b8\u03c5\u03bc\u03af\u03b1", + "\u03b1\u03b3\u03bb\u03b1\u0390\u03b1", + "\u03b8\u03ad\u03ba\u03bb\u03b1", + "\u03b4\u03b9\u03b1\u03bc\u03b1\u03bd\u03c4\u03ae\u03c2", + "\u03bc\u03b1\u03ba\u03c1\u03af\u03bd\u03b1", + "\u03bc\u03b9\u03c1\u03ac\u03bd\u03c4\u03b1", + "\u03bc\u03cc\u03c3\u03c7\u03b1", + "\u03c4\u03c1\u03b9\u03b1\u03bd\u03c4\u03ac\u03c6\u03c5\u03bb\u03bb\u03bf\u03c2", + "\u03b1\u03b3\u03b1\u03b8\u03cc\u03bd\u03b9\u03ba\u03bf\u03c2", + "\u03b3\u03bb\u03b1\u03cd\u03ba\u03b7", + "\u03b5\u03c5\u03c4\u03c5\u03c7\u03af\u03b1", + "\u03b5\u03c5\u03b1\u03b3\u03b3\u03b5\u03bb\u03af\u03b1", + "\u03c5\u03b1\u03ba\u03af\u03bd\u03b8\u03b7", + "\u03b1\u03c1\u03b9\u03c3\u03c4\u03bf\u03bc\u03ad\u03bd\u03b7\u03c2", + "\u03b5\u03c5\u03bb\u03b1\u03bc\u03c0\u03af\u03b1", + "\u03bb\u03b5\u03bf\u03bd\u03ac\u03c1\u03b4\u03bf\u03c2", + "\u03ba\u03bf\u03c1\u03bd\u03b7\u03bb\u03af\u03b1", + 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"\u03b8\u03b5\u03bf\u03b4\u03bf\u03cd\u03bb\u03b7", + "\u03b4\u03b9\u03b1\u03bb\u03b5\u03ba\u03c4\u03ae", + "\u03b8\u03ac\u03bb\u03b5\u03b9\u03b1", + "\u03b5\u03c0\u03b9\u03c3\u03c4\u03ae\u03bc\u03b7", + "\u03bc\u03b1\u03c1\u03b3\u03b9\u03ad\u03c4\u03c4\u03b1", + "\u03b1\u03c1\u03ad\u03b8\u03b1", + "\u03c1\u03bf\u03cd\u03c3\u03b1", + "\u03c0\u03af\u03bd\u03b4\u03b1\u03c1\u03bf\u03c2", + "\u03c0\u03b5\u03c1\u03c3\u03b5\u03c6\u03cc\u03bd\u03b7", + "\u03c0\u03b1\u03c1\u03b8\u03ad\u03bd\u03b1", + "\u03ba\u03b1\u03bb\u03ae", + "\u03c3\u03b5\u03bb\u03ae\u03bd\u03b7", + "\u03b1\u03c1\u03c4\u03b5\u03bc\u03b9\u03c3\u03af\u03b1", + "\u03b5\u03bc\u03bc\u03b1\u03bd\u03bf\u03c5\u03ad\u03bb\u03b1", + "\u03b1\u03c1\u03c7\u03bf\u03bd\u03c4\u03af\u03b1", + "\u03bc\u03b9\u03ba\u03ad\u03c2", + "\u03b1\u03b2\u03c1\u03b1\u03ac\u03bc", + "\u03ba\u03c9\u03bd\u03c3\u03c4\u03b1\u03bd\u03c4\u03af\u03bd\u03b1", + "\u03c1\u03b5\u03b2\u03ad\u03ba\u03ba\u03b1", + 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+ "\u03b1\u03b3\u03b3\u03b5\u03bb\u03af\u03b4\u03bf\u03c5", + "\u03c6\u03c1\u03b1\u03bd\u03c4\u03b6\u03ae\u03c2", + "\u03b4\u03cc\u03b2\u03b1\u03c2", + "\u03c3\u03b9\u03ce\u03c1\u03b7\u03c2", + "\u03ba\u03bf\u03c5\u03c4\u03bf\u03c5\u03b6\u03af\u03b4\u03bf\u03c5", + "\u03be\u03ad\u03bd\u03bf\u03c5", + "\u03bc\u03b1\u03c3\u03b1\u03bf\u03cd\u03c4\u03b7", + "\u03b4\u03b7\u03bc\u03b1\u03ba\u03bf\u03b3\u03b9\u03ac\u03bd\u03bd\u03b7", + "\u03c4\u03c3\u03bf\u03bc\u03ce\u03ba\u03bf\u03c2", + "\u03bc\u03b1\u03c1\u03bf\u03c5\u03b3\u03b9\u03ac\u03bd\u03bd\u03b7", + "\u03ba\u03c9\u03bd\u03c3\u03c4\u03b1\u03bd\u03c4\u03bf\u03c0\u03bf\u03cd\u03bb\u03bf\u03c5", + "\u03ba\u03b1\u03bb\u03b1\u03ca\u03c4\u03b6\u03ac\u03ba\u03b7\u03c2", + "\u03c0\u03b1\u03c0\u03b1\u03c6\u03ce\u03c4\u03b7\u03c2", + "\u03ba\u03bf\u03c5\u03c1\u03ac\u03ba\u03bf\u03c2", + "\u03ba\u03c9\u03c3\u03c4\u03af\u03b4\u03b7\u03c2", + "\u03c6\u03c9\u03c4\u03cc\u03c0\u03bf\u03c5\u03bb\u03bf\u03c2", + "\u03bc\u03c0\u03b1\u03bb\u03ae", + 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"\u03bb\u03bf\u03c5\u03c1\u03ac\u03bd\u03c4\u03bf\u03c2", + "\u03ba\u03bf\u03bb\u03bf\u03b2\u03cc\u03c2", + "\u03c0\u03b1\u03c1\u03ac\u03bd\u03bf\u03c5", + "\u03c0\u03b1\u03c4\u03b5\u03bb\u03ae\u03c2", + "\u03b2\u03bf\u03cd\u03bb\u03b3\u03b1\u03c1\u03b7\u03c2", + "\u03c1\u03bf\u03ca\u03b4\u03bf\u03cd\u03bb\u03b7\u03c2", + "\u03b3\u03b9\u03b1\u03bd\u03bd\u03cc\u03c0\u03bf\u03c5\u03bb\u03bf\u03c2", + "\u03bc\u03b5\u03c4\u03b1\u03be\u03ac\u03c2", + "\u03c0\u03bf\u03bb\u03b1\u03c4\u03af\u03b4\u03bf\u03c5", + "\u03c3\u03ba\u03c1\u03b5\u03bc\u03bc\u03cd\u03b4\u03b1", + "\u03c3\u03c0\u03ac\u03bb\u03b1\u03c2", + "\u03b2\u03b5\u03c1\u03b2\u03af\u03c4\u03b7", + "\u03c3\u03b9\u03bc\u03b7\u03c4\u03bf\u03c0\u03bf\u03cd\u03bb\u03bf\u03c5", + "\u03b4\u03b7\u03bc\u03b7\u03c4\u03c1\u03ad\u03bb\u03bf\u03c5", + "\u03ba\u03c5\u03c0\u03c1\u03b9\u03ce\u03c4\u03b7\u03c2", + "\u03be\u03b7\u03c1\u03af\u03b4\u03bf\u03c5", + "\u03c6\u03b5\u03b9\u03b4\u03b5\u03c1\u03cc\u03c0\u03bf\u03c5\u03bb\u03bf\u03c2", + "\u03c3\u03bc\u03b1\u03c1\u03b4\u03ac\u03c2", + "\u03c7\u03c9\u03c1\u03b9\u03bd\u03bf\u03cd", + "\u03b1\u03bd\u03c4\u03c9\u03bd\u03b9\u03ac\u03b4\u03b7\u03c2", + "\u03c0\u03b1\u03c0\u03b1\u03c7\u03c1\u03ae\u03c3\u03c4\u03bf\u03c5", + "\u03b4\u03ad\u03bb\u03b9\u03bf\u03c2", + "\u03bd\u03c4\u03ac\u03bd\u03bf\u03c5", + "\u03b2\u03b9\u03bb\u03b4\u03cc\u03c2", + "\u03bc\u03ac\u03c1\u03b1", + "\u03bc\u03b1\u03c4\u03c3\u03bf\u03cd\u03ba\u03b1\u03c2", + "\u03ba\u03bf\u03c5\u03c1\u03ba\u03bf\u03c5\u03c4\u03ac\u03c2", + "\u03b3\u03b9\u03b1\u03bd\u03bd\u03ac\u03ba\u03b7\u03c2", + "\u03c3\u03b9\u03b3\u03b1\u03bd\u03cc\u03c2", + "\u03c4\u03bf\u03c5\u03c1\u03bd\u03ac", + "\u03b2\u03bf\u03c5\u03c4\u03c3\u03b5\u03bb\u03b1\u03c2", + "\u03c0\u03b1\u03c0\u03b1\u03b4\u03bf\u03c0\u03bf\u03cd\u03bb\u03bf\u03c5", + "\u03c4\u03c1\u03b9\u03b1\u03bd\u03c4\u03b1\u03c6\u03cd\u03bb\u03bb\u03bf\u03c5", + "\u03bf\u03c1\u03c6\u03b1\u03bd\u03b9\u03ce\u03c4\u03b7\u03c2", + 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"\u03b1\u03bd\u03b4\u03c1\u03b9\u03b1\u03bd\u03cc\u03c2", + "\u03bc\u03b1\u03bd\u03b5\u03bb\u03af\u03b4\u03b7\u03c2", + "\u03bb\u03b9\u03ac\u03ba\u03bf\u03c5", + "\u03c4\u03bf\u03bc\u03c0\u03bf\u03c5\u03bb\u03af\u03b4\u03bf\u03c5", + "\u03c8\u03ac\u03bb\u03c4\u03b7\u03c2", + "\u03ba\u03b1\u03ba\u03b1\u03c4\u03c3\u03cc\u03c2", + "\u03c3\u03c5\u03c1\u03b3\u03ae\u03c2", + "\u03c3\u03c4\u03b1\u03b8\u03ac", + "\u03b2\u03b1\u03ba\u03b1\u03bb\u03ac\u03ba\u03b7\u03c2", + "\u03b2\u03bb\u03ac\u03c3\u03c3\u03b7", + "\u03ba\u03bf\u03c5\u03c4\u03c3\u03bf\u03bd\u03af\u03ba\u03b1", + "\u03b3\u03b1\u03b2\u03c1\u03b9\u03ae\u03bb", + "\u03b4\u03c1\u03b1\u03ba\u03bf\u03c5\u03bb\u03ae", + "\u03ba\u03b1\u03c1\u03bf\u03cd\u03c3\u03bf\u03c2", + "\u03bb\u03bf\u03c5\u03bc\u03c0\u03bf\u03cd\u03c4\u03c3\u03ba\u03bf\u03c5", + "\u03ba\u03bf\u03c5\u03c1\u03c3\u03ac\u03c1\u03b7\u03c2", + "\u03ba\u03b1\u03c1\u03b1\u03bd\u03c4\u03ac\u03bd\u03b1", + "\u03b5\u03bd\u03c9\u03c4\u03b9\u03ac\u03b4\u03b7", + 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"\u03c3\u03b5\u03bc\u03c0\u03ad\u03c0\u03bf\u03c5", + "\u03bc\u03b1\u03c1\u03c4\u03b9\u03ac\u03b4\u03bf\u03c5", + "\u03b4\u03b1\u03bd\u03b4\u03b1\u03bd\u03af\u03b4\u03bf\u03c5", + "\u03bc\u03b5\u03bb\u03b9\u03c4\u03c3\u03cc\u03c0\u03bf\u03c5\u03bb\u03bf\u03c2", + "\u03c4\u03b6\u03b1\u03bd\u03bf\u03c5\u03b4\u03ac\u03ba\u03b7\u03c2", + "\u03b8\u03c9\u03bc\u03cc\u03c0\u03bf\u03c5\u03bb\u03bf\u03c2", + "\u03b1\u03be\u03b9\u03ce\u03c4\u03b7\u03c2", + "\u03c4\u03c1\u03b9\u03c6\u03c4\u03b1\u03bd\u03af\u03b4\u03bf\u03c5", + "\u03ba\u03cc\u03bb\u03bb\u03b9\u03b1", + "\u03c0\u03bf\u03bb\u03c5\u03c7\u03c1\u03cc\u03bd\u03b7\u03c2", + "\u03b2\u03bf\u03cd\u03c1\u03b1\u03c2", + "\u03ba\u03b1\u03c1\u03b1\u03ba\u03c9\u03bd\u03c3\u03c4\u03b1\u03bd\u03c4\u03b9\u03bd\u03bf\u03cd", + "\u03bb\u03b1\u03bc\u03c0\u03c1\u03b9\u03bd\u03cc\u03c2", + "\u03c3\u03c4\u03b1\u03bc\u03ac\u03c4\u03b7\u03c2", + "\u03c3\u03bc\u03c0\u03c1\u03af\u03bd\u03b7\u03c2", + "\u03c3\u03af\u03b2\u03b2\u03b1", + "\u03b3\u03ba\u03b1\u03bd\u03ac\u03c4\u03c3\u03b9\u03bf\u03c2", + "\u03c0\u03ad\u03c4\u03c4\u03b1", + "\u03c3\u03cd\u03c8\u03b1", + "\u03bc\u03b1\u03b3\u03ba\u03bf\u03cd\u03c6\u03b7\u03c2", + "\u03b4\u03b1\u03bc\u03ae\u03bb\u03bf\u03c5", + "\u03b6\u03ce\u03b7", + "\u03b4\u03b1\u03c1\u03b4\u03b9\u03ce\u03c4\u03b7", + "\u03b4\u03bf\u03c5\u03b2\u03af\u03ba\u03b1\u03c2", + "\u03bc\u03b1\u03b3\u03ba\u03b1\u03bd\u03ac\u03c1\u03b7", + "\u03c4\u03c3\u03bf\u03cd\u03c1\u03b1", + "\u03b1\u03bd\u03b1\u03c3\u03c4\u03cc\u03c0\u03bf\u03c5\u03bb\u03bf\u03c2", + "\u03c1\u03ad\u03bd\u03c4\u03b6\u03bf\u03c2", + "\u03b9\u03c9\u03b1\u03ba\u03b5\u03b9\u03bc\u03af\u03b4\u03bf\u03c5", + "\u03c7\u03bf\u03c5\u03c7\u03bf\u03c5\u03bb\u03ae\u03c2", + "\u03c0\u03b1\u03bb\u03bb\u03ac\u03c2", + "\u03c4\u03cc\u03bc\u03c0\u03c1\u03b7", + "\u03ba\u03b1\u03c1\u03b1\u03bc\u03c0\u03af\u03bd\u03b1", + "\u03bc\u03ac\u03c3\u03c4\u03bf\u03c1\u03b1\u03c2", + "\u03b4\u03b1\u03c5\u03af\u03b4", + "\u03bc\u03b1\u03c3\u03b3\u03b1\u03bb\u03ac\u03c2", + "\u03bc\u03b9\u03c7\u03b1\u03bb\u03ac\u03c1\u03bf\u03c5", + "\u03c0\u03b5\u03c4\u03c1\u03af\u03b4\u03bf\u03c5", + "\u03c0\u03b1\u03bd\u03bf\u03c0\u03bf\u03cd\u03bb\u03bf\u03c5", + "\u03b3\u03c1\u03b1\u03bc\u03bc\u03b1\u03c4\u03b9\u03ba\u03cc\u03c2", + "\u03ba\u03b1\u03c4\u03c3\u03af\u03c6\u03bf\u03c2", + "\u03c7\u03c1\u03c5\u03c3\u03ac\u03c6\u03b7", + "\u03b3\u03ba\u03bf\u03cd\u03bd\u03b7", + "\u03c3\u03c6\u03cd\u03c1\u03bb\u03b1\u03c2", + "\u03c4\u03bf\u03c5\u03bb\u03bf\u03cd\u03c0\u03b7", + "\u03ba\u03bf\u03c5\u03c4\u03c3\u03bf\u03c5\u03bd\u03ac\u03ba\u03b7", + "\u03b2\u03b1\u03ca\u03c1\u03b1\u03bc\u03af\u03b4\u03bf\u03c5", + "\u03b1\u03b3\u03b3\u03b5\u03bb\u03cc\u03c0\u03bf\u03c5\u03bb\u03bf\u03c2", + "\u03ba\u03bf\u03cd\u03c4\u03c1\u03b7\u03c2", + "\u03bc\u03b1\u03bd\u03bf\u03c5\u03c3\u03b9\u03ac\u03b4\u03b7\u03c2", + "\u03c4\u03c3\u03b1\u03bd\u03c4\u03af\u03b4\u03bf\u03c5", + "\u03b3\u03b1\u03bb\u03ac\u03bd\u03b7", + "\u03c1\u03cc\u03ba\u03ba\u03b1", + "\u03c0\u03b5\u03c4\u03c1\u03ac\u03ba\u03b7\u03c2", + "\u03ba\u03bf\u03c5\u03b8\u03bf\u03cd\u03c1\u03b7", + "\u03b5\u03c5\u03b1\u03b3\u03b3\u03b5\u03bb\u03ac\u03ba\u03b7", + "\u03b1\u03c1\u03c7\u03ac\u03ba\u03b7", + "\u03bb\u03c5\u03bc\u03b1\u03be\u03ae", + "\u03b3\u03b1\u03bb\u03b1\u03bd\u03ac\u03ba\u03b7", + "\u03bc\u03b1\u03bd\u03c4\u03b6\u03ce\u03c1\u03bf\u03c2", + "\u03c0\u03b5\u03c1\u03c1\u03ac\u03ba\u03b7\u03c2", + "\u03c3\u03b9\u03cc\u03bb\u03bf\u03c5", + "\u03b1\u03bd\u03b4\u03c1\u03b9\u03cc\u03c0\u03bf\u03c5\u03bb\u03bf\u03c2", + "\u03b3\u03b5\u03c9\u03c1\u03b3\u03b9\u03ac\u03b4\u03bf\u03c5", + "\u03bb\u03b5\u03bd\u03c4\u03b6\u03af\u03bf\u03c5", + "\u03ba\u03af\u03c3\u03c3\u03b1\u03c2", + "\u03ba\u03b1\u03c4\u03c3\u03af\u03c0\u03b7\u03c2", + "\u03ba\u03b1\u03b2\u03bf\u03cd\u03c1\u03b7\u03c2", + "\u03c3\u03c0\u03b1\u03bd\u03b4\u03c9\u03bd\u03af\u03b4\u03b7\u03c2", + "\u03c3\u03b5\u03bb\u03b9\u03bd\u03bf\u03c0\u03bf\u03cd\u03bb\u03bf\u03c5", + "\u03c3\u03b5\u03c6\u03ad\u03ba\u03bf\u03c2", + "\u03b5\u03c5\u03ba\u03b1\u03c1\u03c0\u03af\u03b4\u03b7\u03c2", + "\u03c0\u03bf\u03c5\u03c6\u03c4\u03c3\u03ae\u03c2", + "\u03c4\u03b1\u03b2\u03b5\u03c1\u03bd\u03b1\u03c1\u03ac\u03ba\u03b7\u03c2", + "\u03ba\u03c5\u03c1\u03bf\u03cd\u03b4\u03b7", + "\u03bc\u03b1\u03ba\u03b1\u03c1\u03b9\u03ac\u03b4\u03b7\u03c2", + "\u03b1\u03bb\u03b5\u03be\u03b1\u03bd\u03b4\u03c1\u03cc\u03c0\u03bf\u03c5\u03bb\u03bf\u03c2", + "\u03ba\u03bf\u03c5\u03bb\u03bf\u03c5\u03bc\u03c0\u03bf\u03cd", + "\u03bd\u03af\u03ba\u03b1", + "\u03ba\u03b1\u03c4\u03b1\u03c1\u03b1\u03c7\u03b9\u03ac\u03c2", + "\u03b3\u03c1\u03b1\u03c4\u03c3\u03b9\u03ac\u03c2", + "\u03ba\u03b1\u03c1\u03b1\u03c4\u03ac\u03c3\u03bf\u03c5", + "\u03bd\u03c4\u03b1\u03b2\u03ac\u03c2", + "\u03ba\u03b1\u03c3\u03c4\u03ac\u03bd\u03b7\u03c2", + "\u03bb\u03ac\u03ba\u03ba\u03b1\u03c2", + "\u03b3\u03ba\u03bf\u03cd\u03b2\u03b5\u03bb\u03bf\u03c2", + "\u03bc\u03b1\u03bb\u03af\u03bc\u03b7", + 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"\u03ba\u03b1\u03c1\u03ac\u03bc\u03c0\u03b7", + "\u03b4\u03b9\u03bf\u03c0\u03bf\u03cd\u03bb\u03bf\u03c5", + "\u03c1\u03bf\u03c5\u03c0\u03b1\u03ba\u03ac\u03c2", + "\u03b3\u03b5\u03c9\u03c1\u03b3\u03b1\u03bb\u03ac\u03c2", + "\u03bc\u03b1\u03bd\u03bf\u03c5\u03c3\u03bf\u03c0\u03bf\u03cd\u03bb\u03bf\u03c5", + "\u03c4\u03c3\u03b9\u03b3\u03b1\u03c1\u03af\u03b4\u03b1\u03c2", + "\u03c0\u03b1\u03c0\u03bf\u03c5\u03c4\u03c3\u03bf\u03c0\u03bf\u03cd\u03bb\u03bf\u03c5", + "\u03ba\u03c5\u03c1\u03b9\u03ac\u03ba\u03bf\u03c5", + "\u03c0\u03b1\u03c0\u03b1\u03bd\u03b9\u03ba\u03bf\u03bb\u03ac\u03bf\u03c5", + "\u03bb\u03b9\u03cc\u03bb\u03b9\u03bf\u03c2", + "\u03b8\u03b1\u03c3\u03af\u03c4\u03bf\u03c5", + "\u03bc\u03c0\u03b1\u03ba\u03bf\u03c5\u03bb\u03ae", + "\u03c3\u03bf\u03ba\u03bf\u03bb\u03ac\u03ba\u03b7", + "\u03c3\u03ba\u03b1\u03b2\u03ad\u03bd\u03c4\u03b6\u03bf\u03c5", + "\u03c7\u03b1\u03bb\u03ba\u03af\u03b4\u03bf\u03c5", + "\u03b1\u03c1\u03bc\u03ad\u03bd\u03b7\u03c2", + 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"\u03b2\u03b1\u03c7\u03bf\u03c5\u03b8\u03b9\u03b1\u03bd\u03ac\u03ba\u03b7\u03c2", + "\u03ba\u03b1\u03c1\u03b1\u03bc\u03ac\u03bd\u03b7", + "\u03c4\u03c3\u03b1\u03ba\u03af\u03c1\u03b7", + "\u03c3\u03c4\u03c5\u03bb\u03b9\u03b1\u03bd\u03af\u03b4\u03bf\u03c5", + "\u03b3\u03ba\u03bf\u03c5\u03c4\u03b6\u03b1\u03bc\u03ac\u03bd\u03b7\u03c2", + "\u03c3\u03c4\u03b1\u03bc\u03bf\u03cd\u03bb\u03b7", + "\u03b3\u03ba\u03b9\u03bf\u03bb\u03b4\u03b5\u03bb\u03ae\u03c2", + "\u03ba\u03b1\u03c1\u03b1\u03ba\u03ac\u03be\u03b7\u03c2", + "\u03bc\u03b1\u03c1\u03b3\u03b1\u03c1\u03ce\u03bd\u03b7\u03c2", + "\u03bc\u03c0\u03cc\u03c4\u03b7\u03c2", + "\u03c7\u03ad\u03bb\u03b9\u03bf\u03c2", + "\u03c4\u03b5\u03c1\u03b6\u03ae\u03c2", + "\u03c6\u03b5\u03b9\u03b6\u03b1\u03c4\u03af\u03b4\u03bf\u03c5", + "\u03b3\u03b5\u03c9\u03c1\u03b3\u03ae", + "\u03ba\u03b1\u03bb\u03bf\u03b3\u03b9\u03ac\u03bd\u03bd\u03b7", + "\u03c1\u03af\u03b3\u03ba\u03bf\u03c2", + "\u03c4\u03bf\u03c3\u03bf\u03cd\u03bd\u03b7", + 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"\u03bd\u03b9\u03ba\u03bf\u03c5\u03bb\u03ae\u03c2", + "\u03b1\u03bd\u03c4\u03c9\u03bd\u03ac\u03ba\u03b7", + "\u03b2\u03bf\u03c1\u03bb\u03cc\u03ba\u03b1\u03c2", + "\u03b2\u03b1\u03c3\u03b9\u03bb\u03b5\u03b9\u03ac\u03b4\u03b7", + "\u03b3\u03b9\u03b1\u03bd\u03bd\u03b1\u03ba\u03cc\u03c0\u03bf\u03c5\u03bb\u03bf\u03c2", + "\u03ba\u03bf\u03c5\u03c4\u03c3\u03bf\u03b2\u03af\u03b4\u03bf\u03c5", + "\u03b2\u03c1\u03b1\u03b4\u03ae", + "\u03c0\u03b1\u03bd\u03b1\u03b3\u03b9\u03ce\u03c4\u03bf\u03c5", + "\u03ba\u03b5\u03c3\u03b1\u03bb\u03af\u03b4\u03b7\u03c2", + "\u03c1\u03cc\u03b3\u03b1\u03c1\u03b7\u03c2", + "\u03b3\u03b5\u03c1\u03bf\u03ba\u03ce\u03c3\u03c4\u03b1", + "\u03ba\u03bf\u03ba\u03ba\u03b9\u03bd\u03af\u03b4\u03bf\u03c5", + "\u03bc\u03b1\u03c1\u03ba\u03b1\u03bd\u03c4\u03c9\u03bd\u03ac\u03ba\u03b7", + "\u03b4\u03bf\u03c5\u03bb\u03b3\u03b5\u03c1\u03ac\u03ba\u03b7\u03c2", + "\u03b3\u03ba\u03cc\u03c4\u03c3\u03b7\u03c2", + "\u03c3\u03c0\u03b7\u03bb\u03b9\u03ac\u03b4\u03bf\u03c5", + "\u03b1\u03bd\u03c4\u03c9\u03bd\u03cc\u03c0\u03bf\u03c5\u03bb\u03bf\u03c2", + "\u03ba\u03c1\u03b9\u03ac\u03bb\u03b7\u03c2", + "\u03bc\u03b1\u03c3\u03c4\u03c1\u03bf\u03b3\u03b9\u03ac\u03bd\u03bd\u03b7\u03c2", + "\u03ba\u03bf\u03bd\u03b4\u03c5\u03bb\u03af\u03b4\u03b7\u03c2", + "\u03c7\u03b9\u03c4\u03cc\u03c2", + "\u03b3\u03bf\u03cd\u03c0\u03b1", + "\u03c4\u03b6\u03b9\u03ce\u03c4\u03b6\u03b7\u03c2", + "\u03ba\u03bf\u03cd\u03c4\u03c3\u03b9\u03ba\u03bf\u03c2", + "\u03ba\u03c9\u03c4\u03bf\u03cd\u03bb\u03b1", + "\u03c3\u03c5\u03c1\u03bc\u03bf\u03cd", + "\u03b9\u03bd\u03c4\u03b6\u03ad\u03c2", + "\u03b1\u03c3\u03b7\u03bc\u03b1\u03ba\u03cc\u03c0\u03bf\u03c5\u03bb\u03bf\u03c2", + "\u03c3\u03c5\u03c1\u03c1\u03ae\u03c2", + "\u03b3\u03bf\u03cd\u03bb\u03b1", + "\u03ba\u03b5\u03c3\u03b5\u03bc\u03af\u03b4\u03b7\u03c2", + "\u03b8\u03b5\u03bf\u03b4\u03c9\u03c1\u03b9\u03ba\u03ac\u03ba\u03bf\u03c2", + "\u03b1\u03bd\u03b5\u03b6\u03ac\u03ba\u03b7", + "\u03bc\u03b1\u03bc\u03bc\u03ae\u03c2", + "\u03b3\u03ba\u03b1\u03bb\u03af\u03bf\u03c5", + "\u03ba\u03b1\u03c4\u03b5\u03b2\u03ac\u03c4\u03b7\u03c2", + "\u03c3\u03b1\u03c1\u03b1\u03bd\u03c4\u03b9\u03bd\u03cc\u03c2", + "\u03ba\u03b1\u03c1\u03b1\u03ba\u03c5\u03c1\u03af\u03bf\u03c5", + "\u03c0\u03af\u03c0\u03c0\u03b1\u03c2", + "\u03b6\u03ce\u03bd\u03b9\u03bf\u03c2", + "\u03b6\u03b9\u03ce\u03b3\u03bf\u03c2", + "\u03c4\u03cc\u03bb\u03b7", + "\u03bd\u03b1\u03c3\u03af\u03ba\u03b1\u03c2", + "\u03ba\u03bf\u03c5\u03c1\u03c3\u03bf\u03c5\u03bc\u03af\u03b4\u03b7\u03c2", + "\u03c0\u03af\u03c3\u03c0\u03b1", + "\u03b1\u03bb\u03b5\u03be\u03b1\u03bd\u03b4\u03c1\u03ac\u03ba\u03b7", + "\u03c4\u03c3\u03ad\u03b3\u03b1\u03c2", + "\u03ba\u03b1\u03c1\u03b3\u03ac\u03ba\u03bf\u03c5", + "\u03b2\u03b1\u03b3\u03b5\u03bd\u03ac", + "\u03c6\u03bb\u03b1\u03c3\u03ba\u03ae", + "\u03c0\u03b5\u03c4\u03c1\u03cc\u03c0\u03bf\u03c5\u03bb\u03bf\u03c2", + "\u03b4\u03c1\u03b1\u03bc\u03bf\u03c5\u03bd\u03c4\u03ac\u03bd\u03b7", + "\u03bc\u03b1\u03c1\u03ac\u03ba\u03b7", + "\u03c1\u03ac\u03bb\u03bb\u03b7\u03c2", + "\u03bc\u03b5\u03be\u03ae", + "\u03c3\u03bc\u03b9\u03c4", + "\u03bc\u03b7\u03c4\u03c1\u03cc\u03c0\u03bf\u03c5\u03bb\u03bf\u03c2", + "\u03bc\u03b7\u03c4\u03c3\u03bf\u03c0\u03bf\u03cd\u03bb\u03bf\u03c5", + "\u03ba\u03bf\u03bd\u03c4\u03bf\u03ba\u03ce\u03c3\u03c4\u03b1\u03c2", + "\u03be\u03b1\u03bd\u03b8\u03bf\u03c0\u03bf\u03cd\u03bb\u03bf\u03c5", + "\u03bb\u03ac\u03bb\u03b1\u03c2", + "\u03c7\u03b1\u03c4\u03b6\u03b5\u03bb\u03bb\u03ae\u03c2", + "\u03b3\u03b9\u03b1\u03c3\u03b7\u03bc\u03ac\u03ba\u03b7\u03c2", + "\u03ba\u03c5\u03c0\u03c1\u03b1\u03af\u03bf\u03c2", + "\u03b1\u03c1\u03c7\u03b1\u03c5\u03bb\u03ae\u03c2", + "\u03b1\u03bd\u03b4\u03c1\u03b5\u03b1\u03bd\u03af\u03b4\u03b7\u03c2", + "\u03b4\u03b5\u03c1\u03bb\u03ce\u03c0\u03b1", + "\u03ba\u03c1\u03b9\u03c4\u03c3\u03ad\u03bb\u03b7\u03c2", + "\u03b6\u03b7\u03c1\u03cc\u03c2", + "\u03b4\u03c1\u03b1\u03ba\u03ac\u03ba\u03b7\u03c2", + "\u03ba\u03ce\u03c4\u03c3\u03bf\u03c5", + 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"\u03bc\u03b7\u03c4\u03c3\u03cc\u03c0\u03bf\u03c5\u03bb\u03bf\u03c2", + "\u03bd\u03ac\u03c3\u03c3\u03bf\u03c5", + "\u03ba\u03c5\u03c1\u03af\u03c4\u03c3\u03b7\u03c2", + "\u03bd\u03c4\u03cc\u03c4\u03b7\u03c2", + "\u03c0\u03ad\u03c4\u03c1\u03bf\u03c5", + "\u03bc\u03c0\u03b5\u03c1\u03b5\u03b4\u03ae\u03bc\u03b1\u03c2", + "\u03b4\u03b7\u03bc\u03b7\u03c4\u03c1\u03af\u03bf\u03c5", + "\u03ba\u03b1\u03c1\u03b1\u03bc\u03ac\u03bd\u03bf\u03c2", + "\u03c0\u03b1\u03c0\u03b1\u03b4\u03b7\u03bc\u03b7\u03c4\u03c1\u03bf\u03c0\u03bf\u03cd\u03bb\u03bf\u03c5", + "\u03ba\u03b1\u03c1\u03b1\u03b3\u03b9\u03ac\u03bd\u03bd\u03b7", + "\u03c3\u03ba\u03b1\u03c3\u03af\u03bb\u03b1", + "\u03b4\u03b7\u03bc\u03b7\u03c3\u03ba\u03ae\u03c2", + "\u03b3\u03b9\u03b1\u03bd\u03bd\u03ad\u03bb\u03bf\u03c2", + "\u03c1\u03bf\u03c5\u03c3\u03b9\u03b1\u03bd\u03cc\u03c2", + "\u03c0\u03bf\u03c4\u03b1\u03bc\u03b9\u03ac\u03bd\u03bf\u03c5", + "\u03c6\u03c9\u03ba\u03b1\u03b4\u03b5\u03bb\u03ae\u03c2", + 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"\u03bc\u03b1\u03ba\u03c1\u03ae\u03c2", + "\u03b3\u03b1\u03bb\u03b1\u03bd\u03bf\u03c0\u03bf\u03cd\u03bb\u03bf\u03c5", + "\u03bc\u03b1\u03bd\u03b9\u03ac\u03c4\u03b7", + "\u03c0\u03b1\u03c0\u03b1\u03b3\u03b9\u03ac\u03bd\u03bd\u03b7\u03c2", + "\u03c3\u03b1\u03bc\u03b1\u03ba\u03af\u03b4\u03b7\u03c2", + "\u03c0\u03b1\u03c0\u03b1\u03b4\u03ac\u03ba\u03b7\u03c2", + "\u03b3\u03c1\u03b7\u03b3\u03bf\u03c1\u03af\u03bf\u03c5", + "\u03b1\u03b3\u03b1\u03bb\u03b9\u03ce\u03c4\u03b7\u03c2", + "\u03ba\u03bf\u03c5\u03ba\u03bf\u03c5\u03b2\u03af\u03bd\u03bf\u03c2", + "\u03ba\u03bf\u03c5\u03c4\u03b5\u03bd\u03c4\u03ac\u03ba\u03b7\u03c2", + "\u03b4\u03bf\u03c5\u03c1\u03ac\u03bd\u03b7\u03c2", + "\u03c3\u03b9\u03b4\u03b7\u03c1\u03bf\u03c0\u03bf\u03cd\u03bb\u03bf\u03c5", + "\u03bd\u03c4\u03b1\u03bd\u03ce\u03bb\u03b1", + "\u03ba\u03b1\u03bc\u03c0\u03b5\u03c1\u03af\u03b4\u03b7\u03c2", + "\u03c6\u03bf\u03cd\u03c3\u03ba\u03b1\u03c2", + "\u03ba\u03b1\u03c4\u03c3\u03b9\u03bc\u03ac\u03bb\u03b7", + "\u03b1\u03b3\u03b3\u03b5\u03bb\u03af\u03b4\u03b7\u03c2", + "\u03c3\u03b9\u03ce\u03bc\u03bf\u03c2", + "\u03bc\u03c5\u03c4\u03ac\u03c1\u03b7", + "\u03ba\u03bf\u03ba\u03bf\u03c1\u03b4\u03ad\u03bb\u03b7\u03c2", + "\u03bb\u03b1\u03bf\u03c5\u03c1\u03b4\u03ad\u03ba\u03b7\u03c2", + "\u03b3\u03ba\u03b9\u03ba\u03cc\u03c0\u03bf\u03c5\u03bb\u03bf\u03c2", + "\u03b2\u03b1\u03c1\u03bf\u03c5\u03c4\u03af\u03b4\u03bf\u03c5", + "\u03b5\u03bc\u03bc\u03b1\u03bd\u03bf\u03c5\u03b7\u03bb\u03af\u03b4\u03bf\u03c5", + "\u03ba\u03c5\u03c1\u03ba\u03bf\u03cd\u03b4\u03b7", + "\u03bc\u03c0\u03bf\u03c4\u03b6\u03b9\u03ce\u03c1\u03b7", + "\u03c4\u03c3\u03b9\u03ac\u03ba\u03bf\u03c2", + "\u03c4\u03c3\u03ad\u03c4\u03bf\u03c5", + "\u03bc\u03c0\u03b1\u03ba\u03bb\u03ac\u03b2\u03b1\u03c2", + "\u03c0\u03bb\u03b1\u03c4\u03ac\u03ba\u03b7", + "\u03c8\u03c5\u03c1\u03c1\u03ae", + "\u03c7\u03b1\u03c1\u03b1\u03bb\u03ac\u03bc\u03c0\u03bf\u03c5\u03c2", + "\u03ba\u03b1\u03ba\u03bf\u03c4\u03c1\u03af\u03c7\u03b7", + "\u03b1\u03bd\u03c4\u03c9\u03bd\u03af\u03bf\u03c5", + "\u03bc\u03b1\u03c5\u03c1\u03bf\u03cd\u03c4\u03c3\u03bf\u03c2", + "\u03ba\u03b5\u03c4\u03b5\u03c3\u03af\u03b4\u03bf\u03c5", + "\u03ba\u03b1\u03c1\u03b1\u03bc\u03c3\u03b1\u03bb\u03ae\u03c2", + "\u03b3\u03b5\u03c1\u03ac\u03c1\u03b4\u03b7\u03c2", + "\u03c4\u03ac\u03c3\u03c3\u03b7", + "\u03bc\u03b1\u03bd\u03bf\u03c5\u03c3\u03ad\u03bb\u03b7\u03c2", + "\u03c7\u03c1\u03b9\u03c3\u03c4\u03bf\u03b4\u03bf\u03c5\u03bb\u03ac\u03ba\u03b7\u03c2", + "\u03b1\u03b3\u03b3\u03b5\u03bb\u03ac\u03ba\u03b7", + "\u03bf\u03c1\u03c6\u03b1\u03bd\u03af\u03b4\u03bf\u03c5", + "\u03bc\u03b7\u03bb\u03b9\u03ce\u03c1\u03b7\u03c2", + "\u03bd\u03b9\u03c4\u03c3\u03bf\u03c4\u03cc\u03bb\u03b7\u03c2", + "\u03c3\u03c5\u03bb\u03bb\u03af\u03b3\u03b1\u03c1\u03b4\u03bf\u03c2", + "\u03c7\u03bf\u03c5\u03bb\u03b9\u03ac\u03c1\u03b1\u03c2", + "\u03c0\u03b9\u03c3\u03ba\u03bf\u03c0\u03ac\u03bd\u03b7", + "\u03b3\u03b9\u03ce\u03c4\u03b7\u03c2", + "\u03b3\u03b5\u03c9\u03c1\u03b3\u03bf\u03cd\u03b4\u03b7\u03c2", + "\u03c0\u03b1\u03bd\u03bf\u03cd\u03c3\u03b7\u03c2", + "\u03c3\u03b1\u03bf\u03c5\u03bb\u03af\u03b4\u03b7\u03c2", + "\u03ba\u03bf\u03c4\u03c3\u03b9\u03bd\u03ac", + "\u03c7\u03c1\u03c5\u03c3\u03af\u03b4\u03b7\u03c2", + "\u03c0\u03b1\u03bd\u03c4\u03af\u03c3\u03ba\u03b1", + "\u03c7\u03b1\u03c7\u03bf\u03cd\u03b4\u03b7\u03c2", + "\u03c0\u03ad\u03c0\u03c0\u03b1\u03c2", + "\u03bd\u03b9\u03ba\u03bf\u03bb\u03bf\u03c5\u03b4\u03ac\u03ba\u03b7", + "\u03ba\u03bf\u03bd\u03b9\u03b4\u03ac\u03c1\u03b7\u03c2", + "\u03b2\u03b5\u03c1\u03b2\u03b5\u03c1\u03af\u03b4\u03bf\u03c5", + "\u03c4\u03c3\u03b5\u03c4\u03c3\u03ad\u03c1\u03b7", + "\u03ba\u03bf\u03c5\u03c4\u03c7\u03b9\u03ac\u03c2", + "\u03b9\u03b1\u03c4\u03c1\u03cc\u03c0\u03bf\u03c5\u03bb\u03bf\u03c2", + "\u03b1\u03b3\u03ba\u03c5\u03c1\u03cc\u03c0\u03bf\u03c5\u03bb\u03bf\u03c2", + "\u03b8\u03b5\u03bf\u03c7\u03ac\u03c1\u03b7\u03c2", + "\u03ba\u03b1\u03c4\u03c3\u03bf\u03cd\u03bb\u03b1", + 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"\u03ba\u03bf\u03c1\u03b4\u03b1\u03c4\u03b6\u03ae\u03c2", + "\u03ba\u03b5\u03bb\u03bb\u03ac\u03c1\u03b7\u03c2", + "\u03c7\u03b1\u03b2\u03c1\u03b5\u03b4\u03ac\u03ba\u03b7\u03c2", + "\u03b2\u03b1\u03bb\u03b1\u03b2\u03ac\u03bd\u03b7\u03c2", + "\u03bb\u03c5\u03c1\u03ae", + "\u03c1\u03ac\u03c0\u03c4\u03b7\u03c2", + "\u03c0\u03b1\u03c0\u03b1\u03bd\u03ac\u03bd\u03bf\u03c5", + "\u03c7\u03bf\u03c1\u03cc\u03b6\u03b7", + "\u03c4\u03c3\u03bf\u03cd\u03bc\u03bf\u03c2", + "\u03c7\u03c1\u03ae\u03c3\u03c4\u03bf\u03c5", + "\u03c0\u03b9\u03c3\u03c7\u03b9\u03bd\u03ac\u03c2", + "\u03c3\u03b1\u03ba\u03ba\u03ae", + "\u03ba\u03c9\u03c4\u03c3\u03b9\u03ba\u03cc\u03c1\u03b7\u03c2", + "\u03ba\u03c9\u03c3\u03c4\u03b1\u03bb\u03ae\u03c2", + "\u03c4\u03b6\u03b5\u03b2\u03b5\u03bb\u03ad\u03ba\u03bf\u03c2", + "\u03c4\u03c3\u03ad\u03bb\u03b9\u03bf\u03c2", + "\u03c0\u03b1\u03c0\u03b1\u03b5\u03c5\u03b1\u03b3\u03b3\u03ad\u03bb\u03bf\u03c5", + "\u03c3\u03c9\u03c4\u03b7\u03c1\u03ac\u03bb\u03b7\u03c2", + "\u03c7\u03b1\u03c4\u03b6\u03ae", + "\u03ba\u03b9\u03bf\u03c5\u03c0\u03bb\u03b9\u03ce\u03c4\u03b7\u03c2", + "\u03b3\u03b9\u03b1\u03bd\u03bd\u03b1\u03c1\u03ac", + "\u03c4\u03c3\u03b1\u03c4\u03c3\u03ac\u03bd\u03b7\u03c2", + "\u03b1\u03c3\u03b1\u03c1\u03af\u03b4\u03b7\u03c2", + "\u03c0\u03bf\u03c5\u03bb\u03b7\u03bc\u03ad\u03bd\u03bf\u03c2", + "\u03c1\u03cc\u03ba\u03b1\u03c2", + "\u03c0\u03bf\u03bb\u03ad\u03bc\u03b7", + "\u03c4\u03c3\u03b1\u03b3\u03bb\u03b9\u03ce\u03c4\u03b7\u03c2", + "\u03b3\u03b9\u03b1\u03bd\u03bd\u03bf\u03cd\u03ba\u03bf\u03c2", + "\u03c0\u03b1\u03c0\u03b1\u03c3\u03c4\u03b5\u03c1\u03b3\u03af\u03bf\u03c5", + "\u03c1\u03cc\u03b3\u03b3\u03b1", + "\u03ba\u03b1\u03c4\u03c3\u03b1\u03bd\u03c4\u03ce\u03bd\u03b7", + "\u03b4\u03c1\u03b1\u03ba\u03ac\u03ba\u03b7", + "\u03c7\u03b1\u03c1\u03c0\u03b1\u03bd\u03c4\u03af\u03b4\u03b7\u03c2", + "\u03b2\u03b1\u03bc\u03b2\u03b1\u03ba\u03ac\u03c2", + "\u03bc\u03c0\u03bf\u03c4\u03ce\u03bd\u03b7\u03c2", + 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"\u03bc\u03b1\u03c5\u03c1\u03bf\u03b5\u03af\u03b4\u03b7", + "\u03bc\u03c0\u03b1\u03c1\u03ba\u03bf\u03cd\u03c4\u03b1", + "\u03c0\u03b1\u03bd\u03c4\u03b1\u03b6\u03ae\u03c2", + "\u03b3\u03b9\u03b1\u03bd\u03bd\u03b1\u03ba\u03bf\u03c5\u03b4\u03ac\u03ba\u03b7", + "\u03b3\u03bf\u03cd\u03c3\u03b9\u03bf\u03c2", + "\u03b3\u03ba\u03bf\u03cd\u03c3\u03ba\u03bf\u03c2", + "\u03b3\u03ba\u03b1\u03c4\u03b6\u03bf\u03b3\u03b9\u03ac\u03bd\u03bd\u03b7\u03c2", + "\u03c6\u03c5\u03c4\u03b9\u03bb\u03ae", + "\u03ba\u03b1\u03c3\u03bc\u03b9\u03c1\u03bb\u03ae", + "\u03ba\u03bf\u03c5\u03bb\u03bf\u03c5\u03c1\u03b9\u03ce\u03c4\u03b7\u03c2", + "\u03b6\u03c5\u03b3\u03bf\u03cd\u03c1\u03b7\u03c2", + "\u03ba\u03b1\u03bb\u03b9\u03ac\u03bc\u03c0\u03bf\u03c2", + "\u03ba\u03b1\u03c4\u03c3\u03b9\u03bc\u03ac\u03bd\u03b7", + "\u03ba\u03b1\u03c1\u03b1\u03bd\u03af\u03ba\u03b1\u03c2", + "\u03b4\u03c1\u03cc\u03c3\u03bf\u03c5", + "\u03b1\u03bb\u03b5\u03be\u03bf\u03c0\u03bf\u03cd\u03bb\u03bf\u03c5", + "\u03c4\u03c3\u03b1\u03bc\u03bf\u03c0\u03bf\u03cd\u03bb\u03bf\u03c5", + "\u03c3\u03c4\u03b1\u03bc\u03cc\u03c0\u03bf\u03c5\u03bb\u03bf\u03c2", + "\u03c3\u03c4\u03b5\u03c1\u03b3\u03b9\u03b1\u03bb\u03ae\u03c2", + "\u03b2\u03b1\u03ca\u03c4\u03c3\u03cc\u03c0\u03bf\u03c5\u03bb\u03bf\u03c2", + "\u03b6\u03c5\u03b3\u03bf\u03cd\u03c1\u03b7", + "\u03c7\u03c1\u03c5\u03c3\u03bf\u03c5\u03bb\u03ae\u03c2", + "\u03ba\u03b1\u03bb\u03bb\u03b9\u03ac\u03bd\u03c4\u03b1\u03c3\u03b7", + "\u03be\u03b7\u03c1\u03cc\u03c2", + "\u03b2\u03b1\u03b6\u03bf\u03cd\u03c1\u03b1", + "\u03ba\u03b1\u03c0\u03b1\u03bd\u03c4\u03b1\u03ca\u03b4\u03ac\u03ba\u03b7", + "\u03b4\u03b9\u03b1\u03bc\u03b1\u03bd\u03c4\u03bf\u03c0\u03bf\u03cd\u03bb\u03bf\u03c5", + "\u03b1\u03bd\u03b4\u03c1\u03b9\u03ce\u03c4\u03b7\u03c2", + "\u03c6\u03b5\u03c1\u03b5\u03bd\u03c4\u03af\u03bd\u03bf\u03c2", + "\u03bb\u03b9\u03cc\u03bd\u03c4\u03b7", + "\u03c0\u03bf\u03c5\u03bb\u03b9\u03ad\u03b6\u03bf\u03c2", + "\u03b5\u03c5\u03b1\u03b3\u03b3\u03b5\u03bb\u03ac\u03c4\u03bf\u03c2", + "\u03ba\u03b1\u03c1\u03b1\u03bf\u03b3\u03bb\u03ac\u03bd\u03b7", + "\u03ba\u03c9\u03c3\u03c4\u03bf\u03c0\u03bf\u03cd\u03bb\u03bf\u03c5", + "\u03b2\u03bf\u03c3\u03b9\u03bd\u03ac\u03ba\u03b7", + "\u03c4\u03b6\u03b9\u03cc\u03c1\u03c4\u03b6\u03b9\u03bf\u03c2", + "\u03c4\u03c5\u03bc\u03b2\u03af\u03bf\u03c5", + "\u03bc\u03c0\u03bf\u03cd\u03c3\u03b9\u03bf\u03c2", + "\u03b1\u03c1\u03b1\u03c0\u03ac\u03ba\u03b7", + "\u03c7\u03b1\u03c1\u03b1\u03bb\u03b1\u03bc\u03c0\u03af\u03b4\u03b7\u03c2", + "\u03c1\u03b1\u03c6\u03b9\u03cc\u03c2", + "\u03b3\u03b5\u03bd\u03b5\u03c4\u03b6\u03ac\u03ba\u03b7\u03c2", + "\u03ba\u03b9\u03bf\u03cd\u03c3\u03b7\u03c2", + "\u03be\u03b5\u03bd\u03ac\u03ba\u03b7", + "\u03ba\u03b1\u03c1\u03ac\u03bc\u03c0\u03b1\u03c2", + "\u03b2\u03c1\u03b1\u03ba\u03ac", + "\u03bb\u03b9\u03b2\u03b1\u03bd\u03cc\u03c2", + "\u03b2\u03bf\u03bb\u03b9\u03ba\u03ac\u03ba\u03b7\u03c2", + "\u03c3\u03c4\u03b1\u03b8\u03cc\u03c0\u03bf\u03c5\u03bb\u03bf\u03c2", + "\u03c0\u03b1\u03bd\u03c4\u03b6\u03ad\u03ba\u03bf\u03c2", + "\u03bc\u03b1\u03bd\u03bf\u03c0\u03bf\u03cd\u03bb\u03bf\u03c5", + "\u03bc\u03b1\u03c3\u03c4\u03c1\u03b1\u03b3\u03b3\u03b5\u03bb\u03ae", + "\u03ba\u03b1\u03c3\u03bf\u03cd\u03c4\u03c3\u03b1\u03c2", + "\u03c0\u03bf\u03bb\u03af\u03c4\u03bf\u03c5", + "\u03c3\u03c4\u03b1\u03bc\u03b1\u03c4\u03b9\u03ac\u03b4\u03b7\u03c2", + "\u03c4\u03c3\u03af\u03bc\u03b7", + "\u03bc\u03c0\u03b1\u03bb\u03b1\u03bc\u03c0\u03ac\u03bd\u03b7", + "\u03bc\u03b9\u03c3\u03af\u03b4\u03bf\u03c5", + "\u03be\u03b7\u03c1\u03bf\u03c4\u03cd\u03c1\u03b7", + "\u03c3\u03af\u03b4\u03b5\u03c1\u03b7\u03c2", + "\u03c4\u03b6\u03ad\u03ba\u03bf\u03c2", + "\u03c0\u03b5\u03bc\u03bf\u03cd\u03c3\u03b7", + "\u03b2\u03bf\u03cd\u03ba\u03b1\u03c2", + "\u03c7\u03c1\u03b9\u03c3\u03c4\u03bf\u03b4\u03bf\u03cd\u03bb\u03bf\u03c5", + "\u03b2\u03b1\u03b2\u03ac\u03c3\u03b7", + "\u03bc\u03c0\u03b1\u03c6\u03ad\u03c1\u03b1", + "\u03c0\u03bf\u03c1\u03af\u03c7\u03b7\u03c2", + "\u03ba\u03b1\u03c1\u03b1\u03b4\u03ae\u03bc\u03bf\u03c2", + "\u03c3\u03c0\u03c5\u03c1\u03b9\u03b4\u03ac\u03ba\u03b7\u03c2", + "\u03c7\u03b1\u03bb\u03b2\u03b1\u03c4\u03b6\u03ae", + "\u03c0\u03b1\u03bb\u03b7\u03cc\u03c2", + "\u03c3\u03cc\u03c6\u03c1\u03b1", + "\u03b1\u03bd\u03b4\u03c1\u03b9\u03ba\u03cc\u03c0\u03bf\u03c5\u03bb\u03bf\u03c2", + "\u03bc\u03c0\u03b1\u03ba\u03bf\u03c3\u03c4\u03b5\u03c1\u03b3\u03af\u03bf\u03c5", + "\u03c0\u03b5\u03c5\u03ba\u03b9\u03b1\u03bd\u03ac\u03ba\u03b7\u03c2", + "\u03b3\u03b9\u03b1\u03bd\u03bd\u03b1\u03ba\u03ad\u03b1\u03c2", + "\u03c4\u03bf\u03b4\u03ce\u03c1\u03b7\u03c2", + "\u03c0\u03b1\u03c0\u03b1\u03c4\u03b6\u03ae\u03ba\u03b1", + "\u03c0\u03b1\u03bb\u03b1\u03b9\u03bf\u03bb\u03bf\u03b3\u03bf\u03c0\u03bf\u03cd\u03bb\u03bf\u03c5", + "\u03ba\u03b1\u03c0\u03b5\u03c4\u03ac\u03bd\u03b9\u03bf\u03c2", + "\u03b8\u03b7\u03b2\u03b1\u03af\u03bf\u03c2", + "\u03ba\u03cc\u03bb\u03ba\u03b1\u03c2", + 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"\u03c0\u03b9\u03c4\u03b5\u03c1\u03cc\u03c2", + "\u03ba\u03bf\u03c5\u03bc\u03b9\u03ce\u03c4\u03b7\u03c2", + "\u03c3\u03ba\u03c1\u03af\u03bc\u03c0\u03b1\u03c2", + "\u03c4\u03b6\u03b9\u03ac\u03c1\u03b1\u03c2", + "\u03b4\u03b5\u03c3\u03cd\u03bb\u03bb\u03b1\u03c2", + "\u03ba\u03b1\u03c1\u03b1\u0390\u03c3\u03ba\u03bf\u03c2", + "\u03ba\u03b1\u03bc\u03c0\u03ac\u03ba\u03b1\u03c2", + "\u03bd\u03ac\u03bd\u03c4\u03c3\u03bf\u03c5", + "\u03ba\u03bf\u03c4\u03c3\u03b1\u03c1\u03ae\u03c2", + "\u03b1\u03b8\u03b1\u03bd\u03b1\u03c3\u03cc\u03c0\u03bf\u03c5\u03bb\u03bf\u03c2", + "\u03c7\u03b1\u03c3\u03ac\u03c0\u03b7", + "\u03b4\u03c1\u03af\u03b2\u03b1", + "\u03c1\u03b9\u03b6\u03bf\u03cd\u03bb\u03b7\u03c2", + "\u03bc\u03b1\u03c5\u03c1\u03bf\u03b3\u03bf\u03bd\u03ac\u03c4\u03bf\u03c2", + "\u03b1\u03bc\u03c0\u03bb\u03b9\u03ac\u03bd\u03b9\u03c4\u03b7\u03c2", + "\u03c3\u03c0\u03b1\u03b8\u03cc\u03c0\u03bf\u03c5\u03bb\u03bf\u03c2", + "\u03c7\u03c1\u03b9\u03c3\u03c4\u03ac\u03c1\u03b1\u03c2", + 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"\u03c4\u03c3\u03b5\u03bd\u03c4\u03bf\u03cd\u03c1\u03bf\u03c2", + "\u03c0\u03b5\u03c1\u03ac\u03ba\u03b7\u03c2", + "\u03c4\u03c3\u03bf\u03c5\u03ba\u03b9\u03ac", + "\u03b1\u03c1\u03b3\u03c5\u03c1\u03bf\u03c0\u03bf\u03cd\u03bb\u03bf\u03c5", + "\u03ba\u03c9\u03c4\u03bf\u03cd\u03bb\u03b1\u03c2", + "\u03c3\u03b1\u03bc\u03c0\u03ac\u03bd\u03b7", + "\u03c0\u03bf\u03c5\u03bb\u03bf\u03b3\u03b9\u03b1\u03bd\u03bd\u03cc\u03c0\u03bf\u03c5\u03bb\u03bf\u03c2", + "\u03bb\u03b5\u03bb\u03b5\u03b4\u03ac\u03ba\u03b7\u03c2", + "\u03ba\u03bf\u03c5\u03ba\u03bf\u03c5\u03b8\u03ac\u03ba\u03b7", + "\u03c3\u03c4\u03bf\u03c6\u03bf\u03c1\u03b9\u03ac\u03b4\u03b7\u03c2", + "\u03b1\u03bd\u03b1\u03c3\u03c4\u03b1\u03c3\u03ac\u03ba\u03b7\u03c2", + "\u03b2\u03b1\u03c3\u03b9\u03bb\u03bf\u03b3\u03b9\u03ac\u03bd\u03bd\u03b7\u03c2", + "\u03b6\u03b1\u03c7\u03b1\u03c1\u03b9\u03bf\u03c5\u03b4\u03ac\u03ba\u03b7", + "\u03b5\u03bb\u03b5\u03c5\u03b8\u03b5\u03c1\u03af\u03bf\u03c5", + 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"\u03ba\u03bf\u03bd\u03c4\u03bf\u03cd", + "\u03b4\u03bf\u03c5\u03bc\u03ac\u03c2", + "\u03bc\u03c5\u03c4\u03b5\u03bb\u03ad\u03c4\u03c3\u03b7\u03c2", + "\u03b3\u03b9\u03b1\u03c0\u03b1\u03c4\u03b6\u03ae\u03c2", + "\u03b1\u03bb\u03b1\u03c4\u03b6\u03ac\u03ba\u03b7\u03c2", + "\u03ba\u03bf\u03c5\u03ba\u03bf\u03c5\u03bb\u03b9\u03ac\u03bd\u03c4\u03b1\u03c2", + "\u03c3\u03b9\u03bc\u03b9\u03c4\u03b6\u03ae", + "\u03b6\u03b1\u03c1\u03b6\u03ac\u03bd\u03b7", + "\u03ba\u03bf\u03c5\u03c4\u03ba\u03b9\u03ac", + "\u03c4\u03b1\u03be\u03af\u03b4\u03bf\u03c5", + "\u03ba\u03b9\u03bf\u03c1\u03af\u03b4\u03bf\u03c5", + "\u03bc\u03bf\u03c3\u03c7\u03bf\u03b2\u03ac\u03ba\u03b7", + "\u03bc\u03c0\u03b1\u03bb\u03c4\u03b1\u03b3\u03b9\u03ac\u03bd\u03bd\u03b7\u03c2", + "\u03b4\u03b7\u03bc\u03b7\u03c4\u03c1\u03cc\u03c0\u03bf\u03c5\u03bb\u03bf\u03c2", + "\u03c1\u03b1\u03c5\u03c4\u03bf\u03c0\u03bf\u03cd\u03bb\u03bf\u03c5", + "\u03c4\u03b1\u03ba\u03b1\u03bd\u03c4\u03b6\u03ac\u03c2", + "\u03c0\u03b1\u03bb\u03b1\u03bc\u03c0\u03bf\u03c5\u03b3\u03b9\u03bf\u03cd\u03ba\u03b7", + "\u03c3\u03b1\u03bb\u03c4\u03b1\u03bf\u03cd\u03c1\u03b1\u03c2", + "\u03ba\u03b1\u03c0\u03b1\u03c4\u03c3\u03ce\u03c1\u03b7\u03c2", + "\u03b3\u03b1\u03b2\u03c1\u03b9\u03b4\u03ac\u03ba\u03b7\u03c2", + "\u03bc\u03c0\u03bf\u03c4\u03c3\u03ce\u03bb\u03b7\u03c2", + "\u03c4\u03c3\u03b9\u03c0\u03bb\u03af\u03ba\u03c9\u03c6", + "\u03c0\u03b1\u03c4\u03c3\u03bf\u03c5\u03c1\u03ad\u03b1", + "\u03bc\u03af\u03c7\u03bf\u03c5", + "\u03b9\u03b1\u03ba\u03c9\u03b2\u03ac\u03ba\u03b7\u03c2", + "\u03ba\u03b1\u03c1\u03c4\u03ac\u03c2", + "\u03c3\u03c0\u03b1\u03bd\u03bf\u03c5\u03b4\u03ac\u03ba\u03b7\u03c2", + "\u03bc\u03b1\u03bd\u03b9\u03c4\u03ac\u03c1\u03bf\u03c5", + "\u03ba\u03b1\u03c4\u03c3\u03b9\u03bb\u03bb\u03ae", + "\u03c4\u03b6\u03b9\u03cc\u03b2\u03b1", + "\u03b1\u03b4\u03b1\u03bc\u03cc\u03c0\u03bf\u03c5\u03bb\u03bf\u03c2", + "\u03c1\u03b1\u03b4\u03b9\u03bf\u03c0\u03bf\u03cd\u03bb\u03bf\u03c5", + "\u03c0\u03b1\u03c0\u03bf\u03c5\u03b4\u03ae\u03c2", + "\u03ba\u03c1\u03b1\u03b2\u03b2\u03b1\u03c1\u03af\u03c4\u03b7\u03c2", + "\u03c3\u03b1\u03c1\u03af\u03ba\u03b1\u03c2", + "\u03c3\u03b7\u03ba\u03c9\u03c4\u03af\u03b4\u03bf\u03c5", + "\u03b2\u03b1\u03c3\u03b9\u03bb\u03ac\u03ba\u03b7\u03c2", + "\u03bc\u03b1\u03bd\u03c9\u03bb\u03ac\u03ba\u03b7\u03c2", + "\u03bc\u03b9\u03c7\u03b1\u03b7\u03bb\u03af\u03b4\u03b7\u03c2", + "\u03bc\u03b1\u03c1\u03b3\u03b1\u03c1\u03b9\u03c4\u03ac\u03ba\u03b7", + "\u03bb\u03c5\u03bc\u03c0\u03ad\u03c1\u03b7\u03c2", + "\u03b6\u03b5\u03b3\u03bb\u03af\u03bd\u03b1", + "\u03c4\u03b6\u03b9\u03bd\u03b9\u03ad\u03c1\u03b7\u03c2", + "\u03b6\u03b5\u03bd\u03b5\u03bc\u03c0\u03af\u03c3\u03b7\u03c2", + "\u03c3\u03b3\u03bf\u03c5\u03c1\u03ad\u03bd\u03b1", + "\u03bb\u03b9\u03b1\u03bd\u03ac\u03ba\u03b7\u03c2", + "\u03c1\u03ad\u03c0\u03c0\u03b1", + "\u03c0\u03b1\u03c0\u03b1\u03ba\u03ce\u03c3\u03c4\u03b1", + "\u03b4\u03c1\u03b1\u03ba\u03cc\u03c0\u03bf\u03c5\u03bb\u03bf\u03c2", + "\u03c0\u03b9\u03c4\u03c3\u03ac\u03ba\u03b7\u03c2", + "\u03c4\u03c3\u03b5\u03bc\u03c0\u03b5\u03c1\u03bb\u03af\u03b4\u03b7\u03c2", + "\u03c1\u03ad\u03b3\u03ba\u03b1\u03c2", + "\u03b1\u03c5\u03b3\u03bf\u03c5\u03c3\u03c4\u03ae\u03c2", + "\u03c4\u03c3\u03b9\u03b1\u03c4\u03ae\u03c2", + "\u03c7\u03b1\u03c4\u03b6\u03b7\u03c6\u03ce\u03c4\u03b7", + "\u03c0\u03b5\u03c1\u03b9\u03c3\u03c4\u03b5\u03c1\u03cc\u03c0\u03bf\u03c5\u03bb\u03bf\u03c2", + "\u03c4\u03c3\u03ce\u03c4\u03c3\u03b7\u03c2", + "\u03bc\u03b5\u03bd\u03b3\u03ba", + "\u03c0\u03b9\u03c0\u03b5\u03c1\u03af\u03b4\u03b7", + "\u03ba\u03b9\u03bf\u03c3\u03ad\u03c2", + "\u03c0\u03b5\u03c4\u03c1\u03af\u03b4\u03b7\u03c2", + "\u03c1\u03ad\u03c0\u03c0\u03bf\u03c2", + "\u03c4\u03c3\u03b9\u03b1\u03bc\u03bf\u03cd\u03c1\u03b1\u03c2", + "\u03ba\u03bf\u03c5\u03c4\u03c3\u03b9\u03ba\u03bf\u03cd\u03c1\u03b7", + "\u03c0\u03b1\u03c5\u03bb\u03ac\u03ba\u03b7", + "\u03c4\u03b5\u03bc\u03bf\u03c5\u03c1\u03c4\u03b6\u03af\u03b4\u03b7\u03c2", + 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"\u03c4\u03c3\u03b1\u03bd\u03b4\u03ae\u03bb\u03b1\u03c2", + "\u03c3\u03bf\u03bb\u03b1\u03ba\u03bf\u03cd\u03b4\u03b7\u03c2", + "\u03b2\u03b1\u03c3\u03b9\u03bb\u03ac\u03ba\u03b7", + "\u03bc\u03c0\u03b1\u03b3\u03b1\u03bd\u03ac\u03c2", + "\u03ba\u03c5\u03bc\u03c0\u03ac\u03c1\u03b7\u03c2", + "\u03b2\u03bb\u03ac\u03c7\u03bf\u03c2", + "\u03b3\u03b9\u03b1\u03c4\u03c1\u03ac\u03ba\u03bf\u03c5", + "\u03b3\u03b5\u03c9\u03c1\u03b3\u03b1\u03c1\u03ac", + "\u03ba\u03b1\u03c1\u03ba\u03b1\u03bb\u03ad\u03c4\u03c3\u03b7", + "\u03c0\u03b1\u03bd\u03c4\u03b6\u03b1\u03c1\u03c4\u03b6\u03af\u03b4\u03b7\u03c2", + "\u03b2\u03b1\u03b2\u03bf\u03c5\u03c1\u03ac\u03ba\u03b7\u03c2", + "\u03bc\u03c0\u03b5\u03bb\u03ad\u03ba\u03bf\u03c5", + "\u03ba\u03b1\u03c6\u03af\u03c1\u03b7\u03c2", + "\u03bc\u03b1\u03bd\u03c4\u03ac\u03c2", + "\u03c4\u03c3\u03ac\u03c1\u03ba\u03bf\u03c2", + "\u03c7\u03c1\u03bf\u03bd\u03bf\u03c0\u03bf\u03cd\u03bb\u03bf\u03c5", + "\u03c4\u03c3\u03b1\u03bd\u03ac\u03ba\u03b1", + "\u03b2\u03ce\u03c3\u03c3\u03bf\u03c2", + "\u03c3\u03c4\u03c1\u03b1\u03b2\u03bf\u03c3\u03bd\u03af\u03c7\u03b7\u03c2", + "\u03c3\u03bc\u03c0\u03bf\u03bd\u03b9\u03ac\u03c2", + "\u03bb\u03b9\u03b8\u03bf\u03be\u03bf\u0390\u03b4\u03b7\u03c2", + "\u03bc\u03c0\u03bf\u03cd\u03ba\u03bf\u03c2", + "\u03ba\u03b1\u03c6\u03b1\u03bd\u03c4\u03ac\u03c1\u03b7", + "\u03bc\u03b1\u03c5\u03c1\u03bf\u03bc\u03b1\u03bd\u03c9\u03bb\u03ac\u03ba\u03b7\u03c2", + "\u03bc\u03b7\u03bb\u03b9\u03ac\u03b4\u03bf\u03c5", + "\u03c7\u03b1\u03c4\u03b6\u03b7\u03c3\u03ac\u03b2\u03b2\u03b1\u03c2", + "\u03b3\u03ba\u03b1\u03b3\u03ba\u03b1\u03bf\u03c5\u03b4\u03ac\u03ba\u03b7\u03c2", + "\u03c7\u03b1\u03bb\u03b1\u03bd\u03c4\u03b6\u03bf\u03cd\u03ba\u03b1", + "\u03b1\u03c0\u03bf\u03c3\u03c4\u03bf\u03bb\u03af\u03b4\u03b7\u03c2", + "\u03bc\u03c0\u03af\u03bb\u03bb\u03b1\u03c2", + "\u03b8\u03b5\u03bf\u03b4\u03c9\u03c1\u03cc\u03c0\u03bf\u03c5\u03bb\u03bf\u03c2", + "\u03c0\u03b5\u03c1\u03bf\u03c5\u03bb\u03ac\u03ba\u03b7", + "\u03c6\u03b1\u03c3\u03b1\u03c4\u03ac\u03ba\u03b7", + "\u03b1\u03c0\u03bf\u03c3\u03c4\u03bf\u03bb\u03ac\u03ba\u03b7\u03c2", + "\u03b3\u03b5\u03c9\u03c1\u03b3\u03af\u03c4\u03c3\u03b7", + "\u03c6\u03b9\u03bb\u03af\u03c0\u03c0\u03bf\u03c5", + "\u03b1\u03b3\u03b3\u03b5\u03bb\u03bf\u03c5\u03c3\u03bf\u03c0\u03bf\u03cd\u03bb\u03bf\u03c5", + "\u03c0\u03bf\u03bb\u03c5\u03c7\u03c1\u03bf\u03bd\u03af\u03b4\u03b7\u03c2", + "\u03bc\u03bf\u03c5\u03c4\u03bf\u03c5\u03c3\u03af\u03b4\u03b7\u03c2", + "\u03bd\u03ce\u03b5", + "\u03ba\u03b1\u03c0\u03bd\u03b9\u03ac", + "\u03c3\u03ba\u03b1\u03c6\u03c4\u03bf\u03cd\u03c1\u03bf\u03c5", + "\u03bd\u03b9\u03ba\u03bf\u03bb\u03bf\u03c0\u03bf\u03cd\u03bb\u03bf\u03c5", + "\u03ba\u03bf\u03bc\u03ba\u03bf\u03cd\u03b4\u03b7\u03c2", + "\u03ba\u03b1\u03b6\u03b1\u03bd\u03cc\u03c0\u03bf\u03c5\u03bb\u03bf\u03c2", + "\u03b4\u03b7\u03bc\u03c4\u03c3\u03bf\u03cd\u03b4\u03b7", + "\u03ba\u03b1\u03c0\u03bf\u03cd\u03bd\u03b7\u03c2", + "\u03bd\u03c4\u03cc\u03c4\u03c3\u03b7", + "\u03ba\u03b1\u03bb\u03b9\u03c4\u03c3\u03bf\u03c5\u03bd\u03ac\u03ba\u03b7\u03c2", + "\u03c0\u03b5\u03c1\u03b4\u03af\u03ba\u03b7\u03c2", + "\u03bc\u03c0\u03bf\u03bd\u03ad\u03bb\u03b7", + "\u03b3\u03c1\u03b7\u03b3\u03bf\u03c1\u03b9\u03ac\u03b4\u03bf\u03c5", + "\u03c3\u03c0\u03b1\u03bd\u03cc\u03c2", + "\u03b2\u03b1\u03bd\u03b4\u03ce\u03c1\u03bf\u03c2", + "\u03b1\u03c0\u03bf\u03c3\u03c4\u03bf\u03bb\u03af\u03b4\u03bf\u03c5", + "\u03c6\u03c1\u03bf\u03b3\u03ac\u03ba\u03b7\u03c2", + "\u03c3\u03b9\u03bf\u03cd\u03c4\u03b1", + "\u03bb\u03b1\u03b3\u03bf\u03b3\u03b9\u03ac\u03bd\u03bd\u03b7\u03c2", + "\u03ba\u03b1\u03c4\u03c3\u03b1\u03bd\u03c4\u03ce\u03bd\u03b7\u03c2", + "\u03ba\u03c5\u03c1\u03b9\u03b1\u03ba\u03bf\u03cd\u03bb\u03b7", + "\u03c0\u03b1\u03c0\u03b1\u03c3\u03c0\u03b7\u03bb\u03b9\u03c9\u03c4\u03bf\u03c0\u03bf\u03cd\u03bb\u03bf\u03c5", + "\u03ba\u03b1\u03bb\u03b1\u03bc\u03ac\u03c1\u03b1\u03c2", + "\u03bd\u03ac\u03c3\u03c4\u03bf\u03c2", + "\u03b3\u03b5\u03c1\u03bf\u03b4\u03ae\u03bc\u03bf\u03c2", + "\u03b6\u03b1\u03c7\u03b1\u03c1\u03af\u03bf\u03c5", + "\u03bc\u03ac\u03bb\u03b1\u03bc\u03b1", + "\u03c3\u03b5\u03b2\u03b4\u03ac\u03c2", + "\u03ba\u03b1\u03c1\u03b1\u03bd\u03b1\u03c3\u03af\u03bf\u03c5", + "\u03b3\u03b1\u03bb\u03b1\u03c4\u03bf\u03cd\u03bb\u03b1\u03c2", + "\u03b3\u03c1\u03b1\u03bc\u03bc\u03ad\u03bd\u03bf\u03c5", + "\u03bc\u03b9\u03c7\u03b5\u03bb\u03ae", + "\u03b3\u03c1\u03b5\u03c4\u03cc\u03c2", + "\u03b1\u03c1\u03c3\u03b5\u03bd\u03ac\u03ba\u03b7", + "\u03c0\u03b5\u03c4\u03c1\u03b9\u03c4\u03ac\u03ba\u03b7\u03c2", + "\u03ba\u03bf\u03bc\u03c0\u03bf\u03bb\u03b9\u03ac\u03c2", + "\u03bc\u03b1\u03ba\u03c1\u03c5\u03b3\u03b9\u03ac\u03bd\u03bd\u03b7\u03c2", + "\u03bd\u03c4\u03b1\u03b3\u03ba\u03b1\u03bb\u03ae", + "\u03bd\u03b1\u03c4\u03c3\u03bf\u03c5\u03bb\u03ae", + "\u03ba\u03b1\u03bb\u03b1\u03c0\u03cc\u03b4\u03b7\u03c2", + "\u03b1\u03b2\u03c1\u03b1\u03bc\u03b9\u03ce\u03c4\u03b7\u03c2", + "\u03c0\u03b1\u03c0\u03b1\u03b3\u03b9\u03b1\u03bd\u03bd\u03b1\u03ba\u03cc\u03c0\u03bf\u03c5\u03bb\u03bf\u03c2", + "\u03c0\u03ac\u03bd\u03bf\u03c2", + "\u03c7\u03bf\u03bd\u03b4\u03c1\u03bf\u03bb\u03af\u03b4\u03b7\u03c2", + "\u03ba\u03b1\u03ba\u03bf\u03c3\u03b1\u03af\u03bf\u03c2", + "\u03b2\u03b1\u03c1\u03b4\u03ac\u03ba\u03b7\u03c2", + "\u03ba\u03b5\u03c1\u03b1\u03c3\u03bf\u03b2\u03af\u03c4\u03b7\u03c2", + "\u03bc\u03b1\u03c5\u03c1\u03af\u03b4\u03b7", + "\u03bc\u03c0\u03bf\u03c6\u03cc\u03c2", + "\u03ba\u03bf\u03bd\u03c4\u03cc\u03c2", + "\u03c4\u03c1\u03b9\u03b1\u03bd\u03c4\u03b1\u03ba\u03c9\u03bd\u03c3\u03c4\u03b1\u03bd\u03c4\u03ae\u03c2", + "\u03c0\u03ac\u03bd\u03bf\u03c5", + "\u03ba\u03bf\u03bd\u03c4\u03bf\u03b3\u03b5\u03c9\u03c1\u03b3\u03ac\u03ba\u03b7", + "\u03c0\u03b5\u03c1\u03c1\u03ce\u03c4\u03b7\u03c2", + "\u03c0\u03bb\u03b1\u03ba\u03c9\u03c4\u03ac\u03c1\u03b7\u03c2", + "\u03b5\u03c5\u03b1\u03b3\u03b3\u03b5\u03bb\u03af\u03b4\u03b7", + "\u03ba\u03bf\u03c4\u03c1\u03ce\u03c4\u03c3\u03bf\u03c5", + "\u03ba\u03b1\u03c3\u03ba\u03b1\u03bf\u03cd\u03c4\u03b7", + "\u03b3\u03b5\u03c9\u03c1\u03b3\u03bf\u03cd\u03bb\u03b1", + "\u03bd\u03c4\u03cc\u03b2\u03b1\u03c2", + "\u03b1\u03c6\u03c1\u03bf\u03c5\u03b4\u03ac\u03ba\u03b7\u03c2", + "\u03c4\u03c3\u03b9\u03c4\u03bf\u03cd\u03c1\u03b1\u03c2", + "\u03be\u03b1\u03bd\u03b8\u03ac\u03ba\u03b7\u03c2", + "\u03bc\u03b1\u03c1\u03c4\u03b6\u03bf\u03cd\u03ba\u03bf\u03c5", + "\u03c0\u03b9\u03c0\u03b5\u03c1\u03af\u03b3\u03ba\u03bf\u03c2", + "\u03ba\u03b1\u03c1\u03b1\u03b8\u03b1\u03bd\u03ac\u03c3\u03b7", + "\u03bc\u03c0\u03b1\u03c4\u03b6\u03ac\u03bd\u03b7", + "\u03ba\u03b1\u03bd\u03b1\u03b2\u03cc\u03c2", + "\u03c3\u03c0\u03c5\u03c1\u03cc\u03c0\u03bf\u03c5\u03bb\u03bf\u03c2", + "\u03ba\u03c5\u03c1\u03b9\u03b1\u03ba\u03ac\u03ba\u03b7\u03c2", + "\u03bb\u03b5\u03b2\u03ad\u03bd\u03c4\u03b7\u03c2", + "\u03c3\u03c4\u03b1\u03b8\u03ac\u03c4\u03bf\u03c2", + "\u03bd\u03c4\u03c1\u03b9\u03b2\u03b1\u03bb\u03ac", + "\u03bc\u03ac\u03c1\u03b3\u03b1\u03c1\u03b7\u03c2", + "\u03b2\u03b1\u03c3\u03b9\u03bb\u03b5\u03af\u03bf\u03c5", + "\u03ba\u03bf\u03c1\u03c9\u03bd\u03af\u03b4\u03bf\u03c5", + "\u03ba\u03bf\u03bd\u03c4\u03bf\u03b3\u03b9\u03ac\u03bd\u03bd\u03b7\u03c2", + "\u03ba\u03c1\u03b5\u03bc\u03bc\u03cd\u03b4\u03b1\u03c2", + "\u03c7\u03c1\u03bf\u03bd\u03cc\u03c0\u03bf\u03c5\u03bb\u03bf\u03c2", + "\u03b1\u03bd\u03c4\u03c9\u03bd\u03ac\u03ba\u03bf\u03c2", + "\u03c0\u03b1\u03c0\u03b1\u03bd\u03b4\u03c1\u03ad\u03bf\u03c5", + "\u03bc\u03c0\u03bf\u03c5\u03c1\u03bb\u03ae\u03c2", + "\u03ba\u03c9\u03bd\u03c3\u03c4\u03b1\u03bd\u03c4\u03ac\u03c2", + "\u03ba\u03b1\u03c3\u03c3\u03c9\u03c4\u03ac\u03ba\u03b7", + "\u03b6\u03bf\u03bb\u03ce\u03c4\u03b1\u03c2", + "\u03bc\u03b1\u03c4\u03c3\u03bf\u03cd\u03c1\u03b7", + "\u03ba\u03b1\u03bb\u03b1\u03ca\u03c4\u03b6\u03bf\u03c0\u03bf\u03cd\u03bb\u03bf\u03c5", + "\u03bd\u03b9\u03ba\u03b7\u03c4\u03cc\u03c0\u03bf\u03c5\u03bb\u03bf\u03c2", + 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"\u03b9\u03c3\u03ac\u03c1\u03b7\u03c2", + "\u03c4\u03bf\u03bb\u03bf\u03cd\u03b4\u03b7\u03c2", + "\u03b1\u03c1\u03b1\u03c0\u03af\u03b4\u03bf\u03c5", + "\u03c4\u03c5\u03c1\u03ac\u03bb\u03b7\u03c2", + "\u03bc\u03c0\u03c1\u03bf\u03cd\u03b6\u03bf\u03c5", + "\u03b1\u03b2\u03c1\u03b1\u03bc\u03af\u03b4\u03bf\u03c5", + "\u03c0\u03c5\u03c1\u03bf\u03b2\u03cc\u03bb\u03bf\u03c5", + "\u03c4\u03ac\u03c3\u03b9\u03bf\u03c2", + "\u03b3\u03b9\u03b1\u03bd\u03bd\u03b1\u03ba\u03bf\u03c5\u03b4\u03ac\u03ba\u03b7\u03c2", + "\u03c6\u03b1\u03bb\u03b9\u03ad\u03c1\u03bf\u03c2", + "\u03bb\u03ac\u03c0\u03c0\u03b1\u03c2", + "\u03c3\u03b1\u03c1\u03b9\u03b4\u03ac\u03ba\u03b7", + "\u03ba\u03b1\u03bb\u03b4\u03ae", + "\u03c6\u03b9\u03bb\u03b9\u03c0\u03c0\u03cc\u03c0\u03bf\u03c5\u03bb\u03bf\u03c2", + "\u03bc\u03b9\u03c7\u03b1\u03bb\u03ad\u03bb\u03bb\u03b7\u03c2", + "\u03c6\u03bf\u03c5\u03c3\u03b9\u03ad\u03ba\u03b7\u03c2", + "\u03b2\u03b5\u03bb\u03b5\u03bd\u03c4\u03b6\u03ac\u03c2", + 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+ "\u03c0\u03b1\u03c5\u03bb\u03af\u03b4\u03bf\u03c5", + "\u03b6\u03b9\u03ac\u03ba\u03b1\u03c2", + "\u03ba\u03bf\u03c1\u03bf\u03bc\u03ae\u03bb\u03b1\u03c2", + "\u03ba\u03c9\u03bd\u03c3\u03c4\u03b1\u03bd\u03c4\u03b9\u03bd\u03af\u03b4\u03b7\u03c2", + "\u03b1\u03c1\u03b3\u03c5\u03c1\u03ac\u03ba\u03b7", + "\u03b1\u03c3\u03c3\u03b1\u03c1\u03b3\u03b9\u03c9\u03c4\u03ac\u03ba\u03b7", + "\u03c4\u03bf\u03c1\u03bf\u03bc\u03af\u03b4\u03b7\u03c2", + "\u03b6\u03b1\u03c1\u03b5\u03b9\u03c6\u03bf\u03c0\u03bf\u03cd\u03bb\u03bf\u03c5", + "\u03c3\u03bf\u03c5\u03c1\u03bc\u03c0\u03ae\u03c2", + "\u03b3\u03b1\u03c1\u03bf\u03c5\u03c6\u03b1\u03bb\u03ae\u03c2", + "\u03bc\u03b1\u03c3\u03cc\u03c0\u03bf\u03c5\u03bb\u03bf\u03c2", + "\u03c6\u03c1\u03bf\u03bd\u03b9\u03bc\u03ac\u03ba\u03b7", + "\u03ba\u03b1\u03c4\u03c3\u03b1\u03bd\u03af\u03ba\u03bf\u03c5", + "\u03bc\u03c9\u03c5\u03c3\u03af\u03b4\u03bf\u03c5", + "\u03bf\u03b9\u03ba\u03bf\u03bd\u03bf\u03bc\u03bf\u03c0\u03bf\u03cd\u03bb\u03bf\u03c5", + 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"\u03c7\u03c1\u03c5\u03c3\u03b9\u03ba\u03ac\u03ba\u03b7", + "\u03b3\u03b9\u03b1\u03bd\u03bd\u03bf\u03c0\u03bf\u03cd\u03bb\u03bf\u03c5", + "\u03c3\u03b1\u03c1\u03c1\u03cc\u03c2", + "\u03bc\u03c0\u03b1\u03bb\u03ac\u03c3\u03ba\u03b1\u03c2", + "\u03b4\u03bf\u03c5\u03bb\u03bf\u03c5\u03c6\u03ac\u03ba\u03b7", + "\u03b1\u03c3\u03bf\u03c5\u03c7\u03af\u03b4\u03bf\u03c5", + "\u03b2\u03b1\u03bc\u03b2\u03bf\u03c5\u03ba\u03ac\u03ba\u03b7", + "\u03bc\u03b7\u03c4\u03c1\u03bf\u03c0\u03bf\u03cd\u03bb\u03bf\u03c5", + "\u03c6\u03af\u03bb\u03ba\u03b1", + "\u03c3\u03ba\u03b1\u03c1\u03bb\u03ac\u03c4\u03bf\u03c2", + "\u03bc\u03ac\u03bd\u03c4\u03bf\u03c5", + "\u03c7\u03bf\u03bd\u03c4\u03b6\u03b9\u03ac", + "\u03c3\u03c4\u03c1\u03bf\u03cd\u03bc\u03c0\u03b1", + "\u03ba\u03ce\u03c4\u03c4\u03b1\u03c2", + "\u03c3\u03b1\u03bb\u03ad\u03bc\u03b7", + "\u03c3\u03b1\u03c1\u03b1\u03c6\u03af\u03b4\u03b7\u03c2", + "\u03ba\u03b1\u03ba\u03b1\u03b2\u03cc\u03c2", + "\u03b2\u03b1\u03bb\u03b1\u03c3\u03af\u03b4\u03b7\u03c2", + "\u03ba\u03b1\u03c1\u03ac\u03bd\u03b7\u03c2", + "\u03ba\u03bf\u03ba\u03ba\u03af\u03bd\u03bf\u03c5", + "\u03c4\u03b1\u03c5\u03bb\u03b1\u03c1\u03af\u03b4\u03bf\u03c5", + "\u03b4\u03ac\u03c6\u03bd\u03b7", + "\u03bb\u03cd\u03c4\u03c1\u03b1", + "\u03ba\u03c5\u03c1\u03b9\u03b1\u03bd\u03bd\u03ac\u03ba\u03b7", + "\u03bc\u03b1\u03bd\u03c4\u03ac", + "\u03b4\u03b1\u03bc\u03b1\u03bb\u03ac", + "\u03bc\u03b1\u03b6\u03b1\u03c1\u03ac\u03ba\u03b7\u03c2", + "\u03c0\u03b1\u03c0\u03b1\u03c1\u03bf\u03ca\u03b4\u03ac\u03bc\u03b7\u03c2", + "\u03c7\u03bf\u03c5\u03c1\u03b6\u03b1\u03bc\u03ac\u03bd\u03b7", + "\u03c4\u03c3\u03b1\u03c1\u03b1\u03bc\u03b9\u03ac\u03b4\u03b7\u03c2", + "\u03c0\u03b5\u03c4\u03c1\u03bf\u03b3\u03b9\u03ac\u03bd\u03bd\u03b7\u03c2", + "\u03b3\u03bf\u03c5\u03c1\u03b3\u03bf\u03c5\u03bb\u03ae\u03c2", + "\u03bb\u03b5\u03bc\u03bf\u03bd\u03ae\u03c2", + "\u03c3\u03c5\u03bc\u03b5\u03c9\u03bd\u03af\u03b4\u03bf\u03c5", + "\u03ba\u03b1\u03c4\u03c3\u03bf\u03b3\u03b9\u03ac\u03bd\u03bd\u03b7\u03c2", + "\u03b3\u03ba\u03ac\u03b3\u03ba\u03b1\u03c2", + "\u03ba\u03b1\u03c1\u03b1\u03ba\u03ce\u03c3\u03c4\u03b1", + "\u03c4\u03c3\u03b1\u03b3\u03ba\u03c1\u03b1\u03c3\u03bf\u03cd\u03bb\u03b7\u03c2", + "\u03c7\u03b1\u03bd\u03c4\u03b6\u03ae", + "\u03b2\u03bb\u03ac\u03c7\u03bf\u03c5", + "\u03c4\u03c3\u03b1\u03bc\u03b1\u03c3\u03bb\u03af\u03b4\u03b7\u03c2", + "\u03c4\u03c3\u03ce\u03bd\u03b7\u03c2", + "\u03c7\u03b1\u03c4\u03b6\u03b7\u03bc\u03b9\u03c7\u03b1\u03ae\u03bb", + "\u03bc\u03ae\u03c4\u03c3\u03bf\u03c5", + "\u03bc\u03ac\u03bd\u03b4\u03b1\u03bb\u03bf\u03c2", + "\u03b1\u03b3\u03b3\u03b5\u03bb\u03ae\u03c2", + "\u03ba\u03bf\u03c5\u03c4\u03c3\u03bf\u03cd\u03c1\u03b1\u03c2", + "\u03c0\u03b1\u03c4\u03bc\u03b1\u03bd\u03af\u03b4\u03b7\u03c2", + "\u03b1\u03c0\u03bf\u03c3\u03c4\u03bf\u03bb\u03b1\u03ba\u03ac\u03ba\u03b7\u03c2", + "\u03bc\u03b1\u03c5\u03c1\u03b9\u03ba\u03ac\u03ba\u03b7\u03c2", + "\u03ba\u03b1\u03c1\u03b1\u03c4\u03b6\u03b1\u03c6\u03ad\u03c1\u03b7\u03c2", + 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"\u03bc\u03c0\u03b1\u03bb\u03b1\u03bd\u03af\u03ba\u03b1", + "\u03b3\u03ba\u03b9\u03c4\u03c3\u03ac\u03ba\u03b7\u03c2", + "\u03c0\u03b1\u03c0\u03b1\u03bd\u03b4\u03c1\u03b9\u03ba\u03bf\u03c0\u03bf\u03cd\u03bb\u03bf\u03c5", + "\u03b6\u03b1\u03c1\u03b1\u03c6\u03ad\u03c4\u03b1\u03c2", + "\u03b1\u03bb\u03b1\u03c6\u03ac\u03ba\u03b7\u03c2", + "\u03b4\u03b1\u03bd\u03b9\u03b7\u03bb\u03af\u03b4\u03b7\u03c2", + "\u03b4\u03bf\u03c5\u03bb\u03ac\u03bc\u03b7", + "\u03bc\u03c0\u03b5\u03c1\u03bc\u03c0\u03b1\u03c4\u03b9\u03ce\u03c4\u03b7\u03c2", + "\u03bc\u03ac\u03c1\u03c1\u03b1\u03c2", + "\u03ba\u03af\u03c4\u03c3\u03bf\u03c5", + "\u03bc\u03c0\u03b1\u03bb\u03c4\u03b6\u03ae\u03c2", + "\u03c0\u03b1\u03c0\u03c0\u03ac", + "\u03b3\u03b5\u03c9\u03c1\u03b3\u03bf\u03cd\u03bb\u03b1\u03c2", + "\u03ba\u03b1\u03c1\u03b1\u03bb\u03ae\u03c2", + "\u03bc\u03af\u03c7\u03bf\u03c2", + "\u03b1\u03b2\u03b1\u03b3\u03b9\u03b1\u03bd\u03cc\u03c2", + 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"\u03b9\u03c9\u03b1\u03ba\u03b5\u03af\u03bc", + "\u03bc\u03b1\u03bd\u03bf\u03cd\u03ba\u03b1\u03c2", + "\u03c0\u03b1\u03bd\u03b1\u03b3\u03b9\u03c9\u03c4\u03b1\u03ba\u03bf\u03c0\u03bf\u03cd\u03bb\u03bf\u03c5", + "\u03bb\u03c5\u03b3\u03ba\u03bf\u03cd\u03c1\u03b1\u03c2", + "\u03c3\u03b4\u03c1\u03b1\u03bb\u03bb\u03ae\u03c2", + "\u03c0\u03b1\u03c1\u03b1\u03c3\u03ba\u03b5\u03c5\u03ac", + "\u03c4\u03c1\u03af\u03ba\u03b1", + "\u03c3\u03c0\u03b1\u03c3\u03cc\u03c0\u03bf\u03c5\u03bb\u03bf\u03c2", + "\u03bc\u03b1\u03c1\u03b3\u03b9\u03ac", + "\u03bc\u03b1\u03c5\u03c1\u03bf\u03b5\u03b9\u03b4\u03ac\u03ba\u03bf\u03c2", + "\u03c8\u03c5\u03bb\u03bb\u03ac\u03ba\u03b7\u03c2", + "\u03c3\u03bf\u03bb\u03c9\u03bc\u03af\u03b4\u03bf\u03c5", + "\u03c3\u03c0\u03b1\u03bd\u03bf\u03c7\u03c1\u03b9\u03c3\u03c4\u03bf\u03b4\u03bf\u03cd\u03bb\u03bf\u03c5", + "\u03bc\u03b1\u03b3\u03bf\u03cd\u03bb\u03b1", + "\u03c8\u03c5\u03c7\u03b9\u03ac\u03c2", + "\u03b2\u03b1\u03c3\u03b9\u03bb\u03bf\u03c0\u03bf\u03cd\u03bb\u03bf\u03c5", + "\u03c0\u03bf\u03bb\u03c5\u03b6\u03c9\u03ac\u03ba\u03b7\u03c2", + "\u03c3\u03ba\u03c5\u03bb\u03bf\u03b3\u03b9\u03ac\u03bd\u03bd\u03b7", + "\u03ba\u03b1\u03c1\u03b1\u03b3\u03b9\u03bf\u03b2\u03ac\u03bd\u03bd\u03b7", + "\u03bc\u03c0\u03af\u03ba\u03b1", + "\u03b1\u03b3\u03b3\u03b5\u03bb\u03ac\u03ba\u03bf\u03c2", + "\u03c3\u03b5\u03b2\u03b1\u03c3\u03c4\u03bf\u03cd", + "\u03c0\u03b1\u03c0\u03bf\u03c5\u03bb\u03ae\u03c2", + "\u03bc\u03b1\u03b3\u03ba\u03b1\u03c6\u03bf\u03c0\u03bf\u03cd\u03bb\u03bf\u03c5", + "\u03ba\u03b1\u03c8\u03ac\u03bb\u03b7\u03c2", + "\u03c3\u03c4\u03cc\u03b3\u03b9\u03bf\u03c2", + "\u03ba\u03c5\u03c1\u03b3\u03b9\u03ac\u03ba\u03b7\u03c2", + "\u03bb\u03bf\u03c5\u03c0\u03b1\u03c3\u03ac\u03ba\u03b7\u03c2", + "\u03bf\u03c1\u03c6\u03b1\u03bd\u03ac\u03ba\u03b7\u03c2", + "\u03c3\u03ba\u03cc\u03c1\u03b4\u03bf\u03c2", + "\u03c4\u03b1\u03c7\u03bc\u03b1\u03b6\u03af\u03b4\u03b7\u03c2", + "\u03c6\u03c1\u03b1\u03b3\u03ba\u03cc\u03c0\u03bf\u03c5\u03bb\u03bf\u03c2", + "\u03c0\u03b1\u03c0\u03b1\u03b3\u03b9\u03b1\u03bd\u03bd\u03cc\u03c0\u03bf\u03c5\u03bb\u03bf\u03c2", + "\u03c0\u03b1\u03c0\u03b1\u03b8\u03b1\u03bd\u03b1\u03c3\u03af\u03bf\u03c5", + "\u03c7\u03c1\u03c5\u03c3\u03b9\u03ba\u03cc\u03c2", + "\u03c1\u03ad\u03bd\u03c4\u03b1\u03c2", + "\u03b6\u03b5\u03c5\u03b3\u03af\u03c4\u03b7\u03c2", + "\u03bc\u03c0\u03b9\u03bc\u03c0\u03af\u03ba\u03b1", + "\u03ba\u03b1\u03c1\u03b1\u03c4\u03b6\u03af\u03ba\u03bf\u03c2", + "\u03bc\u03c0\u03b5\u03ba\u03ac\u03ba\u03bf\u03c5", + "\u03bc\u03c0\u03b1\u03bd\u03c4\u03ad\u03c2", + "\u03ba\u03bf\u03bd\u03b9\u03ac\u03c1\u03b7", + "\u03c8\u03c5\u03c7\u03ac\u03c1\u03b7", + "\u03c7\u03bf\u03c5\u03b4\u03b1\u03bb\u03ac\u03ba\u03b7\u03c2", + "\u03c4\u03c1\u03b9\u03b2\u03ad\u03bb\u03bb\u03b1\u03c2", + "\u03b3\u03ba\u03ac\u03b3\u03ba\u03b1", + "\u03ba\u03b1\u03c4\u03c3\u03b1\u03b2\u03cc\u03c2", + "\u03b1\u03bd\u03c4\u03c9\u03bd\u03ad\u03b1\u03c2", + "\u03c5\u03c6\u03b1\u03bd\u03c4\u03ae", + "\u03c7\u03c1\u03b9\u03c3\u03c4\u03bf\u03c6\u03cc\u03c1\u03b7", + "\u03b4\u03b1\u03bc\u03b1\u03c4\u03bf\u03c0\u03bf\u03cd\u03bb\u03bf\u03c5", + "\u03c4\u03c3\u03b9\u03b1\u03bc\u03af\u03c4\u03b1\u03c2", + "\u03c7\u03b1\u03c4\u03b6\u03b7\u03c7\u03b1\u03c1\u03af\u03c3\u03c4\u03bf\u03c5", + "\u03bc\u03ad\u03bb\u03b1\u03bd\u03b9", + "\u03b2\u03b1\u03b2\u03bf\u03c5\u03bb\u03af\u03b4\u03b7\u03c2", + "\u03c3\u03b1\u03bb\u03af\u03c7\u03bf\u03c2", + "\u03bc\u03c0\u03b1\u03c6\u03af\u03c4\u03b7", + "\u03c7\u03bf\u03c1\u03c4\u03ac\u03c4\u03bf\u03c5", + "\u03c7\u03b1\u03c4\u03b6\u03b7\u03b4\u03ac\u03ba\u03b7", + "\u03c7\u03b1\u03c4\u03b6\u03b7\u03ba\u03cd\u03c1\u03ba\u03bf\u03c2", + "\u03b4\u03c1\u03b1\u03b6\u03b9\u03ce\u03c4\u03b7\u03c2", + "\u03c0\u03b1\u03bb\u03b1\u03b9\u03bf\u03bb\u03cc\u03b3\u03bf\u03c2", + "\u03bd\u03bf\u03cd\u03c3\u03b7\u03c2", + "\u03c7\u03c1\u03b9\u03c3\u03c4\u03cc\u03c0\u03bf\u03c5\u03bb\u03bf\u03c2", + "\u03ba\u03b1\u03bc\u03b9\u03bd\u03ac\u03c1\u03b7", + "\u03b5\u03c5\u03c3\u03c4\u03c1\u03b1\u03c4\u03cc\u03c0\u03bf\u03c5\u03bb\u03bf\u03c2", + "\u03bc\u03c0\u03b1\u03bb\u03ac\u03c3\u03b7", + "\u03b3\u03b9\u03c9\u03c4\u03ac\u03ba\u03b7\u03c2", + "\u03b2\u03bf\u03cd\u03bb\u03ba\u03bf\u03c2", + "\u03b1\u03b8\u03b1\u03bd\u03b1\u03c3\u03ac\u03ba\u03b7\u03c2", + "\u03c4\u03c3\u03b1\u03bc\u03c0\u03bf\u03cd\u03c1\u03b7", + "\u03c0\u03b1\u03c0\u03b1\u03b4\u03ae\u03bc\u03b1", + "\u03c3\u03c0\u03b1\u03c3\u03ad\u03b3\u03ba\u03bf\u03c5", + "\u03c0\u03c1\u03bf\u03cd\u03b2\u03b1", + "\u03bc\u03b7\u03bb\u03b9\u03ac\u03ba\u03b7", + "\u03b2\u03b1\u03ba\u03b1\u03bb\u03ae\u03c2", + "\u03c0\u03b1\u03bb\u03b9\u03b5\u03c1\u03ac\u03ba\u03b7", + "\u03b3\u03ba\u03ac\u03b2\u03c1\u03bf\u03c5", + "\u03c7\u03bf\u03c5\u03bd\u03c4\u03ae\u03c2", + "\u03c3\u03c4\u03c1\u03b1\u03c4\u03bf\u03b3\u03b9\u03ac\u03bd\u03bd\u03b7", + "\u03c4\u03c3\u03ac\u03c4\u03b7", + "\u03c7\u03b7\u03c4\u03cc\u03c2", + "\u03b2\u03b1\u03bb\u03b9\u03ac\u03ba\u03b1", + 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b/data_tooling/pii_processing/ontology/data/en.json @@ -0,0 +1,16023 @@ +{ + "PLANT": [ + "creeping_willow", + "lepidium_alpina", + "acer_negundo", + "cucurbita_ficifolia", + "quercus_wislizenii", + "viola_pedata", + "hibiscus_syriacus", + "eucalypt_ovata", + "nothofagus_solanderi", + "leatherleaf_saxifrage", + "acanthocereus_tetragonus", + "gomphrena_globosa", + "hibiscus_mutabilis", + "arceuthobium_pusillum", + "brachychiton_populneus", + "glaucium_flavum", + "cryptogramma_acrostichoides", + "primula_auricula", + "senecio_vulgaris", + "robinia_hispida", + "physalis_viscosa", + "epigaea_repens", + "trichostema_lanatum", + "tsuga_caroliniana", + "entoloma_sinuatum", + "polypodium_virgianum", + "lilium_martagon", + "lupinus_luteus", + "one_flowered_wintergreen", + "pennisetum_ruppelii", + "hevea", + "pyracantha", + "acer_rubrum", + "botrychium_matricariifolium", + "vittaria_lineata", + "agathis_lanceolata", + "mahonia", + "heritiera_macrophylla", + "senna_marilandica", + "taraxacum_ruderalia", + "lespedeza_cuneata", + "cirsium_rivulare", + "western_mugwort", + "campanula_persicifolia", + "prunus_alleghaniensis", + "leucogenes_leontopodium", + "bergamot", + "eriophyllum_wallacei", + "diospyros_virginiana", + "dryopteris_fragrans", + "anthericum_liliago", + "senega", + "adiantum_tenerum", + "malaxis_ophioglossoides", + "dog_fennel", + "helenium_autumnale", + "pteris_multifida", + "iris_cristata", + "rhododendron_viscosum", + "mastic", + "sea_lyme_grass", + "pine", + "pak_choi", + "gentiana_holopetala", + "chrysanthemum_ptarmiciflorum", + "verbascum_thapsus", + "lycium_barbarum", + "adenium_multiflorum", + "coquelicot", + "red_campion", + "wormwood", + "hieracium_pilocella", + "sophora_sinensis", + "pleurotus_phosphoreus", + "carduus_crispus", + "parnassia", + "pityrogramma_chrysophylla", + "asclepia_meadii", + "giant_coreopsis", + "helicteres_isora", + "dog_rose", + "salvia_leucophylla", + "iris_germanica", + "burdock", + "lilium_philadelphicum", + "rhus_copallina", + "mule's_ears", + "tricholoma_sejunctum", + "coeloglossum_viride", + "lilium_longiflorum", + "sorghum_halepense", + "isopyrum_biternatum", + "giant_buttercup", + "rubus_saxatilis", + "florest's_cineraria", + "phoradendron_flavescens", + "genus_dracaena", + "veronica_beccabunga", + "lysimachia_ciliatum", + "dennstaedtia_punctilobula", + "mentzelia_laevicaulis", + "hyoscyamus_muticus", + "athyrium_thelypteroides", + "callitris_calcarata", + "ornithogalum_pyrenaicum", + "liriodendron_tulipifera", + "quercus_coccinea", + "dioscorea_elephantipes", + "arabidopsis_lyrata", + "cladonia_rangiferina", + "melissa", + "triglochin_maritima", + "seriphidium_tridentatum", + "canavalia_gladiata", + "sandalwood", + "impatiens_walleriana", + "geranium_molle", + "dioscorea_bulbifera", + "polystichum_adiantiformis", + "hoya_carnosa", + "tricholoma_pardinum", + "helianthus_petiolaris", + "erythronium_albidum", + "sea_dahlia", + "european_hornbeam", + "viola_arvensis", + "sapindus", + "rhapis_humilis", + "castanopsis_chrysophylla", + "scutellaria_galericulata", + "claviceps_purpurea", + "viola_reichenbachiana", + "fleawort", + "chimaphila_umbellata", + "crabgrass", + "sambucus_canadensis", + "lilium_lancifolium", + "agastache_mexicana", + "man_of_earth", + "polybotria_cervina", + "rosehip", + "black_eyed_susan", + "tragopogon_pratensis", + "plantago_psyllium", + "sarcoscypha_coccinea", + "corncockle", + "scolopendrium_nigripes", + "aleuria_aurantia", + "mountain_sandwort", + "philadelphus_coronarius", + "penstemon_davidsonii", + "aralia_elata", + "zygocactus_truncatus", + "brassica_nigra", + "pitanga", + "shittim", + "torreya_californica", + "bearberry_willow", + "eleocharis_dulcis", + "sea_rocket", + "sweetsop", + "poppyseed", + "betula_populifolia", + "bromus_tectorum", + "helleborus_niger", + "epidendrum_venosum", + "cleome_hassleriana", + "helianthus", + "aristolochia_serpentaria", + "auricularia_auricula", + "pterocarpus_santalinus", + "horehound", + "gaillardia_pulchella", + "hygrophorus_sordidus", + "rosa_chinensis", + "scarlet_lychnis", + "common_alder", + "spergularia_rubra", + "leucanthemum_superbum", + "polygala_senega", + "lysimachia_terrestris", + "lathyrus_latifolius", + "florence_fennel", + "banksia_integrifolia", + "carissa", + "lysiloma_latisiliqua", + "scorzonera_hispanica", + "terrietia_trifoliolata", + "sea_squill", + "marsilea_quadrifolia", + "polybotrya_cervina", + "eupatorium_maculatum", + "cucurbita_moschata", + "euphorbia_hirsuta", + "pilea_microphylla", + "monarda_citriodora", + "common_vetchling", + "rudbeckia_laciniata", + "solanaceae", + "bramble", + "eupatorium_perfoliatum", + "francoa_ramosa", + "clintonia_andrewsiana", + "salvia_verbenaca", + "cordia_alliodora", + "talinum_brevifolium", + "erica_tetralix", + "carpobrotus_edulis", + "campanula_medium", + "chrysanthemum_lacustre", + "caryota_urens", + "quercus_kelloggii", + "erigeron_divergens", + "vanilla_planifolia", + "viola_cornuta", + "mountain_alder", + "juncus_articulatus", + "peach_bells", + "eryngium_maritimum", + "squawbush", + "schefflera_actinophylla", + "amelanchier_bartramiana", + "tannia", + "pityrogramma_calomelanos", + "rubus_cuneifolius", + "sida_rhombifolia", + "lactuca_scariola", + "pachysandra_terminalis", + "hibiscus_heterophyllus", + "salix_babylonica", + "sparmannia_africana", + "adlumia_fungosa", + "celastric_articulatus", + "dryopteris_marginalis", + "chamomile", + "thermopsis_villosa", + "protium_heptaphyllum", + "asclepias_exaltata", + "willow", + "enoki", + "cyclamen_purpurascens", + "oxytropis_lambertii", + "huckleberry", + "marri", + "magnolia_acuminata", + "gymnocarpium_robertianum", + "cypripedium_parviflorum", + "pseudofruit", + "pseudotsuga_macrocarpa", + "white_horehound", + "kennedia_prostrata", + "solanum_giganteum", + "suillus_albivelatus", + "lycopodium_clavitum", + "birthwort", + "trichomanes_reniforme", + "meconopsis_betonicifolia", + "polygonatum_commutatum", + "anthyllis_vulneraria", + "physalis_pruinosa", + "prunus_japonica", + "abies_grandis", + "leucanthemum_maximum", + "anemia_adiantifolia", + "laurus_nobilis", + "yellow_rocket", + "lathyrus_odoratus", + "blephilia_celiata", + "non_flowering_plant", + "selaginella_lepidophylla", + "rhamnus_carolinianus", + "common_lavander", + "gawri", + "fraxinus_americana", + "strongylodon_macrobotrys", + "brachycome_iberidifolia", + "amanita", + "sequoiadendron", + "white_alder", + "vespula_vulgaris", + "coriaria_japonica", + "macrotyloma_uniflorum", + "achillea_ptarmica", + "matricaria_oreades", + "good_king_henry", + "arabidopsis_thaliana", + "caesalpinia_gilliesii", + "centaurea_nigra", + "cassia_acutifolia", + "rowan", + "pilularia_globulifera", + "bracelet_wood", + "vaccinium_pennsylvanicum", + "green_bean", + "saint_mary", + "salmonberry", + "microgramma_piloselloides", + "centaurea_moschata", + "santa_maria", + "gyromitra_fastigiata", + "mountain_laurel", + "bertholletia_excelsa", + "iris_tingitana", + "adenium_obesum", + "helianthus_annuus", + "dianthus_latifolius", + "gentiana_villosa", + "epipremnum_aureum", + "cirsium_lanceolatum", + "gentianopsis_holopetala", + "cat_thyme", + "agrostis_palustris", + "pluteus_aurantiorugosus", + "chinese_evergreen", + "euphorbia_heterophylla", + "arundo", + "nephrolepis_pectinata", + "cirsium_eriophorum", + "cassiope_mertensiana", + "astilbe_biternata", + "monarda", + "sorbus_torminalis", + "munjit", + "artist", + "trichostema_dichotomum", + "parathelypteris_simulata", + "lepiota_procera", + "campion", + "pot_plant", + "achillea", + "commiphora_meccanensis", + "magnolia_grandiflora", + "phlebodium_aureum", + "podocarpus_elongatus", + "tulipa_clusiana", + "berteroa_incana", + "cardamine_bulbifera", + "pelargonium_odoratissimum", + "mentzelia_livicaulis", + "colutea_arborescens", + "mille_feuille", + "erigonum_fasciculatum", + "capparis_mitchellii", + "yuca", + "andropogon_scoparius", + "alliaria_officinalis", + "camptosorus_rhizophyllus", + "prosopis_glandulosa", + "liparis_loeselii", + "chionanthus_virginicus", + "mullein", + "pennisetum_americanum", + "coprinus_comatus", + "red_starthistle", + "papaver_alpinum", + "lygodium_microphyllum", + "hydrangea_petiolaris", + "lettuce", + "podocarpus_elatus", + "bidens_tripartita", + "sinapis", + "solanum_burbankii", + "prunus_laurocerasus", + "pachysandra_procumbens", + "seriphidium_maritimum", + "astreus_pteridis", + "napaea_dioica", + "rhizoctinia_solani", + "allium_tuberosum", + "desmodium_motorium", + "datura_sanguinea", + "cherry_tomato", + "pennisetum_glaucum", + "adiantum_pedatum", + "hypericum_virginianum", + "schizachyrium_scoparium", + "senecio_triangularis", + "amelanchier_alnifolia", + "machaeranthera_tanacetifolia", + "yucca_gloriosa", + "hygrophorus_caeruleus", + "passiflora_ligularis", + "salix_triandra", + "leucaena_leucocephala", + "silene_virginica", + "lilium_michiganense", + "cercidiphyllum_japonicum", + "atriplex_hortensis", + "vaccinium_corymbosum", + "stenocarpus_sinuatus", + "spiraea_prunifolia", + "cortinarius_armillatus", + "eupatorium_purpureum", + "solanum_pseudocapsicum", + "quercus_falcata", + "agropyron_intermedium", + "dog_violet", + "begonia_heracleifolia", + "teucrium_scorodonia", + "acer_campestre", + "anastatica_hierochuntica", + "cirsium_helenioides", + "micromeria_chamissonis", + "nemophila_maculata", + "bletilla_striata", + "boletellus_russellii", + "hamelia_erecta", + "helianthus_angustifolius", + "sea_aster", + "cheilanthes_alabamensis", + "sambal", + "mimosa_pudica", + "larix_siberica", + "sarcocephalus_esculentus", + "leontopodium_alpinum", + "stapelias_asterias", + "saxifraga_sarmentosam", + "chamaecyparis_thyoides", + "habenaria_orbiculata", + "cherry", + "rubus_caesius", + "papaver_somniferum", + "green_hellebore", + "pythium_debaryanum", + "manioc", + "allium_sphaerocephalum", + "convolvulus", + "malus_angustifolia", + "sea_island_cotton", + "cortinarius_gentilis", + "carex_pseudocyperus", + "bunya", + "gentiana_lutea", + "tricholoma_irinum", + "giant_granadilla", + "montia_chamissoi", + "polystichum_acrostichoides", + "mercurialis_perennis", + "matthiola_incana", + "granny's_bonnets", + "centaurea_cineraria", + "pe_tsai", + "anona", + "quercus_velutina", + "arctostaphylos_alpina", + "caladenia_cairnsiana", + "boneset", + "botrychium_virginianum", + "acacia_pycnantha", + "cynoglossum_amabile", + "galium_lanceolatum", + "actinidia_chinensis", + "taxus_baccata", + "saxifraga_granulata", + "quercus_montana", + "sakura", + "bradley's_spleenwort", + "jicama", + "plum", + "mountain_rose", + "chloris_gayana", + "mountain_spinach", + "rheum_palmatum", + "geranium_richardsonii", + "sporobolus_cryptandrus", + "lycopodium_obscurum", + "valerianella_locusta", + "periploca_graeca", + "geum_macrophyllum", + "papaver", + "rhus_typhina", + "salix_humilis", + "nymphaea_alba", + "rhamnus_purshianus", + "silene_dioica", + "dicentra_spectabilis", + "penstemon_centranthifolius", + "matteuccia_struthiopteris", + "euphorbia_esula", + "dryopteris_oreopteris", + "phaseolus_coccineus", + "diplotaxis_tenuifolia", + "rhamnus_frangula", + "euphorbia_dentata", + "candida_albicans", + "pulicaria_dysenterica", + "ranunculus_ficaria", + "luluabourg", + "cladrastis_lutea", + "polygala_paucifolia", + "malope_trifida", + "callirhoe_involucrata", + "graptophyllum_pictum", + "senna_alata", + "nothofagus_procera", + "schinus_terebinthifolius", + "amaryllis_belladonna", + "veronica_officinalis", + "phegopteris_connectilis", + "illicium_floridanum", + "cynoglossum_virginaticum", + "shaggymane", + "philippine_mahogany", + "asperula", + "magnolia_soulangiana", + "sansevieria_zeylanica", + "rumex_scutatus", + "amphicarpaea_bracteata", + "sorb", + "mustard", + "pontederia_cordata", + "pycnanthemum_virginianum", + "phalaenopsis_amabilis", + "chrysanthemum_segetum", + "calophyllum_inophyllum", + "aconitum_lycoctonum", + "rosa_multiflora", + "corn_speedwell", + "hygrophorus_borealis", + "prunus_cerasus", + "anthemis_arvensis", + "helianthus_giganteus", + "microstrobos_niphophilus", + "solidago_rugosa", + "cassia_augustifolia", + "ligustrum_ovalifolium", + "piptadenia_macrocarpa", + "peltiphyllum_peltatum", + "pimenta_officinalis", + "anemone_riparia", + "citrus_decumana", + "acer_macrophyllum", + "nemophila_aurita", + "asclepias_purpurascens", + "acacia_dealbata", + "native_cranberry", + "capsicum_baccatum", + "avene_sterilis", + "pogonia_divaricata", + "silver_bell", + "herb_robert", + "rorippa_islandica", + "euonymus_americanus", + "dianthus_caryophyllus", + "gumamela", + "agrimonia_eupatoria", + "brasenia_schreberi", + "anaphalis_margaritacea", + "bidens_bipinnata", + "sea_milkwort", + "native_pomegranate", + "calamus_australis", + "melicocca_bijugatus", + "cheiranthus_asperus", + "jatropha_stimulosus", + "larix_occidentalis", + "spiny_talinum", + "plantago_lanceolata", + "swietinia_mahogani", + "pseudobombax_ellipticum", + "scindapsus_aureus", + "sciadopitys", + "mentha_citrata", + "erythronium_grandiflorum", + "trichostema_lanceolatum", + "polystichum_lonchitis", + "ononis_spinosa", + "polystichum_braunii", + "tanacetum_ptarmiciflorum", + "andropogon_virginicus", + "hamamelis_vernalis", + "baby's_tears", + "ranunculus_glaberrimus", + "xanthosoma_sagittifolium", + "gleichenia_flabellata", + "ipomoea_leptophylla", + "acer_palmatum", + "thlaspi_arvense", + "pericallis_hybrida", + "richardson's_geranium", + "agrostemma_githago", + "ligustrum_ibolium", + "dactyloctenium_aegypticum", + "geranium_pratense", + "silene_caroliniana", + "hedge", + "pseudolarix_amabilis", + "phyllodoce_breweri", + "solanum_carolinense", + "hypericum_androsaemum", + "alpinia_officinalis", + "poterium_sanguisorba", + "carolina_lupine", + "stylomecon_heterophyllum", + "damson", + "castanea_chrysophylla", + "phaseolus_aconitifolius", + "herb_paris", + "taxus_cuspidata", + "salix_viminalis", + "common_bamboo", + "athyrium_distentifolium", + "tilia_japonica", + "calvatia_gigantea", + "rhus_laurina", + "connarus_guianensis", + "melibe_japonica", + "melampodium_leucanthum", + "juniperus_virginiana", + "sphaeralcea_coccinea", + "calamintha_grandiflora", + "acacia_auriculiformis", + "sand_myrtle", + "arctostaphylos_andersonii", + "eriophorum_angustifolium", + "chrysanthemum_maximum", + "leonotis_nepetifolia", + "few_flowered_leek", + "veronica_serpyllifolia", + "alstonia_scholaris", + "dioscorea_paniculata", + "cycloloma_atriplicifolium", + "machaeranthera_tortifoloia", + "nemophila", + "eucalyptus_globulus", + "high_mallow", + "cassia_fistula", + "phyllocladus_alpinus", + "vaccinium_arboreum", + "pterospermum_acerifolium", + "platanus_occidentalis", + "passiflora_incarnata", + "phaseolus_angularis", + "clusia", + "festuca_ovina", + "zanthoxylum_americanum", + "oleandra_neriiformis", + "quercus_ellipsoidalis", + "syringa_reticulata", + "eriophyllum_lanatum", + "bromus_arvensis", + "polygala_vulgaris", + "hypericum_tetrapterum", + "milkwort", + "ardisia_crenata", + "canola_oil", + "haplopappus_phyllocephalus", + "fraxinus_quadrangulata", + "physostigma_venenosum", + "genus_brassica", + "polystichum_setiferum", + "veronica_peregrina", + "scutellaria_lateriflora", + "passiflora_maliformis", + "beet", + "chrysanthemum_leucanthemum", + "nothofagus_menziesii", + "tiarella_unifoliata", + "gramineous_plant", + "clematis_virginiana", + "cortinarius_semisanguineus", + "pennisetum_setaceum", + "star_saxifrage", + "penstemon_barbatus", + "lathyrus_maritimus", + "asphodeline_lutea", + "rubus_trivialis", + "artemisia_tridentata", + "chenopodium_capitatum", + "chaenomeles_speciosa", + "coral_necklace", + "selenicereus_grandiflorus", + "citrus_aurantium", + "pelargonium_peltatum", + "hydrophyllum_virginianum", + "amaranthus_spinosus", + "reseda", + "barbarea_vulgaris", + "aster_cordifolius", + "osmanthus_americanus", + "kochia_scoparia", + "felicia_bergeriana", + "psidium_cattleianum", + "delairea_odorata", + "annona_cherimola", + "lobelia_cardinalis", + "ulmus_sarniensis", + "helleborus_orientalis", + "dicot_genus", + "cortinarius_violaceus", + "dianthus_barbatus", + "myxomycete", + "platanus_orientalis", + "piper_longum", + "gossypium_hirsutum", + "holm", + "sugar_beet", + "larch", + "filago", + "bursera_microphylla", + "ceratopteris_pteridioides", + "blackthorn", + "abronia_maritima", + "kingcup", + "prunus_armeniaca", + "campanula_americana", + "entoloma_lividum", + "castanea_dentata", + "quercus_stellata", + "allamanda_cathartica", + "cocculus_carolinus", + "magnolia_macrophylla", + "liquidambar", + "nymphaea_odorata", + "diplazium_pycnocarpon", + "petasites_hybridus", + "urtica", + "potamogeton_crispus", + "red_sandalwood", + "iris_ensata", + "parthenocissus_tricuspidata", + "anthurium_andraeanum", + "iris_kaempferi", + "dog_stinkhorn", + "mentha_rotundifolia", + "lychnis", + "pseudowintera_colorata", + "thelypteris_dryopteris", + "elymus_hispidus", + "artemisia_cana", + "paspalum_distichum", + "tropaeolum_minus", + "macadamia_tetraphylla", + "ligustrum_obtusifolium", + "quercus_garryana", + "genus_discina", + "man_on_horse", + "coreopsis_maritima", + "lanceolate_spleenwort", + "saxifraga_hypnoides", + "carissa_grandiflora", + "fritillaria_mutica", + "maclura_pomifera", + "stenocarpus_salignus", + "bearberry", + "malus_baccata", + "cucurbita_argyrosperma", + "aster_arenosus", + "cardamine_rotundifolia", + "salix_fragilis", + "amanita_muscaria", + "pseudocolus_fusiformis", + "pterocarpus_indicus", + "margosa", + "olive", + "corylus_americana", + "yucca_filamentosa", + "brachychiton_australis", + "phylloporus_boletinoides", + "calla_palustris", + "leonurus_cardiaca", + "silybum", + "arenaria_peploides", + "spergula_arvensis", + "cassia_alata", + "physostegia_virginiana", + "asplenium_trichomanes", + "carissa_bispinosa", + "emilia_sagitta", + "acer_japonicum", + "tripleurospermum_inodorum", + "cliff_rose", + "pipsissewa", + "silene_acaulis", + "doryopteris_pedata", + "arrhenatherum_elatius", + "fraxinus_caroliniana", + "larkspur", + "agrostis_nebulosa", + "habenaria_lacera", + "asplenium_nigripes", + "blister_rust", + "asplenium_rhizophyllum", + "conocarpus_erectus", + "eucalyptus_camphora", + "lysimachia_quadrifolia", + "dryopteris_noveboracensis", + "nicotiana_alata", + "kniphofia", + "agana", + "dracocephalum", + "carissa_macrocarpa", + "populus_balsamifera", + "vorticella_convallaria", + "armeria_maritima", + "nicotiana_tabacum", + "quercus_incana", + "centaurea_scabiosa", + "myosotis_sylvatica", + "mirasol", + "cineraria_maritima", + "tracheophyte", + "kananga", + "loosestrife", + "woodwardia_virginica", + "rattail_cactus", + "chamaecrista_fasciculata", + "asclepias_verticillata", + "phyllostachys_nigra", + "rosa_laevigata", + "puccinia_graminis", + "astragalus_alpinus", + "quercus_variabilis", + "california_privet", + "hedgerow", + "ulmus_americana", + "markery", + "arisaema_atrorubens", + "hypericum_hypericoides", + "carex_arenaria", + "psidium_guineense", + "antennaria_plantaginifolia", + "eriodictyon_californicum", + "pilosella_officinarum", + "american_sycamore", + "wild_bergamot", + "laccopetalum_giganteum", + "erigeron_annuus", + "prem", + "platycladus_orientalis", + "cassia_marginata", + "nasturtium_amphibium", + "farkleberry", + "lepista_irina", + "sphaeralcea_fasciculata", + "acanthus_mollis", + "chervil", + "corallorhiza_striata", + "antirrhinum_filipes", + "hermannia_verticillata", + "crataegus_tomentosa", + "salix_lasiolepis", + "schizaea_pusilla", + "christmas_fern", + "mountain_mint", + "yucca_baccata", + "alpine_clubmoss", + "pholiota_squarrosoides", + "savin", + "stellaria_media", + "erica_perspicua", + "leucanthemum_vulgare", + "asplenium_bradleyi", + "jatropha_urens", + "solanum_nigrum", + "genus_angelica", + "calochortus_amabilis", + "marginal_placentation", + "abies_lasiocarpa", + "campanula_rapunculus", + "common_dandelion", + "fave", + "melastoma_malabathricum", + "lagarostrobus_franklinii", + "rhus_trilobata", + "genus_prunus", + "cystopteris_montana", + "astronium_fraxinifolium", + "serpentaria", + "rubus_parviflorus", + "chrysopsis_villosa", + "diplotaxis_muralis", + "derris_elliptica", + "sciadopitys_verticillata", + "ulmus_alata", + "calochortus_amoenus", + "geranium_robertianum", + "lycopodium_complanatum", + "pansy", + "lonicera_dioica", + "coconut_palm", + "peperomia_sandersii", + "aralia_spinosa", + "clematis", + "cyclophorus_lingua", + "anthemis_tinctoria", + "cranberry", + "helianthus_tuberosus", + "parthenium_argentatum", + "hedysarum_coronarium", + "senna_occidentalis", + "helianthus_maximilianii", + "lysiloma_bahamensis", + "eryngium_yuccifolium", + "woodruff", + "clematis_lasiantha", + "polypodium_aureum", + "camassia_leichtlinii", + "lithospermum_canescens", + "cleistes_divaricata", + "nogales", + "acanthocereus_pentagonus", + "hibiscus_elatus", + "water_gillyflower", + "wallpepper", + "crotalaria_sagitallis", + "sticherus_flabellatus", + "hippocrepis_comosa", + "saccharum", + "aster_divaricatus", + "white_rocket", + "usnea_barbata", + "amphicarpa_bracteata", + "verbena_officinalis", + "cornus_stolonifera", + "rewarewa", + "coeloglossum_bracteatum", + "pseudotaxus_chienii", + "lycopus_americanus", + "prunus_domestica", + "bryanthus_taxifolius", + "draba_verna", + "dendrocalamus_giganteus", + "giant_taro", + "limnodium_spongia", + "cercis_occidentalis", + "tricholoma_aurantium", + "lithophragma_parviflorum", + "cheilanthes_lanosa", + "medusa's_head", + "portulaca_grandiflora", + "phytophthora_infestans", + "linaria_japonica", + "gymnosperm_genus", + "chlorophyllum_molybdites", + "centaurea_americana", + "bilimbi", + "leptarrhena_pyrolifolia", + "polyporus_tenuiculus", + "muscicapa_striata", + "laguncularia_racemosa", + "tectaria_macrodonta", + "arundinaria_gigantea", + "asclepias_albicans", + "christmas_bells", + "russian_olive", + "prosopis_juliflora", + "acer_platanoides", + "cotoneaster_horizontalis", + "blue_star", + "snapdragon", + "rubus_idaeus", + "quercus_grosseserrata", + "lentiscus", + "haplopappus_spinulosus", + "brassica_pekinensis", + "divi_divi", + "monggo", + "viburnum_prunifolium", + "quercus_macrocarpa", + "prunus_pensylvanica", + "eucalyptus_maculata", + "callirhoe_digitata", + "styphelia_humifusum", + "gossypium_barbadense", + "brassica_chinensis", + "brachychiton_rupestris", + "calochortus_luteus", + "platylobium_formosum", + "argemone", + "ustilaginoidea_virens", + "great_millet", + "sophora_secundiflora", + "hedysarum_boreale", + "erica_carnea", + "cimicifuga_racemosa", + "euphorbia_cyparissias", + "colewort", + "salvia_pratensis", + "centaurea_cyanus", + "euphorbia_cyathophora", + "aster_falcatus", + "ormosia_coarctata", + "asclepias_incarnata", + "santolina_chamaecyparissus", + "delonix_regia", + "dorotheanthus_bellidiformis", + "cascara", + "guelder_rose", + "urtica_dioica", + "agaricus_campestris", + "oleandra_mollis", + "gymnadenia_conopsea", + "trifolium_repens", + "eugenia_uniflora", + "black_currant", + "cytisus_ramentaceus", + "blackberry", + "cardamine_bulbosa", + "quercus_prinoides", + "chrysolepis_chrysophylla", + "calopogon_pulchellum", + "veronica_michauxii", + "parochetus_communis", + "sunflower_seeds", + "oenanthe_aquatica", + "rosa_eglanteria", + "arctic_willow", + "carpenteria_californica", + "crab_apple", + "cortaderia_selloana", + "solanum", + "gentianella_amarella", + "ballota_nigra", + "parietal_placentation", + "cherrywood", + "helipterum_manglesii", + "campanula_carpatica", + "hymenoxys_acaulis", + "trichomanes_boschianum", + "sisymbrium_officinale", + "xerophyllum_tenax", + "florida_selaginella", + "salmwood", + "scarlet_fritillary", + "angelica_archangelica", + "black_mallee", + "acalypha_virginica", + "chinaberry", + "begonia_erythrophylla", + "allium_acuminatum", + "common_soapwort", + "campsis_radicans", + "cirsium_vulgare", + "rhodosphaera_rhodanthema", + "eryngium_aquaticum", + "echinocactus_grusonii", + "eupatorium_capillifolium", + "heterotheca_villosa", + "lilium_canadense", + "ruff", + "privet", + "evergreen_huckleberry", + "allium_neopolitanum", + "andromeda_glaucophylla", + "medinilla_magnifica", + "mountain_ebony", + "corypha_umbraculifera", + "brachychiton_acerifolius", + "bartle_frere", + "raffia_farinifera", + "caragana_arborescens", + "chickweed", + "sorbus_aucuparia", + "eviota_japonica", + "chard", + "senecio_cineraria", + "black_mangrove", + "monterey_pine", + "rose_chestnut", + "dianthus_chinensis", + "penstemon_linarioides", + "acer_pseudoplatanus", + "lycium_halimifolium", + "aristolochia_macrophylla", + "lotus_corniculatus", + "allium_triquetrum", + "montia_perfoliata", + "clematis_tangutica", + "polygonum_orientale", + "anchovy_pear", + "tulipa_suaveolens", + "gymnadenia_odoratissima", + "chrysolepis_sempervirens", + "robinia_viscosa", + "common_osier", + "hydrangea_arborescens", + "monarda_fistulosa", + "athyrium_pycnocarpon", + "bougainvillaea", + "davidson's_penstemon", + "martynia_fragrans", + "calamagrostis_acutiflora", + "polyporus_squamosus", + "raphanus_raphanistrum", + "cornus_florida", + "johnson_grass", + "lithophragma_affine", + "ficus_diversifolia", + "cytisus_multiflorus", + "chinese_holly", + "amaranthus_caudatus", + "phytelephas_macrocarpa", + "silene_latifolia", + "gymnocladus_dioica", + "sapindus_marginatus", + "ceroxylon_alpinum", + "genus_erica", + "saxifraga_stellaris", + "crataegus_pedicellata", + "polygala_japonica", + "cronartium_ribicola", + "melisa", + "botrychium_lunaria", + "fraxinus_velutina", + "rudbeckia_serotina", + "anagallis_tenella", + "hypericum_pyramidatum", + "combretum_erythrophyllum", + "chrysosplenium_americanum", + "arenaria_caroliniana", + "tetragonia_tetragonioides", + "amatungulu", + "septobasidium_pseudopedicellatum", + "monarda_pectinata", + "fagus_sylvatica", + "dog_laurel", + "scleranthus_annuus", + "laportea_canadensis", + "leonotis_nepetaefolia", + "golden_aster", + "gentiana_andrewsii", + "acrocarpus_fraxinifolius", + "cupressus_lusitanica", + "salix_pentandra", + "genus_echinocactus", + "emilia_flammea", + "tricholoma_flavovirens", + "metaplexis_japonica", + "aureolaria_virginica", + "collinsia_verna", + "cinchona_cordifolia", + "betula_fontinalis", + "cerastium_tomentosum", + "rubus_spectabilis", + "prunus_subcordata", + "broomcorn_millet", + "bittersweet_chocolate", + "drosophyllum_lusitanicum", + "crataegus_laevigata", + "antirrhinum_coulterianum", + "plagianthus_betulinus", + "coniogramme_japonica", + "genus_ricinus", + "anemone_virginiana", + "sinapis_arvensis", + "populus_canescens", + "quercus_lyrata", + "collinsia_parviflora", + "martynia_arenaria", + "acer_circinatum", + "euscaphis_japonica", + "lycopodium_alopecuroides", + "lindheimera_texana", + "scottish_maple", + "alexandrian_laurel", + "epilobium_angustifolium", + "wall_rocket", + "salix_repens", + "southern_harebell", + "water_hyacinth", + "hay_scented", + "stanleya_pinnata", + "sabina", + "sweetbrier", + "arum", + "abelmosk", + "silene_uniflora", + "dracunculus_vulgaris", + "pilosella_aurantiaca", + "brussels_sprout", + "little_barley", + "pinus_attenuata", + "polygala_alba", + "scleroderma_aurantium", + "acacia_melanoxylon", + "cyperus_papyrus", + "leucaena_glauca", + "agrostis_canina", + "saccharomyces_cerevisiae", + "listera_cordata", + "carya_laciniosa", + "platymiscium_pinnatum", + "tropaeolum_peregrinum", + "sweet_calabash", + "boletus_edulis", + "melampsora_lini", + "phyllocladus_asplenifolius", + "saccharum_officinarum", + "hydrangea_paniculata", + "buckeye", + "thrinax_keyensis", + "ceratostomella_ulmi", + "campanula_trachelium", + "aster_ptarmicoides", + "ranunculus_bulbosus", + "hesperis_matronalis", + "wild_geranium", + "poinciana_gilliesii", + "camphor", + "sugarberry", + "sourwood", + "peziza_coccinea", + "erythronium_americanum", + "taraxacum_officinale", + "cape_yellowwood", + "arenaria_serpyllifolia", + "solenostemon_scutellarioides", + "dog_grass", + "tetraneuris_grandiflora", + "lysimachia_vulgaris", + "daphne_cneorum", + "fraxinus_pennsylvanica", + "iris_persica", + "juglans_californica", + "eugenia_corynantha", + "viburnum_dentatum", + "calyptridium_umbellatum", + "erica_cinerea", + "dracaena_draco", + "campanula_rotundifolia", + "phytolacca_dioica", + "clinopodium_grandiflorum", + "phaseolus_multiflorus", + "begonia_cocchinea", + "columbine", + "medicago_intertexta", + "crotalaria_spectabilis", + "nettle", + "trichomanes_speciosum", + "malvastrum_coccineum", + "helianthus_laetiflorus", + "campanula_glomerata", + "chrysanthemum_coccineum", + "phaseolus_lunatus", + "marum", + "oxalo", + "christmas_rose", + "lonicera_tatarica", + "pachyrhizus_tuberosus", + "schizanthus", + "maritime_groundel", + "hypochaeris_radicata", + "clusia_flava", + "pellaea_mucronata", + "pulsatilla_occidentalis", + "actinidia_deliciosa", + "aporocactus_flagelliformis", + "dalbergia_latifolia", + "polystichum_aculeatum", + "anemopsis_californica", + "geranium_viscosissimum", + "crabapple", + "marathi", + "dipladenia_boliviensis", + "gaultheria_procumbens", + "thelypteris_hexagonoptera", + "anemone_pulsatilla", + "christmas_bush", + "beta_vulgaris", + "eucalyptus_amygdalina", + "sallow", + "polystichum_scopulinum", + "allium_carinatum", + "prunus_lyonii", + "cerastium_alpinum", + "helleborine", + "cypripedium_fasciculatum", + "pleurotus_ostreatus", + "omphalotus_illudens", + "allium_ursinum", + "harpullia_pendula", + "ligustrum_amurense", + "tetraneuris_acaulis", + "pseudotsuga_menziesii", + "helianthemum_scoparium", + "salvia_lancifolia", + "monotropa_uniflora", + "aaron's_beard", + "penstemon_dolius", + "american_watercress", + "spotted_flycatcher", + "stephanomeria_malheurensis", + "tanacetum_parthenium", + "american_planetree", + "hymenoxys_grandiflora", + "rosa_odorata", + "erythrina", + "lithospermum_officinale", + "genus_coreopsis", + "chrysothamnus_nauseosus", + "arisaema_dracontium", + "salix_vitellina", + "para_rubber", + "blephilia_hirsuta", + "silkwood", + "senna_alexandrina", + "sabal_palmetto", + "haricots_verts", + "vangueria_infausta", + "centaurium_minus", + "asparagus_plumosus", + "hygrophorus_tennesseensis", + "calandrinia_ciliata", + "mountain_hare", + "heracleum_sphondylium", + "lobelia_siphilitica", + "crataegus_aestivalis", + "drimys_winteri", + "dolichos_biflorus", + "erigeron_pulchellus", + "leucadendron_argenteum", + "prunus_cuneata", + "lepidothamnus_laxifolius", + "phlox_subulata", + "elymus_arenarius", + "rhus_toxicodenedron", + "sand_blackberry", + "penstemon_deustus", + "lathyrus_sylvestris", + "sida_hermaphrodita", + "marasmius_oreades", + "mountain_fern", + "symphytum_officinale", + "solidago_nemoralis", + "dicentra_canadensis", + "heteranthera_dubia", + "sapindus_drumondii", + "rosa_moschata", + "viola_tricolor", + "viburnum_opulus", + "rhus_quercifolia", + "carlina_vulgaris", + "allium_vineale", + "sophora_japonica", + "lychins_chalcedonica", + "our_lord's_candle", + "hieracium_praealtum", + "parasitic_plant", + "gentiana_saponaria", + "platycerium_andinum", + "sugarcane", + "gentiana_acaulis", + "salvia_farinacea", + "elaeis_guineensis", + "calla", + "calocedrus_decurrens", + "lupinus_arboreus", + "arctostaphylos_manzanita", + "artemis_spinescens", + "erythronium_montanum", + "dianthus_plumarius", + "poppy", + "leptopteris_superba", + "snowdrop_windflower", + "pelargonium_hortorum", + "carrot", + "brass_buttons", + "vaccinium_ovatum", + "prunus_serrulata", + "euphorbia_corollata", + "aspidistra_elatior", + "galium_verum", + "calopogon_tuberosum", + "aralia_stipulata", + "cycas_circinalis", + "populus_nigra", + "mentha_longifolia", + "asplenium_billotii", + "saxe_gothea", + "solanum_macranthum", + "nasturtium", + "darnel", + "pipestem_clematis", + "muscari_comosum", + "stenotaphrum_secundatum", + "clatonia_lanceolata", + "artemisia_filifolia", + "ranunculus_repens", + "honeysuckle", + "berberis_canadensis", + "humulus_japonicus", + "calochortus_elegans", + "apocynum_androsaemifolium", + "ribes_sativum", + "eustoma_grandiflorum", + "tricholoma_venenata", + "manioca", + "stellaria_holostea", + "strelitzia_reginae", + "agathis_australis", + "quira", + "lemna_minor", + "southern_magnolia", + "larix_laricina", + "coleus_aromaticus", + "corydalis_claviculata", + "aster_ericoides", + "cirsium_heterophylum", + "flower_bud", + "yew", + "pyrola_rotundifolia", + "salvinia_auriculata", + "rhododendron_californicum", + "colocasia_esculenta", + "coral_tree", + "leucothoe_fontanesiana", + "ustilago_maydis", + "inga_edulis", + "edelweiss", + "canangium", + "anemone_tetonensis", + "spiranthes_spiralis", + "gymnocarpium_dryopteris", + "protium_guianense", + "artillery_plant", + "lonicera_albiflora", + "enokitake", + "monardella_lanceolata", + "cardamine_pratensis", + "salpiglossis_sinuata", + "trifolium_stoloniferum", + "hypericum_calycinum", + "bindweed", + "pteris_serrulata", + "pteretis_struthiopteris", + "dichondra_micrantha", + "hypericum_maculatum", + "urocystis_cepulae", + "phyllitis_scolopendrium", + "zoisia", + "hypericum_perforatum", + "wolfberry", + "allium_fistulosum", + "menispermum_canadense", + "anthurium_scherzerianum", + "acrostichum_aureum", + "callitris_cupressiformis", + "azaleastrum", + "lychnis_coronaria", + "tangerine", + "brunfelsia_americana", + "salix_arctica", + "conyza_canadensis", + "cananga", + "pellicularia_filamentosa", + "cassia_javonica", + "corallorhiza_maculata", + "michaelmas_daisy", + "rosa_spithamaea", + "phacelia_campanularia", + "montia_cordifolia", + "gentiana_calycosa", + "campanula_aparinoides", + "amaranthus_hypochondriacus", + "solidago_multiradiata", + "lithocarpus_densiflorus", + "alnus_glutinosa", + "gerardia_virginica", + "cnidoscolus_urens", + "gymnopilus_ventricosus", + "diplotaxis_erucoides", + "cypripedium_montanum", + "eucalyptus_calophylla", + "erodium_texanum", + "desmodium_gyrans", + "viola_sylvatica", + "dioscorea_alata", + "christmas_tree", + "arctium_minus", + "arrhenatherum", + "eucalyptus_pauciflora", + "juneberry", + "annona_reticulata", + "cheilanthes_gracillima", + "pinus_muricata", + "paris_quadrifolia", + "bird_of_paradise", + "agropyron_repens", + "honeyberry", + "chrysanthemum_morifolium", + "phytolacca_americana", + "nicotiana_rustica", + "reseda_odorata", + "heuchera_americana", + "nyctaginia_capitata", + "lathyrus_sativus", + "oxalis", + "veronica_arvensis", + "anthriscus_sylvestris", + "belladonna", + "marchantia_polymorpha", + "astreus_hygrometricus", + "anemonella_thalictroides", + "chop_suey_greens", + "lima_bean", + "campanula_pyramidalis", + "sweet_corn", + "calamus_oil", + "pteridium_aquilinum", + "waldmeister", + "polygala_lutea", + "begonia_cheimantha", + "aglaonema_modestum", + "nightshade", + "maianthemum_canadense", + "cinnamomum_cassia", + "panicum_capillare", + "scarlet_runner", + "lathyrus_splendens", + "erysimum_arkansanum", + "papaver_californicum", + "smilax_aspera", + "begonia_socotrana", + "salvia_sclarea", + "scaly_lentinus", + "larix_russica", + "sterculia_acerifolia", + "aristolochia_clematitis", + "allium_ampeloprasum", + "catharanthus_roseus", + "christ's_thorn", + "crataegus_mollis", + "mirabilis_longiflora", + "ageratum_houstonianum", + "agropyron_trachycaulum", + "corticium_salmonicolor", + "cephalanthera_rubra", + "tellima_affinis", + "vangueria_madagascariensis", + "cypripedium_calceolus", + "mountain_heath", + "abies_bracteata", + "cyrtomium_aculeatum", + "viola_odorata", + "virginia_snakeroot", + "poa_nemoralis", + "aster_turbinellis", + "antheropeas_wallacei", + "corylus_cornuta", + "bladder_cherry", + "toxicodendron_radicans", + "lingonberry", + "western_blackberry", + "solidago_spathulata", + "amaranthus_albus", + "robin's_plantain", + "habenaria_chlorantha", + "saxegothea", + "iris_florentina", + "sorrel", + "iris_virginica", + "lotus_tetragonolobus", + "arctostaphylos_uva_ursi", + "hieracium_aurantiacum", + "big_sagebrush", + "leucothoe_racemosa", + "dandelion_green", + "prosopis_pubescens", + "falcatifolium_falciforme", + "beetroot", + "chrysanthemum", + "polypodium_polypodioides", + "linaria_canadensis", + "russian_thistle", + "agrimonia", + "myrica_gale", + "allium_scorodoprasum", + "white_stringybark", + "vallisneria", + "holcus_mollis", + "crambe_maritima", + "helichrysum_secundiflorum", + "erythrina_variegata", + "solanum_melanocerasum", + "platanthera_chlorantha", + "rosa_banksiae", + "acer_glabrum", + "rubus_canadensis", + "epipactis_gigantea", + "euphorbia_milii", + "taxus_floridana", + "begonia_tuberhybrida", + "spraguea_umbellatum", + "rubus_occidentalis", + "castilleja_sulphurea", + "calochortus_macrocarpus", + "thrinax_parviflora", + "ringworm_bush", + "be_careful", + "alder", + "paradisea_liliastrum", + "genus_urtica", + "euphorbia_marginata", + "lamb's_quarters", + "asplenium_montanum", + "mazzard", + "hakea_laurina", + "castanea", + "hygrophorus_kauffmanii", + "passiflora_mollissima", + "arundinaria_tecta", + "rudbeckia_hirta", + "callirhoe_triangulata", + "para_rubber_tree", + "brem", + "phyllostachys_bambusoides", + "solanum_commersonii", + "beaumontia_grandiflora", + "hygrophorus_turundus", + "bletia_striata", + "platanus_acerifolia", + "physalis_peruviana", + "scleroderma_flavidium", + "parthenium_integrifolium", + "evergreen_blueberry", + "chestnut", + "sambucus_ebulus", + "rubus_odoratus", + "floppydock", + "jerusalem_artichoke", + "agropyron_pauciflorum", + "hamamelis_virginiana", + "arctostaphylos_tomentosa", + "quercus_virginiana", + "allgood", + "platanthera_leucophea", + "sarcocephalus_latifolius", + "gossypium_thurberi", + "clematis_verticillaris", + "calystegia_sepium", + "cassava", + "podocarpus_latifolius", + "wolffiella_gladiata", + "dicksonia_antarctica", + "muscari_neglectum", + "red_currant", + "baccharis_pilularis", + "paper_spurge", + "penstemon_fruticosus", + "cherokee_rose", + "magnolia", + "dryopteris_thelypteris", + "solanum_wrightii", + "black_willow", + "eucalyptus_regnans", + "marsh_marigold", + "galium_boreale", + "fireweed", + "leucothoe_editorum", + "centaurea_gymnocarpa", + "passiflora_foetida", + "pinewood", + "ulmus_hollandica", + "nyssa_sylvatica", + "cassia_marilandica", + "nephrolepis_exaltata", + "polyporus_frondosus", + "asclepias_meadii", + "gerardia_pedicularia", + "pterocarpus_macrocarpus", + "cowberry", + "cherimoya", + "quercus_texana", + "coleus_amboinicus", + "diplopterygium_longissimum", + "gyromitra_brunnea", + "phellodendron_amurense", + "hevea_brasiliensis", + "nolina_microcarpa", + "cordyline_australis", + "ranunculus_aquatilis", + "avena_barbata", + "polypodium_vulgare", + "oligoporus_leucospongia", + "bromus_secalinus", + "anemone_occidentalis", + "pinus_palustris", + "virginia_strawberry", + "conium_maculatum", + "plantago_media", + "plumeria_acutifolia", + "astroloma_humifusum", + "wild_hollyhock", + "asplenium_scolopendrium", + "mahonia_nervosa", + "erythrina_corallodendrum", + "oenanthe_crocata", + "downy_birch", + "lotus_berthelotii", + "artemisia_maritima", + "ranunculus_acris", + "cirsium_arvense", + "centaurea_imperialis", + "cypripedium_reginae", + "gray_willow", + "alpinia_officinarum", + "juneberry_holly", + "abronia_villosa", + "andromeda_polifolia", + "canada_violet", + "teucrium_canadense", + "spurge", + "pinus_echinata", + "malacothamnus_fasciculatus", + "verbascum_lychnitis", + "silver_fern", + "quercus_borealis", + "betula_papyrifera", + "phyllostachys_aurea", + "rosa_damascena", + "pterocarpus_angolensis", + "aegilops_triuncalis", + "platanthera_bifolia", + "bulbous_plant", + "scirpus_acutus", + "anchusa_capensis", + "salix_pyrifolia", + "camellia_japonica", + "nothofagus_truncata", + "anthericum_torreyi", + "calamagrostic_quadriseta", + "solanum_quitoense", + "eastern_hemlock", + "tritoma", + "centaurium_scilloides", + "hibiscus_moschatus", + "podocarpus_nivalis", + "stylophorum_diphyllum" + ], + "PRODUCT": [ + "no_limits", + "magnetic_stripe", + "st_vincent", + "south_walian", + "castle_walls", + "deja_vu", + "justin_bieber", + "new_zealand", + "nickel_plate", + "fyodor_dostoyevsky", + "morn", + "medical_school", + "philosopher's_stone", + "esp\u00edrito_santo", + "in_higher_place", + "take_off", + "end_of_world", + "saint_mary", + "al_jazeera", + "four_seasons", + "john_lackland", + "human_rights", + "water_mill", + "caesarean_section", + "o_ring", + "diego_garcia", + "tutti_frutti", + "south_west", + "la_salle", + "dolly_varden", + "echinopsis_pachanoi", + "saxony_anhalt", + "cape_horn", + "stepping_stones", + "double_headed", + "jumping_jack", + "la_fl\u00e8che", + "in_memoriam", + "new_edition", + "sea_monkeys", + "ai_cham", + "doll's_house", + "ga_ga", + "s_train", + "la_forza_del_destino", + "julius_caesar", + "astronomical_clock", + "saint_vincent", + "off_road", + "by_grace_of_god", + "tile_cutter", + "forget_me_not", + "tai_pan", + "st_john_baptist", + "c_net", + "ghettoblaster", + "mary_magdalene", + "in_nick_of_time", + "san_diegan", + "don_quixote", + "monte_cristo", + "as_you_wish", + "mau_mau", + "holy_spirit", + "d_subminiature", + "noah's_ark", + "colour_tube", + "silver_wedding_anniversary", + "die_hard", + "all_saints", + "three_rivers", + "city_hall", + "konstantin_stanislavsky", + "after_burner", + "s\u00e3o_tom\u00e9_and_pr\u00edncipe", + "three_dimensional", + "me_too", + "boxing_day", + "dead_end", + "father_christmas", + "la_dolce_vita", + "deutsche_welle", + "all_right", + "job's_tears", + "gong", + "st_mary_magdalene", + "mount_st_helens", + "there_is_rub", + "town_hall", + "floral_decoration", + "new_testament", + "north_rhine_westphalia", + "saint_nicholas", + "what_happened", + "three_sisters", + "ferdinand_magellan", + "sierra_blanca", + "emperor_huizong", + "myosotis_scorpiodes", + "mario_andretti", + "mary_jane", + "off_limits", + "san_sebastian", + "halfpipe", + "st_george's", + "u_boat", + "as_if", + "lang_lang", + "santa_catarina", + "de_facto", + "st_george_s", + "has_been", + "what_if", + "nordrhein_westfalen", + "will_o_wisp", + "seven_sisters", + "cape_verdean", + "three_kingdoms", + "david_beckham", + "in_between", + "saint_peter", + "heinrich_heine", + "scarlet_tanager", + "novo_mesto", + "s\u00e3o_paulo" + ], + "PUBLIC_FIGURE": [ + "lawrence_durrell", + "la_tour", + "henry_cavendish", + "matthew_arnold", + "harding", + "maria_montesorri", + "lambert", + "burbage", + "forester", + "lev_ivanov", + "st_david", + "goldmark", + "freemason", + "guggenheim", + "styron", + "mccormick", + "streisand", + "benjamin_franklin", + "maitland", + "martin_buber", + "john_bartlett", + "e_b_white", + "longfellow", + "gropius", + "karl_gjellerup", + "sullivan", + "akira_kurosawa", + "frances_wright", + "mayer", + "niccolo_paganini", + "on_lower_floor", + "yastrzemski", + "carnegie", + "maria_tallchief", + "curtis", + "noah_webster", + "jean_genet", + "von_rundstedt", + "tradescant", + "dinesen", + "john_knox", + "heinrich_hertz", + "kesey", + "mauriac", + "waldheim", + "jean_laffite", + "roger_williams", + "lovelace", + "henry_i", + "livingstone", + "le_duc_tho", + "giovanni_boccaccio", + "obsessively", + "saint_maarten", + "cornelius_vanderbilt", + "ekman", + "huntington", + "wren", + "rudolf_steiner", + "klinefelter", + "thomas_wolfe", + "eccles", + "cuvier", + "david_rittenhouse", + "ernesto_guevara", + "o'casey", + "thomas_bayes", + "tindale", + "gjellerup", + "ben_hogan", + "joliot", + "ziegfeld", + "johann_bernoulli", + "charles_great", + "max_bruch", + "mays", + "winckelmann", + "leonard_bernstein", + "c_k_ogden", + "sibelius", + "weill", + "thomas_decker", + "van_allen", + "alistair_cooke", + "che_guevara", + "roget", + "malevich", + "charles_townes", + "ederle", + "kline", + "georges_simenon", + "sir_john_frederick_william_herschel", + "james_barrie", + "c", + "botticelli", + "david_grun", + "mccauley", + "van_beethoven", + "salinger", + "karl_scheele", + "alan_seeger", + "gillespie", + "medawar", + "shostakovich", + "wickliffe", + "ren\u00e9_descartes", + "john_endecott", + "thomas_hodgkin", + "wright", + "dos_passos", + "belloc", + "fleming", + "bearded_mountaineer", + "andrews", + "john_barth", + "edward_albee", + "chess_master", + "bruegel", + "dorothy_parker", + "lipchitz", + "armstrong", + "zhukov", + "bonney", + "francis_ferdinand", + "maria_callas", + "victor_herbert", + "black_marketeer", + "de_sica", + "william_walton", + "leary", + "henrik_ibsen", + "rushdie", + "abelard", + "winslow", + "prospero_lambertini", + "morgan", + "antonio_ghislieri", + "rabelais", + "emerson", + "hendrix", + "frobisher", + "laffer", + "yardbird_parker", + "william_gladstone", + "charles_liston", + "stoppard", + "de_valera", + "hughes", + "mary_shelley", + "franz_werfel", + "quine", + "marcello_malpighi", + "peter_lorre", + "karl_baedeker", + "william_tindale", + "asa_yoelson", + "mergenthaler", + "cellini", + "beckett", + "watteau", + "david_livingstone", + "eduard_buchner", + "david_smith", + "pierre_terrail", + "michelson", + "bruckner", + "john_herschel", + "henry_villard", + "gauss", + "johannes_van_der_waals", + "andrzej_wajda", + "meyerhof", + "jan_van_eyck", + "hoffman", + "rossini", + "carl_rogers", + "macgregor", + "bernhardt", + "cortez", + "george_balanchine", + "i_richards", + "bethe", + "georg_wilhelm_steller", + "richard_burton", + "gerbert", + "douglas_macarthur", + "hawkins", + "james_michener", + "mary_wollstonecraft", + "brunelleschi", + "j_edgar_hoover", + "herschel", + "curtiss", + "thomas_reid", + "dukas", + "john_jacob_astor", + "otto_frisch", + "anna_pavlova", + "winston_churchill", + "allen_stewart_konigsberg", + "gustav", + "johannes_diderik_van_der_waals", + "waite", + "giambattista_marini", + "mendelssohn", + "robert_macgregor", + "gustavus_v", + "b", + "maillol", + "conrad_aiken", + "emile_gaboriau", + "on_par", + "karl_landsteiner", + "josephus", + "monnet", + "ivan_pavlov", + "didrikson", + "dmitri_shostakovich", + "paul_mccartney", + "snead", + "sinclair", + "alfredo", + "ulanova", + "richard_smalley", + "yamani", + "waugh", + "andrew_marvell", + "terry_pratchett", + "vermeer", + "k", + "trevino", + "clausewitz", + "otto_great", + "francois_rabelais", + "macdowell", + "woodward", + "stephen_king", + "francis_crick", + "roebling", + "john_trumbull", + "sherry", + "van_gogh", + "joseph_greenberg", + "de_sade", + "chirico", + "miles_standish", + "de_gaulle", + "isaac_newton", + "sherman", + "richard_upjohn", + "michener", + "m_j_schleiden", + "woolf", + "alfred_eisenstaedt", + "depardieu", + "victor_hugo", + "delius", + "joseph_smith", + "bartholdi", + "edwin_hubble", + "senefelder", + "saint_bridget", + "colette", + "malebranche", + "milton_friedman", + "al_hasan_ibn_al_haytham", + "inge", + "john_rock", + "amy_lowell", + "benton", + "edward_gibbon", + "schoolcraft", + "schiaparelli", + "thomas_doubting_apostle", + "mary_stuart", + "van_de_velde", + "james_usher", + "pincus", + "j_c_maxwell", + "jefferson_davis", + "arafat", + "bertillon", + "saint_louis", + "holbein", + "cass_gilbert", + "giosue_carducci", + "george_stephenson", + "watson", + "osborne", + "john_glenn", + "beauvoir", + "john_webster", + "wykeham", + "john_davis", + "lorenz_okenfuss", + "george_burns", + "jarrell", + "bakunin", + "bartlett", + "george_harrison", + "stowe", + "erwin_schrodinger", + "peter_minuit", + "galois", + "mark_clark", + "sandor_kellner", + "sebastian_vizcaino", + "amundsen", + "george_orwell", + "ellison", + "chimney_sweep", + "morrison", + "woolworth", + "black_horehound", + "georg_meissner", + "aleksandr_pavlovich", + "arthur_koestler", + "hernan_cortes", + "richard_wagner", + "cat_valium", + "joseph_john_thomson", + "williams", + "stanislavsky", + "moshe", + "thornton_wilder", + "e_l_doctorow", + "der_fuhrer", + "pancho_villa", + "diaz", + "o'flaherty", + "monet", + "aleksandr_borodin", + "j_j_hill", + "johns", + "john_hemminge", + "leopold_stokowski", + "higginson", + "jonson", + "rebecca_west", + "stockton", + "mary_magdalen", + "marie_curie", + "mount_wilson", + "malthus", + "simenon", + "francis_galton", + "jussieu", + "john_rowlands", + "mccarthy", + "tandy", + "mary_martin", + "gordimer", + "arnold_schonberg", + "constantine", + "michael_jackson", + "george_iv", + "nicolson", + "louis_jolliet", + "carl_sandburg", + "pugin", + "alexander_i", + "taylor", + "stephenson", + "thomas_hobbes", + "goldman", + "sir_william_chambers", + "faberge", + "seleucus", + "charles_gounod", + "joseph_lister", + "derain", + "edward_weston", + "meissner", + "el_greco", + "macleod", + "philip_ii_of_spain", + "waller", + "samuel_beckett", + "seaman", + "maximian", + "jacques_costeau", + "clinton", + "connolly", + "david", + "russell", + "galileo_galilei", + "skeat", + "van_eyck", + "repp", + "czerny", + "ernest_bevin", + "jane_goodall", + "john_donne", + "chaim_weizmann", + "lardner", + "andrea_guarneri", + "robert_koch", + "wajda", + "van_vleck", + "burbank", + "i_m_pei", + "marshall", + "todd", + "joseph_goebbels", + "george_eastman", + "john_steinbeck", + "asimov", + "radiologic_technologist", + "epstein", + "erich_mendelsohn", + "utrillo", + "catherine", + "northrop", + "saint_peter_apostle", + "mantegna", + "donald_glaser", + "barth", + "strickland", + "demille", + "langmuir", + "mendeleyev", + "c_northcote_parkinson", + "edmund_hillary", + "munchausen", + "brigid", + "binet", + "trevithick", + "galvani", + "corbett", + "vincent_van_gogh", + "richard_hooker", + "strasberg", + "w", + "william_hazlitt", + "gustavus_iii", + "prince_eugene_of_savoy", + "pickford", + "marie_stopes", + "anne_boleyn", + "has_been", + "john_ruskin", + "franz_lehar", + "granville_barker", + "louis_le_begue", + "robert_burns", + "john_henry", + "inca_empire", + "hans_albrecht_bethe", + "carl_anderson", + "nathaniel_bailey", + "behrens", + "steinbeck", + "visconti", + "bunche", + "john_galbraith", + "hess", + "thomas_paine", + "bari", + "ustinov", + "murrow", + "elizabeth_seaman", + "sully", + "liliuokalani", + "gielgud", + "francis_beaumont", + "hans_jurgen_eysenck", + "alhacen", + "i_f_stone", + "marini", + "justinian", + "be_responsible_for", + "karl_wernicke", + "bergman", + "math_teacher", + "wilkins", + "steven_weinberg", + "p", + "mary_pickford", + "hans_fischer", + "be_in_charge_of", + "emiliano_zapata", + "boulez", + "lavoisier", + "cristobal_colon", + "karl_barth", + "dowland", + "yuri_gagarin", + "millais", + "calvino", + "willem_einthoven", + "johann_winckelmann", + "rockwell", + "cather", + "sikorsky", + "phil_anderson", + "thomas_willis", + "bernard_malamud", + "samuel_johnson", + "jesus", + "giovanni_battista_montini", + "allen_iverson", + "nimitz", + "wesley", + "smith", + "marie_antoinette", + "anne_hutchinson", + "louise_nevelson", + "giuseppe_verdi", + "galsworthy", + "walter_lippmann", + "edward_appleton", + "breuer", + "e", + "scheele", + "lafitte", + "karl_jaspers", + "korzybski", + "emily_bronte", + "beethoven", + "helmholtz", + "ferber", + "hideki_yukawa", + "connors", + "konrad_adenauer", + "st_george", + "grigori_potemkin", + "mencken", + "bessel", + "howe", + "vanderbilt", + "c_vann_woodward", + "donatus", + "john_l_lewis", + "bush", + "marianne_moore", + "norbert_wiener", + "st_vitus", + "john_masefield", + "horatio_nelson", + "mark_rothko", + "shepard", + "brueghel", + "maurice_chevalier", + "gottlieb_daimler", + "fourier", + "francoise_athenais_de_rochechouart", + "saint_ignatius", + "schlesinger", + "finnbogadottir", + "scriabin", + "mayakovski", + "frank_sinatra", + "isherwood", + "edward_martyr", + "bowditch", + "fallopio", + "arendt", + "abel_tasman", + "katharine_hepburn", + "noguchi", + "guthrie", + "henri_becquerel", + "henri_matisse", + "alfonso_borgia", + "pahlevi", + "bertram_brockhouse", + "ginsberg", + "louis_pasteur", + "van_de_graaff", + "ponselle", + "hoffmann", + "gaboriau", + "berra", + "sherrington", + "j", + "richard_strauss", + "stephen_decatur", + "herculius", + "galbraith", + "leslie_howard", + "jean_baptiste_racine", + "mehemet_ali", + "theodosius_i", + "joseph_oliver", + "hugo_grotius", + "pushkin", + "maginot", + "kissinger", + "mahalia_jackson", + "william_franklin_graham", + "kendrew", + "ben_shahn", + "mohorovicic", + "john_ford", + "stephen_foster", + "alphonse_bertillon", + "laurence", + "charles_ringling", + "katherine_mansfield", + "gertrude_stein", + "fallopius", + "van_der_waals", + "j_b_s_haldane", + "saladin", + "kettering", + "sarah_bernhardt", + "george_beadle", + "white_friar", + "dostoevski", + "krasner", + "e_h_harriman", + "v", + "hayes", + "philip_marlowe", + "greene", + "gretzky", + "luigi_pirandello", + "peter_tchaikovsky", + "t_s_eliot", + "shapley", + "e_g_marshall", + "watts", + "madame_tussaud", + "karol_wojtyla", + "mallarme", + "marc_blitzstein", + "hank_williams", + "hazlitt", + "weston", + "benchley", + "mandelshtam", + "rube_goldberg", + "dorothea_lange", + "james_thurber", + "st_christopher", + "william_menninger", + "strachey", + "chaplin", + "charles_de_gaulle", + "paul_von_hindenburg", + "da_gamma", + "ilk", + "florio", + "y", + "nikolai_gogol", + "henry_moore", + "perutz", + "schumann", + "holden", + "mary_mallon", + "i_translations", + "lytton", + "ralph_bunche", + "rudolf_bultmann", + "dempsey", + "douglass", + "charles_lindbergh", + "fremont", + "clive", + "grappelli", + "erythrina", + "jespersen", + "villon", + "emile_herzog", + "vincenzo_bellini", + "samuel_barber", + "tobias_smollett", + "joseph_stalin", + "schrodinger", + "hammarskjold", + "al_haytham", + "f", + "john_jay", + "tobey", + "ludwig_wittgenstein", + "august_strindberg", + "stalin", + "bunyan", + "thomas_mann", + "bernard_montgomery", + "paton", + "hathaway", + "kendall", + "bin_laden", + "alla_nazimova", + "charles_goodyear", + "dante_alighieri", + "hoyle", + "wernicke", + "cunningham", + "charles", + "vesalius", + "robert_lee", + "margot_fonteyn", + "nathaniel_currier", + "david_hubel", + "peter_pan", + "james_tobin", + "john_irving", + "panofsky", + "simon_peter", + "samuel_de_champlain", + "copper_sulfate", + "shirer", + "paxton", + "davit", + "chekhov", + "e_h_weber", + "giacomo_puccini", + "edward_fitzgerald", + "eyck", + "fridtjof_nansen", + "louis_braille", + "herbert_marcuse", + "mungo_park", + "benedict_arnold", + "wyatt", + "paul_verlaine", + "cowper", + "q", + "scribes", + "edward_confessor", + "tappan", + "robert_johnson", + "kropotkin", + "niccol\u00f2_paganini", + "mark_hopkins", + "hearing_examiner", + "traubel", + "mount_sherman", + "balfour", + "james_dean", + "robert", + "richard_lovelace", + "jacob_harmensen", + "scorsese", + "leuwenhoek", + "mason", + "marie_tussaud", + "burnett", + "roger_bannister", + "john_cash", + "theodor_schwann", + "max_beerbohm", + "tasman", + "greeley", + "alessandro_manzoni", + "joseph_priestley", + "hermann_snellen", + "robert_oppenheimer", + "hal", + "louis_joliet", + "nicolas_poussin", + "andrea_mantegna", + "qadhafi", + "from_scratch", + "adolf_windaus", + "francois_mansart", + "hayek", + "clemenceau", + "joseph_pulitzer", + "ring_lardner", + "sperry", + "george_huntington", + "charles_schulz", + "irving", + "barany", + "caruso", + "jim_corbett", + "mommsen", + "james_naismith", + "marlowe", + "malpighi", + "oscar_wilde", + "socinus", + "montgolfier", + "mobius", + "antoine_domino", + "de_l_orme", + "philip_roth", + "maintenon", + "burroughs", + "j_d_salinger", + "ochoa", + "henry", + "lawrence", + "roy_wilkins", + "franklin", + "andre_weil", + "sorensen", + "jules_massenet", + "humperdinck", + "richard_trevithick", + "lowry", + "william_bradford", + "johan_august_strindberg", + "heinrich_schliemann", + "montespan", + "liston", + "kean", + "lendl", + "louis_stammerer", + "bartholomeu_diaz", + "john_davys", + "carlyle", + "eli_whitney", + "nell_gwynn", + "ivan_terrible", + "jackson", + "glenn_curtiss", + "telemann", + "paola_caliari", + "saint_crispin", + "clark", + "pizarro", + "morley", + "benedick", + "merckx", + "bradstreet", + "romberg", + "corelli", + "jan_van_der_meer", + "chambers", + "mary_magdalene", + "john_witherspoon", + "william_falkner", + "laurence_olivier", + "victor_hess", + "hussein", + "jeffers", + "evans", + "cocteau", + "pierre_larousse", + "norris", + "christiaan_eijkman", + "adolf_eichmann", + "sverdrup", + "kaiser_wilhelm", + "heyward", + "paganini", + "marilyn_horne", + "boole", + "ibsen", + "lorca", + "nell_gwynne", + "marvell", + "stan_musial", + "rimbaud", + "francis_bacon", + "compton", + "pete_seeger", + "richard_m_nixon", + "walter_hess", + "john_wycliffe", + "gaskell", + "husayn", + "joseph_heller", + "lessing", + "a", + "boone", + "francois_jacob", + "heyerdahl", + "peary", + "gustavus_i", + "gershwin", + "rossetti", + "morris", + "peter_carl_goldmark", + "apollinaire", + "hassam", + "trotsky", + "montagu", + "norman_rockwell", + "boris_spassky", + "khadafy", + "francois_duvalier", + "james_brown", + "william_hogarth", + "kachaturian", + "modigliani", + "charles_baudelaire", + "luigi_cherubini", + "sir_william_rowan_hamilton", + "cassia_alata", + "francis_joseph", + "deere", + "david_ricardo", + "barkley", + "john_mitchell", + "henri_labrouste", + "mary_leakey", + "charlie_parker", + "z", + "immanuel_kant", + "jacques_bernoulli", + "goodall", + "kinsey", + "himmler", + "beaverbrook", + "james_franck", + "william_crookes", + "antonius_stradivarius", + "james_meredith", + "samuel_gompers", + "nellie_bly", + "brancusi", + "john_haldane", + "weber", + "lewis", + "warburg", + "fulton", + "parsons", + "alexandre_yersin", + "francois_mitterrand", + "octavius", + "n", + "richardson", + "michel_montaigne", + "tunney", + "stephen_leacock", + "hope", + "albert_schweitzer", + "miller", + "flavius_theodosius", + "chagall", + "john_mccormick", + "john_harvard", + "lower_ranking", + "johann_friedrich_herbart", + "giulio_natta", + "hardy", + "erik_weisz", + "musset", + "guarnieri", + "dewey", + "subnormal", + "canetti", + "saint_martin", + "titus", + "johannes_kepler", + "anatoli_karpov", + "sergei_rachmaninov", + "metchnikov", + "william_s_burroughs", + "most", + "david_hartley", + "max_planck", + "dostoyevsky", + "charles_bald", + "william_blake", + "t_e_lawrence", + "rundstedt", + "julio_iglesias", + "john_bardeen", + "rodin", + "arthur", + "hutchins", + "middleton", + "sarah_vaughan", + "nietzsche", + "dubya", + "john_wilkes", + "francois_mauriac", + "davis", + "konstantin_stanislavsky", + "thoreau", + "william_byrd", + "william_henry", + "christopher_fry", + "godard", + "scott_joplin", + "latrobe", + "samuel_houston", + "supermex", + "carl_lewis", + "sarah_siddons", + "george_vancouver", + "hinault", + "o'neill", + "gardner", + "president_wilson", + "vuillard", + "thackeray", + "cesar_franck", + "samuel_rosenstock", + "canberra", + "stephane_mallarme", + "cooke", + "carry_nation", + "bramante", + "goethals", + "knox", + "elias_canetti", + "norrish", + "von_braun", + "robert_lowell", + "johann_strauss", + "bohme", + "eisenstein", + "edward_jenner", + "hutton", + "john_mercer", + "oscar_robertson", + "marquand", + "huston", + "take_turns", + "oliver_hardy", + "louis_quarreller", + "kenyata", + "moore", + "johan_kepler", + "husserl", + "groves", + "cole_porter", + "samuel_wilder", + "benjamin_west", + "jean_luc_godard", + "stokowski", + "graham_greene", + "baryshnikov", + "frans_hals", + "edward", + "lysenko", + "medic", + "stroheim", + "whistler", + "la_fontaine", + "lars_onsager", + "willard", + "jewison", + "cardinal_bellarmine", + "margaret_mitchell", + "goldoni", + "konoye", + "leadbelly", + "bunuel", + "igor_stravinsky", + "duse", + "j_b_rhine", + "stuart_davis", + "henri", + "olmsted", + "gary_weinstein", + "mary_mccauley", + "lola_montez", + "tucker", + "john_wain", + "jan_swammerdam", + "bellini", + "mary_mccarthy", + "jimenez", + "wilkes", + "tully", + "david_riesman", + "laughton", + "doctorow", + "john_walker", + "mythical_monster", + "dvorak", + "virchow", + "flavius_josephus", + "william_herschel", + "wheatley", + "joseph_black", + "marcus_whitman", + "mikhail_baryshnikov", + "du_barry", + "montesquieu", + "oakley", + "william_john_clifton_haley_jr", + "marcus_aurelius_valerius_maximianus", + "franz_joseph", + "peirce", + "arthur_rubinstein", + "calvin", + "cherubini", + "arthur_compton", + "koussevitzky", + "lindbergh", + "robbins", + "niels_bohr", + "sergei_rachmaninoff", + "kenneth_grahame", + "naismith", + "larousse", + "hickock", + "sheridan", + "bardeen", + "henry_fielding", + "bertrand_russell", + "fragonard", + "jakob_hermandszoon", + "katherine_anne_porter", + "madame_curie", + "hawkyns", + "michael_faraday", + "john_d_rockefeller", + "malamud", + "j_craig_ventner", + "arthur_schlesinger", + "dionysius_elder", + "burt", + "anthony_burgess", + "anthony", + "take_bladders_for_lanterns", + "cummings", + "jan_tinbergen", + "swanson", + "peter_mark_roget", + "lake_tana", + "robert_venturi", + "johnny_appleseed", + "greg", + "schumpeter", + "schliemann", + "o'keeffe", + "gregory", + "ben_gurion", + "kreisler", + "maurois", + "sir_francis_galton", + "ellen_price_wood", + "ralegh", + "irving_berlin", + "wavell", + "peter_seamus_o'toole", + "marstan", + "otho_of_lagery", + "gauguin", + "malory", + "bernard_baruch", + "rudolf_diesel", + "hans_holbein", + "walt_disney", + "meredith", + "ben_jonson", + "peter", + "lippi", + "la_spezia", + "czar_peter_i", + "robert_benchley", + "dowding", + "oates", + "albee", + "e_t_hoffmann", + "florey", + "h_l_mencken", + "lully", + "munchhausen", + "vesey", + "aleksandr_prokhorov", + "rubens", + "black_quarter", + "ondaatje", + "percy", + "joseph_schumpeter", + "beveridge", + "max_muller", + "gabriel_lippmann", + "steve_reich", + "groucho", + "adenauer", + "lee", + "derrida", + "lamarck", + "benny_goodman", + "ted_williams", + "karl_menninger", + "william_beaumont", + "froebel", + "friedrich_engels", + "huldreich_zwingli", + "haley", + "pavlov", + "steichen", + "jane_austen", + "anthony_vandyke", + "charles_laughton", + "parker", + "eichmann", + "magritte", + "gibson", + "moses", + "ventner", + "gustav_mahler", + "ed_sullivan", + "phil_collins", + "nevelson", + "alice_paul", + "erving", + "robert_redford", + "robert_barany", + "monod", + "jean_giraudoux", + "fuller", + "jack_dempsey", + "brindisi", + "ian_fleming", + "swedenborg", + "richard_feynman", + "harrod", + "menninger", + "willebrand", + "kandinski", + "wolfgang_pauli", + "wycherley", + "ellington", + "landowska", + "ruskin", + "wollaston", + "lipmann", + "dodgson", + "theodore_dreiser", + "theodor_mommsen", + "andrew_huxley", + "schoenberg", + "marcel_proust", + "klimt", + "jessica_mitford", + "thomas_more", + "jesse_louis_jackson", + "homo_heidelbergensis", + "milhaud", + "paul_hindemith", + "elizabeth_taylor", + "thomas_chippendale", + "meyerbeer", + "lunt", + "anne_sullivan", + "walesa", + "feodor_dostoevski", + "paul_robeson", + "william_conqueror", + "arnold", + "benedict", + "anton_chekov", + "shute", + "thomas_middleton", + "metchnikoff", + "lugosi", + "gladstone", + "nell_gywn", + "john_dowland", + "sumner", + "le_carre", + "van_dyck", + "peter_great", + "sarnoff", + "zaharias", + "millay", + "daniel_jones", + "hellman", + "benjamin_jonson", + "william_golding", + "robert_motherwell", + "william_caxton", + "john_milton", + "c_h_best", + "karl_wilhelm_scheele", + "rudolf_serkin", + "couperin", + "siqueiros", + "peter_stuyvesant", + "rattigan", + "henri_louis_bergson", + "ethel_merman", + "szilard", + "rittenhouse", + "riesman", + "frank_baum", + "hotspur", + "samuel_adams", + "albert_speer", + "james_baldwin", + "frederick_william", + "lindsay", + "o_hara", + "john_copley", + "john_vanbrugh", + "gracie", + "cavell", + "leacock", + "indira_gandhi", + "daumier", + "whitman", + "millikan", + "davys", + "william_mitchell", + "albers", + "bertolucci", + "jane_seymour", + "peter_goldmark", + "peter_minnewit", + "klopstock", + "rehnquist", + "george_gershwin", + "toynbee", + "schopenhauer", + "alberto_giacometti", + "laney", + "wallace", + "frank_whittle", + "alfred_nobel", + "jesse_owens", + "eisenstaedt", + "tenniel", + "daniel_rutherford", + "ashe", + "marco_polo", + "koestler", + "john_fletcher", + "heidegger", + "georgi_zhukov", + "caravaggio", + "matthias_schleiden", + "beria", + "lorenzo_de'medici", + "charlie_watts", + "albert_gore_jr", + "moussorgsky", + "spenser", + "m", + "charlotte_corday", + "jamison", + "hargreaves", + "marcel_marceau", + "gilmer", + "oort", + "allen_ginsberg", + "fred_zinnemann", + "ringling", + "hammerstein", + "coleridge", + "daniel_bernoulli", + "kelly", + "guillaume_apollinaire", + "william_strickland", + "gibbs", + "john_marquand", + "l_s_lowry", + "brandt", + "pablo_casals", + "joseph_henry", + "juan_ponce_de_leon", + "henri_bergson", + "st_brigid", + "speke", + "craigie", + "bergson", + "antonius", + "jean_bernoulli", + "edward_macdowell", + "josef_hoffmann", + "johnny_raw", + "hammett", + "prokhorov", + "boris_karloff", + "sveti_nikole", + "pierre_corneille", + "phillis_wheatley", + "tussaud", + "oppenheimer", + "mohammed_reza_pahlavi", + "condorcet", + "patrick_white", + "hans_zinsser", + "saul_steinberg", + "boehm", + "greenberg", + "bartholomew_roberts", + "eileen_farrell", + "catherine_howard", + "little_leaguer", + "daniel_morgan", + "hans_christian_andersen", + "peter_cooper", + "reich", + "schwann", + "william_morris", + "anton_van_leeuwenhoek", + "william_dawes", + "cary_grant", + "hideyo_noguchi", + "thomas", + "isaac_watts", + "saint_lawrence", + "harmsworth", + "ford", + "pieter_zeeman", + "arnold_gesell", + "scripps", + "herrick", + "glenn_miller", + "thomas_straussler", + "navratilova", + "sir_thomas_gresham", + "passive_smoking", + "goring", + "steward", + "karl_von_clausewitz", + "gustavus", + "musial", + "c_w_post", + "fitzgerald", + "wegener", + "pablo_picasso", + "newman", + "horne", + "mansart", + "john_philip_marquand", + "marian_anderson", + "natalie_wood", + "l_ron_hubbard", + "national_character", + "tagore", + "raffles", + "james_bernoulli", + "kennelly", + "alan_hodgkin", + "malinowski", + "anderson", + "thomas_moore", + "sergei_vasilievich_rachmaninov", + "geometry_teacher", + "robeson", + "paul_apostle", + "louis_ix", + "osman_i", + "kurt_weill", + "kieslowski", + "otto_hahn", + "webster", + "nast", + "lester_young", + "welty", + "christian_huygens", + "otto_meyerhof", + "john_marshall", + "mamet", + "christiaan_huygens", + "duvalier", + "hector_berlioz", + "smalley", + "lucille_ball", + "paul_simon", + "mussorgsky", + "claudio_monteverdi", + "benjamin_jowett", + "rubinstein", + "nabokov", + "robert_scott", + "stravinsky", + "john_galsworthy", + "knut_pedersen", + "robert_robinson", + "scott", + "ziegler", + "pieter_breughel", + "karloff", + "khachaturian", + "dickinson", + "bronte", + "spielberg", + "gombrowicz", + "o", + "goodman", + "king_james", + "mccartney", + "wallenstein", + "one", + "adam_smith", + "william_james", + "diaghilev", + "joseph_joffre", + "lipscomb", + "taney", + "u", + "vizcaino", + "jean_harlow", + "henry_miller", + "sayers", + "mcguffey", + "karl_marx", + "einthoven", + "paul_bunyan", + "rickover", + "friedrich_nietzsche", + "zsigmondy", + "i", + "strindberg", + "pedro", + "robert_indiana", + "william_burroughs", + "noyes", + "peter_alexander_ustinov", + "jimmy_durante", + "howard", + "john_wesley", + "march_king", + "hasek", + "dorothy_sayers", + "berlage", + "st_maarten", + "tallis", + "e_o_wilson", + "melanchthon", + "goldwyn", + "sandro_botticelli", + "endecott", + "parrish", + "von_willebrand", + "carson_mccullers", + "frank_stockton", + "magna_mater", + "bloch", + "huss", + "seiji_ozawa", + "nazimova", + "ehrenberg", + "proust", + "nikola_tesla", + "de_mille", + "al_capone", + "jim_bowie", + "charles_barkley", + "billy_graham", + "robert_schumann", + "mel_gibson", + "le_corbusier", + "malraux", + "carlo_goldoni", + "trumbo", + "kaufman", + "shankar", + "william_patterson", + "boleyn", + "ninigi", + "leo_delibes", + "john_locke", + "tharp", + "alexis_carrel", + "le_notre", + "du_maurier", + "l_enfant", + "j_e_johnston", + "mitchum", + "symonds", + "king_lear", + "serkin", + "joseph_marie_jacquard", + "antonin_dvorak", + "henry_james", + "stephen_sondheim", + "henson", + "st_martin", + "richards", + "crawford", + "oscar_hammerstein", + "steinway", + "lorenz_hart", + "marie_grosholtz", + "robert_bartlett", + "stewart", + "e_housman", + "horney", + "jakobson", + "bierce", + "hevesy", + "perry", + "helen_keller", + "grotius", + "paul_dukas", + "e_t_s_walton", + "home_help", + "ingrid_bergman", + "saint_david", + "siddons", + "tillich", + "george_ii", + "crosby", + "denmark_vesey", + "hindemith", + "hodgkin", + "leonard_bloomfield", + "congreve", + "jane_jacobs", + "thurber", + "lulli", + "kosciusko", + "verlaine", + "kerensky", + "trevelyan", + "jean_piaget", + "meany", + "soutine", + "sondheim", + "william_congreve", + "franz_kline", + "henri_rousseau", + "paul_tillich", + "hilaire_belloc", + "massine", + "mondrian", + "darrow", + "shakspere", + "brigadier_general", + "jolliet", + "montgomery_ward", + "reichstein", + "de_kooning", + "baudelaire", + "angelo_correr", + "st_denis", + "rogers", + "carducci", + "frank_norris", + "francois_couperin", + "konoe", + "pieter_brueghel", + "peter_ilich_tchaikovsky", + "behring", + "francois_de_la_rochefoucauld", + "frank_stella", + "durrell", + "paige", + "stilwell", + "robert_southey", + "prince_charming", + "valentina_tereshkova", + "eddington", + "one_translations", + "h_g_wells", + "walt_whitman", + "hernando_cortes", + "william_wyler", + "warren", + "john_osborne", + "colin_powell", + "moliere", + "ludwig_boltzmann", + "antoninus", + "tereshkova", + "beerbohm", + "carl_nielsen", + "ciardi", + "karl_gauss", + "chopin", + "weizmann", + "vasarely", + "smollett", + "merton", + "hearst", + "pauling", + "rankin", + "bunsen", + "vaux", + "carl_jung", + "israel_strassberg", + "richard_neville", + "leopold_kronecker", + "goering", + "masefield", + "small_businessman", + "francis_richard_stockton", + "simpson", + "richard_wright", + "heyse", + "benjamin_thompson", + "st_benedict", + "kandinsky", + "adolf_hitler", + "maria_mitchell", + "prokofiev", + "dindymene", + "fritz_haber", + "dekker", + "archibald_macleish", + "fowler", + "richard_starkey", + "peter_behrens", + "john_tradescant", + "nathan_bailey", + "jaspers", + "alfred_stieglitz", + "gabriele_fallopius", + "redford", + "joseph_haydn", + "stephen_spender", + "garfield", + "mendelsohn", + "ballad_singer", + "jones", + "bailey", + "george_boole", + "solvay", + "fyodor_dostoevsky", + "mahan", + "paul_revere", + "philipp_schwarzerd", + "sontag", + "ruth_fulton", + "helen_wills", + "kruger", + "daniel_boone", + "buffalo_bill", + "william_fulbright", + "edvard_grieg", + "radhakrishnan", + "gorgas", + "jacques", + "robert_boyle", + "korchnoi", + "arthur_laffer", + "edith_cavell", + "mitchell", + "alan_paton", + "zinsser", + "deliverer", + "eliot", + "hopkinson", + "verwoerd", + "ralph_richardson", + "prima_donna", + "paderewski", + "lenard", + "1", + "schubert", + "karsavina", + "alberti", + "krzysztof_kieslowski", + "cordell_hull", + "robert_bruce", + "blixen", + "james_wilson", + "rosa_parks", + "tchaikovsky", + "norman_jewison", + "marceau", + "townes", + "tarkovsky", + "crichton", + "riley", + "samuel_goldwyn", + "steller", + "mccullers", + "x", + "elizabeth_seton", + "ernest_walton", + "vladimir_putin", + "jacob", + "orbison", + "crockett", + "giuseppe_mazzini", + "gromyko", + "carolus", + "runyon", + "jim_thorpe", + "woodhull", + "karl_augustus_menninger", + "hertz", + "bradbury", + "h", + "randall_jarrell", + "old_bullion", + "verrazzano", + "richler", + "swammerdam", + "manson", + "sekhet", + "laurence_sterne", + "markov", + "hutchinson", + "jacqueline_cochran", + "george_fox", + "john_lackland", + "graves", + "peter_paul_mauser", + "ben_hecht", + "christopher_isherwood", + "bloomfield", + "fritz_kreisler", + "john_heming", + "copley", + "henry_bolingbroke", + "anne_hathaway", + "david_garrick", + "don_budge", + "meade", + "ozawa", + "bill_russell", + "margaret_court", + "emile_zola", + "berlioz", + "evers", + "owen", + "thomson", + "henry_le_chatelier", + "baldwin", + "gallaudet", + "bomber_harris", + "jeannette_rankin", + "clarence_darrow", + "marya_sklodowska", + "alben_william_barkley", + "dawes", + "agassiz", + "mallon", + "charles_lamb", + "harry", + "g", + "sills", + "william_of_wykeham", + "labrouste", + "albert_michelson", + "dulles", + "cattell", + "king_john", + "nansen", + "vespucci", + "de_niro", + "savonarola", + "brady", + "john_chapman", + "anthony_comstock", + "ellsworth", + "lemaitre", + "jansen", + "arthur_schopenhauer", + "sam_goldwyn", + "thomas_dekker", + "el_caudillo", + "custer", + "harriman", + "james_cagney", + "john_keble", + "johns_hopkins", + "l_m_montgomery", + "henri_pitot", + "wanda_landowska", + "edward_pusey", + "billy_mitchell", + "martin_heidegger", + "hans_eysenck", + "shockley", + "christopher_columbus", + "gaius_flaminius", + "aiken", + "tyson", + "muller", + "arnold_schoenberg", + "r", + "george_lucas", + "andrew_jackson", + "and_so_forth", + "tindal", + "peter_abelard", + "edith_wharton", + "louis_armstrong", + "spallanzani", + "ortega", + "cornell", + "barnum", + "balanchine", + "st_mark", + "pieter_bruegel", + "loeb", + "dubyuh", + "antony_tudor", + "saint_christopher", + "steven_spielberg", + "sir_john_cockcroft", + "gregory_great", + "sydenham", + "bultmann", + "comstock", + "jean_monnet", + "leonard", + "sellers", + "georgiana_barrymore", + "d_w_griffith", + "robert_fulton", + "southern_pig_tailed_macaque", + "goudy", + "thomas_hardy", + "eddie_rickenbacker", + "thomas_gainsborough", + "stefan_wyszynski", + "franz_ferdinand", + "giuseppe_garibaldi", + "small_farmer", + "wister", + "philip_warren_anderson", + "karlfeldt", + "hemminge", + "blitzstein", + "fra_filippo_lippi", + "alexandre_dumas", + "pirandello", + "philipp_melanchthon", + "robert_brown", + "doolittle", + "bethune", + "markoff", + "thomas_carlyle", + "wiesenthal", + "johann_gutenberg", + "roberts", + "shah_pahlavi", + "bragg", + "gagarin", + "allen_tate", + "algren", + "donald_barthelme", + "andre_maurois", + "alphonse_capone", + "william_tyndale", + "tamara_karsavina", + "ibert", + "bobby_fischer", + "crookes", + "din_land", + "menotti", + "johannes_gutenberg", + "svedberg", + "thornton", + "kaunda", + "barrymore", + "d", + "hooke", + "breughel", + "james_bowie", + "thomas_malthus", + "giambattista_marino", + "gaetano_donizetti", + "dreiser", + "castro", + "beadle", + "william_faulkner", + "wordsworth", + "cockcroft", + "plath", + "johannes_eckhart", + "edward_white", + "edouard_manet", + "andre", + "titus_flavius_vespasianus", + "simon_de_montfort", + "amerigo_vespucci", + "selznick", + "rachmaninov", + "wilmut", + "arthur_holmes", + "montessori", + "laurentius", + "anouilh", + "pierre_boulez", + "hans_adolf_krebs", + "grahame", + "mcmaster", + "chekov", + "hollerith", + "le_chatelier", + "girolamo_savonarola", + "salk", + "smitty_stevens", + "housman", + "emma_goldman", + "robert_gray", + "blake", + "haywood", + "anna_kournikova", + "francis_poulenc", + "james_ussher", + "wolfe", + "john_barrymore", + "john_constable", + "rachel_louise_carson", + "c_d_gibson", + "huggins", + "james_mill", + "robert_heinlein", + "john_ciardi", + "albino_luciano", + "putin", + "landsteiner", + "gary_kasparov", + "matthew_flinders", + "hanks", + "thomas_crawford", + "chomsky", + "robert_herrick", + "joseph_campbell", + "st_peter", + "grainger", + "zeppo", + "molnar", + "john_m_browning", + "swift", + "klaproth", + "jean_de_la_fontaine", + "robert_hooke", + "davy", + "lovell", + "o_henry", + "hoffa", + "harriet_wilson", + "kekule", + "karl_popper", + "benjamin_kubelsky", + "alfred", + "von_sternberg", + "coleman_hawkins", + "saint_james_apostle", + "kronecker", + "frye", + "untermeyer", + "john_calvin", + "george_sand", + "sousa", + "peter_sellers", + "homo_rhodesiensis", + "steffens", + "charles_fourier", + "john_mcgraw", + "henry_clay", + "toscanini", + "giraudoux", + "marcus_aurelius", + "cousteau", + "bolingbroke", + "e_w_morley", + "peter_o'toole", + "joseph_conrad", + "edmund_halley", + "william_shockley", + "de_spinoza", + "lone_wolf", + "glass_cutter", + "keble", + "kenneth_roberts", + "balenciaga", + "peter_paul_rubens", + "mahatma_gandhi", + "jim_morrison", + "saint_peter", + "cromwell", + "masters", + "jules_verne", + "paul_newman", + "robert_mills", + "george_meredith", + "trollope", + "galton", + "john_marstan", + "menuhin", + "robert_morris", + "kastler", + "carroll", + "hopkins", + "antonio_pignatelli", + "zimbalist", + "eugene_ionesco", + "matisse", + "woody_herman", + "boell", + "charlotte_bronte", + "heaviside", + "gehrig", + "fyodor_dostoyevsky", + "alexander_wilson", + "john_roebling", + "josef_albers", + "jackson_pollock", + "spinoza", + "laffite", + "david_crockett", + "welles", + "dayan", + "steinem", + "lion's_den", + "kasparov", + "john_lennon", + "seton", + "andrea_palladio", + "cornelis_jansen", + "golding", + "john_speke", + "buchner", + "wilson", + "fontanne", + "gandhi", + "heinlein", + "cheever", + "poulenc", + "motherwell", + "bob_woodward", + "charlie_chaplin", + "lillian_russell", + "d_h_lawrence", + "humboldt", + "mcpherson", + "so_much", + "edward_morley", + "barthelme", + "j_m_barrie", + "lippmann", + "hitchings", + "robert_woodward", + "schonberg", + "pavarotti", + "thomas_malory", + "tilden", + "lea", + "john_brown", + "al_jolson", + "elizabeth_gaskell", + "jinnah", + "caldwell", + "john_mill", + "langtry", + "william_of_ockham", + "teasdale", + "hugo_junkers", + "overgrown_gate", + "zinnemann", + "j_r_firth", + "burnham", + "maurice_barrymore", + "haldane", + "piscis_austrinus", + "norman_thomas", + "lillian_hellman", + "e_w_mason", + "brescia", + "brecht", + "peter_carl_faberge", + "carter", + "john_macleod", + "vasco_da_gamma", + "satie", + "tallchief", + "thomas_merton", + "benedetto_odescalchi", + "sennett", + "massenet", + "villard", + "riemann", + "shahn", + "jenny_wren", + "stopes", + "pyotr_tchaikovsky", + "rothko", + "asa_gray", + "donkin", + "bonhoeffer", + "spillane", + "hannah_arendt", + "antonio_stradivari", + "wanamaker", + "c_s_forester", + "philip_anderson", + "kuhn", + "cushing", + "robinson_jeffers", + "farrell", + "and_finally", + "antony", + "eckhart", + "alice_walker", + "priestley", + "d_oyly_carte", + "andrei_sakharov", + "karl_czerny", + "casals", + "sir_james_murray", + "strauss", + "macleish", + "miles_davis", + "edmund_cartwright", + "koopmans", + "rupert", + "mubarak", + "octavian", + "sir_william_walton", + "wollstonecraft", + "pusey", + "bruce", + "butterfield", + "james_parkinson", + "heyrovsky", + "brummell", + "j_m_synge", + "gustave", + "william_augustus", + "qaddafi", + "hurrah", + "oldfield", + "george_marshall", + "von_willebrand_factor", + "onsager", + "cochran", + "eijkman", + "cagney", + "tuchman", + "gesell", + "harold_nicolson", + "jesse_jackson", + "willa_cather", + "ethelred", + "stanley_kubrick", + "mohammed_ali", + "gustavus_adolphus", + "willow_grouse", + "cornelius_jansenius", + "leontief", + "john_deere", + "andre_markoff", + "champollion", + "cronyn", + "keaton", + "john_huston", + "robert_merton", + "carothers", + "ivanov", + "jean_baptiste_joseph_fourier", + "debs", + "william_gilbert", + "rene_magritte", + "kosciuszko", + "mcgraw", + "le_gallienne", + "astaire", + "james_watt", + "jonathan_edwards", + "have_green_fingers", + "ronald_reagan", + "great_grandparent", + "helmut_schmidt", + "jenny_lind", + "leigh", + "homo", + "frederick_douglass", + "tebaldi", + "von_bismarck", + "symons", + "moynihan", + "la_rochefoucauld", + "david_hilbert", + "skinner", + "wilhelm_reich", + "duchamp", + "boehme", + "william_thornton", + "roman_jakobson", + "oliver_cromwell", + "nicolas_de_malebranche", + "vinogradoff", + "henry_beauclerc", + "beaumont", + "lionel_hampton", + "newcomb", + "martin_luther_king", + "bukharin", + "purcell", + "james_hargreaves", + "louis_great", + "prince_charles", + "hermann_goering", + "st_james", + "goncourt", + "delbruck", + "lorenz", + "raymond_lully", + "frank_capra", + "william_wordsworth", + "rex_harrison", + "s", + "william_clark", + "s_smith_stevens", + "woodrow_wilson", + "thomas_jackson", + "delibes", + "william_wycherley", + "walton", + "o'brien", + "margaret_sanger", + "proudhon", + "heming", + "bankhead", + "southey", + "edgar_varese", + "gustav_hertz", + "americus_vespucius", + "yevgeni_yevtushenko", + "acheson", + "george_mason", + "george_wallace", + "common_wormwood", + "el_cid", + "andrei_voznesenski", + "quincy", + "borges", + "mosander", + "marcus_antonius", + "gas_fitter", + "mazzini", + "schulz", + "otto_i", + "dostoevsky", + "lake_powell", + "alonso", + "sapir", + "torricelli", + "frank_cooper", + "de_quincey", + "t_h_white", + "sargent", + "agrippina", + "st_louis", + "richard_rodgers", + "karpov", + "don_quixote", + "george", + "soufflot", + "kleist", + "gogh", + "leeuwenhoek", + "anne_sexton", + "holmes", + "thomas_bradley", + "hogarth", + "kroto", + "john_dryden", + "jim_henson", + "friedrich_max_muller", + "kuznets", + "mercouri", + "furnivall", + "frank", + "saarinen", + "ernest_hemingway", + "burns", + "fiedler", + "voznesenski", + "john_eccles", + "lech_walesa", + "von_neumann", + "george_westinghouse", + "constantin_brancusi", + "richard_haldane", + "tourette", + "thomas_higginson", + "aquila", + "truffaut", + "brockhouse", + "saint_lawrence_river", + "jacques_charles", + "eero_saarinen", + "pauli", + "arthur_miller", + "o'toole", + "henry_russell", + "john_cheever", + "friedrich_wilhelm_bessel", + "cristoforo_colombo", + "gracie_allen", + "john_bernoulli", + "billy_sunday", + "nelson_mandela", + "heinrich_himmler", + "al_gore", + "jacobs", + "farragut", + "john_rutledge", + "hans_bethe", + "hans_geiger", + "michinomiya_hirohito", + "nicklaus", + "gaius_octavianus", + "special_functions", + "mandelbrot", + "cesare_borgia", + "bluegrass_stater", + "woodbury", + "j_p_morgan", + "whittier", + "hampton", + "christopher_carson", + "loewi", + "wheatstone", + "swinburne", + "kerouac", + "fire_warden", + "kierkegaard", + "kutuzov", + "roald_amundsen", + "starkey", + "mossbauer", + "stephane_grappelli", + "sherwood_anderson", + "andersen", + "richard_leakey", + "alfred_korzybski", + "ledbetter", + "charles_dickens", + "verrazano", + "dining_room_attendant", + "pershing", + "jean_chauvin", + "fairbanks", + "kirchhoff", + "delorme", + "maugham", + "e_o_lawrence", + "bellarmino", + "sean_o'casey", + "samuel_huntington", + "de_saussure", + "gesner", + "st_ignatius", + "ella_fitzgerald", + "fats_waller", + "alfred_krupp", + "jakob_bernoulli", + "philip_augustus", + "thomas_sydenham", + "bernoulli", + "jack_robinson", + "tatum", + "alois_senefelder", + "george_enescu", + "wallace_carothers", + "jacques_offenbach", + "anne_bronte", + "schweitzer", + "joseph_paxton", + "manzoni", + "seles", + "silverstein", + "louis_untermeyer", + "william_curtis", + "kennan", + "francisco_villa", + "macaulay", + "john_uhler", + "callas", + "tombaugh", + "lozier", + "bose", + "william_chambers", + "gilbert", + "ironsides", + "minnewit", + "leakey", + "fellini", + "guardian_angel", + "bronislaw_malinowski", + "van_doren", + "von_mauser", + "tawney", + "hans_conrad_julius_reiter", + "george_stevens", + "federico_fellini", + "woolley", + "karl_linne", + "bessie_smith", + "bradley", + "bentham", + "jean_antoine_watteau", + "patrick_henry", + "carnot", + "honegger", + "willy_brandt", + "vestris", + "charles_wilkes", + "francisco_pizarro", + "francisco_franco", + "friedan", + "shelley", + "katherine_cornell", + "jackie_robinson", + "montfort", + "bernardo_bertolucci", + "don_luchino_visconti_conte_di_modrone", + "stevenson", + "king_oliver", + "corday", + "charles_augustus_lindbergh", + "jan_steen", + "lichtenstein", + "frank_harris", + "e_e_cummings", + "white_grouse", + "john_ross", + "ali_baba", + "cassius_longinus", + "powell", + "philibert_delorme", + "guevara", + "peabody", + "stevens", + "andrew_mellon", + "little_red_riding_hood", + "hans_arp", + "browne", + "andrew_carnegie", + "alcott", + "weismann", + "halevy", + "franz_schubert", + "william_butterfield", + "edward_d_white", + "howells", + "johnny_cash", + "vidal", + "joseph_mccarthy", + "wyler", + "alfred_kastler", + "marduk", + "mick_jagger", + "warhol", + "otto_loewi", + "steinman", + "robinson", + "tom_bradley", + "don_marquis", + "charles_peirce", + "mandelstam", + "georges_cuvier", + "peter_seeger", + "ethelred_i", + "sessions", + "hemingway", + "william_harvey", + "husain", + "walter_scott", + "wyat", + "h_j_eysenck", + "parkinson", + "francois_villon", + "charcot", + "august_von_wassermann", + "peter_medawar", + "paul_cezanne", + "jenner", + "werfel", + "stuyvesant", + "vladimir_lenin", + "sam_houston", + "fugard", + "dimaggio", + "robert_peary", + "rodgers", + "littre", + "zangwill", + "bartok", + "wilder", + "henry_steinway", + "kahlil_gibran", + "steiner", + "peter_i", + "daguerre", + "robert_browning", + "comenius", + "charles_kettering", + "mellon", + "alessandro_farnese", + "ralph_ellison", + "john_bunyan", + "jonathan_swift", + "franck", + "goebbels", + "iglesias", + "walter_gropius", + "albert_einstein", + "l", + "henry_sweet", + "donizetti", + "robert_joffrey", + "william_shakspere", + "aletta_jacobs", + "stubbs", + "thomas_edison", + "elizabeth", + "rasputin", + "chiang_kai_shek", + "benjamin_harris", + "beecher", + "claude_bernard", + "ailey", + "raymond_chandler", + "charles_dodgson", + "henry_purcell", + "francis_hopkinson", + "queen's_counsel", + "trumbull", + "windaus", + "de_la_mare", + "ormuzd", + "ostwald", + "john_wickliffe", + "nixon", + "t", + "griffith", + "jean_francois_champollion", + "gainsborough", + "le_douanier_rousseau", + "thatcher", + "lemmon", + "lily", + "cervantes", + "gonne", + "marley", + "witherspoon", + "wilhelm_ostwald" + ], + "SOC_ECO_CLASS": [ + "trade", + "commonality", + "peerage", + "bon_ton", + "commons", + "academe", + "labor", + "philistinism", + "center", + "literati", + "landed_gentry", + "commonalty", + "fraternity", + "sodality", + "samurai", + "squirearchy", + "noblesse", + "lumpenproletariat", + "society", + "third_estate", + "craft", + "labor_force", + "brotherhood", + "caste", + "nobleness", + "organized_labor", + "booboisie", + "fourth_estate", + "cream", + "baronetage", + "elect", + "old_school", + "black_market", + "proletariat", + "demimonde", + "few", + "knighthood", + "jati", + "underworld", + "gentry", + "baronage", + "underclass", + "working_class", + "petite_bourgeoisie", + "pick", + "shinobi", + "peasantry", + "academia", + "bourgeoisie", + "culturati", + "yeomanry", + "first_estate", + "agriculture", + "highbrow", + "age_class", + "petit_bourgeois" + ], + "JOB": [ + "assistant", + "racker", + "coppersmith", + "minter", + "collector", + "neurologist", + "coastguardsman", + "proctologist", + "cabinetmaker", + "creator", + "cytogeneticist", + "door_guard", + "persona_grata", + "bushwhacker", + "vintager", + "yardmaster", + "planner", + "anaesthesiologist", + "falconer", + "buyer", + "teaser", + "verger", + "galvaniser", + "churchwarden", + "healer", + "governess", + "mistress", + "developer", + "paster", + "comptroller", + "guru", + "housewrecker", + "surveyor", + "man_friday", + "merchandiser", + "amanuensis", + "labourer", + "mercator", + "warder", + "sweep", + "dishwasher", + "hierarch", + "wrangler", + "managing_director", + "milliner", + "locksmith", + "indexer", + "sartor", + "public_procurator", + "bureaucrat", + "periodontist", + "sealer", + "sponger", + "carer", + "shill", + "lovely", + "shearer", + "mace", + "sentinel", + "immunologist", + "varnisher", + "wingman", + "mariner", + "forester", + "scratcher", + "twiner", + "businessman", + "non_commissioned_officer", + "splitter", + "scorekeeper", + "bailiff", + "attendant", + "bridesmaid", + "quack", + "houseman", + "magaziner", + "breadwinner", + "speaker", + "stenographer", + "holdover", + "schoolmistress", + "shopkeeper", + "general_manager", + "cattleman", + "reseller", + "ranger", + "ringleader", + "gaoler", + "stainer", + "potter", + "packer", + "beautician", + "unionist", + "huntress", + "menial", + "armiger", + "dragger", + "make", + "stippler", + "miller", + "runner", + "monger", + "rescuer", + "sourdough", + "alderman", + "gerontologist", + "platelayer", + "airman", + "shingler", + "diesinker", + "translator", + "selectman", + "trustbuster", + "strikebreaker", + "dog_catcher", + "horseherd", + "roundsman", + "paramedical", + "adang", + "washwoman", + "sprayer", + "employable", + "gutter", + "dresser", + "baggageman", + "salter", + "armorer", + "gillie", + "health_professional", + "framer", + "lascar", + "scullion", + "hand", + "laborer", + "pathologist", + "purser", + "cooper", + "luthier", + "manageress", + "remover", + "registrar", + "groomsman", + "sea_captain", + "scab", + "canoer", + "immigration_officer", + "scourer", + "artillery_crew", + "gasman", + "weaponsmith", + "staffer", + "glazier", + "sexton", + "subaltern", + "druggist", + "pantryman", + "curator", + "aeronautical_engineer", + "roper", + "demonstrator", + "lockman", + "scorer", + "industrialist", + "gallant", + "moonlighter", + "internist", + "temp", + "bouncer", + "upholsterer", + "don", + "varlet", + "aquanaut", + "stevedore", + "king", + "planter", + "common_soldier", + "maid", + "sergeant", + "man_midwife", + "rigger", + "mailman", + "rhinolaryngologist", + "timekeeper", + "coyote", + "pothunter", + "mahout", + "groundskeeper", + "cleaner", + "calligrapher", + "valet", + "tier", + "muzzler", + "ergonomist", + "temporary", + "plumber", + "translatress", + "machinist", + "waiter", + "glazer", + "headwaiter", + "carver", + "bondman", + "woodworker", + "intern", + "winder", + "troubleshooter", + "peacemaker", + "turncock", + "public_servant", + "originator", + "compositor", + "conveyancer", + "dockhand", + "shifter", + "cuirassier", + "art_teacher", + "hakeem", + "parlourmaid", + "political_instructor", + "skinner", + "pretor", + "woodcarver", + "puller", + "sheller", + "chairwoman", + "char", + "noticer", + "warehouseman", + "yardman", + "carrier", + "geoscientist", + "dramaturge", + "bellboy", + "jawan", + "sommelier", + "paperboy", + "trainmaster", + "beater", + "thresher", + "counsel", + "processor", + "tallyman", + "man_servant", + "chieftain", + "burgomaster", + "repertor", + "cataloguer", + "riveter", + "blacksmith", + "prosthodontist", + "resident", + "doge", + "\u00e9chevin", + "gentleman", + "plaiter", + "minder", + "au_pair_girl", + "trimmer", + "lister", + "letterer", + "busboy", + "sheepherder", + "sceneshifter", + "lapidary", + "torchbearer", + "pensionary", + "prompter", + "trencher", + "territorial", + "wainwright", + "hydrologist", + "distributor", + "von_blucher", + "inductee", + "excavator", + "amputator", + "placeseeker", + "gaffer", + "novelist", + "phlebotomist", + "ostler", + "trustee", + "crewman", + "cooky", + "paediatrician", + "legal_assistant", + "grip", + "para", + "router", + "magistrate", + "conductor", + "paperer", + "leatherneck", + "essayist", + "lockmaster", + "woodcutter", + "fuller", + "pharmacist", + "chief", + "sensei", + "arrowsmith", + "thatcher", + "bodyguard", + "currier", + "microbiologist", + "helmsman", + "buckaroo", + "chemist", + "hairdresser", + "cook", + "spotter", + "becker", + "couturier", + "carbineer", + "mastermind", + "paramedic", + "curatrix", + "tapper", + "privy_councillor", + "hydrogeologist", + "tollkeeper", + "perfecter", + "aesthetician", + "plasterer", + "trial_attorney", + "trainer", + "land", + "doorman", + "encyclopedist", + "hakim", + "justiciar", + "tailor", + "brakeman", + "marines", + "pallbearer", + "steersman", + "noncombatant", + "boss", + "vigilante", + "roadman", + "barmaid", + "throwster", + "coadjutor", + "reader", + "transcriber", + "housebreaker", + "crammer", + "ophthalmologist", + "obstetrician", + "female_companion", + "internuncio", + "treasurer", + "cartographer", + "muleteer", + "striver", + "craftsman", + "weaver", + "paperhanger", + "boatswain", + "bowdlerizer", + "veisalgia", + "butler", + "groundsman", + "wheelwright", + "therapist", + "grenadier", + "stonecutter", + "counterperson", + "splicer", + "paralegal", + "gentleman's_gentleman", + "inventor", + "bagger", + "safebreaker", + "handyman", + "macebearer", + "academician", + "surgeon", + "overseer", + "pitman", + "homoeopath", + "publisher", + "endodontist", + "vaquero", + "canoeist", + "retailer", + "lumper", + "printer", + "meteorologist", + "sweeper", + "manufacturer", + "cutter", + "qadi", + "pruner", + "comber", + "brigadier", + "garnishee", + "breeder", + "cavalryman", + "typesetter", + "independent", + "lackey", + "freelance", + "scientist", + "leader", + "prosecutor", + "deaconess", + "clerk", + "warden", + "kamikaze", + "moviemaker", + "driver", + "wheeler", + "lather", + "slavey", + "sea_lawyer", + "man_at_arms", + "performer", + "hangover", + "goldbeater", + "caregiver", + "balloonist", + "page", + "comedian", + "dietitian", + "voicer", + "tanner", + "horologist", + "interne", + "trainbandsman", + "baker", + "umpire", + "etcher", + "transactor", + "submariner", + "mayor", + "troller", + "salesgirl", + "glassblower", + "keyboarder", + "shopgirl", + "sculptor", + "freelancer", + "lapidist", + "herbalist", + "punter", + "gunsmith", + "newsboy", + "schoolmarm", + "hewer", + "bargeman", + "sketcher", + "bursar", + "attorney", + "lockkeeper", + "selectwoman", + "stalker", + "printmaker", + "courser", + "alcalde", + "salesman", + "lancer", + "master", + "headman", + "rheumatologist", + "bracer", + "percussor", + "stroke", + "chairperson", + "blackleg", + "hedger", + "counsellor", + "doughboy", + "intelligence_agent", + "almoner", + "president", + "seneschal", + "dyer", + "government_agent", + "barnstormer", + "electroplater", + "nullifier", + "lamplighter", + "seller", + "standard_bearer", + "gravedigger", + "steeplejack", + "minister", + "headmistress", + "mandarin", + "carpenter", + "public_prosecutor", + "tollgatherer", + "setter", + "liveryman", + "floorwalker", + "herder", + "groom", + "entertainer", + "courtier", + "bracero", + "dressmaker", + "mason", + "regidor", + "lasher", + "dermatologist", + "counterfeiter", + "chronicler", + "companion", + "fowler", + "pleader", + "hussar", + "bunny", + "mate", + "stoker", + "infantryman", + "pharmacologist", + "adjutant_general", + "roustabout", + "guide", + "lion_hunter", + "school_superintendent", + "stamper", + "interpreter", + "longshoreman", + "sawyer", + "macer", + "hotel_manager", + "sandwichman", + "fitter", + "hanger", + "fugleman", + "haematologist", + "angler", + "herald", + "wharfie", + "designer", + "enforcer", + "cashier", + "sitter", + "hematologist", + "foreman", + "buckeroo", + "pastor", + "turtler", + "cataloger", + "stocktaker", + "manservant", + "marshal", + "saleswoman", + "barrister", + "tracklayer", + "announcer", + "linkboy", + "radiologic_technologist", + "drudge", + "guestworker", + "placeman", + "rapporteur", + "sheriff", + "hawker", + "picker", + "ropemaker", + "stewardess", + "clinician", + "database_administrator", + "diplomate", + "nailer", + "councillor", + "doorkeeper", + "regulator", + "governor", + "cartwright", + "gardener", + "incumbent", + "stage_director", + "greyback", + "dairyman", + "squire", + "schoolmaster", + "fellah", + "landlord", + "moneyer", + "bill_poster", + "tollman", + "perinatologist", + "carabineer", + "associate", + "placer_miner", + "player", + "grocer", + "cropper", + "boilermaker", + "mellah", + "gaucho", + "waker", + "hostess", + "corporal", + "beadle", + "angiologist", + "justiciary", + "wallpaperer", + "charioteer", + "shipwright", + "baster", + "preserver", + "slave", + "district_attorney", + "lumberman", + "dancer", + "gamekeeper", + "washerman", + "stitcher", + "renovator", + "cornhusker", + "diplomatic_minister", + "clockmaker", + "underboss", + "gastroenterologist", + "chimneysweep", + "salesperson", + "sifu", + "darner", + "abortionist", + "collier", + "lender", + "manager", + "familiar", + "seaman", + "bleacher", + "shepherdess", + "broker", + "wetter", + "shipbuilder", + "midwife", + "carter", + "endocrinologist", + "porter", + "shopwalker", + "subeditor", + "linkman", + "diemaker", + "knacker", + "conveyer", + "insurance_broker", + "electrologist", + "catechist", + "stripper", + "fumigator", + "deckhand", + "handmaiden", + "gleaner", + "rivetter", + "neurosurgeon", + "carabinier", + "glassmaker", + "cop", + "barista", + "handmaid", + "shepherd", + "colonel", + "flanker", + "rouser", + "skivvy", + "sorter", + "warehouser", + "warrior", + "sprog", + "merchant", + "barber", + "glassworker", + "songwriter", + "charwoman", + "herdsman", + "maidservant", + "weigher", + "toller", + "allergist", + "ranker", + "tinner", + "housemaster", + "bonesetter", + "principal", + "childminder", + "pitchman", + "night_watchman", + "man", + "dockworker", + "earth_scientist", + "whaler", + "voider", + "doc", + "caster", + "quartermaster", + "logger", + "regent", + "bargee", + "stacker", + "schoolteacher", + "marine", + "peacekeeper", + "statistician", + "fireman", + "dragoon", + "social_secretary", + "manual_laborer", + "businesswoman", + "mapper", + "washer", + "sprigger", + "chancellor", + "soundman", + "striker", + "swineherd", + "strafer", + "tacker", + "point_guard", + "counselor", + "painter", + "recorder", + "wallah", + "draughtsman", + "councilor", + "propman", + "cannoneer", + "armourer", + "chargeman", + "usher", + "gilder", + "stipendiary", + "invalidator", + "messenger", + "exciseman", + "founder", + "cardiologist", + "chauffeur", + "bellman", + "lacer", + "composer", + "parlormaid", + "weeder", + "au_pair", + "tinsmith", + "anaesthetist", + "bricklayer", + "sentry", + "proconsul", + "striper", + "businessperson", + "licenser", + "cox", + "stuffer", + "janitor", + "bombardier", + "lighterman", + "die_sinker", + "trier", + "sublieutenant", + "cameraman", + "public_defender", + "shelver", + "rancher", + "farrier", + "councilman", + "housekeeper", + "goldbrick", + "woman", + "yardbird", + "harvestman", + "plotter", + "tracker", + "melter", + "hostler", + "paratrooper", + "presenter", + "heaver", + "canvasser", + "sailor", + "vestryman", + "blaster", + "galvanizer", + "sculler", + "sidesman", + "croupier", + "usherette", + "candy_striper", + "steward", + "mounter", + "courier", + "chartered_accountant", + "lawman", + "laryngologist", + "searcher", + "presbyter", + "sergeant_major", + "abridger", + "sharecrop_farmer", + "arouser", + "extern", + "sub_lieutenant", + "ruler", + "horseshoer", + "joiner", + "vestrywoman", + "osteopath", + "concierge", + "bearer", + "jailer", + "chairman", + "marshall", + "chimneysweeper", + "trial_judge", + "doula", + "docker", + "tuner", + "abbreviator", + "coxswain", + "sub", + "anthologist", + "harpooner", + "parer", + "bowdleriser", + "taskmaster", + "settler", + "trade_unionist", + "caretaker", + "turner", + "solicitor", + "bishop", + "calligraphist", + "tiler", + "signalman", + "postmaster_general", + "coolie", + "lumberjack", + "groundkeeper", + "washerwoman", + "sharecropper", + "headmaster", + "mayoress", + "chambermaid", + "cookie", + "headteacher", + "scavenger", + "boatbuilder", + "harpooneer", + "drawer", + "bellhop", + "techie", + "esquire", + "science_teacher", + "waterer", + "clocksmith", + "tapster", + "airwoman", + "gunner", + "topper", + "alienist", + "rocker", + "charcoal_burner", + "regular", + "paddler", + "managing", + "gatekeeper", + "autor", + "lieutenant", + "thrower", + "millwright", + "steamfitter", + "high_commissioner", + "peeler", + "deliveryman", + "cartoonist", + "loader", + "stonemason", + "footman", + "banker", + "firefighter", + "stringer", + "dairymaid", + "conductress", + "preceptor", + "trainbearer" + ], + "FOOD": [ + "dog_food", + "soy_flour", + "ham_and_eggs", + "collard_greens", + "jerusalem_artichoke", + "monosodium_glutamate", + "scotch_woodcock", + "olla_podrida", + "julienne_vegetable", + "mousse", + "bitter_orange", + "steak_tartare", + "homogenized_milk", + "chocolate_bar", + "loukoum", + "golden_delicious", + "promulsis", + "desert", + "sugarloaf_mountain", + "sea_trout", + "tiffin", + "symphytum_officinale", + "betel_nut", + "daucus_carota", + "nada_daiquiri", + "bechamel", + "common_carp", + "christmas_pudding", + "juniper_berries", + "fritter_batter", + "crisphead_lettuce", + "tomato_concentrate", + "mint_sauce", + "lemonade", + "thompson_seedless", + "chicken_provencale", + "white_chocolate", + "jacket_potato", + "vigna_unguiculata", + "guinea_hen", + "cat_food", + "beefsteak_plant", + "american_lobster", + "granny_smith", + "capsicum", + "orange_marmalade", + "granola_bar", + "rocambole", + "sauce", + "cakes", + "russian_mayonnaise", + "won_ton", + "taffy", + "barbecued_spareribs", + "stick_cinnamon", + "soy_milk", + "pickle", + "sweet_pepper", + "white_russian", + "mineral_water", + "anchovy_sauce", + "pina_colada", + "t_bone_steak", + "farina", + "ham_sandwich", + "jordan_almond", + "candyfloss", + "lemon_extract", + "pinot_noir", + "sodium_chloride", + "rock_candy", + "chilli", + "tom_collins", + "black_bread", + "red_currant", + "lima_bean", + "entr\u00e9e", + "pepper", + "macedoine", + "appetizer", + "savoy_cabbage", + "meatloaf", + "cowpea", + "tonic_water", + "sea_bream", + "pastry", + "dog_biscuit", + "french_dressing", + "fruit_salad", + "gelato", + "chili", + "clarified_butter", + "sweet_orange", + "napa_cabbage", + "wild_rice", + "head_cabbage", + "rose_apple", + "red_hot", + "dietary_fiber", + "lunch", + "brazil_nut", + "chile", + "green_tea", + "pinyon", + "sockeye_salmon", + "antipasto", + "appetiser", + "soy_sauce", + "candied_apple", + "maryland_chicken", + "northern_pike", + "sweet_potato", + "poppy_seed", + "beef_tongue", + "pudding", + "c_ration", + "may_wine", + "oysters_rockefeller", + "atlantic_salmon", + "blutwurst", + "chinese_cabbage", + "dessert", + "baguet", + "mustard_seed", + "hushpuppy", + "tutti_frutti", + "dragon_fruit", + "french_toast", + "k_ration", + "scotch_broth", + "coffee", + "soy_bean_oil", + "drinkwater", + "ros\u00e9", + "black_pepper", + "sonchus_oleraceus", + "petit_four", + "omelette", + "harvey_wallbanger", + "pot_au_feu", + "mandarin_orange", + "gustatio", + "blue_crab", + "breakfast", + "bok_choy", + "cohoe", + "catsup", + "mangel_wurzel", + "uruguay_potato", + "juglans_regia", + "freshwater_fish", + "chevre", + "cocoa" + ], + "DISEASE": [ + "cyanose", + "hurt", + "kaluresis", + "hydrocephalus", + "sars", + "sneeze", + "fructosuria", + "pertussis", + "lipidaemia", + "nicotinism", + "ophidism", + "arthritis", + "chorioretinitis", + "addiction", + "monogenic_disease", + "montezuma's_revenge", + "angriness", + "sea_sickness", + "disturbance", + "filovirus", + "cramp", + "acanthosis_nigricans", + "abrasion", + "clubfoot", + "leak", + "potence", + "freshness", + "cellulitis", + "maidism", + "villoma", + "cerebromeningitis", + "hydramnios", + "paise", + "quadriplegia", + "plumbism", + "chilblains", + "rheumatoid_spondylitis", + "chickenpox", + "stuffiness", + "ki", + "polio", + "aniseikonia", + "tabes_dorsalis", + "seasickness", + "complication", + "alerting", + "tamponage", + "flection", + "bunion", + "panencephalitis", + "flavivirus", + "desire", + "lassitude", + "carbuncle", + "rubeola", + "stasis", + "hermaphrodism", + "rinderpest", + "rosette", + "protozoal_infection", + "furuncle", + "hydrarthrosis", + "anesthesia", + "psychoneurosis", + "myositis_trichinosa", + "mastadenitis", + "arthralgia", + "squeamishness", + "descensus", + "alertness", + "malady", + "rage", + "fettle", + "chemosis", + "anthrax", + "carotenemia", + "cosmid", + "non_insulin_dependent_diabetes_mellitus", + "jaundice", + "astasia", + "bowleg", + "analgesia", + "anestrus", + "chill", + "smallpox", + "costochondritis", + "als", + "prodrome", + "chestnut", + "whiplash", + "rabies", + "mastitis", + "squint", + "heat", + "palilalia", + "rectocele", + "clubbing", + "gumma", + "vitalization", + "complaint", + "wen", + "habituation", + "parvo", + "hsv_1", + "ventricular_fibrillation", + "longsightedness", + "pontes", + "undernourish", + "quinsy", + "epidemic_roseola", + "phenylketonuria", + "anthrax_pneumonia", + "siderosis", + "polyarteritis_nodosa", + "catarrh", + "inversion", + "coughing", + "adenomatous_polyp", + "diestrum", + "steatorrhea", + "distemper", + "clinocephalism", + "progeria", + "mange", + "aquaphobia", + "verruca_acuminata", + "poison_ivy", + "sleeping", + "camelpox", + "papovavirus", + "potency", + "graphospasm", + "non_insulin_dependent_diabetes", + "hordeolum", + "frostbite", + "sore", + "congestion", + "cardiomegaly", + "singultus", + "congested", + "sciatica", + "analgia", + "listeriosis", + "prodroma", + "choking", + "mouse", + "clinodactyly", + "strawberry_haemangioma", + "stutter", + "distomatosis", + "steatocystoma", + "sternutation", + "ravenousness", + "wasting", + "brachydactyly", + "xerodermia", + "croup", + "energy", + "genus_oestrus", + "monochromatic_vision", + "induration", + "anger", + "pachyderma", + "lordosis", + "famishment", + "distress", + "aeroembolism", + "radiation", + "clavus", + "lump", + "clap", + "smarting", + "cough", + "claustrophobia", + "pinealoma", + "cataphasia", + "formication", + "metacyesis", + "indigestion", + "pharyngitis", + "smartness", + "plasmacytoma", + "bradycardia", + "gotta", + "burning", + "beriberi", + "healthiness", + "seminoma", + "natriuresis", + "wheal", + "mitral_stenosis", + "gall", + "mania", + "dementia", + "mastalgia", + "spots", + "radiance", + "looseness", + "warble", + "diabetic_acidosis", + "xeroderma", + "lithiasis", + "arenavirus", + "stroke", + "kink", + "vellication", + "scours", + "succus", + "genus_anomia", + "piles", + "herniation", + "pang", + "picornavirus", + "struma", + "rickets", + "phytophthora_infestans", + "hydrophobia", + "paraesthesia", + "phalangitis", + "agammaglobulinemia", + "perleche", + "streptococcus_tonsilitis", + "barrenness", + "shape", + "heartrot", + "brath", + "myxoma_virus", + "lipidemia", + "starvation", + "welt", + "livedo", + "ms", + "sneezing", + "overgrowth", + "bunt", + "bleeding", + "have_runs", + "cowpox", + "otorrhea", + "gravidness", + "scotoma", + "fantods", + "overweight", + "autoimmunity", + "hydrocele", + "human_papillomavirus", + "arthropathy", + "epstein_barr_virus", + "coronary_thrombosis", + "rachischisis", + "intertrigo", + "gimpiness", + "rust", + "slice", + "pinkroot", + "mareo", + "contusion", + "arrhythmia", + "proteinuria", + "menorrhagia", + "furunculosis", + "torpidity", + "orthomyxovirus", + "claudication", + "paramyxovirus", + "pancreatitis", + "heterotaxy", + "monoblastic_leukaemia", + "thirstiness", + "salmonellosis", + "trouble", + "regional_ileitis", + "teratoma", + "hyperchromic_anaemia", + "logagraphia", + "hypoxic_hypoxia", + "cheloid", + "lassa_virus", + "balanoposthitis", + "haleness", + "goitre", + "albuminuria", + "suntan", + "parity", + "schizotypal_personality", + "vaccination", + "analbuminemia", + "xanthoma_multiplex", + "quartan", + "lipoid_granulomatosis", + "plant_virus", + "meromelia", + "murrain", + "mercury_poisoning", + "deuteranopia", + "materialism", + "anchylosis", + "pasteurellosis", + "chondrosarcoma", + "ammoniuria", + "rosacea", + "glycosuria", + "humpback", + "para", + "seif", + "brucellosis", + "van_bogaert_encephalitis", + "maladjustment", + "paracentral_scotoma", + "photoretinitis", + "founder", + "ada_scid", + "alexic", + "valgus", + "hay_fever", + "chorea", + "costiasis", + "lysinemia", + "hunger", + "bruising", + "snowblindness", + "handicap", + "elastosis", + "hs1", + "lipaemia", + "cyanosis", + "arenaviridae", + "graze", + "stricture", + "tarantism", + "pimple", + "orchitis", + "siriasis", + "appendicitis", + "gravidation", + "alalia", + "pernio", + "chloasma", + "tenesmus", + "cyclothymia", + "yatobyo", + "astraphobia", + "herpes_virus", + "gastric_fistula", + "scar", + "hearing_loss", + "kernicterus", + "laparocele", + "strangulation", + "machupo_virus", + "vasculitis", + "sodoku", + "lallation", + "bluetongue", + "cva", + "wale", + "shortsightedness", + "lumbago", + "be_poisoned", + "gravida", + "stitch", + "orchidalgia", + "metabolic_acidosis", + "vaccina", + "cecity", + "dactylomegaly", + "miliaria", + "equine_distemper", + "shingles", + "variola_major", + "pancarditis", + "sightlessness", + "herpes_simplex_virus", + "tracheitis", + "ochronosis", + "erythema_multiforme", + "debility", + "crick", + "lymphocytic_choriomeningitis_virus", + "consumption", + "galactosemia", + "anaclitic_depression", + "paralysis", + "torpor", + "cachexy", + "amastia", + "crookback", + "lepidophobia", + "black_eye", + "horniness", + "cachexia", + "presbyopia", + "festination", + "landry's_paralysis", + "microcytic_anaemia", + "tarsitis", + "alphavirus", + "phaeochromocytoma", + "visual_aphasia", + "posthitis", + "meteorism", + "lightheadedness", + "tamponade", + "drug_addiction", + "schistorrhachis", + "pachycheilia", + "lameness", + "shortsighted", + "genetic_disorder", + "bruise", + "pemphigus", + "undernutrition", + "diaphragmatic_pleurisy", + "flexure", + "epidemic_meningitis", + "oxycephaly", + "ache", + "hamartoma", + "superinfection", + "chi", + "ringworm", + "rachitis", + "delirium", + "glow", + "balanitis", + "injury", + "glucopenia", + "satanophobia", + "catalepsy", + "stridor", + "lichen", + "hickey", + "vigil", + "rubor", + "rickettsialpox", + "sclerosing_leukoencephalitis", + "transposition", + "qi", + "hydrocephaly", + "flutter", + "thalassaemia", + "corn", + "trembles", + "blain", + "preeclampsia", + "granuloma", + "herpes_simplex", + "metamorphopsia", + "creeps", + "palsy", + "weal", + "bends", + "infirmity", + "areflexia", + "thirst", + "akinesia", + "metabolic_disorder", + "parasitaemia", + "congenital_megacolon", + "scarlatina", + "muscularity", + "pancreatic_fibrosis", + "caranx_bartholomaei", + "malaise", + "lockjaw", + "wheeziness", + "strabismus", + "von_recklinghausen's_disease", + "monocytic_leukemia", + "spina_bifida", + "passion", + "mycoplasmal_pneumonia", + "hydremia", + "deaf_muteness", + "gargoylism", + "malignance", + "seizure", + "cardiopathy", + "flaviviridae", + "bloodiness", + "heartburn", + "paralysis_agitans", + "monocytic_leukaemia", + "american_leishmaniasis", + "windburn", + "clostridial_myonecrosis", + "orthostatic_hypotension", + "spinal", + "kala_azar", + "quadrantanopia", + "gimp", + "oestrus", + "blastocytoma", + "ague", + "estrus", + "snakebite", + "mers", + "caffeinism", + "regional_enteritis", + "headache", + "abasia", + "frenzy", + "fester", + "hernia", + "alexia", + "gangrene", + "gestation", + "stinging", + "herpes", + "paraparesis", + "epidural_anaesthesia", + "toxemia", + "dieback", + "effect", + "mediterranean_anaemia", + "crud", + "pityriasis", + "rash", + "hypnophobia", + "aching", + "wakefulness", + "cardiomyopathy", + "parkinsonism", + "gravidity", + "twist", + "chancre", + "lipemia", + "yellow_jack", + "intermittent_tetanus", + "smart", + "amelia", + "hydrops", + "failure", + "epidemic_encephalitis", + "marasmus", + "kraurosis", + "collywobbles", + "eventration", + "obliquity", + "gumboil", + "gummosis", + "sandfly_fever", + "ed", + "clinocephaly", + "sunstroke", + "breakdown", + "callosity", + "proctocele", + "dentalgia", + "folliculitis", + "paratyphoid", + "blister", + "kaliuresis", + "chlorosis", + "pica", + "tracheobronchitis", + "stenosis", + "papilloma", + "grieven", + "blackwater", + "sickness", + "distension", + "meralgia", + "alveolitis", + "renal_lithiasis", + "glucosuria", + "costalgia", + "afterpains", + "corpulence", + "callus", + "acetonuria", + "macrocytic_anaemia", + "chorditis", + "rhus_radicans", + "vaccinia", + "acetonemia", + "bloom", + "trachoma", + "hebetude", + "classical_haemophilia", + "paresis", + "tachycardia", + "acorea", + "furring", + "galactocele", + "soreness", + "causalgia", + "choke", + "schizothymia", + "blockage", + "choriomeningitis", + "talipes", + "keratosis_blennorrhagica", + "sensation", + "psychopathic_personality", + "yellow_fever", + "floater", + "pancytopenia", + "toxaemia", + "fluorosis", + "murmur", + "radiculitis", + "parametritis", + "humpbacked", + "chiralgia", + "funiculitis", + "strangles", + "automysophobia", + "nosebleed", + "mastocarcinoma", + "tabes", + "earache", + "poliovirus", + "photophobia", + "african_trypanosomiasis", + "monoblastic_leukemia", + "rubella", + "mongolism", + "anthracosis", + "epidermolysis_bullosa", + "hurting", + "fugue", + "overbite", + "pansinusitis", + "pain", + "softness", + "walleye", + "vitality", + "goiter", + "diphtheria", + "diestrus", + "gammopathy", + "abrachia", + "bunyaviridae", + "malacia", + "akinesis", + "genus_icterus", + "arbovirus", + "incisura", + "catatonic_schizophrenia", + "voicelessness", + "cervicitis", + "peritonsillar_abscess", + "strain", + "gynecomastia", + "hsv_i", + "dilatation", + "thalassemia", + "photalgia", + "von_willebrand's_disease", + "contagion", + "xanthoma_disseminatum", + "purpura", + "peritoneal_inflammation", + "papilledema", + "spermatocele", + "distention", + "rick", + "whitlow", + "aerodontalgia", + "schizoid", + "eburnation", + "blackheart", + "tmv", + "puffiness", + "vasovesiculitis", + "sequela", + "tone_deafness", + "enchondroma", + "stammer", + "cat_scratch_disease", + "singe", + "arborvirus", + "wtv", + "diastasis", + "coryza", + "constipation", + "celioma", + "actinic_keratosis", + "eschar", + "silicosis", + "hyperchromic_anemia", + "laminitis", + "valetudinarianism", + "epidemic_cholera", + "ill", + "chalazion", + "gash", + "parasitemia", + "paraplegia", + "greensickness", + "bellyache", + "misshapenness", + "panaritium", + "sprain", + "anestrum", + "locoism", + "pull", + "parkinson's", + "hypertrophic_cardiomyopathy", + "stigmata", + "variola_major_virus", + "slough", + "shuteye", + "scald", + "concussion", + "demineralization", + "rosiness", + "sawan", + "normothermia", + "herpangia", + "staggers", + "collapse", + "valvulitis", + "chondrodystrophy", + "sterility", + "lethargy", + "pollinosis", + "bandyleg", + "smut", + "odontalgia", + "malocclusion", + "pellagra", + "exotropia", + "pinch", + "leper", + "togaviridae", + "paralytic_abasia", + "orthopnea", + "granulocytopenia", + "mastopathy", + "schistosomiasis", + "androphobia", + "hydrothorax", + "maternity", + "traumatophobia", + "laceration", + "disseminated_sclerosis", + "mi", + "tilletia_caries", + "orthochorea", + "disintegration", + "roseola", + "coronary", + "alastrim", + "shigellosis", + "aura", + "glanders", + "proctalgia", + "mazopathy", + "roset", + "brachydactylia", + "tan", + "flue", + "arousal", + "rheumatic_aortitis", + "lipidosis", + "molluscum", + "sting", + "pestis_bubonica", + "wart", + "blastoma", + "lipid_granulomatosis", + "innervation", + "morphea", + "dandruff", + "giantism", + "achylia_gastrica", + "protanopia", + "emmetropia", + "peliosis", + "excoriation", + "aftereffect", + "hsv_ii", + "lambdacism", + "adiposity", + "break", + "sturdiness", + "indisposition", + "malignancy", + "heatstroke", + "sleep", + "poliomyelitis", + "nys", + "swelling", + "hardening", + "unhealthiness", + "undernourishment", + "trauma", + "hydronephrosis", + "nicotine_addiction", + "chancroid", + "breathlessness", + "chondroma", + "echovirus", + "primary_syphilis", + "uraemia", + "rawness", + "thanatophobia", + "chilblain", + "harelip", + "lichen_planus", + "aminoaciduria", + "kuru", + "burn", + "dropsy", + "pinkeye", + "lagophthalmos", + "flexion", + "gameness", + "corditis", + "cellularity", + "biliousness", + "actinic_dermatitis", + "noma", + "deviance", + "tyrosinemia", + "emptiness", + "thermalgesia", + "hemeralopia", + "rickettsiosis", + "periarteritis_nodosa", + "genus_scleroderma", + "central_scotoma", + "diaphragmatic_hernia", + "bedsore", + "shivering", + "condition", + "dengue", + "anasarca", + "comminuted_fracture", + "cataract", + "demineralisation", + "roseola_infantilis", + "torment", + "dog_bite", + "cartilaginification", + "paresthesia", + "flare", + "wilt", + "hungriness", + "le", + "bunyavirus", + "slow_virus", + "hayfever", + "harm", + "proctitis", + "madness", + "dysomia", + "bruh", + "keratoderma_blennorrhagica", + "sprue", + "wrench", + "shiner", + "parvovirus", + "salmonella", + "runza", + "toxicodendron_radicans", + "vitalisation", + "verruca", + "mooneye", + "toothache", + "cacogenesis", + "tritanopia", + "dysosmia", + "cold", + "variola_virus", + "hermaphroditism", + "petechia", + "cyclopia", + "phonophobia", + "spinal_curvature", + "esotropia", + "ill_health", + "ozena", + "viraemia", + "heaves", + "backache", + "carditis", + "arteriosclerosis_obliterans", + "taphephobia", + "malaria", + "phocomelia", + "mongolianism", + "gout", + "palmature", + "philistinism", + "mastoiditis", + "subluxation" + ], + "ANIMAL": [ + "blackbird", + "pierid", + "sea_spider", + "protoctist_family", + "acherontia", + "apodemus", + "peregrine_falcon", + "giant_manta", + "cat", + "coris_marquesensis", + "sparrow", + "copper_rockfish", + "buteo", + "class_cyanobacteria", + "calimocho", + "sea_lettuce", + "brant", + "atlantic_sailfish", + "goldfinch", + "bearberry_willow", + "sea_anemone", + "pine_grosbeak", + "sapo", + "common_starling", + "dog_flea", + "drosophila", + "homo_sapiens_sapiens", + "anuran", + "salmo_gairdneri", + "blackgame", + "montagu's_harrier", + "philippine_tarsier", + "bare_headed", + "red_spider", + "take_all", + "stag", + "atlantic_herring", + "otter", + "heron", + "black_widow", + "firefox", + "cottontail", + "greek_partridge", + "lowland_burrowing_treefrog", + "sparrowhawk", + "harridan", + "woodlouse", + "horse_riding", + "lemmus_lemmus", + "sitta_europaea", + "stag_beetle", + "uma_notata", + "sea_snake", + "snoek", + "she_cat", + "billy_elliot", + "baleen_whale", + "tern", + "bullfinch", + "australian_blacksnake", + "carabid", + "saratoga_spittlebug", + "kunduz", + "sea_swallow", + "sea_eagle", + "buzzard", + "tortoiseshell", + "thomson's_gazelle", + "tineid", + "canis_minor", + "bullpout", + "manta", + "hippotragus_niger", + "junin_virus", + "mussel", + "sitta_carolinensis", + "frankliniella_fusca", + "badger", + "thrush", + "sea_lion", + "wobbegong", + "white_pelican", + "carduelis", + "mei_long", + "pisces", + "mammal", + "eretmochelys", + "lake_whitefish", + "sea_raven", + "piranga_olivacea", + "mavis", + "felis_tigrina", + "goshawk", + "sea_cucumber", + "swift", + "sea_slug", + "yellow_bellied", + "chipmunk", + "sand_martin", + "florida_gallinule", + "sandpiper", + "tobacco_mosaic_virus", + "erne", + "sea_cow", + "lactobacillus_acidophilus", + "giant_panda", + "queltehue", + "troupial", + "angelica_anomala", + "arthropods", + "alaska_king_crab", + "cliff_swallow", + "musteline_mammal", + "king_whiting", + "leptodactylid", + "pieris_brassicae", + "ferret", + "western_kingbird", + "skilletfish", + "crow", + "western_wheatgrass", + "english_partridge", + "barrow's_goldeneye", + "chinese_angelica", + "artiodactyl", + "gordon_setter", + "western_meadowlark", + "perennial_salt_marsh_aster", + "capercailzie", + "ebola_virus_disease", + "giant_salamander", + "vibe", + "diamondback", + "kestrel", + "cushat", + "electrophorus_electric", + "spavin", + "mountain_beaver", + "wilga", + "micropterus", + "canyon_treefrog", + "bearded_woodpecker", + "fratercula_arctica", + "martes_martes", + "faina", + "bewick's_swan", + "wiesel", + "perca_flavescens", + "c_diphtheriae", + "black_buffalo", + "womanizer", + "galgo", + "stormcock", + "guaco", + "sea_moss", + "hermissenda", + "lama_peruana", + "giant_petrel", + "makaira_mazara", + "salmonella_enteritidis", + "margaritifera_laevis", + "raven", + "black_tortoise", + "homo_sapiens", + "mink", + "arthropod", + "james's_gerbil", + "harrier", + "grateloupia_elliptica", + "blackcock", + "sea_turtle", + "carabao", + "sprosser", + "lakeland_terrier", + "ebola_virus", + "greater_bilby", + "passer", + "chinese_goose", + "tetranychid", + "frog", + "carrion_crow", + "io_moth", + "bare_backed", + "condor", + "greater_yellowlegs", + "rainbow_trout", + "hydropote", + "sea_scallop", + "maggie", + "cape_buffalo", + "european_eider", + "hound", + "cyanophyceae", + "donkey", + "hornet", + "trp", + "cocker", + "prunus_tenella", + "white_rhinoceros", + "hawk", + "cro_magnon", + "genus_erignathus", + "merl", + "waterdog", + "accipiter", + "nitidotellina_nitidula", + "jackknife_fish", + "oriole", + "staffordshire_bullterrier", + "greater_whitethroat", + "variola_minor_virus", + "water_dog", + "american_lobster", + "greyhound", + "ophioplocus_japonicus", + "west_nile_virus", + "bumblebee", + "cota_tinctoria", + "stieglitz", + "falcon", + "sea_tangle", + "domestic_buffalo", + "variola_minor", + "parainfluenza_virus", + "e_coli", + "chlorophyll_d", + "mizuhiki", + "snake_polypody", + "consecutive_interpretation", + "sicyopterus_japonicus", + "cancer_japonicus", + "greenhouse_whitefly", + "marburg_virus", + "common_chaffinch", + "thomomys_talpoides", + "sei_whale", + "dovekie", + "banteng", + "olympic_salamander", + "sea_duck", + "c_trachomatis", + "bullock", + "greater_scaup", + "cockroach", + "wren", + "franklin's_gull", + "hazel_grouse", + "pearl_oyster", + "eastern_woodrat", + "gimpel", + "pinctada_margaritifera", + "common_booklouse", + "european_bittern", + "magpie", + "pieris_melete", + "potamophis_striatula", + "jerboa", + "donald_duck", + "nathusius's_pipistrelle", + "cafard", + "salmo_salar", + "maasbanker", + "sanicula_europaea", + "red_fox", + "adelie", + "rainbow_smelt", + "iller", + "moose", + "grackle", + "bengal_tiger", + "edible_dormouse", + "taguan", + "sarcophile", + "heath_fritillary", + "eastern_cottontail", + "coho_salmon", + "wisent", + "marten", + "genus_staphylococcus", + "sirenian", + "black_rhinoceros", + "berner_sennenhund", + "brock", + "suslik", + "barn_swallow", + "thorny_skate", + "vulture", + "araguato", + "sea_lily", + "martes_foina", + "sand_snake", + "baldpate", + "porpoise", + "wild_cinnamon", + "sea_catfish", + "chicken", + "millipede", + "l_monocytogenes", + "ictiobus_niger", + "cape_lobster", + "tarrock", + "sable", + "capreolus_capreolus", + "bombyx", + "branta_bernicla", + "foumart", + "herpes_zoster", + "mountain_devil", + "cavia_cobaya", + "woodcock", + "arthropoda", + "beaver", + "mahonia_aquifolium", + "cabbageworm", + "ringdove", + "barramunda", + "common_shelduck", + "three_spined_stickleback", + "nitrobacteria", + "pagellus_centrodontus", + "tamanoir", + "gallinaceous", + "quack_quack", + "eastern_meadowlark", + "scleropages", + "new_england_aster", + "sheltie", + "willow_aster", + "human_immunodeficiency_virus", + "green_woodpecker", + "field_mouse", + "gull", + "sea_urchin", + "lychnis_flos_cuculi", + "tortrix", + "hemipteron", + "merle", + "blackie", + "sand_tiger", + "acorn_barnacle", + "sea_star", + "capercaillie", + "sitta_canadensis", + "mantis", + "primula_vulgaris", + "grey_partridge", + "wound_tumor_virus", + "european_flatfish", + "herpes_zoster_virus", + "varicella_zoster_virus", + "gymnorhina", + "herpes_simplex_1", + "guinea_pig", + "michelia_compressa", + "squirrel", + "cat_translations", + "h_pylori", + "green_tea", + "mane", + "common_kestrel", + "santa_gertrudis", + "common_yellowwood", + "animal_virus", + "diving_duck", + "respiratory_syncytial_virus", + "whippet", + "lavatera_arborea", + "zeus_faber", + "blattella_nipponica", + "by_catch", + "salvelinus_fontinalis", + "western_chimpanzee", + "barramundi", + "potato_yellow_dwarf_virus", + "barnacle", + "northern_shoveler", + "yorkshire_terrier", + "lemming", + "wall_creeper", + "peregrine", + "eagle", + "abudefduf_saxatilis", + "sea_lamprey", + "kingfisher", + "western_capercaillie", + "remilegia_australis", + "patronne", + "pigeon_pea", + "giant_armadillo", + "hungarian_partridge", + "vole", + "water_rat", + "potamogale", + "constrictor_constrictor", + "gorilla_gorilla", + "dormouse", + "fire_salamander", + "graylag", + "grouse", + "sergeant_major", + "shad", + "roseate_spoonbill", + "icterid", + "angelshark", + "chelydra", + "sea_louse", + "seagull", + "cat_flea", + "martes_zibellina", + "polecat", + "irish_wolfhound", + "southern_lapwing", + "snipe", + "erignathus", + "sea_horse", + "eider", + "capiz", + "snub_nosed", + "mistle_thrush", + "northern_cardinal", + "arvicola", + "sea_otter", + "wolf_spider" + ], + "ORG": [ + "yulia_tymoshenko", + "dominion", + "ida", + "more_than", + "san_marco", + "treasury", + "shinto", + "sand_lake", + "jehovah's_witnesses", + "exact_sciences", + "town_centre", + "foreign_country", + "justice", + "our_lady_of_sorrows", + "all_nations", + "mitsui_zaibatsu", + "shiah", + "le_figaro", + "doi", + "de_facto_segregation", + "lower_house", + "free_will", + "tammany", + "sabaoth", + "marshals", + "protestant_church", + "military", + "municipal_government", + "gironde", + "drug_enforcement_administration", + "high_commission", + "tom_thumb", + "christian_association", + "wicca", + "dixiecrats", + "new_frontier_party", + "one_way", + "so_many", + "malignant_tumor", + "all_for", + "paul_cezanne", + "take_turn_for_better", + "jan_mayen", + "battalion", + "take_after", + "ins", + "three_stars", + "nist", + "shakers", + "transportation", + "in_place", + "lower_class", + "not_moving", + "kemal_ataturk", + "all_powerful", + "be_at", + "shua", + "aa", + "nasa", + "saint_nicholas", + "airforce", + "second_empire", + "at_home", + "arda", + "hinayana", + "in_vivo", + "palestine_authority", + "huang_he", + "isi", + "bollywood", + "ang", + "fema", + "united_states_government", + "la_trobe", + "too_many", + "hassidim", + "in_utero", + "foreign_languages", + "management_consulting", + "st_christopher", + "europol", + "schutzstaffel", + "franco_british", + "in_flight", + "bakkie", + "al_qanoon", + "sankt_andreasberg", + "upper_class", + "chorus_line", + "international_association", + "u_s_army_special_forces", + "dippers", + "off_and_on", + "abu_ali_al_husain_ibn_abdallah_ibn_sina", + "ad_libitum", + "old_town", + "domestic_violence", + "once_again", + "non_plus_ultra", + "haganah", + "educational_institution", + "up_country", + "opera_company", + "care_for", + "karaites", + "after_all", + "porte", + "college", + "central_city", + "san_francisco", + "chambered_nautilus", + "un", + "social_democratic_party", + "war_machine", + "fincen", + "on_site", + "exec", + "from_time_to_time", + "chongqing_university", + "thomas_doubting_apostle", + "why_not", + "old_church", + "trade_union", + "no_frills", + "electoral_college", + "village_community", + "zen_buddhism", + "lo_fi", + "first_international", + "i_o_data", + "flashmob", + "papa_john's", + "st_mary_magdalene", + "v\u0129nh_long", + "in_common", + "nara", + "one_parent_family", + "va", + "music_school", + "saint_george", + "park_chung_hee", + "cathars", + "my_school", + "saint_peter_apostle", + "col_legno", + "no_paper_society", + "no_worries", + "machine_shop", + "non_literate_society", + "shopping_centre", + "sc", + "sainte_ursule", + "han_dynasty", + "third_party", + "face_amount_certificate_company", + "militant_tendency", + "son_goku", + "by_way", + "church_of_christ_scientist", + "at_all", + "albigenses", + "gao", + "khalsa", + "philosophy_department", + "united_states", + "dot", + "prohibition_party", + "marine_department", + "mon_ami", + "we_all", + "s_hertogenbosch", + "nanak", + "international_organization", + "mahayana", + "as_yet", + "core", + "allies", + "take_part", + "ad_lib", + "one_up", + "japan_railways", + "girl_guides", + "art_collection", + "british_council", + "saint_vincent", + "freemasonry", + "ec", + "golf_club", + "communications_corporation", + "matteo_ricci", + "john_tuzo_wilson", + "peasant_party", + "teamsters_union", + "highschool", + "saint_helena", + "plexus_celiacus", + "medical_profession", + "don_juan", + "petty_bourgeoisie", + "sea_power", + "sea_wolves", + "training_college", + "oni", + "scottish_law", + "ai", + "garden_party", + "new_world", + "all_one's_family", + "once_upon_time", + "closed_corporation", + "academic_institution", + "christ_child", + "superior_court", + "landed_gentry", + "down_below", + "have_nice_meal", + "ds", + "military_government", + "japan_socialist_party", + "chiang_mai", + "town_hall", + "et_al", + "gop", + "physical_sciences", + "sao_paulo", + "dia", + "dominican_order", + "civil_service", + "mitsubishi_zaibatsu", + "st_kilda", + "winnie_pooh", + "gatt", + "lablink", + "old_guard", + "department_of_chemistry", + "sayeret", + "reform_judaism", + "as_new", + "masonry", + "tantrism", + "ab_initio", + "mutawa", + "shivaism", + "parasport", + "le_mans", + "foreign_mission", + "saint_lucian", + "shopping_mall", + "cathari", + "christian_science", + "honky_tonk", + "shaktism", + "doe", + "ne_plus_ultra", + "caf\u00e9_au_lait", + "shia", + "no_parking", + "nha_trang", + "de_jure_segregation", + "little_by_little", + "on_or_about", + "fletc", + "quakers", + "school", + "german_language", + "ice_sports", + "saktism", + "one_way_street", + "national_fascist_party", + "mounties", + "defense", + "sub_society", + "ruling_class", + "and_also", + "brahmanism", + "rabindranath_tagore", + "trades_union", + "gestapo", + "one_family", + "de_novo", + "jelly_beans", + "curly_heads", + "shah_alam", + "li_keqiang", + "all_you_can_eat", + "enfants_terribles", + "austin_friars", + "justice_party", + "mount_olivet", + "kashag", + "fibonacci_sequence", + "percussion_section", + "on_board", + "hasidism", + "chiang_chung_cheng", + "de_luxe", + "santa_sophia", + "white_house", + "pressure_points", + "al_muhajiroun", + "pac", + "counterterrorist_center", + "what_is", + "mental_hospital", + "mormons", + "fishnet_stockings", + "drug_company", + "very_friendly", + "nestorian_church", + "stara_zagora", + "lake_of_woods", + "venereal_disease", + "red_sea", + "li_fi", + "man_overboard", + "kokka", + "conservative_judaism", + "st_nicholas", + "reserve_officers", + "chassidim", + "maquis", + "catholic_church", + "troops", + "not_too", + "le_monde", + "upper_lower_class", + "heinrich_theodor_boell", + "methodists", + "sao_tome", + "green_hills", + "who_are_you", + "same_sex_marriage", + "i_ching", + "chiang_rai", + "saint_joseph", + "al_hijrah", + "al_jazeera", + "carmaker", + "craft_union", + "my_name_is", + "art_union", + "from_this", + "non_market_economy", + "chewing_gum", + "waldenses", + "cum_laude", + "disa", + "assembl\u00e9e_nationale", + "s\u00e3o_paulo", + "marines", + "europe", + "po", + "addis_ababa", + "soviets", + "drug_cartel", + "war_department", + "dag_hjalmar_agne_carl_hammarskjold", + "one_eyed", + "be_mad", + "mount_carmel", + "man_made", + "mossad", + "hare_krishna", + "mentally_retarded", + "latter_day_saints", + "ferdinand_magellan", + "drug_enforcement_agency", + "company_union", + "christmas_lights", + "capetian_dynasty", + "my_company", + "industrial_union", + "amnesty_international", + "up_to_date", + "hollywood", + "imperial_council", + "assumption_of_mary", + "by_day", + "cid", + "hwang_ho", + "ursa_major", + "nicu", + "hasidim", + "care_bears", + "kurt_godel", + "charles_babbage", + "central_bank", + "saint_barth\u00e9lemy", + "lake_superior", + "vested_interest", + "sturmabteilung", + "vaishnavism", + "city_center", + "in_this", + "custom_house", + "progressive_conservative_party", + "socialist_international", + "who", + "chasidim", + "los_angeles", + "nato", + "wine_tasting", + "mass_media", + "caf\u00e9_con_leche", + "guardian_spirit", + "baltimore_orioles", + "seven_kingdoms", + "no_time_to_lose", + "anno_domini", + "sivaism", + "anti_antifa", + "federal_department", + "opposition_party", + "mathematics_department", + "upper_crust", + "other_way_around", + "ad_hoc", + "standing_stone", + "this_evening", + "diplomatic_mission", + "roman_catholic_church", + "my_family", + "collective_farm", + "notre_dame_de_montauban", + "city_hall", + "mi", + "vaisnavism", + "students_union", + "state_council", + "anchor_line", + "in_situ", + "dunkers", + "transportation_company", + "st_francis", + "democratic_liberal_party", + "non_party", + "sa", + "federal_police", + "middle_class", + "paramount_pictures", + "liberal_democrat_party", + "individual_differences", + "i_love_you", + "andromeda_galaxy", + "bureau_of_justice_assistance", + "international_organisation", + "doc", + "saint_lawrence_river", + "med_school", + "eurasian_kingfisher", + "civic_association", + "caesalpinia_coriaria", + "hot_sauce", + "at_grade", + "have_family", + "people's_alliance_party", + "military_academy", + "bubble_gum", + "st_john's", + "marching_band", + "anthropology_department", + "correspondence_school", + "al_ain", + "golden_age", + "down_with", + "yangtze_kiang", + "holy_family", + "aquinas", + "port_said", + "military_intelligence", + "taoism", + "ace", + "red_cross", + "aclant", + "industrial_park", + "commerce", + "now_and_then", + "reit", + "roman_law", + "afisr", + "blue_jeans", + "war_memorial", + "penal_code", + "streptococcus_pyogenes", + "executive_department", + "brahminism", + "eu", + "one_hundred_percent", + "st_mary's_church", + "first_quarter", + "chang_jiang", + "little_red_riding_hood", + "augustinian_hermits", + "bee's_knees", + "face_off", + "las_palmas", + "labour_union", + "naval_underwater_warfare_center", + "north_eastern", + "hirundo_rustica", + "our_party", + "haredi", + "keys", + "department_of_justice", + "all_hallows", + "scorched_earth", + "in_vitro", + "great_council", + "isn", + "house_of_lords", + "st_lucia", + "guomindang", + "all_people", + "yellow_river", + "democratic_socialist_party", + "al_quds", + "s\u00e3o_tom\u00e9", + "non_linear", + "liberal_democratic_party", + "maritime_industry", + "bundesbank", + "global_village", + "seamen's_union", + "van_gogh", + "three_sisters", + "olympic_village", + "democratic_progressive_party", + "united_states_post_office" + ], + "LOCATION": [ + "al_jazeera", + "on_road", + "la_plata", + "s_train", + "in_case", + "da_gamma", + "plantago_lanceolata", + "st_eustatius", + "blue_whale", + "you're_welcome", + "mia_mia", + "mu_guiying", + "don't_mention_it", + "arbor_vitae", + "alt_treptow", + "for_good_measure", + "hippodrome", + "bangka_belitung", + "dos_hermanas", + "trifolium_pratense", + "so_what", + "railway_station", + "air_force", + "vespucci", + "prince_george's_county", + "green_tea", + "on_street", + "columbus_day", + "sugar_loaf", + "urban_center", + "just_in_case", + "gray_whale", + "park", + "non_plus_ultra", + "abd", + "eryngium_maritimum", + "freshwater", + "corpus_christi", + "two_brothers", + "u.s", + "dark_horse", + "bow_wow", + "business_district", + "united_states_army", + "blue_house", + "s_hertogenbosch", + "department_store", + "college_town", + "in_case_of", + "juarez", + "piet_mondrian", + "la_roche_en_ardenne", + "trifolium_repens", + "santa_fe", + "sint_maarten", + "civil_engineering", + "petasites_hybridus", + "doi_moi", + "de_nada", + "centennial_state", + "country_house", + "national_parliament", + "chang_jiang", + "dog_hole", + "zhu_jiangi", + "in_park", + "christmas_eve", + "shopping_centre", + "greylag_goose", + "man_o_war", + "cape_verde", + "marie_grosholtz", + "trois_rivi\u00e8res", + "allahu_akbar", + "sleeping_beauty", + "shing_wong", + "end_point", + "five_spot", + "saint_patrick", + "on_brink", + "above_all", + "saint_george", + "li_qingzhao", + "three_sisters", + "thomas_doubting_apostle", + "mary_magdalene", + "land", + "changbaishan_tianchi", + "la_mancha", + "huang_he", + "montagu's_harrier", + "all_day", + "white_house", + "eurasian_jay", + "saint_vincent", + "iris_pseudacorus", + "sponge_cake", + "apostle_of_gentiles", + "blue_mountains", + "pieris_rapae", + "technical_school", + "north_island", + "police_station", + "joseph_louis_gay_lussac", + "plantago_major", + "tussaud", + "saint_lawrence_river", + "nuphar_lutea", + "on_board", + "date_palm", + "holy_land", + "bon_voyage", + "vaccinium_oxycoccos", + "no_problem", + "training_center", + "plantago_media", + "gay_lussac", + "wba", + "mondrian", + "two_sisters", + "all_blacks", + "my_pleasure", + "tom_thumb", + "black_forest", + "saint_christopher", + "alnus_glutinosa", + "saint_nicholas", + "all_countries", + "new_year's_day", + "cape_of_good_hope", + "usa", + "st_albans", + "saint_valentine's_day", + "west_bromwich", + "saint_lucia", + "field", + "west_papua", + "hwang_ho", + "aussig", + "coal_tit", + "little_egret", + "pension_fund", + "bare_top", + "small_tortoiseshell", + "valentine's_day", + "salt_water", + "sea_holly", + "saint_peter", + "hat_yai", + "no_worries", + "here_be_dragons", + "arena", + "kriss_kringle", + "two_groups", + "sri_lanka", + "air_corps", + "zhu_jiang", + "river_basin", + "villa_lobos", + "main_station", + "star_of_bethlehem", + "lake_st_clair", + "your_home", + "mount_of_olives", + "southern_cross", + "catholic_church", + "yangtze_kiang", + "st_malo", + "three_amigos", + "scutellaria_galericulata", + "royal_stables", + "ritz_carlton", + "central_business_district", + "market_cross", + "san_joaquin_river", + "botanical_garden", + "temple_buildings", + "cordon_bleu", + "new_year's_eve", + "red_sea", + "forget_me_not", + "saint_lawrence", + "kryvyi_rih", + "downtown", + "virgin_mary", + "town_walls", + "qi_baishi", + "court", + "great_egret", + "pieris_brassicae", + "there_are", + "whooper_swan", + "black_alder", + "heitor_villa_lobos", + "qingming", + "holy_family", + "vale_of_glamorgan", + "suburban_railway", + "al_ain", + "metropolitan_region", + "trifolium_dubium", + "saint_barbara", + "field_house", + "fresh_water", + "pterocarpus_indicus", + "national_assembly", + "santa_claus", + "red_water", + "justice_of_peace", + "apostle_paul", + "pot_hole", + "st_patrick", + "delonix_regia", + "iron_cross", + "town_hall", + "never_never", + "psychiatric_hospital", + "prunus_avium" + ], + "DATE": [ + "off_day", + "market_day", + "name_day", + "by_and_by", + "anomalistic_month", + "patriot's_day", + "dog_days", + "this_evening", + "before_long", + "over_there", + "happy_hour", + "all_hallows_day", + "v_e_day", + "all_hallows", + "these_days", + "saint_valentine's_day", + "solar_month", + "fourth_dimension", + "in_time", + "new_year's_eve", + "here_and_now", + "immaculate_conception", + "summer_school", + "v_j_day", + "man_hour", + "infant_deathrate", + "all_saints_day", + "be_vigilant_in_peacetime", + "female_child", + "new_moon", + "in_one_case", + "solar_constant", + "rainy_day", + "hunting_season", + "shaaban", + "theatrical_season", + "islamic_calendar", + "january_1", + "d_day", + "face_time", + "in_long_run", + "church_calendar", + "off_year", + "day_shift", + "one_way_light_time", + "sha'ban", + "quasimodogeniti", + "christmas_day", + "corpus_christi", + "v_day", + "may_day", + "all_souls_day", + "twelfth_night", + "day_watch", + "new_year", + "eleventh_hour", + "just_minute", + "lunar_month" + ], + "PERSON": [ + "han_xin", + "han_seung_soo", + "dai_di", + "in_re", + "li_chan", + "hai_rui", + "cui_wei", + "li_ying", + "li_jun", + "li_hongzhi", + "blessed_virgin", + "prince_albert", + "li_chaowei", + "julius_caesar", + "ha_ha", + "st_dominic", + "li_ruzhen", + "al_gore", + "mount_hubbard", + "seleucus", + "li_chen", + "h_g_wells", + "li_chun", + "kim_dae_jung", + "du_fu", + "hai_he", + "han_yu", + "han_fei", + "bo_gu", + "ho_ho", + "d_c", + "li_minyong", + "albert_francis_charles_augustus_emmanuel", + "saint_vincent", + "su_yijian", + "li_guang", + "li_yuan", + "li_zhao", + "zi_lu", + "la_grange", + "li_zhe", + "ai_qing", + "m_f", + "st_mary_magdalene", + "li_fuchun", + "me_too", + "joe_bloggs", + "li_ye", + "st_vincent", + "i_ching", + "cui_hong", + "kim_young_sam", + "e_o_wilson", + "st_ambrose", + "ma_chao", + "min_zhong", + "li_baiyao", + "william_playfair", + "li_zicheng", + "ma_zhiyuan", + "don_delillo", + "li_na", + "by_means_of", + "dai_mingshi", + "li_huaiyuan", + "ji_yun", + "li_cui", + "igor_ivanovich_sikorsky", + "saint_ambrose", + "he_chao", + "li_zhaoxing", + "dong_zhuo", + "cui_hao", + "li_zongren", + "bi_gan", + "li_delin", + "margaret_munnerlyn_mitchell", + "e_e_cummings", + "fu_hao", + "li_jiancheng", + "peter_higgs", + "black_bee", + "han_zheng", + "fu_jian", + "li_ao", + "black_partridge", + "apostle_of_gentiles", + "al_mansur", + "bi_sheng", + "edward_osborne_wilson", + "roger_eliot_fry", + "li_changchun", + "li_fang", + "li_hung_chang", + "li_ling", + "ni_guizhen", + "li_ning", + "li_shimin", + "philip_ii_of_macedon", + "dan_brown", + "kim_yong_nam", + "ma_liang", + "li_yu", + "ke_shaomin", + "li_zhifu", + "he_she", + "lei_feng", + "cui_jian", + "li_heng", + "han_han", + "walther_richard_rudolf_hess", + "de_witt", + "fu_ling", + "ma_chu", + "n_ball", + "saul_of_tarsus", + "min_dong", + "willard_frank_libby", + "kim_jong_il", + "li_he", + "mi_fu", + "george_v", + "al_amin", + "li_shangyin", + "li_bai", + "li_yanshou", + "li_gongpu", + "igor_sikorsky", + "su_yu", + "li_chongmao", + "la_la", + "du_wei", + "in_memory", + "su_zhe", + "su_xun", + "t_bone_steak", + "dong_dong", + "li_tie", + "frederick_great", + "li_yuanhao", + "peter_dawson", + "li_peng", + "li_kui", + "seleucus_i_nicator", + "edward_franklin_albeen", + "peter_brook", + "ma_zhongxi", + "li_shizhen", + "li_gefei", + "carl_david_anderson", + "ma_gu", + "di_renjie", + "su_wu", + "li_zhi", + "gaius_julius_caesar", + "wieland", + "para_rubber_tree", + "zeno_of_citium", + "li_zhan", + "john_dory", + "maxwell_anderson", + "boletus_edulis", + "yo_yo", + "mei_cheng", + "li_jing", + "rudolf_hess", + "k_drama", + "li_lianjie", + "han_shichang", + "li_dan", + "dr_watson", + "ge_hong", + "e_t_hoffmann", + "da_qiao", + "saint_john_apostle", + "hearing_officer", + "ji_lu", + "herbert_george_wells", + "han_yanzhi", + "li_kuo", + "cha_cha", + "li_boyuan", + "li_tianlu" + ], + "RACE": [ + "filipino", + "irishwoman", + "native_people", + "middle_eastern", + "islander", + "latino", + "french", + "polynesian", + "north_korean", + "frenchlike", + "turk", + "irish", + "latin", + "amerindian", + "australian_person", + "spanish", + "australian_aborigine", + "vietnamese", + "autochthon", + "malagasy_person", + "korean", + "sassenach", + "jewish", + "african", + "irishman", + "mestiza", + "persian_person", + "irish_person", + "white", + "chinese", + "american", + "american_person", + "irelander", + "japanese", + "frenchwoman", + "south_american", + "negro", + "latina", + "german_person", + "kazakh", + "danish_person", + "russian_person", + "amerind", + "frenchman", + "americans" + ], + "GENDER": [ + "old_gentleman", + "women", + "miss", + "mademoiselle", + "guy", + "girl", + "gentleman", + "matron", + "girls", + "old_chap", + "old_girl", + "woman", + "men", + "olding", + "chap", + "dame", + "boy", + "male", + "boys", + "pucelle", + "old_woman", + "guido", + "maid", + "senorita", + "lassie", + "tribade", + "transgender", + "old_men", + "lass", + "young_man", + "ladies", + "damsel", + "man", + "gentlemen", + "gal", + "maiden", + "lady", + "chaps", + "fair_sex" + ], + "LANGUAGE": [ + "danish", + "panjabi", + "shona", + "catalan", + "bengali", + "russian", + "rundi", + "venda", + "interlingue", + "bambara", + "kashmiri", + "east_franconian", + "kongo", + "sundanese", + "smith", + "akan", + "lithuanian", + "greek", + "swedish", + "sindhi", + "blacksmith", + "north_marquesan", + "pali", + "polish", + "navajo", + "romanian", + "ganda", + "south_marquesan", + "aymara", + "french_guianese", + "manx", + "welsh", + "french", + "persian", + "malayalam", + "basc", + "arabic", + "finnish", + "georgian", + "saint_lucian", + "faroese", + "spanish", + "fulah", + "galician", + "kanuri", + "sinhala", + "belarusian", + "hindi", + "alviri_vidari", + "assamese", + "chamorro", + "franco_proven\u00e7al", + "arpetan", + "guarani", + "zhuang", + "herero", + "german", + "sango", + "orloff", + "chinese", + "walloon", + "esperanto", + "portuguese", + "bashkir", + "japanese", + "pa_hng", + "komi", + "lingala", + "sechuana", + "hausa", + "icelandic", + "hungarian", + "english", + "wolof", + "cree", + "cornish", + "lao", + "kikuyu", + "speech", + "malay", + "tagalog", + "dutch", + "ido", + "kazakh", + "marathi", + "malagasy", + "romansh", + "kalaallisut", + "quechua", + "chichewa", + "chechen", + "ese_ejja", + "samoan", + "marshallese", + "tonga", + "kannada", + "corsican" + ], + "RELIGION_MEMBER": [ + "anabaptist", + "orangeman", + "anglican_catholic", + "blackfriar", + "dunkard", + "guru", + "augustine", + "shaktist", + "protestant", + "pentecostal", + "mulla", + "moor", + "mandean", + "dunker", + "pentecostalist", + "wesleyan", + "wahhabi", + "brother", + "parsee", + "chartreux", + "cistercian", + "moonie", + "old_catholic", + "benedictine", + "melchite", + "atheist", + "austin_friar", + "augustinian", + "congregationalist", + "carthusian", + "catholic", + "roman_catholic", + "muhammaden", + "melkite", + "mormon", + "jihadist", + "shivaist", + "shaker", + "shiite", + "vaishnava", + "saracen", + "mussulman", + "muhammadan", + "baptist", + "methodist", + "paynim", + "carmelite", + "christian", + "tunker", + "mandaean", + "mollah", + "sister", + "mohammedan", + "mullah", + "puritan", + "mormons", + "trappist", + "sunni", + "franciscan", + "satanist", + "holy_father", + "parsi", + "nazarene", + "presbyterian", + "wahabi", + "tractarian", + "catholic_pope", + "friend", + "jain", + "mon", + "sufi", + "episcopalian", + "christian_scientist", + "sunnite" + ], + "RELIGION": [ + "tractarianism", + "krishnaism", + "vedism", + "zen", + "methodism", + "shinto", + "judaism", + "darsana", + "puritanism", + "mahdism", + "hinayana", + "adventism", + "presbyterianism", + "vedanta", + "brahminism", + "albigensianism", + "catharism", + "lamaism", + "buddhism", + "confucianism", + "manichaeanism", + "zen_buddhism", + "jainism", + "puseyism", + "mandaeism", + "mennonitism", + "salafism", + "catholicism", + "calvinism", + "shaktism", + "islam", + "vishnuism", + "rastafarianism", + "roman_catholicism", + "parsiism", + "hinduism", + "shingon", + "chabad", + "congregationalism", + "sikhism", + "christian_science", + "hsuan_chiao", + "bahaism", + "cathari", + "eastern_catholicism", + "shivaism", + "sunni_islam", + "manichaeism", + "sivaism", + "brahmanism", + "wesleyism", + "atheism", + "romanism", + "wahabism", + "mormon_church", + "ismailism", + "wicca", + "wesleyanism", + "christianity", + "shintoism", + "parseeism", + "mimamsa", + "anabaptism", + "trinitarianism", + "donatism" + ], + "FAC": [ + "arnold_schoenberg", + "t_cell", + "sublime_porte", + "holy_spirit", + "triumphal_arch", + "presidential_palace", + "police_station", + "college_town", + "schoenberg", + "louis_vuitton", + "daniel_o'connell", + "peter_great", + "transfer_station", + "industrial_park", + "schonberg", + "peter_i", + "fernand_leger", + "notre_dame_cathedral", + "d_frame", + "central_station", + "papeda", + "standing_stone", + "roman_basilica", + "three_countries", + "marine_terrace", + "catholic_church", + "grade_school", + "plaza", + "ministry_of_posts_and_telecommunications", + "curtain_wall", + "saint_joseph", + "high_window", + "san_sebasti\u00e1n", + "sea_wall", + "mineralnye_vody", + "market_place", + "saint_james_apostle", + "roman_arch", + "mall", + "max_muller", + "petropavlovsk", + "garden_city", + "saint_lucia", + "music_library", + "guardian_angels", + "st_james", + "primary_school", + "bus_terminal", + "arnold_schonberg", + "our_lady_of_victories", + "control_center", + "titus_livius", + "on_call", + "elementary_school", + "art_gallery", + "dog_pound", + "this_evening", + "our_lady_of_sorrows", + "saint_peter", + "petropavlovsk_kamchatsky", + "shopping_mall", + "saint_pancras", + "popular_front", + "gold_mine", + "post_office", + "western_wall", + "friedrichshain_kreuzberg", + "st_john_baptist", + "medical_school" + ], + "UNION": [ + "general_union", + "in_house_union", + "yellow_union", + "itu", + "professional_association", + "labor_union", + "labour_union", + "united_mine_workers", + "federal_union", + "international_telecommunications_union", + "international_telecommunication_union", + "iww", + "united_mine_workers_of_america", + "company_union", + "christian_democratic_union", + "i.w.w", + "enterprise_union" + ], + "PERSON_PRONOUN": [ + "thou", + "hers", + "myself", + "yourself", + "oneself", + "i", + "herself", + "thee", + "he", + "yourselves", + "mine", + "notre", + "his", + "y_all", + "our", + "that_person", + "ourselves", + "her", + "she", + "on_one's_own", + "him", + "ours", + "i_or_me", + "we", + "thy", + "me", + "you", + "themselves", + "my", + "your", + "tech", + "lhe", + "thine", + "kalian", + "by_oneself", + "yours", + "us" + ], + "BIO_CHEM_ENTITY": [ + "parabanic_acid", + "lauryl_alcohol", + "c_reactive_protein", + "ni_resist", + "d_fructose", + "plasminogen_activator", + "cool_water", + "anti_m\u00fcllerian", + "n_methylethanolamine", + "insulin_dependent_diabetes_mellitus", + "xanthinoxidase", + "dipotassium_sulfide", + "d_octopine", + "polyvinyl_chloride", + "pancreatic_polypeptide", + "sassafras_oil", + "appetite_for", + "old_fashioned", + "almond_oil", + "bile_salt", + "l_glyceraldehyde", + "chlormequat_chloride", + "edward_thatch", + "d_glyceraldehyde", + "polylactide", + "wheat_germ", + "diethyl_ether", + "bitter_almond_oil" + ], + "QUANTITY": [ + "common_multiple", + "one_eighth", + "rupee", + "one_fourth", + "parking_garage", + "one_third", + "el_salvadoran_monetary_unit", + "sterling", + "calorie", + "voltampere", + "circulating_decimal", + "two_thirds", + "danish_krone", + "one_seventh", + "shilling", + "d_mark", + "planck's_constant", + "three_stranded", + "schilling", + "dinar", + "not_at_all", + "tone", + "krona", + "ton", + "planck_constant", + "one_tenth", + "one_hundredth", + "dollar", + "hair's_breadth", + "riyal", + "nautical_mile", + "one_at_time", + "g", + "circular_measure", + "of_century", + "malawi_kwacha", + "rial", + "one_sixth", + "one_ninth", + "austrian_schilling", + "one_fifth", + "krone", + "one_millionth", + "pound", + "pa_anga", + "parking_lot", + "gasterosteus_aculeatus", + "pond", + "touch_typing", + "complex_fraction", + "cosmological_constant", + "drag_coefficient", + "face_to_face", + "deutschmark", + "temperature_unit", + "volt_ampere", + "valet_parking", + "anders_celsius", + "all_inclusive", + "ezra_loomis_pound", + "force_unit", + "nz" + ], + "LAW": [ + "maritime_law", + "class_action", + "constructive_possession", + "p_l", + "first_amendment", + "judicial_branch", + "cross_examination", + "bja", + "dairy_products", + "civil_rights", + "law_enforcement", + "notary_public", + "marital_status", + "civil_law", + "final_judgment", + "general_verdict", + "jus_civile", + "ne_bis_in_idem", + "international_law", + "attorney_general", + "divorce_lawyer", + "chief_justice", + "direct_examination", + "non_prosequitur", + "defective_pleading", + "supreme_court", + "joint_resolution", + "defense_attorney", + "criminal_code", + "federal_bureau_of_investigation", + "sui_generis" + ], + "TITLE": [ + "mister", + "sir", + "mr", + "ma_am", + "ms", + "missus" + ], + "POLITICAL_PARTY": [ + "pirate_party", + "political_party", + "conservative_party", + "states_rights_democratic_party", + "labor_party", + "constitutional_democratic_party", + "green_party", + "constitutional_union_party", + "gironde", + "free_soil_party", + "national_party", + "democratic_republican_party", + "labour_party", + "ba_ath_party", + "progressive_party", + "republican_party", + "people_first_party", + "political_opposition", + "bharatiya_janata_party", + "federalist_party", + "labour", + "labor", + "russian_communist_party", + "kuomintang", + "socialist_labor_party", + "british_labour_party", + "know_nothing_party", + "greenback_party", + "liberal_party", + "christian_democratic_party", + "liberty_party", + "black_panthers", + "american_federalist_party", + "workers_party", + "whig_party", + "communist_party", + "same_political_party", + "new_korea_party", + "dixiecrats", + "reformist_party", + "people's_party", + "japanese_communist_party", + "populist_party", + "anti_masonic_party", + "nazi_party", + "minority_party", + "free_democratic_party", + "radical_party", + "american_party", + "parliamentary_party", + "national_congress_party", + "socialist_party", + "agrarian_party", + "nationalist_party", + "farmer_labor_party", + "american_labor_party", + "democratic_party", + "bull_moose_party", + "new_democratic_party", + "new_conservative_party", + "national_socialist_german_workers_party", + "proletarian_party", + "federal_party", + "australian_labor_party", + "nationalsozialistische_deutsche_arbeiterpartei", + "people's_action_party", + "opposition", + "reform_party", + "worker's_party", + "guomindang", + "moderate_party" + ], + "GPE": [ + "la_pampa", + "st_john_baptist", + "sea_peoples", + "north_region", + "st_christopher", + "st_peter", + "northern_region", + "st_vitus", + "white_house", + "saint_domingue", + "st_jude", + "kotte", + "dar_es_salaam", + "old_town", + "saint_peter_apostle", + "valentine_day", + "ivan_cankar", + "rio_grande_do_sul", + "sint_maarten", + "pandanus_tectorius", + "st_matthew", + "human_rights", + "circuit_intendant", + "holy_spirit", + "german_empire", + "nam_\u0111\u1ecbnh", + "sugar_loaf", + "n_djamena", + "hagia_sophia", + "saint_peter", + "heiligenberg", + "saint_andrew", + "central_america", + "simon_peter", + "s\u00e3o_tom\u00e9", + "little_auk", + "hagia_sofia", + "human_right", + "our_lady_of_sorrows", + "school_district", + "gran_canaria", + "china_rose", + "\u00fc_tsang", + "industrial_park", + "la_tuque", + "saint_george", + "ponta_delgada", + "saint_barbara", + "holy_land", + "valentine's_day", + "rio_tinto", + "al_andalus", + "thousand_islands", + "white_gold", + "south_region", + "la_rochelle", + "saint_andrew_apostle", + "town_square", + "sugarloaf_mountain", + "borassus_flabellifer", + "our_lady", + "sveti_nikole", + "hibiscus_rosa_sinensis", + "charlottenburg_wilmersdorf", + "notre_dame_du_mont_carmel", + "mount_tai", + "la_gomera", + "st_louis", + "santa_sofia", + "tr\u00e0_vinh" + ], + "POLITICAL_PARTY_MEMBER": [ + "menshevik", + "potemkin", + "federalist", + "labourite", + "communist", + "communistic", + "fabian", + "potyokin" + ], + "EVENT": [ + "c_est_la_vie", + "one_victory", + "para_alpine", + "fleur_de_lys", + "electronic_game", + "last_judgment", + "game_design", + "world_exposition", + "sing_sing", + "no_way_out", + "fleur_de_lis", + "grand_prix", + "castile_and_le\u00f3n", + "war_victims", + "up_and_coming", + "such_is_life", + "saint_david's" + ], + "ANAT": [ + "quadriceps_femoris", + "medial_rectus", + "corrugator_supercilii", + "arteria_arcuata", + "tibialis_anticus", + "coccygeal_vertebra" + ], + "MEDICAL_THERAPY": [ + "magnetic_resonance" + ], + "ner_regexes": [ + [ + "PERSON", + "\\D+ \\D+|\\D+ \\D+|\\D+ \\D+|\\D+ \\D+|\\D+ \\D+-\\D+|\\D+ \\D+|\\D+ \\D+|\\D+ \\D+|\\D+ \\D+|\\D+ \\D+-\\D+|\\D+ \\D+ \\D+|\\D+ \\D+ \\D+|\\D+ \\D+ \\D+|\\D+ \\D+ \\D+", + false, + [] + ], + [ + "PERSON", + "\\D+ \\D+|\\D+ \\D+|\\D+ \\D+|\\D+ \\D+|\\D+ \\D+-\\D+|\\D+ \\D+|\\D+ \\D+|\\D+ \\D+|\\D+ \\D+|\\D+ \\D+-\\D+|\\D+ \\D+ \\D+|\\D+ \\D+ \\D+|\\D+ \\D+ \\D+|\\D+ \\D+ \\D+", + false, + [] + ], + [ + "PERSON", + "\\D+ \\D+", + false, + [] + ], + [ + "PERSON", + "\\D+ \\D+|\\D+ \\D+|\\D+ \\D+|\\D+ \\D+|\\D+ \\D+-\\D+|\\D+ \\D+|\\D+ \\D+|\\D+ \\D+|\\D+ \\D+|\\D+ \\D+-\\D+", + false, + [] + ], + [ + "PERSON", + "\\D+ \\D+|\\D+ \\D+|\\D+ \\D+|\\D+ \\D+|\\D+ \\D+|\\D+ \\D+|\\D+ \\D+ \\D+", + false, + [] + ], + [ + "PERSON", + "\\D+ \\D+|\\D+ \\D+ \\D+|\\D+ \\D+ \\D+|\\D+ \\D+ \\D+ \\D+|\\D+ \\D+|\\D+ \\D+ \\D+|\\D+ \\D+ \\D+|\\D+ \\D+ \\D+ \\D+", + false, + [] + ], + [ + "DOMAIN_NAME", + "(?i)((?:https?://|www\\d{0,3}[.])?[a-z0-9.\\-]+[.](?:(?:international)|(?:construction)|(?:contractors)|(?:enterprises)|(?:photography)|(?:immobilien)|(?:management)|(?:technology)|(?:directory)|(?:education)|(?:equipment)|(?:institute)|(?:marketing)|(?:solutions)|(?:builders)|(?:clothing)|(?:computer)|(?:democrat)|(?:diamonds)|(?:graphics)|(?:holdings)|(?:lighting)|(?:plumbing)|(?:training)|(?:ventures)|(?:academy)|(?:careers)|(?:company)|(?:domains)|(?:florist)|(?:gallery)|(?:guitars)|(?:holiday)|(?:kitchen)|(?:recipes)|(?:shiksha)|(?:singles)|(?:support)|(?:systems)|(?:agency)|(?:berlin)|(?:camera)|(?:center)|(?:coffee)|(?:estate)|(?:kaufen)|(?:luxury)|(?:monash)|(?:museum)|(?:photos)|(?:repair)|(?:social)|(?:tattoo)|(?:travel)|(?:viajes)|(?:voyage)|(?:build)|(?:cheap)|(?:codes)|(?:dance)|(?:email)|(?:glass)|(?:house)|(?:ninja)|(?:photo)|(?:shoes)|(?:solar)|(?:today)|(?:aero)|(?:arpa)|(?:asia)|(?:bike)|(?:buzz)|(?:camp)|(?:club)|(?:coop)|(?:farm)|(?:gift)|(?:guru)|(?:info)|(?:jobs)|(?:kiwi)|(?:land)|(?:limo)|(?:link)|(?:menu)|(?:mobi)|(?:moda)|(?:name)|(?:pics)|(?:pink)|(?:post)|(?:rich)|(?:ruhr)|(?:sexy)|(?:tips)|(?:wang)|(?:wien)|(?:zone)|(?:biz)|(?:cab)|(?:cat)|(?:ceo)|(?:com)|(?:edu)|(?:gov)|(?:int)|(?:mil)|(?:net)|(?:onl)|(?:org)|(?:pro)|(?:red)|(?:tel)|(?:uno)|(?:xxx)|(?:ac)|(?:ad)|(?:ae)|(?:af)|(?:ag)|(?:ai)|(?:al)|(?:am)|(?:an)|(?:ao)|(?:aq)|(?:ar)|(?:as)|(?:at)|(?:au)|(?:aw)|(?:ax)|(?:az)|(?:ba)|(?:bb)|(?:bd)|(?:be)|(?:bf)|(?:bg)|(?:bh)|(?:bi)|(?:bj)|(?:bm)|(?:bn)|(?:bo)|(?:br)|(?:bs)|(?:bt)|(?:bv)|(?:bw)|(?:by)|(?:bz)|(?:ca)|(?:cc)|(?:cd)|(?:cf)|(?:cg)|(?:ch)|(?:ci)|(?:ck)|(?:cl)|(?:cm)|(?:cn)|(?:co)|(?:cr)|(?:cu)|(?:cv)|(?:cw)|(?:cx)|(?:cy)|(?:cz)|(?:de)|(?:dj)|(?:dk)|(?:dm)|(?:do)|(?:dz)|(?:ec)|(?:ee)|(?:eg)|(?:er)|(?:es)|(?:et)|(?:eu)|(?:fi)|(?:fj)|(?:fk)|(?:fm)|(?:fo)|(?:fr)|(?:ga)|(?:gb)|(?:gd)|(?:ge)|(?:gf)|(?:gg)|(?:gh)|(?:gi)|(?:gl)|(?:gm)|(?:gn)|(?:gp)|(?:gq)|(?:gr)|(?:gs)|(?:gt)|(?:gu)|(?:gw)|(?:gy)|(?:hk)|(?:hm)|(?:hn)|(?:hr)|(?:ht)|(?:hu)|(?:id)|(?:ie)|(?:il)|(?:im)|(?:in)|(?:io)|(?:iq)|(?:ir)|(?:is)|(?:it)|(?:je)|(?:jm)|(?:jo)|(?:jp)|(?:ke)|(?:kg)|(?:kh)|(?:ki)|(?:km)|(?:kn)|(?:kp)|(?:kr)|(?:kw)|(?:ky)|(?:kz)|(?:la)|(?:lb)|(?:lc)|(?:li)|(?:lk)|(?:lr)|(?:ls)|(?:lt)|(?:lu)|(?:lv)|(?:ly)|(?:ma)|(?:mc)|(?:md)|(?:me)|(?:mg)|(?:mh)|(?:mk)|(?:ml)|(?:mm)|(?:mn)|(?:mo)|(?:mp)|(?:mq)|(?:mr)|(?:ms)|(?:mt)|(?:mu)|(?:mv)|(?:mw)|(?:mx)|(?:my)|(?:mz)|(?:na)|(?:nc)|(?:ne)|(?:nf)|(?:ng)|(?:ni)|(?:nl)|(?:no)|(?:np)|(?:nr)|(?:nu)|(?:nz)|(?:om)|(?:pa)|(?:pe)|(?:pf)|(?:pg)|(?:ph)|(?:pk)|(?:pl)|(?:pm)|(?:pn)|(?:pr)|(?:ps)|(?:pt)|(?:pw)|(?:py)|(?:qa)|(?:re)|(?:ro)|(?:rs)|(?:ru)|(?:rw)|(?:sa)|(?:sb)|(?:sc)|(?:sd)|(?:se)|(?:sg)|(?:sh)|(?:si)|(?:sj)|(?:sk)|(?:sl)|(?:sm)|(?:sn)|(?:so)|(?:sr)|(?:st)|(?:su)|(?:sv)|(?:sx)|(?:sy)|(?:sz)|(?:tc)|(?:td)|(?:tf)|(?:tg)|(?:th)|(?:tj)|(?:tk)|(?:tl)|(?:tm)|(?:tn)|(?:to)|(?:tp)|(?:tr)|(?:tt)|(?:tv)|(?:tw)|(?:tz)|(?:ua)|(?:ug)|(?:uk)|(?:us)|(?:uy)|(?:uz)|(?:va)|(?:vc)|(?:ve)|(?:vg)|(?:vi)|(?:vn)|(?:vu)|(?:wf)|(?:ws)|(?:ye)|(?:yt)|(?:za)|(?:zm)|(?:zw))(?:/[^\\s()<>]+[^\\s`!()\\[\\]{};:'\".,<>?\u00ab\u00bb\u201c\u201d\u2018\u2019])?)", + true, + [] + ], + [ + "EMAIL_ADDRESS", + "([a-z0-9!#$%&'*+\\/=?^_`{|.}~-]+@(?:[a-z0-9](?:[a-z0-9-]*[a-z0-9])?\\.)+[a-z0-9](?:[a-z0-9-]*[a-z0-9])?)", + false, + [] + ], + [ + "USER_NAME", + "^[a-z0-9](@[a-z0-9!#$%&'*+\\/=?^_`{|.}~-]+)", + true, + [] + ], + [ + "DATE", + "(?:(?\\D+ \\D+ \\D+|\\D+ \\D+ \\D+|\\D+ \\D+ \\D+|\\D+ \\D+ \\D+|\\D+ \\D+ \\D+|\\D+ \\D+ \\D+|\\D+ \\D+|\\D+ \\D+ \\D+|\\D+ \\D+-\\D+|\\D+ \\D+ \\D+ \\D+|\\D+ \\D+ \\D+|\\D+ \\D+ \\D+|\\D+ \\D+ \\D+|\\D+ \\D+ \\D+|\\D+ \\D+ \\D+|\\D+ \\D+ \\D+|\\D+ \\D+|\\D+ \\D+ \\D+|\\D+ \\D+-\\D+|\\D+ \\D+ \\D+ \\D+", + false, + [] + ], + [ + "PERSON", + "\\D+ \\D+ \\D+|\\D+ \\D+ \\D+|\\D+ \\D+ \\D+|\\D+ \\D+ \\D+|\\D+ \\D+ \\D+|\\D+ \\D+ \\D+|\\D+ \\D+|\\D+ \\D+ \\D+|\\D+ \\D+-\\D+|\\D+ \\D+ \\D+ \\D+|\\D+ \\D+ \\D+|\\D+ \\D+ \\D+|\\D+ \\D+ \\D+|\\D+ \\D+ \\D+|\\D+ \\D+ \\D+|\\D+ \\D+ \\D+|\\D+ \\D+|\\D+ \\D+ \\D+|\\D+ \\D+-\\D+|\\D+ \\D+ \\D+ \\D+", + false, + [] + ], + [ + "PERSON", + "\\D+ \\D+ \\D+|\\D+ \\D+ \\D+|\\D+ \\D+ \\D+ \\D+|\\D+ \\D+|\\D+ \\D+ \\D+", + false, + [] + ] + ], + "FIRST_NAME_FEMALE": [ + "adelaida", + "j\u00falia", + "nydia", + "candelas", + "am\u00e9rica", + "lupita", + "mercedes", + "hortensia", + "luisa", + "consuelo", + "vicenta", + "abiga\u00edl", + "rosaura", + "antonia", + "inmaculada", + "piedad", + "clotilde", + "flor", + "dionisia", + "valentina", + "trini", + "crescencia", + "asunci\u00f3n", + "\u00e1ngela", + "purificaci\u00f3n", + "cloe", + "\u00e1gueda", + "miguela", + "visitaci\u00f3n", + "javiera", + "modesta", + "dolores", + "sandra", + "melania", + "melisa", + "fortunata", + "tecla", + "concepci\u00f3n", + "adelia", + "saturnina", + "serafina", + "evangelina", + "dominga", + "gala", + "eva", + "aurora", + "rosa_mar\u00eda", + "d\u00e9bora", + "olimpia", + "josefa", + "cintia", + "leonor", + "petrona", + "fanny", + "virginia", + "nazaret", + "elvira", + "aroa", + "mar\u00eda", + "selena", + "marina", + "alejandra", + "noelia", + "ver\u00f3nica", + "chelo", + "rufina", + "evelia", + "estela", + "paca", + "s\u00edlvia", + "andrea", + "candela", + "elo\u00edsa", + "isabela", + "esther", + "pastora", + "yolanda", + "luciana", + "guiomar", + "camila", + "\u00farsula", + "juliana", + "\u00e1ngeles", + "ana", + "carmelita", + "julia", + "\u00e1urea", + "jimena", + "elisabet", + "febe", + "azahar", + "encarnacion", + "ana_bel\u00e9n", + "gloria", + "caridad", + "luc\u00eda", + "eligia", + "calixta", + "xiomara", + "clarisa", + "jacinta", + "jos\u00e9", + "gracia", + "irma", + "belen", + "n\u00faria", + "bibiana", + "mar\u00eda_jes\u00fas", + "socorro", + "aina", + "amaya", + "nicolasa", + "paz", + "micaela", + "flavia", + "fidela", + "pilar", + "ramona", + "loreto", + "pac\u00edfica", + "luna", + "paula", + "azucena", + "patricia", + "consuela", + "mia", + "alicia", + "perlita", + "noem\u00ed", + "eufemia", + "maricela", + "malena", + "mar\u00eda_luisa", + "lara", + "lucila", + "prudencia", + "estefan\u00eda", + "anastasia", + "albina", + "carina", + "sonia", + "dorotea", + "sol", + "dafne", + "olga", + "eulalia", + "soledad", + "ar\u00e1nzazu", + "jordana", + "vanesa", + "rebeca", + "mar\u00eda_\u00e1ngeles", + "lorenza", + "eusebia", + "alexandra", + "lola", + "marianela", + "daniela", + "ricarda", + "roc\u00edo", + "maite", + "maribel", + "dulce", + "martina", + "abril", + "elisa", + "encarnita", + "jennifer", + "victoria", + "custodia", + "anselma", + "macaria", + "laura", + "jana", + "casandra", + "gertrudis", + "rosenda", + "cristina", + "amarilis", + "chus", + "esmeralda", + "apolonia", + "julie", + "adora", + "jovita", + "ligia", + "ant\u00f2nia", + "marisa", + "benita", + "genoveva", + "palmira", + "montserrat", + "encarna", + "joaquina", + "amalia", + "te\u00f3fila", + "marcia", + "mariana", + "samanta", + "bernarda", + "fernanda", + "aura", + "feliciana", + "mireia", + "octavia", + "gabriela", + "tania", + "emperatriz", + "florina", + "ascensi\u00f3n", + "zaida", + "mamen", + "delfina", + "lupe", + "blanca", + "y\u00e9ssica", + "viviana", + "mar\u00eda_del_carmen", + "nidia", + "lidia", + "rosal\u00eda", + "rita", + "morena", + "agustina", + "remedios", + "marta", + "elena", + "angelita", + "olalla", + "ximena", + "milagros", + "mar\u00eda_cristina", + "delia", + "sarita", + "violeta", + "magdalena", + "odalis", + "soraya", + "tomasa", + "mar\u00eda_teresa", + "lorena", + "edelmira", + "francisca", + "almudena", + "concha", + "salom\u00e9", + "pascuala", + "rosalva", + "adriana", + "vera", + "cruz", + "rosalina", + "paloma", + "priscila", + "pepita", + "lucia", + "reyna", + "josefina", + "in\u00e9s", + "nadia", + "candelaria", + "calista", + "noa", + "ani", + "narcisa", + "manola", + "f\u00e1tima", + "araceli", + "bel\u00e9n", + "sara", + "nuria", + "gema", + "teresita", + "gisela", + "marisol", + "eva_mar\u00eda", + "maricruz", + "berta", + "encarnaci\u00f3n", + "olivia", + "nayara", + "ariadna", + "alba", + "benigna", + "vilma", + "anunciaci\u00f3n", + "isidora", + "salud", + "ainoa", + 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"mar\u00eda_manuela", + "judith", + "estrella", + "iris", + "regina", + "maxi", + "margarita", + "florinda", + "manuelita", + "alma", + "mar\u00eda_dolores", + "zoraida", + "esperanza", + "fabiola", + "emilia", + "susana", + "b\u00e1rbara", + "ileana", + "nilda", + "rafaela", + "mar\u00eda_pilar", + "oriana", + "lina", + "leocadia", + "br\u00edgida", + "\u00e1gata", + "felipa", + "reyes", + "constanza", + "paola", + "ignacia", + "marita", + "paulina", + "florentina", + "isa", + "felicia", + "mar", + "arcelia", + "teodora", + "emiliana", + "val\u00e8ria", + "griselda", + "diana", + "graciela", + "graciana", + "raquel", + "celia", + "bego\u00f1a", + "reina", + "macarena", + "manuela", + "felicidad", + "anita", + "beatriz", + "maura", + "leticia", + "juana", + "elba", + "fabiana", + "perla", + "adela", + "itziar", + "sof\u00eda", + "aurelia", + "p\u00eda", + "ariel", + "nereida", + "roberta", + "laia", + "cl\u00e0udia", + "marcela", + "chl\u00f3e", + "rosario", + "mayte", + "mar\u00eda_fernanda", + "isabel", + "florencia", + "amor", + "claudia", + "jessica", + "susanita", + "angelina", + "mar\u00eda_jos\u00e9", + "manu", + "matilde", + "hilda", + "teresa", + "maristela", + "natividad", + "cayetana", + "n\u00e9lida", + "amanda", + "leandra", + "georgina", + "eli", + "mirta", + "m\u00e1xima", + "mar\u00eda_bel\u00e9n", + "flora", + "primitiva", + "\u00edngrid", + "valeria", + "roxana", + "carmela", + "bernardita", + "mar\u00eda_carmen", + "dora", + "cecilia", + "emelina", + "pili", + "bienvenida", + "jesusa", + "renata", + "catalina", + "ofelia", + "miriam", + "corona", + "luz", + "\u00e1frica", + "eliana", + "filomena", + "clara", + "ona", + "otilia", + "dorita" + ], + "FIRST_NAME_MALE": [ + "isidro", + "bautista", + "rom\u00e1n", + "atilio", + "chuy", + "ovidio", + "jes\u00fas", + "fabricio", + "reynaldo", + "\u00e1ngel", + "luis", + "blas", + "edelmiro", + "hermenegildo", + "octavio", + "biel", + "ismael", + "jose_manuel", + "elpidio", + "eugenio", + "dimas", + "chucho", + "maximiano", + "miguel_\u00e1ngel", + "timoteo", + "quirino", + "abel", + "gervasio", + "v\u00edctor", + "jose_angel", + "joan", + "amado", + "natalio", + "celestino", + "juan_luis", + "patricio", + "mart\u00ed", + "juan_carlos", + "carmelo", + "glauco", + "le\u00f3n", + "gilberto", + "arnau", + "lorenzo", + "emigdio", + "nazaret", + "juan_manuel", + "mar\u00eda", + "n\u00e9stor", + "curro", + "ad\u00e1n", + "renato", + "gil", + "teobaldo", + "jenaro", + "jan", + "gustavo", + "guiomar", + "pepito", + "abraham", + "heraclio", + "ciro", + "artemio", + "onofre", + "alejandro", + "joaqu\u00edn", + "maximino", + "heriberto", + "nico", + "to\u00f1o", + "severo", + "gregorio", + "marcio", + "vicente", + "adam", + "nicodemo", + "edmundo", + "emilio", + "\u00e9dgar", + "jos\u00e9_luis", + "crist\u00f3bal", + "nicol\u00e1s", + "jos\u00e9", + "juanito", + "eligio", + "leoncio", + "alberto", + "donato", + "te\u00f3filo", + "marcial", + "vidal", + "pablo", + "epifanio", + "jacinto", + "adri\u00e1n", + "leopoldo", + "yago", + "rico", + "aureliano", + "am\u00e9rico", + "p\u00e1nfilo", + "loreto", + "diego", + "alfonso", + "hilario", + "andr\u00e9s_felipe", + "vinicio", + "ren\u00e9", + "eliseo", + "roque", + "lucho", + "urbano", + "cl\u00edmaco", + "moreno", + "samu", + "teo", + "lucio", + "josep", + "ruperto", + "ruy", + "dionisio", + "amador", + "espiridi\u00f3n", + "rold\u00e1n", + "angelino", + "marc", + "andr\u00e9s", + "virgilio", + "francisco", + "\u00f3scar", + "ferm\u00edn", + "apolinar", + "adalberto", + "seve", + "prudencio", + "daniel", + "gaspar", + "borja", + "manolo", + "juan_francisco", + "toni", + "h\u00e9ctor", + "augusto", + "miguel", + "macario", + "alejo", + "alex", + "severiano", + "ram\u00f3n", + "narciso", + "teodosio", + "claudio", + "benigno", + "albino", + "pedro", + "baudelio", + "jord\u00e1n", + "ignacio", + "cipriano", + "anastasio", + "isa\u00edas", + "chus", + "federico", + "florentino", + "santos", + "evaristo", + "amando", + "mario", + "ceferino", + "ib\u00e1n", + "jos\u00e9_\u00e1ngel", + "baldomero", + "pelayo", + "lisandro", + "chema", + "segismundo", + "teodoro", + "lu\u00eds", + "custodio", + "luciano", + "candelario", + "dani", + "adelardo", + "nilo", + "juli\u00e1n", + "duilio", + "cesar", + "javi", + "salom\u00f3n", + "leonardo", + "ildefonso", + "iv\u00e1n", + "marco", + "emiliano", + "lupe", + "humberto", + "nacho", + "iker", + "p\u00edo", + "vito", + "goyo", + "cir\u00edaco", + "telmo", + "aristides", + "gast\u00f3n", + "dar\u00edo", + "ciriaco", + "sebastian", + "alfredo", + "rufino", + "sosimo", + "rub\u00e9n", + "jaime", + "pancho", + "javier", + "godofredo", + "jer\u00f3nimo", + "eustaquio", + "fidel", + "tom\u00e1s", + "rodrigo", + "pau", + "arsenio", + "xavier", + "marciano", + "cruz", + "basilio", + "agapito", + "am\u00edlcar", + "omar", + "sandalio", + "no\u00e9", + "silvio", + "leandro", + "modesto", + "aurelio", + "julio_c\u00e9sar", + "rodolfo", + "jose_ram\u00f3n", + "haroldo", + "benito", + "efra\u00edn", + "flavio", + "marino", + "melchor", + "felix", + "amancio", + "victorino", + "natanael", + "mat\u00edas", + "sigfrido", + "camilo", + "r\u00f3mulo", + "cecilio", + "lucas", + "florencio", + "cayetano", + "valent\u00edn", + "roberto", + "eleuterio", + "josu\u00e9", + "geraldo", + "agust\u00edn", + "bernardino", + "fortunato", + "cirino", + "poncio", + "fabi\u00e1n", + "isaac", + "silvestre", + "celso", + "arturo", + "hugo", + "\u00e8ric", + "conrado", + "saturnino", + "juan_bautista", + "nil", + "gerardo", + "ra\u00fal", + "ale", + "nazario", + "albano", + "jose_luis", + "ernesto", + "m\u00e1ximo", + "porfirio", + "tiburcio", + "enrique", + "alcides", + "juan_pablo", + "mois\u00e9s", + "jerem\u00edas", + "severino", + "\u00e1lex", + "joel", + "primitivo", + "vasco", + "jos\u00e9_mar\u00eda", + "leo", + "\u00ed\u00f1igo", + "esteban", + "jose_miguel", + "tadeo", + "adolfo", + "f\u00e9lix", + "sabas", + "victoriano", + "jos\u00e9_antonio", + "enzo", + "asdrubal", + "jose", + "germ\u00e1n", + "trinidad", + "ramiro", + "eloy", + "guadalupe", + "eric", + "isidoro", + "fito", + "juan_jos\u00e9", + "herberto", + "valero", + "che", + "leonel", + "toribio", + "benjam\u00edn", + "edu", + "dami\u00e1n", + "mateo", + "david", + "baltasar", + "vencesl\u00e1s", + "fulgencio", + "leocadio", + "eutropio", + "jacobo", + "paulino", + "maxi", + "trist\u00e1n", + "ezequiel", + "anacleto", + "marcelino", + "felipe", + "lope", + "eusebio", + "mauricio", + "casemiro", + "nicanor", + "c\u00e1ndido", + "jos\u00e9_mari", + "ulises", + "aar\u00f3n", + "victor", + "nacio", + "fernando", + "santiago", + "reinaldo", + "r\u00e9gulo", + "carlito", + "inocencio", + "abilio", + "fausto", + "lino", + "reyes", + "cornelio", + "rafael", + "danilo", + "ambrosio", + "plinio", + "francisco_jose", + "feliciano", + "jonatan", + "hern\u00e1n", + "galo", + "olegario", + "pol", + "domingo", + "ger\u00f3nimo", + "demetrio", + "tito", + "sergio", + "calixto", + "armando", + "nando", + "mariano", + "antonio", + "rogelio", + "cosme", + "c\u00e9sar", + "max", + "marcelo", + "jafet", + "bernab\u00e9", + "gabriel", + "w\u00e1lter", + "carlos", + "sebasti\u00e1n", + "bonifacio", + "manuel", + "balduino", + "jose_carlos", + "ruben", + "raimundo", + "amaro", + "desiderio", + "heliodoro", + "salvador", + "jorge", + "jose_ignacio", + "ariel", + "calisto", + "cebri\u00e1n", + "sancho", + "bartolom\u00e9", + "jose_francisco", + "rosario", + "horacio", + "faustino", + "eladio", + "herminio", + "kike", + "amor", + "edgardo", + "hernando", + "luis_miguel", + "cleto", + "graciano", + "manu", + "marcos", + "martin", + "luis_\u00e1ngel", + "lalo", + "l\u00e1zaro", + "eduardo", + "aleix", + "an\u00edbal", + "pl\u00e1cido", + "pepe", + "hip\u00f3lito", + "guillermo", + "gabino", + "anselmo", + "bernardo", + "hector", + "francisco_javier", + "quique", + "fabio", + "jose_antonio", + "ricardo", + "julio", + "samuel", + "juan", + "rolando", + "buenaventura", + "norberto", + "sim\u00f3n", + "alonso", + "mohamed", + "pascual", + "berto", + "jordi", + "erasmo", + "aitor", + "zacar\u00edas", + "jos\u00e9_manuel", + "rosendo", + "dan", + "pastor", + "juan_antonio", + "victor_manuel", + "\u00e1lvaro", + "wilfredo", + "paco", + "clemente", + "el\u00edas", + "eutimio", + "gonzalo", + "rafa", + "mart\u00edn", + "albert", + "osvaldo", + "bruno", + "valerio", + "cristian", + "maximiliano", + "remigio" + ], + "FIRST_NAME": [ + "adelaida", + "j\u00falia", + "nydia", + "isidro", + "bautista", + "candelas", + "rom\u00e1n", + "atilio", + "chuy", + "am\u00e9rica", + "ovidio", + "jes\u00fas", + "fabricio", + "jos\u00e9_manu\u00e9l", + "lupita", + "reynaldo", + "mercedes", + "hortensia", + "luisa", + "consuelo", + "vicenta", + "\u00e1ngel", + "homero", + "luis", + "abiga\u00edl", + "ana_mar\u00eda", + "edelmiro", + "antonia", + "blas", + "rosaura", + "inmaculada", + "genaro", + "piedad", + "hermenegildo", + "yeni", + "clotilde", + "flor", + "octavio", + "dionisia", + "valentina", + "trini", + "biel", + "ismael", + "jose_manuel", + "crescencia", + "elpidio", + "eugenio", + "asunci\u00f3n", + "\u00e1ngela", + "dimas", + "purificaci\u00f3n", + "chucho", + "cloe", + "salma", + "maximiano", + "miguela", + "miguel_\u00e1ngel", + "timoteo", + "visitaci\u00f3n", + "\u00e1gueda", + "quirino", + "abel", + "gervasio", + "javiera", + "modesta", + "dolores", + "sandra", + "melania", + "melisa", + "fortunata", + "tecla", + "oswaldo", + "concepci\u00f3n", + "v\u00edctor", + "adelia", + "jose_angel", + "joan", + "saturnina", + "helena", + "amado", + "celestino", + "natalio", + "serafina", + "aldo", + "jos\u00e9_eduardo", + "aida", + "evangelina", + "juan_luis", + "gala", + "eva", + "patricio", + "dominga", + "aurora", + "rosa_mar\u00eda", + "mart\u00ed", + "juan_carlos", + "d\u00e9bora", + "carmelo", + "glauco", + "olimpia", + "josefa", + "le\u00f3n", + "gilberto", + "cintia", + "leonor", + "arnau", + "lorenzo", + "fanny", + "petrona", + "virginia", + "emigdio", + "nazaret", + "elvira", + "juan_manuel", + "aroa", + "mar\u00eda", + "selena", + "marina", + "n\u00e9stor", + "alejandra", + "curro", + "noelia", + "ver\u00f3nica", + "chelo", + "rufina", + "ad\u00e1n", + "evelia", + "estela", + "renato", + "gil", + "teobaldo", + "silvano", + "paca", + "s\u00edlvia", + "andrea", + "jenaro", + "elo\u00edsa", + "candela", + "isabela", + "jan", + "esther", + "pastora", + "yolanda", + "cristal", + "luciana", + "gustavo", + "guiomar", + "pepito", + "camila", + "\u00farsula", + "israel", + "juliana", + "abraham", + "\u00e1ngeles", + "ana", + "itzel", + "artemio", + "ciro", + "heraclio", + "carmelita", + "julia", + "\u00e1urea", + "onofre", + "jimena", + "elisabet", + "alejandro", + "febe", + "azahar", + "joaqu\u00edn", + "encarnacion", + "ana_bel\u00e9n", + "maximino", + "heriberto", + "nico", + "to\u00f1o", + "severo", + "gregorio", + "marcio", + "vicente", + "adam", + "nicodemo", + "edmundo", + "emilio", + "gloria", + "caridad", + "\u00e9dgar", + "luc\u00eda", + "eligia", + "calixta", + "xiomara", + "jos\u00e9_luis", + "crist\u00f3bal", + "jacinta", + "clarisa", + "nicol\u00e1s", + "jos\u00e9", + "juanito", + "gracia", + "leoncio", + "belen", + "irma", + "n\u00faria", + "eligio", + "alberto", + "donato", + "te\u00f3filo", + "karla", + "bibiana", + "marcial", + "socorro", + "aina", + "vidal", + "pablo", + "epifanio", + "mar\u00eda_jes\u00fas", + "adri\u00e1n", + "nicolasa", + "amaya", + "leopoldo", + "jacinto", + "paz", + "wendolin", + "yago", + "micaela", + "rico", + "flavia", + "aureliano", + "fidela", + "pilar", + "am\u00e9rico", + "ramona", + "p\u00e1nfilo", + "loreto", + "pac\u00edfica", + "luna", + "alfonso", + "diego", + "hilario", + "paula", + "andr\u00e9s_felipe", + "azucena", + "patricia", + "consuela", + "vinicio", + "ren\u00e9", + "mia", + "eliseo", + "roque", + "alicia", + "elvia", + "lucho", + "perlita", + "urbano", + "cl\u00edmaco", + "moreno", + "noem\u00ed", + "samu", + "eufemia", + "teo", + "maricela", + "lucio", + "malena", + "josep", + "mar\u00eda_luisa", + "ruperto", + "lara", + "ruy", + "dionisio", + "lucila", + "prudencia", + "estefan\u00eda", + "amador", + "anastasia", + "espiridi\u00f3n", + "rold\u00e1n", + "albina", + "angelino", + "marc", + "carina", + "sonia", + "dorotea", + "sol", + "dafne", + "olga", + "eulalia", + "andr\u00e9s", + "soledad", + "virgilio", + "francisco", + "ar\u00e1nzazu", + "jordana", + "vanesa", + "rebeca", + "\u00f3scar", + "mar\u00eda_\u00e1ngeles", + "mitzy", + "lorenza", + "eusebia", + "ferm\u00edn", + "alexandra", + "apolinar", + "adalberto", + "seve", + "prudencio", + "lola", + "daniel", + "marianela", + "gaspar", + "daniela", + "borja", + "ricarda", + "manolo", + "roc\u00edo", + "juan_francisco", + "toni", + "guillermina", + "maite", + "nayeli", + "h\u00e9ctor", + "augusto", + "miguel", + "maribel", + "dulce", + "martina", + "macario", + "alejo", + "elisa", + "abril", + "encarnita", + "severiano", + "alex", + "ram\u00f3n", + "jennifer", + "victoria", + "teodosio", + "narciso", + "claudio", + "benigno", + "albino", + "custodia", + "anselma", + "pedro", + "ana_luisa", + "macaria", + "laura", + "baudelio", + "jana", + "casandra", + "gertrudis", + "jord\u00e1n", + "cristina", + "rosenda", + "ignacio", + "cipriano", + "anastasio", + "amarilis", + "isa\u00edas", + "chus", + "federico", + "esmeralda", + "florentino", + "norma", + "apolonia", + "julie", + "adora", + "jovita", + "ligia", + "santos", + "ant\u00f2nia", + "marisa", + "benita", + "evaristo", + "genoveva", + "palmira", + "montserrat", + "encarna", + "amando", + "joaquina", + "mario", + "ceferino", + "amalia", + "te\u00f3fila", + "marcia", + "ib\u00e1n", + "jos\u00e9_\u00e1ngel", + "mariana", + "ivonne", + "baldomero", + "pelayo", + "lisandro", + "chema", + "samanta", + "bernarda", + "fernanda", + "segismundo", + "aura", + "feliciana", + "teodoro", + "lu\u00eds", + "custodio", + "mireia", + "luciano", + "octavia", + "candelario", + "dani", + "gabriela", + "adelardo", + "nilo", + "juli\u00e1n", + "duilio", + "tania", + "cesar", + "emperatriz", + "javi", + "salom\u00f3n", + "leonardo", + "florina", + "ascensi\u00f3n", + "ildefonso", + "iv\u00e1n", + "zaida", + "marco", + "emiliano", + "mamen", + "delfina", + "lupe", + "blanca", + "humberto", + "y\u00e9ssica", + "nacho", + "iker", + "viviana", + "mar\u00eda_del_carmen", + "nidia", + "lidia", + "rosal\u00eda", + "rita", + "p\u00edo", + "agustina", + "vito", + "goyo", + "morena", + "cir\u00edaco", + "telmo", + "remedios", + "marta", + "minerva", + "angelita", + "elena", + "aristides", + "gast\u00f3n", + "olalla", + "mauro", + "dar\u00edo", + "ciriaco", + "sebastian", + "ximena", + "alfredo", + "rufino", + "milagros", + "mar\u00eda_cristina", + "delia", + "sarita", + "rub\u00e9n", + "sosimo", + "violeta", + "jaime", + "pancho", + "magdalena", + "odalis", + "soraya", + "javier", + "mar\u00eda_teresa", + "godofredo", + "tomasa", + "eustaquio", + "lorena", + "jer\u00f3nimo", + "fidel", + "edelmira", + "francisca", + "almudena", + "frida", + "tom\u00e1s", + "rodrigo", + "concha", + "salom\u00e9", + "pau", + "nelly", + "arsenio", + "xavier", + "pascuala", + "rosalva", + "adriana", + "marciano", + "cruz", + "vera", + "basilio", + "rosalina", + "marco_antonio", + "yuridia", + "paloma", + "agapito", + "sessa", + "priscila", + "pepita", + "lucia", + "am\u00edlcar", + "omar", + "sandalio", + "no\u00e9", + "reyna", + "josefina", + "in\u00e9s", + "silvio", + "nadia", + "leandro", + "modesto", + "aurelio", + "candelaria", + "calista", + "noa", + "julio_c\u00e9sar", + "ani", + "narcisa", + "rodolfo", + "manola", + "haroldo", + "f\u00e1tima", + "jose_ram\u00f3n", + "araceli", + "benito", + "bel\u00e9n", + "efra\u00edn", + "flavio", + "seraf\u00edn", + "sara", + "nuria", + "jos", + "gema", + "marino", + "melchor", + "teresita", + "gisela", + "felix", + "marisol", + "amancio", + "victorino", + "eva_mar\u00eda", + "maricruz", + "berta", + "natanael", + "mat\u00edas", + "sigfrido", + "camilo", + "r\u00f3mulo", + "cecilio", + "lucas", + "encarnaci\u00f3n", + "florencio", + "olivia", + "nayara", + "cayetano", + "ariadna", + "indira", + "wilfrido", + "ilse", + "roberto", + "eleuterio", + "abelardo", + "dulce_mar\u00eda", + "benigna", + "alba", + "valent\u00edn", + "josu\u00e9", + "geraldo", + "agust\u00edn", + "vilma", + "jaqueline", + "anunciaci\u00f3n", + "isidora", + "salud", + "bernardino", + "fortunato", + "cirino", + "ainoa", + "alondra", + "fabi\u00e1n", + "conchita", + "poncio", + "isaac", + "elodia", + "azahara", + "silvestre", + "dalia", + "anna", + "evelio", + "sabina", + "ruperta", + "celso", + "zaira", + "martirio", + "arturo", + "felisa", + "ana_sof\u00eda", + "hermelinda", + "c\u00e1ndida", + "hugo", + "juanita", + "leire", + "herminia", + "\u00e8ric", + "etelvina", + "conrado", + "saturnino", + "juan_bautista", + "carlota", + "nieves", + "m\u00f3nica", + "imelda", + "lilia", + "nil", + "gerardo", + "ra\u00fal", + "ale", + "nazario", + "loida", + "carla", + "albano", + "jose_luis", + "charo", + "ernesto", + "chita", + "m\u00e1ximo", + "leyre", + "tatiana", + "adoraci\u00f3n", + "carolina", + "porfirio", + "lourdes", + "aitana", + "coral", + "tiburcio", + "azeneth", + "rosa", + "ainara", + "nerea", + "ruth", + "eugenia", + "brunilda", + "adelina", + "luisina", + "tere", + "enrique", + "alcides", + "juan_pablo", + "mois\u00e9s", + "jerem\u00edas", + "rosalinda", + "severino", + "\u00e1lex", + "joel", + "primitivo", + "vasco", + "linda", + "zo\u00e9", + "carmen", + "y\u00e9sica", + "obdulia", + "jos\u00e9_mar\u00eda", + "leo", + "amada", + "\u00ed\u00f1igo", + "carmina", + "esteban", + "jose_miguel", + "tadeo", + "adolfo", + "f\u00e9lix", + "hayd\u00e9e", + "odalys", + "amelia", + "silvia", + "ester", + "evita", + "bianca", + "sabas", + "jenny", + "esparta", + "victoriano", + "julieta", + "domitila", + "elsa", + "jos\u00e9_antonio", + "dalila", + "cynthia", + "liliana", + "enzo", + "asdrubal", + "jose", + "marisela", + "isaura", + "arlet", + "alta__gracia", + "germ\u00e1n", + "trinidad", + "ramiro", + "eloy", + "pamela", + "yaiza", + "guadalupe", + "eric", + "ema", + "isidoro", + "armida", + "merche", + "ang\u00e9lica", + "fito", + "natalia", + "\u00e1mbar", + "juan_jos\u00e9", + "celestina", + "anabel", + "amparo", + "valero", + "herberto", + "irene", + "che", + "leonel", + "tamara", + "toribio", + "jon\u00e1s", + "benjam\u00edn", + "edu", + "dami\u00e1n", + "emma", + "mateo", + "david", + "clementina", + "uriel", + "mar\u00eda_manuela", + "baltasar", + "estrella", + "judith", + "iris", + "vencesl\u00e1s", + "fulgencio", + "leocadio", + "regina", + "eutropio", + "jacobo", + "paulino", + "maxi", + "trist\u00e1n", + "ezequiel", + "margarita", + "florinda", + "anacleto", + "manuelita", + "marcelino", + "alma", + "felipe", + "lope", + "mar\u00eda_dolores", + "eusebio", + "zoraida", + "esperanza", + "mar\u00eda_eugenia", + "fabiola", + "emilia", + "nancy", + "susana", + "mauricio", + "martha", + "casemiro", + "b\u00e1rbara", + "nicanor", + "ileana", + "jos\u00e9_mari", + "c\u00e1ndido", + "nilda", + "ulises", + "aar\u00f3n", + "rafaela", + "victor", + "nacio", + "fernando", + "mar\u00eda_pilar", + "oriana", + "reinaldo", + "santiago", + "lina", + "r\u00e9gulo", + "citlali", + "leocadia", + "carlito", + "inocencio", + "br\u00edgida", + "abilio", + "\u00e1gata", + "felipa", + "fausto", + "lino", + "ruby", + "reyes", + "constanza", + "cornelio", + "rafael", + "danilo", + "ambrosio", + "paola", + "plinio", + "francisco_jose", + "ignacia", + "cristobal", + "marita", + "paulina", + "florentina", + "feliciano", + "espartaco", + "isa", + "felicia", + "jonatan", + "hern\u00e1n", + "mar", + "jorge_luis", + "arcelia", + "teodora", + "galo", + "olegario", + "alvaro", + "pol", + "domingo", + "ger\u00f3nimo", + "demetrio", + "tito", + "sergio", + "calixto", + "armando", + "nando", + "emiliana", + "mariano", + "val\u00e8ria", + "griselda", + "jos\u00e9_carlos", + "antonio", + "diana", + "rogelio", + "cosme", + "graciela", + "c\u00e9sar", + "max", + "graciana", + "raquel", + "celia", + "marcelo", + "jafet", + "bernab\u00e9", + "bego\u00f1a", + "reina", + "gabriel", + "macarena", + "carlos", + "w\u00e1lter", + "manuela", + "felicidad", + "rafa\u00e9l", + "anita", + "beatriz", + "anel", + "maura", + "leticia", + "bonifacio", + "sebasti\u00e1n", + "juana", + "karina", + "manuel", + "fabiana", + "elba", + "perla", + "balduino", + "adela", + "elias", + "jose_carlos", + "itziar", + "ruben", + "raimundo", + "amaro", + "desiderio", + "heliodoro", + "sof\u00eda", + "aurelia", + "jorge", + "jose_ignacio", + "salvador", + "p\u00eda", + "ariel", + "nereida", + "roberta", + "calisto", + "barbara", + "cebri\u00e1n", + "sancho", + "rosalia", + "laia", + "bartolom\u00e9", + "cl\u00e0udia", + "marcela", + "mar\u00eda_elena", + "jose_francisco", + "chl\u00f3e", + "rosario", + "horacio", + "mayte", + "mar\u00eda_fernanda", + "faustino", + "isabel", + "eladio", + "herminio", + "aldonza", + "kike", + "florencia", + "amor", + "edgardo", + "claudia", + "jessica", + "hernando", + "susanita", + "angelina", + "luis_miguel", + "cleto", + "graciano", + "mar\u00eda_jos\u00e9", + "manu", + "marcos", + "martin", + "luis_\u00e1ngel", + "lalo", + "l\u00e1zaro", + "eloisa", + "eduardo", + "matilde", + "aleix", + "hilda", + "pl\u00e1cido", + "pepe", + "hip\u00f3lito", + "maristela", + "teresa", + "an\u00edbal", + "guillermo", + "gabino", + "anselmo", + "natividad", + "cayetana", + "n\u00e9lida", + "bernardo", + "hector", + "leandra", + "amanda", + "francisco_javier", + "quique", + "fabio", + "georgina", + "eli", + "jose_antonio", + "ricardo", + "julio", + "samuel", + "mirta", + "juan", + "m\u00e1xima", + "luis_manuel", + "jos\u00e9_emilio", + "rolando", + "mar\u00eda_bel\u00e9n", + "buenaventura", + "norberto", + "flora", + "primitiva", + "sim\u00f3n", + "\u00edngrid", + "alonso", + "mohamed", + "pascual", + "berto", + "valeria", + "roxana", + "carmela", + "jordi", + "bernardita", + "abigail", + "erasmo", + "aitor", + "zeferino", + "mar\u00eda_carmen", + "dora", + "zacar\u00edas", + "cecilia", + "jos\u00e9_manuel", + "emelina", + "pili", + "dan", + "bienvenida", + "\u00f3liver", + "rosendo", + "jesusa", + "pastor", + "juan_antonio", + "renata", + "catalina", + "victor_manuel", + "\u00e1lvaro", + "ofelia", + "miriam", + "wilfredo", + "corona", + "luz", + "\u00e1frica", + "clemente", + "el\u00edas", + "eutimio", + "paco", + "eliana", + "gonzalo", + "rafa", + "mart\u00edn", + "albert", + "osvaldo", + "bruno", + "filomena", + "valerio", + "cristian", + "clara", + "ona", + "otilia", + "dorita", + "maximiliano", + "remigio" + ], + "LAST_NAME": [ + "pantoja", + "escalante", + "rom\u00e1n", + "armenta", + "espinosa", + "pintor", + "cazares", + "mora", + "valles", + "soriano", + "canet", + "tafoya", + "d\u00e1vila", + "jurado", + "tur", + "romero", + "ponce", + "casanova", + "balaguer", + "alvarado", + "pi\u00f1a", + "maestas", + "escriv\u00e1", + "mart\u00ed", + "portillo", + "mayoral", + "parejo", + "acedo", + "tejeda", + "mercado", + "calvet", + "oller", + "almansa", + "serrato", + "mir\u00f3", + "chac\u00f3n", + "planas", + "pou", + "martinez", + "esparza", + "cervantes", + "ripoll", + "far\u00edas", + "ojeda", + "barreto", + "figueroa", + "zabala", + "avil\u00e9s", + "cab\u00e1n", + "v\u00e9lez", + "zabaleta", + "atienza", + "aguirre", + "ballester", + "rodarte", + "ruelas", + "bola\u00f1os", + "almaz\u00e1n", + "valenciano", + "puig", + "sanmiguel", + "batlle", + "morell", + "osorio", + "amores", + "alberto", + "ferr\u00e1ndez", + "marroqu\u00edn", + "blazquez", + "arcos", + "amaya", + "palomares", + "paz", + "mariscal", + "cant\u00fa", + "espa\u00f1a", + "r\u00edos", + "fuente", + "bar\u00f3", + "mu\u00f1iz", + "roque", + "de_la_garza", + "almanza", + "moreno", + "puente", + "blasco", + "ochoa", + "ch\u00e1vez", + "capdevila", + "querol", + "andr\u00e9s", + "holgu\u00edn", + "ortega", + "albero", + "de_la_rosa", + "colom", + "heras", + "verduzco", + "pab\u00f3n", + "garmendia", + "beltran", + "esteve", + "requena", + "mancebo", + "d\u00edez", + "rubio", + "monta\u00f1ez", + "berm\u00fadez", + "ram\u00f3n", + "milla", + "carro", + "di\u00e9guez", + "marti", + "terr\u00f3n", + "tejera", + "pedrero", + "palomino", + "catal\u00e1", + "tamez", + "loya", + "porras", + "montserrat", + "guevara", + "crespi", + "pelayo", + "gir\u00f3n", + "gal\u00e1n", + "fortuny", + "cordero", + "aparicio", + "bertr\u00e1n", + "juli\u00e1n", + "ceballos", + "armengol", + "sastre", + "zamorano", + "cu\u00e9llar", + "arias", + "solorio", + "buend\u00eda", + "qui\u00f1\u00f3nez", + "montesinos", + "sarabia", + "chico", + "ceja", + "v\u00e1squez", + "verd\u00fa", + "tom\u00e1s", + "parra", + "abascal", + "cruz", + "bustos", + "mel\u00e9ndez", + "lira", + "cadena", + "benavente", + "hoyos", + "lucena", + "ba\u00f1os", + "cases", + "riera", + "pi\u00f1eiro", + "laureano", + "benet", + "almonte", + "huerta", + "talavera", + "almeida", + "agust\u00edn", + "sevillano", + "hern\u00e1ndez", + "jim\u00e9nez", + "enr\u00edquez", + "orozco", + "moll", + "sauceda", + "garrido", + "torrijos", + "nieves", + "r\u00edo", + "roda", + "verdugo", + "f\u00e1bregas", + "olvera", + "lled\u00f3", + "c\u00e1ceres", + "teruel", + "villalba", + "bonet", + "exp\u00f3sito", + "aramburu", + "comas", + "clavero", + "moya", + "del_r\u00edo", + "bosch", + "g\u00e1lvez", + "moles", + "maya", + "est\u00e9vez", + "escribano", + "tello", + "mar\u00ed", + "ocampo", + "leal", + "arranz", + "arriaga", + "ayll\u00f3n", + "malave", + "salda\u00f1a", + "nevado", + "ant\u00fanez", + "polanco", + "canales", + "ontiveros", + "monreal", + "cobo", + "alcal\u00e1", + "alvarez", + "valverde", + "garc\u00e9s", + "aguilar", + "calvillo", + "salamanca", + "porcel", + "herrera", + "sol\u00eds", + "castellanos", + "barranco", + "mar\u00edn", + "urrutia", + "agullo", + "cintr\u00f3n", + "borrell", + "santiago", + "guill\u00e9n", + "rojas", + "vi\u00f1a", + "caldera", + "malo", + "nicolau", + "jaimes", + "calder\u00f3n", + "villase\u00f1or", + "llano", + "luevano", + "nogu\u00e9s", + "montero", + "g\u00f3mez", + "chaves", + "ferr\u00e1n", + "camino", + "carre\u00f1o", + "ybarra", + "sep\u00falveda", + "\u00e1lamo", + "bayona", + "cortez", + "fr\u00edas", + "sanabria", + "reina", + "nava", + "altamirano", + "carlos", + "ropero", + "luj\u00e1n", + "dur\u00e1n", + "tolosa", + "alsina", + "cuenca", + "sebasti\u00e1n", + "blanes", + "ayuso", + "llorens", + "portero", + "pi", + "mari\u00f1o", + "sancho", + "gabald\u00f3n", + "alc\u00e1ntara", + "ca\u00f1ete", + "pedrosa", + "palomar", + "iriarte", + "chaparro", + "amor", + "mayorga", + "cal", + "rovira", + "tormo", + "de_la_fuente", + "cortes", + "monta\u00f1o", + "olmos", + "madrid", + "linares", + "juan", + "villalobos", + "tamayo", + "zorrilla", + "pascual", + "j\u00f3dar", + "mendez", + "montez", + "ulibarri", + "maza", + "figuerola", + "elorza", + "guitart", + "trillo", + "frutos", + "dom\u00ednguez", + "cabrera", + "manj\u00f3n", + "torrecilla", + "palacios", + "isern", + "serrano", + "salinas", + "boix", + "barajas", + "prada", + "cabello", + "z\u00fa\u00f1iga", + "godoy", + "narv\u00e1ez", + "bautista", + "fuentes", + "perell\u00f3", + "carbajal", + "caba\u00f1as", + "ord\u00f3\u00f1ez", + "ocasio", + "valderrama", + "grijalva", + "m\u00fagica", + "alberdi", + "solorzano", + "vega", + "barriga", + "palma", + "orosco", + "jara", + "campillo", + "cornejo", + "trejo", + "benavides", + "valdez", + "villena", + "coello", + "mena", + "le\u00f3n", + "irizarry", + "res\u00e9ndez", + "ortiz", + "lorenzo", + "torre", + "lasa", + "nieto", + "samper", + "rodr\u00edquez", + "sanchez", + "ribera", + "macias", + "gil", + "sanz", + "villegas", + "huertas", + "pla", + "hoz", + "pe\u00f1alver", + "cuevas", + "vizca\u00edno", + "puerta", + "gisbert", + "amo", + "montoya", + "bernat", + "olmo", + "arjona", + "losa", + "perez", + "checa", + "falc\u00f3", + "baeza", + "alejandro", + "pinedo", + "pazos", + "lucero", + "egea", + "bravo", + "dom\u00e9nech", + "carretero", + "sevilla", + "serra", + "romeu", + "casado", + "sim\u00f3", + "nicol\u00e1s", + "merino", + "fabregat", + "ugarte", + "gaona", + "vald\u00e9s", + "castrillo", + "aliaga", + "pablo", + "c\u00f3rdoba", + "de_le\u00f3n", + "pi\u00f1ol", + "laguna", + "chapa", + "donaire", + "rico", + "henr\u00edquez", + "castro", + "asensio", + "carre\u00f3n", + "lucio", + "saiz", + "rosas", + "rold\u00e1n", + "medina", + "morales", + "andrade", + "menendez", + "colunga", + "perea", + "acu\u00f1a", + "miranda", + "garc\u00eda", + "rael", + "mateu", + "gallegos", + "l\u00f3pez", + "ortu\u00f1o", + "valls", + "izquierdo", + "alcalde", + "borja", + "cabrero", + "botello", + "oliv\u00e9", + "llobet", + "gait\u00e1n", + "regalado", + "herrero", + "gordillo", + "oliver", + "jord\u00e1n", + "anguita", + "guillen", + "barral", + "solana", + "sanches", + "olivera", + "haro", + "ca\u00f1ellas", + "valladares", + "soler", + "pag\u00e8s", + "lu\u00eds", + "salazar", + "ayala", + "salcido", + "blanca", + "perales", + "zambrano", + "vel\u00e1zquez", + "berenguer", + "caparr\u00f3s", + "balderas", + "ricart", + "solera", + "casanovas", + "mojica", + "coloma", + "rocamora", + "jaime", + "cuervo", + "guajardo", + "rodrigo", + "tomas", + "arag\u00f3n", + "oquendo", + "peres", + "santamaria", + "cerezo", + "alcolea", + "cabo", + "samaniego", + "fonseca", + "tejedor", + "cabanillas", + "barros", + "saez", + "segovia", + "roura", + "ar\u00e9valo", + "verdejo", + "olivares", + "agudo", + "salmer\u00f3n", + "chavarr\u00eda", + "qui\u00f1ones", + "barrera", + "aguilera", + "suarez", + "mat\u00edas", + "villag\u00f3mez", + "campos", + "r\u00f3denas", + "dalmau", + "azorin", + "bru", + "vel\u00e1squez", + "cifuentes", + "caro", + "barela", + "romo", + "manzanares", + "redondo", + "fuster", + "ni\u00f1o", + "villarreal", + "bad\u00eda", + "leiva", + "varela", + "gim\u00e9nez", + "iba\u00f1ez", + "nazario", + "batista", + "pardo", + "lopez", + "ariza", + "abreu", + "ca\u00f1izares", + "lozada", + "riojas", + "espada", + "quesada", + "roig", + "castell\u00f3", + "soria", + "larra\u00f1aga", + "arredondo", + "valenzuela", + "carrillo", + "mata", + "aznar", + "esquibel", + "herranz", + "granados", + "pombo", + "fiol", + "brise\u00f1o", + "ferrero", + "cotto", + "apodaca", + "zavala", + "tapia", + "n\u00e1jera", + "bl\u00e1zquez", + "ruano", + "valero", + "c\u00f3rdova", + "mate", + "arce", + "asenjo", + "olivas", + "c\u00e1mara", + "aguil\u00f3", + "cueto", + "cuellar", + "muro", + "baquero", + "go\u00f1i", + "casas", + "alva", + "lumbreras", + "anguiano", + "lago", + "flores", + "vanegas", + "arana", + "tom\u00e9", + "del_valle", + "alfaro", + "palau", + "elizondo", + "campo", + "cort\u00e9s", + "gamez", + "castilla", + "escolano", + "alegria", + "galvez", + "reguera", + "herv\u00e1s", + "puga", + "feliciano", + "arenas", + "sarmiento", + "p\u00e9rez", + "gras", + "ter\u00e1n", + "beltr\u00e1n", + "bonilla", + "torrent", + "pol", + "alonzo", + "domingo", + "hinojosa", + "madera", + "gayt\u00e1n", + "pe\u00f1as", + "cas\u00e1rez", + "carballo", + "vazquez", + "ribes", + "matas", + "iglesias", + "berr\u00edos", + "villalonga", + "infante", + "boada", + "t\u00f3rrez", + "bayo", + "canals", + "berrocal", + "guardado", + "galiano", + "mendoza", + "cortina", + "ba\u00f1uelos", + "rend\u00f3n", + "zurita", + "bernal", + "bartolom\u00e9", + "arevalo", + "camacho", + "carbajo", + "pel\u00e1ez", + "arco", + "garriga", + "delgadillo", + "badillo", + "saucedo", + "quiroz", + "jove", + "marcos", + "estevez", + "revilla", + "rosell\u00f3", + "moliner", + "gibert", + "galarza", + "navarro", + "artigas", + "arguello", + "montenegro", + "trevi\u00f1o", + "pallar\u00e8s", + "pinto", + "castell", + "esquivel", + "almaraz", + "ros", + "vara", + "font", + "vargas", + "becerra", + "uribe", + "mendiz\u00e1bal", + "velasco", + "meza", + "clemente", + "el\u00edas", + "gonzalo", + "mart\u00edn", + "zamudio", + "villalpando", + "barreda", + "bas", + "andreu", + "j\u00e1quez", + "zayas", + "\u00e1ngel", + "jover", + "lozano", + "negr\u00f3n", + "gasc\u00f3n", + "cerd\u00e1n", + "pont", + "bustamante", + "m\u00fa\u00f1iz", + "estrada", + "llanos", + "cerd\u00e1", + "mur", + "nogueira", + "oliva", + "griego", + "mulet", + "cardona", + "noguera", + "c\u00e9spedes", + "tejero", + "c\u00e1rdenas", + "ferrer", + "bilbao", + "soliz", + "zamora", + "raya", + "morillo", + "araujo", + "poza", + "arnau", + "cedillo", + "hernandes", + "valdivia", + "quevedo", + "nebot", + "ad\u00e1n", + "gual", + "mondrag\u00f3n", + "anaya", + "rebollo", + "centeno", + "nu\u00f1ez", + "posada", + "batalla", + "costa", + "mayol", + "caraballo", + "alcala", + "pomares", + "sanjuan", + "de_la_o", + "due\u00f1as", + "navarrete", + "landa", + "salcedo", + "pizarro", + "vicente", + "vallejo", + "terrazas", + "toro", + "rocha", + "arnal", + "pozo", + "guti\u00e9rrez", + "ramis", + "tijerina", + "franch", + "bueno", + "gracia", + "pav\u00f3n", + "royo", + "hidalgo", + "fierro", + "maga\u00f1a", + "orellana", + "torres", + "barroso", + "covarrubias", + "santacruz", + "jimenez", + "b\u00e1rcena", + "robledo", + "rinc\u00f3n", + "gamboa", + "alemany", + "echevarr\u00eda", + "carrera", + "guzm\u00e1n", + "cid", + "amador", + "codina", + "g\u00e1rate", + "naranjo", + "montes", + "quintero", + "francisco", + "zarate", + "noriega", + "sandoval", + "pujadas", + "valc\u00e1rcel", + "agust\u00ed", + "briones", + "murillo", + "quezada", + "ruiz", + "cuesta", + "gutierrez", + "miguel", + "criado", + "abril", + "maldonado", + "olmedo", + "vall\u00e9s", + "matos", + "mayo", + "losada", + "bar\u00f3n", + "ju\u00e1rez", + "hervia", + "pedro", + "arnaiz", + "ledesma", + "negrete", + "manrique", + "meraz", + "ferreras", + "m\u00e1rmol", + "escamilla", + "santos", + "ram\u00edrez", + "villaverde", + "iborra", + "brito", + "ulloa", + "pinilla", + "casals", + "pichardo", + "iniesta", + "mor\u00e1n", + "jerez", + "miramontes", + "ur\u00edas", + "tejada", + "paredes", + "barrag\u00e1n", + "martorell", + "camps", + "pedroza", + "espinoza", + "fuertes", + "toledo", + "s\u00e1nchez", + "farr\u00e9", + "crespo", + "d\u00edaz", + "vera", + "rosell", + "tenorio", + "adame", + "burgos", + "reyna", + "vicens", + "casares", + "aragon\u00e9s", + "zelaya", + "lomeli", + "rosales", + "borr\u00e1s", + "garibay", + "guerra", + "quir\u00f3s", + "sol\u00e9", + "falc\u00f3n", + "castej\u00f3n", + "ornelas", + "novoa", + "god\u00ednez", + "viera", + "almagro", + "bermejo", + "gallo", + "conde", + "calderon", + "iglesia", + "lobato", + "garza", + "renter\u00eda", + "de_jes\u00fas", + "nev\u00e1rez", + "zaragoza", + "lobo", + "perera", + "porta", + "grande", + "casal", + "roca", + "pereira", + "rosado", + "segu\u00ed", + "llorente", + "franco", + "aponte", + "lloret", + "medrano", + "acero", + "silva", + "rosa", + "roybal", + "vilar", + "carranza", + "serna", + "angulo", + "mungu\u00eda", + "morcillo", + "rangel", + "garz\u00f3n", + "collado", + "prat", + "aguado", + "i\u00f1iguez", + "barber\u00e1", + "soto", + "peir\u00f3", + "s\u00e1enz", + "jim\u00ednez", + "oca\u00f1a", + "caballero", + "fernandez", + "bastida", + "corral", + "abella", + "manso", + "p\u00e1ez", + "acosta", + "mateo", + "gomis", + "echeverr\u00eda", + "giralt", + "olivo", + "sotelo", + "archuleta", + "cuadrado", + "pera", + "viana", + "\u00e1valos", + "mateos", + "m\u00e1rquez", + "garay", + "valbuena", + "mesa", + "mercader", + "villareal", + "prado", + "recio", + "barrientos", + "cobos", + "reynoso", + "gaya", + "machado", + "benitez", + "bay\u00f3n", + "alegre", + "gonz\u00e1lez", + "sosa", + "cazorla", + "higueras", + "ramirez", + "robles", + "cantero", + "cano", + "seco", + "bejarano", + "peinado", + "segura", + "folch", + "riba", + "santill\u00e1n", + "marin", + "roma", + "calatayud", + "n\u00fa\u00f1ez", + "campoy", + "padilla", + "hurtado", + "armend\u00e1riz", + "leyva", + "moraleda", + "real", + "cardenas", + "duque", + "barbero", + "sacrist\u00e1n", + "borrego", + "amor\u00f3s", + "tovar", + "mosquera", + "ferrera", + "ibarra", + "lovato", + "daza", + "amig\u00f3", + "rosario", + "llamas", + "calzada", + "hernando", + "llabr\u00e9s", + "navas", + "martin", + "fern\u00e1ndez", + "nadal", + "sierra", + "lemus", + "gomez", + "\u00e1guila", + "lamas", + "llad\u00f3", + "bahena", + "pina", + "alonso", + "neira", + "saldivar", + "oliv\u00e1rez", + "su\u00e1rez", + "espejo", + "pellicer", + "solano", + "cisneros", + "grau", + "fl\u00f3rez", + "ferrando", + "andres", + "carri\u00f3n", + "taboada", + "guerrero", + "blanco", + "pastor", + "alarc\u00f3n", + "guzman", + "ca\u00f1as", + "vergara", + "prieto", + "bou", + "jasso", + "diez", + "alcaraz", + "espinal", + "pons", + "morera", + "gomila", + "somoza", + "baca", + "valencia", + "corrales", + "jord\u00e1", + "luque", + "vaquero", + "montalb\u00e1n", + "dominguez", + "flor", + "belmonte", + "\u00e1vila", + "hernandez", + "mares", + "vaca", + "carpio", + "arregui", + "yuste", + "pino", + "concepci\u00f3n", + "collazo", + "aller", + "goicoechea", + "reig", + "cerro", + "pulido", + "alc\u00e1zar", + "murcia", + "bellido", + "casta\u00f1eda", + "abrego", + "montalvo", + "t\u00e9llez", + "hierro", + "venegas", + "palmer", + "arellano", + "aguayo", + "correa", + "palomo", + "monroy", + "marquez", + "guijarro", + "bernad", + "casillas", + "sedano", + "pareja", + "molins", + "aroca", + "huguet", + "ur\u00eda", + "rasc\u00f3n", + "mas", + "plaza", + "men\u00e9ndez", + "heredia", + "coca", + "carb\u00f3", + "saura", + "cerv\u00e1ntez", + "mej\u00eda", + "sales", + "tirado", + "bello", + "sisneros", + "mac\u00edas", + "botella", + "alc\u00e1ntar", + "sobrino", + "carrasco", + "mu\u00f1oz", + "gelabert", + "loera", + "gollum", + "cabezas", + "vidal", + "partida", + "larrea", + "madrigal", + "guardia", + "granado", + "torralba", + "barraza", + "riquelme", + "salv\u00e0", + "osuna", + "mascare\u00f1as", + "m\u00ednguez", + "luna", + "rios", + "alfonso", + "valle", + "diego", + "uriarte", + "ja\u00e9n", + "lugo", + "palacio", + "arteaga", + "saavedra", + "arrieta", + "lara", + "marrero", + "tudela", + "piquer", + "escudero", + "lluch", + "fabra", + "prats", + "zedillo", + "llopis", + "calleja", + "preciado", + "catal\u00e1n", + "galv\u00e1n", + "rossell\u00f3", + "villa", + "gimenez", + "pati\u00f1o", + "arreola", + "roman", + "ben\u00edtez", + "bauz\u00e0", + "chamorro", + "lerma", + "salgado", + "exposito", + "barcel\u00f3", + "mota", + "sanmart\u00edn", + "v\u00e9liz", + "zepeda", + "garica", + "villar", + "b\u00e1ez", + "rozas", + "adadia", + "giner", + "coll", + "rivero", + "carbonell", + "barco", + "gimeno", + "barba", + "vi\u00f1as", + "pe\u00f1a", + "lillo", + "rey", + "pujol", + "colomer", + "benav\u00eddez", + "carreras", + "marco", + "cabeza", + "torrents", + "pineda", + "salom", + "castillo", + "villanueva", + "laboy", + "coronado", + "mireles", + "peralta", + "pacheco", + "zapata", + "escalona", + "b\u00e9tancourt", + "sala", + "rodriguez", + "gallardo", + "carvajal", + "candelaria", + "plana", + "espa\u00f1ol", + "contreras", + "benito", + "vela", + "c\u00e1novas", + "segarra", + "rueda", + "otero", + "polo", + "bermudez", + "izaguirre", + "calvo", + "gonzalez", + "ramos", + "lucas", + "carnero", + "morante", + "lastra", + "valent\u00edn", + "alba", + "carmona", + "barrena", + "mascar\u00f3", + "c\u00f3zar", + "sola", + "blanch", + "ari\u00f1o", + "ferr\u00e1ndiz", + "paniagua", + "company", + "vall", + "quintanilla", + "ant\u00f3n", + "espino", + "cavazos", + "menchaca", + "quiroga", + "ballesteros", + "de_la_cr\u00faz", + "de_anda", + "carrero", + "cervera", + "vilanova", + "jaume", + "vendrell", + "benavent", + "arribas", + "arroyo", + "pozuelo", + "padr\u00f3n", + "cepeda", + "armas", + "corbacho", + "esteban", + "curiel", + "amat", + "ure\u00f1a", + "vilalta", + "feijoo", + "orta", + "acevedo", + "rodr\u00edgez", + "sainz", + "gargallo", + "belda", + "guardiola", + "quintana", + "tena", + "diaz", + "feliu", + "azcona", + "mart\u00ednez", + "monta\u00f1a", + "sans", + "galan", + "gilabert", + "rojo", + "abad", + "trujillo", + "abell\u00e1n", + "cadenas", + "rol\u00f3n", + "vives", + "delgado", + "v\u00e1zquez", + "conesa", + "lebr\u00f3n", + "s\u00e1ez", + "corominas", + "sureda", + "duran", + "morata", + "baena", + "jaramillo", + "ib\u00e1\u00f1ez", + "g\u00e1mez", + "duarte", + "alem\u00e1n", + "j\u00e1uregui", + "reyes", + "longoria", + "barrio", + "peral", + "gurule", + "roldan", + "escobedo", + "leon", + "girona", + "rius", + "gast\u00e9lum", + "castells", + "y\u00e1\u00f1ez", + "juli\u00e1", + "marqu\u00e9s", + "oliveras", + "rodr\u00edguez", + "m\u00e9ndez", + "garcia", + "sabater", + "barrios", + "valera", + "alberola", + "aranda", + "ozuna", + "manuel", + "molina", + "santana", + "valadez", + "vila", + "salvador", + "miralles", + "hern\u00e1dez", + "melero", + "cant\u00f3n", + "de_la_torre", + "salas", + "\u00e1lvarez", + "gonzales", + "melgar", + "busquets", + "torrens", + "priego", + "escobar", + "solsona", + "rivas", + "mill\u00e1n", + "anglada", + "col\u00f3n", + "vigil", + "urbina", + "fajardo", + "maestre", + "santamar\u00eda", + "galindo", + "donoso", + "tamarit", + "mir", + "quero", + "montemayor", + "\u00e1lvaro", + "camarillo", + "corona", + "luz", + "figueras", + "pedraza", + "vilaplana", + "ribas", + "razo", + "lim\u00f3n", + "rivera", + "gallart", + "gallego", + "manzano" + ], + "OTHER_PRONOUN": [ + "it", + "them" + ], + "LAST_NAME_MALE": [], + "LAST_NAME_FEMALE": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "superiora": "abba", + "abadesa": "archimandita", + "actriz": "histri\u00f3n", + "aviadora": "aviador", + "bibi": "tiu", + "ti\u00edta": "tiu", + "baronesa": "magnata", + "bot\u00f3nesa": "botones", + "novia": "almohazar", + "mujer_de_negocios": "empresario", + "working_girl": "empresario", + "negocianta": "empresario", + "pich\u00f3n": "gaur", + "polluelo": "gaur", + "poulette": "gaur", + "vaquera": "corredor_de_rodeo", + "filia": "son", + "hija": "son", + "duquesa": "duque", + "emperatriz": "saturnia_pavonia", + "imperatriz": "emperador", + "femenino": "masculino", + "hembra": "masculino", + "gal": "guido", + "mujercita": "guido", + "chamaca": "guido", + "chiquilla": "guido", + "muchacha": "mozalbete", + "jovencita": "guido", + "lola": "guido", + "institutor": "gobernadora", + "institutriz": "vali", + "nieta": "nieto", + "jeje": "lia", + "hero\u00edna": "heros", + "las_suyas": "suya", + "los_suyos": "suya", + "el_suyo": "suya", + "la_suya": "suyas", + "ella_misma": "s\u00ed_mismo", + "s\u00ed_misma": "\u00e9l_mismo", + "anfitriona": "fondista", + "se\u00f1ora": "mr", + "arredataria": "arrendador", + "terrateniente": "arrendador", + "casera": "arrendador", + "chiquita": "mozalbete", + "pubilla": "mozalbete", + "marquesa": "marqu\u00e9s", + "flama": "m\u00e1ster", + "la_madre": "pap\u00e1", + "progenitora": "pap\u00e1", + "sobreproteger": "pap\u00e1", + "mimar_en_exceso": "vater", + "sra": "mr", + "sobrina": "sobrino", + "monja": "religioso", + "religiosa": "monachus", + "religieuse": "monachus", + "nun": "monachus", + "sacerdotisa": "flamen", + "pr\u00edncipe": "prince", + "princesa": "el_pr\u00edncipe", + "infanta": "regulus", + "princessa": "regulus", + "homosexual": "rey", + "reg": "key", + "soberana_reinante": "king", + "hetman": "key", + "queens": "reyes", + "hechicera": "sorcerer", + "solterona": "soltero", + "sotlerona": "soltero", + "la_portavoz": "vocero", + "portavoz": "vocero", + "hijastra": "hijastro", + "madrastra": "oide", + "azafata": "intendente", + "aeromoza": "intendente", + "camarera": "mesonero", + "mesera": "mesonero", + "oficiante": "mesero", + "vidua": "viudo", + "viuda": "viudo", + "bean": "isla_de_man", + "marido": "esposo", + "esposa": "esposo", + "mujer": "man", + "duna": "esposo", + "feto": "isla_de_man", + "hembra_adulta": "isla_de_man", + "mujeres": "hombres_hombres", + "boy": "jovencita", + "yaro": "mujercita", + "var\u00f3n": "chamaca", + "cauc\u00e1sico": "blanca", + "persona_blanca": "blanca" + }, + "other_gender_swap": { + "them": "jeje", + "one": "jeje", + "a_ellos": "jeje", + "a_ellas": "jeje", + "tey": "jeje", + "aca": "jeje", + "lia": "suyos", + "suya": "el_suyo", + "suyo": "la_suya", + "suyos": "la_suya", + "suyas": "la_suya", + "\u3078": "ellas", + "elli": "epi", + "de_\u00e9l": "suyos", + "jeje": "aca", + "las_suyas": "suyas", + "los_suyos": "suyo", + "el_suyo": "suyo", + "la_suya": "suyo" + }, + "en_pronoun2gender": { + "they": [ + "transexual", + "homosexual", + "bisexual", + "transg\u00e9nero", + "queer", + "transg\u00e9nera" + ], + "he": [ + "gentilhombre", + "yaro", + "agrietarse", + "masculino", + "boy", + "guido", + "chamaquito", + "chiquito", + "resquebrajarse", + "fidalgo", + "isla_de_man", + "gentleman", + "var\u00f3n", + "man", + "tripular", + "mozalbete", + "little_boy", + "el_hombre", + "chiquitin", + "marido", + "gaur" + ], + "she": [ + "doncella_dom\u00e9stica", + "peque\u00f1a", + "faltar", + "echar_de_menos", + "lesbianismo", + "hembra_adulta", + "brasa", + "lesbio", + "se\u00f1ora", + "a\u00f1orar", + "chiquilla", + "perderse", + "feto", + "bean", + "chamaca", + "yerro", + "hembra", + "sirvienta", + "carecer", + "fallir", + "srta", + "desacierto", + "gal", + "femenino", + "mu\u00f1eca", + "ausentarse", + "criada", + "extra\u00f1ar", + "lola", + "pulcella", + "mademoiselle", + "pubilla", + "sexo_d\u00e9bil", + "chiquitina", + "bello_sexo", + "jovencita", + "miss_a", + "goce", + "mujercita", + "chiquita", + "muchacha", + "lesbiana", + "mujer" + ] + }, + "en_pronoun2pronoun": { + "he": [ + "\u00e9l_mismo", + "lia", + "de_\u00e9l", + "elli", + "\u3078", + "s\u00ed_mismo" + ], + "she": [ + "la_suya", + "las_suyas", + "el_suyo", + "ella_misma", + "los_suyos", + "jeje", + "s\u00ed_misma" + ], + "they": [ + "one", + "huma", + "ellas", + "tey", + "aca", + "lia", + "oms", + "a_ellas", + "suya", + "them", + "suyas", + "a_ellos", + "suyos", + "ellos", + "suyo", + "epi" + ], + "it": [ + "ello", + "\u00e9stos", + "\u00e9sas", + "\u00e9sos", + "aquellas", + "illo", + "esas", + "a_si_mismo", + "\u00e9sa", + "esta", + "ico", + "aqu\u00e9llas", + "it", + "esos", + "estos", + "eso", + "aqu\u00e9llos", + "por_si_mismo", + "\u00e9se", + "tyto", + "aqu\u00e9l", + "estes", + "aqu\u00e9lla" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/esu.json b/data_tooling/pii_processing/ontology/data/esu.json new file mode 100644 index 0000000..8476b87 --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/esu.json @@ -0,0 +1,49 @@ +{ + "ANIMAL": [ + "lumarrallertuyuli", + "arlunaq" + ], + "PUBLIC_FIGURE": [ + "malruk" + ], + "ORG": [ + "elitnaurvik", + "united_states" + ], + "RELIGION_MEMBER": [ + "anngaq" + ], + "FOOD": [ + "kuuvviaq" + ], + "GENDER": [ + "arnaq" + ], + "LOCATION": [ + "ami_ulikaq" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": {}, + "other_gender_swap": {}, + "en_pronoun2gender": { + "she": [ + "arnaq" + ] + }, + "en_pronoun2pronoun": { + "it": [ + "tauna" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/et.json b/data_tooling/pii_processing/ontology/data/et.json new file mode 100644 index 0000000..77c063f --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/et.json @@ -0,0 +1,2332 @@ +{ + "ANIMAL": [ + "p\u00e4hklin\u00e4pp", + "k\u00f5rvukr\u00e4ts", + "apodemus", + "kanakull", + "polaarrebane", + "idalunn", + "kirdekr\u00fc\u00fcsel", + "leethiir", + "haugas", + "randal", + "elektriangerjas", + "kartulimardikas", + "rohtlahaukur", + "punahirv", + "pringellased", + "kihulased", + "hallvaal", + "leevike", + "hunt\u00e4mbliklased", + "karupoeg", + "reesusmakaak", + "roostep\u00e4\u00e4suke", + "kanepilind", + "kahvrip\u00fchvel", + "loorkakk", + "l\u00e4\u00e4nes\u00f5tkas", + "bengali_tiiger", + "salutihane", + "heron", + "kalaan", + "kisakurg", + "stepivuril", + "kassikakk", + "riisiamadiin", + "kaljukotkas", + "koerliblikas", + "mustr\u00e4stas", + "muskusveis", + "kirjatuvi", + "mustlagle", + "vasarhailased", + "l\u00fcpsilehm", + "elevantkilpkonn", + "p\u00e4\u00e4sukalalased", + "haigurlased", + "rannikugorilla", + "musttihane", + "p\u00f5hjatirk", + "herilaseviu", + "heeringavaal", + "p\u00f5hjatihane", + "kanalis\u00e4ga", + "grinda", + "hallhani", + "teder", + "hangelind", + "mustvares", + "h\u00f5bekajakas", + "kivinugis", + "ninaahv", + "karkjalg", + "ka\u0161elott", + "rookass", + "kaaren", + "katkubakter", + "punavetiktaimed", + "mink", + "baribal", + "ilves", + "nahkkilpkonn", + "vesirott", + "tait", + "arukuklane", + "s\u00f5ralised", + "hirvlased", + "p\u00f5ldp\u00fc\u00fc", + "kaljutuvi", + "rohukoskel", + "paalia", + "lendorav", + "saarmas", + "m\u00e4nnileevike", + "p\u00f5ldtsiitsitaja", + "k\u00e4rnkonn", + "apteegikaan", + "lakkhunt", + "kurvits", + "luitekass", + "pulstikkits", + "vahaleedik", + "soolekepike", + "aaga", + "nugis", + "sini_r\u00e4gapart", + "politseikoer", + "rohukonn", + "karpkala", + "m\u00e4gigorilla", + "kakulised", + "suurs\u00e4\u00e4lik", + "hallj\u00e4nes", + "vereimejalased", + "valgesaba", + "turb", + "kalakajakas", + "herilane", + "tavadelfiin", + "m\u00e4gikiur", + "vikerforell", + "kivikakk", + "konlased", + "naerukajakas", + "grisli", + "vandelkajakas", + "h\u00f5behaigur", + "pistrik", + "pringel", + "listeeriabakter", + "kajaklased", + "kivirullija", + "hagijas", + "naaskelnokk", + "tuuletallaja", + "eesel", + "sookiur", + "raudkull", + "kunel", + "kabehirv", + "kond\u016bz", + "mustvaeras", + "suur\u00e4nn", + "vaskuss", + "rohunepp", + "habekakk", + "meem\u00e4ger", + "\u00fcheksav\u00f6\u00f6lane", + "ristpart", + "mustluik", + "tuhatjalg", + "lemming", + "monarhliblikas", + "vereimeja", + "kadakas\u00e4\u00e4lik", + "kaldap\u00e4\u00e4suke", + "vaalhai", + "rabapistrik", + "samblikus\u00e4\u00e4lik", + "kanaliha", + "laanep\u00fc\u00fc", + "hall\u00f5gija", + "l\u00f5unatirk", + "l\u00e4\u00e4ne_niiluse_viirus", + "poilased", + "eider", + "pollak", + "valgevaal" + ], + "PUBLIC_FIGURE": [ + "henry_cavendish", + "koolmekoht", + "benjamin_franklin", + "martin_buber", + "akira_kurosawa", + "valentina_tere\u0161kova", + "giovanni_boccaccio", + "rudolf_steiner", + "thomas_bayes", + "max_bruch", + "leonard_bernstein", + "sibelius", + "che_guevara", + "georges_simenon", + "c", + "edward_albee", + "hendrik", + "dorothy_parker", + "maria_callas", + "william_walton", + "henrik_ibsen", + "mary_shelley", + "marcello_malpighi", + "peter_lorre", + "david_livingstone", + "andrzej_wajda", + "carl_rogers", + "george_balanchine", + "douglas_macarthur", + "mary_wollstonecraft", + "j_edgar_hoover", + "thomas_reid", + "anna_pavlova", + "winston_churchill", + "gustav", + "conrad_aiken", + "karl_landsteiner", + "ivan_pavlov", + "paul_mccartney", + "terry_pratchett", + "stephen_king", + "francis_crick", + "joseph_greenberg", + "isaac_newton", + "heinrich_von_hohenstaufen", + "victor_hugo", + "jiang_jieshi", + "milton_friedman", + "edward_gibbon", + "mary_stuart", + "jefferson_davis", + "saint_louis", + "brigaadikindral", + "george_stephenson", + "john_glenn", + "john_davis", + "george_harrison", + "george_orwell", + "arthur_koestler", + "richard_wagner", + "thornton_wilder", + "marie_curie", + "francis_galton", + "hubilai", + "michael_jackson", + "thomas_hobbes", + "el_greco", + "samuel_beckett", + "katariina", + "galileo_galilei", + "robert_koch", + "joseph_goebbels", + "george_eastman", + "john_steinbeck", + "donald_glaser", + "c_northcote_parkinson", + "edmund_hillary", + "vincent_van_gogh", + "martina_navr\u00e1tilov\u00e1", + "lauri", + "anne_boleyn", + "robert_burns", + "thomas_paine", + "liliuokalani", + "steven_weinberg", + "mary_pickford", + "karl_barth", + "kaarel", + "allen_iverson", + "marie_antoinette", + "lennart", + "giuseppe_verdi", + "walter_lippmann", + "karl_jaspers", + "konrad_adenauer", + "norbert_wiener", + "gottlieb_daimler", + "frank_sinatra", + "abel_tasman", + "katharine_hepburn", + "henri_becquerel", + "henri_matisse", + "louis_pasteur", + "richard_strauss", + "theodosius_i", + "hugo_grotius", + "alphonse_bertillon", + "gertrude_stein", + "saladin", + "sarah_bernhardt", + "j\u00fcrgen", + "sergei_rahmaninov", + "luigi_pirandello", + "t_s_eliot", + "hank_williams", + "edward_usutunnistaja", + "igor_stravinski", + "dorothea_lange", + "charles_de_gaulle", + "paul_von_hindenburg", + "y", + "henry_moore", + "holden", + "ralph_bunche", + "rudolf_bultmann", + "ja_nii_edasi", + "charles_lindbergh", + "vincenzo_bellini", + "samuel_barber", + "f", + "ludwig_wittgenstein", + "august_strindberg", + "thomas_mann", + "william_ockham", + "dante_alighieri", + "percy_shelley", + "robert_lee", + "john_irving", + "samuel_de_champlain", + "giacomo_puccini", + "fridtjof_nansen", + "louis_braille", + "herbert_marcuse", + "mungo_park", + "paul_verlaine", + "robert_johnson", + "james_dean", + "robert", + "marie_tussaud", + "henrik", + "joseph_priestley", + "nicolas_poussin", + "andrea_mantegna", + "joseph_pulitzer", + "oscar_wilde", + "philip_roth", + "richard_trevithick", + "heinrich_schliemann", + "balletitantsija", + "don_quijote", + "georg", + "adolf_eichmann", + "linnuk\u00fctt", + "francis_bacon", + "pete_seeger", + "konstantin_stanislavski", + "joseph_heller", + "a", + "james_brown", + "charles_baudelaire", + "luigi_cherubini", + "david_ricardo", + "mary_leakey", + "charlie_parker", + "immanuel_kant", + "charles_de_montesquieu", + "nellie_bly", + "lewis", + "albert_schweitzer", + "johann_friedrich_herbart", + "titus", + "johannes_kepler", + "david_hartley", + "max_planck", + "william_blake", + "julio_iglesias", + "john_bardeen", + "piip", + "william_byrd", + "scott_joplin", + "carl_lewis", + "george_vancouver", + "canberra", + "elias_canetti", + "edward_jenner", + "oscar_robertson", + "oliver_hardy", + "michelangelo_caravaggio", + "jean_luc_godard", + "graham_greene", + "frans_hals", + "edward", + "lars_onsager", + "margaret_mitchell", + "henri", + "flavius_josephus", + "william_herschel", + "joseph_black", + "arthur_compton", + "niels_bohr", + "kenneth_grahame", + "bertrand_russell", + "michael_faraday", + "john_d_rockefeller", + "jan_tinbergen", + "rudolf_diesel", + "walt_disney", + "gabriel_lippmann", + "steve_reich", + "benny_goodman", + "friedrich_engels", + "jane_austen", + "gustav_mahler", + "phil_collins", + "robert_redford", + "jean_giraudoux", + "saint_lawrence_i_j\u00f5gi", + "ian_fleming", + "richard_feynman", + "theodore_dreiser", + "theodor_mommsen", + "andrew_huxley", + "marcel_proust", + "thomas_more", + "paul_hindemith", + "elizabeth_taylor", + "arnold", + "john_dowland", + "william_golding", + "john_milton", + "albert_speer", + "james_baldwin", + "indira_gandhi", + "jane_seymour", + "george_gershwin", + "e_t_a_hoffmann", + "alfred_nobel", + "jesse_owens", + "marco_polo", + "m", + "charlotte_corday", + "kuninghahk", + "allen_ginsberg", + "daniel_bernoulli", + "guillaume_apollinaire", + "henri_bergson", + "antonius", + "boris_karloff", + "pierre_corneille", + "patrick_white", + "bartholomew_roberts", + "hans_christian_andersen", + "cary_grant", + "thomas", + "pieter_zeeman", + "glenn_miller", + "mooses", + "pablo_picasso", + "l_ron_hubbard", + "peeter", + "madrus", + "christiaan_huygens", + "hector_berlioz", + "claudio_monteverdi", + "thomas_morgan", + "john_galsworthy", + "adam_smith", + "william_james", + "henry_miller", + "karl_marx", + "friedrich_nietzsche", + "i", + "william_burroughs", + "sandro_botticelli", + "nikola_tesla", + "al_capone", + "billy_graham", + "robert_schumann", + "mel_gibson", + "le_corbusier", + "carlo_goldoni", + "john_locke", + "alexis_carrel", + "henry_james", + "stephen_sondheim", + "helen_keller", + "ingrid_bergman", + "anna_kurnikova", + "leonard_bloomfield", + "koole", + "jean_piaget", + "paul_tillich", + "kaitseingel", + "maarja_magdaleena", + "walt_whitman", + "colin_powell", + "ludwig_boltzmann", + "carl_nielsen", + "richard_wright", + "adolf_hitler", + "alfred_stieglitz", + "joseph_haydn", + "george_boole", + "edvard_grieg", + "robert_boyle", + "cordell_hull", + "rosa_parks", + "x", + "vladimir_putin", + "jim_thorpe", + "arnold_sch\u00f6nberg", + "fritz_kreisler", + "anne_hathaway", + "bill_russell", + "clarence_darrow", + "robert_fischer", + "g", + "arthur_schopenhauer", + "james_cagney", + "wanda_landowska", + "martin_heidegger", + "riigipea", + "r", + "george_lucas", + "andrew_jackson", + "louis_armstrong", + "steven_spielberg", + "jean_monnet", + "robert_fulton", + "thomas_hardy", + "thomas_gainsborough", + "giuseppe_garibaldi", + "robert_brown", + "johannes_gutenberg", + "gaetano_donizetti", + "william_faulkner", + "amerigo_vespucci", + "pierre_boulez", + "hans_adolf_krebs", + "girolamo_savonarola", + "emma_goldman", + "francis_poulenc", + "john_constable", + "james_mill", + "putin", + "joseph_campbell", + "jean_de_la_fontaine", + "robert_hooke", + "o_henry", + "karl_popper", + "george_sand", + "peter_sellers", + "charles_fourier", + "marcus_aurelius", + "peter_o'toole", + "joseph_conrad", + "peter_paul_rubens", + "mahatma_gandhi", + "jim_morrison", + "jules_verne", + "paul_newman", + "alexander_wilson", + "jackson_pollock", + "john_lennon", + "andrea_palladio", + "kurttumm", + "charlie_chaplin", + "j_m_barrie", + "robert_woodward", + "lea", + "john_brown", + "kuuria", + "peetrus", + "brescia", + "hannah_arendt", + "antonio_stradivari", + "maximianus", + "strauss", + "miles_davis", + "wilhelm_tell", + "george_marshall", + "stanley_kubrick", + "james_watt", + "jonathan_edwards", + "ronald_reagan", + "helmut_schmidt", + "jenny_lind", + "david_hilbert", + "wilhelm_reich", + "roman_jakobson", + "korstnap\u00fchkija", + "kustav", + "oliver_cromwell", + "martin_luther_king", + "william_wordsworth", + "s", + "woodrow_wilson", + "lootma", + "marcus_antonius", + "jim_henson", + "b\u00e9la_lugosi", + "ernest_hemingway", + "jacques_charles", + "eero_saarinen", + "arthur_miller", + "john_cheever", + "nelson_mandela", + "heinrich_himmler", + "al_gore", + "cesare_borgia", + "roald_amundsen", + "saint_martini_saar", + "c_a", + "anton", + "charles_dickens", + "ella_fitzgerald", + "fats_waller", + "alois_senefelder", + "jacques_offenbach", + "eliisabet", + "federico_fellini", + "hru\u0161t\u0161ov", + "willy_brandt", + "francisco_pizarro", + "francisco_franco", + "bernardo_bertolucci", + "powell", + "kristoforus", + "hans_arp", + "pontius_pilatus", + "christoph_kolumbus", + "franz_schubert", + "johnny_cash", + "joseph_mccarthy", + "hans_j\u00fcrgen_eysenck", + "titusele", + "mick_jagger", + "georges_cuvier", + "william_harvey", + "walter_scott", + "p\u00fcha_j\u00fcri", + "vladimir_lenin", + "felipe_ii", + "reigo", + "modest_mussorgski", + "jonathan_swift", + "walter_gropius", + "albert_einstein", + "claude_bernard", + "raymond_chandler", + "henry_purcell", + "t", + "william_vallutaja", + "wilhelm_ostwald" + ], + "JOB": [ + "tulet\u00f5rjuja", + "dood\u017e", + "madrus", + "allohvitser", + "guru", + "lambur", + "kindralmajor", + "brigadir", + "lakei", + "kutsealune", + "riigiametnik", + "seersant", + "kapral", + "tantsija", + "mehaanika", + "asutaja", + "koopia", + "leitnant", + "the_ecologist", + "kindralleitnant", + "kirurg", + "valvur", + "linnapea", + "kuraator", + "heerold", + "k\u00f5neleja", + "ametlik", + "hobuserautaja", + "jutlustaja", + "magistraat", + "temp", + "don", + "king", + "valitsejer", + "lennujuht", + "aamissepp", + "the_police", + "joonlaud", + "juhataja", + "taust", + "autojuht", + "armeekindral", + "kajutiteenija", + "silitama", + "vahendaja", + "ajateenija", + "t\u00f6\u00f6line", + "the_scientist", + "helilooja", + "pankur", + "tisler", + "keldri\u00f6\u00f6lane", + "s\u00f5jav\u00e4elane", + "majandusteadlane", + "piiskop", + "printer", + "pintsaklipslane", + "passija", + "plokkfl\u00f6\u00f6t", + "tanner", + "muusikariist", + "p\u00fcttsepp", + "juhatama", + "korstnap\u00fchkija", + "muusik", + "the_guardian", + "portjee", + "president", + "nooremleitnant", + "seller", + "brigaadikindral", + "pearahak\u00fctt", + "s\u00f5ltumatu", + "maaler", + "mate", + "salakaubavedaja", + "kuberner", + "rabi", + "pastor", + "paberim\u00e4\u00e4rija", + "kolonel", + "\u00f5igusvahemees", + "hambaarst", + "viitseadmiral", + "juht", + "the_economist", + "t\u00e4navap\u00fchkija", + "streigimurdja", + "barista", + "loomaarst", + "man", + "pressiesindaja", + "doc", + "regent", + "mikrobioloog", + "treener", + "raadiovastuv\u00f5tja", + "disainer", + "preetor", + "konnetaabel", + "nouandja", + "usher", + "messenger", + "insener", + "peakokk", + "vabakutseline", + "krupjee", + "junga", + "keetma", + "r\u00e4\u00e4kija", + "labak\u00e4si", + "teadlane", + "kolonelleitnant", + "maalija", + "linnuk\u00fctt", + "meremees", + "the_independent", + "kaupmees", + "ettev\u00f5tja", + "autor" + ], + "ORG": [ + "ida", + "andromeeda_galaktika", + "magistri\u00f5pe", + "wicca", + "failipaigutustabel", + "ennastt\u00e4is", + "jan_mayen", + "kristlikud_demokraadid", + "ins", + "vanalinn", + "kinnisvaramaakler", + "puuviljasalat", + "\u00fclemn\u00f5ukogu", + "aa", + "nasa", + "ii_vatikani_kirikukogu", + "praemuna", + "kaubanduskeskus", + "ol\u00fcmpiak\u00fcla", + "the_who", + "keelpillikvartett", + "perepea", + "noort\u00fcrklased", + "san_francisco", + "t\u00e4heparv", + "armee", + "roheneemesaared", + "majanduss\u00fcsteem", + "survegrupp", + "konservatiivne_partei", + "haridus", + "gao", + "perekonna\u00f5igus", + "transportimine", + "kuldhord", + "keemiat\u00f6\u00f6stus", + "ma_armastan_sind", + "valdus\u00fching", + "john_tuzo_wilson", + "ol\u00fcmpiatuli", + "saint_helena", + "don_juan", + "rahvusvaheline_telekommunikatsiooni_liit", + "tsiviil\u00f5igus", + "kodaniku\u00fchiskond", + "koduv\u00e4givald", + "asutus", + "chiang_mai", + "sala\u00fching", + "alamkoda", + "dia", + "turumajandus", + "massimeedia", + "kihelkonnakirik", + "as_duur", + "baskimaa", + "roheline_partei", + "heaoluriik", + "vi\u0161nuism", + "karupoeg_puhh", + "caf\u00e9_au_lait", + "valimisringkond", + "al_jaz\u012brah", + "p\u00f5letatud_maa_taktika", + "rabindranath_tagore", + "gestapo", + "postkontor", + "saksa_keisririik", + "peadiagonaal", + "haldus\u00fcksus", + "maav\u00e4gi", + "kolled\u017e", + "valitsus", + "relvaj\u00f5ud", + "jehoova_tunnistajad", + "jesuiidid", + "reisib\u00fcroo", + "konservatoorium", + "kollane_j\u00f5gi", + "popkunst", + "ristikorrutis", + "kuussada", + "sotsialistlik_partei", + "europe", + "lennuv\u00e4gi", + "po", + "kolm_\u00f5de", + "i_nikaia_kirikukogu", + "n\u00e4gemisn\u00e4rv", + "i_konstantinoopoli_kirikukogu", + "plaanimajandus", + "mossad", + "merev\u00e4gi", + "huvir\u00fchm", + "ameti\u00fching", + "p\u00e4\u00e4stearmee", + "k\u00f5rgahi", + "vabam\u00fc\u00fcrlus", + "saientoloogia", + "magevesi", + "saint_barth\u00e9lemy", + "sturmabteilung", + "linnriik", + "los_angeles", + "nato", + "puhkpilliorkester", + "l\u00f5unapoolus", + "kordeballett", + "varimajandus", + "p\u00fchap\u00e4evakool", + "arengumaa", + "vabariiklik_partei", + "dominiiklased", + "noorkuu", + "sa", + "doc", + "generaalstaadid", + "veel_\u00fcks_kord", + "nukuvalitsus", + "politseiakadeemia", + "mahajaana", + "hagana", + "taoism", + "esindajatekoda", + "streptococcus_pyogenes", + "loodev\u00e4il", + "issanda_aastal", + "botaanikaaed", + "\u00fclemj\u00e4rv", + "n\u00e4rimiskumm", + "hautes_fagnes", + "kapetingid", + "mecklenburg_vorpommern", + "keelkond", + "punane_rist", + "guomindang", + "kutsekool", + "era\u00f5igus", + "s\u00e3o_tom\u00e9", + "pataljon", + "punane_meri" + ], + "LOCATION": [ + "al_jaz\u012brah", + "harilik_j\u00f5hvikas", + "ilmajaam", + "mardip\u00e4ev", + "umbtee", + "saint_clairi_j\u00e4rv", + "mustr\u00e4hn", + "harilik_alang", + "mis_siis", + "park", + "soolaj\u00e4rv", + "linnutee", + "madalmaad", + "linav\u00e4strik", + "piet_mondrian", + "j\u00f5uluvana", + "la_manche", + "sint_maarten", + "kirsiaed", + "hallvares", + "\u00fclemj\u00e4rv", + "como_j\u00e4rv", + "saksi_anhalt", + "umbt\u00e4nav", + "joseph_louis_gay_lussac", + "laugasuu", + "peat\u00e4nav", + "botaanikaaed", + "tagaplaanil", + "lake_of_the_woods", + "mets\u00fcmiseja", + "l\u00e4\u00e4nepoolkera", + "usa", + "saint_lucia", + "roheneemesaared", + "magevesi", + "ameerika", + "sri_lanka", + "konservatoorium", + "kanalisaared", + "hallhaigur", + "lennuv\u00e4gi", + "t\u00e4isnurk", + "lihav\u00f5ttesaar", + "the_rolling_stones", + "michigani_j\u00e4rv", + "tere_\u00f5htust", + "kr\u00f5v\u00f5i_rig", + "kaubamaja", + "kuumaveeallikas", + "keskpank", + "uus_maailm", + "j\u00f5ululaup\u00e4ev", + "ringristmik" + ], + "LAW": [ + "kohtuotsus", + "kaitseseisukord", + "valimiss\u00fcsteem", + "ne_bis_in_idem", + "mere\u00f5igus", + "kasumiaruanne", + "haldus\u00f5igus", + "rooma_\u00f5igus", + "kriminaal\u00f5igus", + "pressivabadus", + "riigikohus", + "s\u00f5jaseisukord" + ], + "PRODUCT": [ + "stara_planina", + "t\u00e4hes\u00f5jad", + "virvatuli", + "muusikainstrument", + "justin_bieber", + "kuullaager", + "meieisapalve", + "orbitaaljaam", + "automaatkaitsel\u00fcliti", + "suurbritannia_saar", + "meelespea", + "kolme_riigi_ajastu", + "maailmal\u00f5pp", + "ajamasin", + "ristimiskivi", + "julius_caesar", + "diskett", + "signaalit\u00f6\u00f6tlus", + "the_star_spangled_banner", + "k\u00f5rvitslatern", + "virtuaalmasin", + "armastuskiri", + "v\u00f5idukaar", + "san_joaquini_j\u00f5gi", + "tabanip\u00e4ev", + "keskmaa", + "hoorni_neem", + "s\u00f5jalennuk", + "deutsche_welle", + "neli_aastaaega", + "aval\u00f6\u00f6k", + "kohvitass", + "t\u00e4ppisteadused", + "\u00fclemlaul", + "keisril\u00f5ige", + "nordrhein_westfalen", + "merisiga", + "kosmoses\u00fcstik", + "nukumaja", + "p\u00fcha_maria", + "suurbritannia", + "soomusauto", + "arvutusl\u00fckati", + "padaemand" + ], + "FAC": [ + "kaubanduskeskus", + "loodusm\u00e4lestis", + "raudrist", + "arnold_sch\u00f6nberg", + "suusakeskus", + "katoliku_kirik", + "politseijaoskond", + "mall", + "tolliamet", + "rooma_katoliku_kirik", + "pansion", + "saint_lucia", + "k\u00fclalistemaja", + "pansionaat", + "peeter_i", + "rippsild", + "titus_livius", + "alamkoda", + "triumfikaar", + "t_l\u00fcmfots\u00fc\u00fcdid", + "t\u00e4na_\u00f5htul", + "postkontor", + "lasketiir", + "kontserdihall" + ], + "DISEASE": [ + "v\u00e4rvipimedus", + "langet\u00f5bi", + "kalor", + "teetanus", + "soolat\u00fc\u00fcgas", + "luksatus", + "salmonellabakter", + "nakkushaigused", + "klaustrofoobia", + "sarlakid", + "brutselloos", + "halvatus", + "als", + "pidalit\u00f5bi", + "vingum\u00fcrgistus", + "kolets\u00fcstiit", + "kollapalavik", + "soojus", + "jalakasurm", + "follikuliit", + "leetrid", + "suhkurt\u00f5bi", + "lamblioos", + "kraapima", + "l\u00fchin\u00e4gevus", + "kink", + "pang", + "aneemia", + "talveuni", + "silikoos", + "maohammustus", + "palavik", + "v\u00f6\u00f6tohatis", + "asutaja", + "materialism", + "valgus", + "marutaud", + "beribeeri", + "vaktsiniirmine", + "katk", + "kanapimedus", + "kaugelen\u00e4gevus", + "preeklampsia", + "hullulehmat\u00f5bi", + "koolera", + "furunkul", + "hingeldus", + "valguskartus", + "arahnofoobia", + "kraapsima", + "qi", + "autoimmuunsus", + "tagaj\u00e4rg", + "vanaean\u00e4gevus", + "c_hepatiit", + "maksap\u00f5letik", + "gimp", + "kratsima", + "rosett", + "dementsus", + "maania", + "elektril\u00f6\u00f6k", + "s\u00fcgama", + "samblikud", + "kogelema", + "progeeria", + "katalepsia", + "geneetiline_h\u00e4ire", + "arvutihiir", + "hiir", + "deliirium", + "polioviirus", + "toime", + "ebola_viirushaigus", + "haige", + "silitama", + "kobedus", + "malaaria", + "hammustama", + "lastehalvatus", + "rasedus", + "kastanipuu", + "lamatis", + "roostetamine", + "elektri\u0161okk", + "liigesep\u00f5letik", + "ill", + "s\u00fcdamepuudulikkus", + "k\u00fcberseks", + "pull", + "luksumine", + "odraiva", + "kessoont\u00f5bi", + "n\u00e4gemispuue", + "luumurd", + "salmonelloos", + "sting", + "a_hepatiit", + "kraapama", + "kiirgus", + "lisama", + "vistrik", + "trauma", + "haigus", + "samblik", + "kassikartus", + "struuma", + "listerioos", + "janu", + "ablatsioon", + "gaasistuma", + "vaktsineerimine", + "veenilaiendid", + "lordoos", + "k\u00f5rgverer\u00f5hkt\u00f5bi", + "gangreen" + ], + "SOC_ECO_CLASS": [ + "kastis\u00fcsteem", + "labor", + "samurai", + "allilm", + "proletariaat", + "t\u00f6\u00f6lisklass", + "talurahvas", + "\u00fchiskond", + "p\u00f5llumajandus", + "vennaskond", + "varimajandus" + ], + "PLANT": [ + "humallutsern", + "kurekell", + "v\u00e4\u00e4ristubakas", + "maniokk", + "vesihein", + "valgej\u00e4nes", + "eksportvili", + "kevadkogrits", + "reseeda", + "parasiittaim", + "the_joshua_tree", + "kolmisruse", + "nurmnelk", + "piinia", + "lepp", + "merikapsas", + "malpiigiat", + "harilik_maarjaohakas", + "nisulill", + "paju", + "valges\u00f5star", + "konnakilbukas", + "k\u00fclmamailane", + "visnamari", + "guajuula", + "maapirn", + "aednelk", + "austerservik", + "suvivikk", + "metsmaasikas", + "teekummel", + "kobars\u00fcsik", + "pomerantsipuu", + "sookask", + "harilik_pihlakas", + "vesim\u00fcnt", + "harilik_parkhein", + "granadill", + "tutkas", + "kardemon", + "kannike", + "toomingas", + "meliss", + "pigim\u00e4nd", + "lillkapsas", + "magun", + "sanglepp", + "kurekellukas", + "sidrunmeliss", + "bergamott", + "soontaim", + "vesilobeelia", + "katteseemnetaimed", + "harilik_jalakas", + "mets\u00fclane", + "musts\u00f5star", + "kummibursera", + "palsamnulg", + "aaskannike", + "liivtarn", + "kesamailane", + "kapsas", + "bilimbi", + "pagarip\u00e4rm", + "ranniksekvoia", + "kunstnik", + "meripuju", + "blackberry", + "k\u00f5rven\u00f5ges", + "musts\u00f5strap\u00f5\u00f5sas", + "vissel", + "maarjalepp", + "kakaouba", + "soontaimed", + "jalakas", + "kassiratas", + "l\u00f5osilm", + "j\u00f5ulupuu", + "lehis", + "valges\u00f5strap\u00f5\u00f5sas", + "habenelk", + "sirmokas", + "konnaosi", + "taidur", + "rooskapsas", + "j\u00f5ulukuusk", + "peet", + "oliivipuu", + "kassitapp", + "metsporgand", + "jumalak\u00e4pp", + "harilik_saar", + "paradiisilindlased", + "kirss", + "hiidmuna", + "parap\u00e4hklipuu", + "laukapuu", + "remmelgas", + "tondipea", + "maksak", + "seap\u00e4hkel", + "kanakoole", + "keerdm\u00e4nd", + "j\u00e4nesekapsas", + "toompuu", + "vesipaju", + "rabamurakas", + "kibuvitsamari", + "kraavtarn", + "bataat", + "v\u00e4ike_n\u00f5mmem\u00fcnt", + "tangeriin", + "meelespea", + "allikmailane", + "metskannike" + ], + "FOOD": [ + "magustoit", + "hapukoor", + "piiniap\u00e4hkel", + "poolfabrikaat", + "karastusjook", + "seesami\u00f5li", + "toiduv\u00e4rvid", + "joogivesi", + "kiirtoit", + "hakkima", + "konnakoivad", + "verivorst", + "s\u00fcnnip\u00e4evatort", + "hanemaksa", + "kartulisalat", + "friikartulid", + "palmi\u00f5li", + "kondenspiim", + "pinot_noir", + "friikad", + "t\u00e4isteraleib", + "sinihallitusjuust", + "kartulikr\u00f5ps", + "puuviljasalat", + "hommikueine", + "kaneelirull", + "vahak\u00f5rvits", + "koeratoit", + "kodujuust", + "kassitoit", + "dessert", + "hernesupp", + "kalapulk", + "kakaopulber", + "kraanivesi", + "piimatoode", + "kokakoola", + "piparkoogimehike", + "morss", + "hommikus\u00f6\u00f6k", + "limonaad", + "j\u00e4\u00e4kohv", + "piiniaseeme" + ], + "PERSON": [ + "c_vitamiin", + "julius_caesar", + "al_gore", + "edward_osborne_wilson", + "george_v", + "harilik_kivipuravik", + "rudolf_hess", + "herbert_george_wells" + ], + "RACE": [ + "hollandlased", + "inglased", + "saarlane", + "ameeriklased", + "araablased", + "juudi", + "jaapanlased", + "t\u00fcrklane", + "k\u00f5mrid", + "t\u00fcrklased" + ], + "BIO_CHEM_ENTITY": [ + "pol\u00fcvin\u00fc\u00fclkloriid", + "karmiinhape", + "d_vitamiin", + "diet\u00fc\u00fcleeter", + "rasvhapped", + "adenosiindifosfaat", + "mineraal\u00f5li", + "magneesiumkloriid", + "salits\u00fc\u00fclhape", + "atset\u00fc\u00fclkloriid", + "sidrunhape", + "r\u00e4nidioksiid" + ], + "MEDICAL_THERAPY": [ + "virtuaalreaalsus", + "verer\u00f5hk" + ], + "RELIGION": [ + "sintoism", + "judaism", + "katarid", + "vi\u0161nuism", + "salafism", + "islam", + "rastafarianism", + "presb\u00fcterlus", + "hinduism", + "wicca", + "donatism" + ], + "LANGUAGE": [ + "jidi\u0161", + "kongo", + "portugallane", + "venemaalane", + "p\u00f5hjasaami", + "norralane", + "walesi", + "kreeklane", + "prantsuse", + "katalaani", + "sakslane", + "esperanto", + "heebrealane", + "ido", + "tonga", + "aktsent" + ], + "QUANTITY": [ + "si_s\u00fcsteem", + "fibonacci_rida", + "algarv", + "meremiil", + "ton", + "dollar", + "kardinaalarv", + "g", + "ruutkilomeeter", + "viissada", + "elektronvolt", + "valgusaasta", + "ruutjalg", + "naelsterling", + "tiik", + "anders_celsius" + ], + "PERSON_PRONOUN": [ + "meie", + "i", + "sinatama", + "me", + "minu" + ], + "RELIGION_MEMBER": [ + "guru", + "frantsisklased", + "kristlane", + "kristjan" + ], + "DATE": [ + "poolkuu", + "tuhkap\u00e4ev", + "kosmoseajastu", + "kooliaasta", + "menstruaalts\u00fckkel", + "volbrip\u00e4ev", + "suremus", + "poolestusaeg", + "solaarkonstant", + "gregoriuse_kalender", + "noorkuu", + "tipptund", + "s\u00fcndimuskordaja", + "p\u00fchakutep\u00e4ev", + "v\u00f5idup\u00fcha", + "veerandsajand", + "isadep\u00e4ev", + "palmipuudep\u00fcha", + "poolsajand", + "emadep\u00e4ev" + ], + "EVENT": [ + "lahes\u00f5da", + "surmatants" + ], + "GPE": [ + "valentinip\u00e4ev", + "al_\u00e1ndalus", + "dar_es_salaam", + "p\u00f5hjapiirkond", + "mustmets", + "rannikupiirkond", + "suhkrupeam\u00e4gi", + "sint_maarten", + "elevandiluurannik", + "p\u00fcha_nikolai", + "l\u00f5unapiirkond", + "valge_maja", + "p\u00fcha_vaim", + "hagia_sophia", + "ol\u00fcmpiak\u00fcla", + "s\u00e3o_tom\u00e9", + "gran_canaria", + "uus_testament", + "vanalinn", + "kroonikoloonia", + "inim\u00f5igused", + "kristoforus", + "p\u00fcha_nikolaus", + "peetrus" + ], + "POLITICAL_PARTY": [ + "natsionaalsotsialistlik_saksa_t\u00f6\u00f6lispartei", + "demokraatlik_partei", + "t\u00f6\u00f6partei", + "labor", + "kommunistlik_partei", + "norra_t\u00f6\u00f6lispartei", + "sotsiaaldemokraatlik_erakond", + "erakond", + "leiboristlik_partei", + "guomindang" + ], + "UNION": [ + "ameti\u00fching" + ], + "POLITICAL_PARTY_MEMBER": [ + "enamlane" + ], + "GENDER": [ + "male", + "poiss", + "man", + "plika" + ], + "ANAT": [ + "abaluut\u00f5stur" + ], + "ner_regexes": [ + [ + "PERSON", + "\\D+ \\D+|\\D+ \\D+", + false, + [] + ] + ], + "FIRST_NAME_FEMALE": [ + "ljubov", + "reet", + "anu", + "kristiina", + "diana", + "anna", + "piret", + "kadri", + "eve", + "sirje", + "anne", + "viktoria", + "olga", + "galina", + "natalja", + "tiina", + "aino", + "mare", + "jekaterina", + "katrin", + "jelena", + "laura", + "aleksandra", + "maie", + "nina", + "marika", + "julia", + "merike", + "anneli", + "valentina", + "riina", + "malle", + "tatiana", + "triin", + "kristina", + "marina", + "maria", + "tatjana", + "natalia", + "svetlana", + "elena", + "tiiu", + "\u00fclle", + "nade\u017eda", + "ljudmila", + "niina", + "tamara", + "irina", + "linda", + "ene", + "kristi" + ], + "FIRST_NAME_MALE": [ + "roman", + "igor", + "rein", + "artur", + "t\u00f5nu", + "priit", + "mihhail", + "ants", + "jaanus", + "tarmo", + "pavel", + "margus", + "mihkel", + "jevgeni", + "valeri", + "juri", + "raivo", + "urmas", + "tiit", + "mati", + "nikolai", + "aleksander", + "peeter", + "aleksandr", + "aivar", + "sergey", + "martin", + "andres", + "sergei", + "maksim", + "marko", + "ivan", + "aleksei", + "sander", + "indrek", + "siim", + "toomas", + "andrei", + "viktor", + "marek", + "vello", + "jaan", + "alexander", + "j\u00fcri", + "andrus", + "dmitri", + "oleg", + "kristjan", + "vladimir", + "meelis" + ], + "PREFIX_FEMALE": [ + "proua", + "dr", + "doktor", + "prof", + "pr" + ], + "PREFIX_MALE": [ + "h\u00e4rra", + "hr", + "dr", + "doktor", + "prof" + ], + "FIRST_NAME": [ + "igor", + "artur", + "kristiina", + "mihhail", + "margus", + "olga", + "valeri", + "aleksandra", + "aino", + "raivo", + "aleksander", + "marika", + "maksim", + "anneli", + "aleksei", + "valentina", + "riina", + "toomas", + "triin", + "kristina", + "maria", + "tatjana", + "vello", + "alexander", + "j\u00fcri", + "oleg", + "roman", + "ljubov", + "diana", + "rein", + "anna", + "kadri", + "ants", + "anne", + "pavel", + "jelena", + "galina", + "katrin", + "maie", + "urmas", + "laura", + "aivar", + "sergey", + "sergei", + "merike", + "malle", + "indrek", + "tatiana", + "marina", + "jaan", + "ljudmila", + "niina", + "dmitri", + "linda", + "mihkel", + "viktoria", + "tiina", + "natalja", + "jekaterina", + "juri", + "nina", + "aleksandr", + "julia", + "martin", + "marko", + "viktor", + "marek", + "natalia", + "elena", + "tamara", + "andrus", + "kristjan", + "ene", + "kristi", + "reet", + "anu", + "piret", + "t\u00f5nu", + "priit", + "eve", + "sirje", + "jaanus", + "tarmo", + "jevgeni", + "mare", + "tiit", + "mati", + "nikolai", + "peeter", + "andres", + "ivan", + "sander", + "siim", + "andrei", + "svetlana", + "tiiu", + "\u00fclle", + "nade\u017eda", + "irina", + "meelis", + "vladimir" + ], + "LAST_NAME": [ + "vasiliev", + "sirel", + "kostin", + "nazarov", + "p\u00f5der", + "johanson", + "k\u00e4sper", + "k\u00f5iv", + "raamat", + "leppik", + "maripuu", + "kivilo", + "k\u00e4\u00e4rik", + "p\u00f5ldma", + "k\u00fctt", + "kasak", + "loginov", + "urb", + "kiisk", + "kikkas", + "kuzmin", + "tuulik", + "vares", + "p\u00f5llu", + "salumets", + "koger", + "suits", + "sulg", + "tamme", + "aasa", + "roosileht", + "abel", + "vahtra", + "zahharov", + "\u0161t\u0161erbakov", + "rohtla", + "p\u00e4rnpuu", + "grigoriev", + "alas", + "paap", + "soon", + "olesk", + "titov", + "mikk", + "trofimov", + "m\u00f5ttus", + "filippov", + "vorobjov", + "timofejev", + "trei", + "ilves", + "ploom", + "p\u00f5ldmaa", + "holm", + "kadak", + "allik", + "kask", + "tooming", + "rebane", + "novikov", + "tamm", + "jaanson", + "kool", + "kroon", + "raud", + "raag", + "medvedev", + "klaas", + "oks", + "j\u00e4rv", + "kurg", + "kuningas", + "juhkam", + "aavik", + "kangro", + "sepp", + "lauri", + "jakobson", + "saare", + "kesk\u00fcla", + "frolov", + "remmel", + "hunt", + "fomin", + "v\u00e4hi", + "toom", + "roos", + "n\u00f5mmik", + "vaht", + "heinsalu", + "vinogradov", + "sarap", + "laanemets", + "h\u00e4rm", + "abramov", + "kotkas", + "sikk", + "tamberg", + "lipp", + "kangur", + "raadik", + "p\u00e4rna", + "j\u00f5gi", + "nurk", + "gorbunov", + "klimov", + "sander", + "vahter", + "tuisk", + "vill", + "arro", + "kaasik", + "kirs", + "kaljurand", + "suvi", + "mandel", + "saveljev", + "unt", + "kuusk", + "tali", + "beljajev", + "leht", + "fedorov", + "m\u00f6lder", + "anissimov", + "m\u00e4ndla", + "toomsalu", + "aasm\u00e4e", + "madisson", + "arula", + "danilov", + "mets", + "gusev", + "merila", + "soosaar", + "uibo", + "laks", + "jakovlev", + "p\u00e4rn", + "randmaa", + "silm", + "m\u00e4gi", + "andreev", + "teearu", + "poom", + "tilk", + "kase", + "pihlak", + "hanson", + "kulikov", + "teder", + "romanov", + "konovalov", + "kr\u00f5lov", + "\u00f5unapuu", + "toots", + "rosin", + "konstantinov", + "kohv", + "p\u00e4rtel", + "orav", + "paas", + "rumjantsev", + "lind", + "kallas", + "kasemaa", + "pajula", + "kirsipuu", + "antonov", + "k\u00e4rner", + "kalm", + "saul", + "mark", + "adamson", + "l\u00e4\u00e4ts", + "kuus", + "nuut", + "jer\u0161ov", + "juhanson", + "viira", + "m\u00e4nd", + "n\u00f5mme", + "m\u00fcrk", + "raudsepp", + "tsvetkov", + "kirillov", + "laane", + "tiik", + "maidla", + "vlassov", + "jalakas", + "volkov", + "peterson", + "laine", + "sisask", + "bogdanov", + "tihhomirov", + "kattai", + "uus", + "panov", + "m\u00e4nnik", + "v\u00e4li", + "kuuse", + "pent", + "pulk", + "kivim\u00e4e", + "laur", + "tuul", + "ernits", + "moroz", + "sarapuu", + "zujev", + "kivi", + "paal", + "kurm", + "lebedev", + "denissov", + "koit", + "kotov", + "puusepp", + "t\u00e4ht", + "allas", + "poljakov", + "\u017euravljov", + "kont", + "petrov", + "sorokin", + "kudrjavtsev", + "kuznetsov", + "kallaste", + "suur", + "maksimov", + "roots", + "meister", + "mironov", + "nikitin", + "r\u00fc\u00fctel", + "sibul", + "paju", + "palu", + "pavlov", + "semenov", + "popov", + "j\u00fcrgenson", + "maslov", + "koppel", + "kiik", + "j\u00fcrisson", + "baranov", + "l\u00e4\u00e4ne", + "reimann", + "maasik", + "ivask", + "lepp", + "karpov", + "aru", + "s\u00f6\u00f6t", + "kozlov", + "loorits", + "lumiste", + "m\u00fc\u00fcr", + "lillemets", + "melnik", + "kelder", + "m\u00e4nniste", + "varik", + "pruul", + "reinsalu", + "lehiste", + "oja", + "solovjov", + "j\u00fcrgens", + "sild", + "kilk", + "\u00f5un", + "link", + "veski", + "miller", + "kalmus", + "vain", + "afanasjev", + "heinsoo", + "raja", + "jermakov", + "kikas", + "kala", + "b\u00f5strov", + "susi", + "lukk", + "sillaots", + "tarassov", + "j\u00e4nes", + "moor", + "v\u00f5su", + "naumov", + "hallik", + "nurm", + "tammik", + "korol", + "kivistik", + "treial", + "leis", + "valge", + "luik", + "org", + "s\u00e4de", + "sutt", + "gross", + "koval", + "ots", + "truu", + "annus", + "egorov", + "alekseev", + "suvorov", + "tiits", + "kiis", + "l\u00e4tt", + "kolesnik", + "matvejev", + "laht", + "saks", + "nikolaev", + "p\u00f5ld", + "sarv", + "liiv", + "soo", + "p\u00f5dra", + "pukk", + "aas", + "schmidt", + "liblik", + "fedotov", + "soots", + "luts", + "teras", + "ignatjev", + "tomson", + "piir", + "toome", + "p\u00fcvi", + "liivak", + "j\u00f5e", + "lang", + "muru", + "oras", + "bondarenko", + "koitla", + "uustalu", + "kazakov", + "lomp", + "stepanov", + "salu", + "kapp", + "voronin", + "sobolev", + "erik", + "kaljula", + "fjodorov", + "sokolov", + "kruglov", + "koort", + "meier", + "dav\u00f5dov", + "kalda", + "kaur", + "parts", + "iljin", + "smirnov", + "kokk", + "sillaste", + "laan", + "eller", + "j\u00f5esaar", + "lember", + "lumi", + "vaino", + "randoja", + "mitt", + "aun", + "valk", + "ruus", + "gromov", + "mihhailov", + "palm", + "kasemets", + "teesalu", + "sidorov", + "m\u00e4esalu", + "kiil", + "kalamees", + "filatov", + "rand", + "safronov", + "makarov", + "r\u00e4tsep", + "kisseljov", + "saar", + "aus", + "drozdov", + "ojaste", + "piho", + "klein", + "viks", + "niit", + "hein", + "kondratjev", + "kaljuvee", + "jaakson", + "karro", + "lass", + "belov", + "anton", + "kirss", + "sergejev", + "ojala", + "zaitsev", + "sokk", + "visnapuu", + "\u017eukov", + "lehtmets", + "laas", + "\u00f5ispuu", + "piirsalu", + "l\u00f5hmus", + "pikk", + "taal", + "j\u00e4rve", + "treier", + "gerassimov", + "kuusik", + "markus", + "post", + "ossipov", + "\u0161evt\u0161enko", + "michelson", + "martin", + "liiva", + "ader", + "lehtla", + "ivanov", + "nikiforov", + "gavrilov", + "anderson", + "m\u00fc\u00fcrsepp", + "m\u00e4e", + "m\u00e4eots", + "must", + "erm", + "aleksandrov", + "kriisa", + "k\u00e4\u00e4r", + "simson", + "pihelgas", + "raidma", + "kink", + "kurvits", + "t\u00f5nisson", + "lepik", + "mal\u00f5\u0161ev", + "luht", + "kolk", + "rosenberg", + "jaanus", + "soosalu", + "n\u00f5mm", + "lokk", + "kass", + "martinson", + "komarov", + "borissov", + "villemson", + "golubev", + "pettai", + "orlov", + "liivam\u00e4gi", + "lukin", + "dmitriev", + "talts", + "siim", + "hansen", + "kaljuste", + "viik", + "salum\u00e4e", + "ott", + "lill", + "kutsar", + "tomingas", + "gont\u0161arov", + "raid", + "karu", + "jefimov", + "vaher", + "kalinin", + "jegorov" + ], + "OTHER_PRONOUN": [ + "it" + ], + "LAST_NAME_MALE": [], + "LAST_NAME_FEMALE": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "abtiss": "abt", + "lellenaine": "lell", + "paruness": "parun", + "\u00e4rinaine": "\u00e4rimees", + "t\u00fctar": "poeg", + "hertsoginna": "hertsog", + "plika": "t\u00fc\u00fcp", + "t\u00fcdruk": "kutt", + "pojat\u00fctar": "pojapoeg", + "t\u00fctret\u00fctar": "t\u00fctrepoeg", + "emaema": "emaisa", + "isaema": "emaisa", + "kangelanna": "kangelane", + "matrix": "es\u00e4", + "nunn": "munk", + "pr\u00edncipe": "prince", + "printsess": "prince", + "kuninganna": "kuningas", + "queens": "kuningate_raamatud", + "elu": "too", + "s\u00f5ssar": "veli", + "s\u00f5sar": "veli", + "\u00f5de": "veli", + "kasuema": "kasuisa", + "ikma": "leskmees", + "lesk": "ikma", + "naine": "man", + "n\u00f5id": "v\u00f5lur", + "wicca": "v\u00f5lur", + "nisu": "man", + "poiss": "plika" + }, + "other_gender_swap": { + "epi": "elu", + "nemad": "elu", + "too": "epi", + "ilu": "epi", + "elu": "epi" + }, + "en_pronoun2gender": { + "they": [ + "biseksuaalne" + ], + "he": [ + "kutt", + "mees", + "male", + "h\u00e4rra", + "gaur", + "man", + "t\u00fc\u00fcp", + "little_boy", + "poiss" + ], + "she": [ + "missa", + "preili", + "lesbi", + "nisu", + "plika", + "t\u00fcdruk", + "naine" + ] + }, + "en_pronoun2pronoun": { + "he": [ + "siis", + "elu", + "ilu", + "too", + "siin", + "seine" + ], + "she": [ + "sitt", + "elu" + ], + "they": [ + "sitt", + "nemad", + "epi" + ], + "it": [ + "too", + "need", + "it" + ] + }, + "en_pronoun2title": {}, + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/eu.json b/data_tooling/pii_processing/ontology/data/eu.json new file mode 100644 index 0000000..6034432 --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/eu.json @@ -0,0 +1,2165 @@ +{ + "JOB": [ + "elizako_doktore", + "pikadera", + "bizargile", + "interpretari", + "zentsuratzaile", + "kartzelari", + "laburtzaile", + "marrazkilari", + "korazari", + "lorazain", + "zuzendari", + "tailista", + "planifikatzaile", + "guru", + "fundatzaile", + "ferratzaile", + "maitre", + "karrozazain", + "marrazkigile", + "ertzainburu", + "tailugile", + "bereter", + "fabrikatzaile", + "etxezain", + "bolazain", + "sarrailgin", + "dendari", + "hobiratzaile", + "markatzaile", + "komandante", + "gortesau", + "faltsutzaile", + "tapizari", + "bokatari", + "sindikatzaile", + "berreskuratzaile", + "estatistikari", + "gerrari", + "gainbegiratzaile", + "zergari", + "zuzendaritza_departamentu", + "galeriano", + "bukatzaile", + "tornulari", + "maneiatzaile", + "kozinatu", + "fabrikante", + "armagin", + "urreztatzaile", + "ekortu", + "garagardo_beltz", + "mariskal", + "en_buru_izan", + "kartografo", + "faltsifikatzaile", + "brotxal", + "tripulatzaile", + "espetxeburu", + "botereguztidun", + "don", + "king", + "asmatzaile", + "tapizgile", + "mendizain", + "gerontologo", + "banderari", + "konpositore", + "haginlari", + "gelari", + "bolatzaile", + "the_police", + "margotzaile", + "larrugin", + "pintore", + "bankari", + "eskulangile", + "terapeuta", + "hegazkinlari", + "gelazain", + "skinner", + "sakristau", + "losintxari", + "hartzekodun", + "artatu", + "kargudun", + "errotulatzaile", + "saskiratzaile", + "otsein", + "trimmer", + "amaitzaile", + "eratzaile", + "boluntario", + "estomatologo", + "saiolari", + "liburuzain", + "diplomazi_ministro", + "komodoro", + "seneskal", + "perzkin", + "paketatzaile", + "jokozain", + "ero_sendagile", + "para", + "lematu", + "unionista", + "lagunkide", + "garraiatzaile", + "zamaltzain", + "zeramista", + "sarraskijale", + "ingeniari", + "mandazain", + "tren_makinista", + "mastermind", + "hitzemaile", + "albaitari", + "lehendakari", + "hargailu", + "yatelari", + "errabino", + "gautxo", + "buruxkari", + "zentsore", + "aztarnari", + "alderdiburu", + "alkate", + "mintzazaile", + "agintariorde", + "maletazain", + "gerente", + "gudamutil", + "sakatzaile", + "banderadun", + "elektronikari", + "garri", + "farolari", + "intendente", + "ile_apaintzaile", + "fintzaile", + "legegizon", + "karrozagin", + "nobelagile", + "mintzalari", + "industriari", + "brigadier", + "kliniko", + "alferiz", + "antolatzaile", + "argazkilari", + "gurdizain", + "kamikaze", + "osteopata", + "arratoi", + "driver", + "aseguru_agente", + "kirurgialari", + "kantagile", + "dermatologo", + "interpretatzaile", + "erradiologo", + "kameralari", + "salerosle", + "pastelgile", + "karroza", + "takigrafo", + "bisir", + "margolari", + "manifestari", + "koordinatzaile", + "udaltzain", + "grebalari", + "haziendazain", + "beterano", + "burgumaisu", + "oharrarazle", + "master", + "the_guardian", + "ginekologo", + "goldelari", + "garbitzaile", + "kabalzain", + "partzuer", + "biltzaile", + "karikaturagile", + "bidaide", + "geofisikari", + "granadari", + "mandarin", + "mandatugile", + "buruzagi", + "elkarkide", + "botilari", + "istripu_zerebrobaskular", + "setter", + "arrailari", + "galdaragile", + "orrialde", + "kaligrafo", + "mate", + "ebanista", + "aseguru_flotatzaile", + "sugile", + "bizargin", + "lorezain", + "garraiolari", + "larreratu", + "kopari", + "jole", + "neurokirurgilari", + "botikari", + "amiralorde", + "mintzatzaile", + "fosforu", + "bulegari", + "taldeburu", + "erizain", + "zarakar", + "umezain", + "presozain", + "pastor", + "mailegatzaile", + "txanpongile", + "sheriff", + "sakalari", + "maketagile", + "sorosle", + "zaharberritzaile", + "eramaile", + "tailagin", + "gauzain", + "aldeko", + "kristalari", + "eskirol", + "markazain", + "behizain", + "kanpaigile", + "mahaizain", + "bozeramaile", + "alkaide", + "treveris", + "lotinant", + "fideikomisodun", + "golegile", + "amatatzaile", + "trakzio", + "geometria_irakasle", + "the_economist", + "abiadore", + "tokologo", + "lantzari", + "okin", + "latorrigile", + "beiragile", + "maistra", + "carter", + "gabarrari", + "haurtzain", + "argitaletxe", + "igeltsero", + "saiogile", + "neurologo", + "piraguista", + "artezilari", + "errotari", + "merkatari", + "koronel", + "kronikari", + "man", + "eskultore", + "marine", + "zamaketari", + "eleberrigile", + "kardiologo", + "subirano", + "elizain", + "urdain", + "hematologo", + "botari", + "argitaratzaile", + "sarrailari", + "biharamun", + "barano", + "hazle", + "the_machinist", + "trazu", + "kamioilari", + "haratusteljale", + "tindatzaile", + "gantzulari", + "bestondo", + "au_pair", + "tenienteorde", + "orga_gidari", + "despentsari", + "zientzialari", + "proconsul", + "zubizain", + "kudeatzaile", + "presondegiburu", + "teniente", + "baleazale", + "sukaldari", + "papereztatzaile", + "kronometratzaile", + "bustigailu", + "giltzain", + "takimekanografo", + "bilakari", + "paraxutista", + "bigarren", + "karrozari", + "baratzezain", + "croupier", + "kantziler", + "maiordomo", + "edarizain", + "trangadera", + "the_deer_hunter", + "interprete", + "latorrilari", + "neurozirujau", + "printzipal", + "ebakitzaile", + "kaporal", + "diseinugile", + "seintzain", + "zirujau", + "giltzari", + "funtzionario", + "cookie", + "tramoiari", + "pintatzaile", + "egile", + "mazolari", + "arinkari", + "rocker", + "entziklopedista", + "gainkargu", + "pastore", + "administrazio_sail", + "upelagile", + "aje", + "langilezain" + ], + "PUBLIC_FIGURE": [ + "lawrence_durrell", + "henry_cavendish", + "lambert", + "lev_ivanov", + "benjamin_franklin", + "martin_buber", + "akira_kurosawa", + "noah_webster", + "jean_genet", + "john_knox", + "heinrich_hertz", + "jean_laffite", + "giovanni_boccaccio", + "rudolf_steiner", + "thomas_wolfe", + "thomas_bayes", + "ben_hogan", + "maria_magdalakoa", + "johann_bernoulli", + "arte_irakasle", + "leonard_bernstein", + "che_guevara", + "georges_simenon", + "c", + "augustin_fresnel", + "edward_albee", + "dorothy_parker", + "maria_callas", + "william_walton", + "henrik_ibsen", + "makiavelo", + "vasili_kandinski", + "mary_shelley", + "marcello_malpighi", + "peter_lorre", + "karl_baedeker", + "david_livingstone", + "john_herschel", + "gauss", + "andrzej_wajda", + "jan_van_eyck", + "carl_rogers", + "george_balanchine", + "richard_burton", + "douglas_macarthur", + "mary_wollstonecraft", + "maria_magdalena", + "thomas_reid", + "john_jacob_astor", + "protagonistakide", + "anna_pavlova", + "winston_churchill", + "trobalari", + "b", + "karl_landsteiner", + "ivan_pavlov", + "paul_mccartney", + "andrew_marvell", + "terry_pratchett", + "stephen_king", + "francis_crick", + "isaac_newton", + "victor_hugo", + "joseph_smith", + "edwin_hubble", + "milton_friedman", + "edward_gibbon", + "jefferson_davis", + "saint_louis", + "george_stephenson", + "john_glenn", + "john_davis", + "george_harrison", + "ponpeio", + "peter_minuit", + "george_orwell", + "maximiano", + "arthur_koestler", + "richard_wagner", + "thornton_wilder", + "pancho_villa", + "leopold_stokowski", + "marie_curie", + "francis_galton", + "michael_jackson", + "carl_sandburg", + "thomas_hobbes", + "partitzaile", + "samuel_beckett", + "david", + "galileo_galilei", + "jane_goodall", + "chaim_weizmann", + "elizabete", + "robert_koch", + "george_eastman", + "john_steinbeck", + "edmund_hillary", + "vincent_van_gogh", + "martina_navr\u00e1tilov\u00e1", + "magallaes", + "john_ruskin", + "robert_burns", + "koblakari", + "thomas_paine", + "hans_jurgen_eysenck", + "steven_weinberg", + "estatuburu", + "mary_pickford", + "emiliano_zapata", + "elisabet", + "karl_barth", + "phil_anderson", + "samuel_johnson", + "jesus", + "katalina", + "marie_antoinette", + "giuseppe_verdi", + "e", + "karl_jaspers", + "gehiago", + "beethoven", + "hideki_yukawa", + "konrad_adenauer", + "norbert_wiener", + "mark_rothko", + "maurice_chevalier", + "frank_sinatra", + "abel_tasman", + "katharine_hepburn", + "henri_becquerel", + "henri_matisse", + "bertram_brockhouse", + "kasio", + "louis_pasteur", + "j", + "richard_strauss", + "leslie_howard", + "hugo_grotius", + "ben_shahn", + "john_ford", + "katherine_mansfield", + "gertrude_stein", + "bolazain", + "saladin", + "sarah_bernhardt", + "philip_marlowe", + "luigi_pirandello", + "t_s_eliot", + "igor_stravinski", + "charles_de_gaulle", + "paul_von_hindenburg", + "y", + "henry_moore", + "rudolf_bultmann", + "charles_lindbergh", + "vincenzo_bellini", + "sastrakadi", + "samuel_barber", + "tobias_smollett", + "f", + "ludwig_wittgenstein", + "august_strindberg", + "thomas_mann", + "charles_goodyear", + "dante_alighieri", + "behetar", + "margot_fonteyn", + "peter_pan", + "james_tobin", + "john_irving", + "samuel_de_champlain", + "giacomo_puccini", + "fridtjof_nansen", + "louis_braille", + "herbert_marcuse", + "mungo_park", + "paul_verlaine", + "james_dean", + "zientzia_irakasle", + "roger_bannister", + "theodor_schwann", + "alessandro_manzoni", + "joseph_priestley", + "nicolas_poussin", + "andrea_mantegna", + "joseph_pulitzer", + "oscar_wilde", + "philip_roth", + "henry", + "kuria", + "heinrich_schliemann", + "laurence_olivier", + "pierre_larousse", + "christiaan_eijkman", + "adolf_eichmann", + "marilyn_horne", + "francis_bacon", + "pete_seeger", + "konstantin_stanislavski", + "a", + "morris", + "peter_brian_medawar", + "mendizain", + "james_brown", + "william_hogarth", + "ameriko_vespuzio", + "charles_baudelaire", + "luigi_cherubini", + "david_ricardo", + "henri_labrouste", + "mary_leakey", + "charlie_parker", + "z", + "immanuel_kant", + "james_franck", + "william_crookes", + "weber", + "alexandre_yersin", + "n", + "albert_schweitzer", + "giulio_natta", + "johannes_kepler", + "max_planck", + "william_blake", + "t_e_lawrence", + "julio_iglesias", + "john_bardeen", + "john_wilkes", + "christopher_fry", + "scott_joplin", + "carl_lewis", + "sarah_siddons", + "canberra", + "elias_canetti", + "edward_jenner", + "juglare", + "oreonympha_nobilis", + "moises", + "oliver_hardy", + "san_martin", + "cole_porter", + "benjamin_west", + "jean_luc_godard", + "graham_greene", + "frans_hals", + "lars_onsager", + "igor_stravinsky", + "stuart_davis", + "jan_swammerdam", + "mary_mccarthy", + "david_riesman", + "john_walker", + "william_herschel", + "ernst_hoffmann", + "joseph_black", + "montesquieu", + "arthur_rubinstein", + "karmelita", + "arthur_compton", + "leon_trotski", + "niels_bohr", + "kenneth_grahame", + "henry_fielding", + "bertrand_russell", + "katherine_anne_porter", + "michael_faraday", + "sergei_rakhmaninov", + "anthony_burgess", + "jan_tinbergen", + "robert_venturi", + "johnny_appleseed", + "rudolf_diesel", + "walt_disney", + "ben_jonson", + "joseph_schumpeter", + "steve_reich", + "lee", + "benny_goodman", + "friedrich_engels", + "jane_austen", + "charles_laughton", + "gustav_mahler", + "phil_collins", + "robert_redford", + "jean_giraudoux", + "on_kixote", + "ian_fleming", + "richard_feynman", + "wolfgang_pauli", + "theodore_dreiser", + "theodor_mommsen", + "erremintari", + "marcel_proust", + "thomas_more", + "homo_heidelbergensis", + "paul_hindemith", + "elizabeth_taylor", + "thomas_chippendale", + "paul_robeson", + "john_dowland", + "william_golding", + "robert_motherwell", + "john_milton", + "rudolf_serkin", + "peter_stuyvesant", + "c_programazio_lengoaia", + "samuel_adams", + "james_baldwin", + "john_vanbrugh", + "indira_gandhi", + "jane_seymour", + "george_gershwin", + "alberto_giacometti", + "frank_whittle", + "alfred_nobel", + "jesse_owens", + "marco_polo", + "macaca_nemestrina", + "john_fletcher", + "jeronimo_bosch", + "caravaggio", + "charlotte_corday", + "marcel_marceau", + "allen_ginsberg", + "fred_zinnemann", + "daniel_bernoulli", + "guillaume_apollinaire", + "antoine_watteau", + "joseph_henry", + "henri_bergson", + "josef_hoffmann", + "zizeron", + "boris_karloff", + "pierre_corneille", + "on_kixote_mantxakoa", + "patrick_white", + "hans_christian_andersen", + "reich", + "william_morris", + "cary_grant", + "valentina_terexkova", + "ford", + "pieter_zeeman", + "glenn_miller", + "zintzinato", + "pablo_picasso", + "marian_anderson", + "natalie_wood", + "alan_hodgkin", + "thomas_moore", + "kurt_weill", + "otto_hahn", + "lester_young", + "christiaan_huygens", + "hector_berlioz", + "paul_simon", + "claudio_monteverdi", + "stravinsky", + "john_galsworthy", + "robert_robinson", + "o", + "adam_smith", + "william_james", + "jean_harlow", + "henry_miller", + "karl_marx", + "friedrich_nietzsche", + "i", + "robert_indiana", + "william_burroughs", + "john_wesley", + "sandro_botticelli", + "carson_mccullers", + "seiji_ozawa", + "nikola_tesla", + "al_capone", + "charles_barkley", + "robert_schumann", + "mel_gibson", + "le_corbusier", + "carlo_goldoni", + "john_locke", + "alexis_carrel", + "joseph_marie_jacquard", + "henry_james", + "helen_keller", + "paul_dukas", + "ingrid_bergman", + "leonard_bloomfield", + "jean_piaget", + "henri_rousseau", + "frank_norris", + "sekula_belar", + "frank_stella", + "robert_southey", + "walt_whitman", + "william_wyler", + "colin_powell", + "ludwig_boltzmann", + "carl_nielsen", + "chopin", + "karl_maria_von_weber", + "adolf_hitler", + "maria_mitchell", + "san_jurgi", + "fritz_haber", + "archibald_macleish", + "joseph_haydn", + "george_boole", + "zibeles", + "daniel_boone", + "buffalo_bill", + "edvard_grieg", + "robert_boyle", + "alan_paton", + "james_wilson", + "rosa_parks", + "tomas", + "samuel_goldwyn", + "fresatzeko_makina", + "x", + "vladimir_putin", + "giuseppe_mazzini", + "jim_thorpe", + "hertz", + "arnold_sch\u00f6nberg", + "laurence_sterne", + "george_fox", + "christopher_isherwood", + "anne_hathaway", + "margaret_court", + "emile_zola", + "charles_lamb", + "g", + "anthony_comstock", + "arthur_schopenhauer", + "thomas_dekker", + "james_cagney", + "henri_pitot", + "wanda_landowska", + "martin_heidegger", + "r", + "george_lucas", + "andrew_jackson", + "louis_armstrong", + "antony_tudor", + "steven_spielberg", + "jean_monnet", + "robert_fulton", + "thomas_hardy", + "thomas_gainsborough", + "giuseppe_garibaldi", + "alexandre_dumas", + "thomas_carlyle", + "bobby_fischer", + "johannes_gutenberg", + "thomas_malthus", + "giambattista_marino", + "gaetano_donizetti", + "william_faulkner", + "andre", + "pierre_boulez", + "hans_adolf_krebs", + "bolzano_bozen", + "girolamo_savonarola", + "emma_goldman", + "anna_kournikova", + "francis_poulenc", + "john_constable", + "putin", + "matthew_flinders", + "jean_de_la_fontaine", + "robert_hooke", + "o_henry", + "karl_popper", + "hegaldiko_laguntzaile", + "mary_harris", + "george_sand", + "peter_sellers", + "homo_rhodesiensis", + "charles_fourier", + "peter_o'toole", + "joseph_conrad", + "william_shockley", + "peter_paul_rubens", + "jim_morrison", + "jules_verne", + "paul_newman", + "george_meredith", + "robert_morris", + "jackson_pollock", + "john_lennon", + "andrea_palladio", + "charlie_chaplin", + "d_h_lawrence", + "john_brown", + "elizabeth_gaskell", + "hugo_junkers", + "lillian_hellman", + "carter", + "thomas_merton", + "hannah_arendt", + "antonio_stradivari", + "robinson_jeffers", + "andrei_sakharov", + "miles_davis", + "itzain", + "edmund_cartwright", + "george_marshall", + "jesse_jackson", + "willa_cather", + "stanley_kubrick", + "john_huston", + "william_gilbert", + "james_watt", + "jonathan_edwards", + "ronald_reagan", + "gorka", + "helmut_schmidt", + "homo", + "frederick_douglass", + "david_hilbert", + "skinner", + "wilhelm_reich", + "oliver_cromwell", + "lionel_hampton", + "martin_luther_king", + "frank_capra", + "william_wordsworth", + "rex_harrison", + "s", + "william_clark", + "woodrow_wilson", + "margaret_sanger", + "gustav_hertz", + "richard_rodgers", + "morgana", + "john_dryden", + "jim_henson", + "b\u00e9la_lugosi", + "ernest_hemingway", + "george_westinghouse", + "aquila", + "richelieu_kardinala", + "jacques_charles", + "eero_saarinen", + "arthur_miller", + "john_cheever", + "bolatzaile", + "nelson_mandela", + "heinrich_himmler", + "al_gore", + "hans_bethe", + "hans_geiger", + "cesare_borgia", + "roald_amundsen", + "sherwood_anderson", + "richard_leakey", + "charles_dickens", + "ella_fitzgerald", + "fats_waller", + "thomas_sydenham", + "george_enescu", + "wallace_carothers", + "jacques_offenbach", + "joseph_paxton", + "william_curtis", + "george_stevens", + "federico_fellini", + "willy_brandt", + "francisco_pizarro", + "francisco_franco", + "bernardo_bertolucci", + "jan_steen", + "john_ross", + "andrew_carnegie", + "franz_schubert", + "johnny_cash", + "joseph_mccarthy", + "alfred_kastler", + "mick_jagger", + "otto_loewi", + "georges_cuvier", + "william_harvey", + "walter_scott", + "august_von_wassermann", + "vladimir_lenin", + "robert_peary", + "robert_browning", + "antton", + "comenius", + "ralph_ellison", + "john_bunyan", + "jonathan_swift", + "goebbels", + "walter_gropius", + "albert_einstein", + "l", + "robert_joffrey", + "chiang_kai_shek", + "claude_bernard", + "raymond_chandler", + "henry_purcell", + "t" + ], + "FAC": [ + "komisarian", + "komisaria", + "komisaldegi", + "enparantza", + "saltegi", + "kiroldegi", + "josef_nazaretekoa", + "arnold_sch\u00f6nberg", + "plaza", + "santa_luzia", + "donostia", + "petri_i.a_errusiakoa", + "herriko_etxe", + "san_jakue", + "postetxe", + "erostetxe", + "familia_santua", + "hogeita_hamahiru", + "erromatar_eliza_katolikoa" + ], + "ANIMAL": [ + "gabatxo", + "terenura_sharpei", + "urretxori", + "basazaldi", + "xibarta", + "apodemus", + "mandeuli", + "monachus_schauinslandi", + "atalar", + "kaliforniar_galeper", + "kurruka", + "komatula", + "martin_hegalzuri", + "erbinude", + "zelabere", + "arkanbele", + "lehoikume", + "aie_aie", + "sai_arre", + "billy_elliot", + "adarzabal", + "hegagorri", + "pasatzaile", + "mirounga_leonina", + "basasto", + "hontza", + "basahuntz", + "belatz", + "canis_minor", + "manta", + "sitta_carolinensis", + "kurumino", + "carduelis", + "gauhontz", + "erlama", + "kalimotxo", + "mantodea", + "istingor", + "erne", + "muxar_gris", + "antseriforme", + "pertziforme", + "beletxiki", + "apodun", + "zapelatz", + "atalo", + "mokoker", + "felido", + "basurde", + "gailupa", + "marikoi_handi", + "erremige", + "galgo", + "frantximent", + "hegabera", + "pinipedio", + "la_ardilla_roja", + "anuru", + "zigala", + "koartza", + "passer", + "itsasantzar", + "artiodaktilo", + "andrezale", + "kaleko_katu", + "belabeltz", + "lagopodo", + "birigarro", + "cocker", + "tetraoninae", + "larreoilo", + "accipiter", + "sai_beltz", + "hankarin", + "betaundi", + "garraztarro", + "gautar", + "basoilar", + "limikolo", + "giloi", + "basatxakur", + "banteng", + "ikaraio", + "pagauso", + "zinipido", + "kolaka", + "luhartz", + "diktioptero", + "erlatxori", + "perisodaktilo", + "ammospermophilus", + "ictiobus_niger", + "muskuilu", + "sable", + "tintoleta", + "herpes_zoster", + "basasagu", + "mazopa", + "oniscidea", + "mirotz", + "eskarda", + "estomatomikosi", + "milazango", + "zankaluze", + "makarela", + "erroi", + "errauli", + "flagelatu", + "ziraun", + "zamari", + "katamotz", + "holoturia", + "fukusa", + "sai_motz", + "mamalio", + "sitta_canadensis", + "artropodo", + "cadernera", + "sai_papargorri", + "zerbido", + "gautxori", + "labezomorro", + "salvelinus_fontinalis", + "eagle", + "gonazale", + "homoptero", + "hontz", + "ross_antzara", + "martin_arrantzale", + "kondor", + "martes_zibellina", + "katagorri", + "sai_zuri", + "karnaba", + "peristediidae", + "eider", + "zeroi", + "arvicola" + ], + "LOCATION": [ + "al_jazeera", + "jokaleku", + "burdinbide", + "psikiatriko", + "patrizio_irlandakoa", + "ameriketako_estatu_batuetako_armada", + "corpus_christi", + "yangzi", + "kristobal_kolon", + "piet_mondrian", + "gabonzahar", + "sint_maarten", + "badaezpada", + "banalerro", + "hornos_lurmuturra", + "selvagens", + "justiziako_sala", + "saint_vincent", + "osman_i.a", + "ez_horregatik", + "hungariako_biltzar_nazionala", + "bizarzuri", + "usa", + "ingalaterra_berria", + "oihanetako_aintzira", + "sri_lanka", + "urtezahar_gau", + "banku_zentral", + "eroetxe", + "kantxa", + "three_amigos", + "ha_long_badia", + "the_rolling_stones", + "falklandak", + "kryvyi_rih", + "estatu_batuak", + "heitor_villa_lobos", + "louis_joseph_gay_lussac", + "karmel_mendia", + "frantziako_nazio_biltzarra" + ], + "PERSON": [ + "tai_mendia", + "al_gore", + "c_bitamina", + "saint_vincent", + "gioconda", + "i_ching", + "william_playfair", + "onddozuri", + "don_delillo", + "edward_osborne_wilson", + "autoestimu", + "autodiziplina", + "autoestimazio", + "carl_david_anderson", + "yo_yo", + "herbert_george_wells" + ], + "DISEASE": [ + "su_eman", + "arbindu", + "sastako", + "goragale", + "mizetismo", + "inarrosaldi", + "bahitze", + "eskoliosi", + "afariusi", + "bektore", + "polinosi", + "errubeola", + "eskorbuto", + "geun", + "erredura", + "landaretza", + "ernaldi", + "orbain", + "bozio", + "kolazio", + "kuraia", + "analgesia", + "larreratze", + "kukutxeztul", + "salmonellosi", + "betxindor", + "xaramel", + "ahuspezte", + "herdoildura", + "negel", + "aldigaizto", + "progeria", + "sinfisi", + "ernalmin", + "pikante", + "zurieri", + "hamarretako", + "esklerosi", + "legenar", + "erradiazio", + "erremin", + "makatu", + "toxikomania", + "energy", + "minusbaliotasun", + "eskrofula", + "itsutasun", + "erreumatismo", + "berezi", + "maskur", + "konplikazio", + "galbeko", + "zornadura", + "erroseta", + "esterilitate", + "juanikote", + "eskorbutu", + "beriberi", + "kondizio", + "elgorri", + "mania", + "alderantzikatze", + "handitsu", + "umeske", + "zitomegalobirus", + "struma", + "phytophthora_infestans", + "sumundu", + "min_hori", + "dementzia", + "poliomielitis", + "ziro", + "eskarlatina", + "deshidratazio", + "distrofia", + "franbesia", + "karrakatze", + "ernetasun", + "alditxar", + "karranpa", + "dosifikazio", + "bateraezintasun", + "pirosi", + "klaustrofobia", + "ez_gustatu", + "gainazpiketa", + "indigestio", + "down_sindrome", + "pelagra", + "kretinismo", + "sarjenta", + "desmineralizazio", + "furunkulu", + "beltzarandu", + "burtsitis", + "para", + "aheri", + "gaztaina", + "katarata", + "handicap", + "ubeldu", + "mieloma", + "talasemia", + "zimeltze", + "urbasa", + "hamaiketako", + "loeri", + "babatu", + "begetazio", + "zaintiratu", + "tetelatu", + "urtzaile", + "pedikulu", + "indurazio", + "sabelaldi", + "anasarka", + "takikardia", + "perlesia", + "kailu", + "xerratu", + "faringitis", + "goitenperatura", + "erreskaldatu", + "delirium", + "erregresio", + "estrabismo", + "zainbihurtu", + "izozketa", + "herdoiltze", + "aholegar", + "erisipela", + "toteltasun", + "araldi", + "maingutasun", + "beherako", + "gorrina", + "haurduntza", + "silikosis", + "kolitis", + "gimp", + "oestrus", + "biroide", + "erraldoitasun", + "frenzy", + "hernia", + "leuzemia", + "alexia", + "herpes", + "toxemia", + "kartzinoma", + "lo_egin", + "astanafarreri", + "elbarritasun", + "doministiku", + "paralisi", + "arreske", + "katalepsia", + "ezkeltasun", + "trokatze", + "garatxo", + "gaixotasun", + "tentetze", + "kalanbre", + "barizela_zoster_birus", + "gandu", + "helgaitz", + "kokainazaletasun", + "kolapso", + "moldagabezia", + "the_sting", + "listeriosi", + "erretrobirus", + "pozoidura", + "erreuma", + "oftalmia", + "inpetigo", + "murmur", + "lunbago", + "makaleria", + "odoljario", + "erdibitu", + "paludismo", + "hazizurri", + "adipositate", + "lo_galtze", + "heroinomania", + "satar", + "polidaktilia", + "kokainomania", + "loratu", + "zoster_herpes", + "the_passion_of_the_christ", + "purpura", + "freskotasun", + "mugiarazi", + "filtrazio", + "barizela", + "tontotasun", + "laringitis", + "lokadura", + "hordikeria", + "paraplegia", + "als_uhartea", + "kaltzifikazio", + "distentsio", + "mielitis", + "bazkatze", + "betor", + "ebola_gaixotasun_biriko", + "hantura", + "mongolismo", + "bekatxo", + "barize", + "mi", + "kongestio", + "gibeleko", + "aura", + "beltz_beltz", + "kakexia", + "erlakizten", + "txerritegi", + "sting", + "gorreri", + "gainazpikaldi", + "burtzoro", + "haurdunaldi", + "arritmia", + "biriketako", + "azkordin", + "zinkurin", + "tronbosi", + "oilaur", + "alborengo", + "trauma", + "silikosi", + "errotabirus", + "fundatzaile", + "larrudura", + "uspeldu", + "baginismo", + "gangeri", + "logabezia", + "eskandalizatu", + "pozoitze", + "bruzelosi", + "salmonelosi", + "ihartze", + "zailtze", + "abitaminosi", + "sugarrastu", + "flemoi", + "zornatu", + "zimeldura", + "min_gorri", + "pirexia", + "amigdalitis", + "minbizi", + "salmonella", + "odolustu", + "paresia", + "horditasun", + "malaria", + "errakitismo" + ], + "PLANT": [ + "sagarmin", + "indi_gaztaina", + "haltz", + "basaerramu", + "aihenzuri", + "melissa", + "gereziondo", + "minbera", + "bioleta", + "the_joshua_tree", + "astakardo", + "heskai", + "helianthus", + "almeza", + "beltxata", + "krisantemo", + "solanaceae", + "kinkina", + "lasturrin", + "apoperrexil", + "tartiku", + "sikomoro", + "gandoilar", + "amanita", + "marmaratilla", + "mastika", + "basabitxilore", + "santa_maria", + "gramineo", + "pastana", + "arkakarats", + "babarrun_loregorri", + "iraka", + "basaka", + "salix_triandra", + "azalore", + "bergamotondo", + "convolvulus", + "gentiana_lutea", + "aranondo", + "kautxu_zuhaitz", + "arctostaphylos_alpina", + "sakura", + "gingondo", + "papaver", + "urdinbelar", + "tipuleta", + "guinda", + "klementinondo", + "arantzabeltz", + "irabelar", + "urbeltz", + "hidrofito", + "gerezi", + "goilora", + "alkanforrondo", + "basagereziondo", + "mendaski", + "oilakaran", + "urrilo", + "basaran", + "manioka", + "astapiko", + "sasiakazia", + "ositxeka", + "santio_belar", + "kamamila", + "palaxu", + "dianthus_barbatus", + "terebuzu", + "pipermorro", + "margosa", + "basabaratxuri", + "ostartx", + "garraiska", + "lekugi", + "eglantina", + "azenario", + "getozka", + "basagurbe", + "okotillo", + "saiestu", + "pinu", + "astigar", + "astalikardu", + "laritz", + "phytophthora_infestans", + "sasifruitu", + "abaritz", + "martxuka", + "marakuia", + "zurikatx", + "milorri", + "kardamomo", + "helofito", + "blackberry", + "solanum", + "erremolatxa", + "lo_belar", + "ahuntzadar", + "sasiokaran", + "anagallis_tenella", + "mostaza", + "pseudokarpo", + "frantses_patata", + "sabina", + "arum", + "cyperus_papyrus", + "saccharomyces_cerevisiae", + "kaputxina", + "txirimoia", + "zalke", + "hazibiluzi", + "eskuhori", + "eskortzonera", + "askimotz", + "errebelar", + "asentsio", + "belaiki", + "alertze", + "likidanbar", + "basatabako", + "kotiledoibiko", + "azaburu", + "gentiana_acaulis", + "mingots", + "nasturtium", + "legeltxor", + "hierarka", + "kuleto", + "zimelegur", + "edelweiss", + "sasiama", + "alkanfor", + "sahats", + "phytolacca_americana", + "artelatz", + "belladonna", + "bruselaza", + "zikadal", + "arctostaphylos_uva_ursi", + "myrica_gale", + "lausarda", + "sapelar", + "castanea", + "magnolia", + "errizino", + "arangurbe", + "ginga", + "barrengorri", + "zihaurri", + "sandalo" + ], + "SOC_ECO_CLASS": [ + "merkatu_beltz", + "nekazalgo", + "anaiarte", + "esnegain", + "samurai", + "emakumetasun", + "gizarte", + "burgesia", + "pikatxoi", + "proletalgo", + "gantzugailu", + "noblezia" + ], + "FOOD": [ + "bexamel", + "gosaldu", + "mousse", + "tripotx", + "ile_gogortzaile", + "barruki", + "postre", + "hostore", + "janari_laster", + "pinazi", + "pipermin", + "budin", + "galirin", + "hanburgesa", + "gosari", + "txingoma", + "menda_likore", + "chili", + "babarrun_zuri", + "gomagoxo", + "deserta", + "zuringo", + "gibelerrai", + "esne_gaingabetu", + "urazukre", + "sakote", + "limonada", + "indipiku", + "nahaski", + "freskagarri" + ], + "ORG": [ + "postetxe", + "auto_fabrikatzailea", + "batailoi", + "doi", + "gabonzahar_gau", + "gorbernu", + "kode_zibil", + "loti_ederra", + "lizeo", + "pluskuanperfektu", + "proletalgo", + "ibai_horia", + "jan_mayen", + "espazio_metriko", + "the_usual_suspects", + "san_nikolas", + "aa", + "nasa", + "bollywood", + "on_egin", + "gorteiatzaile", + "europol", + "schutzstaffel", + "konstantzako_kontzilioa", + "justizia_departamentu", + "the_who", + "san_nikolas_barikoa", + "laukitxo", + "haganah", + "sasienpresa", + "on_dagizula", + "yangzi", + "hamaikako", + "gomagoxo", + "san_francisco", + "norvegiako_alderdi_laborista", + "bitxigintza", + "herri_fronte", + "aire_armada", + "kode_penal", + "gudaroste", + "justizia_sail", + "alemaniako_langile_alderdi_nazionalsozialista", + "klasismo", + "brahmanismo", + "gao", + "ikerketa_bulego_federala", + "eliza_katolikoa", + "irlandako_alderdi_berdea", + "aeb", + "saint_vincent", + "josef_nazaretekoa", + "gabonzahar", + "the_faculty", + "alderdi_kontserbadorea", + "erresuma_batuko_alderdi_kontserbadorea", + "bateko", + "dia", + "taoismo", + "arraintalde", + "etxe_zuria", + "framazoneria", + "psikiatriko", + "lorategi_botaniko", + "frankmazoneria", + "vishnuismo", + "han_dinastia", + "the_breakfast_club", + "rabindranath_tagore", + "gestapo", + "barnetegi", + "hautesbarruti", + "santa_helena", + "donostia", + "the_full_monty", + "auzitegi_goren", + "andromeda_galaxia", + "erregimen", + "andrekoi", + "eskola", + "alderdi_komunista", + "masoneria", + "frantziako_alderdi_sozialista", + "pentsio_plan", + "abangoardismo", + "alderdi_laborista", + "eltzeitsu", + "i_ching", + "al_jazeera", + "fronte_popularra", + "alderdi_progresista", + "po", + "telekomunikazioen_batasun_internazionala", + "mossad", + "enara_arrunt", + "nautilus_pompilius", + "the_grapes_of_wrath", + "armada_gorria", + "koadrikula", + "ursa_major", + "tabakogintza", + "saint_barth\u00e9lemy", + "los_angeles", + "nato", + "aldundi", + "mariaren_jasokundea", + "mazoneria", + "eliza_katoliko", + "mi", + "by_the_way", + "hanpa", + "irakaskuntza_erakunde", + "hartz_handia", + "hazibide", + "goi_mailako_klase", + "ilberri", + "hedabide", + "errebindikazio", + "blue_jeans", + "troiatar", + "streptococcus_pyogenes", + "txingoma", + "lis_lore", + "mahainguru", + "olibetako_mendia", + "haredi", + "superpotentzia", + "ospitale_psikiatriko", + "irakaskuntza", + "on_dagizuela", + "s\u00e3o_tom\u00e9" + ], + "QUANTITY": [ + "daniar_koroa", + "seiren", + "dinar", + "kaloria", + "frantziar_libera", + "libera", + "g", + "bederatziren", + "elektronvolt", + "rial", + "bosten", + "daktilografia", + "milioiren", + "anders_celsius", + "laurogeita_hamahiru" + ], + "LANGUAGE": [ + "jidish", + "katalana", + "cree_etnia", + "hungariar", + "arabiera", + "portugaldar", + "irlandera", + "greziera", + "kongo", + "hindiera", + "poloniera", + "portuges", + "mazedoniera", + "gaztelania", + "islandiera", + "zeltera", + "georgiera", + "paliera", + "navajo", + "mazedoniar", + "finlandiera", + "javera", + "tagalera", + "malabarera", + "galiziera", + "bielorrusiera", + "georgiako", + "persiera", + "hindi", + "nederlandera", + "espainiera", + "guarani", + "kataluniar", + "galiziar", + "erremintari", + "esperanto", + "portugalera", + "lingala", + "katalan", + "daniera", + "txinatar", + "bengalera", + "ido", + "malaysiera", + "pertsiera", + "hungariera", + "gaztelera", + "tonga", + "kannada" + ], + "PRODUCT": [ + "zirkuitulabur", + "justin_bieber", + "gurutzegrama", + "al_jazeera", + "bataiontzi", + "eguberrietako_zuhaitz", + "lau_urtaroak", + "aitagure", + "bizarzuri", + "saint_vincent", + "the_star_spangled_banner", + "zesarea", + "die_hard", + "s\u00e3o_tom\u00e9_eta_pr\u00edncipe", + "zamuka", + "oroilore", + "boxing_day", + "saxonia_anhalt", + "giza_eskubideak", + "txori_gorri", + "la_dolce_vita", + "zelazapi", + "rosetta_harria", + "gong", + "garaipen_arku", + "mario_andretti", + "bataiarri", + "itun_berria", + "te_joko", + "espiritu_santua", + "rosetta_harri", + "irazeki", + "novo_mesto" + ], + "RELIGION_MEMBER": [ + "guru", + "budista", + "sarrazeno", + "sinesgabe", + "jainkogabe", + "presbiteriano", + "karmelita", + "mormon", + "baptista", + "mormoi", + "katoliko", + "mahomatar", + "giristino", + "gogaide", + "parsi", + "kongregazionalista", + "metodista", + "frantziskotar", + "konformagaitz", + "fedegabe" + ], + "RELIGION": [ + "zen", + "presbiterianismo", + "kalbinismo", + "islam", + "vishnuismo", + "xintoismo", + "katarismo", + "salafismo", + "manikeismo", + "lamaismo", + "brahmanismo" + ], + "RACE": [ + "arraza_zuriko", + "polinesiar", + "latin", + "frantziar", + "hego_amerikako", + "ingalaterrako", + "hegoamerikar", + "filipinar", + "amerindiera", + "latinoamerikar", + "uhartetar", + "zuritasun", + "latinoamerikako" + ], + "UNION": [ + "itu" + ], + "DATE": [ + "latentzia", + "ilargialdi", + "maiatzaren_1", + "lanordu", + "hutsarte", + "urrezko_aroa", + "the_day_after_tomorrow", + "ilgora", + "in_time", + "aitaren", + "zahartzaro", + "neguburu", + "gosalordu", + "ilargibete", + "bisurte", + "astialdi", + "mariaren_jasokundea", + "corpus_christi", + "ilargi_berri", + "the_day_after" + ], + "GPE": [ + "saint_domingue", + "dar_es_salaam", + "boli_kosta", + "jurgi_kapadoziakoa", + "sint_maarten", + "tai_mendia", + "san_laurendi", + "alde_zaharra", + "gurutze_gorri", + "hegoamerika", + "s\u00e3o_tom\u00e9", + "gurutze_gorria", + "mentura", + "al_andalus", + "alemaniar_inperioa", + "itunberia", + "itsaso_gorria", + "santa_sofia", + "industrialde" + ], + "GENDER": [ + "guy", + "andere_handi", + "adineko", + "men", + "male", + "damatxo", + "gizaseme", + "man", + "erizainburu", + "gal" + ], + "PERSON_PRONOUN": [ + "i", + "mea_erauzi", + "gure" + ], + "POLITICAL_PARTY_MEMBER": [ + "burkide", + "errepublikazale", + "laboralista", + "errepublikar", + "errepublikano", + "boltxebike", + "federalista" + ], + "LAW": [ + "arrasta", + "men_ez_egite", + "auzitegi_nagusi", + "barrutiko_fiskal", + "erromatar_zuzenbide", + "nazioarteko_zuzenbide" + ], + "POLITICAL_PARTY": [ + "oposizio", + "kuomintang", + "ameriketako_estatu_batuetako_alderdi_demokrata", + "alderdi_sozialdemokrata", + "erresuma_batuko_alderdi_laborista", + "alderdi_sozialista", + "ameriketako_estatu_batuetako_alderdi_errepublikanoa" + ], + "TITLE": [ + "sir" + ], + "EVENT": [ + "dan_dan", + "jazzaldi", + "sing_sing", + "itzarri" + ], + "ANAT": [ + "lepaorno" + ], + "BIO_CHEM_ENTITY": [ + "d_bitamina" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "ama_gehiena": "abba", + "abata": "abba", + "abadesa": "abba", + "izeba": "jagole", + "baronesa": "boteredun", + "emaztegai": "gizongai", + "andregai": "senargai", + "negozio_emakume": "enpresari", + "txita": "dandy", + "dukesa": "duke", + "enperatriz": "enperadore", + "tentatzaile": "liluratzaile", + "dalila": "liluratzaile", + "femenino": "gizaseme", + "urrixa": "gizaseme", + "gal": "tentsio_soka", + "etxe_irakasle": "gobernari", + "heroina": "heroi", + "heroi": "heroina", + "anfitrioi": "ospatu", + "markesa": "markes", + "masaje_emaile": "masajista", + "arrotz_gertatu": "sir", + "maitale": "jabe", + "amorante": "kapitain", + "lekaime": "fraidearen", + "moja": "fraide", + "nun": "fraidearen", + "apaiz_emakume": "kleriko", + "apaizeme": "meza_emaile", + "printzesa": "prince", + "homosexual": "errege", + "erregina": "errege", + "queens": "erregeak", + "sun": "bera", + "serora": "neba", + "ahizpa": "neba", + "arreba": "beix", + "naja": "gogaide", + "beix": "gogaide", + "mutxurdin": "emaztegabe", + "neskazahar": "emaztegabe", + "ugazalaba": "semeorde", + "alabaorde": "semeorde", + "ugazama": "ugazaita", + "amaorde": "aitaorde", + "azafata": "intendente", + "hegazkineko_laguntzaile": "intendente", + "emazte": "man", + "duna": "senar", + "bike": "fitxa", + "emakumezko": "man", + "emakume": "fitxa", + "neska_lagun": "fitxa", + "bikotekide": "fitxa" + }, + "other_gender_swap": { + "jale": "sun", + "haiek": "sun", + "tey": "sun", + "bera": "jale", + "sun": "jale" + }, + "en_pronoun2gender": { + "they": [ + "transexual", + "homosexual", + "bisexual" + ], + "he": [ + "tentsio_soka", + "male", + "arrakala", + "gaur", + "guy", + "gizaseme", + "dandy", + "man", + "fitxa", + "mutiko", + "gizonezko", + "zagon", + "ariar", + "little_boy", + "guri" + ], + "she": [ + "bikotekide", + "neska_lagun", + "emakume", + "lesbianismo", + "brasa", + "emazte", + "emakumezko", + "neskatila", + "gal", + "dama_gazte", + "panpina", + "femenino", + "urrixa", + "bike", + "neskato", + "dontzeila", + "damatxo", + "neskatxa", + "lesbiana", + "arrotz_gertatu" + ] + }, + "en_pronoun2pronoun": { + "he": [ + "bera" + ], + "she": [ + "sun" + ], + "they": [ + "haiek", + "jale", + "tey" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + 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"sienimyrkytys", + "taisteluvamma", + "nielemish\u00e4iri\u00f6", + "rasitusrintakipu", + "o_jalat", + "filovirus", + "ruokamyrkytys", + "dekompressiotauti", + "acanthosis_nigricans", + "siitep\u00f6lyallergia", + "karjarutto", + "toispuolihalvaus", + "hollanninjalavatauti", + "pajunvitsamurtuma", + "hermotulehdus", + "mahahaava", + "viherdikromasia", + "heijasteettomuus", + "pusutauti", + "karpalonmuumiopikari", + "verenkiertoh\u00e4iri\u00f6", + "karsinosarkooma", + "j\u00e4rvisyyhy", + "bataattitauti", + "kromosomivaurio", + "gammopatia", + "norsutauti", + "k\u00e4ytt\u00f6h\u00e4iri\u00f6", + "kaksiv\u00e4rin\u00e4k\u00f6", + "paratyphus", + "komplikaatio", + "okronoosi", + "valekuolema", + "karsinoidi", + "kouristaa", + "ruokavilja", + "paise", + "traumatofobia", + "dementoituminen", + "lamaannus", + "rikkoontuminen", + "sidekalvontulehdus", + "ki", + "sinkil\u00f6id\u00e4", + "polio", + "aniseikonia", + "tabes_dorsalis", + "jomottaa", + "radikuliitti", + "nukahtelusairaus", + "bunion", + "hengitysvaikeusoireyhtym\u00e4", + "linturutto", + "tihe\u00e4ly\u00f6ntisyys", + "hajataittoisuus", + "neulasruoste", + "rauhasten_sairaus", + "rautaylim\u00e4\u00e4r\u00e4", + "v\u00e4lkep\u00e4lvi", + "araknofobia", + "flavivirus", + "sirist\u00e4\u00e4", + "kokaiiniriippuvuus", + "lakastumistauti", + "punasokeus", + "proktalgia", + "pikku_juttu", + "valkomuunnos", + "taudinaiheuttaja", + "myrkytys", + "kariutuminen", + "samentuma", + "hermos\u00e4rky", + "ruusufinni", + "psykoneuroosi", + "hietakuha", + "salmonelloosi", + "vilunv\u00e4reet", + "hereill\u00e4olo", + "flavivirukset", + "suurikielisyys", + "rage", + "sairaus", + "juurim\u00e4t\u00e4", + "devianssi", + "pernatulehdus", + "haihduttaminen", + "innervaatio", + "lamautuminen", + "astasia", + "ekstraduraali", + "analgesia", + "anestrus", + "mahakipu", + "lehm\u00e4nrokko", + "alaraajahalvaus", + "nikotella", + "rusottaa", + "merisairaus", + "sirppisolu", + "paisetauti", + "costochondritis", + "reisis\u00e4rky", + "als", + "sy\u00f6mish\u00e4iri\u00f6", + "alipainetauti", + "androfobia", + "ruskom\u00e4t\u00e4", + "takellella", + "hengenahdistus", + "paraservikaalipuudutus", + "verenkieroh\u00e4iri\u00f6", + "kystoseele", + "rabies", + "haisunoki", + "fotofobia", + "kampurajalka", + "valkohilse", + "muutostila", + "plasmasytooma", + "pikkuaivoataksia", + "lavantauti", + "palilalia", + "maitorupi", + "liikal\u00e4mp\u00f6isyys", + "strabismi", + "hidas_virus", + "gumma", + "transpositio", + "kaukokipu", + "areenavirus", + "rakiitti", + "kitalakihalkio", + "pleomorfinen_rabdomyosarkooma", + "lihasreuma", + "pahanolontunne", + "parvo", + "mahanpuru", + "luunmurtuma", + "hsv_1", + "kivitauti", + "arpi", + "lihasdystrofia", + "lasiaissamentuma", + "kauranavonoki", + "pansytopenia", + "nuoruusvuodet", + "v\u00e4rikalvotulehdus", + "hein\u00e4nuha", + "valoammus", + "koulupelko", + "puutiaiskuume", + "anthrax_pneumonia", + "verentungos", + "siderosis", + "papilloomavirukset", + "luksaatio", + "paiserutto", + "skotooma", + "denguekuume", + "tenniskyyn\u00e4rp\u00e4\u00e4", + "marasmi", + "nelj\u00e4sp\u00e4iv\u00e4inen", + "progeria", + "ortomyksovirus", + "adenomatoottinen_polyyppi", + "sokeerata", + "munasarjatulehdus", + "hiertym\u00e4", + "postiitti", + "verruca_acuminata", + "putkin\u00e4k\u00f6", + "affektih\u00e4iri\u00f6", + "hiekkakasvain", + "pikkuvika", + "suippop\u00e4\u00e4", + "papovavirus", + "arbovirukset", + "hordeolum", + "kvasiorkor", + "harmaakaihi", + "klinodaktylia", + "munasarjaraskaus", + "verkkokalvosairaus", + "hernia_diaphragmatica", + "monihermotulehdus", + "verenmyrkytys", + "treenausvamma", + "alfavirus", + "syntym\u00e4vika", + "kilpirauhastulehdus", + "meritauti", + "k\u00e4rist\u00e4minen", + "valkorokko", + "kuppa", + "zikavirus", + "tornikallo", + "liikuntah\u00e4iri\u00f6", + "distomatosis", + "mahatauti", + "aristavuus", + "sensaatio", + "akateksia", + "listerioosi", + "geofagia", + "megacolon_congenitum", + "versotauti", + "materialismi", + "seisomiskyvytt\u00f6myys", + "vedenpelko", + "sijoiltaanmeno", + "ratsupaikkapuudutus", + "m\u00e4\u00e4rly", + "logagrafia", + "repe\u00e4minen", + "tieleikkaus", + "sanantoisto", + "lepidofobia", + "clavus", + "vilkeuni", + "valekuristustauti", + "nelj\u00e4nnesn\u00e4k\u00f6kentt\u00e4sokeus", + "hermojuuritulehdus", + "sukeltajantauti", + "haavoittuminen", + "limattomuus", + "vehn\u00e4nsilohaisunoki", + "naftaliinimyrkytys", + "phytophthora_ramorum", + "vajaal\u00e4mp\u00f6isyys", + "kuristusventtiili", + "natriureesi", + "virtsaamiskyvytt\u00f6myys", + "sairastelu", + "ajetus", + "puheh\u00e4iri\u00f6", + "kolmip\u00e4iv\u00e4kuume", + "talinvuoto", + "oikeataittoisuus", + "transponointi", + "ennakkotunne", + "hikata", + "haistamiskyvytt\u00f6myys", + "pharyngitis", + "rasitusmurtuma", + "vaahterasiirappitauti", + "kofeiiniriippuvuus", + "maksatulehdus", + "sirist\u00e4minen", + "ammoniakkivirtsaisuus", + "heroiiniriippuvuus", + "k\u00e4pylis\u00e4kekasvain", + "punatauti", + "pernakuume", + "kvadriplegia", + "bradykardia", + "monilihastulehdus", + "kurtistuminen", + "kvadrantanopia", + "maitorokko", + "beriberi", + "ragadit", + "r\u00e4j\u00e4hdysvamma", + "erkanema", + "kromosomipoikkeavuus", + "silikoosi", + "borrelioosi", + "rivopuheisuus", + "s\u00e4teilysairaus", + "kuristusk\u00e4\u00e4mi", + "gall", + "heikkorakenteisuus", + "mania", + "dementia", + "koronaarinen", + "j\u00e4k\u00e4l\u00e4tauti", + "radianssi", + "valkom\u00e4t\u00e4", + "akineesi", + "toisintokuume", + "the_bends", + "arenavirus", + "hapanverisyys", + "kielitulehdus", + "kammiov\u00e4rin\u00e4", + "virtsanjohdinlaajentuma", + "struma", + "phytophthora_infestans", + "haukkapala", + "kakeksia", + "ummetus", + "lordoosi", + "per\u00e4airon_soutaja", + "agammaglobulinemia", + "streptococcus_tonsilitis", + "nuhavirus", + "s\u00e4hk\u00f6isku", + "shape", + "k\u00e4rkikasvuisuus", + "tarvepakotus", + "satanofobia", + "yhteenkasvettuminen", + "lipidemia", + "kalkkeutuma", + "v\u00e4lirikko", + "livedo", + "poskiontelontulehdus", + "otseena", + "ms", + "heisimatotartunta", + "alkuer\u00e4", + "floora", + "siirtym\u00e4murtuma", + "valtimonpullistuma", + "prodomi", + "nuhakuume", + "huonovointisuus", + "ristihuulisuus", + "pernaruttoajos", + "askites", + "ekstrasystolia", + "verenpurkauma", + "perunarutto", + "uniapnea", + "rauhaskuume", + "epstein_barr_virus", + "korkeustauti", + "herukanvillaruoste", + "rachischisis", + "orgasmivaikeus", + "slice", + "fruktosuria", + "huimaus", + "proteinuria", + "myrkkyverisyys", + "koukkuselk\u00e4inen", + "tummasolusy\u00f6p\u00e4", + "superinfektio", + "maksasy\u00f6p\u00e4", + "karvastelu", + "haavauma", + "harjarinta", + "lapsivuodekuume", + "harmaahome", + "kuteloiminen", + "kuvasokeus", + "vilutauti", + "vastustuskyvytt\u00f6myys", + "servisiitti", + "talvihorros", + "draivi", + "virtsatieinfektio", + "kieroselk\u00e4isyys", + "pikkukohtaus", + "liikepahoinvointi", + "vitamiinimyrkytys", + "harmistuminen", + "virtsaamish\u00e4iri\u00f6", + "yksisilm\u00e4ep\u00e4muodostuma", + "lehm\u00e4rokko", + "talviuni", + "laihuush\u00e4iri\u00f6", + "leikkuu", + "lihaskouristus", + "haittatekij\u00e4t", + "ahtaanpaikankammo", + "hengitystieinfektio", + "harhatuntemus", + "kuuromykkyys", + "surkastuneisuus", + "lukivaikeus", + "kovettuma", + "mustavesikuume", + "napostelu", + "klaustrofobia", + "albuminuria", + "tamponishokki", + "solullisuus", + "hapenpuute", + "akatafasia", + "m\u00f6hk\u00f6nen\u00e4", + "v\u00e4lilevytyr\u00e4", + "ientulehdus", + "lehtilaikkubakterioosi", + "analbuminemia", + "meromelia", + "valtimonlaajentuma", + "klassinen_hemofilia", + "lukih\u00e4iri\u00f6", + "lehtiruusuke", + "deuteranopia", + "koittaa", + "pernarutto", + "ruumiinvamma", + "heikkon\u00e4k\u00f6isyys", + "normaalil\u00e4mp\u00f6isyys", + "johtoratakimppu", + "lipidoosi", + "kaviohalkeama", + "hermokompressio", + "ammoniuria", + "ruumismyrkytys", + "para", + "torikammo", + "levyepiteelisy\u00f6p\u00e4", + "bolivian_verenvuotokuume", + "eversio", + "solutulehdus", + "unitauti", + "koirakammo", + "haava", + "kirpunpurema", + "kristuksen_haavat", + "rohtuma", + "proktiitti", + "suonikohju", + "myrkkymuratti", + "kallonsis\u00e4inen_valtimonlaajentuma", + "ada_scid", + "kukkia", + "valgus", + "chorea", + "perunavirus", + "costiasis", + "a_hepatiitti", + "ei_gonokokkaalinen_virtsaputkitulehdus", + "lysinemia", + "maitotauti", + "johtoratapuudutus", + "maksamatotauti", + "handicap", + "kuristaminen", + "autoimmuunisairaus", + "mansikkaluomi", + "vointi", + "abrakia", + "hs1", + "arenaviridae", + "puristuminen", + "sirppisoluanemia", + "kissanraapaisutauti", + "marmoritauti", + "siriasis", + "liikeataksia", + "ryypp\u00e4\u00e4minen", + "spinaalinen", + "alalia", + "pernio", + "chloasma", + "kouristustauti", + "oftalmoplegia", + "cyclothymia", + "pirstalemurtuma", + "rustoutuminen", + "hydronefroosi", + "happomyrkytys", + "haavautuminen", + "yhteenkasvama", + "arefleksia", + "j\u00e4\u00e4kylmyys", + "monivarpaisuus", + "kastanjanruostesieni", + "ajoura", + "runsasvirtsaisuus", + "j\u00e4ttikasvu", + "sodoku", + "suurisyd\u00e4misyys", + "cva", + "wale", + "riisitauti", + "vaivaisenluu", + "kaihota", + "per\u00e4suolitulehdus", + "mahakatarri", + "malationimyrkytys", + "kaksiraajahalvaus", + "verenvuototauti", + "palleatyr\u00e4", + "kastanjanruoste", + "maksakasvain", + "gravida", + "sarveistuma", + "stitch", + "tulehdus", + "nikotiinimyrkytys", + "sotapsykoosi", + "spermatoseele", + "lohkokeuhkokuume", + "vaccina", + "v\u00e4likorvatulehdus", + "grafospasmi", + "miliaria", + "humalatila", + "variola_major", + "p\u00e4\u00e4st\u00f6aristus", + "herpes_simplex_virus", + "k\u00e4\u00e4pi\u00f6kasvuisuus", + "kissakammo", + "v\u00e4likorvantulehdus", + "kausalgia", + "lumisokeus", + "crick", + "rikastaa", + "pajunoksamurtuma", + "lintuinfluenssa", + "mola_hydatidosa", + "multippeliskleroosi", + "valokuvayhdistelm\u00e4", + "mongoloidismi", + "ristikanavapuudutus", + "sepelvaltimotauti", + "pronssidiabetes", + "kynsitauti", + "yhteenkasvettuma", + "rapsuttaa", + "persoonallisuush\u00e4iri\u00f6t", + "houretila", + "suomyrkkysumakki", + "amastia", + "turpoaminen", + "paramyksovirus", + "sokkitila", + "kamelirokko", + "kromosomimuutos", + "presbyopia", + "olla_n\u00e4lk\u00e4", + "fluoroosi", + "hinkuysk\u00e4", + "kuusokeus", + "tarsitis", + "sarveiskalvotulehdus", + "v\u00e4risokeus", + "terveysongelma", + "notkoselk\u00e4isyys", + "kaasugangreeni", + "ristiselk\u00e4kipu", + "kaasuembolia", + "granulosyyttileukemia", + "kretinismi", + "anasarka", + "hermoromahdus", + "tutia", + "schistorrhachis", + "koolifagi", + "haimatulehdus", + "kyberseksi", + "mahatulehdus", + "kaarijalka", + "kuristuskela", + "tuhkarokko", + "hydrokefalia", + "aliravitsemus", + "aurajoki", + "chi", + "sulatush\u00e4iri\u00f6", + "rachitis", + "delirium", + "ydinkaihi", + "blastooma", + "kefalalgia", + "kissanraapimatauti", + "tapaturmavahinko", + "von_recklinghausenin_tauti", + "valonarkuus", + "pudendaalipuudutus", + "karotenemia", + "stridor", + "napatyr\u00e4", + "dissosiaatioh\u00e4iri\u00f6", + "punavihersokeus", + "kumivuoto", + "sokeus", + "rytmih\u00e4iri\u00f6", + "koiranpurema", + "turvotus", + "qi", + "gargoilismi", + "olla_kukassa", + "puristusmurtuma", + "alkuvaikeudet", + "harminkappale", + "paleltumavamma", + "kuukautiskivut", + "glykosuria", + "litiaasi", + "herpes_simplex", + "hakkuuaukea", + "happivelka", + "proktoseele", + "kapillaarifraktuura", + "s\u00e4teitt\u00e4isyys", + "akolia", + "tartunnanlevitt\u00e4j\u00e4", + "isop\u00e4isyys", + "nielemiskipu", + "posttraumaattinen_epilepsia", + "kivip\u00f6lykeuhko", + "kire\u00e4kielisyys", + "palautusly\u00f6nti", + "akinesia", + "kolmoishermos\u00e4rky", + "epstein_barrin_virus", + "parametriitti", + "k\u00e4\u00e4pi\u00f6kasvu", + "scarlatina", + "pikkuaivovarsi", + "palohaava", + "jalkakramppi", + "caranx_bartholomaei", + "lockjaw", + "scleroderma_suku", + "suonenveto", + "lokeronivusajos", + "poliomyeliitti", + "spina_bifida", + "talinvuotosarveistuma", + "hydremia", + "munasarjantulehdus", + "persoonallisuush\u00e4iri\u00f6", + "rao", + "hermo\u00e4rsytys", + "rusketus", + "parapareesi", + "raskausaika", + "mutakuoppa", + "metamorfopsia", + "flaviviridae", + "horkka", + "paralysis_agitans", + "sinikielitauti", + "tyreotoksikoosi", + "punasoluhajoanemia", + "homep\u00f6lykeuhko", + "vauvarokko", + "painehaava", + "galaktosemia", + "lihastulehdus", + "isop\u00e4\u00e4", + "keltatauti", + "kala_azar", + "gimp", + "oestrus", + "hyvitell\u00e4", + "spigelia", + "yksikiveksisyys", + "olla_janoinen", + "panenkefaliitti", + "punehtuminen", + "bensa", + "kalkkeutuminen", + "hiirilavantauti", + "sepelvaltimotautikohtaus", + "rauhassairaus", + "hydrartroosi", + "furunkuloosi", + "raskauskouristus", + "pelkoneuroosi", + "abasia", + "frenzy", + "lehtiruoste", + "vinokalloisuus", + "varrellinen_polyyppi", + "mastiitti", + "limap\u00f6h\u00f6tauti", + "alexia", + "sanasokea", + "lepoaika", + "herpes", + "tartuntatauti", + "normaalipaineglaukooma", + "kuhmuleuka", + "trillata", + "kudoskuolio", + "rauhassy\u00f6p\u00e4", + "akardia", + "kosmidi", + "hammaskuoppatulehdus", + "avosilm\u00e4isyys", + "primaarikuppa", + "verkkoseksi", + "paleltuminen", + "maitorauhastulehdus", + "kausijuoppous", + "verenpunasairaus", + "nikamatulehdus", + "twist", + "lipemia", + "lihasrappeuma", + "punaj\u00e4k\u00e4l\u00e4", + "kaihi", + "tajuamattomuus", + "maksasolukasvain", + "kirjoitush\u00e4iri\u00f6", + "smart", + "papilledeema", + "amelia", + "karsinooma", + "hermostosairaus", + "spruutauti", + "epidemic_encephalitis", + "alil\u00e4mp\u00f6isyys", + "ahdaskulmaglaukooma", + "katalepsia", + "genitaaliherpes", + "akustikofobia", + "valtimonymp\u00e4rystulehdus", + "keiloosi", + "puhevika", + "gumboil", + "l\u00e4nsi_niilin_virus", + "haimasy\u00f6p\u00e4", + "lukemish\u00e4iri\u00f6", + "heikkohermoisuus", + "kromosomih\u00e4iri\u00f6", + "ed", + "liikaunisuus", + "breakdown", + "verenpunavirtsaisuus", + "raskausmyrkytys", + "karpaalitunnelioireyhtym\u00e4", + "lehtipuunsy\u00f6p\u00e4", + "viidakkokuume", + "kiertokaula", + "kaliuresis", + "sikainfluenssa", + "hermoheikkous", + "akarofobia", + "hionta", + "pica", + "kammiov\u00e4lisein\u00e4aukko", + "kankroidi", + "mooseksen", + "lapsihalvaus", + "kulkutauti", + "invertointi", + "valtimonkovettumatauti", + "naisnis\u00e4isyys", + "naarmuttaminen", + "mielenterveysh\u00e4iri\u00f6", + "granulomatoosi", + "aukiokammo", + "hengityselinsairaus", + "vilunv\u00e4ristykset", + "miekkailuarpi", + "nikotiiniriippuvuus", + "pylorusstenoosi", + "sulkukulmaglaukooma", + "acetonuria", + "peilisymmetria", + "lintukolera", + "ruostuminen", + "nielurisatulehdus", + "rhus_radicans", + "katarrikuume", + "vaccinia", + "kirjoittamiskyvytt\u00f6myys", + "automysofobia", + "delta_hepatiitti", + "vaihtuvakorkoinen_joukkovelkakirjalaina", + "hermotus", + "kvartaanakuume", + "munasarjakysta", + "koliikki", + "pehmytkudospatti", + "virtsarakontulehdus", + "pienip\u00e4isyys", + "per\u00e4suolentulehdus", + "lihaviipale", + "valerokko", + "albrightin_sairaus", + "kallus", + "nokitauti", + "myrkytt\u00e4minen", + "tarkkaavaisuush\u00e4iri\u00f6", + "piilokiveksisyys", + "j\u00e4nisrutto", + "verenv\u00e4hyys", + "limakalvovihoittuma", + "siristell\u00e4", + "talipes", + "sikotauti", + "keratosis_blennorrhagica", + "nis\u00e4sairaus", + "olla_kiimassa", + "puolikent\u00e4npuutos", + "kryptobioosi", + "karvatupentulehdus", + "v\u00e4lilevypullistuma", + "oftalmia", + "tulipolte", + "aktinomykoosi", + "uutisvuoto", + "sikakuume", + "kielij\u00e4nteenrakennevirhe", + "lihaskasvain", + "velttohalvaus", + "parestesia", + "paleltuma", + "tabes", + "ammattitauti", + "poliovirus", + "demineralisaatio", + "luum\u00e4t\u00e4", + "kaviokuume", + "joukkohysteria", + "aleksinen", + "aitosy\u00f6p\u00e4", + "lyhytkasvuisuus", + "balanopostiitti", + "s\u00e4velkuurous", + "alil\u00e4mp\u00f6", + "rubella", + "ly\u00f6d\u00e4_kevyesti", + "epidermolysis_bullosa", + "maksakooma", + "pain", + "abeetalipoproteinemia", + "verkkokalvotulehdus", + "sotaneuroosi", + "sarveisihoisuus", + "pinealooma", + "diestrus", + "luhistuminen", + "kihomatotauti", + "punastus", + "rokonarpi", + "aamupahoinvointi", + "bunyaviridae", + "jalkas\u00e4rky", + "aleksikko", + "arbovirus", + "laskimotulehdus", + "pohjukaissuolihaava", + "nikamansiirtym\u00e4", + "cervicitis", + "valittaminen", + "elastoosi", + "lassakuume", + "herpesaivokuume", + "sokeritauti", + "huimaavuus", + "parainfluenssavirus", + "bruselloosi", + "hsv_i", + "hydramnion", + "lukuh\u00e4iri\u00f6", + "hansikashalvaus", + "masentuneisuush\u00e4iri\u00f6", + "hermosairaus", + "the_passion_of_the_christ", + "kissanraapimakuume", + "keltakasvama", + "verenvuoto", + "talassemia", + "haukata", + "kuru\u015f", + "maligniteetti", + "seminooma", + "pareesi", + "aerodontalgia", + "akorea", + "skalenusoireyhtym\u00e4", + "tmv", + "nettiseksi", + "lehtisairaus", + "hyperkrominen_anemia", + "liikaliikkuvuus", + "vasovesiculitis", + "talik\u00f6hn\u00e4ihottuma", + "virtsaputkitulehdus", + "konduktioafasia", + "kaasukuolio", + "leikkautua", + "tulehdussairaus", + "kolestaasi", + "pansinuiitti", + "haparoivuus", + "t\u00e4ysk\u00e4heys", + "fonofobia", + "verekkyys", + "steatokystooma", + "luutulehdus", + "juurikasrutto", + "kruppi", + "wtv", + "alkuel\u00e4ininfektio", + "autoimmuniteetti", + "kolhaista", + "viherkaihi", + "ill", + "keltasiniv\u00e4risokeus", + "levytt\u00e4\u00e4", + "chalazion", + "rannekanavaoireyhtym\u00e4", + "parasitemia", + "useassa_paikassa_\u00e4\u00e4nest\u00e4v\u00e4_\u00e4\u00e4nest\u00e4j\u00e4", + "pikkulavantauti", + "torajyv\u00e4myrkytys", + "kestoerektio", + "paraplegia", + "faryngiitti", + "anestrum", + "gynekomastia", + "locoism", + "kondrodystrofia", + "hikirakkulatauti", + "palovamma", + "stigmata", + "surkastuminen", + "variola_major_virus", + "pienisolukarsinooma", + "tulirokko", + "maksakirroosi", + "als_tauti", + "sawan", + "verenvuotokuume", + "valvulitis", + "haavautuma", + "nielutulehdus", + "punoitus", + "oppimisvaikeus", + "hamartooma", + "lihaskipu", + "spitaali", + "kosketusallergia", + "pellagra", + "johtopuudutus", + "liikavarvas", + "parationimyrkytys", + "y\u00f6nsilm\u00e4", + "sammallus", + "strabismus_convergens", + "kyhmyruusu", + "sinkinpuute", + "rokahtuma", + "ei_trombosytopeeninen_purppura", + "togaviridae", + "h\u00e4t\u00e4soihtu", + "antaa_viljarehua", + "teratooma", + "herpesenkefaliitti", + "miliaarituberkuloosi", + "karjakuume", + "kiinnikasvettuma", + "hilsetystauti", + "addiktio", + "yleisanestesia", + "mi", + "tilletia_caries", + "virtsamyrkytys", + "eventraatio", + "k\u00e4rsimykset", + "rappeuma", + "kongestio", + "raudanvarastoitumistauti", + "sivu\u00e4\u00e4ni", + "follikuliitti", + "autoimmuunidiabetes", + "sappirakontulehdus", + "heikkomielisyys", + "shigellosis", + "valkuaisvirtsaisuus", + "sorkkam\u00e4t\u00e4", + "maitokysta", + "napanuoratyr\u00e4", + "lihass\u00e4rky", + "avokulmaglaukooma", + "aura", + "tarkkakatseisuus", + "oftalmiitti", + "funikuliitti", + "a_hemofilia", + "tan", + "verenpunatauti", + "supistukset", + "piippi", + "rusotus", + "sting", + "pahoinvointi", + "pestis_bubonica", + "sidekudoskasvain", + "punkkitartunta", + "ruskettua", + "ortokorea", + "sienitauti", + "ulkokorvatulehdus", + "sellerihome", + "taisteluv\u00e4symys", + "kefaalihematooma", + "sappitietulehdus", + "lintunuha", + "aminoasiduria", + "tarantismi", + "the_bleeding", + "kondrooma", + "alveoliitti", + "hiilip\u00f6lykeuhko", + "topaasinv\u00e4ri", + "achylia_gastrica", + "rektoseele", + "sukupuoliherpes", + "protanopia", + "koisata", + "emmetropia", + "peliosis", + "hermoh\u00e4iri\u00f6", + "hsv_ii", + "kaukotaitteisuus", + "rauhastulehdus", + "talvilepo", + "sepelvaltimotukos", + "kartiopullistuma", + "paratyyfus", + "rustokasvain", + "poskiontelotulehdus", + "keltakuume", + "hiekkak\u00e4rp\u00e4skuume", + "aliravita", + "kierouma", + "tietokonekammo", + "trauma", + "kernikterus", + "limapussintulehdus", + "pahanlaatuisuus", + "surkastua", + "suomutauti", + "temporaaliepilepsia", + "valekaksineuvoisuus", + "echovirus", + "uraemia", + "punat\u00e4pl\u00e4hilseily", + "paniikkih\u00e4iri\u00f6", + "lichen_planus", + "hermov\u00e4re", + "hankaushaava", + "kuru", + "burn", + "kalvetustauti", + "kovettaminen", + "tukikudostulehdus", + "kielill\u00e4puhuminen", + "lagophthalmos", + "von_willerbrandin_tauti", + "paloj\u00e4lki", + "kehitysvamma", + "kaukotaittoisuus", + "parasentraalinen_skotooma", + "ruokahaluttomuus", + "parakvattimyrkytys", + "raudanpuutosanemia", + "karotinemia", + "valeraskaus", + "sukuelinherpes", + "luunpehmeneminen", + "sammastulehdus", + "balaniitti", + "granulosytopenia", + "kondrosarkooma", + "vadelmanversotauti", + "papillooma", + "herkk\u00e4nahkaisuus", + "pilkkukuume", + "aeroembolia", + "noma", + "mulkosilm\u00e4", + "kynsinauhantulehdus", + "ortopnea", + "siemenkohju", + "hydrofobia", + "the_hives", + "mongolismi", + "hemeralopia", + "valtimotulehdus", + "struuma", + "astrafobia", + "nappaaminen", + "peltikorva", + "kyynelpussitulehdus", + "koriomeningiitti", + "kielikipu", + "dengue", + "valkovatsuri", + "ruoste", + "punahome", + "meripahoinvointi", + "kuroutuminen", + "monisormisuus", + "heikkoverisyys", + "venekalloisuus", + "kirjoituskyvytt\u00f6myys", + "flare", + "papilloomakasvain", + "kofeiinimyrkytys", + "rauhastauti", + "petekia", + "hermopinne", + "sairaalatartunta", + "salmonellat", + "l\u00e4\u00e4keannos", + "holkkuvuus", + "massahysteria", + "kaksoishalvaus", + "vuoristotauti", + "habituaatio", + "le", + "bunyavirus", + "paisuminen", + "maksasairaus", + "appendisiitti", + "heng\u00e4styneisyys", + "pitk\u00e4taittoisuus", + "s\u00e4teilevyys", + "kolekystiitti", + "keratoderma_blennorrhagica", + "para_joki", + "himota", + "parvovirus", + "salmonella", + "toxicodendron_radicans", + "raudanpuuteanemia", + "kelluja", + "hankautua", + "kontuusio", + "dekstrokardia", + "krakeloida", + "vuotokohta", + "s\u00e4\u00e4skenpurema", + "sapettaa", + "p\u00e4ivetty\u00e4", + "cacogenesis", + "tritanopia", + "normotermia", + "dysosmia", + "karvakieli", + "variola_virus", + "kovettuminen", + "fritsu", + "avausly\u00f6nti", + "virtsatietulehdus", + "kiilautuminen", + "staasi", + "salisylaattimyrkytys", + "mustam\u00e4t\u00e4", + "puutossairaus", + "haukkaus", + "lihasheikkous", + "mieskammo", + "spinal_curvature", + "karsastus", + "esotropia", + "pensaikkopilkkukuume", + "laskimontukkotulehdus", + "kryptorkia", + "hammass\u00e4rky", + "sekundaarikuppa", + "hiirikammo", + "yleisvakuutus", + "laskimolaajentuma", + "s\u00e4hk\u00f6shokki", + "malaria", + "palsi", + "riippuluomi", + "verenpainetauti" + ], + "JOB": [ + "verokarhu", + "sikojenhoitaja", + "nikkari", + "pillerinpy\u00f6ritt\u00e4j\u00e4", + "mustuttaa", + "tertiusvelallinen", + "kattilanpaikkaaja", + "sanansaattaja", + "kursija", + "suolakauppias", + "sijoituspankkiiri", + "muulinajaja", + "naputtelija", + "assistentti", + "kasviparantaja", + "rakennusinsin\u00f6\u00f6ri", + "naiskirjailija", + "reistraattori", + "sanakirjantoimittaja", + "perinatologi", + "sonnustautua", + "plastiikkakirurgi", + "rekisteriviranomainen", + "teatteriarvostelija", + "guru", + "yleisvakuutus", + "setteri", + "varastonhoitaja", + "morsiustytt\u00f6", + "kellokalle", + "lakkoilija", + "vartiosto", + "mercator", + "j\u00e4rjestynyt", + "kilpikonnanmets\u00e4st\u00e4j\u00e4", + "palomiesleikki", + "virsiseppo", + "matee", + "stoukkeri", + "galvanoija", + "harsija", + "tallentaja", + "lentomekaanikko", + "yliopistonopettaja", + "vesipoika", + "oikeusavustaja", + "molari", + "vara_amiraali", + "kondiittori", + "shearer", + "kipparoida", + "koistinen", + "asianajosihteeri", + "ruokakauppias", + "kauriinmets\u00e4st\u00e4j\u00e4", + "forester", + "kunniavartiosto", + "rapsuttaja", + "s\u00e4velt\u00e4j\u00e4", + "lentokapteeni", + "retorikko", + "konitohtori", + "huippuarvostelu", + "draiveri", + "valaistusmestari", + "taimistoviljelij\u00e4", + "remonttireiska", + "kansantaloustieteilij\u00e4", + "sauvankantaja", + "tarkkailulaite", + "siistij\u00e4", + "bestman", + "harppunoija", + "mokkeri", + "tanssinopettaja", + "sokerileipuri", + "veroarvioija", + "perinn\u00f6llisyydentutkija", + "olkikatontekij\u00e4", + "naispoliisi", + "kotiavustaja", + "s\u00e4kitt\u00e4j\u00e4", + "taksidermisti", + "k\u00e4sity\u00f6l\u00e4inen", + "nebraskalainen", + "make", + "muotisuunnittelija", + "raatimies", + "aumaaja", + "miller", + "linjaty\u00f6ntekij\u00e4", + "viikonloppusoturi", + "ihotautil\u00e4\u00e4k\u00e4ri", + "tennesseel\u00e4inen", + "keinuttaja", + "mainospala", + "sotapoliisi", + "kollektori", + "nuorisoty\u00f6ntekij\u00e4", + "ruorimies", + "naislent\u00e4j\u00e4", + "kamikazelent\u00e4j\u00e4", + "turvamies", + "kuutamourakoitsija", + "sis\u00e4tautil\u00e4\u00e4k\u00e4ri", + "valmentaja", + "lakeija", + "kaarti", + "devaaja", + "paarinkantaja", + "rahanly\u00f6j\u00e4", + "astioidenker\u00e4\u00e4j\u00e4", + "hanslankari", + "salaneuvos", + "reititin", + "haavuri", + "erikoisl\u00e4hettil\u00e4s", + "sahaaja", + "vanginvartija", + "kivisepp\u00e4", + "lascar", + "hirvenmets\u00e4st\u00e4j\u00e4", + "asetehtailija", + "j\u00e4\u00e4toimittaja", + "hammashoitaja", + "taitolent\u00e4j\u00e4", + "maitomies", + "maalinpoistoaine", + "hallintovirkamies", + "cooper", + "territoriaaliarmeija", + "haukankasvattaja", + "kartanpiirt\u00e4j\u00e4", + "veitset", + "tapahtumasuunnittelija", + "hoviherra", + "teatterikriitikko", + "maaherra", + "keitt\u00e4j\u00e4", + "reseptionisti", + "hiustenleikkaaja", + "korkeanpaikanty\u00f6l\u00e4inen", + "hummerinpyyt\u00e4j\u00e4", + "artesaani", + "poistoaine", + "perinn\u00f6llisyystieteilij\u00e4", + "neurokirurgi", + "sexton", + "per\u00e4npit\u00e4j\u00e4", + "parkitsija", + "velkap\u00e4\u00e4oma", + "sekatavarakauppias", + "mets\u00e4st\u00e4j\u00e4t\u00e4r", + "viinitarjoilija", + "hallintovirkailija", + "palsamoija", + "korttik\u00e4si", + "lammaspaimen", + "viulunrakentaja", + "kosketusvarsi", + "lampunsytytt\u00e4j\u00e4", + "panostaja", + "desinfektiokammio", + "don", + "king", + "linnustaja", + "maalaisl\u00e4\u00e4k\u00e4ri", + "ojittaja", + "taideopettaja", + "tiskikone", + "pankinjohtaja", + "puukot", + "koulumies", + "lauluntekij\u00e4", + "kulissimaalari", + "hierarkki", + "tahranpoistaja", + "tykkimies", + "huuhtoja", + "mahout", + "kehite", + "kaupunginjohtaja", + "plantaasinomistaja", + "ei_toivottu_henkil\u00f6", + "lestikala", + "terveyspiiri", + "elintarvikekauppias", + "vaalitoimitsija", + "v\u00e4litystuomarin", + "vierasty\u00f6l\u00e4inen", + "telakkaty\u00f6ntekij\u00e4", + "carver", + "asentaja", + "the_police", + "printteri", + "peacemaker", + "turncock", + "kirkonvartija", + "luuparantaja", + "kellosepp\u00e4", + "valelija", + "s\u00e4hk\u00f6insin\u00f6\u00f6ri", + "tullivirkailija", + "sananjulistaja", + "hakeem", + "sisustussuunnittelija", + "kelluja", + "mortti", + "skinner", + "kantakersantti", + "saarnamies", + "kansimies", + "kodinrikkoja", + "vakiasiakas", + "oikeusasiamies", + "myllytytt\u00f6", + "jawan", + "sommelier", + "kausiluonteinen", + "poliittinen_johtaja", + "sopimuspuoli", + "kassamyyj\u00e4", + "viinuri", + "ammattitanssija", + "pokaalinpyydyst\u00e4j\u00e4", + "sotapoika", + "uranainen", + "alikersantti", + "doge", + "pesin", + "rakuunarykmentti", + "j\u00e4n\u00f6pupu", + "kansleri", + "lister", + "valtamerentutkija", + "panssarimies", + "sovintotuomari", + "virityslaippa", + "asevelvollinen", + "pianonviritt\u00e4j\u00e4", + "lisenssinantaja", + "hallintoviranomainen", + "tiedusteluvirkamies", + "valaanpyyt\u00e4j\u00e4", + "riistanhoitaja", + "tartunnankantaja", + "punnitsija", + "nikamanniksauttaja", + "asemestari", + "kausittainen", + "apopleksia", + "suolaaja", + "rasvari", + "krupieeri", + "tuutori", + "korpraali", + "para", + "valmistaja", + "orjapalvelija", + "ty\u00f6nt\u00f6veturi", + "rokottaja", + "py\u00f6r\u00e4ntekij\u00e4", + "lassomies", + "puusepp\u00e4", + "lehtori", + "fuller", + "vahtimestari", + "antologisti", + "rivisotilas", + "lentosuunnistaja", + "the_scientist", + "thatcher", + "ravintolaty\u00f6ntekij\u00e4", + "jalokivihioja", + "currier", + "kuunteluoppilas", + "kukkalaatikko", + "sijaishallitsija", + "hiveleminen", + "paikallistoimittaja", + "asettelija", + "cook", + "spotter", + "viisari", + "s\u00e4\u00e4t\u00f6laite", + "ylipursimies", + "lapioija", + "mastermind", + "tapper", + "kassaneiti", + "astianpesij\u00e4", + "kaleeriorja", + "ahertaja", + "kuski", + "taksonomisti", + "morsiusneito", + "airomies", + "teollisuudenharjoittaja", + "liikeyritt\u00e4j\u00e4", + "jarruaine", + "ulkoty\u00f6mies", + "liukastuja", + "kankkunen", + "land", + "petata", + "rodeoratsastaja", + "kemisti", + "keinahdella", + "hakim", + "savustuskammio", + "keraamikko", + "mallintaja", + "norsunajaja", + "kameramies", + "valtiosihteeri", + "koulumestari", + "verhoilija", + "vapaaehtoisty\u00f6ntekij\u00e4", + "taistelulent\u00e4j\u00e4", + "viestintuoja", + "hammaskirurgi", + "elinkeinonharjoittaja", + "the_cutter", + "butler", + "k\u00e4rr\u00e4\u00e4j\u00e4", + "regulaattori", + "ihmiskauppias", + "nokikolari", + "tiedonantaja", + "kengitt\u00e4j\u00e4", + "kaupitsija", + "plakaatti", + "sisustusarkkitehti", + "kent\u00e4nhoitaja", + "nylkij\u00e4", + "kuuraaja", + "aivokirurgi", + "yritt\u00e4j\u00e4", + "maustaja", + "sulattaja", + "asiapoika", + "matkatoveri", + "liikkeenharjoittaja", + "yleisl\u00e4\u00e4k\u00e4ri", + "graafikko", + "korinrakentaja", + "eversti", + "pitman", + "miespalvelija", + "sotamarsalkka", + "pussittaja", + "kersantti", + "ammattikirjoittaja", + "kausity\u00f6ntekij\u00e4", + "j\u00e4rjestyksenvalvoja", + "miilunpolttaja", + "itsemurhalent\u00e4j\u00e4", + "kirvesmies", + "paakari", + "seriffi", + "olla_olevinaan_jtak", + "qadi", + "nokisutari", + "el\u00e4inl\u00e4\u00e4k\u00e4ri", + "lukiopettaja", + "vastaanottovirkailija", + "freelance", + "scientist", + "rahastaja", + "sissipartio", + "suntio", + "parsija", + "sotilasjohtaja", + "tiedusteluanalyytikko", + "lepakkomies", + "tynnyrintekij\u00e4", + "veneenveist\u00e4j\u00e4", + "systeemianalyytikko", + "lainlaatija", + "kamikaze", + "pakkaaja", + "teenlehtirasia", + "vakuutusmeklari", + "wheeler", + "paistokokki", + "autoinsin\u00f6\u00f6ri", + "pujottaja", + "the_advocate", + "kirkonpalvelija", + "mets\u00e4nvartija", + "rahastonhoitaja", + "maatalousty\u00f6l\u00e4inen", + "veska", + "page", + "reititt\u00e4j\u00e4", + "valaistusteknikko", + "el\u00e4intenhoitaja", + "leipuri", + "rauhanturvaaja", + "tuotekehitt\u00e4j\u00e4", + "olkikaton_tekij\u00e4", + "l\u00e4mmitt\u00e4j\u00e4", + "baker", + "keritsij\u00e4", + "satamaty\u00f6l\u00e4inen", + "tietokoneohjelmoija", + "puheenjohtaja", + "erikoishammasteknikko", + "matkustamohenkil\u00f6kunta", + "tukialus", + "ravintoloitsija", + "hyttipoika", + "takiloija", + "hankaaja", + "lammasfarmari", + "valaja", + "modisti", + "listoittaja", + "lehmipoika", + "taidekriitikko", + "teatteriohjaaja", + "suurl\u00e4hettil\u00e4s", + "freelancer", + "sumuttaja", + "ravitsemusterapeutti", + "meren", + "tutkintotuomari", + "juomanlaskija", + "lakonrikkoja", + "vakoaura", + "a_duuri", + "linssinhioja", + "pursimies", + "asuntomurtaja", + "kuljetuslaite", + "koordinaattori", + "endodontti", + "autonasentaja", + "liuskay\u00f6kk\u00f6nen", + "markkinoija", + "puputytt\u00f6", + "kentt\u00e4marsalkka", + "kitkij\u00e4", + "p\u00f6yt\u00e4kirjanpit\u00e4j\u00e4", + "per\u00e4mies", + "huonesiivooja", + "syd\u00e4nkirurgi", + "huonekalupuusepp\u00e4", + "varusmies", + "v\u00e4\u00e4r\u00e4nrahantekij\u00e4", + "kohmelo", + "hammashuoltaja", + "huonekalupy\u00f6r\u00e4", + "lentoper\u00e4mies", + "ovenvartija", + "valkaisija", + "kitsastelija", + "virranjakaja", + "kortistoija", + "veneenrakentaja", + "the_guardian", + "purseri", + "huippumalli", + "upseeri", + "saamamies", + "olla_jkn_puolella", + "turkkuri", + "henkivartiosto", + "rockmuusikko", + "solttu", + "sinitakki", + "ylitarkastaja", + "lukkosepp\u00e4", + "kantoaine", + "naisopettaja", + "kunniavartio", + "vakinainen", + "punatakki", + "erotuomari", + "kampauskone", + "inventoija", + "au_pair_tytt\u00f6", + "teatterikuiskaaja", + "suojalaite", + "tilastotieteilij\u00e4", + "eteisvahtimestari", + "mainostoimittaja", + "palotarkastaja", + "pes\u00e4nselvitt\u00e4j\u00e4", + "kouluttaja", + "palvelustytt\u00f6", + "olla_ty\u00f6harjoittelussa", + "linkitt\u00e4\u00e4", + "pakkauskone", + "herder", + "pukija", + "varakuvern\u00f6\u00f6ri", + "maisemansuunnittelija", + "luokanopettaja", + "liikemiehet", + "r\u00e4yst\u00e4skouru", + "mason", + "lippuvartio", + "kaupunginis\u00e4", + "matkatavarapalvelija", + "korval\u00e4\u00e4k\u00e4ri", + "satamaty\u00f6ntekij\u00e4", + "puoltaja", + "hallinnoija", + "fowler", + "kiskottaja", + "tiedemies", + "aivoverenkiertoh\u00e4iri\u00f6", + "mate", + "stoker", + "laastinkantaja", + "don_joki", + "preeriasusi", + "lukutaitoinen", + "kvestori", + "kirkonis\u00e4nt\u00e4", + "hapantaikina", + "tilap\u00e4isty\u00f6ntekij\u00e4", + "vakuutusmyyj\u00e4", + "puolestapuhuja", + "muurari", + "koelent\u00e4j\u00e4", + "pelintekij\u00e4", + "paikkasidonnainen", + "lippueamiraali", + "lipunkantaja", + "designer", + "elintarvikekauppa", + "sairaalal\u00e4\u00e4k\u00e4ri", + "portinvartija", + "sitter", + "novascotiannoutaja", + "maksuvirkailija", + "renki", + "maalintekij\u00e4", + "uutisaineisto", + "nukutusl\u00e4\u00e4k\u00e4ri", + "kuvittaja", + "viininmaistaja", + "haudankaivaja", + "hengenpelastaja", + "ojankaivaja", + "kirkkov\u00e4\u00e4rtin_apulainen", + "koiranhoitaja", + "pinoaja", + "viskaali", + "para_joki", + "perkaaja", + "kansliap\u00e4\u00e4llikk\u00f6", + "taidemaalari", + "lintsaaja", + "koulunjohtaja", + "cartwright", + "terapeutti", + "syd\u00e4nl\u00e4\u00e4k\u00e4ri", + "leip\u00e4kone", + "tie_ja_vesirakennusinsin\u00f6\u00f6ri", + "kuomuvaunut", + "paikann\u00e4ytt\u00e4j\u00e4", + "varastomies", + "fellah", + "kotiopettajatar", + "kaasuasentaja", + "geometrian_opettaja", + "talkkari", + "tinasepp\u00e4", + "kruunup\u00e4\u00e4", + "tilastoija", + "aliluutnantti", + "puoluep\u00e4\u00e4llikk\u00f6", + "koulupinnari", + "gaucho", + "kengityssepp\u00e4", + "beadle", + "trassentti", + "esitelm\u00f6ij\u00e4", + "lakkolainen", + "amputoija", + "osteopaatti", + "oikeudenpalvelija", + "sommelieeri", + "kunnostaja", + "kellonvalaja", + "kotihoitaja", + "trimmaaja", + "merijalkav\u00e4en", + "pitkitt\u00e4isj\u00e4ykiste", + "oikeusasianajaja", + "h\u00e4kkilintu", + "kastelija", + "territoriaalinen", + "cornhusker", + "konduktori", + "valkki", + "transkriptionisti", + "ilmapurjehtija", + "esseisti", + "syd\u00e4ntautil\u00e4\u00e4k\u00e4ri", + "yl\u00e4jyrsin", + "merkkaaja", + "pikakirjoittaja", + "viiruttaa", + "lentoem\u00e4nt\u00e4", + "sosiaality\u00f6ntekij\u00e4", + "kuparisepp\u00e4", + "the_economist", + "sulkuvahti", + "rokkari", + "seaman", + "kokata", + "suoneniskij\u00e4", + "basteri", + "carter", + "turkiskauppias", + "rintamamies", + "porter", + "kirkkov\u00e4\u00e4rti", + "internoida", + "tullimies", + "portteri", + "kokoustaja", + "vankilanjohtaja", + "aivol\u00e4\u00e4k\u00e4ri", + "preetori", + "metsuri", + "koulutuslentokone", + "lennonjohtaja", + "v\u00e4est\u00f6nlaskija", + "tilastotutkija", + "dosentti", + "barista", + "kaupittelija", + "valokuvaaja", + "valtiatar", + "rotanpyydyst\u00e4j\u00e4", + "ilmailija", + "warrior", + "barber", + "leimaaja", + "maanmittausinsin\u00f6\u00f6ri", + "laskuvarjoj\u00e4\u00e4k\u00e4ri", + "rovasti", + "mokkeli", + "lippujunkkari", + "el\u00e4intent\u00e4ytt\u00e4j\u00e4", + "entis\u00f6ij\u00e4", + "rakennusty\u00f6l\u00e4inen", + "ammattisotilas", + "liukastelija", + "lapiomies", + "jalokivisepp\u00e4", + "mit\u00e4t\u00f6ij\u00e4", + "ty\u00f6llistett\u00e4v\u00e4", + "asesepp\u00e4", + "sikopaimen", + "kiinteist\u00f6kehitt\u00e4j\u00e4", + "aurasepp\u00e4", + "taiteiden_opettaja", + "man", + "lankuntekij\u00e4", + "j\u00e4lkikoira", + "kartoittaja", + "patsaantekij\u00e4", + "valaanpyyntialus", + "doc", + "vuohipaimen", + "avaruussuunnistaja", + "sienensukeltaja", + "sanakirjantekij\u00e4", + "jakop\u00e4\u00e4", + "mailapoika", + "pes\u00e4nhoitaja", + "taidej\u00e4ljent\u00e4j\u00e4", + "kokoaja", + "everstiluutnantti", + "v\u00e4limies", + "hivell\u00e4", + "k\u00e4rryjentekij\u00e4", + "lentokoneinsin\u00f6\u00f6ri", + "p\u00e4\u00e4kirjanpit\u00e4j\u00e4", + "roolin\u00e4yttelij\u00e4", + "liikemies", + "kultaaja", + "s\u00e4\u00e4din", + "kakkos", + "vanuttaja", + "t\u00e4htitieteilij\u00e4", + "kilpimaalari", + "katusiivooja", + "jalostaja", + "myll\u00e4ri", + "puhuja", + "kaartoliike", + "jalokivenleikkaaja", + "tilintarkastaja", + "p\u00e4\u00e4sihteeri", + "murtautuja", + "rannikkovartija", + "perhel\u00e4\u00e4k\u00e4ri", + "vetolaatikko", + "l\u00e4nkk\u00e4ri", + "latoja", + "timperi", + "palmikoija", + "loppus\u00e4e", + "automekaanikko", + "maistraatti", + "the_machinist", + "palvelin", + "omaehtoinen", + "usher", + "messenger", + "romaanikirjailija", + "voimasakset", + "lumppuri", + "sesonki", + "kutsuttu", + "torninrakentaja", + "riistanvalvoja", + "amat\u00f6\u00f6riarkeologi", + "lajittelukone", + "koggi", + "opettajatar", + "hellapoliisi", + "verottaja", + "valtionsyytt\u00e4j\u00e4", + "rupeutua", + "au_pair", + "ilmailul\u00e4\u00e4k\u00e4ri", + "aluerakentaja", + "bridgenpelaaja", + "proconsul", + "kitaranrakentaja", + "laskuvarjosotilas", + "portsari", + "cox", + "hovimies", + "taittaja", + "krenat\u00f6\u00f6ri", + "transkriptori", + "k\u00e4rryntekij\u00e4", + "kissantassu", + "tiilenkantaja", + "\u00f6ljynporaaja", + "kalligraafikko", + "hienopuusepp\u00e4", + "kolonokkalestikala", + "lehmitytt\u00f6", + "karabinieeri", + "sotilas", + "kelluva_esine", + "hammasproteesispesialisti", + "perkausv\u00e4line", + "muotoilija", + "kurssiassistentti", + "kartantekij\u00e4", + "huonepalvelija", + "lainanantaja", + "sulunvartija", + "lyijyty\u00f6ntekij\u00e4", + "paksup\u00e4\u00e4t", + "liikenn\u00f6itsij\u00e4", + "kadunlakaisija", + "s\u00e4il\u00f6j\u00e4", + "porttivahti", + "balladisti", + "virassa_oleva", + "imett\u00e4j\u00e4", + "savenvalaja", + "sorsanmets\u00e4st\u00e4j\u00e4", + "kallonkutistaja", + "preettori", + "silm\u00e4l\u00e4\u00e4k\u00e4ri", + "sotilasupseeri", + "kaupungintuomari", + "kuriiri", + "ylimatruusi", + "sotilaspalvelija", + "pianonsoitonopettaja", + "ruotija", + "nokkamies", + "haukkamets\u00e4st\u00e4j\u00e4", + "majuri", + "alienisti", + "hermol\u00e4\u00e4k\u00e4ri", + "lentosotamies", + "marshall", + "sanomalehtikriitikko", + "doula", + "j\u00e4tt\u00e4j\u00e4", + "palomies", + "kaaso", + "erikoissairaanhoitaja", + "allergial\u00e4\u00e4k\u00e4ri", + "v\u00e4litystuomari", + "t\u00e4yskenraali", + "yleispelaaja", + "sub", + "tietokonefriikki", + "strippari", + "ehdonalaisvalvoja", + "merkillepanija", + "voimalaty\u00f6ntekij\u00e4", + "the_independent", + "leikkuuter\u00e4", + "hiusmuotoilija", + "harjoituttaja", + "turner", + "kamaripalvelija", + "sotilastarkastaja", + "kaartilainen", + "astianpesukone", + "yliper\u00e4mies", + "suuramiraali", + "hallintomies", + "varakommodori", + "rautanuija", + "hammasl\u00e4\u00e4k\u00e4ri", + "meist\u00e4j\u00e4", + "tallennin", + "luotonantaja", + "poimija", + "kuraattori", + "aliupseeri", + "leijonanmets\u00e4st\u00e4j\u00e4", + "soihdunkantaja", + "hammasteknikko", + "kivenhakkaaja", + "valtionhoitaja", + "liikenainen", + "kartanvalmistaja", + "topper", + "j\u00e4rjestysmies", + "parturoida", + "synnytysl\u00e4\u00e4k\u00e4ri", + "kasvisparantaja", + "taakkateline", + "parantaja", + "lent\u00e4j\u00e4", + "hammashygienisti", + "raaputtaja", + "navettapiika", + "l\u00e4hihoitaja", + "aivohalvaus", + "riidanselvitt\u00e4j\u00e4", + "jalas", + "marsalkka", + "pankkiiri", + "kuulemismenettelyst\u00e4_vastaava_virkamies", + "p\u00e4\u00e4tekij\u00e4", + "punakottaraiset", + "husaari", + "mets\u00e4nhoitaja", + "sahuri", + "painaja", + "mist\u00e4_kaikki_alkoi", + "laatija", + "tilap\u00e4inen_ty\u00f6ntekij\u00e4", + "avustusty\u00f6ntekij\u00e4" + ], + "PLANT": [ + "v\u00e4limerentaateli", + "lepidium_alpina", + "acer_negundo", + "raphia_vinifera", + "malkolmia", + "viola_pedata", + "jeffreynm\u00e4nty", + "hibiscus_syriacus", + "isok\u00f6ynn\u00f6skrassi", + "eucalypt_ovata", + "jalosauramo", + "voikukanlehti", + "nothofagus_solanderi", + "acanthocereus_tetragonus", + "maksabegonia", + "gomphrena_globosa", + "kollink\u00e4p\u00e4l\u00e4", + "hibiscus_mutabilis", + "kartiohuhtasieni", + "arceuthobium_pusillum", + "brachychiton_populneus", + "amerikanpy\u00f6kki", + "hammasheisi", + "tummaraunioinen", + "glaucium_flavum", + "cryptogramma_acrostichoides", + "huimaluste", + "kultapallo", + "primula_auricula", + "senecio_vulgaris", + "kilpisuolahein\u00e4", + "rikkamalikka", + "aitovirna", + "preeriahelmikki", + "robinia_hispida", + "physalis_viscosa", + "epigaea_repens", + "korallipuu", + "trichostema_lanatum", + "tsuga_caroliniana", + "puutarhaherne", + "entoloma_sinuatum", + "polypodium_virgianum", + "alaskankoivu", + "maniokkit\u00e4rkkelys", + "lilium_martagon", + "lupinus_luteus", + "pennisetum_ruppelii", + "hevea", + "nystymukulakuukunen", + "pyracantha", + "acer_rubrum", + "botrychium_matricariifolium", + "vittaria_lineata", + "agathis_lanceolata", + "j\u00e4ttikuukunen", + "mahonia", + "heritiera_macrophylla", + "senna_marilandica", + "siperianlehtikuusi", + "taraxacum_ruderalia", + "t\u00f6yht\u00f6helmililja", + "lespedeza_cuneata", + "cirsium_rivulare", + "marunatuoksukki", + "campanula_persicifolia", + "prunus_alleghaniensis", + "leucogenes_leontopodium", + "ruokohelpi", + "mustepipo", + "pikkutrumpettik\u00f6ynn\u00f6s", + "mikadonk\u00e4mmen", + "eriophyllum_wallacei", + "orasutipuu", + "diospyros_virginiana", + "dryopteris_fragrans", + "anthericum_liliago", + "senega", + "karanda", + "adiantum_tenerum", + "amurinkorkkipuu", + "malaxis_ophioglossoides", + "vihannesportulakka", + "leivinhiiva", + "rantavuonankaali", + "helenium_autumnale", + "juutalaiskirsikka", + "pteris_multifida", + "iris_cristata", + "rhododendron_viscosum", + "jumalainpuu", + "pine", + "peruukkipensas", + "chrysanthemum_ptarmiciflorum", + "verbascum_thapsus", + "lycium_barbarum", + "adenium_multiflorum", + "helminukkaj\u00e4kk\u00e4r\u00e4", + "pikkusoihtuk\u00f6ynn\u00f6s", + "wormwood", + "hieracium_pilocella", + "sophora_sinensis", + "pleurotus_phosphoreus", + "isosorsimo", + "neilikkakuparilehti", + "kermaomena", + "intiankrassi", + "carduus_crispus", + "muuriyrtti", + "vesiapila", + "pityrogramma_chrysophylla", + "kantasieni", + "asclepia_meadii", + "helicteres_isora", + "auringonkukat", + "salvia_leucophylla", + "hirvenkieli", + "iris_germanica", + "saunakukka", + "jasmiinitee", + "nurmikohokki", + "lilium_philadelphicum", + "rentukka", + "rhus_copallina", + "mets\u00e4j\u00e4nis", + "tricholoma_sejunctum", + "coeloglossum_viride", + "parsaherne", + "lilium_longiflorum", + "englanninsinililja", + "sorghum_halepense", + "isopyrum_biternatum", + "rubus_saxatilis", + "rantaminttu", + "solusein\u00e4", + "mets\u00e4vaahtera", + "orkideapuu", + "kyhmyk\u00e4pym\u00e4nty", + "phoradendron_flavescens", + "bintangor", + "k\u00e4\u00e4pi\u00f6vuorim\u00e4nty", + "veronica_beccabunga", + "lysimachia_ciliatum", + "dennstaedtia_punctilobula", + "mentzelia_laevicaulis", + "hyoscyamus_muticus", + "athyrium_thelypteroides", + "callitris_calcarata", + "ornithogalum_pyrenaicum", + "liriodendron_tulipifera", + "kurkkupuu", + "mustabambu", + "quercus_coccinea", + "dioscorea_elephantipes", + "villijamssi", + "kyyhkynherne", + "p\u00e4iv\u00e4nkakkara", + "arabidopsis_lyrata", + "cladonia_rangiferina", + "melissa", + "triglochin_maritima", + "seriphidium_tridentatum", + "canavalia_gladiata", + "adiantumi", + "k\u00e4\u00e4pi\u00f6jaloangervo", + "lehtoneidonvaippa", + "geranium_molle", + "dioscorea_bulbifera", + "polystichum_adiantiformis", + "lyijypuu", + "amerikanvadelma", + "hoya_carnosa", + "veripy\u00f6kki", + "tricholoma_pardinum", + "helianthus_petiolaris", + "erythronium_albidum", + "herneenpalko", + "viola_arvensis", + "sapindus", + "rhapis_humilis", + "castanopsis_chrysophylla", + "j\u00e4ttiruoko", + "claviceps_purpurea", + "viola_reichenbachiana", + "amerikanvalkopy\u00f6kki", + "floridansuosypressi", + "aromikasvi", + "kaali", + "chimaphila_umbellata", + "sambucus_canadensis", + "jokivalkotammi", + "lilium_lancifolium", + "pikkuruskus", + "agastache_mexicana", + "nahkasanikka", + "preeriasalvia", + "kistus", + "polybotria_cervina", + "the_joshua_tree", + "lehtolemmikki", + "tragopogon_pratensis", + "mekkapalsami", + "plantago_psyllium", + "sarcoscypha_coccinea", + "isovelholehti", + "marjatuomipihlaja", + "scolopendrium_nigripes", + "aleuria_aurantia", + "philadelphus_coronarius", + "penstemon_davidsonii", + "aralia_elata", + "myrobalaani", + "zygocactus_truncatus", + "brassica_nigra", + "harmaakaunokki", + "shittim", + "torreya_californica", + "eleocharis_dulcis", + "juurikas", + "italianraihein\u00e4", + "annansilm\u00e4", + "hedelm\u00e4puu", + "clematis_ochroleuca", + "mustasilm\u00e4susanna", + "mets\u00e4omenapuu", + "saunionoidanlukko", + "betula_populifolia", + "bromus_tectorum", + "helleborus_niger", + "epidendrum_venosum", + "kanadankilpikierto", + "sericocarpus_linifolius", + "cleome_hassleriana", + "helianthus", + "hietaunikko", + "aristolochia_serpentaria", + "virginianvuoriminttu", + "kaasuj\u00e4rjestelm\u00e4", + "auricularia_auricula", + "pterocarpus_santalinus", + "amerikanginseng", + "kyn\u00e4kataja", + "mets\u00e4mansikka", + "adlumi", + "gaillardia_pulchella", + "hygrophorus_sordidus", + "rosa_chinensis", + "kiiltotuomi", + "j\u00e4ttipiikkikruunu", + "masmalo", + "kassiankuori", + "spergularia_rubra", + "leucanthemum_superbum", + "polygala_senega", + "pterostylis_orkidea", + "lysimachia_terrestris", + "lathyrus_latifolius", + "sein\u00e4raunioinen", + "banksia_integrifolia", + "purppuratatar", + "pihlaja", + "carissa", + "lysiloma_latisiliqua", + "scorzonera_hispanica", + "terrietia_trifoliolata", + "isolimaska", + "marsilea_quadrifolia", + "polybotrya_cervina", + "eupatorium_maculatum", + "cucurbita_moschata", + "euphorbia_hirsuta", + "silkkipuu", + "pilea_microphylla", + "monarda_citriodora", + "rudbeckia_laciniata", + "solanaceae", + "anthriscus_cerefolium", + "sarjatalvikki", + "eupatorium_perfoliatum", + "isosamettikukka", + "herukanvillaruoste", + "kentuckynkahvipuu", + "francoa_ramosa", + "preeriav\u00e4riminttu", + "clintonia_andrewsiana", + "salvia_verbenaca", + "cordia_alliodora", + "euroopanpy\u00f6kki", + "linnunruoho", + "talinum_brevifolium", + "erica_tetralix", + "carpobrotus_edulis", + "mustakuusi", + "campanula_medium", + "chrysanthemum_lacustre", + "mets\u00e4n\u00e4tkelm\u00e4", + "liljakasvi", + "caryota_urens", + "aaroninparta", + "quercus_kelloggii", + "erigeron_divergens", + "vanilla_planifolia", + "boehmeria_cylindrica", + "viola_cornuta", + "haisusieni", + "juncus_articulatus", + "eryngium_maritimum", + "schefflera_actinophylla", + "amelanchier_bartramiana", + "pityrogramma_calomelanos", + "rubus_cuneifolius", + "sida_rhombifolia", + "lactuca_scariola", + "pachysandra_terminalis", + "perhoskukka", + "hibiscus_heterophyllus", + "salix_babylonica", + "soreahiirenporras", + "sparmannia_africana", + "adlumia_fungosa", + "rantakukka", + "celastric_articulatus", + "dryopteris_marginalis", + "thermopsis_villosa", + "protium_heptaphyllum", + "senegajuuri", + "kannukasvi", + "vuosisaniainen", + "asclepias_exaltata", + "enoki", + "cyclamen_purpurascens", + "oxytropis_lambertii", + "marri", + "magnolia_acuminata", + "gymnocarpium_robertianum", + "kylm\u00e4kukka", + "galearis_spectabilis", + "cypripedium_parviflorum", + "pseudotsuga_macrocarpa", + "poppelikoivu", + "sammalpiilea", + "isoriippasalava", + "kennedia_prostrata", + "solanum_giganteum", + "suillus_albivelatus", + "lycopodium_clavitum", + "trichomanes_reniforme", + "meconopsis_betonicifolia", + "puolipensas", + "polygonatum_commutatum", + "sinit\u00e4ht\u00f6nen", + "hajuherne", + "anthyllis_vulneraria", + "physalis_pruinosa", + "prunus_japonica", + "abies_grandis", + "leucanthemum_maximum", + "anemia_adiantifolia", + "laurus_nobilis", + "lathyrus_odoratus", + "papelorikko", + "blephilia_celiata", + "paju", + "selaginella_lepidophylla", + "rhamnus_carolinianus", + "munkinhuput", + "venkoli", + "hein\u00e4vita", + "suonim\u00f6rsky", + "fraxinus_americana", + "strongylodon_macrobotrys", + "brachycome_iberidifolia", + "amanita", + "kalvasvalmuska", + "kissapaju", + "sipulinnaattihome", + "hietakirsikka", + "lehtojalava", + "sequoiadendron", + "vespula_vulgaris", + "peitekasvit", + "partanaava", + "macrotyloma_uniflorum", + "achillea_ptarmica", + "sienikeh\u00e4", + "matricaria_oreades", + "curuba", + "olkisieni", + "hiirenohra", + "arabidopsis_thaliana", + "caesalpinia_gilliesii", + "kaliforniantuliunikko", + "centaurea_nigra", + "cassia_acutifolia", + "kapeaosmank\u00e4\u00e4mi", + "sinapinsiemen", + "pilularia_globulifera", + "matkustajanpuu", + "v\u00e4limerenlimetti", + "guyakkipuu", + "vaccinium_pennsylvanicum", + "vesinen\u00e4tti", + "aguehein\u00e4", + "ambrapuu", + "microgramma_piloselloides", + "centaurea_moschata", + "peurankello", + "mets\u00e4omena", + "riskin_pienent\u00e4minen", + "kultasadekassia", + "gyromitra_fastigiata", + "rautatammi", + "siperianjalava", + "bertholletia_excelsa", + "leve\u00e4osmank\u00e4\u00e4mi", + "iris_tingitana", + "palloh\u00e4nt\u00e4", + "adenium_obesum", + "ojaleinikki", + "helianthus_annuus", + "mustamarjaorapihlaja", + "dianthus_latifolius", + "gentiana_villosa", + "epipremnum_aureum", + "villiriisi", + "cirsium_lanceolatum", + "gentianopsis_holopetala", + "pikim\u00e4nty", + "agrostis_palustris", + "sauramo", + "pluteus_aurantiorugosus", + "euphorbia_heterophylla", + "nephrolepis_pectinata", + "cirsium_eriophorum", + "cassiope_mertensiana", + "astilbe_biternata", + "sorbus_torminalis", + "kierrevallisneria", + "tulenlento", + "pikkujamssipapu", + "kokapensas", + "galanganjuuri", + "isoanopinkieli", + "perhoskleitonia", + "kirjokuusama", + "goweninsypressi", + "karpalo", + "trichostema_dichotomum", + "mustalinnunherne", + "hevosminttu", + "parathelypteris_simulata", + "lepiota_procera", + "kotkansiipi", + "commiphora_meccanensis", + "nevaimarre", + "hammasakankaali", + "jobinkyynelhein\u00e4", + "pallohuhtasieni", + "magnolia_grandiflora", + "kentt\u00e4t\u00e4dyke", + "jokip\u00e4\u00e4ryn\u00e4", + "phlebodium_aureum", + "podocarpus_elongatus", + "tulipa_clusiana", + "berteroa_incana", + "cardamine_bulbifera", + "kierrekaktus", + "vesitammi", + "koripaju", + "pelargonium_odoratissimum", + "mentzelia_livicaulis", + "ruutusiida", + "colutea_arborescens", + "risiinipapu", + "balkaninvuokko", + "krassikanankaali", + "veriapila", + "erigonum_fasciculatum", + "capparis_mitchellii", + "lumpeenlehti", + "lituruoho", + "lohik\u00e4\u00e4rmepuu", + "risiinikasvi", + "andropogon_scoparius", + "alliaria_officinalis", + "sammalheimo", + "camptosorus_rhizophyllus", + "prosopis_glandulosa", + "tupsup\u00e4\u00e4laventeli", + "microsorum_punctatum", + "liparis_loeselii", + "chionanthus_virginicus", + "pallesorvarinpensas", + "pennisetum_americanum", + "coprinus_comatus", + "harmaankeltainen", + "papaver_alpinum", + "lygodium_microphyllum", + "hydrangea_petiolaris", + "m\u00e4kileinikki", + "nummikellokanerva", + "flamingonnokka", + "podocarpus_elatus", + "bidens_tripartita", + "solanum_burbankii", + "prunus_laurocerasus", + "pachysandra_procumbens", + "karpalopensas", + "silosumakki", + "napaea_dioica", + "rhizoctinia_solani", + "allium_tuberosum", + "desmodium_motorium", + "datura_sanguinea", + "pennisetum_glaucum", + "barbadoskirsikka", + "harmaakellokanerva", + "vuohenkello", + "palmupuu", + "adiantum_pedatum", + "kavalak\u00e4rp\u00e4ssieni", + "salaattikiinankaali", + "hypericum_virginianum", + "schizachyrium_scoparium", + "kultak\u00f6ynn\u00f6s", + "senecio_triangularis", + "amelanchier_alnifolia", + "machaeranthera_tanacetifolia", + "yucca_gloriosa", + "illakko", + "perunbalsami", + "hygrophorus_caeruleus", + "passiflora_ligularis", + "murattimikania", + "salix_triandra", + "leucaena_leucocephala", + "silene_virginica", + "vesiminttu", + "oranssimaljakas", + "lilium_michiganense", + "cercidiphyllum_japonicum", + "atriplex_hortensis", + "vaccinium_corymbosum", + "salava", + "stenocarpus_sinuatus", + "karkeaviuhkalehti", + "villikirsikka", + "spiraea_prunifolia", + "cortinarius_armillatus", + "eupatorium_purpureum", + "solanum_pseudocapsicum", + "quercus_falcata", + "agropyron_intermedium", + "huippupaikka", + "begonia_heracleifolia", + "siperianunikko", + "teucrium_scorodonia", + "acer_campestre", + "anastatica_hierochuntica", + "mets\u00e4tammi", + "pomeranssipuu", + "reunusasteri", + "kaliforniant\u00f6tter\u00f6", + "kanadanvesirutto", + "kellok\u00e4rh\u00f6", + "cirsium_helenioides", + "micromeria_chamissonis", + "nemophila_maculata", + "villiluumu", + "bletilla_striata", + "manjista", + "boletellus_russellii", + "hamelia_erecta", + "j\u00e4ttipihta", + "helianthus_angustifolius", + "hietalaukka", + "babassup\u00e4hkin\u00e4", + "suippoh\u00e4rkyl\u00e4", + "cheilanthes_alabamensis", + "kilpirikko", + "sambal", + "mimosa_pudica", + "larix_siberica", + "sarcocephalus_esculentus", + "lohenkukka", + "leontopodium_alpinum", + "stapelias_asterias", + "harmio", + "saxifraga_sarmentosam", + "chamaecyparis_thyoides", + "habenaria_orbiculata", + "kirkiruoho", + "eucalyptus_stellulata", + "leve\u00e4lehtikalmia", + "asparagus_setaceus", + "keisarik\u00e4rp\u00e4ssieni", + "rubus_caesius", + "sinilaakakataja", + "papaver_somniferum", + "pythium_debaryanum", + "ruisjyv\u00e4", + "virginianmansikka", + "mastiksipistaasi", + "laventeli", + "allium_sphaerocephalum", + "lamopinaatti", + "malus_angustifolia", + "esparsetti", + "cortinarius_gentilis", + "silopersilja", + "carex_pseudocyperus", + "maarianverijuuri", + "amerikanukonsieni", + "v\u00e4limerensypressi", + "gentiana_lutea", + "murattivillakko", + "kanadanrantavehn\u00e4", + "amerikanhumala", + "tricholoma_irinum", + "guadaloupensypressi", + "mukelo", + "montia_chamissoi", + "polystichum_acrostichoides", + "mercurialis_perennis", + "euroopanmustam\u00e4nty", + "matthiola_incana", + "centaurea_cineraria", + "vihanneskrysanteemi", + "kultalehtikuusi", + "m\u00e4kiarho", + "pe_tsai", + "quercus_velutina", + "arctostaphylos_alpina", + "liberiankahvi", + "s\u00e4rkynytsyd\u00e4n", + "linnunkirsikkapuu", + "caladenia_cairnsiana", + "rantaluikka", + "botrychium_virginianum", + "acacia_pycnantha", + "pitaijakaktus", + "kanadanvuokko", + "t\u00e4pl\u00e4kirjovehka", + "cynoglossum_amabile", + "galium_lanceolatum", + "actinidia_chinensis", + "taxus_baccata", + "saxifraga_granulata", + "hammasmaissi", + "hieskoivu", + "quercus_montana", + "ritarink\u00f6ynn\u00f6s", + "chloris_gayana", + "rheum_palmatum", + "geranium_richardsonii", + "sporobolus_cryptandrus", + "lycopodium_obscurum", + "valerianella_locusta", + "periploca_graeca", + "kivikkokasvi", + "kierrot", + "islanninj\u00e4k\u00e4l\u00e4", + "kolibrikukka", + "geum_macrophyllum", + "rhus_typhina", + "ketoneilikka", + "salix_humilis", + "hiirenvirna", + "lehtisilmu", + "harmaapihta", + "nymphaea_alba", + "rhamnus_purshianus", + "lehtosinijuuri", + "silene_dioica", + "isop\u00e4iv\u00e4nkakkara", + "dicentra_spectabilis", + "penstemon_centranthifolius", + "matteuccia_struthiopteris", + "euphorbia_esula", + "dryopteris_oreopteris", + "phaseolus_coccineus", + "diplotaxis_tenuifolia", + "rhamnus_frangula", + "euphorbia_dentata", + "pulicaria_dysenterica", + "ranunculus_ficaria", + "luluabourg", + "sokuriherne", + "italiantulppaani", + "aerofyytti", + "silkkiunikko", + "cladrastis_lutea", + "polygala_paucifolia", + "malope_trifida", + "callirhoe_involucrata", + "amboinakauri", + "graptophyllum_pictum", + "senna_alata", + "mets\u00e4imarre", + "nothofagus_procera", + "ydinkudos", + "schinus_terebinthifolius", + "kellokasvi", + "amaryllis_belladonna", + "veronica_officinalis", + "phegopteris_connectilis", + "illicium_floridanum", + "cynoglossum_virginaticum", + "kiharavita", + "magnolia_soulangiana", + "kirsikkaluumu", + "sansevieria_zeylanica", + "rumex_scutatus", + "eurybia_schreberi", + "amphicarpaea_bracteata", + "pontederia_cordata", + "pycnanthemum_virginianum", + "bergamotti", + "phalaenopsis_amabilis", + "chrysanthemum_segetum", + "calophyllum_inophyllum", + "osageappelsiini", + "t\u00e4pl\u00e4kurjenpolvi", + "suojuskalvo", + "aconitum_lycoctonum", + "rosa_multiflora", + "euroopankuusi", + "hygrophorus_borealis", + "mustakoiso", + "prunus_cerasus", + "anthemis_arvensis", + "helianthus_giganteus", + "douglasinkuusi", + "microstrobos_niphophilus", + "alaskanlehdokki", + "solidago_rugosa", + "cassia_augustifolia", + "ligustrum_ovalifolium", + "niver\u00e4vaahtera", + "vesihyasintti", + "pantterililja", + "reunuspietaryrtti", + "piptadenia_macrocarpa", + "peltiphyllum_peltatum", + "pimenta_officinalis", + "anemone_riparia", + "citrus_decumana", + "acer_macrophyllum", + "nemophila_aurita", + "brysselinkaali", + "asclepias_purpurascens", + "kiivik\u00f6ynn\u00f6s", + "acacia_dealbata", + "capsicum_baccatum", + "avene_sterilis", + "pogonia_divaricata", + "ketokaunokki", + "isopuksipuu", + "harajuuri", + "silver_bell", + "lawsoninsypressi", + "rorippa_islandica", + "euonymus_americanus", + "dianthus_caryophyllus", + "agrimonia_eupatoria", + "karoliinankoiso", + "brasenia_schreberi", + "anaphalis_margaritacea", + "bidens_bipinnata", + "mantelityr\u00e4kki", + "sareptansinappi", + "calamus_australis", + "melicocca_bijugatus", + "cheiranthus_asperus", + "kellohunajakukka", + "astraeus_hygrometricus", + "jatropha_stimulosus", + "larix_occidentalis", + "euroopanvalkopy\u00f6kki", + "sinijuuri", + "spiny_talinum", + "plantago_lanceolata", + "swietinia_mahogani", + "sinivihvil\u00e4", + "laakerin\u00e4si\u00e4", + "pseudobombax_ellipticum", + "leukotti", + "piispanm\u00e4nty", + "scindapsus_aureus", + "mentha_citrata", + "erythronium_grandiflorum", + "trichostema_lanceolatum", + "polystichum_lonchitis", + "lehtotikankontti", + "ononis_spinosa", + "polystichum_braunii", + "tanacetum_ptarmiciflorum", + "andropogon_virginicus", + "kampet\u0161epuu", + "viherjouluruusu", + "hamamelis_vernalis", + "pirunpuolukka", + "ranunculus_glaberrimus", + "kirimoija", + "xanthosoma_sagittifolium", + "gleichenia_flabellata", + "astraeus_pteridis", + "hokkaidonvaahtera", + "siperiankuusi", + "kriikunapuu", + "ipomoea_leptophylla", + "acer_palmatum", + "thlaspi_arvense", + "pericallis_hybrida", + "sericocarpus_liniforius", + "ranskanlaventeli", + "agrostemma_githago", + "lis\u00e4\u00e4ntymisosa", + "ligustrum_ibolium", + "maitohorsma", + "dactyloctenium_aegypticum", + "geranium_pratense", + "pilleriviikuna", + "luostariunikko", + "silene_caroliniana", + "sitruunaeukalyptus", + "koppelok\u00e4\u00e4p\u00e4", + "mets\u00e4kuusi", + "pseudolarix_amabilis", + "mets\u00e4haapa", + "phyllodoce_breweri", + "solanum_carolinense", + "hypericum_androsaemum", + "alpinia_officinalis", + "poterium_sanguisorba", + "stylomecon_heterophyllum", + "raatihuonevilliviini", + "puhvelihein\u00e4", + "pulskaneilikka", + "kanadanlehtikuusi", + "castanea_chrysophylla", + "pohjankallioimarre", + "kultanauhalilja", + "phaseolus_aconitifolius", + "isomaite", + "taxus_cuspidata", + "montereynm\u00e4nty", + "salix_viminalis", + "athyrium_distentifolium", + "amerikanrautatammi", + "tilia_japonica", + "calvatia_gigantea", + "villiomenapuu", + "rhus_laurina", + "connarus_guianensis", + "koristeruoho", + "kalabarpapukasvi", + "melampodium_leucanthum", + "juniperus_virginiana", + "perunpippuripuu", + "sphaeralcea_coccinea", + "calamintha_grandiflora", + "omenapelargonia", + "munkinhuppu", + "kolmioka", + "acacia_auriculiformis", + "arctostaphylos_andersonii", + "marginaalinen_plasentaatio", + "eriophorum_angustifolium", + "chrysanthemum_maximum", + "leonotis_nepetifolia", + "veronica_serpyllifolia", + "parakautsu", + "kassava", + "alstonia_scholaris", + "dioscorea_paniculata", + "mustakaunokki", + "cycloloma_atriplicifolium", + "thalictrum_thalictroides", + "machaeranthera_tortifoloia", + "harmaapoppeli", + "eucalyptus_globulus", + "passio", + "cassia_fistula", + "phyllocladus_alpinus", + "ketot\u00e4dyke", + "vaccinium_arboreum", + "ruostehappomarja", + "pterospermum_acerifolium", + "platanus_occidentalis", + "passiflora_incarnata", + "phaseolus_angularis", + "clusia", + "festuca_ovina", + "preeriaeustoma", + "zanthoxylum_americanum", + "oleandra_neriiformis", + "quercus_ellipsoidalis", + "syringa_reticulata", + "ruisvirna", + "eriophyllum_lanatum", + "laakerikirsikka", + "putkiloj\u00e4nne", + "siniselja", + "spiranthes_parksii", + "arizonanplataani", + "bromus_arvensis", + "polygala_vulgaris", + "hypericum_tetrapterum", + "ardisia_crenata", + "haplopappus_phyllocephalus", + "fraxinus_quadrangulata", + "kesantokasvi", + "maustekirveli", + "liejupahaputki", + "physostigma_venenosum", + "tabaskopippuri", + "varpupipo", + "polystichum_setiferum", + "veronica_peregrina", + "sinisievikki", + "scutellaria_lateriflora", + "passiflora_maliformis", + "rikkaverihirssi", + "chrysanthemum_leucanthemum", + "nothofagus_menziesii", + "tiarella_unifoliata", + "laikkuvehka", + "koreat\u00f6rm\u00e4kukka", + "sinjuuri", + "clematis_virginiana", + "meleguettapippuri", + "cortinarius_semisanguineus", + "pennisetum_setaceum", + "valejasmiini", + "penstemon_barbatus", + "lathyrus_maritimus", + "amerikanliesu", + "asphodeline_lutea", + "rubus_trivialis", + "artemisia_tridentata", + "chenopodium_capitatum", + "chaenomeles_speciosa", + "lootusluumu", + "savumalikka", + "douglaskuusi", + "selenicereus_grandiflorus", + "citrus_aurantium", + "pelargonium_peltatum", + "vesikastanja", + "hydrophyllum_virginianum", + "vallisneriat", + "kasvilahko", + "amaranthus_spinosus", + "perhosorkidea", + "koristeraparperi", + "reseda", + "barbarea_vulgaris", + "aster_cordifolius", + "kasviheimo", + "osmanthus_americanus", + "kochia_scoparia", + "felicia_bergeriana", + "psidium_cattleianum", + "delairea_odorata", + "palmulilja", + "annona_cherimola", + "lobelia_cardinalis", + "man_of_the_earth", + "ulmus_sarniensis", + "helleborus_orientalis", + "riippapaju", + "cortinarius_violaceus", + "dianthus_barbatus", + "kanelo", + "jaloakileija", + "platanus_orientalis", + "vesis\u00e4tkin", + "piper_longum", + "pikkutyr\u00e4kki", + "gossypium_hirsutum", + "pikkuauringonkukka", + "chilenaraukaria", + "filago", + "klusia", + "bursera_microphylla", + "ceratopteris_pteridioides", + "perunkoiso", + "piippuruoho", + "abronia_maritima", + "prunus_armeniaca", + "puistolemmikki", + "campanula_americana", + "ratamosarpio", + "keikarinkukka", + "entoloma_lividum", + "castanea_dentata", + "kangaskeltavalmuska", + "tungpuu", + "maakrassi", + "quercus_stellata", + "allamanda_cathartica", + "cocculus_carolinus", + "magnolia_macrophylla", + "liquidambar", + "nymphaea_odorata", + "diplazium_pycnocarpon", + "petasites_hybridus", + "urtica", + "potamogeton_crispus", + "aavikkoruusu", + "parthenocissus_tricuspidata", + "kleitonia", + "nahkalehti", + "anthurium_andraeanum", + "iris_kaempferi", + "mentha_rotundifolia", + "villivehn\u00e4", + "hukkakaura", + "pseudowintera_colorata", + "thelypteris_dryopteris", + "elymus_hispidus", + "artemisia_cana", + "sielikk\u00f6", + "paspalum_distichum", + "tropaeolum_minus", + "macadamia_tetraphylla", + "ligustrum_obtusifolium", + "quercus_garryana", + "coreopsis_maritima", + "siluettilehti", + "saxifraga_hypnoides", + "carissa_grandiflora", + "fritillaria_mutica", + "maclura_pomifera", + "ilmaperuna", + "stenocarpus_salignus", + "malus_baccata", + "cucurbita_argyrosperma", + "aster_arenosus", + "pikkulimaska", + "cardamine_rotundifolia", + "salix_fragilis", + "amanita_muscaria", + "pseudocolus_fusiformis", + "pterocarpus_indicus", + "corylus_americana", + "yucca_filamentosa", + "brachychiton_australis", + "korpipaatsama", + "m\u00e4kikuisma", + "phylloporus_boletinoides", + "calla_palustris", + "leonurus_cardiaca", + "silybum", + "amerikankanukka", + "arenaria_peploides", + "spergula_arvensis", + "amurinlikusteri", + "cassia_alata", + "physostegia_virginiana", + "asplenium_trichomanes", + "symphyotrichum_patens", + "merin\u00e4tkelm\u00e4", + "carissa_bispinosa", + "emilia_sagitta", + "engelmanninkuusi", + "tangori", + "acer_japonicum", + "tripleurospermum_inodorum", + "silene_acaulis", + "doryopteris_pedata", + "arrhenatherum_elatius", + "lilium_maritimum", + "fraxinus_caroliniana", + "sinappi", + "agrostis_nebulosa", + "habenaria_lacera", + "asplenium_nigripes", + "asplenium_rhizophyllum", + "py\u00f6rt\u00e4n\u00f6kattara", + "conocarpus_erectus", + "vesisulka", + "eucalyptus_camphora", + "kivikkoalvejuuri", + "sormihein\u00e4", + "magnoliat", + "lysimachia_quadrifolia", + "viinihiiva", + "dryopteris_noveboracensis", + "nicotiana_alata", + "carissa_macrocarpa", + "vatukka", + "isohirvenj\u00e4k\u00e4l\u00e4", + "populus_balsamifera", + "konnanvihvil\u00e4", + "armeria_maritima", + "nicotiana_tabacum", + "varvashein\u00e4", + "quercus_incana", + "j\u00e4ttikurpitsa", + "kentt\u00e4k\u00e4enminttu", + "centaurea_scabiosa", + "myosotis_sylvatica", + "kivikasvit", + "cineraria_maritima", + "kanariank\u00f6ynn\u00f6skrassi", + "tracheophyte", + "puolik\u00f6ynn\u00f6s", + "kananga", + "harmaalepp\u00e4", + "mongoliantammi", + "woodwardia_virginica", + "hiussaniainen", + "bahiaruoho", + "chamaecrista_fasciculata", + "asclepias_verticillata", + "phyllostachys_nigra", + "rosa_laevigata", + "haroasteri", + "huntuadiantumi", + "puccinia_graminis", + "astragalus_alpinus", + "quercus_variabilis", + "ulmus_americana", + "arisaema_atrorubens", + "sateenvarjomagnolia", + "hypericum_hypericoides", + "carex_arenaria", + "aguejuuri", + "sinappi\u00f6ljy", + "psidium_guineense", + "antennaria_plantaginifolia", + "eriodictyon_californicum", + "pilosella_officinarum", + "laccopetalum_giganteum", + "erigeron_annuus", + "platycladus_orientalis", + "cassia_marginata", + "nasturtium_amphibium", + "lepista_irina", + "sphaeralcea_fasciculata", + "acanthus_mollis", + "kellopasuuna", + "sinisalvia", + "corallorhiza_striata", + "p\u00e4iv\u00e4nkakkarat", + "sphaeralcea_ambigua", + "kirjovehka", + "antirrhinum_filipes", + "hermannia_verticillata", + "crataegus_tomentosa", + "meskalpapu", + "salix_lasiolepis", + "schizaea_pusilla", + "siipipapu", + "rusokoiranhammas", + "yucca_baccata", + "laidunkarstaohdake", + "stellaria_media", + "erica_perspicua", + "leucanthemum_vulgare", + "asplenium_bradleyi", + "jatropha_urens", + "kreikanakantti", + "mustakoirank\u00f6ynn\u00f6s", + "solanum_nigrum", + "rentoakankaali", + "calochortus_amabilis", + "abies_lasiocarpa", + "mustamarjakanukka", + "campanula_rapunculus", + "jokipaju", + "tuomi", + "melastoma_malabathricum", + "arokurjenherne", + "lagarostrobus_franklinii", + "rhus_trilobata", + "unkarinsyreeni", + "rannikki", + "hammashaapa", + "lumikellot", + "cystopteris_montana", + "astronium_fraxinifolium", + "rubus_parviflorus", + "chrysopsis_villosa", + "diplotaxis_muralis", + "derris_elliptica", + "saarnivaahtera", + "leinikkikasvi", + "sciadopitys_verticillata", + "kanjonitammi", + "ulmus_alata", + "kalliovuortensembra", + "k\u00e4\u00e4pi\u00f6esikko", + "calochortus_amoenus", + "geranium_robertianum", + "lycopodium_complanatum", + "lonicera_dioica", + "peperomia_sandersii", + "aralia_spinosa", + "euroopanlehtikuusi", + "veripasuuna", + "ketok\u00e4enminttu", + "cyclophorus_lingua", + "anthemis_tinctoria", + "helianthus_tuberosus", + "hurtanminttu", + "parthenium_argentatum", + "hedysarum_coronarium", + "senna_occidentalis", + "helianthus_maximilianii", + "lysiloma_bahamensis", + "eryngium_yuccifolium", + "kanadankannusruoho", + "lampaannata", + "lehtop\u00e4hk\u00e4m\u00f6", + "korvasieni", + "pes\u00e4raunioinen", + "clematis_lasiantha", + "sarviorvokki", + "nappipellea", + "espanjantamarindi", + "polypodium_aureum", + "camassia_leichtlinii", + "artisti", + "lithospermum_canescens", + "sudenmarja", + "m\u00e4kiminttu", + "cleistes_divaricata", + "nogales", + "acanthocereus_pentagonus", + "hibiscus_elatus", + "pinaattikiinankaali", + "italianpantahein\u00e4", + "rannikonlaukkaneilikka", + "crotalaria_sagitallis", + "vaaleajouluruusu", + "sticherus_flabellatus", + "hippocrepis_comosa", + "aster_divaricatus", + "italiantalvent\u00e4hti", + "usnea_barbata", + "amphicarpa_bracteata", + "aitoel\u00e4m\u00e4nlanka", + "juovaruoho", + "keskip\u00e4iv\u00e4nkukka", + "englanninjalava", + "cornus_stolonifera", + "silkkiyrtit", + "amerikanplataani", + "coeloglossum_bracteatum", + "turkintammi", + "rantavehn\u00e4", + "rikkasinijuuri", + "oravanmarja", + "nystyk\u00e4mmek\u00e4t", + "pseudotaxus_chienii", + "meksikonsypressi", + "lycopus_americanus", + "prunus_domestica", + "bryanthus_taxifolius", + "sinapinlehti", + "suomuk\u00e4\u00e4p\u00e4", + "pohjantuomipihlaja", + "draba_verna", + "dendrocalamus_giganteus", + "sammalsuku", + "limnodium_spongia", + "cercis_occidentalis", + "enkelinsiipi", + "hapankirsikkapuu", + "tricholoma_aurantium", + "norsunk\u00e4rs\u00e4", + "kerrannaislehti", + "lithophragma_parviflorum", + "imuk\u00e4rhivilliviini", + "cheilanthes_lanosa", + "portulaca_grandiflora", + "phytophthora_infestans", + "chlorophyllum_molybdites", + "centaurea_americana", + "mustasaarni", + "varpukalmia", + "poppelimagnolia", + "bilimbi", + "leptarrhena_pyrolifolia", + "polyporus_tenuiculus", + "laguncularia_racemosa", + "hein\u00e4kaura", + "tectaria_macrodonta", + "pesup\u00e4hkin\u00e4", + "arundinaria_gigantea", + "asclepias_albicans", + "kultaetel\u00e4nherne", + "kanadanhemlokki", + "kangaspuola", + "prosopis_juliflora", + "kotikataja", + "amerikankimikki", + "acer_platanoides", + "cotoneaster_horizontalis", + "rubus_idaeus", + "h\u00e4rmesalvia", + "quercus_grosseserrata", + "haplopappus_spinulosus", + "kruunuohdake", + "rikkasinappi", + "divi_divi", + "viburnum_prunifolium", + "hevoskastanja", + "amerikankastanja", + "hein\u00e4kaurat", + "quercus_macrocarpa", + "prunus_pensylvanica", + "eucalyptus_maculata", + "jouhisara", + "oravank\u00e4p\u00e4l\u00e4", + "callirhoe_digitata", + "herttakaksikko", + "haavakyyhky", + "rahakasvi", + "styphelia_humifusum", + "sienilahko", + "gossypium_barbadense", + "j\u00e4ttituija", + "kultaimarre", + "pikkuluppio", + "vahapapu", + "safiirikorumarja", + "brachychiton_rupestris", + "sinisade", + "rustokki", + "calochortus_luteus", + "platylobium_formosum", + "ustilaginoidea_virens", + "lehtokuusama", + "sophora_secundiflora", + "oratuomi", + "hedysarum_boreale", + "erica_carnea", + "cimicifuga_racemosa", + "euphorbia_cyparissias", + "salvia_pratensis", + "centaurea_cyanus", + "euphorbia_cyathophora", + "aster_falcatus", + "haurasloikko", + "ormosia_coarctata", + "asclepias_incarnata", + "santolina_chamaecyparissus", + "balsamipuu", + "rakkopensas", + "delonix_regia", + "dorotheanthus_bellidiformis", + "jalokallioinen", + "villipersilja", + "urtica_dioica", + "p\u00e4\u00e4skynkukka", + "agaricus_campestris", + "villikaali", + "virginianmalvia", + "strobusm\u00e4nty", + "oleandra_mollis", + "hein\u00e4ratamo", + "gymnadenia_conopsea", + "arizonansypressi", + "trifolium_repens", + "merimaruna", + "eugenia_uniflora", + "cytisus_ramentaceus", + "blackberry", + "cardamine_bulbosa", + "viinivaahtera", + "quercus_prinoides", + "ketoh\u00e4rkki", + "chrysolepis_chrysophylla", + "calopogon_pulchellum", + "veronica_michauxii", + "kentt\u00e4tyr\u00e4kki", + "koristekurpitsa", + "parochetus_communis", + "mustakumina", + "maniokki", + "oenanthe_aquatica", + "virginiantupakka", + "bassaminkaijamahonki", + "tiikerinlilja", + "konnanlilja", + "espanjanneito", + "rosa_eglanteria", + "ker\u00e4kaali", + "carpenteria_californica", + "cortaderia_selloana", + "solanum", + "gentianella_amarella", + "ballota_nigra", + "kalifornianmustatammi", + "helipterum_manglesii", + "campanula_carpatica", + "hymenoxys_acaulis", + "trichomanes_boschianum", + "sisymbrium_officinale", + "xerophyllum_tenax", + "lehtosinilatva", + "nen\u00e4tti", + "sineraaria", + "salmwood", + "amerikankilpukka", + "angelica_archangelica", + "nokkonen", + "kolap\u00e4hkin\u00e4", + "acalypha_virginica", + "allium_acuminatum", + "sagittaria_latifolia", + "kolmilehti", + "campsis_radicans", + "py\u00f6r\u00f6orapihlaja", + "kanarianpietaryrtti", + "cirsium_vulgare", + "rhodosphaera_rhodanthema", + "eryngium_aquaticum", + "echinocactus_grusonii", + "eupatorium_capillifolium", + "leip\u00e4home", + "heterotheca_villosa", + "lilium_canadense", + "pallerolaukka", + "parkkitammi", + "kruunusaniainen", + "tyr\u00e4kki", + "sininen_kurjenmiekka", + "allium_neopolitanum", + "keisarinpikarililja", + "virginiansumakki", + "andromeda_glaucophylla", + "alvejuuri", + "medinilla_magnifica", + "virginianvuokko", + "corypha_umbraculifera", + "brachychiton_acerifolius", + "bartle_frere", + "raffia_farinifera", + "caragana_arborescens", + "sorbus_aucuparia", + "mustikka", + "sammakonkukka", + "senecio_cineraria", + "omenan_ruostetauti", + "intianhamppu", + "laitaistukka", + "pihlajasumakki", + "perunpalsami", + "dianthus_chinensis", + "penstemon_linarioides", + "acer_pseudoplatanus", + "lycium_halimifolium", + "salviamaruna", + "aristolochia_macrophylla", + "lotus_corniculatus", + "allium_triquetrum", + "montia_perfoliata", + "kanervamaay\u00f6kk\u00f6nen", + "clematis_tangutica", + "pikkulehtikatsura", + "polygonum_orientale", + "tulipa_suaveolens", + "gymnadenia_odoratissima", + "chrysolepis_sempervirens", + "koristetupakka", + "robinia_viscosa", + "mustaviinimarjapensas", + "hydrangea_arborescens", + "monarda_fistulosa", + "athyrium_pycnocarpon", + "amerikankello", + "meriasteri", + "brasilianp\u00e4hkin\u00e4puu", + "koristekastikka", + "amazoninkapokkipuu", + "maarianohdake", + "visteria", + "martynia_fragrans", + "calamagrostis_acutiflora", + "palmunydin", + "helluntaikukka", + "pikkusyd\u00e4n", + "putkilokasvi", + "nurmimailanen", + "polyporus_squamosus", + "raphanus_raphanistrum", + "k\u00e4\u00e4rmeenpistonyrtti", + "cornus_florida", + "lithophragma_affine", + "paratiisililja", + "ficus_diversifolia", + "katekasvi", + "cytisus_multiflorus", + "ananaskirsikka", + "mustaruoste", + "amaranthus_caudatus", + "phytelephas_macrocarpa", + "silene_latifolia", + "koristepaprika", + "kasvielin", + "mahonkipuu", + "gymnocladus_dioica", + "sapindus_marginatus", + "ceroxylon_alpinum", + "saxifraga_stellaris", + "crataegus_pedicellata", + "cronartium_ribicola", + "kotipihlaja", + "botrychium_lunaria", + "kuningasmagnolia", + "fraxinus_velutina", + "rudbeckia_serotina", + "ruohoselja", + "hanhenpaju", + "pikkuneulakaktus", + "anagallis_tenella", + "hypericum_pyramidatum", + "combretum_erythrophyllum", + "chrysosplenium_americanum", + "arenaria_caroliniana", + "echinocereus_pectinatus", + "chinkapintammi", + "tetragonia_tetragonioides", + "amatungulu", + "septobasidium_pseudopedicellatum", + "monarda_pectinata", + "fagus_sylvatica", + "scleranthus_annuus", + "laportea_canadensis", + "leonotis_nepetaefolia", + "yrttiliisukka", + "gentiana_andrewsii", + "marjaomenapuu", + "kaareutuva_lehti", + "acrocarpus_fraxinifolius", + "cupressus_lusitanica", + "salix_pentandra", + "tricholoma_flavovirens", + "aureolaria_virginica", + "collinsia_verna", + "cinchona_cordifolia", + "betula_fontinalis", + "cerastium_tomentosum", + "iisoppirantakukka", + "harmaak\u00e4enkukka", + "rubus_spectabilis", + "nurmipuntarp\u00e4\u00e4", + "prunus_subcordata", + "symphyotrichum_tenuifolium", + "marjakuusi", + "porkkana", + "drosophyllum_lusitanicum", + "crataegus_laevigata", + "antirrhinum_coulterianum", + "plagianthus_betulinus", + "coniogramme_japonica", + "anemone_virginiana", + "sinapis_arvensis", + "uudenseelanninpinaatti", + "populus_canescens", + "kasvisolukko", + "quercus_lyrata", + "ambrapuut", + "lehtikuusi", + "collinsia_parviflora", + "m\u00e4nty", + "martynia_arenaria", + "pikkuvesisulka", + "acer_circinatum", + "pokaalim\u00f6rsky", + "erigonum", + "isoauringonkukka", + "lycopodium_alopecuroides", + "lindheimera_texana", + "gloksinia", + "kampasaniainen", + "venuksenhiussaniainen", + "niilinlumme", + "kanariankrassi", + "epilobium_angustifolium", + "salix_repens", + "stanleya_pinnata", + "parap\u00e4hkin\u00e4puu", + "k\u00e4\u00e4pi\u00f6vaahtera", + "nokkoset", + "sabina", + "abelmosk", + "silene_uniflora", + "dracunculus_vulgaris", + "pilosella_aurantiaca", + "platylobium_obtusangulum", + "tupakkasinihome", + "pinus_attenuata", + "polygala_alba", + "scleroderma_aurantium", + "acacia_melanoxylon", + "surinaminkirsikka", + "cyperus_papyrus", + "leucaena_glauca", + "amerikanpersimoni", + "intianminttu", + "agrostis_canina", + "saccharomyces_cerevisiae", + "j\u00e4ttiauringonkukka", + "listera_cordata", + "carya_laciniosa", + "malvio", + "mahoniat", + "platymiscium_pinnatum", + "tropaeolum_peregrinum", + "muskottipelargonia", + "sitruunapelargonia", + "kultarikko", + "melampsora_lini", + "phyllocladus_asplenifolius", + "saccharum_officinarum", + "vahapuu", + "hydrangea_paniculata", + "kasvisolu", + "v\u00e4limerenpihlaja", + "perunroseepippuri", + "silkkialbitsia", + "buckeye", + "kielo", + "villiappelsiini", + "thrinax_keyensis", + "ceratostomella_ulmi", + "campanula_trachelium", + "kurjenkello", + "aster_ptarmicoides", + "ranunculus_bulbosus", + "johnsonhein\u00e4", + "suppilohunajakukka", + "hesperis_matronalis", + "s\u00e4dekallioinen", + "kellusvesisaniainen", + "poinciana_gilliesii", + "sourwood", + "peziza_coccinea", + "erythronium_americanum", + "taraxacum_officinale", + "laakakataja", + "kyn\u00e4jalava", + "virginianpihta", + "harmaamustesieni", + "pikkuapila", + "arenaria_serpyllifolia", + "solenostemon_scutellarioides", + "barbadoksenakerola", + "tetraneuris_grandiflora", + "lysimachia_vulgaris", + "villaheisi", + "daphne_cneorum", + "pikkuvelholehti", + "fraxinus_pennsylvanica", + "iris_persica", + "juglans_californica", + "isopiikkikruunu", + "sinivalmuska", + "kirsikkapuu", + "aarnihelokka", + "ristilimaska", + "eugenia_corynantha", + "velholehti", + "viburnum_dentatum", + "calyptridium_umbellatum", + "erica_cinerea", + "mastiksipistaasipuu", + "dracaena_draco", + "campanula_rotundifolia", + "phytolacca_dioica", + "clinopodium_grandiflorum", + "koristeomenapuu", + "purppurapihta", + "piassavapalmu", + "ruostesienitauti", + "phaseolus_multiflorus", + "begonia_cocchinea", + "medicago_intertexta", + "crotalaria_spectabilis", + "trichomanes_speciosum", + "malvastrum_coccineum", + "helianthus_laetiflorus", + "villikaura", + "bengalinruusu", + "campanula_glomerata", + "chrysanthemum_coccineum", + "phaseolus_lunatus", + "lonicera_tatarica", + "pachyrhizus_tuberosus", + "hypochaeris_radicata", + "oranssikeltano", + "miehenk\u00e4mmekk\u00e4", + "amerikanterttuselja", + "villanm\u00f6yhennyskone", + "clusia_flava", + "pellaea_mucronata", + "pulsatilla_occidentalis", + "actinidia_deliciosa", + "aporocactus_flagelliformis", + "jumaltenpuu", + "dalbergia_latifolia", + "polystichum_aculeatum", + "anemopsis_californica", + "geranium_viscosissimum", + "liilanv\u00e4rinen", + "rikkaportulakka", + "marathi", + "mets\u00e4korte", + "dipladenia_boliviensis", + "gaultheria_procumbens", + "thelypteris_hexagonoptera", + "anemone_pulsatilla", + "anjovisp\u00e4\u00e4ryn\u00e4puu", + "lehtoakileija", + "villitiikki", + "beta_vulgaris", + "eucalyptus_amygdalina", + "mastik", + "polystichum_scopulinum", + "allium_carinatum", + "seneganjuuri", + "kiiltomalva", + "prunus_lyonii", + "cerastium_alpinum", + "cypripedium_fasciculatum", + "takiaistammi", + "pleurotus_ostreatus", + "ruistankio", + "omphalotus_illudens", + "allium_ursinum", + "harpullia_pendula", + "keisarinkruunu", + "sorvarinpensas", + "ligustrum_amurense", + "tetraneuris_acaulis", + "pseudotsuga_menziesii", + "helianthemum_scoparium", + "syzygium_jambos", + "amerikansuolilja", + "salvia_lancifolia", + "monotropa_uniflora", + "ole_varovainen", + "tonkapapupuu", + "kiiltoraunioinen", + "penstemon_dolius", + "rotkohemlokki", + "stephanomeria_malheurensis", + "tanacetum_parthenium", + "puolukka", + "hymenoxys_grandiflora", + "rosa_odorata", + "suopursu", + "erythrina", + "lithospermum_officinale", + "jalava", + "chrysothamnus_nauseosus", + "arisaema_dracontium", + "salix_vitellina", + "p\u00e4iv\u00e4nsini", + "blephilia_hirsuta", + "sabal_palmetto", + "piennarkaunokki", + "kolmis\u00e4detyr\u00e4kki", + "kongonkahvi", + "vangueria_infausta", + "centaurium_minus", + "sipulinnoki", + "kirsikkapuumets\u00e4", + "asparagus_plumosus", + "hygrophorus_tennesseensis", + "tundrapaju", + "calandrinia_ciliata", + "tangeriini", + "heracleum_sphondylium", + "kirveli", + "lobelia_siphilitica", + "pyh\u00e4_maria", + "crataegus_aestivalis", + "drimys_winteri", + "dolichos_biflorus", + "erigeron_pulchellus", + "leucadendron_argenteum", + "prunus_cuneata", + "luikka", + "k\u00e4\u00e4pi\u00f6banaani", + "lepidothamnus_laxifolius", + "phlox_subulata", + "kurttukaali", + "guajakki", + "amerikanvilliomena", + "elymus_arenarius", + "puukaktus", + "rhus_toxicodenedron", + "penstemon_deustus", + "lathyrus_sylvestris", + "piippuk\u00f6ynn\u00f6s", + "anjovisp\u00e4\u00e4ryn\u00e4", + "kalkkimaariank\u00e4mmekk\u00e4", + "hiirenporras", + "sida_hermaphrodita", + "marasmius_oreades", + "symphytum_officinale", + "parsapapu", + "solidago_nemoralis", + "dicentra_canadensis", + "himalajansyreeni", + "kengurunk\u00e4p\u00e4l\u00e4", + "heteranthera_dubia", + "sapindus_drumondii", + "rosa_moschata", + "viola_tricolor", + "viburnum_opulus", + "rusokuusama", + "tuhkapaju", + "rhus_quercifolia", + "carlina_vulgaris", + "allium_vineale", + "sophora_japonica", + "lychins_chalcedonica", + "hieracium_praealtum", + "preerianhahtuhein\u00e4", + "gentiana_saponaria", + "porkkanatikku", + "platycerium_andinum", + "plasmamembraani", + "brasilianp\u00e4hkin\u00e4", + "tiibetinkoirankieli", + "tummaorapihlaja", + "sirotuomipihlaja", + "gentiana_acaulis", + "salvia_farinacea", + "elaeis_guineensis", + "calocedrus_decurrens", + "kuumepuu", + "lupinus_arboreus", + "euroopansorvarinpensas", + "arctostaphylos_manzanita", + "artemis_spinescens", + "oliivipuu", + "erythronium_montanum", + "dianthus_plumarius", + "viisis\u00e4detyr\u00e4kki", + "teeruusu", + "leptopteris_superba", + "valtilla_kaataminen", + "pelargonium_hortorum", + "virginiant\u00e4dyke", + "h\u00e4meenkylm\u00e4nkukka", + "kalliopullopuu", + "vaccinium_ovatum", + "prunus_serrulata", + "popahtava", + "beetelp\u00e4hkin\u00e4", + "euphorbia_corollata", + "aspidistra_elatior", + "galium_verum", + "sinit\u00e4htihyasintti", + "calopogon_tuberosum", + "l\u00e4\u00e4keaaloe", + "aralia_stipulata", + "cycas_circinalis", + "populus_nigra", + "kanadanselja", + "mentha_longifolia", + "kalabarpapu", + "maljakataja", + "englanninraihein\u00e4", + "asplenium_billotii", + "saxe_gothea", + "solanum_macranthum", + "mets\u00e4alvejuuri", + "isokaulussieni", + "muscari_comosum", + "stenotaphrum_secundatum", + "clatonia_lanceolata", + "alopekuuri", + "artemisia_filifolia", + "ranunculus_repens", + "kurjennokka", + "katinjuustomalva", + "herttaikikukka", + "tabernaemontana_divaricata", + "berberis_canadensis", + "kalifornianmansikkapuu", + "pussik\u00e4mmekk\u00e4", + "humulus_japonicus", + "calochortus_elegans", + "p\u00e4\u00e4si\u00e4iskaktus", + "apocynum_androsaemifolium", + "palmuaraalia", + "ribes_sativum", + "mazatecinsalvia", + "karttaohdake", + "eustoma_grandiflorum", + "tricholoma_venenata", + "mustaviinimarja", + "stellaria_holostea", + "strelitzia_reginae", + "agathis_australis", + "quira", + "lemna_minor", + "larix_laricina", + "euroopanmarjakuusi", + "coleus_aromaticus", + "corydalis_claviculata", + "aster_ericoides", + "cirsium_heterophylum", + "kivikkok\u00e4enminttu", + "hibatuija", + "tomaatinkorkkijuurisuus", + "montereynsypressi", + "pukinpensas", + "hiekkamaruna", + "villipurjo", + "kellohyasintti", + "raatihuoneviini", + "pyrola_rotundifolia", + "afrikankataja", + "sirolitutilli", + "salvinia_auriculata", + "rhododendron_californicum", + "limanpapu", + "colocasia_esculenta", + "leucothoe_fontanesiana", + "ustilago_maydis", + "inga_edulis", + "canangium", + "leopardililja", + "kaarisulkasaniainen", + "anemone_tetonensis", + "spiranthes_spiralis", + "symplocos_paniculata", + "husaarinnappi", + "gymnocarpium_dryopteris", + "protium_guianense", + "lehtonurmikka", + "lonicera_albiflora", + "hietalilja", + "enokitake", + "kimalaisorho", + "monardella_lanceolata", + "cardamine_pratensis", + "salpiglossis_sinuata", + "rairuoho", + "rakkok\u00f6ynn\u00f6s", + "trifolium_stoloniferum", + "hypericum_calycinum", + "villipetunia", + "pteris_serrulata", + "pteretis_struthiopteris", + "hypericum_maculatum", + "harmaasieppo", + "urocystis_cepulae", + "phyllitis_scolopendrium", + "zoisia", + "hypericum_perforatum", + "mustaherukkapensas", + "sievikki", + "pyramidipoppeli", + "hedgata", + "pampahein\u00e4", + "allium_fistulosum", + "banksinm\u00e4nty", + "menispermum_canadense", + "anthurium_scherzerianum", + "ampiaisyrtit", + "mannasaarni", + "acrostichum_aureum", + "melissat", + "mustatammi", + "callitris_cupressiformis", + "kaalivalvatti", + "azaleastrum", + "j\u00e4ttiagaave", + "lychnis_coronaria", + "brunfelsia_americana", + "naamakukkaiskasvi", + "t\u00e4pl\u00e4munkinhuppu", + "riippakirjopeippi", + "salix_arctica", + "eucalyptus_grandis", + "conyza_canadensis", + "resedat", + "cananga", + "suoluikka", + "pellicularia_filamentosa", + "cassia_javonica", + "corallorhiza_maculata", + "rosa_spithamaea", + "alligaattoriruoho", + "phacelia_campanularia", + "savoijinkaali", + "montia_cordifolia", + "gentiana_calycosa", + "campanula_aparinoides", + "amaranthus_hypochondriacus", + "kampylotrooppinen_siemenaihe", + "solidago_multiradiata", + "lithocarpus_densiflorus", + "sarvip\u00e4hkin\u00e4", + "kellokuusama", + "jaakopin_portaat", + "h\u00e4m\u00e4h\u00e4kkikukat", + "alnus_glutinosa", + "rannikkotammi", + "amerikan\u00f6ljypalmu", + "gerardia_virginica", + "cnidoscolus_urens", + "gymnopilus_ventricosus", + "diplotaxis_erucoides", + "cypripedium_montanum", + "eucalyptus_calophylla", + "solidago_flexicaulis", + "erodium_texanum", + "desmodium_gyrans", + "verihelttaseitikki", + "viola_sylvatica", + "dioscorea_alata", + "arctium_minus", + "kanadanakileija", + "arrhenatherum", + "eucalyptus_pauciflora", + "annona_reticulata", + "cheilanthes_gracillima", + "pinus_muricata", + "paris_quadrifolia", + "agropyron_repens", + "ruotsinpitk\u00e4palko", + "samettisumakki", + "chrysanthemum_morifolium", + "phytolacca_americana", + "nicotiana_rustica", + "isorusokas", + "reseda_odorata", + "heuchera_americana", + "nyctaginia_capitata", + "lathyrus_sativus", + "oranssikorallipuu", + "lemmenkukka", + "viherliljapuu", + "veronica_arvensis", + "anthriscus_sylvestris", + "belladonna", + "marchantia_polymorpha", + "anemonella_thalictroides", + "sipulikurjenmiekka", + "leopardinkukka", + "campanula_pyramidalis", + "goanpapu", + "pteridium_aquilinum", + "polygala_lutea", + "mesquitehein\u00e4", + "begonia_cheimantha", + "aglaonema_modestum", + "ruostevaleatsalea", + "ketomaruna", + "maianthemum_canadense", + "cinnamomum_cassia", + "lehtisalaatti", + "panicum_capillare", + "lathyrus_splendens", + "erysimum_arkansanum", + "papaver_californicum", + "tatinriesa", + "smilax_aspera", + "begonia_socotrana", + "papukasvi", + "salvia_sclarea", + "haisusauramo", + "keuhkosammal", + "larix_russica", + "teurikka", + "sterculia_acerifolia", + "sarvisieni", + "j\u00e4rvikorte", + "aristolochia_clematitis", + "allium_ampeloprasum", + "catharanthus_roseus", + "crataegus_mollis", + "huovinkukka", + "mirabilis_longiflora", + "ageratum_houstonianum", + "campyloneurum_angustifolium", + "lepp\u00e4", + "merimiehensyd\u00e4n", + "agropyron_trachycaulum", + "corticium_salmonicolor", + "cephalanthera_rubra", + "tellima_affinis", + "vangueria_madagascariensis", + "cypripedium_calceolus", + "mustasinappi", + "abies_bracteata", + "cyrtomium_aculeatum", + "rusovuohenkuusama", + "sitruunamelissa", + "viola_odorata", + "poa_nemoralis", + "luumupuu", + "aster_turbinellis", + "antheropeas_wallacei", + "pikkusormustinkukka", + "corylus_cornuta", + "amerikanjalava", + "lehtonoidanlukko", + "kalifornianlaakeripuu", + "kasvisuku", + "toxicodendron_radicans", + "mansikkakoiso", + "pikkujasmike", + "solidago_spathulata", + "amaranthus_albus", + "juuripersilja", + "habenaria_chlorantha", + "saxegothea", + "lettokasvi", + "katajanmarja", + "iris_florentina", + "mets\u00e4lehmus", + "kellokatkero", + "iris_virginica", + "lotus_tetragonolobus", + "arctostaphylos_uva_ursi", + "hieracium_aurantiacum", + "kirjokurjenmiekka", + "leucothoe_racemosa", + "prosopis_pubescens", + "nurmit\u00e4dyke", + "amerikanmisteli", + "suomumustesieni", + "falcatifolium_falciforme", + "jalavakasvi", + "mustapoppeli", + "ritarinkello", + "chrysanthemum", + "peuranvirna", + "polypodium_polypodioides", + "viikunanlehti", + "konnant\u00e4dyke", + "linaria_canadensis", + "kontortam\u00e4nty", + "liuskahytykk\u00e4", + "taskuhein\u00e4", + "myrica_gale", + "isovesikrassi", + "allium_scorodoprasum", + "osterivinokas", + "sinikki", + "vallisneria", + "euroopantamus", + "pisarak\u00e4rh\u00f6", + "holcus_mollis", + "crambe_maritima", + "helichrysum_secundiflorum", + "alastonimpi", + "erythrina_variegata", + "kreetanmeirami", + "solanum_melanocerasum", + "piilipuu", + "platanthera_chlorantha", + "sinivatukka", + "rosa_banksiae", + "acer_glabrum", + "rubus_canadensis", + "silkkiyrtti", + "kellussaniainen", + "epipactis_gigantea", + "sinivaleunikko", + "euphorbia_milii", + "taxus_floridana", + "begonia_tuberhybrida", + "s\u00e4rm\u00e4kuisma", + "spraguea_umbellatum", + "marraskuunkaktus", + "rubus_occidentalis", + "castilleja_sulphurea", + "myyr\u00e4nporras", + "calochortus_macrocarpus", + "thrinax_parviflora", + "helmisulkahirssi", + "isolinnunruoho", + "paradisea_liliastrum", + "euphorbia_marginata", + "asplenium_montanum", + "amerikanpunam\u00e4nty", + "kirjodurra", + "tervalepp\u00e4", + "vaihtelevarevonh\u00e4nt\u00e4", + "hakea_laurina", + "mombinluumupuu", + "villahibiskus", + "alaskanvatukka", + "kiertokasvi", + "hygrophorus_kauffmanii", + "t\u00f6tter\u00f6lehti", + "passiflora_mollissima", + "arundinaria_tecta", + "solmuvihvil\u00e4", + "rudbeckia_hirta", + "meelia", + "callirhoe_triangulata", + "tummarusokki", + "guajakkipuu", + "phyllostachys_bambusoides", + "saniaissuku", + "solanum_commersonii", + "beaumontia_grandiflora", + "madonnanlilja", + "viherpantahein\u00e4", + "hygrophorus_turundus", + "purppurasulkahirssi", + "bletia_striata", + "platanus_acerifolia", + "riekonmarja", + "physalis_peruviana", + "taiteilija", + "scleroderma_flavidium", + "parthenium_integrifolium", + "kanarianhelpi", + "sambucus_ebulus", + "amerikanginsengjuuri", + "rubus_odoratus", + "agropyron_pauciflorum", + "hyv\u00e4nheikinsavikka", + "leijonankita", + "balkaninhevoskastanja", + "hamamelis_virginiana", + "tonkapapu", + "kukankorallipuu", + "arctostaphylos_tomentosa", + "puutarhakasvi", + "quercus_virginiana", + "kirsikkapaprika", + "metrinpapu", + "parakautsupuu", + "amerikanharmaalepp\u00e4", + "platanthera_leucophea", + "tikankontti", + "sarcocephalus_latifolius", + "gossypium_thurberi", + "clematis_verticillaris", + "calystegia_sepium", + "likusteri", + "podocarpus_latifolius", + "wolffiella_gladiata", + "tammisavikka", + "dicksonia_antarctica", + "muscari_neglectum", + "pitk\u00e4pippuri", + "baccharis_pilularis", + "penstemon_fruticosus", + "kivimaissi", + "magnolia", + "dryopteris_thelypteris", + "solanum_wrightii", + "konnanleinikki", + "tervakukka", + "eucalyptus_regnans", + "pomeranssi", + "galium_boreale", + "leucothoe_editorum", + "centaurea_gymnocarpa", + "passiflora_foetida", + "ulmus_hollandica", + "nyssa_sylvatica", + "kirjopikarililja", + "cassia_marilandica", + "nephrolepis_exaltata", + "polyporus_frondosus", + "asclepias_meadii", + "gerardia_pedicularia", + "pterocarpus_macrocarpus", + "amerikanheisi", + "cherimoya", + "ahonoidanlukko", + "quercus_texana", + "coleus_amboinicus", + "villiperuna", + "diplopterygium_longissimum", + "gyromitra_brunnea", + "brasilianroseepippuri", + "muinaism\u00e4nty", + "brodia", + "phellodendron_amurense", + "hevea_brasiliensis", + "nolina_microcarpa", + "cordyline_australis", + "tangeriin", + "ranunculus_aquatilis", + "kuningassaniainen", + "avena_barbata", + "mustamulperi", + "polypodium_vulgare", + "merikohokki", + "oligoporus_leucospongia", + "bromus_secalinus", + "anemone_occidentalis", + "pinus_palustris", + "conium_maculatum", + "omenaminttu", + "luumu", + "haisukurjenpolvi", + "plantago_media", + "plumeria_acutifolia", + "syd\u00e4nkirsikka", + "astroloma_humifusum", + "asplenium_scolopendrium", + "mahonia_nervosa", + "erythrina_corallodendrum", + "jokileinikki", + "oenanthe_crocata", + "honka", + "kreikanlohik\u00e4\u00e4rmevehka", + "lotus_berthelotii", + "artemisia_maritima", + "ranunculus_acris", + "t\u00e4pl\u00e4punalatva", + "sebastiana_palmeri", + "untuvahein\u00e4", + "cirsium_arvense", + "centaurea_imperialis", + "cypripedium_reginae", + "alpinia_officinarum", + "abronia_villosa", + "andromeda_polifolia", + "mustasilm\u00f6", + "kengurupensas", + "teucrium_canadense", + "kangasparkki", + "amerikankuusama", + "sinivanda", + "lemmenmarja", + "hydrofyytti", + "pinus_echinata", + "malacothamnus_fasciculatus", + "verbascum_lychnitis", + "silver_fern", + "quercus_borealis", + "betula_papyrifera", + "phyllostachys_aurea", + "rosa_damascena", + "rantamaite", + "pterocarpus_angolensis", + "purppurarevonh\u00e4nt\u00e4", + "torvikukka", + "aegilops_triuncalis", + "platanthera_bifolia", + "valehortensia", + "kanadanluumu", + "scirpus_acutus", + "saniaisheimo", + "anchusa_capensis", + "salix_pyrifolia", + "camellia_japonica", + "nothofagus_truncata", + "kanadanlilja", + "anthericum_torreyi", + "calamagrostic_quadriseta", + "kangaskorte", + "maariankello", + "santelipuu", + "solanum_quitoense", + "sormituoksukki", + "centaurium_scilloides", + "rinnevalkotammi", + "hibiscus_moschatus", + "karnaubavaha", + "rantakanerva", + "podocarpus_nivalis", + "stylophorum_diphyllum" + ], + "PUBLIC_FIGURE": [ + "lawrence_durrell", + "la_tour", + "henry_cavendish", + "matthew_arnold", + "harding", + "maria_montesorri", + "lambert", + "burbage", + "forester", + "lev_ivanov", + "goldmark", + "guggenheim", + "styron", + "helmikirjoahven", + "mccormick", + "streisand", + "benjamin_franklin", + "maitland", + "martin_buber", + "john_bartlett", + "e_b_white", + "longfellow", + "gropius", + "karl_gjellerup", + "sullivan", + "akira_kurosawa", + "frances_wright", + "mayer", + "niccolo_paganini", + "yastrzemski", + "carnegie", + "hurrata", + "maria_tallchief", + "valentina_tere\u0161kova", + "curtis", + "noah_webster", + "jean_genet", + "von_rundstedt", + "tradescant", + "dinesen", + "john_knox", + "alempitasoinen", + "heinrich_hertz", + "kesey", + "mauriac", + "waldheim", + "jean_laffite", + "roger_williams", + "jevtu\u0161enko", + "lovelace", + "marsalkka", + "livingstone", + "le_duc_tho", + "giovanni_boccaccio", + "saint_maarten", + "cornelius_vanderbilt", + "ekman", + "dionysios", + "huntington", + "wren", + "rudolf_steiner", + "klinefelter", + "thomas_wolfe", + "eccles", + "cuvier", + "david_rittenhouse", + "ernesto_guevara", + "o'casey", + "thomas_bayes", + "sukkela", + "gjellerup", + "ben_hogan", + "joliot", + "ziegfeld", + "johann_bernoulli", + "max_bruch", + "mays", + "winckelmann", + "okkamilainen", + "leonard_bernstein", + "c_k_ogden", + "sibelius", + "weill", + "thomas_decker", + "van_allen", + "p_kristoffer", + "alistair_cooke", + "che_guevara", + "roget", + "charles_townes", + "ederle", + "kline", + "lasity\u00f6ntekij\u00e4", + "georges_simenon", + "sir_john_frederick_william_herschel", + "james_barrie", + "c", + "botticelli", + "david_grun", + "mccauley", + "van_beethoven", + "saharov", + "lasinleikkuri", + "salinger", + "karl_scheele", + "alan_seeger", + "gillespie", + "medawar", + "frankki", + "i_a_richards", + "wickliffe", + "john_endecott", + "sarjakuvastrippi", + "thomas_hodgkin", + "wright", + "dos_passos", + "philipp_schwartzerd", + "belloc", + "fleming", + "andrews", + "john_barth", + "edward_albee", + "bruegel", + "dorothy_parker", + "lipchitz", + "armstrong", + "zhukov", + "bonney", + "maria_callas", + "victor_herbert", + "de_sica", + "william_walton", + "leary", + "henrik_ibsen", + "rushdie", + "abelard", + "winslow", + "prospero_lambertini", + "morgan", + "antonio_ghislieri", + "rabelais", + "emerson", + "k\u00e4rr\u00e4\u00e4j\u00e4", + "hendrix", + "suojeluspyhimys", + "frobisher", + "laffer", + "yardbird_parker", + "william_gladstone", + "charles_liston", + "stoppard", + "de_valera", + "hughes", + "mary_shelley", + "franz_werfel", + "quine", + "marcello_malpighi", + "peter_lorre", + "karl_baedeker", + "asa_yoelson", + "mergenthaler", + "cellini", + "beckett", + "watteau", + "david_livingstone", + "frans_ferdinand", + "eduard_buchner", + "david_smith", + "pierre_terrail", + "michelson", + "bruckner", + "john_herschel", + "erikoiskoe", + "mets\u00e4nhoitaja", + "henry_villard", + "gauss", + "johannes_van_der_waals", + "andrzej_wajda", + "meyerhof", + "jan_van_eyck", + "hoffman", + "rossini", + "carl_rogers", + "macgregor", + "bernhardt", + "cortez", + "george_balanchine", + "a_e_burnside", + "bethe", + "georg_wilhelm_steller", + "richard_burton", + "gerbert", + "o_veriryhm\u00e4", + "douglas_macarthur", + "hawkins", + "james_michener", + "mary_wollstonecraft", + "brunelleschi", + "j_edgar_hoover", + "herschel", + "curtiss", + "thomas_reid", + "dukas", + "john_jacob_astor", + "otto_frisch", + "anna_pavlova", + "winston_churchill", + "allen_stewart_konigsberg", + "johannes_diderik_van_der_waals", + "andrei_saharov", + "waite", + "giambattista_marini", + "mendelssohn", + "robert_macgregor", + "b", + "maillol", + "conrad_aiken", + "emile_gaboriau", + "karl_landsteiner", + "josephus", + "monnet", + "ivan_pavlov", + "didrikson", + "paul_mccartney", + "snead", + "sinclair", + "ulanova", + "richard_smalley", + "yamani", + "waugh", + "andrew_marvell", + "terry_pratchett", + "vermeer", + "k", + "trevino", + "clausewitz", + "francois_rabelais", + "macdowell", + "woodward", + "stephen_king", + "francis_crick", + "roebling", + "peter_o\u2019toole", + "john_trumbull", + "sherry", + "van_gogh", + "gregorius_suuri", + "joseph_greenberg", + "de_sade", + "mets\u00e4nvartija", + "chirico", + "miles_standish", + "de_gaulle", + "isaac_newton", + "sherman", + "richard_upjohn", + "michener", + "m_j_schleiden", + "woolf", + "alfred_eisenstaedt", + "depardieu", + "victor_hugo", + "delius", + "joseph_smith", + "bartholdi", + "edwin_hubble", + "senefelder", + "colette", + "malebranche", + "milton_friedman", + "al_hasan_ibn_al_haytham", + "inge", + "john_rock", + "amy_lowell", + "benton", + "edward_gibbon", + "justinianus", + "televisiot\u00e4hti", + "salaivallinen", + "schoolcraft", + "schiaparelli", + "louis_tiffany", + "van_de_velde", + "grigori_potjomkin", + "james_usher", + "pincus", + "j_c_maxwell", + "jefferson_davis", + "arafat", + "bertillon", + "saint_louis", + "holbein", + "cass_gilbert", + "giosue_carducci", + "george_stephenson", + "watson", + "osborne", + "john_glenn", + "beauvoir", + "john_webster", + "wykeham", + "john_davis", + "malevit\u0161", + "lorenz_okenfuss", + "george_burns", + "kaarle", + "jarrell", + "bakunin", + "bartlett", + "nikolaus_v", + "george_harrison", + "stowe", + "peter_minuit", + "galois", + "mark_clark", + "sandor_kellner", + "sebastian_vizcaino", + "amundsen", + "george_orwell", + "ellison", + "morrison", + "woolworth", + "georg_meissner", + "arthur_koestler", + "hernan_cortes", + "richard_wagner", + "cat_valium", + "joseph_john_thomson", + "williams", + "stanislavsky", + "thornton_wilder", + "e_l_doctorow", + "der_fuhrer", + "pancho_villa", + "diaz", + "o'flaherty", + "monet", + "aleksandr_borodin", + "j_j_hill", + "johns", + "john_hemminge", + "leopold_stokowski", + "higginson", + "jonson", + "rebecca_west", + "stockton", + "marie_curie", + "mount_wilson", + "malthus", + "simenon", + "francis_galton", + "jussieu", + "john_rowlands", + "mccarthy", + "prokofjev", + "peukaloiset", + "tandy", + "mary_martin", + "gordimer", + "reijo", + "richard_roberts", + "constantine", + "michael_jackson", + "da_gama", + "nicolson", + "louis_jolliet", + "carl_sandburg", + "pugin", + "taylor", + "stephenson", + "thomas_hobbes", + "goldman", + "sir_william_chambers", + "faberge", + "satuprinssi", + "joseph_lister", + "derain", + "the_admirable_crichton", + "edward_weston", + "meissner", + "el_greco", + "macleod", + "waller", + "samuel_beckett", + "puulusikka", + "katariina", + "tasatilanne", + "prohorov", + "seaman", + "jacques_costeau", + "james_william_reiher_jr", + "clinton", + "connolly", + "david", + "russell", + "galileo_galilei", + "skeat", + "van_eyck", + "czerny", + "ernest_bevin", + "jane_goodall", + "john_donne", + "valtionp\u00e4\u00e4mies", + "chaim_weizmann", + "sergei_vasiljevit\u0161_rahmaninov", + "nikolai_i", + "lardner", + "andrea_guarneri", + "robert_koch", + "wajda", + "van_vleck", + "burbank", + "i_m_pei", + "marshall", + "todd", + "joseph_goebbels", + "george_eastman", + "john_steinbeck", + "asimov", + "hans_holbein_nuorempi", + "epstein", + "erich_mendelsohn", + "utrillo", + "a_e_w_mason", + "northrop", + "mantegna", + "donald_glaser", + "barth", + "strickland", + "demille", + "langmuir", + "mendeleyev", + "c_northcote_parkinson", + "edmund_hillary", + "brigid", + "binet", + "trevithick", + "galvani", + "corbett", + "vincent_van_gogh", + "richard_hooker", + "strasberg", + "w", + "william_hazlitt", + "pickford", + "martina_navr\u00e1tilov\u00e1", + "marie_stopes", + "lauri", + "dostojevski", + "yrj\u00e4n\u00e4", + "john_ruskin", + "franz_lehar", + "granville_barker", + "robert_burns", + "john_henry", + "hans_albrecht_bethe", + "carl_anderson", + "nathaniel_bailey", + "behrens", + "steinbeck", + "visconti", + "bunche", + "john_galbraith", + "hess", + "thomas_paine", + "bari", + "ustinov", + "ulkomuuri", + "murrow", + "elizabeth_seaman", + "sully", + "liliuokalani", + "gielgud", + "francis_beaumont", + "hans_jurgen_eysenck", + "alhacen", + "i_f_stone", + "marini", + "karl_wernicke", + "edvard", + "bergman", + "wilkins", + "steven_weinberg", + "the_great_compromiser", + "p", + "mary_pickford", + "hans_fischer", + "emiliano_zapata", + "boulez", + "lavoisier", + "elisabet", + "cristobal_colon", + "karl_barth", + "dowland", + "millais", + "calvino", + "willem_einthoven", + "johann_winckelmann", + "rockwell", + "cather", + "sikorsky", + "phil_anderson", + "thomas_willis", + "charles_chaplin", + "bernard_malamud", + "samuel_johnson", + "giovanni_battista_montini", + "allen_iverson", + "nimitz", + "wesley", + "smith", + "marie_antoinette", + "anne_hutchinson", + "louise_nevelson", + "giuseppe_verdi", + "galsworthy", + "walter_lippmann", + "edward_appleton", + "breuer", + "e", + "c_g_jung", + "hevoskuski", + "scheele", + "riivaaja", + "lafitte", + "frankfurtinmakkara", + "karl_jaspers", + "korzybski", + "emily_bronte", + "beethoven", + "helmholtz", + "ferber", + "hideki_yukawa", + "connors", + "konrad_adenauer", + "mencken", + "bessel", + "howe", + "vanderbilt", + "c_vann_woodward", + "donatus", + "john_l_lewis", + "bush", + "marianne_moore", + "norbert_wiener", + "john_masefield", + "horatio_nelson", + "mark_rothko", + "shepard", + "brueghel", + "maurice_chevalier", + "gottlieb_daimler", + "fourier", + "francoise_athenais_de_rochechouart", + "schlesinger", + "finnbogadottir", + "scriabin", + "frank_sinatra", + "valkoporro", + "isherwood", + "pipin", + "bowditch", + "fallopio", + "rahank\u00e4sittelij\u00e4", + "arendt", + "abel_tasman", + "katharine_hepburn", + "noguchi", + "guthrie", + "henri_becquerel", + "henri_matisse", + "alfonso_borgia", + "pahlevi", + "bertram_brockhouse", + "ginsberg", + "louis_pasteur", + "van_de_graaff", + "ponselle", + "hoffmann", + "gaboriau", + "berra", + "sherrington", + "j", + "richard_strauss", + "stephen_decatur", + "herculius", + "galbraith", + "leslie_howard", + "jean_baptiste_racine", + "mehemet_ali", + "theodosius_i", + "aristarkhos", + "joseph_oliver", + "hugo_grotius", + "pushkin", + "maginot", + "kissinger", + "mahalia_jackson", + "william_franklin_graham", + "kendrew", + "ben_shahn", + "mohorovicic", + "john_ford", + "stephen_foster", + "alphonse_bertillon", + "wilhelm_ockhamilainen", + "charles_ringling", + "katherine_mansfield", + "gertrude_stein", + "fallopius", + "van_der_waals", + "j_b_s_haldane", + "saladin", + "kettering", + "sarah_bernhardt", + "george_beadle", + "trotski", + "krasner", + "e_h_harriman", + "sergei_rahmaninov", + "taidekauppias", + "v", + "h_c_andersen", + "hayes", + "philip_marlowe", + "greene", + "gretzky", + "luigi_pirandello", + "roope", + "t_s_eliot", + "shapley", + "tarkovski", + "e_g_marshall", + "watts", + "madame_tussaud", + "sanasokeus", + "karol_wojtyla", + "mallarme", + "marc_blitzstein", + "hank_williams", + "hazlitt", + "weston", + "vanuttaja", + "benchley", + "rube_goldberg", + "dorothea_lange", + "james_thurber", + "st_christopher", + "william_menninger", + "strachey", + "chaplin", + "charles_de_gaulle", + "ylikersanttikala", + "paul_von_hindenburg", + "florio", + "y", + "henrik_beauclerc", + "henry_moore", + "perutz", + "schumann", + "komentop\u00e4\u00e4llikk\u00f6", + "holden", + "mary_mallon", + "p_crispin", + "lytton", + "vatsatanssija", + "ralph_bunche", + "rudolf_bultmann", + "dempsey", + "douglass", + "charles_lindbergh", + "fremont", + "clive", + "grappelli", + "erythrina", + "grimminsukeltajakauris", + "jespersen", + "villon", + "emile_herzog", + "vincenzo_bellini", + "samuel_barber", + "tobias_smollett", + "joseph_stalin", + "olkikatontekij\u00e4", + "al_haytham", + "f", + "john_jay", + "tobey", + "ludwig_wittgenstein", + "august_strindberg", + "stalin", + "bunyan", + "thomas_mann", + "paton", + "hathaway", + "kendall", + "kahlauspaikka", + "bin_laden", + "alla_nazimova", + "charles_goodyear", + "dante_alighieri", + "kaarlo", + "hoyle", + "wernicke", + "cunningham", + "charles", + "vesalius", + "margot_fonteyn", + "nathaniel_currier", + "david_hubel", + "peter_pan", + "a_tyyppi", + "prinssi_charles", + "james_tobin", + "john_irving", + "panofsky", + "samuel_de_champlain", + "shirer", + "paxton", + "taimistoviljelij\u00e4", + "e_h_weber", + "giacomo_puccini", + "edward_fitzgerald", + "eyck", + "fridtjof_nansen", + "louis_braille", + "herbert_marcuse", + "junioriasteen", + "mungo_park", + "benedict_arnold", + "wyatt", + "paul_verlaine", + "cowper", + "q", + "tappan", + "robert_johnson", + "kropotkin", + "p\u00e4\u00e4asiamies", + "mark_hopkins", + "traubel", + "mount_sherman", + "g\u00f6ring", + "balfour", + "james_dean", + "robert", + "richard_lovelace", + "jacob_harmensen", + "scorsese", + "mason", + "marie_tussaud", + "burnett", + "roger_bannister", + "charles_hall", + "heinrich_i", + "john_cash", + "lasinhioja", + "theodor_schwann", + "max_beerbohm", + "tasman", + "greeley", + "alessandro_manzoni", + "joseph_priestley", + "frederick_furnivall", + "hermann_snellen", + "robert_oppenheimer", + "nicolas_poussin", + "andrea_mantegna", + "adolf_windaus", + "francois_mansart", + "kolumbus", + "hayek", + "clemenceau", + "joseph_pulitzer", + "ring_lardner", + "sperry", + "george_huntington", + "charles_schulz", + "irving", + "barany", + "caruso", + "jim_corbett", + "mommsen", + "james_naismith", + "marlowe", + "malpighi", + "oscar_wilde", + "socinus", + "billie_the_kid", + "montgolfier", + "antoine_domino", + "de_l_orme", + "philip_roth", + "maintenon", + "burroughs", + "j_d_salinger", + "ochoa", + "konstantinus", + "simon_pietari", + "henry", + "lawrence", + "roy_wilkins", + "franklin", + "andre_weil", + "sorensen", + "humperdinck", + "richard_trevithick", + "lowry", + "william_bradford", + "johan_august_strindberg", + "heinrich_schliemann", + "montespan", + "liston", + "kean", + "lendl", + "rokkit\u00e4hti", + "bartholomeu_diaz", + "john_davys", + "carlyle", + "eli_whitney", + "vilhelm_punainen", + "jackson", + "glenn_curtiss", + "telemann", + "paola_caliari", + "don_quijote", + "clark", + "pizarro", + "morley", + "merckx", + "bradstreet", + "romberg", + "corelli", + "jan_van_der_meer", + "chambers", + "lenni", + "john_witherspoon", + "william_falkner", + "laurence_olivier", + "victor_hess", + "rhodesianihminen", + "hussein", + "jeffers", + "evans", + "cocteau", + "e_a_von_willebrand", + "pierre_larousse", + "norris", + "christiaan_eijkman", + "adolf_eichmann", + "sverdrup", + "heyward", + "paganini", + "marilyn_horne", + "boole", + "ibsen", + "lorca", + "nell_gwynne", + "marvell", + "stan_musial", + "rimbaud", + "francis_bacon", + "compton", + "pete_seeger", + "konstantin_stanislavski", + "richard_m_nixon", + "walter_hess", + "john_wycliffe", + "gaskell", + "husayn", + "joseph_heller", + "lessing", + "a", + "boone", + "francois_jacob", + "lasinleikkaaja", + "heyerdahl", + "peary", + "gershwin", + "rossetti", + "morris", + "peter_carl_goldmark", + "apollinaire", + "hassam", + "montagu", + "norman_rockwell", + "boris_spassky", + "francois_duvalier", + "james_brown", + "william_hogarth", + "modigliani", + "charles_baudelaire", + "luigi_cherubini", + "sir_william_rowan_hamilton", + "cassia_alata", + "ei_k\u00e4yt\u00f6ss\u00e4", + "deere", + "pikkuliikemies", + "david_ricardo", + "barkley", + "john_mitchell", + "henri_labrouste", + "mary_leakey", + "charlie_parker", + "z", + "immanuel_kant", + "jacques_bernoulli", + "goodall", + "kinsey", + "himmler", + "beaverbrook", + "james_franck", + "william_crookes", + "antonius_stradivarius", + "james_meredith", + "samuel_gompers", + "nellie_bly", + "brancusi", + "john_haldane", + "weber", + "lewis", + "warburg", + "fulton", + "parsons", + "alexandre_yersin", + "francois_mitterrand", + "n", + "richardson", + "pikkukeisari", + "lukemiskyvytt\u00f6myys", + "michel_montaigne", + "tunney", + "stephen_leacock", + "hope", + "albert_schweitzer", + "miller", + "flavius_theodosius", + "chagall", + "hammarskj\u00f6ld", + "john_mccormick", + "valentinois'n_herttuatar", + "john_harvard", + "johann_friedrich_herbart", + "giulio_natta", + "hardy", + "erik_weisz", + "musset", + "dewey", + "canetti", + "saint_martin", + "titus", + "johannes_kepler", + "anatoli_karpov", + "metchnikov", + "william_s_burroughs", + "david_hartley", + "max_planck", + "william_blake", + "t_e_lawrence", + "rundstedt", + "julio_iglesias", + "john_bardeen", + "rodin", + "arthur", + "hutchins", + "middleton", + "sarah_vaughan", + "nietzsche", + "dubya", + "john_wilkes", + "francois_mauriac", + "davis", + "konstantin_stanislavsky", + "thoreau", + "william_byrd", + "william_henry", + "christopher_fry", + "godard", + "scott_joplin", + "latrobe", + "samuel_houston", + "supermex", + "carl_lewis", + "sarah_siddons", + "george_vancouver", + "hinault", + "o'neill", + "gardner", + "vuillard", + "thackeray", + "passiivinen_tupakointi", + "cesar_franck", + "samuel_rosenstock", + "canberra", + "stephane_mallarme", + "cooke", + "carry_nation", + "bramante", + "goethals", + "knox", + "visuaalinen_afasia", + "elias_canetti", + "norrish", + "von_braun", + "robert_lowell", + "johann_strauss", + "eisenstein", + "edward_jenner", + "hutton", + "john_mercer", + "oscar_robertson", + "marquand", + "huston", + "oliver_hardy", + "simon_kananeus", + "kenyata", + "moore", + "von_bl\u00fccher", + "ko\u015bciuszko", + "kahlaamo", + "johan_kepler", + "husserl", + "groves", + "cole_porter", + "samuel_wilder", + "benjamin_west", + "jean_luc_godard", + "stokowski", + "graham_greene", + "baryshnikov", + "frans_hals", + "henrik_i", + "edward", + "lysenko", + "stroheim", + "whistler", + "la_fontaine", + "turkiskauppias", + "lars_onsager", + "willard", + "metallity\u00f6mies", + "jewison", + "margaret_mitchell", + "goldoni", + "konoye", + "leadbelly", + "bunuel", + "igor_stravinsky", + "duse", + "j_b_rhine", + "stuart_davis", + "olmsted", + "gary_weinstein", + "mary_mccauley", + "lola_montez", + "tucker", + "john_wain", + "jan_swammerdam", + "bellini", + "mary_mccarthy", + "jimenez", + "wilkes", + "karmeliittamunkki", + "presidentti_wilson", + "tully", + "david_riesman", + "laughton", + "doctorow", + "john_walker", + "lent\u00e4v\u00e4_hollantilainen", + "virchow", + "flavius_josephus", + "frankeerata", + "puukauha", + "william_herschel", + "wheatley", + "joseph_black", + "marcus_whitman", + "mikhail_baryshnikov", + "rooman_keisari", + "du_barry", + "montesquieu", + "oakley", + "william_john_clifton_haley_jr", + "marcus_aurelius_valerius_maximianus", + "franz_joseph", + "peirce", + "arthur_rubinstein", + "calvin", + "venekurki", + "cherubini", + "arthur_compton", + "koussevitzky", + "lindbergh", + "robbins", + "niels_bohr", + "kenneth_grahame", + "naismith", + "larousse", + "hickock", + "sheridan", + "bardeen", + "henry_fielding", + "bertrand_russell", + "fragonard", + "jakob_hermandszoon", + "katherine_anne_porter", + "ludvig_pyh\u00e4", + "madame_curie", + "hawkyns", + "michael_faraday", + "john_d_rockefeller", + "malamud", + "j_craig_ventner", + "arthur_schlesinger", + "burt", + "anthony_burgess", + "anthony", + "pyh\u00e4_yrj\u00f6", + "cummings", + "jan_tinbergen", + "swanson", + "peter_mark_roget", + "robert_venturi", + "johnny_appleseed", + "greg", + "schumpeter", + "maria_magdaleena", + "schliemann", + "o'keeffe", + "gwynne", + "ben_gurion", + "kreisler", + "maurois", + "sir_francis_galton", + "ellen_price_wood", + "ralegh", + "irving_berlin", + "wavell", + "peter_seamus_o'toole", + "julia_agrippina", + "marstan", + "otho_of_lagery", + "gauguin", + "linnustaja", + "malory", + "bernard_baruch", + "rudolf_diesel", + "hans_holbein", + "walt_disney", + "meredith", + "ben_jonson", + "lippi", + "la_spezia", + "robert_benchley", + "dowding", + "oates", + "albee", + "florey", + "h_l_mencken", + "lully", + "vesey", + "rubens", + "ondaatje", + "percy", + "joseph_schumpeter", + "beveridge", + "max_muller", + "gabriel_lippmann", + "maria_verinen", + "steve_reich", + "groucho", + "adenauer", + "lee", + "derrida", + "lamarck", + "benny_goodman", + "\u0161akkimestari", + "ted_williams", + "karl_menninger", + "william_beaumont", + "froebel", + "friedrich_engels", + "huldreich_zwingli", + "haley", + "pavlov", + "asianajoneuvos", + "steichen", + "jane_austen", + "anthony_vandyke", + "charles_laughton", + "parker", + "eichmann", + "magritte", + "gibson", + "moses", + "koloverkosto", + "ventner", + "gustav_mahler", + "lasiveitsi", + "ed_sullivan", + "phil_collins", + "nevelson", + "alice_paul", + "erving", + "robert_redford", + "robert_barany", + "monod", + "jean_giraudoux", + "fuller", + "jack_dempsey", + "brindisi", + "ian_fleming", + "swedenborg", + "richard_feynman", + "harrod", + "augustinolaismunkki", + "menninger", + "saparomakaki", + "willebrand", + "valtionjohtaja", + "kandinski", + "wolfgang_pauli", + "wycherley", + "ellington", + "landowska", + "ruskin", + "wollaston", + "lipmann", + "pietari_i", + "dodgson", + "theodore_dreiser", + "theodor_mommsen", + "andrew_huxley", + "marcel_proust", + "vilkkupyrst\u00f6kolibri", + "klimt", + "jessica_mitford", + "thomas_more", + "jesse_louis_jackson", + "homo_heidelbergensis", + "milhaud", + "paul_hindemith", + "elizabeth_taylor", + "thomas_chippendale", + "meyerbeer", + "lunt", + "anne_sullivan", + "walesa", + "paul_robeson", + "hyvinpukeutuva", + "arnold", + "benedict", + "shute", + "thomas_middleton", + "metchnikoff", + "lugosi", + "gladstone", + "m\u00fcnchhausen", + "john_dowland", + "sumner", + "le_carre", + "van_dyck", + "sarnoff", + "dag_hammarskj\u00f6ld", + "zaharias", + "millay", + "daniel_jones", + "hellman", + "benjamin_jonson", + "suurvisiiri", + "william_golding", + "robert_motherwell", + "a_e_housman", + "william_caxton", + "john_milton", + "c_h_best", + "karl_wilhelm_scheele", + "rudolf_serkin", + "couperin", + "erikoisfunktio", + "siqueiros", + "peter_stuyvesant", + "rattigan", + "henri_louis_bergson", + "ethel_merman", + "szilard", + "rittenhouse", + "riesman", + "r\u00f6ntgenteknikko", + "frank_baum", + "hotspur", + "samuel_adams", + "albert_speer", + "james_baldwin", + "lindsay", + "o_hara", + "john_copley", + "john_vanbrugh", + "gracie", + "cavell", + "kahluupaikka", + "leacock", + "indira_gandhi", + "ceylonilainen", + "daumier", + "whitman", + "millikan", + "davys", + "william_mitchell", + "albers", + "bertolucci", + "jane_seymour", + "peter_goldmark", + "peter_minnewit", + "klopstock", + "rehnquist", + "george_gershwin", + "toynbee", + "schopenhauer", + "alberto_giacometti", + "elisabet_i", + "laney", + "wallace", + "e_t_a_hoffmann", + "frank_whittle", + "alfred_nobel", + "jesse_owens", + "eisenstaedt", + "tenniel", + "friedrich_fr\u00f6bel", + "daniel_rutherford", + "ashe", + "marco_polo", + "koestler", + "john_fletcher", + "heidegger", + "georgi_zhukov", + "maria_i", + "caravaggio", + "matthias_schleiden", + "beria", + "lorenzo_de'medici", + "charlie_watts", + "albert_gore_jr", + "spenser", + "m", + "charlotte_corday", + "jamison", + "hargreaves", + "marcel_marceau", + "gilmer", + "oort", + "allen_ginsberg", + "henry_thoreau", + "fred_zinnemann", + "ringling", + "hammerstein", + "coleridge", + "daniel_bernoulli", + "kelly", + "guillaume_apollinaire", + "william_strickland", + "rautarouva", + "gibbs", + "john_marquand", + "antoine_watteau", + "l_s_lowry", + "brandt", + "pablo_casals", + "joseph_henry", + "juan_ponce_de_leon", + "henri_bergson", + "is\u00e4nn\u00f6itsij\u00e4", + "jos\u00e9_ortega_y_gasset", + "speke", + "craigie", + "bergson", + "antonius", + "jean_bernoulli", + "edward_macdowell", + "josef_hoffmann", + "potjomkin", + "hammett", + "kahlaaminen", + "kentuckylainen", + "boris_karloff", + "gottfried_leibniz", + "pierre_corneille", + "anttoni", + "heinrich_b\u00f6ll", + "phillis_wheatley", + "tussaud", + "oppenheimer", + "mohammed_reza_pahlavi", + "gregorius", + "condorcet", + "kotiavustaja", + "patrick_white", + "hans_zinsser", + "saul_steinberg", + "greenberg", + "bartholomew_roberts", + "eileen_farrell", + "daniel_morgan", + "hans_christian_andersen", + "peter_cooper", + "reich", + "schwann", + "william_morris", + "william_dawes", + "cary_grant", + "hideyo_noguchi", + "thomas", + "isaac_watts", + "saint_lawrence", + "harmsworth", + "ford", + "pieter_zeeman", + "arnold_gesell", + "scripps", + "herrick", + "glenn_miller", + "mooses", + "thomas_straussler", + "navratilova", + "sir_thomas_gresham", + "strippi", + "j\u00e4niksenk\u00e4p\u00e4l\u00e4", + "karl_von_clausewitz", + "merimieskuningas", + "musial", + "c_w_post", + "fitzgerald", + "wegener", + "pablo_picasso", + "newman", + "horne", + "mansart", + "john_philip_marquand", + "marian_anderson", + "natalie_wood", + "l_ron_hubbard", + "tagore", + "raffles", + "james_bernoulli", + "kennelly", + "alan_hodgkin", + "malinowski", + "anderson", + "thomas_moore", + "vihellin", + "robeson", + "osman_i", + "kurt_weill", + "kieslowski", + "otto_hahn", + "webster", + "nast", + "lester_young", + "welty", + "otto_meyerhof", + "john_marshall", + "mamet", + "christiaan_huygens", + "duvalier", + "hector_berlioz", + "smalley", + "hermann_g\u00f6ring", + "lucille_ball", + "paul_simon", + "mussorgsky", + "claudio_monteverdi", + "benjamin_jowett", + "rubinstein", + "nabokov", + "kuulemismenettelyst\u00e4_vastaava_neuvonantaja", + "robert_scott", + "stravinsky", + "john_galsworthy", + "knut_pedersen", + "robert_robinson", + "scott", + "ziegler", + "pieter_breughel", + "karloff", + "khachaturian", + "dickinson", + "bronte", + "spielberg", + "gombrowicz", + "o", + "goodman", + "mccartney", + "wallenstein", + "adam_smith", + "william_james", + "lipscomb", + "taney", + "mezzosopraano", + "u", + "vizcaino", + "jean_harlow", + "henry_miller", + "rautakansleri", + "sayers", + "mcguffey", + "karl_marx", + "einthoven", + "paul_bunyan", + "rickover", + "friedrich_nietzsche", + "zsigmondy", + "i", + "strindberg", + "p_daavid", + "robert_indiana", + "william_burroughs", + "noyes", + "peter_alexander_ustinov", + "jimmy_durante", + "howard", + "john_wesley", + "march_king", + "hasek", + "dorothy_sayers", + "berlage", + "st_maarten", + "tallis", + "e_o_wilson", + "melanchthon", + "goldwyn", + "sandro_botticelli", + "endecott", + "parrish", + "von_willebrand", + "carson_mccullers", + "frank_stockton", + "magna_mater", + "bloch", + "seiji_ozawa", + "nazimova", + "ehrenberg", + "proust", + "nikola_tesla", + "de_mille", + "al_capone", + "jim_bowie", + "charles_barkley", + "billy_graham", + "robert_schumann", + "mel_gibson", + "le_corbusier", + "malraux", + "carlo_goldoni", + "kuparivihtrilli", + "trumbo", + "kaufman", + "shankar", + "william_patterson", + "boleyn", + "ninigi", + "leo_delibes", + "john_locke", + "tharp", + "alexis_carrel", + "le_notre", + "du_maurier", + "l_enfant", + "j_e_johnston", + "mitchum", + "ludvig_ix", + "a_noam_chomsky", + "symonds", + "ylij\u00e4\u00e4m\u00e4nainen", + "serkin", + "joseph_marie_jacquard", + "henry_james", + "stephen_sondheim", + "henson", + "st_martin", + "richards", + "crawford", + "tri_johnson", + "myll\u00e4ri", + "oscar_hammerstein", + "steinway", + "lorenz_hart", + "marie_grosholtz", + "robert_bartlett", + "stewart", + "horney", + "jakobson", + "bierce", + "hevesy", + "perry", + "helen_keller", + "grotius", + "mandel\u0161tam", + "paul_dukas", + "e_t_s_walton", + "musta_karvanokkonen", + "ingrid_bergman", + "anna_kurnikova", + "siddons", + "tillich", + "crosby", + "tuomas", + "denmark_vesey", + "hindemith", + "hodgkin", + "leonard_bloomfield", + "congreve", + "patakuningas", + "jane_jacobs", + "thurber", + "lulli", + "verlaine", + "kerensky", + "trevelyan", + "jean_piaget", + "meany", + "soutine", + "sondheim", + "william_congreve", + "franz_kline", + "henri_rousseau", + "paul_tillich", + "hilaire_belloc", + "massine", + "aleksandr_prohorov", + "mondrian", + "darrow", + "vastan\u00e4yttelij\u00e4", + "shakspere", + "jolliet", + "montgomery_ward", + "reichstein", + "de_kooning", + "baudelaire", + "angelo_correr", + "st_denis", + "tsaari_pietari_i", + "rogers", + "carducci", + "aleksanteri_pavlovits", + "frank_norris", + "francois_couperin", + "konoe", + "pieter_brueghel", + "pyh\u00e4_apostoli_pietari", + "behring", + "francois_de_la_rochefoucauld", + "frank_stella", + "durrell", + "paige", + "stilwell", + "robert_southey", + "eddington", + "h_g_wells", + "walt_whitman", + "hernando_cortes", + "william_wyler", + "viem\u00e4ritukos", + "warren", + "jamesinlahti", + "john_osborne", + "colin_powell", + "moliere", + "ludwig_boltzmann", + "antoninus", + "beerbohm", + "carl_nielsen", + "ciardi", + "yhdysvaltain_oikeusministeri", + "karl_gauss", + "chopin", + "weizmann", + "vasarely", + "smollett", + "merton", + "pelastusliivit", + "hearst", + "pauling", + "rankin", + "bunsen", + "vaux", + "carl_jung", + "pehtori", + "israel_strassberg", + "richard_neville", + "leopold_kronecker", + "masefield", + "vilhelm_okkamilainen", + "francis_richard_stockton", + "simpson", + "richard_wright", + "heyse", + "kristoffer_kolumbus", + "benjamin_thompson", + "kandinsky", + "adolf_hitler", + "maria_mitchell", + "james_d_watson", + "kotkat", + "dindymene", + "fritz_haber", + "dekker", + "salamoitsija", + "archibald_macleish", + "fowler", + "richard_starkey", + "kaasuasentaja", + "peter_behrens", + "john_tradescant", + "nathan_bailey", + "jaspers", + "alfred_stieglitz", + "gabriele_fallopius", + "redford", + "joseph_haydn", + "stephen_spender", + "garfield", + "mendelsohn", + "jones", + "maria_tudor", + "bailey", + "george_boole", + "solvay", + "mahan", + "paul_revere", + "sontag", + "ruth_fulton", + "helen_wills", + "kruger", + "daniel_boone", + "buffalo_bill", + "william_fulbright", + "edvard_grieg", + "apostoli_jaakob", + "radhakrishnan", + "gorgas", + "robert_boyle", + "korchnoi", + "arthur_laffer", + "edith_cavell", + "mitchell", + "alan_paton", + "zinsser", + "eliot", + "hopkinson", + "verwoerd", + "ralph_richardson", + "paderewski", + "lenard", + "1", + "schubert", + "karsavina", + "alberti", + "krzysztof_kieslowski", + "cordell_hull", + "a_a_michelson", + "robert_bruce", + "blixen", + "james_wilson", + "rosa_parks", + "kustaa", + "norman_jewison", + "marceau", + "townes", + "crichton", + "riley", + "samuel_goldwyn", + "steller", + "mccullers", + "x", + "elizabeth_seton", + "ernest_walton", + "vladimir_putin", + "jacob", + "orbison", + "crockett", + "giuseppe_mazzini", + "gromyko", + "runyon", + "jim_thorpe", + "woodhull", + "karl_augustus_menninger", + "hertz", + "bradbury", + "h", + "randall_jarrell", + "old_bullion", + "verrazzano", + "richler", + "swammerdam", + "arnold_sch\u00f6nberg", + "manson", + "sekhet", + "laurence_sterne", + "markov", + "hutchinson", + "jacqueline_cochran", + "george_fox", + "graves", + "peter_paul_mauser", + "hans_holbein_vanhempi", + "ben_hecht", + "christopher_isherwood", + "bloomfield", + "fritz_kreisler", + "john_heming", + "copley", + "henry_bolingbroke", + "anne_hathaway", + "david_garrick", + "don_budge", + "meade", + "ozawa", + "bill_russell", + "margaret_court", + "emile_zola", + "berlioz", + "evers", + "owen", + "thomson", + "henry_le_chatelier", + "baldwin", + "gallaudet", + "sarjis", + "a_conan_doyle", + "jeannette_rankin", + "clarence_darrow", + "marya_sklodowska", + "alben_william_barkley", + "dawes", + "agassiz", + "mallon", + "sotilasmestari", + "charles_lamb", + "g", + "sills", + "william_of_wykeham", + "labrouste", + "albert_michelson", + "dulles", + "cattell", + "nansen", + "vespucci", + "de_niro", + "savonarola", + "brady", + "john_chapman", + "anthony_comstock", + "ellsworth", + "lemaitre", + "jansen", + "arthur_schopenhauer", + "sam_goldwyn", + "thomas_dekker", + "el_caudillo", + "custer", + "harriman", + "james_cagney", + "john_keble", + "johns_hopkins", + "l_m_montgomery", + "henri_pitot", + "wanda_landowska", + "edward_pusey", + "billy_mitchell", + "martin_heidegger", + "hans_eysenck", + "shockley", + "gaius_flaminius", + "pilkulleen", + "aiken", + "tyson", + "muller", + "tiedonimij\u00e4", + "r", + "p_patrick", + "george_lucas", + "andrew_jackson", + "konstantinus_suuri", + "edith_wharton", + "louis_armstrong", + "spallanzani", + "ortega", + "cornell", + "barnum", + "balanchine", + "pieter_bruegel", + "loeb", + "dubyuh", + "kaniiniyhdyskunta", + "antony_tudor", + "saint_christopher", + "steven_spielberg", + "sir_john_cockcroft", + "sydenham", + "bultmann", + "comstock", + "jean_monnet", + "leonard", + "sellers", + "georgiana_barrymore", + "d_w_griffith", + "robert_fulton", + "laulutaiteilija", + "goudy", + "thomas_hardy", + "eddie_rickenbacker", + "thomas_gainsborough", + "stefan_wyszynski", + "franz_ferdinand", + "giuseppe_garibaldi", + "wister", + "philip_warren_anderson", + "karlfeldt", + "hemminge", + "blitzstein", + "fra_filippo_lippi", + "alexandre_dumas", + "pirandello", + "philipp_melanchthon", + "robert_brown", + "doolittle", + "bethune", + "markoff", + "thomas_carlyle", + "wiesenthal", + "johann_gutenberg", + "roberts", + "shah_pahlavi", + "bragg", + "gagarin", + "allen_tate", + "kansankiihottaja", + "algren", + "donald_barthelme", + "andre_maurois", + "heikki", + "alphonse_capone", + "william_tyndale", + "tamara_karsavina", + "ibert", + "bobby_fischer", + "crookes", + "din_land", + "menotti", + "johannes_gutenberg", + "vakuutusmyyj\u00e4", + "thornton", + "kaunda", + "barrymore", + "d", + "karvinen", + "hooke", + "breughel", + "james_bowie", + "lasittaja", + "thomas_malthus", + "giambattista_marino", + "gaetano_donizetti", + "dreiser", + "castro", + "beadle", + "william_faulkner", + "wordsworth", + "cockcroft", + "pentti", + "plath", + "johannes_eckhart", + "edward_white", + "edouard_manet", + "titus_flavius_vespasianus", + "simon_de_montfort", + "amerigo_vespucci", + "selznick", + "wilmut", + "arthur_holmes", + "montessori", + "laurentius", + "anouilh", + "pierre_boulez", + "hans_adolf_krebs", + "grahame", + "lars", + "mcmaster", + "hollerith", + "le_chatelier", + "girolamo_savonarola", + "salk", + "smitty_stevens", + "housman", + "emma_goldman", + "robert_gray", + "blake", + "haywood", + "francis_poulenc", + "pyh\u00e4_patrick", + "james_ussher", + "wolfe", + "john_barrymore", + "john_constable", + "rachel_louise_carson", + "c_d_gibson", + "huggins", + "james_mill", + "john_ciardi", + "e_entertainment_television", + "albino_luciano", + "putin", + "landsteiner", + "gary_kasparov", + "matthew_flinders", + "hanks", + "thomas_crawford", + "chomsky", + "vilhelm_valloittaja", + "robert_herrick", + "joseph_campbell", + "charles_a_lindbergh", + "vaihtosy\u00f6tt\u00e4j\u00e4", + "st_lawrence_joki", + "grainger", + "zeppo", + "molnar", + "john_m_browning", + "swift", + "klaproth", + "jean_de_la_fontaine", + "robert_hooke", + "davy", + "lovell", + "o_henry", + "hoffa", + "harriet_wilson", + "punahilkka", + "kekule", + "karl_popper", + "birgit_nilsson", + "benjamin_kubelsky", + "alfred", + "von_sternberg", + "coleman_hawkins", + "kronecker", + "frye", + "untermeyer", + "john_calvin", + "george_sand", + "sousa", + "peter_sellers", + "homo_rhodesiensis", + "steffens", + "charles_fourier", + "john_mcgraw", + "henry_clay", + "antoni_van_leeuwenhoek", + "toscanini", + "konsta", + "giraudoux", + "marcus_aurelius", + "cousteau", + "bolingbroke", + "e_w_morley", + "peter_o'toole", + "joseph_conrad", + "william_shockley", + "hammaskeiju", + "de_spinoza", + "g\u00fcnter_grass", + "keble", + "kenneth_roberts", + "balenciaga", + "peter_paul_rubens", + "mahatma_gandhi", + "jim_morrison", + "cromwell", + "masters", + "jules_verne", + "paul_newman", + "robert_mills", + "george_meredith", + "sch\u00f6nberg", + "trollope", + "galton", + "john_marstan", + "menuhin", + "robert_morris", + "kastler", + "carroll", + "hopkins", + "antonio_pignatelli", + "zimbalist", + "eugene_ionesco", + "matisse", + "woody_herman", + "charlotte_bronte", + "heaviside", + "gehrig", + "alexander_wilson", + "john_roebling", + "vihtahousu", + "josef_albers", + "jackson_pollock", + "spinoza", + "laffite", + "david_crockett", + "welles", + "dayan", + "steinem", + "kasparov", + "p_simon", + "john_lennon", + "seton", + "andrea_palladio", + "cornelis_jansen", + "golding", + "john_speke", + "buchner", + "wilson", + "fontanne", + "gandhi", + "heinlein", + "cheever", + "poulenc", + "motherwell", + "bob_woodward", + "charlie_chaplin", + "lillian_russell", + "d_h_lawrence", + "humboldt", + "mcpherson", + "edward_morley", + "barthelme", + "j_m_barrie", + "lippmann", + "hitchings", + "robert_woodward", + "pavarotti", + "thomas_malory", + "tilden", + "lea", + "john_brown", + "al_jolson", + "pietari_suuri", + "elizabeth_gaskell", + "pyh\u00e4_jaakob", + "jinnah", + "caldwell", + "vasco_da_gama", + "john_mill", + "langtry", + "teasdale", + "kuuria", + "hugo_junkers", + "varojenk\u00e4sittelij\u00e4", + "zinnemann", + "j_r_firth", + "burnham", + "maurice_barrymore", + "haldane", + "kyrillos", + "norman_thomas", + "herttakuningas", + "lillian_hellman", + "brescia", + "brecht", + "peter_carl_faberge", + "carter", + "john_macleod", + "satie", + "tallchief", + "thomas_merton", + "benedetto_odescalchi", + "alempi_korkeakoulututkinto", + "sennett", + "massenet", + "boris_spasski", + "villard", + "riemann", + "shahn", + "stopes", + "rothko", + "asa_gray", + "donkin", + "bonhoeffer", + "spillane", + "saint_lawrence_joki", + "hannah_arendt", + "antonio_stradivari", + "wanamaker", + "c_s_forester", + "philip_anderson", + "kuhn", + "cushing", + "maximianus", + "robinson_jeffers", + "farrell", + "eckhart", + "kylm\u00e4nkest\u00e4v\u00e4", + "alice_walker", + "priestley", + "d_oyly_carte", + "karl_czerny", + "casals", + "sir_james_murray", + "strauss", + "macleish", + "miles_davis", + "edmund_cartwright", + "koopmans", + "rupert", + "mubarak", + "sir_william_walton", + "wollstonecraft", + "pusey", + "bruce", + "tere\u0161kova", + "butterfield", + "james_parkinson", + "heyrovsky", + "brummell", + "a_e_kennelly", + "wilhelm_tell", + "j_m_synge", + "william_augustus", + "oldfield", + "g_voima", + "george_marshall", + "onsager", + "cochran", + "eijkman", + "cagney", + "tuchman", + "gesell", + "harold_nicolson", + "jesse_jackson", + "willa_cather", + "ethelred", + "vakuutusmeklari", + "stanley_kubrick", + "mohammed_ali", + "cornelius_jansenius", + "leontief", + "john_deere", + "andre_markoff", + "champollion", + "cronyn", + "keaton", + "john_huston", + "robert_merton", + "carothers", + "takamets\u00e4", + "ivanov", + "jean_baptiste_joseph_fourier", + "debs", + "william_gilbert", + "rene_magritte", + "tanaj\u00e4rvi", + "mcgraw", + "le_gallienne", + "astaire", + "james_watt", + "jonathan_edwards", + "ronald_reagan", + "helmut_schmidt", + "jenny_lind", + "leigh", + "homo", + "frederick_douglass", + "tebaldi", + "von_bismarck", + "symons", + "moynihan", + "la_rochefoucauld", + "alamaalainen", + "david_hilbert", + "skinner", + "kyhmyhaahka", + "wilhelm_reich", + "duchamp", + "william_thornton", + "roman_jakobson", + "oliver_cromwell", + "vinogradoff", + "aurinkokuningas", + "beaumont", + "lionel_hampton", + "newcomb", + "martin_luther_king", + "bukharin", + "purcell", + "james_hargreaves", + "goncourt", + "delbruck", + "lorenz", + "raymond_lully", + "frank_capra", + "william_wordsworth", + "rex_harrison", + "s", + "william_clark", + "s_smith_stevens", + "woodrow_wilson", + "thomas_jackson", + "delibes", + "william_wycherley", + "walton", + "o'brien", + "margaret_sanger", + "proudhon", + "heming", + "bankhead", + "southey", + "edgar_varese", + "gustav_hertz", + "americus_vespucius", + "acheson", + "george_mason", + "george_wallace", + "el_cid", + "andrei_voznesenski", + "quincy", + "borges", + "mosander", + "marcus_antonius", + "mazzini", + "schulz", + "otto_i", + "p_brigid", + "p_markus", + "alonso", + "sapir", + "torricelli", + "frank_cooper", + "de_quincey", + "t_h_white", + "sargent", + "agrippina", + "st_louis", + "richard_rodgers", + "karpov", + "soufflot", + "kleist", + "gogh", + "leeuwenhoek", + "anne_sexton", + "holmes", + "thomas_bradley", + "hogarth", + "kroto", + "john_dryden", + "jim_henson", + "friedrich_max_muller", + "kuznets", + "mercouri", + "furnivall", + "frank", + "saarinen", + "ernest_hemingway", + "burns", + "fiedler", + "voznesenski", + "markiisi_laplace", + "john_eccles", + "lech_walesa", + "von_neumann", + "george_westinghouse", + "constantin_brancusi", + "gaussi", + "richard_haldane", + "tourette", + "thomas_higginson", + "aquila", + "truffaut", + "fariseusmainen", + "brockhouse", + "jacques_charles", + "henrik_navarralainen", + "taideopettaja", + "eero_saarinen", + "pauli", + "arthur_miller", + "o'toole", + "henry_russell", + "napatanssija", + "john_cheever", + "friedrich_wilhelm_bessel", + "gracie_allen", + "john_bernoulli", + "billy_sunday", + "nelson_mandela", + "heinrich_himmler", + "al_gore", + "jacobs", + "farragut", + "john_rutledge", + "hans_bethe", + "hans_geiger", + "alle_normaalin_oleva", + "michinomiya_hirohito", + "nicklaus", + "gaius_octavianus", + "mandelbrot", + "ravintolaty\u00f6ntekij\u00e4", + "cesare_borgia", + "bluegrass_stater", + "woodbury", + "j_p_morgan", + "whittier", + "hampton", + "christopher_carson", + "loewi", + "wheatstone", + "swinburne", + "kerouac", + "kierkegaard", + "kutuzov", + "roald_amundsen", + "starkey", + "mossbauer", + "stephane_grappelli", + "nuohous", + "sherwood_anderson", + "andersen", + "richard_leakey", + "alfred_korzybski", + "c_a", + "anton", + "ledbetter", + "charles_dickens", + "verrazano", + "pershing", + "jean_chauvin", + "fairbanks", + "nicolas_malebranche", + "kirchhoff", + "delorme", + "maugham", + "e_o_lawrence", + "bellarmino", + "sean_o'casey", + "samuel_huntington", + "de_saussure", + "gesner", + "ella_fitzgerald", + "fats_waller", + "alfred_krupp", + "jakob_bernoulli", + "thomas_sydenham", + "bernoulli", + "jack_robinson", + "tatum", + "alois_senefelder", + "george_enescu", + "wallace_carothers", + "jacques_offenbach", + "anne_bronte", + "schweitzer", + "joseph_paxton", + "manzoni", + "seles", + "silverstein", + "louis_untermeyer", + "william_curtis", + "kennan", + "francisco_villa", + "macaulay", + "john_uhler", + "callas", + "tombaugh", + "lozier", + "bose", + "william_chambers", + "gilbert", + "ironsides", + "minnewit", + "leakey", + "fellini", + "bronislaw_malinowski", + "van_doren", + "von_mauser", + "tawney", + "hans_conrad_julius_reiter", + "george_stevens", + "federico_fellini", + "hru\u0161t\u0161ov", + "woolley", + "karl_linne", + "bessie_smith", + "bradley", + "bentham", + "jean_antoine_watteau", + "patrick_henry", + "carnot", + "honegger", + "willy_brandt", + "vestris", + "charles_wilkes", + "otto_lagerylainen", + "francisco_pizarro", + "francisco_franco", + "friedan", + "petteri", + "shelley", + "pes\u00e4k\u00e4yt\u00e4v\u00e4", + "katherine_cornell", + "jackie_robinson", + "maria_ii", + "montfort", + "bernardo_bertolucci", + "don_luchino_visconti_conte_di_modrone", + "stevenson", + "king_oliver", + "corday", + "charles_augustus_lindbergh", + "jan_steen", + "lichtenstein", + "frank_harris", + "e_e_cummings", + "john_ross", + "jaroslav_ha\u0161ek", + "ali_baba", + "cassius_longinus", + "powell", + "philibert_delorme", + "guevara", + "peabody", + "stevens", + "andrew_mellon", + "hans_arp", + "browne", + "andrew_carnegie", + "alcott", + "pontius_pilatus", + "weismann", + "halevy", + "posti\u00e4\u00e4nestys", + "majakovski", + "franz_schubert", + "william_butterfield", + "edward_d_white", + "howells", + "johnny_cash", + "vidal", + "joseph_mccarthy", + "wyler", + "pesim\u00e4alue", + "alfred_kastler", + "postilaitoksen_p\u00e4\u00e4johtaja", + "marduk", + "mick_jagger", + "warhol", + "otto_loewi", + "steinman", + "robinson", + "tom_bradley", + "don_marquis", + "charles_peirce", + "mandelstam", + "lasimestari", + "georges_cuvier", + "peter_seeger", + "ethelred_i", + "sessions", + "hemingway", + "william_harvey", + "walter_scott", + "wyat", + "h_j_eysenck", + "parkinson", + "francois_villon", + "charcot", + "august_von_wassermann", + "peter_medawar", + "paul_cezanne", + "jenner", + "werfel", + "stuyvesant", + "vladimir_lenin", + "sam_houston", + "fugard", + "dimaggio", + "robert_peary", + "rodgers", + "littre", + "zangwill", + "bartok", + "wilder", + "henry_steinway", + "kahlil_gibran", + "steiner", + "daguerre", + "robert_browning", + "seleukos", + "comenius", + "fr\u00f6bel", + "charles_kettering", + "mellon", + "alessandro_farnese", + "ralph_ellison", + "john_bunyan", + "jonathan_swift", + "franck", + "goebbels", + "rahmaninov", + "iglesias", + "walter_gropius", + "albert_einstein", + "l", + "henry_sweet", + "donizetti", + "vilhelm_occamilainen", + "robert_joffrey", + "william_shakspere", + "fritz_lipmann", + "aletta_jacobs", + "stubbs", + "thomas_edison", + "rasputin", + "benjamin_harris", + "beecher", + "claude_bernard", + "ailey", + "luonnontieteen_opettaja", + "raymond_chandler", + "charles_dodgson", + "henry_purcell", + "francis_hopkinson", + "trumbull", + "windaus", + "de_la_mare", + "ormuzd", + "ostwald", + "john_wickliffe", + "nixon", + "t", + "griffith", + "jean_francois_champollion", + "gainsborough", + "le_douanier_rousseau", + "thatcher", + "lemmon", + "cervantes", + "gonne", + "marley", + "witherspoon", + "wilhelm_ostwald" + ], + "ORG": [ + "raja_asutus", + "hinajana", + "dominion", + "ida", + "akvinolainen", + "heimoyhteiskunta", + "asiakohtaisesti", + "shinto", + "jesuiitat", + "eurooppa", + "perustuslakioikeus", + "jehovan_todistajat", + "yksikk\u00f6matriisi", + "tieteiskirjallisuus", + "balettiseurue", + "keilailuliiga", + "massadata", + "kirjankustantamo", + "ei_haittaa", + "kauppaministeri\u00f6", + "sheriffilaitos", + "doi", + "nimeni_on", + "tietokoneliike", + "tammany", + "rokkib\u00e4ndi", + "mormonit", + "r\u00e4ttikauppa", + "muurarius", + "j\u00e4senpankki", + "avolava", + "aseteollisuus", + "ensiluokkainen", + "san_jos\u00e9", + "agraaripuolue", + "kaupunginvaltuusto", + "gironde", + "ter\u00e4syhti\u00f6", + "drug_enforcement_administration", + "mist\u00e4_on_kysymys", + "oikeusministeri\u00f6", + "kannentiiviste", + "salakuljetustavaraan_liittyv\u00e4", + "wicca", + "dixiecrats", + "kompostikasa", + "p_nikolaos", + "an_education", + "p\u00e4iv\u00e4koulu", + "akselivaltiot", + "paul_cezanne", + "jan_mayen", + "musta_leski", + "sokeripuristin", + "postileikki", + "ins", + "kunnantalo", + "hansaliitto", + "puolustustoimi", + "sukkasaippua", + "nist", + "natsipuolue", + "shakers", + "rahoituskomitea", + "admiraltysaari", + "sukellusvenelaivue", + "balettikunta", + "l\u00e4\u00e4k\u00e4rikunta", + "ammattiryhm\u00e4", + "olla_omillaan", + "l\u00e4tt\u00e4hatut", + "andromedan_galaksi", + "kreivikunnanvaltuusto", + "loistoaika", + "shua", + "valinnanvapaus", + "\u00f6ljyteollisuus", + "kapetingit", + "halinallet", + "aa", + "homoavioliitto", + "mormonikirkko", + "nasa", + "koripallosarja", + "korkea_portti", + "ajoneuvoliikenne", + "s\u00e4\u00e4d\u00f6soikeus", + "brahmanismi", + "arda", + "federatiivinen_oikeuslaitos", + "myyntihenkil\u00f6st\u00f6", + "palestine_authority", + "hipit", + "isi", + "bollywood", + "pikkuliiga", + "puolustautuminen", + "ang", + "fema", + "normaalikoulu", + "varmuuskopioida", + "arkij\u00e4rki", + "lainausmerkeiss\u00e4", + "vallankaappaus", + "st_christopher", + "alaluokan", + "luokkarakenne", + "takamailla", + "kokousp\u00f6yt\u00e4", + "puutarhakutsut", + "huoltohenkil\u00f6st\u00f6", + "europol", + "schutzstaffel", + "maatalousministeri\u00f6", + "al_qanoon", + "elektroniikkateollisuus", + "u_s_army_special_forces", + "the_who", + "dippers", + "noususuhdanne", + "rotaryklubi", + "tienpintaheijastin", + "uusikuu", + "haganah", + "v\u00e4h\u00e4", + "uniaattikirkko", + "herraninkutsut", + "tietoyhteiskunta", + "t\u00e4t\u00e4_tarkoitusta_varten", + "h\u00e4rk\u00e4markkinat", + "tilitoimisto", + "beatnikit", + "lyseo", + "asiakohtainen", + "alasarja", + "toimitusketju", + "mainososasto", + "\u00f6ljyala", + "musiikkikoulu", + "porte", + "college", + "erikoisyksikk\u00f6", + "korkkarit", + "san_francisco", + "katedraalikoulu", + "fincen", + "voimayhti\u00f6", + "pikavippiyritys", + "miksei", + "siviilioikeus", + "exec", + "uhrilampaat", + "kaupallisuus", + "pullojenker\u00e4\u00e4minen", + "vishnulaisuus", + "perustuslakikokous", + "keltainenjoki", + "kampanjaryhm\u00e4", + "v\u00e4riskaala", + "johtokunta", + "kauppakamari", + "pyh\u00e4_nikolaus", + "lastikultti", + "el\u00e4inryhm\u00e4", + "poliittinen_oppositio", + "tennisklubi", + "golfmaila", + "mik\u00e4_h\u00e4t\u00e4n\u00e4", + "hallintotoimet", + "pyh\u00e4_andreas", + "nara", + "pelastusarmeija", + "pullokokoelma", + "helluntaikirkko", + "j\u00e4lkeen_kristuksen", + "verkkokalvorappeuma", + "hedgerahasto", + "va", + "kahlevangit", + "verkkoyritys", + "ravintolaketju", + "palolaitos", + "alempi_yhteiskuntaluokka", + "golfkerho", + "puuhevonen", + "olla_juonessa_mukana", + "postitoimisto", + "t\u00e4htijoukko", + "yksityisyritteli\u00e4isyys", + "kuusisataa", + "jalkapalloliiga", + "musiikkij\u00e4rjest\u00f6", + "sc", + "sissiarmeija", + "rahanvaihtopiste", + "militant_tendency", + "pikkuporvaristo", + "jesuiittaveljeskunta", + "iskuryhm\u00e4", + "joukkotiedotusv\u00e4lineet", + "church_of_christ_scientist", + "ymp\u00e4rist\u00f6puolue_vihre\u00e4t", + "sukupuolitutkimus", + "gao", + "paukkupurukumi", + "mestaruussarja", + "khalsa", + "radioyhti\u00f6", + "tehohoitoyksikk\u00f6", + "armeija", + "puutarhajuhla", + "dominikaanit", + "kamariorkesteri", + "vetoomustuomioistuin", + "kuolemanpartio", + "tasavaltalaiskaarti", + "dot", + "homoliitto", + "valuutanvaihtotoimisto", + "nanak", + "kuka_te_olette", + "tanssiyhtye", + "v\u00e4h\u00e4n_kerrassaan", + "huutokauppayhti\u00f6", + "l\u00e4\u00e4keteollisuus", + "core", + "alahuone", + "konservatiivinen_juutalaisuus", + "rivit", + "neli\u00f6matriisi", + "koordinoitu", + "moonilaisuus", + "yhteiskunnallis_taloudellinen", + "riskirahasto", + "pataljoona", + "merivalta", + "yhdysvaltojen_ilmavoimat", + "wiccalaisuus", + "painostusryhm\u00e4", + "punainen_risti", + "matkatoimisto", + "tietokoneteollisuus", + "saint_vincent", + "puolustusministeri\u00f6", + "sosiaalidemokraattinen_puolue", + "kuningasperhe", + "l\u00e4nsikulttuuri", + "ec", + "herrainkutsut", + "toimitusosasto", + "p\u00e4iv\u00e4vuoro", + "kommunistinen_puolue", + "john_tuzo_wilson", + "teamsters_union", + "mennoniittakirkko", + "muurausty\u00f6", + "saint_helena", + "plexus_celiacus", + "lentokoulu", + "don_juan", + "postimerkkikokoelma", + "sis\u00e4oppilaitos", + "s\u00e4ilymislaki", + "amishit", + "oni", + "the_new_school", + "pyh\u00e4koulu", + "tuskien_\u00e4iti", + "ai", + "alakoulu", + "\u0161iiamuslimit", + "kieltolakipuolue", + "kristillisdemokraatit", + "kristillisdemokraattinen", + "salaneuvosto", + "tietokonetomografi", + "suunnittelutoimikunta", + "asutus", + "poliisivaltio", + "merijalkav\u00e4ki", + "miksi_ei", + "ds", + "kierteisgalaksi", + "holdingyhti\u00f6", + "mustan_p\u00f6rssin", + "sy\u00f6p\u00e4kasvain", + "the_football_league", + "chiang_mai", + "soutukerho", + "vaateketju", + "vaalikomissio", + "muutoksenhakutuomioistuin", + "kastijako", + "iltakoulu", + "augustinolaisveljet", + "gop", + "hiilipohjainen", + "uudenkuun_vaihe", + "kaupungintalo", + "sao_paulo", + "augustinolaiset", + "dia", + "vierailup\u00e4iv\u00e4", + "miesvahvuus", + "kunnanhallitus", + "hallitustapa", + "asiakaspalveluosasto", + "metodistit", + "hyvinvointivaltio", + "t\u00e4m\u00e4n_t\u00e4st\u00e4", + "pihajuhla", + "lainvalmistelukunta", + "aherrus", + "skalaarikentt\u00e4", + "ilmaliikenne", + "yhdysvaltain_asevoimat", + "maalaisj\u00e4rki", + "kotiv\u00e4kivalta", + "afrikan_unioni", + "makuuhuonekalusto", + "republikaaninen_puolue", + "gatt", + "lablink", + "kissansilm\u00e4", + "postikonttori", + "jalankulkuliikenne", + "hallintoasiakirja", + "laivaus", + "sayeret", + "varusmiespalvelus", + "s\u00e4hk\u00f6yhti\u00f6", + "perustuslakituomioistuin", + "valitustuomioistuin", + "erityisbaptisti", + "yhdysvaltain_maavoimat", + "ei_en\u00e4\u00e4_ikin\u00e4", + "uudistusliike", + "ylempi_oikeusaste", + "rannikkojalkav\u00e4ki", + "sis\u00e4asiainministeri\u00f6", + "ammattiyhdistys", + "patenttitoimisto", + "sihteeriopisto", + "tietokonevalmistaja", + "retardoitunut", + "baskimaa", + "hallintoelin", + "le_mans", + "ihmisoikeustoimikunta", + "tiety\u00f6miesjoukko", + "vaisnavismi", + "maatalousv\u00e4est\u00f6", + "christian_science", + "silm\u00e4klinikka", + "lain_mukainen_erottelu", + "naruleikki", + "doe", + "caf\u00e9_au_lait", + "marionettihallitus", + "golfklubi", + "salaseura", + "kokoava", + "pretoriaanikaarti", + "donjuan", + "nukkehallitus", + "fletc", + "s\u00e4\u00e4ntelytoimisto", + "kunnallishallinto", + "t\u00e4ysk\u00e4si", + "puolustusvoimat", + "laittomat_markkinat", + "tanssiorkesteri", + "henkil\u00f6st\u00f6osasto", + "merivoimat", + "mounties", + "rauhanjoukot", + "sis\u00e4ministeri\u00f6", + "lakkovartio", + "rabindranath_tagore", + "gestapo", + "muotiala", + "albertinj\u00e4rvi", + "de_novo", + "nikolaos", + "reaalimatriisi", + "k\u00e4ymisalkoholi", + "maihinnousujuhlat", + "rikosmaailma", + "lains\u00e4\u00e4t\u00f6osasto", + "kashag", + "kultakausi", + "the_blood_brothers", + "eturivi", + "rivij\u00e4senet", + "baptistien_uskontokunta", + "iida", + "santa_sophia", + "salapoliisitoimisto", + "al_muhajiroun", + "kansainv\u00e4linen_oikeus", + "counterterrorist_center", + "toimeenpanovalta", + "kiinteist\u00f6sijoitusyhti\u00f6", + "suihkuseurapiiri", + "atomienergiakomissio", + "maametallimineraali", + "mainostoimisto", + "nostov\u00e4ki", + "punakaarti", + "lain_t\u00e4yt\u00e4nt\u00f6\u00f6npanoelin", + "australian_ty\u00f6v\u00e4enpuolue", + "tapahtumataulukko", + "kukkaiskansa", + "voimistelusali", + "\u0161into", + "kutsuntalautakunta", + "jalostusteollisuus", + "laivanrakennusteollisuus", + "konstanzin_kirkolliskokous", + "susilauma", + "kotiel\u00e4intarha", + "hiljalleen", + "kierteissumu", + "kokka", + "rivimiehet", + "v\u00e4risuora", + "kotirintama", + "peruskoulu", + "maquis", + "tenniskerho", + "leikkikaluteollisuus", + "toimeenpano_osasto", + "jenkkifutis", + "rajavastuuyhti\u00f6", + "punakaartilainen", + "the_young_turks", + "alemman_yhteiskuntaluokan", + "fibonaccin_sarja", + "viininmaistelu", + "virkamiehist\u00f6", + "masuuni", + "kohdeyhti\u00f6", + "alioikeus", + "sao_tome", + "who_are_you", + "meikata", + "oikeauskoisten_armeija", + "selvitysyhti\u00f6", + "pommiryhm\u00e4", + "maissitalkoot", + "musiikkiorganisaatio", + "siki\u00f6vaiheessa", + "puolijalokivi", + "kuka_sin\u00e4_olet", + "saint_joseph", + "sokkotreffit", + "al_jazeera", + "uinuva_mahdollisuus", + "hallitusmuoto", + "anabaptistit", + "kuvakehys", + "\u00f6ljym\u00e4ki", + "n\u00e4k\u00f6hermo", + "koulu", + "cum_laude", + "disa", + "aselaji", + "s\u00e3o_paulo", + "talletuslaitos", + "elektronikuori", + "militokratia", + "vammaisurheilu", + "po", + "lempi\u00e4", + "pekka_peukaloinen", + "hiiliteollisuus", + "aamut\u00e4hti", + "ty\u00f6ministeri\u00f6", + "ruohonjuuritaso", + "skalaarimatriisi", + "brahmalaisuus", + "alumiiniteollisuus", + "a_team", + "valitusinstanssi", + "musiikkiopisto", + "mossad", + "surmanhyppy", + "radiogalaksi", + "sukupuolitauti", + "valdolaiset", + "hare_krishna", + "hengelliset_lordit", + "ferdinand_magellan", + "hallintotoiminta", + "\u0161intolaisuus", + "drug_enforcement_agency", + "uskonnontutkimus", + "kirjeopisto", + "ala_aste", + "punainenmeri", + "linjaorganisaatio", + "herrarotu", + "karmeliittas\u00e4\u00e4nt\u00f6kunta", + "generaalibaptisti", + "dominikaaniveljeskunta", + "shaktismi", + "hollywood", + "vitaaliparametrit", + "p\u00e4iv\u00e4ss\u00e4", + "v\u00e4rv\u00e4ysjoukko", + "cid", + "hwang_ho", + "tehdaspalokunta", + "ursa_major", + "nicu", + "muotiyritys", + "p\u00e4\u00e4l\u00e4vist\u00e4j\u00e4", + "pullojenker\u00e4ys", + "rikostuomioistuin", + "ty\u00f6maalla", + "kurt_godel", + "lainakirjasto", + "diplomaattikunta", + "saint_barth\u00e9lemy", + "muutoksenhakuaste", + "sturmabteilung", + "etel\u00e4ossetialainen", + "vaishnavismi", + "julkishallinto", + "yhdysvaltain_ilmavoimat", + "kiert\u00e4j\u00e4nikama", + "sosialistinen_ty\u00f6v\u00e4enpuolue", + "who", + "makea_vesi", + "lionsklubi", + "markkinatalous", + "rahamarkkinat", + "muutoksenhakuinstanssi", + "los_angeles", + "nato", + "pyh\u00e4_barbara", + "poliisilaitos", + "kuolevuustaulu", + "baltimore_orioles", + "koripallojoukkue", + "ranskan_kansalliskokous", + "hallitseva_luokka", + "jesuiittaj\u00e4rjest\u00f6", + "hallitustoimet", + "sebaot", + "mineraalikunta", + "irokeesiliitto", + "j\u00e4\u00e4kiekkoliiga", + "ammattioppilaitos", + "elinkaarimalli", + "yhdysvaltain_whig_puolue", + "ad_hoc", + "po_joki", + "ammattiyhdistysliike", + "postivirasto", + "etel\u00e4inen_baptistikonventio", + "rajavartiosto", + "bussiliikenne", + "kuusipeuranaaras", + "roinat", + "sisuspunos", + "kustannuskonserni", + "mi", + "kaupunkivaltio", + "l\u00e4\u00e4keyritys", + "edistyspuolue", + "by_the_way", + "vanhakatolinen_kirkko", + "in_situ", + "dunkers", + "oranialaisveljeskunta", + "japanin_alahuone", + "mielisairaanhoitolaitos", + "st_francis", + "arabiliitto", + "sa", + "purjehduskerho", + "vaiheittain", + "talio_periaate", + "vaateteollisuus", + "bureau_of_justice_assistance", + "serbitasavalta", + "kiertoakseli", + "doc", + "caesalpinia_coriaria", + "suojelupoliisi", + "myyntiosasto", + "saksan_valtakunta", + "hallintoyksikk\u00f6", + "sosialistinen_puolue", + "laskumarkkina", + "rahoitusmarkkinat", + "ensimm\u00e4inen_nelj\u00e4nnes", + "st_john's", + "herrakutsut", + "urheilutoimitus", + "pikkuporvari", + "haarap\u00e4\u00e4sky", + "kolmas_osapuoli", + "poliisikoulu", + "huoltohallintoneuvosto", + "korkein_oikeus", + "al_ain", + "pakolaishallitus", + "huoltopoliisi", + "v\u00e4h\u00e4n_kerrallaan", + "karaiitit", + "huanghe", + "yangtze_kiang", + "bernhardinkoira", + "apostoli_andreas", + "ylemm\u00e4n_alaluokan", + "p_joosef", + "konservatiivipuolue", + "maryjane", + "verohallitus", + "ace", + "cat_skanneri", + "clematis_ochroleuca", + "aclant", + "yksityisoppilaitos", + "rosvovaltio", + "raakadata", + "paneelikeskustelu", + "aleksanteri_suuri", + "ylin_oikeusaste", + "reit", + "yhdysvaltain_hallitus", + "t\u00e4n\u00e4_y\u00f6n\u00e4", + "uudenvuodenaatto", + "kolikkokokoelma", + "pankkikonserni", + "n\u00e4k\u00f6juostevana", + "valkokulta", + "kulttuuriliike", + "\u00f6ljykartelli", + "eu", + "koulutuslaitos", + "uusi_kuu", + "vanhakaupunki", + "ajantasainen", + "toimeenpanovirasto", + "saksan_kansallissosialistinen_ty\u00f6v\u00e4enpuolue", + "uskontotiede", + "psykiatrinen_sairaala", + "naval_underwater_warfare_center", + "fransiskaaniveljeskunta", + "myrskyjoukot", + "ratsastuskoulu", + "hirundo_rustica", + "kielikoulu", + "metodistikirkko", + "haredi", + "musiikkiryhm\u00e4", + "pannub\u00e4ndi", + "shivalaisuus", + "henkil\u00f6st\u00f6nvuokraaja", + "house_of_lords", + "st_lucia", + "olla_mieltynyt", + "ter\u00e4steollisuus", + "guomindang", + "yhdysvaltojen_hallitus", + "saktismi", + "as_duuri", + "valvontatoimisto", + "yhdysvaltain_kansalliskaarti", + "s\u00e3o_tom\u00e9", + "tupakkateollisuus", + "yhdysvaltain_demokraattinen_puolue", + "bundesbank", + "poliisiopisto", + "kauppaoppilaitos", + "van_gogh", + "kirjanpitotoimisto", + "merisotakoulu", + "nukkevaltio", + "valitsijamiehist\u00f6", + "tautientorjuntakeskus" + ], + "ANIMAL": [ + "eskimokuiri", + "kingcharlesinspanieli", + "kes\u00e4kampela", + "kanadansuosopuli", + "alli", + "valkoh\u00e4nt\u00e4preerikko", + "saukko", + "kanarianhemppo", + "mustamarliini", + "euroopanmajava", + "pumpulih\u00e4nt\u00e4kaniini", + "isosilm\u00e4piikkimakrilli", + "lehm\u00e4haikara", + "kuusitiainen", + "acherontia", + "viittoilijarapu", + "apodemus", + "keltat\u00e4pl\u00e4inen", + "alligaattorilisko", + "puutiainen", + "viljakoi", + "afrikankultakissa", + "tulisalamanteri", + "enkelihai", + "matok\u00e4\u00e4rme", + "hevosmuurahainen", + "amerikaniibishaikara", + "australianarovana", + "laukonpeura", + "cat", + "australianpikkutiira", + "kannuskilpikonna", + "ruskosuohaukka", + "punahirvi", + "vuorikirvinen", + "cockeri", + "bordercollie", + "rakkolev\u00e4", + "rubiinityranni", + "valkoh\u00e4nt\u00e4peura", + "pilvihiirihaukka", + "kalpeakasvoinen", + "punanapsija", + "amerikantavi", + "koloradonkuoriainen", + "pohjanmerikarhu", + "buteo", + "l\u00e4nnenkotelokilpikonna", + "parainfluenssavirus", + "l\u00e4nnenkuningaslintu", + "omenak\u00e4\u00e4ri\u00e4inen", + "mustahaikara", + "labradorinnoutaja", + "iltavirkku", + "helmikana", + "huilupreeriaturpiaali", + "kiinanp\u00e4\u00e4st\u00e4ismaamyyr\u00e4", + "tonko", + "harmaatyranni", + "maitok\u00e4\u00e4rme", + "matelijaheimo", + "vesispanieli", + "suolalehtijalkainen", + "lehtit\u00e4i", + "ametistipython", + "bandicootrotta", + "valashai", + "kennokonna", + "muurariampiainen", + "harmaavalas", + "jokidelfiini", + "j\u00e4niksenmets\u00e4stys", + "keltalev\u00e4", + "englanninspringerspanieli", + "lintukoira", + "sillisiika", + "faaraomuurahainen", + "villih\u00e4rk\u00e4", + "ravihevonen", + "kymmenpiikki", + "russakka", + "marunakana", + "irlanninsetteri", + "ruostep\u00e4\u00e4sky", + "timanttikalkkarok\u00e4\u00e4rme", + "oranssikaviokuonoy\u00f6kk\u00f6", + "lehtoturpiaali", + "pernaruttobasilli", + "vuorigorilla", + "orvokkipeippo", + "bostoninterrieri", + "valkokulmanakkeli", + "siankuonoleikko", + "thomsoningaselli", + "tarhah\u00e4m\u00e4h\u00e4kki", + "kirsis\u00e4\u00e4ski", + "lymfosyyttikoriomeningiittivirus", + "amerikansepelkyyhky", + "lapasotka", + "kalliovilist\u00e4j\u00e4", + "sateenkaariahven", + "amerikanlehtokurppa", + "homo_sapiens_sapiens", + "putkikuono", + "mustarotta", + "iguaani", + "mustaselk\u00e4kampela", + "keltakurkkumesikko", + "pienikorvainen", + "simultaanitulkkaus", + "k\u00e4ytt\u00f6koira", + "junin_viirus", + "a_testudineus", + "englanninsetteri", + "salmo_gairdneri", + "amerikankaulushaikara", + "irlanninvesispanieli", + "ter\u00e4v\u00e4katseinen", + "pulmunen", + "mielikuvitusel\u00e4in", + "karkaju", + "t\u00e4htihai", + "kanadanmajava", + "osterinkuori", + "tarahumarasammakko", + "maasalamanteri", + "mongolianjirdi", + "pommikiit\u00e4j\u00e4inen", + "naurulokki", + "amatsoninmuurahainen", + "kanadantaskurotta", + "amerikansaukko", + "lehtokurppa", + "belgianpaimenkoira", + "mississippinalligaattori", + "kirjaskorpioni", + "villakilpikk\u00e4", + "venuksenvy\u00f6", + "ruokamerisiili", + "kirjekyyhkynen", + "etel\u00e4nisohylje", + "euroopanbiisoni", + "viljak\u00e4\u00e4rme", + "kondori", + "planktonlev\u00e4", + "karvajalkavampyyri", + "kirjolohi", + "nitraattibakteerit", + "heron", + "leip\u00e4kuoriainen", + "kruunuy\u00f6haikara", + "amerikanniittysirkku", + "valkosarvikuono", + "paholaisrausku", + "alligaattorikilpikonna", + "keltaper\u00e4kerttuli", + "karhunpentu", + "berninpaimenkoira", + "valkoreunainen", + "pelikaanilintu", + "harmaanapsija", + "pyy", + "sittisontiainen", + "amerikanvaris", + "id\u00e4nkirjolepink\u00e4inen", + "harmaaorava", + "ruskohyeena", + "amerikansirohaukka", + "wisconsilainen", + "riisilintu", + "korvahylje", + "mokkasiinik\u00e4\u00e4rme", + "ruostevahanokka", + "hedelm\u00e4puupunkki", + "hopeahapsinen", + "mustah\u00e4nt\u00e4peura", + "kauluskaija", + "savanninorsu", + "letitys", + "kylkiviiva", + "harmaaviklo", + "flanderinpaimenkoira", + "valkojalkahiiri", + "kimolepakko", + "myskikenguru", + "m\u00f6nki\u00e4inen", + "tornip\u00f6ll\u00f6", + "karvalakki", + "omenak\u00e4rp\u00e4nen", + "koirasalamanterit", + "noukkijalepakko", + "riisirotta", + "pajusirkku", + "orvokkihopeat\u00e4pl\u00e4", + "luhtahuitti", + "villamaki", + "rohmukuoriainen", + "kalliotamaani", + "lemmus_lemmus", + "fasaanikukaali", + "sitta_europaea", + "nokkosperhonen", + "niittymyyr\u00e4", + "tappajavalas", + "t\u00e4htikotkarausku", + "lierok\u00e4\u00e4rme", + "uma_notata", + "viiri\u00e4ispyyjuoksija", + "punap\u00e4\u00e4tikka", + "kapintamaani", + "sumeri", + "kafferipuhveli", + "billy_elliot", + "kanahaukka", + "viinik\u00e4\u00e4rme", + "lasisieni", + "valtamerilintu", + "hietakielikampela", + "kraitti", + "medinamato", + "sarvikyy", + "kujakissa", + "mustamamba", + "amerikanpikkuhaikara", + "bullfinch", + "j\u00e4rvitaimen", + "kidushait", + "kokosukeltajasorsat", + "per\u00e4kk\u00e4istulkkaus", + "afrikankynsisammakko", + "etikkak\u00e4rp\u00e4nen", + "mustajalkahilleri", + "lasivaskitsa", + "tamminopsasiipi", + "harmaalokki", + "euroopanbrahmakehr\u00e4\u00e4j\u00e4", + "sateenkaarirautu", + "beletti", + "riisirattu", + "kirkup\u00f6ll\u00f6", + "lintuhaukat", + "tummakvolli", + "japaninosteri", + "bakteeriperhe", + "karakullakaritsa", + "kolibakteeri", + "mustajuovainen", + "isotrappi", + "harjasusi", + "ruusukottarainen", + "h\u00e4rk\u00e4k\u00e4\u00e4rme", + "ketosirkkuli", + "mustah\u00e4nt\u00e4preeriakoira", + "kleopatrankobra", + "matelijasuku", + "japaninmakrilli", + "canis_minor", + "jauhokoisa", + "sateenkaariharppoja", + "burmant\u00e4htikilpikonna", + "beringinhanhi", + "id\u00e4nkulkusirkka", + "sireeniel\u00e4in", + "kiekua", + "pyh\u00e4iibis", + "maakotka", + "luukala", + "hippotragus_niger", + "mustahauki", + "kardinaalitetra", + "sitta_carolinensis", + "frankliniella_fusca", + "harmaavahanokka", + "badger", + "punasusi", + "savannikoira", + "tornip\u00f6ll\u00f6t", + "vuoriseepra", + "kahlaajalintu", + "j\u00e4ykk\u00e4per\u00e4inen", + "ranskanbulldoggi", + "teeri", + "tammitangara", + "clydesdalenterrieri", + "huilutylli", + "sahelinvahanokka", + "sieppop\u00f6ll\u00f6", + "euroopanhummeri", + "kirjohylje", + "valkokurkkusirkku", + "aku_ankka", + "norwichinterrieri", + "vesiel\u00e4in", + "kemppi", + "louhikkok\u00e4\u00e4rme", + "aasiankukaali", + "pisces", + "lehtikuonok\u00e4\u00e4rme", + "hevospiikkimakrilli", + "puusalamanteri", + "kiekuminen", + "kasvivirus", + "k\u00e4til\u00f6sammakko", + "puutarhajuoksiainen", + "kuhankeitt\u00e4j\u00e4", + "lampaant\u00e4ik\u00e4rp\u00e4nen", + "keltaraitainen", + "tupakkaripsi\u00e4inen", + "piranga_olivacea", + "alppipikkulepakko", + "vuoriskinkki", + "teksasinkalkarok\u00e4\u00e4rme", + "maitovalas", + "punamyyr\u00e4", + "partahylkeet", + "davidinhirvi", + "felis_tigrina", + "isolunni", + "punarummuttaja", + "punatyranni", + "tiaiskerttuli", + "afrikanpuhveli", + "amerikann\u00e4\u00e4t\u00e4", + "niittykirvinen", + "riisipeippo", + "hietak\u00e4\u00e4rme", + "vaatekoi", + "swift", + "niveljalkainen", + "vanhaenglanninlammaskoira", + "sointumuura", + "t\u00f6rm\u00e4p\u00e4\u00e4sky", + "mongoliangerbiili", + "kitasampi", + "punatulkku", + "rupikonna", + "harjakoskelo", + "harmaanieri\u00e4", + "hanhikorppikotka", + "andienkondori", + "ruostesirppimatkija", + "kylki\u00e4islisko", + "hernekerttu", + "it\u00e4kanadansusi", + "rotanpuremakuumebakteeri", + "kunelude", + "amerikanhaapana", + "hirviel\u00e4in", + "tarhak\u00e4\u00e4rme", + "mustakaulakobra", + "burmankissa", + "sarvisisilisko", + "maamyyr\u00e4sirkka", + "lactobacillus_acidophilus", + "sussexinspanieli", + "shetlanninlammaskoira", + "amerikanliitohaukka", + "hopeahiuksinen", + "leijonanpentu", + "piikkimakrilli", + "amerikanpitk\u00e4jalka", + "luhtakana", + "sarviromisko", + "pumpulipeurahiiri", + "dandiedinmontinterrieri", + "stellerinmerileijona", + "pullonokkadelfiini", + "amerikanbiisoni", + "marhet", + "kalliok\u00e4\u00e4rme", + "riisimaina", + "walesinspringerspanieli", + "banaanik\u00e4rp\u00e4nen", + "leptodactylid", + "amerikankoskikara", + "helttasorsa", + "kelop\u00e4\u00e4sky", + "sundankalahuuhkaja", + "ristih\u00e4m\u00e4h\u00e4kki", + "satamarotta", + "lintuhyttynen", + "verkkopyton", + "skorpionilisko", + "pieris_brassicae", + "p\u00e4\u00e4si\u00e4ispupu", + "afrikanvilliaasi", + "perunakoi", + "mantisravut", + "aitosiipat", + "panssarisimput", + "harmaakuvemyyr\u00e4", + "sukkela", + "jumaltenpuukehr\u00e4\u00e4j\u00e4", + "mattopyton", + "partahaikalat", + "tulitikli", + "meksikonaavikkokettu", + "skilletfish", + "crow", + "amerikanviirup\u00f6ll\u00f6", + "hietakiit\u00e4j\u00e4inen", + "punasilm\u00e4vireo", + "joutsenhanhi", + "suippohuulisarvikuono", + "borneonoranki", + "villasarvikuono", + "kivin\u00e4\u00e4t\u00e4", + "punalepakko", + "obinsopuli", + "rautio", + "kurnusimppu", + "supikoira", + "teksasinkalkkarok\u00e4\u00e4rme", + "iberianilves", + "ruskeakarhu", + "alppisalamanteri", + "pienihampainen", + "valkoposkihanhi", + "hopeaturska", + "sahiainen", + "electrophorus_electric", + "paratiisikaija", + "kotihiiri", + "amerikanpuukiipij\u00e4", + "sukeltajasorsa", + "ruostehiirihaukka", + "rohtop\u00e4hk\u00e4m\u00f6", + "kuori\u00e4yri\u00e4inen", + "kolmivarvaslaiskiaiset", + "somalianvilliaasi", + "kaliforniankondori", + "etel\u00e4nkultaper\u00e4", + "sotakiihkoilija", + "micropterus", + "tammih\u00e4rk\u00e4", + "satiinilavastaja", + "fratercula_arctica", + "amerikanpeltomyyr\u00e4", + "j\u00e4\u00e4pingviini", + "karkeakarvainen_kettuterrieri", + "martes_martes", + "sarapeukaloinen", + "minkki", + "unikeot", + "hirssivahanokka", + "villiminkki", + "satiainen", + "jyv\u00e4koi", + "wiesel", + "perca_flavescens", + "c_diphtheriae", + "mustajoutsen", + "sorsalintu", + "afrikannorsu", + "sierramadrentikka", + "kampasarvinen", + "machesterterrieri", + "matoperhe", + "villamammutti", + "hermissenda", + "lama_peruana", + "suurriista", + "helmikananliha", + "etel\u00e4nbastardikilpikonna", + "paksunokkainen", + "palsasirri", + "amerikanhummeri", + "beringinmerimetso", + "makaira_mazara", + "salmonella_enteritidis", + "maasiira", + "raven", + "valkoh\u00e4nt\u00e4orava", + "lankalev\u00e4t", + "id\u00e4nnaakka", + "karjarotu", + "erakkorastas", + "homo_sapiens", + "valkoh\u00e4nt\u00e4kauris", + "amerikanhauki", + "manchesterinterrieri", + "vaikertajakyyhky", + "puistotiainen", + "marhi", + "tummajunkko", + "valkopilkkahai", + "vuorimajava", + "amerikanohdakeperhonen", + "kentt\u00e4sirkkuli", + "ka\u0161mirvuohi", + "ampiaissy\u00f6j\u00e4", + "amerikanp\u00e4\u00e4sky", + "tarhaturpiaali", + "seitivalas", + "kakominen", + "minervanp\u00f6ll\u00f6", + "hedelm\u00e4k\u00e4rp\u00e4nen", + "mustan\u00e4\u00e4t\u00e4", + "harrier", + "ilves", + "harlekiinipeippo", + "pohjankiisla", + "amerikannokikana", + "harmaakuukkeli", + "kulmaritariy\u00f6kk\u00f6nen", + "kirjosaku", + "kehr\u00e4\u00e4j\u00e4punkki", + "satamarosvo", + "ebola_virus", + "kidushai", + "dikidiki", + "norfolkinterrieri", + "syyhypunkki", + "pohjoisenpullonokkavalas", + "kalasuku", + "punaviidakkokana", + "ai_ai", + "nitraattibakteeri", + "hidaslori", + "lampaannen\u00e4nsaivartaja", + "harmaamurmeli", + "tetranychid", + "tukkakoskelo", + "sulttaanikana", + "trumpettikurki", + "kaliforniantimali", + "lahtivalas", + "nelivarvaskilpikonna", + "tunturisopuli", + "islannintelkk\u00e4", + "munkkikorppikotka", + "pallop\u00e4\u00e4valas", + "ponnahdella", + "gr\u00f6nlanninhylje", + "australianmerileijona", + "marmotini", + "indigok\u00e4\u00e4rme", + "hattumakaki", + "kettuorava", + "patagoniannandu", + "ylikersanttikala", + "sagriinikotilo", + "nokkasaukko", + "rusakko", + "amerikankantasilli", + "cyanophyceae", + "alko", + "ei_varpuslintu", + "pumpulipeurahiiru", + "kanadanilves", + "selk\u00e4j\u00e4nteisheimo", + "punareunainen", + "vesimyyr\u00e4", + "viiksihai", + "oranssiharjakotinga", + "riuttatiira", + "majava", + "gordoninsetteri", + "haarap\u00e4\u00e4sky", + "karvahattu", + "amerikankaniini", + "lyhtysilm\u00e4", + "sitruunahai", + "caligidae", + "prunus_tenella", + "lehtop\u00f6ll\u00f6", + "karmiinikirva", + "keltakuumehyttynen", + "kalliomerisiili", + "lavantautibakteeri", + "amerikanbassi", + "englanninvinttikoira", + "h\u00e4m\u00e4h\u00e4kkijuoksiainen", + "tarhatyranni", + "mormonisirkka", + "majavannahka", + "yhteiskuntahy\u00f6nteinen", + "muurarimehil\u00e4inen", + "viinim\u00e4kikotilo", + "kuormajuhta", + "purjemarliini", + "amerikanviklo", + "kiljukotka", + "tammipunavarpunen", + "s\u00e4dehohtaja", + "taivaanvuohi", + "cro_magnon", + "kantojuhta", + "rissondelfiini", + "yorkshirenterrieri", + "bakteerilajit", + "kaislikkokissa", + "monarkkiperhonen", + "lamantiini", + "suomuh\u00e4nt\u00e4inen", + "paperivene", + "punamahlatikka", + "accipiter", + "h\u00e4m\u00e4h\u00e4kkijuoksijainen", + "hanhenkaula", + "amerikankettukoira", + "vesikoira", + "ripsujalkaleguaani", + "takaraaja", + "cockerspanieli", + "kerrynterrieri", + "poliisikoira", + "etel\u00e4nkiisla", + "amerikannakkeli", + "mississipink\u00e4ki", + "kirppa", + "kolmikorvainen", + "lehtikuoriainen", + "harjakotingat", + "variola_minor_virus", + "atollilenkko", + "sotilasmestari", + "ansarijauhiainen", + "adjutanttihaikara", + "persiankissa", + "mustapalkkinen", + "niveljalkaiset", + "greyhound", + "sealyhaminterrieri", + "myrkkylisko", + "viidakkokissa", + "k\u00e4rs\u00e4kunkki", + "sakke", + "kuulokoira", + "komodonvaraani", + "suokaniini", + "pihapeukaloinen", + "kissakettu", + "ratamoverkkoperhonen", + "yliv\u00e4\u00e4peli", + "rengash\u00e4nt\u00e4leguaani", + "ruokokerttunen", + "stieglitz", + "tasankokengururotta", + "d_klorofylli", + "ruskuaispussi", + "kielikampela", + "kiinanalligaattori", + "chesapeakelahdennoutaja", + "kermodekarhu", + "loistohammaskarppi", + "valkolaikkuinen", + "m\u00e4nnikk\u00f6kehr\u00e4\u00e4j\u00e4", + "pilkkupiikkimonni", + "liemikilpikonna", + "salmonellabakteeri", + "tervap\u00e4\u00e4sky", + "bengalintiikeri", + "valkop\u00e4\u00e4merikotka", + "amerikanvesispanieli", + "vatsaev\u00e4", + "variola_minor", + "vetohevonen", + "kauluskarhu", + "lehtisammakko", + "savanniseepra", + "juoruakka", + "naurisperhonen", + "h\u00e4rk\u00e4hai", + "punakoralli", + "snake_polypody", + "kettuterrieri", + "karolinananolis", + "sipuliripsi\u00e4inen", + "taviokuurna", + "spermofiili", + "rusoposkikerttuli", + "lehtinunna", + "hevosk\u00e4rp\u00e4nen", + "porsasskunkki", + "marburg_virus", + "isoleikko", + "isopussikaniini", + "thomomys_talpoides", + "cro_magnonin_ihminen", + "jalokoralli", + "rottak\u00e4\u00e4rme", + "villisorsa", + "punaorava", + "c_trachomatis", + "walesinterrieri", + "kirjekyyhky", + "reesusmakaki", + "villiaasi", + "skotlanninterrieri", + "mustapilkkahai", + "jalohaikara", + "wren", + "musta_mehil\u00e4inen", + "aisahevonen", + "aroseepra", + "partahai", + "eskimokuovi", + "tylpp\u00e4kuonokarhu", + "ruutana", + "punanflamingo", + "kanadanpyy", + "hepatiitti_a_virus", + "hopealokki", + "tikkalintu", + "sarvikuonokas", + "alkueli\u00f6suku", + "karhunpoikanen", + "kapeakuonokrokotiili", + "valkohai", + "mustaimukarppi", + "etel\u00e4amerikanhyypp\u00e4", + "selk\u00e4ev\u00e4", + "mustapiikkimonni", + "pinctada_margaritifera", + "jallittaa", + "lehtihy\u00f6nteinen", + "australianpitk\u00e4jalka", + "hein\u00e4kurppa", + "sukkanauhak\u00e4\u00e4rme", + "stellerinmerilehm\u00e4", + "tasankotaskurotta", + "villaindri", + "partasuu", + "irlanninterrieri", + "potamophis_striatula", + "erakkorapu", + "tarhamehil\u00e4inen", + "korppi", + "roskakala", + "villisika", + "langustiini", + "silm\u00e4kekalkkuna", + "amerikanhiirihaukka", + "filippiinienkummitusel\u00e4in", + "sinettik\u00e4\u00e4rme", + "salmo_salar", + "irlanninsammal", + "saksanpaimenkoira", + "suistokrokotiili", + "norsulintu", + "punastunut", + "sanicula_europaea", + "etel\u00e4nkeiju", + "filippiinienkummittelija", + "adelie", + "harakka", + "ristilukki", + "korihai", + "h\u00e4nt\u00e4sammakko", + "iller", + "turkiskoi", + "hietakissa", + "hietakurki", + "palmukyyhky", + "maay\u00f6kk\u00f6nen", + "ilmarakko", + "kellosammakko", + "nykyihminen", + "puuleopardi", + "punarumpukala", + "australiankeuhkokala", + "keltainen_lippu", + "punaselk\u00e4sopuli", + "sillivalas", + "kierteish\u00e4nt\u00e4apina", + "varjokotinga", + "vesipeto", + "perunarupibakteeri", + "kaliforniantupsuviiri\u00e4inen", + "saunamaija", + "coho_salmon", + "partahylje", + "villikaniini", + "kondorikotka", + "ter\u00e4v\u00e4nen\u00e4inen", + "maamyyr\u00e4rotta", + "pihkatikka", + "amerikanhakki", + "takajalka", + "parrynsiiseli", + "mustalepp\u00e4lintu", + "h_nasicus", + "kes\u00e4tangara", + "corallium_rubrum", + "niittytyranni", + "kulkuy\u00f6kk\u00f6nen", + "amerikantikli", + "el\u00e4invirus", + "mandariinisorsa", + "hirvas", + "isolehtikuonolepakko", + "harmaarotta", + "liitokala", + "koirasalamanteri", + "martes_foina", + "amerikantaivaanvuohi", + "australiantorakka", + "amerikanhuuhkaja", + "ruovikkokissa", + "maissikoisa", + "amerikanharmaahaikara", + "perunavirus", + "saparomakaki", + "l_monocytogenes", + "mustahevosantilooppi", + "lentosulka", + "ictiobus_niger", + "floridanhylje", + "tammitiainen", + "siipikarjanliha", + "koiralohi", + "puliveivata", + "amerikanisolepink\u00e4inen", + "t\u00e4htikuonokontiainen", + "capreolus_capreolus", + "kivikkopyy", + "valkoh\u00e4nt\u00e4j\u00e4nis", + "hyypp\u00e4", + "bombyx", + "l\u00e4nnenharmaaorava", + "kuusipeura", + "myskisorsa", + "pihapunavarpunen", + "mustanokkak\u00e4ki", + "kuormael\u00e4in", + "branta_bernicla", + "kissakarhu", + "harmaakettu", + "kilpikirva", + "andienflamingo", + "naaraskissa", + "rantak\u00e4\u00e4rme", + "kiinantammisilkkikehr\u00e4\u00e4j\u00e4", + "tuberkuloosibakteeri", + "punaselk\u00e4salamanteri", + "vuorinjala", + "herpes_zoster", + "cavia_cobaya", + "piekana", + "hetulavalas", + "id\u00e4nkyl\u00e4p\u00f6ll\u00f6nen", + "villihanhi", + "forelli", + "verivampyyri", + "perhoskala", + "susih\u00e4m\u00e4h\u00e4kki", + "beaver", + "vuorikauris", + "parivarpainen", + "mahonia_aquifolium", + "id\u00e4nkentt\u00e4myyr\u00e4", + "ruusukapustahaikara", + "kausiesiintym\u00e4kaskas", + "kalliomeriahven", + "suursnautseri", + "amerikankultasiipi", + "sitti\u00e4inen", + "przewalskinhevonen", + "kalatiira", + "panssaridinosaurus", + "amerikanviherrupisammakko", + "jalohaukka", + "springerspanieli", + "amerikannokkavarpunen", + "hopeaviist\u00e4j\u00e4", + "italianvinttikoira", + "sirvik\u00e4s", + "siivet\u00f6nruokki", + "hermostoputki", + "kalliopeukaloinen", + "etel\u00e4nmerinorsu", + "sammakko", + "afrikanpingviini", + "kuplahylje", + "ruostekampela", + "valeskorpioni", + "pagellus_centrodontus", + "saukonnahka", + "silm\u00e4lasivireo", + "jaakonsiilik\u00e4s", + "punat\u00e4pl\u00e4vesilisko", + "helmivene", + "tuliharjakotinga", + "meksikonkengururotta", + "kiilavuokkokala", + "mustah\u00e4nt\u00e4j\u00e4nis", + "mustarastas", + "postihevonen", + "pensasn\u00e4rhi", + "niilin_kissakala", + "scleropages", + "irlanninsusikoira", + "jouhihietakyyhky", + "lehm\u00e4rausku", + "kaislasirkku", + "kyl\u00e4p\u00f6ll\u00f6nen", + "lapinharakka", + "valkosampi", + "sirovarpushaukka", + "maakiit\u00e4j\u00e4inen", + "mongolianhyppymyyr\u00e4", + "ydinsukellusvene", + "sokeritorakka", + "myksoomavirus", + "pehme\u00e4turkkinen_vehn\u00e4terrieri", + "rubiinihippi\u00e4inen", + "mattokuoriainen", + "isorokko_virus", + "harmaap\u00e4\u00e4kerttuli", + "liekkitikkanen", + "bedlingtoninterrieri", + "karettikilpikonna", + "borneonkissa", + "shastanluolasalamanteri", + "selk\u00e4j\u00e4nteissuku", + "peltolude", + "lychnis_flos_cuculi", + "tortrix", + "eskimokoira", + "hemipteron", + "amerikanpelikaani", + "amerikantuulihaukka", + "vesimokkasiinik\u00e4\u00e4rme", + "lapinp\u00f6ll\u00f6", + "kissamaki", + "tanskandoggi", + "pilkkusilli", + "gr\u00f6nlanninvalas", + "bengalinkissa", + "etel\u00e4nseepra", + "saukkop\u00e4\u00e4st\u00e4inen", + "vuoripaca", + "kuparisorsa", + "nen\u00e4apina", + "sumuhai", + "vaharauhanen", + "rengash\u00e4nt\u00e4maki", + "harmaaisokenguru", + "lakelandinterrieri", + "karhukehr\u00e4\u00e4j\u00e4", + "tapettikoi", + "amerikanpiippa", + "besoaarivuohi", + "sile\u00e4karvainennoutaja", + "aldabranj\u00e4ttil\u00e4iskilpikonna", + "kanalintu", + "rukoilijasirkka", + "sitta_canadensis", + "sormiel\u00e4in", + "morsiosorsa", + "amerikansipi", + "savannikotka", + "lenkko", + "primula_vulgaris", + "kalliovuortenpuromyyr\u00e4", + "amerikanvesip\u00e4\u00e4sky", + "reunuskilpikonna", + "makohai", + "wound_tumor_virus", + "amerikansirri", + "punakaulagaselli", + "petolintu", + "floridankalkkarok\u00e4\u00e4rme", + "puusisilisko", + "k\u00e4rpp\u00e4hai", + "herpes_zoster_virus", + "kauluspekari", + "islanninsilli", + "varicella_zoster_virus", + "puunkaivaja", + "herpes_simplex_1", + "karibianhylje", + "murrikka", + "loistokerttuli", + "vaunuhevonen", + "kirvinen", + "ailanthuskehr\u00e4\u00e4j\u00e4", + "paksunokkauikku", + "sipulit\u00e4i", + "sonorankultatikka", + "maksamato", + "viitatiainen", + "hietahai", + "siipisulka", + "vaaksiaiset", + "h_pylori", + "purotaimen", + "kotkarausku", + "shetlanninponi", + "kirkup\u00f6ll\u00f6nen", + "p\u00e4hkin\u00e4hiiri", + "amerikantilhi", + "santa_gertrudis", + "punakottarainen", + "lehtikirva", + "whippet", + "tarharastas", + "paksuhuulinen", + "mongolianvillihevonen", + "lavatera_arborea", + "kehr\u00e4\u00e4j\u00e4lintu", + "varvasastuja", + "h\u00e4nn\u00e4t\u00f6ntanrekki", + "sitruunakerttuli", + "kreikankilpikonna", + "vesirotta", + "valkoraitainen", + "niittysuohaukka", + "harmaasusi", + "rottaterrieri", + "valkoselk\u00e4skunkki", + "australianpyh\u00e4iibis", + "salvelinus_fontinalis", + "seeprapeippo", + "hevosen_p\u00e4\u00e4ntauti", + "peurapunkki", + "barramundi", + "maskareenienkaija", + "mustakaulauikku", + "micropetrus", + "walesinponi", + "ahdassuusammakko", + "amerikanstaffordshirenterrieri", + "setritilhi", + "sienikoralli", + "amerikantelkk\u00e4", + "id\u00e4nlehtoturpiaali", + "kanadanloikka", + "riisik\u00e4rs\u00e4k\u00e4s", + "amerikanh\u00f6m\u00f6tiainen", + "eagle", + "abudefduf_saxatilis", + "aasianvillihevonen", + "leprabakteeri", + "kilpikonnankuori", + "poronliha", + "l\u00e4nnenpiivi", + "lemmini", + "kev\u00e4tkurnuttaja", + "amerikantorakka", + "kaukasianteeri", + "vesipuhveli", + "remilegia_australis", + "kaskelotti", + "amerikanpohjanlepakko", + "harmaapapukaija", + "alkueli\u00f6heimo", + "sonoransiippa", + "p\u00e4hkin\u00e4nakkeli", + "helmirintamuura", + "patagonianmerileijona", + "isoputkikuono", + "constrictor_constrictor", + "torakka", + "gorilla_gorilla", + "kasmirvuohi", + "eskimohanhi", + "ruutuk\u00e4rp\u00e4nen", + "punaolkaturpiaali", + "faraomuurahainen", + "persiaaninahka", + "afrikanlepink\u00e4inen", + "avomerilintu", + "mustakondori", + "kissael\u00e4in", + "kalifornianmerileijona", + "sambarhirvi", + "omenakirva", + "grevynseepra", + "shad", + "mustakarhu", + "turpiaali", + "broilerinliha", + "maalaiskiaiset", + "chelydra", + "haarapyrst\u00f6inen", + "visentti", + "mustapilkkuahven", + "martes_zibellina", + "siank\u00e4rs\u00e4k\u00e4\u00e4rme", + "vaatet\u00e4i", + "kyl\u00e4n\u00e4\u00e4t\u00e4", + "vahvanokkainen", + "peltoviiri\u00e4inen", + "kaljumyyrikk\u00f6", + "kuusamaperhonen", + "maissikoi", + "kaaliperhonen", + "lavantautisalmonellat", + "kalaheimo", + "vaatekoit", + "sheltti", + "huulikarhu", + "l\u00e4nsi_niilin_enkefaliitti_virus", + "myskihirvi", + "mustamuurahainen", + "kanelisaniainen", + "galapagosinmerimetso", + "kanadankuukkeli", + "punasiipi", + "rintaev\u00e4", + "h\u00e4rk\u00e4lintu", + "keltajalkaviklo", + "teksasinkerttuli", + "australianterrieri", + "kirjohanhi", + "hunajamehil\u00e4inen", + "kiinank\u00e4\u00e4pi\u00f6tulilisko", + "berberiapina", + "chilensarda", + "kissakirppu", + "kanadankerttuli", + "helmisimpukka", + "eider", + "h\u00e4m\u00e4h\u00e4kkiapina", + "amerikanisokoskelo", + "adjutanttilintu", + "piikkirausku", + "samettipunkki", + "korppikotka", + "oregonilainen", + "punalakkipipilo", + "staffordshirenterrieri", + "keltaviherlev\u00e4", + "l\u00e4tt\u00e4nen\u00e4inen", + "c_klorofylli", + "harmaamarmotti", + "kalkkunakondori", + "kalkkunakukko" + ], + "LAW": [ + "kansalaisvapaus", + "ristikuulustelu", + "kansalaisoikeus", + "vaalioikeus", + "maanpetostuomio", + "hylk\u00e4ysp\u00e4\u00e4t\u00f6s", + "lains\u00e4\u00e4t\u00e4minen", + "tietokantahallinnoija", + "liittovaltion_vetoomustuomioistuin", + "siviilis\u00e4\u00e4ty", + "sijoittajasuhteet", + "k\u00f6yh\u00e4inhoitolaki", + "indiisit", + "lain_harjoittaminen", + "tuloilmoitus", + "laillisuusperiaate", + "sukupuolirikos", + "seksuaalirikos", + "yhteiskanne", + "lain_t\u00e4yt\u00e4nt\u00f6\u00f6npano", + "in_personam_tuomio", + "\u00e4\u00e4nestysj\u00e4rjestelm\u00e4", + "yhteisp\u00e4\u00e4t\u00f6s", + "kruununjuristi", + "laivakirja", + "bja", + "kartellilaki", + "syntym\u00e4maaperiaate", + "kokoontumisvapaus", + "johdannaisinstrumentti", + "kilpailulains\u00e4\u00e4d\u00e4nt\u00f6", + "puolustusasianajaja", + "kauppakirja", + "siviilioikeus", + "seksirikos", + "lain_toimeenpano", + "tulostase", + "lain_mukainen_vahingonkorvaus", + "v\u00e4est\u00f6rekisteri", + "asumuserop\u00e4\u00e4t\u00f6s", + "roomalainen_oikeus", + "perinn\u00e4istavat", + "piirisyytt\u00e4j\u00e4", + "kilpailunrajoitussopimus", + "murhatuomio", + "valtakunnansyytt\u00e4j\u00e4", + "merenkulkuoikeus", + "ty\u00f6turvallisuuslaki", + "ilmaisunvapaus", + "puhevapaus", + "\u00e4\u00e4nivalta", + "syyteoikeus", + "asianajajakunta", + "merioikeus", + "verolaki", + "nuorisorikollisuus", + "jus_civile", + "ne_bis_in_idem", + "sotalaki", + "asianajotoimisto", + "kuolemantuomio", + "merilaki", + "hyvityssakko", + "oikeuksien_julistus", + "hallintolaki", + "painovapaus", + "yritysjuridiikka", + "syntyper\u00e4periaate", + "avioerojuristi", + "arvopaperilaki", + "poliisituomioistuin", + "vaalitapa", + "sananvapaus", + "hoitotestamentti", + "kauppapaperi", + "aihetodisteet", + "virantoimitus", + "kauppaoikeus", + "raiskaustuomio", + "hoitotahto", + "lainvalvonta", + "verotusj\u00e4rjestelm\u00e4", + "sotatilalaki", + "kotietsint\u00e4lupa", + "lehdist\u00f6nvapaus", + "julkisoikeus", + "asetuskokoelma" + ], + "LOCATION": [ + "partaalla", + "al_jazeera", + "la_plata", + "uusivuosi", + "mielisairaanhoitolaitos", + "musiikkiopisto", + "plantago_lanceolata", + "st_eustatius", + "katkoa", + "selvagenssaaret", + "kulisseissa", + "silt\u00e4_varalta", + "orsz\u00e1ggy\u00fcl\u00e9s", + "trifolium_pratense", + "so_what", + "deuteriumoksidi", + "tiikeriveljekset", + "keskikaupunki", + "raskasvesi", + "rapanui", + "amerikan_manner", + "vespucci", + "omenapuutarha", + "huvittelukeskus", + "kaupunginmuuri", + "park", + "yhdyskuntatekniikka", + "eryngium_maritimum", + "ylip\u00e4\u00e4t\u00e4ns\u00e4", + "liikuntakasvatus", + "isokarpalo", + "corpus_christi", + "kolmikolkkainen", + "u.s", + "liikenneympyr\u00e4", + "sis\u00e4kentt\u00e4", + "kap_verde", + "kantakaupunki", + "bow_wow", + "krikettimaila", + "tenniskentt\u00e4", + "olla_ulkovuorossa", + "laivakanava", + "viljap\u00f6rssi", + "osteris\u00e4rkk\u00e4", + "keisarinkanava", + "s_tog", + "hoitokoti", + "juarez", + "p\u00e4\u00e4skysenpes\u00e4", + "piet_mondrian", + "loppupiste", + "punainenjoki", + "trifolium_repens", + "santa_fe", + "sint_maarten", + "yhdysvallat", + "\u00f6ljym\u00e4ki", + "petasites_hybridus", + "musiikkikoulu", + "keltainenjoki", + "centennial_state", + "toriaukio", + "linnunrataj\u00e4rjestelm\u00e4", + "siin\u00e4_tapauksessa_ett\u00e4", + "linnunpes\u00e4", + "marie_grosholtz", + "trois_rivi\u00e8res", + "allahu_akbar", + "sleeping_beauty", + "da_gama", + "mattimeik\u00e4l\u00e4inen", + "kanaalisaaret", + "rautatiekisko", + "tyrrhenanmeri", + "saksi_anhalt", + "mestarikokki", + "kartanolla", + "tekstiilitehdas", + "tuntiosoitin", + "ampumahaava", + "land", + "pohjanmeri", + "vappu", + "oikeudenistunto", + "kasvispuutarha", + "saint_vincent", + "suolaj\u00e4rvi", + "pelikentt\u00e4", + "iris_pseudacorus", + "toimintaedellytykset", + "keskuspuisto", + "kansalliskokous", + "kivikkopuutarha", + "saint_clair_j\u00e4rvi", + "vihannespalsta", + "pieris_rapae", + "osterimatalikko", + "kirsikkapuisto", + "oppositiopuolue", + "harmaahaikara", + "pekka_peukaloinen", + "joseph_louis_gay_lussac", + "plantago_major", + "tussaud", + "maailman_paras_juttu", + "sadep\u00e4iv\u00e4", + "palkinp\u00e4\u00e4t", + "pikkuviisari", + "saul_tarsolainen", + "liikekorttelit", + "st_clair_j\u00e4rvi", + "nuphar_lutea", + "vanhainkoti", + "keltainenmeri", + "liikearvo", + "pohjamaininki", + "liikekeskusta", + "plantago_media", + "gay_lussac", + "perusmaininki", + "mondrian", + "chathamsaaret", + "piippopaksup\u00e4\u00e4", + "edwardinj\u00e4rvi", + "sienikakku", + "ei_haittaa", + "mustameri", + "saint_christopher", + "lake_of_the_woods", + "alnus_glutinosa", + "sotilashallitus", + "psykiatrinen_hoitolaitos", + "st_helens", + "halonginlahti", + "newnjoki", + "tiedepuisto", + "usa", + "the_city", + "ruusutarha", + "yrityspuisto", + "saint_lucia", + "vienanjoki", + "michiganj\u00e4rvi", + "etel\u00e4saari", + "hwang_ho", + "viherkulta", + "appelsiinilehto", + "asuntola", + "ranskan_kansalliskokous", + "hermopiste", + "ket\u00e4_kiinnostaa", + "jouluaatto", + "kap_horn", + "huanghe", + "hat_yai", + "digimedia", + "p\u00e4iv\u00e4\u00e4", + "kolmas_henkil\u00f6", + "keskustassa", + "tanaj\u00e4rvi", + "kirsikkaperhonen", + "erotuomaripallo", + "sri_lanka", + "kap_verden_tasavalta", + "air_corps", + "zhu_jiang", + "painepiste", + "silt\u00e4_varalta_ett\u00e4", + "isohaarahaukka", + "villa_lobos", + "siinainvuori", + "new_mexicon_p\u00e4\u00e4kaupunki", + "lake_st_clair", + "us_asevoimat", + "yangtze_kiang", + "sinipeippo", + "irlannin_ilmavoimat", + "sotakorkeakoulu", + "karmel_vuori", + "aatelislinna", + "l\u00e4nsirannikko", + "varoiksi", + "tuomaripallo", + "rantariutta", + "yl\u00e4j\u00e4rvi", + "el\u00e4kes\u00e4\u00e4ti\u00f6", + "nam_nam", + "mainearvo", + "the_rolling_stones", + "edwardj\u00e4rvi", + "keskustaslummi", + "u.s_asevoimat", + "pohjanlahti", + "kolumbus", + "p\u00e4\u00e4si\u00e4issaari", + "juomakelpoinen_vesi", + "jangtse_joki", + "porot", + "p_patrick", + "falklandinsaaret", + "teknillinen_oppilaitos", + "man_o'war", + "kaupunkikeskus", + "saint_lawrence", + "rantalomakohde", + "kryvyi_rih", + "virgin_mary", + "painelupiste", + "sokerikakku", + "court", + "ampumamatka", + "mit\u00e4_v\u00e4li\u00e4", + "pieris_brassicae", + "heitor_villa_lobos", + "linnunrata", + "louis_joseph_gay_lussac", + "aluksessa", + "militokratia", + "vapaasatama", + "tuntiviisari", + "al_ain", + "temppelivuori", + "trifolium_dubium", + "joulupukki", + "pterocarpus_indicus", + "p\u00e4\u00e4rata", + "kulissientakainen", + "pohjoissaari", + "prinsessa_ruusunen", + "delonix_regia", + "never_never", + "prunus_avium" + ], + "LANGUAGE": [ + "malaijilainen", + "panjabi", + "shona", + "englannin", + "valkoven\u00e4j\u00e4nkielinen", + "bengali", + "marshalli", + "venda", + "painotusmerkki", + "bambara", + "ranskan", + "ket\u0161uanpuhuja", + "tiibetin", + "kongo", + "smith", + "sinhalan", + "akan", + "assamilainen", + "georgialainen", + "lausahdus", + "portugalin", + "cornwallin", + "sindhi", + "mansaarelainen", + "shonan", + "pali", + "navajo", + "romanian", + "buurilainen", + "pohjoissaame", + "ganda", + "manx", + "retoromaaninen", + "welsh", + "ruotsalaisten", + "malagassi", + "french", + "persian", + "bengalilainen", + "malayalam", + "hollannin", + "valkoven\u00e4j\u00e4n", + "georgian", + "kanuri", + "sinhala", + "katalaani", + "hindi", + "madjaari", + "chamorro", + "ven\u00e4j\u00e4n", + "kiinan", + "espanjan", + "arabiankieli", + "eestil\u00e4inen", + "saksan", + "sindil\u00e4inen", + "guarani", + "zhuang", + "herero", + "valkoven\u00e4j\u00e4", + "kiinankieli", + "sango", + "walesin", + "jaavan", + "divehi", + "sinhalin", + "irlannin", + "helleeninen_kieli", + "vieraanvoittoisuus", + "bengalin", + "persu", + "galitsialainen", + "esperanto", + "metallity\u00f6mies", + "puheviestint\u00e4", + "mukavuudensaari", + "tanskan", + "sundalaiset", + "creet", + "aksenttimerkki", + "komi", + "lingala", + "saksatar", + "viron", + "sechuana", + "ruotsin", + "hausa", + "assamin", + "kelttil\u00e4inen", + "wolof", + "cree", + "cornish", + "lao", + "malaijin", + "katalonialainen", + "islannin", + "puolan", + "tagalog", + "katalonian", + "tiibetil\u00e4inen", + "ido", + "japaninkielinen", + "marathi", + "virolainen", + "kalaallisut", + "chichewa", + "japanin", + "eestin", + "vastak\u00e4\u00e4nn\u00f6s", + "samoan", + "singaleesin", + "tonga", + "samoalainen", + "kannada", + "mansaaren", + "abhaasin", + "malajalam" + ], + "FOOD": [ + "glukoosisiirappi", + "cheshirenjuusto", + "piirakkataikina", + "maitoj\u00e4\u00e4tel\u00f6", + "reisipihvi", + "suolakurkku", + "appelsiinimarmeladi", + "kalapulla", + "scotch_woodcock", + "appelsiinimehutiiviste", + "paistinneste", + "jauhelihapiirakka", + "p\u00e4\u00e4ruokalaji", + "vahakurpitsa", + "meijerituote", + "lampaanreisi", + "mousse", + "kuoriperuna", + "maissimuffini", + "murukahvi", + "halpajuusto", + "mustamakkara", + "munakeitto", + "maitojuoma", + "kuivamuona", + "sinappikastike", + "helmisuurimot", + "onnenkeksi", + "papumuhennos", + "tummaleip\u00e4", + "golden_delicious", + "mantelipikkuleip\u00e4", + "sienikastike", + "maitotaloustuote", + "kampelanliha", + "naudanpaisti", + "kev\u00e4trulla", + "minttukastike", + "piparminttukaramelli", + "benediktinmunat", + "eskimoj\u00e4\u00e4tel\u00f6", + "ysk\u00e4npastilli", + "symphytum_officinale", + "etanavoi", + "pannukakkutaikina", + "leivontasuklaa", + "karpalomehu", + "koiranruoka", + "daucus_carota", + "kalkkunant\u00e4yte", + "bechamel", + "konjakkikahvi", + "laakerinlehti", + "hampurilaispihvi", + "simpukkakeitto", + "ristikukkainen_vihannes", + "hummerivoi", + "ikenet", + "christmas_pudding", + "mustikkapiirakka", + "lehm\u00e4npapu", + "maitojauhe", + "maitotuote", + "kanansiipi", + "sillinm\u00e4ti", + "valkosuklaa", + "hanhenmaksapasteija", + "lehtitaikinaleivonnainen", + "riisimuro", + "pakasteet", + "ohravesi", + "niva", + "jauhelihapihvi", + "thompson_seedless", + "grahamkeksi", + "tuoremehu", + "roseviini", + "tuutti", + "olkiviini", + "linnunsiemenet", + "bambunverso", + "perunankuori", + "kolauute", + "olla_h\u00e4vyt\u00f6n", + "puuvillansiemen\u00f6ljy", + "kermavaahto", + "vigna_unguiculata", + "s\u00e4ilykeruoka", + "sifonkikakku", + "lohivuoka", + "porkkanavanukas", + "k\u00e4\u00e4rmepapu", + "valkoinen_ven\u00e4l\u00e4inen", + "kilpikonnaliemi", + "ranskanperunat", + "keittosuola", + "papaijamehu", + "granny_smith", + "capsicum", + "sukaatti", + "lapapaisti", + "porsaankylki", + "chilijauhe", + "vasikanaivot", + "espanjansipuli", + "musta_tee", + "paukkupurukumi", + "porevesi", + "juomavesi", + "ulkopaisti", + "vasikankieli", + "pekaanip\u00e4hkin\u00e4piirakka", + "kalkkunamuhennos", + "pepperonipizza", + "p\u00e4iv\u00e4npolttava", + "huulirasva", + "t_luupihvi", + "russian_mayonnaise", + "fariinisokeri", + "aavikko", + "persikkamelba", + "pikkupurtava", + "ranskikset", + "aprikoosikastike", + "kala_\u00e4yri\u00e4iskastike", + "nicoise_salaatti", + "kopra\u00f6ljy", + "murukakku", + "j\u00e4rvikala", + "kalamuhennos", + "lampaankyljys", + "persikkakastike", + "saflori\u00f6ljy", + "kanelileip\u00e4", + "maksapasteija", + "pina_colada", + "ankkakastike", + "pekaanipiiras", + "kev\u00e4tk\u00e4\u00e4ryle", + "j\u00e4lkiruokahyytel\u00f6", + "sekasalaatti", + "kissanruoka", + "j\u00e4\u00e4kahvi", + "bambuverso", + "ranskalainen_maitokahvi", + "pinot_noir", + "linssikeitto", + "terveysuoka", + "kierrepulla", + "hummerimuhennos", + "porkkanamehu", + "karkkisauva", + "t\u00f6lkkiruoka", + "seesaminsiemen", + "seesami\u00f6ljy", + "hedelm\u00e4salaatti", + "maitopunssi", + "tom_collins", + "vinegrettekastike", + "chilikastike", + "liemikuutio", + "sekapata", + "broilerinkoipi", + "appelsiininkuori", + "pakaste", + "sianlihapiiras", + "pitk\u00e4papu", + "maustekurkku", + "maalaisjuusto", + "patonki", + "piirakankuori", + "maissisiirappi", + "teenlehti", + "kalkkunankoipi", + "macedoine", + "perunalastut", + "j\u00e4lkiruokaviini", + "k\u00f6yh\u00e4t_ritarit", + "kanaliemi", + "ravintorasva", + "lammascurry", + "tasaosuus", + "maitosuklaa", + "vaahterasiirappi", + "sammakonreisi", + "tattarikakku", + "perunasalaatti", + "ohrauute", + "vitamiinipilleri", + "paksu_simpukkakeitto", + "auringonkukka\u00f6ljy", + "muotidieetti", + "sammakonkoipi", + "sokerivesi", + "tulinen_kastike", + "sea_bream", + "kanelipaahtoleip\u00e4", + "maissisokeri", + "popcornkaramelli", + "\u00f6ljykakkujauhe", + "kaurakeksi", + "veripalttu", + "caesarsalaatti", + "voisula", + "tartarikastike", + "vasikanmaksa", + "rehuvilja", + "hunajapulla", + "reininviini", + "karkkipatukka", + "talvimeloni", + "makeispatukka", + "grahamjauho", + "lis\u00e4ruoka", + "ruisleip\u00e4", + "gelato", + "chili", + "johanneksenleip\u00e4puumakeinen", + "kanamousse", + "pastakastike", + "vauvanpuppu", + "savunauta", + "raakakaakao", + "lehm\u00e4nmaito", + "ankkapatee", + "lusikkaruoka", + "waldorfinsalaatti", + "savulohi", + "kurpitsapiirakka", + "terveysruoka", + "appelsiinit\u00e4ysmehu", + "melassitoffee", + "karpalokastike", + "mustasilm\u00e4papu", + "karamellipatukka", + "kuivahedelm\u00e4t", + "tomusokeri", + "chile", + "jauhelihaperunasoselaatikko", + "kananmuna", + "tartarpihvi", + "sianlihamakkara", + "elatusmaksu", + "sveitsinpihvi", + "melassikeksi", + "munuaispiirakka", + "antipasto", + "kurpitsansiemen", + "kentuckynpapu", + "kilpikonnakeitto", + "mansikkas\u00e4ilyke", + "lounastaa", + "h\u00e4r\u00e4nh\u00e4nt\u00e4liemi", + "punakaali", + "roseeviini", + "tarkastusmaito", + "sellerinsiemen", + "h\u00e4\u00e4kakku", + "maryland_chicken", + "ranskanperuna", + "limppari", + "mantelisarvi", + "maissiviski", + "rosee", + "rintasokeri", + "spagettikastike", + "chiliseos", + "lisuke", + "kanariansiemenet", + "grahamleip\u00e4", + "chilietikka", + "maissi\u00f6ljy", + "palasokeri", + "c_ration", + "kivisokeri", + "vasikansorkat", + "hiusvaahto", + "naudanlihas\u00e4ilyke", + "curryjauhe", + "vasikanlihaviipale", + "sekoiteviski", + "tillinsiemen", + "melonipallo", + "tiikerikakku", + "hillokaramelli", + "kanelipulla", + "kalanpaistoretki", + "kananmaksa", + "osterit\u00e4yte", + "perunasose", + "hattara", + "alttariviini", + "ginik\u00e4\u00e4re", + "osterimuhennos", + "cocktailkastike", + "chilipata", + "syntt\u00e4rikakku", + "tapiokavanukas", + "hushpuppy", + "munuaiset", + "h\u00e4r\u00e4npaisti", + "tutti_frutti", + "pastasalaatti", + "valkosipulipatonki", + "laihdutuskuuri", + "salaattiainekset", + "siiderietikka", + "tasaosuuksinen", + "k_ration", + "kalkkunansiipi", + "simpukkadippi", + "kermavanukas", + "hernesoppa", + "valkokastike", + "maitotiiviste", + "jouluvanukas", + "kamara", + "vannike", + "mansikkaj\u00e4\u00e4tel\u00f6", + "kanavoileip\u00e4", + "mielipuuha", + "luonnonriisi", + "kasvis\u00f6ljy", + "sulatejuusto", + "valkosipulileip\u00e4", + "hummeripiirakka", + "persikkaj\u00e4\u00e4tel\u00f6", + "mansikkahillo", + "kanelikierre", + "pikkumusta", + "vesijohtovesi", + "virvoitusjuoma", + "myslipatukka", + "tikkunekku", + "manteliuute", + "sellerisuola", + "hedelm\u00e4mehu", + "pieni_pannukakku", + "munanuudeli", + "valkosipulivoi", + "italiankastike", + "sonchus_oleraceus", + "tartarkastike", + "kapriskastike", + "meritaimen", + "kalapuikko", + "vissy", + "hunajakarkki", + "morsiuskakku", + "huulivoide", + "harvey_wallbanger", + "aniskeksi", + "p\u00e4hkin\u00e4voi", + "kanaviillokki", + "klubileip\u00e4", + "koirankeksi", + "torttutaikina", + "hernekeitto", + "kotijuusto", + "verimakkara", + "kurri", + "hernemuhennos", + "sherrykakku", + "fenkolinsiemen", + "lammasmuhennos", + "mantelikeksi", + "vaahtokarkkilevite", + "perunankuoret", + "appelsiinimehu", + "sianlihaviipale", + "annoonahedelm\u00e4", + "munakokkeli", + "teetauko", + "ruskeakastike", + "leivonnaiset", + "muotoiluvaahto", + "mansikkadaiquiri", + "kinkkukerrosvoileip\u00e4", + "syntym\u00e4p\u00e4iv\u00e4kakku", + "hanavesi", + "standardiviina", + "kanakeitto", + "cohoe", + "kraanavesi", + "lampaanlihaviipale", + "greippimehu", + "katajanmarjat", + "viikunakaktus", + "hanhenmaksa", + "maitojuusto", + "maissivanukas", + "m\u00fcnchener", + "juglans_regia", + "salaatti\u00f6ljy", + "chevre", + "linnunruoka", + "siankyljet", + "perinneruoka", + "tynnyriolut" + ], + "PRODUCT": [ + "sudenpes\u00e4", + "st_vincent", + "aarnivalkea", + "poistu", + "patarouva", + "virvatuli", + "magneettijuova", + "boolimalja", + "yl\u00e4puolelle", + "justin_bieber", + "laivakompassi", + "automaattisulake", + "uusikaledonialainen", + "tapaninp\u00e4iv\u00e4", + "ter\u00e4v\u00e4piirtotelevisio", + "s_tog", + "jobinkyynelhein\u00e4", + "viime_hetkess\u00e4", + "hedelm\u00e4peli", + "ruokakuppi", + "korvariipus", + "tennispallo", + "kruununjalokivet", + "virrankatkaisin", + "paperinukke", + "putkikellot", + "kruununkalleudet", + "al_jazeera", + "aurinkokuivattu", + "saapasjalkakissa", + "hopeah\u00e4\u00e4p\u00e4iv\u00e4", + "riemukaari", + "cookinsaaret", + "yhdennell\u00e4toista_hetkell\u00e4", + "lennonjohtopalvelu", + "luonnonhistoria", + "puheradio", + "kokoruutu", + "diego_garcia", + "tutti_frutti", + "kovaksikeitetty", + "musiikkisoitin", + "kipin\u00e4suojus", + "n\u00e4lk\u00e4peli", + "omaisuusvakuudellinen", + "j\u00e4\u00e4kiekkomaila", + "die_hard_vain_kuolleen_ruumiini_yli", + "kaakelileikkuri", + "umpikatu", + "seksiorjuus", + "kanooppiastia", + "verkkokirjasto", + "panssariauto", + "sulkapallomaila", + "lepolassi", + "haukansilm\u00e4inen", + "j\u00e4\u00e4kuutio", + "julius_caesar", + "saint_vincent", + "virtuaalikone", + "t\u00f6rm\u00e4ilyautot", + "aarnituli", + "pelipallo", + "the_star_spangled_banner", + "pulloposti", + "stilleben", + "kumistin", + "vesipullo", + "haarahyppy", + "monte_cristo", + "kahvikuppi", + "taivaankappale", + "tenorirumpu", + "tanssilattia", + "loppiaisaatto", + "gongi", + "kumahtaa", + "kolme_kuningaskuntaa", + "seesamtie", + "banaanilaiva", + "pallolaakeri", + "konstantin_stanislavsky", + "kaasulamppu", + "kastemalja", + "rakkauskirje", + "mit\u00e4_jos", + "maastokelpoinen", + "ii_maailmansota", + "johannes_kastaja", + "munasauva", + "autovarkaus", + "l\u00e4mp\u00f6kilpi", + "oikosulku", + "laskutikku", + "teetarjotin", + "digitaalinen_kamera", + "ensimm\u00e4inen_maailmansota", + "ponnahdusikkuna", + "patakuningatar", + "joulupuu", + "tapani", + "kuulalaakeri", + "sokerilusikka", + "deutsche_welle", + "j\u00e4rjestelm\u00e4riippumaton", + "varttua", + "mount_st_helens", + "sektio", + "ferdinand_magellan", + "pyh\u00e4_henki", + "yhdestoista_hetki", + "urheiluauto", + "o_rengas", + "myosotis_scorpiodes", + "mario_andretti", + "soittorasia", + "solariumi", + "san_sebastian", + "mit\u00e4_uutta", + "aikakone", + "mobiililaite", + "p\u00e4iv\u00e4ty\u00f6", + "st_george's", + "maaliruisku", + "musta_pallo", + "de_facto", + "taistelukirves", + "rullalaakeri", + "ihmisoikeudet", + "mankka", + "nordrhein_westfalen", + "kirveenhamara", + "balkanvuoret", + "tiikeriveljekset", + "nelj\u00e4_vuodenaikaa", + "disketti", + "kuolemanj\u00e4lkeinen", + "nen\u00e4rengas", + "paperilentokone", + "grenadan_p\u00e4\u00e4kaupunki", + "muistolle", + "korttipelip\u00f6yt\u00e4", + "taistelukutsu", + "ruiskupistooli", + "san_joaquin_joki", + "novo_mesto", + "laiskanlinna", + "syvyyspommi", + "heittokoukku", + "lounaaseen", + "s\u00e3o_paulo" + ], + "RACE": [ + "filipino", + "valkoiset", + "amerikan_intiaani", + "pohjoiseurooppalainen", + "pohjoiskorealainen", + "latino", + "french", + "polynesian", + "intian", + "amerikanintiaani", + "ranskatar", + "kymrit", + "maakalainen", + "afrikan", + "filippiinil\u00e4inen", + "saarelainen", + "englantilaiset", + "intialainen", + "korean", + "sassenach", + "the_mexican", + "hollantilaiset", + "filippiino", + "alkuper\u00e4iskansa", + "white", + "maailmanalun", + "filippiinien", + "autoktoni", + "etel\u00e4amerikkalainen", + "etel\u00e4korealainen", + "intiaanien", + "alkuper\u00e4isasukas", + "iiril\u00e4iset", + "saaristolainen", + "latinalaisamerikkalainen", + "latina", + "meksikon", + "turkkilaiset", + "afrikkalainen", + "japanilaiset", + "australian_alkuper\u00e4iskielet", + "amerind" + ], + "QUANTITY": [ + "si_j\u00e4rjestelm\u00e4", + "ei_yhtik\u00e4s_mit\u00e4\u00e4n", + "volttiampeeri", + "seitsem\u00e4nnes", + "kolme_sisarta", + "hevosvoimatunti", + "imaginaariosa", + "ilmanvastuskerroin", + "ep\u00e4murtoluku", + "tilavuusyksikk\u00f6", + "varausyksikk\u00f6", + "seitsem\u00e4sosa", + "nesteyksikk\u00f6", + "miljoonasosa", + "wattitunti", + "tulostusyksikk\u00f6", + "merilineaariyksikk\u00f6", + "kolmikymmenvuotinen_sota", + "ilmamaili", + "fahrenheitaste", + "hengitystila", + "normaalipaine", + "madagaskarin_frangi", + "koripallorengas", + "isosata", + "transsendenttiluku", + "saksanmarkka", + "dollari", + "painoyksikk\u00f6", + "viskositeettikerroin", + "hengitystilaa", + "elektronivoltti", + "grammakalori", + "malawin_kwacha", + "ison_britannian_rahayksikk\u00f6", + "ton", + "hajoamisvakio", + "painoj\u00e4rjestelm\u00e4", + "jalkatonni", + "irrationaaliluku", + "kolmasosa", + "shillinki", + "kvarttosidonta", + "kitkakerroin", + "perussuure", + "el\u00e4inkoti", + "rajapiste", + "ison_britannian_\u0161illinki", + "tilavuuskimmokerroin", + "allokointiyksikk\u00f6", + "binaarinumero", + "\u00e4\u00e4nenvoimakkuusyksikk\u00f6", + "pituusmitta", + "miljoonakertaisesti", + "vastusyksikk\u00f6", + "oikokulma", + "koiratarha", + "belizen_dollari", + "dissosiaatiovakio", + "alayksikk\u00f6", + "pistej\u00e4rjestelm\u00e4", + "magneettinen_voimavaikutus", + "g", + "kentt\u00e4kapasiteetti", + "kompassipiiru", + "tilavuusmitta", + "mauritiuksen_rupia", + "ketjumurtoluku", + "s\u00e3o_tom\u00e9n_ja_pr\u00edncipen_rahayksikk\u00f6", + "tavukorko", + "rial", + "ei_tuon_taivaallista", + "kaarimitta", + "rationaaliluku", + "kolmipiikki", + "alkutekij\u00e4", + "kaksinumeroinen", + "si_yksikk\u00f6", + "kasvotusten", + "kolmoiskaari", + "vetop\u00f6yt\u00e4", + "satatuhatta", + "s\u00e4hk\u00f6virtayksikk\u00f6", + "pound", + "massayksikk\u00f6", + "pa_anga", + "kolmivaihekytkin", + "gasterosteus_aculeatus", + "energiayksikk\u00f6", + "kolmiulotteisuus", + "paineyksikk\u00f6", + "ordinaalilukusana", + "metrij\u00e4rjestelm\u00e4", + "kokos\u00e4vel", + "el_salvadorin_rahayksikk\u00f6", + "kasvokkain", + "burundin_frangi", + "rusikoida", + "kaarisekunti", + "taala", + "tooni", + "binaariluku", + "tuon", + "vastatusten", + "perusmitta", + "massaluku", + "dinaari", + "lukuarvo", + "pintamitta", + "anders_celsius", + "hiuskarva", + "meripeninkulma", + "vastuskerroin", + "ezra_loomis_pound", + "s\u00e4velaskel" + ], + "DATE": [ + "huippuluokkainen", + "lasko", + "l\u00e4hetyskatko", + "markkinap\u00e4iv\u00e4", + "avaruusaika", + "kirkkokalenteri", + "relaksaatioaika", + "vaalip\u00e4iv\u00e4", + "empim\u00e4tt\u00e4", + "aurinkokalenteri", + "kyselytunti", + "t\u00e4htiaikavuosi", + "elinkautinen", + "tiedonsiirtonopeus", + "k\u00e4sittelyaika", + "kaksikymment\u00e4nelj\u00e4_seitsem\u00e4n", + "marssitahti", + "sairasloma", + "keskikolmannes", + "vapaahetki", + "patriot's_day", + "pyh\u00e4inp\u00e4iv\u00e4", + "vuorokausirytmi", + "is\u00e4np\u00e4iv\u00e4", + "henkil\u00f6ty\u00f6tunti", + "tuhkakeskiviikko", + "senkka", + "huvikausi", + "t\u00e4ysikuu", + "v\u00e4litysaika", + "kaksikymment\u00e4viisivuotisjuhla", + "syysp\u00e4iv\u00e4ntasaus", + "itsen\u00e4isyysp\u00e4iv\u00e4", + "kuukalenteri", + "lepovuosi", + "vappuaatto", + "miesty\u00f6tunti", + "korkotaso", + "elinajanodote", + "koripallokausi", + "piinaviikko", + "sairasp\u00e4iv\u00e4", + "happy_hour", + "rukoussunnuntai", + "normaalivuosi", + "a_ja_o", + "the_day_after_tomorrow", + "kylm\u00e4aalto", + "kes\u00e4koulu", + "kev\u00e4tharjoittelu", + "voitonp\u00e4iv\u00e4", + "lepop\u00e4iv\u00e4", + "suojaik\u00e4raja", + "alkupuolisko", + "t\u00e4htiaikakuukausi", + "kansalaisuusp\u00e4iv\u00e4", + "lain_m\u00e4\u00e4r\u00e4\u00e4m\u00e4_vapaap\u00e4iv\u00e4", + "vuosisadanvaihde", + "loppiaisaatto", + "tapani", + "lankalauantai", + "kirkkojuhla", + "palmusunnuntai", + "inflaatioaste", + "\u00e4\u00e4nestysik\u00e4", + "in_time", + "sapattivuosi", + "loistoaika", + "kes\u00e4kurssit", + "keskihakuiskiihtyvyys", + "aluepainos", + "suoritusvaihe", + "kulta_aika", + "laskiaistiistai", + "urheilukilpailut", + "aurinkokuukausi", + "s\u00e4ilyvyysaika", + "rikosm\u00e4\u00e4r\u00e4", + "ajonaikainen", + "kansallisp\u00e4iv\u00e4", + "veteraanip\u00e4iv\u00e4", + "hindukalenteri", + "kentt\u00e4harjoitus", + "l\u00e4pimenoaika", + "nimip\u00e4iv\u00e4", + "avaruusaikakausi", + "p\u00e4iv\u00e4vuoro", + "normaaliaika", + "hengitystaajuus", + "elonkorjuukuu", + "kalenterip\u00e4iv\u00e4", + "torip\u00e4iv\u00e4", + "lukuvuosi", + "kasvuvauhti", + "talvip\u00e4iv\u00e4nseisaus", + "k\u00e4rsimysviikko", + "varapresidenttiys", + "tilivuosi", + "lapsikuolleisuus", + "kolmenelj\u00e4sosatahti", + "kouluvuosi", + "avioliittoik\u00e4", + "kev\u00e4tp\u00e4iv\u00e4ntasaus", + "valovirta", + "hopeah\u00e4\u00e4p\u00e4iv\u00e4", + "rikosaste", + "mets\u00e4styskausi", + "maailmanluokan", + "t\u00e4m\u00e4_hetki", + "universaaliaika", + "virkaanastumisp\u00e4iv\u00e4", + "kiertojakso", + "shaaban", + "iltavuoro", + "kes\u00e4yliopisto", + "t\u00e4ss\u00e4_ja_nyt", + "elini\u00e4nodote", + "rajanopeus", + "perussyy", + "ei_karkausvuosi", + "pitk\u00e4perjantai", + "vappuviini", + "neutronivuo", + "j\u00e4lkikes\u00e4", + "pakonopeus", + "lomasesonki", + "p\u00e4\u00e4tt\u00e4j\u00e4isp\u00e4iv\u00e4", + "kalenterivuosi", + "sulkemisaika", + "aloitushetki", + "kiirastorstai", + "d_day", + "sirkadiaanirytmi", + "uusikuu", + "j\u00e4\u00e4kiekkokausi", + "kuolevuus", + "tilikausi", + "t\u00e4htiaika", + "lomakausi", + "aamiaisaika", + "vapaap\u00e4iv\u00e4", + "t\u00e4htiaikatunti", + "aurinkovuosi", + "kes\u00e4lukio", + "l\u00e4ht\u00f6nopeus", + "keskeytt\u00e4mism\u00e4\u00e4r\u00e4", + "kultakausi", + "aurinkovakio", + "sha'ban", + "intiaanikes\u00e4", + "quasimodogeniti", + "sairausloma", + "hengitystiheys", + "ruusun\u00e4si\u00e4", + "kalastuskausi", + "gregoriaaninen_kalenteri", + "jalkapallokausi", + "juhannusaatto", + "herran_vuonna", + "niin_kauan_kuin_muistetaan", + "annosnopeus", + "corpus_christi", + "annosteho", + "kes\u00e4p\u00e4iv\u00e4nseisaus", + "maailmanaika", + "kuin_ammuttuna", + "joutoaika", + "juhannusp\u00e4iv\u00e4", + "glasiaalikausi", + "promootiop\u00e4iv\u00e4", + "marian_taivaaseenottaminen", + "kasvunopeus", + "adventtisunnuntai", + "kalenterikuukausi" + ], + "GPE": [ + "teollisuuspuisto", + "keskustori", + "kammioneste", + "st_christopher", + "saint_domingue", + "xihu", + "kotte", + "dar_es_salaam", + "merikansat", + "sint_maarten", + "pandanus_tectorius", + "pyh\u00e4_kristoffer", + "etel\u00e4_amerikka", + "p_yrj\u00f6", + "tsemppi\u00e4", + "punainenmeri", + "simon_pietari", + "olympiakyl\u00e4", + "pyh\u00e4_pietari", + "norsunluurannikko", + "schwartzwald", + "pitk\u00e4aalto", + "s\u00e3o_tom\u00e9", + "hagia_sofia", + "gran_canaria", + "tappioputki", + "nikolaos", + "taddeus", + "pyh\u00e4_kristoforos", + "pyh\u00e4_nikolaos", + "vanhakaupunki", + "al_andalus", + "valkokulta", + "jooniansaaret", + "la_rochelle", + "uusi_testamentti", + "koulupiiri", + "kruununsiirtomaa", + "borassus_flabellifer", + "valkoinen_talo", + "liittovaltion_hallintoalue", + "taishan", + "p_kristoffer", + "hibiscus_rosa_sinensis", + "komipermjakki", + "la_gomera", + "pyh\u00e4_yrj\u00e4n\u00e4", + "nikolaos_ihmeidentekij\u00e4", + "st_louis", + "santa_sofia", + "suolatasanko" + ], + "ANAT": [ + "siki\u00f6kudos", + "h\u00e4nt\u00e4nikama", + "kaarivaltimo", + "suolievelaskimo", + "kaulanikama", + "keuhkovaltimorunko", + "maksavaltimo", + "niskanikama", + "parietaalipleura", + "ristinikama", + "arteria_arcuata", + "verisuonirengas", + "tibialis_anticus" + ], + "RELIGION_MEMBER": [ + "metodistinen", + "kreikkalaiskatolilainen", + "orangeman", + "helluntalainen", + "karmeliittamunkki", + "jihadisti", + "guru", + "baptistinen", + "benediktiininunna", + "sunnalainen", + "the_hindu", + "trappisti", + "donkkaaja", + "mulla", + "fransiskaanit", + "mandean", + "kartusiaaninen", + "wahhabi", + "moonilainen", + "ravistelija", + "parsee", + "j\u00e4nishousu", + "shaiviitti", + "sapattilainen", + "benediktiini", + "augustinolaismunkki", + "traktarianisti", + "sunnilainen", + "rooman_kirkko", + "kartusiaani", + "valkoinen_munkki", + "muhamettilainen", + "saraseeni", + "katolinen", + "mormoni", + "helluntailainen", + "parsit", + "mandea", + "sapatin", + "mormon", + "vanhakatolinen", + "shaker", + "fransiskaanimunkki", + "kartusiaanien", + "vaishnava", + "shaktisti", + "kastaja", + "karmeliitta", + "presbyteerinen", + "wesleyl\u00e4inen", + "mollah", + "munkkilik\u00f6\u00f6ri", + "sisterssil\u00e4inen", + "mullah", + "sunni", + "fransiskaani", + "ravistin", + "parsi", + "protestanttinen", + "augustinolainen", + "saarnaajaveli", + "wahabi", + "melkiitti", + "benediktiinil\u00e4inen", + "shiialainen", + "vastaanhangoittelija", + "muhammadin", + "benediktiinimunkki", + "mon", + "sunnaislam", + "kveekari", + "mandealainen", + "kongregationalisti", + "christian_scientist", + "sunnimuslimi", + "shivaisti", + "benediktiinilik\u00f6\u00f6ri" + ], + "SOC_ECO_CLASS": [ + "pikkuporvari", + "baronetit", + "sosieteetti", + "paronit", + "ritaris\u00e4\u00e4ty", + "labor", + "muutama", + "kastilaitos", + "oppineet", + "talonpojat", + "talonpoikaisto", + "vallassa_oleva_s\u00e4\u00e4ty", + "maalaisk\u00f6yh\u00e4list\u00f6", + "jalous", + "yhtenevyys", + "samurai", + "keskiluokka", + "p\u00e4\u00e4rit", + "kerma", + "lukeneisto", + "kulttuurifriikit", + "naissuku", + "silm\u00e4\u00e4tekev\u00e4t", + "proletariaatti", + "vallassa_olevat_henkil\u00f6t", + "tilanomistajisto", + "alaluokka", + "ritarius", + "maatalousv\u00e4est\u00f6", + "poroporvarit", + "valitut", + "ty\u00f6l\u00e4iset", + "henkil\u00f6st\u00f6nvuokraaja", + "paronikunta", + "ty\u00f6v\u00e4enluokka", + "alaluokan", + "pikkuporvaristo", + "vastavalittu", + "maa_aateli", + "jati", + "ty\u00f6voimareservi", + "j\u00e4rjest\u00e4ytynyt_ty\u00f6voima", + "jalosukuisuus", + "jokunen", + "yhteislaidun", + "siniverinen", + "maahanmuuttajaluokka", + "ty\u00f6v\u00e4enluokkainen", + "maa_aatelisto", + "ty\u00f6l\u00e4is" + ], + "PERSON_PRONOUN": [ + "h\u00e4nelle", + "h\u00e4neksi", + "minua", + "i", + "miinoittaa", + "he", + "h\u00e4nest\u00e4", + "meit\u00e4", + "sinun", + "meid\u00e4t", + "minun", + "meid\u00e4n_mme", + "h\u00e4nen", + "sinun_si", + "meid\u00e4n", + "teit\u00e4", + "omillaan", + "minun_ni", + "thy", + "me", + "sin\u00e4", + "teid\u00e4t", + "teid\u00e4n", + "h\u00e4neen", + "us" + ], + "BIO_CHEM_ENTITY": [ + "d_vitamiini", + "tuumorinekroositekij\u00e4", + "asetyylikoliinikloridi", + "ni_resisti", + "adefoviiridipivoksiili", + "rasvahapot", + "sitruuna\u00f6ljy", + "fulvohappo", + "metaaniklatraatti", + "deoksisytidiinimonofosfaatti", + "magnesiumkloridi", + "klooritrifluoridi", + "syaanihappo", + "sassafras\u00f6ljy", + "kaliumjodidi", + "veriagar", + "sinkkikloridi", + "\u00e4kkikuolema", + "yrtti\u00f6ljy", + "kaulmoogra\u00f6ljy", + "karbamoyylifosfaatti", + "vehn\u00e4nalkio", + "strontiumkloridi", + "kaliumalumiinisulfaatti", + "rasvahappo", + "alfafetoproteiini", + "polylaktidi", + "volframihappo", + "angiotensiinikonvertaasi", + "prostataspesifinen_antigeeni", + "dikromihappo", + "kalsiferoli", + "ni_resisti_ter\u00e4s", + "metafosforihappo", + "adenylaattideaminaasi", + "adenosiinidifosfaatti", + "molybdeenidisulfidi", + "ksantiinioksidaasi", + "piparminttu\u00f6ljy", + "ergokalsiferoli", + "c_reaktiivinen_proteiini", + "mineraali\u00f6ljy", + "salisyylihappo", + "silikonikumi", + "prostasykliinisyntaasi", + "lauryylialkoholi", + "guanosiinidifosfaatti", + "karvasmanteli\u00f6ljy", + "sitronella\u00f6ljy", + "karbonyylikloridi", + "molybdeenihappo", + "perboorihappo", + "viherminttu\u00f6ljy", + "old_fashioned", + "asetyylikloridi", + "maitohappo", + "bariumtitanaatti", + "mangaanihappo", + "itakonihappo", + "plasminogeeniaktivaattori", + "makeamanteli\u00f6ljy", + "k\u00e4\u00e4nteiskopioijaentsyymi", + "kroton\u00f6ljy", + "manteli\u00f6ljy", + "p\u00e4hkin\u00e4\u00f6ljy", + "hopeaoksidi", + "bentsalkoniumkloridi", + "poliorokote", + "fenyylietikkahappo", + "monoamiinioksidaasi", + "hermokasvutekij\u00e4", + "lyijysokeri", + "edward_thatch", + "kalmojuuri\u00f6ljy", + "beetaendorfiini", + "lauriinihappo", + "polyvinyylikloridi", + "sitruunauute", + "neroli\u00f6ljy", + "kostus\u00f6ljy", + "traneksaamihappo", + "kala\u00f6ljy" + ], + "RELIGION": [ + "roomalaiskatolisuus", + "suufilaisuus", + "lamalaisuus", + "salafismi", + "zen", + "shaktismi", + "shinto", + "shivalaisuus", + "hinajana", + "brahmalaisuus", + "lamaismi", + "rastafarismi", + "darsana", + "wiccalaisuus", + "vedanta", + "presbyterismi", + "presbyteeril\u00e4isyys", + "puseyismi", + "vishnulaisuus", + "parsilaisuus", + "manikealaisuus", + "donatolaisuus", + "islam", + "kataarit", + "ismailiittiliike", + "mahdismi", + "brahmanismi", + "vedalaisuus", + "kongregationalismi", + "traktarianismi", + "shingon", + "taolaisuus", + "chabad", + "christian_science", + "hsuan_chiao", + "bahaism", + "reformijuutalaisuus", + "donatismi", + "presbyteriaaninen_kirkko", + "trinitaarisuus", + "manilaisuus", + "wahabismi", + "mennonilaisuus", + "kristillinen_tiede", + "wicca", + "mimamsa" + ], + "GENDER": [ + "kimma", + "tukikaapeli", + "guy", + "kiltsi", + "naisia", + "miespaha", + "pekka", + "mieshenkil\u00f6", + "male", + "ahavoitua", + "senorita", + "pikkupoika", + "sierettym\u00e4", + "harmaaparta", + "lassie", + "hemmo", + "nais", + "daami", + "naisvanginvartija", + "transgender", + "matroona", + "muunsukupuolinen", + "man", + "gal", + "maiden", + "pikkutytt\u00f6", + "lady", + "nahkasuojukset" + ], + "FAC": [ + "toimistorakennus", + "haulinvalutorni", + "vedonly\u00f6ntitoimisto", + "sublime_porte", + "valvontakeskus", + "ottomaanien_imperiumi", + "hiilivaja", + "urheiluhalli", + "postikonttori", + "katolinen_kirkko", + "kunnantalo", + "valitusmuuri", + "fernand_leger", + "riippusilta", + "the_last_supper", + "kivisein\u00e4", + "papeda", + "rantatalo", + "k\u00e4\u00e4nt\u00f6silta", + "kuivatelakka", + "taikavuori", + "maakellari", + "alakoulu", + "kansanrintama", + "arnold_sch\u00f6nberg", + "taideoppilaitos", + "plaza", + "l\u00e4\u00e4ketieteellinen_tiedekunta", + "saint_joseph", + "komentopaikka", + "kakkosasunto", + "postileikki", + "toimistotalo", + "bussiterminaali", + "askelittain", + "hyv\u00e4ntoivonniemi", + "sch\u00f6nberg", + "juomalaite", + "t_lymfosyytti", + "ydinvoimala", + "postitoimisto", + "t\u00e4yshoitola", + "l\u00e4nsimuuri", + "max_muller", + "bussiasema", + "kolmekymment\u00e4kolme", + "ostari", + "t_solu", + "t_imusolu", + "j\u00e4\u00e4silta", + "kauppakeskus", + "lepokoti", + "ministeri\u00f6rakennus", + "luistelukaukalo", + "rautaristi", + "hiljalleen", + "koulutuslaitos", + "hallintorakennus", + "junapys\u00e4kki", + "saint_lucia", + "ty\u00f6v\u00e4entalo", + "p\u00e4ivyst\u00e4\u00e4", + "pietari_i", + "pikaraitiotie", + "tulliasema", + "yliopistokaupunki", + "p\u00e4\u00e4tteet\u00f6n", + "pietari_suuri", + "paperitehdas", + "presidentinlinna", + "n\u00e4ytt\u00e4m\u00f6oikea", + "sotilassairaala", + "naurutalo", + "nalle_puh", + "l\u00e4\u00e4ketieteellinen_yliopisto", + "sotilasvankila", + "v\u00e4h\u00e4", + "vuorovesimylly", + "kes\u00e4huvila", + "kauppapaikka", + "oppilaitos", + "laivastoasema", + "karttahuone", + "titus_livius", + "konserttitalo", + "pyh\u00e4_joosef", + "kuritushuone", + "muonituskeskus", + "ostosparatiisi", + "v\u00e4hitt\u00e4ismyym\u00e4l\u00e4", + "syyskuun_11_p\u00e4iv\u00e4", + "tuulitunneli", + "luonnonmuistomerkki", + "taideaineet", + "virastorakennus", + "t\u00e4n\u00e4_y\u00f6n\u00e4", + "espanjan_kansanrintama", + "kuivamuuri", + "kiviaita" + ], + "POLITICAL_PARTY": [ + "konservatiivipuolue", + "brittil\u00e4inen_ty\u00f6v\u00e4enpuolue", + "states_rights_democratic_party", + "populistipuolue", + "yhdysvaltain_demokraattis_republikaaninen_puolue", + "constitutional_union_party", + "gironde", + "free_soil_party", + "democratic_republican_party", + "aherrus", + "konservatiivinen_puolue", + "liberaalipuolue", + "amerikan_ty\u00f6v\u00e4enpuolue", + "vastaisuus", + "vastapeluri", + "vihre\u00e4_puolue", + "liberaalidemokraatit", + "labor", + "kuomintang", + "demokraattinen_puolue", + "know_nothing_party", + "greenback_party", + "liberty_party", + "agraaripuolue", + "natsipuolue", + "kieltolakipuolue", + "federatiivinen_puolue", + "amerikan_federalistinen_puolue", + "federalistinen_puolue", + "kansallispuolue", + "partido_socialista", + "dixiecrats", + "people's_party", + "edistyspuolue", + "anti_masonic_party", + "american_party", + "yhdysvaltain_republikaaninen_puolue", + "puutarhakutsut", + "mustat_pantterit", + "kansanpuolue", + "farmer_labor_party", + "american_labor_party", + "puutarhajuhla", + "bull_moose_party", + "australian_labor_party", + "guomindang", + "etel\u00e4_afrikan_konservatiivinen_puolue", + "pihajuhla", + "whig_puolue" + ], + "UNION": [ + "itu", + "opiskelijatalo", + "industrial_workers_of_the_world", + "ylioppilaskunta", + "united_mine_workers", + "teollisuusliitto", + "kansainv\u00e4linen_televiestint\u00e4liitto", + "ammattiyhdistys", + "iww", + "united_mine_workers_of_america", + "yhti\u00f6n_alainen_ammattiyhdistys", + "i.w.w" + ], + "PERSON": [ + "prince_albert", + "julius_caesar", + "ha_ha", + "al_gore", + "h_g_wells", + "yhteisvoitto", + "albert_francis_charles_augustus_emmanuel", + "saint_vincent", + "pyh\u00e4_paavali", + "st_vincent", + "e_o_wilson", + "parakautsupuu", + "oliivinharmaa", + "don_delillo", + "penisl\u00e4vistys", + "margaret_munnerlyn_mitchell", + "e_e_cummings", + "ei_eik\u00e4", + "nyyh", + "edward_osborne_wilson", + "roger_eliot_fry", + "walther_richard_rudolf_hess", + "c_vitamiini", + "willard_frank_libby", + "apostoli_paavali", + "igor_sikorsky", + "la_la", + "musta_kilpikonna", + "edward_franklin_albeen", + "carl_david_anderson", + "gaius_julius_caesar", + "wieland", + "miekankantaja", + "maxwell_anderson", + "rudolf_hess", + "siit\u00e4_saakka", + "uppopaistettu", + "kes\u00e4p\u00e4iv\u00e4nhattu", + "herbert_george_wells", + "cha_cha", + "t_luupihvi" + ], + "POLITICAL_PARTY_MEMBER": [ + "punikki", + "menshevikki", + "kommunisti", + "kommunistinen", + "fabianisti", + "marxisti", + "fabianistinen", + "federalisti", + "fabianismin" + ], + "TITLE": [ + "sir", + "ms" + ], + "MEDICAL_THERAPY": [ + "aivopaine", + "virtuaalitodellisuus", + "verenpaine" + ], + "ner_regexes": [ + [ + "PERSON", + "\\D+ \\D+|\\D+ \\D+|\\D+ \\D+|\\D+ \\D+|\\D+ \\D+-\\D+|\\D+ \\D+|\\D+ \\D+|\\D+ \\D+|\\D+ \\D+|\\D+ \\D+-\\D+", + false, + [] + ] + ], + "FIRST_NAME_FEMALE": [ + "kristiina", + "iiris", + "teija", + "iida", + "hannele", + "sara", + "marketta", + "oona", + "maaria", + "lotta", + "aleksandra", + "aino", + "jenna", + "saara", + "p\u00e4ivi", + "carita", + "marita", + "marika", + "virpi", + "lea", + "alexandra", + "sanna", + "lilja", + "anneli", + "olivia", + "kirsi", + "kristina", + "ritva", + "katriina", + "mervi", + "leila", + "margit", + "pia", + "merja", + "maria", + "kaarina", + "vilma", + "jenni", + "katariina", + "kaija", + "maija", + "jasmin", + "helmi", + "anniina", + "anna", + "helena", + "elisa", + "eila", + "sari", + "eija", + "nea", + "miia", + "anne", + "kati", + "karoliina", + "pirkko", + "milla", + "marjo", + "alina", + "aurora", + "maire", + "laura", + "piia", + "susanna", + "linnea", + "anita", + "hilkka", + "emmi", + "aune", + "esteri", + "sisko", + "pauliina", + "arja", + "elli", + "heidi", + "terttu", + "katja", + "hanna", + "jaana", + "annikki", + "sirpa", + "raija", + "irmeli", + "krista", + "vuokko", + "petra", + "marjaana", + "mira", + "liisa", + "niina", + "tuulikki", + "linda", + "terhi", + "tuula", + "taina", + "ilona", + "ella", + "annika", + "tuija", + "marjatta", + "pirjo", + "irja", + "helin\u00e4", + "kaisa", + "ida", + "martta", + "alisa", + "tiina", + "kirsti", + "nina", + "elsa", + "airi", + "julia", + "sonja", + "johanna", + "elisabeth", + "marja", + "marjut", + "helvi", + "elisabet", + "tanja", + "matilda", + "erika", + "anna_liisa", + "eliisa", + "eveliina", + "aila", + "aili", + "veera", + "margareta", + "elina", + "essi", + "p\u00e4ivikki", + "amanda", + "mirjami", + "kerttu", + "maarit", + "eeva", + "irene", + "kyllikki", + "mirjam", + "maritta", + "anni", + "minna", + "outi", + "ellen", + "emma", + "anu", + "annukka", + "marianne", + "irma", + "siiri", + "heli", + "riikka", + "sirkka", + "aada", + "mari", + "tuulia", + "henna", + "riitta", + "anja", + "taru", + "sini", + "birgitta", + "jonna", + "viivi", + "tiia", + "inkeri", + "venla", + "marjukka", + "juulia", + "hillevi", + "tellervo", + "aulikki", + "marja_liisa", + "satu", + "emilia", + "seija", + "tarja", + "roosa", + "paula", + "josefiina", + "sanni", + "sinikka", + "christina", + "hellevi", + "mirja", + "ulla", + "mia", + "sofia", + "suvi", + "katri", + "tuuli", + "orvokki", + "raili", + "vilhelmiina", + "noora", + "marja_leena", + "leena" + ], + "FIRST_NAME_MALE": [ + "reijo", + "valdemar", + "anssi", + "ahti", + "tuomas", + "roope", + "kauko", + "tapani", + "paavo", + "ensio", + "joonatan", + "antero", + "kari", + "pertti", + "benjamin", + "jani", + "janne", + "aarne", + "eetu", + "rasmus", + "edvard", + "peter", + "verneri", + "miika", + "pekka", + "elmeri", + "teuvo", + "heikki", + "ilari", + "anders", + "niko", + "seppo", + "daniel", + "jere", + "atte", + "toivo", + "arttu", + "riku", + "johannes", + "juuso", + "petteri", + "asko", + "aukusti", + "aaro", + "alexander", + "niklas", + "tapio", + "vesa", + "kimmo", + "toni", + "taisto", + "martti", + "jalmari", + "joonas", + "viljami", + "tommi", + "jussi", + "v\u00e4in\u00f6", + "kristian", + "raimo", + "santeri", + "eemeli", + "erkki", + "ossi", + "patrik", + "aatos", + "akseli", + "vilho", + "jesse", + "henry", + "mikael", + "oliver", + "jorma", + "kalevi", + "ville", + "kim", + "tomi", + "viljo", + "ismo", + "joona", + "joni", + "tuomo", + "emil", + "osmo", + "uolevi", + "juhani", + "ilmari", + "aleksanteri", + "elias", + "teemu", + "anton", + "einari", + "julius", + "arto", + "yrj\u00f6", + "eero", + "arvo", + "niilo", + "kustaa", + "joel", + "sakari", + "henri", + "reino", + "veikko", + "allan", + "jouni", + "jan", + "vilhelm", + "christian", + "rauno", + "leo", + "aulis", + "mauno", + "keijo", + "veeti", + "armas", + "aapo", + "valtteri", + "markus", + "kaarlo", + "otto", + "johan", + "kasper", + "lauri", + "tero", + "markku", + "matias", + "oskar", + "marko", + "lassi", + "oiva", + "pentti", + "henrik", + "sami", + "mikko", + "lasse", + "kullervo", + "aleksi", + "antti", + "onni", + "topias", + "jarkko", + "ari", + "risto", + "iisakki", + "pasi", + "sebastian", + "eerik", + "hermanni", + "samuel", + "kalle", + "olli", + "kalervo", + "esa", + "jukka", + "artturi", + "jaakko", + "simo", + "tuukka", + "taneli", + "jarmo", + "mauri", + "miro", + "eemil", + "samuli", + "veli", + "aki", + "robert", + "aaron", + "eelis", + "eino", + "erik", + "matti", + "harri", + "rainer", + "jyrki", + "aimo", + "kai", + "pauli", + "juho", + "juha", + "karl", + "olavi", + "oskari", + "tauno", + "jouko", + "samu", + "jarno", + "petri", + "jari", + "timo", + "hannu", + "henrikki", + "mika", + "esko", + "leevi", + "veijo", + "juhana", + "ilkka" + ], + "FIRST_NAME": [ + "valdemar", + "iida", + "kauko", + "paavo", + "oona", + "antero", + "benjamin", + "virpi", + "edvard", + "peter", + "heikki", + "anders", + "leila", + "niko", + "maria", + "arttu", + "aukusti", + "vesa", + "taisto", + "viljami", + "tommi", + "raimo", + "erkki", + "helena", + "eila", + "nea", + "anne", + "karoliina", + "henry", + "jorma", + "aurora", + "ville", + "viljo", + "uolevi", + "aune", + "sisko", + "terttu", + "yrj\u00f6", + "raija", + "irmeli", + "petra", + "marjaana", + "mira", + "liisa", + "terhi", + "taina", + "jan", + "annika", + "rauno", + "mauno", + "aulis", + "kaisa", + "kirsti", + "nina", + "lauri", + "julia", + "sonja", + "matias", + "marjut", + "elisabet", + "tanja", + "erika", + "anna_liisa", + "sami", + "aleksi", + "ari", + "maritta", + "outi", + "anni", + "ellen", + "anu", + "artturi", + "annukka", + "irma", + "tuukka", + "heli", + "mauri", + "samuli", + "mari", + "taru", + "jonna", + "inkeri", + "juulia", + "eelis", + "matti", + "aulikki", + "marja_liisa", + "seija", + "paula", + "kai", + "mirja", + "mia", + "tauno", + "suvi", + "orvokki", + "samu", + "mika", + "reijo", + "iiris", + "kristiina", + "teija", + "tuomas", + "roope", + "aleksandra", + "aino", + "jenna", + "saara", + "carita", + "lea", + "rasmus", + "verneri", + "alexandra", + "sanna", + "ritva", + "seppo", + "katriina", + "daniel", + "jere", + "toivo", + "jenni", + "katariina", + "aaro", + "toni", + "kimmo", + "helmi", + "joonas", + "v\u00e4in\u00f6", + "elisa", + "eija", + "miia", + "patrik", + "aatos", + "milla", + "jesse", + "mikael", + "oliver", + "maire", + "laura", + "piia", + "tuomo", + "osmo", + "teemu", + "katja", + "julius", + "sirpa", + "vuokko", + "kustaa", + "niina", + "tuulikki", + "sakari", + "henri", + "tuula", + "ilona", + "ella", + "jouni", + "christian", + "helin\u00e4", + "martta", + "otto", + "johan", + "kasper", + "elisabeth", + "lassi", + "matilda", + "aila", + "aili", + "topias", + "essi", + "p\u00e4ivikki", + "jarkko", + "maarit", + "pasi", + "mirjam", + "sebastian", + "minna", + "kalle", + "jukka", + "marianne", + "simo", + "taneli", + "jarmo", + "miro", + "eemil", + "tuulia", + "riitta", + "anja", + "viivi", + "sanni", + "christina", + "olavi", + "ulla", + "sofia", + "jarno", + "petri", + "leevi", + "noora", + "juhana", + "karl", + "anssi", + "ahti", + "hannele", + "sara", + "maaria", + "kari", + "pertti", + "p\u00e4ivi", + "janne", + "aarne", + "eetu", + "miika", + "pekka", + "lilja", + "anneli", + "elmeri", + "olivia", + "teuvo", + "kirsi", + "merja", + "vilma", + "johannes", + "alexander", + "jasmin", + "jalmari", + "jussi", + "eemeli", + "ossi", + "anna", + "kati", + "pirkko", + "marjo", + "tomi", + "emil", + "ilmari", + "esteri", + "aleksanteri", + "pauliina", + "arja", + "hanna", + "arto", + "jaana", + "eero", + "annikki", + "joel", + "linda", + "reino", + "tuija", + "irja", + "leo", + "keijo", + "veeti", + "armas", + "tiina", + "aapo", + "valtteri", + "elsa", + "airi", + "tero", + "johanna", + "oskar", + "marko", + "helvi", + "eliisa", + "eveliina", + "mikko", + "kullervo", + "veera", + "onni", + "elina", + "mirjami", + "risto", + "kerttu", + "iisakki", + "eeva", + "irene", + "kyllikki", + "eerik", + "olli", + "emma", + "veli", + "tiia", + "venla", + "aaron", + "erik", + "hillevi", + "rainer", + "jyrki", + "satu", + "emilia", + "aimo", + "pauli", + "josefiina", + "sinikka", + "juha", + "katri", + "tuuli", + "jari", + "vilhelmiina", + "henrikki", + "esko", + "tapani", + "ensio", + "joonatan", + "marketta", + "lotta", + "jani", + "marita", + "marika", + "ilari", + "kristina", + "mervi", + "margit", + "pia", + "atte", + "riku", + "kaarina", + "veijo", + "juuso", + "petteri", + "asko", + "niklas", + "tapio", + "kaija", + "maija", + "martti", + "anniina", + "kristian", + "santeri", + "sari", + "akseli", + "vilho", + "alina", + "kalevi", + "kim", + "susanna", + "linnea", + "anita", + "hilkka", + "ismo", + "joona", + "joni", + "emmi", + "juhani", + "elias", + "elli", + "heidi", + "anton", + "einari", + "arvo", + "niilo", + "krista", + "veikko", + "allan", + "marjatta", + "vilhelm", + "pirjo", + "ida", + "alisa", + "markus", + "kaarlo", + "markku", + "marja", + "oiva", + "henrik", + "pentti", + "lasse", + "antti", + "margareta", + "amanda", + "hermanni", + "samuel", + "kalervo", + "esa", + "siiri", + "jaakko", + "riikka", + "sirkka", + "aada", + "henna", + "sini", + "birgitta", + "aki", + "robert", + "marjukka", + "eino", + "harri", + "tellervo", + "roosa", + "juho", + "hellevi", + "oskari", + "jouko", + "raili", + "timo", + "hannu", + "tarja", + "marja_leena", + "leena", + "ilkka" + ], + "LAST_NAME": [ + "helin", + "rantala", + "jaakkola", + "kuusisto", + "suomalainen", + "kein\u00e4nen", + "t\u00e4htinen", + "rautio", + "hietanen", + "kangas", + "hokkanen", + "juntunen", + "huttunen", + "nuutinen", + "ahonen", + "v\u00e4is\u00e4nen", + "turpeinen", + "taipale", + "puustinen", + "lindfors", + "hartikainen", + "lindstr\u00f6m", + "eskola", + "lappalainen", + "nevala", + "sj\u00f6blom", + "virta", + "salmela", + "rauhala", + "harju", + "sallinen", + "riikonen", + "j\u00e4rvi", + "muhonen", + "halonen", + "kolehmainen", + "pesonen", + "marttinen", + "puranen", + "viitala", + "auvinen", + "lipponen", + "aaltonen", + "laiho", + "pulkkinen", + "lassila", + "helenius", + "holm", + "j\u00e4rvinen", + "gustafsson", + "tirkkonen", + "kanerva", + "j\u00e4ntti", + "liimatainen", + "miettinen", + "lampinen", + "hautala", + "jalonen", + "lehikoinen", + "k\u00e4rki", + "kujala", + "reinikainen", + "ylitalo", + "m\u00e4ntyl\u00e4", + "heinonen", + "peltonen", + "vuorinen", + "k\u00e4m\u00e4r\u00e4inen", + "yl\u00f6nen", + "kivim\u00e4ki", + "paavilainen", + "autio", + "sutinen", + "p\u00e4\u00e4kk\u00f6nen", + "eklund", + "kivel\u00e4", + "koskinen", + "parviainen", + "hiltunen", + "huotari", + "rytk\u00f6nen", + "kainulainen", + "nurminen", + "v\u00e4yrynen", + "j\u00e4rvel\u00e4", + "niemi", + "holmberg", + "riihim\u00e4ki", + "soini", + "pelkonen", + "parkkinen", + "karjalainen", + "koivula", + "karhunen", + "koivisto", + "puhakka", + "simonen", + "saari", + "tiihonen", + "peltola", + "ven\u00e4l\u00e4inen", + "valkama", + "sepp\u00e4nen", + "m\u00e4enp\u00e4\u00e4", + "turunen", + "ketola", + "ollikainen", + "haverinen", + "tuomi", + "takala", + "saarela", + "nissinen", + "tikka", + "moilanen", + "ruotsalainen", + "lahtinen", + "moisio", + "alanen", + "h\u00e4m\u00e4l\u00e4inen", + "palom\u00e4ki", + "immonen", + "pajunen", + "heikkil\u00e4", + "ruuskanen", + "markkanen", + "laakkonen", + "sainio", + "kettunen", + "honkanen", + "heino", + "holopainen", + "ojanen", + "lehtola", + "korhonen", + "pasanen", + "anttila", + "pitk\u00e4nen", + "pekkala", + "backman", + "paananen", + "kuusela", + "jansson", + "valtonen", + "vuori", + "matilainen", + "r\u00e4s\u00e4nen", + "komulainen", + "kallio", + "lehto", + "pietil\u00e4", + "aho", + "ahokas", + "r\u00e4is\u00e4nen", + "keskitalo", + "salomaa", + "eronen", + "korpela", + "sirvi\u00f6", + "jokinen", + "laukkanen", + "kulmala", + "kaikkonen", + "soininen", + "syrj\u00e4l\u00e4", + "tarvainen", + "viljanen", + "v\u00e4lim\u00e4ki", + "lindqvist", + "haapaniemi", + "laine", + "lammi", + "tanskanen", + "saastamoinen", + "kyll\u00f6nen", + "m\u00e4ki", + "tiainen", + "tolvanen", + "lindholm", + "luukkonen", + "toivanen", + "kauppinen", + "heiskanen", + "rossi", + "nieminen", + "uusitalo", + "rintala", + "lindberg", + "rinne", + "laakso", + "keskinen", + "toivonen", + "jauhiainen", + "kuosmanen", + "niemel\u00e4", + "kosonen", + "eskelinen", + "kiuru", + "salmi", + "kurki", + "huovinen", + "oksanen", + "hyv\u00f6nen", + "kantola", + "huuskonen", + "l\u00e4hteenm\u00e4ki", + "berg", + "hirvonen", + "salminen", + "malinen", + "kari", + "kumpulainen", + "mikkonen", + "hautam\u00e4ki", + "nurmi", + "viitanen", + "partanen", + "lilja", + "sihvonen", + "nyk\u00e4nen", + "halme", + "pekkarinen", + "kilpel\u00e4inen", + "per\u00e4l\u00e4", + "hietala", + "mikkola", + "juvonen", + "laaksonen", + "tuovinen", + "uotila", + "voutilainen", + "haapala", + "karvonen", + "vuorela", + "m\u00e4nnist\u00f6", + "kukkonen", + "salonen", + "kankaanp\u00e4\u00e4", + "r\u00e4ty", + "alanko", + "leinonen", + "laurila", + "oinonen", + "hakkarainen", + "koponen", + "kauppila", + "sepp\u00e4", + "manninen", + "elo", + "kivinen", + "makkonen", + "pehkonen", + "rajala", + "koski", + "salo", + "forsman", + "blomqvist", + "karttunen", + "taskinen", + "h\u00e4nninen", + "nyman", + "vesterinen", + "koskela", + "jaatinen", + "h\u00e4rk\u00f6nen", + "j\u00e4rvenp\u00e4\u00e4", + "j\u00e4\u00e4skel\u00e4inen", + "valkonen", + "aro", + "mattila", + "oikarinen", + "latvala", + "m\u00e4\u00e4tt\u00e4", + "meril\u00e4inen", + "peltoniemi", + "varis", + "marttila", + "k\u00e4rkk\u00e4inen", + "linna", + "rantanen", + "lindroos", + "hyttinen", + "timonen", + "hannula", + "sir\u00e9n", + "niiranen", + "leskinen", + "ronkainen", + "mononen", + "r\u00f6nkk\u00f6", + "martikainen", + "piirainen", + "p\u00f6ll\u00e4nen", + "johansson", + "ranta", + "m\u00e4kinen", + "kemppainen", + "v\u00e4\u00e4n\u00e4nen", + "suhonen", + "m\u00e4kel\u00e4", + "holmstr\u00f6m", + "kivist\u00f6", + "hyv\u00e4rinen", + "nousiainen", + "lehtim\u00e4ki", + "sepp\u00e4l\u00e4", + "helminen", + "lehtonen", + "nikula", + "pennanen", + "myllym\u00e4ki", + "kuronen", + "paavola", + "kokkonen", + "ihalainen", + "anttonen", + "heikkinen", + "lindgren", + "tikkanen", + "tuominen", + "pakarinen", + "andersson", + "airaksinen", + "nylund", + "ollila", + "sipil\u00e4", + "lehtinen", + "vartiainen", + "kokko", + "penttinen", + "pirinen", + "pohjola", + "matikainen", + "holappa", + "lahti", + "haataja", + "huhtala", + "ikonen", + "lankinen", + "silvennoinen", + "tolonen", + "ojala", + "asikainen", + "laitinen", + "koivunen", + "ker\u00e4nen", + "eriksson", + "jokela", + "korpi", + "nyberg", + "konttinen", + "nevalainen", + "haapanen", + "simola", + "rissanen", + "karlsson", + "saarinen", + "penttil\u00e4", + "leino", + "repo", + "raatikainen", + "k\u00e4hk\u00f6nen", + "mustonen", + "rautiainen", + "antikainen", + "ahola", + "tamminen", + "h\u00e4kkinen", + "eloranta", + "kuisma", + "karhu", + "kovanen", + "ryyn\u00e4nen", + "sillanp\u00e4\u00e4", + "savolainen", + "liukkonen", + "virtanen", + "erkkil\u00e4", + "kinnunen", + "kiviniemi", + "haavisto", + "alatalo", + "kortelainen", + "koistinen", + "karppinen", + "henriksson", + "suominen", + "ylinen", + "hakala", + "niskanen", + "lepp\u00e4nen", + "tervo", + "jussila", + "karvinen", + "mattsson", + "vainio", + "gr\u00f6nroos", + "lepist\u00f6", + "aalto", + "luoma", + "hyt\u00f6nen" + ], + "OTHER_PRONOUN": [ + "it" + ], + "LAST_NAME_MALE": [], + "LAST_NAME_FEMALE": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "prioritar": "abb", + "abbedissa": "johtomies", + "n\u00e4yttelij\u00e4t\u00e4r": "toiminnan_mies", + "t\u00e4ti": "enopuoli", + "vapaaherratar": "vapaaherra", + "paronitar": "paroni", + "morsian": "sulhanen", + "bride": "sulho", + "liikenainen": "bisnesmies", + "bisnesnainen": "liikemies", + "linnunpoika": "j\u00e4b\u00e4", + "untuvikko": "hemmo", + "kananpoika": "dude", + "poussin": "dude", + "linnunpoikanen": "j\u00e4pik\u00e4s", + "poulette": "heebo", + "lehmitytt\u00f6": "karjanhoitaja", + "herttuatar": "herttua", + "keisarinna": "pikkuriikinkukkokehr\u00e4\u00e4j\u00e4", + "maharani": "saturnia_pavonia", + "\u0161aahitar": "keisari", + "nainen": "miehitt\u00e4\u00e4", + "naaras": "mieshenkil\u00f6", + "naispuolinen": "miespuolinen", + "nais": "male", + "gal": "tukea_k\u00f6ydell\u00e4", + "likka": "guy", + "nuori_nainen": "tukea_vaijerilla", + "modi": "guy", + "lassie": "poju", + "kotiopettajatar": "maaherra", + "pojantyt\u00e4r": "tytt\u00e4renpoika", + "tytt\u00e4rentyt\u00e4r": "lapsenlapsi", + "iso\u00e4iti": "ukki", + "h\u00e4nen": "heid\u00e4n", + "p\u00e4\u00e4henkil\u00f6": "heeros", + "sankaritar": "sankari", + "uuma": "heid\u00e4n", + "em\u00e4nt\u00e4": "efendi", + "lady": "efendi", + "vuokraem\u00e4nt\u00e4": "vuokrais\u00e4nt\u00e4", + "vuokranantaja": "vuokrais\u00e4nt\u00e4", + "piika": "miespalvelija", + "palvelijatar": "miespalvelija", + "markiisitar": "marquis", + "hierojatar": "hieroja", + "hieroja": "miespuolinen_hieroja", + "naispuolinen_hieroja": "hieroja", + "missata": "sir", + "my\u00f6h\u00e4sty\u00e4": "sir", + "olla_p\u00e4\u00e4sem\u00e4tt\u00e4": "sir", + "menn\u00e4_ohi": "sir", + "olla_vailla": "sir", + "j\u00e4\u00e4d\u00e4_vaille": "sir", + "miss_a": "sir", + "ampua_ohi": "sir", + "olla_ymm\u00e4rt\u00e4m\u00e4tt\u00e4": "sir", + "olla_kadoksissa": "sir", + "valtiatar": "p\u00e4\u00e4st\u00e4_jyv\u00e4lle_jstak", + "hoivata": "ayr", + "hiiva": "pid", + "olla_\u00e4itin\u00e4": "ayr", + "mam": "johtomies", + "ylisuojella": "siitt\u00e4j\u00e4", + "matrix": "siitt\u00e4j\u00e4", + "naispuolinen_vanhempi": "pid", + "bh": "hra", + "rva": "hra", + "ms": "tn", + "sisarentyt\u00e4r": "veljenpoika", + "veljentyt\u00e4r": "veljenpoika", + "nunna": "monk", + "nun": "monk", + "naispoliisi": "konstaapeli", + "papitar": "flamen", + "pr\u00edncipe": "prince", + "prinsessa": "ruhtinas", + "princessa": "prince", + "kaljurotta": "kuningas", + "naishallitsija": "king", + "tulla_kuningattareksi": "kingi", + "sultana": "king", + "tehd\u00e4_sotilaasta_kuningatar": "king", + "buumi": "indra", + "akkapari": "kunkkupari", + "queens": "kuninkaiden_kirja", + "systir": "veriveli", + "sour": "veli", + "sisko": "veli", + "sisar": "taina", + "velhotar": "taikuri", + "vanhapiika": "poikamies", + "puolestapuhuja": "\u00e4\u00e4nitorvi", + "tyt\u00e4rpuoli": "poikapuoli", + "\u00e4itipuoli": "is\u00e4puoli", + "lentoemo": "taloudenhoitaja", + "lentoem\u00e4nt\u00e4": "stuertti", + "tarjoilijatar": "odottaja", + "naispuolinen_tarjoilija": "odottaja", + "j\u00e4tt\u00e4\u00e4_leskeksi": "leskimies", + "vidua": "leski", + "leskinainen": "leskimies", + "vaimo": "siippa", + "naimisissa_oleva_nainen": "aviomies", + "aviovaimo": "siippa", + "aikuinen_nainen": "miehitt\u00e4\u00e4", + "nisu": "man", + "virino": "miehitt\u00e4\u00e4", + "fema": "man", + "stara": "man", + "valkoinen_nainen": "valkoinen_mies", + "valkoinen_mies": "valkoinen_nainen", + "valkoihoinen": "valkoinen_nainen" + }, + "other_gender_swap": { + "heit\u00e4": "h\u00e4nen", + "heid\u00e4t": "h\u00e4nen", + "heilt\u00e4": "h\u00e4nen", + "heill\u00e4": "h\u00e4nen", + "y\u00f6n_pedot": "h\u00e4nen", + "heille": "h\u00e4nen", + "uk": "h\u00e4nen", + "heid\u00e4n": "uuma", + "niiden": "h\u00e4nen", + "luri": "h\u00e4nen", + "essi": "h\u00e4n", + "ii": "h\u00e4n", + "epi": "h\u00e4n", + "h\u00e4n": "epi", + "he": "ii", + "elli": "essi", + "h\u00e4nelle": "heilt\u00e4", + "h\u00e4nest\u00e4": "heill\u00e4", + "h\u00e4neksi": "heill\u00e4", + "isti": "heill\u00e4", + "h\u00e4neen": "heill\u00e4", + "sini": "heid\u00e4n", + "seine": "heid\u00e4n", + "uuma": "heid\u00e4n", + "siis": "heid\u00e4n", + "h\u00e4nen": "heid\u00e4n" + }, + "en_pronoun2gender": { + "they": [ + "homoseksuaali", + "homoseksuaalinen", + "biseksuaalinen", + "homofiili", + "transgender", + "muunsukupuolinen", + "biseksuaali" + ], + "he": [ + "mieshenkil\u00f6", + "telttanaru", + "miespaha", + "hemmo", + "ahavoitua", + "guy", + "herrasmies", + "j\u00e4pik\u00e4s", + "tukik\u00f6ysi", + "pelinappula", + "koiras", + "sierettym\u00e4", + "nahkasuojukset", + "tukikaapeli", + "heebo", + "pikkupoika", + "j\u00e4b\u00e4", + "aikuinen_mies", + "tukea_vaijerilla", + "jalu", + "kolli", + "uros", + "man", + "poju", + "little_boy", + "dude", + "halkeilla", + "male", + "mansaari", + "tukea_k\u00f6ydell\u00e4", + "miehitt\u00e4\u00e4", + "miespuolinen" + ], + "she": [ + "virino", + "maiden", + "pieni_tytt\u00f6", + "nuori_nainen", + "ampua_ohi", + "tytt\u00f6nen", + "missata", + "petite", + "olla_vailla", + "daami", + "nais", + "poussin", + "yl\u00e4luokkainen_nainen", + "nainen", + "aikuinen_nainen", + "lassie", + "olla_kadoksissa", + "piika", + "nisu", + "stara", + "hieno_nainen", + "typykk\u00e4", + "sis\u00e4kk\u00f6", + "kiltsi", + "kauniimpi_sukupuoli", + "senorita", + "gal", + "em\u00e4nt\u00e4", + "my\u00f6h\u00e4sty\u00e4", + "homoseksuaalinen_nainen", + "kimma", + "neito", + "lady", + "olla_ymm\u00e4rt\u00e4m\u00e4tt\u00e4", + "neitonen", + "menn\u00e4_ohi", + "tytt\u00f6lapsi", + "naispuolinen", + "j\u00e4\u00e4d\u00e4_vaille", + "naaras", + "pikkutytt\u00f6", + "likka", + "kotiapulainen", + "miss_a", + "palvelijatar", + "lesboslainen", + "olla_p\u00e4\u00e4sem\u00e4tt\u00e4", + "modi", + "fema", + "lesbolainen" + ] + }, + "en_pronoun2pronoun": { + "he": [ + "h\u00e4neksi", + "siis", + "h\u00e4nelle", + "he", + "uuma", + "sini", + "isti", + "seine", + "h\u00e4nest\u00e4", + "elli", + "h\u00e4neen", + "h\u00e4nen", + "itsens\u00e4", + "h\u00e4n" + ], + "she": [ + "uuma", + "h\u00e4nen", + "itsens\u00e4", + "h\u00e4n" + ], + "they": [ + "essi", + "heill\u00e4", + "heid\u00e4t", + "niiden", + "heille", + "y\u00f6n_pedot", + "heit\u00e4", + "ii", + "heid\u00e4n", + "heilt\u00e4", + "luri", + "uk", + "epi" + ], + "it": [ + "bt", + "ties", + "uuma", + "ett\u00e4", + "ky", + "t\u00e4m\u00e4", + "niit\u00e4", + "it", + "esso", + "n\u00e4m\u00e4", + "ovi", + "itsens\u00e4" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/fil.json b/data_tooling/pii_processing/ontology/data/fil.json new file mode 100644 index 0000000..32621b9 --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/fil.json @@ -0,0 +1,1072 @@ +{ + "QUANTITY": [ + "dalawampo", + "di_angkop_na_hatimbilang", + "limandaan", + "pariugat", + "beintyuno", + "dolyar", + "g", + "buyak", + "pangita", + "pound", + "beintikuwatro", + "esterlina", + "pangunahing_bilang", + "taluugat", + "beintitres" + ], + "PUBLIC_FIGURE": [ + "henry_cavendish", + "hru\u0161\u010d\u00ebv", + "benjamin_franklin", + "martin_buber", + "akira_kurosawa", + "noah_webster", + "heinrich_hertz", + "giovanni_boccaccio", + "che_guevara", + "c", + "maria_callas", + "henrik_ibsen", + "mary_shelley", + "marcello_malpighi", + "david_livingstone", + "andrzej_wajda", + "jan_van_eyck", + "richard_burton", + "douglas_macarthur", + "mary_wollstonecraft", + "maria_magdalena", + "anna_pavlova", + "winston_churchill", + "johannes_diderik_van_der_waals", + "josephus", + "paul_mccartney", + "francis_crick", + "isaac_newton", + "victor_hugo", + "edwin_hubble", + "edward_gibbon", + "george_burns", + "george_harrison", + "george_orwell", + "richard_wagner", + "pancho_villa", + "marie_curie", + "michael_jackson", + "thomas_hobbes", + "maximian", + "david", + "galileo_galilei", + "jane_goodall", + "chaim_weizmann", + "robert_koch", + "joseph_goebbels", + "john_steinbeck", + "edmund_hillary", + "vincent_van_gogh", + "richard_hooker", + "anne_boleyn", + "thomas_paine", + "liliuokalani", + "emiliano_zapata", + "yuri_gagarin", + "marie_antoinette", + "giuseppe_verdi", + "tagalabos", + "gottlieb_daimler", + "frank_sinatra", + "abel_tasman", + "katharine_hepburn", + "henri_becquerel", + "henri_matisse", + "louis_pasteur", + "theodosius_i", + "hugo_grotius", + "j_b_s_haldane", + "saladin", + "sarah_bernhardt", + "t_s_eliot", + "charles_de_gaulle", + "y", + "ralph_bunche", + "charles_lindbergh", + "prangka", + "samuel_barber", + "joseph_stalin", + "f", + "ludwig_wittgenstein", + "dante_alighieri", + "samuel_de_champlain", + "giacomo_puccini", + "edward_fitzgerald", + "fridtjof_nansen", + "primadona", + "james_dean", + "joseph_priestley", + "nicolas_poussin", + "james_naismith", + "oscar_wilde", + "j_d_salinger", + "tapetan", + "laurence_olivier", + "christiaan_eijkman", + "francis_bacon", + "pete_seeger", + "a", + "david_ricardo", + "charlie_parker", + "immanuel_kant", + "james_franck", + "william_crookes", + "weber", + "albert_schweitzer", + "titus", + "johannes_kepler", + "max_planck", + "julio_iglesias", + "john_bardeen", + "nietzsche", + "scott_joplin", + "sarah_siddons", + "canberra", + "edward_jenner", + "moises", + "oliver_hardy", + "graham_greene", + "igor_stravinsky", + "henri", + "jan_swammerdam", + "william_herschel", + "mikhail_baryshnikov", + "montesquieu", + "arthur_rubinstein", + "niels_bohr", + "bertrand_russell", + "michael_faraday", + "walt_disney", + "gabriel_lippmann", + "jane_austen", + "charles_laughton", + "phil_collins", + "alice_paul", + "robert_redford", + "richard_feynman", + "wolfgang_pauli", + "marcel_proust", + "homo_heidelbergensis", + "elizabeth_taylor", + "anne_sullivan", + "paul_robeson", + "john_milton", + "indira_gandhi", + "jane_seymour", + "george_gershwin", + "alberto_giacometti", + "alfred_nobel", + "jesse_owens", + "marco_polo", + "daniel_bernoulli", + "joseph_henry", + "boris_karloff", + "gottfried_leibniz", + "phillis_wheatley", + "hans_christian_andersen", + "hideyo_noguchi", + "pieter_zeeman", + "pablo_picasso", + "natalie_wood", + "kurt_weill", + "christiaan_huygens", + "lucille_ball", + "o", + "saint_louis_missouri", + "adam_smith", + "diaghilev", + "jean_harlow", + "karl_marx", + "friedrich_nietzsche", + "i", + "pedro", + "jimmy_durante", + "asahan", + "nikola_tesla", + "al_capone", + "mel_gibson", + "john_locke", + "joseph_marie_jacquard", + "dalaw\u00e1", + "helen_keller", + "ingrid_bergman", + "valentina_tereshkova", + "h_g_wells", + "walt_whitman", + "ludwig_boltzmann", + "carl_jung", + "richard_wright", + "adolf_hitler", + "james_d_watson", + "pagkabingi", + "joseph_haydn", + "george_boole", + "daniel_boone", + "robert_boyle", + "ralph_richardson", + "1", + "rosa_parks", + "x", + "vladimir_putin", + "jacob", + "giuseppe_mazzini", + "anne_hathaway", + "g", + "pintakasi", + "arthur_schopenhauer", + "james_cagney", + "martin_heidegger", + "christopher_columbus", + "arnold_schoenberg", + "r", + "andrew_jackson", + "louis_armstrong", + "pulo_ng_san_martin", + "steven_spielberg", + "thomas_gainsborough", + "giuseppe_garibaldi", + "patricio_ng_irlanda", + "alexandre_dumas", + "thomas_carlyle", + "johannes_gutenberg", + "thomas_malthus", + "emma_goldman", + "james_mill", + "putin", + "robert_hooke", + "karl_popper", + "john_calvin", + "peter_sellers", + "homo_rhodesiensis", + "charles_fourier", + "marcus_aurelius", + "peter_o'toole", + "william_shockley", + "mahatma_gandhi", + "jules_verne", + "paul_newman", + "jackson_pollock", + "dayan", + "mahiyain", + "john_lennon", + "charlie_chaplin", + "kuwako", + "hilagyo", + "kablekotse", + "stanley_kubrick", + "john_huston", + "james_watt", + "ronald_reagan", + "homo", + "frederick_douglass", + "dalubgubat", + "pedro_ang_dakila_ng_rusya", + "david_hilbert", + "oliver_cromwell", + "rex_harrison", + "woodrow_wilson", + "margaret_sanger", + "marcus_antonius", + "don_quixote", + "dabaw", + "jim_henson", + "ernest_hemingway", + "george_westinghouse", + "nelson_mandela", + "al_gore", + "hans_bethe", + "roald_amundsen", + "charles_dickens", + "ella_fitzgerald", + "fats_waller", + "bessie_smith", + "jackie_robinson", + "johnny_cash", + "joseph_mccarthy", + "georges_cuvier", + "william_harvey", + "walter_scott", + "vladimir_lenin", + "robert_peary", + "jonathan_swift", + "albert_einstein", + "thomas_edison", + "chiang_kai_shek", + "claude_bernard", + "t" + ], + "PLANT": [ + "kanipay", + "hibiscus_syriacus", + "karanda", + "kukuyuli", + "makahiya", + "krisantemo", + "alerses", + "solanaceae", + "laurus_nobilis", + "sikomoro", + "asinorya", + "letsugas", + "sapinit", + "seresa", + "singkamas", + "apulid", + "sakura", + "kranberya", + "petsay", + "kainito", + "gumamela", + "payumpong", + "tangantangan", + "bayabas", + "sarsamora", + "kamias", + "dalubsining", + "asanorya", + "almasiga", + "repolyo", + "karot", + "balbalut", + "kawayan", + "mirasol", + "dahunan", + "yedra", + "remolatsa", + "alkampor", + "nogales", + "warit", + "monggo", + "alangilan", + "mustasa", + "sirwelas", + "kalamo", + "actinidia_deliciosa", + "agrimonya", + "lobolobohan", + "kalamismis", + "nasturtium", + "magnolya", + "dilambuwaya", + "lansina", + "kaimito", + "koliplor", + "aliso", + "amapola", + "ampalaya", + "hirasol", + "sigarilyas", + "kamyas" + ], + "ANIMAL": [ + "sakit_na_ebola", + "karag", + "banyas", + "kulyawan", + "mamalya", + "galapago", + "palaka", + "anuran", + "black_widow", + "tangginggi", + "billy_elliot", + "susulbot", + "managat", + "ardilya", + "buharo", + "kilyawan", + "kardelina", + "butanding", + "tasugo", + "tripang", + "garsa", + "bangk\u00e2", + "pamurulan", + "kasaykasay", + "galgo", + "gulyasan", + "kalabaw", + "malabiga", + "parikparik", + "mink", + "dungon", + "mutit", + "manok", + "konehilyo", + "kamamarung", + "daganlulundag", + "anwang", + "mandadangkal", + "tungkod", + "putakti", + "falcon", + "polilya", + "limbas", + "manlilingkis", + "lulumbo", + "salungo", + "taguan", + "lapati", + "tanigi", + "balagbagan", + "singsingpari", + "mandarangkal", + "sable", + "babaero", + "tambakol", + "arthropoda", + "alse", + "bakaw", + "marsopa", + "dagang_puti", + "bingkungan", + "sambasamba", + "kuwago", + "manunubing", + "katubaghay", + "kondor", + "taningue", + "nuwang", + "sagay", + "taliptip", + "dumagat", + "sasamba" + ], + "DISEASE": [ + "sars", + "kalamayo", + "butlig", + "bululos", + "kabuntisan", + "sugat", + "tahip", + "almuranas", + "daragis", + "siyok", + "taghiyawat", + "eskorbuto", + "kubusdiin", + "deliryo", + "anthrax", + "sipilis", + "kombulsyon", + "rabies", + "tomayna", + "katabaan", + "sugapa", + "aktinomikosis", + "bulutong", + "matulog", + "kiyawa", + "halintubig", + "poison_ivy", + "suko", + "salot", + "kuliti", + "dengge", + "sigok", + "lagatak", + "ulanag", + "trangkaso", + "bisil", + "pangiki", + "alibadbad", + "balaod", + "tagulabay", + "stroke", + "bubuwit", + "tugano", + "yedra", + "demensiya", + "tagihawat", + "kasalimuutan", + "human_papillomavirus", + "ulsera", + "blacklash", + "dimarim", + "silag", + "katim", + "para", + "katarata", + "tibi", + "kastanyas", + "kisay", + "kurarap", + "pananakit", + "hinekomastiya", + "galactosemia", + "ansisilaw", + "karsinoma", + "sigam", + "katas", + "tulog", + "kankroid", + "malakimpali", + "peklat", + "rakitis", + "herpes", + "balariid", + "pangangandi", + "pertilidad", + "pamumunglo", + "balakubak", + "ganggrena", + "pamamayat", + "hirandam", + "pamamanas", + "panunubigbato", + "suba", + "beke", + "parapleya", + "sirosis", + "pigsa", + "kagat", + "bingot", + "gotakural", + "burog", + "paltos", + "radiyasyon", + "sabanyon", + "rabis", + "african_trypanosomiasis", + "altapresyon", + "rubella", + "pain", + "strain", + "bukol", + "mularan", + "malisok", + "paghihimula", + "himula", + "paninilaw", + "kahalmanan", + "sawan", + "pantal", + "kulugo", + "klorosis", + "lalak", + "palasakitan", + "makabanli", + "nasakitan", + "istarbasyon", + "malaking_talon", + "malarya", + "kuru", + "kalawang", + "paglalak", + "siyatika", + "awanggana", + "balinguyngoy", + "dengue", + "kanggrena", + "lipak", + "kirot", + "kanipay", + "kanser", + "materyalismo", + "butig", + "gapong", + "salmonella", + "paglurandugo", + "krup", + "masakit" + ], + "RACE": [ + "filipino", + "dampuluanin", + "yuropin", + "kawkasin", + "aprikahin" + ], + "PRODUCT": [ + "pigang", + "ama_namin", + "the_hunger_games", + "justin_bieber", + "konehilyo", + "new_zealand", + "pangkalawakan", + "benditahan", + "tagikaw", + "karapatang_pantao", + "the_star_spangled_banner", + "don_quixote", + "puno_ng_pasko", + "bunsuran", + "boxing_day", + "panugtog", + "malaking_tabo", + "daang_sukol", + "tatluhing_sukod", + "taghikaw", + "tatlong_kaharian" + ], + "ORG": [ + "shinto", + "wicca", + "pangangalagang_pangkalusugan", + "aa", + "lapian", + "nasa", + "partidong_politiko", + "batas_pandaigdig", + "isi", + "ang", + "punong_bangko", + "dalubsakahan", + "pagsasaka", + "partido_berde", + "san_francisco", + "un", + "daung_daungan", + "pangangalakal", + "kapisanan_ng_mga_manggagawa", + "pambansang_asemblea_ng_timog_korea", + "kulisaw", + "partidong_nazi", + "kaguro", + "paaralan", + "can_tho", + "talisikan", + "talumpon", + "samahang_manggagawa", + "bangko_sentral", + "dalubhasaan", + "mula_kay_kristo", + "banal_na_mag_anak", + "taoismo", + "krus_na_pula", + "libay", + "ilog_dilaw", + "ilog_na_dilaw", + "ingatang_yaman", + "rabindranath_tagore", + "kaisahan", + "santa_helena", + "hainismo", + "at_iba_pa", + "white_house", + "gusaling_panlunsod", + "mababang_kapulungan", + "punumbangko", + "halipsusi", + "chiang_rai", + "kataas_taasang_hukuman", + "bagong_buwan", + "po", + "addis_ababa", + "san_tomas", + "patay_na_bulan", + "taluhog", + "pooh_garcia", + "palagamutan", + "daulat", + "simbahang_katolika_romana", + "alilisan", + "sturmabteilung", + "bahay_pamahalaan", + "los_angeles", + "katuruan", + "gansuwa", + "sa", + "simbahang_katolika", + "linangan", + "al_ain", + "hukbong_himpapawid", + "koreo", + "dagat_pula", + "panggitnang_uri", + "bisperas_ng_bagong_taon" + ], + "DATE": [ + "mula_kay_kristo", + "dog_days", + "magaganap", + "kalahatimbuhay", + "katandaan", + "samakalawa", + "bagong_bulan", + "todos_los_santos", + "taning", + "kapaskuhan", + "panghinaharap", + "bulang_nagbibilog" + ], + "PERSON": [ + "an_an", + "al_gore", + "h_g_wells", + "kim_yoo_jin", + "george_v", + "seleucus_i_nicator", + "dr_watson" + ], + "FAC": [ + "arnold_schoenberg", + "palanguyan", + "cheongwadae", + "san_bonifacio", + "santa_lucia", + "koreo" + ], + "JOB": [ + "apungot", + "mangkakalot", + "alkalde", + "koredor", + "drogista", + "manghuhuwad", + "mamumuslit", + "dalubpagkain", + "manananggol", + "lupainin", + "manlalaro", + "manggagawa", + "sakristan", + "mariskal", + "mandaragat", + "pansamantala", + "paladiglap", + "sulong", + "gintay", + "dalubpakain", + "kalsunsilyo", + "maninikap", + "sisiwa", + "manlililok", + "tindera", + "pangulo", + "patnubay", + "palasakit", + "para", + "kasangguni", + "kumpay", + "propesor", + "piyon", + "mangangalalang", + "kahero", + "busabos", + "doorman", + "mananahi", + "kumadrona", + "pamilyar", + "dalubsigwasan", + "trabahador", + "laksamana", + "palamata", + "langib", + "kalupon", + "basahan", + "stroke", + "mananayaw", + "maninigmo", + "pandaw", + "kasama", + "sarilinin", + "mambabasa", + "panamtam", + "mamay", + "mate", + "ebanista", + "dalubsulip", + "pamuno", + "karagatnin", + "maykapal", + "guro", + "eskirol", + "kataluna", + "manggugupit", + "kartero", + "rabino", + "ulungguro", + "dalubsakit", + "hardinera", + "malim", + "paladugo", + "mandirigma", + "magsasaka", + "pakusa", + "mananaggol", + "galaw", + "malahakan", + "tungkulanin", + "dalubtala", + "karpintero", + "manununig", + "manlilipad", + "messenger", + "palapuso", + "sitolohiya", + "galod", + "mangungulti", + "palabalat", + "barbero", + "mangangalap", + "kalihim", + "manunulat", + "siyentipiko", + "estibador", + "bombero", + "magkakahoy", + "dalubgubat", + "alipin", + "dalubguro", + "rehente", + "hardinero", + "parasyutista", + "serip", + "manginginag", + "dalubturo", + "lingkurang_bayanhin", + "mangongondola" + ], + "LOCATION": [ + "estados_unidos", + "punumbangko", + "sint_maarten", + "lunduyang_bangko", + "cape_verde", + "bundok_carmelo", + "white_house", + "almasen", + "portoriko", + "hukbong_panghimpapawid", + "bundok_ng_mga_olibo", + "estados_unidos_ng_amerika", + "usa", + "sri_lanka", + "bayanhing_agsikapan", + "the_rolling_stones", + "santa_klaus", + "santa_elena_ascension_at_tristan_da_cunha", + "kapulungang_pambansa", + "trois_rivi\u00e8res_qu\u00e9bec", + "kabo_berde", + "heitor_villa_lobos", + "al_ain", + "santa_claus" + ], + "POLITICAL_PARTY": [ + "lapian", + "labor", + "partido_komunista" + ], + "BIO_CHEM_ENTITY": [ + "betsin", + "bitsin" + ], + "FOOD": [ + "tumanan", + "payap", + "pastelerya", + "kundol", + "malasado", + "tumakas", + "kayena", + "balkutsa", + "sodium_chloride", + "tinto", + "paayap", + "sorbetes", + "toyo", + "chile", + "pinyon", + "magpabaya", + "ilang", + "panghimagas", + "limonada", + "kending_baston", + "meryenda", + "pamutat", + "tanghalian", + "balikutsa", + "abitsuwelas" + ], + "RELIGION": [ + "zen", + "shinto", + "islam", + "katarismo", + "wicca" + ], + "GPE": [ + "gawaimbayan", + "white_house", + "espiritu_santo", + "sint_maarten", + "karapatang_pantao", + "hagia_sophia", + "san_cristobal", + "ina_ng_pitong_hapis", + "pakayan", + "bagong_tipan", + "dagat_na_pula" + ], + "SOC_ECO_CLASS": [ + "labor", + "samuray", + "pagsasaka", + "samurai", + "dalubsakahan", + "butikasan", + "lipunan", + "kubliphay", + "kamaharlikahan" + ], + "LANGUAGE": [ + "unggaro", + "portuges", + "kastila", + "olandes", + "sundanes", + "pali", + "ganda", + "manx", + "munggolin", + "galiyego", + "hindi", + "pagsasalita", + "malayo", + "esperanto", + "islandes", + "katalan", + "malay", + "tagalog", + "irlandes", + "kastilain", + "heyorhiyano", + "pinlandes", + "tonga" + ], + "PERSON_PRONOUN": [ + "yumi", + "i", + "kaniya", + "dulangan", + "me", + "dukalan" + ], + "EVENT": [ + "gising", + "baliksuwa" + ], + "GENDER": [ + "babae", + "neneng", + "lalaki" + ], + "RELIGION_MEMBER": [ + "kristyano", + "mormon", + "makakristo", + "totoy", + "franciscano", + "kuwakero" + ], + "TITLE": [ + "misis" + ], + "LAW": [ + "pamparusang_kabatasan", + "sangay_tagapaghukom" + ], + "UNION": [ + "kaisahan" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "bibi": "tiu", + "dukesa": "duke", + "gintay": "gobernador", + "heroina": "bayani", + "damo": "panginoon", + "markesa": "markes", + "lakambini": "prinsipe", + "dayangdayang": "ang_prinsipe", + "prinsesa": "ang_prinsipe", + "danaus_gilippus": "indra", + "reyna": "walo", + "haribini": "walo", + "hariginang": "indra", + "queens": "mga_hari", + "siya": "baginda", + "kaniya": "siya", + "niya": "baginda", + "way": "kapatid_na_lalaki", + "kakak": "totoy", + "abla": "totoy", + "pindangga": "baguntao", + "inang_panguman": "amang_pangaman", + "lumot": "amang_pangaman", + "madrasta": "amang_pangaman", + "bini": "esposo", + "esposa": "lalaking_asawa", + "babaeng_asawa": "esposo", + "wicca": "asbang", + "mananagisama": "asbang", + "mangkukulam": "asbang", + "barera": "lalaki", + "babae": "lalaki", + "lalaki": "dalaga", + "batang_lalaki": "dalaga" + }, + "other_gender_swap": {}, + "en_pronoun2gender": { + "they": [ + "bakla" + ], + "he": [ + "ginoo", + "lalaki", + "batang_lalaki" + ], + "she": [ + "kakak", + "lesbya", + "binibini", + "batang_babae", + "abla", + "babae", + "damo", + "barera", + "dalaga" + ] + }, + "en_pronoun2pronoun": { + "he": [ + "siya", + "baginda" + ], + "she": [ + "niya", + "siya", + "kaniya" + ], + "they": [ + "suya" + ], + "it": [ + "kuwa" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/fj.json b/data_tooling/pii_processing/ontology/data/fj.json new file mode 100644 index 0000000..cedf72d --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/fj.json @@ -0,0 +1,47 @@ +{ + "PUBLIC_FIGURE": [ + "jisu" + ], + "PRODUCT": [ + "na_masu" + ], + "ORG": [ + "va", + "na_lotu_i_jisu_karisito_ni_yalododonu_edaidai" + ], + "ANIMAL": [ + "vivini" + ], + "PLANT": [ + "kareti" + ], + "JOB": [ + "kalavo" + ], + "DISEASE": [ + "veivakararawataki" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": {}, + "other_gender_swap": {}, + "en_pronoun2gender": {}, + "en_pronoun2pronoun": { + "he": [ + "koya" + ], + "she": [ + "koya" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/fo.json b/data_tooling/pii_processing/ontology/data/fo.json new file mode 100644 index 0000000..129ddee --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/fo.json @@ -0,0 +1,631 @@ +{ + "LOCATION": [ + "vetrarbreyt", + "stj\u00f8rnubreyt", + "mj\u00f3lkarvegur", + "gr\u00f8nh\u00f8vdaoyggjarnar", + "piet_mondrian", + "sint_maarten", + "atlanshav", + "p\u00e1vast\u00f3lur", + "biscayafl\u00f3gvin", + "land", + "atlantshavi\u00f0", + "falklandsoyggjar", + "usa", + "sri_lanka", + "vei\u00f0ihundarnir", + "svartahavi\u00f0", + "sankta_p\u00e1trikur", + "the_rolling_stones", + "ermarsundsoyggjar", + "ermarsund" + ], + "ANIMAL": [ + "fjallv\u00e1kur", + "kettur", + "feigdarsveimari", + "ravnur", + "flatl\u00fas", + "bringurey\u00f0i", + "gorpur", + "hv\u00edtabj\u00f8rn", + "krunkur", + "brandg\u00e1s", + "minkur", + "silvurhegri", + "drunnhv\u00edti", + "grevlingur", + "villg\u00e1s", + "heykur", + "steyrhvalur", + "brandstari", + "sundgr\u00e6lingur", + "heykugla", + "skalla\u00f8rn", + "huldut\u00edta", + "mastrarhvalur", + "topplundi", + "ketta", + "krossnev", + "letibj\u00f8rn", + "mort\u00edtlingur", + "kyrrfuglur", + "hv\u00edtfiskur", + "fransaterna", + "konga\u00f8rn", + "lonasvala", + "brug\u00f0a", + "froskur", + "stroktr\u00f8stur", + "heygsm\u00e1si", + "tjaldursgr\u00e6lingur", + "augustur", + "bakur", + "fer\u00f0afalkur", + "visundur", + "bolladunna", + "sildreki", + "brandsvala", + "hjartaugla", + "grindahvalur", + "fagur\u00edg\u00f0a", + "helsig\u00e1s", + "barr\u00edg\u00f0a", + "sveimari", + "hornalundi", + "gammur", + "heslim\u00fas", + "spurvaheykur", + "m\u00e1nad\u00fagva", + "gull", + "marsv\u00edn", + "bundi", + "flogfiskur", + "hj\u00f8rtur", + "ternum\u00e1si", + "toppont", + "skatum\u00e1si", + "gr\u00e1tyrningur", + "vendisn\u00edpa", + "sigdartr\u00f8stur", + "brituterna", + "framfaks", + "mastrarfiskur", + "rey\u00f0gr\u00e6lingur", + "brugda", + "villsv\u00edn", + "kambsgj\u00f8r", + "kolont" + ], + "PLANT": [ + "kannubj\u00f8lluv\u00edsa", + "furuvi\u00f0ur", + "pirikum", + "bratsj", + "tranuber", + "skar\u00f0ss\u00fdrusm\u00e6ra", + "flugusoppur", + "almur", + "hoyl\u00fas", + "dreyms\u00f3lja", + "gular\u00f3t", + "leygingargras", + "margaritt", + "rogn", + "h\u00f8snagras", + "gr\u00e1n\u00e1pur", + "listama\u00f0ur", + "brenninota", + "rossaber", + "takstr\u00e6", + "elri", + "k\u00e1pugr\u00e6lingur", + "urtap\u00edlur", + "h\u00f8snag\u00f8rn", + "popputur", + "listakona", + "tikaralilja", + "vetrarbj\u00f8lluv\u00edsa", + "selja", + "kirsuber" + ], + "LANGUAGE": [ + "svenskt", + "venda", + "nor\u00f0urs\u00e1miskt", + "kongo", + "keltiskt", + "teilendskur", + "danskt", + "kinesiskur", + "nor\u00f0ma\u00f0ur", + "tailendskur", + "hv\u00edtarussiskur", + "hindi", + "persiskt", + "esperanto", + "japanskur", + "franskt", + "kekskur", + "spanskur", + "wienarbrey\u00f0", + "tonga", + "malajalam" + ], + "JOB": [ + "raddaleikari", + "sj\u00e1lvr\u00e6ttarma\u00f0ur", + "skraddari", + "hjartal\u00e6kni", + "jar\u00f0arm\u00f3\u00f0ir", + "potter", + "borgarstj\u00f3ri", + "grannsko\u00f0ari", + "duravaktari", + "skorsteinss\u00f3pari", + "br\u00fa\u00f0kona", + "herma\u00f0ur", + "r\u00e6ttlesari", + "tannl\u00e6knar", + "timburma\u00f0ur", + "land", + "biskupur", + "lesari", + "forma\u00f0ur", + "neytakona", + "alisfr\u00f8\u00f0ingur", + "preriu\u00falvur", + "veska", + "prentari", + "bakari", + "apopleksi", + "hundasj\u00faka", + "mandarin", + "stj\u00f8rnufr\u00f8\u00f0ingur", + "trolari", + "mate", + "nevaleikari", + "h\u00f8vundur", + "bilstj\u00f3ri", + "man", + "deiligur", + "tannl\u00e6kni", + "kanslari", + "durav\u00f8r\u00f0ur" + ], + "DATE": [ + "hundadagar", + "langafr\u00edggjadagur", + "heystjavnd\u00f8gur", + "j\u00f3ladagur", + "alla_s\u00e1lnadagur", + "gregorianski_kalendarin", + "ovurmorgin", + "allahalgannadagur", + "p\u00e1lmasunnudagur", + "heystl\u00fdkka" + ], + "PERSON_PRONOUN": [ + "t\u00fa", + "i", + "her", + "tykkum" + ], + "PUBLIC_FIGURE": [ + "che_guevara", + "heindrikur", + "skorsteinss\u00f3pari", + "henrik_ibsen", + "mary_shelley", + "richard_burton", + "georgius", + "paul_mccartney", + "stephen_king", + "isaac_newton", + "victor_hugo", + "antinis", + "george_harrison", + "marie_curie", + "michael_jackson", + "samuel_beckett", + "edmund_hillary", + "vincent_van_gogh", + "elisabet", + "jesus", + "mark_rothko", + "henri_matisse", + "louis_pasteur", + "lavrans", + "saladin", + "sarah_bernhardt", + "hank_williams", + "y", + "charles_lindbergh", + "f", + "dante_alighieri", + "samuel_de_champlain", + "giacomo_puccini", + "james_dean", + "robert", + "taka_l\u00edvi\u00f0_av_s\u00e6r", + "tveir", + "a", + "eins", + "immanuel_kant", + "kristoffur_kolumbus", + "saint_martin", + "carl_lewis", + "canberra", + "hjartarkongur", + "burt", + "walt_disney", + "sveimari", + "joseph_schumpeter", + "marcel_proust", + "elizabeth_taylor", + "jesus_kristus", + "gengis_kan", + "indira_gandhi", + "petur", + "gr\u00e6karis", + "davidur", + "pablo_picasso", + "heinrikur", + "lucille_ball", + "adam_smith", + "karl_marx", + "friedrich_nietzsche", + "i", + "le_corbusier", + "john_locke", + "colin_powell", + "adolf_hitler", + "joseph_haydn", + "1", + "rosa_parks", + "vladimir_putin", + "h", + "g", + "martin_heidegger", + "h.c_andersen", + "r", + "george_lucas", + "louis_armstrong", + "steven_spielberg", + "jorgen", + "lars", + "alfred", + "mahatma_gandhi", + "john_lennon", + "runnur", + "charlie_chaplin", + "ronald_reagan", + "david_hilbert", + "martin_luther_king", + "woodrow_wilson", + "jesusp\u00e1pi", + "st_louis", + "jim_henson", + "frank", + "mort\u00edtlingur", + "nelson_mandela", + "benadikt", + "roald_amundsen", + "fjarst\u00fdring", + "anton", + "francisco_franco", + "jan_steen", + "johnny_cash", + "vladimir_lenin", + "robert_peary", + "john_bunyan", + "albert_einstein", + "t" + ], + "FOOD": [ + "p\u00edskir\u00f3mi", + "rey\u00f0v\u00edn", + "hv\u00edtv\u00edn", + "plantuolja", + "kovaostur", + "p\u00edskifl\u00f8ti", + "heitv\u00edn", + "rey\u00f0k\u00e1l", + "hv\u00edtleyksbrey\u00f0", + "tannhald", + "ros\u00e9v\u00edn", + "kettuf\u00f3\u00f0ur", + "appilsindj\u00fas", + "salatolja", + "morgunmatur", + "florsukur", + "olivinolja", + "bl\u00f3\u00f0pylsa", + "kettumatur", + "tannkj\u00f8t", + "baksturv\u00f8ra", + "tannhold", + "s\u00f3lbl\u00f3muolja" + ], + "PRODUCT": [ + "justin_bieber", + "diskil", + "st\u00f3rabretland", + "bretland", + "av_gu\u00f0s_n\u00e1\u00f0i", + "eitt_dukkuheim", + "hoyl\u00fas", + "the_star_spangled_banner", + "gloymmegei", + "j\u00f3lama\u00f0urin", + "gong", + "vitramannasteinurin", + "keisaraskur\u00f0ur", + "nor\u00f0l\u00fdsi" + ], + "SOC_ECO_CLASS": [ + "landb\u00fana\u00f0ur", + "brotsmannaheimur", + "undirheimur", + "brotsmannaver\u00f0" + ], + "ORG": [ + "jan_mayen", + "nasa", + "milj\u00f6partiet", + "landb\u00fana\u00f0ur", + "berlinm\u00farurin", + "gr\u00f8nh\u00f8vdaoyggjarnar", + "san_francisco", + "heiliv\u00e1gs\u00eddna\u00f0ur", + "mi\u00f0banki", + "polterabend", + "taoisma", + "r\u00f3mversk_kat\u00f3lska_kirkjan", + "rey\u00f0ahavi\u00f0", + "ai", + "eg_eiti", + "evropasamveldi\u00f0", + "republikanski_flokkurin", + "demokratiski_flokkurin", + "heimshandilsfelagsskapurin", + "rabindranath_tagore", + "amason\u00e1", + "r\u00edkisstj\u00f3rn", + "st_lusia", + "mi\u00f0evropa", + "eg_elski_teg", + "menningarland", + "h\u00f8gri", + "kat\u00f3lska_kirkjan", + "addis_ababa", + "markna\u00f0arb\u00faskapur", + "who", + "los_angeles", + "nato", + "tyggigummi", + "posth\u00fas", + "herur", + "hin_f\u00f8royski_f\u00f3lkaflokkurin", + "s\u00f8lumi\u00f0st\u00f8\u00f0", + "so_vi\u00f0_og_vi\u00f0", + "vald\u00f8mi" + ], + "DISEASE": [ + "miltisbruni", + "kambfj\u00f8\u00f0ur", + "fatan", + "svartidey\u00f0i", + "beriberi", + "havhestasj\u00faka", + "gall", + "neyta\u00f8\u00f0i", + "frosts\u00e1r", + "stama", + "frans\u00f3sir", + "miltbrandur", + "spitalskusj\u00faka", + "sj\u00e1lv\u00f3rin", + "skr\u00e6pus\u00f3tt", + "verkur", + "finnur", + "kolubrand", + "talubrek", + "kolubrandur", + "sukursj\u00faka", + "sk\u00e1ldkoppar", + "hitas\u00f3tt", + "the_passion_of_the_christ", + "milts\u00fdki", + "drykkjuskapur", + "hungur", + "rustur", + "n\u00e1tasj\u00faka", + "tan", + "stj\u00f8rnutoka", + "gass", + "salmonella", + "gorlop", + "krabbamein", + "malaria", + "p\u00edning" + ], + "GPE": [ + "dar_es_salaam", + "ta\u00f0_hv\u00edta_h\u00fasi\u00f0", + "su\u00f0uramerika", + "sint_maarten", + "n\u00fdggja_testamenti\u00f0", + "mi\u00f0amerika", + "rey\u00f0ahavi\u00f0", + "mannar\u00e6ttindi", + "santa_nikolaus_fr\u00e1_myra", + "n\u00fdggja_testamenti", + "st_louis" + ], + "POLITICAL_PARTY": [ + "partij_van_de_arbeid", + "arbei\u00f0araflokkurin", + "milj\u00f6partiet", + "javna\u00f0arflokkurin", + "socialistische_partij", + "hin_f\u00f8royski_f\u00f3lkaflokkurin" + ], + "FAC": [ + "p\u00e6tur_mikli", + "jarnbreytarst\u00f8\u00f0", + "tokst\u00f8\u00f0", + "palli_pumm", + "vesturm\u00farurin", + "svimjihylur", + "t_kykna", + "posth\u00fas" + ], + "QUANTITY": [ + "dollari", + "tretivu\u00e1rakr\u00edggi\u00f0", + "parkeringarb\u00f3t", + "kombikk", + "lj\u00f3s\u00e1r", + "ein_og_tj\u00fagu", + "g", + "millumtj\u00f3\u00f0a_eindarskipanin", + "amerikanskur_dollari" + ], + "BIO_CHEM_ENTITY": [ + "mj\u00f3lkars\u00fdra", + "salmiakk" + ], + "LAW": [ + "talufr\u00e6lsi" + ], + "GENDER": [ + "men", + "drongur", + "man", + "konuf\u00f3lk" + ], + "RACE": [ + "ni\u00f0urlendingar", + "afrikanskur", + "hv\u00edtt" + ], + "UNION": [ + "fakfel\u00f8g" + ], + "MEDICAL_THERAPY": [ + "bl\u00f3\u00f0trykk" + ], + "RELIGION": [ + "islam", + "sunni_islam" + ], + "RELIGION_MEMBER": [ + "mon" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "d\u00f3ttir": "son", + "d\u00f3tturd\u00f3ttir": "sonarsonur", + "ommud\u00f3ttir": "d\u00f3ttursonur", + "sonard\u00f3ttir": "ommusonur", + "abbad\u00f3ttir": "abbasonur", + "omma": "abbi", + "heroin": "hetja", + "d\u00e1ma": "h\u00fasb\u00f3ndi", + "fr\u00fagv": "h\u00fasb\u00f3ndi", + "m\u00f3\u00f0ir": "babba", + "nunna": "munkur", + "kongsd\u00f3ttir": "prinsur", + "prinsessa": "fyrst", + "kongad\u00f3ttir": "prinsur", + "drotning": "kongur", + "systir": "br\u00f3\u00f0ir", + "stj\u00fakm\u00f3\u00f0ir": "stj\u00fakfa\u00f0ir", + "v\u00edv": "b\u00f3ndi", + "dunna": "ektama\u00f0ur", + "kvennma\u00f0ur": "man", + "kvinna": "man", + "konuf\u00f3lk": "man", + "piltur": "didda", + "drongur": "genta" + }, + "other_gender_swap": { + "t\u00e6r": "her", + "teir": "her", + "teim": "her", + "teimum": "her", + "tey": "her", + "hj\u00e1_s\u00e6r": "her", + "teirra": "her", + "hj\u00e1_teimum": "her", + "hann": "teir", + "elli": "tey", + "bera": "tey", + "her": "hj\u00e1_s\u00e6r" + }, + "en_pronoun2gender": { + "they": [ + "tv\u00edkyndur", + "samkyndur" + ], + "he": [ + "drongur", + "hann", + "piltur", + "man" + ], + "she": [ + "missa", + "d\u00e1ma", + "didda", + "konuf\u00f3lk", + "fr\u00f8kun", + "likka", + "genta", + "fr\u00fagv", + "kvinna", + "kvennma\u00f0ur" + ] + }, + "en_pronoun2pronoun": { + "he": [ + "hann", + "elli", + "bera" + ], + "she": [ + "her" + ], + "they": [ + "teir", + "teim", + "tey", + "hj\u00e1_s\u00e6r", + "hj\u00e1_teimum", + "t\u00e6r", + "teimum", + "teirra" + ], + "it": [ + "ta\u00f0", + "hetta", + "hasin", + "henda", + "hesin", + "tann" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/fon.json b/data_tooling/pii_processing/ontology/data/fon.json new file mode 100644 index 0000000..aaf378d --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/fon.json @@ -0,0 +1,22 @@ +{ + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": {}, + "other_gender_swap": {}, + "en_pronoun2gender": { + "she": [ + "ny\u0254nu" + ] + }, + "en_pronoun2pronoun": {}, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/fr.json b/data_tooling/pii_processing/ontology/data/fr.json new file mode 100644 index 0000000..e85a73e --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/fr.json @@ -0,0 +1,6653 @@ +{ + "DISEASE": [ + "souffle_cardiaque", + "analg\u00e9sie", + "cyanose", + "verrue", + "hydrocephalus", + "taillader", + "sars", + "rosac\u00e9e", + "pertussis", + "granulome", + "le_strabisme", + "addiction", + "filovirus", + "acanthosis_nigricans", + "abrasion", + "potence", + "cosmide", + "tocade", + "peste_noire", + "essoufflement", + "hydramnios", + "escarboucle", + "ki", + "polio", + "tabes_dorsalis", + "complication", + "ravageur", + "anomalie_cong\u00e9nitale", + "flection", + "bunion", + "bourrade", + "flavivirus", + "shigellose", + "lassitude", + "crise_cardiaque", + "l_arnaque", + "dorst", + "rosette", + "amabiase", + "papovaviridae", + "hamartome", + "rage", + "meurtrir", + "anthrax", + "cin\u00e9pathie", + "les_dents_de_la_mort", + "mat\u00e9rialisme", + "lac\u00e9ration", + "als", + "prodrome", + "cardiopathie_cong\u00e9nitale", + "torsader", + "paramyxoviridae", + "schistosomiase", + "arthropathie", + "rachianalg\u00e9sie", + "trach\u00e9ite", + "hernie", + "pesse", + "wen", + "hydrophobie", + "pachydermie", + "salmonelle", + "posthite", + "sumac_v\u00e9n\u00e9neux", + "graphiose", + "stigmates", + "inversion", + "activation_physiologique", + "cardiomyopathie", + "mange", + "la_passion_du_christ", + "caranome", + "sleeping", + "plasmocytome", + "sore", + "congestion", + "sanglot", + "presbytie", + "flagrer", + "hydropisie", + "chondrome", + "accoutumance", + "sternutation", + "enclavement", + "poliomy\u00e9lite", + "croup", + "energy", + "supplicier", + "carboncle", + "s_effa\u00e7ant_\u00e0_la_vitopression", + "herbe_\u00e0_puce", + "radiation", + "lump", + "clap", + "brucellose", + "hydroc\u00e8le", + "pasteurellose", + "indigestion", + "comitialit\u00e9", + "lutzomyia", + "tachycardie", + "gall", + "mania", + "radiance", + "the_bends", + "xeroderma", + "thalass\u00e9mies", + "m\u00e9lie", + "s_affaisser", + "blastome", + "cardite", + "shape", + "arthrite", + "ms", + "souriceau", + "cowpox", + "brachydactylie", + "dular", + "la_naus\u00e9e", + "the_suffering", + "intertrigo", + "phonophobie", + "prog\u00e9ria", + "pruine", + "rust", + "\u00e9chauder", + "contusion", + "avc", + "pharyngite", + "scotome", + "les_scarifi\u00e9s", + "claudication", + "paramyxovirus", + "tarentulisme", + "statisme", + "de_fatigue", + "trouble", + "blacklash", + "tarsite", + "jubarte", + "goitre", + "androphobie", + "vaccination", + "saucissonner", + "chlorose", + "astasie", + "galactos\u00e9mie", + "cataphasie", + "para", + "abras", + "orgelet", + "coxiellose", + "escarre", + "handicap", + "la_peste", + "moniliose", + "arenaviridae", + "obliquit\u00e9", + "chloasma", + "renflement", + "rio_par\u00e1", + "causalgie", + "prot\u00e9inurie", + "rachitisme", + "syndrome_confusionnel", + "annexite", + "alv\u00e9olite", + "strangulation", + "sodoku", + "lallation", + "spinale", + "wale", + "lumbago", + "dipht\u00e9rie", + "stitch", + "catalepsie", + "loeri", + "crick", + "salmonellose", + "ros\u00e9ole", + "cachexia", + "abasie", + "fondeur", + "schizo\u00efde", + "kailu", + "pemphigus", + "susseyement", + "silicose", + "photophobie", + "ache", + "leegte", + "chi", + "hydron\u00e9phrose", + "manquement", + "flicaille", + "ornithine_carbamoyltransf\u00e9rase", + "stridor", + "lichen", + "picornavirid\u00e9s", + "gravidit\u00e9", + "analgie", + "transposition", + "qi", + "onusida", + "flutter", + "thalass\u00e9mie", + "corn", + "blain", + "pancr\u00e9atite", + "galactoc\u00e8le", + "pourridi\u00e9", + "rickettsiose", + "sumac_grimpant", + "hypotension_orthostatique", + "malaise", + "amiantose", + "parapl\u00e9gie", + "sesseyement", + "spina_bifida", + "passion", + "lordose", + "fourbure", + "flaviviridae", + "varon", + "spinal", + "kala_azar", + "gimp", + "sartan", + "vascularites", + "hydroc\u00e9phalie", + "sarm", + "frenzy", + "malacie", + "alexia", + "gestation", + "crud", + "pityriasis", + "mongolisme", + "ochronose", + "grogne", + "parasit\u00e9mie", + "twist", + "chancre", + "paludisme", + "tarentisme", + "smart", + "hydrops", + "thanatophobie", + "pseudo_hermaphrodisme", + "maladie_cardiovasculaire", + "h\u00e9m\u00e9ralopie", + "suba", + "stase", + "ed", + "breakdown", + "pinc\u00e9e", + "blister", + "en_surpoids", + "pica", + "stenosis", + "papilloma", + "blackwater", + "adiposit\u00e9", + "distension", + "cardiopathie", + "cachexie", + "corpulence", + "astrarophobie", + "vascularite", + "aquaphobie", + "bloom", + "parasites", + "dartre", + "akin\u00e9sie", + "appendicite", + "trachome", + "choke", + "l_aveuglement", + "rougeole", + "coronarien", + "flottement", + "sensation", + "contusionner", + "zinzinuler", + "furoncle", + "tontura", + "pellagre", + "\u00e9crouelles", + "poliovirus", + "fugue", + "pain", + "cervicite", + "bradycardie", + "bissen", + "pellicules", + "virus_ebola", + "bunyaviridae", + "grelottement", + "abrutissement", + "chondrosarcome", + "arbovirus", + "sickl\u00e9mie", + "c\u00e9cit\u00e9", + "rachianesth\u00e9sie", + "lipidologie", + "strain", + "dilatation", + "glycosurie", + "cyclothymie", + "contagion", + "purpura", + "l_empoisonneuse", + "imp\u00e9tigo", + "parvoviridae", + "herp\u00e8s", + "hermaphrodisme", + "brulage", + "paresth\u00e9sie", + "p\u00e9liose", + "bouleverser", + "singe", + "anis\u00e9\u00efconie", + "arthralgie", + "coryza", + "constipation", + "virus_de_la_mosa\u00efque_du_tabac", + "ill", + "chalazion", + "an_qi", + "salmonelles", + "pull", + "sangloter", + "t\u00e9nesme", + "diphth\u00e9rie", + "basaner", + "panaris", + "concussion", + "conditionner", + "handicaper", + "mammite", + "lambdacisme", + "collapse", + "paradontose", + "rhumatisme", + "brulure", + "odontalgie", + "catarrhe", + "taniser", + "togaviridae", + "rougeoyer", + "surcreusement", + "sid\u00e9rose", + "hydrothorax", + "b\u00e9rib\u00e9ri", + "mi", + "tosse", + "\u00e9picondylite", + "aura", + "virus_d_epstein_barr", + "tan", + "carboucle", + "anthrax_staphylococcique", + "molluscum", + "sting", + "roussi", + "cin\u00e9tose", + "vadrouilleur", + "innervation", + "c\u00e2linerie", + "boursouflure", + "cramer", + "ophidisme", + "the_bleeding", + "break", + "scarlatine", + "parulie", + "plaie", + "indisposition", + "trypanosomiase_africaine", + "de_niveau", + "communication_interauriculaire", + "palilalie", + "rougeur", + "papillome", + "trauma", + "maladie_contagieuse", + "masto\u00efdite", + "echovirus", + "tousser", + "fondatrice", + "kuru", + "burn", + "oreillons", + "flexion", + "automysophobie", + "durillon", + "art\u00e9rite", + "noma", + "vomi_noir", + "the_hives", + "en_cloque_mais_pas_trop", + "chleuasme", + "mastite", + "condition", + "enquiquiner", + "dengue", + "a_b\u00eata_lipoprot\u00e9in\u00e9mie", + "hyst\u00e9rie_collective", + "taillade", + "bouleversement", + "conflans", + "talure", + "phocom\u00e9lie", + "art\u00e9rioscl\u00e9rose", + "coqueluche", + "le", + "taph\u00e9phobie", + "albuminurie", + "wrench", + "parvovirus", + "salmonella", + "rutiler", + "folliculite", + "boulimie", + "mooneye", + "peste_am\u00e9ricaine", + "cyclopia", + "hypocratisme_digital", + "boulevers\u00e9", + "pancytop\u00e9nie", + "gelure", + "malaria", + "bossu", + "ph\u00e9nylc\u00e9tonurie", + "gout", + "palmature" + ], + "PUBLIC_FIGURE": [ + "lawrence_durrell", + "la_tour", + "henry_cavendish", + "matthew_arnold", + "harding", + "lambert", + "lev_ivanov", + "de_musset", + "goldmark", + "et_tout_et_tout", + "benjamin_franklin", + "martin_buber", + "e_b_white", + "akira_kurosawa", + "frances_wright", + "alexandre_balandine", + "maria_tallchief", + "meuni\u00e8re", + "lac_tana", + "curtis", + "noah_webster", + "jean_genet", + "dinesen", + "john_knox", + "swedberg", + "mauriac", + "waldheim", + "roger_williams", + "anne_bront\u00eb", + "lovelace", + "livingstone", + "cornelius_vanderbilt", + "ekman", + "rudolf_steiner", + "thomas_wolfe", + "eccles", + "cuvier", + "david_rittenhouse", + "thomas_bayes", + "tindale", + "ben_hogan", + "max_bruch", + "mays", + "langage_c", + "leonard_bernstein", + "sibelius", + "che_guevara", + "kline", + "georges_simenon", + "c", + "alan_seeger", + "ren\u00e9_descartes", + "thomas_hodgkin", + "wright", + "augustin_fresnel", + "humaine", + "belloc", + "andrews", + "john_barth", + "edward_albee", + "bruegel", + "dorothy_parker", + "joseph_albers", + "maria_callas", + "victor_herbert", + "william_walton", + "henrik_ibsen", + "winslow", + "morgan", + "emerson", + "bossoir", + "octavien", + "mary_shelley", + "franz_werfel", + "quine", + "marcello_malpighi", + "peter_lorre", + "karl_baedeker", + "beckett", + "david_livingstone", + "eduard_buchner", + "david_smith", + "john_herschel", + "gauss", + "andrzej_wajda", + "jan_van_eyck", + "carl_rogers", + "cortez", + "george_balanchine", + "georg_wilhelm_steller", + "richard_burton", + "c\u00e9sar_franck", + "douglas_macarthur", + "troglodytin\u00e9s", + "mary_wollstonecraft", + "j_edgar_hoover", + "le_mime_marceau", + "thomas_reid", + "john_jacob_astor", + "otto_frisch", + "anna_pavlova", + "winston_churchill", + "johannes_diderik_van_der_waals", + "mendelssohn", + "b", + "conrad_aiken", + "karl_landsteiner", + "ivan_pavlov", + "georges", + "paul_mccartney", + "richard_smalley", + "waugh", + "andrew_marvell", + "terry_pratchett", + "k", + "macdowell", + "stephen_king", + "francis_crick", + "max_m\u00fcller", + "john_trumbull", + "sherry", + "joseph_greenberg", + "isaac_newton", + "richard_upjohn", + "woolf", + "alfred_eisenstaedt", + "victor_hugo", + "joseph_smith", + "edwin_hubble", + "colette", + "milton_friedman", + "amy_lowell", + "edward_gibbon", + "siffleur", + "schiaparelli", + "augustus_pugin", + "van_de_velde", + "jefferson_davis", + "arafat", + "saint_louis", + "cass_gilbert", + "brindes", + "george_stephenson", + "osborne", + "john_glenn", + "john_webster", + "john_davis", + "george_burns", + "bartlett", + "le_roi_jean", + "george_harrison", + "entertainment_television", + "amundsen", + "george_orwell", + "ellison", + "la_diseuse_de_bonne_aventure", + "arthur_koestler", + "richard_wagner", + "gauthier", + "williams", + "thornton_wilder", + "e_l_doctorow", + "jacques_maillot", + "pancho_villa", + "diaz", + "michel_bakounine", + "non_applicable", + "bed\u0159ich_smetana", + "leopold_stokowski", + "trafiquante", + "rebecca_west", + "stockton", + "marie_curie", + "malthus", + "francis_galton", + "jussieu", + "mary_martin", + "richard_roberts", + "constantine", + "michael_jackson", + "nicolson", + "louis_jolliet", + "carl_sandburg", + "spera", + "stephenson", + "thomas_hobbes", + "goldman", + "edward_weston", + "el_greco", + "macleod", + "waller", + "samuel_beckett", + "connolly", + "david", + "galileo_galilei", + "czerny", + "ernest_bevin", + "jane_goodall", + "der_fliegende_holl\u00e4nder", + "john_donne", + "chaim_weizmann", + "andrea_guarneri", + "robert_koch", + "marshall", + "joseph_goebbels", + "george_eastman", + "john_steinbeck", + "erich_mendelsohn", + "l_avocat_du_diable", + "catherine", + "strickland", + "edmund_hillary", + "binet", + "justinien", + "corbett", + "jacob_gershowitz", + "vincent_van_gogh", + "richard_hooker", + "w", + "william_hazlitt", + "martina_navr\u00e1tilov\u00e1", + "marie_stopes", + "anne_boleyn", + "alexandre_iii", + "has_been", + "john_ruskin", + "\u00e0_partir_de_z\u00e9ro", + "robert_burns", + "staline", + "hans_albrecht_bethe", + "valentina_terechkova", + "thomas_paine", + "bari", + "ustinov", + "liliuokalani", + "francis_beaumont", + "marini", + "steven_weinberg", + "p", + "mary_pickford", + "hans_fischer", + "emiliano_zapata", + "karl_barth", + "millais", + "willem_einthoven", + "rockwell", + "phil_anderson", + "thomas_willis", + "le_baronet_noir", + "bernard_malamud", + "samuel_johnson", + "jesus", + "allen_iverson", + "nimitz", + "marie_antoinette", + "anne_hutchinson", + "louise_nevelson", + "giuseppe_verdi", + "les_tuatha_d\u00e9_d\u00e2nann", + "walter_lippmann", + "e", + "scheele", + "lafitte", + "karl_jaspers", + "franz_leh\u00e1r", + "hideki_yukawa", + "konrad_adenauer", + "bessel", + "ockenfels", + "john_l_lewis", + "marianne_moore", + "norbert_wiener", + "john_masefield", + "frederick_austerlitz", + "krzysztof_kie\u015blowski", + "mark_rothko", + "fran\u00e7ois_couperin", + "maurice_chevalier", + "gottlieb_daimler", + "marie_madeleine", + "richer_klein", + "tom_straussler", + "frank_sinatra", + "tabagisme_passif", + "fran\u00e7ois_rabelais", + "fran\u00e7ois_duvalier", + "crabes", + "abel_tasman", + "katharine_hepburn", + "guthrie", + "henri_becquerel", + "henri_matisse", + "bertram_brockhouse", + "ginsberg", + "louis_pasteur", + "berra", + "josef_hoffman", + "j", + "richard_strauss", + "stephen_decatur", + "galbraith", + "\u00e0_la_perfection", + "leslie_howard", + "hugo_grotius", + "mahalia_jackson", + "ben_shahn", + "john_ford", + "stephen_foster", + "alphonse_bertillon", + "foulon", + "john_james", + "laurence", + "katherine_mansfield", + "gertrude_stein", + "saladin", + "sarah_bernhardt", + "tu_parles", + "v", + "phillis", + "philip_marlowe", + "greene", + "luigi_pirandello", + "t_s_eliot", + "e_g_marshall", + "prince_\u00e9douardien", + "marc_blitzstein", + "hank_williams", + "weston", + "igor_stravinski", + "sadus", + "stadiaire", + "rube_goldberg", + "emily_elizabeth_dickinson", + "dorothea_lange", + "james_thurber", + "fonceur", + "charles_de_gaulle", + "paul_von_hindenburg", + "y", + "henry_moore", + "holden", + "le_tasse", + "mary_mallon", + "ralph_bunche", + "rudolf_bultmann", + "douglass", + "charles_lindbergh", + "erythrina", + "villon", + "vincenzo_bellini", + "samuel_barber", + "tobias_smollett", + "descends", + "f", + "john_jay", + "ludwig_wittgenstein", + "august_strindberg", + "bunyan", + "thomas_mann", + "kendall", + "b\u00e9la_bart\u00f3k", + "alla_nazimova", + "charles_goodyear", + "dante_alighieri", + "cunningham", + "charles", + "robert_lee", + "margot_fonteyn", + "peter_pan", + "james_tobin", + "john_irving", + "samuel_de_champlain", + "paxton", + "giacomo_puccini", + "edward_fitzgerald", + "fridtjof_nansen", + "louis_braille", + "herbert_marcuse", + "mungo_park", + "benedict_arnold", + "georges_ii", + "paul_verlaine", + "anselme", + "q", + "james_a_murray", + "scribes", + "robert_johnson", + "niccol\u00f2_paganini", + "james_dean", + "robert", + "richard_lovelace", + "mason", + "marie_tussaud", + "burnett", + "bronis\u0142aw_malinowski", + "roger_bannister", + "theodor_schwann", + "max_beerbohm", + "greeley", + "alessandro_manzoni", + "pierre_ier", + "mikha\u00efl_barychnikov", + "donald_budge", + "joseph_priestley", + "robert_oppenheimer", + "hal", + "salaheddine", + "nicolas_poussin", + "andrea_mantegna", + "hayek", + "clemenceau", + "joseph_pulitzer", + "ring_lardner", + "george_huntington", + "caruso", + "jim_corbett", + "james_naismith", + "baudouin", + "oscar_wilde", + "de_l_orme", + "philip_roth", + "maintenon", + "j_d_salinger", + "ochoa", + "henry", + "lawrence", + "franklin", + "richard_trevithick", + "william_bradford", + "johan_august_strindberg", + "heinrich_schliemann", + "willard_gibbs", + "liston", + "kean", + "emil_erlenmeyer", + "carlyle", + "eli_whitney", + "jackson", + "glenn_curtiss", + "romberg", + "le_roi_lear", + "roy_crowson", + "\u00e0_merveille", + "a_e", + "chambers", + "malure", + "david_selznick", + "johannes_peter_m\u00fcller", + "laurence_olivier", + "hussein", + "pierre_larousse", + "norris", + "christiaan_eijkman", + "adolf_eichmann", + "sverdrup", + "catharijne", + "marilyn_horne", + "lorca", + "stan_musial", + "francis_bacon", + "compton", + "pete_seeger", + "joseph_heller", + "a", + "boone", + "morris", + "peter_carl_goldmark", + "apollinaire", + "montagu", + "peter_brian_medawar", + "norman_rockwell", + "boris_spassky", + "eins", + "james_brown", + "william_hogarth", + "charles_baudelaire", + "luigi_cherubini", + "david_ricardo", + "henri_labrouste", + "mary_leakey", + "charlie_parker", + "z", + "james_franck", + "william_crookes", + "james_meredith", + "samuel_gompers", + "le_caravage", + "nellie_bly", + "weber", + "warburg", + "fulton", + "parsons", + "alexandre_yersin", + "octavius", + "n", + "stephen_leacock", + "hope", + "albert_schweitzer", + "dumoulin", + "longin", + "john_harvard", + "johann_friedrich_herbart", + "giulio_natta", + "subnormal", + "saint_martin", + "titus", + "johannes_kepler", + "william_s_burroughs", + "david_hartley", + "max_planck", + "william_blake", + "julio_iglesias", + "john_bardeen", + "arthur", + "middleton", + "sarah_vaughan", + "john_wilkes", + "william_byrd", + "william_henry", + "christopher_fry", + "godard", + "charles_holmes", + "scott_joplin", + "latrobe", + "samuel_houston", + "carl_lewis", + "sarah_siddons", + "george_vancouver", + "o'neill", + "samuel_rosenstock", + "canberra", + "bramante", + "knox", + "elias_canetti", + "robert_lowell", + "eisenstein", + "edward_jenner", + "dominique_ingres", + "la_plupart_de", + "john_mercer", + "oscar_robertson", + "oliver_hardy", + "groves", + "cole_porter", + "modeste_et_crescence", + "benjamin_west", + "jean_luc_godard", + "graham_greene", + "frans_hals", + "edward", + "whistler", + "lars_onsager", + "margaret_mitchell", + "igor_stravinsky", + "stuart_davis", + "henri", + "lola_montez", + "jan_swammerdam", + "bellini", + "mary_mccarthy", + "tully", + "david_riesman", + "john_walker", + "william_herschel", + "joseph_black", + "francis_rous", + "montesquieu", + "oakley", + "arthur_rubinstein", + "calvin", + "le_petit_lord", + "nikita_khrouchtchev", + "arthur_compton", + "marc_antoine", + "lindbergh", + "robbins", + "niels_bohr", + "saint_vit", + "kenneth_grahame", + "larousse", + "sheridan", + "henry_fielding", + "bertrand_russell", + "katherine_anne_porter", + "michael_faraday", + "john_d_rockefeller", + "burt", + "anthony_burgess", + "jan_tinbergen", + "robert_venturi", + "johnny_appleseed", + "maurois", + "irving_berlin", + "galina_oulanova", + "morgane", + "peter_seamus_o'toole", + "bernard_baruch", + "rudolf_diesel", + "walt_disney", + "ben_jonson", + "peter", + "la_spezia", + "constantin_stanislavski", + "robert_benchley", + "ali_baba_et_les_quarante_voleurs", + "h_l_mencken", + "le_pieux", + "joseph_schumpeter", + "beveridge", + "gabriel_lippmann", + "steve_reich", + "lee", + "lamarck", + "benny_goodman", + "ted_williams", + "william_beaumont", + "friedrich_engels", + "pavlov", + "jane_austen", + "charles_laughton", + "parker", + "gustav_mahler", + "ed_sullivan", + "phil_collins", + "alice_paul", + "giosu\u00e8_carducci", + "robert_redford", + "monod", + "jean_giraudoux", + "jack_dempsey", + "brindisi", + "ian_fleming", + "richard_feynman", + "wolfgang_pauli", + "wollaston", + "pouchkine", + "theodore_dreiser", + "theodor_mommsen", + "le_che", + "andrew_huxley", + "schoenberg", + "marcel_proust", + "jessica_mitford", + "thomas_more", + "homo_heidelbergensis", + "fonceuse", + "milhaud", + "paul_hindemith", + "elizabeth_taylor", + "thomas_chippendale", + "l_\u00e9lu", + "anne_sullivan", + "paul_robeson", + "arnold", + "simon_pierre", + "thomas_middleton", + "john_dowland", + "sumner", + "van_dyck", + "dag_hammarskj\u00f6ld", + "johny_jacob", + "daniel_jones", + "benjamin_jonson", + "william_golding", + "robert_motherwell", + "william_caxton", + "john_milton", + "rudolf_serkin", + "couperin", + "ethel_merman", + "aide_m\u00e9nag\u00e8re", + "samuel_adams", + "albert_speer", + "james_baldwin", + "john_vanbrugh", + "gracie", + "indira_gandhi", + "william_mitchell", + "george_brummell", + "jane_seymour", + "peter_minnewit", + "george_gershwin", + "alberto_giacometti", + "nicolas_machiavel", + "frank_whittle", + "alfred_nobel", + "jesse_owens", + "friedrich_fr\u00f6bel", + "daniel_rutherford", + "khayy\u0101m", + "saint_cyrille", + "ashe", + "marco_polo", + "macaca_nemestrina", + "john_fletcher", + "charlie_watts", + "m", + "charlotte_corday", + "marcel_marceau", + "gilmer", + "le_petit_lord_fauntleroy", + "oort", + "allen_ginsberg", + "fred_zinnemann", + "daniel_bernoulli", + "guillaume_apollinaire", + "gibbs", + "antoine_watteau", + "brandt", + "pablo_casals", + "joseph_henry", + "henri_bergson", + "jos\u00e9_ortega_y_gasset", + "antonius", + "jean_bernoulli", + "edward_macdowell", + "josef_hoffmann", + "boris_karloff", + "pierre_corneille", + "heinrich_b\u00f6ll", + "phillis_wheatley", + "patrick_white", + "hans_zinsser", + "saul_steinberg", + "constantin", + "bartholomew_roberts", + "eileen_farrell", + "troisi\u00e8me_croisade", + "catherine_howard", + "daniel_morgan", + "hans_christian_andersen", + "peter_cooper", + "reich", + "william_morris", + "william_dawes", + "cary_grant", + "hideyo_noguchi", + "thomas", + "isaac_watts", + "pieter_zeeman", + "arnold_gesell", + "glenn_miller", + "steward", + "wegener", + "pablo_picasso", + "mansart", + "marian_anderson", + "natalie_wood", + "l_ron_hubbard", + "raffles", + "fosse_aux_lions", + "thomas_moore", + "robeson", + "louis_ix", + "kurt_weill", + "otto_hahn", + "lester_young", + "christian_huygens", + "john_marshall", + "georges_boole", + "hector_berlioz", + "hermann_g\u00f6ring", + "lucille_ball", + "paul_simon", + "claudio_monteverdi", + "robert_scott", + "john_galsworthy", + "robert_robinson", + "ziegler", + "chevtchenko", + "dickinson", + "spielberg", + "o", + "rakhmaninov", + "goodman", + "mccartney", + "one", + "adam_smith", + "william_james", + "mohamed_ali", + "u", + "jean_harlow", + "henry_miller", + "karl_marx", + "paul_bunyan", + "friedrich_nietzsche", + "albrecht_d\u00fcrer", + "i", + "pedro", + "robert_indiana", + "jimmy_durante", + "john_wesley", + "henry_longfellow", + "l_\u00e9lue", + "sandro_botticelli", + "parrish", + "carson_mccullers", + "ren\u00e9_magritte", + "bloch", + "seiji_ozawa", + "ehrenberg", + "paolo_caliari", + "nikola_tesla", + "al_capone", + "jim_bowie", + "charles_barkley", + "billy_graham", + "robert_schumann", + "mel_gibson", + "le_corbusier", + "joseph_caulle", + "carlo_goldoni", + "john_locke", + "tharp", + "alexis_carrel", + "du_maurier", + "l_enfant", + "joseph_marie_jacquard", + "henry_james", + "stephen_sondheim", + "henson", + "richards", + "lorado", + "lorenz_hart", + "philippe_melanchthon", + "perry", + "helen_keller", + "paul_dukas", + "ingrid_bergman", + "saint_david", + "le_valentinois", + "crosby", + "denmark_vesey", + "leonard_bloomfield", + "jane_jacobs", + "sergue\u00ef_rachmaninov", + "verlaine", + "jean_piaget", + "william_congreve", + "franz_kline", + "henri_rousseau", + "paul_tillich", + "hilaire_belloc", + "montgomery_ward", + "frank_norris", + "konoe", + "frank_stella", + "paul_v\u00e9ron\u00e8se", + "robert_southey", + "h_g_wells", + "walt_whitman", + "william_wyler", + "john_osborne", + "colin_powell", + "ludwig_boltzmann", + "carl_nielsen", + "chopin", + "hearst", + "rankin", + "vaux", + "richard_neville", + "leopold_kronecker", + "richard_wright", + "benjamin_thompson", + "adolf_hitler", + "maria_mitchell", + "fritz_haber", + "archibald_macleish", + "fowler", + "richard_starkey", + "peter_behrens", + "john_tradescant", + "jaspers", + "alfred_stieglitz", + "joseph_haydn", + "stephen_spender", + "joseph_staline", + "garfield", + "d\u00e9chet_blanc", + "george_boole", + "paul_revere", + "helen_wills", + "kruger", + "daniel_boone", + "buffalo_bill", + "edvard_grieg", + "jacques", + "robert_boyle", + "arthur_laffer", + "edith_cavell", + "alan_paton", + "ralph_richardson", + "prima_donna", + "lenard", + "1", + "alberti", + "cordell_hull", + "james_wilson", + "rosa_parks", + "norman_jewison", + "marceau", + "riley", + "samuel_goldwyn", + "mikha\u00efl_kalinine", + "x", + "ernest_walton", + "tcha\u00efkovski", + "jacob", + "giuseppe_mazzini", + "carolus", + "jim_thorpe", + "hertz", + "bradbury", + "h", + "randall_jarrell", + "arnold_sch\u00f6nberg", + "manson", + "laurence_sterne", + "andre\u00ef_sakharov", + "hutchinson", + "jacqueline_cochran", + "george_fox", + "ben_hecht", + "christopher_isherwood", + "kremer", + "bloomfield", + "fritz_kreisler", + "anne_hathaway", + "david_garrick", + "bill_russell", + "berlioz", + "nicolas_copernic", + "thomson", + "baldwin", + "le_duce", + "jeannette_rankin", + "clarence_darrow", + "agassiz", + "charles_lamb", + "harry", + "g", + "john_chapman", + "jansen", + "arthur_schopenhauer", + "thomas_dekker", + "james_cagney", + "john_keble", + "johns_hopkins", + "henri_pitot", + "wanda_landowska", + "billy_mitchell", + "martin_heidegger", + "hans_eysenck", + "aiken", + "r", + "george_lucas", + "andrew_jackson", + "v\u00e9ron\u00e8se", + "edith_wharton", + "louis_armstrong", + "spallanzani", + "fran\u00e7ois_jacob", + "ortega", + "john_roberts", + "loeb", + "antony_tudor", + "steven_spielberg", + "lac_powell", + "comstock", + "jean_monnet", + "khrouchtchev", + "leonard", + "sellers", + "mikha\u00efl_bakounine", + "d_w_griffith", + "robert_fulton", + "thomas_hardy", + "sebasti\u00e1n_vizca\u00edno", + "thomas_gainsborough", + "giuseppe_garibaldi", + "philip_warren_anderson", + "alexandre_dumas", + "karel_\u010dapek", + "le_petit_chaperon_rouge", + "robert_brown", + "bethune", + "thomas_carlyle", + "bragg", + "donald_barthelme", + "william_tyndale", + "tamara_karsavina", + "bobby_fischer", + "johannes_gutenberg", + "grand_manitou", + "svedberg", + "thornton", + "d", + "james_bowie", + "thomas_malthus", + "giambattista_marino", + "gaetano_donizetti", + "castro", + "beadle", + "william_faulkner", + "simon_de_montfort", + "amerigo_vespucci", + "arthur_holmes", + "pierre_boulez", + "hans_adolf_krebs", + "lars", + "emma_goldman", + "robert_gray", + "blake", + "haywood", + "anna_kournikova", + "eug\u00e8ne_delacroix", + "francis_poulenc", + "james_ussher", + "john_barrymore", + "john_constable", + "rachel_louise_carson", + "james_mill", + "john_ciardi", + "matthew_flinders", + "george_kaufman", + "robert_herrick", + "joseph_campbell", + "grainger", + "michel_greg", + "molnar", + "jean_de_la_fontaine", + "robert_hooke", + "davy", + "o_henry", + "hoffa", + "les_dix_derniers_jours_d_hitler", + "karl_popper", + "alfred", + "coleman_hawkins", + "frye", + "george_sand", + "sousa", + "peter_sellers", + "homo_rhodesiensis", + "charles_fourier", + "lapini\u00e8re", + "henry_clay", + "cousteau", + "bolingbroke", + "peter_o'toole", + "joseph_conrad", + "william_shockley", + "g\u00fcnter_grass", + "kenneth_roberts", + "jim_morrison", + "cromwell", + "jules_verne", + "paul_newman", + "robert_mills", + "george_meredith", + "robert_morris", + "chaumier", + "carroll", + "woody_herman", + "alexander_wilson", + "josef_albers", + "jackson_pollock", + "laffite", + "david_crockett", + "welles", + "kasparov", + "john_lennon", + "andrea_palladio", + "golding", + "gr\u00e9goire", + "gandhi", + "bob_woodward", + "charlie_chaplin", + "lillian_russell", + "d_h_lawrence", + "mcpherson", + "edward_morley", + "j_m_barrie", + "thomas_malory", + "john_brown", + "al_jolson", + "elizabeth_gaskell", + "l_admirable_crichton", + "caldwell", + "pieter_cornelis_mondriaan", + "christophe_colomb", + "hugo_junkers", + "burnham", + "maurice_barrymore", + "paul_gleason", + "papinette", + "lillian_hellman", + "brescia", + "brecht", + "carter", + "thomas_merton", + "villard", + "asa_gray", + "hannah_arendt", + "antonio_stradivari", + "c_s_forester", + "kuhn", + "cushing", + "robinson_jeffers", + "le_bouffon_du_roi", + "algernon", + "alice_walker", + "strauss", + "macleish", + "miles_davis", + "lydia_liliuokalani", + "bruce", + "andr\u00e9_weil", + "james_parkinson", + "gustave", + "george_marshall", + "cochran", + "gesell", + "harold_nicolson", + "jesse_jackson", + "willa_cather", + "bozen", + "stanley_kubrick", + "rudolph_bultmann", + "niccol\u00f2_amati", + "john_deere", + "john_huston", + "william_cook", + "haacht", + "ivanov", + "william_gilbert", + "mcgraw", + "james_watt", + "jonathan_edwards", + "ronald_reagan", + "helmut_schmidt", + "jenny_lind", + "homo", + "frederick_douglass", + "la_rochefoucauld", + "david_hilbert", + "le_joueur_de_fl\u00fbte_de_hamelin", + "wilhelm_reich", + "william_thornton", + "roman_jakobson", + "oliver_cromwell", + "vladimir_poutine", + "lionel_hampton", + "martin_luther_king", + "purcell", + "james_hargreaves", + "patrick_d_irlande", + "kekul\u00e9", + "paul_c\u00e9zanne", + "lorenz", + "frank_capra", + "william_wordsworth", + "rex_harrison", + "s", + "william_clark", + "woodrow_wilson", + "pierre_ier_le_grand", + "william_wycherley", + "riehen", + "o'brien", + "margaret_sanger", + "xubila\u00ef", + "george_mason", + "george_wallace", + "quincy", + "schulz", + "alonso", + "sargent", + "agrippina", + "richard_rodgers", + "george", + "anne_sexton", + "saint_cr\u00e9pinien", + "georges_de_lydda", + "john_dryden", + "jim_henson", + "frank", + "b\u00e9la_lugosi", + "ernest_hemingway", + "john_eccles", + "george_westinghouse", + "jeanne_seymour", + "aquila", + "jacques_charles", + "eero_saarinen", + "arthur_miller", + "john_cheever", + "gracie_allen", + "nelson_mandela", + "heinrich_himmler", + "al_gore", + "john_rutledge", + "hans_bethe", + "hans_geiger", + "woodbury", + "whittier", + "hampton", + "fernand_l\u00e9ger", + "swinburne", + "roald_amundsen", + "sherwood_anderson", + "andersen", + "richard_leakey", + "alfred_korzybski", + "c_a", + "charles_dickens", + "pershing", + "fairbanks", + "samuel_huntington", + "de_saussure", + "ella_fitzgerald", + "fats_waller", + "thomas_sydenham", + "jack_robinson", + "manipulateur_en_\u00e9lectroradiologie_m\u00e9dicale", + "jacques_offenbach", + "saint_laurent", + "schweitzer", + "joseph_paxton", + "william_curtis", + "bose", + "william_chambers", + "gilbert", + "leakey", + "hans_conrad_julius_reiter", + "george_stevens", + "federico_fellini", + "the_one", + "bessie_smith", + "bentham", + "patrick_henry", + "carnot", + "willy_brandt", + "charles_wilkes", + "francisco_pizarro", + "francisco_franco", + "jackie_robinson", + "montfort", + "bernardo_bertolucci", + "michael_sinnott", + "z\u00e9non", + "king_oliver", + "jan_steen", + "lichtenstein", + "frank_harris", + "e_e_cummings", + "john_ross", + "jaroslav_ha\u0161ek", + "ali_baba", + "antonin", + "powell", + "philibert_delorme", + "andrew_mellon", + "andrew_carnegie", + "fils_de_jonas", + "franz_schubert", + "arnaud", + "johnny_cash", + "vidal", + "joseph_mccarthy", + "alfred_kastler", + "marduk", + "mick_jagger", + "otto_loewi", + "robinson", + "don_quichotte", + "friedrich_max_m\u00fcller", + "beno\u00eet", + "georges_cuvier", + "sessions", + "william_harvey", + "constantin_br\u00e2ncu\u015fi", + "de_vliegende_hollander", + "walter_scott", + "august_von_wassermann", + "peter_medawar", + "jenner", + "sam_houston", + "robert_peary", + "rodgers", + "robert_browning", + "comenius", + "ralph_ellison", + "john_bunyan", + "jonathan_swift", + "franck", + "goebbels", + "iglesias", + "walter_gropius", + "albert_einstein", + "l", + "henry_sweet", + "robert_joffrey", + "aletta_jacobs", + "stubbs", + "thomas_edison", + "joukov", + "claude_bernard", + "raymond_chandler", + "henry_purcell", + "pieter_stuyvesant", + "ormuzd", + "ostwald", + "t", + "griffith", + "thatcher", + "lemmon", + "jorioz", + "marley", + "wilhelm_ostwald" + ], + "RELIGION_MEMBER": [ + "jihadiste", + "le_pr\u00e9dicateur", + "\u00e9piscopalien", + "christiano", + "guru", + "the_hindu", + "j\u00e9suite", + "protestant", + "sarrasins", + "mulla", + "chi_ite", + "dunker", + "moll\u00e2", + "wahhabi", + "chartreux", + "anabaptiste", + "chartreuses_anglaises", + "melchite", + "sarrazin", + "mahom\u00e9tan", + "melkite", + "mormon", + "armano", + "parsis", + "shaker", + "mahom\u00e9tisme", + "congr\u00e9gationaliste", + "christian", + "mollah", + "le_retour_du_fr\u00e8re_prodigue", + "franciscain", + "sister", + "mullah", + "sunni", + "parsi", + "presbyt\u00e9rien", + "bouddhiste", + "catholique", + "cistercien", + "mon", + "ath\u00e9iste", + "secoueur", + "sunnite", + "pent\u00e9costaire", + "pentec\u00f4tiste" + ], + "PLANT": [ + "canneberge", + "acer_negundo", + "quercus_wislizenii", + "hibiscus_syriacus", + "jambose", + "carline_commune", + "petite_oseille", + "acanthocereus_tetragonus", + "mille_pertuis", + "hibiscus_mutabilis", + "arceuthobium_pusillum", + "brachychiton_populneus", + "glaucium_flavum", + "primula_auricula", + "senecio_vulgaris", + "robinia_hispida", + "tsuga_caroliniana", + "lilium_martagon", + "lupinus_luteus", + "hevea", + "pyracantha", + "acer_rubrum", + "botrychium_matricariifolium", + "agathis_lanceolata", + "liseron", + "mahonia", + "senna_marilandica", + "chalef_argent\u00e9", + "lespedeza_cuneata", + "campanula_persicifolia", + "prunus_alleghaniensis", + "leucogenes_leontopodium", + "eriophyllum_wallacei", + "cin\u00e9raire_maritime", + "diospyros_virginiana", + "dryopteris_fragrans", + "nielle", + "helenium_autumnale", + "iris_cristata", + "pourgh\u00e8re", + "rhododendron_viscosum", + "mastic", + "pine", + "verbascum_thapsus", + "lycium_barbarum", + "coquelicot", + "monarde", + "surelle", + "cam\u00e9risier", + "carduus_crispus", + "parnassia", + "helicteres_isora", + "if_commun", + "ch\u00e2tain", + "salvia_leucophylla", + "iris_germanica", + "if_du_japon", + "lilium_philadelphicum", + "ficaire", + "lilium_longiflorum", + "sorghum_halepense", + "rubus_saxatilis", + "charme_commun", + "salicaire_commune", + "veronica_beccabunga", + "liriodendron_tulipifera", + "quercus_coccinea", + "sois_prudent", + "camphre", + "cladonia_rangiferina", + "melissa", + "canavalia_gladiata", + "impatiens_walleriana", + "geranium_molle", + "ch\u00e2taigne", + "hoya_carnosa", + "helianthus_petiolaris", + "charme_houblon", + "viola_arvensis", + "sapindus", + "l_empoisonneuse", + "viola_reichenbachiana", + "chimaphila_umbellata", + "lilium_lancifolium", + "the_joshua_tree", + "tragopogon_pratensis", + "sarcoscypha_coccinea", + "philadelphus_coronarius", + "aralia_elata", + "busserole", + "brassica_nigra", + "torreya_californica", + "atte", + "eleocharis_dulcis", + "carotte", + "balding\u00e8re", + "betula_populifolia", + "bromus_tectorum", + "helleborus_niger", + "volubilis", + "helianthus", + "quetschier", + "aristolochia_serpentaria", + "pterocarpus_santalinus", + "gaillardia_pulchella", + "rosa_chinensis", + "le_myst\u00e8re_silkwood", + "polygala_senega", + "lathyrus_latifolius", + "banksia_integrifolia", + "carissa", + "scorzonera_hispanica", + "eupatorium_maculatum", + "cucurbita_moschata", + "monarda_citriodora", + "rudbeckia_laciniata", + "solanaceae", + "eupatorium_perfoliatum", + "marronnier", + "salvia_verbenaca", + "cordia_alliodora", + "erica_tetralix", + "campanula_medium", + "quercus_kelloggii", + "cynorhodon", + "erigeron_divergens", + "vanilla_planifolia", + "viola_cornuta", + "juncus_articulatus", + "eryngium_maritimum", + "schefflera_actinophylla", + "amelanchier_bartramiana", + "rubus_cuneifolius", + "sida_rhombifolia", + "pachysandra_terminalis", + "hibiscus_heterophyllus", + "salix_babylonica", + "dryopteris_marginalis", + "thermopsis_villosa", + "asclepias_exaltata", + "centaur\u00e9e_scabieuse", + "cyclamen_purpurascens", + "oxytropis_lambertii", + "marri", + "magnolia_acuminata", + "cypripedium_parviflorum", + "pseudotsuga_macrocarpa", + "kennedia_prostrata", + "anthyllis_vulneraria", + "arctostaphylos_alpinus", + "prunus_japonica", + "abies_grandis", + "leucanthemum_maximum", + "alliaire", + "laurus_nobilis", + "lathyrus_odoratus", + "selaginella_lepidophylla", + "fraxinus_americana", + "strongylodon_macrobotrys", + "amanita", + "bergamotier", + "pe_tsa\u00ef", + "sequoiadendron", + "vespula_vulgaris", + "macrotyloma_uniflorum", + "achillea_ptarmica", + "arabidopsis_thaliana", + "caesalpinia_gilliesii", + "centaurea_nigra", + "pilularia_globulifera", + "maniguette", + "putet", + "reine_marguerite", + "bertholletia_excelsa", + "iris_tingitana", + "adenium_obesum", + "helianthus_annuus", + "arundo", + "cassiope_mertensiana", + "astilbe_biternata", + "monarda", + "sorbus_torminalis", + "muflier", + "trichostema_dichotomum", + "achillea", + "magnolia_grandiflora", + "podocarpus_elongatus", + "berteroa_incana", + "colutea_arborescens", + "scammon\u00e9e", + "mille_feuille", + "yuca", + "prosopis_glandulosa", + "chionanthus_virginicus", + "podocarpus_elatus", + "bidens_tripartita", + "morgeline", + "sinapis", + "campanelle", + "amanites", + "prunus_laurocerasus", + "pachysandra_procumbens", + "napaea_dioica", + "allium_tuberosum", + "pennisetum_glaucum", + "schizachyrium_scoparium", + "senecio_triangularis", + "amelanchier_alnifolia", + "machaeranthera_tanacetifolia", + "ravenelle", + "salix_triandra", + "m\u00e9lisse", + "leucaena_leucocephala", + "silene_virginica", + "lilium_michiganense", + "cercidiphyllum_japonicum", + "atriplex_hortensis", + "vaccinium_corymbosum", + "camphrier", + "eupatorium_purpureum", + "ravenale", + "quercus_falcata", + "platane_commun", + "begonia_heracleifolia", + "teucrium_scorodonia", + "acer_campestre", + "plante_annuelle", + "ne_m\u2019_oubliez_pas", + "bletilla_striata", + "helianthus_angustifolius", + "sambal", + "mimosa_pudica", + "leontopodium_alpinum", + "chamaecyparis_thyoides", + "merisier", + "rubus_caesius", + "papaver_somniferum", + "manioc", + "convolvulus", + "malus_angustifolia", + "par\u00e9", + "cynoglosse", + "gentiana_lutea", + "mercurialis_perennis", + "arcos", + "quercus_velutina", + "arctostaphylos_alpina", + "botrychium_virginianum", + "acacia_pycnantha", + "cynoglossum_amabile", + "actinidia_chinensis", + "taxus_baccata", + "gr\u00e9vill\u00e9e", + "saxifraga_granulata", + "sakura", + "chloris_gayana", + "sporobolus_cryptandrus", + "lycopodium_obscurum", + "valerianella_locusta", + "periploca_graeca", + "geum_macrophyllum", + "papaver", + "rhus_typhina", + "salix_humilis", + "nymphaea_alba", + "silene_dioica", + "dicentra_spectabilis", + "euphorbia_esula", + "phaseolus_coccineus", + "diplotaxis_tenuifolia", + "guinda", + "candida_albicans", + "pulicaria_dysenterica", + "ranunculus_ficaria", + "polygala_paucifolia", + "callirhoe_involucrata", + "graptophyllum_pictum", + "senna_alata", + "schinus_terebinthifolius", + "amaryllis_belladonna", + "veronica_officinalis", + "phegopteris_connectilis", + "dartrier", + "asperula", + "betterave", + "amphicarpaea_bracteata", + "pycnanthemum_virginianum", + "ortie", + "aconitum_lycoctonum", + "rosa_multiflora", + "soyez_prudente", + "prunus_cerasus", + "anthemis_arvensis", + "helianthus_giganteus", + "microstrobos_niphophilus", + "solidago_rugosa", + "ligustrum_ovalifolium", + "acer_macrophyllum", + "asclepias_purpurascens", + "acacia_dealbata", + "capsicum_baccatum", + "doubeurre", + "agrimonia_eupatoria", + "brasenia_schreberi", + "anaphalis_margaritacea", + "bidens_bipinnata", + "larix_occidentalis", + "plantago_lanceolata", + "pseudobombax_ellipticum", + "sciadopitys", + "chrysanth\u00e8me", + "erythronium_grandiflorum", + "trichostema_lanceolatum", + "polystichum_lonchitis", + "ononis_spinosa", + "tanacetum_ptarmiciflorum", + "andropogon_virginicus", + "hamamelis_vernalis", + "margousier", + "ranunculus_glaberrimus", + "xanthosoma_sagittifolium", + "ipomoea_leptophylla", + "acer_palmatum", + "thlaspi_arvense", + "agrostemma_githago", + "ligustrum_ibolium", + "pseudolarix_amabilis", + "ou_myrique_baumier", + "cortinaire_violet", + "hypericum_androsaemum", + "taxus_cuspidata", + "salix_viminalis", + "ou_s\u00e9nev\u00e9", + "tilia_japonica", + "melampodium_leucanthum", + "juniperus_virginiana", + "sphaeralcea_coccinea", + "calamintha_grandiflora", + "acacia_auriculiformis", + "arctostaphylos_andersonii", + "bergamote", + "leonotis_nepetifolia", + "alstonia_scholaris", + "eucalyptus_globulus", + "cassia_fistula", + "phyllocladus_alpinus", + "vaccinium_arboreum", + "pterospermum_acerifolium", + "platanus_occidentalis", + "passiflora_incarnata", + "clusia", + "festuca_ovina", + "zanthoxylum_americanum", + "quercus_ellipsoidalis", + "syringa_reticulata", + "plantule", + "bromus_arvensis", + "polygala_vulgaris", + "hypericum_tetrapterum", + "ardisia_crenata", + "fraxinus_quadrangulata", + "moutarde", + "physostigma_venenosum", + "veronica_peregrina", + "scutellaria_lateriflora", + "ganteline", + "nothofagus_menziesii", + "clematis_virginiana", + "pennisetum_setaceum", + "calebassier", + "dividivi", + "rubus_trivialis", + "artemisia_tridentata", + "tracheobionta", + "chenopodium_capitatum", + "chaenomeles_speciosa", + "selenicereus_grandiflorus", + "citrus_aurantium", + "pelargonium_peltatum", + "amaranthus_spinosus", + "barbarea_vulgaris", + "eremobates_gladiolus", + "osmanthus_americanus", + "kochia_scoparia", + "felicia_bergeriana", + "psidium_cattleianum", + "delairea_odorata", + "annona_cherimola", + "helleborus_orientalis", + "piper_longum", + "gossypium_hirsutum", + "filago", + "abronia_maritima", + "prunus_armeniaca", + "campanula_americana", + "marrube", + "castanea_dentata", + "quercus_stellata", + "allamanda_cathartica", + "magnolia_macrophylla", + "liquidambar", + "ch\u00e8vrefeuille", + "petasites_hybridus", + "charme_am\u00e9ricain", + "urtica", + "parthenocissus_tricuspidata", + "lychnis", + "artemisia_cana", + "paspalum_distichum", + "ligustrum_obtusifolium", + "quercus_garryana", + "coreopsis_maritima", + "maclura_pomifera", + "malus_baccata", + "cucurbita_argyrosperma", + "aster_arenosus", + "coulemelle", + "odon", + "salix_fragilis", + "amanita_muscaria", + "pterocarpus_indicus", + "olive", + "corylus_americana", + "brachychiton_australis", + "mildiou_de_la_pomme_de_terre", + "leonurus_cardiaca", + "silybum", + "castagnaro", + "malherbologie", + "physostegia_virginiana", + "asplenium_trichomanes", + "paradisier", + "carissa_bispinosa", + "acer_japonicum", + "silene_acaulis", + "cnidolscolus_stimulosus", + "arrhenatherum_elatius", + "masako", + "fraxinus_caroliniana", + "larkspur", + "agrostis_nebulosa", + "eucalyptus_camphora", + "nicotiana_alata", + "kniphofia", + "dracocephalum", + "carissa_macrocarpa", + "sorbier", + "populus_balsamifera", + "armeria_maritima", + "pavots", + "nicotiana_tabacum", + "centaurea_scabiosa", + "myosotis_sylvatica", + "kananga", + "asarets", + "chamaecrista_fasciculata", + "asclepias_verticillata", + "phyllostachys_nigra", + "rosa_laevigata", + "puccinia_graminis", + "astragalus_alpinus", + "quercus_variabilis", + "ulmus_americana", + "lentisque", + "carex_arenaria", + "psidium_guineense", + "antennaria_plantaginifolia", + "eriodictyon_californicum", + "erigeron_annuus", + "platycladus_orientalis", + "acanthus_mollis", + "albugine", + "if_japonais", + "grande_bardane", + "sanguin", + "alth\u00e9a", + "stellaria_media", + "erica_perspicua", + "leucanthemum_vulgare", + "solanum_nigrum", + "abies_lasiocarpa", + "campanula_rapunculus", + "melastoma_malabathricum", + "rhus_trilobata", + "cystopteris_montana", + "rubus_parviflorus", + "sciadopitys_verticillata", + "ulmus_alata", + "lycopodium_complanatum", + "lonicera_dioica", + "aralia_spinosa", + "clematis", + "anthemis_tinctoria", + "cranberry", + "helianthus_tuberosus", + "merise", + "parthenium_argentatum", + "hedysarum_coronarium", + "senna_occidentalis", + "eryngium_yuccifolium", + "clematis_lasiantha", + "petite_digitale", + "camassia_leichtlinii", + "lithospermum_canescens", + "alisme", + "tartifle", + "hippocrepis_comosa", + "saccharum", + "usnea_barbata", + "hoffe", + "lycopus_americanus", + "prunus_domestica", + "draba_verna", + "dendrocalamus_giganteus", + "cercis_occidentalis", + "bardanes", + "portulaca_grandiflora", + "chlorophyllum_molybdites", + "centaurea_americana", + "m\u00e9lissa", + "bilimbi", + "gilas", + "muscicapa_striata", + "arundinaria_gigantea", + "asclepias_albicans", + "prosopis_juliflora", + "acer_platanoides", + "cotoneaster_horizontalis", + "ronce", + "rubus_idaeus", + "viburnum_prunifolium", + "grifola", + "quercus_macrocarpa", + "prunus_pensylvanica", + "gossypium_barbadense", + "brachychiton_rupestris", + "platylobium_formosum", + "argemone", + "hedysarum_boreale", + "erica_carnea", + "cimicifuga_racemosa", + "euphorbia_cyparissias", + "salvia_pratensis", + "centaurea_cyanus", + "euphorbia_cyathophora", + "ormosia_coarctata", + "asclepias_incarnata", + "santolina_chamaecyparissus", + "delonix_regia", + "cascara", + "urtica_dioica", + "agaricus_campestris", + "monotrope_uniflore", + "caboche", + "trifolium_repens", + "blackberry", + "quercus_prinoides", + "parochetus_communis", + "oenanthe_aquatica", + "marsault", + "rubus_leucodermis", + "cortaderia_selloana", + "solanum", + "ballota_nigra", + "campanula_carpatica", + "xerophyllum_tenax", + "chardon_pench\u00e9", + "acalypha_virginica", + "begonia_erythrophylla", + "allium_acuminatum", + "campsis_radicans", + "cirsium_vulgare", + "rhodosphaera_rhodanthema", + "eryngium_aquaticum", + "echinocactus_grusonii", + "flamboyants", + "eupatorium_capillifolium", + "millepertuis_andros\u00e8me", + "heterotheca_villosa", + "lilium_canadense", + "allium_neopolitanum", + "medinilla_magnifica", + "brachychiton_acerifolius", + "caragana_arborescens", + "consoude_officinale", + "sorbus_aucuparia", + "senecio_cineraria", + "ne_m_oubliez_pas", + "acer_pseudoplatanus", + "aristolochia_macrophylla", + "liserons", + "lotus_corniculatus", + "allium_triquetrum", + "clematis_tangutica", + "robinia_viscosa", + "millepertuis_perfor\u00e9", + "hydrangea_arborescens", + "monarda_fistulosa", + "calamagrostis_acutiflora", + "tamier", + "cornus_florida", + "cytisus_multiflorus", + "mol\u00e8nes", + "amaranthus_caudatus", + "silene_latifolia", + "gymnocladus_dioica", + "filao", + "botrychium_lunaria", + "fraxinus_velutina", + "anagallis_tenella", + "combretum_erythrophyllum", + "tetragonia_tetragonioides", + "monarda_pectinata", + "fagus_sylvatica", + "gentiana_andrewsii", + "acrocarpus_fraxinifolius", + "cupressus_lusitanica", + "salix_pentandra", + "aureolaria_virginica", + "rubus_spectabilis", + "prunus_subcordata", + "drosophyllum_lusitanicum", + "crataegus_laevigata", + "plagianthus_betulinus", + "anemone_virginiana", + "quercus_lyrata", + "collinsia_parviflora", + "plantes", + "acer_circinatum", + "salix_repens", + "sabina", + "arum", + "silene_uniflora", + "seibo", + "dracunculus_vulgaris", + "pinus_attenuata", + "polygala_alba", + "v\u00e9ronique_agreste", + "acacia_melanoxylon", + "cyperus_papyrus", + "pavot", + "agrostis_canina", + "saccharomyces_cerevisiae", + "ballote", + "listera_cordata", + "carya_laciniosa", + "platymiscium_pinnatum", + "salicaire", + "tropaeolum_peregrinum", + "boletus_edulis", + "saccharum_officinarum", + "hydrangea_paniculata", + "ambrette", + "buckeye", + "campanula_trachelium", + "ranunculus_bulbosus", + "cassave", + "mor\u00e8ne", + "erythronium_americanum", + "taraxacum_officinale", + "l_\u00e9rable_\u00e0_sucre", + "arenaria_serpyllifolia", + "solenostemon_scutellarioides", + "daphne_cneorum", + "fraxinus_pennsylvanica", + "iris_persica", + "juglans_californica", + "viburnum_dentatum", + "erica_cinerea", + "dracaena_draco", + "campanula_rotundifolia", + "phytolacca_dioica", + "columbine", + "medicago_intertexta", + "crotalaria_spectabilis", + "plante_parasite", + "campanula_glomerata", + "phaseolus_lunatus", + "marum", + "lonicera_tatarica", + "pachyrhizus_tuberosus", + "schizanthus", + "hypochaeris_radicata", + "sawi", + "actinidia_deliciosa", + "dalbergia_latifolia", + "polystichum_aculeatum", + "anemopsis_californica", + "marathi", + "peste_des_eaux", + "anemone_pulsatilla", + "beta_vulgaris", + "eucalyptus_amygdalina", + "prunus_lyonii", + "cerastium_alpinum", + "cypripedium_fasciculatum", + "pleurotus_ostreatus", + "allium_ursinum", + "pseudotsuga_menziesii", + "monotropa_uniflora", + "stephanomeria_malheurensis", + "tanacetum_parthenium", + "erythrina", + "lithospermum_officinale", + "arisaema_dracontium", + "blephilia_hirsuta", + "senna_alexandrina", + "haricots_verts", + "vangueria_infausta", + "asparagus_plumosus", + "heracleum_sphondylium", + "crataegus_aestivalis", + "drimys_winteri", + "erigeron_pulchellus", + "phlox_subulata", + "lathyrus_sylvestris", + "bucar\u00e9", + "sois_prudente", + "sida_hermaphrodita", + "symphytum_officinale", + "solidago_nemoralis", + "dicentra_canadensis", + "armillaires", + "rosa_moschata", + "viola_tricolor", + "viburnum_opulus", + "allium_vineale", + "dion\u00e9e", + "gentiana_saponaria", + "malaguette", + "salvia_farinacea", + "tang\u00e9rois", + "samanea_saman", + "calla", + "calocedrus_decurrens", + "lupinus_arboreus", + "coix_lacryma_jobi", + "arctostaphylos_manzanita", + "erythronium_montanum", + "cassissier", + "vaccinium_ovatum", + "prunus_serrulata", + "galium_verum", + "la_beno\u00eete_\u00e0_trois_fleurs", + "cycas_circinalis", + "populus_nigra", + "mentha_longifolia", + "nasturtium", + "aster_maritime", + "muscari_comosum", + "stenotaphrum_secundatum", + "artemisia_filifolia", + "cerfeuil_commun", + "ranunculus_repens", + "berberis_canadensis", + "apocynum_androsaemifolium", + "veluette", + "strelitzia_reginae", + "agathis_australis", + "bourdaine", + "lemna_minor", + "pelin", + "larix_laricina", + "chardon_dore", + "ornier", + "pyrola_rotundifolia", + "colocasia_esculenta", + "ustilago_maydis", + "inga_edulis", + "edelweiss", + "anemone_tetonensis", + "lonicera_albiflora", + "trifolium_stoloniferum", + "hypericum_calycinum", + "piper_betle", + "hypericum_perforatum", + "allium_fistulosum", + "anthurium_scherzerianum", + "callitris_cupressiformis", + "tangerine", + "fromental", + "salix_arctica", + "conyza_canadensis", + "phacelia_campanularia", + "gentiana_calycosa", + "campanula_aparinoides", + "amaranthus_hypochondriacus", + "solidago_multiradiata", + "lithocarpus_densiflorus", + "stellaire_interm\u00e9diaire", + "cormier", + "alnus_glutinosa", + "cnidoscolus_urens", + "diplotaxis_erucoides", + "cypripedium_montanum", + "eucalyptus_calophylla", + "arctium_minus", + "arrhenatherum", + "eucalyptus_pauciflora", + "annona_reticulata", + "pinus_muricata", + "paris_quadrifolia", + "chrysanthemum_morifolium", + "phytolacca_americana", + "nicotiana_rustica", + "lathyrus_sativus", + "oxalis", + "anthriscus_sylvestris", + "belladonna", + "campanula_pyramidalis", + "pteridium_aquilinum", + "polygala_lutea", + "begonia_cheimantha", + "pitchpin", + "maianthemum_canadense", + "barbar\u00e9e", + "panicum_capillare", + "lathyrus_splendens", + "begonia_socotrana", + "salvia_sclarea", + "larix_russica", + "aristolochia_clematitis", + "allium_ampeloprasum", + "catharanthus_roseus", + "crataegus_mollis", + "ageratum_houstonianum", + "cephalanthera_rubra", + "vangueria_madagascariensis", + "ou_pour_les_francophones_d_am\u00e9rique_le", + "abies_bracteata", + "poa_nemoralis", + "soyez_prudent", + "corylus_cornuta", + "solidago_spathulata", + "attier", + "barbar\u00e9e_commune", + "iris_virginica", + "lotus_tetragonolobus", + "arctostaphylos_uva_ursi", + "hieracium_aurantiacum", + "prosopis_pubescens", + "putier", + "dragonnier", + "chrysanthemum", + "agrimonia", + "myrica_gale", + "fausse_morille", + "allium_scorodoprasum", + "chardon_marie", + "vallisneria", + "holcus_mollis", + "erythrina_variegata", + "platanthera_chlorantha", + "rosa_banksiae", + "acer_glabrum", + "rubus_canadensis", + "epipactis_gigantea", + "euphorbia_milii", + "ataca", + "taxus_floridana", + "begonia_tuberhybrida", + "rubus_occidentalis", + "paradisea_liliastrum", + "piloselle", + "hakea_laurina", + "castanea", + "rudbeckia_hirta", + "brem", + "phyllostachys_bambusoides", + "oreille_de_souris", + "beaumontia_grandiflora", + "grand_plantain", + "physalis_peruviana", + "parthenium_integrifolium", + "sambucus_ebulus", + "salice", + "rubus_odoratus", + "j\u00edcama", + "hamamelis_virginiana", + "arctostaphylos_tomentosa", + "quercus_virginiana", + "sarcocephalus_latifolius", + "gossypium_thurberi", + "podocarpus_latifolius", + "dicksonia_antarctica", + "muscari_neglectum", + "baccharis_pilularis", + "magnolia", + "eucalyptus_regnans", + "galium_boreale", + "centaurea_gymnocarpa", + "ulmus_hollandica", + "nephrolepis_exaltata", + "asclepias_meadii", + "pterocarpus_macrocarpus", + "quercus_texana", + "phellodendron_amurense", + "hevea_brasiliensis", + "cordyline_australis", + "ranunculus_aquatilis", + "avena_barbata", + "amanite", + "polypodium_vulgare", + "bromus_secalinus", + "anemone_occidentalis", + "pinus_palustris", + "conium_maculatum", + "takamaka", + "plantago_media", + "mahonia_nervosa", + "erythrina_corallodendrum", + "oenanthe_crocata", + "lotus_berthelotii", + "artemisia_maritima", + "ranunculus_acris", + "t\u00eate_de_maure", + "cirsium_arvense", + "centaurea_imperialis", + "cypripedium_reginae", + "alpinia_officinarum", + "castagner", + "abronia_villosa", + "andromeda_polifolia", + "teucrium_canadense", + "pinus_echinata", + "malacothamnus_fasciculatus", + "verbascum_lychnitis", + "betula_papyrifera", + "phyllostachys_aurea", + "rosa_damascena", + "euphorbe_h\u00e9t\u00e9rophylle", + "pterocarpus_angolensis", + "parisette", + "alliaire_officinale", + "digitaire", + "achill\u00e9e", + "anchusa_capensis", + "cl\u00e9matite", + "salix_pyrifolia", + "camellia_japonica", + "nothofagus_truncata", + "solanum_quitoense", + "tritoma", + "tang\u00e9roise", + "podocarpus_nivalis" + ], + "JOB": [ + "assistant", + "racker", + "minter", + "tiroir", + "tamponneuse", + "persona_grata", + "videur", + "falconer", + "teaser", + "verger", + "galvaniser", + "pigiste", + "le_facteur", + "cornac", + "guru", + "vanesse", + "ramoneur", + "labourer", + "mercator", + "warder", + "myod\u00e9sopsie", + "l_heure_des_sorci\u00e8res", + "indexer", + "stripteaseuse", + "savonner", + "l_habilleur", + "barbier_chirurgien", + "nettoyeur", + "carangue_coubali", + "shearer", + "laiti\u00e8re", + "mariner", + "scratcher", + "parleur", + "businessman", + "manageuse", + "assistent", + "obst\u00e9tricien", + "attendant", + "houseman", + "dermatologue", + "quartier_ma\u00eetre_de_deuxi\u00e8me_classe", + "speaker", + "la_majeur", + "magasinier", + "ranger", + "arrimeur", + "cano\u00e9iste", + "packer", + "huntress", + "de_taille", + "make", + "runner", + "gouverneure", + "alderman", + "dinandier", + "the_ecologist", + "enrouleuse", + "adang", + "employable", + "dresser", + "\u00e9clairagiste", + "foulon", + "lascar", + "hand", + "hussard", + "blanchisseuse", + "luthier", + "the_lifeguard", + "compositeur", + "jeteur", + "registrar", + "meuni\u00e8re", + "charg\u00e9_de_cours", + "territoriale", + "gestionnaire", + "garagiste", + "grenadir", + "serdar", + "travailleuse", + "obst\u00e9tricienne", + "d_artagnan", + "sexton", + "riveteur", + "dressoir", + "demonstrator", + "rob_overseer", + "briscard", + "affranchisseur", + "gallant", + "temp", + "registraire", + "don", + "infirmier", + "varlet", + "h\u00f4tesse", + "stevedore", + "king", + "planter", + "gastro_ent\u00e9rologue", + "hydrogiste", + "coyote", + "berg\u00e8re", + "caporal", + "mahout", + "cleaner", + "valet", + "proth\u00e9siste_dentaire", + "neurologue", + "cin\u00e9aste", + "carver", + "the_police", + "routeur", + "pastourelle", + "pr\u00e9sidente", + "sauveteur", + "the_sentinel", + "ergoth\u00e9rapeute", + "parajuriste", + "cuirassier", + "moussaillon", + "char", + "carrier", + "marien", + "dramaturge", + "la_ratte", + "sommelier", + "caissi\u00e8re", + "charpentier", + "cataloguer", + "riveter", + "paral\u00e9gal", + "doge", + "\u00e9chevin", + "gentleman", + "endocrinologiste", + "lister", + "statisticien", + "le_docteur", + "ost\u00e9opathe", + "cuirassiers", + "dellal", + "habilleur", + "guerri\u00e8re", + "poti\u00e8re", + "territorial", + "hussards", + "serran", + "dessinateur", + "perruqui\u00e8re", + "gaffer", + "brancardi\u00e8re", + "marchande", + "bouteiller", + "paediatrician", + "brancardier", + "grip", + "para", + "router", + "se_porter_volontaire", + "cartographe", + "fermi\u00e8re", + "herboriste", + "bourgmestre", + "chief", + "b\u00e9n\u00e9vole", + "le_correcteur", + "sensei", + "arrowsmith", + "thatcher", + "relieur", + "doreuse", + "cook", + "statisticienne", + "couturier", + "mastermind", + "harponneur", + "aouteron", + "buteuse", + "tonnelier", + "argousin", + "autrice", + "trainer", + "land", + "agenda_\u00e9lectronique", + "nourrice", + "boss", + "doreur", + "vigilante", + "le_propri\u00e9taire", + "planificateur", + "mousquetaire", + "barmaid", + "en_main", + "shifu", + "transcripteur", + "chaumier", + "revendeur", + "greffier", + "butler", + "graphiste", + "cartooniste", + "machiniste", + "grenadier", + "stadiaire", + "neurochirurgien", + "stewardesse", + "surgeon", + "overseer", + "pitman", + "jeff_richards", + "vaquero", + "cytog\u00e9n\u00e9ticien", + "muletier", + "esclaves", + "cordi\u00e8re", + "escobar", + "manufacturer", + "cutter", + "brigadier", + "syntonisateur", + "freelance", + "scientist", + "leader", + "laveur", + "kamikaze", + "driver", + "endocrinologue", + "wheeler", + "se_proposer", + "slavey", + "formateur", + "inventeur", + "le_proviseur", + "the_advocate", + "enregistreur", + "performer", + "fondatrice", + "bardach", + "page", + "protestataire", + "domesticit\u00e9", + "sergent", + "tanner", + "marguillier", + "le_directeur_de_la_photographie", + "fantassin", + "interne", + "interpr\u00e9teur", + "luftmarschall", + "baker", + "avou\u00e9", + "bureaucrate", + "chimiste", + "publicateur", + "troller", + "gribouilleuse", + "barreur", + "divertisseur", + "freelancer", + "surintendant", + "cadi", + "accisien", + "le_liseur", + "perruquier", + "plombeur", + "le_professeur", + "tapissier", + "courser", + "lancer", + "master", + "tondeur", + "percepteur", + "the_guardian", + "pacificatrice", + "dumoulin", + "boulanger", + "agricultrice", + "dyer", + "manutentionnaire", + "nullifier", + "bischof", + "l_astronome", + "seller", + "une_nounou_d_enfer", + "mandarin", + "auriste", + "ferblantier", + "baleinier", + "setter", + "l_effet_glee", + "herder", + "groom", + "chargeuse", + "sommeli\u00e8re", + "justicier", + "courtier", + "mason", + "r\u00e9gatier", + "fowler", + "bunny", + "mate", + "nettoyeuse", + "terrassier", + "guide", + "param\u00e9dic", + "adjudant_g\u00e9n\u00e9ral", + "le_dentiste", + "l_horloger_de_saint_paul", + "d\u00e9coupure", + "galvaniseur", + "bader", + "m\u00e9treur", + "very_bad_trip", + "angler", + "dessinatrice", + "manageur", + "designer", + "g\u00e9rante", + "foreman", + "standardiste", + "the_babysitter", + "chasseresse", + "marshal", + "barrister", + "marguilli\u00e8re", + "chevrier", + "grouillot", + "rapporteur", + "scieur", + "horloger", + "carreleur", + "non_inscrit", + "g\u00e9rant", + "stewardess", + "cuisiner", + "diplomate", + "presbytre", + "plaisancier", + "squire", + "bouvi\u00e8re", + "fellah", + "relieuse", + "tailleuse", + "horlog\u00e8re", + "boutiqui\u00e8re", + "pharmacologue", + "cropper", + "tourneur", + "mellah", + "gaucho", + "corporal", + "beadle", + "attendante", + "collectionneuse", + "microbiologiste", + "neurologiste", + "slave", + "le_clandestin", + "pastoureau", + "dancer", + "cultivatrice", + "chevri\u00e8re", + "essayiste", + "ballonniste", + "the_consul", + "ergonomiste", + "sifu", + "the_economist", + "collier", + "infanteriste", + "manager", + "barbier", + "broker", + "wetter", + "p\u00e9riodontiste", + "carter", + "porter", + "chalutier", + "raffineur", + "fondeur", + "coupeur", + "stripper", + "ma\u00e7on", + "drogan", + "parleuse", + "styliste", + "carabinier", + "compositeurs", + "cop", + "barista", + "colonel", + "flanker", + "boulang\u00e8re", + "conseiller_municipal", + "vigilantisme", + "scoreur", + "coloniste", + "barber", + "droguiste", + "neurochirurgienne", + "aconier", + "traqueur", + "le_m\u00e9decin_d_ispahan", + "gribouilleur", + "chanceli\u00e8re", + "principal", + "huissier", + "man", + "immunologiste", + "mairesse", + "doc", + "collecteur", + "caster", + "physicien_physicienne", + "logger", + "gouverneur", + "savante", + "covergirl", + "statthalter", + "marine", + "arroseur", + "douani\u00e8re", + "coadjuteur", + "businesswoman", + "the_boxer", + "mapper", + "aguiche", + "strafer", + "h\u00e9matologue", + "wallah", + "le_briseur_de_gr\u00e8ve", + "subr\u00e9cargue", + "serrurier", + "l\u00e9v\u00eaque", + "the_hire", + "coursi\u00e8re", + "the_machinist", + "m\u00e9decin_traitant", + "usher", + "messenger", + "varans", + "chauffeur", + "solliciteur", + "plombier", + "mandataire_social", + "lacer", + "th\u00e9rapeute", + "composer", + "fossoyeur", + "au_pair", + "anthologiste", + "buteur", + "proconsul", + "lanciers", + "cox", + "bombardier", + "metteur", + "schiava", + "pharmacologiste", + "brigadi\u00e8re", + "trier", + "cameraman", + "syntoniseur", + "ploter", + "plotter", + "myiod\u00e9sopsie", + "grouille", + "tracker", + "melter", + "charron", + "dermatologiste", + "cardiologue", + "calligraphe", + "chancelier", + "croupier", + "s\u00e9n\u00e9chal", + "steward", + "gouvernante", + "morillon", + "michel_morin", + "boutiquier", + "caniveau", + "proctologue", + "laryngologue", + "troupier", + "horologiste", + "le_sang_du_diamant", + "gardienne", + "concierge", + "la_laiti\u00e8re", + "marshall", + "doula", + "docker", + "jardini\u00e8re", + "tuner", + "l_interpr\u00e8te", + "pharmacienne", + "sub", + "parer", + "romancier", + "hydrog\u00e9ologue", + "the_independent", + "solicitor", + "bishop", + "exploitant", + "coolie", + "timonier", + "cookie", + "sculpteur", + "personnelle", + "esquire", + "chaudronnier", + "amuseur", + "ergonome", + "friseuse", + "regular", + "esquisseur", + "charpenti\u00e8re", + "gatekeeper", + "autor", + "lieutenant", + "gourou", + "aurige", + "cornaquer", + "le_cerveau", + "interpr\u00e8te" + ], + "ANIMAL": [ + "marsouiner", + "panth\u00e8re_n\u00e9buleuse", + "peste_am\u00e9ricaine", + "martre", + "acherontia", + "quiscale", + "apodemus", + "cat", + "monachus_schauinslandi", + "renard_volant", + "zober", + "grand_barracuda", + "buteo", + "desmodontinae", + "moineau", + "la_mouette", + "bruche", + "drosophila", + "homo_sapiens_sapiens", + "chardonneret", + "pic_barbu", + "ours_brun", + "sinanthrope", + "la_panth\u00e8re_noire", + "l_\u00e2ne", + "hurleurs", + "vendangeron", + "diplopodes", + "condors", + "pic_des_saguaros", + "maguy", + "bondr\u00e9e", + "le_grand_cor\u00e9gone", + "cochon_d\u2019_inde", + "bihoreau", + "bor\u00e9id\u00e9s", + "sternini", + "hydrophiid\u00e9s", + "woodlouse", + "pic_\u00e0_face_blanche", + "lemmus_lemmus", + "sitta_europaea", + "nasique", + "billy_elliot", + "ophidiid\u00e9", + "squatiniformes", + "anthonome", + "tyrannid\u00e9s", + "cavaleur", + "thomson's_gazelle", + "passereau", + "squatine", + "manta", + "grand_nacr\u00e9", + "loutre", + "sitta_carolinensis", + "roselin_familier", + "langoustine_commune", + "mouarf", + "martres", + "dor\u00e9e", + "roucouler", + "carduelis", + "ours_noir", + "lagotriche", + "eretmochelys", + "effraie", + "haridelle", + "agriote", + "piranga_olivacea", + "moschid\u00e9s", + "grand_cachalot", + "sea_slug", + "mantodea", + "lactobacillus_acidophilus", + "colubrid\u00e9s", + "grand_chevalier", + "platyrrhiniens", + "vivaneau", + "interpr\u00e9tation_cons\u00e9cutive", + "grand_t\u00e9tras", + "hirondelle_des_granges", + "kaloupil\u00e9", + "pieris_brassicae", + "achiropsettidae", + "leucopt\u00e8re", + "ferret", + "brachypteraciidae", + "chaus", + "duc", + "le_chat", + "chaetodontid\u00e9s", + "h\u00e9matobie", + "crow", + "oriolo", + "ours_brun_de_syrie", + "bouquetin", + "ours_blanc", + "infection_herp\u00e9tique", + "vibe", + "la_langoustine", + "diamondback", + "fouine", + "bis_\u00e0_cou_noir", + "artiodactyles", + "chlorophytes", + "rupicole", + "micropterus", + "pic_macul\u00e9", + "fratercula_arctica", + "martes_martes", + "faina", + "chardonneret_\u00e9l\u00e9gant", + "womanizer", + "globic\u00e9phale", + "galgo", + "guaco", + "malure", + "petit_polatouche", + "grand_h\u00e9ron", + "oc\u00e9anite", + "touladi", + "raven", + "la_gu\u00eape", + "homo_sapiens", + "muscardin", + "dynastinae", + "harrier", + "baribal", + "ammospermophile", + "carabao", + "du_pauvre", + "lakeland_terrier", + "muscicapid\u00e9s", + "passer", + "pic_goertan", + "bernarche", + "hippotrague_noir", + "condor", + "hydropote", + "chevreuil", + "gerbillus_jamesi", + "chat_persan", + "the_crow", + "cagne", + "brachyote", + "blattopt\u00e8res", + "cyanophyceae", + "bousier", + "cocker", + "terrier_sealyham", + "ours_polaire", + "prunus_tenella", + "cancrelat", + "gonnelle", + "daims", + "cro_magnon", + "bruchinae", + "tetraoninae", + "accipiter", + "homme_de_cro_magnon", + "oriole", + "greyhound", + "mantopt\u00e8res", + "loir_gris", + "virus_du_nil_occidental", + "stieglitz", + "falcon", + "trombidium", + "perchaude", + "ours_noir_d_asie", + "e_coli", + "mizuhiki", + "koter", + "drosophile", + "le_corbeau", + "baudet", + "lingue_franche", + "manicou", + "thomomys_talpoides", + "banteng", + "guillemot_colombin", + "palombe", + "greater_scaup", + "bruches", + "pycnogonides", + "lion_marin", + "virus_marburg", + "couleuvre_verte", + "frelon", + "sergent_major", + "pinctada_margaritifera", + "arthropode", + "la_gu\u00eape_commune", + "platyrhiniens", + "donald_duck", + "pic_mineur", + "cafard", + "salmo_salar", + "pic_chryso\u00efde", + "petit_fourmilier", + "sanicula_europaea", + "ath\u00e9rure", + "loriquet_versicolore", + "pic_d_elliot", + "bernache_cravant", + "iller", + "planirostre", + "sarcophile", + "blattes", + "priodonte", + "eiders", + "conraua_goliath", + "wisent", + "berner_sennenhund", + "carencro", + "bungare", + "diplopode", + "martes_foina", + "bartavelle", + "cariacou", + "ammospermophilus", + "megascops", + "petit_sylvain", + "sable", + "capreolus_capreolus", + "bombyx", + "dynastin\u00e9s", + "chlorophylle_d", + "branta_bernicla", + "grosse_vrillette", + "staphylinid\u00e9s", + "courtili\u00e8re", + "arthropoda", + "ours_panda", + "mahonia_aquifolium", + "z\u00e9e", + "lion_de_mer", + "sarcophagidae", + "kond\u00f4z", + "alouates", + "cochenilles", + "tamanoir", + "estorlet", + "bradype", + "la_gerbille_de_mongolie", + "marsouin", + "sheltie", + "platanistid\u00e9s", + "terrier_gallois", + "mille_pattes", + "hystricid\u00e9s", + "carabe", + "terrier_australien", + "virus_varicelle_zona", + "mante", + "pic_flamboyant", + "tamia", + "merle", + "cervid\u00e9s", + "gerbo", + "amstaff", + "baleine_bor\u00e9ale", + "bernache_nonnette", + "draine", + "sitta_canadensis", + "mantis", + "primula_vulgaris", + "spongieuse", + "limule", + "limicoles", + "martinet_ramoneur", + "loriot", + "gymnorhina", + "martre_commune", + "le_z\u00e8bre_des_plaines", + "cathartid\u00e9s", + "campagnol", + "pic_d_arizona", + "belouga", + "mane", + "santa_gertrudis", + "grand_corbeau", + "alticinae", + "whippet", + "anatife", + "zeus_faber", + "roucoulement", + "rhodophytes", + "pseudoscorpions", + "barramundi", + "osteichtyes", + "pic_\u00e0_t\u00eate_rouge", + "yorkshire_terrier", + "lemming", + "eagle", + "caponner", + "tortora", + "wezel", + "patronne", + "hirondelle_de_chemin\u00e9e", + "drenne", + "vole", + "potamogale", + "maladie_\u00e0_virus_ebola", + "hydrophiidae", + "bernache", + "ch\u00e9lydre", + "shad", + "merel", + "ours_kermode", + "chelydra", + "ranid\u00e9s", + "martes_zibellina", + "dactylopt\u00e9rid\u00e9", + "irish_wolfhound", + "canardage", + "microbes", + "p\u00e9rissodactyle", + "hirondelle_rousseline", + "p\u00e9dionomid\u00e9", + "peristediidae", + "erignathus", + "pedunculata", + "eider", + "abad\u00e8che", + "artiodactyle", + "balane", + "hemitripteridae", + "arvicola", + "pintade", + "mille_pieds", + "luberne" + ], + "ORG": [ + "m\u00e9lanobutyrophtalmie", + "dominion", + "the_united_states_postal_service", + "alli\u00e9s", + "nieuwer_amstel", + "shinto", + "de_temps_\u00e0_autre", + "le_libre_arbitre", + "je_t\u2019_aime", + "cour_constitutionnelle", + "justice", + "et_coll", + "la_main_dans_le_sac", + "saint_r\u00e9my", + "au_grand_jamais", + "san_jos\u00e9", + "gironde", + "je_vous_aime", + "radiogalaxie", + "drug_enforcement_administration", + "jinisme", + "wicca", + "la_b\u00e9mol_majeur", + "jan_mayen", + "un_homme_\u00e0_la_mer", + "ins", + "s_gravenambacht", + "nist", + "shakers", + "transportation", + "aller_se_faire_pomper_chez_les_grecs", + "qui_est_ce_que", + "les_griffin", + "sint_amands", + "police_municipale", + "aa", + "la_science_et_la_culture", + "embarqu\u00e9", + "nasa", + "troisi\u00e8me_parti", + "le_droit", + "le_chesne", + "second_empire", + "arda", + "in_vivo", + "les_twist", + "le_nec_plus_ultra", + "huang_he", + "bollywood", + "ang", + "clinique_psychiatrique", + "le_chat_noir", + "la_trobe", + "la_poste", + "in_utero", + "cocard", + "europol", + "schutzstaffel", + "minshut\u014d", + "bakkie", + "la_bave_du_crapaud_n_atteint_pas_la_blanche_colombe", + "chorus_line", + "tiers_\u00e9tat", + "la_com\u00e9die_des_erreurs", + "the_who", + "action_collective", + "la_tour_de_babel", + "ad_libitum", + "non_plus_ultra", + "haganah", + "the_planetary_society", + "aller_simple", + "au_miroir", + "porte", + "college", + "le_berceau_du_chat", + "central_city", + "san_francisco", + "vivat", + "un", + "war_machine", + "vid\u00e9oconf\u00e9rence", + "en_vol", + "militant_tendancy", + "zone_industrielle", + "parti_vert", + "sainte_sophie", + "forces_canadiennes", + "champ_scalaire", + "flashmob", + "v\u0129nh_long", + "postkantoor", + "nara", + "talons", + "notre_dame_des_douleurs", + "sarl", + "mon_nom_est", + "csars", + "va", + "parti_nazi", + "front_populaire", + "sparkle_computer", + "col_legno", + "cour_supr\u00eame", + "sainte_ursule", + "militant_tendency", + "parti_travailliste_australien", + "pain_perdu", + "gao", + "saint_jacques", + "il_\u00e9tait_une_fois", + "dot", + "sint_gillis_waas", + "association_professionnelle", + "core", + "pas_touche", + "allies", + "castel_campagnano", + "ad_lib", + "qui_est_ce_qui", + "collectivit\u00e9_locale", + "c_est_le_must", + "le_sens_commun", + "saint_vincent", + "bluejean", + "de_concert", + "cap_vert", + "parti_lepep", + "ec", + "ho_chunk", + "john_tuzo_wilson", + "p\u00f4", + "the_faculty", + "don_juan", + "bisounours", + "les_raisins_de_la_col\u00e8re", + "tu_es_qui", + "the_new_school", + "ai", + "sauce_chili", + "garden_party", + "s_f", + "ds", + "chiang_mai", + "et_al", + "passage_du_nord_ouest", + "force_a\u00e9rienne", + "parti_de_l_environnement_les_verts", + "parti_r\u00e9publicain", + "dia", + "winnie_l_ourson", + "mariage_gay", + "montagne_des_oliviers", + "porte_tournante", + "b\u00e9n\u00e9lux", + "escarpins", + "m\u00e9rovingiens", + "de_pointe", + "sturmtruppen", + "villanova_di_camposampiero", + "gatt", + "marie_ange", + "s_gravenhoek", + "aller_en_enfer", + "ab_initio", + "valle_san_nicolao", + "parti_national_socialiste_des_travailleurs_allemands", + "parasport", + "anase", + "le_mans", + "ham_les_moines", + "partis_verts_\u00e0_travers_le_monde", + "la_soci\u00e9t\u00e9", + "doe", + "caf\u00e9_au_lait", + "petite_capitalisation", + "ouder_amstel", + "\u00e9glise_catholique", + "cherbourg_octeville", + "the_breakfast_club", + "parti_d\u00e9mocrate", + "tiers_monde", + "shabak", + "defense", + "fonction_publique", + "rabindranath_tagore", + "al_a\u00efn", + "gestapo", + "de_novo", + "\u00e2ge_d_airain", + "s_en_sortir_sans_perte", + "une_\u00e9ducation", + "sept_heures", + "westkapelle_binnen", + "sint_pieters_leeuw", + "de_luxe", + "the_full_monty", + "pac", + "grande_puissance", + "parti_conservateur", + "nieuw_ginneken", + "li_fi", + "parti_d\u00e9mocratique", + "houd", + "empires_centraux", + "maquis", + "une_nouvelle_fois", + "calinours", + "m\u00e9gadonn\u00e9es", + "qui_\u00eates_vous", + "the_young_turks", + "le_silence_des_agneaux", + "krivoy_rog", + "le_monde", + "who_are_you", + "lac_des_bois", + "h\u00f4tel_communal", + "syndicat_professionnel", + "de_vuursche", + "i_ching", + "gomme_\u00e0_m\u00e2cher", + "babyboom", + "tchang", + "petit_poucet", + "chiang_rai", + "al_jazeera", + "droit_civil", + "saint_l\u00e9onard", + "chewing_gum", + "ham_sur_heure_nalinnes", + "la_chaux", + "un_aller_simple", + "disa", + "je_m_appelle", + "notodontid\u00e9", + "grandview", + "assembl\u00e9e_nationale", + "s\u00e3o_paulo", + "parti_du_peuple", + "europe", + "terre_br\u00fbl\u00e9e", + "po", + "addis_ababa", + "the_opposition", + "encabaner", + "centre_historique", + "sur_le_plat", + "classe_ouvri\u00e8re", + "\u00e9glise_catholique_apostolique_romaine", + "march\u00e9_financier", + "mossad", + "parti_du_travail", + "nouveau_parti_d\u00e9mocratique", + "hare_krishna", + "arm\u00e9e_de_l\u2019_air", + "de_jour", + "dividivi", + "nautilus_pompilius", + "sauce_piquante", + "orioles_de_baltimore", + "la_derni\u00e8re", + "ayuntamiento", + "ap\u00f4tre_andr\u00e9", + "cyanophtalme", + "hollywood", + "cid", + "ja\u00efnisme", + "domezain_berraute", + "h\u00eenay\u00e2na", + "sint_oedenrode", + "congr\u00e9gationalisme", + "parti_anti_ma\u00e7onnique", + "gukhoe", + "saint_barth\u00e9lemy", + "qui_trouve_garde", + "andr\u00e9_sens_et_origine_du_nom", + "asile_psychiatrique", + "sturmabteilung", + "le_commando_de_sa_majest\u00e9", + "la_nuit_des_juges", + "parti_d\u00e9mocrate_r\u00e9publicain", + "carr\u00e9_latin", + "los_angeles", + "vous_\u00eates_qui", + "dans_l_autre_sens", + "les_trois_s\u0153urs", + "en_commun", + "le_vigan", + "qu_est_ce_qu_il_y_a", + "ad_hoc", + "sainte_foi", + "salade_de_fruits", + "campiglia_cervo", + "notre_dame_de_montauban", + "or_blanc", + "city_hall", + "mi", + "by_the_way", + "bataillon", + "la_vie", + "union_internationale_des_t\u00e9l\u00e9communications", + "le_ou_vers_le", + "alla_polacca", + "\u00e0_la_pointe", + "syndicalisme_jaune", + "in_situ", + "san_cataldo", + "galerie_d\u2019_art", + "spet", + "sint_martens_latem", + "arm\u00e9e_de_l_air", + "science_chr\u00e9tienne", + "sa", + "le_soir", + "germanistique", + "stups", + "droit_romain", + "le_brouet_des_sorci\u00e8res", + "i_love_you", + "doc", + "lucienne", + "le_coq", + "caesalpinia_coriaria", + "coll\u00e8ge", + "la_f\u00eate_\u00e0_la_maison", + "lac_sup\u00e9rieur", + "soit_disant", + "l_essence_de_l_art", + "les_quatre", + "notre_dame_des_sept_douleurs", + "la_selve", + "village_olympique", + "p\u00e9troli\u00e8re", + "l_\u00e9tat_de_la_technique", + "saint_nicolas_de_myre", + "ace", + "c_est_en_forgeant_qu_on_devient_forgeron", + "la_belle_au_bois_dormant", + "commerce", + "banque_centrale", + "blue_jeans", + "sainte_barbe", + "streptococcus_pyogenes", + "\u00e9ua", + "porte_tambour", + "eu", + "aller_crever", + "\u00e2ge_d_or", + "corps_a\u00e9rien_irlandais", + "militaires", + "chang_jiang", + "rapports", + "l_union_fait_la_force", + "morgenstern", + "s_\u00e9puiser_\u00e0_la_t\u00e2che", + "franco_britannique", + "\u00e9tablissement_d_enseignement", + "las_palmas", + "hirundo_rustica", + "maison_communale", + "tom_pouce", + "mont_des_oliviers", + "sainte_h\u00e9l\u00e8ne", + "hautes_fagnes", + "langemark_poelkapelle", + "marine_britannique", + "keys", + "qu_est_ce_qui_se_passe", + "classe_moyenne", + "qui_es_tu", + "parti_conservateur_d_afrique_du_sud", + "in_vitro", + "lac_sainte_claire", + "guomindang", + "march\u00e9_boursier", + "lapine", + "croix_rouge", + "chambre_basse", + "s\u00e3o_tom\u00e9", + "tao\u00efsme", + "cour_sup\u00e9rieure", + "\u00e9milie_simon", + "entre_guillemets", + "assembl\u00e9e_nationale_de_la_r\u00e9publique_serbe_de_bosnie" + ], + "LOCATION": [ + "al_jazeera", + "la_plata", + "rocca_imperiale", + "de_wolden", + "la_dalle", + "hai_duong", + "plantago_lanceolata", + "alt_treptow", + "belle_au_bois_dormant", + "hippodrome", + "the_good_night", + "de_rien", + "pommeraie", + "sint_margriete", + "trifolium_pratense", + "\u00e0_ton_service", + "so_what", + "composante_a\u00e9rienne_militaire", + "rapanui", + "chiens_de_chasse", + "la_foret", + "les_dents_de_la_mort", + "saint_laurent", + "park", + "het_bildt", + "de_l_autre_c\u00f4t\u00e9_du_d\u00e9cor", + "non_plus_ultra", + "la_belle_au_bois_dormant", + "eryngium_maritimum", + "bow_wow", + "united_states_army", + "h\u00f4pitaux_psychiatriques", + "kryvy\u00ef_rih", + "allah_akbar", + "embarqu\u00e9", + "liste_des_\u00e9coles_militaires", + "s_tog", + "grande_aiguille", + "malouines", + "piet_mondrian", + "la_roche_en_ardenne", + "trifolium_repens", + "entre_deux", + "la_manche", + "emiliano_zapata_salazar", + "la_ch\u00e8ze", + "santa_fe", + "sint_maarten", + "petasites_hybridus", + "le_conquet", + "qingmingjie", + "chang_jiang", + "noyeraie", + "h\u00f4pital_psychiatrique", + "greylag_goose", + "sylvaine", + "s\u00e3o_bernardo_do_campo", + "trois_rivi\u00e8res", + "allahu_akbar", + "saint_patrick", + "les_grands_lacs", + "australie_m\u00e9ridionale", + "sainte_foy", + "mont_carmel", + "land", + "de_pinte", + "une_heure_et_quart", + "sainte_h\u00e9l\u00e8ne", + "huang_he", + "r\u00e9publique_du_cap_vert", + "bonsoir", + "saint_vincent", + "le_paradis", + "iris_pseudacorus", + "le_nec_plus_ultra", + "harlan_county", + "sponge_cake", + "ville_satellite", + "pic_noir", + "blue_mountains", + "pierre_blanche", + "kryviy_rih", + "plantago_major", + "allahou_akbar", + "saint_amand", + "ju\u00e1rez", + "cerisaie", + "l_am\u00e9rique", + "bon_voyage", + "plantago_media", + "pas_de_quoi", + "sans_issue", + "asile_de_fous", + "cheval_marin", + "se_mettre_debout", + "bois_le_duc", + "alnus_glutinosa", + "usa", + "centre_ville", + "les_poissons", + "au_cas_que", + "australie_occidentale", + "il_n'y_a_pas_de_quoi", + "liste_des_villes_de_g\u00e9orgie", + "montagnes_guadalupe", + "hat_yai", + "hers_vif", + "arena", + "r\u00e9seau_express_r\u00e9gional", + "nymphalis_polychloros", + "assembl\u00e9e_nationale_de_la_r\u00e9publique_d_azerba\u00efdjan", + "sri_lanka", + "la_cerisaie", + "ce_fut_un_plaisir", + "zhu_jiang", + "tierce_partie", + "de_bilt", + "sint_kruis", + "assembl\u00e9e_nationale_de_saint_christophe_et_ni\u00e9v\u00e8s", + "clinique_psychiatrique", + "al_anbar", + "sint_pieter", + "grande_ville", + "the_rolling_stones", + "catalan_central", + "la_t\u00e8ne", + "cordon_bleu", + "en_cas_de", + "politique_de_la_terre_br\u00fbl\u00e9e", + "man_o'war", + "hers_mort", + "r\u00e9veillon_de_la_saint_sylvestre", + "saint_albans", + "downtown", + "in_amenas", + "les_deux_s\u0153urs", + "s\u00e3o_jo\u00e3o_de_meriti", + "st_augustin", + "de_marne", + "au_cas_o\u00f9", + "court", + "christophe_colomb", + "pieris_brassicae", + "la_vache", + "whooper_swan", + "heitor_villa_lobos", + "louis_joseph_gay_lussac", + "le_trou_noir", + "quartier_d_affaires", + "al_a\u00efn", + "vale_of_glamorgan", + "trifolium_dubium", + "je_vous_remercie", + "pterocarpus_indicus", + "il_y_a_longtemps", + "grandview", + "\u00e9_u", + "c_est_le_must", + "sint_anthonis", + "delonix_regia", + "sur_la_route", + "nouveau_monde", + "prunus_avium" + ], + "RACE": [ + "filipino", + "sudam\u00e9ricain", + "turke", + "am\u00e9rindienne", + "indian_airlines", + "latino", + "french", + "am\u00e9ricains", + "polyn\u00e9sien", + "turk", + "latin", + "africano", + "le_mexicain", + "fran\u00e7aise", + "moyen_oriental", + "esquimaux", + "africaine", + "am\u00e9rindien", + "africain", + "american", + "est_asiatique", + "latinoam\u00e9ricain", + "viet", + "negro", + "latina", + "kazakh" + ], + "DATE": [ + "\u00e9t\u00e9_indien", + "mi_novembre", + "\u00e0_jour_lendemain", + "dog_days", + "la_bonne_paye", + "mi_mai", + "happy_hour", + "toussaint", + "mi_aout", + "mi_mars", + "\u00e9t\u00e9_de_la_saint_martin", + "la_nuit_des_rois", + "apr\u00e8s_jc", + "la_ronde_de_nuit", + "\u00e0_la_derni\u00e8re_minute", + "poste_de_jour", + "couvaison", + "11_septembre", + "mi_janvier", + "hier_aujourd'hui_et_demain", + "maitrank", + "il_est_grand_temps", + "mi_juin", + "demi_vie", + "le_jour_d_apr\u00e8s", + "bissexte", + "mi_d\u00e9cembre", + "ap_jc", + "the_golden_years", + "ou_ce_que_vous_voudrez", + "mi_avril", + "mi_octobre", + "demi_si\u00e8cle", + "assomption_de_marie", + "demi_heure", + "ces_jours_ci", + "vastlap\u00e4ev", + "mi_septembre", + "phase_lut\u00e9ale", + "\u00e9t\u00e9_des_indiens", + "mi_f\u00e9vrier", + "de_notre_\u00e8re", + "mi_juillet", + "calendrier_musulman", + "nouvelle_lune", + "day_watch" + ], + "FOOD": [ + "chiclet", + "olla_podrida", + "citrus_aurantiifolia", + "mousse", + "encas", + "steak_tartare", + "barboute", + "herbes_aromatiques", + "loukoum", + "golden_delicious", + "symphytum_officinale", + "daucus_carota", + "christmas_pudding", + "en_cas", + "vigna_unguiculata", + "granny_smith", + "capsicum", + "rocambole", + "plombi\u00e8res", + "polkagris", + "sauce", + "cakes", + "pickle", + "pinot_noir", + "savouries", + "tapera", + "citronnade", + "entr\u00e9e", + "limettier", + "parmentier", + "et_que_\u00e7a_saute", + "gelato", + "chili", + "laitage", + "red_hot", + "lunch", + "chile", + "pudding", + "pain_dor\u00e9", + "daurade", + "dessert", + "yai", + "tutti_frutti", + "cassonade", + "loukoumia", + "tranche_napolitaine", + "boudin", + "ros\u00e9", + "chiclette", + "achigan_\u00e0_petite_bouche", + "sonchus_oleraceus", + "petit_four", + "omelette", + "pot_au_feu", + "courge_cireuse", + "bifteck_d_aloyau", + "bok_choy", + "juglans_regia", + "cocoa" + ], + "QUANTITY": [ + "chelin", + "voltamp\u00e8re", + "mille_carr\u00e9", + "calorie", + "ne_rien_branler", + "sellette", + "\u00e0_deux_doigts", + "cent_mille", + "shilling", + "pilonner", + "perilleux", + "schilling", + "les_trois_s\u0153urs", + "dinar", + "ton", + "couronne_islandaise", + "dollar", + "riyal", + "parcom\u00e8tre", + "won_nord_cor\u00e9en", + "mille_carr\u00e9e", + "en_t\u00eate_\u00e0_t\u00eate", + "g", + "fourri\u00e8re", + "\u00e0_un_jet_de_pierre", + "rial", + "franc_guin\u00e9en", + "mille_nautique", + "pound", + "wattheure", + "face_\u00e0_face", + "gasterosteus_aculeatus", + "parcm\u00e8tre", + "mille_marin", + "mark_allemand", + "won_sud_cor\u00e9en", + "ton_a", + "esterlin", + "distincts", + "anders_celsius", + "franc_fran\u00e7ais", + "all_inclusive" + ], + "POLITICAL_PARTY": [ + "minshut\u014d", + "partij", + "gironde", + "the_opposition", + "parti_r\u00e9publicain_d\u00e9mocrate", + "nsdap", + "labour", + "kuomintang", + "parti_travailliste", + "parti_socialiste_japonais", + "parti_social_d\u00e9mocrate_d_azerba\u00efdjan", + "parti_socialiste", + "parti_lib\u00e9ral_du_japon", + "parti_national", + "parti_progressiste_conservateur", + "parti_lib\u00e9ral", + "parti_agrarien_de_bi\u00e9lorussie", + "parti_social_d\u00e9mocrate", + "parti_communiste", + "opposition", + "parti_progressiste", + "guomindang", + "kuo_min_tang", + "parti_populaire" + ], + "PERSON_PRONOUN": [ + "thou", + "hers", + "la_v\u00f4tre", + "les_tiennes", + "\u00e0_moi", + "la_sienne", + "i", + "lui_m\u00eame", + "elles_m\u00eames", + "le_v\u00f4tre", + "he", + "la_tienne", + "eux_m\u00eames", + "mine", + "les_siens", + "notre", + "les_miennes", + "nous_m\u00eames", + "our", + "la_mienne", + "les_siennes", + "les_n\u00f4tres", + "la_n\u00f4tre", + "le_sien", + "ours", + "le_mien", + "les_v\u00f4tres", + "le_n\u00f4tre", + "elle_m\u00eame", + "me", + "votre", + "les_miens", + "le_tien", + "my", + "moi_m\u00eame", + "les_tiens", + "vous_m\u00eame", + "vous_m\u00eames", + "us", + "nous_autres" + ], + "FAC": [ + "san_quirino", + "la_montagne_magique", + "sublime_porte", + "schoenberg", + "anges_gardiens", + "11_septembre", + "max_m\u00fcller", + "bella_bella", + "pierre_lev\u00e9e", + "bureau_de_poste", + 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"fagauvea", + "romane", + "bichelamar", + "venda", + "germaine", + "interlingue", + "cornique", + "bachkir", + "esp\u00e9ranto", + "samoen", + "bambara", + "ernest_gagnon", + "akan", + "saint_lucienne", + "assami", + "chamoru", + "sindhi", + "astiquer", + "nootkas", + "village_magique", + "saint_lucien", + "pali", + "navajo", + "ganda", + "aymara", + "manx", + "welsh", + "catalane", + "french", + "deg_xinag", + "malayalam", + "tamoul", + "samo\u00ebn", + "haoussa", + "sama_pangutaran", + "hindi", + "otto_struve", + "tchouvache", + "communaut\u00e9_de_communes_de_chautagne", + "chamorro", + "franco_proven\u00e7al", + "cachemirie", + "f\u00e9ringien", + "hausawa", + "guarani", + "zhuang", + "kanouri", + "sango", + "orloff", + "assamais", + "divehi", + "wallon", + "cachemiri", + "lucienne", + "soundanais", + "tai_hongjin", + "yidiche", + "francoproven\u00e7al", + "bashkir", + "a_hmao", + "samo\u00efen", + "kuanyama", + "l_ha\u00eftien", + "komi", + "lingala", + "mele_fila", + "forgeron", + "hausa", + "portuguesa", + "wolof", + "lao", + "grecques", + "kikuyu", + "speech", + "portugaise", + "tagalog", + "same_du_nord", + "ido", + "john_collins", + "kazakh", + "marathi", + "cassegrain", + "kalaallisut", + "ese_eja", + "quechua", + "chichewa", + "lithuanien", + "bichlamar", + "kannara", + "ese_ejja", + "marshallais", + "samoan", + "kazakhe", + "tonga", + "galicienne", + "kannada", + "chinoise" + ], + "LAW": [ + "non_bis_in_idem", + "class_action", + "p_l", + "les_agressions_sexuelles", + "la_constitution_des_\u00e9tats_unis", + "haute_cour", + "droit_des_\u00e9tats", + "de_son_genre", + "m_tout_le_monde", + "convention_internationale", + "punitifs", + "code_p\u00e9nal", + "droit_des_quirites", + "federal_bureau_of_investigation", + "action_collective", + "droit_continental", + "recours_collectif", + "sui_generis", + "bureau_f\u00e9d\u00e9ral_d_investigation" + ], + "PRODUCT": [ + "jean_baptiste", + "justin_bieber", + "s_il_pla\u00eet_\u00e0_dieu", + "le_petit_fr\u00e8re", + "s_tog", + "la_fin_du_monde", + "cuy", + "multi_plateforme", + "ne_m_oubliez_pas", + "al_jazeera", + "le_chien_des_baskerville", + "trois_royaumes_de_chine", + "o_ring", + "diego_garcia", + "tutti_frutti", + "le_guide_du_voyageur_galactique", + "echinopsis_pachanoi", + "va_loin", + "la_machine_\u00e0_explorer_le_temps", + "est_bon", + "je_suis_d\u00e9sol\u00e9", + "si_dieu_le_veut_bien", + "la_fl\u00e8che", + "les_quatre_saisons", + "la_lettre_\u00e9carlate", + "new_edition", + "cornier", + "ai_cham", + "automitrailleuse", + "saint_vincent", + "et_si", + "ne_m\u2019_oubliez_pas", + "en_souvenir_de", + "glace_plombi\u00e8res", + "les_diamants_sont_\u00e9ternels", + "the_star_spangled_banner", + "ghettoblaster", + "le_feu_follet", + "la_nuit_des_rois", + "plombi\u00e8res", + "monte_cristo", + "saxe_anhalt", + "cap_horn", + "le_seigneur_des_anneaux", + "nouveau_testament", + "city_hall", + "les_deux_s\u0153urs", + "la_ciociara", + "majong", + "after_burner", + "cochon_d_inde", + "boxing_day", + "droits_humains", + "joulupuu", + "de_fait", + "la_dolce_vita", + "deutsche_welle", + "deathcharge", + "all_right", + "grand_chariot", + "\u00e0_grande_vitesse", + "gong", + "ou_ce_que_vous_voudrez", + "tangara_\u00e9carlate", + "les_royaumes_du_nord", + "le_ma\u00eetre_chat_ou_le_chat_bott\u00e9", + "la_terre", + "\u00e0_la_derni\u00e8re_minute", + "par_la_gr\u00e2ce_de_dieu", + "sierra_blanca", + "droits_de_la_personne", + "mario_andretti", + "la_dame_de_pique", + "je_suis_d\u00e9sol\u00e9e", + "\u00e0_toute_\u00e9preuve", + "de_facto", + "la_modification", + "la_lettre_d_amour", + "la_foire_aux_vanit\u00e9s", + "has_been", + "la_divine_com\u00e9die", + "droits_de_l_homme", + "deux_fr\u00e8res", + "y_regarder_\u00e0_deux_fois", + "le_voyage_du_p\u00e8lerin", + "une_maison_de_poup\u00e9e", + "chabraque", + "envoler", + "novo_mesto", + "s\u00e3o_paulo" + ], + "GPE": [ + "san_sostene", + "la_cit\u00e9_de_dieu", + "eau_chaude", + "montalbano_jonico", + "saint_domingue", + "castellazzo_bormida", + "sint_laureins", + "lo_reninge", + "saint_nicolas_de_bari", + "sri_jayawardenapura", + "mille_\u00eeles", + "sint_maarten", + "archipel_des_mille_\u00eeles", + "pandanus_tectorius", + "camisano_vicentino", + "empire_allemand", + "sint_eloois_winkel", + "la_louvi\u00e8re", + "campo_san_martino", + "mer_rouge", + "saint_guy", + "figuerie", + "palazzo_canavese", + "le_manoir", + "san_floriano_del_collio", + "roccella_ionica", + "sainte_menehould", + "sint_maria_lierde", + "s\u00e3o_tom\u00e9", + "valle_mosso", + "francavilla_marittima", + "\u00eele_saint_christophe", + "la_tuque", + "la_hulpe", + "or_blanc", + "somme_leuze", + "oud_valkenburg", + "sint_martens_lierde", + "el_karimia", + "sint_pieters_kapelle", + "sint_laureins_berchem", + "christophe_de_lycie", + "al_andalus", + "saint_jean_baptiste", + "dar_es_salam", + "notre_dame", + "marano_principato", + "barbe_la_grande_martyre", + "nicolas_de_myre", + "perosa_canavese", + "la_rochelle", + "oliveto_lucano", + "san_pietro_apostolo", + "saint_georges", + "maison_blanche", + "san_didero", + "hibiscus_rosa_sinensis", + "charlottenburg_wilmersdorf", + "notre_dame_des_sept_douleurs", + "notre_dame_du_mont_carmel", + "iaokanann", + "la_gomera", + "santa_severina", + "villar_dora", + "sint_jan_in_eremo", + "simon_pierre", + "notre_dame_des_douleurs", + "parc_industriel", + "villanova_marchesana", + "monteforte_irpino", + "grande_canarie", + "tr\u00e0_vinh" + ], + "PERSON": [ + "charbon_bitumineux", + "cui_cui", + "prince_albert", + "al_harakat_al_islamiyya", + "mar_mar", + "moi_aussi", + "ha_ha", + "you_you", + "al_gore", + "n_boule", + "h_g_wells", + "s_li", + "saint_vincent", + "la_grange", + "est_sud_est", + "i_ching", + "william_playfair", + "s_x", + "don_delillo", + "au_moyen_de", + "j_li", + "la_joconde", + "c_v", + "margaret_munnerlyn_mitchell", + "e_e_cummings", + "n_v", + "edward_osborne_wilson", + "roger_eliot_fry", + "mont_tai", + "de_witt", + "george_v", + "igor_sikorsky", + "bifteck_\u00e0_la_florentine", + "peter_dawson", + "j_c", + "dor\u00e9e", + "carl_david_anderson", + "tortue_noire", + "maxwell_anderson", + "boletus_edulis", + "yo_yo", + "autocontr\u00f4le", + "rudolf_hess", + "cha_cha" + ], + "BIO_CHEM_ENTITY": [ + "monoamine_oxydases", + "d_glyc\u00e9rald\u00e9hyde", + "\u00e0_l_ancienne", + "l_glyc\u00e9rald\u00e9hyde", + "edward_drummond", + "m\u00e9thionique", + "monoamine_oxydase", + "r\u00e9trotranscriptase" + ], + "POLITICAL_PARTY_MEMBER": [ + "menchevik", + "fabien", + "communiste" + ], + "EVENT": [ + "c_est_la_vie", + "para_alpin", + "la_vie_est_ainsi_faite", + "fleur_de_lys", + "manche_d\u00e9cisive", + "sing_sing", + "fleur_de_lis", + "grand_prix" + ], + "UNION": [ + "industrial_workers_of_the_world", + "iww", + "association_professionnelle", + "enterprise_union", + "syndicat_\u00e9tudiant" + ], + "ANAT": [ + "perforant" + ], + "ner_regexes": [ + [ + "PERSON", + "\\D+ \\D+|\\D+ \\D+|\\D+ \\D+|\\D+ \\D+|\\D+ \\D+|\\D+ \\D+|\\D+ 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+ "lorraine", + "c\u00e9line", + "capucine", + "claudine", + "hortense", + "alexandra", + "marie", + "margot", + "olivia", + "fran\u00e7oise", + "lucie", + "danielle", + "no\u00e9mi", + "maria", + "mathilde", + "virginie", + "sophie", + "nicole", + "rosalie", + "ad\u00e8le", + "sandra", + "chantal", + "maggie", + "marguerite", + "germaine", + "anna", + "elisa", + "alex", + "dominique", + "c\u00e9cile", + "maude", + "anne", + "christelle", + "karine", + "ren\u00e9e", + "eva", + "emilie", + "laurie", + "b\u00e9atrice", + "jeannine", + "laetitia", + "lisa", + "laura", + "catherine", + "olivie", + "l\u00e9a", + "agn\u00e8s", + "cl\u00e9mence", + "p\u00e9n\u00e9lope", + "alix", + "susanne", + "christiane", + "brigitte", + "julie", + "antoinette", + "genevi\u00e8ve", + "\u00e9lisabeth", + "denise", + "georgette", + "th\u00e9r\u00e8se", + "laure", + "nathalie", + "fabienne", + "st\u00e9phanie", + "simone", + "ana\u00efs", + "charlotte", + "gabrielle", + "zo\u00e9", + "paulette", + "laurence", + "josette", + "luce", + "emmanuelle", + "alexandria", + "h\u00e9l\u00e8ne", + "diane", + "jos\u00e9phine", + "jeanne", + "\u00e9dith", + "vanessa", + "aurore", + "aim\u00e9e", + "\u00e9milie", + "in\u00e8s", + "jessica", + "ana", + "alexandrie", + "valentine", + "michelle", + "sarah", + "adrienne", + "martine", + "elisabeth", + "marcelle", + "caroline", + "lucy", + "chlo\u00e9", + "\u00e9l\u00e9onore", + "doroth\u00e9e", + "odette", + "manon", + "v\u00e9ronique", + "claire", + "isabelle", + "henriette", + "oc\u00e9ane", + "val\u00e9rie", + "camille", + "yvette", + "christine", + "margaret", + "constance", + "sabine", + "emma", + "arnaude", + "marianne", + "corinne", + "alice", + "liliane", + "marthe", + "margaud", + "yvonne", + "aur\u00e9lie", + "suzanne", + "florence", + "margaux", + "bernadette", + "nelly", + "\u00e9lodie", + "jacqueline", + "claude", + "pauline", + "elodie", + "josiane", + "victoire", + "no\u00e9mie", + "fr\u00e9d\u00e9rique", + "sandrine", + "nath", + "\u00e9lise", + "louise", + "am\u00e9lie", + "madeleine", + "patricia", + "c\u00e9lina", + "anouk", + "monique", + "sylvie", + "audrey", + "juliette", + "alicia", + "colette", + "anastasie", + "clara", + "eliane", + "agathe", + "ad\u00e9la\u00efde" + ], + "FIRST_NAME_MALE": [ + "mathieu", + "roger", + "auguste", + "raymond", + "s\u00e9bastien", + "luca", + "thierry", + "marc", + "benjamin", + "j\u00e9r\u00f4me", + "yves", + "jonathan", + "maurice", + "noah", + "lucas", + "alain", + "daniel", + "nicolas", + "emmanuel", + "olivier", + "maxime", + "beno\u00eet", + "isaac", + "alphonse", + "antonio", + "marcel", + "romain", + "\u00e9mile", + "florian", + "hugo", + "nathan", + "gabriel", + "antoine", + "vincent", + "alexis", + "rapha\u00ebl", + "\u00e9tienne", + "jules", + "jean", + "guillaume", + "g\u00e9rard", + "manuel", + "denis", + "georges", + "louis", + "l\u00e9o", + "aim\u00e9", + "bernard", + "jean_claude", + "augustin", + "joseph", + "honor\u00e9", + "fr\u00e9d\u00e9ric", + "zacharie", + "roland", + "henri", + "guy", + "christian", + "timoth\u00e9e", + "philippe", + "\u00e9ric", + "nolan", + "paul", + "kevin", + "christophe", + "th\u00e9ophile", + "william", + "hugues", + "alexandre", + "martin", + "pierre", + "lo\u00efc", + "thibault", + "eric", + "l\u00e9on", + "andr\u00e9", + "tristan", + "richard", + "r\u00e9my", + "alfred", + "samuel", + "adrien", + "bertrand", + "jos\u00e9", + "david", + "th\u00e9odore", + "fran\u00e7ois", + "\u00e9douard", + "arthur", + "matthieu", + "laurent", + "eug\u00e8ne", + "pascal", + "matteo", + "jean_pierre", + "julien", + "robert", + "claude", + "xavier", + "michel", + "thomas", + "thibaut", + "gilles", + "gilbert", + "st\u00e9phane", + "jacques", + "ethan", + "luc", + "franck", + "charles", + "ren\u00e9", + "no\u00ebl", + "albert", + "th\u00e9o", + "michael", + "bruno", + "victor", + "gr\u00e9goire", + "patrick" + ], + "FIRST_NAME": [ + "mathieu", + "susan", + "lara", + "roger", + "maryse", + "auguste", + "andr\u00e9e", + "raymond", + "s\u00e9bastien", + "m\u00e9lanie", + "philippine", + "astrid", + "luca", + "thierry", + "marc", + "mich\u00e8le", + "sara", + "marine", + "lorraine", + "c\u00e9line", + "benjamin", + "j\u00e9r\u00f4me", + "claudine", + "capucine", + "yves", + "jonathan", + "hortense", + "maurice", + "alexandra", + "marie", + "noah", + "lucas", + "margot", + "olivia", + "fran\u00e7oise", + "alain", + "lucie", + "danielle", + "daniel", + "nicolas", + "no\u00e9mi", + "emmanuel", + "maria", + "mathilde", + "virginie", + "sophie", + "maxime", + "olivier", + "nicole", + "rosalie", + "ad\u00e8le", + "beno\u00eet", + "isaac", + "sandra", + "chantal", + "maggie", + "marguerite", + "germaine", + "alphonse", + "antonio", + "marcel", + "anna", + "elisa", + "alex", + "romain", + "dominique", + "c\u00e9cile", + "maude", + "\u00e9mile", + "anne", + "christelle", + "florian", + "hugo", + "nathan", + "karine", + "ren\u00e9e", + "eva", + "gabriel", + "antoine", + "emilie", + "vincent", + "b\u00e9atrice", + "jeannine", + "alexis", + "laetitia", + "laurie", + "lisa", + "laura", + "rapha\u00ebl", + "catherine", + "olivie", + "\u00e9tienne", + "agn\u00e8s", + "l\u00e9a", + "jules", + "cl\u00e9mence", + "p\u00e9n\u00e9lope", + "jean", + "alix", + "guillaume", + "susanne", + "g\u00e9rard", + "manuel", + "denis", + "georges", + "louis", + "christiane", + "brigitte", + "julie", + "antoinette", + "genevi\u00e8ve", + "\u00e9lisabeth", + "denise", + "georgette", + "l\u00e9o", + "aim\u00e9", + "th\u00e9r\u00e8se", + "bernard", + "laure", + "nathalie", + "fabienne", + "joseph", + "jean_claude", + "st\u00e9phanie", + "honor\u00e9", + "simone", + "augustin", + "fr\u00e9d\u00e9ric", + "ana\u00efs", + "charlotte", + "roland", + "gabrielle", + "henri", + "zo\u00e9", + "zacharie", + "paulette", + "laurence", + "josette", + "luce", + "emmanuelle", + "guy", + "alexandria", + "h\u00e9l\u00e8ne", + "christian", + "timoth\u00e9e", + "diane", + "philippe", + "jos\u00e9phine", + "\u00e9ric", + "nolan", + "jeanne", + "\u00e9dith", + "vanessa", + "paul", + "aurore", + "kevin", + "aim\u00e9e", + "christophe", + "th\u00e9ophile", + "in\u00e8s", + "\u00e9milie", + "william", + "hugues", + "jessica", + "alexandre", + "ana", + "alexandrie", + "valentine", + "michelle", + "sarah", + "martin", + "adrienne", + "elisabeth", + "martine", + "marcelle", + "pierre", + "caroline", + "lo\u00efc", + "lucy", + "chlo\u00e9", + "thibault", + "\u00e9l\u00e9onore", + "eric", + "l\u00e9on", + "doroth\u00e9e", + "odette", + "andr\u00e9", + "manon", + "v\u00e9ronique", + "isabelle", + "henriette", + "claire", + "oc\u00e9ane", + "val\u00e9rie", + "tristan", + "camille", + "richard", + "yvette", + "r\u00e9my", + "alfred", + "christine", + "samuel", + "margaret", + "adrien", + "bertrand", + "jos\u00e9", + "constance", + "sabine", + "emma", + "david", + "arnaude", + "marianne", + "corinne", + "alice", + "th\u00e9odore", + "fran\u00e7ois", + "\u00e9douard", + "arthur", + "marthe", + "laurent", + "liliane", + "eug\u00e8ne", + "matthieu", + "margaud", + "pascal", + "yvonne", + "aur\u00e9lie", + "suzanne", + "matteo", + "florence", + "margaux", + "jean_pierre", + "nelly", + "bernadette", + "\u00e9lodie", + "julien", + "jacqueline", + "claude", + "xavier", + "robert", + "michel", + "thibaut", + "thomas", + "gilles", + "pauline", + "elodie", + "josiane", + "victoire", + "gilbert", + "no\u00e9mie", + "st\u00e9phane", + "fr\u00e9d\u00e9rique", + "sandrine", + "nath", + "jacques", + "ethan", + "\u00e9lise", + "louise", + "am\u00e9lie", + "luc", + "franck", + "patricia", + "charles", + "c\u00e9lina", + "anouk", + "madeleine", + "monique", + "sylvie", + "ren\u00e9", + "audrey", + "juliette", + "alicia", + "no\u00ebl", + "albert", + "th\u00e9o", + "michael", + "colette", + "bruno", + "victor", + "anastasie", + "gr\u00e9goire", + "patrick", + "clara", + "eliane", + "agathe", + "ad\u00e9la\u00efde" + ], + "LAST_NAME": [ + "lema\u00eetre", + "aubry", + "barbe", + "pons", + "riou", + "charest", + "raymond", + "saudan", + "masson", + "bailly", + "grojean", + "carrier", + "bonnet", + "besse", + "dias", + "robitaille", + "vermeil", + "blanchette", + "thierry", + "labrecque", + "blanchard", + "botteron", + "ferland", + "gaillard", + "weber", + "pineau", + "dufour", + "cyr", + "cossy", + "lacasse", + "sandoz", + "bourdon", + "sansonnens", + "guyon", + "mercier", + "bernasconi", + "hernandez", + "faivre", + "nicolas", + "dubey", + "dub\u00e9", + "normand", + "le_goff", + "barbey", + "fleury", + "beno\u00eet", + "plante", + "asselin", + "carraud", + "poulin", + "dijoux", + "le_gall", + "durand", + "provencher", + "langlois", + "delaunay", + "paschoud", + "lef\u00e8vre", + "l\u00e9v\u00eaque", + "poirier", + "guichard", + "desjardins", + "vuille", + "pilon", + "p\u00e9pin", + "henry", + "merle", + "vincent", + "st_laurent", + "ferrand", + "lebon", + "godard", + "renard", + "jean", + "guillou", + "niquille", + "boily", + "blouin", + "sanchez", + "cohen", + "voisin", + "deshusses", + "charpi\u00e9", + "\u00e9mond", + "dos_santos", + "fernandes", + "techer", + "bernard", + "girard", + "morin", + "caron", + "chauveau", + "daigle", + "bigot", + "martinez", + "lemire", + "ollivier", + "nussl\u00e9", + "droz", + "philippe", + "garnier", + "provost", + "roy", + "lagarde", + "de_sousa", + "curdy", + "b\u00e9rub\u00e9", + "aubert", + "clerc", + "costa", + "peltier", + "perez", + "besen\u00e7on", + "chatriant", + "chauvet", + "legrand", + "gros", + "carre", + "laporte", + "hebert", + "paradis", + "hoarau", + "pich\u00e9", + "fouquet", + "delahaye", + "da_costa", + "doucet", + "adam", + "gillet", + "foucher", + "cosandey", + "simon", + "rosselet", + "mallet", + "l\u00e9ger", + "goulet", + "legros", + "rocher", + "carraux", + "duguay", + "smith", + "schmitt", + "legendre", + "de_oliveira", + "reynaud", + "monnet", + "andre", + "maillard", + "cousin", + "vidal", + "pouliot", + "veilleux", + "b\u00e9gin", + "torres", + "courvoisier", + "lamy", + "regnier", + "boisvert", + "mend\u00e8s", + "toussaint", + "imbert", + "germain", + "n\u00fcsslin", + "barillon", + "alves", + "sirois", + "matile", + "marion", + "neveu", + "plourde", + "coste", + "petit", + "robadey", + "perron", + "marques", + "simard", + "moreau", + "nguyen", + "rosselat", + "moreno", + "charbonneau", + "petitjean", + "grenier", + "leblanc", + "carpentier", + "ribeiro", + "blin", + "g\u00e9linas", + "lemonnier", + "duchesne", + "monney", + "lecomte", + "comte", + "martins", + "boulanger", + "delattre", + "vall\u00e9lian", + "blondel", + "barthelemy", + "huet", + "vasseur", + "chr\u00e9tien", + "st_pierre", + "tr\u00e9panier", + "martineau", + "poulain", + "couturier", + "guilbert", + "daniel", + "ruiz", + "didier", + "babey", + "cl\u00e9ment", + "coulombe", + "letellier", + "gimenez", + "gauthier", + "corboz", + "fontaine", + "leleu", + "pages", + "da_silva", + "fortier", + "meunier", + "evrard", + "bousquet", + "thorens", + "beauregard", + "teixeira", + "b\u00e9dard", + "antoine", + "b\u00e8gue", + "hardy", + "chauvin", + "therrien", + "marti", + "maire", + "tessier", + "guillaume", + "julliard", + "lalibert\u00e9", + "ledoux", + "georges", + "louis", + "colas", + "vienne", + "carlier", + "badel", + "rappaz", + "villeneuve", + "chevalley", + "lauzon", + "morissette", + "joseph", + "lombard", + "lamoureux", + "boudreau", + "duvanel", + "larose", + "fischer", + "gendron", + "v\u00e9zina", + "beauchamp", + "gaudreault", + "chevallier", + "richer", + "uldry", + "rey", + "jourdan", + "monnard", + "larocque", + "delannoy", + "barbier", + "bazin", + "bonvin", + "herv\u00e9", + "marchal", + "pierre", + "chapuis", + "guillemette", + "laine", + "wicht", + "thibault", + "larivi\u00e8re", + "rivi\u00e8re", + "muller", + "dumont", + "lessard", + "collet", + "mary", + "lemoine", + "bourgeois", + "m\u00fcller", + "leli\u00e8vre", + "bonnin", + "richard", + "r\u00e9my", + "diesbach", + "meyer", + "duval", + "grosjean", + "rousseau", + "guillet", + "monnier", + "boillat", + "galland", + "beguin", + "mass\u00e9", + "champagne", + "patel", + "fran\u00e7ois", + "comman", + "laurent", + "lebrun", + "rossi", + "mar\u00e9chal", + "guibert", + "beuchat", + "leclercq", + "rodrigue", + "lavoie", + "julien", + "le_roux", + "thomas", + "boichat", + "gilles", + "brunel", + "masseron", + "rodriguez", + "charrier", + "lapointe", + "guillon", + "laflamme", + "boyer", + "bergeron", + "perrot", + "jacques", + "badan", + "collin", + "gigu\u00e8re", + "no\u00ebl", + "vaillant", + "lapierre", + "hamel", + "fournier", + "quartier", + "rolland", + "besan\u00e7on", + "chaudet", + "paquette", + "mathieu", + "roger", + "conrad", + "landry", + "jacob", + "dufresne", + "pelletier", + "bouvet", + "renault", + "hamon", + "humbert", + "bolduc", + "dionne", + "rodrigues", + "menthonnex", + "colin", + "carron", + "joye", + "potvin", + "diallo", + "samson", + "ev\u00e9quoz", + "brahier", + "lejeune", + "laplante", + "b\u00e9lisle", + "lemieux", + "th\u00e9riault", + "gallet", + "maurice", + "chatriand", + "gonzalez", + "ramos", + "lucas", + "lambert", + "cloutier", + "ouellet", + "devaux", + "legault", + "dubois", + "croteau", + "tremblay", + "delado\u00eby", + "camus", + "m\u00e9nard", + "hubert", + "auger", + "corbat", + "aebi", + "l\u00e9vesque", + "barre", + "brisson", + "marcoux", + "bruneau", + "s\u00e9guin", + "michaud", + "leroy", + "lafontaine", + "bahon", + "munoz", + "charpentier", + "peron", + "labelle", + "pereira", + "lopez", + "menard", + "gilli\u00e8ron", + "g\u00e9rard", + "denis", + "del\u00e8ze", + "valentin", + "savoie", + "perret", + "bernier", + "berthelot", + "paccot", + "godin", + "rivard", + "rapraz", + "deschamps", + "perrin", + "tanguy", + "blais", + "briand", + "gu\u00e9rin", + "forget", + "cormier", + "broquet", + "duhamel", + "joly", + "bugnon", + "lecoq", + "arsenault", + "lachapelle", + "texier", + "traore", + "laroche", + "soucy", + "beaulieu", + "fonjallaz", + "arnaud", + "d\u00e9l\u00e8ze", + "rossellat", + "piccand", + "pichon", + "paquin", + "chopard", + "paul", + "morel", + "chouinard", + "roche", + "mottiez", + "bonvini", + "tardif", + "dupuis", + "lacroix", + "marty", + "boivin", + "sauvage", + "gravel", + "besnard", + "fernandez", + "privet", + "vonlanthen", + "berger", + "chevrolet", + "fabre", + "diaz", + "marchand", + "launay", + "lenoir", + "rousset", + "bisson", + "desbiens", + "parent", + "chappuis", + "b\u00e9land", + "balmat", + "david", + "blanc", + "st_onge", + "dumas", + "benoit", + "lopes", + "bodin", + "moulin", + "turpin", + "pascal", + "audet", + "hoareau", + "boucher", + "lefort", + "par\u00e9", + "michel", + "jacot_descombes", + "labont\u00e9", + "beaudry", + "jomini", + "l\u00e9vy", + "renaud", + "tanguay", + "fr\u00e9chette", + "brassard", + "treboux", + "francillon", + "bouchet", + "valette", + "jacquet", + "ferreira", + "allard", + "becker", + "lemay", + "pachoud", + "maltais", + "pires", + "coulon", + "lalonde", + "bourquard", + "masse", + "weiss", + "corpataux", + "pr\u00e9vost", + "pellet", + "lemaire", + "benard", + "pottier", + "harvey", + "grondin", + "gay", + "schneider", + "descamps", + "brun", + "charette", + "gomes", + "trudel", + "berberat", + "raynaud", + "savard", + "royer", + "chenaux", + "marie", + "labb\u00e9", + "breton", + "jacot_guillarmod", + "st_jean", + "gaudin", + "delisle", + "racine", + "pruvost", + "fillion", + "crevoisier", + "archambault", + "candaux", + "dallaire", + "demers", + "payet", + "lacombe", + "trottier", + "olivier", + "morard", + "lesage", + "chevalier", + "courtois", + "proulx", + "b\u00e9langer", + "maillet", + "marin", + "nadeau", + "gingras", + "blot", + "guillot", + "baudry", + "garcia", + "bourquin", + "verdier", + "bouvier", + "gilli\u00e9ron", + "vall\u00e9e", + "beaudoin", + "houde", + "grand", + "lavigne", + "charron", + "rapin", + "joubert", + "buisson", + "drouin", + "brandt", + "klein", + "cornut", + "romanens", + "\u00e9tienne", + "b\u00e9guelin", + "crivelli", + "bavaud", + "dupuy", + "aeby", + "guay", + "picard", + "allain", + "leroux", + "polla", + "boechat", + "beuret", + "gagnon", + "musy", + "mahe", + "potier", + "leconte", + "faure", + "th\u00e9raulaz", + "h\u00e9bert", + "bouchard", + "delorme", + "brunet", + "alber", + "vachon", + "chartier", + "gagn\u00e9", + "cattin", + "salmon", + "dupont", + "seguin", + "gervais", + "cretton", + "de_dardel", + "boulay", + "morvan", + "beurret", + "vallet", + "bertin", + "bilodeau", + "bovet", + "lebel", + "morand", + "barman", + "lussier", + "desch\u00eanes", + "alexandre", + "lefebvre", + "bujard", + "thibodeau", + "larouche", + "l\u00e9tourneau", + "isella", + "lepage", + "martin", + "desrosiers", + "roberge", + "roussel", + "jacquot", + "loiseau", + "besson", + "mayor", + "houle", + "muriset", + "dion", + "giraud", + "bonneau", + "drolet", + "c\u00f4t\u00e9", + "wagner", + "lebreton", + "blanchet", + "desrochers", + "guyot", + "gomez", + "chartrand", + "navarro", + "paris", + "tinguely", + "robin", + "lamontagne", + "vaillancourt", + "gautier", + "bochud", + "pasquier", + "dupr\u00e9", + "mottet", + "rioux", + "maury", + "goncalves", + "bertrand", + "boutin", + "millet", + "pinto", + "chabot", + "perreault", + "maillot", + "mace", + "turcotte", + "coigny", + "comment", + "roux", + "lavall\u00e9e", + "gosselin", + "cornuz", + "robert", + "marcotte", + "fortin", + "gilbert", + "turgeon", + "peitrequin", + "giroux", + "duroux", + "leclerc", + "couture", + "gub\u00e9ran", + "montandon", + "charles", + "martel", + "cordier", + "albert", + "godet", + "gr\u00e9goire", + "lachance", + "delmas", + "leduc", + "cosendey", + "baron", + "perrier" + ], + "OTHER_PRONOUN": [ + "its" + ], + "LAST_NAME_MALE": [], + "LAST_NAME_FEMALE": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "abbesse": "abb", + "m\u00e8re_sup\u00e9rieure": "abbot", + "actrice": "com\u00e9dien", + "aviatrice": "aviateur", + "tantine": "oncle", + "zia": "sio", + "bibi": "sio", + "tatie": "oncle", + "baronne": "baron", + "belle": "beau", + "future_\u00e9pouse": "palefrenier", + "jeune_mari\u00e9": "groom", + "future_mari\u00e9e": "palefrenier", + "bride": "jeune_mari\u00e9", + "jeune_mari\u00e9e": "\u00e9triller", + "mari\u00e9e": "palefrenier", + "\u00e9pouse": "gour", + "femme_d_affaires": "businessman", + "working_girl": "businessman", + "femme_d\u2019_affaires": "businessman", + "businesswoman": "homme_d\u2019_affaires", + "chick": "pinpin", + "coquelet": "gaur", + "gonzesse": "fashion_victim", + "poussin": "dandy", + "poupoule": "fashion_victim", + "autruchon": "pinpin", + "poulette": "gaur", + "andromaque": "cow_boy", + "vach\u00e8re": "vacher", + "wawa": "son", + "fie": "son", + "fia": "son", + "duchesse": "duc", + "maharani": "saturnia_pavonia", + "imp\u00e9ratrice": "saturnia_pavonia", + "femme_fatale": "ensorceleur", + "heks": "magicien", + "enchanteresse": "enchanter", + "l_enchanteresse": "enchanteuse", + "sir\u00e8ne": "enchanteuse", + "ensorceleur": "sorcerer", + "tentatrice": "enchanter", + "dalila": "enchanteuse", + "f\u00e9minin": "male", + "nais": "male", + "femelle": "masculin", + "gal": "gille", + "flicka": "guy", + "pige": "guy", + "yuna": "gille", + "lassie": "lad", + "gouvernante": "gouverneure", + "petite_fille": "petit_fils", + "a\u00efeule": "grand_papa", + "nine": "babu", + "grand_m\u00e8re": "a\u00efeul", + "proviseure": "proviseur", + "de_la": "les_siennes", + "varone": "h\u00e9ros", + "h\u00e9ro\u00efne": "hero", + "le_sien": "le_leur", + "les_siens": "la_leur", + "la_sienne": "les_leurs", + "hers": "la_leur", + "les_siennes": "les_leurs", + "elle_m\u00eame": "lui_m\u00eame", + "ma\u00eetresse_de_maison": "accueillir", + "animateur": "l\u00e9gion", + "ma\u00eetresses_de_maison": "h\u00f4telier", + "h\u00f4tesse": "steward", + "lady": "laird", + "fru": "gv", + "poup\u00e9e": "groom", + "fillette": "lad", + "putta": "groom", + "marquise": "marquis", + "mademoiselle": "sir", + "dlle": "sir", + "miss": "sir", + "rater": "sir", + "misse": "sir", + "mlle": "mr", + "mam\u2019zelle": "sir", + "miss_a": "sir", + "ma\u00eetresse": "master", + "anya": "pater", + "mam": "paire", + "la_m\u00e8re": "mon_p\u00e8re", + "m\u00e8re": "pair", + "mame": "pair", + "mutter": "fader", + "matrix": "vader", + "materner": "mon_p\u00e8re", + "mrs": "mgr", + "ms": "mr", + "matc": "mgr", + "ni\u00e8ce_fraternelle": "neveu_sororel", + "ni\u00e8ce_sororelle": "neveu", + "ni\u00e8ce": "neveu_sororel", + "coquill\u00e9_hollandais": "monial", + "nonnain": "moine", + "moniale": "monge", + "religieuse": "ikhwan", + "s\u0153ur": "le_retour_du_fr\u00e8re_prodigue", + "bonne_s\u0153ur": "monial", + "pr\u00eatresse": "pope", + "princesse": "prince", + "monthly_princess": "agaric_auguste", + "princessa": "de_principe", + "danaus_gilippus": "key", + "reg": "key", + "drag_queen": "rex", + "reine": "rou\u00e9", + "hetman": "rou\u00e9", + "queen": "indra", + "queens": "reyes", + "koya": "he", + "haec": "\u3078", + "saur": "fr\u00e8re", + "way": "le_retour_du_fr\u00e8re_prodigue", + "sister": "broder", + "nurse": "frater", + "naja": "frater", + "infirmi\u00e8re": "broder", + "vieille_fille": "bachelor", + "belle_fille": "beau_fils", + "belle_m\u00e8re": "beau_p\u00e8re", + "mar\u00e2tre": "beau_p\u00e8re", + "agente_de_bord": "steward", + "h\u00f4tesse_de_l_air": "steward", + "stewardess": "steward", + "h\u00f4tesse_de_l\u2019_air": "steward", + "stewardesse": "steward", + "serveuse": "loufiat", + "serveur": "cambrer", + "veuve": "veuf", + "vidua": "veuf", + "ligne_veuve": "veuf", + "veuf_veuve": "veuf", + "bean": "din\u00e9", + "bini": "gatte", + "naine": "gv", + "kobi\u00e8ta": "m\u00e9na", + "duna": "gour", + "hex": "magicien", + "striga": "magicien", + "wicca": "magicien", + "strie": "magicien", + "glyptocephalus_cynoglossus": "magicien", + "f\u00e2me": "i_love_you", + "dynes": "m\u0119\u017cczyzna", + "women": "men", + "donne": "men", + "boy": "yuna", + "laddie": "yuna", + "gille": "lassie", + "jeune_homme": "lassie", + "lad": "flicka", + "fiu": "pige", + "bube": "pige", + "madame_claude": "fran\u00e7aise", + "fran\u00e7aise": "madame_claude", + "french": "madame_claude", + "langue_fran\u00e7aise": "madame_claude", + "liste_d_historiens_de_la_bretagne": "madame_claude", + "fran\u00e7ois": "madame_claude", + "polonaise": "polonais", + "glose": "polonaise", + "astiquer": "polonaise", + "poliment": "polonaise", + "polonais": "polonaise", + "vernis": "polonaise", + "raffinement": "polonaise", + "journaliste": "journalist", + "journalist": "journaliste" + }, + "other_gender_swap": { + "one": "haec", + "eux": "haec", + "leur": "de_la", + "haec": "essi", + "des_monstres_attaquent_la_ville": "de_la", + "elles": "koya", + "leus": "de_la", + "leurs": "de_la", + "lia": "la_leur", + "la_leur": "hers", + "suya": "hers", + "le_leur": "la_sienne", + "les_leurs": "la_sienne", + "essi": "koya", + "epi": "koya", + "ils": "koya", + "oms": "haec", + "iel": "koya", + "ell": "one", + "ew": "elles", + "he": "essi", + "\u3078": "elles", + "koya": "haec", + "bera": "epi", + "ihm": "leur", + "le_sien": "le_leur", + "seine": "suya", + "la_sienne": "le_leur", + "les_siens": "le_leur", + "les_siennes": "le_leur", + "de_la": "leurs", + "hers": "la_leur" + }, + "en_pronoun2gender": { + "they": [ + "homosexuel", + "bisexuel", + "transgend\u00e9risme", + "queer", + "transgenre", + "sodomite", + "bisexu\u00e9", + "homosexuelle" + ], + "he": [ + "guy", + "dandy", + "jeune_homme", + "groom", + "zigomar", + "bubi", + "boy", + "gar\u00e7onnet", + "omu", + "i_love_you", + "fiston", + "lad", + "gv", + "gercer", + "m\u0119\u017cczyzna", + "hauban", + "gentilhomme", + "petit_gar\u00e7on", + "bube", + "gentleman", + "pinpin", + "man", + "laddie", + "messieurs", + "little_boy", + "male", + "masculin", + "gaur", + "bougre", + "fiu", + "din\u00e9", + "\u00eele_de_man", + "fashion_victim", + "chap", + "coll\u00e8gue", + "gille" + ], + "she": [ + "gonzesse", + "lesbienne", + "matrone", + "beau_sexe", + "fillette", + "miss", + "flicka", + "lesbien", + "naine", + "brasa", + "petite", + "dlle", + "nais", + "poussin", + "gent_f\u00e9minine", + "lassie", + "gouine", + "fru", + "bean", + "pige", + "saphisme", + "lesbianisme", + "femelle", + "jupe", + "gal", + "misse", + "dame", + "f\u00e2me", + "sexe_faible", + "petite_fille", + "f\u00e9minin", + "lady", + "yuna", + "pucelle", + "rater", + "mademoiselle", + "mlle", + "homosexuel", + "poup\u00e9e", + "dynes", + "mam\u2019zelle", + "fifille", + "miss_a", + "tribade", + "lesbier" + ] + }, + "en_pronoun2pronoun": { + "he": [ + "les_siens", + "la_sienne", + "he", + "bera", + "le_sien", + "lia", + "les_siennes", + "ihm", + "seine", + "\u3078", + "lui_m\u00eame", + "ell", + "koya", + "ew" + ], + "she": [ + "les_siens", + "la_sienne", + "de_la", + "le_sien", + "les_siennes", + "elle_m\u00eame", + "haec", + "hers", + "koya" + ], + "they": [ + "one", + "les_leurs", + "essi", + "elles", + "iel", + "leurs", + "oms", + "lia", + "leur", + "suya", + "eux", + "le_leur", + "haec", + "des_monstres_attaquent_la_ville", + "la_leur", + "ils", + "leus", + "epi" + ], + "it": [ + "esti", + "per_se", + "isso", + "ces", + "ceux_l\u00e0", + "issu", + "dette", + "its", + "cette_ci", + "ce_ci", + "essa", + "celui", + "cette", + "c\u2019_est", + "ceci", + "ceux_ci", + "ovi", + "cisse", + "celle_l\u00e0", + "ky", + "tyto", + "celles_ci", + "celui_l\u00e0", + "celles_l\u00e0", + "ces_ci", + "celui_ci" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/frm.json b/data_tooling/pii_processing/ontology/data/frm.json new file mode 100644 index 0000000..f3f976f --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/frm.json @@ -0,0 +1,45 @@ +{ + "PERSON_PRONOUN": [ + "dain", + "me" + ], + "JOB": [ + "roy" + ], + "PUBLIC_FIGURE": [ + "morgain", + "moyse", + "robert", + "cauvin", + "george" + ], + "ANIMAL": [ + "duc" + ], + "GENDER": [ + "dame" + ], + "LOCATION": [ + "trois_rivieres" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": {}, + "other_gender_swap": {}, + "en_pronoun2gender": { + "she": [ + "dame" + ] + }, + "en_pronoun2pronoun": {}, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/fro.json b/data_tooling/pii_processing/ontology/data/fro.json new file mode 100644 index 0000000..455b9de --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/fro.json @@ -0,0 +1,125 @@ +{ + "ORG": [ + "dominion", + "tranque", + "porte" + ], + "JOB": [ + "creator", + "mercator", + "ranger", + "char", + "sommelier", + "grip", + "chief", + "plombeur", + "paisan", + "pastor", + "cop", + "rancher", + "gaite" + ], + "ANIMAL": [ + "moisset", + "duc", + "bievre", + "chate", + "merel", + "luberne" + ], + "FOOD": [ + "mousse", + "saus" + ], + "RACE": [ + "fran\u00e7oyse", + "franceis", + "franceise", + "fraunceise" + ], + "DISEASE": [ + "ki", + "carbuncle", + "complaint", + "pecol", + "espasme", + "toser", + "crache", + "fugue", + "eschalfer" + ], + "PUBLIC_FIGURE": [ + "quine", + "k", + "beauvoir", + "galois", + "david", + "chaplin", + "buison", + "robert", + "edward", + "mansart", + "i", + "davi", + "paige", + "jacob", + "moyses", + "beaumont", + "lorenz" + ], + "PERSON_PRONOUN": [ + "dain", + "i" + ], + "PRODUCT": [ + "se_dex_me_gart" + ], + "RELIGION_MEMBER": [ + "sarrazin" + ], + "SOC_ECO_CLASS": [ + "pairie" + ], + "GENDER": [ + "dame", + "pucelle" + ], + "PLANT": [ + "caboche" + ], + "GPE": [ + "nostre_dame" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": {}, + "other_gender_swap": {}, + "en_pronoun2gender": { + "she": [ + "pucelle", + "dame", + "feme" + ] + }, + "en_pronoun2pronoun": { + "they": [ + "eles" + ], + "it": [ + "issu", + "ces", + "cest", + "cestui" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/frp.json b/data_tooling/pii_processing/ontology/data/frp.json new file mode 100644 index 0000000..d99b491 --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/frp.json @@ -0,0 +1,45 @@ +{ + "ANIMAL": [ + "chatta" + ], + "DISEASE": [ + "chalor" + ], + "LANGUAGE": [ + "francoproven\u00e7\u00e2l", + "arpetan" + ], + "RELIGION": [ + "calvinismo" + ], + "LOCATION": [ + "sri_lanka" + ], + "ORG": [ + "alemand" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": {}, + "other_gender_swap": {}, + "en_pronoun2gender": { + "she": [ + "fem\u00e8la" + ] + }, + "en_pronoun2pronoun": { + "he": [ + "jal" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/frr.json b/data_tooling/pii_processing/ontology/data/frr.json new file mode 100644 index 0000000..9ee8ece --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/frr.json @@ -0,0 +1,76 @@ +{ + "PERSON_PRONOUN": [ + "jamens" + ], + "JOB": [ + "taust", + "k\u00f6ning", + "maage", + "tweete", + "man" + ], + "ORG": [ + "ai" + ], + "PLANT": [ + "spasahorn" + ], + "RELIGION_MEMBER": [ + "brouder" + ], + "ANIMAL": [ + "weederh\u00fcnj" + ], + "DISEASE": [ + "breege", + "breeg", + "breek" + ], + "GENDER": [ + "man" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "s\u00fcster": "bruler", + "saster": "bruler", + "s\u00f6ster": "bruler", + "w\u00fcset": "man", + "dr\u00e4ng": "foomen", + "jongen": "foomen" + }, + "other_gender_swap": { + "djo": "sun", + "sun": "djo" + }, + "en_pronoun2gender": { + "he": [ + "jongen", + "man", + "dr\u00e4ng" + ], + "she": [ + "foomen", + "w\u00fcset" + ] + }, + "en_pronoun2pronoun": { + "she": [ + "sun" + ], + "they": [ + "uk", + "djo" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/fur.json b/data_tooling/pii_processing/ontology/data/fur.json new file mode 100644 index 0000000..508b424 --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/fur.json @@ -0,0 +1,192 @@ +{ + "DISEASE": [ + "struc", + "schelfe", + "sanglo\u00e7", + "starnud\u00e2", + "muardi", + "lichil", + "durm\u00ee", + "gangrene", + "ruzin", + "mi", + "rabie", + "torment" + ], + "PERSON_PRONOUN": [ + "nestri", + "m\u00ea", + "me" + ], + "ANIMAL": [ + "mardar", + "cheche", + "tortorele", + "pole\u00e7", + "forcel", + "sparv\u00e2l", + "vari\u0171l", + "dordei", + "stambec", + "falcu\u00e7", + "martar", + "cornile", + "cengl\u00e2r", + "viespe", + "bo_salvadi", + "cagne", + "mierli", + "gjesp\u00e2r", + "falcon", + "jespe", + "bilite", + "cavie", + "barbezuan", + "cjavr\u00fbl", + "cast\u00f4r", + "cagn\u0155s" + ], + "ORG": [ + "doi", + "un", + "lav\u00f4r", + "justizie", + "ai", + "europe", + "mi", + "cumier\u00e7" + ], + "FOOD": [ + "desert", + "gust\u00e0", + "ging\u00ece" + ], + "RELIGION_MEMBER": [ + "fradi" + ], + "JOB": [ + "miedi", + "past\u00f4r", + "arad\u00f4r", + "pior\u00e2r", + "marangon", + "guide", + "fevelant", + "pantiane", + "vuarzen\u00e2r", + "cusin\u00e2" + ], + "PUBLIC_FIGURE": [ + "bari", + "e", + "lurin\u00e7", + "davide", + "liston", + "most", + "sper\u00e2", + "mois\u00e8s", + "sperance", + "griv\u00f4r", + "lenart" + ], + "PRODUCT": [ + "spirtussant", + "cavie" + ], + "TITLE": [ + "miss\u00e2r", + "sign\u00f4r" + ], + "PLANT": [ + "siespe", + "papaver", + "urtie", + "fave", + "bromb", + "brocul", + "molec", + "brugnul" + ], + "LANGUAGE": [ + "greche", + "greghe", + "portugh\u00eas" + ], + "GENDER": [ + "frutat", + "dame", + "frutate", + "mascli" + ], + "QUANTITY": [ + "ton" + ], + "LOCATION": [ + "pic_neri" + ], + "RELIGION": [ + "islam", + "sintoisim" + ], + "GPE": [ + "spirtussant" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "simil": "fradi", + "fiastre": "fiastri", + "madrigne": "padreu", + "vedue": "vedul", + "cristiane": "mar\u00eet", + "mu\u00eer": "cristian", + "femine": "cristian", + "frut": "frutate", + "frutat": "frutate" + }, + "other_gender_swap": { + "l\u00f4r": "sun", + "j\u00ea": "l\u00f4r", + "sun": "l\u00f4r", + "s\u00f4": "l\u00f4r" + }, + "en_pronoun2gender": { + "he": [ + "mascli", + "frutat", + "frut" + ], + "she": [ + "frute", + "dame", + "femine", + "frutate" + ] + }, + "en_pronoun2pronoun": { + "he": [ + "s\u00f4" + ], + "she": [ + "sun", + "j\u00ea", + "s\u00f4" + ], + "they": [ + "l\u00f4r" + ], + "it": [ + "chest" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/fy.json b/data_tooling/pii_processing/ontology/data/fy.json new file mode 100644 index 0000000..e4bb27d --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/fy.json @@ -0,0 +1,712 @@ +{ + "PUBLIC_FIGURE": [ + "willem_de_oermasterder", + "matthew_arnold", + "benjamin_franklin", + "john_knox", + "rudolf_steiner", + "tomkes", + "che_guevara", + "georges_simenon", + "henrik_ibsen", + "mary_shelley", + "david_livingstone", + "john_herschel", + "richard_burton", + "anna_pavlova", + "hoopje", + "winston_churchill", + "ivan_pavlov", + "paul_mccartney", + "joseph_greenberg", + "isaac_newton", + "victor_hugo", + "joseph_smith", + "edwin_hubble", + "milton_friedman", + "george_stephenson", + "george_harrison", + "george_orwell", + "richard_wagner", + "don_quichot", + "michael_jackson", + "samuel_beckett", + "readkapke", + "galileo_galilei", + "john_donne", + "chaim_weizmann", + "kristoffel_kolumbus", + "robert_koch", + "joseph_goebbels", + "john_steinbeck", + "petrus", + "edmund_hillary", + "vincent_van_gogh", + "josef_stalin", + "robert_burns", + "hans_fischer", + "konrad_adenauer", + "frank_sinatra", + "abel_tasman", + "katharine_hepburn", + "henri_matisse", + "louis_pasteur", + "john_ford", + "gertrude_stein", + "saladin", + "sarah_bernhardt", + "charles_de_gaulle", + "paul_von_hindenburg", + "y", + "charles_lindbergh", + "samuel_barber", + "f", + "august_strindberg", + "thomas_mann", + "charles_goodyear", + "charles", + "samuel_de_champlain", + "fridtjof_nansen", + "robert_johnson", + "james_dean", + "george_huntington", + "oscar_wilde", + "heinrich_schliemann", + "glenn_curtiss", + "christiaan_eijkman", + "andrej_sacharov", + "adolf_eichmann", + "francis_bacon", + "immanuel_kant", + "hope", + "albert_schweitzer", + "john_harvard", + "titus", + "william_blake", + "piip", + "carl_lewis", + "elias_canetti", + "edward_jenner", + "graham_greene", + "frans_hals", + "marije_magdalena", + "leon_trotski", + "niels_bohr", + "bertrand_russell", + "michael_faraday", + "jan_tinbergen", + "greg", + "walt_disney", + "maksimianus", + "friedrich_engels", + "jane_austen", + "charles_laughton", + "theodor_mommsen", + "marcel_proust", + "thomas_more", + "john_milton", + "albert_speer", + "indira_gandhi", + "jane_seymour", + "george_gershwin", + "alfred_nobel", + "jesse_owens", + "daniel_rutherford", + "caravaggio", + "boris_karloff", + "hans_christian_andersen", + "thomas", + "isaac_watts", + "pieter_zeeman", + "pablo_picasso", + "kurt_weill", + "christiaan_huygens", + "adam_smith", + "chroesjtsjov", + "jean_harlow", + "karl_marx", + "friedrich_nietzsche", + "i", + "nikola_tesla", + "john_locke", + "henry_james", + "ingrid_bergman", + "hugo_de_groot", + "vladimir_p\u00fbtin", + "robert_southey", + "walt_whitman", + "carl_jung", + "adolf_hitler", + "alfred_stieglitz", + "joseph_haydn", + "buffalo_bill", + "ivan_t\u00fbrgenjev", + "edvard_grieg", + "rosa_parks", + "laurence_sterne", + "peter_de_grutte", + "anne_hathaway", + "jeannette_rankin", + "g", + "martin_heidegger", + "marije_fan_magdala", + "r", + "george_lucas", + "louis_armstrong", + "thomas_hardy", + "thomas_gainsborough", + "giuseppe_garibaldi", + "alexandre_dumas", + "johann_gutenberg", + "bobby_fischer", + "john_constable", + "joseph_campbell", + "jean_de_la_fontaine", + "robert_hooke", + "peter_sellers", + "peter_o'toole", + "joseph_conrad", + "peter_paul_rubens", + "mahatma_gandhi", + "jim_morrison", + "jules_verne", + "jackson_pollock", + "john_lennon", + "charlie_chaplin", + "marko_polo", + "lea", + "elizabeth_gaskell", + "alice_walker", + "jesse_jackson", + "james_watt", + "jonathan_edwards", + "ronald_reagan", + "frederick_douglass", + "david_hilbert", + "oliver_cromwell", + "martin_luther_king", + "woodrow_wilson", + "ernest_hemingway", + "george_westinghouse", + "arthur_miller", + "sint_louis", + "nelson_mandela", + "heinrich_himmler", + "al_gore", + "roald_amundsen", + "sherwood_anderson", + "alfred_korzybski", + "charles_dickens", + "ella_fitzgerald", + "jacques_offenbach", + "joseph_paxton", + "tasitus", + "bessie_smith", + "willy_brandt", + "francisco_franco", + "joris", + "keningseider", + "jan_steen", + "andrew_carnegie", + "franz_schubert", + "johnny_cash", + "mick_jagger", + "georges_cuvier", + "walter_scott", + "vladimir_lenin", + "robert_peary", + "john_bunyan", + "jonathan_swift", + "walter_gropius", + "albert_einstein", + "aletta_jacobs", + "thomas_edison", + "claude_bernard", + "pieter_stuyvesant", + "t" + ], + "DISEASE": [ + "streakje", + "slymbeurs\u00fbntstekking", + "stammerje", + "koarstmoas", + "harsensskodding", + "wetterpokken", + "gynekomasty", + "ynfeksjesykte", + "wintersliep", + "swierw\u00eazen", + "brekke", + "goalera", + "tongblier", + "de_pest", + "marteling", + "groei", + "ferk\u00e2ldenens", + "skuorbot", + "demintens", + "plaktyfus", + "long\u00fbntstekking", + "hawar", + "malaria" + ], + "PLANT": [ + "duvelswannelst\u00f4k", + "boerekoal", + "leppeltsjeblom", + "pine", + "wetterplant", + "finnestikel", + "b\u00fbterblom", + "barchjeblom", + "bremerheide", + "alsemambrosia", + "kamperfoelje", + "kantroas", + "hoants", + "koweblomke", + "piipkr\u00fbd", + "keunstner", + "maaieklokje", + "paradysf\u00fbgels", + "frisselgrien", + "kalmuswoartel", + "wylch", + "wylgebeam", + "eskdoarn", + "foksebei", + "miedesweltsje", + "skieppeklokje", + "wichter", + "flear", + "belladonna", + "teeplant", + "knolstienbrek", + "slaad" + ], + "LOCATION": [ + "skierroek", + "konservatoarium", + "it_kanaal", + "om_it_gefal", + "park", + "goemiddei", + "sint_helena", + "de_nederlannen", + "saksen_anhalt", + "psychiatrysk_sikeh\u00fbs", + "michiganmar", + "psychiatryske_ynrjochting", + "kaap_hoarn", + "frederjochter", + "falkl\u00e2neilannen", + "toarnroaske", + "tafelberch", + "boumantsje", + "boppemar", + "aldjiersdei", + "rjochtbank", + "the_rolling_stones", + "botanyske_t\u00fan", + "marije_magdalena", + "mar_fan_de_w\u00e2lden", + "jordaan" + ], + "ANIMAL": [ + "meau", + "keizergoes", + "houtsnip", + "marters", + "hjerringslynder", + "deim", + "s\u00e2nslieper", + "poepeletaat", + "beamiikhoarntsjes", + "monarchflinter", + "boskm\u00fbzen", + "stienmurd", + "krie", + "otter", + "boskoaljefant", + "tomkes", + "waarlamke", + "tsjoksnaffelskoet", + "przewalskyhynder", + "wetterh\u00fbn", + "hartm\u00fbs", + "sparwer", + "stienkrobbe", + "kuorhin", + "stienbok", + "readhalsd\u00fbker", + "wezeling", + "swartpoatmurd", + "kabbeljau", + "waskbearh\u00fbn", + "toerswel", + "bevers", + "goud\u00fblen", + "trompetswan", + "vibe", + "ekster", + "iisbear", + "raven", + "hazzem\u00fbs", + "kapeseachbek", + "berchlemming", + "kloekswan", + "everswyn", + "goud\u00fblef\u00fbgels", + "steltkl\u00fat", + "trompetkraan", + "goud\u00fble", + "str\u00e2nljip", + "unwaarsf\u00fbgel", + "marter", + "bloedkralen", + "boskplakflinter", + "dassen", + "donald_duck", + "wetterr\u00f4t", + "stikelbaarch", + "gielegou", + "eiders", + "stien\u00fbltsje", + "karein", + "wangsekiikhoarntsjes", + "evenhoevigen", + "ivoarsnaffelspjocht", + "d\u00fbkerke", + "feereager", + "reidhintsje", + "reager", + "pylksturt", + "amerikaanske_nerts", + "toarteldo", + "jolling", + "podde", + "frosk", + "sliepm\u00fbzen", + "de_raven", + "dominylyster", + "goudhamster", + "keningsearn", + "knobbelswan", + "berchein", + "hoarn\u00fble", + "klyster", + "goesearn", + "ljip", + "mients", + "readboarstke", + "skoet", + "mallemok", + "manaty", + "swarthalsd\u00fbker", + "otters", + "eider", + "lysterf\u00fbgels", + "boskm\u00fbs" + ], + "FOOD": [ + "moarnsiten", + "kaugom" + ], + "JOB": [ + "sekonde", + "guru", + "oersetter", + "biskop", + "groukopflinters", + "potter", + "plysje", + "komyk", + "meitsje", + "abbekaat", + "don", + "underwizer", + "the_police", + "pastoar", + "boargemaster", + "skearbaas", + "sersjant", + "printer", + "learaar", + "blokfluit", + "master", + "stjerrekundige", + "groom", + "streakje", + "mate", + "ferloskundige", + "sheriff", + "stewardess", + "arbeider", + "boekh\u00e2lder", + "presidint", + "heraut", + "heechlearaar", + "barbier", + "wetter", + "hoarnwiif", + "polysje", + "man" + ], + "GENDER": [ + "jonge", + "man", + "gal" + ], + "GPE": [ + "wite_h\u00fbs", + "dar_es_salaam", + "nikolaas_fan_myra", + "sint_louis", + "minskerjochten", + "nije_testamint", + "hillige_geast" + ], + "RELIGION_MEMBER": [ + "guru", + "fransiskanen", + "sister", + "broer", + "minnisten" + ], + "PRODUCT": [ + "justin_bieber", + "minskerjochten", + "ferjit_my_net", + "trijekeningej\u00fbn", + "de_kat_op_learzens", + "in_poppeh\u00fbs", + "amerikaanske_boargeroarloch", + "goemoarn", + "julius_caesar", + "sint_steffensdei", + "kavia", + "sint_pierre_en_miquelon", + "rosetta_stien", + "krystbeam", + "stillibben", + "de_godlike_komeedzje", + "forjit_my_net", + "muzykynstrumint", + "himellichem", + "de_pylgerreize", + "de_tiidmasine", + "romtestasjon", + "ein_goed_alles_goed", + "de_h\u00fbn_fan_e_baskervilles" + ], + "LANGUAGE": [ + "catalan", + "oerd\u00fb", + "kongo", + "deensk", + "hindy", + "esperanto", + "latyn", + "lao", + "ido", + "japansk", + "galisysk", + "arabysk", + "tonga" + ], + "ORG": [ + "jan_mayen", + "sint_helena", + "nasa", + "boargerlik_rjocht", + "sneinsskoalle", + "dominikanen", + "frijmitselderij", + "schutzstaffel", + "kapetingers", + "normaalskoalle", + "ferljochting", + "electoral_college", + "mar_fan_de_w\u00e2lden", + "heilsleger", + "mahayana", + "feriene_steaten", + "d\u00fatske_keizerryk", + "baskenl\u00e2n", + "tsjow", + "rasseskieding", + "basis\u00fbnderwiis", + "gestapo", + "milit\u00ear", + "weimarrepublyk", + "konservatoarium", + "jeropa", + "toarnroaske", + "po", + "l\u00e2nbou", + "mossad", + "fersoargingssteat", + "nijmoanne", + "ja\u00efnisme", + "sturmabteilung", + "los_angeles", + "kaapverdje", + "giele_rivier", + "sa", + "ik_hjit", + "yndustryterrein", + "konsily", + "sao_tomee", + "regear", + "fraachteken", + "sint_lusia", + "ambachtsskoalle", + "reade_see", + "de_swarte_kat", + "in_komeedzje_fol_fersinnen", + "tao\u00efsme" + ], + "DATE": [ + "trijekeningej\u00fbn", + "nijmoanne", + "juliaanske_kalinder", + "gregoriaanske_kalinder", + "palmpeaske" + ], + "EVENT": [ + "golfoarloch" + ], + "RELIGION": [ + "donatisme", + "wahabisme", + "kataren", + "islam", + "sjinto\u00efsme", + "manige\u00efsme", + "sjintoisme" + ], + "PERSON": [ + "julius_caesar", + "al_gore", + "igor_sikorsky", + "rudolf_hess" + ], + "FAC": [ + "sint_lusia", + "legere_skoalle", + "kearnsintrale", + "peter_de_grutte", + "gemaal", + "hingbr\u00eage", + "roomsk_katolike_tsjerke" + ], + "PERSON_PRONOUN": [ + "i", + "him" + ], + "POLITICAL_PARTY": [ + "nsdap", + "demokratyske_partij", + "partij_fan_de_arbeid", + "politike_partij", + "republikeinske_partij" + ], + "QUANTITY": [ + "dollar", + "fjouwerentweintich", + "parkeargaraazje", + "g", + "anders_celsius" + ], + "LAW": [ + "publykrjocht", + "strafrjocht", + "rjochtssteat" + ], + "UNION": [ + "nea" + ], + "RACE": [ + "ingelsen" + ], + "SOC_ECO_CLASS": [ + "samoerai", + "maatskippij" + ], + "OTHER_PRONOUN": [ + "it" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "b\u00fbk": "groom", + "keizerinne": "keizer", + "heldinne": "held", + "prysteresse": "preester", + "preesteresse": "preester", + "keningin": "kening", + "reine": "kening", + "hja": "hy", + "sister": "broer", + "suster": "broer", + "bean": "man", + "benyn": "man", + "wiif": "man", + "frou": "man", + "jonge": "famke" + }, + "other_gender_swap": { + "thay": "hja", + "iel": "hja", + "hy": "hja", + "hja": "thay" + }, + "en_pronoun2gender": { + "he": [ + "minske", + "jonge", + "man", + "groom" + ], + "she": [ + "benyn", + "wiif", + "faam", + "bean", + "frou", + "famke", + "gal" + ] + }, + "en_pronoun2pronoun": { + "he": [ + "hy", + "seine", + "him" + ], + "she": [ + "hja" + ], + "they": [ + "iel", + "harren", + "seus", + "thay", + "hja" + ], + "it": [ + "dizze", + "it" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/ga.json b/data_tooling/pii_processing/ontology/data/ga.json new file mode 100644 index 0000000..3baa353 --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/ga.json @@ -0,0 +1,5356 @@ +{ + "PUBLIC_FIGURE": [ + "henry_cavendish", + "benjamin_franklin", + "akira_kurosawa", + "seoirse", + "giovanni_boccaccio", + "cornelius_vanderbilt", + "max_bruch", + "che_guevara", + "c", + "thomas_hodgkin", + "henrik_ibsen", + "mary_shelley", + "david_livingstone", + "jan_van_eyck", + "richard_burton", + "mary_wollstonecraft", + "winston_churchill", + "johannes_diderik_van_der_waals", + "b", + "karl_landsteiner", + "dmitri_shostakovich", + "paul_mccartney", + "richard_smalley", + "terry_pratchett", + "k", + "stephen_king", + "francis_crick", + "isaac_newton", + "glant\u00f3ir_siml\u00e9ar", + "victor_hugo", + "edwin_hubble", + "cianrialt\u00e1n", + "cass_gilbert", + "george_stephenson", + "john_glenn", + "john_davis", + "george_harrison", + "george_orwell", + "richard_wagner", + "an_p\u00edobaire_breac", + "marie_curie", + "francis_galton", + "michael_jackson", + "el_greco", + "samuel_beckett", + "galileo_galilei", + "john_donne", + "constaint\u00edn", + "robert_koch", + "i_m_pei", + "joseph_goebbels", + "george_eastman", + "john_steinbeck", + "foraoiseoir", + "fonorm\u00e1lta", + "edmund_hillary", + "brigid", + "an_r\u00ed_lir", + "vincent_van_gogh", + "w", + "hans_jurgen_eysenck", + "p", + "emiliano_zapata", + "tom\u00e1s", + "yuri_gagarin", + "willem_einthoven", + "samuel_johnson", + "giuseppe_verdi", + "e", + "hideki_yukawa", + "konrad_adenauer", + "norbert_wiener", + "gottlieb_daimler", + "ardaidi\u00fanach", + "frank_sinatra", + "katharine_hepburn", + "henri_matisse", + "bertram_brockhouse", + "louis_pasteur", + "j", + "richard_strauss", + "john_ford", + "gertrude_stein", + "saladin", + "sarah_bernhardt", + "v", + "luigi_pirandello", + "t_s_eliot", + "incigh", + "robert_millikan", + "charles_de_gaulle", + "y", + "charles_lindbergh", + "f", + "ludwig_wittgenstein", + "august_strindberg", + "thomas_mann", + "charles_goodyear", + "dante_alighieri", + "samuel_de_champlain", + "giacomo_puccini", + "louis_braille", + "mungo_park", + "paul_verlaine", + "q", + "james_dean", + "marie_tussaud", + "theodor_schwann", + "joseph_priestley", + "nicolas_poussin", + "oscar_wilde", + "philip_roth", + "j_d_salinger", + "richard_trevithick", + "heinrich_schliemann", + "eli_whitney", + "laurence_olivier", + "christiaan_eijkman", + "francis_bacon", + "pete_seeger", + "joseph_heller", + "a", + "peter_brian_medawar", + "james_brown", + "charles_baudelaire", + "z", + "immanuel_kant", + "james_franck", + "william_crookes", + "n", + "coinic\u00e9ar", + "giulio_natta", + "johannes_kepler", + "max_planck", + "t_e_lawrence", + "john_bardeen", + "william_henry", + "george_vancouver", + "canberra", + "elias_canetti", + "beirt", + "edward_jenner", + "frans_hals", + "igor_stravinsky", + "william_herschel", + "joseph_black", + "niels_bohr", + "henry_fielding", + "bertrand_russell", + "michael_faraday", + "rudolf_diesel", + "antaine", + "walt_disney", + "friedrich_engels", + "jane_austen", + "gustav_mahler", + "robert_redford", + "jack_dempsey", + "ian_fleming", + "richard_feynman", + "wolfgang_pauli", + "beinidict", + "theodor_mommsen", + "andrew_huxley", + "marcel_proust", + "thomas_more", + "elizabeth_taylor", + "thomas_chippendale", + "william_golding", + "william_caxton", + "albert_speer", + "john_vanbrugh", + "gr\u00e9ag\u00f3ir", + "frank_whittle", + "alfred_nobel", + "marco_polo", + "caravaggio", + "m", + "daniel_bernoulli", + "joseph_henry", + "henri_bergson", + "gottfried_leibniz", + "phillis_wheatley", + "patrick_white", + "hans_zinsser", + "hans_christian_andersen", + "william_morris", + "cary_grant", + "pablo_picasso", + "thomas_moore", + "otto_hahn", + "christiaan_huygens", + "antonio_stradivarius", + "hector_berlioz", + "claudio_monteverdi", + "john_galsworthy", + "o", + "adam_smith", + "william_james", + "antoin", + "u", + "karl_marx", + "friedrich_nietzsche", + "i", + "sandro_botticelli", + "carson_mccullers", + "nikola_tesla", + "al_capone", + "robert_schumann", + "mel_gibson", + "le_corbusier", + "john_locke", + "alexis_carrel", + "joseph_marie_jacquard", + "an_tiolar", + "jean_piaget", + "valentina_tereshkova", + "h_g_wells", + "walt_whitman", + "colin_powell", + "ludwig_boltzmann", + "carl_jung", + "ramasaes_ii", + "richard_wright", + "benjamin_thompson", + "adolf_hitler", + "fritz_haber", + "george_boole", + "paul_revere", + "robert_boyle", + "edith_cavell", + "tu\u00edod\u00f3ir", + "1", + "rosa_parks", + "x", + "ernest_walton", + "laurence_sterne", + "owen", + "g", + "arthur_schopenhauer", + "james_cagney", + "martin_heidegger", + "arnold_schoenberg", + "r", + "george_lucas", + "andrew_jackson", + "louis_armstrong", + "steven_spielberg", + "robert_fulton", + "thomas_hardy", + "giuseppe_garibaldi", + "philip_warren_anderson", + "robert_brown", + "wilhelm_weber", + "bobby_fischer", + "johannes_gutenberg", + "d", + "thomas_malthus", + "gaetano_donizetti", + "william_faulkner", + "amerigo_vespucci", + "hans_adolf_krebs", + "francis_poulenc", + "james_ussher", + "john_constable", + "rachel_louise_carson", + "matthew_flinders", + "jean_de_la_fontaine", + "iodhadh", + "peter_o'toole", + "joseph_conrad", + "peter_paul_rubens", + "mahatma_gandhi", + "jim_morrison", + "jules_verne", + "paul_newman", + "fyodor_dostoyevsky", + "jackson_pollock", + "john_lennon", + "andrea_palladio", + "charlie_chaplin", + "d_h_lawrence", + "naomh_seoirse", + "thomas_merton", + "asa_gray", + "miles_davis", + "edmund_cartwright", + "andrey_sakharov", + "william_gilbert", + "james_watt", + "homo", + "david_hilbert", + "wilhelm_reich", + "martin_luther_king", + "james_hargreaves", + "william_wordsworth", + "s", + "william_clark", + "woodrow_wilson", + "gustav_hertz", + "st_louis", + "don_quixote", + "ernest_hemingway", + "george_westinghouse", + "eero_saarinen", + "arthur_miller", + "nelson_mandela", + "heinrich_himmler", + "al_gore", + "hans_bethe", + "hans_geiger", + "roald_amundsen", + "charles_dickens", + "ella_fitzgerald", + "peadar_m\u00f3r", + "joseph_paxton", + "bessie_smith", + "francisco_pizarro", + "francisco_franco", + "johnny_cash", + "joseph_mccarthy", + "mick_jagger", + "dreoil\u00edn", + "georges_cuvier", + "william_harvey", + "walter_scott", + "robert_peary", + "john_bunyan", + "jonathan_swift", + "maorsh\u00e1irsint", + "t\u00edteas", + "albert_einstein", + "l", + "thomas_edison", + "chiang_kai_shek", + "raymond_chandler", + "t" + ], + "JOB": [ + "mairn\u00e9alach", + "pluim\u00e9ir", + "eitleoir", + "taifead\u00e1n", + "an_dealbh\u00f3ir", + "seand\u00e1la\u00ed", + "cadh\u00f3it", + "armad\u00f3ir", + "ceathr\u00famh\u00e1istir", + "aistire", + "rialt\u00e1n", + "reiligire", + "eagarth\u00f3ir", + "oist\u00e9apat", + "geilleagra\u00ed", + "banambasad\u00f3ir", + "feirmeoir", + "sirriam", + "ollamh", + "banch\u00faram\u00f3ir", + "garda\u00ed", + "ardcheannasa\u00ed", + "gunnad\u00f3ir", + "aontachta\u00ed", + "saighdi\u00fair", + "miasniteoir", + "docht\u00fair", + "doirseoir", + "bandeag\u00e1nach", + "rothad\u00f3ir", + "maorlatha\u00ed", + "cathaoirleach", + "char", + "rinceoir", + "aistritheoir", + "aireag\u00f3ir", + "aturnae", + "innealt\u00f3ir", + "bainisteoir", + "bangharda", + "fichill\u00edn", + "baird\u00e9ir", + "reacht\u00f3ir", + "foraoiseoir", + "bantr\u00e9ada\u00ed", + "gruagaire", + "dorn\u00e1la\u00ed", + "reachtaire", + "banalms\u00f3ir", + "ardaidi\u00fanach", + "rial\u00f3ir", + "bunaitheoir", + "giolla", + "ceolt\u00f3ir", + "cruinnitheoir", + "bardach", + "vacsa\u00edneoir", + "saothra\u00ed", + "gort\u00f3ir", + "buachaill_caorach", + "acadamha\u00ed", + "banaoire", + "acht\u00faire", + "poitig\u00e9ir", + "dugaire", + "ban\u00fadar", + "seansail\u00e9ir", + "easpag", + "optaim\u00e9adra\u00ed", + "radharceola\u00ed", + "norm\u00e1lta", + "innealt\u00f3ir_sibhialta", + "alms\u00f3ir", + "br\u00fastocaire", + "ain\u00e9ist\u00e9is\u00ed", + "bainc\u00e9ir", + "coimirceoir", + "cairdeola\u00ed", + "n\u00e9areola\u00ed", + "feighl\u00ed", + "briog\u00e1idire_ghinear\u00e1l", + "molt\u00f3ir", + "p\u00f3staer", + "gaucho", + "anail\u00eds\u00ed", + "vaidht\u00e9ir", + "aigneola\u00ed", + "m\u00e1lfheidhmeannach", + "gearrscr\u00edobha\u00ed", + "balsam\u00f3ir", + "gairneoir", + "aist\u00ed", + "tonnleasaitheoir", + "cl\u00f3churad\u00f3ir", + "urlabhra\u00ed", + "croiniceoir", + "coime\u00e1da\u00ed", + "gearb", + "abhc\u00f3ide", + "bansti\u00farth\u00f3ir", + "radagrafa\u00ed", + "fond\u00fair", + "croinic\u00ed", + "leifteanant", + "banchigire", + "vaidht\u00e9ara\u00ed", + "miond\u00edolt\u00f3ir", + "baneitleoir", + "neamhsple\u00e1ch", + "banghiolla", + "grianghrafad\u00f3ir", + "muic\u00ed", + "breacaire", + "bunfhr\u00e9amh", + "bansealgaire", + "aisteoir", + "raideola\u00ed", + "ceithearnach", + "damhs\u00f3ir" + ], + "LOCATION": [ + "al_jazeera", + "saint\u00ed", + "an_me\u00e1noirthear", + "an_su\u00ed_naofa", + "luibhghaird\u00edn", + "arbor_vitae", + "an_taig\u00e9an_ci\u00fain", + "b\u00e9ar_m\u00f3r", + "athbhliain", + "staidiam", + "an_mhuir_dhubh", + "piet_mondrian", + "an_astr\u00e1il_thiar", + "colarad\u00f3", + "an_leon_beag", + "daid\u00ed_na_nollag", + "cnoc_na_nol\u00f3g", + "an_veas\u00faiv", + "an_huaing_h\u00f3", + "an_astr\u00e1il_theas", + "arm_na_st\u00e1t_aontaithe", + "na_t\u00edortha_faoi_thoinn", + "air\u00e9ine", + "criost\u00f3ir_colambas", + "an_b\u00e9ar_beag", + "abhantrach", + "cathair_ardeaglaise", + "joseph_louis_gay_lussac", + "an_mhuir_thuaidh", + "aerfh\u00f3rsa", + "na_lochanna_m\u00f3ra", + "compal", + "m\u00e1ire_mhaigdil\u00e9ana", + "rinn_verde", + "ceolscoil", + "rinn_an_choirn", + "an_iond\u00fais", + "cathair_londan", + "aig\u00e9an_atlantach", + "an_l\u00e1r_r\u00e9igi\u00fan_thoir", + "meirice\u00e1", + "na_madra\u00ed_fiaigh", + "char\u00f3g_liath", + "the_rolling_stones", + "cumhachtst\u00e1isi\u00fan", + "an_tsacsain_anhalt", + "naomh_p\u00e1draig", + "banc_ceannais", + "an_b\u00e9ar_m\u00f3r", + "banl\u00e1mh", + "an_taig\u00e9an_atlantach", + "an_taig\u00e9an_indiach" + ], + "ORG": [ + "an_eoraip", + "an_ph\u00f3", + "reifirm\u00e9isean", + "r\u00e9altbhraisle", + "talmha\u00edocht", + "an_oir_ghearm\u00e1in", + "cathairst\u00e1it", + "ainiomad", + "wicca", + "gairmscoil", + "an_l\u00e1r_r\u00e9igi\u00fan_thiar", + "loch_laomainn", + "socheacnama\u00edoch", + "banghas\u00f3g", + "an_tr\u00ed\u00fa_reich", + "an_b\u00e9ar_m\u00f3r", + "le_taobh_a_ch\u00e9ile", + "aa", + "nasa", + "na_halc\u00f3laigh_gan_ainm", + "isi", + "an_p\u00e1irt\u00ed_liobr\u00e1lach", + "the_who", + "le_hais_a_ch\u00e9ile", + "gi\u00fadachas_ceartchreidmheach", + "cros_dhearg", + "bunscoil", + "san_francisco", + "\u00edosaicme", + "ar_chor_ar_bith", + "gi\u00fadachas_coime\u00e1dach", + "an_huaing_h\u00f3", + "mahayana", + "luibhghaird\u00edn", + "an_amas\u00f3in", + "dl\u00ed_r\u00f3mh\u00e1nach", + "sa_bhaile", + "don_juan", + "ardmhinic\u00edochta", + "an_taontas_eorpach", + "ceolscoil", + "an_p\u00e1irt\u00ed_coime\u00e1dach", + "naomhtheaghlach", + "dia", + "ardmhinic\u00edocht", + "an_mhuir_rua", + "an_chipir_thuaidh", + "ceardchumann", + "de_dh\u00e9ant\u00fas_an_duine", + "eaglais_cheartchreidmheach", + "muir_rua", + "jabionad", + "is_mise", + "me\u00e1nscoil", + "eaglais_chaitliceach", + "fuinneamh", + "rabindranath_tagore", + "guma_coganta", + "scoil_cheoil", + "beinidictigh", + "an_ch\u00e9ad_comhairle_vatac\u00e1ine", + "san_h\u00e9ilin", + "an_p\u00e1irt\u00ed_daonlathach_liobr\u00e1lach", + "al_jazeera", + "stocmhalart\u00e1n", + "san_lucia", + "ardch\u00fairt", + "st\u00e1it_aontaithe", + "gealtlann", + "teach_custaim", + "an_ghuine_mhe\u00e1nchriosach", + "buanchoiste", + "loch_superior", + "idirph\u00f3sadh", + "ardscoil", + "o\u00edche_chaille", + "ceartchreidmheachas", + "ponc", + "los_angeles", + "p\u00e1irt\u00ed_an_lucht_oibre", + "aons\u00faileach", + "an_ch\u00e9ad_comhdh\u00e1il_nicea", + "inchinne", + "an_mathshlua_\u00f3rga", + "don_diabhal_leis", + "an_eola\u00edocht_chr\u00edosta\u00ed", + "gi\u00fadachas_leasaitheach", + "margadh_bull\u00fail", + "cathl\u00e1n", + "aerarm", + "an_eagna\u00edocht", + "an_ghearm\u00e1inis", + "ar_bith", + "na_meirv\u00ednsigh", + "an_ch\u00fairt_bhreithi\u00fanais_idirn\u00e1isi\u00fanta", + "oile\u00e1n_\u00far" + ], + "GENDER": [ + "homaighn\u00e9asach", + "cail\u00edneog", + "leispiach", + "baineannach", + "caileag", + "gars\u00fan", + "a_dhaoine_uaisle", + "bantiarna" + ], + "PRODUCT": [ + "an_soitheach_naofa", + "caifechup\u00e1n", + "justin_bieber", + "fyodor_dostoyevsky", + "an_taontas_s\u00f3iv\u00e9adach", + "an_me\u00e1n_domhan", + "tine_gheal\u00e1in", + "an_dara_cogadh_domhanda", + "al_jazeera", + "gearrchiorcad", + "s\u00e3o_tom\u00e9_agus_pr\u00edncipe", + "sacsain_anhalt", + "an_choim\u00e9ide_dhiaga", + "naomhspiorad", + "muc_ghuine", + "an_bhreatain", + "an_spiorad_naomh", + "the_star_spangled_banner", + "le_c\u00fanamh_d\u00e9", + "na_seoda", + "don_quixote", + "an_tsacsain_anhalt", + "an_r\u00edocht_aontaithe", + "an_nua_sh\u00e9alainn", + "taebhosca", + "an_ch\u00e9ad_chogadh_domhanda", + "tiomna_nua", + "saint\u00ed", + "lus_m\u00edonla" + ], + "DISEASE": [ + "cam_mhuin", + "seiptic\u00e9ime", + "airtr\u00edteas", + "ballbhr\u00faigh", + "an_fhiol\u00e1iri\u00e1is", + "siondr\u00f3m", + "r\u00e9amheaclaimsia", + "ainglis", + "pairilis", + "tacht", + "tritheamh", + "sciots\u00f3ideach", + "toircheas", + "fleib\u00edteas", + "an_phl\u00e1_mh\u00f3r", + "cataileipse", + "oftailme", + "galareola\u00edocht", + "maolteanga", + "loch_ascaille", + "pianadh", + "murtall", + "fothach", + "an_phl\u00e1_dhubh", + "an_port\u00e1n", + "rada\u00edocht", + "polaip", + "saic\u00edn\u00edteas", + "seachr\u00e1n", + "griand\u00f3", + "heirne", + "vacsa\u00edni\u00fa", + "gall", + "geimhri\u00fa", + "scr\u00edob", + "achtanim\u00edoc\u00f3is", + "m\u00ed_dh\u00edle\u00e1", + "anchuma", + "pataigin", + "urtac\u00e1ire", + "laraing\u00edteas", + "adanaiv\u00edreas", + "polaic\u00edotaemacht", + "giairdi\u00e1is", + "cliseadh", + "peireat\u00f3in\u00edteas", + "deinge", + "fiocas", + "paireacht", + "cuais\u00edteas", + "soiri\u00e1is", + "reitriv\u00edreas", + "seif", + "polaimiail\u00edteas", + "conslaod", + "goir\u00edn", + "cr\u00e9acht", + "greim", + "an_bhruit\u00edneach", + "luch", + "ceangailteacht", + "feinilc\u00e9at\u00f3n\u00faire", + "talasaemacht", + "broinc\u00edteas", + "tochais", + "scar", + "beri_beri", + "athlasadh", + "forghabh\u00e1il", + "raic\u00edteas", + "polaimi\u00f3is\u00edteas", + "anch\u00fainseacht", + "bunaitheoir", + "trac\u00f3ime", + "gearrgh\u00e9agacht", + "seargadh", + "masmas", + "\u00edsleacht", + "ballbhr\u00fa", + "an_chiorr\u00f3is", + "adanacarcan\u00f3ma", + "daille", + "paiteola\u00edocht", + "meisce", + "granal\u00f3ma", + "ancal\u00f3is", + "corn", + "an_faolch\u00fa", + "arasaipil", + "gonairith", + "spina_bifida", + "coiliceam", + "mast\u00f3id\u00edteas", + "bolgach", + "creit\u00edneacht", + "codail", + "leonadh", + "tine_dhia", + "treighid", + "teiteanas", + "aileac\u00f3", + "adan\u00f3ma", + "peireacaird\u00edteas", + "ailb\u00edneachas", + "an_dift\u00e9ire", + "cumhdaitheoir", + "sileac\u00f3is", + "gear\u00e1n", + "an_liomf\u00f3ma", + "faithne", + "trioc\u00f3m\u00f3ini\u00e1is", + "meilean\u00f3ma", + "casaoid", + "triuch", + "meining\u00edteas", + "cr\u00e9achta", + "r\u00e9altn\u00e9al", + "deirmit\u00edteas", + "eidhne\u00e1n_nimhe", + "galr\u00fa", + "smut", + "dinnireacht", + "lasadh", + "ang\u00f3ma", + "colaicist\u00edteas", + "galar_parkinson", + "sting", + "confadh", + "str\u00f3c", + "baict\u00e9arafagach", + "ruachtach", + "fond\u00fair", + "aonachas", + "sleamhn\u00e1n", + "kuru", + "peallagra", + "morgadh", + "daitheacha", + "ciapadh", + "otracht", + "freang", + "le", + "comhtholgadh", + "salmonella", + "sion\u00f3ibh\u00edteas", + "uathachas", + "seineaf\u00f3ibe", + "luch\u00f3g", + "piolaineifr\u00edteas", + "meisceoireacht", + "an_gaistr\u00edteas", + "carrmhogal" + ], + "FAC": [ + "arnold_schoenberg", + "ionad_siopad\u00f3ireachta", + "an_suip\u00e9ar_d\u00e9anach", + "hall_an_bhaile", + "naomh_i\u00f3saf", + "mall", + "oifig_poist", + "cloch_seasaimh", + "san_lucia", + "eaglais_chaitliceach_r\u00f3mh\u00e1nach", + "pinni\u00far", + "naomhtheaghlach", + "oifig_an_phoist", + "siopalann", + "bunscoil", + "go_n_\u00e9ir\u00ed_an_b\u00f3thar_leat" + ], + "PLANT": [ + "magn\u00f3ilia", + "casabhach", + "leaith\u00edn", + "the_joshua_tree", + "cleim\u00e9atas", + "meispeal", + "cair\u00e9ad", + "cost\u00f3g", + "labhras", + "coinnle_muire", + "ceannbh\u00e1n", + "seams\u00f3g", + "lear\u00f3g", + "garbhlus", + "criosantamam", + "scornlus", + "leit\u00eds", + "seiceam\u00f3ir", + "candida_albicans", + "sabhairc\u00edn", + "beirgeam\u00f3", + "rufach\u00e1n", + "beiteal", + "goirm\u00edn", + "maraitis", + "maol\u00edosa", + "daims\u00edn", + "corcdhair", + "raideog", + "seiceamar", + "feirdhris", + "beathnua", + "draighean", + "barr_margaidh", + "gallfheochad\u00e1n", + "broim\u00edn", + "fearn\u00f3g", + "tains\u00e9ir\u00edn", + "balsaim\u00edn", + "morm\u00f3nta", + "samhadh", + "bior\u00f3g", + "mailp", + "edelweiss", + "crann_nollag", + "codlaid\u00edn", + "d\u00fachan_pr\u00e1ta\u00ed", + "belladonna", + "barbr\u00f3g", + "andraim\u00e9id", + "bachl\u00f3g", + "naomh_m\u00e1ire", + "hevea_brasiliensis", + "pribh\u00e9ad" + ], + "DATE": [ + "leathuair", + "am_na_r\u00e9alta\u00ed", + "an\u00f3irthear", + "an_tseachtain_mh\u00f3r", + "am_uil\u00edoch_comheagartha", + "nuar\u00e9", + "griantairiseach", + "leathch\u00e9ad", + "leathghealach", + "deast\u00f3g\u00e1il_muire", + "an_mhe\u00e1naois", + "leathr\u00e9", + "amanathar" + ], + "ANIMAL": [ + "cat", + "coir\u00e9al", + "cruid\u00edn", + "ulchabh\u00e1n", + "rapiolar", + "cornfhoiche", + "cat_coille", + "blat\u00f3g", + "tarmachan", + "cat_crainn", + "garrfhiach", + "buachrapaire", + "foracha", + "condar", + "speirsheabhac", + "traonach", + "maintis", + "seolt\u00f3ir", + "adhairc\u00edn", + "maorsh\u00e1irsint", + "seabhac", + "artadachtail", + "cadhan", + "bleachtfh\u00e9ileac\u00e1n", + "caiseal\u00f3id", + "m\u00edlechosach", + "g\u00e1lfhoiche", + "bult\u00far", + "riabh\u00f3g", + "nathair_choir\u00e9alach", + "naoscach", + "gust\u00fan", + "pilib\u00edn", + "minc", + "ollarmadail\u00edn", + "leim\u00edn", + "frog", + "taipir", + "cat_aibis\u00edneach", + "an_lincse", + "giorria_gallda", + "cat_siamach", + "n\u00e9arfhead\u00e1n", + "guairdeall", + "na_h\u00e9isc", + "fear\u00e1n", + "sealta\u00ed", + "fear\u00e1n_gubhach", + "donald_duck", + "priompall\u00e1n", + "cat_crainn_clochra", + "droimeiteach", + "mamach", + "liathchearc", + "beachad\u00f3ir", + "cearnabh\u00e1n", + "biorearrach", + "treaghd\u00e1n", + "francach_donn", + "artrap\u00f3d", + "cat_crainn_p\u00edb_bhu\u00ed", + "lincse", + "goraille", + "brann\u00f3g", + "an_madra_beag", + "sisc\u00edn", + "seile\u00e1n", + "airp", + "cat_gainimh", + "seirice\u00e1n", + "earrdhearg\u00e1n" + ], + "LANGUAGE": [ + "bascais", + "c\u00f3isis", + "teileag\u00fais", + "ceatsuais", + "labhairt", + "casacach", + "macad\u00f3nach", + "asarbaise\u00e1nach", + "airm\u00e9anach", + "boisniach", + "an_ion\u00faitis", + "briot\u00e1nach", + "an_araibis", + "an_mhail\u00e9alaimis", + "an_hiond\u00fais", + "macad\u00f3inise", + "portaing\u00e9alach", + "liotu\u00e1nach", + "afrac\u00e1inis", + "an_tsaird\u00ednis", + "an_ph\u00e1ilis", + "coimis", + "east\u00f3nach", + "mairsillis", + "macad\u00f3ine", + "peirsis", + "an_urdais", + "baiscireach", + "vall\u00fanais", + "catal\u00f3nach", + "navach\u00f3ch", + "corsacach", + "an_tsanscrait", + "as_maenmar", + "esperanto", + "an_am\u00e1iris", + "sprantais", + "cornach", + "an_laidin", + "indin\u00e9iseach", + "seisniach", + "vall\u00fainis", + "gearm\u00e1nach", + "an_aiv\u00e9istis", + "bealar\u00faiseach", + "lao", + "eabhrach", + "coirdise", + "ido", + "fraincis", + "seiceach", + "cannadais", + "an_afrac\u00e1inis", + "tonga" + ], + "PERSON_PRONOUN": [ + "t\u00fa", + "i", + "i_d_aonar" + ], + "FOOD": [ + "scroid", + "gaineamhlach", + "im_piseanna_tal\u00fan", + "burgar", + "sceall\u00f3ga", + "taosr\u00e1n", + "garbh\u00e1nach", + "caife", + "caisc\u00edn", + "bricfeasta", + "t\u00f3sta_francach" + ], + "POLITICAL_PARTY_MEMBER": [ + "poblacht\u00e1nach", + "cumannach", + "boils\u00e9iveach", + "daonlatha\u00ed", + "poblachtach" + ], + "UNION": [ + "ceardchumann", + "aontas_idirn\u00e1isi\u00fanta_teileachumars\u00e1ide" + ], + "RELIGION": [ + "zen", + "an_mhainic\u00e9asa\u00edocht", + "preispit\u00e9ireachas", + "sufaisteachas", + "cailv\u00edneachas", + "wicca", + "an_eola\u00edocht_chr\u00edosta\u00ed" + ], + "RACE": [ + "breatnaigh", + "seap\u00e1naigh", + "astr\u00e1lach", + "afracach", + "bund\u00fachasach", + "sasanaigh", + "filip\u00ednis", + "pacast\u00e1nach", + "francaigh", + "eiscimigh", + "cugasach" + ], + "GPE": [ + "spiorad_naomh", + "an_mhuir_aeig\u00e9ach", + "cearta_daonna", + "an_mhuir_rua", + "an_talamh_naofa", + "impireacht_na_gearm\u00e1ine", + "hagia_sofia", + "naomh_niocl\u00e1s", + "cumann_na_croise_deirge", + "naomh_peadar", + "al_andalus", + "naomhspiorad", + "an_spiorad_naomh", + "an_c\u00f3sta_eabhair", + "an_fhoraois_dhubh", + "teach_b\u00e1n", + "st_louis", + "cearta_an_duine" + ], + "PERSON": [ + "al_gore", + "h_g_wells", + "don_delillo", + "domhainfhriochta", + "edward_osborne_wilson", + "carl_david_anderson", + "rudolf_hess" + ], + "SOC_ECO_CLASS": [ + "me\u00e1naicme", + "\u00edosaicme", + "margadh_dubh", + "talmha\u00edocht", + "lucht_oibre", + "beag\u00e1n" + ], + "RELIGION_MEMBER": [ + "amanaigh", + "protast\u00fanach", + "dearth\u00e1ir", + "proinsiasaigh", + "proinsiasach", + "preispit\u00e9ireach", + "beinidicteach", + "b\u00fada\u00edoch", + "caitliceach", + "mahamadach" + ], + "QUANTITY": [ + "scilling", + "ton", + "dollar", + "g", + "vatuair", + "franc_eilv\u00e9iseach", + "punt_steirling", + "carrchl\u00f3s", + "solasbhliain", + "anders_celsius" + ], + "POLITICAL_PARTY": [ + "comhaontas_glas", + "p\u00e1irt\u00ed_poblachtach", + "p\u00e1irt\u00ed_polait\u00edochta", + "p\u00e1irt\u00ed_daonlathach", + "p\u00e1irt\u00ed", + "an_p\u00e1irt\u00ed_liobr\u00e1lach", + "an_p\u00e1irt\u00ed_coime\u00e1dach" + ], + "LAW": [ + "ardch\u00fairt", + "croscheisti\u00fa" + ], + "EVENT": [ + "fl\u00f3r_de_l\u00fais" + ], + "BIO_CHEM_ENTITY": [ + "polaiviniolcl\u00f3ir\u00edd" + ], + "ner_regexes": [ + [ + "PERSON", + "\\D+ \\D+|\\D+ \\D+|\\D+ \\D+|\\D+ \\D+|\\D+ \\D+-\\D+|\\D+ \\D+|\\D+ \\D+|\\D+ \\D+|\\D+ \\D+|\\D+ \\D+-\\D+|\\D+ \\D+ \\D+|\\D+ \\D+ \\D+|\\D+ \\D+ \\D+|\\D+ \\D+ \\D+", + false, + [] + ] + ], + "FIRST_NAME_FEMALE": [ + "adeline", + "stephanie", + "priscilla", + "vivien", + "hannah", + "genevieve", + "natasha", + "zoe", + "janet", + "fionnuala", + "antonia", + "claudine", + "caoimhe", + "maighread", + "karin", + "glenda", + "dana", + "ailbhe", + "dearbhla", + "winifred", + "donna", + "maria", + "lynn", + "lavinia", + "maxine", + "annette", + "marian", + "ailish", + "arlene", + "dolores", + "heather", + "sandra", + "isobel", + "daragh", + "philomena", + "ingrid", + "janine", + "joan", + "helena", + "tonya", + "ethna", + "anne", + "gwendoline", + "eithne", + "eva", + "loyola", + "wendy", + "moira", + "hazel", + "bronwen", + "jean", + "virginia", + "michele", + "michell", + "antoinette", + "marina", + "eunice", + "darina", + "davnet", + "zita", + "thelma", + "trina", + "leonie", + "loraine", + "cait", + "jocelyn", + "charlotte", + "gabrielle", + "andrea", + "brona", + "esther", + "yolanda", + "valerie", + "vanessa", + "grania", + "madeline", + "cheryl", + "rhonda", + "erica", + "gertrude", + "bernadine", + "josephine", + "nina", + "collette", + "eleanor", + "michelle", + "julia", + "caroline", + "ita", + "phyllis", + "michaela", + "erika", + "noeleen", + "katharine", + "derval", + "neasa", + "siobain", + "gloria", + "siobhan", + "violet", + "helan", + "freda", + "justine", + "yvette", + "liza", + "davida", + "jacinta", + "christine", + "dara", + "breeda", + "ellen", + "sioban", + "fiona", + "therese", + "alice", + "leone", + "orlaith", + "karan", + "joanne", + "jacqueline", + "norah", + "catherina", + "cathriona", + "judy", + "paula", + "marion", + "patricia", + "celine", + "samantha", + "juliette", + "alicia", + "elizabeth", + "rosarie", + "colette", + "natalie", + "lillian", + "lara", + "susan", + "elaine", + "marlene", + "shona", + "nicola", + "anastasia", + "belinda", + "carina", + "beverley", + "sonia", + "olga", + "janice", + "camilla", + "mairin", + "cora", + "rebecca", + "sonya", + "elva", + "clodagh", + "briget", + "noirin", + "stella", + "hillary", + "alexandra", + "miranda", + "gail", + "danielle", + "gillian", + "jacintha", + "darragh", + "nessa", + "ide", + "petrina", + "sophie", + "dervla", + "rowena", + "noeline", + "muriel", + "loretto", + "lucinda", + "julianna", + "lilian", + "toni", + "dymphna", + "marguerite", + "angeline", + "martina", + "anastatia", + "katrina", + "jennifer", + "victoria", + "amber", + "joyce", + "rachel", + "muireann", + "sheela", + "alexis", + "lisa", + "felicity", + "maire", + "laura", + "catherine", + "jill", + "cathleen", + "june", + "susanne", + "norma", + "julie", + "denise", + "breffni", + "vivian", + "dianne", + "olive", + "rosanne", + "noelle", + "ella", + "mairead", + "samanta", + "daphne", + "gerardine", + "sile", + "sophia", + "jillian", + "shauna", + "aideen", + "deborah", + "deborrah", + "rhona", + "jayne", + "treacy", + "rena", + "leona", + "tania", + "eavan", + "cathrina", + "clair", + "dona", + "matilda", + "rita", + "grainne", + "bridie", + "loretta", + "mary", + "leonora", + "maeve", + "elena", + "clare", + "cara", + "saundra", + "caitriona", + "katharina", + "brid", + "margaret", + "delia", + "treasa", + "marianne", + "dympna", + "gretta", + "ciara", + "katherine", + "bronwyn", + "florence", + "bronagh", + "annie", + "serena", + "bairbre", + "gwendolen", + "vera", + "cathy", + "lucia", + "melanie", + "christina", + "sheena", + "eileen", + "kerry", + "katriona", + "nichola", + "gemma", + "diann", + "monica", + "henrietta", + "rosaleen", + "evelyn", + "emer", + "sara", + "naimh", + "tracey", + "lorraine", + "amy", + "marese", + "pearl", + "cliona", + "corinna", + "sylvia", + "ashley", + "olivia", + "aedin", + "aileen", + "sorcha", + "rosemary", + "niamh", + "rosemarie", + "una", + "kathryn", + "carmel", + "averil", + "mandy", + "olwen", + "gina", + "anna", + "juliet", + "sheelagh", + "aishling", + "juanita", + "orla", + "tracy", + "imelda", + "lynne", + "adele", + "shirley", + "carla", + "ethel", + "carolyn", + "jenifer", + "janette", + "charmaine", + "sally", + "shiela", + "rosa", + "hanora", + "geraldine", + "orna", + "ruth", + "angela", + "linda", + "rosanna", + "dervilla", + "carmen", + "fionna", + "helen", + "edwina", + "kathleen", + "diane", + "celina", + "jeanne", + "moya", + "amelia", + "ursula", + "sarah", + "cynthia", + "theresa", + "johanna", + "joy", + "marcella", + "lucy", + "doreen", + "pamela", + "joanna", + "aoife", + "eimear", + "claire", + "brigid", + "mona", + "noleen", + "irene", + "dawn", + "deirdre", + "emma", + "naomh", + "debbie", + "judith", + "iris", + "eveline", + "regina", + "nadine", + "ashling", + "nuala", + "lynda", + "attracta", + "tara", + "tina", + "alva", + "alma", + "ailis", + "sheila", + "deidre", + "abina", + "nancy", + "martha", + "avril", + "eilis", + "monique", + "audrey", + "aisling", + "shinead", + "penelope", + "fidelma", + "grace", + "edel", + "finola", + "brenda", + "estelle", + "breda", + "bernice", + "ann", + "catheriona", + "emily", + "ethne", + "concepta", + "brighid", + "katherina", + "marie", + "lorna", + "melinda", + "cliodhna", + "tanya", + "blathnaid", + "alison", + "nicole", + "naomi", + "gwen", + "marilyn", + "helga", + "leslie", + "diana", + "inez", + "roisin", + "eimer", + "celia", + "veronica", + "marjorie", + "oonagh", + "kim", + "noreen", + "susanna", + "rachael", + "catriona", + "anita", + "maura", + "rose", + "sinead", + "karina", + "majella", + "heidi", + "siobhain", + "maureen", + "fionnula", + "jeannette", + "roberta", + "barbara", + "honora", + "agnes", + "simone", + "eilish", + "lena", + "aine", + "assumpta", + "paulette", + "nora", + "rosario", + "debra", + "lesley", + "isabel", + "jeanette", + "cathrine", + "ida", + "roslyn", + "cecelia", + "claudia", + "jessica", + "angelina", + "leah", + "vivienne", + "adrienne", + "bridget", + "hilda", + "teresa", + "jane", + "breege", + "april", + "dearbhail", + "sharon", + "celene", + "johanne", + "amanda", + "dorothy", + "georgina", + "melissa", + "rona", + "eve", + "harriet", + "frances", + "yvonne", + "triona", + "suzanne", + "allison", + "bernadette", + "dora", + "cecilia", + "kara", + "pauline", + "karen", + "miriam", + "louise", + "corona", + "hilary", + "kate", + "edith", + "myra", + "nollaig", + "andrena", + "colleen", + "carol", + "beatrice", + "clara", + "adrianne", + "carole" + ], + "FIRST_NAME_MALE": [ + "shaun", + "raymond", + "justin", + "jarlath", + "garrett", + "kilian", + "benjamin", + "thaddeus", + "daire", + "tadhg", + "peter", + "hugh", + "edwin", + "jude", + "leigh", + "mathew", + "finbarr", + "alphonsus", + "daragh", + "nial", + "ross", + "ciaran", + "gareth", + "jarleth", + "dermott", + "henry", + "luke", + "finbar", + "vincent", + "howard", + "darrin", + "jean", + "dermot", + "james", + "edmund", + "gerard", + "darran", + "bernard", + "killian", + "wayne", + "mortimer", + "mac", + "roy", + "austin", + "owen", + "valentine", + "cyril", + "pierce", + "neville", + "raphael", + "adam", + "simon", + "alfred", + "dara", + "desmond", + "angus", + "andre", + "ray", + "conleth", + "ronan", + "phelim", + "garech", + "fearghal", + "stewart", + "columba", + "frank", + "rowan", + "bruce", + "mervyn", + "fionan", + "donagh", + "cillian", + "bartley", + "flannan", + "kieran", + "emmett", + "matthew", + "marc", + "gerrard", + "dennis", + "camillus", + "jonathan", + "darren", + "bryan", + "daniel", + "keith", + "steve", + "darragh", + "myles", + "ambrose", + "scott", + "donald", + "kiernan", + "emmet", + "colum", + "fabian", + "warren", + "noel", + "domhnall", + "jesse", + "walter", + "oliver", + "john", + "davin", + "spencer", + "brendan", + "herbert", + "julian", + "george", + "padraigh", + "gavan", + "colman", + "diarmuid", + "glenn", + "louis", + "paschal", + "vivian", + "lawrence", + "mark", + "joseph", + "basil", + "eoghan", + "cormac", + "guy", + "malcolm", + "christian", + "morgan", + "gordan", + "mervin", + "aidan", + "peadar", + "tony", + "reginald", + "connell", + "craig", + "mel", + "donough", + "darryl", + "rolf", + "richard", + "augustine", + "sebastian", + "gearoid", + "liam", + "jeremy", + "florence", + "thomas", + "tomas", + "cormack", + "derick", + "cornelius", + "nicholas", + "brian", + "darrell", + "conan", + "alan", + "michael", + "patrick", + "karl", + "roger", + "kenneth", + "colin", + "anthony", + "nigel", + "donal", + "conn", + "maurice", + "eugene", + "cathal", + "arnold", + "fergal", + "terence", + "ashley", + "damian", + "derek", + "gavin", + "hubert", + "benedict", + "carl", + "shane", + "alexander", + "garry", + "ian", + "conor", + "fergus", + "finian", + "jason", + "geoffrey", + "andreas", + "fiachra", + "fintan", + "padraic", + "stephen", + "clifford", + "duncan", + "ruairi", + "denis", + "cian", + "oisin", + "kirk", + "russell", + "jack", + "laurence", + "eamon", + "enda", + "leo", + "troy", + "garvan", + "paul", + "aongus", + "dereck", + "stuart", + "eanna", + "jermiah", + "gordon", + "philip", + "bartholomew", + "clinton", + "aiden", + "eric", + "steven", + "norman", + "connor", + "peader", + "kiaran", + "harold", + "adrian", + "david", + "derrick", + "seosamh", + "pearse", + "arthur", + "pascal", + "micheal", + "sean", + "michel", + "lorcan", + "ivor", + "aaron", + "ivan", + "neil", + "allen", + "conal", + "dominic", + "diarmaid", + "damien", + "billy", + "victor", + "rodney", + "timothy", + "leonard", + "wesley", + "graham", + "andrew", + "brien", + "canice", + "jim", + "lee", + "pauric", + "darin", + "coleman", + "rossa", + "trevor", + "rory", + "jeffrey", + "ralph", + "antonio", + "leslie", + "seamus", + "willie", + "neill", + "manus", + "rodger", + "gabriel", + "carlos", + "senan", + "eoin", + "ernest", + "feargal", + "douglas", + "alistair", + "kieron", + "naoise", + "don", + "conall", + "sheamus", + "daren", + "allan", + "garret", + "donncha", + "niall", + "marcus", + "kevin", + "cecil", + "william", + "garreth", + "gerald", + "barry", + "martin", + "roderick", + "sylvester", + "edward", + "donnacha", + "frederick", + "phillip", + "clive", + "clement", + "malachy", + "ronald", + "robin", + "miceal", + "dominick", + "stanley", + "eamonn", + "samuel", + "gary", + "aengus", + "jerome", + "redmond", + "robert", + "melvin", + "ultan", + "colm", + "dean", + "gilbert", + "evan", + "danny", + "padraig", + "christopher", + "charles", + "edmond", + "francis", + "albert", + "jeremiah", + "declan", + "neal", + "glen", + "turlough", + "gregory" + ], + "PREFIX_FEMALE": [ + "dr", + "miss", + "ms", + "mrs" + ], + "PREFIX_MALE": [ + "dr", + "mr" + ], + "FIRST_NAME": [ + "shaun", + "raymond", + "justin", + "adeline", + "jarlath", + "stephanie", + "garrett", + "kilian", + "vivien", + "hannah", + "priscilla", + "genevieve", + "natasha", + "zoe", + "janet", + "fionnuala", + "benjamin", + "antonia", + "thaddeus", + "claudine", + "daire", + "tadhg", + "caoimhe", + "peter", + "maighread", + "karin", + "glenda", + "dana", + "ailbhe", + "dearbhla", + "hugh", + "winifred", + "edwin", + "donna", + "maria", + "lynn", + "lavinia", + "jude", + "leigh", + "maxine", + "mathew", + "annette", + "marian", + "ailish", + "finbarr", + "alphonsus", + "arlene", + "dolores", + "heather", + "sandra", + "isobel", + "daragh", + "philomena", + "nial", + "ross", + "ingrid", + "janine", + "joan", + "helena", + "ciaran", + "gareth", + "tonya", + "ethna", + "jarleth", + "anne", + "dermott", + "gwendoline", + "eithne", + "henry", + "eva", + "luke", + "finbar", + "loyola", + "vincent", + "wendy", + "howard", + "moira", + "darrin", + "hazel", + "bronwen", + "jean", + "dermot", + "james", + "edmund", + "virginia", + "michele", + "michell", + "gerard", + "antoinette", + "marina", + "darran", + "eunice", + "darina", + "davnet", + "zita", + "bernard", + "thelma", + "leonie", + "killian", + "trina", + "loraine", + "cait", + "jocelyn", + "charlotte", + "gabrielle", + "andrea", + "wayne", + "mortimer", + "brona", + "esther", + "yolanda", + "mac", + "valerie", + "roy", + "grania", + "vanessa", + "austin", + "madeline", + "cheryl", + "rhonda", + "erica", + "owen", + "gertrude", + "bernadine", + "josephine", + "nina", + "collette", + "valentine", + "eleanor", + "cyril", + "michelle", + "julia", + "caroline", + "ita", + "phyllis", + "michaela", + "erika", + "noeleen", + "katharine", + "derval", + "pierce", + "neasa", + "neville", + "siobain", + "raphael", + "adam", + "gloria", + "siobhan", + "violet", + "helan", + "simon", + "freda", + "justine", + "yvette", + "liza", + "davida", + "alfred", + "jacinta", + "christine", + "dara", + "breeda", + "desmond", + "angus", + "ellen", + "sioban", + "fiona", + "andre", + "therese", + "alice", + "leone", + "ray", + "orlaith", + "conleth", + "karan", + "ronan", + "joanne", + "phelim", + "garech", + "jacqueline", + "fearghal", + "norah", + "stewart", + "catherina", + "columba", + "frank", + "cathriona", + "judy", + "paula", + "rowan", + "marion", + "bruce", + "patricia", + "celine", + "samantha", + "mervyn", + "fionan", + "juliette", + "alicia", + "donagh", + "elizabeth", + "rosarie", + "colette", + "cillian", + "natalie", + "lillian", + "bartley", + "flannan", + "lara", + "susan", + "elaine", + "marlene", + "shona", + "kieran", + "emmett", + "nicola", + "matthew", + "anastasia", + "belinda", + "marc", + "carina", + "beverley", + "sonia", + "olga", + "janice", + "camilla", + "dennis", + "gerrard", + "cora", + "rebecca", + "mairin", + "sonya", + "elva", + "clodagh", + "camillus", + "jonathan", + "briget", + "noirin", + "stella", + "hillary", + "alexandra", + "miranda", + "darren", + "gail", + "danielle", + "gillian", + "bryan", + "daniel", + "keith", + "steve", + "jacintha", + "darragh", + "nessa", + "myles", + "ambrose", + "sophie", + "ide", + "petrina", + "dervla", + "rowena", + "noeline", + "muriel", + "loretto", + "lucinda", + "scott", + "julianna", + "lilian", + "donald", + "toni", + "kiernan", + "dymphna", + "marguerite", + "angeline", + "martina", + "anastatia", + "emmet", + "colum", + "fabian", + "katrina", + "warren", + "jennifer", + "victoria", + "amber", + "joyce", + "noel", + "domhnall", + "jesse", + "rachel", + "muireann", + "walter", + "oliver", + "sheela", + "john", + "spencer", + "alexis", + "davin", + "brendan", + "lisa", + "felicity", + "laura", + "catherine", + "maire", + "jill", + "herbert", + "julian", + "cathleen", + "george", + "june", + "padraigh", + "gavan", + "susanne", + "colman", + "diarmuid", + "norma", + "glenn", + "louis", + "julie", + "paschal", + "denise", + "breffni", + "vivian", + "dianne", + "olive", + "lawrence", + "mark", + "joseph", + "basil", + "eoghan", + "rosanne", + "noelle", + "ella", + "cormac", + "guy", + "malcolm", + "christian", + "mairead", + "morgan", + "samanta", + "gordan", + "mervin", + "daphne", + "aidan", + "gerardine", + "peadar", + "sophia", + "tony", + "sile", + "shauna", + "jillian", + "aideen", + "deborah", + "deborrah", + "rhona", + "reginald", + "jayne", + "connell", + "treacy", + "craig", + "leona", + "tania", + "rena", + "eavan", + "cathrina", + "clair", + "mel", + "dona", + "matilda", + "donough", + "rita", + "grainne", + "bridie", + "loretta", + "mary", + "leonora", + "maeve", + "elena", + "darryl", + "rolf", + "clare", + "richard", + "cara", + "augustine", + "sebastian", + "saundra", + "gearoid", + "caitriona", + "katharina", + "brid", + "margaret", + "delia", + "treasa", + "marianne", + "dympna", + "liam", + "gretta", + "ciara", + "jeremy", + "katherine", + "bronwyn", + "florence", + "bronagh", + "annie", + "serena", + "thomas", + "bairbre", + "gwendolen", + "vera", + "tomas", + "cormack", + "derick", + "cornelius", + "nicholas", + "brian", + "darrell", + "cathy", + "lucia", + "melanie", + "christina", + "sheena", + "eileen", + "kerry", + "katriona", + "conan", + "alan", + "nichola", + "michael", + "gemma", + "patrick", + "diann", + "monica", + "henrietta", + "karl", + "rosaleen", + "roger", + "kenneth", + "evelyn", + "emer", + "sara", + "naimh", + "colin", + "anthony", + "nigel", + "tracey", + "lorraine", + "amy", + "donal", + "conn", + "marese", + "pearl", + "maurice", + "eugene", + "cathal", + "arnold", + "cliona", + "corinna", + "sylvia", + "fergal", + "terence", + "ashley", + "olivia", + "damian", + "aedin", + "aileen", + "derek", + "sorcha", + "gavin", + "rosemary", + "niamh", + "rosemarie", + "hubert", + "benedict", + "una", + "carl", + "shane", + "kathryn", + "carmel", + "alexander", + "averil", + "mandy", + "olwen", + "garry", + "gina", + "ian", + "conor", + "anna", + "juliet", + "fergus", + "finian", + "jason", + "sheelagh", + "aishling", + "geoffrey", + "juanita", + "andreas", + "fiachra", + "orla", + "tracy", + "fintan", + "padraic", + "imelda", + "stephen", + "clifford", + "duncan", + "lynne", + "adele", + "shirley", + "ruairi", + "carla", + "carolyn", + "ethel", + "denis", + "jenifer", + "janette", + "cian", + "charmaine", + "sally", + "shiela", + "rosa", + "hanora", + "oisin", + "geraldine", + "orna", + "kirk", + "russell", + "ruth", + "angela", + "jack", + "linda", + "rosanna", + "dervilla", + "carmen", + "laurence", + "fionna", + "helen", + "edwina", + "eamon", + "enda", + "kathleen", + "diane", + "leo", + "celina", + "jeanne", + "troy", + "moya", + "garvan", + "paul", + "amelia", + "aongus", + "ursula", + "dereck", + "stuart", + "eanna", + "jermiah", + "gordon", + "sarah", + "cynthia", + "theresa", + "johanna", + "philip", + "joy", + "bartholomew", + "clinton", + "marcella", + "lucy", + "aiden", + "doreen", + "pamela", + "joanna", + "aoife", + "eric", + "steven", + "eimear", + "claire", + "brigid", + "mona", + "norman", + "connor", + "noleen", + "irene", + "dawn", + "deirdre", + "peader", + "kiaran", + "emma", + "harold", + "adrian", + "naomh", + "derrick", + "david", + "debbie", + "judith", + "iris", + "eveline", + "seosamh", + "pearse", + "arthur", + "regina", + "nadine", + "ashling", + "pascal", + "nuala", + "micheal", + "lynda", + "sean", + "michel", + "attracta", + "tara", + "tina", + "lorcan", + "alva", + "aaron", + "ivor", + "alma", + "ailis", + "neil", + "allen", + "ivan", + "conal", + "sheila", + "deidre", + "abina", + "dominic", + "nancy", + "diarmaid", + "martha", + "avril", + "eilis", + "monique", + "damien", + "audrey", + "billy", + "victor", + "aisling", + "shinead", + "penelope", + "rodney", + "fidelma", + "grace", + "leonard", + "edel", + "finola", + "timothy", + "brenda", + "estelle", + "wesley", + "graham", + "breda", + "andrew", + "brien", + "bernice", + "canice", + "jim", + "ann", + "catheriona", + "emily", + "ethne", + "concepta", + "lee", + "brighid", + "katherina", + "marie", + "lorna", + "melinda", + "cliodhna", + "pauric", + "tanya", + "blathnaid", + "alison", + "darin", + "nicole", + "coleman", + "naomi", + "rossa", + "gwen", + "trevor", + "rory", + "jeffrey", + "marilyn", + "helga", + "ralph", + "antonio", + "leslie", + "seamus", + "diana", + "inez", + "willie", + "neill", + "roisin", + "eimer", + "celia", + "manus", + "veronica", + "marjorie", + "rodger", + "gabriel", + "oonagh", + "carlos", + "kim", + "noreen", + "susanna", + "rachael", + "catriona", + "senan", + "anita", + "eoin", + "ernest", + "maura", + "rose", + "feargal", + "sinead", + "karina", + "douglas", + "alistair", + "majella", + "kieron", + "heidi", + "siobhain", + "naoise", + "don", + "maureen", + "conall", + "fionnula", + "jeannette", + "roberta", + "sheamus", + "barbara", + "honora", + "agnes", + "simone", + "eilish", + "lena", + "aine", + "assumpta", + "paulette", + "nora", + "rosario", + "daren", + "debra", + "allan", + "garret", + "lesley", + "isabel", + "donncha", + "jeanette", + "niall", + "cathrine", + "ida", + "roslyn", + "marcus", + "kevin", + "cecil", + "cecelia", + "claudia", + "william", + "jessica", + "angelina", + "leah", + "garreth", + "vivienne", + "gerald", + "barry", + "martin", + "adrienne", + "bridget", + "roderick", + "sylvester", + "edward", + "donnacha", + "hilda", + "frederick", + "teresa", + "phillip", + "clive", + "jane", + "breege", + "clement", + "april", + "dearbhail", + "malachy", + "ronald", + "sharon", + "celene", + "johanne", + "amanda", + "miceal", + "robin", + "dorothy", + "georgina", + "dominick", + "stanley", + "melissa", + "eamonn", + "samuel", + "rona", + "gary", + "aengus", + "eve", + "jerome", + "harriet", + "redmond", + "frances", + "yvonne", + "triona", + "suzanne", + "allison", + "bernadette", + "dora", + "robert", + "melvin", + "cecilia", + "ultan", + "kara", + "colm", + "pauline", + "dean", + "gilbert", + "evan", + "danny", + "padraig", + "christopher", + "karen", + "miriam", + "louise", + "corona", + "hilary", + "charles", + "kate", + "edith", + "myra", + "edmond", + "nollaig", + "andrena", + "francis", + "colleen", + "albert", + "jeremiah", + "declan", + "neal", + "beatrice", + "carol", + "clara", + "glen", + "adrianne", + "carole", + "turlough", + "gregory" + ], + "LAST_NAME": [ + "mac_gaoith", + "mac_neacail", + "\u00f3_donnghusa", + "\u00f3_hualla", + "\u00f3_hainligh", + "\u00f3_doirn\u00edn", + "\u00f3_guith\u00edn", + "\u00f3_laidhigh", + "mac_guidhir", + "mac_giolla_\u00edosa", + "giob\u00fan", + "\u00f3_beaglaoich", + "\u00f3_han\u00e1in", + "\u00f3_monach\u00e1in", + "\u00f3_conar\u00e1in", + "\u00f3_h\u00e1g\u00e1in", + "\u00f3_flathartaigh", + "criomhthain", + "\u00f3_heireamh\u00f3in", + "\u00f3_hannrach\u00e1in", + "\u00f3_rabhartaigh", + "\u00f3_d\u00fag\u00e1in", + "mac_cuille\u00e1in", + "\u00f3_c\u00e9idigh", + "bair\u00e9ad", + "mac_an_phearsain", + "\u00f3_c\u00edobh\u00e1in", + "droma", + "mac_rath", + "mac_c\u00e1rthaigh", + "scribh\u00edn", + "\u00f3_h\u00e9in\u00ed", + "\u00f3_mainn\u00edn", + "\u00f3_luinigh", + "\u00f3_hartag\u00e1in", + "callahan", + "\u00f3_colla", + "mac_giolla_an_\u00e1tha", + "mac_seafraigh", + "mac_eochaidh", + "\u00f3_conmhach\u00e1in", + "\u00f3_moithide", + "\u00f3_biaidh", + "mac_g\u00edontaigh", + "\u00f3_laoidhe", + "\u00f3_me\u00e1raidh", + "mac_carra", + "\u00f3_ci\u00fart\u00e1in", + "cuirt\u00e9is", + "\u00f3_caoth\u00e1in", + "\u00f3_duinnshl\u00e9", + "mac_pharthol\u00e1in", + "\u00f3_maoilmhiadhaigh", + "\u00f3_leathaigh", + "\u00f3_biorainn", + "\u00f3_c\u00e1rthaigh", + "\u00f3_duibh\u00ednn", + "\u00f3_glas\u00e1in", + "\u00f3_hailp\u00edn", + "mac_\u00f3g\u00e1in", + "\u00f3_ceoth\u00e1naigh", + "\u00f3_creag\u00e1in", + "\u00f3_hainion", + "\u00f3_m\u00f3r\u00e1in", + "\u00f3_fuallaigh", + "\u00f3_cinn\u00e9ide", + "mac_tom\u00e1is", + "\u00f3_h\u00e9anaigh", + "\u00f3_h\u00e9alaithe", + "\u00f3_mil\u00e9adha", + "mac_rod\u00e1in", + "\u00f3_c\u00e9adaigh", + "mac_maonagail", + "\u00f3_c\u00fand\u00fain", + "\u00f3_caoch\u00e1in", + "diol\u00fan", + "\u00f3_muircheartaigh", + "\u00f3_sosn\u00e1in", + "caimbeul", + "\u00f3_haonghusa", + "mac_an_adhastair", + "cormican", + "d\u00e1ibh\u00eds", + "\u00f3_h\u00e1il\u00edosa", + "gine\u00e1", + "\u00f3_heimhr\u00edn", + "mac_dhiarmada", + "\u00f3_lochn\u00e1in", + "\u00f3_h\u00f3ghartaigh", + "\u00f3_maoil\u00e9adaigh", + "\u00f3_stiof\u00e1in", + "\u00f3_m\u00f3ir\u00edn", + "\u00f3_heallaigh", + "\u00f3_mionach\u00e1in", + "\u00f3_coisteala", + "piog\u00f3id", + "mac_caitig\u00edn", + "mac_siacais", + "\u00f3_luaire", + "\u00f3_cios\u00e1in", + "mac_maongail", + "\u00f3_mull\u00e1in", + "\u00f3_sion\u00e1in", + "\u00f3_fiodhabhra", + "\u00f3_hiceadha", + "\u00f3_frighil", + "de_fr\u00e9in", + "\u00f3_donnag\u00e1in", + "mac_se\u00e1in", + "criost\u00f3ir", + "\u00f3_maoildhia", + "mac_giolla_mh\u00e1rtain", + "mac_l\u00e9anach\u00e1in", + "mac_fhual\u00e1in", + "de_ge\u00e1rd", + "\u00f3_heachthigheirn", + "\u00f3_suibhne", + "\u00f3_dr\u00f3ch\u00e1in", + "mac_cuag", + "\u00f3_rallaigh", + "\u00f3_gallchobhair", + "\u00f3_maolalaidh", + "\u00f3_haitheasa", + "d\u00e9iseach", + "\u00f3_h\u00e9amhthaigh", + "\u00f3_marcach\u00e1in", + "\u00f3_maolfh\u00e1bhaill", + "\u00f3_huaithne", + "mac_cathasaigh", + "\u00f3_dubhg\u00e1in", + "mac_guibhir", + "mac_conn\u00e1in", + "feirt\u00e9ar", + "\u00f3_cinnseam\u00e1in", + "d\u00edsc\u00edn", + "\u00f3_cr\u00e1bh\u00e1in", + "\u00f3_broin", + "de_bhaldraithe", + "\u00f3_gath\u00e1in", + "mac_oilifir", + "\u00f3_loinnsgigh", + "mac_gabhann", + "breasail", + "\u00f3_fionnachtaigh", + "mac_sheitric", + "mac_conallta", + "de_breit", + "mac_an_le\u00e1gha", + "\u00f3_m\u00edon\u00e1in", + "mac_conluain", + "mac_oireachtaigh", + "\u00f3_bia", + "g\u00e9aran", + "\u00f3_ceoin\u00edn", + "turraoin", + "mac_eoch\u00e1in", + "mac_fhionntaigh", + "\u00f3_floinn", + "\u00f3_fuada", + "\u00f3_curr\u00e1in", + "\u00f3_loingse", + "\u00f3_conall\u00e1in", + "\u00f3_madag\u00e1in", + "\u00f3_fuaruisce", + "mac_an_bhioc\u00e1ire", + "\u00f3_haoidhne", + "mac_dhuibhir", + "\u00f3_cr\u00f3nallaigh", + "mac_amhlaoigh", + "\u00f3_bann\u00e1in", + "\u00f3_deag\u00e1naigh", + "\u00f3_b\u00e9ice", + "\u00f3_heifearn\u00e1in", + "carmaig", + "\u00f3_cuire\u00e1in", + "\u00f3_gramhna", + "\u00f3_hailgheasa", + "mac_cuinneag\u00e1in", + "t\u00e1illi\u00fair", + "mac_comn\u00ed", + "\u00f3_fiannaigh", + "\u00f3_comhghain", + "\u00f3_m\u00edodhach\u00e1in", + "\u00f3_tuairisc", + "\u00f3_fiannachtaigh", + "\u00f3_flaithbheartaigh", + "\u00f3_lup\u00e1in", + "\u00f3_duille\u00e1in", + "mac_coineoil", + "\u00f3_s\u00edoda", + "\u00f3_moch\u00f3irghe", + "\u00f3_nian\u00e1in", + "coinn\u00edn", + "mac_giolla_bhaird", + "\u00f3_dubhchain", + "\u00f3_dolainn", + "mac_giolla_gheimhridh", + "bodhlaer", + "\u00f3_sl\u00e9ibh\u00edn", + "\u00f3_conmha\u00eddhe", + "\u00f3_cairbre", + "mac_aodhchain", + "\u00f3_connach\u00e1in", + "\u00f3_fatha", + "\u00f3_dearmada", + "loibh\u00e9ad", + "\u00f3_siochfhradha", + "\u00f3_finneachta", + "\u00f3_deor\u00e1in", + "\u00f3_muighe", + "\u00f3_d\u00farch\u00e1in", + "\u00f3_con\u00f3il", + "\u00f3_craidhe\u00e1in", + "\u00f3_d\u00fara\u00ed", + "mac_an_abbadh", + "\u00f3_cl\u00e9irigh", + "\u00f3broin\u00edn", + "mac_mbriartaigh", + "\u00f3_f\u00e1g\u00e1in", + "mac_ph\u00e1rtol\u00e1in", + "\u00f3_tuama", + "\u00f3_f\u00f3r\u00e1in", + "mac_confraoich", + "\u00f3_holl\u00fain", + "mac_coluim", + "budhlaeir", + "criost\u00fair", + "a_tsithigh", + "raifteir\u00ed", + "\u00f3_m\u00edoch\u00e1in", + "mist\u00e9al", + "\u00f3_cuinnle\u00e1in", + "ceafarcaigh", + "\u00f3_cumhail", + "\u00f3_brad\u00e1in", + "mac_hugo", + "\u00f3_coil\u00e9ir", + "\u00f3_cuarn\u00e1in", + "\u00f3_cinnseala", + "\u00f3_donnabh\u00e1in", + "mac_an_\u00e9anaigh", + "\u00f3_seighin", + "mac_cail\u00edn", + "\u00f3_hannag\u00e1in", + "\u00f3_maolriain", + "mac_ceanndubh\u00e1in", + "laighnigh", + "\u00f3_d\u00fanadhaighe", + "\u00f3_caola", + "\u00f3_fearach\u00e1in", + "doingeard", + "mac_fhionnachta", + "lochlann", + "\u00f3_speal\u00e1in", + "\u00f3_corrdhuibh", + "\u00f3_meitheag\u00e1in", + "\u00f3_hiol\u00e1in", + "\u00f3_moth\u00e1in", + "\u00f3_conbhaigh", + "mac_fhaol\u00e1in", + "\u00f3_fighead\u00f3ra", + "\u00f3_cuan\u00e1in", + "mac_cosgair", + "mac_iomaire", + "\u00f3_ciardhubh\u00e1in", + "\u00f3_sl\u00e1m\u00e1in", + "\u00f3_caobh\u00e1in", + "\u00f3_maolruanaigh", + "\u00f3_h\u00e9anach\u00e1in", + "\u00f3_n\u00e1radhaigh", + "\u00f3_cadhain", + "\u00f3_lamhna", + "mac_thorcail", + "\u00f3_ruairc", + "\u00f3_raghaille", + "\u00f3_scollaigh", + "de_lonndra", + "\u00f3_luasaigh", + "\u00f3_r\u00edoghbhard\u00e1in", + "mac_raghallaigh", + "\u00f3_smeal\u00e1in", + "mac_airligh", + "\u00f3_g\u00e1ineard", + "\u00f3_g\u00e1ibh\u00edn", + "\u00f3_conaola", + "\u00f3_c\u00e9ileachair", + "\u00f3_mearlaigh", + "mac_\u00e9il", + "peirc\u00edn", + "\u00f3_liadhain", + "\u00f3_mul\u00e1in", + "\u00f3_long\u00e1in", + "\u00f3_gall\u00e1in", + "\u00f3_tom\u00e1is", + "\u00f3_dabhoireann", + "\u00f3_math\u00fana", + "mac_an_ghoill", + "airmeas", + "mac_uiginn", + "\u00f3_m\u00f3rach\u00e1in", + "l\u00e1sa", + "mac_confhaola", + "\u00f3_d\u00edoch\u00e1in", + "coscair", + "\u00f3_grian\u00e1in", + "de_r\u00f3iste", + "mac_luain", + "\u00f3_connghamhna", + "\u00f3_seasn\u00e1in", + "mac_shamhr\u00e1in", + "\u00f3_fl\u00e1rta", + "searl\u00f3g", + "\u00f3_hairt", + "\u00f3_moghr\u00e1in", + "\u00f3_carbaire", + "a_b\u00farca", + "\u00f3_huirthille", + "\u00f3_h\u00fab\u00e1in", + "\u00f3_longaigh", + "\u00f3_ceannabh\u00e1in", + "\u00f3_d\u00e1ibhis", + "\u00f3_scola\u00ed", + "\u00f3_caln\u00e1in", + "\u00f3_tiarnaigh", + "glionn\u00e1in", + "\u00f3_c\u00e1pa", + "\u00f3_h\u00f3dhr\u00e1in", + "\u00f3_cathl\u00e1in", + "\u00f3_m\u00edodhch\u00e1in", + "stac", + "\u00f3_hainmneach", + "\u00f3_cr\u00edog\u00e1in", + "mac_tamhais", + "\u00f3_duinn", + "\u00f3_h\u00e9ighnigh", + "\u00f3_ciar\u00e1in", + "mac_giolla_dhuinn", + "mac_giolla_rua", + "\u00f3_gloinn", + "\u00f3_ceamharcaigh", + "mac_giolla_chaoin", + "\u00f3_lailligh", + "\u00f3_bruach\u00e1in", + "\u00f3_gaill\u00edn", + "de_h\u00f3r", + "\u00f3_tiomanaigh", + "\u00f3_maoileag\u00e1in", + "\u00f3_fallamh\u00e1in", + "\u00f3_conthra", + "\u00f3_n\u00e1raigh", + "\u00f3_maolchaoine", + "\u00f3_seitheach\u00e1in", + "mac_an_bheatha", + "\u00f3_huaithn\u00edn", + "\u00f3_murchaidhe", + "\u00f3_muinneach\u00e1in", + "\u00f3_collaigh", + "\u00f3_ruaidh\u00edn", + "\u00f3_confhaola", + "\u00f3_giobl\u00e1in", + "\u00f3_coirn\u00edn", + "\u00f3_smol\u00e1in", + "mac_uait\u00e9ir", + "mac_glionn\u00e1in", + "mac_cobhthaigh", + "mac_caoidhe\u00e1in", + "\u00f3_muimhneach\u00e1in", + "\u00f3_c\u00e1d\u00e1in", + "\u00f3_caoidhe\u00e1in", + "mac_giolla_riabhaigh", + "\u00f3_biasta", + "\u00f3_dubh\u00e1in", + "\u00f3_hurmholtaigh", + "mac_thuathail", + "\u00f3_raighill", + "cr\u00f3il", + "mac_c\u00e9ide", + "mac_tuile", + "c\u00e9ide", + "\u00f3_dear\u00e1in", + "\u00f3_rodaigh", + "fearraigh", + "\u00f3_cr\u00f3in\u00edn", + "de_faoite", + "\u00f3_fionn\u00e1in", + "de_geard", + "de_nais", + "\u00f3_corcora", + "\u00f3_niallghuis", + "\u00f3_duibhealla", + "mac_an_ultaigh", + "mac_connghamhna", + "\u00f3_connacht\u00e1in", + "mac_osgair", + "r\u00e9amonn", + "\u00f3_hanluain", + "de_bhosc", + "\u00f3_breasail", + "\u00f3_haic\u00e9ad", + "mac_aodhchaoin", + "\u00f3_hainch\u00edn", + "\u00f3_scolaighe", + "mac_coill\u00edn", + "\u00f3_coitir", + "\u00f3_flaithearta", + "\u00f3_callan\u00e1in", + "mac_amhlaoimh", + "\u00f3_riain", + "\u00f3_cl\u00fain", + "\u00f3_hairtn\u00e9ada", + "m\u00e1rtan", + "\u00f3_f\u00edonartaigh", + "\u00f3_beigg", + "\u00f3_reachtabhair", + "\u00f3_cart\u00e1in", + "\u00f3_h\u00e9aghr\u00e1in", + "\u00f3_me\u00e1dhra", + "\u00f3_maoilchiar\u00e1in", + "\u00f3_donnchaidh", + "\u00f3_dr\u00f3naidhe", + "de_bh\u00e1l", + "\u00f3_h\u00e9imh\u00edn", + "\u00f3_h\u00e9idhni\u00fa", + "briain", + "mac_thuathal\u00e1in", + "\u00f3_c\u00f3mair", + "de_b\u00farca", + "mac_dhonnchaidh", + "\u00f3_corra", + "\u00f3_loirgne\u00e1in", + "\u00f3_gl\u00e1imh\u00edn", + "\u00f3_treasaigh", + "ail\u00edn", + "mac_fhionnlaich", + "\u00f3_cuinneach\u00e1in", + "mac_giolla_ghailing", + "mac_raith", + "\u00f3_ciarmhaic", + "mac_an_bhaird", + "\u00f3_murae", + "\u00f3_caitig\u00edn", + "\u00f3_faircheallaigh", + "blowick", + "mac_giolla", + "cuidithe", + "mac_conghamhna", + "\u00f3_conbh\u00e1", + "\u00f3_madaoin", + "mac_g\u00e9idigh", + "conrach", + "mac_cochl\u00e1in", + "\u00f3_claimh\u00edn", + "mac_cionnaith", + "mac_na_midhe", + "\u00f3_m\u00e1irt\u00edn", + "\u00f3_cuanaigh", + "\u00f3_g\u00e1ibhtheach\u00e1in", + "\u00f3_harc\u00e1in", + "\u00f3_siochr\u00fa", + "mac_giolla_dhuibh", + "mac_cumhail", + "mac_lughbhadha", + "\u00f3_leallaigh", + "\u00f3_haibheartaigh", + "mac_thoirdhealbhaigh", + "\u00f3_coin\u00edn", + "\u00f3_car\u00fain", + "\u00f3_dubhuidhe", + "habha", + "\u00f3_raithbheartaigh", + "\u00f3_maoiliadh", + "\u00f3_mian\u00e1in", + "mac_gloin", + "\u00f3_ruaidhinn", + "\u00f3_hairmheasaigh", + "\u00f3_heichthigheirn", + "stond\u00fan", + "\u00f3_mear\u00e1in", + "mac_dhuibh", + "mac_ceamharcaigh", + "\u00f3_daibhidh", + "mac_a_d\u00e9ise", + "\u00f3_duibhlearga", + "\u00f3_ceannfhaola", + "\u00f3_connmhaigh", + "\u00f3_baoill", + "\u00f3_maoilshearcaigh", + "\u00f3_donghaile", + "\u00f3_me\u00e1dhra\u00ed", + "mac_ail\u00edn", + "\u00f3_cr\u00f3nghaile", + "\u00f3_c\u00edos\u00f3ig", + "\u00f3_ceiri\u00fach\u00e1in", + "\u00f3_dubhlainn", + "\u00f3_muineach\u00e1in", + "mac_cn\u00e1imh\u00edn", + "\u00f3_carra", + "\u00f3_maoilriain", + "d\u00fainsm\u00e9arach", + "\u00f3_luain", + "\u00f3_tuile", + "\u00f3_fearghaile", + "mac_an_tsaoir", + "\u00f3_bog\u00e1in", + "\u00f3_gionn\u00e1in", + "mac_an_ghirr", + "\u00f3_cuill", + "\u00f3_tuachair", + "mac_calbhaigh", + "mac_conn\u00f3il", + "\u00f3_corrghamhna", + "tr\u00e9infhear", + "\u00f3_cianaigh", + "\u00f3_muirgheasa", + "de_grae", + "b\u00e1caer", + "\u00f3_muar\u00e1in", + "\u00f3_cuana", + "mac_n\u00e9ill", + "mac_giolla_iasachta", + "\u00f3_dubhd\u00e1bhoireann", + "\u00f3_mannt\u00e1in", + "\u00f3_simeoin", + "\u00f3_brian\u00e1in", + "\u00f3_duibhghealla", + "mac_bhait\u00e9ir", + "\u00f3_grallaigh", + "\u00f3_m\u00e9al\u00f3id", + "\u00f3_ruadh\u00e1in", + "baisceir", + "\u00f3_ruach\u00e1in", + "mac_airt", + "b\u00e9ataigh", + "mac_cais\u00edn", + "de_si\u00fan", + "\u00f3_diarmada", + "\u00f3_hail\u00edn", + "mac_fhionnachtaigh", + "mac_p\u00e1id\u00edn", + "\u00f3_taichligh", + "a_b\u00farc", + "mac_h\u00e9il", + "\u00f3_muimhnigh", + "mac_giolla_mh\u00f3ir", + "\u00f3_c\u00e9r\u00fac\u00e1in", + "\u00f3_l\u00e1mh\u00e1in", + "\u00f3_maoldomhnaigh", + "\u00f3_griallais", + "\u00f3_caiside", + "\u00f3_h\u00edghne", + "\u00f3_coitirigh", + "\u00f3_lighe", + "\u00f3_f\u00e9inneadha", + "\u00f3_capuaigh", + "\u00f3_maoileanaigh", + "mac_seanlaoich", + "\u00f3_conbha\u00ed", + "mac_curt\u00e1in", + "\u00f3_coighin", + "\u00f3_tuathail", + "\u00f3_heithchir", + "\u00f3_lideadha", + "\u00f3_harrag\u00e1in", + "\u00f3_cosgair", + "\u00f3_mug\u00e1in", + "mac_clochartaigh", + "\u00f3_flannghaile", + "\u00f3_duinn\u00edn", + "\u00f3_craobh\u00e1in", + "\u00f3_flanag\u00e1in", + "\u00f3_hoile\u00e1in", + "mac_stibhin", + "burnach", + "\u00f3_cr\u00e1ibh\u00edn", + "mac_s\u00e9amuis", + "\u00f3_scalaidhe", + "\u00f3_hoirbheaird", + "meidhreach", + "mac_cruit\u00edn", + "mac_an_iarla", + "\u00f3_ruaidhr\u00ed", + "mac_allmh\u00far\u00e1in", + "\u00f3_slatara", + "\u00f3_h\u00e1g\u00fartaigh", + "mac_an_r\u00edogh", + "mac_ceallaigh", + "mac_duibhir", + "\u00f3_hanrachtaigh", + "\u00f3_fionndhubhc\u00e1in", + "\u00f3_maoilia", + "mac_uidhlinn", + "\u00f3_gaibhtheach\u00e1in", + "\u00f3_cluan\u00e1in", + "\u00f3_maolruaidhe", + "\u00f3_hear\u00e1in", + "\u00f3_maolfh\u00e1bhail", + "de_bhial", + "\u00f3_meall\u00e1in", + "\u00f3_heag\u00e1in", + "\u00f3_nearaigh", + "\u00f3_flaitheamh\u00e1in", + "\u00f3_graith", + "mac_cearnaigh", + "mac_callan\u00e1in", + "\u00f3_lachtn\u00e1in", + "\u00f3_muirithe", + "\u00f3_pilb\u00edn", + "\u00f3_cr\u00e9ag\u00e1in", + "mac_eachaidh", + "mac_an_iascaire", + "\u00f3_flannchadha", + "\u00f3_conbhuaidh", + "\u00f3_loingseach\u00e1in", + "\u00f3_coincheanainn", + "\u00f3_ceannfhaolaidh", + "\u00f3_broic", + "\u00f3_mant\u00e1in", + "\u00f3_maoilige\u00e1in", + "\u00f3_clocharta", + "\u00f3_s\u00edor\u00e1in", + "\u00f3_tighearn\u00e1in", + "\u00f3_maoltuile", + "\u00f3_scannl\u00e1in", + "mac_coinneirtinne", + "\u00f3_br\u00e1daigh", + "\u00f3_cearbhall\u00e1in", + "\u00f3_hois\u00edn", + "\u00f3_h\u00e9igeartaigh", + "\u00f3_m\u00f3rdha", + "\u00f3_diolain", + "\u00f3_fearraigh", + "\u00f3_meirligh", + "\u00f3_hic\u00edn", + "\u00f3_criag\u00e1in", + "mac_cr\u00edod\u00e1in", + "mac_oitir", + "\u00f3_fathartaigh", + "\u00f3_leathlobhair", + "\u00f3_domhnaill", + "mac_aodhg\u00e1in", + "mac_craith", + "\u00f3_lonag\u00e1in", + "\u00f3_neachtain", + "\u00f3_guaire", + "\u00f3_ladhradha", + "mac_stiof\u00e1in", + "mac_ph\u00e1rthol\u00e1in", + "\u00f3_gibne", + "\u00f3_conb\u00e1", + "\u00f3_meardha", + "\u00f3_murthuile", + "\u00f3_laodh\u00f3g", + "mac_riag\u00e1in", + "mac_g\u00e9ibheannaigh", + "\u00f3_heifr\u00edn", + "\u00f3_cl\u00e9irch\u00edn", + "glost\u00e9ir", + "\u00f3_scannaill", + "mac_corra", + "conaola", + "\u00f3_goil\u00edn", + "\u00f3_donch\u00fa", + "de_gr\u00e1s", + "\u00f3_cl\u00famh\u00e1in", + "mac_maic\u00edn", + "mac_arta", + "\u00f3_d\u00e9isigh", + "\u00f3_manach\u00e1in", + "de_bhailis", + "tighe", + "\u00f3_l\u00f3rd\u00e1in", + "\u00f3_gr\u00e1da", + "kirwan", + "mac_m\u00e1ghnuis", + "\u00f3_conghaile", + "\u00f3_mog\u00e1in", + "\u00f3_sibhle\u00e1in", + "mac_ciar\u00e1in", + "\u00f3_hiarfhlaithe", + "\u00f3_beartlaigh", + "ainmneach", + "\u00f3_heibhr\u00edn", + "\u00f3_haodha", + "mac_coil\u00edn", + "mac_r\u00e1ighne", + "\u00f3_gabhl\u00e1in", + "\u00f3_gruag\u00e1in", + "mac_th\u00e1mhais", + "\u00f3_gloinne", + "\u00f3_cearbhl\u00e1in", + "\u00f3_raifearta", + "\u00f3_raithile", + "\u00f3_cionnaigh", + "\u00f3_fatharta", + "\u00f3_cathbhuaidh", + "mac_ruairc", + "\u00f3_caolla\u00ed", + "mac_br\u00e1daigh", + "mac_t\u00e1mhais", + "\u00f3_nuall\u00e1in", + "\u00f3_laide\u00e1in", + "\u00f3_deirg", + "mac_laithimh", + "\u00f3_c\u00fan\u00fain", + "\u00f3_maolchatha", + "mac_eachain", + "\u00f3_siard\u00e1in", + "\u00f3_scanl\u00e1in", + "\u00f3_leamhna", + "\u00f3_duibhgeannaigh", + "\u00f3_dunc\u00e1in", + "\u00f3_duibhthe", + "\u00f3_fathaigh", + "de_stac", + "mac_thom\u00e1is", + "\u00f3_cear\u00e1in", + "\u00f3_heaghra", + "\u00f3_seochr\u00fa", + "traoin", + "\u00f3_corraigh", + "\u00f3_murch\u00e1in", + "mac_dhuinnshl\u00e9ibhe", + "\u00f3_main\u00edn", + "\u00f3_ruadhch\u00e1in", + "\u00f3_cuinne\u00e1in", + "\u00f3_maolchathaigh", + "\u00f3_gr\u00e9il", + "mac_e\u00f3thach", + "\u00f3_siorad\u00e1in", + "\u00f3_tiarn\u00e1in", + "firt\u00e9ar", + "\u00f3_canainn", + "\u00f3_d\u00e1ibhidh", + "\u00f3_haithbheartaigh", + "\u00f3_brolch\u00e1in", + "\u00f3_coluim", + "\u00f3_cionnfhaola", + "\u00f3_corrag\u00e1in", + "\u00f3_hairmeasaigh", + "mac_coscair", + "\u00f3_flaithimh", + "\u00f3_m\u00f3in\u00edol", + "mac_ionrachtaigh", + "\u00f3_maoilc\u00e9ir", + "\u00f3_coinghiallaigh", + "\u00f3_seithneach\u00e1in", + "mac_giolla_cheara", + "\u00f3_scannail", + "\u00f3_r\u00edle", + "mac_gothraidh", + "\u00f3_laithimh", + "mac_each\u00e1in", + "mac_lochlainn", + "mac_congail", + "\u00f3_searcaigh", + "\u00f3_fionnghalaigh", + "\u00f3_riallaigh", + "\u00f3_hearchaidh", + "mac_reachtain", + "\u00f3_mathghamhna", + "\u00f3_meadhra", + "\u00f3_c\u00e9ir\u00edn", + "mac_giolla_ph\u00f3il", + "\u00f3_colm\u00e1in", + "\u00f3_muichille", + "de_h\u00f3ir", + "mac_ealanaidh", + "\u00f3_h\u00e1inle", + "ceanainn", + "\u00f3_gob\u00e1in", + "\u00f3_h\u00e9igheartaigh", + "\u00f3_dabhr\u00e1in", + "de_sp\u00e1in", + "mac_aidic\u00edn", + "\u00f3_diol\u00e1in", + "mac_lathaigh", + "mac_coinnich", + "\u00f3_c\u00e9adag\u00e1in", + "\u00f3_dulchaointigh", + "mac_gearailt", + "\u00f3_d\u00edghe", + "\u00f3_gearg\u00e1in", + "mac_\u00e1dhaimh", + "mac_giolla_l\u00e9ith", + "\u00f3_h\u00e9ineach\u00e1in", + "\u00f3_heoghan\u00e1in", + "\u00f3_gallch\u00f3ir", + "mac_gr\u00e1inne", + "\u00f3_gamhn\u00e1in", + "mac_fheargail", + "mac_searraigh", + "\u00f3_heachadha", + "\u00f3_niallag\u00e1in", + "mac_raghnaill", + "\u00f3_tonra", + "mac_coitir", + "mac_cormaic", + "mac_colla", + "mac_briartaigh", + "\u00f3_corrach\u00e1in", + "\u00f3_bhaldraithe", + "mac_fhlaithbheartaigh", + "\u00f3_gairbhighe", + "mac_c\u00failriabhaigh", + "\u00f3_h\u00e9idhn\u00ed", + "mac_an_aba", + "\u00f3_duibhleanna", + "\u00f3_heodhasa", + "\u00f3_coingh\u00edola", + "mac_cr\u00edon\u00e1in", + "mac_cinn\u00e9ide", + "\u00f3_coim\u00edn", + "\u00f3_gabh\u00e1in", + "mac_seoin", + "\u00f3_rothlainn", + "mac_laghmainn", + "mac_conmara", + "\u00f3_consaid\u00edn", + "\u00f3_s\u00failliobh\u00e1in", + "mac_an_d\u00e9isigh", + "mac_con\u00f3il", + "\u00f3_r\u00f3ch\u00e1in", + "\u00f3_cr\u00f3dhal", + "mac_alastroim", + "de_buadha", + "\u00f3_hallach\u00e1in", + "\u00f3_beirne", + "\u00f3_goillidhe", + "c\u00fand\u00fan", + "mac_cuirc", + "mac_fhearghusa", + "\u00f3_rathaile", + "mac_grianna", + "mac_conghaile", + "mac_cuinn", + "\u00f3_foghl\u00fadha", + "\u00f3_cuirre\u00e1in", + "\u00f3_maille", + "\u00f3_maolalla", + "duffy", + "de_priondrag\u00e1is", + "mac_mathghamhna", + "mac_an_tsagairt", + "\u00f3_h\u00e1inl\u00ed", + "\u00f3_c\u00f3g\u00e1in", + "\u00f3_finnthighearn", + "\u00e1ghas", + "\u00f3_horc\u00e1in", + "\u00f3_haithchir", + "mac_aonghusa", + "\u00f3_collata", + "\u00f3_sean\u00e1in", + "\u00f3_dorchaidh", + "\u00f3_bortach\u00e1in", + "\u00f3_muire\u00e1n", + "\u00f3_teangna\u00ed", + "\u00f3_capua", + "de_bl\u00e1ca", + "\u00f3_cath\u00e1in", + "\u00f3_daeid", + "mac_an_oireachtaigh", + "\u00f3_mugabh\u00e1in", + "\u00f3_fiaich", + "\u00f3_moch\u00e1in", + "\u00f3_hoibic\u00edn", + "\u00f3_heachairn", + "\u00f3_giollag\u00e1in", + "mac_giob\u00fain", + "\u00f3_cormac\u00e1in", + "\u00f3_ruana\u00ed", + "mac_cill\u00edn", + "\u00f3_connaigh", + "mac_ceallbhu\u00ed", + "\u00f3_tiobraide", + "\u00f3_heiteag\u00e1in", + "\u00f3_mag\u00e1in", + "\u00f3_praoidhe\u00e1il", + "\u00f3_moin\u00e9al", + "\u00f3_caochlaigh", + "\u00f3_coinne\u00e1in", + "mac_dh\u00e1ibhidh", + "stund\u00fan", + "\u00f3_maoileoin", + "\u00f3_clochasaigh", + "\u00f3_m\u00e1l\u00f3id", + "mac_dubhrad\u00e1in", + "mac_braon\u00e1in", + "mac_daeid", + "mac_fhinn", + "mac_laithbheartaigh", + "\u00f3_tuathlainn", + "\u00f3_halmhain", + "mac_giolla_chat\u00e1in", + "\u00f3_rabhlaigh", + "mac_curraidh", + "\u00f3_s\u00edthigh", + "\u00f3_f\u00f3garta", + "\u00f3_lubhaing", + "mac_ci\u00fart\u00e1in", + "stand\u00fan", + "mac_conaonaigh", + "\u00f3_maoil_mheana", + "\u00f3_coile\u00e1in", + "\u00f3_hic\u00f3g", + "\u00f3_maoilfheabhail", + "mac_cr\u00e1bh\u00e1in", + "\u00f3_horg\u00e1in", + "\u00f3_donnacha", + "dorcha", + "\u00f3_connmha\u00ed", + "\u00f3_connchamh\u00e1in", + "ceorais", + "\u00f3_huiginn", + "\u00f3_heanna", + "suip\u00e9al", + "\u00f3_haidhleart", + "c\u00fan\u00fan", + "\u00f3_heochaidh", + "\u00f3_h\u00e9alaigh", + "\u00f3_duibhir", + "\u00f3_s\u00edothch\u00e1in", + "\u00f3_haoilbheard", + "\u00f3_maolruana\u00ed", + "\u00f3_c\u00fairn\u00edn", + "\u00f3_gioll\u00e1in", + "\u00f3_mraoiligh", + "\u00f3_hiarn\u00e1in", + "\u00f3_rothallaigh", + "mac_thaidhg", + "\u00f3_gach\u00e1in", + "\u00f3_madaidh", + "\u00f3_huig\u00edn", + "\u00f3_ginne\u00e1", + "\u00f3_haoidhgin", + "\u00f3_duinneach\u00e1in", + "\u00f3_caoile", + "tre\u00f3igh", + "\u00f3_treasa", + "\u00f3_gean\u00e1in", + "bruis\u00e9al", + "\u00f3_criost\u00f3ir", + "\u00f3_fearra\u00ed", + "mac_fh\u00edontaigh", + "\u00f3_connmhach\u00e1in", + "\u00f3_muingh\u00edle", + "\u00f3_gr\u00edobhtha", + "\u00f3_cafraigh", + "mac_muiris", + "\u00f3_duinnl\u00e9i", + "carville", + "\u00f3_tarlaigh", + "mac_coim\u00edn", + "mac_dhuarc\u00e1in", + "\u00f3_coilige\u00e1in", + "mac_corrghamhna", + "\u00f3_laoingsigh", + "\u00f3_maoileoghain", + "\u00f3_faith", + "\u00f3_fraincl\u00edn", + "\u00f3_gabhach\u00e1in", + "bodaic\u00edn", + "\u00f3_creim\u00edn", + "c\u00e9itinn", + "\u00f3_bheach\u00e1in", + "\u00f3_duilearga", + "\u00f3_fearadhaigh", + "mac_giolla_eoin", + "mac_thr\u00e9infhir", + "\u00f3_corraidhin", + "\u00f3_lonarg\u00e1in", + "\u00f3_duarc\u00e1in", + "\u00f3_gr\u00edobhth\u00e1in", + "\u00f3_giollaruaidhe", + "mac_fhearghail", + "mac_fhion\u00e1in", + "\u00f3_reithil", + "bri\u00fatean", + "\u00f3_cabhail", + "mac_dhonnchadha", + "mac_an_ridire", + "mac_thighearn\u00e1in", + "ciothaigh", + "\u00f3_garbh\u00e1in", + "mac_canainn", + "searraigh", + "cheara", + "cart\u00far", + "mac_fhionnghaile", + "\u00f3_l\u00e1s", + "\u00f3_gioball\u00e1in", + "\u00f3_fearachair", + "\u00f3_ciarmhac\u00e1in", + "\u00f3_con\u00e1in", + "\u00f3_d\u00fan\u00e1in", + "mac_eochadha", + "\u00f3_muirthile", + "mac_uilc\u00edn", + "\u00f3_biataigh", + "\u00f3_ruadhainn", + "\u00f3_duibhgead\u00e1in", + "mac_gr\u00e9il", + "\u00f3_laimhbheartaigh", + "mac_an_iomaire", + "mac_con_ultaigh", + "\u00f3_cearbh\u00e1in", + "\u00f3_gr\u00e1inne", + "\u00f3_martain", + "\u00f3_conbhu\u00ed", + "mac_th\u00f3mais", + "mac_dhuinnshl\u00e9", + "mac_daibheid", + "\u00f3_coillte", + "\u00f3_seiread\u00e1in", + "mac_an_airchinnigh", + "mac_an_oirchinnigh", + "\u00f3_hearbhaird", + "mac_aog\u00e1in", + "\u00f3_br\u00f3g\u00e1in", + "\u00f3_b\u00e1in", + "pl\u00e9imionn", + "\u00f3_nuadhan", + "\u00f3_daoda", + "mac_connmhaigh", + "mac_dhorchaidh", + "\u00f3_siadhach\u00e1in", + "mac_cuidithe", + "mac_conle\u00e1gha", + "\u00f3_caoinigh", + "\u00f3_n\u00e9ill", + "\u00f3_holl\u00e1in", + "\u00f3_caobhac\u00e1in", + "mac_an_tsionnaigh", + "\u00f3_dubha", + "\u00f3_muadaigh", + "mac_giollaruaidhe", + "mac_ph\u00e1id\u00edn", + "\u00f3_maolruana", + "\u00f3_tuathaigh", + "\u00f3_beol\u00e1in", + "de_c\u00farsa", + "\u00f3_haonghuis", + "cond\u00fan", + "\u00f3_gealabh\u00e1in", + "mac_cuarta", + "\u00f3_fearghail", + "\u00f3_lallaidh", + "\u00f3_ceatharnaigh", + "\u00f3_me\u00e1ra", + "\u00f3_grealaigh", + "\u00f3_corraidh", + "\u00f3_raigne", + "\u00f3_greanach\u00e1in", + "mac_an_bhiadhtaigh", + "\u00f3_leighinn", + "mac_gr\u00e1dha", + "mac_thighearnaigh", + "\u00f3_danachair", + "\u00f3_d\u00e1laigh", + "\u00f3_maoil\u00edn", + "\u00f3_daola", + "\u00f3_donncha", + "mac_an_liagha", + "\u00f3_h\u00e9igcheartaigh", + "\u00f3_loingsigh", + "\u00f3_lainn", + "\u00f3_muirighthe", + "seitric", + "\u00f3_bl\u00e1thmhaic", + "mac_an_mhilidh", + "\u00f3_r\u00fa\u00e1in", + "\u00f3_sc\u00e9ach\u00e1in", + "\u00f3_ciarag\u00e1in", + "\u00f3_fiannaidhe", + "\u00f3_craith", + "mac_an_luain", + "mac_mhuircheartaigh", + "de_long", + "\u00f3_gr\u00e1laigh", + "achaorainn", + "\u00f3_hoireachtaigh", + "mac_eoin\u00edn", + "\u00f3_gairbh\u00edn", + "paor", + "\u00f3_murn\u00e1in", + "\u00f3_gabhann", + "bail\u00eds", + "\u00f3_d\u00falaigh", + "raghna", + "mac_giolla_bhu\u00ed", + "\u00f3_droma", + "mac_\u00edomhair", + "\u00f3_dochartaigh", + "mac_eitheag\u00e1in", + "mac_giolla_ghunna", + "mac_eochag\u00e1in", + "\u00f3_foghludha", + "\u00f3_flathamh\u00e1in", + "mac_gairbhe", + "\u00f3_mead\u00f3g", + "mac_fhearraigh", + "\u00f3_gorm\u00e1in", + "de_l\u00fandra", + "proinnsias", + "mac_dubhghaill", + "risteard", + "\u00f3_doibhilin", + "\u00f3_hiorbhaird", + "\u00f3_c\u00farn\u00e1in", + "\u00f3_conn\u00f3il", + "de_stond\u00fan", + "\u00f3_maolmhuaidh", + "\u00f3_giolla_rua", + "\u00f3_cuimil\u00edn", + "de_b\u00farc", + "breathnach", + "\u00f3_gilli\u00fain", + "\u00f3_seibhl\u00edn", + "\u00f3_cioltr\u00e1in", + "ginne\u00e1dha", + "\u00f3_loingscigh", + "mac_\u00e9nr\u00ed", + "mac_grianra", + "\u00f3_rachtag\u00e1in", + "\u00f3_r\u00e1inne", + "mac_art\u00e1in", + "\u00f3_gadhra", + "mac_cath\u00e1in", + "mac_meanman", + "\u00f3_feargha\u00edosa", + "mac_coin\u00edn", + "\u00f3_leidhin", + "\u00f3_coisdeala", + "\u00f3_sgulla", + "c\u00edos\u00f3g", + "maguidhir", + "m\u00e1irt\u00edn", + "mac_amhlaigh", + "\u00f3_clochartaigh", + "\u00f3_cr\u00edod\u00e1in", + "mac_aodh\u00e1in", + "mac_ceallabhu\u00ed", + "\u00f3_riada", + "\u00f3_r\u00f3n\u00e1in", + "\u00f3_hinneirghe", + "mac_calaigh", + "cioth\u00f3g", + "\u00f3_conmha\u00ed", + "\u00f3_muirge\u00e1in", + "\u00f3_sionnaigh", + "\u00f3_tighearna", + "maccrohan", + "\u00f3_gr\u00e9ill", + "mac_uallach\u00e1in", + "mac_an_fhir", + "\u00f3_tiom\u00e1naidhe", + "mac_gairbhia", + "cuill\u00edn", + "\u00f3_cuigeannaigh", + "mac_maiti\u00fa", + "\u00f3_daibh\u00edn", + "\u00f3_h\u00e9inr\u00ed", + "\u00f3_h\u00e9iligh", + "\u00f3_duinneacha", + "\u00f3_conbhuidhe", + "\u00f3_donchadha", + "\u00f3_conrach", + "\u00f3_scallaigh", + "\u00f3_conl\u00e1in", + "mac_caoch\u00e1in", + "\u00f3_dubhlaigh", + "mac_u\u00ed_sm\u00e1l", + "\u00f3_maoil_aodha", + "mac_casaide", + "\u00f3_maoilch\u00e9ire", + "\u00f3_l\u00e9anach\u00e1in", + "\u00f3_modhr\u00e1in", + "mac_oibic\u00edn", + "\u00f3_coinnigh", + "\u00f3_teangana", + "mac_aonghuis", + "mac_ceoin\u00edn", + "\u00f3_cochl\u00e1in", + "mac_cumascaigh", + "mac_fhlann\u00e1in", + "mac_an_fhailghigh", + "\u00f3_roda\u00ed", + "\u00f3_triall", + "\u00f3_moidhe", + "mac_giolla_eoghain", + "t\u00f3ib\u00edn", + "\u00f3_lailli\u00fa", + "\u00f3_m\u00e1ille", + "de_londra", + "\u00f3_h\u00f3b\u00e1in", + "\u00f3_cathala", + "\u00f3_drisceoil", + "\u00f3_cuanna", + "\u00f3_grianna", + "\u00f3_fionnag\u00e1in", + "\u00f3_h\u00fardail", + "bar\u00f3id", + "\u00f3_haoile\u00e1in", + "mac_giolla_chomhghaill", + "\u00f3_caochla\u00ed", + "de_priondarg\u00e1s", + "\u00f3_r\u00f3l\u00e1in", + "bodhlaeir", + "mac_conbhu\u00ed", + "\u00f3_hioc\u00f3g", + "\u00f3_beag\u00e1in", + "\u00f3_flaithbhearta", + "\u00f3_caoindealbh\u00e1in", + "\u00f3_h\u00e9il\u00ed", + "\u00f3_c\u00e9it\u00edn", + "\u00f3_frithile", + "\u00f3_naoidhean\u00e1in", + "\u00f3_corr\u00e1in", + "\u00f3_n\u00fan\u00e1in", + "\u00f3_faodhag\u00e1in", + "\u00f3_maing\u00edn", + "mac_niocl\u00e1is", + "\u00f3_c\u00e9illeachair", + "mac_giolla_easboig", + "\u00f3_dora\u00ed", + "\u00f3_m\u00eddhia", + "mac_dh\u00fairn\u00edn", + "\u00f3_h\u00e9anag\u00e1in", + "\u00f3_hadhra", + "\u00f3_ciar\u00fac\u00e1in", + "mac_cailp\u00edn", + "\u00f3_daochain", + "mac_coile\u00e1in", + "\u00f3_duibhgeann\u00e1in", + "mac_anna", + "\u00f3_marcaigh", + "mac_giolla_bhr\u00edde", + "\u00f3_bruic", + "mac_d\u00e1ibhid", + "\u00f3_fiannaidh", + "\u00f3_dubhluachra", + "\u00f3_conraoi", + "\u00f3_cobhthaigh", + "\u00f3_haol\u00e1in", + "mac_curraoin", + "\u00f3_cuilinn", + "\u00f3_gion\u00e1in", + "\u00f3_cafua", + "de_lonnradh", + "\u00f3_hinn\u00e9irghe", + "\u00f3_maolmuaidh", + "\u00f3_gl\u00e1ibh\u00edn", + "\u00f3_laochdha", + "\u00f3_lochr\u00e1in", + "mac_e\u00f3in\u00edn", + "\u00f3_maolallaidh", + "neachtain", + "\u00f3_giobal\u00e1in", + "\u00f3_criost\u00fair", + "\u00f3_r\u00fan\u00fa", + "\u00f3_maid\u00edn", + "\u00f3_hallmh\u00far\u00e1in", + "m\u00e9al\u00e1id", + "\u00f3_neabhail", + "coincheanainn", + "\u00f3_h\u00e1rlaigh", + "mac_leann\u00e1in", + "mac_caisle\u00e1in", + "\u00f3_gealag\u00e1in", + "\u00f3_hull\u00e1in", + "mac_d\u00e1ibhidh", + "\u00f3_heigheartaigh", + "mac_duarc\u00e1in", + "\u00f3_haog\u00e1in", + "\u00f3_deasmhumhna", + "\u00f3_dorchaigh", + "\u00f3_lallaigh", + "\u00e1s", + "r\u00eds", + "l\u00fanam", + "\u00f3_fachtna", + "\u00f3_cathasaigh", + "mac_ualtair", + "\u00f3_tuimlin", + "\u00f3_curraidh", + "\u00f3_breisle\u00e1in", + "mac_math\u00fana", + "mac_oralaigh", + "\u00f3_fionnghusa", + "dalt\u00fan", + "\u00f3_filb\u00edn", + "mac_igo", + "\u00f3_droighne\u00e1in", + "\u00f3_conaill", + "mac_connallta", + "\u00f3_maolmhuire", + "\u00f3_muilligh", + "mac_cathail", + "\u00f3_c\u00edrr\u00edc", + "\u00f3_dabh\u00e1in", + "mac_donnchadha", + "\u00f3_cuileamhain", + "\u00f3_goireachtaigh", + "\u00f3_muilleag\u00e1in", + "de_l\u00e1s", + "\u00f3_hurthuile", + "\u00f3_duigeannaigh", + "\u00f3_madadh\u00e1in", + "\u00f3_cuinneag\u00e1in", + "\u00f3_fionnachta", + "\u00f3_glaisne", + "\u00f3_heodhusa", + "mac_carmaig", + "confhaola", + "\u00f3_caireall\u00e1in", + "\u00f3_hin\u00e9ir\u00ed", + "mac_eibhir", + "\u00f3_heithir", + "\u00f3_headhra", + "mac_s\u00e9artha", + "\u00f3_hearghaile", + "mac_geimhridh", + "\u00f3_fuar\u00e1in", + "\u00f3_partlainn", + "\u00f3_rodach\u00e1in", + "cinn\u00e9ir", + "\u00f3_beannuille", + "\u00f3_r\u00e1ighle", + "\u00f3_glias\u00e1in", + "mac_grealaigh", + "\u00f3_helaoire", + "mac_caithir", + "\u00f3_hain\u00edn", + "mac_annraoi", + "\u00f3_caollaidhe", + "mac_ghille_mhaoil", + "bruadar", + "mcgilligan", + "\u00f3_call\u00e1in", + "\u00f3_niall\u00e1in", + "\u00f3_c\u00edobh\u00e1naigh", + "innsead\u00fan", + "\u00f3_labhradha", + "\u00f3_donaoile", + "\u00f3_hifearn\u00e1in", + "de_built\u00e9ir", + "\u00f3_bric", + "mac_d\u00e1id", + "de_hindeberg", + "\u00f3_lomgaigh", + "\u00f3_m\u00e9al\u00f3ide", + "\u00f3_cr\u00edon\u00e1in", + "mac_u\u00ed_bheannuille", + "\u00f3_luasa", + "mac_cuaig", + "\u00f3_fionnlaoich", + "de_hae", + "\u00f3_h\u00e9inni\u00fa", + "\u00f3_cos\u00e1in", + "de_ceap\u00f3g", + "mac_fhuallaigh", + "\u00f3_niadh", + "mac_donncha", + "mac_anabadha", + "\u00f3_tormaigh", + "mac_muireadhaigh", + "mac_r\u00e9amoinn", + "mac_con\u00e1mha", + "mac_fhiachra", + "\u00f3_h\u00e9ighni\u00fa", + "\u00f3_harta", + "\u00f3_claon\u00e1in", + "mac_ugo", + "mac_giolla_bh\u00e1in", + "\u00f3_fearghusa", + "cill\u00edn", + "mac_cluanaigh", + "\u00f3_cuideag\u00e1naigh", + "\u00f3_ciarba", + "\u00f3_coistealbhaigh", + "\u00f3_calbhaigh", + "\u00f3_faran\u00e1in", + "\u00f3_haonach\u00e1in", + "mac_domhnaill", + "\u00f3_briain", + "mac_goill", + "de_bhail\u00eds", + "\u00f3_taidhg", + "mac_r\u00e9ill", + "mac_giolla_uidhir", + "mac_grallaigh", + "\u00f3_piot\u00e1in", + "\u00f3_deoraidhin", + "\u00f3_sith", + "\u00f3_maoil\u00e9ide", + "\u00f3_cn\u00e1imhs\u00ed", + "\u00f3_meirnigh", + "\u00f3_mothair", + "hynman", + "\u00f3_laoi", + "mac_ginneadha", + "\u00f3_laighin", + "\u00f3_bliosc\u00e1in", + "mac_daibh\u00edd", + "\u00f3_corb\u00e1in", + "\u00f3_laoidh", + "\u00f3_seochfhradha", + "\u00f3_cathbhuadha", + "\u00f3_me\u00e1ra\u00ed", + "mac_connach\u00e1in", + "\u00f3_maolfhachtna", + "\u00f3_siadhail", + "mac_uidhir", + "mac_caiside", + "gabh\u00e1in", + "\u00f3_laighnigh", + "de_l\u00e1sa", + "\u00f3_maithn\u00edn", + "\u00f3_hearc\u00e1in", + "mac_cafraigh", + "mac_s\u00edthigh", + "\u00f3_conchubhair", + "\u00f3_t\u00e9ach\u00e1in", + "\u00f3_caoillidhe", + "\u00f3_spol\u00e1in", + "\u00f3_f\u00e1tharta", + "\u00f3_hollar\u00e1in", + "mac_speal\u00e1in", + "mac_a'_bhu\u00ed", + "haic\u00e9ad", + "\u00f3_finneadha", + "mac_an_bheithigh", + "\u00f3_liain", + "mac_giolla_tuile", + "\u00f3_h\u00edc\u00edn", + "\u00f3_giob\u00fain", + "mac_se\u00e1ghain", + "de_creag", + "\u00f3_muine\u00f3g", + "\u00f3_cuideag\u00e1in", + "\u00f3_dubhabhoireann", + "\u00f3_h\u00e9adtrom\u00e1in", + "\u00f3_lochlainn", + "\u00f3_cadhla", + "triall", + "\u00f3_r\u00edog\u00e1in", + "\u00f3_gr\u00e1llaigh", + "\u00f3_tuairisg", + "\u00f3_corrad\u00e1in", + "\u00f3_caithl\u00edn", + "\u00f3_caibe", + "mac_s\u00edom\u00f3in", + "\u00f3_laithmhe", + "\u00f3_coil\u00edn", + "cill_dia", + "\u00f3_cearbhaill", + "conbhae", + "de_bail\u00eds", + "mac_giolla_fhinn\u00e9in", + "\u00f3_sidhe\u00e1il", + "\u00f3_maonghaile", + "\u00f3_c\u00fal\u00e1in", + "curraoin", + "de_ngeard", + "\u00f3_f\u00e9ith", + "\u00f3_raighne", + "\u00f3_conchobhair", + "mac_cear\u00e1in", + "\u00f3_tuaraisce", + "\u00f3_hainmhireach", + "\u00f3_fionnt\u00e1in", + "mac_art\u00fair", + "mac_oscair", + "\u00f3_corcor\u00e1in", + "\u00f3_fithcheallaigh", + "mac_fhearghaile", + "de_bhulf", + "\u00f3_seachnasaigh", + "\u00f3_cionnaith", + "\u00f3_dior\u00e1in", + "\u00f3_scoll\u00e1in", + "\u00f3_beirn", + "mac_giolla_luaithrinn", + "\u00f3_meachair", + "gubain", + "\u00f3_maolfhabhail", + "\u00f3_l\u00fabh\u00f3g", + "mac_cros\u00e1in", + "\u00f3_g\u00e1bh\u00e1in", + "\u00f3_tuam\u00e1in", + "\u00f3_n\u00e1dhraigh", + "mac_con_r\u00ed", + "\u00f3_lorc\u00e1in", + "\u00f3_huaillearan", + "mac_carrghamhne", + "\u00f3_riabhaigh", + "mac_giolla_domhnaigh", + "pl\u00e9imeann", + "mac_conaill", + "\u00f3_tuathaill", + "\u00f3_ceallabhu\u00ed", + "\u00f3_haoll\u00e1in", + "\u00f3_gr\u00e9ach\u00e1in", + "\u00f3_brosnach\u00e1in", + "scannl\u00e1in", + "\u00f3_coinghialla", + "\u00f3_hairbheasaigh", + "mac_caochlaigh", + "mac_bhriain", + "\u00f3_harracht\u00e1in", + "\u00f3_cuine\u00e1in", + "cl\u00e1rach", + "\u00f3_croidhe\u00e1in", + "\u00f3_haodhg\u00e1in", + "\u00f3_turraoin", + "\u00f3_caoimh", + "\u00f3_hearr\u00e1in", + "mac_cuileann\u00e1in", + "\u00f3_cabraigh", + "\u00f3_dubhartaigh", + "mac_conm\u00ed", + "\u00f3_d\u00fanl\u00e1ing", + "mac_carrghamhna", + "\u00f3_murch\u00fa", + "puirs\u00e9al", + "mac_cunnaidh", + "\u00f3_collar\u00e1in", + "mac_d\u00e9id", + "mac_aitig\u00edn", + "\u00f3_labhra", + "\u00f3_cadhlaigh", + "\u00f3_fionnghaile", + "mac_fhionnlaoich", + "\u00f3_raghaill", + "\u00f3_rod\u00e1in", + "\u00f3_croith\u00edn", + "lonnd\u00fan", + "each", + "mac_con_na_buaile", + "\u00f3_l\u00faing", + "\u00f3_hoist\u00edn", + "\u00f3_casarlaigh", + "\u00f3_harg\u00e1in", + "\u00f3_maoldhomhnaigh", + "mac_sein\u00edn", + "\u00f3_caoinle\u00e1in", + "\u00f3_treabhair", + "\u00f3_seibhle\u00e1in", + "\u00f3_fiachra", + "\u00f3_haimhirg\u00edn", + "\u00f3_ciollabh\u00e1in", + "mac_alastair", + "\u00f3_d\u00e9id", + "mac_eoghain", + "mac_conduibh", + "\u00f3_l\u00fa\u00f3g", + "\u00f3_grif\u00edn", + "\u00f3_ceanntabhail", + "\u00f3_cior\u00e1in", + "\u00f3_gn\u00edmh", + "\u00f3_ceallaigh", + "s\u00e1irs\u00e9al", + "\u00f3_t\u00f3l\u00e1in", + "mac_niallghuis", + "mac_cl\u00fain", + "mac_nia", + "mac_giolla_dh\u00e9", + "\u00f3_c\u00e9itinn", + "\u00f3_daimh\u00edn", + "cafua", + "\u00f3_h\u00e9adhn\u00fa", + "\u00f3_ciabh\u00e1in", + "\u00f3_ceafarcaigh", + "\u00f3_raghallaigh", + "mac_anraoi", + "\u00f3_dubhaigh", + "\u00f3_heochadha", + "\u00f3_d\u00e1la", + "laidhl\u00e9is", + "\u00f3_highne", + "de_m\u00f3rdha", + "\u00f3_cao\u00e1in", + "de_l\u00f3ndra", + "\u00f3_f\u00f3gartaigh", + "mac_gamhna", + "macnamee", + "car\u00fan", + "\u00f3_cual\u00e1in", + "\u00f3_laogh\u00f3g", + "\u00f3_ceannduibh", + "\u00f3_conn\u00fach\u00e1in", + "mac_m\u00e1irt\u00edn", + "\u00f3_reachtaire", + "\u00f3_duithche", + "\u00f3_m\u00farn\u00e1in", + "mac_dhubhghail", + "ci\u00fain\u00edn", + "\u00f3_si\u00fard\u00e1in", + "\u00f3_muinilligh", + "\u00f3_hannraoi", + "\u00f3_murach\u00e1in", + "\u00f3_coigligh", + "\u00f3_druach\u00e1in", + "\u00f3_br\u00e9an\u00e1in", + "\u00f3_macasa", + "mac_philb\u00edn", + "mac_taidhg", + "\u00f3_loinne", + "\u00f3_h\u00e9imhigh", + "ruis\u00e9al", + "\u00f3_cinn\u00e9ir", + "mac_ginne\u00e1", + "\u00f3_maolruaidh", + "\u00f3_hioll\u00e1in", + "\u00f3_maine", + "\u00f3_h\u00e9ala\u00ed", + "\u00f3_duibhginn", + "\u00f3_h\u00e9aluighthe", + "mac_ruaidhr\u00ed", + "mac_conacha", + "\u00f3_reachtar", + "\u00f3_lunaigh", + "\u00f3_connollaigh", + "comart\u00fan", + "\u00f3_fuadach\u00e1in", + "\u00f3_cian\u00e1in", + "mac_garaidh", + "\u00f3_cn\u00e1imhsighe", + "\u00f3_conch\u00fair", + "mac_oistig\u00edn", + "\u00f3_marn\u00e1in", + "\u00f3_gaora", + "\u00f3_d\u00fan\u00farta", + "\u00f3_donn\u00e1in", + "\u00f3_liod\u00e1in", + "mac_aodha", + "mac_coisdeala", + "\u00f3_cilltr\u00e1in", + "\u00f3_f\u00e1ilbhe", + "\u00f3_gamhna", + "de_buitl\u00e9ir", + "\u00f3_s\u00edr\u00edn", + "\u00f3_lachn\u00e1in", + "coinn\u00e9r", + "mac_gr\u00e9ill", + "\u00f3_lond\u00e1in", + "\u00f3_hoisc\u00edn", + "mac_caislin", + "\u00f3_meiscill", + "\u00f3_donndhubhartaigh", + "\u00f3_ruanaidhe", + "\u00f3_cruch\u00e1in", + "\u00f3_grialais", + "\u00f3_ceallach\u00e1in", + "\u00f3_coinnle\u00e1in", + "\u00f3_fiachna", + "\u00f3_liathaigh", + "\u00f3_peat\u00e1in", + "\u00f3_cuirr\u00edn", + "mac_coisteala", + "mac_caochla\u00ed", + "\u00f3_gal\u00e1in", + "\u00f3_guairim", + "mac_glion\u00e1in", + "\u00f3_b\u00e1idh", + "\u00f3_scalaighe", + "\u00f3_cuirc", + "br\u00fan", + "\u00f3_coineoil", + "\u00f3_greadaigh", + "\u00f3_leidhinn", + "\u00f3_ceanndubh\u00e1in", + "\u00f3_maolag\u00e1in", + "\u00f3_hiarfhlatha", + "\u00f3_maoilmh\u00edn", + "\u00f3_ceannaigh", + "\u00f3_g\u00e9ibheannaigh", + "\u00f3_hainth\u00edn", + "\u00f3_coscair", + "\u00f3_d\u00e9ide", + "\u00f3_gr\u00edofha", + "\u00f3_br\u00edon\u00e1in", + "mac_claochla\u00ed", + "\u00f3_cuinn", + "\u00f3_gobhann", + "\u00f3_diothch\u00e1in", + "\u00f3_nuan\u00e1in", + "\u00f3_cormaic", + "\u00f3_d\u00fanaighe", + "\u00f3_carr\u00e1in", + "\u00f3_brisle\u00e1in", + "luibh\u00e9ad", + "a_g\u00edontaigh", + "mac_conaola", + "\u00f3_muilc\u00edn", + "\u00f3_huallaigh", + "\u00f3_gaibhre", + "mac_casarlaigh", + "\u00f3_loineach\u00e1in", + "\u00f3_duibhghiolla", + "\u00f3_flaithimh\u00edn", + "mac_dh\u00e1ibhis", + "\u00f3_d\u00farc\u00e1in", + "\u00f3_robhartaigh", + "\u00f3_murraigh", + "mead\u00f3g", + "\u00f3_comhdhain", + "\u00f3_raifteir\u00ed", + "\u00f3_l\u00e1imh\u00edn", + "mac_braoin", + "\u00f3_l\u00fabhaing", + "\u00f3_muire\u00e1in", + "\u00f3_dr\u00edsc\u00edn", + "\u00f3_reachtair", + "mac_ailp\u00edn", + "\u00f3_de\u00e1ghdha", + "\u00f3_leighin", + "\u00f3_mainch\u00edn", + "mac_fhlannchadha", + "\u00f3_s\u00edoch\u00e1in", + "mac_giolla_mh\u00e1irt\u00edn", + "\u00f3_flatharta", + "\u00f3_conghamhna", + "\u00f3_r\u00e1naigh", + "mac_tuathal\u00e1in", + "\u00f3_muireag\u00e1in", + "\u00f3_cnuach\u00e1in", + "\u00f3_l\u00e1sa", + "\u00f3_comair", + "\u00f3_bruadair", + "\u00f3_cail\u00edn", + "mac_gafraigh", + "mac_fhloinn", + "\u00f3_teimhne\u00e1in", + "mac_giolla_fhaol\u00e1in", + "\u00f3_doighre", + "\u00f3_f\u00faraigh", + "sionainn", + "\u00f3_meadhra\u00ed", + "b\u00e1caeir", + "\u00f3_laoghaire", + "\u00f3_heaghr\u00e1in", + "philib", + "\u00f3_raighilligh", + "\u00f3_breasl\u00e1in", + "\u00f3_maoilmhich\u00edl", + "de_l\u00e9ad\u00fas", + "\u00f3_maran\u00e1in", + "caomh\u00e1nach", + "\u00f3_conmhu\u00ed", + "\u00f3_f\u00e9ich\u00edn", + "mac_giolla_sean\u00e1in", + "mr\u00edos\u00e1in", + "mac_\u00f3da", + "\u00f3_hurdail", + "mac_corcor\u00e1in", + "\u00f3_caonaigh", + "freis", + "mac_ghilleathain", + "\u00f3_larc\u00e1in", + "\u00f3_h\u00e9ighne", + "treoigh", + "\u00f3_baoighill", + "mac_diarmada", + "mac_gairbh\u00edn", + "\u00f3_dubhshl\u00e1ine", + "\u00f3_fiacha", + "\u00f3_hodhr\u00e1in", + "mac_cearbhaill", + "mac_giolla_choda", + "\u00f3_bear\u00e1in", + "de_brae", + "\u00f3_tuataigh", + "\u00f3_cearr", + "mac_fhinneachtaigh", + "mac_reanach\u00e1in", + "\u00f3_gearabh\u00e1in", + "mac_aoidh", + "mac_curdaigh", + "\u00f3_coine\u00e1in", + "\u00f3_feith\u00edn", + "\u00f3_curraoin", + "\u00f3_h\u00e9nr\u00ed", + "de_b\u00e9alat\u00fan", + "\u00f3_raighle", + "\u00f3_glionn\u00e1in", + "\u00f3_lurg\u00e1in", + "\u00f3_tuathal\u00e1in", + "mac_giolla_ph\u00e1draig", + "\u00f3_casaide", + "\u00f3_caomh\u00e1naigh", + "\u00f3_hannlaoigh", + "mac_an_ghabhann", + "mac_giolla_na_naomh", + "\u00f3_cailp\u00edn", + "\u00f3_hadhlairt", + "\u00f3_d\u00edomasaigh", + "\u00f3_duibh\u00edn", + "i\u00fast\u00e1s", + "mac_ghille_fhaol\u00e1in", + "\u00f3_maoinigh", + "eilfirt", + "\u00f3_bolghuidhir", + "landy", + "mac_\u00edos\u00f3g", + "\u00f3_murchadha", + "mac_coinnigh", + "\u00f3_carrghamhna", + "\u00f3_flaitile", + "p\u00e1irceir", + "\u00f3_ceanainn", + "\u00f3_cn\u00e1imh\u00edn", + "\u00f3_coirb\u00edn", + "\u00f3_conra", + "\u00f3_maolchraoibhe", + "mac_gaora", + "mac_grialais", + "\u00f3_s\u00e9agha", + "\u00f3_tomhnair", + "mac_fh\u00f3gartaigh", + "\u00f3_duibheannaigh", + "mac_neachtain", + "\u00f3_miadha", + "\u00f3_gog\u00e1in", + "\u00f3_curraidhin", + "mac_suibhne", + "\u00f3_hanraoi", + "\u00f3_diol\u00fain", + "\u00f3_cuag\u00e1in", + "\u00f3_maolalaigh", + "\u00f3_dubhthaigh", + "mac_gr\u00e9ine", + "bar\u00fan", + "\u00f3_cearr\u00fain", + "\u00f3_dr\u00f3na", + "\u00f3_leann\u00e1in", + "uaithne", + "\u00f3_l\u00f3n\u00e1in", + "de_cl\u00e9ir", + "mac_eachmharcaigh", + "\u00f3_haiseadha", + "mac_fheorais", + "de_st\u00f3c", + "mac_c\u00e1ba", + "consaid\u00edn", + "\u00f3_caid\u00edn", + "\u00f3_heislin", + "a'_cillartr\u00e1in", + "mac_an_mh\u00e1istir", + "\u00f3_saoraidhe", + "\u00f3_com\u00e1in", + "\u00f3_guill\u00ed", + "\u00f3_cumhaill", + "\u00f3_h\u00e1nusaigh", + "\u00f3_maoilch\u00e9ir", + "\u00f3_comhra\u00ed", + "\u00f3_reacht\u00faire", + "\u00f3_tr\u00e9infhear", + "\u00f3_sceall\u00e1in", + "mac_aindri\u00fa", + "\u00f3_cuidithe", + "soolach\u00e1n", + "\u00f3_siaghail", + "\u00f3_duigne\u00e1in", + "ceara", + "mac_rabhartaigh", + "\u00f3_\u00e1nusaigh", + "\u00f3_tolain", + "mac_loingsigh", + "caimb\u00e9al", + "\u00f3_t\u00e9idheach\u00e1in", + "\u00f3_murach\u00fa", + "mac_giolla_choinnigh", + "\u00f3_s\u00edom\u00f3in", + "\u00f3_f\u00edona", + "\u00f3_cathal\u00e1in", + "\u00f3_mullala", + "\u00f3_reachtag\u00e1in", + "mac_cathaoir", + "\u00f3_miadhach\u00e1in", + "mac_giolla_mhuire", + "\u00f3_gr\u00edf\u00edn", + "\u00f3_claochla\u00ed", + "\u00f3_h\u00f3g\u00e1in", + "mac_an_mhadaidh", + "\u00f3_maic\u00edn", + "de_car\u00fan", + "\u00f3_haichir", + "\u00f3_mianaigh", + "\u00f3_c\u00e9ide", + "\u00f3_hiorbhard", + "\u00f3_labhr\u00fa", + "\u00f3_coll\u00e1in", + "\u00f3_lionn\u00e1in", + "mac_conchoille", + "\u00f3_bion\u00e1in", + "mac_sl\u00e9ibh\u00edn", + "\u00f3_cuacach", + "\u00f3_bior\u00e1in", + "ceoth\u00e1nach", + "de_barra", + "\u00f3_hoireabhard", + "\u00f3_laoithe", + "\u00f3_coinneach\u00e1in", + "mac_robhartaigh", + "\u00f3_ruan\u00e1in", + "mac_giolla_an_chloig", + "\u00f3_loinnsge", + "mac_firbhisigh", + "\u00f3_ciaraigh", + "\u00f3_maoile\u00e1in", + "\u00f3_costag\u00e1in", + "mac_conn\u00f3l", + "\u00f3_miadhaigh", + "\u00f3_braon\u00e1in", + "\u00f3_corlaigh", + "mac_niocail", + "\u00f3_cuilean\u00e1in", + "\u00f3_cuirle\u00e1in", + "\u00f3_mach\u00e1in", + "\u00f3_ciothaigh", + "\u00f3_maolmhudh\u00f3g", + "\u00f3_fiannachta", + "\u00f3_mainich\u00edn", + "\u00f3_reannach\u00e1in", + "\u00f3_cuinn\u00e9ir", + "\u00f3_bolguidhir", + "mac_an_ghall\u00f3glaigh", + "mac_thiarn\u00e1in", + "\u00f3_duirn\u00edn", + "\u00f3_maold\u00fain", + "\u00f3_dighe", + "\u00f3_maoineach\u00e1in", + "\u00f3_nia", + "mac_cuilean\u00e1in", + "\u00f3_dorch\u00e1in", + "\u00f3_tiomanaidh", + "\u00f3_s\u00e9", + "\u00f3_cill\u00edn", + "\u00f3_nuadhain", + "mac_concharraige", + "l\u00fais\u00e9ad", + "\u00f3_mal\u00f3id", + "\u00f3_cearmada", + "\u00f3_donnch\u00fa", + "de_liost\u00fan", + "mac_giolla_choille", + "\u00f3_maolriagh\u00e1in", + "\u00f3_ceithearnaigh", + "mac_coingheall\u00e1", + "\u00f3_muireann", + "\u00f3_tarpaigh", + "mac_ghoill", + "\u00f3_luachra", + "doghair", + "mac_catail\u00edn", + "\u00f3_hin\u00e9irigh", + "mac_sh\u00f3mais", + "\u00f3_l\u00edonach\u00e1in", + "\u00f3_b\u00e9ag\u00e1in", + "\u00f3_con\u00fach\u00e1in", + "mac_uaid", + "\u00f3_caol\u00e1in", + "\u00f3_t\u00f3rpaigh", + "\u00f3_maoilearca", + "\u00f3_luag", + "mac_canna", + "\u00f3_mor\u00e1in", + "\u00f3_fearchair", + "mac_an_mh\u00edlidh", + "de_h\u00f3ra", + "\u00f3_lonn\u00e1in", + "mac_riada", + "\u00f3_cuille\u00e1in", + "mac_fhionghuin", + "\u00f3_maol_aodha", + "capua", + "\u00f3_beirgin", + "mac_giolla_geimhridh", + "\u00f3_maoil_eoin", + "de_tre\u00f3", + "\u00f3_br\u00f3ithe", + "mac_gorm\u00e1in", + "\u00f3_laithbheartaigh", + "de_lonndraigh", + "\u00f3_scolaidhe", + "mac_le\u00f3id", + "\u00f3_f\u00e1rta", + "mac_niallghais", + "\u00f3_h\u00edomhair", + "\u00f3_dubhthaigh_recte_dooly", + "mac_an_bhreithimh", + "\u00f3_gr\u00edofa", + "de_l\u00e9is", + "\u00f3_g\u00e9ibhinn", + "\u00f3_maoileach\u00e1in", + "\u00f3_dubhda", + "de_l\u00e1saidhe", + "\u00f3_maoileala", + "mac_cr\u00e9adaigh", + "\u00f3_tuaruisce", + "\u00f3_cruadhlaoich", + "de_r\u00f3s", + "neanc\u00f3l", + "mac_dhubhghaill", + "de_neanc\u00f3l", + "\u00f3_coingheallaigh", + "\u00f3_cuil\u00edn", + "\u00f3_cibhil", + "colum", + "mac_aindriais", + "mac_inneirghe", + "mac_costag\u00e1in", + "\u00f3_coinne", + "mac_an_mh\u00edleadha", + "mac_giolla_e\u00e1in", + "mac_coiligh", + "bhail\u00eds", + "\u00f3_l\u00f3g\u00e1in", + "\u00f3_ce\u00e1rna", + "\u00f3_tuathal\u00edn", + "\u00f3_madaidhe", + "mac_cairbre", + "\u00f3_moch\u00f3raigh", + "\u00f3_rioll\u00e1in", + "mac_fhlannag\u00e1in", + "\u00f3_s\u00edththe", + "\u00f3_fiach\u00e1in", + "\u00f3_braoin", + "\u00f3_reachtabhra", + "\u00f3_foghl\u00fa", + "\u00f3_d\u00edochon", + "\u00f3_coigil", + "\u00f3_c\u00faise", + "\u00f3_scanaill", + "\u00f3_muirgheas\u00e1in", + "\u00f3_comhghaill", + "\u00f3_d\u00edsc\u00edn", + "\u00f3_h\u00e9ide\u00e1in", + "\u00f3_caodhla", + "mac_fearadhaigh", + "\u00f3_traoin", + "\u00f3_dubhl\u00e1in", + "de_cr\u00fais", + "mac_ualghairg", + "\u00f3_hearn\u00e1in", + "\u00f3_finn", + "\u00f3_molraoghain", + "\u00f3_luineach\u00e1in", + "\u00f3_domhnall\u00e1in", + "mac_giollarn\u00e1th", + "\u00f3_heidhin", + "\u00f3_coinn\u00e9ir", + "\u00f3_connbhu\u00ed", + "g\u00e1ineard", + "\u00f3_g\u00edontaigh", + "mac_cathbhaid", + "\u00f3_dubhlaoich", + "\u00f3_bearn\u00e1in", + "\u00f3_laoidhigh", + "de_nge\u00e1rd", + "mac_shi\u00fard\u00e1in", + "\u00f3_toirbhealaigh", + "gug\u00e1n", + "\u00f3_r\u00e1ighne", + "\u00f3_loide\u00e1in", + "mac_eoin", + "\u00f3_c\u00edor\u00e1in", + "\u00f3_buadhach\u00e1in", + "\u00f3_dire\u00e1in", + "\u00f3_creag", + "mac_\u00fag\u00f3", + "\u00f3_rathallaigh", + "\u00f3_caoile\u00e1in", + "\u00f3_heideag\u00e1in", + "\u00f3_diothchain", + "\u00f3_hailghean\u00e1in", + "\u00f3_buachalla", + "\u00f3_searraigh", + "\u00f3_hoireabaird", + "\u00f3_maolghuala", + "l\u00e1s", + "\u00f3_laidhin", + "\u00f3_hearch\u00fa", + "\u00f3_beach\u00e1in", + "\u00f3_seanainn", + "mac_shi\u00fart\u00e1in", + "\u00f3_caoin", + "mac_cual\u00e1in", + "de_h\u00f3rdha", + "\u00f3_dubhag\u00e1in", + "\u00f3_d\u00f3l\u00e1in", + "mac_an_\u00e1tha", + "\u00f3_c\u00f3rrain", + "\u00f3_carraidhin", + "\u00f3_huallach\u00e1in", + "mac_an_mhaoir", + "\u00f3_hearghail", + "\u00f3_g\u00e9ar\u00e1in", + "mac_amhalghaidh", + "\u00f3_cathbhuadhaigh", + "mac_thr\u00e9infhear", + "\u00f3_cearr\u00fac\u00e1in", + "\u00f3_cainnigh", + "\u00f3_treasa\u00ed", + "mac_giolla_deacair", + "\u00f3_maothag\u00e1in", + "\u00f3_cuirt\u00e9ir", + "\u00f3_hargad\u00e1in", + "\u00f3_huitseach\u00e1in", + "\u00f3_maoir", + "\u00f3_liath\u00e1in", + "mac_gearachaigh", + "\u00f3_cullaigh", + "\u00f3_hicidhe", + "\u00f3_g\u00fan\u00e1in", + "\u00f3_fear\u00e1in", + "mac_risteard", + "\u00f3_de\u00e1gha", + "\u00f3_gleann\u00e1in", + "\u00f3_criomhthain", + "mac_cathmhaoil", + "\u00f3_fionnmhac\u00e1in", + "\u00f3_baoigheall\u00e1in", + "\u00f3_ruanadha", + "\u00f3_gairbhia", + "\u00f3_maonaigh", + "\u00f3_d\u00e9adaigh", + "mac_murchadha", + "\u00f3_lon\u00e1in", + "mac_aonghais", + "\u00f3_coile", + "\u00f3_loididh", + "mac_giolla_ghuala", + "\u00f3_fearraidhe", + "mac_coisdealbha", + "\u00f3_loinn", + "\u00f3_cuim\u00edn", + "\u00f3_niath\u00e1in", + "\u00f3_maol\u00e1in", + "mac_maol\u00e1in", + "mac_lughadha", + "\u00f3_murghaile", + "\u00f3_muraoile", + "\u00f3_riard\u00e1in", + "de_n\u00f3gla", + "\u00f3_l\u00f3ch\u00e1in", + "mac_ois\u00edn", + "cuine\u00e1in", + "mac_shitric", + "\u00f3_birn", + "\u00f3_dubhdh\u00e1in", + "\u00f3_muireadhaigh", + "\u00f3_h\u00e9ilidhe", + "\u00f3_goib\u00edn", + "mac_ceannabh\u00e1in", + "\u00f3_caingne", + "\u00f3_dord\u00e1in", + "\u00f3_d\u00fada", + "\u00f3_liaghain", + "\u00f3_hourach\u00e1in", + "\u00f3_cathaoir", + "\u00f3_biach\u00e1in", + "\u00f3_heochach", + "\u00f3_buadhaigh", + "\u00f3_gailli\u00fain", + "\u00f3_coine\u00f3il", + "mac_philib", + "\u00f3_fodhladha", + "\u00f3_donnghaile", + "mac_an_chros\u00e1in", + "ceirisc", + "mac_comhghaill", + "de_bhulbh", + "\u00f3_cuannaigh", + "\u00f3_m\u00e1th\u00fana", + "\u00f3_cl\u00fan\u00e1in", + "dion\u00fan", + "\u00f3_r\u00fanaidhe", + "de_b\u00e1th", + "muilleoir", + "mac_fhlaithimh", + "\u00f3_robhach\u00e1in", + "mac_cn\u00e1imhsighe", + "\u00f3_hannaidh", + "\u00f3_breannd\u00e1in", + "\u00f3_crotaigh", + "mac_consaid\u00edn", + "mac_giollag\u00e1in", + "\u00f3_d\u00fanlaing", + "mac_bhloscaigh", + "\u00f3_dearg\u00e1in", + "\u00f3_m\u00edl\u00e9ada", + "\u00f3_daghn\u00e1in", + "\u00f3_gaoith\u00edn", + "mac_seafraidh", + "\u00f3_muinn\u00edle", + "mac_dhuinneabh\u00e1in", + "\u00f3_riag\u00e1in", + "mac_conmhaoil", + "\u00f3_cearnaigh", + "\u00f3_sluaghdh\u00e1in", + "\u00f3_donndubhartaigh", + "\u00f3_meidhir", + "mac_an_leagha", + "\u00f3_mong\u00e1in", + "\u00f3_tighearnaigh", + "mac_giolla_dhiarmada", + "\u00f3_calaigh", + "\u00f3_spioll\u00e1in", + "ceothach", + "\u00f3_h\u00e9imhthigh", + "\u00f3_feardhaigh", + "\u00f3_cunnaidh", + "mac_tiarn\u00e1in", + "\u00f3_doghair", + "mac_niadh", + "p\u00f3il", + "\u00f3_muirneach\u00e1in", + "mac_cn\u00e1imhs\u00ed", + "mac_uibhr\u00edn", + "\u00f3_mill\u00e9adha", + "\u00f3_ludh\u00f3g", + "gionnachtaigh", + "\u00f3_n\u00fain", + "\u00f3_cuileann\u00e1in", + "\u00f3_loinnigh", + "\u00f3_cathail", + "de_h\u00edde", + "\u00f3_flabh\u00e1in", + "\u00f3_hearbhard", + "mac_eiteag\u00e1in", + "\u00f3_niaidh", + "mac_an_bhreitheamhain", + "mac_carluis", + "\u00f3_fuarth\u00e1in", + "\u00f3_r\u00edord\u00e1in", + "\u00f3_flannag\u00e1in", + "capuaigh", + "\u00f3_ruaidhe", + "\u00f3_h\u00f3r\u00e1in", + "\u00f3_hainif\u00edn", + "\u00f3_dorchaidhe", + "\u00f3_c\u00falach\u00e1in", + "mac_an_r\u00ed", + "mac_riocaird", + "\u00f3_hionnghaile", + "\u00f3_roithle\u00e1in", + "\u00f3_lochtn\u00e1in", + "\u00f3_caoilte", + "\u00f3_dunshl\u00e9ibhe", + "mac_an_bhua", + "mac_nail\u00edn", + "\u00f3_cathmhaoil", + "\u00f3_seanach\u00e1in", + "mac_an_tsaoi", + "\u00f3_donnchadha", + "\u00f3_cais\u00edn", + "\u00f3_contra", + "ruairc", + "\u00f3_f\u00f3ghladha", + "\u00f3_gill\u00edn", + "\u00f3_dubhghaill", + "\u00f3_caodh\u00e1in", + "mac_roib\u00edn", + "\u00f3_cruach\u00e1in", + "\u00f3_goll\u00e1in", + "\u00f3_priongal\u00f3id", + "mac_conagail", + "\u00f3_cl\u00e9ireach\u00e1in", + "\u00f3_coisdealbha", + "\u00f3_carrag\u00e1in", + "\u00f3_rinn", + "\u00f3_caomh\u00e1in", + "\u00f3_hoireabhaird", + "seoighe", + "mac_criomhthain", + "\u00f3_gr\u00e1daigh", + "mac_conchradha", + "\u00f3_madaidhin", + "cios\u00f3g", + "\u00f3_duinnshl\u00e9ibhe", + "\u00f3_cuanach\u00e1in", + "\u00f3_b\u00e9arra", + "\u00f3_l\u00edthe", + "de_br\u00fan", + "\u00f3_duineacha", + "\u00f3_geann\u00e1in", + "\u00f3_h\u00f3dhra", + "\u00f3_maolallaigh", + "mac_giolla_mhuiris", + "\u00f3_crim\u00edn", + "\u00f3_s\u00failleabh\u00e1in", + "coin\u00edn", + "\u00f3_gealbh\u00e1in", + "mac_gilleathain", + "mac_cart\u00e1in", + "\u00f3_sionach\u00e1in", + "\u00f3_conaire", + "\u00f3_coill\u00edn", + "\u00f3_faol\u00e1in", + "\u00f3_ceoch\u00e1in", + "b\u00e9ireach", + "mac_g\u00e1ineard", + "mac_sheoin\u00edn", + "\u00f3_ban\u00e1in", + "mac_an_deag\u00e1naigh", + "\u00f3_ciardha", + "\u00f3_duibhne", + "\u00f3_hoirbheard", + "\u00f3_fithchealla", + "\u00f3_rudaigh", + "\u00f3_fionnall\u00e1in", + "\u00f3_hic\u00ed", + "\u00f3_g\u00e1naird", + "de_noraidh", + "mac_gearchaigh", + "mac_ghille_\u00edosa", + "mac_conraoi", + "mac_gloinn", + "\u00f3_monghaile", + "mac_st\u00edn", + "de_r\u00f3isde", + "\u00f3_laidhe", + "mac_thoirbhealaigh", + "\u00f3_huisc\u00edn", + "mac_craobh\u00e1in", + "mac_tuathail", + "\u00f3_flannabhra", + "tre\u00f3", + "\u00f3_darg\u00e1in", + "\u00f3_seanaigh", + "\u00f3_gr\u00edbhth\u00edn", + "\u00f3_l\u00e9ineach\u00e1in", + "mac_giollarua", + "\u00f3_muirth\u00edn", + "grialais", + "mac_fhearadhaigh", + "ginne\u00e1", + "\u00f3_seibhlin", + "ciarag\u00e1in", + "\u00f3_maolmhoch\u00f3irghe", + "cadhain", + "\u00f3_cuilliudha", + "\u00f3_d\u00fana\u00ed", + "\u00f3_br\u00e1on\u00e1in", + "\u00f3_cuilli\u00fa", + "\u00f3_r\u00e9ag\u00e1in", + "\u00f3_claochlaoigh", + "\u00f3_c\u00e9itig", + "\u00f3_heoghain", + "\u00f3_heil\u00edre", + "\u00f3_r\u00e1ghaill", + "\u00f3_huidhir", + "mac_liam", + "mac_dhonncha", + "\u00f3_fual\u00e1in", + "\u00f3_lionach\u00e1in", + "\u00f3_lap\u00e1in", + "de_paor", + "conraoi", + "\u00f3_connachtaigh", + "de_searl\u00f3g", + "\u00f3_luanaigh", + "\u00f3_tiom\u00e1na\u00ed", + "\u00f3_caona", + "\u00f3_h\u00e9igearta", + "\u00f3_mad\u00e1in", + "\u00f3_duibhfhinn", + "\u00f3_lanag\u00e1in", + "a_goireachtaigh", + "\u00f3_hoirchinnigh", + "\u00f3_spiol\u00e1in", + "mac_fhearchair", + "mac_gaoith\u00edn", + "\u00f3_somach\u00e1in" + ], + "LAST_NAME_MALE": [], + "LAST_NAME_FEMALE": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "m\u00e1thairab": "abba", + "ban_ab": "abba", + "banbhar\u00fan": "bar\u00fan", + "br\u00eddeach": "giolla_scoir", + "cathaoirleach": "fear_cathaoireach", + "bandi\u00fac": "di\u00fac", + "banimpire": "c\u00e1r", + "baineannach": "fireannach", + "boireannach": "fireannach", + "baineann": "fireannach", + "garin\u00edon": "mac_mic", + "ardmh\u00e1istre\u00e1s": "ardmh\u00e1istir", + "banlaoch": "gaisc\u00edoch", + "banghaisc\u00edoch": "gaisc\u00edoch", + "ban\u00f3stach": "\u00f3stach", + "bean_uasal": "tiarna", + "d\u00e1ma": "tiarna", + "bantiarna": "tiarna", + "bantiarna_tal\u00fan": "tiarna_talaimh", + "gearrchaile": "fi\u00fa", + "caileag": "leaid", + "in\u00edon": "ridire", + "\u00f3gbhean": "ridire", + "mam": "athair", + "bh": "uas", + "bean_rialta": "manach", + "cailleach_dhubh": "manach", + "bansagart": "athair_naofa", + "in\u00edon_r\u00ed": "an_prionsa", + "flaith": "prionsa", + "banr\u00edon": "r\u00ed", + "queens": "r\u00edthe", + "singil": "dearth\u00e1ir", + "deirfi\u00far": "dearth\u00e1ir", + "leasin\u00edon": "leasmhac", + "leasmh\u00e1thair": "leasathair", + "baintreach": "baintreach_fir", + "bean": "fear_c\u00e9ile", + "bean_ch\u00e9ile": "fear_c\u00e9ile", + "wicca": "draoi", + "cailleach": "m\u00e1g", + "cailleach_ultach": "asarla\u00ed", + "bean_ultach": "asarla\u00ed", + "gars\u00fan": "hine", + "fi\u00fa": "caileag", + "buachaill": "hine" + }, + "other_gender_swap": {}, + "en_pronoun2gender": { + "they": [ + "homaighn\u00e9asach", + "d\u00e9ghn\u00e9asach" + ], + "he": [ + "leaid", + "buachaill", + "gars\u00fan", + "fireannach", + "fi\u00fa" + ], + "she": [ + "boireannach", + "d\u00e1ma", + "in\u00edon", + "cail\u00edneog", + "bean", + "baineannach", + "bean_uasal", + "bantiarna", + "baineann", + "hine", + "caileag", + "ainnir", + "\u00f3gbhean", + "leispiach", + "cine\u00e1l_baineann", + "cine\u00e1l_banda" + ] + }, + "en_pronoun2pronoun": { + "he": [ + "lia" + ], + "they": [ + "siad", + "lia", + "iad", + "iadsan", + "siadsan", + "olar" + ] + }, + "en_pronoun2title": {}, + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/gag.json b/data_tooling/pii_processing/ontology/data/gag.json new file mode 100644 index 0000000..f8fd595 --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/gag.json @@ -0,0 +1,57 @@ +{ + "JOB": [ + "don", + "para" + ], + "DISEASE": [ + "para" + ], + "ANIMAL": [ + "mink" + ], + "ORG": [ + "ekincilik" + ], + "PUBLIC_FIGURE": [ + "o", + "zambak" + ], + "LANGUAGE": [ + "saksan" + ], + "SOC_ECO_CLASS": [ + "ekincilik" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "unuka": "torun", + "kar\u0131": "ki\u015fi", + "kad\u0131n": "ki\u015fi" + }, + "other_gender_swap": {}, + "en_pronoun2gender": { + "he": [ + "ki\u015fi" + ], + "she": [ + "kad\u0131n", + "kar\u0131" + ] + }, + "en_pronoun2pronoun": { + "he": [ + "elli" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/gd.json b/data_tooling/pii_processing/ontology/data/gd.json new file mode 100644 index 0000000..ab4b696 --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/gd.json @@ -0,0 +1,526 @@ +{ + "PLANT": [ + "seircean", + "learag", + "muileag", + "buidheag", + "plumas", + "cathair_thalmhainn", + "curran", + "biotais", + "slinnean", + "caorann", + "naomh_moire", + "abragod", + "deanntag" + ], + "PUBLIC_FIGURE": [ + "henry_cavendish", + "mar_sin_air_adhart", + "che_guevara", + "william_gladstone", + "eduard_buchner", + "winston_churchill", + "paul_mccartney", + "richard_smalley", + "artair", + "isaac_newton", + "victor_hugo", + "milton_friedman", + "raibeart", + "george_harrison", + "george_orwell", + "arthur_koestler", + "richard_wagner", + "marie_curie", + "griogair", + "samuel_beckett", + "galileo_galilei", + "jane_goodall", + "robert_koch", + "john_steinbeck", + "vincent_van_gogh", + "hans_fischer", + "marie_antoinette", + "giuseppe_verdi", + "e", + "frank_sinatra", + "abel_tasman", + "katharine_hepburn", + "louis_pasteur", + "luigi_pirandello", + "t_s_eliot", + "charles_de_gaulle", + "y", + "mary_mallon", + "f", + "thomas_mann", + "dante_alighieri", + "james_tobin", + "giacomo_puccini", + "joseph_priestley", + "oscar_wilde", + "piet_mondriaan", + "richard_trevithick", + "laurence_olivier", + "a", + "james_brown", + "immanuel_kant", + "john_haldane", + "ealasaid", + "giulio_natta", + "william_blake", + "canberra", + "elias_canetti", + "john_mercer", + "lars_onsager", + "joseph_black", + "bertrand_russell", + "michael_faraday", + "jan_tinbergen", + "friedrich_engels", + "jane_austen", + "robert_redford", + "theodor_mommsen", + "william_golding", + "alfred_nobel", + "daniel_rutherford", + "marco_polo", + "charlie_watts", + "henri_bergson", + "naomh_p\u00e0draig", + "patrick_white", + "hans_christian_andersen", + "cary_grant", + "isaac_watts", + "otto_hahn", + "john_galsworthy", + "gille_m\u00f9chain", + "o", + "adam_smith", + "karl_marx", + "i", + "mel_gibson", + "ingrid_bergman", + "adolf_hitler", + "fritz_haber", + "eideard", + "vladimir_putin", + "g", + "james_cagney", + "r", + "george_lucas", + "andrew_jackson", + "st_louis_missouri", + "johannes_gutenberg", + "d", + "william_faulkner", + "putin", + "marcus_aurelius", + "paul_newman", + "john_lennon", + "charlie_chaplin", + "james_watt", + "ronald_reagan", + "s", + "woodrow_wilson", + "ernest_hemingway", + "cristoforo_colombo", + "nelson_mandela", + "roald_amundsen", + "charles_dickens", + "ella_fitzgerald", + "fulangach", + "wallace_carothers", + "francisco_franco", + "andrew_carnegie", + "johnny_cash", + "mick_jagger", + "walter_scott", + "vladimir_lenin", + "sam_houston", + "albert_einstein", + "t", + "cervantes", + "wilhelm_ostwald" + ], + "JOB": [ + "banchaig", + "banarach", + "fuineadair", + "copaidh", + "radan", + "maraiche", + "ministear", + "marsal", + "deasaiche", + "lighiche", + "muireach", + "dannsair", + "dotair", + "gruagaire", + "uachdaran", + "meacanaig", + "obraiche", + "loingear", + "malairtiche", + "lethbhreac", + "fastachadh", + "siorram", + "buachaill_chaorach", + "reiceadair", + "rianaire", + "searmonaiche", + "grosair", + "deathan", + "roithlear", + "clachair", + "dealbhadair_thogalach", + "rothadair", + "teiripiche", + "riaghladair", + "f\u00f9cadair", + "caiptean" + ], + "ANIMAL": [ + "beathadach", + "los_leathann", + "cat", + "rasmhaol", + "taghan", + "firefox", + "athaid", + "mamal", + "speireag", + "starrag", + "clamhan", + "curracag", + "cam_ghob", + "sgrab", + "seabhag", + "goiriola", + "glasag", + "minc", + "speach", + "fearaid", + "puthag", + "peileag", + "bronnag", + "gobhlan_gaoithe", + "cathan", + "neas", + "losgann", + "glaisean", + "coileach_dubh", + "gearra_mhuc", + "connspeach", + "cairgein" + ], + "DISEASE": [ + "a_phluc", + "siataig", + "dragh", + "cadal", + "f\u00e0illigeadh", + "gall", + "pronnadh", + "dolair", + "buaireas", + "galar_pearraide", + "luch", + "neach_st\u00e8idheachaidh", + "alltan", + "failc", + "an_galar_tuiteamas_cadail", + "torraicheas", + "a_chaitheamh", + "a_phloic", + "breisleach", + "gaiseadh", + "bramasag", + "mearan", + "am_b\u00e0s_dubh", + "a_bhanachrach", + "caidil", + "bruaillean", + "a_bhreac", + "sl\u00ecog", + "uathachas", + "leatromachd", + "casadaich" + ], + "PRODUCT": [ + "justin_bieber", + "am_manifesto_commanach", + "s\u00e3o_tom\u00e9_agus_pr\u00edncipe", + "an_spiorad_naomh", + "s_fhearr_deireadh_math_na_droch_thoiseach", + "sagsainn_anhalt", + "na_fir_chlis", + "an_d\u00e0rna_cogadh", + "nordrhein_westfalen", + "bodach_na_nollaige", + "c\u00f2raichean_daonna", + "an_r\u00ecoghachd_aonaichte", + "an_cogadh_m\u00f2r" + ], + "RELIGION": [ + "zen", + "siont\u00f2", + "islam", + "wicca" + ], + "ORG": [ + "wicca", + "an_t_aonadh_e\u00f2rpach", + "loch_laomainn", + "nasa", + "an_roinn_e\u00f2rpa", + "an_t_aonadh_eorpach", + "an_cogadh_fuar", + "san_francisco", + "a_ghearmailt_an_ear", + "\u00e0iteachas", + "saothair", + "an_gearasdan", + "oidhche_challainn", + "eaglais_chaitligeach", + "na_d\u00f9thchannan_aonaichte", + "dia", + "rabindranath_tagore", + "siont\u00f2", + "foghlam", + "addis_ababa", + "p\u00e0rtaidh_phoileatagach", + "hare_krishna", + "loch_superior", + "an_t_ath_leasachadh", + "na_st\u00e0itean_aonaichte", + "los_angeles", + "a_ghearmailt_n\u00e0sach", + "is_e_an_cleachdadh_a_n\u00ec_te\u00f2ma", + "cuaigearan", + "an_dr\u00e0sta_s_a_rithist", + "eaglais_an_r\u00f2imh", + "domhan_\u00f9r", + "an_\u00e0irc", + "baisteach", + "gearmailtis", + "s\u00e3o_tom\u00e9", + "p\u00e0irtidh" + ], + "GENDER": [ + "balach", + "balachan", + "caileag", + "gruagach", + "baintighearna" + ], + "GPE": [ + "spiorad_naomh", + "dar_es_salaam", + "sri_jayawardenapura", + "s\u00e3o_tom\u00e9", + "gran_canaria", + "al_andalus", + "naomh_se\u00f2ras", + "an_spiorad_naomh", + "ar_baintighearna", + "impireachd_na_gearmailte", + "la_gomera", + "tiomnadh_nuadh", + "naomh_nicol" + ], + "LANGUAGE": [ + "suainis", + "arabais", + "nirribheach", + "afraganais", + "frangais", + "malaidheach", + "hindi", + "esperanto", + "afrag\u00e0ns", + "an_t_seann_gh\u00e0idhlig", + "airmeineach", + "bealaruiseach", + "seiceach", + "alb\u00e0ineach", + "amarais", + "ruiseanach", + "tonga" + ], + "LOCATION": [ + "daida\u00edn_na_nollaig", + "na_rolling_stones", + "o_shean", + "callainn", + "an_cuan_a_tuath", + "cape_verde", + "o_chionn_fhada", + "s_e_do_bheatha", + "na_st\u00e0itean_aonaichte", + "na_h_aimearagan", + "an_ear_mheadhan", + "an_ear_mheadhanach", + "ameireaganach", + "am_muir_dubh", + "na_h_eileanan_f\u00e0clainn" + ], + "FOOD": [ + "marag", + "brisg", + "pastra" + ], + "PERSON_PRONOUN": [ + "i", + "agamsa", + "me" + ], + "RELIGION_MEMBER": [ + "cuaigear", + "abstol" + ], + "TITLE": [ + "a_bh", + "sir", + "maighstir" + ], + "FAC": [ + "ionad_bh\u00f9than", + "mall", + "oifis_a'phuist", + "naomh_l\u00f9isia" + ], + "RACE": [ + "sasannaich", + "afragach", + "innseanach", + "frangach" + ], + "SOC_ECO_CLASS": [ + "samurai", + "clas_obrach" + ], + "DATE": [ + "thall", + "an_earar", + "lusa" + ], + "QUANTITY": [ + "g", + "tr\u00ec_mheudach" + ], + "POLITICAL_PARTY": [ + "saothair" + ], + "POLITICAL_PARTY_MEMBER": [ + "comannach", + "co_mhaoineach" + ], + "UNION": [ + "aonadh_obrach" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "nighean": "balach", + "nighneag": "balach", + "n\u00econag": "gille", + "ban_di\u00f9c": "di\u00f9c", + "ban_\u00ecmpire": "ceusair", + "banail": "fireannta", + "boireannach": "mac_an_duine", + "caileag": "balach", + "nighean_mhic": "mac_ighne", + "nighean_ighne": "mac_ighne", + "ban_ogha": "mac_ighne", + "bana_ghaisgeach": "laoch", + "bean_uasal": "tighearna", + "baintighearna": "tighearna", + "gruagach": "gille", + "r\u00ecbhinn": "balach", + "rach_iomrall": "sir", + "m\u00e0thair": "athair", + "a_bh": "mgr", + "bean_chr\u00e0bhaidh": "manach", + "cailleach_dhubh": "manach", + "bana_phrionnsa": "flath", + "banrigh": "r\u00ecgh", + "s\u00f2r": "br\u00e0thair", + "piuthar": "br\u00e0thair", + "bana_bhuidseach": "buidseach", + "seana_mhaighdeann": "fleasgach", + "leas_nighean": "mac_c\u00e8ile", + "leas_mh\u00e0thair": "leas_athair", + "muime": "leas_athair", + "maighdeann_frithealaidh": "gille_frithealaidh", + "bean": "mac_an_duine", + "bean_ch\u00e8ile": "fear_p\u00f2sda", + "bean_ph\u00f2sda": "fear_p\u00f2sda", + "wicca": "draoidh", + "cailleach": "draoidh", + "ban_draoidh": "draoidh", + "buidseach": "draoidh", + "seun": "nighean", + "balachan": "nighneag", + "gille": "n\u00econag", + "balach": "nighneag" + }, + "other_gender_swap": {}, + "en_pronoun2gender": { + "they": [ + "g\u00e8idh", + "d\u00e0_mhiannach", + "co_ghn\u00e8itheach", + "d\u00e0_ghn\u00e8itheach", + "co_she\u00f2rsach", + "tar_ghn\u00e8itheach" + ], + "he": [ + "balachan", + "fireannta", + "balach", + "duine_uasal", + "seun", + "mac_an_duine", + "gille" + ], + "she": [ + "boireannach", + "n\u00econag", + "rach_iomrall", + "nighean", + "\u00f2igh", + "banail", + "bean", + "bean_uasal", + "caileag", + "ainnir", + "r\u00ecbhinn", + "baintighearna", + "nighneag", + "gruagach" + ] + }, + "en_pronoun2pronoun": { + "they": [ + "aca", + "iad", + "iadsan" + ], + "it": [ + "iad_seo" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/gl.json b/data_tooling/pii_processing/ontology/data/gl.json new file mode 100644 index 0000000..b3c55dc --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/gl.json @@ -0,0 +1,2039 @@ +{ + "PUBLIC_FIGURE": [ + "lawrence_durrell", + "la_tour", + "henry_cavendish", + "matthew_arnold", + "lev_ivanov", + "benjamin_franklin", + "martin_buber", + "john_bartlett", + "karl_gjellerup", + "akira_kurosawa", + "frances_wright", + "maria_tallchief", + "noah_webster", + "jean_genet", + "john_knox", + "heinrich_hertz", + "roger_williams", + "le_duc_tho", + "giovanni_boccaccio", + "cornelius_vanderbilt", + "rudolf_steiner", + "thomas_wolfe", + "ernesto_guevara", + "thomas_bayes", + "ben_hogan", + "johann_bernoulli", + "max_bruch", + "leonard_bernstein", + "alistair_cooke", + "che_guevara", + "charles_townes", + "georges_simenon", + "c", + "alan_seeger", + "i_a_richards", + "ren\u00e9_descartes", + "thomas_hodgkin", + "augustin_fresnel", + "john_barth", + "edward_albee", + "dorothy_parker", + "maria_callas", + "victor_herbert", + "william_walton", + "henrik_ibsen", + "william_gladstone", + "mary_shelley", + "franz_werfel", + "marcello_malpighi", + "peter_lorre", + "karl_baedeker", + "david_livingstone", + "eduard_buchner", + "david_smith", + "john_herschel", + "andrzej_wajda", + "jan_van_eyck", + "carl_rogers", + "george_balanchine", + "georg_wilhelm_steller", + "richard_burton", + "douglas_macarthur", + "james_michener", + "mary_wollstonecraft", + "lamberto", + "j_edgar_hoover", + "thomas_reid", + "o_holand\u00e9s_voador", + "john_jacob_astor", + "anna_pavlova", + "winston_churchill", + "diplomatura", + "johannes_diderik_van_der_waals", + "giambattista_marini", + "b", + "conrad_aiken", + "karl_landsteiner", + "ivan_pavlov", + "dmitri_shostakovich", + "paul_mccartney", + "richard_smalley", + "andrew_marvell", + "terry_pratchett", + "k", + "stephen_king", + "francis_crick", + "john_trumbull", + "topete", + "joseph_greenberg", + "isaac_newton", + "richard_upjohn", + "alfred_eisenstaedt", + "victor_hugo", + "joseph_smith", + "edwin_hubble", + "milton_friedman", + "amy_lowell", + "mui\u00f1eiro", + "edward_gibbon", + "jefferson_davis", + "cass_gilbert", + "george_stephenson", + "john_glenn", + "john_webster", + "john_davis", + "george_burns", + "bakunin", + "george_harrison", + "peter_minuit", + "george_orwell", + "maximiano", + "arthur_koestler", + "richard_wagner", + "joseph_john_thomson", + "thornton_wilder", + "e_l_doctorow", + "pancho_villa", + "aleksandr_borodin", + "leopold_stokowski", + "rebecca_west", + "o_enxe\u00f1oso_fidalgo_don_quixote_da_mancha", + "marie_curie", + "francis_galton", + "mary_martin", + "michael_jackson", + "louis_jolliet", + "carl_sandburg", + "alexander_i", + "thomas_hobbes", + "joseph_lister", + "edward_weston", + "el_greco", + "roberto", + "samuel_beckett", + "david", + "galileo_galilei", + "ernest_bevin", + "jane_goodall", + "der_fliegende_holl\u00e4nder", + "john_donne", + "chaim_weizmann", + "andrea_guarneri", + "robert_koch", + "i_m_pei", + "joseph_goebbels", + "george_eastman", + "john_steinbeck", + "erich_mendelsohn", + "baldu\u00edno", + "edmund_hillary", + "vincent_van_gogh", + "richard_hooker", + "w", + "william_hazlitt", + "marie_stopes", + "anne_boleyn", + "john_ruskin", + "robert_burns", + "john_henry", + "hans_albrecht_bethe", + "carl_anderson", + "thomas_paine", + "bari", + "francis_beaumont", + "steven_weinberg", + "p", + "mary_pickford", + "hans_fischer", + "emiliano_zapata", + "karl_barth", + "yuri_gagarin", + "willem_einthoven", + "constantino", + "phil_anderson", + "marco_aurelio", + "thomas_willis", + "bernard_malamud", + "samuel_johnson", + "allen_iverson", + "marie_antoinette", + "anne_hutchinson", + "louise_nevelson", + "giuseppe_verdi", + "walter_lippmann", + "edward_appleton", + "e", + "karl_jaspers", + "beethoven", + "hideki_yukawa", + "konrad_adenauer", + "john_l_lewis", + "marianne_moore", + "norbert_wiener", + "john_masefield", + "horatio_nelson", + "mark_rothko", + "maurice_chevalier", + "gottlieb_daimler", + "catarina", + "frank_sinatra", + "e_as\u00ed_por_diante", + "abel_tasman", + "katharine_hepburn", + "henri_becquerel", + "henri_matisse", + "bertram_brockhouse", + "louis_pasteur", + "j", + "richard_strauss", + "stephen_decatur", + "leslie_howard", + "hugo_grotius", + "o_holand\u00e9s_errante", + "mahalia_jackson", + "ben_shahn", + "john_ford", + "stephen_foster", + "alphonse_bertillon", + "katherine_mansfield", + "gertrude_stein", + "j_b_s_haldane", + "sarah_bernhardt", + "v", + "philip_marlowe", + "luigi_pirandello", + "t_s_eliot", + "e_g_marshall", + "marc_blitzstein", + "hank_williams", + "rube_goldberg", + "dorothea_lange", + "james_thurber", + "charles_de_gaulle", + "paul_von_hindenburg", + "y", + "henry_moore", + "mary_mallon", + "ralph_bunche", + "rudolf_bultmann", + "charles_lindbergh", + "vincenzo_bellini", + "samuel_barber", + "tobias_smollett", + "f", + "john_jay", + "ludwig_wittgenstein", + "august_strindberg", + "thomas_mann", + "alla_nazimova", + "charles_goodyear", + "dante_alighieri", + "margot_fonteyn", + "peter_pan", + "james_tobin", + "john_irving", + "giacomo_puccini", + "edward_fitzgerald", + "fridtjof_nansen", + "louis_braille", + "herbert_marcuse", + "mungo_park", + "benedict_arnold", + "hercio", + "paul_verlaine", + "q", + "james_dean", + "richard_lovelace", + "marie_tussaud", + "roger_bannister", + "theodor_schwann", + "max_beerbohm", + "alessandro_manzoni", + "joseph_priestley", + "robert_oppenheimer", + "nicolas_poussin", + "andrea_mantegna", + "adolf_windaus", + "joseph_pulitzer", + "ring_lardner", + "george_huntington", + "charles_schulz", + "james_naismith", + "oscar_wilde", + "philip_roth", + "j_d_salinger", + "henry", + "richard_trevithick", + "william_bradford", + "heinrich_schliemann", + "eli_whitney", + "glenn_curtiss", + "laurence_olivier", + "pierre_larousse", + "christiaan_eijkman", + "gustavo", + "adolf_eichmann", + "marilyn_horne", + "personaxe_imaxinaria", + "stan_musial", + "xerez", + "francis_bacon", + "pete_seeger", + "john_wycliffe", + "joseph_heller", + "a", + "morris", + "saladino", + "norman_rockwell", + "boris_spassky", + "james_brown", + "william_hogarth", + "charles_baudelaire", + "luigi_cherubini", + "david_ricardo", + "john_mitchell", + "henri_labrouste", + "mary_leakey", + "charlie_parker", + "z", + "immanuel_kant", + "james_franck", + "william_crookes", + "charles_de_montesquieu", + "james_meredith", + "samuel_gompers", + "nellie_bly", + "alexandre_yersin", + "n", + "marco_antonio", + "stephen_leacock", + "albert_schweitzer", + "john_harvard", + "johann_friedrich_herbart", + "giulio_natta", + "subnormal", + "johannes_kepler", + "anatoli_karpov", + "sergei_rachmaninov", + "william_s_burroughs", + "david_hartley", + "max_planck", + "william_blake", + "t_e_lawrence", + "julio_iglesias", + "john_bardeen", + "sarah_vaughan", + "john_wilkes", + "william_byrd", + "william_henry", + "christopher_fry", + "xurxo_de_capadocia", + "scott_joplin", + "samuel_houston", + "carl_lewis", + "sarah_siddons", + "george_vancouver", + "canberra", + "elias_canetti", + "robert_lowell", + "johann_strauss", + "edward_jenner", + "john_mercer", + "oscar_robertson", + "oliver_hardy", + "cole_porter", + "benjamin_west", + "jean_luc_godard", + "graham_greene", + "frans_hals", + "lars_onsager", + "margaret_mitchell", + "igor_stravinsky", + "stuart_davis", + "lola_montez", + "jan_swammerdam", + "mary_mccarthy", + "david_riesman", + "john_walker", + "william_herschel", + "joseph_black", + "marcus_whitman", + "mikhail_baryshnikov", + "montesquieu", + "arthur_rubinstein", + "arthur_compton", + "niels_bohr", + "sergei_rachmaninoff", + "kenneth_grahame", + "henry_fielding", + "bertrand_russell", + "katherine_anne_porter", + "michael_faraday", + "john_d_rockefeller", + "anthony_burgess", + "jan_tinbergen", + "robert_venturi", + "johnny_appleseed", + "irving_berlin", + "bernard_baruch", + "rudolf_diesel", + "hans_holbein", + "walt_disney", + "ben_jonson", + "la_spezia", + "tom\u00e9", + "constantin_stanislavski", + "robert_benchley", + "joseph_schumpeter", + "gabriel_lippmann", + "steve_reich", + "benny_goodman", + "ted_williams", + "william_beaumont", + "friedrich_engels", + "jane_austen", + "charles_laughton", + "gustav_mahler", + "ed_sullivan", + "alice_paul", + "robert_redford", + "jean_giraudoux", + "jack_dempsey", + "brindisi", + "ian_fleming", + "richard_feynman", + "wolfgang_pauli", + "theodore_dreiser", + "theodor_mommsen", + "andrew_huxley", + "marcel_proust", + "jessica_mitford", + "thomas_more", + "homo_heidelbergensis", + "paul_hindemith", + "elizabeth_taylor", + "thomas_chippendale", + "anne_sullivan", + "paul_robeson", + "thomas_middleton", + "john_dowland", + "daniel_jones", + "william_golding", + "robert_motherwell", + "william_caxton", + "john_milton", + "rudolf_serkin", + "peter_stuyvesant", + "ethel_merman", + "samuel_adams", + "albert_speer", + "james_baldwin", + "john_vanbrugh", + "indira_gandhi", + "william_mitchell", + "jane_seymour", + "george_gershwin", + "alberto_giacometti", + "mostea", + "e_t_a_hoffmann", + "frank_whittle", + "alfred_nobel", + "jesse_owens", + "daniel_rutherford", + "marco_polo", + "john_fletcher", + "caravaggio", + "m", + "charlotte_corday", + "marcel_marceau", + "allen_ginsberg", + "fred_zinnemann", + "daniel_bernoulli", + "guillaume_apollinaire", + "william_strickland", + "antoine_watteau", + "joseph_henry", + "henri_bergson", + "edward_macdowell", + "josef_hoffmann", + "boris_karloff", + "pierre_corneille", + "phillis_wheatley", + "patrick_white", + "saul_steinberg", + "bartholomew_roberts", + "eileen_farrell", + "catherine_howard", + "hans_christian_andersen", + "peter_cooper", + "william_morris", + "cary_grant", + "hideyo_noguchi", + "isaac_watts", + "illa_de_san_marti\u00f1o", + "pieter_zeeman", + "glenn_miller", + "pablo_picasso", + "suicidarse", + "marian_anderson", + "natalie_wood", + "l_ron_hubbard", + "thomas_moore", + "kurt_weill", + "otto_hahn", + "christian_huygens", + "john_marshall", + "christiaan_huygens", + "hector_berlioz", + "lucille_ball", + "paul_simon", + "claudio_monteverdi", + "rubinstein", + "robert_scott", + "john_galsworthy", + "robert_robinson", + "o", + "adam_smith", + "william_james", + "u", + "jean_harlow", + "henry_miller", + "karl_marx", + "paul_bunyan", + "friedrich_nietzsche", + "i", + "pedro", + "robert_indiana", + "jimmy_durante", + "john_wesley", + "sandro_botticelli", + "carson_mccullers", + "seiji_ozawa", + "nikola_tesla", + "al_capone", + "jim_bowie", + "charles_barkley", + "billy_graham", + "robert_schumann", + "mel_gibson", + "le_corbusier", + "carlo_goldoni", + "john_locke", + "alexis_carrel", + "mar\u00eda_antonieta_de_austria", + "joseph_marie_jacquard", + "henry_james", + "stephen_sondheim", + "lorenz_hart", + "robert_bartlett", + "helen_keller", + "paul_dukas", + "ingrid_bergman", + "leonard_bloomfield", + "jane_jacobs", + "jean_piaget", + "william_congreve", + "franz_kline", + "henri_rousseau", + "paul_tillich", + "hilaire_belloc", + "frank_norris", + "pieter_brueghel", + "frank_stella", + "robert_southey", + "valentina_tereshkova", + "h_g_wells", + "walt_whitman", + "william_wyler", + "john_osborne", + "colin_powell", + "ludwig_boltzmann", + "carl_nielsen", + "carl_jung", + "leopold_kronecker", + "richard_wright", + "benjamin_thompson", + "adolf_hitler", + "maria_mitchell", + "fritz_haber", + "archibald_macleish", + "peter_behrens", + "john_tradescant", + "alfred_stieglitz", + "joseph_haydn", + "stephen_spender", + "garfield", + "george_boole", + "paul_revere", + "daniel_boone", + "buffalo_bill", + "edvard_grieg", + "robert_boyle", + "arthur_laffer", + "edith_cavell", + "san_patricio", + "alan_paton", + "benedito", + "ralph_richardson", + "1", + "cordell_hull", + "james_wilson", + "rosa_parks", + "norman_jewison", + "samuel_goldwyn", + "x", + "ernest_walton", + "vladimir_putin", + "giuseppe_mazzini", + "jim_thorpe", + "hertz", + "h", + "randall_jarrell", + "arnold_sch\u00f6nberg", + "laurence_sterne", + "jacqueline_cochran", + "george_fox", + "ben_hecht", + "christopher_isherwood", + "fritz_kreisler", + "anne_hathaway", + "david_garrick", + "don_budge", + "bill_russell", + "baldwin", + "jeannette_rankin", + "clarence_darrow", + "charles_lamb", + "g", + "henrio", + "arthur_schopenhauer", + "thomas_dekker", + "lourenzo", + "james_cagney", + "john_keble", + "johns_hopkins", + "henri_pitot", + "wanda_landowska", + "martin_heidegger", + "hans_eysenck", + "estar_calado", + "muller", + "r", + "george_lucas", + "andrew_jackson", + "edith_wharton", + "louis_armstrong", + "antony_tudor", + "steven_spielberg", + "jean_monnet", + "d_w_griffith", + "robert_fulton", + "thomas_hardy", + "eddie_rickenbacker", + "thomas_gainsborough", + "franz_ferdinand", + "giuseppe_garibaldi", + "philip_warren_anderson", + "fra_filippo_lippi", + "alexandre_dumas", + "philipp_melanchthon", + "robert_brown", + "thomas_carlyle", + "johann_gutenberg", + "donald_barthelme", + "william_tyndale", + "tamara_karsavina", + "bobby_fischer", + "johannes_gutenberg", + "i_latino", + "barrymore", + "d", + "james_bowie", + "thomas_malthus", + "giambattista_marino", + "gaetano_donizetti", + "castro", + "william_faulkner", + "edward_white", + "amerigo_vespucci", + "arthur_holmes", + "pierre_boulez", + "hans_adolf_krebs", + "girolamo_savonarola", + "emma_goldman", + "francis_poulenc", + "james_ussher", + "john_barrymore", + "john_constable", + "james_mill", + "putin", + "matthew_flinders", + "robert_herrick", + "joseph_campbell", + "jean_de_la_fontaine", + "robert_hooke", + "o_henry", + "karl_popper", + "san_lu\u00eds_de_francia", + "coleman_hawkins", + "john_calvin", + "george_sand", + "peter_sellers", + "homo_rhodesiensis", + "charles_fourier", + "henry_clay", + "peter_o'toole", + "joseph_conrad", + "edmund_halley", + "william_shockley", + "peter_paul_rubens", + "mahatma_gandhi", + "jim_morrison", + "jules_verne", + "paul_newman", + "robert_mills", + "george_meredith", + "robert_morris", + "lili\u02bbuokalani", + "woody_herman", + "alexander_wilson", + "josef_albers", + "jackson_pollock", + "john_lennon", + "andrea_palladio", + "mar\u00eda_madalena", + "bob_woodward", + "charlie_chaplin", + "lillian_russell", + "d_h_lawrence", + "edward_morley", + "j_m_barrie", + "thomas_malory", + "lea", + "john_brown", + "al_jolson", + "elizabeth_gaskell", + "hugo_junkers", + "maurice_barrymore", + "piscis_austrinus", + "norman_thomas", + "lillian_hellman", + "brescia", + "henrique", + "thomas_merton", + "abanqueiro", + "asa_gray", + "hannah_arendt", + "antonio_stradivari", + "robinson_jeffers", + "alice_walker", + "miles_davis", + "rupert", + "james_parkinson", + "george_marshall", + "harold_nicolson", + "jesse_jackson", + "willa_cather", + "san_xurxo", + "stanley_kubrick", + "camberra", + "john_deere", + "john_huston", + "robert_merton", + "dorothy_crowfoot", + "jean_baptiste_joseph_fourier", + "william_gilbert", + "james_watt", + "jonathan_edwards", + "ronald_reagan", + "helmut_schmidt", + "jenny_lind", + "homo", + "frederick_douglass", + "la_rochefoucauld", + "david_hilbert", + "wilhelm_reich", + "william_thornton", + "roman_jakobson", + "oliver_cromwell", + "lionel_hampton", + "martin_luther_king", + "james_hargreaves", + "frank_capra", + "william_wordsworth", + "rex_harrison", + "s", + "william_clark", + "woodrow_wilson", + "william_wycherley", + "margaret_sanger", + "san_marti\u00f1o", + "gustav_hertz", + "george_mason", + "el_cid", + "edgar_wilson", + "st_louis", + "richard_rodgers", + "don_quixote", + "illa_de_san_cristovo", + "anne_sexton", + "morgana", + "john_dryden", + "jim_henson", + "b\u00e9la_lugosi", + "ernest_hemingway", + "john_eccles", + "george_westinghouse", + "aquila", + "jacques_charles", + "eero_saarinen", + "arthur_miller", + "john_cheever", + "friedrich_wilhelm_bessel", + "gracie_allen", + "nelson_mandela", + "baldovino", + "heinrich_himmler", + "al_gore", + "john_rutledge", + "hans_bethe", + "hans_geiger", + "cesare_borgia", + "roald_amundsen", + "carami\u00f1ola", + "sherwood_anderson", + "richard_leakey", + "alfred_korzybski", + "charles_dickens", + "sean_o'casey", + "samuel_huntington", + "ella_fitzgerald", + "fats_waller", + "jakob_bernoulli", + "thomas_sydenham", + "alois_senefelder", + "george_enescu", + "wallace_carothers", + "jacques_offenbach", + "joseph_paxton", + "william_curtis", + "william_chambers", + "george_stevens", + "federico_fellini", + "bessie_smith", + "patrick_henry", + "willy_brandt", + "charles_wilkes", + "francisco_pizarro", + "francisco_franco", + "ap\u00f3stolo_tom\u00e9", + "jackie_robinson", + "bernardo_bertolucci", + "king_oliver", + "jan_steen", + "frank_harris", + "john_ross", + "pedro_papa", + "philibert_delorme", + "hans_arp", + "andrew_carnegie", + "gregorio", + "franz_schubert", + "johnny_cash", + "joseph_mccarthy", + "alfred_kastler", + "mick_jagger", + "otto_loewi", + "charles_peirce", + "georges_cuvier", + "william_harvey", + "walter_scott", + "peter_medawar", + "vladimir_lenin", + "sam_houston", + "robert_peary", + "mui\u00f1eira", + "robert_browning", + "alessandro_farnese", + "ralph_ellison", + "john_bunyan", + "jonathan_swift", + "walter_gropius", + "mari\u00f1eira", + "albert_einstein", + "l", + "aletta_jacobs", + "thomas_edison", + "chiang_kai_shek", + "claude_bernard", + "raymond_chandler", + "guedello", + "henry_purcell", + "t", + "wilhelm_ostwald" + ], + "SOC_ECO_CLASS": [ + "trade", + "fraternidade", + "labor", + "da_clase_media", + "nobreza", + "samurai", + "campesi\u00f1ado", + "clase_media", + "de_clase_alta", + "de_clase_baixa", + "proletariado", + "clase_alta", + "picara\u00f1a", + "academia", + "burgues\u00eda" + ], + "LOCATION": [ + "al_jazeera", + "la_plata", + "mar_tirreno", + "estados_unidos", + "san_patricio", + "mar_da_china_oriental", + "san_vicente", + "goberno_dos_estados_unidos_de_am\u00e9rica", + "noitevella", + "corpus_christi", + "piet_mondrian", + "santa_fe", + "sint_maarten", + "cristovo_col\u00f3n", + "de_nada", + "al_jazira", + "lebreiros", + "peto_negro", + "huang_he", + "goberno_americano", + "na_r\u00faa", + "asemblea_nacional_de_polonia", + "joseph_louis_gay_lussac", + "mar_do_norte", + "goberno_dos_eua", + "a_bela_dormente", + "australia_occidental", + "on_the_road", + "mar_negro", + "mar_amarelo", + "polgari\u00f1o", + "o_novo_mundo", + "sri_lanka", + "de_auga_doce", + "the_rolling_stones", + "estados_unidos_de_am\u00e9rica", + "homenaxe", + "pai_nadal", + "forzas_a\u00e9reas", + "am\u00e9rico_vespucio", + "forza_a\u00e9rea", + "illa_de_san_vicente", + "patricio_de_irlanda", + "ex\u00e9rcito_dos_estados_unidos", + "heitor_villa_lobos", + "louis_joseph_gay_lussac", + "goberno_dos_estados_unidos", + "santa_claus", + "pieter_mondrian" + ], + "DISEASE": [ + "catalepsia", + "arrefriado", + "peste_bub\u00f3nica", + "filovirus", + "polio", + "lique", + "salucio", + "amigdalite", + "salmonelose", + "engadir", + "vinchoca", + "xinecomastia", + "salmonela", + "esterilidade", + "moldear", + "als", + "tanatofobia", + "androfobia", + "feila", + "carrabouxa", + "queimadura", + "parada_cardiorrespiratoria", + "rebanda", + "parvo", + "escofar", + "minusval\u00eda", + "andazo", + "triquinose", + "energy", + "frenes\u00ed", + "andaxe", + "beriberi", + "borracheira", + "the_bends", + "eslasar", + "succus", + "phytophthora_infestans", + "cardite", + "xoanete", + "la_naus\u00e9e", + "xenxivite", + "teratoma", + "pate\u00f1o", + "bruzo", + "para", + "la_peste", + "xigantismo", + "traumatismo", + "contusi\u00f3n", + "radiaci\u00f3n", + "carranas", + "ripar", + "farnes\u00eda", + "mazadura", + "espurrar", + "estrabismo", + "rubor", + "escarlatina", + "qi", + "embriaguez", + "listeriose", + "carb\u00fanculo", + "claustrofobia", + "autoinmunidade", + "michazo", + "saluco", + "gimp", + "indixesti\u00f3n", + "sarm", + "abasia", + "hernia", + "alexia", + "herpes", + "poliomielite", + "raspi\u00f1ar", + "toler\u00eda", + "paix\u00f3n", + "analxesia", + "escr\u00f3fula", + "inmunodeficiencia", + "farinxite", + "pica", + "tiriz\u00f3", + "espulla", + "mastoidite", + "avermellamento", + "inanici\u00f3n", + "parestesia", + "espermatocele", + "paludismo", + "almorr\u00e1", + "a_peste", + "subalimentaci\u00f3n", + "raiba", + "espirro", + "the_passion_of_the_christ", + "zambro", + "rubideza", + "sarampelo", + "vasculite", + "tose", + "beliscar", + "carrand\u00e1n", + "o_golpe", + "xiard\u00edase", + "ananismo", + "fraguar", + "lambetada", + "carrancholas", + "aura", + "escoliose", + "deshidrataci\u00f3n", + "virus_animal", + "sotelo", + "gripe_porcina", + "anemia_drepanoc\u00edtica", + "fundador", + "quecer", + "bullaco", + "trauma", + "salouco", + "quentar", + "the_hives", + "a_vinganza_de_moctezuma", + "dengue", + "bullaca", + "colecistite", + "esquistosomiase", + "a_praga", + "laceraci\u00f3n", + "rabiar", + "verruga", + "vincha", + "tenrura", + "freila", + "trambull\u00f3n", + "ardent\u00eda", + "malaria" + ], + "RACE": [ + "filipino", + "africano", + "\u00e1rabes", + "paquistan\u00ed", + "suramericana", + "suramericano", + "africana", + "the_mexican", + "francesa", + "primixenio", + "negro", + "latina", + "amerindio" + ], + "JOB": [ + "cabedel", + "tallista", + "puxilista", + "microbi\u00f3logo", + "borrallo", + "sancrist\u00e1n", + "camar\u00f3grafo", + "o_maquinista", + "call\u00f3n", + "presidenta", + "arrocheiro", + "baleeiro", + "ama_de_chaves", + "cart\u00f3grafo", + "agrimensor", + "potter", + "perruqueiro", + "masa_fermentada", + "artes\u00e1n", + "carpinteira", + "peiteador", + "luthier", + "cuestor", + "neur\u00f3loga", + "senescal", + "fundador", + "distribuidor", + "caporal", + "caldeireiro", + "the_police", + "xinec\u00f3logo", + "compositor", + "adestrador", + "pretor", + "a_nanny", + "entallador", + "picheleiro", + "the_musketeer", + "suboficial", + "territorial", + "para", + "router", + "titor", + "temoneiro", + "alguacil", + "parteira", + "mercador", + "coleccionista", + "inventor", + "danzar\u00edn", + "leiteiro", + "cerralleiro", + "pedreiro", + "mari\u00f1eira", + "alcaldesa", + "portador", + "granxeiro", + "carpinteiro", + "dermat\u00f3logo", + "mensaxeiro", + "kamikaze", + "mui\u00f1eiro", + "ferradora", + "modisto", + "condest\u00e1bel", + "novelista", + "coudel", + "sculptor", + "palaciano", + "mui\u00f1eira", + "alcalde", + "the_guardian", + "falante", + "maxistrado", + "microbi\u00f3loga", + "mariscal", + "neur\u00f3logo", + "concelleiro", + "proc\u00f3nsul", + "tesoureiro", + "adail", + "comediante", + "catedr\u00e1tico", + "mate", + "ebanista", + "cardi\u00f3logo", + "hidr\u00f3logo", + "limpador", + "pastor", + "barrister", + "trallada", + "bombeiro", + "tenente", + "corporal", + "internista", + "rabino", + "carteiro", + "coronel", + "hemat\u00f3logo", + "decapante", + "de_temporada", + "familiar", + "rastrexador", + "campesi\u00f1o", + "sepulteiro", + "toller", + "principal", + "departamento_executivo", + "man", + "armeiro", + "albanel", + "forraxe", + "marine", + "neurocirurxi\u00e1n", + "apoplex\u00eda", + "fontaneiro", + "usher", + "messenger", + "endocrin\u00f3logo", + "cox", + "panadeiro", + "the_interpreter", + "servizo_dom\u00e9stico", + "corsario", + "formador", + "mari\u00f1o", + "tendeiro", + "bailador", + "sub", + "xastre", + "avogado", + "guerreira", + "cookie", + "cineasta", + "esquire", + "obreiro", + "debuxante", + "toneleiro", + "comadroa", + "regular", + "marmit\u00f3n", + "autor", + "ferrador", + "pirag\u00fcista" + ], + "PLANT": [ + "pyracantha", + "estruga", + "labaza", + "lycium_barbarum", + "corticeira", + "caiota", + "maracux\u00e1", + "teixoeira", + "matacandil", + "teixo", + "xinkgo", + "sobreira", + "the_joshua_tree", + "xenebreiro", + "magnolio", + "vimbieira", + "s\u00e1ndalo", + "liquid\u00e1mbar", + "lentisco", + "engo", + "ortiga", + "marroxo", + "amanita", + "arabidopsis_thaliana", + "epipremnum_aureum", + "ruxideira", + "brimial", + "col_chinesa", + "cerefolio", + "estripo", + "corni\u00f1os", + "negundo", + "pleuroto", + "sic\u00f3moro", + "madeirudo", + "esteva", + "alcanfor", + "lamargueiro", + "cortadeira", + "avea_bouba", + "candida_albicans", + "rebentabois", + "schinus_terebinthifolius", + "lodoeiro", + "armol", + "abeneiro", + "muruxa", + "madreselva", + "moreira_branca", + "col_de_savoia", + "panqueixo", + "ambru\u00ed\u00f1a", + "feix\u00f3n", + "reseda", + "coliflor", + "cerdeira", + "rillamachos", + "remolacha", + "cancereixo", + "macadamia_tetraphylla", + "sufreiro", + "carall\u00e1n", + "cerollo", + "agana", + "gabanceira", + "mirasol", + "sendeiri\u00f1a", + "mostaza_branca", + "planta_acu\u00e1tica", + "gati\u00f1a", + "\u00e1rbore_de_nadal", + "correola", + "canfreixo", + "ervellaca", + "nonmesquezas", + "col_de_bruxelas", + "phytophthora_infestans", + "sorbeira", + "herba_belida", + "escornacabras", + "amieiro", + "planta_carn\u00edvora", + "nogueira", + "xilbarbeira", + "laderno", + "citomembrana", + "solanum", + "beladona", + "conv\u00f3lvulo", + "bergamoteira", + "guindeira", + "lampaza", + "chirimoio", + "crisantemo", + "ameneiro", + "melisa", + "mostaza", + "salgueiro", + "papoula", + "pradio", + "repolo", + "trogalleiro", + "pementeira", + "sabina", + "arum", + "saccharomyces_cerevisiae", + "durmideira", + "cereixa", + "abeloura", + "marathi", + "eixola", + "luceiros", + "casti\u00f1eiro_americano", + "castiro", + "verbasco", + "carnabudo", + "capudre", + "alcanforeiro", + "santa_mar\u00eda", + "edelweiss", + "escambr\u00f3n", + "clem\u00e1tide", + "loderno", + "capudrio", + "silvarda", + "c\u00e1ncaro", + "ballico", + "gomarresina", + "pradairo", + "segorella", + "casti\u00f1eiro", + "castanea", + "mentraste", + "saltasebes", + "hidr\u00f3fito", + "raponcio", + "dicksonia_antarctica", + "magnolia", + "esprego", + "fari\u00f1ento", + "leituga" + ], + "RELIGION_MEMBER": [ + "cristi\u00e1n", + "budista", + "sunnita", + "cristi\u00e1", + "presbiteriano", + "baptista", + "franciscano", + "parsi", + "metodista", + "xesu\u00edta", + "mahometano" + ], + "FAC": [ + "a_derradeira_cea", + "igrexa_cat\u00f3lica", + "a_\u00faltima_cea", + "arnold_sch\u00f6nberg", + "saint_joseph", + "santiago_ap\u00f3stolo", + "este_ser\u00e1n", + "igrexa_cat\u00f3lica_romana", + "esta_tarde", + "aos_poucos", + "comisar\u00eda", + "santa_luc\u00eda", + "pedro_i_de_rusia", + "xos\u00e9_de_nazaret" + ], + "ANIMAL": [ + "can_de_caza", + "estrixiformes", + "perc\u00eddeos", + "can_menor", + "voitre", + "esqu\u00edo", + "toni\u00f1a", + "peneiri\u00f1o", + "cachalote", + "sapo", + "carroucha", + "chibato", + "avetarda", + "arroaz", + "malv\u00eds", + "carrapucho", + "nespreiro", + "artr\u00f3podos", + "cascuda", + "peto_verde", + "aie_aie", + "billy_elliot", + "pigargo", + "abadexo", + "chorva", + "moucho", + "canis_minor", + "manta", + "cornella", + "perisod\u00e1ctilos", + "centolo", + "sanmarti\u00f1o", + "paporroibo", + "pisces", + "malacopterixio", + "arnelo", + "caxato", + "communis", + "anuro", + "carei", + "carr\u00e1n", + "cirr\u00edpedes", + "rata_de_auga", + "artiod\u00e1ctilos", + "vichelocrego", + "alcandorca", + "narcexa", + "virus_do_mosaico_do_tabaco", + "salientio", + "torcaza", + "aguaneta", + "vacaloura", + "galgo", + "coral_precioso", + "av\u00e9spora", + "garzota", + "robaliza", + "lagostino", + "holoturoideos", + "gran_simio", + "gatafornela", + "candorca", + "denoci\u00f1a", + "pedunculados", + "chibardo", + "zancuda", + "picapeixe", + "avespeiro", + "zamborca", + "pernalonga", + "lagarteiro", + "paporrubio", + "garzas", + "ghaldaripo", + "pincaouro", + "peneireiro", + "perc\u00eddeo", + "acantopterixios", + "leir\u00f3n_rabudo", + "tour\u00f3n", + "tele\u00f3steo", + "rata_negra", + "sable", + "cullerete", + "can_de_auga", + "escacho", + "catarrinos", + "pardal", + "percebe", + "cobaia", + "loberno", + "barbantesa", + "falc\u00f3n", + "lince", + "actiniarios", + "quebraosos", + "couza", + "cabiro", + "xibardo", + "mexill\u00f3n", + "gardu\u00f1a", + "avespa", + "picacrega", + "quelonioideos", + "avesporeiro", + "eagle", + "ouriolo", + "picaza", + "curuxa", + "mi\u00f1ato", + "teixugo", + "picoteiro", + "chalra", + "cabeleira", + "escornabois", + "avelaiona", + "lagaria" + ], + "FOOD": [ + "xantar", + "alta_coci\u00f1a", + "requeixo", + "morcela", + "churume", + "nata_montada", + "postre", + "bechamel", + "arroz_fritido", + "nabiza", + "chirume", + "almibre", + "white_russian", + "catchup", + "pinot_noir", + "masa_follada", + "repostar\u00eda", + "lombarda", + "col_galega", + "masa_\u00e1cida", + "almorzo", + "pastelar\u00eda", + "chile", + "prebe", + "pancenteo", + "torromica" + ], + "ORG": [ + "dolorosa", + "drug_enforcement_administration", + "aos_poucos", + "wicca", + "jan_mayen", + "no_lugar", + "comercializaci\u00f3n", + "aa", + "nasa", + "mar_vermello", + "huang_he", + "bollywood", + "schutzstaffel", + "manterse_informado", + "the_who", + "san_tom\u00e9_san_tom\u00e9_e_pr\u00edncipe", + "haganah", + "estados_xerais", + "clase_baixa", + "san_francisco", + "un", + "vangardas", + "andr\u00e9_ap\u00f3stolo", + "de_clase_alta", + "que_pasa", + "escola", + "viceversa", + "asemblea_nacional_de_francia", + "sc", + "the_family_man", + "nanak", + "mahayana", + "l\u00faa_nova", + "john_tuzo_wilson", + "can_tho", + "plexus_celiacus", + "the_faculty", + "don_juan", + "lei_de_conservaci\u00f3n", + "batall\u00f3n", + "armada_invencible", + "dereito_internacional", + "dereito_romano", + "ds", + "ministerio_de_asuntos_exteriores_de_francia", + "casa_branca", + "dia", + "r\u00edo_amazonas", + "manterse", + "bo_proveito", + "partido_socialdem\u00f3crata", + "santa_sof\u00eda", + "a_bela_dormente", + "rabindranath_tagore", + "gestapo", + "santo_andr\u00e9", + "uni\u00f3n_internacional_de_telecomunicaci\u00f3ns", + "dereito_civil", + "santa_helena", + "colexio", + "winnie_the_pooh", + "rangers", + "da_clase_media", + "de_primeira_clase", + "albanelar\u00eda", + "al_jazira", + "quen", + "i_ching", + "polgari\u00f1o", + "saint_joseph", + "al_jazeera", + "xard\u00edn_bot\u00e1nico", + "o_novo_mundo", + "santa_luc\u00eda_caribe", + "po", + "virxe_da_caridade", + "addis_ababa", + "b\u00e1rbara_de_nicomedia", + "hare_krishna", + "the_grapes_of_wrath", + "lago_superior", + "de_abaixo_para_arriba", + "partido_dem\u00f3crata", + "hollywood", + "ursa_major", + "este_ser\u00e1n", + "tribunal_supremo", + "de_clase_baixa", + "saint_barth\u00e9lemy", + "sturmabteilung", + "nato", + "goberno", + "virxe_da_soidade", + "petroleira", + "virxe_da_amargura", + "igrexa_de_cristo_cient\u00edfico", + "by_the_way", + "ciencia_cristi\u00e1", + "igrexa_de_santa_sof\u00eda", + "in_situ", + "st_francis", + "clase_traballadora", + "estar_ao_d\u00eda", + "st_john's", + "spyashchaya_krasavitsa", + "partido_nacionalsocialista_alem\u00e1n_dos_traballadores", + "idade_de_ouro", + "auga_doce", + "streptococcus_pyogenes", + "santa_luc\u00eda", + "eu", + "r\u00edo_amarelo", + "masonar\u00eda", + "fronte_popular", + "a_car\u00f3n", + "cienciolox\u00eda", + "agosti\u00f1o", + "in_fraganti", + "partido_republicano" + ], + "PRODUCT": [ + "astroso", + "the_hunger_games", + "justin_bieber", + "caboverdiano", + "esp\u00edrito_santo", + "al_jazeera", + "nonmesquezas", + "o_can_dos_baskerville", + "o_detective_conan", + "bo_d\u00eda", + "o_se\u00f1or_dos_aneis", + "multiplataforma", + "the_star_spangled_banner", + "santa_mar\u00eda", + "dereitos_humanos", + "don_quixote", + "bo_nadal", + "die_hard", + "boxing_day", + "saxonia_anhalt", + "que_hai_de_novo", + "la_dolce_vita", + "mario_andretti", + "o_gato_con_botas", + "st_george's", + "de_facto", + "la_modification", + "reino_unido", + "xo\u00e1n_bautista", + "a_guerra_das_galaxias", + "cobaia", + "pap\u00e1_noel", + "novo_mesto" + ], + "QUANTITY": [ + "qui\u00f1entos", + "voltampere", + "tonelada", + "calor\u00eda", + "ton", + "won_norcoreano", + "g", + "franco_franc\u00e9s", + "esterlina", + "anders_celsius", + "electronvoltio" + ], + "RELIGION": [ + "zen", + "presbiterianismo", + "manique\u00edsmo", + "catarismo", + "tao\u00edsmo", + "islam", + "calvinismo", + "xinto\u00edsmo", + "wicca" + ], + "LAW": [ + "desacato", + "lei_marcial", + "sufraxio", + "federal_bureau_of_investigation" + ], + "LANGUAGE": [ + "alem\u00e1n", + "venda", + "xavan\u00e9s", + "xapon\u00e9s", + "catal\u00e1n", + "lingua_afric\u00e1ner", + "manx", + "catal\u00e1", + "sundan\u00e9s", + "tailand\u00e9s", + "hindi", + "alviri_vidari", + "acerbaixano", + "zhuang", + "lingua_lingala", + "alem\u00e1", + "esperanto", + "roman\u00e9s", + "coreano", + "hausa", + "cree", + "acerbaixana", + "kikuyu", + "ido", + "marathi", + "quechua", + "checo", + "chichewa", + "bielorrusa", + "tonga", + "tagalo" + ], + "POLITICAL_PARTY": [ + "partido_conservador", + "f\u00f3lkaflokkurin", + "partido_comunista", + "labor", + "partido_progresista", + "partido_popular", + "partido_democr\u00e1tico", + "partido_laborista", + "partido_socialista", + "partido_laborista_australiano", + "partido_dos_traballadores_noruegueses" + ], + "PERSON": [ + "al_gore", + "eu_tam\u00e9n", + "h_g_wells", + "san_vicente", + "i_ching", + "don_delillo", + "edward_osborne_wilson", + "madeirudo", + "les_sueste", + "willard_frank_libby", + "igor_sikorsky", + "carl_david_anderson", + "maxwell_anderson", + "rudolf_hess", + "san_vicente_san_vicente_e_granadinas", + "herbert_george_wells" + ], + "PERSON_PRONOUN": [ + "i_latino", + "un_mesmo", + "i", + "he" + ], + "GENDER": [ + "garela", + "transx\u00e9nera", + "trondia", + "doncela", + "transx\u00e9nero", + "guido", + "man", + "gal" + ], + "GPE": [ + "dar_es_salaam", + "porto_de_monta\u00f1a", + "san_nicolau", + "imperio_alem\u00e1n", + "san_cristovo", + "sint_maarten", + "novo_testamento", + "lu\u00eds_ix_de_francia", + "hagia_sophia", + "san_valent\u00edn", + "r\u00edo_san_lourenzo", + "hagia_sofia", + "gran_canaria", + "san_tom\u00e9_san_tom\u00e9_e_pr\u00edncipe", + "portela", + "mar_exeo", + "santo_andr\u00e9", + "andr\u00e9_ap\u00f3stolo", + "virxe_das_angustias", + "pol\u00edgono_industrial", + "franco_condado", + "mar_vermello", + "al_andalus", + "lu\u00eds_ix_de_francia_o_santo", + "virxe_da_piedade", + "centroam\u00e9rica", + "virxe_das_dores", + "la_gomera", + "st_louis", + "dolorosa" + ], + "TITLE": [ + "sir" + ], + "DATE": [ + "a_toma_da_bastilla", + "era_dixital", + "new_moon", + "asunci\u00f3n_de_mar\u00eda", + "horario_estelar", + "semivida", + "de_\u00faltima_hora", + "corpus_christi" + ], + "ANAT": [ + "arteria_hep\u00e1tica", + "arteria_arcuata", + "tibiosupratarsiano", + "tibialis_anticus" + ], + "EVENT": [ + "gran_premio", + "grand_prix", + "castela_e_le\u00f3n" + ], + "BIO_CHEM_ENTITY": [ + "monoaminooxidase", + "ni_resistente", + "adenosindifosfato", + "alcohol_l\u00e1urico" + ], + "POLITICAL_PARTY_MEMBER": [ + "comunista" + ], + "OTHER_PRONOUN": [ + "it" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "abadesa": "abade", + "baronesa": "bar\u00f3n", + "noiva": "adobiarse", + "alarosa": "enfeitarse", + "muller_de_negocios": "empresario", + "filla": "fillo", + "filia": "son", + "duquesa": "duque", + "emperatriz": "emperador", + "femia": "masculino", + "feminino": "masculino", + "gal": "guido", + "institutriz": "gobernador", + "hero\u00edna": "heroe", + "patroa": "terratenente", + "faltar": "sir", + "estar_perdido": "sir", + "mancar": "sir", + "perderse": "sir", + "matrix": "ayr", + "sobri\u00f1a": "sobri\u00f1o", + "monxa": "frade", + "pr\u00edncipe": "prince", + "princesa": "prince", + "irm\u00e1": "taina", + "portavoz": "voceiro", + "enteada": "fillastro", + "andada": "fillastro", + "fillastra": "fillastro", + "sogra": "padrasto", + "madrasta": "padrasto", + "camareira": "camareiro", + "viuvez": "vi\u00favo", + "vi\u00fava": "vi\u00favo", + "marido": "cristian", + "esposa": "esposo", + "duna": "esposo", + "feto": "marido" + }, + "other_gender_swap": { + "eles": "de_la", + "seus": "de_la", + "s\u00faas": "de_la", + "s\u00faa": "de_la", + "he": "epi", + "de_la": "s\u00faa" + }, + "en_pronoun2gender": { + "they": [ + "transexual", + "transx\u00e9nero", + "homosexual", + "bisexual", + "transx\u00e9nera" + ], + "he": [ + "toxo", + "marido", + "man", + "masculino", + "rachar", + "neno", + "fidalgo", + "guido" + ], + "she": [ + "estar_perdido", + "se\u00f1ora", + "feminino", + "rapaza", + "lesbianismo", + "femia", + "empregada", + "perderse", + "camareira", + "feto", + "garela", + "faltar", + "doncela", + "mancar", + "trondia", + "lesbiana", + "gal" + ] + }, + "en_pronoun2pronoun": { + "he": [ + "he" + ], + "she": [ + "de_la" + ], + "they": [ + "eles", + "s\u00faa", + "s\u00faas", + "seus", + "elas", + "epi" + ], + "it": [ + "it", + "tento", + "ico" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/gml.json b/data_tooling/pii_processing/ontology/data/gml.json new file mode 100644 index 0000000..e3de89b --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/gml.json @@ -0,0 +1,34 @@ +{ + "RELIGION_MEMBER": [ + "dunker" + ], + "PERSON_PRONOUN": [ + "he" + ], + "OTHER_PRONOUN": [ + "it" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": {}, + "other_gender_swap": {}, + "en_pronoun2gender": {}, + "en_pronoun2pronoun": { + "he": [ + "he" + ], + "it": [ + "it" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/gn.json b/data_tooling/pii_processing/ontology/data/gn.json new file mode 100644 index 0000000..962ff12 --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/gn.json @@ -0,0 +1,90 @@ +{ + "LOCATION": [ + "la_plata", + "para_h\u0169" + ], + "PLANT": [ + "karanda", + "karanda'y" + ], + "ANIMAL": [ + "guasu", + "okamb\u00fava", + "pirachuguasu" + ], + "PERSON_PRONOUN": [ + "i", + "me" + ], + "PUBLIC_FIGURE": [ + "y", + "a", + "i" + ], + "SOC_ECO_CLASS": [ + "\u00f1emit\u1ef9" + ], + "JOB": [ + "para" + ], + "DISEASE": [ + "para", + "ague", + "tuguyasuka" + ], + "FOOD": [ + "tave'\u00ff" + ], + "RACE": [ + "morot\u0129" + ], + "ORG": [ + "po", + "sa" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "embireko": "m\u00e9na", + "ku\u00f1a": "yvyp\u00f3ra" + }, + "other_gender_swap": { + "ha_eku\u00e9ra": "ah\u1ebd", + "ah\u1ebd": "ha_eku\u00e9ra" + }, + "en_pronoun2gender": { + "he": [ + "yvyp\u00f3ra" + ], + "she": [ + "mit\u00e3ku\u00f1a", + "yk\u00e9ra", + "ku\u00f1ata\u0129", + "yke", + "eindy", + "ku\u00f1a" + ] + }, + "en_pronoun2pronoun": { + "he": [ + "ah\u1ebd" + ], + "she": [ + "ah\u1ebd", + "imba_e" + ], + "they": [ + "ha_eku\u00e9ra" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/goh.json b/data_tooling/pii_processing/ontology/data/goh.json new file mode 100644 index 0000000..8fb7bec --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/goh.json @@ -0,0 +1,36 @@ +{ + "ANIMAL": [ + "heigaro", + "reigaro" + ], + "DISEASE": [ + "brehhan", + "hungar" + ], + "PERSON_PRONOUN": [ + "her" + ], + "PUBLIC_FIGURE": [ + "lulli" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": {}, + "other_gender_swap": {}, + "en_pronoun2gender": {}, + "en_pronoun2pronoun": { + "she": [ + "her" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/got.json b/data_tooling/pii_processing/ontology/data/got.json new file mode 100644 index 0000000..af7775e --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/got.json @@ -0,0 +1,43 @@ +{ + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + 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[], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/haw.json b/data_tooling/pii_processing/ontology/data/haw.json new file mode 100644 index 0000000..6828069 --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/haw.json @@ -0,0 +1,136 @@ +{ + "LOCATION": [ + "he_mea_\u02bbole", + "kanakaloka", + "he_mea_iki" + ], + "JOB": [ + "mea_unuhi", + "potter", + "make", + "mea_\u02bbohi", + "polopeka" + ], + "PUBLIC_FIGURE": [ + "lopaka", + "hanal\u0113", + "e", + "a", + "kakalina", + "henel\u0113", + "one", + "kelekolio", + "mana\u02bbolana", + "lea", + "pekelo" + ], + "FOOD": [ + "liliko\u02bbi" + ], + "RELIGION_MEMBER": [ + "moramona" + ], + "QUANTITY": [ + "ikehu\u02bb\u0101" + ], + "PERSON_PRONOUN": [ + "he", + "\u02bb\u012b" + ], + "PLANT": [ + "lanalana", + "pal\u0101naka" + ], + "LANGUAGE": [ + "pali", + "pelek\u0101ne" + ], + "PRODUCT": [ + "mele_kalikimaka", + "kanakaloka", + "mele_a_solomona" + ], + "ANIMAL": [ + "poloka", + "wulekula", + "kokei\u02bba", + "kalapuna" + ], + "SOC_ECO_CLASS": [ + "kakaikahi" + ], + "ORG": [ + "laeuliuli", + "kapalakiko" + ], + "DISEASE": [ + "pilikia", + "ho\u02bbom\u0101inoino" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "p\u0101lona_wahine": "p\u0101lona", + "barona_wahine": "barona", + "duke_wahine": "duke", + "\u0101na": "k\u0101na", + "k\u0101na": "\u0101na", + "m\u014d\u02bb\u012b_wahine": "m\u014d\u02bb\u012b", + "kaikuahine": "kaikua\u02bbana", + "kaikaina": "kaikua\u02bbana", + "wahine": "k\u0101ne", + "k\u0101ne_\u02bb\u014dpio": "wahine_\u02bb\u014dpio", + "keiki_k\u0101ne": "wahine_\u02bb\u014dpio" + }, + "other_gender_swap": { + "one": "\u0101na", + "l\u0101kou": "\u0101na", + "k\u0101": "\u0101na", + "l\u0101ua": "k\u0101na", + "he": "l\u0101ua", + "\u0101na": "k\u0101", + "k\u0101na": "l\u0101kou" + }, + "en_pronoun2gender": { + "he": [ + "keiki_k\u0101ne", + "k\u0101ne_\u02bb\u014dpio" + ], + "she": [ + "kaikamahine", + "wahine", + "wahine_\u02bb\u014dpio" + ] + }, + "en_pronoun2pronoun": { + "he": [ + "k\u0101na", + "\u0101na", + "he" + ], + "she": [ + "k\u0101na", + "\u0101na" + ], + "they": [ + "one", + "k\u0101", + "l\u0101kou", + "l\u0101ua" + ], + "it": [ + "k\u0101na", + "k\u0113ia" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/hbo.json b/data_tooling/pii_processing/ontology/data/hbo.json new file mode 100644 index 0000000..0c0228d --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/hbo.json @@ -0,0 +1,41 @@ +{ + "DATE": [ + "\u05ea\u05d7\u05dc\u05d4" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "\u05db\u05dc\u05d4": "\u05d7\u05ea\u05df", + "\u05d9\u05dc\u05d3": "\u05d9\u05dc\u05d3\u05d4", + "\u05e0\u05e2\u05e8": "\u05d9\u05dc\u05d3\u05d4" + }, + "other_gender_swap": {}, + "en_pronoun2gender": { + "he": [ + "\u05d9\u05dc\u05d3", + "\u05e0\u05e2\u05e8", + "\u05de\u05df", + "\u05d2\u05d1\u05d9\u05e8" + ], + "she": [ + "\u05e0\u05e7\u05d1\u05d4", + "\u05d9\u05dc\u05d3\u05d4" + ] + }, + "en_pronoun2pronoun": { + "it": [ + "\u05db\u05d9", + "\u05d0\u05e9\u05e8" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/he.json b/data_tooling/pii_processing/ontology/data/he.json new file mode 100644 index 0000000..b32109a --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/he.json @@ -0,0 +1,2170 @@ +{ + "LANGUAGE": [ + 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+ "\u05d1\u05d9\u05ea_\u05e1\u05e4\u05e8_\u05d9\u05e1\u05d5\u05d3\u05d9", + "dia", + "\u05d4\u05db\u05e0\u05e1\u05d9\u05d9\u05d4_\u05d4\u05d0\u05e4\u05d9\u05e1\u05e7\u05d5\u05e4\u05dc\u05d9\u05ea", + "\u05d4\u05de\u05e9\u05e4\u05d8_\u05d4\u05e8\u05d5\u05de\u05d9", + "\u05de\u05d5\u05e8\u05de\u05d5\u05e0\u05d9\u05dd", + "\u05d3\u05d0\u05e8", + "\u05d4\u05de\u05e4\u05dc\u05d2\u05d4_\u05d4\u05dc\u05d0\u05d5\u05de\u05d9\u05ea", + "\u05d0\u05d6\u05d5\u05e8_\u05ea\u05e2\u05e9\u05d9\u05d9\u05d4", + "\u05db\u05e4\u05e8_\u05d0\u05d5\u05dc\u05d9\u05de\u05e4\u05d9", + "\u05de\u05e2\u05d8_\u05de\u05e2\u05d8", + "\u05d1\u05d9\u05ea_\u05d4\u05de\u05e9\u05e4\u05d8_\u05d4\u05e2\u05dc\u05d9\u05d5\u05df", + "\u05d4\u05d9\u05e4\u05d4\u05e4\u05d9\u05d9\u05d4_\u05d4\u05e0\u05e8\u05d3\u05de\u05ea", + "\u05e1\u05e0\u05d5\u05e0\u05d9\u05ea_\u05d4\u05e8\u05e4\u05ea\u05d5\u05ea", + "\u05de\u05e4\u05dc\u05d2\u05ea_\u05d4\u05dc\u05d9\u05d9\u05d1\u05d5\u05e8_\u05d4\u05d0\u05d5\u05e1\u05d8\u05e8\u05dc\u05d9\u05ea", 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"\u05d4\u05d9\u05d9\u05d8\u05d5\u05e8_\u05d5\u05d9\u05dc\u05d4_\u05dc\u05d5\u05d1\u05d5\u05e1", + "\u05e1\u05e0\u05d8_\u05dc\u05d5\u05d0\u05d9\u05e1", + "\u05e2\u05d5\u05ea'\u05de\u05d0\u05df_\u05d4\u05e8\u05d0\u05e9\u05d5\u05df", + "\u05e1\u05de\u05d9\u05ea", + "\u05d0\u05e0\u05d3\u05e8\u05e1_\u05e6\u05dc\u05d6\u05d9\u05d5\u05e1", + "t" + ], + "LOCATION": [ + "\u05d0\u05e7\u05d3\u05de\u05d9\u05d4_\u05dc\u05de\u05d5\u05d6\u05d9\u05e7\u05d4", + "\u05d4\u05e8_\u05d4\u05d6\u05d9\u05ea\u05d9\u05dd", + "\u05db\u05e3_\u05d5\u05e8\u05d3\u05d4", + "\u05e7\u05e8\u05d9\u05d1\u05d9_\u05e8\u05d9\u05d4", + "\u05d1\u05d9\u05ea_\u05d7\u05d5\u05dc\u05d9\u05dd_\u05e4\u05e1\u05d9\u05db\u05d9\u05d0\u05d8\u05e8\u05d9", + "\u05d0\u05de\u05d9\u05dc\u05d9\u05d0\u05e0\u05d5_\u05e1\u05e4\u05d0\u05d8\u05d4", + "\u05d4\u05d0\u05e1\u05e4\u05d4_\u05d4\u05dc\u05d0\u05d5\u05de\u05d9\u05ea_\u05d1\u05e2\u05ea_\u05d4\u05de\u05d4\u05e4\u05db\u05d4_\u05d4\u05e6\u05e8\u05e4\u05ea\u05d9\u05ea", + 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"\u05de\u05d5\u05e0\u05d2\u05d5_\u05e4\u05d0\u05e8\u05e7", + "\u05db\u05e8\u05d9\u05e1\u05d8\u05d5\u05e4\u05e8_\u05e7\u05d5\u05dc\u05d5\u05de\u05d1\u05d5\u05e1", + "\u05d0\u05e7\u05d3\u05de\u05d9\u05d4_\u05e6\u05d1\u05d0\u05d9\u05ea" + ], + "PLANT": [ + "\u05de\u05e1\u05d8\u05d9\u05e7\u05d0", + "the_joshua_tree", + "candida_albicans", + "\u05e4\u05d5\u05d9\u05d6\u05df_\u05d0\u05d9\u05d9\u05d1\u05d9" + ], + "ANIMAL": [ + "\u05d8\u05d9\u05e4\u05d5\u05dc\u05ea\u05d9\u05d9\u05dd", + "\u05de\u05d5\u05e8\u05d9\u05d2", + "lactobacillus_acidophilus", + "\u05d0\u05d3\u05e8\u05d9\u05ea", + "\u05de\u05d5\u05e8\u05d9\u05d2\u05df_\u05d4\u05db\u05ea\u05dd", + "\u05d0\u05d1\u05d5\u05dc\u05d4", + "\u05de\u05d5\u05d6\u05d0\u05d9\u05e7\u05ea_\u05d4\u05d8\u05d1\u05e7", + "\u05d0\u05d5\u05e8\u05d6\u05d9\u05ea", + "\u05e1\u05d9\u05e1\u05d9\u05d9\u05dd", + "\u05d0\u05dc\u05de\u05e0\u05d4_\u05e9\u05d7\u05e8\u05d4", + "\u05d5\u05d9\u05e8\u05d5\u05e1_\u05d0\u05e4\u05e9\u05d8\u05d9\u05d9\u05df_\u05d1\u05e8", + 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"\u05e1\u05e0\u05d8_\u05dc\u05d5\u05e1\u05d9\u05d4" + ], + "PERSON": [ + "\u05de\u05d5\u05e8\u05d9\u05d2", + "\u05d4\u05e8_\u05d8\u05d0\u05d9", + "\u05d4\u05d5\u05d5\u05d0\u05d4_\u05d1\u05e8\u05d6\u05d9\u05dc\u05d0\u05d9\u05ea" + ], + "SOC_ECO_CLASS": [ + "\u05d4\u05e2\u05d9\u05ea\u05d5\u05e0\u05d5\u05ea", + "\u05d4\u05e8\u05e9\u05d5\u05ea_\u05d4\u05e8\u05d1\u05d9\u05e2\u05d9\u05ea", + "\u05e9\u05d5\u05e7_\u05e9\u05d7\u05d5\u05e8", + "\u05d7\u05e7\u05dc\u05d0\u05d5\u05ea", + "\u05e1\u05de\u05d5\u05e8\u05d0\u05d9" + ], + "UNION": [ + "\u05d0\u05d2\u05d5\u05d3\u05ea_\u05e1\u05d8\u05d5\u05d3\u05e0\u05d8\u05d9\u05dd", + "\u05d0\u05d2\u05d5\u05d3_\u05de\u05e7\u05e6\u05d5\u05e2\u05d9" + ], + "QUANTITY": [ + "g", + "\u05e9\u05dc\u05d5\u05e9_\u05d0\u05d7\u05d9\u05d5\u05ea" + ], + "RACE": [ + "\u05d0\u05e0\u05d2\u05dc\u05d9\u05dd" + ], + "DATE": [ + "\u05ea\u05d7\u05dc\u05d4", + "\u05de\u05d5\u05dc\u05d3_\u05d4\u05dc\u05d1\u05e0\u05d4", + 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"\u05d2'\u05d5\u05dc\u05d9\u05df", + "\u05d0\u05d9\u05d9\u05dc\u05d4", + "\u05d0\u05d9\u05d9\u05d3\u05dc", + "\u05e9\u05d5\u05d4\u05dd", + "\u05d4\u05d3\u05e8", + "\u05d0\u05de\u05d9", + "\u05ea\u05d0\u05dc\u05d0", + "\u05d9\u05dd", + "\u05dc\u05d9\u05d9\u05d4", + "\u05e0\u05d2\u05d4", + "\u05e2\u05d8\u05e8\u05d4", + "\u05d4\u05d9\u05d9\u05dc\u05d9", + "\u05d1\u05d9\u05e1\u05d0\u05df", + "\u05db\u05e0\u05e8\u05ea", + "\u05d0\u05d9\u05dc\u05ea", + "\u05d0\u05de\u05dc\u05d9", + "\u05de\u05e0\u05d5\u05e8", + "\u05e8\u05d5\u05df", + "\u05ea\u05d4\u05dc\u05d4", + "\u05e0\u05d0\u05d9\u05d4", + "\u05e0\u05d5\u05e8", + "\u05d8\u05dc", + "\u05d0\u05d5\u05e8\u05df", + "\u05e2\u05d3\u05d9", + "\u05e8\u05d9\u05dd", + "\u05d0\u05e0\u05d4", + "\u05e2\u05d3\u05df", + "\u05e0\u05e2\u05de\u05d4", + "\u05d0\u05de\u05d5\u05e0\u05d4", + "\u05d9\u05d4\u05dc", + "\u05e2\u05d5\u05de\u05e8", + "\u05d1\u05dc\u05d5\u05de\u05d4", + "\u05d9\u05d0\u05e8\u05d0", + "\u05dc\u05d9\u05d4\u05d9\u05d0", + "\u05d8\u05dc\u05d9\u05d4", + "\u05e9\u05e4\u05e8\u05d4", + "\u05e0\u05d9\u05e7\u05d4", + "\u05d8\u05d5\u05d4\u05e8", + "\u05d9\u05d5\u05d8\u05d0", + "\u05de\u05d0\u05d9", + "\u05d4\u05dc\u05dc\u05d9", + "\u05d1\u05d9\u05d0\u05df", + "\u05e2\u05d8\u05e8\u05ea", + "\u05d3\u05d5\u05e8", + "\u05e4\u05dc\u05d2", + "\u05e8\u05d9\u05ea\u05d0\u05d2'", + "\u05d3\u05d5\u05e8\u05d5\u05df", + "\u05e8\u05e2\u05d5\u05ea", + "\u05de\u05dc\u05db\u05d4", + "\u05de\u05d9\u05e9\u05dc", + "\u05e1\u05d5\u05e4\u05d9\u05d4", + "\u05e0\u05e2\u05de\u05d9", + "\u05e6\u05e4\u05d5\u05e8\u05d4", + "\u05e9\u05d9\u05e8", + "\u05de\u05e8\u05d9\u05d4", + "\u05d7\u05d5\u05d4", + "\u05dc\u05d0\u05d4", + "\u05e4\u05e8\u05d9\u05d9\u05d3\u05d0", + "\u05dc\u05d9\u05d4", + "\u05e8\u05e0\u05d9", + "\u05e1\u05d9\u05dc\u05d0", + "\u05d9\u05e2\u05dc", + "\u05d3\u05d5\u05e8\u05d9\u05df", + "\u05e8\u05d9\u05de\u05d0\u05e1", + "\u05d0\u05d5\u05e8", + "\u05d0\u05d9\u05d9\u05dc\u05ea", + "\u05e9\u05e7\u05d3", + "\u05d2\u05dc", + "\u05d3\u05d9\u05e0\u05d4", + "\u05d4\u05e0\u05d9\u05d4", + "\u05e1\u05dc\u05de\u05d0", + "\u05e2\u05e0\u05d0\u05dc", + "\u05d0\u05d5\u05d5\u05d4", + "\u05e0\u05d0\u05d9\u05d0", + "\u05d0\u05dc\u05d9", + "\u05d7\u05df", + "\u05de\u05d0\u05d9\u05d4", + "\u05d0\u05de\u05d5\u05e8", + "\u05d6\u05d9\u05e0\u05d4", + "\u05d0\u05d1\u05d9\u05d2\u05d9\u05dc", + "\u05d3\u05e8\u05d5\u05e8", + "\u05d2'\u05e0\u05d0", + "\u05d4\u05d3\u05e1\u05d4", + "\u05de\u05d9\u05ea\u05e8", + "\u05e8\u05d9\u05e0\u05d4", + "\u05de\u05d9\u05dc\u05d4", + "\u05d0\u05dc\u05db\u05e1", + "\u05de\u05d0\u05d5\u05e8", + "\u05e8\u05d9\u05de\u05d0", + "\u05e9\u05d5\u05e9\u05e0\u05d4", + "\u05d0\u05dc\u05d9\u05e1", + "\u05d9\u05e2\u05e8\u05d4", + "\u05d2'\u05d5\u05dc\u05d9", + "\u05d0\u05d1\u05d9\u05e9\u05d2", + "\u05d0\u05d5\u05d3\u05dc", + "\u05d0\u05dc\u05d9\u05e1\u05d4", + "\u05d3\u05e0\u05d9\u05d0\u05dc\u05d4", + "\u05d2\u05dc\u05d9", + "\u05e8\u05d5\u05e0\u05d9", + "\u05de\u05d9\u05dc\u05d0", + "\u05e2\u05d3\u05d9\u05d4", + "\u05e1\u05e4\u05d9\u05e8", + "\u05d0\u05d5\u05e8\u05d0\u05dc", + "\u05d0\u05d9\u05d4", + "\u05dc\u05d9\u05dc\u05d9", + "\u05ea\u05d9\u05d0", + "\u05e0\u05d5\u05e4\u05e8", + "\u05dc\u05e0\u05d9", + "\u05d2\u05d9\u05dc", + "\u05d1\u05d9\u05dc\u05d0", + "\u05d2\u05d9\u05dc\u05d9", + "\u05e0\u05d9\u05dc\u05d9", + "\u05d9\u05e1\u05de\u05d9\u05df", + "\u05dc\u05d9\u05d0\u05df", + "\u05d0\u05d7\u05d9\u05e0\u05d5\u05e2\u05dd", + "\u05e0\u05d5\u05e2\u05dd", + "\u05e7\u05d0\u05e8\u05d9\u05df", + "\u05e1\u05d5\u05e4\u05d9", + "\u05e9\u05d9\u05d9\u05e0\u05d0", + "\u05e9\u05d9\u05e8\u05d4", + "\u05dc\u05d9\u05e8\u05d6", + "\u05d1\u05ea_\u05e9\u05d1\u05e2", + "\u05dc\u05d9\u05e2\u05d3", + "\u05e9\u05d9\u05d9\u05e0\u05d3\u05dc", + "\u05d7\u05dc\u05d0", + "\u05e2\u05de\u05dc\u05d9\u05d4", + "\u05e2\u05e0\u05d1\u05e8", + "\u05d3\u05e0\u05d4", + "\u05e8\u05d5\u05ea", + "\u05d6\u05d9\u05e0\u05d1", + "\u05dc\u05d9\u05dc\u05da", + "\u05e1\u05de\u05d0", + "\u05d4\u05d3\u05e1", + "\u05de\u05d9\u05e8\u05d0\u05dc", + "\u05d2'\u05d5\u05e8\u05d9", + "\u05d4\u05d5\u05d3\u05d9\u05d4", + "\u05ea\u05d4\u05d9\u05dc\u05d4", + "\u05d0\u05d5\u05e4\u05dc", + "\u05dc\u05d9\u05d0\u05d5\u05e8", + "\u05dc\u05d9\u05e0\u05d5\u05d9", + "\u05ea\u05d1\u05dc", + "\u05d0\u05d5\u05d3\u05d9\u05d4", + "\u05d0\u05d5\u05e8\u05d9\u05d0\u05df", + "\u05d3\u05e4\u05e0\u05d4", + "\u05d9\u05d4\u05dc\u05d9", + "\u05e2\u05e0\u05d4\u05d0\u05dc", + "\u05d9\u05d5\u05d1\u05dc", + "\u05ea\u05d0\u05d9\u05e8", + "\u05d0\u05d9\u05dc\u05d9\u05df", + "\u05d2\u05d9\u05dc\u05d4", + "\u05e0\u05d0\u05d9", + "\u05de\u05d9\u05e7\u05d4", + "\u05e9\u05d9", + "\u05d0\u05de\u05d9\u05dc\u05d9", + "\u05e4\u05e0\u05d9\u05e0\u05d4", + "\u05ea\u05de\u05e8\u05d4", + "\u05d9\u05d5\u05db\u05d1\u05d3", + "\u05de\u05d5\u05e8\u05d9\u05d4", + "\u05e2\u05d3\u05d9\u05e0\u05d4", + "\u05d0\u05df", + "\u05de\u05d9\u05d8\u05dc", + "\u05dc\u05de\u05d0\u05e8", + "\u05de\u05e0\u05d5\u05d7\u05d4", + "\u05dc\u05d9\u05e8\u05d9", + "\u05dc\u05d9\u05d0\u05dc", + "\u05d0\u05de\u05d4", + "\u05d3\u05d9\u05de\u05d0", + "\u05e8\u05d4\u05e3", + "\u05dc\u05d9\u05e8\u05d5\u05df", + "\u05d0\u05d9\u05d9\u05de\u05d9", + "\u05dc\u05d5\u05e8", + "\u05d0\u05d3\u05e8", + "\u05d2\u05d6\u05dc", + "\u05e8\u05d5\u05e0\u05d4", + "\u05de\u05d9\u05d0\u05e8", + "\u05d0\u05d9\u05de\u05d0\u05df", + "\u05dc\u05d9\u05df", + "\u05de\u05d9\u05e8\u05d9\u05dc", + "\u05e7\u05d9\u05dd", + "\u05e0\u05d5\u05e2\u05d4", + "\u05dc\u05d5\u05d8\u05dd", + "\u05d0\u05dc\u05d9\u05e0\u05d5\u05e8", + "\u05e0\u05d8\u05dc\u05d9", + "\u05e8\u05e2\u05d9\u05d4", + "\u05d9\u05e8\u05d9\u05df", + "\u05e9\u05d5\u05dc\u05de\u05d9\u05ea", + "\u05ea\u05d5\u05dc\u05d9\u05df", + "\u05d2\u05d9\u05d8\u05dc", + "\u05db\u05e8\u05de\u05dc", + "\u05d0\u05d5\u05d3\u05dc\u05d9\u05d4", + "\u05d9\u05d4\u05d5\u05d3\u05d9\u05ea", + "\u05d0\u05e0\u05d0\u05d1\u05dc", + "\u05dc\u05d9\u05d0\u05dd", + "\u05d0\u05d5\u05e8\u05d9\u05d4", + "\u05d7\u05d9\u05d4", + "\u05d9\u05d5\u05dc\u05d9", + "\u05d0\u05d1\u05d9\u05d1", + "\u05e6\u05d1\u05d9\u05d4", + "\u05d9\u05e1\u05db\u05d4", + "\u05d0\u05d3\u05dc", + "\u05d0\u05dc\u05d9\u05e2\u05e0\u05d4", + "\u05d0\u05de\u05d9\u05dc\u05d9\u05d4", + "\u05de\u05d9\u05dc\u05d9", + "\u05e2\u05d5\u05e4\u05e8\u05d9", + "\u05de\u05e9\u05d9", + "\u05ea\u05d5\u05dd", + "\u05d0\u05d5\u05e8\u05d4", + "\u05de\u05d9\u05db\u05dc", + "\u05d0\u05d5\u05e4\u05d9\u05e8", + "\u05d0\u05e8\u05d9\u05d0\u05dc", + "\u05d0\u05d3\u05d5\u05d4", + "\u05e9\u05d9\u05e8\u05d9", + "\u05e2\u05d9\u05d3\u05df", + "\u05d0\u05dc\u05d4", + "\u05e7\u05e8\u05df", + "\u05e6\u05d5\u05e4\u05d9\u05d4", + "\u05d0\u05dc\u05d9\u05d4", + "\u05d7\u05e0\u05d4", + "\u05d3\u05e0\u05d9", + "\u05ea\u05de\u05e8", + "\u05d1\u05ea", + "\u05d0\u05dc\u05d9\u05d0\u05e0\u05d4", + "\u05d9\u05e4\u05d4", + "\u05dc\u05d9\u05d1\u05d9", + "\u05d2'\u05d5\u05d0\u05dc", + "\u05de\u05e8\u05d9\u05dd", + "\u05e4\u05e8\u05d7", + "\u05e8\u05d5\u05d7\u05de\u05d4", + "\u05de\u05e2\u05d9\u05d9\u05df", + "\u05d9\u05e8\u05d3\u05df", + "\u05d7\u05d2\u05d9\u05ea", + "\u05e0\u05d0\u05d5\u05d4", + "\u05d0\u05de\u05dc", + "\u05d4\u05dc\u05dc", + "\u05ea\u05d4\u05dc", + "\u05d2\u05d0\u05d9\u05d4", + "\u05e4\u05d9\u05d2\u05d0", + "\u05e0\u05d9\u05e0\u05d4", + "\u05e8\u05d1\u05e7\u05d4", + "\u05d4\u05d9\u05e0\u05d3\u05d0", + "\u05d2\u05d5\u05dc\u05d3\u05d4", + "\u05e8\u05d5\u05ea\u05dd", + "\u05d0\u05e1\u05ea\u05e8", + "\u05db\u05dc\u05d9\u05dc", + "\u05e9\u05e0\u05d9", + "\u05d6\u05d4\u05d1\u05d4", + "\u05e9\u05d4\u05d3", + "\u05d8\u05dc\u05d9", + "\u05e4\u05d0\u05d8\u05de\u05d4", + "\u05ea\u05d0\u05dc\u05d9\u05df", + "\u05d1\u05d0\u05e8\u05d9", + "\u05d3\u05e0\u05d9\u05d0\u05dc", + "\u05de\u05d9\u05d0\u05dc", + "\u05d0\u05d5\u05e8\u05d9", + "\u05e2\u05e0\u05d1\u05dc", + "\u05e0\u05d9\u05e6\u05df", + "\u05e8\u05e4\u05d9\u05e3", + "\u05e9\u05d5\u05d1\u05dc", + "\u05e1\u05d5\u05dc", + "\u05e0\u05d5\u05d9", + "\u05d2\u05d5\u05e8\u05d9", + "\u05e8\u05d6", + "\u05d0\u05dc\u05de\u05d5\u05d2", + "\u05d0\u05dc\u05d5\u05e0\u05d4", + "\u05dc\u05d9\u05d8\u05dc", + "\u05e1\u05d9\u05dc\u05d9\u05df", + "\u05d1\u05e8", + "\u05dc\u05d9", + "\u05d2'\u05d5\u05d9\u05dc", + "\u05de\u05d5\u05e8", + "\u05e1\u05ea\u05d9\u05d5", + "\u05de\u05d9\u05e8\u05d0", + "\u05e9\u05d9_\u05dc\u05d9", + "\u05e2\u05de\u05d9\u05ea", + "\u05e7\u05e8\u05e0\u05d9", + "\u05e9\u05d7\u05e8", + "\u05e4\u05e8\u05d9\u05d0\u05dc", + "\u05d0\u05dc\u05d5\u05de\u05d4", + "\u05d0\u05dc\u05d8\u05e2", + "\u05d0\u05dc\u05d9\u05df", + "\u05d0\u05d5\u05e4\u05e7", + "\u05d0\u05e1\u05d9\u05dc", + "\u05d0\u05e8\u05d1\u05dc", + "\u05e0\u05d9\u05e7\u05d5\u05dc", + "\u05e0\u05d7\u05de\u05d4", + "\u05d1\u05e8\u05db\u05d4", + "\u05e1\u05d4\u05e8", + "\u05d0\u05dc\u05de\u05d4", + "\u05e9\u05d9\u05e8\u05d0\u05dc", + "\u05d6\u05d5\u05d0\u05d9", + "\u05e4\u05d0\u05e8", + "\u05dc\u05d9\u05d1\u05d0", + "\u05d0\u05d5\u05e9\u05e8", + "\u05d0\u05e1\u05e0\u05ea", + "\u05d6\u05d9\u05d5", + "\u05d4\u05e2\u05e0\u05d0", + "\u05e0\u05d8\u05e2", + "\u05d8\u05d5\u05d1\u05d4", + "\u05e8\u05d9\u05d9\u05d6\u05dc", + "\u05d0\u05dc\u05d9\u05e9\u05d1\u05e2", + "\u05dc\u05d9\u05d1", + "\u05d3\u05d1\u05d5\u05e8\u05d4", + "\u05d4\u05d9\u05dc\u05d4", + "\u05e9\u05e8\u05d4", + "\u05e9\u05dc\u05d9", + "\u05e8\u05d7\u05dc", + "\u05e1\u05d9\u05d5\u05df", + "\u05dc\u05e0\u05d0", + "\u05d0\u05d2\u05dd", + "\u05d2\u05e4\u05df", + "\u05d1\u05ea\u05d9\u05d4", + "\u05d0\u05d4\u05d5\u05d1\u05d4", + "\u05e2\u05dc\u05de\u05d4", + "\u05e9\u05d9\u05dc\u05ea", + "\u05e9\u05d8\u05e2\u05e8\u05e0\u05d0", + "\u05e0\u05d5\u05d9\u05d4", + "\u05de\u05d9\u05d9\u05d4" + ], + "FIRST_NAME_MALE": [ + "\u05de\u05d5\u05e1\u05d0", + "\u05d2\u05d1\u05e8\u05d9\u05d0\u05dc", + "\u05dc\u05d5\u05d9", + "\u05d0\u05d1\u05d9\u05e0\u05d5\u05e2\u05dd", + "\u05e2\u05de\u05e0\u05d5\u05d0\u05dc", + "\u05e8\u05d5\u05d0\u05d9", + "\u05e8\u05d5\u05e2\u05d9", + "\u05d6\u05d5\u05d4\u05e8", + "\u05d9\u05d5\u05e1\u05e3", + "\u05de\u05e0\u05d7\u05dd", + "\u05e2\u05e7\u05d9\u05d1\u05d0", + "\u05d9\u05d0\u05df", + "\u05d7\u05d2\u05d9", + "\u05e1\u05d5\u05dc\u05d9\u05de\u05d0\u05df", + "\u05d0\u05d5\u05e8\u05d9\u05df", + "\u05d0\u05e8\u05d3", + "\u05d0\u05e8\u05d6", + "\u05d7\u05d9\u05d9\u05dd", + "\u05dc\u05d9\u05e8\u05df", + "\u05d9\u05e4\u05ea\u05d7", + "\u05dc\u05d1\u05d9\u05d0", + "\u05d8\u05d5\u05d1\u05d9\u05d4", + "\u05d3\u05d1", + "\u05d7\u05e1\u05df", + "\u05d2'\u05d5\u05d3", + "\u05e9\u05de\u05e2\u05d5\u05df", + "\u05e0\u05d4\u05d5\u05e8\u05d0\u05d9", + "\u05d2\u05dc\u05e2\u05d3", + "\u05d9\u05e0\u05d5\u05df", + "\u05de\u05ea\u05df", + "\u05d0\u05d7\u05de\u05d3", + "\u05d9\u05d4\u05d1", + "\u05e8\u05d1\u05d9\u05d3", + "\u05e9\u05d5\u05d4\u05dd", + "\u05e0\u05d9\u05ea\u05d0\u05d9", + "\u05d4\u05d3\u05e8", + "\u05d6\u05d0\u05d1", + "\u05d9\u05d4\u05d5\u05e9\u05e2", + "\u05d0\u05de\u05e8\u05d9", + "\u05db\u05e4\u05d9\u05e8", + "\u05d0\u05d1\u05d9\u05e2\u05d3", + "\u05e0\u05d1\u05d5", + "\u05d0\u05dc\u05d9\u05d0\u05d1", + "\u05e0\u05d5\u05d4", + "\u05e8\u05df", + "\u05e8\u05d5\u05df", + "\u05d1\u05d5\u05e2\u05d6", + "\u05e0\u05d0\u05d5\u05e8", + "\u05d2'\u05d5\u05d6\u05e3", + "\u05e2\u05dc\u05d9", + "\u05d8\u05dc", + "\u05d0\u05d5\u05e9\u05e8\u05d9", + "\u05d0\u05d5\u05e8\u05df", + "\u05e2\u05d3\u05d9", + "\u05e9\u05d0\u05d5\u05dc", + "\u05e9\u05de\u05d5\u05d0\u05dc", + "\u05d0\u05dc\u05d9\u05d0\u05d5\u05e8", + "\u05d0\u05d1\u05d9\u05ea\u05e8", + "\u05e2\u05de\u05d9\u05d7\u05d9", + "\u05e2\u05d3\u05df", + "\u05de\u05e9\u05d4", + "\u05d0\u05d9\u05dc\u05df", + "\u05d0\u05e9\u05e8", + "\u05e8\u05d9\u05e3", + "\u05d9\u05d4\u05dc", + "\u05e9\u05e0\u05d9\u05d0\u05d5\u05e8", + "\u05e2\u05d5\u05de\u05e8", + "\u05d0\u05dc\u05d5\u05df", + "\u05dc\u05d9\u05e8\u05d5\u05d9", + "\u05d9\u05d5\u05d7\u05d0\u05d9", + "\u05d8\u05d5\u05d4\u05e8", + "\u05d9\u05d5\u05d2\u05d1", + "\u05d9\u05e0\u05d9\u05d1", + "\u05d0\u05d9\u05ea\u05d9\u05d0\u05dc", + "\u05dc\u05d0\u05d5\u05df", + "\u05d3\u05d5\u05e8", + "\u05e4\u05dc\u05d2", + "\u05e0\u05e8\u05d9\u05d4", + "\u05d3\u05d5\u05e8\u05d5\u05df", + "\u05e1\u05d9\u05e0\u05d9", + "\u05e8\u05e2\u05d9", + "\u05d0\u05e4\u05e8\u05d9\u05dd", + "\u05d0\u05d9\u05dc\u05d5\u05df", + "\u05e9\u05d9\u05e8", + "\u05d9\u05d6\u05df", + "\u05e7\u05d5\u05e8\u05df", + "\u05e8\u05e0\u05d9", + "\u05d1\u05e0\u05d9\u05de\u05d9\u05df", + "\u05e0\u05d9\u05e1\u05d9\u05dd", + "\u05d0\u05d3\u05dd", + "\u05d0\u05dc\u05d7\u05e0\u05df", + "\u05d0\u05d5\u05e8", + "\u05e9\u05e7\u05d3", + "\u05e8\u05d5\u05dd", + "\u05d2\u05dc", + "\u05d9\u05d0\u05e1\u05d9\u05df", + "\u05d0\u05d9\u05d9\u05dc", + "\u05d4\u05e8\u05d0\u05dc", + "\u05ea\u05d5\u05de\u05e8", + "\u05de\u05dc\u05d0\u05db\u05d9", + "\u05e2\u05d1\u05d3", + "\u05d0\u05dc\u05d9\u05d4\u05d5", + "\u05d9\u05d7\u05d9\u05d0", + "\u05e2\u05d5\u05d1\u05d3\u05d9\u05d4", + "\u05d0\u05dc\u05d9\u05d0\u05dc", + "\u05d3\u05e8\u05d5\u05e8", + "\u05d0\u05e8\u05d0\u05dc", + "\u05de\u05d9\u05dc\u05d0\u05df", + "\u05ea\u05d1\u05d5\u05e8", + "\u05d0\u05dc\u05db\u05e1", + "\u05de\u05d0\u05d5\u05e8", + "\u05d9\u05d5\u05d0\u05dc", + "\u05e0\u05d9\u05dc", + "\u05e2\u05e8\u05df", + "\u05d0\u05dc\u05d9\u05e8\u05df", + "\u05e8\u05d5\u05e0\u05d9", + "\u05e1\u05e2\u05e8", + "\u05d0\u05d5\u05e8\u05d0\u05dc", + "\u05dc\u05d9\u05d0\u05d1", + "\u05d0\u05dc\u05d9\u05e9\u05e2", + "\u05d1\u05e8\u05d5\u05da", + "\u05d3\u05df", + "\u05d0\u05d7\u05d9\u05d4", + "\u05dc\u05e0\u05d9", + "\u05d2\u05d9\u05dc", + "\u05e0\u05e4\u05ea\u05dc\u05d9", + "\u05e9\u05dc\u05d5", + "\u05d2\u05d9\u05dc\u05d9", + "\u05dc\u05d9\u05d0\u05d5", + "\u05d9\u05e9\u05db\u05e8", + "\u05e0\u05d5\u05e2\u05dd", + "\u05d0\u05d9\u05d0\u05df", + "\u05d6\u05d9\u05d9\u05df", + "\u05e1\u05d0\u05dc\u05d7", + "\u05dc\u05d9\u05d9\u05ea", + "\u05d0\u05d1\u05e8\u05d0\u05d4\u05d9\u05dd", + "\u05d0\u05dc\u05d9\u05de\u05dc\u05da", + "\u05dc\u05d9\u05e2\u05d3", + "\u05e2\u05d9\u05d3\u05d5", + "\u05de\u05ea\u05e0\u05d9\u05d4", + "\u05e2\u05ea\u05d9", + "\u05e2\u05e0\u05d1\u05e8", + "\u05e9\u05de\u05d7\u05d4", + "\u05e9\u05dc\u05de\u05d4", + "\u05d3\u05d9\u05df", + "\u05d0\u05d5\u05d4\u05d3", + "\u05e0\u05ea\u05e0\u05d0\u05dc", + "\u05e2\u05d1\u05e8\u05d9", + "\u05dc\u05d9\u05d0\u05d5\u05e8", + "\u05de\u05d5\u05d7\u05de\u05d3", + "\u05d0\u05dc\u05e2\u05d3", + "\u05e2\u05d9\u05dc\u05d9", + "\u05dc\u05d9\u05d3\u05d5\u05e8", + "\u05d0\u05dc\u05d9\u05e8\u05d6", + "\u05de\u05e8\u05d5\u05dd", + "\u05d9\u05d4\u05dc\u05d9", + "\u05e2\u05d3\u05d9\u05d0\u05dc", + "\u05d9\u05d5\u05d1\u05dc", + "\u05d0\u05dc\u05e8\u05d5\u05d0\u05d9", + "\u05d0\u05d9\u05de\u05e8\u05d9", + "\u05e7\u05d3\u05dd", + "\u05d0\u05dc\u05db\u05e1\u05e0\u05d3\u05e8", + "\u05e0\u05d9\u05e8", + "\u05d0\u05dc\u05e2\u05d6\u05e8", + "\u05dc\u05d9\u05e2\u05dd", + "\u05e9\u05d9", + "\u05e0\u05d9\u05d1", + "\u05d2'\u05d5\u05dc\u05d9\u05d0\u05df", + "\u05ea\u05d9\u05d9\u05dd", + "\u05d9\u05e9\u05d9", + "\u05d3\u05d5\u05dc\u05d1", + "\u05e6\u05d5\u05e8", + "\u05d1\u05e6\u05dc\u05d0\u05dc", + "\u05d2\u05d1\u05e2", + "\u05d9\u05d4\u05d5\u05e0\u05ea\u05df", + "\u05dc\u05d9\u05d0\u05dc", + "\u05e8\u05e4\u05d0\u05dc", + "\u05dc\u05d9\u05e8\u05d5\u05df", + "\u05d9\u05e2\u05e7\u05d1", + "\u05d0\u05d9\u05ea\u05de\u05e8", + "\u05d0\u05d3\u05e8", + "\u05d8\u05d5\u05de\u05d9", + "\u05d0\u05d9\u05ea\u05d9", + "\u05d2\u05d5\u05d3", + "\u05d9\u05d7\u05d9\u05d0\u05dc", + "\u05de\u05d5\u05e1\u05d8\u05e4\u05d0", + "\u05d4\u05d9\u05dc\u05dc", + "\u05d8\u05d5\u05dd", + "\u05d2\u05d5\u05e8", + "\u05d0\u05d9\u05dc\u05d9\u05d9", + "\u05e9\u05d2\u05d1", + "\u05d9\u05e6\u05d7\u05e7", + "\u05d0\u05e8\u05d9", + "\u05d0\u05d1\u05d9\u05d4\u05d5", + "\u05d9\u05e8\u05d9\u05df", + "\u05db\u05e8\u05de\u05dc", + "\u05d3\u05d1\u05d9\u05e8", + "\u05d0\u05d1\u05e8\u05d4\u05dd", + "\u05dc\u05d9\u05d0\u05dd", + "\u05d0\u05d5\u05e8\u05d9\u05d4", + "\u05e7\u05d5\u05e1\u05d0\u05d9", + "\u05d0\u05d1\u05d9\u05d1", + "\u05d2\u05d9\u05d0", + "\u05d9\u05e9\u05e9\u05db\u05e8", + "\u05d0\u05dc\u05e8\u05d5\u05e2\u05d9", + "\u05d9\u05e7\u05d9\u05e8", + "\u05e2\u05d5\u05e4\u05e8\u05d9", + "\u05ea\u05d5\u05dd", + "\u05db\u05e8\u05d9\u05e1\u05d8\u05d9\u05d0\u05df", + "\u05d0\u05d5\u05e4\u05d9\u05e8", + "\u05d0\u05e8\u05d9\u05d0\u05dc", + "\u05d0\u05d5\u05e8\u05d9\u05d0\u05dc", + "\u05d5\u05e8\u05d3", + "\u05e8\u05dd", + "\u05d0\u05dc\u05d9\u05e2\u05d6\u05e8", + "\u05de\u05d9\u05db\u05d0\u05dc", + "\u05e0\u05d7\u05de\u05df", + "\u05d9\u05e9\u05e8\u05d0\u05dc", + "\u05de\u05d2'\u05d3", + "\u05d0\u05dc\u05d9\u05d0\u05e1", + "\u05e2\u05d9\u05d3\u05df", + "\u05d1\u05e0\u05d9\u05d4\u05d5", + "\u05d0\u05dc\u05d9\u05d4", + "\u05d9\u05e9\u05e2\u05d9\u05d4", + "\u05d0\u05d4\u05e8\u05d5\u05df", + "\u05d9\u05d2\u05dc", + "\u05d1\u05e8\u05e7", + "\u05d0\u05dc\u05d3\u05e8", + "\u05e9\u05dc\u05d9\u05d5", + "\u05de\u05d0\u05d9\u05e8", + "\u05d9\u05d5\u05d0\u05d1", + "\u05d0\u05d9\u05ea\u05df", + "\u05de\u05e2\u05d9\u05d9\u05df", + "\u05d1\u05e0\u05d9\u05d4", + "\u05d7\u05e0\u05d5\u05da", + "\u05d9\u05e8\u05d3\u05df", + "\u05e8\u05d0\u05dd", + "\u05d4\u05dc\u05dc", + "\u05e2\u05d5\u05de\u05e8\u05d9", + "\u05d0\u05d1\u05d9\u05e9\u05d9", + "\u05e4\u05e0\u05d7\u05e1", + "\u05d9\u05d4\u05d5\u05d3\u05d4", + "\u05e9\u05e8\u05d1\u05dc", + "\u05e2\u05d1\u05d3\u05d0\u05dc\u05dc\u05d4", + "\u05d0\u05de\u05d9\u05ea\u05d9", + "\u05e8\u05d5\u05ea\u05dd", + "\u05d0\u05dc\u05e7\u05e0\u05d4", + "\u05d0\u05d5\u05e8\u05d5\u05df", + "\u05d7\u05d5\u05e1\u05d9\u05df", + "\u05d9\u05d5\u05ea\u05dd", + "\u05db\u05e8\u05dd", + "\u05e8\u05d0\u05d5\u05d1\u05df", + "\u05d1\u05d0\u05e8\u05d9", + "\u05d0\u05d1\u05d9\u05d7\u05d9", + "\u05e0\u05ea\u05df", + "\u05d3\u05e0\u05d9\u05d0\u05dc", + "\u05d0\u05d5\u05e8\u05d9", + "\u05e0\u05d9\u05e6\u05df", + "\u05d9\u05d0\u05de\u05df", + "\u05d9\u05d7\u05d6\u05e7\u05d0\u05dc", + "\u05e8\u05d6", + "\u05d0\u05dc\u05de\u05d5\u05d2", + "\u05e9\u05dc\u05d5\u05dd", + "\u05d1\u05e8", + "\u05e2\u05d5\u05e4\u05e8", + "\u05d0\u05e8\u05d9\u05d4", + "\u05d9\u05e0\u05d0\u05d9", + "\u05e1\u05ea\u05d9\u05d5", + "\u05d0\u05e0\u05d9\u05dc", + "\u05d3\u05d9\u05dc\u05df", + "\u05d9\u05d5\u05e0\u05ea\u05df", + "\u05d9\u05d0\u05d9\u05e8", + "\u05d2'\u05d5\u05e8\u05d2'", + "\u05e9\u05d9\u05dc\u05d4", + "\u05e2\u05de\u05d9\u05ea", + "\u05e1\u05de\u05d9\u05e8", + "\u05e9\u05d7\u05e8", + "\u05d0\u05d9\u05d4\u05d0\u05dd", + "\u05db\u05e8\u05d9\u05dd", + "\u05e2\u05d9\u05dc\u05d0\u05d9", + "\u05d0\u05d5\u05e4\u05e7", + "\u05d0\u05de\u05d9\u05e8", + "\u05d0\u05e8\u05d1\u05dc", + "\u05e6\u05d1\u05d9", + "\u05d0\u05d3\u05d9\u05e8", + "\u05e1\u05d4\u05e8", + "\u05e8\u05d9\u05d0\u05df", + "\u05de\u05e8\u05d3\u05db\u05d9", + "\u05e4\u05d0\u05e8", + "\u05e2\u05d5\u05d6", + "\u05e9\u05d5\u05df", + "\u05d0\u05d5\u05e9\u05e8", + "\u05e9\u05d2\u05d9\u05d0", + "\u05d6\u05d9\u05d5", + "\u05e0\u05d8\u05e2", + "\u05d1\u05df", + "\u05d7'\u05d0\u05dc\u05d3", + "\u05d9\u05d5\u05d7\u05e0\u05df", + "\u05de\u05d7\u05de\u05d5\u05d3", + "\u05e0\u05d3\u05d1", + "\u05de\u05ea\u05e0\u05d0\u05dc", + "\u05d7\u05de\u05d6\u05d4", + "\u05d9\u05d3\u05d9\u05d3\u05d9\u05d4", + "\u05d0\u05e4\u05e7", + "\u05d2\u05e4\u05df", + "\u05e1\u05d0\u05e8\u05d9", + "\u05d0\u05d1\u05d9\u05d0\u05dc", + "\u05e0\u05d7", + "\u05e8\u05d5\u05d9", + "\u05ea\u05de\u05d9\u05e8", + "\u05d0\u05e1\u05e3", + "\u05d3\u05d5\u05d3" + ], + "FIRST_NAME": [ + "\u05de\u05d9\u05db\u05d0\u05dc\u05d4", + "\u05d4\u05d9\u05dc\u05d9", + "\u05de\u05d5\u05e1\u05d0", + "\u05d2\u05d1\u05e8\u05d9\u05d0\u05dc", + "\u05dc\u05d5\u05d9", + "\u05d0\u05d1\u05d9\u05e0\u05d5\u05e2\u05dd", + "\u05d2\u05d5\u05e0\u05d9", + "\u05e2\u05de\u05e0\u05d5\u05d0\u05dc", + "\u05e4\u05e2\u05e8\u05dc", + "\u05e8\u05d5\u05d0\u05d9", + "\u05ea\u05e4\u05d0\u05e8\u05ea", + "\u05dc\u05d9\u05d0\u05d5\u05e8\u05d4", + "\u05e8\u05d5\u05e2\u05d9", + "\u05d6\u05d5\u05d4\u05e8", + "\u05d9\u05d5\u05e1\u05e3", + "\u05de\u05e0\u05d7\u05dd", + "\u05e8\u05d0\u05e9\u05d9\u05ea", + "\u05de\u05dc\u05d0\u05e7", + "\u05d0\u05dc\u05d9\u05d0\u05df", + "\u05e2\u05e7\u05d9\u05d1\u05d0", + "\u05d0\u05d1\u05d9\u05d8\u05dc", + "\u05d9\u05d0\u05df", + "\u05d0\u05d5\u05e8\u05d8\u05dc", + "\u05d0\u05e4\u05e8\u05ea", + "\u05e1\u05d0\u05e8\u05d4", + "\u05d2\u05dc\u05d9\u05d4", + "\u05d9\u05e2\u05dc\u05d4", + "\u05e8\u05e0\u05e0\u05d4", + "\u05d7\u05d2\u05d9", + "\u05e1\u05d5\u05dc\u05d9\u05de\u05d0\u05df", + "\u05d0\u05d5\u05e8\u05d9\u05df", + "\u05d0\u05e8\u05d3", + "\u05e1\u05d9\u05de\u05d4", + "\u05d0\u05e8\u05d6", + "\u05d0\u05d9\u05d8\u05d4", + "\u05de\u05d0\u05d5\u05e8\u05d9", + "\u05e8\u05d5\u05de\u05d9", + "\u05d7\u05d9\u05d9\u05dd", + "\u05dc\u05d0\u05e8\u05d0", + "\u05dc\u05d9\u05e8\u05df", + "\u05d9\u05e4\u05ea\u05d7", + "\u05d0\u05e0\u05d0\u05dc", + "\u05d3\u05e8\u05d9\u05d4", + "\u05d0\u05d1\u05d9\u05d4", + "\u05e7\u05d5\u05e8\u05dc", + "\u05de\u05e8\u05d2\u05dc\u05d9\u05ea", + "\u05dc\u05d1\u05d9\u05d0", + "\u05dc\u05d9\u05d4\u05d9", + "\u05dc\u05d5\u05e8\u05df", + "\u05d8\u05d5\u05d1\u05d9\u05d4", + "\u05e8\u05d9\u05ea\u05d0\u05dc", + "\u05d3\u05d1", + "\u05d7\u05e1\u05df", + "\u05dc\u05d9\u05d0\u05d4", + "\u05d2'\u05d5\u05d3", + "\u05e9\u05de\u05e2\u05d5\u05df", + "\u05e0\u05d4\u05d5\u05e8\u05d0\u05d9", + "\u05d0\u05dc\u05de\u05d0", + "\u05d2\u05dc\u05e2\u05d3", + "\u05d9\u05e0\u05d5\u05df", + "\u05de\u05ea\u05df", + "\u05e9\u05d0\u05dd", + "\u05d0\u05d7\u05de\u05d3", + "\u05d9\u05d4\u05d1", + "\u05d2'\u05d5\u05dc\u05d9\u05df", + "\u05d0\u05d9\u05d9\u05dc\u05d4", + "\u05e8\u05d1\u05d9\u05d3", + "\u05d0\u05d9\u05d9\u05d3\u05dc", + "\u05e9\u05d5\u05d4\u05dd", + "\u05e0\u05d9\u05ea\u05d0\u05d9", + "\u05d4\u05d3\u05e8", + "\u05d0\u05de\u05d9", + "\u05d6\u05d0\u05d1", + "\u05ea\u05d0\u05dc\u05d0", + "\u05d9\u05dd", + "\u05d9\u05d4\u05d5\u05e9\u05e2", + "\u05dc\u05d9\u05d9\u05d4", + "\u05d0\u05de\u05e8\u05d9", + "\u05db\u05e4\u05d9\u05e8", + "\u05e0\u05d2\u05d4", + "\u05e2\u05d8\u05e8\u05d4", + "\u05d0\u05d1\u05d9\u05e2\u05d3", + "\u05e0\u05d1\u05d5", + "\u05d0\u05dc\u05d9\u05d0\u05d1", + "\u05d4\u05d9\u05d9\u05dc\u05d9", + "\u05d1\u05d9\u05e1\u05d0\u05df", + "\u05e0\u05d5\u05d4", + "\u05db\u05e0\u05e8\u05ea", + "\u05d0\u05d9\u05dc\u05ea", + "\u05e8\u05df", + "\u05d0\u05de\u05dc\u05d9", + "\u05de\u05e0\u05d5\u05e8", + "\u05e8\u05d5\u05df", + "\u05d1\u05d5\u05e2\u05d6", + "\u05ea\u05d4\u05dc\u05d4", + "\u05e0\u05d0\u05d9\u05d4", + "\u05e0\u05d5\u05e8", + "\u05e0\u05d0\u05d5\u05e8", + "\u05d2'\u05d5\u05d6\u05e3", + "\u05e2\u05dc\u05d9", + "\u05d8\u05dc", + "\u05d0\u05d5\u05e9\u05e8\u05d9", + "\u05d0\u05d5\u05e8\u05df", + "\u05e2\u05d3\u05d9", + "\u05e9\u05d0\u05d5\u05dc", + "\u05e9\u05de\u05d5\u05d0\u05dc", + "\u05e8\u05d9\u05dd", + "\u05d0\u05e0\u05d4", + "\u05d0\u05dc\u05d9\u05d0\u05d5\u05e8", + "\u05d0\u05d1\u05d9\u05ea\u05e8", + "\u05e2\u05de\u05d9\u05d7\u05d9", + "\u05e2\u05d3\u05df", + "\u05de\u05e9\u05d4", + "\u05e0\u05e2\u05de\u05d4", + "\u05d0\u05d9\u05dc\u05df", + "\u05d0\u05e9\u05e8", + "\u05e8\u05d9\u05e3", + "\u05d0\u05de\u05d5\u05e0\u05d4", + "\u05d9\u05d4\u05dc", + "\u05e9\u05e0\u05d9\u05d0\u05d5\u05e8", + "\u05e2\u05d5\u05de\u05e8", + "\u05d0\u05dc\u05d5\u05df", + "\u05dc\u05d9\u05e8\u05d5\u05d9", + "\u05d1\u05dc\u05d5\u05de\u05d4", + "\u05d9\u05d0\u05e8\u05d0", + "\u05dc\u05d9\u05d4\u05d9\u05d0", + "\u05d8\u05dc\u05d9\u05d4", + "\u05e9\u05e4\u05e8\u05d4", + "\u05e0\u05d9\u05e7\u05d4", + "\u05d8\u05d5\u05d4\u05e8", + "\u05d9\u05d5\u05d7\u05d0\u05d9", + "\u05d9\u05d5\u05d8\u05d0", + "\u05d9\u05d5\u05d2\u05d1", + "\u05de\u05d0\u05d9", + "\u05d9\u05e0\u05d9\u05d1", + "\u05d0\u05d9\u05ea\u05d9\u05d0\u05dc", + "\u05dc\u05d0\u05d5\u05df", + "\u05d4\u05dc\u05dc\u05d9", + "\u05d1\u05d9\u05d0\u05df", + "\u05e2\u05d8\u05e8\u05ea", + "\u05d3\u05d5\u05e8", + "\u05e4\u05dc\u05d2", + "\u05e8\u05d9\u05ea\u05d0\u05d2'", + "\u05e0\u05e8\u05d9\u05d4", + "\u05d3\u05d5\u05e8\u05d5\u05df", + "\u05e1\u05d9\u05e0\u05d9", + "\u05e8\u05e2\u05d5\u05ea", + "\u05e8\u05e2\u05d9", + "\u05de\u05dc\u05db\u05d4", + "\u05de\u05d9\u05e9\u05dc", + "\u05d0\u05e4\u05e8\u05d9\u05dd", + "\u05d0\u05d9\u05dc\u05d5\u05df", + "\u05e1\u05d5\u05e4\u05d9\u05d4", + "\u05e0\u05e2\u05de\u05d9", + "\u05e6\u05e4\u05d5\u05e8\u05d4", + "\u05e9\u05d9\u05e8", + "\u05de\u05e8\u05d9\u05d4", + "\u05d7\u05d5\u05d4", + "\u05dc\u05d0\u05d4", + "\u05e4\u05e8\u05d9\u05d9\u05d3\u05d0", + "\u05d9\u05d6\u05df", + "\u05dc\u05d9\u05d4", + "\u05e7\u05d5\u05e8\u05df", + "\u05e8\u05e0\u05d9", + "\u05e1\u05d9\u05dc\u05d0", + "\u05d1\u05e0\u05d9\u05de\u05d9\u05df", + "\u05d9\u05e2\u05dc", + "\u05d3\u05d5\u05e8\u05d9\u05df", + "\u05e0\u05d9\u05e1\u05d9\u05dd", + "\u05d0\u05d3\u05dd", + "\u05d0\u05dc\u05d7\u05e0\u05df", + "\u05e8\u05d9\u05de\u05d0\u05e1", + "\u05d0\u05d5\u05e8", + "\u05d0\u05d9\u05d9\u05dc\u05ea", + "\u05e9\u05e7\u05d3", + "\u05e8\u05d5\u05dd", + "\u05d2\u05dc", + "\u05d3\u05d9\u05e0\u05d4", + "\u05d4\u05e0\u05d9\u05d4", + "\u05e1\u05dc\u05de\u05d0", + "\u05e2\u05e0\u05d0\u05dc", + "\u05d0\u05d5\u05d5\u05d4", + "\u05e0\u05d0\u05d9\u05d0", + "\u05d9\u05d0\u05e1\u05d9\u05df", + "\u05d0\u05dc\u05d9", + "\u05d0\u05d9\u05d9\u05dc", + "\u05d4\u05e8\u05d0\u05dc", + "\u05ea\u05d5\u05de\u05e8", + "\u05d7\u05df", + "\u05de\u05dc\u05d0\u05db\u05d9", + "\u05e2\u05d1\u05d3", + "\u05d0\u05dc\u05d9\u05d4\u05d5", + "\u05de\u05d0\u05d9\u05d4", + "\u05d9\u05d7\u05d9\u05d0", + "\u05d0\u05de\u05d5\u05e8", + "\u05e2\u05d5\u05d1\u05d3\u05d9\u05d4", + "\u05d6\u05d9\u05e0\u05d4", + "\u05d0\u05d1\u05d9\u05d2\u05d9\u05dc", + "\u05d0\u05dc\u05d9\u05d0\u05dc", + "\u05d3\u05e8\u05d5\u05e8", + "\u05d2'\u05e0\u05d0", + "\u05d4\u05d3\u05e1\u05d4", + "\u05d0\u05e8\u05d0\u05dc", + "\u05de\u05d9\u05dc\u05d0\u05df", + "\u05de\u05d9\u05ea\u05e8", + "\u05ea\u05d1\u05d5\u05e8", + "\u05e8\u05d9\u05e0\u05d4", + "\u05de\u05d9\u05dc\u05d4", + "\u05d0\u05dc\u05db\u05e1", + "\u05de\u05d0\u05d5\u05e8", + "\u05e8\u05d9\u05de\u05d0", + "\u05e9\u05d5\u05e9\u05e0\u05d4", + "\u05d0\u05dc\u05d9\u05e1", + "\u05d9\u05d5\u05d0\u05dc", + "\u05e0\u05d9\u05dc", + "\u05e2\u05e8\u05df", + "\u05d2'\u05d5\u05dc\u05d9", + "\u05d9\u05e2\u05e8\u05d4", + "\u05d0\u05d1\u05d9\u05e9\u05d2", + "\u05d0\u05d5\u05d3\u05dc", + "\u05d0\u05dc\u05d9\u05e1\u05d4", + "\u05d3\u05e0\u05d9\u05d0\u05dc\u05d4", + "\u05d0\u05dc\u05d9\u05e8\u05df", + "\u05d2\u05dc\u05d9", + "\u05e8\u05d5\u05e0\u05d9", + "\u05de\u05d9\u05dc\u05d0", + "\u05e2\u05d3\u05d9\u05d4", + "\u05e1\u05e2\u05e8", + "\u05d0\u05d5\u05e8\u05d0\u05dc", + "\u05e1\u05e4\u05d9\u05e8", + "\u05dc\u05d9\u05d0\u05d1", + "\u05d0\u05dc\u05d9\u05e9\u05e2", + "\u05d1\u05e8\u05d5\u05da", + "\u05d0\u05d9\u05d4", + "\u05d3\u05df", + "\u05dc\u05d9\u05dc\u05d9", + "\u05ea\u05d9\u05d0", + "\u05e0\u05d5\u05e4\u05e8", + "\u05d0\u05d7\u05d9\u05d4", + "\u05dc\u05e0\u05d9", + "\u05d2\u05d9\u05dc", + "\u05e0\u05e4\u05ea\u05dc\u05d9", + "\u05d1\u05d9\u05dc\u05d0", + "\u05e9\u05dc\u05d5", + "\u05d2\u05d9\u05dc\u05d9", + "\u05dc\u05d9\u05d0\u05d5", + "\u05e0\u05d9\u05dc\u05d9", + "\u05d9\u05e1\u05de\u05d9\u05df", + "\u05d9\u05e9\u05db\u05e8", + "\u05dc\u05d9\u05d0\u05df", + "\u05d0\u05d7\u05d9\u05e0\u05d5\u05e2\u05dd", + "\u05e0\u05d5\u05e2\u05dd", + "\u05d0\u05d9\u05d0\u05df", + "\u05d6\u05d9\u05d9\u05df", + "\u05e1\u05d0\u05dc\u05d7", + "\u05e7\u05d0\u05e8\u05d9\u05df", + "\u05dc\u05d9\u05d9\u05ea", + "\u05e1\u05d5\u05e4\u05d9", + "\u05e9\u05d9\u05d9\u05e0\u05d0", + "\u05e9\u05d9\u05e8\u05d4", + "\u05d0\u05d1\u05e8\u05d0\u05d4\u05d9\u05dd", + "\u05dc\u05d9\u05e8\u05d6", + "\u05d0\u05dc\u05d9\u05de\u05dc\u05da", + "\u05d1\u05ea_\u05e9\u05d1\u05e2", + "\u05dc\u05d9\u05e2\u05d3", + "\u05e2\u05d9\u05d3\u05d5", + "\u05de\u05ea\u05e0\u05d9\u05d4", + "\u05e9\u05d9\u05d9\u05e0\u05d3\u05dc", + "\u05e2\u05ea\u05d9", + "\u05d7\u05dc\u05d0", + "\u05e2\u05de\u05dc\u05d9\u05d4", + "\u05e2\u05e0\u05d1\u05e8", + "\u05d3\u05e0\u05d4", + "\u05e8\u05d5\u05ea", + "\u05d6\u05d9\u05e0\u05d1", + "\u05e9\u05de\u05d7\u05d4", + "\u05dc\u05d9\u05dc\u05da", + "\u05e1\u05de\u05d0", + "\u05e9\u05dc\u05de\u05d4", + "\u05d3\u05d9\u05df", + "\u05d0\u05d5\u05d4\u05d3", + "\u05e0\u05ea\u05e0\u05d0\u05dc", + "\u05d4\u05d3\u05e1", + "\u05de\u05d9\u05e8\u05d0\u05dc", + "\u05d2'\u05d5\u05e8\u05d9", + "\u05d4\u05d5\u05d3\u05d9\u05d4", + "\u05e2\u05d1\u05e8\u05d9", + "\u05ea\u05d4\u05d9\u05dc\u05d4", + "\u05d0\u05d5\u05e4\u05dc", + "\u05dc\u05d9\u05d0\u05d5\u05e8", + "\u05de\u05d5\u05d7\u05de\u05d3", + "\u05dc\u05d9\u05e0\u05d5\u05d9", + "\u05ea\u05d1\u05dc", + "\u05d0\u05d5\u05d3\u05d9\u05d4", + "\u05d0\u05dc\u05e2\u05d3", + "\u05d0\u05d5\u05e8\u05d9\u05d0\u05df", + "\u05e2\u05d9\u05dc\u05d9", + "\u05d3\u05e4\u05e0\u05d4", + "\u05dc\u05d9\u05d3\u05d5\u05e8", + "\u05d0\u05dc\u05d9\u05e8\u05d6", + "\u05de\u05e8\u05d5\u05dd", + "\u05d9\u05d4\u05dc\u05d9", + "\u05e2\u05e0\u05d4\u05d0\u05dc", + "\u05e2\u05d3\u05d9\u05d0\u05dc", + "\u05d9\u05d5\u05d1\u05dc", + "\u05d0\u05dc\u05e8\u05d5\u05d0\u05d9", + "\u05d0\u05d9\u05de\u05e8\u05d9", + "\u05e7\u05d3\u05dd", + "\u05ea\u05d0\u05d9\u05e8", + "\u05d0\u05d9\u05dc\u05d9\u05df", + "\u05d0\u05dc\u05db\u05e1\u05e0\u05d3\u05e8", + "\u05e0\u05d9\u05e8", + "\u05d0\u05dc\u05e2\u05d6\u05e8", + "\u05d2\u05d9\u05dc\u05d4", + "\u05e0\u05d0\u05d9", + "\u05de\u05d9\u05e7\u05d4", + "\u05dc\u05d9\u05e2\u05dd", + "\u05e9\u05d9", + "\u05d0\u05de\u05d9\u05dc\u05d9", + "\u05e4\u05e0\u05d9\u05e0\u05d4", + "\u05e0\u05d9\u05d1", + "\u05ea\u05de\u05e8\u05d4", + "\u05d9\u05d5\u05db\u05d1\u05d3", + "\u05d2'\u05d5\u05dc\u05d9\u05d0\u05df", + "\u05ea\u05d9\u05d9\u05dd", + "\u05de\u05d5\u05e8\u05d9\u05d4", + "\u05e2\u05d3\u05d9\u05e0\u05d4", + "\u05d9\u05e9\u05d9", + "\u05d0\u05df", + "\u05de\u05d9\u05d8\u05dc", + "\u05d3\u05d5\u05dc\u05d1", + "\u05dc\u05de\u05d0\u05e8", + "\u05e6\u05d5\u05e8", + "\u05de\u05e0\u05d5\u05d7\u05d4", + "\u05d1\u05e6\u05dc\u05d0\u05dc", + "\u05dc\u05d9\u05e8\u05d9", + "\u05d2\u05d1\u05e2", + "\u05d9\u05d4\u05d5\u05e0\u05ea\u05df", + "\u05dc\u05d9\u05d0\u05dc", + "\u05d0\u05de\u05d4", + "\u05e8\u05e4\u05d0\u05dc", + "\u05d3\u05d9\u05de\u05d0", + "\u05e8\u05d4\u05e3", + "\u05dc\u05d9\u05e8\u05d5\u05df", + "\u05d0\u05d9\u05d9\u05de\u05d9", + "\u05d9\u05e2\u05e7\u05d1", + "\u05dc\u05d5\u05e8", + "\u05d0\u05d9\u05ea\u05de\u05e8", + "\u05d0\u05d3\u05e8", + "\u05d8\u05d5\u05de\u05d9", + "\u05d2\u05d6\u05dc", + "\u05d0\u05d9\u05ea\u05d9", + "\u05d2\u05d5\u05d3", + "\u05d9\u05d7\u05d9\u05d0\u05dc", + "\u05e8\u05d5\u05e0\u05d4", + "\u05de\u05d5\u05e1\u05d8\u05e4\u05d0", + "\u05de\u05d9\u05d0\u05e8", + "\u05d4\u05d9\u05dc\u05dc", + "\u05d0\u05d9\u05de\u05d0\u05df", + "\u05dc\u05d9\u05df", + "\u05de\u05d9\u05e8\u05d9\u05dc", + "\u05e7\u05d9\u05dd", + "\u05e0\u05d5\u05e2\u05d4", + "\u05d8\u05d5\u05dd", + "\u05dc\u05d5\u05d8\u05dd", + "\u05d2\u05d5\u05e8", + "\u05d0\u05dc\u05d9\u05e0\u05d5\u05e8", + "\u05d0\u05d9\u05dc\u05d9\u05d9", + "\u05e9\u05d2\u05d1", + "\u05d9\u05e6\u05d7\u05e7", + "\u05e0\u05d8\u05dc\u05d9", + "\u05d0\u05e8\u05d9", + "\u05d0\u05d1\u05d9\u05d4\u05d5", + "\u05e8\u05e2\u05d9\u05d4", + "\u05d9\u05e8\u05d9\u05df", + "\u05e9\u05d5\u05dc\u05de\u05d9\u05ea", + "\u05ea\u05d5\u05dc\u05d9\u05df", + "\u05d2\u05d9\u05d8\u05dc", + "\u05db\u05e8\u05de\u05dc", + "\u05d0\u05d5\u05d3\u05dc\u05d9\u05d4", + "\u05d9\u05d4\u05d5\u05d3\u05d9\u05ea", + "\u05d3\u05d1\u05d9\u05e8", + "\u05d0\u05d1\u05e8\u05d4\u05dd", + "\u05d0\u05e0\u05d0\u05d1\u05dc", + "\u05dc\u05d9\u05d0\u05dd", + "\u05d0\u05d5\u05e8\u05d9\u05d4", + "\u05e7\u05d5\u05e1\u05d0\u05d9", + "\u05d7\u05d9\u05d4", + "\u05d9\u05d5\u05dc\u05d9", + "\u05d0\u05d1\u05d9\u05d1", + "\u05d2\u05d9\u05d0", + "\u05d9\u05e9\u05e9\u05db\u05e8", + "\u05e6\u05d1\u05d9\u05d4", + "\u05d0\u05dc\u05e8\u05d5\u05e2\u05d9", + "\u05d9\u05e1\u05db\u05d4", + "\u05d9\u05e7\u05d9\u05e8", + "\u05d0\u05d3\u05dc", + "\u05d0\u05dc\u05d9\u05e2\u05e0\u05d4", + "\u05d0\u05de\u05d9\u05dc\u05d9\u05d4", + "\u05de\u05d9\u05dc\u05d9", + "\u05e2\u05d5\u05e4\u05e8\u05d9", + "\u05de\u05e9\u05d9", + "\u05ea\u05d5\u05dd", + "\u05db\u05e8\u05d9\u05e1\u05d8\u05d9\u05d0\u05df", + "\u05d0\u05d5\u05e8\u05d4", + "\u05de\u05d9\u05db\u05dc", + "\u05d0\u05d5\u05e4\u05d9\u05e8", + "\u05d0\u05e8\u05d9\u05d0\u05dc", + "\u05d0\u05d3\u05d5\u05d4", + "\u05d0\u05d5\u05e8\u05d9\u05d0\u05dc", + "\u05d5\u05e8\u05d3", + "\u05e8\u05dd", + "\u05d0\u05dc\u05d9\u05e2\u05d6\u05e8", + "\u05de\u05d9\u05db\u05d0\u05dc", + "\u05e9\u05d9\u05e8\u05d9", + "\u05e0\u05d7\u05de\u05df", + "\u05d9\u05e9\u05e8\u05d0\u05dc", + "\u05de\u05d2'\u05d3", + "\u05d0\u05dc\u05d9\u05d0\u05e1", + "\u05e2\u05d9\u05d3\u05df", + "\u05d0\u05dc\u05d4", + "\u05e7\u05e8\u05df", + "\u05d1\u05e0\u05d9\u05d4\u05d5", + "\u05e6\u05d5\u05e4\u05d9\u05d4", + "\u05d0\u05dc\u05d9\u05d4", + "\u05d9\u05e9\u05e2\u05d9\u05d4", + "\u05d0\u05d4\u05e8\u05d5\u05df", + "\u05d9\u05d2\u05dc", + "\u05d7\u05e0\u05d4", + "\u05d3\u05e0\u05d9", + "\u05ea\u05de\u05e8", + "\u05d1\u05e8\u05e7", + "\u05d0\u05dc\u05d3\u05e8", + "\u05d1\u05ea", + "\u05d0\u05dc\u05d9\u05d0\u05e0\u05d4", + "\u05e9\u05dc\u05d9\u05d5", + "\u05d9\u05e4\u05d4", + "\u05de\u05d0\u05d9\u05e8", + "\u05dc\u05d9\u05d1\u05d9", + "\u05d9\u05d5\u05d0\u05d1", + "\u05d2'\u05d5\u05d0\u05dc", + "\u05de\u05e8\u05d9\u05dd", + "\u05e4\u05e8\u05d7", + "\u05e8\u05d5\u05d7\u05de\u05d4", + "\u05d0\u05d9\u05ea\u05df", + "\u05de\u05e2\u05d9\u05d9\u05df", + "\u05d1\u05e0\u05d9\u05d4", + "\u05d7\u05e0\u05d5\u05da", + "\u05d9\u05e8\u05d3\u05df", + "\u05d7\u05d2\u05d9\u05ea", + "\u05e0\u05d0\u05d5\u05d4", + "\u05d0\u05de\u05dc", + "\u05e8\u05d0\u05dd", + "\u05d4\u05dc\u05dc", + "\u05ea\u05d4\u05dc", + "\u05d2\u05d0\u05d9\u05d4", + "\u05e2\u05d5\u05de\u05e8\u05d9", + "\u05e4\u05d9\u05d2\u05d0", + "\u05d0\u05d1\u05d9\u05e9\u05d9", + "\u05e0\u05d9\u05e0\u05d4", + "\u05e8\u05d1\u05e7\u05d4", + "\u05e4\u05e0\u05d7\u05e1", + "\u05d4\u05d9\u05e0\u05d3\u05d0", + "\u05d9\u05d4\u05d5\u05d3\u05d4", + "\u05e9\u05e8\u05d1\u05dc", + "\u05e2\u05d1\u05d3\u05d0\u05dc\u05dc\u05d4", + "\u05d0\u05de\u05d9\u05ea\u05d9", + "\u05d2\u05d5\u05dc\u05d3\u05d4", + "\u05e8\u05d5\u05ea\u05dd", + "\u05d0\u05e1\u05ea\u05e8", + "\u05db\u05dc\u05d9\u05dc", + "\u05d0\u05dc\u05e7\u05e0\u05d4", + "\u05e9\u05e0\u05d9", + "\u05d6\u05d4\u05d1\u05d4", + "\u05e9\u05d4\u05d3", + "\u05d0\u05d5\u05e8\u05d5\u05df", + "\u05d7\u05d5\u05e1\u05d9\u05df", + "\u05d8\u05dc\u05d9", + "\u05e4\u05d0\u05d8\u05de\u05d4", + "\u05d9\u05d5\u05ea\u05dd", + "\u05db\u05e8\u05dd", + "\u05e8\u05d0\u05d5\u05d1\u05df", + "\u05ea\u05d0\u05dc\u05d9\u05df", + "\u05d1\u05d0\u05e8\u05d9", + "\u05d0\u05d1\u05d9\u05d7\u05d9", + "\u05e0\u05ea\u05df", + "\u05d3\u05e0\u05d9\u05d0\u05dc", + "\u05de\u05d9\u05d0\u05dc", + "\u05d0\u05d5\u05e8\u05d9", + "\u05e2\u05e0\u05d1\u05dc", + "\u05e0\u05d9\u05e6\u05df", + "\u05e8\u05e4\u05d9\u05e3", + "\u05e9\u05d5\u05d1\u05dc", + "\u05e1\u05d5\u05dc", + "\u05d9\u05d0\u05de\u05df", + "\u05e0\u05d5\u05d9", + "\u05d9\u05d7\u05d6\u05e7\u05d0\u05dc", + "\u05d2\u05d5\u05e8\u05d9", + "\u05e8\u05d6", + "\u05d0\u05dc\u05de\u05d5\u05d2", + "\u05e9\u05dc\u05d5\u05dd", + "\u05d0\u05dc\u05d5\u05e0\u05d4", + "\u05dc\u05d9\u05d8\u05dc", + "\u05e1\u05d9\u05dc\u05d9\u05df", + "\u05d1\u05e8", + "\u05e2\u05d5\u05e4\u05e8", + "\u05dc\u05d9", + "\u05d2'\u05d5\u05d9\u05dc", + "\u05d0\u05e8\u05d9\u05d4", + "\u05de\u05d5\u05e8", + "\u05d9\u05e0\u05d0\u05d9", + "\u05e1\u05ea\u05d9\u05d5", + "\u05d0\u05e0\u05d9\u05dc", + "\u05d3\u05d9\u05dc\u05df", + "\u05d9\u05d5\u05e0\u05ea\u05df", + "\u05de\u05d9\u05e8\u05d0", + "\u05d9\u05d0\u05d9\u05e8", + "\u05d2'\u05d5\u05e8\u05d2'", + "\u05e9\u05d9_\u05dc\u05d9", + "\u05e9\u05d9\u05dc\u05d4", + "\u05e2\u05de\u05d9\u05ea", + "\u05e1\u05de\u05d9\u05e8", + "\u05e9\u05d7\u05e8", + "\u05d0\u05d9\u05d4\u05d0\u05dd", + "\u05db\u05e8\u05d9\u05dd", + "\u05e7\u05e8\u05e0\u05d9", + "\u05e2\u05d9\u05dc\u05d0\u05d9", + "\u05e4\u05e8\u05d9\u05d0\u05dc", + "\u05d0\u05dc\u05d5\u05de\u05d4", + "\u05d0\u05dc\u05d8\u05e2", + "\u05d0\u05dc\u05d9\u05df", + "\u05d0\u05d5\u05e4\u05e7", + "\u05d0\u05e1\u05d9\u05dc", + "\u05d0\u05de\u05d9\u05e8", + "\u05d0\u05e8\u05d1\u05dc", + "\u05e0\u05d9\u05e7\u05d5\u05dc", + "\u05e6\u05d1\u05d9", + "\u05d0\u05d3\u05d9\u05e8", + "\u05e0\u05d7\u05de\u05d4", + "\u05d1\u05e8\u05db\u05d4", + "\u05e1\u05d4\u05e8", + "\u05e8\u05d9\u05d0\u05df", + "\u05d0\u05dc\u05de\u05d4", + "\u05e9\u05d9\u05e8\u05d0\u05dc", + "\u05de\u05e8\u05d3\u05db\u05d9", + "\u05e4\u05d0\u05e8", + "\u05d6\u05d5\u05d0\u05d9", + "\u05e2\u05d5\u05d6", + "\u05dc\u05d9\u05d1\u05d0", + "\u05e9\u05d5\u05df", + "\u05d0\u05d5\u05e9\u05e8", + "\u05d0\u05e1\u05e0\u05ea", + "\u05e9\u05d2\u05d9\u05d0", + "\u05d6\u05d9\u05d5", + "\u05d4\u05e2\u05e0\u05d0", + "\u05e0\u05d8\u05e2", + "\u05d1\u05df", + "\u05d7'\u05d0\u05dc\u05d3", + "\u05d9\u05d5\u05d7\u05e0\u05df", + "\u05de\u05d7\u05de\u05d5\u05d3", + "\u05e0\u05d3\u05d1", + "\u05d8\u05d5\u05d1\u05d4", + "\u05e8\u05d9\u05d9\u05d6\u05dc", + "\u05d0\u05dc\u05d9\u05e9\u05d1\u05e2", + "\u05dc\u05d9\u05d1", + "\u05d3\u05d1\u05d5\u05e8\u05d4", + "\u05d4\u05d9\u05dc\u05d4", + "\u05e9\u05e8\u05d4", + "\u05e9\u05dc\u05d9", + "\u05e8\u05d7\u05dc", + "\u05de\u05ea\u05e0\u05d0\u05dc", + "\u05e1\u05d9\u05d5\u05df", + "\u05dc\u05e0\u05d0", + "\u05d7\u05de\u05d6\u05d4", + "\u05d0\u05d2\u05dd", + "\u05d9\u05d3\u05d9\u05d3\u05d9\u05d4", + "\u05d0\u05e4\u05e7", + "\u05d2\u05e4\u05df", + "\u05d1\u05ea\u05d9\u05d4", + "\u05d0\u05d4\u05d5\u05d1\u05d4", + "\u05e2\u05dc\u05de\u05d4", + "\u05e1\u05d0\u05e8\u05d9", + "\u05d0\u05d1\u05d9\u05d0\u05dc", + "\u05e9\u05d9\u05dc\u05ea", + "\u05e0\u05d7", + "\u05e8\u05d5\u05d9", + "\u05e9\u05d8\u05e2\u05e8\u05e0\u05d0", + "\u05ea\u05de\u05d9\u05e8", + "\u05e0\u05d5\u05d9\u05d4", + "\u05de\u05d9\u05d9\u05d4", + "\u05d0\u05e1\u05e3", + "\u05d3\u05d5\u05d3" + ], + "LAST_NAME": [ + "\u05e9\u05d1\u05ea\u05d0\u05d9", + "\u05e2\u05de\u05d0\u05e9", + "\u05de\u05d5\u05e1\u05d0", + "\u05dc\u05d5\u05d9", + "\u05d0\u05dc\u05e1\u05d9\u05d9\u05d3", + "\u05de\u05d5\u05e2\u05dc\u05dd", + "\u05d5\u05d5\u05dc\u05e3", + "\u05de\u05d6\u05d5\u05e8", + "\u05d1\u05df_\u05d7\u05de\u05d5", + "\u05e8\u05d2\u05d1", + "\u05e1\u05d5\u05e4\u05e8", + "\u05d4\u05d9\u05e8\u05e9", + "\u05d0\u05d5\u05d6\u05df", + "\u05d6\u05d5\u05d4\u05e8", + "\u05d7\u05de\u05d3\u05d0\u05df", + "\u05d9\u05d5\u05e1\u05e3", + "\u05de\u05e0\u05d7\u05dd", + "\u05e8\u05d5\u05d1\u05d9\u05df", + "\u05d1\u05df_\u05d3\u05d5\u05d3", + "\u05d2\u05d5\u05dc\u05d3\u05d1\u05e8\u05d2", + "\u05d7\u05d9", + "\u05d0\u05d1\u05e8\u05d4\u05de\u05d9", + "\u05d0\u05d1\u05d9\u05d8\u05dc", + "\u05d9\u05e2\u05e7\u05d5\u05d1\u05d9", + "\u05e1\u05e8\u05d5\u05e1\u05d9", + "\u05d0\u05d1\u05e8\u05de\u05d5\u05d1", + "\u05d0\u05de\u05e8", + "\u05d3\u05d4\u05d0\u05df", + "\u05e4\u05d9\u05e0\u05d8\u05d5", + "\u05e9\u05e4\u05e8", + "\u05d1\u05e8\u05d0\u05d5\u05df", + "\u05d7'\u05dc\u05d9\u05dc", + "\u05d1\u05e8\u05d2\u05e8", + "\u05d0\u05d9\u05d1\u05d2\u05d9", + "\u05e9\u05db\u05d8\u05e8", + "\u05d0\u05e8\u05d6", + "\u05d0\u05d4\u05e8\u05df", + "\u05e8\u05d5\u05d8\u05e0\u05d1\u05e8\u05d2", + "\u05e9\u05e8\u05d5\u05df", + "\u05d9\u05d5\u05e0\u05e1", + "\u05d7\u05d9\u05d9\u05dd", + "\u05d0\u05d1\u05d5_\u05db\u05e3", + "\u05de\u05e1\u05e8\u05d9", + "\u05de\u05d5\u05e8\u05d0\u05d3", + "\u05e0\u05e1\u05d9\u05dd", + "\u05e1\u05dc\u05de\u05d0\u05df", + "\u05d1\u05dc\u05d5\u05dd", + "\u05d3\u05d2\u05df", + "\u05de\u05e8\u05d2\u05dc\u05d9\u05ea", + "\u05dc\u05d1\u05d9\u05d0", + "\u05d3\u05d9\u05d9\u05df", + "\u05d7\u05e1\u05df", + "\u05e9\u05d9\u05d1\u05dc\u05d9", + "\u05e9\u05de\u05e2\u05d5\u05df", + "\u05d2\u05d5\u05d8\u05dc\u05d9\u05d1", + "\u05d2\u05dc\u05e2\u05d3", + "\u05e8\u05d5\u05d6\u05e0\u05d1\u05e8\u05d2", + "\u05d0\u05d7\u05de\u05d3", + "\u05dc\u05d4\u05d1", + "\u05d0\u05e1\u05e2\u05d3", + "\u05e2\u05de\u05e8\u05dd", + "\u05d7\u05d9\u05d9\u05de\u05d5\u05d1", + "\u05e8\u05d1\u05d9\u05d1\u05d5", + "\u05d4\u05d3\u05e8", + "\u05e4\u05e8\u05e7\u05e9", + "\u05e9\u05d8\u05d9\u05d9\u05df", + "\u05e1\u05e8\u05d7\u05d0\u05df", + "\u05dc\u05d5\u05d2\u05e1\u05d9", + "\u05d5\u05d9\u05e1", + "\u05e2\u05d6\u05d0\u05dd", + "\u05e1\u05d1\u05d7", + "\u05e0\u05e1\u05d0\u05e8", + "\u05d7\u05d9\u05d5\u05df", + "\u05e8\u05d5\u05df", + "\u05d2\u05d0\u05d1\u05e8", + "\u05d0\u05d8\u05e8\u05e9", + "\u05e2\u05d6\u05e8", + "\u05e1\u05dc\u05d0\u05de\u05d4", + "\u05e0\u05d0\u05d5\u05e8", + "\u05e2\u05dc\u05d9", + "\u05d8\u05dc", + "\u05e9\u05de\u05e2\u05d5\u05e0\u05d9", + "\u05de\u05e8\u05e6\u05d9\u05d0\u05e0\u05d5", + "\u05d0\u05d5\u05e8\u05df", + "\u05e9\u05e8\u05d9\u05e7\u05d9", + "\u05d5\u05d9\u05e0\u05e8", + "\u05e9\u05d0\u05d5\u05dc", + "\u05d4\u05d5\u05e8\u05d1\u05d9\u05e5", + "\u05e9\u05de\u05d5\u05d0\u05dc", + "\u05e2\u05ea\u05d0\u05de\u05e0\u05d4", + "\u05d7\u05d8\u05d9\u05d1", + "\u05e1\u05dc\u05d9\u05de\u05d0\u05df", + "\u05e9\u05d0\u05d4\u05d9\u05df", + "\u05e9\u05d5\u05d5\u05e8\u05e5", + "\u05e9\u05e0\u05d9\u05d9\u05d3\u05e8", + "\u05de\u05e9\u05d4", + "\u05e2\u05d9\u05e1\u05d0", + "\u05d2\u05dc\u05d9\u05e7", + "\u05d0\u05d1\u05d5_\u05e1\u05d0\u05dc\u05d7", + "\u05e8\u05d5\u05d8", + "\u05db\u05d4\u05df", + "\u05d0\u05e9\u05e8", + "\u05d1\u05df_\u05d4\u05e8\u05d5\u05e9", + "\u05e2\u05de\u05d9\u05e8\u05d4", + "\u05de\u05e0\u05d3\u05dc", + "\u05e2\u05d5\u05de\u05e8", + "\u05e4\u05d3\u05d9\u05d3\u05d4", + "\u05d2\u05e0\u05d0\u05d9\u05dd", + "\u05e7\u05d0\u05d5\u05e4\u05de\u05df", + "\u05d0\u05dc\u05d5\u05df", + "\u05e9\u05d7\u05d0\u05d3\u05d4", + "\u05e1\u05dc\u05d5\u05de\u05d5\u05df", + "\u05e1\u05e8\u05d5\u05e8", + "\u05e2\u05d5\u05d3\u05d4", + "\u05d1\u05e8\u05e0\u05e9\u05d8\u05d9\u05d9\u05df", + "\u05e9\u05e4\u05d9\u05e8\u05d0", + "\u05de\u05e8\u05e7\u05d5\u05d1\u05d9\u05e5", + "\u05e8\u05d7\u05de\u05d9\u05dd", + "\u05de\u05dc\u05de\u05d3", + "\u05d5\u05ea\u05d3", + "\u05d0\u05e8\u05dc\u05d9\u05da", + "\u05de\u05d5\u05e9\u05e7\u05d5\u05d1\u05d9\u05e5", + "\u05d3\u05d0\u05d5\u05d3", + "\u05e4\u05dc\u05d2", + "\u05e4\u05d5\u05e8\u05ea", + "\u05e1\u05d9\u05e0\u05d9", + "\u05d3\u05d5\u05e8\u05d5\u05df", + "\u05d0\u05dc\u05de\u05dc\u05d7", + "\u05d1\u05df_\u05de\u05e9\u05d4", + "\u05de\u05d3\u05e8", + "\u05e0\u05d7\u05de\u05d9\u05d0\u05e1", + "\u05e2\u05d6\u05e8\u05df", + "\u05de\u05dc\u05db\u05d4", + "\u05d6\u05d9\u05d3\u05d0\u05df", + "\u05e6\u05d1\u05e8\u05d9", + "\u05e0\u05d7\u05de\u05e0\u05d9", + "\u05d0\u05d8\u05d9\u05d0\u05e1", + "\u05d7\u05d6\u05df", + "\u05d0\u05dc\u05e7\u05d9\u05d9\u05dd", + "\u05e7\u05dc\u05d9\u05d9\u05df", + "\u05db\u05e1\u05e4\u05d9", + "\u05e7\u05d5\u05e8\u05df", + "\u05de\u05e8\u05e2\u05d9", + "\u05e1\u05e2\u05d3", + "\u05d1\u05e0\u05d9\u05de\u05d9\u05df", + "\u05d1\u05df_\u05e9\u05d1\u05ea", + "\u05de\u05e9\u05d5\u05dc\u05dd", + "\u05d0\u05d1\u05d5_\u05e1\u05e0\u05d9\u05e0\u05d4", + "\u05d4\u05dc\u05d5\u05d9", + "\u05e0\u05d5\u05d9\u05de\u05df", + "\u05d3\u05d4\u05df", + "\u05e9\u05d5\u05e8\u05e5", + "\u05d8\u05d5\u05d9\u05d8\u05d5", + "\u05d0\u05d5\u05e8", + "\u05e1\u05e2\u05d3\u05d4", + "\u05e4\u05dc\u05d3", + "\u05e9\u05e7\u05d3", + "\u05d9\u05e2\u05e7\u05d5\u05d1\u05d5\u05d1", + "\u05d2\u05dc", + "\u05de\u05e1\u05d9\u05e7\u05d4", + "\u05e7\u05de\u05d7\u05d9", + "\u05d2'\u05d1\u05d0\u05e8\u05d9\u05df", + "\u05d0\u05d9\u05e1\u05e7\u05d5\u05d1", + "\u05e9\u05e8\u05e2\u05d1\u05d9", + "\u05d0\u05d6\u05d1\u05e8\u05d2\u05d4", + "\u05e4\u05e8\u05d9\u05d3", + "\u05d9\u05d0\u05e1\u05d9\u05df", + "\u05e2\u05d5\u05d0\u05d3", + "\u05e9\u05d5\u05d5\u05d9\u05e7\u05d9", + "\u05d4\u05e8\u05d0\u05dc", + "\u05d7\u05df", + "\u05d6\u05d2\u05d5\u05e8\u05d9", + "\u05d1\u05df_\u05dc\u05d5\u05dc\u05d5", + "\u05d0\u05dc\u05d9\u05d4\u05d5", + "\u05d0\u05d1\u05d5_\u05de\u05d5\u05da", + "\u05de\u05dc\u05d5\u05dc", + "\u05d0\u05d9\u05e4\u05e8\u05d2\u05df", + "\u05d0\u05dc\u05e7\u05e8\u05d9\u05e0\u05d0\u05d5\u05d9", + "\u05d0\u05e8\u05d1\u05d9\u05d1", + "\u05d1\u05d5\u05e1\u05e7\u05d9\u05dc\u05d4", + "\u05d9\u05d7\u05d9\u05d0", + "\u05d9\u05e8\u05d5\u05e9\u05dc\u05de\u05d9", + "\u05d0\u05d1\u05d9\u05d8\u05d1\u05d5\u05dc", + "\u05e1\u05d5\u05d9\u05e1\u05d4", + "\u05e1\u05e2\u05d9\u05d3", + "\u05e2\u05d5\u05d1\u05d3\u05d9\u05d4", + "\u05e9\u05d8\u05e8\u05df", + "\u05ea\u05d5\u05e8\u05d2\u05de\u05df", + "\u05d3\u05e8\u05d5\u05e8", + "\u05e6\u05e8\u05e4\u05ea\u05d9", + "\u05e0\u05d0\u05e1\u05e8", + "\u05d7\u05d2'\u05d0\u05d6\u05d9", + "\u05d7\u05d5\u05e8\u05d9", + "\u05e2\u05dc\u05d9\u05d0\u05df", + "\u05d0\u05d1\u05d5_\u05e8\u05de\u05d9\u05dc\u05d4", + "\u05d7\u05dc\u05d1\u05d9", + "\u05e8\u05d5\u05d6\u05e0\u05e4\u05dc\u05d3", + "\u05de\u05d0\u05d5\u05e8", + "\u05e7\u05d0\u05e1\u05dd", + "\u05e6\u05de\u05d7", + "\u05d7\u05d0\u05d2_\u05d9\u05d7\u05d9\u05d0", + "\u05d6\u05d5\u05e2\u05d1\u05d9", + "\u05de\u05e1\u05d0\u05e8\u05d5\u05d5\u05d4", + "\u05ea\u05d5\u05e8\u05d2'\u05de\u05df", + "\u05d2\u05d5\u05dc\u05d3\u05de\u05df", + "\u05d2\u05d1\u05d0\u05e8\u05d4", + "\u05d3\u05e8\u05d5\u05e8\u05d9", + "\u05e1\u05e4\u05d9\u05e8", + "\u05d8\u05d0\u05d4\u05d0", + "\u05d1\u05e8\u05d5\u05da", + "\u05d1\u05db\u05e8", + "\u05d9\u05e4\u05e8\u05d7", + "\u05d3\u05d5\u05d9\u05d8\u05e9", + "\u05d0\u05e0\u05d2\u05dc", + "\u05d2\u05d9\u05dc", + "\u05d0\u05d4\u05e8\u05d5\u05e0\u05d9", + "\u05d4\u05e8\u05e9\u05e7\u05d5\u05d1\u05d9\u05e5", + "\u05e9\u05dc\u05d5", + "\u05d0\u05e1\u05d3\u05d9", + "\u05d0\u05d6\u05d5\u05dc\u05d0\u05d9", + "\u05d6\u05d9\u05dc\u05d1\u05e8\u05de\u05df", + "\u05e4\u05d9\u05e0\u05e7\u05dc\u05e9\u05d8\u05d9\u05d9\u05df", + "\u05dc\u05d5\u05d9\u05df", + "\u05e9\u05d8\u05d9\u05d9\u05e0\u05d1\u05e8\u05d2", + "\u05d1\u05d3\u05d9\u05e8", + "\u05d2\u05d5\u05dc\u05d0\u05e0\u05d9", + "\u05e1\u05d0\u05dc\u05d7", + "\u05d0\u05d1\u05e8\u05d0\u05d4\u05d9\u05dd", + "\u05e1\u05e2\u05d3\u05d9", + "\u05d0\u05dc\u05d9\u05de\u05dc\u05da", + "\u05de\u05db\u05dc\u05d5\u05e3", + "\u05e1\u05e8\u05e1\u05d5\u05e8", + "\u05d0\u05de\u05d0\u05e8\u05d4", + "\u05d3\u05e8\u05e2\u05d9", + "\u05e9\u05de\u05d5\u05d0\u05dc\u05d9", + "\u05d1\u05e7\u05e8", + "\u05d0\u05d1\u05d5_\u05dc\u05d9\u05dc", + "\u05db\u05e8\u05de\u05d9", + "\u05d7\u05d1\u05d9\u05d1\u05d0\u05dc\u05dc\u05d4", + "\u05e8\u05d5\u05d8\u05de\u05df", + "\u05e9\u05dc\u05de\u05d4", + "\u05d1\u05e8\u05e7\u05d5\u05d1\u05d9\u05e5", + "\u05e2\u05d0\u05d6\u05dd", + "\u05e2\u05d5\u05d1\u05d3", + "\u05d3\u05e7\u05dc", + "\u05d1\u05e1\u05d5\u05dc", + "\u05de\u05e0\u05e1\u05d5\u05e8", + "\u05d0\u05d1\u05d5_\u05e2\u05e8\u05d0\u05e8", + "\u05de\u05d6\u05e8\u05d7\u05d9", + "\u05e8\u05d5\u05d6\u05df", + "\u05d0\u05dc\u05d5\u05e9", + "\u05e4\u05d5\u05e8\u05de\u05df", + "\u05de\u05d7\u05d0\u05d2'\u05e0\u05d4", + "\u05d6\u05de\u05d9\u05e8", + "\u05d7\u05de\u05d5\u05d3", + "\u05d6\u05db\u05e8\u05d9\u05d4", + "\u05de\u05e0\u05e6\u05d5\u05e8", + "\u05e9\u05e8\u05d1\u05d9\u05d8", + "\u05d4\u05d5\u05e8\u05d5\u05d1\u05d9\u05e5", + "\u05de\u05e8\u05d5\u05dd", + "\u05e2\u05d0\u05de\u05e8", + "\u05d1\u05e8\u05d6\u05d9\u05dc\u05d9", + "\u05e9\u05d5\u05dc\u05de\u05df", + "\u05d0\u05d1\u05e8\u05d2\u05dc", + "\u05d7\u05d3\u05d3", + "\u05d9\u05d5\u05e0\u05d4", + "\u05e2\u05d8\u05d9\u05d4", + "\u05e4\u05e8\u05e5", + "\u05de\u05d8\u05e8", + "\u05e0\u05d9\u05e8", + "\u05e7\u05e4\u05dc\u05df", + "\u05e9\u05dc\u05d1\u05d9", + "\u05e9\u05d9", + "\u05d8\u05d5\u05dc\u05d3\u05e0\u05d5", + "\u05e0\u05ea\u05e9\u05d4", + "\u05d0\u05d5\u05d7\u05e0\u05d4", + "\u05de\u05d7\u05d0\u05de\u05d9\u05d3", + "\u05e0\u05d9\u05e1\u05df", + "\u05d1\u05d3\u05e8", + "\u05d9\u05e9\u05e8\u05d0\u05dc\u05d9", + "\u05e2\u05d0\u05e1\u05dc\u05d4", + "\u05e4\u05d5\u05dc\u05e7", + "\u05e4\u05dc\u05d3\u05de\u05df", + "\u05e4\u05d9\u05e9\u05de\u05df", + "\u05db\u05e5", + "\u05d0\u05d1\u05e8\u05de\u05d5\u05d1\u05d9\u05e5", + "\u05d5\u05e7\u05e0\u05d9\u05df", + "\u05d0\u05d1\u05d5_\u05d0\u05dc_\u05d4\u05d9\u05d2'\u05d0", + "\u05e6\u05d5\u05e8", + "\u05d1\u05df_\u05e2\u05de\u05d9", + "\u05d1\u05e6\u05dc\u05d0\u05dc", + "\u05d2\u05d1\u05e2", + "\u05d4\u05d5\u05e4\u05de\u05df", + "\u05d1\u05df_\u05e2\u05d6\u05e8\u05d0", + "\u05e9\u05de\u05d9\u05e8", + "\u05e4\u05d5\u05d2\u05dc", + "\u05e9\u05d8\u05e8\u05d9\u05ea", + "\u05e8\u05e4\u05d0\u05dc", + "\u05d2\u05d3\u05d9\u05e8", + "\u05e9\u05dd_\u05d8\u05d5\u05d1", + "\u05d9\u05e2\u05e7\u05d1", + "\u05e1\u05d9\u05de\u05df_\u05d8\u05d5\u05d1", + "\u05e2\u05d3\u05d5\u05d9", + "\u05dc\u05d9\u05d1\u05d5\u05d1\u05d9\u05e5", + "\u05e7\u05d5\u05d2\u05df", + "\u05d5\u05d5\u05e7\u05e0\u05d9\u05df", + "\u05de\u05d5\u05d6\u05e1", + "\u05e1\u05d0\u05dc\u05dd", + "\u05db\u05d7\u05dc\u05d5\u05df", + "\u05d9\u05e6\u05d7\u05e7\u05d9", + "\u05d2\u05de\u05dc\u05d9\u05d0\u05dc", + "\u05d1\u05e8\u05d3\u05d4", + "\u05d6\u05d4\u05d1\u05d9", + "\u05de\u05e0\u05e9\u05d4", + "\u05d2\u05d5\u05e8", + "\u05d0\u05dc\u05d5\u05e0\u05d9", + "\u05e9\u05d2\u05d1", + "\u05d9\u05e6\u05d7\u05e7", + "\u05d1\u05df_\u05d7\u05d9\u05d9\u05dd", + "\u05de\u05e1\u05d0\u05e8\u05d5\u05d4", + "\u05dc\u05d9\u05d1\u05e8\u05de\u05df", + "\u05d0\u05d2\u05d1\u05d0\u05e8\u05d9\u05d4", + "\u05d0\u05dc\u05e4\u05e1\u05d9", + "\u05d3\u05d1\u05d9\u05e8", + "\u05d0\u05d1\u05e8\u05d4\u05dd", + "\u05d4\u05d9\u05d9\u05d1", + "\u05de\u05d9\u05de\u05d5\u05df", + "\u05d3\u05d4\u05e8\u05d9", + "\u05d3\u05d5\u05d9\u05d3\u05d5\u05d1", + "\u05d0\u05d5\u05d7\u05d9\u05d5\u05df", + "\u05d3\u05e8\u05d0\u05d5\u05e9\u05d4", + "\u05d4\u05e8\u05e8\u05d9", + "\u05d1\u05e9\u05d9\u05e8", + "\u05e7\u05d9\u05e0\u05df", + "\u05d0\u05d1\u05d9\u05d1", + "\u05d5\u05d9\u05e1\u05de\u05df", + "\u05e8\u05d5\u05e0\u05df", + "\u05d7\u05d0\u05d2'", + "\u05de\u05d9\u05db\u05d0\u05dc\u05d9", + "\u05d1\u05d5\u05d7\u05d1\u05d5\u05d8", + "\u05d5\u05d9\u05e0\u05d1\u05e8\u05d2", + "\u05d0\u05d1\u05d9\u05d8\u05df", + "\u05e0\u05d1\u05d5\u05df", + "\u05e2\u05d1\u05d0\u05e1\u05d9", + "\u05d7\u05d1\u05d9\u05d1", + "\u05d1\u05e9\u05d0\u05e8\u05d4", + "\u05e8\u05d5\u05d6\u05e0\u05d8\u05dc", + "\u05e2\u05d5\u05d6\u05e8\u05d9", + "\u05d0\u05e9\u05db\u05e0\u05d6\u05d9", + "\u05d1\u05d9\u05d8\u05d5\u05df", + "\u05d0\u05d5\u05e4\u05d9\u05e8", + "\u05e1\u05d2\u05dc", + "\u05d2\u05d5\u05dc\u05df", + "\u05e1\u05dc\u05e2", + "\u05d0\u05d1\u05d5\u05d8\u05d1\u05d5\u05dc", + "\u05d7'\u05d8\u05d9\u05d1", + "\u05e4\u05d5\u05e7\u05e1", + "\u05e7\u05e8\u05df", + "\u05d9\u05e9\u05e8\u05d0\u05dc", + "\u05d0\u05dc\u05d9\u05d0\u05e1", + "\u05d8\u05d5\u05d5\u05d9\u05dc", + "\u05e9\u05d5\u05e8", + "\u05e4\u05e8\u05d9", + "\u05d9\u05de\u05d9\u05df", + "\u05d0\u05d4\u05e8\u05d5\u05df", + "\u05d8\u05d9\u05d9\u05d1", + "\u05e2\u05d1\u05d0\u05e1", + "\u05e1\u05d5\u05dc\u05d5\u05de\u05d5\u05df", + "\u05d1\u05df_\u05e1\u05d9\u05de\u05d5\u05df", + "\u05d2\u05d5\u05dc\u05d3\u05e9\u05d8\u05d9\u05d9\u05df", + "\u05d1\u05e8\u05e7", + "\u05d0\u05d1\u05d5_\u05e8\u05d0\u05e1", + "\u05d9\u05e4\u05d4", + "\u05e8\u05d1\u05d9\u05e0\u05d5\u05d1\u05d9\u05e5", + "\u05de\u05d0\u05d9\u05e8", + "\u05e0\u05d7\u05d5\u05dd", + "\u05d1\u05e8\u05de\u05df", + "\u05d7\u05e1\u05d5\u05df", + "\u05e2\u05d5\u05d5\u05d3", + "\u05d0\u05d9\u05dc\u05d5\u05d6", + "\u05d2\u05e8\u05d5\u05e1", + "\u05d2\u05d5\u05dc\u05d3\u05e0\u05d1\u05e8\u05d2", + "\u05d7'\u05d5\u05e8\u05d9", + "\u05d2\u05e8\u05d9\u05df", + "\u05d3\u05d1\u05e9", + "\u05e9\u05d9\u05d8\u05e8\u05d9\u05ea", + "\u05d2\u05d0\u05e0\u05dd", + "\u05d0\u05d9\u05d5\u05d1", + "\u05d4\u05dc\u05dc", + "\u05e1\u05d1\u05d2", + "\u05e7\u05e8\u05de\u05e8", + "\u05d6\u05d9\u05e0\u05d2\u05e8", + "\u05de\u05d5\u05d9\u05d0\u05dc", + "\u05d0\u05d1\u05d5_\u05d8\u05d9\u05e8", + "\u05e4\u05e0\u05d7\u05e1", + "\u05d9\u05d4\u05d5\u05d3\u05d4", + "\u05e4\u05d6", + "\u05d2\u05d1\u05d0\u05d9", + "\u05e2\u05d1\u05d3\u05d0\u05dc\u05dc\u05d4", + "\u05e4\u05e8\u05e0\u05e7\u05dc", + "\u05d7\u05d3\u05d0\u05d3", + "\u05e9\u05e8\u05e3", + "\u05d2\u05d5\u05d0\u05d8\u05d4", + "\u05e9\u05e0\u05d9", + "\u05d9\u05e4\u05ea", + "\u05d5\u05d9\u05d9\u05e1", + "\u05de\u05d9\u05dc\u05e8", + "\u05d0\u05d3\u05dc\u05e8", + "\u05d7\u05d5\u05e1\u05d9\u05df", + "\u05d0\u05dc\u05e0\u05d1\u05d0\u05e8\u05d9", + "\u05e8\u05d5\u05d1\u05d9\u05e0\u05e9\u05d8\u05d9\u05d9\u05df", + "\u05db\u05d4\u05e0\u05d0", + "\u05e8\u05d0\u05d5\u05d1\u05df", + "\u05e2\u05d1\u05d5\u05d3", + "\u05de\u05de\u05df", + "\u05e0\u05ea\u05df", + "\u05d3\u05e0\u05d9\u05d0\u05dc", + "\u05d1\u05d5\u05d6\u05d2\u05dc\u05d5", + "\u05d1\u05df_\u05e9\u05d5\u05e9\u05df", + "\u05e7\u05d3\u05d5\u05e9", + "\u05e1\u05d1\u05df", + "\u05d0\u05e1\u05d5\u05dc\u05d9\u05df", + "\u05d6\u05d4\u05e8", + "\u05d1\u05df_\u05d9\u05d5\u05e1\u05e3", + "\u05d9\u05e2\u05e7\u05d5\u05d1\u05d5\u05d1\u05d9\u05e5", + "\u05e9\u05de\u05e9", + "\u05d7\u05d5\u05d2'\u05d9\u05e8\u05d0\u05ea", + "\u05e0\u05e2\u05d9\u05dd", + "\u05e9\u05d5\u05e9\u05df", + "\u05d3\u05de\u05e8\u05d9", + "\u05d9\u05d7\u05d6\u05e7\u05d0\u05dc", + "\u05d1\u05d3\u05d0\u05e8\u05e0\u05d4", + "\u05d7'\u05dc\u05d0\u05d9\u05dc\u05d4", + "\u05dc\u05d9\u05e4\u05e9\u05d9\u05e5", + "\u05d0\u05dc\u05de\u05d5\u05d2", + "\u05e8\u05d6", + "\u05de\u05d5\u05e1\u05e7\u05d5\u05d1\u05d9\u05e5", + "\u05dc\u05e0\u05d3\u05d0\u05d5", + "\u05d2\u05d5\u05e8\u05df", + "\u05e9\u05dc\u05d5\u05dd", + "\u05d0\u05d1\u05d5_\u05e8\u05d9\u05d0", + "\u05d1\u05e8", + "\u05e2\u05d1\u05d3_\u05d0\u05dc_\u05e7\u05d0\u05d3\u05e8", + "\u05de\u05e9\u05d9\u05d7", + "\u05de\u05d5\u05e8", + "\u05d3\u05d3\u05d5\u05df", + "\u05d2\u05d5\u05d8\u05de\u05df", + "\u05d0\u05de\u05e1\u05dc\u05dd", + "\u05dc\u05d1", + "\u05dc\u05e8\u05e0\u05e8", + "\u05d2\u05e8\u05d9\u05e0\u05d1\u05e8\u05d2", + "\u05e2\u05de\u05e8", + "\u05e2\u05de\u05d9\u05ea", + "\u05e9\u05d7\u05e8", + "\u05e1\u05d5\u05d0\u05e2\u05d3", + "\u05e9\u05d3\u05d4", + "\u05d3\u05e0\u05d9\u05e0\u05d5", + "\u05d0\u05de\u05d9\u05e8", + "\u05d7\u05dc\u05e4\u05d5\u05df", + "\u05d1\u05d3\u05e8\u05d0\u05df", + "\u05e9\u05e9\u05d5\u05df", + "\u05d1\u05e8\u05db\u05d4", + "\u05e8\u05d9\u05d0\u05df", + "\u05de\u05e8\u05d3\u05db\u05d9", + "\u05e1\u05d1\u05d0\u05d2", + "\u05e4\u05d0\u05e8", + "\u05d7\u05de\u05d5", + "\u05d9\u05e2\u05e7\u05d1\u05d9", + "\u05d2\u05d5\u05e8\u05d3\u05d5\u05df", + "\u05e2\u05d5\u05d0\u05d5\u05d3\u05d4", + "\u05e2\u05d5\u05d6", + "\u05d4\u05e8\u05d5\u05e9", + "\u05d0\u05e4\u05e9\u05d8\u05d9\u05d9\u05df", + "\u05d0\u05d3\u05e8\u05d9", + "\u05d0\u05dc\u05d8\u05d5\u05e8\u05d9", + "\u05e9\u05d2\u05d9\u05d0", + "\u05d6\u05d9\u05d5", + "\u05d5\u05d9\u05e6\u05de\u05df", + "\u05de\u05d7\u05de\u05d5\u05d3", + "\u05d9\u05d5\u05e1\u05d5\u05e4\u05d5\u05d1", + "\u05d0\u05d1\u05e0\u05d9", + "\u05e4\u05e8\u05d9\u05d3\u05de\u05df", + "\u05d3\u05d9\u05d0\u05d1", + "\u05d1\u05e8\u05e0\u05e1", + "\u05e6\u05d3\u05d5\u05e7", + "\u05e9\u05d5\u05e7\u05e8\u05d5\u05df", + "\u05d2\u05e8\u05d1\u05d0\u05df", + "\u05e0\u05d2\u05e8", + "\u05e4\u05d9\u05e9\u05e8", + "\u05e2\u05d6\u05e8\u05d0", + "\u05d0\u05dc\u05d1\u05d6", + "\u05e4\u05d7\u05d9\u05de\u05d4", + "\u05d0\u05dc\u05e7\u05d5\u05d1\u05d9", + "\u05d2\u05e8\u05d5\u05e1\u05de\u05df", + "\u05d7\u05d0\u05d2'_\u05d9\u05d7\u05d9\u05d0", + "\u05ea\u05de\u05d9\u05e8", + "\u05e8\u05d6\u05e0\u05d9\u05e7", + "\u05d0\u05e1\u05e8\u05e3", + "\u05e9\u05d1\u05d9\u05d8", + "\u05d3\u05d5\u05d3" + ], + "OTHER_PRONOUN": [ + "they" + ], + "LAST_NAME_MALE": [], + "LAST_NAME_FEMALE": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "\u05e9\u05d7\u05e7\u05e0\u05d9\u05ea": "\u05e9\u05d7\u05e7\u05df", + "\u05db\u05dc\u05d4": "\u05d7\u05ea\u05df", + "\u05d0\u05e9\u05ea_\u05e2\u05e1\u05e7\u05d9\u05dd": "\u05d0\u05d9\u05e9_\u05e2\u05e1\u05e7\u05d9\u05dd", + "\u05d2\u05d5\u05d6\u05dc": "\u05d0\u05d9\u05e9", + "\u05d0\u05e4\u05e8\u05d5\u05d7": "\u05d0\u05d9\u05e9", + "\u05d1\u05ea": "\u05d1\u05df", + "\u05e0\u05e7\u05d1\u05d4": "\u05de\u05dc\u05d4", + "\u05e0\u05e9\u05d9": "\u05de\u05dc\u05d4", + "\u05d1\u05d7\u05d5\u05e8\u05d4": "\u05d2\u05d0\u05d9", + "\u05d9\u05dc\u05d3\u05d4": "\u05d2\u05d0\u05d9", + 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"\u05de\u05dc\u05da", + "\u05e7\u05d5\u05d5\u05d9\u05e0\u05e1": "\u05de\u05dc\u05db\u05d9\u05dd", + "\u05d4\u05d9\u05d0": "\u05d4\u05d5\u05d0", + "\u05de\u05dc\u05e6\u05e8\u05d9\u05ea": "\u05de\u05dc\u05e6\u05e8", + "\u05d0\u05dc\u05de\u05e0\u05d4": "\u05d0\u05dc\u05de\u05df", + "\u05d0\u05dc\u05de\u05e0\u05d5\u05ea": "\u05d0\u05dc\u05de\u05df", + "\u05d1\u05ea_\u05d6\u05d5\u05d2": "\u05d1\u05e2\u05dc", + "\u05d0\u05e9\u05d4": "\u05d1\u05e2\u05dc", + "\u05de\u05db\u05e9\u05e4\u05d4": "\u05e7\u05d5\u05e1\u05dd", + "fema": "\u05de\u05df", + "\u05d0\u05d9\u05e9\u05d4": "\u05de\u05df", + "\u05d9\u05dc\u05d3": "\u05e0\u05e2\u05e8\u05d4", + "\u05d1\u05d7\u05d5\u05e8": "\u05e0\u05e2\u05e8\u05d4", + "\u05e0\u05e2\u05e8": "\u05d1\u05d7\u05d5\u05e8\u05d4" + }, + "other_gender_swap": { + "\u05e9\u05dc\u05d4\u05dd": "\u05e9\u05dc\u05d4", + "they": "\u05d4\u05d9\u05d0", + "\u05d4\u05dd": "\u05d4\u05d9\u05d0", + "\u05d4\u05df": "\u05d4\u05d9\u05d0", + "\u05e2\u05e8": "they", + "\u05d4\u05d5\u05d0": "\u05d4\u05df", + "\u05d4\u05d0": "they", + "\u05d4\u05d9\u05d0": "\u05d4\u05dd", + "\u05e9\u05dc\u05d4": "\u05e9\u05dc\u05d4\u05dd" + }, + "en_pronoun2gender": { + "they": [ + "\u05d4\u05d5\u05de\u05d5\u05e1\u05e7\u05e1\u05d5\u05d0\u05dc", + "\u05d8\u05e8\u05e0\u05e1\u05d2\u05f3\u05e0\u05d3\u05e8\u05d9", + "\u05d1\u05d9\u05e1\u05e7\u05e1\u05d5\u05d0\u05dc\u05d9", + "\u05d3\u05d5_\u05de\u05d9\u05e0\u05d9", + "\u05d8\u05e8\u05e0\u05e1\u05d2'\u05e0\u05d3\u05e8" + ], + "he": [ + "\u05d7\u05d1\u05d5\u05d1", + "\u05d9\u05dc\u05d3", + "\u05d0\u05d9\u05e9", + "\u05e0\u05e2\u05e8", + "\u05d2\u05d0\u05d9", + "\u05d2'\u05e0\u05d8\u05dc\u05de\u05df", + "\u05d2\u05d1\u05d9\u05e8", + "\u05d2\u05d9\u05d0", + "\u05de\u05df", + "\u05d0\u05e0\u05d5\u05e9\u05d5\u05ea", + "\u05d1\u05d7\u05d5\u05e8", + "\u05de\u05dc\u05d4", + "\u05d9\u05dc\u05d3_\u05e7\u05d8\u05df" + ], + "she": [ + "\u05d0\u05d9\u05e9\u05d4", + "\u05d1\u05d7\u05d5\u05e8\u05d4", + "\u05e4\u05e1\u05e4\u05e1", + "\u05d9\u05dc\u05d3\u05d4", + "\u05dc\u05e1\u05d1\u05d9\u05ea", + "\u05de\u05d9\u05e1_\u05d0\u05d9\u05d9", + "\u05d2\u05d1\u05e8\u05ea", + "\u05e0\u05e9\u05d9", + "\u05e0\u05e7\u05d1\u05d4", + "\u05e0\u05e2\u05e8\u05d4", + "\u05e2\u05dc\u05de\u05d4", + "fema", + "\u05dc\u05d9\u05d3\u05d9", + "\u05d4\u05d7\u05d8\u05d9\u05d0" + ] + }, + "en_pronoun2pronoun": { + "he": [ + "\u05e9\u05dc\u05d5", + "\u05e2\u05e8", + "\u05d4\u05d0", + "\u05d4\u05d5\u05d0" + ], + "she": [ + "\u05e9\u05dc\u05d4", + "\u05d4\u05d9\u05d0" + ], + "they": [ + "\u05e9\u05dc\u05d4\u05dd", + "\u05d4\u05dd", + "\u05d4\u05df", + "they" + ], + "it": [ + "\u05d6\u05d4", + "\u05db\u05d9", + "\u05d6\u05d5", + "\u05d0\u05e9\u05e8", + "\u05d6\u05d0\u05ea", + "\u05e9" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/hi.json b/data_tooling/pii_processing/ontology/data/hi.json new file mode 100644 index 0000000..89fcaed --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/hi.json @@ -0,0 +1,525 @@ +{ + "RACE": [ + "\u0905\u092e\u0947\u0930\u093f\u0915\u0940", + "\u092b\u094d\u0930\u093e\u0902\u0938\u0940\u0938\u0940" + ], + "ORG": [ + "\u090f\u0915_\u092c\u093e\u0930_\u0914\u0930", + "\u0930\u093e\u091c\u0917\u0940\u0930\u0940", + "\u0915\u0943\u0937\u093f\u0915\u0930\u094d\u092e", + "\u0905\u0928\u094d\u0924\u0930\u094d\u0930\u093e\u0937\u094d\u091f\u094d\u0930\u0940\u092f_\u0926\u0942\u0930\u0938\u0902\u091a\u093e\u0930_\u0938\u0902\u0918", + "\u092a\u093e\u0930\u094d\u091f\u0940", + "\u092b\u0947\u0921\u0930\u0932_\u092c\u094d\u092f\u0942\u0930\u094b_\u0911\u092b_\u0907\u0928\u094d\u0935\u0947\u0938\u094d\u091f\u093f\u0917\u0947\u0936\u0928", + "\u090f\u0915_\u092c\u093e\u0930_\u092b\u093f\u0930", + "\u0939\u094d\u0935\u093e\u0902\u0917\u0939\u094b", + "\u0915\u093e\u092e\u0917\u093e\u0930_\u0935\u0930\u094d\u0917", + 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+ "franjo", + "dra\u017een", + "dalibor", + "ante", + "martina", + "bo\u017eo", + "marin", + "antonio", + "domagoj", + "aldo", + "vlado", + "josip", + "patrik", + "darko", + "kristijan", + "pero", + "katarina", + "suzana", + "eva", + "\u0111uro", + "jelena", + "nik\u0161a", + "nata\u0161a", + "dino", + "vjekoslav", + "bo\u017eica", + "ivanka", + "laura", + "du\u0161an", + "\u0111ur\u0111ica", + "jana", + "anita", + "snje\u017eana", + "dominik", + "sanja", + "ika", + "elvis", + "denis", + "tea", + "ane", + "nika", + "anton", + "marina", + "matija", + "biljana", + "vedran", + "lana", + "\u017eeljka", + "lovre", + "an\u0111a", + "jozo", + "petra", + "mario", + "barbara", + "mira", + "mateja", + "andrea", + "zoran", + "mara", + "nada", + "hrvoje", + "stana", + "dejan", + "goran", + "terezija", + "anto", + "roko", + "ljiljana", + "ana", + "nenad", + "slavica", + "nina", + "sini\u0161a", + "ru\u017eica", + "martin", + "lucija", + "marko", + "zora", + "mihael", + "alen", + "zlatko", + "janko", + "mijo", + "barica", + "mato", + "mile", + "elizabeta", + "viktor", + "ema", + "luka", + "hana", + "jele", + "marta", + "maja", + "miroslav", + "bo\u017eena", + "fuma", + "gordana", + "mate", + "mirko", + "lidija", + "mateo", + "anka", + "david", + "nikola", + "ru\u017ea", + "rudolf", + "ivana", + "boris", + "danijela", + "filip", + "sa\u0161a", + "lorena", + "karla", + "ankica", + "marijan", + "marijana", + "veronika", + "milan", + "zorka", + "mare", + "stjepan", + "julijana", + "davor", + "nevenka", + "damir", + "anica", + "dora", + "robert", + "vera", + "ivan", + "erik", + "ivica", + "renata", + "danijel", + "antun", + "antonija", + "mladen", + "juraj", + "mislav", + "dragan", + "branka", + "pavao", + "\u017eeljko", + "janja", + "kate", + "mia", + "danica", + "jasna", + "bruno", + "marija", + "rozalija", + "vladimir", + "ilija", + "\u0161tefica", + "dragutin" + ], + "LAST_NAME": [ + "pokas", + "mikul\u010di\u0107", + "forjan", + "\u0161imi\u010di\u0107", + "buni\u0107", + "zeli\u0107", + "\u0161pi\u0161i\u0107", + "miki\u0107", + "varga", + "damjanovi\u0107", + "raj\u010di\u0107", + "ignac", + "goti\u0107", + "kne\u017eevi\u0107", + "toti\u0107", + "lelas", + "pokos", + "stiperski", + "mei\u0107", + "bali\u0107", + "don\u010devi\u0107", + "laba\u0161", + "luk\u0161a", + "franji\u0107", + "debeli\u0107", + "cvetkovi\u0107", + "\u0161estan", + "andra\u0161ek", + "rojni\u0107", + "\u0161kunca", + "meda\u010d", + "polovi\u0107", + "horvat", + "klanac", + "dragojevi\u0107", + "radman", + "stojanov", + "\u010dulina", + "\u0161uran", + "bol\u010devi\u0107", + "solomun", + "babi\u0107", + "vitasovi\u0107", + "radojkovi\u0107", + "bla\u017ei\u010dko", + "cari\u0107", + "ragu\u017e", + "ra\u017eov", + "fu\u010dek", + "odoba\u0161i\u0107", + "tomi\u0107", + "abramovi\u0107", + "\u0161urina", + "karamarko", + "matija\u0161", + "bobanovi\u0107", + "amanovi\u0107", + "\u0161imi\u0107", + "lovri\u0107", + "turina", + "lisica", + "volarevi\u0107", + "pongrac", + "halapir", + "roso", + "pribani\u0107", + "luci\u0107", + "triplat", + "bur\u0161i\u0107", + "stojni\u0107", + "vu\u010din", + "kuzmi\u0107", + "ra\u0111enovi\u0107", + "puljiz", + "mikulandra", + "bradi\u0107", + "radeli\u0107", + "mi\u0161e", + "jure\u0161ko", + "\u017eufika", + "vozila", + "\u010dop", + "ko\u0161\u010devi\u0107", + "beni\u0107", + "erceg", + "barac", + "ba\u0161i\u0107", + "pe\u0161i\u0107", + "karagi\u0107", + "skupnjak", + "mesari\u0107", + "dobri\u0107", + "bojani\u0107", + "kele\u010di\u0107", + "priselac", + "marku\u0161", + "uki\u0107", + "kuve\u017edi\u0107", + "prpi\u0107", + "pavin", + "flego", + "birki\u0107", + "\u010dubri\u0107", + "juki\u0107", + "\u0161itum", + "magi\u0107", + "crevar", + "mi\u0161kovi\u0107", + "kopjar", + "nedi\u0107", + "\u0161ok\u010devi\u0107", + "peterlik", + "bi\u010dani\u0107", + "drakuli\u0107", + "miloslavi\u0107", + "soka\u010d", + "semialjac", + "viljevac", + "mihel\u010di\u0107", + "markanjevi\u0107", + "filar", + "grba", + "grbac", + "moslavac", + "dragi\u010devi\u0107", + "komljenovi\u0107", + "mu\u0161\u0107et", + "kupsjak", + "ugrini\u0107", + "vukman", + "ergoti\u0107", + "mikulec", + "galovi\u0107", + "labinjan", + "lukini\u0107", + "kujund\u017ei\u0107", + "bezi\u0107", + "slavica", + "zano\u0161ki", + "han\u017eek", + "moscarda", + "kevo", + "milina", + "\u017eu\u017ei\u0107", + "crnkovi\u0107", + "ben\u010di\u0107", + "godini\u0107", + "kocijan\u010di\u0107", + "kolarec", + "bebi\u0107", + "volari\u0107", + "leni\u0107", + "po\u017eega", + "krajcar", + "horak", + "\u0161pika", + "pali\u0107", + "\u010dargonja", + "maleti\u0107", + "rube\u0161a", + "kraljevi\u0107", + "le\u0161i\u0107", + "\u010dagalj", + "\u0161egovi\u0107", + "kosanovi\u0107", + "luki\u0107", + "panduri\u0107", + "had\u017ei\u0107", + "legovi\u0107", + "marasovi\u0107", + "bu\u0161ljeta", + "kresonja", + "dragobratovi\u0107", + "dominkovi\u0107", + "krpan", + "bogovi\u0107", + "vi\u017eintin", + "\u017eunec", + "mo\u010dibob", + "sladonja", + "herceg", + "jovi\u0107", + "strinavi\u0107", + "bungi\u0107", + "hodak", + "\u017eikovi\u0107", + "mi\u0161ak", + "\u0161ali\u0107", + "bosilj", + "sever", + "frani\u0107", + "\u0161kugor", + "huljev", + "ciganovi\u0107", + "\u0161pralja", + "milati\u0107", + "\u017eic", + "antoni\u0107", + "marijanovi\u0107", + "cestari\u0107", + "gali\u0107", + "pajur", + "damijani\u0107", + "\u0161kara", + "saka\u010d", + "pe\u010dur", + "vu\u010deti\u0107", + "puhari\u0107", + "valenti\u0107", + "stan\u010din", + "tu\u0161kan", + "mahnet", + "barbieri", + "karmeli\u0107", + "rastija", + "he\u0107imovi\u0107", + "culi", + "\u0161timac", + "bu\u010dar", + "glasnovi\u0107", + "\u0161urbek", + "le\u0161\u010di\u0107", + "glavor", + "jakovi\u0107", + "bo\u017ei\u0107", + "\u010dupi\u0107", + "mudri", + "rogo\u0161i\u0107", + "zeba", + "peni\u0107", + "iliji\u0107", + "gligora", + "turudi\u0107", + "bingula", + "kuku\u010dka", + "mesi\u0107", + "mara\u0161", + "franu\u0161i\u0107", + "novak", + "pavi\u010di\u0107", + "ore\u0161kovi\u0107", + "\u0161o\u0161i\u0107", + "petrovi\u0107", + "\u0161trlji\u0107", + "\u017eabja\u010dan", + "\u017eivkovi\u0107", + "hrvoji\u0107", + "baljak", + "\u0161imuni\u0107", + "ili\u0107", + "mar\u017ei\u0107", + "pikec", + "ra\u0161eta", + "kos", + "bogdan", + "marjanovi\u0107", + "gabud", + "iv\u0161i\u0107", + "mustapi\u0107", + "or\u0161oli\u0107", + "buzov", + "batrac", + "ljubi\u010di\u0107", + "rajn", + "vuk", + "gelemanovi\u0107", + "macan", + "boti\u0107", + "brcko", + "\u0161arga\u010d", + "mudronja", + "brlas", + "ku\u010di\u0107", + "brajkovi\u0107", + "jozi\u0107", + "\u0161tefanec", + "vidovi\u0107", + "horvati\u0107", + "\u0161krlin", + "pero\u0161", + "radovi\u0107", + "kolega", + "rubini\u0107", + "seni\u010di\u0107", + "maru\u0161i\u0107", + "gr\u017eeti\u0107", + "so\u0161i\u0107", + "vrban", + "medved", + "tu\u0111a", + "bogadi", + "hardi", + "ferenac", + "ple\u0161e", + "sr\u0161en", + "novosel", + "jagarinec", + "hadrovi\u0107", + "horvatinec", + "mori\u0107", + "bazjak", + "zub\u010di\u0107", + "kralj", + "sto\u0161i\u0107", + "barnaba", + "bari\u0161i\u0107", + "\u0107osi\u0107", + "dubove\u010dak", + "turk", + "hr\u017eenjak", + "klari\u0107", + "sura\u0107", + "kauzlari\u0107", + "koli\u0107", + "raljevi\u0107", + "\u017eagar", + "ni\u0161evi\u0107", + "pozder", + "resanovi\u0107", + "perak", + "jurlina", + "bare\u0161i\u0107", + "dizdar", + "\u010duljak", + "bani\u010devi\u0107", + "obratov", + "keli\u0107", + "tomljanovi\u0107", + "abi\u010di\u0107", + "bo\u017ei\u010devi\u0107", + "dere\u017ei\u0107", + "mili\u010di\u0107", + "\u0161verko", + "gredi\u010dak", + "u\u0161i\u0107", + "brleti\u0107", + "gregov", + "plantak", + "jeli\u0107", + "berto\u0161a", + "gracin", + "boro\u0161ak", + "merka\u0161", + "matana", + "\u0111urini\u0107", + "paveli\u0107", + "hini\u0107", + "nimac", + "d\u017eapo", + "ladavac", + "bo\u017eikovi\u0107", + "grguri\u0107", + "cvetni\u0107", + "valjeti\u0107", + "ba\u0161nec", + "or\u0161o\u0161", + "kati\u0107", + "jakovljevi\u0107", + "marinovi\u0107", + "sobota", + "dretvi\u0107", + "tuksar", + "naki\u0107", + "peri\u0161i\u0107", + "mraovi\u0107", + "pavi\u0107", + "bo\u017eanovi\u0107", + "pla\u017eanin", + "\u0107ori\u0107", + "vrhovec", + "jaku\u0161", + "kova\u010di\u0107", + "polonijo", + "mato\u0161evi\u0107", + "maras", + "poropat", + "ani\u010di\u0107", + "kinkela", + "le\u0161kovi\u0107", + "barkovi\u0107", + "\u0161koda", + "malnar", + "bla\u017eevi\u0107", + "ad\u017eijevi\u0107", + "jur\u010di\u0107", + "antolkovi\u0107", + "\u0161anti\u0107", + "kirin\u010di\u0107", + "dautanec", + "pe\u0161a", + "peru\u0161ko", + "drandi\u0107", + "tu\u0161ek", + "de\u017ee", + "jakopec", + "filipovi\u0107", + "sokol", + "vukobratovi\u0107", + "rumora", + "\u017eerjav", + "darojkovi\u0107", + "matko", + "britvec", + "fabijani\u0107", + "medi\u0107", + "bla\u017eek", + "juri\u0161i\u0107", + "bun\u010di\u0107", + "kr\u0161anac", + "vuku\u0161i\u0107", + "kova\u010devi\u0107", + "vela", + "kova\u010d", + "bajan", + "balin\u010di\u0107", + "orbani\u0107", + "majdeni\u0107", + "radi\u0107", + "kova\u010dek", + "vorkapi\u0107", + "jurkovi\u0107", + "brandi\u0107", + "akma\u010di\u0107", + "karlovi\u0107", + "jurjevi\u0107", + "zgorelec", + "grubi\u0161i\u0107", + "matokanovi\u0107", + "jovanovac", + "jugovac", + "brezjan", + "\u017ee\u017eeli\u0107", + "paradi", + "prtenja\u010da", + "lasi\u0107", + "jelavi\u0107", + "vla\u0161i\u0107", + "mihaljevi\u0107", + "fri\u0161\u010di\u0107", + "papak", + "mami\u0107", + "trnski", + "piljek", + "mio\u010di\u0107", + "matahlija", + "salopek", + "komar", + "jakopovi\u0107", + "ko\u0161ki", + "jemri\u0107", + "vugec", + "stra\u017ei\u010di\u0107", + "kokori\u0107", + "soldo", + "peri\u0107", + "or\u0161uli\u0107", + "radolovi\u0107", + "er\u0161ek", + "petek", + "cik", + "dabo", + "sabol", + "topi\u0107", + "jakovac", + "roca", + "milevoj", + "karuza", + "vaci", + "hren", + "stani\u0107", + "dvojak", + "mihi\u0107", + "mimica", + "hranj", + "alkovi\u0107", + "jasprica", + "\u0161estak", + "\u010dizmi\u0107", + "andrijevi\u0107", + "beleti\u0107", + "bukvi\u0107", + "mikle\u010di\u0107", + "smokovi\u0107", + "kosi\u0107", + "andrija\u0161evi\u0107", + "coli\u0107", + "kr\u017eelj", + "bi\u0107ani\u0107", + "dominikovi\u0107", + "\u010dukman", + "pu\u0161kari\u0107", + "pecoti\u0107", + "rakela", + "liovi\u0107", + "per\u010di\u0107", + "gu\u0161tin", + "kerekovi\u0107", + "ba\u010di\u0107", + "martini\u0107", + "jage\u010di\u0107", + "markovac", + "lazar", + "urli\u0107", + "kunac", + "bur\u010dul", + "ra\u0161i\u0107", + "bo\u0161njak", + "mavra", + "eterovi\u0107", + "birti\u0107", + "stipanovi\u0107", + "gulan", + "vugdelija", + "bo\u0161njakovi\u0107", + "barbi\u0107", + "dolinar", + "pami\u0107", + "lu\u010di\u0107", + "rito\u0161a", + "didovi\u0107", + "boban", + "jakupi\u0107", + "vojkovi\u0107", + "matkovi\u0107", + "bijeli\u0107", + "ribi\u010di\u0107", + "obradovi\u0107", + "bernardi\u0107", + "herout", + "sedlar", + "licul", + "\u010di\u017eme\u0161ija", + "lako\u0161eljac", + "putinja", + "borojevi\u0107", + "balatinac", + "gegi\u0107", + "jonji\u0107", + "modri\u0107", + "tudi\u0107", + "filip\u010di\u0107", + "mileti\u0107", + "star\u010devi\u0107", + "vrabelj", + "pavkovi\u0107", + "vretenar", + "hrabar", + "banko", + "stoj\u010devi\u0107", + "doli\u0107", + "mati\u0107", + "ri\u010dko", + "bjeli\u0161", + "guberovi\u0107", + "liber", + "popovi\u0107", + "pavlovi\u0107", + "boljkovac", + "cukon", + "belo\u0161evi\u0107", + "rahija", + "\u010du\u010dek", + "\u0161poljari\u0107", + "kostani\u0107", + "bari\u010devi\u0107", + "zrili\u0107", + "\u010doti\u0107", + "jovanovi\u0107", + "\u010di\u0161", + "risek", + "perkovi\u0107", + "kr\u010deli\u0107", + "buri\u0107", + "matulin", + "krznari\u0107", + "banovac", + "\u0161ipek", + "hrani\u0107", + "ozimec", + "gudelj", + "harapin", + "marde\u0161i\u0107", + "lojen", + "prskalo", + "trutani\u0107", + "frani\u010devi\u0107", + "\u017eivi\u0107", + "duki\u0107", + "kligl", + "majstorovi\u0107", + "marti\u0107", + "zebec", + "ma\u0107e\u0161i\u0107", + "knezovi\u0107", + "\u0161ibali\u0107", + "halambek", + "zakinja", + "\u0161trbac", + "rijetkovi\u0107", + "amid\u017ei\u0107", + "rado\u0161evi\u0107", + "stani\u010di\u0107", + "\u0161ari\u0107", + "matuli\u0107", + "\u0161imara", + "orlovi\u0107", + "mamula", + "mi\u010deti\u0107", + "\u0161unji\u0107", + "kralji\u0107", + "tur\u010dinov", + "baksa", + "vidakovi\u0107", + "glavan", + "kadija", + "\u0161o\u0161tari\u0107", + "rukavina", + "rakulji\u0107", + "barbir", + "rado\u010daj", + "trgov\u010di\u0107", + "predovan", + "mihali\u0107", + "mar\u0161i\u0107", + "\u017euvela", + "norac", + "petri\u010devi\u0107", + "martinovi\u0107", + "\u0161tefovi\u0107", + "kostelac", + "buljan", + "vidas", + "vinceti\u0107", + "dujmovi\u0107", + "roce", + "sabljak", + "nikoli\u0107", + "klasi\u0107", + "brali\u0107", + "stolnik", + "tonc", + "zmai\u0107", + "dra\u017ei\u0107", + "ribi\u0107", + "\u0161eparovi\u0107", + "marinkovi\u0107", + "miloti\u0107", + "ribari\u0107", + "blagai\u0107", + "bi\u010dak", + "marin", + "\u0161tifani\u0107", + "\u0111ura\u0161evi\u0107", + "bu\u010danac", + "perkov", + "matas", + "frketi\u0107", + "malo\u010da", + "sikiri\u0107", + "ilinovi\u0107", + "cafuk", + "vidov", + "\u0161krti\u0107", + "vu\u010dkovi\u0107", + "crnekovi\u0107", + "tomi\u010di\u0107", + "gale\u0161i\u0107", + "mofardin", + "\u0161krni\u010dki", + "kokanovi\u0107", + "horvatek", + "petri\u0107", + "gr\u017ein\u010di\u0107", + "siroti\u0107", + "begonja", + "luk\u0161i\u0107", + "poljak", + "\u0161imunovi\u0107", + "milovac", + "radin", + "vei\u0107", + "raspor", + "tisaj", + "\u0161elendi\u0107", + "pintari\u0107", + "na\u010dinovi\u0107", + "jureti\u0107", + "ivanovi\u0107", + "ivandi\u0107", + "vladislavi\u0107", + "kahlina", + "berakovi\u0107", + "bo\u017eani\u0107", + "ban", + "ljubi\u0107", + "\u0161inkovi\u0107", + "bo\u017ei\u010dkovi\u0107", + "\u0161arlija", + "rebi\u0107", + "mirt", + "cindri\u0107", + "hr\u0161ak", + "poli\u0107", + "tolj", + "terlevi\u0107", + "cvitan", + "smoli\u0107", + "\u0107uri\u0107", + "borak", + "matijevi\u0107", + "milas", + "husnjak", + "batrnek", + "duvan\u010di\u0107", + "mu\u017ei\u0107", + "mareti\u0107", + "papari\u0107", + "ba\u010dak", + "kani\u0161ki", + "ercegovi\u0107", + "toi\u0107", + "radinovi\u0107", + "\u010dovi\u0107", + "svetli\u010di\u0107", + "kurtoi\u0107", + "pedi\u0161i\u0107", + "sardeli\u0107", + "\u0161upraha", + "plantek", + "jerkovi\u0107", + "ni\u017eeti\u0107", + "makovac", + "simi\u0107", + "vuljak", + "trbovi\u0107", + "mu\u017eina", + "josipovi\u0107", + "martin\u010devi\u0107", + "lorencin", + "soki\u0107", + "butkovi\u0107", + "mate\u0161a", + "markovi\u0107", + "kelekovi\u0107", + "grgurovac", + "botica", + "baru\u0161i\u0107", + "car", + "klarin", + "juri\u0107", + "\u0161ipi\u0107", + "kramari\u0107", + "te\u0161ija", + "kri\u017ean", + "ljubeti\u0107", + "ivan\u010dan", + "maduni\u0107", + "anti\u0107", + "cveni\u0107", + "renduli\u0107", + "\u017eupani\u0107", + "mari\u0107", + "kalanjo\u0161", + "vukovi\u0107", + "bari\u0107", + "preo\u010danin", + "grgurevi\u0107", + "mirosavljevi\u0107", + "ku\u0161\u010devi\u0107", + "mari\u010devi\u0107", + "vrani\u0107", + "ser\u0161i\u0107", + "dautovi\u0107", + "tudor", + "kalazi\u0107", + "orli\u0107", + "\u0161turlan", + "brankovi\u0107", + "sori\u0107", + "sino\u017ei\u0107", + "peharda", + "tepe\u0161", + "stupalo", + "govor\u010dinovi\u0107", + "hrastinski", + "bara\u0107", + "poslon", + "terzi\u0107", + "zrinski", + "grgi\u0107", + "golubi\u0107", + "cvrtila", + "brlek", + "prelec", + "\u010dudi\u0107", + "bra\u010dun", + "matovina", + "musta\u010d", + "\u017eugec" + ], + "LAST_NAME_MALE": [], + "LAST_NAME_FEMALE": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": {}, + "other_gender_swap": {}, + "en_pronoun2gender": {}, + "en_pronoun2pronoun": {}, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/hsb.json b/data_tooling/pii_processing/ontology/data/hsb.json new file mode 100644 index 0000000..0cfd695 --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/hsb.json @@ -0,0 +1,130 @@ +{ + "LANGUAGE": [ + "hindi\u0161\u0107ina", + "danski", + "manx", + "japanski", + "esperanto", + "jend\u017aelski", + "franco\u0161\u0107ina", + "portugalski" + ], + "ANIMAL": [ + "rapak", + "kohlica", + "kozor\u00f3\u017ek", + "paskulica", + "kuli\u0161k", + "parlawa", + "pa\u0161turlica", + "kwikawa", + "pardal", + "burunduk", + "\u0161kraholc", + "kraholc" + ], + "PUBLIC_FIGURE": [ + "sherry", + "w", + "jurij", + "a", + "toma\u0161", + "katarina", + "putin", + "frank" + ], + "JOB": [ + "kral", + "propst", + "kralik" + ], + "RACE": [ + "turk", + "francoz" + ], + "PERSON_PRONOUN": [ + "na\u0161", + "we", + "naju" + ], + "DISEASE": [ + "jakota\u0107" + ], + "FAC": [ + "dw\u00f3rni\u0161\u0107o" + ], + "PRODUCT": [ + "njezapomni\u010dak", + "wulkobritaniska", + "nowoseelandska", + "wujk" + ], + "RELIGION_MEMBER": [ + "bratr" + ], + "PLANT": [ + "fija\u0142ka", + "jejku\u0161", + "serbowka" + ], + "FOOD": [ + "chile", + "limonada" + ], + "SOC_ECO_CLASS": [ + "ratarstwo" + ], + "ORG": [ + "ratarstwo", + "\u010derwjene_morjo" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "jeje": "jeho", + "sotra": "bratr", + "\u017eona": "mu\u017e", + "\u017e\u00f3nska": "mu\u017e" + }, + "other_gender_swap": { + "n\u011b": "jeje" + }, + "en_pronoun2gender": { + "he": [ + "mu\u017e" + ], + "she": [ + "\u017eona", + "\u017e\u00f3nska", + "d\u017aow\u0107o" + ] + }, + "en_pronoun2pronoun": { + "he": [ + "hij", + "w\u00f3n", + "jeho" + ], + "she": [ + "jeje" + ], + "they": [ + "n\u011b" + ], + "it": [ + "esta", + "hij", + "jeho" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/ht.json b/data_tooling/pii_processing/ontology/data/ht.json new file mode 100644 index 0000000..aec3dd8 --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/ht.json @@ -0,0 +1,260 @@ +{ + "PUBLIC_FIGURE": [ + "henry_cavendish", + "benjamin_franklin", + "thomas_bayes", + "otto_frisch", + "johannes_diderik_van_der_waals", + "isaac_newton", + "victor_hugo", + "marie_curie", + "michael_jackson", + "galileo_galilei", + "vincent_van_gogh", + "steven_weinberg", + "e", + "norbert_wiener", + "henri_becquerel", + "bertram_brockhouse", + "y", + "f", + "james_franck", + "johannes_kepler", + "max_planck", + "john_bardeen", + "lars_onsager", + "arthur_compton", + "niels_bohr", + "bertrand_russell", + "michael_faraday", + "walt_disney", + "karl_menninger", + "richard_feynman", + "andrew_huxley", + "daniel_bernoulli", + "joseph_henry", + "gottfried_leibniz", + "pieter_zeeman", + "pablo_picasso", + "otto_hahn", + "christiaan_huygens", + "saint_louis_missouri", + "karl_marx", + "i", + "nikola_tesla", + "ludwig_boltzmann", + "leopold_kronecker", + "adolf_hitler", + "robert_boyle", + "1", + "ernest_walton", + "g", + "r", + "philip_warren_anderson", + "wilhelm_weber", + "thomas_malthus", + "robert_hooke", + "jezikri", + "alexander_wilson", + "charlie_chaplin", + "william_gilbert", + "james_watt", + "ronald_reagan", + "david_hilbert", + "martin_luther_king", + "nelson_mandela", + "hans_bethe", + "alfred_kastler", + "charles_peirce", + "albert_einstein", + "t" + ], + "LANGUAGE": [ + "lapaw\u00f2l", + "kongo", + "frans\u00e8", + "pany\u00f2l", + "bichlamar", + "tonga" + ], + "PLANT": [ + "moye", + "kalbas", + "maskreti", + "kachiman", + "moutad", + "seriz", + "abdenwel", + "mangliye", + "kokliko", + "koupye", + "madl\u00e8n", + "choublak" + ], + "DISEASE": [ + "anfis\u00e8m", + "nebilez", + "ki", + "maladi", + "kans\u00e8", + "lajonis", + "doul\u00e8", + "chal\u00e8", + "gros\u00e8s", + "maladi_andemik", + "radyasyon", + "tan", + "malarya", + "viris", + "gout" + ], + "JOB": [ + "lapolis", + "make", + "gentleman", + "kolon\u00e8l", + "achit\u00e8k", + "kizinye", + "travay\u00e8", + "chawoya", + "segonn", + "acht\u00e8", + "lieutenant" + ], + "PRODUCT": [ + "justin_bieber", + "abdenwel", + "julius_caesar", + "sentespri", + "sen_tome_ak_pw\u00e8nsip" + ], + "GPE": [ + "sen_domeng", + "sri_jayawardenapura", + "sentespri", + "py\u00e8", + "nouvo_testaman" + ], + "PERSON": [ + "julius_caesar", + "carl_david_anderson" + ], + "ANIMAL": [ + "bourik", + "atwop\u00f2d", + "sourit", + "rosiny\u00f2l", + "malfini", + "homo_sapiens", + "milip\u00e8d", + "maladi_viris_ebola" + ], + "ORG": [ + "saint_albans_vermont", + "ang", + "mizajou", + "sent_lisi", + "kap_v\u00e8", + "oni", + "sao_tome", + "po", + "mossad", + "sant_kom\u00e8syal", + "gouv\u00e8nman" + ], + "SOC_ECO_CLASS": [ + "literati", + "agrikilti" + ], + "DATE": [ + "to_m\u00f2talite", + "demi_vi", + "ton_natalite", + "almanak_gregoryen" + ], + "GENDER": [ + "gentleman", + "gason", + "men", + "tifi", + "gal" + ], + "PERSON_PRONOUN": [ + "i", + "me" + ], + "QUANTITY": [ + "vennkat", + "vennde", + "ventuit", + "g", + "venntwa", + "ventn\u00e8f", + "vennsis", + "venteyen", + "venns\u00e8t", + "vennsenk" + ], + "LOCATION": [ + "joseph_louis_gay_lussac", + "krist\u00f2f_kolon", + "nou_meksiko", + "etazini", + "ke_kontan_ane_nouvo", + "srilanka", + "ozetazini" + ], + "FOOD": [ + "chili" + ], + "RELIGION_MEMBER": [ + "kretyen" + ], + "FAC": [ + "tranntwa" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "bonda": "pid", + "fem\u00e8l": "gason", + "prens\u00e8s": "prens_la", + "fanm": "moun", + "gason": "tifi" + }, + "other_gender_swap": {}, + "en_pronoun2gender": { + "they": [ + "biseksy\u00e8l" + ], + "he": [ + "gentleman", + "moun", + "gason" + ], + "she": [ + "fem\u00e8l", + "fanm", + "tifi", + "gal" + ] + }, + "en_pronoun2pronoun": { + "he": [ + "tij" + ], + "they": [ + "nich" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/hu.json b/data_tooling/pii_processing/ontology/data/hu.json new file mode 100644 index 0000000..51c7761 --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/hu.json @@ -0,0 +1,2530 @@ +{ + "DATE": [ + "\u00e9letfogytiglan", + "midenszentek", + "szabadnap", + "a_b\u00f6jt_megt\u00f6r\u00e9s\u00e9nek_\u00fcnnepe", + "mindenszentek", + "villanyolt\u00e1s", + "holdf\u00e1zis", + "holdt\u00f6lte", + "aranykorm\u00edtosz", + "telihold", + "the_golden_years", + "itt_\u00e9s_most", + "\u00fajhold", + "sz\u00e1zadfordul\u00f3", + "holnaput\u00e1n" + ], + "PERSON": [ + "al_am\u00edn_abb\u00e1szida_kalifa", + "kakashal", + "al_gore", + "ji_csing", + "h_g_wells", + "kaucsukfa", + "taj_hegy", + "don_delillo", + "nekem_is", + "igor_sikorsky", + "in_memory", + "carl_david_anderson", + "\u00e9n_is", + "c_vitamin", + "rudolf_hess" + ], + "PUBLIC_FIGURE": [ + "henry_cavendish", + "matthew_arnold", + "alfr\u00e9d", + "benjamin_franklin", + "martin_buber", + "jean_genet", + "john_knox", + "heinrich_hertz", + "giovanni_boccaccio", + "cornelius_vanderbilt", + "rudolf_steiner", + "david_rittenhouse", + "thomas_bayes", + "johann_bernoulli", + "max_bruch", + "leonard_bernstein", + "sibelius", + "che_guevara", + "georges_simenon", + "c", + "i_a_richards", + "john_barth", + "edward_albee", + "maria_callas", + "henrik_ibsen", + "william_gladstone", + "mary_shelley", + "franz_werfel", + "peter_lorre", + "david_livingstone", + "eduard_buchner", + "\u00fcresfej\u0171", + "john_herschel", + "andrzej_wajda", + "jan_van_eyck", + "carl_rogers", + "georg_wilhelm_steller", + "i_theodosius_r\u00f3mai_cs\u00e1sz\u00e1r", + "richard_burton", + "douglas_macarthur", + "mary_wollstonecraft", + "thomas_reid", + "winston_churchill", + "johannes_diderik_van_der_waals", + "conrad_aiken", + "karl_landsteiner", + "paul_mccartney", + "sz\u00e9llelb\u00e9lelt", + "andrew_marvell", + "terry_pratchett", + "stephen_king", + "francis_crick", + "peter_o\u2019toole", + "sherry", + "isaac_newton", + "victor_hugo", + "joseph_smith", + "edwin_hubble", + "colette", + "milton_friedman", + "edward_gibbon", + "i_lajos_frank_cs\u00e1sz\u00e1r", + "jefferson_davis", + "saint_louis", + "george_stephenson", + "john_glenn", + "nem_alkalmazhat\u00f3", + "john_webster", + "john_davis", + "george_harrison", + "george_orwell", + "vi_gy\u00f6rgy_brit_kir\u00e1ly", + "ronald_norrish", + "arthur_koestler", + "richard_wagner", + "thornton_wilder", + "ii_f\u00fcl\u00f6p_spanyol_kir\u00e1ly", + "pancho_villa", + "leopold_stokowski", + "marie_curie", + "francis_galton", + "michael_jackson", + "carl_sandburg", + "thomas_hobbes", + "el_greco", + "samuel_beckett", + "\u00e9s_\u00edgy_tov\u00e1bb", + "galileo_galilei", + "jane_goodall", + "john_donne", + "robert_koch", + "ii_szent_edu\u00e1rd_angol_kir\u00e1ly", + "i_m_pei", + "joseph_goebbels", + "george_eastman", + "john_steinbeck", + "catherine", + "edmund_hillary", + "vincent_van_gogh", + "richard_hooker", + "john_ruskin", + "robert_burns", + "ii_ramszesz", + "john_henry", + "hans_albrecht_bethe", + "\u00e1llamf\u0151", + "i_constantinus_r\u00f3mai_cs\u00e1sz\u00e1r", + "thomas_paine", + "bari", + "francis_beaumont", + "steven_weinberg", + "mary_pickford", + "hans_fischer", + "emiliano_zapata", + "willem_einthoven", + "bernard_malamud", + "samuel_johnson", + "allen_iverson", + "giuseppe_verdi", + "walter_lippmann", + "e", + "karl_jaspers", + "beethoven", + "konrad_adenauer", + "norbert_wiener", + "li_cseng_tao", + "mark_rothko", + "maurice_chevalier", + "gottlieb_daimler", + "frank_sinatra", + "i_vilmos_angol_kir\u00e1ly", + "katharine_hepburn", + "henri_becquerel", + "henri_matisse", + "gergely", + "louis_pasteur", + "j", + "richard_strauss", + "leslie_howard", + "hugo_grotius", + "mahalia_jackson", + "john_ford", + "gertrude_stein", + "sarah_bernhardt", + "katalin", + "philip_marlowe", + "luigi_pirandello", + "t_s_eliot", + "v_gy\u00f6rgy_brit_kir\u00e1ly", + "robert_millikan", + "charles_de_gaulle", + "paul_von_hindenburg", + "y", + "henry_moore", + "holden", + "ii_erzs\u00e9bet_brit_kir\u00e1lyn\u0151", + "charles_lindbergh", + "vincenzo_bellini", + "f", + "ludwig_wittgenstein", + "august_strindberg", + "thomas_mann", + "william_ockham", + "alla_nazimova", + "charles_goodyear", + "dante_alighieri", + "john_irving", + "bokor", + "samuel_de_champlain", + "giacomo_puccini", + "benedek", + "edward_fitzgerald", + "fridtjof_nansen", + "louis_braille", + "herbert_marcuse", + "mungo_park", + "paul_verlaine", + "robert_johnson", + "james_dean", + "marie_tussaud", + "alessandro_manzoni", + "henrik", + "joseph_priestley", + "hal", + "nicolas_poussin", + "andrea_mantegna", + "oscar_wilde", + "philip_roth", + "j_d_salinger", + "henry", + "lawrence", + "j\u00f3_t\u00fcnd\u00e9r", + "richard_trevithick", + "william_bradford", + "heinrich_schliemann", + "eli_whitney", + "don_quijote", + "sakkmester", + "lenni", + "laurence_olivier", + "pierre_larousse", + "christiaan_eijkman", + "adolf_eichmann", + "francis_bacon", + "pete_seeger", + "john_wycliffe", + "joseph_heller", + "a", + "morris", + "james_brown", + "william_hogarth", + "charles_baudelaire", + "luigi_cherubini", + "david_ricardo", + "mary_leakey", + "charlie_parker", + "immanuel_kant", + "william_crookes", + "i_r\u00f3bert_sk\u00f3t_kir\u00e1ly", + "n", + "albert_schweitzer", + "john_harvard", + "johann_friedrich_herbart", + "johannes_kepler", + "william_s_burroughs", + "most", + "david_hartley", + "max_planck", + "william_blake", + "julio_iglesias", + "john_bardeen", + "arthur", + "sarah_vaughan", + "william_byrd", + "scott_joplin", + "carl_lewis", + "sarah_siddons", + "george_vancouver", + "canberra", + "elias_canetti", + "edward_jenner", + "oliver_hardy", + "cole_porter", + "jean_luc_godard", + "i_d\u00e1rajavaus_perzsa_kir\u00e1ly", + "graham_greene", + "frans_hals", + "lars_onsager", + "margaret_mitchell", + "igor_stravinsky", + "lola_montez", + "john_walker", + "william_herschel", + "mikhail_baryshnikov", + "montesquieu", + "arthur_rubinstein", + "arthur_compton", + "niels_bohr", + "henry_fielding", + "bertrand_russell", + "michael_faraday", + "anthony_burgess", + "sikets\u00e9g", + "irving_berlin", + "bernard_baruch", + "rudolf_diesel", + "walt_disney", + "i_oszm\u00e1n_oszm\u00e1n_szult\u00e1n", + "emsemak\u00e1k\u00f3", + "steve_reich", + "benny_goodman", + "friedrich_engels", + "ii_k\u00e1roly_nyugati_frank_kir\u00e1ly", + "jane_austen", + "gustav_mahler", + "phil_collins", + "robert_redford", + "ian_fleming", + "richard_feynman", + "wolfgang_pauli", + "theodore_dreiser", + "theodor_mommsen", + "andrew_huxley", + "marcel_proust", + "paul_hindemith", + "elizabeth_taylor", + "thomas_chippendale", + "john_dowland", + "benjamin_jonson", + "william_golding", + "william_caxton", + "john_milton", + "i_m\u00e1ria_sk\u00f3t_kir\u00e1lyn\u0151", + "i_edu\u00e1rd_wessexi_kir\u00e1ly", + "albert_speer", + "indira_gandhi", + "jane_seymour", + "george_gershwin", + "alberto_giacometti", + "e_t_a_hoffmann", + "frank_whittle", + "jesse_owens", + "marco_polo", + "caravaggio", + "ii_kurus_perzsa_kir\u00e1ly", + "charlie_watts", + "m", + "charlotte_corday", + "marcel_marceau", + "allen_ginsberg", + "fred_zinnemann", + "daniel_bernoulli", + "guillaume_apollinaire", + "henri_bergson", + "boris_karloff", + "pierre_corneille", + "patrick_white", + "bartholomew_roberts", + "hans_christian_andersen", + "william_morris", + "cary_grant", + "pieter_zeeman", + "arnold_gesell", + "glenn_miller", + "pablo_picasso", + "marian_anderson", + "natalie_wood", + "l_ron_hubbard", + "thomas_moore", + "kurt_weill", + "otto_hahn", + "christiaan_huygens", + "hector_berlioz", + "paul_simon", + "claudio_monteverdi", + "john_galsworthy", + "robert_robinson", + "o", + "one", + "adam_smith", + "william_james", + "ii_katalin_orosz_c\u00e1rn\u0151", + "levit\u00e9zlett", + "u", + "jean_harlow", + "karl_marx", + "friedrich_nietzsche", + "i", + "moln\u00e1r", + "jimmy_durante", + "john_wesley", + "sandro_botticelli", + "nikola_tesla", + "al_capone", + "charles_barkley", + "billy_graham", + "robert_schumann", + "mel_gibson", + "le_corbusier", + "carlo_goldoni", + "john_locke", + "alexis_carrel", + "joseph_marie_jacquard", + "henry_james", + "stephen_sondheim", + "a_hamelni_patk\u00e1nyfog\u00f3", + "helen_keller", + "paul_dukas", + "ingrid_bergman", + "jean_piaget", + "william_congreve", + "henri_rousseau", + "paul_tillich", + "legt\u00f6bb", + "h_g_wells", + "walt_whitman", + "william_wyler", + "ludwig_boltzmann", + "leopold_kronecker", + "i_klodvig_frank_kir\u00e1ly", + "richard_wright", + "adolf_hitler", + "james_d_watson", + "fritz_haber", + "peter_behrens", + "alfred_stieglitz", + "john_h_watson", + "joseph_haydn", + "stephen_spender", + "garfield", + "george_boole", + "buffalo_bill", + "edvard_grieg", + "robert_boyle", + "i_harold_angol_kir\u00e1ly", + "1", + "liliom", + "cordell_hull", + "r\u00f3bert", + "rosa_parks", + "norman_jewison", + "samuel_goldwyn", + "jacob", + "giuseppe_mazzini", + "jim_thorpe", + "hertz", + "arnold_sch\u00f6nberg", + "laurence_sterne", + "jacqueline_cochran", + "george_fox", + "fritz_kreisler", + "anne_hathaway", + "katarina", + "david_garrick", + "margaret_court", + "ii_edmund_angol_kir\u00e1ly", + "szent_m\u00e1rton_sziget", + "g", + "i_p\u00e9ter_orosz_c\u00e1r", + "arthur_schopenhauer", + "thomas_dekker", + "james_cagney", + "wanda_landowska", + "martin_heidegger", + "hans_eysenck", + "szent_krist\u00f3f", + "kett\u0151", + "r", + "george_lucas", + "andrew_jackson", + "edith_wharton", + "louis_armstrong", + "steven_spielberg", + "jean_monnet", + "d_w_griffith", + "robert_fulton", + "thomas_hardy", + "thomas_gainsborough", + "giuseppe_garibaldi", + "philip_warren_anderson", + "alexandre_dumas", + "robert_brown", + "thomas_carlyle", + "m\u00e1ria_magdal\u00e9na", + "william_tyndale", + "bobby_fischer", + "johannes_gutenberg", + "d", + "james_bowie", + "thomas_malthus", + "giambattista_marino", + "gaetano_donizetti", + "william_faulkner", + "amerigo_vespucci", + "pierre_boulez", + "hans_adolf_krebs", + "girolamo_savonarola", + "emma_goldman", + "francis_poulenc", + "john_barrymore", + "john_constable", + "rachel_louise_carson", + "james_mill", + "matthew_flinders", + "joseph_campbell", + "jean_de_la_fontaine", + "robert_hooke", + "i_edmund_wessexi_kir\u00e1ly", + "o_henry", + "i_justinianus_biz\u00e1nci_cs\u00e1sz\u00e1r", + "karl_popper", + "hruscsov", + "vi_s\u00e1ndor_p\u00e1pa", + "george_sand", + "peter_sellers", + "charles_fourier", + "a_bolyg\u00f3_hollandi", + "k\u00e9m\u00e9nysepr\u0151", + "joseph_conrad", + "kenneth_roberts", + "peter_paul_rubens", + "jim_morrison", + "jules_verne", + "paul_newman", + "george_meredith", + "robert_morris", + "woody_herman", + "alexander_wilson", + "josef_albers", + "jackson_pollock", + "john_lennon", + "andrea_palladio", + "bob_woodward", + "charlie_chaplin", + "d_h_lawrence", + "robert_woodward", + "john_brown", + "al_jolson", + "\u00e9s_a_t\u00f6bbi", + "thomas_merton", + "hannah_arendt", + "antonio_stradivari", + "i_szeleukosz_szeleukida_uralkod\u00f3", + "alice_walker", + "miles_davis", + "\u00f6k\u00f6rszemf\u00e9l\u00e9k", + "james_parkinson", + "hurr\u00e1", + "jesse_jackson", + "stanley_kubrick", + "john_huston", + "james_watt", + "jonathan_edwards", + "ronald_reagan", + "helmut_schmidt", + "david_hilbert", + "wilhelm_reich", + "roman_jakobson", + "oliver_cromwell", + "lionel_hampton", + "martin_luther_king", + "ii_lajos_nyugati_frank_kir\u00e1ly", + "frank_capra", + "william_wordsworth", + "s", + "vi_gy\u00f6rgy", + "marcus_antonius", + "sergey_rachmaninov", + "agrippina", + "richard_rodgers", + "tana_t\u00f3", + "anne_sexton", + "john_dryden", + "frank", + "ernest_hemingway", + "aquila", + "jacques_charles", + "arthur_miller", + "henry_russell", + "nelson_mandela", + "heinrich_himmler", + "al_gore", + "cesare_borgia", + "roald_amundsen", + "charles_dickens", + "ella_fitzgerald", + "jack_robinson", + "nagy_pele", + "alois_senefelder", + "george_enescu", + "jacques_offenbach", + "george_stevens", + "federico_fellini", + "bessie_smith", + "jean_antoine_watteau", + "willy_brandt", + "francisco_pizarro", + "francisco_franco", + "ii_frigyes_porosz_kir\u00e1ly", + "bernardo_bertolucci", + "jan_steen", + "i_khsaj\u00e1rs\u00e1_perzsa_kir\u00e1ly", + "john_ross", + "hans_arp", + "franz_schubert", + "johnny_cash", + "ii_philipposz_maked\u00f3n_kir\u00e1ly", + "sarl\u00f3sfecskef\u00e9l\u00e9k", + "alfred_kastler", + "mick_jagger", + "otto_loewi", + "s_a_t\u00f6bbi", + "georges_cuvier", + "william_harvey", + "walter_scott", + "peter_medawar", + "robert_peary", + "robert_browning", + "comenius", + "alessandro_farnese", + "john_bunyan", + "de_sade_m\u00e1rki", + "jonathan_swift", + "walter_gropius", + "albert_einstein", + "l", + "raymond_chandler", + "henry_purcell", + "t", + "wilhelm_ostwald" + ], + "ORG": [ + "ida", + "az_amerikai_egyes\u00fclt_\u00e1llamok_elektori_koll\u00e9giuma", + "\u00f3v\u00e1ros", + "mellesleg", + "hadig\u00e9p", + "benc\u00e9sek", + "nagyboldogasszony", + "s\u00e1rga_foly\u00f3", + "gironde", + "macskab\u00f6lcs\u0151", + "wicca", + "khonken", + "\u00fczletk\u00f6zpont", + "jan_mayen", + "micimack\u00f3", + "az_amerikai_egyes\u00fclt_\u00e1llamok_haditenger\u00e9szete", + "kamarazenekar", + "akad\u00e9mia", + "piacgazdas\u00e1g", + "nasa", + "ingatlank\u00f6zvet\u00edt\u0151", + "arda", + "isi", + "bollywood", + "k\u00f6zv\u00e9lem\u00e9ny", + "sang_dinasztia", + "europol", + "schutzstaffel", + "the_who", + "v\u00e1rosh\u00e1za", + "germanisztika", + "le\u00e1nyb\u00facs\u00fa", + "capeting_dinasztia", + "\u00faj_hull\u00e1m", + "aranykorm\u00edtosz", + "the_planetary_society", + "a_b\u00e1r\u00e1nyok_hallgatnak", + "cserk\u00e9szl\u00e1ny", + "tornacsarnok", + "san_francisco", + "nagy_medve_csillagk\u00e9p", + "dom\u00ednium", + "nagy_szent_vazul", + "titkosszolg\u00e1lat", + "el_a_kezekkel", + "elmegy\u00f3gyint\u00e9zet", + "baszkf\u00f6ld", + "a_fekete_macska", + "k\u00e9pcsarnok", + "rezesbanda", + "fels\u0151_t\u00f3", + "gao", + "vil\u00e1gbank", + "szecesszi\u00f3", + "j\u00f3_\u00e9tv\u00e1gyat", + "szuratthani", + "szabadelv\u0171_p\u00e1rt", + "tornaterem", + "f\u00fcsti_fecske", + "androm\u00e9da_galaxis", + "in_situ_v\u00e9delem", + "feketepiac", + "bikapiac", + "n\u00e9pp\u00e1rt", + "nagyolvaszt\u00f3", + "szakszervezet", + "hatsz\u00e1z", + "hagia_szophia", + "az_amerikai_egyes\u00fclt_\u00e1llamok_tenger\u00e9szgyalogs\u00e1ga", + "ai", + "hidegh\u00e1bor\u00fa", + "the_football_league", + "vaisnavizmus", + "et_al", + "dia", + "zeneipar", + "beatnemzed\u00e9k", + "holtverseny", + "szent_mikl\u00f3s", + "el_ajn", + "ki_vagy", + "szoci\u00e1ldemokr\u00e1cia", + "a_baby_boom_gener\u00e1ci\u00f3_tagja", + "csal\u00e1dfa", + "torl\u00f3d\u00e1s", + "ne_ny\u00falj_hozz\u00e1", + "k\u0151m\u0171vess\u00e9g", + "ellenszeg\u00fcl\u00e9s", + "mindenki_mag\u00e1\u00e9rt_felel", + "whig_p\u00e1rt", + "r\u00e1g\u00f3gumi", + "kolozsv\u00e1r", + "gestapo", + "nevel\u00e9s", + "nemzetbiztons\u00e1g", + "monokli", + "vall\u00e1studom\u00e1ny", + "munk\u00e1soszt\u00e1ly", + "fibonacci_sorozat", + "tejesk\u00e1v\u00e9", + "nemzetiszocialista_n\u00e9met_munk\u00e1sp\u00e1rt", + "h\u00e1rom_n\u0151v\u00e9r", + "az_utols\u00f3_napok_szentjeinek_j\u00e9zus_krisztus_egyh\u00e1za", + "han_dinasztia", + "szakk\u00f6z\u00e9piskola", + "az_egyes\u00fclt_\u00e1llamok_k\u00e9pvisel\u0151h\u00e1za", + "als\u00f3h\u00e1z", + "haditenger\u00e9szet", + "\u00e9s_tsai", + "oktat\u00e1s", + "ellenkez\u00e9s", + "z\u00f6ld_foki_k\u00f6zt\u00e1rsas\u00e1g", + "kereszt\u00e9nydemokrat\u00e1k", + "leg\u00e9nyb\u00facs\u00fa", + "feh\u00e9rarany", + "az_amerikai_egyes\u00fclt_\u00e1llamok_l\u00e9giereje", + "kereszt\u00e9ny_tudom\u00e1ny", + "hollywood", + "szabadk\u0151m\u0171vess\u00e9g", + "saint_barth\u00e9lemy", + "vegyipar", + "sturmabteilung", + "los_angeles", + "nato", + "az_egyes\u00fclt_\u00e1llamok_parti_\u0151rs\u00e9ge", + "baltimore_orioles", + "melegh\u00e1zass\u00e1g", + "ad_hoc", + "a_nevem", + "ivano_frankivszk", + "nemzetk\u00f6zi_jog", + "l\u00e9gier\u0151", + "mi", + "by_the_way", + "krivij_rih", + "nagyd\u00edj", + "k\u00e1rmel", + "m\u0171csarnok", + "f\u00fcv\u00e9szkert", + "bern\u00e1thegyi", + "doc", + "munk\u00e1sp\u00e1rt", + "aktu\u00e1lis", + "szent_borb\u00e1la", + "ellenz\u00e9s", + "ae\u00e1", + "forg\u00f3ajt\u00f3", + "ez_az", + "ace", + "csillaghalmaz", + "v\u00f6r\u00f6skereszt", + "demokrata_p\u00e1rt", + "nagy_medve", + "bund\u00e1s_keny\u00e9r", + "k\u00f6z\u00e9piskola", + "taoizmus", + "az_egyes\u00fclt_\u00e1llamok_szen\u00e1tusa", + "eu", + "szeretlek", + "csig\u00e1spolip", + "sz\u00ednsor", + "koroszt\u00e1ly", + "kincst\u00e1r", + "r\u00e1di\u00f3galaxis", + "\u00e9desv\u00edz", + "az_egyes\u00fclt_\u00e1llamok_kongresszusa", + "babszem_jank\u00f3", + "angkorvat", + "republik\u00e1nus_p\u00e1rt", + "s\u00e3o_tom\u00e9" + ], + "ANIMAL": [ + "terenura_sharpei", + "bar\u00e1tr\u00e9ce", + "keny\u00e9rbog\u00e1r", + "apodemus", + "elef\u00e1ntf\u00f3ka", + "pehelyr\u00e9ce", + "indi\u00e1n\u00f6k\u00f6rszem", + "narancstrupi\u00e1l", + "tigrisc\u00e1paf\u00e9l\u00e9k", + "kukor\u00e9kol", + "s\u00e1rgarig\u00f3f\u00e9l\u00e9k", + "buteo", + "dankasir\u00e1ly", + "csillagr\u00e1ja", + "bar\u00e1tcsuszka", + "sarl\u00f3sfecske", + "tengerir\u00f3zsa", + "k\u00edgy\u00e1szkesely\u0171", + "nagy_pele", + "nagy_viaszmoly", + "nagy_pr\u00e9rity\u00fak", + "husz\u00e1rmajom", + "medvep\u00e1vi\u00e1n", + "l\u00e9gykap\u00f3f\u00e9l\u00e9k", + "kesely\u0171tekn\u0151s", + "babirussza", + "nagy_\u0151rg\u00e9bics", + "sarl\u00f3sfecskef\u00e9l\u00e9k", + "farkass\u00fcg\u00e9r", + "k\u00e9szletmoly", + "tigrisc\u00e1pa", + "burgonyabog\u00e1r", + "kaliforniai_oroszl\u00e1nf\u00f3ka", + "siketfajd", + "k\u00e1posztalepke", + "hal\u00e1lk\u00edgy\u00f3", + "barnamoszatok", + "ecetmuslica", + "feny\u0151fajd", + "almamoly", + "vaddiszn\u00f3", + "gr\u00e1n\u00e1tpinty", + "eger\u00e9sz\u00f6lyv", + "tigrispiton", + "kaliforniai_szam\u00e1rny\u00fal", + "manta", + "a_holl\u00f3", + "bankivaty\u00fak", + "partifecske", + "kesely\u0171", + "carduelis", + "r\u00e9palepke", + "mandarinr\u00e9ce", + "csonttoll\u00fa", + "nyuszt", + "angyalc\u00e1pa", + "iszapt\u00f6cs", + "lactobacillus_acidophilus", + "tigriscs\u00f6rg\u0151k\u00edgy\u00f3", + "tengeris\u00fcn\u00f6k", + "emsemak\u00e1k\u00f3", + "gumiboa", + "thomson_gazella", + "kolor\u00e1d\u00f3bog\u00e1r", + "micropterus", + "v\u00f6r\u00f6sbegy", + "gyalogs\u00fclf\u00e9l\u00e9k", + "csap\u00f3s\u00fcg\u00e9r", + "ruhatet\u0171", + "galgo", + "k\u00f6z\u00f6ns\u00e9ges_levestekn\u0151s", + "nagy_kudu", + "coboly", + "rend\u0151rkutya", + "gulip\u00e1n", + "holdhal", + "holyvaf\u00e9l\u00e9k", + "b\u00e9ka", + "harrier", + "pettyes_billeget\u0151cank\u00f3", + "k\u00e9sei_meggyv\u00e1g\u00f3", + "jegesmedve", + "karvalybagoly", + "deres_erdeipocok", + "nagy_k\u00e1r\u00f3katona", + "feny\u0151szajk\u00f3", + "jegesr\u00e9ce", + "bar\u00e1tcinege", + "marmotini", + "p\u00e1lmagerle", + "meny\u00e9t", + "karvaly", + "gubacsdar\u00e1zs", + "citromc\u00e1pa", + "fut\u00f3mad\u00e1r", + "accipiter", + "fatty\u00fahering", + "tengerir\u00f3zs\u00e1k", + "sugarastekn\u0151s", + "kondorkesely\u0171", + "postagalamb", + "galamblumma", + "gyapoteg\u00e9r", + "eszkim\u00f3p\u00f3ling", + "szalonka", + "kakashal", + "gerle", + "szil\u00e1scetek", + "nagy_s\u00e1rszalonka", + "krumplibog\u00e1r", + "banteng", + "nagy_f\u0171r\u00e9szesr\u00e1ja", + "kardin\u00e1lispinty", + "varj\u00fa", + "nagy_p\u00f6r\u00f6lyc\u00e1pa", + "paradicsompapag\u00e1j", + "k\u00e9m\u00e9nysarl\u00f3sfecske", + "tengeriubork\u00e1k", + "s\u00e1rgarig\u00f3", + "iller", + "kalauzhal", + "pampab\u00edbic", + "\u00e1llatvil\u00e1g", + "bar\u00e1tkesely\u0171", + "pelef\u00e9l\u00e9k", + "c\u00e9druscsonttoll\u00fa", + "kercer\u00e9ce", + "nagy_pir\u00f3k", + "keresztcs\u0151r\u0171", + "b\u00edborpirok", + "lev\u00e9lbog\u00e1rf\u00e9l\u00e9k", + "ammospermophilus", + "megascops", + "emberbag\u00f3cs", + "alig\u00e1tortekn\u0151s", + "borz", + "holl\u00f3kesely\u0171", + "baktri\u00e1n", + "bikac\u00e1pa", + "vadszam\u00e1r", + "indi\u00e1ng\u00e9bics", + "feketerig\u00f3", + "sziv\u00e1rv\u00e1nys\u00fcg\u00e9r", + "inkakakadu", + "varangyf\u00e9l\u00e9k", + "l\u00e9prig\u00f3", + "remeter\u00e1k", + "gyapjaslepke", + "diszn\u00f3delfinf\u00e9l\u00e9k", + "u_bet\u0171s_aranybagoly", + "holl\u00f3", + "kafferbivaly", + "burunduk", + "csik\u00f3hal", + "fenyvescinege", + "nagy_sz\u00ednj\u00e1tsz\u00f3lepke", + "r\u00e9tisas", + "barramundi", + "t\u00fcnd\u00e9rasztrild", + "epstein_barr_v\u00edrus", + "indi\u00e1ncinege", + "nagy_\u00e1mbr\u00e1scet", + "v\u00f6r\u00f6smoszatok", + "tengelic", + "kesely\u0171k", + "varangy", + "anyakir\u00e1lyn\u0151", + "kotl\u00f3s", + "tengerimalac", + "si_cu", + "farkasp\u00f3kf\u00e9l\u00e9k", + "kondor", + "nagy_buk\u00f3", + "sz\u00e1mb\u00e1rszarvas", + "nagy_f\u00fclem\u00fcle", + "nagy_halfarkas", + "alkabuk\u00f3", + "bivaly", + "ikerszelv\u00e9nyesek", + "eider", + "pisztr\u00e1ngs\u00fcg\u00e9r", + "arvicola", + "nagy_k\u00f3csag" + ], + "DISEASE": [ + "sars", + "sz\u00e1mol\u00e1szavar", + "b\u0151rgyullad\u00e1s", + "ki", + "hiszt\u00e9ria", + "elg\u00e1zos\u00edt", + "angolk\u00f3r", + "rohamiv\u00e1s", + "rage", + "effektus", + "sug\u00e1rz\u00e1s", + "hasny\u00e1lmirigyr\u00e1k", + "materializmus", + "simogat", + "rendelleness\u00e9g", + "vissz\u00e9r", + "terhess\u00e9g", + "ty\u00fakszem", + "panasz", + "daganat", + "korp\u00e1sod\u00e1s", + "polyarteritis_nodosa", + "rozsda", + "furunkulus", + "torokgy\u00edk", + "mononucleosis_infectiosa", + "radi\u00e1ci\u00f3", + "lump", + "deviancia", + "t\u00e9velyg\u00e9s", + "kank\u00f3", + "leforr\u00e1z", + "dadog", + "hervad", + "gall", + "the_bends", + "gyermekb\u00e9nul\u00e1s", + "pang", + "porckorongs\u00e9rv", + "herer\u00e1k", + "a_b\u00e1r\u00e1nyhiml\u0151", + "gyullad\u00e1s", + "mellr\u00e1k", + "sipoly", + "tarantizmus", + "pikkelys\u00f6m\u00f6r", + "vakb\u00e9lgyullad\u00e1s", + "szelet", + "mell\u00e9khat\u00e1s", + "golyva", + "k\u00f6z\u00e9pf\u00fclgyullad\u00e1s", + "hasmen\u00e9s", + "csillagk\u00f6d", + "der\u00e9kf\u00e1j\u00e1s", + "alap\u00edt\u00f3", + "sert\u00e9sinfluenza", + "testess\u00e9g", + "lebarnul", + "beri_beri", + "parit\u00e1s", + "lambdacizmus", + "veszetts\u00e9g", + "besz\u00e9dhiba", + "hullamerevs\u00e9g", + "kanyar\u00f3", + "szilfav\u00e9sz", + "hamartoma", + "hurut", + "szem\u00e9lyis\u00e9gzavar", + "klausztrof\u00f3bia", + "hast\u00edfusz", + "aneszt\u00e9zia", + "mormol\u00e1s", + "down_szindr\u00f3ma", + "gesztenye", + "indulat", + "gimp", + "cukorbetegs\u00e9g", + "mirigyk\u00f3r", + "meghib\u00e1sod\u00e1s", + "ed", + "sclerosis_multiplex", + "pica", + "vitust\u00e1nc", + "m\u00e1jgyullad\u00e1s", + "sz\u00fcrkeh\u00e1lyog", + "pattan\u00e1s", + "szalmonella", + "keszonbetegs\u00e9g", + "sensation", + "teniszk\u00f6ny\u00f6k", + "betegs\u00e9g", + "kergemarhak\u00f3r", + "szindr\u00f3ma", + "pain", + "here_vissz\u00e9rt\u00e1gulat", + "benn", + "m\u00e9regcs\u00f3k", + "polidaktilia", + "megf\u00e1z\u00e1s", + "kancsals\u00e1g", + "gerincferd\u00fcl\u00e9s", + "ill", + "kisz\u00e1rad\u00e1s", + "aura_t\u00fcnetegy\u00fcttes", + "tengeribetegs\u00e9g", + "pellagra", + "schistosomiasis", + "tachikardia", + "mi", + "medd\u0151s\u00e9g", + "nem_j\u00f6n_szememre_\u00e1lom", + "skorbut", + "szam\u00e1rk\u00f6h\u00f6g\u00e9s", + "szilik\u00f3zis", + "korpulencia", + "sting", + "forrad\u00e1s", + "the_bleeding", + "szab\u00e1lytalans\u00e1g", + "veseel\u00e9gtelens\u00e9g", + "trauma", + "tompal\u00e1t\u00e1s", + "szem\u00f6lcs", + "bradikardia", + "eml\u0151r\u00e1k", + "kuru", + "burn", + "gy\u00fcm\u00f6lcsl\u00e9", + "mandulagyullad\u00e1s", + "selyp\u00edt\u00e9s", + "noma", + "the_hives", + "l\u00e9gibetegs\u00e9g", + "feh\u00e9rv\u00e9r\u0171s\u00e9g", + "beteg", + "a_passi\u00f3", + "gangr\u00e9na", + "kudarc", + "le", + "orrs\u00f6v\u00e9nyferd\u00fcl\u00e9s", + "\u00e9tv\u00e1gytalans\u00e1g", + "papag\u00e1jk\u00f3r", + "csontritkul\u00e1s", + "takonyk\u00f3r", + "kretenizmus", + "faridegzs\u00e1ba", + "csukl\u00e1s" + ], + "PLANT": [ + "acanthocereus_tetragonus", + "pap\u00edrny\u00edr", + "borzaskata", + "franciaperje", + "must\u00e1rmag", + "erdeifeny\u0151", + "v\u00f6r\u00f6sfeny\u0151", + "simafeny\u0151", + "nadragulya", + "kornist\u00e1rnics", + "amerikai_k\u0151ris", + "mangrovep\u00e1lma", + "feh\u00e9rm\u00e1jvir\u00e1g", + "the_joshua_tree", + "szel\u00eddgesztenye", + "selyembokor", + "sulyom", + "nagy_v\u00edzibogl\u00e1rka", + "gyalogak\u00e1c", + "ed\u00e9nynyal\u00e1b", + "ty\u00fakh\u00far", + "vadmurok", + "guttaperchafa", + "anyarozs", + "lapockacsont", + "p\u00fcsp\u00f6kfeny\u0151", + "kakukkszegf\u0171", + "b\u00fazavir\u00e1g", + "must\u00e1r", + "selyemk\u00f3r\u00f3", + "margitvir\u00e1g", + "magyalt\u00f6lgy", + "gomberny\u0151", + "macskam\u00e9z", + "zelnicemeggy", + "kaszkarilla", + "baracklevel\u0171_harangvir\u00e1g", + "sug\u00e1rkankalin", + "kelk\u00e1poszta", + "szikomorfa", + "szenegaf\u0171", + "takarm\u00e1nybaltacim", + "candida_albicans", + "p\u00e1sztort\u00e1ska", + "cs\u00e1sz\u00e1rgomba", + "tobozmirigy", + "v\u00edzip\u00e1lma", + "\u00f3ri\u00e1sbambusz", + "vadk\u00e1poszta", + "cik\u00e1szok", + "kar\u00e1csonyfa", + "oroszl\u00e1nsz\u00e1j", + "erdei_turbolya", + "farkassz\u0151l\u0151", + "tangerin", + "selenicereus_grandiflorus", + "feny\u00e9rgamandor", + "amerikai_mocs\u00e1rciprus", + "piros_gy\u0171sz\u0171vir\u00e1g", + "chilei_arauk\u00e1ria", + "tiszafa", + "parat\u00f6lgy", + "turb\u00e1nliliom", + "kakasmandik\u00f3", + "mos\u00f3di\u00f3fa", + "bark\u00f3cafa", + "csirimoj\u00f3", + "katicavir\u00e1g", + "nefelejcs", + "olaszn\u00e1d", + "g\u00f6r\u00f6gtekercs", + "bark\u00f3ca", + "pipacs", + "blackberry", + "nagy_csal\u00e1n", + "s\u00e1rgabors\u00f3", + "farkasboroszl\u00e1n", + "t\u00f6r\u00f6kr\u00f3zsa", + "jap\u00e1ncseresznye", + "nagy_v\u00f6lgycsillag", + "rezeda", + "csemegekukorica", + "eg\u00e9r\u00e1rpa", + "gy\u00f6ngyvir\u00e1g", + "nagy_\u00fatif\u0171", + "feny\u00e9rmirtusz", + "napraforg\u00f3", + "s\u00e1rgar\u00e9pa", + "bark\u00f3caberkenye", + "mani\u00f3ka", + "sono_keling", + "p\u00e9zsmam\u00e1lyva", + "\u00f3ri\u00e1sp\u00f6feteg", + "liliomfa", + "balzsamfeny\u0151", + "hagymaburok", + "lampionvir\u00e1g", + "raponcharangvir\u00e1g", + "oregoni_hamisciprus", + "csillagp\u00e1zsit", + "sejtfal", + "vadgesztenye", + "juhar", + "\u00e9desburgonya", + "feny\u00e9rcirok", + "trombitafolyond\u00e1r", + "tarl\u00f3r\u00e9pa", + "szakura", + "erdei_ibolya", + "lonc", + "vadalma", + "angolperje", + "vetem\u00e9nybab", + "atlaszc\u00e9drus", + "k\u00f6nnyez\u0151p\u00e1lma", + "kelbimb\u00f3" + ], + "FOOD": [ + "macskaeledel", + "porcukor", + "narancsh\u00e9j", + "mogyor\u00f3vaj", + "fagylalt", + "szult\u00e1nkeny\u00e9r", + "gy\u00f3gytea", + "feh\u00e9rbor", + "besamelm\u00e1rt\u00e1s", + "borecet", + "tejesk\u00e1v\u00e9", + "jegesk\u00e1v\u00e9", + "reggeli", + "narancsl\u00e9", + "m\u00e1rt\u00e1s", + "m\u00e9zeskal\u00e1csfigura", + "pinot_noir", + "szez\u00e1molaj", + "\u00e9letelix\u00edr", + "juharszirup", + "tejsz\u00ednhab", + "csirkesz\u00e1rny", + "paradicsomsz\u00f3sz", + "viaszt\u00f6k", + "falatoz\u00e1s", + "b\u00f6l\u00e9nysz\u00e1rny", + "chile", + "gyors\u00e9telek", + "paradicsoml\u00e9", + "r\u00e9pacukor", + "port\u00f3i", + "bab\u00e9rlev\u00e9l", + "limon\u00e1d\u00e9", + "cukr\u00e1szs\u00fctem\u00e9ny", + "szerencses\u00fcti", + "desszert", + "roz\u00e9bor", + "szalmakrumpli", + "nassolnival\u00f3", + "kandiscukor", + "p\u00e1lmaolaj", + "feketek\u00e1v\u00e9", + "rozskeny\u00e9r", + "leveskocka", + "r\u00e1ntotta", + "kaka\u00f3vaj", + "burgonyaszirom", + "v\u00f6r\u00f6sbor", + "vattacukor", + "almal\u00e9", + "citroml\u00e9", + "libam\u00e1j" + ], + "JOB": [ + "sz\u00e9nb\u00e1ny\u00e1sz", + "dragonyos", + "csillag\u00e1sz", + "munk\u00e1s", + "guru", + "krupi\u00e9", + "berep\u00fcl\u0151pil\u00f3ta", + "karmester", + "nevel\u0151n\u0151", + "moln\u00e1r", + "a_kezdetek", + "cukr\u00e1sz", + "gyakornok", + "jeges", + "konzul", + "polg\u00e1rmester", + "meteores\u0151", + "fogorvos", + "a_j\u00f6v\u0151_h\u00edrn\u00f6ke", + "herold", + "neurol\u00f3gus", + "elef\u00e1nthajcs\u00e1r", + "kelmefest\u0151", + "a_tolm\u00e1cs", + "simogat", + "obsitos", + "busalepkef\u00e9l\u00e9k", + "szappanoz", + "felcser", + "horg\u00e1sz", + "meteorol\u00f3gus", + "vonalz\u00f3", + "erd\u00e9sz", + "b\u00f6rt\u00f6n\u0151r", + "kalauzol", + "katona", + "rakt\u00e1ros", + "pint\u00e9r", + "don", + "a_d\u00far", + "szendvicsember", + "fazekas", + "dietetikus", + "kidob\u00f3", + "the_police", + "olvas\u00f3szerkeszt\u0151", + "z\u00e1szl\u00f3viv\u0151", + "terapeuta", + "szabad\u00fasz\u00f3", + "boltos", + "kartogr\u00e1fus", + "v\u00edziment\u0151", + "kozmetikus", + "tejesember", + "gentleman", + "utcasepr\u0151", + "szinkronsz\u00edn\u00e9sz", + "csin\u00e1l", + "kert\u00e9sz", + "korm\u00e1nyz\u00f3", + "tengernagy", + "formatervez\u0151", + "grip", + "h\u00e1zi\u00far", + "macskajaj", + "mastermind", + "kir\u00e1ly", + "kond\u00e1s", + "szolga", + "minden_kezdet_neh\u00e9z", + "tenger\u00e9sz", + "termel\u0151", + "sim\u00edt", + "antol\u00f3gus", + "az_amerikai_egyes\u00fclt_\u00e1llamok_eln\u00f6ke", + "takar\u00edt\u00f3", + "marhap\u00e1sztor", + "nagyk\u00f6vet", + "hord\u00e1r", + "abrak", + "hematol\u00f3gus", + "scientist", + "port\u00e1s", + "kamikaze", + "furulya", + "bevezet\u0151", + "the_advocate", + "kapus", + "a_dadus", + "altengernagy", + "alkusz", + "orvostanhallgat\u00f3", + "dalszerz\u0151", + "freelancer", + "t\u00e1bornagy", + "f\u00e9nyk\u00e9p\u00e9sz", + "rend\u0151rn\u0151", + "the_guardian", + "kardiol\u00f3gus", + "rendez\u0151", + "tak\u00e1cs", + "borb\u00e9ly", + "immunol\u00f3gus", + "a_szarvasvad\u00e1sz", + "mandarin", + "solym\u00e1r", + "tud\u00f3s", + "fest\u0151", + "f\u00fcggetlen", + "mate", + "alezredes", + "erd\u0151ker\u00fcl\u0151", + "ideggy\u00f3gy\u00e1sz", + "diszn\u00f3p\u00e1sztor", + "hint\u00f3", + "a_t\u00e1rsas\u00e1g_embere", + "erd\u0151\u0151r", + "patikus", + "takar\u00edt\u00f3n\u0151", + 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"\u057d\u0578\u0582\u0580\u0562_\u0570\u0578\u0563\u056b", + "\u0561\u0576\u0574\u0578\u057c\u0578\u0582\u056f", + "\u0563\u0576\u0564\u0561\u057c\u0561\u0576\u0581\u0584\u0561\u056f\u0561\u056c", + "\u0574\u0561\u0580\u0564\u0578\u0582_\u056b\u0580\u0561\u057e\u0578\u0582\u0576\u0584\u0576\u0565\u0580", + "\u0583\u0561\u056f\u0578\u0582\u0572\u056b", + "\u0570\u0578\u057c\u0576_\u0570\u0580\u057e\u0561\u0576\u0564\u0561\u0576" + ], + "PLANT": [ + "\u0577\u0561\u0584\u0561\u0580\u0565\u0572\u0565\u0563", + "\u056d\u0581\u0561\u0576\u0561\u056f\u0561\u0572\u0576\u056b", + "\u056e\u0578\u057e\u0561\u056f\u0561\u0572\u0561\u0574\u0562", + "\u057d\u0578\u0582\u0580\u0562_\u0574\u0561\u0580\u056b\u0561\u0574", + "\u0570\u0561\u0566\u0561\u0580\u0561\u057f\u0565\u0580\u0565\u0582\u0578\u0582\u056f", + "\u056e\u0561\u0572\u056f\u0561\u056f\u0561\u0572\u0561\u0574\u0562", + "blackberry", + "\u0562\u0561\u0574\u0562\u0578\u0582\u056f", + "\u0565\u0572\u057b\u0565\u0580\u0561\u057d\u0578\u0582\u0576\u056f", + "\u0565\u0572\u0565\u0563\u0576\u0561\u0562\u0578\u0582\u0575\u057d", + "\u056a\u0561\u0576\u057f\u0561\u0583\u0578\u0582\u0577", + "\u0561\u0580\u0565\u057e\u0561\u056e\u0561\u0572\u056b\u056f" + ], + "LOCATION": [ + "\u0584\u0561\u0572\u0561\u0584\u0561\u057a\u0565\u057f\u0561\u0580\u0561\u0576", + "\u057e\u0565\u0580\u056b\u0576_\u056c\u056b\u0573", + "\u057d\u0561\u0576\u057f\u0561_\u056f\u056c\u0561\u0578\u0582\u057d", + "\u056f\u0580\u056b\u057e\u0578\u0575_\u057c\u0578\u0563", + "\u057d\u0565\u0580\u0562\u056b\u0561\u0575\u056b_\u056d\u0578\u0580\u0570\u0580\u0564\u0561\u0580\u0561\u0576", + "\u057c\u0585\u0578\u0582", + "\u056f\u0565\u0576\u057f\u0580\u0578\u0576\u0561\u056f\u0561\u0576_\u0562\u0561\u0576\u056f", + "\u057c\u0561\u0566\u0574\u0561_\u0585\u0564\u0561\u0575\u056b\u0576_\u0578\u0582\u056a\u0565\u0580", + "the_rolling_stones", + "\u057d\u0561\u0584\u057d\u0578\u0576\u056b\u0561_\u0561\u0576\u0570\u0561\u056c\u0569", + "\u0562\u0578\u0582\u057d\u0561\u0562\u0561\u0576\u0561\u056f\u0561\u0576_\u0561\u0575\u0563\u056b", + "\u0574\u0565\u056e_\u0561\u0580\u057b", + "\u056f\u0561\u0576\u0561\u0579_\u0570\u0580\u057e\u0561\u0576\u0564\u0561\u0576", + "\u0574\u0561\u0580\u0566\u0561\u0564\u0561\u0577\u057f", + "\u0584\u0580\u056b\u057d\u057f\u0561\u0583\u0578\u0580_\u056f\u0578\u056c\u0578\u0582\u0574\u0562\u0578\u057d", + "\u057d\u0578\u0582\u0580\u0562_\u0570\u0565\u0572\u056b\u0576\u0565\u056b_\u056f\u0572\u0566\u056b", + "\u0586\u0580\u0561\u0576\u057d\u056b\u0561\u0575\u056b_\u0561\u0566\u0563\u0561\u0575\u056b\u0576_\u056a\u0578\u0572\u0578\u057e", + "\u057c\u0561\u0566\u0574\u0561\u0585\u0564\u0561\u0575\u056b\u0576_\u0578\u0582\u056a\u0565\u0580" + ], + "RELIGION": [ + "\u0574\u0578\u0580\u0574\u0578\u0576\u0576\u0565\u0580", + "\u056f\u0561\u056c\u057e\u056b\u0576\u0561\u056f\u0561\u0576\u0578\u0582\u0569\u0575\u0578\u0582\u0576", + "\u057f\u0561\u0576\u057f\u0580\u056b\u0566\u0574", + "\u0566\u0565\u0576" + ], + "ORG": [ + "\u0584\u0561\u0572\u0561\u0584\u0561\u057a\u0565\u057f\u0561\u0580\u0561\u0576", + "\u056f\u0561\u057c\u0561\u057e\u0561\u0580\u0578\u0582\u0569\u0575\u0578\u0582\u0576", + "\u056f\u0561\u0569\u0578\u056c\u056b\u056f_\u0565\u056f\u0565\u0572\u0565\u0581\u056b", + "\u0576\u0578\u0580\u0561\u056c\u0578\u0582\u057d\u056b\u0576", + "\u0563\u0565\u0580\u0574\u0561\u0576\u0561\u056f\u0561\u0576_\u056f\u0561\u0575\u057d\u0580\u0578\u0582\u0569\u0575\u0578\u0582\u0576", + "\u0574\u0561\u057d\u0578\u0576\u0578\u0582\u0569\u0575\u0578\u0582\u0576", + "\u0571\u056b\u0569\u0565\u0576\u0575\u0561\u0581_\u056c\u0565\u057c", + "\u0574\u056b\u057b\u056b\u0576_\u056d\u0561\u057e", + "\u0561\u057d\u057f\u057e\u0561\u056e\u0561\u056e\u0576\u056b_\u057e\u0565\u0580\u0561\u0583\u0578\u056d\u0574\u0561\u0576_\u057f\u0578\u0576", + "\u0584\u0576\u0561\u056e_\u0563\u0565\u0572\u0565\u0581\u056f\u0578\u0582\u0570\u056b\u0576", + "\u0561\u056c_\u057b\u0561\u0566\u056b\u0580\u0561", + "\u0563\u0578\u0574\u056b\u0576\u0564\u0561\u0576", + "\u056f\u0561\u0562\u0578_\u057e\u0565\u0580\u0564\u0565", + "\u0574\u0580\u0563\u0561\u0575\u056b\u0576_\u0561\u0572\u0581\u0561\u0576", + "\u056f\u0578\u0576\u057d\u0565\u0580\u057e\u0561\u057f\u0578\u0580\u056b\u0561", + "\u0564\u0561\u0578\u057d\u0561\u056f\u0561\u0576\u0578\u0582\u0569\u0575\u0578\u0582\u0576", + "\u0561\u0580\u057f\u0561\u057d\u0561\u0570\u0574\u0561\u0576", + "\u057d\u056b\u0576\u057f\u0578\u056b\u0566\u0574", + "\u0570\u0565\u057f\u0561\u0584\u0576\u0576\u0578\u0582\u0569\u0575\u0578\u0582\u0576\u0576\u0565\u0580\u056b_\u0564\u0561\u0577\u0576\u0561\u0575\u056b\u0576_\u0562\u0575\u0578\u0582\u0580\u0578", + "\u0563\u056b\u0577\u0565\u0580\u0585\u0569\u056b\u056f", + "\u0574\u0561\u0584\u057d\u0561\u057f\u0578\u0582\u0576", + "\u057d\u0561\u0576_\u057f\u0578\u0574\u0565", + "\u0585\u0564\u0578\u0582\u056a", + "\u056a\u0578\u0572\u0578\u057e\u0580\u0564\u0561\u056f\u0561\u0576_\u056f\u0578\u0582\u057d\u0561\u056f\u0581\u0578\u0582\u0569\u0575\u0578\u0582\u0576", + "\u057d\u0565\u0582_\u0561\u0575\u0580\u056b", + "\u057e\u056b\u0576\u056b_\u0569\u0578\u0582\u056d", + "\u0563\u0565\u0580\u0574\u0561\u0576\u0565\u0580\u0565\u0576", + "by_the_way", + "\u057d\u0565\u0576\u057f_\u056c\u0575\u0578\u0582\u057d\u056b\u0561", + "in_situ", + "\u0574\u056b\u0561\u0581\u0575\u0561\u056c_\u0576\u0561\u0570\u0561\u0576\u0563\u0576\u0565\u0580", + "\u0576\u0561\u0574\u0561\u056f\u0561\u057f\u0578\u0582\u0576", + "\u0561\u057d\u057f\u0572\u0561\u056f\u0578\u0582\u0575\u057f\u0565\u0580", + "\u056f\u0561\u0580\u0574\u056b\u0580_\u056d\u0561\u0579", + "\u0566\u056b\u0576\u057e\u0578\u0580\u0561\u056f\u0561\u0576", + "\u0570\u0578\u0582\u0561\u0576\u0570\u0565", + "\u0574\u0561\u057d\u057f\u0561\u056f", + "\u057d\u0578\u0582\u0580\u0562_\u057d\u0578\u0586\u056b\u0561\u0575\u056b_\u057f\u0561\u0573\u0561\u0580", + "\u057c\u0561\u0564\u056b\u0578\u0563\u0561\u056c\u0561\u056f\u057f\u056b\u056f\u0561", + "\u057d\u057a\u056b\u057f\u0561\u056f_\u057f\u0578\u0582\u0576", + "\u0561\u056c_\u0561\u0575\u056b\u0576", + "\u0561\u0580\u0570\u0565\u057d\u057f\u0561\u056f\u0581\u0561\u056f\u0561\u0576_\u0574\u056b\u0578\u0582\u0569\u0575\u0578\u0582\u0576", + "\u0561\u0564\u0580\u0562\u0565\u057b\u0561\u0576\u056b_\u0561\u0566\u0563\u0561\u0575\u056b\u0576_\u056a\u0578\u0572\u0578\u057e", + "\u0583\u0578\u057d\u057f\u056b_\u0562\u0561\u056a\u0561\u0576\u0574\u0578\u0582\u0576\u0584", + "\u0568\u0576\u0564\u0564\u056b\u0574\u0578\u0582\u0569\u0575\u0578\u0582\u0576", + "\u056f\u0578\u0582\u057d\u0561\u056f\u0581\u0578\u0582\u0569\u0575\u0578\u0582\u0576" + ], + "LANGUAGE": [ + "\u056f\u0561\u057f\u0561\u056c\u0578\u0576\u0561\u0581\u056b", + "\u057a\u0561\u0580\u057d\u056f\u0565\u0580\u0565\u0576", + "\u056b\u057d\u056c\u0561\u0576\u0564\u0565\u0580\u0565\u0576", + "\u0569\u0578\u0582\u0580\u0584\u0574\u0565\u0576\u0561\u056f\u0561\u0576", + "\u0561\u0580\u0561\u0562\u0565\u0580\u0565\u0576", + "\u0586\u0580\u0561\u0576\u057d\u0565\u0580\u0565\u0576", + "\u057d\u0574\u056b\u0569" + ], + "GPE": [ + "\u057d\u0578\u0582\u0580\u0562_\u0576\u056b\u056f\u0578\u0572\u0561\u0575\u0578\u057d", + "\u057d\u0578\u0582\u0580\u0562_\u056c\u0561\u057e\u0580\u0565\u0576\u057f\u056b\u0578\u057d\u056b_\u0563\u0565\u057f", + "\u057d\u0578\u0582\u0580\u0562_\u056c\u0561\u057e\u0580\u0565\u0576\u057f\u056b\u0578\u057d_\u0563\u0565\u057f", + "\u057d\u0578\u0582\u0580\u0562_\u0576\u056b\u056f\u0578\u0572\u0561\u0575\u0578\u057d_\u0566\u0574\u0575\u0578\u0582\u057c\u0576\u0561\u0581\u056b", + "\u056f\u0561\u0580\u0574\u056b\u0580_\u056e\u0578\u057e", + "\u057a\u0565\u057f\u0580\u0578\u057d_\u0561\u057c\u0561\u0584\u0575\u0561\u056c" + ], + "FAC": [ + "\u0570\u0561\u0572\u0569\u0561\u056f\u0561\u0574\u0561\u0580", + "\u0562\u0561\u0580\u0571\u0580_\u0564\u0578\u0582\u057c", + "\u0570\u057c\u0578\u0574\u056b_\u056f\u0561\u0569\u0578\u056c\u056b\u056f_\u0565\u056f\u0565\u0572\u0565\u0581\u056b", + "\u057a\u0565\u057f\u0580\u0578\u057d_i" + ], + "ANIMAL": [ + "\u057e\u0561\u0580\u0561\u0566", + "\u0565\u0580\u056f\u057d\u0574\u0562\u0561\u056f\u0561\u057e\u0578\u0580\u0576\u0565\u0580", + "\u0565\u0572\u0576\u057b\u0561\u0569\u057c\u0579\u0576\u0561\u056f\u0576\u0565\u0580", + "\u0576\u0561\u057e\u0561\u056d\u0565\u0581\u056b\u0576\u0565\u0580", + "\u056f\u0561\u0569\u0576\u0561\u057d\u0578\u0582\u0576", + 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"\u057d\u0565\u0580\u0578\u0562", + "\u0570\u0561\u0580\u0578\u0582\u0569\u0575\u0578\u0582\u0576", + "\u0566\u0578\u0570\u0580\u0561\u057a", + "\u057e\u056c\u0561\u0564\u056b\u0574\u056b\u0580", + "\u056f\u056c\u0578\u0564", + "\u0563\u0561\u0580\u057d\u0587\u0561\u0576", + "\u057d\u0578\u0582\u0580\u0565\u0576", + "\u0561\u0580\u0561\u0574", + "\u0567\u0564\u0563\u0561\u0580", + "\u056f\u056b\u056f\u0578\u057d", + "\u057a\u0561\u0580\u0569\u0587", + "\u0576\u0561\u056b\u0580\u056b", + "\u0570\u0561\u056f\u0578\u0562", + "\u0570\u0561\u0575\u056f\u0561\u0566", + "\u0563\u0580\u056b\u0563\u0578\u0580", + "\u056d\u0578\u057d\u0580\u0578\u057e", + "\u057e\u0561\u0570\u0561\u0563\u0576", + "\u057b\u056b\u057e\u0561\u0576", + "\u0563\u0561\u0580\u0580\u056b", + "\u0564\u0561\u0576\u056b\u0565\u056c", + "\u0561\u0580\u0565\u0563", + "\u0570\u0561\u0575\u056f", + "\u057d\u0565\u0575\u0580\u0561\u0576", + "\u057b\u0578\u0580\u057b", + "\u057f\u056b\u0563\u0580\u0561\u0576", + "\u0561\u0577\u0578\u057f", + "\u057a\u0561\u0580\u0563\u0587", + "\u0583\u0561\u0576\u0578\u057d", + "\u057c\u0578\u0582\u0562\u0565\u0576", + "\u056d\u0578\u0580\u0565\u0576", + "\u0563\u0587\u0578\u0580\u0563", + "\u0561\u0580\u057f\u0578\u0582\u0580", + "\u0563\u0561\u056c\u0578\u0582\u057d\u057f", + "\u0564\u0578\u0574\u056b\u0576\u056b\u056f", + "\u0585\u0570\u0561\u0576", + "\u0561\u0566\u0561\u057f", + "\u0562\u0561\u0572\u0580\u0561\u0574", + "\u0565\u0580\u057e\u0561\u0576\u0564", + "\u0561\u0580\u0577\u0561\u056f", + "\u057f\u0580\u0564\u0561\u057f", + "\u0561\u0562\u056b\u0563", + "\u0570\u0565\u0576\u0580\u056b", + "\u0576\u0565\u0580\u057d\u0565\u057d", + "\u0563\u0561\u057c\u0576\u056b\u056f", + "\u0569\u0578\u0580\u0578\u057d", + "\u0577\u0574\u0561\u057e\u0578\u0576", + "\u0562\u0561\u0580\u056d\u0578\u0582\u0564\u0561\u0580", + "\u0576\u0578\u0580\u0561\u0575\u0580", + "\u0575\u0578\u0582\u0580\u056b", + "\u0574\u0561\u0584\u057d\u056b\u0574", + "\u057d\u0565\u0580\u0563\u0565\u0575", + "\u0570\u0578\u057e\u056b\u056f", + "\u0562\u0561\u0580\u057d\u0565\u0572", + "\u0561\u0580\u057f\u0565\u0574", + "\u0574\u0561\u0580\u056f\u0578\u057d", + "\u057d\u0561\u0580\u0563\u056b\u057d", + "\u056f\u0578\u0580\u0575\u0578\u0582\u0576", + "\u0570\u0578\u0582\u0576\u0561\u0576", + "\u0566\u0578\u0570\u0580\u0561\u0562", + "\u0561\u0562\u0580\u0561\u0570\u0561\u0574", + "\u0563\u0565\u0572\u0561\u0574", + "\u0577\u0561\u057e\u0561\u0580\u0577", + "\u057d\u0561\u0576\u0561\u057d\u0561\u0580", + "\u0562\u0561\u0572\u0564\u0561\u057d\u0561\u0580", + "\u0561\u0580\u0563\u056b\u0577\u057f\u056b", + "\u057d\u0561\u0572\u0561\u0569\u0565\u056c", + "\u0574\u056b\u0570\u0580\u0561\u0576", + "\u0580\u0561\u0586\u0586\u056b", + "\u0574\u0565\u057d\u0580\u0578\u057a", + "\u0561\u0580\u056b\u057d\u057f\u0561\u056f\u0565\u057d", + "\u0562\u0561\u0572\u056b\u0577", + "\u056f\u0561\u0580\u056c", + "\u0574\u0565\u056c\u0584\u0578\u0582\u0574", + "\u057e\u0561\u0570\u0580\u0561\u0574", + "\u0579\u0561\u0580\u056c\u056b", + "\u0574\u056d\u056b\u0569\u0561\u0580", + "\u0567\u0564\u0578\u0582\u0561\u0580\u0564", + "\u0569\u0561\u0564\u0587\u0578\u057d", + "\u0561\u057c\u0578\u0582\u0577\u0561\u0576", + "\u0562\u0561\u0563\u0580\u0561\u057f", + "\u057a\u0561\u057f\u057e\u0561\u056f\u0561\u0576", + "\u0584\u0580\u056b\u057d\u057f\u0578\u0586\u0565\u0580", + "\u0561\u057f\u0578\u0574", + "\u057c\u0561\u0586\u0561\u0575\u0565\u056c", + "\u0574\u0561\u0574\u056b\u056f\u0578\u0576", + "\u057e\u0561\u0580\u0578\u0582\u056a\u0561\u0576", + "\u0561\u0580\u0561\u0574\u0561\u0566\u0564", + "\u0569\u0578\u0580\u0563\u0578\u0574", + "\u0563\u0561\u0580\u0565\u0563\u056b\u0576", + "\u0566\u0561\u057e\u0565\u0576", + "\u0574\u0578\u0582\u0580\u0561\u0564", + "\u0574\u0570\u0565\u0580", + "\u057e\u0561\u0566\u0563\u0565\u0576", + "\u0564\u0561\u057e\u056b\u0569", + "\u057e\u0561\u056d\u0569\u0561\u0576\u0563", + "\u0574\u0561\u0580\u0563\u0561\u0580", + "\u0561\u0580\u0569\u0578\u0582\u0580", + "\u057d\u0561\u057d\u0578\u0582\u0576", + "\u0561\u057c\u0561\u0584\u0565\u056c", + "\u0563\u0561\u0562\u0580\u056b\u0565\u056c", + "\u057f\u0561\u0580\u0578\u0576", + "\u0562\u0561\u0562\u056f\u0565\u0576", + "\u0570\u0580\u0561\u0576\u057f", + "\u056c\u0587\u0578\u0576", + "\u0561\u056c\u0562\u0565\u0580\u057f", + "\u057e\u0561\u0572\u0561\u0580\u0577\u0561\u056f", + "\u0570\u0561\u0574\u0561\u0566\u0561\u057d\u057a", + "\u057c\u0578\u0582\u0564\u0578\u056c\u0586", + "\u057e\u0561\u0570\u0565", + "\u056f\u0561\u0580\u0565\u0576", + "\u0561\u0580\u057f\u0578\u0582\u0577", + "\u057a\u0565\u057f\u0580\u0578\u057d", + "\u056a\u056b\u0580\u0561\u0575\u0580", + "\u0586\u056b\u056c\u056b\u057a", + "\u057d\u0578\u0582\u0584\u056b\u0561\u057d", + "\u0561\u0580\u0577\u0561\u057e\u056b\u0580", + "\u056f\u056b\u0580\u0561\u056f\u0578\u057d", + "\u057e\u0561\u057d\u0561\u056f", + "\u0576\u0577\u0561\u0576", + "\u0574\u0565\u056d\u0561\u056f", + "\u0561\u056c\u0565\u0584\u057d\u0561\u0576\u0564\u0580", + "\u0576\u0578\u0582\u0562\u0561\u0580", + "\u0565\u0572\u056b\u0577", + "\u057c\u0578\u0574\u0561\u0576", + "\u0562\u0578\u0580\u056b\u057d", + "\u0561\u0580\u0563\u0561\u0574", + "\u057d\u0561\u0570\u0561\u056f", + "\u0562\u0565\u057c\u0576\u0561\u0580", + "\u0585\u056c\u0565\u0563", + "\u0569\u0561\u0569\u0578\u057d", + "\u0564\u0565\u0580\u0565\u0576\u056b\u056f", + "\u0561\u0580\u057f\u0561\u057e\u0561\u0566\u0564", + "\u0561\u0570\u0561\u0580\u0578\u0576", + "\u0578\u0582\u056b\u056c\u0575\u0561\u0574", + "\u057d\u057a\u0561\u0580\u057f\u0561\u056f" + ], + "FIRST_NAME": [ + "\u0574\u0561\u0580\u0563\u0561\u0580\u056b\u057f\u0561", + "\u0561\u057e\u0565\u057f\u056b\u057d", + "\u0586\u0565\u056c\u056b\u0584\u057d", + "\u057a\u0561\u0580\u0578\u0582\u0575\u0580", + "\u0567\u0580\u056b\u056f\u0561", + "\u0561\u0576\u056a\u0565\u056c\u0561", + "\u0561\u0580\u0574\u0565\u0576\u0561\u056f", + "\u0569\u0561\u0569\u0578\u0582\u056c", + "\u0562\u0565\u0569\u056b", + "\u0561\u0576\u0564\u0580\u0565\u0561\u057d", + "\u0563\u0561\u057d\u057a\u0561\u0580", + "\u0563\u0578\u0570\u0561\u0580", + "\u057c\u0578\u0562\u0565\u0580\u057f", + "\u0561\u0580\u0587\u056b\u056f", + "\u057e\u0561\u0570\u0561\u0576", + "\u0566\u0561\u0580\u0578\u0582\u0570\u056b", + "\u0574\u0561\u0576\u057e\u0565\u056c", + "\u0583\u0561\u0575\u056c\u0561\u056f", + "\u0561\u0576\u0564\u0580\u0561\u0576\u056b\u056f", + "\u0561\u056c\u057e\u0561\u0580\u0564", + "\u0561\u0580\u057d\u0565\u0576", + "\u0561\u0576\u0561\u0570\u056b\u057f", + "\u0570\u0561\u0580\u0578\u0582\u0569\u0575\u0578\u0582\u0576", + "\u0576\u0565\u056c\u056c\u056b", + "\u056c\u056b\u0566\u0561", + "\u0563\u0561\u0575\u0561\u0576\u0565", + "\u0561\u0580\u0561\u0574", + "\u0574\u0565\u0580\u056b", + "\u0563\u0575\u0578\u0582\u056c\u0576\u0561\u0580\u0561", + "\u057d\u0565\u0564\u0561", + "\u057c\u056b\u057f\u0561", + "\u057e\u0561\u0570\u0561\u0563\u0576", + "\u0570\u0561\u0575\u056f\u0578\u0582\u0570\u056b", + "\u057a\u0561\u0580\u0563\u0587", + "\u057f\u056b\u0563\u0580\u0561\u0576", + "\u056d\u0578\u0580\u0565\u0576", + "\u0561\u0574\u0561\u056c\u0575\u0561", + "\u0576\u0561\u0580\u056b\u0576\u0565", + "\u057d\u056b\u0580\u0561\u0580\u0583\u056b", + "\u0563\u0561\u056c\u0578\u0582\u057d\u057f", + "\u0574\u0561\u0576\u0565", + "\u0565\u0580\u057e\u0561\u0576\u0564", + "\u0561\u0580\u0577\u0561\u056f", + "\u0561\u0562\u056b\u0563", + "\u0576\u0565\u0580\u057d\u0565\u057d", + "\u0574\u056b\u056c\u0565\u0576\u0561", + "\u0569\u0578\u0580\u0578\u057d", + "\u0561\u0580\u0583\u056b\u0576\u0565", + "\u0576\u0561\u056b\u0580\u0561", + "\u0576\u0561\u0576\u0561", + "\u057d\u0561\u0580\u0563\u056b\u057d", + "\u056f\u0578\u0580\u0575\u0578\u0582\u0576", + "\u0570\u0578\u0582\u0576\u0561\u0576", + "\u0563\u0565\u0572\u0561\u0574", + "\u0577\u0561\u057e\u0561\u0580\u0577", + "\u057d\u0561\u0576\u0561\u057d\u0561\u0580", + "\u0586\u0580\u056b\u0564\u0561", + "\u0562\u0565\u056c\u056c\u0561", + "\u0574\u0565\u057d\u0580\u0578\u057a", + "\u0574\u0565\u056c\u0584\u0578\u0582\u0574", + "\u057c\u0561\u056b\u057d\u0561", + "\u056c\u0578\u0582\u056b\u0566\u0561", + "\u0567\u0564\u0578\u0582\u0561\u0580\u0564", + "\u0584\u0580\u056b\u057d\u057f\u0578\u0586\u0565\u0580", + "\u0574\u0565\u056c\u0561\u0576\u0575\u0561", + "\u0562\u0561\u0563\u0580\u0561\u057f", + "\u0561\u056b\u0564\u0561", + "\u0561\u057f\u0578\u0574", + "\u0569\u0565\u0570\u0574\u056b\u0576\u0565", + "\u056c\u0561\u0578\u0582\u0580\u0561", + "\u0576\u0561\u057f\u0561\u0577\u0561", + "\u0574\u0561\u0580\u056b\u0561\u0576\u0576\u0561", + "\u0574\u0578\u0576\u056b\u056f\u0561", + "\u0561\u0563\u0561\u057a\u056b", + "\u057c\u0565\u0562\u0565\u056f\u0561", + "\u056c\u0587\u0578\u0576", + "\u0576\u0578\u0576\u0576\u0561", + "\u056c\u0565\u0575\u056c\u0561", + "\u0561\u0580\u057f\u0578\u0582\u0577", + "\u056f\u0561\u0580\u0565\u0576", + "\u056c\u056b\u0564\u0561", + "\u057b\u0565\u0575\u0576", + "\u057a\u0565\u057f\u0580\u0578\u057d", + "\u057a\u0561\u057f\u0580\u056b\u057d\u056b\u0561", + "\u056f\u056b\u0580\u0561\u056f\u0578\u057d", + "\u057e\u0561\u057d\u0561\u056f", + "\u0576\u0577\u0561\u0576", + "\u0561\u0576\u0561\u057d\u057f\u0561\u057d\u056b\u0561", + "\u0565\u0572\u056b\u0577", + "\u0584\u0576\u0561\u0580\u056b\u056f", + "\u057d\u0575\u0578\u0582\u0566\u0561\u0576\u0576\u0561", + "\u057d\u0561\u0570\u0561\u056f", + "\u0585\u056c\u0565\u0563", + "\u0569\u0561\u0569\u0578\u057d", + "\u057c\u056b\u0574\u0561", + "\u0561\u056c\u056b\u057d\u0561", + "\u0565\u0580\u0561\u0576\u0578\u0582\u0570\u056b", + "\u0570\u0578\u0582\u057d\u056b\u056f", + "\u0561\u0580\u057f\u0561\u0577\u0565\u057d", + "\u0565\u057e\u0561", + "\u0574\u0561\u0580\u056b\u0576\u0565", + "\u0561\u0580\u057f\u0561\u056f", + "\u0562\u0580\u056b\u057b\u056b\u057f", + "\u056a\u0561\u0576\u0576\u0561", + "\u0569\u056b\u0576\u0561", + "\u056b\u0576\u0565\u057d\u0561", + "\u057d\u057f\u0565\u0586\u0561\u0576", + "\u0561\u0580\u0574\u0561\u0576", + "\u0576\u0561\u0580\u0565\u056f", + "\u0584\u056b\u0574", + "\u0570\u0578\u057e\u0570\u0561\u0576\u0576\u0565\u057d", + "\u057a\u0578\u0572\u0578\u057d", + "\u0574\u0561\u0580\u056b\u0561", + "\u057e\u056b\u056f\u057f\u0578\u0580", + "\u056c\u056b\u0561\u0576\u0561", + "\u057b\u0578\u0582\u056c\u056b\u0565\u057f\u0561", + "\u057c\u056b\u0579\u0561\u0580\u0564", + "\u0570\u0561\u057d\u0574\u056b\u056f", + "\u0561\u0576\u056b", + "\u0567\u057e\u0565\u056c\u056b\u0576\u0561", + "\u0570\u0561\u0575\u056f\u0561\u0566", + "\u0563\u0580\u056b\u0563\u0578\u0580", + "\u057b\u056b\u057e\u0561\u0576", + "\u056b\u0576\u0563\u0561", + "\u0570\u0561\u0575\u056f", + "\u0563\u0561\u0580\u0580\u056b", + "\u0561\u056c\u0565\u0584\u057d\u0561\u0576\u0564\u0580\u0561", + "\u057d\u057e\u0565\u057f\u056c\u0561\u0576\u0561", + "\u057c\u0578\u0582\u0562\u0565\u0576", + "\u0564\u0578\u0574\u056b\u0576\u056b\u056f", + "\u0576\u0578\u0582\u0576\u0565", + "\u0562\u0561\u0572\u0580\u0561\u0574", + "\u057d\u0561\u057c\u0561", + "\u057d\u0565\u0580\u0563\u0565\u0575", + "\u0585\u0586\u0565\u056c\u0575\u0561", + "\u0562\u0561\u0580\u0562\u0561\u0580\u0561", + "\u0576\u056b\u0576\u0561", + "\u0576\u0561\u0580\u0565", + "\u0574\u056b\u0570\u0580\u0561\u0576", + "\u0580\u0561\u0586\u0586\u056b", + "\u0562\u0561\u0572\u056b\u0577", + "\u0574\u056d\u056b\u0569\u0561\u0580", + "\u057a\u0561\u057f\u057e\u0561\u056f\u0561\u0576", + "\u0563\u0561\u0562\u0580\u056b\u0565\u056c\u056c\u0561", + "\u0574\u0561\u0574\u056b\u056f\u0578\u0576", + "\u056c\u056b\u056c\u056b\u0569", + "\u0561\u0580\u0561\u0574\u0561\u0566\u0564", + "\u056f\u056b\u0580\u0561", + "\u0569\u0578\u0580\u0563\u0578\u0574", + "\u0563\u0561\u0580\u0565\u0563\u056b\u0576", + "\u057d\u0561\u0569\u0565\u0576\u056b\u056f", + "\u0574\u0570\u0565\u0580", + "\u0564\u0561\u057e\u056b\u0569", + 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+ "\u0561\u0580\u0565\u0563", + "\u0561\u0577\u0578\u057f", + "\u0583\u0561\u0576\u0578\u057d", + "\u0563\u0587\u0578\u0580\u0563", + "\u0561\u0576\u056b\u057f\u0561", + "\u0565\u057e\u0563\u056b\u0576\u0565", + "\u0584\u0580\u056b\u057d\u057f\u056b\u0576\u0565", + "\u056f\u0561\u0580\u056b\u0576\u0565", + "\u0561\u0566\u0561\u057f", + "\u0567\u0574\u056b\u056c\u056b\u0561", + "\u0576\u0578\u0580\u0561", + "\u0570\u0565\u0576\u0580\u056b", + "\u056c\u0561\u056c\u0561", + "\u057d\u057f\u0565\u056c\u056c\u0561", + "\u0574\u0561\u0584\u057d\u056b\u0574", + "\u0586\u056c\u0578\u0580\u0561", + "\u0561\u0580\u057f\u0565\u0574", + "\u0574\u0561\u0580\u056f\u0578\u057d", + "\u0561\u0562\u0580\u0561\u0570\u0561\u0574", + "\u057d\u0565\u057d\u056b\u056c\u056b\u0561", + "\u057d\u0561\u0572\u0561\u0569\u0565\u056c", + "\u057e\u056b\u056f\u057f\u0578\u0580\u0575\u0561", + "\u057e\u0561\u0570\u0580\u0561\u0574", + "\u0579\u0561\u0580\u056c\u056b", + "\u0569\u0561\u0564\u0587\u0578\u057d", + 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"\u0574\u0578\u0582\u0577\u0565\u0572", + "\u057d\u0574\u0562\u0561\u057f", + "\u056b\u0580\u056b\u0576\u0561", + "\u0561\u0564\u0561\u0574", + "\u0563\u0578\u0582\u0580\u0563\u0565\u0576", + "\u0574\u0561\u0580\u0569\u0561", + "\u0563\u0580\u0565\u057f\u0561", + "\u0563\u0578\u057c", + "\u057d\u0578\u0586\u0575\u0561", + "\u0561\u056c\u056c\u0561", + "\u057d\u056b\u0574\u0578\u0576", + "\u0577\u0578\u0582\u0577\u0561\u0576\u056b\u056f", + "\u0581\u0578\u056c\u0561\u056f", + "\u0569\u0565\u0580\u0565\u0566\u0561", + "\u0577\u0561\u0570\u0565\u0576", + "\u056f\u056c\u0561\u0580\u0561", + "\u057d\u0565\u0580\u0578\u0562", + "\u0561\u0576\u0563\u0565\u056c\u056b\u0576\u0561", + "\u0566\u0578\u0570\u0580\u0561\u057a", + "\u057e\u0565\u0580\u0578\u0576\u056b\u056f\u0561", + "\u057e\u056c\u0561\u0564\u056b\u0574\u056b\u0580", + "\u0570\u0565\u0580\u0574\u056b\u0576\u0565", + "\u056f\u056c\u0578\u0564", + "\u057a\u0561\u0580\u0569\u0587", + "\u0570\u0561\u056f\u0578\u0562", + "\u057d\u056b\u056c\u057e\u0561", + "\u0569\u0561\u0563\u0578\u0582\u0570\u056b", + "\u0561\u0580\u0574\u0565\u0576\u0578\u0582\u0570\u056b", + "\u056d\u0578\u057d\u0580\u0578\u057e", + "\u0574\u0565\u056c\u056b\u0576\u0565", + "\u0564\u0561\u0576\u056b\u0565\u056c", + "\u0562\u0580\u056b\u056a\u056b\u057f", + "\u057d\u0565\u0575\u0580\u0561\u0576", + "\u057b\u0578\u0580\u057b", + "\u0561\u0580\u057f\u0578\u0582\u0580", + "\u056c\u0561\u057c\u0561", + "\u0585\u0570\u0561\u0576", + "\u057f\u0580\u0564\u0561\u057f", + "\u0567\u056c\u056b\u0576\u0561", + "\u0563\u0561\u057c\u0576\u056b\u056f", + "\u056e\u0578\u057e\u056b\u0576\u0561\u0580", + "\u0577\u0574\u0561\u057e\u0578\u0576", + "\u0562\u0561\u0580\u056d\u0578\u0582\u0564\u0561\u0580", + "\u0576\u0578\u0580\u0561\u0575\u0580", + "\u0575\u0578\u0582\u0580\u056b", + "\u0570\u0578\u057e\u056b\u056f", + "\u0562\u0561\u0580\u057d\u0565\u0572", + "\u0566\u0578\u0570\u0580\u0561\u0562", + "\u0562\u0561\u0572\u0564\u0561\u057d\u0561\u0580", + "\u0561\u0580\u0563\u056b\u0577\u057f\u056b", + "\u0561\u0580\u056b\u057d\u057f\u0561\u056f\u0565\u057d", + "\u056f\u0561\u0580\u056c", + "\u0561\u056c\u056b\u0576\u0561", + "\u057b\u0565\u0574\u0574\u0561", + "\u0561\u057c\u0578\u0582\u0577\u0561\u0576", + "\u057c\u0561\u0586\u0561\u0575\u0565\u056c", + "\u057e\u0561\u0580\u0578\u0582\u056a\u0561\u0576", + "\u056c\u0578\u0582\u057d\u056b\u0576\u0565", + "\u057e\u0561\u0566\u0563\u0565\u0576", + "\u0561\u0580\u0569\u0578\u0582\u0580", + "\u057d\u0561\u057d\u0578\u0582\u0576", + "\u0561\u0580\u0561\u0584\u057d\u0575\u0561", + "\u0561\u0576\u057f\u0578\u0576\u056b\u0576\u0561", + "\u057f\u0561\u0580\u0578\u0576", + "\u0570\u056b\u056c\u0564\u0561", + "\u057e\u0561\u0572\u0561\u0580\u0577\u0561\u056f", + "\u0561\u0576\u0576\u0561", + "\u057e\u0561\u0570\u0565", + "\u056a\u056b\u0580\u0561\u0575\u0580", + "\u0586\u056b\u056c\u056b\u057a", + "\u0577\u0561\u0570\u0561\u0576\u0565", + "\u0576\u0578\u0582\u0562\u0561\u0580", + "\u0562\u0565\u057c\u0576\u0561\u0580", + "\u0561\u0580\u057f\u0561\u057e\u0561\u0566\u0564", + "\u057d\u0578\u0582\u057d\u0561\u0576\u0576\u0561", + "\u056a\u0561\u0584\u056c\u056b\u0576" + ], + "LAST_NAME": [ + "\u0561\u0566\u0563\u0561\u056c\u0564\u0575\u0561\u0576", + "\u0564\u0578\u0582\u0566\u0573\u0561\u056f\u0561\u057f\u0579\u0575\u0561\u0576", + "\u0561\u0566\u0561\u0580\u0575\u0561\u0576", + "\u0583\u0561\u0574\u0562\u0578\u0582\u056f\u0579\u0575\u0561\u0576", + "\u0561\u0566\u0561\u057f\u0575\u0561\u0576\u0581", + "\u056f\u0561\u0580\u0573\u056b\u056f\u0575\u0561\u0576", + "\u0577\u0561\u0580\u0561\u0562\u056d\u0561\u0576\u0575\u0561\u0576", + "\u0574\u057d\u0561\u0563\u0578\u0580\u056e\u0575\u0561\u0576", + "\u0561\u0576\u0578\u0583\u0575\u0561\u0576", + "\u0570\u0578\u057e\u056b\u057e\u0575\u0561\u0576", + "\u0564\u0578\u056d\u0578\u056c\u0575\u0561\u0576", + "\u0561\u0566\u056b\u056c\u0561\u0566\u0575\u0561\u0576", + 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b/data_tooling/pii_processing/ontology/data/ia.json @@ -0,0 +1,319 @@ +{ + "JOB": [ + "collector", + "planator", + "compositor", + "pretor", + "episcopo", + "pharmaceutico", + "romancero", + "fermero", + "inseniator", + "interne", + "jocator", + "the_guardian", + "marechal", + "internista", + "parlator", + "burgomaestro", + "chairman" + ], + "PLANT": [ + "tremulo", + "ceresia", + "urtica", + "salice" + ], + "DISEASE": [ + "arthritis", + "rabies", + "maladia", + "parvo", + "appendicitis", + "chi", + "pollinosis", + "sternutar", + "mi", + "tan", + "dengue", + "le", + "malaria" + ], + "PUBLIC_FIGURE": [ + "che_guevara", + "c", + "winston_churchill", + "le_parve_lord", + "isaac_newton", + "victor_hugo", + "aristarcho", + "maximiano", + "richard_wagner", + "marie_curie", + "michael_jackson", + "el_greco", + "galileo_galilei", + "jane_goodall", + "edmund_hillary", + "vincent_van_gogh", + "josef_stalin", + "robert_burns", + "karl_barth", + "marco_aurelio", + "jesus", + "giuseppe_verdi", + "e", + "henri_matisse", + "don_quixote_de_la_mancha", + "sarah_bernhardt", + "dante_alighieri", + "sperar", + "giacomo_puccini", + "oscar_wilde", + "henry", + "sperantia", + "a", + "charles_baudelaire", + "immanuel_kant", + "weber", + "max_planck", + "william_blake", + "edward_jenner", + "niels_bohr", + "michael_faraday", + "walt_disney", + "benny_goodman", + "moses", + "indira_gandhi", + "alfred_nobel", + "marco_polo", + "m", + "allen_ginsberg", + "guillaume_apollinaire", + "hans_christian_andersen", + "pablo_picasso", + "o", + "karl_marx", + "friedrich_nietzsche", + "nikola_tesla", + "le_corbusier", + "jean_piaget", + "adolf_hitler", + "joseph_haydn", + "garfield", + "paul_revere", + "edvard_grieg", + "1", + "hertz", + "louis_armstrong", + "st_louis_missouri", + "johann_gutenberg", + "thomas_malthus", + "william_faulkner", + "christophoro_columbo", + "peter_paul_rubens", + "mahatma_gandhi", + "jules_verne", + "charlie_chaplin", + "ronald_reagan", + "homo", + "wilhelm_reich", + "william_wordsworth", + "ernest_hemingway", + "aquila", + "nelson_mandela", + "roald_amundsen", + "charles_dickens", + "jacques_offenbach", + "sancte_martin", + "francisco_franco", + "vladimir_lenin", + "albert_einstein", + "wilhelm_ostwald" + ], + "RELIGION_MEMBER": [ + "christiano" + ], + "PRODUCT": [ + "justin_bieber", + "astrostation", + "derectos_human", + "spirito_sancte", + "saxonia_anhalt", + "patrenostre", + "le_senior_del_anellos" + ], + "RELIGION": [ + "zen", + "presbyterianismo", + "manicheismo", + "islam", + "methodismo", + "calvinismo", + "wicca" + ], + "ORG": [ + "wicca", + "nasa", + "a_basso", + "schutzstaffel", + "san_francisco", + "un", + "partito_nazi", + "assemblea_national_del_republica_azerbaijan", + "taoismo", + "statos_unite", + "laco_superior", + "assumption_de_maria", + "io_vos_adora", + "los_angeles", + "io_te_adora", + "mi", + "schola", + "judices" + ], + "RACE": [ + "latino", + "latin", + "chinese" + ], + "DATE": [ + "medievo", + "era_commun" + ], + "LOCATION": [ + "mar_del_nord", + "mar_nigre", + "christophoro_columbo", + "sri_lanka" + ], + "GENDER": [ + "puera", + "senioretta", + "transgenere", + "mascule" + ], + "ANIMAL": [ + "lynce", + "mammal", + "scuriolo", + "millepedes", + "myriapodo", + "catto", + "grypho", + "arthropodo", + "donald_duck", + "catta", + "alsi" + ], + "PERSON": [ + "est_sud_est", + "autocontrolo", + "herbert_george_wells" + ], + "FAC": [ + "imperio_ottoman", + "ecclesia_catholic" + ], + "LANGUAGE": [ + "russa", + "arabic", + "catalano", + "german", + "chinese", + "esperanto", + "hungare", + "polac", + "portugese", + "ido", + "quechua", + "tonga" + ], + "FOOD": [ + "farina", + "gelato", + "chile", + "jentaculo", + "omelette", + "prandio" + ], + "QUANTITY": [ + "dollar", + "anders_celsius" + ], + "PERSON_PRONOUN": [ + "me_ipse", + "me" + ], + "TITLE": [ + "seniora" + ], + "GPE": [ + "nove_testamento", + "san_pietro_apostolo", + "vinh_long" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "abbatessa": "abba", + "sposa": "sponso", + "femina": "esser_human", + "feminin": "mascule", + "granfilia": "nepote", + "soror": "german", + "monacha": "monacho", + "sponsa": "sposo", + "uxor": "sposo", + "garson": "puera", + "puero": "puera" + }, + "other_gender_swap": { + "ille": "illes" + }, + "en_pronoun2gender": { + "they": [ + "homosexual", + "bisexual", + "transgenere" + ], + "he": [ + "mascule", + "homine", + "esser_human", + "puero", + "garson" + ], + "she": [ + "puera", + "senioretta", + "femina", + "feminin" + ] + }, + "en_pronoun2pronoun": { + "he": [ + "ille" + ], + "they": [ + "illas", + "illos", + "illes" + ], + "it": [ + "essa", + "isto", + "illo" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/id.json b/data_tooling/pii_processing/ontology/data/id.json new file mode 100644 index 0000000..c2e400b --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/id.json @@ -0,0 +1,1714 @@ +{ + "ner_regexes": [ + [ + "PERSON", + "\\D+ \\D+|\\D+ \\D+|\\D+ \\D+|\\D+ \\D+|\\D+ \\D+|\\D+ \\D+|\\D+ \\D+|\\D+ \\D+|\\D+ \\D+ \\D+|\\D+ \\D+ \\D+|\\D+ \\D+, \\D+|\\D+ \\D+, \\D+|\\D+ \\D+ \\D+, \\D+|\\D+ \\D+ \\D+, \\D+", + false, + [] + ] + ], + "FIRST_NAME_FEMALE": [ + "maida", + "dinda", + "rini", + "gabriella", + "ratih", + "anastasia", + "hasna", + "elma", + "belinda", + "elvina", + "mila", + "icha", + "febi", + "qori", + "lili", + "janet", + "cornelia", + "gilda", + "vicky", + "endah", + "vanesa", + "salwa", + "zaenab", + "ifa", + "sadina", + "salimah", + "bella", + "zizi", + "olivia", + "halima", + "salsabila", + "melinda", + "mutia", + "vivi", + "aisyah", + "ilsa", + "oliva", + "pia", + "maria", + "jelita", + "sabrina", + "zahra", + "intan", + "wani", + "ophelia", + "cinthia", + "jamalia", + "juli", + "genta", + "nilam", + "oni", + "zamira", + "jasmin", + "gina", + "winda", + "diana", + "wulan", + "elisa", + "kiandra", + "wirda", + "widya", + "sari", + "latika", + "chelsea", + "victoria", + "faizah", + "septi", + "paulin", + "eva", + "rachel", + "lidya", + "yessi", + "aurora", + "ira", + "yani", + "cinta", + "anita", + "queen", + "kayla", + "nabila", + "carla", + "ika", + "ulya", + "rahayu", + "uli", + "raina", + "padma", + "tira", + "fathonah", + "rahmi", + "puput", + "siska", + "zulaikha", + "dian", + "hamima", + "unjani", + "amalia", + "agnes", + "shania", + "ina", + "kamaria", + "novi", + "padmi", + "ella", + "restu", + "putri", + "zulfa", + "tari", + "humaira", + "lalita", + "indah", + "hafshah", + "ida", + "shakila", + "titi", + "zelda", + "dewi", + "samiah", + "fitria", + "amelia", + "sakura", + "silvia", + "lintang", + "jessica", + "safina", + "maya", + "ana", + "ratna", + "tania", + "kezia", + "hesti", + "michelle", + "julia", + "sarah", + "ade", + "titin", + "malika", + "siti", + "hilda", + "umi", + "mala", + "yance", + "gawati", + "jane", + "laras", + "syahrini", + "alika", + "betania", + "hana", + "paris", + "violet", + "ciaobella", + "devi", + "kartika", + "natalia", + "ulva", + "dina", + "puji", + "cici", + "eli", + "tantri", + "puti", + "usyi", + "rina", + "keisha", + "talia", + "laila", + "dalima", + "lala", + "irma", + "najwa", + "ajeng", + "gasti", + "cindy", + "nadine", + "almira", + "yulia", + "yunita", + "fitriani", + "yuliana", + "yuni", + "vera", + "paramita", + "maimunah", + "tina", + "rika", + "iriana", + "raisa", + "vanya", + "suci", + "zalindra", + "ghaliyati", + "karen", + "eka", + "hani", + "uchita", + "kania", + "tiara", + "patricia", + "kasiyah", + "karimah", + "zelaya", + "nadia", + "citra", + "kani", + "tami", + "diah", + "calista", + "ami", + "nurul", + "ellis", + "nova", + "ani", + "puspa", + "ayu", + "farah", + "clara", + "kamila", + "farhunnisa", + "azalea" + ], + "FIRST_NAME_MALE": [ + "hari", + "kanda", + "kamidin", + "karman", + "makuta", + "marwata", + "bagya", + "wira", + "bakda", + "indra", + "luis", + "halim", + "kenari", + "dasa", + "cakrajiya", + "balamantri", + "wisnu", + "balangga", + "cakrawangsa", + "bala", + "abyasa", + "caturangga", + "catur", + "nasim", + "balapati", + "nyoman", + "darmana", + "vega", + "dimas", + "martani", + "hairyanto", + "marsudi", + "pardi", + "jamal", + "niyaga", + "dwi", + "luluh", + "hasta", + "jayadi", + "karsa", + "jaeman", + "waluyo", + "sidiq", + "garan", + "lantar", + "emas", + "ismail", + "cahyono", + "karta", + "jarwadi", + "nyana", + "uda", + "lanang", + "dimaz", + "umar", + "eko", + "kurnia", + "warta", + "imam", + "cahyadi", + "makara", + "gangsa", + "darman", + "soleh", + "kasiran", + "maryadi", + "bakijan", + "aswani", + "gatot", + "cengkir", + "rizki", + "ibrahim", + "damar", + "jaya", + "cawuk", + "harto", + "agus", + "gaduh", + "tedi", + "cager", + "bambang", + "tasdik", + "cawisono", + "mariadi", + "daru", + "kambali", + "jatmiko", + "mulyanto", + "arsipatra", + "dacin", + "estiawan", + "pranawa", + "aris", + "langgeng", + "artawan", + "simon", + "harsana", + "saka", + "hasan", + "najib", + "rudi", + "jaswadi", + "carub", + "enteng", + "luwar", + "hartana", + "bakidin", + "asman", + "ajiono", + "ibun", + "cemani", + "caraka", + "caket", + "galur", + "kayun", + "unggul", + "warsa", + "purwadi", + "bakiman", + "daruna", + "wage", + "eman", + "yoga", + "endra", + "vino", + "teddy", + "bakti", + "ajiman", + "ikhsan", + "gandi", + "jaga", + "gangsar", + "mursinin", + "drajat", + "heryanto", + "opan", + "banara", + "olga", + "baktiadi", + "jasmani", + "pangestu", + "luhung", + "mulya", + "jindra", + "mustofa", + "kariman", + "upik", + "joko", + "dalimin", + "cemeti", + "rama", + "prabu", + "galak", + "bahuwirya", + "daniswara", + "lega", + "tri", + "kamal", + "ghani", + "emong", + "wardaya", + "raditya", + "kuncara", + "gamblang", + "prayoga", + "limar", + "atmaja", + "gara", + "asmadi", + "edi", + "emin", + "prakosa", + "dariati", + "cakrabirawa", + "mahesa", + "irnanto", + "rahmat", + "karja", + "jaka", + "lurhur", + "viman", + "prayitna", + "bakianto", + "mahfud", + "hardana", + "nardi", + "liman", + "saadat", + "ridwan", + "hardi", + "budi", + "prabowo", + "bagiya", + "ikin", + "luwes", + "jati", + "lembah", + "edison", + "jarwi", + "pangeran", + "pandu", + "nalar", + "banawa", + "among", + "cecep", + "johan", + "ade", + "cakrawala", + "taswir", + "utama", + "darsirah", + "taufan", + "maman", + "rusman", + "jinawi", + "viktor", + "reksa", + "rangga", + "dartono", + "wadi", + "galih", + "cawisadi", + "lanjar", + "koko", + "harjaya", + "kadir", + "rahman", + "virman", + "cakrabuana", + "galiono", + "anggabaya", + "maras", + "dirja", + "usman", + "parman", + "kemba", + "lasmanto", + "setya", + "ajimin", + "umay", + "omar", + "harjasa", + "sabri", + "ganep", + "karna", + "kenes", + "digdaya", + "maryanto", + "asmianto", + "teguh", + "ihsan", + "irsad", + "nugraha", + "purwanto", + "mahmud", + "salman", + "nasrullah", + "anom", + "kasusra", + "hartaka", + "alambana", + "wakiman", + "ganda", + "warsita", + "gilang", + "yono", + "prabawa", + "vinsen", + "sakti", + "slamet", + "galang", + "balijan", + "ian", + "bahuwarna", + "wawan", + "purwa", + "mustika", + "bancar", + "darmanto", + "bakiono", + "tugiman", + "wahyu", + "reza", + "karma", + "rosman", + "tomi", + "surya", + "malik", + "emil", + "mulyono", + "gamanto", + "cemplunk", + "irwan", + "gaiman", + "ega", + "yusuf", + "martana", + "yahya", + "gatra", + "daryani", + "kala", + "hamzah", + "labuh", + "timbul", + "rendy", + "bahuraksa", + "jail", + "darimin", + "latif", + "kalim", + "opung", + "bagas", + "sabar", + "leo", + "dipa", + "jais", + "xanana", + "rafi", + "gandewa", + "tasnim", + "dono", + "taufik", + "oskar", + "estiono", + "naradi", + "lulut", + "wardi", + "cahya", + "luthfi", + "gambira", + "banawi", + "tirtayasa", + "mumpuni", + "kawaya", + "atma", + "jaiman", + "ibrani", + "kenzie", + "baktianto", + "kasim", + "najam", + "asirwada", + "ganjaran", + "marsito", + "garang", + "nrima", + "praba", + "karya", + "warji", + "gada", + "gading", + "adika", + "ivan", + "erik", + "damu", + "eka", + "jarwa", + "margana", + "jagapati", + "lukman", + "gantar", + "galar", + "saiful", + "harimurti", + "harjo", + "cengkal", + "prima", + "kawaca", + "jumadi", + "danang", + "prasetyo", + "umaya", + "muni", + "capa", + "aslijan", + "heru", + "danuja", + "daliono", + "hadi", + "bakiadi", + "paiman", + "jono", + "argono", + "eja", + "harja", + "jagaraga", + "kusuma", + "elon", + "cayadi", + "raihan", + "okta", + "kairav", + "asmuni", + "gadang", + "kemal", + "dadap", + "nasab", + "narji", + "darmaji", + "radika", + "galuh", + "darijan", + "elvin", + "eluh", + "jayeng", + "perkasa", + "adiarja", + "lasmono", + "oman", + "samsul", + "kacung", + "mursita", + "radit", + "adinata", + "hendri", + "laksana", + "kardi", + "respati", + "jumari", + "candra", + "adikara", + "martaka", + "candrakanta", + "gaman", + "mahdi", + "okto", + "artanto", + "mujur", + "pranata", + "putu", + "panca", + "jamil", + "dodo", + "harsaya", + "daliman", + "jefri", + "cagak", + "manah", + "prasetya", + "baktiono", + "balidin", + "hendra", + "hasim", + "jabal", + "edward", + "lutfan", + "bajragin", + "satya", + "wasis", + "embuh", + "chandra", + "ajimat", + "danu", + "aditya", + "irfan", + "muhammad", + "ilyas", + "ozy", + "vero", + "dadi", + "kunthara", + "yosef", + "karsana", + "raden", + "cahyanto", + "raharja", + "garda", + "akarsana", + "gamani", + "prayogo", + "rafid", + "cahyo", + "himawan", + "laswi", + "murti", + "tirta", + "asirwanda", + "empluk", + "adhiarja", + "panji", + "lukita", + "mitra", + "bagus", + "dagel", + "lamar", + "kajen", + "legawa", + "arta", + "harsanto" + ], + "LAST_NAMES_FEMALE": [ + "Agustina", + "Laksita", + "Maryati", + "Nurdiyanti", + "Riyanti", + "Wulandari", + "Fujiati", + "Susanti", + "Astuti", + "Namaga", + "Mardhiyah", + "Melani", + "Wastuti", + "Winarsih", + "Novitasari", + "Mandasari", + "Pratiwi", + "Nasyidah", + "Utami", + "Padmasari", + "Nuraini", + "Aryani", + "Mayasari", + "Hasanah", + "Puspita", + "Mulyani", + "Permata", + "Prastuti", + "Sudiati", + "Kusmawati", + "Yuniar", + "Puspasari", + "Hassanah", + "Laksmiwati", + "Palastri", + "Handayani", + "Haryanti", + "Usada", + "Oktaviani", + "Usamah", + "Suartini", + "Hartati", + "Pudjiastuti", + "Anggraini", + "Rahmawati", + "Hastuti", + "Wahyuni", + "Andriani", + "Zulaika", + "Purwanti", + "Rahimah", + "Yulianti", + "Yolanda", + "Farida", + "Safitri", + "Uyainah", + "Halimah", + "Yuliarti", + "Purnawati", + "Lestari", + "Nasyiah", + "Suryatmi", + "Hariyah", + "Pertiwi", + "Lailasari", + "Widiastuti", + "Rahayu", + "Kuswandari", + "Wijayanti" + ], + "PREFIX_FEMALE": [ + "drg", + "r", + "hj", + "tgk", + "dr", + "r.a", + "ir", + "drs", + "puti", + "cut" + ], + "PREFIX_MALE": [ + "t", + "drg", + "h", + "kh", + "r", + "r.m", + "sutan", + "tgk", + "dr", + "ir", + "drs", + "dt" + ], + "FIRST_NAME": [ + "hari", + "kanda", + "kamidin", + "karman", + "makuta", + "marwata", + "mila", + "bagya", + "wira", + "janet", + "bakda", + "indra", + "luis", + "halim", + "kenari", + "dasa", + "cornelia", + "cakrajiya", + "balamantri", + "zaenab", + "wisnu", + "balangga", + "salimah", + "cakrawangsa", + "bala", + "abyasa", + "caturangga", + "catur", + "nasim", + "balapati", + "nyoman", + "vivi", + "mutia", + "ilsa", + "darmana", + "vega", + "dimas", + "oliva", + "maria", + "martani", + "hairyanto", + "marsudi", + "wani", + "pardi", + "jamal", + "niyaga", + "jamalia", + "nilam", + "dwi", + "luluh", + "hasta", + "jayadi", + "winda", + "karsa", + "jaeman", + "kiandra", + "waluyo", + "widya", + "sidiq", + "garan", + "lantar", + "emas", + "eva", + "ismail", + "aurora", + "cahyono", + "karta", + "jarwadi", + "nyana", + "uda", + "kayla", + "lanang", + "dimaz", + "ulya", + "rahayu", + "uli", + "umar", + "eko", + "kurnia", + "warta", + "imam", + "fathonah", + "cahyadi", + "makara", + "gangsa", + "darman", + "soleh", + "kasiran", + "maryadi", + "shania", + "bakijan", + "aswani", + "zulfa", + "gatot", + "cengkir", + "rizki", + "ibrahim", + "tari", + "damar", + "hafshah", + "shakila", + "jaya", + "cawuk", + "harto", + "agus", + "gaduh", + "tedi", + "ana", + "cager", + "bambang", + "michelle", + "julia", + "tasdik", + "cawisono", + "mariadi", + "daru", + "mala", + "gawati", + "kambali", + "jatmiko", + "syahrini", + "mulyanto", + "arsipatra", + "dacin", + "estiawan", + "pranawa", + "devi", + "violet", + "aris", + "langgeng", + "artawan", + "simon", + "puji", + "harsana", + "saka", + "usyi", + "hasan", + "najib", + "rudi", + "jaswadi", + "irma", + "carub", + "enteng", + "luwar", + "hartana", + "bakidin", + "asman", + "ajiono", + "ibun", + "cemani", + "yulia", + "caraka", + "caket", + "vanya", + "galur", + "kayun", + "unggul", + "warsa", + "purwadi", + "patricia", + "bakiman", + "daruna", + "wage", + "tami", + "eman", + "yoga", + "endra", + "vino", + "teddy", + "bakti", + "ajiman", + "farah", + "ikhsan", + "gandi", + "jaga", + "azalea", + "gangsar", + "mursinin", + "drajat", + "rini", + "ratih", + "anastasia", + "belinda", + "heryanto", + "icha", + "febi", + "lili", + "opan", + "qori", + "banara", + "olga", + "baktiadi", + "jasmani", + "pangestu", + "luhung", + "mulya", + "vanesa", + "jindra", + "salwa", + "mustofa", + "ifa", + "kariman", + "upik", + "joko", + "dalimin", + "cemeti", + "rama", + "prabu", + "galak", + "bahuwirya", + "daniswara", + "lega", + "tri", + "kamal", + "ghani", + "emong", + "wardaya", + "raditya", + "genta", + "oni", + "kuncara", + "gamblang", + "prayoga", + "limar", + "wulan", + "elisa", + "atmaja", + "gara", + "asmadi", + "edi", + "emin", + "prakosa", + "chelsea", + "dariati", + "victoria", + "cakrabirawa", + "septi", + "mahesa", + "irnanto", + "paulin", + "rahmat", + "karja", + "rachel", + "jaka", + "lurhur", + "viman", + "prayitna", + "yani", + "bakianto", + "mahfud", + "hardana", + "nardi", + "nabila", + "liman", + "raina", + "saadat", + "padma", + "tira", + "ridwan", + "hardi", + "rahmi", + "puput", + "budi", + "prabowo", + "siska", + "dian", + "unjani", + "bagiya", + "amalia", + "ikin", + "luwes", + "jati", + "padmi", + "ella", + "restu", + "lembah", + "putri", + "edison", + "jarwi", + "pangeran", + "pandu", + "nalar", + "lalita", + "banawa", + "among", + "tania", + "cecep", + "johan", + "kezia", + "ade", + "titin", + "siti", + "cakrawala", + "taswir", + "utama", + "darsirah", + "taufan", + "laras", + "maman", + "alika", + "rusman", + "jinawi", + "viktor", + "dina", + "tantri", + "reksa", + "rangga", + "dartono", + "wadi", + "galih", + "cawisadi", + "lanjar", + "koko", + "dalima", + "harjaya", + "kadir", + "lala", + "rahman", + "virman", + "najwa", + "cakrabuana", + "galiono", + "anggabaya", + "almira", + "maras", + "yuni", + "vera", + "dirja", + "maimunah", + "usman", + "parman", + "suci", + "kemba", + "lasmanto", + "setya", + "ajimin", + "umay", + "uchita", + "omar", + "harjasa", + "kasiyah", + "karimah", + "zelaya", + "nadia", + "sabri", + "diah", + "calista", + "ami", + "ganep", + "nurul", + "ellis", + "ani", + "karna", + "kamila", + "kenes", + "maida", + "dinda", + "digdaya", + "gabriella", + "maryanto", + "hasna", + "asmianto", + "elvina", + "teguh", + "ihsan", + "irsad", + "nugraha", + "purwanto", + "mahmud", + "endah", + "gilda", + "vicky", + "salman", + "nasrullah", + "anom", + "sadina", + "bella", + "zizi", + "olivia", + "salsabila", + "kasusra", + "hartaka", + "alambana", + "wakiman", + "ganda", + "warsita", + "sabrina", + "gilang", + "yono", + "prabawa", + "vinsen", + "sakti", + "ophelia", + "juli", + "slamet", + "zamira", + "jasmin", + "galang", + "balijan", + "gina", + "ian", + "bahuwarna", + "wirda", + "wawan", + "purwa", + "mustika", + "bancar", + "lidya", + "darmanto", + "bakiono", + "ira", + "tugiman", + "wahyu", + "reza", + "karma", + "rosman", + "tomi", + "surya", + "queen", + "malik", + "emil", + "carla", + "ika", + "mulyono", + "gamanto", + "cemplunk", + "irwan", + "gaiman", + "ega", + "yusuf", + "martana", + "yahya", + "gatra", + "daryani", + "kala", + "hamzah", + "labuh", + "timbul", + "rendy", + "hamima", + "bahuraksa", + "jail", + "darimin", + "latif", + "ina", + "kamaria", + "kalim", + "opung", + "bagas", + "sabar", + "leo", + "zelda", + "dipa", + "kajen", + "jais", + "xanana", + "rafi", + "amelia", + "sakura", + "silvia", + "lintang", + "samiah", + "gandewa", + "tasnim", + "safina", + "dono", + "maya", + "taufik", + "hesti", + "sarah", + "malika", + "oskar", + "estiono", + "naradi", + "lulut", + "wardi", + "cahya", + "luthfi", + "gambira", + "betania", + "banawi", + "tirtayasa", + "mumpuni", + "natalia", + "ciaobella", + "kartika", + "ulva", + "kawaya", + "cici", + "atma", + "rina", + "keisha", + "talia", + "jaiman", + "ibrani", + "kenzie", + "gasti", + "baktianto", + "kasim", + "najam", + "nadine", + "asirwada", + "ganjaran", + "marsito", + "garang", + "fitriani", + "nrima", + "praba", + "karya", + "warji", + "paramita", + "gada", + "tina", + "gading", + "adika", + "ivan", + "erik", + "zalindra", + "damu", + "eka", + "jarwa", + "margana", + "hani", + "lukman", + "kania", + "tiara", + "jagapati", + "legawa", + "gantar", + "kani", + "galar", + "saiful", + "harimurti", + "nova", + "harjo", + "ayu", + "puspa", + "cengkal", + "prima", + "kawaca", + "jumadi", + "danang", + "prasetyo", + "elma", + "umaya", + "muni", + "capa", + "aslijan", + "heru", + "danuja", + "daliono", + "hadi", + "bakiadi", + "paiman", + "jono", + "argono", + "eja", + "harja", + "jagaraga", + "kusuma", + "elon", + "halima", + "cayadi", + "melinda", + "raihan", + "aisyah", + "okta", + "kairav", + "pia", + "jelita", + "zahra", + "gadang", + "kemal", + "intan", + "dadap", + "cinthia", + "nasab", + "narji", + "darmaji", + "radika", + "galuh", + "diana", + "darijan", + "sari", + "elvin", + "latika", + "eluh", + "faizah", + "jayeng", + "perkasa", + "adiarja", + "yessi", + "lasmono", + "oman", + "cinta", + "samsul", + "kacung", + "anita", + "mursita", + "radit", + "adinata", + "hendri", + "laksana", + "kardi", + "respati", + "jumari", + "candra", + "adikara", + "martaka", + "candrakanta", + "zulaikha", + "gaman", + "mahdi", + "okto", + "artanto", + "agnes", + "mujur", + "pranata", + "novi", + "putu", + "panca", + "jamil", + "dodo", + "harsaya", + "daliman", + "humaira", + "indah", + "titi", + "ida", + "jefri", + "cagak", + "manah", + "prasetya", + "dewi", + "fitria", + "baktiono", + "jessica", + "ratna", + "balidin", + "hendra", + "hasim", + "jabal", + "edward", + "lutfan", + "hilda", + "bajragin", + "umi", + "yance", + "satya", + "wasis", + "jane", + "embuh", + "chandra", + "ajimat", + "hana", + "paris", + "danu", + "aditya", + "irfan", + "eli", + "puti", + "muhammad", + "ilyas", + "laila", + "ozy", + "vero", + "dadi", + "kunthara", + "ajeng", + "yosef", + "cindy", + "karsana", + "raden", + "cahyanto", + "raharja", + "garda", + "yunita", + "akarsana", + "yuliana", + "gamani", + "rika", + "iriana", + "raisa", + "rafid", + "prayogo", + "cahyo", + "himawan", + "ghaliyati", + "laswi", + "karen", + "murti", + "tirta", + "asirwanda", + "empluk", + "adhiarja", + "citra", + "panji", + "lukita", + "mitra", + "bagus", + "dagel", + "clara", + "lamar", + "farhunnisa", + "asmuni", + "arta", + "harsanto" + ], + "LAST_NAME": [ + "waskita", + "prasetyo", + "permata", + "hassanah", + "wibisono", + "wijaya", + "maheswara", + "zulkarnain", + "purwanti", + "tampubolon", + "sudiati", + "mandasari", + "suwarno", + "suartini", + "puspita", + "natsir", + "latupono", + "kuswoyo", + "yuliarti", + "uwais", + "tamba", + "usamah", + "halim", + "wahyuni", + "prakasa", + "pangestu", + "pudjiastuti", + "salahudin", + "mustofa", + "lailasari", + "megantara", + "sinaga", + "wulandari", + "adriansyah", + "sitorus", + "pratiwi", + "firgantoro", + "halimah", + "mangunsong", + "setiawan", + "winarsih", + "purnawati", + "permadi", + "kurniawan", + "nashiruddin", + "pranowo", + "prayoga", + "simanjuntak", + "kusmawati", + "andriani", + "palastri", + "nuraini", + "haryanti", + "waluyo", + "sihombing", + "uyainah", + "kusumo", + "astuti", + "yulianti", + "mulyani", + "pradana", + "rajata", + "zulaika", + "anggraini", + "wijayanti", + "utami", + "irawan", + "sihotang", + "melani", + "nainggolan", + "simbolon", + "rahayu", + "aryani", + "prastuti", + "usada", + "budiyanto", + "dongoran", + "mahendra", + "saragih", + "prabowo", + "pratama", + "nasyiah", + "wasita", + "suryono", + "saefullah", + "maulana", + "saptono", + "damanik", + "wacana", + "laksita", + "marbun", + "situmorang", + "riyanti", + "maryadi", + "laksmiwati", + "hariyah", + "narpati", + "wibowo", + "yolanda", + "mayasari", + "jailani", + "lazuardi", + "wahyudin", + "mardhiyah", + "prasetya", + "napitupulu", + "ramadan", + "hidayat", + "nasyidah", + "widiastuti", + "farida", + "sitompul", + "safitri", + "haryanto", + "firmansyah", + "utama", + "nurdiyanti", + "hastuti", + "pradipta", + "mansur", + "agustina", + "wastuti", + "suryatmi", + "susanti", + "kuswandari", + "sirait", + "rajasa", + "prasasta", + "padmasari", + "hidayanto", + "marpaung", + "thamrin", + "hakim", + "oktaviani", + "nababan", + "yuniar", + "putra", + "nugroho", + "mandala", + "lestari", + "manullang", + "iswahyudi", + "ardianto", + "santoso", + "budiman", + "anggriawan", + "hutapea", + "gunarto", + "widodo", + "winarno", + "januar", + "maryati", + "novitasari", + "siregar", + "saputra", + "fujiati", + "tarihoran", + "hartati", + "hardiansyah", + "rahimah", + "habibi", + "rahmawati", + "samosir", + "najmudin", + "pertiwi", + "namaga", + "hutagalung", + "hasanah", + "hutasoit", + "gunawan", + "handayani", + "puspasari", + "dabukke" + ], + "LAST_NAME_MALE": [], + "LAST_NAME_FEMALE": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": {}, + "other_gender_swap": {}, + "en_pronoun2gender": {}, + "en_pronoun2pronoun": {}, + "en_pronoun2title": {}, + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/ie.json b/data_tooling/pii_processing/ontology/data/ie.json new file mode 100644 index 0000000..3e89de0 --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/ie.json @@ -0,0 +1,67 @@ +{ + "SOC_ECO_CLASS": [ + "societ\u00e1", + "fraternit\u00e1" + ], + "ANIMAL": [ + "pirrul" + ], + "PLANT": [ + "carotte", + "plum", + "salice" + ], + "LANGUAGE": [ + "interlingue", + "german", + "chinese" + ], + "JOB": [ + "don", + "chofero" + ], + "PUBLIC_FIGURE": [ + "e", + "esperantie", + "putin" + ], + "ORG": [ + "un" + ], + "RACE": [ + "chinese" + ], + "LOCATION": [ + "sri_lanka" + ], + "FAC": [ + "poc_a_poc" + ], + "FOOD": [ + "ros\u00e9" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "reyessa": "rey", + "sestra": "german" + }, + "other_gender_swap": {}, + "en_pronoun2gender": {}, + "en_pronoun2pronoun": { + "they": [ + "ellas", + "illos" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/io.json b/data_tooling/pii_processing/ontology/data/io.json new file mode 100644 index 0000000..214242a --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/io.json @@ -0,0 +1,916 @@ +{ + "DISEASE": [ + "doloro", + "giboza", + "agaco", + "handikapo", + "beriberio", + "tusar", + "kastano", + "cikatro", + "araneofobio", + "hungro", + "kuperoso", + "suko", + "hungrar", + "kiragro", + "dozo", + "furunklo", + "krupo", + "stigmato", + "skorbuto", + "inversigo", + "hernio", + "sunofrapo", + "katalepsio", + "kapdoloro", + "mareo", + "dementeso", + "poliomielito", + "para", + "ekimoso", + "rozeolo", + "gravida", + "dursto", + "gangreno", + "loncho", + "manio", + "rakito", + "kastanea", + "rabio", + "maladeso", + "perturbo", + "pelagro", + "alexia", + "ranio", + "stotero", + "anestezio", + "smart", + "domajo", + "ed", + "katarakto", + "strumo", + "kakexio", + "plevrito", + "stroko", + "purpura", + "impulsiva", + "gravideso", + "dolorar", + "kancero", + "sternutar", + "strabeso", + "mi", + "kapodoloro", + "bruneskar", + "singulto", + "malario", + "pasiono", + "likeno", + "le", + "torporo", + "traumato", + "oreliono" + ], + "PUBLIC_FIGURE": [ + "benjamin_franklin", + "akira_kurosawa", + "jean_genet", + "giovanni_boccaccio", + "kabloveturo", + "leonard_bernstein", + "che_guevara", + "georges_simenon", + "augustin_fresnel", + "maria_callas", + "willard_quine", + "henrik_ibsen", + "dentofeo", + "mary_shelley", + "marcello_malpighi", + "david_livingstone", + "eduard_buchner", + "andrzej_wajda", + "douglas_macarthur", + "e_cetera", + "winston_churchill", + "johannes_diderik_van_der_waals", + "andrei_saharov", + "karl_landsteiner", + "ivan_pavlov", + "dmitri_shostakovich", + "paul_mccartney", + "stephen_king", + "francis_crick", + "joseph_greenberg", + "isaac_newton", + "victor_hugo", + "edwin_hubble", + "milton_friedman", + "john_glenn", + "george_harrison", + "george_orwell", + "arthur_koestler", + "richard_wagner", + "williams", + "marie_curie", + "francis_galton", + "michael_jackson", + "thomas_hobbes", + "samuel_beckett", + "galileo_galilei", + "chaim_weizmann", + "robert_koch", + "joseph_goebbels", + "george_eastman", + "john_steinbeck", + "petrus", + "edmund_hillary", + "vincent_van_gogh", + "hans_albrecht_bethe", + "komenius", + "thomas_paine", + "steven_weinberg", + "mary_pickford", + "hans_fischer", + "yuri_gagarin", + "willem_einthoven", + "marie_antoinette", + "giuseppe_verdi", + "e", + "karl_jaspers", + "hideki_yukawa", + "konrad_adenauer", + "maurice_chevalier", + "gottlieb_daimler", + "frank_sinatra", + "abel_tasman", + "katharine_hepburn", + "henri_becquerel", + "henri_matisse", + "louis_pasteur", + "richard_strauss", + "mahalia_jackson", + "gertrude_stein", + "sarah_bernhardt", + "luigi_pirandello", + "t_s_eliot", + "charles_de_gaulle", + "paul_von_hindenburg", + "charles_lindbergh", + "vincenzo_bellini", + "f", + "ludwig_wittgenstein", + "august_strindberg", + "thomas_mann", + "dante_alighieri", + "james_tobin", + "samuel_de_champlain", + "giacomo_puccini", + "fridtjof_nansen", + "louis_braille", + "herbert_marcuse", + "mungo_park", + "paul_verlaine", + "james_dean", + "alessandro_manzoni", + "nicolas_poussin", + "andrea_mantegna", + "oscar_wilde", + "j_d_salinger", + "richard_trevithick", + "don_quijote", + "laurence_olivier", + "christiaan_eijkman", + "adolf_eichmann", + "francis_bacon", + "pete_seeger", + "bachelero", + "joseph_heller", + "a", + "james_brown", + "charles_baudelaire", + "david_ricardo", + "charlie_parker", + "immanuel_kant", + "james_franck", + "konstantin_stanislawski", + "charles_de_montesquieu", + "albert_schweitzer", + "giulio_natta", + "titus", + "johannes_kepler", + "william_s_burroughs", + "max_planck", + "preavo", + "william_blake", + "julio_iglesias", + "john_bardeen", + "sarah_vaughan", + "william_byrd", + "sarah_siddons", + "canberra", + "elias_canetti", + "edward_jenner", + "dominique_ingres", + "oliver_hardy", + "cole_porter", + "graham_greene", + "lars_onsager", + "margaret_mitchell", + "santa_petrus", + "igor_stravinsky", + "william_herschel", + "niels_bohr", + "sergei_rachmaninoff", + "bertrand_russell", + "michael_faraday", + "anthony_burgess", + "jan_tinbergen", + "irving_berlin", + "rudolf_diesel", + "walt_disney", + "gabriel_lippmann", + "benny_goodman", + "friedrich_engels", + "jane_austen", + "gustav_mahler", + "phil_collins", + "robert_redford", + "jean_giraudoux", + "ian_fleming", + "richard_feynman", + "wolfgang_pauli", + "theodor_mommsen", + "andrew_huxley", + "marcel_proust", + "thomas_more", + "paul_hindemith", + "elizabeth_taylor", + "william_golding", + "indira_gandhi", + "jane_seymour", + "george_gershwin", + "frank_whittle", + "alfred_nobel", + "marco_polo", + "caravaggio", + "allen_ginsberg", + "daniel_bernoulli", + "guillaume_apollinaire", + "henri_bergson", + "boris_karloff", + "pierre_corneille", + "patrick_white", + "hans_christian_andersen", + "cary_grant", + "friedrich_hegel", + "pieter_zeeman", + "glenn_miller", + "pablo_picasso", + "natalie_wood", + "kurt_weill", + "otto_hahn", + "christiaan_huygens", + "hector_berlioz", + "lucille_ball", + "paul_simon", + "claudio_monteverdi", + "john_galsworthy", + "robert_robinson", + "o", + "saint_louis_missouri", + "adam_smith", + "william_james", + "u", + "karl_marx", + "friedrich_nietzsche", + "i", + "sandro_botticelli", + "nikola_tesla", + "charles_barkley", + "robert_schumann", + "mel_gibson", + "le_corbusier", + "carlo_goldoni", + "john_locke", + "alexis_carrel", + "henry_james", + "ingrid_bergman", + "leonard_bloomfield", + "jean_piaget", + "henri_rousseau", + "h_g_wells", + "walt_whitman", + "adolf_hitler", + "james_d_watson", + "fritz_haber", + "joseph_haydn", + "george_boole", + "edvard_grieg", + "hrushchev", + "1", + "cordell_hull", + "rosa_parks", + "ernest_walton", + "vladimir_putin", + "giuseppe_mazzini", + "arnold_sch\u00f6nberg", + "fritz_kreisler", + "arthur_schopenhauer", + "james_cagney", + "martin_heidegger", + "george_lucas", + "andrew_jackson", + "louis_armstrong", + "steven_spielberg", + "giuseppe_garibaldi", + "philip_warren_anderson", + "bobby_fischer", + "johannes_gutenberg", + "thomas_malthus", + "gaetano_donizetti", + "william_faulkner", + "hans_adolf_krebs", + "anna_kournikova", + "francis_poulenc", + "su_ocidar", + "putin", + "jean_de_la_fontaine", + "robert_hooke", + "karl_popper", + "george_sand", + "peter_sellers", + "charles_fourier", + "julius_cezaro", + "marcus_aurelius", + "peter_o'toole", + "joseph_conrad", + "peter_paul_rubens", + "mahatma_gandhi", + "jim_morrison", + "jules_verne", + "paul_newman", + "apuso", + "jackson_pollock", + "john_lennon", + "charlie_chaplin", + "d_h_lawrence", + "boris_spasski", + "antonio_stradivari", + "miles_davis", + "george_marshall", + "stanley_kubrick", + "james_watt", + "ronald_reagan", + "helmut_schmidt", + "homo", + "wilhelm_reich", + "roman_jakobson", + "oliver_cromwell", + "lionel_hampton", + "martin_luther_king", + "woodrow_wilson", + "marcus_antonius", + "b\u00e9la_lugosi", + "ernest_hemingway", + "arthur_miller", + "cristoforo_colombo", + "nelson_mandela", + "heinrich_himmler", + "al_gore", + "cesare_borgia", + "roald_amundsen", + "charles_dickens", + "ella_fitzgerald", + "jacques_offenbach", + "federico_fellini", + "bessie_smith", + "willy_brandt", + "francisco_pizarro", + "francisco_franco", + "bernardo_bertolucci", + "franz_schubert", + "johnny_cash", + "joseph_mccarthy", + "alfred_kastler", + "mick_jagger", + "otto_loewi", + "georges_cuvier", + "william_harvey", + "walter_scott", + "peter_medawar", + "vladimir_lenin", + "robert_peary", + "jonathan_swift", + "albert_einstein", + "muelisto", + "raymond_chandler", + "henry_purcell", + "wilhelm_ostwald" + ], + "PLANT": [ + "manioko", + "badiano", + "tremulo", + "florkaulo", + "guindiero", + "kaprifolio", + "konvolvulo", + "cibolo", + "frangulo", + "karoto", + "magnolio", + "margrito", + "guindo", + "sikomoro", + "mustardo", + "kolareto", + "salikario", + "kaulo", + "pichpino", + "sequoyo", + "larico", + "fazeolo", + "beladono", + "panseo", + "pinealo", + "patato", + "quecho", + "rezedo", + "papavero", + "helianto", + "kokosiero", + "ampelopso", + "kasisiero", + "solano", + "serpolo", + "kardamomo", + "antirino", + "ergoto", + "arumo", + "lentisko", + "heleboro_verda", + "merizo", + "oxalo", + "ligustro", + "bergamoto", + "edelweiss", + "artisto", + "dateliero", + "pastoroburso", + "olivo", + "klematido", + "pinastro", + "meliso", + "kapuchino", + "urtiko", + "karubiero", + "quechiero", + "sandalo" + ], + "JOB": [ + "husaro", + "depozario", + "muelisto", + "lanciero", + "hidrologo", + "quartermastro", + "lietnanto", + "kapristo", + "kolonelo", + "endetalvendisto", + "skabino", + "herboristo", + "barelisto", + "dietizanto", + "gardenisto", + "gerontologo", + "episkopo", + "seruristo", + "premiochasisto", + "romanisto", + "seneshalo", + "enciklopediisto", + "forejo", + "premiochasero", + "kamilisto", + "laboristo", + "komodoro", + "ciencisto", + "para", + "lavistino", + "autoro", + "preceptoro", + "familiara", + "stroko", + "furiero", + "stewardulo", + "almonero", + "autoracho", + "gardenistulo", + "spicovendisto", + "vaskulala_cerebrala_stroko", + "ginekologo", + "spicisto", + "almonisto", + "episkopino", + "episkopulo", + "stewardino", + "manuo", + "ushero", + "motoristo", + "linealo", + "rabino", + "pikerino", + "masonisto", + "parolanto", + "bankisto", + "jeristo", + "skudiero", + "konduktoro", + "hematologo", + "kemiisto", + "pretoro", + "tirkesto", + "muzik_instrumento", + "maristo", + "aktisto", + "kolektero", + "korsaronavo", + "regento", + "endetalisto", + "menajisto", + "urbestro", + "gardenistino", + "sub", + "dragono", + "gardisto", + "pikerulo", + "springar" + ], + "PRODUCT": [ + "sovietia", + "kobayo", + "homala_yuri", + "analitiko", + "saxonia_anhalt", + "mario_andretti", + "triumf_arko" + ], + "ANIMAL": [ + "moskardino", + "ciprino", + "makio", + "katino", + "cervulo", + "martro", + "kardelo", + "skurelo", + "leonyuno", + "chasohundo", + "kantarido", + "palumbo", + "lemingo", + "holoturio", + "horniso", + "marsuino", + "kondoro", + "sparviero", + "tetraso", + "abelino", + "pigino", + "askarido", + "karabo", + "huo", + "martin_peskero", + "molao", + "korniko", + "daimo", + "alko", + "aselo", + "ekino", + "kashaloto", + "pleuronekto", + "vulturo", + "galinelo", + "kastoro", + "bifacia", + "mar_lutro", + "leonyunulo", + "para_hufajo", + "antuso", + "redpektoro", + "gilemoto", + "barsho", + "hueto", + "kobayo", + "apro", + "falkono", + "basoto", + "dubar", + "fureto", + "artropodo", + "spanieleto", + "kapreolo", + "leonyunino", + "kanabino" + ], + "BIO_CHEM_ENTITY": [ + "silico" + ], + "ORG": [ + "me_nomesas", + "germaniana_imperio", + "the_who", + "koncilo", + "san_francisco", + "un", + "dolor_matro", + "cientologio", + "armeo", + "enceluligar", + "medicinala_skolo", + "la_dormanta_belino", + "taliono", + "kolegio", + "don_juan", + "red_armeo", + "guvernerio", + "archo", + "taoismo", + "sindikato", + "the_breakfast_club", + "san_tome", + "rabindranath_tagore", + "sant_helena", + "kabo_verda", + "flegado", + "al_jazira", + "reda_maro", + "nordrheno_vestfalia", + "est_germania", + "addis_ababa", + "framasonaro", + "tempope", + "questionopunto", + "generala_stati", + "matro_doloroza", + "ed_altri", + "los_angeles", + "nato", + "dementeskar", + "me_amas_tu", + "mi", + "skolo", + "de_tempo_a_tempo", + "linguaro", + "ciencologio", + "posto_kontoro", + "batado" + ], + "LOCATION": [ + "nacional_asemblo", + "me_dankas", + "staceskar", + "la_dormanta_belino", + "piet_mondrian", + "laktovoyo", + "al_jazira", + "joseph_louis_gay_lussac", + "falklandi", + "atlantiko", + "usa", + "kabverdo", + "sri_lanka", + "tranchar", + "the_rolling_stones", + "aer_armeo", + "centrala_banko", + "heitor_villa_lobos", + "ne_dankinde" + ], + "FAC": [ + "katolik_eklezio", + "balnobaseno", + "arnold_sch\u00f6nberg", + "policeyo", + "petrus_1ma_di_rusia", + "pazope", + "titus_livius", + "santa_lucia", + "katolik_eklesio" + ], + "FOOD": [ + "sauco", + "kechupo", + "dejuno", + "aperitivo", + "tizano", + "entreo", + "repasteto", + "limonado", + "dejuneto", + "chili", + "chile", + "entremeso", + "kerio", + "piklokukombreto" + ], + "SOC_ECO_CLASS": [ + "kremo", + "samurai", + "nobeleso", + "agrokultivo", + "laboristaro", + "frateso", + "kasto" + ], + "LANGUAGE": [ + "finlandana", + "franciana", + "bielorusiala", + "nederlandana", + "espo", + "sango", + "esperanto", + "angliana", + "ido", + "germaniano", + "tonga" + ], + "PERSON": [ + "al_gore", + "h_g_wells", + "igor_sikorsky", + "carl_david_anderson" + ], + "QUANTITY": [ + "la_tri_robotala_legi", + "kalorio", + "dollar", + "lageto", + "libera", + "dolaro", + "anders_celsius" + ], + "PERSON_PRONOUN": [ + "i", + "ni_ipsa", + "he", + "we", + "me", + "tu_ipsa", + "me_ipsa" + ], + "GENDER": [ + "ekzemeskar", + "transgenra", + "men", + "yunino", + "muliero", + "plako", + "transgenreso", + "homeosexuala" + ], + "LAW": [ + "legalesoprincipo" + ], + "DATE": [ + "paskosundio", + "la_dio_pos_morge" + ], + "POLITICAL_PARTY_MEMBER": [ + "kamarado" + ], + "RELIGION_MEMBER": [ + "fratulo", + "franciskano", + "katolika" + ], + "RACE": [ + "insulanulo", + "franciano", + "afrikana", + "insulano", + "insulanino", + "negro" + ], + "RELIGION": [ + "presbiterismo", + "manikeismo", + "lamaismo" + ], + "GPE": [ + "di_mezo_pirenei", + "hagia_sofia", + "reda_kruco", + "nova_testamento", + "al_andalus", + "champania_ardeni", + "blanka_domo" + ], + "POLITICAL_PARTY": [ + "partiso" + ], + "UNION": [ + "sindikato" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "abadino": "abado", + "barono": "baronulo", + "baronino": "baronulo", + "ucelyuno": "plako", + "puerino": "kerlo", + "yunino": "kerlo", + "yuna": "kerlo", + "heroino": "heroo", + "damo": "kastelestro", + "patrino": "patro", + "nun": "monako", + "princino": "regulus", + "rejino": "vua", + "elu": "he", + "fratino": "fratulo", + "damzelo": "celibulo", + "stif_filiino": "stif_filiulo", + "tabloservistino": "garsono", + "vidvino": "vidvulo", + "balo": "vidvulo", + "frue": "spozulo", + "spozino": "spozulo", + "yuno": "yunino", + "yunulo": "yunino", + "yaro": "yuna", + "puero": "yuna", + "puerulo": "puerino", + "infantulo": "yuna" + }, + "other_gender_swap": {}, + "en_pronoun2gender": { + "they": [ + "transgenra", + "homeosexuala", + "bisexuala", + "transgenreso" + ], + "he": [ + "yuno", + "puerulo", + "plako", + "yaro", + "yunulo", + "kerlo", + "puero", + "ekzemeskar", + "infantulo" + ], + "she": [ + "yunino", + "damzelo", + "yuna", + "feto", + "puerino", + "homino", + "damo", + "muliero" + ] + }, + "en_pronoun2pronoun": { + "he": [ + "elu", + "ilu", + "he", + "lia", + "seine", + "ilua" + ], + "she": [ + "elua", + "elu" + ], + "they": [ + "lia" + ], + "it": [ + "eso", + "olu", + "esas", + "olua", + "tento", + "ico" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/is.json b/data_tooling/pii_processing/ontology/data/is.json new file mode 100644 index 0000000..99a8e15 --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/is.json @@ -0,0 +1,1317 @@ +{ + "EVENT": [ + "stangarst\u00f6kk", + "spilakassaleikur", + "persafl\u00f3astr\u00ed\u00f0i\u00f0", + "lands\u00fdn" + ], + "FOOD": [ + "eftirr\u00e9ttur", + "engifer\u00f6l", + "jurtaol\u00eda", + "bl\u00f3\u00f0m\u00f6r", + "ullarbrj\u00f3stsykur", + "linso\u00f0inn", + "hv\u00edtv\u00edn", + "appels\u00ednusafi", + "kart\u00f6flufl\u00f6gur", + "sykurfrau\u00f0", + "rau\u00f0gl\u00f3andi", + "hv\u00edtlauksbrau\u00f0", + "kotas\u00e6la", + "rau\u00f0v\u00edn", + "pinot_noir", + "l\u00e9ttmj\u00f3lk", + "kand\u00eds", + "\u00f3l\u00edfuol\u00eda", + "kranavatn", + "undanrenna", + "frey\u00f0iv\u00edn", + "chile", + "morgunmatur", + "heilhveitibrau\u00f0", + "rau\u00f0k\u00e1l", + "morgunver\u00f0ur", + "reyrsykur", + "bakkelsi", + "franskbrau\u00f0", + "augnbaun" + ], + "PUBLIC_FIGURE": [ + "lawrence_durrell", + "henry_cavendish", + "gregor", + "benjamin_franklin", + "don_k\u00edk\u00f3ti", + "myndasyrpa", + "baldvin", + "giovanni_boccaccio", + "johann_bernoulli", + "che_guevara", + "c", + "kapetingar", + "maria_callas", + "william_walton", + "henrik_ibsen", + "mary_shelley", + "heyrnarleysi", + "david_livingstone", + "carl_rogers", + "mary_wollstonecraft", + "thomas_reid", + "winston_churchill", + "gustav", + "paul_mccartney", + "terry_pratchett", + "stephen_king", + "francis_crick", + "joseph_greenberg", + "isaac_newton", + "victor_hugo", + "joseph_smith", + "edwin_hubble", + "milton_friedman", + "edward_gibbon", + "john_glenn", + "salad\u00edn", + "george_harrison", + "george_orwell", + "arthur_koestler", + "richard_wagner", + "marie_curie", + "francis_galton", + "michael_jackson", + "carl_sandburg", + "thomas_hobbes", + "el_greco", + "samuel_beckett", + "jane_goodall", + "robert_koch", + "i_m_pei", + "m\u00fasarindill", + "joseph_goebbels", + "john_steinbeck", + "edmund_hillary", + "vincent_van_gogh", + "verndard\u00fdrlingur", + "thomas_paine", + "liliuokalani", + "mary_pickford", + "emiliano_zapata", + "allen_iverson", + "marie_antoinette", + "giuseppe_verdi", + "karl_jaspers", + "s\u00f3tari", + "frank_sinatra", + "andrei_sakarov", + "abel_tasman", + "katharine_hepburn", + "henri_becquerel", + "henri_matisse", + "louis_pasteur", + "richard_strauss", + "hugo_grotius", + "john_ford", + "gertrude_stein", + "sarah_bernhardt", + "luigi_pirandello", + "t_s_eliot", + "charles_de_gaulle", + "paul_von_hindenburg", + "y", + "el\u00edsabet", + "charles_lindbergh", + "f", + "john_jay", + "ludwig_wittgenstein", + "august_strindberg", + "thomas_mann", + "dante_alighieri", + "margot_fonteyn", + "samuel_de_champlain", + "giacomo_puccini", + "fridtjof_nansen", + "c_pl\u00fas_pl\u00fas", + "q", + "james_dean", + "marie_tussaud", + "nicolas_poussin", + "joseph_pulitzer", + "oscar_wilde", + "j_d_salinger", + "dav\u00ed\u00f0", + "georg", + "adolf_eichmann", + "valent\u00edna_tereshkova", + "francis_bacon", + "tveir", + "a", + "james_brown", + "william_hogarth", + "charles_baudelaire", + "david_ricardo", + "immanuel_kant", + "saint_martin", + "johannes_kepler", + "max_planck", + "william_blake", + "john_bardeen", + "krist\u00f3fer_k\u00f3lumbus", + "william_byrd", + "canberra", + "elias_canetti", + "edward_jenner", + "graham_greene", + "edward", + "william_herschel", + "montesquieu", + "niels_bohr", + "sergei_rachmaninoff", + "bertrand_russell", + "michael_faraday", + "john_d_rockefeller", + "burt", + "o_s_frv", + "walt_disney", + "arth\u00far", + "joseph_schumpeter", + "friedrich_engels", + "jane_austen", + "gustav_mahler", + "ian_fleming", + "richard_feynman", + "theodor_mommsen", + "andrew_huxley", + "marcel_proust", + "thomas_more", + "elizabeth_taylor", + "john_dowland", + "william_golding", + "john_milton", + "samuel_adams", + "gengis_kan", + "indira_gandhi", + "e_t_a_hoffmann", + "alfred_nobel", + "marco_polo", + "caravaggio", + "m", + "allen_ginsberg", + "loftferja", + "daniel_bernoulli", + "guillaume_apollinaire", + "henri_bergson", + "pierre_corneille", + "william_morris", + "cary_grant", + "thomas", + "pieter_zeeman", + "pablo_picasso", + "otto_hahn", + "christiaan_huygens", + "hector_berlioz", + "paul_simon", + "claudio_monteverdi", + "benjamin_jowett", + "robert_scott", + "adam_smith", + "william_james", + "karl_marx", + "friedrich_nietzsche", + "i", + "robert_indiana", + "sandro_botticelli", + "nikola_tesla", + "al_capone", + "charles_barkley", + "robert_schumann", + "mel_gibson", + "le_corbusier", + "john_locke", + "heilagur_georg", + "helen_keller", + "ingrid_bergman", + "j\u00f6rgen", + "bakkal\u00e1rgr\u00e1\u00f0a", + "h_g_wells", + "walt_whitman", + "leopold_kronecker", + "adolf_hitler", + "james_d_watson", + "fritz_haber", + "joseph_haydn", + "edvard_grieg", + "robert_boyle", + "arthur_laffer", + "r\u00f3bert", + "rosa_parks", + "laurence_sterne", + "anne_hathaway", + "g", + "arthur_schopenhauer", + "martin_heidegger", + "h.c_andersen", + "r", + "george_lucas", + "andrew_jackson", + "louis_armstrong", + "steven_spielberg", + "robert_fulton", + "thomas_hardy", + "johann_gutenberg", + "bobby_fischer", + "kalv\u00edn", + "thomas_malthus", + "rau\u00f0hetta", + "william_faulkner", + "amerigo_vespucci", + "hans_adolf_krebs", + "lars", + "emma_goldman", + "james_mill", + "matthew_flinders", + "robert_hooke", + "karl_popper", + "alfred", + "peter_o'toole", + "joseph_conrad", + "peter_paul_rubens", + "p\u00e9tur_postuli", + "jules_verne", + "herkinn", + "jackson_pollock", + "john_lennon", + "bob_woodward", + "charlie_chaplin", + "hannah_arendt", + "antonio_stradivari", + "maximianus", + "miles_davis", + "\u00e6\u00f0ark\u00f3ngur", + "stanley_kubrick", + "james_watt", + "ronald_reagan", + "helmut_schmidt", + "david_hilbert", + "roman_jakobson", + "oliver_cromwell", + "william_wordsworth", + "woodrow_wilson", + "el_cid", + "marcus_antonius", + "st_louis", + "frank", + "ernest_hemingway", + "arthur_miller", + "nelson_mandela", + "heinrich_himmler", + "al_gore", + "p\u00e9tur_mikli", + "mohandas_gandhi", + "roald_amundsen", + "fjarst\u00fdring", + "anton", + "charles_dickens", + "ella_fitzgerald", + "wallace_carothers", + "jacques_offenbach", + "varr\u00f3", + "federico_fellini", + "willy_brandt", + "francisco_pizarro", + "francisco_franco", + "john_ross", + "andrew_carnegie", + "franz_schubert", + "johnny_cash", + "dawid", + "stal\u00edn", + "sam_houston", + "robert_peary", + "jonathan_swift", + "walter_gropius", + "albert_einstein", + "raymond_chandler", + "henry_purcell", + "t" + ], + "ORG": [ + "ida", + "v\u00edsindakirkjan", + "almenningsb\u00f3kasafn", + "umfer\u00f0arteppa", + "wicca", + "sj\u00f3ntaug", + "menntask\u00f3li", + "mannger\u00f0ur", + "jan_mayen", + "birtingsmarka\u00f0ur", + "leyni\u00fej\u00f3nusta", + "r\u00edkisbylting", + "loftvopn", + "landb\u00fana\u00f0ur", + "barnask\u00f3li", + "bangs\u00edmon", + "hlutaf\u00e9lag", + "rau\u00f0i_krossinn", + "san_francisco", + "framhaldssk\u00f3li", + "af_hverju_ekki", + "n\u00e1ttfatapart\u00ed", + "flugher", + "tyggig\u00famm\u00ed", + "fastanefnd", + "verkamannaflokkurinn", + "samf\u00e9lagsmi\u00f0ill", + "heimavistarsk\u00f3li", + "hansasambandi\u00f0", + "albertsvatn", + "nanak", + "vildarr\u00fam", + "\u00edhaldsflokkurinn", + "nor\u00f0vesturlei\u00f0in", + "morgunver\u00f0arkl\u00fabburinn", + "sturlast", + "v\u00edsindask\u00e1ldskapur", + "einkask\u00f3li", + "r\u00f3mversk_ka\u00fe\u00f3lska_kirkjan", + "merv\u00edkingar", + "leikfimisalur", + "r\u00e1\u00f0h\u00fas", + "grunnsk\u00f3li", + "karmelfjall", + "kjarnafj\u00f6lskylda", + "sankti_helena", + "l\u00f6greglur\u00edki", + "nasistaflokkurinn", + "tungum\u00e1la\u00e6tt", + "afr\u00edkusambandi\u00f0", + "gula_flj\u00f3t", + "svarts\u00fdnismarka\u00f0ur", + "gr\u00e6nh\u00f6f\u00f0aeyjar", + "ge\u00f0sj\u00fakrah\u00fas", + "berl\u00ednarm\u00farinn", + "listasafn", + "sankti_l\u00fas\u00eda", + "eineyg\u00f0ur", + "rabindranath_tagore", + "tjingveldi\u00f0", + "r\u00edkisstj\u00f3rn", + "upp_me\u00f0_hendurnar", + "apalhraun", + "tr\u00faarbrag\u00f0afr\u00e6\u00f0i", + "borgr\u00edki", + "menntun", + "englandsbanki", + "steggjapart\u00ed", + "sanngirni", + "kokka", + "einstefnugata", + "hv\u00edta_h\u00fasi\u00f0", + "kyrkja", + "bjarts\u00fdnismarka\u00f0ur", + "gagnfr\u00e6\u00f0ask\u00f3li", + "addis_ababa", + "songveldi\u00f0", + "litar\u00f6\u00f0", + "meginhornal\u00edna", + "a\u00f0alhornal\u00edna", + "mossad", + "ferdinand_magellan", + "heimilisofbeldi", + "hallarbylting", + "\u00e1_\u00fev\u00ed_gu\u00f0s_\u00e1ri", + "eineygur", + "bandar\u00edkja\u00feing", + "hornal\u00ednufylki", + "konungsfj\u00f6lskylda", + "saint_barth\u00e9lemy", + "lake_superior", + "torfa", + "t\u00f3nlistarsk\u00f3li", + "los_angeles", + "spurningarmerki", + "arababandalagi\u00f0", + "j\u00f3rt\u00farle\u00f0ur", + "atlantshafsbandalagi\u00f0", + "vottar_jeh\u00f3va", + "jar\u00f0yrkja", + "se\u00f0labanki", + "jes\u00fa\u00edtareglan", + "ge\u00f0sp\u00edtali", + "r\u00f3marr\u00e9ttur", + "mingveldi\u00f0", + "hergagnai\u00f0na\u00f0urinn", + "rau\u00f0ahaf", + "tangveldi\u00f0", + "dem\u00f3krataflokkurinn", + "as_d\u00far", + "verslunarmi\u00f0st\u00f6\u00f0", + "jafna\u00f0arflokkurinn", + "faldmengi", + "pennsylvan\u00eduh\u00e1sk\u00f3li", + "kauph\u00f6ll", + "tyggj\u00f3", + "dumbungsmarka\u00f0ur", + "almenningssamg\u00f6ngur", + "landher", + "\u00feyrnir\u00f3s", + "akadem\u00eda", + "\u00e1_\u00fev\u00ed_herrans_\u00e1ri", + "strengjakvartett" + ], + "LOCATION": [ + "hv\u00edtfjall", + "mj\u00f3lkursl\u00e6\u00f0a", + "vetrarbrautin", + "deildaverslun", + "gaml\u00e1rskv\u00f6ld", + "bandar\u00edkin", + "flugher", + "elliheimili", + "ermarsundseyjar", + "piet_mondrian", + "sint_maarten", + "gr\u00e6nh\u00f6f\u00f0aeyjar", + "n\u00fdi_heimurinn", + "svartahaf", + "atlantshaf", + "land", + "svarthol", + "gulahaf", + "a\u00f0alstr\u00e6ti", + "bna", + "blindgata", + "tyrrenahaf", + "vetrarbraut", + "mar\u00eduerla", + "michiganvatn", + "t\u00f3nlistarsk\u00f3li", + "loftvopn", + "sri_lanka", + "su\u00f0urey", + "vei\u00f0ihundarnir", + "r\u00f3sagar\u00f0ur", + "orkuver", + "the_rolling_stones", + "p\u00e1skaeyja", + "indusflj\u00f3t", + "ni\u00f0url\u00f6nd", + "kraftverk", + "falklandseyjar", + "hornh\u00f6f\u00f0i", + "ermarsund", + "ve\u00f0urathugunarst\u00f6\u00f0" + ], + "PLANT": [ + "brasil\u00edutr\u00e9", + "holurt", + "musteristr\u00e9", + "baunagras", + "vallarsveifgras", + "fuglakirsuber", + "skinaldin", + "sortulyng", + "dalalilja", + "litunarjafni", + "matbaun", + "vepjulilja", + "giljafl\u00e6kja", + "sveigfura", + "gr\u00e6nserkur", + "vallarr\u00fdgresi", + "nellika", + "sk\u00f3garkerfill", + "vatnsberar", + "brenninetla", + "flipareynir", + "gr\u00e1selja", + "holugeitungur", + "lambagras", + "linditr\u00e9", + "stj\u00f6rnusteinbrj\u00f3tur", + "svart\u00f6sp", + "hinriksnj\u00f3li", + "s\u00edtr\u00f3numelissa", + "haugarfi", + "lindifura", + "ferlaufungur", + "hagahlynur", + "hjartago\u00f0i", + "marh\u00e1lmur", + "m\u00fasareyra", + "t\u00fankempa", + "silfurbla\u00f0", + "hjartafr\u00f3", + "p\u00edpukragi", + "j\u00f3latr\u00e9", + "fergin", + "ullserkur", + "sinnepsk\u00e1l", + "sinnep", + "arfi", + "skollakambur", + "venusargildra", + "degli", + "brennis\u00f3ley", + "holtas\u00f3ley", + "listama\u00f0ur", + "huldulykill", + "broddgreni", + "vorlyng", + "laugadepla", + "kassavar\u00f3t", + "anganma\u00f0ra", + "draums\u00f3ley", + "vetrarbl\u00f3m", + "dulfr\u00e6vingar", + "kart\u00f6flumygla", + "sk\u00f3garfura", + "elri", + "sykurreyr", + "k\u00f3ngssveppur", + "kalmusr\u00f3t", + "vatnsberi", + "mosasteinbrj\u00f3tur", + "tonkabaunir", + "\u00fe\u00fasundbla\u00f0ar\u00f3s", + "geldingahnappur", + "st\u00f3riburkni", + "vorperla", + "gr\u00e1tv\u00ed\u00f0ir", + "\u00e1staraldin", + "hj\u00e1lmgras", + "korndrj\u00f3li", + "vallarfoxgras", + "reifasveppir", + "stafafura", + "svartgreni", + "lyngb\u00fai", + "listakona", + "freyjubr\u00e1", + "frumuveggur", + "bergfl\u00e9tta", + "sk\u00f3gelfting", + "skarfak\u00e1l", + "vallhumall", + "perureynir", + "selja", + "beinvi\u00f0ur", + "kirsuber", + "dvergastigi", + "strandrau\u00f0vi\u00f0ur", + "v\u00f6ludepla", + "k\u00f6rfuv\u00ed\u00f0ir", + "risal\u00edfvi\u00f0ur", + "bjarnarber", + "berserkjasveppur", + "broddfura", + "bl\u00f3\u00f0rifs", + "furur", + "keisaraserkur" + ], + "ANIMAL": [ + "p\u00e9tursfiskur", + "grindhvalir", + "evr\u00f3puv\u00edsundur", + "skalla\u00f6rn", + "skrofa", + "flatl\u00fas", + "cat", + "rau\u00f0h\u00f6f\u00f0a\u00f6nd", + "mar\u00edusvunta", + "brand\u00f6nd", + "kameld\u00fdr", + "turnugla", + "steypirey\u00f0ur", + "krummi", + "kanadag\u00e6s", + "blindrahundur", + "mandar\u00edn\u00f6nd", + "silfurm\u00e1fur", + "gull\u00f6rn", + "fjallageit", + "barrfinka", + "hv\u00edtabj\u00f6rn", + "topp\u00f6nd", + "hettum\u00e1fur", + "keldusv\u00edn", + "minkur", + "grindhvalur", + "krossnefur", + "bjargd\u00fafa", + "haftyr\u00f0ill", + "grassn\u00e1kur", + "dugg\u00f6nd", + "kr\u00f3nhj\u00f6rtur", + "naggr\u00eds", + "stormsvala", + "langrey\u00f0ur", + "froskar", + "makki", + "stiki", + "bakuggi", + "nor\u00f0hvalur", + "sandl\u00e6gja", + "kafendur", + "safali", + "landselur", + "lindableikja", + "hj\u00f6rtur", + "rau\u00f0brystingur", + "afr\u00edkuf\u00edll", + "tunglfiskur", + "flagari", + "stuttnefja", + "skarkoli", + "naggr\u00edsir", + "mar\u00edgull", + "langv\u00eda", + "hv\u00edth\u00e1karl", + "marg\u00e6s", + "gullins\u00e6kir", + "froskur", + "sorgarskikkja", + "hagam\u00fas", + "villisv\u00edn", + "sebrafinka", + "sparrhaukur", + "g\u00e6sagammur", + "geitungur", + "vinnud\u00fdr", + "heimskautarefur", + "hamarh\u00e1karl", + "grindahvalur", + "beinagr\u00e1ni", + "kyrrahafs\u00feorskur", + "graf\u00f6nd", + "br\u00fa\u00f0\u00f6nd", + "klaufd\u00fdr", + "kornsn\u00e1kur", + "safasp\u00e6ta", + "kart\u00f6flubjalla", + "belta\u00feyrill", + "gammur", + "bifur", + "leturhumar", + "spend\u00fdr", + "konungsk\u00f3bra", + "heslim\u00fas", + "starri", + "engirella", + "vorselur", + "villig\u00f6ltur", + "lj\u00f3sh\u00f6f\u00f0a\u00f6nd", + "hausk\u00fapufi\u00f0rildi", + "mistil\u00fer\u00f6stur", + "\u00feistilfinka", + "sela\u00e6tt", + "kamb\u00f6nd", + "gull", + "marsv\u00edn", + "hr\u00fa\u00f0urkarl", + "marab\u00fastorkur", + "skrokklanga", + "kvennab\u00f3si", + "beinh\u00e1karl", + "froska\u00e6tt", + "kampselur", + "h\u00fasam\u00fas", + "sandrey\u00f0ur", + "j\u00f6tunuxar", + "klettafjallageit", + "mosastelkur", + "greifingi", + "l\u00e6kningaigla", + "hjartard\u00fdr", + "fengrani", + "stormm\u00e1fur" + ], + "DISEASE": [ + "mengisb\u00f3lga", + "mergruni", + "kossas\u00f3tt", + "holdsveiki", + "pers\u00f3nuleikar\u00f6skun", + "graftars\u00f3tt", + "reikniblinda", + "ofst\u00f6\u00f0ur", + "sj\u00f3nskekkja", + "heilal\u00f6mun", + "lasinn", + "standp\u00edna", + "varmi", + "ringulrei\u00f0", + "hlaupab\u00f3la", + "nabbi", + "hausverkur", + "flot\u00f6gn", + "flasa", + "malar\u00eda", + "loftst\u00edfla", + "barkak\u00fdliskvef", + "vatnsb\u00f3la", + "h\u00f6fu\u00f0verkur", + "einhverfa", + "staklitnun", + "heilahristingur", + "sl\u00e1ttarst\u00f6\u00f0vun", + "tannvegsb\u00f3lga", + "mj\u00f3lkur\u00f3\u00feol", + "gall", + "koparhr\u00f6rnun", + "tungutal", + "kolbrandur", + "einkirningas\u00f3tt", + "heilaskemmd", + "barnaveiki", + "ms", + "amel\u00eda", + "tannp\u00edna", + "munnangursb\u00f3lga", + "\u00e1str\u00ed\u00f0a", + "sultur", + "pyntingar", + "barkab\u00f3lga", + "berklar", + "draumsvefn", + "tannholdsb\u00f3lga", + "flensa", + "glundro\u00f0i", + "t\u00e1rapokab\u00f3lga", + "svartidau\u00f0i", + "stama", + "kolm\u00f3nox\u00ed\u00f0eitrun", + "vessab\u00f3la", + "bein\u00feynning", + "meinafr\u00e6\u00f0i", + "heilahimnub\u00f3lga", + "barkak\u00fdlisb\u00f3lga", + "kart\u00f6flumygla", + "s\u00e1rsauki", + "matareitrun", + "marblettur", + "sortu\u00e6xli", + "brotna", + "ge\u00f0sj\u00fakd\u00f3mur", + "gallbl\u00f6\u00f0rub\u00f3lga", + "parkinsonsveiki", + "b\u00f3lus\u00f3tt", + "berkjukvef", + "koff\u00edneitrun", + "geislun", + "heilabl\u00f3\u00f0fall", + "verkur", + "miltisbrandur", + "loftb\u00f3lurek", + "helftarl\u00f6mun", + "lotugr\u00e6\u00f0gi", + "n\u00e6ringarkvilli", + "innlyksuheilab\u00f3lga", + "vessa\u00feurr\u00f0", + "gimp", + "vatnsh\u00f6fu\u00f0", + "li\u00f0agigt", + "frenzy", + "krans\u00e6\u00f0ast\u00edfla", + "rafleysa", + "talnablinda", + "geril\u00e6ta", + "offita", + "beinbrunas\u00f3tt", + "mi\u00f0eyrab\u00f3lga", + "heimsfaraldur", + "skarlatss\u00f3tt", + "oddvarta", + "helftarblinda", + "lystarstol", + "gyllin\u00e6\u00f0", + "hitas\u00f3tt", + "brandur", + "raddbandakvef", + "dau\u00f0af\u00e6lni", + "flogaveiki", + "hv\u00edtbl\u00e6\u00f0i", + "ill", + "krabbinn", + "drykkjuskapur", + "heilab\u00f3lga", + "hungur", + "skorpulifur", + "drulla", + "raufar\u00e6\u00f0ahn\u00fatur", + "sting", + "bliksvefn", + "fl\u00e9tta", + "graftarb\u00f3la", + "faraldur", + "gerilveira", + "the_hives", + "hunda\u00e6\u00f0i", + "bl\u00f6\u00f0rub\u00f3lga", + "krans\u00e6\u00f0asj\u00fakd\u00f3mar", + "botnlangab\u00f3lga", + "krabbamein", + "hersli", + "p\u00edning" + ], + "LAW": [ + "r\u00f3marr\u00e9ttur", + "brotavilji", + "hegningarl\u00f6g", + "refsil\u00f6g", + "refsir\u00e9ttur", + "bandar\u00edska_alr\u00edkisl\u00f6greglan", + "r\u00e9ttarr\u00edki", + "dau\u00f0ad\u00f3mur", + "prentfrelsi", + "fundafrelsi" + ], + "RACE": [ + "frumbyggi", + "svertingi", + "japanar", + "englendingar", + "bl\u00e1ma\u00f0ur" + ], + "LANGUAGE": [ + "manskur", + "ni\u00f0urlenskur", + "\u00fe\u00fdskur", + "hollenskur", + "eistneskur", + "nor\u00f0ursam\u00edska", + "svah\u00edl\u00ed", + "nor\u00f0ma\u00f0ur", + "norska", + "persneska", + "german", + "georg\u00edska", + "hind\u00ed", + "esperanto", + "\u00fej\u00f3\u00f0verji", + "arab\u00edska", + "franska", + "japanskur", + "port\u00fagalskur", + "ido", + "kanar\u00edska", + "kom\u00edska", + "finnskur", + "hv\u00edtr\u00fassneskur", + "m\u00e1lh\u00e6fileiki", + "tonga", + "malajalam" + ], + "PRODUCT": [ + "sk\u00edrnarfontur", + "disketta", + "justin_bieber", + "k\u00falulega", + "sundsk\u00fdla", + "sigurboginn", + "disklingur", + "take_off", + "gleym_m\u00e9r_ei", + "har\u00f0so\u00f0inn", + "bretland", + "papp\u00edrsskutla", + "klaki", + "heilskj\u00e1r", + "brei\u00f0\u00feota", + "amer\u00edkubikarinn", + "botngata", + "annar_\u00ed_j\u00f3lum", + "naggr\u00edsir", + "lj\u00f3sabekkur", + "allt_er_gott_sem_endar_vel", + "the_star_spangled_banner", + "viskusteinn", + "st\u00e6r\u00f0fr\u00e6\u00f0igreining", + "\u00fer\u00edv\u00ed\u00f0ur", + "die_hard", + "j\u00f3lasveinninn", + "hringadr\u00f3ttinssaga", + "n\u00fdja_testamenti\u00f0", + "j\u00f3latr\u00e9", + "hornh\u00f6f\u00f0i", + "seglsk\u00fata", + "naggr\u00eds", + "fl\u00f6skuskeyti", + "saxland_anhalt", + "nor\u00f0urlj\u00f3s", + "ferdinand_magellan", + "hungurleikarnir", + "komm\u00fanista\u00e1varpi\u00f0", + "seglskip", + "mannr\u00e9ttindi", + "af_gu\u00f0s_n\u00e1\u00f0", + "j\u00f3lasveinn", + "blindgata", + "keisaraskur\u00f0ur", + "h\u00e1skerpusj\u00f3nvarp", + "a\u00f0alhaf", + "kaffikanna", + "kaffibolli", + "heilagur_andi", + "s\u00ed\u00f0ustu_forv\u00f6\u00f0" + ], + "JOB": [ + "gar\u00f0yrkjuma\u00f0ur", + "fulltr\u00fai", + "barnap\u00eda", + "flot\u00f6gn", + "skraddari", + "blokkflauta", + "sj\u00fakraflutningama\u00f0ur", + "framlei\u00f0andi", + "kapari", + "endursko\u00f0andi", + "make", + "borgarstj\u00f3ri", + "herma\u00f0ur", + "framkv\u00e6mdastj\u00f3ri", + "don", + "timburmenn", + "landstj\u00f3ri", + "kaups\u00fdsluma\u00f0ur", + "geislal\u00e6knir", + "skerfari", + "biskup", + "svarama\u00f0ur", + "snikkari", + "kerfiskarl", + "grip", + "timburma\u00f0ur", + "forritari", + "land", + "s\u00f3tari", + "forst\u00f6\u00f0uma\u00f0ur", + "ruslakarl", + "bartskeri", + "kaupma\u00f0ur", + "handverksma\u00f0ur", + "t\u00f3nlistarma\u00f0ur", + "koparsmi\u00f0ur", + "hvalvei\u00f0ima\u00f0ur", + "bakari", + "n\u00e6ringarfr\u00e6\u00f0ingur", + "j\u00e1rningama\u00f0ur", + "fatafella", + "heilabl\u00f3\u00f0fall", + "the_guardian", + "forstj\u00f3ri", + "sk\u00f3garh\u00f6ggsma\u00f0ur", + "markv\u00f6r\u00f0ur", + "smalama\u00f0ur", + "h\u00e1seti", + "mjaltakona", + "hlj\u00f3\u00f0f\u00e6raleikari", + "reglustika", + "yfirmatsveinn", + "\u00fe\u00fasund\u00fejalasmi\u00f0ur", + "kennslukona", + "heimilis\u00fej\u00f3nn", + "rakari", + "leigusali", + "augngrugg", + "kafteinn", + "le\u00f0urbl\u00f6kuma\u00f0urinn", + "sk\u00faffa", + "flugma\u00f0ur", + "reglulegur", + "heimilisl\u00e6knir", + "sj\u00e1lfst\u00e6\u00f0ur", + "man", + "barnal\u00e6knir", + "framkv\u00e6mdarvald", + "rottur", + "matsveinn", + "gar\u00f0yrkjufr\u00e6\u00f0ingur", + "drag\u00f3ni", + "kump\u00e1ni", + "togari", + "augnl\u00e6knir", + "brau\u00f0v\u00e9l", + "k\u00f3ngur", + "kanslari", + "skur\u00f0l\u00e6knir", + "boxari", + "kortager\u00f0arma\u00f0ur", + "brj\u00f3stm\u00f3\u00f0ir" + ], + "FAC": [ + "tollg\u00e6sla", + "hengibr\u00fa", + "l\u00f6greglust\u00f6\u00f0", + "brandenborgarhli\u00f0i\u00f0", + "verslunarmi\u00f0st\u00f6\u00f0", + "l\u00e6knastofa", + "sporgar\u00f0ur", + "j\u00e1rnbrautarst\u00f6\u00f0", + "fj\u00f6lb\u00fdlish\u00fas", + "barnask\u00f3li", + "p\u00f3sth\u00fas", + "tyrkjaveldi", + "prentsmi\u00f0ja", + "lund\u00fanaturn", + "grunnsk\u00f3li", + "brautarst\u00f6\u00f0", + "sundh\u00f6ll", + "kjarnorkuver", + "sundlaug", + "bangs\u00edmon", + "innilaug" + ], + "PERSON": [ + "k\u00f3ngssveppur", + "al_gore", + "p\u00e9tursfiskur", + "h_g_wells", + "c_v\u00edtam\u00edn", + "rudolf_hess" + ], + "BIO_CHEM_ENTITY": [ + "fj\u00f6lv\u00edn\u00fdlkl\u00f3r\u00ed\u00f0", + "s\u00edtr\u00f3nus\u00fdra", + "fitus\u00fdra", + "mj\u00f3lkurs\u00fdra" + ], + "SOC_ECO_CLASS": [ + "landb\u00fana\u00f0ur", + "jar\u00f0yrkja", + "undirheimar", + "\u00fej\u00f3\u00f0f\u00e9lag", + "rj\u00f3mi" + ], + "DATE": [ + "\u00fej\u00f3\u00f0h\u00e1t\u00ed\u00f0ardagur", + "kvartilaskipti", + "samr\u00e6\u00f0isaldur", + "sk\u00f3la\u00e1r", + "p\u00e1skavika", + "sumars\u00f3lhv\u00f6rf", + "kj\u00f6rdagur", + "er_til_lengdar_l\u00e6tur", + "vetrars\u00f3lhv\u00f6rf", + "j\u00f3ladagur", + "vetrars\u00f3lst\u00f6\u00f0ur", + "helmingunart\u00edmi", + "p\u00e1lmasunnudagur", + "bastilludagurinn", + "sprengidagur", + "til_lengdar", + "ellefta_stund", + "kyrravika", + "l\u00f6gri\u00f0ilsaldur", + "kosningadagur", + "vorpunktur", + "haustjafnd\u00e6gur", + "bl\u00f3\u00f0s\u00f6kk", + "lausnarhra\u00f0i", + "sumars\u00f3lst\u00f6\u00f0ur" + ], + "QUANTITY": [ + "frumtala", + "fermetri", + "metrakerfi\u00f0", + "franskur_franki", + "horns\u00edli", + "lj\u00f3s\u00e1r", + "algildi", + "g", + "rauntala", + "bandar\u00edkjadalur", + "algebrutala", + "sels\u00edusgr\u00e1\u00f0a", + "m\u00e6lieining" + ], + "RELIGION_MEMBER": [ + "postuli", + "kristjana" + ], + "GPE": [ + "dar_es_salaam", + "sint_maarten", + "mannr\u00e9ttindi", + "gran_canaria", + "\u00e6gisif", + "valent\u00ednusardagurinn", + "eyjahaf", + "myrkvi\u00f0ur", + "rau\u00f0ahaf", + "la_gomera", + "svartisk\u00f3gur", + "st_louis" + ], + "PERSON_PRONOUN": [ + "i", + "hennar", + "henni", + "her", + "me" + ], + "RELIGION": [ + "katarar", + "daoismi", + "sjint\u00f3ismi", + "wicca", + "kristin_v\u00edsindi" + ], + "GENDER": [ + "drengur", + "men", + "str\u00e1kur", + "sveinn", + "man", + "transf\u00f3lk", + "stelpa" + ], + "POLITICAL_PARTY_MEMBER": [ + "komm\u00fanisti", + "komm\u00fanist\u00edskur" + ], + "POLITICAL_PARTY": [ + "nasistaflokkurinn", + "f\u00f3lkaflokkurinn", + "rep\u00fablikanaflokkurinn", + "verkamannaflokkurinn", + "stj\u00f3rnm\u00e1laflokkur", + "dem\u00f3krataflokkurinn", + "jafna\u00f0arflokkurinn" + ], + "TITLE": [ + "ms" + ], + "MEDICAL_THERAPY": [ + "bl\u00f3\u00f0\u00fer\u00fdstingur" + ], + "UNION": [ + "st\u00e9ttarf\u00e9lag" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "abbad\u00eds": "\u00e1b\u00f3ti", + "fie": "son", + "d\u00f3ttir": "son", + "d\u00f3tturd\u00f3ttir": "sonarsonur", + "sonard\u00f3ttir": "sonarsonur", + "minna": "\u00fej\u00f3nn", + "m\u00f3\u00f0ir": "fa\u00f0ir", + "nunna": "munkur", + "l\u00f6greglukona": "l\u00f6gga", + "prinsessa": "furstinn", + "reyna": "k\u00f3ngur", + "drottning": "k\u00f3ngur", + "h\u00fan": "bera", + "jei": "elli", + "saur": "german", + "systir": "german", + "fr\u00f6ken": "\u00f3kv\u00e6ntur_ma\u00f0ur", + "stj\u00fapd\u00f3ttir": "stj\u00fapsonur", + "stj\u00fapa": "stj\u00fapi", + "stj\u00fapm\u00f3\u00f0ir": "stj\u00fapi", + "stj\u00fapmamma": "stj\u00fapi", + "ekkja": "ekkill", + "eiginkona": "b\u00f3ndi", + "wicca": "galdrama\u00f0ur", + "norn": "t\u00f6frama\u00f0ur", + "langl\u00fara": "galdrakarl", + "stara": "man", + "kvenma\u00f0ur": "menn", + "str\u00e1kur": "telpa", + "sveinn": "telpa", + "piltur": "st\u00falka", + "drengur": "telpa" + }, + "other_gender_swap": { + "\u00feeirra": "her", + "sitt": "her", + "\u00feau": "jei", + "jei": "\u00feeir", + "\u00feeir": "h\u00fan", + "\u00fe\u00e6r": "h\u00fan", + "hann": "\u00feeir", + "elli": "\u00feeir", + "bera": "jei", + "h\u00fan": "\u00feau", + "henni": "sitt", + "her": "sitt", + "hennar": "\u00feeirra" + }, + "en_pronoun2gender": { + "they": [ + "tv\u00edkynhneig\u00f0ur", + "transf\u00f3lk", + "samkynhneig\u00f0ur" + ], + "he": [ + "drengur", + "gaur", + "menn", + "sveinn", + "man", + "hann", + "str\u00e1kur", + "piltur" + ], + "she": [ + "kvenma\u00f0ur", + "st\u00falka", + "stelpa", + "telpa", + "stara", + "ungfr\u00fa", + "brasa", + "fr\u00f6ken" + ] + }, + "en_pronoun2pronoun": { + "he": [ + "hann", + "elli", + "bera", + "isti" + ], + "she": [ + "her", + "sitt", + "h\u00fan", + "hennar", + "henni", + "jei" + ], + "they": [ + "\u00feeir", + "sitt", + "jei", + "\u00feeirra", + "\u00fe\u00e6r", + "\u00feau" + ], + "it": [ + "ta\u00f0", + "hetta", + "\u00feessi", + "hinn", + "\u00feetta", + "henda", + "\u00fea\u00f0", + "\u00feess", + "\u00feessar", + "\u00feessir" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/ist.json b/data_tooling/pii_processing/ontology/data/ist.json new file mode 100644 index 0000000..53b022c --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/ist.json @@ -0,0 +1,61 @@ +{ + "FOOD": [ + "dazierto" + ], + "PLANT": [ + "sareza" + ], + "DISEASE": [ + "mursag\u00e0" + ], + "GENDER": [ + "mas'cio" + ], + "JOB": [ + "mare\u00eetimo", + "cunpagno" + ], + "ORG": [ + "nato" + ], + "LANGUAGE": [ + "abrieo" + ], + "PUBLIC_FIGURE": [ + "sparansa" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "muier": "mare\u00ee" + }, + "other_gender_swap": {}, + "en_pronoun2gender": { + "he": [ + "mas'cio" + ], + "she": [ + "duona" + ] + }, + "en_pronoun2pronoun": { + "they": [ + "luri" + ], + "it": [ + "quisto", + "stu", + "quista" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/it.json b/data_tooling/pii_processing/ontology/data/it.json new file mode 100644 index 0000000..12f43e4 --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/it.json @@ -0,0 +1,6272 @@ +{ + "PUBLIC_FIGURE": [ + "lawrence_durrell", + "henry_cavendish", + "matthew_arnold", + "lambert", + "benjamin_franklin", + "martin_buber", + "akira_kurosawa", + "frances_wright", + "il_principe_azzurro", + "maria_tallchief", + "noah_webster", + "jean_genet", + "john_knox", + "the_king", + "roger_williams", + "collaboratrice_familiare", + "giovanni_boccaccio", + "cornelius_vanderbilt", + "rudolf_steiner", + "thomas_wolfe", + "eccetera", + "thomas_bayes", + "ben_hogan", + "johann_bernoulli", + "max_bruch", + "giovan_battista_marino", + "leonard_bernstein", + "sibelius", + "che_guevara", + "georges_simenon", + "c", + "foramacchia", + "i_a_richards", + "controfiocco", + "thomas_hodgkin", + "john_barth", + "edward_albee", + "dorothy_parker", + "forasiepe", + "maria_callas", + "henrik_ibsen", + "mary_shelley", + "franz_werfel", + "marcello_malpighi", + "peter_lorre", + "karl_baedeker", + "david_livingstone", + "eduard_buchner", + "david_smith", + "john_herschel", + "gauss", + "andrzej_wajda", + "jan_van_eyck", + "rossini", + "carl_rogers", + "george_balanchine", + "georg_wilhelm_steller", + "richard_burton", + "douglas_macarthur", + "mary_wollstonecraft", + "lamberto", + "per_legittima_accusa", + "thomas_reid", + "winston_churchill", + "johannes_diderik_van_der_waals", + "e_cos\u00ec_via", + "b", + "conrad_aiken", + "don_chisciotte_della_mancia", + "karl_landsteiner", + "ivan_pavlov", + "paul_mccartney", + "alfredo", + "richard_smalley", + "andrew_marvell", + "terry_pratchett", + "k", + "stephen_king", + "francis_crick", + "john_trumbull", + "sherry", + "joseph_greenberg", + "isaac_newton", + "alfred_eisenstaedt", + "victor_hugo", + "joseph_smith", + "edwin_hubble", + "colette", + "carrettiere", + "milton_friedman", + "amy_lowell", + "edward_gibbon", + "il_giullare_del_re", + "mezzosoprano", + "jefferson_davis", + "saint_louis", + "tommaso", + "agostiniano", + "george_stephenson", + "john_glenn", + "john_webster", + "di_tommaso", + "john_davis", + "george_burns", + "george_harrison", + "peter_minuit", + "george_orwell", + "ronald_norrish", + "georg_meissner", + "arthur_koestler", + "richard_wagner", + "williams", + "il_prescelto", + "thornton_wilder", + "e_l_doctorow", + "pancho_villa", + "leopold_stokowski", + "rebecca_west", + "marie_curie", + "francis_galton", + "mary_martin", + "richard_roberts", + "michael_jackson", + "louis_jolliet", + "carl_sandburg", + "thomas_hobbes", + "ernst_weber", + "edward_weston", + "el_greco", + "roberto", + "samuel_beckett", + "clinton", + "david", + "galileo_galilei", + "ernest_bevin", + "jane_goodall", + "john_donne", + "chaim_weizmann", + "andrea_guarneri", + "robert_koch", + "joseph_goebbels", + "george_eastman", + "john_steinbeck", + "erich_mendelsohn", + "catherine", + "donald_glaser", + "edmund_hillary", + "vincent_van_gogh", + "richard_hooker", + "william_hazlitt", + "martina_navr\u00e1tilov\u00e1", + "marie_stopes", + "john_ruskin", + "robert_burns", + "john_henry", + "carl_anderson", + "guardaboschi", + "thomas_paine", + "bari", + "francis_beaumont", + "alessandro_farnese_il_giovane", + "steven_weinberg", + "p", + "mary_pickford", + "hans_fischer", + "emiliano_zapata", + "karl_barth", + "willem_einthoven", + "comenio", + "phil_anderson", + "marco_aurelio", + "thomas_willis", + "bernard_malamud", + "samuel_johnson", + "allen_iverson", + "anne_hutchinson", + "louise_nevelson", + "giuseppe_verdi", + "walter_lippmann", + "e", + "karl_jaspers", + "beethoven", + "hideki_yukawa", + "konrad_adenauer", + "affabulatrice", + "marianne_moore", + "norbert_wiener", + "culaccino", + "john_masefield", + "mark_rothko", + "maurice_chevalier", + "gottlieb_daimler", + "di_pi\u00f9", + "catarina", + "cambiamonete", + "frank_sinatra", + "abel_tasman", + "katharine_hepburn", + "henri_matisse", + "bertram_brockhouse", + "louis_pasteur", + "richard_strauss", + "leslie_howard", + "somateria_spectabilis", + "mahalia_jackson", + "ben_shahn", + "francesco_bacone", + "john_ford", + "non_applicabile", + "stephen_foster", + "re_art\u00f9", + "alphonse_bertillon", + "katherine_mansfield", + "gertrude_stein", + "la_maggioranza_di", + "sarah_bernhardt", + "v", + "philip_marlowe", + "luigi_pirandello", + "hank_williams", + "robert_millikan", + "rube_goldberg", + "dorothea_lange", + "james_thurber", + "riccardi", + "charles_de_gaulle", + "paul_von_hindenburg", + "y", + "henry_moore", + "holden", + "mary_mallon", + "ralph_bunche", + "rudolf_bultmann", + "charles_lindbergh", + "vincenzo_bellini", + "samuel_barber", + "tobias_smollett", + "f", + "john_jay", + "ludwig_wittgenstein", + "august_strindberg", + "thomas_mann", + "alla_nazimova", + "charles_goodyear", + "dante_alighieri", + "charles", + "margot_fonteyn", + "telecomando", + "peter_pan", + "james_tobin", + "john_irving", + "samuel_de_champlain", + "giacomo_puccini", + "edward_fitzgerald", + "fridtjof_nansen", + "louis_braille", + "herbert_marcuse", + "mungo_park", + "benedict_arnold", + "paul_verlaine", + "q", + "sergente_maggiore", + "robert_johnson", + "james_dean", + "marie_tussaud", + "roger_bannister", + "theodor_schwann", + "max_beerbohm", + "alessandro_manzoni", + "joseph_priestley", + "berlic", + "nicolas_poussin", + "andrea_mantegna", + "joseph_pulitzer", + "ring_lardner", + "george_huntington", + "jim_corbett", + "l_olandese_volante", + "james_naismith", + "affabulatore", + "oscar_wilde", + "gilberto", + "philip_roth", + "henry", + "lawrence", + "birocciaio", + "davide", + "richard_trevithick", + "william_bradford", + "heinrich_schliemann", + "willard_gibbs", + "cimiciotta_comune", + "eli_whitney", + "glenn_curtiss", + "laurence_olivier", + "pierre_larousse", + "christiaan_eijkman", + "gustavo", + "adolf_eichmann", + "marilyn_horne", + "francis_bacon", + "pete_seeger", + "joseph_heller", + "a", + "morris", + "peter_carl_goldmark", + "saladino", + "norman_rockwell", + "james_brown", + "william_hogarth", + "charles_baudelaire", + "luigi_cherubini", + "david_ricardo", + "henri_labrouste", + "mary_leakey", + "charlie_parker", + "z", + "immanuel_kant", + "james_franck", + "william_crookes", + "nellie_bly", + "weber", + "lewis", + "warburg", + "alexandre_yersin", + "n", + "marco_antonio", + "albert_schweitzer", + "costantino_i", + "john_harvard", + "johann_friedrich_herbart", + "giulio_natta", + "saint_martin", + "william_s_burroughs", + "david_hartley", + "max_planck", + "william_blake", + "julio_iglesias", + "john_bardeen", + "arthur", + "sarah_vaughan", + "john_wilkes", + "william_byrd", + "william_henry", + "christopher_fry", + "scott_joplin", + "carl_lewis", + "sarah_siddons", + "george_vancouver", + "canberra", + "bramante", + "elias_canetti", + "iorio", + "robert_lowell", + "edward_jenner", + "john_mercer", + "oscar_robertson", + "la_prescelta", + "oliver_hardy", + "da_basso", + "cole_porter", + "benjamin_west", + "jean_luc_godard", + "sagomatrice", + "graham_greene", + "frans_hals", + "edward", + "lars_onsager", + "margaret_mitchell", + "barrocciaio", + "igor_stravinsky", + "s_pronto_soccorso", + "stuart_davis", + "lola_montez", + "jan_swammerdam", + "mary_mccarthy", + "david_riesman", + "john_walker", + "william_herschel", + "joseph_black", + "marcus_whitman", + "montesquieu", + "arthur_rubinstein", + "arthur_compton", + "niels_bohr", + "kenneth_grahame", + "massimiano", + "henry_fielding", + "bertrand_russell", + "katherine_anne_porter", + "michael_faraday", + "anthony_burgess", + "jan_tinbergen", + "robert_venturi", + "johnny_appleseed", + "greg", + "irving_berlin", + "pietro_apostolo", + "baccellierato", + "giulio_cesare", + "bernard_baruch", + "rudolf_diesel", + "walt_disney", + "ben_jonson", + "la_spezia", + "joseph_schumpeter", + "gabriel_lippmann", + "steve_reich", + "lee", + "benny_goodman", + "ted_williams", + "friedrich_engels", + "jane_austen", + "charles_laughton", + "gustav_mahler", + "ed_sullivan", + "phil_collins", + "alice_paul", + "joseph_rhine", + "robert_redford", + "jean_giraudoux", + "jack_dempsey", + "brindisi", + "ian_fleming", + "richard_feynman", + "follatore", + "wolfgang_pauli", + "dall_inizio", + "subnormale", + "theodore_dreiser", + "theodor_mommsen", + "andrew_huxley", + "marcel_proust", + "jessica_mitford", + "homo_heidelbergensis", + "paul_hindemith", + "elizabeth_taylor", + "thomas_chippendale", + "paul_robeson", + "thomas_middleton", + "john_dowland", + "daniel_jones", + "william_golding", + "robert_motherwell", + "william_caxton", + "john_milton", + "rudolf_serkin", + "peter_stuyvesant", + "ethel_merman", + "giovanni_calvino", + "frank_baum", + "samuel_adams", + "albert_speer", + "james_baldwin", + "john_vanbrugh", + "indira_gandhi", + "jane_seymour", + "george_gershwin", + "alberto_giacometti", + "e_t_a_hoffmann", + "frank_whittle", + "alfred_nobel", + "jesse_owens", + "daniel_rutherford", + "marco_polo", + "macaca_nemestrina", + "john_fletcher", + "charlie_watts", + "m", + "marcel_marceau", + "allen_ginsberg", + "fred_zinnemann", + "daniel_bernoulli", + "guillaume_apollinaire", + "antoine_watteau", + "joseph_henry", + "henri_bergson", + "antonius", + "michail_bary\u0161nikov", + "edward_macdowell", + "josef_hoffmann", + "boris_karloff", + "pierre_corneille", + "phillis_wheatley", + "patrick_white", + "saul_steinberg", + "rotella_tagliavetro", + "mugnaio", + "bartholomew_roberts", + "eileen_farrell", + "catherine_howard", + "daniel_morgan", + "hans_christian_andersen", + "peter_cooper", + "reich", + "william_morris", + "cary_grant", + "hideyo_noguchi", + "thomas", + "isaac_watts", + "pieter_zeeman", + "giorgio", + "glenn_miller", + "steward", + "pablo_picasso", + "marian_anderson", + "natalie_wood", + "poggia", + "thomas_moore", + "osman_i", + "kurt_weill", + "otto_hahn", + "lester_young", + "john_marshall", + "christiaan_huygens", + "hector_berlioz", + "lucille_ball", + "paul_simon", + "claudio_monteverdi", + "re_giovanni", + "robert_scott", + "stravinsky", + "john_galsworthy", + "robert_robinson", + "mario_rossi", + "o", + "mulinaio", + "one", + "adam_smith", + "william_james", + "pietro", + "u", + "jean_harlow", + "henry_miller", + "karl_marx", + "cassio_longino", + "friedrich_nietzsche", + "costantino", + "i", + "robert_indiana", + "arnoldo", + "jimmy_durante", + "re_di_cuori", + "john_wesley", + "magellano", + "sandro_botticelli", + "carson_mccullers", + "di_riccardo", + "seiji_ozawa", + "nikola_tesla", + "al_capone", + "jim_bowie", + "charles_barkley", + "billy_graham", + "robert_schumann", + "mel_gibson", + "le_corbusier", + "carlo", + "carlo_goldoni", + "john_locke", + "alexis_carrel", + "joseph_marie_jacquard", + "henry_james", + "stephen_sondheim", + "lorenz_hart", + "perry", + "helen_keller", + "paul_dukas", + "ingrid_bergman", + "anna_kurnikova", + "leonard_bloomfield", + "jane_jacobs", + "jean_piaget", + "anna_bolena", + "radiotelecomando", + "william_congreve", + "franz_kline", + "henri_rousseau", + "paul_tillich", + "hilaire_belloc", + "frank_norris", + "frank_stella", + "robert_southey", + "h_g_wells", + "walt_whitman", + "william_wyler", + "john_osborne", + "colin_powell", + "ludwig_boltzmann", + "carl_nielsen", + "chopin", + "leopold_kronecker", + "richard_wright", + "benito", + "benjamin_thompson", + "adolf_hitler", + "nepero", + "maria_mitchell", + "fritz_haber", + "archibald_macleish", + "peter_behrens", + "alfred_stieglitz", + "stephen_spender", + "garfield", + "robert_livingston", + "george_boole", + "paul_revere", + "daniel_boone", + "buffalo_bill", + "edvard_grieg", + "robert_boyle", + "arthur_laffer", + "edith_cavell", + "dispensiere", + "alan_paton", + "picciotto", + "ralph_richardson", + "prima_donna", + "1", + "pesce_damigella", + "cordell_hull", + "james_wilson", + "rosa_parks", + "norman_jewison", + "don_chisciotte", + "samuel_goldwyn", + "x", + "ernest_walton", + "vladimir_putin", + "ceditore", + "jacob", + "baccalaureato", + "giuseppe_mazzini", + "jim_thorpe", + "hertz", + "randall_jarrell", + "arnold_sch\u00f6nberg", + "laurence_sterne", + "hutchinson", + "jacqueline_cochran", + "george_fox", + "ben_hecht", + "christopher_isherwood", + "fritz_kreisler", + "mulinaro", + "anne_hathaway", + "david_garrick", + "don_budge", + "bill_russell", + "piazzista", + "di_sana_pianta", + "baldwin", + "jeannette_rankin", + "charles_lamb", + "harry", + "g", + "forestale", + "lorenzo", + "arthur_schopenhauer", + "thomas_dekker", + "james_cagney", + "john_keble", + "johns_hopkins", + "henri_pitot", + "wanda_landowska", + "billy_mitchell", + "ottavio", + "martin_heidegger", + "hans_eysenck", + "r", + "george_lucas", + "andrew_jackson", + "edith_wharton", + "louis_armstrong", + "antony_tudor", + "steven_spielberg", + "quella_scelta", + "jean_monnet", + "robert_fulton", + "thomas_hardy", + "eddie_rickenbacker", + "quello_scelto", + "thomas_gainsborough", + "suicidarsi", + "giuseppe_garibaldi", + "philip_warren_anderson", + "alexandre_dumas", + "robert_brown", + "abelardo", + "thomas_carlyle", + "allen_tate", + "donald_barthelme", + "william_tyndale", + "bobby_fischer", + "johannes_gutenberg", + "san_lorenzo", + "agente_d_assicurazioni", + "d", + "gaetano_donizetti", + "william_faulkner", + "amerigo_vespucci", + "niccol\u00f2_copernico", + "arthur_holmes", + "pierre_boulez", + "hans_adolf_krebs", + "uomo_moderno", + "girolamo_savonarola", + "emma_goldman", + "robert_gray", + "francis_poulenc", + "james_ussher", + "john_barrymore", + "john_constable", + "james_mill", + "john_ciardi", + "putin", + "matthew_flinders", + "a_e_network", + "robert_herrick", + "joseph_campbell", + "jean_de_la_fontaine", + "robert_hooke", + "fernando_cortes", + "o_henry", + "karl_popper", + "arboricoltore", + "coleman_hawkins", + "antonio", + "george_sand", + "peter_sellers", + "homo_rhodesiensis", + "charles_fourier", + "henry_clay", + "pietro_i_di_russia", + "peter_o'toole", + "joseph_conrad", + "william_shockley", + "mahatma_gandhi", + "jim_morrison", + "jules_verne", + "paul_newman", + "robert_mills", + "george_meredith", + "robert_morris", + "woody_herman", + "alexander_wilson", + "josef_albers", + "jackson_pollock", + "il_pifferaio_di_hamelin", + "john_lennon", + "andrea_palladio", + "bob_woodward", + "charlie_chaplin", + "lillian_russell", + "j_m_barrie", + "hans_wilhelm_geiger", + "thomas_malory", + "lea", + "john_brown", + "al_jolson", + "elizabeth_gaskell", + "hugo_junkers", + "caterina", + "re_di_picche", + "lillian_hellman", + "brescia", + "fresatrice", + "carter", + "tommasi", + "dabbasso", + "john_macleod", + "giovanni_florio", + "re_lear", + "thomas_merton", + "fata_madrina", + "asa_gray", + "hannah_arendt", + "antonio_stradivari", + "robinson_jeffers", + "alice_walker", + "sir_james_murray", + "molinaro", + "miles_davis", + "edmund_cartwright", + "bruce", + "james_parkinson", + "maria_maddalena", + "george_marshall", + "harold_nicolson", + "jesse_jackson", + "willa_cather", + "stanley_kubrick", + "john_huston", + "william_gilbert", + "james_watt", + "jonathan_edwards", + "ronald_reagan", + "helmut_schmidt", + "jenny_lind", + "homo", + "frederick_douglass", + "seleuco", + "david_hilbert", + "wilhelm_reich", + "roman_jakobson", + "oliver_cromwell", + "lionel_hampton", + "martin_luther_king", + "james_hargreaves", + "frank_capra", + "william_wordsworth", + "rex_harrison", + "s", + "william_clark", + "gustav_hertz", + "george_mason", + "george_wallace", + "el_cid", + "agrippina", + "richard_rodgers", + "anne_sexton", + "morgana", + "john_dryden", + "jim_henson", + "ernest_hemingway", + "george_westinghouse", + "aquila", + "eero_saarinen", + "arthur_miller", + "john_cheever", + "cristoforo_colombo", + "gracie_allen", + "nelson_mandela", + "baldovino", + "heinrich_himmler", + "al_gore", + "john_rutledge", + "hans_bethe", + "hans_geiger", + "cesare_borgia", + "radioguida", + "roald_amundsen", + "donchisciotte", + "alessia", + "sherwood_anderson", + "richard_leakey", + "alfred_korzybski", + "patrizio_d_irlanda", + "charles_dickens", + "samuel_huntington", + "il_piccolo_lord", + "ella_fitzgerald", + "fats_waller", + "thomas_sydenham", + "jack_robinson", + "alois_senefelder", + "george_enescu", + "jacques_offenbach", + "joseph_paxton", + "william_curtis", + "william_chambers", + "leakey", + "george_stevens", + "federico_fellini", + "the_one", + "bessie_smith", + "bradley", + "patrick_henry", + "willy_brandt", + "charles_wilkes", + "francisco_pizarro", + "francisco_franco", + "jackie_robinson", + "bernardo_bertolucci", + "king_oliver", + "jan_steen", + "frank_harris", + "john_ross", + "powell", + "philibert_delorme", + "berlicche", + "andrew_mellon", + "hans_arp", + "andrew_carnegie", + "gregorio", + "franz_schubert", + "william_butterfield", + "johnny_cash", + "joseph_mccarthy", + "alfred_kastler", + "mick_jagger", + "otto_loewi", + "pistrinaio", + "georges_cuvier", + "sessions", + "colf", + "william_harvey", + "walter_scott", + "august_von_wassermann", + "peter_medawar", + "arnaldo", + "sam_houston", + "robert_browning", + "assenzio_vero", + "san_giorgio", + "john_bunyan", + "jonathan_swift", + "walter_gropius", + "albert_einstein", + "l", + "aletta_jacobs", + "thomas_edison", + "chiang_kai_shek", + "claude_bernard", + "raymond_chandler", + "henry_purcell", + "george_cohan", + "t", + "wilhelm_ostwald" + ], + "ANIMAL": [ + "bove", + "pesci", + "apodemus", + "ghiro", + "scoiattolo", + "francolino_di_monte", + "chelonioidea", + "calabrone", + "labbo", + "alfana", + "alamaro", + "buteo", + "sirratte", + "cheppia", + "gruccione", + "barbagianni", + "natasha_romanoff", + "mantide", + "homo_sapiens_sapiens", + "coregone", + "colombaccio", + "nottambulo", + "scricciolo", + "lanzardo", + "palombaccio", + "corrugata", + "beccapesci", + "il_gatto", + "topino", + "edredone", + "forapaglie", + "cecca", + "grillotalpa", + "caponare", + "il_corvo", + "vedova_nera", + "foramacchia", + "cauro", + "focena", + "virus_del_nilo_occidentale", + "lemmus_lemmus", + "sitta_europaea", + "gerboa", + "billy_elliot", + "konduz", + "pigargo", + "avvoltoio", + "mirounga_leonina", + "grandule", + "dorifora", + "ranocchio", + "zigrinata", + "artiodattilo", + "manta", + "micia", + "passera_planuzza", + "hippotragus_niger", + "uropigio", + "sitta_carolinensis", + "barbozzo", + "cavalcatura", + "pernice", + "serpentario", + "astore", + "tigrotto", + "lanzarda", + "mitilo", + "carduelis", + "lagotriche", + "carassio", + "cinomio", + "airone", + "il_corvo_e_altre_poesie", + "citello", + "flebotomo", + "felis_tigrina", + "tarabugio", + "sea_slug", + "chipmunk", + "castoro", + "mantodea", + "anuro", + "sparviero", + "lactobacillus_acidophilus", + "forapaglia", + "artropodi", + "bigatto", + "stambecco", + "beccaccino", + "monachino", + "sarcofilo", + "pesce_timone", + "lagotrice", + "pieris_brassicae", + "brachypteraciidae", + "starna", + "balenottera_boreale", + "oriolo", + "cinomologo", + "sceloporo", + "vibe", + "poana", + "verdesca", + "albanella", + "fratercula_arctica", + "il_gabbiano", + "gallinaccia", + "martes_martes", + "faina", + "perca_flavescens", + "rigogolo", + "cardello", + "scienidi", + "lama_peruana", + "fillio", + "furetto", + "nocciolaia", + "onisco", + "raven", + "homo_sapiens", + "mink", + "leone_marino", + "baribal", + "kodiac", + "cozzeca", + "ceraste", + "assiolo", + "drosofila", + "condor", + "aleuroide", + "lucertolone", + "bugherlac", + "maruzza", + "cannocchia", + "cocker", + "mugnaiaccio", + "cro_magnon", + "pennino", + "granchivoro", + "tetraoninae", + "monti_flinders", + "accipiter", + "rondone", + "pappataci", + "passerotto", + "gazza", + "sampietro", + "spalace", + "falcon", + "botuto", + "virus_del_mosaico_del_tabacco", + "ratele", + "alaccia", + "xenopo", + "thomomys_talpoides", + "banteng", + "donnola", + "squadro", + "scatarrare", + "re_degli_animali", + "croccolone", + "albanella_reale", + "l_inganno", + "pinctada_margaritifera", + "nettatoia", + "atropo", + "lutianido", + "salmo_salar", + "iller", + "forasiepe", + "altica", + "orsetto", + "taguan", + "chiromio", + "callorino", + "suslik", + "corallium_rubrum", + "martes_foina", + "pizzarda", + "millipede", + "martora", + "bozzago", + "cedrone", + "sable", + "capreolus_capreolus", + "trottatore", + "tubare", + "branta_bernicla", + "barbotto", + "crisocione", + "herpes_zoster", + "sparviere", + "cavia_cobaya", + "trampoliere", + "arthropoda", + "bozzagro", + "ragano", + "lupicante", + "ramarro", + "oniscidea", + "acheronzia", + "sputacchina", + "cantaride", + "voltolino", + "garzetta", + "capriolo", + "racano", + "lychnis_flos_cuculi", + "tamia", + "globicefalo", + "sergente_maggiore", + "alle_alle", + "borgognone", + "paolino_paperino", + "lince", + "mantis", + "primula_vulgaris", + "calandro", + "artropodo", + "cavolaia", + "petauro", + "nitticora", + "malattia_da_virus_ebola", + "mane", + "capopiatto", + "whippet", + "capodoglio", + "platanistoidea", + "salmarino", + "zeus_faber", + "salvelinus_fontinalis", + "sorello", + "yorkshire_terrier", + "lemming", + "uomo_di_cro_magnon", + "phalangista", + "abudefduf_saxatilis", + "rondine_comune", + "lemmini", + "canocchia", + "ciuffolotto", + "tortora", + "vole", + "braccare", + "gorilla_gorilla", + "capovaccaio", + "coturnice", + "bottinatrice", + "cinciarella", + "leoncina", + "martes_zibellina", + "beccaccia", + "scaglione", + "peristediidae", + "pedunculata", + "chioccia", + "eider", + "cornacchia", + "lanciardo", + "arvicola", + "capidoglio", + "picchio_verde", + "martin_pescatore" + ], + "PLANT": [ + "acer_negundo", + "cucurbita_ficifolia", + "hibiscus_syriacus", + "glaucium_flavum", + "primula_auricula", + "senecio_vulgaris", + "lilium_martagon", + "lupinus_luteus", + "mazzasorda", + "mahonia", + "albogatto", + "ardica", + "campanula_persicifolia", + "anthericum_liliago", + "marugola", + "mastic", + "pine", + "verbascum_thapsus", + "lycium_barbarum", + "carduus_crispus", + "iperico", + "parnassia", + "acetosa", + "iris_germanica", + "coeloglossum_viride", + "sorghum_halepense", + "rubus_saxatilis", + "serenella", + "morella", + "veronica_beccabunga", + "bardana", + "ornithogalum_pyrenaicum", + "liriodendron_tulipifera", + "quercus_coccinea", + "betulla_verrucosa", + "cladonia_rangiferina", + "melissa", + "cardo_campestre", + "geranium_molle", + "lattuga", + "viola_arvensis", + "sapindus", + "scutellaria_galericulata", + "avena_altissima", + "claviceps_purpurea", + "viola_reichenbachiana", + "sorbezzolo", + "the_joshua_tree", + "orniello", + "sarcoscypha_coccinea", + "liliastro", + "ceraso", + "aralia_elata", + "brassica_nigra", + "lappa", + "marrubio", + "eleocharis_dulcis", + "helleborus_niger", + "helianthus", + "salvia_minore", + "baccarello", + "santoreggia_montana", + "scagliola", + "rosa_chinensis", + "spergularia_rubra", + "lathyrus_latifolius", + "scorzonera_hispanica", + "laureola", + "sicomoro", + "marsilea_quadrifolia", + "cucurbita_moschata", + "pungitopo", + "monarda_citriodora", + "solanaceae", + "anthriscus_cerefolium", + "salvia_verbenaca", + "campanula_medium", + "juncus_articulatus", + "brunella", + "eryngium_maritimum", + "salix_babylonica", + "lisimachia", + "cyclamen_purpurascens", + "gymnocarpium_robertianum", + "inchiodacristi", + "lentisco", + "anthyllis_vulneraria", + "abies_grandis", + "laurus_nobilis", + "lathyrus_odoratus", + "clematide", + "fanciullacce", + "salice_comune", + "mordigallina", + "amanita", + "vespula_vulgaris", + "arabidopsis_thaliana", + "centaurea_nigra", + "tremella_auricula", + "santa_maria", + "bertholletia_excelsa", + "helianthus_annuus", + "avorniello", + "epipremnum_aureum", + "avena_selvatica", + "arundo", + "cirsium_eriophorum", + "vellutino", + "monarda", + "sorbus_torminalis", + "cedronella", + "elianto", + "achillea", + "magnolia_grandiflora", + "stella_alpina", + "settembrini", + "berteroa_incana", + "cardamine_bulbifera", + "colutea_arborescens", + "ebbio", + "liparis_loeselii", + "coprinus_comatus", + "papaver_alpinum", + "pseudocarpio", + "vincibosco", + "bidens_tripartita", + "cantamaggio", + "campanelle", + "prunus_laurocerasus", + "acetosella", + "allium_tuberosum", + "sanguinella_comune", + "anagallide", + "amelanchier_alnifolia", + "passiflora_ligularis", + "salix_triandra", + "atriplex_hortensis", + "cassia_angustifolia", + "agropyron_intermedium", + "pianta_carnivora", + "teucrium_scorodonia", + "acer_campestre", + "mimosa_pudica", + "pratolina_comune", + "sughera", + "rubus_caesius", + "papaver_somniferum", + "consolida_maggiore", + "chinotto", + "convolvulus", + "carex_pseudocyperus", + "gentiana_lutea", + "mercurialis_perennis", + "matthiola_incana", + "pe_tsai", + "anona", + "centocchio", + "malbianco", + "actinidia_chinensis", + "taxus_baccata", + "caprifico", + "saxifraga_granulata", + "valerianella_locusta", + "periploca_graeca", + "alcachengi", + "papaver", + "fargna", + "nymphaea_alba", + "silene_dioica", + "larice", + "euphorbia_esula", + "diplotaxis_tenuifolia", + "candida_albicans", + "pulicaria_dysenterica", + "ranunculus_ficaria", + "rosa_muschiata", + "cicerchione", + "sinfito", + "veronica_officinalis", + "asperula", + "rumex_scutatus", + "chrysanthemum_segetum", + "aconitum_lycoctonum", + "prunus_cerasus", + "tossilaggine_alpina", + "anthemis_arvensis", + "caprifoglio", + "amaranto_spinoso", + "bambagione_pubescente", + "carpino_comune", + "acacia_dealbata", + "capsicum_baccatum", + "ranuncolo_strisciante", + "rorippa_islandica", + "dianthus_caryophyllus", + "agrimonia_eupatoria", + "larix_occidentalis", + "plantago_lanceolata", + "madreselva", + "senape_selvatica", + "polystichum_lonchitis", + "ononis_spinosa", + "tassobarbasso", + "cimiciotto", + "acer_palmatum", + "thlaspi_arvense", + "agrostemma_githago", + "strigoli", + "geranium_pratense", + "salce", + "asteroide_salicina", + "moraiola", + "acero_canadese", + "salix_viminalis", + "susina", + "athyrium_distentifolium", + "calvatia_gigantea", + "crotonella_coronaria", + "calamintha_grandiflora", + "eriophorum_angustifolium", + "veronica_serpyllifolia", + "susino", + "sommacco", + "eucalyptus_globulus", + "platanus_occidentalis", + "passiflora_incarnata", + "olivastro", + "bromus_arvensis", + "polygala_vulgaris", + "arenaria_serpillifolia", + "lill\u00e0", + "hypericum_tetrapterum", + "maharatto", + "querciola", + "polystichum_setiferum", + "veronica_peregrina", + "sulla_comune", + "fanciullaccia", + "marrubio_fetido", + "tracheobionta", + "spongino", + "citrus_aurantium", + "amaranthus_spinosus", + "reseda", + "barbarea_vulgaris", + "kochia_scoparia", + "annona_cherimola", + "cinorrodo", + "cortinarius_violaceus", + "platanus_orientalis", + "piper_longum", + "prunus_armeniaca", + "castanea_dentata", + "liquidambar", + "petasites_hybridus", + "urtica", + "potamogeton_crispus", + "maclura_pomifera", + "salix_fragilis", + "amanita_muscaria", + "calla_palustris", + "psillio", + "amareno", + "leonurus_cardiaca", + "castagnaro", + "spergula_arvensis", + "asplenium_trichomanes", + "papavero", + "silene_acaulis", + "arrhenatherum_elatius", + "dracocephalum", + "pans\u00e9", + "citrus_tangerina", + "populus_balsamifera", + "nicotiana_tabacum", + "centaurea_scabiosa", + "myosotis_sylvatica", + "ulmus_americana", + "scardaccione", + "erigeron_annuus", + "acanthus_mollis", + "albugine", + "alkikinger", + "crisantemo_campestre", + "stellaria_media", + "leucanthemum_vulgare", + "solanum_nigrum", + "abies_lasiocarpa", + "campanula_rapunculus", + "acero_montano", + "serpentaria", + "diplotaxis_muralis", + "sciadopitys_verticillata", + "geranium_robertianum", + "senape", + "clematis", + "anthemis_tinctoria", + "helianthus_tuberosus", + "parthenium_argentatum", + "hedysarum_coronarium", + "lilioasfodelo_maggiore", + "lappola", + "astro_americano", + "lepista_nuda", + "hippocrepis_comosa", + "agriotto", + "solano", + "verbena_officinalis", + "prunus_domestica", + "veccia", + "phytophthora_infestans", + "fertro", + "millefoglio_montano", + "marrobio", + "muscicapa_striata", + "sorghetto", + "aquileia", + "acer_platanoides", + "rubus_idaeus", + "centocchio_comune", + "riparella", + "platantera_verdastra", + "gossypium_barbadense", + "argemone", + "erica_carnea", + "euphorbia_cyparissias", + "salvia_pratensis", + "centaurea_cyanus", + "delonix_regia", + "urtica_dioica", + "agaricus_campestris", + "gymnadenia_conopsea", + "trifolium_repens", + "blackberry", + "palloncini", + "genep\u00ec", + "oenanthe_aquatica", + "cardo_mariano", + "papavero_comune", + "solanum", + "ballota_nigra", + "sisymbrium_officinale", + "ortica", + "angelica_archangelica", + "mirobolano", + "campsis_radicans", + "cirsium_vulgare", + "echinocactus_grusonii", + "salcio", + "celoglosso", + "corypha_umbraculifera", + "mentuccia_montana", + "sorbus_aucuparia", + "abbracciabosco", + "genip\u00ec", + "acer_pseudoplatanus", + "lotus_corniculatus", + "coralloriza", + "gymnadenia_odoratissima", + "malva_selvatica", + "crisantemo", + "polyporus_squamosus", + "raphanus_raphanistrum", + "lichene_islandico", + "bozzolina", + "amaranthus_caudatus", + "saxifraga_stellaris", + "botrychium_lunaria", + "anagallis_tenella", + "gommaresina", + "fagus_sylvatica", + "scleranthus_annuus", + "mirabolano", + "cerastium_tomentosum", + "melo_selvatico", + "drosophyllum_lusitanicum", + "nontiscordardim\u00e9", + "sinapis_arvensis", + "populus_canescens", + "epilobium_angustifolium", + "vulvaria", + "sabina", + "arum", + "dracunculus_vulgaris", + "pilosella_aurantiaca", + "acacia_melanoxylon", + "gattice", + "cyperus_papyrus", + "agrostis_canina", + "saccharomyces_cerevisiae", + "ciliegia", + "listera_cordata", + "boletus_edulis", + "buckeye", + "marruca", + "campanula_trachelium", + "ranunculus_bulbosus", + "scopina", + "bergamotto", + "cerasa", + "taraxacum_officinale", + "acino_annuale", + "arenaria_serpyllifolia", + "lysimachia_vulgaris", + "daphne_cneorum", + "campanula_rotundifolia", + "phytolacca_dioica", + "sanguisorba", + "pomodorino", + "convolvolo", + "campanula_glomerata", + "millefoglie", + "dragontea", + "amarena", + "stellina_tintoria", + "actinidia_deliciosa", + "polystichum_aculeatum", + "ligustro", + "gaultheria_procumbens", + "beta_vulgaris", + "vetriola", + "cerastium_alpinum", + "pleurotus_ostreatus", + "allium_ursinum", + "pseudotsuga_menziesii", + "sagginella", + "tanacetum_parthenium", + "lithospermum_officinale", + "campanula_toscana", + "heracleum_sphondylium", + "senapa", + "drimys_winteri", + "piante_parassite", + "verbasco", + "lathyrus_sylvestris", + "spinacristi", + "marasmius_oreades", + "symphytum_officinale", + "viola_tricolor", + "viburnum_opulus", + "carlina_vulgaris", + "allium_vineale", + "limonella", + "raperella", + "gentiana_acaulis", + "elaeis_guineensis", + "calla", + "coix_lacryma_jobi", + "cavolfiore", + "prunus_serrulata", + "galium_verum", + "cycas_circinalis", + "populus_nigra", + "mentha_longifolia", + "calamenta", + "artemisia_filifolia", + "canfora", + "ranunculus_repens", + "valeriana_rossa", + "manioca", + "stellaria_holostea", + "agathis_australis", + "lemna_minor", + "muraiola", + "castagno", + "non_ti_scordar_di_me", + "pyrola_rotundifolia", + "avanese", + "idrofita", + "colocasia_esculenta", + "gommoresina", + "edelweiss", + "spiranthes_spiralis", + "gymnocarpium_dryopteris", + "cardamine_pratensis", + "erica_carnicina", + "phyllitis_scolopendrium", + "hypericum_perforatum", + "visciolo", + "allium_fistulosum", + "ippocastano", + "lychnis_coronaria", + "conyza_canadensis", + "papaveto", + "mela_selvatica", + "amaranthus_hypochondriacus", + "barbabietola", + "alnus_glutinosa", + "diplotaxis_erucoides", + "tamaro", + "arctium_minus", + "pinus_muricata", + "paris_quadrifolia", + "agropyron_repens", + "phytolacca_americana", + "lathyrus_sativus", + "cavolino", + "oxalis", + "veronica_arvensis", + "anthriscus_sylvestris", + "belladonna", + "asplenio_tricomane", + "aggirare", + "pteridium_aquilinum", + "paradisea", + "cinnamomum_cassia", + "panicum_capillare", + "terzanella", + "smilax_aspera", + "salvia_sclarea", + "aristolochia_clematitis", + "savina", + "cephalanthera_rubra", + "cypripedium_calceolus", + "sorbolo", + "miosotide", + "viola_odorata", + "poa_nemoralis", + "lauroceraso", + "olivo", + "amaranthus_albus", + "campanula_serpeggiante", + "iris_florentina", + "piscialetto", + "santoreggia_domestica", + "arctostaphylos_uva_ursi", + "chrysanthemum", + "agrimonia", + "battitoio", + "capraggine", + "vallisneria", + "mentastro", + "holcus_mollis", + "crambe_maritima", + "platanthera_chlorantha", + "euphorbia_milii", + "robbio", + "paradisea_liliastrum", + "pinastro", + "peste_d_acqua_comune", + "castanea", + "kiwicha", + "vitalba", + "physalis_peruviana", + "sambucus_ebulus", + "salice", + "rubus_odoratus", + "grisantemo", + "brasca_increspata", + "tignosa", + "hamamelis_virginiana", + "calystegia_sepium", + "magnolia", + "mostarda", + "cardo_asinino", + "pterocarpus_macrocarpus", + "ciliegio", + "hevea_brasiliensis", + "ranunculus_aquatilis", + "avena_barbata", + "polypodium_vulgare", + "conium_maculatum", + "plantago_media", + "ranunculus_acris", + "cirsium_arvense", + "gramigna_intermedia", + "campanella_turchina", + "verbascum_lychnitis", + "millefoglio", + "sandalo", + "platanthera_bifolia", + "aerofita", + "solanum_quitoense", + "rosa_selvatica" + ], + "JOB": [ + "birocciaio", + "furiere", + "cancerologo", + "liutaio", + "persona_grata", + "droghiera", + "battifiacca", + "lancere", + "sceriffo", + "alienista", + "allogatore", + "tiretto", + "paranza", + "fondatore", + "ginecologa", + "guru", + "allibratore", + "capocronista", + "tappezziere", + "figulo", + "sonorista", + "mercator", + "manifatturiere", + "sweep", + "bottaio", + "conciaiolo", + "presidentessa", + "prestinaio", + "moschettiere", + "badilante", + "mulattiere", + "stagista", + "il_console", + "fattoressa", + "maniscalco", + "mestolone", + "canoista", + "laringologo", + "motopeschereccio", + "speaker", + "serraturiere", + "ginecologo", + "vetraio", + "compendiatore", + "cardiologo", + "granatiere", + "the_analyst", + "carradore", + "agrimensore", + "lessicografo", + "ribattitore", + "mandriana", + "assistente_sociale", + "pettinatore", + "sarto", + "stagnaio", + "doratore", + "the_cutter_il_trafficante_di_diamanti", + "make", + "trovarobe", + "scioperante", + "acquirente", + "stagnino", + "cancelliere", + "tesoriere", + "puericultore", + "lettrice", + "metronotte", + "catechista", + "esercente", + "agricoltrice", + "tessitore", + "coppiere", + "the_dentist", + "procaccino", + "droghiere", + "guerriera", + "estetista", + "spazzacamino", + "quartiermastro", + "prima_cittadina", + "schivafatiche", + "bagnino", + "speziale", + "ramaio", + "incassatore", + "endocrinologo", + "fornaio", + "strinare", + "the_lifeguard", + "ristoratrice", + "frenatore", + "colf", + "coniglietto", + "territoriale", + "connestabile", + "proprietaria", + "fresatrice", + "impagliatore", + "fabbricante", + "bagnaiolo", + "cacciatrice", + "endocrinologa", + "governatore", + "addestratore", + "d_artagnan", + "puericoltore", + "reumatologa", + "sexton", + "elettrotecnico", + "cardex", + "follatore", + "saldacontista", + "cattedratico", + "lanciere", + "capoccio", + "tassidermista", + "intrattenitore", + "parruccaio", + "scaricatore", + "don", + "ricoglitore", + "capofabbrica", + "parteggiante", + "scalpellino", + "escavatorista", + "guidatore", + "locomotorista", + "panettiera", + "quando_ho_aperto_gli_occhi", + "portinaio", + "coyote", + "gerontologo", + "conciaio", + "mazziere", + "la_tata", + "lavorante", + "registratore", + "cordaio", + "camerinista", + "the_police", + "lo_spaventapassere", + "inventore", + "muratore", + "peacemaker", + "pastora", + "macchinista", + "terapeuta", + "il_broker", + "dattilografa", + "the_sentinel", + "legatore", + "vetrinista", + "maresciallo", + "tagliaboschi", + "bailo", + "la_maggiore", + "ostetrica", + "proctologa", + "broker_d_assicurazioni", + "angiologo", + "perchia", + "sommelier", + "cannoniere", + "barbiere", + "boscaiolo", + "manovratore", + "protocollista", + "compositore", + "segretario", + "doge", + "gentleman", + "cavalleggero", + "sindacalista", + "lapidario", + "mammana", + "stallino", + "aguzzina", + "ramazzare", + "correttore", + "episcopo", + "corriere", + "esattore", + "caporeparto", + "dispensiere", + "giardiniere", + "ematologo", + "camallo", + "locandiera", + "ramponiere", + "sostentatore", + "paracadutista_militare", + "stradino", + "baleniera", + "para", + "valletto", + "pittrice", + "proctologo", + "arredatore", + "fonditore", + "unionista", + "neuropsichiatra", + "facchino", + "indoratore", + "the_scientist", + "artefice", + "una_notte_da_leoni", + "chiappacani", + "coniglietta", + "vetturino", + "calderaio", + "couturier", + "mastermind", + "portatore", + "rilegatore", + "manovale", + "daziere", + "irroratore", + "internunzio", + "apportatore", + "autrice", + "l_orologiaio_di_saint_paul", + "cartografo", + "trainer", + "land", + "insaponare", + "boss", + "capocuoco", + "vigilante", + "compratore", + "portamazze", + "pompiere", + "il_cacciatore", + "una_donna_in_carriera", + "apoplessia", + "spazzino", + "fittacamere", + "mancipe", + "urinare", + "ingegnere", + "giardinaio", + "sbucciatore", + "governante", + "chiavaio", + "velista", + "saggista", + "scudiero", + "balivo", + "casellante", + "ausiliario", + "cavalleggiero", + "cartaio", + "jeff_richards", + "internare", + "scultrice", + "armaiolo", + "dettagliante", + "cutter", + "barrocciaio", + "colonnello", + "treviri", + "lattoniere", + "idrologo", + "retore", + "alto_commissario", + "buttero", + "freelance", + "scientist", + "leader", + "legatrice", + "trattatore", + "spaccalegna", + "vigile_del_fuoco", + "fantaccino", + "capraia", + "panificatore", + "feldmaresciallo", + "kamikaze", + "osteopata", + "solcatore", + "assessore", + "the_advocate", + "cerusico", + "orticultore", + "dermatologo", + "una_prova_per_non_morire", + "staffiere", + "fondatrice", + "portabandiera", + "sagomatrice", + "art\u00e9fice", + "borgomastro", + "reggente", + "didatta", + "trebbiatrice", + "levatrice", + "compratrice", + "rivenditore", + "riparatore", + "calligrafo", + "sonatore", + "diportista", + "portalettere", + "cassetto", + "barelliere", + "fumettista", + "visagista", + "trombaio", + "salsamentario", + "il_dottor_arrowsmith", + "fornaia", + "stalker", + "trascrittore", + "salesman", + "sovrintendente", + "buttafuori", + "the_guardian", + "blackleg", + "polizza_flottante", + "dermatologa", + "attendente", + "fattorino", + "lancia_spezzata", + "tagliapietre", + "molinaro", + "attanagliare", + "mezzadro", + "mingere", + "helena_bertinelli", + "disegnatore", + "portuale", + "allergologo", + "schiavo", + "mercantessa", + "mulinaro", + "carceriere", + "setter", + "complottista", + "collaboratrice_familiare", + "conciapelli", + "boaro", + "barellante", + "bottegaia", + "conciatore", + "epitomatore", + "tornitore", + "mercante", + "cassiere", + "cardiochirurgo", + "mate", + "ebanista", + "callista", + "legnaiolo", + "carrettaio", + "fontaniere", + "zelatore", + "fanalista", + "riveditore", + "guerriero", + "impiegato", + "sindaco", + "banchiere", + "stuccatore", + "cardiologa", + "idrologa", + "gassista", + "falegname", + "a_voce_alta_the_reader", + "designer", + "parrucchiera", + "carango_mediterraneo", + "coscritto", + "sterratore", + "passacarte", + "stagionale", + "offerente", + "lattaia", + "parteggiatore", + "pavoneggiarsi", + "antesignano", + "pilota_collaudatore", + "barrister", + "crumira", + "affittacamere", + "razzolatore", + "coltivatore", + "ricopiare", + "messo", + "sommergibilista", + "immunologo", + "piantatore", + "corazziere", + "crumiro", + "falconiere", + "translatore", + "becchino", + "regista", + "idrogista", + "romanziere", + "caporale", + "mercatante", + "tenente", + "pellaio", + "dimostratore", + "patrocinatore", + "ammaestratore", + "precettrice", + "neurochirurgo", + "carrista", + "infermiere", + "gaucho", + "hostess", + "intagliatore", + "impaccatore", + "casaro", + "pincerna", + "capopartito", + "barilaio", + "internista", + "carruca", + "mulinaio", + "district_attorney", + "cannista", + "cantero", + "basters", + "the_principal_una_classe_violenta", + "pettinatrice", + "aggiudicatario", + "scultore", + "dattilografo", + "parrucchiere", + "mappatore", + "sottotenente", + "cineoperatore", + "propugnatore", + "the_economist", + "collier", + "manager", + "ristoratore", + "paramedico", + "broker", + "wetter", + "carter", + "dispensatore", + "paradontologo", + "mandriano", + "lampionaio", + "biscazziere", + "gerontoiatra", + "stripper", + "the_dressmaker", + "raffinatore", + "vignettista", + "allenatore", + "il_servo_di_scena", + "neurologo", + "mitragliere", + "sottufficiale", + "dimostrante", + "barista", + "freniatra", + "latore", + "allevatore", + "warrior", + "laringologa", + "carpentiere", + "mercadante", + "forestale", + "galoppino", + "para_yugoslavo", + "acquafortista", + "perfezionatore", + "ispettore", + "vasellaio", + "regolatore", + "tutti_contro_tutti", + "bottegaio", + "parlatore", + "patrocinante", + "doc", + "buffatore", + "gestore", + "catalogatore", + "bottegante", + "scienziata", + "colpo_apoplettico", + "tuttofare", + "idrogisto", + "lanciatrice", + "torcitore", + "fitoterapeuta", + "the_boxer", + "bambinaia", + "colpitore", + "conduttore", + "armiere", + "miodesopsia", + "stilista", + "lattaio", + "the_hire", + "bagnante", + "tessitrice", + "usher", + "messenger", + "annunziatore", + "cabinista", + "lavoratrice", + "chauffeur", + "pisciare", + "orticoltore", + "falangio", + "procaccia", + "au_pair", + "fenditore", + "danzatrice", + "sentry", + "proconsul", + "mercatore", + "carangidi", + "capintesta", + "gabelliere", + "baleniere", + "stampante", + "convivente", + "bracciante", + "schiava", + "diurnista", + "sviluppatore", + "tagliatrice", + "the_interpreter", + "cameraman", + "romanzatore", + "sagrista", + "capotrib\u00f9", + "strumentista", + "maniscalca", + "curatore", + "vasaio", + "l_uomo_senza_sonno", + "amanuense", + "il_padrone_di_casa", + "pastorella", + "cartonista", + "il_correttore_di_bozze", + "elemosiniere", + "porgitore", + "mezzamanica", + "carbonaio", + "ussero", + "capraio", + "assumibile", + "croupier", + "bridgista", + "istruttore", + "stenografo", + "il_professore", + "steward", + "tossicologo", + "carratore", + "vasaia", + "spalatore", + "reumatologo", + "spogliarellista", + "segretaria", + "interprete", + "reggitore", + "autotrenista", + "massaio", + "collezionista", + "doula", + "cappellone", + "carrettiere", + "timoniere", + "caramellaio", + "antologista", + "conciario", + "fucinatore", + "sub", + "soprintendente", + "parer", + "sagrestano", + "saprofagia", + "statuario", + "the_independent", + "solicitor", + "bishop", + "strumentalista", + "abbreviatore", + "sindaca", + "di_propria_iniziativa", + "terapista", + "coolie", + "associato", + "cookie", + "infermiera", + "taglialegna", + "figulinaio", + "suonatore", + "panettiere", + "mugnaio", + "cineasta", + "intagliatrice", + "esquire", + "carraio", + "tutto_fare", + "annunciatore", + "caporione", + "capocameriere", + "danzatore", + "sergente", + "attacchino", + "marmittone", + "orinare", + "linotipista", + "crestaia", + "ferracavallo", + "panificatrice", + "direttore_finanziario", + "barbitonsore", + "cartoonist", + "pastore", + "regnante", + "giuntatrice", + "nostromo" + ], + "DISEASE": [ + "rettocele", + "rigonfiatura", + "sars", + "singhiozzare", + "grattatura", + "galattosemia", + "attaccabottoni", + "condroma", + "minorazione", + "rangolare", + "chirospasmo", + "stipsi", + "embriogenesi", + "voltastomaco", + "faringite", + "spellamento", + "piressia", + "sbornia", + "misofobia", + "fondatore", + "quadriplegia", + "oftalmite", + "patimento", + "ki", + "polio", + "orticaria", + "piastrinopenia", + "glicosuria", + "suppurare", + "ernia", + "rubeola", + "polidipsia", + "cardiopalma", + "lichene", + "amigdalite", + "sociofobia", + "accanimento", + "paradontosi", + "rage", + "panereccio", + "paresi", + "sternutare", + "corizza", + "cheratomalacia", + "palatoschisi", + "astasia", + "analgesia", + "trancio", + "tanatofobia", + "androfobia", + "angosciare", + "abrasione", + "fotofobia", + "salmonellosi", + "tossicomania", + "capogiro", + "martoriare", + "raschio", + "cacherella", + "scottamento", + "lividura", + "denutrizione", + "vogata", + "scottatura", + "batteriofago", + "progeria", + "laringite", + "poison_ivy", + "acconciare", + "bruciacchiatura", + "rottorio", + "sottoalimentazione", + "catalessi", + "sciatica", + "strazio", + "ginecomastia", + "psiconevrosi", + "gestazione", + "dolenzia", + "mouse", + "soffocamento", + "rachitismo", + "pancreatite", + "ammaccamento", + "xerodermia", + "croup", + "sciatalgia", + "lambdacismo", + "cianosi", + "ebrezza", + "frattura", + "mielite", + "crioanestesia", + "defaillance", + "accorazione", + "gambestorte", + "strinatura", + "starnutire", + "brachidattilia", + "parametrite", + "valvulite", + "accecamento", + "accorciato", + "gibbosit\u00e0", + "anemia_aplastica", + "incenerire", + "presbitismo", + "singhiozzo", + "presbiopia", + "infiammazione", + "gotta", + "follicolite", + "beriberi", + "psiconeurosi", + "mania", + "mastalgia", + "nicotinismo", + "ingrossamento", + "the_bends", + "risipola", + "anemia_drepanocitica", + "xeroderma", + "sferzante", + "ustione", + "struma", + "cheratoacantoma", + "phytophthora_infestans", + "tossire", + "la_citt\u00e0_delle_navi", + "cardite", + "dolere", + "la_stangata", + "lussazione", + "peste_nera", + "coriza", + "beccatura", + "trichomoniasi_vaginale", + "ms", + "gengivite", + "sordomutismo", + "indisposizione", + "sternutire", + "scotoma", + "orecchioni", + "brucellosi", + "distrofia", + "galattocele", + "autoimmunit\u00e0", + "cacaiola", + "the_suffering", + "bottacciolo", + "colera", + "rust", + "padre_fondatore", + "proteinuria", + "torpore", + "stiratura", + "anchilosi", + "attorcigliare", + "cheratocono", + "radiosit\u00e0", + "setticemia", + "amartoma", + "arrossire", + "esse_moscia", + "maidismo", + "barbugliamento", + "crucciare", + "teratoma", + "blacklash", + "pirosi", + "estumescenza", + "empetiggine", + "cardiomegalia", + "albuminuria", + "postema", + "mastodinia", + "podoflemmatite", + "corrasione", + "tenesmo", + "dissenteria", + "catarro", + "calcolosi_renale", + "rosacea", + "allineato", + "piemia", + "para", + "avvelenamento", + "cacarella", + "pirofobia", + "coronario", + "malessere", + "gavocciolo", + "atassia", + "nascenza", + "handicap", + "la_peste", + "collasso", + "tarantismo", + "anchiloglossia", + "itterizia", + "tracheite", + "pertosse", + "ustionare", + "pernio", + "emangioma", + "mieloma", + "bruciore", + "oftalmoplegia", + "ciucca", + "contusione", + "fratturarsi", + "giracapo", + "beri_beri", + "spinale", + "wale", + "schistosomiasi", + "disidratazione", + "gravida", + "stitch", + "radianza", + "tireotossicosi", + "vaccina", + "politezza", + "gravidanza", + "escoriazione", + "miliaria", + "la_passione_di_cristo", + "rickettsiosi", + "costipazione", + "stitichezza", + "ammaccarsi", + "cecit\u00e0", + "starnuto", + "collasso_cardiaco", + "lussatura", + "panareccio", + "accoramento", + "turgore", + "mercurialismo", + "grafospasmo", + "sottalimentazione", + "strozzamento", + "manio", + "squacquera", + "crepitazione", + "chi", + "giramento", + "stiramento", + "piedecavo", + "strangolamento", + "indolenzimento", + "pollinosi", + "talismo", + "qi", + "erisipela", + "preeclampsia", + "granuloma", + "patereccio", + "supplizio", + "strangolazione", + "stabbiolo", + "rapacit\u00e0", + "pinguetudine", + "rosolia", + "gravidanza_indesiderata", + "formentone", + "bradicardia", + "spina_bifida", + "beguk", + "rifulgenza", + "silicosi", + "adiposit\u00e0", + "pamplegia", + "martellatore", + "claustrofobia", + "distimia", + "indurimento", + "gimp", + "dolorare", + "vinismo", + "calazio", + "abasia", + "frenzy", + "risplendenza", + "cachessia", + "alexia", + "herpes", + "angustiare", + "tachicardia", + "poliomielite", + "morsicata", + "strabismo", + "ritocchino", + "proctite", + "fissaggio", + "risciacquo", + "menorragia", + "ammalarsi", + "meteorismo", + "orzaiolo", + "indietreggiamento", + "morsicare", + "smart", + "tossicodipendenza", + "amelia", + "paralisi", + "callosit\u00e0", + "cerebrolesione", + "tiroidismo", + "bubbone", + "tenerezza", + "vena_varicosa", + "boglire", + "cardiomiopatia", + "ed", + "malattia", + "breakdown", + "blister", + "intertrigine", + "storcere", + "sigmatismo", + "pica", + "sopraffollamento", + "gassare", + "papilloma", + "spellatura", + "spezzarsi", + "claudicazione", + "congiuntivite", + "natriuresi", + "tracoma", + "vescicante", + "morsicatura", + "sclerosi_multipla", + "trasposizione", + "attorcigliarsi", + "acetonemia", + "bloom", + "fruttosuria", + "gommosi", + "mordere", + "costipamento", + "indiscrezione", + "litiasi", + "lombaggine", + "ritagliato", + "appendicite", + "mastoidite", + "listeriosi", + "seviziare", + "collassare", + "sensation", + "indigestione", + "oftalmia", + "starnutare", + "borsite", + "achilia", + "peste_bovina", + "contrastare", + "parestesia", + "poliovirus", + "cardiopatia", + "paludismo", + "fugue", + "pain", + "congestione", + "kernittero", + "muscolosit\u00e0", + "mastadenite", + "ingrossatura", + "malacia", + "arbovirus", + "incisura", + "svergolamento", + "contorcere", + "giradito", + "freschezza", + "talassemia", + "palla_smorzata", + "papilledema", + "ringrosso", + "sequela", + "superinfezione", + "vasculite", + "fonofobia", + "contagio", + "complicazione", + "ill", + "strangolatura", + "crampo", + "paraplegia", + "an_qi", + "pull", + "bruciamento", + "brachicardia", + "tarantolismo", + "areflessia", + "escara", + "virus_dell'herpes_simplex", + "stranguglione", + "gobbo", + "pellagra", + "aviaria", + "sterilit\u00e0", + "mongolismo", + "aeroembolismo", + "menomazione", + "mi", + "bruciatura", + "stomatite_gangrenosa", + "acantosi_nigricans", + "folgorazione", + "tosse", + "reclamazione", + "para_yugoslavo", + "aura", + "scalfittura", + "arousal", + "gelidezza", + "sting", + "in_sovrappeso", + "blastoma", + "chinetosi", + "labirintite", + "ostruzionismo", + "policitemia", + "the_bleeding", + "tumore_maligno", + "polimiosite", + "contundere", + "siderosi", + "livellato", + "emmetropia", + "pancitopenia", + "gomitata", + "break", + "erpete", + "coronaropatia", + "la_nausea", + "tagliato", + "tintarella", + "superaffollamento", + "pizzicata", + "singulto", + "senofobia", + "trauma", + "tossiemia", + "shigellosi", + "lichen_planus", + "fondatrice", + "cardiopalmo", + "kuru", + "burn", + "carbonchio", + "assuefazione", + "stenosi", + "polmonite", + "strappamento", + "scandalizzare", + "catalessia", + "noma", + "sommovimento", + "the_hives", + "lessare", + "ibernazione", + "paratifo", + "fersa", + "malattia_congenita", + "astrafobia", + "mastite", + "assodamento", + "polidattilia", + "arrangolare", + "dengue", + "anasarca", + "lordosi", + "colecistite", + "sevizie", + "fendente", + "le", + "rossore", + "lustrezza", + "vergognare", + "salmonella", + "fonditore", + "verruca", + "normotermia", + "schizotimia", + "stimmate", + "lebbra", + "dolorante", + "carboncello", + "epidermolisi_bollosa", + "tremante", + "schizoide", + "malcaduco", + "lombalgia", + "malaria" + ], + "LOCATION": [ + "al_jazeera", + "rocca_imperiale", + "mar_cinese_orientale", + "plantago_lanceolata", + "mar_tirreno", + "e_allora", + "di_nulla", + "il_meglio_del_meglio", + "the_good_night", + "trifolium_pratense", + "so_what", + "la_manica", + "acquasanta", + "mar_nero", + "dryocopus_martius", + "columbus_day", + "il_giardino_dei_ciliegi", + "non_plus_ultra", + "mar_del_nord", + "lago_st_clair", + "eryngium_maritimum", + "bow_wow", + "united_states_army", + "isola_rotatoria", + "monte_degli_ulivi", + "s_tog", + "piet_mondrian", + "la_roche_en_ardenne", + "trifolium_repens", + "servizio_ferroviario", + "sint_maarten", + "buonasera", + "petasites_hybridus", + "autocommutatore", + "due_fratelli", + "chang_jiang", + "chelus_fimbriata", + "da_nessun_altra_parte", + "man_o_war", + "kryvyj_rih", + "non_c_\u00e8_di_che", + "trois_rivi\u00e8res", + "aer_ch\u00f3r_na_h\u00e9ireann", + "monti_guadalupe", + "capo_horn", + "centrale_telefonica", + "cul_di_sacco", + "land", + "non_c_\u00e8_problema", + "sulla_terrazza", + "saint_vincent", + "iris_pseudacorus", + "sulla_strada", + "the_black_hole_il_buco_nero", + "blue_mountains", + "maria_maddalena", + "pieris_rapae", + "ci_sono", + "medio_oriente", + "acqua_pesante", + "aviazione_militare", + "joseph_louis_gay_lussac", + "accademia_militare", + "plantago_major", + "sassonia_anhalt", + "falkland", + "roseto", + "nuphar_lutea", + "di_niente", + "mar_giallo", + "capodanno", + "eventualmente", + "plantago_media", + "ingegneria_civile", + "babbo_natale", + "australia_occidentale", + "buonanotte", + "v_eri", + "banca_centrale", + "alnus_glutinosa", + "usa", + "terra_bruciata", + "saint_lucia", + "la_bella_addormentata", + "hat_yai", + "arena", + "pandispagna", + "sri_lanka", + "lago_dei_boschi", + "lago_superiore", + "scutellaria_galericulata", + "the_rolling_stones", + "cordon_bleu", + "monte_carmelo", + "in_caso", + "grande_dorsale", + "pollicino", + "\u00e8_un_piacere", + "al_ayn", + "downtown", + "lago_tana", + "orto_botanico", + "pieris_brassicae", + "heitor_villa_lobos", + "la_terza_via", + "orsa_maggiore", + "a_tre_gambe", + "ospedale_psichiatrico", + "resecare", + "portorico", + "delonix_regia", + "strada_senza_uscita", + "red_water_terrore_sott_acqua", + "prunus_avium" + ], + "ORG": [ + "dominion", + "ida", + "san_marco", + "reparto_vendite", + "frammassoneria", + "agenzia_turistica", + "radiotelevisione", + "germanistica", + "san_nicola_di_bari", + "marineria", + "politecnico", + "il_silenzio_degli_innocenti", + "wicca", + "radiogalassia", + "an_education", + "marina_militare", + "trasporto_pubblico", + "jan_mayen", + "marina_reale", + "messaggeria", + "natasha_romanoff", + "aa", + "di_ultima_generazione", + "democrazia_diretta", + "nasa", + "tre_sorelle", + "chi_sei", + "arda", + "seicento", + "bollywood", + "i_soliti_sospetti", + "a_spizzichi", + "partito_nazionalsocialista_dei_lavoratori_tedeschi", + "ivano_frankivs'k", + "punto_interrogativo", + "europol", + "mano_d_opera", + "violenza_domestica", + "the_who", + "assemblea_nazionale_della_repubblica_serba_di_bosnia_ed_erzegovina", + "manodopera", + "capetingi", + "non_plus_ultra", + "assemblea_nazionale", + "haganah", + "gli_amici_di_pap\u00e0", + "massoneria", + "to_the_core", + "in_comune", + "stanotte", + "college", + "laburismo", + "san_francisco", + "in_flagranza", + "un", + "a_chorus_line", + "war_machine", + "fiume_giallo", + "fondo_pensione", + "la_pratica_rende_esperti_sbagliando_s_impara", + "partito_social_democratico", + "epistrofeo", + "nunziatura", + "da_prima", + "v\u0129nh_long", + "camera_bassa", + "a_poco_a_poco", + "madonna_addolorata", + "albero_genealogico", + "zona_industriale", + "sant_elena", + "nuovo_mondo", + "col_legno", + "viceversa", + "consiglio_municipale", + "mar_rosso", + "periodo_d_oro", + "dipartimento_ministeriale", + "partito_popolare", + "brahmanismo", + "gao", + "casa_automobilistica", + "alessandro_magno", + "the_family_man", + "partito_liberale", + "castel_campagnano", + "partito_del_lavoro", + "saint_vincent", + "farragine", + "agenzia_pubblicitaria", + "l_oca_selvaggia_colpisce_ancora", + "john_tuzo_wilson", + "gironda", + "mai_pi\u00f9", + "the_faculty", + "san_basilio", + "partito_nazionale", + "impazzire", + "alto_commissariato", + "centrale_termica", + "the_new_school", + "ai", + "istituto_di_emissione", + "fuoriclasse", + "chiang_mai", + "aeronautica_militare", + "poco_alla_volta", + "dia", + "consiglio_aziendale", + "codice_civile", + "ditta_farmaceutica", + "classe_operaia", + "winnie_pooh", + "taoismo", + "villanova_di_camposampiero", + "maestranze", + "vi_voglio_bene", + "islamistica", + "sfaccendare", + "partito_ambientalista_i_verdi", + "ambasceria", + "discarico", + "chiesa_cattolica_romana", + "la_bemolle_maggiore", + "diritti_civili", + "le_mans", + "perch\u00e9_no", + "mi_chiamo", + "novilunio", + "don_giovanni", + "classe_lavoratrice", + "con_le_mani_nel_sacco", + "demosociale", + "di_sola_andata", + "rabindranath_tagore", + "trapassato", + "gestapo", + "mar_dei_caraibi", + "assennatezza", + "rubacuori", + "giardino_botanico", + "chiesa_cattolica", + "carabattole", + "l_unione_fa_la_forza", + "addolorata", + "winnie_the_pooh", + "la_commedia_degli_errori", + "dindarolo", + "partito_laburista_australiano", + "boscoducale", + "fisco", + "muratura", + "tra_virgolette", + "li_fi", + "casa_farmaceutica", + "diritto_romano", + "manovalanza", + "impero_tedesco", + "un_altra_volta", + "se_uomo", + "assemblea_nazionale_francese", + "who_are_you", + "catadiottro", + "arma_bianca", + "malattia_venerea", + "chiang_rai", + "al_jazeera", + "costellare", + "ginnasio", + "valenzia", + "eccelso", + "chewing_gum", + "disa", + "collettivamente", + "visnuismo", + "il_meglio_del_meglio", + "europe", + "po", + "cristianesimo_scientista", + "a_team", + "mossad", + "nautilus_pompilius", + "notte_di_san_silvestro", + "ordine_professionale", + "la_manina", + "hollywood", + "dopo_cristo", + "lo_stato_dell_arte", + "battaglione", + "ti_voglio_bene", + "man_mano", + "sinedrio", + "semiprezioso", + "saint_barth\u00e9lemy", + "maestranza", + "partito_verde", + "sturmabteilung", + "ed_altri", + "luna_nuova", + "los_angeles", + "nato", + "mass_media", + "partito_repubblicano", + "baltimore_orioles", + "terra_bruciata", + "anno_domini", + "ad_hoc", + "socialist_party_of_england_and_wales", + "i_segreti_di_twin_peaks", + "brahmanesimo", + "fondo_pensioni", + "a_pezzi_e_bocconi", + "turno_di_giorno", + "partito_dell_uguaglianza", + "mi", + "san_niccol\u00f2", + "san_silvestro", + "villaggio_olimpico", + "by_the_way", + "students_union", + "alla_polacca", + "in_situ", + "sacra_famiglia", + "sa", + "doc", + "al_ayn", + "padronato", + "shintoismo", + "la_bella_addormentata", + "un_uomo_in_mare", + "giovani_turchi", + "battismo", + "alta_fedelt\u00e0", + "cianfrusaglie", + "panperso", + "proprietari_terrieri", + "istituzione_medica", + "americanistica", + "il_gatto_nero", + "unione_internazionale_delle_telecomunicazioni", + "congiuntamente", + "commerce", + "casa_bianca", + "minutaglia", + "blue_jeans", + "alta_frequenza", + "streptococcus_pyogenes", + "eu", + "gomma_da_masticare", + "i_griffin", + "san_giovanni_battista", + "chang_jiang", + "assieme", + "giovani_arrabbiati", + "pollicino", + "il_faro_incantato", + "hirundo_rustica", + "hautes_fagnes", + "la_sfida_di_landover", + "inizialmente", + "in_vitro", + "corte_suprema", + "maria_dolorosa", + "elementari", + "gomma_americana", + "ninni_puf", + "s\u00e3o_tom\u00e9", + "vaishnavismo", + "madre_dolorosa" + ], + "POLITICAL_PARTY": [ + "gironda", + "laborismo", + "partito_socialdemocratico", + "kuomintang", + "partito_socialista", + "liberal_party", + "partito_democratico_repubblicano", + "partito_laburista", + "partito_whig", + "partito_progressista", + "partito_democratico", + "partito_conservatore", + "laburismo", + "partito_comunista", + "partito_proibizionista" + ], + "PRODUCT": [ + "bananiera", + "st_vincent", + "autoblindo", + "per_la_grazia_di_dio", + "deja_vu", + "justin_bieber", + "la_scala_musicale", + "migliorarsi", + "salvavita", + "prima_guerra_mondiale", + "unione_sovietica", + "miosotide", + "s_tog", + "monte_sant_elena", + "la_macchina_del_tempo", + "grande_berta", + "al_jazeera", + "all_ultimo_momento", + "le_quattro_stagioni", + "diego_garcia", + "echinopsis_pachanoi", + "la_dodicesima_notte", + "paternostro", + "battistero", + "analisi_matematica", + "corto_circuito", + "il_pellegrinaggio_del_cristiano", + "monti_balcani", + "la_colazione_dei_campioni", + "diritti_umani", + "il_mastino_dei_baskerville", + "buond\u00ec", + "saint_vincent", + "il_signore_degli_anelli", + "the_star_spangled_banner", + "macchina_truccata", + "tanto_rumore_per_nulla", + "se_dio_vuole", + "la_bussola_d_oro", + "monte_cristo", + "arco_trionfale", + "trincotto", + "schiavit\u00f9_sessuale", + "la_modificazione", + "padrenostro", + "non_ti_scordar_di_me", + "battisterio", + "la_ciociara", + "after_burner", + "la_lettera_scarlatta", + "sulla_terrazza", + "boxing_day", + "parole_incrociate", + "il_fratello_minore", + "fonte_battesimale", + "la_dolce_vita", + "una_cascata_di_diamanti", + "la_dama_di_picche", + "deutsche_welle", + "pulsiossimetro", + "sode", + "gong", + "la_camera_rossa", + "gassometro", + "all_ultimo_minuto", + "mi_dispiace", + "mario_andretti", + "cortocircuito", + "multipiattaforma", + "capoverdiano", + "a_dio_piacendo", + "angiporto", + "tutto_\u00e8_bene_quel_che_finisce_bene", + "de_facto", + "albero_di_natale", + "il_gatto_con_gli_stivali", + "decollare", + "la_fiera_della_vanit\u00e0", + "va_bene", + "cortocircuitare", + "tazzina", + "tutto_\u00e8_bene_ci\u00f2_che_finisce_bene", + "gelato_ai_frutti_misti", + "cacciabombardiere", + "novo_mesto", + "gelato_di_frutta_mista" + ], + "FOOD": [ + "cotenna", + "olla_podrida", + "intingolo", + "cioccolatino", + "mousse", + "sanguinaccio", + "golden_delicious", + "borlotto", + "cornetti", + "symphytum_officinale", + "sughetto", + "daucus_carota", + "besciamella", + "bechamel", + "pasta_sfoglia", + "fiorentina", + "christmas_pudding", + "pastina", + "polpettone", + "ficodindia", + "rosato", + "vigna_unguiculata", + "becchime", + "agretto", + "granny_smith", + "capsicum", + "latticino", + "alla_coque", + "whiskey_irlandese", + "aperitivo", + "cantaro", + "patatina", + "surgelazione", + "farina", + "colazione", + "panperso", + "candito", + "tinto", + "latticini", + "broccoletti", + "pranzo", + "rosatello", + "abboffata", + "gelato", + "chili", + "bagna", + "stracotto", + "bibita_analcolica", + "antipasto", + "latticinio", + "prandere", + "prima_colazione", + "pudding", + "fagiolini", + "ventrata", + "dessert", + "sventrata", + "mangiata", + "lattemiele", + "budino", + "bakhasatang", + "bodino", + "scatolame", + "strippata", + "ros\u00e9", + "sonchus_oleraceus", + "petit_four", + "omelette", + "pot_au_feu", + "fegatino", + "pranzare", + "juglans_regia" + ], + "QUANTITY": [ + "wattora", + "ventotto", + "chilogrammetro", + "won_sudcoreano", + "centomila", + "novantatr\u00e9", + "dollaro", + "tre_sorelle", + "won_della_corea_del_nord", + "franco_guineano", + "libbra", + "ventisette", + "shilling", + "elettronvolt", + "parchimetro", + "chilowattora", + "sterlina_egiziana", + "riyal", + "diecimila", + "tre_regni", + "ventinove", + "settantotto", + "franco_camerunense", + "ventitr\u00e9", + "won_della_corea_del_sud", + "g", + "sterlina", + "autoparco", + "stabulario", + "the_real_world", + "rial", + "franco_senegalese", + "caloria", + "ventiquattro", + "spinarello", + "gasterosteus_aculeatus", + "dinaro", + "ventisei", + "ventidue", + "franco_francese", + "gattile", + "autoparcheggio", + "di_rimpetto", + "costante_cosmologica", + "ordinale", + "scellino", + "parcheggiatore", + "centiara", + "won_nordcoreano", + "sterlina_britannica", + "anders_celsius", + "mq", + "i_tre_amigos" + ], + "PERSON_PRONOUN": [ + "te_stessa", + "te_stesso", + "le_nostre", + "i", + "voi_stesse", + "he", + "da_soli", + "voi_tutti", + "our", + "noialtri", + "la_mia", + "i_nostri", + "voi_stessi", + "me", + "la_nostra", + "suoi", + "tuoi", + "il_nostro" + ], + "FAC": [ + "san_quirino", + "poco_alla_volta", + "galleria_aerodinamica", + "camera_bassa", + "centro_commerciale", + "a_poco_a_poco", + "autostazione", + "poco_per_volta", + "scuola_primaria", + "carbonaia", + "the_trap_door", + "the_last_supper", + "elementari", + "arnold_sch\u00f6nberg", + "man_mano", + "san_giuseppe", + "commissariato", + "saint_lucia", + "gradatamente", + "santiago_di_compostela", + "guardian_angels", + "cartiera", + "centrale_elettronucleare", + "ufficio_postale", + "bottiglieria", + "fronte_popolare", + "le_quattro_stagioni", + "gualchiera", + "trentatr\u00e8", + "santa_lucia", + "facolt\u00e0_di_medicina", + "a_spizzichi", + "la_montagna_incantata", + "winnie_puh", + "a_pezzi_e_bocconi", + "stanotte", + "friedrichshain_kreuzberg", + "scuola_elementare" + ], + "BIO_CHEM_ENTITY": [ + "protoporfirinogeno_ossidasi", + "polivinilcloruro", + "poliaminossidasi", + "aldeideossidasi", + "sorpassato", + "alcol_coniferilico", + "betamiloide", + "guanosindifosfato", + "antipolio" + ], + "TITLE": [ + "mister", + "ms" + ], + "DATE": [ + "novilunio", + "mezzora", + "gioved\u00ec_santo", + "prima_o_poi", + "marted\u00ec_grasso", + "dog_days", + "tutti_i_giorni_ventiquatt_ore_su_ventiquattro", + "decorrenza", + "happy_hour", + "la_dodicesima_notte", + "bisesto", + "inizialmente", + "diviato", + "in_time", + "a_volte_ritornano", + "plenilunio", + "da_prima", + "a_lungo_andare", + "alla_lunga", + "medioevo", + "primo_quarto", + "era_glaciale", + "dopodomani", + "vecchiezza", + "lunazione", + "et\u00e0_dell_oro", + "immantinente", + "et\u00e0_d_oro", + "new_moon", + "anzitutto", + "era_spaziale", + "cinquantennio", + "the_day_after_il_giorno_dopo", + "senilit\u00e0", + "solleone", + "bissesto", + "battibaleno", + "the_day_after_tomorrow_l_alba_del_giorno_dopo", + "the_golden_years", + "in_primis", + "semivita", + "tutti_i_santi", + "assunzione_di_maria", + "prima_di_tutto", + "in_tempo", + "come_prima_cosa", + "alla_fin_fine", + "tantosto", + "giornataccia", + "era_volgare" + ], + "LANGUAGE": [ + "tailandese", + "bengali", + "da_lontano", + "nemica", + "venda", + "romena", + "bambara", + "sundanese", + "georgiano", + "sindhi", + "magiaro", + "coreana", + "samoana", + "pali", + "russa", + "manx", + "faroese", + "hindi", + "lustrare", + "assamese", + "francoprovenzale", + "guarani", + "catalano", + "lingua_lingala", + "tedesco", + "esperanto", + "latino_americana", + "tedesca", + "coreano", + "cinese", + "cree", + "lao", + "kikuyu", + "tagalog", + "ido", + "nipponico", + "arabico", + "galliciano", + "schipetaro", + "baschiro", + "tonga", + "kannada" + ], + "GPE": [ + "san_sostene", + "centro_storico", + "montalbano_jonico", + "nuovo_testamento", + "madonna_addolorata", + "saint_domingue", + "nostra_signora", + "impero_germanico", + "\u0111ur\u0111evdan", + "dar_es_salaam", + "pietro_apostolo", + "favonio", + "sint_maarten", + "san_valentino", + "casa_bianca", + "basilica_di_santa_sofia", + "pandanus_tectorius", + "camisano_vicentino", + "campo_san_martino", + "villaggio_olimpico", + "palazzo_canavese", + "croce_rossa", + "mille_isole", + "s\u00e3o_tom\u00e9", + "san_cristoforo", + "distretto_scolastico", + "francavilla_marittima", + "gran_canaria", + "franca_contea", + "spirito_santo", + "al_andalus", + "mar_rosso", + "marano_principato", + "oro_bianco", + "perosa_canavese", + "la_rochelle", + "oliveto_lucano", + "sudamerica", + "san_pietro_apostolo", + "andalusa", + "madonna_dei_sette_dolori", + "citt\u00e0_vecchia", + "san_didero", + "hibiscus_rosa_sinensis", + "charlottenburg_wilmersdorf", + "la_gomera", + "santa_severina", + "villanova_marchesana", + "monteforte_irpino", + "maria_addolorata" + ], + "RELIGION_MEMBER": [ + "guru", + "the_hindu", + "sunnita", + "mormonico", + "orangista", + "indostano", + "chi_agita", + "francescano", + "carmelitano", + "agostino", + "non_conformista", + "agostiniano", + "cristiano", + "mussulmano", + "benedettina", + "induista", + "presbiteriano", + "domenicano", + "mormon", + "nazareno", + "shaker", + "cistercense", + "trappista", + "benedettino", + "veterocattolico", + "cisterciense", + "mormone", + "parsi", + "metodista", + "testimone_di_geova", + "sufi", + "anticonformistico", + "anabattista", + "l_apostolo", + "senzadio" + ], + "POLITICAL_PARTY_MEMBER": [ + "fabiano", + "laburista", + "laborista", + "comunista", + "federalista" + ], + "RELIGION": [ + "zen", + "presbiterianismo", + "brahmanesimo", + "catarismo", + "mennonitismo", + "manicheismo", + "islam", + "presbiterianesimo", + "puritanesimo", + "calvinismo", + "scintoismo", + "shintoismo", + "parsismo", + "cristianesimo_scientista", + "salafismo", + "congregazionalismo", + "wahabismo", + "lamaismo", + "brahmanismo", + "wicca", + "anglocattolicesimo" + ], + "RACE": [ + "polinesiano", + "indian_airlines", + "latino", + "filippino", + "nordcoreano", + "isolano", + "nordcoreana", + "pachistano", + "gallesi", + "africano", + "inglesi", + "isolana", + "israelitico", + "francesi", + "africana", + "sudamericano", + "pallidezza", + "amerindiano", + "giudaico", + "latinoamericano", + "the_mexican_amore_senza_sicura", + "statunitensi", + "olandesi", + "giapponesi", + "negro", + "latina", + "amerindio", + "pachistana", + "nordeuropeo", + "bianchi" + ], + "SOC_ECO_CLASS": [ + "pochi", + "malavita", + "eleggere", + "samurai", + "sfaccendare", + "classe_dirigente", + "borghesia", + "popolino", + "intellettualoide", + "alta_societ\u00e0", + "proletariato", + "mercato_nero", + "proprietari_terrieri", + "classe_media", + "ceto_medio", + "sottoclasse", + "fraternit\u00e0", + "padronato" + ], + "GENDER": [ + "caposala", + "mademoiselle", + "gentleman", + "men", + "maschietto", + "boy", + "male", + "boys", + "vecchia", + "guido", + "fantesca", + "debbo", + "madamigella", + "galantuomo", + "tribade", + "transgender", + "putta", + "gentil_sesso", + "ragazzi", + "gal", + "gentildonna", + "damigella", + "capoinfermiera" + ], + "LAW": [ + "divorzista", + "p_l", + "controinterrogatorio", + "ne_bis_in_idem", + "ufficio_federale_investigativo", + "federal_bureau_of_investigation", + "avvocatura", + "patteggiamento" + ], + "PERSON": [ + "al_gore", + "h_g_wells", + "monte_tai", + "saint_vincent", + "gioconda", + "est_sud_est", + "st_vincent", + "william_playfair", + "don_delillo", + "a_chi", + "edward_osborne_wilson", + "ceppatello", + "de_witt", + "min_dong", + "george_v", + "al_amin", + "in_memory", + "carl_david_anderson", + "maxwell_anderson", + "boletus_edulis", + "yo_yo", + "rudolf_hess", + "pesce_san_pietro" + ], + "EVENT": [ + "gran_premio", + "destarsi", + "danza_macabra", + "sing_sing", + "festival_cinematografico", + "appassionare" + ], + "ANAT": [ + "gran_dorsale" + ], + "ner_regexes": [ + [ + "PERSON", + "\\D+ \\D+|\\D+ \\D+|\\D+ \\D+|\\D+ \\D+|\\D+ \\D+-\\D+|\\D+ \\D+ \\D+|\\D+ \\D+|\\D+ \\D+|\\D+ \\D+|\\D+ \\D+|\\D+ \\D+-\\D+|\\D+ \\D+ \\D+", + false, + [] + ] + ], + "FIRST_NAME_FEMALE": [ + "lara", + "licia", + "gabriella", + "giorgia", + "bettina", + "stefani", + "priscilla", + "giovanna", + "sonia", + "mercedes", + "olga", + "camilla", + "luisa", + "pierina", + "paola", + "antonia", + "annamaria", + "allegra", + "paulina", + "stella", + "milena", + "evangelista", + "sylvia", + "isa", + "valentina", + "rossana", + "romina", + "gelsomina", + "francesca", + "antonietta", + "donna", + "maria", + "alessandra", + "alessia", + "giulia", + "iolanda", + "dolores", + "sandra", + "melania", + "paoletta", + "marissa", + "michela", + "fortunata", + "liana", + "romana", + "martina", + "angelica", + "griselda", + "filippa", + "diana", + "elisa", + "ornella", + "serafina", + "zaira", + "etta", + "clelia", + "victoria", + "veronica", + "raffaella", + "eva", + "alina", + "aurora", + "fabrizia", + "lisa", + "annalisa", + "sole", + "laura", + "susanna", + "imelda", + "patrizia", + "rosina", + "cristina", + "anita", + "ilaria", + "nicoletta", + "maura", + "viridiana", + "adele", + "carla", + "virginia", + "adelasia", + "elvira", + "carolina", + "tatiana", + "tonia", + "cassandra", + "marina", + "simonetta", + "rosa", + "marisa", + "vittoria", + "eugenia", + "roberta", + "barbara", + "amalia", + "rosalia", + "chiara", + "giuseppina", + "mariana", + "germana", + "annunziata", + "melina", + "luciana", + "fernanda", + "caterina", + "ida", + "vanessa", + "sophia", + "bianca", + "silvia", + "claudia", + "angelina", + "nina", + "rosaria", + "liliana", + "jolanda", + "marcella", + "annetta", + "lolita", + "teresa", + "matilda", + "erika", + "lidia", + "stefania", + "rita", + "morena", + "ludovica", + "fabia", + "loretta", + "gloria", + "natalia", + "marta", + "amanda", + "elena", + "margherita", + "dina", + "nedda", + "melissa", + "lauretta", + "aria", + "vincenza", + "ninetta", + "fiamma", + "letizia", + "concetta", + "isabella", + "emma", + "flora", + "antonella", + "donatella", + "irma", + "pina", + "livia", + "gianna", + "valeria", + "daria", + "federica", + "lilla", + "berenice", + "serena", + "giulietta", + "cecilia", + "adriana", + "flavia", + "tina", + "paloma", + "ramona", + "renata", + "giada", + "loredana", + "lucrezia", + "lucia", + "giuliana", + "lina", + "luigina", + "nadia", + "eliana", + "beatrice", + "antonina", + "gemma", + "greca", + "graziella", + "monica", + "tiziana", + "eleanora" + ], + "FIRST_NAME_MALE": [ + "fabrizio", + "liberto", + "giuseppe", + "micheletto", + "nicola", + "benito", + "uberto", + "luca", + "pasquale", + "massimo", + "flavio", + "annibale", + "gioachino", + "raffaello", + "benedetto", + "amico", + "piero", + "romolo", + "fausto", + "guido", + "ivo", + "livio", + "damiano", + "pompeo", + "salvatore", + "danilo", + "giacomo", + "raimondo", + "piermaria", + "marcello", + "virgilio", + "laureano", + "lazzaro", + "angelo", + "pierpaolo", + "luigi", + "pomponio", + "giampaolo", + "giacobbe", + "biagio", + "gioacchino", + "gionata", + "arnulfo", + "giampiero", + "roberto", + "carlo", + "sante", + "antonello", + "adelmo", + "guglielmo", + "salvi", + "tonino", + "alessio", + "gianpaolo", + "greco", + "dario", + "santino", + "ranieri", + "baldassare", + "maurizio", + "toni", + "orazio", + "armando", + "pierluigi", + "girolamo", + "augusto", + "mariano", + "baccio", + "antonino", + "roman", + "antonio", + "ermes", + "puccio", + "aldo", + "nanni", + "pierangelo", + "pellegrino", + "napoleone", + "piergiorgio", + "ronaldo", + "enrico", + "gastone", + "arturo", + "michelotto", + "claudio", + "tullio", + "gioele", + "giancarlo", + "hugo", + "coluccio", + "calcedonio", + "ennio", + "arnaldo", + "ugo", + "domenico", + "goffredo", + "benvenuto", + "alessandro", + "costantino", + "dino", + "gianni", + "gianluca", + "fulvio", + "carmelo", + "piergiuseppe", + "gilberto", + "ricciotti", + "rembrandt", + "cipriano", + "adamo", + "fredo", + "lorenzo", + "raffaele", + "gianfrancesco", + "geronimo", + "amleto", + "franco", + "michele", + "stefano", + "amadeo", + "federico", + "ernesto", + "ruggero", + "manuel", + "coriolano", + "riccardo", + "pasqual", + "agostino", + "martino", + "daniele", + "lamberto", + "federigo", + "donatello", + "mario", + "ettore", + "giorgio", + "simone", + "severino", + "cirillo", + "gioffre", + "gianmarco", + "alderano", + "vincentio", + "rosario", + "paolo", + "atenulf", + "filippo", + "camillo", + "gustavo", + "giulio", + "ferdinando", + "gian", + "lando", + "durante", + "luciano", + "giustino", + "amedeo", + "alfio", + "gabriele", + "venancio", + "sebastiano", + "pietro", + "ciro", + "leonardo", + "patrizio", + "fiorenzo", + "ludovico", + "ottavio", + "vincenzo", + "enzo", + "marco", + "ippazio", + "sandro", + "elladio", + "mirco", + "achille", + "nicol\u00f2", + "costanzo", + "ermanno", + "vito", + "renzo", + "nico", + "eraldo", + "maurilio", + "luchino", + "torquato", + "piersanti", + "emilio", + "pier", + "lodovico", + "adriano", + "ruggiero", + "bernardo", + "oreste", + "fabio", + "umberto", + "azeglio", + "giacinto", + "mauro", + "alberico", + "agnolo", + "mirko", + "alfredo", + "fiorino", + "jacopo", + "gino", + "ugolino", + "temistocle", + "rolando", + "giovanni", + "bartolomeo", + "dionigi", + "sabatino", + "beppe", + "michelangelo", + "ubaldo", + "gaetano", + "alberto", + "donato", + "panfilo", + "alphons", + "leone", + "telemaco", + "gianfranco", + "saverio", + "graziano", + "delfino", + "sergius", + "leopoldo", + "cesare", + "enzio", + "matteo", + "corrado", + "arsenio", + "elmo", + "dante", + "massimiliano", + "guarino", + "romeo", + "fedele", + "ivan", + "calogero", + "giosu\u00e8", + "marcantonio", + "francesco", + "ignazio", + "tiziano", + "silvestro", + "gianpietro", + "niccol\u00f2", + "nino", + "edoardo", + "paride", + "ansaldo", + "ermenegildo", + "giuliano", + "orlando", + "milo", + "galasso", + "silvio", + "gianluigi", + "mattia", + "ezio", + "gaspare", + "osvaldo", + "bruno", + "ottone", + "valerio", + "lucio", + "rodolfo", + "raffaellino", + "vittorio", + "rocco" + ], + "PREFIX_FEMALE": [ + "sig.ra", + "dott" + ], + "PREFIX_MALE": [ + "dott", + "sig" + ], + "FIRST_NAME": [ + "liberto", + "pasquale", + "bettina", + "luca", + "stefani", + "raffaello", + "priscilla", + "ivo", + "mercedes", + "luisa", + "pierina", + "giacomo", + "antonia", + "angelo", + "pierpaolo", + "milena", + "evangelista", + "biagio", + "valentina", + "arnulfo", + "gelsomina", + "donna", + "maria", + "alessio", + "gianpaolo", + "santino", + "giulia", + "baldassare", + "dolores", + "sandra", + "paoletta", + "melania", + "marissa", + "girolamo", + "fortunata", + "liana", + "nanni", + "ermes", + "aldo", + "pierangelo", + "ronaldo", + "serafina", + "gioele", + "eva", + "aurora", + "carmelo", + "piergiuseppe", + "gilberto", + "nicoletta", + "rembrandt", + "adamo", + "fredo", + "niccol\u00f2", + "raffaele", + "lorenzo", + "virginia", + "michele", + "adelasia", + "elvira", + "cassandra", + "pasqual", + "marina", + "martino", + "donatello", + "cirillo", + "gianmarco", + "giuseppina", + "atenulf", + "annunziata", + "melina", + "luciana", + "gustavo", + "vanessa", + "amedeo", + "gabriele", + "venancio", + "sebastiano", + "ciro", + "nina", + "rosaria", + "ottavio", + "lolita", + "erika", + "fabia", + "nico", + "piersanti", + "emilio", + "pier", + "gloria", + "adriano", + "giacinto", + "jacopo", + "fiamma", + "letizia", + "concetta", + "giovanni", + "dionigi", + "donatella", + "irma", + "ubaldo", + "alberto", + "gaetano", + "donato", + "panfilo", + "daria", + "leone", + "saverio", + "delfino", + "leopoldo", + "guarino", + "flavia", + "francesco", + "ramona", + "lucrezia", + "edoardo", + "paride", + "orlando", + "luigina", + "ezio", + "lucio", + "vittorio", + "lara", + "nicola", + "massimo", + "annibale", + "benedetto", + "amico", + "giovanna", + "sonia", + "olga", + "camilla", + "pompeo", + "raimondo", + "salvatore", + "virgilio", + "stella", + "gionata", + "rossana", + "romina", + "carlo", + "francesca", + "antonello", + "toni", + "augusto", + "romana", + "martina", + "angelica", + "baccio", + "roman", + "filippa", + "puccio", + "elisa", + "pellegrino", + "piergiorgio", + "victoria", + "claudio", + "calcedonio", + "ennio", + "ugo", + "lisa", + "annalisa", + "laura", + "cristina", + "cipriano", + "geronimo", + "gianfrancesco", + "amadeo", + "federico", + "riccardo", + "marisa", + "vittoria", + "federigo", + "mario", + "amalia", + "vincentio", + "mariana", + "paolo", + "camillo", + "fernanda", + "durante", + "sophia", + "luciano", + "pietro", + "leonardo", + "fiorenzo", + "ludovico", + "vincenzo", + "marco", + "annetta", + "elladio", + "matilda", + "achille", + "lidia", + "rita", + "morena", + "vito", + "loretta", + "margherita", + "marta", + "oreste", + "elena", + "dina", + "mauro", + "alberico", + "agnolo", + "alfredo", + "aria", + "vincenza", + "antonella", + "gianna", + "alphons", + "gianfranco", + "sergius", + "federica", + "cesare", + "enzio", + "lilla", + "corrado", + "arsenio", + "elmo", + "serena", + "giulietta", + "adriana", + "fedele", + "paloma", + "ignazio", + "gianpietro", + "lucia", + "giuliano", + "milo", + "gianluigi", + "mattia", + "silvio", + "nadia", + "ottone", + "gaspare", + "antonina", + "gemma", + "rodolfo", + "graziella", + "monica", + "tiziana", + "rocco", + "licia", + "micheletto", + "gabriella", + "benito", + "giorgia", + "uberto", + "flavio", + "romolo", + "guido", + "livio", + "damiano", + "laureano", + "piermaria", + "marcello", + "allegra", + "luigi", + "sylvia", + "giacobbe", + "giampaolo", + "gioacchino", + "roberto", + "antonietta", + "tonino", + "alessia", + "ranieri", + "iolanda", + "michela", + "zaira", + "arturo", + "michelotto", + "tullio", + "hugo", + "fabrizia", + "domenico", + "gianni", + "imelda", + "patrizia", + "rosina", + "adele", + "carla", + "amleto", + "franco", + "stefano", + "ernesto", + "carolina", + "tatiana", + "tonia", + "agostino", + "simonetta", + "rosa", + "eugenia", + "lamberto", + "chiara", + "severino", + "gioffre", + "germana", + "filippo", + "giulio", + "caterina", + "bianca", + "alfio", + "silvia", + "patrizio", + "liliana", + "enzo", + "jolanda", + "sandro", + "ippazio", + "marcella", + "ludovica", + "costanzo", + "ermanno", + "luchino", + "maurilio", + "natalia", + "azeglio", + "nedda", + "mirko", + "fiorino", + "gino", + "ugolino", + "temistocle", + "emma", + "bartolomeo", + "sabatino", + "beppe", + "telemaco", + "berenice", + "massimiliano", + "tina", + "ivan", + "calogero", + "marcantonio", + "tiziano", + "ansaldo", + "giuliana", + "greca", + "lina", + "raffaellino", + "goffredo", + "eleanora", + "fabrizio", + "giuseppe", + "gioachino", + "piero", + "fausto", + "danilo", + "lazzaro", + "paola", + "annamaria", + "paulina", + "pomponio", + "isa", + "giampiero", + "sante", + "adelmo", + "guglielmo", + "salvi", + "alessandra", + "greco", + "dario", + "maurizio", + "orazio", + "armando", + "pierluigi", + "mariano", + "antonino", + "griselda", + "antonio", + "diana", + "ornella", + "napoleone", + "enrico", + "gastone", + "etta", + "clelia", + "veronica", + "giancarlo", + "raffaella", + "arnaldo", + "coluccio", + "alina", + "benvenuto", + "alessandro", + "costantino", + "dino", + "sole", + "fulvio", + "susanna", + "gianluca", + "anita", + "ricciotti", + "ilaria", + "maura", + "viridiana", + "ruggero", + "manuel", + "coriolano", + "daniele", + "roberta", + "barbara", + "ettore", + "rosalia", + "giorgio", + "simone", + "alderano", + "rosario", + "ferdinando", + "gian", + "lando", + "ida", + "giustino", + "claudia", + "angelina", + "teresa", + "mirco", + "nicol\u00f2", + "stefania", + "renzo", + "eraldo", + "torquato", + "lodovico", + "bernardo", + "amanda", + "ruggiero", + "fabio", + "umberto", + "melissa", + "lauretta", + "ninetta", + "isabella", + "rolando", + "flora", + "pina", + "michelangelo", + "livia", + "valeria", + "graziano", + "matteo", + "dante", + "cecilia", + "romeo", + "giosu\u00e8", + "renata", + "giada", + "loredana", + "silvestro", + "nino", + "ermenegildo", + "galasso", + "eliana", + "osvaldo", + "bruno", + "beatrice", + "valerio" + ], + "LAST_NAME": [ + "nievo", + "armellini", + "gaiatto", + "sabatini", + "lombardi", + "sraffa", + "barzini", + "cherubini", + "traetta", + "bajardi", + "pugliese", + "zoppetti", + "giammusso", + "seddio", + "borghese", + "sommaruga", + "cibin", + "monte", + "chiaramonte", + "donarelli", + "cipolla", + "pertini", + "scarlatti", + "verdone", + "tagliafierro", + "trapani", + "nosiglia", + "tarantini", + "bosio", + "broggini", + "romano", + "nitti", + "garobbio", + "pucci", + "cutuli", + "gucci", + "panatta", + "campanella", + "finetti", + "sonnino", + "lettiere", + "cilibrasi", + "cugia", + "gilardoni", + "speri", + "biagi", + "mimun", + "verri", + "brambilla", + "ruggeri", + "argan", + "pennetta", + "bertolucci", + "nitto", + "cianciolo", + "detti", + "bonino", + "smirnoff", + "sgalambro", + "tartini", + "ferrabosco", + "anastasi", + "trezzini", + "segr\u00e8", + "trevisan", + "borroni", + "pellico", + "milanesi", + "folliero", + "saraceno", + "giovine", + "rensi", + "pinamonte", + "belletini", + "pisani", + "lupo", + "duodo", + "toselli", + "gianvecchio", + "boccaccio", + "toldo", + "gabbana", + "bajamonti", + "tomaselli", + "bottigliero", + "travia", + "abatantuono", + "fibonacci", + "treves", + "prati", + "camilleri", + "ottino", + "pellegrini", + "farnese", + "tasca", + "ravaglioli", + "olivetti", + "interminelli", + "callegari", + "papetti", + "maccanelli", + "morgagni", + "rocca", + "gentili", + "vespucci", + "crispi", + "carli", + "soffici", + "ceravolo", + "sagese", + "majorana", + "giannini", + "ammaniti", + "tarchetti", + "sagnelli", + "sordi", + "marazzi", + "cainero", + "canevascini", + "salvemini", + "gigli", + "cocci", + "alfonsi", + "ubaldi", + "giunti", + "cilea", + "nolcini", + "scalfaro", + "toscani", + "vasari", + "altera", + "vismara", + "manolesso", + "dellucci", + "bell\u00f2", + "grossi", + "metella", + "busoni", + "rosmini", + "parmitano", + "varano", + "ungaretti", + "malatesta", + "mascheroni", + "pedrazzini", + "ludovisi", + "combi", + "agnesi", + "casadei", + "ferraris", + "pizzo", + "bonolis", + "zoppetto", + "guinizzelli", + "bianchini", + "ruffini", + "saragat", + "calbo", + "molesini", + "guarato", + "panzera", + "antonetti", + "curci", + "mastandrea", + "benussi", + "toscanini", + "cavanna", + "castelli", + "mazzacurati", + "strangio", + "argentero", + "mondadori", + "trapanese", + "interminei", + "borromini", + "salgari", + "gregorio", + "angiolello", + "botta", + "cignaroli", + "fuseli", + "filippelli", + "gianinazzi", + "iannucci", + "pozzecco", + "caccioppoli", + "sauli", + "bocelli", + "viviani", + "scialpi", + "benigni", + "andreozzi", + "bossi", + "stoppani", + "zanazzo", + "tamburello", + "boezio", + "udinese", + "esposito", + "pininfarina", + "frescobaldi", + "pavone", + "galtarossa", + "scotto", + "agostinelli", + "saffi", + "ossola", + "alonzi", + "poerio", + "littizzetto", + "contarini", + "lombardo", + "leone", + "aloisio", + "palmisano", + "cicilia", + "nadi", + "gritti", + "sgarbi", + "marcacci", + "squarcione", + "bondumier", + "panicucci", + "casagrande", + "vercelloni", + "dallara", + "luria", + "natta", + "gaggini", + "bonanno", + "carpaccio", + "zaguri", + "niggli", + "bova", + "grasso", + "gravina", + "guariento", + "capuana", + "zeffirelli", + "telesio", + "palladio", + "ferrucci", + "turchetta", + "blasi", + "fo", + "valmarana", + "abba", + "inzaghi", + "colletti", + "corcos", + "silvestri", + "florio", + "luna", + "saracino", + "infantino", + "bongiorno", + "grisoni", + "orlando", + "sandi", + "brunello", + "basso", + "musatti", + "boiardo", + "alfieri", + "conti", + "rusticucci", + "ariasso", + "roth", + "maglio", + "montalti", + "burcardo", + "acerbi", + "trombetta", + "canali", + "montalcini", + "mogherini", + "trentin", + "aulenti", + "fioravanti", + "campise", + "cutrufo", + "leblanc", + "contrafatto", + "fantini", + "zamengo", + "desio", + "trevisani", + "tarantino", + "gremese", + "jilani", + "federici", + "vigorelli", + "giannetti", + "monaco", + "puglisi", + "monti", + "casaleggio", + "morellato", + "pasolini", + "ginesio", + "buscetta", + "petrucci", + "tacchini", + "basadonna", + "balla", + "lombroso", + "virgilio", + "gemito", + "dibiasi", + "barbarigo", + "goldstein", + "casalodi", + "santoro", + "galiazzo", + "fagiani", + "sabbatini", + "tropea", + "gagliardi", + "salata", + "trillini", + "morandi", + "galilei", + "antonello", + "monteverdi", + "montanariello", + "bold\u00f9", + "sforza", + "priuli", + "baggio", + "marenzio", + "scaduto", + "gussoni", + "fischetti", + "migliaccio", + "fermi", + "mannoia", + "zaccardo", + "zabarella", + "mozart", + "germano", + "amato", + "battisti", + "bartoli", + "muti", + "lamborghini", + "luzi", + "asprucci", + "donatoni", + "righi", + "torricelli", + "zarlino", + "palombi", + "malenchini", + "veltroni", + "casale", + "malaparte", + "cafarchia", + "oscuro", + "villarosa", + "malacarne", + "bellini", + "novaro", + "lattuada", + "modiano", + "mancini", + "calgari", + "rismondo", + "garzoni", + "stucchi", + "micca", + "cossiga", + "ricci", + "botticelli", + "cerquiglini", + "moccia", + "lopresti", + "ricolfi", + "antelami", + "abate", + "galuppi", + "scandone", + "pizzamano", + "anguillara", + "marconi", + "gualandi", + "camicione", + "ciampi", + "catenazzi", + "marangoni", + "dossi", + "tremonti", + "bernardi", + "vecoli", + "celentano", + "nonis", + "visintini", + "badoer", + "onio", + "federico", + "savorgnan", + "scotti", + "ostinelli", + "boaga", + "vitturi", + "pisano", + "malipiero", + "argento", + "balbo", + "ricciardi", + "morricone", + "munari", + "marsili", + "pascarella", + "corbo", + "faugno", + "liverotti", + "borgia", + "crespi", + "cagnotto", + "berlusconi", + "nicoletti", + "ovadia", + "ortolani", + "mantegna", + "maggioli", + "ferrata", + "napolitano", + "martinelli", + "bruscantini", + "dallap\u00e9", + "antonacci", + "leonardi", + "mortati", + "giusti", + "letta", + "durante", + "tommaseo", + "galvani", + "zampa", + "pelli", + "procacci", + "montesano", + "parpinel", + "morucci", + "carosone", + "guidotti", + "canova", + "querini", + "catalano", + "grassi", + "peruzzi", + "giannotti", + "marini", + "tanzini", + "murri", + "pignatti", + "rosiello", + "magrassi", + "tartaglia", + "puccini", + "forza", + "buonauro", + "scamarcio", + "argurio", + "tassoni", + "dossetti", + "modugno", + "bataglia", + "agazzi", + "zola", + "regge", + "baroffio", + "asmundo", + "vanvitelli", + "ferrazzi", + "offredi", + "franzese", + "salvini", + "collodi", + "don\u00e0", + "lerner", + "caracciolo", + "gasperi", + "valentino", + "roero", + "segni", + "quasimodo", + "pirelli", + "mercadante", + "pisacane", + "opizzi", + "sermonti", + "jacuzzi", + "dalla", + "pagnotto", + "benedetti", + "tamburini", + "bertoni", + "finotto", + "barsanti", + "carullo", + "mazzanti", + "troisi", + "morabito", + "villadicani", + "gibilisco", + "rossi", + "lercari", + "mazzeo", + "zanichelli", + "cadorna", + "ceri", + "rossellini", + "vento", + "brichese", + "fantozzi", + "navone", + "guglielmi", + "mantegazza", + "trebbi", + "mondaini", + "staglieno", + "cattaneo", + "raurica", + "tirabassi", + "vergerio", + "travaglio", + "geraci", + "tuzzolino", + "balbi", + "marzorati", + "casarin", + "druso", + "zamorani", + "udinesi", + "correr", + "fiorucci", + "santi", + "orsini", + "fogazzaro", + "solimena", + "gottardi", + "petrocelli", + "valier", + "volta", + "parisi", + "carducci", + "faggiani", + "draghi", + "nugnes", + "cesarotti", + "tasso", + "veneziano", + "baracca", + "trupiano", + "renault", + "beccaria", + "sollima", + "ferrara", + "palazzo", + "tomasini", + "bosurgi", + "riccardi", + "trincavelli", + "ginese", + "ferretti", + "serraglio", + "cortese", + "luxardo", + "gagliano", + "morandini", + "albertini", + "morlacchi", + "comeriato", + "peano", + "sauro", + "marino", + "boitani", + "gioberti", + "greggio", + "pace", + "bersani", + "golgi", + "pratesi", + "lippomano", + "fracci", + "fo\u00e0", + "bonomo", + "vigliotti", + "calvo", + "rosselli", + "antonini", + "dandolo", + "depero", + "cerutti", + "capecchi", + "corradi", + "argenti", + "toso", + "turrini", + "costalonga", + "antonelli", + "verga", + "caboto", + "scarpetta", + "fieramosca", + "ossani", + "zaccagnini", + "civaschi", + "bernini", + "mercati", + "bellocchio", + "modigliani", + "bazzi", + "petruzzi", + "turchi", + "tomasetti", + "zichichi", + "bignardi", + "bragaglia", + "cagnin", + "oliboni", + "iacobucci", + "bresciani", + "randazzo", + "giradello", + "ariosto", + "soranzo", + "paganini", + "tornatore", + "barracco", + "piacentini", + "cremonesi", + "viola", + "rossetti", + "montecchi", + "maffei", + "moresi", + "falier", + "gualtieri", + "leopardi", + "filzi", + "dovara", + "vezzali", + "borzom\u00ec", + "magnani", + "maderna", + "doglioni", + "vergassola", + "pizzetti", + "beccheria", + "muratori", + "gianetti", + "gori", + "fabbri", + "delle", + "morpurgo", + "treccani", + "soprano", + "pausini", + "columbo", + "iacovelli", + "guarneri", + "franscini", + "pareto", + "juvara", + "bonatti", + "salandra", + "cendron", + "castellitto", + "bragadin", + "borrani", + "cheda", + "prodi", + "baresi", + "taliercio", + "pigafetta", + "bodoni", + "mascagni", + "papafava", + "comencini", + "redi", + "peranda", + "errigo", + "doria", + "togliatti", + "fagotto", + "fallaci", + "filogamo", + "bramante", + "ponti", + "piovani", + "flaiano", + "barozzi", + "schiavone", + "ruggieri", + "borromeo", + "avogadro", + "totino", + "brunelleschi", + "impastato", + "ceschi", + "mazzocchi", + "barberini", + "cappelli", + "ajello", + "pederiva", + "anguissola", + "salvo", + "santorio", + "ramazzotti", + "paruta", + "fusani", + "morrocco", + "trobbiani", + "gabrieli", + "barillaro", + "finzi", + "micheletti", + "bassi", + "spinola", + "montanelli", + "boccherini", + "coppola", + "cesaroni", + "siffredi", + "venditti", + "tamborini", + "visconti", + "taccola", + "tiepolo", + "bernetti", + "ciani", + "giannuzzi", + "gangemi", + "merisi", + "curiel", + "lucciano", + "bellucci", + "parini", + "solari", + "simeoni", + "cimarosa", + "pasqua", + "monduzzi", + "bottaro", + "pertile", + "garibaldi", + "bandello", + "gadda", + "tafuri", + "sobrero", + "manunta", + "gargallo", + "crisafulli", + "aldobrandi", + "schiavo", + "marinetti", + "canetta", + "terragni", + "giannone", + "castiglione", + "ortese", + "deledda", + "comboni", + "michelangeli", + "bettin", + "loredan", + "casini", + "tonisto", + "nibali", + "maderno", + "rizzoli", + "chindamo", + "foconi", + "baglioni", + "nicolini", + "omma", + "donati", + "comolli", + "legnante", + "campano", + "odescalchi", + "calarco", + "polani", + "einaudi", + "broschi", + "dulbecco", + "scarpa", + "roccabonella", + "romagnoli", + "andreotti", + "bevilacqua", + "scalera", + "almagi\u00e0", + "agostini", + "orengo", + "lollobrigida", + "toninelli", + "naccari", + "cociarelli", + "tutino", + "storladi", + "berr\u00e8", + "necci", + "capone", + "giacconi", + "ferragni", + "pacelli", + "stradivari", + "mazzini", + "accardo", + "vivaldi", + "babato", + "rapisardi", + "lancisi", + "ferragamo", + "leoncavallo", + "cabrini", + "barcaccia", + "foletti", + "malpighi", + "tozzo", + "babati", + "chiesa", + "binaghi", + "mocenigo", + "ceci", + "pizziol", + "vecellio", + "leonetti", + "rizzo", + "scarponi", + "zecchini", + "moneta", + "giolitti", + "caruso", + "stein", + "satriani", + "persico", + "ferrante", + "rubbia", + "tedesco", + "sokolov", + "verdi", + "pisaroni", + "pirandello", + "donini", + "petrassi", + "fantoni", + "montanari", + "marrone", + "gonzaga", + "lucchesi", + "pacetti", + "farina", + "trotta", + "abbagnale", + "medici", + "eco", + "serao", + "casellati", + "iannuzzi", + "piccio", + "sibilia", + "zanzi", + "matteotti", + "duse", + "schiaparelli", + "polesel", + "caironi", + "fattori", + "gregori", + "taliani", + "murialdo", + "vianello", + "ferrari", + "camuccini", + "torlonia", + "romiti", + "semitecolo", + "bergoglio", + "cardano", + "sanudo", + "berengario", + "pedroni", + "porzio", + "ligorio", + "mattarella", + "alighieri", + "parri", + "farinelli", + "gotti", + "endrizzi", + "cundari", + "goldoni", + "rastelli", + "norbiato", + "tomei", + "bianchi", + "stefanelli", + "platini", + "iannotti", + "bertoli", + "montessori", + "longhena", + "borsellino", + "branciforte", + "bulzoni", + "gradenigo", + "pometta", + "majewski", + "borsiere", + "emanuelli", + "brugnaro", + "riccati", + "cuomo", + "lanfranchi", + "greco", + "gozzano", + "pistoletto", + "paolini", + "gullotta", + "manacorda", + "mennea", + "zetticci", + "gulotta", + "rinaldi", + "condoleo", + "chiappetta", + "gelli", + "spanevello", + "chittolini", + "cavalcanti", + "giorgetti", + "ioppi", + "boito", + "armani", + "renier", + "barcella", + "gatto", + "pietrangeli", + "mazzi", + "ficino", + "chinnici", + "curatoli", + "traversa", + "vattimo", + "onisto", + "gentilini", + "volterra", + "mengolo", + "foscari", + "satta", + "soderini", + "boccioni", + "roncalli", + "spadafora", + "passalacqua", + "padovano", + "polizzi", + "filippini", + "turati", + "giannelli", + "fanucci", + "porcellato", + "tolentino", + "grifeo", + "babbo", + "disdero", + "grimani", + "gentileschi", + "tosto", + "scaramucci", + "perozzo", + "paoletti", + "pastine", + "beffa", + "battaglia", + "franceschi", + "renzi", + "cannizzaro", + "praga", + "errani", + "piccinni", + "carriera", + "piane", + "chigi", + "monicelli", + "bettoni", + "cusano", + "raimondi", + "bompiani", + "manzoni", + "fabrizi", + "tebaldi", + "ughi", + "pulci", + "antonucci", + "giacometti", + "bixio", + "vidoni", + "zacchia", + "russo", + "lovato", + "caetani", + "angeli", + "iannelli", + "golino", + "gaito", + "scarfoglio", + "bembo", + "emo", + "comisso", + "garozzo", + "coardi", + "guarana", + "sbarbaro", + "cantimori", + "amaldi", + "palumbo", + "liguori", + "rossini", + "samele", + "falcone", + "garrone", + "pergolesi", + "spallanzani", + "missoni", + "briccialdi", + "ritacca", + "lucarelli", + "mastroianni", + "aporti", + "mercantini", + "meucci", + "pacomio", + "cammarata", + "turci", + "ziani", + "fittipaldi", + "pontecorvo", + "bombieri", + "anichini", + "mezzetta", + "martucci", + "chechi", + "tamburi", + "ruberto", + "tognazzi", + "caffarelli", + "giulietti", + "sanguineti", + "venier", + "canil", + "pepe", + "nordio", + "travaglia", + "piazzi", + "bignami", + "tencalla", + "petralli", + "vittadello", + "badoglio", + "sagredo", + "petrucelli", + "guidone", + "respighi", + "paolucci", + "iadanza", + "costanzi", + "brancaccio", + "granatelli", + "proietti", + "vespa", + "govoni", + "barese", + "carnera", + "camiscione", + "sismondi", + "vendetti", + "valguarnera", + "guicciardini", + "antonioni", + "tron", + "niscoromni", + "carfagna", + "bonaventura", + "cassar\u00e0", + "fornaciari", + "cuda", + "bacosi", + "notarbartolo", + "cabibbo", + "pavarotti", + "perini", + "jovinelli", + "innocenti", + "callegaro", + "tresoldi", + "serlupi", + "bocca", + "lussu", + "pincherle", + "versace", + "bernardini", + "zito", + "foa", + "schicchi", + "moretti", + "venturi", + "gabba", + "brenna", + "interiano", + "salieri", + "morosini", + "tosi", + "biagiotti", + "faranda", + "conte", + "rienzo", + "nicolucci", + "miniati", + "favata", + "moschino", + "zacco", + "navarria", + "filangieri", + "paltrinieri", + "spinelli", + "sansoni", + "pacillo", + "mercalli", + "battelli", + "pagliaro", + "castioni", + "adinolfi", + "gozzi", + "falloppio", + "camanni", + "pezzali", + "carocci", + "alboni", + "tozzi", + "balotelli", + "cimini", + "luciani", + "maspero", + "pavanello", + "sorrentino", + "surian", + "caccianemico", + "gramsci", + "trussardi", + "pedersoli", + "bruno", + "trentini", + "collina", + "sinisi", + "prada", + "galeati", + "cicala", + "cuzzocrea", + "cristoforetti" + ], + "OTHER_PRONOUN": [ + "it" + ], + "LAST_NAME_MALE": [], + "LAST_NAME_FEMALE": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "abbatessa": "archimandrita", + "abbadessa": "abba", + "superiora": "abato", + "abadessa": "abbate", + "priora": "archimandrita", + "abatino": "abato", + "badessa": "archimandrita", + "attrice": "istrione", + "baronin": "bonzo", + "baronessa": "barone", + "sposa": "ammogliato", + "fidanzata": "cavallaio", + "donna_d_affari": "uomo_d_affari", + "pulcino": "gaur", + "mandriana": "gaucho", + "figlia": "figliolo", + "figliola": "figliolo", + "filia": "figliolo", + "duchessa_brutta": "duca", + "duchessa": "duca", + "maharani": "imperatore", + "imperatrice": "imperatore", + "imperatore": "kaiser", + "femme_fatale": "ammaliatore", + "fattucchiera": "wizard", + "maliarda": "ammaliatore", + "incantatrice": "ammaliatore", + "donna_fatale": "ammaliatore", + "la_maliarda": "ammaliatore", + "tentatrice": "ammaliatore", + "dalila": "ammaliatore", + "femminile": "masculino", + "femmina": "male", + "gal": "bullo", + "giovane": "tizio", + "madamigella": "tizio", + "nine": "opi", + "direttrice": "preside", + "eroina": "eroe", + "locandiera": "oste", + "hostess": "steward", + "damo": "lordo", + "locatrice": "affittacamere", + "h\u00fastr\u00fain": "proprietaria", + "marchesa": "marchese", + "massaggiatore": "massaggiatrice", + "massaggiatrice": "massaggiatore", + "mademoiselle": "baronetto", + "perdere": "ridire", + "perdersi": "baronetto", + "miss_a": "baronetto", + "mancare_il_bersaglio": "ridire", + "scampare": "ridire", + "sbagliare": "ridire", + "ma\u00eetresse": "padroneggiare", + "mantenuta": "efendi", + "padrona": "laureato", + "la_madre": "babbo", + "fare_da_madre_a": "padre_della_chiesa", + "genitrice": "padre_della_chiesa", + "madre_dell_aceto": "pap\u00e0", + "matrix": "babbo", + "monaca": "religioso", + "religiosa": "frate", + "nun": "monacato", + "poliziotta": "polizia", + "sacerdotessa": "imam", + "pr\u00edncipe": "il_principe", + "principessa": "regulus", + "princess": "pr\u00edncipe", + "sorella": "fratello_di_sangue", + "fratino": "fratello_di_sangue", + "nurse": "frate", + "naja": "frate", + "zitella": "scapolo", + "vecchia_zitella": "zito", + "figliastra": "privigno", + "matrigna": "patrigno", + "madrigna": "patrigno", + "cameriera": "cameriere", + "vedova": "vedovo", + "bean": "cavolo", + "maritata": "ammogliato", + "duna": "ammogliato", + "moglie": "maritino", + "hex": "wizard", + "wicca": "wizard", + "glyptocephalus_cynoglossus": "wizard", + "feto": "cavolo", + "debbo": "cavolo", + "donne": "men", + "boy": "madamigella", + "guaglione": "madamigella", + "maschietto": "giovane", + "ragazzino": "madamigella", + "polonaise": "rifinire", + "polacco": "polonaise", + "rifinire": "polonaise", + "raffinare": "polonaise", + "sgrossare": "polonaise", + "ripulire": "polonaise", + "affinare": "polonaise", + "ingentilire": "polonaise", + "lucidare": "polonaise", + "lustrare": "polonaise", + "dirozzare": "polonaise" + }, + "other_gender_swap": { + "egli": "epi", + "he": "one", + "elli": "oms", + "suoi": "i_loro", + "lia": "le_loro" + }, + "en_pronoun2gender": { + "they": [ + "omoerotico", + "ermafrodita", + "omosex", + "omofilo", + "transgender", + "ermafrodito", + "invertito", + "omosessuale", + "bisex", + "bisessuale" + ], + "he": [ + "ragazzi", + "guaglione", + "maschile", + "dandy", + "cavolo", + "cavaliere", + "masculino", + "mascolino", + "boy", + "screpolo", + "guido", + "screpolarsi", + "gentleman", + "virile", + "little_boy", + "male", + "masculin", + "gaur", + "bullo", + "screpolatura", + "ragazzino", + "galantuomo", + "gentiluomo", + "tizio", + "maschietto" + ], + "she": [ + "femminile", + "madamigella", + "gonnella", + "lesbico", + "pulzella", + "giovane", + "perdersi", + "cameriera", + "mancare_il_bersaglio", + "perdere", + "donna_di_servizio", + "lesbica", + "feto", + "bean", + "debbo", + "femmina", + "ragazzina", + "scampare", + "damo", + "damigella", + "gal", + "domestica", + "bambola", + "pulcella", + "bimba", + "mademoiselle", + "sesso_debole", + "gentildonna", + "fanciulla", + "sbagliare", + "donzella", + "miss_a", + "tribade", + "fantesca", + "gentil_sesso" + ] + }, + "en_pronoun2pronoun": { + "he": [ + "he", + "lia", + "suoi", + "egli", + "elli" + ], + "they": [ + "one", + "i_loro", + "essi", + "assalto_alla_terra", + "le_loro", + "lia", + "oms", + "la_loro", + "il_loro", + "epi" + ], + "it": [ + "ovi", + "isto", + "ello", + "quei", + "quello", + "eso", + "quegli", + "tyto", + "quest", + "questa", + "questo", + "dette", + "questi", + "it", + "esso", + "alea", + "essa", + "ico" + ] + }, + "en_pronoun2title": {}, + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/iu.json b/data_tooling/pii_processing/ontology/data/iu.json new file mode 100644 index 0000000..406c81d --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/iu.json @@ -0,0 +1,38 @@ +{ + "SOC_ECO_CLASS": [ + "\u1431\u1548\u1550\u14f0\u14c2\u1585_\u14c2\u1405\u1550\u1548\u144e\u1483\u14f4\u14d5\u140a\u1546\u14ea\u14d7\u148b\u1466" + ], + "GENDER": [ + "arnaq" + ], + "PUBLIC_FIGURE": [ + "\u1505\u14a5\u1466" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "\u140a\u14c8\u14c7": "\u140a\u1456\u1455" + }, + "other_gender_swap": {}, + "en_pronoun2gender": { + "she": [ + "arnaq", + "\u140a\u1550\u14c7\u1585" + ] + }, + "en_pronoun2pronoun": { + "he": [ + "\u1405\u14c7" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/ja.json b/data_tooling/pii_processing/ontology/data/ja.json new file mode 100644 index 0000000..596d2f7 --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/ja.json @@ -0,0 +1,2374 @@ +{ + "DISEASE": [ + "sars", + "\u5efa\u56fd\u8005", + "\u30df\u30ba", + "chill", + "als", + "frostbite", + "mouse", + "\u30cb\u30e5\u30fc\u30ab\u30c3\u30b9\u30eb\u75c5", + "\u30ab\u30b5\u30b5\u30ae\u5c5e", + "\u30c4\u30c4\u30ac\u30e0\u30b7\u75c5", + "rust", + "\u30d5\u30a1\u30ed\u30fc\u56db\u5fb4\u75c7", + "\u56fd\u969b\u9023\u5408\u30a8\u30a4\u30ba\u5408\u540c\u8a08\u753b", + "\u30e1\u30fc\u30d7\u30eb\u30b7\u30ed\u30c3\u30d7\u5c3f\u75c7", + "\u30a2\u30d5\u30ea\u30ab\u7761\u7720\u75c5", + "\u30d6\u30e9\u30c3\u30af\u30a6\u30a9\u30fc\u30bf\u30fc", + "gimp", + "\u30d6\u30e9\u30c3\u30af\u30e9\u30c3\u30b7\u30e5", + "ed", + "\u6803\u306e\u5b9f", + "\u3072\u3068\u306a\u3067", + "\u30af\u30e9\u30a4\u30f3\u30d5\u30a7\u30eb\u30bf\u30fc\u75c7\u5019\u7fa4", + "sensation", + "\u30dd\u30a4\u30ba\u30f3_\u30a2\u30a4\u30d3\u30fc", + "\u64ab\u3067\u6469\u308b", + "\u5275\u8a2d\u8005", + "\u30df\u30e5\u30f3\u30d2\u30cf\u30a6\u30bc\u30f3\u75c7\u5019\u7fa4", + "\u30d5\u30a7\u30cb\u30eb\u30b1\u30c8\u30f3\u5c3f\u75c7", + "\u30a6\u30a8\u30b9\u30c8\u30ca\u30a4\u30eb\u30a6\u30a4\u30eb\u30b9", + "mi", + "\u30a6\u30a8\u30b9\u30c8_\u30ca\u30a4\u30eb_\u30a6\u30a4\u30eb\u30b9", + "a_\u578b\u809d\u708e", + "\u30b9\u30c6\u30a3\u30f3\u30b0", + "\u64ab\u56de\u3059", + "\u78e8\u3059\u308b", + "\u30de\u30fc\u30eb\u30d6\u30eb\u30b0_\u30a6\u30a4\u30eb\u30b9", + "\u9045\u767a\u6027\u30a6\u30a4\u30eb\u30b9", + "\u7523\u307f\u306e\u89aa", + "\u30a6\u30a9\u30fc\u30eb\u30a2\u30a4", + "\u6c34\u75d8_\u5e2f\u72b6\u75b1\u75b9\u30a6\u30a4\u30eb\u30b9", + "c_\u578b\u809d\u708e", + "\u8a2d\u7acb\u8005", + "\u64ab\u6469\u308b", + "\u30a6\u30a3\u30ea\u30a2\u30e0\u30ba\u75c7\u5019\u7fa4" + ], + "QUANTITY": [ + "\u30d5\u30a7\u30fc\u30b9\u30c4\u30fc\u30d5\u30a7\u30fc\u30b9", + "\u30b9\u30bf\u30fc\u30ea\u30f3\u30b0", + "\u30a2\u30e1\u30ea\u30ab\u30c9\u30eb", + "\u30a2\u30e1\u30ea\u30ab\u5408\u8846\u56fd\u30c9\u30eb", + "g", + "\u30a2\u30f3\u30c7\u30eb\u30b9_\u30bb\u30eb\u30b7\u30a6\u30b9", + "\u30a8\u30ba\u30e9\u30d1\u30a6\u30f3\u30c9", + "\u30d0\u30b9\u30b1\u30c3\u30c8\u30ea\u30f3\u30b0" + ], + "PLANT": [ + "\u30e8\u30fc\u30ed\u30c3\u30d1\u30a2\u30ab\u30de\u30c4", + "pine", + "\u30b7\u30e7\u30a6\u30b8\u30e7\u30a6\u30bd\u30a6", + "\u30af\u30ea\u5c5e", + "\u30a2\u30d5\u30ea\u30ab\u83eb", + "\u30d0\u30e9\u30e2\u30f3\u30b8\u30f3", + "\u30d0\u30c3\u30d5\u30a1\u30ed\u30fc\u30b0\u30e9\u30b9", + "\u30ab\u30ed\u30e9\u30a4\u30ca\u30b8\u30e3\u30b9\u30df\u30f3", + "\u30d6\u30e9\u30c3\u30af\u30d9\u30ea\u30fc", + "\u30a4\u30bf\u30ea\u30a2\u30f3\u30b5\u30a4\u30d7\u30ec\u30b9", + "\u30a6\u30a9\u30fc\u30eb\u30ca\u30c3\u30c8", + "\u30b8\u30e3\u30fc\u30de\u30f3\u30a2\u30a4\u30ea\u30b9", + "\u30b4\u30fc\u30eb\u30c7\u30f3\u30ad\u30e3\u30f3\u30c9\u30eb", + "\u30af\u30ea\u30b9\u30de\u30b9\u30ed\u30fc\u30ba", + "\u30a2\u30e1\u30ea\u30ab\u4eba\u53c2", + "\u30c0\u30b0\u30e9\u30b9\u30d5\u30a1\u30fc", + "\u30a2\u30e1\u30ea\u30ab\u7be0\u61f8\u306e\u6728", + "\u30aa\u30a6\u30b4\u30f3\u30ab\u30ba\u30e9", + "\u30e8\u30fc\u30ed\u30c3\u30d1\u30b0\u30ea", + "\u30e8\u30fc\u30ed\u30c3\u30d1\u30ab\u30e9\u30de\u30c4", + "\u30a2\u30e1\u30ea\u30ab\u30b9\u30ba\u30ab\u30b1\u30ce\u30ad", + "\u30a4\u30f3\u30b0\u30ea\u30c3\u30b7\u30e5\u30a2\u30a4\u30ea\u30b9", + "\u30e8\u30fc\u30ed\u30c3\u30d1\u30c0\u30b1\u30ab\u30f3\u30d0", + "\u30db\u30ef\u30a4\u30c8\u30ab\u30e9\u30f3\u30c8", + "\u30a2\u30e1\u30ea\u30ab\u30de\u30c4", + "\u30a2\u30e1\u30ea\u30ab\u30ca\u30c7\u30b7\u30b3", + "\u30d5\u30e9\u30f3\u30b9\u30ae\u30af", + "\u30d0\u30f3\u30af\u30b9\u30de\u30c4", + "blackberry", + "\u30e8\u30fc\u30ed\u30c3\u30d1\u6817", + "\u30e8\u30fc\u30ed\u30c3\u30d1\u6a05", + "\u30a2\u30d5\u30ea\u30ab\u30f3\u30de\u30ea\u30fc\u30b4\u30fc\u30eb\u30c9", + "\u30ec\u30c3\u30c9\u30ad\u30e3\u30f3\u30d4\u30aa\u30f3", + "\u30de\u30b9\u30bf\u30fc\u30c9", + "\u30a2\u30e1\u30ea\u30ab\u30aa\u30cb\u30a2\u30b6\u30df", + "\u5fd8\u308b\u306a\u8349", + "\u30e9\u30d6\u30eb\u30b9\u30ab\u7a2e", + "\u30a2\u30e1\u30ea\u30ab\u30b0\u30ea", + "\u30af\u30ea\u30b9\u30de\u30b9_\u30c4\u30ea\u30fc", + "\u30a2\u30d5\u30ea\u30ab\u30d0\u30aa\u30d0\u30d6", + "\u30bb\u30a4\u30bf\u30ab\u30a2\u30ef\u30c0\u30c1\u30bd\u30a6", + "\u30e8\u30fc\u30ed\u30c3\u30d1\u30d6\u30c9\u30a6", + "\u30ef\u30b9\u30ec\u30ca\u30b0\u30b5", + "\u30e8\u30fc\u30ed\u30c3\u30d1\u30ca\u30e9", + "\u30a2\u30d5\u30ea\u30ab\u30db\u30a6\u30bb\u30f3\u30ab", + "\u30e8\u30fc\u30ed\u30c3\u30d1\u5c71\u6bdb\u6b05", + "\u30a2\u30e1\u30ea\u30ab\u30ac\u30ad", + "\u30b5\u30f3\u30b7\u30e7\u30a6\u30e2\u30c9\u30ad", + "\u30a2\u30e1\u30ea\u30ab\u30d6\u30ca", + "\u6817\u6bdb", + "\u30a2\u30d5\u30ea\u30ab\u30b9\u30df\u30ec", + "\u30b8\u30e5\u30ba\u30c0\u30de", + "\u6a61\u306e\u5b9f", + "\u30d6\u30e9\u30c3\u30af\u30ab\u30e9\u30f3\u30c8", + "\u30b7\u30d9\u30ea\u30a2\u30d2\u30ca\u30b2\u30b7", + "\u30e8\u30fc\u30ed\u30c3\u30d1\u30af\u30ed\u30de\u30c4", + "\u30b1\u30f3\u30bf\u30c3\u30ad\u30fc\u30d6\u30eb\u30fc\u30b0\u30e9\u30b9", + "\u30ec\u30c3\u30c9\u30d5\u30e9\u30ef\u30fc\u30ab\u30e9\u30f3\u30c8", + "\u30af\u30ea\u30b9\u30de\u30b9\u30c4\u30ea\u30fc", + "\u30b8\u30e3\u30b3\u30a6\u30a2\u30aa\u30a4", + "\u30a2\u30e1\u30ea\u30ab\u30c7\u30a4\u30b4", + "\u30e8\u30fc\u30ed\u30c3\u30d1\u30a4\u30c1\u30a4", + "\u30a2\u30e1\u30ea\u30ab\u30c5\u30bf" + ], + "PRODUCT": [ + "\u30aa\u30fc\u30d7\u30f3\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0", + "\u30b3\u30fc\u30d2\u30fc\u30ab\u30c3\u30d7", + "\u30b0\u30ea\u30fc\u30f3\u30d5\u30e9\u30c3\u30b7\u30e5", + "s_tog", + "\u30b7\u30e7\u30fc\u30c8\u30b5\u30fc\u30ad\u30c3\u30c8", + "\u30a2\u30e1\u30ea\u30ab\u5408\u8846\u56fd\u306e\u56fd\u6b4c", + "\u30a4\u30bf\u30ea\u30a2\u9818\u30bd\u30de\u30ea\u30e9\u30f3\u30c9", + "\u30d5\u30a9\u30b2\u30c3\u30c8\u30df\u30fc\u30ce\u30c3\u30c8", + "\u30b0\u30e9\u30a6\u30f3\u30c9\u30b3\u30f3\u30c8\u30ed\u30fc\u30eb", + "\u30df\u30e5\u30fc\u30b8\u30c3\u30af\u30dc\u30c3\u30af\u30b9", + "\u30dc\u30af\u30b7\u30f3\u30b0_\u30c7\u30fc", + "\u30b5\u30f3\u30bf_\u30af\u30ed\u30fc\u30b9", + "\u30b9\u30a4\u30df\u30f3\u30b0\u30c8\u30e9\u30f3\u30af\u30b9", + "\u5fd8\u308c\u306a\u8349", + "\u65b0\u7d04\u5168\u66f8", + "\u30ae\u30cb\u30fc\u30d4\u30c3\u30b0", + "\u30a2\u30e1\u30ea\u30ab\u30b9\u30ab\u30c3\u30d7", + "\u30b0\u30fc\u30c6\u30f3\u30e2\u30eb\u30b2\u30f3", + "\u5341\u4e8c\u591c", + "\u30d5\u30a9\u30fc\u30b2\u30c3\u30c8\u30df\u30fc\u30ce\u30c3\u30c8", + "o_\u30ea\u30f3\u30b0", + "\u30dc\u30af\u30b7\u30f3\u30b0\u30c7\u30fc" + ], + "ORG": [ + "\u30a2\u30a4\u30a2\u30a4\u30a8\u30b9", + "\u30d7\u30e9\u30a4\u30de\u30ea\u30fc_\u30b9\u30af\u30fc\u30eb", + "\u7121\u7523\u968e\u7d1a\u306e", + "\u30b5\u30fc\u30c9\u30d1\u30fc\u30c6\u30a3\u30fc", + "\u30de\u30a6\u30f3\u30c8\u30ab\u30fc\u30e1\u30eb", + "\u30ab\u30df\u30f3\u30b0\u30b9\u30fc\u30f3", + "\u30ae\u30ea\u30b7\u30e3\u6b63\u6559\u4f1a", + "\u30a2\u30e1\u30ea\u30ab\u56fd\u7acb\u516c\u6587\u66f8\u8a18\u9332\u7ba1\u7406\u5c40", + "\u30bc\u30cd\u30e9\u30eb\u30b9\u30bf\u30c3\u30d5", + "\u82f1\u56fd\u56fd\u6559\u4f1a\u7cfb\u6559\u4f1a", + "\u30ed\u30fc\u30de\u6cd5", + "\u30d0\u30d7\u30c6\u30b9\u30c8\u6559\u4f1a", + "\u30d6\u30e9\u30c3\u30af\u30de\u30fc\u30b1\u30c3\u30c8", + "\u30a2\u30e1\u30ea\u30ab\u56fd\u5bb6\u5075\u5bdf\u5c40", + "\u30ae\u30ea\u30b7\u30a2\u6b63\u6559", + "nasa", + "\u53f0\u6e7e\u52b4\u50cd\u515a", + 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"\u30ac\u30fc\u30c7\u30f3_\u30d1\u30fc\u30c6\u30a3\u30fc", + "\u30a2\u30e1\u30ea\u30ab\u5408\u8846\u56fd\u5185\u56fd\u6b73\u5165\u5e81", + "\u30d6\u30e9\u30c3\u30af\u30ad\u30e3\u30c3\u30c8", + "\u79d1\u5b66\u6280\u8853\u5e81", + "\u30ab\u30fc\u30dc\u30d9\u30eb\u30c7", + "ec", + "\u30af\u30e9\u30d5\u30c8\u30e6\u30cb\u30aa\u30f3", + "\u793e\u6c11", + "\u30a2\u30e1\u30ea\u30ab\u6cbf\u5cb8\u8b66\u5099\u968a", + "\u30a2\u30e1\u30ea\u30ab\u5408\u8846\u56fd\u884c\u653f\u7ba1\u7406\u4e88\u7b97\u5c40", + "\u30ab\u30d5\u30a7\u30aa\u30fc\u30ec", + "ai", + "\u6b66\u65ad\u653f\u6cbb", + "\u8d64\u5341\u5b57", + "\u30c0\u30a6\u30cb\u30f3\u30b0\u8857", + "\u30ed\u30b7\u30a2\u5171\u7523\u515a", + "\u30b5\u30fc\u30c9_\u30d1\u30fc\u30c6\u30a3\u30fc", + "gop", + "\u30af\u30e9\u30b9_\u30a2\u30af\u30b7\u30e7\u30f3", + "dia", + "\u30bc\u30cd\u30e9\u30eb\u30e6\u30cb\u30aa\u30f3", + "\u9664\u65e5", + "\u30bd\u30b7\u30a2\u30eb\u30bb\u30ad\u30e5\u30ea\u30c6\u30a3\u30fc", + "\u30a2\u30e1\u30ea\u30ab\u30f3\u30b9\u30af\u30fc\u30eb", + "\u30af\u30de\u306e\u30d7\u30fc\u3055\u3093", + "\u30db\u30ef\u30a4\u30c8\u30b4\u30fc\u30eb\u30c9", + "\u533b\u5b66\u5927\u5b66\u9662", + "\u5c0f\u5b66", + "\u30a2\u30d5\u30ea\u30ab\u9023\u5408", + "\u30bb\u30f3\u30c8\u30b8\u30e7\u30fc\u30bc\u30d5", + "gatt", + "\u795e\u8056\u30ed\u30fc\u30de\u5e1d\u56fd", + "\u5de5\u696d\u5c02\u9580\u5b66\u6821", + "\u30a2\u30e1\u30ea\u30ab\u56fd\u7acb\u885b\u751f\u7814\u7a76\u6240", + "\u30b5\u30fc\u30c9\u30d1\u30fc\u30c6\u30a3", + "\u30ab\u30c8\u30ea\u30c3\u30af\u6559\u4f1a", + "\u30a2\u30e1\u30ea\u30ab\u30f3\u30e9\u30b0\u30d3\u30fc", + "\u30a4\u30f3\u30c6\u30ea\u30b8\u30a7\u30f3\u30c8\u30b7\u30b9\u30c6\u30e0\u30ba", + "\u5fa1\u7528\u7d44\u5408", + "\u30c8\u30ec\u30fc\u30c9_\u30e6\u30cb\u30aa\u30f3", + "\u30db\u30c3\u30c8\u30bd\u30fc\u30b9", + "\u7c92\u7c92\u8f9b\u82e6_\u3059\u308b", + "\u30c1\u30e5\u30fc\u30a4\u30f3\u30ac\u30e0", + "\u30b9\u30da\u30ea\u30aa\u30eb\u6e56", + "\u30a2\u30e1\u30ea\u30ab\u9678\u8ecd", + "\u30a2\u30e1\u30ea\u30ab\u56fd\u9632\u7dcf\u7701", + "\u642d\u4e57\u3057\u3066", + "\u4e0b\u306e\u4e0a\u306e", + "\u7c92\u3005\u8f9b\u82e6_\u3059\u308b", + "\u30d6\u30eb\u30fc\u30ab\u30e9\u30fc\u306e", + "\u4e0b\u9662\u8b70", + "\u30a2\u30fc\u30c8\u30ae\u30e3\u30e9\u30ea\u30fc", + "\u4e2d\u6d41\u793e\u4f1a", + "\u30d7\u30ed\u30ec\u30bf\u30ea\u30e4\u30fc\u30c8", + "\u30a2\u30e1\u30ea\u30ab\u8b70\u4f1a\u56f3\u66f8\u9928", + "\u30a2\u30e1\u30ea\u30ab\u5408\u8846\u56fd\u9023\u90a6\u7dca\u6025\u4e8b\u614b\u7ba1\u7406\u5e81", + "\u30e8\u30fc\u30ed\u30c3\u30d1\u9023\u5408", + "\u7acb\u61b2\u6c11\u653f\u515a", + "\u30d7\u30c1\u30d6\u30eb\u30b8\u30e7\u30a2", + "\u663c\u52e4", + "\u6559\u80b2\u6a5f\u95a2", + "\u8d64\u5341\u5b57\u793e", + "\u6c11\u793e\u515a", + "\u30af\u30eb\u30a3\u30f4\u30a3\u30fc\u30a4_\u30ea\u30fc\u30d5", + "\u30a2\u30e1\u30ea\u30ab\u56fd\u9632\u5175\u7ad9\u5c40", + "a_\u30af\u30e9\u30b9", + "\u30a2\u30eb\u30e1\u30cb\u30a2\u6559\u4f1a", + "\u30c4\u30d0\u30e1", + "\u30a2\u30e1\u30ea\u30ab\u539f\u5b50\u529b\u59d4\u54e1\u4f1a", + "\u30d7\u30ed\u30ec\u30bf\u30ea\u30a2\u968e\u7d1a", + "\u30a4\u30f3\u30c0\u30b9\u30c8\u30ea\u30a2\u30eb\u30d1\u30fc\u30af", + "\u30b7\u30e7\u30c3\u30d4\u30f3\u30b0_\u30e2\u30fc\u30eb", + "\u6838\u90fd\u5e02", + "\u30d5\u30ec\u30f3\u30c9\u6559\u4f1a", + "\u30bb\u30f3\u30c8_\u30b8\u30e7\u30f3\u30ba_\u30ab\u30ec\u30c3\u30b8", + "\u30a2\u30e1\u30ea\u30ab\u6d77\u5175\u968a", + "\u5f79\u5834", + "\u30ed\u30fc\u30bf\u30ea\u30fc\u30af\u30e9\u30d6", + "\u30a2\u30e1\u30ea\u30ab\u5408\u8846\u56fd\u56fd\u52d9\u7701", + "\u99c5\u9013\u5c40", + "\u30a2\u30e1\u30ea\u30ab\u52b4\u50cd\u7dcf\u540c\u76df\u7523\u696d\u5225\u4f1a\u8b70", + "\u30c1\u30e3\u30f3\u30b0", + "\u30c1\u30e5\u30a4\u30f3\u30ac\u30e0", + "\u30b5\u30fc\u30d3\u30b9\u30d3\u30e5\u30fc\u30ed", + "\u30a2\u30e1\u30ea\u30ab\u56fd\u5bb6\u5b89\u5168\u4fdd\u969c\u5c40", + "\u30d6\u30eb\u30b8\u30e7\u30a2\u793e\u4f1a", + "\u30d7\u30c1_\u30d6\u30eb\u30b8\u30e7\u30a2", + "\u30a2\u30e1\u30ea\u30ab\u5408\u8846\u56fd\u4e0a\u9662", + "\u30aa\u30ea\u30fc\u30d6\u5c71", + "\u5b66\u3073\u306e\u5712", + "\u8239\u4e0a", + "\u30a2\u30e1\u30ea\u30ab\u90f5\u4fbf\u516c\u793e", + "\u30a2\u30e1\u30ea\u30ab\u98df\u54c1\u533b\u85ac\u54c1\u5c40", + "\u30df\u30c9\u30eb\u30af\u30e9\u30b9", + "\u30a2\u30e1\u30ea\u30ab\u5408\u8846\u56fd\u4e0b\u9662", + "nato", + "\u65e5\u672c\u81ea\u7531\u515a", + "\u30a4\u30b9\u30e9\u30e0\u539f\u7406\u4e3b\u7fa9", + "\u30af\u30a8\u30b9\u30c1\u30e7\u30f3\u30de\u30fc\u30af", + "\u65e5\u5171", + "\u8f9b\u82e6_\u3059\u308b", + "\u30a2\u30e1\u30ea\u30ab\u9678\u8ecd\u7279\u6b8a\u90e8\u968a\u7fa4", + "\u52b4\u50cd\u8005\u968e\u7d1a\u306e", + "\u30a2\u30e1\u30ea\u30ab\u56fd\u7acb\u6a19\u6e96\u6280\u8853\u7814\u7a76\u6240", + "\u30d5\u30e9\u30f3\u30b9\u5916\u4eba\u90e8\u968a", + "\u30b7\u30c6\u30a3\u30fc_\u30db\u30fc\u30eb", + "\u30d1\u30d6\u30ea\u30c3\u30af\u30b9\u30af\u30fc\u30eb", + "\u30de\u30b9\u30bf\u30fc\u30ad\u30fc", + "mi", + "\u30a2\u30e1\u30ea\u30ab\u7d71\u5408\u53c2\u8b00\u672c\u90e8", + "\u30de\u30fc\u30c1\u30e3\u30f3\u30c8\u30d0\u30f3\u30af", + "\u30a2\u30e1\u30ea\u30ab\u6d77\u8ecd", + "in_situ", + "\u50cd\u304d\u8a70\u3081\u308b", + "\u52b4\u50cd\u8005\u968e\u7d1a", + "\u6700\u9ad8\u88c1", + "\u56fd\u6c11\u5927\u4f1a", + "\u30aa\u30dd\u30b8\u30b7\u30e7\u30f3_\u30d1\u30fc\u30c6\u30a3\u30fc", + "doc", + "\u30ae\u30ea\u30b7\u30a2\u6b63\u6559\u4f1a", + "\u4e2d\u9593\u968e\u7d1a", + "\u30a2\u30e1\u30ea\u30ab\u822a\u7a7a\u5b87\u5b99\u5c40", + "\u30ab\u30eb\u30e1\u30eb\u5c71", + "\u4e0b\u5c64\u968e\u7d1a\u4e0a\u90e8\u5c64\u306e", + "\u30ae\u30ea\u30b7\u30e3\u795e\u8a71", + "\u30ac\u30fc\u30c7\u30f3\u30d1\u30fc\u30c6\u30a3\u30fc", + "\u30bb\u30f3\u30c8\u30b8\u30e7\u30f3\u30ba", + "\u52b4\u4f5c_\u3059\u308b", + "\u5c0f\u4e57", + "\u9032\u6b69\u515a", + "\u30d0\u30e9\u30e2\u30f3\u6559", + "\u4e09\u4eba\u59c9\u59b9", + "\u30a4\u30f3\u30b0\u30e9\u30f3\u30c9\u9280\u884c", + "\u30a2\u30e1\u30ea\u30ab\u4e2d\u592e\u60c5\u5831\u5c40", + "\u30a2\u30e1\u30ea\u30ab\u30f3\u30d5\u30c3\u30c8\u30dc\u30fc\u30eb", + "\u30c8\u30e0_\u30b5\u30e0", + "\u4eba\u6c11\u6226\u7dda", + "reit", + "\u30bb\u30f3\u30c8\u30af\u30ec\u30a2\u6e56", + "\u30d7\u30e9\u30a4\u30de\u30ea\u30fc\u30b9\u30af\u30fc\u30eb", + "\u6c11\u4e3b\u515a", + "\u521d\u7b49\u5b66\u6821", + "eu", + "\u4eba\u6c11\u515a", + "\u30de\u30eb\u30af\u30b9\u5144\u5f1f", + "\u30bb\u30f3\u30c8\u30d8\u30ec\u30ca", + "\u30b3\u30f3\u30b9\u30bf\u30f3\u30c4\u516c\u4f1a\u8b70", + "\u30c1\u30e3\u30fc\u30f4\u30a3\u30f3", + "\u30db\u30c3\u30c8_\u30bd\u30fc\u30b9", + "\u30d1\u30d6\u30ea\u30c3\u30af\u30aa\u30d4\u30cb\u30aa\u30f3", + "\u30e1\u30fc\u30b8\u30e3\u30fc\u30ea\u30fc\u30b0", + "\u30aa\u30ea\u30f3\u30d4\u30c3\u30af\u6751", + "\u753a\u5f79\u5834", + "\u30a2\u30e1\u30ea\u30ab\u30f3\u822a\u7a7a", + "\u30b4\u30fc\u30eb\u30c7\u30f3\u30a8\u30fc\u30b8", + "\u30a2\u30e1\u30ea\u30ab\u52b4\u50cd\u7dcf\u540c\u76df", + "\u4e57\u8239\u3057\u3066", + "\u30a8\u30a2\u30d5\u30a9\u30fc\u30b9", + "\u30a4\u30f3\u30d9\u30b9\u30c8\u30e1\u30f3\u30c8\u30ab\u30f3\u30d1\u30cb\u30fc", + "\u30d6\u30eb\u30b8\u30a7\u30a2\u30b8\u30fc", + "\u30ae\u30ea\u30b7\u30a2\u795e\u8a71", + "\u30d5\u30eb\u30fc\u30c4_\u30b5\u30e9\u30c0", + "\u30a2\u30eb\u30b8\u30e3\u30b8\u30fc\u30e9", + "\u30a2\u30e4\u30bd\u30d5\u30a3\u30a2", + "\u30a2\u30e1\u30ea\u30ab\u7a7a\u8ecd", + "\u30b8\u30ed\u30f3\u30c9", + "\u8cc3\u91d1\u52b4\u50cd\u8005\u306e" + ], + "ANIMAL": [ + "\u30e9\u30c3\u30b5\u71b1\u30a6\u30a4\u30eb\u30b9", + "\u30aa\u30fc\u30eb\u30c9\u30a4\u30f3\u30b0\u30ea\u30c3\u30b7\u30e5\u30b7\u30fc\u30d7\u30c9\u30c3\u30b0", + "\u30a4\u30fc\u30b9\u30bf\u30fc\u30d0\u30cb\u30fc", + "\u5e2f\u72b6\u75b1\u75b9\u30a6\u30a4\u30eb\u30b9", + "\u30aa\u30ec\u30f3\u30b8\u30d2\u30ad\u30ac\u30a8\u30eb", + "\u30ef\u30fc\u30ad\u30f3\u30b0\u30c9\u30c3\u30b0", + "\u30d6\u30e9\u30a6\u30f3\u30c8\u30e9\u30a6\u30c8", + "\u30b5\u30fc\u30b8\u30e3\u30f3\u30c8\u30e1\u30fc\u30b8\u30e3\u30fc", + "\u30a2\u30a4\u30ea\u30c3\u30b7\u30e5\u30a6\u30eb\u30d5\u30cf\u30a6\u30f3\u30c9", + "\u30bb\u30ad\u30b7\u30e7\u30af\u30e4\u30b1\u30a4", + "\u30a8\u30ea\u30de\u30ad\u30e9\u30a4\u30c1\u30e7\u30a6", + "\u30c8\u30e9\u30b3\u30fc\u30de\u75c5\u539f\u4f53", + "\u8178\u30c1\u30d5\u30b9\u83cc", + "\u30b9\u30b3\u30c3\u30c1\u30c6\u30ea\u30a2", + "\u30cf\u30b4\u30ed\u30e2\u30ac\u30e9\u30b9", + "\u5358\u7d14\u75b1\u75b9\u30a6\u30a4\u30eb\u30b9", + "\u30b8\u30d5\u30c6\u30ea\u30a2\u83cc", + "\u75d8\u7621\u30a6\u30a4\u30eb\u30b9", + "\u30b3\u30ed\u30e9\u30c9\u8449\u866b", + "\u30b8\u30e3\u30fc\u30de\u30f3\u30b7\u30a7\u30d1\u30fc\u30c9", + "\u30e0\u30e9\u30b5\u30ad\u30de\u30b7\u30b3", + "\u30b9\u30ed\u30fc_\u30a6\u30a4\u30eb\u30b9", + "\u30b7\u30e5\u30eb\u30c4\u30a7\u30de\u30c0\u30cb", + "\u5358\u7d14\u75b1\u75b9", + "\u7684\u9bdb", + "mink", + "\u30d8\u30eb\u30de\u30f3\u30ea\u30af\u30ac\u30e1", + "\u30b9\u30da\u30a4\u30f3\u30df\u30ba\u30c8\u30ac\u30ea\u30cd\u30ba\u30df", + "\u30e0\u30e9\u30b5\u30ad\u30c4\u30d0\u30e1", + "\u30ae\u30cb\u30fc_\u30d4\u30c3\u30b0", + "\u30e0\u30e9\u30b5\u30ad\u30cc\u30bf\u30a6\u30ca\u30ae", + "\u30ea\u30b9\u30c6\u30ea\u30a2\u83cc", + "\u30b0\u30ec\u30fc\u30c8\u30cf\u30f3\u30de\u30fc\u30d8\u30c3\u30c9", + "\u30d6\u30e9\u30a4\u30f3\u30b7\u30e5\u30ea\u30f3\u30d7", + "\u30b9\u30d7\u30ea\u30f3\u30ac\u30fc\u30b9\u30d1\u30cb\u30a8\u30eb", + "\u30b0\u30ec\u30fc\u30c8\u30c7\u30f3", + "\u30aa\u30fc\u30b7\u30e3\u30cb\u30c3\u30af\u30db\u30ef\u30a4\u30c8\u30c6\u30a3\u30c3\u30d7\u30b7\u30e3\u30fc\u30af", + "\u30a6\u30a8\u30b9\u30c8\u30ca\u30a4\u30eb\u30a6\u30a4\u30eb\u30b9", + "\u30b3\u30ed\u30e9\u30c9\u30cf\u30e0\u30b7", + "chicken", + "\u30ae\u30ea\u30b7\u30e3\u30ea\u30af\u30ac\u30e1", + "\u9e1a\u9d61\u8c9d", + "\u30de\u30c8\u30a6\u30c0\u30a4", + 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"bengkuang", + "par\u00e9", + "dewandaru", + "zaitun", + "blackberry", + "trembesi", + "mlinjo", + "juwawut", + "sawi", + "jamb\u00e9", + "pring", + "bengkowang", + "tembako" + ], + "DISEASE": [ + "hydrocephalus", + "sars", + "sampar", + "kalor", + "panyakit", + "progeria", + "watuk", + "sunar", + "anestesi", + "stroke", + "kukul", + "buyuten", + "rabi\u00e8s", + "gimp", + "radhiasi", + "panyakit_ebola", + "mi", + "gondhok", + "materialisme", + "kastanya", + "tetikus", + "salmonella", + "malaria" + ], + "PUBLIC_FIGURE": [ + "benjamin_franklin", + "johann_bernoulli", + "c", + "douglas_macarthur", + "mary_wollstonecraft", + "maria_magdalena", + "winston_churchill", + "karl_landsteiner", + "ivan_pavlov", + "dmitri_shostakovich", + "paul_mccartney", + "francis_crick", + "isaac_newton", + "milton_friedman", + "george_stephenson", + "george_orwell", + "richard_wagner", + "marie_curie", + "michael_jackson", + "thomas_hobbes", + "samuel_beckett", + "galileo_galilei", + "robert_koch", + "george_eastman", + "john_steinbeck", + "edmund_hillary", + "vincent_van_gogh", + "josef_stalin", + "emiliano_zapata", + "elisabet", + "yuri_gagarin", + "willem_einthoven", + "samuel_johnson", + "marie_antoinette", + "giuseppe_verdi", + "abel_tasman", + "henri_becquerel", + "henri_matisse", + "louis_pasteur", + "hugo_grotius", + "charles_de_gaulle", + "paul_von_hindenburg", + "ludwig_wittgenstein", + "dante_alighieri", + "theodor_schwann", + "joseph_priestley", + "nicolas_poussin", + "oscar_wilde", + "richard_trevithick", + "francis_bacon", + "immanuel_kant", + "james_franck", + "johannes_kepler", + "max_planck", + "scott_joplin", + "canberra", + "elias_canetti", + "edward_jenner", + "igor_stravinsky", + "william_herschel", + "montesquieu", + "niels_bohr", + "bertrand_russell", + "michael_faraday", + "jan_tinbergen", + "irving_berlin", + "rudolf_diesel", + "walt_disney", + "gabriel_lippmann", + "gustav_mahler", + "ian_fleming", + "richard_feynman", + "theodor_mommsen", + "elizabeth_taylor", + "indira_gandhi", + "george_gershwin", + "alfred_nobel", + "jesse_owens", + "marco_polo", + "daniel_bernoulli", + "henri_bergson", + "gottfried_leibniz", + "hans_christian_andersen", + "pieter_zeeman", + "pablo_picasso", + "otto_hahn", + "christiaan_huygens", + "adam_smith", + "henry_miller", + "karl_marx", + "paul_bunyan", + "friedrich_nietzsche", + "john_wesley", + "al_capone", + "john_locke", + "alexis_carrel", + "helen_keller", + "leonard_bloomfield", + "jean_piaget", + "valentina_tereshkova", + "colin_powell", + "benjamin_thompson", + "adolf_hitler", + "fritz_haber", + "joseph_haydn", + "garfield", + "robert_boyle", + "rosa_parks", + "vladimir_putin", + "anne_hathaway", + "charles_coulomb", + "johns_hopkins", + "christopher_columbus", + "andrew_jackson", + "louis_armstrong", + "robert_brown", + "bobby_fischer", + "johannes_gutenberg", + "putin", + "jean_de_la_fontaine", + "robert_hooke", + "mary_harris", + "peter_o'toole", + "william_shockley", + 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+ "salikur", + "selangkung", + "leksa", + "selikur", + "rolikur", + "anders_celsius" + ], + "DATE": [ + "bodo_kaji", + "the_day_after_tomorrow", + "dina_bastille", + "bodo_besar", + "riyaya" + ], + "RELIGION_MEMBER": [ + "guru", + "moor", + "wong_muslim", + "sunni", + "kangmas" + ], + "PRODUCT": [ + "justin_bieber", + "fyodor_dostoyevsky", + "hak_asasi_manungsa", + "cemara_natal", + "julius_caesar", + "s\u00e3o_tom\u00e9_lan_pr\u00edncipe", + "the_star_spangled_banner", + "piranti_musik", + "sachsen_anhalt", + "the_lord_of_the_rings", + "the_red_hot_chili_peppers", + "ferdinand_magellan", + "nordrhein_westfalen", + "prejanj\u00e8n_anyar" + ], + "UNION": [ + "itu", + "sar\u00e9kat_dagang" + ], + "RELIGION": [ + "shinto", + "salafiyah" + ], + "PERSON": [ + "julius_caesar", + "al_gore", + "dominikus", + "kar\u00e8t" + ], + "GPE": [ + "dina_valentine", + "dar_es_salaam", + "gedung_putih", + "hagia_sophia", + "ser\u00e9", + "simon_petrus", + "al_andalus", + "nikolas_saka_myra" + ], + "LOCATION": [ + "selat_melaka", + "saint_lucia", + "angkatan_udhara", + "al_haram_al_qudsi_asy_syarif", + "sri_lanka", + "gunung_karmel", + "am\u00e9rika_sar\u00e9kat", + "samudra_hindhia", + "tanjung_verde" + ], + "SOC_ECO_CLASS": [ + "samurai", + "\ua9a5\ua9bc\ua982\ua9a0\ua9a4\ua9b6\ua9b2\ua9a4\ua9c0", + "jati", + "shinobi", + "tetan\u00e8n" + ], + "FOOD": [ + "glali", + "endhog", + "chili" + ], + "GENDER": [ + "wadon" + ], + "POLITICAL_PARTY": [ + "kuomintang", + "democratic_party", + "nationalsozialistische_deutsche_arbeiterpartei" + ], + "FAC": [ + "peter_ingkang_agung", + "gr\u00e9ja_katulik_roma", + "saint_lucia", + "sekolah_dhasar" + ], + "RACE": [ + "pethak" + ], + "LANGUAGE": [ + "wong_jawa", + "tonga" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "putri": "regulus", + "nduk": "kangmas", + "mbak": "dimas" + }, + "other_gender_swap": {}, + "en_pronoun2gender": { + "she": [ + "wedok", + "wadon", + "mbak" + ] + }, + "en_pronoun2pronoun": { + "they": [ + "jali" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/ka.json b/data_tooling/pii_processing/ontology/data/ka.json new file mode 100644 index 0000000..c0915bb --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/ka.json @@ -0,0 +1,1378 @@ +{ + "RACE": [ + "\u10d8\u10dc\u10d2\u10da\u10d8\u10e1\u10d4\u10da\u10d4\u10d1\u10d8", + "\u10e1\u10d0\u10db\u10ee\u10e0\u10d4\u10d7\u10d0\u10db\u10d4\u10e0\u10d8\u10d9\u10e3\u10da\u10d8", + "\u10d8\u10d0\u10de\u10dd\u10dc\u10d4\u10da\u10d4\u10d1\u10d8", + "\u10d8\u10e0\u10da\u10d0\u10dc\u10d3\u10d8\u10d4\u10da\u10d4\u10d1\u10d8", + "\u10dc\u10d8\u10d3\u10d4\u10e0\u10da\u10d0\u10dc\u10d3\u10d4\u10da\u10d4\u10d1\u10d8", + 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"\u10d9\u10d0\u10ee\u10d0\u10d1\u10d4\u10e0", + "\u10dd\u10db\u10d0\u10e0", + "\u10d8\u10da\u10d8\u10d0", + "\u10d2\u10dd\u10d2\u10d8", + "\u10d1\u10d4\u10e1\u10d8\u10d9", + "\u10d3\u10d8\u10db\u10d8\u10e2\u10e0\u10d8", + "\u10d0\u10dc\u10d6\u10dd\u10e0", + "\u10d2\u10d4\u10dc\u10d0\u10d3\u10d8", + "\u10d4\u10da\u10d2\u10e3\u10ef\u10d0", + "\u10d8\u10d5\u10d0\u10dc\u10d4", + "\u10ef\u10d0\u10d1\u10d0", + "\u10d7\u10dd\u10e0\u10dc\u10d8\u10d9\u10d4", + "\u10ef\u10dd\u10dc\u10d8", + "\u10d6\u10d0\u10d6\u10d0", + "\u10d2\u10d8\u10d2\u10da\u10d0", + "\u10d7\u10d0\u10db\u10d0\u10d6", + "\u10d0\u10e0\u10db\u10d4\u10dc", + "\u10da\u10d0\u10e8\u10d0", + "\u10d8\u10e3\u10e0\u10d8", + "\u10d2\u10dd\u10e9\u10d0", + "\u10d9\u10d0\u10ee\u10d0", + "\u10d5\u10d0\u10ee\u10e2\u10d0\u10dc\u10d2", + "\u10e1\u10d4\u10e0\u10d2\u10dd", + "\u10d7\u10d4\u10d8\u10db\u10e3\u10e0\u10d0\u10d6", + "\u10db\u10e3\u10e0\u10d7\u10d0\u10d6", + "\u10e0\u10dd\u10d8\u10dc", + "\u10e0\u10dd\u10db\u10d0\u10dc", + "\u10d6\u10d0\u10e5\u10d0\u10e0\u10d8\u10d0", + "\u10e0\u10d4\u10d5\u10d0\u10d6", + "\u10d7\u10d4\u10dc\u10d2\u10d8\u10d6", + "\u10dc\u10e3\u10d2\u10d6\u10d0\u10e0", + "\u10d0\u10db\u10d8\u10e0\u10d0\u10dc", + "\u10d2\u10d4\u10da\u10d0", + "\u10d8\u10dd\u10e1\u10d4\u10d1", + "\u10d1\u10d0\u10d3\u10e0\u10d8", + "\u10d0\u10da\u10d4\u10e5\u10e1\u10d0\u10dc\u10d3\u10e0\u10d4", + "\u10d1\u10dd\u10e0\u10d8\u10e1", + "\u10d8\u10e0\u10d0\u10d9\u10da\u10d8", + "\u10dc\u10d8\u10d9\u10d0", + "\u10e8\u10d0\u10e5\u10e0\u10dd", + "\u10db\u10d4\u10e0\u10d0\u10d1", + "\u10dc\u10dd\u10d3\u10d0\u10e0", + "\u10e0\u10dd\u10da\u10d0\u10dc\u10d3", + "\u10db\u10d0\u10da\u10ee\u10d0\u10d6", + "\u10d1\u10d4\u10e1\u10d0\u10e0\u10d8\u10dd\u10dc", + "\u10d8\u10d0\u10d2\u10dd", + "\u10d4\u10db\u10d6\u10d0\u10e0", + "\u10db\u10d8\u10ee\u10d4\u10d8\u10da", + "\u10d9\u10dd\u10d1\u10d0", + "\u10dc\u10e3\u10d9\u10e0\u10d8", + "\u10dd\u10d7\u10d0\u10e0", + "\u10de\u10d0\u10d0\u10e2\u10d0", + "\u10db\u10e3\u10e0\u10db\u10d0\u10dc", + "\u10d5\u10d4\u10e4\u10ee\u10d5\u10d8\u10d0", + "\u10d2\u10e0\u10d8\u10d2\u10dd\u10da", + "\u10db\u10d8\u10e0\u10d8\u10d0\u10dc", + "\u10d0\u10e0\u10e2\u10e3\u10e0", + "\u10d7\u10d4\u10db\u10e3\u10e0", + "\u10d1\u10dd\u10dc\u10d3\u10dd", + "\u10e0\u10d4\u10d6\u10dd", + "\u10d3\u10d4\u10db\u10e3\u10e0", + "\u10e0\u10dd\u10d1\u10d4\u10e0\u10e2", + "\u10d9\u10d0\u10e0\u10da\u10dd", + "\u10d2\u10d8\u10dd\u10e0\u10d2\u10d8", + "\u10d0\u10da\u10d4\u10e5\u10e1", + "\u10e2\u10d0\u10e0\u10d8\u10d4\u10da", + "\u10e0\u10d0\u10e2\u10d8", + "\u10d5\u10d0\u10da\u10d4\u10e0\u10d8", + "\u10ef\u10e3\u10db\u10d1\u10d4\u10e0" + ], + "FIRST_NAME": [ + "\u10e3\u10e9\u10d0", + "\u10d6\u10e3\u10e0\u10d0\u10d1", + "\u10d2\u10dd\u10d2\u10d0", + "\u10e0\u10d0\u10db\u10d0\u10d6", + "\u10d4\u10d9\u10d0\u10e2\u10d4\u10e0\u10d8\u10dc\u10d4", + "\u10e1\u10dd\u10e1\u10dd", + "\u10d8\u10e0\u10d8\u10dc\u10d0", + "\u10da\u10d4\u10d5\u10d0\u10dc", + "\u10da\u10d8\u10d3\u10d0", + "\u10dc\u10d0\u10d6\u10d8", + "\u10dc\u10d0\u10dc\u10d8", + "\u10e1\u10dd\u10e4\u10d8\u10d9\u10dd", + "\u10d8\u10dc\u10d4\u10d6\u10d0", + "\u10d2\u10e3\u10e0\u10d0\u10db", + "\u10db\u10d8\u10dc\u10d3\u10d8\u10d0", + "\u10df\u10d4\u10dc\u10d8\u10d0", + "\u10d3\u10d0\u10d5\u10d8\u10d7", + "\u10e8\u10d0\u10da\u10d5\u10d0", + "\u10d4\u10da\u10d4\u10dc\u10d4", + "\u10d5\u10d0\u10e1\u10d8\u10da", + "\u10d5\u10da\u10d0\u10d3\u10d8\u10db\u10d4\u10e0", + "\u10d7\u10d0\u10db\u10e3\u10dc\u10d0", + "\u10d4\u10d3\u10e3\u10d0\u10e0\u10d3", + "\u10db\u10d4\u10e0\u10d8", + "\u10d0\u10d5\u10d7\u10d0\u10dc\u10d3\u10d8\u10da", + "\u10dc\u10d0\u10d7\u10d8\u10d0", + "\u10da\u10d8\u10d0", + "\u10dc\u10d0\u10dc\u10e3\u10da\u10d8", + "\u10d1\u10d8\u10eb\u10d8\u10dc\u10d0", + "\u10d8\u10d6\u10dd\u10da\u10d3\u10d0", + "\u10d0\u10e1\u10da\u10d0\u10dc", + "\u10d6\u10d0\u10e3\u10e0", + "\u10d3\u10d0\u10d7\u10dd", + "\u10d0\u10dc\u10d8", + "\u10d2\u10d8\u10d2\u10d0", + "\u10de\u10d4\u10e2\u10e0\u10d4", + "\u10e8\u10dd\u10d7\u10d0", + "\u10d0\u10d9\u10d0\u10d9\u10d8", + "\u10ef\u10d4\u10db\u10d0\u10da", + "\u10d6\u10d5\u10d8\u10d0\u10d3", + "\u10da\u10d8\u10da\u10d8", + "\u10d1\u10d4\u10e5\u10d0", + "\u10d5\u10d0\u10da\u10d4\u10dc\u10e2\u10d8\u10dc\u10d0", + "\u10d5\u10d4\u10e0\u10d0", + "\u10dc\u10d0\u10e2\u10dd", + "\u10d2\u10d8\u10d0", + "\u10dc\u10d0\u10d8\u10e0\u10d0", + "\u10d4\u10da\u10d8\u10d6\u10d0", + "\u10ee\u10d5\u10d8\u10e9\u10d0", + "\u10da\u10d8\u10d0\u10dc\u10d0", + "\u10d2\u10d8\u10d5\u10d8", + "\u10e3\u10e8\u10d0\u10dc\u10d2\u10d8", + "\u10d5\u10d0\u10dc\u10dd", + "\u10de\u10d0\u10d5\u10da\u10d4", + "\u10db\u10d0\u10db\u10e3\u10d9\u10d0", + "\u10d0\u10da\u10d0", + "\u10e1\u10e3\u10da\u10d8\u10d9\u10dd", + "\u10e1\u10d8\u10db\u10dd\u10dc", + "\u10d8\u10d0\u10db\u10d6\u10d4", + "\u10ef\u10e3\u10db\u10d1\u10d4\u10e0", + "\u10d2\u10dd\u10d2\u10d8\u10e2\u10d0", + "\u10db\u10d0\u10d2\u10d3\u10d0", + "\u10d5\u10d8\u10e5\u10e2\u10dd\u10e0", + "\u10dc\u10d8\u10d9\u10dd\u10da\u10dd\u10d6", + "\u10d0\u10d6\u10d0", + "\u10d0\u10e0\u10e9\u10d8\u10da", + "\u10d9\u10dd\u10dc\u10e1\u10e2\u10d0\u10dc\u10e2\u10d8\u10dc\u10d4", + "\u10d2\u10dd\u10d3\u10d4\u10e0\u10eb\u10d8", + "\u10d7\u10d0\u10d7\u10d8\u10d0", + "\u10d8\u10e0\u10d8\u10dc\u10d4", + "\u10d5\u10d0\u10df\u10d0", + "\u10d5\u10d0\u10da\u10d4\u10e0\u10d8\u10d0\u10dc", + "\u10ef\u10e3\u10da\u10d8\u10d4\u10e2\u10d0", + "\u10d9\u10d0\u10ee\u10d0\u10d1\u10d4\u10e0", + "\u10d8\u10d6\u10d0", + "\u10d0\u10e1\u10db\u10d0\u10d7", + "\u10db\u10d0\u10e7\u10d5\u10d0\u10da\u10d0", + "\u10dd\u10db\u10d0\u10e0", + "\u10da\u10d0\u10dc\u10d0", + "\u10dc\u10d0\u10e2\u10d0\u10da\u10d8\u10d0", + "\u10e1\u10d5\u10d4\u10e2\u10da\u10d0\u10dc\u10d0", + "\u10d8\u10da\u10d8\u10d0", + "\u10d2\u10dd\u10d2\u10d8", + "\u10db\u10d0\u10d3\u10dd\u10dc\u10d0", + "\u10d1\u10d4\u10e1\u10d8\u10d9", + "\u10d3\u10d8\u10db\u10d8\u10e2\u10e0\u10d8", + "\u10ea\u10d8\u10e1\u10d0\u10dc\u10d0", + "\u10d0\u10dc\u10d6\u10dd\u10e0", + "\u10d2\u10d5\u10d0\u10dc\u10ea\u10d0", + "\u10d6\u10d0\u10d8\u10e0\u10d0", + "\u10d2\u10d4\u10dc\u10d0\u10d3\u10d8", + "\u10e5\u10d4\u10d7\u10d4\u10d5\u10d0\u10dc", + "\u10d4\u10d5\u10d2\u10d4\u10dc\u10d8\u10d0", + "\u10db\u10d0\u10e0\u10d8\u10d9\u10d0", + "\u10d4\u10da\u10d2\u10e3\u10ef\u10d0", + "\u10e4\u10d8\u10e5\u10e0\u10d8\u10d0", + "\u10d8\u10d5\u10d0\u10dc\u10d4", + "\u10d8\u10e0\u10db\u10d0", + "\u10ef\u10d0\u10d1\u10d0", + "\u10dc\u10d0\u10d3\u10d4\u10ef\u10d3\u10d0", + "\u10d2\u10d8\u10e3\u10da\u10d8", + "\u10e8\u10dd\u10e0\u10d4\u10dc\u10d0", + "\u10d7\u10dd\u10e0\u10dc\u10d8\u10d9\u10d4", + "\u10ef\u10dd\u10dc\u10d8", + "\u10df\u10d0\u10dc\u10d0", + "\u10e0\u10dd\u10d6\u10d0", + "\u10d6\u10d0\u10d6\u10d0", + "\u10d2\u10d8\u10d2\u10da\u10d0", + "\u10d7\u10d0\u10db\u10d0\u10e0", + "\u10da\u10d4\u10dc\u10d0", + "\u10dd\u10da\u10d8\u10d0", + "\u10db\u10d0\u10d8\u10d0", + "\u10ea\u10d8\u10e3\u10e0\u10d8", + "\u10d8\u10dc\u10d2\u10d0", + "\u10dc\u10d8\u10dc\u10d4\u10da\u10d8", + "\u10df\u10e3\u10df\u10e3\u10dc\u10d0", + "\u10db\u10d0\u10e0\u10d8\u10d0", + "\u10e0\u10e3\u10e1\u10e3\u10d3\u10d0\u10dc", + "\u10ee\u10d0\u10d7\u10e3\u10dc\u10d0", + "\u10d4\u10da\u10db\u10d8\u10e0\u10d0", + "\u10e5\u10e0\u10d8\u10e1\u10e2\u10d8\u10dc\u10d4", + "\u10d7\u10d8\u10dc\u10d0\u10d7\u10d8\u10dc", + "\u10d2\u10e3\u10da\u10dc\u10d0\u10e0\u10d0", + "\u10db\u10d8\u10e0\u10d0\u10dc\u10d3\u10d0", + "\u10d7\u10d0\u10db\u10d0\u10d6", + "\u10d4\u10da\u10d8\u10e1\u10dd", + "\u10e1\u10e3\u10e1\u10d0\u10dc\u10d0", + "\u10d7\u10d4\u10d0", + "\u10d0\u10e0\u10db\u10d4\u10dc", + "\u10da\u10d0\u10db\u10d0\u10e0\u10d0", + "\u10da\u10d0\u10e8\u10d0", + "\u10db\u10d0\u10d9\u10d0", + "\u10dc\u10d0\u10d7\u10d4\u10da\u10d0", + "\u10db\u10d0\u10e0\u10d8\u10d0\u10db", + "\u10db\u10d4\u10d3\u10d4\u10d0", + "\u10d8\u10e3\u10e0\u10d8", + "\u10d4\u10d7\u10d4\u10e0", + "\u10e1\u10dd\u10e4\u10d8\u10dd", + "\u10e1\u10dd\u10e4\u10d8\u10d0", + "\u10d7\u10d0\u10db\u10d0\u10e0\u10d0", + "\u10d0\u10dc\u10d8\u10d9\u10dd", + "\u10db\u10d6\u10d8\u10d0", + "\u10e5\u10d4\u10d7\u10d8\u10dc\u10dd", + "\u10d2\u10dd\u10e9\u10d0", + "\u10d9\u10d0\u10ee\u10d0", + "\u10d5\u10d0\u10ee\u10e2\u10d0\u10dc\u10d2", + "\u10e1\u10d4\u10e0\u10d2\u10dd", + "\u10d7\u10d4\u10d8\u10db\u10e3\u10e0\u10d0\u10d6", + "\u10d5\u10d0\u10e0\u10d3\u10dd", + "\u10db\u10e3\u10e0\u10d7\u10d0\u10d6", + "\u10e0\u10dd\u10d8\u10dc", + "\u10dc\u10d0\u10d6\u10d8\u10d9\u10dd", + "\u10e1\u10dd\u10dc\u10d8\u10d0", + "\u10e1\u10d0\u10da\u10dd\u10db\u10d4", + "\u10e0\u10dd\u10db\u10d0\u10dc", + "\u10d6\u10d0\u10e5\u10d0\u10e0\u10d8\u10d0", + "\u10da\u10d4\u10d8\u10da\u10d0", + "\u10d2\u10e3\u10da\u10d8\u10d9\u10dd", + "\u10dc\u10d0\u10dc\u10d0", + "\u10e0\u10d4\u10d5\u10d0\u10d6", + "\u10d5\u10d8\u10dd\u10da\u10d4\u10e2\u10d0", + "\u10da\u10d4\u10da\u10d0", + "\u10da\u10e3\u10d3\u10db\u10d8\u10da\u10d0", + "\u10d7\u10d4\u10dc\u10d2\u10d8\u10d6", + "\u10dc\u10e3\u10d2\u10d6\u10d0\u10e0", + "\u10d7\u10d0\u10db\u10d8\u10da\u10d0", + "\u10d9\u10d0\u10e0\u10d8\u10dc\u10d4", + "\u10d2\u10e3\u10d2\u10e3\u10da\u10d8", + "\u10ea\u10d8\u10e0\u10d0", + "\u10e4\u10d0\u10e2\u10d8", + "\u10d5\u10d4\u10e0\u10d8\u10d9\u10dd", + "\u10d0\u10db\u10d8\u10e0\u10d0\u10dc", + "\u10d2\u10d4\u10da\u10d0", + "\u10d8\u10dd\u10e1\u10d4\u10d1", + "\u10e0\u10d8\u10db\u10d0", + "\u10d1\u10d0\u10d3\u10e0\u10d8", + "\u10d9\u10da\u10d0\u10e0\u10d0", + "\u10d3\u10d8\u10d0\u10dc\u10d0", + "\u10db\u10d0\u10e0\u10d8\u10dc\u10d4", + "\u10d0\u10d8\u10d3\u10d0", + "\u10d0\u10da\u10d4\u10e5\u10e1\u10d0\u10dc\u10d3\u10e0\u10d4", + "\u10d3\u10d0\u10e0\u10d4\u10ef\u10d0\u10dc", + "\u10d1\u10dd\u10e0\u10d8\u10e1", + "\u10d4\u10db\u10d0", + "\u10d8\u10e0\u10d0\u10d9\u10da\u10d8", + "\u10db\u10d4\u10d3\u10d8\u10d9\u10dd", + "\u10db\u10d0\u10dc\u10d0\u10dc\u10d0", + "\u10dc\u10d8\u10d9\u10d0", + "\u10e8\u10d0\u10e5\u10e0\u10dd", + "\u10d1\u10d4\u10da\u10d0", + "\u10dc\u10d4\u10e1\u10e2\u10d0\u10dc", + "\u10e5\u10d4\u10d7\u10dd", + "\u10ee\u10d0\u10e2\u10d8\u10d0", + "\u10db\u10d7\u10d5\u10d0\u10e0\u10d8\u10e1\u10d0", + "\u10dc\u10dd\u10e0\u10d0", + "\u10db\u10d4\u10e0\u10d0\u10d1", + "\u10dc\u10dd\u10d3\u10d0\u10e0", + "\u10db\u10d0\u10e0\u10d8\u10dc\u10d0", + "\u10db\u10d4\u10d2\u10d8", + "\u10dc\u10d8\u10dc\u10dd", + "\u10e0\u10dd\u10da\u10d0\u10dc\u10d3", + "\u10db\u10d0\u10da\u10ee\u10d0\u10d6", + "\u10d1\u10d4\u10e1\u10d0\u10e0\u10d8\u10dd\u10dc", + "\u10d8\u10d0\u10d2\u10dd", + "\u10e4\u10d0\u10e2\u10d8\u10db\u10d0", + "\u10dc\u10d0\u10d6\u10d8\u10d1\u10e0\u10dd\u10da\u10d0", + "\u10dc\u10d0\u10d3\u10d8\u10d0", + "\u10d3\u10dd\u10d3\u10dd", + "\u10d4\u10da\u10d4\u10dc\u10d0", + "\u10ea\u10d8\u10ea\u10d8\u10dc\u10dd", + "\u10db\u10d0\u10e0\u10d2\u10d0\u10da\u10d8\u10e2\u10d0", + "\u10d7\u10d8\u10dc\u10d0", + "\u10d0\u10dc\u10df\u10d4\u10da\u10d0", + "\u10d8\u10d0", + "\u10d4\u10db\u10d6\u10d0\u10e0", + "\u10db\u10d8\u10ee\u10d4\u10d8\u10da", + "\u10d9\u10dd\u10d1\u10d0", + "\u10dc\u10e3\u10d9\u10e0\u10d8", + "\u10dd\u10d7\u10d0\u10e0", + "\u10d0\u10dc\u10dc\u10d0", + "\u10de\u10d0\u10d0\u10e2\u10d0", + "\u10d2\u10d0\u10da\u10d8\u10dc\u10d0", + "\u10db\u10e3\u10e0\u10db\u10d0\u10dc", + "\u10dc\u10d4\u10da\u10d8", + "\u10da\u10d8\u10d6\u10d0", + "\u10e0\u10d8\u10e2\u10d0", + "\u10d5\u10d4\u10e4\u10ee\u10d5\u10d8\u10d0", + "\u10d2\u10e0\u10d8\u10d2\u10dd\u10da", + "\u10db\u10d8\u10e0\u10d8\u10d0\u10dc", + "\u10da\u10d0\u10da\u10d8", + "\u10d6\u10dd\u10d8\u10d0", + "\u10d0\u10e0\u10e2\u10e3\u10e0", + "\u10d7\u10d4\u10db\u10e3\u10e0", + "\u10d6\u10d8\u10dc\u10d0", + "\u10d1\u10dd\u10dc\u10d3\u10dd", + "\u10e0\u10d4\u10d6\u10dd", + "\u10da\u10e3\u10d1\u10d0", + "\u10dc\u10dd\u10dc\u10d0", + "\u10d3\u10d4\u10db\u10e3\u10e0", + "\u10e0\u10dd\u10d1\u10d4\u10e0\u10e2", + "\u10dc\u10e3\u10ea\u10d0", + "\u10dc\u10d0\u10e0\u10d2\u10d8\u10d6\u10d0", + "\u10d0\u10dc\u10d0", + "\u10d5\u10d4\u10dc\u10d4\u10e0\u10d0", + "\u10e2\u10d0\u10e2\u10d8\u10d0\u10dc\u10d0", + "\u10d9\u10d0\u10e0\u10da\u10dd", + "\u10da\u10d0\u10e0\u10d8\u10e1\u10d0", + "\u10d4\u10da\u10d6\u10d0", + "\u10da\u10d0\u10db\u10d6\u10d8\u10e0\u10d0", + "\u10da\u10d8\u10d9\u10d0", + "\u10ea\u10d8\u10d0\u10da\u10d0", + "\u10da\u10e3\u10d8\u10d6\u10d0", + "\u10d2\u10d8\u10dd\u10e0\u10d2\u10d8", + "\u10d0\u10da\u10d4\u10e5\u10e1", + "\u10e2\u10d0\u10e0\u10d8\u10d4\u10da", + "\u10e0\u10d0\u10e2\u10d8", + "\u10dc\u10e3\u10dc\u10e3", + "\u10db\u10d0\u10e0\u10d8", + "\u10db\u10d0\u10e0\u10dd", + "\u10d5\u10d0\u10da\u10d4\u10e0\u10d8", + "\u10d7\u10d0\u10db\u10d0\u10e0\u10d8", + "\u10d7\u10d0\u10db\u10d7\u10d0", + "\u10d7\u10d4\u10dd\u10dc\u10d0", + "\u10dd\u10da\u10e6\u10d0", + "\u10d3\u10d0\u10da\u10d8", + "\u10d4\u10d9\u10d0" + ], + "LAST_NAME": [ + "\u10e9\u10d8\u10e5\u10dd\u10d5\u10d0\u10dc\u10d8", + "\u10ea\u10d0\u10d0\u10d5\u10d0", + "\u10d1\u10e3\u10d9\u10d8\u10d0", + 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"\u10d9\u10d5\u10d0\u10dc\u10e2\u10d0\u10da\u10d8\u10d0\u10dc\u10d8", + "\u10d3\u10d0\u10d5\u10d8\u10d7\u10d0\u10eb\u10d4", + "\u10db\u10e3\u10e1\u10e2\u10d0\u10e4\u10d0\u10d4\u10d5\u10d8", + "\u10d2\u10d5\u10d4\u10da\u10d4\u10e1\u10d8\u10d0\u10dc\u10d8", + "\u10db\u10d2\u10d0\u10da\u10dd\u10d1\u10da\u10d8\u10e8\u10d5\u10d8\u10da\u10d8", + "\u10d2\u10dd\u10ea\u10d8\u10e0\u10d8\u10eb\u10d4", + "\u10db\u10d4\u10e1\u10ee\u10d8", + "\u10e8\u10d5\u10d4\u10da\u10d8\u10eb\u10d4", + "\u10d2\u10dd\u10e0\u10d2\u10d8\u10da\u10d0\u10eb\u10d4", + "\u10d2\u10d0\u10e4\u10e0\u10d8\u10dc\u10d3\u10d0\u10e8\u10d5\u10d8\u10da\u10d8", + "\u10d2\u10dd\u10d2\u10d8\u10e2\u10d8\u10eb\u10d4", + "\u10d2\u10d0\u10d1\u10e0\u10d8\u10ed\u10d8\u10eb\u10d4", + "\u10d9\u10d0\u10dc\u10d3\u10d4\u10da\u10d0\u10d9\u10d8", + "\u10d9\u10dd\u10dc\u10ea\u10d4\u10da\u10d8\u10eb\u10d4", + "\u10d1\u10e0\u10d4\u10d2\u10d0\u10eb\u10d4", + "\u10d8\u10e1\u10d0\u10d4\u10d5\u10d8", + "\u10d2\u10e0\u10d8\u10d2\u10d0\u10da\u10d0\u10e8\u10d5\u10d8\u10da\u10d8", + "\u10d2\u10dd\u10e0\u10d2\u10dd\u10eb\u10d4", + "\u10d9\u10d5\u10d8\u10e0\u10d8\u10d9\u10d0\u10e8\u10d5\u10d8\u10da\u10d8", + "\u10e9\u10dd\u10ee\u10d4\u10da\u10d8", + "\u10e9\u10ee\u10d4\u10d8\u10eb\u10d4", + "\u10dc\u10d8\u10d9\u10dd\u10da\u10d4\u10d8\u10e8\u10d5\u10d8\u10da\u10d8", + "\u10d9\u10d8\u10e0\u10d5\u10d0\u10da\u10d8\u10eb\u10d4", + "\u10d9\u10d0\u10e0\u10d0\u10de\u10d4\u10e2\u10d8\u10d0\u10dc\u10d8", + "\u10e6\u10d5\u10d8\u10dc\u10ef\u10d8\u10da\u10d8\u10d0", + "\u10ee\u10e3\u10e0\u10ea\u10d8\u10eb\u10d4", + "\u10e6\u10d5\u10d8\u10dc\u10d8\u10d0\u10e8\u10d5\u10d8\u10da\u10d8", + "\u10d2\u10d0\u10e9\u10d4\u10e9\u10d8\u10da\u10d0\u10eb\u10d4", + "\u10e1\u10d8\u10db\u10dd\u10dc\u10d8\u10e8\u10d5\u10d8\u10da\u10d8", + "\u10ee\u10d8\u10d6\u10d0\u10dc\u10d8\u10e8\u10d5\u10d8\u10da\u10d8", + "\u10db\u10d2\u10d4\u10da\u10d0\u10eb\u10d4", + "\u10de\u10d0\u10e2\u10d0\u10e0\u10d0\u10d8\u10d0", + "\u10d6\u10d0\u10e0\u10d0\u10dc\u10d3\u10d8\u10d0", + "\u10e9\u10d8\u10ee\u10da\u10d0\u10eb\u10d4", + "\u10df\u10dd\u10e0\u10df\u10dd\u10da\u10d8\u10d0\u10dc\u10d8", + "\u10d3\u10d4\u10db\u10d4\u10e2\u10e0\u10d0\u10e8\u10d5\u10d8\u10da\u10d8", + "\u10d9\u10dd\u10de\u10d0\u10eb\u10d4", + "\u10d3\u10d8\u10d0\u10e1\u10d0\u10db\u10d8\u10eb\u10d4", + "\u10e9\u10ee\u10d0\u10d8\u10eb\u10d4", + "\u10e5\u10d0\u10db\u10d0\u10d3\u10d0\u10eb\u10d4", + "\u10db\u10d4\u10e2\u10e0\u10d4\u10d5\u10d4\u10da\u10d8", + "\u10d0\u10e0\u10e9\u10d5\u10d0\u10eb\u10d4", + "\u10e9\u10d0\u10d9\u10d5\u10d4\u10e2\u10d0\u10eb\u10d4", + "\u10d2\u10dd\u10d2\u10e1\u10d0\u10eb\u10d4", + "\u10e5\u10d0\u10e0\u10e9\u10d0\u10d5\u10d0", + "\u10db\u10d0\u10ee\u10d0\u10e0\u10d0\u10e8\u10d5\u10d8\u10da\u10d8", + "\u10e2\u10d0\u10d9\u10d8\u10eb\u10d4", + "\u10d5\u10d0\u10da\u10d8\u10d4\u10d5\u10d8", + "\u10ed\u10d8\u10dc\u10ed\u10d0\u10e0\u10d0\u10e3\u10da\u10d8", + "\u10db\u10d0\u10ee\u10d0\u10e0\u10d0\u10eb\u10d4", + "\u10d0\u10e0\u10d5\u10d4\u10da\u10d0\u10eb\u10d4", + "\u10e2\u10e3\u10e6\u10e3\u10e8\u10d8", + "\u10d1\u10d4\u10df\u10d0\u10dc\u10d8\u10eb\u10d4", + "\u10d2\u10d0\u10d2\u10e3\u10d0", + "\u10ee\u10d8\u10db\u10e8\u10d8\u10d0\u10e8\u10d5\u10d8\u10da\u10d8", + "\u10e5\u10d0\u10d5\u10d7\u10d0\u10e0\u10d0\u10eb\u10d4", + "\u10d7\u10d0\u10d1\u10d0\u10d2\u10d0\u10e0\u10d8", + "\u10e1\u10d0\u10da\u10e3\u10e5\u10d5\u10d0\u10eb\u10d4", + "\u10d8\u10db\u10dc\u10d0\u10eb\u10d4", + "\u10d9\u10d8\u10e0\u10d9\u10d8\u10e2\u10d0\u10eb\u10d4", + "\u10db\u10d0\u10ed\u10d0\u10e0\u10d0\u10e8\u10d5\u10d8\u10da\u10d8", + "\u10dc\u10d0\u10e1\u10e7\u10d8\u10d3\u10d0\u10e8\u10d5\u10d8\u10da\u10d8", + "\u10e2\u10e7\u10d4\u10db\u10d0\u10da\u10d0\u10eb\u10d4", + "\u10d1\u10d0\u10e0\u10d1\u10d0\u10e5\u10d0\u10eb\u10d4", + "\u10d9\u10e3\u10ee\u10d8\u10d0\u10dc\u10d8\u10eb\u10d4", + "\u10db\u10d0\u10ed\u10d0\u10d5\u10d0\u10e0\u10d8\u10d0\u10dc\u10d8", + "\u10d9\u10d0\u10d6\u10d0\u10e0\u10d8\u10d0\u10dc\u10d8", + "\u10ea\u10d0\u10e0\u10ea\u10d8\u10eb\u10d4", + "\u10eb\u10dc\u10d4\u10da\u10d0\u10eb\u10d4", + "\u10d9\u10d8\u10dc\u10ec\u10e3\u10e0\u10d0\u10e8\u10d5\u10d8\u10da\u10d8", + "\u10d9\u10d5\u10d0\u10e0\u10d0\u10ea\u10ee\u10d4\u10da\u10d8\u10d0", + "\u10e2\u10e3\u10e0\u10d0\u10e8\u10d5\u10d8\u10da\u10d8", + "\u10df\u10e6\u10d4\u10dc\u10e2\u10d8", + "\u10d2\u10d5\u10d4\u10dc\u10d4\u10e2\u10d0\u10eb\u10d4", + "\u10ee\u10d0\u10e2\u10d8\u10d0\u10e8\u10d5\u10d8\u10da\u10d8", + "\u10d1\u10d8\u10ec\u10d0\u10eb\u10d4", + "\u10db\u10d4\u10d2\u10e0\u10d4\u10da\u10d8\u10e8\u10d5\u10d8\u10da\u10d8", + "\u10db\u10d4\u10da\u10d0\u10eb\u10d4", + "\u10ee\u10d0\u10e0\u10d0\u10d1\u10d0\u10eb\u10d4", + "\u10d0\u10d3\u10e3\u10d0\u10e8\u10d5\u10d8\u10da\u10d8", + "\u10d2\u10dd\u10d2\u10e3\u10d0", + "\u10d0\u10ee\u10d0\u10da\u10d0\u10d8\u10d0", + "\u10ee\u10e3\u10ea\u10d8\u10e8\u10d5\u10d8\u10da\u10d8", + "\u10d8\u10dc\u10d0\u10e1\u10d0\u10e0\u10d8\u10eb\u10d4", + "\u10d0\u10da\u10d0\u10d3\u10d0\u10e8\u10d5\u10d8\u10da\u10d8", + "\u10de\u10d4\u10e2\u10e0\u10dd\u10e1\u10d8\u10d0\u10dc\u10d8", + "\u10d2\u10e0\u10eb\u10d4\u10da\u10d8\u10e8\u10d5\u10d8\u10da\u10d8", + "\u10ef\u10d0\u10dc\u10ef\u10e6\u10d0\u10d5\u10d0", + "\u10d1\u10d0\u10d9\u10e3\u10e0\u10d0\u10eb\u10d4", + "\u10d5\u10d0\u10e0\u10e8\u10d0\u10dc\u10d8\u10eb\u10d4", + "\u10d5\u10d0\u10e0\u10d3\u10dd\u10e1\u10d0\u10dc\u10d8\u10eb\u10d4", + "\u10e9\u10d0\u10d3\u10e3\u10dc\u10d4\u10da\u10d8", + "\u10e4\u10d4\u10d8\u10e5\u10e0\u10d8\u10e8\u10d5\u10d8\u10da\u10d8", + "\u10d8\u10dd\u10d1\u10d8\u10eb\u10d4", + "\u10e5\u10d0\u10e0\u10ea\u10d8\u10d5\u10d0\u10eb\u10d4", + "\u10d9\u10d0\u10da\u10d0\u10dc\u10d3\u10d0\u10eb\u10d4", + "\u10d2\u10d4\u10da\u10d0\u10eb\u10d4", + "\u10d9\u10d0\u10ea\u10d8\u10e2\u10d0\u10eb\u10d4", + "\u10d3\u10d0\u10e0\u10d1\u10d0\u10d8\u10eb\u10d4", + "\u10e3\u10d2\u10e0\u10d4\u10ee\u10d4\u10da\u10d8\u10eb\u10d4", + "\u10d9\u10d4\u10d5\u10da\u10d8\u10e8\u10d5\u10d8\u10da\u10d8", + "\u10e0\u10dd\u10d1\u10d0\u10e5\u10d8\u10eb\u10d4", + "\u10ea\u10dd\u10db\u10d0\u10d8\u10d0", + "\u10d1\u10dd\u10ed\u10dd\u10e0\u10d8\u10e8\u10d5\u10d8\u10da\u10d8", + "\u10dc\u10dd\u10d6\u10d0\u10eb\u10d4", + "\u10ee\u10d4\u10da\u10d0\u10eb\u10d4", + "\u10e7\u10d8\u10e4\u10e8\u10d8\u10eb\u10d4", + "\u10d2\u10e3\u10db\u10d1\u10d4\u10e0\u10d8\u10eb\u10d4", + "\u10e5\u10dd\u10d1\u10d0\u10da\u10d8\u10d0", + "\u10ea\u10e3\u10ea\u10e5\u10d8\u10e0\u10d8\u10eb\u10d4", + "\u10d7\u10e3\u10e0\u10db\u10d0\u10dc\u10d8\u10eb\u10d4", + "\u10e8\u10d0\u10d8\u10dc\u10d8\u10eb\u10d4", + "\u10d9\u10dd\u10d1\u10d4\u10e0\u10d8\u10eb\u10d4", + "\u10dc\u10d0\u10d9\u10d0\u10e8\u10d8\u10eb\u10d4", + "\u10d1\u10d4\u10e0\u10e3\u10da\u10d0\u10d5\u10d0", + "\u10d2\u10dd\u10d2\u10e3\u10d0\u10eb\u10d4", + "\u10ef\u10d8\u10d1\u10da\u10d0\u10eb\u10d4", + "\u10d4\u10da\u10d8\u10d6\u10d1\u10d0\u10e0\u10d0\u10e8\u10d5\u10d8\u10da\u10d8", + "\u10e0\u10dd\u10e1\u10e2\u10d8\u10d0\u10e8\u10d5\u10d8\u10da\u10d8", + "\u10e5\u10d0\u10e0\u10d7\u10d5\u10d4\u10da\u10d8\u10e8\u10d5\u10d8\u10da\u10d8", + "\u10d1\u10d4\u10e0\u10d0\u10d8\u10d0", + "\u10d6\u10d0\u10e0\u10e5\u10e3\u10d0", + "\u10d7\u10dd\u10d3\u10e3\u10d0", + "\u10ea\u10d8\u10e0\u10d4\u10d9\u10d8\u10eb\u10d4", + "\u10d9\u10e3\u10de\u10e0\u10d4\u10d8\u10e8\u10d5\u10d8\u10da\u10d8", + "\u10e1\u10e3\u10e0\u10db\u10d0\u10dc\u10d8\u10eb\u10d4", + "\u10dc\u10d0\u10e0\u10d8\u10db\u10d0\u10dc\u10d8\u10eb\u10d4", + "\u10d9\u10d0\u10ee\u10d0\u10eb\u10d4", + "\u10e1\u10d5\u10d0\u10dc\u10d8\u10eb\u10d4", + "\u10ed\u10d9\u10d0\u10d3\u10e3\u10d0", + "\u10dc\u10d0\u10ed\u10e7\u10d4\u10d1\u10d8\u10d0", + "\u10d0\u10d3\u10d0\u10db\u10d8\u10d0", + "\u10d8\u10e0\u10d4\u10db\u10d0\u10eb\u10d4", + "\u10ed\u10d0\u10dc\u10e2\u10e3\u10e0\u10d8\u10eb\u10d4", + "\u10e2\u10d0\u10d1\u10d0\u10e2\u10d0\u10eb\u10d4", + "\u10de\u10d4\u10e2\u10e0\u10d8\u10d0\u10e8\u10d5\u10d8\u10da\u10d8", + "\u10e8\u10dd\u10dc\u10d8\u10d0", + "\u10d1\u10d8\u10d1\u10d8\u10da\u10d0\u10e8\u10d5\u10d8\u10da\u10d8", + "\u10d6\u10dd\u10d8\u10eb\u10d4", + "\u10e5\u10dd\u10e0\u10d8\u10eb\u10d4", + "\u10d1\u10d4\u10e0\u10d8\u10d0\u10dc\u10d8\u10eb\u10d4", + "\u10d0\u10d1\u10d3\u10e3\u10da\u10d0\u10d4\u10d5\u10d8", + "\u10dd\u10e5\u10e0\u10dd\u10de\u10d8\u10e0\u10d8\u10eb\u10d4", + "\u10db\u10d8\u10e5\u10d4\u10da\u10d0\u10eb\u10d4", + "\u10ee\u10dd\u10e0\u10d0\u10d5\u10d0", + "\u10d2\u10e3\u10da\u10e3\u10d0", + "\u10e5\u10dd\u10d1\u10e3\u10da\u10d0\u10eb\u10d4", + "\u10ec\u10d8\u10e5\u10d0\u10e0\u10d8\u10e8\u10d5\u10d8\u10da\u10d8", + "\u10da\u10d0\u10ea\u10d0\u10d1\u10d8\u10eb\u10d4", + "\u10dc\u10d0\u10d1\u10d8\u10d4\u10d5\u10d8", + "\u10df\u10d5\u10d0\u10dc\u10d8\u10d0", + "\u10d5\u10d0\u10e1\u10d0\u10eb\u10d4", + "\u10d0\u10e0\u10d0\u10d1\u10e3\u10da\u10d8", + "\u10db\u10e3\u10e1\u10e2\u10d0\u10e4\u10d0\u10d4\u10d5\u10d0", + "\u10de\u10d0\u10d5\u10da\u10d8\u10d0\u10e8\u10d5\u10d8\u10da\u10d8", + "\u10d9\u10d0\u10ee\u10d8\u10eb\u10d4", + "\u10da\u10dd\u10db\u10d0\u10eb\u10d4", + "\u10d1\u10d0\u10da\u10d8\u10d0\u10e8\u10d5\u10d8\u10da\u10d8", + "\u10e1\u10dd\u10e4\u10e0\u10dd\u10db\u10d0\u10eb\u10d4", + "\u10e8\u10d4\u10dc\u10d2\u10d4\u10da\u10d8\u10d0", + "\u10d9\u10d5\u10d0\u10ed\u10d0\u10eb\u10d4", + "\u10e9\u10d8\u10dc\u10e9\u10d0\u10da\u10d0\u10eb\u10d4", + "\u10d0\u10ee\u10dd\u10d1\u10d0\u10eb\u10d4", + "\u10ee\u10d0\u10e0\u10d0\u10e2\u10d8\u10e8\u10d5\u10d8\u10da\u10d8", + "\u10e5\u10e3\u10e0\u10d3\u10d0\u10eb\u10d4", + "\u10ee\u10d0\u10e0\u10e8\u10d8\u10da\u10d0\u10eb\u10d4", + "\u10ec\u10e3\u10e0\u10ec\u10e3\u10db\u10d8\u10d0", + "\u10d3\u10d0\u10da\u10d0\u10e5\u10d8\u10e8\u10d5\u10d8\u10da\u10d8", + "\u10d2\u10d8\u10dd\u10e0\u10d2\u10dd\u10d1\u10d8\u10d0\u10dc\u10d8", + "\u10ef\u10d0\u10dc\u10d0\u10e8\u10d8\u10d0", + "\u10dc\u10d0\u10d3\u10d8\u10e0\u10d0\u10eb\u10d4", + "\u10e5\u10d4\u10d5\u10ee\u10d8\u10e8\u10d5\u10d8\u10da\u10d8", + "\u10dc\u10d8\u10df\u10d0\u10e0\u10d0\u10eb\u10d4", + "\u10e8\u10d0\u10db\u10d0\u10d7\u10d0\u10d5\u10d0", + "\u10e1\u10d0\u10ef\u10d0\u10d8\u10d0", + "\u10ed\u10d4\u10da\u10d8\u10eb\u10d4", + "\u10d5\u10d4\u10d9\u10e3\u10d0", + "\u10d1\u10d8\u10d2\u10d5\u10d0\u10d5\u10d0", + "\u10ea\u10d0\u10dc\u10d0\u10d5\u10d0", + "\u10d2\u10dd\u10d2\u10d8\u10eb\u10d4", + "\u10d0\u10dc\u10d7\u10d0\u10eb\u10d4", + "\u10d2\u10d4\u10da\u10d0\u10e8\u10d5\u10d8\u10da\u10d8", + "\u10ed\u10d4\u10d8\u10e8\u10d5\u10d8\u10da\u10d8", + "\u10da\u10dd\u10da\u10d0\u10eb\u10d4", + "\u10db\u10e3\u10db\u10da\u10d0\u10eb\u10d4", + "\u10ee\u10d0\u10e0\u10e9\u10d8\u10da\u10d0\u10d5\u10d0", + "\u10db\u10e3\u10e1\u10d0\u10d4\u10d5\u10d0", + "\u10d2\u10dd\u10d2\u10d8\u10d0", + "\u10db\u10d8\u10dc\u10d3\u10d8\u10d0\u10e8\u10d5\u10d8\u10da\u10d8", + "\u10e6\u10dd\u10dc\u10e6\u10d0\u10eb\u10d4", + "\u10dc\u10d4\u10db\u10e1\u10d0\u10eb\u10d4", + "\u10ee\u10d0\u10e0\u10d0\u10d8\u10e8\u10d5\u10d8\u10da\u10d8", + "\u10d9\u10d0\u10da\u10d0\u10dc\u10d3\u10d8\u10d0", + "\u10d5\u10d0\u10da\u10d8\u10d4\u10d5\u10d0", + "\u10e8\u10d4\u10da\u10d8\u10d0", + "\u10de\u10d0\u10de\u10d8\u10d0\u10e8\u10d5\u10d8\u10da\u10d8", + "\u10e5\u10d8\u10e0\u10d8\u10d0", + "\u10e1\u10d8\u10ed\u10d8\u10dc\u10d0\u10d5\u10d0", + "\u10d8\u10db\u10d4\u10e0\u10da\u10d8\u10e8\u10d5\u10d8\u10da\u10d8", + "\u10d2\u10d0\u10ef\u10d8\u10d4\u10d5\u10d0", + "\u10e8\u10d0\u10e0\u10d8\u10e5\u10d0\u10eb\u10d4", + "\u10e1\u10d0\u10dc\u10d8\u10d9\u10d8\u10eb\u10d4", + "\u10e7\u10dd\u10da\u10d1\u10d0\u10d8\u10d0", + "\u10d6\u10d4\u10d3\u10d2\u10d8\u10dc\u10d8\u10eb\u10d4", + "\u10dc\u10d0\u10e2\u10e0\u10dd\u10e8\u10d5\u10d8\u10da\u10d8", + "\u10d1\u10e3\u10e0\u10d3\u10e3\u10da\u10d8", + "\u10e4\u10d8\u10e4\u10d8\u10d0", + "\u10db\u10d0\u10db\u10e3\u10da\u10d0\u10e8\u10d5\u10d8\u10da\u10d8", + "\u10e9\u10ee\u10d8\u10d9\u10d5\u10d0\u10eb\u10d4", + "\u10d2\u10d0\u10d1\u10e3\u10dc\u10d8\u10d0", + "\u10d8\u10e0\u10d4\u10db\u10d0\u10e8\u10d5\u10d8\u10da\u10d8", + "\u10ed\u10d8\u10ed\u10d8\u10dc\u10d0\u10eb\u10d4", + "\u10d1\u10d4\u10df\u10d0\u10dc\u10d8\u10e8\u10d5\u10d8\u10da\u10d8", + "\u10db\u10dd\u10e1\u10d8\u10d0\u10e8\u10d5\u10d8\u10da\u10d8", + "\u10ef\u10d0\u10da\u10d0\u10e6\u10dd\u10dc\u10d8\u10d0", + "\u10e8\u10e3\u10d1\u10d8\u10d7\u10d8\u10eb\u10d4", + "\u10da\u10dd\u10e0\u10d7\u10e5\u10d8\u10e4\u10d0\u10dc\u10d8\u10eb\u10d4", + "\u10db\u10d8\u10db\u10d8\u10dc\u10dd\u10e8\u10d5\u10d8\u10da\u10d8", + "\u10e1\u10d4\u10ee\u10dc\u10d8\u10d0\u10e8\u10d5\u10d8\u10da\u10d8", + "\u10db\u10d0\u10e9\u10d8\u10e2\u10d8\u10eb\u10d4", + "\u10d9\u10e3\u10ed\u10d0\u10d5\u10d0", + "\u10d2\u10dd\u10d2\u10d0\u10da\u10d0\u10eb\u10d4", + "\u10e2\u10e7\u10d4\u10d1\u10e3\u10e9\u10d0\u10d5\u10d0", + "\u10d9\u10d5\u10d8\u10dc\u10d8\u10d9\u10d0\u10eb\u10d4", + "\u10db\u10d4\u10da\u10e5\u10d0\u10eb\u10d4", + "\u10d1\u10d4\u10e5\u10d0\u10e3\u10e0\u10d8", + "\u10de\u10d0\u10de\u10d0\u10d5\u10d0", + "\u10ee\u10d5\u10d8\u10e9\u10d8\u10d0", + "\u10e0\u10d0\u10db\u10d8\u10e8\u10d5\u10d8\u10da\u10d8", + "\u10e1\u10d8\u10e0\u10d1\u10d8\u10da\u10d0\u10eb\u10d4", + "\u10dd\u10e5\u10e0\u10e3\u10d0\u10e8\u10d5\u10d8\u10da\u10d8", + "\u10db\u10d4\u10da\u10d8\u10e5\u10d8\u10e8\u10d5\u10d8\u10da\u10d8", + "\u10d9\u10d0\u10ed\u10d0\u10e0\u10d0\u10d5\u10d0", + "\u10d2\u10d0\u10d2\u10dc\u10d8\u10eb\u10d4", + "\u10d3\u10d5\u10d0\u10da\u10d8\u10e8\u10d5\u10d8\u10da\u10d8", + "\u10db\u10ed\u10d4\u10d3\u10da\u10d8\u10eb\u10d4", + "\u10db\u10d0\u10d7\u10d8\u10d0\u10e8\u10d5\u10d8\u10da\u10d8", + "\u10e9\u10d0\u10e9\u10e3\u10d0", + "\u10dc\u10d4\u10e4\u10d0\u10e0\u10d8\u10eb\u10d4", + "\u10dc\u10d0\u10d3\u10d8\u10e0\u10d0\u10e8\u10d5\u10d8\u10da\u10d8", + "\u10d0\u10e0\u10d0\u10d1\u10d8\u10eb\u10d4", + "\u10d1\u10d4\u10dc\u10d3\u10d4\u10da\u10d8\u10d0\u10dc\u10d8", + "\u10d9\u10d8\u10da\u10d0\u10eb\u10d4", + "\u10d2\u10e3\u10da\u10d8\u10d0\u10e8\u10d5\u10d8\u10da\u10d8", + "\u10d1\u10d0\u10e0\u10d0\u10db\u10d8\u10eb\u10d4", + "\u10e7\u10d8\u10e4\u10d8\u10d0\u10dc\u10d8", + "\u10d9\u10d0\u10d9\u10d0\u10e3\u10e0\u10d8\u10eb\u10d4", + "\u10d2\u10d8\u10dd\u10e0\u10d2\u10d0\u10eb\u10d4", + "\u10d2\u10dd\u10d2\u10d8\u10e9\u10d0\u10d8\u10e8\u10d5\u10d8\u10da\u10d8", + "\u10d2\u10d0\u10d1\u10d0\u10d8\u10eb\u10d4", + "\u10d2\u10d8\u10d2\u10d0\u10e3\u10e0\u10d8", + "\u10d3\u10d0\u10dc\u10d4\u10da\u10d8\u10d0", + "\u10ee\u10d0\u10e9\u10d0\u10e2\u10e3\u10e0\u10d8\u10d0\u10dc\u10d8", + "\u10d0\u10d1\u10d0\u10e8\u10d8\u10eb\u10d4", + "\u10ef\u10d0\u10e4\u10d0\u10e0\u10d8\u10eb\u10d4", + "\u10e4\u10d0\u10e0\u10e2\u10d4\u10dc\u10d0\u10eb\u10d4", + "\u10d9\u10d8\u10da\u10d0\u10e1\u10dd\u10dc\u10d8\u10d0", + "\u10d7\u10d0\u10d5\u10d0\u10eb\u10d4", + "\u10d1\u10e3\u10ea\u10ee\u10e0\u10d8\u10d9\u10d8\u10eb\u10d4", + "\u10da\u10d4\u10df\u10d0\u10d5\u10d0", + "\u10d3\u10d4\u10d5\u10d8\u10eb\u10d4", + "\u10ec\u10d8\u10d9\u10da\u10d0\u10e3\u10e0\u10d8", + "\u10ed\u10d0\u10dc\u10e2\u10e3\u10e0\u10d8\u10d0", + "\u10eb\u10d8\u10eb\u10d8\u10d2\u10e3\u10e0\u10d8", + "\u10d9\u10d8\u10d9\u10d5\u10d0\u10eb\u10d4", + "\u10d1\u10d4\u10d2\u10d8\u10d0\u10e8\u10d5\u10d8\u10da\u10d8", + "\u10d2\u10e3\u10e0\u10e3\u10da\u10d8", + "\u10e8\u10d0\u10da\u10d0\u10db\u10d1\u10d4\u10e0\u10d8\u10eb\u10d4", + "\u10d9\u10d8\u10e0\u10d7\u10d0\u10eb\u10d4", + "\u10d0\u10d1\u10e0\u10d0\u10db\u10d8\u10e8\u10d5\u10d8\u10da\u10d8", + "\u10e4\u10d8\u10e0\u10ea\u10ee\u10d0\u10da\u10d0\u10d5\u10d0", + "\u10d3\u10d4\u10d5\u10d0\u10eb\u10d4", + "\u10d9\u10e3\u10d1\u10da\u10d0\u10e8\u10d5\u10d8\u10da\u10d8", + "\u10e5\u10d0\u10e0\u10d3\u10d0\u10d5\u10d0", + "\u10d1\u10d0\u10e5\u10e0\u10d0\u10eb\u10d4", + "\u10da\u10d0\u10d1\u10d0\u10eb\u10d4", + "\u10ee\u10dd\u10d6\u10e0\u10d4\u10d5\u10d0\u10dc\u10d8\u10eb\u10d4", + "\u10d0\u10da\u10d8\u10d4\u10d5\u10d0", + "\u10d8\u10d0\u10e8\u10d5\u10d8\u10da\u10d8", + "\u10e4\u10e3\u10e2\u10d9\u10d0\u10e0\u10d0\u10eb\u10d4", + "\u10e7\u10e3\u10e0\u10d0\u10e8\u10d5\u10d8\u10da\u10d8", + "\u10ec\u10d4\u10e0\u10d4\u10d7\u10d4\u10da\u10d8", + "\u10d9\u10e3\u10ed\u10e3\u10ee\u10d8\u10eb\u10d4", + "\u10d1\u10d4\u10e0\u10d8\u10eb\u10d4", + "\u10d5\u10d0\u10e8\u10d0\u10e7\u10db\u10d0\u10eb\u10d4", + "\u10d1\u10d0\u10ee\u10e2\u10d0\u10eb\u10d4", + "\u10e8\u10d0\u10db\u10e3\u10d2\u10d8\u10d0", + "\u10dd\u10dc\u10d8\u10d0\u10dc\u10d8", + "\u10d0\u10dc\u10d3\u10e6\u10e3\u10da\u10d0\u10eb\u10d4", + "\u10dc\u10d8\u10e5\u10d0\u10d1\u10d0\u10eb\u10d4", + "\u10e1\u10d0\u10db\u10ee\u10d0\u10e0\u10d0\u10eb\u10d4", + "\u10db\u10d0\u10d6\u10db\u10d8\u10e8\u10d5\u10d8\u10da\u10d8", + "\u10d3\u10d0\u10d5\u10d8\u10d7\u10d0\u10e8\u10d5\u10d8\u10da\u10d8", + "\u10e4\u10d0\u10e0\u10ea\u10d5\u10d0\u10dc\u10d8\u10d0", + "\u10ee\u10d4\u10ea\u10e3\u10e0\u10d8\u10d0\u10dc\u10d8", + "\u10e5\u10d0\u10dc\u10d7\u10d0\u10e0\u10d8\u10d0", + "\u10d1\u10d4\u10e0\u10d0\u10eb\u10d4", + "\u10ee\u10d0\u10ed\u10d0\u10de\u10e3\u10e0\u10d8\u10eb\u10d4", + "\u10ef\u10e6\u10d0\u10e0\u10d9\u10d0\u10d5\u10d0", + "\u10d2\u10d4\u10d2\u10d4\u10e8\u10d8\u10eb\u10d4", + "\u10d9\u10e3\u10de\u10d0\u10e2\u10d0\u10eb\u10d4", + "\u10da\u10d8\u10de\u10d0\u10e0\u10e2\u10d4\u10da\u10d8\u10d0\u10dc\u10d8", + "\u10d2\u10d0\u10d1\u10d4\u10da\u10d8\u10d0", + "\u10db\u10d0\u10dc\u10d0\u10d2\u10d0\u10eb\u10d4", + "\u10d7\u10dd\u10e4\u10e3\u10e0\u10d8\u10d0", + "\u10e2\u10e7\u10d4\u10e8\u10d4\u10da\u10d0\u10e8\u10d5\u10d8\u10da\u10d8", + "\u10d1\u10d4\u10dc\u10d8\u10eb\u10d4", + "\u10d9\u10d5\u10d8\u10e0\u10d9\u10d5\u10d4\u10da\u10d8\u10d0", + "\u10d3\u10dd\u10da\u10d8\u10eb\u10d4", + "\u10ee\u10d0\u10e0\u10d4\u10d1\u10d0\u10d5\u10d0", + "\u10d6\u10e3\u10e0\u10d0\u10d1\u10d0\u10e8\u10d5\u10d8\u10da\u10d8", + "\u10dc\u10d8\u10d9\u10dd\u10da\u10d0\u10d8\u10e8\u10d5\u10d8\u10da\u10d8", + "\u10e1\u10d0\u10e0\u10d0\u10da\u10d8\u10eb\u10d4", + "\u10d2\u10dd\u10d2\u10dd\u10ee\u10d8\u10d0", + "\u10d0\u10ee\u10d5\u10da\u10d4\u10d3\u10d8\u10d0\u10dc\u10d8", + "\u10db\u10d4\u10e4\u10d0\u10e0\u10d8\u10e8\u10d5\u10d8\u10da\u10d8", + "\u10e5\u10d0\u10ef\u10d0\u10d8\u10d0", + "\u10d7\u10dd\u10da\u10dd\u10e0\u10d3\u10d0\u10d5\u10d0", + "\u10e0\u10dd\u10d2\u10d0\u10d5\u10d0", + "\u10d8\u10da\u10e3\u10e0\u10d8\u10eb\u10d4", + "\u10d2\u10dd\u10e0\u10d2\u10d0\u10eb\u10d4", + "\u10db\u10df\u10d0\u10d5\u10d0\u10dc\u10d0\u10eb\u10d4", + "\u10e1\u10d0\u10db\u10e3\u10e8\u10d8\u10d0", + "\u10ef\u10d8\u10e5\u10d8\u10d0", + "\u10d1\u10da\u10d8\u10d0\u10eb\u10d4", + "\u10db\u10d0\u10e6\u10da\u10d0\u10d9\u10d4\u10da\u10d8\u10eb\u10d4", + "\u10d1\u10d4\u10e0\u10e3\u10d0\u10e8\u10d5\u10d8\u10da\u10d8", + "\u10db\u10d0\u10db\u10d0\u10da\u10d0\u10eb\u10d4", + "\u10d2\u10dd\u10d2\u10dd\u10da\u10d0\u10eb\u10d4", + "\u10db\u10e3\u10e1\u10d0\u10d4\u10d5\u10d8", + "\u10d2\u10e3\u10e0\u10d4\u10e8\u10d8\u10eb\u10d4", + "\u10e0\u10d0\u10d6\u10db\u10d0\u10eb\u10d4", + "\u10d2\u10d0\u10d1\u10d4\u10d3\u10d0\u10d5\u10d0", + "\u10d0\u10d1\u10d4\u10e1\u10d0\u10eb\u10d4", + "\u10e1\u10ee\u10d8\u10e0\u10e2\u10da\u10d0\u10eb\u10d4", + "\u10db\u10d4\u10da\u10d8\u10e5\u10d8\u10eb\u10d4", + "\u10db\u10d8\u10e5\u10d0\u10d1\u10d4\u10e0\u10d8\u10eb\u10d4", + "\u10da\u10dd\u10d1\u10df\u10d0\u10dc\u10d8\u10eb\u10d4", + "\u10da\u10dd\u10db\u10e1\u10d0\u10eb\u10d4", + "\u10e8\u10d0\u10d7\u10d8\u10e0\u10d8\u10e8\u10d5\u10d8\u10da\u10d8", + "\u10d6\u10d0\u10e0\u10d8\u10eb\u10d4", + "\u10d0\u10e1\u10d0\u10d7\u10d8\u10d0\u10dc\u10d8", + "\u10e7\u10d0\u10d5\u10d4\u10da\u10d0\u10e8\u10d5\u10d8\u10da\u10d8", + "\u10ef\u10d0\u10d5\u10d0\u10ee\u10d8\u10e8\u10d5\u10d8\u10da\u10d8", + "\u10d1\u10dd\u10d9\u10e3\u10e9\u10d0\u10d5\u10d0", + "\u10dc\u10e3\u10ea\u10e3\u10d1\u10d8\u10eb\u10d4", + "\u10d0\u10d5\u10d0\u10da\u10d8\u10d0\u10dc\u10d8", + "\u10e1\u10d8\u10da\u10d0\u10d2\u10d0\u10eb\u10d4", + "\u10e9\u10e3\u10d1\u10d8\u10dc\u10d8\u10eb\u10d4", + "\u10db\u10d0\u10ee\u10d0\u10d7\u10d0\u10eb\u10d4", + "\u10d9\u10dd\u10d1\u10d8\u10d0\u10e8\u10d5\u10d8\u10da\u10d8", + "\u10e0\u10d4\u10ee\u10d5\u10d8\u10d0\u10e8\u10d5\u10d8\u10da\u10d8", + "\u10d0\u10ee\u10d0\u10da\u10d0\u10eb\u10d4", + "\u10ef\u10dd\u10ee\u10d0\u10eb\u10d4", + "\u10e6\u10d0\u10e0\u10d8\u10d1\u10d0\u10e8\u10d5\u10d8\u10da\u10d8", + "\u10d9\u10d4\u10d9\u10d4\u10da\u10d8\u10eb\u10d4", + "\u10ef\u10dd\u10ef\u10e3\u10d0", + "\u10e9\u10ee\u10d0\u10e0\u10e2\u10d8\u10e8\u10d5\u10d8\u10da\u10d8", + "\u10d2\u10dd\u10d2\u10d8\u10e9\u10d0\u10e8\u10d5\u10d8\u10da\u10d8", + "\u10da\u10d0\u10e2\u10d0\u10e0\u10d8\u10d0", + "\u10d3\u10e3\u10db\u10d1\u10d0\u10eb\u10d4", + "\u10ee\u10d5\u10d4\u10d3\u10d4\u10da\u10d8\u10eb\u10d4", + "\u10ed\u10d8\u10d7\u10d0\u10dc\u10d0\u10d5\u10d0", + "\u10ef\u10d0\u10dc\u10d4\u10da\u10d8\u10eb\u10d4", + "\u10e2\u10d0\u10da\u10d0\u10ee\u10d0\u10eb\u10d4", + "\u10d2\u10d0\u10ef\u10d8\u10d4\u10d5\u10d8", + "\u10db\u10d4\u10e0\u10d0\u10d1\u10d8\u10e8\u10d5\u10d8\u10da\u10d8", + "\u10d7\u10d4\u10d3\u10dd\u10e0\u10d0\u10eb\u10d4", + "\u10d9\u10dd\u10d1\u10d0\u10d8\u10eb\u10d4", + "\u10e6\u10da\u10dd\u10dc\u10e2\u10d8", + "\u10d4\u10da\u10d1\u10d0\u10e5\u10d8\u10eb\u10d4", + "\u10db\u10d8\u10e5\u10d0\u10d5\u10d0", + "\u10dd\u10d7\u10d0\u10e0\u10d0\u10e8\u10d5\u10d8\u10da\u10d8", + "\u10e8\u10d0\u10d5\u10d0\u10eb\u10d4", + "\u10ea\u10d4\u10e0\u10ea\u10d5\u10d0\u10eb\u10d4", + "\u10ec\u10e3\u10da\u10e3\u10d9\u10d8\u10eb\u10d4", + "\u10db\u10ed\u10d4\u10d3\u10da\u10d8\u10e8\u10d5\u10d8\u10da\u10d8", + "\u10d9\u10d0\u10d9\u10e3\u10da\u10d8\u10d0", + "\u10db\u10d0\u10e6\u10e0\u10d0\u10eb\u10d4", + "\u10ee\u10e3\u10e0\u10ea\u10d8\u10da\u10d0\u10d5\u10d0", + "\u10e4\u10d4\u10e0\u10d0\u10eb\u10d4", + "\u10ea\u10d4\u10ea\u10ee\u10da\u10d0\u10eb\u10d4", + "\u10d9\u10d5\u10d4\u10e0\u10dc\u10d0\u10eb\u10d4", + "\u10e4\u10ee\u10d0\u10da\u10d0\u10eb\u10d4", + "\u10dc\u10d4\u10d1\u10d8\u10d4\u10e0\u10d8\u10eb\u10d4", + "\u10d9\u10d4\u10e0\u10d4\u10e1\u10d4\u10da\u10d8\u10eb\u10d4", + "\u10d9\u10e3\u10e0\u10e2\u10d0\u10dc\u10d8\u10eb\u10d4", + "\u10e1\u10e3\u10da\u10d0\u10d1\u10d4\u10e0\u10d8\u10eb\u10d4", + "\u10d0\u10da\u10d0\u10dc\u10d8\u10d0", + "\u10d1\u10d4\u10e0\u10eb\u10d4\u10dc\u10d8\u10e8\u10d5\u10d8\u10da\u10d8", + "\u10d2\u10e3\u10e0\u10d2\u10d4\u10dc\u10d8\u10eb\u10d4", + "\u10d2\u10dd\u10d2\u10d8\u10e8\u10d5\u10d8\u10da\u10d8", + "\u10ef\u10d0\u10dc\u10d8\u10d0\u10e8\u10d5\u10d8\u10da\u10d8", + "\u10d9\u10e3\u10de\u10e0\u10d0\u10e8\u10d5\u10d8\u10da\u10d8", + "\u10e1\u10d0\u10e0\u10e5\u10d8\u10e1\u10d8\u10d0\u10dc\u10d8", + "\u10e1\u10d8\u10e0\u10d0\u10eb\u10d4", + "\u10d1\u10e0\u10d4\u10d2\u10d5\u10d0\u10eb\u10d4", + "\u10e4\u10dd\u10e4\u10ee\u10d0\u10eb\u10d4", + "\u10de\u10d0\u10de\u10e3\u10d0\u10e8\u10d5\u10d8\u10da\u10d8", + "\u10d0\u10e4\u10ea\u10d8\u10d0\u10e3\u10e0\u10d8", + "\u10d2\u10d5\u10d0\u10e1\u10d0\u10da\u10d8\u10d0", + "\u10d9\u10d0\u10de\u10d0\u10dc\u10d0\u10eb\u10d4", + "\u10e0\u10d4\u10d5\u10d0\u10d6\u10d8\u10e8\u10d5\u10d8\u10da\u10d8", + "\u10da\u10d0\u10d2\u10d5\u10d8\u10da\u10d0\u10d5\u10d0", + "\u10db\u10d0\u10db\u10e3\u10da\u10d0\u10eb\u10d4", + "\u10d9\u10dd\u10ee\u10e0\u10d4\u10d8\u10eb\u10d4", + "\u10d7\u10d0\u10d5\u10d0\u10e0\u10d7\u10e5\u10d8\u10da\u10d0\u10eb\u10d4", + "\u10d2\u10dd\u10d2\u10d8\u10dc\u10d0\u10e8\u10d5\u10d8\u10da\u10d8", + "\u10de\u10d0\u10de\u10d0\u10e8\u10d5\u10d8\u10da\u10d8", + "\u10e5\u10d0\u10d7\u10d0\u10db\u10d0\u10eb\u10d4", + "\u10d0\u10e1\u10d0\u10dc\u10d8\u10eb\u10d4", + "\u10d1\u10dd\u10da\u10e5\u10d5\u10d0\u10eb\u10d4", + "\u10da\u10dd\u10db\u10d8\u10eb\u10d4", + "\u10d0\u10d1\u10e3\u10da\u10d0\u10eb\u10d4", + "\u10ef\u10d0\u10d8\u10d0\u10dc\u10d8", + "\u10db\u10e6\u10d4\u10d1\u10e0\u10d8\u10e8\u10d5\u10d8\u10da\u10d8", + "\u10ed\u10d0\u10e6\u10d0\u10da\u10d8\u10eb\u10d4", + "\u10d1\u10d0\u10e1\u10d8\u10da\u10d0\u10e8\u10d5\u10d8\u10da\u10d8", + "\u10ee\u10d0\u10e9\u10d8\u10eb\u10d4", + "\u10db\u10d8\u10e5\u10d0\u10eb\u10d4", + "\u10e8\u10e3\u10d9\u10d0\u10d9\u10d8\u10eb\u10d4", + "\u10d9\u10dd\u10d1\u10d0\u10ee\u10d8\u10eb\u10d4", + "\u10d0\u10da\u10d8\u10d4\u10d5\u10d8", + "\u10dc\u10d0\u10ea\u10d5\u10da\u10d8\u10e8\u10d5\u10d8\u10da\u10d8" + ], + "LAST_NAME_MALE": [], + "LAST_NAME_FEMALE": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "\u10d3\u10d4\u10d3\u10dd\u10e4\u10d0\u10da\u10d8": "\u10ee\u10d4\u10da\u10db\u10ec\u10d8\u10e4\u10d4", + "\u10db\u10d3\u10d4\u10d3\u10e0\u10dd\u10d1\u10d8\u10d7\u10d8": "\u10db\u10d0\u10db\u10e0\u10d8", + "\u10e5\u10d0\u10da\u10d8": "\u10db\u10d0\u10db\u10d0\u10d9\u10d0\u10ea\u10d8", + "\u10db\u10d3\u10d4\u10d3\u10e0\u10d8": "\u10db\u10d0\u10db\u10e0\u10dd\u10d1\u10d8\u10d7\u10d8", + "\u10d3\u10d4\u10d3\u10d0": "\u10db\u10d0\u10db\u10d0", + "\u10d3\u10d8\u10d3\u10d0": "\u10db\u10d0\u10db\u10d0", + "\u10db\u10dd\u10dc\u10d0\u10d6\u10dd\u10dc\u10d8": "\u10d1\u10d4\u10e0\u10db\u10dd\u10dc\u10d0\u10d6\u10d5\u10dc\u10dd\u10d1\u10d0", + "\u10de\u10e0\u10d8\u10dc\u10ea\u10d4\u10e1\u10d0": "\u10de\u10e0\u10d8\u10dc\u10ea\u10d8", + "\u10d3\u10d0": "\u10eb\u10db\u10d0", + "\u10d3\u10d4\u10d3\u10d8\u10dc\u10d0\u10ea\u10d5\u10d0\u10da\u10d8": "\u10db\u10d0\u10db\u10d8\u10dc\u10d0\u10ea\u10d5\u10d0\u10da\u10d8", + "\u10ea\u10dd\u10da\u10d8": "\u10e5\u10db\u10d0\u10e0\u10d8", + "\u10d2\u10e0\u10eb\u10dc\u10d4\u10e3\u10da\u10d8": "\u10ef\u10d0\u10d3\u10dd\u10e5\u10d0\u10e0\u10d8", + "\u10d9\u10e3\u10d3\u10d8\u10d0\u10dc\u10d8": "\u10db\u10d8\u10e1\u10d0\u10dc\u10d8", + "\u10ef\u10d0\u10d3\u10dd\u10e5\u10d0\u10e0\u10d8": "\u10db\u10d8\u10e1\u10d0\u10dc\u10d8", + "\u10d3\u10d8\u10d0\u10ea\u10d8": "\u10db\u10d0\u10db\u10d0\u10d9\u10d0\u10ea\u10d8", + "\u10d3\u10d4\u10d3\u10d0\u10d9\u10d0\u10ea\u10d8": "\u10d0\u10d3\u10d0\u10db\u10d8\u10d0\u10dc\u10d8", + "\u10d1\u10d0\u10dc\u10dd\u10d5\u10d0\u10dc\u10d8": "\u10d0\u10d3\u10d0\u10db\u10d8\u10d0\u10dc\u10d8", + "\u10d1\u10d8\u10ed\u10d8": "\u10d2\u10dd\u10d2\u10dd" + }, + "other_gender_swap": { + "\u10d8\u10e1\u10d8\u10dc\u10d8": "\u10d8\u10e1", + "\u10d8\u10e1": "\u10d8\u10e1\u10d8\u10dc\u10d8" + }, + "en_pronoun2gender": { + "they": [ + "\u10d1\u10d8\u10e1\u10d4\u10e5\u10e1\u10e3\u10d0\u10da\u10d8", + "\u10e2\u10e0\u10d0\u10dc\u10e1\u10d2\u10d4\u10dc\u10d3\u10d4\u10e0\u10d8", + "\u10f0\u10dd\u10db\u10dd\u10e1\u10d4\u10e5\u10e1\u10e3\u10d0\u10da\u10d8" + ], + "he": [ + "\u10db\u10d0\u10db\u10d0\u10d9\u10d0\u10ea\u10d8", + "\u10d1\u10d8\u10ed\u10d8", + "\u10d0\u10d3\u10d0\u10db\u10d8\u10d0\u10dc\u10d8", + "\u10d1\u10d8\u10ed\u10e3\u10dc\u10d0", + "\u10db\u10d0\u10db\u10e0\u10dd\u10d1\u10d8\u10d7\u10d8", + "\u10db\u10d0\u10db\u10e0\u10d8", + "\u10ef\u10d4\u10dc\u10e2\u10da\u10db\u10d4\u10dc\u10d8" + ], + "she": [ + "\u10d2\u10dd\u10d2\u10dd", + "\u10da\u10d4\u10e1\u10d1\u10dd\u10e1\u10d4\u10da\u10d8", + "\u10d3\u10d4\u10d3\u10d0\u10d7\u10db\u10d0\u10d5\u10d0\u10da\u10d8", + "\u10e5\u10d0\u10da\u10ec\u10e3\u10da\u10d8", + "\u10e5\u10d0\u10da\u10d8", + "\u10d3\u10d8\u10d0\u10ea\u10d8", + "\u10e5\u10d0\u10da\u10d8\u10e8\u10d5\u10d8\u10da\u10d8", + "\u10d3\u10d4\u10d3\u10d0\u10d9\u10d0\u10ea\u10d8", + "\u10db\u10d3\u10d4\u10d3\u10e0\u10d8", + "\u10d1\u10d0\u10dc\u10dd\u10d5\u10d0\u10dc\u10d8", + "\u10db\u10d3\u10d4\u10d3\u10e0\u10dd\u10d1\u10d8\u10d7\u10d8" + ] + }, + "en_pronoun2pronoun": { + "he": [ + "\u10d8\u10e1" + ], + "she": [ + "\u10d8\u10e1" + ], + "they": [ + "\u10d8\u10e1\u10d8\u10dc\u10d8", + "\u10d8\u10db\u10d0\u10d7\u10d8", + "\u10db\u10d0\u10d7", + "\u10d7\u10d0\u10d5\u10d8\u10d0\u10dc\u10d7\u10d8", + "\u10d8\u10db\u10d0\u10d7", + "\u10db\u10d0\u10d7\u10d8" + ], + "it": [ + "\u10d8\u10e1", + "\u10e0\u10dd\u10db", + "\u10d4\u10e1" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/kbd.json b/data_tooling/pii_processing/ontology/data/kbd.json new file mode 100644 index 0000000..ac80d00 --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/kbd.json @@ -0,0 +1,26 @@ +{ + "FOOD": [ + "\u0434\u0436\u044d\u0434\u044b\u043a\u04cf\u044d" + ], + "PRODUCT": [ + "\u043a\u044a\u0440\u0443\u0445\u0443\u0433\u0443" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "\u043d\u044b": "\u0442\u044b" + }, + "other_gender_swap": {}, + "en_pronoun2gender": {}, + "en_pronoun2pronoun": {}, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/khb.json b/data_tooling/pii_processing/ontology/data/khb.json new file mode 100644 index 0000000..6b07b7b --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/khb.json @@ -0,0 +1,30 @@ +{ + "ORG": [ + "\u19b7\u19a3\u19c2\u19b5\u19a3\u19c3\u1993\u19be\u19c9" + ], + "PERSON": [ + "\u1989\u19b1\u19c4\u1989\u19b2\u19c7\u1989\u19b8\u19c2" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "\u19b6\u1999\u19c8": "\u1997\u19b8\u19c8" + }, + "other_gender_swap": {}, + "en_pronoun2gender": {}, + "en_pronoun2pronoun": { + "it": [ + "\u1993\u19b2\u19b0" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/ki.json b/data_tooling/pii_processing/ontology/data/ki.json new file mode 100644 index 0000000..d0f209a --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/ki.json @@ -0,0 +1,68 @@ +{ + 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"\ucc28", + "\uc624", + "\ud5c8", + "\ud558", + "\uc591", + "\uc190", + "\ub178", + "\uc2ec", + "\uc815", + "\uc720", + "\uc870", + "\uc1a1", + "\ubc31", + "\uc6b0", + "\uc9c4", + "\uacfd", + "\uc804", + "\uace0", + "\ud55c", + "\uc784", + "\uc5c4", + "\uc2e0", + "\uc8fc", + "\uae40", + "\ub958", + "\ubb38", + "\ud669", + "\uc9c0", + "\ub098", + "\uc548", + "\uc131", + "\uc724", + "\uac15", + "\ubc15", + "\uc11c", + "\ud64d", + "\ub0a8", + "\ubbfc", + "\uad8c", + "\uad6c", + "\uc774" + ], + "OTHER_PRONOUN": [ + "it" + ], + "LAST_NAME_MALE": [], + "LAST_NAME_FEMALE": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "\u7687\u540e": "key", + "\uc18c\ub140": "\ub188", + "\ubbf8\uc4f0\uc5d0\uc774": "\uacbd", + "\uc544\uac00\uc528": "\uc11c", + "\uc5b4\uba38\ub2c8": "\u7236\u6bcd", + "\u7236\u6bcd": "\u8056\u7236", + "\u4fee\u5973": "\u50e7\u4f3d", + "\uc218\ub140": "\u50e7\u4f3d", + "\ud504\ub9b0\uc138\uc2a4": "\uad70\uc8fc\ub860", + "\uacf5\uc8fc": "\ud504\ub9b0\uc2a4", + "\u516c\u4e3b": "\uad70\uc8fc\ub860", + "\ud038_\uc5ed": "key", + "\uc5ec\uc655": "key", + "\u5973\u738b": "\uc655", + "\uadf8": "\u3078", + "\uc81c\uad70_\uc0ac": "\uadf8", + "\u914d\u5076\u8005": "\ub0a8\ud3b8", + "\uc544\ub0b4": "\ub0a8\ud3b8", + "\uc5ec\uc790": "\ub0a8\uc131", + "\uc5ec\uc131": "\ub0a8\uc131", + "\ubcf4\uc774": "\uc18c\ub140", + "\uc544\uc774": "\uc18c\ub140", + "\uc18c\ub144": "\uc18c\ub140" + }, + "other_gender_swap": {}, + "en_pronoun2gender": { + "they": [ + "\ud2b8\ub79c\uc2a4\uc820\ub354", + "\u540c\u6027", + "\u540c\u6027\u611b" + ], + "he": [ + "\ub9ac\ud2c0_\ubcf4\uc774", + "\uc820\ud2c0\ub9e8", + "\ub188", + "\ub0a8", + "\uc778\uac04", + "\uc18c\ub144", + "\uc544\uc774", + "\ub0a8\uc131", + "\ubcf4\uc774" + ], + "she": [ + "\uc5ec\uc131", + "\uc5b8\ub2c8", + "\uc544\uac00\uc528", + "\u5bb6\u653f\u5a66", + "\uc5ec\uc790", + "\uc18c\ub140", + "\ubbf8\uc4f0\uc5d0\uc774" + ] + }, + "en_pronoun2pronoun": { + "he": [ + "lia", + "\uadf8", + "\u3078" + ], + "she": [ + "\uadf8", + "\uc81c\uad70_\uc0ac" + ], + "they": [ + "lia" + ], + "it": [ + "\uadf8", + "bt", + "\u60c5\u5831\u6280\u8853", + "it" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/koy.json b/data_tooling/pii_processing/ontology/data/koy.json new file mode 100644 index 0000000..b0aa220 --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/koy.json @@ -0,0 +1,28 @@ +{ + "PUBLIC_FIGURE": [ + "delbegge" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": {}, + "other_gender_swap": {}, + "en_pronoun2gender": {}, + "en_pronoun2pronoun": { + "he": [ + "too" + ], + "it": [ + "too" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/krc.json b/data_tooling/pii_processing/ontology/data/krc.json new file mode 100644 index 0000000..7f7e560 --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/krc.json @@ -0,0 +1,35 @@ +{ + "PERSON_PRONOUN": [ + "\u043e\u043b" + ], + "ANIMAL": [ + "\u0441\u0443\u0443\u0441\u0430\u0440" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "\u0430\u043d\u0430": "\u044d\u043c\u0435\u043d", + "\u044d\u0433\u0435\u0447": "\u043a\u044a\u0430\u0440\u043d\u0430\u0448", + "\u0445\u043e": "\u043a\u044a\u0430\u0440\u044b\u043d\u0434\u0430\u0448" + }, + "other_gender_swap": {}, + "en_pronoun2gender": {}, + "en_pronoun2pronoun": { + "he": [ + "\u043e\u043b" + ], + "she": [ + "\u043e\u043b" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/krl.json b/data_tooling/pii_processing/ontology/data/krl.json new file mode 100644 index 0000000..f3d3778 --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/krl.json @@ -0,0 +1,41 @@ +{ + "ANIMAL": [ + "alli", + "korppi" + ], + "PLANT": [ + "paju" + ], + "PERSON_PRONOUN": [ + "sin\u00e4" + ], + "LOCATION": [ + "passibo" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": {}, + "other_gender_swap": {}, + "en_pronoun2gender": { + "she": [ + "naine" + ] + }, + "en_pronoun2pronoun": { + "he": [ + "he\u00e4n", + "h\u00e4i", + "hi\u00e4n" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/ku.json b/data_tooling/pii_processing/ontology/data/ku.json new file mode 100644 index 0000000..303f6d1 --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/ku.json @@ -0,0 +1,493 @@ +{ + "PUBLIC_FIGURE": [ + "benjamin_franklin", + "akira_kurosawa", + "giovanni_boccaccio", + "c", + "dorothy_parker", + "mary_wollstonecraft", + "winston_churchill", + "johannes_diderik_van_der_waals", + "paul_mccartney", + "victor_hugo", + "joseph_smith", + "edwin_hubble", + "george_orwell", + "marie_curie", + "michael_jackson", + "thomas_hobbes", + "samuel_beckett", + "galileo_galilei", + "john_donne", + "robert_koch", + "pawlos", + "john_steinbeck", + "vincent_van_gogh", + "josef_stalin", + "john_ruskin", + "hans_albrecht_bethe", + "p", + "emiliano_zapata", + "karl_barth", + "hideki_yukawa", + "gottlieb_daimler", + "henri_becquerel", + "bertram_brockhouse", + "louis_pasteur", + "gertrude_stein", + "luigi_pirandello", + "charles_de_gaulle", + "f", + "thomas_mann", + "dante_alighieri", + "samuel_de_champlain", + "fridtjof_nansen", + "paul_verlaine", + "hal", + "oscar_wilde", + "francis_bacon", + "charles_baudelaire", + "james_franck", + "albert_schweitzer", + "max_planck", + "william_blake", + "john_bardeen", + "elias_canetti", + "edward_jenner", + "kendava_james", + "graham_greene", + "arthur_compton", + "niels_bohr", + "bertrand_russell", + "michael_faraday", + "don_k\u00ee\u015fot", + "gabriel_lippmann", + "friedrich_engels", + "richard_feynman", + "wolfgang_pauli", + "theodor_mommsen", + "marcel_proust", + "elizabeth_taylor", + "william_golding", + "alfred_nobel", + "marco_polo", + "guillaume_apollinaire", + "henri_bergson", + "patrick_white", + "hans_christian_andersen", + "pieter_zeeman", + "hector_berlioz", + "john_galsworthy", + "henrik_\u0131bsen", + "adam_smith", + "karl_marx", + "john_locke", + "king_lear", + "\u0131", + "jean_piaget", + "\u067e\u06ce\u062a\u0631\u06c6\u0633", + "adolf_hitler", + "george_boole", + "robert_boyle", + "cordell_hull", + "mahatma_gand\u00ee", + "ernest_walton", + "g", + "arthur_schopenhauer", + "r", + "andrew_jackson", + "philip_warren_anderson", + "johannes_gutenberg", + "william_faulkner", + "william_shockley", + "paul_newman", + "john_lennon", + "charlie_chaplin", + "j_m_barrie", + "hannah_arendt", + "george_marshall", + "john_deere", + "peter\u00ea_mezin", + "james_watt", + "ronald_reagan", + "wilhelm_reich", + "martin_luther_king", + "gustav_hertz", + "anne_sexton", + "frank", + "ernest_hemingway", + "george_westinghouse", + "nelson_mandela", + "al_gore", + "roald_amundsen", + "jacques_offenbach", + "willy_brandt", + "charles_wilkes", + "alfred_kastler", + "dawid", + "\u0644\u0648_\u06a9\u06c6\u0631\u0628\u0648\u0632\u06cc\u06ce", + "william_harvey", + "jonathan_swift", + "albert_einstein", + "t" + ], + "ANIMAL": [ + "siwar", + "guhandar", + "\u062a\u0627\u062c\u06cc\u0644\u06c6\u06a9\u06d5", + 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"dibistan", + "san_francisco", + "m\u0131z\u0131r_amer\u00eekay\u00ea", + "di_ser_de_girtin", + "ayasofya", + "\u0626\u0627\u06cc\u0627\u0633\u06c6\u0641\u06cc\u0627", + "ramanxane", + "deryaya_sor", + "\u067e\u0627\u0631\u062a\u06cc", + "\u06a9\u06b5\u06ce\u0633\u0627\u06cc_\u06a9\u0627\u062a\u06c6\u0644\u06cc\u06a9", + "partiya_karker\u00ean_alman_a_nasyonalsosyal\u00eest", + "\u062d\u06cc\u0632\u0628\u06cc_\u0646\u0627\u0632\u06cc", + "rabindranath_tagore", + "taybeti", + "\u00e7\u00eena_karker", + "\u062f\u06d5\u0631\u06cc\u0627\u06cc_\u0633\u0648\u0648\u0631", + "sao_tome", + "ben\u00ee\u015ft", + "mossad", + "\u0645\u0646_\u062a\u06c6\u0645_\u062e\u06c6\u0634_\u064a\u06d5\u0648\u06ce\u200c", + "ferdinand_magellan", + "modern\u00eezm", + "\u0633\u06d5\u06cc\u0646\u062a_\u0644\u0648\u0648\u0633\u06cc\u0627", + "berbilav\u00ee", + "los_angeles", + "nato", + "\u062f\u0628\u0633\u062a\u0627\u0646", + "\u067e\u06c6\u0633\u062a\u0647\u200c", + "ji_n\u00fb_ve", + "perwerde", + "cardin", 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"percussor", + "cancellarius", + "gurus", + "endocrinologista", + "minister", + "coquo", + "causidicus", + "macer", + "cinerarius", + "pastor", + "caminarius", + "lapicida", + "diplomate", + "marinus", + "struo", + "laryngologa", + "dermatologistus", + "coquus", + "treveris", + "pincerna", + "ancilla", + "carruca", + "interpres", + "the_economist", + "temporarius", + "porter", + "caprarius", + "episcopus", + "ornatrix", + "chemicus", + "demarchus", + "coqua", + "plumbarius", + "miles", + "usher", + "sanatrix", + "lacer", + "lagemannus", + "tabularius", + "proconsul", + "clava_ferrea", + "venatrix", + "laryngologus", + "conditor", + "presbyter", + "abbreviator", + "sub", + "the_independent", + "figulus", + "agaga", + "induo", + "publicanus", + "fullo" + ], + "DATE": [ + "perendie", + "dies_cinerum", + "dies_victoriae", + "dies_intercalarius", + "the_day_after_tomorrow", + "plenilunium", + "vigiliae_nocturnae", + "dies_consociationis_nationum", + "dies_cenae_domini", + "serius_ocius", + "dies_memoriae_primi_belli_mundani", + "semihora", + "dies_passionis_domini", + "twelfth_night", + "the_day_after" + ], + "ORG": [ + "shinto", + "ignis_olympicus", + "me_vocor", + "dolorosa", + "wicca", + "napoca", + "mediterranea_occidentalia", + "pronepos", + "nasa", + "the_comedy_of_errors", + "the_who", + "dominium", + "res_publica_cypri_septentrionalis", + "vivat", + "basilius_magnus", + "dominus_ioannes", + "copiae", + "lancastria", + "sc", + "in_domo", + "aetas_aurea", + "luna_prima", + "ivano_frankivscum", + "cultura_occidentalis", + "exercitus_civitatum_foederatarum", + "ec", + "flumen_flavum", + "violentia_domestica", + "carolus_sagan", + "insula_sanctae_helenae", + "media_socialia", + "ai", + "res_publica_serbica", + "factio_socialistica", + "factio_popularis_hispanica", + "nicolaus_myrensis", + "et_al", + "the_big_four", + "factio_liberalis", + "imperia_centralia", + "gubernatio", + "res_publica_vimariana", + "cathari", + "paulatim", + "res_publica_democratica_germanica", + "neanthopolis", + "de_novo", + "ursa_maior", + "denuo", + "agnio", + "the_full_monty", + "sancta_lucia", + "americanologia", + "archiva_nationalia", + "argentaria_centralis", + "rectio", + "res_militaris", + "res_publica_capitis_viridis", + "mythologia_romana", + "administratio", + "luscus", + "martyres", + "urbs_sancti_thomae", + "the_grapes_of_wrath", + "quis", + "ursa_major", + "ecclesia_catholica_romana", + "factio_whig", + "diribitorium", + "nato", + "neoplantae", + "anno_domini", + "unio_europaea", + "te_amo", + "ad_hoc", + "gummi_manducabile", + "factio_conservativa", + "ius_canonicum", + "domi", + "schola", + "in_situ", + "franciscopolis", + "sa", + "taoismus", + "factio_politica", + "assumptio_beatae_mariae_virginis", + "winnie_ille_pu", + "democratia_socialis", + "claudiopolis", + "cervulus", + "praediator", + "eu", + "dei_genitrix", + "vasconia", + "domus_alba", + "latomismus", + "factio_operaria_socialistarum_nationalium_germanica", + "mater_dolorosa" + ], + "PLANT": [ + "lilium_martagon", + "diospyros_virginiana", + "mastiche", + "melissa", + "the_joshua_tree", + "lappa", + "laureola", + "solanaceae", + "anthriscus_cerefolium", + "laurus_nobilis", + "amanita", + "sequoiadendron", + "arabidopsis_thaliana", + "bertholletia_excelsa", + "helianthus_annuus", + "arundo", + "achillea", + "magnolia_grandiflora", + "convolvulus", + "matthiola_incana", + "papaver", + "lapathus", + "cerasum", + "clusia", + "reseda", + "prunus_armeniaca", + "liquidambar", + "urtica", + "lychnis", + "castanearius", + "luteus", + "amanita_muscaria", + "dracocephalum", + "citrus_tangerina", + "sinapi", + "ulmus_americana", + "hippocrepis_comosa", + "saccharum", + "lentiscus", + "trifolium_repens", + "solanum", + "acer_pseudoplatanus", + "arbor_natalicia", + "cornus_florida", + "cerasus", + "cyperus_papyrus", + "saccharomyces_cerevisiae", + "ballote", + "camphora", + "sancta_maria", + "caprifolium", + "aralia_stipulata", + "colocasia_esculenta", + "piper_betle", + "planta_carnivora", + "oxalis", + "belladonna", + "viola_odorata", + "chrysanthemum", + "rubus_ardens", + "castanea", + "magnolia", + "batus", + "rosa_damascena", + "tritoma" + ], + "SOC_ECO_CLASS": [ + "optimas", + "labor", + "ingenuitas", + "fraternitas", + "paucus", + "samuraeus", + "cramum", + "muliebris_status" + ], + "ANIMAL": [ + "mammalis", + "palumbes", + "buteo", + "the_raven", + "sapo", + "cattus", + "feles", + "sitta_europaea", + "billy_elliot", + "canis_minor", + "carduelis", + "pisces", + "ardeo", + "cornix", + "pompilus", + "communis", + "chaus", + "homo_sapiens", + "dolichovespa", + "passer", + "porphirio", + "crabro", + "accipiter", + "ursulus", + "platanista", + "bombyx", + "catta", + "herpes_zoster", + "arthropoda", + "honos", + "campagnol", + "profelis", + "mane", + "salvelinus_fontinalis", + "ferre" + ], + "FOOD": [ + "citrus_aurantiifolia", + "promulsis", + "tyropatina", + "daucus_carota", + "prandium", + "mixtella", + "vigna_unguiculata", + "capsicum", + "embamma", + "farina", + "lucumium", + "sodium_chloride", + "tragemata", + "coffeum", + "chili", + "transfugio", + "chile", + "deserta", + "limonada", + "gummi_manducabile", + "gustatio", + "lacticinium", + "caseus_castrensis" + ], + "QUANTITY": [ + "mille_passuum", + "undetriginta", + "numerus_atomicus", + "libera", + "g", + "dollarium", + "quingenti", + "metrum_cubicum", + "systema_internationale", + "andreas_celsius", + "numerus_rationalis" + ], + "PRODUCT": [ + "the_hunger_games", + "abite", + "televisio_digitalis", + "in_memoriam", + "mons_sanctae_helenae", + "canticum_canticorum", + "the_star_spangled_banner", + "nova_seelandia", + "vi_fi", + "la_ciociara", + "the_lord_of_the_rings", + "canticum_solomonis", + "navis_velifera", + "saxonia_anhaltium", + "la_dolce_vita", + "deutsche_welle", + "spiritus_sanctus", + "dei_gratia", + "de_facto", + "ioannes_baptista", + "hornanum_caput" + ], + "GPE": [ + "gentes_maritimae", + "aurifodina", + "dominicopolis", + "dar_es_salaam", + "imperium_germanicum", + "pandanus_tectorius", + "auraria", + "dies_sancti_georgii", + "novum_testamentum", + "aedes_sanctae_sophiae", + "aquae_sextiae", + "sanctus_nicolaus", + "mare_aegaeum", + "america_centralis", + "iura_humana", + "nicolaus_myrensis", + "sancti_laurentii_fluvius", + "beata_maria_virgo_perdolens", + "vinh_long", + "urbs_sancti_ludovici", + "mare_rubrum", + "dolorosa", + "non_non" + ], + "RELIGION_MEMBER": [ + "christianus", + "baptista", + "trappista", + "baptisma", + "protestans", + "procer" + ], + "PERSON": [ + "insula_sancti_vincentii", + "don_delillo", + "e_e_cummings", + "seleucus_i_nicator" + ], + "GENDER": [ + "guidus", + "puera", + "babae", + "male", + "guido", + "transgenerismus" + ], + "RACE": [ + "latino", + "africanus", + "africus", + "francus", + "escimaeus", + "autochthon", + "americani", + "nigricolores", + "albicolores", + "latina" + ], + "FAC": [ + "der_zauberberg", + "compostella", + "sancta_lucia", + "arnoldus_schoenberg", + "educatio_primaria", + "porta_brandenburgensis", + "trigintatres", + "ludus_litterarius", + "teloneum", + "titus_livius", + "gradatim", + "petrus_i", + "ecclesia_catholica", + "diribitorium" + ], + "LOCATION": [ + "insula_sancti_martini", + "australia_occidentalis", + "electrificina", + "trifolium_repens", + "res_adversae", + "novus_orbis", + "collegium_sancti_ioannis", + "non_forsit", + "campus_physicus", + "iordanis", + "non_obstat", + "insulae_tristanenses", + "plantago_major", + "dies_sancti_martini", + "pridem", + "mons_oliveti", + "australia_australis", + "concilium_nationale_atropatenicum", + "res_mala", + "statio_meteorologica", + "pantopolium", + "arena", + "turricula_ardozensis", + "urbs_trifluvianensis", + "aemilianus_zapata", + "ottomanus_i", + "fortuna_mala", + "the_rolling_stones", + "statio_ferriviaria", + "propero", + "via_romana", + "lacus_superior", + "res_publica_capitis_viridis", + "classis_aeria", + "lithgoana", + "trifolium_dubium", + "pater_natalis", + "falklandia" + ], + "PERSON_PRONOUN": [ + "i", + "dein", + "huic", + "me", + "vosmet", + "my", + "nobis", + "meus", + "illius", + "us" + ], + "BIO_CHEM_ENTITY": [ + "acidum_butyricum" + ], + "POLITICAL_PARTY": [ + "labor", + "kuomintang", + "factio_laboris", + "girundia", + "factio_socialis_democratica", + "factio_republicana", + "factio_democratica" + ], + "LAW": [ + "libertas_religionis", + "ius_romanum", + "ne_bis_in_idem" + ], + "EVENT": [ + "expergisci", + "chorea_macchab\u00e6orum" + ], + "UNION": [ + "sodalitas_internationalis_telecommunicationum", + "collegium_opificum" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "abbatissa": "abba", + "negotiatrix": "negotians", + "filia": "filius", + "dalila": "incantator", + "femella": "male", + "femina": "coniunx", + "feminal": "male", + "femineus": "male", + "puella": "guidus", + "babae": "guidus", + "adolescens": "facio", + "puera": "guidus", + "neptis": "nepos", + "eius": "eorum", + "huius": "horum", + "heroine": "heros", + "illius": "illorum", + "sibi": "sese", + "sese": "sibi", + "matrix": "parens", + "maximus": "patro", + "soror": "frater", + "monacha": "monachus", + "denuntiatrix": "denuntiator", + "sacerdos": "flamen", + "sacerdotessa": "imam", + "filia_regis": "regulus", + "haec": "ille", + "naja": "frater", + "venefica": "fascinatorius", + "fascinatoria": "veneficus", + "fascinatrix": "fascinator", + "fascinans": "veneficus", + "privigna": "privignus", + "noverca": "vitricus", + "vidua": "viduus", + "balo": "viduus", + "marita": "maritus", + "coniunx": "maritus", + "sponsa": "maritus", + "mulier": "maritus", + "nupta": "maritus", + "uxor": "maritus", + "striga": "fascinatorius", + "wicca": "veneficus", + "pythonissa": "fascinatorius", + "masca": "fascinans", + "malefica": "fascinatorius", + "adulescens": "puella", + "catulaster": "babae" + }, + "other_gender_swap": { + "illas": "haec", + "illos": "haec", + "has": "huius", + "haec": "eae", + "illorum": "eius", + "earum": "illius", + "horum": "eius", + "illarum": "eius", + "lia": "eorum", + "eorum": "huius", + "ii": "haec", + "illae": "haec", + "eae": "haec", + "illi": "illas", + "ille": "ii", + "huic": "haec", + "isti": "illas", + "eius": "eorum", + "illius": "earum", + "huius": "illarum" + }, + "en_pronoun2gender": { + "they": [ + "transgenerismus", + "homosexualis" + ], + "he": [ + "guidus", + "masculus", + "male", + "catulaster", + "adulescens", + "facio", + "bullo", + "guido" + ], + "she": [ + "missa", + "dominula", + "desum", + "puera", + "mulier", + "adolescens", + "femina", + "femineus", + "domestica", + "babae", + "feminal", + "femella", + "puella" + ] + }, + "en_pronoun2pronoun": { + "he": [ + "illi", + "sese", + "illius", + "lia", + "eius", + "isti", + "ille", + "sibi", + "huic" + ], + "she": [ + "huius", + "sese", + "eius", + "illius", + "haec", + "sibi" + ], + "they": [ + "eorum", + "illarum", + "illi", + "lia", + "illos", + "earum", + "illorum", + "haec", + "illae", + "illas", + "ii", + "eae", + "has", + "horum" + ], + "it": [ + "per_se", + "sese", + "eius", + "suae", + "esses", + "dies", + "alea", + "sibi", + "tento" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/lad.json b/data_tooling/pii_processing/ontology/data/lad.json new file mode 100644 index 0000000..5e16ee1 --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/lad.json @@ -0,0 +1,60 @@ +{ + "PLANT": [ + "asetunal", + "safan\u00f3rya" + ], + "RACE": [ + "djudio" + ], + "PUBLIC_FIGURE": [ + "moshe", + "i", + "putin" + ], + "PERSON_PRONOUN": [ + "i", + "mozotros" + ], + "FOOD": [ + "farina", + "chile", + "guevo", + "desyerto" + ], + "RELIGION": [ + "djudaismo_reformista" + ], + "RELIGION_MEMBER": [ + "ermano" + ], + "ORG": [ + "biznyeto" + ], + "LOCATION": [ + "giulan", + "mar_preta" + ], + "DISEASE": [ + "shasheo" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": {}, + "other_gender_swap": {}, + "en_pronoun2gender": { + "she": [ + "mujer" + ] + }, + "en_pronoun2pronoun": {}, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/lb.json b/data_tooling/pii_processing/ontology/data/lb.json new file mode 100644 index 0000000..f820d67 --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/lb.json @@ -0,0 +1,700 @@ +{ + "LANGUAGE": [ + "japanesch", + "portugisesch", + "sindhi", + "aymara", + "frans\u00e9isch", + "arabesch", + "hindi", + "esperanto", + "speech", + "ido", + "schwedesch", + "tonga" + ], + "PUBLIC_FIGURE": [ + "benjamin_franklin", + "akira_kurosawa", + "john_knox", + "leonard_bernstein", + "che_guevara", + "georges_simenon", + "c", + "maria_callas", + "henrik_ibsen", + "peter_lorre", + "john_herschel", + "jan_van_eyck", + "richard_burton", + "douglas_macarthur", + "winston_churchill", + "paul_mccartney", + "terry_pratchett", + "isaac_newton", + "victor_hugo", + "edwin_hubble", + "milton_friedman", + "schiaparelli", + "george_stephenson", + "john_glenn", + "george_orwell", + "richard_wagner", + "marie_curie", + "michael_jackson", + "thomas_hobbes", + "el_greco", + "samuel_beckett", + "david", + "galileo_galilei", + "jane_goodall", + "robert_koch", + "joseph_goebbels", + "john_steinbeck", + "edmund_hillary", + "vincent_van_gogh", + "martina_navr\u00e1tilov\u00e1", + "anne_boleyn", + "josef_stalin", + "trausch", + "steven_weinberg", + "mary_pickford", + "hans_fischer", + "willem_einthoven", + "giuseppe_verdi", + "hoffnung", + "konrad_adenauer", + "frank_sinatra", + "katharine_hepburn", + "henri_becquerel", + "henri_matisse", + "louis_pasteur", + "richard_strauss", + "hugo_grotius", + "mahalia_jackson", + "john_ford", + "gertrude_stein", + "sarah_bernhardt", + "t_s_eliot", + "dorothea_lange", + "zwee", + "charles_de_gaulle", + "paul_von_hindenburg", + "henry_moore", + "charles_lindbergh", + "f", + "ludwig_wittgenstein", + "thomas_mann", + "dante_alighieri", + "giacomo_puccini", + "fridtjof_nansen", + "louis_braille", + "herbert_marcuse", + "paul_verlaine", + "james_dean", + "oscar_wilde", + "heinrich_schliemann", + "laurence_olivier", + "francis_bacon", + "pete_seeger", + "a", + "james_brown", + "charles_baudelaire", + "charlie_parker", + "immanuel_kant", + "igor_strawinsky", + "alexandre_yersin", + "albert_schweitzer", + "saint_martin", + "johannes_kepler", + "max_planck", + "scott_joplin", + "canberra", + "elias_canetti", + "edward_jenner", + "oliver_hardy", + "cole_porter", + "jean_luc_godard", + "montesquieu", + "arthur_rubinstein", + "bertrand_russell", + "michael_faraday", + "rudolf_diesel", + "walt_disney", + "gabriel_lippmann", + "steve_reich", + "lee", + "benny_goodman", + "friedrich_engels", + "jane_austen", + "charles_laughton", + "moses", + "gustav_mahler", + "robert_redford", + "ian_fleming", + "marcel_proust", + "elizabeth_taylor", + "thomas_chippendale", + "indira_gandhi", + "george_gershwin", + "alberto_giacometti", + "hellege_christophorus", + "alfred_nobel", + "jesse_owens", + "marco_polo", + "marcel_marceau", + "guillaume_apollinaire", + "antoine_watteau", + "boris_karloff", + "pierre_corneille", + "hans_christian_andersen", + "cary_grant", + "glenn_miller", + "pablo_picasso", + "natalie_wood", + "kurt_weill", + "lester_young", + "christiaan_huygens", + "hector_berlioz", + "adam_smith", + "jean_harlow", + "henry_miller", + "karl_marx", + "friedrich_nietzsche", + "i", + "sandro_botticelli", + "al_capone", + "robert_schumann", + "le_corbusier", + "john_locke", + "helen_keller", + "paul_dukas", + "ingrid_bergman", + "frank_stella", + "h_g_wells", + "adolf_hitler", + "joseph_haydn", + "buffalo_bill", + "edvard_grieg", + "robert_boyle", + "rosa_parks", + "anne_hathaway", + "g", + "arthur_schopenhauer", + "james_cagney", + "george_lucas", + "andrew_jackson", + "louis_armstrong", + "steven_spielberg", + "jean_monnet", + "thomas_gainsborough", + "giuseppe_garibaldi", + "alexandre_dumas", + "bobby_fischer", + "johannes_gutenberg", + "wilhelm_herschel", + "amerigo_vespucci", + "girolamo_savonarola", + "emma_goldman", + "john_barrymore", + "putin", + "jean_de_la_fontaine", + "george_sand", + "peter_sellers", + "peter_o'toole", + "joseph_conrad", + "peter_paul_rubens", + "jules_verne", + "paul_newman", + "jackson_pollock", + "john_lennon", + "gandhi", + "charlie_chaplin", + "piscis_austrinus", + "hannah_arendt", + "antonio_stradivari", + "staatschef", + "miles_davis", + "bozen", + "stanley_kubrick", + "john_huston", + "james_watt", + "ronald_reagan", + "helmut_schmidt", + "david_hilbert", + "oliver_cromwell", + "lionel_hampton", + "passivf\u00ebmmen", + "zwirkinnek", + "frank_capra", + "william_wordsworth", + "woodrow_wilson", + "jean_auguste_ingres", + "don_quixote", + "ernest_hemingway", + "aquila", + "arthur_miller", + "nelson_mandela", + "heinrich_himmler", + "hans_bethe", + "roald_amundsen", + "sherwood_anderson", + "charles_dickens", + "ella_fitzgerald", + "fats_waller", + "jacques_offenbach", + "george_stevens", + "federico_fellini", + "willy_brandt", + "francisco_franco", + "bernardo_bertolucci", + "christoph_kolumbus", + "franz_schubert", + "johnny_cash", + "joseph_mccarthy", + "georges_cuvier", + "william_harvey", + "walter_gropius", + "albert_einstein", + "raymond_chandler" + ], + "ANIMAL": [ + "hoen", + "fallek", + "mierschw\u00e9ngchen", + "seideschwanz", + "adeliepinguin", + "mamend\u00e9ieren", + "mamend\u00e9ier", + "tureil", + "runn", + "blannschl\u00e9cher", + "kaweechelcher", + "arthropoden", + "canis_minor", + "pisces", + "mouk", + "gromees", + "harespel", + "kinnekspinguin", + "weidemees", + "glidderf\u00e9isser", + "kabesp\u00e4ipel", + "goldmouk", + "routhirsch", + "keeserpinguin", + "hauskaz", + "hong", + "donald_duck", + "fleeschm\u00e9cken", + "spatz", + "piwitsch", + "kaweechelchen", + "polarfuuss", + "blomees", + "spuervull", + "ouschterhues", + "polarbier", + "schl\u00e9ifer", + "karausch", + "haushong" + ], + "RELIGION": [ + "shint\u014d", + "schintoismus", + "islam", + "vishnuismus", + "daoismus" + ], + "JOB": [ + "mercator", + "the_nanny", + "glasbl\u00e9iser", + "hand", + "blockfl\u00fctt", + "don", + "buergermeeschter", + "spullmaschinn", + "the_musketeer", + "nekrophag", + "schr\u00e4iner", + "land", + "musekerin", + "museker", + "schauspiller", + "vers\u00e9cherungsmathematiker", + "ingenieurin", + "m\u00ebllechmann", + "pompjee", + "zwangsrekrut\u00e9ierten", + "sculptor", + "tirang", + "ingenieur", + "president", + "pompjee\u00ebn", + "collier", + "schr\u00ebftsteller", + "kinnek", + "doc", + "sch\u00e9ifer", + "brutschen", + "wiewer" + ], + "GPE": [ + "kleeschen", + "hellege_christophorus", + "dar_es_salaam", + "valentinsdag", + "s\u00e3o_tom\u00e9", + "zockerhutt", + "la_rochelle", + "helleg_b\u00e4erbel", + "la_gomera", + "s\u00fcdamerika" + ], + "LOCATION": [ + "zentralbank", + "westaustralien", + "friddensgeriicht", + "kap_verde", + "nordmier", + "la_roche_en_ardenne", + "friddensriichterin", + "wiederstatioun", + "land", + "huang_he", + "saint_vincent", + "s\u00fcdaustralien", + "joseph_louis_gay_lussac", + "geriicht", + "botanesche_gaart", + "fleegeheem", + "al_dschasira", + "kap_hoorn", + "saint_lucia", + "friddensriichter", + "sri_lanka", + "seniorenheem", + "the_rolling_stones", + "m\u00ebllechstrooss", + "al_ain", + "santa_claus" + ], + "DATE": [ + "liichtvitesse", + "ouschtersonndeg", + "vollmound", + "neimound", + "radialvitesse", + "allers\u00e9ilen", + "l\u00e9iffraw\u00ebschdag", + "schaltjoer", + "gregorianesche_kalenner", + "nationalfeierdag", + "karfreideg", + "moundphas", + "allerhellegen", + "karsamschdeg", + "solarkonstant", + "allers\u00e9ilendag", + "allerhellgen" + ], + "ORG": [ + "krichsmarine", + "san_jos\u00e9", + "jan_mayen", + "zentralbank", + "nasa", + "huang_he", + "generalst\u00e4nn", + "hirschkou", + "tallekeschung", + "m\u00ebttelschoul", + "san_francisco", + "kn\u00e4tsch", + "stammbam", + "no_an_no", + "kapetinger", + "dot", + "saint_vincent", + "cap_vert", + "saint_helena", + "privatschoul", + "jesuiten", + "kn\u00e4tschgummi", + "vereenegt_staate_vun_amerika", + "weltgesondheetsorganisatioun", + "talleken", + "kathoulesch_kierch", + "kleeschen", + "den_d\u00e9cken_an_den_d\u00ebnnen", + "schintoismus", + "winnie_the_pooh", + "reen", + "rout_mier", + "arm\u00e9i", + "po", + "mount_carmel", + "ferdinand_magellan", + "vishnuismus", + "schoul", + "ursa_major", + "saint_barth\u00e9lemy", + "froenzeechen", + "los_angeles", + "al_dschasira", + "st\u00e4rekoup", + "radiogalaxis", + "andromedagalaxis", + "doc", + "grondschoul", + "al_ain", + "m\u00e4rei", + "house_of_lords", + "s\u00e3o_tom\u00e9", + "entw\u00e9cklungsland", + "shint\u014d" + ], + "PRODUCT": [ + "justin_bieber", + "segelsch\u00ebff", + "s\u00e3o_tom\u00e9_a_pr\u00edncipe", + "stiefesdag", + "hellege_geescht", + "beliichten", + "saint_vincent", + "naturl\u00e9ier", + "diskett", + "the_star_spangled_banner", + "mierschw\u00e9ngchen", + "don_quixote", + "moien", + "seegelsch\u00ebff", + "sachsen_anhalt", + "the_lord_of_the_rings", + "la_dolce_vita", + "himmelskierper", + "museksinstrument", + "ferdinand_magellan", + "neis\u00e9iland", + "nordrhein_westfalen", + "chr\u00ebschtbeemchen" + ], + "POLITICAL_PARTY": [ + "conservative_party", + "labour_party", + "republican_party", + "politesch_partei", + "parti_socialiste", + "democratic_party" + ], + "PLANT": [ + "gef\u00e4ssplanzen", + "moschter", + "melissa", + "sonneblumm", + "wanterlann", + "tulpebam", + "mille_feuille", + "muert", + "spirebam", + "feierblumm", + "abr\u00ebllsblumm", + "ambaraskr\u00e9imer", + "biergahorn", + "routeech", + "meer\u00e9ischen", + "maasselter", + "kierwel", + "brennnessel", + "kiischt", + "sauerampel", + "kam\u00e9ileblumm", + "routbuch", + "praum", + "hobich", + "gaardeboun", + "austerechampignon", + "klett", + "stilleech", + "promm", + "frans\u00e9ische_p\u00e4llem" + ], + "FOOD": [ + "cayennepeffer", + "olivenueleg", + "schockelaskaffi", + "pascht\u00e9it", + "uebstjus", + "fritten", + "lorberblat", + "pinot_noir", + "schlagsahn", + "spigelee", + "chile", + "zockerwatt", + "dessert", + "drauwejus" + ], + "PERSON": [ + "zweeandr\u00ebsseg", + "h_g_wells", + "saint_vincent" + ], + "DISEASE": [ + "nesselsucht", + "schued", + "gielzecht", + "klont", + "schw\u00e9ngsgripp", + "welt", + "schlofen", + "riselen", + "demenz", + "pautsch", + "weesch\u00ebsser", + "k\u00e4scht", + "computermaus", + "schubber", + "pescht", + "frenzy", + "moschwier", + "fugue", + "houschten", + "waasserpouken", + "opreegung", + "stralung", + "pull", + "longenentz\u00fcndung", + "aura", + "waarzel", + "recken", + "riedelen", + "h\u00e9ichtenangscht", + "the_hives", + "gr\u00ebnner", + "roserei", + "schwangerschaft", + "duuscht" + ], + "FAC": [ + "grondschoul", + "p\u00e9iter_de_groussen", + "prim\u00e4rschoul", + "no_an_no", + "saint_lucia", + "m\u00e4rei", + "dr\u00e9chemauer" + ], + "RELIGION_MEMBER": [ + "brudder" + ], + "PERSON_PRONOUN": [ + "i", + "our", + "noss", + "hien", + "senger" + ], + "BIO_CHEM_ENTITY": [ + "almoudesch", + "m\u00ebllechsaier" + ], + "QUANTITY": [ + "primzuel", + "kalorie", + "dollar", + "quadratmeter", + "aachtanzwanzeg", + "g", + "parkauer", + "pond", + "pond_sterling", + "anders_celsius" + ], + "TITLE": [ + "sir" + ], + "EVENT": [ + "sing_sing" + ], + "UNION": [ + "weltpostver\u00e4in", + "gewerkschaft" + ], + "MEDICAL_THERAPY": [ + "bluttdrock" + ], + "GENDER": [ + "transgender", + "gal" + ], + "LAW": [ + "chanc\u00ebgl\u00e4ichheet" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "verfeelen": "sir", + "joffer": "sir", + "mamm": "dax", + "pr\u00edncipe": "pr\u00ebnz", + "prinzessin": "prince", + "kinnigin": "kinnek", + "hunn": "ell", + "schw\u00ebster": "brudder", + "gutt": "meedchen" + }, + "other_gender_swap": { + "iddi": "hunn", + "hien": "iddi", + "ell": "iddi", + "hunn": "iddi" + }, + "en_pronoun2gender": { + "they": [ + "transgender" + ], + "he": [ + "little_boy", + "mees", + "gutt" + ], + "she": [ + "gal", + "joffer", + "hunn", + "jupe", + "verfeelen", + "meedchen" + ] + }, + "en_pronoun2pronoun": { + "he": [ + "s\u00e4i", + "seine", + "senger", + "hien", + "ell" + ], + "she": [ + "hunn" + ], + "they": [ + "iddi" + ], + "it": [ + "d\u00ebs" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/lexicon_by_prefix.json.gz b/data_tooling/pii_processing/ontology/data/lexicon_by_prefix.json.gz new file mode 100644 index 0000000..c76a562 Binary files /dev/null and b/data_tooling/pii_processing/ontology/data/lexicon_by_prefix.json.gz differ diff --git a/data_tooling/pii_processing/ontology/data/li.json b/data_tooling/pii_processing/ontology/data/li.json new file mode 100644 index 0000000..55bd7e4 --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/li.json @@ -0,0 +1,69 @@ +{ + "DATE": [ + "namesdaag", + "vaderdaag", + "trinitatis" + ], + "PUBLIC_FIGURE": [ + "maria_magdalena", + "petrus", + "e", + "titus" + ], + "LANGUAGE": [ + "lingalisj", + "gallesisj", + "nachoeroe", + "ido", + "quechua", + "tonga" + ], + "RELIGION": [ + "calvinisme" + ], + "JOB": [ + "hand" + ], + "QUANTITY": [ + "leechjaor" + ], + "PLANT": [ + "craemsjnitje" + ], + "ORG": [ + "l\u00f3chh\u00e8\u00e8r" + ], + "GPE": [ + "zwarsb\u00f3sj" + ], + "LOCATION": [ + "sri_lanka" + ], + "ANIMAL": [ + "gelidpoetege" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": {}, + "other_gender_swap": {}, + "en_pronoun2gender": { + "she": [ + "bomma" + ] + }, + "en_pronoun2pronoun": { + "it": [ + "denne" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/lij.json b/data_tooling/pii_processing/ontology/data/lij.json new file mode 100644 index 0000000..943ec66 --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/lij.json @@ -0,0 +1,43 @@ +{ + "JOB": [ + "main\u00e2", + "past\u00f4", + "acat\u00f2u" + ], + "ORG": [ + "un" + ], + "PUBLIC_FIGURE": [ + "n" + ], + "RELIGION": [ + "scintoiximo" + ], + "LOCATION": [ + "sri_lanka" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": {}, + "other_gender_swap": {}, + "en_pronoun2gender": { + "he": [ + "m\u00e0sccio" + ] + }, + "en_pronoun2pronoun": { + "it": [ + "qu\u00e9sto" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/liv.json b/data_tooling/pii_processing/ontology/data/liv.json new file mode 100644 index 0000000..1558623 --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/liv.json @@ -0,0 +1,31 @@ +{ + "LOCATION": [ + "tien\u016b" + ], + "DISEASE": [ + "magg\u00f5" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "le\u0161knai": "atr\u0101ita", + "atr\u0101itanai": "atr\u0101ita" + }, + "other_gender_swap": {}, + "en_pronoun2gender": { + "she": [ + "neit\u0161ki" + ] + }, + "en_pronoun2pronoun": {}, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/lkt.json b/data_tooling/pii_processing/ontology/data/lkt.json new file mode 100644 index 0000000..68135af --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/lkt.json @@ -0,0 +1,49 @@ +{ + "PERSON_PRONOUN": [ + "he" + ], + "LOCATION": [ + "phil\u00e1mayayapi", + "phil\u00e1mayaye" + ], + "PLANT": [ + "cansapa" + ], + "DISEASE": [ + "mi", + "le" + ], + "ORG": [ + "mi" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": {}, + "other_gender_swap": { + "he": "iyepi" + }, + "en_pronoun2gender": { + "she": [ + "w\u00ed\u014bya\u014b" + ] + }, + "en_pronoun2pronoun": { + "he": [ + "he" + ], + "they": [ + "iyepi", + "epi" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/lld.json b/data_tooling/pii_processing/ontology/data/lld.json new file mode 100644 index 0000000..20cfbf4 --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/lld.json @@ -0,0 +1,72 @@ +{ + "ANIMAL": [ + "ghiro", + "castour", + "gialina", + "passer", + "stambech", + "lustrel", + "falcon", + "capriol", + "schirata", + "valtoi", + "belora" + ], + "ORG": [ + "doi", + "aa", + "l\u00ebur", + "scola" + ], + "DISEASE": [ + "pontes", + "mania", + "ronia", + "parpaiola" + ], + "JOB": [ + "saud\u00e9", + "laurant" + ], + "PUBLIC_FIGURE": [ + "laur\u00ebnz", + "n", + "bulsan", + "l" + ], + "DATE": [ + "vedleza" + ], + "LANGUAGE": [ + "spanuel", + "franz\u00ebus" + ], + "PRODUCT": [ + "porcel_de_mar" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": {}, + "other_gender_swap": {}, + "en_pronoun2gender": { + "she": [ + "\u00ebila", + "femena" + ] + }, + "en_pronoun2pronoun": { + "it": [ + "chest" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/lmo.json b/data_tooling/pii_processing/ontology/data/lmo.json new file mode 100644 index 0000000..e572a24 --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/lmo.json @@ -0,0 +1,195 @@ +{ + "PUBLIC_FIGURE": [ + "akira_kurosawa", + "che_guevara", + "abelard", + "mary_shelley", + "giorgiu", + "terry_pratchett", + "isaac_newton", + "joseph_smith", + "saint_louis", + "marie_curie", + "michael_jackson", + "galileo_galilei", + "john_donne", + "vincent_van_gogh", + "robert_burns", + "henri_matisse", + "louis_pasteur", + "john_ford", + "sarah_bernhardt", + "f", + "nicol\u00e0us_cop\u00e8rnich", + "charles_baudelaire", + "johannes_kepler", + "max_planck", + "canberra", + "niels_bohr", + "tom\u00e0s", + "michael_faraday", + "marco_polo", + "allen_ginsberg", + "gottfried_leibniz", + "pablo_picasso", + "karl_marx", + "i", + "nikola_tesla", + "le_corbusier", + "john_locke", + "adolf_hitler", + "rosa_parks", + "g", + "crist\u00f2foro_col\u00f3mbo", + "johann_gutenberg", + "giusep_verdi", + "mahatma_gandhi", + "charlie_chaplin", + "d_h_lawrence", + "ronald_reagan", + "lorenz", + "nelson_mandela", + "roald_amundsen", + "don_quijote_de_la_mancha", + "federico_fellini", + "bulsan", + "francisco_franco", + "johnny_cash", + "michelangelo_merisi", + "albert_einstein", + "thomas_edison" + ], + "PRODUCT": [ + "pozz", + "el_scior_di_anei", + "sas\u00f2nia_anhalt" + ], + "PLANT": [ + "lilium_martagon", + "viola_arvensis", + "viola_reichenbachiana", + "helleborus_niger", + "solanaceae", + "viola_cornuta", + "cyclamen_purpurascens", + "bidens_tripartita", + "ranunculus_ficaria", + "prunus_armeniaca", + "stellaria_media", + "helianthus_tuberosus", + "verbena_officinalis", + "gymnadenia_conopsea", + "sorbus_aucuparia", + "saxifraga_stellaris", + "fagus_sylvatica", + "saccharomyces_cerevisiae", + "campanula_trachelium", + "taraxacum_officinale", + "stellaria_holostea", + "cardamine_pratensis", + "viola_odorata" + ], + "ANIMAL": [ + "bissa", + "donald_duck", + "pirol", + "primula_vulgaris" + ], + "FOOD": [ + "desert", + "juglans_regia" + ], + "DISEASE": [ + "presb\u00edzzia", + "corn" + ], + "GPE": [ + "dar_es_salaam", + "san_lureenz", + "sint_maarten", + "mar_russ", + "mar_egee", + "s\u00e3o_tom\u00e9", + "san_peder", + "n\u00f6v_testament" + ], + "PERSON_PRONOUN": [ + "i" + ], + "ORG": [ + "san_francisco", + "sant_elena", + "can_tho", + "chiang_mai", + 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+ "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/ln.json b/data_tooling/pii_processing/ontology/data/ln.json new file mode 100644 index 0000000..9e901db --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/ln.json @@ -0,0 +1,59 @@ +{ + "FOOD": [ + "like\u00ed" + ], + "RELIGION_MEMBER": [ + "mozilmani" + ], + "PLANT": [ + "many\u0254\u0301k\u0254" + ], + "LANGUAGE": [ + "ling\u00e1la", + "falans\u00e9", + "tonga" + ], + "JOB": [ + "mokomi" + ], + "LOCATION": [ + "sri_lanka" + ], + "EVENT": [ + "kolamuka" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "y\u011b": "elu" + }, + "other_gender_swap": {}, + "en_pronoun2gender": { + "she": [ + "m\u00e1i", + "bambola", + "mwasi", + "bimba" + ] + }, + "en_pronoun2pronoun": { + "he": [ + "elu", + "y\u011b" + ], + 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"arnold_sch\u00f6nberg", + "anne_hathaway", + "titas", + "povis", + "bill_russell", + "g", + "albert_michelson", + "\u0161v_martyno_sala", + "arthur_schopenhauer", + "martin_heidegger", + "\u0161v_patrikas", + "r", + "andrew_jackson", + "louis_armstrong", + "steven_spielberg", + "d_w_griffith", + "thomas_gainsborough", + "giuseppe_garibaldi", + "alexandre_dumas", + "johann_gutenberg", + "al_kapon\u0117", + "tamara_karsavina", + "d", + "thomas_malthus", + "gaetano_donizetti", + "william_faulkner", + "raudonkepuraite", + "john_constable", + "markas_polas", + "joseph_campbell", + "robert_hooke", + "karl_popper", + "joseph_conrad", + "peter_paul_rubens", + "jim_morrison", + "jules_verne", + "paul_newman", + "jackson_pollock", + "john_lennon", + "andrea_palladio", + "charlie_chaplin", + "al_jolson", + "apa\u0161talas_petras", + "miles_davis", + "george_marshall", + "stanley_kubrick", + "robertas_braunas", + "james_watt", + "ronald_reagan", + "helmut_schmidt", + "david_hilbert", + "siamo_dvyniai", + "oliver_cromwell", + "martin_luther_king", + "gerardas_merkatorius", + "woodrow_wilson", + "michailas_bakuninas", + "jim_henson", + "ernest_hemingway", + "arthur_miller", + "karolis", + "nelson_mandela", + "heinrich_himmler", + "al_gore", + "mohandas_gandhi", + "j_p_morgan", + "roald_amundsen", + "sherwood_anderson", + "charles_dickens", + "marija_stiuart", + "ella_fitzgerald", + "jacques_offenbach", + "marija_magdaliet\u0117", + "federico_fellini", + "jok\u016bbo_lai\u0161kas", + "jean_antoine_watteau", + "willy_brandt", + "francisco_pizarro", + "francisco_franco", + "bernardo_bertolucci", + "jan_steen", + "nikita_chru\u0161\u010diovas", + "powell", + "philibert_delorme", + "hans_arp", + "andrew_carnegie", + "franz_schubert", + "\u0161ventasis_kristoforas", + "alfred_kastler", + "georges_cuvier", + "william_harvey", + "walter_scott", + "ivanas_turgenevas", + "maksimianas", + "bethuovens", + "jonathan_swift", + "albert_einstein", + "thomas_edison", + "antanas", + "raymond_chandler", + "henry_purcell", + "t", + "wilhelm_ostwald" + ], + "PRODUCT": [ + "stara_planina", + "popierinis_l\u0117ktuv\u0117lis", + "justin_bieber", + "trys_valstyb\u0117s", + "krik\u0161tykla", + "san_choakinas", + "juru_kiaulyte", + "natiurmortas", + "sen_pjeras_ir_mikelonas", + "logaritmin\u0117_liniuot\u0117", + "diskelis", + "teve_musu", + "vargonai", + "glaudes" + ], + "PLANT": [ + "menininkas", + "maumedis", + "amerikin\u0117_fitolaka", + "ragan\u0117", + "kiauliauoge", + "magnolija", + "the_joshua_tree", + "girtuokle", + "varnale\u0161a", + "aronas", + "chrizantema", + "mastika", + "mahonija", + "monarda", + "malpigija", + "kopustas", + "altas", + "batatas", + "paprastasis_\u010diobrelis", + "kamparas", + "\u0161ventoji_marija", + "anona", + "sakura", + "artistas", + "juodalksnis", + "blind\u0117", + "stambiauog\u0117_spanguol\u0117", + "pelynas", + "europinis_o\u017eek\u0161nis", + "tikrinis_baravykas", + "krauja\u017eole", + "karklavijas", + "vaismedis", + "rafija", + "kiauliauog\u0117", + "pakalnute", + "drebul\u0117", + "europinis_p\u016bkenis", + "sausmedis", + "europinis_k\u0117nis", + "paragvajinis_bugienis", + "saul\u0117gr\u0105\u017ea", + "kal\u0117d\u0173_eglut\u0117", + "amerikinis_bukas", + "kakava", + "blackberry", + "valisnerija", + "melisa", + "klevas", + "juodgr\u016bd\u0117", + "krauja\u017eol\u0117", + "gaisrena", + "putoklis", + "induo\u010diai", + "spanguol\u0117", + "gleiv\u016bnai", + "baltalksnis", + "burokelis", + "magnolij\u016bnai", + "ka\u0161tainis", + "garsty\u010dios", + "\u0161unvy\u0161ne", + "balinis_asi\u016bklis", + "bobausis", + "saulegra\u017ea", + "karklas", + "neu\u017emir\u0161tuole", + "pelevirk\u0161tis" + ], + "LANGUAGE": [ + "lenku", + "ispanu", + "jidi\u0161", + "rusas", + "dani\u0161kai", + "lenki\u0161kas", + "graikas", + "kirtis", + "arabu", + "pali", + "hindi", + "kalvis", + "persu", + "esperanto", + "arabi\u0161kas", + "anglu", + "danakilu", + "malajaliu", + "graike", + "ido", + "angli\u0161kas", + "kanadu", + "tonga" + ], + "FAC": [ + "geros_kelione", + "rotu\u0161e", + "sent_lusija", + "mik\u0117_p\u016bkuotukas", + "arnold_sch\u00f6nberg", + "atakama", + "muitine", + "aik\u0161te", + "t_limfocitai", + "juozapas_i\u0161_nazareto", + "devintin\u0117s", + "prekybos_centras", + "pa\u0161to_skyrius", + "tangutai", + "triumfo_arka", + "petras_i" + ], + "ANIMAL": [ + "menk\u0117", + "pelesakalis", + "blakut\u0117s", + "kiriniai", + "strazdiniai", + "amerikinis_omaras", + "storkulniniai", + "laibapir\u0161tiniai", + "volunge", + "narioutakuoj\u0113", + "gagos", + "volunginiai", + "raudondumbliai", + "burundukai", + "neporakanopiai", + "juodasis_v\u0117\u017elys", + "maldininkai", + "audine", + "kranklys", + "markata_husaras", + "artemijos", + "laibapir\u0161tis", + "trumpasparniai", + "katinas", + "ridl\u0117ja", + "barsukas", + "miegapele", + "antilopiniai_starai", + "sprak\u0161iai", + "kund\u016bzas", + "garniniai", + "garnys", + "miegapeliniai", + "paprastoji_raudonuodeg\u0117", + "gelsvadumbliai", + "borderkolis", + "briedis", + "danielius", + "stulgys", + "pauk\u0161tvanagis", + "grinda", + "vanagas", + "tarakonas", + "dilg\u0117linukas", + "tarakonai", + "staug\u016bnai", + "grifai", + "rudadumbliai", + "vanagai", + "liepsnel\u0117", + "asilas", + "dygliatriu\u0161iniai", + "porakanopiai", + "ragys", + "tauk\u017euv\u0117", + "strazdas", + "holoturijos", + "burnakojai", + "kiaune", + "kurtinys", + "sprag\u0117s", + "paprastasis_tenrekas", + "bombo\u017eygiai", + "liutukas", + "kiras", + "karetaitiniai", + "peleda", + "ciegorius", + "tabako_mozaikos_virusas", + "\u017ealtys", + "pekaris", + "laivasnapis", + "grifas", + "j\u016br\u0173_kiaulyt\u0117", + "musinukiniai", + "peledike", + "amerikinis_lamantinas", + "dagilis", + "avocet\u0117", + "trapusis_gluodenas", + "varn\u0117nas", + "sabalas", + "paprastasis_kirstukas", + "alse", + "skydamariniai", + "alksninukas", + "grie\u017el\u0117", + "maldininkas", + "\u010diurliniai", + "askarid\u0117s", + "kalviukai", + "jerub\u0117", + "nariuotakojai", + "taist\u0117", + "stumbras", + "\u017eagata", + "varl\u0117s", + "karetait\u0117", + "slanka", + "patar\u0161ka", + "bitininkiniai", + "mevas", + "vedarelis", + "kiaun\u0117s", + "namine_peleda", + "strazdas_giesmininkas" + ], + "ORG": [ + "baltieji_rumai", + "lavinimas", + "lomondas", + "savivalda", + "wicca", + "andromedos_galaktika", + "akademija", + "ii_vatikano_susirinkimas", + "klaustukas", + "\u0161elmenin\u0117_kreg\u017ed\u0117", + "guomindanas", + "airijos_darbinink\u0173_partija", + "aa", + "nasa", + "arda", + "karmelio_kalnas", + "the_who", + "huangh\u0117", + "sofijos_soboras", + "kantas", + "romos_kataliku_ba\u017eny\u010dia", + "pradine_mokykla", + "kataliku_ba\u017eny\u010dia", + "va", + "profesine_sajunga", + "konservatorija", + "vokietijos_nacionalsocialistin\u0117_darbinink\u0173_partija", + "gao", + "mike_pukuotukas", + "islamo_tauta", + "europolas", + "al_d\u017eazira", + "bolivudas", + "profsajunga", + "kariuomen\u0117", + "trua_rivjeras", + "nanakas", + "the_football_league", + "dominija", + "holdingas", + "senbernaras", + "dia", + "koled\u017eas", + "khonkenas", + "azerbaid\u017eano_socialdemokrat\u0173_partija", + "nyderland\u0173_darbo_partija", + "i_nik\u0117jos_susirinkimas", + "rotu\u0161e", + "jaunatis", + "centrinis_bankas", + "namie", + "vai\u0161navizmas", + "fabianizmas", + "beniliuksas", + "komunist\u0173_partija", + "proanukis", + "provaikaitis", + "romos_katalik\u0173_ba\u017eny\u010dia", + "grand\u0117", + "jungtin\u0117s_amerikos_valstijos", + "kapetingai", + "leidykla", + "\u0161v_barbora", + "pranc\u016bzijos_socialist\u0173_partija", + "aukso_am\u017eius", + "portugalijos_socialist\u0173_partija", + "ivano_frankivskas", + "karines_oro_pajegos", + "modernas", + "auklejimas", + "\u0161intoizmas", + "tarptautin\u0117_telekomunikacij\u0173_s\u0105junga", + "po", + "\u0161ventoji_barbora", + "mossad", + "kariuomene", + "\u0161into\u0117zmos", + "andoros_socialdemokrat\u0173_partija", + "sturmabteilung", + "armija", + "primor\u0117s_kra\u0161tas", + "nato", + "aleksandras_makedonietis", + "baltieji_r\u016bmai", + "by_the_way", + "profesin\u0117_s\u0105junga", + "pradin\u0117_mokykla", + "gestapas", + "civilin\u0117_teis\u0117", + "baskija", + "mano_vardas", + "talionas", + "ii_nik\u0117jos_susirinkimas", + "muok\u012bkla", + "surathanis", + "didieji_gri\u017eulo_ratai", + "didieji_gr\u012f\u017eulo_ratai", + "streptococcus_pyogenes", + "maltos_darbinink\u0173_partija", + "\u017ealiasis_ky\u0161ulys", + "segregacija", + "nacionalinis_susirinkimas", + "ainas", + "komercija", + "san_siro_stadionas", + "nakhonrat\u010dasima", + "karin\u0117s_oro_paj\u0117gos" + ], + "RACE": [ + "turke", + "valai", + "turkai", + "indenu", + "turkas", + "airiai", + "olandai", + "afrikietis", + "afrikie\u010diu", + "afrikieti\u0161kas", + "japonai" + ], + "GPE": [ + "sint_martenas", + "raudonojo_kry\u017eiaus", + "raudonoji_j\u016bra", + "\u017emogaus_teises", + "\u0161ventoji_dvasia", + "vokietijos_imperija", + "\u010diangrajus", + "dar_es_salamas", + "sent_luisas", + "\u0161v_mikalojus", + "al_andalusija", + "\u0161ventasis_mikalojus", + "tai_\u0161anas", + "manilos_metropolija", + "naujasis_testamentas", + "\u0161v_lauryno_up\u0117", + "kampongtjamas", + "\u017emogaus_teis\u0117s", + "raudonoji_jura", + "la_gomera", + "jurgin\u0117s", + "san_tom\u0117" + ], + "DATE": [ + "gimstamumas", + "\u017eolin\u0117", + "viduram\u017eiai", + "ledynmetis", + "radialinis_greitis", + "porytdiena", + "didysis_penktadienis", + "ed_al_fitr", + "jaunatis" + ], + "UNION": [ + "profsajunga", + "student\u0173_atstovyb\u0117" + ], + "QUANTITY": [ + "\u0161viesmetis", + "kudra", + "jungo_modulis", + "pranc\u016bzijos_frankas", + "doleris", + "g", + "jordanijos_dinaras", + "modulis", + "tonas", + "danijos_krona", + "kalorija", + "svaras", + "anders_celsius" + ], + "BIO_CHEM_ENTITY": [ + "adenozindifosfatas", + "tirozinkinaz\u0117", + "dietileteris", + "polivinilchloridas", + "edward_thatch" + ], + "FOOD": [ + "limunada", + "pranc\u016bzi\u0161kas_skrebutis", + "portveinas", + "ledai", + "liespienis", + "lukumas", + "desertas", + "kramtomoji_guma", + "limonadas", + "pietus", + "vaisi\u0173_salotos" + ], + "PERSON": [ + "al_gore", + "tai_\u0161anas", + "brazilinis_kau\u010diukmedis", + "rudolf_hess", + "herbert_george_wells" + ], + "GENDER": [ + "mergina", + "moteri\u0161kas", + "mergaite", + "berniukas", + "moteris", + "man", + "gal", + "senukas" + ], + "SOC_ECO_CLASS": [ + "grietin\u0117l\u0117", + "samurajus", + "proletariatas", + "\u017eemes_ukis", + "juodoji_rinka", + "\u017eem\u0117s_\u016bkis", + "nedaug" + ], + "POLITICAL_PARTY": [ + "demokrat\u0173_respublikon\u0173_partija", + "liberal\u0173_partija", + "australijos_darbinink\u0173_partija", + "liaudies_partija", + "leiborist\u0173_partija", + "konservatori\u0173_partija", + "guomindanas", + "rumunijos_socialdemokrat\u0173_partija", + "politin\u0117_partija", + "jav_demokrat\u0173_partija", + "estijos_socialdemokrat\u0173_partija", + "norvegijos_darbo_partija", + "demokrat\u0173_partija", + "socialdemokrat\u0173_partija", + "politine_partija", + "jav_respublikon\u0173_partija", + "jav_vig\u0173_partija" + ], + "PERSON_PRONOUN": [ + "i", + "savas", + "kasykla" + ], + "POLITICAL_PARTY_MEMBER": [ + "bendra\u017eygis", + "bendra\u017eyge" + ], + "LAW": [ + "karo_pad\u0117tis", + "auk\u0161\u010diausiasis_teismas", + "federalinis_tyrim\u0173_biuras", + "karo_padetis", + "rom\u0117n\u0173_teis\u0117", + "civiline_teise" + ], + "TITLE": [ + "ponas" + ], + "MEDICAL_THERAPY": [ + "kraujosp\u016bdis" + ], + "EVENT": [ + "superliga" + ], + "ner_regexes": [ + [ + "PERSON", + "\\D+ \\D+|\\D+ \\D+|\\D+, \\D+", + false, + [] + ] + ], + "FIRST_NAME": [ + "liepa", + "raminta", + "rugil\u0117", + "benas", + "ieva", + "arminas", + "markas", + "milda", + "erikas", + "tautvydas", + "orestas", + "giedrius", + "radvil\u0117", + "rokas", + "robertas", + "arnas", + "vanesa", + "paulina", + "andrius", + "rasa", + "paulius", + "\u017eivil\u0117", + "tadas", + "sigita", + "kipras", + "gerda", + "greta", + "kristina", + "leila", + "simona", + "gintar\u0117", + "jor\u016bn\u0117", + "nedas", + "ugn\u0117", + "martynas", + "milana", + "aur\u0117ja", + "adomas", + "ryt\u0117", + "olivija", + "egidijus", + "darija", + "eidvil\u0117", + "edvinas", + "sandra", + "simas", + "nojus", + "nerijus", + "deividas", + "justina", + "lukas", + "diana", + "titas", + "simonas", + "ernestas", + "matas", + "izabel\u0117", + "dominykas", + "goda", + "vytautas", + "edita", + "neringa", + "edgaras", + "armandas", + "reda", + "gyt\u0117", + "aronas", + "ingrida", + "\u0161ar\u016bnas", + "ri\u010dardas", + "laura", + "enrika", + "donatas", + "arnoldas", + "agn\u0117", + "karina", + "aurimas", + "perla", + "justinas", + "ar\u016bnas", + "jok\u016bbas", + "l\u0117ja", + "ign\u0117", + "julius", + "jovita", + "danielius", + "v\u0117j\u016bn\u0117", + "aistis", + "linas", + "mant\u0117", + "monika", + "r\u016bta", + "gediminas", + "dovil\u0117", + "arvydas", + "mantas", + "emilis", + "marius", + "\u0105\u017euolas", + "eleonora", + "arijus", + "kajus", + "algirdas", + "aivaras", + "rojus", + "rolandas", + "evelina", + "vaida", + "kotryna", + "evaldas", + "joris", + "romualdas", + "adrija", + "ana", + "dainius", + "augustas", + "jurgita", + "au\u0161ra", + "amelija", + "vaidas", + "gabrielius", + "rytis", + "antanas", + "smilt\u0117", + "\u017eemyna", + "jolanta", + "erika", + "vilt\u0117", + "kristupas", + "dovydas", + "rita", + "aurelija", + "viktorija", + "iveta", + "ineta", + "ema", + "brigita", + "gytis", + "med\u0117ja", + "elena", + "kornelija", + "vakris", + "vyt\u0117", + "indr\u0117", + "vakar\u0117", + "edvardas", + "tajus", + "dominyka", + "eimantas", + "vigilija", + "irma", + "leticija", + "laurynas", + "petras", + "saulius", + "aleksandras", + "ram\u016bnas", + "giedr\u0117", + "povilas", + "juozas", + "gustas", + "ariana", + "audrius", + "au\u0161rin\u0117", + "egl\u0117", + "tomas", + "k\u0119stutis", + "\u017eygimantas", + "ramun\u0117", + "vasar\u0117", + "domas", + "pijus", + "naglis", + "darius", + "justas", + "irmantas", + "jonas", + "vilius", + "vitalija", + "karolina", + "faustas", + "meda", + "domantas", + "sonata", + "ligita", + "rimant\u0117", + "ariel\u0117", + "karolis", + "svetlana", + "migl\u0117", + "laurita", + "marija", + "mindaugas", + "ignas", + "art\u016bras", + "rusn\u0117" + ], + "LAST_NAME": [ + "gronskis", + "pocius", + "gailys", + "jankauskas", + "naru\u0161is", + "ambrasas", + "\u017eukauskas", + "grinius", + "kaupas", + "sakalauskas", + "gai\u010di\u016bnas", + "kavaliauskas", + "povilonis", + "naujokas", + "petrauskas", + "kalvaitis", + "galdikas", + "gagys", + "paulauskas", + "po\u0161ka", + "nagys", + "kazlauskas", + "akelis", + "ki\u0161ka", + "gai\u017eauskas", + "kalv\u0117nas", + "ginzburgas", + "urbonas", + "stankevi\u010dius", + "gintalas", + "kairys", + "kalvelis", + "vsiliauskas", + "gailius", + "butkus", + "naus\u0117da" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "baroniene": "baronas", + "dukra": "zoon", + "dukte": "sunus", + "hercogiene": "hercogas", + "imperatore": "imperatorius", + "moteri\u0161kas": "vyri\u0161kas", + "gal": "gvidas", + "mergina": "gvidas", + "mergaite": "gvidas", + "anuke": "anukas", + "dukraite": "vaikaitis", + "didvyre": "didvyris", + "cik": "ponas", + "panele": "ponas", + "motina": "tevas", + "ponia": "ponas", + "freiras": "vienuolis", + "princese": "princas", + "karaliene": "indra", + "kvinsas": "karaliu_knyga", + "jei": "jis", + "sesuo": "brolis", + "na\u0161le": "na\u0161lys", + "\u017emona": "sutuoktinis", + "duona": "man", + "moteris": "vyras", + "berniukas": "mergaite", + "darbininkas": "darbininke" + }, + "other_gender_swap": { + "juos": "jei", + "jie": "jei", + "jis": "juos", + "jei": "juos" + }, + "en_pronoun2gender": { + "they": [ + "homoseksuali", + "homoseksualus" + ], + "he": [ + "gvidas", + "vyru", + "ma\u017eylis", + "man", + "vyras", + "berniukas", + "d\u017eentelmenas", + "vyri\u0161kas" + ], + "she": [ + "moteri\u0161kas", + "duona", + "moteris", + "mergaite", + "mergina", + "panele", + "cik", + "gal" + ] + }, + "en_pronoun2pronoun": { + "he": [ + "jis", + "savas" + ], + "she": [ + "jei" + ], + "they": [ + "jei", + "jie", + "juos" + ], + "it": [ + "esti", + "\u0161ita", + "\u0161is", + "jis", + "\u0161itas", + "\u0161i" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/ltg.json b/data_tooling/pii_processing/ontology/data/ltg.json new file mode 100644 index 0000000..0a3b6b2 --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/ltg.json @@ -0,0 +1,127 @@ +{ + "ANIMAL": [ + "vysta", + "luoseica", + "krauklis", + "rubyns", + "lapsine", + "vuorna", + "kaiva", + "brusaks", + "strods", + "vardive" + ], + "JOB": [ + "zinineica", + "vaduojs", + "kara\u013cs", + "zinin\u012bks", + "sorgs", + "viergs", + "kiene\u0146\u0161", + "linejals", + "slave", + "glausteit", + "glaudeit" + ], + "PERSON_PRONOUN": [ + "i" + ], + "FOOD": [ + "reiti\u0161kys" + ], + "PUBLIC_FIGURE": [ + "kryums", + "a", + "i", + "ontons", + "antoneis" + ], + "SOC_ECO_CLASS": [ + "drupeit", + "krai\u0161kys", + "kriejums" + ], + "DISEASE": [ + "navasals", + "plauki", + "ciertums", + "klikss", + "suope", + "tveikst", + "naveseleiba", + "kuos\u0113t", + "vaideiba", + "syltums" + ], + "ORG": [ + "ai", + "prounuks", + "reit" + ], + "PLANT": [ + "tresneica", + "veituls", + "bese\u0146\u0161", + "bryukline" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "unuce": "unuks", + "\u0161ei": "jis", + "jei": "\u0161ys", + "muosa": "bruo\u013cs" + }, + "other_gender_swap": { + "jei": "j\u012b", + "\u0161\u012b": "jei", + "juos": "\u0161ei", + "\u0161uos": "\u0161ei", + "j\u012b": "\u0161ei", + "\u0161ys": "\u0161\u012b", + "jis": "juos", + "\u0161ei": "juos" + }, + "en_pronoun2gender": { + "she": [ + "sakne", + "m\u0101rga", + "meitine", + "s\u012bv\u012bte" + ] + }, + "en_pronoun2pronoun": { + "he": [ + "\u0161ys", + "jis" + ], + "she": [ + "jei", + "\u0161ei" + ], + "they": [ + "\u0161\u012b", + "\u0161uos", + "j\u012b", + "juos", + "jei" + ], + "it": [ + "\u0161\u012b", + "itys", + "jis", + "itei" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/lv.json b/data_tooling/pii_processing/ontology/data/lv.json new file mode 100644 index 0000000..097f971 --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/lv.json @@ -0,0 +1,1188 @@ +{ + "LOCATION": [ + "al_jazeera", + "zieme\u013cj\u016bra", + "austrummidlenda", + "laman\u0161s", + "civilin\u017eenierija", + "hornas_rags", + "univers\u0101lveikals", + "saksija_anhalte", + "lielie_greizie_rati", + "dienvidsala", + "lielpils\u0113ta", + "steitenailenda", + "dienvidaustr\u0101lija", + "marija_magdal\u0113na", + "krivojroga", + "tanas_ezers", + "ildefransa", + "arlabunakti", + "p\u012bts_mondri\u0101ns", + "bot\u0101niskais_d\u0101rzs", + "senthelensa_kalns", + "senmart\u0113na", + "lielais_l\u0101cis", + "meteostacija", + "isikuls", + "huanhe", + "zieme\u013csala", + "portoprensa", + "jord\u0101na", + "the_rolling_stones", + "centr\u0101l\u0101_banka", + "aug\u0161ezers" + ], + "ANIMAL": [ + "borderkollijs", + "glodene", + "medusbites", + "riekstrozis", + "sermu\u013ci", + "zobenvalis", + "bissa", + "klij\u0101ns", + "dambriedis", + "daudzk\u0101jis", + "j\u016bras_c\u016bci\u0146a", + "vanags", + "sudrabkaija", + "gonokoks", + "paved\u0113js", + "pacepl\u012btis", + "zieme\u013cp\u016bce", + "platkn\u0101bis", + "dumbrc\u0101lis", + "medus\u0101psis", + "imperatorpingv\u012bns", + "sarkanr\u012bkl\u012bte", + "murk\u0161\u0137i", + "sabulis", + "krupis", + "manta", + "ebolas_v\u012brusslim\u012bba", + "krauklis", + "mikipele", + "brie\u017evabole", + "kurts", + "briedis", + "dzied\u0101t\u0101jstrazds", + "grinda", + "sprogk\u0101ji", + "zalktis", + "staltbriedis", + "nep\u0101rnad\u017ei", + "basets", + "piek\u016bni", + "slaidpirkstainis", + "garkaklis", + "tarak\u0101ns", + "taimi\u0146\u0161", + "antilopv\u0101veres", + "cekuld\u016bkuris", + "sprak\u0161\u0137i", + "susuris", + "pundurn\u012blzirgs", + "dievl\u016bdz\u0113ji", + "kaiva", + "rubenis", + "sv\u012bru_dzimta", + "baltv\u0113deris", + "kuprvalis", + "citronhaizivs", + "zvirbulis", + "manuls", + "vienplau\u0161zivjveid\u012bg\u0101s", + "garstilbis", + "caunas", + "baltvalis", + "parastais_zalktis", + "\u017eagata", + "mandar\u012bnp\u012ble", + "lapsene", + "slokas", + "dienvidlidv\u0101vere", + "varde", + "posmk\u0101ji" + ], + "DISEASE": [ + "sars", + "drudzis", + "slims", + "skarlat\u012bna", + "vaisl\u012bba", + "paral\u012bze", + "kristus_cie\u0161anas", + "klepot", + "poliomiel\u012bts", + "kont\u016bzija", + "stingumkrampji", + "kasta\u0146as", + "krampji", + "vaisl\u012bgums", + "the_bends", + "sliktums", + "kait\u0113jums", + "mokas", + "mal\u0101rija", + "n\u0101trene", + "klepus", + "katarakta", + "leikocit\u016brija", + "riests", + "caureja", + "materi\u0101lisms", + "neizdo\u0161an\u0101s", + "gimp", + "atkar\u012bba", + "pica", + "\u016bdensgalva", + "sensation", + "prog\u0113rija", + "leik\u0113mija", + "sal\u016bzt", + "anest\u0113zija", + "pinnes", + "sasirdzis", + "migl\u0101js", + "galvass\u0101pes", + "neveiksme", + "sting", + "radi\u0101cija", + "masalas", + "saind\u0113\u0161an\u0101s", + "bakas", + "blaugzna", + "mazasin\u012bba", + "noma", + "parat\u012bfs", + "datorpele", + "pievienot", + "slim\u012bba" + ], + "PUBLIC_FIGURE": [ + "ronalds_reigans", + "t_e_lorenss", + "salad\u012bns", + "bertolts_brehts", + "c", + "edmonds_halejs", + "henriks_ibsens", + "ella_ficd\u017eeralda", + "lielvez\u012brs", + "gustavs", + "frederiks_sengers", + "anna_pavlova", + "leonards_bernsteins", + "anna_boleina", + "antons_brukners", + "williams", + "indira_gandija", + "elizabete", + "fransisko_pisarro", + "\u010de_gevara", + "alfr\u0113ds", + "osmans_i", + "e", + "ivans_pavlovs", + "henrijs_kisind\u017eers", + "indri\u0137is", + "sandro_boti\u010delli", + "gregors", + "pauels", + "leonards_eilers", + "akira_kurosava", + "donalds_bartelms", + "y", + "mihails_bari\u0161\u0146ikovs", + "lekorbizj\u0113", + "nelsons_mandela", + "pauls_tillihs", + "karavad\u017eo", + "f", + "alberts_ein\u0161teins", + "gregors_mendelis", + "valent\u012bna_tere\u0161kova", + "marija_antuanete", + "gustavs_m\u0101lers", + "alberts_seibins", + "amerigo_vespu\u010di", + "a", + "leonards", + "fransiss_pulenks", + "glenns_millers", + "henrijs_millers", + "roberts_adams", + "arnolds", + "lorenss_olivj\u0113", + "johanness_keplers", + "emiljano_sapata", + "kristofors_kolumbs", + "o_henrijs", + "marks_tvens", + "katr\u012bna", + "emilija_dikinsone", + "dalailama", + "marija_kallasa", + "d_h_lorenss", + "lilija", + "gerhards_merkators", + "arturs_salivens", + "sentluisa", + "ingr\u012bda_bergmane", + "franss_halss", + "one", + "i", + "harijs", + "nikola_tesla", + "sentlorensa", + "perijs", + "bernardo_bertolu\u010di", + "alberts_\u0161veicers", + "konstant\u012bns", + "fritjofs_nansens", + "andrejs_saharovs", + "sv\u0113tais_p\u0113teris", + "e_t_a_hofmanis", + "1", + "anna_hetaveja", + "g", + "antons", + "r", + "als_kapone", + "sarkangalv\u012bte", + "mart\u012bns_heidegers", + "roberts", + "pacepl\u012b\u0161u_dzimta", + "lauris", + "divas", + "bei_juimins", + "bernhards_r\u012bmanis", + "sidnijs_polaks", + "putins", + "brasls", + "un_t\u0101_t\u0101l\u0101k", + "andrea_palladio", + "vasilijs_kandinskis", + "marko_polo", + "hubilajs", + "matrozis", + "hercs", + "strauss", + "kolete", + "te\u010dere", + "van_gogs", + "karls_nilsens", + "homo", + "olivers_kromvels", + "elizabete_teilore", + "li_d\u017eendao", + "henrijs", + "roberts_hainlains", + "antonio_stradiv\u0101ri", + "monteskj\u0113", + "el_greko", + "hru\u0161\u010dovs", + "p\u0113teris_i", + "lielais_susuris", + "mart\u012bns_b\u016bbers", + "arnolds_p\u0101lmers", + "felipe_ii", + "titam", + "jozefs_\u0161umpeters", + "henrijs_hadsons", + "t" + ], + "PLANT": [ + "baltais_\u0101mulis", + "pela\u0161\u0137is", + "bebruk\u0101rkli\u0146\u0161", + "floridas_purvciprese", + "rubija", + "the_joshua_tree", + "burk\u0101ns", + "\u016bdensaugs", + "gugatnis", + "alts", + "kadi\u0137oga", + "maijpu\u0137\u012bte", + "galvi\u0146k\u0101posti", + "saulespu\u0137e", + "parast\u0101_k\u013cava", + "melnalksnis", + "manioka", + "priede", + "parast\u0101_liepa", + "kalme", + "melnsakne", + "\u016bdensce\u013cmal\u012bte", + "kazene", + "ziedk\u0101posts", + "kampars", + "kakaokoks", + "malp\u012bgiju", + "lapegles", + "gobas", + "kardamons", + "ezerrieksts", + "dadzis", + "date\u013cpalma", + "saulgrieze", + "baltalksnis", + "mazpuren\u012bte", + "neaizmirstule", + "parastais_devi\u0146v\u012brusp\u0113ks", + "priedes", + "beladonna", + "aprikozes" + ], + "ORG": [ + "karasp\u0113ks", + "slepenpolicija", + "krivojroga", + "bolivuda", + "anglik\u0101\u0146u_bazn\u012bca", + "dienvidpols", + "sv\u0113t\u0101_sofija", + "vinnijs_p\u016bks", + "gaisa_sp\u0113ki", + "serde", + "nasa", + "novisada", + "aug\u0161ezers", + "fle\u0161mobs", + "br\u012bvm\u016brniec\u012bba", + "schutzstaffel", + "the_who", + "un", + "radiogalaktika", + "angkorvata", + "gomi\u0146dan", + "akad\u0113mija", + "dot", + "kareivji", + "centr\u0101leiropa", + "milit\u0101rs", + "sv\u0113t\u0101s_hel\u0113nas_sala", + "kato\u013cu_bazn\u012bca", + "komandekonomika", + "zieme\u013ckipra", + "ugunsdz\u0113s\u0113ji", + "sabiedriskais_transports", + "v\u0101cijas_imp\u0113rija", + "asv_demokr\u0101tisk\u0101_partija", + "tvinp\u012bka", + "huanhe", + "sastr\u0113gums", + "pasta_noda\u013ca", + "vudsu_ezers", + "gestapo", + "pils\u0113tvalsts", + "santome", + "mormons", + "jauns_m\u0113ness", + "mana_trak\u0101_\u0123imene", + "ko\u0161\u013c\u0101jam\u0101_gumija", + "andromedas_galaktika", + "turkl\u0101t", + "sentl\u016bsija", + "al_jazeera", + "po", + "mossad", + "domn\u012bca", + "liel\u0101_porta", + "asv_armija", + "sturmabteilung", + "armija", + "benilukss", + "savienot\u0101s_valstis", + "kaboverde", + "nato", + "feder\u0101lais_izmekl\u0113\u0161anas_birojs", + "mazmazd\u0113ls", + "sv\u0113tais_j\u0101zeps", + "by_the_way", + "pamatskola", + "romie\u0161u_ties\u012bbas", + "eiropola", + "sanfrancisko", + "baltais_nams", + "romas_kato\u013cu_bazn\u012bca", + "vald\u012bba", + "str\u0101dnieku_\u0161\u0137ira", + "eu", + "asv_republik\u0101nisk\u0101_partija", + "r\u0101tsnams", + "ivanofrankivska", + "komercija", + "lauksaimniec\u012bba", + "rietummidlenda", + "papildus" + ], + "PRODUCT": [ + "lielbrit\u0101nija", + "no_dieva_\u017e\u0113last\u012bbas", + "strupce\u013c\u0161", + "al_jazeera", + "ziemassv\u0113tku_vec\u012btis", + "sv\u0113ta_marija", + "krist\u0101mtrauks", + "jaunz\u0113lande", + "j\u016brasc\u016bci\u0146a", + "kuka_salas", + "burinieks", + "labr\u012bt", + "pitk\u0113rna", + "\u016bdensdzirnavas", + "piedodiet", + "ziemassv\u0113tku_egle", + "malduguns", + "mario_andreti" + ], + "JOB": [ + "skolot\u0101js", + "kartogr\u0101fs", + "priek\u0161s\u0113d\u0113t\u0101js", + "lieltirgot\u0101js", + "kurjers", + "kolekcion\u0101rs", + "brokeris", + "pulkvedis", + "lakijs", + "vergs", + "maiznieks", + "lauksaimnieks", + "karalis", + "ties\u012bbsargs", + "rab\u012bns", + "the_police", + "karot\u0101js", + "pavadonis", + "sludin\u0101t\u0101js", + "neatkar\u012bgs", + "japijs", + "karav\u012brs", + "regente", + "kaligr\u0101fe", + "stiklinieks", + "krevele", + "insults", + "kaligr\u0101fs", + "jurists", + "skolot\u0101ja", + "line\u0101ls", + "z\u012bd\u012bt\u0101ja", + "leitnants", + "the_guardian", + "verdzene", + "visp\u0101r\u0113js", + "slauc\u0113ja", + "kolekcion\u0101re", + "tirgot\u0101js", + "rati", + "plak\u0101ts", + "glaud\u012bt", + "kartogr\u0101fe", + "mait\u0113d\u0101ji", + "pulkve\u017eleitnants", + "ratnieks", + "aktieris", + "usher", + "messenger", + "sargs", + "autors", + "pastnieks", + "drag\u016bns", + "dejot\u0101js", + "pastniece", + "kareivis", + "dejot\u0101ja", + "kariete" + ], + "GPE": [ + "veiksmi", + "jaun\u0101_der\u012bba", + "cilv\u0113kties\u012bbas", + "sentlorensa", + "jaunsp\u0101nija", + "centr\u0101lamerika", + "sentluisa", + "grankan\u0101rija", + "sv\u0113tais_nikolajs", + "sintm\u0101rtena", + "sv\u0113tais_juris", + "sarkan\u0101_j\u016bra", + "santodomingo", + "dienvidamerika", + "sarkan\u0101_krusta", + "santome", + "sv\u0113tais_gars", + "andalusa", + "sv\u0113t\u0101_sofija", + "fran\u0161kont\u0113", + "sv\u0113tais_jur\u0123is" + ], + "LANGUAGE": [ + "katalonis", + "islandie\u0161u", + "ebrejisks", + "katal\u0101niete", + "kazahiete", + "kongo", + "somisks", + "anglisks", + "beng\u0101\u013cu", + "persie\u0161u", + "krievs", + "pali", + "horv\u0101tisks", + "grie\u0137iete", + "baltkrievu", + "kazahs", + "taizemie\u0161u", + "grie\u0137is", + "komie\u0161u", + "hindi", + "baltkrievisks", + "esperanto", + "katal\u0101nis", + "fricis", + "katalonietis", + "kataloniete", + "svahili", + "krieviete", + "portug\u0101lisks", + "taizemisks", + "polisks", + "ido", + "horv\u0101tu", + "fran\u010du_valoda", + "portug\u0101\u013cu", + "malaj\u0101lama", + "tonga" + ], + "RELIGION_MEMBER": [ + "kristietis", + "ebrejs", + "mormons", + "ebrejiete", + "jehovas_liecinieks", + "apustulis" + ], + "FOOD": [ + "sarkanv\u012bns", + "baltmaize", + "portv\u012bns", + "asinsdesa", + "sausais_piens", + "baltv\u012bns", + "sald\u0113jums", + "brokastis", + "smaganas", + "kafija", + "karstv\u012bns", + "ol\u012bve\u013c\u013ca" + ], + "BIO_CHEM_ENTITY": [ + "laur\u012bnsk\u0101be", + "itakonsk\u0101be", + "c_reakt\u012bvais_olbaltums", + "salicilsk\u0101be", + "piensk\u0101be", + "fenileti\u0137sk\u0101be", + "dietil\u0113teris", + "cervonsk\u0101be", + "enantsk\u0101be", + "kapronsk\u0101be", + "d_vitam\u012bns", + "glioksilsk\u0101be", + "citronsk\u0101be", + "kapr\u012bnsk\u0101be" + ], + "SOC_ECO_CLASS": [ + "lauksaimniec\u012bba", + "proletari\u0101ts", + "samuraji", + "melnais_tirgus", + "samurajs" + ], + "RACE": [ + "ebreju", + "afrik\u0101nis", + "afrik\u0101\u0146u", + "fran\u010di", + "franc\u016bzis", + "ang\u013ci", + "jap\u0101\u0146i", + "amerik\u0101\u0146i", + "franc\u016bziete" + ], + "TITLE": [ + "sers" + ], + "QUANTITY": [ + "transcendents_skaitlis", + "junga_modulis", + "anderss_celsijs", + "tonis", + "g", + "masas_skaitlis", + "pirmskaitlis" + ], + "POLITICAL_PARTY": [ + "politiska_partija", + "nsdap", + "leiboristu_partija", + "soci\u0101ldemokr\u0101tisk\u0101_partija", + "politisk\u0101_partija", + "gomi\u0146dan", + "konservat\u012bv\u0101_partija" + ], + "PERSON_PRONOUN": [ + "i" + ], + "FAC": [ + "pamatskola", + "atomelektrostacija", + "baseins", + "nolans_raiens", + "hantimansijska", + "\u010detri_gadalaiki", + "pansion\u0101ts", + "policijas_iecirknis", + "peldbaseins", + "ju\u017enosaha\u013cinska", + "arnolds_\u0161\u0113nbergs", + "s\u0101kumskola", + "sentl\u016bsija" + ], + "RELIGION": [ + "daoisms", + "prezbiteri\u0101nisms", + "maniheisms", + "sintoisms" + ], + "EVENT": [ + "pamosties", + "atmosties" + ], + "ANAT": [ + "miokards", + "aug\u0161delms" + ], + "DATE": [ + "viduslaiki", + "liel\u0101_piektdiena" + ], + "UNION": [ + "arodbiedr\u012bba" + ], + "GENDER": [ + "vecene", + "puisis", + "sieviete" + ], + "PERSON": [ + "es_ar\u012b", + "c_vitam\u012bns" + ], + "LAW": [ + "civilties\u012bbas", + "krimin\u0101lties\u012bbas" + ], + "MEDICAL_THERAPY": [ + "asinsspiediens" + ], + "ner_regexes": [ + [ + "PERSON", + "\\D+ \\D+|\\D+ \\D+|\\D+, \\D+", + false, + [] + ] + ], + "FIRST_NAME": [ + "voldem\u0101rs", + "ieva", + "aivars", + "j\u0101nis", + "erna", + "margrieta", + "nikolajs", + "milda", + "k\u0101rlis", + "mikels", + "vineta", + "vilnis", + "aija", + "j\u016blijs", + "evija", + "ivo", + "laimonis", + "olga", + "m\u0101ris", + "am\u0101lija", + "indri\u0137is", + "indra", + "ziedonis", + "dainis", + "dzintars", + "andre\u0161s", + "inga", + "berta", + "elita", + "gunita", + "l\u012bna", + "j\u0113kabs", + "l\u012bga", + "jannis", + "art\u016brs", + "hanss", + "ermanis", + "andrejs", + "arnis", + "ot\u012blija", + "solvita", + "made", + "sapa", + "augusts", + "kaspars", + "lizete", + "vija", + "vilma", + "sandis", + "em\u012blija", + "ilze", + "mirdza", + "normunds", + "alise", + "j\u016ble", + "sandra", + "maija", + "zenta", + "vita", + "toms", + "\u0101dams", + "aiga", + "oto", + "annija", + "aigars", + "anna", + "arturs", + "sarm\u012bte", + "elizabete", + "osvalds", + "ir\u0113na", + "ain\u0101rs", + "\u017eanis", + "mi\u0137elis", + "janis", + "gun\u0101rs", + "doroteja", + "leont\u012bne", + "eva", + "kri\u0161j\u0101nis", + "sintija", + "katr\u012bna", + "m\u0101r\u012bte", + "kri\u0161s", + "valda", + "henriks", + "laura", + "jana", + "anita", + "ma\u017ea", + "p\u0113teris", + "rasma", + "rud\u012bte", + "al\u012bda", + "anete", + "ilga", + "arnolds", + "veneranda", + "biruta", + "karina", + "agnese", + "ansis", + "elvis", + "arv\u012bds", + "aleksandrs", + "ruta", + "d\u0101rta", + "alv\u012bne", + "igors", + "mihels", + "pauls", + "zigr\u012bda", + "visvaldis", + "kristaps", + "valdis", + "lilija", + "\u0101dolfs", + "alfr\u0113ds", + "lauris", + "elm\u0101rs", + "roberts", + "brencis", + "leons", + "lav\u012bze", + "krista", + "andris", + "monika", + "valija", + "zelma", + "viesturs", + "linda", + "\u0123ederts", + "silvija", + "ina", + "vilis", + "b\u0113rends", + "ilona", + "reg\u012bna", + "karl\u012bna", + "eda", + "modris", + "dzidra", + "baba", + "samanta", + "di\u0101na", + "alberts", + "j\u0101zeps", + "daniels", + "viktors", + "liene", + "grieta", + "nat\u0101lija", + "mareks", + "rolands", + "daiga", + "ivars", + "evita", + "agris", + "\u0101rija", + "gr\u0113ta", + "raimonds", + "ri\u010dards", + "anto\u0146ina", + "zane", + "tr\u012bne", + "niks", + "j\u016blija", + "rita", + "antra", + "tenis", + "iveta", + "\u0113rika", + "ineta", + "uldis", + "santa", + "skaidr\u012bte", + "margareta", + "konradus", + "guntis", + "\u0123irts", + "bro\u0146islava", + "edgars", + "marta", + "sta\u0146islavs", + "lilita", + "raivis", + "edv\u012bns", + "vladislavs", + "tekla", + "jezups", + "teodors", + "rute", + "\u0113valds", + "egils", + "lidija", + "minna", + "\u0113riks", + "l\u012bza", + "laila", + "elv\u012bra", + "emma", + "m\u0101rti\u0146\u0161", + "austra", + "jakobs", + "katar\u012bna", + "irma", + "l\u016bcija", + "b\u0113rtulis", + "genovefa", + "macs", + "gunta", + "inguna", + "janina", + "vi\u013cums", + "elza", + "aina", + "veronika", + "valent\u012bna", + "mat\u012bss", + "reinis", + "hermanis", + "mare", + "edmunds", + "juris", + "o\u013c\u0123erts", + "ingr\u012bda", + "aldis", + "el\u012bna", + "gaida", + "inese", + "ernests", + "madara", + "ed\u012bte", + "vera", + "l\u012bba", + "alma", + "guntars", + "ausma", + "dzintra", + "dace", + "antons", + "gatis", + "kristers", + "em\u012bls", + "ilm\u0101rs", + "harijs", + "kristi\u0101na", + "fricis", + "paula", + "velta", + "j\u0113kaubs", + "armands", + "sanita", + "r\u016bdolfs", + "m\u0101ra", + "oskars", + "j\u016bla", + "ligita", + "d\u0101vis", + "johans", + "daina", + "baiba", + "paul\u012bna", + "imants", + "in\u0101ra", + "inta", + "rihards", + "marija", + "hel\u0113na", + "artis", + "krists", + "eduards" + ], + "LAST_NAME": [ + "liepa", + "auni\u0146\u0161", + "zelti\u0146\u0161", + "zvirbulis", + "z\u0101l\u012btis", + "balodis", + "kr\u0113sli\u0146\u0161", + "luksti\u0146\u0161", + "b\u0113rzi\u0146\u0161", + "ka\u0146eps", + "\u0101bele", + "vanags", + "balti\u0146\u0161", + "\u0101bols", + "spro\u0123is", + "zari\u0146\u0161", + "lapsa", + "kr\u016bze", + "avoti\u0146\u0161", + "saul\u012btis", + "krasti\u0146\u0161", + "rieksti\u0146\u0161", + "strazdi\u0146\u0161", + "egl\u012btis", + "kal\u0113js", + "roz\u012btis", + "pried\u012btis", + "lagzdi\u0146\u0161", + "krievs", + "polis", + "caune", + "k\u0101rkli\u0146\u0161", + "turi\u0146\u0161", + "kr\u016bmi\u0146\u0161", + "vilci\u0146\u0161", + "ziemelis", + "zirnis", + "puri\u0146\u0161", + "sili\u0146\u0161", + "purmals", + "zvaigzne", + "briedis", + "priede", + "jaunzems", + "v\u012btols", + "rubenis", + "alksnis", + "v\u012btoli\u0146\u0161", + "celmi\u0146\u0161", + "liepi\u0146\u0161", + "rudz\u012btis", + "l\u012bcis", + "skuja", + "c\u012brulis", + "v\u012bksna", + "dzenis", + "vilks", + "roze", + "za\u0137is", + "\u0101boli\u0146\u0161", + "krievi\u0146\u0161", + "p\u0113rkons", + "aps\u012btis", + "birznieks", + "d\u016bmi\u0146\u0161", + "paegle", + "kundzi\u0146\u0161", + "apinis", + "bite", + "skuji\u0146\u0161", + "l\u016bsis", + "celms", + "k\u013cavi\u0146\u0161", + "kauli\u0146\u0161", + "l\u0101cis", + "kalni\u0146\u0161", + "podnieks", + "auzi\u0146\u0161" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "baronese": "barons", + "br\u012bvkundze": "br\u012bvkungs", + "hija": "d\u0113ls", + "meita": "d\u0113ls", + "hercogiene": "hercogs", + "\u0137eizariene": "\u0137eizars", + "imperatore": "\u0137eizars", + "sievie\u0161u_dzimtes": "v\u012brie\u0161u", + "telpa": "gvido", + "meitene": "gvido", + "sku\u0137is": "gvido", + "mei\u010da": "gvido", + "sku\u0137e": "gvido", + "d\u0113lameita": "d\u0113lad\u0113ls", + "mazmeita": "mazd\u0113ls", + "vi\u0146as": "vi\u0146u", + "varone": "varonis", + "vi\u0146\u0113jais": "vi\u0146u", + "vi\u0146\u0113js": "vi\u0146u", + "cik": "sers", + "netr\u0101p\u012bt": "sers", + "jaunkundze": "sers", + "sakne": "sers", + "m\u0101te": "t\u0113tis", + "m\u016b\u0137ene": "m\u016bks", + "priesteriene": "priesteris", + "princese": "prinss", + "karaliene": "indra", + "kv\u012bnsa": "pirm\u0101_\u0137\u0113ni\u0146u", + "vi\u0146a": "vi\u0146\u0161", + "hona": "vi\u0146\u0161", + "m\u0101sa": "br\u0101lis", + "pameita": "aud\u017eu_d\u0113ls", + "pam\u0101te": "pat\u0113vs", + "viesm\u012ble": "viesm\u012blis", + "oficiante": "viesm\u012ble", + "atraitne": "atraitnis", + "dz\u012bvesbiedre": "v\u012brs", + "sieva": "dz\u012bvesbiedrs", + "dz\u012bvesbiedrene": "pats", + "ragana": "zintnieks", + "sieviete": "v\u012brietis", + "puisis": "sku\u0137is", + "z\u0113ns": "meitene", + "puika": "mei\u010da" + }, + "other_gender_swap": { + "one": "hona", + "k\u0101": "vi\u0146as", + "vi\u0146u": "vi\u0146\u0113js", + "vi\u0146\u0113js": "vi\u0146u", + "vi\u0146as": "vi\u0146\u0113js", + "\u0161\u012b": "vi\u0146a", + "vi\u0146i": "hona", + "oms": "hona", + "vi\u0146\u0161": "one", + "vi\u0146a": "oms", + "hona": "vi\u0146as", + "vi\u0146\u0113jais": "vi\u0146u" + }, + "en_pronoun2gender": { + "they": [ + "homoseksu\u0101ls" + ], + "he": [ + "z\u0113ns", + "v\u012brietis", + "gvido", + "v\u012brie\u0161u_dzimuma", + "v\u012brie\u0161u", + "puisis", + "mazais_z\u0113ns", + "runcis", + "puika" + ], + "she": [ + "meitene", + "netr\u0101p\u012bt", + "mei\u010da", + "sku\u0137e", + "sieviete", + "sievie\u0161u_dzimtes", + "telpa", + "sakne", + "sku\u0137is", + "cik", + "jaunkundze" + ] + }, + "en_pronoun2pronoun": { + "he": [ + "vi\u0146a", + "vi\u0146\u0161" + ], + "she": [ + "vi\u0146\u0113js", + "hona", + "vi\u0146a", + "vi\u0146\u0113jais", + "vi\u0146as" + ], + "they": [ + "one", + "k\u0101", + "\u0161\u012b", + "vi\u0146\u0113js", + "oms", + "vi\u0146i", + "vi\u0146u", + "vi\u0146as" + ], + "it": [ + "\u0161\u012b", + "\u0161is", + "\u0161\u0101s", + "\u0161\u012bs", + "\u0161ie" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/lzz.json b/data_tooling/pii_processing/ontology/data/lzz.json new file mode 100644 index 0000000..bc038b4 --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/lzz.json @@ -0,0 +1,24 @@ +{ + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "\u10d3\u10d8\u10d3\u10d0": "\u10db\u10e3\u10db\u10e3\u10da\u10d8" + }, + "other_gender_swap": {}, + "en_pronoun2gender": { + "he": [ + "\u10d1\u10d8\u10ed\u10d8" + ] + }, + "en_pronoun2pronoun": {}, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/mdf.json b/data_tooling/pii_processing/ontology/data/mdf.json new file mode 100644 index 0000000..3722a25 --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/mdf.json @@ -0,0 +1,29 @@ +{ + "ANIMAL": [ + "\u043a\u043e\u0440\u043e\u0436" + ], + "PLANT": [ + "\u043a\u0430\u043b\u044c" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "\u0430\u0432\u0430": "\u0430\u043b\u044f", + "\u0442\u044f\u0434\u044f": "\u0430\u043b\u044f", + "\u0430\u043a\u0430": "\u043f\u044f\u043b\u044c\u043d\u0435", + "\u0441\u0430\u0437\u043e\u0440": "\u043f\u044f\u043b\u044c\u043d\u0435" + }, + "other_gender_swap": {}, + "en_pronoun2gender": {}, + "en_pronoun2pronoun": {}, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/mg.json b/data_tooling/pii_processing/ontology/data/mg.json new file mode 100644 index 0000000..748aec7 --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/mg.json @@ -0,0 +1,498 @@ +{ + "PUBLIC_FIGURE": [ + "henry_cavendish", + "benjamin_franklin", + "martin_buber", + "akira_kurosawa", + "maria_tallchief", + "john_knox", + "giovanni_boccaccio", + "cornelius_vanderbilt", + "ben_hogan", + "leonard_bernstein", + "che_guevara", + "augustin_fresnel", + "henrik_ibsen", + "mary_shelley", + "peter_lorre", + "david_livingstone", + "john_herschel", + "andrzej_wajda", + "jan_van_eyck", + "carl_rogers", + "richard_burton", + "douglas_macarthur", + "mary_wollstonecraft", + "john_jacob_astor", + "winston_churchill", + "johannes_diderik_van_der_waals", + "ivan_pavlov", + "dmitri_shostakovich", + "paul_mccartney", + "stephen_king", + "francis_crick", + "isaac_newton", + "alfred_eisenstaedt", + "victor_hugo", + "joseph_smith", + "edwin_hubble", + "milton_friedman", + "edward_gibbon", + "george_stephenson", + "john_glenn", + "george_orwell", + "richard_wagner", + "pancho_villa", + "marie_curie", + "mary_martin", + "michael_jackson", + "carl_sandburg", + "thomas_hobbes", + "edward_weston", + "el_greco", + "samuel_beckett", + "david", + "galileo_galilei", + "jane_goodall", + "john_donne", + "robert_koch", + "joseph_goebbels", + "george_eastman", + "john_steinbeck", + "erich_mendelsohn", + "edmund_hillary", + "vincent_van_gogh", + "valentina_terechkova", + "thomas_paine", + "mary_pickford", + "karl_barth", + "yuri_gagarin", + "willem_einthoven", + "allen_iverson", + "giuseppe_verdi", + "karl_jaspers", + "konrad_adenauer", + "mark_rothko", + "gottlieb_daimler", + "frank_sinatra", + "abel_tasman", + "katharine_hepburn", + "henri_becquerel", + "henri_matisse", + "louis_pasteur", + "richard_strauss", + "leslie_howard", + "theodosius_i", + "hugo_grotius", + "john_ford", + "saladin", + "sarah_bernhardt", + "luigi_pirandello", + "t_s_eliot", + "hank_williams", + "charles_de_gaulle", + "charles_lindbergh", + "joseph_stalin", + "f", + "ludwig_wittgenstein", + "august_strindberg", + "thomas_mann", + "charles_goodyear", + "dante_alighieri", + "margot_fonteyn", + "giacomo_puccini", + "louis_braille", + "james_dean", + "roger_bannister", + "joseph_priestley", + "nicolas_poussin", + "andrea_mantegna", + "james_naismith", + "oscar_wilde", + "j_d_salinger", + "richard_trevithick", + "willard_gibbs", + "glenn_curtiss", + "laurence_olivier", + "peter_carl_goldmark", + "james_brown", + "william_hogarth", + "charles_baudelaire", + "david_ricardo", + "immanuel_kant", + "james_franck", + "le_caravage", + "giulio_natta", + "johannes_kepler", + "max_planck", + "william_blake", + "julio_iglesias", + "john_bardeen", + "carl_lewis", + "canberra", + "bramante", + "edward_jenner", + "oscar_robertson", + "cole_porter", + "jean_luc_godard", + "lars_onsager", + "margaret_mitchell", + "igor_stravinsky", + "mikhail_baryshnikov", + "montesquieu", + "niels_bohr", + "bertrand_russell", + "michael_faraday", + "john_d_rockefeller", + "anthony_burgess", + "irving_berlin", + "rudolf_diesel", + "walt_disney", + "constantin_stanislavski", + "gabriel_lippmann", + "ted_williams", + "friedrich_engels", + "jane_austen", + "charles_laughton", + "gustav_mahler", + "ed_sullivan", + "phil_collins", + "robert_redford", + "jack_dempsey", + "richard_feynman", + "wolfgang_pauli", + "theodor_mommsen", + "marcel_proust", + "thomas_more", + "elizabeth_taylor", + "william_golding", + "john_milton", + "ethel_merman", + "indira_gandhi", + "george_gershwin", + "frank_whittle", + "alfred_nobel", + "jesse_owens", + "marco_polo", + "allen_ginsberg", + "fred_zinnemann", + "daniel_bernoulli", + "guillaume_apollinaire", + "henri_bergson", + "pierre_corneille", + "hans_christian_andersen", + "peter_cooper", + "cary_grant", + "glenn_miller", + "pablo_picasso", + "marian_anderson", + "osman_i", + "otto_hahn", + "christian_huygens", + "hector_berlioz", + "claudio_monteverdi", + "adam_smith", + "william_james", + "jean_harlow", + "henry_miller", + "karl_marx", + "friedrich_nietzsche", + "i", + "john_wesley", + "sandro_botticelli", + "nikola_tesla", + "al_capone", + "charles_barkley", + "billy_graham", + "robert_schumann", + "le_corbusier", + "john_locke", + "joseph_marie_jacquard", + "henry_james", + "perry", + "helen_keller", + "ingrid_bergman", + "jean_piaget", + "william_congreve", + "henri_rousseau", + "paul_v\u00e9ron\u00e8se", + "h_g_wells", + "walt_whitman", + "william_wyler", + "ludwig_boltzmann", + "benjamin_thompson", + "adolf_hitler", + "fritz_haber", + "peter_behrens", + "joseph_haydn", + "george_boole", + "edvard_grieg", + "robert_boyle", + "rosa_parks", + "norman_jewison", + "samuel_goldwyn", + "ernest_walton", + "jim_thorpe", + "andre\u00ef_sakharov", + "don_budge", + "bill_russell", + "nicolas_copernic", + "g", + "arthur_schopenhauer", + "james_cagney", + "henri_pitot", + "martin_heidegger", + "hans_eysenck", + "arnold_schoenberg", + "george_lucas", + "andrew_jackson", + "louis_armstrong", + "steven_spielberg", + "st_louis_missouri", + "d_w_griffith", + "robert_fulton", + "giuseppe_garibaldi", + "alexandre_dumas", + "tamara_karsavina", + "bobby_fischer", + "johannes_gutenberg", + "thomas_malthus", + "william_faulkner", + "amerigo_vespucci", + "girolamo_savonarola", + "emma_goldman", + "robert_hooke", + "o_henry", + "karl_popper", + "peter_sellers", + "marcus_aurelius", + "peter_o'toole", + "joseph_conrad", + "william_shockley", + "jules_verne", + "paul_newman", + "fyodor_dostoyevsky", + "jackson_pollock", + "john_lennon", + "andrea_palladio", + "bob_woodward", + "charlie_chaplin", + "william_of_ockham", + "christophe_colomb", + "hugo_junkers", + "alice_walker", + "miles_davis", + "george_marshall", + "stanley_kubrick", + "john_huston", + "peter_the_great", + "james_watt", + "ronald_reagan", + "helmut_schmidt", + "jenny_lind", + "david_hilbert", + "oliver_cromwell", + "vladimir_poutine", + "martin_luther_king", + "james_hargreaves", + "frank_capra", + "william_wordsworth", + "woodrow_wilson", + "richard_rodgers", + "georges_de_lydda", + "john_dryden", + "ernest_hemingway", + "george_westinghouse", + "arthur_miller", + "nelson_mandela", + "al_gore", + "hans_bethe", + "hans_geiger", + "j_p_morgan", + "richard_leakey", + "alfred_korzybski", + "charles_dickens", + "jacques_offenbach", + "george_stevens", + "federico_fellini", + "willy_brandt", + "francisco_pizarro", + "francisco_franco", + "jackie_robinson", + "bernardo_bertolucci", + "andrew_carnegie", + "franz_schubert", + "johnny_cash", + "alfred_kastler", + "mick_jagger", + "william_harvey", + "walter_scott", + "vladimir_lenin", + "kahlil_gibran", + "jonathan_swift", + "walter_gropius", + "albert_einstein", + "robert_joffrey", + "thomas_edison", + "chiang_kai_shek", + "raymond_chandler", + "wilhelm_ostwald" + ], + "PLANT": [ + "pesombazaha", + "salady", + "tanamasoandro", + "ravintsara", + "iraka", + "karaoty", + "mamankona", + "karoty" + ], + "FAC": [ + "fiangonana_katolika", + "arnold_schoenberg", + "peter_the_great", + "titus_livius", + "eglizy_katolika_apostolika_romana", + "empira_otomana" + ], + "PRODUCT": [ + "justin_bieber", + "fyodor_dostoyevsky", + "empira_romana", + "ferdinand_magellan", + "testamenta_vaovao", + "mario_andretti" + ], + "FOOD": [ + "tanimaty" + ], + "POLITICAL_PARTY": [ + "antoko_politika" + ], + "PERSON": [ + "al_gore", + "h_g_wells", + "william_playfair", + "edward_osborne_wilson", + "igor_sikorsky", + "seleucus_i_nicator" + ], + "ANIMAL": [ + "vorondolo", + "sabakaka", + "kalabe", + "crow", + "goaika", + "bibindandy", + "vintsy", + "sahona", + "vorombozaka" + ], + "DISEASE": [ + "angatra", + "solavady", + "korontana", + "fitohanana", + "angadrano" + ], + "PERSON_PRONOUN": [ + "i" + ], + "SOC_ECO_CLASS": [ + "fiarahamonina", + "tsena_maizina" + ], + "ORG": [ + "san_francisco", + "masina_lucie", + "eglizy_katolika", + "tafika", + "fanabeazana", + "aleksandra_lehibe", + "fitsaboana", + "rabindranath_tagore", + "gestapo", + "ferdinand_magellan", + "los_angeles", + "sa", + "antoko_politika", + "s\u00e3o_tom\u00e9" + ], + "RACE": [ + "botsatsaka" + ], + "LOCATION": [ + "piet_mondrian", + "ranomasina_mainty", + "sri_lanka", + "the_rolling_stones", + "etazonia", + "christophe_colomb", + "louis_joseph_gay_lussac" + ], + "JOB": [ + "le_docteur", + "dokotera", + "usher" + ], + "RELIGION_MEMBER": [ + "miozolmana", + "anadahy" + ], + "DATE": [ + "afakampitso" + ], + "GPE": [ + "s\u00e3o_tom\u00e9", + "kianja", + "dar_es_salam", + "nicolas_de_myre", + "ranomasina_mena" + ], + "TITLE": [ + "ramatoa" + ], + "QUANTITY": [ + "g" + ], + "LANGUAGE": [ + "soedoa", + "cree", + "malagasy" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "reny": "voa", + "anabavy": "anadahy", + "andefimandry": "ibaban_tsaiky", + "tokantrano": "lahy" + }, + "other_gender_swap": { + "\u3078": "ony" + }, + "en_pronoun2gender": { + "she": [ + "barera" + ] + }, + "en_pronoun2pronoun": { + "he": [ + "\u3078" + ], + "they": [ + "ony" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/mi.json b/data_tooling/pii_processing/ontology/data/mi.json new file mode 100644 index 0000000..831c915 --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/mi.json @@ -0,0 +1,453 @@ +{ + "DISEASE": [ + "waikura", + "kiritona", + "mamae", + "ki", + "haramonera", + "hikahikanga", + "momonatanga", + "tahumaero", + "mahaki", + "kaikoiwi", + "warowaro", + "haurakiraki", + "hakoko", + "kawekawenga", + "paipairuaki", + "marupo", + "k\u014drangaranga", + "tokopuhake", + "mania", + "tauhekenga", + "kutiwera", + "urut\u0101", + "wairere", + "turiwaitaitai", + "haurehu", + "korera", + "kikikiki", + "kaitoroh\u012btanga", + "kaikaru", + "huaketo", + "kautona", + "kukunetanga", + "para", + "tongako", + "takewhenua", + "kinawhea", + "kaurapa", + "kunawhea", + "raraku", + "maiao", + "hinamokimoki", + "raur\u0113kau", + "pohopiri", + "kaihanu", + "pukoko", + "kuiki", + "rewharewha", + "mamamama", + "koute", + "rarapi", + "pohongawh\u0101", + "poutukitanga", + "tarutaruhea", + "moe_takarerewa", + "m\u0101ngiongio", + "parerori", + "koeketanga", + "kiritoi", + "mumutu", + "rapirapi", + "takereh\u0101ia", + "koroputaputa", + "whaturama", + "kotiuru", + "kautoroh\u012btanga", + "matahuatanga", + "kauanu", + "huang\u014d", + "mate_moana", + "wharatanga", + "h\u014dripiripi", + "paraiti", + "moremore", + "kaik\u014diwi", + "katirehe", + "karawaka", + "korokiwa", + "hokomirimiri", + "whitinga", + "kaimatatanga", + "pukuwhenewhene", + "ronanga", + "taukini", + "korou", + "kuru", + "mariao", + "papahewa", + "maiorohea", + "takoki", + "ngaupuku", + "taratarawai", + "kaiwhakat\u016b", + "kokohu", + "korohiko" + ], + "PLANT": [ + "whangewhange", + "pine", + "natahama", + "raupeti", + "hengahenga", + "aonan\u012b", + "manarini", + "wirou", + "puatororaro", + "parakipere", + "erema", + "aute", + "rewarewa", + "horopito", + "manitareki", + "karepar\u0101oa", + "paina", + "ringatoi", + "remuroa", + "taraonga", + "hangehange", + "horera", + "hakeka" + ], + "ORG": [ + "whakangaio", + "mautohetanga", + "p\u014dhutuhutu", + "oni", + "ai", + "kini_ekuatoria", + "taka_puoro", + "ko_taku_ingoa", + "karap\u012bpiti", + "wai_m\u0101ori", + "te_mea_ai", + "te_k\u016brae_matomato", + "haukaiwahine", + "ko_ahau", + "pia_ngaungau", + "tauhokohoko" + ], + "JOB": [ + "minita", + "pirihimana", + "te_rua", + "t\u0101maramara", + "papaunguungu", + "ahorangi", + "poumatua", + "wh\u0101rangi", + "t\u016bmataiti", + "t\u0101kuta", + "kuruwhengi", + "para", + "hokomirimiri", + "whakatoke", + "amapaea", + "moremore", + "kaing\u0101rahu", + "kaiomaoma", + "takahoa", + "kaupoai", + "mate", + "kaumoana", + "mea_whakatangi", + "pirikitia", + "karere", + "poutoko", + "kauhoe", + "perehitini", + "matawh\u0101nui", + "manukura", + "kurutangi", + "kiripaepae", + "haihana", + "menetia", + "takawaenga" + ], + "FOOD": [ + "wai_r\u0113mana", + "kohia", + "tinipia", + "akakaik\u016b", + "kanokawhe", + "hamapaka", + "purini_huar\u0101kau", + "purini", + "parakuihi" + ], + "LOCATION": [ + "te_moana_nui_a_kiwa", + "te_k\u016brae_matomato", + "te_waipounamu", + "tapepetanga", + "tautoru", + "e_pai_ana", + "hana_k\u014dk\u014d", + "te_ika_a_m\u0101ui", + "me_kore", + "te_mang\u014droa", + "tau\u0101_rangi", + "te_hononga_o_amerika", + "te_ikaroa", + "meri_makarini", + "te_taki_o_autahi" + ], + "PUBLIC_FIGURE": [ + "kauranga", + "taituha", + "kiripeta", + "kerekori", + "a", + "k\u0101napera", + "one", + "i", + "kataraina", + "riria", + "meri_makarini" + ], + "SOC_ECO_CLASS": [ + "tokoitiiti", + "tokoiti", + "whakarangatiratanga", + "wahinetanga", + "porihanga", + "te_aitanga_a_tiki", + "k\u014dtahitahi" + ], + "PRODUCT": [ + "piharoa", + "kawenata_hou", + "mea_whakatangitangi" + ], + "GENDER": [ + "titupu", + "taitama", + "kouwha", + "purengi", + "taitam\u0101hine" + ], + "ANIMAL": [ + "kewa", + "takahikare", + "kutupapa", + "kokoroihe", + "paikea", + "kahuku", + "heroni", + "maroro", + "peketua", + "p\u0101titotito", + "hinamoki", + "karoro", + "pepeketua", + "whakahao", + "kirera", + "makipai", + "mane", + "k\u014dkako" + ], + "DATE": [ + "koroheketanga", + "te_ihu_o_hineraumati", + "te_ihu_o_hinetakurua", + "tauinew\u0101" + ], + "GPE": [ + "te_tai_rei" + ], + "PERSON_PRONOUN": [ + "i", + "me", + "keringa", + "koutou" + ], + "LANGUAGE": [ + "ingarihi", + "p\u0101niora", + "kariki", + "komi" + ], + "POLITICAL_PARTY": [ + "mautohetanga", + "\u0101tetenga", + "r\u014dp\u016b_t\u014drangap\u016b" + ], + "QUANTITY": [ + "kotiri", + "matirua", + "tone", + "heringi", + "ahutoru" + ], + "PERSON": [ + "te_rangi" + ], + "RELIGION_MEMBER": [ + "perehipitiriana", + "mihinare", + "porotehana" + ], + "FAC": [ + "mataihi", + "wharehokohoko", + "terenga" + ], + "LAW": [ + "k\u014dti_mana_nui" + ], + "ANAT": [ + "kikopuku" + ], + "RACE": [ + "mangumangu" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "tutahe": "tiuka", + "tamahine": "purengi", + "uwha": "t\u0101ne", + "kouwha": "t\u0101ne", + "wahine": "t\u0101ne", + "uha": "t\u0101ne", + "k\u014dhine": "purengi", + "hine": "purengi", + "taitam\u0101hine": "purengi", + "k\u014dtiro": "purengi", + "k\u014dhaia": "purengi", + "t\u014dna": "k\u0101na", + "\u0101na": "t\u0101na", + "k\u0101na": "\u014dna", + "t\u0101na": "\u0101na", + "\u014dna": "k\u0101na", + "pirinihi": "piriniha", + "kuini": "kingi", + "tuahine": "taina", + "teina": "tung\u0101ne", + "marokore": "t\u0101ne_takakau", + "takakau": "t\u0101ne_takakau", + "maro_kau": "takakau", + "wahine_kiritapu": "t\u0101ne_takakau", + "wahine_takakau": "takakau", + "wahine_taumaro": "t\u0101ne_takakau", + "tam\u0101hine_k\u0113": "tamat\u0101ne_whakaangi", + "hine_whakaangi": "tama_whakaangi", + "tam\u0101hine_whakaangi": "tamat\u0101ne_whakaangi", + "whaea_k\u0113": "m\u0101tua_k\u0113", + "whaea_whakaangi": "m\u0101tua_k\u0113", + "takahore": "pouaru", + "pouaru": "takahore", + "hoa_rangatira": "hoa_t\u0101ne", + "hoa_wahine": "hoa_t\u0101ne", + "tamaiti_t\u0101ne": "taitam\u0101hine", + "taitama": "k\u014dhine" + }, + "other_gender_swap": { + "one": "hona", + "r\u0101ua": "hona", + "r\u0101tau": "\u014dna", + "r\u0101tou": "hona", + "t\u014d_r\u0101ua": "t\u0101na", + "\u0101_r\u0101ua": "\u0101na", + "\u014d_r\u0101ua": "t\u0101na", + "\u0101_r\u0101tau": "\u014dna", + "\u014d_r\u0101tau": "k\u0101na", + "t\u0101_r\u0101tau": "k\u0101na", + "t\u014d_r\u0101tau": "k\u0101na", + "t\u0101_r\u0101ua": "t\u0101na", + 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"lawrence_durrell", + "la_tour", + "henry_cavendish", + "matthew_arnold", + "harding", + "maria_montesorri", + "lambert", + "burbage", + "forester", + "lev_ivanov", + "st_david", + "goldmark", + "freemason", + "guggenheim", + "styron", + "mccormick", + "streisand", + "benjamin_franklin", + "maitland", + "martin_buber", + "john_bartlett", + "e_b_white", + "longfellow", + "gropius", + "karl_gjellerup", + "marsyal", + "sullivan", + "akira_kurosawa", + "frances_wright", + "mayer", + "niccolo_paganini", + "yastrzemski", + "carnegie", + "walter_whitman", + "maria_tallchief", + "curtis", + "noah_webster", + "jean_genet", + "von_rundstedt", + "tradescant", + "dinesen", + "john_knox", + "heinrich_hertz", + "kesey", + "mauriac", + "waldheim", + "jean_laffite", + "roger_williams", + "lovelace", + "henry_i", + "livingstone", + "le_duc_tho", + "giovanni_boccaccio", + "cornelius_vanderbilt", + "ekman", + "huntington", + "wren", + "rudolf_steiner", + "klinefelter", + "thomas_wolfe", + "eccles", + "cuvier", + "david_rittenhouse", + "ernesto_guevara", + "thomas_bayes", + "tindale", + "gjellerup", + "ben_hogan", + "joliot", + "ziegfeld", + "johann_bernoulli", + "max_bruch", + "mays", + "winckelmann", + "leonard_bernstein", + "c_k_ogden", + "sibelius", + "weill", + "thomas_decker", + "van_allen", + "alistair_cooke", + "che_guevara", + "roget", + "malevich", + "ederle", + "kline", + "georges_simenon", + "sir_john_frederick_william_herschel", + "james_barrie", + "c", + "botticelli", + "david_grun", + "mccauley", + "van_beethoven", + "salinger", + "karl_scheele", + "alan_seeger", + "gillespie", + "medawar", + "shostakovich", + "i_a_richards", + "wickliffe", + "john_endecott", + "thomas_hodgkin", + "wright", + "dos_passos", + "si_kerudung_merah", + "belloc", + "fleming", + "andrews", + "john_barth", + "edward_albee", + "bruegel", + "dorothy_parker", + "lipchitz", + "armstrong", + "zhukov", + "bonney", + "francis_ferdinand", + "maria_callas", + "victor_herbert", + "de_sica", + "william_walton", + "leary", + "henrik_ibsen", + "rushdie", + "abelard", + "winslow", + "prospero_lambertini", + "morgan", + "antonio_ghislieri", + "rabelais", + "emerson", + "hendrix", + "frobisher", + "laffer", + "yardbird_parker", + "william_gladstone", + "charles_liston", + "stoppard", + "de_valera", + "hughes", + "mary_shelley", + "franz_werfel", + "quine", + "marcello_malpighi", + "peter_lorre", + "pelayan_pesawat", + "karl_baedeker", + "william_tindale", + "asa_yoelson", + "mergenthaler", + "cellini", + "beckett", + "watteau", + "david_livingstone", + "eduard_buchner", + "david_smith", + "pierre_terrail", + "michelson", + "bruckner", + "john_herschel", + "henry_villard", + "gauss", + "johannes_van_der_waals", + "andrzej_wajda", + "meyerhof", + "jan_van_eyck", + "hoffman", + "peter_seamus_o\u2019toole", + "rossini", + "carl_rogers", + "macgregor", + "bernhardt", + "cortez", + "george_balanchine", + "a_e_burnside", + "bethe", + "georg_wilhelm_steller", + "richard_burton", + "gerbert", + "douglas_macarthur", + "hawkins", + "james_michener", + "mary_wollstonecraft", + "brunelleschi", + "j_edgar_hoover", + "herschel", + "curtiss", + "maria_magdalena", + "thomas_reid", + "dukas", + "john_jacob_astor", + "otto_frisch", + "anna_pavlova", + "winston_churchill", + "allen_stewart_konigsberg", + "johannes_diderik_van_der_waals", + "waite", + "giambattista_marini", + "mendelssohn", + "robert_macgregor", + "gustavus_v", + "b", + "maillol", + "conrad_aiken", + "emile_gaboriau", + "karl_landsteiner", + "josephus", + "monnet", + "ivan_pavlov", + "didrikson", + "dmitri_shostakovich", + "paul_mccartney", + "ibu_bapa_moyang", + "snead", + "sinclair", + "ulanova", + "richard_smalley", + "yamani", + "waugh", + "andrew_marvell", + "vermeer", + "k", + "trevino", + "clausewitz", + "francois_rabelais", + "macdowell", + "woodward", + "stephen_king", + "francis_crick", + "roebling", + "peter_o\u2019toole", + "john_trumbull", + "sherry", + "van_gogh", + "joseph_greenberg", + "de_sade", + "chirico", + "miles_standish", + "de_gaulle", + "isaac_newton", + "sherman", + "richard_upjohn", + "michener", + "m_j_schleiden", + "woolf", + "alfred_eisenstaedt", + "depardieu", + "victor_hugo", + "delius", + "joseph_smith", + "bartholdi", + "edwin_hubble", + "senefelder", + "saint_bridget", + "colette", + "malebranche", + "milton_friedman", + "al_hasan_ibn_al_haytham", + "inge", + "john_rock", + "amy_lowell", + "benton", + "edward_gibbon", + "schoolcraft", + "schiaparelli", + "mary_stuart", + "van_de_velde", + "james_usher", + "pincus", + "j_c_maxwell", + "jefferson_davis", + "arafat", + "bertillon", + "saint_louis", + "holbein", + "cass_gilbert", + "giosue_carducci", + "george_stephenson", + "watson", + "osborne", + "john_glenn", + "beauvoir", + "john_webster", + "wykeham", + "john_davis", + "yaakub", + "lorenz_okenfuss", + "george_burns", + "jarrell", + "bakunin", + "bartlett", + "george_harrison", + "stowe", + "erwin_schrodinger", + "peter_minuit", + "galois", + "mark_clark", + "sandor_kellner", + "sebastian_vizcaino", + "amundsen", + "george_orwell", + "ellison", + "morrison", + "woolworth", + "georg_meissner", + "aleksandr_pavlovich", + "arthur_koestler", + "hernan_cortes", + "richard_wagner", + "joseph_john_thomson", + "williams", + "stanislavsky", + "syeri", + "thornton_wilder", + "e_l_doctorow", + "der_fuhrer", + "pancho_villa", + "diaz", + "monet", + "aleksandr_borodin", + "don_kihote", + "j_j_hill", + "johns", + "john_hemminge", + "leopold_stokowski", + "higginson", + "jonson", + "rebecca_west", + "stockton", + "mary_magdalen", + "marie_curie", + "malthus", + "simenon", + "francis_galton", + "jussieu", + "john_rowlands", + "mccarthy", + "tandy", + "mary_martin", + "gordimer", + "arnold_schonberg", + "constantine", + "michael_jackson", + "george_iv", + "nicolson", + "louis_jolliet", + "carl_sandburg", + "pugin", + "alexander_i", + "taylor", + "stephenson", + "thomas_hobbes", + "goldman", + "sir_william_chambers", + "faberge", + "seleucus", + "joseph_lister", + "derain", + "the_admirable_crichton", + "edward_weston", + "meissner", + "el_greco", + "macleod", + "philip_ii_of_spain", + "waller", + "samuel_beckett", + "seaman", + "maximian", + "jacques_costeau", + "clinton", + "connolly", + "david", + "russell", + "galileo_galilei", + "skeat", + "van_eyck", + "czerny", + "ernest_bevin", + "jane_goodall", + "john_donne", + "chaim_weizmann", + "lardner", + "lorenzo_de\u2019medici", + "andrea_guarneri", + "tempat_kurungan_binatang_yang_ditahan", + "robert_koch", + "wajda", + "van_vleck", + "burbank", + "i_m_pei", + "marshall", + "todd", + "joseph_goebbels", + "george_eastman", + "john_steinbeck", + "asimov", + "epstein", + "erich_mendelsohn", + "utrillo", + "a_e_w_mason", + "catherine", + "northrop", + "petrus", + "mantegna", + "donald_glaser", + "barth", + "strickland", + "demille", + "langmuir", + "mendeleyev", + "c_northcote_parkinson", + "edmund_hillary", + "munchausen", + "brigid", + "binet", + "trevithick", + "galvani", + "corbett", + "vincent_van_gogh", + "richard_hooker", + "strasberg", + "william_hazlitt", + "gustavus_iii", + "prince_eugene_of_savoy", + "pickford", + "martina_navr\u00e1tilov\u00e1", + "marie_stopes", + "anne_boleyn", + "josef_stalin", + "john_ruskin", + "franz_lehar", + "granville_barker", + "louis_le_begue", + "robert_burns", + "john_henry", + "hans_albrecht_bethe", + "carl_anderson", + "nathaniel_bailey", + "behrens", + "steinbeck", + "visconti", + "bunche", + "john_galbraith", + "hess", + "thomas_paine", + "bari", + "ustinov", + "murrow", + "elizabeth_seaman", + "sully", + "liliuokalani", + "gielgud", + "francis_beaumont", + "hans_jurgen_eysenck", + "alhacen", + "i_f_stone", + "marini", + "justinian", + "karl_wernicke", + "bergman", + "wilkins", + "steven_weinberg", + "the_great_compromiser", + "mary_pickford", + "hans_fischer", + "emiliano_zapata", + "boulez", + "lavoisier", + "elisabet", + "cristobal_colon", + "karl_barth", + "dowland", + "yuri_gagarin", + "millais", + "calvino", + "willem_einthoven", + "johann_winckelmann", + "rockwell", + "cather", + "sikorsky", + "phil_anderson", + "thomas_willis", + "bernard_malamud", + "samuel_johnson", + "jesus", + "giovanni_battista_montini", + "allen_iverson", + "nimitz", + "wesley", + "smith", + "marie_antoinette", + "anne_hutchinson", + "louise_nevelson", + "giuseppe_verdi", + "galsworthy", + "walter_lippmann", + "edward_appleton", + "breuer", + "e", + "scheele", + "lafitte", + "karl_jaspers", + "korzybski", + "emily_bronte", + "beethoven", + "helmholtz", + "ferber", + "hideki_yukawa", + "connors", + "konrad_adenauer", + "st_george", + "grigori_potemkin", + "mencken", + "bessel", + "howe", + "vanderbilt", + "c_vann_woodward", + "donatus", + "john_l_lewis", + "bush", + "marianne_moore", + "norbert_wiener", + "st_vitus", + "john_masefield", + "horatio_nelson", + "mark_rothko", + "shepard", + "brueghel", + "maurice_chevalier", + "gottlieb_daimler", + "fourier", + "francoise_athenais_de_rochechouart", + "saint_ignatius", + "schlesinger", + "finnbogadottir", + "scriabin", + "mayakovski", + "frank_sinatra", + "isherwood", + "bowditch", + "fallopio", + "arendt", + "abel_tasman", + "katharine_hepburn", + "noguchi", + "guthrie", + "henri_becquerel", + "henri_matisse", + "alfonso_borgia", + "pahlevi", + "bertram_brockhouse", + "ginsberg", + "louis_pasteur", + "van_de_graaff", + "ponselle", + "hoffmann", + "gaboriau", + "berra", + "sherrington", + "richard_strauss", + "stephen_decatur", + "herculius", + "galbraith", + "leslie_howard", + "jean_baptiste_racine", + "mehemet_ali", + "pekilang", + "theodosius_i", + "joseph_oliver", + "hugo_grotius", + "pushkin", + "maginot", + "kissinger", + "mahalia_jackson", + "william_franklin_graham", + "kendrew", + "ben_shahn", + "mohorovicic", + "john_ford", + "stephen_foster", + "alphonse_bertillon", + "charles_ringling", + "katherine_mansfield", + "gertrude_stein", + "fallopius", + "van_der_waals", + "j_b_s_haldane", + "saladin", + "kettering", + "sarah_bernhardt", + "george_beadle", + "dostoevski", + "krasner", + "e_h_harriman", + "v", + "hayes", + "philip_marlowe", + "greene", + "gretzky", + "luigi_pirandello", + "peter_tchaikovsky", + "t_s_eliot", + "shapley", + "e_g_marshall", + "watts", + "madame_tussaud", + "karol_wojtyla", + "mallarme", + "marc_blitzstein", + "hank_williams", + "hazlitt", + "weston", + "benchley", + "mandelshtam", + "rube_goldberg", + "dorothea_lange", + "james_thurber", + "st_christopher", + "william_menninger", + "strachey", + "chaplin", + "charles_de_gaulle", + "paul_von_hindenburg", + "da_gamma", + "florio", + "y", + "henry_moore", + "perutz", + "schumann", + "holden", + "mary_mallon", + "lytton", + "ralph_bunche", + "rudolf_bultmann", + "dempsey", + "douglass", + "charles_lindbergh", + "fremont", + "clive", + "grappelli", + "jespersen", + "villon", + "emile_herzog", + "vincenzo_bellini", + "samuel_barber", + "tobias_smollett", + "joseph_stalin", + "schrodinger", + "hammarskjold", + "al_haytham", + "f", + "john_jay", + "tobey", + "ludwig_wittgenstein", + "august_strindberg", + "stalin", + "bunyan", + "thomas_mann", + "paton", + "hathaway", + "kendall", + "bin_laden", + "william_ockham", + "alla_nazimova", + "charles_goodyear", + "dante_alighieri", + "hoyle", + "wernicke", + "cunningham", + "charles", + "vesalius", + "margot_fonteyn", + "nathaniel_currier", + "david_hubel", + "peter_pan", + "james_tobin", + "john_irving", + "panofsky", + "simon_peter", + "samuel_de_champlain", + "shirer", + "paxton", + "chekhov", + "e_h_weber", + "giacomo_puccini", + "edward_fitzgerald", + "eyck", + "fridtjof_nansen", + "louis_braille", + "herbert_marcuse", + "mungo_park", + "benedict_arnold", + "wyatt", + "paul_verlaine", + "cowper", + "q", + "tappan", + "robert_johnson", + "kropotkin", + "mark_hopkins", + "traubel", + "ibu_peri", + "balfour", + "james_dean", + "robert", + "richard_lovelace", + "jacob_harmensen", + "scorsese", + "leuwenhoek", + "mason", + "marie_tussaud", + "burnett", + "roger_bannister", + "john_cash", + "theodor_schwann", + "max_beerbohm", + "tasman", + "greeley", + "alessandro_manzoni", + "joseph_priestley", + "hermann_snellen", + "robert_oppenheimer", + "hal", + "louis_joliet", + "nicolas_poussin", + "andrea_mantegna", + "qadhafi", + "adolf_windaus", + "francois_mansart", + "hayek", + "clemenceau", + "joseph_pulitzer", + "ring_lardner", + "sperry", + "george_huntington", + "charles_schulz", + "irving", + "barany", + "caruso", + "jim_corbett", + "mommsen", + "james_naismith", + "marlowe", + "malpighi", + "oscar_wilde", + "socinus", + "billie_the_kid", + "montgolfier", + "mobius", + "antoine_domino", + "philip_roth", + "maintenon", + "burroughs", + "j_d_salinger", + "ochoa", + "henry", + "lawrence", + "roy_wilkins", + "franklin", + "andre_weil", + "burung_ren", + "sorensen", + "humperdinck", + "richard_trevithick", + "lowry", + "william_bradford", + "johan_august_strindberg", + "heinrich_schliemann", + "montespan", + "liston", + "kean", + "lendl", + "bartholomeu_diaz", + "john_davys", + "carlyle", + "eli_whitney", + "nell_gwynn", + "jackson", + "glenn_curtiss", + "telemann", + "paola_caliari", + "saint_crispin", + "clark", + "pizarro", + "morley", + "merckx", + "bradstreet", + "romberg", + "a_e", + "corelli", + "jan_van_der_meer", + "chambers", + "mary_magdalene", + "john_witherspoon", + "william_falkner", + "laurence_olivier", + "victor_hess", + "hussein", + "jeffers", + "evans", + "cocteau", + "e_a_von_willebrand", + "pierre_larousse", + "norris", + "christiaan_eijkman", + "yakub", + "adolf_eichmann", + "sverdrup", + "kaiser_wilhelm", + "heyward", + "paganini", + "marilyn_horne", + "boole", + "ibsen", + "lorca", + "nell_gwynne", + "marvell", + "stan_musial", + "rimbaud", + "francis_bacon", + "compton", + "pete_seeger", + "konstantin_stanislavski", + "richard_m_nixon", + "walter_hess", + "john_wycliffe", + "gaskell", + "marc_rothko", + "husayn", + "joseph_heller", + "lessing", + "a", + "boone", + "francois_jacob", + "heyerdahl", + "peary", + "gustavus_i", + "gershwin", + "rossetti", + "morris", + "peter_carl_goldmark", + "apollinaire", + "hassam", + "trotsky", + "montagu", + "peter_brian_medawar", + "norman_rockwell", + "boris_spassky", + "khadafy", + "francois_duvalier", + "james_brown", + "william_hogarth", + "kachaturian", + "modigliani", + "charles_baudelaire", + "luigi_cherubini", + "sir_william_rowan_hamilton", + "francis_joseph", + "deere", + "david_ricardo", + "barkley", + "john_mitchell", + "henri_labrouste", + "mary_leakey", + "charlie_parker", + "immanuel_kant", + "jacques_bernoulli", + "goodall", + "kinsey", + "himmler", + "beaverbrook", + "james_franck", + "william_crookes", + "antonius_stradivarius", + "james_meredith", + "samuel_gompers", + "nellie_bly", + "brancusi", + "john_haldane", + "weber", + "lewis", + "warburg", + "fulton", + "parsons", + "alexandre_yersin", + "francois_mitterrand", + "n", + "richardson", + "michel_montaigne", + "tunney", + "stephen_leacock", + "hope", + "albert_schweitzer", + "miller", + "flavius_theodosius", + "chagall", + "john_mccormick", + "john_harvard", + "johann_friedrich_herbart", + "giulio_natta", + "hardy", + "erik_weisz", + "musset", + "guarnieri", + "dewey", + "canetti", + "saint_martin", + "titus", + "johannes_kepler", + "anatoli_karpov", + "sergei_rachmaninov", + "metchnikov", + "william_s_burroughs", + "david_hartley", + "st_peter_the_apostle", + "max_planck", + "dostoyevsky", + "william_blake", + "t_e_lawrence", + "rundstedt", + "julio_iglesias", + "john_bardeen", + "rodin", + "arthur", + "hutchins", + "middleton", + "sarah_vaughan", + "nietzsche", + "dubya", + "john_wilkes", + "francois_mauriac", + "davis", + "konstantin_stanislavsky", + "thoreau", + "william_byrd", + "william_henry", + "christopher_fry", + "godard", + "scott_joplin", + "latrobe", + "samuel_houston", + "supermex", + "carl_lewis", + "sarah_siddons", + "george_vancouver", + "hinault", + "gardner", + "president_wilson", + "vuillard", + "thackeray", + "renjer", + "cesar_franck", + "samuel_rosenstock", + "canberra", + "stephane_mallarme", + "cooke", + "carry_nation", + "bramante", + "goethals", + "knox", + "stephanie_hwang", + "elias_canetti", + "norrish", + "von_braun", + "robert_lowell", + "alfonse_bertillon", + "johann_strauss", + "bohme", + "eisenstein", + "edward_jenner", + "hutton", + "john_mercer", + "oscar_robertson", + "marquand", + "huston", + "oliver_hardy", + "kenyata", + "moore", + "johan_kepler", + "husserl", + "groves", + "cole_porter", + "samuel_wilder", + "benjamin_west", + "jean_luc_godard", + "stokowski", + "graham_greene", + "baryshnikov", + "frans_hals", + "edward", + "maximilian_weber", + "lysenko", + "stroheim", + "whistler", + "la_fontaine", + "lars_onsager", + "willard", + "jewison", + "cardinal_bellarmine", + "margaret_mitchell", + "goldoni", + "konoye", + "leadbelly", + "bunuel", + "igor_stravinsky", + "duse", + "j_b_rhine", + "stuart_davis", + "olmsted", + "gary_weinstein", + "mary_mccauley", + "lola_montez", + "tucker", + "john_wain", + "jan_swammerdam", + "bellini", + "mary_mccarthy", + "jimenez", + "wilkes", + "tully", + "david_riesman", + "laughton", + "doctorow", + "john_walker", + "dvorak", + "virchow", + "flavius_josephus", + "william_herschel", + "wheatley", + "joseph_black", + "marcus_whitman", + "mikhail_baryshnikov", + "du_barry", + "montesquieu", + "oakley", + "william_john_clifton_haley_jr", + "marcus_aurelius_valerius_maximianus", + "franz_joseph", + "peirce", + "arthur_rubinstein", + "calvin", + "cherubini", + "arthur_compton", + "koussevitzky", + "lindbergh", + "robbins", + "maria_antonia", + "niels_bohr", + "sergei_rachmaninoff", + "kenneth_grahame", + "naismith", + "larousse", + "hickock", + "sheridan", + "bardeen", + "henry_fielding", + "bertrand_russell", + "fragonard", + "jakob_hermandszoon", + "katherine_anne_porter", + "madame_curie", + "hawkyns", + "michael_faraday", + "john_d_rockefeller", + "malamud", + "j_craig_ventner", + "arthur_schlesinger", + "burt", + "anthony_burgess", + "anthony", + "cummings", + "jan_tinbergen", + "swanson", + "peter_mark_roget", + "robert_venturi", + "johnny_appleseed", + "schumpeter", + "schliemann", + "gregory", + "ben_gurion", + "kreisler", + "maurois", + "sir_francis_galton", + "ellen_price_wood", + "ralegh", + "irving_berlin", + "wavell", + "marstan", + "otho_of_lagery", + "gauguin", + "malory", + "bernard_baruch", + "rudolf_diesel", + "hans_holbein", + "sungai_st_lawrence", + "walt_disney", + "meredith", + "ben_jonson", + "peter", + "lippi", + "la_spezia", + "czar_peter_i", + "robert_benchley", + "dowding", + "oates", + "albee", + "florey", + "h_l_mencken", + "lully", + "munchhausen", + "vesey", + "aleksandr_prokhorov", + "harungan", + "rubens", + "ondaatje", + "percy", + "joseph_schumpeter", + "beveridge", + "max_muller", + "gabriel_lippmann", + "steve_reich", + "groucho", + "adenauer", + "lee", + "derrida", + "lamarck", + "benny_goodman", + "ted_williams", + "karl_menninger", + "william_beaumont", + "froebel", + "friedrich_engels", + "huldreich_zwingli", + "haley", + "pavlov", + "steichen", + "jane_austen", + "anthony_vandyke", + "charles_laughton", + "parker", + "eichmann", + "magritte", + "gibson", + "moses", + "ventner", + "gustav_mahler", + "ed_sullivan", + "phil_collins", + "nevelson", + "alice_paul", + "erving", + "robert_redford", + "robert_barany", + "monod", + "jean_giraudoux", + "fuller", + "jack_dempsey", + "brindisi", + "ian_fleming", + "swedenborg", + "richard_feynman", + "harrod", + "menninger", + "willebrand", + "kandinski", + "wolfgang_pauli", + "wycherley", + "ellington", + "landowska", + "j_tuzo_wilson", + "ruskin", + "wollaston", + "lipmann", + "dodgson", + "theodore_dreiser", + "theodor_mommsen", + "andrew_huxley", + "schoenberg", + "marcel_proust", + "klimt", + "jessica_mitford", + "thomas_more", + "jesse_louis_jackson", + "homo_heidelbergensis", + "milhaud", + "paul_hindemith", + "elizabeth_taylor", + "thomas_chippendale", + "meyerbeer", + "lunt", + "anne_sullivan", + "walesa", + "feodor_dostoevski", + "paul_robeson", + "arnold", + "benedict", + "anton_chekov", + "shute", + "thomas_middleton", + "metchnikoff", + "lugosi", + "gladstone", + "nell_gywn", + "john_dowland", + "sumner", + "le_carre", + "van_dyck", + "sarnoff", + "zaharias", + "millay", + "daniel_jones", + "hellman", + "benjamin_jonson", + "william_golding", + "robert_motherwell", + "a_e_housman", + "william_caxton", + "john_milton", + "c_h_best", + "karl_wilhelm_scheele", + "the_virgin", + "rudolf_serkin", + "couperin", + "siqueiros", + "peter_stuyvesant", + "rattigan", + "henri_louis_bergson", + "ethel_merman", + "the_nazarene", + "szilard", + "rittenhouse", + "riesman", + "frank_baum", + "hotspur", + "samuel_adams", + "albert_speer", + "james_baldwin", + "frederick_william", + "lindsay", + "john_copley", + "john_vanbrugh", + "gracie", + "cavell", + "leacock", + "indira_gandhi", + "daumier", + "whitman", + "millikan", + "davys", + "william_mitchell", + "albers", + "bertolucci", + "jane_seymour", + "peter_goldmark", + "peter_minnewit", + "klopstock", + "rehnquist", + "george_gershwin", + "toynbee", + "schopenhauer", + "alberto_giacometti", + "laney", + "wallace", + "e_t_a_hoffmann", + "frank_whittle", + "alfred_nobel", + "jesse_owens", + "o\u2019keeffe", + "eisenstaedt", + "tenniel", + "daniel_rutherford", + "ashe", + "marco_polo", + "koestler", + "john_fletcher", + "heidegger", + "georgi_zhukov", + "caravaggio", + "matthias_schleiden", + "beria", + "charlie_watts", + "albert_gore_jr", + "moussorgsky", + "spenser", + "m", + "charlotte_corday", + "penjual_kaca", + "jamison", + "hargreaves", + "marcel_marceau", + "gilmer", + "oort", + "allen_ginsberg", + "fred_zinnemann", + "ringling", + "hammerstein", + "coleridge", + "daniel_bernoulli", + "kelly", + "guillaume_apollinaire", + "william_strickland", + "gibbs", + "john_marquand", + "l_s_lowry", + "brandt", + "pablo_casals", + "joseph_henry", + "henri_bergson", + "st_brigid", + "speke", + "craigie", + "bergson", + "antonius", + "jean_bernoulli", + "edward_macdowell", + "josef_hoffmann", + "hammett", + "prokhorov", + "boris_karloff", + "gottfried_leibniz", + "pierre_corneille", + "phillis_wheatley", + "tussaud", + "oppenheimer", + "mohammed_reza_pahlavi", + "condorcet", + "patrick_white", + "hans_zinsser", + "saul_steinberg", + "boehm", + "si_kecil_pemakai_tudung_merah", + "greenberg", + "bartholomew_roberts", + "eileen_farrell", + "catherine_howard", + "daniel_morgan", + "hans_christian_andersen", + "peter_cooper", + "reich", + "schwann", + "william_morris", + "anton_van_leeuwenhoek", + "william_dawes", + "cary_grant", + "hideyo_noguchi", + "thomas", + "isaac_watts", + "saint_lawrence", + "harmsworth", + "ford", + "pieter_zeeman", + "arnold_gesell", + "scripps", + "herrick", + "glenn_miller", + "thomas_straussler", + "navratilova", + "sir_thomas_gresham", + "goring", + "karl_von_clausewitz", + "gustavus", + "musial", + "c_w_post", + "fitzgerald", + "wegener", + "pablo_picasso", + "newman", + "horne", + "mansart", + "john_philip_marquand", + "marian_anderson", + "natalie_wood", + "l_ron_hubbard", + "tagore", + "raffles", + "james_bernoulli", + "kennelly", + "alan_hodgkin", + "malinowski", + "anderson", + "thomas_moore", + "sergei_vasilievich_rachmaninov", + "robeson", + "louis_ix", + "osman_i", + "kurt_weill", + "kieslowski", + "otto_hahn", + "kelayang", + "webster", + "nast", + "welty", + "christian_huygens", + "otto_meyerhof", + "john_marshall", + "mamet", + "christiaan_huygens", + "duvalier", + "hector_berlioz", + "smalley", + "lucille_ball", + "paul_simon", + "mussorgsky", + "claudio_monteverdi", + "benjamin_jowett", + "rubinstein", + "nabokov", + "robert_scott", + "stravinsky", + "john_galsworthy", + "knut_pedersen", + "robert_robinson", + "scott", + "ziegler", + "pieter_breughel", + "karloff", + "khachaturian", + "dickinson", + "bronte", + "spielberg", + "gombrowicz", + "o", + "goodman", + "king_james", + "mccartney", + "wallenstein", + "adam_smith", + "william_james", + "diaghilev", + "kristoforus_kolumbus", + "lipscomb", + "taney", + "vizcaino", + "jean_harlow", + "henry_miller", + "sayers", + "mcguffey", + "karl_marx", + "einthoven", + "paul_bunyan", + "rickover", + "friedrich_nietzsche", + "zsigmondy", + "i", + "strindberg", + "robert_indiana", + "william_burroughs", + "noyes", + "peter_alexander_ustinov", + "jimmy_durante", + "howard", + "john_wesley", + "march_king", + "de_l\u2019_orme", + "hasek", + "dorothy_sayers", + "berlage", + "tallis", + "e_o_wilson", + "melanchthon", + "goldwyn", + "sandro_botticelli", + "endecott", + "parrish", + "von_willebrand", + "carson_mccullers", + "frank_stockton", + "bloch", + "huss", + "seiji_ozawa", + "nazimova", + "ehrenberg", + "proust", + "nikola_tesla", + "de_mille", + "al_capone", + "jim_bowie", + "charles_barkley", + "billy_graham", + "robert_schumann", + "mel_gibson", + "le_corbusier", + "malraux", + "carlo_goldoni", + "trumbo", + "kaufman", + "shankar", + "william_patterson", + "boleyn", + "ninigi", + "leo_delibes", + "john_locke", + "tharp", + "alexis_carrel", + "le_notre", + "du_maurier", + "j_e_johnston", + "mitchum", + "a_noam_chomsky", + "symonds", + "king_lear", + "serkin", + "joseph_marie_jacquard", + "antonin_dvorak", + "henry_james", + "stephen_sondheim", + "henson", + "st_martin", + "richards", + "crawford", + "oscar_hammerstein", + "steinway", + "lorenz_hart", + "marie_grosholtz", + "robert_bartlett", + "stewart", + "horney", + "jakobson", + "bierce", + "hevesy", + "perry", + "helen_keller", + "grotius", + "paul_dukas", + "e_t_s_walton", + "ingrid_bergman", + "nama_jenis_anggur_putih", + "saint_david", + "siddons", + "tillich", + "douwes_dekker", + "pengarah_urusan", + "george_ii", + "crosby", + "denmark_vesey", + "hindemith", + "hodgkin", + "leonard_bloomfield", + "congreve", + "jane_jacobs", + "thurber", + "lulli", + "kosciusko", + "verlaine", + "kerensky", + "trevelyan", + "jean_piaget", + "meany", + "soutine", + "sondheim", + "william_congreve", + "franz_kline", + "henri_rousseau", + "paul_tillich", + "hilaire_belloc", + "massine", + "mondrian", + "the_adventures_of_sherlock_holmes", + "darrow", + "shakspere", + "jolliet", + "montgomery_ward", + "reichstein", + "de_kooning", + "baudelaire", + "dua_sukatan", + "angelo_correr", + "st_denis", + "rogers", + "carducci", + "frank_norris", + "francois_couperin", + "konoe", + "pieter_brueghel", + "peter_ilich_tchaikovsky", + "behring", + "francois_de_la_rochefoucauld", + "frank_stella", + "durrell", + "paige", + "stilwell", + "robert_southey", + "valentina_tereshkova", + "eddington", + "h_g_wells", + "walt_whitman", + "hernando_cortes", + "william_wyler", + "warren", + "john_osborne", + "colin_powell", + "moliere", + "ludwig_boltzmann", + "antoninus", + "tereshkova", + "beerbohm", + "carl_nielsen", + "sir_winston_churchill", + "ciardi", + "karl_gauss", + "chopin", + "weizmann", + "vasarely", + "smollett", + "merton", + "hearst", + "pauling", + "rankin", + "bunsen", + "vaux", + "carl_jung", + "israel_strassberg", + "richard_neville", + "leopold_kronecker", + "goering", + "masefield", + "francis_richard_stockton", + "simpson", + "richard_wright", + "heyse", + "benjamin_thompson", + "st_benedict", + "kandinsky", + "adolf_hitler", + "maria_mitchell", + "gunung_sherman", + "prokofiev", + "danau_tana", + "fritz_haber", + "dekker", + "archibald_macleish", + "fowler", + "richard_starkey", + "peter_behrens", + "john_tradescant", + "nathan_bailey", + "jaspers", + "alfred_stieglitz", + "gabriele_fallopius", + "redford", + "joseph_haydn", + "tempat_kurungan_binatang_yg_ditahan", + "stephen_spender", + "garfield", + "mendelsohn", + "jones", + "bailey", + "george_boole", + "solvay", + "fyodor_dostoevsky", + "mahan", + "paul_revere", + "philipp_schwarzerd", + "sontag", + "ruth_fulton", + "helen_wills", + "kruger", + "daniel_boone", + "buffalo_bill", + "william_fulbright", + "edvard_grieg", + "radhakrishnan", + "gorgas", + "robert_boyle", + "korchnoi", + "rickenbaker", + "arthur_laffer", + "edith_cavell", + "mitchell", + "alan_paton", + "zinsser", + "deliverer", + "eliot", + "hopkinson", + "verwoerd", + "ralph_richardson", + "paderewski", + "lenard", + "1", + "schubert", + "karsavina", + "alberti", + "krzysztof_kieslowski", + "cordell_hull", + "a_a_michelson", + "blixen", + "james_wilson", + "rosa_parks", + "tchaikovsky", + "norman_jewison", + "marceau", + "tarkovsky", + "crichton", + "riley", + "samuel_goldwyn", + "steller", + "mccullers", + "x", + "elizabeth_seton", + "ernest_walton", + "vladimir_putin", + "pegawai_kehutanan", + "jacob", + "orbison", + "crockett", + "giuseppe_mazzini", + "gromyko", + "carolus", + "runyon", + "jim_thorpe", + "woodhull", + "karl_augustus_menninger", + "hertz", + "bradbury", + "randall_jarrell", + "old_bullion", + "verrazzano", + "richler", + "swammerdam", + "manson", + "sekhet", + "laurence_sterne", + "markov", + "hutchinson", + "jacqueline_cochran", + "george_fox", + "john_lackland", + "graves", + "peter_paul_mauser", + "ben_hecht", + "christopher_isherwood", + "bloomfield", + "fritz_kreisler", + "john_heming", + "copley", + "henry_bolingbroke", + "anne_hathaway", + "david_garrick", + "don_budge", + "meade", + "ozawa", + "bill_russell", + "margaret_court", + "emile_zola", + "berlioz", + "evers", + "owen", + "thomson", + "henry_le_chatelier", + "baldwin", + "gallaudet", + "a_conan_doyle", + "bomber_harris", + "jeannette_rankin", + "clarence_darrow", + "marya_sklodowska", + "alben_william_barkley", + "dawes", + "sean_o\u2019casey", + "agassiz", + "mallon", + "charles_lamb", + "g", + "sills", + "william_of_wykeham", + "labrouste", + "albert_michelson", + "dulles", + "cattell", + "king_john", + "nansen", + "charles_coulomb", + "vespucci", + "de_niro", + "savonarola", + "brady", + "john_chapman", + "anthony_comstock", + "ellsworth", + "lemaitre", + "jansen", + "arthur_schopenhauer", + "sam_goldwyn", + "thomas_dekker", + "el_caudillo", + "custer", + "harriman", + "james_cagney", + "john_keble", + "johns_hopkins", + "l_m_montgomery", + "henri_pitot", + "wanda_landowska", + "edward_pusey", + "billy_mitchell", + "martin_heidegger", + "hans_eysenck", + "shockley", + "christopher_columbus", + "gaius_flaminius", + "aiken", + "tyson", + "muller", + "arnold_schoenberg", + "r", + "george_lucas", + "andrew_jackson", + "tindal", + "peter_abelard", + "edith_wharton", + "louis_armstrong", + "spallanzani", + "ortega", + "cornell", + "barnum", + "balanchine", + "st_mark", + "pieter_bruegel", + "loeb", + "dubyuh", + "antony_tudor", + "saint_christopher", + "steven_spielberg", + "sir_john_cockcroft", + "sydenham", + "bultmann", + "comstock", + "st_louis_missouri", + "jean_monnet", + "leonard", + "sellers", + "georgiana_barrymore", + "d_w_griffith", + "robert_fulton", + "goudy", + "thomas_hardy", + "eddie_rickenbacker", + "thomas_gainsborough", + "stefan_wyszynski", + "franz_ferdinand", + "giuseppe_garibaldi", + "wister", + "philip_warren_anderson", + "karlfeldt", + "hemminge", + "blitzstein", + "fra_filippo_lippi", + "alexandre_dumas", + "pirandello", + "philipp_melanchthon", + "robert_brown", + "doolittle", + "bethune", + "markoff", + "thomas_carlyle", + "wiesenthal", + "johann_gutenberg", + "roberts", + "shah_pahlavi", + "bragg", + "gagarin", + "allen_tate", + "algren", + "donald_barthelme", + "andre_maurois", + "alphonse_capone", + "william_tyndale", + "tamara_karsavina", + "ibert", + "bobby_fischer", + "crookes", + "din_land", + "menotti", + "johannes_gutenberg", + "svedberg", + "thornton", + "kaunda", + "barrymore", + "d", + "hooke", + "breughel", + "james_bowie", + "thomas_malthus", + "giambattista_marino", + "gaetano_donizetti", + "dreiser", + "castro", + "beadle", + "william_faulkner", + "wordsworth", + "cockcroft", + "plath", + "johannes_eckhart", + "edward_white", + "edouard_manet", + "titus_flavius_vespasianus", + "simon_de_montfort", + "amerigo_vespucci", + "selznick", + "rachmaninov", + "wilmut", + "arthur_holmes", + "montessori", + "laurentius", + "anouilh", + "pierre_boulez", + "hans_adolf_krebs", + "grahame", + "mcmaster", + "chekov", + "don_kisot", + "bolzano_bozen", + "hollerith", + "le_chatelier", + "girolamo_savonarola", + "salk", + "smitty_stevens", + "housman", + "emma_goldman", + "robert_gray", + "blake", + "haywood", + "anna_kournikova", + "francis_poulenc", + "james_ussher", + "wolfe", + "john_barrymore", + "john_constable", + "rachel_louise_carson", + "c_d_gibson", + "huggins", + "james_mill", + "john_ciardi", + "albino_luciano", + "putin", + "landsteiner", + "gary_kasparov", + "matthew_flinders", + "hanks", + "thomas_crawford", + "chomsky", + "robert_herrick", + "joseph_campbell", + "charles_a_lindbergh", + "st_peter", + "grainger", + "zeppo", + "molnar", + "john_m_browning", + "swift", + "klaproth", + "jean_de_la_fontaine", + "robert_hooke", + "davy", + "lovell", + "o_henry", + "hoffa", + "harriet_wilson", + "kekule", + "karl_popper", + "benjamin_kubelsky", + "alfred", + "von_sternberg", + "coleman_hawkins", + "kronecker", + "frye", + "untermeyer", + "mary_harris", + "john_calvin", + "george_sand", + "sousa", + "peter_sellers", + "homo_rhodesiensis", + "steffens", + "charles_fourier", + "john_mcgraw", + "henry_clay", + "toscanini", + "giraudoux", + "marcus_aurelius", + "cousteau", + "bolingbroke", + "e_w_morley", + "peter_o'toole", + "joseph_conrad", + "edmund_halley", + "william_shockley", + "de_spinoza", + "keble", + "kenneth_roberts", + "balenciaga", + "peter_paul_rubens", + "mahatma_gandhi", + "jim_morrison", + "saint_peter", + "cromwell", + "pembuat_atap_jerami", + "masters", + "jules_verne", + "paul_newman", + "robert_mills", + "george_meredith", + "trollope", + "galton", + "john_marstan", + "menuhin", + "robert_morris", + "kastler", + "carroll", + "hopkins", + "antonio_pignatelli", + "zimbalist", + "eugene_ionesco", + "matisse", + "woody_herman", + "boell", + "charlotte_bronte", + "heaviside", + "gehrig", + "fyodor_dostoyevsky", + "alexander_wilson", + "john_roebling", + "josef_albers", + "jackson_pollock", + "spinoza", + "laffite", + "david_crockett", + "welles", + "dayan", + "steinem", + "kasparov", + "john_lennon", + "seton", + "andrea_palladio", + "cornelis_jansen", + "golding", + "john_speke", + "buchner", + "wilson", + "fontanne", + "gandhi", + "heinlein", + "cheever", + "poulenc", + "motherwell", + "bob_woodward", + "dedap", + "charlie_chaplin", + "lillian_russell", + "d_h_lawrence", + "humboldt", + "mcpherson", + "edward_morley", + "barthelme", + "j_m_barrie", + "lippmann", + "hitchings", + "robert_woodward", + "schonberg", + "pavarotti", + "thomas_malory", + "tilden", + "lea", + "john_brown", + "al_jolson", + "elizabeth_gaskell", + "jinnah", + "caldwell", + "ibu_bapa_datuk_nenek", + "john_mill", + "langtry", + "william_of_ockham", + "teasdale", + "hugo_junkers", + "zinnemann", + "j_r_firth", + "burnham", + "maurice_barrymore", + "haldane", + "piscis_austrinus", + "norman_thomas", + "lillian_hellman", + "brescia", + "brecht", + "peter_carl_faberge", + "carter", + "john_macleod", + "vasco_da_gamma", + "satie", + "tallchief", + "thomas_merton", + "benedetto_odescalchi", + "sennett", + "pyotr_i_dari_rusia", + "massenet", + "villard", + "riemann", + "shahn", + "jenny_wren", + "stopes", + "pyotr_tchaikovsky", + "rothko", + "asa_gray", + "donkin", + "bonhoeffer", + "spillane", + "hannah_arendt", + "antonio_stradivari", + "wanamaker", + "c_s_forester", + "philip_anderson", + "kuhn", + "cushing", + "maximianus", + "robinson_jeffers", + "farrell", + "antony", + "eckhart", + "arungan", + "alice_walker", + "priestley", + "andrei_sakharov", + "karl_czerny", + "casals", + "sir_james_murray", + "strauss", + "macleish", + "miles_davis", + "edmund_cartwright", + "koopmans", + "rupert", + "mubarak", + "octavian", + "sir_william_walton", + "wollstonecraft", + "pusey", + "bruce", + "butterfield", + "james_parkinson", + "heyrovsky", + "brummell", + "a_e_kennelly", + "wilhelm_tell", + "j_m_synge", + "william_augustus", + "qaddafi", + "george_marshall", + "onsager", + "cochran", + "eijkman", + "cagney", + "tuchman", + "gesell", + "harold_nicolson", + "jesse_jackson", + "willa_cather", + "ethelred", + "bozen", + "stanley_kubrick", + "mohammed_ali", + "gustavus_adolphus", + "cornelius_jansenius", + "leontief", + "john_deere", + "andre_markoff", + "champollion", + "cronyn", + "keaton", + "john_huston", + "robert_merton", + "peter_the_great", + "palayan_gereja", + "carothers", + "ivanov", + "jean_baptiste_joseph_fourier", + "debs", + "william_gilbert", + "rene_magritte", + "tukang_pemotong_kaca", + "kosciuszko", + "mcgraw", + "le_gallienne", + "astaire", + "james_watt", + "jonathan_edwards", + "ronald_reagan", + "helmut_schmidt", + "jenny_lind", + "leigh", + "homo", + "frederick_douglass", + "tebaldi", + "von_bismarck", + "symons", + "moynihan", + "la_rochefoucauld", + "david_hilbert", + "skinner", + "wilhelm_reich", + "duchamp", + "boehme", + "william_thornton", + "roman_jakobson", + "oliver_cromwell", + "nicolas_de_malebranche", + "vinogradoff", + "henry_beauclerc", + "beaumont", + "lionel_hampton", + "newcomb", + "martin_luther_king", + "bukharin", + "purcell", + "james_hargreaves", + "prince_charles", + "hermann_goering", + "st_james", + "goncourt", + "delbruck", + "lorenz", + "raymond_lully", + "frank_capra", + "william_wordsworth", + "rex_harrison", + "william_clark", + "s_smith_stevens", + "woodrow_wilson", + "thomas_jackson", + "delibes", + "william_wycherley", + "walton", + "margaret_sanger", + "proudhon", + "heming", + "bankhead", + "southey", + "edgar_varese", + "gustav_hertz", + "americus_vespucius", + "yevgeni_yevtushenko", + "acheson", + "george_mason", + "daud", + "el_cid", + "andrei_voznesenski", + "quincy", + "borges", + "mosander", + "marcus_antonius", + "mazzini", + "schulz", + "otto_i", + "dostoevsky", + "alonso", + "sapir", + "torricelli", + "frank_cooper", + "de_quincey", + "t_h_white", + "sargent", + "agrippina", + "st_louis", + "richard_rodgers", + "karpov", + "don_quixote", + "george", + "soufflot", + "kleist", + "gogh", + "leeuwenhoek", + "anne_sexton", + "holmes", + "thomas_bradley", + "hogarth", + "o\u2019connor", + "kroto", + "john_dryden", + "jim_henson", + "friedrich_max_muller", + "kuznets", + "mercouri", + "furnivall", + "saarinen", + "b\u00e9la_lugosi", + "ernest_hemingway", + "burns", + "fiedler", + "voznesenski", + "john_eccles", + "lech_walesa", + "von_neumann", + "george_westinghouse", + "simon_petrus", + "constantin_brancusi", + "richard_haldane", + "tourette", + "thomas_higginson", + "aquila", + "truffaut", + "brockhouse", + "jacques_charles", + "eero_saarinen", + "pauli", + "arthur_miller", + "henry_russell", + "john_cheever", + "friedrich_wilhelm_bessel", + "cristoforo_colombo", + "gracie_allen", + "john_bernoulli", + "st_edward_the_confessor", + "billy_sunday", + "nelson_mandela", + "heinrich_himmler", + "al_gore", + "jacobs", + "farragut", + "john_rutledge", + "hans_bethe", + "hans_geiger", + "michinomiya_hirohito", + "nicklaus", + "gaius_octavianus", + "mandelbrot", + "cesare_borgia", + "woodbury", + "j_p_morgan", + "whittier", + "hampton", + "christopher_carson", + "loewi", + "wheatstone", + "swinburne", + "kerouac", + "kierkegaard", + "kutuzov", + "roald_amundsen", + "starkey", + "mossbauer", + "stephane_grappelli", + "sherwood_anderson", + "andersen", + "richard_leakey", + "alfred_korzybski", + "ledbetter", + "charles_dickens", + "verrazano", + "pershing", + "jean_chauvin", + "fairbanks", + "kirchhoff", + "delorme", + "maugham", + "e_o_lawrence", + "bellarmino", + "samuel_huntington", + "de_saussure", + "gesner", + "st_ignatius", + "ella_fitzgerald", + "fats_waller", + "alfred_krupp", + "jakob_bernoulli", + "philip_augustus", + "thomas_sydenham", + "bernoulli", + "jack_robinson", + "tatum", + "alois_senefelder", + "george_enescu", + "wallace_carothers", + "jacques_offenbach", + "anne_bronte", + "schweitzer", + "joseph_paxton", + "manzoni", + "seles", + "silverstein", + "louis_untermeyer", + "william_curtis", + "francisco_villa", + "macaulay", + "john_uhler", + "callas", + "tombaugh", + "lozier", + "bose", + "william_chambers", + "gilbert", + "ironsides", + "minnewit", + "leakey", + "fellini", + "bronislaw_malinowski", + "van_doren", + "von_mauser", + "tawney", + "hans_conrad_julius_reiter", + "george_stevens", + "federico_fellini", + "woolley", + "karl_linne", + "bessie_smith", + "bradley", + "bentham", + "jean_antoine_watteau", + "patrick_henry", + "carnot", + "honegger", + "willy_brandt", + "vestris", + "charles_wilkes", + "francisco_pizarro", + "francisco_franco", + "friedan", + "shelley", + "katherine_cornell", + "jackie_robinson", + "thomas_the_doubting_apostle", + "montfort", + "bernardo_bertolucci", + "don_luchino_visconti_conte_di_modrone", + "stevenson", + "king_oliver", + "corday", + "charles_augustus_lindbergh", + "jan_steen", + "lichtenstein", + "frank_harris", + "e_e_cummings", + "john_ross", + "ali_baba", + "cassius_longinus", + "powell", + "philibert_delorme", + "guevara", + "peabody", + "stevens", + "andrew_mellon", + "kristoforus", + "hans_arp", + "browne", + "andrew_carnegie", + "alcott", + "pontius_pilatus", + "weismann", + "halevy", + "franz_schubert", + "william_butterfield", + "edward_d_white", + "howells", + "johnny_cash", + "vidal", + "joseph_mccarthy", + "wyler", + "alfred_kastler", + "penyelenggaraannya", + "marduk", + "mick_jagger", + "warhol", + "otto_loewi", + "steinman", + "robinson", + "tom_bradley", + "don_marquis", + "charles_peirce", + "mandelstam", + "georges_cuvier", + "peter_seeger", + "ethelred_i", + "sessions", + "saint_peter_the_apostle", + "hemingway", + "william_harvey", + "husain", + "walter_scott", + "wyat", + "h_j_eysenck", + "parkinson", + "francois_villon", + "charcot", + "august_von_wassermann", + "peter_medawar", + "paul_cezanne", + "jenner", + "werfel", + "stuyvesant", + "vladimir_lenin", + "sam_houston", + "pemilik_kilang_pengisar", + "fugard", + "dimaggio", + "robert_peary", + "rodgers", + "littre", + "zangwill", + "bartok", + "wilder", + "henry_steinway", + "kahlil_gibran", + "steiner", + "peter_i", + "daguerre", + "robert_browning", + "comenius", + "charles_kettering", + "mellon", + "alessandro_farnese", + "ralph_ellison", + "john_bunyan", + "jonathan_swift", + "franck", + "peter_i_dari_rusia", + "goebbels", + "iglesias", + "walter_gropius", + "albert_einstein", + "henry_sweet", + "donizetti", + "robert_joffrey", + "william_shakspere", + "aletta_jacobs", + "stubbs", + "thomas_edison", + "elizabeth", + "rasputin", + "chiang_kai_shek", + "benjamin_harris", + "beecher", + "claude_bernard", + "ailey", + "raymond_chandler", + "charles_dodgson", + "henry_purcell", + "francis_hopkinson", + "trumbull", + "windaus", + "de_la_mare", + "ostwald", + "flannery_o\u2019connor", + "john_wickliffe", + "nixon", + "t", + "tukang_gerobak", + "griffith", + "jean_francois_champollion", + "gainsborough", + "le_douanier_rousseau", + "thatcher", + "lemmon", + "cervantes", + "gonne", + "marley", + "witherspoon", + "wilhelm_ostwald" + ], + "ORG": [ + "laut_kulzum", + "the_states", + "dominion", + "ida", + "parti_demokrat", + "shinto", + "partai_demokratik", + "gerakan_oxford", + "proyek_manhattan", + "rumah_putih", + "pendidikan_rendah", + "pembelajaran", + "perikatan_utara", + "gironde", + "disesuaikan", + "paul_cezanne", + "jan_mayen", + "bukit_zaitun", + "balatentara", + "shift_kerja", + "aku_cinta_padamu", + "kemal_ataturk", + "malaikat_pelindung", + "nasa", + "the_street", + "kebudayaan_barat", + "saint_nicholas", + "duane", + "hinayana", + "batalyon", + "the_national_archives", + "isi", + "bollywood", + "kuartal_pertama", + "handalan", + "st_christopher", + "europol", + "schutzstaffel", + "pernikahan_sejenis", + "the_who", + "abu_ali_al_husain_ibn_abdallah_ibn_sina", + "pihak_pembangkang", + "haganah", + "empat_besar", + "partai_komunis", + "turut_serta", + "san_francisco", + "a_chorus_line", + "layang_layang_asia", + "tidak_sekali", + "taoisme", + "st_mary_magdalene", + "juga_sebaliknya", + "nara", + "pengasuhan", + "va", + "saint_george", + "pasifik_utara", + "sc", + "luar_biasa_hebatnya", + "kantor_pos", + "gao", + "united_states", + "dot", + "bertaburan_di", + "nanak", + "mahayana", + "golongan_borjuis", + "kongregasional", + "saint_vincent", + "angkatan_tentera", + "freemasonry", + "ec", + "hari_saint_joseph", + "palang_merah", + "john_tuzo_wilson", + "can_tho", + "saint_helena", + "don_juan", + "saus_pedas", + "waktu_sekolah", + "bunda_kedukaan", + "oni", + "the_new_school", + "partai_sosialis", + "aku_menyayangimu", + "ai", + "ibukota_new_mexico", + "kelas_pertengahan", + "majelis_nasional_republik_polandia", + "republik_cape_verde", + "aku_mengasihimu", + "the_football_league", + "chiang_mai", + "saint_andrew_the_apostle", + "bumi_hangus", + "akademi", + "sao_paulo", + "dia", + "the_big_four", + "aku_sayang_akan_engkau", + "persatuan_planet", + "sungai_yangtze", + "tak_piawai", + "gatt", + "galaksi_spiral", + "danau_st_clair", + "pengajian_islam", + "mulai_dari_tibet_ke_laut_cina", + "partai_sosial_demokrat", + "galeri_seni", + "le_mans", + "bulan_baru", + "pulang_modal", + "christian_science", + "nama_saya", + "caf\u00e9_au_lait", + "nama_saya_ialah", + "tahun_masihi", + "aku_sayang_kamu", + "rabindranath_tagore", + "pegawai_negeri", + "gestapo", + "gerakan_politik", + "shah_alam", + "chiang_chung_cheng", + "winnie_the_pooh", + "kantor_pabean", + "partai_republik", + "yesuit", + "putri_tidur", + "bunda_dari_tujuh_kedukaan", + "st_nicholas", + "heinrich_theodor_boell", + "sao_tome", + "who_are_you", + "dibuat_sesuai_pesanan", + "i_ching", + "saint_joseph", + "al_jazeera", + "rumah_sakit_jiwa", + "perhimpunan_kebangsaan_republik_korea", + "angkatan_darat", + "prasekolah", + "europe", + "addis_ababa", + "dag_hjalmar_agne_carl_hammarskjold", + "kota_kara", + "parti_buruh_norway", + "mossad", + "hare_krishna", + "ferdinand_magellan", + "bom_mobil", + "berasas", + "parti_republikan", + "kekaisaran_jerman", + "gula_gula_getah", + "pihak_berkuasa_palestin", + "hollywood", + "kurt_godel", + "daulat", + "saint_barth\u00e9lemy", + "sturmabteilung", + "cita_rasa_anggur", + "los_angeles", + "nato", + "burung_perkakak_eurasia", + "baltimore_orioles", + "puteri_beradu", + "agen_periklanan", + "majelis_nasional_perancis", + "malam_tahun_baru", + "city_hall", + "mi", + "by_the_way", + "uni_telekomunikasi_internasional", + "sungai_kuning", + "marinir", + "in_situ", + "sa", + "doc", + "di_era_kristen", + "ketenteraan", + "john_the_baptist", + "sekolah_dasar", + "marching_band", + "permen_karet", + "berkuli", + "al_ain", + "kaidah", + "biro_investigasi_federal", + "aquinas", + "kesatuan_telekomunikasi_antarabangsa", + "empayar_jerman", + "tentera_darat_amerika_syarikat", + "demokrasi_langsung", + "bunda_dari_kedukaan", + "streptococcus_pyogenes", + "pada_mulanya", + "organisasi_siswa_intra_sekolah", + "kopi_susu", + "perserikatan_bangsa_bangsa", + "sungai_huang_he", + "konsili_konstanz", + "bunda_dari_tujuh_kesedihan", + "merenjong", + "parti_buruh_australia", + "biro_penyiasatan_persekutuan", + "keluarga_kudus", + "partai_buruh_australia", + "isn", + "house_of_lords", + "st_lucia", + "mueang_chiang_rai", + "nikolas_dari_myra", + "yellow_river", + "angkatan_bersenjata", + "bekerja_bertungkus_lumus", + "undang_undang_sivil", + "s\u00e3o_tom\u00e9", + "van_gogh" + ], + "DISEASE": [ + "gamang", + "koreng", + "penjangkitan", + "hydrocephalus", + "dayungan", + "paratipoid", + "sars", + "keadaan_sedang_hamil", + "biasanya_ditandai_oleh_ritme_jantung_abnormal", + "kurang_sihat", + "bukan_kolera_tetapi_mirip", + "sampar", + "lipidaemia", + "mongolianisme", + "chorioretinitis", + "tinitus", + "jelatang", + "filovirus", + "tidak_kompatibel", + "kastanye", + "mimisan", + "gelegata", + "dan_panas", + "poliuria", + "aeroembolisme", + "penyakit_kuning", + "misofobia", + "mampu_menghasilkan_keturunan", + "bergores", + "rubela", + "traumatofobia", + "keadaan_abnormal_kehamilan", + "giantisme", + "menggandeng", + "penyibuk", + "ki", + "polio", + "aniseikonia", + "tabes_dorsalis", + "benggol", + "beberapa_penyakit_virus_pada_tanaman", + "kataphasia", + "kementahan", + "membuat_orang_kebingungan", + "periarteristis_nodosa", + "kalazion", + "dimulai_dari_pucuk", + "bunion", + "kepatahan", + "okronosis", + "flavivirus", + "kalus", + "galaktosele", + "demam_kambuhan", + "polidipsia", + "bisa_ditularkan_oleh_i_ricinus", + "kolik_usus", + "formikasi", + "kaki_melengkung", + "masa_mengawan", + "terjadi_saat_perjalanan_kendaraan_gerak", + "berderak", + "pendiri", + "keadaan_sukar", + "kelahapan", + "klinosephalisme", + "echimosis", + "rasa_tegang", + "arthralgia", + "rage", + "bagian_keuntungan", + "berkereta", + "astasia", + "analgesia", + "anestrus", + "sipilis", + "chill", + "tinggi_rendah", + "salmonela", + "epileptikus_status", + "als", + "tanatofobia", + "kinofobia", + "pengirfakan", + "denggi", + "habituasi", + "mencalar", + "rabies", + "pengeringan", + "bruccelosis", + "mastitis", + "paramyxoviridae", + "fotofobia", + "mencelakai", + "bersin", + "semakin_panas", + "kopok", + "keadaan_patologis", + "biasanya_berukuran_besar", + "skarlatina", + "kondrosarkoma", + "aktinomikosis", + "bodong", + "laringopharingitis", + "karena_parasit_penyerang_akar", + "teraniaya", + "dakriosistitis", + "molor", + "brusellosis", + "rembet", + "hsv_1", + "polidaktili", + "rasa_jengkel", + "pukul_deras", + "memekar", + "kelembekan", + "sub_normal", + "hemangioma_stroberi", + "daktilomegali", + "dan_kulit_melepuh", + "fatan", + "eburnasi", + "siderosis", + "herpes_simpleks", + "tidak_sihat", + "koriza", + "festinasi", + "diestrum", + "kebaharuan", + "aphasia_lancar", + "progeria", + "beberapa_gangguan_kulit", + "pemacu", + "mengigit", + "aquaphobia", + "suatu_serangan_histeria", + "tongos", + "mencekuk", + "keadaan_mental_ditandai_perasaan_pesimis_tidak_cukup", + "virus_herpes_zoster", + "hordeolum", + "kostokondritis", + "sore", + "biasanya_akibat_aborsi_spontan", + "furunkel", + "listeriosis", + "picit", + "jumlah_berlebih_natirum_dalam_darah", + "bobok", + "kerentaan", + "gangguan_personaliti", + "lallasi", + "kutil", + "distomatosis", + "poliarteritis", + "agak_sakit", + "personaliti_terbelah", + "brachydactyly", + "xerodermia", + "termasuk_suaranya_sendiri", + "kesiapsiagaan", + "croup", + "gangren", + "lordosis", + "logagrafia", + "tak_ada_bukti_klinis", + "kondrodistrofi", + "lepidofobia", + "herniasi", + "gondong", + "labirinthitis", + "handikap", + "penyongsangan", + "arthropati", + "striktur", + "julingan", + "claustrophobia", + "rasa_tidak_sihat", + "bintil", + "demam", + "mazopati", + "paramiksovirus", + "papiledema", + "mirip_gigitan_dingin_tetapi_tanpa_pembekuan", + "lembutnya", + "krisis_ekonomi", + "insectofobia", + "anestesi", + "menggosongkan", + "presbiopia", + "rasa_lemah", + "beriberi", + "seminoma", + "barah", + "demam_spirillum", + "mononeuropati_multipel", + "merasionalisasikan", + "mania", + "terkilir", + "kolestasis", + "the_bends", + "keluarbiasaan", + "katalepsi", + "labirintitis", + "lithiasis", + "stroke", + "polisipsia", + "keilosis", + "umum_pada_multipel_sklerosis", + "masa_kehamilan", + "picornavirus", + "shigelosis", + "struma", + "pengkaratan", + "phytophthora_infestans", + "sembap", + "terdiri_dari_spongioblast", + "phalangitis", + "korditis", + "bermayang", + "agammaglobulinemia", + "perleche", + "poliomielitis", + "pempigus", + "shape", + "apit", + "pengeluaran_nanah", + "satanofobia", + "lipidemia", + "demensia", + "keiloskisis", + "eksitasi", + "livedo", + "ms", + "si_gagal", + "keadaan_yang_menua", + "bengkang_bengkok", + "dan_sesaat", + "otorrhea", + "graviditas", + "fantods", + "pertusis", + "sengsai", + "askites", + "mengakibatkan_kepincangan", + "cupang", + "esensi", + "fruktosuria", + "pelebur", + "pharingitis", + "gondok", + "difabel", + "kudap", + "distropi_pseudohipertropik", + "kulampair", + "terjadi_pada_tulang_belakang", + "kegoncangan", + "sengatan", + "keadaan_tidak_dapat_tidur", + "lambdasisme", + "terasa_pedih", + "penyiksaan", + "seperti_pada_lidah", + "biasanya_menyerang_anak_anak_dan_orang_dewasa", + "pelecetan", + "sentak", + "sesitas", + "liliti", + "bisa_jadi_gejala_infeksi_keracunan_makanan_colitis_tumor", + "desikasi", + "rasa_berang", + "lalu_hati", + "klaustrofobia", + "albuminuria", + "si_bongkok", + "robohnya", + "analbuminemia", + "keadaan_sihat", + "kaki_ceruk", + "deuteranopia", + "pelagra", + "getilan", + "keadaan_tidak_dapat_bertindak", + "cacar", + "pengamputasian", + "umum_pada_anak_anak", + "piemia", + "rincian", + "para", + "abras", + "superinfeksi", + "presbiopi", + "ketaksekataan", + "pirofobia", + "granulositopenia", + "koreng_oriental", + "akaropobia", + "ada_scid", + "tibi", + "hay_fever", + "chorea", + "umum_pada_wanita_muda", + "polisithemia", + "anthraks_pneumonia", + "kolangitis", + "papiloma", + "melipatkan", + "elastosis", + "menjadi_makmur", + "juga_berkedutnya_muka_dan_anggota_badan", + "deraan", + "tetapi_jika_tidak_normal", + "radikulitis", + "lipaemia", + "menjadi_rosak", + "sipu", + "pendarahan", + "keadaan_menjadi_berdarah", + "siriasis", + "melecetkan", + "masa_kehamilan_ekstrauterine", + "ada_beberapa_bukaan_untuk_keluarnya_nanah", + "alalia", + "biasanya_diperoleh", + "penghibernatan", + "mieloma", + "astraphobia", + "talasemia", + "balanopostitis", + "arefleksia", + "abrasi", + "berlangsung_beberapa_jam_hari", + "kakogenesis", + "sodoku", + "beri_beri", + "cva", + "tiroiditis", + "lumbago", + "steatosistoma", + "bisa_jinak_ganas", + "kafeinisme", + "gravida", + "deviasi", + "preeklampsia", + "kolik_timbal", + "sianosis", + "klinosephali", + "koronari", + "bisa_disebabkan_oleh_salmonella_enteritidis", + "dan_sakit_kepala", + "transposisi", + "lebih_gula", + "menggeragau", + "kebiasan", + "psikoneurosis", + "tracheitis", + "kausalgia", + "crick", + "terdiri_dari_melanosit", + "raja_singa", + "demam_serebrospinal", + "pariti", + "gangguan_penglihatan", + "biasanya_terjadi_pada_tahun_ketiga_kehidupan", + "amastia", + "memberikan_perincian", + "strangulasi", + "umum_pada_pria_tua", + "skotoma", + "polineuritis", + "totikolis", + "tarsitis", + "distropi", + "solidifikasi", + "panensephalitis", + "tertoreh", + "muskularitas", + "karsinoma", + "katarak", + "posthitis", + "pasteurelosis", + "karsinokarsoma", + "anasarka", + "pelecok", + "geret", + "menggoreskan", + "geronyot", + "faringitis", + "hamartoma", + "chi", + "graphospasme", + "seloid", + "rachitis", + "delirium", + "ditambahkan", + "virus_mosaik_tembakau", + "balanitis", + "kaki_pincang", + "karotenemia", + "keterangsangan", + "melepuh", + "terutama_saat_turbulensi", + "skeleredema", + "rektosele", + "qi", + "gammopati", + "pembocoran", + "kankroid", + "parut", + "konstipasi", + "flutter", + "dilatasi", + "keadaan_sedang_subur", + "kayap", + "virus_miksima", + "teratu", + "granuloma", + "glikosuria", + "krisis_politik", + "dan_tak_bisa_kencing_sesuai_kehendak", + "lagophtalmos", + "biasanya_terkait_dengan_knock_knee", + "akolia", + "metamorphopsia", + "mola_hidatidosa", + "rakitis", + "erisipelas", + "akinesia", + "eritema_nodosum", + "scarlatina", + "tidak_hadam", + "hadangan", + "bisa_kronis_bila_berlanjut", + "malaise", + "renjat", + "stenosis_pilorik", + "terutama_pada_wajah", + "virus_tmv", + "kelemumur", + "spina_bifida", + "silikosis", + "beguk", + "periodontitis_kronis", + "kepengapan", + "flaviviridae", + "kolitis", + "segala_kelemahan_otot", + "memedihkan", + "distimia", + "rasa_loya", + "galaktosemia", + "kala_azar", + "quadrantanopia", + "gimp", + "kebalaran", + "sartan", + "philistinisme", + "estrus", + "kolik_pelukis", + "keadaan_mual_ringan", + "suatu_kondisi_ganas", + "air_merah", + "frenzy", + "keadaan_yg_menua", + "hernia", + "herpes", + "kerewelan", + "funikulitis", + "menguntum", + "bruselosis", + "protosele", + "kaki_panjang", + "penyakit_metabolik", + "viloma", + "hidatid", + "mongolisme", + "cerana", + "penyahhidratan", + "mirip_demam_texas", + "lipemia", + "vitalisasi", + "smart", + "amelia", + "keadaan_terangsang", + "bukan_di_janin", + "kaki_cakar", + "kurang_gisi", + "marasmus", + "umum_di_tropik_dan_timur_jauh", + "beri_seksaan", + "kraurosis", + "penyakit_karat", + "buta_bulan", + "rematik", + "akustikofobia", + "pimosis", + "plasenta_abruptio", + "paralitik_abasia", + "ed", + "lalu_ke_vesikle_dan_pecah_keluarkan_racun", + "lokoisme", + "pencekik", + "kostiasis", + "dan_kerak_kering", + "pica", + "kartilaginifikasi", + "tracheobronchitis", + "stenosis", + "mielofibrosis", + "anemi_mediterania", + "sternutasi", + "menanah", + "schizoprenia_katatonik", + "kepandiran", + "alveolitis", + "dedar", + "bertwist", + "salmonelosis", + "pitiriasis", + "mendorongsupaya", + "simphisis", + "selioma", + "rasa_gayat", + "cahayakan", + "paresis", + "seliuh", + "gangren_dingin", + "acorea", + "paralisis", + "lelasan", + "disthimia", + "tidak_bertidur", + "kemandulan", + "kederiaan", + "biasanya_karena", + "multipleks_disostosis", + "sesuatu_yang_dihasrati", + "tumbesaran", + "tak_terkait_kehilangan_pendengaran", + "perdarahan", + "choriomeningitis", + "talipes", + "gastritis_kronis", + "ketakdayaan", + "menjadi_merah_muka", + "servikitis", + "gravidasi", + "kepeningan", + "masa_kehamilan_ektopik", + "sumbatan", + "fluorosis", + "parametritis", + "automysophobia", + "keadaan_pingsan", + "barah_mulut", + "terpotong", + "selap", + "cosmida", + "rubella", + "tidak_ada_refleks", + "epidermolysis_bullosa", + "tetralogi_fallot", + "pansinusitis", + "kesumpekan", + "pain", + "melecur", + "kolesistitis", + "gargoylisme", + "ortochorea", + "keadaan_mabuk", + "goiter", + "coret", + "virus_ebola", + "diestrus", + "moluskum", + "bunyaviridae", + "metasiesis", + "akinesis", + "kurang_berhasil", + "menjadi_usang", + "merembesi", + "getah_kayu", + "setengah_gila", + "hal_menggerakkan_jantung", + "atau_fonem_r_diucapkan_sebagai_l", + "heterotaksi", + "the_passion_of_the_christ", + "purpura", + "thirotoksikosis", + "polyarteristis_nodosa", + "kurang_kasih_sayang", + "rasa_pedih", + "kretinisme", + "aerodontalgia", + "schizoid", + "kambuh", + "hermaphrodisme", + "vasovesiculitis", + "inversi", + "odinofagia", + "suatu_kemalangan", + "klinodaktili", + "fonofobia", + "thalasemia", + "furunkulosis", + "nimpolepsi", + "laringitis", + "keadaan_terjaga", + "kolik_saluran_pencernaan", + "laminitis", + "blastositoma", + "autoimunitas", + "rasa_mual", + "parasitemia", + "paraplegia", + "keadaan_tidak_cergas", + "bisa_gatal", + "semua_yang_merusak", + "kaki_gajah", + "anestrum", + "kemudikan", + "keterujaan", + "stigmata", + "mengcopy", + "pakiderma", + "appendikitis", + "kontusi", + "kelemahlunglaian", + "parestesi", + "mengapakan", + "menjangkar", + "anastesia", + "sawan", + "mengantup", + "pirosis", + "umum_pada_remaja", + "herpangia", + "jangkitan", + "virus_west_nile", + "melecup", + "plasmasitoma", + "valvulitis", + "mielitis", + "sangkak", + "pollinosis", + "peracunan", + "kedongkolan", + "laparosele", + "smut", + "odontalgia", + "leper", + "lisinemia", + "pembengkakan", + "togaviridae", + "orthopnea", + "schistosomiasis", + "tachikardia", + "kerlingan", + "androphobia", + "telah_putus", + "mastopati", + "bisa_jadi_tanda_lahir", + "umum_pada_orang_tua", + "dissinergia", + "aerombolisme", + "terlalu_banyak_makan_karbohidrat_kurang_protein", + "mi", + "pirai", + "biasanya_karena_alergi", + "seperti_pada_aterosklerosis", + "pembengkokan", + "rasa_sakit", + "polipus", + "biasanya_gejala_sakit_saluran_kencing", + "seperti_raspberi", + "suatu_pemborokan", + "alastrim", + "klorosis", + "terutama_disebabkan_kondisi_syaraf", + "virus_tanaman", + "biasa_pada_payudara", + "mengalami_keruntuhan", + "kondroma", + "ketaknormalan", + "mememarkan", + "suatu_bentuk_tuberkolosis", + "aura", + "pencetusan", + "suatu_gejala_dari_keadaan_alergi", + "roset", + "garukan", + "brachydactylia", + "tan", + "selularitas", + "lipidosis", + "sting", + "blastoma", + "bertambah_sengit", + "mencurah", + "morphea", + "oksisephali", + "seperti_tulang", + "laserasi", + "biasanya_terkait_anemi", + "aminoasiduria", + "ophidisme", + "mono_framework", + "beberapa_penyakit_cemara", + "berbara", + "plumbisme", + "protanopia", + "emmetropia", + "peliosis", + "break", + "karsinoid", + "ginekomastia", + "anthraks", + "kegemasan", + "pansitopenia", + "kejulingan", + "umum_pada_bayi", + "merupakan_ciri_saat_melahirkan", + "kaki_dan_muka", + "naik_merah", + "virus_wtv", + "allamah", + "trauma", + "kernikterus", + "keadaan_sakit", + "chancroid", + "buah_berangan", + "dan_jaringan_konektif", + "tirosinemia", + "bradikardia", + "uraemia", + "dimulai_dari_wajah", + "gondongan", + "kuru", + "kistitis", + "kepialu", + "ketandusan", + "hal_tanpa_gairah", + "bukan_karena_penyakit", + "hawar", + "bermotokar", + "kiloderma", + "fotoretinitis", + "sekuela", + "sitomegalovirus", + "proktitis", + "sitopenia", + "selaran_matahari", + "semakin_hangat", + "ketakcernaan", + "pandangan_monokromatik", + "hangitkan", + "keempukan", + "ekstrasistol", + "noma", + "materialisme", + "boleh_tidur_dalam", + "hemeralopia", + "pokok_berangan", + "kastanya", + "essiesis", + "astrafobia", + "torpiditas", + "chorea_huntington", + "cucuran", + "eksim", + "burut", + "jerawat", + "polisomi", + "ulser", + "roseola_infantilis", + "tetikus", + "flare", + "petekia", + "polimiositis", + "demineralisasi", + "kanser", + "distensi", + "berotot", + "virus_junin", + "hermaphroditisme", + "demielinasi", + "bunyavirus", + "sedang_dalam_bentuk_atau_dalam_kondisi", + "anthraks_inhalasi", + "gangguan_saraf", + "ahli_pengasas", + "distrofi", + "taksekataan", + "parvovirus", + "salmonella", + "dekstrokardia", + "jaundis", + "kalsifikasi", + "krup", + "indisposisi", + "rasa_kebas", + "tritanopia", + "virus_variola", + "normotermia", + "rubuh", + "pemumiaan", + "naik_motor", + "kolik_timah_hitam", + "distropi_muskular", + "sesuatu_yang_sentimental", + "pencekikan", + "albuminura", + "tak_bisa_bergerak_sendiri_dan_bereaksi_atas_rangsangan", + "kalositi", + "esotropia", + "eventrasi", + "katarak_kortikal", + "maloklusi", + "bagian_dari_sesuatu", + "rosasea", + "penyakit_cushing", + "sangat_bingung", + "atau_saluran_pencernaan", + "seperti_pada_kencing_manis", + "suatu_tumor_abdominal", + "melukakan_perasaan", + "taphephobia", + "paritas", + "malaria", + "lalu_gagal_ginjal", + "tarantisme", + "palsi", + "gout", + "kongesi", + "mastoiditis", + "pada_anak_anak", + "biasanya_diperoleh_ketika_berenang", + "bungkuk" + ], + "RELIGION": [ + "albigensis", + "zen", + "donatisme", + "shinto", + "manichaeisme", + "calvinisme", + "hinayana", + "katarisme", + "islam", + "namun_bukan_buddha_dan_gaib", + "salafiyah", + "christian_science", + "ismailiyah", + "maniisme", + "wedanta", + "syinto", + "agama_buddha_theravada_punah_di_india", + "kresnaisme", + "ditandai_dengan_pemujaan_roh_nenek_moyang_dan_roh_ala", + "kesufian" + ], + "LOCATION": [ + "al_jazeera", + "terimakasih", + "s_train", + "da_gamma", + "ruang_pandang", + "st_eustatius", + "danau_edward", + "vespucci", + "la_plata_buenos_aires", + "park", + "hari_colombus", + "sungai_yangtze", + "makasih", + "corpus_christi", + "u.s", + "cara_pamungkas", + "bimasakti", + "ke_pusat_bandar", + "hari_santo_martin", + "al_haram_al_sharif", + "sinterklas", + "kota_terdalam", + "cepatlah", + "juarez", + "piet_mondrian", + "selat_melaka", + "santa_fe", + "sint_maarten", + "angkatan_darat_amerika_serikat", + "centennial_state", + "waktu_bersenang_senang", + "cape_verde", + "marie_grosholtz", + "trois_rivi\u00e8res", + "allahu_akbar", + "sleeping_beauty", + "samudra_hindia", + "saint_patrick", + "the_states", + "saint_george", + "mary_magdalene", + "land", + "saint_vincent", + "hemisfera_barat", + "blue_mountains", + "joseph_louis_gay_lussac", + "tussaud", + "terusan_utara", + "holy_land", + "hari_tahun_baru", + "gay_lussac", + "mulai_dari_tibet_ke_laut_cina", + "mondrian", + "selat_inggeris", + "bank_sentral", + "tanjung_horn", + "saint_christopher", + "bank_pusat", + "saint_nicholas", + "tempat_percutian", + "medan_gaya", + "cape_of_good_hope", + "usa", + "the_city", + "hari_sebelum_krismas", + "saint_lucia", + "malam_natal", + "saint_peter", + "hat_yai", + "arena", + "kriss_kringle", + "danau_superior", + "sri_lanka", + "hari_tahun_baharu", + "al_haram_asy_syarif", + "villa_lobos", + "southern_cross", + "gunung_karmel", + "tahun_baru", + "the_rolling_stones", + "cordon_bleu", + "gunung_carmel", + "saint_lawrence", + "medan_pertarungan", + "tanah_lapang", + "downtown", + "virgin_mary", + "court", + "kerajaan_tentera", + "ditandai_oleh_hematuria", + "tentera_udara", + "rumah_sakit_gila", + "the_holy_see", + "angkatan_udara", + "heitor_villa_lobos", + "selat_inggris", + "hari_santo_martinus", + "tanjung_verde", + "al_ain", + "santa_claus", + "bandar_baru", + "apostle_paul", + "tasik_superior", + "hari_columbus", + "st_patrick", + "iron_cross", + "never_never" + ], + "FOOD": [ + "beligo", + "pastri", + "ati_angsa", + "cara_membuat_kuih_dan_pastri", + "agar_agar_sari_anggur", + "mousse", + "saus_kranberi", + "pai_epal", + "es_krim_neapolitan", + "kundur", + "desert", + "sugarloaf_mountain", + "ati_ayam", + "rutbir", + "gabah", + "stimbot", + "dan_sandung_lamur", + "es_teh", + "kaki_anak_domba", + "sarapan_ringan", + "capsicum", + "kaki_kalkun", + "sarapan", + "lemonad", + "has_dalam", + "rebung", + "gulali", + "air_kelapa", + "saus", + "kaki_kodok", + "teh_ais", + "farina", + "tulang_t", + "mie_telur", + "es_krim_pisang", + "bersarapan", + "es_kopi", + "rasanya_sedikit_pahit", + "bir_dari_munich", + "chili", + "sengkel", + "chile", + "croasang", + "danablu", + "saus_cranberi", + "teh_herbal", + "daun_salam", + "menyarap", + "teh_manis", + "sukade", + "capcai", + "es_susu", + "ati_anak_sapi", + "sancan", + "angsu", + "es_krim", + "has_luar", + "kon_aiskrim", + "masih_kuat", + "kari_kambing", + "teh_hitam" + ], + "PLANT": [ + "hibiscus_syriacus", + "kacang_parang", + "melissa", + "baru_cina", + "jelatang", + "komak", + "srikaya", + "the_joshua_tree", + "helianthus", + "kubis", + "kacang_botor", + "vanili", + "solanaceae", + "bengkuang", + "chamomile", + "tengguli", + "kapasan", + "arabidopsis_thaliana", + "cendana", + "artist", + "kayu_berangan", + "jeringau", + "beri_hitam", + "gentiana_lutea", + "kenanga", + "sakura", + "plum", + "candida_albicans", + "luluabourg", + "mustard", + "calophyllum_inophyllum", + "kranberi", + "salayar", + "sitomembran", + "sirih_gading", + "karot", + "allamanda_cathartica", + "zaitun", + "amanita_muscaria", + "silybum", + "leunca", + "trengguli", + "talas_belitung", + "kamperfuli", + "kananga", + "prem", + "jejarum", + "pokokpopi", + "nogales", + "pinang", + "phytophthora_infestans", + "gilas", + "rumbia", + "flamboyan", + "seruni", + "blackberry", + "beberapa_penyakit_cemara", + "rambusa", + "ki_hujan", + "terulak", + "dewadaru", + "kuda_perang", + "blumkol", + "bunga_bungan", + "arum", + "saccharomyces_cerevisiae", + "boletus_edulis", + "juwawut", + "buluh_minyak", + "dudaim", + "marum", + "sawi", + "tanacetum_parthenium", + "cervil", + "kedaung", + "manuskrip_papirus", + "mentha_longifolia", + "nasturtium", + "klematis", + "yew", + "enokitake", + "pering", + "pandan_duri", + "cinnamomum_cassia", + "netel", + "tusam", + "gembolo", + "buah_berangan", + "sengkuang", + "euphorbia_milii", + "ranti", + "magnolia", + "palem", + "dadap", + "racun_tanaman_merambat", + "pokok_getah", + "pulai", + "pancar", + "bunga_forget_me_not" + ], + "DATE": [ + "cukup_umur", + "waktu_nostalgia", + "tidak_lama_lagi", + "hari_kemenangan_eropa", + "masa_keemasan", + "hari_suci_kristen", + "setengah_abad", + "hari_kemerdekaan_texas", + "masa_menstruasi", + "tahun_komariah", + "hari_pemilihan", + "waktu_standard_alaska", + "masa_hukuman", + "waktu_kerja_program", + "hari_libur_bank", + "hari_sial", + "tahun_sipil", + "saat_lompat", + "hari_victoria", + "kalendar_komariah", + "waktu_kosmik", + "setiap_saat", + "hari_hallowmass", + "hari_bendera_argentina", + "pertengahan_januari", + "hari_raya_semua_orang_kudus", + "masa_wakil_presiden", + "waktu_setempat", + "hari_raya_puasa", + "era_kristian", + "hari_pelantikan", + "tahun_akademik", + "waktu_universal_terkoordinasi", + "periode_orbit", + "bulan_biru", + "waktu_musik_duple", + "tahun_kabisat", + "waktu_residens", + "hari_besar", + "hari_pertandingan_atletik", + "hari_peringatan_veteran", + "hari_ayah", + "hari_persemakmuran", + "minggu_natal", + "anak_bulan", + "hari_siderial", + "hari_raya_haji", + "hari_angkatan_bersenjata", + "hari_rogasi", + "waktu_universal", + "terpenting", + "hari_perserikatan_bangsa_bangsa", + "waktu_musik_triple", + "masa_prima", + "hari_pernikahan", + "the_day_after_tomorrow", + "apabila_sudah", + "waktu_standard_atlantik", + "hari_angkatan_tentera", + "lewat_batas", + "hari_kanada", + "hari_kebangsaan", + "hari_bastile", + "tahun_masihi", + "waktu_transmisi", + "waktu_terakhir", + "dengan_tidak_lama", + "in_time", + "hari_h", + "hari_memorial", + "hari_peringatan", + "waktu_sibuk", + "hari_orang_suci", + "hari_libur_keagamaan", + "hari_pan_amerika", + "hari_bendera", + "hari_groundhog", + "awal_waktu", + "hari_dominion", + "waktu_pertanyaan", + "hari_ibu", + "hari_santo_patrick", + "hari_april_fool", + "waktu_tempuh_perjalanan", + "tahun_matahari", + "hari_suci_yahudi", + "bulan_anomali", + "hari_dalam_seminggu", + "hari_militer", + "konstanta_matahari", + "tahun_platonik", + "waktu_standard_timur", + "waktu_sarapan", + "tahun_anomali", + "renaisans_italia", + "lama_betul", + "hari_kemenangan", + "waktu_paruh", + "pada_mulanya", + "tahun_kosong", + "hari_pengakuan", + "masa_noenatal", + "setengah_jam", + "waktu_standard_hawaii", + "waktu_habis", + "new_moon", + "hari_presiden", + "waktu_kedatangan", + "perkelahan", + "hari_raya_aidilfitri", + "hari_pidato", + "hari_perjanjian", + "de_nachtwacht", + "sekilat", + "bulan_baru", + "masa_pensiun", + "hari_kabisat", + "waktu_prima", + "waktu_reaksi", + "satu_kali", + "masa_perdana", + "hari_pasar", + "hari_st_patrick", + "waktu_siderial", + "waktu_bumi", + "hari_veteran", + "hari_dingin", + "lebaran", + "revolusi_perindustrian", + "waktu_semesta_berkoordinat", + "d_day", + "hari_kemerdekaan", + "zaman_kejayaan", + "waktu_greenwich", + "hari_para_orang_kudus", + "waktu_standard_bering", + "hari_panas", + "zaman_keemasan", + "tahun_lompat", + "hari_saint_agnes", + "sepanjang_waktu", + "hari_perjuangan", + "hari_raya_aidiladha", + "waktu_sideris", + "waktu_standar", + "suatu_masa_dulu", + "lusa", + "waktu_keberangkatan", + "hari_gereja", + "hari_kelahiran_lincoln", + "tahun_utama", + "pertama_sekali", + "waktu_min_greenwich", + "waktu_standard_pasifik", + "waktu_menonton_tv", + "hari_boxing", + "waktu_tutup", + "tahun_fiskal", + "waktu_perdana", + "corpus_christi", + "rata_rata_pernafasan", + "bulan_purnama", + "waktu_standard_pusat", + "waktu_tempuh", + "masa_sulit", + "kerajaan_baru", + "hari_menanam_pohon", + "masa_masa_sulit", + "hari_pengakuan_dosa", + "hari_guy_fawkes", + "di_era_kristen", + "hari_bapa", + "hari_bastille", + "hari_kue_pancake", + "bulan_penuh", + "tahun_siderial" + ], + "ANIMAL": [ + "bekerja_dengan_rajin", + "probiotik", + "nasar", + "cat", + "butang_kepalalat", + "kera_bekantan", + "the_raven", + "bulik", + "berang_berang", + "tebuan", + "kongkang", + "cangak", + "heron", + "berdekut", + "bis_australia", + "lemmus_lemmus", + "bullfinch", + "genus_sperilium", + "kunduz", + "si_pemalas_darat", + "menjadi_merah", + "canis_minor", + "gagak", + "badger", + "pisces", + "mammal", + "falkon", + "berkukur", + "berkik", + "belangkas", + "swift", + "mamalia", + "lactobacillus_acidophilus", + "seguni", + "virus_herpes_simpleks", + "berkek", + "ibu_suri", + "virus_epstein_barr", + "virus_varicella_zoster", + "surai", + "xuan_wu", + "artiodaktil", + "virus_parainfluensa", + "wiesel", + "baqa", + "kerawai", + "raven", + "betok", + "mentibang", + "virus_kentang", + "mink", + "menjangan", + "torani", + "artropod", + "penyakit_bakteri_akut_pada_kuda", + "penyengat", + "malacopterigian", + "hound", + "teh_hijau", + "kerbau", + "sesorok", + "virus_machupo", + "berkuku", + "arthoropoda", + "bumblebee", + "mengkira", + "stieglitz", + "sistem_syaraf", + "variola_minor", + "pungguk", + "ketitir", + "banteng", + "manusia_peking", + "feret", + "wren", + "virus_marburg", + "kelomang", + "donald_duck", + "kupang", + "perkici_pelangi", + "moose", + "conraua_goliath", + "virus_varisela_zoster", + "millipede", + "virus_lassa", + "herpes_zoster", + "mempengaruhi_kulit", + "beaver", + "kodok", + "kelayang", + "burung_sualo_api", + "muntah_hitam", + "mentok", + "kowak", + "bertelapuk", + "camar", + "virus_binatang", + "kokok", + "mendekut", + "genus_stafilococus", + "penyakit_virus_ebola", + "bejar", + "belitung", + "bengkatak", + "kaki_seribu", + "yorkshire_terrier", + "kuntul", + "raja_udang", + "selar_bentong", + "gonggok", + "tabuhan", + "vole", + "berkokok", + "grouse", + "kondor", + "katak", + "ikan_dari_mississippi", + "mentadak", + "artropoda", + "eider", + "capiz", + "kondoz" + ], + "QUANTITY": [ + "dua_puluh_sembilan", + "keadaan_oksidasi", + "rupee", + "dua_puluh_enam", + "dua_puluh_dua", + "kaki_persegi", + "dua_puluh_satu", + "dua_puluh_pitu", + "sterling", + "won_korea_selatan", + "keadaan_pengoksidaan", + "dua_puluh_delapan", + "konstanta_kesetimbangan", + "dua_puluh_lapan", + "tiga_hukum_robot", + "tiga_kerajaan", + "pelataran_parkir", + "jumlah_sperma", + "dua_puluh_empat", + "sejumlah_tertentu", + "dua_puluh_telu", + "satu_likur", + "shilling", + "dalam_jumlah_tertentu", + "satu_perempat", + "tempat_kurungan_binatang_yang_ditahan", + "satu_persejuta", + "dinar", + "tiga_likur", + "krona", + "setengah_dozen", + "satu_persembilan", + "won_korea_utara", + "ton", + "dua_puluh_tujuh", + "tempat_kereta_berhenti", + "selikur", + "sepertujuh", + "sepertiga", + "riyal", + "tahun_cahaya", + "zaman_tiga_negara", + "satu_pertiga", + "mark_jerman", + "satuan_pengukuran", + "lima_likur", + "memodulasikan", + "g", + "jumlah_yang_pasti", + "yang_kelima", + "dua_puluh_lima", + "elektronvolt", + "rial", + "dua_puluh_tiga", + "rupee_india", + "panjang_tubuh", + "krone", + "jumlah_yang_diperkirakan", + "jumlah_kepala", + "pound", + "ke_seratus", + "keti", + "tempat_kurungan_binatang_yg_ditahan", + "dua_likur", + "lima_ratus", + "satu_perseratus", + "satu_pertujuh", + "franc_swiss", + "empat_likur", + "perenam", + "anders_celsius", + "tempat_kurungan_binatang", + "tiga_hukum_robotik", + "ezra_loomis_pound", + "jumlah_relatif" + ], + "JOB": [ + "mahaguru", + "pelakon", + "pereka", + "cegahan", + "penjahit", + "guru", + "pelebur", + "mercator", + "sukarelawan", + "ibu_tumah_tangga", + "the_nanny", + "mandur", + "shearer", + "sentinel", + "komandan", + "biskop", + "forester", + "penjaring", + "pengkonduksi", + "pengaturcara", + "pemeran", + "speaker", + "penganalisa", + "berhadir", + "saintis", + "sersan", + "pengepak", + "sutradara", + "pustakawan", + "serikandi", + "kelautan", + "ke_dua", + "miller", + "manajer", + "penganyam", + "kolonis", + "wirausahawan", + "tandil", + "residen", + "bersukarela", + "pengusaha", + "tukang_tembikar", + "peniaga", + "adang", + "seorang_pembuat_peta", + "berkawal", + "koordinator", + "kecelakaan_cerebrovascular", + "lascar", + "cooper", + "sipir", + "pendiri", + "sexton", + "renjer", + "mistar", + "masinis", + "berada_dalam_comberan", + "obstetrisian", + "koperal", + "don", + "king", + "fomen", + "peternak", + "dirahsiakan", + "mahout", + "penulis", + "menakhlikkan", + "carver", + "the_police", + "penghibur", + "intern", + "dimasak", + "seorang_penulis_kaligrafi", + "skinner", + "pemelihara", + "pretor", + "bentara", + "petahana", + "tauke", + "paramedis", + "narapati", + "lister", + "pengendali", + "wasit", + "penghilang", + "pentafsir", + "peservis", + "panglima", + "distributor", + "seorang_gadis_pengawas", + "pelobi", + "kanselir", + "barbir", + "grip", + "para", + "pengajar", + "menggadaikan", + "mendada", + "fuller", + "sensei", + "thatcher", + "pengutus", + "currier", + "cook", + "couturier", + "kastroli", + "mastermind", + "coret", + "kerahan", + "land", + "hakim", + "bertanak", + "penaip", + "tempat_membawa_barang", + "kuartermaster", + "vigilante", + "pekilang", + "demang", + "anemer", + "penguasa", + "sahaya", + "sambungkan", + "butler", + "pensyarah", + "pentadbir", + "sekon", + "paralegal", + "pengambin", + "teritorial", + "pitman", + "kurator", + "qadi", + "penguji", + "si_piutang", + "brigadier", + "pengurus", + "rekan", + "novelis", + "kamikaze", + "wheeler", + "seseorang_yang_mengedit", + "penari", + "bendahari", + "menjeramah", + "the_advocate", + "adiperagawan", + "bidak", + "penskor", + "laksamana", + "merinyu", + "amberal", + "page", + "tukang_batu", + "volenter", + "korporal", + "seorang_pembuat_perahu", + "mayor", + "mejar", + "sculptor", + "perabu", + "pengilustrasi", + "letnan", + "meteorologis", + "kuak", + "pegawai_polis", + "pelaksana", + "pengilang", + "apopleksi", + "peninju", + "menginternir", + "syerif", + "master", + "the_guardian", + "kataloger", + "pengagih", + "stroke", + "tukang_labu", + "industrialis", + "seorang_spesialis_anestesi", + "memperhubungkan", + "cengkut", + "kartunis", + "penterjemah", + "penasehat", + "akuntan", + "mandarin", + "reguler", + "pengatur", + "wataniah", + "pramugara", + "walikota", + "herder", + "pengasuh", + "mason", + "kerani", + "fowler", + "hussar", + "pengalir", + "stoker", + "seorang_pembuat_kue", + "pengusung", + "dayungan", + "mengelui", + "merentungkan", + "loyar", + "jaksa", + "besteler", + "rabi", + "mencontohkan", + "desainer", + "komander", + "sitter", + "pengucap", + "pengoperasi", + "pastor", + "berada_dalam_kubangan", + "uskop", + "bermusim", + "kolonel", + "pengawas_hutan", + "guner", + "dosen", + "regulator", + "menggembala", + "brigedier", + "cartwright", + "marsyal", + "tukang_langsir", + "canselor", + "ibu_susu", + "eksekutif", + "paramedik", + "kopral", + "seorang_pembuat_roti", + "gaucho", + "beadle", + "ibu_susuan", + "pengemban", + "jelata", + "perajurit", + "pengecat", + "menggadai", + "penunjuk_perasaan", + "penganalisis", + "malim", + "the_economist", + "seaman", + "seniwati", + "broker", + "mendalangi", + "the_broker_si_broker", + "wetter", + "carter", + "porter", + "seorang_kritikus_lukisan", + "periwayat", + "merekayasa", + "tukang_gerobak", + "pengkhutbah", + "setiausaha", + "barista", + "gauco", + "pengedit", + "gabenor", + "penakik", + "bergadai", + "warrior", + "barber", + "pemalsu_wang", + "pesawah", + "perakam", + "pelancung", + "the_hangover", + "peraih", + "penala", + "menghulurkan_tangan", + "doc", + "bermasak", + "saudagar", + "the_boxer", + "tidak_lazim", + "yang_menghasilkan", + "pengemudi", + "petinju", + "the_machinist", + "pengandam", + "usher", + "messenger", + "setiausaha_agung", + "pramusiwi", + "serdadu", + "sudah_tahu", + "mangkubumi", + "hulubalang", + "pengail", + "pengerusi", + "pelanggar_mogok", + "cakupan", + "pedagang", + "pendaftar", + "marbut", + "pengisih", + "the_interpreter", + "rabai", + "salatin", + "akauntan", + "blaster", + "pengulin", + "pramugari", + "ajudan_jenderal", + "muhami", + "pengelola", + "bidan", + "partikelir", + "pengedar", + "marshall", + "penggergaji", + "pemogok", + "sub", + "the_independent", + "turner", + "menyabun", + "berganding", + "esquire", + "pengukir", + "pendandan", + "sungai_para", + "asisten", + "jumpelang", + "pengutip", + "memperkaitkan", + "kardiolog", + "brigedier_jeneral", + "pengeluar", + "bintara", + "angin_ahmar" + ], + "RELIGION_MEMBER": [ + "penggoncang", + "anabaptist", + "guru", + "augustine", + "the_hindu", + "kakanda", + "moor", + "mandean", + "dunker", + "fransiskan", + "brother", + "seorang_misionaris_kristen", + "mormon", + "shivaist", + "mengufurkan", + "kanda", + "orang_protestan", + "the_apostle", + "mullah", + "puritan", + "sunni", + "parsi", + "wahabi", + "jihadis", + "adinda", + "christian_scientist", + "shaktis", + "kangmas", + "akang" + ], + "LANGUAGE": [ + "dari_jauh", + "bengali", + "bahasa_avestan", + "bahasa_tatar", + "bahasa_lithuania", + "bahasa_macedonia", + "kashmiri", + "kongo", + "bahasa_burma", + "smith", + "akan", + "greek", + "guranani", + "bahasa_sardinia", + "bahasa_romania", + "bahasa_albania", + "ganda", + "gilap", + "bahasa_makedonia", + "wicara", + "biri_biri_betina_dewasa", + "french", + "ibrani", + "malayalam", + "keinggrisan", + "sinhala", + "hindi", + "belandawi", + "assamese", + "herero", + "bahasa_rumania", + "divehi", + "wallon", + "walloon", + "benggali", + "esperanto", + "rumawi", + "biri_biri_betina", + "katalan", + "bahasa_malayalam", + "lao", + "bahasa_amhar", + "speech", + "ido", + "kazakh", + "tonga", + "kannada" + ], + "FAC": [ + "arnold_schoenberg", + "saint_james_the_apostle", + "schoenberg", + "tanjung_harapan", + "balai_polis", + "sekolah_rendah", + "tiga_puluh_tiga", + "schonberg", + "peter_i", + "fernand_leger", + "plaza", + "saint_joseph", + "peter_the_great", + "hari_saint_joseph", + "memperluaskan", + "peti_tiang", + "max_muller", + "peter_i_dari_rusia", + "gereja_katolik_roma", + "saint_lucia", + "st_james", + "empat_musim", + "arnold_schonberg", + "sekolah_kedokteran", + "titus_livius", + "duane", + "saint_peter", + "uncit", + "st_james_the_apostle", + "gereja_roman_katolik", + "besar_besarkan" + ], + "SOC_ECO_CLASS": [ + "menggisi", + "center", + "samurai", + "kutip", + "seorang_pilihan", + "berkuli", + "pasaran_gelap", + "pasar_gelap", + "golongan_bangsawan", + "proletariat", + "bekerja_bertungkus_lumus", + "meruntih", + "jati", + "kearistokrasian", + "sosialit", + "perburuhan", + "seludupan", + "keningratan", + "sedikit_saja" + ], + "GPE": [ + "medan_bandar", + "hak_asasi_manusia", + "hari_st_george", + "gunung_kerinci", + "selamat_pulang", + "st_christopher", + "st_peter", + "serai_wangi", + "bunda_kesedihan", + "st_vitus", + "matius", + "st_jude", + "kotte", + "dar_es_salaam", + "taman_industri", + "gedung_putih", + "sint_maarten", + "santo_peter", + "st_matthew", + "bunda_dari_kesedihan", + "balai_balai", + "air_panas", + "hak_asasi", + "hagia_sophia", + "saint_peter", + "parakletos", + "saint_andrew", + "simon_peter", + "s\u00e3o_tom\u00e9", + "santo_george", + "gran_canaria", + "saint_george", + "aya_sophia", + "simon_petrus", + "holy_land", + "santo_nicholas", + "gunung_tai", + "laut_merah", + "al_andalus", + "sugarloaf_mountain", + "vinh_long", + "la_gomera", + "hari_valentine", + "st_louis", + "hari_kasih_sayang", + "kristoforus", + "st_john_the_baptist" + ], + "PRODUCT": [ + "the_hunger_games", + "justin_bieber", + "new_zealand", + "fyodor_dostoyevsky", + "selandia_baru", + "ruhul_qudus", + "al_jazeera", + "john_lackland", + "diego_garcia", + "pokok_krismas", + "malam_keduabelas", + "hari_santo_stefanus", + "cape_horn", + "twelfth_night_or_what_you_will", + "membuat_hubungan_pendek", + "tanjung_horn", + "s_train", + "julius_caesar", + "saint_vincent", + "st_george\u2019s", + "the_star_spangled_banner", + "mary_magdalene", + "don_quixote", + "sachsen_anhalt", + "sirkuit", + "die_hard", + "city_hall", + "konstantin_stanislavsky", + "the_lord_of_the_rings", + "parakletos", + "tiga_kerajaan", + "father_christmas", + "la_dolce_vita", + "berlalu_bersama_angin", + "deutsche_welle", + "gong", + "st_mary_magdalene", + "membuat_sirkuit_pendek", + "north_rhine_westphalia", + "saint_nicholas", + "ferdinand_magellan", + "roh_kudus", + "mario_andretti", + "sungai_san_joaquin", + "pelengkung_kemenangan", + "san_sebastian", + "s\u00e3o_tom\u00e9_dan_pr\u00edncipe", + "pohon_natal", + "the_hitchhiker's_guide_to_the_galaxy", + "bohongan", + "hari_boxing", + "empat_musim", + "ibukota_grenada", + "nordrhein_westfalen", + "deux_fr\u00e8res", + "peringatan_pernikahan_perak", + "saint_peter", + "waktu_terakhir", + "novo_mesto" + ], + "UNION": [ + "itu", + "organisasi_profesional" + ], + "PERSON": [ + "blessed_virgin", + "prince_albert", + "julius_caesar", + "ha_ha", + "paul_the_apostle", + "st_dominic", + "al_gore", + "seleucus", + "h_g_wells", + "albert_francis_charles_augustus_emmanuel", + "saint_vincent", + "st_mary_magdalene", + "i_ching", + "e_o_wilson", + "st_ambrose", + "igor_ivanovich_sikorsky", + "saint_ambrose", + "margaret_munnerlyn_mitchell", + "e_e_cummings", + "edward_osborne_wilson", + "roger_eliot_fry", + "philip_ii_of_macedon", + "walther_richard_rudolf_hess", + "saul_of_tarsus", + "willard_frank_libby", + "george_v", + "al_amin", + "igor_sikorsky", + "seleucus_i_nicator", + "edward_franklin_albeen", + "carl_david_anderson", + "gaius_julius_caesar", + "zeno_of_citium", + "maxwell_anderson", + "boletus_edulis", + "dominikus", + "yo_yo", + "rudolf_hess", + "tiga_puluh_dua", + "dr_watson", + "apostle_of_the_gentiles", + "herbert_george_wells", + "timur_tenggara" + ], + "POLITICAL_PARTY_MEMBER": [ + "menshevik", + "populis", + "sungai_republican" + ], + "RACE": [ + "dari_lahir", + "indian_airlines", + "french", + "abiaz", + "asmaradanta", + "latin", + "anak_kelahiran", + "warga_afrika", + "pasifik_selatan", + "bumiputera", + "white", + "bangsa_jepang", + "sungai_putih", + "ganih", + "negro", + "kazakh", + "keputihan" + ], + "GENDER": [ + "si_genit", + "matron", + "si_manis", + "dame", + "pak_tua", + "male", + "mas_isle", + "transgender", + "ibu_tua" + ], + "POLITICAL_PARTY": [ + "gironde", + "partidul_social_democrat", + "partai_konservatif", + "partai_sosialis", + "partai_whig", + "kuomintang", + "partai_buruh", + "partai_demokratik_sosial", + "partai_demokratik_republik", + "daftar_partai_demokrat", + "partai_nasional", + "pasukan_lawan", + "parti_buruh_jerman_sosialis_nasional", + "pihak_pembangkang", + "parti_buruh", + "parti_kebangsaan", + "parti_demokrat", + "nationalsozialistische_deutsche_arbeiterpartei", + "parti_konservatif" + ], + "BIO_CHEM_ENTITY": [ + "c_reactive_protein", + "edward_thatch" + ], + "PERSON_PRONOUN": [ + "i", + "he", + "daku", + "kepunyaanku", + "him", + "berengkau", + "melombong", + "kelian", + "me", + "milikku", + "kalian", + "engkau", + "beliau", + "us" + ], + "TITLE": [ + "encik", + "sir", + "mr", + "ms" + ], + "LAW": [ + "hukum_romawi", + "hukum_sipil", + "mahkamah_agung", + "hukum_internasional", + "bukan_upacara", + "undang_undang_antarabangsa", + "mahkamah_persekutuan" + ], + "EVENT": [ + "grand_prix" + ], + "OTHER_PRONOUN": [ + "it" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "pelakon": "petugas", + "aktris": "pelakon", + "seniwati": "pelakon", + "mak_su": "tetak", + "bibik": "bapa_saudara", + "mak_cu": "paman", + "bonda": "ayr", + "mak_ngah": "pakcik", + "mak_bongsu": "pakcik", + "bibi": "paman", + "mak_long": "tetak", + "mak_usu": "paman", + "mak_saudara": "bapa_saudara", + "ibu_saudara": "pak_cu", + "mak_cik": "bap", + "mak_busu": "mamang", + "makcik": "pak_cik", + "mempelai_perempuan": "pengantin_lelaki", + "pengantin_perempuan": "mempelai_lelaki", + "pengantin": "pengantin_lelaki", + "bride": "pengantin_lelaki", + "pengusaha_wanita": "usahawan", + "ahli_perniagaan": "usahawan", + "poussin": "bung", + "anak_ayam": "bung", + "anak_burung": "bung", + "putri": "pangeran", + "bayi_perempuan": "anak_lelaki", + "anak_perempuan": "putera", + "amoi": "anak_laki_laki", + "panik": "anak_laki_laki", + "kanak_kanak_perempuan": "putera", + "puteri": "prince", + "anak_gadis": "putera", + "filia": "anak_lelaki", + "budak_perempuan": "anak_lelaki", + "female_off_spring": "anak_laki_laki", + "istri_adipati": "duke", + "duchess": "adipati", + "maharani": "kaisar", + "maharatu": "khakan", + "femme_fatale": "tukang_sihir", + "pemikat": "tukang_sihir", + "perempuan_sihir": "penyihir", + "penggoda": "tukang_sihir", + "wanita_penggoda": "tukang_sihir", + "ahli_sihir_perempuan": "tukang_sihir", + "kike": "laki_laki", + "\u0628\u062a\u064a\u0646\u0627": "male", + "feminin": "\u062c\u0646\u062a\u0646", + "\u06a4\u0631\u0645\u06a4\u0648\u0627\u0646": "pria", + "betina": "male", + "mak_we": "bujang", + "genta": "pak_we", + "cucu_perempuan": "biadi", + "srikandi": "perwira", + "heroin": "hero", + "wirawati": "hero", + "tuan_rumah": "pengurus_rumah_penginapan", + "kak": "komrad", + "kajang_kaca": "marquis", + "isteri_marquis": "marquis", + "cik": "sir", + "terbebas": "encik", + "luncas": "sir", + "miss_a": "sir", + "tertinggal": "sir", + "merindui": "encik", + "berkurangan": "cikgu", + "merindukan": "sir", + "tidak_ada": "encik", + "terasa_kehilangan": "sir", + "perempuan_yang_berkuasa": "ketua_pasukan", + "perempuan_yg_berkuasa": "master", + "wanita_simpanan": "komodor", + "perempuan_simpanan": "komodor", + "cik_puan": "memperoleh_kecekapan", + "bermanja": "bapak", + "ummi": "bapa_suci", + "emak": "bapa_suci", + "ibunda": "isa", + "\u0645\u0627\u0633": "bapa_suci", + "bh": "tn", + "nyonya": "mr", + "ms": "tn", + "anak_saudara_perempuan": "anak_buah", + "kemanakan": "anak_saudara_lelaki", + "biarawati": "monk", + "sista": "monk", + "rahib_perempuan": "monako", + "paderi_wanita": "pendeta", + "permaisuri": "kening", + "raja_permaisuri_agung": "datu", + "kuins": "reyes", + "queens": "reyes", + "koya": "he", + "kakak_atau_adik_perempuan": "abang_ngah", + "saur": "ikhwan", + "saudari": "brother", + "rahib_wanita": "adik_seibu_sebapa", + "adik_perempuan": "adik_laki_laki", + "kakak": "kakanda", + "kakak_perempuan": "akang", + "suster": "kangmas", + "tukang_sihir_perempuan": "ahli_hikmat", + "wanita_bujang": "bujangan", + "anak_dara_tua": "orang_bujang", + "jurucakap_wanita": "jurucakap", + "ibu_tiri": "bapa_tiri", + "emak_tiri": "ayah_tiri", + "terna": "pramugara", + "pramugari": "pengelola", + "istri": "laki_laki", + "bini": "matan", + "isteri": "matan", + "penyihir": "tukang_sihir", + "pawang_perempuan": "tukang_sihir", + "hex": "penyihir", + "penyihir_wanita": "penyihir", + "norn": "penyihir", + "orang_perempuan": "buah", + "orang_rumah": "jongos", + "yuno": "genta", + "budak_lelaki": "genta", + "guri": "genta", + "anak_laki_laki": "genta", + "polonaise": "memperhalusi", + "kehalusan_kerja": "polonaise", + "keadaban": "polonaise", + "mengilap": "polonaise", + "mempoles": "polonaise", + "menghalusi": "polonaise", + "kultur": "polonaise", + "menyinar": "polonaise", + "gilap": "polonaise", + "bahasa_poland": "polonaise", + "kerlap": "polonaise", + "memoles": "polonaise", + "memalis": "polonaise", + "penggilap": "polonaise", + "vernis": "polonaise", + "memolesi": "polonaise", + "kilatkan": "polonaise", + "memperindah": "polonaise", + "keanggunan": "polonaise", + "bahasa_polandia": "polonaise", + "memperhaluskan": "polonaise", + "kecanggihan": "polonaise", + "melampas": "polonaise", + "mengupam": "polonaise", + "memperhalusi": "polonaise", + "mencanai": "polonaise", + "memperhalus": "polonaise", + "menyemir": "polonaise", + "peradaban": "polonaise", + "wanita_berkulit_putih": "manusia_berkulit_putih", + "manusia_berkulit_putih": "wanita_berkulit_putih", + "pria_berkulit_putih": "wanita_berkulit_putih", + "pucat": "wanita_berkulit_putih", + "ras_kulit_putih": "wanita_berkulit_putih", + "warna_putih": "wanita_berkulit_putih" + }, + "other_gender_swap": { + "jali": "koya", + "ellas": "koya", + "beliau": "ellas", + "he": "jali", + "koya": "ellas", + "ilu": "jali", + "baginda": "jali", + "him": "jeju", + "sini": "deras", + "nya": "deras", + "lia": "deras" + }, + "en_pronoun2gender": { + "they": [ + "homoseks", + "biseksual", + "dwiseksual", + "dwiseks", + "homoseksual", + "dwijantina", + "biseks", + "transgender", + "queer" + ], + "he": [ + "yuno", + "menyebabkan_pecah_pecah", + "maskulin", + "tuan_tuan", + "budak_lelaki", + "anak_laki_laki", + "pria", + "sesama", + "isle_of_man", + "guri", + "pulau_man", + "laki_laki", + "manik", + "jongos", + "orang_lelaki", + "mas_isle", + "buah", + "human", + "bujang", + "suami", + "meretakkan", + "little_boy", + "pecah_pecah", + "male", + "\u062c\u0646\u062a\u0646", + "cik_abang", + "bung", + "jantan", + "pak_we", + "\u0644\u0644\u0627\u06a9\u064a" + ], + "she": [ + "\u0628\u062a\u064a\u0646\u0627", + "kakak", + "tertinggal", + "amoi", + "orang_gaji", + "betina", + "mak_we", + "gadis_dara", + "kike", + "cik", + "kak", + "poussin", + "budak_perempuan", + "orang_perempuan", + "luncas", + "terasa_kehilangan", + "anak_perempuan", + "merindui", + "merindukan", + "anak_gadis", + "si_manis", + "berkurangan", + "feminin", + "anak_patung", + "tidak_ada", + "lesbian", + "terbebas", + "pembantu_rumah", + "penduduk_lesbos", + "orang_rumah", + "istri", + "\u06a4\u0631\u0645\u06a4\u0648\u0627\u0646", + "genta", + "miss_a", + "gadis_remaja", + "dame", + "mak_cik", + "si_genit" + ] + }, + "en_pronoun2pronoun": { + "he": [ + "ilu", + "he", + "nya", + "sini", + "lia", + "beliau", + "baginda", + "koya", + "him" + ], + "she": [ + "koya" + ], + "they": [ + "jim", + "ellas", + "jeju", + "lia", + "jali", + "deras", + "uk" + ], + "it": [ + "bt", + "stu", + "ky", + "\u0627\u064a\u0646", + "bahawa", + "it", + "bahwa", + "\u0628\u0647\u0627\u0648\u0627", + "yang_itu" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/mt.json b/data_tooling/pii_processing/ontology/data/mt.json new file mode 100644 index 0000000..1bc67a0 --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/mt.json @@ -0,0 +1,239 @@ +{ + "ORG": [ + "l_ewropa_\u010bentrali", + "kummer\u010b", + "il_\u0121nus_maqg\u0127uda", + "warakollox", + "l_ikla_t_tajba", + "kokka", + "ba\u0127ar_l_a\u0127mar", + "disa", + "addis_ababa", + "san_nikola", + "id_dar_il_bajda", + "kape_verde", + "is_sbej\u0127a_rieqda", + "il_pratika_tag\u0127mlek_perfett" + ], + "ANIMAL": [ + "sparvier", + "farawni", + "bijver", + "gamiema", + "kakarachka", + "kokro\u010b", + "kakarachi", + "ballottra", + "barba\u0121ann", + "avultun", + "russett", + "falkun", + "fellus", + "wirdiena" + ], + "LOCATION": [ + "l_ewwel_tas_sena", + "santa_klaws", + "wardija", + "il_lejla_t_tajba", + "il_lejl_it_tajjeb", + "park", + "is_sieg\u0127a_u_\u0127mistax_il_minuta", + "is_sieg\u0127a_u_kwart", + "m_hemmx_g\u0127alxiex", + "lejliet_l_ewwel_tas_sena", + "usa", + "l_istati_uniti_ta_l_amerika", + "sri_lanka", + "is_sbej\u0127a_rieqda", + "bonasira", + "is_sena_t_tajba", + "l_istati_uniti", + "il_\u0121urnata_t_tajba" + ], + "PRODUCT": [ + "missierna", + "new_zealand", + "it_testment_il_\u0121did", + "il_milied_it_tajjeb", + "drittijiet_umani", + "l_g\u0127odwa_t_tajba", + "si\u0121ra_tal_milied", + "it_tieni_gwerra_dinjija", + "l_g\u0127anja_tal_g\u0127anjiet", + "fenek_ta_l_indi" + ], + "DISEASE": [ + "passjoni", + "qaras", + "malarja", + "raqad", + "marid", + "marda", + "appendicite", + "kundizzjoni", + "kallu", + "irqad", + "vajrus", + "gass", + "le" + ], + "FOOD": [ + "luminata", + "brejkfast", + "kolazzjon", + "ros\u00e9" + ], + "LANGUAGE": [ + "g\u0127arbija", + "griega", + "griegi", + "ingli\u017c", + "korniku", + "belarussu", + "fran\u010bi\u017c", + "portugi\u017c", + "ungeri\u017c", + "katalan", + "dani\u017c", + "anglu", + "l_afrikan", + "belarussa", + "ido", + "persjan", + "ingli\u017ca" + ], + "JOB": [ + "it_tieni", + "kelliem", + "temp", + "barbiera", + "meni\u0121er", + "arlu\u0121\u0121ar", + "merkantiera", + "bankiera", + "sekonda", + "furnar", + "president", + "furnara", + "mastrudaxxa", + "merkantier", + "kelliema", + "kurunell", + "barbier", + "qabla", + "interpretu", + "bankier", + "klienta" + ], + "PUBLIC_FIGURE": [ + "bari", + "dwardu", + "nardu", + "u", + "pietru", + "x", + "anard", + "katarina", + "katerina", + "putin", + "karmenu", + "anton", + "karlu", + "leonardu" + ], + "PLANT": [ + "artist", + "cirasa", + "g\u0127anbaqar", + "favetta", + "kabo\u010b\u010ba", + "karrota" + ], + "GPE": [ + "spirtu_santu", + "salib_l_a\u0127mar", + "ru\u0127_il_qodos", + "san_\u0121or\u0121", + 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"SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "nantli": "tahtli", + "cihuatlahto\u0101ni": "tlahto\u0101ni", + "cihuatl": "oquichtli" + }, + "other_gender_swap": {}, + "en_pronoun2gender": { + "he": [ + "oquichtli" + ], + "she": [ + "cihuatl" + ] + }, + "en_pronoun2pronoun": { + "he": [ + "he" + ], + "they": [ + "aca" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/nan.json b/data_tooling/pii_processing/ontology/data/nan.json new file mode 100644 index 0000000..f6497f5 --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/nan.json @@ -0,0 +1,97 @@ +{ + "GPE": [ + "\u7d05\u6d77", + "\u4eba\u6743", + "\u7ea2\u6d77" + ], + "ORG": [ + "jan_mayen", + "\u5929\u4e3b\u6559\u6703" + ], + "FOOD": [ + "\u6a61\u5976\u7cd6", + "chile" + ], + "PLANT": [ + "a_s\u00e1_g\u00e1_o\u0358h" + ], + "PRODUCT": [ + "don_quixote", + "\u4eba\u6b0a" + ], + "FAC": [ + "\u90f5\u4fbf\u5c40", + "\u5929\u4e3b\u6559\u4f1a", + "\u90ae\u4fbf\u5c40" + ], + "LOCATION": [ + "\u7a7a\u519b", + "sri_lanka" + ], + "PUBLIC_FIGURE": [ + "don_quixote", + "ta_bi\u030dt" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "\u65b0\u5a18": "\u65b0\u90ce", + "\u65b0\u5987": "\u65b0\u90ce", + "\u65b0\u5a66": "\u65b0\u90ce", + "\u5a18\u4eb2": "\u5a18\u7236", + "\u6bcd\u4eb2": "\u8001\u7238", + "\u5a18\u89aa": "\u7236\u89aa", + "\u7236\u6bcd": "\u7236\u4eb2", + "\u963f\u59c6": "\u963f\u7238", + "\u963f\u6bcd": "\u7236\u89aa", + "\u5976": "\u8001\u7238", + "\u6bcd\u89aa": "\u5a18\u7238", + "\u963f\u59ca": "\u5144\u54e5", + "\u5c0f\u59b9": "\u54e5\u54e5", + "\u5927\u59ca": "\u5c0f\u5f1f", + "\u59ca\u59b9": "\u54e5\u54e5", + "\u67d0\u56dd": "ang1", + "\u5bb6\u5f8c": "dai6_lou6", + "\u67e5\u67d0\u4eba": "dai6_lou6", + "\u5bb6\u5a46": "dai6_lou6", + "\u727d\u7684": "\u7fc1\u5a7f", + "\u592a\u592a": "\u67e5\u57d4\u4eba", + "\u5973\u4eba": "dai6_lou6", + "\u727d\u624b": "\u67e5\u57d4\u4eba", + "\u67e5\u57d4\u36e0\u4ed4": "\u5c0f\u59b9", + "\u67e5\u57d4\ud846\udc83\u4ed4": "\u5c0f\u59b9", + "\u67e5\u57d4\u56e1\u4ed4": "\u5c0f\u59b9" + }, + "other_gender_swap": {}, + "en_pronoun2gender": { + "he": [ + "\u67e5\u57d4\u56e1\u4ed4", + "\u67e5\u57d4\ud846\udc83\u4ed4", + "\u67e5\u57d4\u36e0\u4ed4" + ], + "she": [ + "\u67e5\u67d0\u4eba", + "\u5973\u4eba", + "\u963f\u59ca", + "\u5927\u59ca", + "\u5c0f\u59b9", + "\u67e5\u67d0\u56e1\u4ed4" + ] + }, + "en_pronoun2pronoun": { + "they": [ + "\ud869\udf36", + "\u4ebb\u56e0" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/nap.json b/data_tooling/pii_processing/ontology/data/nap.json new file mode 100644 index 0000000..e6efa39 --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/nap.json @@ -0,0 +1,176 @@ +{ + "PLANT": [ + "cazzipocchio", + "ardica", + "ceraso", + "cucuzzigl", + "solanaceae", + "sammuch", + "ramegna", + "avrusca", + "catiegl", + "puocchi\u00eb", + "contrerva", + "alvaniegl", + "matr\u00ebcana", + "cierr", + "cerasa", + "p\u00ebrcacchia", + "pastenaca", + "caci\u00f2la" + ], + "LOCATION": [ + "mar_tirreno" + ], + "ANIMAL": [ + "passaro", + "russignuolo", + "cardillo", + "mammifere", + "pernice", + "surice", + "pietterusso", + "capreolo", + "pizzestuorto", + "farcone", + "tremmula", + "scarraf\u00f3ne" + ], + "JOB": [ + "portal\u00e9ttere", + "vammana", + "pitt\u00f3re", + "don", + "zoccula", + "mammana", + "portalettere", + "pett\u00f3re" + ], + "PRODUCT": [ + "justin_bieber" + ], + "DISEASE": [ + "recchiune", + "segli\u00f9zzo", + "gratt\u00e0", + "paposcia", + "selluzzo", + "guallecchia", + "guallara", + "cacagli\u00e0", + "chi", + "scarfatura", + "sorece", + "suonno", + "mengr\u00e0nia", + "ruttura" + ], + "PUBLIC_FIGURE": [ + "winston_churchill", + "giambattista_marini", + "michael_jackson", + "grev\u00f2rio", + "vincent_van_gogh", + "marco_aurelio", + "e", + "sarah_bernhardt", + "stalin", + "dante_alighieri", + "nicolas_poussin", + "bened\u00e8tt\u00eb", + "a", + "caravaggio", + "o", + "william_james", + "sandro_botticelli", + "al_capone", + "le_corbusier", + "adolf_hitler", + "giuseppe_garibaldi", + "ant\u00f9one", + "gaetano_donizetti", + "charlie_chaplin", + "ronald_reagan", + "ernest_hemingway", + "nelson_mandela", + "san_giorgio" + ], + "DATE": [ + "calannario_greguriano", + "medioevo" + ], + "ORG": [ + "nasa", + "alessandro_magno", + "mar_ruosso", + "core", + "state_aunite_d_amereca", + "los_angeles", + "nato", + "chiesia_cattoleca", + "scola", + "san_nicola_e_mira" + ], + "FOOD": [ + "attisena", + "sciavecaria", + "patanella" + ], + "EVENT": [ + "se_scet\u00e0" + ], + "FAC": [ + "san_giuseppe" + ], + "RELIGION": [ + "islam" + ], + "LANGUAGE": [ + "hindjan", + "taliano", + "franzese" + ], + "GENDER": [ + "peccerella" + ], + "GPE": [ + "mar_ruosso", + "novo_testamiento" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "riggina": "rr\u00e9", + "femmena": "ommo", + "guaglione": "peccerella" + }, + "other_gender_swap": {}, + "en_pronoun2gender": { + "he": [ + "guaglione", + "ommo" + ], + "she": [ + "femmena", + "nenna", + "peccerella" + ] + }, + "en_pronoun2pronoun": { + "it": [ + "isso", + "chist", + "stu" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/nci.json b/data_tooling/pii_processing/ontology/data/nci.json new file mode 100644 index 0000000..b231d3d --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/nci.json @@ -0,0 +1,60 @@ +{ + "JOB": [ + "amoxtlahcuiloh" + ], + "PERSON_PRONOUN": [ + "i" + ], + "PLANT": [ + "zanahoria", + "xochihcualcuahuitl" + ], + "QUANTITY": [ + "ton" + ], + "ANIMAL": [ + "cacalotl", + "chimalmichin", + "ahuitzotl", + "mazatl", + "molotl" + ], + "ORG": [ + "aquihqueh" + ], + "PUBLIC_FIGURE": [ + "i", + "h" + ], + "LOCATION": [ + "tlateochihualatl" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "nantli": "tahtli" + }, + "other_gender_swap": {}, + "en_pronoun2gender": { + "she": [ + "cihuatl" + ] + }, + "en_pronoun2pronoun": { + "it": [ + "inihqueh_on", + "inihqueh_in", + "inin" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/nds.json b/data_tooling/pii_processing/ontology/data/nds.json new file mode 100644 index 0000000..001ad59 --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/nds.json @@ -0,0 +1,464 @@ +{ + "RELIGION_MEMBER": [ + "kathoolsch", + "bruer", + "brauder", + "broer" + ], + "DISEASE": [ + "sars", + "plietsch", + "slapen", + "gloot", + "bloom", + "h\u00f6hneroog", + "the_sting", + "liekdoorn", + "blievergiften", + "heuhneroog", + "wart" + ], + "PUBLIC_FIGURE": [ + "akira_kurosawa", + "giovanni_boccaccio", + "max_bruch", + "staatsh\u00f6\u00f6ft", + "eduard_buchner", + "jan_van_eyck", + "mary_wollstonecraft", + "johannes_diderik_van_der_waals", + "terry_pratchett", + "peter_o\u2019toole", + "joseph_greenberg", + "isaac_newton", + "milton_friedman", + "george_harrison", + "george_orwell", + "richard_wagner", + "marie_curie", + "michael_jackson", + "el_greco", + "galileo_galilei", + "vincent_van_gogh", + "anne_boleyn", + "robert_burns", + "liliuokalani", + "karl_barth", + "giuseppe_verdi", + "konrad_adenauer", + "peter_de_grote", + "waberich", + "holden", + "rudolf_bultmann", + "thomas_mann", + "peter_pan", + "paul_verlaine", + "james_dean", + "heinrich_schliemann", + "don_quijote", + "christiaan_eijkman", + "charlie_parker", + "immanuel_kant", + "max_planck", + "lars_onsager", + "john_walker", + "michael_faraday", + "walt_disney", + "lee", + "benny_goodman", + "charles_laughton", + "gustav_mahler", + "homo_heidelbergensis", + "indira_gandhi", + "thomas", + "glenn_miller", + "pablo_picasso", + "otto_hahn", + "lester_young", + "claudio_monteverdi", + "jean_harlow", + "karl_marx", + "robert_schumann", + "john_locke", + "helen_keller", + "william_wyler", + "adolf_hitler", + "joseph_haydn", + "edvard_grieg", + "1", + "rosa_parks", + "harry", + "arthur_schopenhauer", + "andrew_jackson", + "louis_armstrong", + "gaetano_donizetti", + "wilhelm_herschel", + "william_faulkner", + "amerigo_vespucci", + "emma_goldman", + "putin", + "coleman_hawkins", + "mary_harris", + "george_sand", + "jules_verne", + "woody_herman", + "jackson_pollock", + "john_lennon", + "charlie_chaplin", + "hannah_arendt", + "sottje", + "miles_davis", + "bozen", + "john_deere", + "ronald_reagan", + "helmut_schmidt", + "homo", + "oliver_cromwell", + "lionel_hampton", + "hapen", + "marcus_antonius", + "st_louis", + "ernest_hemingway", + "simon_petrus", + "nelson_mandela", + "heinrich_himmler", + "roald_amundsen", + "ella_fitzgerald", + "fats_waller", + "willy_brandt", + "pontius_pilatus", + "christoph_kolumbus", + "franz_schubert", + "johnny_cash", + "de_r\u00f6ttenfanger_vun_hameln", + "john_bunyan", + "jonathan_swift", + "albert_einstein" + ], + "ANIMAL": [ + "roothirsch", + "huusrott", + "tacks", + "otter", + "reier", + "hartbock", + "bargaante", + "kaisergoos", + "achterbeen", + "achterbein", + "waalhai", + "h\u00f6hnergoos", + "graugoos", + "h\u00e4ger", + "wildswien", + "heekster", + "gr\u00f6\u00f6nlandgoos", + "homo_sapiens", + "heister", + "eerdp\u00fc\u00fcster", + "liddpoten", + "kraa", + "swattkoppm\u00f6we", + "rottgoos", + "pingstvagel", + "reiger", + "slaapm\u00fc\u00fcs", + "kundus", + "hasselmuus", + "koter", + "swaangoos", + "donald_duck", + "heckster", + "brock", + "b\u00fclo", + "roov", + "kreih", + "liddf\u00f6\u00f6t", + "liester", + "haavke", + "grote_kanadagoos", + "holtduuv", + "kiewitt", + "kreeg", + "bolz", + "eider", + "haavk" + ], + "PLANT": [ + "maiklocken", + "wegewinne", + "kaarze", + "marjenblome", + "kroonsbeer", + "boerenklokjen", + "walln\u00f6\u00f6tboom", + "fluitekruud", + "klokkebloeme", + "fuhr", + "akkelei", + "beet", + "holm", + "bergamott", + "zockaboom", + "schierling", + "lork", + "arikelken", + "suckerr\u00f6\u00f6r", + "walln\u00f6\u00f6t", + "klokjen", + "krusenkohl", + "hoornvij\u00f6\u00f6lken", + "rickelwinn", + "teeplant", + "todecktsadige", + "vigelett", + "slaad", + "grootmudderbloom" + ], + "GPE": [ + "nieg_testament", + "simon_petrus", + "la_rochelle", + "la_gomera", + "st_louis" + ], + "JOB": [ + "warder", + "sweep", + "lesersch", + "potter", + "weverin", + "timmermann", + "wacht", + "lesersche", + "putzb\u00fcdel", + "wever", + "goorner", + "grip", + "weversch", + "land", + "snieder", + "sniedersche", + "persepter", + "leserin", + "weversche", + "mandarin", + "keunig", + "schipper", + "sottje", + "kock", + "wetter", + "barber", + "man", + "goornersche", + "marine", + "schriever", + "goornersch", + "sniederin", + "goornerin", + "kaken", + "k\u00f6nig", + "b\u00f6rgermeester", + "sniedersch" + ], + "PRODUCT": [ + "vadderunser", + "die_hard", + "onzevaoder", + "s\u00e3o_tom\u00e9_un_pr\u00edncipe", + "dodenl\u00fccht", + "grootbritannien", + "sassen_anholt" + ], + "MEDICAL_THERAPY": [ + "blooddruck" + ], + "LANGUAGE": [ + "deens", + "malayalam", + "hindi", + "esperanto", + "latyn", + "sweedsch", + "cree", + "ido", + "franz\u00f6\u00f6sch", + "tonga", + "kannada" + ], + "FOOD": [ + "golden_delicious", + "fr\u00f6hst\u00fcck", + "oliven\u00f6\u00f6l", + "rootspoon", + "granny_smith", + "rootwien", + "stuut", + "krentenstoete", + "tappwater", + "wittwien", + "chili", + "appelkoken", + "chile", + "drinkwater", + "ros\u00e9wien" + ], + "DATE": [ + "mudderdag", + "gregoriaansch_klenner", + "greundunnerdag", + "neemaand", + "vullmaand", + "middel\u00f6ller", + "stillfreedag", + "gr\u00f6ndunnersdag", + "maandphaas" + ], + "ORG": [ + "nasa", + "bueree", + "repr\u00e4sentantenhuus", + "the_who", + "neemaand", + "san_francisco", + "kristdemokraterna", + "un", + "fraagteken", + "r\u00f6\u00f6msch_recht", + "nanak", + "highschool", + "saint_helena", + "ai", + "steernhopen", + "dia", + "gatt", + "school", + "ik_heet", + "the_breakfast_club", + "schintoismus", + "grundschool", + "dschainismus", + "baskenland", + "hedgefonds", + "alexander_de_grote", + "los_angeles", + "spraakfamilie", + "taoismus", + "natschonalversammeln_vun_aserbaidschan", + "noordzypern", + "st_lucia", + "inwahnerdicht" + ], + "EVENT": [ + 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a/data_tooling/pii_processing/ontology/data/nhn.json b/data_tooling/pii_processing/ontology/data/nhn.json new file mode 100644 index 0000000..664deaa --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/nhn.json @@ -0,0 +1,44 @@ +{ + "FOOD": [ + "cacahuatl" + ], + "ANIMAL": [ + "tlacuachin", + "quimichpatlani", + "cuacuauhxolotl", + "cacalotl", + "ahuitzotl", + "tlacaxolotl", + "mazatl", + "cuetlachtli" + ], + "JOB": [ + "maitl", + "coyotl" + ], + "DISEASE": [ + "chahuiztli" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "nantli": "tahtli" + }, + "other_gender_swap": {}, + "en_pronoun2gender": { + "she": [ + "cihuatl" + ] + }, + "en_pronoun2pronoun": {}, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/nl.json b/data_tooling/pii_processing/ontology/data/nl.json new file mode 100644 index 0000000..7c2bdd8 --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/nl.json @@ -0,0 +1,6493 @@ +{ + "PUBLIC_FIGURE": [ + "lawrence_durrell", + "henry_cavendish", + "matthew_arnold", + "lev_ivanov", + "benjamin_franklin", + "martin_buber", + "akira_kurosawa", + "noah_webster", + "jean_genet", + "john_knox", + "heinrich_hertz", + "zakratte", + "the_king", + "hopen", + "edward_rickenbacker", + "giovanni_boccaccio", + "derde_kruistocht", + "cornelius_vanderbilt", + "rudolf_steiner", + "thomas_wolfe", + "sukkel", + "thomas_bayes", + "ben_hogan", + "max_bruch", + "charles_best", + "leonard_bernstein", + "che_guevara", + "georges_simenon", + "c", + "john_barth", + "edward_albee", + "hendrik", + "kerkbaljuw", + "dorothy_parker", + "maria_callas", + "william_walton", + "henrik_ibsen", + "morgan", + "constantijn", + "sergej_rachmaninov", + "hughes", + "mary_shelley", + "franz_werfel", + "marcello_malpighi", + "peter_lorre", + "de_rattenvanger_van_hamelen", + "openhartig", + "david_livingstone", + "eduard_buchner", + "david_smith", + "john_herschel", + "andrzej_wajda", + "jan_van_eyck", + "balletdanseres", + "carl_rogers", + "george_balanchine", + "georg_wilhelm_steller", + "richard_burton", + "douglas_macarthur", + "mary_wollstonecraft", + "j_edgar_hoover", + "maria_magdalena", + "thomas_reid", + "john_jacob_astor", + "otto_frisch", + "anna_pavlova", + "hoopje", + "winston_churchill", + "johannes_diderik_van_der_waals", + "giambattista_marini", + "b", + "conrad_aiken", + "karl_landsteiner", + "ivan_pavlov", + "paul_mccartney", + "richard_smalley", + "andrew_marvell", + "terry_pratchett", + "k", + "stephen_king", + "francis_crick", + "john_trumbull", + "sherry", + "van_gogh", + "joseph_greenberg", + "isaac_newton", + "gregoor", + "alfred_eisenstaedt", + "victor_hugo", + "joseph_smith", + "edwin_hubble", + "colette", + "milton_friedman", + "edward_gibbon", + "michael_a_jackson", + "jefferson_davis", + "saint_louis", + "cass_gilbert", + "george_stephenson", + "zuidervis", + "john_glenn", + "john_webster", + "john_davis", + "pedel", + "george_burns", + "george_harrison", + "peter_minuit", + "george_orwell", + "arthur_koestler", + "richard_wagner", + "williams", + "thornton_wilder", + "don_quichot", + "pancho_villa", + "dr_james_wilson", + "leopold_stokowski", + "rebecca_west", + "sint_joris", + "marie_curie", + "francis_galton", + "mary_martin", + "michael_jackson", + "louis_jolliet", + "carl_sandburg", + "thomas_hobbes", + "minteken", + "edward_weston", + "el_greco", + "samuel_beckett", + "catharina_howard", + "von_willebrandfactor", + "david", + "engelbewaarder", + "galileo_galilei", + "ernest_bevin", + "jane_goodall", + "john_donne", + "chaim_weizmann", + "robert_l_mills", + "andrea_guarneri", + "robert_koch", + "brigadegeneraal", + "joseph_goebbels", + "george_eastman", + "john_steinbeck", + "erich_mendelsohn", + "petrus", + "donald_glaser", + "edmund_hillary", + "vincent_van_gogh", + "richard_hooker", + "martina_navr\u00e1tilov\u00e1", + "marie_stopes", + "john_ruskin", + "robert_burns", + "carl_anderson", + "thomas_paine", + "bari", + "liliuokalani", + "francis_beaumont", + "steven_weinberg", + "p", + "mary_pickford", + "hans_fischer", + "emiliano_zapata", + "elisabet", + "karl_barth", + "willem_einthoven", + "johann_winckelmann", + "phil_anderson", + "thomas_willis", + "bernard_malamud", + "samuel_johnson", + "allen_iverson", + "anne_hutchinson", + "louise_nevelson", + "giuseppe_verdi", + "e", + "karl_jaspers", + "hideki_yukawa", + "konrad_adenauer", + "bush", + "marianne_moore", + "norbert_wiener", + "john_masefield", + "mark_rothko", + "maurice_chevalier", + "gottlieb_daimler", + "frank_sinatra", + "abel_tasman", + "katharine_hepburn", + "henri_matisse", + "bertram_brockhouse", + "louis_pasteur", + "j", + "richard_strauss", + "stephen_decatur", + "leslie_howard", + "theodosius_i", + "mahalia_jackson", + "ben_shahn", + "john_ford", + "stephen_foster", + "alphonse_bertillon", + "katherine_mansfield", + "gertrude_stein", + "saladin", + "sarah_bernhardt", + "v", + "philip_marlowe", + "luigi_pirandello", + "robert_millikan", + "rube_goldberg", + "roodkapje", + "dorothea_lange", + "james_thurber", + "charles_de_gaulle", + "paul_von_hindenburg", + "y", + "henry_moore", + "holden", + "bezoedelen", + "mary_mallon", + "ralph_bunche", + "rudolf_bultmann", + "charles_lindbergh", + "vincenzo_bellini", + "samuel_barber", + "tobias_smollett", + "f", + "john_jay", + "ludwig_wittgenstein", + "august_strindberg", + "stalin", + "bunyan", + "thomas_mann", + "johan_bernoulli", + "tijn", + "alla_nazimova", + "charles_goodyear", + "dante_alighieri", + "charles", + "robert_lee", + "margot_fonteyn", + "peter_pan", + "james_tobin", + "molenaarster", + "john_irving", + "samuel_de_champlain", + "davit", + "giacomo_puccini", + "edward_fitzgerald", + "fridtjof_nansen", + "louis_braille", + "herbert_marcuse", + "mungo_park", + "benedict_arnold", + "paul_verlaine", + "winterkoninkje", + "q", + "vladimir_poetin", + "robert_johnson", + "james_dean", + "robert", + "marie_tussaud", + "roger_bannister", + "beschermheilige", + "theodor_schwann", + "max_beerbohm", + "alessandro_manzoni", + "joseph_priestley", + "hal", + "nicolas_poussin", + "andrea_mantegna", + "joseph_pulitzer", + "george_huntington", + "james_naismith", + "oscar_wilde", + "philip_roth", + "piet_mondriaan", + "henry", + "lawrence", + "richard_trevithick", + "william_bradford", + "heinrich_schliemann", + "eli_whitney", + "glenn_curtiss", + "augustijn", + "clark", + "the_court_jester", + "laurence_olivier", + "koningseider", + "pierre_larousse", + "christiaan_eijkman", + "george_kennan", + "andrej_sacharov", + "adolf_eichmann", + "catharijne", + "marilyn_horne", + "francis_bacon", + "pete_seeger", + "konstantin_stanislavski", + "joseph_heller", + "a", + "molenaar", + "morris", + "peter_carl_goldmark", + "norman_rockwell", + "james_brown", + "william_hogarth", + "charles_baudelaire", + "luigi_cherubini", + "david_ricardo", + "the_tragedy_of_king_richard_the_second", + "henri_labrouste", + "mary_leakey", + "charlie_parker", + "z", + "tandenfee", + "immanuel_kant", + "richard_gatling", + "james_franck", + "william_crookes", + "nellie_bly", + "weber", + "warburg", + "octavius", + "n", + "albert_schweitzer", + "miller", + "john_harvard", + "johann_friedrich_herbart", + "giulio_natta", + "staatshoofd", + "titus", + "johannes_kepler", + "most", + "max_planck", + "william_blake", + "s_serie", + "julio_iglesias", + "john_bardeen", + "arthur", + "sarah_vaughan", + "arnoud", + "john_wilkes", + "william_byrd", + "william_henry", + "richard_sheridan", + "christopher_fry", + "scott_joplin", + "carl_lewis", + "george_vancouver", + "canberra", + "michail_kalinin", + "elias_canetti", + "robert_lowell", + "edward_jenner", + "oliver_hardy", + "the_life_and_death_of_king_john", + "cole_porter", + "charel", + "benjamin_west", + "jean_luc_godard", + "the_flying_dutchman", + "graham_greene", + "frans_hals", + "edward", + "lars_onsager", + "margaret_mitchell", + "igor_stravinsky", + "stuart_davis", + "lola_montez", + "jan_swammerdam", + "mary_mccarthy", + "john_walker", + "flavius_josephus", + "william_herschel", + "joseph_black", + "mikhail_baryshnikov", + "arthur_rubinstein", + "gierzwaluwen", + "leon_trotski", + "niels_bohr", + "kenneth_grahame", + "schoorsteenveger", + "henry_fielding", + "bertrand_russell", + "katherine_anne_porter", + "michael_faraday", + "john_d_rockefeller", + "anthony_burgess", + "jan_tinbergen", + "stripboek", + "robert_venturi", + "greg", + "irving_berlin", + "rudolf_diesel", + "kunsthandelaar", + "walt_disney", + "ben_jonson", + "peter", + "bergnimf", + "joseph_schumpeter", + "steve_reich", + "lee", + "benny_goodman", + "friedrich_engels", + "jane_austen", + "charles_laughton", + "gustav_mahler", + "ed_sullivan", + "phil_collins", + "alice_paul", + "robert_redford", + "jean_giraudoux", + "jack_dempsey", + "ian_fleming", + "richard_feynman", + "wolfgang_pauli", + "overgrootouder", + "theodore_dreiser", + "theodor_mommsen", + "andrew_huxley", + "marcel_proust", + "thomas_more", + "homo_heidelbergensis", + "paul_hindemith", + "elizabeth_taylor", + "thomas_chippendale", + "paul_robeson", + "arnold", + "thomas_middleton", + "pieter", + "john_dowland", + "de_ware", + "hans_krebs", + "daniel_jones", + "william_golding", + "robert_motherwell", + "william_caxton", + "john_milton", + "rudolf_serkin", + "peter_stuyvesant", + "ethel_merman", + "samuel_adams", + "albert_speer", + "james_baldwin", + "valentina_teresjkova", + "john_vanbrugh", + "indira_gandhi", + "jane_seymour", + "george_gershwin", + "alberto_giacometti", + "perenwijn", + "frank_whittle", + "alfred_nobel", + "jesse_owens", + "niet_van_toepassing", + "marco_polo", + "john_fletcher", + "caravaggio", + "charlie_watts", + "m", + "marcel_marceau", + "allen_ginsberg", + "fred_zinnemann", + "daniel_bernoulli", + "guillaume_apollinaire", + "lampongaap", + "pablo_casals", + "joseph_henry", + "henri_bergson", + "antonius", + "edward_macdowell", + "josef_hoffmann", + "boris_karloff", + "pierre_corneille", + "patrick_white", + "saul_steinberg", + "bartholomew_roberts", + "hans_christian_andersen", + "william_morris", + "cary_grant", + "thomas", + "saint_lawrence", + "pieter_zeeman", + "glenn_miller", + "steward", + "pablo_picasso", + "natalie_wood", + "l_ron_hubbard", + "thomas_moore", + "osman_i", + "kurt_weill", + "otto_hahn", + "lester_young", + "john_marshall", + "hartenheer", + "christiaan_huygens", + "hector_berlioz", + "lucille_ball", + "paul_simon", + "claudio_monteverdi", + "benjamin_jowett", + "john_galsworthy", + "robert_robinson", + "o", + "adam_smith", + "william_james", + "chroesjtsjov", + "u", + "jean_harlow", + "henry_miller", + "karl_marx", + "paul_bunyan", + "friedrich_nietzsche", + "i", + "hersenloos", + "robert_indiana", + "grootvizier", + "john_wesley", + "sandro_botticelli", + "carson_mccullers", + "bloch", + "seiji_ozawa", + "peter_i_van_rusland", + "nikola_tesla", + "al_capone", + "charles_barkley", + "billy_graham", + "robert_schumann", + "mel_gibson", + "le_corbusier", + "carlo_goldoni", + "john_locke", + "alexis_carrel", + "king_lear", + "joseph_marie_jacquard", + "henry_james", + "stephen_sondheim", + "lorenz_hart", + "helen_keller", + "paul_dukas", + "ingrid_bergman", + "inca's", + "leonard_bloomfield", + "jane_jacobs", + "thurber", + "verlaine", + "jean_piaget", + "william_congreve", + "franz_kline", + "henri_rousseau", + "paul_tillich", + "hilaire_belloc", + "hugo_de_groot", + "frank_norris", + "frank_stella", + "robert_southey", + "walt_whitman", + "william_wyler", + "warren", + "john_osborne", + "colin_powell", + "ludwig_boltzmann", + "carl_nielsen", + "leopold_kronecker", + "richard_wright", + "benjamin_thompson", + "adolf_hitler", + "winterkoningen", + "fritz_haber", + "dekker", + "archibald_macleish", + "peter_behrens", + "alfred_stieglitz", + "john_h_watson", + "joseph_haydn", + "stephen_spender", + "garfield", + "george_boole", + "paul_revere", + "wangzakratte", + "daniel_boone", + "buffalo_bill", + "edvard_grieg", + "robert_boyle", + "arthur_laffer", + "edith_cavell", + "alan_paton", + "ralph_richardson", + "prima_donna", + "1", + "cordell_hull", + "james_wilson", + "rosa_parks", + "norman_jewison", + "samuel_goldwyn", + "steller", + "x", + "ernest_walton", + "jacob", + "giuseppe_mazzini", + "jim_thorpe", + "hertz", + "h", + "arnold_sch\u00f6nberg", + "laurence_sterne", + "hutchinson", + "george_fox", + "ben_hecht", + "christopher_isherwood", + "fritz_kreisler", + "anne_hathaway", + "david_garrick", + "don_budge", + "bill_russell", + "baldwin", + "jeannette_rankin", + "clarence_darrow", + "harry", + "g", + "beschermengel", + "albert_michelson", + "arthur_schopenhauer", + "thomas_dekker", + "james_cagney", + "henri_pitot", + "wanda_landowska", + "billy_mitchell", + "martin_heidegger", + "hans_eysenck", + "gustaaf", + "r", + "george_lucas", + "andrew_jackson", + "edith_wharton", + "louis_armstrong", + "steven_spielberg", + "jean_monnet", + "leonard", + "robert_fulton", + "thomas_hardy", + "thomas_gainsborough", + "giuseppe_garibaldi", + "koning_arthur", + "schepper", + "robert_brown", + "thomas_carlyle", + "tanameer", + "william_tyndale", + "tamara_karsavina", + "bobby_fischer", + "johannes_gutenberg", + "d", + "james_bowie", + "thomas_malthus", + "gaetano_donizetti", + "william_faulkner", + "amerigo_vespucci", + "arthur_holmes", + "pierre_boulez", + "girolamo_savonarola", + "emma_goldman", + "francis_poulenc", + "james_ussher", + "john_barrymore", + "john_constable", + "james_mill", + "robert_heinlein", + "matthew_flinders", + "robert_herrick", + "joseph_campbell", + "jean_de_la_fontaine", + "robert_hooke", + "volder", + "o_henry", + "karl_popper", + "alfred", + "coleman_hawkins", + "george_sand", + "peter_sellers", + "charles_fourier", + "henry_clay", + "marcus_aurelius", + "peter_o'toole", + "joseph_conrad", + "william_shockley", + "peter_paul_rubens", + "jim_morrison", + "jules_verne", + "paul_newman", + "meeste", + "george_meredith", + "robert_morris", + "woody_herman", + "alexander_wilson", + "john_roebling", + "josef_albers", + "jackson_pollock", + "john_lennon", + "andrea_palladio", + "bob_woodward", + "charlie_chaplin", + "the_tragedy_of_richard_the_third", + "hans_wilhelm_geiger", + "thomas_malory", + "lea", + "john_brown", + "al_jolson", + "elizabeth_gaskell", + "en_zo_voorts", + "lillian_hellman", + "brecht", + "john_macleod", + "thomas_merton", + "boris_spasski", + "asa_gray", + "hannah_arendt", + "antonio_stradivari", + "philip_anderson", + "maximianus", + "alice_walker", + "miles_davis", + "edmund_cartwright", + "balletdanser", + "james_parkinson", + "george_marshall", + "harold_nicolson", + "jesse_jackson", + "willa_cather", + "bozen", + "stanley_kubrick", + "koning_david", + "john_deere", + "john_huston", + "haacht", + "william_gilbert", + "voorde", + "james_watt", + "jonathan_edwards", + "ronald_reagan", + "helmut_schmidt", + "jenny_lind", + "homo", + "frederick_douglass", + "david_hilbert", + "wilhelm_reich", + "roman_jakobson", + "oliver_cromwell", + "lionel_hampton", + "martin_luther_king", + "james_hargreaves", + "frank_capra", + "william_wordsworth", + "rex_harrison", + "s", + "william_clark", + "woodrow_wilson", + "thomas_jackson", + "william_wycherley", + "margaret_sanger", + "jamesbaai", + "modest_moessorgski", + "george_mason", + "george_wallace", + "marcus_antonius", + "richard_rodgers", + "george", + "henk", + "anne_sexton", + "christoffel_columbus", + "morgana", + "john_dryden", + "jim_henson", + "frank", + "b\u00e9la_lugosi", + "ernest_hemingway", + "john_eccles", + "george_westinghouse", + "aquila", + "jacques_charles", + "eero_saarinen", + "arthur_miller", + "john_cheever", + "gracie_allen", + "nelson_mandela", + "heinrich_himmler", + "al_gore", + "john_rutledge", + "hans_bethe", + "johannes_calvijn", + "cesare_borgia", + "roald_amundsen", + "sherwood_anderson", + "alfred_korzybski", + "c_a", + "anton", + "charles_dickens", + "ella_fitzgerald", + "fats_waller", + "jack_robinson", + "alois_senefelder", + "george_enescu", + "wallace_carothers", + "jacques_offenbach", + "joseph_paxton", + "william_curtis", + "leakey", + "george_stevens", + "federico_fellini", + "rhodesi\u00ebmens", + "bessie_smith", + "jean_antoine_watteau", + "patrick_henry", + "willy_brandt", + "francisco_pizarro", + "francisco_franco", + "joris", + "jackie_robinson", + "louis_gay_lussac", + "bernardo_bertolucci", + "king_oliver", + "jan_steen", + "frank_harris", + "john_ross", + "cassius_longinus", + "powell", + "philibert_delorme", + "andrew_carnegie", + "pontius_pilatus", + "franz_schubert", + "jurriaan", + "johnny_cash", + "joseph_mccarthy", + "powellmeer", + "alfred_kastler", + "mick_jagger", + "otto_loewi", + "georges_cuvier", + "william_harvey", + "de_vliegende_hollander", + "walter_scott", + "august_von_wassermann", + "peter_medawar", + "vladimir_lenin", + "sam_houston", + "robert_browning", + "alessandro_farnese", + "ralph_ellison", + "john_bunyan", + "jonathan_swift", + "walter_gropius", + "albert_einstein", + "l", + "henry_sweet", + "aletta_jacobs", + "thomas_edison", + "elizabeth", + "chiang_kai_shek", + "claude_bernard", + "raymond_chandler", + "henry_purcell", + "boudewijn", + "t", + "wilhelm_ostwald" + ], + "DISEASE": [ + "griep", + "cyanose", + "koortsachtig", + "hydrocephalus", + "clusterhoofdpijn", + "sars", + "leewater", + "rijstziekte", + "beenmergdepressie", + "acanthosis_nigricans", + "prodroom", + "cellulitis", + "niesen", + "zweer", + "hydrocoele", + "bloederziekte", + "chickenpox", + "polio", + "lassakoorts", + "shigellose", + "dorst", + "rosette", + "bloeduitstorting", + "mastadenitis", + "nevelvlek", + "humaan_papillomavirus", + "rage", + "krassen", + "arbovirussen", + "vlektyfus", + "catarre", + "anthrax", + "de_ziekte_van_parkinson", + "slangenbeet", + "hongeren", + "harttamponade", + "paraplegie", + "als", + "mastitis", + "delier", + "palilalia", + "matheid", + "schok", + "hondsdolheid", + "paniekstoornis", + "galknobbel", + "hartstilstand", + "leerstoornis", + "watervrees", + "lastigvallen", + "stichter", + "sneeuwblindheid", + "progeria", + "cardiomyopathie", + "botontkalking", + "nekkramp", + "poison_ivy", + "beklag", + "aandoening", + "frostbite", + "groeipijn", + "scheurbuik", + "furunkel", + "bloedspuwing", + "jeugdpuistjes", + "papegaaienziekte", + "herpes_simplexvirus", + "nachtblindheid", + "distomatosis", + "hartritmestoornis", + "grondlegger", + "paresthesie", + "verhitten", + "mazelen", + "kraamvrouwenkoorts", + "spraakgebrek", + "conditie", + "ventrikelfibrilleren", + "masto\u00efditis", + "galbulten", + "zwemmersjeuk", + "o_benen", + "brucellose", + "duizeligheid", + "bloeding", + "fotofobie", + "baarmoederkanker", + "groenhoutbreuk", + "spierkramp", + "hartaanval", + "koortslip", + "beriberi", + "strontje", + "mankement", + "tachycardie", + "mania", + "portale_hypertensie", + "dementia", + "korstmos", + "trache\u00eftis", + "regenboogvliesontsteking", + "the_bends", + "kink", + "pang", + "horrelvoet", + "picornavirus", + "klont", + "litteken", + "hersenontsteking", + "paratyfus", + "verstikken", + "kinkhoest", + "kraamkoorts", + "runderpest", + "maanblind", + "la_naus\u00e9e", + "intertrigo", + "pariteitsymmetrie", + "hoofdpijn", + "antisociale_persoonlijkheidsstoornis", + "rust", + "vreemdelingenhaat", + "galactosemie", + "varicella_zostervirus", + "onderkoeling", + "klaplong", + "claustrofobie", + "slapen", + "pancreatitis", + "hydrocefalus", + "hoogtevrees", + "presbyopie", + "boezemfibrilleren", + "miltbrand", + "verslaafdheid", + "reisziekte", + "lethargie", + "aderverwijding", + "zonnebrand", + "windpokken", + "persoonlijkheidsstoornis", + "verlamming", + "oprichter", + "tabaksmoza\u00efekvirus", + "tering", + "stoflong", + "rosacea", + "para", + "teruggang", + "kastanjebruine", + "krentenbaard", + "aardappelziekte", + "eileiderontsteking", + "handicap", + "de_jongen_met_de_klompvoet", + "prikkelbaredarmsyndroom", + "hersenoedeem", + "verstikking", + "longkanker", + "orchitis", + "psychische_aandoening", + "geschokt", + "hooikoorts", + "hoesten", + "hamartoom", + "schildkliervergroting", + "kernicterus", + "vasculitis", + "rodehond", + "wale", + "indigestie", + "letsel", + "overbeet", + "lumbago", + "catalepsie", + "miliaria", + "polyarteriitis_nodosa", + "plaveiselcelcarcinoom", + "gespierdheid", + "waterpokken", + "crick", + "verstopping", + "teratoom", + "kroep", + "hazenlip", + "adervernauwing", + "abasie", + "schizo\u00efde", + "varkensgriep", + "silicose", + "leegte", + "koortsig", + "chi", + "uithongering", + "rachitis", + "delirium", + "strelen", + "balanitis", + "loodvergiftiging", + "zwartwater", + "hersenvliesontsteking", + "hersenverlamming", + "hartinfarct", + "carpaletunnelsyndroom", + "caissonziekte", + "beroepsziekte", + "qi", + "piekdrinken", + "winterslaap", + "loswringen", + "kaposisarcoom", + "anesthesie", + "van_streek", + "snijden", + "koolstofmonoxidevergiftiging", + "klacht", + "contacteczeem", + "rickettsiose", + "vergiftiging", + "malaise", + "acetonurie", + "tennisarm", + "passie", + "lordose", + "de_pest", + "bindvliesontsteking", + "drachttijd", + "gimp", + "oestrus", + "comazuipen", + "marteling", + "stenose", + "downsyndroom", + "frenzy", + "maanoog", + "leverkanker", + "hernia", + "alexia", + "dronkenschap", + "effect", + "verstarring", + "benauwdheid", + "mongolisme", + "maculadegeneratie", + "poliep", + "twist", + "verwonding", + "katalepsie", + "myxoma_cordis", + "smart", + "groei", + "kattenkrabziekte", + "amelia", + "huiduitslag", + "marasmus", + "kelderen", + "zonnesteek", + "stase", + "ed", + "folliculitis", + "blister", + "ouderdomsverziendheid", + "voedselvergiftiging", + "pica", + "grieven", + "ambeteren", + "constipatie", + "cachexie", + "overstuur", + "streptokokkenfaryngitis", + "steenpuist", + "hoofdroos", + "roodvonk", + "longontsteking", + "hoogteziekte", + "hersentumor", + "koorts", + "eksteroog", + "the_sting", + "uitwas", + "vetzucht", + "pariteit", + "keratosis_actinica", + "bloedvergiftiging", + "verstuiking", + "wiegendood", + "sensation", + "sikkelcelanemie", + "stijg", + "brandwond", + "tandpijn", + "poliovirus", + "bedenking", + "bloedarmoede", + "sluimering", + "rubella", + "te_zwaar", + "epidermolysis_bullosa", + "pain", + "bradycardie", + "geelzucht", + "vruchtbaarheid", + "leververvetting", + "schijndood", + "bijholteontsteking", + "the_passion_of_the_christ", + "cyclothymie", + "zweetziekte", + "verziendheid", + "chillen", + "ondervoeding", + "scotoom", + "verkoudheid", + "vogelchlamydiose", + "tenniselleboog", + "coryza", + "klompvoet", + "straling", + "hoest", + "ill", + "chalazion", + "hartfalen", + "hinkend", + "builenpest", + "ischemische_hartklachten", + "waanstoornis", + "huidkanker", + "glasvochttroebeling", + "stigmata", + "strimon", + "stressfractuur", + "scheelzien", + "rughernia", + "chronischevermoeidheidssyndroom", + "lambdacisme", + "golfsyndroom", + "paradontose", + "stuiptrekking", + "wijnpokken", + "kleurenblindheid", + "pellagra", + "gordelroos", + "danswoede", + "catarrhe", + "minamataziekte", + "schistosomiasis", + "oorsuizen", + "kwikvergiftiging", + "mi", + "suikerziekte", + "pellekes", + "aansnijden", + "verhoging", + "middenoorontsteking", + "aura", + "nekstijfheid", + "lijkstijfheid", + "ijzergebreksanemie", + "arousal", + "warmte", + "sting", + "zonneslag", + "wart", + "verstuiken", + "zweepslag", + "afschuring", + "bruinen", + "canofobie", + "the_bleeding", + "vaccinatie", + "gynaecomastie", + "thalassemie", + "break", + "rustelozebenensyndroom", + "conditio", + "cerebrovasculair_accident", + "waterwrat", + "sleep", + "koppijn", + "poliomyelitis", + "palilalie", + "verslaving", + "trauma", + "waterzaknier", + "waterzucht", + "vergassen", + "lichen_planus", + "kuru", + "nevenwerking", + "schurft", + "steriliteit", + "pinkeye", + "materniteit", + "gevoelloosheid", + "temporalekwabepilepsie", + "ventrikelseptumdefect", + "miltvuur", + "draagtijd", + "schuurziekte", + "trachoom", + "noma", + "tandvleesontsteking", + "bloedneus", + "the_hives", + "materialisme", + "west_nijlvirus", + "zwart_water", + "voorhuidsvernauwing", + "dengue", + "vuurpijl", + "postpoliosyndroom", + "cataract", + "torment", + "jicht", + "granuloom", + "klierkoorts", + "overstrekken", + "kiespijn", + "le", + "borstkanker", + "harm", + "proctitis", + "vaccinering", + "leverontsteking", + "albuminurie", + "roest", + "salmonella", + "blauwtongvirus", + "blaasje", + "bipolaire_stoornis", + "spatader", + "boulimie", + "dollekoeienziekte", + "gestatie", + "beroerte", + "de_stad_der_blinden", + "lymeziekte", + "neveneffect", + "stralingsziekte", + "malaria", + "tarantisme", + "gangreen" + ], + "DATE": [ + "vaderdag", + "laatpaleolithicum", + "d_dag", + "middeleeuwen", + "the_wedding_night", + "vastenavond", + "geboortecijfer", + "ziekteverlof", + "paaszondag", + "huwelijksdag", + "mensenheugenis", + "offerfeest", + "tweede_kerstdag", + "kerstdag", + "the_day_after_tomorrow", + "trouwdag", + "schijngestalten", + "levavi", + "bruiloftsdag", + "schrikkeljaar", + "koudegolf", + "elfde_uur", + "nazomer", + "onvoltooid_toekomstige_tijd", + "in_time", + "trinitatis", + "werktijd", + "walpurgisnacht", + "palmzondag", + "overmorgen", + "standaardtijd", + "menstruatiecyclus", + "maria_tenhemelopneming", + "naamdag", + "nieuwe_maan", + "houdbaarheid", + "de_nachtwacht", + "op_termijn", + "het_moment_van_de_waarheid", + "ruimtevaarttijdperk", + "middenpaleolithicum", + "gregoriaanse_kalender", + "zonneconstante", + "sterftecijfer", + "manuur", + "in_het_jaar_des_heren", + "eeuwwisseling", + "op_den_duur", + "regentijd", + "bejaarde", + "sabbatsjaar", + "zomerwende", + "arbeidsongeschiktheid", + "lichtsnelheid", + "allerheiligen", + "halveringstijd", + "opraken", + "tijdschaal", + "twelfth_night", + "spitsuur", + "suikerfeest", + "na_christus", + "allerzielen", + "the_day_after" + ], + "JOB": [ + "bouwvakster", + "assistant", + "brievenbesteller", + "engeltjesmaker", + "planner", + "scheepsjongen", + "jachtopziener", + "tandwieltand", + "mistress", + "rijksdienst", + "guru", + "leermeester", + "amanuensis", + "schoonmaakster", + "mercator", + "therapeut", + "loodgieter", + "voorzitster", + "de_deal", + "lakei", + "the_nanny", + "schepen", + "makelaar", + "dierenarts", + "kapster", + "werktuigbouwkundige", + "assistent", + "tuinlieden", + "speaker", + "heler", + "brigadegeneraal", + "kinderjuffrouw", + "grafdelver", + "kopersmid", + "potter", + "kelderen", + "make", + "deelpachter", + "miller", + "herderinnetje", + "ploeger", + "uitvinder", + "academielid", + "glazenmaker", + "wacht", + "the_dentist", + "wagenmenner", + "voetknecht", + "bestuursvoorzitter", + "doelwachter", + "herderin", + "kerkbaljuw", + "schaapherder", + "slotenmaker", + "lascar", + "ballonvaarder", + "boekhoudster", + "hand", + "kleermaakster", + "purser", + "inkorter", + "luthier", + "remover", + "striptekenaar", + "spelleidster", + "vrouwenarts", + "klokkenmaker", + "stamhoofd", + "vlaggendrager", + "engeltjesmaakster", + "spreker", + "gevolmachtigde", + "schoonheidsspecialiste", + "sexton", + "dragonder", + "dressoir", + "curator", + "magistraat", + "jageres", + "pakker", + "kruier", + "verspreider", + "molenaarster", + "registrator", + "internist", + "temp", + "don", + "meteoroloog", + "speler", + "sergeant", + "scheikundige", + "broodbakmachine", + "tandarts", + "huisbaas", + "stakingsbreker", + "oprichter", + "glasvochttroebeling", + "glaszetter", + "wever", + "coyote", + "huishoudster", + "melkmeid", + "ploegman", + "machinist", + "timmerman", + "melkmeisje", + "the_police", + "intern", + "voetman", + "winder", + "componist", + "koster", + "vertaalster", + "wetenschapper", + "carrier", + "kerkmeesteres", + "marien", + "sommelier", + "kassier", + "caissi\u00e8re", + "foelie", + "loopjongen", + "processor", + "lerares", + "a_majeur", + "doge", + "huisarts", + "gentleman", + "minder", + "trimmer", + "bladzijde", + "bekant", + "the_musketeer", + "bestuurder", + "studiebegeleider", + "dessinateur", + "gaffer", + "wiegewacht", + "schapenhoedster", + "wetenschapster", + "slavin", + "grip", + "para", + "conductor", + "deelbouwer", + "leder", + "kapper", + "bakster", + "sensei", + "arrowsmith", + "bestuurslid", + "bodyguard", + "conci\u00ebrge", + "romanschrijver", + "spotter", + "arbeidskracht", + "mastermind", + "curatrix", + "tapper", + "cardioloog", + "volder", + "inkoopster", + "trainer", + "land", + "kleermaker", + "schrijfster", + "tailor", + "gerontoloog", + "vigilante", + "pottenbakster", + "meesteres", + "systeemanaliste", + "poetsvrouw", + "broodwinner", + "gemeenteraadslid", + "klopper", + "goeroe", + "spreekster", + "wethouder", + "striptekenares", + "pottenbakker", + "dagloner", + "butler", + "a_groot", + "doelwachtster", + "boodschapper", + "wielmaker", + "grenadier", + "bagger", + "valsmunter", + "koning", + "hovenier", + "kunstschilder", + "zandhaas", + "printer", + "boerin", + "cutter", + "kanselier", + "brigadier", + "patholoog", + "tollenaar", + "leader", + "zuurdesem", + "scheepsbouwer", + "territoriaal", + "werktuigkundige", + "schildknaap", + "kamikaze", + "driver", + "boekhouder", + "algemeen", + "the_advocate", + "timmervrouw", + "grondlegger", + "zeilster", + "blokfluit", + "performer", + "page", + "premiejager", + "metselaar", + "interne", + "staatssecretaris", + "baker", + "umpire", + "haarkapper", + "dermatoloog", + "aaseter", + "tuinman", + "freelancer", + "meren", + "tingieter", + "ingenieur", + "bouwvakker", + "heleres", + "opperhoofd", + "master", + "the_guardian", + "der_vorleser", + "diender", + "president", + "broodmachine", + "opperman", + "tuinier", + "houthakker", + "minister", + "raadsman", + "voorzitter", + "agrari\u00ebr", + "culi", + "schrijver", + "herder", + "koekje", + "de_astronoom", + "groom", + "strijdknots", + "entertainer", + "melkboer", + "korporaal", + "griffier", + "mate", + "stoker", + "strelen", + "hoofdopzichter", + "schoonheidsspecialist", + "gastarbeider", + "sterrenkundige", + "stamper", + "l_horloger_de_saint_paul", + "horlogemaakster", + "sandwichman", + "galvaniseur", + "molenaar", + "hanger", + "bader", + "timmeraar", + "plaatsaanwijzer", + "designer", + "kerkvoogd", + "samenvatter", + "stichter", + "pastor", + "hooiwagen", + "middenstander", + "raadgever", + "rapporteur", + "sheriff", + "kolonel", + "interneren", + "stewardess", + "luchtverkeersleider", + "vertaler", + "regulator", + "kostendeskundige", + "hoefsmid", + "toneelspeelster", + "afschrift", + "koopman", + "arbeider", + "vervalser", + "beheerder", + "liedjesschrijver", + "dikkopjes", + "scheidsrechter", + "gaucho", + "waker", + "schipper", + "hostess", + "het_melkmeisje", + "station_wetter", + "veldofficier", + "schoorsteenveger", + "meetlat", + "koets", + "zoogmoeder", + "paringsgezel", + "gevangenbewaarder", + "buttler", + "cartograaf", + "schuif", + "veehouder", + "heraut", + "basters", + "wondkorst", + "zakenman", + "the_economist", + "voetsoldaat", + "collier", + "doelman", + "infanteriste", + "manager", + "zeiler", + "regisseur", + "barbier", + "broker", + "wetter", + "koelie", + "horlogemaker", + "infanterist", + "inkoper", + "catechist", + "vaandrig", + "ma\u00e7on", + "stuurman", + "barista", + "koerier", + "maritiem", + "kogge", + "songwriter", + "koopvrouw", + "the_hangover", + "bakker", + "leidinggevende", + "man", + "chemicus", + "doc", + "collecteur", + "regent", + "trainster", + "gouverneur", + "klokkenmaakster", + "hoogleraar", + "borstvoeden", + "marine", + "jachtmeester", + "tandtechnicus", + "ergotherapeut", + "verwerker", + "bootsman", + "smokkelaar", + "the_pallbearer", + "vaandeldrager", + "tacker", + "counselor", + "aardkundige", + "bisschop", + "meier", + "werker", + "the_machinist", + "handelaar", + "usher", + "gardist", + "kinderoppas", + "messenger", + "dienstplichtige", + "chauffeur", + "stuwadoor", + "zakenvrouw", + "burgemeester", + "au_pair", + "verzorger", + "krijger", + "sentry", + "vliegenier", + "roesje", + "tijdelijk", + "bombardier", + "bezetter", + "bureaucraat", + "vrijwilligster", + "trier", + "steenhouwer", + "the_interpreter", + "stalmeester", + "opsteller", + "belastinginner", + "hoveling", + "kerkmeester", + "thesaurier", + "natuurkundige", + "valkenier", + "schoonmaker", + "spelleider", + "the_negotiator", + "zwartwerker", + "croupier", + "jutter", + "steward", + "catecheet", + "vertolker", + "laryngoloog", + "presbyter", + "extern", + "the_deer_hunter", + "opperbevelhebber", + "brandweerman", + "leerkracht", + "dingen", + "volmatroos", + "doula", + "koempel", + "stenograaf", + "beeldhouwer", + "systeemanalist", + "sub", + "schildwacht", + "veldmaarschalk", + "romancier", + "settler", + "buitenwipper", + "bordenwasser", + "the_independent", + "turner", + "bishop", + "exploitant", + "wijnkelner", + "wagenmaker", + "pedel", + "kindermeisje", + "zeepsop", + "cookie", + "neurochirurg", + "sculpteur", + "verloskundige", + "bankier", + "esquire", + "topper", + "jachtopzichter", + "beroerte", + "wachter", + "luitenant", + "afgezant", + "preses", + "staljongen", + "allergoloog", + "bouwmeester", + "kruidenierster", + "winkelier" + ], + "PLANT": [ + "denneboom", + "vlasbekje", + "sareptamosterd", + "hibiscus_syriacus", + "koningskaars", + "egelboterbloem", + "tuinmelde", + "groenknolorchis", + "hibiscus_mutabilis", + "kruidvlier", + "pijlriet", + "parapluutjesmos", + "kalbas", + "tuinwolfsmelk", + "uitvoergewas", + "mahonia", + "braamstruik", + "veldzuring", + "bergamot", + "spijklavendel", + "peper", + "pine", + "boksdoorn", + "reigersbek", + "aardaker", + "parnassia", + "doornappel", + "ingerolde_palmvaren", + "rozenkransje", + "kroot", + "hokjespeul", + "hartgespan", + "akkerzenegroen", + "melissa", + "aardappelziekte", + "theeplant", + "japanse_parasolden", + "muskaatpompoen", + "zwartsteel", + "steranijs", + "spruitjes", + "groot_hoefblad", + "schubappel", + "liguster", + "esdoorn", + "the_joshua_tree", + "mariadistel", + "fijnspar", + "mottenkruid", + "akkerviooltje", + "fruitboom", + "kamperfoelie", + "helianthus", + "mahonie", + "auricularia_auricula", + "pterocarpus_santalinus", + "rosa_chinensis", + "mastiek", + "marsilea_quadrifolia", + "pampasgras", + "boswederik", + "westerse_plataan", + "quercus_kelloggii", + "vanilla_planifolia", + "aardveil", + "vuurdoorn", + "grasklokje", + "veenbes", + "atlasceder", + "hoenderbeet", + "schietwilg", + "cyclamen_purpurascens", + "kruipertje", + "custardappel", + "mannaes", + "herfstschroeforchis", + "laurus_nobilis", + "dubbelloof", + "kronkelwilg", + "geitenhoefwinde", + "dauwbraam", + "draaiden", + "curuba", + "eulalia_japonica", + "parelgierst", + "kropaar", + "hoornviooltje", + "maanbloem", + "fladderiep", + "grote_kattenstaart", + "spruiten", + "waterlobelia", + "magnolia_grandiflora", + "herderstasje", + "wondklaver", + "moerasden", + "vrouwenkruid", + "wildemanskruid", + "aronskelk", + "papaver_alpinum", + "mastaka", + "abelmos", + "grote_brandnetel", + "sinapis", + "allium_tuberosum", + "vergeet_mij_niet", + "penningkruid", + "passiflora_ligularis", + "hondsroos", + "cercidiphyllum_japonicum", + "alsemambrosia", + "exportgewas", + "paradijsvogelbloem", + "moerascipres", + "blaasvaren", + "gatenplant", + "voorjaarskluifzwam", + "goudbes", + "herfsttijloos", + "vaatbundel", + "boswilg", + "lenteroos", + "nogal", + "lavendelhei", + "drakenwortel", + "vogelmuur", + "vaatplanten", + "matthiola_incana", + "paardenhoefklaver", + "echte_kamille", + "stinkende_ballote", + "actinidia_chinensis", + "parasolden", + "koekoeksbloem", + "sakura", + "kikkerbeet", + "papaver", + "schaafstro", + "wilde_kamperfoelie", + "mannetjesereprijs", + "moerasvaren", + "waterhyacint", + "candida_albicans", + "witte_klaverzuring", + "moerashyacint", + "zaailing", + "oliepalm", + "herik", + "bedektzadigen", + "calophyllum_inophyllum", + "goudenregen", + "wonderboom", + "rosa_multiflora", + "seto", + "laurierkers", + "prachtklokje", + "heelkruid", + "klaproos", + "rietgras", + "lansvaren", + "koraalmalve", + "zomerfijnstraal", + "vroegeling", + "dikkemanskruid", + "slangenwortel", + "klaverzuring", + "herfstadonis", + "capsicum_baccatum", + "steenbreekvaren", + "dianthus_caryophyllus", + "dadelboom", + "tompoes", + "vliegenzwam", + "pijpkraag", + "biefstukzwam", + "libanonceder", + "amaniet", + "melindjoe", + "waterplant", + "schapenzuring", + "hydrangea_hortensia", + "robertskruid", + "pijnappelklier", + "reuzenzilverspar", + "taxus_cuspidata", + "gerw", + "athyrium_distentifolium", + "montereyden", + "prachtframboos", + "mosterd", + "schorrenzoutgras", + "passiflora_incarnata", + "festuca_ovina", + "piramidezenegroen", + "moeraseik", + "bonte_paardenstaart", + "beet", + "moerasstruisgras", + "tuinboon", + "citrus_aurantium", + "handelsgewas", + "hopklaver", + "reseda", + "postelein", + "avondkoekoeksbloem", + "bijenkruid", + "holm", + "mosterdplant", + "kunstenares", + "fluitenkruid", + "melganzenvoet", + "prunus_armeniaca", + "douglasspar", + "kleefkruid", + "balsemzilverspar", + "kustmammoetboom", + "akkerklokje", + "liquidambar", + "torenkruid", + "heidezenegroen", + "tuinbingelkruid", + "valse_salie", + "zonnebloem", + "trosvlier", + "treurwilg", + "glanshaver", + "tuinhibiscus", + "paardenkastanje", + "pterocarpus_indicus", + "moeraslathyrus", + "altviool", + "honingboom", + "zeekool", + "acer_japonicum", + "spruitkool", + "pinksterbloem", + "belladonnalelie", + "tonkaboon", + "heidewikke", + "pomerans", + "nicotiana_tabacum", + "klein_kruiskruid", + "kerstboom", + "bergnachtorchis", + "veenpluis", + "laurierwilg", + "stokroos", + "sopropo", + "woestijnroos", + "meiklokje", + "terpentijnboom", + "winterlinde", + "pruikenboom", + "akkerwinde", + "amandelwolfsmelk", + "pitchpine", + "knolsteenbreek", + "kraakwilg", + "reuzenviool", + "cystopteris_montana", + "zoetzak", + "wolfskers", + "karpatenklokje", + "arengpalm", + "gele_plomp", + "clematis", + "cranberry", + "mastiekboom", + "parthenium_argentatum", + "kompassla", + "cipreswolfsmelk", + "palmvarens", + "weidekringzwam", + "torkruid", + "nachtschade", + "bosorchis", + "zomprus", + "prunus_domestica", + "sleedoorn", + "lork", + "stekelpapaver", + "greppelrus", + "molensteenkraag", + "paranoot", + "amandelwilg", + "beemdooievaarsbek", + "brassica_pekinensis", + "paradijsvogels", + "pronkboon", + "pijnboom", + "waternoot", + "brassica_chinensis", + "koolzaadolie", + "zeepkruid", + "heermoes", + "deodarceder", + "muskuskaasjeskruid", + "centaurea_cyanus", + "zilverkruid", + "hondspeterselie", + "paascactus", + "trifolium_repens", + "steeneik", + "voorjaarslathyrus", + "blackberry", + "zeeraket", + "speenkruid", + "veldhondstong", + "kattendoorn", + "lariks", + "strandpopulier", + "veldereprijs", + "zomerviolier", + "rode_klaver", + "winterjasmijn", + "aardpeer", + "echinocactus_grusonii", + "moerasandoorn", + "pruim", + "zomereik", + "medinilla_magnifica", + "zandraket", + "hertsmunt", + "blaassilene", + "sikkelklaver", + "vliegenorchis", + "ridderzuring", + "aristolochia_macrophylla", + "witte_paardenkastanje", + "doodsbeenderenboom", + "zwarte_moerbei", + "rozenpelargonium", + "savooienkool", + "kievitsbloem", + "bloemes", + "wilg", + "kerspruim", + "spinnenorchis", + "kardemom", + "reuzenlevensboom", + "gewone_steenraket", + "moseik", + "bloemkool", + "boslathyrus", + "wolfspoot", + "kroontjeskruid", + "parasolwaaierpalm", + "siertabak", + "beekpunge", + "vederesdoorn", + "schaduwgras", + "kardinaalswinde", + "waterlelie", + "wratziekte", + "knopherik", + "saccharomyces_cerevisiae", + "lievevrouwebedstro", + "saccharum_officinarum", + "vrouwenschoentje", + "wrangwortel", + "bijvoet", + "marmeladestruik", + "buckeye", + "cassave", + "vogelwikke", + "zeealsem", + "taraxacum_officinale", + "geelhout", + "bosanemoon", + "katwilg", + "bosrank", + "borstelkrans", + "blauwspar", + "akkerereprijs", + "marum", + "pas_op", + "steenbraam", + "witte_moerbei", + "veldbeemdgras", + "bosaardbei", + "zevenboom", + "beta_vulgaris", + "huttentut", + "sneeuwhaas", + "reukerwt", + "venusvliegenvanger", + "kersenboom", + "inkarnaatklaver", + "tayer", + "senna_alexandrina", + "spoorbloem", + "peet", + "zadelzwam", + "graslathyrus", + "wortelsysteem", + "bolletjesvaren", + "handjesgras", + "kleine_zandkool", + "bishopden", + "sparappel", + "kunstenaar", + "mansoor", + "slaapbol", + "tuinanjer", + "zwartmoeskervel", + "klokjesgentiaan", + "wegdistel", + "pronkerwt", + "coix_lacryma_jobi", + "malrove", + "akkermunt", + "hemelboom", + "jakobsladder", + "kruipbraam", + "verfbrem", + "witte_waterlelie", + "pijnboomhout", + "watervliegenval", + "speerdistel", + "yuka", + "witte_klaver", + "brandnetel", + "colocasia_esculenta", + "knolboterbloem", + "edelweiss", + "kalmoes", + "hypericum_maculatum", + "sint_janskruid", + "reuzenbovist", + "koraalwortel", + "allium_fistulosum", + "kemphaan", + "akkerdistel", + "mannetjesvaren", + "tuinkamperfoelie", + "koninginnekruid", + "arrhenatherum", + "braziliaanse_rubberboom", + "chrysanthemum_morifolium", + "lubbenkraag", + "bijenorchis", + "belladonna", + "moederkoorn", + "pteridium_aquilinum", + "gelderse_roos", + "netel", + "muurpeper", + "kruidwilg", + "mannetjesorchis", + "frederiksbloem", + "viola_odorata", + "zeepnotenboom", + "keizerskroon", + "reuzenbamboe", + "zandzegge", + "brazielboom", + "veldsalie", + "chrysanthemum", + "sint_maria", + "pijpbloem", + "kurkeik", + "vallisneria", + "venijnboom", + "mari\u00ebtteklokje", + "pinushout", + "castanea", + "scharlei", + "zeelathyrus", + "voortplantingssysteem", + "zilverlinde", + "brem", + "kapokboom", + "steenanjer", + "watermunt", + "bataat", + "natalpruim", + "alpenden", + "bokkenorchis", + "magnolia", + "kafferkoren", + "koningsvaren", + "hoornbloem", + "winterakoniet", + "dadelpalm", + "nephrolepis_exaltata", + "puntkroos", + "cherimoya", + "phellodendron_amurense", + "bosbingelkruid", + "berendruif", + "cacaoboon", + "abeel", + "beenbreek", + "haagwinde", + "bosandoorn", + "springkomkommer", + "heelblaadjes", + "seringen", + "reuzenpompoen", + "kruldistel", + "bolderik", + "vossenbes", + "kaneelappel", + "grijskruid", + "waterviolier", + "slangenden", + "camellia_japonica", + "slangenkruid", + "palmboom", + "slaplant", + "veldlathyrus" + ], + "ANIMAL": [ + "riviergronde", + "jachthond", + "zwemblaas", + "warana", + "kroongalziekte", + "acherontia", + "tongschar", + "ivoormeeuw", + "neusaap", + "hoorntje", + "sonomachipmunk", + "hoen", + "steenloper", + "houtsnip", + "vliegenvangers", + "rashond", + "chelonioidea", + "antilopegrondeekhoorns", + "marters", + "zwaangans", + "bordercollie", + "katvogel", + "witlippekari", + "dikhoornschaap", + "heremietkreeften", + "negenbandgordeldier", + "beringaalscholver", + "sperwer", + "buteo", + "bijeneters", + "riemvis", + "grondscharrelaars", + "nashvillezanger", + "schreeuwuil", + "the_raven", + "manenrob", + "lastdier", + "kniptorren", + "lachmeeuw", + "witkruingors", + "klauwkikker", + "waterhond", + "driestreepboa", + "vuursalamander", + "lachuil", + "brilpingu\u00efn", + "torenvalk", + "schaatsenrijder", + "veenmol", + "winterkoning", + "lederschildpad", + "lavendelastrild", + "bakerhaaien", + "poolwolf", + "porseleinhoen", + "hexagrammos_otakii", + "epstein_barrvirus", + "katoensnuitkever", + "zwartkuif_mierklauwier", + "alligatorschildpad", + "bruinvissen", + "teugelastrild", + "maskarenenpapegaai", + "slaapmuizen", + "spitssnuitsnavelhaai", + "schol", + "koningsstern", + "lierhert", + "groefkopadders", + "bastaardarend", + "eendenmossel", + "treurduif", + "steltstrandloper", + "heremietkreeft", + "zwaardwalvis", + "vogelhond", + "welpje", + "otter", + "winterkoninkje", + "black_widow", + "witkopzeearend", + "kortbekzeekoet", + "bakerhaai", + "marlijn", + "hazelhoen", + "elandantilope", + "bandsteltkluut", + "groenstaarttowie", + "goudfazant", + "ringmus", + "koereiger", + "grootoorkitvos", + "monniksgier", + "schapenteek", + "meeuw", + "arabier", + "stormmeeuw", + "brandgans", + "visdief", + "bandstaartduif", + "chinookzalm", + "pantserponen", + "schildluis", + "groenrugastrild", + "huzaaraap", + "snoek", + "billy_elliot", + "pijlstaart", + "vorkstaartmeeuw", + "schaapskopbrasem", + "wangzakeekhoorn", + "appelbloedluis", + "goudmakreel", + "poolhaas", + "grondeekhoorns", + "palmtortel", + "bosmuizen", + "wangzakeekhoorns", + "rubberboa", + "kunduz", + "ransuil", + "werkhond", + "haakbek", + "andescondor", + "zwaluwstaartwouw", + "mestkever", + "graanmot", + "zandwallaby", + "zwartrugfluitvogel", + "zanglijster", + "manta", + "meeltor", + "wandelstok", + "lemmingen", + "berglemming", + "zwartstaarthaas", + "sidderaal", + "parelhoen", + "carolina_winterkoning", + "wolfspinnen", + "krombekstrandloper", + "wielewaal", + "gierzwaluw", + "nachtbraker", + "tennesseezanger", + "carduelis", + "stellerzeeleeuw", + "uilen", + "muskuseend", + "kleine_buideleekhoorn", + "pisces", + "bronforel", + "korhoen", + "beerbaviaan", + "kroeskarper", + "strandwolf", + "achterbeen", + "sterns", + "rosse_franjepoot", + "gewone_vampier", + "bruinvis", + "riviergrondel", + "langpootmuggen", + "fazantspoorkoekoek", + "amerikaanse_marter", + "rivierdolfijnen", + "moeraskat", + "windhond", + "chipmunk", + "breedneusapen", + "huiscavia", + "boskoe", + "manenwolf", + "bevers", + "renvogel", + "steenuil", + "lactobacillus_acidophilus", + "grondluiaards", + "berenwelp", + "masaigiraffe", + "anioema", + "bankivahoen", + "bergnyala", + "ringstaartmaki", + "watermoccasinslang", + "teder", + "barbarieeend", + "regenboogforel", + "eikenpage", + "soepschildpad", + "bloedkoraal", + "tripang", + "havik", + "waterdwerghert", + "zeeleeuw", + "roomtipje", + "schemerhaai", + "stekelstaarthoen", + "poelepetaat", + "boomklever", + "hamerhaaien", + "stellerzeekoe", + "sabelmarter", + "diamondback", + "baardspecht", + "savannearend", + "politiehond", + "amerikaanse_nerts", + "zeehonden", + "zwartpunthaai", + "micropterus", + "zijdevlinderrups", + "trompetzwaan", + "zwartvoetpingu\u00efn", + "ekster", + "rietzanger", + "amerikaanse_rotswinterkoning", + "knobbelzwaan", + "kolenbranderschildpad", + "stermol", + "napoleonnetje", + "grienden", + "steppezebra", + "kruisbek", + "kriebelmuggen", + "raven", + "plakker", + "homo_sapiens", + "hertogsvis", + "steenarend", + "loopkevers", + "hoornaar", + "la_ardilla_roja", + "postduif", + "tortelduif", + "arkansaskoningstiran", + "kleinste_strandloper", + "tabaksmoza\u00efekvirus", + "beekforel", + "pissebed", + "witkinstormvogel", + "horsmakreel", + "grielen", + "withandgibbon", + "kievit", + "sultanshoen", + "sierschildpad", + "passer", + "forelbaars", + "katoenrat", + "blaaswier", + "hekstaartleguaan", + "bartrams_ruiter", + "gerbillus_jamesi", + "the_crow", + "wolfsspin", + "kerrieboom", + "prairiehonden", + "chinese_vuurbuiksalamander", + "zeelamprei", + "fluitzwaan", + "ruitpython", + "hamerhaai", + "brilparulazanger", + "reigers", + "donkey", + "doornhaai", + "bijtschildpad", + "veldtrechterspin", + "berghoen", + "sijs", + "koehaaien", + "bosuil", + "manenschaap", + "stormvogeltje", + "citruswolluis", + "karetschildpad", + "sporenkievit", + "boomeekhoorns", + "witborstboomklever", + "andesflamingo", + "langstaartwezel", + "kippenvlees", + "zonnevis", + "landpissebedden", + "waterpieper", + "baltimoretroepiaal", + "lossen", + "witkeelgors", + "elft", + "kikkers", + "zandkat", + "ijseend", + "keizergans", + "mossel", + "galapagosreuzenschildpad", + "reiger", + "appelvlieg", + "guanovleermuis", + "accipiter", + "dambordvlieg", + "dodaars", + "pestvogel", + "poolvos", + "de_meeuw", + "huismuis", + "varkensbeest", + "veldgors", + "amerikaanse_boslijster", + "marter", + "helmparelhoen", + "nevelpanter", + "karbouw", + "strontkever", + "vierteenlandschildpad", + "falcon", + "zwartkapastrild", + "kortsnuitbeer", + "fruitmot", + "steenmarter", + "gestreepte_strandloper", + "cacaomot", + "everzwijn", + "secretarisvogel", + "werkbij", + "fluiter", + "zijdevlinder", + "kraaghoen", + "koter", + "hoenderachtig", + "kleintandzaagvis", + "waterkonijn", + "stierhaai", + "watersnip", + "goudwolf", + "bijenkoningin", + "walvishaai", + "zwartvoetalbatros", + "banteng", + "chumzalm", + "koningsmakreel", + "waterhoen", + "troepialen", + "kettingsnoek", + "hazelmuis", + "piesen", + "gierzwaluwen", + "stralenschildpad", + "witbuikzandhoen", + "brulapen", + "hoendergans", + "pinctada_margaritifera", + "zeegans", + "dassen", + "rijstvogel", + "winterkoningen", + "leeuwenwelp", + "kanoet", + "zanggors", + "duikeenden", + "borstvin", + "shamalijster", + "pauwkalkoen", + "donald_duck", + "thomsongazelle", + "eskimowulp", + "salmo_salar", + "koningsgier", + "pantserkrokodil", + "prairiehoen", + "zeggewinterkoning", + "ortolaan", + "oeverzwaluw", + "buidelduivel", + "zilvermeeuw", + "iller", + "zandloopkevers", + "rietwolf", + "boomkwartel", + "houtduif", + "moose", + "dambordvliegen", + "boommarter", + "schijnaardbei", + "musgors", + "buikvin", + "knorrepos", + "langstaartschubdier", + "steppehoen", + "wisent", + "zeenegenoog", + "prairiehond", + "zomertortel", + "glanskop", + "rankpootkreeften", + "evenhoevigen", + "kortschildkevers", + "steenpatrijs", + "bunzing", + "diamantrugschildpad", + "buizerd", + "botervis", + "baleinwalvissen", + "sterschildpad", + "huiszwaluw", + "douglaseekhoorn", + "goudsijs", + "mestkevers", + "robijnkeelkolibrie", + "zadelrob", + "ictiobus_niger", + "bananenvlieg", + "waterral", + "megascops", + "goudvink", + "zwartsnavelkoekoek", + "klapmuts", + "sable", + "geleedpotigen", + "coloradokever", + "zilvertaling", + "panterschildpad", + "beloega", + "zilverdas", + "texasschildpad", + "halsbandpekari", + "savanneolifant", + "floridakonijn", + "rijstklander", + "laplanduil", + "schuitbekreiger", + "herpes_zoster", + "monnikszanger", + "gordelmol", + "mensenhaai", + "trompetkraanvogel", + "arthropoda", + "berenjong", + "kaswittevlieg", + "schildluizen", + "miljoenpoten", + "amerikaanse_klapekster", + "spinduizendpoot", + "balkansperwer", + "rotgans", + "steltkluut", + "bosmuis", + "melkslang", + "zwartvoetbunzing", + "grote_weerschijnvlinder", + "dooierzak", + "nachtpauwoog", + "tienponder", + "bergkwartel", + "elfenstern", + "podde", + "kanaalmeerval", + "rugstreeppad", + "hertachtigen", + "kruisboomkikker", + "strandgaper", + "goudstofdaggekko", + "borneogoudkat", + "bossneeuwhoen", + "kaalkopooievaar", + "roekoe", + "huismus", + "braamsluiper", + "przewalskipaard", + "bruinwieren", + "kamratten", + "spintmijten", + "goudhamster", + "granaatastrild", + "kafferbuffel", + "witkopmeeuw", + "nonastrild", + "varkensdas", + "lampongaap", + "schoorsteengierzwaluw", + "congopauw", + "witliphert", + "klein_koolwitje", + "kerkuil", + "kropgazelle", + "botswanatrap", + "mantis", + "rouwmantel", + "duifzeekoet", + "ni_uil", + "poelsnip", + "koningscobra", + "verpleegsterhaai", + "vrouwenloper", + "geleidehond", + "sint_jacobsvlinder", + "citroenhaai", + "klokschildpad", + "driehoeksmossel", + "muskusschildpad", + "berggorilla", + "pimpelmees", + "gramper", + "zandvlo", + "graspieper", + "kleerluis", + "bosspitsmuis", + "grindewal", + "paashaas", + "mandarijneend", + "amerikaanse_watersnip", + "raaf", + "korenslang", + "bergzebra", + "baleinwalvis", + "kleine_marters", + "barramundi", + "waterbuffel", + "lemming", + "hoofdluis", + "moerasgors", + "monarchvlinder", + "sterrog", + "kermodebeer", + "amazonemier", + "eidereend", + "hoornaars", + "keizerspingu\u00efn", + "miljoenpoot", + "koeren", + "boomhoppen", + "bandijsvogel", + "millers_waterspitsmuis", + "kardinaaltetra", + "wezel", + "ruwenzoriduiker", + "langharig", + "leeuwenwelpje", + "wijfjeskat", + "tadelrob", + "prairiehaas", + "heidehoen", + "spoelworm", + "heremietlijster", + "javamens", + "baardrob", + "trapvechtkwartel", + "gorilla_gorilla", + "kerkuilen", + "griend", + "edelhert", + "kreeg", + "louisianatangare", + "halsbandparkiet", + "rietkat", + "houtbij", + "slingerapen", + "sporenschildpad", + "merel", + "langstaartstekelvarken", + "scharrelaar", + "wilgengors", + "otters", + "koningspingu\u00efn", + "cederpestvogel", + "guinees_biggetje", + "bergeend", + "ringslang", + "vingerdier", + "microbes", + "goudjakhals", + "waakhond", + "grote_parelmoervlinder", + "lippenbeer", + "zwarthalsooievaar", + "zijderups", + "bultrug", + "eider", + "damagazelle", + "bosolifant", + "pollak", + "zandbankhaai", + "meeuwen", + "boomzwaluw", + "arvicola", + "carolinaparkiet", + "geleedpotige", + "komodovaraan", + "berner_sennenhond" + ], + "LOCATION": [ + "al_jazeera", + "de_wolden", + "falklandeilanden", + "chathameilanden", + "bejaardentehuis", + "westkust", + "speelplein", + "bedrijventerrein", + "maar_natuurlijk", + "sint_margriete", + "sint_eustatius", + "so_what", + "rodelampjesbuurt", + "muziekschool", + "bosmarmot", + "speeltuin", + "vsa", + "speelterrein", + "zoet_water", + "park", + "het_bildt", + "non_plus_ultra", + "het_voor", + "dark_horse", + "bow_wow", + "united_states_army", + "s_hertogenbosch", + "s_tog", + "sint_helena", + "tennisbaan", + "la_roche_en_ardenne", + "trifolium_repens", + "entre_deux", + "qingmingfestival", + "de_haan", + "sint_maarten", + "op_de_koop_toe", + "op_straat", + "het_kanaal", + "de_ori\u00ebnt", + "de_oost", + "de_jaren", + "tennisveld", + "saksen_anhalt", + "trois_rivi\u00e8res", + "sint_truiden", + "biscuitgebak", + "tempelberg", + "in_de_wolken", + "drakenvrucht", + "land", + "de_pinte", + "een_steek_laten_vallen", + "saint_vincent", + "niets_te_danken", + "geen_dank", + "ringweg", + "blue_mountains", + "verschroeide_aarde", + "het_eiland", + "er_zijn", + "bruine_lijster", + "de_veer", + "sint_stevens_woluwe", + "in_het_midden", + "kanaaleilanden", + "nieuw_engeland", + "olijfberg", + "lake_of_the_woods", + "on_the_road", + "beluik", + "the_black_hole", + "nationale_vergadering", + "saint_lucia", + "vogelnestje", + "de_panne", + "krachtcentrale", + "de_eilanden", + "kerstman", + "hat_yai", + "arena", + "sri_lanka", + "twee_zusjes", + "de_vrede", + "de_bilt", + "sint_kruis", + "edwardmeer", + "kerstavond", + "energiecentrale", + "hongaars_parlement", + "three_amigos", + "de_kersentuin", + "t_kofschip", + "sint_pieter", + "the_rolling_stones", + "psychiatrisch_ziekenhuis", + "al_anz", + "tanameer", + "cordon_bleu", + "saint_lawrence", + "michiganmeer", + "kryvy_rih", + "de_marne", + "nieuwe_wereld", + "oudjaar", + "schone_slaapster", + "heitor_villa_lobos", + "het_einde", + "psychiatrische_instelling", + "de_amazone", + "telefooncentrale", + "jordaan", + "al_ain", + "om_en_bij", + "pterocarpus_indicus", + "sint_niklaas", + "hoofdstraat", + "sint_anthonis", + "het_spoor", + "hoerenbuurt" + ], + "ORG": [ + "dominion", + "marechaussee", + "nieuwer_amstel", + "zondagsschool", + "mogolrijk", + "politiestaat", + "het_goede", + "vele_handen_maken_licht_werk", + "gele_rivier", + "wentelteefje", + "doortje", + "burgerrechten", + "kauwgom", + "wicca", + "welvaartsstaat", + "zonnevlecht", + "an_education", + "jan_mayen", + "ambtenarij", + "s_gravenambacht", + "kunstgalerie", + "the_usual_suspects", + "sint_amands", + "sint_helena", + "eenheidsmatrix", + "brokstukken", + "aa", + "draaideur", + "the_comedy_of_errors", + "arda", + "gemeentehuis", + "bollywood", + "strijdkrachten", + "toerekeningsvatbaar", + "det_norske_arbeiderpartiet", + "schminken", + "trouwens", + "posterij", + "europol", + "schutzstaffel", + "kieskring", + "bakkie", + "sankt_andreasberg", + "upper_class", + "volksfront", + "the_who", + "staatskapitalisme", + "homohuwelijk", + "luchtmacht", + "don_juan_tenorio", + "non_plus_ultra", + "moedersleutel", + "het_nieuwe", + "sint_barbara", + "porte", + "college", + "saint_clairmeer", + "oudejaarsavond", + "rassensegregatie", + "san_francisco", + "kristdemokraterna", + "rijksdienst", + "vivat", + "kiescollege", + "un", + "a_chorus_line", + "war_machine", + "overheid", + "overigens", + "natriumsilicaat", + "volkenbond", + "den_helder", + "burgerlijk_recht", + "sterrenhoop", + "privaatonderwijs", + "peuterklas", + "op_heterdaad", + "hoge_porte", + "flashmob", + "strijdmacht", + "v\u0129nh_long", + "postkantoor", + "armee", + "nara", + "nieuwe_maan", + "normaalschool", + "kredietunie", + "va", + "vrijmetselarij", + "werkgroep", + "wie_bent_u", + "landbouw", + "verzorgingsstaat", + "magisch_vierkant", + "middenschool", + "andromedanevel", + "gao", + "stadhuis", + "van_alles_en_nog_wat", + "botanische_tuin", + "zedenbrigade", + "blaaskapel", + "dot", + "prohibition_party", + "sint_gillis_waas", + "the_family_man", + "weimarrepubliek", + "s_hertogenbosch", + "heilsleger", + "mahayana", + "niet_aanraken", + "markteconomie", + "onderzoeksinstituut", + "strijkkwartet", + "kerngezin", + "bloedbroeders", + "amerikanistiek", + "sint_genesius_rode", + "nicolaas_van_myra", + "wat_is_er_aan_de_hand", + "saint_vincent", + "han_dynastie", + "kostschool", + "rechtvaardigheid", + "metselen", + "vaishnavisme", + "the_faculty", + "don_juan", + "de_grote_vier", + "mijn_naam_is", + "the_new_school", + "ai", + "vers_water", + "front_progressiste_du_peuple_seychellois", + "in_het_jaar_des_heren", + "wie_ben_je", + "winkelcentrum", + "nog_steeds", + "noordwestelijke_doorvaart", + "chiang_mai", + "nu_dat_ik_eraan_denk", + "kunstgalerij", + "sint_lievens_houtem", + "kaapverdi\u00eb", + "harmonieorkest", + "dia", + "heersende_klasse", + "de_heer", + "gatt", + "staatsgreep", + "hoogoven", + "studentenvakbond", + "muziekindustrie", + "s_gravenhoek", + "de_druiven_der_gramschap", + "germanistiek", + "ab_initio", + "raadhuis", + "hooggerechtshof", + "parasport", + "albertmeer", + "doodseskader", + "le_mans", + "lobbygroep", + "bijvullen", + "christian_science", + "behoudswet", + "parochiekerk", + "donjuan", + "ouder_amstel", + "verdediging", + "bondsraad", + "quakers", + "school", + "morgenster", + "verenigingskerk", + "ik_heet", + "middenklasse", + "schaduwkabinet", + "the_breakfast_club", + "vsa", + "hogerhuis", + "sint_agatha_berchem", + "andersom", + "zeemacht", + "rabindranath_tagore", + "the_marx_brothers", + "gestapo", + "ik_hou_van_jou", + "gerechtigheid", + "zeshonderd", + "westkapelle_binnen", + "sint_agatha", + "sint_pieters_leeuw", + "ronselaarsbende", + "turnzaal", + "stadstaat", + "the_full_monty", + "zwarte_markt", + "na_christus", + "aangepast", + "maria_tenhemelopneming", + "centrale_bank", + "commercie", + "vraagteken", + "troetelbeertjes", + "nieuw_ginneken", + "effectenbeurs", + "eenogig", + "duitse_keizerrijk", + "muziekschool", + "rentabiliteitsdrempel", + "kattenoog", + "personeelszaken", + "scholengemeenschap", + "who_are_you", + "de_vuursche", + "babyboom", + "man_overboord", + "chiang_rai", + "stronnictwo_narodowe", + "al_jazeera", + "koppakking", + "wederom", + "de_maatschappij", + "vakbond", + "ham_sur_heure_nalinnes", + "gouden_eeuw", + "disa", + "ambachtsschool", + "ontwikkelingsland", + "assembl\u00e9e_nationale", + "europe", + "wie_ben_jij", + "dimokratik\u00f3_k\u00f3mma", + "po", + "mossad", + "derde_partij", + "weermacht", + "rode_zee", + "nautilus_pompilius", + "toerekenbaar", + "baskenland", + "as_majeur", + "reisbureau", + "basisschool", + "gehandicaptensport", + "hedgefonds", + "hollywood", + "alexander_de_grote", + "karmelgebergte", + "ja\u00efnisme", + "sint_oedenrode", + "tactiek_van_de_verschroeide_aarde", + "militaire_academie", + "klein_duimpje", + "saint_barth\u00e9lemy", + "sturmabteilung", + "romeins_recht", + "who", + "nationaalsocialistische_duitse_arbeiderspartij", + "vrijgezellenfeest", + "los_angeles", + "nato", + "spaarbank", + "baltimore_orioles", + "brandweer", + "anno_domini", + "groepszaak", + "jozef_van_nazareth", + "ad_hoc", + "krijgsmacht", + "koffie_verkeerd", + "city_hall", + "bevolkingsdichtheid", + "mi", + "kunstmuseum", + "ik_hou_van_je", + "by_the_way", + "rooms_katholieke_kerk", + "en_anderen", + "burgermaatschappij", + "internationale_telecommunicatie_unie", + "persbureau", + "in_situ", + "wisselkantoor", + "katholieke_kerk", + "hortus_botanicus", + "sint_martens_latem", + "zuidpool", + "manhattanproject", + "middle_class", + "doc", + "olijfberg", + "marinier", + "volkenrecht", + "manschappen", + "al_ain", + "basisonderwijs", + "niet_lineair_systeem", + "groepsvordering", + "hagana", + "dominicanen", + "van_tijd_tot_tijd", + "commerce", + "streptococcus_pyogenes", + "heilige_familie", + "j\u00e9_van_h\u00e9t", + "eu", + "opstopping", + "lagerhuis", + "reclamebureau", + "slaapfeestje", + "uitverkorene", + "rode_kruis", + "blauwogig", + "langemark_poelkapelle", + "doornroosje", + "al_lang", + "the_silence_of_the_lambs", + "groene_partij", + "bovenmeer", + "soennisme", + "bloomsburygroep", + "house_of_lords", + "duitse_rijk", + "planwirtschaft", + "nieuwe_wegen", + "dierenrechten", + "troepen", + "door_mensenhanden_gemaakt", + "internationaal_gerechtshof", + "witte_huis", + "konserwatiewe_party", + "tao\u00efsme", + "van_gogh", + "hanze", + "bomauto" + ], + "PRODUCT": [ + "de_liefdesbrief", + "installatieautomaat", + "noorderlicht", + "het_spijt_me", + "justin_bieber", + "goeiemorgen", + "stilleven", + "cookeilanden", + "koffiekan", + "raderstoomboot", + "jachtbommenwerper", + "rekenliniaal", + "s_tog", + "keizersnede", + "goedemorgen", + "take_off", + "al_jazeera", + "signaalverwerking", + "schoppenvrouw", + "zeilschip", + "een_poppenhuis", + "o_ring", + "diego_garcia", + "koffiepot", + "drie_koninkrijken", + "tweebenig", + "tuttifrutti", + "mensenrechten", + "levenswerk", + "sportwagen", + "booglamp", + "militair_luchtvaartuig", + "de_goddelijke_komedie", + "muziekdoos", + "achterafstraatje", + "julius_caesar", + "saint_vincent", + "zwembroek", + "the_music_box", + "the_star_spangled_banner", + "hemellichaam", + "het_transgalactisch_liftershandboek", + "poppenhuis", + "monte_cristo", + "pantserwagen", + "de_hongerspelen", + "bij_de_gratie_gods", + "eens_christens_reize_naar_de_eeuwigheid", + "die_hard", + "te_voorschijn_komen", + "kogellager", + "city_hall", + "hardgekookt", + "ik_bied_mijn_excuses_aan", + "la_ciociara", + "after_burner", + "achterafstraat", + "ga_weg", + "vergeet_mij_niet", + "waterput", + "leidstar", + "op_het_nippertje", + "ijsklontje", + "kortsluiting", + "zonnebank", + "liefdesbrief", + "vergeet_me_niet", + "la_dolce_vita", + "deutsche_welle", + "voerbak", + "all_right", + "gong", + "etensbak", + "the_scarlet_letter", + "rechten_van_de_mens", + "de_vier_jaargetijden", + "kaap_hoorn", + "in_de_ban_van_de_ring", + "speeldoos", + "driedimensionaal", + "de_gelaarsde_kat", + "mario_andretti", + "theebus", + "hooglied", + "de_tijdmachine", + "triomfboog", + "sint_maria", + "het_noorderlicht", + "kerstman", + "heilige_geest", + "the_hitchhiker's_guide_to_the_galaxy", + "beluik", + "de_facto", + "la_modification", + "huiscavia", + "door_activa_gedekt", + "raderboot", + "strijdbijl", + "op_onderpand_van_activa", + "pijporgel", + "de_hongerspelentrilogie", + "de_hond_van_de_baskervilles", + "halfpijp", + "kerstboom", + "raderschip", + "novo_mesto" + ], + "BIO_CHEM_ENTITY": [ + "c_reactief_prote\u00efne", + "siliciumdioxide", + "mononatriumglutamaat", + "siliciumnitride", + "strontiumchloride", + "guanosinedifosfaat", + "antimoonkaliumtartraat", + "magnesiumchloride", + "melkzuur", + "coniferylalcohol", + "capronzuur", + "polyvinylchloride", + "adenosinedifosfaat", + "di_ethylether", + "cesiumjodide", + "magnesiumperoxide", + "citroenzuur", + "salmiakzout", + "diethylether", + "beendermeel", + "fenylazijnzuur", + "wolfraamzuur", + "magnesiumcitraat", + "boterzuur", + "kaliumjodide", + "zenuwgroeifactor", + "telluurzuur", + "laurinezuur", + "salicylzuur", + "polymelkzuur", + "zinkchloride" + ], + "QUANTITY": [ + "parkeerterrein", + "vierkantswortel", + "si_stelsel", + "franse_frank", + "zeemijl", + "vijfhonderd", + "calorie", + "driedimensionaal", + "schilling", + "twee\u00ebntwintig", + "drie\u00ebnnegentig", + "ton", + "zesentwintig", + "dollar", + "vierentwintig", + "riyal", + "rangtelwoord", + "drie_koninkrijken", + "toontaal", + "g", + "drie\u00ebntwintig", + "negenentwintig", + "the_real_world", + "elektronvolt", + "zevenentwintig", + "vijver", + "rial", + "achtentwintig", + "parkeerbon", + "parkeergarage", + "windrichting", + "een_voor_een", + "priemgetal", + "verdichtingspunt", + "parkeermeter", + "pond", + "vijfentwintig", + "pond_sterling", + "een_tegelijk", + "kettingbreuk", + "cypriotisch_pond", + "lichtjaar", + "parkeerplaats", + "anders_celsius" + ], + "FOOD": [ + "appelsap", + "bruiloftstaart", + "suikerwater", + "druivensap", + "tartaarsaus", + "leidingwater", + "nagerecht", + "mousse", + "chocoladereep", + "chocolademelk", + "smeltkaas", + "golden_delicious", + "borrelhapjes", + "sinaasappelsap", + "chocoladetaart", + "soesje", + "woestijn", + "waspompoen", + "cayennepeper", + "daucus_carota", + "bubbelwijn", + "kleinbekbaars", + "oploskoffie", + "christmas_pudding", + "melkchocolade", + "paneermeel", + "kropbrood", + "suikerspin", + "petitfour", + "vijgcactus", + "slagroom", + "hollandaisesaus", + "roggebrood", + "wijnazijn", + "verjaarstaart", + "granny_smith", + "capsicum", + "zachtgekookt", + "appelflap", + "wentelteefje", + "frisdrank", + "kandij", + "lendebiefstuk", + "zuurstok", + "sterrenkers", + "volkorenbrood", + "pasteitje", + "bittergarnituur", + "kauwgom", + "verjaardagstaart", + "waldorfsalade", + "saus", + "h\u00fcttenk\u00e4se", + "zonnebloemolie", + "esdoornsiroop", + "kikkerbilletjes", + "cornedbeef", + "tarwebloem", + "melkpoeder", + "chilipeper", + "ahornsiroop", + "visstick", + "schuimwijn", + "pinot_noir", + "rawit", + "appeltaart", + "friet", + "bruidstaart", + "frieten", + "cacaoboter", + "spuitwater", + "schildpadsoep", + "fastfood", + "wittebrood", + "koemelk", + "ganzenlever", + "paasei", + "palmolie", + "t_bone", + "plantenolie", + "rodekool", + "ossenstaartsoep", + "chili", + "huttenkaas", + "lunch", + "kruidenthee", + "vruchtensalade", + "kattenvoer", + "antipasto", + "middageten", + "olijfolie", + "pudding", + "pindakaas", + "gelukskoekje", + "citroensap", + "dessert", + "tuttifrutti", + "stoofappel", + "cassonade", + "kraantjeswater", + "eendenlever", + "roomijs", + "aardappelsalade", + "tafelzout", + "pompernikkel", + "drinkwater", + "gemberbier", + "bitterkers", + "aardappelchips", + "lippenbalsem", + "snoepreep", + "ros\u00e9wijn", + "bladerdeeg", + "pot_au_feu", + "tussendoortje", + "priklimonade", + "bechamelsaus", + "caesarsalade", + "klappermelk", + "veenbessap", + "pompoentaart", + "kippensoep", + "ijskoffie", + "theeblad", + "cacaopoeder", + "strijkroom" + ], + "LANGUAGE": [ + "assamees", + "waals", + "shona", + "ooi", + "galicisch", + "maleisich", + "deens", + "klemtoon", + "venda", + "marshallees", + "poetsmiddel", + "bambara", + "griek", + "kongo", + "grieks", + "akan", + "peipusmeer", + "assami", + "roemeense", + "corsicaans", + "sindhi", + "aksent", + "griekse", + "pools", + "hongaarse", + "chinees", + "pali", + "gasser", + "iers", + "aymara", + "manx", + "welsh", + "noorse", + "malayalam", + "proven\u00e7aals", + "roemeens", + "catalaan", + "japannees", + "zweeds", + "hindi", + "samoaan", + "divehi", + "georgisch", + "chinese", + "keltisch", + "esperanto", + "duitser", + "tongval", + "shangaan", + "koerdisch", + "soendanezen", + "portugees", + "lingala", + "francoproven\u00e7aals", + "wolof", + "cree", + "catalaanse", + "portugese", + "maleis", + "hongaars", + "speech", + "tagalog", + "japanse", + "ido", + "quechua", + "tonga", + "kannada" + ], + "RACE": [ + "ierse", + "blanken", + "islander", + "indian_airlines", + "turk", + "eilandbewoner", + "zwarten", + "turkse", + "vietnamese", + "fran\u00e7aise", + "the_mexican", + "engelsen", + "fransman", + "chinese", + "nederlanders", + "japanners", + "polynesisch", + "eilander", + "fransen", + "joodse" + ], + "LAW": [ + "publiekrecht", + "civiel_recht", + "handelspapier", + "huiszoekingsbevel", + "hooggerechtshof", + "persvrijheid", + "kiessysteem", + "krijgswet", + "burgerlijk_recht", + "groepsvordering", + "groepszaak", + "godsdienstvrijheid", + "volkenrecht", + "ne_bis_in_idem", + "strafrecht", + "doodvonnis", + "bestuursrecht", + "advocatenkantoor", + "federal_bureau_of_investigation", + "handelsrecht" + ], + "RELIGION_MEMBER": [ + "anabaptist", + "guru", + "the_hindu", + "katholiek", + "protestant", + "moor", + "jezu\u00efet", + "baptistisch", + "benedictijn", + "athe\u00efst", + "goddeloze", + "broeder", + "athe\u00efste", + "mormon", + "baptist", + "franciscanen", + "trappist", + "zendeling", + "satanist", + "parsi", + "mon", + "broer", + "godloochenaar", + "boeddhistisch", + "benedictijner" + ], + "ANAT": [ + "opperarm", + "bovenarm", + "hartspierweefsel" + ], + "GPE": [ + "sint_agatha_rode", + "sint_ulriks_kapelle", + "witgoud", + "sint_kruis_winkel", + "sint_amandsberg", + "saint_domingue", + "sint_blasius_boekel", + "sint_laureins", + "lo_reninge", + "sint_baafs_vijve", + "dar_es_salaam", + "sint_martens_bodegem", + "industriegebied", + "sint_joris", + "valentijnsdag", + "sint_goriks_oudenhove", + "s_gravenvoeren", + "olympisch_dorp", + "werkverschaffing", + "sint_maarten", + "bergpas", + "veel_geluk", + "sint_margriete_houtem", + "sint_barbara", + "sint_eloois_winkel", + "sint_michielsgestel", + "sint_pieters_voeren", + "novum_testamentum", + "suikerbroodberg", + "sint_lambrechts_herk", + "hagia_sophia", + "heilige_geest", + "sint_maria_lierde", + "sint_lenaarts", + "sint_pieters_rode", + "nieuwe_testament", + "onze_lieve_vrouw_van_zeven_wee\u00ebn", + "gran_canaria", + "duizendeilanden", + "sint_maria_latem", + "sint_gillis_bij_dendermonde", + "suikerbrood", + "somme_leuze", + "oud_valkenburg", + "sint_kornelis_horebeke", + "sint_martens_lierde", + "sint_martens_voeren", + "sint_pieters_kapelle", + "rode_kruis", + "sint_antelinks", + "sint_laureins_berchem", + "al_andalus", + "sint_denijs_boekel", + "sint_joris_winge", + "la_rochelle", + "sint_maria_oudenhove", + "sint_maria_horebeke", + "onze_lieve_vrouw", + "taishan", + "charlottenburg_wilmersdorf", + "barbara_van_nicomedi\u00eb", + "la_gomera", + "sint_eloois_vijve", + "sint_jan_in_eremo", + "sao_tom\u00e9", + "onze_lieve_vrouw_van_smarten", + "mensenrechten", + "sint_lievens_esse", + "tr\u00e0_vinh" + ], + "FAC": [ + "kerncentrale", + "volksfront", + "concertgebouw", + "westmuur", + "bovenkruier", + "drukkerij", + "het_laatste_avondmaal", + "sacramentsdag", + "drie\u00ebndertig", + "the_trap_door", + "de_vier_jaargetijden", + "mauritius_papeda", + "raadhuis", + "peter_i_van_rusland", + "arnold_sch\u00f6nberg", + "politiebureau", + "handelspost", + "handelsplaats", + "plaza", + "het_laatste_oordeel", + "universiteitsstad", + "sublieme_porte", + "kunstacademie", + "lagere_school", + "basisschool", + "t_cel", + "concertzaal", + "drinkenfontein", + "kunstgalerie", + "flatgebouw", + "saint_lucia", + "papiermolen", + "triomfboog", + "winnie_de_poeh", + "sint_denijs_westrem", + "winkelcentrum", + "schreefloos", + "sint_jozefkerk", + "gemaal", + "winkelgalerij", + "verhevene_porte", + "posterij", + "titus_livius", + "klaagmuur", + "kunstgalerij", + "gemeentehuis", + "gradatim", + "getijdenmolen", + "hangbrug", + "treinstation", + "de_toverberg", + "verheven_porte", + "friedrichshain_kreuzberg" + ], + "POLITICAL_PARTY": [ + "partij", + "conservative_party", + "labour_party", + "partij_van_de_arbeid", + "agrarische_partij", + "politieke_partij", + "kommunistiska_partiet", + "liberal_party", + "liberale_partij", + "nationale_partij_van_zuid_afrika", + "democratische_partij", + "whig_party", + "partido_popular", + "democratisch_republikeinse_partij", + "malta_labour_party", + "det_norske_arbeiderpartiet", + "irish_labour_party", + "partido_socialista", + "progressieve_partij", + "kwomintang", + "parti_socialiste", + "republikeinse_partij", + "communistische_partij", + "milj\u00f6partiet_de_gr\u00f6na", + "sociaaldemocratische_partij", + "australian_labor_party", + "conservatieve_partij", + "socialistische_partij", + "parti_populaire" + ], + "GENDER": [ + "jonge", + "mademoiselle", + "meidje", + "gentleman", + "grietje", + "deern", + "het_zwakke_geslacht", + "men", + "vrijster", + "jongedame", + "dame", + "boy", + "van_de_verkeerde_kant", + "guido", + "het_schone_geslacht", + "masculien", + "tribade", + "transgender", + "vrouwelijk", + "matrone", + "man", + "gal", + "lady", + "transgenderisme" + ], + "PERSON": [ + "zelfcontrole", + "door_middel_van", + "julius_caesar", + "al_gore", + "saint_vincent", + "boek_der_veranderingen", + "er_niet_bij", + "la_grange", + "don_delillo", + "aan_de_hand_van", + "ik_ook", + "edward_osborne_wilson", + "gewoon_eekhoorntjesbrood", + "de_witt", + "t_bone", + "al_de", + "george_v", + "al_amin", + "igor_sikorsky", + "van_de", + "peter_dawson", + "franciscus_van_assisi", + "seleucus_i_nicator", + "zonnevis", + "maxwell_anderson", + "rudolf_hess", + "herbert_george_wells" + ], + "SOC_ECO_CLASS": [ + "landbouw", + "samenleving", + "bon_ton", + "landadel", + "center", + "broederschap", + "kastenstelsel", + "middenklasse", + "proletariaat", + "burgerklasse", + "volksplaats", + "misdaadwereld", + "maatschappij", + "weinig", + "waki", + "samoerai", + "bourgeoisie" + ], + "RELIGION": [ + "zen", + "salafisme", + "donatisme", + "presbyterianisme", + "calvinisme", + "wahabisme", + "katharen", + "maniche\u00efsme", + "methodisme", + "islam", + "christian_science", + "wicca" + ], + "PERSON_PRONOUN": [ + "mijzelf", + "vosse", + "het_hare", + "de_jouwe", + "groeve", + "het_jouwe", + "tutoyeren", + "mezelf", + "i", + "de_hare", + "thee", + "he", + "uw", + "jijen", + "our", + "her", + "die_van_ons", + "de_onze", + "het_onze", + "we", + "me", + "mijne", + "van_jou" + ], + "EVENT": [ + "wereldtentoonstelling", + "fleur_de_lys", + "zo_is_het_leven", + "filmfestival", + "golfoorlog", + "sing_sing", + "polsstokhoogspringen", + "arcadespel", + "dodendans", + "grote_prijs" + ], + "POLITICAL_PARTY_MEMBER": [ + "makker", + "communiste", + "communist", + "communistisch" + ], + "UNION": [ + "studentenvakbond", + "wereldpostunie" + ], + "TITLE": [ + "meneer" + ], + "MEDICAL_THERAPY": [ + "bloeddruk" + ], + "ner_regexes": [ + [ + "PERSON", + "\\D+ \\D+|\\D+ \\D+|\\D+ \\D+|\\D+ \\D+-\\D+|\\D+ \\D+|\\D+ \\D+|\\D+ \\D+|\\D+ \\D+-\\D+", + false, + [] + ] + ], + "FIRST_NAME_FEMALE": [ + "lara", + "noortje", + "fabi\u00ebnne", + "silke", + "mila", + "karlijn", + "sara", + "yara", + "danique", + "lindsey", + "hannah", + "no\u00eblle", + "jenna", + "renske", + "suus", + "amy", + "emily", + "cornelia", + "janne", + "jolijn", + "maryam", + "meike", + "lizzy", + "jade", + "stella", + "pippa", + "dana", + "isa", + "elise", + "ashley", + "olivia", + "yinthe", + "tessa", + "linde", + "vaj\u00e8n", + "jasmijn", + "ilse", + "jo\u00eblle", + "chlo\u00eb", + "lois", + "lola", + "tirza", + "sofie", + "maria", + "lynn", + "ise", + "myrthe", + "yasmine", + "esm\u00e9e", + "fenne", + "quinty", + "sophie", + "nisa", + "naomi", + "catharina", + "jet", + "rosalie", + "janna", + "lauren", + "yfke", + "imke", + "zoey", + "ize", + "sanne", + "eliza", + "kaylee", + "f\u00e9line", + "feline", + "puck", + "anna", + "helena", + "maartje", + "elisa", + "annemijn", + "saar", + "jennifer", + "maaike", + "madelief", + "anne", + "lizz", + "victoria", + "amber", + "maud", + "floortje", + "tess", + "eva", + "merle", + "lisa", + "fiene", + "mette", + "laura", + "evi", + "kim", + "femke", + "jill", + "esmee", + "lily", + "aaliyah", + "frederique", + "liz", + "ivy", + "evie", + "veerle", + "kiki", + "suze", + "julie", + "lieve", + "selena", + "jaylinn", + "liv", + "pien", + "zo\u00eb", + "senna", + "hanna", + "rosa", + "lana", + "juul", + "kyra", + "lena", + "demi", + "kayleigh", + "noor", + "charlotte", + "merel", + "annabel", + "nora", + "yasmin", + "lo\u00efs", + "bo", + "mara", + "ella", + "jinthe", + "fien", + "eline", + "esther", + "fleur", + "isabel", + "britt", + "lot", + "valerie", + "elize", + "daphne", + "fatima", + "milou", + "sophia", + "amina", + "puk", + "dewi", + "amelia", + "aim\u00e9e", + "sterre", + "nikki", + "selina", + "carlijn", + "maya", + "angelina", + "esila", + "romy", + "leah", + "josephine", + "nina", + "michelle", + "julia", + "sarah", + "johanna", + "elisabeth", + "joy", + "jente", + "cato", + "lucy", + "chlo\u00e9", + "floor", + "bente", + "isis", + "lisanne", + "isabelle", + "lieke", + "nynke", + "robin", + "maja", + "elena", + "roos", + "dina", + "fenna", + "zara", + "liza", + "melissa", + "mirte", + "jolie", + "marit", + "isabella", + "jayda", + "emma", + "bibi", + "amira", + "iris", + "ceylin", + "livia", + "lotte", + "alyssa", + "elin", + "faye", + "nadine", + "indy", + "mirthe", + "mare", + "lize", + "azra", + "benthe", + "ninthe", + "evelien", + "norah", + "vera", + "adriana", + "tara", + "sienna", + "aylin", + "nienke", + "phileine", + "hailey", + "luna", + "louise", + "am\u00e9lie", + "loes", + "sam", + "zeynep", + "evy", + "anouk", + "fay", + "kate", + "pleun", + "inaya", + "sylvie", + "nadia", + "sofia", + "elizabeth", + "mia", + "juliette", + "alicia", + "guusje", + "ecrin", + "noa", + "linn", + "elif", + "nova", + "aya", + "fem", + "lise", + "kyara", + "lina", + "megan" + ], + "FIRST_NAME_MALE": [ + "vigo", + "floris", + "wesley", + "jacob", + "justin", + "rens", + "jo\u00ebl", + "luca", + "maxim", + "bas", + "bart", + "emir", + "colin", + "seth", + "jim", + "keano", + "maarten", + "rafael", + "kyan", + "felix", + "benjamin", + "mats", + "wessel", + "jesper", + "nick", + "imran", + "jonathan", + "mick", + "noah", + "leon", + "niels", + "jens", + "lucas", + "merijn", + "rick", + "marinus", + "ties", + "lex", + "damian", + "giel", + "levi", + "raf", + "jort", + "pim", + "bryan", + "pepijn", + "daniel", + "tijmen", + "koen", + "maurits", + "sjoerd", + "fedde", + "stef", + "olivier", + "johannes", + "stan", + "wouter", + "tobias", + "alexander", + "abel", + "jayson", + "bradley", + "rik", + "oscar", + "sil", + "brent", + "tygo", + "mason", + "hidde", + "casper", + "thijs", + "lukas", + "stijn", + "ian", + "fabian", + "alex", + "kick", + "max", + "jason", + "roan", + "florian", + "hugo", + "nathan", + "jesse", + "luke", + "loek", + "boaz", + "vincent", + "melle", + "sep", + "jules", + "beau", + "zakaria", + "thom", + "quinn", + "julian", + "tijn", + "joshua", + "sebastiaan", + "lorenzo", + "james", + "aron", + "duuk", + "jelle", + "muhammed", + "jordy", + "elias", + "yusuf", + "ruben", + "sven", + "julius", + "senna", + "sem", + "mathijs", + "lars", + "ryan", + "naud", + "mark", + "jack", + "noud", + "joey", + "thijmen", + "jorn", + "ayoub", + "jan", + "berend", + "tyler", + "mike", + "twan", + "ibrahim", + "dirk", + "jip", + "matthias", + "jake", + "mads", + "ali", + "youssef", + "joris", + "kevin", + "tijs", + "sten", + "kyano", + "tim", + "dani", + "lenn", + "finn", + "yassin", + "gerrit", + "berat", + "hamza", + "owen", + "rayan", + "joost", + "sepp", + "joep", + "quinten", + "philip", + "senn", + "arie", + "dion", + "wout", + "luuk", + "mustafa", + "aiden", + "dani\u00ebl", + "sami", + "matthijs", + "jurre", + "jayden", + "luka", + "adam", + "cas", + "robin", + "guus", + "simon", + "tristan", + "vince", + "cornelis", + "riley", + "bram", + "tycho", + "samuel", + "micha", + "bilal", + "niek", + "mees", + "giovanni", + "siem", + "david", + "valentijn", + "liam", + "thijn", + "mohammed", + "mohamed", + "boris", + "arthur", + "laurens", + "jay", + "milan", + "jelte", + "stefan", + "jamie", + "teun", + "ravi", + "jasper", + "xavi", + "thomas", + "dex", + "hendrik", + "aaron", + "amin", + "dean", + "kay", + "daan", + "pieter", + "sander", + "ivan", + "brian", + "olaf", + "jonas", + "morris", + "dylan", + "bastiaan", + "nout", + "rowan", + "gijs", + "sam", + "kai", + "luc", + "milo", + "mart", + "ayden", + "chris", + "dave", + "collin", + "dylano", + "mehmet", + "tom", + "marijn", + "victor", + "michael", + "job", + "willem", + "jari", + "timo", + "amir", + "ben", + "faas", + "mika", + "kian", + "bjorn" + ], + "FIRST_NAME": [ + "floris", + "justin", + "rens", + "fabi\u00ebnne", + "silke", + "maxim", + "bas", + "luca", + "mila", + "bart", + "hannah", + "renske", + "benjamin", + "cornelia", + "jolijn", + "dana", + "niels", + "vaj\u00e8n", + "jasmijn", + "maria", + "lynn", + "esm\u00e9e", + "maurits", + "fedde", + "catharina", + "wouter", + "tobias", + "janna", + "abel", + "brent", + "mason", + "helena", + "anne", + "florian", + "nathan", + "eva", + "luke", + "merle", + "vincent", + "evi", + "beau", + "zakaria", + "esmee", + "aaliyah", + "sebastiaan", + "lorenzo", + "james", + "veerle", + "kiki", + "muhammed", + "suze", + "selena", + "senna", + "sem", + "mathijs", + "charlotte", + "yasmin", + "mara", + "jinthe", + "jan", + "britt", + "fleur", + "esther", + "tyler", + "lot", + "valerie", + "elize", + "ibrahim", + "milou", + "mads", + "yassin", + "owen", + "selina", + "carlijn", + "hamza", + "josephine", + "sepp", + "nina", + "michelle", + "julia", + "arie", + "wout", + "cato", + "dani\u00ebl", + "sami", + "chlo\u00e9", + "bente", + "adam", + "guus", + "simon", + "roos", + "tristan", + "zara", + "liza", + "jolie", + "mees", + "giovanni", + "ceylin", + "mohammed", + "lotte", + "laurens", + "milan", + "stefan", + "azra", + "lize", + "jasper", + "teun", + "norah", + "sander", + "pieter", + "olaf", + "luna", + "gijs", + "sam", + "rowan", + "kai", + "zeynep", + "dave", + "pleun", + "evy", + "inaya", + "mia", + "juliette", + "alicia", + "elizabeth", + "dylano", + "tom", + "linn", + "elif", + "mika", + "bjorn", + "lara", + "jo\u00ebl", + "seth", + "no\u00eblle", + "maarten", + "jenna", + "kyan", + "mats", + "jonathan", + "stella", + "mick", + "noah", + "merijn", + "marinus", + "tessa", + "levi", + "jort", + "lola", + "bryan", + "pepijn", + "daniel", + "tirza", + "myrthe", + "yasmine", + "fenne", + "stef", + "sophie", + "rosalie", + "lauren", + "bradley", + "oscar", + "ize", + "sil", + "sanne", + "casper", + "fabian", + "elisa", + "maartje", + "alex", + "maaike", + "jennifer", + "madelief", + "victoria", + "amber", + "tess", + "jesse", + "loek", + "lisa", + "mette", + "laura", + "jules", + "jill", + "julian", + "lily", + "joshua", + "frederique", + "aron", + "duuk", + "jordy", + "julie", + "julius", + "lana", + "naud", + "mark", + "noud", + "merel", + "demi", + "noor", + "jorn", + "annabel", + "bo", + "ayoub", + "ella", + "berend", + "twan", + "jip", + "daphne", + "ali", + "sophia", + "amina", + "sten", + "nikki", + "dani", + "lenn", + "finn", + "gerrit", + "berat", + "elisabeth", + "senn", + "mustafa", + "luka", + "isabelle", + "elena", + "dina", + "fenna", + "cornelis", + "tycho", + "jayda", + "niek", + "liam", + "alyssa", + "mirthe", + "ninthe", + "thomas", + "ravi", + "vera", + "adriana", + "sienna", + "dex", + "brian", + "hailey", + "am\u00e9lie", + "luc", + "milo", + "mart", + "fay", + "chris", + "collin", + "nadia", + "sofia", + "mehmet", + "michael", + "ecrin", + "noa", + "job", + "willem", + "ben", + "rik", + "fem", + "lise", + "megan", + "jacob", + "karlijn", + "sara", + "colin", + "keano", + "suus", + "felix", + "amy", + "janne", + "wessel", + "jesper", + "lizzy", + "jade", + "pippa", + "lucas", + "ashley", + "olivia", + "damian", + "yinthe", + "giel", + "ilse", + "jo\u00eblle", + "pim", + "ise", + "koen", + "sjoerd", + "johannes", + "nisa", + "jet", + "alexander", + "yfke", + "imke", + "zoey", + "thijs", + "stijn", + "ian", + "f\u00e9line", + "puck", + "anna", + "annemijn", + "kick", + "jason", + "lizz", + "roan", + "floortje", + "hugo", + "boaz", + "melle", + "sep", + "thom", + "tijn", + "liz", + "ivy", + "yusuf", + "sven", + "lieve", + "zo\u00eb", + "hanna", + "rosa", + "juul", + "lars", + "kyra", + "ryan", + "jack", + "joey", + "kayleigh", + "lo\u00efs", + "fien", + "mike", + "matthias", + "jake", + "joris", + "tijs", + "puk", + "kyano", + "amelia", + "tim", + "rayan", + "maya", + "joep", + "sarah", + "johanna", + "philip", + "joy", + "jente", + "luuk", + "lucy", + "aiden", + "matthijs", + "floor", + "jurre", + "isis", + "jayden", + "lieke", + "vince", + "riley", + "mirte", + "micha", + "emma", + "david", + "iris", + "boris", + "arthur", + "jay", + "faye", + "nadine", + "indy", + "jelte", + "mare", + "benthe", + "xavi", + "tara", + "nienke", + "aaron", + "kay", + "amin", + "phileine", + "ivan", + "jonas", + "morris", + "nout", + "sylvie", + "victor", + "guusje", + "nova", + "jari", + "aya", + "amir", + "lukas", + "kyara", + "lina", + "kian", + "vigo", + "wesley", + "noortje", + "yara", + "lindsey", + "emir", + "danique", + "jim", + "rafael", + "emily", + "nick", + "imran", + "meike", + "maryam", + "jens", + "isa", + "leon", + "elise", + "rick", + "ties", + "lex", + "linde", + "raf", + "chlo\u00eb", + "lois", + "sofie", + "tijmen", + "quinty", + "olivier", + "naomi", + "stan", + "jayson", + "tygo", + "eliza", + "hidde", + "kaylee", + "feline", + "saar", + "max", + "maud", + "fiene", + "kim", + "femke", + "quinn", + "evie", + "jelle", + "elias", + "ruben", + "jaylinn", + "liv", + "pien", + "lena", + "thijmen", + "nora", + "eline", + "isabel", + "dirk", + "fatima", + "youssef", + "kevin", + "dewi", + "aim\u00e9e", + "sterre", + "angelina", + "esila", + "romy", + "leah", + "joost", + "quinten", + "dion", + "lisanne", + "cas", + "nynke", + "robin", + "maja", + "bram", + "melissa", + "marit", + "samuel", + "bilal", + "isabella", + "siem", + "bibi", + "amira", + "valentijn", + "thijn", + "livia", + "mohamed", + "elin", + "jamie", + "evelien", + "aylin", + "hendrik", + "dean", + "daan", + "dylan", + "louise", + "bastiaan", + "loes", + "ayden", + "kate", + "anouk", + "marijn", + "timo", + "faas" + ], + "LAST_NAME": [ + "phillipsen", + "bouthoorn", + "van_haspengouw", + "le_marec", + "pons", + "robbrechts_bruijne", + "westerburg", + "boddaugh", + "peronne", + "oversteeg", + "hulskes", + "spruyt", + "de_grote", + "van_berkum", + "van_es", + "de_mol", + "nijman", + "boer", + "van_gorp", + "de_jode_vastraedsd", + "osterhoudt", + "beekman", + "bertho", + "zeldenrust", + "van_dommelen", + "jansen", + "brugman", + "schulten", + "noordijk", + "werdes", + "de_jager", + "aelftrud_van_wessex", + "geertsen", + "de_marduras", + "van_haeften", + "fran\u00e7oise", + "recers", + "de_grunt", + "heinrichs", + "persijn", + "verkade", + "wigman", + "de_bont", + "van_de_klashorst", + "van_de_weterink", + "schelvis", + "lether", + "van_der_pouw", + "van_northeim", + "louws", + "haengreve", + "hendrikse", + "van_den_henst", + "kisman", + "van_luyssel", + "jorlink", + "chrodtrud", + "van_de_darnau", + "pieters", + "winters", + "arens", + "ariens_ansems", + "van_der_heijden", + "van_der_meulen", + "jochems", + "van_oirschot", + "van_saksen", + "coret", + "verhoeven", + "spruit", + "roose", + "van_der_laar", + "groenestein", + "simons", + "schiffer", + "ridder", + "bud", + "heijman", + "appelman", + "uphus", + "lage", + "hakker", + "lutterveld", + "hoogers", + "stichter", + "van_bernicia", + "van_den_heuvel", + "west_franci\u00eb,_van", + "wipstrik", + "van_wassenaar", + "hagendoorn", + "buijs", + "wilcken", + "de_korte", + "goedhart", + "kramer", + "van_den_bosch", + "wolfsdr", + "le_matelot", + "de_keijser", + "claassen", + "janssens", + "de_la_fleche", + "alpaidis", + "recer", + "velderman", + "krabbe", + "spanhaak", + "janse", + "van_den_nieuwenhuijsen", + "van_brunswijk", + "stinis", + "van_de_water", + "wendt", + "aarts", + "kunen", + "bleijenberg", + "van_nimwegen", + "van_luin", + "lips", + "estey", + "van_beek", + "hoppenbrouwer", + "gerrits", + "brandon", + "doesburg", + "scheffers", + "schenkel", + "stuivenberg", + "smeets", + "manne", + "westermann", + "hoedemakers", + "van_der_veen", + "van_der_laarse", + "van_kuijc_van_malsen", + "verda", + "loreal", + "jacobi", + "oosterhout", + "backer", + "de_bruin", + "kwaadland", + "gepa_van_bourgondi\u00eb", + "jeggij", + "van_breukelveen", + "lambers", + "van_der_leek", + "willems", + "wilson", + "friehus", + "van_clootwijck", + "horrocks", + "hexspoor", + "borman", + "de_backer", + "rackham", + "van_emmelen", + "kleibrink", + "pierson", + "blees", + "moensendijk", + "pratt", + "van_den_nuwenhijsen", + "van_der_strigt", + "van_dijk", + "woudenberg", + "van_doorn", + "aertsz", + "gnodde", + "prinsen", + "van_schevinghuizen", + "zijlemans", + "brands", + "greij", + "wunderink", + "broeders", + "feltzer", + "brievingh", + "de_koning", + "ketel", + "van_den_corput", + "willemsen", + "cosman", + "van_'t_riet", + "dirven", + "van_der_flaas", + "frankhuizen", + "mallien", + "elberts", + "van_der_lede", + "giselmeyer", + "claesdr", + "van_vliet", + "scuylenborchs", + "westerbeek", + "serra", + "beijring", + "hoes", + "hoekstra", + "van_nes", + "scardino", + "cornelisz", + "van_den_brink", + "roodesteijn", + "puig", + "lagerweij", + "van_wickerode", + "smith", + "molen", + "kremer", + "van_voorst", + "uittenbosch", + "waardeloo", + "van_buuren", + "schotte", + "rippey", + "de_beer", + "matthews", + "jansse", + "reimes", + "van_den_nyeuwenhuysen", + "van_'t_houteveen", + "de_strigter", + "mens", + "vaessen", + "van_boulogne", + "mathol", + "van_der_wal", + "steenbakkers", + "spaan", + "heymans", + "rubben", + "zevenboom", + "breugelensis", + "rotteveel", + "van_breugel", + "bosman", + "sam", + "stoffel", + "van_'t_erve", + "dircken", + "vrancken", + "lathrope", + "van_rijnsbergen", + "van_de_biezenbos", + "van_de_berg", + "bres\u00e9", + "driessen", + "van_de_noordmark", + "kosten", + "van_ommeren", + "bezemer", + "rietveld", + "vignon", + "haack", + "van_der_laan", + "kleybrink", + "lansink", + "van_den_velden", + "van_eck", + "ruijs", + "van_susa", + "van_metz", + "van_maaren", + "rouwenhorst", + "huijben", + "kriens", + "brisee", + "vi", + "blokland", + "jorrisen", + "tammerijn", + "karels", + "arts", + "geerling", + "korsman", + "overdijk", + "veenstra", + "lamore", + "van_wallaert", + "helmerhorst", + "van_der_linden", + "draaisma", + "room", + "van_rooij", + "hulshouts", + "joosten", + "jurrijens", + "ansems", + "fechant", + "van_geffen", + "ooms", + "van_drenthe", + "van_hoevel_en_van_zwindrecht", + "schrant", + "jerusalem", + "weijland", + "van_den_nuwenhuysen", + "becht", + "lafleur", + "hanegraaff", + "van_den_wittenboer", + "de_haas", + "adriaansen", + "keltenie", + "butselaar", + "van_beeck_beeckmans", + "van_stralen", + "loep", + "van_westfalen", + "der_kijnder", + "ouwel", + "weyland", + "stamrood", + "van_grinsven", + "roosenboom", + "cadefau", + "van_brenen", + "welf", + "totwiller", + "rousselet", + "salet", + "aeije", + "mulders", + "sprong", + "visser", + "weylant", + "eijkelboom", + "van_der_veiver", + "schatteleijn", + "van_noort", + "carnotte", + "b\u00f6kenkamp", + "van_kusen", + "van_der_avoirt", + "walter", + "van_de_elzas", + "de_lange", + "van_oudewater", + "adelaar", + "lind", + "kok", + "van_laarhoven", + "van_asten", + "van_evelingen", + "van_poppel", + "eckhardt", + "van_ginneke", + "van_den_oever", + "le_briel", + "jonker", + "van_der_maath", + "knoers", + "schilt", + "van_gastel", + "miner", + "van_mil", + "van_ginkel", + "bierstraten", + "van_der_horst", + "risma", + "hellevoort", + "boudewijns", + "van_der_maes", + "koret", + "moenen", + "engels", + "oosterhek", + "van_limburg", + "kleijse", + "kerkhof", + "lorreijn", + "saxo", + "weijters", + "van_leuven", + "wouters", + "martens", + "heribert_van_laon", + "van_herstal", + "dachgelder", + "pauwels", + "van_maasgouw", + "briere", + "wolffel", + "erhout", + "ulrich", + "zeemans", + "kortman", + "jonkman", + "van_wijk", + "van_opper_lotharingen", + "timmerman", + "uit_de_willigen", + "van_der_heyden", + "le_gulcher", + "zwart", + "fortuyn", + "van_zwaben", + "sitters", + "de_reede", + "van_dooren", + "van_salmen", + "goderts", + "otto", + "koeman", + "olykan", + "jacobs", + "rijcken", + "marchal", + "kof", + "bolkesteijn", + "oda", + "de_kale", + "boetet", + "van_spreeuwel", + "van_praagh", + "hoelen", + "van_enschot", + "verbeek", + "kloppert", + "vervoort", + "van_duyvenvoorde", + "olthof", + "van_este", + "van_dam", + "muller", + "ariens", + "chevresson", + "van_bruchem", + "kuiper", + "van_rijthoven", + "schroeff", + "korstman", + "beourgeois", + "wolzak", + "poncelet", + "den_haag", + "verschuere", + "kronenberg", + "huijbrechts", + "boeser", + "de_haan", + "jaceps", + "meyer", + "neuteboom", + "melet", + "van_jumi\u00e8ge", + "belpere", + "flink", + "overeem", + "laffray", + "frerichs", + "govarts", + "elsemulder", + "van_laon", + "remmers", + "huijzing", + "mol", + "winnrich", + "barents", + "schellekens", + "van_der_steen", + "fran\u00e7ois", + "van_de_kooij", + "van_dagsburg", + "kas", + "heijmans", + "tamsma", + "van_den_eerenbeemt", + "le_luc", + "geneart", + "evers", + "kuipers", + "van_daal", + "groote", + "molenaar", + "de_boer", + "van_ochten", + "kamper", + "weeldenburg", + "fredriks", + "knuf", + "postma", + "bourgondi\u00eb,_van", + "thomas", + "passchiers", + "van_de_biesenbos", + "maas", + "bruijne_van_der_veen", + "pieters_van_der_maes", + "the_elder", + "van_der_velden", + "van_der_smeede", + "van_der_klein", + "coolen", + "van_alenburg", + "van_leeuwen", + "peterse", + "roukes", + "langevoort", + "ehlert", + "stook", + "van_de_pavert", + "michiels", + "dijkstra", + "ellis", + "van_schweinfurt", + "van_luxemburg", + "van_dalem", + "leguit", + "de_graaf", + "holthuis", + "jansdr", + "rijn", + "verwoert", + "mathieu", + "van_dokkum", + "hondeveld", + "van_rheineck", + "brizee", + "van_der_pol", + "le_guellec", + "vegt", + "de_hoog", + "eerden", + "hulst", + "gerritse", + "broeshart", + "van_klaarwater", + "de_pauw", + "hehl", + "die_pelser", + "coreth_von_und_zu_coredo_und_starkenberg", + "van_ooste", + "eelman", + "stettyn", + "de_ruiter", + "van_santen", + "vergeer", + "chotzen", + "bakker", + "verheij", + "van_der_loo", + "van_der_velde", + "haring", + "van_engelen", + "heijmen", + "jones", + "boogaerts", + "sas", + "arnold", + "van_cuijck", + "romijn", + "lucas", + "billung", + "mansveld", + "veltman", + "van_bentheim", + "van_vermandois", + "goyaerts_van_waderle", + "sire", + "dubois", + "wagenvoort", + "van_den_assem", + "van_oosten", + "ramaker", + "koning", + "van_der_ploeg", + "van_beeck", + "zijlmans", + "bloemendaal", + "van_holland", + "van_waas", + "scherms", + "weerdenburg", + "kirpenstein", + "verhagen", + "amalrada", + "glasses", + "verhaar", + "heyne", + "van_den_bergh", + "guit", + "soos", + "hofman", + "de_hoogh", + "demmendaal", + "de_wit", + "everde", + "van_noordeloos", + "van_luinenburg", + "kalman", + "den_teuling", + "strik", + "van_der_hoeven", + "wever", + "mudden", + "rijks", + "van_bovene", + "ter_waarbeek", + "van_landen", + "brouwer", + "van_rossum", + "le_grand", + "van_roijen", + "dachgelt", + "arent", + "van_bergen", + "thout", + "sterkman", + "aschman", + "elbertse", + "van_der_kaay", + "wolfswinkel", + "dijkman", + "bruynzeels", + "de_roos", + "van_gelder", + "koster", + "kolster", + "van_der_zijl", + "bresse", + "vertoor", + "riem", + "van_goerle", + "van_haspengouw_hesbaye", + "broeckx", + "lemmens", + "peters", + "stange", + "potters", + "doorhof", + "van_parijs", + "uphaus", + "lieshout", + "ghoerle", + "henric_van_den_nuwenhuse", + "de_kok", + "die_witte", + "bruggeman", + "van_arkel", + "ferran", + "van_de_brink", + "booden", + "van_der_ven", + "broekhoven", + "jekel", + "den_buytelaar", + "de_keijzer", + "segerszoen", + "van_geest", + "schouten", + "kort", + "teunissen", + "stoffelsz", + "van_allemani\u00eb", + "bellemans", + "van_oostendorp", + "van_duivenvoorde", + "texier", + "heerkens", + "de_jonge", + "nollee", + "kathagen", + "wensen", + "bouwhuisen", + "van_'t_wel", + "mater", + "genefaas", + "kamp", + "galenzone", + "klerks", + "schakelaar", + "verheuvel", + "meeres", + "mahieu", + "jans", + "bosch", + "emmen", + "dekker", + "luboch", + "van_tours", + "huls", + "van_der_noot", + "klomp_jan", + "van_tuijl", + "rehorst", + "van_haarlem", + "van_nederlotharingen", + "aalts", + "kruns", + "speijer", + "woutersz", + "van_arnsberg", + "vos", + "perck", + "courtier", + "van_boven", + "bastiaense", + "de_bock", + "van_der_brink", + "voortman", + "van_gils", + "schokman", + "marchand", + "le_floch", + "de_gruson", + "van_suinvorde", + "volcke", + "linschoten", + "geerts", + "versluijs", + "van_wessex", + "gruijl", + "van_baalen", + "van_der_spaendonck", + "grondel", + "mathurin", + "van_hostaden", + "furda", + "berends", + "merckx", + "van_straaten", + "pison", + "bijlsma", + "van_den_brand", + "godfrey_van_alemanni\u00eb", + "levesque", + "van_de_leemput", + "van_velzen", + "claesner", + "hollander", + "vink", + "van_dillen", + "rutten", + "david", + "lonen", + "van_de_greef", + "suijker", + "boers", + "lelijveld", + "heerschop", + "cammel", + "goudriaan", + "mosley", + "de_swart", + "ketting", + "zuidweg", + "wildschut", + "peeters", + "feenstra", + "keijzer", + "de_werd", + "van_den_hoek", + "van_mispelen", + "hak", + "nieuwstraten", + "van_den_broek", + "simonis", + "shupe", + "de_plantard", + "vierdag", + "veenendaal", + "diesbergen", + "van_beaumont", + "van_den_nuwenhuijzen", + "wijland", + "van_de_eerenbeemt", + "doyle", + "bave", + "fremie", + "geldens", + "van_de_coterlet", + "tirie", + "kolen", + "luster", + "mijsberg", + "vallenduuk", + "van_de_ven", + "d'_heripon", + "van_breukeleveen", + "van_velthoven", + "wilmont", + "doornhem", + "molegraaf", + "groenendaal", + "wouters_van_eijndhoven", + "de_nijs", + "huberts", + "groen", + "miltenburg", + "hekker", + "van_hemert", + "van_hagen", + "van_de_veen", + "heere", + "huijs", + "tielemans", + "van_der_klijn", + "de_gratie", + "labado", + "rouwhorst", + "muijs", + "van_duvenvoirde", + "vastenhouw", + "slaetsdochter", + "van_wel", + "palman", + "van_ooyen", + "schenk", + "tuithof", + "prins", + "roessink", + "galijn", + "elsenaar", + "leene", + "de_bruyn", + "sanders", + "vertooren", + "vermeulen", + "freshour", + "van_den_eijssel", + "willems_van_lier", + "sestig", + "cant", + "wright", + "van_kasteelen", + "haneberg", + "le_gallen", + "van_lucel", + "thatcher", + "schuylenborch", + "takkelenburg", + "van_der_kint", + "de_vrome", + "wolters", + "kallen", + "spiker", + "van_het_heerenveen", + "van_soest", + "huurdeman", + "van_hamaland", + "van_den_velde", + "adriaensdr", + "scheer", + "moet", + "unruoch_hunerik", + "reijers", + "bartels", + "van_de_velde", + "zwijsen", + "strijker", + "meijer", + "haselaar", + "van_veen", + "blonk", + "dachgeldt", + "de_smit", + "van_gent", + "van_gemert", + "tillmanno", + "blom", + "de_gruijl", + "gellemeyer", + "van_der_stael", + "van_riet", + "schwartsbach", + "verharen", + "van_der_sande", + "van_venrooy", + "van_salm", + "keijser", + "k\u00f6ster", + "meis", + "brandt", + "klein", + "van_grondelle", + "van_de_plas", + "scharroo", + "van_der_heiden", + "van_der_pluijm", + "van_berkel", + "van_orleans", + "michielsen", + "wutke", + "lankle", + "van_munster", + "mangel", + "huisman", + "sarneel", + "verbruggen", + "cornelisse", + "bastiaanse", + "everts", + "schuurmans", + "van_de_wiel", + "die_bont", + "steenbeek", + "middelkoop", + "van_der_mast", + "de_groot", + "de_heer", + "'s_gravensande", + "hendriks", + "honing", + "van_der_plas", + "coenen", + "janssen", + "vial", + "van_engeland", + "smit", + "van_spreuwel", + "zuijdveld", + "kuilenburg", + "ligtvoet", + "bernaards", + "hendricks", + "hemma_van_allemani\u00eb", + "perrono", + "van_nus", + "van_verdun", + "de_vos", + "bos", + "van_der_stael_de_jonge", + "perkins", + "terry", + "van_de_wal", + "berendse", + "opmans", + "neuzerling", + "van_henegouwen", + "van_der_spaendonc", + "walsteijn", + "de_gruijter", + "van_laar", + "tins", + "gervais", + "van_formbach", + "verbeeck", + "van_der_sloot", + "steinmeiern", + "garret", + "bekbergen", + "van_bunschoten", + "beernink", + "uphuis", + "van_bragt", + "van_de_pol", + "dries", + "fiere", + "vandenbergh", + "smits", + "wooning", + "van_den_pol", + "van_mare", + "houdijk", + "latier", + "h\u00f6ning", + "van_hulten", + "lambregt", + "blaak", + "de_bruijn", + "oemencs", + "kuit", + "hermans", + "van_heusden", + "schipper", + "post", + "van_vlaanderen", + "lensen", + "van_voorhout", + "oennen", + "bouhuizen", + "gemen", + "van_beieren", + "spreeuw", + "jacquot", + "kuijpers", + "blewanus", + "broek", + "mansvelt", + "aarden", + "van_kempen", + "coret_coredo", + "van_embden", + "pastoors", + "hazenveld", + "de_vroege", + "ponci", + "van_der_meer", + "huel", + "mercks", + "oostveen", + "ouwerkerk", + "waltrade_walderade", + "mulder", + "meeusen", + "nek", + "van_der_berg", + "van_liendert", + "niermann", + "ernst", + "zaal", + "duivenvoorden", + "konings", + "van_loon", + "hoeks", + "van_bovenen", + "verboom", + "cornelissen", + "van_amstel", + "rademaker", + "pasman", + "adryaens", + "van_geenen", + "van_kuijc", + "lommert", + "de_vries", + "slingerland", + "van_ham", + "lijn", + "dorsman", + "scholten", + "momberg", + "massa", + "schagen", + "marceron", + "drysdale", + "spies", + "de_man", + "maaswinkel", + "nihoe", + "charon", + "werl_arnsberg,_van", + "lamotte", + "corstiaens", + "van_de_velden", + "oude_heer", + "merkx", + "dirksen", + "gerritsen", + "van_der_schuijt", + "rijntjes", + "dennenberg", + "bronder", + "slagmolen", + "timmermans", + "adriaense", + "brumleve", + "van_mook", + "de_jong", + "verschut", + "van_dongen", + "van_den_berg", + "schrik", + "spier", + "nedermeijer", + "van_olst", + "van_egisheim", + "van_wijland", + "martel", + "rek", + "luitgardis_van_neustri\u00eb", + "de_roo", + "otte", + "van_ghoerle", + "symons", + "de_gruil", + "jdotte", + "paillet", + "de_leeuw" + ], + "OTHER_PRONOUN": [ + "it", + "them", + "these" + ], + "LAST_NAME_MALE": [], + "LAST_NAME_FEMALE": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "priorin": "abb\u00e9", + "abdis": "abb\u00e9", + "actrice": "ator", + "ator": "acteur", + "toneelspeelster": "ator", + "baronesse": "baron", + "barones": "baron", + "bruut": "groom", + "bruid": "groom", + "zakenvrouw": "zakenman", + "working_girl": "zakenman", + "voorzitster": "voorzitter", + "kuiken": "gaur", + "pui": "dandy", + "bint": "zoon", + "dochter": "zoon", + "hertogin": "hertog", + "keizerin": "imperator", + "vrouwelijk": "masculien", + "gal": "kerel", + "griet": "gozer", + "meidje": "guido", + "goof": "gozer", + "meid": "kerel", + "grietje": "kerel", + "faam": "guido", + "wicht": "gozer", + "deern": "kerel", + "kleindochter": "kleinzoon", + "her": "tij", + "heldin": "heros", + "het_hare": "de_hunne", + "de_hare": "de_hunne", + "hostess": "representant", + "lady": "lord", + "kak": "frater", + "hospita": "huisbaas", + "h\u00fastr\u00fain": "huisbaas", + "masseuse": "masseur", + "missen": "meneer", + "mademoiselle": "meneer", + "juffrouw": "meneer", + "mejuffrouw": "meneer", + "bomma": "meneer", + "ma\u00eetresse": "master", + "meesteres": "master", + "minnares": "master", + "mistress": "professional", + "mevrouw": "master", + "moeder": "pater", + "mam": "pater", + "matrix": "pair", + "bh": "dhr", + "mw": "dhr", + "mevr": "dhr", + "zuster": "broer", + "moniale": "monnik", + "priesteres": "priester", + "prinses": "prins", + "danaus_gilippus": "indra", + "koningin": "key", + "hetman": "indra", + "queens": "koningen", + "zij": "he", + "zus": "broeder", + "sour": "broer", + "tovenares": "sorcerer", + "ongehuwde_vrouw": "baccalaureus", + "oude_vrijster": "bachelor", + "woordvoerster": "woordvoerder", + "stiefdochter": "stiefzoon", + "stiefmoeder": "stiefvader", + "stewardess": "steward", + "serveerster": "serveuse", + "weduwe": "weduwnaar", + "echtgenote": "echtgenoot", + "vrouw": "bemannen", + "hex": "magi\u00ebr", + "tovenaar": "magi\u00ebr", + "wicca": "tovenaar", + "heks": "tovenaar", + "norn": "tovenaar", + "hondstong": "tovenaar", + "arnoglossus_scapha": "tovenaar", + "boy": "meid", + "jonge": "grietje", + "knaap": "wicht", + "jongen": "wicht", + "journaliste": "dagboekschrijver", + "dagboekschrijver": "journaliste", + "journalist": "journaliste" + }, + "other_gender_swap": { + "them": "her", + "jeju": "her", + "leur": "her", + "leen": "her", + "leus": "her", + "uk": "her", + "het_hunne": "de_hare", + "de_hunne": "het_hare", + "epi": "zij", + "iel": "zij", + "hij": "zij", + "he": "zij", + "jal": "iel", + "tij": "de_hunne", + "seine": "het_hunne", + "zij": "epi", + "her": "leus", + "het_hare": "het_hunne", + "de_hare": "de_hunne" + }, + "en_pronoun2gender": { + "they": [ + "van_de_verkeerde_kant", + "biseksueel", + "transgenderisme", + "transgender", + "homoseksueel" + ], + "he": [ + "jongen", + "kerel", + "mees", + "gaur", + "gentleman", + "bemannen", + "dandy", + "gozer", + "man", + "groom", + "gentiluomo", + "boy", + "knaap", + "little_boy", + "jonge", + "knul", + "masculien", + "guido" + ], + "she": [ + "lesbienne", + "matrone", + "kak", + "jongedame", + "vrouw", + "het_zwakke_geslacht", + "juffrouw", + "gal", + "missen", + "lesbisch", + "het_schone_geslacht", + "wicht", + "maagd", + "lady", + "bomma", + "deern", + "mademoiselle", + "vrijster", + "vrouwelijk", + "meid", + "goof", + "deem", + "faam", + "griet", + "mejuffrouw", + "tribade", + "meidje", + "grietje", + "madam", + "dame" + ] + }, + "en_pronoun2pronoun": { + "he": [ + "he", + "hij", + "seine", + "tij", + "zichzelf", + "jal" + ], + "she": [ + "zij", + "de_hare", + "het_hare", + "her" + ], + "they": [ + "de_hunne", + "iel", + "jeju", + "zij", + "leen", + "het_hunne", + "leur", + "them", + "leus", + "uk", + "epi" + ], + "it": [ + "onen", + "deze", + "stas", + "these", + "per_se", + "tyto", + "it", + "dies", + "zichzelf", + "hij", + "ict" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/nmn.json b/data_tooling/pii_processing/ontology/data/nmn.json new file mode 100644 index 0000000..8b4e790 --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/nmn.json @@ -0,0 +1,63 @@ +{ + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "\u00e3_h\u02bb\u00e3": "\u00e8h", + "\u00e3_h": "\u00e8h", + "\u00e8h\u02bb\u00e8": "\u00e3_h\u02bb\u00e3", + "\u00e8h": "\u00e8h\u02bb\u00e8", + "t\u00e2a_q\u00e1e": "t\u00e2a_a\u0330a" + }, + "other_gender_swap": { + "\u00f9h": "\u00e3_h\u02bb\u00e3", + "\u00f9h\u02bb\u00f9": "\u00e3_h", + "\u00e3_h\u02bb\u00e3": "\u00f9h\u02bb\u00f9", + "\u00e3_h": "\u00f9h\u02bb\u00f9", + "\u00e8h\u02bb\u00e8": "\u00f9h\u02bb\u00f9", + "\u00e8h": "\u00f9h" + }, + "en_pronoun2gender": { + "she": [ + "t\u00e2a_q\u00e1e" + ] + }, + "en_pronoun2pronoun": { + "he": [ + "\u00e3_h\u02bb\u00e3", + "\u00e8h", + "\u00e8h\u02bb\u00e8", + "\u00e3_h" + ], + "she": [ + "\u00e3_h\u02bb\u00e3", + "\u00e8h", + "\u00e8h\u02bb\u00e8", + "\u00e3_h" + ], + "they": [ + "\u00f9h\u02bb\u00f9", + "\u00f9h" + ], + "it": [ + "tvv\u02bbvv", + "\u02bbvv", + "\u00e8h", + "\u00e8h\u02bb\u00e8", + "tv\u02bbvv", + "\u00e3h\u02bb\u00e3", + "tv\u02bbv", + "\u00ech", + "\u00e3h" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/no.json b/data_tooling/pii_processing/ontology/data/no.json new file mode 100644 index 0000000..41a6870 --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/no.json @@ -0,0 +1,4069 @@ +{ + "ORG": [ + "plan\u00f8konomi", + "h\u00f8yteknologisk", + "dominion", + "ida", + "kommunistparti", + "sukkerfri", + "den_kontinentale_kongress", + "tenketank", + "republikanergarden", + "den_r\u00f8de_arm\u00e9", + "jeg_heter", + "bataljon", + "besteven", + "auksjonshus", + "jakobinerlue", + "han_dynastiet", + "shint\u014disme", + "milit\u00e6rteneste", + "p\u00e5_fersk_gjerning", + "en_gang_til", + "raudekrossen", + "bestevenn", + "baskarland", + "hekkefond", + "fagorganisasjon", + "myndigheter", + "den_gule_flod", + "den_trojanske_hest", + "den_europeiske_sentralbank", + "wicca", + "masomn", + "an_education", + "statskupp", + "marknads\u00f8konomi", + "musikkbransjen", + "jan_mayen", + "brente_jords_taktikk", + "jesuittordenen", + "den_palestinske_frigjeringsorganisasjonen", + "den_gresk_ortodokse_kirke", + "kongressen", + "strykekvartett", + "det_tyske_keiserrike", + "flytrafikk", + "nordvestpassasjen", + "aa", + "nasa", + "h\u00f8yesterett", + "de_mistenkte", + "handelsskole", + "stjernehop", + "den_ortodokse_kirke", + "arda", + "the_new_school_for_social_research", + "the_national_archives", + "den_europeiske_union", + "myndigheiter", + "bollywood", + "ikke_noe_annet_enn", + "bevaringslovene", + "tredjeperson", + "den_tredje_verden", + "bilbombe", + "den_internasjonale_organisasjonen_for_sivil_luftfart", + "europol", + "schutzstaffel", + "det_britiske_austindiske_kompaniet", + "det_kvite_huset_i_washington_d.c", + "leverand\u00f8rkjede", + "the_who", + "blankv\u00e5pen", + "nym\u00e5ne", + "reklamebyr\u00e5", + "haganah", + "stenderforsamling", + "direktedemokrati", + "den_internasjonale_telekommunikasjonsunion", + "markeds\u00f8konomi", + "tredjemann", + "strangitter", + "college", + "det_kinesiske_kommunistiske_parti", + "handelsregning", + "forretningsbank", + "dei_sameinte_nasjonane", + "san_francisco", + "kristdemokraterna", + "tankesmie", + "nytt\u00e5rsaftan", + "nytt\u00e5rsaften", + "brannvern", + "a_chorus_line", + "den_arabiske_ligaen", + "\u00f8vresj\u00f8en", + "det_europeiske_fellesskap", + "det_sosialdemokratiske_parti", + "kollektivtransport", + "under_samme_tak", + "taoisme", + "vandrarheim", + "elle_melle", + "jeg_er_glad_i_deg", + "i_det_hele_tatt", + "fleinsopp", + "den_trojanske_hesten", + "i_blanke_messingen", + "romerretten", + "s\u00f8r\u00f8stlig", + "st_clairsj\u00f8en", + "ungdomsherberge", + "kjernefamilie", + "frankrikes_nasjonalforsamling", + "den_raude_h\u00e6ren", + "den_gylne_horde", + "frimureri", + "grunnskole", + "fariseisk", + "bystat", + "h\u00f8gsterett", + "de_forente_nasjoner", + "tornerose", + "sankt_nikolas", + "det_nordatlantiske_r\u00e5d", + "gao", + "opp_med_henda", + "den_spanske_inkvisisjonen", + "storband", + "styresmakter", + "prohibition_party", + "botanisk_hage", + "the_family_man", + "mahayana", + "den_internasjonale_domstolen", + "den_tyske_demokratiske_republikk", + "der_oppe", + "den_katolske_kirkja", + "kunstgalleri", + "det_konservative_partiet_i_storbritannia", + "besteveninne", + "uline\u00e6r", + "valkollegium", + "sentralmaktene", + "bestevenninne", + "det_demokratisk_republikanske_parti", + "ferskvatn", + "det_internasjonale_pengefondet", + "saint_vincent", + "manhattanprosjektet", + "den_anglikanske_kyrkja", + "n\u00e5_og_d\u00e5", + "can_tho", + "saint_helena", + "det_republikanske_partiet_i_usa", + "vaishnavisme", + "the_faculty", + "don_juan", + "den_arabiske_liga", + "serbias_parlament", + "den_frie_vilje", + "den_store_bj\u00f8rnen", + "oljeberget", + "ai", + "nattsvermeren", + "fremmedlegionen", + "dominikanarordenen", + "det_tysk_romerske_rike", + "baskerland", + "bibelselskap", + "tyggis", + "nikolas_av_myra", + "sankt_helena", + "the_football_league", + "chiang_mai", + "det_republikanske_parti", + "gullalderen", + "akademi", + "dia", + "andromedagalaksen", + "kostskole", + "selvrettferdig", + "den_forente_familie", + "mitt_navn_er", + "stordata", + "olympisk_landsby", + "weimarrepublikken", + "homoekteskap", + "baktanke", + "skallselskap", + "den_ortodokse_kyrkja", + "det_palestinske_omr\u00e5det", + "in_flagranti", + "det_internasjonale_finansieringsinstituttet", + "det_internasjonale_atomenergibyr\u00e5et", + "akse", + "den_internasjonale_bank_for_gjenoppbygging_og_utvikling", + "kollektivtrafikk", + "styrem\u00f8te", + "milit\u00e6rtjeneste", + "studentting", + "le_mans", + "estlands_sosialdemokratiske_parti", + "s\u00f8ndagsskule", + "christian_science", + "caf\u00e9_au_lait", + "det_britiske_ostindiske_kompani", + "vandrerhjem", + "flyv\u00e5pen", + "partit_socialdem\u00f2crata", + "gullalder", + "middelklasse", + "den_olympiske_ild", + "det_demokratiske_partiet_i_usa", + "det_konservative_parti", + "i_ny_og_ne", + "rabindranath_tagore", + "den_h\u00f8ge_porten", + "gestapo", + "overf\u00f8ring", + "postkontor", + "den_kongelige_marine", + "den_afrikanske_union", + "politistat", + "den_kalde_krigen", + "bevaringslov", + "svarteb\u00f8rs", + "verdshandelsorganisasjonen", + "straffelov", + "milit\u00e6r", + "litt_etter_kvart", + "stordomstid", + "den_afrikanske_unionen", + "huangelva", + "raudehavet", + "det_liberale_parti", + "raseadskillelse", + "den_romersk_katolske_kirke", + "enevelde", + "massemedier", + "overklasse", + "den_spanske_armada", + "milit\u00e6rpoliti", + "den_minoiske_sivilisasjonen", + "fruktsalat", + "who_are_you", + "babyboom", + "partido_del_trabajo", + "chiang_rai", + "overhodet", + "dyrerettigheter", + "al_jazeera", + "overhus", + "utenriksdepartementet", + "popkunst", + "kyrkja", + "den_internasjonale_sj\u00f8fartsorganisasjonen", + "hansaforbundet", + "europe", + "kvekarane", + "dimokratik\u00f3_k\u00f3mma", + "po", + "addis_ababa", + "golfk\u00f8lle", + "den_heilage_nikolas", + "p\u00f8_om_p\u00f8", + "fra_tid_til_annen", + "styremakter", + "den_internasjonale_arbeidsorganisasjonen", + "oldes\u00f8nn", + "mossad", + "verdensbanken", + "frelsesarmeen", + "i_det_heile_teke", + "ferdinand_magellan", + "ikkje_line\u00e6rt_system", + "den_milit\u00e6re_sjefsnemnd", + "up_to_date", + "sognekirke", + "s\u00f8ndagsskole", + "menneskeskapt", + "janitsjarkorps", + "det_britiske_samveldet", + "den_katolske_kyrkja", + "den_russisk_ortodokse_kirke", + "vekslingskontor", + "saint_barth\u00e9lemy", + "lake_superior", + "bl\u00e5veis", + "sturmabteilung", + "det_demokratiske_enhetspartiet", + "den_russisk_ortodokse_kirkja", + "den_katolske_kirke", + "posthus", + "dominikanerordenen", + "los_angeles", + "nato", + "det_britiske_arbeidarpartiet", + "den_anglikanske_kirke", + "politiskolen", + "sentralbank", + "karmelberget", + "andre_person", + "skogsj\u00f8en", + "den_nordatlantiske_traktats_organisasjon", + "andre_veien", + "forsvarsdepartementet", + "ad_hoc", + "normalskole", + "ole_brumm", + "det_tyske_keisard\u00f8met", + "by_the_way", + "milit\u00e6rvesen", + "det_demokratiske_parti", + "den_kontinentale_arm\u00e9", + "albertsj\u00f8en", + "toppakning", + "verdsbanken", + "in_situ", + "pensjonsfond", + "tre_s\u00f8stre", + "r\u00f8dehavet", + "doc", + "det_hvite_hus", + "syd\u00f8stlig", + "den_heilage_josef", + "brent_jords_taktikk", + "berlinmuren", + "reisebyr\u00e5", + "den_usa_amerikanske_h\u00e6ren", + "al_ain", + "underhus", + "tyggjegummi", + "den_palestinske_selvstyremyndigheten", + "den_greske_ortodokse_kirkja", + "komposthaug", + "litt_etter_hvert", + "heilage_nikolas", + "forresten", + "sorte_enke", + "samfunnsklasse", + "kongefamilie", + "den_europeiske_unionen", + "commerce", + "privatskole", + "den_europeiske_sentralbanken", + "det_tredje_riket", + "morselskap", + "valmannskollegium", + "sparebank", + "radiogalakse", + "psykiatrisk_sykehus", + "den_tyske_demokratiske_republikken", + "chang_jiang", + "den_nordatlantiske_traktat_organisasjonen", + "den_russisk_ortodokse_kyrkja", + "masovn", + "store_bj\u00f8rn", + "kapp_verde", + "arme_riddere", + "hautes_fagnes", + "tyggegummi", + "mecklenburg_vorpommern", + "framandlegionen", + "d\u00f8dsskvadron", + "jomfru_marias_opptagelse_i_himmelen", + "house_of_lords", + "statskapitalisme", + "det_tysk_romerske_riket", + "om_bord", + "germanistikk", + "s\u00e3o_tom\u00e9", + "tredjepart", + "hedgefond", + "hansaen", + "forsikringsselskap", + "forbundsr\u00e5det", + "vandrerheim" + ], + "PUBLIC_FIGURE": [ + "lawrence_durrell", + "henry_cavendish", + "matthew_arnold", + "benjamin_franklin", + "martin_buber", + "e_b_white", + "akira_kurosawa", + "john_knox", + "heinrich_hertz", + "hopen", + "giovanni_boccaccio", + "ikke_anvendbar", + "cornelius_vanderbilt", + "rudolf_steiner", + "thomas_wolfe", + "thomas_bayes", + "ben_hogan", + "johann_bernoulli", + "menneskevesen", + "max_bruch", + "leonard_bernstein", + "edvard_vedkjennaren", + "che_guevara", + "georges_simenon", + "c", + "augustin_fresnel", + "edward_albee", + "dorothy_parker", + "maria_callas", + "william_walton", + "henrik_ibsen", + "grasenkemann", + "william_gladstone", + "mary_shelley", + "franz_werfel", + "peter_lorre", + "david_livingstone", + "eduard_buchner", + "john_herschel", + "andrzej_wajda", + "jan_van_eyck", + "lawliet", + "carl_rogers", + "george_balanchine", + "georg_wilhelm_steller", + "richard_burton", + "douglas_macarthur", + "mary_wollstonecraft", + "j_edgar_hoover", + "maria_magdalena", + "john_jacob_astor", + "anna_pavlova", + "grasenkjemann", + "winston_churchill", + "gustav", + "johannes_diderik_van_der_waals", + "b", + "karl_landsteiner", + "ivan_pavlov", + "sparkonge", + "paul_mccartney", + "seilerfamilien", + "richard_smalley", + "andrew_marvell", + "terry_pratchett", + "stephen_king", + "francis_crick", + "john_trumbull", + "sherry", + "joseph_greenberg", + "isaac_newton", + "victor_hugo", + "joseph_smith", + "edwin_hubble", + "von_willebrants_faktor", + "milton_friedman", + "magedansarinne", + "edward_gibbon", + "jefferson_davis", + "saint_louis", + "cass_gilbert", + "george_stephenson", + "john_glenn", + "john_webster", + "john_davis", + "george_burns", + "george_harrison", + "peter_minuit", + "george_orwell", + "arthur_koestler", + "richard_wagner", + "williams", + "storvesir", + "thornton_wilder", + "pancho_villa", + "leopold_stokowski", + "rebecca_west", + "marie_curie", + "administrerande_direkt\u00f8r", + "francis_galton", + "michael_jackson", + "louis_jolliet", + "carl_sandburg", + "thomas_hobbes", + "edward_weston", + "el_greco", + "samuel_beckett", + "david", + "galileo_galilei", + "ernest_bevin", + "jane_goodall", + "john_donne", + "chaim_weizmann", + "robert_koch", + "joseph_goebbels", + "george_eastman", + "john_steinbeck", + "erich_mendelsohn", + "c_northcote_parkinson", + "edmund_hillary", + "bendik", + "vincent_van_gogh", + "martina_navr\u00e1tilov\u00e1", + "marie_stopes", + "anne_boleyn", + "josef_stalin", + "john_ruskin", + "robert_burns", + "thomas_paine", + "bari", + "liliuokalani", + "francis_beaumont", + "edvard", + "steven_weinberg", + "mary_pickford", + "hans_fischer", + "emiliano_zapata", + "karl_barth", + "willem_einthoven", + "phil_anderson", + "samuel_johnson", + "den_s\u00f8rlige_fisken", + "jesus", + "allen_iverson", + "marie_antoinette", + "giuseppe_verdi", + "walter_lippmann", + "e", + "karl_jaspers", + "beethoven", + "hideki_yukawa", + "konrad_adenauer", + "rullere", + "antoni", + "norbert_wiener", + "det_fjerde_krosstoget", + "mark_rothko", + "maurice_chevalier", + "gottlieb_daimler", + "frank_sinatra", + "katharine_hepburn", + "henri_becquerel", + "henri_matisse", + "bertram_brockhouse", + "louis_pasteur", + "richard_strauss", + "leslie_howard", + "lavrans", + "aristarkhos", + "hugo_grotius", + "mahalia_jackson", + "john_ford", + "stephen_foster", + "jamesbukta", + "laurits", + "katherine_mansfield", + "sergej_rakhmaninov", + "gertrude_stein", + "j_b_s_haldane", + "saladin", + "lewisgun", + "sarah_bernhardt", + "philip_marlowe", + "luigi_pirandello", + "hank_williams", + "rube_goldberg", + "dorothea_lange", + "james_thurber", + "charles_de_gaulle", + "paul_von_hindenburg", + "ilk", + "y", + "henry_moore", + "holden", + "peter_i_av_russland", + "ralph_bunche", + "rudolf_bultmann", + "charles_lindbergh", + "vincenzo_bellini", + "samuel_barber", + "tobias_smollett", + "f", + "john_jay", + "ludwig_wittgenstein", + "august_strindberg", + "thomas_mann", + "alla_nazimova", + "charles_goodyear", + "dante_alighieri", + "margot_fonteyn", + "peter_pan", + "james_tobin", + "john_irving", + "samuel_de_champlain", + "giacomo_puccini", + "edward_fitzgerald", + "fridtjof_nansen", + "louis_braille", + "herbert_marcuse", + "mungo_park", + "benedict_arnold", + "paul_verlaine", + "q", + "robert_johnson", + "tanasj\u00f8en", + "james_dean", + "robert", + "marie_tussaud", + "roger_bannister", + "theodor_schwann", + "alessandro_manzoni", + "henrik", + "joseph_priestley", + "hal", + "nicolas_poussin", + "andrea_mantegna", + "joseph_pulitzer", + "george_huntington", + "james_naismith", + "oscar_wilde", + "philip_roth", + "henry", + "lawrence", + "richard_trevithick", + "william_bradford", + "heinrich_schliemann", + "glenn_curtiss", + "don_quijote", + "laurence_olivier", + "georg", + "christiaan_eijkman", + "adolf_eichmann", + "francis_bacon", + "pete_seeger", + "john_wycliffe", + "joseph_heller", + "a", + "morris", + "norman_rockwell", + "james_brown", + "william_hogarth", + "charles_baudelaire", + "luigi_cherubini", + "david_ricardo", + "charlie_parker", + "immanuel_kant", + "james_franck", + "william_crookes", + "nellie_bly", + "weber", + "albert_schweitzer", + "georg_steller", + "giulio_natta", + "saint_martin", + "titus", + "johannes_kepler", + "william_s_burroughs", + "most", + "david_hartley", + "max_planck", + "william_blake", + "julio_iglesias", + "john_bardeen", + "det_tredje_korstog", + "arthur", + "sarah_vaughan", + "william_byrd", + "christopher_fry", + "scott_joplin", + "carl_lewis", + "sarah_siddons", + "george_vancouver", + "canberra", + "elias_canetti", + "edward_jenner", + "oscar_robertson", + "oliver_hardy", + "cole_porter", + "benjamin_west", + "jean_luc_godard", + "konstantin", + "graham_greene", + "frans_hals", + "lars_onsager", + "margaret_mitchell", + "stuart_davis", + "lola_montez", + "jan_swammerdam", + "david_riesman", + "john_walker", + "magedanserinne", + "william_herschel", + "arthur_rubinstein", + "arthur_compton", + "niels_bohr", + "kenneth_grahame", + "henry_fielding", + "bertrand_russell", + "michael_faraday", + "john_d_rockefeller", + "anthony_burgess", + "jan_tinbergen", + "robert_venturi", + "johnny_appleseed", + "irving_berlin", + "bernard_baruch", + "rudolf_diesel", + "walt_disney", + "ben_jonson", + "peter", + "james_whistler", + "d\u00f8dsseileren", + "kristoffer_columbus", + "joseph_schumpeter", + "gabriel_lippmann", + "steve_reich", + "lee", + "benny_goodman", + "friedrich_engels", + "jane_austen", + "charles_laughton", + "moses", + "gustav_mahler", + "ed_sullivan", + "phil_collins", + "alice_paul", + "den_heilage_j\u00f8rgen", + "robert_redford", + "jack_dempsey", + "ian_fleming", + "richard_feynman", + "wolfgang_pauli", + "theodore_dreiser", + "theodor_mommsen", + "andrew_huxley", + "marcel_proust", + "thomas_more", + "paul_hindemith", + "elizabeth_taylor", + "thomas_chippendale", + "m\u00f8llar", + "paul_robeson", + "arnold", + "pedro_rodr\u00edguez", + "thomas_middleton", + "john_dowland", + "den_s\u00f8rlege_fisken", + "william_golding", + "jesus_kristus", + "magedanser", + "william_caxton", + "john_milton", + "rudolf_serkin", + "ethel_merman", + "samuel_adams", + "albert_speer", + "stuert", + "james_baldwin", + "valentina_teresjkova", + "john_vanbrugh", + "indira_gandhi", + "jane_seymour", + "george_gershwin", + "alberto_giacometti", + "frank_whittle", + "alfred_nobel", + "jesse_owens", + "marco_polo", + "john_fletcher", + "menneskedyr", + "\u00f8rnen", + "caravaggio", + "charlie_watts", + "m", + "charlotte_corday", + "allen_ginsberg", + "fred_zinnemann", + "daniel_bernoulli", + "guillaume_apollinaire", + "antoine_watteau", + "joseph_henry", + "henri_bergson", + "boris_karloff", + "gottfried_leibniz", + "pierre_corneille", + "det_fjerde_korstog", + "phillis_wheatley", + "patrick_white", + "saul_steinberg", + "bartholomew_roberts", + "apostelen_paulus", + "daniel_morgan", + "william_morris", + "cary_grant", + "thomas", + "isaac_watts", + "pieter_zeeman", + "glenn_miller", + "\u00f8ya_st_martin", + "pablo_picasso", + "marian_anderson", + "natalie_wood", + "l_ron_hubbard", + "anderson", + "thomas_moore", + "osman_i", + "kurt_weill", + "otto_hahn", + "lester_young", + "john_marshall", + "christiaan_huygens", + "hector_berlioz", + "folkedansar", + "lucille_ball", + "paul_simon", + "claudio_monteverdi", + "folkedanser", + "john_galsworthy", + "robert_robinson", + "heilage_j\u00f8rgen", + "o", + "adam_smith", + "william_james", + "det_sjette_korstog", + "u", + "jean_harlow", + "henry_miller", + "karl_marx", + "friedrich_nietzsche", + "i", + "pedro", + "robert_indiana", + "jimmy_durante", + "john_wesley", + "statsoverhode", + "sandro_botticelli", + "carson_mccullers", + "nikola_tesla", + "al_capone", + "jim_bowie", + "charles_barkley", + "billy_graham", + "robert_schumann", + "mel_gibson", + "le_corbusier", + "carlo_goldoni", + "john_locke", + "alexis_carrel", + "joseph_marie_jacquard", + "henry_james", + "stephen_sondheim", + "menneskebarn", + "andrej_sakharov", + "christofer_columbus", + "helen_keller", + "paul_dukas", + "ingrid_bergman", + "anna_kurnikova", + "leonard_bloomfield", + "jean_piaget", + "william_congreve", + "henri_rousseau", + "paul_tillich", + "robert_southey", + "walt_whitman", + "william_wyler", + "john_osborne", + "colin_powell", + "ludwig_boltzmann", + "carl_nielsen", + "leopold_kronecker", + "richard_wright", + "benjamin_thompson", + "adolf_hitler", + "james_d_watson", + "fritz_haber", + "peter_behrens", + "alfred_stieglitz", + "joseph_haydn", + "stephen_spender", + "garfield", + "george_boole", + "daniel_boone", + "skogsrype", + "buffalo_bill", + "edvard_grieg", + "jacques", + "robert_boyle", + "edith_cavell", + "alan_paton", + "1", + "cordell_hull", + "rosa_parks", + "tomas", + "samuel_goldwyn", + "j\u00f8rgen", + "forh\u00e5pning", + "ernest_walton", + "vladimir_putin", + "jacob", + "giuseppe_mazzini", + "lafranz", + "jim_thorpe", + "hertz", + "arnold_sch\u00f6nberg", + "laurence_sterne", + "jacqueline_cochran", + "george_fox", + "den_flyvende_hollender", + "ben_hecht", + "mikhail_barysjnikov", + "fritz_kreisler", + "anne_hathaway", + "katarina", + "david_garrick", + "don_budge", + "bill_russell", + "baldwin", + "den_flygende_hollender", + "jeannette_rankin", + "nyman", + "harry", + "g", + "antons", + "arthur_schopenhauer", + "thomas_dekker", + "james_cagney", + "john_keble", + "johns_hopkins", + "gregers", + "wanda_landowska", + "billy_mitchell", + "martin_heidegger", + "hans_eysenck", + "gjerdesmettfamilien", + "h.c_andersen", + "muller", + "r", + "george_lucas", + "andrew_jackson", + "peter_abelard", + "louis_armstrong", + "tannfe", + "steven_spielberg", + "jean_monnet", + "leonard", + "d_w_griffith", + "robert_fulton", + "thomas_hardy", + "eddie_rickenbacker", + "thomas_gainsborough", + "giuseppe_garibaldi", + "philip_warren_anderson", + "alexandre_dumas", + "robert_brown", + "thomas_carlyle", + "johann_gutenberg", + "william_tyndale", + "tamara_karsavina", + "bobby_fischer", + "d", + "thomas_malthus", + "gaetano_donizetti", + "william_faulkner", + "andre", + "amerigo_vespucci", + "pierre_boulez", + "hans_adolf_krebs", + "lars", + "girolamo_savonarola", + "emma_goldman", + "francis_poulenc", + "james_ussher", + "john_barrymore", + "john_constable", + "james_mill", + "putin", + "matthew_flinders", + "seglarar", + "joseph_campbell", + "jean_de_la_fontaine", + "robert_hooke", + "o_henry", + "hoffa", + "karl_popper", + "john_william_robinson", + "alfred", + "coleman_hawkins", + "george_sand", + "peter_sellers", + "charles_fourier", + "henry_clay", + "marcus_aurelius", + "peter_o'toole", + "joseph_conrad", + "william_shockley", + "tsjajkovskij", + "peter_paul_rubens", + "mahatma_gandhi", + "jim_morrison", + "tresleiv", + "jules_verne", + "paul_newman", + "george_meredith", + "michelangelos_david", + "woody_herman", + "jackson_pollock", + "administrerende_direkt\u00f8r", + "brigadegeneral", + "john_lennon", + "andrea_palladio", + "stanley_jevons", + "oldeforelder", + "gandhi", + "bob_woodward", + "charlie_chaplin", + "thomas_malory", + "lea", + "john_brown", + "al_jolson", + "elizabeth_gaskell", + "statssjef", + "norman_thomas", + "minustegn", + "hannah_arendt", + "antonio_stradivari", + "maximianus", + "alice_walker", + "miles_davis", + "hjerterkonge", + "james_parkinson", + "wilhelm_tell", + "george_marshall", + "jesse_jackson", + "willa_cather", + "stanley_kubrick", + "edvard_martyren", + "minusteikn", + "john_huston", + "william_gilbert", + "james_watt", + "jonathan_edwards", + "ronald_reagan", + "helmut_schmidt", + "jenny_lind", + "homo", + "frederick_douglass", + "david_hilbert", + "wilhelm_reich", + "roman_jakobson", + "oliver_cromwell", + "lionel_hampton", + "james_hargreaves", + "frank_capra", + "william_wordsworth", + "rex_harrison", + "s", + "william_clark", + "woodrow_wilson", + "william_wycherley", + "gustav_hertz", + "george_mason", + "george_wallace", + "daud", + "el_cid", + "marcus_antonius", + "agrippina", + "st_louis", + "richard_rodgers", + "anne_sexton", + "john_dryden", + "jim_henson", + "frank", + "ernest_hemingway", + "john_eccles", + "george_westinghouse", + "magedansar", + "apostelen_peter", + "gressenkemann", + "jacques_charles", + "eero_saarinen", + "arthur_miller", + "gracie_allen", + "nelson_mandela", + "heinrich_himmler", + "al_gore", + "hans_bethe", + "hans_geiger", + "roald_amundsen", + "andersen", + "alfred_korzybski", + "mennesker", + "anton", + "charles_dickens", + "ella_fitzgerald", + "fats_waller", + "jack_robinson", + "alois_senefelder", + "george_enescu", + "jacques_offenbach", + "joseph_paxton", + "josefus", + "heidelbergmennesket", + "george_stevens", + "federico_fellini", + "statsoverhovud", + "bessie_smith", + "patrick_henry", + "willy_brandt", + "charles_wilkes", + "francisco_pizarro", + "francisco_franco", + "jackie_robinson", + "bernardo_bertolucci", + "king_oliver", + "jan_steen", + "frank_harris", + "philibert_delorme", + "andrew_carnegie", + "pontius_pilatus", + "franz_schubert", + "johnny_cash", + "joseph_mccarthy", + "alfred_kastler", + "dawid", + "mick_jagger", + "otto_loewi", + "georges_cuvier", + "william_harvey", + "walter_scott", + "peter_medawar", + "vladimir_lenin", + "sam_houston", + "robert_peary", + "robert_browning", + "ralph_ellison", + "john_bunyan", + "jonathan_swift", + "prakt\u00e6rfugl", + "walter_gropius", + "albert_einstein", + "thomas_edison", + "chiang_kai_shek", + "raymond_chandler", + "henry_purcell", + "pieter_stuyvesant", + "t", + "wilhelm_ostwald" + ], + "LOCATION": [ + "pensjonsfond", + "al_jazeera", + "linerle", + "p\u00e5ske\u00f8ya", + "flyv\u00e5pen", + "den_vestlige_halvkule", + "rappringvinge", + "markedskors", + "tempelh\u00f8yden", + "den_vesle_bj\u00f8rnen", + "kirseb\u00e6rhagen", + "mortensmesse", + "den_store_bj\u00f8rnen", + "tredjemann", + "\u00f8vresj\u00f8en", + "park", + "biscayabukta", + "aserbajdsjans_nasjonalforsamling", + "selvagens\u00f8yene", + "kanal\u00f8yene", + "drabantby", + "tungtvatn", + "mj\u00f8lkevegen", + "kanal\u00f8yane", + "bow_wow", + "united_states_army", + "mentalsykehus", + "s_tog", + "edvardsj\u00f8en", + "piet_mondrian", + "ha_long", + "nasjonalforsamling", + "krigsskole", + "sint_maarten", + "nord\u00f8ya", + "ungarns_parlament", + "chang_jiang", + "tredjeperson", + "atlanterhavet", + "fredsdommer", + "dei_amerikanske_sambandsstatane", + "om_bord", + "kryvyj_rih", + "bulgarias_parlament", + "to_br\u00f8dre", + "engsmyger", + "austkinahavet", + "allahu_akbar", + "patrick_av_irland", + "den_lille_l\u00f8ve", + "gulehavet", + "chatham\u00f8yane", + "de_store_sj\u00f8er", + "tornerose", + "skogsj\u00f8en", + "ringvei", + "kraftstasjon", + "land", + "\u00e5ker", + "selvagens\u00f8yane", + "qingmingfesten", + "saint_vincent", + "hoff", + "skogmurmeldyr", + "blue_mountains", + "biscayabukten", + "falklands\u00f8yane", + "kvit\u00f8ya", + "chatham\u00f8yene", + "saltsj\u00f8", + "joseph_louis_gay_lussac", + "luftforsvar", + "michigansj\u00f8en", + "saltvann", + "tredjepart", + "krigsskule", + "frankrikes_nasjonalforsamling", + "svartspett", + "tungtvann", + "ingen_\u00e5rsak", + "indiahavet", + "mentalsjukehus", + "den_vestlege_halvkula", + "i_tilfelle", + "barriererev", + "tennisbane", + "heimebane", + "dei_store_sj\u00f8ane", + "on_the_road", + "usa", + "bare_hyggelig", + "kirseb\u00e6rsommerfugl", + "saint_lucia", + "keiserkanalen", + "oljeberget", + "martinsdag", + "tungvatn", + "nordsj\u00f8en", + "jordanelva", + "det_indiske_hav", + "tanasj\u00f8en", + "hat_yai", + "sukkerbr\u00f8d", + "det_indiske_havet", + "arena", + "sri_lanka", + "blindveg", + "st_clairsj\u00f8en", + "den_usa_amerikanske_h\u00e6ren", + "den_gule_flod", + "den_engelske_kanal", + "s\u00f8r_koreas_nasjonalforsamling", + "fredsdomar", + "fredsdommar", + "keisarkanalen", + "blindvei", + "the_rolling_stones", + "varemagasin", + "blindgate", + "de_forente_stater", + "julenissen", + "kraftverk", + "saltvatn", + "psykiatrisk_sjukehus", + "huangelva", + "byggeteknikk", + "i_tilfelle_av", + "den_vesle_l\u00f8va", + "tyrrenhavet", + "for_godt_m\u00e5ls_skyld", + "per_p\u00e5l_og_askeladden", + "falklands\u00f8yene", + "ikke_noe_problem", + "telefonsentral", + "heitor_villa_lobos", + "den_engelske_kanalen", + "den_r\u00f8de_elv", + "hvit\u00f8ya", + "qingming", + "al_ain", + "svartehavet", + "stillehavet", + "den_hellige_stol", + "tempelh\u00f8gda", + "osman_i_av_det_osmanske_riket" + ], + "POLITICAL_PARTY": [ + "det_demokratiske_enhetspartiet", + "det_konservative_partiet_i_storbritannia", + "det_republikanske_parti", + "det_liberale_parti", + "partidul_social_democrat", + "partidul_conservator", + "nasjonalistpartiet", + "labour_party", + "partij_van_de_arbeid", + "f\u00f3lkaflokkurin", + "politisk_parti", + "det_konservative_parti", + "united_kingdom_independence_party", + "nsdap", + "det_demokratiske_parti", + "opposisjon", + "det_republikanske_partiet_i_usa", + "kommunistiska_partiet", + "kuomintang", + "det_demokratiske_partiet_i_usa", + "det_britiske_arbeidarpartiet", + "kommunistparti", + "det_sosialdemokratiske_parti", + "whig_party", + "sosialistpartiet_i_nederland", + "partido_popular", + "det_demokratisk_republikanske_parti", + "partido_socialista", + "anti_masonic_party", + "parti_socialiste", + "milj\u00f6partiet_de_gr\u00f6na", + "partito_democratico", + "sosialistpartiet", + "folkets_parti", + "arbeidarpartiet", + "javna\u00f0arflokkurin", + "australian_labor_party", + "nationalsozialistische_deutsche_arbeiterpartei", + "socialistische_partij", + "arbeiderpartiet" + ], + "PRODUCT": [ + "cook\u00f8yene", + "st_vincent", + "kaffekopp", + "forglemmegei", + "balkanfjella", + "badebukser", + "signalhandsaming", + "justin_bieber", + "tidsmaskinen", + "forgl\u00f8ymmegei", + "blindveg", + "new_zealand", + "kappverdisk", + "sportsbil", + "det_kommunistiske_manifest", + "s_tog", + "romerriket", + "s\u00e3o_tom\u00e9_og_pr\u00edncipe", + "morn", + "kaledonsk", + "cook\u00f8yane", + "karlsvognen", + "kaffekanne", + "blindvei", + "minneblom", + "al_jazeera", + "himmellekam", + "diego_garcia", + "heilaganden", + "den_amerikanske_borgerkrigen", + "i_ellevte_time", + "kaffikopp", + "helligtrekongersaften", + "f\u00f8rste_verdenskrig", + "nordljos", + "bli_voksen", + "automatsikring", + "johana", + "kulelager", + "den_heilage_maria", + "seilskip", + "pipeorgel", + "menneskerettigheter", + "sprettoppvindu", + "badebukse", + "allordbok", + "hjuldamper", + "av_guds_n\u00e5de", + "de_tre_rikers_tid", + "h\u00f8gsongen", + "blindgate", + "saint_vincent", + "diskett", + "h\u00f8ysangen", + "det_s\u00f8te_liv", + "det_nye_testamentet", + "milit\u00e6rfly", + "den_fyrste_verdskrigen", + "the_star_spangled_banner", + "storbritannia", + "andre_verdskrigen", + "stilleben", + "kaledonisk", + "effektbryter", + "musikkinstrument", + "som_om", + "bananb\u00e5t", + "menneskerettar", + "reknestav", + "de_vises_stein", + "den_hellige_\u00e5nd", + "sachsen_anhalt", + "to_br\u00f8dre", + "n\u00e5r_enden_er_god_er_allting_godt", + "dei_fire_\u00e5rstidene", + "ringdrotten", + "hockeyk\u00f8lle", + "kortslutning", + "hva_om", + "trekkopp", + "de_fire_\u00e5rstidene", + "boxing_day", + "sprettoppvindauge", + "et_dukkehjem", + "den_guddommelege_komedie", + "deutsche_welle", + "i_siste_\u00f8yeblikk", + "to_kvinner", + "gong", + "den_hellige_gral", + "mount_st_helens", + "ferdinand_magellan", + "regnestav", + "i_grevens_tid", + "hardkokt", + "det_kommunistiske_manifestet", + "mario_andretti", + "den_heilage_ande", + "keisarsnitt", + "panserbil", + "himmellegeme", + "dansegolv", + "keisersnitt", + "det_gylne_kompasset", + "seglskip", + "dei_tre_konged\u00f8ma_i_kina", + "romstasjon", + "johannes_d\u00f8peren", + "ringenes_herre", + "tredimensjonal", + "naturhistorie", + "andre_juledag", + "det_romerske_keiserriket", + "nordrhein_westfalen", + "isterning", + "det_nye_testamente", + "rosettasteinen", + "balkanfjellene", + "rosettastenen", + "gongong", + "andre_verdenskrig", + "i_siste_stund", + "novo_mesto", + "kapp_horn", + "nordlys", + "romarriket", + "den_guddommelige_komedie" + ], + "QUANTITY": [ + "austerriksk_schilling", + "primtal", + "rupee", + "beaufortskala", + "primfaktor", + "fransk_franc", + "desimaltal", + "planckkonstanten", + "metersystemet", + "under_fire_\u00f8yne", + "tone", + "parkeringshus", + "de_tre_rikers_tid", + "si_systemet", + "dollar", + "svingskive", + "ordinaltal", + "primtall", + "dei_tre_konged\u00f8ma_i_kina", + "ordenstal", + "titusen", + "dyreinternat", + "g", + "sveitserfranc", + "vektenhet", + "the_real_world", + "elektronvolt", + "tretti\u00e5rskrigen", + "hundretusen", + "beaufortskalaen", + "krone", + "einingssystem", + "parkeringsbot", + "tonespr\u00e5k", + "hongkongdollar", + "pond", + "ljos\u00e5r", + "kubikkmeter", + "ordenstall", + "smule", + "anders_celsius", + "desimaltall" + ], + "ANIMAL": [ + "steppefly", + "ringtrast", + "treleopard", + "tapetm\u00f8ll", + "styltel\u00f8per", + "amasonmaur", + "ferskvassdelfinfamilien", + "r\u00f8d_skogsmaur", + "vannrikse", + "acherontia", + "spekkhoggar", + "raudmus", + "terner", + "skogm\u00e5r", + "baktriakamel", + "villgeit", + "havl\u00earskjelpadde", + "stillits", + "polarsymjesnipe", + "hettem\u00e5se", + "bastardskilpadde", + "diamantskilpadde", + "moskusoks", + "lundtrupial", + "storfugl", + "storskrik\u00f8rn", + "eremittkreps", + "kermodebj\u00f8rn", + "przewalskihest", + "hettem\u00e5ke", + "sandloppe", + "tangsprell", + "hjelmfiskand", + "klovdyr", + "amerikansk_grevling", + "brugde", + "bergand", + "sambarhjort", + "varslar", + "sabinem\u00e5ke", + "arbeidsbie", + "siland", + "pirolfamilien", + "sandjegere", + "spissneshorn", + "skrukketroll", + "californiasj\u00f8l\u00f8ve", + "trielar", + "flygefisker", + "australstyltel\u00f8par", + "rustspettmeis", + "vinterjunko", + "saltvannskrokodille", + "havengler", + "reveekorn", + "grindhvaler", + "dachs", + "vandredue", + "rottesnok", + "franklinm\u00e5ke", + "hawaiimunkesel", + "tykkhornsau", + "kanadar\u00f8ye", + "kakaom\u00f8ll", + "seikval", + "andeskondor", + "jakthund", + "steinvendar", + "vestaper", + "ringtrost", + "sobel", + "hornugle", + "vandrealbatross", + "suppeskilpadde", + "billy_elliot", + "steppeh\u00f8ne", + "gullfasan", + "bananflue", + "baykatt", + "kongekobra", + "stjertand", + "kunduz", + "grindhval", + "styltel\u00f8par", + "araberhest", + "grevling", + "konge\u00f8rn", + "kj\u00f8ttfluer", + "dompap", + "sebramusling", + "jungelkatt", + "hunnkatt", + "masaisjiraff", + "horngjeterfugl", + "hjortebiller", + "selfamilien", + "jakthunder", + "jordlopper", + "spurvehauk", + "arabarhest", + "storstankelbein", + "kvalhai", + "splitterne", + "stokkmaur", + "irissommerfugl", + "tusselus", + "stellersj\u00f8l\u00f8ve", + "kanadag\u00e5s", + "trollflaggermus", + "maskarenepapeg\u00f8ye", + "havl\u00e6rskilpadde", + "klappmyss", + "kjempeblekksprut", + "sibirspurv", + "rubinstrupekolibri", + "stormsvaler", + "storjo", + "vestnilfeber", + "vannpiplerke", + "saigaantilope", + "enghauk", + "gullsjakal", + "kvitkinng\u00e5s", + "brillepingvin", + "den_vesle_hunden", + "askepottastrild", + "stumpneshorn", + "kornsnok", + "gumpkjertel", + "tynnhornsau", + "hodelus", + "gribb", + "savanneastrild", + "ravn", + "klumpfisk", + "steinvender", + "granatastrild", + "kvithakepetrell", + "den_lille_hund", + "pelsm\u00f8ll", + "gullskilpadde", + "latterugle", + "s\u00f8rkjempepetrell", + "rankef\u00f8ttinger", + "klatremus", + "raudaugevireo", + "herodiashegre", + "kongekondor", + "taggmakrell", + "eskimospove", + "rosenboa", + "amerikar\u00f8rdrum", + "mongolkaie", + "kirkeugle", + "kjempepetrellar", + "alligatorskilpadde", + "skorsteinsseiler", + "javaneshorn", + "spettmeis", + "ildsalamander", + "marimjellerutevinge", + "appelsinflue", + "ringg\u00e5s", + "grindkval", + "vasspiplerke", + "bardekval", + "flyvefisk", + "kongeterne", + "politihund", + "kvithalesymjesnipe", + "polarlomvi", + "malayfiskeugle", + "kongepingvin", + "bietere", + "bardehvaler", + "bekker\u00f8ye", + "nordpadde", + "austmarkmus", + "d\u00f8dsorm", + "stankelbein", + "kvithovudhav\u00f8rn", + "mink", + "r\u00f8dkardinal", + "gulstillits", + "stortrappe", + "hortulan", + "troster", + "kongeboa", + "dronningmor", + "moskusskilpadde", + "latterm\u00e5se", + "passer", + "mandarinand", + "kyllingkj\u00f8tt", + "amerikansk_hummar", + "vannb\u00f8ffel", + "villsvin", + "davidshjort", + "vannrotte", + "cairnterrier", + "sporvehauk", + "munkegribb", + "lappugle", + "makrellterne", + "stormsvale", + "kongemakrell", + "bl\u00e5kval", + "amerikamanat", + "aglajaperlemorvinge", + "sitronhai", + "styltesnipe", + "mankeulv", + "visent", + "langbeint", + "nordkrattvaktel", + "adeliepingvin", + "plystresnipe", + "albusnegl", + "ringdue", + "hundse", + "ringnebbdykker", + "andesflamingo", + "gummiboa", + "islandsand", + "krattastrild", + "langh\u00e5ret", + "geithams", + "karminspinner", + "vassrikse", + "langbeina", + "stivhaleand", + "finnkval", + "accipiter", + "havedderkopper", + "markr\u00e5kar", + "skogsm\u00e5r", + "kaffebiller", + "stillehavsmakrell", + "sebrafink", + "skogspurv", + "eikestjertvinge", + "granmeis", + "steinbukk", + "konglebit", + "flygefisk", + "amerikakrikkand", + "skogh\u00f8ns", + "sj\u00f8rose", + "skjeand", + "brunhyene", + "storkobbe", + "latterm\u00e5ke", + "villhest", + "kronhjort", + "sandkryper", + "vassrotte", + "vandrefalk", + "asiagullkatt", + "elvedelfiner", + "skaberakktapir", + "kr\u00e5kebolle", + "polarsnipe", + "rosenflamingo", + "lerkefalk", + "raudstjert", + "kvefs", + "spermhval", + "hammarhai", + "sultanh\u00f8ne", + "leirtrost", + "kalkunkondor", + "l\u00f8veunge", + "halsb\u00e5ndparakitt", + "kyrkjeugle", + "buorm", + "pattedyr", + "eplevikler", + "skogsh\u00f8ns", + "monarksommerfugl", + "leppebj\u00f8rn", + "grankorsnebb", + "punaflamingo", + "smellere", + "langbent", + "hornulke", + "karuss", + "vadefugl", + "donald_duck", + "slettevandrar", + "kamrotter", + "gribbar", + "brunalger", + "str\u00f8mpeb\u00e5ndssnok", + "hjortedyr", + "tundrasnipe", + "iller", + "vassb\u00f8ffel", + "kardinaltetra", + "gulbrynkjernebiter", + "gr\u00e5hval", + "polarhare", + "grankrossnebb", + "neslesommerfugl", + "berner_sennenhund", + "\u00e5kerrikse", + "hjort", + "krattspissmus", + "sangspurv", + "trastefamilien", + "brunrotte", + "teppepyton", + "kjempeblekkspruter", + "rosenst\u00e6r", + "biedronning", + "komodovaran", + "murerbier", + "lundugle", + "garvor", + "kaskelott", + "r\u00f8dgumpastrild", + "megascops", + "amerikahubro", + "maisild", + "hussmett", + "\u00e5tselgribb", + "kortvinger", + "taffeland", + "marabustork", + "alkekonge", + "gulskuldermaursmett", + "gulbeinsnipe", + "alveterne", + "saltvasskrokodille", + "afrikagullkatt", + "karett", + "sabinem\u00e5se", + "leprabasill", + "heipiplerke", + "brudeand", + "panserneshorn", + "gjerdesmett", + "gallvepser", + "bietarfamilien", + "gulstrupehonningeter", + "stormsvalefamilien", + "haimalle", + "marsvin", + "bj\u00f8rnung", + "kvithai", + "shetlandsponni", + "stripehyene", + "kjempemaursluker", + "gull", + "frosk", + "ringhalelemur", + "r\u00f8dmus", + "helligibis", + "havlire", + "hasselmus", + "husarape", + "fluesnapperfamilien", + "steppesebra", + "polarsv\u00f8mmesnipe", + "huskatt", + "moskusand", + "st_petersfisk", + "bengaltiger", + "songsvane", + "gulflankedelfin", + "stillehavstorsk", + "gouldamadin", + "kloskate", + "sandsvale", + "gjerdesmettfamilien", + "nettpyton", + "varicella_zoster_virus", + "enkeltbekkasin", + "r\u00f8dfotand", + "sildekonge", + "seilerfamilien", + "mankesau", + "vandretrost", + "bevere", + "vindm\u00f8llepalme", + "sanktpetersfisk", + "jordrotte", + "springpadder", + "r\u00f8dvingetrupial", + "heilo", + "kvitkval", + "laksand", + "sovemus", + "papirb\u00e5t", + "barramundi", + "l\u00f8pebiller", + "hovdyr", + "sangsvane", + "coloradobille", + "toppdukkar", + "munkelus", + "r\u00f8dalger", + "p\u00e5skehare", + "havelle", + "vorte\u00f8gle", + "vannmokkasin", + "raudspette", + "tussalus", + "spermkval", + "buttsnutefrosk", + "elefantskilpadde", + "gultoppkakadu", + "raudstrupe", + "hoggorm", + "dobbeltbekkasin", + "ringnebbdukkar", + "l\u00e5vesvale", + "kondor", + "zairegorilla", + "beltestyltel\u00f8par", + "wilsonstormsvale", + "skogmus", + "hamarhai", + "javarisfugl", + "gullklippehane", + "spekkhogger", + "brunbj\u00f8rn", + "amerikablesand", + "polarulv", + "fritte", + "peristediidae", + "falker", + "tornirisk", + "gulfinnetun", + "eider", + "sandkatt", + "toppdykker", + "palmedue", + "gullbryntrupial", + "gr\u00e5astrild", + "vannhund", + "skogfl\u00e5tt", + "kappingvin", + "teiste", + "klauvdyr" + ], + "DISEASE": [ + "hydrocephalus", + "pasjon", + "sars", + "samanbrot", + "dvergvekst", + "personlighetsforstyrrelse", + "bieffekt", + "overvektig", + "cellulitis", + "vendehalsar", + "klaustrofobi", + "tredagersfeber", + "i_den_retning", + "flekktyfus", + "bukhinnebetennelse", + "vestnilfeber", + "rage", + "skj\u00f8rbuk", + "neseblod", + "funksjonshemning", + "als", + "feila", + "reveskabb", + "rabies", + "mellomm\u00e5ltid", + "hovudverk", + "kverke", + "grunnleggjar", + "basalgangliene", + "stikket", + "mandelbetennelse", + "svartedauden", + "magekatarr", + "stamma", + "solbrenthet", + "rakitt", + "plantesykdom", + "svangerskapsforgiftning", + "katarr", + "tretthetsbrudd", + "progeria", + "stivkrampe", + "hordeolum", + "tannverk", + "presbyopi", + "herpes_simplexvirus", + "kaldsvette", + "gangren", + "anger", + "utstr\u00e5ling", + "knokkelbrot", + "kastanjeslekten", + "skrivekrampe", + "handikap", + "brucellose", + "raudne", + "i_retning_av", + "vannkopper", + "brystkreft", + "anestesi", + "beriberi", + "branns\u00e5r", + "mania", + "dementia", + "the_bends", + "uten_musikk\u00f8re", + "struma", + "paratyfus", + "ill_i_austerrike", + "hodepine", + "bunt", + "koldbrann", + "hussopp", + "poliomyelitt", + "brennkopper", + "rust", + "stjernet\u00e5ke", + "vasskoppar", + "testikkelkreft", + "sovesyke", + "benvevskreft", + "kaldbrann", + "panikklidelse", + "rosacea", + "vannblemme", + "verkebyll", + "hunger", + "anden\u00f8d", + "kj\u00f8retur", + "forstoppelse", + "brekke", + "lassafeber", + "mollusker", + "ulven", + "forstyrrelse", + "aura_\u00e5", + "gr\u00f8derikdom", + "ventrikkelflimmer", + "bistikk", + "sukkersyke", + "epidermiolysis_bullosa", + "harehjerte", + "leddgikt", + "andenaud", + "fremmedfrykt", + "vannbrokk", + "delirium", + "plevritt", + "almesjuke", + "betennelse", + "qi", + "kvise", + "kullosforgiftning", + "rakitis", + "ford\u00f8yelsesproblemer", + "sv\u00f8mmekl\u00f8e", + "lidenskap", + "f\u00f8resetnad", + "raseri", + "kolecystitt", + "gimp", + "rosett", + "fruktbarhet", + "stenose", + "mers", + "skarlagensfeber", + "frenzy", + "herpes", + "sammenbrudd", + "fargeblind", + "en_beretning_om_blindhet", + "brannskade", + "smart", + "amelia", + "marasmus", + "tannpine", + "datamus", + "hundegalskap", + "brunst", + "ed", + "pica", + "gj\u00f8rmehull", + "appendisitt", + "ford\u00f8yelsesbesv\u00e6r", + "helvetesild", + "liding", + "sugemerke", + "skarlaksfeber", + "beinbrudd", + "sensation", + "jernmangelanemi", + "forstuelse", + "potetpest", + "pain", + "ventrikkelseptumdefekt", + "spiseforstyrrelse", + "nettopp", + "pincheffekt", + "funksjonshemming", + "lammelse", + "the_passion_of_the_christ", + "ill_i_frankrike", + "karsinom", + "lesping", + "hermafrodittisme", + "schizoid", + "krepsen", + "naseblod", + "ill", + "chalazion", + "denguefeber", + "bradykardi", + "svangerskap", + "grunnlegger", + "\u00f8rebetennelse", + "stigmata", + "sinnsbevegelse", + "gulsott", + "underern\u00e6ring", + "pellagra", + "feilern\u00e6ring", + "tallblindhet", + "tunnelsyn", + "dykkarsjuke", + "friskhet", + "flue", + "sting", + "netthinneavl\u00f8sning", + "skrumplever", + "kategori:enterovirus", + "paritet", + "vendehalser", + "nys", + "sukkersjuke", + "forstopping", + "kuru", + "burn", + "krybbed\u00f8d", + "sovesjuke", + "fruktbarheit", + "elveblest", + "morgenkvalme", + "saltmangel", + "clusterhodepine", + "noma", + "the_hives", + "materialisme", + "dengue", + "preeklampsi", + "miltbrann", + "sigdcelleanemi", + "gass", + "le", + "papeg\u00f8yesyke", + "sensasjon", + "skyttergravsfeber", + "salmonella", + "kortvoksthet", + "hundebitt", + "nasebl\u00f8ding", + "grunnleggar", + "mili\u00e6rtuberkulose", + "graviditet", + "mages\u00e5r", + "bamblesyke", + "kakesi", + "malaria", + "reisesyke", + "fargeblindhet", + "drektighet", + "karfunkel" + ], + "POLITICAL_PARTY_MEMBER": [ + "kamerat", + "kommunistisk", + "kommunist" + ], + "PLANT": [ + "vivendel", + "markmalurt", + "h\u00f8stberberis", + "hjortetr\u00f8st", + "filtkrossved", + "strandflatbelg", + "strandsmelle", + "dunbj\u00f8rk", + "pine", + "sankt_maria", + "nonsblom", + "balsamgran", + "tytteb\u00e6r", + "paran\u00f8tt", + "rundbelg", + "meldr\u00f8ye", + "korallrot", + "svarterteknapp", + "kongsbregne", + "dragehodeslekta", + "himalaiaseder", + "markjordb\u00e6r", + "plomme", + "svartor", + "buksbom", + "melissa", + "prestekrage", + "klengjemaure", + "hvitpil", + "karplanter", + "prikkperikum", + "villeple", + "jordr\u00f8yk", + "strandmalurt", + "v\u00e5rerteknapp", + "vaid", + "salig", + "the_joshua_tree", + "philadelphus_coronarius", + "vierslekta", + "kakaob\u00f8nne", + "bratsj", + "terpentintre", + "hjertensfryd", + "platanl\u00f8nn", + "kornvalmue", + "teieb\u00e6r", + "legepestrot", + "tiriltunge", + "dekkfr\u00f8plantar", + "fjellarve", + "konglekjertelen", + "toppklokke", + "gr\u00f8nnburkne", + "solb\u00e6rbusk", + "furu", + "taggbregne", + "judaspengar", + "buskfuru", + "sennep", + "hengeving", + "paradisfugl", + "r\u00f8dsildre", + "balsampoppel", + "s\u00f8lvpoppel", + "morell", + "istervier", + "hvitkl\u00f8ver", + "arizonasypress", + "fagerklokke", + "monarda", + "artist", + "svartpoppel", + "barbadoslykt", + "fjellflokk", + "vierslekten", + "konglekjertel", + "kirseb\u00e6r", + "bredflangre", + "steineik", + "m\u00f8llesteinskrage", + "bladsalat", + "forglemmegei", + "laurb\u00e6rhegg", + "vaccinium_corymbosum", + "olivengr\u00f8nn", + "rutelilje", + "vegtistel", + "firtann", + "myrtelg", + "kurvpil", + "tempeltre", + "edelrogn", + "korstorn", + "sommereik", + "coloradoedelgran", + "dronningstarr", + "fjelledelgran", + "karsporeplante", + "parkhagtorn", + "venusfluefanger", + "candida_albicans", + "kjerringrokk", + "fjellhemlokk", + "svartvaln\u00f8tt", + "edelkastanje", + "ugrasklokke", + "sommerhyll", + "fjellburkne", + "forgl\u00f8ymmegei", + "strandnellik", + "pipelauk", + "melb\u00e6r", + "korallbusk", + "hvitmorb\u00e6r", + "larix_occidentalis", + "kardemomme", + "soleihov", + "sverdlilje", + "vasspest", + "beiskambrosia", + "andemat", + "reinrose", + "spissl\u00f8nn", + "ringblom", + "viere", + "kassiakanel", + "spolebusk", + "kvassd\u00e5", + "stortrollurt", + "kirseb\u00e6rplomme", + "vannlilje", + "jordskokk", + "mastikstre", + "gummifiken", + "blankburkne", + "kirseb\u00e6rslekten", + "brudespore", + "vasskrans", + "tangerin", + "rundskolm", + "smalkjempe", + "erteblomst", + "sevenbom", + "vrangalm", + "blodrips", + "islandslav", + "pengeurt", + "skarntyde", + "barlind", + "lychnis", + "bergamott", + "blomk\u00e5l", + "virginiaeiner", + "ormehode", + "sm\u00f8rvaln\u00f8tt", + "haustberberis", + "juletre", + "geittelg", + "krossved", + "pomerans", + "jonsokkoll", + "oliven", + "stankstorkenebb", + "sibirvalmue", + "kinak\u00e5l", + "flittiglise", + "australnesletre", + "strandvindel", + "montereyfuru", + "marsfiol", + "johannesurt", + "storrobinia", + "hagen\u00f8kleblom", + "rogn", + "leddved", + "svartfuru", + "sisselrot", + "furuslekta", + "sm\u00e5syre", + "vannplante", + "kaprifol", + "malurt", + "gullfuru", + "gyldenlakk", + "stjernesildre", + "almeslekta", + "ananaskirseb\u00e6r", + "keiserkrone", + "vasslilje", + "falkbregne", + "solsikke", + "tviskjeggveronika", + "negerhirse", + "hageb\u00f8nne", + "vierslekt", + "konglepalmer", + "steinnype", + "blackberry", + "pipekrage", + "belladonnaurt", + "hvitveis", + "amerikanesletre", + "gulflatbelg", + "sukkerr\u00f8yr", + "enghumleblom", + "koyamaki", + "legeveronika", + "vassarve", + "ruff", + "balderbr\u00e5", + "den_heilage_maria", + "traneb\u00e6r", + "morb\u00e6rfiken", + "setermjelt", + "kornblom", + "fuglevikke", + "tundravier", + "krike", + "tobakksplante", + "minneblom", + "bukketorn", + "gjerdevikke", + "engelmanngran", + "bermudaeiner", + "drosophyllum_lusitanicum", + "duskull", + "hengebj\u00f8rk", + "gr\u00e5selje", + "strandtorn", + "einstape", + "ulme", + "kattefot", + "vassplante", + "oliventre", + "skjoldberar", + "legesteinkl\u00f8ver", + "betlehemsstjerna", + "snauveronika", + "gyllenlakk", + "tebusk", + "engstorkenebb", + "filtkongslys", + "bekkeblom", + "engsmelle", + "cookfuru", + "halsekrus", + "beta_vulgaris", + "lawsonsypress", + "blomsterplanter", + "mastik", + "betlehemsstjernen", + "gulltorn", + "fredlaus", + "engsyre", + "furuslekten", + "pasjonsfrukt", + "stornesle", + "meldestokk", + "tytteb\u00e6rlyng", + "naverl\u00f8nn", + "tarmvriasal", + "sitronmelisse", + "gudetre", + "hjortesumak", + "hagesalat", + "leddvedslekta", + "klokkes\u00f8te", + "bostonbregne", + "mannaask", + "lyssiv", + "brennesle", + "pipekrave", + "rosetysbast", + "moskuskattost", + "r\u00f8dhyll", + "engkarse", + "trelyng", + "solb\u00e6rplante", + "lundstjerneblom", + "klematis", + "ligusterslekta", + "agathis_australis", + "libanonseder", + "hodek\u00e5l", + "jordveps", + "edelweiss", + "kl\u00f8versyre", + "kratthumleblom", + "paradisfuglar", + "brasiltre", + "froskebitt", + "plantedel", + "strandreddik", + "engsoleie", + "dunkjempe", + "torskemunn", + "floridaanis", + "virakfuru", + "brushane", + "ormetelg", + "belladonna", + "valurt", + "smilax_aspera", + "kanadagullris", + "sukkerr\u00f8r", + "europalerk", + "blokkeb\u00e6r", + "liljekonvall", + "stjerneanis", + "atlasseder", + "nattfiol", + "potetkreft", + "vallisneria", + "lundfiol", + "storalm", + "alder", + "magnoliaslekten", + "kj\u00f8rvel", + "bergflette", + "solblom", + "dauvnesle", + "oreslekten", + "brennesler", + "svartgran", + "t\u00f8rr\u00e5te", + "storborre", + "skjellgran", + "dicksonia_antarctica", + "rosenk\u00e5l", + "magnolia", + "s\u00f8lvlind", + "veitistel", + "svartolder", + "parykkbusk", + "sommareik", + "laurb\u00e6rtysbast", + "palmetre", + "musekl\u00f8ver", + "hengjebj\u00f8rk", + "frukttre", + "lintorskemunn", + "paradisfugler", + "matblekksopp", + "solanum_quitoense" + ], + "FOOD": [ + "skillingsbolle", + "blodp\u00f8lse", + "mousse", + "kanelbolle", + "egger\u00f8re", + "laurb\u00e6rblad", + "fiskepinne", + "fullkornbr\u00f8d", + "soyamelk", + "r\u00f8dk\u00e5l", + "karbonadesm\u00f8rbr\u00f8d", + "tartarsaus", + "kanelsnurr", + "bechamel", + "christmas_pudding", + "hvitvin", + "helmelk", + "l\u00f8nnesirup", + "blodpudding", + "h\u00f8nseegg", + "hurtigmat", + "kandissukker", + "\u00f8rken", + "chilipepper", + "kveitemj\u00f8l", + "hytteost", + "bambusskudd", + "bordsalt", + "heilmj\u00f8lk", + "pepperkakemann", + "saus", + "melkepulver", + "g\u00e5selever", + "appelsinskall", + "sveitserost", + "graskarpai", + "sn\u00f8ggmat", + "kajennepepar", + "pinot_noir", + "helmj\u00f8lk", + "mellomm\u00e5l", + "chilipepar", + "r\u00f8dgl\u00f8dende", + "ertesuppe", + "konditorfarge", + "matbit", + "pepper", + "sterkvin", + "hvitl\u00f8ksbr\u00f8d", + "bursdagskake", + "buljongterning", + "p\u00e5skeegg", + "appelsinskal", + "chili", + "speilegg", + "kvitvin", + "sylteagurk", + "olivenolje", + "sukkerspinn", + "peparkakemann", + "chile", + "antipasto", + "soyasaus", + "rullekake", + "kremfl\u00f8te", + "pudding", + "ros\u00e9vin", + "dessert", + "iskaffe", + "potetsalat", + "rosevin", + "raudvin", + "karbonadedeig", + "melkesjokolade", + "str\u00f8kavring", + "yorkshirepudding", + "kvitl\u00f8ksbr\u00f8d", + "mj\u00f8lkesjokolade", + "ostesaus", + "kvitlauksbr\u00f8d", + "holland\u00e9s", + "cayennepepper", + "ingef\u00e6r\u00f8l", + "gresskarpai", + "butterdeig", + "iskaffi", + "palmeolje", + "appelsinjuice", + "kumelk", + "waldorfsalat", + "heilmelk", + "kakaopulver", + "blautkokt", + "soyaolje" + ], + "JOB": [ + "brigader", + "kvalfangar", + "fengselsbetjent", + "den_ut\u00f8vande_makta", + "treskj\u00e6rer", + "grosserar", + "konditor", + "sjukepleiar", + "guru", + "g\u00e5rdbruker", + "kastar", + "cand.psych", + "grunnlegger", + "distribut\u00f8r", + "lakei", + "seter", + "biskop", + "seiler", + "tannlege", + "assistent", + "gatefeier", + "l\u00e6kjar", + "renholder", + "hjortejegeren", + "tanntekniker", + "budeie", + "mikrobiolog", + "handverkar", + "brannkonstabel", + "melkepiken", + "herold", + "naturviter", + "rennestein", + "trener", + "kjeleflikker", + "kirurg", + "foredragsholder", + "lascar", + "sakristan", + "hand", + "feltmarskalk", + "ergoterapeut", + "gjestearbeidar", + "borgermester", + "treningsfly", + "vitskapskvinne", + "bestyrer", + "don", + "planter", + "toksikolog", + "cand.jur", + "kansler", + "dermatolog", + "grunnleggjar", + "fyrb\u00f8ter", + "the_police", + "intern", + "lederskikkelse", + "pretor", + "pr\u00e6rieulv", + "formann", + "kasserar", + "grunnleggar", + "gentleman", + "romanforfattar", + "kabinpersonale", + "krigar", + "ingeni\u00f8r", + "hjerneslag", + "fremmedarbeider", + "territorial", + "glasbl\u00e5sar", + "forretningsmann", + "blomsterpike", + "regelmessig", + "taler\u00f8r", + "formynder", + "leder", + "borgarmeister", + "kondukt\u00f8r", + "bartskj\u00e6r", + "eigedomsmeklar", + "brigadegeneral", + "hvalfanger", + "spotter", + "mastermind", + "kirkeverge", + "tapper", + "hoffdame", + "skodespelar", + "snikkar", + "flaggberar", + "klokkar", + "billedhuggeren", + "finansdirekt\u00f8r", + "testflyver", + "svenn", + "land", + "stallmester", + "eiendomsmekler", + "boss", + "vinkelner", + "universitetslektor", + "kjemiker", + "grenadier", + "underoffiser", + "glassbl\u00e5ser", + "veverske", + "sersjant", + "slagtilfelle", + "printer", + "kurator", + "assisterende", + "reinholder", + "verje", + "slavinne", + "premierl\u00f8ytnant", + "reinhaldar", + "kamikaze", + "\u00f8yenlege", + "performer", + "streikebrytar", + "strippar", + "korporal", + "baker", + "borgermesterinne", + "kolonialhandler", + "forretningsfolk", + "treskjerar", + "endokrinolog", + "tusenkunstner", + "glasmeister", + "sikkerheitsvakt", + "glassmester", + "the_guardian", + "m\u00f8llar", + "berebjelke", + "vinduspusser", + "vesir", + "president", + "laupar", + "gruppel\u00e6rer", + "minister", + "mandarin", + "setter", + "st\u00f8ttekontakt", + "oversetter", + "h\u00e5ndverker", + "leksikograf", + "sj\u00f8kaptein", + "vitenskapskvinne", + "gatefeiar", + "lensmann", + "oberstl\u00f8ytnant", + "blokkfl\u00f8yte", + "forretningsperson", + "mate", + "guide", + "terapeut", + "kaster", + "kunstm\u00e5lar", + "designer", + "kunstmaler", + "formyndar", + "mylnar", + "pastor", + "skolel\u00e6rer", + "grovf\u00f4r", + "barnevakt", + "altmogelegmann", + "sheriff", + "grafiker", + "regulator", + "stridsmann", + "arbeider", + "rullef\u00f8rer", + "resepsjonist", + "hjelpel\u00e6rer", + "skrankeadvokat", + "f\u00f8rsteamanuensis", + "flaggb\u00e6rer", + "vever", + "gardbrukar", + "gaucho", + "viseadmiral", + "bosetter", + "mottaker", + "gardbruker", + "orkesterleder", + "slave", + "framandarbeidar", + "ha_tilsyn_med", + "the_economist", + "\u00f8verstkommanderende", + "spelar", + "kasserer", + "wetter", + "pantsette", + "brannslokningsapparat", + "sysselmann", + "flislegger", + "foredragshaldar", + "infanterist", + "stripper", + "grafikar", + "barista", + "annenfiolin", + "hjelpar", + "f\u00f8redragshaldar", + "patolog", + "barber", + "the_hangover", + "man", + "konge", + "stripperske", + "doc", + "regent", + "kjemikar", + "sekondl\u00f8ytnant", + "marine", + "sj\u00f8mann", + "mellombels", + "cand.med", + "grosserer", + "the_boxer", + "hjelper", + "sykepleier", + "neurolog", + "usher", + "messenger", + "statssekret\u00e6r", + "arbeidar", + "kolonialhandlar", + "alt_mulig_mann", + "au_pair", + "vernehjelm", + "fris\u00f8r", + "fallskjermsoldat", + "familiefors\u00f8rger", + "havnearbeider", + "trier", + "harepus", + "bakrus", + "andrefiolin", + "allmenn", + "selvstendig", + "kassadame", + "altmuligmann", + "vekter", + "jordmor", + "veileder", + "barnepike", + "romanforfatter", + "nevrolog", + "handelsmann", + "the_independent", + "nevrokirurg", + "turner", + "bishop", + "sikkerhetsvakt", + "gjestearbeider", + "statsr\u00e5d", + "streikebryter", + "bankier", + "brannmann", + "springar", + "samfunns\u00f8konom", + "kardiolog", + "fengselsdirekt\u00f8r", + "gartnar", + "preceptor" + ], + "FAC": [ + "hengjebru", + "den_heilage_josef", + "vindtunnel", + "pumpestasjon", + "hengebru", + "universitetsby", + "konsertsal", + "den_engelske_kirkja", + "kjernekraftverk", + "atomkraftverk", + "det_osmanske_riket", + "den_siste_nattverden", + "georgskross", + "underhus", + "der_zauberberg", + "skytebane", + "georgskors", + "t_celle", + "hengebro", + "politistasjon", + "den_engelske_kirke", + "ole_brumm", + "klagemuren", + "den_romersk_katolske_kirke", + "skisted", + "steinmur", + "triumfbue", + "arnold_sch\u00f6nberg", + "kruttm\u00f8lle", + "dei_fire_\u00e5rstidene", + "kaffirlime", + "josef_jesu_fosterfar", + "den_katolske_kirke", + "fisketank", + "forelesningssal", + "politikammer", + "vindtunell", + "de_fire_\u00e5rstidene", + "vestmuren", + "den_katolske_kyrkja", + "tollbod", + "svingbru", + "trolldomsfjellet", + "peter_i_av_russland", + "nattverden", + "saint_lucia", + "kunstakademi", + "guardian_angels", + "papirfabrikk", + "den_ubesmittede_unnfangelse", + "svingbro", + "vaktarrest", + "posthus", + "titus_livius", + "h\u00f8yporten", + "den_h\u00f8ge_porten", + "steingjerde", + "steingard", + "den_engelske_kyrkja", + "grunnskole", + "det_osmanske_rike", + "postkontor", + "marinebase", + "den_katolske_kirkja", + "steinvegg", + "friedrichshain_kreuzberg" + ], + "DATE": [ + "middelalder", + "valgdag", + "overmorgon", + "gullalderen", + "langfredag", + "den_industrielle_revolusjon", + "palmes\u00f8ndag", + "feitetirsdag", + "treenighetss\u00f8ndag", + "mellomalderen", + "allehelgensdag", + "feitetysdag", + "halvtime", + "minnedagen", + "fridag", + "v\u00e5r_tidsregning", + "stengetid", + "f\u00f8r_eller_siden", + "romalderen", + "nattskift", + "the_day_after_tomorrow", + "den_industrielle_revolusjonen", + "gullalder", + "minuttvolum", + "sensommer", + "h\u00f8stjevnd\u00f8gn", + "istid", + "f\u00f8r_eller_seinare", + "in_time", + "menstruasjonssyklus", + "den_stille_veka", + "skj\u00e6rtorsdag", + "mellomalder", + "parabolsk_hastighet", + "overmorgen", + "sykefrav\u00e6r", + "farsdag", + "solkonstanten", + "sommersolverv", + "i_tide", + "halveringstid", + "den_gregorianske_kalenderen", + "arbeidstid", + "nattevakten", + "den_julianske_kalenderen", + "palmesundag", + "f\u00f8r_eller_seinere", + "m\u00e5nefase", + "nasjonaldag", + "spedbarnsd\u00f8delighet", + "sykepenger", + "helligtrekongersaften", + "sumarsolkverv", + "regntid", + "haustjamnd\u00f8gn", + "vintersolverv", + "stordomstid", + "holdbarhetstid", + "harlemrenessansen", + "stengjetid", + "millenniumdomen", + "i_verdensklasse", + "bryllupsdag", + "askeonsdag", + "sommarsolkverv", + "fullm\u00e5ne", + "lyshastighet", + "radialhastighet", + "vintersolkverv", + "der_borte", + "mortalitet", + "haustjamnd\u00f8ger", + "nattvakt", + "kalender\u00e5r", + "gregoriansk_kalender", + "normaltid", + "feittysdag", + "treeiningssundag", + "hvitetirsdag", + "helgemesse", + "fritid", + "feittirsdag", + "hundre\u00e5rsskifte", + "rushtid", + "den_stille_uke", + "morsdag", + "grautatirsdag", + "middelalderen", + "d\u00f8dsrate" + ], + "LANGUAGE": [ + "walisisk", + "portugisisk", + "polsk", + "persisk", + "rumensk", + "nordsamisk", + "venda", + "vallonsk", + "kongo", + "akan", + "forfine", + "norsk", + "marshallesisk", + "russar", + "kasakhstaner", + "malayisk", + "aksent", + "finlandsk", + "hviterussisk", + "madagasser", + "pali", + "tysker", + "gasser", + "manx", + "madagassar", + "malayalam", + "samoanar", + "betoning", + "russer", + "hindi", + "spansk", + "kviterussisk", + "esperanto", + "grusisk", + "roman\u00e9s", + "kasakhstanar", + "lingala", + "islandsk", + "georgisk", + "lao", + "langveisfra", + "ido", + "gassar", + "japansk", + "quechua", + "akansk", + "tonga", + "kannada" + ], + "RACE": [ + "turke", + "j\u00f8disk", + "nordkorean", + "indian_airlines", + "engelskmenn", + "latinamerikanar", + "latin", + "japanar", + "filippinsk", + "latinamerikaner", + "nederlendere", + "afrikansk", + "franskmenn", + "polynesisk", + "franskmann", + "negro", + "nordkoreaner", + "nordkoreanar" + ], + "GENDER": [ + "vaskehjelp", + "stovejente", + "mine_damer_og_herrer", + "gentleman", + "hunkj\u00f8nn", + "fruentimmer", + "men", + "dame", + "stuejente", + "male", + "mannsperson", + "hunnlig", + "holeg", + "hunlig", + "svarteper", + "lass", + "transkj\u00f8nnet", + "man", + "det_smukke_kj\u00f8nn", + "transgen", + "gal", + "hushjelp", + "hankj\u00f8nnsvesen", + "hannkj\u00f8nn" + ], + "RELIGION_MEMBER": [ + "guru", + "the_hindu", + "protestant", + "christin", + "kristne", + "fransiskanarordenen", + "pinsevenn", + "mormon", + "muhammedaner", + "parsarar", + "fransiskanerordenen" + ], + "GPE": [ + "menneskerettar", + "gamleby", + "det_tyske_keisard\u00f8met", + "gullgruve", + "det_nye_testamentet", + "saint_domingue", + "xihu", + "kotte", + "dar_es_salaam", + "valentinsdag", + "j\u00f8rgensdagen", + "mellom_amerika", + "sint_maarten", + "menneskerett", + "det_hellige_land", + "st_lawrence_elva", + "den_heilage_j\u00f8rgen", + "det_nye_testamente", + "sankt_j\u00f8rgen", + "det_heilage_landet", + "den_heilage_nikolas", + "valentinsdagen", + "sankt_georg", + "industriomr\u00e5de", + "s\u00e3o_tom\u00e9", + "j\u00f8rgensdag", + "hagia_sofia", + "raudekrossen", + "det_kvite_huset_i_washington_d.c", + "det_tyske_keiserrike", + "gran_canaria", + "langb\u00f8lgje", + "taishanfjellet", + "tyske_rike", + "sankta_barbara", + "den_heilage_ande", + "heilaganden", + "menneskerettighet", + "det_hvite_hus", + "raudehavet", + "st_kristoffer", + "al_andalus", + "langbylgje", + "fjellpass", + "la_rochelle", + "r\u00f8dehavet", + "nytt_testament", + "den_hellige_\u00e5nd", + "r\u00f8de_kors", + "charlottenburg_wilmersdorf", + "vinh_long", + "fjellovergang", + "la_gomera", + "menneskerettigheter", + "st_louis" + ], + "BIO_CHEM_ENTITY": [ + "laurinsyre", + "silisiumdioksid", + "sinkklorid", + "kaliumjodid", + "beinmel", + "polyvinylklorid", + "c_reaktivt_protein", + "melkesyre", + "feittsyre", + "feittsyrer", + "druekjerneolje", + "sitronsyre", + "peparmynteolje", + "salisylsyre", + "salmiakk", + "peppermynteolje", + "d_vitamin", + "mj\u00f8lkesyre", + "fettsyre" + ], + "RELIGION": [ + "zen", + "salafisme", + "presbyterianisme", + "den_evangelisk_lutherske_kyrkja", + "islam", + "den_evangelisk_lutherske_kirke", + "christian_science", + "shint\u014disme", + "donatister", + "manikeisme", + "wicca" + ], + "EVENT": [ + "stavsprang", + "golfkrigen", + "d\u00f8dsdans", + "filmfestival", + "verdensutstilling", + "gulfkrigen", + "sing_sing", + "forvarsel", + "s\u00e5nn_er_livet", + "opp_med_haken" + ], + "LAW": [ + "d\u00f8dsdom", + "pressefrihet", + "forsamlingsfrihet", + "h\u00f8yesterett", + "advokatfirma", + "religionsfrihet", + "valgordning", + "rettsstat", + "statsforfatning", + "rettssp\u00f8rsm\u00e5l", + "trykkefridom", + "strafferett", + "rettergangsstraff", + "den_amerikanske_grunnloven", + "storjury", + "romerretten", + "straffelov", + "trykkefrihet", + "federal_bureau_of_investigation", + "religionsfridom", + "h\u00f8gsterett" + ], + "UNION": [ + "den_internasjonale_telekommunikasjonsunion", + "fagorganisasjon", + "verdspostforeininga", + "international_telecommunication_union", + "studentting", + "verdenspostforeningen" + ], + "PERSON": [ + "al_gore", + "saint_vincent", + "st_vincent", + "william_playfair", + "don_delillo", + "ekte_gummitre", + "george_v", + "igor_sikorsky", + "distr\u00e9", + "carl_david_anderson", + "st_petersfisk", + "c_vitamin", + "ko_ko", + "maxwell_anderson", + "rudolf_hess", + "dr_watson" + ], + "MEDICAL_THERAPY": [ + "blodtrykk" + ], + "PERSON_PRONOUN": [ + "i", + "mine", + "our", + "dykk", + "her", + "hennes", + "meg_selv", + "me", + "ditt" + ], + "SOC_ECO_CLASS": [ + "brorskap", + "samurai", + "overklasse", + "caste", + "underverden", + "arbeiderklasse", + "arbeidarklasse", + "proletariat", + "middelklasse", + "svarteb\u00f8rs" + ], + "ANAT": [ + "hjartemuskel" + ], + "ner_regexes": [ + [ + "PERSON", + "\\D+ \\D+|\\D+ \\D+|\\D+ \\D+|\\D+ \\D+|\\D+ \\D+|\\D+ \\D+|\\D+ \\D+|\\D+ \\D+|\\D+ \\D+|\\D+ \\D+|\\D+ \\D+|\\D+ \\D+|\\D+ \\D+|\\D+ \\D+|\\D+ \\D+|\\D+ \\D+|\\D+-\\D+ \\D+|\\D+-\\D+ \\D+|\\D+-\\D+ \\D+|\\D+-\\D+ \\D+|\\D+ \\D+-\\D+|\\D+ \\D+-\\D+|\\D+ \\D+ \\D+", + false, + [] + ] + ], + "FIRST_NAME_FEMALE": [ + "astrid", + "solveig", + "sara", + "kari", + "camilla", + "tone", + "ann", + "hanne", + "janne", + "thea", + "karin", + "marie", + "elise", + "kjersti", + "grete", + "cecilie", + "sofie", + "maria", + "kirsten", + "kristin", + "siv", + "aud", + "helene", + "ingrid", + "anna", + "maren", + "tove", + "anne", + "ingeborg", + "eva", + "emilie", + "silje", + "unni", + "mette", + "lene", + "anita", + "torill", + "line", + "anette", + "grethe", + "julie", + "inger", + "heidi", + "liv", + "hanna", + "ruth", + "bj\u00f8rg", + "ragnhild", + "hilde", + "may", + "linda", + "andrea", + "nora", + "reidun", + "britt", + "trine", + "ida", + "cathrine", + "malin", + "jenny", + "vilde", + "nina", + "martine", + "elisabeth", + "wenche", + "sigrid", + "rita", + "kristine", + "bente", + "siri", + "hege", + "mona", + "eli", + "irene", + "turid", + "sissel", + "\u00e5se", + "marit", + "jorunn", + "ellen", + "laila", + "gunn", + "emma", + "gerd", + "marianne", + "elin", + "mari", + "berit", + "tonje", + "karoline", + "stine", + "karen", + "synn\u00f8ve", + "marte", + "linn", + "randi", + "else", + "lise", + "monica", + "gro" + ], + "FIRST_NAME_MALE": [ + "h\u00e5vard", + "kenneth", + "roger", + "arild", + "fredrik", + "vidar", + "p\u00e5l", + "joakim", + "jens", + "kjell", + "thor", + "anders", + "h\u00e5kon", + "daniel", + "\u00f8ystein", + "tore", + "kristoffer", + "johannes", + "tobias", + "alexander", + "roar", + "alf", + "torbj\u00f8rn", + "tor", + "terje", + "magnus", + "kristian", + "einar", + "ivar", + "ola", + "trond", + "knut", + "steinar", + "andreas", + "john", + "kim", + "hans", + "asbj\u00f8rn", + "sigurd", + "helge", + "dag", + "emil", + "j\u00f8rgen", + "eivind", + "lars", + "marius", + "geir", + "jan", + "christian", + "arne", + "sindre", + "\u00f8yvind", + "leif", + "roy", + "jon", + "stig", + "nils", + "finn", + "markus", + "sondre", + "johan", + "per", + "martin", + "ole", + "tommy", + "bj\u00f8rn", + "olav", + "morten", + "henrik", + "stian", + "eirik", + "harald", + "rolf", + "sebastian", + "mathias", + "gunnar", + "adrian", + "odd", + "k\u00e5re", + "svein", + "frode", + "egil", + "robert", + "thomas", + "petter", + "vegard", + "erik", + "sander", + "simen", + "frank", + "rune", + "stein", + "erling", + "jonas", + "sverre", + "espen", + "tom", + "kjetil", + "magne", + "karl" + ], + "FIRST_NAME": [ + "h\u00e5vard", + "kenneth", + "roger", + "astrid", + "solveig", + "arild", + "fredrik", + "sara", + "vidar", + "kari", + "camilla", + "p\u00e5l", + "tone", + "ann", + "hanne", + "joakim", + "janne", + "thea", + "karin", + "marie", + "jens", + "elise", + "kjell", + "kjersti", + "grete", + "thor", + "anders", + "h\u00e5kon", + "daniel", + "cecilie", + "\u00f8ystein", + "tore", + "sofie", + "maria", + "kirsten", + "kristoffer", + "johannes", + "kristin", + "tobias", + "alexander", + "roar", + "siv", + "tor", + "alf", + "torbj\u00f8rn", + "aud", + "helene", + "terje", + "magnus", + "kristian", + "ingrid", + "einar", + "anna", + "ivar", + "maren", + "ola", + "tove", + "trond", + "knut", + "anne", + "steinar", + "andreas", + "ingeborg", + "eva", + "john", + "emilie", + "silje", + "unni", + "mette", + "kim", + "lene", + "hans", + "anita", + "torill", + "line", + "asbj\u00f8rn", + "sigurd", + "helge", + "dag", + "emil", + "grethe", + "anette", + "j\u00f8rgen", + "julie", + "inger", + "heidi", + "eivind", + "liv", + "hanna", + "ruth", + "bj\u00f8rg", + "lars", + "ragnhild", + "hilde", + "may", + "linda", + "andrea", + "marius", + "nora", + "reidun", + "geir", + "jan", + "monica", + "britt", + "christian", + "arne", + "sindre", + "\u00f8yvind", + "trine", + "leif", + "ida", + "roy", + "cathrine", + "malin", + "jon", + "stig", + "nils", + "finn", + "markus", + "jenny", + "sondre", + "vilde", + "nina", + "johan", + "per", + "martin", + "martine", + "elisabeth", + "wenche", + "ole", + "tommy", + "bj\u00f8rn", + "olav", + "sigrid", + "morten", + "henrik", + "rita", + "kristine", + "bente", + "siri", + "stian", + "eirik", + "hege", + "mona", + "harald", + "rolf", + "eli", + "irene", + "turid", + "sissel", + "\u00e5se", + "sebastian", + "marit", + "jorunn", + "mathias", + "ellen", + "laila", + "gunn", + "emma", + "adrian", + "gerd", + "gunnar", + "marianne", + "odd", + "elin", + "k\u00e5re", + "mari", + "svein", + "frode", + "berit", + "egil", + "robert", + "thomas", + "karoline", + "petter", + "vegard", + "erik", + "sander", + "simen", + "frank", + "rune", + "stein", + "stine", + "karen", + "erling", + "sverre", + "synn\u00f8ve", + "jonas", + "espen", + "marte", + "tom", + "kjetil", + "linn", + "randi", + "magne", + "else", + "lise", + "tonje", + "gro", + "karl" + ], + "LAST_NAME": [ + "hanssen", + "berg", + "nyg\u00e5rd", + "ellingsen", + "kristensen", + "berge", + "christensen", + "johansen", + "eriksen", + "str\u00f8m", + "birkeland", + "simonsen", + "knudsen", + "karlsen", + "s\u00f8rensen", + "haug", + "helland", + "danielsen", + "henriksen", + "isaksen", + "thomassen", + "sivertsen", + "svendsen", + "jakobsen", + "lie", + "hagen", + "brekke", + "solberg", + "myklebust", + "gundersen", + "mikkelsen", + "ruud", + "eide", + "engen", + "jensen", + "paulsen", + "haugland", + "lund", + "bakke", + "s\u00e6ther", + "dahl", + "aune", + "thorsen", + "johannessen", + "n\u00e6ss", + "sandvik", + "holm", + "andreassen", + "andresen", + "jenssen", + "solheim", + "myhre", + "larsen", + "lunde", + "fredriksen", + "nielsen", + "j\u00f8rgensen", + "ali", + "nilsen", + "berntsen", + "knutsen", + "strand", + "amundsen", + "vik", + "moe", + "halvorsen", + "antonsen", + "moen", + "arnesen", + "kristoffersen", + "aas", + "olsen", + "eliassen", + "bakken", + "evensen", + "b\u00f8e", + "aasen", + "martinsen", + "andersen", + "gulbrandsen", + "hauge", + "iversen", + "edvardsen", + "rasmussen", + "mathisen", + "pettersen", + "madsen", + "abrahamsen", + "lien", + "\u00f8deg\u00e5rd", + "tangen", + "tveit", + "ahmed", + "hansen", + "r\u00f8nning", + "nguyen", + "jacobsen", + "haugen", + "kristiansen", + "pedersen", + "johnsen" + ], + "OTHER_PRONOUN": [ + "it" + ], + "LAST_NAME_MALE": [], + "LAST_NAME_FEMALE": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "abbedisse": "abbed", + "baronesse": "baron", + "working_girl": "forretningsmann", + "fugleunge": "dandy", + "datter": "son", + "filla": "son", + "dotter": "son", + "hertuginne": "duk", + "keisarinne": "keiser", + "keiserinne": "keiser", + "hunlig": "hannkj\u00f8nn", + "hunn": "ille", + "holeg": "male", + "hunnlig": "hankj\u00f8nnsvesen", + "kvinneleg": "hankj\u00f8nnsvesen", + "kvinnelig": "male", + "feminin": "hankj\u00f8nnsvesen", + "s\u00f8nnedatter": "dotterbarn", + "datterdatter": "dotterson", + "bestemor": "farfar", + "farmor": "morfar", + "mormor": "bestefar", + "hennes": "seine", + "her": "seine", + "henne": "seine", + "heroin": "heltinne", + "fru": "human", + "hokj\u00f8nn": "man", + "fruentimmer": "minske", + "kvinne": "isle_of_man", + "kvinnemenneske": "man", + "hunkj\u00f8nn": "man", + "lass": "ladd", + "frue": "husbond", + "elsker": "mester", + "moder": "fatter", + "mutter": "fader", + "niese": "nev\u00f8", + "nun": "klosterbror", + "politikvinne": "politibetjent", + "prestinne": "prest", + "pr\u00edncipe": "fyrsten", + "prinsesse": "prins", + "majestet": "kung", + "dronning": "konge", + "hetman": "konge", + "queen": "konge", + "regine": "f\u00f8rste_kongebok", + "queens": "f\u00f8rste_kongebok", + "stores\u00f8ster": "blod", + "syster": "bror", + "naja": "blod", + "s\u00f8ster": "blod", + "lilles\u00f8ster": "broder", + "stedotter": "steson", + "stedatter": "stes\u00f8nn", + "stemor": "stefar", + "enkje": "enkjemann", + "enke": "enkjemann", + "hustru": "husbond", + "viv": "husbond", + "ektehustru": "husbond", + "hex": "magiker", + "wicca": "magiker", + "heks": "magiker", + "norn": "trollmann", + "sm\u00f8rflyndre": "trollmann", + "ten\u00e5ringsgutt": "jenta", + "fant": "jente", + "gutt": "jente" + }, + "other_gender_swap": { + "elles": "hunn", + "deres": "her", + "deira": "henne", + "dems": "her", + "lia": "her", + "hann": "elles", + "ille": "elles", + "hunn": "elles", + "hennes": "dems", + "her": "dems", + "henne": "deres" + }, + "en_pronoun2gender": { + "they": [ + "transkj\u00f8nnet", + "homoseksuell", + "transgen", + "transperson" + ], + "he": [ + "mannsperson", + "dandy", + "minske", + "hovud", + "maskulin", + "mannlig", + "isle_of_man", + "individ", + "human", + "ladd", + "hankj\u00f8nnsvesen", + "gentleman", + "man", + "hannkj\u00f8nn", + "gutt", + "little_boy", + "male", + "gaur", + "ten\u00e5ringsgutt", + "hann", + "fant" + ], + "she": [ + "stuejente", + "hunnlig", + "kvinnemenneske", + "hushjelp", + "lesbisk", + "kvinne", + "vaskehjelp", + "fru", + "savne", + "eininga_gal", + "fr\u00f8ken", + "gal", + "sm\u00e5jente", + "jente", + "jenta", + "kvinnelig", + "feminin", + "sakne", + "hunlig", + "hunkj\u00f8nn", + "hokj\u00f8nn", + "det_smukke_kj\u00f8nn", + "stuepike", + "lesbe", + "holeg", + "fruentimmer", + "hunn", + "stovejente", + "dame", + "kvinneleg" + ] + }, + "en_pronoun2pronoun": { + "he": [ + "hann", + "seine", + "ille", + "lia" + ], + "she": [ + "henne", + "hunn", + "hennes", + "her" + ], + "they": [ + "elles", + "dems", + "lia", + "deira", + "deres" + ], + "it": [ + "tyto", + "disse", + "dess", + "dette", + "dets", + "it", + "denne", + "dass", + "tann" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/nog.json b/data_tooling/pii_processing/ontology/data/nog.json new file mode 100644 index 0000000..cfa8d46 --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/nog.json @@ -0,0 +1,56 @@ +{ + "RELIGION_MEMBER": [ + "\u043c\u043e\u043b\u043b\u0430" + ], + "ANIMAL": [ + "\u0431\u0430\u043a\u0430", + "\u043a\u0430\u0432\u044b\u0441" + ], + "PERSON_PRONOUN": [ + "\u043e\u043b" + ], + "GENDER": [ + "\u043a\u0430\u0440\u0442" + ], + "LOCATION": [ + "\u0435\u0442\u0435\u0433\u0435\u043d" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "\u0430\u0432\u0430": "\u044d\u043c\u0435\u043d" + }, + "other_gender_swap": { + "\u0443\u043b\u0430\u0440": "\u043e\u043b", + "\u043e\u043b\u0430\u0440": "\u043e\u043b", + "\u043e\u043b": "\u0443\u043b\u0430\u0440" + }, + "en_pronoun2gender": { + "she": [ + "\u044f\u0441", + "\u043a\u044b\u0441" + ] + }, + "en_pronoun2pronoun": { + "he": [ + "\u043e\u043b" + ], + "she": [ + "\u043e\u043b" + ], + "they": [ + "\u0443\u043b\u0430\u0440", + "\u043e\u043b\u0430\u0440" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/non.json b/data_tooling/pii_processing/ontology/data/non.json new file mode 100644 index 0000000..4d56af2 --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/non.json @@ -0,0 +1,61 @@ +{ + "ANIMAL": [ + "brant", + "ketta", + "korpr" + ], + "PLANT": [ + "reynir" + ], + "DATE": [ + "palmasunnudagr", + "palmadr\u00f3ttinsdagr" + ], + "LOCATION": [ + "svartahaf", + "innbyr\u00f0is" + ], + "DISEASE": [ + "hungr" + ], + "LANGUAGE": [ + "finnskr" + ], + "PUBLIC_FIGURE": [ + "pedr", + "lafranz" + ], + "JOB": [ + "kongr" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "dr\u00f3ttning": "kongr", + "systir": "br\u00f3\u00f0ir" + }, + "other_gender_swap": {}, + "en_pronoun2gender": { + "he": [ + "hann" + ], + "she": [ + "kvinna" + ] + }, + "en_pronoun2pronoun": { + "he": [ + "hann" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/nov.json b/data_tooling/pii_processing/ontology/data/nov.json new file mode 100644 index 0000000..765a20e --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/nov.json @@ -0,0 +1,95 @@ +{ + "LANGUAGE": [ + "katalana", + "venda", + "spani", + "katalane", + "katalano", + "fransum", + "esperanto" + ], + "DISEASE": [ + "pasione", + "mause", + "le" + ], + "ORG": [ + "fema", + "porte", + "un", + "po" + ], + "JOB": [ + "amindi", + "sub" + ], + "GENDER": [ + "puera", + "men" + ], + "PUBLIC_FIGURE": [ + "e", + "o", + "putin" + ], + "RELIGION_MEMBER": [ + "fratro" + ], + "QUANTITY": [ + "kalorie", + "sinksent" + ], + "DATE": [ + "mihore" + ], + "PERSON_PRONOUN": [ + "me" + ], + "ANIMAL": [ + "herone" + ], + "LOCATION": [ + "sri_lanka" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "abata": "abato", + "nun": "monako", + "fratra": "fratro", + "yuno": "puera", + "puero": "yuna" + }, + "other_gender_swap": {}, + "en_pronoun2gender": { + "he": [ + "yuno", + "puero" + ], + "she": [ + "yuna", + "femal", + "fema", + "puera" + ] + }, + "en_pronoun2pronoun": { + "she": [ + "de_la" + ], + "it": [ + "lum", + "disi" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/nrf.json b/data_tooling/pii_processing/ontology/data/nrf.json new file mode 100644 index 0000000..fbf76bd --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/nrf.json @@ -0,0 +1,240 @@ +{ + "PLANT": [ + "reunellyi", + "grand_suthelle", + "coquelicot", + "lianne", + "ch\u00e8rfi", + "preunelle", + "preune", + "betterave", + "moutarde", + "tchoeuryi", + "bantchie", + "caboche", + "fossa\u00ef", + "tourn\u00e9sol", + "meuthe_en_c'm\u00een", + "tch\u00e8rpentchi\u00e9the", + "tchoeur", + "magnolia" + ], + "ANIMAL": [ + "martre", + "cat", + "alicracq", + "cahouain", + "maoue", + "con_d'rotchi", + "mille_pids", + "duc", + "caqu'ter", + "gra\u00efve", + "brotchet", + "mataud", + "cardrinnette", + "pourpais" + ], + "DISEASE": [ + "addiction", + "rage", + "stchinnancie", + "bliesse\u00fbthe", + "m\u00e9lie", + "turb\u00e9", + "conseunmtion", + "boursoufliuthe", + "courte_haleine", + "traler", + "constip\u00e2tion", + "plieur\u00easie", + "chancre", + "roui", + "crache", + "pain", + "meurdri", + "pliainte", + "roussi", + "br\u00fbleuse", + "bouaissonn'nie", + "coqueluche" + ], + "LANGUAGE": [ + "gudgiarati", + "angliais", + "souahili", + "bastchais", + "angllais", + "tonga" + ], + "LAW": [ + "parchonn'nie_civile", + "protchul\u00e2tion" + ], + "JOB": [ + "volontaithe", + "seurgien", + "tchilieux", + "soudard", + "corpotha", + "acateux", + "coutchi", + "bantchi", + "tch\u00e9thtchi", + "chent'nyi", + "annonceux", + "barbyi", + "gardgienne", + "tchu\u00eesinnyi", + "boulandgi", + "fonctionnaithe", + "seller", + "ramonneux", + "monnyi", + "travailleux", + "faithe", + "g\u00e9rant", + "diplomate", + "fanmilyi", + "fraudeux", + "maitr\u00easse", + "laver\u00easse", + "coronel", + "arpenteux", + "nettisseux", + "canonnyi", + "portchi", + "charron", + "douannyi", + "d'sabil'r\u00easse", + "monniteu", + "halaeux", + "lanminneux" + ], + "PUBLIC_FIGURE": [ + "piteur", + "monnyi", + "charles", + "thonmas", + "t\u00e9l\u00e9c'mande", + "ramonneux", + "suicider", + "ra\u00eet\u00e9", + "l" + ], + "FOOD": [ + "mousse", + "desert", + "denchive", + "chile" + ], + "RELIGION_MEMBER": [ + "wesleyen", + "chap'lain", + "nazar\u00e9tchien" + ], + "ORG": [ + "porte", + "v\u00e8rt_cap", + "transport\u00e2tion", + "longue_pi\u00e8rre", + "machon'nie", + "rouoge_m\u00e9", + "marinne", + "\u00eatats_unnis", + "bataillon", + "gouv\u00e8rn\u00e9ment", + "pays_bastchais" + ], + "DATE": [ + "toussaint" + ], + "PRODUCT": [ + "drouaits_d'l'houmme", + "papa_nou\u00e9", + "couochon_d'la_dginn\u00e9e", + "tchu_d'sa", + "distchette", + "arbre_d'nou\u00e9", + "vailyi" + ], + "SOC_ECO_CLASS": [ + "agritchulteure", + "agritchultuthe", + "soci\u00eat\u00e9" + ], + "GENDER": [ + "hardelle", + "matronne" + ], + "LOCATION": [ + "australie_m\u00e9ridionale", + "ieau_douoche", + "australie_occidentale", + "sri_lanka" + ], + "POLITICAL_PARTY_MEMBER": [ + "canmathade", + "commeuniste" + ], + "PERSON": [ + "jean_dor\u00e9" + ], + "FAC": [ + "sainte_lucie" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "abb\u00easse": "abb\u00e9", + "b\u00e2ronne": "b\u00e2ron", + "duch\u00easse": "duc", + "hardelle": "bouonhoumme", + "p'tite_fil'ye": "p'tit_fis", + "maitr\u00easse": "sp\u00e9cialiste", + "pr\u00eenc\u00easse": "pr\u00eence", + "soeu": "broder", + "faume": "bouonhoumme", + "bou\u00f4nnefemme": "bouonhoumme" + }, + "other_gender_swap": {}, + "en_pronoun2gender": { + "they": [ + "homosexuel", + "bisexuel" + ], + "he": [ + "coll\u00e8gue", + "bouonhoumme" + ], + "she": [ + "f\u00e2me", + "homosexuel", + "faume", + "bike", + "mantchi", + "lesbien", + "foume", + "hardelle", + "fenme" + ] + }, + "en_pronoun2pronoun": { + "he": [ + "seine" + ], + "it": [ + "dette" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/nv.json b/data_tooling/pii_processing/ontology/data/nv.json new file mode 100644 index 0000000..d50a5b0 --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/nv.json @@ -0,0 +1,179 @@ +{ + "ANIMAL": [ + "t\u00f3_w\u00f3naan\u00edd\u0119\u0301\u0119\u0301\u02bc_l\u00f3k\u02bcaatah_noo\u0142nahii", + "choozhghalii", + "b\u00edlaneezii", + "nahashch\u02bcid\u00ed", + "naaldeehii", + "binii\u02bc\u0142igaii", + "ch\u0105\u0105nei\u0142maasii", + "na\u02bcashj\u00e9\u02bciitsoh", + "b\u012f\u012fh", + "t\u00e1shchozhii\u0142ch\u00ed\u00ed\u02bc", + "deeteel", + "jeesh\u00f3\u00f3\u02bc", + "shashtsoh", + "ch\u02bca\u0142", + "\u0142\u00e9\u02bc\u00e9tsoh_beeni\u02bc\u00edhoniitaah\u00edg\u00ed\u00ed", + "godit\u00e1n\u00ed", + "tsintasd\u00eds\u00ed", + "na\u02bcashj\u00e9\u02bcii_di\u0142hi\u0142\u00ed", + "ch\u02bciltaat\u02bcagii" + ], + "PRODUCT": [ + "n\u00ed\u0142ch\u02bci_diyinii", + "k\u00e9shmish_hastiin", + "nahoogaii", + "s\u00e3o_tom\u00e9_d\u00f3\u00f3_pr\u00edncipe" + ], + "TITLE": [ + "hastiin" + ], + "JOB": [ + "azee\u02bc\u00ed\u00ed\u0142\u02bc\u00edn\u00ed", + "don", + "naabaahii", + "yool\u00e9\u00e9\u0142", + "naa\u02bcnil", + "agha\u02bcdiit\u02bcaahii", + "naat\u02bc\u00e1anii", + "yishb\u00e9\u00e9zh", + "binant\u02bca\u02bc\u00ed", + "nanit\u02bc\u00e1ii", + "naalt\u00e9" + ], + "ORG": [ + "w.b.a", + "kin\u00e1h\u00e1lgaa\u00ed", + 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"SUFIX_FEMALE": [], + "binary_gender_swap": { + "t\u02bc\u00e1\u00e1_h\u00f3": "t\u02bc\u00e1\u00e1_b\u00ed", + "t\u02bc\u00e1\u00e1_b\u00ed": "t\u02bc\u00e1\u00e1_h\u00f3", + "adeezh\u00ed": "atsil\u00ed", + "h\u00e1d\u00ed": "atsil\u00ed", + "hatsi\u02bc_\u00e1j\u00ed\u0142\u02bc\u00edn\u00ed": "haye\u02bc_\u00e1j\u00ed\u0142\u02bc\u00edn\u00ed", + "hatsi\u02bc_j\u00ed\u0142\u02bc\u00edn\u00ed": "haye\u02bc_\u00e1j\u00ed\u0142\u02bc\u00edn\u00ed", + "hach\u02bc\u00e9\u02bc\u00e9_j\u00ed\u0142\u02bc\u00edn\u00ed": "haye\u02bc_\u00e1j\u00ed\u0142\u02bc\u00edn\u00ed", + "hach\u02bc\u00e9\u02bc\u00e9_\u00e1j\u00ed\u0142\u02bc\u00edn\u00ed": "haye\u02bc_\u00e1j\u00ed\u0142\u02bc\u00edn\u00ed", + "ham\u00e1_j\u00ed\u0142\u02bc\u00edn\u00ed": "hazh\u00e9\u02bc\u00e9_\u00e1j\u00ed\u0142\u02bc\u00edn\u00ed", + "ham\u00e1_\u00e1j\u00ed\u0142\u02bc\u00edn\u00ed": "hazh\u00e9\u02bc\u00e9_\u00e1j\u00ed\u0142\u02bc\u00edn\u00ed", + "hwe\u02bcesdz\u00e1\u00e1n": "hahastiin", + "asdz\u00e1\u00e1n": "din\u00e9", + "ayol": "din\u00e9", + "asdz\u0105\u0301\u0105\u0301": "din\u00e9", + "ashkii": "at\u02bc\u00e9\u00e9d" + }, + "other_gender_swap": {}, + "en_pronoun2gender": { + "he": [ + "ashkii", + "din\u00e9", + "din\u00e9\u00e9h" + ], + "she": [ + "at\u02bc\u00e9\u00e9d", + "ayol", + "asdz\u00e1\u00e1n", + "asdz\u0105\u0301\u0105\u0301", + "ch\u02bcik\u0119\u0301\u0119\u0301h" + ] + }, + "en_pronoun2pronoun": { + "he": [ + "t\u02bc\u00e1\u00e1_b\u00ed", + "t\u02bc\u00e1\u00e1_h\u00f3", + "his" + ], + "she": [ + "t\u02bc\u00e1\u00e1_h\u00f3", + "t\u02bc\u00e1\u00e1_b\u00ed" + ], + "it": [ + "d\u00ed\u00ed", + "\u00e9\u00ed", + "t\u02bc\u00e1\u00e1_b\u00ed" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/oc.json b/data_tooling/pii_processing/ontology/data/oc.json new file mode 100644 index 0000000..2c741a8 --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/oc.json @@ -0,0 +1,861 @@ +{ + "LOCATION": [ + "assemblada_nacionala", + "al_jazeera", + "plantago_lanceolata", + "mar_tirr\u00e8na", + "mar_del_n\u00f2rd", + "jardin_botanic", + "piet_mondrian", + "mar_n\u00eara", + "sint_maarten", + "an_n\u00f2u", + "mar_negra", + "gara_ferrovi\u00e0ria", + "aiga_do\u00e7a", + "pic_negre", + "austr\u00e0lia_occidentala", + "sus_la_rota", + "plantago_major", + "mont_carm\u00e8l", + "mar_de_china_orientala", + "las_salas", + "arena", + "sri_lanka", + "bernat_pescaire", + "the_rolling_stones", + "mar_jauna", + "bonser", + "sax\u00f2nia_anhalt", + "osman_i\u00e8r", + "heitor_villa_lobos", + "sit_arqueologic" + ], + "PUBLIC_FIGURE": [ + "vlad\u00edmir_nab\u00f2kov", + "benjamin_franklin", + "akira_kurosawa", + "jean_genet", + "john_knox", + "giovanni_boccaccio", + "che_guevara", + "georges_simenon", + "c", + "augustin_fresnel", + "dorothy_parker", + "maria_callas", + "henrik_ibsen", + "nicolau_copernic", + "marcello_malpighi", + "david_livingstone", + "eduard_buchner", + "john_herschel", + "richard_burton", + "maria_magdalena", + "winston_churchill", + "johannes_diderik_van_der_waals", + "karl_landsteiner", + "sorditge", + "ivan_pavlov", + "paul_mccartney", + "terry_pratchett", + "sant_lauren\u00e7", + "stephen_king", + "francis_crick", + "sant_martin", + "isaac_newton", + "victor_hugo", + "edwin_hubble", + "milton_friedman", + "saint_louis", + "john_glenn", + "george_harrison", + "george_orwell", + "richard_wagner", + "marie_curie", + "michael_jackson", + "thomas_hobbes", + "el_greco", + "samuel_beckett", + "galileo_galilei", + "chaim_weizmann", + "robert_koch", + "john_steinbeck", + "edmund_hillary", + "vincent_van_gogh", + "anne_boleyn", + "robert_burns", + "bari", + "mary_pickford", + "hans_fischer", + "emiliano_zapata", + "karl_barth", + "willem_einthoven", + "anne_hutchinson", + "louise_nevelson", + "giuseppe_verdi", + "e", + "karl_jaspers", + "hideki_yukawa", + "konrad_adenauer", + "maurice_chevalier", + "frank_sinatra", + "abel_tasman", + "katharine_hepburn", + "henri_becquerel", + "henri_matisse", + "louis_pasteur", + "richard_strauss", + "mahalia_jackson", + "gertrude_stein", + "saladin", + "sarah_bernhardt", + "trotski", + "luigi_pirandello", + "t_s_eliot", + "charles_de_gaulle", + "paul_von_hindenburg", + "y", + "charles_lindbergh", + "f", + "ludwig_wittgenstein", + "august_strindberg", + "thomas_mann", + "dante_alighieri", + "arnau", + "peter_pan", + "james_tobin", + "samuel_de_champlain", + "giacomo_puccini", + "fridtjof_nansen", + "louis_braille", + "herbert_marcuse", + "paul_verlaine", + "james_dean", + "alessandro_manzoni", + "andrea_mantegna", + "jim_corbett", + "oscar_wilde", + "philip_roth", + "laurence_olivier", + "christiaan_eijkman", + "francis_bacon", + "pete_seeger", + "a", + "peter_brian_medawar", + "james_brown", + "charles_baudelaire", + "luigi_cherubini", + "charlie_parker", + "immanuel_kant", + "james_franck", + "james_meredith", + "warburg", + "giulio_natta", + "titus", + "johannes_kepler", + "william_s_burroughs", + "max_planck", + "john_bardeen", + "sarah_vaughan", + "william_byrd", + "scott_joplin", + "george_vancouver", + "canberra", + "bramante", + "elias_canetti", + "edward_jenner", + "oscar_robertson", + "cole_porter", + "graham_greene", + "tawantinsuyu", + "lars_onsager", + "margaret_mitchell", + "vlad\u00edmir_p\u00f3tin", + "william_herschel", + "montesquieu", + "niels_bohr", + "tom\u00e0s", + "bertrand_russell", + "michael_faraday", + "sergei_rakhmaninov", + "anthony_burgess", + "jan_tinbergen", + "rudolf_diesel", + "walt_disney", + "joseph_schumpeter", + "gabriel_lippmann", + "launart", + "benny_goodman", + "friedrich_engels", + "jane_austen", + "gustav_mahler", + "ed_sullivan", + "phil_collins", + "robert_redford", + "breissa", + "ian_fleming", + "richard_feynman", + "andrew_huxley", + "marcel_proust", + "thomas_more", + "homo_heidelbergensis", + "elizabeth_taylor", + "john_dowland", + "daniel_jones", + "william_golding", + "p\u00e8ire_i_de_russia", + "indira_gandhi", + "george_gershwin", + "alfred_nobel", + "marco_polo", + "caravaggio", + "charlotte_corday", + "allen_ginsberg", + "henri_bergson", + "boris_karloff", + "gottfried_leibniz", + "pierre_corneille", + "patrick_white", + "daniel_morgan", + "hans_christian_andersen", + "cary_grant", + "pieter_zeeman", + "arnold_gesell", + "glenn_miller", + "pablo_picasso", + "natalie_wood", + "kurt_weill", + "otto_hahn", + "christiaan_huygens", + "hector_berlioz", + "lucille_ball", + "paul_simon", + "claudio_monteverdi", + "john_galsworthy", + "robert_robinson", + "adam_smith", + "karl_marx", + "paul_bunyan", + "friedrich_nietzsche", + "i", + "sandro_botticelli", + "nikola_tesla", + "al_capone", + "robert_schumann", + "mel_gibson", + "le_corbusier", + "carlo_goldoni", + "john_locke", + "alexis_carrel", + "helen_keller", + "ingrid_bergman", + "paul_tillich", + "valentina_tereshkova", + "walt_whitman", + "ludwig_boltzmann", + "adolf_hitler", + "james_d_watson", + "fritz_haber", + "joseph_haydn", + "george_boole", + "edvard_grieg", + "mikha\u00efl_gorbachov", + "cordell_hull", + "tomas", + "giuseppe_mazzini", + "jacqueline_cochran", + "fritz_kreisler", + "anne_hathaway", + "g", + "arthur_schopenhauer", + "martin_heidegger", + "r", + "george_lucas", + "andrew_jackson", + "louis_armstrong", + "steven_spielberg", + "sant_p\u00e8ir", + "robert_fulton", + "alexandre_dumas", + "bobby_fischer", + "johannes_gutenberg", + "thomas_malthus", + "william_faulkner", + "amerigo_vespucci", + "hans_adolf_krebs", + "girolamo_savonarola", + "putin", + "jean_de_la_fontaine", + "robert_hooke", + "karl_popper", + "nikita_khrushchov", + "george_sand", + "peter_sellers", + "homo_rhodesiensis", + "charles_fourier", + "peter_o'toole", + "joseph_conrad", + "edmund_halley", + "william_shockley", + "peter_paul_rubens", + "jim_morrison", + "jules_verne", + "paul_newman", + "jackson_pollock", + "john_lennon", + "andrea_palladio", + "charlie_chaplin", + "d_h_lawrence", + "j_m_barrie", + "asa_gray", + "antonio_stradivari", + "miles_davis", + "george_marshall", + "don_quich\u00f2te", + "bozen", + "stanley_kubrick", + "rudolph_bultmann", + "liunard", + "james_watt", + "ronald_reagan", + "helmut_schmidt", + "homo", + "david_hilbert", + "wilhelm_reich", + "oliver_cromwell", + "lionel_hampton", + "martin_luther_king", + "woodrow_wilson", + "gustav_hertz", + "lo_capaironet_roge", + "borges", + "crist\u00f2l_colomb", + "jim_henson", + "ernest_hemingway", + "aquila", + "arthur_miller", + "nelson_mandela", + "al_gore", + "roald_amundsen", + "charles_dickens", + "ella_fitzgerald", + "george_enescu", + "jacques_offenbach", + "federico_fellini", + "bessie_smith", + "willy_brandt", + "francisco_franco", + "andrew_carnegie", + "franz_schubert", + "johnny_cash", + "joseph_mccarthy", + "alfred_kastler", + "sant_j\u00f2rdi", + "mick_jagger", + "otto_loewi", + "georges_cuvier", + "john_bunyan", + "jonathan_swift", + "albert_einstein", + "l", + "chiang_kai_shek", + "henry_purcell", + "t", + "wilhelm_ostwald" + ], + "DISEASE": [ + "escarraunhadura", + "abrasion", + "chuc", + "raum\u00e0s", + "ernia", + "mordedura", + "escorgadura", + "malauti\u00e1", + "liqu\u00e8n", + "ratuga", + "esternut", + "sarrampiu", + "pecol", + "esternudar", + "prodr\u00f2me", + "cremadura", + "mossegar", + "letz", + "rovilh", + "poliomieliti", + "rodam", + "ivernacion", + "gimp", + "paludisme", + "carral", + "espasme", + "pedoncul", + "virus_ebola", + "addiccion", + "accident_vascular_cerebral", + "fureta", + "rube\u00f2la", + "pellagra", + "virus_d_epstein_barr", + "sting", + "diab\u00e8ta_sacarina", + "senepiu", + "rodal", + "materialisme", + "dengue", + "castanha", + "salmonella" + ], + "POLITICAL_PARTY": [ + "gironda", + "partit_comunista", + "partit_popular", + "partit_socialista" + ], + "PLANT": [ + "assale\u00e7", + "poncidara", + "magn\u00f2lia", + "actinidia_sinensis", + "pastenaga", + "melissa", + "castanhi\u00e8r", + "vedissa", + "solanaceae", + "tartifla", + "ortiga", + "escapula", + "caprifu\u00e8lh", + "campion", + "mille_feuille", + "peri\u00e8r", + "leucaena_leucocephala", + "amaron", + "mauv\u00eds", + "virasolelh", + "papaver_somniferum", + "manioc", + "valerianella_locusta", + "falabreguier", + "plantago_lanceolata", + "manh\u00f2lia", + "lill\u00e0", + "tracheobionta", + "abelhana", + "urtica", + "amanita_muscaria", + "past\u00e8l", + "vidable", + "sorbin", + "tartifle", + "cabrifu\u00e8lh", + "milafu\u00e8lhas", + "serbi\u00e8r", + "indig\u00f2t", + "lauri\u00e8r", + "solanum", + "asperbi\u00e8r", + "albricoti\u00e8r", + "fagus_sylvatica", + "carrobi\u00e8r", + "sabina", + "boletus_edulis", + "phytolacca_dioica", + "albar", + "pernamboc", + "aubi\u00e8ca", + "laituga", + "groselhi\u00e8r", + "plat\u00e8la", + "carr\u00f2ta", + "lachuga", + "nogui\u00e8r", + "castanha", + "castanea", + "sambucus_ebulus", + "corniol" + ], + "ANIMAL": [ + "apodemus", + "cat", + "moisset", + "randal", + "sapo", + "granh\u00f2ta", + "pintarda", + "esquir\u00f2l", + "blaveta", + "manhan", + "most\u00e8la", + "manta", + "missara", + "condar", + "lebreta", + "singlar", + "cabir\u00f2l", + "cabr\u00f2l", + "polida", + "dugan\u00e8l", + "cobai", + "ferret", + "duc", + "granolha", + "cr\u00f2s_manhon", + "greule", + "pollamb\u00e8rt", + "homo_sapiens", + "lebri\u00e8r", + "ramonaire", + "brotonica", + "pic_verd", + "rami\u00e8r", + "accipiter", + "falcon", + "vernh\u00f2la", + "duganel\u00e0s", + "donald_duck", + "voltor", + "milapatas", + "nadu\u00e8lh", + "ammospermophilus", + "sable", + "capreolus_capreolus", + "arthropoda", + "boquetin", + "peisses", + "zeus_faber", + "tortora", + "\u00f2me_de_cr\u00f2smanhon", + "eider", + "arvicola" + ], + "ORG": [ + "luna_nov\u00e8la", + "san_jos\u00e9", + "jan_mayen", + "sublima_p\u00f2rta", + "justesa", + "the_who", + "san_francisco", + "un", + "m_ap\u00e8li", + "va", + "francma\u00e7oneria", + "edat_d_aur", + "gironda", + "ai", + "me_soni", + "drech_civil", + "cr\u00f2smanhon", + "cap_verd", + "autoritat_palestiniana", + "emp\u00e8ri_alemand", + "granda_orsa", + "rabindranath_tagore", + "gestapo", + "partit_republican", + "partit_democrata", + "partit_politic", + "me_dison", + "monarquia_constitucionala", + "ostal_blanc", + "the_young_turks", + "fluvi_jaune", + "al_jazeera", + "los_rasins_de_la_col\u00e8ra", + "ja\u00efnisme", + "lac_superior", + "mar_roja", + "los_angeles", + "bascoat", + "mont_dels_olius", + "alemand", + "estats_units_d_america", + "gl\u00e8isa_catolica", + "cardin", + "t\u00e8rra_cremada", + "elementari", + "s\u00e3o_tom\u00e9", + "tao\u00efsme" + ], + "SOC_ECO_CLASS": [ + "samorai" + ], + "JOB": [ + "tetar", + "jardini\u00e8r", + "vaqui\u00e8r", + "potter", + "quimista", + "curator", + "lachi\u00e8r", + "don", + "facultatiu", + "lauraire", + "the_police", + "compositor", + "char", + "mastermind", + "urinar", + "inventor", + "coron\u00e8u", + "garri", + "academician", + "escobar", + "laurador", + "fantassin", + "crompaire", + "legeire", + "avesque", + "the_guardian", + "oelhi\u00e8r", + "sentin\u00e8la", + "president", + "mandarin", + "cabri\u00e8r", + "mate", + "pastor", + "gaucho", + "legeira", + "rabin", + "pastre", + "associat", + "barbier", + "wetter", + "vaisseladoira", + "ma\u00e7on", + "tunar", + "messatgi\u00e8r", + "colleccionaire", + "man", + "regent", + "messenger", + "proconsul", + "bombardier", + "cartonista", + "crompaira", + "lampista", + "the_independent", + "solicitor", + "cookie", + "dessenhaire", + "autor", + "cortesan" + ], + "PRODUCT": [ + "justin_bieber", + "las_quate_sasons", + "al_jazeera", + "cobai", + "analisi_matematica", + "la_modificacion", + "cortcircuit", + "the_star_spangled_banner", + "lagremas_de_j\u00f2b", + "arbre_de_nadal", + "cap_h\u00f2rn", + "la_dolce_vita", + "arc_de_trionf", + "lo_canh\u00e0s_dels_baskervilles", + "dreches_de_l_\u00f2me", + "sent_esperit", + "lo_senhor_dels_an\u00e8ls", + "novo_mesto" + ], + "LANGUAGE": [ + "catalan", + "t\u00f2nga", + "bambara", + "catalana", + "pali", + "malayalam", + "basc", + "tailand\u00e9s", + "esperanto", + "lingala", + "cree", + "ido" + ], + "RELIGION": [ + "zen", + "donatisme", + "manique\u00efsme", + "calvinisme", + "islam", + "catarisme" + ], + "PERSON": [ + "al_gore", + "igor_sikorsky", + "carl_david_anderson", + "boletus_edulis" + ], + "QUANTITY": [ + "franc_franc\u00e9s", + "ton", + "g", + "rial", + "peri\u00f2de_dei_tres_reiaumes", + "anders_celsius" + ], + "FAC": [ + "pauc_a_pauc", + "elementari", + "gl\u00e8isa_catolica_romana", + "la_montanha_magica", + "santa_l\u00facia", + "las_quate_sasons", + "compost\u00e8la" + ], + "GPE": [ + "dar_es_salaam", + "champanha_ardena", + "sint_maarten", + "mar_eg\u00e8a", + "hagia_sophia", + "s\u00e3o_tom\u00e9", + "sant_lauren\u00e7", + "al_andal\u00fas", + "grand_can\u00e0ria", + "sri_jayawardenepura", + "vinh_long", + "la_gomera", + "sant_esperit", + "mar_roja" + ], + "FOOD": [ + "niva", + "sauce", + "farina", + "tapera", + "goma_de_mastolhar", + "chile", + "dess\u00e8rt", + "pudding", + "pastissari\u00e1", + "limonada", + "pastra", + "pot_au_feu", + "juglans_regia" + ], + "PERSON_PRONOUN": [ + "i", + "seuna", + "nosautres", + "her", + "el_meu" + ], + "RACE": [ + "latin", + "african", + "american" + ], + "DATE": [ + "toussaint", + "the_night_watch", + "vielhesa" + ], + "RELIGION_MEMBER": [ + "josieu", + "vaishnava", + "mon", + "crestian" + ], + "GENDER": [ + "joventa", + "filheta", + "donz\u00e8la", + "man", + "gal" + ], + "LAW": [ + "drech_roman", + "federal_bureau_of_investigation" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "abadessa": "abba", + "feminin": "masculin", + "her": "seuna", + "matrix": "pap\u00e0", + "neboda": "nebot", + "monja": "monge", + "monaca": "monge", + "moja": "monge", + "infanta": "prens", + "princessa": "regulus", + "r\u00e8n": "indra", + "s\u00f2r": "fraire", + "s\u00f2rre": "fraire", + "abla": "fraire", + "veusa": "veuse", + "esposa": "marit", + "femena": "\u00f2me", + "duna": "cristian", + "femna": "\u00f2me", + "d\u00f2na": "man", + "fem\u00e8la": "\u00f2me", + "frut": "gojata", + "metgessa": "fisician", + "facultatiu": "metgessa", + "doctor": "metgessa", + "m\u00e8tge": "metgessa", + "fisician": "metgessa" + }, + "other_gender_swap": { + "\u3078": "epi" + }, + "en_pronoun2gender": { + "he": [ + "masculin", + "frut", + "\u00f2me", + "man" + ], + "she": [ + "femna", + "gojata", + "donz\u00e8la", + "filheta", + "femena", + "fem\u00e8la", + "feminin", + "abla", + "drolleta", + "dr\u00f2lla", + "domais\u00e8la", + "d\u00f2na", + "gal" + ] + }, + "en_pronoun2pronoun": { + "he": [ + "\u3078", + "seuna" + ], + "she": [ + "seuna", + "her" + ], + "they": [ + "epi" + ], + "it": [ + "aquest", + "lum" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/oge.json b/data_tooling/pii_processing/ontology/data/oge.json new file mode 100644 index 0000000..ed46e0b --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/oge.json @@ -0,0 +1,24 @@ +{ + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": {}, + "other_gender_swap": {}, + "en_pronoun2gender": { + "she": [ + "\u10e5\u10d0\u10da\u10d8", + "\u10d3\u10d8\u10d0\u10ea\u10d8", + "\u10d3\u10d4\u10d3\u10d0\u10d9\u10d0\u10ea\u10d8" + ] + }, + "en_pronoun2pronoun": {}, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/oj.json b/data_tooling/pii_processing/ontology/data/oj.json new file mode 100644 index 0000000..7bc7c81 --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/oj.json @@ -0,0 +1,92 @@ +{ + "RELIGION_MEMBER": [ + "nisayenh" + ], + "DATE": [ + "bekaa" + ], + "ANIMAL": [ + "bizhiw", + "moonz", + "agongos", + "namegos", + "jachakanoo", + "omakakii", + "gayaashk", + "namegoshens", + "ajidamoo" + ], + "JOB": [ + "ogimaa", + "ganoodiye", + "gaashpinajiged" + ], + "QUANTITY": [ + "naanwaak", + "midaasosagoons" + ], + "PLANT": [ + "aninaatig", + "askiibwaan", + "mitigomizh", + "moosewijiibik" + ], + "ORG": [ + "ingodwaaswaak", + "giigidoowininiwag", + "indizhinikaaz", + "anishinaabeg_gichigami" + ], + "PUBLIC_FIGURE": [ + "o" + ], + "PERSON": [ + "ge_niin" + ], + "PERSON_PRONOUN": [ + "niinawind" + ], + "LOCATION": [ + "debizi", + "chi_miigwech" + ], + "FOOD": [ + "miskwaaboo" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "nishiime": "nisayenh", + "nimisenh": "nisayenh" + }, + "other_gender_swap": { + "wiinawaa": "wiin", + "wiin": "wiinawaa" + }, + "en_pronoun2gender": { + "she": [ + "ikwe" + ] + }, + "en_pronoun2pronoun": { + "he": [ + "wiin" + ], + "she": [ + "wiin" + ], + "they": [ + "wiinawaa" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/or.json b/data_tooling/pii_processing/ontology/data/or.json new file mode 100644 index 0000000..949f4e5 --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/or.json @@ -0,0 +1,1904 @@ +{ + "ORG": [ + "\u0b15\u0b43\u0b37\u0b3f", + "\u0b36\u0b3f\u0b15\u0b4d\u0b37\u0b3e" + ], + "GPE": [ + "\u0b2e\u0b3e\u0b28\u0b2c\u0b3f\u0b15_\u0b05\u0b27\u0b3f\u0b15\u0b3e\u0b30" + ], + "ner_regexes": [ + [ + "PERSON", + "\\D+ \\D+|\\D+ \\D+|\\D+ \\D+ \\D+|\\D+ \\D+ \\D+|\\D+ \\D+|\\D+ \\D+ \\D+|\\D+ \\D+ \\D+|\\D+ \\D+ \\D+", + false, + [] + ] + ], + "FIRST_NAME_FEMALE": [ + "\u0b2c\u0b3f\u0b28\u0b4b\u0b26\u0b3f\u0b28\u0b40", + "\u0b36\u0b3f\u0b2c\u0b3e\u0b28\u0b40", + "\u0b05\u0b28\u0b41\u0b2a\u0b4d\u0b30\u0b3f\u0b5f\u0b3e", + "\u0b32\u0b47\u0b16\u0b3e", + "\u0b17\u0b3e\u0b30\u0b4d\u0b17\u0b40", + "\u0b30\u0b3f\u0b28\u0b3e", + "\u0b38\u0b4d\u0b28\u0b3f\u0b17\u0b4d\u0b27\u0b3e", + "\u0b2f\u0b36\u0b4b\u0b26\u0b3e", + "\u0b2e\u0b3f\u0b28\u0b24\u0b3f", + "\u0b1c\u0b5f\u0b28\u0b4d\u0b24\u0b40", + "\u0b36\u0b41\u0b2d\u0b36\u0b4d\u0b30\u0b40", + "\u0b1b\u0b2c\u0b3f", + "\u0b2a\u0b4d\u0b30\u0b2e\u0b3f\u0b33\u0b3e", + "\u0b24\u0b28\u0b4d\u0b26\u0b4d\u0b30\u0b3e", + "\u0b2a\u0b3e\u0b30\u0b4d\u0b2c\u0b24\u0b40", + "\u0b2a\u0b41\u0b2a\u0b41\u0b32", + "\u0b2d\u0b17\u0b2c\u0b24\u0b40", + "\u0b2e\u0b19\u0b4d\u0b17\u0b33\u0b3e", + "\u0b38\u0b40\u0b2e\u0b3e\u0b30\u0b3e\u0b23\u0b40", + "\u0b05\u0b2e\u0b3f\u0b24\u0b3e", + "\u0b38\u0b41\u0b1a\u0b3f\u0b24\u0b4d\u0b30\u0b3e", + 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"bernard_malamud", + "samuel_johnson", + "allen_iverson", + "anne_hutchinson", + "giuseppe_verdi", + "aleksandr_prochorow", + "walter_lippmann", + "e", + "karl_jaspers", + "beethoven", + "hideki_yukawa", + "konrad_adenauer", + "baletmistrzyni", + "antoni", + "marianne_moore", + "norbert_wiener", + "mark_rothko", + "maurice_chevalier", + "antoniusz", + "gottlieb_daimler", + "frank_sinatra", + "abel_tasman", + "katharine_hepburn", + "henri_becquerel", + "henri_matisse", + "bertram_brockhouse", + "louis_pasteur", + "j", + "richard_strauss", + "stephen_decatur", + "leslie_howard", + "jean_baptiste_racine", + "mahalia_jackson", + "john_ford", + "alphonse_bertillon", + "katherine_mansfield", + "gertrude_stein", + "sarah_bernhardt", + "konstantyn", + "v", + "philip_marlowe", + "luigi_pirandello", + "marc_blitzstein", + "hank_williams", + "robert_millikan", + "rube_goldberg", + "dorothea_lange", + "james_thurber", + "charles_de_gaulle", + "paul_von_hindenburg", + "y", + "henry_moore", + "holden", + "mary_mallon", + "ralph_bunche", + "rudolf_bultmann", + "charles_lindbergh", + "vincenzo_bellini", + "samuel_barber", + "tobias_smollett", + "f", + "john_jay", + "ludwig_wittgenstein", + "august_strindberg", + "stalin", + "thomas_mann", + "komiwoja\u017cer", + "william_ockham", + "alla_nazimova", + "charles_goodyear", + "dante_alighieri", + "margot_fonteyn", + "james_tobin", + "john_irving", + "samuel_de_champlain", + "giacomo_puccini", + "fridtjof_nansen", + "louis_braille", + "herbert_marcuse", + "mungo_park", + "benedict_arnold", + "paul_verlaine", + "q", + "scribes", + "maksymian", + "henryk", + "robert_johnson", + "james_dean", + "robert", + "mason", + "marie_tussaud", + "mezzosopran", + "roger_bannister", + "theodor_schwann", + "max_beerbohm", + "james_cattell", + "alessandro_manzoni", + "joseph_priestley", + "nicolas_poussin", + "andrea_mantegna", + "joseph_pulitzer", + "george_huntington", + "charles_schulz", + "jim_corbett", + "james_naismith", + "oscar_wilde", + "ba\u0142agu\u0142a", + "jane_marple", + "le\u015bnik", + "philip_roth", + "j_d_salinger", + "marszand", + "lawrence", + "kuria", + "richard_trevithick", + "william_bradford", + "heinrich_schliemann", + "eli_whitney", + "laurence_olivier", + "pierre_larousse", + "christiaan_eijkman", + "george_kennan", + "adolf_eichmann", + "majoretka", + "marilyn_horne", + "francis_bacon", + "pete_seeger", + "john_wycliffe", + "joseph_heller", + "a", + "laurenty", + "morris", + "m\u0142ynarska", + "norman_rockwell", + "nowak", + "james_brown", + "william_hogarth", + "charles_baudelaire", + "luigi_cherubini", + "david_ricardo", + "henri_labrouste", + "mary_leakey", + "charlie_parker", + "z", + "immanuel_kant", + "richard_gatling", + "james_franck", + "william_crookes", + "samuel_gompers", + "nellie_bly", + "weber", + "warburg", + "alexandre_yersin", + "n", + "stephen_leacock", + "albert_schweitzer", + "georg_steller", + "john_harvard", + "johann_friedrich_herbart", + "giulio_natta", + "johannes_kepler", + "william_s_burroughs", + "most", + "david_hartley", + "max_planck", + "william_blake", + "julio_iglesias", + "john_bardeen", + "sarah_vaughan", + "john_wilkes", + "william_byrd", + "william_henry", + "christopher_fry", + "scott_joplin", + "carl_lewis", + "george_vancouver", + "canberra", + "elias_canetti", + "robert_lowell", + "edward_jenner", + "oscar_robertson", + "piotr_aposto\u0142", + "oliver_hardy", + "ko\u015bciuszko", + "cole_porter", + "benjamin_west", + "jean_luc_godard", + "karol_marks", + "graham_greene", + "frans_hals", + "edward", + "lars_onsager", + "margaret_mitchell", + "m\u0142ynarz", + "lola_montez", + "jan_swammerdam", + "mary_mccarthy", + "david_riesman", + "john_walker", + "lapunder", + "william_herschel", + "joseph_black", + "karmelita", + "arthur_compton", + "niels_bohr", + "kenneth_grahame", + "henry_fielding", + "bertrand_russell", + "katherine_anne_porter", + "michael_faraday", + "john_d_rockefeller", + "anthony_burgess", + "jan_tinbergen", + "robert_venturi", + "johnny_appleseed", + "andrzejewicz", + "irving_berlin", + "bernard_baruch", + "rudolf_diesel", + "bonkreta", + "walt_disney", + "ben_jonson", + "henr", + "popielica_szara", + "joseph_schumpeter", + "gabriel_lippmann", + "steve_reich", + "lee", + "benny_goodman", + "ted_williams", + "jane_austen", + "charles_laughton", + "gustav_mahler", + "ed_sullivan", + "phil_collins", + "alice_paul", + "robert_redford", + "jean_giraudoux", + "jack_dempsey", + "ian_fleming", + "richard_feynman", + "wolfgang_pauli", + "theodore_dreiser", + "theodor_mommsen", + "marcel_proust", + "jedna", + "homo_heidelbergensis", + "paul_hindemith", + "elizabeth_taylor", + "paul_robeson", + "thomas_middleton", + "john_dowland", + "anton_czechow", + "daniel_jones", + "william_golding", + "robert_motherwell", + "william_caxton", + "john_milton", + "rudolf_serkin", + "peter_stuyvesant", + "ethel_merman", + "u_otwarte", + "agent_ubezpieczeniowy", + "frank_baum", + "samuel_adams", + "albert_speer", + "james_baldwin", + "piotr_i_wielki", + "john_vanbrugh", + "indira_gandhi", + "jane_seymour", + "george_gershwin", + "alberto_giacometti", + "lilija", + "frank_whittle", + "alfred_nobel", + "jesse_owens", + "daniel_rutherford", + "marco_polo", + "john_fletcher", + "caravaggio", + "charlie_watts", + "m", + "charlotte_corday", + "marcel_marceau", + "allen_ginsberg", + "fred_zinnemann", + "daniel_bernoulli", + "guillaume_apollinaire", + "joseph_henry", + "henri_bergson", + "anna_paw\u0142owa", + "edward_macdowell", + "josef_hoffmann", + "boris_karloff", + "pierre_corneille", + "niedowiarek", + "patrick_white", + "saul_steinberg", + "bartholomew_roberts", + "hans_christian_andersen", + "peter_cooper", + "william_morris", + "cary_grant", + "hideyo_noguchi", + "igor_strawinski", + "thomas", + "pieter_zeeman", + "glenn_miller", + "steward", + "pablo_picasso", + "marian_anderson", + "natalie_wood", + "l_ron_hubbard", + "thomas_moore", + "galileusz", + "osman_i", + "kurt_weill", + "otto_hahn", + "lester_young", + "otto_meyerhof", + "michai\u0142_kalinin", + "john_marshall", + "christiaan_huygens", + "hector_berlioz", + "lucille_ball", + "paul_simon", + "claudio_monteverdi", + "robert_scott", + "john_galsworthy", + "robert_robinson", + "aleksja", + "o", + "one", + "adam_smith", + "william_james", + "u", + "jean_harlow", + "henry_miller", + "od_zera", + "paul_bunyan", + "friedrich_nietzsche", + "i", + "jimmy_durante", + "john_wesley", + "sandro_botticelli", + "carson_mccullers", + "seiji_ozawa", + "nikola_tesla", + "al_capone", + "charles_barkley", + "billy_graham", + "robert_schumann", + "mel_gibson", + "le_corbusier", + "carlo_goldoni", + "john_locke", + "alexis_carrel", + "genera\u0142_brygady", + "joseph_marie_jacquard", + "henry_james", + "stephen_sondheim", + "katullus", + "helen_keller", + "paul_dukas", + "ingrid_bergman", + "leonard_bloomfield", + "jean_piaget", + "william_congreve", + "franz_kline", + "henri_rousseau", + "paul_tillich", + "hilaire_belloc", + "william_sherman", + "frank_norris", + "don_quichote", + "frank_stella", + "robert_southey", + "walt_whitman", + "william_wyler", + "john_osborne", + "colin_powell", + "ludwig_boltzmann", + "carl_nielsen", + "chopin", + "i_tak_dalej", + "leopold_kronecker", + "richard_wright", + "benjamin_thompson", + "adolf_hitler", + "maria_mitchell", + "fritz_haber", + "skala\u0107", + "archibald_macleish", + "peter_behrens", + "alfred_stieglitz", + "henry_richardson", + "joseph_haydn", + "stephen_spender", + "garfield", + "tamara_karsawina", + "george_boole", + "hans_reiter", + "paul_revere", + "daniel_boone", + "buffalo_bill", + "edvard_grieg", + "robert_boyle", + "arthur_laffer", + "alan_paton", + "ralph_richardson", + "1", + "cordell_hull", + "james_wilson", + "rosa_parks", + "norman_jewison", + "samuel_goldwyn", + "zenon_izauryjczyk", + "x", + "ernest_walton", + "giuseppe_mazzini", + "jim_thorpe", + "h", + "randall_jarrell", + "arnold_sch\u00f6nberg", + "laurence_sterne", + "ben_hecht", + "christopher_isherwood", + "fritz_kreisler", + "anne_hathaway", + "david_garrick", + "don_budge", + "bill_russell", + "baldwin", + "jeannette_rankin", + "clarence_darrow", + "charles_lamb", + "g", + "albert_michelson", + "charles_coulomb", + "arthur_schopenhauer", + "thomas_dekker", + "james_cagney", + "johns_hopkins", + "henri_pitot", + "wanda_landowska", + "billy_mitchell", + "martin_heidegger", + "hans_eysenck", + "r", + "george_lucas", + "andrew_jackson", + "edith_wharton", + "louis_armstrong", + "helen_jackson", + "laurencjusz", + "steven_spielberg", + "jean_monnet", + "leonard", + "robert_fulton", + "\u015bwi\u0119ty_jerzy", + "thomas_hardy", + "thomas_gainsborough", + "giuseppe_garibaldi", + "philip_warren_anderson", + "robert_brown", + "wilhelm_weber", + "thomas_carlyle", + "allen_tate", + "donald_barthelme", + "william_tyndale", + "bobby_fischer", + "johannes_gutenberg", + "d", + "james_bowie", + "thomas_malthus", + "giambattista_marino", + "gaetano_donizetti", + "william_faulkner", + "amerigo_vespucci", + "pierre_boulez", + "hans_adolf_krebs", + "girolamo_savonarola", + "emma_goldman", + "piotr", + "robert_gray", + "francis_poulenc", + "james_ussher", + "john_barrymore", + "john_constable", + "james_mill", + "putin", + "matthew_flinders", + "robert_herrick", + "joseph_campbell", + "jean_de_la_fontaine", + "robert_hooke", + "o_henry", + "hoffa", + "karl_popper", + "alfred", + "coleman_hawkins", + "mary_harris", + "george_sand", + "peter_sellers", + "homo_rhodesiensis", + "charles_fourier", + "henry_clay", + "husajn", + "peter_o'toole", + "joseph_conrad", + "edmund_halley", + "william_shockley", + "peter_paul_rubens", + "mahatma_gandhi", + "jim_morrison", + "jules_verne", + "paul_newman", + "robert_mills", + "george_meredith", + "robert_morris", + "woody_herman", + "juliusz_cezar", + "jackson_pollock", + "john_lennon", + "andrea_palladio", + "katarzyna", + "bob_woodward", + "charlie_chaplin", + "lillian_russell", + "robert_woodward", + "thomas_malory", + "lea", + "john_brown", + "al_jolson", + "elizabeth_gaskell", + "john_mill", + "od_nowa", + "hugo_junkers", + "lillian_hellman", + "brescia", + "john_macleod", + "wawrzyniec", + "thomas_merton", + "boris_spasski", + "asa_gray", + "hannah_arendt", + "antonio_stradivari", + "marek_antoniusz", + "robinson_jeffers", + "alice_walker", + "dalajlama", + "miles_davis", + "edmund_cartwright", + "james_parkinson", + "wilhelm_tell", + "george_marshall", + "jesse_jackson", + "willa_cather", + "mezzosopranistka", + "stanley_kubrick", + "john_huston", + "william_gilbert", + "james_watt", + "jonathan_edwards", + "ronald_reagan", + "helmut_schmidt", + "ubezpieczeniowiec", + "jenny_lind", + "homo", + "frederick_douglass", + "david_hilbert", + "wilhelm_reich", + "roman_jakobson", + "grzegorz", + "oliver_cromwell", + "lionel_hampton", + "martin_luther_king", + "james_hargreaves", + "frank_capra", + "william_wordsworth", + "rex_harrison", + "rzeka_\u015bwi\u0119tego_wawrzy\u0144ca", + "s", + "william_clark", + "woodrow_wilson", + "thomas_jackson", + "william_wycherley", + "margaret_sanger", + "george_wallace", + "agrippina", + "richard_rodgers", + "george", + "anne_sexton", + "strawi\u0144ski", + "john_dryden", + "jim_henson", + "frank", + "b\u00e9la_lugosi", + "ernest_hemingway", + "john_eccles", + "george_westinghouse", + "andriej_sacharow", + "aquila", + "eero_saarinen", + "arthur_miller", + "john_cheever", + "gracie_allen", + "billy_sunday", + "nelson_mandela", + "heinrich_himmler", + "al_gore", + "john_rutledge", + "hans_bethe", + "hans_geiger", + "cesare_borgia", + "strzy\u017cyki", + "donkiszot", + "gaus", + "roald_amundsen", + "sherwood_anderson", + "richard_leakey", + "alfred_korzybski", + "c_a", + "charles_dickens", + "samuel_huntington", + "ella_fitzgerald", + "fats_waller", + "thomas_sydenham", + "jack_robinson", + "alois_senefelder", + "taszilama", + "george_enescu", + "wallace_carothers", + "jacques_offenbach", + "joseph_paxton", + "william_chambers", + "gilbert", + "george_stevens", + "federico_fellini", + "the_one", + "m\u0142ynarski", + "bessie_smith", + "don_kiszot", + "jean_antoine_watteau", + "patrick_henry", + "willy_brandt", + "ochmistrz", + "charles_wilkes", + "francisco_pizarro", + "francisco_franco", + "jackie_robinson", + "bernardo_bertolucci", + "jan_steen", + "tercjan", + "john_ross", + "ali_baba", + "antonin", + "strzy\u017cyk", + "powell", + "philibert_delorme", + "hans_arp", + "andrew_carnegie", + "franz_schubert", + "william_butterfield", + "johnny_cash", + "alfred_kastler", + "kopy\u015b\u0107", + "dawid", + "mick_jagger", + "otto_loewi", + "georges_cuvier", + "william_harvey", + "walter_scott", + "parkinson", + "peter_medawar", + "sam_houston", + "benedykt", + "robert_browning", + "alessandro_farnese", + "ralph_ellison", + "john_bunyan", + "jonathan_swift", + "lydia_lili\u02bbuokalani", + "walter_gropius", + "albert_einstein", + "l", + "robert_joffrey", + "fritz_lipmann", + "aletta_jacobs", + "claude_bernard", + "raymond_chandler", + "henry_purcell", + "ormuzd", + "flannery_o\u2019connor", + "t", + "wilhelm_ostwald" + ], + "ORG": [ + "szko\u0142a", + "ida", + "shinto", + "armia_czerwona", + "wisznuizm", + "szintoizm", + "nieliniowo\u015b\u0107", + "rada_federalna", + "choroba_francuska", + "san_jos\u00e9", + "dominikanie", + "hydroksyetan", + "wicca", + "mormonizm", + "psychiatryk", + "aktualny", + "marynarka", + "jan_mayen", + "as_dur", + "policja_stanowa", + "szyityzm", + "wieczorem", + "aa", + "pompka", + "nasa", + "niebieskooki", + "arda", + "huang_he", + "bollywood", + "ang", + "garkuchnia", + "wysoka_cz\u0119stotliwo\u015b\u0107", + "murarstwo", + "europol", + "schutzstaffel", + "the_who", + "podstaw\u00f3wka", + "dominium", + "rada_gminy", + "the_planetary_society", + "college", + "wariatkowo", + "san_francisco", + "na_odwr\u00f3t", + "irlandzki_korpus_lotniczy", + "\u015br\u00f3dmie\u015bcie", + "zagranica", + "germanistyka", + "nowobogacz", + "v\u0129nh_long", + "wioska_olimpijska", + "prawo_cywilne", + "nara", + "aleksander_wielki", + "partia_socjaldemokratyczna", + "va", + "retinopatia_barwnikowa", + "dzieci\u0105teczko", + "zabawkarstwo", + "rozs\u0105dek", + "islamistyka", + "spierdala\u0107", + "m\u0142odoturcy", + "wyspa_\u015bwi\u0119tej_heleny", + "i_in", + "sc", + "kszta\u0142cenie", + "niebieskooka", + "politechnika", + "ko\u015bci\u00f3\u0142_anglika\u0144ski", + "baskonia", + "gao", + "szyntoizm", + "prohibition_party", + "franciszkanie", + "s_hertogenbosch", + "nanak", + "partia_pracy", + "z\u0142oty_wiek", + "bogarodzicielka", + "shintoizm", + "legislatywa", + "saint_vincent", + "zesp\u00f3\u0142_baletowy", + "augustianie", + "john_tuzo_wilson", + "armia", + "don_juan", + "oni", + "the_new_school", + "rada_ministr\u00f3w", + "ai", + "podejrzani", + "s_f", + "ds", + "fundusz_emerytalny", + "the_football_league", + "chiang_mai", + "yorkowie", + "dia", + "druga_osoba", + "radiogalaktyka", + "fabianie", + "po_trochu", + "partia_socjalistyczna", + "a_r\u00f3b_jak_chcesz", + "ab_initio", + "le_mans", + "barbara_z_nikomedii", + "samorz\u0105d", + "partia_komunistyczna", + "caf\u00e9_au_lait", + "prawo_rzymskie", + "prawnuk", + "ko\u015bci\u00f3\u0142_katolicki", + "marynarka_wojenna", + "rada_miasta", + "rabindranath_tagore", + "taoizm", + "gestapo", + "zwariowa\u0107", + "skarbiec", + "s\u0105d_najwy\u017cszy", + "n\u00f3w", + "pac", + "sprawiedliwo\u015b\u0107", + "o\u015bwiata", + "lancasterowie", + "drobnomieszcza\u0144stwo", + "masoneria", + "matka_bo\u017ca_siedmiobolesna", + "ma\u0142opolska", + "baon", + "who_are_you", + "og\u00f3lniak", + "partia_konserwatywna", + "partido_del_trabajo", + "partia_zielonych", + "chiang_rai", + "stronnictwo_narodowe", + "hippisi", + "europe", + "po", + "the_opposition", + "krisznowiec", + "fabryka_marze\u0144", + "\u015bwi\u0119ta_rodzina", + "rada_p\u00f3\u0142nocnoatlantycka", + "partia_polityczna", + "izba_ni\u017csza", + "posprz\u0105ta\u0107", + "hollywood", + "rasa_pan\u00f3w", + "s\u0142odka_woda", + "al_ajn", + "socjaldemokratyczna_partia_andory", + "minoryci", + "saint_barth\u00e9lemy", + "sturmabteilung", + "las_bawarski", + "pretorianie", + "los_angeles", + "nato", + "mass_media", + "baltimore_orioles", + "zgromadzenie_narodowe_republiki_serbskiej", + "anno_domini", + "rada_miejska", + "ad_hoc", + "zesp\u00f3\u0142_rockowy", + "braminizm", + "city_hall", + "almand", + "polucja", + "by_the_way", + "alla_polacca", + "skautka", + "in_situ", + "miko\u0142aj_z_miry", + "polibuda", + "sa", + "\u015bwiadkowie_jehowy", + "murarka", + "urz\u0105d_pocztowy", + "si\u0142y_powietrzne", + "bia\u0142y_dom", + "partia_republika\u0144ska", + "szinto", + "matka_boska_bolesna", + "krysznowiec", + "al_d\u017cazira", + "stowarzyszenie_chrze\u015bcija\u0144skiej_nauki", + "hagana", + "mi\u0119dzynarodowa_unia_telekomunikacyjna", + "kolegium", + "republika_zielonego_przyl\u0105dka", + "cesarstwo_niemieckie", + "commerce", + "streptococcus_pyogenes", + "eu", + "na_nowo", + "zgromadzenie_narodowe_korei_po\u0142udniowej", + "kapetyngowie", + "ratusz", + "kadry", + "tak_w_og\u00f3le", + "czerwony_krzy\u017c", + "woda_s\u0142odka", + "wilki_morskie", + "sprz\u0105ta\u0107", + "zgromadzenie_narodowe_republiki_serbii", + "wojska_lotnicze", + "park_przemys\u0142owy", + "mosad", + "s\u00e3o_tom\u00e9", + "hipisi", + "lowelas", + "akademia_wojskowa", + "shint\u014d", + "drobnomieszczanin", + "\u015bwi\u0119te_cesarstwo_rzymskie", + "stany", + "skarbnica" + ], + "JOB": [ + "fagas", + "laufer", + "lutownik", + "protokolant", + "licencjodawca", + "marsza\u0142ek", + "baka\u0142arz", + "leksykograf", + "mincarz", + "developer", + "guru", + "sweep", + "terakociarz", + "psor", + "fundator", + "gastarbajter", + "baga\u017cowy", + "seter", + "balsamista", + "pomagier", + "stangret", + "rejestrator", + "arcypasterz", + "businessman", + "\u015bluzowy", + "faktotum", + "kapral", + "czeladnik", + "speaker", + "elektromonter", + "szczuro\u0142ap", + "hydrolog", + "niedorajda", + "magazynier", + "skarbnik", + "osadnik", + "mikrobiolog", + "make", + "piekarz", + "golarz", + "drogista", + "piastunka", + "pokojowa", + "herold", + "endokrynolog", + "trener", + "stra\u017cak", + "nawijarka", + "japiszon", + "translator", + "handlowiec", + "sokolnik", + "angiolog", + "autorka", + "renowator", + "kochanica", + "wolontariusz", + "pastuszka", + "alkad", + "mincerz", + "koronowana_g\u0142owa", + "kosarz", + "tkacz", + "suwerenny", + "sexton", + "trybik", + "podczaszy", + "biuralista", + "\u015bwiniopas", + "don", + "king", + "stra\u017cniczka_wi\u0119zienna", + "ludwisarz", + "karabinier", + "golkiper", + "dermatolog", + "doradca", + "the_police", + "stolarz", + "gestor", + "terapeuta", + "biskup", + "pil\u015bniarz", + "pretor", + "feldmarsza\u0142ek", + "sommelier", + "weterynarka", + "amunicyjny", + "niepodleg\u0142y", + "gentleman", + "praczka", + "fabrykant", + "budowlany", + "midynetka", + "szkoleniowiec", + "weterynarz", + "hematolog", + "kr\u00f3liczek", + "pakarz", + "ochotnik", + "kamienicznik", + "kaczkarz", + "kornak", + "burmistrz", + "porucznik", + "estetyk", + "drugi_pilot", + "ramiarz", + "para", + "router", + "tapicer", + "stra\u017cnik", + "tkaczka", + "romansopisarz", + "lokaj", + "grotnik", + "sensei", + "arrowsmith", + "bodyguard", + "krawcowa", + "prowost", + "torowiec", + "dziejopisarz", + "mastermind", + "syndyk", + "sidlarz", + "listonosz", + "deweloper", + "land", + "introligator", + "gonciarz", + "boss", + "stenografka", + "odlewca", + "baloniarz", + "stenograf", + "stewardesa", + "furman", + "artylerzysta", + "interpretator", + "muszkieter", + "grenadier", + "inwentaryzator", + "kawalerzysta", + "portowiec", + "prowincja\u0142", + "zarz\u0105dca", + "wierzyciel", + "sternik", + "husarz", + "nabijacz", + "odlewacz", + "kurator", + "comber", + "dystrybutorka", + "harpunnik", + "independent", + "leader", + "kamikaze", + "warzy\u0107", + "driver", + "the_advocate", + "osiedleniec", + "wiarus", + "goniec", + "farbiarz", + "pasterka", + "farbiarka", + "kirasjer", + "niezale\u017cny", + "kafelkarz", + "liternik", + "kanclerz", + "belfer", + "baker", + "sklepowy", + "terapeutka", + "dziejopis", + "freelancer", + "krupierka", + "krowiarz", + "celnik", + "hierarcha", + "glazurnik", + "homiletyk", + "przyw\u00f3dca", + "komandos", + "brid\u017cysta", + "radca", + "kardiochirurg", + "the_guardian", + "budziciel", + "mydli\u0107", + "szkutnik", + "nagabywacz", + "niania", + "toksykolog", + "numerowy", + "kaligrafista", + "planista", + "akwanauta", + "minister", + "trewir", + "kamieniarz", + "kaznodzieja", + "stelmach", + "stomatolog", + "hydrograf", + "radny", + "sklepikarz", + "galernik", + "kamerdyner", + "piechociarz", + "mason", + "niezawis\u0142y", + "herbatnik", + "mate", + "stoker", + "koziarka", + "ustawodawca", + "marynarz", + "egzekutywa", + "nieudacznica", + "bednarz", + "interpreter", + "kaemista", + "smarowacz", + "korepetycje", + "fornal", + "smarownik", + "rockman", + "\u015bwiniarz", + "piekarka", + "pastor", + "hostessa", + "dyrektor", + "gerontolog", + "bryd\u017cysta", + "energetyk", + "kolekcjoner", + "gosposia", + "regulator", + "gaziarz", + "managerka", + "piecz\u0119tarz", + "wielorybnik", + "handlarz", + "odga\u0142\u0119ziacz", + "fellach", + "bosman", + "zakrystian", + "woluntariusz", + "gaucho", + "koordynator", + "pikolak", + "logistyk", + "stewardessa", + "internista", + "gajowy", + "\u017co\u0142nierz", + "bezpieczniak", + "rabin", + "fabrykantka", + "plantator", + "pokoj\u00f3wka", + "tokarz", + "koniuch", + "sortownik", + "the_economist", + "bramkarz", + "manager", + "lutowacz", + "broker", + "wetter", + "porter", + "dobrowolny", + "rakarz", + "szczur", + "immunolog", + "barista", + "sortowacz", + "sorter", + "tropiciel", + "kurier", + "kierownik", + "kronikarz", + "giermek", + "podkuwacz", + "dw\u00f3rka", + "ubezpieczeniowiec", + "zakrystianka", + "garderobiany", + "chemik", + "a_dur", + "regent", + "stajenny", + "koniuszy", + "wo\u017any", + "fitoterapeuta", + "businesswoman", + "the_boxer", + "neurolog", + "malarka", + "sier\u017cant", + "usher", + "messenger", + "stronica", + "panuj\u0105cy", + "dysponent", + "menad\u017cerka", + "protok\u00f3lant", + "kartograf", + "krupier", + "au_pair", + "bryd\u017cowiec", + "kamerzysta", + "barkarz", + "zielarz", + "poganiacz", + "bombardier", + "klinicysta", + "laryngolog", + "egzaminator", + "tercjan", + "ginekolog", + "ploter", + "dostarczyciel", + "drogerzysta", + "kwatermistrz", + "dostawca", + "\u0142apiduch", + "regentka", + "tracz", + "steward", + "dziennikarz", + "cyrulik", + "kupiec", + "topiarz", + "kartownik", + "murarz", + "robotnik", + "konduktorka", + "sterownik", + "statystyk", + "the_independent", + "bishop", + "herbowiec", + "padlino\u017cercy", + "rozsadnik", + "pedel", + "mroczek", + "metresa", + "cookie", + "neurochirurg", + "komandor", + "bankier", + "garbarz", + "sortownica", + "esquire", + "gospodyni", + "folusznik", + "higienista", + "cukiernik", + "kombatant", + "garncarz", + "autor", + "miedziownik", + "drapaczka", + "golibroda", + "kardiolog", + "towarzyszka", + "reumatolog", + "przedstawiciel_ubezpieczeniowy", + "kamikadze", + "lansjer", + "mened\u017cerka", + "preceptor", + "udar_m\u00f3zgu" + ], + "DISEASE": [ + "hurt", + "sars", + "rozedma", + "niedowidzenie", + "nerwiak_zarodkowy", + "gruczolak", + "nienormalno\u015b\u0107", + "acanthosis_nigricans", + "nietrze\u017awo\u015b\u0107", + "szajba", + "zaka\u017cenie", + "poliuria", + "cellulitis", + "zachorowanie", + "bezg\u0142os", + "tego", + "polio", + "szcz\u0119ko\u015bcisk", + "hydrocefalia", + "heinemedina", + "trzepota\u0107", + "wiroid", + "przetoka", + "galaktozemia", + "rage", + "szczep", + "betafibryloza", + "wariactwo", + "chill", + "als", + "androfobia", + "galeofobia", + "niedoczynno\u015b\u0107", + "marsko\u015b\u0107", + "bezp\u0142odno\u015b\u0107", + "clubbing", + "pernoitar", + "podgrza\u0107", + "rakowiak", + "galas\u00f3wka", + "krosta", + "brzemienno\u015b\u0107", + "progeria", + "przepuklina_przeponowa", + "gor\u0105czka_krwotoczna_ebola", + "sleeping", + "polidaktylia", + "frostbite", + "g\u0142askanie", + "marazm", + "stulejka", + "muskularo\u015b\u0107", + "geofagia", + "skarga", + "lamblioza", + "niekompetencja", + "suchoty", + "akinezja", + "pora\u017cenie", + "parestezja", + "stenoza", + "bezsenno\u015b\u0107", + "kar\u0142owato\u015b\u0107", + "bradykardia", + "niedomoga", + "cukrzyca", + "arbowirusy", + "gall", + "mania", + "niemiarowo\u015b\u0107", + "felinofobia", + "the_bends", + "niedow\u0142ad", + "przekrwienie", + "grad\u00f3wka", + "liszaj", + "wielkog\u0142owie", + "struma", + "paratyfus", + "ms", + "spodziectwo", + "bunt", + "radiacja", + "wiremia", + "przyz\u0119bica", + "halluks", + "sen_zimowy", + "the_suffering", + "salmonelloza", + "rust", + "zastrza\u0142", + "proteinuria", + "gestoza", + "konwulsja", + "gatofobia", + "paradontoza", + "zanik", + "niewydolno\u015b\u0107", + "pochp", + "klaustrofobia", + "albuminuria", + "paludyzm", + "promienica", + "ziarniniak", + "malinka", + "pelagra", + "rozwolnienie", + "para", + "char\u0142actwo", + "kurzajka", + "pokrzywka", + "handicap", + "puchlina", + "krwawi\u0105czka", + "paradentoza", + "starczowzroczno\u015b\u0107", + "parzysto\u015b\u0107", + "talasemia", + "niesystematyczno\u015b\u0107", + "beri_beri", + "wale", + "schorzenie", + "jagodzica", + "wielomocz", + "kretynizm", + "anewryzm", + "katarakta", + "zachorowa\u0107", + "presbyopia", + "demineralizacja", + "m\u0119ty_cia\u0142a_szklistego", + "wirus_epsteina_barr", + "przegrzanie", + "krzemica", + "fundator", + "szale\u0144stwo", + "niestrawny", + "hamartoma", + "moj\u017ceszowy", + "aurajoki", + "tryper", + "delirium", + "niedokrwienie", + "materializm", + "listerioza", + "lordoza", + "choroba_kawasakiego", + "qi", + "torbiel", + "promieniowanie", + "wytrzeszcz", + "nosacizna", + "siatk\u00f3wczak", + "kropidlakowica", + "denga", + "czerwonka", + "choroba_morska", + "tachykardia", + "ropomocz", + "gimp", + "abazja", + "schistosomatoza", + "pype\u0107", + "kr\u00f3tkowzroczno\u015b\u0107", + "ksi\u0119gosusz", + "prezbyopia", + "brachydaktylia", + "twist", + "smart", + "amelia", + "przepuklina", + "ed", + "blister", + "pica", + "potencja", + "kamica", + "chloroza", + "poparzenie", + "acetonemia", + "trachoma", + "nowotw\u00f3r", + "sensation", + "pancytopenia", + "szczypa\u0107", + "naczyniak", + "habituacja", + "awitaminoza", + "zamartwica", + "wegetacja", + "krzywda", + "pain", + "niedyspozycja", + "malinica", + "ropie\u0144", + "jaglica", + "silikoza", + "polisomia", + "niedocukrzenie", + "purpura", + "niedodma", + "krowianka", + "powik\u0142anie", + "katalepsja", + "ill", + "paraplegia", + "an_qi", + "bielactwo", + "gruczolakorak", + "wylinka", + "podekscytowanie", + "padaczka", + "rozdra\u017cnienie", + "bezdech", + "jaskra", + "dolegliwo\u015b\u0107", + "kr\u0119gozmyk", + "wirus_ospy_wietrznej_i_p\u00f3\u0142pa\u015bca", + "nadpobudliwo\u015b\u0107", + "nieuda\u0142ota", + "posocznica", + "astygmatyzm", + "oponiak", + "mocznica", + "kostniakomi\u0119sak", + "reifikacja", + "aura", + "zdenerwowanie", + "bruceloza", + "sting", + "wart", + "za\u0142o\u017cyciel", + "plamisto\u015b\u0107", + "czerniak", + "the_bleeding", + "demencja", + "ginekomastia", + "niestrawno\u015b\u0107", + "g\u0142aska\u0107", + "trauma", + "niedokrwisto\u015b\u0107", + "zawa\u0142", + "nienasycono\u015b\u0107", + "kuru", + "burn", + "twardzina", + "szczepienie", + "rumie\u0144", + "szpat", + "zaro\u015bni\u0119cie", + "niedo\u017cywienie", + "podgrzewa\u0107", + "parali\u017c", + "noma", + "polidypsja", + "hydrofobia", + "the_hives", + "zapicie", + "przerost", + "choroba", + "liszajec", + "nieurodzajno\u015b\u0107", + "borelioza", + "biegunka", + "chlewnia", + "spanie", + "le", + "truj\u0105cy_bluszcz", + "zimno", + "kolaps", + "salmonella", + "sensacja", + "krup", + "abrazja", + "rozstr\u00f3j", + "pieczenie", + "niedomaganie", + "alessia_aquilani", + "malaria", + "\u015bwi\u0105d_p\u0142ywak\u00f3w" + ], + "PLANT": [ + "ziarnop\u0142on", + "jarz\u0119bina", + "fio\u0142ek", + "ambrowiec", + "mahonia", + "musztarda", + "kasztan", + "pine", + "adenium_arabskie", + "klepak", + "gutaperkowiec", + "drzewko", + "cyprys_arizo\u0144ski", + "the_joshua_tree", + "sanda\u0142owiec", + "sosna", + "arenga_pierzasta", + "przetacznik_polny", + "czarnuszka", + "kosodrzewina", + "jedlica", + "amanita", + "tarnina", + "ostrogowiec", + "sokora", + "gorczyca", + "laurowi\u015bnia_wschodnia", + "hydrofity", + "kassawa", + "leucaena_leucocephala", + "macoszka", + "modrzew", + "niezapominajka", + "bertolecja", + "sakura", + "mastyks", + "przetacznik_macierzankowy", + "ligustr", + "candida_albicans", + "sit_chudy", + "szczawik", + "bergamota", + "piestrzenica", + "wierzba", + "pszczelnik", + "aleuryt", + "czeremcha", + "anginka", + "s\u0142onecznik", + "marchewka", + "konopianka", + "sit_cz\u0142onowaty", + "kroplan", + "holm", + "paklon", + "kunsztmistrz", + "muchomor_cesarski", + "brzoza_brodawkowata", + "pokrzyk", + "dziewi\u0119\u0107si\u0142", + "zaraza_ziemniaka", + "witwa", + "kasztanowiec", + "welingtonia", + "pinang", + "\u0142zawnica_ogrodowa", + "kalafior", + "blackberry", + "magnolia_frasera", + "malpigia_granatolistna", + "echinocactus_grusonii", + "chryzantema", + "arabika", + "sit_rozpierzch\u0142y", + "pokrzywa", + "aldrowanda_p\u0119cherzykowata", + "r\u00f3\u017ca_damasce\u0144ska", + "s\u0142onecznik_zwyczajny", + "rezeda", + "tungowiec", + "melisa", + "balsamka_og\u00f3rkowata", + "sabina", + "saccharomyces_cerevisiae", + "buckeye", + "konwalia", + "rojownik", + "modrzewnica", + "obrazki", + "marathi", + "senna_alexandrina", + "ponik\u0142o_s\u0142odkie", + "mucho\u0142\u00f3wka", + "klonina", + "jawor", + "anginowiec", + "sierotki", + "mirabela", + "korona_cierniowa", + "szyszynka", + "batat", + "pinus_muricata", + "belladonna", + "kleparka", + "alt\u00f3wka", + "kluzja", + "bratek", + "sit_dwudzielny", + "szczaw_zwyczajny", + "czere\u015bnia", + "macierzanka_piaskowa", + "lipa_srebrzysta", + "schinus_peruwia\u0144ski", + "magnolia", + "magnolia_parasolowata", + "tatarak", + "hewea" + ], + "SOC_ECO_CLASS": [ + "drobnomieszcza\u0144stwo", + "ch\u0142opstwo", + "czarny_rynek", + "mieszcza\u0144stwo", + "ma\u0142o", + "klasa_\u015brednia", + "lumpenproletariat", + "rolnictwo", + "braterstwo", + "socjeta", + "samuraj", + "proletariat", + "klasa_robotnicza", + "drobnomieszczanin" + ], + "LOCATION": [ + "la_plata", + "maryja_panna", + "columbus_day", + "falklandy", + "park", + "bow_wow", + "saksonia_anhalt", + "united_states_army", + "s_hertogenbosch", + "s_tog", + "kirkut", + "dobranoc", + "piet_mondrian", + "krzysztof_kolumb", + "la_manche", + "tomcio_paluch", + "sint_maarten", + "warzywnik", + "dziedziniec", + "qingmingjie", + "szpital_psychiatryczny", + "trois_rivi\u00e8res", + "uczelnia_muzyczna", + "na_ulicy", + "land", + "huang_he", + "rozarium", + "saint_vincent", + "szybka_kolej_miejska", + "godzinnik", + "osoba_trzecia", + "murawa", + "do_siego_roku", + "g\u00f3ra_karmel", + "dyspozytornia", + "na_wszelki_wypadek", + "al_d\u017cazira", + "psychiatryk", + "jezioro_g\u00f3rne", + "alpinarium", + "\u015br\u00f3dmie\u015bcie", + "na_wypadek_gdyby", + "usa", + "st_albans", + "\u015bpi\u0105ca_kr\u00f3lewna", + "w_f", + "rzeka_\u017c\u00f3\u0142ta", + "saint_lucia", + "malwiny", + "i_co_z_tego", + "hat_yai", + "arena", + "sri_lanka", + "taktyka_spalonej_ziemi", + "joseph_gay_lussac", + "\u015bwi\u0119ty_patryk", + "the_rolling_stones", + "jezioro_le\u015bne", + "stany", + "ogr\u00f3d_botaniczny", + "za_kulisami", + "g\u00f3ra_oliwna", + "krzywy_r\u00f3g", + "heitor_villa_lobos", + "portoryko", + "czeskie_budziejowice", + "dwaj_bracia", + "stany_zjednoczone", + "al_ajn" + ], + "ANIMAL": [ + "ostrop\u0142etwiec", + "labraks", + "lemingi", + "szczuroskocznik_jedwabisty", + "sosn\u00f3wka", + "rybitwy", + "polatucha", + "popielica", + "kot_pustynny", + "bia\u0142ucha", + "buteo", + "fiszbinowce", + "homarzec", + "czarnowron", + "dropiatka", + "paszczak_australijski", + "karaczany", + "rybitwa", + "suse\u0142", + "puchacz", + "karczownik", + "sinantrop", + "czerwce", + "g\u0142owom\u0142ot", + "pustyniogwan", + "wilgowate", + "likaon", + "leniwcowate", + "billy_elliot", + "kot_perski", + "wirus_mozaiki_tytoniu", + "kunduz", + "pigmejka", + "kaszalot", + "krogulec", + "palczakowate", + "dog_niemiecki", + "karaluch", + "sze\u015bcioszparowate", + "carduelis", + "tawroszowate", + "ogniczek", + "buffalo_czarny", + "wydrzyk_wielki", + "puszczyk", + "rdzawiec", + "zimorodkowate", + "lactobacillus_acidophilus", + "zielonooki", + "pogo\u0144cowate", + "kikutnice", + "vibe", + "brunatnice", + "wilga", + "jarz\u0105bek", + "micropterus", + "stonoga", + "piotrosz", + "bass_wielkog\u0119bowy", + "zimorodek", + "parzystokopytne", + "jerzykowate", + "raven", + "homo_sapiens", + "czarny_\u017c\u00f3\u0142w", + "makakowate", + "baribal", + "nieparzystokopytne", + "potrzos", + "samog\u0142\u00f3w", + "pieg\u017ca", + "kapturnik", + "kot_abisy\u0144ski", + "amadyniec", + "winniczek", + "popielicowate", + "trzyszczowate", + "galas\u00f3wkowate", + "accipiter", + "grzechotnikowate", + "grzywacz", + "kot_b\u0142otny", + "archeany", + "kokiet", + "sierpodudki", + "assapan", + "soko\u0142y", + "polnik", + "stonkowate", + "\u015bwiergotek", + "archebakterie", + "jask\u00f3\u0142ka_dym\u00f3wka", + "goryl", + "nied\u017awied\u017a_himalajski", + "miodny", + "eubakterie", + "s\u0142owik\u00f3wka", + "ziemnokraski", + "nied\u017awied\u017a_kr\u00f3tkopyski", + "karolinka", + "iller", + "siwerniak", + "daniel_mezopotamski", + "humbak", + "nied\u017awiadek", + "przepi\u00f3r_kalifornijski", + "grzywa", + "cietrzew", + "ammospermophilus", + "borowiak_kanadyjski", + "megascops", + "archeowce", + "g\u0142owom\u0142ot_pospolity", + "\u015bcierwnik", + "ostrobok_pospolity", + "grindwal", + "nawa\u0142niki", + "nieszporek", + "kara\u015b", + "jelonkowate", + "pustu\u0142ka", + "pirol", + "\u015blepowron", + "kacyki", + "zeberka", + "kapodzi\u00f3b", + "ptaszorowate", + "kopytny", + "\u0142odzik", + "biegaczowate", + "archeobakterie", + "przepi\u00f3r_wirginijski", + "szczupak_pospolity", + "kusakowate", + "fokowate", + "kumak", + "koryfena", + "paszczak", + "kot_syjamski", + "burunduk", + "kropiatka", + "mucho\u0142\u00f3wkowate", + "preriowiec", + "barramundi", + "yorkshire_terrier", + "eagle", + "babiarz", + "rakojad", + "nosacz", + "krasnorosty", + "mendoweszka", + "manaty", + "polatuchy", + "szczygie\u0142", + "koziu\u0142kowate", + "szczuroskoczek", + "sierpiec", + "wirus_opryszczki_pospolitej", + "turkawka", + "miodo\u017cer", + "majkong", + "peristediidae", + "eider", + "paszkot", + "jask\u00f3lak", + "nocek", + "szersze\u0144", + "arvicola" + ], + "RELIGION_MEMBER": [ + "katolicki", + "chrze\u015bcijanka", + "prezbiteria\u0144ski", + "kongregacjonalista", + "guru", + "minoryta", + "the_hindu", + "augustianin", + "protestantka", + "protestant", + "sunnita", + "unita", + "satanistka", + "parsowie", + "panikarz", + "anabaptysta", + "prezbiterianin", + "benedyktyn", + "krysznowiec", + "metodystka", + "nazarejczyk", + "cysters", + "jezuita", + "karmelita", + "mormon", + "nowochrzczeniec", + "baptystyczny", + "bezwyznaniowiec", + "shaker", + "benedyktynka", + "metodysta", + "saracen", + "oran\u017cysta", + "kartuz", + "wikkanin", + "anabaptystka", + "rzymskokatolicki", + "starokatolik", + "mahometanka", + "kwakier", + "franciszkanin", + "grekokatolik", + "niekonformista", + "krisznowiec", + "starokatolicki", + "mahometanin", + "nazareta\u0144ski", + "augustyn", + "zielono\u015bwi\u0105tkowiec", + "baptysta", + "purytanin" + ], + "LANGUAGE": [ + "francuszczyzna", + "greczynka", + "rundi", + "venda", + "kowacz", + "kongo", + "katalonka", + "nawaho", + "perski", + "akan", + "citonga", + "arabszczyzna", + "francuski", + "tybeta\u0144ski", + "angielszczyzna", + "polski", + "sindhi", + "kazach", + "niemczyzna", + "pali", + "eskimoski", + "manx", + "polszczyzna", + "galicyjski", + "hindi", + "prowansalski", + "keczua", + "malajski", + "guarani", + "turecki", + "kornwalijski", + "chitonga", + "wietnamski", + "german", + "sango", + "walijski", + "tajlandzki", + "niemiec", + "esperanto", + "islandzki", + "bia\u0142oruski", + "katalo\u0144czyk", + "chorwacki", + "kazaszka", + "komi", + "hausa", + "nowogrecki", + "jawajka", + "portugalczyk", + "litewski", + "tagalog", + "niemka", + "ido", + "irlandzki", + "marathi", + "angielski", + "portugalski", + "tonga", + "kannada", + "malajalam" + ], + "POLITICAL_PARTY_MEMBER": [ + "labourzysta", + "mienszewik", + "laburzysta", + "federalista" + ], + "RELIGION": [ + "shint\u014d", + "zen", + "trynitarianizm", + "shinto", + "kalwinizm", + "lamaizm", + "katarzy", + "salafizm", + "wisznuizm", + "szyntoizm", + "sintoizm", + "islam", + "manicheizm", + "donatyzm", + "prezbiterianizm", + "braminizm", + "wedanta", + "rastafarianizm", + "shintoizm", + "wicca", + "kataryzm", + "mitraizm" + ], + "PRODUCT": [ + "radiomagnetofon", + "justin_bieber", + "s_tog", + "imperium_rzymskie", + "martwa_natura", + "diego_garcia", + "tutti_frutti", + "druga_wojna_\u015bwiatowa", + "epoka_trzech_kr\u00f3lestw", + "braciszek", + "liniowiec", + "baptysterium", + "z_bo\u017cej_\u0142aski", + "saint_vincent", + "\u015bwi\u0119ta_maria", + "tr\u00f3jwymiarowy", + "radioodtwarzacz", + "the_music_box", + "pancerka", + "jan_baptysta", + "i_wojna_\u015bwiatowa", + "monte_cristo", + "city_hall", + "mahjongg", + "boxing_day", + "kawia_domowa", + "cztery_pory_roku", + "nowokaledo\u0144ski", + "deutsche_welle", + "gong", + "mount_st_helens", + "niezapominajka", + "\u015bwinka_morska", + "nowy_testament", + "drugi_dzie\u0144_\u015bwi\u0105t", + "kot_w_butach", + "lusterko", + "bezpiecznik", + "bananowiec", + "mario_andretti", + "san_sebastian", + "m_ger\u00e4t", + "bila_rozgrywaj\u0105ca", + "ii_wojna_\u015bwiatowa", + "has_been", + "bila_zagrywaj\u0105ca", + "dorasta\u0107", + "derka", + "dzieci_triady", + "novo_mesto" + ], + "FOOD": [ + "rogal", + "sok_pomidorowy", + "golden_delicious", + "kran\u00f3wka", + "rachat\u0142ukum", + "christmas_pudding", + "guma_do_\u017cucia", + "sok_cytrynowy", + "granny_smith", + "limoniada", + "sa\u0142atka_owocowa", + "bakalie", + "kaszanka", + "sok_pomara\u0144czowy", + "pinot_noir", + "chilli", + "sok_jab\u0142kowy", + "tatarka", + "przegryzka", + "batonik", + "placek", + "szarlotka", + "sok_marchewkowy", + "beszamel", + "chili", + "chipsy", + "lunch", + "chile", + "razowiec", + "sok_\u017curawinowy", + "landrynka", + "pudding", + "lemoniada", + "przek\u0105ska", + "landryna", + "tutti_frutti", + "schab", + "deser", + "racuch", + "pulpet", + "nabia\u0142", + "przystawka", + "krem\u00f3wka", + "grzaniec", + "przegryzek" + ], + "PERSON": [ + "samokontrola", + "ha_ha", + "al_gore", + "ja_te\u017c", + "saint_vincent", + "gioconda", + "don_delillo", + "edward_osborne_wilson", + "tai_shan", + "de_witt", + "stek_na_ko\u015bci", + "george_v", + "al_amin", + "in_memory", + "peter_dawson", + "carl_david_anderson", + "jo_jo", + "yo_yo", + "za_pomoc\u0105", + "rudolf_hess", + "samoocena", + "herbert_george_wells", + "cha_cha" + ], + "QUANTITY": [ + "tr\u00f3jwymiarowy", + "baks", + "sterling", + "frank_belgijski", + "frank_gwinejski", + "stopotona", + "dolec", + "gramoatom", + "dinar", + "won_p\u00f3\u0142nocnokorea\u0144ski", + "ton", + "jednodolar\u00f3wka", + "ciernik", + "frank_szwajcarski", + "dollar", + "kaloria", + "marka_niemiecka", + "parkometr", + "gram_si\u0142a", + "g", + "frank_francuski", + "the_real_world", + "elektronowolt", + "rial", + "trzy_siostry", + "teralitr", + "pond", + "won_po\u0142udniowokorea\u0144ski", + "woltamper", + "woltoamper", + "mikrolitr", + "anders_celsius", + "nz" + ], + "GENDER": [ + "transgenderyzm", + "gentleman", + "men", + "male", + "boys", + "samica", + "dziewa", + "salowa", + "transgen", + "samiec", + "dziewcz\u0119", + "gal", + "gwido" + ], + "GPE": [ + "cesarstwo_niemieckie", + "saint_domingue", + "dar_es_salaam", + "walentynki", + "sint_maarten", + "tai_shan", + "\u015bwi\u0119ty_krzysztof", + "hagia_sophia", + "s\u00e3o_tom\u00e9", + "\u015bwi\u0119ta_barbara", + "hagia_sofia", + "gran_canaria", + "stare_miasto", + "duch_\u015bwi\u0119ty", + "al_andalus", + "region_nadmorski", + "la_rochelle", + "morze_czerwone", + "la_gomera", + "piotr_aposto\u0142", + "dolno\u015bl\u0105ski", + "tr\u00e0_vinh", + "prawa_cz\u0142owieka" + ], + "RACE": [ + "indian_airlines", + "walijczycy", + "polinezyjski", + "japo\u0144czycy", + "francuz", + "white", + "francuzka", + "anglicy", + "francuzi", + "turek", + "amerykanie", + "holendrzy" + ], + "BIO_CHEM_ENTITY": [ + "staro\u015bwiecki", + "chlorek_magnezu", + "mleczan", + "karbamoilofosforan", + "monoaminooksydaza", + "polilaktyd" + ], + "PERSON_PRONOUN": [ + "panie", + "i", + "he", + "our", + "we", + "siebie", + "me", + "my", + "sobie", + "kopalnia" + ], + "DATE": [ + "zaduszki", + "bezrybie", + "popielec", + "wiecz\u00f3r_trzech_kr\u00f3li", + "o_czasie", + "kaniku\u0142a", + "ksi\u0119\u017cyc_w_nowiu", + "nocka", + "lorenc", + "sommersolverv", + "m_c", + "dwudziestopi\u0119ciolecie", + "cykl_miesi\u0105czkowy", + "antrakt", + "nazajutrz", + "osobogodzina", + "wniebowzi\u0119cie_naj\u015bwi\u0119tszej_maryi_panny", + "drugi_dzie\u0144_\u015bwi\u0105t", + "prima_aprilis" + ], + "POLITICAL_PARTY": [ + "the_opposition", + "partia_demokratyczno_republika\u0144ska", + "farerska_partia_ludowa", + "kuomintang", + "australijska_partia_pracy", + "partia_narodowa", + "ameryka\u0144ska_partia_wig\u00f3w", + "farerska_partia_socjaldemokratyczna", + "narodowosocjalistyczna_niemiecka_partia_robotnik\u00f3w", + "partia_demokratyczna", + "bia\u0142oruska_partia_agrarna", + "partia_ludowa", + "partia_liberalna" + ], + "LAW": [ + "stan_wojenny", + "praworz\u0105dno\u015b\u0107", + "ne_bis_in_idem", + "najwy\u017cszy_s\u0105d", + "federal_bureau_of_investigation", + "prawnicy" + ], + "FAC": [ + "czarodziejska_g\u00f3ra", + "papeda", + "ciastkarnia", + "most_wisz\u0105cy", + "arnold_sch\u00f6nberg", + "atakama", + "san_sebasti\u00e1n", + "papiernia", + "urz\u0105d_celny", + "podstaw\u00f3wka", + "gornoa\u0142tajsk", + "kamienica", + "saint_lucia", + "j\u00f3zef_z_nazaretu", + "komenda", + "wysoka_porta", + "szko\u0142a_podstawowa", + "xixia", + "wieczorem", + "komisariat_policji", + "kubu\u015b_puchatek" + ], + "UNION": [ + "mi\u0119dzynarodowy_zwi\u0105zek_telekomunikacyjny", + "samorz\u0105d_studencki" + ], + "EVENT": [ + "i_wojna_w_zatoce_perskiej", + "sing_sing", + "fleur_de_lis" + ], + "TITLE": [ + "ms" + ], + "ANAT": [ + "napinacz" + ], + "ner_regexes": [ + [ + "PERSON", + "\\D+ \\D+|\\D+ \\D+|\\D+ \\D+|\\D+ \\D+|\\D+ \\D+|\\D+ \\D+ \\D+|\\D+ \\D+|\\D+ \\D+ \\D+", + false, + [] + ] + ], + "FIRST_NAME_FEMALE": [ + "roksana", + "liwia", + "dorota", + "gaja", + "ada", + "bianka", + "marianna", + "ida", + "sara", + "janina", + "anna_maria", + "dagmara", + "sonia", + "olga", + "kaja", + "kalina", + "angelika", + "rozalia", + "anita", + "inga", + "blanka", + "natasza", + "marika", + "malwina", + "julita", + "karina", + "r\u00f3\u017ca", + "lidia", + "sylwia", + "el\u017cbieta", + "marcelina", + "anastazja", + "apolonia", + "justyna", + "aniela", + "agnieszka", + "kornelia", + "aurelia", + "ewa", + "nicole", + "monika", + "urszula", + "klara", + "julianna", + "krystyna", + "ewelina", + "sandra", + "melania", + "kamila", + "adrianna", + "tola", + "nela", + "eliza" + ], + "FIRST_NAME_MALE": [ + "micha\u0142", + "igor", + "artur", + "antoni", + "mieszko", + "rafa\u0142", + "aleks", + "oliwier", + "fryderyk", + "aleksander", + "grzegorz", + "leon", + "damian", + "kacper", + "daniel", + "andrzej", + "mi\u0142osz", + "borys", + "dariusz", + "hubert", + "kazimierz", + "eryk", + "marcel", + "fabian", + "alex", + "b\u0142a\u017cej", + "maksymilian", + "natan", + "maciej", + "gabriel", + "ryszard", + "jacek", + "tymon", + "julian", + "ernest", + "dominik", + "emil", + "j\u00f3zef", + "nataniel", + "iwo", + "mateusz", + "ksawery", + "krystian", + "kamil", + "szymon", + "pawe\u0142", + "olgierd", + "jan", + "kornel", + "cezary", + "ignacy", + "cyprian", + "karol", + "arkadiusz", + "\u0142ukasz", + "tobiasz", + "piotr", + "konrad", + "nikodem", + "konstanty", + "wojciech", + "patryk", + "oskar", + "maurycy", + "tymoteusz", + "tadeusz", + "jeremi", + "kajetan", + "bartek", + "marek", + "adam", + "gustaw", + "franciszek", + "sebastian", + "wiktor", + "rados\u0142aw", + "adrian", + "maks", + "filip", + "witold", + "mariusz", + "krzysztof", + "norbert", + "stefan", + "robert", + "stanis\u0142aw", + "jerzy", + "juliusz", + "j\u0119drzej", + "marcin", + "miko\u0142aj", + "dawid", + "olaf", + "tomasz", + "albert", + "alan", + "bruno", + "przemys\u0142aw", + "leonard", + "jakub" + ], + "PREFIX_FEMALE": [ + "pani" + ], + "PREFIX_MALE": [ + "pan" + ], + "FIRST_NAME": [ + "micha\u0142", + "igor", + "liwia", + "artur", + "dorota", + "antoni", + "mieszko", + "rafa\u0142", + "aleks", + "sara", + "sonia", + "olga", + "oliwier", + "fryderyk", + "angelika", + "aleksander", + "inga", + "marika", + "grzegorz", + "leon", + "damian", + "kacper", + "daniel", + "andrzej", + "mi\u0142osz", + "borys", + "kornelia", + "dariusz", + "hubert", + "nicole", + "klara", + "julianna", + "kazimierz", + "sandra", + "melania", + "eryk", + "nela", + "eliza", + "marcel", + "fabian", + "alex", + "b\u0142a\u017cej", + "maksymilian", + "bianka", + "natan", + "maciej", + "gabriel", + "ryszard", + "jacek", + "tymon", + "anita", + "rozalia", + "julian", + "ernest", + "natasza", + "dominik", + "emil", + "j\u00f3zef", + "karina", + "julita", + "r\u00f3\u017ca", + "apolonia", + "nataniel", + "iwo", + "aniela", + "mateusz", + "ksawery", + "krystian", + "aurelia", + "kamil", + "ewa", + "szymon", + "monika", + "urszula", + "pawe\u0142", + "ewelina", + "adrianna", + "olgierd", + "jan", + "kornel", + "gaja", + "cezary", + "ida", + "anna_maria", + "ignacy", + "cyprian", + "karol", + "arkadiusz", + "\u0142ukasz", + "tobiasz", + "piotr", + "konrad", + "nikodem", + "konstanty", + "wojciech", + "patryk", + "oskar", + "maurycy", + "malwina", + "tymoteusz", + "tadeusz", + "lidia", + "el\u017cbieta", + "anastazja", + "agnieszka", + "jeremi", + "kajetan", + "bartek", + "marek", + "adam", + "gustaw", + "franciszek", + "sebastian", + "wiktor", + "blanka", + "roksana", + "rados\u0142aw", + "adrian", + "maks", + "ada", + "marianna", + "filip", + "witold", + "janina", + "dagmara", + "mariusz", + "krzysztof", + "norbert", + "stefan", + "kaja", + "kalina", + "robert", + "stanis\u0142aw", + "jerzy", + "juliusz", + "j\u0119drzej", + "marcin", + "miko\u0142aj", + "sylwia", + "dawid", + "olaf", + "tomasz", + "justyna", + "albert", + "alan", + "bruno", + "krystyna", + "kamila", + "przemys\u0142aw", + "marcelina", + "tola", + "leonard", + "jakub" + ], + "LAST_NAME": [ + "doe" + ], + "LAST_NAME_MALE": [], + "LAST_NAME_FEMALE": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "opatka": "abas", + "przeorysza": "abas", + "ksieni": "abas", + "ciotka": "wujcio", + "ciocia": "stryj", + "pi\u0119kno\u015b\u0107": "dandys", + "narzeczona": "narzeczony", + "niewiasta": "nowo\u017ceniec", + "panna_m\u0142oda": "pan_m\u0142ody", + "bizneswomen": "cz\u0142owiek_interesu", + "biznesmenka": "przedsi\u0119biorca", + "kobieta_interesu": "cz\u0142owiek_interes\u00f3w", + "businesswoman": "cz\u0142owiek_interesu", + "bizneswoman": "businessman", + "piskl\u0119": "gaur", + "kowbojka": "gaucho", + "dziewczynka": "son", + "c\u00f3ra": "zoon", + "filia": "ch\u0142opak", + "c\u00f3rka": "zoon", + "ksi\u0119\u017cna": "ksi\u0105\u017c\u0119", + "cesarzowa": "imperator", + "imperatorowa": "husarz_w\u0142adca", + "samica": "cz\u0142owiek_p\u0142ci_m\u0119skiej", + "cz\u0142owiek_p\u0142ci_\u017ce\u0144skiej": "male", + "\u017ce\u0144ski": "m\u0119ski", + "oblubienica": "oblubieniec", + "gal": "ch\u0142op", + "dziewcz\u0119": "facio", + "dziewa": "go\u015b\u0107", + "guwernerka": "gubernator", + "guwernantka": "regulator", + "wnuczka": "wnuczek", + "nine": "dziadek", + "jej": "sw\u00f3j", + "heroina": "rycerzyk", + "bohaterka": "p\u00f3\u0142b\u00f3g", + "heroska": "bohaterka", + "ober\u017cystka": "karczmarz", + "pani_domu": "intruz", + "gospodyni": "amfitrion", + "markiza": "margrabia", + "masa\u017cystka": "masa\u017cysta", + "chybi\u0107": "ja\u015bniepan", + "nie_trafi\u0107": "ja\u015bniepan", + "spud\u0142owa\u0107": "ja\u015bniepan", + "metresa": "w\u0142adca", + "flama": "komodor", + "kochanica": "w\u0142adca", + "mi\u0142o\u015bnica": "komodor", + "mam": "rodziciel", + "matrix": "rodziciel", + "ma\u0107": "ojciec", + "bh": "mgr", + "mw": "mgr", + "ms": "mgr", + "siostra": "towarzysz", + "mniszka": "mnich", + "moja": "mnich", + "zakonnica": "zakon_mniszy", + "siostra_zakonna": "zakon_mniszy", + "nun": "monako", + "policjantka": "policjant", + "kap\u0142anka": "kap\u0142an", + "princessa": "regulus", + "ksi\u0119\u017cniczka": "regulus", + "kr\u00f3lowa_matka": "damka", + "kr\u00f3l\u00f3wka": "king", + "drag_queen": "king", + "kr\u00f3lowa": "king", + "hetman": "indra", + "queens": "ksi\u0119ga_kr\u00f3lewska", + "stara_panna": "kawaler", + "rzeczniczka": "rzecznik_prasowy", + "pasierbica": "pasierb", + "macocha": "ojczym", + "stewardessa": "steward", + "stewardesa": "steward", + "hostessa": "ochmistrz", + "kelnerka": "garson", + "wdowa": "wdowiec", + "\u017cona": "bierka", + "bean": "m\u0119\u017cczyzna", + "\u015blubna": "m\u0105\u017c", + "ma\u0142\u017conka": "\u015blubny", + "bia\u0142ka": "osoba", + "kobieta": "m\u0119\u017cczyzna", + "kobita": "osoba", + "stara": "istota_ludzka", + "garson": "dziewa", + "fant": "dziewa", + "ch\u0142opak": "dziewa" + }, + "other_gender_swap": { + "one": "jej", + "has": "jej", + "lia": "jej", + "he": "one", + "jej": "lia" + }, + "en_pronoun2gender": { + "they": [ + "biseksualny", + "transgen", + "homoseksualny", + "biseksualista", + "homoseksualista", + "transgenderyzm", + "gej" + ], + "he": [ + "go\u015b\u0107", + "m\u0119ski", + "facio", + "d\u017centelmen", + "garson", + "m\u0119\u017cczyzna", + "bierka", + "istota_ludzka", + "ch\u0142op", + "gentleman", + "ch\u0142opak", + "osoba", + "ch\u0142opczyk", + "little_boy", + "cz\u0142owiek_p\u0142ci_m\u0119skiej", + "samiec", + "male", + "go\u015bciu", + "gwido", + "gaur", + "fant" + ], + "she": [ + "lesbijka", + "homoseksualistka", + "spud\u0142owa\u0107", + "\u017cona", + "p\u0142e\u0107_pi\u0119kna", + "\u017ce\u0144ski", + "cz\u0142owiek_p\u0142ci_\u017ce\u0144skiej", + "lesbijska", + "s\u0142aba_p\u0142e\u0107", + "chybi\u0107", + "samica", + "lesbijski", + "bean", + "stara", + "dziewcz\u0119", + "gal", + "kobita", + "kobieta", + "bimba", + "panienka", + "dziewa", + "bia\u0142ka", + "dziewczynka", + "nie_trafi\u0107" + ] + }, + "en_pronoun2pronoun": { + "he": [ + "he", + "lia", + "sw\u00f3j", + "jego" + ], + "she": [ + "jej" + ], + "they": [ + "one", + "lia", + "jej", + "has", + "epi" + ], + "it": [ + "si\u0119", + "\u017ce", + "taj", + "i\u017c" + ] + }, + "en_pronoun2title": {}, + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/pms.json b/data_tooling/pii_processing/ontology/data/pms.json new file mode 100644 index 0000000..86c443a --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/pms.json @@ -0,0 +1,408 @@ +{ + "PUBLIC_FIGURE": [ + "benjamin_franklin", + "akira_kurosawa", + "heinrich_hertz", + "giovanni_boccaccio", + "thomas_bayes", + "johann_bernoulli", + "georges_simenon", + "maria_callas", + "pero_i_\u00ebd_russia", + "john_herschel", + "douglas_macarthur", + "winston_churchill", + "johannes_diderik_van_der_waals", + "isaac_newton", + "victor_hugo", + "edwin_hubble", + "colette", + "edward_gibbon", + "saint_louis", + "george_orwell", + "richard_wagner", + "marie_curie", + "francis_galton", + "michael_jackson", + "carl_sandburg", + "thomas_hobbes", + "galileo_galilei", + "edmund_hillary", + "vincent_van_gogh", + "john_ruskin", + "costantin", + "giuseppe_verdi", + "karl_jaspers", + "konrad_adenauer", + "norbert_wiener", + "mark_rothko", + "maurice_chevalier", + "frank_sinatra", + "henri_matisse", + "louis_pasteur", + "somateria_spectabilis", + "saladin", + "sarah_bernhardt", + "luigi_pirandello", + "charles_de_gaulle", + "rudolf_bultmann", + "charles_lindbergh", + "vincenzo_bellini", + "ludwig_wittgenstein", + "august_strindberg", + "thomas_mann", + "dante_alighieri", + "samuel_de_champlain", + "giacomo_puccini", + "herbert_marcuse", + "paul_verlaine", + "james_dean", + "alessandro_manzoni", + "nicolas_poussin", + "andrea_mantegna", + "oscar_wilde", + "george_kennan", + "francis_bacon", + "james_brown", + "charles_baudelaire", + "immanuel_kant", + "james_franck", + "william_crookes", + "johannes_kepler", + "william_s_burroughs", + "scott_joplin", + "canberra", + "robert_lowell", + "san_martin", + "gabriel_lippman", + "graham_greene", + "william_herschel", + "montesquieu", + "niels_bohr", + "henry_fielding", + "bertrand_russell", + "michael_faraday", + "john_d_rockefeller", + "jan_tinbergen", + "walt_disney", + "crist\u00f2fo_colomb", + "friedrich_engels", + "jane_austen", + "gustav_mahler", + "phil_collins", + "ian_fleming", + "richard_feynman", + "wolfgang_pauli", + "marcel_proust", + "paul_hindemith", + "john_dowland", + "william_golding", + "peter_stuyvesant", + "alfred_nobel", + "nicolaus_cop\u00e8rnich", + "caravaggio", + "daniel_bernoulli", + "joseph_henry", + "henri_bergson", + "josef_hoffmann", + "gottfried_leibniz", + "pierre_corneille", + "hans_christian_andersen", + "pieter_zeeman", + "pablo_picasso", + "l_ron_hubbard", + "kurt_weill", + "christiaan_huygens", + "hector_berlioz", + "adam_smith", + "william_james", + "karl_marx", + "friedrich_nietzsche", + "sandro_botticelli", + "nikola_tesla", + "al_capone", + "le_corbusier", + "carlo_goldoni", + "john_locke", + "alexis_carrel", + "henry_james", + "helen_keller", + "ingrid_bergman", + "jean_piaget", + "ludwig_boltzmann", + "leopold_kronecker", + "benjamin_thompson", + "adolf_hitler", + "alfred_stieglitz", + "joseph_haydn", + "george_boole", + "robert_boyle", + "christopher_isherwood", + "fritz_kreisler", + "martin_heidegger", + "george_lucas", + "andrew_jackson", + "edith_wharton", + "louis_armstrong", + "steven_spielberg", + "thomas_hardy", + "giuseppe_garibaldi", + "alexandre_dumas", + "robert_brown", + "johannes_gutenberg", + "giambattista_marino", + "amerigo_vespucci", + "jean_de_la_fontaine", + "robert_hooke", + "karl_popper", + "peter_o'toole", + "joseph_conrad", + "edmund_halley", + "peter_paul_rubens", + "mahatma_gandhi", + "jules_verne", + "charlie_chaplin", + "miles_davis", + "stanley_kubrick", + "william_gilbert", + "james_watt", + "ronald_reagan", + "david_hilbert", + "oliver_cromwell", + "martin_luther_king", + "gustav_hertz", + "ernest_hemingway", + "nelson_mandela", + "heinrich_himmler", + "roald_amundsen", + "sherwood_anderson", + "charles_dickens", + "jacques_offenbach", + "federico_fellini", + "andrew_carnegie", + "franz_schubert", + "simon_pero", + "georges_cuvier", + "walter_scott", + "robert_browning", + "jonathan_swift", + "walter_gropius", + "albert_einstein", + "thomas_edison", + "claude_bernard", + "wilhelm_ostwald" + ], + "PLANT": [ + "lilium_martagon", + "verbascum_thapsus", + "veronica_beccabunga", + "liriodendron_tulipifera", + "claviceps_purpurea", + "sarcoscypha_coccinea", + "philadelphus_coronarius", + "langermannia_gigantea", + "anthriscus_cerefolium", + "cyclamen_purpurascens", + "arctostaphylos_alpinus", + "abies_grandis", + "laurus_nobilis", + "sorbus_torminalis", + "magnolia_grandiflora", + "coprinus_comatus", + "prunus_laurocerasus", + "salix_triandra", + "acer_campestre", + "gentiana_lutea", + "taxus_baccata", + "valerianella_locusta", + "silene_dioica", + "diplotaxis_tenuifolia", + "ranunculus_ficaria", + "veronica_officinalis", + "prunus_cerasus", + "acacia_dealbata", + "agrimonia_eupatoria", + "plantago_lanceolata", + "salix_viminalis", + "juniperus_virginiana", + "eucalyptus_globulus", + "citrus_aurantium", + "barbarea_vulgaris", + "cortinarius_violaceus", + "prunus_armeniaca", + "salix_fragilis", + "amanita_muscaria", + "sanguin", + "stellaria_media", + "helianthus_tuberosus", + "lepista_nuda", + "prunus_domestica", + "tricholoma_aurantium", + "muscicapa_striata", + "acer_platanoides", + "erica_carnea", + "salvia_pratensis", + "urtica_dioica", + "agaricus_campestris", + "platanus_hispanica", + "sorbus_aucuparia", + "acer_pseudoplatanus", + "polyporus_squamosus", + "fagus_sylvatica", + "salix_pentandra", + "crataegus_laevigata", + "acacia_melanoxylon", + "boletus_edulis", + "citrus_deliciosa", + "taraxacum_officinale", + "cerastium_alpinum", + "pleurotus_ostreatus", + "pseudotsuga_menziesii", + "heracleum_sphondylium", + "lathyrus_sylvestris", + "marasmius_oreades", + "sophora_japonica", + "gentiana_acaulis", + "galium_verum", + "populus_nigra", + "alnus_glutinosa", + "cypripedium_calceolus", + "viola_odorata", + "ulmus_hollandica", + "plantago_media", + "ranunculus_acris" + ], + "LOCATION": [ + "plantago_lanceolata", + "trifolium_pratense", + "dryocopus_martius", + "mar_n\u00e8ir", + "stat_un\u00ec_d_am\u00e9rica", + "piet_mondrian", + "sint_maarten", + "sass\u00f2nia_anhalt", + "pieris_rapae", + "plantago_media", + "mar_d\u00ebl_n\u00f2rd", + "alnus_glutinosa", + "nymphalis_polychloros", + "sri_lanka", + "the_rolling_stones", + "pieris_brassicae", + "prunus_avium" + ], + "ORG": [ + "santa_luss\u00eca", + "the_who", + "san_francisco", + "ca_bianca", + "ai", + "cap_verd", + "rabindranath_tagore", + "part\u00ec_pol\u00ectich", + "nic\u00f2la_\u00ebd_myra", + "los_angeles", + "nato", + "cesa_cat\u00f2lica", + "taoism", + "hirundo_rustica", + "s\u00e3o_tom\u00e9", + "cicles" + ], + "PRODUCT": [ + "justin_bieber" + ], + "RELIGION": [ + "zen", + "confucianism", + "jainism", + "islam" + ], + "LANGUAGE": [ + "t\u00f2nga", + "frans\u00e8is", + "oland\u00e8is", + "ido" + ], + "DISEASE": [ + "vair\u00f2le", + "mania", + "colera", + "materialism", + "radiassion", + "rossaso" + ], + "ANIMAL": [ + "lagopus_mutus", + "sitta_europaea", + "pieris_brassicae", + "giari", + "singial", + "banteng", + "branta_bernicla", + "alle_alle", + "primula_vulgaris" + ], + "GPE": [ + "dar_es_salaam", + "ca_bianca", + "sint_maarten", + "franca_cont\u00e0", + "drit_\u00ebd_l_\u00f2m", + "s\u00e3o_tom\u00e9", + "simon_pero", + "neuv_testament" + ], + "JOB": [ + "temp", + "the_police", + "the_guardian" + ], + "FOOD": [ + "cicles", + "pinot_noir", + "bagna", + "sonchus_oleraceus", + "juglans_regia" + ], + "GENDER": [ + "men" + ], + "POLITICAL_PARTY": [ + "part\u00ec_nasista" + ], + "FAC": [ + "pero_i_\u00ebd_russia" + ], + "PERSON": [ + "boletus_edulis" + ], + "RELIGION_MEMBER": [ + "mon" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": {}, + "other_gender_swap": {}, + "en_pronoun2gender": { + "she": [ + "fumna", + "fomna" + ] + }, + "en_pronoun2pronoun": { + "she": [ + "chila" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/ppl.json b/data_tooling/pii_processing/ontology/data/ppl.json new file mode 100644 index 0000000..63b219d --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/ppl.json @@ -0,0 +1,81 @@ +{ + "ANIMAL": [ + "mistun", + "masat", + "mututzin" + ], + "GENDER": [ + "siwat" + ], + "PERSON_PRONOUN": [ + "i", + "tehemet", + "tejemet", + "nech", + "metzin", + "tech" + ], + "GPE": [ + "shiktal" + ], + "PUBLIC_FIGURE": [ + "a", + "i" + ], + "DISEASE": [ + "cucua", + "kukua" + ], + "ORG": [ + "nimetztasujta" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "yaja": "yaha", + "yaha": "yaja" + }, + "other_gender_swap": { + "yejemet": "yaha", + "yehemet": "yaja", + "yaja": "yehemet", + "yaha": "yehemet" + }, + "en_pronoun2gender": { + "she": [ + "cihuat", + "kak", + "siwat" + ] + }, + "en_pronoun2pronoun": { + "he": [ + "yaja", + "yaha", + "neki" + ], + "she": [ + "yaja", + "yaha" + ], + "they": [ + "yehemet", + "yejemet" + ], + "it": [ + "yaja", + "esti", + "yaha" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/prg.json b/data_tooling/pii_processing/ontology/data/prg.json new file mode 100644 index 0000000..03da293 --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/prg.json @@ -0,0 +1,36 @@ +{ + "ANIMAL": [ + "zambrus", + "gabawo", + "wissambris" + ], + "PUBLIC_FIGURE": [ + "nadruw\u012bsn\u0101" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "swestro": "br\u0101ti" + }, + "other_gender_swap": {}, + "en_pronoun2gender": { + "he": [ + "w\u012brs" + ] + }, + "en_pronoun2pronoun": { + "it": [ + "stas" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/pro.json b/data_tooling/pii_processing/ontology/data/pro.json new file mode 100644 index 0000000..60765ec --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/pro.json @@ -0,0 +1,55 @@ +{ + "JOB": [ + "creator", + "messatger", + "coadjutor", + "pastor", + "bisbe" + ], + "DISEASE": [ + "cremadura", + "corn" + ], + "ANIMAL": [ + "duc", + "cavec" + ], + "LANGUAGE": [ + "engles" + ], + "PUBLIC_FIGURE": [ + "speran\u00e7a" + ], + "RELIGION_MEMBER": [ + "frayre" + ], + "GPE": [ + "novel_testament" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "domna": "human" + }, + "other_gender_swap": {}, + "en_pronoun2gender": { + "he": [ + "human" + ], + "she": [ + "donzella", + "domna" + ] + }, + "en_pronoun2pronoun": {}, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/ps.json b/data_tooling/pii_processing/ontology/data/ps.json new file mode 100644 index 0000000..83e64bb --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/ps.json @@ -0,0 +1,81 @@ +{ + "POLITICAL_PARTY": [ + "\u06ab\u0648\u0646\u062f" + ], + "PRODUCT": [ + "\u0628\u0631\u064a\u062a\u0627\u0646\u064a\u0627", + "\u0648\u06ab\u0693\u0646\u064a\u0632_\u062d\u0642\u0648\u0642" + ], + "ORG": [ + "\u069a\u0648\u0648\u0646\u0681\u06cc", + "\u0698\u0627\u0648\u0644\u0647", + "\u067e\u0648\u0633\u062a\u0647_\u062e\u0627\u0646\u0647", + "\u0633\u0648\u062f\u0627\u06ab\u0631\u064a" + ], + "DISEASE": [ + "\u0646\u0627\u0631\u0648\u063a\u064a" + ], + "SOC_ECO_CLASS": [ + "\u06a9\u0631\u0646\u0647" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "\u0627\u062a\u0644\u0647": "\u0627\u062a\u0644", + "\u0645\u0644\u0648\u06a9\u0647": "\u067e\u0627\u062f\u0634\u0627", + "\u0647\u063a\u0647": "\u062f\u06cc", + "\u062f\u0627": "\u062f\u06cc", + "\u062e\u0648\u0631": "\u0648\u0631\u0648\u0631", + "\u069a\u0681\u0647": "\u0633\u0693\u06cc", + "\u0648\u0631\u062a\u064a\u0646\u0647": "\u0645\u06d0\u0693\u0647", + "\u0632\u0648\u062c\u0647": "\u062e\u0627\u0648\u0646\u062f", + "\u0648\u0648\u0693\u06a9\u06cc": "\u0648\u0648\u0693\u0643\u06cd", + "\u06a9\u0648\u0631": "\u0648\u0648\u0693\u0643\u06cd", + "\u0647\u0644\u06a9": "\u0646\u062c\u0644\u06cd" + }, + "other_gender_swap": { + "\u062f\u0648\u06cc": "\u0647\u063a\u0647", + "\u0647\u063a\u0648\u06cc": "\u0647\u063a\u0647", + "\u062f\u06cc": "\u0647\u063a\u0648\u06cc", + "\u0647\u063a\u0647": "\u0647\u063a\u0648\u06cc", + "\u062f\u0627": "\u0647\u063a\u0648\u06cc" + }, + "en_pronoun2gender": { + "he": [ + "\u0646\u0631", + "\u0647\u0644\u06a9", + "\u06a9\u0648\u0631", + "\u0648\u0648\u0693\u06a9\u06cc", + "\u0645\u0693\u0647" + ], + "she": [ + "\u0648\u0648\u0693\u0643\u06cd", + "\u0646\u062c\u0644\u06cd", + "\u069a\u0681\u0647" + ] + }, + "en_pronoun2pronoun": { + "he": [ + "\u0647\u063a\u0647", + "\u062f\u06cc" + ], + "she": [ + "\u0647\u063a\u0647", + "\u062f\u0627" + ], + "they": [ + "\u0647\u063a\u0648\u06cc", + "\u062f\u0648\u06cc" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/pt.json b/data_tooling/pii_processing/ontology/data/pt.json new file mode 100644 index 0000000..d918374 --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/pt.json @@ -0,0 +1,4481 @@ +{ + "PUBLIC_FIGURE": [ + "lawrence_durrell", + "henry_cavendish", + "matthew_arnold", + "benjamin_franklin", + "martin_buber", + "akira_kurosawa", + "niccolo_paganini", + "noah_webster", + "jean_genet", + "john_knox", + "heinrich_hertz", + "roger_williams", + "anne_bront\u00eb", + "giovanni_boccaccio", + "cornelius_vanderbilt", + "huntington", + "rudolf_steiner", + "thomas_wolfe", + "thomas_bayes", + "ben_hogan", + "johann_bernoulli", + "max_bruch", + "james_doolittle", + "leonard_bernstein", + "sibelius", + "julio_verne", + "che_guevara", + "georges_simenon", + "c", + "i_a_richards", + "ren\u00e9_descartes", + "thomas_hodgkin", + "fleming", + "john_barth", + "edward_albee", + "dorothy_parker", + "zhukov", + "maria_callas", + "william_walton", + "henrik_ibsen", + "roald_am\u00fandsen", + "mary_shelley", + "franz_werfel", + "marcello_malpighi", + "peter_lorre", + "karl_baedeker", + "maria_antonieta", + "david_livingstone", + "eduard_buchner", + "david_smith", + "john_herschel", + "gauss", + "andrzej_wajda", + "jan_van_eyck", + "carl_rogers", + "george_balanchine", + "richard_burton", + "mais_completo", + "andrija_mohorovi\u010di\u0107", + "c\u00e9sar_franck", + "douglas_macarthur", + "mary_wollstonecraft", + "thomas_reid", + "john_jacob_astor", + "anna_pavlova", + "winston_churchill", + "johannes_diderik_van_der_waals", + "mendelssohn", + "b", + "s\u00e3o_crist\u00f3v\u00e3o", + "conrad_aiken", + "karl_landsteiner", + "ivan_pavlov", + "dmitri_shostakovich", + "paul_mccartney", + "alfredo", + "richard_smalley", + "andrew_marvell", + "terry_pratchett", + "k", + "stephen_king", + "francis_crick", + "max_m\u00fcller", + "john_trumbull", + "topete", + "van_gogh", + "joseph_greenberg", + "isaac_newton", + "alfred_eisenstaedt", + "victor_hugo", + "colette", + "milton_friedman", + "amy_lowell", + "edward_gibbon", + "mezzosoprano", + "schiaparelli", + "jefferson_davis", + "arafat", + "cass_gilbert", + "george_stephenson", + "john_glenn", + "john_webster", + "john_davis", + "george_burns", + "george_harrison", + "erwin_schrodinger", + "peter_minuit", + "h\u00e9ming", + "george_orwell", + "ronald_norrish", + "maximiano", + "arthur_koestler", + "hernan_cortes", + "richard_wagner", + "williams", + "thornton_wilder", + "pancho_villa", + "bed\u0159ich_smetana", + "leopold_stokowski", + "o_piedoso", + "rebecca_west", + "marie_curie", + "antomio", + "francis_galton", + "mary_martin", + "arnold_schonberg", + "richard_roberts", + "michael_jackson", + "louis_jolliet", + "carl_sandburg", + "elisabete", + "thomas_hobbes", + "charles_gounod", + "edward_weston", + "imperadores_romanos", + "el_greco", + "roberto", + "samuel_beckett", + "david", + "jane_goodall", + "der_fliegende_holl\u00e4nder", + "john_donne", + "chaim_weizmann", + "robert_l_mills", + "andrea_guarneri", + "robert_koch", + "joseph_goebbels", + "george_eastman", + "john_steinbeck", + "ant\u00f3nio", + "erich_mendelsohn", + "ali_bab\u00e1", + "edmund_hillary", + "vincent_van_gogh", + "richard_hooker", + "w", + "william_hazlitt", + "martina_navr\u00e1tilov\u00e1", + "josef_stalin", + "john_ruskin", + "franz_lehar", + "robert_burns", + "carl_anderson", + "marduque", + "thomas_paine", + "bari", + "liliuokalani", + "francis_beaumont", + "greg\u00f3rio", + "steven_weinberg", + "p", + "mary_pickford", + "hans_fischer", + "emiliano_zapata", + "tom\u00e1s", + "karl_barth", + "willem_einthoven", + "constantino", + "phil_anderson", + "thomas_willis", + "duarte", + "bernard_malamud", + "samuel_johnson", + "jesus", + "allen_iverson", + "anne_hutchinson", + "louise_nevelson", + "giuseppe_verdi", + "walter_lippmann", + "e", + "karl_jaspers", + "franz_leh\u00e1r", + "emily_bronte", + "beethoven", + "hideki_yukawa", + "konrad_adenauer", + "john_l_lewis", + "bush", + "marianne_moore", + "norbert_wiener", + "agripina", + "john_masefield", + "horatio_nelson", + "mark_rothko", + "fran\u00e7ois_couperin", + "n\u00e3o_aplic\u00e1vel", + "maurice_chevalier", + "gottlieb_daimler", + "catarina", + "o_cid", + "frank_sinatra", + "fran\u00e7ois_rabelais", + "fran\u00e7ois_duvalier", + "abel_tasman", + "katharine_hepburn", + "o_m\u00e1rtir", + "henri_matisse", + "louis_pasteur", + "berra", + "j", + "richard_strauss", + "stephen_decatur", + "leslie_howard", + "pushkin", + "mahalia_jackson", + "john_ford", + "stephen_foster", + "alphonse_bertillon", + "katherine_mansfield", + "gertrude_stein", + "j_b_s_haldane", + "sarah_bernhardt", + "george_beadle", + "crist\u00f3v\u00e3o_colombo", + "v", + "zezinho", + "philip_marlowe", + "luigi_pirandello", + "t_s_eliot", + "e_g_marshall", + "hank_williams", + "igor_stravinski", + "rube_goldberg", + "dorothea_lange", + "s\u00e3o_patr\u00edcio", + "james_thurber", + "charles_de_gaulle", + "paul_von_hindenburg", + "y", + "nikolai_gogol", + "henry_moore", + "holden", + "mary_mallon", + "andr\u00e9_maurois", + "charles_lindbergh", + "vincenzo_bellini", + "samuel_barber", + "tobias_smollett", + "f", + "john_jay", + "ludwig_wittgenstein", + "august_strindberg", + "stalin", + "thomas_mann", + "b\u00e9la_bart\u00f3k", + "alla_nazimova", + "charles_goodyear", + "dante_alighieri", + "margot_fonteyn", + "telecomando", + "peter_pan", + "james_tobin", + "john_irving", + "samuel_de_champlain", + "giacomo_puccini", + "edward_fitzgerald", + "fridtjof_nansen", + "louis_braille", + "herbert_marcuse", + "mungo_park", + "benedict_arnold", + "paul_verlaine", + "q", + "robert_johnson", + "niccol\u00f2_paganini", + "james_dean", + "robert", + "bronis\u0142aw_malinowski", + "o_velho", + "carl_von_clausewitz", + "theodor_schwann", + "max_beerbohm", + "leon_tr\u00f3tski", + "alessandro_manzoni", + "joseph_priestley", + "pedro_abelardo", + "hal", + "nicolas_poussin", + "andrea_mantegna", + "joseph_pulitzer", + "george_huntington", + "jim_corbett", + "james_naismith", + "oscar_wilde", + "gilberto", + "philip_roth", + "j_d_salinger", + "henry", + "lawrence", + "jules_massenet", + "mohammed_omar", + "richard_trevithick", + "heinrich_schliemann", + "eli_whitney", + "madrigueira", + "jackson", + "the_court_jester", + "a_e", + "\u00e9douard_manet", + "serguei_prokofiev", + "johannes_peter_m\u00fcller", + "laurence_olivier", + "cesar_b\u00f3rgia", + "pierre_larousse", + "christiaan_eijkman", + "gustavo", + "adolf_eichmann", + "marilyn_horne", + "tribunais", + "xerez", + "francis_bacon", + "pete_seeger", + "john_wycliffe", + "joseph_heller", + "a", + "o_jovem", + "morris", + "peter_carl_goldmark", + "saladino", + "peter_brian_medawar", + "norman_rockwell", + "boris_spassky", + "sem_medo", + "james_brown", + "william_hogarth", + "charles_baudelaire", + "luigi_cherubini", + "david_ricardo", + "henri_labrouste", + "mary_leakey", + "charlie_parker", + "z", + "immanuel_kant", + "peter_carl_faberg\u00e9", + "james_franck", + "william_crookes", + "charles_de_montesquieu", + "james_meredith", + "samuel_gompers", + "aime\u00e9_mcpherson", + "nellie_bly", + "weber", + "lewis", + "warburg", + "alexandre_yersin", + "n", + "stephen_leacock", + "albert_schweitzer", + "georg_steller", + "jo\u00e3o_calvino", + "john_harvard", + "johann_friedrich_herbart", + "giulio_natta", + "cristov\u00e3o_colombo", + "justiniano", + "johannes_kepler", + "william_s_burroughs", + "david_hartley", + "max_planck", + "william_blake", + "t_e_lawrence", + "julio_iglesias", + "john_bardeen", + "arthur", + "sarah_vaughan", + "john_wilkes", + "william_byrd", + "william_henry", + "scott_joplin", + "carl_lewis", + "sarah_siddons", + "george_vancouver", + "cesar_franck", + "canberra", + "elias_canetti", + "jean_fran\u00e7ois_champollion", + "robert_lowell", + "johann_strauss", + "edward_jenner", + "limpador_de_chamin\u00e9s", + "oscar_robertson", + "moises", + "oliver_hardy", + "san_martin", + "cole_porter", + "benjamin_west", + "jean_luc_godard", + "graham_greene", + "frans_hals", + "edward", + "lars_onsager", + "willard", + "margaret_mitchell", + "leadbelly", + "lola_montez", + "jan_swammerdam", + "mary_mccarthy", + "busseta", + "john_walker", + "dvorak", + "al_hazen", + "william_herschel", + "joseph_black", + "marcus_whitman", + "mikhail_baryshnikov", + "francis_rous", + "montesquieu", + "arthur_rubinstein", + "leon_trotski", + "niels_bohr", + "sergei_rachmaninoff", + "kenneth_grahame", + "henry_fielding", + "bertrand_russell", + "katherine_anne_porter", + "michael_faraday", + "anthony_burgess", + "jan_tinbergen", + "robert_venturi", + "johnny_appleseed", + "o_flautista_de_hamelin", + "e_por_a\u00ed_fora", + "irving_berlin", + "fundamentado", + "bernard_baruch", + "rudolf_diesel", + "walt_disney", + "ben_jonson", + "peter", + "la_spezia", + "tom\u00e9", + "prima_dona", + "constantin_stanislavski", + "robert_benchley", + "b\u00e9la_bartok", + "ter_esperan\u00e7a", + "joseph_schumpeter", + "max_muller", + "gabriel_lippmann", + "steve_reich", + "lee", + "benny_goodman", + "ted_williams", + "friedrich_engels", + "valdivino", + "monges", + "jane_austen", + "charles_laughton", + "gustav_mahler", + "ed_sullivan", + "phil_collins", + "giosu\u00e8_carducci", + "robert_redford", + "jean_giraudoux", + "jack_dempsey", + "brindisi", + "ian_fleming", + "richard_feynman", + "wolfgang_pauli", + "padroeiro", + "theodore_dreiser", + "theodor_mommsen", + "andrew_huxley", + "marcel_proust", + "s\u00e3o_jorge", + "jessica_mitford", + "thomas_more", + "homo_heidelbergensis", + "paul_hindemith", + "elizabeth_taylor", + "thomas_chippendale", + "ilha_de_s\u00e3o_martinho", + "anne_sullivan", + "paul_robeson", + "arnold", + "thomas_middleton", + "john_dowland", + "hans_krebs", + "dag_hammarskj\u00f6ld", + "moli\u00e9re", + "galileu_galilei", + "daniel_jones", + "william_golding", + "robert_motherwell", + "william_caxton", + "john_milton", + "rudolf_serkin", + "peter_stuyvesant", + "ethel_merman", + "samuel_adams", + "albert_speer", + "james_baldwin", + "john_vanbrugh", + "s\u00e3o_pedro", + "indira_gandhi", + "jane_seymour", + "george_gershwin", + "alberto_giacometti", + "e_t_a_hoffmann", + "frank_whittle", + "alfred_nobel", + "jesse_owens", + "daniel_rutherford", + "marco_polo", + "macaca_nemestrina", + "john_fletcher", + "caravaggio", + "charlie_watts", + "m", + "charlotte_corday", + "marcel_marceau", + "allen_ginsberg", + "fred_zinnemann", + "daniel_bernoulli", + "guillaume_apollinaire", + "antoine_watteau", + "leonide_massine", + "joseph_henry", + "henri_bergson", + "jos\u00e9_ortega_y_gasset", + "edward_macdowell", + "josef_hoffmann", + "boris_karloff", + "gottfried_leibniz", + "pierre_corneille", + "heinrich_b\u00f6ll", + "patrick_white", + "saul_steinberg", + "aura_masda", + "bartholomew_roberts", + "daniel_morgan", + "hans_christian_andersen", + "peter_cooper", + "reich", + "william_morris", + "cary_grant", + "hideyo_noguchi", + "thomas", + "isaac_watts", + "ford", + "pieter_zeeman", + "glenn_miller", + "composi\u00e7\u00f5es_de_arnold_schoenberg", + "pablo_picasso", + "marian_anderson", + "natalie_wood", + "l_ron_hubbard", + "alan_hodgkin", + "thomas_moore", + "osman_i", + "kurt_weill", + "kieslowski", + "otto_hahn", + "lester_young", + "john_marshall", + "christiaan_huygens", + "hector_berlioz", + "hermann_g\u00f6ring", + "lucille_ball", + "paul_simon", + "claudio_monteverdi", + "fran\u00e7ois_mansart", + "o_soberbo", + "john_galsworthy", + "robert_robinson", + "o", + "adam_smith", + "william_james", + "joseph_joffre", + "imperador_romano", + "u", + "jean_harlow", + "henry_miller", + "karl_marx", + "paul_bunyan", + "friedrich_nietzsche", + "albrecht_d\u00fcrer", + "i", + "pedro", + "marco_ant\u00f4nio", + "davi", + "jimmy_durante", + "john_wesley", + "sandro_botticelli", + "carson_mccullers", + "ren\u00e9_magritte", + "seiji_ozawa", + "nikola_tesla", + "al_capone", + "jim_bowie", + "charles_barkley", + "billy_graham", + "robert_schumann", + "mel_gibson", + "le_corbusier", + "nicolau_maquiavel", + "carlo_goldoni", + "leo_delibes", + "john_locke", + "alexis_carrel", + "joseph_marie_jacquard", + "carreteiro", + "antonin_dvorak", + "henry_james", + "stephen_sondheim", + "louren\u00e7o", + "helen_keller", + "paul_dukas", + "ingrid_bergman", + "e_assim_por_diante", + "leonard_bloomfield", + "jane_jacobs", + "jean_piaget", + "william_congreve", + "franz_kline", + "henri_rousseau", + "paul_tillich", + "hilaire_belloc", + "o_escolhido", + "frank_stella", + "robert_southey", + "valentina_tereshkova", + "h_g_wells", + "walt_whitman", + "william_wyler", + "john_osborne", + "colin_powell", + "moliere", + "ludwig_boltzmann", + "carl_nielsen", + "joana_seymour", + "leopold_kronecker", + "richard_wright", + "benjamin_thompson", + "adolf_hitler", + "maria_mitchell", + "fritz_haber", + "archibald_macleish", + "peter_behrens", + "herman_snellen", + "alfred_stieglitz", + "joseph_haydn", + "s\u00e3o_david", + "stephen_spender", + "garfield", + "mais_cheio", + "jones", + "patr\u00edcio_da_irlanda", + "george_boole", + "paul_revere", + "daniel_boone", + "buffalo_bill", + "edvard_grieg", + "robert_boyle", + "arthur_laffer", + "edith_cavell", + "benedito", + "ralph_richardson", + "1", + "krzysztof_kieslowski", + "cordell_hull", + "james_wilson", + "rosa_parks", + "tchaikovsky", + "norman_jewison", + "samuel_goldwyn", + "x", + "ernest_walton", + "vladimir_putin", + "jacob", + "giuseppe_mazzini", + "jim_thorpe", + "hertz", + "h", + "arnold_sch\u00f6nberg", + "laurence_sterne", + "fran\u00e7ois_mitterrand", + "george_fox", + "fran\u00e7ois_de_la_rochefoucauld", + "christopher_isherwood", + "anne_hathaway", + "david_garrick", + "don_budge", + "bill_russell", + "margaret_court", + "emile_zola", + "baldwin", + "clarence_darrow", + "alben_william_barkley", + "charles_lamb", + "harry", + "g", + "fausto_socino", + "king_john", + "de_niro", + "arthur_schopenhauer", + "thomas_dekker", + "james_cagney", + "john_keble", + "johns_hopkins", + "henri_pitot", + "wanda_landowska", + "billy_mitchell", + "martin_heidegger", + "hans_eysenck", + "fran\u00e7ois_mauriac", + "r", + "george_lucas", + "andrew_jackson", + "edith_wharton", + "louis_armstrong", + "fran\u00e7ois_jacob", + "steven_spielberg", + "l\u00e9onide_massine", + "jean_monnet", + "d_w_griffith", + "robert_fulton", + "thomas_hardy", + "eddie_rickenbacker", + "thomas_gainsborough", + "stefan_wyszynski", + "giuseppe_garibaldi", + "philip_warren_anderson", + "alexandre_dumas", + "karel_\u010dapek", + "philipp_melanchthon", + "robert_brown", + "abelardo", + "thomas_carlyle", + "donald_barthelme", + "william_tyndale", + "tamara_karsavina", + "bobby_fischer", + "johannes_gutenberg", + "d", + "sem_c\u00e9rebro", + "thomas_malthus", + "giambattista_marino", + "gaetano_donizetti", + "castro", + "william_faulkner", + "s\u00e3o_cirilo", + "edouard_manet", + "arthur_holmes", + "pierre_boulez", + "girolamo_savonarola", + "nikolai_bukharin", + "emma_goldman", + "anna_kournikova", + "eug\u00e8ne_delacroix", + "francis_poulenc", + "james_ussher", + "john_barrymore", + "john_constable", + "james_mill", + "e_entertainment_television", + "putin", + "matthew_flinders", + "joseph_campbell", + "jean_de_la_fontaine", + "robert_hooke", + "o_henry", + "hoffa", + "karl_popper", + "coleman_hawkins", + "nikita_khrushchov", + "george_sand", + "peter_sellers", + "homo_rhodesiensis", + "charles_fourier", + "henry_clay", + "antoni_van_leeuwenhoek", + "peter_o'toole", + "joseph_conrad", + "g\u00fcnter_grass", + "do_zero", + "peter_paul_rubens", + "mahatma_gandhi", + "jim_morrison", + "paul_newman", + "robert_mills", + "george_meredith", + "robert_morris", + "woody_herman", + "alexander_wilson", + "josef_albers", + "jackson_pollock", + "tirinhas", + "john_lennon", + "andrea_palladio", + "gandhi", + "bob_woodward", + "e_assim_vai", + "charlie_chaplin", + "lillian_russell", + "d_h_lawrence", + "thomas_malory", + "lea", + "john_brown", + "al_jolson", + "elizabeth_gaskell", + "hugo_junkers", + "j_r_firth", + "piscis_austrinus", + "lillian_hellman", + "brescia", + "henrique", + "john_macleod", + "thomas_merton", + "asa_gray", + "hannah_arendt", + "antonio_stradivari", + "c_s_forester", + "robinson_jeffers", + "limpa_chamin\u00e9s", + "alice_walker", + "andrei_sakharov", + "strauss", + "miles_davis", + "andr\u00e9_weil", + "george_marshall", + "jesse_jackson", + "willa_cather", + "stanley_kubrick", + "camberra", + "john_deere", + "john_huston", + "william_gilbert", + "rene_magritte", + "james_watt", + "jonathan_edwards", + "ronald_reagan", + "helmut_schmidt", + "jenny_lind", + "homo", + "frederick_douglass", + "tebaldi", + "seleuco", + "david_hilbert", + "wilhelm_reich", + "roman_jakobson", + "oliver_cromwell", + "lionel_hampton", + "james_hargreaves", + "paul_c\u00e9zanne", + "frank_capra", + "william_wordsworth", + "rex_harrison", + "s", + "william_clark", + "woodrow_wilson", + "margaret_sanger", + "george_wallace", + "el_cid", + "t_h_white", + "agrippina", + "st_louis", + "richard_rodgers", + "george", + "aimee_mcpherson", + "anne_sexton", + "morgana", + "john_dryden", + "jim_henson", + "frank", + "b\u00e9la_lugosi", + "ernest_hemingway", + "john_eccles", + "george_westinghouse", + "constantin_brancusi", + "aquila", + "jacques_charles", + "eero_saarinen", + "arthur_miller", + "john_cheever", + "gracie_allen", + "nelson_mandela", + "heinrich_himmler", + "al_gore", + "john_rutledge", + "o_pequeno_lord", + "hans_bethe", + "hans_geiger", + "fernand_l\u00e9ger", + "roald_amundsen", + "stephane_grappelli", + "sherwood_anderson", + "alfred_korzybski", + "c_a", + "charles_dickens", + "do_in\u00edcio", + "sean_o'casey", + "o_zelote", + "ella_fitzgerald", + "fats_waller", + "thomas_sydenham", + "jack_robinson", + "alois_senefelder", + "george_enescu", + "wallace_carothers", + "jacques_offenbach", + "joseph_paxton", + "william_curtis", + "william_chambers", + "george_stevens", + "federico_fellini", + "the_one", + "bessie_smith", + "patrick_henry", + "willy_brandt", + "charles_wilkes", + "francisco_pizarro", + "francisco_franco", + "s\u00e3o_cristov\u00e3o", + "niccol\u00f3_paganini", + "jackie_robinson", + "bernardo_bertolucci", + "jan_steen", + "aeromo\u00e7o", + "bacharelado", + "e_e_cummings", + "john_ross", + "powell", + "hans_arp", + "andrew_carnegie", + "franz_schubert", + "chafariz", + "johnny_cash", + "joseph_mccarthy", + "alfred_kastler", + "estaline", + "mick_jagger", + "otto_loewi", + "don_marquis", + "georges_cuvier", + "william_harvey", + "constantin_br\u00e2ncu\u015fi", + "walter_scott", + "paul_cezanne", + "arnaldo", + "serguei_prok\u00f3fiev", + "sam_houston", + "robert_peary", + "robert_browning", + "s\u00e3o_louren\u00e7o", + "comenius", + "a_escolhida", + "alessandro_farnese", + "john_bunyan", + "jonathan_swift", + "walter_gropius", + "albert_einstein", + "l", + "cl\u00e1udio_monteverdi", + "corretor_de_seguros", + "thomas_edison", + "elizabeth", + "chiang_kai_shek", + "claude_bernard", + "raymond_chandler", + "henry_purcell", + "fran\u00e7ois_villon", + "t", + "wilhelm_ostwald" + ], + "DISEASE": [ + "ceratite", + "desmineraliza\u00e7\u00e3o", + "catalepsia", + "paragem_card\u00edaca", + "pertussis", + "sangramento", + "secagem", + "tropesia", + "condroma", + "fundidor", + "peste_bub\u00f3nica", + "equimose", + "filovirus", + "estase", + "invernada", + "pisadura", + "anelar", + "parada_cardiorrespirat\u00f3ria", + "cravagem", + "concuss\u00e3o", + "faringite", + "anciloglossia", + "misofobia", + "ki", + "tabes_dorsalis", + "parvov\u00edrus", + "scarro", + "flavivirus", + "rubeola", + "polidipsia", + "polidactilia", + "pseudo_hermafroditismo", + "sobremordida", + "amigdalite", + "sociofobia", + "grafiose", + "salmonelose", + "mordedura", + "rage", + "espondilolistese", + "analgesia", + "chill", + "caleira", + "als", + "tanatofobia", + "androfobia", + "galeofobia", + "almorroida", + "fotofobia", + "enrubescimento", + "almorreima", + "quel\u00f3ide", + "cortamento", + "contundir", + "queimadura", + "maladia", + "pernoitar", + "acantose_nigricans", + "raspado", + "sobrepeso", + "fluorose", + "escotoma", + "parvo", + "espondilite", + "aquilia", + "turgidez", + "catufobia", + "pocilgas", + "com_excesso_de_peso", + "progeria", + "calosidade", + "laringite", + "frostbite", + "analgia", + "ginecomastia", + "pervers\u00e3o", + "afacia", + "mouse", + "semicerrar", + "triquinose", + "aminoacid\u00faria", + "anestesia\u00e7\u00e3o", + "maciez", + "anemia_megalobl\u00e1stica", + "pancreatite", + "geofagia", + "despersonaliza\u00e7\u00e3o", + "lambdacismo", + "pirose", + "mielite", + "aceton\u00faria", + "pontada", + "papiledema", + "autoimunidade", + "presbiopia", + "dolorimento", + "polihidr\u00e2mnio", + "brucelose", + "borracheira", + "espinhal", + "seminoma", + "mania", + "the_bends", + "arenavirus", + "trombose_coronariana", + "poliarterite", + "habitua\u00e7\u00e3o", + "picornavirus", + "escr\u00f3fulas", + "hernia\u00e7\u00e3o", + "lacera\u00e7\u00e3o", + "phytophthora_infestans", + "hansen\u00edase", + "cardite", + "coriza", + "condicionar", + "queima\u00e7\u00e3o", + "gengivite", + "aquafobia", + "distrofia", + "the_suffering", + "intertrigo", + "prog\u00e9ria", + "rust", + "raspagem", + "avc", + "colestase", + "gatofobia", + "paramyxovirus", + "pancreatitis", + "paralisia", + "sofrendo", + "teratoma", + "alveolite", + "cardiomegalia", + "febre_tif\u00f3ide", + "mastodinia", + "parada_card\u00edaca", + "analbuminemia", + "frenesi", + "tremular", + "tenesmo", + "epiderm\u00f3lise_bolhosa", + "pelagra", + "catarro", + "polenose", + "para", + "esquistossomose", + "handicap", + "papiloma", + "mosca_volante", + "tarantismo", + "ginofobia", + "alalia", + "estenose", + "rio_par\u00e1", + "traumatismo", + "wale", + "ruborizar", + "verruga_plantar", + "coron\u00e1rio", + "gravida", + "stitch", + "herpes_simplex_virus", + "distens\u00e3o", + "afundir", + "galactosemia", + "torpor", + "inani\u00e7\u00e3o", + "morrinha", + "amastia", + "moscas_volantes", + "estarrecer", + "tutia", + "indisposi\u00e7\u00e3o", + "silicose", + "chicotada", + "hamartoma", + "chi", + "gesta\u00e7\u00e3o", + "berib\u00e9ri", + "delirium", + "estrabismo", + "queloide", + "poli\u00faria", + "mijada", + "escarlatina", + "qi", + "embriaguez", + "erisipela", + "granuloma", + "ferrugem", + "problem\u00e3o", + "cardiopatia_cong\u00eanita", + "transtorno", + "rickettsiose", + "v\u00edrus_varicela_zoster", + "bradicardia", + "spina_bifida", + "lordose", + "tremida", + "flaviviridae", + "listeriose", + "carb\u00fanculo", + "claustrofobia", + "distimia", + "quadrantanopia", + "gimp", + "desidrata\u00e7\u00e3o", + "radia\u00e7\u00e3o", + "sarm", + "abasia", + "frenzy", + "hernia", + "alexia", + "herpes", + "arbov\u00edrus", + "poliomielite", + "toxemia", + "esquitosom\u00edase", + "arranh\u00e3o", + "proctite", + "poliov\u00edrus", + "menorragia", + "agamaglobulinemia", + "lama\u00e7al", + "smart", + "quinh\u00e3o", + "amelia", + "suba", + "escr\u00f3fula", + "cardiomiopatia", + "ed", + "estado_gasoso", + "cinetose", + "dentalgia", + "ceratocone", + "pachorra", + "sigmatismo", + "pica", + "bebedeira", + "abraquia", + "rodeira", + "surdos", + "tracoma", + "puxada", + "gravidez", + "acetonemia", + "transposi\u00e7\u00e3o", + "escorbuto", + "the_sting", + "galactocele", + "mastoidite", + "sarampo", + "tireoidite", + "sensation", + "oftalmia", + "tontura", + "ralado", + "laringotraqueobronquite", + "peste_bovina", + "dartro", + "parestesia", + "acidose_respirat\u00f3ria", + "cardiopatia", + "solu\u00e7ar", + "sin\u00e9quia", + "paludismo", + "machudar", + "abrasamento", + "a_peste", + "pain", + "cervicite", + "fissura_labial", + "fatiar", + "cobr\u00e3o", + "cont\u00e1gio", + "bunyaviridae", + "dist\u00farbio_bipolar", + "anemia_apl\u00e1stica", + "desmieliniza\u00e7\u00e3o", + "a_paix\u00e3o_de_cristo", + "radia\u00e7\u00f5es", + "espirro", + "que_est\u00e1_acima_do_peso_normal", + "talassemia", + "enchaqueca", + "pert\u00fassis", + "catapora", + "ter_fome", + "corcunda", + "coisav\u00e3", + "sequela", + "albumin\u00faria", + "solu\u00e7o", + "assistolia", + "latejar", + "baguncar", + "garrotilho", + "doen\u00e7a_por_v\u00edrus_\u00e9bola", + "vasculite", + "fonofobia", + "taquicardia", + "paraplegia", + "an_qi", + "beliscar", + "v\u00edrus_de_marburg", + "claudica\u00e7\u00e3o", + "poliglobulia", + "esteatorr\u00e9ia", + "ter\u00e7ol", + "escara", + "cafun\u00e9", + "congest\u00e3o", + "queratite", + "aeroembolismo", + "enxaqueca", + "mi", + "tosse", + "alastrim", + "aura", + "escoliose", + "sting", + "otorr\u00e9ia", + "arenav\u00edrus", + "estomatite", + "resseca\u00e7\u00e3o", + "hera_venenosa", + "arritmia", + "gripe_porcina", + "labirintite", + "policitemia", + "the_bleeding", + "fundador", + "salmonelas", + "polimiosite", + "condrossarcoma", + "virus_de_marburg", + "peste_bubonica", + "pancitopenia", + "alfav\u00edrus", + "ebulir", + "chamuscada", + "ravia", + "distrofia_muscular", + "esteatorreia", + "trauma", + "xerodermia_pigmentosa", + "tirosinemia", + "aminoaciduria", + "contus\u00e3o", + "peste_bub\u00f4nica", + "kuru", + "burn", + "claudica\u00e7\u00e3o_intermitente", + "espinal", + "mononucleose_infecciosa", + "ros\u00e9ola", + "tireotoxicose", + "noma", + "hord\u00e9olo", + "ancilose", + "the_hives", + "hemeralopia", + "a_n\u00e1usea", + "mastite", + "arreflexia", + "polineurite", + "dengue", + "anasarca", + "aniseiconia", + "filistinismo", + "castanha", + "cicie", + "mormo", + "colecistite", + "spina_b\u00edfida", + "chup\u00e3o", + "coqueluche", + "fratura", + "fatia", + "escald\u00e3o", + "parvovirus", + "salmonella", + "hifema", + "verruga", + "radian\u00e7a", + "paresia", + "malignidade", + "indigest\u00e3o", + "flaviv\u00edrus", + "passamento", + "urdume", + "talass\u00e9mia", + "cianose", + "malaria", + "engasgo", + "furunculose", + "microrganismos_patog\u00e9nicos" + ], + "PLANT": [ + "acer_negundo", + "brachychiton_populneus", + "glaucium_flavum", + "senecio_vulgaris", + "clematite", + "cherim\u00f3ia", + "lilium_martagon", + "hevea", + "pyracantha", + "acer_rubrum", + "mahonia", + "pine", + "verbascum_thapsus", + "corticeira", + "parnassia", + "acetosa", + "pinho", + "lilium_philadelphicum", + "lilium_longiflorum", + "sorghum_halepense", + "caiota", + "veronica_beccabunga", + "bardana", + "liriodendron_tulipifera", + "melissa", + "impatiens_walleriana", + "geranium_molle", + "dioscorea_bulbifera", + "hoya_carnosa", + "mamona", + "sapindus", + "scutellaria_galericulata", + "aquil\u00e9gia", + "teixo", + "the_joshua_tree", + "sarcoscypha_coccinea", + "philadelphus_coronarius", + "aralia_elata", + "pitanga", + "bromus_tectorum", + "acetosela", + "helianthus", + "edelvais", + "dendezeiro", + "lathyrus_latifolius", + "scorzonera_hispanica", + "marsilea_quadrifolia", + "cucurbita_moschata", + "tramazeira", + "solanaceae", + "flor_leopardo", + "vanilla_planifolia", + "juncus_articulatus", + "eryngium_maritimum", + "schefflera_actinophylla", + "salix_babylonica", + "lari\u00e7o", + "margarida_amarela", + "anthyllis_vulneraria", + "lathyrus_odoratus", + "selaginella_lepidophylla", + "ortiga", + "confrei", + "amanita", + "sequoiadendron", + "aristol\u00f3quia", + "esporeira", + "morugem", + "arabidopsis_thaliana", + "santa_maria", + "bertholletia_excelsa", + "cerefolho", + "epipremnum_aureum", + "arundo", + "monarda", + "sorbus_torminalis", + "marroio", + "cris\u00e2ntemo", + "camapu", + "achillea", + "podocarpus_elongatus", + "pelargonium_odoratissimum", + "bidens_tripartita", + "sinapis", + "prunus_laurocerasus", + "allium_tuberosum", + "mafumeira", + "sic\u00f3moro", + "passiflora_ligularis", + "salix_triandra", + "melicoccus_bijugatus", + "lilium_michiganense", + "teucrium_scorodonia", + "acer_campestre", + "dioneia", + "esteva", + "bletilla_striata", + "sanguina", + "mimosa_pudica", + "cons\u00f3lida", + "convolvulus", + "madressilva", + "carex_pseudocyperus", + "n\u00e3o_me_esque\u00e7as", + "gentiana_lutea", + "mercurialis_perennis", + "matthiola_incana", + "anona", + "arctostaphylos_alpina", + "cortadeira", + "acacia_pycnantha", + "actinidia_chinensis", + "taxus_baccata", + "saxifraga_granulata", + "sakura", + "valerianella_locusta", + "papaver", + "nymphaea_alba", + "silene_dioica", + "dicentra_spectabilis", + "larice", + "delf\u00ednio", + "euphorbia_esula", + "diplotaxis_tenuifolia", + "candida_albicans", + "pulicaria_dysenterica", + "ranunculus_ficaria", + "amaryllis_belladonna", + "veronica_officinalis", + "asperula", + "calophyllum_inophyllum", + "rosa_multiflora", + "koel\u00e9ria", + "anthemis_arvensis", + "microstrobos_niphophilus", + "acer_macrophyllum", + "acacia_dealbata", + "capsicum_baccatum", + "agrimonia_eupatoria", + "pimenta_negra", + "plantago_lanceolata", + "plantas_parasitas", + "bergamota", + "ononis_spinosa", + "xanthosoma_sagittifolium", + "acer_palmatum", + "thlaspi_arvense", + "girassol", + "agrostemma_githago", + "hypericum_androsaemum", + "taxus_cuspidata", + "salix_viminalis", + "juniperus_virginiana", + "hera_venenosa", + "tangerina", + "castanheiro", + "eriophorum_angustifolium", + "leonotis_nepetifolia", + "veronica_serpyllifolia", + "sabugueirinho", + "eucalyptus_globulus", + "passiflora_incarnata", + "clusia", + "polygala_vulgaris", + "pomares", + "veronica_peregrina", + "scutellaria_lateriflora", + "antirrino", + "ceref\u00f3lio", + "dividivi", + "laranjeira_da_terra", + "pelargonium_peltatum", + "xer\u00f3fito", + "reseda", + "barbarea_vulgaris", + "platanus_orientalis", + "gossypium_hirsutum", + "urtica", + "potamogeton_crispus", + "lychnis", + "cherimoia", + "salix_fragilis", + "amanita_muscaria", + "leonurus_cardiaca", + "silybum", + "spergula_arvensis", + "asplenium_trichomanes", + "acer_japonicum", + "arrhenatherum_elatius", + "conocarpus_erectus", + "dracocephalum", + "populus_balsamifera", + "armeria_maritima", + "myosotis_sylvatica", + "kananga", + "aquil\u00e9ia", + "primula_acaulis", + "helianto", + "carex_arenaria", + "acanthus_mollis", + "pseudofruto", + "as_de_mim", + "magn\u00f3lia", + "leucanthemum_vulgare", + "n\u00e3o_te_esquece", + "campanula_rapunculus", + "diplotaxis_muralis", + "mostardeira", + "sciadopitys_verticillata", + "pseudofrutos", + "geranium_robertianum", + "clematis", + "helianthus_tuberosus", + "hedysarum_coronarium", + "kniph\u00f3fia", + "balhico", + "tupinambor", + "saccharum", + "verbena_officinalis", + "prunus_domestica", + "arm\u00e9ria", + "phytophthora_infestans", + "bilimbi", + "aquileia", + "prosopis_juliflora", + "acer_platanoides", + "viburnum_prunifolium", + "amieiro", + "gossypium_barbadense", + "planta_carn\u00edvora", + "nogueira", + "centaurea_cyanus", + "delonix_regia", + "urtica_dioica", + "agaricus_campestris", + "gymnadenia_conopsea", + "trifolium_repens", + "platanus_hispanica", + "blackberry", + "olaia", + "cortaderia_selloana", + "solanum", + "ballota_nigra", + "arequeira", + "sisymbrium_officinale", + "marati", + "tremo\u00e7o_branco", + "angelica_archangelica", + "beladona", + "campsis_radicans", + "cirsium_vulgare", + "planta_lenhosa", + "conv\u00f3lvulo", + "echinocactus_grusonii", + "lilium_canadense", + "bergamoteira", + "brachychiton_acerifolius", + "sorveira", + "sorbus_aucuparia", + "taboca", + "lari\u00e7o_europeu", + "acer_pseudoplatanus", + "campanulastrum", + "lotus_corniculatus", + "oxicoco", + "cerejeira", + "polyporus_squamosus", + "raphanus_raphanistrum", + "cytisus_multiflorus", + "amaranthus_caudatus", + "urtiga", + "silene_latifolia", + "saxifraga_stellaris", + "anagallis_tenella", + "scleranthus_annuus", + "dormideira", + "salgueiro", + "papoula", + "pinheirobrasileiro", + "drosophyllum_lusitanicum", + "crataegus_laevigata", + "sinapis_arvensis", + "traque\u00f3fitos", + "acer_circinatum", + "arum", + "silene_uniflora", + "repolho", + "dracunculus_vulgaris", + "acacia_melanoxylon", + "cyperus_papyrus", + "agrostis_canina", + "saccharomyces_cerevisiae", + "boletus_edulis", + "buckeye", + "ranunculus_bulbosus", + "tetragonia_tetragonoides", + "taraxacum_officinale", + "arenaria_serpyllifolia", + "papoila", + "lysimachia_vulgaris", + "dracaena_draco", + "amargoseira", + "trichomanes_speciosum", + "hypochaeris_radicata", + "a\u00e7oro", + "amarena", + "carrasca", + "ligustro", + "cypripedium_fasciculatum", + "pseudotsuga_menziesii", + "tangerineira", + "tanacetum_parthenium", + "lithospermum_officinale", + "heracleum_sphondylium", + "lepidothamnus_laxifolius", + "verbasco", + "lathyrus_sylvestris", + "viola_tricolor", + "viburnum_opulus", + "ervilhaca", + "amoreira", + "samanea_saman", + "calla", + "erythronium_montanum", + "azeitona", + "prunus_serrulata", + "galium_verum", + "acronicta_aceris", + "hiperic\u00e3o", + "aralia_stipulata", + "cycas_circinalis", + "populus_nigra", + "mentha_longifolia", + "ranunculus_repens", + "leucena", + "stellaria_holostea", + "strelitzia_reginae", + "tupinambo", + "tamareira", + "inga_edulis", + "edelweiss", + "spiranthes_spiralis", + "cicad\u00f3fita", + "enokitake", + "cardamine_pratensis", + "hypericum_calycinum", + "piper_betle", + "conyza_canadensis", + "amaranthus_hypochondriacus", + "cypripedium_montanum", + "erodium_texanum", + "arctium_minus", + "arrhenatherum", + "annona_reticulata", + "pinus_muricata", + "mios\u00f3tis", + "phytolacca_americana", + "nicotiana_rustica", + "reseda_odorata", + "lathyrus_sativus", + "oxalis", + "veronica_arvensis", + "anthriscus_sylvestris", + "belladonna", + "pteridium_aquilinum", + "panicum_capillare", + "convolvul\u00e1cea", + "smilax_aspera", + "salvia_sclarea", + "aristolochia_clematitis", + "catharanthus_roseus", + "ageratum_houstonianum", + "pinheirinho", + "hidr\u00f3fita", + "lansium", + "cypripedium_calceolus", + "viola_odorata", + "poa_nemoralis", + "olivo", + "amaranthus_albus", + "falcatifolium_falciforme", + "chrysanthemum", + "liquid\u00e2mbar", + "agrimonia", + "myrica_gale", + "vallisneria", + "holcus_mollis", + "castanha", + "acer_glabrum", + "seringueira", + "macaxeira", + "plasmalema", + "castanea", + "batatadoce", + "physalis_peruviana", + "sambucus_ebulus", + "cinco_chagas", + "calystegia_sepium", + "dicksonia_antarctica", + "mostarda", + "taquara", + "ranunculus_aquatilis", + "bromus_secalinus", + "pinus_palustris", + "conium_maculatum", + "ranunculus_acris", + "cypripedium_reginae", + "abronia_villosa", + "sobreiro", + "engos", + "pinus_echinata", + "camellia_japonica", + "tritoma", + "podocarpus_nivalis", + "milef\u00f3lio" + ], + "BIO_CHEM_ENTITY": [ + "defasado", + "obsessivo", + "betacarbolina", + "antim\u00fclleriano", + "alfafetoprote\u00edna" + ], + "ORG": [ + "ida", + "lei_de_conserva\u00e7\u00e3o", + "filarm\u00f3nica", + "mar_vermelho", + "lei_de_tali\u00e3o", + "classe_trabalhadora", + "zanolho", + "estado_de_bem_estar_social", + "hospital_psiqui\u00e1trico", + "direito_romano", + "s\u00e3o_jos\u00e9", + "ansea", + "era_dourada", + "san_jos\u00e9", + "drug_enforcement_administration", + "cientologia", + "aos_poucos", + "wicca", + "an_education", + "paul_cezanne", + "monte_das_oliveiras", + "sete_horas", + "jan_mayen", + "depois_de_cristo", + "congregacionalismo", + "nossa_senhora_da_soledade", + "bom_proveito", + "the_usual_suspects", + "midlands_ocidentais", + "nossa_senhora_das_sete_dores", + "em_flagrante", + "ursinho_pooh", + "grande_pr\u00eamio", + "a_pr\u00e1tica_faz_a_perfei\u00e7\u00e3o", + "hospitais_psiqui\u00e1tricos", + "aa", + "nasa", + "the_comedy_of_errors", + "a_uni\u00e3o_faz_a_for\u00e7a", + "pastilha_el\u00e1stica", + "in_vivo", + "esta_noite", + "s\u00e3o_sebasti\u00e3o", + "huang_he", + "bollywood", + "v\u00e9spera_do_ano_novo", + "de_pouco_em_pouco", + "estadosunidosdaam\u00e9rica", + "de_primeira", + "grundschule", + "europol", + "schutzstaffel", + "estado_do_bem_estar_social", + "noite_de_s\u00e3o_silvestre", + "assun\u00e7\u00e3o_de_maria", + "nossa_senhora_do_calv\u00e1rio", + "the_who", + "haganah", + "por_que_n\u00e3o", + "to_the_core", + "porte", + "lago_saint_clair", + "em_companhia_de", + "hoje_\u00e0_noite", + "j\u00e1_agora", + "san_francisco", + "tach\u00e3o", + "nossa_senhora_das_ang\u00fastias", + "a_chorus_line", + "dixiecrat", + "pedraria", + "por_sinal", + "hoje_\u00e0_tarde", + "guizeira", + "vai_tomar_no_cu", + "nara", + "a_bela_adormecida", + "afinal", + "escola", + "em_casa", + "sistema_de_reserva_federal_dos_estados_unidos", + "de_m\u00e3o_\u00fanica", + "partido_trabalhista_noruegu\u00eas", + "escolarizar", + "na\u00e7\u00f5es_unidas", + "dar_valor", + "gao", + "o_gato_preto", + "khalsa", + "s\u00e3o_bernardo", + "partido_democrata", + "the_family_man", + "s_hertogenbosch", + "core", + "maquilar", + "frente_popular", + "quem_\u00e9s_tu", + "maria_joana", + "estado_de_bem_estar", + "se_parece", + "de_olhos_azuis", + "john_tuzo_wilson", + "gironda", + "can_tho", + "manic\u00f4mio", + "the_faculty", + "don_juan", + "oni", + "the_new_school", + "ai", + "nossa_senhora_das_l\u00e1grimas", + "bom_apetite", + "stosstruppen", + "rudeltaktik", + "chiang_mai", + "manic\u00f3mio", + "escolas", + "et_al", + "casa_branca", + "dia", + "estado_maior_conjunto_dos_estados_unidos", + "nossa_senhora_das_dores", + "the_big_four", + "taoismo", + "yang_ts\u00e9", + "de_\u00faltima_tecnologia", + "german\u00edstica", + "com_a_boca_na_botija", + "a_igreja_de_jesus_cristo_dos_santos_dos_\u00faltimos_dias", + "radiogal\u00e1xia", + "direito_da_roma_antiga", + "chuinga", + "the_breakfast_club", + "shabak", + "castela_e_le\u00e3o", + "rabindranath_tagore", + "estado_da_arte", + "vai_em_frente", + "gestapo", + "santo_andr\u00e9", + "de_novo", + "chama_ol\u00edmpica", + "dar\u00e0luz", + "funcion\u00e1rio_p\u00fablico", + "hagan\u00e1", + "thinktank", + "santa_helena", + "ursa_maior", + "nossa_senhora_da_piedade", + "a\u00e7\u00e3o_popular", + "laurel_hardy", + "petrol\u00edfera", + "justeza", + "partido_verde", + "com_a_m\u00e3o_na_massa", + "partido_liberal", + "alvenaria", + "marinha", + "li_fi", + "e_outros", + "maquis", + "al_jazira", + "assembleia_nacional_da_hungria", + "isl\u00e3o_sunita", + "estadosunidos", + "lua_nova", + "who_are_you", + "i_ching", + "nesta_noitinha", + "chiang_rai", + "alta_fidelidade", + "filarm\u00f4nica", + "disa", + "s\u00e3o_paulo", + "mercado_negro", + "altos_fagnes", + "mossad", + "v\u00e9spera_de_ano_novo", + "at\u00e9_a_data", + "dividivi", + "lago_superior", + "assembleia_nacional_do_azerbaij\u00e3o", + "nossa_senhora_do_pranto", + "escolinha", + "rio_amarelo", + "francoma\u00e7onaria", + "superpoder", + "de_vez_em_quando", + "hollywood", + "ursa_major", + "kurt_godel", + "uni\u00e3o_internacional_de_telecomunica\u00e7\u00f5es", + "c\u00f3digo_penal", + "polegarzinho", + "ilha_de_s\u00e3o_tom\u00e9", + "sturmabteilung", + "jo\u00e3o_baptista", + "assembleia_nacional_da_s\u00e9rvia", + "bancos", + "los_angeles", + "nato", + "de_quando_em_quando", + "florestas_h\u00famidas", + "baltimore_orioles", + "petroleira", + "conselhos_profissionais", + "estado_fantoche", + "assembleia_nacional_da_coreia_do_sul", + "te_amo", + "ad_hoc", + "qual_\u00e9_o_problema", + "viuva_negra", + "de_ponta", + "uma_vez_mais", + "\u00e1gua_doce", + "hosp\u00edcio", + "mi", + "quem_\u00e9_voc\u00ea", + "by_the_way", + "de_in\u00edcio", + "in_situ", + "gr\u00eamio", + "b\u00e1rbara_de_nicom\u00e9dia", + "s\u00e3o_nicolau", + "doc", + "de_tempo_a_tempo", + "limitada", + "marching_band", + "al_ain", + "partido_trabalhista_australiano", + "ace", + "terceiros", + "cidadelivre", + "american\u00edstica", + "direito_internacional", + "maquiar", + "as_tr\u00eas_irm\u00e3s", + "s\u00e3o_jo\u00e3o_batista", + "os_democratas_crist\u00e3os", + "corpo_a\u00e9reo_irland\u00eas", + "assembleia_nacional_francesa", + "densidade_demogr\u00e1fica", + "streptococcus_pyogenes", + "eu", + "bom_senso", + "em_comum", + "andorinha_de_bando", + "zonas_industriais", + "bolsadevalores", + "vila_ol\u00edmpica", + "chang_jiang", + "ex\u00e9rcito_dos_estados_unidos_da_am\u00e9rica", + "as_vinhas_da_ira", + "anos_dourados", + "hirundo_rustica", + "haredi", + "terra_queimada", + "assembleia_nacional_da_bulg\u00e1ria", + "movimento_internacional_da_cruz_vermelha_e_do_crescente_vermelho", + "fundo_de_pens\u00e3o", + "zona_industrial", + "in_vitro", + "corte_suprema", + "caolho", + "iansequi\u00e3o", + "engarrafamentos", + "sin\u00e9drio", + "ou_tudo_ou_nada", + "coletivamente", + "hinaiana", + "s\u00e3o_tom\u00e9", + "partido_republicano", + "van_gogh", + "s\u00e3o_francisco", + "com_a_boca_na_butija" + ], + "POLITICAL_PARTY": [ + "gironda", + "partido_conservador", + "partido_nacional", + "dixiecrat", + "partido_democrata_republicano", + "partido_comunista", + "labor", + "kuomintang", + "partido_da_proibi\u00e7\u00e3o", + "partido_do_trabalho", + "partido_trabalhista", + "partido_nacional_socialista_dos_trabalhadores_alem\u00e3es", + "partido_popular", + "partido_democr\u00e1tico", + "partido_social_democrata_do_azerbaij\u00e3o", + "partido_socialista", + "partido_da_direita", + "partido_progressista" + ], + "RELIGION_MEMBER": [ + "mandeu", + "guru", + "agostinho", + "the_hindu", + "budista", + "pentecostal", + "wahhabi", + "batistas", + "sarraceno", + "cristiano", + "presbiteriano", + "siques", + "mormon", + "sarracenos", + "shaker", + "baptista", + "vaishnava", + "franciscanos", + "sunita", + "the_apostle", + "franciscano", + "indostani", + "pentecostais", + "trapista", + "metodista", + "beneditinos", + "beneditino", + "crist\u00e3", + "crist\u00e3os", + "sique", + "budistas", + "parses" + ], + "RACE": [ + "filipino", + "afrancesado", + "latino", + "ingleses", + "paquistan\u00eas", + "brancos", + "africano", + "polin\u00e9sio", + "sul_coreano", + "polin\u00e9sico", + "\u00e1rabes", + "sul_coreana", + "neerlandeses", + "francesa", + "latinoamericano", + "da_\u00e1frica", + "franceses", + "esquimos", + "insulano", + "galeses", + "norte_coreana", + "a_mexicana", + "negro", + "sul_americano", + "da_\u00edndia" + ], + "JOB": [ + "primeiroministro", + "cortador", + "empenhar", + "teaser", + "alienista", + "brigadeiro", + "cano\u00edsta", + "endocrin\u00f2leg", + "developer", + "guru", + "param\u00e9dico", + "latoeiro", + "microbi\u00f3logo", + "proct\u00f3loga", + "encenador", + "torneiro", + "arruela", + "the_nanny", + "bombeiros", + "presidenta", + "violeiro", + "baleeiro", + "casaeditora", + "cule", + "mensageiro", + "chargista", + "encanador", + "hematologista", + "interpretador", + "treinadores", + "cart\u00f3grafo", + "general_manager", + "couraceiro", + "ranger", + "agrimensor", + "capataz", + "abreviador", + "cardiologista", + "potter", + "mais_alerta", + "laringologista", + "dermatologista", + "em_ordem", + "make", + "esteticista", + "condest\u00e1vel", + "microbiologistas", + "vereadora", + "servidor_p\u00fablico", + "carpinteira", + "engenheiro", + "cientista", + "a_leiteira", + "feitor", + "lascar", + "agenda_electr\u00f3nica", + "cooper", + "luthier", + "the_lifeguard", + "remover", + "registrar", + "autora", + "camicase", + "neurologista", + "estivador", + "amputador", + "curtidor", + "senescal", + "fundador", + "enfermeira", + "foguista", + "don", + "agropecuarista", + "king", + "metralhador", + "incumbente", + "timoneiros", + "cartun", + "granadeiro", + "caporal", + "descascador", + "fornecedora", + "industrialista", + "parteiro", + "the_police", + "meteorologista", + "pastora", + "gestor", + "terapeuta", + "compositor", + "pretor", + "sommelier", + "fornalheiro", + "tafeiro", + "doge", + "gentleman", + "palestrante", + "cartunistas", + "picheleiro", + "palafreneiro", + "regente", + "suboficial", + "territorial", + "burgomestre", + "pol\u00edcias", + "catalogador", + "assalariar", + "goleiro", + "pasteleiro", + "para", + "router", + "cardi\u00f3loga", + "cavalariano", + "grevista", + "porta_estandarte", + "trac\u00e7\u00e3o", + "conductor", + "coveiro", + "o_leitor", + "lenhador", + "sensei", + "arrowsmith", + "autarca", + "costureira", + "mastermind", + "balconista", + "parteira", + "mercador", + "proct\u00f3logo", + "hussardo", + "carcereiro", + "trimpot", + "urinar", + "rehoboth_basters", + "vigilante", + "funileiro", + "coadjutor", + "pregador", + "rotineiro", + "veisalgia", + "gerente", + "caus\u00eddico", + "governante", + "ginecologista", + "inventor", + "catequista", + "lanceiro", + "leiteiro", + "cavador", + "intendente", + "pedreiro", + "padeiro", + "letreiro", + "coelhinho", + "portador", + "promotora", + "rabinos", + "carpinteiro", + "alvenel", + "ginec\u00f3logo", + "the_principal", + "kamikaze", + "driver", + "arador", + "alfandeg\u00e1rio", + "quiropr\u00e1tico", + "caixeiro", + "ferradora", + "the_advocate", + "pajem", + "novelista", + "marceneiro", + "enfermeiros", + "frisador", + "governador", + "sculptor", + "visagista", + "freelancer", + "proc\u00f4nsul", + "punter", + "ama_de_leite", + "cadi", + "salva_vidas", + "zelador", + "encolhimento", + "mais_completo", + "cabeleireiros", + "jardineiro", + "curadores", + "the_guardian", + "alveitar", + "justiceiro", + "falante", + "param\u00e9dica", + "vaqueira", + "bodum", + "microbi\u00f3loga", + "lauda", + "torneador", + "estacional", + "pagem", + "associado", + "biscoitos", + "neur\u00f3logo", + "the_physician", + "esbirro", + "falcoeiro", + "magist\u00e9rio", + "tesoureiro", + "ama_seca", + "comediante", + "prefeita", + "hidrologista", + "mate", + "ebanista", + "tripulante", + "cardi\u00f3logo", + "hidr\u00f3logo", + "l_horloger_de_saint_paul", + "porta_bandeira", + "marechal", + "serrador", + "chimarrao", + "rabi", + "couteiro", + "designer", + "pastorear", + "aquanauta", + "the_babysitter", + "limpador", + "cabreira", + "pastor", + "mosqueteiro", + "barrister", + "juntador", + "historinha", + "the_sitter", + "bombeiro", + "alferes", + "inventora", + "leitora", + "subtenente", + "interveniente", + "neurocirurgi\u00e3o", + "obstetra", + "agricultores", + "player", + "tenente", + "corporal", + "escavador", + "a_int\u00e9rprete", + "botic\u00e1rio", + "resumidor", + "rabino", + "carteiro", + "gerenciador", + "coronel", + "engenheira", + "tanoeiro", + "a_mensageira", + "hemat\u00f3logo", + "forragens", + "meirinho", + "romancista", + "angiologista", + "the_economist", + "familiar", + "paramedico", + "broker", + "engenheiro_civil", + "wetter", + "governanta", + "hospedeira", + "vereador", + "stripper", + "mijar", + "barista", + "carreteiro", + "vidraceiro", + "tunar", + "the_batman", + "roteador", + "warrior", + "latoaria", + "merceeira", + "cabeleireira", + "quiropraxista", + "the_hangover", + "principal", + "portaria", + "chimarr\u00e3o", + "merceeiro", + "the_pilot", + "sargento", + "contra_almirante", + "retalhista", + "doc", + "cartunista", + "tratadista", + "armeiro", + "enfermeiro", + "fazendeiro", + "cartaz", + "boiadeiro", + "aborteiro", + "primeiro_tenente", + "escan\u00e7\u00e3o", + "fundidor", + "empilhadora", + "mais_cheio", + "the_machinist", + "usher", + "messenger", + "timoneiro", + "cientistas", + "au_pair", + "proconsul", + "lavrador", + "trier", + "o_negociador", + "de_forma_marcial", + "cameraman", + "carroceiro", + "carcereira", + "amanuense", + "cabeleireiro", + "plotter", + "designers", + "aupair", + "cornaca", + "formador", + "colonato", + "fabricante", + "castuveira", + "the_deer_hunter", + "cors\u00e1rios", + "marceneira", + "concierge", + "doula", + "atriz", + "cabreiro", + "estat\u00edsticos", + "antologista", + "the_floorwalker", + "rastreador", + "sub", + "the_dresser", + "the_landlord", + "the_independent", + "mandarete", + "xastre", + "coolie", + "varejista", + "guerreira", + "presidentes", + "cookie", + "cineasta", + "esquire", + "obreiro", + "lojista", + "comodoro", + "regular", + "autor", + "esten\u00f3grafo", + "vaqueiro", + "encadernador", + "ferrador", + "sazonal", + "bab\u00e1", + "preceptor" + ], + "ANIMAL": [ + "digit\u00edgrado", + "acherontia", + "apodemus", + "cervos", + "centop\u00e9ia", + "montes_flinders", + "buteo", + "poraqu\u00ea", + "the_raven", + "cachalote", + "galomont\u00eas", + "sapo", + "desempenadeira", + "v\u00edrus_do_mosaico_do_tabaco", + "arroaz", + "galinhola", + "perissod\u00e1ctilos", + "a_gaivota", + "baratas", + "estrige", + "artiod\u00e1tilos", + "lemingue", + "tamandua\u00ed", + "peto_verde", + "aie_aie", + "galin\u00e1ceo", + "veados", + "holot\u00faria", + "arrulho", + "billy_elliot", + "cerasta", + "konduz", + "pigargo", + "estapagado", + "albatroz_errante", + "lacraia", + "canis_minor", + "castanheta_das_rochas", + "manta", + "casa_alugada", + "sitta_carolinensis", + "calafate", + "carduelis", + "pletodont\u00eddeos", + "pisces", + "colubr\u00eddeos", + "artiod\u00e1ctilo", + "jumento", + "art\u00eamia", + "elande", + "furao", + "sternidae", + "caititu", + "anuro", + "lactobacillus_acidophilus", + "javardo", + "mulherengo", + "guaraxaim", + "mant\u00eddeo", + "artiod\u00e1ctilos", + "curru\u00edra", + "pieris_brassicae", + "brachypteraciidae", + "cariacu", + "oriolo", + "pintasilgo", + "vibe", + "dros\u00f3fila", + "pintassilgo", + "tetra_cardeal", + "micropterus", + "supermouse", + "faina", + "vacaloura", + "galgo", + "guaco", + "sombria", + "artiod\u00e1tilo", + "tour\u00e3o", + "homo_sapiens", + "dynastinae", + "esquilos", + "ceraste", + "lakeland_terrier", + "tartaranh\u00e3o", + "passer", + "cerv\u00eddeos", + "tatuzinho", + "condor", + "the_crow", + "v\u00edrus_do_oeste_do_nilo", + "hound", + "crisomel\u00eddeo", + "artropode", + "cro_magnon", + "esperm\u00f3filo", + "bruchinae", + "misticetos", + "accipiter", + "murganho", + "abelha_mestra", + "baleia_branca", + "cacha\u00e7o", + "cant\u00e1rida", + "mexilh\u00e3o", + "flamingo_andino", + "paquinha", + "dipl\u00f3pode", + "toninha", + "arapap\u00e1", + "jerboa", + "sanicula_europaea", + "lebr\u00e9u", + "iller", + "peneireiro", + "perc\u00eddeo", + "moose", + "pulg\u00f5es", + "conraua_goliath", + "wisent", + "galolira", + "savacu", + "galin\u00e1ceos", + "serpent\u00e1rio", + "carango", + "mabeco", + "gamar", + "araguato", + "ammospermophilus", + "megascops", + "sable", + "le\u00e3ozinho", + "herpes_zoster", + "marta_europeia", + "irishterrie", + "pardal", + "arganaz", + "oniscidea", + "percebe", + "mariposa_cigana", + "baratinha", + "cobaia", + "barr\u00e3o", + "lychnis_flos_cuculi", + "v\u00edboracornuda", + "blata", + "narceja", + "lince", + "gerbo", + "auroque", + "tarrafa", + "petinha", + "pedionomidae", + "carri\u00e7a", + "mane", + "whippet", + "lavatera_arborea", + "caminheiro", + "salvelinus_fontinalis", + "ravena", + "juruviara", + "epstein_barr", + "yorkshire_terrier", + "mil\u00edpede", + "tamarutaca", + "muscicap\u00eddeos", + "abecoinha", + "gorilla_gorilla", + "andorinha_das_chamin\u00e9s", + "hydrophiidae", + "artr\u00f3podes", + "sargento_mor", + "pedunculata", + "cabeleira", + "andorinha_comum", + "arvicola", + "tetraz", + "sabi\u00e1", + "pigarreada" + ], + "LOCATION": [ + "roseiral", + "plantago_lanceolata", + "mar_tirreno", + "por_baixo_dos_panos", + "estados_unidos", + "mar_da_china_oriental", + "the_good_night", + "por_nada", + "trifolium_pratense", + "sint_eustatius", + "\u00e0_beira_de", + "rapanui", + "n\u00e3o_h\u00e1_de_qu\u00ea", + "anjos_da_guarda", + "no_caso_de", + "uma_e_quinze", + "eryngium_maritimum", + "n\u00e3o_tem_de_qu\u00ea", + "corpus_christi", + "bow_wow", + "s_hertogenbosch", + "pai_natal", + "piet_mondrian", + "intramuros", + "la_roche_en_ardenne", + "trifolium_repens", + "beco_sem_sa\u00edda", + "doi_moi", + "consoada", + "de_nada", + "cabo_horn", + "disponha", + "chang_jiang", + "al_jazira", + "man_o_war", + "s\u00e3o_bernardo_do_campo", + "trois_rivi\u00e8res", + "allahu_akbar", + "e.u.a", + "assembleia_nacional_da_pol\u00f3nia", + "huang_he", + "pieris_rapae", + "mar_do_norte", + "plantago_major", + "central_el\u00e9ctrica", + "col\u00fambia", + "estados_unidos_da_am\u00e9rica", + "eventualmente", + "o_dia_todo", + "bois_le_duc", + "vial\u00e1ctea", + "polegarzinho", + "on_the_road", + "papai_noel", + "the_black_hole", + "estado_unidenses", + "nos_bastidores", + "rio_azul", + "mar_negro", + "ochlodes_sylvanus", + "mar_amarelo", + "manic\u00f4mio", + "por_precau\u00e7\u00e3o", + "hat_yai", + "arena", + "metr\u00f3poles", + "nymphalis_polychloros", + "sankt_martin", + "sri_lanka", + "dia_de_colombo", + "pascoense", + "in_the_park", + "s\u00e3o_vicente", + "villa_lobos", + "pequeno_polegar", + "nas_ruas", + "three_amigos", + "bancos_centrais", + "scutellaria_galericulata", + "the_rolling_stones", + "cordon_bleu", + "monte_carmelo", + "s\u00e3o_patr\u00edcio", + "am\u00e9rico_vespucio", + "golfodeb\u00f3tnia", + "zica", + "por_detr\u00e1s_dos_bastidores", + "kryvyi_rih", + "o_jardim_das_cerejeiras", + "bela_adormecida", + "lago_tana", + "s\u00e3o_jo\u00e3o_de_meriti", + "cidades", + "pieris_brassicae", + "am\u00e9rico_vesp\u00facio", + "ex\u00e9rcito_dos_estados_unidos", + "heitor_villa_lobos", + "louis_joseph_gay_lussac", + "h\u00e1_muito_tempo_atr\u00e1s", + "manic\u00f3mio", + "al_ain", + "passagem_de_ano", + "trifolium_dubium", + "lago_dos_bosques", + "banco_central", + "a_bela_adormecida", + "peto_preto", + "delonix_regia", + "o_prazer_\u00e9_todo_meu", + "prunus_avium" + ], + "RELIGION": [ + "os_santos_dos_\u00faltimos_dias", + "zen", + "ismaelismo", + "maniqueismo", + "vedanta", + "presbiterianismo", + "manique\u00edsmo", + "catarismo", + "tao\u00edsmo", + "darshana", + "hinaiana", + "calvinismo", + "xintoismo", + "trinitarianismo", + "xinto\u00edsmo", + "ci\u00eancia_crist\u00e3", + "salafismo", + "wahabismo", + "anglocatolicismo", + "wicca" + ], + "PRODUCT": [ + "st_vincent", + "o_c\u00e3o_dos_baskervilles", + "the_hunger_games", + "justin_bieber", + "o_senhor_dos_an\u00e9is", + "as_quatro_esta\u00e7\u00f5es", + "em_mem\u00f3ria", + "the_time_machine", + "pela_gra\u00e7a_de_deus", + "as_pistas_de_blue", + "esp\u00edrito_santo", + "arco_triunfal", + "gongo", + "prensa_hidr\u00e1ulica", + "diego_garcia", + "pre\u00e1_da_\u00edndia", + "polichinelo", + "o_peregrino", + "as_de_mim", + "pinheirinho", + "multiplataforma", + "julius_caesar", + "por_um_fio", + "s\u00e3o_pedro_e_miquelon", + "the_star_spangled_banner", + "the_end_of_the_world", + "jo\u00e3o_galafoice", + "the_kid_brother", + "fim_do_mundo", + "mau_mau", + "novazel\u00e2ndia", + "die_hard", + "n\u00e3o_te_esquece", + "sax\u00f4nia_anhalt", + "montanhas_russas", + "after_burner", + "esta\u00e7\u00e3o_espacial", + "boxing_day", + "palavrascruzadas", + "o_gato_de_botas", + "deutsche_welle", + "autometralhadora", + "the_scarlet_letter", + "rio_san_joaquin", + "como_queira", + "mario_andretti", + "autom\u00f3vel_desportivo", + "n\u00e3o_me_esque\u00e7as", + "nova_zel\u00e2ndia", + "pinheiro_de_natal", + "st_george's", + "muito_barulho_por_nada", + "entre_dois_extremos", + "the_hitchhiker's_guide_to_the_galaxy", + "mios\u00f3tis", + "santa_catarina", + "de_facto", + "reino_unido", + "porquinho_da_\u00edndia", + "cal\u00e7\u00e3odebanho", + "cobaia", + "terra_m\u00e9dia", + "rolim\u00e3", + "antia\u00e9reo", + "a_doce_vida", + "novo_mesto", + "\u00e1rvore_de_natal", + "s\u00e3o_paulo" + ], + "DATE": [ + "dia_onom\u00e1stico", + "o_momento_da_verdade", + "sem_delonga", + "dia_mundial_da_\u00e1rvore", + "dog_days", + "dia_das_na\u00e7\u00f5es_unidas", + "era_comum", + "dia_da_independ\u00eancia_dos_estados_unidos", + "dia_de_todos_os_santos", + "happy_hour", + "ao_princ\u00edpio", + "dia_de_natal", + "a_ronda_noturna", + "horas_de_trabalho", + "in_time", + "dia_dos_fi\u00e9is_defuntos", + "veranico", + "walpurgisnacht", + "era_espacial", + "dia_da_independ\u00eancia", + "de_in\u00edcio", + "depois_de_cristo", + "era_do_gelo", + "era_glacial", + "dia_de_s\u00e3o_patr\u00edcio", + "dia_da_vit\u00f3ria", + "o_dia_depois_de_amanh\u00e3", + "plenil\u00fanio", + "dia_santo", + "dia_de_finados", + "the_golden_years", + "calend\u00e1rio_lunissolar", + "dia_das_m\u00e3es", + "dia_depois_de_amanh\u00e3", + "depois_de_amanh\u00e3", + "renascen\u00e7a_italiana", + "semivida", + "dia_de_f\u00e9rias", + "antes_de_tudo", + "dia_seguinte", + "dia_da_marmota", + "corpus_christi", + "noite_de_reis", + "era_dourada", + "dia_dos_pais", + "dia_da_mentira", + "twelfth_night", + "dia_do_canad\u00e1", + "em_primeiro_lugar", + "the_day_after" + ], + "FOOD": [ + "magustoit", + "kartoffelsalat", + "olla_podrida", + "mousse", + "lima_comum", + "morcela", + "fritada", + "bechamel", + "antepasto", + "desertos", + "kinako", + "almo\u00e7o", + "chicla", + "vigna_unguiculata", + "salada_de_frutas", + "chantili", + "capsicum", + "sandu\u00edche_submarino", + "rocambole", + "massa_folhada", + "aperitivo", + "white_russian", + "pinh\u00e3o", + "latic\u00ednio", + "catchup", + "pinot_noir", + "tinto", + "almo\u00e7ar", + "tapera", + "uvas", + "frisante", + "fraldinha", + "gengibirra", + "chuinga", + "comidinha", + "t_bone", + "alta_cozinha", + "chili", + "macrobi\u00f3tica", + "volov\u00e3", + "chile", + "caldeirada", + "latic\u00ednios", + "dessert", + "alta_gastronomia", + "pastilha_el\u00e1stica", + "limonada", + "maria_sangrenta", + "quent\u00e3o", + "ros\u00e9", + "birib\u00e1", + "sobremesas", + "sonchus_oleraceus", + "harvey_wallbanger", + "pot_au_feu", + "chiclete", + "lactic\u00ednio", + "sorvetes" + ], + "PERSON_PRONOUN": [ + "o_teu", + "a_si_pr\u00f3pria_mesma", + "i", + "as_senhoras", + "a_dela", + "he", + "minhas", + "minha", + "nosso", + "a_gente", + "de_algu\u00e9m", + "os_senhores", + "me", + "a_sua", + "o_seu", + "voc\u00eas", + "convosco", + "lhe", + "meus", + "consigo", + "o_dela", + "o_nosso" + ], + "SOC_ECO_CLASS": [ + "samurais", + "classe_oper\u00e1ria", + "fraternidade", + "labor", + "center", + "alguns", + "nobreza", + "samurai", + "caste", + "rossio", + "campesinato", + "proletariado", + "castas", + "classe_dominante", + "lumpemproletariado", + "classe_m\u00e9dia", + "classe_media", + "pariato", + "burguesia", + "de_elite", + "academia", + "alta_sociedade" + ], + "LANGUAGE": [ + "panjabi", + "vascon\u00e7o", + "shona", + "tchuvache", + "hisp\u00e2nico", + "tchetcheno", + "taitiano", + "portugu\u00eas", + "bengali", + "herer\u00f3", + "sindi", + "catal\u00e3o", + "rundi", + "caxemirense", + "requinte", + "venda", + "interlingue", + "canar\u00eas", + "tonicidade", + "lusit\u00e2nico", + "romena", + "bambara", + "coreanas", + "akan", + "bachquir", + "cazaque", + "georgiano", + "malaiala", + "sindhi", + "herer\u00f3s", + "coreana", + "samoana", + "mal\u00e1sio", + "pali", + "navajo", + "russa", + "sundan\u00eas", + "isl\u00e2ndes", + "r\u00e9tico", + "manx", + "portuguesas", + "refinamento", + "o_haitiano", + "portugueses", + "checheno", + "polimento", + "hindi", + "t\u00e2mil", + "tcheca", + "hereros", + "guarani", + "zhuang", + "herero", + "assam\u00eas", + "sango", + "laociano", + "divehi", + "esperanto", + "latino_americana", + "noruego", + "coreano", + "sotaque", + "lingala", + "hausa", + "lingua_h\u00fangara", + "portuguesa", + "marshall\u00eas", + "wolof", + "cree", + "lao", + "kikuyu", + "canar\u00e1", + "madagascarense", + "feroico", + "ido", + "faro\u00eas", + "tailandesa", + "checo", + "tcheco", + "tonga", + "tagalo" + ], + "QUANTITY": [ + "n\u00e3o_em_nada", + "polegada_c\u00fabica", + "volt_amp\u00e8re", + "quinhentos", + "estado_de_oxida\u00e7\u00e3o", + "franco_guineense", + "voltampere", + "tonelada", + "som_puro", + "quinze_para", + "arcossegundo", + "n\u00e3o_em_absoluto", + "dinar", + "won_sul_coreano", + "carrocinha", + "won_norte_coreano", + "tr\u00eas_reinos", + "g", + "rial", + "datilografia", + "face_a_face", + "parc\u00f4metro", + "caloria", + "pound", + "gasterosteus_aculeatus", + "um_a_um", + "esterlina", + "as_tr\u00eas_irm\u00e3s", + "c\u00e9lsio", + "octanagem", + "franco_franc\u00eas", + "volt_ampere", + "anders_celsius" + ], + "GENDER": [ + "piquiticu", + "miss", + "rapazote", + "garotinha", + "transg\u00e9nero", + "gentleman", + "petitinho", + "menininha", + "catatau", + "puatdabucets", + "boy", + "guido", + "cavalheiro", + "bissexual", + "rapazinho", + "petiz", + "bissexuado", + "transg\u00eanero", + "mocinho", + "fedelho", + "gal", + "cafetina", + "lady", + "garotinho", + "mulheril" + ], + "GPE": [ + "dia_de_s\u00e3o_jorge", + "centro_hist\u00f3rico", + "la_pampa", + "nossa_senhora_da_piedade", + "nossa_senhora_do_calv\u00e1rio", + "saint_domingue", + "nossa_senhora_da_soledade", + "kotte", + "dar_es_salaam", + "mar_vermelho", + "s\u00e3o_cristov\u00e3o", + "rio_grande_do_sul", + "espirito_santo", + "nossa_senhora", + "s\u00e3o_louren\u00e7o", + "s\u00e3o_nicolau", + "dia_de_s\u00e3o_valentim", + "novo_testamento", + "s\u00e3o_crist\u00f3v\u00e3o", + "bas\u00edlica_de_santa_sofia", + "grande_manila", + "s\u00e3o_tom\u00e9", + "vila_ol\u00edmpica", + "hagia_sofia", + "nossa_senhora_das_l\u00e1grimas", + "nossa_senhora_das_dores", + "s\u00e3o_jorge", + "santo_andr\u00e9", + "ponta_delgada", + "nossa_senhora_do_pranto", + "franco_condado", + "nossa_senhora_das_ang\u00fastias", + "s\u00e3o_pedro", + "s\u00e3o_jo\u00e3o_batista", + "al_andalus", + "s\u00e3o_martinho", + "cruz_vermelha", + "la_rochelle", + "s\u00e3o_judas_tadeu", + "nossa_senhora_das_sete_dores", + "hibiscus_rosa_sinensis", + "vinh_long", + "la_gomera", + "dia_dos_namorados", + "st_louis", + "nicolau_de_mira", + "santa_sofia", + "parque_industrial" + ], + "TITLE": [ + "mister", + "sir" + ], + "LAW": [ + "desacato", + "estatuo", + "tabeli\u00e3o", + "estado_de_direito", + "direito_romano", + "civil_law", + "supremo_tribunal", + "direito_administrativo", + "lei_marcial", + "derivativos", + "sistema_eleitoral", + "direito_civil", + "federal_bureau_of_investigation", + "direito_romano_germ\u00e2nico", + "suprema_corte_dos_estados_unidos_da_am\u00e9rica" + ], + "FAC": [ + "bebedouro", + "max_m\u00fcller", + "esta_noite", + "cabodaboaesperan\u00e7a", + "arcos_triunfais", + "de_sobreaviso", + "the_last_supper", + "arnold_sch\u00f6nberg", + "s\u00e3o_jos\u00e9_dos_campos", + "grundschule", + "frente_popular", + "max_muller", + "esta_tarde", + "santa_l\u00facia", + "petropavlovsk", + "cavalari\u00e7a", + "esta\u00e7\u00e3o_de_correios", + "pedro_i_da_r\u00fassia", + "aos_poucos", + "a_montanha_m\u00e1gica", + "as_quatro_esta\u00e7\u00f5es", + "estabelecimentos_de_ensino", + "arnold_schonberg", + "c\u00e2mara_baixa", + "combava", + "a_\u00faltima_ceia", + "sem_serifa", + "11_de_setembro", + "faculdade_de_medicina", + "de_pouquinho_em_pouquinho", + "faxinar", + "escola_prim\u00e1ria" + ], + "PERSON": [ + "julius_caesar", + "al_gore", + "tartaruga_negra", + "em_que_todos_saem_ganhando", + "h_g_wells", + "monte_tai", + "gioconda", + "woland", + "peixe_de_s\u00e3o_pedro", + "st_vincent", + "i_ching", + "s\u00e3o_jo\u00e3o_evangelista", + "don_delillo", + "este_sueste", + "e_e_cummings", + "s\u00e3o_vicente", + "edward_osborne_wilson", + "desde_ent\u00e3o", + "em_que_todos_ganham", + "de_witt", + "peixe_galo", + "ilha_de_s\u00e3o_vicente", + "t_bone", + "al_amin", + "igor_sikorsky", + "in_memory", + "\u00e9s_sueste", + "carl_david_anderson", + "este_sudeste", + "maxwell_anderson", + "boletus_edulis", + "rudolf_hess", + "s\u00e3o_jo\u00e3o_cris\u00f3stomo", + "dr_watson", + "auto_controle", + "eu_tamb\u00e9m", + "herbert_george_wells" + ], + "UNION": [ + "industrial_workers_of_the_world", + "gr\u00eamio_estudantil", + "uni\u00e3o_de_telecomunica\u00e7\u00e3o_internacional" + ], + "EVENT": [ + "grande_pr\u00e9mio", + "flor_de_lis" + ], + "POLITICAL_PARTY_MEMBER": [ + "da_rep\u00fablica", + "comunistas", + "comunista", + "federalista" + ], + "ner_regexes": [ + [ + "PERSON", + "\\D+ \\D+|\\D+ \\D+|\\D+ \\D+|\\D+ \\D+|\\D+ \\D+|\\D+ \\D+ \\D+|\\D+ \\D+|\\D+ \\D+|\\D+ \\D+|\\D+ \\D+|\\D+ \\D+|\\D+ \\D+ \\D+", + false, + [] + ], + [ + "PERSON", + "\\D+ \\D+|\\D+ \\D+|\\D+ \\D+|\\D+ \\D+|\\D+ \\D+|\\D+ \\D+|\\D+ \\D+|\\D+ \\D+ \\D+|\\D+ \\D+-\\D+|\\D+ \\D+|\\D+ \\D+|\\D+ \\D+|\\D+ \\D+|\\D+ \\D+|\\D+ \\D+|\\D+ \\D+|\\D+ \\D+ \\D+|\\D+ \\D+-\\D+|\\D+-\\D+ \\D+", + false, + [] + ] + ], + "FIRST_NAME_FEMALE": [ + "brenda", + "lara", + "ana_l\u00edvia", + "j\u00falia", + "m\u00e9lanie", + "\u00e9rica", + "evelyn", + "nat\u00e1lia", + "yara", + "sara", + "giovanna", + "isabelly", + "stephany", + "mirella", + "vit\u00f3ria", + "kelly", + "rebeca", + "mariane", + "stella", + "larissa", + "milena", + "flor", + "alexandra", + "olivia", + "valentina", + "alana", + "l\u00edvia", + "vict\u00f3ria", + "maria_julia", + "maria", + "al\u00edcia", + "sabrina", + "daniela", + "sophie", + "nicole", + "j\u00e9ssica", + "helo\u00edsa", + "emanuelly", + "diana", + "isadora", + "\u00e2ngela", + "helena", + "lav\u00ednia", + "bruna", + "elisa", + "maria_vit\u00f3ria", + "raquel", + "ana_vit\u00f3ria", + "eloah", + "maria_luiza", + "eva", + "\u00edris", + "constan\u00e7a", + "benedita", + "d\u00e9bora", + "laura", + "ana_j\u00falia", + "carlota", + "manuela", + "anita", + "beatriz", + "emanuella", + "ana_clara", + "leonor", + "caetana", + "lu\u00edsa", + "ana_sophia", + "fabiana", + "carolina", + "alexia", + "tatiana", + "mait\u00ea", + "iara", + "l\u00facia", + "cec\u00edlia", + "marina", + "gabrielly", + "carminho", + "la\u00eds", + "filipa", + "am\u00e9lia", + "petra", + "in\u00eas", + "maria_fernanda", + "marcela", + "catarina", + "yasmin", + "mariana", + "isabela", + "mara", + "andreia", + "esther", + "isabel", + "maria_clara", + "maria_alice", + "luciana", + "ana_carolina", + "fernanda", + "camila", + "ana_luiza", + "sophia", + "bianca", + "maria_eduarda", + "juliana", + "ana_julia", + "erica", + "gabriela", + "luiza", + "ana", + "nina", + "nair", + "julia", + "sarah", + "matilde", + "margarida", + "agatha", + "teresa", + "caroline", + "emilly", + "lia", + "erika", + "rita", + "kamilly", + "isis", + "ema", + "marta", + "amanda", + "ana_beatriz", + "let\u00edcia", + "melissa", + "isabella", + "naiara", + "violeta", + "emma", + "em\u00edlia", + "n\u00faria", + "alice", + "lorena", + "pietra", + "francisca", + "patr\u00edcia", + "ana_laura", + "soraia", + "salom\u00e9", + "clarice", + "mafalda", + "maria_cec\u00edlia", + "ariana", + "vera", + "adriana", + "maysa", + "pilar", + "renata", + "joana", + "luana", + "luna", + "miriam", + "madalena", + "n\u00e1dia", + "b\u00e1rbara", + "mia", + "sofia", + "rafaela", + "maria_sophia", + "irina", + "clara", + "kyara", + "eduarda" + ], + "FIRST_NAME_MALE": [ + "emanuel", + "igor", + "artur", + "duarte", + "luca", + "jo\u00e3o_pedro", + "jo\u00e3o_guilherme", + "anthony", + "k\u00e9vim", + "ivo", + "rafael", + "danilo", + "benjamin", + "francisco", + "pedro_henrique", + "breno", + "erick", + "luigi", + "gustavo_henrique", + "noah", + "lucas", + "levi", + "ismael", + "guilherme", + "m\u00e1rcio", + "renan", + "ben\u00edcio", + "bryan", + "daniel", + "nicolas", + "vitor", + "luiz_ot\u00e1vio", + "gaspar", + "jo\u00e3o_lucas", + "s\u00e9rgio", + "filipe", + "calebe", + "\u00e2ngelo", + "isaac", + "augusto", + "miguel", + "valentim", + "ian", + "jo\u00e3o_miguel", + "c\u00e9sar", + "vitor_hugo", + "edgar", + "enrico", + "thiago", + "marcelo", + "nathan", + "hugo", + "cau\u00e3", + "gabriel", + "pedro", + "caio", + "carlos", + "micael", + "ant\u00f3nio", + "diogo", + "lorenzo", + "manuel", + "denis", + "lucca", + "pedro_lucas", + "paulo", + "v\u00edtor", + "luiz_felipe", + "enzo_gabriel", + "jo\u00e3o_gabriel", + "jorge", + "salvador", + "jo\u00e3o_vitor", + "ryan", + "renato", + "gil", + "ot\u00e1vio", + "joel", + "vasco", + "theo", + "pedro_miguel", + "gon\u00e7alo", + "lisandro", + "mateus", + "wilson", + "gustavo", + "martim", + "louren\u00e7o", + "lu\u00eds", + "kaique", + "kevin", + "william", + "marcos_vinicius", + "alexandre", + "pietro", + "davi", + "afonso", + "leonardo", + "marcos", + "heitor", + "eduardo", + "enzo", + "matias", + "marco", + "luiz_fernando", + "sandro", + "cau\u00ea", + "raul", + "r\u00faben", + "sim\u00e3o", + "murilo", + "sebasti\u00e3o", + "lucas_gabriel", + "vinicius", + "andr\u00e9", + "vicente", + "bernardo", + "cl\u00e1udio", + "mauro", + "matheus", + "frederico", + "ricardo", + "m\u00e1rio", + "samuel", + "nelson", + "henrique", + "juan", + "jos\u00e9", + "nuno", + "davi_lucca", + "carlos_eduardo", + "luiz_miguel", + "jaime", + "david", + "davi_luiz", + "luiz_gustavo", + "thales", + "arthur", + "tom\u00e1s", + "rodrigo", + "dinis", + "jo\u00e3o", + "yago", + "thomas", + "xavier", + "jo\u00e3o_felipe", + "ant\u00f4nio", + "vitor_gabriel", + "felipe", + "ivan", + "luiz_henrique", + "f\u00e1bio", + "cristiano", + "brian", + "\u00e1lvaro", + "diego", + "davi_lucas", + "benjamim", + "yuri", + "tiago", + "leandro", + "bruno", + "noa", + "fernando", + "santiago", + "tom\u00e9", + "rui", + "joaquim" + ], + "PREFIX_FEMALE": [ + "sra", + "srta", + "dra" + ], + "PREFIX_MALE": [ + "dr", + "sr" + ], + "FIRST_NAME": [ + "emanuel", + "j\u00falia", + "luca", + "nat\u00e1lia", + "k\u00e9vim", + "ivo", + "vit\u00f3ria", + "benjamin", + "breno", + "milena", + "flor", + "gustavo_henrique", + "valentina", + "ismael", + "nicolas", + "vitor", + "maria", + "luiz_ot\u00e1vio", + "helena", + "lav\u00ednia", + "maria_vit\u00f3ria", + "eloah", + "maria_luiza", + "nathan", + "eva", + "constan\u00e7a", + "caio", + "d\u00e9bora", + "leonor", + "caetana", + "lorenzo", + "ana_sophia", + "alexia", + "pedro_lucas", + "luiz_felipe", + "v\u00edtor", + "marina", + "la\u00eds", + "am\u00e9lia", + "petra", + "renato", + "gil", + "theo", + "catarina", + "yasmin", + "isabela", + "gon\u00e7alo", + "mara", + "esther", + "wilson", + "luciana", + "gustavo", + "martim", + "camila", + "juliana", + "erica", + "luiza", + "ana", + "afonso", + "nina", + "julia", + "matias", + "agatha", + "raul", + "cau\u00ea", + "caroline", + "erika", + "vicente", + "matheus", + "let\u00edcia", + "henrique", + "nelson", + "jos\u00e9", + "n\u00faria", + "alice", + "pietra", + "patr\u00edcia", + "dinis", + "jo\u00e3o", + "yago", + "jo\u00e3o_felipe", + "vitor_gabriel", + "pilar", + "luna", + "diego", + "yuri", + "mia", + "rui", + "lara", + "jo\u00e3o_guilherme", + "giovanna", + "isabelly", + "francisco", + "rebeca", + "stella", + "alexandra", + "noah", + "levi", + "guilherme", + "alana", + "m\u00e1rcio", + "bryan", + "daniel", + "vict\u00f3ria", + "maria_julia", + "al\u00edcia", + "gaspar", + "jo\u00e3o_lucas", + "daniela", + "sophie", + "calebe", + "augusto", + "miguel", + "valentim", + "emanuelly", + "isadora", + "elisa", + "ana_vit\u00f3ria", + "cau\u00e3", + "pedro", + "benedita", + "laura", + "ana_j\u00falia", + "micael", + "lucca", + "cec\u00edlia", + "gabrielly", + "mariana", + "lisandro", + "fernanda", + "louren\u00e7o", + "lu\u00eds", + "sophia", + "gabriela", + "marcos_vinicius", + "pietro", + "leonardo", + "marco", + "margarida", + "sim\u00e3o", + "murilo", + "rita", + "marta", + "cl\u00e1udio", + "mauro", + "carlos_eduardo", + "violeta", + "jaime", + "davi_luiz", + "luiz_gustavo", + "lorena", + "francisca", + "ana_laura", + "tom\u00e1s", + "soraia", + "rodrigo", + "salom\u00e9", + "ariana", + "thomas", + "xavier", + "vera", + "adriana", + "maysa", + "f\u00e1bio", + "brian", + "tiago", + "leandro", + "sofia", + "noa", + "eduarda", + "ana_l\u00edvia", + "igor", + "\u00e9rica", + "evelyn", + "sara", + "anthony", + "mirella", + "kelly", + "mariane", + "luigi", + "lucas", + "olivia", + "l\u00edvia", + "sabrina", + "\u00e2ngelo", + "isaac", + "j\u00e9ssica", + "helo\u00edsa", + "ian", + "jo\u00e3o_miguel", + "bruna", + "edgar", + "hugo", + "\u00edris", + "carlota", + "ant\u00f3nio", + "diogo", + "denis", + "carolina", + "mait\u00ea", + "tatiana", + "paulo", + "l\u00facia", + "enzo_gabriel", + "jo\u00e3o_gabriel", + "filipa", + "jo\u00e3o_vitor", + "ryan", + "in\u00eas", + "ot\u00e1vio", + "joel", + "vasco", + "mateus", + "ana_carolina", + "kaique", + "bianca", + "ana_julia", + "nair", + "sarah", + "enzo", + "luiz_fernando", + "sandro", + "r\u00faben", + "emilly", + "lia", + "lucas_gabriel", + "isis", + "ema", + "vinicius", + "ana_beatriz", + "naiara", + "nuno", + "emma", + "david", + "thales", + "arthur", + "clarice", + "felipe", + "ivan", + "luiz_henrique", + "luana", + "joana", + "davi_lucas", + "b\u00e1rbara", + "rafaela", + "maria_sophia", + "fernando", + "santiago", + "tom\u00e9", + "kyara", + "joaquim", + "brenda", + "artur", + "duarte", + "m\u00e9lanie", + "jo\u00e3o_pedro", + "yara", + "stephany", + "rafael", + "danilo", + "pedro_henrique", + "erick", + "larissa", + "ben\u00edcio", + "renan", + "s\u00e9rgio", + "nicole", + "filipe", + "diana", + "\u00e2ngela", + "c\u00e9sar", + "vitor_hugo", + "enrico", + "raquel", + "thiago", + "marcelo", + "gabriel", + "carlos", + "manuela", + "anita", + "beatriz", + "emanuella", + "ana_clara", + "lu\u00edsa", + "manuel", + "fabiana", + "iara", + "salvador", + "jorge", + "carminho", + "maria_fernanda", + "pedro_miguel", + "marcela", + "andreia", + "isabel", + "maria_clara", + "maria_alice", + "ana_luiza", + "kevin", + "maria_eduarda", + "william", + "alexandre", + "davi", + "marcos", + "heitor", + "eduardo", + "matilde", + "teresa", + "sebasti\u00e3o", + "kamilly", + "andr\u00e9", + "bernardo", + "amanda", + "frederico", + "melissa", + "ricardo", + "m\u00e1rio", + "samuel", + "juan", + "isabella", + "davi_lucca", + "luiz_miguel", + "em\u00edlia", + "mafalda", + "maria_cec\u00edlia", + "ant\u00f4nio", + "renata", + "cristiano", + "\u00e1lvaro", + "miriam", + "madalena", + "n\u00e1dia", + "benjamim", + "bruno", + "irina", + "clara" + ], + "LAST_NAME": [ + "machado", + "duarte", + "rodrigues", + "neto", + "barbosa", + "dias", + "gomes", + "andrade", + "martins", + "ara\u00fajo", + "da_rosa", + "faria", + "arag\u00e3o", + "tavares", + "ramos", + "miranda", + "campos", + "peixoto", + "nogueira", + "almeida", + "cunha", + "gaspar", + "macedo", + "cardoso", + "maia", + "porto", + "assun\u00e7\u00e3o", + "cavalcanti", + "garcia", + "teixeira", + "morais", + "matos", + "guerreiro", + "leite", + "mota", + "pereira", + "anjos", + "novaes", + "da_cunha", + "batista", + "oliveira", + "jesus", + "branco", + "figueiredo", + "nunes", + "abreu", + "esteves", + "amaral", + "lima", + "mendes", + "moraes", + "santos", + "das_neves", + "silva", + "fernandes", + "foga\u00e7a", + "da_luz", + "da_mota", + "vaz", + "da_concei\u00e7\u00e3o", + "magalh\u00e3es", + "coelho", + "louren\u00e7o", + "moura", + "da_rocha", + "borges", + "carvalho", + "reis", + "costa", + "brito", + "pinho", + "matias", + "sim\u00f5es", + "henriques", + "antunes", + "leal", + "monteiro", + "sousa", + "souza", + "da_costa", + "caldeira", + "sales", + "vicente", + "valente", + "amorim", + "da_cruz", + "rocha", + "gon\u00e7alves", + "farias", + "pacheco", + "pinto", + "correia", + "melo", + "da_mata", + "moreira", + "lopes", + "rezende", + "vieira", + "torres", + "cruz", + "s\u00e1", + "viana", + "castro", + "soares", + "alves", + "pinheiro", + "costela", + "ferreira", + "da_paz", + "domingues", + "fonseca", + "freitas", + "silveira", + "paiva", + "marques", + "loureiro", + "baptista", + "carneiro", + "azevedo", + "barros", + "pires", + "neves", + "nascimento", + "ribeiro" + ], + "OTHER_PRONOUN": [ + "it" + ], + "LAST_NAME_MALE": [], + "LAST_NAME_FEMALE": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "abbadessa": "abba", + "abadessa": "arquimandrita", + "actriz": "int\u00e9rprete", + "atriz": "ator", + "ator": "actriz", + "aviadora": "aviador", + "baronesa": "magnata", + "rec\u00e9m_casada": "estribeiro", + "noiva": "cuidar_se", + "mulher_de_neg\u00f3cios": "empres\u00e1rio", + "working_girl": "homem_de_neg\u00f3cios", + "vaqueira": "cowboy", + "duquesa": "duque", + "imperadora": "kaiser", + "imperatriz": "kaiser", + "fem\u00edneo": "m\u00e1sculo", + "feminal": "masculina", + "femeal": "m\u00e1sculo", + "f\u00eamea": "masculina", + "feminino": "masculino", + "feminil": "masculino", + "mulheril": "m\u00e1sculo", + "f\u00eameo": "m\u00e1sculo", + "gal": "guido", + "governanta": "governadora", + "jeje": "lia", + "heroina": "her\u00f3i", + "hero\u00edna": "heroina", + "a_sua": "deles", + "o_dela": "deles", + "o_seu": "deles", + "a_dela": "deles", + "a_si_pr\u00f3pria_mesma": "a_si_mesmo", + "anfitri\u00e3o": "celebrar", + "anfitrioa": "the_host", + "anfitri\u00e3": "hoste", + "lady": "lorde", + "marquise": "marqu\u00eas", + "marquesa": "marqu\u00eas", + "massageadora": "massageador", + "errar_o_golpe": "sir", + "miss": "sir", + "faltar": "sir", + "sentir_saudade": "sir", + "falhar": "sir", + "senhorita": "sir", + "necessitar": "sir", + "miss_a": "sir", + "ter_car\u00eancia_de": "sir", + "mancar": "sir", + "sentir_falta": "sir", + "missa": "sir", + "sentir_saudades": "sir", + "n\u00e3o_ter": "sir", + "evadir_se": "sir", + "ter_falta_de": "sir", + "carecer": "sir", + "flama": "patr\u00e3o", + "chefa": "m\u00e1ster", + "directoria": "patr\u00e3o", + "m\u00e3e": "genitor", + "progenitora": "genitor", + "matrix": "painho", + "sra": "\u03ba", + "sobrinha": "sobrinho", + "monja": "monachus", + "religiosa": "monachus", + "freiras": "frade", + "soror": "monge", + "freira": "monachus", + "nun": "religioso", + "sacerdotisa": "abade", + "pr\u00edncipe": "prince", + "princesa": "regulus", + "infanta": "regulus", + "princessa": "prince", + "esta\u00e7\u00e3o_queen": "esta\u00e7\u00e3o_king", + "rainha": "key", + "hetman": "indra", + "feiticeira": "wizard", + "solteirona": "celibat\u00e1rio", + "solteira": "solteir\u00e3o", + "enteada": "enteado", + "andada": "enteado", + "sogra": "padrasto", + "madrasta": "padrasto", + "aeromo\u00e7a": "gestor", + "hospedeira": "tafeiro", + "camareira": "empregado_de_mesa", + "gar\u00e7om": "gar\u00e7onete", + "gar\u00e7onete": "empregado_de_mesa", + "viuvez": "vi\u00favo", + "enviuvar": "vi\u00favo", + "vi\u00fava": "vi\u00favo", + "marido": "c\u00f4njuge", + "esposa": "marido", + "duna": "esposo", + "bojo": "esposo", + "hex": "magician", + "striga": "wizard", + "bruxa": "wizard", + "wicca": "wizard", + "feto": "tripular" + }, + "other_gender_swap": { + "eles": "jeje", + "lhes": "jeje", + "seus": "jeje", + "lia": "deles", + "deles": "o_seu", + "he": "elas", + "elli": "elas", + "lhe": "eles", + "jeje": "seus", + "a_sua": "deles", + "o_dela": "deles", + "o_seu": "deles", + "a_dela": "deles" + }, + "en_pronoun2gender": { + "they": [ + "transexual", + "homossexual", + "transg\u00e9nero", + "bissexual", + "transg\u00eanero", + "bissexuado" + ], + "he": [ + "mo\u00e7o", + "rapazinho", + "masculino", + "rachar", + "boy", + "petiz", + "fedelho", + "guri", + "guido", + "fidalgo", + "cavalheiro", + "masculina", + "gentleman", + "ilha_de_man", + "petitinho", + "rapazote", + "catatau", + "m\u00e1sculo", + "tripular", + "gentil_homem", + "little_boy", + "piquiticu", + "garotinho", + "baixinho", + "marido", + "rachadura", + "mancebo", + "mocinho" + ], + "she": [ + "f\u00eamea", + "falhar", + "femeal", + "miss", + "faltar", + "sentir_saudade", + "fem\u00edneo", + "arrumadeira", + "ter_falta_de", + "lesbianismo", + "n\u00e3o_ter", + "brasa", + "puatdabucets", + "missa", + "evadir_se", + "f\u00eameo", + "empregada", + "lesbica", + "feto", + "empregada_dom\u00e9stica", + "carecer", + "sexo_fr\u00e1gil", + "sentir_falta", + "feminal", + "srta", + "gal", + "sentir_saudades", + "feminino", + "ter_car\u00eancia_de", + "garotinha", + "menininha", + "mulheril", + "criada", + "feminil", + "lady", + "cafetina", + "l\u00e9sbica", + "senhorita", + "camareira", + "miss_a", + "mancar", + "necessitar", + "errar_o_golpe", + "criada_de_quarto" + ] + }, + "en_pronoun2pronoun": { + "he": [ + "he", + "lia", + "lhe", + "elli", + "a_si_mesmo" + ], + "she": [ + "a_si_pr\u00f3pria_mesma", + "o_dela", + "a_sua", + "o_seu", + "a_dela", + "jeje" + ], + "they": [ + "eles", + "lhes", + "lia", + "oms", + "seus", + "deles", + "elas", + "epi" + ], + "it": [ + "diese", + "aquele", + "ova", + "isto", + "essa", + "per_se", + "tyto", + "estes", + "disse", + "quisto", + "it", + "esses", + "a_si_mesmo", + "esta", + "isso", + "tento", + "ico", + "aqueles" + ] + }, + "en_pronoun2title": {}, + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/qu.json b/data_tooling/pii_processing/ontology/data/qu.json new file mode 100644 index 0000000..08a3614 --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/qu.json @@ -0,0 +1,437 @@ +{ + "PLANT": [ + "purutu", + "insina", + "una_llunku", + "chaqullu", + "tutuma", + "santa_mariya", + "chaparru", + "chipika", + "chamiku", + "sanurya", + "awaymantu", + "saramuyu", + "sanawrya", + "yarawisqu", + "chirimuya", + "hawas", + "sawintu", + "sayri", + "kapiqantu", + "walusa", + "tarku", + "siwuk", + "saqarara", + "lumu", + "rimulacha", + "piliyuyu", + "kharwinchu", + "chanqu", + "pinu", + "k_uyu", + "mustasa", + "k_awchu_sach_a", + "pilliyuyu", + "k_aspicha_ruwli", + "yuka", + "wayaw", + "k_ita_p_akincha", + "kapuli", + "kiwicha", + "hanachiwa", + "sirwila", + "kampachu", + "alkachu", + "kukuna", + "k_ita_waranqaysu" + ], + "PUBLIC_FIGURE": [ + "benjamin_franklin", + "akira_kurosawa", + "heinrich_hertz", + "giovanni_boccaccio", + "ernesto_guevara", + "maria_callas", + "iskay", + "eduard_buchner", + "winston_churchill", + "ivan_pavlov", + "isaac_newton", + "victor_hugo", + "mary_stuart", + "george_harrison", + "george_orwell", + "richard_wagner", + "pancho_villa", + "marie_curie", + "michael_jackson", + "el_greco", + "galileo_galilei", + "robert_koch", + "edmund_hillary", + "vincent_van_gogh", + "emiliano_zapata", + "cristobal_colon", + "yuri_gagarin", + "samuel_johnson", + "jesus", + "marie_antoinette", + "giuseppe_verdi", + "karl_jaspers", + "konrad_adenauer", + "frank_sinatra", + "katharine_hepburn", + "henri_becquerel", + "louis_pasteur", + "john_ford", + "charles_de_gaulle", + "paul_von_hindenburg", + "y", + "f", + "thomas_mann", + "dante_alighieri", + "giacomo_puccini", + "louis_braille", + "nicolas_poussin", + "oscar_wilde", + "don_quijote", + "laurence_olivier", + "francis_bacon", + "pete_seeger", + "immanuel_kant", + "johannes_kepler", + "max_planck", + "julio_iglesias", + "john_bardeen", + "carl_lewis", + "canberra", + "edward_jenner", + "tawantinsuyu", + "montesquieu", + "arthur_rubinstein", + "niels_bohr", + "bertrand_russell", + "rudolf_diesel", + "walt_disney", + "friedrich_engels", + "ian_fleming", + "wolfgang_pauli", + "marcel_proust", + "thomas_more", + "elizabeth_taylor", + "indira_gandhi", + "alfred_nobel", + "jesse_owens", + "marco_polo", + "caravaggio", + "cary_grant", + "pieter_zeeman", + "pablo_picasso", + "paul_simon", + "adam_smith", + "karl_marx", + "friedrich_nietzsche", + "i", + "sandro_botticelli", + "nikola_tesla", + "charles_barkley", + "robert_schumann", + "le_corbusier", + "helen_keller", + "ingrid_bergman", + "jean_piaget", + "william_wyler", + "adolf_hitler", + "fritz_haber", + "joseph_haydn", + "garfield", + "edvard_grieg", + "robert_boyle", + "vladimir_putin", + "g", + "martin_heidegger", + "r", + "andrew_jackson", + "louis_armstrong", + "steven_spielberg", + "giuseppe_garibaldi", + "alexandre_dumas", + "bobby_fischer", + "johannes_gutenberg", + "william_faulkner", + "amerigo_vespucci", + "putin", + "jean_de_la_fontaine", + "peter_o'toole", + "peter_paul_rubens", + "jules_verne", + "paul_newman", + "iskai", + "mikhail_gorbachov", + "john_lennon", + "charlie_chaplin", + "hannah_arendt", + "miles_davis", + "stanley_kubrick", + "john_huston", + "james_watt", + "ronald_reagan", + "helmut_schmidt", + "martin_luther_king", + "frank_capra", + "woodrow_wilson", + "gustav_hertz", + "st_louis", + "ernest_hemingway", + "jacques_charles", + "nelson_mandela", + "mohandas_gandhi", + "roald_amundsen", + "charles_dickens", + "ella_fitzgerald", + "jacques_offenbach", + "willy_brandt", + "francisco_pizarro", + "francisco_franco", + "bernardo_bertolucci", + "anna_pawlowa", + "franz_schubert", + "johnny_cash", + "mick_jagger", + "georges_cuvier", + "albert_einstein", + "chiang_kai_shek", + "t", + "wilhelm_ostwald" + ], + "DISEASE": [ + "chincha_kasta\u00f1a", + "k_iri", + "chhulli", + "nanay", + "wiksayay", + "garaca", + "para", + "khachuy", + "kanii", + "amaychura", + "chi", + "muchhi", + "illanchay", + "hilli", + "t_ukuch_uqu", + "miraywa", + "qarati", + "papa_lancha", + "chukchu", + "wirakaray", + "kallu", + "uma_nanay", + "punkillikuy", + "qharqayuy", + "evola_virusmanta_unquyqa", + "t_iyu_unquy", + "kuru", + "kaniy", + "jilli", + "krup", + "suphullu" + ], + "ORG": [ + "barbara_nikomidyamanta", + "hananqucha", + "san_francisco", + "wayrachina", + "palistina_kamachikuy", + "munayki", + "hatun_yachaq_tantari", + "allpa_llamk_ay", + "los_angeles", + "santa_lusiya_wat_a", + "killa_wa\u00f1uy" + ], + "PRODUCT": [ + "justin_bieber", + "yayayku", + "gowi", + "waqachina", + "sachsen_anhalt", + "kuymi", + "ch_uya_ispiritu", + "nordrhein_westfalen", + "romeowan_juliet", + "musuq_rimanakuy", + "wasi_quwi", + "kututu" + ], + "ANIMAL": [ + "kuyucha", + "sillwichaki", + "antharu", + "chinkirma", + "waqar", + "ruysi\u00f1ur", + "kuntur", + "bisunti", + "k_ayra", + "chururu", + "iskaynintinchaki", + "linsi", + "wiskul", + "wankana", + "achuqalla", + "kututu", + "wiruchu", + "gurila", + "kuchipillan", + "uma_usa", + "ampatu", + "huku", + "lachiwa", + "k_illichu", + "kutimpu", + "murira_pillpintu", + "manqu", + "unchuchukuy", + "ullasku", + "alsi", + "illawi", + "pallaysu", + "tiwtinku" + ], + "JOB": [ + "hampiqhatuq", + "takichaq", + "pichaq", + "para", + "chayachiy", + "awqapuri", + "kuyuti", + "chapaq", + "kuraka", + "t_aqsaq", + "umalliq", + "kamachiq", + "willaq", + "hampikamayuq", + "qillqaq", + "pichay" + ], + "GPE": [ + "dar_es_salaam", + "barbara_nikomidyamanta", + "runa_hay\u00f1i", + "aya_sophiya", + "st_louis", + "simun_pidru" + ], + "PERSON_PRONOUN": [ + "i", + "nogakuna" + ], + "BIO_CHEM_ENTITY": [ + "ullaya" + ], + "GENDER": [ + "chakwas", + "macu", + "warmi", + "taski" + ], + "FAC": [ + "huch_uy_yachay_wasi", + "atakama", + "kathuliku_inlisya", + "respecto_pooh" + ], + "LOCATION": [ + "urnu_\u00f1awch_i", + "agradiseyki", + "1_\u00f1iqin_qhulla_puquy_killapi", + "hananqucha", + "usa", + "q_illu_mayu", + "hanpuy", + "sri_lanka", + "q_umir_kawu", + "the_rolling_stones", + "louis_joseph_gay_lussac" + ], + "RELIGION": [ + "islam" + ], + "QUANTITY": [ + "si_tupuy", + "g", + "takay" + ], + "FOOD": [ + "runtu", + "lunqanus", + "chili", + "utsu" + ], + "DATE": [ + "k_ikuy", + "killapura" + ], + "PERSON": [ + "kimsa_chunka_iskayniyuq", + "k_awchu_sach_a" + ], + "SOC_ECO_CLASS": [ + "waki" + ], + "LANGUAGE": [ + "malayalam_simi", + "ido" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "\u00f1ust_a": "awki", + "quya": "qhapaq", + "\u00f1a\u00f1a": "wawqi", + "hatun": "qhari", + "warmi": "qhari" + }, + "other_gender_swap": { + "paykuna": "chila", + "chila": "paykuna" + }, + "en_pronoun2gender": { + "he": [ + "qhari" + ], + "she": [ + "warmi", + "taski", + "hatun" + ] + }, + "en_pronoun2pronoun": { + "she": [ + "chila" + ], + "they": [ + "paykuna", + "suya" + ], + "it": [ + "kuwa", + "disi", + "kaykuna" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/rap.json b/data_tooling/pii_processing/ontology/data/rap.json new file mode 100644 index 0000000..22886bf --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/rap.json @@ -0,0 +1,43 @@ +{ + "DISEASE": [ + "ki" + ], + "PERSON_PRONOUN": [ + "i", + "korua" + ], + "JOB": [ + "mate" + ], + "PUBLIC_FIGURE": [ + "o", + "i" + ], + "GENDER": [ + "vahine" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": {}, + "other_gender_swap": {}, + "en_pronoun2gender": { + "she": [ + "vahine" + ] + }, + "en_pronoun2pronoun": { + "they": [ + "raua" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/rm.json b/data_tooling/pii_processing/ontology/data/rm.json new file mode 100644 index 0000000..ab1def0 --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/rm.json @@ -0,0 +1,221 @@ +{ + "JOB": [ + "translatura", + "mariner", + "litinent", + "schuldo", + "sriptura", + "translatur", + "leder", + "schuldau", + "cuschinier", + "schuld\u00e0", + "marangun", + "ratun", + "tenent", + "cuschinar", + "barbier", + "barber", + "giugadur", + "lainari", + "giovader", + "turner" + ], + "PLANT": [ + "paloja", + "chastagner", + "rischmelna", + "artist", + "ischi", + "carotta", + "plum", + "papaver", + "baguos", + "tscharescha", + "prem", + "rischcotschna", + "cardifiol", + "primbla", + "paloga", + "cavazza", + "tschariescha", + "tscherescha", + "br\u00fcmbla", + "tschirescha", + "riebla" + ], + "ANIMAL": [ + "castur", + "tschierv", + "pignouler", + "sprer", + "merlotscha", + "passer", + "merl", + "mustaila", + "tschess", + "tschuetta", + "fiergna", + "pulschain", + "pirol", + "chavriel", + "stambutg", + "durmigliet" + ], + "DISEASE": [ + "sanglut", + "caleira", + "singlut", + "gumma", + "starn\u00fcder", + "dular", + "calira", + "furuncel", + "dolair", + "furuncul", + "singluot", + "ed", + "crappagls", + "stirnidar", + "furunchel", + "sangluot", + "bignun", + "biergna", + "starn\u00fcdar", + "chalur", + "mi", + "sturnidar", + "aura", + "dulair", + "dolur", + "mieur", + "starnidar" + ], + "LANGUAGE": [ + "germanais", + "grecca", + "polac", + "germanaisa" + ], + "FOOD": [ + "desert", + "limunada", + "farina", + "ensolver", + "dasiert", + "chile", + "desiert" + ], + "QUANTITY": [ + "franc_svizzer" + ], + "PUBLIC_FIGURE": [ + "spraunza", + "speronza", + "jesus", + "e", + "sperar", + "sperer", + "bulsaun", + "peider", + "putin", + "gesu" + ], + "GENDER": [ + "mastgel", + "mascal", + "buob", + "mas_cel", + "mascel", + "mes_cel" + ], + "SOC_ECO_CLASS": [ + "sozietad", + "societed", + "societad" + ], + "RACE": [ + "latin", + "american" + ], + "POLITICAL_PARTY_MEMBER": [ + "camarad" + ], + "LOCATION": [ + "buna_saira", + "buna_notg" + ], + "PERSON_PRONOUN": [ + "our", + "her", + "noss" + ], + "ORG": [ + "armeda", + "furmaziun", + "baselgia_catolica_romana", + "disa", + "mi", + "baselgia_catolica", + "scola" + ], + "PRODUCT": [ + "portg_da_mar" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "femella": "mascel", + "ra\u00efna": "retg", + "rigegna": "retg", + "sour": "camerata", + "duonna": "human", + "femna": "human" + }, + "other_gender_swap": { + "ellas": "sun", + "sun": "ellas" + }, + "en_pronoun2gender": { + "he": [ + "mastgel", + "mascal", + "mas_cel", + "buob", + "giuven", + "mascel", + "mes_cel", + "human" + ], + "she": [ + "femna", + "duonna", + "femella" + ] + }, + "en_pronoun2pronoun": { + "she": [ + "sun", + "her" + ], + "they": [ + "ellas" + ], + "it": [ + "chista", + "ova", + "quest", + "questa" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/ro.json b/data_tooling/pii_processing/ontology/data/ro.json new file mode 100644 index 0000000..709679c --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/ro.json @@ -0,0 +1,3290 @@ +{ + "PUBLIC_FIGURE": [ + "lawrence_durrell", + "henry_cavendish", + "matthew_arnold", + "benjamin_franklin", + "martin_buber", + "akira_kurosawa", + "jean_genet", + "john_knox", + "heinrich_hertz", + "roger_williams", + "giovanni_boccaccio", + "cornelius_vanderbilt", + "rudolf_steiner", + "thomas_bayes", + "johann_bernoulli", + "max_bruch", + "charles_best", + "leonard_bernstein", + "che_guevara", + "georges_simenon", + "c", + "john_barth", + "edward_albee", + "maria_callas", + "henrik_ibsen", + "vasili_kandinski", + "william_gladstone", + "mary_shelley", + "franz_werfel", + "marcello_malpighi", + "peter_lorre", + "david_livingstone", + "eduard_buchner", + "john_herschel", + "andrzej_wajda", + "jan_van_eyck", + "george_balanchine", + "georg_wilhelm_steller", + "richard_burton", + "douglas_macarthur", + "mary_wollstonecraft", + "cei_mai_mul\u021bi", + "j_edgar_hoover", + "maria_magdalena", + "winston_churchill", + "nicolaus_copernic", + "johannes_diderik_van_der_waals", + "andrei_saharov", + "giambattista_marini", + "conrad_aiken", + "karl_landsteiner", + "ivan_pavlov", + "paul_mccartney", + "richard_smalley", + "andrew_marvell", + "terry_pratchett", + "general_de_brigad\u0103", + "stephen_king", + "francis_crick", + "ecaterina", + "isaac_newton", + "victor_hugo", + "edwin_hubble", + "milton_friedman", + "edward_gibbon", + "jefferson_davis", + "saint_louis", + "george_stephenson", + "john_glenn", + "george_burns", + "george_harrison", + "george_orwell", + "ronald_norrish", + "arthur_koestler", + "richard_wagner", + "williams", + "thornton_wilder", + "pancho_villa", + "rebecca_west", + "marie_curie", + "francis_galton", + "michael_jackson", + "spera", + "e_entertainment", + "thomas_hobbes", + "el_greco", + "samuel_beckett", + "maximian", + "david", + "galileo_galilei", + "jane_goodall", + "john_donne", + "robert_koch", + "joseph_goebbels", + "george_eastman", + "john_steinbeck", + "edmund_hillary", + "vincent_van_gogh", + "richard_hooker", + "serghei_rahmaninov", + "william_hazlitt", + "anne_boleyn", + "john_ruskin", + "robert_burns", + "hans_albrecht_bethe", + "thomas_paine", + "bari", + "liliuokalani", + "francis_beaumont", + "steven_weinberg", + "mary_pickford", + "hans_fischer", + "emiliano_zapata", + "karl_barth", + "willem_einthoven", + "thomas_willis", + "samuel_johnson", + "giuseppe_verdi", + "walter_lippmann", + "e", + "karl_jaspers", + "hideki_yukawa", + "konrad_adenauer", + "marianne_moore", + "norbert_wiener", + "john_masefield", + "maurice_chevalier", + "gottlieb_daimler", + "frank_sinatra", + "lauren\u021biu", + "abel_tasman", + "katharine_hepburn", + "henri_matisse", + "louis_pasteur", + "richard_strauss", + "stephen_decatur", + "leslie_howard", + "hugo_grotius", + "mahalia_jackson", + "john_ford", + "stephen_foster", + "katherine_mansfield", + "gertrude_stein", + "saladin", + "sarah_bernhardt", + "feodor_dostoievski", + "moise", + "luigi_pirandello", + "igor_stravinski", + "elisabeta", + "andreescu", + "dorothea_lange", + "charles_de_gaulle", + "paul_von_hindenburg", + "y", + "henry_moore", + "holden", + "charles_lindbergh", + "vincenzo_bellini", + "f", + "john_jay", + "ludwig_wittgenstein", + "august_strindberg", + "thomas_mann", + "william_ockham", + "alla_nazimova", + "charles_goodyear", + "dante_alighieri", + "margot_fonteyn", + "peter_pan", + "james_tobin", + "john_irving", + "samuel_de_champlain", + "giacomo_puccini", + "fridtjof_nansen", + "louis_braille", + "herbert_marcuse", + "mungo_park", + "benedict_arnold", + "paul_verlaine", + "robert_johnson", + "james_dean", + "robert", + "mason", + "marie_tussaud", + "theodor_schwann", + "alessandro_manzoni", + "joseph_priestley", + "nicolas_poussin", + "andrea_mantegna", + "joseph_pulitzer", + "james_naismith", + "oscar_wilde", + "philip_roth", + "j_d_salinger", + "richard_trevithick", + "heinrich_schliemann", + "don_quijote", + "laurence_olivier", + "pierre_larousse", + "christiaan_eijkman", + "adolf_eichmann", + "vulturul", + "octaviu", + "francis_bacon", + "pete_seeger", + "konstantin_stanislavski", + "joseph_heller", + "a", + "morris", + "norman_rockwell", + "james_brown", + "william_hogarth", + "charles_baudelaire", + "luigi_cherubini", + "david_ricardo", + "mary_leakey", + "immanuel_kant", + "licen\u021biat", + "james_franck", + "william_crookes", + "nellie_bly", + "warburg", + "stephen_leacock", + "albert_schweitzer", + "john_harvard", + "johann_friedrich_herbart", + "giulio_natta", + "johannes_kepler", + "william_s_burroughs", + "max_planck", + "william_blake", + "t_e_lawrence", + "julio_iglesias", + "john_bardeen", + "sarah_vaughan", + "john_wilkes", + "william_byrd", + "william_henry", + "scott_joplin", + "carl_lewis", + "sarah_siddons", + "george_vancouver", + "canberra", + "sf\u00e2ntul_cristofor", + "elias_canetti", + "edward_jenner", + "oliver_hardy", + "jean_luc_godard", + "graham_greene", + "frans_hals", + "medic", + "sinucide", + "lars_onsager", + "margaret_mitchell", + "sf\u00e2ntul_gheorghe", + "cristofor_columb", + "william_herschel", + "joseph_black", + "arthur_rubinstein", + "niels_bohr", + "marc_antoniu", + "henry_fielding", + "bertrand_russell", + "michael_faraday", + "john_d_rockefeller", + "anthony_burgess", + "jan_tinbergen", + "charles_de_secondat_baron_de_montesquieu", + "irving_berlin", + "rudolf_diesel", + "walt_disney", + "ben_jonson", + "simon_petru", + "h_l_mencken", + "joseph_schumpeter", + "gabriel_lippmann", + "steve_reich", + "lee", + "friedrich_engels", + "jane_austen", + "charles_laughton", + "gustav_mahler", + "phil_collins", + "robert_redford", + "jean_giraudoux", + "ian_fleming", + "richard_feynman", + "wolfgang_pauli", + "theodore_dreiser", + "theodor_mommsen", + "andrew_huxley", + "marcel_proust", + "homo_heidelbergensis", + "petru", + "paul_hindemith", + "elizabeth_taylor", + "benedict", + "john_dowland", + "william_golding", + "william_caxton", + "john_milton", + "ethel_merman", + "samuel_adams", + "albert_speer", + "indira_gandhi", + "jane_seymour", + "george_gershwin", + "alberto_giacometti", + "alfred_nobel", + "jesse_owens", + "daniel_rutherford", + "marco_polo", + "john_fletcher", + "caravaggio", + "charlie_watts", + "petur", + "marcel_marceau", + "allen_ginsberg", + "fred_zinnemann", + "daniel_bernoulli", + "guillaume_apollinaire", + "antoine_watteau", + "pablo_casals", + "joseph_henry", + "henri_bergson", + "str\u0103bunici", + "boris_karloff", + "pierre_corneille", + "patrick_white", + "saul_steinberg", + "catherine_howard", + "hans_christian_andersen", + "william_morris", + "cary_grant", + "hideyo_noguchi", + "pieter_zeeman", + "petre", + "steward", + "pablo_picasso", + "jack_spintec\u0103torul", + "natalie_wood", + "l_ron_hubbard", + "valentina_tere\u0219kova", + "thomas_moore", + "osman_i", + "otto_hahn", + "christiaan_huygens", + "hector_berlioz", + "paul_simon", + "claudio_monteverdi", + "john_galsworthy", + "robert_robinson", + "o", + "adam_smith", + "william_james", + "u", + "jean_harlow", + "henry_miller", + "karl_marx", + "friedrich_nietzsche", + "co\u0219ar", + "i", + "john_wesley", + "sandro_botticelli", + "carson_mccullers", + "seiji_ozawa", + "nikola_tesla", + "al_capone", + "billy_graham", + "robert_schumann", + "mel_gibson", + "le_corbusier", + "carlo_goldoni", + "john_locke", + "alexis_carrel", + "joseph_marie_jacquard", + "henry_james", + "bacalaureat", + "helen_keller", + "paul_dukas", + "ingrid_bergman", + "anna_kurnikova", + "tuomas", + "antoniu", + "jean_piaget", + "william_congreve", + "frank_norris", + "h_g_wells", + "walt_whitman", + "william_wyler", + "john_osborne", + "colin_powell", + "ludwig_boltzmann", + "carl_nielsen", + "leopold_kronecker", + "richard_wright", + "adolf_hitler", + "james_d_watson", + "fritz_haber", + "archibald_macleish", + "peter_behrens", + "joseph_haydn", + "garfield", + "george_boole", + "paul_revere", + "edvard_grieg", + "robert_boyle", + "edith_cavell", + "alan_paton", + "1", + "rosa_parks", + "norman_jewison", + "samuel_goldwyn", + "ernest_walton", + "vladimir_putin", + "giuseppe_mazzini", + "hertz", + "arnold_sch\u00f6nberg", + "laurence_sterne", + "ben_hecht", + "anne_hathaway", + "clarence_darrow", + "charles_lamb", + "g", + "charles_coulomb", + "arthur_schopenhauer", + "thomas_dekker", + "james_cagney", + "martin_heidegger", + "r", + "george_lucas", + "andrew_jackson", + "louis_armstrong", + "steven_spielberg", + "jean_monnet", + "leonard", + "d_w_griffith", + "robert_fulton", + "thomas_hardy", + "thomas_gainsborough", + "giuseppe_garibaldi", + "philip_warren_anderson", + "alexandre_dumas", + "robert_brown", + "thomas_carlyle", + "donald_barthelme", + "william_tyndale", + "bobby_fischer", + "johannes_gutenberg", + "lacul_tana", + "james_bowie", + "thomas_malthus", + "gaetano_donizetti", + "william_faulkner", + "titus_flavius_vespasianus", + "amerigo_vespucci", + "girolamo_savonarola", + "emma_goldman", + "robert_gray", + "john_constable", + "putin", + "matthew_flinders", + "joseph_campbell", + "jean_de_la_fontaine", + "robert_hooke", + "o_henry", + "karl_popper", + "thomas_mallory", + "george_sand", + "peter_sellers", + "charles_fourier", + "peter_o'toole", + "joseph_conrad", + "peter_paul_rubens", + "mahatma_gandhi", + "fluviu_sf\u00e2ntul_lauren\u021biu", + "jim_morrison", + "jules_verne", + "paul_newman", + "george_meredith", + "petru_i_al_rusiei", + "josef_albers", + "jackson_pollock", + "john_lennon", + "andrea_palladio", + "gandhi", + "charlie_chaplin", + "d_h_lawrence", + "j_m_barrie", + "dou\u0103", + "lea", + "elizabeth_gaskell", + "john_mill", + "brescia", + "boris_spasski", + "asa_gray", + "hannah_arendt", + "antonio_stradivari", + "alice_walker", + "miles_davis", + "octavian", + "wilhelm_tell", + "eduard_martirul", + "hornar", + "george_marshall", + "willa_cather", + "stanley_kubrick", + "glen_miller", + "john_huston", + "william_gilbert", + "james_watt", + "ronald_reagan", + "helmut_schmidt", + "homo", + "frederick_douglass", + "speran\u021b\u0103", + "david_hilbert", + "wilhelm_reich", + "oliver_cromwell", + "martin_luther_king", + "frank_capra", + "william_wordsworth", + "rex_harrison", + "william_clark", + "woodrow_wilson", + "george", + "john_dryden", + "jim_henson", + "b\u00e9la_lugosi", + "ernest_hemingway", + "john_eccles", + "jacques_charles", + "eero_saarinen", + "arthur_miller", + "nelson_mandela", + "heinrich_himmler", + "al_gore", + "hans_geiger", + "cesare_borgia", + "j_p_morgan", + "roald_amundsen", + "sherwood_anderson", + "richard_leakey", + "c_a", + "charles_dickens", + "samuel_huntington", + "costin", + "ella_fitzgerald", + "thomas_sydenham", + "george_enescu", + "wallace_carothers", + "jacques_offenbach", + "george_stevens", + "federico_fellini", + "foarte_mult", + "patrick_henry", + "willy_brandt", + "francisco_pizarro", + "francisco_franco", + "bernardo_bertolucci", + "e_e_cummings", + "john_ross", + "iulius_cezar", + "andrew_carnegie", + "franz_schubert", + "johnny_cash", + "alfred_kastler", + "telecomand\u0103", + "mick_jagger", + "otto_loewi", + "charles_peirce", + "georges_cuvier", + "william_harvey", + "walter_scott", + "august_von_wassermann", + "sam_houston", + "robert_peary", + "robert_browning", + "comenius", + "ralph_ellison", + "john_bunyan", + "jonathan_swift", + "walter_gropius", + "albert_einstein", + "chiang_kai_shek", + "claude_bernard", + "raymond_chandler", + "henry_purcell", + "t", + "wilhelm_ostwald" + ], + "RELIGION_MEMBER": [ + "jihadiste", + "guru", + "mormon", + "baptist", + "metodist\u0103", + "jidanc\u0103", + "baptist\u0103", + "metodist", + "catolic", + "budist" + ], + "JOB": [ + "brigadier\u0103", + "creator", + "gastroenterolog\u0103", + "dietetician", + "portdrapel", + "supraveghetor", + "cornac", + "guru", + "temporar", + "osteopat", + "cresc\u0103toare", + "osta\u0219", + "mare\u0219al", + "businessman", + "compozitor", + "patolog\u0103", + "magaziner", + "somelier", + "agrimensor", + "estetician\u0103", + "supraveghetoare", + "chimist", + "antreprenor", + "caligraf", + "salahor", + "muncitoare", + "imunolog", + "translator", + "montator", + "angiolog", + "port\u0103ri\u021b\u0103", + "pietrar", + "santinel\u0103", + "ergoterapeut", + "dietetician\u0103", + "fr\u00e2nghier", + "angiolog\u0103", + "antreprenoare", + "hidrolog", + "depozitar", + "curator", + "portuar", + "registrator", + "internist", + "temp", + "infirmier", + "grafician", + "caporal", + "maiori", + "valet", + "dermatolog", + "str\u0103jer", + "the_police", + "intern", + "autoare", + "reumatolog\u0103", + "docher", + "pretor", + "camerist\u0103", + "stenograf\u0103", + "interpret\u0103", + "doge", + "samsar", + "asistent", + "hematolog", + "sculptorul", + "ginecolog\u0103", + "sertar", + "excavator", + "prim\u0103ri\u021b\u0103", + "mor\u0103ri\u021b\u0103", + "obstetrician\u0103", + "chelar", + "cardiolog", + "brancardier", + "gropar", + "lupt\u0103toare", + "ini\u021biator", + "casier\u0103", + "metres\u0103", + "menajer\u0103", + "bodyguard", + "microbiologist", + "zidar", + "om_de_serviciu", + "paramedic", + "croitor", + "ebenist", + "vestitor", + "trainer", + "estetician", + "caraul\u0103", + "stenograf", + "obstetrician", + "tapi\u021ber", + "\u0219oimar", + "oberchelner", + "grenadier", + "bancher", + "strungar", + "mor\u0103reas\u0103", + "caligraf\u0103", + "teritorial", + "academician", + "lacheu", + "ginecolog", + "strung\u0103ri\u021b\u0103", + "negustor", + "dermatolog\u0103", + "meteorologist", + "brigadier", + "pielar", + "salariat", + "independent", + "kamikaze", + "magazioner\u0103", + "sergent", + "mahmureal\u0103", + "hematolog\u0103", + "subofi\u021ber", + "sculptor", + "conduc\u0103tor", + "cancelar\u0103", + "herbolog\u0103", + "the_guardian", + "hidrolog\u0103", + "gastroenterolog", + "locotenent", + "canoist", + "cititor", + "ferestar", + "corectoare", + "camerist", + "fursec", + "straj\u0103", + "minister", + "stegar", + "mandarin", + "stomatolog", + "sticlar", + "mason", + "paramedic\u0103", + "mate", + "sculptori\u021b\u0103", + "corsar", + "grafician\u0103", + "magazioner", + "mulg\u0103toare", + "cititoare", + "terapeut", + "dogar", + "designer", + "antrenor", + "ebenist\u0103", + "pastor", + "semnalizator", + "marangoz", + "chimist\u0103", + "neurolog\u0103", + "pictori\u021b\u0103", + "savant\u0103", + "careta\u0219", + "colec\u021bionar", + "culeg\u0103tor", + "prim\u0103reas\u0103", + "mesager", + "regulator", + "p\u0103s\u0103rar", + "curtean", + "om_de_afaceri", + "hornar", + "proctolog\u0103", + "paracliser", + "internist\u0103", + "regizor", + "stucator", + "corporal", + "p\u0103durar", + "birocrat", + "om_de_\u0219tiin\u021b\u0103", + "statistician\u0103", + "arpentor", + "stewardes\u0103", + "translatoare", + "rabin", + "endocrinolog\u0103", + "cazangiu", + "romancier\u0103", + "intendent", + "endocrinolog", + "destitui", + "the_economist", + "manager", + "familiar", + "comerciant", + "broker", + "wetter", + "infanterist", + "stripper", + "barista", + "colonel", + "tunar", + "patolog", + "plumbar", + "herbolog", + "cartograf\u0103", + "principal", + "temnicer", + "doc", + "regent", + "vindec\u0103toare", + "mitralior", + "statistician", + "neurolog", + "canoist\u0103", + "cardiolog\u0103", + "b\u0103rbier", + "c\u0103prar", + "fondator", + "usher", + "messenger", + "ministru", + "catihet", + "boiangiu", + "proconsul", + "sublocotenent", + "bombardier", + "doilea", + "feldmare\u0219al", + "episcop", + "cartograf", + "cameraman", + "comandant", + "revizoare", + "casieri\u021b\u0103", + "corector", + "steward", + "magaziner\u0103", + "extern", + "tinichigiu", + "chairman", + "brutar", + "marinar_brevetat", + "sub", + "romancier", + "comodor", + "the_independent", + "academician\u0103", + "cookie", + "imunolog\u0103", + "neurochirurg", + "proctolog", + "esquire", + "alienist", + "autor", + "picolo", + "vindec\u0103tor", + "reumatolog", + "acordor", + "preceptor" + ], + "LAW": [ + "drept_comercial", + "sistem_electoral", + "drept_maritim", + "drept_roman", + "drept_civil", + "biroul_federal_de_investiga\u021bii", + "drept_jurispruden\u021bial", + "drept_administrativ" + ], + "LOCATION": [ + "al_jazeera", + "unu_\u0219i_un_sfert", + "de_\u00eencredere", + "lacul_superior", + "inginerie_civil\u0103", + "insulele_malvine", + "corpus_christi", + "prim\u0103rie", + "sf\u00e2ntul_patriciu", + "bow_wow", + "piet_mondrian", + "adunarea_na\u021bional\u0103", + "sint_maarten", + "noaptea_de_anul_nou", + "frumoasa_adormit\u0103", + "man_o_war", + "noua_anglie", + "banc\u0103_central\u0103", + "insula_sf\u00e2ntul_martin", + "blue_mountains", + "pieris_rapae", + "insula_sf\u00e2nta_elena", + "joseph_louis_gay_lussac", + "adunarea_na\u021bional\u0103_a_azerbaidjanului", + "a_treia_persoan\u0103", + "noaptea_de_revelion", + "avia\u021bie_militar\u0103", + "sit_arheologic", + "un_an_nou_fericit", + "nenoroc", + "de_trei_partide", + "tom_dege\u021bel", + "frumoasa_din_p\u0103dure_adormit\u0103", + "saint_lucia", + "aren\u0103", + "sri_lanka", + "tripartinic", + "ajunul_anului_nou", + "lacul_saint_clair", + "de_ap\u0103_dulce", + "the_rolling_stones", + "r\u00e2ul_san_joaquin", + "spital_de_boli_mintale", + "cordon_bleu", + "capul_verde", + "doi_fra\u021bi", + "heitor_villa_lobos", + "frumoasa_din_p\u0103durea_adormit\u0103", + "al_ain", + "cartier_de_afaceri", + "ursa_mare", + "spital_psihiatric" + ], + "ORG": [ + "dominion", + "sinedriu", + "str\u0103nepot", + "doi", + "din_c\u00e2nd_\u00een_c\u00e2nd", + "radiogalaxie", + "wicca", + "al_treilea_conciliu_de_la_constantinopol", + "jan_mayen", + "la_curent", + "de_o_sut\u0103_de_procente", + "camera_inferioar\u0103", + "ins", + "la_persoana_a_doua", + "nasa", + "cu_m\u00e2na_\u00een_sac", + "furnal", + "partidul_republican", + "bollywood", + "juste\u021be", + "europol", + "schutzstaffel", + "sankt_andreasberg", + "the_who", + "mai_mic_dec\u00e2t", + "partide_politice", + "luceaf\u0103r", + "tactica_p\u0103m\u00e2ntului_p\u00e2rjolit", + "al_nou\u0103lea_cer", + "tripartinic", + "infanteria_marin\u0103", + "cu_un_singur_ochi", + "partidul_verde", + "san_francisco", + "un", + "de_prima_clas\u0103", + "\u00een_realitate", + "sf\u00e2ntul_ioan_botez\u0103torul", + "for\u021b\u0103_aerian\u0103", + "cerboaic\u0103", + "pu\u021bin_c\u00e2te_pu\u021bin", + "v\u0129nh_long", + "flotare", + "nara", + "va", + "la_zi", + "a_treia_persoan\u0103", + "revelion", + "ospiciu", + "an_tan_te", + "ambuteiaj", + "prea_mul\u021bi", + "gao", + "mahayana", + "toast_fran\u021buzesc", + "drepturile_animalelor", + "gr\u0103din\u0103_botanic\u0103", + "dreptate", + "armata_continental\u0103", + "actualizat", + "muntele_carmel", + "trei_surori", + "marin\u0103_militar\u0103", + "ai", + "clasa_muncitoare", + "marea_ro\u0219ie", + "the_football_league", + "chiang_mai", + "f\u0103r\u0103_vam\u0103", + "liga_na\u021biunilor", + "dia", + "justi\u021bie", + "centru_comercial", + "al_doilea_conciliu_de_la_constantinopol", + "le_mans", + "du_te_naibii", + "centru_de_ora\u0219", + "partidul_muncitoresc_norvegian", + "muntele_m\u0103slinilor", + "rabindranath_tagore", + "gestapo", + "\u00eempotrivire", + "domina\u021bie", + "republica_capului_verde", + "scoal\u0103_de_medicin\u0103", + "hasidism", + "marina_regal\u0103", + "armata_statelor_unite_ale_americii", + "spital_de_psihiatrie", + "saintlucian", + "te_iubesc", + "casa_alb\u0103", + "who_are_you", + "al_jazeera", + "de_trei_partide", + "cei_patru_mari", + "opozi\u021bie", + "lun\u0103_nou\u0103", + "imperiul_german", + "kr\u00eev\u00eei_rih", + "iosif_din_nazaret", + "camera_comunelor", + "camera_superioar\u0103", + "ap\u0103_dulce", + "partidul_whig_sua", + "oficiu_po\u0219tal", + "chior", + "saint_barth\u00e9lemy", + "te_ador", + "sturmabteilung", + "centru_istoric", + "los_angeles", + "nato", + "mass_media", + "ad_hoc", + "partidul_socialist_din_olanda", + "mai_mare_dec\u00e2t", + "la_persoana_a_treia", + "randunea", + "in_situ", + "sa", + "adunarea_na\u021bional\u0103_a_fran\u021bei", + "doc", + "partid_politic", + "germanistic\u0103", + "fluviul_galben", + "al_ain", + "marin\u0103", + "taoism", + "al_doilea_conciliu_de_la_niceea", + "drept_canonic", + "francmasonerie", + "adunarea_na\u021bional\u0103_a_bulgariei", + "guvern", + "clas\u0103_de_mijloc", + "partidul_democrat", + "sf\u00e2nta_elena", + "eu", + "prea_multe", + "parvenit", + "drept_roman", + "mecklenburg_vorpommern", + "epoca_de_aur", + "cruce_ro\u0219ie", + "oaste", + "biserica_romano_catolic\u0103", + "mosad", + "s\u00e3o_tom\u00e9", + "sindicat_comercial" + ], + "DISEASE": [ + "rubeol\u0103", + "sars", + "pelagr\u0103", + "veghe", + "iradiere", + "paralizie", + "cafeniu", + "boala_kawasaki", + "rahitism", + "anestezie", + "sensibil", + "cecidie", + "pseudo_hermafrodism", + "caracter_complet", + "frenezie", + "rage", + "traum\u0103", + "se_chior\u00ee", + "strabism", + "hernie", + "radia\u021bie", + "progeria", + "frostbite", + "cangren\u0103", + "fondator", + "cecitate_cromatic\u0103", + "deger\u0103tur\u0103", + "virusul_west_nile", + "the_bends", + "constipa\u021bie", + "ferbinte", + "phytophthora_infestans", + "virusul_herpes_simplex", + "amigdalit\u0103", + "lucire", + "reclama\u021bie", + "tandre\u021be", + "claustrofobie", + "plenitudine", + "distimie", + "colecistit\u0103", + "materialism", + "furuncul", + "holer\u0103", + "abraziune", + "indigestie", + "catalepsie", + "deshidratare", + "rupere", + "deranjare", + "aprindere", + "lichen", + "poliomielit\u0103", + "corn", + "grea\u021b\u0103", + "poten\u021b\u0103", + "pl\u00e2ngere", + "rugin\u0103", + "deplin\u0103tate", + "silicoz\u0103", + "gimp", + "mers", + "b\u0103t\u0103tur\u0103", + "crud", + "smart", + "pirofobie", + "ed", + "graviditate", + "pica", + "bradicardie", + "tuse", + "murmur", + "moliciune", + "arbovirus", + "scleroz\u0103_multipl\u0103", + "satar", + "scarlatin\u0103", + "accident_vascular_cerebral", + "ill", + "arsur\u0103", + "scald", + "coronarian", + "\u00eentemeietor", + "bruceloz\u0103", + "cataract\u0103", + "devian\u021b\u0103", + "aura", + "sting", + "jigodie", + "boala_viral\u0103_ebola", + "rabie", + "the_bleeding", + "prezbitism", + "neregularitate", + "the_hives", + "malarie", + "le", + "salmonella" + ], + "PRODUCT": [ + "pe_aripile_v\u00e2ntului", + "justin_bieber", + "primul_r\u0103zboi_mondial", + "velier", + "fundac", + "ca_\u0219i_c\u00e2nd", + "al_jazeera", + "cobai", + "mult_zgomot_pentru_nimic", + "autoblindat", + "cornier", + "prin_harul_lui_dumnezeu", + "the_star_spangled_banner", + "da_jos", + "\u00eemi_pare_r\u0103u", + "cezarian\u0103", + "doi_fra\u021bi", + "antiaerian", + "o_cas\u0103_de_p\u0103pu\u0219i", + "fund\u0103tur\u0103", + "sf\u00e2nta_maria", + "saxonia_anhalt", + "dischet\u0103", + "al_doilea_r\u0103zboi_mondial", + "la_dolce_vita", + "deutsche_welle", + "spiritul_sf\u00e2nt", + "gong", + "totul_e_bine_c\u00e2nd_se_termin\u0103_cu_bine", + "mario_andretti", + "noua_zeeland\u0103", + "mo\u0219_cr\u0103ciun", + "capul_horn", + "nu_m\u0103_uita", + "astru", + "cristelni\u021b\u0103", + "baptisteriu", + "nordrhein_westfalen", + "cornier\u0103", + "a_dou\u0103sprezecea_noapte", + "s\u00e3o_tom\u00e9_\u0219i_pr\u00edncipe", + "cum_vre\u021bi_dumneavoastr\u0103", + "novo_mesto", + "pleac\u0103" + ], + "LANGUAGE": [ + "georgian\u0103", + "greac\u0103", + "catalan", + "danez\u0103", + "marshallez\u0103", + "coreean", + "fran\u021buze\u0219te", + "kazah\u0103", + "valon\u0103", + "portughez", + "hindus\u0103", + "bielorus", + "intona\u021bie", + "maghiar", + "ganda", + "basc\u0103", + "manx", + "basc", + "neam\u021b", + "arabic", + "georgian", + "persan\u0103", + "vorbire", + "galician", + "chinezesc", + "germanc\u0103", + "german", + "divehi", + "esperanto", + "unguresc", + "grecoaic\u0103", + "cecen", + "english", + "catalan\u0103", + "wolof", + "lao", + "ido", + "saintlucian", + "rusoaic\u0103", + "samoan", + "tonga", + "corsican" + ], + "PERSON_PRONOUN": [ + "m\u0103", + "s\u0103u", + "\u00eemi", + "i", + "he", + "mine", + "our", + "t\u0103u", + "noastre", + "t\u0103i", + "noastr\u0103" + ], + "PLANT": [ + "lobod\u0103", + "lilium_martagon", + "clematit\u0103", + "hevea", + "m\u0103tr\u0103gun\u0103", + "castan", + "pine", + "albumeal\u0103", + "frag\u0103", + "liriodendron_tulipifera", + "melissa", + "the_joshua_tree", + "lipicioas\u0103", + "salcie", + "helianthus", + "edelvais", + "solanaceae", + "indru\u0219aim", + "brusture", + "ungura\u0219", + "scapul\u0103", + "amanita", + "sequoiadendron", + "sulfin\u0103", + "coconar", + "monarda", + "artist", + "campion", + "achillea", + "magnolia_grandiflora", + "conopid\u0103", + "obligean\u0103", + "argin\u021bica", + "caprifoi", + "curmal", + "mimosa_pudica", + "manioc", + "beladon\u0103", + "voronic", + "taxus_baccata", + "sakura", + "papaver", + "larice", + "sorb", + "chica_voinicului", + "tangerin\u0103", + "corcodu\u0219", + "salix_viminalis", + "platanus_occidentalis", + "cimbri\u0219or", + "anin", + "hidrofit", + "carot\u0103", + "selenicereus_grandiflorus", + "annona_cherimola", + "acri\u0219", + "renglot", + "cormobionta", + "amanita_muscaria", + "leonurus_cardiaca", + "asplenium_trichomanes", + "nicotiana_alata", + "dracocephalum", + "nicotiana_tabacum", + "myosotis_sylvatica", + "pitchpine", + "clematis", + "poligal\u0103", + "phytophthora_infestans", + "nu_m\u0103_uita", + "pom_de_cr\u0103ciun", + "blackberry", + "solanum", + "sisymbrium_officinale", + "hasma\u021buchi", + "silnic", + "spat\u0103", + "ai_grij\u0103", + "miozotis", + "topora\u0219", + "artist\u0103", + "cyperus_papyrus", + "volbur\u0103", + "magnolie", + "vinari\u021b\u0103", + "fasole", + "bobornic", + "pseudotsuga_menziesii", + "plesnitoare", + "cirea\u0219\u0103", + "cruciuli\u021b\u0103", + "pelin", + "margaret\u0103", + "lingurea", + "panselu\u021b\u0103", + "l\u0103ptuc\u0103", + "meri\u0219or", + "batat", + "roini\u021b\u0103", + "annona_reticulata", + "rafie", + "sabin\u0103", + "scoru\u0219", + "belladonna", + "punguli\u021b\u0103", + "neghin\u0103", + "popilnic", + "oliv", + "spilcu\u021b\u0103", + "pansea", + "ataca", + "magnolia", + "cire\u0219", + "conium_maculatum", + "goldan", + "salc\u00e2m", + "tapo\u0219nic" + ], + "ANIMAL": [ + "acherontia", + "strigiform\u0103", + "abisinian\u0103", + "ursule\u021b", + "perisodactile", + "artiodactile", + "cantarid\u0103", + "langustin\u0103", + "platirinieni", + "torpediniforme", + "blatodee", + "tern", + "bursuc", + "bactrian\u0103", + "manta", + "coropi\u0219ni\u021b\u0103", + "albin\u0103rel", + "artiodactil", + "sternidae", + "marsuin", + "virus_epstein_barr", + "cobai", + "linxul", + "mistre\u021b", + "viespe", + "miriapod", + "codalb", + "baribal", + "artropod", + "bradipodide", + "condor", + "marmotini", + "acel", + "artropode", + "filomel\u0103", + "porcu\u0219or", + "crisomelide", + "kundus", + "orbe\u021b", + "banteng", + "histricide", + "mantodee", + "albili\u021b\u0103", + "jerboa", + "donald_duck", + "iller", + "c\u00e2ine_de_v\u00e2n\u0103toare", + "sirenian", + "grangur", + "diplopode", + "strig\u0103", + "randunea", + "pesc\u0103ru\u0219ul", + "jubart\u0103", + "pichire", + "pirol", + "mierl\u0103", + "cucuvea", + "pisic\u0103", + "libarc\u0103", + "vindereu", + "mugurar", + "gorilla_gorilla", + "viespar", + "dumbr\u0103veanc\u0103", + "sticlete", + "eider", + "cabarga", + "pesc\u0103ru\u0219" + ], + "QUANTITY": [ + "c.m.m.d.c", + "calorie", + "livr\u0103", + "dinar", + "ton", + "tridimensional\u0103", + "sistem_metric", + "franc_elve\u021bian", + "libera", + "cel_mai_mare_divizor_comun", + "g", + "o_sut\u0103_de_mii", + "won_sud_coreean", + "perioada_celor_trei_regate", + "won_nord_coreean", + "marc\u0103_german\u0103", + "an_lumin\u0103", + "cele_trei_legi_ale_roboticii", + "trei_surori", + "dinar_iordanian", + "franc_francez", + "anders_celsius" + ], + "GPE": [ + "noua_spanie", + "mult_noroc", + "simon_petru", + "dar_es_salaam", + "sint_maarten", + "tai_shan", + "catedrala_sf\u00e2nta_sofia_din_constantinopol", + "s\u00e3o_tom\u00e9", + "nicolae_de_mira", + "sf\u00e2ntul_nicolae", + "gran_canaria", + "sf\u00e2nta_barbara", + "sf\u00e2ntul_gheorghe", + "noul_testament", + "al_andalus", + "la_rochelle", + "parc_industrial", + "hibiscus_rosa_sinensis", + "drepturile_omului", + "la_gomera", + "trec\u0103toare" + ], + "TITLE": [ + "mister" + ], + "RELIGION": [ + "habad", + "zen", + "maniheism", + "puritanism", + "adventism", + "confucianism", + "jainism", + "catarism", + "\u0219intoism", + "calvinism", + "islam", + "hinduism", + "sikhism", + "presbiterianism", + "wicca", + "anabaptism", + "trinitarianism", + "donatism" + ], + "PERSON": [ + "din_clipa_\u00een_care", + "prin\u021bul_albert", + "al_gore", + "h_g_wells", + "dulgher_mare", + "din_acea_clip\u0103", + "gioconda", + "de_atunci_\u00eencoace", + "din_acel_moment", + "e_e_cummings", + "t_ball", + "tai_shan", + "din_momentul_\u00een_care", + "igor_sikorsky", + "chiar_de_la", + "seleucus_i_nicator", + "chiar_de_c\u00e2nd", + "carl_david_anderson", + "maxwell_anderson", + "rudolf_hess", + "chiar_de_atunci", + "de_atunci_c\u00e2nd", + "de_atunci" + ], + "FAC": [ + "pod_suspendat", + "arnold_sch\u00f6nberg", + "centru_de_cump\u0103r\u0103turi", + "\u0219coal\u0103_primar\u0103", + "sf\u00e2nta_lucia", + "biserica_catolic\u0103", + "biseric\u0103_catolic\u0103", + "piscin\u0103", + "saint_lucia", + "poarta_otoman\u0103", + "bonifacius", + "\u0219coal\u0103_elementar\u0103", + "titus_livius", + "winnie_de_plu\u0219", + "imperiul_otoman", + "arc_de_triumf" + ], + "FOOD": [ + "desert", + "limonad\u0103", + "om_de_turt\u0103_dulce", + "capsicum", + "gum\u0103_de_mestecat", + "pinot_noir", + "coconari", + "gelato", + "r\u0103coritoare", + "patiserie", + "chile", + "scrob", + "ou_de_pa\u0219ti", + "coconar\u0103", + "ou_fiert", + "bok_choy" + ], + "SOC_ECO_CLASS": [ + "clasa_superioar\u0103", + "fraternitate", + "samurai", + "clas\u0103_mijlocie", + "proletariat", + "pia\u021b\u0103_neagr\u0103", + "agricultur\u0103", + "burghezie", + "clasa_muncitoare", + "cast\u0103", + "noble\u021be", + "clas\u0103_medie" + ], + "DATE": [ + "an_bisectil", + "adormirea_maicii_domnului", + "zi_na\u021bional\u0103", + "an_solar", + "era_comun\u0103", + "an_bisect", + "era_spa\u021bial\u0103", + "poim\u00e2ine", + "an_fiscal", + "mortalitate", + "an_universitar", + "an_tropic", + "canicul\u0103", + "\u00een_timp", + "a_patra_dimensiune", + "a_dou\u0103sprezecea_noapte", + "corpus_christi", + "unde_vei_fi_poim\u00e2ine", + "an_de_studiu" + ], + "RACE": [ + "francezi", + "latin", + "amerindian", + "eschimo\u0219i", + "fran\u021bu\u0219c\u0103", + "englezi", + "african", + "francez", + "american", + "fran\u021buzoaic\u0103", + "japonezi", + "galezi" + ], + "POLITICAL_PARTY_MEMBER": [ + "comunist", + "camarad" + ], + "POLITICAL_PARTY": [ + "partidul_social_democrat", + "partidul_conservator", + "partij_van_de_arbeid", + "nsdap", + "partidul_laburist", + "kuomintang", + "partidul_democrat", + "partidul_socialist_japonez", + "partidul_popular", + "partid", + "partid_conservator", + "partidul_socialist", + "partid_comunist", + "partidul_democrat_republican" + ], + "EVENT": [ + "asta_i_via\u021ba", + "sing_sing", + "fleur_de_lis" + ], + "GENDER": [ + "dame", + "boy", + "mascul", + "transgender", + "transgen", + "gal" + ], + "UNION": [ + "nea", + "senatul_studen\u021besc" + ], + "BIO_CHEM_ENTITY": [ + "adenozindifosfat", + "tirozinchinaz\u0103" + ], + "ner_regexes": [ + [ + "PERSON", + "\\D+ \\D+", + false, + [] + ] + ], + "FIRST_NAME_FEMALE": [ + "cleopatra", + "adelaida", + "rafila", + "zoe", + "hortensia", + "antonia", + "cornelia", + "pompilia", + "tudosia", + "milena", + "dana", + "ecaterina", + "alida", + "valentina", + "iosefina", + "speran\u021ba", + "antoaneta", + "constan\u021ba", + "maria", + "lavinia", + "gra\u021biana", + "doina", + "denisa", + "jeana", + "melania", + "liana", + "gianina", + "leti\u021bia", + "aida", + "cosmina", + "norica", + "eva", + "aurora", + "silvana", + "jasmina", + "filofteia", + "codrina", + "olimpia", + "dumitrana", + "virginia", + "elvira", + "andra", + "corina", + "dariana", + "marina", + "semenica", + "ioana", + "dida", + "isabela", + "mina", + "mara", + "blanduzia", + "ivona", + "melina", + "luciana", + "roxelana", + "andrada", + "erica", + "luiza", + "anca", + "ana", + "julia", + "teona", + "l\u0103cr\u0103mioara", + "aureliana", + "fabia", + "nata\u0219a", + "minodora", + "anghelina", + "clarisa", + "leana", + "octaviana", + "stela", + "heracleea", + "saveta", + "catrinel", + "fiona", + "camelia", + "alice", + "ada", + "daria", + "anu\u021ba", + "rodica", + "rada", + "floare", + "flavia", + "janeta", + "alexandrina", + "ramona", + "zamfira", + "paula", + "consuela", + "patricia", + "cerasela", + "sanda", + "zenovia", + "br\u00e2ndu\u0219a", + "iasmina", + "astrid", + "anastasia", + "m\u0103d\u0103lina", + "tiberia", + "nicoleta", + "lili", + "carina", + "ica", + "sonia", + "olga", + "henrieta", + "albertina", + "arina", + "vanesa", + "rebeca", + "eusebia", + "alexandra", + "aristi\u021ba", + "iridenta", + "romina", + "simona", + "francesca", + "daniela", + "venera", + "evanghelina", + "suzana", + "victoria", + "stanca", + "ludmila", + "alis", + "noemi", + "voichi\u021ba", + "laura", + "marga", + "jana", + "casandra", + "cristina", + "dimitrina", + "augustina", + "geta", + "ligia", + "ancu\u021ba", + "amalia", + "mariana", + "ilona", + "aura", + "octavia", + "gabriela", + "estera", + "tania", + "florina", + "marinela", + "maricica", + "smaranda", + "viviana", + "nidia", + "matilda", + "lidia", + "marta", + "elena", + "dina", + "marilena", + "delia", + "violeta", + "anda", + "mioara", + "simina", + "magdalena", + "zenobia", + "lorena", + "ruxanda", + "janina", + "catrina", + "steliana", + "ariana", + "agata", + "vera", + "adriana", + "gherghina", + "antonela", + "viorica", + "lucia", + "lelia", + "ionelia", + "atena", + "nadia", + "sofia", + "aneta", + "narcisa", + "oana", + "dumitra", + "monica", + "domnica", + "vicen\u021bia", + "larisa", + "aglaia", + "draga", + "aurica", + "miruna", + "axenia", + "s\u00e2nziana", + "petronela", + "olivia", + "sorina", + "ariadna", + "roza", + "doriana", + "sabrina", + "eufrosina", + "iolanda", + "constantina", + "elodia", + "tinca", + "georgia", + "floarea", + "gina", + "dalia", + "elisaveta", + "tincu\u021ba", + "sabina", + "geanina", + "betina", + "\u0219tefania", + "codru\u021ba", + "andreea", + "stelu\u021ba", + "anemona", + "ionela", + "carla", + "cezara", + "carolina", + "tatiana", + "teea", + "petru\u021ba", + "angela", + "eugenia", + "adelina", + "daiana", + "\u0219tefana", + "carmen", + "ina", + "ioanina", + "eleonora", + "evelina", + "caterina", + "carmina", + "bianca", + "amelia", + "demetra", + "silvia", + "romani\u021ba", + "julieta", + "zina", + "liliana", + "coralia", + "lia", + "ludovica", + "pamela", + "zaharia", + "viorela", + "lucre\u021bia", + "severina", + "didina", + "natalia", + "mona", + "tamara", + "niculina", + "clementina", + "veta", + "iris", + "ruxandra", + "mirona", + "lumini\u021ba", + "alma", + "ani\u0219oara", + "emilia", + "luana", + "ileana", + "lauren\u021bia", + "paraschiva", + "salomea", + "dorli", + "vl\u0103delina", + "savina", + "giorgiana", + "monalisa", + "floriana", + "bogdana", + "frusina", + "mihaela", + "leontina", + "paulina", + "florentina", + "crina", + "felicia", + "iuliana", + "lioara", + "gra\u021biela", + "teodora", + "m\u0103rioara", + "tudora", + "leopoldina", + "malvina", + "sorana", + "dafina", + "maia", + "eliza", + "lorelei", + "diana", + "celia", + "veronica", + "daciana", + "alina", + "silviana", + "timea", + "robertina", + "manuela", + "varvara", + "florica", + "rozalia", + "elisabeta", + "fabiana", + "adela", + "aurelia", + "ortansa", + "roberta", + "safta", + "marcela", + "emanuela", + "nora", + "dorina", + "raluca", + "georgiana", + "stana", + "vasilica", + "profira", + "izabela", + "floren\u021ba", + "claudia", + "cipriana", + "agripina", + "ozana", + "crengu\u021ba", + "casiana", + "anamaria", + "anaida", + "ilinca", + "adina", + "mirabela", + "margareta", + "m\u0103riuca", + "iulia", + "catinca", + "iustina", + "amanda", + "xenia", + "dochia", + "teodosia", + "marioara", + "paulica", + "flora", + "livia", + "despina", + "valeria", + "alberta", + "roxana", + "m\u0103lina", + "anica", + "dora", + "cecilia", + "artemisa", + "renata", + "c\u0103t\u0103lina", + "gen\u021biana", + "loredana", + "ofelia", + "sidonia", + "tudori\u021ba", + "georgeta", + "mirela", + "rica", + "svetlana", + "eliana", + "eftimia", + "beatrice", + "anabela", + "irina", + "zaraza", + "clara", + "otilia", + "marcheta" + ], + "FIRST_NAME_MALE": [ + "emanuel", + "manole", + "ovidiu", + "basarab", + "francisc", + "gregorian", + "valter", + "adelin", + "stelian", + "luca", + "maxim", + "flaviu", + "theodor", + "corneliu", + "ilarion", + "costin", + "relu", + "anghel", + "c\u0103lin", + "silvian", + "rafael", + "felix", + "vasile", + "jenel", + "aleodor", + "gicu", + "ieremia", + "iulian", + "gelu", + "eusta\u021biu", + "ion", + "cristobal", + "codin", + "andrian", + "nicu\u021b\u0103", + "decebal", + "valeriu", + "georgian", + "iosif", + "florin", + "damian", + "ludovic", + "alexe", + "viorel", + "\u0219erban", + "cezar", + "agnos", + "nicolae", + "petru\u021b", + "daniel", + "claudiu", + "florea", + "lucian", + "codru\u021b", + "iurie", + "remus", + "eugen", + "lasc\u0103r", + "crin", + "stan", + "constantin", + "bogdan", + "marian", + "grigore", + "pompiliu", + "eftimie", + "mitic\u0103", + "silviu", + "timotei", + "ionu\u021b", + "marin", + "stancu", + "visarion", + "vlaicu", + "narcis", + "marcel", + "fabian", + "lorin", + "alex", + "mihail", + "corvin", + "dinu", + "benone", + "edgar", + "maximilian", + "drago\u0219", + "sava", + "codrin", + "leordean", + "florian", + "gheorghe", + "pavel", + "tiberiu", + "gic\u0103", + "alin", + "giorgian", + "ciprian", + "r\u0103zvan", + "bebe", + "ianis", + "cosmin", + "gabriel", + "horea", + "octav", + "nichifor", + "mugurel", + "vasilic\u0103", + "ernest", + "george", + "ghi\u021b\u0103", + "jean", + "oliviu", + "emil", + "titus", + "adonis", + "denis", + "valentin", + "ducu", + "simion", + "casian", + "sabin", + "anton", + "eremia", + "aristide", + "nelu", + "arsenie", + "vincen\u021biu", + "caius", + "nicu\u0219or", + "fiodor", + "petri\u0219or", + "cristofor", + "leontin", + "bernard", + "bucur", + "ionic\u0103", + "augustin", + "inocen\u021biu", + "emilian", + "matei", + "cazimir", + "amedeu", + "marius", + "nechifor", + "nicu", + "jan", + "vlad", + "aurelian", + "cornel", + "m\u0103d\u0103lin", + "pamfil", + "sinic\u0103", + "panagachie", + "antonie", + "mitru\u021b", + "amza", + "camil", + "dorin", + "paul", + "romulus", + "costel", + "mihai", + "iacob", + "voicu", + "laurian", + "zeno", + "antoniu", + "barbu", + "petre", + "miron", + "achim", + "florentin", + "octaviu", + "iuliu", + "ilarie", + "martin", + "nicodim", + "cedrin", + "lucen\u021biu", + "dorinel", + "antim", + "teofil", + "laz\u0103r", + "iustinian", + "raul", + "gheorghi\u021b\u0103", + "aurel", + "anatolie", + "cristea", + "petru", + "lic\u0103", + "iustin", + "p\u0103tru", + "petric\u0103", + "beniamin", + "eric", + "r\u0103ducu", + "sorin", + "adam", + "traian", + "dorel", + "norman", + "alexandru", + "avram", + "toma", + "octavian", + "gra\u021bian", + "severin", + "b\u0103nel", + "olimpian", + "frederic", + "veniamin", + "sebastian", + "hora\u021biu", + "irinel", + "teodor", + "eduard", + "auric\u0103", + "mircea", + "ghenadie", + "eusebiu", + "marcu", + "axinte", + "dorian", + "adrian", + "david", + "georgel", + "liviu", + "vicen\u021biu", + "angel", + "mugur", + "filip", + "costache", + "ilie", + "cantemir", + "\u0219tefan", + "iancu", + "dacian", + "alistar", + "dumitru", + "c\u0103t\u0103lin", + "norbert", + "niculi\u021b\u0103", + "nicoar\u0103", + "rare\u0219", + "sever", + "robert", + "romeo", + "dan", + "adi", + "ionel", + "emanuil", + "sandu", + "ivan", + "tudor", + "nicolaie", + "dominic", + "darius", + "panait", + "horia", + "sergiu", + "andrei", + "br\u0103du\u021b", + "mihnea", + "haralambie", + "edmond", + "ladislau", + "lauren\u021biu", + "zamfir", + "ioan", + "haralamb", + "simi", + "albert", + "arian", + "carol", + "victor", + "radu", + "ple\u0219u", + "doru", + "cristian", + "nae", + "todor", + "teohari", + "gabi", + "vladimir", + "bartolomeu", + "emanoil", + "leonard", + "lucre\u021biu", + "olimpiu" + ], + "FIRST_NAME": [ + "emanuel", + "cleopatra", + "adelaida", + "luca", + "maxim", + "rafila", + "zoe", + "hortensia", + "antonia", + "cornelia", + "iulian", + "ieremia", + "andrian", + "pompilia", + "tudosia", + "milena", + "dana", + "georgian", + "ecaterina", + "iosif", + "florin", + "alida", + "valentina", + "iosefina", + "speran\u021ba", + "agnos", + "antoaneta", + "constan\u021ba", + "petru\u021b", + "maria", + "lucian", + "lavinia", + "codru\u021b", + "lasc\u0103r", + "eugen", + "doina", + "gra\u021biana", + "denisa", + "marian", + "eftimie", + "jeana", + "melania", + "silviu", + "timotei", + "liana", + "visarion", + "gianina", + "mihail", + "leti\u021bia", + "aida", + "cosmina", + "norica", + "florian", + "eva", + "giorgian", + "ciprian", + "aurora", + "silvana", + "jasmina", + "filofteia", + "octav", + "olimpia", + "codrina", + "dumitrana", + "jean", + "virginia", + "titus", + "elvira", + "andra", + "corina", + "dariana", + "marina", + "eremia", + "aristide", + "semenica", + "nelu", + "vincen\u021biu", + "fiodor", + "leontin", + "petri\u0219or", + "bernard", + "bucur", + "inocen\u021biu", + "ioana", + "matei", + "marius", + "dida", + "isabela", + "mina", + "nechifor", + "blanduzia", + "mara", + "jan", + "aurelian", + "ivona", + "melina", + "luciana", + "panagachie", + "roxelana", + "antoniu", + "iacob", + "andrada", + "erica", + "luiza", + "anca", + "ana", + "achim", + "florentin", + "octaviu", + "julia", + "teona", + "lucen\u021biu", + "l\u0103cr\u0103mioara", + "antim", + "raul", + "iustinian", + "iustin", + "aureliana", + "fabia", + "beniamin", + "nata\u0219a", + "adam", + "minodora", + "anghelina", + "severin", + "clarisa", + "leana", + "octaviana", + "stela", + "hora\u021biu", + "heracleea", + "saveta", + "teodor", + "auric\u0103", + "catrinel", + "fiona", + "vicen\u021biu", + "camelia", + "alice", + "ada", + "daria", + "ilie", + "costache", + "anu\u021ba", + "rodica", + "iancu", + "rada", + "c\u0103t\u0103lin", + "floare", + "rare\u0219", + "sever", + "flavia", + "janeta", + "adi", + "ionel", + "alexandrina", + "ramona", + "zamfira", + "paula", + "consuela", + "patricia", + "mihnea", + "cerasela", + "sanda", + "ioan", + "zenovia", + "arian", + "nae", + "gabi", + "bartolomeu", + "lucre\u021biu", + "br\u00e2ndu\u0219a", + "manole", + "iasmina", + "adelin", + "anastasia", + "m\u0103d\u0103lina", + "astrid", + "tiberia", + "nicoleta", + "lili", + "carina", + "ica", + "sonia", + "olga", + "henrieta", + "albertina", + "aleodor", + "arina", + "vanesa", + "eusta\u021biu", + "rebeca", + "ion", + "gelu", + "eusebia", + "decebal", + "alexandra", + "ludovic", + "aristi\u021ba", + "\u0219erban", + "alexe", + "iridenta", + "romina", + "simona", + "francesca", + "daniel", + "daniela", + "iurie", + "crin", + "bogdan", + "mitic\u0103", + "ionu\u021b", + "venera", + "stancu", + "marcel", + "fabian", + "narcis", + "alex", + "evanghelina", + "corvin", + "gheorghe", + "suzana", + "victoria", + "codrin", + "stanca", + "ludmila", + "alis", + "cosmin", + "noemi", + "ianis", + "voichi\u021ba", + "laura", + "marga", + "jana", + "casandra", + "cristina", + "vasilic\u0103", + "george", + "dimitrina", + "oliviu", + "augustina", + "geta", + "ducu", + "sabin", + "ligia", + "arsenie", + "ancu\u021ba", + "ionic\u0103", + "augustin", + "amalia", + "emilian", + "mariana", + "ilona", + "mitru\u021b", + "antonie", + "aura", + "camil", + "romulus", + "costel", + "octavia", + "laurian", + "gabriela", + "zeno", + "estera", + "tania", + "florina", + "marinela", + "maricica", + "smaranda", + "dorinel", + "viviana", + "nidia", + "matilda", + "lidia", + "lic\u0103", + "r\u0103ducu", + "marta", + "elena", + "alexandru", + "dina", + "marilena", + "olimpian", + "veniamin", + "sebastian", + "eduard", + "mircea", + "delia", + "violeta", + "axinte", + "dorian", + "anda", + "mioara", + "simina", + "magdalena", + "zenobia", + "angel", + "filip", + "lorena", + "ruxanda", + "janina", + "cantemir", + "catrina", + "dacian", + "norbert", + "steliana", + "ariana", + "agata", + "vera", + "adriana", + "gherghina", + "nicolaie", + "antonela", + "viorica", + "darius", + "lucia", + "sergiu", + "lelia", + "ionelia", + "atena", + "nadia", + "sofia", + "aneta", + "narcisa", + "vladimir", + "oana", + "dumitra", + "monica", + "domnica", + "ovidiu", + "vicen\u021bia", + "gregorian", + "francisc", + "valter", + "larisa", + "stelian", + "corneliu", + "ilarion", + "c\u0103lin", + "aglaia", + "felix", + "gicu", + "draga", + "aurica", + "codin", + "miruna", + "axenia", + "s\u00e2nziana", + "nicu\u021b\u0103", + "petronela", + "olivia", + "damian", + "sorina", + "viorel", + "cezar", + "ariadna", + "nicolae", + "roza", + "doriana", + "sabrina", + "eufrosina", + "constantin", + "pompiliu", + "iolanda", + "constantina", + "elodia", + "tinca", + "georgia", + "floarea", + "gina", + "vlaicu", + "dalia", + "elisaveta", + "lorin", + "tincu\u021ba", + "sabina", + "benone", + "edgar", + "geanina", + "sava", + "betina", + "\u0219tefania", + "pavel", + "gic\u0103", + "alin", + "r\u0103zvan", + "bebe", + "codru\u021ba", + "andreea", + "stelu\u021ba", + "anemona", + "ionela", + "ghi\u021b\u0103", + "emil", + "carla", + "cezara", + "denis", + "carolina", + "valentin", + "tatiana", + "simion", + "casian", + "teea", + "petru\u021ba", + "cristofor", + "angela", + "eugenia", + "adelina", + "daiana", + "\u0219tefana", + "carmen", + "ina", + "ioanina", + "eleonora", + "m\u0103d\u0103lin", + "evelina", + "caterina", + "carmina", + "dorin", + "paul", + "bianca", + "amelia", + "demetra", + "silvia", + "barbu", + "romani\u021ba", + "julieta", + "zina", + "liliana", + "coralia", + "teofil", + "gheorghi\u021b\u0103", + "aurel", + "lia", + "cristea", + "petru", + "ludovica", + "pamela", + "p\u0103tru", + "zaharia", + "eric", + "viorela", + "sorin", + "lucre\u021bia", + "severina", + "traian", + "didina", + "dorel", + "natalia", + "norman", + "mona", + "octavian", + "gra\u021bian", + "b\u0103nel", + "tamara", + "frederic", + "niculina", + "ghenadie", + "adrian", + "liviu", + "clementina", + "david", + "veta", + "iris", + "ruxandra", + "mirona", + "alistar", + "lumini\u021ba", + "niculi\u021b\u0103", + "sandu", + "alma", + "ani\u0219oara", + "ivan", + "dominic", + "horia", + "luana", + "emilia", + "panait", + "ladislau", + "ileana", + "haralambie", + "zamfir", + "lauren\u021bia", + "paraschiva", + "haralamb", + "salomea", + "simi", + "victor", + "dorli", + "ple\u0219u", + "vl\u0103delina", + "todor", + "savina", + "leonard", + "olimpiu", + "giorgiana", + "monalisa", + "basarab", + "flaviu", + "theodor", + "floriana", + "costin", + "relu", + "anghel", + "silvian", + "bogdana", + "frusina", + "mihaela", + "rafael", + "vasile", + "jenel", + "cristobal", + "leontina", + "paulina", + "florentina", + "crina", + "valeriu", + "felicia", + "iuliana", + "lioara", + "gra\u021biela", + "claudiu", + "teodora", + "florea", + "remus", + "stan", + "m\u0103rioara", + "tudora", + "leopoldina", + "grigore", + "malvina", + "sorana", + "dafina", + "maia", + "eliza", + "marin", + "lorelei", + "diana", + "dinu", + "mugur", + "maximilian", + "celia", + "drago\u0219", + "leordean", + "veronica", + "daciana", + "gabriel", + "alina", + "silviana", + "timea", + "horea", + "robertina", + "nichifor", + "manuela", + "varvara", + "florica", + "rozalia", + "mugurel", + "ernest", + "elisabeta", + "fabiana", + "adonis", + "adela", + "anton", + "caius", + "aurelia", + "nicu\u0219or", + "ortansa", + "roberta", + "safta", + "cazimir", + "amedeu", + "emanuela", + "marcela", + "nora", + "dorina", + "raluca", + "georgiana", + "nicu", + "vlad", + "cornel", + "stana", + "pamfil", + "sinic\u0103", + "profira", + "amza", + "vasilica", + "izabela", + "floren\u021ba", + "voicu", + "mihai", + "claudia", + "cipriana", + "agripina", + "petre", + "miron", + "ozana", + "iuliu", + "ilarie", + "martin", + "nicodim", + "cedrin", + "crengu\u021ba", + "casiana", + "anamaria", + "anaida", + "tiberiu", + "laz\u0103r", + "ilinca", + "anatolie", + "petric\u0103", + "adina", + "mirabela", + "margareta", + "m\u0103riuca", + "iulia", + "catinca", + "iustina", + "amanda", + "xenia", + "avram", + "toma", + "dochia", + "teodosia", + "irinel", + "marioara", + "eusebiu", + "marcu", + "paulica", + "georgel", + "flora", + "livia", + "despina", + "valeria", + "alberta", + "\u0219tefan", + "roxana", + "dumitru", + "m\u0103lina", + "nicoar\u0103", + "anica", + "dora", + "robert", + "cecilia", + "romeo", + "dan", + "artemisa", + "emanuil", + "tudor", + "renata", + "c\u0103t\u0103lina", + "gen\u021biana", + "loredana", + "ofelia", + "sidonia", + "tudori\u021ba", + "georgeta", + "andrei", + "br\u0103du\u021b", + "mirela", + "edmond", + "lauren\u021biu", + "rica", + "svetlana", + "eliana", + "albert", + "eftimia", + "carol", + "beatrice", + "radu", + "doru", + "cristian", + "irina", + "zaraza", + "clara", + "teohari", + "anabela", + "otilia", + "marcheta", + "emanoil" + ], + "LAST_NAME": [ + "stancu", + "marin", + "dobre", + "manole", + "ioni\u021b\u0103", + "popescu", + "diaconescu", + "albu", + "dinu", + "stoica", + "preda", + "pu\u0219ca\u0219u", + "georgescu", + "dima", + "neme\u0219", + "barbu", + "dochioiu", + "ni\u021b\u0103", + "ababei", + "popa", + "tudor", + "ardelean", + "cristea", + "pop", + "ionescu", + "mocanu", + "diaconu", + "voinea", + "gheorghiu", + "mazilescu", + "oprea", + "tabacu", + "florea", + "nistor", + "suciu", + "tomescu", + "stan", + "aanei", + "toma", + "eftimie", + "ene", + "st\u0103nescu", + "dumitrescu" + ], + "OTHER_PRONOUN": [ + "them" + ], + "LAST_NAME_MALE": [], + "LAST_NAME_FEMALE": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "fat\u0103_de_serviciu": "grum", + "nevast\u0103": "so\u021b", + "mireas\u0103": "gr\u0103jdar", + "femeie_de_afaceri": "afacerist", + "afacerist\u0103": "businessman", + "pre\u0219edint\u0103": "pre\u0219edinte", + "pui": "gaur", + "v\u0103c\u0103reas\u0103": "v\u0103car", + "v\u0103c\u0103ri\u021b\u0103": "cowboy", + "\u00eemp\u0103r\u0103teas\u0103": "saturnia_pavonia", + "femeiesc": "masculin", + "muieresc": "mascul", + "feminin": "masculin", + "guvernant": "guvernator_al_unui_stat_al_statelor_unite_ale_americii", + "guvernant\u0103": "guvernator", + "nepoat\u0103": "nepot", + "de_la": "lia", + "s\u0103u": "al_lor", + "eroin\u0103": "erou", + "s\u0103i": "ale_lor", + "masez\u0103": "maseur", + "metres\u0103": "profesionist", + "matrix": "tat\u0103", + "mam\u0103": "tat\u0103", + "maic\u0103": "monachus", + "c\u0103lug\u0103ri\u021b\u0103": "c\u0103lug\u0103r", + "nun": "frate", + "poli\u021bist\u0103": "poli\u021bist", + "femeie_poli\u021bist": "poli\u021bist", + "preoteas\u0103": "pre", + "prin\u021bes\u0103": "prince", + "regin\u0103": "indra", + "homosexual": "indra", + "dumneaei": "dumnealui", + "sun": "he", + "surori": "german", + "sor\u0103": "frate", + "naja": "german", + "mam\u0103_vitreg\u0103": "tat\u0103_vitreg", + "ma\u0219ter\u0103": "tat\u0103_vitreg", + "osp\u0103tar\u0103": "steward", + "stewardes\u0103": "steward", + "garson": "fat\u0103", + "chelneri\u021b\u0103": "chelner", + "osp\u0103t\u0103ri\u021b\u0103": "garson", + "v\u0103duv\u0103": "v\u0103duv", + "muiere": "b\u0103rbat", + "so\u021bie": "so\u021b", + "vr\u0103jitor": "magician", + "striga": "magician", + "wicca": "vr\u0103jitor", + "vr\u0103jitoare": "vr\u0103jitor", + "doamn\u0103": "individ", + "femeie": "individ", + "boy": "copil\u0103", + "fiu": "copil\u0103", + "b\u0103iat": "fat\u0103" + }, + "other_gender_swap": { + "them": "de_la", + "\u00eei": "iad", + "iad": "dumneaei", + "s\u0103i": "ale_lor", + "lia": "ale_lor", + "ai_lor": "s\u0103i", + "a_lor": "s\u0103u", + "al_lor": "s\u0103u", + "ale_lor": "s\u0103u", + "dumnealor": "sun", + "olar": "sun", + "jale": "dumneaei", + "he": "jale", + "dumnealui": "dumnealor", + "s\u0103u": "ai_lor", + "dumneaei": "olar", + "sun": "olar", + "de_la": "s\u0103i" + }, + "en_pronoun2gender": { + "they": [ + "transgender", + "transgen", + "homosexual" + ], + "he": [ + "b\u0103iat", + "mascul", + "b\u0103rbat", + "masculin", + "gaur", + "fiu", + "little_boy", + "boy", + "garson", + "individ" + ], + "she": [ + "fat\u0103", + "femeiesc", + "domni\u0219oara", + "feminin", + "doamn\u0103", + "lesbian", + "feti\u021b\u0103", + "muieresc", + "fecioar\u0103", + "muiere", + "copil\u0103", + "madam", + "dame", + "femeie", + "sexul_frumos", + "gal" + ] + }, + "en_pronoun2pronoun": { + "he": [ + "he", + "s\u0103u", + "lia", + "s\u0103i", + "\u00eei", + "dumnealui" + ], + "she": [ + "de_la", + "s\u0103u", + "dumneaei", + "s\u0103i", + "sun" + ], + "they": [ + "ale_lor", + "al_lor", + "lia", + "ai_lor", + "s\u0103i", + "them", + "\u00eei", + "dumnealor", + "iad", + "jale", + "a_lor", + "olar" + ], + "it": [ + "\u0103ia", + "c\u0103", + "aceast\u0103", + "astea", + "acest", + "\u0103\u0219tia", + "tyto", + "acele", + "aceste", + "ace\u0219ti", + "chist", + "acei", + "ora\u0219ul_b\u00e2ntuit", + "alea", + "\u0103sta" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/roa-opt.json b/data_tooling/pii_processing/ontology/data/roa-opt.json new file mode 100644 index 0000000..33058eb --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/roa-opt.json @@ -0,0 +1,40 @@ +{ + "GENDER": [ + "moller" + ], + "JOB": [ + "marinneiro", + "celorgi\u00e3o" + ], + "PUBLIC_FIGURE": [ + "muller" + ], + "RELIGION_MEMBER": [ + "crisch\u00e3o" + ], + "RACE": [ + "negro" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + 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"\u043a\u0430\u0431\u043e_\u0432\u0435\u0440\u0434\u0435", + "\u043d\u0435\u0442_\u043f\u0440\u043e\u0431\u043b\u0435\u043c", + "\u043d\u0430\u0440\u043e\u0434\u043d\u0430\u044f_\u0441\u043a\u0443\u043f\u0449\u0438\u043d\u0430_\u0441\u0435\u0440\u0431\u0438\u0438", + "\u043c\u043e\u043d\u0434\u0440\u0438\u0430\u043d_\u043f\u0438\u0442", + "\u0434\u0432\u0430_\u0431\u0440\u0430\u0442\u0430", + "\u043d\u0443_\u0438_\u0447\u0442\u043e_\u0438\u0437_\u0442\u043e\u0433\u043e", + "\u0432\u043e\u0435\u043d\u043d\u043e_\u0432\u043e\u0437\u0434\u0443\u0448\u043d\u044b\u0435_\u0441\u0438\u043b\u044b", + "the_rolling_stones", + "\u043d\u0430\u0440\u043e\u0434\u043d\u043e\u0435_\u0441\u043e\u0431\u0440\u0430\u043d\u0438\u0435_\u0431\u043e\u043b\u0433\u0430\u0440\u0438\u0438", + "\u043c\u043d\u043e\u0433\u043e\u0446\u0432\u0435\u0442\u043d\u0438\u0446\u0430", + "\u044d\u043b\u044c_\u0430\u0439\u043d", + "\u0432_\u043f\u0435\u0440\u0432\u044b\u0439_\u043e\u0447\u0435\u0440\u0435\u0434\u044c", + "\u043d\u0430_\u0437\u0434\u043e\u0440\u043e\u0432\u044c\u0435", + "\u0432\u0435\u0441\u043f\u0443\u0447\u0447\u0438_\u0430\u043c\u0435\u0440\u0438\u0433\u043e", + "\u043a\u0430\u0440\u043c\u0435\u043b\u044c", + "\u043a\u043e\u043b\u044c\u0446\u0435\u0432\u0430\u044f", + "\u043d\u0430_\u0432\u0441\u044f\u043a\u0438\u0439_\u043f\u043e\u0436\u0430\u0440\u043d\u044b\u0439_\u0441\u043b\u0443\u0447\u0430\u0439", + "\u043c\u0430\u043b\u044c\u0432\u0438\u043d\u044b", + "\u0441\u043f\u043e\u0440\u0442\u043f\u043b\u043e\u0449\u0430\u0434\u043a\u0430" + ], + "ANIMAL": [ + "\u0447\u0430\u0439\u043a\u043e\u0432\u044b\u0435", + "\u0441\u043e\u0431\u043e\u043b\u044c", + "\u0431\u0435\u0440\u0435\u0433\u043e\u0432\u0443\u0448\u043a\u0430", + "chelonioidea", + "\u043c\u0430\u043d\u0434\u0430\u0440\u0438\u043d\u043a\u0430", + "sapo", + "\u0442\u0440\u0430\u0443\u0440\u043d\u0438\u0446\u0430", + "\u0442\u0435\u043b\u0435\u0434\u0443", + "\u043a\u0430\u0448\u0430\u043b\u043e\u0442", + "\u043c\u0430\u043d\u0434\u0430\u0432\u043e\u0448\u043a\u0430", + "\u0433\u043e\u0440\u0431\u0430\u0447", + "\u0432\u0438\u0440\u0443\u0441_\u0442\u0430\u0431\u0430\u0447\u043d\u043e\u0439_\u043c\u043e\u0437\u0430\u0438\u043a\u0438", + "\u0441\u0443\u0445\u043e\u043d\u043e\u0441", + "sea_slug", + "lactobacillus_acidophilus", + "\u0430\u0440\u0442\u0435\u043c\u0438\u0438", + "vibe", + "\u0432\u0438\u0440\u0443\u0441_\u044d\u043f\u0448\u0442\u0435\u0439\u043d\u0430_\u0431\u0430\u0440\u0440", + "\u043f\u043e\u043b\u0443\u043d\u043e\u0447\u043d\u0438\u043a", + "\u0431\u0435\u0433\u0443\u043d\u043e\u043a", + "\u0441\u0442\u0430\u0440\u0448\u0438\u043d\u0430", + "\u0431\u0430\u0440\u0440\u0430\u043c\u0443\u043d\u0434\u0438", + "\u043e\u0431\u044b\u043a\u043d\u043e\u0432\u0435\u043d\u043d\u044b\u0439_\u0441\u043e\u043b\u043d\u0435\u0447\u043d\u0438\u043a", + "\u043a\u0440\u0430\u0441\u043d\u043e\u0437\u043e\u0431\u0438\u043a", + "\u0447\u0451\u0440\u043d\u044b\u0439_\u0431\u0443\u0444\u0444\u0430\u043b\u043e", + "\u0440\u0443\u0447\u0435\u0439\u043d\u0438\u043a", + "\u0447\u0451\u0440\u043d\u0430\u044f_\u0447\u0435\u0440\u0435\u043f\u0430\u0445\u0430", + "\u043d\u0435\u043f\u0430\u0440\u043d\u043e\u043a\u043e\u043f\u044b\u0442\u043d\u044b\u0435", + "\u0441\u0442\u0440\u0438\u0436\u0438\u043d\u044b\u0435", + "\u0436\u0435\u043b\u0442\u043e\u0431\u0440\u044e\u0445\u0438\u0439", + "\u0433\u043b\u0443\u0445\u0430\u0440\u044c", + "\u0434\u0435\u0440\u0435\u0432\u0435\u043d\u0441\u043a\u0430\u044f_\u043b\u0430\u0441\u0442\u043e\u0447\u043a\u0430", + "\u043a\u0432\u0430\u043a\u0432\u0430", + "\u0441\u043a\u0432\u0430\u0442\u0438\u043d\u0430", + "\u0442\u0438\u0433\u0440\u0451\u043d\u043e\u043a", + "\u0431\u0430\u043a\u0442\u0440\u0438\u0430\u043d", + "\u0441\u043e\u043a\u043e\u043b\u044b", + "sivuch", + "megascops", + "\u0441\u043e\u043d\u044f_\u043f\u043e\u043b\u0447\u043e\u043a", + "\u0433\u0435\u043c\u043e\u0440\u0440\u0430\u0433\u0438\u0447\u0435\u0441\u043a\u0430\u044f_\u043b\u0438\u0445\u043e\u0440\u0430\u0434\u043a\u0430_\u044d\u0431\u043e\u043b\u0430", + "\u043c\u0443\u0445\u043e\u043b\u043e\u0432\u043a\u043e\u0432\u044b\u0435", + "\u043a\u0430\u043c\u043f\u043e\u043d\u043e\u0442\u0443\u0441", + "\u0441\u043e\u043b\u043d\u0435\u0447\u043d\u0438\u043a", + "\u043a\u0430\u0437\u0430\u043d\u043e\u0432\u0430", + "\u0431\u0430\u0440\u0442\u0440\u0430\u043c\u0438\u044f", + "\u043a\u043e\u0440\u0438\u0444\u0435\u043d\u0430", + "\u043f\u0435\u0440\u0435\u043f\u0435\u043b\u044f\u0442\u043d\u0438\u043a", + "\u043b\u0435\u0441\u043d\u0430\u044f_\u0437\u0435\u043c\u043b\u0435\u0440\u043e\u0439\u043a\u0430", + "\u043c\u043e\u0440\u044f\u043d\u043a\u0430", + "\u043f\u043e\u043b\u0447\u043e\u043a", + "eagle", + "\u044d\u0431\u043e\u043b\u0430\u0432\u0438\u0440\u0443\u0441", + "\u043a\u0430\u0441\u0430\u0442\u043a\u0430", + "\u043a\u0443\u0440\u0438\u043d\u044b\u0439", + "\u0430\u0439_\u0430\u0439", + "\u0442\u043e\u043f\u043e\u0440\u043e\u043a", + "\u0432\u0438\u0440\u0443\u0441_\u0437\u0430\u043f\u0430\u0434\u043d\u043e\u0433\u043e_\u043d\u0438\u043b\u0430" + ], + "ORG": [ + "\u0442\u0440\u0438_\u0441\u0435\u0441\u0442\u0440\u044b", + "\u043f\u0435\u0440\u0435\u043f\u043b\u044e\u043d\u0443\u0442\u044c", + "\u0441\u0432\u044f\u0442\u0430\u044f_\u0432\u0430\u0440\u0432\u0430\u0440\u0430", + "\u043d\u0435_\u043d\u0430\u0434\u043e_\u043b\u044f_\u043b\u044f", + "\u043f\u043e\u0436\u0430\u0440\u043d\u044b\u0435", + "\u043c\u0435\u0436\u0434\u0443\u043d\u0430\u0440\u043e\u0434\u043d\u044b\u0439_\u0441\u043e\u044e\u0437_\u0442\u0435\u043b\u0435\u043a\u043e\u043c\u043c\u0443\u043d\u0438\u043a\u0430\u0446\u0438\u0439", + "\u0431\u0435\u0437_\u043f\u0440\u0438\u0431\u0430\u043c\u0431\u0430\u0441\u043e\u0432", + "\u0441\u043e\u043b\u0434\u0430\u0442\u043d\u044f", + "\u043a\u043e\u043b\u043b\u0435\u043a\u0442\u0438\u0432\u043d\u044b\u0439_\u0438\u0441\u043a", + "\u043a\u0430\u043d\u0442\u0445\u043e", + "\u0431\u0435\u0441\u043f\u043e\u0448\u043b\u0438\u043d\u043d\u044b\u0439", + "\u043c\u043e\u0434\u0435\u0440\u043d", + "\u0438\u043d\u0442\u0435\u0440\u043f\u043e\u043b", + "\u0432\u043e\u0437\u043d\u0435\u0441\u0435\u043d\u0438\u0435_\u0434\u0435\u0432\u044b_\u043c\u0430\u0440\u0438\u0438", + "\u043d\u0430\u0447\u0430\u043b\u044c\u043d\u0430\u044f_\u0448\u043a\u043e\u043b\u0430", + "\u0447\u0442\u043e_\u0442\u0430\u043a\u043e\u0435", + "\u0444\u0440\u0430\u043d\u043a\u043c\u0430\u0441\u043e\u043d\u0441\u0442\u0432\u043e", + "\u043d\u0438\u043a\u043e\u0433\u0434\u0430_\u0432_\u0436\u0438\u0437\u043d\u0438", + "the_who", + "\u043f\u043e_\u043f\u043e\u0441\u043b\u0435\u0434\u043d\u0435\u043c\u0443_\u0441\u043b\u043e\u0432\u0443", + "\u043d\u043e\u0432\u0430\u044f_\u043b\u0443\u043d\u0430", + "\u0438\u043d\u0442\u0435\u0440\u043d\u0430\u0442", + "to_the_core", + "\u0430_\u043f\u043e\u0447\u0435\u043c\u0443", + "\u043c\u0430\u0441\u043b\u0438\u0447\u043d\u0430\u044f_\u0433\u043e\u0440\u0430", + "\u043f\u0435\u0440\u0432\u0430\u044f_\u0447\u0435\u0442\u0432\u0435\u0440\u0442\u044c", + "\u043f\u043e\u0434\u043e\u0433\u043d\u0430\u043d\u043d\u044b\u0439", + "\u0432\u043e\u0441\u043f\u0438\u0442\u0430\u043d\u0438\u0435", + "\u044e\u0436\u043d\u043e\u043e\u0441\u0435\u0442\u0438\u043d\u0435\u0446", + "san_francisco", + "\u0433\u043b\u0430\u0437\u0443\u043d\u044c\u044f", + "\u0434\u0430_\u0437\u0434\u0440\u0430\u0432\u0441\u0442\u0432\u0443\u044e\u0442", + "\u043c\u0435\u043d\u044f_\u0437\u043e\u0432\u0443\u0442", + "\u043f\u0440\u0430\u0432\u0438\u0442\u0435\u043b\u044c\u0441\u0442\u0432\u043e", + "\u043f\u043e\u043b\u0443\u0434\u0440\u0430\u0433\u043e\u0446\u0435\u043d\u043d\u044b\u0439", + "\u0443\u0433\u043e\u043b\u043e\u0432\u043d\u044b\u0439_\u043a\u043e\u0434\u0435\u043a\u0441", + "\u0431\u0435\u0437_\u0438\u0437\u043b\u0438\u0448\u0435\u0441\u0442\u0432", + "\u044e\u0436\u043d\u043e\u043e\u0441\u0435\u0442\u0438\u043d\u043a\u0430", + "\u043a\u0442\u043e_\u0432\u044b", + "\u043c\u0430\u043b\u044c\u0447\u0438\u043a_\u0441_\u043f\u0430\u043b\u044c\u0447\u0438\u043a", + "\u0431\u043e\u0440\u0442_\u043e_\u0431\u043e\u0440\u0442", + "\u0446\u0435\u043d\u0442\u0440\u0430\u043b\u044c\u043d\u044b\u0439_\u0431\u0430\u043d\u043a", + "\u0432\u0435\u0440\u0445\u043d\u0435\u0435_\u043e\u0437\u0435\u0440\u043e", + "\u0432\u0430\u0441\u0438\u043b\u0438\u0439_\u0432\u0435\u043b\u0438\u043a\u0438\u0439", + "\u0432\u0438\u043a\u043a\u0430", + "\u0437\u043e\u043b\u043e\u0442\u043e\u0439_\u0432\u0435\u043a", + "\u0445\u0443\u0430\u043d\u0445\u044d", + "\u043a\u0440\u0430\u0441\u043d\u043e\u0433\u0432\u0430\u0440\u0434\u0435\u0435\u0446", + "\u0431\u044b\u0442\u044c_\u0432\u0435\u0441\u044c_\u0432_\u043a\u043e\u0433\u043e_\u0442\u043e", + "\u043f\u0435\u0440\u0435\u043f\u0440\u0430\u0432\u043a\u0430", + "\u0432\u043e\u0435\u043d\u043d\u0430\u044f_\u0430\u043a\u0430\u0434\u0435\u043c\u0438\u044f", + "\u043c\u0430\u0433\u0430\u0442\u044d", + "\u043d\u0430\u0443\u0442\u0438\u043b\u0443\u0441_\u043f\u043e\u043c\u043f\u0438\u043b\u0438\u0443\u0441", + "\u0434\u0435\u043c\u043e\u043a\u0440\u0430\u0442\u0438\u0447\u0435\u0441\u043a\u0430\u044f_\u043f\u0430\u0440\u0442\u0438\u044f", + "\u043c\u0430\u043b\u044c\u0447\u0438\u0448\u043d\u0438\u043a", + "\u0445\u0440\u0438\u0441\u0442\u0438\u0430\u043d\u0441\u043a\u0430\u044f_\u043d\u0430\u0443\u043a\u0430", + "\u0432\u044b_\u043a\u0442\u043e", + "\u0442\u0430\u043c\u043e\u0436\u043d\u044f", + "\u043f\u0440\u0438\u0441\u0442\u0443\u043f\u0430\u0439\u0442\u0435", + "\u043f\u0430\u0440\u0442\u0438\u044f_\u0442\u0440\u0443\u0434\u0430", + "\u0441\u043e\u0446\u0438\u0430\u043b\u0438\u0441\u0442\u0438\u0447\u0435\u0441\u043a\u0430\u044f_\u043f\u0430\u0440\u0442\u0438\u044f", + "dia", + "\u043a\u0430\u043a_\u0443\u0433\u043e\u0434\u043d\u043e", + "\u0432\u0432\u0441", + "\u0433\u043e\u043c\u0438\u043d\u044c\u0434\u0430\u043d", + "\u0430\u0440\u043c\u0438\u044f_\u0441\u0448\u0430", + "\u043f\u043e\u0441\u043b\u0435_\u0440\u043e\u0436\u0434\u0435\u0441\u0442\u0432\u0430_\u0445\u0440\u0438\u0441\u0442\u043e\u0432\u0430", + "\u0432_\u043a\u0430\u0432\u044b\u0447\u043a\u0430\u0445", + "\u0430\u043d\u0442\u0438\u043c\u0430\u0441\u043e\u043d\u0441\u043a\u0430\u044f_\u043f\u0430\u0440\u0442\u0438\u044f", + "\u0442\u044b_\u043a\u0442\u043e", + "\u0432\u0435\u0440\u0445\u043d\u0435\u0435", + "\u043d\u0438\u043a\u043e\u0433\u0434\u0430_\u043d\u0435", + "\u0431\u0435\u0437_\u0432\u0435\u0441\u0442\u0438_\u043f\u0440\u043e\u043f\u0430\u0432\u0448\u0438\u0439", + "\u0438\u0441\u043b\u0430\u043c\u043e\u0432\u0435\u0434\u0435\u043d\u0438\u0435", + "\u0438_\u0434\u0440", + "\u0444\u0435\u0440\u043c\u0435\u0440\u0441\u0442\u0432\u043e", + "\u0436\u0435\u0432\u0430\u0442\u0435\u043b\u044c\u043d\u0430\u044f_\u0440\u0435\u0437\u0438\u043d\u043a\u0430", + "\u0434\u0435\u043b\u043e\u0432\u0430\u044f_\u0447\u0430\u0441\u0442\u044c_\u0433\u043e\u0440\u043e\u0434\u0430", + "\u0432\u043f\u0440\u043e\u0447\u0435\u043c", + "\u0430\u043b\u044c_\u0434\u0436\u0430\u0437\u0438\u0440\u0430", + "\u0438_\u043f\u0440", + "\u0441\u043e\u0446\u0438\u0430\u043b_\u0434\u0435\u043c\u043e\u043a\u0440\u0430\u0442\u0438\u0447\u0435\u0441\u043a\u0430\u044f_\u043f\u0430\u0440\u0442\u0438\u044f_\u044d\u0441\u0442\u043e\u043d\u0438\u0438", + "\u0440\u0430\u0434\u0438\u043e\u0433\u0430\u043b\u0430\u043a\u0442\u0438\u043a\u0430", + "\u043f\u0441\u0438\u0445\u0443\u0448\u043a\u0430", + "\u0441\u0438\u043d\u0442\u043e\u0438\u0437\u043c", + "\u043c\u0438\u043b\u043b\u0438_\u043c\u0435\u0434\u0436\u043b\u0438\u0441_\u0430\u0437\u0435\u0440\u0431\u0430\u0439\u0434\u0436\u0430\u043d\u0430", + "\u043f\u043e\u0447\u0442\u0430\u043c\u0442", + "\u044f_\u0442\u0435\u0431\u044f_\u043b\u044e\u0431\u043b\u044e", + "\u043d\u0430\u0446\u0438\u043e\u043d\u0430\u043b\u044c\u043d\u043e\u0435_\u0441\u043e\u0431\u0440\u0430\u043d\u0438\u0435_\u0444\u0440\u0430\u043d\u0446\u0438\u0438", + "\u0432\u0430\u0439\u0448\u043d\u0430\u0432\u0438\u0437\u043c", + "\u0441\u0438\u043d\u0442\u043e", + "\u043f\u043e\u043b\u0438\u0442\u0438\u0447\u0435\u0441\u043a\u0430\u044f_\u043f\u0430\u0440\u0442\u0438\u044f", + "\u043f\u0430\u0440\u0442\u0438", + "\u043f\u0440\u043e\u0442\u0438\u0432\u043e\u0434\u0435\u0439\u0441\u0442\u0432\u0438\u0435", + "\u043a\u0430\u043d\u0443\u043d_\u043d\u043e\u0432\u043e\u0433\u043e_\u0433\u043e\u0434\u0430", + "\u0433\u043b\u0430\u0432\u043f\u043e\u0447\u0442\u0430\u043c\u0442", + "\u043d\u0438\u043a\u043e\u0433\u0434\u0430_\u0431\u043e\u043b\u044c\u0448\u0435", + "\u0441\u0442\u043e\u043f\u0440\u043e\u0446\u0435\u043d\u0442\u043d\u044b\u0439", + "\u0432\u043e\u0437\u0434\u0443\u0448\u043d\u044b\u0439_\u043a\u043e\u0440\u043f\u0443\u0441_\u0438\u0440\u043b\u0430\u043d\u0434\u0438\u0438", + "\u043d\u0430_\u043c\u0435\u0441\u0442\u0435", + "\u043b\u0430\u043d\u043a\u0430\u0441\u0442\u0435\u0440\u044b", + "\u043a\u0440\u0430\u0441\u043d\u043e\u0435_\u043c\u043e\u0440\u0435", + "\u0434\u0430_\u0437\u0434\u0440\u0430\u0432\u0441\u0442\u0432\u0443\u0435\u0442", + "the_young_turks", + "\u043f\u0440\u043e\u0433\u0440\u0435\u0441\u0441\u0438\u0441\u0442\u0441\u043a\u0430\u044f_\u043f\u0430\u0440\u0442\u0438\u044f_\u0431\u0440\u0430\u0437\u0438\u043b\u0438\u0438", + "\u0430\u0440_\u0434\u0435\u043a\u043e", + "\u043b\u0435\u0441\u043d\u043e\u0435", + "\u043d\u0430\u0446\u0438\u043e\u043d\u0430\u043b\u044c\u043d\u0430\u044f_\u0430\u0441\u0441\u0430\u043c\u0431\u043b\u0435\u044f", + "\u0441\u0443\u0440\u0430\u0442\u0442\u0445\u0430\u043d\u0438", + "\u0441\u0435\u043d\u0442_\u043a\u043b\u044d\u0440", + "\u0431\u043e\u0442\u0430\u043d\u0438\u0447\u0435\u0441\u043a\u0438\u0439_\u0441\u0430\u0434", + "\u043e\u043b\u0438\u043c\u043f\u0438\u0439\u0441\u043a\u0430\u044f_\u0434\u0435\u0440\u0435\u0432\u043d\u044f", + "\u0437\u0430\u043f\u0435\u0440\u0435\u0442\u044c", + "\u043f\u043e\u0447\u0442\u043e\u0432\u043e\u0435_\u043e\u0442\u0434\u0435\u043b\u0435\u043d\u0438\u0435", + "\u0430\u0440_\u043d\u0443\u0432\u043e", + "\u0433\u043e\u043b\u043b\u0438\u0432\u0443\u0434", + "\u043a\u0430\u043a_\u0445\u043e\u0447\u0435\u0448\u044c", + "\u043c\u043e\u043b\u043b", + "\u043a\u0440\u043e\u043c\u0430\u043d\u044c\u043e\u043d\u0435\u0446", + "\u0433\u0440\u0443\u043f\u043f\u043e\u0432\u043e\u0439_\u0438\u0441\u043a", + "\u0441\u0440\u0435\u0434\u043d\u0438\u0439_\u043a\u043b\u0430\u0441\u0441", + "\u0432\u0438\u043d\u043d\u0438_\u043f\u0443\u0445", + "\u043b\u0435\u0439\u0431\u043e\u0440\u0438\u0441\u0442\u0441\u043a\u0430\u044f_\u043f\u0430\u0440\u0442\u0438\u044f", + "\u0438_\u043f\u0440\u043e\u0447\u0438\u0435", + "\u043f\u0435\u043d\u0441\u0438\u043e\u043d\u043d\u044b\u0439_\u0444\u043e\u043d\u0434", + "\u043e\u0441\u0442\u0440\u043e\u0432\u0430_\u0437\u0435\u043b\u0451\u043d\u043e\u0433\u043e_\u043c\u044b\u0441\u0430", + "\u0431\u0435\u043b\u043e\u0435_\u0437\u043e\u043b\u043e\u0442\u043e", + "\u043a\u0442\u043e_\u0442\u044b", + "\u043d\u0430\u0440\u043e\u0434\u043d\u044b\u0439_\u0444\u0440\u043e\u043d\u0442", + "\u0430\u0432\u0441\u0442\u0440\u0430\u043b\u0438\u0439\u0441\u043a\u0430\u044f_\u043b\u0435\u0439\u0431\u043e\u0440\u0438\u0441\u0442\u0441\u043a\u0430\u044f_\u043f\u0430\u0440\u0442\u0438\u044f", + "\u0432\u0438\u043d\u044c\u043b\u043e\u043d\u0433", + "\u043f\u0440\u043e\u043c\u044b\u0448\u043b\u0435\u043d\u043d\u044b\u0439_\u043f\u0430\u0440\u043a", + "\u0436\u0435\u0432\u0430\u0447\u043a\u0430", + "\u043a\u0440\u0438\u0432\u043e\u0439_\u0440\u043e\u0433", + "\u0430\u0433\u0440\u0438\u043a\u0443\u043b\u044c\u0442\u0443\u0440\u0430", + "\u0441\u0432\u044f\u0442\u043e\u0435_\u0441\u0435\u043c\u0435\u0439\u0441\u0442\u0432\u043e", + "by_the_way", + "\u043d\u0430\u0446\u0438\u043e\u043d\u0430\u043b\u044c\u043d\u043e\u0435_\u0441\u043e\u0431\u0440\u0430\u043d\u0438\u0435_\u043f\u043e\u043b\u044c\u0448\u0438", + "\u0442\u0440\u0443\u0430_\u0440\u0438\u0432\u044c\u0435\u0440", + "\u0431\u0435\u0437_\u0441\u0432\u0438\u0441\u0442\u0435\u043b\u043e\u043a_\u0438_\u043f\u0435\u0440\u0434\u0435\u043b\u043e\u043a", + "in_situ", + "\u0447\u0451\u0440\u043d\u044b\u0439_\u0440\u044b\u043d\u043e\u043a", + "\u0431\u0435\u0437_\u043d\u0430\u0432\u043e\u0440\u043e\u0442\u043e\u0432", + "\u0441\u0435\u043d\u0442_\u043b\u044e\u0441\u0438\u044f", + "doc", + "\u043b\u0435\u0439\u0431\u043e\u0440\u0438\u0441\u0442\u0441\u043a\u0430\u044f_\u043f\u0430\u0440\u0442\u0438\u044f_\u0432\u0435\u043b\u0438\u043a\u043e\u0431\u0440\u0438\u0442\u0430\u043d\u0438\u0438", + "\u0436\u0451\u043b\u0442\u0430\u044f_\u0440\u0435\u043a\u0430", + "\u043d\u0430\u0440\u0430\u0441\u0442\u0438\u0442\u044c", + "\u0442\u043e\u0440\u0433\u043e\u0432\u044b\u0439_\u0446\u0435\u043d\u0442\u0440", + "\u043a\u0440\u043e\u043c\u0430\u043d\u044c\u043e\u043d\u043a\u0430", + "\u043f\u0440\u043e\u0444\u0435\u0441\u0441\u0438\u043e\u043d\u0430\u043b\u044c\u043d\u044b\u0439_\u0441\u043e\u044e\u0437", + "ace", + "\u0438_\u0434\u0440\u0443\u0433\u043e\u0435", + "\u0438_\u0434\u0440\u0443\u0433\u0438\u0435", + "\u043a\u0430\u043f\u0435\u0442\u0438\u043d\u0433\u0438", + "\u043f\u043e\u0441\u043b\u0435\u0434\u043e\u0432\u0430\u0442\u0435\u043b\u044c\u043d\u043e\u0441\u0442\u044c_\u0444\u0438\u0431\u043e\u043d\u0430\u0447\u0447\u0438", + "\u043c\u0435\u0434\u0443\u0447\u0438\u043b\u0438\u0449\u0435", + "\u0441\u0432\u0438\u0434\u0435\u0442\u0435\u043b\u0438_\u0438\u0435\u0433\u043e\u0432\u044b", + "streptococcus_pyogenes", + "\u043e\u043f\u043e\u043b\u043e\u0443\u043c\u0435\u0442\u044c", + "\u0444\u0440\u0443\u043a\u0442\u043e\u0432\u044b\u0439_\u0441\u0430\u043b\u0430\u0442", + "\u0441\u0430\u043d\u0442\u0430_\u0444\u0435", + "\u043a\u0440\u043e\u0432\u043d\u044b\u0435_\u0431\u0440\u0430\u0442\u044c\u044f", + "\u0443_\u043a\u043e\u0433\u043e_\u0441\u043d\u043e\u0440\u043e\u0432\u043a\u0430_\u0442\u043e\u0442_\u0440\u0430\u0431\u043e\u0442\u0430\u0435\u0442_\u043b\u043e\u0432\u043a\u043e", + "\u0434\u0438\u0437\u0430", + "\u043f\u0430\u0440\u043b\u0430\u043c\u0435\u043d\u0442_\u0440\u0435\u0441\u043f\u0443\u0431\u043b\u0438\u043a\u0438_\u043a\u043e\u0440\u0435\u044f", + "\u043a_\u043d\u0430\u0441\u0442\u043e\u044f\u0449\u0435\u043c\u0443_\u043c\u043e\u043c\u0435\u043d\u0442\u0443", + "\u0430_\u0447\u0442\u043e_\u0442\u0430\u043a", + "\u0431\u0430\u0442\u0430\u043b\u044c\u043e\u043d", + "\u0430\u043c\u0435\u0440\u0438\u043a\u0430\u043d\u0438\u0441\u0442\u0438\u043a\u0430", + "\u0432\u044b\u0441\u0448\u0438\u0439_\u043a\u043b\u0430\u0441\u0441", + "\u043d\u0430\u0440\u043e\u0434\u043d\u0430\u044f_\u0441\u043a\u0443\u043f\u0449\u0438\u043d\u0430_\u0440\u0435\u0441\u043f\u0443\u0431\u043b\u0438\u043a\u0438_\u0441\u0435\u0440\u0431\u0441\u043a\u043e\u0439", + "\u0437\u0435\u043b\u0451\u043d\u0430\u044f_\u043f\u0430\u0440\u0442\u0438\u044f_\u0438\u0440\u043b\u0430\u043d\u0434\u0438\u0438", + "\u0440\u0430\u0431\u043e\u0447\u0438\u0439_\u043a\u043b\u0430\u0441\u0441", + "\u0441\u043e\u0435\u0434\u0438\u043d\u0451\u043d\u043d\u044b\u0435_\u0448\u0442\u0430\u0442\u044b" + ], + "PRODUCT": [ + "st_vincent", + "\u0432_\u043f\u043e\u0441\u043b\u0435\u0434\u043d\u044e\u044e_\u043c\u0438\u043d\u0443\u0442\u0443", + "deja_vu", + "\u0441\u0430\u043d_\u0445\u043e\u0430\u043a\u0438\u043d", + "\u043d\u0435_\u0436\u0438\u0437\u043d\u044c_\u0430_\u043c\u0430\u043b\u0438\u043d\u0430", + "s_tog", + "\u0442\u0430\u043d\u0446\u043f\u043e\u043b", + "\u0434\u0432\u0430_\u0431\u0440\u0430\u0442\u0430", + "\u0448\u0435\u0441\u0442\u0435\u0440\u0451\u043d\u043a\u0430", + "echinopsis_pachanoi", + "\u0434\u0432\u0435_\u0441\u0435\u0441\u0442\u0440\u044b", + "\u0441_\u0440\u043e\u0436\u0434\u0435\u0441\u0442\u0432\u043e\u043c", + "\u0441_\u0440\u043e\u0436\u0434\u0435\u0441\u0442\u0432\u043e\u043c_\u0445\u0440\u0438\u0441\u0442\u043e\u0432\u044b\u043c", + "\u043a\u0430\u043a_\u0432\u0430\u043c_\u0443\u0433\u043e\u0434\u043d\u043e", + "\u0447\u0442\u043e_\u043d\u043e\u0432\u043e\u0433\u043e", + "\u043d\u043e\u0432\u044b\u0439_\u0437\u0430\u0432\u0435\u0442", + "\u0437\u0430\u043a\u043e\u0443\u043b\u043e\u043a", + "\u043a\u0430\u043a_\u0431\u044b", + "monte_cristo", + "\u0438\u043e\u0432\u043b\u0435\u0432\u044b_\u0441\u043b\u0451\u0437\u044b", + "the_hitchhiker\u2019s_guide_to_the_galaxy", + "\u0434\u0435\u043d\u044c_\u043f\u043e\u0434\u0430\u0440\u043a\u043e\u0432", + "\u043c\u043e\u0440\u0441\u043a\u0430\u044f_\u0441\u0432\u0438\u043d\u043a\u0430", + "\u043f\u0440\u043e\u0442\u0438\u0432\u043e\u0432\u043e\u0437\u0434\u0443\u0448\u043d\u044b\u0439", + "\u0441_\u0431\u043e\u0436\u044c\u0435\u0439_\u043f\u043e\u043c\u043e\u0449\u044c\u044e", + "\u0441\u0435\u043d\u0442_\u0445\u0435\u043b\u0435\u043d\u0441", + "after_burner", + "\u0431\u0440\u043e\u043d\u0435\u0430\u0432\u0442\u043e\u043c\u043e\u0431\u0438\u043b\u044c", + "\u043d\u0435\u043f\u0440\u0435\u043c\u0435\u043d\u043d\u043e", + "\u0442\u0430\u043d\u0446\u043f\u043b\u043e\u0449\u0430\u0434\u043a\u0430", + "deutsche_welle", + "\u043a\u0430\u043a_\u0448\u0442\u044b\u043a", + "\u0434\u0438\u0441\u043a\u0435\u0442\u0430", + "\u0432_\u043f\u0430\u043c\u044f\u0442\u044c", + "\u043d\u0435\u0437\u0430\u0431\u0443\u0434\u043a\u0430", + "\u043c\u043d\u043e\u0433\u043e_\u0448\u0443\u043c\u0430_\u0438\u0437_\u043d\u0438\u0447\u0435\u0433\u043e", + "\u0441\u0435\u043d_\u043f\u044c\u0435\u0440_\u0438_\u043c\u0438\u043a\u0435\u043b\u043e\u043d", + "\u043d\u0430\u0433\u0440\u044f\u043d\u0443\u0442\u044c", + "\u043f\u043e\u0434\u0442\u044f\u043d\u0443\u0442\u044c\u0441\u044f" + ], + "LANGUAGE": [ + "\u043f\u043e\u0440\u0442\u0443\u0433\u0430\u043b\u044c\u0441\u043a\u0438\u0439", + "\u0432\u0430\u043b\u043b\u0438\u0439\u0441\u043a\u0438\u0439", + "\u0438\u0441\u043b\u0430\u043d\u0434\u0441\u043a\u0438\u0439", + "\u043a\u0430\u0442\u0430\u043b\u043e\u043d\u043a\u0430", + "\u0433\u0435\u0440\u043c\u0430\u043d\u0435\u0446", + "\u0447\u0443\u0432\u0430\u0448\u0441\u043a\u0438\u0439", + "\u0441\u0435\u0432\u0435\u0440\u043d\u043e\u0441\u0430\u0430\u043c\u0441\u043a\u0438\u0439", + "\u0430\u043d\u0433\u043b\u0438\u0439\u0441\u043a\u0438\u0439", + "\u0432\u0430\u043b\u043b\u043e\u043d\u0441\u043a\u0438\u0439", + "\u043a\u0430\u0437\u0430\u0448\u043a\u0430", + "\u043a\u043e\u0440\u0441\u0438\u043a\u0430\u043d\u0441\u043a\u0438\u0439", + "\u043a\u043e\u043c\u0438_\u044f\u0437\u044c\u0432\u0438\u043d\u0441\u043a\u0438\u0439", + "\u0442\u0443\u0440\u043a\u043c\u0435\u043d\u0441\u043a\u0438\u0439", + "\u044f\u043f\u043e\u043d\u0441\u043a\u0438\u0439", + "\u0441\u0430\u043c\u043e\u0430\u043d\u043a\u0430", + "\u0434\u0430\u0440_\u0440\u0435\u0447\u0438", + "\u043f\u043e\u0440\u0442\u0443\u0433\u0430\u043b\u0435\u0446", + "\u043b\u0438\u0442\u043e\u0432\u0441\u043a\u0438\u0439", + "\u044e\u0436\u043d\u043e\u0430\u043b\u0442\u0430\u0439\u0441\u043a\u0438\u0439", + "\u043a\u0430\u0442\u0430\u043b\u043e\u043d\u0435\u0446", + "\u0430\u0440\u0430\u0431", + "\u0438\u0440\u043b\u0430\u043d\u0434\u0441\u043a\u0438\u0439", + "\u043e\u0441\u0435\u0442\u0438\u043d\u0441\u043a\u0438\u0439", + "\u0441\u0430\u043c\u043e\u0430\u043d\u0435\u0446", + "\u0438\u0437\u0434\u0430\u043b\u0438", + "\u043c\u0430\u0440\u0448\u0430\u043b\u043b\u044c\u0441\u043a\u0438\u0439", + "\u0444\u0440\u0430\u043d\u0446\u0443\u0437\u0441\u043a\u0438\u0439", + "\u0431\u0435\u043b\u043e\u0440\u0443\u0441\u0441\u043a\u0438\u0439", + "\u0438\u0437\u0434\u0430\u043b\u0435\u043a\u0430" + ], + "JOB": [ + "\u0430\u0440\u0431\u043e\u0440\u0438\u0441\u0442", + "\u0434\u0440\u0430\u043f\u0438\u0440\u043e\u0432\u0449\u0438\u043a", + "\u043a\u043e\u0440\u0430\u0431\u0435\u043b", + "guru", + "\u0433\u0435\u0440\u043f\u0435\u0442\u043e\u043b\u043e\u0433", + "\u043f\u0430\u0440\u0438\u043a\u043c\u0430\u0445\u0435\u0440\u0448\u0430", + "\u0434\u0438\u0441\u0442\u0440\u0438\u0431\u044c\u044e\u0442\u043e\u0440", + "\u043a\u043b\u0430\u0434\u043e\u0432\u0449\u0438\u043a", + "make", + "\u043a\u043e\u043b\u043b\u0435\u043a\u0446\u0438\u043e\u043d\u0435\u0440", + "\u0433\u0430\u0440\u043f\u0443\u043d\u0451\u0440", + "\u043a\u043e\u043c\u0435\u043d\u0434\u0430\u043d\u0442", + "sexton", + "\u044d\u043d\u0434\u043e\u043a\u0440\u0438\u043d\u043e\u043b\u043e\u0433", + "\u0440\u0435\u043f\u0435\u0442\u0438\u0442\u043e\u0440", + "\u043a\u0440\u0430\u0441\u0438\u043b\u044c\u0449\u0438\u043a", + "the_police", + "the_sentinel", + "\u043e_\u043f\u044d\u0440", + "\u0441\u0442\u0440\u0430\u0436", + "\u0432\u0435\u043d\u0434\u043e\u0440", + "\u043a\u0430\u043f\u0440\u0430\u043b", + "\u043c\u0430\u0445\u0430\u0443\u0442", + "\u043f\u0440\u043e\u0444\u0435\u0441\u0441\u043e\u0440", + "\u0448\u0435\u0441\u0442\u0438\u043f\u0435\u043d\u0441\u043e\u0432\u0438\u043a", + "\u0432\u0441\u0435_\u043b\u0433\u0443\u0442", + "\u043b\u0438\u0441\u0442\u0435\u0440", + "\u0431\u043b\u043e\u043a\u0444\u043b\u0435\u0439\u0442\u0430", + "grip", + "\u0434\u0435\u0440\u0435\u0432\u043e\u043e\u0431\u0434\u0435\u043b\u043e\u0447\u043d\u0438\u043a", + "\u0433\u0430\u0440\u043f\u0443\u043d\u0449\u0438\u043a", + "\u043a\u0440\u0430\u0441\u043d\u043e\u0434\u0435\u0440\u0435\u0432\u0449\u0438\u043a", + "\u0433\u0430\u0441\u0442\u0430\u0440\u0431\u0430\u0439\u0442\u0435\u0440", + "\u0430\u043d\u0435\u0441\u0442\u0435\u0437\u0438\u043e\u043b\u043e\u0433", + "\u043f\u043e\u0434\u0441\u043a\u0430\u0437\u0447\u0438\u043a", + "\u043e_\u043f\u0435\u0440", + "\u0441\u0442\u0440\u0430\u0436\u043d\u0438\u043a", + "\u043d\u0435\u0432\u0440\u043e\u043b\u043e\u0433", + "\u043f\u043e\u0434\u043f\u043e\u0440\u0443\u0447\u0438\u043a", + "\u043f\u043e\u0432\u0438\u0442\u0443\u0445\u0430", + "scientist", + "\u0442\u0435\u0440\u0430\u043f\u0435\u0432\u0442", + "the_advocate", + "\u043a\u0443\u0440\u0430\u0442\u043e\u0440", + "\u043c\u0435\u043b\u044c\u043d\u0438\u043a\u043e\u0432", + "\u0440\u0430\u0437\u0440\u0430\u0431\u043e\u0442\u0447\u0438\u0446\u0430", + "\u0441\u0442\u0435\u043d\u043e\u0433\u0440\u0430\u0444\u0438\u0441\u0442\u043a\u0430", + "\u043f\u043e\u043c\u043e\u0435\u0448\u043d\u0438\u043a", + "freelancer", + "\u043c\u0438\u043a\u0440\u043e\u0431\u0438\u043e\u043b\u043e\u0433", + "\u0436\u043e\u043b\u043d\u0451\u0440", + "\u043f\u043e\u0434\u043f\u043e\u043b\u043a\u043e\u0432\u043d\u0438\u043a", + "the_guardian", + "\u0441\u0435\u043b\u0435\u043a\u0446\u0438\u043e\u043d\u0435\u0440", + "\u043a\u043e\u0441\u0442\u044e\u043c\u0435\u0440", + "\u043c\u0430\u0441\u0442\u0435\u0440\u043e\u0432\u043e\u0439", + "\u043f\u0430\u0440\u0430\u043b\u0435\u0433\u0430\u043b", + "\u0433\u0440\u0443\u0437\u0447\u0438\u043a", + "\u0441\u0442\u0435\u043d\u043e\u0433\u0440\u0430\u0444", + "\u043a\u0430\u0440\u0430\u0443\u043b\u044c\u043d\u044b\u0439", + "\u0442\u0440\u0430\u0443\u043b\u0435\u0440", + "\u0432\u043e\u043b\u043e\u043d\u0442\u0451\u0440", + "\u0431\u044b\u0442\u044c_\u043f\u0440\u043e\u0432\u043e\u0434\u043d\u0438\u043a\u043e\u043c", + "mate", + "\u043a\u043e\u043d\u0432\u043e\u0438\u0440", + "\u043d\u0435\u0439\u0440\u043e\u0445\u0438\u0440\u0443\u0440\u0433", + "\u043b\u0438\u0442\u0435\u0439\u0449\u0438\u043a", + "\u043a\u043e\u043c\u0435\u0434\u0438\u0430\u043d\u0442", + "\u0442\u0430\u043c\u043e\u0436\u0435\u043d\u043d\u0438\u043a", + "\u0430\u043a\u0430\u0434\u0435\u043c\u0438\u043a", + "\u0440\u0430\u0437\u0440\u0430\u0431\u043e\u0442\u0447\u0438\u043a", + "\u0433\u0438\u0434\u0440\u043e\u043b\u043e\u0433", + "\u043a\u043e\u043d\u0434\u0438\u0442\u0435\u0440", + "\u0444\u043e\u0442\u043e\u0433\u0440\u0430\u0444", + "\u0432\u0435\u0440\u0445\u043e\u043b\u0430\u0437", + "the_economist", + "\u0442\u043e\u043b\u0441\u0442\u043e\u0433\u043e\u043b\u043e\u0432\u043a\u0438", + "\u043f\u043e\u0447\u0442\u0430\u043b\u044c\u043e\u043d\u0448\u0430", + "\u043a\u0430\u0442\u0435\u0445\u0438\u0437\u0430\u0442\u043e\u0440", + "\u0440\u0443\u043a\u043e\u0432\u043e\u0434\u0438\u0442\u0435\u043b\u044c", + "doc", + "\u043f\u043e\u0447\u0442\u0430\u043b\u044c\u043e\u043d", + "\u043f\u0430\u0440\u0430\u043c\u0435\u0434\u0438\u043a", + "the_boxer", + "\u043f\u0430\u0442\u043e\u043b\u043e\u0433", + "\u0441\u0442\u043e\u043c\u0430\u0442\u043e\u043b\u043e\u0433", + "\u043b\u0430\u0440\u0438\u043d\u0433\u043e\u043b\u043e\u0433", + "\u0433\u043e\u043c\u0435\u043e\u043f\u0430\u0442", + "\u0434\u0435\u0441\u0442\u0440\u0443\u043a\u0446\u0438\u044f_\u0441\u0442\u0435\u043a\u043b\u043e\u0432\u0438\u0434\u043d\u043e\u0433\u043e_\u0442\u0435\u043b\u0430", + "\u0438_\u0448\u0432\u0435\u0446_\u0438_\u0436\u043d\u0435\u0446_\u0438_\u043d\u0430_\u0434\u0443\u0434\u0435_\u0438\u0433\u0440\u0435\u0446", + "\u043f\u0443\u0448\u043a\u0430\u0440\u044c", + "\u0431\u0430\u0440\u0438\u0441\u0442\u0430", + "\u043f\u0430\u0434\u0430\u043b\u044c\u0449\u0438\u043a\u0438", + "\u0441\u043e\u043c\u0435\u043b\u044c\u0435", + "\u043c\u043e\u0440\u0435\u043f\u043b\u0430\u0432\u0430\u0442\u0435\u043b\u044c", + "\u0443\u0447\u0440\u0435\u0434\u0438\u0442\u0435\u043b\u044c\u043d\u0438\u0446\u0430", + "\u043a\u0430\u0432\u0430\u043b\u0435\u0440\u0438\u0441\u0442", + "\u0442\u0430\u0439\u043d\u044b\u0439_\u0441\u043e\u0432\u0435\u0442\u043d\u0438\u043a", + "\u043a\u043e\u0440\u0430\u0431\u043b\u0435\u0441\u0442\u0440\u043e\u0438\u0442\u0435\u043b\u044c", + "\u0434\u0435\u0440\u043c\u0430\u0442\u043e\u043b\u043e\u0433", + "\u044d\u043d\u0434\u043e\u0434\u043e\u043d\u0442\u0438\u0441\u0442", + "\u0430\u0440\u0442\u0438\u043b\u043b\u0435\u0440\u0438\u0441\u0442", + "\u043c\u0435\u043b\u044c\u043d\u0438\u043a\u043e\u0432\u0430", + "\u043c\u0435\u043b\u044c\u043d\u0438\u043a", + "\u0430\u0434\u043c\u0438\u043d\u0438\u0441\u0442\u0440\u0430\u0442\u043e\u0440", + "\u043f\u0440\u0435\u0437\u0438\u0434\u0435\u043d\u0442", + "\u0430\u0440\u0431\u043e\u0440\u0438\u0441\u0442\u043a\u0430", + "the_independent", + "bishop", + "\u043a\u0430\u043f\u0438\u0442\u0430\u043d", + "esquire", + "\u0443\u0447\u0440\u0435\u0434\u0438\u0442\u0435\u043b\u044c", + "\u043e\u043f\u0435\u043a\u0443\u043d" + ], + "DISEASE": [ + "\u0442\u0430\u043b\u0430\u0441\u0441\u0435\u043c\u0438\u044f", + "\u043a\u0430\u0440\u0434\u0438\u043e\u043c\u0438\u043e\u043f\u0430\u0442\u0438\u044f", + "\u0441\u0442\u043e\u043b\u0431\u043d\u044f\u043a", + "\u043f\u0440\u043e\u0442\u0435\u0447\u043a\u0430", + "rage", + "chill", + "\u043f\u043e\u043b\u0438\u0434\u0438\u043f\u0441\u0438\u044f", + "\u043f\u0440\u043e\u043b\u0435\u0436\u0435\u043d\u044c", + "\u0442\u043e\u043a\u0441\u043e\u043f\u043b\u0430\u0437\u043c\u043e\u0437", + "\u043e\u0441\u043d\u043e\u0432\u0430\u0442\u0435\u043b\u044c\u043d\u0438\u0446\u0430", + "\u043f\u0440\u043e\u043a\u0442\u0438\u0442", + "mouse", + "\u043a\u0438\u043d\u043e\u0444\u043e\u0431\u0438\u044f", + "\u0441\u0432\u0435\u0442\u043e\u0431\u043e\u044f\u0437\u043d\u044c", + "\u043c\u0430\u043d\u0438\u044f", + "\u0433\u043e\u043b\u043e\u0432\u043e\u043a\u0440\u0443\u0436\u0435\u043d\u0438\u0435", + "\u0441\u043b\u0435\u043f\u043e\u0442\u0430", + "\u043a\u043e\u043d\u0441\u0442\u0438\u043f\u0430\u0446\u0438\u044f", + "\u043c\u0438\u043b\u0438\u0430\u0440\u0438\u044f", + "the_bends", + "\u043f\u043e\u0434\u0441\u0442\u0430\u0432\u0430", + "shape", + "\u043f\u043e\u0436\u0435\u043b\u0430\u043d\u0438\u0435", + "\u043f\u0430\u0440\u0438\u0442\u0435\u0442", + "\u0433\u0438\u043d\u0435\u043a\u043e\u043c\u0430\u0441\u0442\u0438\u044f", + "\u043f\u043e\u043b\u0438\u0443\u0440\u0438\u044f", + "\u0441\u0442\u0440\u0435\u043f\u0442\u043e\u0434\u0435\u0440\u043c\u0438\u044f", + "the_suffering", + "rust", + "\u043c\u0435\u0442\u0435\u043e\u0440\u0438\u0437\u043c", + "\u0441\u043f\u043e\u0440\u044b\u043d\u044c\u044f", + "\u0433\u043e\u0440\u0431\u0430\u0442\u044b\u0439", + "\u043f\u0435\u0440\u0435\u043a\u0430\u0448\u0438\u0432\u0430\u043d\u0438\u0435", + "\u0440\u0430\u0441\u0441\u0442\u0440\u043e\u0439\u0441\u0442\u0432\u043e", + "\u0430\u043d\u0434\u0440\u043e\u0444\u043e\u0431\u0438\u044f", + "\u043f\u0440\u043e\u0433\u0435\u0440\u0438\u044f", + "\u0432\u043e\u0434\u043e\u0431\u043e\u044f\u0437\u043d\u044c", + "\u0441\u043e\u0446\u0438\u043e\u0444\u043e\u0431\u0438\u044f", + "\u043a\u0430\u0448\u0442\u0430\u043d\u043e\u0432\u044b\u0439", + "\u0431\u0435\u0440\u0435\u043c\u0435\u043d\u043d\u043e\u0441\u0442\u044c", + "\u043b\u0438\u0442\u0435\u0439\u0449\u0438\u043a", + "wale", + "\u043f\u043e\u043b\u0438\u043e\u0432\u0438\u0440\u0443\u0441", + "\u043f\u0440\u043e\u0433\u043e\u043b\u043e\u0434\u0430\u0442\u044c\u0441\u044f", + "\u0438\u043d\u0441\u0443\u043b\u044c\u0442", + "\u0438\u0437\u0432\u0435\u0440\u0436\u0435\u043d\u0438\u0435", + "\u043f\u0430\u043b\u0438\u0442\u044c", + "\u0438\u043c\u043c\u0443\u043d\u043e\u0434\u0435\u0444\u0438\u0446\u0438\u0442", + "\u043a\u043e\u043d\u0442\u0443\u0437\u0438\u044f", + "\u0434\u0430\u0432\u0438\u0442\u044c\u0441\u044f", + "\u0444\u0438\u043b\u0438\u0441\u0442\u0435\u0440\u0441\u0442\u0432\u043e", + "\u0431\u0435\u043b\u043e\u043a\u0440\u043e\u0432\u0438\u0435", + "gimp", + "\u0441\u043a\u0430\u0440\u043b\u0430\u0442\u0438\u043d\u0430", + "\u043b\u0438\u0441\u0442\u0435\u0440\u0438\u043e\u0437", + "\u0433\u0435\u0440\u043c\u0430\u0444\u0440\u043e\u0434\u0438\u0442\u0438\u0437\u043c", + "\u043d\u043e\u0432\u043e\u043e\u0431\u0440\u0430\u0437\u043e\u0432\u0430\u043d\u0438\u0435", + "\u0433\u043e\u0440\u0431", + "\u043f\u043e\u043b\u0438\u043e\u043c\u0438\u0435\u043b\u0438\u0442", + "smart", + "\u0430\u043a\u0442\u0438\u043d\u043e\u043c\u0438\u043a\u043e\u0437", + "ed", + "\u043f\u0435\u0440\u0435\u043a\u043e\u0441", + "\u043e\u0441\u043d\u043e\u0432\u0430\u0442\u0435\u043b\u044c", + "\u0441\u043a\u043e\u0442\u043e\u043c\u0430", + "\u0432\u0438\u0440\u0443\u0441_\u0432\u0435\u0442\u0440\u044f\u043d\u043e\u0439_\u043e\u0441\u043f\u044b", + "sensation", + "\u0432\u0438\u0440\u0443\u0441_\u043f\u0440\u043e\u0441\u0442\u043e\u0433\u043e_\u0433\u0435\u0440\u043f\u0435\u0441\u0430_\u043f\u0435\u0440\u0432\u043e\u0433\u043e_\u0442\u0438\u043f\u0430", + "pain", + "\u0440\u0430\u0434\u0438\u043a\u0443\u043b\u0438\u0442", + "\u043f\u0440\u0435\u043f\u044f\u0442\u0441\u0442\u0432\u043e\u0432\u0430\u043d\u0438\u0435", + "\u0432\u0438\u0440\u0443\u0441_\u044d\u0431\u043e\u043b\u0430", + "\u043f\u0430\u043f\u0438\u043b\u043b\u043e\u043c\u0430", + "\u0440\u0435\u0437\u0430\u043d\u044b\u0439", + "\u0433\u0430\u043b\u0430\u043a\u0442\u043e\u0437\u0435\u043c\u0438\u044f", + "\u043c\u0430\u0440\u0430\u0437\u043c", + "\u043f\u043e\u043b\u0438\u0434\u0430\u043a\u0442\u0438\u043b\u0438\u044f", + "\u043a\u043e\u0440\u043e\u0431\u0438\u0442\u044c", + "\u043f\u043b\u0430\u0432\u0438\u043b\u044c\u0449\u0438\u043a", + "\u043f\u043e\u0433\u043b\u0430\u0434\u0438\u0442\u044c", + "\u043d\u0435\u043f\u043e\u0440\u044f\u0434\u043e\u043a", + "aura", + "\u043f\u0443\u0441\u0442\u0443\u043b\u0430", + "the_bleeding", + "\u043f\u0440\u0435\u0441\u0431\u0438\u043e\u043f\u0438\u044f", + "\u0440\u043e\u0442\u0430\u0432\u0438\u0440\u0443\u0441", + "\u043d\u0430\u0440\u0435\u0437\u0430\u043d\u044b\u0439", + "\u043f\u043e\u0433\u043b\u0430\u0436\u0438\u0432\u0430\u043d\u0438\u0435", + "\u043f\u043e\u043a\u0440\u0430\u0441\u043d\u0435\u043d\u0438\u0435", + "\u0444\u0438\u0442\u043e\u0444\u0442\u043e\u0440\u043e\u0437", + "\u043f\u0430\u0440\u043a\u0438\u043d\u0441\u043e\u043d", + "the_hives", + "\u043f\u043e\u0447\u0435\u0441\u0443\u0445\u0430", + "\u043f\u043e\u043b\u0438\u043f", + "\u0431\u0443\u0440\u0441\u0438\u0442", + "\u0432\u043e\u0441\u043f\u0430\u043b\u0435\u043d\u0438\u0435" + ], + "LAW": [ + "non_bis_in_idem", + "\u0440\u0438\u043c\u0441\u043a\u043e\u0435_\u043f\u0440\u0430\u0432\u043e", + "\u0433\u0440\u0430\u0436\u0434\u0430\u043d\u0441\u043a\u043e\u0435_\u043f\u0440\u0430\u0432\u043e", + "\u043f\u0440\u0430\u0432\u043e\u043f\u0440\u0438\u043c\u0435\u043d\u0435\u043d\u0438\u0435", + "\u043d\u0435_\u0434\u0432\u0430\u0436\u0434\u044b_\u0437\u0430_\u043e\u0434\u043d\u043e_\u0438_\u0442\u043e_\u0436\u0435", + "\u0432\u0435\u0440\u0445\u043e\u0432\u043d\u044b\u0439_\u0441\u0443\u0434" + ], + "PLANT": [ + "\u0437\u0435\u043c\u043b\u0438\u0441\u0442\u044b\u0439", + "\u0433\u0443\u0430\u0439\u044f\u0432\u0430", + "\u043d\u0435\u0437\u0430\u0431\u0443\u0434\u043a\u0430", + "the_joshua_tree", + "\u043a\u0440\u0430\u043f\u0438\u0432\u0430", + "\u043a\u043e\u0437\u0435\u043b\u0435\u0446_\u0438\u0441\u043f\u0430\u043d\u0441\u043a\u0438\u0439", + "\u043b\u0438\u043c\u043e\u043d\u043d\u0438\u043a", + "\u043b\u0438\u0441\u0442\u0432\u0435\u043d\u043d\u0438\u0446\u0430", + "\u043b\u0430\u0432\u0440\u043e\u0432\u0438\u0448\u043d\u044f", + "candida_albicans", + "\u0430\u0440\u0438\u0441\u0442\u043e\u043b\u043e\u0445\u0438\u044f", + "\u0432\u0430\u043b\u043b\u0438\u0441\u043d\u0435\u0440\u0438\u044f", + "\u0441\u0432\u044f\u0442\u0430\u044f_\u043c\u0430\u0440\u0438\u044f", + "\u043a\u043e\u043a\u043e\u0440\u044b\u0448", + "\u043c\u043e\u043a\u0440\u0438\u0447\u043d\u0438\u043a", + "\u043d\u0438\u043c", + "\u043a\u043b\u044e\u043a\u0432\u0430", + "\u0431\u0435\u043b\u043b\u0430\u0434\u043e\u043d\u043d\u0430", + "\u0442\u0443\u0440\u0443\u0445\u0442\u0430\u043d", + "blackberry", + "\u0447\u0435\u0440\u0438\u043c\u043e\u0439\u044f", + "\u0433\u0435\u0432\u0435\u044f_\u0431\u0440\u0430\u0437\u0438\u043b\u044c\u0441\u043a\u0430\u044f", + "\u0447\u0435\u0440\u043d\u0443\u0448\u043a\u0430", + "saccharomyces_cerevisiae", + "\u0440\u0430\u0444\u0438\u044f", + "\u043f\u0435\u0442\u0441\u0430\u0439", + "\u043d\u043e\u0432\u043e\u0433\u043e\u0434\u043d\u044f\u044f_\u0451\u043b\u043a\u0430", + "\u043c\u0430\u043d\u0438\u043e\u0442", + "\u0432\u0430\u0441\u0438\u043b\u0451\u043a_\u0430\u043c\u0435\u0440\u0438\u043a\u0430\u043d\u0441\u043a\u0438\u0439", + "\u0447\u0438\u0441\u0442\u044f\u043a", + "\u0440\u043e\u0436\u0434\u0435\u0441\u0442\u0432\u0435\u043d\u0441\u043a\u0430\u044f_\u0451\u043b\u043a\u0430", + "\u0431\u0430\u043a\u0430\u0439", + "\u0441\u043c\u043e\u043a\u0432\u0430", + "\u0440\u0430\u0441\u0442\u043e\u0440\u043e\u043f\u0448\u0430", + "\u044f\u0434\u043e\u0432\u0438\u0442\u044b\u0439_\u043f\u043b\u044e\u0449" + ], + "DATE": [ + "\u0432_\u043f\u0435\u0440\u0441\u043f\u0435\u043a\u0442\u0438\u0432\u0435", + "\u043f\u043e\u0441\u043b\u0435_\u0440\u043e\u0436\u0434\u0435\u0441\u0442\u0432\u0430_\u0445\u0440\u0438\u0441\u0442\u043e\u0432\u0430", + "dog_days", + "\u0441\u0440\u0435\u0434\u043d\u0435\u0432\u0435\u043a\u043e\u0432\u044c\u0435", + "\u043f\u043e\u0441\u043b\u0435\u0437\u0430\u0432\u0442\u0440\u0430", + "\u0442\u043e\u0442_\u0441\u0432\u0435\u0442", + "\u0434\u0432\u0435\u043d\u0430\u0434\u0446\u0430\u0442\u0430\u044f_\u043d\u043e\u0447\u044c", + "happy_hour", + "\u0432_\u044d\u0442\u0438_\u0434\u043d\u0438", + "\u043f\u043e\u043b\u0447\u0430\u0441\u0430", + "\u043d\u043e\u0432\u043e\u043b\u0443\u043d\u0438\u0435", + "\u0432_\u043f\u043e\u0441\u043b\u0435\u0434\u043d\u044e\u044e_\u043c\u0438\u043d\u0443\u0442\u0443", + "\u043d\u0430_\u0441\u043b\u0435\u0434\u0443\u044e\u0449\u0438\u0439_\u0434\u0435\u043d\u044c" + ], + "PERSON_PRONOUN": [ + "\u043c\u0435\u043d\u044f", + "i", + "\u0442\u0435\u0431\u044f", + "\u0432\u044b_\u0441\u0430\u043c\u0438", + "\u0432\u0430\u043c", + "\u0432\u044b" + ], + "RELIGION_MEMBER": [ + "guru", + "the_hindu", + "\u0431\u0435\u043d\u0435\u0434\u0438\u043a\u0442\u0438\u043d\u043a\u0430", + "\u043c\u0430\u0433\u043e\u043c\u0435\u0442\u0430\u043d\u0438\u043d", + "\u043f\u0440\u0435\u0441\u0432\u0438\u0442\u0435\u0440\u0438\u0430\u043d\u0441\u043a\u0438\u0439", + "\u0434\u043e\u043c\u0438\u043d\u0438\u043a\u0430\u043d\u043a\u0430", + "\u0430\u043d\u0433\u043b\u0438\u043a\u0430\u043d\u0441\u043a\u0438\u0439", + "\u0438\u0435\u0437\u0443\u0438\u0442", + "\u043c\u0435\u0442\u043e\u0434\u0438\u0441\u0442", + "\u043c\u0430\u0433\u043e\u043c\u0435\u0442\u0430\u043d\u043a\u0430", + "\u0434\u043e\u043c\u0438\u043d\u0438\u043a\u0430\u043d\u0435\u0446", + "\u0431\u0430\u043f\u0442\u0438\u0441\u0442\u0441\u043a\u0438\u0439", + "\u0444\u0440\u0430\u043d\u0446\u0438\u0441\u043a\u0430\u043d\u0446\u044b", + "\u0438\u0435\u0437\u0443\u0438\u0442\u043a\u0430", + "\u043c\u043e\u0440\u043c\u043e\u043d", + "\u0441\u0443\u043d\u043d\u0438\u0442\u0441\u043a\u0438\u0439", + "\u0440\u0438\u043c\u0441\u043a\u043e_\u043a\u0430\u0442\u043e\u043b\u0438\u0447\u0435\u0441\u043a\u0438\u0439", + "\u0431\u0435\u043d\u0435\u0434\u0438\u043a\u0442\u0438\u043d\u0435\u0446" + ], + "FOOD": [ + "\u0432\u043e\u043b\u043e\u0432\u0430\u043d", + "\u0441\u043e\u0443\u0441_\u0447\u0438\u043b\u0438", + "\u043e\u0441\u0442\u0440\u044b\u0439_\u0441\u043e\u0443\u0441", + "\u0444\u0440\u0430\u043d\u0446\u0443\u0437\u0441\u043a\u0438\u0439_\u0442\u043e\u0441\u0442", + "\u0431\u0435\u043b\u043e\u0433\u0432\u0430\u0440\u0434\u0435\u0435\u0446", + "\u043c\u043e\u0440\u043e\u0436\u0435\u043d\u043e\u0435_\u0441_\u0444\u0440\u0443\u043a\u0442\u0430\u043c\u0438", + "\u0433\u0430\u0437\u0438\u0440\u043e\u0432\u043a\u0430", + "\u043f\u0435\u0440\u0435\u043a\u0443\u0441", + "\u0430\u043d\u0442\u0440\u0435", + "\u0447\u0438\u043b\u0438_\u0441\u043e\u0443\u0441", + "\u043c\u043d\u0438\u0445\u0438", + "\u0431\u0438\u0444\u0448\u0442\u0435\u043a\u0441_\u0441_\u043a\u043e\u0441\u0442\u043e\u0447\u043a\u043e\u0439", + "\u0441\u0442\u0435\u0439\u043a_\u043d\u0430_\u043a\u043e\u0441\u0442\u043e\u0447\u043a\u0435", + "\u0441\u0443\u0445\u043e\u0444\u0440\u0443\u043a\u0442" + ], + "FAC": [ + "\u0431\u0435\u0437_\u0437\u0430\u0441\u0435\u0447\u0435\u043a", + "\u0438\u043e\u0441\u0438\u0444_\u043e\u0431\u0440\u0443\u0447\u043d\u0438\u043a", + "\u043a\u0430\u0442\u043e\u043b\u0438\u0447\u0435\u0441\u043a\u0430\u044f_\u0446\u0435\u0440\u043a\u043e\u0432\u044c", + "\u043c\u0435\u0434\u0438\u0446\u0438\u043d\u0441\u043a\u0438\u0439_\u0432\u0443\u0437", + "\u043d\u0438\u0436\u043d\u044f\u044f_\u043f\u0430\u043b\u0430\u0442\u0430", + "t_\u043b\u0438\u043c\u0444\u043e\u0446\u0438\u0442\u044b", + "\u043f\u0435\u0442\u0440\u043e\u043f\u0430\u0432\u043b\u043e\u0432\u0441\u043a", + "\u0433\u043b\u0430\u0432\u043f\u043e\u0447\u0442\u0430\u043c\u0442", + "\u0441\u0435\u043c\u0438\u043b\u0435\u0442\u043a\u0430", + "\u0448\u0451\u043d\u0431\u0435\u0440\u0433_\u0430\u0440\u043d\u043e\u043b\u044c\u0434", + "\u043a\u0430\u0440\u0442\u0438\u043d\u043d\u0430\u044f_\u0433\u0430\u043b\u0435\u0440\u0435\u044f", + "\u043f\u0430\u043d\u0441\u0438\u043e\u043d\u0430\u0442", + "\u043c\u0435\u0434\u0438\u0446\u0438\u043d\u0441\u043a\u043e\u0435_\u0443\u0447\u0438\u043b\u0438\u0449\u0435", + "\u0430\u0442\u0430\u043a\u0430\u043c\u0430", + "\u0440\u0438\u043c\u0441\u043a\u043e_\u043a\u0430\u0442\u043e\u043b\u0438\u0447\u0435\u0441\u043a\u0430\u044f_\u0446\u0435\u0440\u043a\u043e\u0432\u044c" + ], + "POLITICAL_PARTY": [ + "\u043b\u0438\u0431\u0435\u0440\u0430\u043b\u044c\u043d\u0430\u044f_\u043f\u0430\u0440\u0442\u0438\u044f", + "\u043a\u043e\u043d\u0441\u0435\u0440\u0432\u0430\u0442\u0438\u0432\u043d\u0430\u044f_\u043f\u0430\u0440\u0442\u0438\u044f", + "\u043d\u0430\u0446\u0438\u043e\u043d\u0430\u043b_\u0441\u043e\u0446\u0438\u0430\u043b\u0438\u0441\u0442\u0438\u0447\u0435\u0441\u043a\u0430\u044f_\u043d\u0435\u043c\u0435\u0446\u043a\u0430\u044f_\u0440\u0430\u0431\u043e\u0447\u0430\u044f_\u043f\u0430\u0440\u0442\u0438\u044f", + "\u043d\u0430\u0446\u0438\u043e\u043d\u0430\u043b\u044c\u043d\u0430\u044f_\u043f\u0430\u0440\u0442\u0438\u044f", + "\u043f\u0440\u043e\u0442\u0438\u0432\u043e\u0434\u0435\u0439\u0441\u0442\u0432\u0438\u0435", + "\u043d\u0430\u0440\u043e\u0434\u043d\u0430\u044f_\u043f\u0430\u0440\u0442\u0438\u044f", + "\u0440\u0435\u0441\u043f\u0443\u0431\u043b\u0438\u043a\u0430\u043d\u0441\u043a\u0430\u044f_\u043f\u0430\u0440\u0442\u0438\u044f", + "\u043b\u0438\u0431\u0435\u0440\u0430\u043b\u044c\u043d\u0430\u044f_\u043f\u0430\u0440\u0442\u0438\u044f_\u0432\u0435\u043b\u0438\u043a\u043e\u0431\u0440\u0438\u0442\u0430\u043d\u0438\u0438", + "\u0434\u0435\u043c\u043e\u043a\u0440\u0430\u0442\u0438\u0447\u0435\u0441\u043a\u043e_\u0440\u0435\u0441\u043f\u0443\u0431\u043b\u0438\u043a\u0430\u043d\u0441\u043a\u0430\u044f_\u043f\u0430\u0440\u0442\u0438\u044f", + "\u0441\u043e\u0446\u0438\u0430\u043b_\u0434\u0435\u043c\u043e\u043a\u0440\u0430\u0442\u0438\u0447\u0435\u0441\u043a\u0430\u044f_\u043f\u0430\u0440\u0442\u0438\u044f", + "\u043a\u043e\u043d\u0441\u0435\u0440\u0432\u0430\u0442\u0438\u0432\u043d\u0430\u044f_\u043f\u0430\u0440\u0442\u0438\u044f_\u0432\u0435\u043b\u0438\u043a\u043e\u0431\u0440\u0438\u0442\u0430\u043d\u0438\u0438", + "\u0431\u0435\u043b\u043e\u0440\u0443\u0441\u0441\u043a\u0430\u044f_\u0430\u0433\u0440\u0430\u0440\u043d\u0430\u044f_\u043f\u0430\u0440\u0442\u0438\u044f", + "\u0441\u043e\u0446\u0438\u0430\u043b_\u0434\u0435\u043c\u043e\u043a\u0440\u0430\u0442\u0438\u0447\u0435\u0441\u043a\u0430\u044f_\u043f\u0430\u0440\u0442\u0438\u044f_\u0430\u043d\u0434\u043e\u0440\u0440\u044b", + "\u043d\u043e\u0440\u0432\u0435\u0436\u0441\u043a\u0430\u044f_\u0440\u0430\u0431\u043e\u0447\u0430\u044f_\u043f\u0430\u0440\u0442\u0438\u044f", + "\u043a\u043e\u043c\u043c\u0443\u043d\u0438\u0441\u0442\u0438\u0447\u0435\u0441\u043a\u0430\u044f_\u043f\u0430\u0440\u0442\u0438\u044f", + "\u043f\u0430\u0440\u0442\u0438\u044f_\u0432\u0438\u0433\u043e\u0432" + ], + "SOC_ECO_CLASS": [ + "\u0430\u0433\u0440\u043e\u043a\u0443\u043b\u044c\u0442\u0443\u0440\u0430", + "\u0441\u043e\u0446\u0438\u0443\u043c", + "\u0434\u0435\u043c\u0438\u043c\u043e\u043d\u0434\u0435\u043d\u043a\u0438", + "\u043f\u043e\u043b\u0443\u0441\u0432\u0435\u0442", + "\u0444\u0435\u0440\u043c\u0435\u0440\u0441\u0442\u0432\u043e", + "\u043c\u0435\u043b\u043a\u0430\u044f_\u0431\u0443\u0440\u0436\u0443\u0430\u0437\u0438\u044f", + "\u0444\u0438\u043b\u0438\u0441\u0442\u0435\u0440\u0441\u0442\u0432\u043e", + "\u043f\u0440\u043e\u0441\u0442\u043e\u043b\u044e\u0434\u0438\u043d\u044b" + ], + "RACE": [ + "\u0444\u0438\u043b\u0438\u043f\u0438\u043d\u043e", + "\u0435\u0432\u0440\u043e\u043f\u0435\u0439\u0441\u043a\u0438\u0439", + "\u043b\u0430\u0442\u0438\u043d\u043e\u0441\u043a\u0430", + "\u0430\u0432\u0442\u043e\u0445\u0442\u043e\u043d", + "\u0432\u043e\u0441\u0442\u043e\u0447\u043d\u043e\u0430\u0437\u0438\u0430\u0442\u0441\u043a\u0438\u0439", + "\u043b\u0430\u0442\u0438\u043d\u043e\u0430\u043c\u0435\u0440\u0438\u043a\u0430\u043d\u0435\u0446", + "\u0438\u0443\u0434\u0435\u0439\u0441\u043a\u0438\u0439", + "\u043b\u0430\u0442\u0438\u043d\u043e\u0430\u043c\u0435\u0440\u0438\u043a\u0430\u043d\u043a\u0430", + "\u0430\u0444\u0440\u0438\u043a\u0430\u043d\u0441\u043a\u0438\u0439", + "\u043b\u0430\u0442\u0438\u043d\u043e\u0441" + ], + "GPE": [ + "\u0441\u0432\u044f\u0442\u043e\u0439_\u043d\u0438\u043a\u043e\u043b\u0430\u0439", + "\u0432\u0430\u0440\u0432\u0430\u0440\u0430_\u0438\u043b\u0438\u043e\u043f\u043e\u043b\u044c\u0441\u043a\u0430\u044f", + "\u0434\u0430\u0440_\u044d\u0441_\u0441\u0430\u043b\u0430\u043c", + "\u0433\u0435\u0440\u043c\u0430\u043d\u0441\u043a\u0430\u044f_\u0438\u043c\u043f\u0435\u0440\u0438\u044f", + "\u0441\u0432\u044f\u0442\u043e\u0439_\u0445\u0440\u0438\u0441\u0442\u043e\u0444\u043e\u0440", + "\u0441\u0432\u044f\u0442\u043e\u0439_\u0434\u0443\u0445", + "\u0441\u0432\u044f\u0442\u043e\u0439_\u0433\u0435\u043e\u0440\u0433\u0438\u0439", + "\u0431\u043e\u0433\u043e\u043c\u0430\u0442\u0435\u0440\u044c", + "\u043a\u0430\u043c\u043f\u043e\u043d\u0433\u0442\u044f\u043c", + "\u0447\u0438\u0430\u043d\u0433\u0440\u0430\u0439", + "\u0441\u0435\u043d\u0442_\u043b\u0443\u0438\u0441", + "\u0442\u0430\u0439\u0448\u0430\u043d\u044c", + "\u0441\u043e\u0431\u043e\u0440_\u0441\u0432\u044f\u0442\u043e\u0439_\u0441\u043e\u0444\u0438\u0438", + "\u043d\u0438\u043a\u043e\u043b\u0430\u0439_\u0447\u0443\u0434\u043e\u0442\u0432\u043e\u0440\u0435\u0446", + "\u0441\u0430\u043d_\u0442\u043e\u043c\u0435", + "\u043a\u0440\u0430\u0441\u043d\u044b\u0439_\u043a\u0440\u0435\u0441\u0442" + ], + "QUANTITY": [ + "\u043a\u0430\u043b\u043e\u0440\u0438\u044f", + "\u0442\u0440\u0438_\u0437\u0430\u043a\u043e\u043d\u0430_\u0440\u043e\u0431\u043e\u0442\u0435\u0445\u043d\u0438\u043a\u0438", + "\u0442\u0440\u0438_\u0441\u0435\u0441\u0442\u0440\u044b", + "\u0446\u0435\u043b\u044c\u0441\u0438\u0439_\u0430\u043d\u0434\u0435\u0440\u0441", + "\u0432\u0441\u0435\u043e\u0445\u0432\u0430\u0442\u044b\u0432\u0430\u044e\u0449\u0438\u0439", + "\u0430\u0432\u0442\u043e\u0441\u0442\u043e\u044f\u043d\u043a\u0430", + "g", + "\u0442\u0440\u0438_\u0430\u043c\u0438\u0433\u043e", + "\u0442\u0440\u0438_\u0447\u0435\u0442\u0432\u0435\u0440\u0442\u0438", + "\u0441\u0442\u0435\u0440\u043b\u0438\u043d\u0433", + "\u044d\u043f\u043e\u0445\u0430_\u0442\u0440\u043e\u0435\u0446\u0430\u0440\u0441\u0442\u0432\u0438\u044f", + "\u0442\u0440\u0451\u0445\u043c\u0435\u0440\u043d\u044b\u0439" + ], + "BIO_CHEM_ENTITY": [ + "\u043c\u043e\u043d\u043e\u0430\u043c\u0438\u043d\u043e\u043a\u0441\u0438\u0434\u0430\u0437\u0430", + "\u043f\u043e\u043b\u0438\u043b\u0430\u043a\u0442\u0438\u0434", + "c_\u0440\u0435\u0430\u043a\u0442\u0438\u0432\u043d\u044b\u0439_\u0431\u0435\u043b\u043e\u043a", + "\u043f\u043e\u043b\u0438\u0432\u0438\u043d\u0438\u043b\u0445\u043b\u043e\u0440\u0438\u0434", + "\u0430\u0434\u0435\u043d\u043e\u0437\u0438\u043d\u0434\u0438\u0444\u043e\u0441\u0444\u0430\u0442" + ], + "RELIGION": [ + "\u043a\u0430\u0442\u0430\u0440\u044b", + "\u0434\u0430\u043e\u0441\u0438\u0437\u043c" + ], + "PERSON": [ + "\u043d\u0438_\u043d\u0438", + "\u0441\u0435\u043d_\u0431\u0430\u0440\u0442\u0435\u043b\u0435\u043c\u0438", + "st_vincent", + "\u043f\u0440\u0438_\u043f\u043e\u043c\u043e\u0449\u0438", + "\u043a_\u0434\u0440\u0430\u043c\u0430", + "\u044f_\u0442\u043e\u0436\u0435", + "\u0438_\u0446\u0437\u0438\u043d", + "\u044f_\u0442\u0430\u043a\u0436\u0435", + "\u0431\u0440\u043e\u043d\u0435\u0442\u0440\u0430\u043d\u0441\u043f\u043e\u0440\u0442\u0451\u0440", + "\u0441\u0435\u043d\u0442_\u0432\u0438\u043d\u0441\u0435\u043d\u0442" + ], + "GENDER": [ + "\u043c\u0430\u0442\u0440\u043e\u043d\u0430", + "\u0431\u0438\u0441\u0435\u043a\u0441\u0443\u0430\u043b\u044c\u043d\u044b\u0439" + ], + "POLITICAL_PARTY_MEMBER": [ + "\u043a\u043e\u043c\u043c\u0443\u043d\u0438\u0441\u0442\u0438\u0447\u0435\u0441\u043a\u0438\u0439", + "\u0431\u043e\u043b\u044c\u0448\u0435\u0432\u0438\u043a" + ], + "UNION": [ + "\u043f\u0440\u043e\u0444\u0441\u043e\u044e\u0437", + "\u043c\u0435\u0436\u0434\u0443\u043d\u0430\u0440\u043e\u0434\u043d\u044b\u0439_\u0441\u043e\u044e\u0437_\u044d\u043b\u0435\u043a\u0442\u0440\u043e\u0441\u0432\u044f\u0437\u0438", + "\u0441\u0442\u0443\u0434\u0435\u043d\u0447\u0435\u0441\u043a\u043e\u0435_\u0441\u0430\u043c\u043e\u0443\u043f\u0440\u0430\u0432\u043b\u0435\u043d\u0438\u0435", + "\u0442\u0440\u0435\u0434_\u044e\u043d\u0438\u043e\u043d" + ], + "ner_regexes": [ + [ + "PERSON", + "\\D+ \\D+ \\D+|\\D+ \\D+ \\D+|\\D+ \\D+ \\D+ \\D+|\\D+ \\D+ \\D+|\\D+ \\D+ \\D+|\\D+ \\D+ \\D+ \\D+", + false, + [] + ] + ], + "FIRST_NAME_FEMALE": [ + "\u0435\u0432\u0434\u043e\u043a\u0438\u044f", + "\u0437\u0438\u043d\u0430\u0438\u0434\u0430", + "\u0432\u0430\u0441\u0438\u043b\u0438\u0441\u0430", + "\u043f\u0440\u0430\u0441\u043a\u043e\u0432\u044c\u044f", + "\u0432\u0435\u0440\u043e\u043d\u0438\u043a\u0430", + "\u0442\u0430\u0442\u044c\u044f\u043d\u0430", + "\u0440\u0430\u0438\u0441\u0430", + "\u043a\u0438\u0440\u0430", + "\u043e\u043a\u0441\u0430\u043d\u0430", + "\u043b\u0430\u0440\u0438\u0441\u0430", + "\u044d\u043b\u0435\u043e\u043d\u043e\u0440\u0430", + "\u043b\u043e\u0440\u0430", + "\u0437\u043e\u044f", + "\u0435\u043a\u0430\u0442\u0435\u0440\u0438\u043d\u0430", + "\u043b\u0443\u043a\u0438\u044f", + "\u0444\u0430\u0438\u043d\u0430", + "\u043c\u0430\u0440\u0444\u0430", + "\u0433\u0430\u043b\u0438\u043d\u0430", + "\u0433\u043b\u0430\u0444\u0438\u0440\u0430", + "\u0430\u043d\u043d\u0430", + "\u0430\u043b\u0435\u043a\u0441\u0430\u043d\u0434\u0440\u0430", + "\u0442\u0430\u043c\u0430\u0440\u0430", + "\u0432\u0435\u0440\u0430", + "\u043d\u0430\u0442\u0430\u043b\u044c\u044f", + "\u0435\u0432\u0433\u0435\u043d\u0438\u044f", + "\u0432\u0430\u043b\u0435\u043d\u0442\u0438\u043d\u0430", + "\u043c\u0430\u0440\u0438\u043d\u0430", + "\u043f\u0435\u043b\u0430\u0433\u0435\u044f", + "\u043c\u0438\u043b\u0438\u0446\u0430", + "\u043d\u0430\u0434\u0435\u0436\u0434\u0430", + "\u0435\u043b\u0435\u043d\u0430", + "\u0444\u0451\u043a\u043b\u0430", + "\u0430\u043d\u0436\u0435\u043b\u0438\u043a\u0430", + "\u0444\u0435\u0432\u0440\u043e\u043d\u0438\u044f", + "\u0438\u0440\u0438\u043d\u0430", + "\u0430\u043d\u0433\u0435\u043b\u0438\u043d\u0430", + "\u0435\u0432\u043f\u0440\u0430\u043a\u0441\u0438\u044f", + "\u0438\u0440\u0430\u0438\u0434\u0430", + "\u0430\u043d\u0430\u0441\u0442\u0430\u0441\u0438\u044f", + "\u0432\u0438\u043a\u0442\u043e\u0440\u0438\u044f", + "\u043b\u0438\u0434\u0438\u044f", + "\u0434\u0430\u0440\u044c\u044f", + "\u043e\u043b\u0438\u043c\u043f\u0438\u0430\u0434\u0430", + "\u0430\u0433\u0430\u0444\u044c\u044f", + "\u0430\u043d\u0442\u043e\u043d\u0438\u043d\u0430", + "\u0430\u043d\u0436\u0435\u043b\u0430", + "\u043d\u0438\u043d\u0430", + "\u0430\u043b\u043b\u0430", + "\u0441\u0432\u0435\u0442\u043b\u0430\u043d\u0430", + "\u0438\u0432\u0430\u043d\u043d\u0430", + "\u043e\u043a\u0442\u044f\u0431\u0440\u0438\u043d\u0430", + "\u043b\u044e\u0434\u043c\u0438\u043b\u0430", + "\u0441\u0438\u043d\u043a\u043b\u0438\u0442\u0438\u043a\u0438\u044f", + "\u043d\u043e\u043d\u043d\u0430", + "\u0435\u0432\u0444\u0440\u043e\u0441\u0438\u043d\u0438\u044f", + 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"colvu", + "tilibriu", + "giacu", + "linci", + "bucchemeli", + "malabiga", + "corbu", + "bentruxiu", + "tapp\u00e0iu", + "castorru", + "schirri", + "crabolu", + "curturzu", + "furittu", + "intulzu", + "boiamericanu", + "sulone", + "cirolitta", + "intruxu", + "iscoj\u00e0ttulu", + "gattu", + "caboniscu", + "gard\u00f9bbulu", + "corronca", + "istr\u00eca", + "porcrabu", + "card\u00f9bbulu", + "guntorzu", + "magliocchina", + "chervu", + "guntruxu", + "crebu", + "picchiaranzu", + "cherbu", + "lintze", + "isbirru", + "astoreddu", + "istambeccu", + "corrancra", + "meurra" + ], + "PUBLIC_FIGURE": [ + "sperai", + "pedru", + "e", + "citiri", + "o", + "gregoriu", + "predu" + ], + "TITLE": [ + "sannori", + "sennore" + ], + "JOB": [ + "cabraxu", + "datori", + "crabarzu", + "crab\u00e0giu", + "crabalzu", + "isclavu", + "cabr\u00e0rgiu", + "sciau", + "cardareri" + ], + "PLANT": [ + "frustinaca", + "saliche", + "saighi", + "fostinaja", + "sagili", + "sabixi", + "lattuca" + ], + "PERSON_PRONOUN": [ + "noltru", + "noso" + ], + "ORG": [ + "studai", + "ai", + "guvernu", + "cuverrinu", + "cabu_birde", + "i_ching", + "cuberru", + "isciola", + "scola" + ], + "LANGUAGE": [ + "atzentu" + ], + "FOOD": [ + "benz\u00eda", + "ghingh\u00eda" + ], + "LOCATION": [ + "campile", + "arena", + "campu" + ], + "PERSON": [ + "i_ching" + ], + "GENDER": [ + "male", + "mascu", + "mascru" + ], + "RELIGION": [ + "islam" + ], + "PRODUCT": [ + "c\u00e0via" + ], + "FAC": [ + "isparadorzu" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "sorre": "fr\u00e0de", + "umbu": "fr\u00e0de", + "sorri": "fr\u00e0de", + "mutzere": "madiru", + "mulleri": "madiru", + "mugere": "madiru", + "mullei": "madiru", + "muzere": "madiru" + }, + "other_gender_swap": {}, + "en_pronoun2gender": { + "he": [ + "male", + "mascru", + "mascu", + "m\u00e0sciu", + "m\u00e0schiu" + ], + "she": [ + "d\u00f2na", + "perdere" + ] + }, + "en_pronoun2pronoun": { + "he": [ + "sese" + ], + "she": [ + "sese" + ], + "it": [ + "issu", + "chistu", + "sese" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/scn.json b/data_tooling/pii_processing/ontology/data/scn.json new file mode 100644 index 0000000..d1dd0f2 --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/scn.json @@ -0,0 +1,437 @@ +{ + "JOB": [ + "agriculturi", + "pinturi", + "carciareri", + "ruluggiaru", + "don", + "mandriotu", + "scinzatu", + "carabbineri", + "parrucchieri", + "casciuni", + "picuraru", + "lattaru", + "pasturi", + "the_guardian", + "funtaneri", + "mastru_muraturi", + "varveri", + "kamikazi", + "cartellu", + "travagghiaturi", + "spizziali", + "schiavu", + "capraru", + "maistru", + "maggiurdomu", + "libbraru" + ], + "DISEASE": [ + "culera", + "foddira", + "gumma", + "sigliuzzu", + "sigghiuzzu", + "pitinia", + "mouse", + "cacaredda", + "murr\u00f2iti", + "tubbirculosi", + "fami", + "poliomil\u00ecti", + "chiaia", + "firita", + "dogghia", + "stranutari", + "firtilitati", + "ruluri", + "chi", + "malancun\u00eca", + "firnic\u00eca", + "patulugg\u00eca", + "rach\u00ectidi", + "prinizza", + "pesti_bubb\u00f2nica", + "cummursioni", + "risibbella", + "vunciuni", + "affizzioni", + "muzzicari", + "dissintir\u00eca", + "canigghiola", + "andicappi", + "cravunchiu", + "caddu", + "firrun\u00eca", + "lebbra", + "ruttura", + "malaria" + ], + "LAW": [ + "drittu_rumanu" + ], + "GPE": [ + "mari_russu", + "dar_es_salaam", + "mari_eggeu", + "casa_janca", + "novu_tistamentu" + ], + "PUBLIC_FIGURE": [ + "johann_bernoulli", + "don_chisciotti", + "che_guevara", + "georges_simenon", + "maria_callas", + "mary_shelley", + "giuseppi_mazzini", + "john_herschel", + "andrzej_wajda", + "mary_wollstonecraft", + "winston_churchill", + "paul_mccartney", + "isaac_newton", + "victor_hugo", + "edwin_hubble", + "george_harrison", + "george_orwell", + "richard_wagner", + "marie_curie", + "gaetanu_donizzetti", + "michael_jackson", + "thomas_hobbes", + "edmund_hillary", + "vincent_van_gogh", + "luiggi_pirandellu", + "massimianu", + "mau_zitung", + "ciciruni", + "yuri_gagarin", + "e", + "catarina", + "frank_sinatra", + "rubertu", + "henri_becquerel", + "henri_matisse", + "louis_pasteur", + "albertu_giacumetti", + "gertrude_stein", + "griguori", + "charles_de_gaulle", + "giuseppi_verdi", + "charles_lindbergh", + "f", + "ludwig_wittgenstein", + "samuel_de_champlain", + "spiranza", + "robert_johnson", + "andrea_mantegna", + "oscar_wilde", + "grigoriu", + "james_brown", + "charles_baudelaire", + "charlie_parker", + "immanuel_kant", + "carlu", + "giulio_natta", + "johannes_kepler", + "jacobbi", + "sarah_siddons", + "canberra", + "oliver_hardy", + "jean_luc_godard", + "william_herschel", + "bertrand_russell", + "michael_faraday", + "walt_disney", + "vicenzu_bellini", + "friedrich_engels", + "wolfgang_pauli", + "petru", + "galileu_galilei", + "george_gershwin", + "alfred_nobel", + "jesse_owens", + "marcel_marceau", + "daniel_bernoulli", + "gottfried_leibniz", + "christiaan_huygens", + "adam_smith", + "william_james", + "henry_miller", + "karl_marx", + "friedrich_nietzsche", + "i", + "nikola_tesla", + "robert_schumann", + "le_corbusier", + "john_locke", + "ingrid_bergman", + "jean_piaget", + "arricu", + "valentina_tereshkova", + "titu", + "carl_jung", + "adolf_hitler", + "vladimir_putin", + "san_giorgiu", + "g", + "arthur_schopenhauer", + "r", + "andrew_jackson", + "louis_armstrong", + "alexandre_dumas", + "johann_gutenberg", + "giambattista_marino", + "san_petru_apostulu", + "putin", + "karl_popper", + "sandru_botticelli", + "peter_sellers", + "peter_paul_rubens", + "mahatma_gandhi", + "john_lennon", + "charlie_chaplin", + "brescia", + "miles_davis", + "saladinu", + "giuseppi_garibbaldi", + "stanley_kubrick", + "maria_antonietta", + "ronald_reagan", + "martin_luther_king", + "amerigu_vespucci", + "frank_capra", + "woodrow_wilson", + "danti_alighieri", + "ernest_hemingway", + "nelson_mandela", + "roald_amundsen", + "charles_dickens", + "ella_fitzgerald", + "jacques_offenbach", + "giuseppi_stalin", + "francisco_franco", + "pietru_lu_granni", + "vladimir_lenin", + "albert_einstein", + "crist\u00f2furu_culommu", + "t" + ], + "ORG": [ + "shintuismu", + "nasa", + "cuvernu", + "illuminismu", + "astutari", + "andr\u00f2mida", + "cuviernu", + "sennu", + "gao", + "capu_virdi", + "guvernu", + "mari_russu", + "chiesa_catt\u00f2lica_rumana", + "muratura", + "partitu_dimucr\u00e0ticu", + "po", + "capitinci", + "nicu", + "tauismu", + "los_angeles", + "nato", + "stasira", + "sucialdimucrazz\u00eca", + "miruvinci", + "scola", + "isercitu_statunitenzi" + ], + "PRODUCT": [ + "justin_bieber", + "corpu_cilesti", + "santa_mar\u00eca", + "dritti_umani" + ], + "UNION": [ + "itu" + ], + "ANIMAL": [ + "virus_a_mos\u00e0icu_d\u00f4_tabbaccu", + "gurilla", + "craccarazza", + "carcarazza", + "sumeri", + "petturrussu", + "jaddina", + "linci", + "corbu", + "rinninuni", + "cervu", + "lebbru", + "gattu", + "sumaro", + "cigniali", + "donald_duck", + "card\u00f9bbulu", + "spriveri", + "arthropoda", + "furami", + "cacciaventu" + ], + "QUANTITY": [ + "dollaru", + "g" + ], + "POLITICAL_PARTY": [ + "partitu_cumunista", + "partitu_sucialista", + "partitu_virdi", + "partitu_ripubbricanu", + "partitu_pul\u00ecticu" + ], + "FOOD": [ + "sangunazzu", + "daucus_carota", + "cicompa", + "farina", + "pisciu\u00f2vu", + "jilatu", + "disertu", + "gingili", + "agghiacciamentu", + "juglans_regia", + "cincili" + ], + "PLANT": [ + "laurus_nobilis", + "helianthus_annuus", + "crisantemu", + "lurdica", + "furricu", + "furd\u00eccula", + "prunus_armeniaca", + "cirasa", + "ciaca", + "castagnu", + "nicotiana_tabacum", + "milucuccu", + "urtica_dioica", + "sipala", + "beta_vulgaris", + "pinnacchiu", + "sambucus_ebulus", + "pignu", + "lattuca" + ], + "RELIGION": [ + "salafismu", + "calvinismu", + "tauismu", + "islam", + "shintuismu" + ], + "PERSON_PRONOUN": [ + "i" + ], + "GENDER": [ + "picciriddu", + "carusa", + "carusu" + ], + "PERSON": [ + "gioconda", + "ascurbatu" + ], + "LANGUAGE": [ + "francupruvinzali", + "esperantu", + "arbanisi", + "purtughisi", + "tonga" + ], + "SOC_ECO_CLASS": [ + "sucitati" + ], + "RELIGION_MEMBER": [ + "mussurmanu", + "parsi" + ], + "FAC": [ + "stasira", + "san_giuseppi", + "santa_lucia" + ], + "LOCATION": [ + "sri_lanka", + "the_rolling_stones", + "visuviu", + "campu" + ], + "DATE": [ + "mediuevu" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "matri": "babbu", + "soru": "frati", + "riggina": "reghi", + "rigina": "reghi", + "idda": "iddu", + "v\u00ecduva": "v\u00ecduu", + "v\u00ecdua": "v\u00ecduvu", + "mugghieri": "maritu", + "f\u00ecmmina": "omu", + "picciriddu": "carusa", + "picciottu": "carusa", + "carusu": "carusa" + }, + "other_gender_swap": { + "idde": "idda", + "iddi": "idda", + "iddu": "idde", + "idda": "iddi" + }, + "en_pronoun2gender": { + "he": [ + "omu", + "m\u00e0sculu", + "picciriddu", + "carusu", + "picciottu" + ], + "she": [ + "carusa", + "f\u00ecmmina" + ] + }, + "en_pronoun2pronoun": { + "he": [ + "iddu" + ], + "she": [ + "idda" + ], + "they": [ + "idde", + "iddi" + ], + "it": [ + "issu", + "chistu", + "chista", + "stu" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/sco.json b/data_tooling/pii_processing/ontology/data/sco.json new file mode 100644 index 0000000..aca2c13 --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/sco.json @@ -0,0 +1,587 @@ +{ + "FOOD": [ + "skoosh", + "desert", + "chuggie", + "het_chocolate", + "disjune", + "capsicum", + "sodium_chloride", + "chile", + "green_tea", + "brakfast", + "dessert", + "coffee", + "omelette", + "juglans_regia" + ], + "SOC_ECO_CLASS": [ + "trade", + "agricultur", + "samurai", + "society", + "caste", + "cream" + ], + "PUBLIC_FIGURE": [ + "gregor", + "benjamin_franklin", + "akira_kurosawa", + "john_knox", + "che_guevara", + "c", + "henrik_ibsen", + "david_livingstone", + "john_herschel", + "andrzej_wajda", + "jan_van_eyck", + "richard_burton", + "mary_wollstonecraft", + "winston_churchill", + "johannes_diderik_van_der_waals", + "karl_landsteiner", + "josephus", + "paul_mccartney", + "terry_pratchett", + "isaac_newton", + "edward_gibbon", + "richard_wagner", + "williams", + "marie_curie", + "griogair", + "michael_jackson", + "carl_sandburg", + "thomas_hobbes", + "david", + "galileo_galilei", + "jane_goodall", + "chaim_weizmann", + "i_m_pei", + "joseph_goebbels", + "edmund_hillary", + "vincent_van_gogh", + "anne_boleyn", + "robert_burns", + "inca_empire", + "emiliano_zapata", + "yuri_gagarin", + "marie_antoinette", + "giuseppe_verdi", + "gottlieb_daimler", + "abel_tasman", + "katharine_hepburn", + "henri_becquerel", + "louis_pasteur", + "theodosius_i", + "saladin", + "sarah_bernhardt", + "charles_de_gaulle", + "ilk", + "y", + "holden", + "joseph_stalin", + "f", + "john_jay", + "ludwig_wittgenstein", + "august_strindberg", + "dante_alighieri", + "giacomo_puccini", + "fridtjof_nansen", + "benedict_arnold", + "nicolas_poussin", + "oscar_wilde", + "laurence_olivier", + "pete_seeger", + "a", + "jaucob", + "charles_baudelaire", + "immanuel_kant", + "titus", + "johannes_kepler", + "max_planck", + "william_blake", + "julio_iglesias", + "carl_lewis", + "canberra", + "edward_jenner", + "maist", + "william_herschel", + "montesquieu", + "niels_bohr", + "sergei_rachmaninoff", + "bertrand_russell", + "michael_faraday", + "jan_tinbergen", + "walt_disney", + "peter", + "friedrich_engels", + "moses", + "ian_fleming", + "richard_feynman", + "wolfgang_pauli", + "theodor_mommsen", + "elizabeth_taylor", + "indira_gandhi", + "jane_seymour", + "george_gershwin", + "alfred_nobel", + "marco_polo", + "caravaggio", + "gottfried_leibniz", + "catherine_howard", + "hans_christian_andersen", + "cary_grant", + "pieter_zeeman", + "pablo_picasso", + "osman_i", + "christiaan_huygens", + "hector_berlioz", + "adam_smith", + "karl_marx", + "friedrich_nietzsche", + "i", + "pedro", + "e_o_wilson", + "sandro_botticelli", + "nikola_tesla", + "billy_graham", + "le_corbusier", + "john_locke", + "ingrid_bergman", + "valentina_tereshkova", + "ludwig_boltzmann", + "adolf_hitler", + "edvard_grieg", + "1", + "cordell_hull", + "vladimir_putin", + "jacob", + "giuseppe_mazzini", + "anne_hathaway", + "g", + "christopher_columbus", + "r", + "george_lucas", + "andrew_jackson", + "steven_spielberg", + "thomas_gainsborough", + "giuseppe_garibaldi", + "alexandre_dumas", + "robert_brown", + "thomas_carlyle", + "johann_gutenberg", + "amerigo_vespucci", + "anna_kournikova", + "putin", + "john_calvin", + "marcus_aurelius", + "peter_o'toole", + "peter_paul_rubens", + "saunt_george", + "fyodor_dostoyevsky", + "jackson_pollock", + "charlie_chaplin", + "piscis_austrinus", + "antonio_stradivari", + "peter_the_great", + "james_watt", + "ronald_reagan", + "helmut_schmidt", + "frederick_douglass", + "david_hilbert", + "frank_capra", + "woodrow_wilson", + "saunt_lawrence_river", + "st_louis", + "don_quixote", + "jim_henson", + "ernest_hemingway", + "aquila", + "nelson_mandela", + "heinrich_himmler", + "al_gore", + "roald_amundsen", + "anton", + "jacques_offenbach", + "francisco_pizarro", + "johnny_cash", + "georges_cuvier", + "walter_scott", + "vladimir_lenin", + "albert_einstein", + "thomas_edison", + "chiang_kai_shek", + "t", + "lily" + ], + "ORG": [ + "shinto", + "nasa", + "airforce", + "schutzstaffel", + "college", + "san_francisco", + "chuggie", + "han_dynasty", + "gao", + "saunt_helena", + "reid_sea", + "chiang_mai", + "consteetuency", + "saunt_lucia", + "eddication", + "yellae_river", + "gestapo", + "white_house", + "winnie_the_pooh", + "a_loue_ye", + "unitit_states", + "europe", + "po", + "quaiker", + "ferdinand_magellan", + "loch_superior", + "capetian_dynasty", + "sturmabteilung", + "ceevil_law", + "labour_pairty", + "los_angeles", + "nato", + "mass_media", + "schuil", + "al_ain", + "peter's_pleuch", + "taoism", + "catholic_kirk", + "roman_law", + "s\u00e3o_tom\u00e9" + ], + "ANIMAL": [ + "cat", + "houlet", + "otter", + "thomson's_gazelle", + "canis_minor", + "mussel", + "shilfie", + "pisces", + "mammal", + "mavis", + "giant_panda", + "ferret", + "capercailzie", + "ebola_virus_disease", + "cushat", + "tarmigan", + "sea_speeder", + "black_tortoise", + "arthropod", + "frog", + "lintie", + "the_corbie", + "groose", + "white_rhinoceros", + "hawk", + "merl", + "mandareen", + "corbie", + "bizzart", + "banteng", + "donald_duck", + "moose", + "black_rhinoceros", + "brock", + "chicken", + "tarrock", + "foumart", + "beaver", + "whitrat", + "sea_urchin", + "blackie", + "green_tea", + "bunnetie", + "dunter", + "fire_salamander" + ], + "QUANTITY": [ + "rupee", + "no_ava", + "poond", + "g" + ], + "PRODUCT": [ + "justin_bieber", + "new_zealand", + "fyodor_dostoyevsky", + "diego_garcia", + "saxony_anhalt", + "the_hunger_gemmes", + "julius_caesar", + "the_star_spangled_banner", + "human_richts", + "don_quixote", + "the_lord_o_the_rings", + "s\u00e3o_tom\u00e9_an_pr\u00edncipe", + "new_testament", + "ferdinand_magellan" + ], + "GENDER": [ + "chiel", + "lassie", + "lass" + ], + "RELIGION": [ + "zen", + "shinto", + "judaism", + "presbyterianism", + "buddhism", + "jainism", + "calvinism", + "islam", + "hinduism", + "sunni_islam", + "manichaeism", + "atheism", + "christianity" + ], + "LANGUAGE": [ + "inglis", + "laitin", + "french", + "malayalam", + "hindi", + "franco_proven\u00e7al", + "esperanto", + "speech", + "romansh", + "tonga", + "kannada" + ], + "PLANT": [ + "viola_arvensis", + "scrog", + "solanaceae", + "amanita", + "cherry", + "taxus_baccata", + "nymphaea_alba", + "athyrium_distentifolium", + "crummock", + "lychnis", + "amanita_muscaria", + "olive", + "leucanthemum_vulgare", + "dentylion", + "geranium_robertianum", + "clematis", + "agaricus_campestris", + "sourock", + "trifolium_repens", + "solanum", + "ploum", + "acer_pseudoplatanus", + "airtist", + "saccharomyces_cerevisiae", + "gowan", + "camphor", + "windlestrae", + "lathyrus_sylvestris", + "ranunculus_repens", + "alnus_glutinosa", + "chrysanthemum", + "cassava", + "magnolia", + "meenonette", + "cirsium_arvense" + ], + "JOB": [ + "speaker", + "potter", + "beeshop", + "king", + "chieftain", + "scientist", + "kamikaze", + "mayor", + "sculptor", + "muisicker", + "pastor", + "straik", + "the_economist", + "sangwriter", + "colonel", + "lieutenant", + "preses", + "washerwife" + ], + "DISEASE": [ + "anthrax", + "rabies", + "heat", + "energy", + "anger", + "radiation", + "scruif", + "brucellosis", + "buffits", + "blain", + "straik", + "haingles", + "sairness", + "sleep", + "skaith", + "burn", + "salmonella", + "gulsoch" + ], + "POLITICAL_PARTY": [ + "poleetical_pairty", + "nazi_pairty", + "republican_pairty", + "parti_socialiste", + "democratic_pairty", + "australie_labor_pairty" + ], + "PERSON": [ + "julius_caesar", + "al_gore", + "e_o_wilson", + "george_v", + "seleucus_i_nicator", + "rudolf_hess" + ], + "LOCATION": [ + "green_tea", + "trifolium_repens", + "cape_verde", + "white_house", + "ne_er's_day", + "iris_pseudacorus", + "munt_olympus", + "black_forest", + "unitit_states_airmy", + "alnus_glutinosa", + "coort", + "sleepin_beauty", + "field", + "sri_lanka", + "richt_angle", + "faither_yuil", + "santae_claus", + "kryvyi_rih", + "al_ain" + ], + "RACE": [ + "french", + "white", + "americans" + ], + "GPE": [ + "white_house", + "dar_es_salaam", + "central_americae", + "german_empire", + "hagia_sophia", + "auld_toun", + "s\u00e3o_tom\u00e9", + "federal_destrict", + "borassus_flabellifer", + "saunt_peter", + "hibiscus_rosa_sinensis", + "vinh_long", + "la_gomera", + "st_louis" + ], + "RELIGION_MEMBER": [ + "wahhabi", + "brither", + "sister" + ], + "PERSON_PRONOUN": [ + "i", + "thee", + "he", + "thoo", + "yersel" + ], + "FAC": [ + "peter_the_great", + "primary_schuil" + ], + "LAW": [ + "federal_bureau_o_investigation" + ], + "DATE": [ + "new_muin" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "lassie": "lad", + "lass": "lad", + "moder": "faither", + "sun": "he", + "sister": "brar", + "weedae_wife": "weedae_man", + "weedae": "weedae_man", + "wife": "husband", + "guidwife": "guidman", + "wumman": "human", + "laddie": "lassie", + "lad": "lassie" + }, + "other_gender_swap": { + "ony": "sun", + "thay": "sun", + "he": "ony", + "sun": "ony" + }, + "en_pronoun2gender": { + "he": [ + "chiel", + "gaur", + "lad", + "laddie", + "human" + ], + "she": [ + "lassie", + "wumman", + "deem" + ] + }, + "en_pronoun2pronoun": { + "he": [ + "seine", + "himsel", + "he" + ], + "she": [ + "sun" + ], + "they": [ + "ony", + "thair", + "thay", + "thaim" + ], + "it": [ + "lum", + "need", + "thae", + "thir", + "thir_anes" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/sd.json b/data_tooling/pii_processing/ontology/data/sd.json new file mode 100644 index 0000000..9c59d8f --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/sd.json @@ -0,0 +1,31 @@ +{ + "ORG": [ + "\u0639\u064a\u0633\u0648\u064a_\u0633\u0627\u0644" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "\u0645\u0627\u062a\u0627": "\u067e\u064a\u0621", + "\u0631\u0627\u06bb\u064a": "\u0628\u0627\u062f\u0634\u0627\u06be", + "\u0680\u064a\u06bb": "\u0680\u0627\u0621", + "\u062f\u064a\u062f\u064a": "\u0680\u0627\u0621" + }, + "other_gender_swap": {}, + "en_pronoun2gender": { + "she": [ + "\u0633\u062a", + "\u0632\u0627\u0644" + ] + }, + "en_pronoun2pronoun": {}, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/se.json b/data_tooling/pii_processing/ontology/data/se.json new file mode 100644 index 0000000..71f889a --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/se.json @@ -0,0 +1,111 @@ +{ + "ANIMAL": [ + "bealljeloa\u0111gu", + "goaskin", + "bulddogas", + "vuoktagoalsi", + "bodneluomi", + "leaibeloddi", + "loddejiev\u017ei", + "vuonccis", + "skire", + "bakku", + "vievssis", + "mearrag\u00e1iru", + "visenta", + "sallit", + "b\u00e1rbmof\u00e1lli", + "bealljeloatku", + "luostegoddi", + "gazza", + "skuolfi", + "bealgeloddi", + "garj\u00e1", + "kan\u00e1da\u010duonj\u00e1", + "mearragoaskin", + "\u00e1hpeliira", + "boaimm\u00e1\u0161", + "buss\u00e1skuolfi", + "niitocivkk\u00e1n" + ], + "DISEASE": [ + "s\u00e1hp\u00e1n", + "leasmed\u00e1vda", + "leasmi", + "nealgi", + "ruosta", + "giegabiig\u00e1" + ], + "JOB": [ + "don", + "maid", + "gonagas", + "ruobbi", + "boliisa", + "gaskaboddosa\u0161", + "seller", + "koahkka", + "filbmadahkki", + "jorgaleaddji" + ], + "PUBLIC_FIGURE": [ + "jesus", + "guokte", + "bealgeloddi", + "lulli", + "putin" + ], + "PLANT": [ + "savoig\u00e1lla", + "ruksesruohtas" + ], + "RELIGION_MEMBER": [ + "viellja", + "mon" + ], + "ORG": [ + "saint_helena", + "suorresp\u00e1lfu" + ], + "GENDER": [ + "maid", + "gal" + ], + "LOCATION": [ + "sri_lanka" + ], + "DATE": [ + "lusa" + ], + "LANGUAGE": [ + "norgala\u0161" + ], + "PRODUCT": [ + "bassi_vuoig\u014ba" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "nieida": "son", + "oabb\u00e1": "viellja" + }, + "other_gender_swap": {}, + "en_pronoun2gender": { + "she": [ + "nisu", + "maid", + "gal" + ] + }, + "en_pronoun2pronoun": {}, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/ses.json b/data_tooling/pii_processing/ontology/data/ses.json new file mode 100644 index 0000000..4205621 --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/ses.json @@ -0,0 +1,58 @@ +{ + "RELIGION": [ + "zen" + ], + "PUBLIC_FIGURE": [ + "berra", + "a" + ], + "LOCATION": [ + "jiji" + ], + "JOB": [ + "minister" + ], + "DISEASE": [ + "gandu" + ], + "PLANT": [ + "bananku", + "yew" + ], + "PERSON_PRONOUN": [ + "gure" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "yaha": "iddu" + }, + "other_gender_swap": {}, + "en_pronoun2gender": { + "she": [ + "woy" + ] + }, + "en_pronoun2pronoun": { + "he": [ + "iddu", + "yaha" + ], + "she": [ + "yaha" + ], + "it": [ + "yaha" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/sga.json b/data_tooling/pii_processing/ontology/data/sga.json new file mode 100644 index 0000000..c70d1ef --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/sga.json @@ -0,0 +1,78 @@ +{ + "ANIMAL": [ + "drean", + "catt", + "brocc" + ], + "ORG": [ + "scol", + "cid" + ], + "DISEASE": [ + "gaethmairecht", + "gaethamlacht", + "brath", + "luch", + "ed", + "benn", + "moirtchenn" + ], + "PUBLIC_FIGURE": [ + "b", + "e", + "erlam", + "a", + "n", + "m", + "i", + "drean", + "s" + ], + "PERSON_PRONOUN": [ + "i", + "me", + "tech", + "us" + ], + "JOB": [ + "don", + "muccaid", + "cerd", + "guide", + "danaim" + ], + "SOC_ECO_CLASS": [ + "terc" + ], + "LANGUAGE": [ + "laiten" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "mathir": "athair" + }, + "other_gender_swap": {}, + "en_pronoun2gender": { + "he": [ + "firend", + "firennach", + "menn" + ] + }, + "en_pronoun2pronoun": { + "it": [ + "issu" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/sh.json b/data_tooling/pii_processing/ontology/data/sh.json new file mode 100644 index 0000000..b9bf508 --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/sh.json @@ -0,0 +1,2248 @@ +{ + "PUBLIC_FIGURE": [ + "lawrence_durrell", + "henry_cavendish", + "benjamin_franklin", + "martin_buber", + "akira_kurosawa", + "andrija\u0161evic", + "andrija\u0161evi\u0107", + "valentina_tere\u0161kova", + "benito_musolini", + "jean_genet", + "john_knox", + "roger_williams", + "\u0161esti_kri\u017earski_rat", + "giovanni_boccaccio", + "cornelius_vanderbilt", + "rudolf_steiner", + "marija_magdalena", + "thomas_wolfe", + "gluhonijem", + "johann_bernoulli", + "max_bruch", + "leonard_bernstein", + "che_guevara", + "oktavijus", + "robert_brus", + "georges_simenon", + "c", + "erik_karlfelt", + "thomas_hodgkin", + "bernhard_riman", + "john_barth", + "edward_albee", + "dorothy_parker", + "maria_callas", + "henrik_ibsen", + "johanes_brams", + "henri_miler", + "mary_shelley", + "franz_werfel", + "marcello_malpighi", + "peter_lorre", + "sveti_georgije", + "david_livingstone", + "eduard_buchner", + "david_smith", + "john_herschel", + "brigadni_general", + "andrzej_wajda", + "jan_van_eyck", + "george_balanchine", + "jakov", + "richard_burton", + "douglas_macarthur", + "mary_wollstonecraft", + "j_edgar_hoover", + "john_jacob_astor", + "winston_churchill", + "johannes_diderik_van_der_waals", + "anton_brukner", + "dvojka", + "b", + "karl_landsteiner", + "ivan_pavlov", + "paul_mccartney", + "le_korbizje", + "terry_pratchett", + "k", + "stephen_king", + "francis_crick", + "isaac_newton", + "victor_hugo", + "joseph_smith", + "edwin_hubble", + "colette", + "bili_d\u017ein_king", + "milton_friedman", + "amy_lowell", + "edward_gibbon", + "jefferson_davis", + "saint_louis", + "george_stephenson", + "john_glenn", + "george_burns", + "henri_kisind\u017eer", + "andreji\u0107", + "kristijan_hajgens", + "george_harrison", + "george_orwell", + "jozef_albers", + "georg_meissner", + "arthur_koestler", + "richard_wagner", + "indira_gandi", + "bil_klinton", + "e_l_doctorow", + "pancho_villa", + "neprimjenjivo", + "rebecca_west", + "marie_curie", + "federiko_felini", + "dante_aligijeri", + "michael_jackson", + "robert_wilson", + "thomas_hobbes", + "charles_louis_de_secondat_montesquieu", + "van_gog", + "el_greco", + "fransisko_pizaro", + "samuel_beckett", + "amelija_erhart", + "karl_bart", + "david", + "galileo_galilei", + "chaim_weizmann", + "robert_koch", + "volt_dizni", + "i_m_pei", + "joseph_goebbels", + "george_eastman", + "john_steinbeck", + "bertrand_rasel", + "mahalija_d\u017eekson", + "donald_glaser", + "jure", + "edmund_hillary", + "vincent_van_gogh", + "martina_navr\u00e1tilov\u00e1", + "anne_boleyn", + "\u010de_gevara", + "jezero_tana", + "john_ruskin", + "robert_burns", + "hans_albrecht_bethe", + "johan_bernuli", + "thomas_paine", + "bari", + "liliuokalani", + "antun", + "mary_pickford", + "hans_fischer", + "emiliano_zapata", + "mik_d\u017eeger", + "willem_einthoven", + "thomas_willis", + "charles_chaplin", + "samuel_johnson", + "caric", + "allen_iverson", + "smith", + "louise_nevelson", + "benedikt_arnold", + "giuseppe_verdi", + "e", + "karl_jaspers", + "beethoven", + "hideki_yukawa", + "konrad_adenauer", + "norbert_wiener", + "mark_rothko", + "maurice_chevalier", + "gottlieb_daimler", + "frank_sinatra", + "leopold_kroneker", + "abel_tasman", + "katharine_hepburn", + "henri_becquerel", + "henri_matisse", + "louis_pasteur", + "richard_strauss", + "sem_hjuston", + "leslie_howard", + "hugo_grotius", + "mahalia_jackson", + "john_ford", + "alphonse_bertillon", + "katherine_mansfield", + "gertrude_stein", + "saladin", + "sergej_rahmanjinov", + "sarah_bernhardt", + "v", + "philip_marlowe", + "albert_sejbin", + "akira_kurosava", + "luigi_pirandello", + "t_s_eliot", + "e_g_marshall", + "hank_williams", + "igor_stravinski", + "robert_millikan", + "rube_goldberg", + "dorothea_lange", + "vasilij_kandinski", + "james_thurber", + "charles_de_gaulle", + "paul_von_hindenburg", + "y", + "stre\u017e", + "henry_moore", + "sergej_ajzen\u0161tajn", + "lilijuokalani", + "ala_nazimova", + "rudolf_bultmann", + "charles_lindbergh", + "vincenzo_bellini", + "samuel_barber", + "tobias_smollett", + "f", + "ludwig_wittgenstein", + "august_strindberg", + "thomas_mann", + "jozef_hajdn", + "william_ockham", + "charles_goodyear", + "dante_alighieri", + "charles", + "margot_fonteyn", + "john_irving", + "\u017eozef_luj_ge_lisak", + "samuel_de_champlain", + "giacomo_puccini", + "edward_fitzgerald", + "ana_pavlova", + "fridtjof_nansen", + "louis_braille", + "herbert_marcuse", + "artur_\u0161openhauer", + "mungo_park", + "benedict_arnold", + "paul_verlaine", + "robert_johnson", + "james_dean", + "robert", + "max_beerbohm", + "alessandro_manzoni", + "gustav_maler", + "joseph_priestley", + "johan_vinkelman", + "petar_i_aleksejevi\u010d_romanov", + "nicolas_poussin", + "andrea_mantegna", + "joseph_pulitzer", + "james_naismith", + "oscar_wilde", + "philip_roth", + "j_d_salinger", + "richard_trevithick", + "heinrich_schliemann", + "eduard_buhner", + "eli_whitney", + "andric", + "don_quijote", + "amerigo_vespu\u010di", + "laurence_olivier", + "pierre_larousse", + "christiaan_eijkman", + "adolf_eichmann", + "francis_bacon", + "pete_seeger", + "bili_vajlder", + "jan_sten", + "konstantin_stanislavski", + "john_wycliffe", + "joseph_heller", + "a", + "od\u017ea\u010dar", + "peter_carl_goldmark", + "norman_rockwell", + "james_brown", + "william_hogarth", + "charles_baudelaire", + "luigi_cherubini", + "david_ricardo", + "charlie_parker", + "z", + "immanuel_kant", + "james_franck", + "william_crookes", + "rajh", + "lewis", + "pauel", + "warburg", + "alexandre_yersin", + "albert_schweitzer", + "varja\u010da", + "johannes_kepler", + "william_s_burroughs", + "most", + "david_hartley", + "max_planck", + "william_blake", + "julio_iglesias", + "john_bardeen", + "nietzsche", + "william_byrd", + "scott_joplin", + "carl_lewis", + "sarah_siddons", + "george_vancouver", + "canberra", + "elias_canetti", + "mahatma_gandi", + "barbra_strajsend", + "edward_jenner", + "oscar_robertson", + "oliver_hardy", + "leonard_ojler", + "boris_spaski", + "johan_kepler", + "cole_porter", + "dva", + "bil_rasel", + "benjamin_west", + "jean_luc_godard", + "konstantin", + "graham_greene", + "frans_hals", + "margaret_mitchell", + "henri", + "lola_montez", + "david_riesman", + "ana_kurnjikova", + "william_herschel", + "joseph_black", + "montesquieu", + "arthur_rubinstein", + "niels_bohr", + "al_kapone", + "kenneth_grahame", + "henry_fielding", + "bertrand_russell", + "oscari", + "michael_faraday", + "john_d_rockefeller", + "anthony_burgess", + "robert_venturi", + "irving_berlin", + "bernard_baruch", + "rudolf_diesel", + "walt_disney", + "ben_jonson", + "h_l_mencken", + "gabriel_lippmann", + "\u0161esti_krsta\u0161ki_rat", + "lee", + "al_gor", + "benny_goodman", + "friedrich_engels", + "nadati", + "jane_austen", + "charles_laughton", + "boldvin", + "karl_land\u0161tajner", + "gustav_mahler", + "ed_sullivan", + "phil_collins", + "robert_redford", + "vladimir_horovic", + "fritjof_nansen", + "roza_parks", + "ian_fleming", + "richard_feynman", + "wolfgang_pauli", + "majmonid", + "li_harvi_osvald", + "theodore_dreiser", + "theodor_mommsen", + "andrew_huxley", + "marcel_proust", + "thomas_more", + "homo_heidelbergensis", + "paul_hindemith", + "elizabeth_taylor", + "paul_robeson", + "luis_salivan", + "garfild", + "daniel_jones", + "william_golding", + "robert_motherwell", + "john_milton", + "rudolf_serkin", + "brigadna_generalica", + "ethel_merman", + "milton_fridman", + "emilijano_zapata", + "samuel_adams", + "albert_speer", + "james_baldwin", + "karava\u0111o", + "tobelija", + "indira_gandhi", + "hru\u0161\u010dov", + "jane_seymour", + "betoven", + "george_gershwin", + "alberto_giacometti", + "alfred_nobel", + "jesse_owens", + "monteskje", + "maksimijan", + "antonije_hrapovicki", + "daniel_rutherford", + "kristofor_kolumbo", + "marco_polo", + "jo_ming_pej", + "caravaggio", + "charlie_watts", + "m", + "charlotte_corday", + "varburg", + "allen_ginsberg", + "fred_zinnemann", + "daniel_bernoulli", + "doris_lesing", + "guillaume_apollinaire", + "antoine_watteau", + "pablo_casals", + "joseph_henry", + "henri_bergson", + "antonius", + "boris_karloff", + "gottfried_leibniz", + "pierre_corneille", + "krin", + "ronald_regan", + "patrick_white", + "gluvonem", + "bartholomew_roberts", + "hans_christian_andersen", + "reich", + "william_morris", + "cary_grant", + "hideyo_noguchi", + "saint_lawrence", + "pieter_zeeman", + "glenn_miller", + "danijel_bernuli", + "pablo_picasso", + "natalie_wood", + "alan_hodgkin", + "anderson", + "osman_i", + "kurt_weill", + "otto_hahn", + "christiaan_huygens", + "hector_berlioz", + "lucille_ball", + "paul_simon", + "claudio_monteverdi", + "smit", + "john_galsworthy", + "robert_robinson", + "o", + "one", + "adam_smith", + "william_james", + "franc_list", + "u", + "jean_harlow", + "henry_miller", + "karl_marx", + "friedrich_nietzsche", + "i", + "ostajnica", + "robert_indiana", + "william_burroughs", + "jimmy_durante", + "ben_d\u017eonson", + "mihail_bari\u0161njikov", + "sto\u017eerni_narednik", + "karen_bliksen", + "e_o_wilson", + "sandro_botticelli", + "don_kihot", + "nikola_tesla", + "al_capone", + "charles_barkley", + "robert_schumann", + "mel_gibson", + "le_corbusier", + "carlo_goldoni", + "john_locke", + "alexis_carrel", + "robert_piri", + "king_lear", + "henry_james", + "stephen_sondheim", + "lorenz_hart", + "katherine_howard", + "helen_keller", + "ingrid_bergman", + "androvi\u0107", + "jean_piaget", + "franz_kline", + "henri_rousseau", + "katul", + "paul_tillich", + "hilaire_belloc", + "bernardo_bertolu\u010di", + "antonije", + "frank_norris", + "frank_stella", + "h_g_wells", + "walt_whitman", + "william_wyler", + "colin_powell", + "ludwig_boltzmann", + "carl_nielsen", + "ero_sarinen", + "marija_antoaneta", + "pit_mondrijan", + "richard_wright", + "adolf_hitler", + "mu\u0161kobanja", + "kris_evert", + "fritz_haber", + "peter_behrens", + "joseph_haydn", + "garfield", + "george_boole", + "buffalo_bill", + "edvard_grieg", + "robert_boyle", + "edith_cavell", + "alan_paton", + "ralph_richardson", + "1", + "robert_bruce", + "henri_filding", + "james_wilson", + "rosa_parks", + "norman_jewison", + "samuel_goldwyn", + "david_rikardo", + "ernest_walton", + "vladimir_putin", + "giuseppe_mazzini", + "jim_thorpe", + "oliver_stoun", + "h", + "arnold_sch\u00f6nberg", + "laurence_sterne", + "ben_hecht", + "toma\u0161", + "christopher_isherwood", + "anne_hathaway", + "katarina", + "don_budge", + "bill_russell", + "margaret_court", + "peter_berens", + "nikola_kopernik", + "anders_celzijus", + "clarence_darrow", + "robert_fischer", + "harry", + "g", + "sara_bernar", + "glenda_d\u017eekson", + "king_john", + "ralf_ri\u010dardson", + "anthony_comstock", + "rijeka_sv_lovrijenca", + "arthur_schopenhauer", + "karl_poper", + "james_cagney", + "sto\u017eerna_narednica", + "wanda_landowska", + "billy_mitchell", + "martin_heidegger", + "hans_eysenck", + "r", + "george_lucas", + "andrew_jackson", + "edith_wharton", + "louis_armstrong", + "jozef_gebels", + "steven_spielberg", + "st_louis_missouri", + "jean_monnet", + "d_w_griffith", + "robert_fulton", + "thomas_hardy", + "thomas_gainsborough", + "giuseppe_garibaldi", + "alexandre_dumas", + "en_hatavej", + "thomas_carlyle", + "johann_gutenberg", + "donald_barthelme", + "william_tyndale", + "bobby_fischer", + "johannes_gutenberg", + "sveti_juraj", + "giambattista_marino", + "gaetano_donizetti", + "william_faulkner", + "staljin", + "amerigo_vespucci", + "don_bad\u017e", + "pierre_boulez", + "hans_adolf_krebs", + "girolamo_savonarola", + "emma_goldman", + "francis_poulenc", + "james_ussher", + "john_barrymore", + "john_constable", + "putin", + "matthew_flinders", + "mlinar", + "joseph_campbell", + "kristifor_kolumbo", + "jean_de_la_fontaine", + "robert_hooke", + "andrejic", + "o_henry", + "johan_gutenberg", + "karl_popper", + "hans_gajger", + "ela_ficd\u017eerald", + "mary_harris", + "edvard_teler", + "george_sand", + "peter_sellers", + "rudolf_bultman", + "homo_rhodesiensis", + "charles_fourier", + "peter_o'toole", + "joseph_conrad", + "\u0161a\u0161avac", + "peter_paul_rubens", + "mahatma_gandhi", + "jim_morrison", + "jules_verne", + "paul_newman", + "george_meredith", + "henri_persel", + "josef_albers", + "jackson_pollock", + "arnold_\u0161enberg", + "john_lennon", + "andrea_palladio", + "ri\u010dard_barton", + "\u0161eri", + "bob_woodward", + "charlie_chaplin", + "d_h_lawrence", + "artur_miler", + "marko_polo", + "j_m_barrie", + "kenet_kaunda", + "lea", + "john_brown", + "al_jolson", + "elizabeth_gaskell", + "arthur_chamberlain", + "john_mill", + "marija_kiri", + "leopold_stokovski", + "andi\u0107", + "thomas_merton", + "andrej_saharov", + "hannah_arendt", + "antonio_stradivari", + "c_s_forester", + "margo_fontejn", + "alice_walker", + "strauss", + "miles_davis", + "juraj", + "andrea_paladio", + "james_parkinson", + "wilhelm_tell", + "george_marshall", + "jesse_jackson", + "willa_cather", + "bozen", + "stanley_kubrick", + "androvic", + "john_deere", + "john_huston", + "karl_bedeker", + "william_gilbert", + "james_watt", + "zambak", + "ronald_reagan", + "helmut_schmidt", + "jenny_lind", + "homo", + "david_hilbert", + "wilhelm_reich", + "roman_jakobson", + "oliver_cromwell", + "salahudin", + "lorens_olivije", + "sen_loren", + "frank_capra", + "william_wordsworth", + "rex_harrison", + "robert_d\u017eonson", + "woodrow_wilson", + "bil_gejts", + "george_wallace", + "francisco_pizzaro", + "ludvig_bolcman", + "sveti_\u0111or\u0111e", + "t_h_white", + "richard_rodgers", + "anne_sexton", + "john_dryden", + "b\u00e9la_lugosi", + "ernest_hemingway", + "george_westinghouse", + "marija_kalas", + "eero_saarinen", + "arthur_miller", + "gracie_allen", + "nelson_mandela", + "e_entertainment_tv", + "heinrich_himmler", + "al_gore", + "artur_lafer", + "hans_bethe", + "fransis_pulank", + "hans_geiger", + "ju\u017eni_svinjorepi_makaki", + "cesare_borgia", + "j_p_morgan", + "roald_amundsen", + "sherwood_anderson", + "julije_cezar", + "anton", + "charles_dickens", + "agripinila", + "i_tako_dalje", + "ella_fitzgerald", + "fats_waller", + "alois_senefelder", + "jacques_offenbach", + "joseph_paxton", + "el_greko", + "ekaterina", + "don_quijote_de_la_mancha", + "mango_park", + "george_stevens", + "federico_fellini", + "petar_veliki", + "jelisaveta", + "the_one", + "peter_minojt", + "bessie_smith", + "jean_antoine_watteau", + "patrick_henry", + "willy_brandt", + "francisco_pizarro", + "francisco_franco", + "jackie_robinson", + "bernardo_bertolucci", + "king_oliver", + "e_e_cummings", + "hans_arp", + "andrew_carnegie", + "franz_schubert", + "johnny_cash", + "joseph_mccarthy", + "hidejo_noguchi", + "mick_jagger", + "otto_loewi", + "james_ross", + "fred_aster", + "georges_cuvier", + "william_harvey", + "walter_scott", + "peter_medawar", + "sam_houston", + "robert_peary", + "robert_browning", + "comenius", + "henri_hadson", + "ralph_ellison", + "john_bunyan", + "jonathan_swift", + "walter_gropius", + "albert_einstein", + "henry_sweet", + "karl_nilsen", + "chiang_kai_shek", + "claude_bernard", + "raymond_chandler", + "henry_purcell", + "t", + "wilhelm_ostwald" + ], + "LOCATION": [ + "al_jazeera", + "la_plata", + "dan_liri", + "silvestrovo", + "laman\u0161", + "park", + "il_de_frans", + "al_d\u017eazira", + "marija_magdalena", + "piet_mondrian", + "ha_long", + "djed_bo\u017ei\u0107njak", + "sveti_patrik", + "la_manche", + "sint_maarten", + "centralna_banka", + "kopnena_vojska_sjedinjenih_dr\u017eava", + "trois_rivi\u00e8res", + "dva_brata", + "visokogradnja", + "hat_jai", + "nort_betlford", + "sent_vinsent", + "huang_he", + "joseph_louis_gay_lussac", + "narodna_skup\u0161tina_republike_srbije", + "ratno_vazduhoplovstvo", + "bela_pliska", + "portoriko", + "nova_engleska", + "falklandi", + "narodna_skup\u0161tina_republike_srpske", + "1_1", + "du\u0161evna_bolnica", + "armija_sjedinjenih_dr\u017eava", + "vojno_zrakoplovstvo", + "slepa_ulica", + "saksonija_anhalt", + "narodna_skup\u0161tina_ma\u0111arske", + "nacionalna_skup\u0161tina_svetog_kristofora_i_nevisa", + "\u0161umsko_jezero", + "sent_kler", + "saska_anhalt", + "huanghe", + "almaaz", + "arena", + "maslinova_gora", + "in_the_park", + "joseph_gay_lussac", + "rt_horn", + "the_rolling_stones", + "gornje_jezero", + "u_parku", + "slijepa_ulica", + "zelenortska_republika", + "saint_lawrence", + "narodna_skup\u0161tina", + "martinje", + "igrali\u0161te", + "heitor_villa_lobos", + "al_ain", + "i_kunto_i_panto", + "maslinska_gora", + "hoanguo", + "vojna_akademija", + "nizozemske", + "prunus_avium" + ], + "ORG": [ + "dominion", + "narodna_skup\u0161tina_republike_srpske", + "botani\u010dka_ba\u0161ta", + "altajska_pokrajina", + "skorojevicka", + "bataljon", + "teretana", + "bolivud", + "velesila", + "prosveta", + "drugi_vaseljenski_sabor", + "neka_po\u017eivi", + "wicca", + "an_education", + "prvi_efe\u0161ki_sabor", + "akademija", + "politi\u010dka_struktura", + "ratno_zrakoplovstvo", + "jan_mayen", + "as_dur", + "predstavni\u010dki_dom_sjedinjenih_ameri\u010dkih_dr\u017eava", + "prosvetiteljstvo", + "liljan", + "the_usual_suspects", + "sveta_varvara", + "obrazovanje", + "sajentologija", + "islamistika", + "aa", + "nasa", + "ne_dirati", + "arda", + "kdo", + "huang_he", + "bollywood", + "sveta_jelena", + "aleksandar_veliki", + "javni_poslovi", + "europol", + "schutzstaffel", + "albertovo_jezero", + "tri_sestre", + "germanistika", + "sveti_nikola", + "the_who", + "gospa_\u017ealosna", + "drugi_carigradski_sabor", + "prosvjetiteljstvo", + "ratarstvo", + "\u0161esti_vaseljenski_sabor", + "zemljoradnja", + "zastoj", + "san_francisco", + "un", + "a_chorus_line", + "sveti_ivan_krstitelj", + "minojska_kultura", + "gustina_stanovni\u0161tva", + "masonstvo", + "drugi_nikejski_sabor", + "plova", + "v\u0129nh_long", + "vasilije_veliki", + "vojni", + "koje\u0161tarija", + "ma\u0111arski_parlament", + "tu_i_tamo", + "prosvjeta", + "dominikanci", + "gao", + "zlatni_vijek", + "nanak", + "al_d\u017eazira", + "crna_udovica", + "aleksandar_makedonski", + "don_juan", + "riznica", + "sedmi_vaseljenski_sabor", + "bijela_ku\u0107a", + "oni", + "rimokatoli\u010dka_crkva", + "narodna_skup\u0161tina", + "vinj_long", + "the_football_league", + "prodajni_centar", + "evropol", + "konzervatorijum", + "sej\u0161elski_narodni_napredni_front", + "skorojevic", + "pravedni_josif", + "dia", + "koled\u017e", + "the_big_four", + "winnie_pooh", + "\u0161intoizam", + "lastavica_poku\u0107arka", + "vaspitanje", + "aktualan", + "mladoturci", + "srbijanski_parlament", + "menja\u010dnica", + "politi\u010dka_stranka", + "krivi_rog", + "ja_sam", + "hoanguo", + "opek", + "don_huan", + "radiogalaksija", + "rabindranath_tagore", + "gestapo", + "na_oko", + "ratna_avijacija", + "ja_te_volim", + "bela_ku\u0107a", + "obrana", + "noina_arka", + "prvi_nicejski_sabor", + "komunisti\u010dka_partija", + "drugi_nicejski_sabor", + "zelenortska_ostrva", + "spaljena_zemlja", + "republikanska_stranka_sad", + "mornarica", + "demokratska_stranka", + "prijatno", + "narodno_sobranje_republike_bugarske", + "trnoru\u017eica", + "demokratska_stranka_sad", + "sao_tome", + "me\u0111unarodna_unija_za_telekomunikacije", + "al_jazeera", + "peti_vaseljenski_sabor", + "mas_mediji", + "po", + "staro_gradsko_jezgro", + "radni\u010dka_stranka", + "s_vremena_na_vreme", + "drugi_vatikanski_sabor", + "nacionalna_skup\u0161tina_sej\u0161ela", + "dija", + "karl_sejgan", + "prvi_carigradski_sabor", + "mossad", + "pokret", + "ferdinand_magellan", + "the_grapes_of_wrath", + "laburisti\u010dka_stranka", + "\u017euta_rijeka", + "prvi_vatikanski_sabor", + "hollywood", + "cid", + "seoska_lasta", + "saint_barth\u00e9lemy", + "kopnena_vojska_sad_a", + "sturmabteilung", + "armija", + "malopoljska", + "who", + "los_angeles", + "nato", + "baltimore_orioles", + "radni\u0161tvo", + "ad_hoc", + "\u010da_vinj", + "mi", + "industrijska_zona", + "konzervatorij", + "by_the_way", + "sredi\u0161nja_banka", + "krivij_rih", + "in_situ", + "\u0161kola", + "taoizam", + "kvekeri", + "botani\u010dki_vrt", + "nacionalsocijalisti\u010dka_njema\u010dka_radni\u010dka_partija", + "baskija", + "gusto\u0107a_stanovni\u0161tva", + "crveni_kri\u017e", + "isusovci", + "silvestrovo", + "al_ain", + "huanghe", + "uspavana_lepotica", + "narodna_stranka", + "sklek", + "praunuk", + "federalni_istra\u017eni_biro", + "veliki_medvjed", + "eu", + "nacionalna_stranka", + "moje_ime_je", + "mladi_mesec", + "haredi", + "vladaju\u0107a_klasa", + "crno_tr\u017ei\u0161te", + "saint_clair", + "prvi_vaseljenski_sabor", + "admiralti", + "troa_rivjer", + "sveta_lucija", + "mosad", + "prvi_nikejski_sabor", + "s\u00e3o_tom\u00e9", + "drugi_vatikanski_koncil", + "\u0161turmabtajlung" + ], + "DATE": [ + "trenutak_istine", + "pepelnica", + "dan_pobjede_i_domovinske_zahvalnosti_dan_hrvatskih_branitelja", + "punoljetnost", + "the_wedding_night", + "preksutra", + "velika_gospa", + "cveti", + "the_day_after_tomorrow", + "dan_pobjede", + "kratkodnevica", + "druga_kosmi\u010dka_brzina", + "dan_poslije_sutra", + "velika_subota", + "kratkodnevnica", + "martinjsko_ljeto", + "ponestati", + "dan_nezavisnosti", + "dan_dr\u017eavnosti", + "1_1", + "dan_pobede", + "mladi_mjesec", + "dan_posle_sutra", + "natalitet", + "dan_svetog_patrika", + "cvjetnica", + "veliki_\u010detvrtak", + "prekosutra", + "mortalitet", + "dan_pobjede_i_domovinske_zahvalnosti", + "dan_\u0161ale", + "twelfth_night", + "dan_organizacije_ujedinjenih_nacija" + ], + "ANIMAL": [ + "veliki_ronac", + "pas_modrulj", + "pravi_tuljani", + "galebi", + "the_raven", + "urlikavci", + "je\u017einci", + "belou\u0161ka", + "ep\u0161tajn_barov_virus", + "zamor\u010de", + "lasice", + "heron", + "crvenda\u0107", + "tetrijebi", + "lasica", + "vodomar", + "pliskavice", + "kobac", + "galebovi", + "billy_elliot", + "rovac", + "bogomoljke", + "kunduz", + "stre\u017e", + "piletina", + "gubar", + "bela_vrana", + "dvojenoge", + "sljepi\u0107", + "veliki_bucanj", + "ronilice", + "velika_u\u0161ara", + "kostelj", + "crna_udovica", + "juri\u010dica", + "balegar", + "neparnoprsta\u0161i", + "obi\u010dni_puh", + "stonoga", + "bogomoljka", + "balegara", + "supovi", + "zimovka", + "biserka", + "feretka", + "zlatka", + "virus_mozaika_duvana", + "gerbillus_jamesi", + "lokarda", + "trp", + "slepi\u0107", + "kunopas", + "klijen", + "krasta\u010da", + "jazavci", + "jami\u010darke", + "banteng", + "jazavac", + "kopitari", + "zlata\u0161", + "donald_duck", + "veliki_vranac", + "karolinka", + "iller", + "kova\u010d", + "grabljivice", + "misirka", + "burnjak", + "virus_mozaika_duhana", + "zlatovrana", + "radilica", + "ce_ce_muha", + "galeb", + "vivak", + "doma\u0107i_zamor\u010di\u0107", + "pirol", + "caric", + "zubar", + "vodomari", + "dabrovi", + "kara\u0161", + "svraka", + "matica", + "parnoprsta\u0161i", + "sabolj", + "\u017eenskar", + "terpan", + "morskovodnice", + "virus_zapadnog_nila", + "kondor", + "muharice", + "zamorac", + "modrovrana", + "mala_lasica", + "papkari" + ], + "DISEASE": [ + "sars", + "bubuljica", + "demencija", + "tinitus", + "kestenjast", + "progerija", + "blastom", + "hendikep", + "ometanje", + "ki", + "rubeola", + "holecistitis", + "zara\u017eenje", + "granulom", + "micetizam", + "salmonela", + "v_t", + "boginje", + "mastitis", + "policitemija", + "kolecistitis", + "onesposobljenost", + "paraliza", + "pothranjenost", + "galaktosemija", + "kijanje", + "bremenitost", + "hordeolum", + "bolest", + "kostobolja", + "kinofobija", + "kancer", + "bolan", + "skotom", + "delirij", + "glavobolja", + "beriberi", + "distres", + "\u0161arlah", + "pretilost", + "polidaktilija", + "strabizam", + "struma", + "kratkovidost", + "bunt", + "pertusis", + "la_naus\u00e9e", + "konstipacija", + "izgladnjelost", + "pijanstvo", + "goropad", + "akvafobija", + "opstrukcija", + "padavica", + "pasija", + "raslinje", + "pelagra", + "klaustrofobija", + "para", + "plikovica", + "paradentoza", + "la_peste", + "aminija", + "dekubitus", + "beri_beri", + "gojaznost", + "wale", + "jektika", + "katarakta", + "torpor", + "epstein_barrov_virus", + "rozacea", + "anestezija", + "jarost", + "toplina", + "poremecenost", + "vrtoglavica", + "listerioza", + "stridor", + "qi", + "rahitis", + "aktinomikoza", + "besanica", + "otrovna_ivy", + "prokaza", + "talasemija", + "\u017eutica", + "gimp", + "estrus", + "frenzy", + "herpes", + "flegmona", + "mahnitost", + "smart", + "obolenje", + "pica", + "radijacija", + "spati", + "belokrvnost", + "the_sting", + "ka\u0161alj", + "bradikardija", + "kratkovidnost", + "promrzlina", + "dalekovidost", + "minamata_sindrom", + "galaktozemija", + "su\u0161ica", + "krivo\u0161ija", + "dalekovidnost", + "silikoza", + "the_passion_of_the_christ", + "purpura", + "zverinac", + "otrovni_br\u0161ljan", + "brahidaktilija", + "grudobolja", + "laringitis", + "neuhranjenost", + "distimija", + "poliomijelitis", + "goru\u0161ica", + "salotok", + "kolike", + "halacion", + "prehlada", + "materijalizam", + "gorljivost", + "mi", + "goropadnost", + "malaksalost", + "skorbut", + "bruceloza", + "sting", + "krivovrat", + "gladovati", + "cerebralna_paraliza", + "grizlica", + "delirijum", + "trauma", + "polidipsija", + "neishranjenost", + "kuru", + "fotofobija", + "bedrenica", + "razderotina", + "maglica", + "the_hives", + "groznica", + "katalepsija", + "beteg", + "bolestan", + "nazadovanje", + "le", + "salmoneloza", + "bruh", + "paraplegija", + "rikavac", + "salmonella", + "krup", + "ahondroplazija", + "bjelokrvnost", + "zubobolja", + "malarija", + "mu\u0161ice", + "mastoiditis" + ], + "JOB": [ + "kolekcionar", + "primalja", + "striptizeta", + "staratelj", + "ko\u010dija", + "genijalac", + "krasopisatelj", + "guru", + "osteopat", + "mercator", + "moreplovac", + "brigadir", + "gastarbajter", + "tu\u017eiteljstvo", + "skelari", + "nadre\u0111eni", + "konzul", + "komandant", + "ravnateljica", + "potter", + "kamenorezac", + "trener", + "stolar", + "sapunjati", + "kirurg", + "hemi\u010dar", + "mamurluk", + "koordinator", + "grenadiri", + "grenadir", + "kozar", + "veleposlanik", + "zdravnik", + "zdravnica", + "poljoprivrednik", + "menad\u017eer", + "gardijan", + "po\u0161tar", + "don", + "hirurg", + "glumci", + "pekar", + "kuharica", + "dimnja\u010dar", + "the_police", + "portparol", + "biskup", + "pretor", + "od\u017ea\u010dar", + "draguni", + "carinik", + "gentleman", + "krasnopisac", + "zanatlija", + "asistent", + "ba\u0161tovan", + "novelist", + "narednik", + "grip", + "episkopos", + "para", + "mu\u0161ice", + "kemi\u010dar", + "mirovnjak", + "zidar", + "blagajnik", + "\u010dista\u010dica", + "kuhati", + "preslika", + "volarica", + "interpretator", + "mehanika", + "nezavisan", + "pomesti", + "kamikaza", + "glumac", + "printer", + "ravnatelj", + "kamikaze", + "\u010dista\u010d", + "debeloglavci", + "the_advocate", + "pastir", + "antologi\u010dar", + "stra\u017ea", + "autorica", + "savetnik", + "zubac", + "stra\u017ear", + "nosa\u010d", + "krasopisac", + "hranitelj", + "nasapunjati", + "brigadirka", + "master", + "harpunar", + "the_guardian", + "veleposlanica", + "pu\u0161kar", + "zapovednik", + "odijevati", + "kuhar", + "listono\u0161a", + "kamenar", + "gradona\u010delnik", + "mitraljezac", + "\u010dasovni\u010dar", + "besednik", + "portparolka", + "mandarin", + "plesa\u010d", + "mehani\u010dar", + "kauboj", + "golman", + "leksikograf", + "slovoslaga\u010d", + "kralj", + "mate", + "gradona\u010delnica", + "enciklopedist", + "interpreter", + "koga", + "kolovo\u0111a", + "rabi", + "kanjac", + "krasta", + "pastor", + "komlov", + "poru\u010dnik", + "narednica", + "izbaciva\u010d", + "slikarica", + "kurir", + "glasnogovornica", + "pekarica", + "vever", + "poru\u010dnica", + "rukovodilac", + "kemi\u010darka", + "krasopisateljica", + "propovjednik", + "kalajd\u017eija", + "mlekarica", + "stanodavac", + "dimni\u010dar", + "rabin", + "vratar", + "strvinari", + "lakejski", + "the_economist", + "deveru\u0161a", + "kitolovac", + "broker", + "wetter", + "barister", + "infanterist", + "spla\u010dina", + "zastavnica", + "regrut", + "krasnopisateljica", + "regent", + "mo\u017edani_udar", + "bankar", + "nosa\u010dica", + "poreznik", + "dizajner", + "plesa\u010dica", + "kalfa", + "usher", + "messenger", + "grafi\u010dar", + "slikarka", + "dadilja", + "korsari", + "kaplar", + "solisitor", + "vesnik", + "ginekolog", + "pacov", + "skuhati", + "strojni\u010dar", + "potr\u010dko", + "lakej", + "pomija", + "the_deer_hunter", + "merkator", + "the_floorwalker", + "vodnik", + "the_independent", + "lakajski", + "feldmar\u0161al", + "kamenoklesar", + "cookie", + "propovednik", + "dobrovoljac", + "autor", + "kardiolog", + "glasnogovornik", + "krasnopisatelj" + ], + "PRODUCT": [ + "stara_planina", + "justin_bieber", + "nezaboravak", + "logaritmar", + "orgulje", + "the_time_machine", + "u_zadnji_\u010das", + "tri_kraljevstva", + "al_jazeera", + "drugi_svetski_rat", + "slavoluk", + "diego_garcia", + "glazbala", + "bo\u017ei\u0107no_drvce", + "julius_caesar", + "the_star_spangled_banner", + "le_feu_follet", + "the_kid_brother", + "san_hoakin", + "die_hard", + "drugi_svjetski_rat", + "la_ciociara", + "the_lord_of_the_rings", + "bo\u017eicno_drvce", + "prvi_svjetski_rat", + "krstionica", + "stevanjdan", + "la_dolce_vita", + "deutsche_welle", + "gong", + "u_posljednji_trenutak", + "the_scarlet_letter", + "ferdinand_magellan", + "mario_andretti", + "krizban", + "sen_pjer_i_mikelon", + "sent_helens", + "the_hound_of_the_baskervilles", + "zamorac", + "po_milosti_bo\u017ejoj", + "prvi_svetski_rat", + "sveti_duh", + "\u010detiri_godi\u0161nja_doba", + "dva_brata", + "mario_andreti", + "deux_fr\u00e8res", + "zamor\u010de", + "ivan_krstitelj", + "novogodi\u0161nje_drvo", + "digitalna_knji\u017enica", + "novo_mesto" + ], + "LANGUAGE": [ + "sindski", + "beloruski", + "jidi\u0161", + "nemica", + "smit", + "venda", + "kineski", + "kongo", + "smith", + "francuski", + "esperantski", + "poljski", + "nemac", + "pali", + "ruskinja", + "danski", + "manx", + "persijski", + "engleski", + "islandski", + "hindi", + "japanski", + "german", + "esperanto", + "naglasak", + "vijetnamski", + "svahili", + "turski", + "lingala", + "talijanski", + "cree", + "holandski", + "nijemac", + "ido", + "bugarski", + "bjeloruski", + "portugalski", + "tonga", + "malajalam" + ], + "FOOD": [ + "skuta", + "mileram", + "desert", + "limunada", + "pr\u017eenice", + "pomfrit", + "slastica", + "bombon", + "pinot_noir", + "sladoled", + "pustinja", + "poslastica", + "\u017evakaca_guma", + "predjelo", + "\u017evaka", + "pisanica", + "kamara", + "pr\u017eenica", + "pavlaka", + "\u017evaka\u0107a_guma", + "krvavica", + "mit_louf" + ], + "PLANT": [ + "lipka", + "pomo\u0107nica", + "brijest", + "\u017eivi\u010dnjak", + "pelen", + "brekinja", + "javor", + "dragoljub", + "krasuljica", + "ljubi\u010dica", + "vrba", + "turica", + "joha", + "rastavi\u0107", + "crna_sla\u010dica", + "pavitina", + "chimaphila_umbellata", + "magnolija", + "the_joshua_tree", + "repuh", + "medvjetka", + "kostri\u0161", + "solanaceae", + "bagrem", + "ivan\u010dica", + "amanita", + "palma_uljarica", + "kandilka", + "arabidopsis_thaliana", + "kopitnjak", + "mrazovac", + "prunus_laurocerasus", + "passiflora_ligularis", + "maslina", + "rujevina", + "brusnica", + "lovorvi\u0161nja", + "maslinovina", + "candida_albicans", + "trskova\u010da", + "ivanjsko_cvije\u0107e", + "acacia_dealbata", + "dianthus_caryophyllus", + "planinka", + "zvezdan", + "lu\u017enjak", + "manioka", + "tangerina", + "passiflora_incarnata", + "lazarkinja", + "skrivenosemenice", + "gavez", + "kritosjemenja\u010de", + "solnja\u010da", + "kantarion", + "kopriva", + "krem\u0161nite", + "velebilje", + "bagrenac", + "kupus", + "skrobut", + "kamilica", + "rakita", + "pavit", + "hionantus", + "suncogled", + "tetivika", + "jova", + "muhara", + "podubica", + "blekberi", + "dra\u010da", + "lesandra", + "ladole\u017e", + "bukova\u010da", + "krbuljica", + "pakujac", + "jarebika", + "\u0161im\u0161irika", + "cveta\u010da", + "blackberry", + "nadli\u0161ka", + "beladona", + "echinocactus_grusonii", + "petrovac", + "tetrljan", + "bunovina", + "rezeda", + "pajavac", + "ljubi\u010dasta", + "melisa", + "rusoma\u010da", + "fagus_sylvatica", + "zuba\u010da", + "drosophyllum_lusitanicum", + "crvena_lisica", + "vi\u0161nja", + "modrika\u010da", + "kukuta", + "marulja", + "saccharomyces_cerevisiae", + "suncokret", + "prokelj", + "krasuljak", + "pavetina", + "beta_vulgaris", + "kustovnica", + "datula", + "maslinast", + "trnina", + "kesten", + "pucalina", + "pasulj", + "barica", + "pelin", + "kestenjast", + "dan_no\u0107", + "ka\u0161ikara", + "skrivenosjemenice", + "batat", + "kiseljak", + "kaor", + "\u010destoslavica", + "belladonna", + "stolisnik", + "bijela_djetelina", + "abdovina", + "bulka", + "nezaboravak", + "agrimonia", + "vallisneria", + "zimolez", + "ljetni_vrganj", + "makovi", + "maginja", + "bakaj", + "kozlac", + "krestu\u0161ac", + "jagor\u010devina", + "magnolia", + "mati\u010dnjak", + "blagva", + "jasika", + "dvoredac", + "aerofita" + ], + "RELIGION_MEMBER": [ + "franjevci", + "guru", + "mormon", + "\u017eidov", + "katoli\u010dka", + "parsi", + "katoli\u010dki", + "metodist" + ], + "RACE": [ + "turkinja", + "japanci", + "amerikanci", + "bijelo", + "francuskinja", + "francuz", + "englezi", + "nizozemci", + "the_mexican", + "ostrvljanin", + "oto\u010danka", + "bijela", + "francuzi", + "oto\u010danin", + "jevrejski", + "meksikanac", + "ostrvljanka", + "afri\u010dki" + ], + "SOC_ECO_CLASS": [ + "zemljoradnja", + "poljodjelstvo", + "poljodelstvo", + "proletarijat", + "podzemlje", + "vladaju\u0107a_klasa", + "vite\u0161tvo", + "samuraj", + "poljoprivreda", + "ratarstvo", + "selja\u0161tvo", + "samuraji", + "vlastela", + "radni\u0161tvo" + ], + "PERSON": [ + "samokontrola", + "julius_caesar", + "min_dong_kineski", + "al_gore", + "trideset_i_dva", + "h_g_wells", + "gioconda", + "de_vit", + "trideset_dva", + "e_o_wilson", + "don_delillo", + "e_e_cummings", + "ji_\u0111ing", + "tai_shan", + "samokonrola", + "al_amin", + "igor_sikorsky", + "rasejan", + "carl_david_anderson", + "samosavla\u0111ivanje", + "sveti_vincent", + "vrganj", + "jo_jo", + "maxwell_anderson", + "rudolf_hess", + "dr_watson", + "herbert_george_wells" + ], + "GPE": [ + "dan_zaljubljenih", + "\u0111ur\u0111evdan", + "dar_es_salaam", + "marija_od_sedam_\u017ealosti", + "sint_maarten", + "tai_shan", + "sveti_georgije", + "al_andaluz", + "s\u00e3o_tom\u00e9", + "valentinovo", + "gran_canaria", + "aja_sofija", + "sveti_kristofor", + "crveno_more", + "sveti_petar", + "sveti_jovan_krstitelj", + "al_andalus", + "crveni_krst", + "ljudska_prava", + "dar_es_salam", + "sveta_barbara", + "sveti_nikola", + "sent_luis", + "sen_loren", + "novi_zavet", + "duh_sveti", + "ha_tin", + "la_gomera", + "bela_kuca", + "sveti_hristifor", + "nema\u010dko_carstvo", + "njema\u010dko_carstvo", + "novi_zavjet", + "tr\u00e0_vinh" + ], + "RELIGION": [ + "zen", + "salafizam", + "puritanstvo", + "daoizam", + "prezbiterijanstvo", + "tesavuf", + "islam", + "prezviterijanstvo", + "donatizam", + "selefizam", + "wicca", + "manihejstvo" + ], + "PERSON_PRONOUN": [ + "tvoj", + "i", + "na\u0161", + "njegov", + "moj", + "rudnik", + "njen", + "tikati" + ], + "GENDER": [ + "kavalir", + "devoj\u010dica", + "gentleman", + "superklinke", + "starica", + "dame", + "mali\u0161a", + "transrodnost", + "starac", + "gal", + "mu\u0161karac" + ], + "BIO_CHEM_ENTITY": [ + "telurinska_kiselina", + "c_reaktivni_protein", + "molibdinska_kiselina", + "n_metiletanolamin", + "salicilna_kiselina", + "glioksilna_kiselina" + ], + "POLITICAL_PARTY": [ + "demokratska_partija", + "konzervativna_partija", + "socijaldemokratska_stranka", + "kuomintang", + "stranka_rada", + "farska_stranka_jednakosti", + "partido_popular", + "laburisti\u010dka_partija", + "socijalisti\u010dka_partija", + "republikanska_stranka", + "politi\u010dka_partija", + "socijaldemokratska_partija", + "narodna_partija", + "nacionalsocijalisti\u010dka_njema\u010dka_radni\u010dka_stranka", + 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"anne_hathawayov\u00e1", + "jana_seymourov\u00e1", + "francis_galton", + "michael_jackson", + "carl_sandburg", + "thomas_hobbes", + "el_greco", + "samuel_beckett", + "ingrid_bergmanov\u00e1", + "galileo_galilei", + "john_donne", + "robert_koch", + "strie\u017eik", + "mlyn\u00e1r", + "joseph_goebbels", + "george_eastman", + "john_steinbeck", + "erich_mendelsohn", + "vincent_van_gogh", + "martina_navr\u00e1tilov\u00e1", + "john_ruskin", + "robert_burns", + "hans_albrecht_bethe", + "bari", + "liliuokalani", + "steven_weinberg", + "mary_pickford", + "hans_fischer", + "emiliano_zapata", + "karl_barth", + "willem_einthoven", + "giuseppe_verdi", + "walter_lippmann", + "karl_jaspers", + "maria_callasov\u00e1", + "tom\u00e1\u0161", + "konrad_adenauer", + "norbert_wiener", + "gottlieb_daimler", + "frank_sinatra", + "sylvia_plathov\u00e1", + "henri_matisse", + "bertram_brockhouse", + "louis_pasteur", + "richard_strauss", + "theodosius_i", + "hugo_grotius", + "john_ford", + "saladin", + "v", + "luigi_pirandello", + "charles_de_gaulle", + "paul_von_hindenburg", + "y", + "holden", + "rudolf_bultmann", + "simone_weilov\u00e1", + "charles_lindbergh", + "vincenzo_bellini", + "f", + "john_jay", + "ludwig_wittgenstein", + "august_strindberg", + "thomas_mann", + "dante_alighieri", + "margot_fonteyn", + "james_tobin", + "john_irving", + "samuel_de_champlain", + "giacomo_puccini", + "fridtjof_nansen", + "louis_braille", + "herbert_marcuse", + "paul_verlaine", + "james_dean", + "theodor_schwann", + "alessandro_manzoni", + "donald_budge", + "joseph_priestley", + "nicolas_poussin", + "andrea_mantegna", + "elizabeth_taylorov\u00e1", + "joseph_pulitzer", + "james_naismith", + "oscar_wilde", + "john_watson", + "henry", + "dorothy_mary_hodgkinov\u00e1", + "heinrich_schliemann", + "willard_gibbs", + "glenn_curtiss", + "laurence_olivier", + "christiaan_eijkman", + "george_kennan", + "adolf_eichmann", + "francis_bacon", + "joseph_heller", + "a", + "katar\u00edna", + "norman_rockwell", + "james_brown", + "william_hogarth", + "margaret_sangerov\u00e1", + "charles_baudelaire", + "luigi_cherubini", + "david_ricardo", + "charlie_parker", + "z", + "immanuel_kant", + "richard_gatling", + "james_franck", + "william_crookes", + "weber", + "stephen_leacock", + "albert_schweitzer", + "john_harvard", + "johann_friedrich_herbart", + "titus", + "johannes_kepler", + "most", + "david_hartley", + "max_planck", + "william_blake", + "pavol", + "julio_iglesias", + "john_bardeen", + "ella_fitzgeraldov\u00e1", + "scott_joplin", + "carl_lewis", + "george_vancouver", + "helen_kellerov\u00e1", + "canberra", + "elias_canetti", + "edward_jenner", + "oliver_hardy", + "cole_porter", + "dva", + "jean_luc_godard", + "graham_greene", + "frans_hals", + "vavrinec", + "joseph_black", + "dve", + "brig\u00e1dny_gener\u00e1l", + "bertrand_russell", + "michael_faraday", + "jan_tinbergen", + "charles_de_secondat_baron_de_montesquieu", + "robert_venturi", + "irving_berlin", + "rudolf_diesel", + "walt_disney", + "peter", + "gabriel_lippmann", + "steve_reich", + "benny_goodman", + "friedrich_engels", + "charles_laughton", + "charlotta_cordayov\u00e1", + "gustav_mahler", + "phil_collins", + "robert_redford", + "ian_fleming", + "richard_feynman", + "wolfgang_pauli", + "potkaniar", + "theodore_dreiser", + "katharine_hepburnov\u00e1", + "theodor_mommsen", + "marcel_proust", + "thomas_more", + "paul_hindemith", + "thomas_chippendale", + "paul_robeson", + "william_golding", + "john_milton", + "samuel_adams", + "albert_speer", + "john_vanbrugh", + "jane_seymour", + "george_gershwin", + "frank_whittle", + "alfred_nobel", + "jesse_owens", + "marco_polo", + "charlie_watts", + "anna_boleynov\u00e1", + "allen_ginsberg", + "daniel_bernoulli", + "guillaume_apollinaire", + "antoine_watteau", + "henri_bergson", + "pierre_corneille", + "patrick_white", + "hans_christian_andersen", + "william_morris", + "cary_grant", + "pieter_zeeman", + "komin\u00e1r", + "glenn_miller", + "pablo_picasso", + "l_ron_hubbard", + "hideki_jukawa", + "osman_i", + "kurt_weill", + "li_\u010deng_tao", + "otto_hahn", + "john_marshall", + "christiaan_huygens", + "hector_berlioz", + "paul_simon", + "claudio_monteverdi", + "john_galsworthy", + "robert_robinson", + "one", + "adam_smith", + "william_james", + "henry_miller", + "karl_marx", + "friedrich_nietzsche", + "i", + "maria_mitchellov\u00e1", + "john_wesley", + "sandro_botticelli", + "nikola_tesla", + "al_capone", + "charles_barkley", + "billy_graham", + "robert_schumann", + "mel_gibson", + "le_corbusier", + "carlo_goldoni", + "john_locke", + "joseph_marie_jacquard", + "henry_james", + "chubilaj", + "jean_piaget", + "henri_rousseau", + "paul_tillich", + "kon\u0161tant\u00edn", + "kri\u0161tof_kolumbus", + "walt_whitman", + "william_wyler", + "colin_powell", + "ludwig_boltzmann", + "leopold_kronecker", + "richard_wright", + "adolf_hitler", + "fritz_haber", + "peter_behrens", + "alfred_stieglitz", + "joseph_haydn", + "garfield", + "katar\u00edna_howardov\u00e1", + "george_boole", + "buffalo_bill", + "edvard_grieg", + "robert_boyle", + "arthur_laffer", + "1", + "james_wilson", + "bessie_smithov\u00e1", + "ernest_walton", + "giuseppe_mazzini", + "hertz", + "arnold_sch\u00f6nberg", + "george_fox", + "robert_fischer", + "g", + "arthur_schopenhauer", + "james_cagney", + "martin_heidegger", + "r", + "george_lucas", + "andrew_jackson", + "louis_armstrong", + "steven_spielberg", + "leonard", + "giuseppe_garibaldi", + "philip_warren_anderson", + "robert_brown", + "barbra_streisandov\u00e1", + "thomas_carlyle", + "johann_gutenberg", + "marie_curiov\u00e1", + "m\u00e1ria_magdal\u00e9na", + "william_tyndale", + "d", + "thomas_malthus", + "gaetano_donizetti", + "william_faulkner", + "flavius_iosephus", + "amerigo_vespucci", + "arthur_holmes", + "hans_adolf_krebs", + "girolamo_savonarola", + "francis_poulenc", + "putin", + "matthew_flinders", + "jean_de_la_fontaine", + "robert_hooke", + "george_sand", + "peter_sellers", + "gertrude_steinov\u00e1", + "marcus_aurelius", + "joseph_conrad", + "edmund_halley", + "william_shockley", + "peter_paul_rubens", + "jim_morrison", + "jules_verne", + "paul_newman", + "jackson_pollock", + "john_lennon", + "andrea_palladio", + "charlie_chaplin", + "lea", + "john_brown", + "hugo_junkers", + "henrich", + "antonio_stradivari", + "robinson_jeffers", + "miles_davis", + "juraj", + "sarah_bernhardtov\u00e1", + "stanley_kubrick", + "john_huston", + "william_gilbert", + "james_watt", + "jonathan_edwards", + "ronald_reagan", + "helmut_schmidt", + "frederick_douglass", + "david_hilbert", + "wilhelm_reich", + "lucille_ballov\u00e1", + "oliver_cromwell", + "william_wordsworth", + "rex_harrison", + "s", + "woodrow_wilson", + "marcus_antonius", + "st_louis", + "jim_henson", + "b\u00e9la_lugosi", + "ernest_hemingway", + "george_westinghouse", + "eero_saarinen", + "arthur_miller", + "nelson_mandela", + "heinrich_himmler", + "al_gore", + "john_rutledge", + "cesare_borgia", + "margaret_mitchellov\u00e1", + "roald_amundsen", + "sherwood_anderson", + "anton", + "charles_dickens", + "fats_waller", + "alois_senefelder", + "jacques_offenbach", + "hannah_arendtov\u00e1", + "federico_fellini", + "willy_brandt", + "francisco_pizarro", + "francisco_franco", + "a_tak_\u010falej", + "bernardo_bertolucci", + "hans_arp", + "franz_schubert", + "johnny_cash", + "joseph_mccarthy", + "hans_j\u00fcrgen_eysenck", + "alfred_kastler", + "mick_jagger", + "georges_cuvier", + "william_harvey", + "marie_stopesov\u00e1", + "sam_houston", + "robert_peary", + "ralph_ellison", + "jonathan_swift", + "walter_gropius", + "albert_einstein", + "raymond_chandler", + "henry_purcell", + "t" + ], + "LOCATION": [ + "sv\u00e4t\u00e1_helena", + "la_plata", + "kapverdy", + "centr\u00e1lna_banka", + "falklandy", + "park", + "stavebn\u00edctvo", + "piet_mondrian", + "sint_maarten", + "kryvyj_rih", + "vojensk\u00e9_letectvo", + "hornsk\u00fd_mys", + "na_ceste", + "jord\u00e1n", + "joseph_louis_gay_lussac", + "portoriko", + "haja_\u010derven\u00e1", + "botanick\u00e1_z\u00e1hrada", + "usa", + "sv\u00e4t\u00fd_martin", + "taktika_sp\u00e1lenej_zeme", + "n\u00e1rodn\u00e9_zhroma\u017edenie", + "no_a_\u010do", + "almaaz", + "\u017elt\u00e1_rieka", + "the_rolling_stones", + "vzdu\u0161n\u00e9_sily", + "sasko_anhaltsko", + "jazero_sv\u00e4tej_kl\u00e1ry", + "za_m\u00e1lo", + "horn\u00e9_jazero" + ], + "JOB": [ + "remeselnik", + "koz\u00e1r", + "morsk\u00fd", + "guru", + "cifer\u0161pi\u00f3n", + "brank\u00e1r", + "konzul", + "hasi\u010d", + "truhl\u00e1r", + "n\u00e1vrh\u00e1r", + "don", + "dermatologi\u010dka", + "vedec", + "koji\u0165", + "pe\u0161iak", + "dermatol\u00f3g", + "the_police", + "lietaj\u00face_mu\u0161ky", + "nekrof\u00e1gia", + "biskup", + "zverolek\u00e1r", + "gentleman", + "velite\u013e", + "v\u00fdrobca", + "para", + "robotn\u00edk", + "lokaj", + "str\u00e1\u017e", + "str\u00e1nka", + "krysa", + "hudobn\u00edk", + "holi\u010d", + "tane\u010dn\u00edk", + "here\u010dka", + "kardiochirurg", + "the_guardian", + "riadite\u013e", + "plag\u00e1t", + "trev\u00edr", + "obchodn\u00edk", + "herec", + "chrasta", + "kraj\u010d\u00edr", + "pek\u00e1r", + "osadn\u00edk", + "tane\u010dnica", + "po\u0161t\u00e1r", + "soch\u00e1r", + "verite\u013e", + "drevoruba\u010d", + "dru\u017eica", + "spolo\u010dn\u00edk", + "str\u00e1\u017enik", + "cop", + "barista", + "chemik", + "regent", + "messenger", + "mana\u017e\u00e9r", + "dobrovo\u013en\u00edk", + "byrokrat", + "podd\u00f4stojn\u00edk", + "vari\u0165", + "robotn\u00ed\u010dka", + "chemi\u010dka", + "kupec", + "bank\u00e1r", + "cievna_mozgov\u00e1_pr\u00edhoda", + "rozhodca", + "pek\u00e1rka", + "kardiol\u00f3g", + "nez\u00e1visl\u00fd", + "opatrovnica", + "autor", + "kamikadze" + ], + "ORG": [ + "ida", + "colnica", + "demokraticko_republik\u00e1nska_strana", + "wicca", + "kapetovci", + "zdravotn\u00edctvo", + "jan_mayen", + "albertovo_jazero", + "odbory", + "mughali", + "islamistika", + "kapverdy", + "aa", + "amerikanistika", + "bollywood", + "masm\u00e9dium", + "europol", + "schutzstaffel", + "arun\u00e1\u010dalprad\u00e9\u0161", + "germanistika", + "the_who", + "san_francisco", + "r\u00edmske_pr\u00e1vo", + "politick\u00e1_strana", + "biely_dom", + "alexander_maced\u00f3nsky", + "gao", + "\u010dching", + "historick\u00e9_centrum", + "baskicko", + "n\u00e1morn\u00edctvo", + "a_\u010fal\u0161\u00ed", + "\u017euva\u010dka", + "jozef_nazaretsk\u00fd", + "slobodomur\u00e1rstvo", + "oni", + "ve\u013ek\u00e1_medvedica", + "r.p", + "tri_sestry", + "\u0161intoizmus", + "gestapo", + "obrana", + "sedembolestn\u00e1_panna_m\u00e1ria", + "najvy\u0161\u0161\u00ed_s\u00fad", + "prisp\u00f4soben\u00fd", + "demokratick\u00e1_strana", + "n\u00e1kupn\u00e9_stredisko", + "\u010derven\u00e9_more", + "vi\u0161nuizmus", + "je\u017ei\u0161ko", + "tchang", + "spravodlivos\u0165", + "n\u00e1rodnosocialistick\u00e1_nemeck\u00e1_robotn\u00edcka_strana", + "po\u013enohospod\u00e1rstvo", + "spojen\u00e9_\u0161t\u00e1ty", + "mikul\u00e1\u0161_z_myry", + "sturmabteilung", + "katol\u00edcka_cirkev", + "silvestrovsk\u00e9_oslavy", + "los_angeles", + "nato", + "anno_domini", + "ad_hoc", + "griffinovci", + "in_situ", + "\u0161kola", + "sa", + "olivov\u00fd_vrch", + "konzervat\u00edvna_a_unionistick\u00e1_strana", + "konzervat\u00f3rium", + "hagana", + "taoizmus", + "lancasterovci", + "yorkovci", + "mosad" + ], + "FAC": [ + "jozef_nazaretsk\u00fd", + "baz\u00e9n", + "arnold_sch\u00f6nberg", + "t_lymfocyt", + "sv\u00e4t\u00e1_lucia", + "z\u00e1kladn\u00e1_\u0161kola", + "peter_ve\u013ek\u00fd", + "vysok\u00e1_porta", + "colnica", + "titus_livius", + "n\u00e1dra\u017eie", + "v\u00ed\u0165azn\u00fd_obl\u00fak", + "sv\u00e4t\u00e1_rodina" + ], + "RELIGION": [ + "vi\u0161nuizmus", + "manicheizmus", + "zen", + "presbyterianizmus", + "islam", + "lamaizmus", + "albig\u00e9nstvo", + "wicca" + ], + "LANGUAGE": [ + "ba\u0161kirsk\u00fd", + "hindsk\u00fd", + "jidi\u0161", + "malaj\u00e1lam\u010dina", + "arab\u010dina", + "kongo", + "nemec", + "arabsk\u00fd", + "anglick\u00fd", + "bielorus", + "bulharsk\u00fd", + "\u010duva\u0161sk\u00fd", + "malajsk\u00fd", + "islandsk\u00fd", + "franc\u00fazsky", + "chorv\u00e1tsky", + "svahil\u010dina", + "taliansky", + "kannad\u010dina", + "esperanto", + "lingal\u010dina", + "bielorusk\u00fd", + "komij\u010dina", + "ido", + "island\u010dina", + "franc\u00faz\u0161tina", + "portugalsk\u00fd", + "tonga", + "hind\u010dina" + ], + "FOOD": [ + "kraslica", + "golden_delicious", + "palmov\u00fd_olej", + "krvavnica", + "limon\u00e1da" + ], + "DISEASE": [ + "tinitus", + "suchotiny", + "neporiadok", + "ru\u017eienka", + "rage", + "boles\u0165", + "chudokrvnos\u0165", + "salmonela", + "podmienka", + "materializmus", + "opitos\u0165", + "listeri\u00f3za", + "analgia", + "suchotin\u00e1rsky", + "sten\u00f3za", + "chor\u00fd", + "suchoty", + "kefalhemat\u00f3m", + "bradykardia", + "tehotenstvo", + "struma", + "ms", + "malomocenstvo", + "prele\u017eanina", + "prog\u00e9ria", + "zajakavos\u0165", + "lord\u00f3za", + "art\u00e9rioskler\u00f3za", + "para", + "rachit\u00edda", + "aura_at_college_park", + "kvapavka", + "papil\u00f3m", + "apostaxia", + "stigmatiz\u00e1cia", + "cukrovka", + "kr\u00e1tkozrakos\u0165", + "\u010falekozrakos\u0165", + "bolie\u0165", + "z\u00e1vislos\u0165", + "gimp", + "smart", + "rakovina", + "pica", + "bul\u00edmia", + "gravidita", + "kachexia", + "z\u00e1padon\u00edlsky_v\u00edrus", + "gynekomastia", + "opilos\u0165", + "skorbut", + "sting", + "hydronefr\u00f3za", + "trauma", + "strabizmus", + "lichen_planus", + "kuru", + "nespavos\u0165", + "paradent\u00f3za", + "nemoc", + "the_hives", + "choroba", + "gangr\u00e9na", + "v\u00edrus_tabakovej_mozaiky", + "plyn" + ], + "GPE": [ + "stredn\u00e1_amerika", + "priesmyk", + "kotte", + "dar_es_salaam", + "duch_sv\u00e4t\u00fd", + "sint_maarten", + "si_chu", + "rieka_sv\u00e4t\u00e9ho_vavrinca", + "sv\u00e4t\u00fd_j\u00e1n_krstite\u013e", + "hagia_sofia", + "gran_canaria", + "\u010derven\u00fd_kr\u00ed\u017e", + "sv\u00e4t\u00fd_mikul\u00e1\u0161", + "nemeck\u00e9_cis\u00e1rstvo", + "sv\u00e4t\u00e1_barbora", + "la_gomera", + "st_louis", + "sv\u00e4t\u00fd_juraj" + ], + "ANIMAL": [ + "liskavkovit\u00e9", + "medojed", + "je\u017eovky", + "vydra", + "kudlanka", + "kosticovce", + "p\u00e1rnokopytn\u00edky", + "cicavce", + "duri\u010d", + "lasica", + "kobercovcotvar\u00e9", + "strie\u017eik", + "stehl\u00edk", + "rohac", + "medvie\u010fa", + "holot\u00farie", + "kanec", + "haja_tmav\u00e1", + "grinda", + "bobor", + "baset", + "diviak", + "cicavec", + "okuliarnik", + "raven", + "zubor", + "choroba_vyvolan\u00e1_v\u00edrusom_ebola", + "straka", + "iller", + "sasanky", + "\u010dajkovit\u00e9", + "hexanchusovit\u00e9", + "\u017eabotvar\u00e9", + "vrabec", + "krkavec", + "tetrov", + "volavka", + "burunduk", + "los_mokra\u010fov\u00fd", + "chyt\u013eanovit\u00e9", + "polorajotvar\u00e9", + "lastovi\u010dka_oby\u010dajn\u00e1", + "nep\u00e1rnokopytn\u00edky", + "bernikla_bielol\u00edca", + "mor\u010da_dom\u00e1ce", + "bieluha", + "norok", + "volavkovit\u00e9" + ], + "PRODUCT": [ + "raketopl\u00e1n", + "digit\u00e1lna_kni\u017enica", + "justin_bieber", + "isti\u010d", + "stredozem", + "z\u00e1ti\u0161ie", + "krstite\u013enica", + "sv\u00e4t\u00e1_m\u00e1ria", + "julius_caesar", + "nov\u00fd_z\u00e1kon", + "the_star_spangled_banner", + "nez\u00e1budka", + "morsk\u00e9_prasiatko", + "mor\u010da", + "star\u00e1_planina", + "\u013eudsk\u00e9_pr\u00e1va", + "novo_mesto" + ], + "PLANT": [ + "palina", + "javor", + "chryzant\u00e9ma", + "the_joshua_tree", + "muchotr\u00e1vka", + "sosna", + "fialka", + "sakura", + "nejedl\u00edk", + "magn\u00f3lia", + "blackberry", + "mucholapka", + "viano\u010dn\u00fd_strom\u010dek", + "mastix", + "fialov\u00e1", + "pestrec_mari\u00e1nsky", + "mirabela", + "blysk\u00e1\u010d" + ], + "RACE": [ + "ostrovan", + "franc\u00faz", + "africk\u00fd", + "severoeur\u00f3psky", + "\u010dernoch", + "franc\u00fazi", + "japonci", + "severok\u00f3rej\u010dan", + "severok\u00f3rej\u010danka", + "ameri\u010dania", + "turek", + "franc\u00fazka", + "turky\u0148a", + "angli\u010dania", + "negro" + ], + "BIO_CHEM_ENTITY": [ + "polyvinylchlorid", + "dietyl\u00e9ter", + "adenoz\u00edndifosf\u00e1t" + ], + "RELIGION_MEMBER": [ + "guru", + "kres\u0165an", + "franti\u0161k\u00e1ni", + "katol\u00edcky", + "kres\u0165anka" + ], + "PERSON_PRONOUN": [ + "tvoj", + "i", + "vami", + "tebou", + "my", + "na\u0161imi" + ], + "GENDER": [ + "women", + "chlap", + "chlapec", + "starena", + "gentleman", + "boys", + "starec" + ], + "UNION": [ + "odbory", + "mednarodna_telekomunikacijska_zveza", + "medzin\u00e1rodn\u00e1_telekomunika\u010dn\u00e1_\u00fania" + ], + "PERSON": [ + "julius_caesar", + "al_gore", + "i_\u0165ing", + "don_delillo", + "edward_osborne_wilson", + "tchaj_\u0161an", + "igor_sikorsky", + "carl_david_anderson", + "hr\u00edb_smrekov\u00fd", + "herbert_george_wells" + ], + "DATE": [ + "pozajtra", + "popolcov\u00e1_streda", + "staroba", + "stredovek", + "trojkr\u00e1\u013eov\u00fd_ve\u010der_alebo_\u010do_len_chcete", + "meniny", + "roku_p\u00e1na", + "the_day_after" + ], + "POLITICAL_PARTY": [ + "politick\u00e1_strana", + "komunistick\u00e1_strana", + "strana_zelen\u00fdch", + "republik\u00e1nska_strana", + "liber\u00e1lna_strana" + ], + "QUANTITY": [ + "dol\u00e1r", + "franc\u00fazsky_frank", + "krona", + "desa\u0165tis\u00edc", + "sveteln\u00fd_rok", + "g", + "tri_sestry", + "anders_celsius" + ], + "POLITICAL_PARTY_MEMBER": [ + "dru\u017eka" + ], + "EVENT": [ + "prebudi\u0165", + "budi\u0165" + ], + "SOC_ECO_CLASS": [ + "nieko\u013eko", + "samuraj", + "podsvetie", + "po\u013enohospod\u00e1rstvo", + "proletari\u00e1t" + ], + "TITLE": [ + "ms" + ], + "LAW": [ + "ne_bis_in_idem", + "ob\u010dianske_pr\u00e1vo", + "federal_bureau_of_investigation" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "here\u010dka": "herec", + "bar\u00f3nka": "bar\u00f3n", + "vojvodky\u0148a": "vojvoda", + "diev\u010da": "chlap", + "vnu\u010dka": "vnuk", + "jej": "jeho", + "d\u00e1ma": "efendi", + "matrix": "foter", + "p\u00ed": "mgr", + "ms": "mgr", + "reho\u013en\u00ed\u010dka": "reho\u013en\u00edk", + "nun": "monako", + "mn\u00ed\u0161ka": "mn\u00edch", + "policajtka": "policajt", + "princezn\u00e1": "knie\u017ea", + "kr\u00e1\u013eovn\u00e1": "indra", + "queens": "kniha_kr\u00e1\u013eov", + "macocha": "nevlastn\u00fd_otec", + "serv\u00edrka": "\u010da\u0161n\u00edk", + "vdova": "vdovec", + "\u017eena": "osoba", + "duna": "man\u017eel", + "man\u017eelka": "man\u017eel", + "hex": "\u010darodej", + "striga": "k\u00fazeln\u00edk", + "\u010darodejnica": "k\u00fazeln\u00edk", + "wicca": "k\u00fazeln\u00edk", + "bosorka": "k\u00fazeln\u00edk", + "women": "\u013eudia", + "chlapec": "diev\u010da" + }, + "other_gender_swap": { + "one": "jej", + "svoj": "jej", + "jej": "svoj" + }, + "en_pronoun2gender": { + "they": [ + "gej", + "transrodov\u00fd_\u010dlovek" + ], + "he": [ + "\u010dlovek", + "chlap", + "gentleman", + "mu\u017e", + "chlapec", + "osoba", + "little_boy" + ], + "she": [ + "d\u00e1ma", + "diev\u010da", + "\u017eena", + "sle\u010dna", + "gospodi\u010dna", + "\u017eensk\u00fd" + ] + }, + "en_pronoun2pronoun": { + "he": [ + "jeho", + "svoj" + ], + "she": [ + "jej" + ], + "they": [ + "one", + "ony", + "jej", + "svoj" + ], + "it": [ + "jeho", + "s\u00e1m", + "t\u00e1to", + "denne", + "t\u00edto", + "tamten", + "tento", + "\u017ee" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/sl.json b/data_tooling/pii_processing/ontology/data/sl.json new file mode 100644 index 0000000..b501727 --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/sl.json @@ -0,0 +1,1985 @@ +{ + "PUBLIC_FIGURE": [ + "henry_cavendish", + "gregor", + "benjamin_franklin", + "martin_buber", + "akira_kurosawa", + "valentina_tere\u0161kova", + "noah_webster", + "baldvin", + "giovanni_boccaccio", + "rudolf_steiner", + "marija_magdalena", + "max_bruch", + "leonard_bernstein", + "che_guevara", + "c", + "maria_callas", + "henrik_ibsen", + "verecha", + "mary_shelley", + "david_livingstone", + "eduard_buchner", + "brigadni_general", + "jan_van_eyck", + "carl_rogers", + "douglas_macarthur", + "mary_wollstonecraft", + "john_jacob_astor", + "winston_churchill", + "gustav", + "johannes_diderik_van_der_waals", + "dvojka", + "b", + "georgius", + "paul_mccartney", + "andrew_marvell", + "terry_pratchett", + "stephen_king", + "francis_crick", + "joseph_greenberg", + "isaac_newton", + "victor_hugo", + "milton_friedman", + "jefferson_davis", + "george_stephenson", + "john_glenn", + "george_harrison", + "george_orwell", + "richard_wagner", + "pancho_villa", + "tretja_kri\u017earska_vojna", + "francis_galton", + "michael_jackson", + "thomas_hobbes", + "el_greco", + "samuel_beckett", + "david", + "galileo_galilei", + "jane_goodall", + "john_donne", + "robert_koch", + "joseph_goebbels", + "john_steinbeck", + "jure", + "vincent_van_gogh", + "jezero_tana", + "francisco_de_goya_y_lucientes", + "hans_albrecht_bethe", + "thomas_paine", + "bari", + "edvard", + "steven_weinberg", + "emiliano_zapata", + "jurij", + "willem_einthoven", + "allen_iverson", + "giuseppe_verdi", + "\u010detrta_kri\u017earska_vojna", + "konrad_adenauer", + "norbert_wiener", + "frank_sinatra", + "abel_tasman", + "katharine_hepburn", + "henri_matisse", + "louis_pasteur", + "richard_strauss", + "hugo_grotius", + "saladin", + "sarah_bernhardt", + "v", + "igor_stravinski", + "dorothea_lange", + "charles_de_gaulle", + "paul_von_hindenburg", + "y", + "charles_lindbergh", + "vincenzo_bellini", + "samuel_barber", + "tobias_smollett", + "f", + "ludwig_wittgenstein", + "august_strindberg", + "thomas_mann", + "dante_alighieri", + "margot_fonteyn", + "peter_pan", + "samuel_de_champlain", + "giacomo_puccini", + "ana_pavlova", + "fridtjof_nansen", + "louis_braille", + "herbert_marcuse", + "mungo_park", + "sveti_peter", + "paul_verlaine", + "robert_johnson", + "theodor_schwann", + "alessandro_manzoni", + "joseph_priestley", + "andrea_mantegna", + "joseph_pulitzer", + "james_naismith", + "oscar_wilde", + "j_d_salinger", + "lawrence", + "d\u017eingiskan", + "heinrich_schliemann", + "adolf_eichmann", + "francis_bacon", + "john_wycliffe", + "a", + "peter_brian_medawar", + "james_brown", + "charles_baudelaire", + "luigi_cherubini", + "z", + "immanuel_kant", + "james_franck", + "william_crookes", + "albert_schweitzer", + "varja\u010da", + "johannes_kepler", + "most", + "max_planck", + "william_blake", + "julio_iglesias", + "john_bardeen", + "william_henry", + "carl_lewis", + "sarah_siddons", + "canberra", + "elias_canetti", + "edward_jenner", + "boris_spaski", + "cole_porter", + "dva", + "jean_luc_godard", + "konstantin", + "graham_greene", + "frans_hals", + "lars_onsager", + "william_herschel", + "joseph_black", + "dve", + "henry_fielding", + "bertrand_russell", + "michael_faraday", + "john_d_rockefeller", + "charles_de_secondat_baron_de_montesquieu", + "irving_berlin", + "rudolf_diesel", + "walt_disney", + "peter", + "gabriel_lippmann", + "lee", + "benny_goodman", + "friedrich_engels", + "jane_austen", + "gustav_mahler", + "ian_fleming", + "andrew_huxley", + "marcel_proust", + "thomas_more", + "paul_hindemith", + "elizabeth_taylor", + "arnold", + "william_golding", + "john_milton", + "albert_speer", + "john_vanbrugh", + "indira_gandhi", + "hru\u0161\u010dov", + "george_gershwin", + "e_t_a_hoffmann", + "frank_whittle", + "alfred_nobel", + "jesse_owens", + "marco_polo", + "caravaggio", + "charlie_watts", + "marcel_marceau", + "daniel_bernoulli", + "guillaume_apollinaire", + "henri_bergson", + "pierre_corneille", + "hans_christian_andersen", + "pieter_zeeman", + "pablo_picasso", + "natalie_wood", + "l_ron_hubbard", + "osman_i", + "kurt_weill", + "otto_hahn", + "john_marshall", + "christiaan_huygens", + "hector_berlioz", + "claudio_monteverdi", + "robert_robinson", + "one", + "adam_smith", + "william_james", + "mojzes", + "henry_miller", + "karl_marx", + "i", + "sandro_botticelli", + "don_kihot", + "nikola_tesla", + "al_capone", + "charles_barkley", + "robert_schumann", + "le_corbusier", + "carlo_goldoni", + "john_locke", + "alexis_carrel", + "helen_keller", + "paul_dukas", + "ingrid_bergman", + "jean_piaget", + "henri_rousseau", + "paul_tillich", + "karel_ple\u0161asti", + "walt_whitman", + "carl_nielsen", + "leopold_kronecker", + "marija_antoinetta", + "richard_wright", + "benjamin_thompson", + "adolf_hitler", + "maria_mitchell", + "fritz_haber", + "joseph_haydn", + "garfield", + "helen_wills", + "buffalo_bill", + "edvard_grieg", + "robert_boyle", + "toma\u017e", + "1", + "robert_bruce", + "rosa_parks", + "vladimir_putin", + "jim_thorpe", + "hertz", + "arnold_sch\u00f6nberg", + "fritz_kreisler", + "anne_hathaway", + "katarina", + "don_budge", + "margaret_court", + "jeannette_rankin", + "g", + "arthur_schopenhauer", + "henri_pitot", + "martin_heidegger", + "hans_eysenck", + "r", + "george_lucas", + "andrew_jackson", + "louis_armstrong", + "steven_spielberg", + "benedikto", + "leonard", + "eddie_rickenbacker", + "giuseppe_garibaldi", + "philip_warren_anderson", + "alexandre_dumas", + "robert_brown", + "william_tyndale", + "bobby_fischer", + "johannes_gutenberg", + "thomas_malthus", + "gaetano_donizetti", + "william_faulkner", + "amerigo_vespucci", + "hans_adolf_krebs", + "girolamo_savonarola", + "emma_goldman", + "francis_poulenc", + "matthew_flinders", + "jean_de_la_fontaine", + "robert_hooke", + "o_henry", + "karl_popper", + "charles_fourier", + "peter_o'toole", + "peter_paul_rubens", + "mahatma_gandhi", + "jim_morrison", + "jules_verne", + "paul_newman", + "alexander_wilson", + "ana_kurnikova", + "peter_veliki", + "jackson_pollock", + "evgen_savojski", + "john_lennon", + "andrea_palladio", + "\u0161eri", + "charlie_chaplin", + "lea", + "hugo_junkers", + "gluhonem", + "hannah_arendt", + "antonio_stradivari", + "dalajlama", + "miles_davis", + "juraj", + "kri\u0161tof_kolumb", + "stanley_kubrick", + "john_deere", + "william_gilbert", + "james_watt", + "jonathan_edwards", + "ronald_reagan", + "jenny_lind", + "david_hilbert", + "roman_jakobson", + "in_tako_dalje", + "oliver_cromwell", + "william_wordsworth", + "s", + "woodrow_wilson", + "reka_svetega_lovrenca", + "el_cid", + "st_louis", + "john_dryden", + "ernest_hemingway", + "john_eccles", + "arthur_miller", + "nelson_mandela", + "heinrich_himmler", + "al_gore", + "roald_amundsen", + "anton", + "charles_dickens", + "upanje", + "george_enescu", + "wallace_carothers", + "jacques_offenbach", + "federico_fellini", + "willy_brandt", + "francisco_pizarro", + "francisco_franco", + "nikolaj_kopernik", + "john_ross", + "powell", + "franz_schubert", + "julij_cezar", + "johnny_cash", + "alfred_kastler", + "mick_jagger", + "georges_cuvier", + "william_harvey", + "mornarka", + "walter_scott", + "jonathan_swift", + "walter_gropius", + "albert_einstein", + "sergej_vasiljevi\u010d_rahmaninov", + "claude_bernard", + "henry_purcell", + "t", + "wilhelm_ostwald" + ], + "ORG": [ + "ida", + "rad_vas_imam", + "prostozidarstvo", + "jan_mayen", + "rimskokatoli\u0161ka_cerkev", + "nasa", + "arda", + "kdo", + "schutzstaffel", + "the_who", + "rada_vas_imam", + "rad_te_imam", + "plav\u017e", + "san_francisco", + "prvi_nicejski_koncil", + "kolid\u017e", + "dominikanci", + "gao", + "naveli\u010dan", + "aleksander_makedonski", + "\u0161intoizem", + "saint_vincent", + "prvi_efe\u0161ki_koncil", + "zvezni_preiskovalni_urad", + "oni", + "naj_\u017eivi", + "prvi_vatikanski_koncil", + "drugi_carigrajski_koncil", + "prvi_carigrajski_koncil", + "rabindranath_tagore", + "gestapo", + "rumena_reka", + "\u010detrti_carigrajski_koncil", + "voja\u0161tvo", + "rad_vaju_imam", + "voja\u0161ki", + "mornarica", + "zakaj_ne", + "demokratska_stranka", + "kmetijstvo", + "sploh", + "aleksander_veliki", + "ferdinand_magellan", + "rada_vaju_imam", + "sveti_jo\u017eef", + "glasbena_\u0161ola", + "rada_te_imam", + "sturmabteilung", + "kapverdski_otoki", + "nacionalsocialisti\u010dna_nem\u0161ka_delavska_stranka", + "los_angeles", + "nato", + "baltimore_orioles", + "obramba", + "kvekerji", + "mi", + "politi\u010dna_stranka", + "trnulj\u010dica", + "spet", + "rotarijci", + "tretji_rajh", + "\u017eve\u010dilni_gumi", + "baskija", + "silvestrovo", + "javna_uprava", + "streptococcus_pyogenes", + "nestandardni", + "osnovna_\u0161ola", + "bela_hi\u0161a", + "botani\u010dni_vrt", + "segregacija", + "drugi_nicejski_koncil", + "kme\u010dka_lastovka", + "haredi", + "sveta_lucija", + "mosad", + "andromedina_galaksija", + "drugi_vatikanski_koncil" + ], + "DISEASE": [ + "sars", + "ohromelost", + "gobavost", + "progerija", + "glavkom", + "debelost", + "salmonela", + "neuspeh", + "porast", + "travma", + "glavobol", + "steklina", + "bolan", + "delirij", + "beriberi", + "norice", + "daljnovidnost", + "rosacea", + "para", + "slabokrvnost", + "brazgotina", + "stradanje", + "parnost", + "anestezija", + "nose\u010dnost", + "davica", + "meglica", + "driska", + "prehlad", + "materializem", + "rahitis", + "spina_bifida", + "kala_azar", + "gimp", + "pogoj", + "nedohranjenost", + "smart", + "pica", + "nespe\u010dnost", + "spati", + "kaheksija", + "sevanje", + "kratkovidnost", + "\u0161kodljivec", + "pain", + "teratom", + "silikoza", + "pasovec", + "ill", + "an_qi", + "kretenizem", + "demenca", + "mi", + "spanec", + "skorbut", + "bruceloza", + "sting", + "cepljenje", + "cerebralna_paraliza", + "polidipsija", + "proti_meticilinu_odporni_staphylococcus_aureus", + "kuru", + "preeklampsija", + "bolezen", + "zlatenica", + "bole\u010dina", + "krup", + "\u0161esta_bolezen", + "plju\u010dnica", + "ahondroplazija", + "bjelokrvnost", + "malarija" + ], + "PRODUCT": [ + "stara_planina", + "justin_bieber", + "sa\u0161ka_anhalt", + "budra", + "krstilnik", + "prva_svetovna_vojna", + "protiletalski", + "utrinek", + "saint_vincent", + "the_star_spangled_banner", + "bo\u017ei\u010dno_drevo", + "nova_zaveza", + "druga_svetovna_vojna", + "slavolok", + "gong", + "ferdinand_magellan", + "bo\u017ei\u010dek", + "mario_andretti", + "glasbilo", + "po_milosti_bo\u017eji", + "sveti_duh", + "dvanajsta_no\u010d", + "digitalna_knji\u017enica", + "novo_mesto" + ], + "FOOD": [ + "skuta", + "fritata", + "sladica", + "jabol\u010dni_zavitek", + "granny_smith", + "sladoled", + "pustinja", + "\u017eve\u010dilna_guma", + "pisanica", + "limonada", + "kosilo", + "krvavica" + ], + "RACE": [ + "angle\u017ei", + "turkinja", + "vali\u017eani", + "francozinja", + "afri\u0161ki", + "japonci", + "nizozemci", + "francozi", + "turek", + "francoz" + ], + "ANIMAL": [ + "galebi", + "zober", + "veliki_metljaj", + "bogomol\u010darji", + "belou\u0161ka", + "brancin", + "heron", + "pliskavka", + "voluharji", + "voluhar", + "noga\u010di", + "merjasec", + "brizga\u010di", + "pisanec", + "meni\u0161\u010dek", + "moko\u017e", + "repnik", + "navadni_polh", + "budra", + "lactobacillus_acidophilus", + "krivokljun", + "virus_epstein_barr", + "baset", + "\u010drni_\u0161karnik", + "mala_uharica", + "stonoga", + "bogomoljka", + "raven", + "belorepec", + "podlesek", + "morski_pra\u0161i\u010dek", + "podlasica", + "\u010drna_vdova", + "cikovt", + "postovka", + "\u0161krjan\u010dar", + "komatar", + "plavcek", + "pegatka", + "kanja", + "kotorna", + "straka", + "podhujka", + "krasta\u010da", + "jereb", + "bogomolke", + "breguljka", + "carar", + "skobec", + "vodomec", + "legati", + "bogomolka", + "kova\u010d", + "bradavi\u010darica", + "virus_herpesa_simpleksa", + "virus_noric", + "str\u017eek", + "dvojnonoge", + "kaparji", + "strako\u0161", + "vrabec", + "strako\u0161i", + "veleligenj", + "galeb", + "viti\u010dnjaki", + "navadna_veverica", + "sesalec", + "vran", + "lepenci", + "matica", + "bengalski_tiger", + "zlatovranka", + "polh", + "ru\u0161evec", + "mala_podlasica", + "priba", + "sesalci" + ], + "PLANT": [ + "robida", + "krebuljica", + "bergamot", + "javor", + "vrba", + "trobentica", + "the_joshua_tree", + "mastika", + "velika_tintnica", + "brusnica", + "macesen", + "candida_albicans", + "kapokovec", + "manioka", + "hidrofit", + "kopriva", + "korenje", + "trilistni_citronovec", + "abra\u0161ica", + "modri_glavinec", + "cveta\u010da", + "bertolecija", + "kritosemenke", + "graden", + "mesojeda_rastlina", + "melisa", + "vi\u0161nja", + "saccharomyces_cerevisiae", + "balzamovec", + "spomin\u010dica", + "togotnik", + "maklen", + "kolme\u017e", + "muholovka", + "brazilski_kav\u010dukovec", + "jerebika", + "pelin", + "rogovilar", + "mala_detelja", + "trepetlika", + "belladonna", + "koren\u010dek", + "mali_jesen", + "mamutovec", + "kakav", + "grenkoslad" + ], + "JOB": [ + "ko\u010dija", + "si_nadeti", + "cerkovnik", + "govorec", + "feldmar\u0161a", + "mercator", + "polkovnica", + "nabornik", + "brigadir", + "se_oble\u010di", + "gasilec", + "konzul", + "ravnilo", + "prapor\u0161\u010dak", + "unionist", + "navaden", + "trener", + "kirurg", + "poveljnik", + "veleposlanik", + "zdravnik", + "zdravnica", + "pomivalec", + "po\u0161tar", + "don", + "kuharica", + "svetovalka", + "pretor", + "gentleman", + "asistent", + "stotnica", + "novelist", + "para", + "poro\u010dnik", + "polkovnik", + "spremljevalec", + "prostovoljen", + "kuhati", + "mehanika", + "dragonec", + "podjetnik", + "govorka", + "poldan", + "kamikaze", + "delavec", + "pastir", + "dobrovolnice", + "stra\u017ea", + "prostovoljka", + "baker", + "stra\u017ear", + "brigadirka", + "kuhar", + "gusarstvo", + "plesalka", + "kralj", + "debeloglav\u010dki", + "mate", + "bojevnik", + "poro\u010dnica", + "plesalec", + "dragonci", + "kemi\u010darka", + "rabin", + "vratar", + "zastavnica", + "man", + "lakaj", + "regent", + "zagovornica", + "stotnik", + "prapor\u0161\u010dakinja", + "podgana", + "kartograf", + "kaplar", + "tovari\u0161", + "ginekolog", + "skuhati", + "molznica", + "galvanizer", + "mo\u017eganska_kap", + "vodnik", + "glasbenik", + "stevardesa", + "the_independent", + "glasbenica", + "svetovalec", + "delavka", + "pisec" + ], + "LANGUAGE": [ + "beloruski", + "ke\u010duan\u0161\u010dina", + "svahil\u0161\u010dina", + "kongo", + "hindij\u0161\u010dina", + "nemec", + "komij\u0161\u010dina", + "poljski", + "danski", + "bosenski", + "naglas", + "franco\u0161\u010dina", + "island\u0161\u010dina", + "romunski", + "kitajski", + "esperanto", + "marshallov\u0161\u010dina", + "malajal\u0161\u010dina", + "arab\u0161\u010dina", + "holandski", + "rusinja", + "ido", + "angle\u0161ki", + "portugalski", + "tonga" + ], + "QUANTITY": [ + "sedemindvajset", + "petindvajset", + "dvaindvajset", + "tone", + "krona", + "ton", + "\u0161estindvajset", + "petsto", + "astronomska_enota", + "g", + "elektronvolt", + "pra\u0161tevilo", + "kalorija", + "enaindvajset", + "francoski_frank", + "\u0161tiriindvajset", + "devetindvajset", + "triindvajset", + "anders_celsius", + "trije_zakoni_robotike" + ], + "DATE": [ + "na\u0161e_\u0161tetje_let", + "velika_sobota", + "julijanski_koledar", + "marijino_vnebovzetje", + "delovnik", + "dan_zmage", + "vsi_sveti", + "dvanajsta_no\u010d", + "prihodnjik", + "dan_neodvisnosti", + "kurbanbajram", + "na\u0161e_\u0161tetje", + "cvetna_nedelja", + "dan_spomina_na_mrtve", + "dan_norcev", + "dan_o\u010detov", + "mlada_luna", + "dan_zmage_in_domovinske_hvale\u017enosti" + ], + "FAC": [ + "peter_veliki", + "slavolok", + "streli\u0161\u010de", + "arnold_sch\u00f6nberg", + "kombava", + "saint_lucia", + "rimokatoli\u0161ka_cerkev", + "medved_pu", + "visoka_porta", + "katoli\u0161ka_cerkev", + "brandenbur\u0161ka_vrata" + ], + "LOCATION": [ + "oljska_gora", + "silvestrovo", + "park", + "marija_magdalena", + "piet_mondrian", + "sveti_patrik", + "gradbeni\u0161tvo", + "centralna_banka", + "sveta_marija_magdalena", + "voja\u0161ka_akademija", + "ni_za_kaj", + "saint_vincent", + "joseph_louis_gay_lussac", + "portoriko", + "saint_lucia", + "slepa_ulica", + "martinovo", + "vojno_letalstvo", + "rt_horn", + "kopenska_vojska_zdru\u017eenih_dr\u017eav_amerike", + "the_rolling_stones", + "gornje_jezero", + "cordon_bleu", + "heitor_villa_lobos", + "zelenortski_otoki" + ], + "PERSON_PRONOUN": [ + "tvoj", + "i", + "na\u0161", + "njegov", + "our", + "moj", + "me", + "rudnik", + "njen", + "tikati" + ], + "GPE": [ + "sveta_de\u017eela", + "rde\u010di_kri\u017e", + "sveti_jurij", + "sveti_nikolaj", + "al_andaluz", + "nem\u0161ko_cesarstvo", + "sveti_kri\u0161tof", + "valentinovo", + "rde\u010de_morje", + "hagija_sofija", + "sveta_barbara", + "la_rochelle", + "st_louis", + "\u010dlovekove_pravice" + ], + "PERSON": [ + "vse_odkar", + "al_gore", + "saint_vincent", + "edward_osborne_wilson", + "al_amin", + "jesenski_goban", + "carl_david_anderson", + "herbert_george_wells" + ], + "SOC_ECO_CLASS": [ + "center", + "poljedelstvo", + "samuraj", + "proletariat", + "kmetijstvo" + ], + "RELIGION": [ + "daoizem", + "prezbiterijanstvo", + "islam", + "donatizem", + "manihejstvo" + ], + "GENDER": [ + "mo\u0161ki", + "gentleman", + "starka", + "guido", + "starec", + "man", + "gal" + ], + "RELIGION_MEMBER": [ + "kristjanka", + "budisti\u010den", + "sunitski", + "fran\u010di\u0161kani", + "jehovova_pri\u010da", + "kristjan", + "budist" + ], + "BIO_CHEM_ENTITY": [ + "salicilna_kislina" + ], + "TITLE": [ + "sir" + ], + "POLITICAL_PARTY": [ + "kuomintang", + "socialisti\u010dna_stranka", + "republikanska_stranka" + ], + "LAW": [ + "civilno_pravo", + "rimsko_pravo" + ], + "EVENT": [ + "tako_je_\u017eivljenje" + ], + "UNION": [ + "mednarodna_telekomunikacijska_zveza" + ], + "POLITICAL_PARTY_MEMBER": [ + "bolj\u0161evik" + ], + "ner_regexes": [ + [ + "PERSON", + "\\D+ \\D+", + false, + [] + ] + ], + "FIRST_NAME_FEMALE": [ + "ljubica", + "lara", + "pavla", + "larisa", + "breda", + "jadranka", + "erna", + "\u0161tefanija", + "milka", + "albina", + "zdenka", + "nives", + "sara", + "marica", + "olga", + "mihaela", + "aleksandra", + "slavka", + "polona", + "vlasta", + "nastja", + "teja", + "milena", + "lilijana", + "\u0161pela", + "vesna", + "valentina", + "kristina", + "simona", + "roza", + "ur\u0161a", + "pia", + "alja", + "milica", + "tatjana", + "irena", + "daniela", + "hedvika", + "jo\u017eica", + "marjanca", + "cecilija", + "klara", + "darinka", + "sandra", + "dragica", + "ur\u0161ka", + "vanja", + "patricija", + "martina", + "romana", + "justina", + "rebeka", + "adrijana", + "sabina", + "vida", + "jerneja", + "jelka", + "suzana", + "katarina", + "eva", + "damjana", + "valerija", + "jelena", + "nata\u0161a", + "alojzija", + "laura", + "jasmina", + "andrejka", + "tadeja", + "anita", + "emilija", + "marjana", + "andreja", + "sanja", + "tea", + "karmen", + "nika", + "katja", + "silva", + "lana", + "mojca", + "angela", + "cvetka", + "monika", + "petra", + "barbara", + "mira", + "stanislava", + "klavdija", + "ljudmila", + "mateja", + "darja", + "\u0161tefka", + "nada", + "bernarda", + "neja", + "zofija", + "du\u0161anka", + "nadja", + "maru\u0161a", + "ana", + "miroslava", + "slavica", + "nina", + "polonca", + "sonja", + "jolanda", + "lucija", + "tanja", + "zora", + "matilda", + "erika", + "melita", + "viktorija", + "manca", + "ksenija", + "ema", + "stanka", + "hana", + "brigita", + "marta", + "maja", + "jo\u017eefa", + "zvonka", + "marinka", + "ajda", + "gordana", + "tamara", + "\u017eiva", + "mirjam", + "natalija", + "nu\u0161a", + "lidija", + "blanka", + "magda", + "anka", + "irma", + "magdalena", + "hermina", + "iris", + "ivana", + "danijela", + "julija", + "sa\u0161a", + "marijana", + "veronika", + "marjeta", + "anja", + "julijana", + "nevenka", + "kaja", + "anica", + "metka", + "tja\u0161a", + "vera", + "tina", + "ma\u0161a", + "antonija", + "karolina", + "branka", + "ne\u017ea", + "liljana", + "jerica", + "ines", + "alenka", + "taja", + "jasna", + "marija", + "amalija", + "rozalija" + ], + "FIRST_NAME_MALE": [ + "jo\u0161ko", + "igor", + "vincenc", + "valter", + "feliks", + "milo\u0161", + "rok", + "aleks", + "zvonko", + "damjan", + "ivo", + "matej", + "rafael", + "jo\u017eef", + "zdenko", + "danilo", + "benjamin", + "\u0161tefan", + "jani", + "aleksander", + "branko", + "edvard", + "peter", + "leon", + "slavko", + "niko", + "daniel", + "silvo", + "lovro", + "petar", + "marjan", + "tine", + "jernej", + "radovan", + "anej", + "zdravko", + "izidor", + "jure", + "bogdan", + "bojan", + "franjo", + "jasmin", + "rado", + "aleksandar", + "stanislav", + "roman", + "nik", + "cvetko", + "vlado", + "klemen", + "josip", + "toma\u017e", + "darko", + "kristijan", + "pavel", + "domen", + "jaka", + "jakob", + "drago", + "\u017eiga", + "du\u0161an", + "stojan", + "miran", + "bla\u017e", + "ernest", + "alojzij", + "edin", + "dominik", + "emil", + "elvis", + "valentin", + "slobodan", + "leopold", + "anton", + "matija", + "albin", + "vid", + "sre\u010dko", + "bernard", + "mark", + "gorazd", + "ciril", + "jan", + "uro\u0161", + "borut", + "matev\u017e", + "tadej", + "karel", + "franci", + "dejan", + "goran", + "miha", + "tim", + "davorin", + "karol", + "sebastijan", + "nenad", + "\u017ean", + "martin", + "alja\u017e", + "tilen", + "marko", + "mihael", + "alen", + "zlatko", + "janko", + "rajko", + "metod", + "viktor", + "avgust", + "luka", + "adolf", + "nikolaj", + "simon", + "franc", + "stanko", + "miroslav", + "kristjan", + "mirko", + "janez", + "matja\u017e", + "gregor", + "aljo\u0161a", + "hasan", + "maksimiljan", + "maks", + "ervin", + "david", + "rudi", + "nikola", + "rudolf", + "boris", + "mirsad", + "filip", + "miro", + "sa\u0161a", + "an\u017ee", + "grega", + "marijan", + "bogomir", + "nejc", + "milan", + "stjepan", + "davor", + "damir", + "robert", + "bo\u0161tjan", + "sa\u0161o", + "fran\u010di\u0161ek", + "gal", + "ivan", + "iztok", + "erik", + "ludvik", + "andrej", + "danijel", + "matic", + "dragan", + "sandi", + "\u017eeljko", + "timotej", + "ladislav", + "sebastjan", + "albert", + "samo", + "bruno", + "damijan", + "vladimir", + "maj", + "viljem", + "karl" + ], + "FIRST_NAME": [ + "ljubica", + "feliks", + "erna", + "\u0161tefanija", + "zvonko", + "ivo", + "benjamin", + "teja", + "branko", + "edvard", + "peter", + "milena", + "slavko", + "valentina", + "niko", + "ur\u0161a", + "silvo", + "milica", + "sandra", + "franjo", + "adrijana", + "justina", + "vlado", + "vida", + "jelka", + "eva", + "jelena", + "jasmina", + "tadeja", + "emilija", + "andreja", + "sanja", + "elvis", + "tea", + "slobodan", + "matija", + "mojca", + "vid", + "bernard", + "petra", + "mira", + "klavdija", + "gorazd", + "jan", + "uro\u0161", + "borut", + "karel", + "nadja", + "maru\u0161a", + "sebastijan", + "ana", + "slavica", + "nina", + "sonja", + "alja\u017e", + "lucija", + "tanja", + "alen", + "zlatko", + "erika", + "manca", + "metod", + "simon", + "ajda", + "lidija", + "magda", + "gregor", + "hasan", + "ervin", + "rudi", + "irma", + "danijela", + "sa\u0161a", + "marijan", + "marijana", + "milan", + "tja\u0161a", + "fran\u010di\u0161ek", + "iztok", + "matic", + "karolina", + "sandi", + "liljana", + "sebastjan", + "alenka", + "jasna", + "damijan", + "marija", + "lara", + "vincenc", + "zdenka", + "milo\u0161", + "albina", + "milka", + "damjan", + "olga", + "aleksandra", + "jo\u017eef", + "slavka", + "polona", + "\u0161tefan", + "nastja", + "aleksander", + "vesna", + "simona", + "lovro", + "daniel", + "petar", + "marjan", + "radovan", + "jernej", + "daniela", + "jo\u017eica", + "bogdan", + "klara", + "aleksandar", + "patricija", + "martina", + "romana", + "roman", + "jerneja", + "josip", + "suzana", + "domen", + "jaka", + "\u017eiga", + "laura", + "miran", + "du\u0161an", + "andrejka", + "bla\u017e", + "dominik", + "leopold", + "nika", + "katja", + "lana", + "cvetka", + "monika", + "mark", + "darja", + "bernarda", + "franci", + "karol", + "polonca", + "mihael", + "matilda", + "melita", + "viktorija", + "viktor", + "avgust", + "luka", + "marta", + "jo\u017eefa", + "stanko", + "zvonka", + "mirjam", + "aljo\u0161a", + "nikola", + "magdalena", + "ivana", + "rudolf", + "mirsad", + "julija", + "miro", + "grega", + "filip", + "marjeta", + "anja", + "julijana", + "kaja", + "vera", + "danijel", + "antonija", + "dragan", + "branka", + "ne\u017ea", + "\u017eeljko", + "ladislav", + "rozalija", + "vladimir", + "viljem", + "karl", + "jo\u0161ko", + "igor", + "valter", + "larisa", + "jadranka", + "nives", + "rok", + "sara", + "marica", + "zdenko", + "roza", + "hedvika", + "izidor", + "jure", + "bojan", + "darinka", + "dragica", + "jasmin", + "rado", + "vanja", + "rebeka", + "stanislav", + "cvetko", + "sabina", + "darko", + "pavel", + "alojzija", + "drago", + "marjana", + "emil", + "valentin", + "karmen", + "silva", + "angela", + "sre\u010dko", + "stanislava", + "mateja", + "ciril", + "nada", + "matev\u017e", + "goran", + "zofija", + "tim", + "du\u0161anka", + "davorin", + "jolanda", + "tilen", + "marko", + "zora", + "ksenija", + "ema", + "brigita", + "stanka", + "adolf", + "nikolaj", + "miroslav", + "marinka", + "tamara", + "kristjan", + "mirko", + "maks", + "anka", + "david", + "iris", + "boris", + "veronika", + "nejc", + "davor", + "nevenka", + "bo\u0161tjan", + "sa\u0161o", + "tina", + "gal", + "ivan", + "erik", + "ludvik", + "timotej", + "taja", + "samo", + "amalija", + "pavla", + "breda", + "aleks", + "matej", + "mihaela", + "rafael", + "danilo", + "jani", + "vlasta", + "\u0161pela", + "lilijana", + "leon", + "kristina", + "pia", + "alja", + "tatjana", + "irena", + "tine", + "anej", + "zdravko", + "marjanca", + "cecilija", + "ur\u0161ka", + "nik", + "klemen", + "kristijan", + "toma\u017e", + "katarina", + "damjana", + "valerija", + "jakob", + "nata\u0161a", + "stojan", + "anita", + "ernest", + "alojzij", + "edin", + "anton", + "albin", + "barbara", + "ljudmila", + "\u0161tefka", + "tadej", + "neja", + "dejan", + "miha", + "nenad", + "miroslava", + "\u017ean", + "martin", + "janko", + "rajko", + "hana", + "maja", + "franc", + "gordana", + "\u017eiva", + "natalija", + "nu\u0161a", + "blanka", + "janez", + "matja\u017e", + "maksimiljan", + "hermina", + "an\u017ee", + "bogomir", + "stjepan", + "damir", + "metka", + "anica", + "robert", + "ma\u0161a", + "andrej", + "jerica", + "ines", + "albert", + "bruno", + "maj" + ], + "LAST_NAME": [ + "kau\u010di\u010d", + "tratnik", + "\u0161inkovec", + "marolt", + "le\u0161nik", + "er\u017een", + "miklav\u010di\u010d", + "perko", + "miheli\u010d", + "su\u0161nik", + "jeri\u010d", + "kova\u010d", + "ko\u010devar", + "skok", + "zalokar", + "tom\u0161i\u010d", + "ho\u010devar", + "toplak", + "kalan", + "hribar", + "filipi\u010d", + "\u0161mid", + "\u010deh", + "dolin\u0161ek", + "poga\u010dnik", + "leban", + "godec", + "krajnc", + "gregori\u010d", + "babi\u010d", + "horvat", + "novak", + "pintari\u010d", + "volk", + "zver", + "sitar", + "ma\u010dek", + "lah", + "resnik", + "kranjc", + "pavlin", + "\u017enidar\u0161i\u010d", + "ili\u0107", + "\u017eibert", + "hod\u017ei\u0107", + "zupan\u010di\u010d", + "kos", + "likar", + "jereb", + "\u0161u\u0161tar", + "kumer", + "markovi\u010d", + "mavri\u010d", + "breznik", + "jerman", + "hafner", + "cvetko", + "toma\u017ei\u010d", + "mlinari\u010d", + "kocjan\u010di\u010d", + "petek", + "blatnik", + "bizjak", + "kastelic", + "lavri\u010d", + "bezjak", + "kramberger", + "\u010derne", + "hribernik", + "kokol", + "mlakar", + "furlan", + "bevc", + "koren", + "ro\u017eman", + "petrovi\u010d", + "jelen", + "\u010duk", + "javornik", + "medved", + "gorenc", + "kokalj", + "knez", + "jane\u017ei\u010d", + "primo\u017ei\u010d", + "klemen\u010di\u010d", + "pavli\u010d", + "debeljak", + "leskovar", + "jenko", + "rozman", + "rajh", + "kramar", + "ram\u0161ak", + "kobal", + "poto\u010dnik", + "turk", + "bo\u017ei\u010d", + "kolari\u010d", + "\u0161trukelj", + "lesjak", + "\u017eagar", + "lazar", + "ribi\u010d", + "rupnik", + "zupanc", + "vidovi\u010d", + "mrak", + "zemlji\u010d", + "vodopivec", + "fras", + "pirnat", + "kolenc", + "dolinar", + "zupan", + "bergant", + "pirc", + "lebar", + "zorko", + "zakraj\u0161ek", + "gorjup", + "logar", + "gomboc", + "bregar", + "vidic", + "bla\u017ei\u010d", + "rus", + "majcen", + "nemec", + "mlinar", + "kotnik", + "hozjan", + "vidmar", + "ko\u017eelj", + "zorman", + "hrovat", + "krivec", + "popovi\u0107", + "\u017ei\u017eek", + "kova\u010di\u010d", + "koro\u0161ec", + "erjavec", + "golob", + "bajc", + "pe\u010dnik", + "kosi", + "sever", + "pintar", + "ro\u017ei\u010d", + "kuhar", + "stopar", + "jarc", + "jamnik", + "jovanovi\u0107", + "kodri\u010d", + "bukovec", + "cerar", + "dolenc", + "dem\u0161ar", + "kolar", + "tav\u010dar", + "\u017eeleznik", + "jug", + "simoni\u010d", + "ko\u0161ir", + "rutar", + "zajc", + "ambro\u017ei\u010d" + ], + "LAST_NAME_MALE": [], + "LAST_NAME_FEMALE": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "opatinja": "opat", + "baronica": "baron", + "pulj": "dude", + "pti\u010dji_mladi\u010d": "dude", + "vojvodinja": "vojvoda", + "cesarica": "veliki_spremljevalec", + "\u017eenski": "mo\u0161ki", + "\u017eena": "man", + "gal": "gvido", + "diev\u010da": "gvido", + "dekle": "borec", + "vnukinja": "vnuk", + "njen": "njihov", + "heroin": "junak", + "junakinja": "heroj", + "heroina": "junakinja", + "kak": "efendi", + "cik": "sir", + "gospodi\u010dna": "sir", + "zgre\u0161iti": "sir", + "sle\u010dna": "sir", + "moder": "peder", + "gospa": "gospod", + "redovnica": "menih", + "poldan": "policist", + "policistka": "mili\u010dnik", + "princesa": "knez", + "kraljica": "kralj", + "hetman": "indra", + "queens": "knjiga_kraljev", + "\u010darovnica": "\u010darovnik", + "pastorka": "pastorek", + "ma\u010deha": "o\u010dim", + "natakarica": "natakar", + "vdova": "vdovec", + "soproga": "soprog", + "\u017eenska": "man", + "de\u010dek": "dekle", + "fant": "diev\u010da" + }, + "other_gender_swap": { + "one": "njen", + "svoj": "njihov", + "njihov": "njen", + "isti": "one", + "njegov": "njihov", + "njen": "njihov" + }, + "en_pronoun2gender": { + "they": [ + "bakla" + ], + "he": [ + "\u010dlovek", + "borec", + "gentleman", + "man", + "de\u010dek", + "gvido", + "mo\u0161ki", + "fant", + "dude", + "guido" + ], + "she": [ + "devica", + "zgre\u0161iti", + "diev\u010da", + "\u017eenski", + "\u017eenska", + "\u017eena", + "sle\u010dna", + "gospodi\u010dna", + "dekle", + "cik", + "kak", + "gal" + ] + }, + "en_pronoun2pronoun": { + "he": [ + "njegov", + "isti", + "svoj" + ], + "she": [ + "njen" + ], + "they": [ + "one", + "njihov", + "svoj" + ], + "it": [ + "\u017ee" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/sm.json b/data_tooling/pii_processing/ontology/data/sm.json new file mode 100644 index 0000000..e9bd4a6 --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/sm.json @@ -0,0 +1,50 @@ +{ + "PLANT": [ + "mamona", + "sinapi", + "taloti" + ], + "JOB": [ + "epikop\u014d", + "tusitala" + ], + "ORG": [ + "ai", + "po" + ], + "FOOD": [ + "aisakulimi" + ], + "FAC": [ + "vai_taele" + ], + "PERSON_PRONOUN": [ + "me" + ], + "LOCATION": [ + "sri_lanka" + ], + "DISEASE": [ + "le" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": {}, + "other_gender_swap": {}, + "en_pronoun2gender": { + "she": [ + "fafine" + ] + }, + "en_pronoun2pronoun": {}, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/smn.json b/data_tooling/pii_processing/ontology/data/smn.json new file mode 100644 index 0000000..0c55138 --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/smn.json @@ -0,0 +1,44 @@ +{ + "ANIMAL": [ + "leibilodd\u00e1\u00e1\u0161", + "skunj\u00e2lodde", + "vuor\u00e2\u0161", + "pieh\u00e2in", + "pagoi" + ], + "PRODUCT": [ + "juovl\u00e2muor\u00e2" + ], + "PLANT": [ + "juovl\u00e2muor\u00e2" + ], + "GENDER": [ + "kand\u00e2", + "p\u00e4rni" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": {}, + "other_gender_swap": {}, + "en_pronoun2gender": { + "he": [ + "p\u00e4rni", + "kand\u00e2" + ] + }, + "en_pronoun2pronoun": { + "she": [ + "sun" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/sms.json b/data_tooling/pii_processing/ontology/data/sms.json new file mode 100644 index 0000000..47ac9fb --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/sms.json @@ -0,0 +1,50 @@ +{ + "JOB": [ + "lookki", + "truub\u0161e\u01e9", + "koon\u01e5\u00f5s" + ], + "PUBLIC_FIGURE": [ + "repp" + ], + "LOCATION": [ + "rosttovk\u00e4\u00e4nan" + ], + "ANIMAL": [ + "k\u00e4\u00e4rn\u00f5s" + ], + "PRODUCT": [ + "kuusk\u00f5\u00f5zz" + ], + "DATE": [ + "maiddp\u00e2\u00e2\u02b9zzl\u00e2\u0161ttam" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "je\u00e4\u02cann": "e\u02b9\u010d\u010d", + "mana\u0161ih": "manah", + "koon\u01e5\u00f5skaav": "koon\u01e5\u00f5s" + }, + "other_gender_swap": {}, + "en_pronoun2gender": { + "he": [ + "\u00e2\u02cal\u01e7\u01e7", + "kutt" + ], + "she": [ + "neezzan" + ] + }, + "en_pronoun2pronoun": {}, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/so.json b/data_tooling/pii_processing/ontology/data/so.json new file mode 100644 index 0000000..dc280be --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/so.json @@ -0,0 +1,75 @@ +{ + "ORG": [ + "beeraha", + "baddacas" + ], + "PLANT": [ + "sallar", + "dabacase", + "karooto" + ], + "PUBLIC_FIGURE": [ + "bari" + ], + "JOB": [ + "turjume", + "barfasoor", + "madaxweyne" + ], + "TITLE": [ + "sir" + ], + "DISEASE": [ + "kansar", + "sokorow", + "busbus" + ], + "RELIGION_MEMBER": [ + "mormon" + ], + "LOCATION": [ + "magaalo" + ], + "LANGUAGE": [ + "af_afrikaanays", + "af_somaali" + ], + "RACE": [ + "carabiya" + ], + "ANIMAL": [ + "sagaaro", + "gumburi", + "digaag" + ], + "SOC_ECO_CLASS": [ + "beeraha", + "labeen" + ], + "FOOD": [ + "bataax" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "boqorad": "boqor", + "huunno": "walaal" + }, + "other_gender_swap": {}, + "en_pronoun2gender": { + "she": [ + "naag" + ] + }, + "en_pronoun2pronoun": {}, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/sq.json b/data_tooling/pii_processing/ontology/data/sq.json new file mode 100644 index 0000000..0bd152a --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/sq.json @@ -0,0 +1,725 @@ +{ + "PUBLIC_FIGURE": [ + "henry_cavendish", + "benjamin_franklin", + "akira_kurosawa", + "moisiu", + "giovanni_boccaccio", + "rudolf_steiner", + "saladini", + "ferr\u00ebkuqe", + "c", + "robert_shumann", + "henrik_ibsen", + "maria_magdalena", + "winston_churchill", + "kostandin", + "paul_mccartney", + "ali_xhinah", + "stephen_king", + "francis_crick", + "isaac_newton", + "victor_hugo", + "joseph_smith", + "edwin_hubble", + "milton_friedman", + "burrnesh\u00eb", + "sh\u00ebn_gjergji", + "george_harrison", + "george_orwell", + "richard_wagner", + "marie_curie", + "michael_jackson", + "carl_sandburg", + "thomas_hobbes", + "samuel_beckett", + "galileo_galilei", + "robert_koch", + "john_steinbeck", + "vincent_van_gogh", + "anne_boleyn", + "robert_burns", + "thomas_paine", + "bari", + "p", + "hans_fischer", + "yuri_gagarin", + "giuseppe_verdi", + "e", + "konrad_adenauer", + "don_kishoti_i_man\u00e7\u00ebs", + "gottlieb_daimler", + "frank_sinatra", + "abel_tasman", + "louis_pasteur", + "richard_strauss", + "sarah_bernhardt", + "luigi_pirandello", + "t_s_eliot", + "charles_de_gaulle", + "charles_lindbergh", + "august_strindberg", + "thomas_mann", + "bin_laden", + "charles_goodyear", + "dante_alighieri", + "giacomo_puccini", + "benedict_arnold", + "james_dean", + "joseph_priestley", + "joseph_pulitzer", + "james_naismith", + "oscar_wilde", + "virgjinesh\u00eb", + "francis_bacon", + "pete_seeger", + "a", + "gustav_flober", + "charles_baudelaire", + "david_ricardo", + "immanuel_kant", + "john_harvard", + "giulio_natta", + "johannes_kepler", + "max_planck", + "julio_iglesias", + "arthur", + "canberra", + "mahatma_gandi", + "john_mercer", + "oliver_hardy", + "margaret_mitchell", + "igor_stravinsky", + "flavius_josephus", + "joseph_black", + "virgjna", + "arthur_compton", + "niels_bohr", + "bertrand_russell", + "michael_faraday", + "walt_disney", + "don_kishoti", + "ted_williams", + "friedrich_engels", + "jane_austen", + "ian_fleming", + "richard_feynman", + "theodor_mommsen", + "william_golding", + "indira_gandhi", + "alfred_nobel", + "pablo_casals", + "henri_bergson", + "patrick_white", + "cary_grant", + "pablo_picasso", + "lui_aragoni", + "otto_hahn", + "john_marshall", + "hector_berlioz", + "john_galsworthy", + "o", + "paul_gaugin", + "adam_smith", + "william_james", + "gjergji", + "karl_marx", + "friedrich_nietzsche", + "i", + "sandro_botticelli", + "nikola_tesla", + "al_capone", + "mel_gibson", + "john_locke", + "helen_keller", + "ingrid_bergman", + "jean_piaget", + "valentina_tereshkova", + "leopold_kronecker", + "adolf_hitler", + "fritz_haber", + "joseph_haydn", + "robert_boyle", + "hans_eysenk", + "vladimir_putin", + "g", + "arthur_schopenhauer", + "martin_heidegger", + "george_lucas", + "andrew_jackson", + "louis_armstrong", + "gjergj", + "steven_spielberg", + "leonard", + "giuseppe_garibaldi", + "alexandre_dumas", + "johannes_gutenberg", + "william_faulkner", + "johannes_eckhart", + "amerigo_vespucci", + "putin", + "karl_popper", + "george_sand", + "marcus_aurelius", + "peter_o'toole", + "peter_paul_rubens", + "jim_morrison", + "jules_verne", + "paul_newman", + "jackson_pollock", + "john_lennon", + "charlie_chaplin", + "osmani_i_i", + "marko_polo", + "jezusi", + "hannah_arendt", + "alice_walker", + "stanley_kubrick", + "zambak", + "ronald_reagan", + "helmut_schmidt", + "david_hilbert", + "oliver_cromwell", + "martin_luther_king", + "frank_capra", + "s", + "woodrow_wilson", + "marcus_antonius", + "ernest_hemingway", + "arthur_miller", + "cristoforo_colombo", + "nelson_mandela", + "al_gore", + "roald_amundsen", + "charles_dickens", + "ella_fitzgerald", + "stalini", + "varroni", + "federico_fellini", + "maria_antoneta", + "patrick_henry", + "willy_brandt", + "francisco_franco", + "bernardo_bertolucci", + "sh\u00ebn_martini", + "franz_schubert", + "johnny_cash", + "albert_einstein", + "thomas_edison" + ], + "PLANT": [ + "panxhar", + "vishnja", + "kallam_sheqeri", + "dish\u00ebll", + "bagrem", + "eryngium_maritimum", + "vishnj\u00eb", + "arundo", + "artist", + "achillea", + "manushaqja", + "gentiana_lutea", + "euphorbia_esula", + "kulpra", + "shelg", + "marule", + "amanita_muscaria", + "kumbull", + "aborotoni", + "clematis", + "artisti", + "spineri", + "shen_merija", + "mushmolla", + "bath\u00ebt", + "euphorbia_cyparissias", + "kanilqyqe", + "kaliboba", + "melisa", + "panj\u00eb", + "selvia", + "karot\u00eb", + "karrota", + "kumbulla", + "edelweiss", + "aerofit", + "erodium_texanum", + "kasht\u00ebfryza", + "chrysanthemum", + "agrimonia", + "euphorbia_milii", + "castanea", + "kallmi", + "bath\u00eb", + "shurb\u00eb" + ], + "LOCATION": [ + "la_plata", + "ju_falem_nderit", + "park", + "eryngium_maritimum", + "saksonia_anhalt", + "trois_rivi\u00e8res", + "ishulli_sh\u00ebn_elena", + "pieris_rapae", + "joseph_louis_gay_lussac", + "te_lutem", + "liqeni_i_sip\u00ebrm", + "forcat_tok\u00ebsore_t\u00eb_shba", + "spital_psikiatrik", + "banka_qendrore", + "portorikoja", + "sri_lanka", + "kepi_i_gjelb\u00ebr", + "pieris_brassicae", + "pandispanj\u00eb" + ], + "ANIMAL": [ + "pula_faraone", + "m\u00ebllenj\u00eb", + "nuselale", + "kryemadh", + "lund\u00ebrz", + "kaprolle", + "larash", + "brekazi", + "greth", + "zardafi", + "kaproll", + "pieris_brassicae", + "gini_thi", + "sorr\u00eb", + "artiodactyl", + "dre", + "thundrak", + "arthropod", + "gomari", + "kaprolli", + "bretkosa", + "barbun", + "baldos\u00eb", + "iller", + "shum\u00ebk\u00ebmb\u00ebsh", + "larask\u00eb", + "peshqit", + "bubuzhel", + "kath", + "petriti", + "cakalli", + "sea_urchin", + "jote", + "marsuin\u00ebt", + "gjeraqina", + "kashalot" + ], + "JOB": [ + "bakall", + "tetar", + "mace", + "banakiere", + "keshilltar", + "pavarur", + "blegtor", + "menaxher", + "sekser", + "valltar", + "kapardisje", + "pretor", + "bastvenes", + "peshkop", + "kopshtar", + "pergjegjes", + "shkarth", + "vizore", + "zanaci", + "grip", + "para", + "funksionar", + "floktar", + "gazetar", + "pajtues", + "interpretues", + "prij\u00ebse", + "sekonda", + "master", + "president", + "manaxhues", + "kopshtare", + "bajraktar", + "ballamar", + "krekosje", + "p\u00ebrmbush\u00ebs", + "kolonel", + "bashkiak", + "infermiere", + "vullnetar", + "rabin", + "komandanti", + "man", + "ushtarak", + "autori", + "ushtar", + "shef", + "valltare", + "karrondreq\u00ebs", + "titullar", + "minist\u00ebr", + "shit\u00ebs", + "asistentt", + "gatuaj", + "bankier", + "autor", + "arkeologe" + ], + "ORG": [ + "komonuelthi", + "kundershtim", + "wicca", + "jan_mayen", + "masmedia", + "\u00e7am\u00e7ak\u00ebzi", + "qendr\u00ebs_tregtare", + "bollywood", + "drejt\u00ebsi", + "partia_naziste", + "ju_b\u00ebft\u00eb_mir\u00eb", + "san_francisco", + "komuniteti_shkenca_krishtere", + "kundershtar", + "va", + "e_drejta_civile", + "ligj_civil", + "agostini", + "post\u00eb", + "masa_mbrojt\u00ebse", + "bashkim_profesional", + "ai", + "gop", + "lumi_huang_he", + "porta_e_lart\u00eb", + "dia", + "sht\u00ebpia_e_bardh\u00eb", + "i_zoti", + "gestapo", + "koktej_frutash", + "grupmosh\u00eb", + "kush", + "makiazh", + "partia_republikane", + "po", + "mossad", + "forca_ajrore", + "shtetet_e_bashkuara_t\u00eb_amerik\u00ebs", + "aya_sofia", + "takim_social", + "iluminizmi", + "los_angeles", + "nato", + "tregu_i_zi", + "deti_i_kuq", + "mi", + "sh\u00ebn_nikolla", + "sa", + "opozite", + "borgjezi", + "bukuroshja_e_fjetur", + "opozicion", + "kolegj", + "partia_konservatore_e_mbret\u00ebris\u00eb_s\u00eb_bashkuar", + "kundert", + "gangster\u00eb", + "komercializ\u00ebm" + ], + "FOOD": [ + "gingiv\u00eb", + "desert", + "kurmagjak", + "capsicum", + "shkret\u00ebtir\u00eb", + "salc\u00eb", + "sill\u00eb", + "past\u00eb", + "chipsy", + "shkret\u00ebtira" + ], + "TITLE": [ + "mister" + ], + "GPE": [ + "pjetri", + "shvarcvalldi", + "kryqi_i_kuq", + "ajasofja", + "shpirti_i_shenjt\u00eb", + "gjergji", + "sh\u00ebn_kolli", + "sh\u00ebn_sofia", + "bes\u00eblidhja_e_re", + "parku_industrial", + "vinh_long", + "drejtat_e_njeriut" + ], + "LAW": [ + "e_drejta_civile", + "kushtetut\u00eb", + "zyra_federative_e_hetimit_amerikan", + "e_drejte" + ], + "PERSON_PRONOUN": [ + "minier\u00eb", + "i", + "me" + ], + "PRODUCT": [ + "justin_bieber", + "ati_yn\u00eb", + "kavie", + "autoblinda", + "baba_dimri", + "mir\u00ebm\u00ebngjes", + "deutsche_welle", + "sh\u00ebn_elena", + "the_hitchhiker's_guide_to_the_galaxy", + "nordrhein_westfalen", + "pema_e_vitit_t\u00eb_ri", + "t\u00eb_drejtat_e_njeriut" + ], + "POLITICAL_PARTY": [ + "partia_demokratike", + "partia_whig", + "kundershtim", + "kundershtar", + "partia_demokratike_republikane", + "partia_demokratike_e_italis\u00eb", + "kundert" + ], + "RACE": [ + "anglez\u00ebt", + "turk", + "hebr\u00e9", + "latin", + "afrikan", + "franceze", + "korean", + "francez", + "vendas" + ], + "SOC_ECO_CLASS": [ + "agrikultur\u00eb", + "samuraj", + "piketoj", + "fuqi_pun\u00ebtore", + "proletariat", + "shinobi", + "borgjezi", + "bujari", + "shtesa_e_mesme" + ], + "DISEASE": [ + "vithisje", + "maturim", + "salmonela", + "murmurij", + "anestezia", + "mossukses", + "progeria", + "mouse", + "shushurij", + "kancer", + "k\u00ebputje", + "dhimbja", + "kollitem", + "kall\u00ebp", + "murtaja", + "shpirr\u00eb", + "para", + "telash", + "likenet", + "parregullsi", + "cenoj", + "poliomieliti", + "strabizmi", + "plok\u00eb", + "shkrumboj", + "listerioza", + "f\u00ebrkoj", + "gimp", + "murtaj\u00eb", + "shtatz\u00ebn\u00ebsi", + "turp\u00ebrohem", + "gangren\u00eb", + "shtatz\u00ebnia", + "kapsll\u00ebk", + "psikonevroz\u00eb", + "thumbim", + "materializmi", + "teshtij", + "ve_n\u00eb_nj\u00eb_nivel", + "stigmata", + "kanceri", + "demenca", + "mi", + "sting", + "papajtueshm\u00ebri", + "marezi", + "teshtima", + "morth", + "pengim", + "i_s\u00ebmur\u00eb", + "le", + "verdh\u00ebza", + "malaria", + "hutoj" + ], + "QUANTITY": [ + "autopark", + "drit\u00ebviti", + "dollari", + "ton", + "dollar", + "franga_zvicerane", + "g" + ], + "FAC": [ + "pishin\u00eb", + "atakama", + "mall", + "post\u00eb", + "sh\u00ebn_lu\u00e7ia", + "pjetri_i_madh", + "institucion_edukimi", + "kisha_katolike" + ], + "RELIGION_MEMBER": [ + "mulla", + "myslimani", + "mormon", + "krishter\u00eb", + "budist" + ], + "RELIGION": [ + "selefizmi", + "islam", + "wicca" + ], + "PERSON": [ + "al_gore", + "rudolf_hess" + ], + "LANGUAGE": [ + "lithuishte", + "pali", + "rafinoj", + "kinez", + "hindi", + "danisht", + "esperanto", + "i_shesht\u00eb", + "tonga" + ], + "DATE": [ + "nataliteti", + "i_rrituri", + "mesjeta", + "the_golden_years" + ], + "GENDER": [ + "mashkull", + "plako", + "gruaja", + "man" + ], + "EVENT": [ + "i_zgjuar_nga_gjumi" + ], + "OTHER_PRONOUN": [ + "them" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "baronesh\u00eb": "baron", + "nuse": "kujdes_estetik", + "person_fem\u00ebror": "mashkull", + "fem\u00ebr": "nj\u00ebri", + "heroina": "trim", + "zonj\u00eb": "efendi", + "prindi_femer": "prind_mashkull", + "nervozoj": "prind_mashkull", + "princesh\u00eb": "princ", + "mbret\u00ebresh\u00eb": "mbret", + "mot\u00ebr": "v\u00eblla", + "njerk\u00eb": "njerk", + "kamariere": "kamarier", + "kameriere": "kamerier", + "feme": "mashkull", + "gruaja": "man", + "fem\u00ebr_e_rritur": "man", + "mace": "nj\u00ebri" + }, + "other_gender_swap": {}, + "en_pronoun2gender": { + "they": [ + "dygjinish\u00ebm" + ], + "he": [ + "djalosh", + "\u00e7un", + "mashkull", + "plako", + "man", + "zot\u00ebri", + "person_mashkull", + "nj\u00ebri", + "individ" + ], + "she": [ + "fem\u00ebr", + "fem\u00ebr_e_rritur", + "munges\u00eb", + "mace", + "zonjush\u00eb", + "zonjushe", + "femer", + "zonjushe_e_re", + "pamjaftueshm\u00ebri", + "grua_e_re", + "gruaja", + "feme", + "zonj\u00eb", + "vajz\u00eb", + "dam\u00eb", + "person_fem\u00ebror", + "goce", + "vog\u00eblush\u00eb", + "madam" + ] + }, + "en_pronoun2pronoun": { + "he": [ + "tij" + ], + "they": [ + "them", + "ils", + "atyre" + ], + "it": [ + "lum", + "kjo", + "ky", + "hyn" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/srn.json b/data_tooling/pii_processing/ontology/data/srn.json new file mode 100644 index 0000000..ce9685b --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/srn.json @@ -0,0 +1,79 @@ +{ + "PLANT": [ + "furu" + ], + "PUBLIC_FIGURE": [ + "bari", + "krin" + ], + "JOB": [ + "don", + "man" + ], + "ORG": [ + "oni", + "sa" + ], + "DISEASE": [ + "grati", + "tan" + ], + "ANIMAL": [ + "sabaku", + "kindi" + ], + "PERSON_PRONOUN": [ + "we", + "noso" + ], + "SOC_ECO_CLASS": [ + "waki" + ], + "QUANTITY": [ + "keti" + ], + "GENDER": [ + "man" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "woy": "omu", + "frow": "man" + }, + "other_gender_swap": {}, + "en_pronoun2gender": { + "he": [ + "omu", + "man" + ], + "she": [ + "woy", + "frow" + ] + }, + "en_pronoun2pronoun": { + "he": [ + "sibi", + "iya", + "neki" + ], + "she": [ + "sibi", + "iya" + ], + "it": [ + "sibi" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/st.json b/data_tooling/pii_processing/ontology/data/st.json new file mode 100644 index 0000000..e68db8b --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/st.json @@ -0,0 +1,66 @@ +{ + "DISEASE": [ + "robala", + "tlhokofatso" + ], + "JOB": [ + "molemi", + "moeletsi", + "lepolesa", + "rameriana", + "molepi", + "moruti", + "sebini", + "modulasetulo" + ], + "RELIGION_MEMBER": [ + "moselamose" + ], + "GENDER": [ + "moshemane", + "mosadi" + ], + "ANIMAL": [ + "ho_tsamaea_thupa" + ], + "PLANT": [ + "khabetjhe", + "kholifolawa" + ], + "ORG": [ + "ke_a_go_rata" + ], + "LANGUAGE": [ + "seburu", + "se_french" + ], + "FOOD": [ + "mofihlolo" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "lefetwa": "lesoha" + }, + "other_gender_swap": {}, + "en_pronoun2gender": { + "he": [ + "moshemane" + ], + "she": [ + "mosadi", + "ausi" + ] + }, + "en_pronoun2pronoun": {}, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/stq.json b/data_tooling/pii_processing/ontology/data/stq.json new file mode 100644 index 0000000..e8583da --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/stq.json @@ -0,0 +1,46 @@ +{ + "JOB": [ + "biskop", + "man" + ], + "PLANT": [ + "alhouden", + "klokkebloume" + ], + "ORG": [ + "skoule" + ], + "GENDER": [ + "man" + ], + "ANIMAL": [ + "lidef\u00e4ite" + ], + "RELIGION_MEMBER": [ + "mon" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": {}, + "other_gender_swap": {}, + "en_pronoun2gender": { + "he": [ + "man" + ] + }, + "en_pronoun2pronoun": { + "they": [ + "has" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/su.json b/data_tooling/pii_processing/ontology/data/su.json new file mode 100644 index 0000000..5495b22 --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/su.json @@ -0,0 +1,234 @@ +{ + "DISEASE": [ + "kangker", + "polio", + "kotomb\u00e9", + "kaligata", + "beubeuritan", + "gondok", + "cacar", + "talas\u00e9mia", + "pites", + "tai_hiang", + "golak", + "sal\u00e9sma", + "parametritis", + "kulem", + "gogot", + "beurit", + "totomb\u00e9", + "malaria" + ], + "GENDER": [ + "bikang", + "wanoja" + ], + "JOB": [ + "guru", + "pajurit", + "dalem", + "tangtara", + "walikota", + "pagarbagus", + "gegendir" + ], + "PUBLIC_FIGURE": [ + "che_guevara", + "johannes_diderik_van_der_waals", + "karl_landsteiner", + "edwin_hubble", + "richard_wagner", + "marie_curie", + "michael_jackson", + "galileo_galilei", + "edmund_hillary", + "vincent_van_gogh", + "louis_pasteur", + "y", + "f", + "james_dean", + "pete_seeger", + "johannes_kepler", + "max_planck", + "arthur_compton", + "niels_bohr", + "michael_faraday", + "walt_disney", + "phil_collins", + "alfred_nobel", + "marco_polo", + "daniel_bernoulli", + "joseph_henry", + "pablo_picasso", + "karl_marx", + "friedrich_nietzsche", + "i", + "adolf_hitler", + "fritz_haber", + "g", + "christopher_columbus", + "r", + "alexandre_dumas", + "peter_o'toole", + "john_lennon", + "charlie_chaplin", + "james_watt", + "ronald_reagan", + "ernest_hemingway", + "nelson_mandela", + "mohandas_gandhi", + "roald_amundsen", + "johnny_cash", + "mick_jagger", + "kahlil_gibran", + "albert_einstein", + "t" + ], + "PLANT": [ + "sampeu", + "pines", + "calingcing", + "bangkuang", + "kawung", + "cendrawasih", + "ki_urat", + "lokatmala", + "leunca", + "kananga", + "bijanggut", + "hanjeli", + "blackberry", + "saroja", + "jamb\u00e9" + ], + "RELIGION_MEMBER": [ + "guru", + "akang" + ], + "PRODUCT": [ + "justin_bieber", + "nun_ama_di_sawarga", + "selandia_baru", + "s\u00e3o_tom\u00e9_jeung_pr\u00edncipe", + "hanjeli" + ], + "ANIMAL": [ + "titinggi", + "cucunguk", + "galatik", + "mamalia", + "bangkong", + "munding", + "congcorang", + "bangbara", + "hayam", + "japati", + "kuntul" + ], + "ORG": [ + "jan_mayen", + "aa", + "laut_beureum", + "kantor_pos", + "pamar\u00e9ntah", + "winnie_the_pooh", + "atikan", + "saint_barth\u00e9lemy", + "part\u00e9y_buruh_norw\u00e9gia", + "saint_lusia", + "perserikatan_bangsa_bangsa", + "\u1b92\u1b92\u1b94\u1ba6\u1b94\u1baa" + ], + "PERSON_PRONOUN": [ + "araranjeun", + "i", + "he" + ], + "SOC_ECO_CLASS": [ + "sakedik", + "samurai", + "agrikultur" + ], + "FOOD": [ + "endog", + "mumuluk", + "baligo" + ], + "LOCATION": [ + "sint_maarten", + "samudra_hindia", + "tanjung_verd\u00e9", + "joseph_louis_gay_lussac", + "am\u00e9rika_sarikat", + "the_rolling_stones" + ], + "GPE": [ + "sint_maarten", + "pandanus_tectorius" + ], + "QUANTITY": [ + "salawe", + "g" + ], + "RELIGION": [ + "islam" + ], + "UNION": [ + "international_telecommunication_union" + ], + "BIO_CHEM_ENTITY": [ + "polyvinyl_chloride" + ], + "LANGUAGE": [ + "tonga" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "bikang": "jalu", + "t\u00e9t\u00e9h": "akang", + "istri": "buah", + "garwa": "salaki", + "bojo": "salaki", + "pamajikan": "salaki", + "awewe": "buah", + "wanoja": "buah" + }, + "other_gender_swap": { + "he": "huma" + }, + "en_pronoun2gender": { + "he": [ + "buah", + "jalu" + ], + "she": [ + "t\u00e9t\u00e9h", + "istri", + "wanoja", + "awewe", + "bikang" + ] + }, + "en_pronoun2pronoun": { + "he": [ + "he" + ], + "they": [ + "huma" + ], + "it": [ + "iyeu" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/sux.json b/data_tooling/pii_processing/ontology/data/sux.json new file mode 100644 index 0000000..673495d --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/sux.json @@ -0,0 +1,53 @@ +{ + "PERSON_PRONOUN": [ + "\ud808\udcb7\ud808\udc8a" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "\ud808\udea9": "\ud808\udf51", + "\ud808\udea9\ud808\uddb3": "\ud808\udc35" + }, + "other_gender_swap": { + "\ud808\udc49\ud808\ude48\ud808\ude48": "\ud808\udc00\ud808\ude4c", + "\ud808\udc00\ud808\ude48\ud808\ude48": "\ud808\udc00\ud808\ude4c", + "\ud808\udc00\ud808\ude4c": "\ud808\udc49\ud808\ude48\ud808\ude48" + }, + "en_pronoun2gender": { + "he": [ + "\ud808\udf51", + "\ud808\udd97" + ], + "she": [ + "\ud808\udea9", + "\ud808\udda0\ud808\udc96", + "\ud808\udea9\ud808\udf06" + ] + }, + "en_pronoun2pronoun": { + "he": [ + "\ud808\udc00\ud808\ude4c", + "\ud808\uded7" + ], + "she": [ + "\ud808\udc00\ud808\ude4c" + ], + "they": [ + "\ud808\udc00\ud808\ude48\ud808\ude48", + "\ud808\udc49\ud808\ude48\ud808\ude48" + ], + "it": [ + "\ud808\udc49" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/sv.json b/data_tooling/pii_processing/ontology/data/sv.json new file mode 100644 index 0000000..005b1ed --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/sv.json @@ -0,0 +1,4968 @@ +{ + "ANIMAL": [ + "fuchsiaastrild", + "manf\u00e5r", + "listkrokodil", + "kaliforniskt_sj\u00f6lejon", + "alkekung", + "ringtrast", + "lotsfisk", + "svingr\u00e4vling", + "murarbin", + "acherontia", + "spermacetival", + "trollfladdermus", + "tornfalk", + "pottval", + "morisk_landsk\u00f6ldpadda", + "flygekorre", + "vitgumpsvr\u00e5k", + "skrattuggla", + "bordercollie", + "ringduva", + "vandringsalbatross", + "vitsvanshjort", + "buteo", + "sillkung", + "brunbj\u00f6rn", + "bandstj\u00e4rtsduva", + "amazonmyra", + "hornuggla", + "v\u00e4derkvarnspalm", + "savann\u00f6rn", + "brant", + "skogsm\u00f6ss", + "hornv\u00e4rnf\u00e5gel", + "bergand", + "lavendelastrild", + "sambarhjort", + "kalkongam", + "tobisgrissla", + "vattensork", + "k\u00e4rrkanin", + "bergtunga", + "fj\u00e4llr\u00e4v", + "fj\u00e4ll\u00e4mmel", + "vattenhund", + "gr\u00f6nsiska", + "gull\u00f6rn", + "afrikansk_sporrsk\u00f6ldpadda", + "kn\u00f6lsvan", + "agapadda", + "stag", + "vattenmyskdjur", + "heron", + "black_widow", + "sj\u00f6lejon", + "firefox", + "mantelb\u00e4lta", + "silverlax", + "h\u00e4stskokrabba", + "galapagossk\u00f6ldpadda", + "\u00e4rts\u00e5ngare", + "stors\u00e4l", + "arguskalkon", + "inkakakadua", + "sporrvipa", + "indiansidensvans", + "tallbit", + "elliotspett", + "vattenbuffel", + "jakthund", + "brugd", + "sobel", + "dubbeltrast", + "gallsteklar", + "harkling", + "guadalupep\u00e4lss\u00e4l", + "sk\u00e4rfl\u00e4cka", + "starrg\u00e4rdsmyg", + "billy_elliot", + "pungdj\u00e4vul", + "h\u00f6kuggla", + "thomsongasell", + "bl\u00e5kr\u00e5ka", + "stenbock", + "bullocktrupial", + "koltrast", + "murraytorsk", + "stj\u00e4rtand", + "chatta", + "kunduz", + "sommargylling", + "skrattm\u00e5s", + "jordl\u00f6pare", + "ortolansparv", + "silverand", + "kanadar\u00f6ding", + "klappmyts", + "hornlocke", + "hammarhaj", + "regementsf\u00f6rvaltare", + "gr\u00e4shoppsm\u00f6ss", + "djurriket", + "manta", + "talltita", + "l\u00e5nghalsar", + "flygekorrar", + "stormsvala", + "br\u00f6dbagge", + "kaskelot", + "luffarspindel", + "karettsk\u00f6ldpadda", + "karolinaparakit", + "besoarget", + "enkelbeckasin", + "shetlandsponny", + "carduelis", + "knubbs\u00e4l", + "kapuschongskogss\u00e5ngare", + "kanadag\u00e5s", + "hudsonspov", + "aftonstenkn\u00e4ck", + "karminspinnare", + "nashvilleskogss\u00e5ngare", + "grisslybj\u00f6rn", + "spindelapor", + "sadeldelfin", + "vandringsduva", + "p\u00e5skhare", + "taggspjutrocka", + "h\u00e4ger", + "klumpfisk", + "garf\u00e5gel", + "tr\u00e4sksparv", + "milit\u00e4rm\u00e4stare", + "sorgmantel", + "g\u00e5rdvar", + "damagasell", + "minervauggla", + "husspindelfoting", + "signalhund", + "bergsnyala", + "balkanh\u00f6k", + "coloradoskalbagge", + "markbl\u00e5kr\u00e5kor", + "bl\u00e4sand", + "lejonunge", + "styltl\u00f6pare", + "snappsk\u00f6ldpadda", + "tornseglare", + "skogselefant", + "aftonsparv", + "micropterus", + "brudand", + "sparvh\u00f6k", + "tallspett", + "m\u00f6rkhaj", + "rostgumpsvala", + "stortrapp", + "spetsnosh\u00f6rning", + "svalstj\u00e4rtsglada", + "g\u00e4dda", + "grevyzebra", + "fj\u00e4llvr\u00e5k", + "skr\u00e4nt\u00e4rna", + "beringskarv", + "floddelfiner", + "spetsbergsgrissla", + "kn\u00f6lval", + "diamantsk\u00f6ldpadda", + "kvastpiggsvin", + "raven", + "nordamerikansk_gr\u00e4vling", + "homo_sapiens", + "bardvalar", + "eremitskogstrast", + "kappgam", + "bergtofsvaktel", + "dubbelfotingar", + "skensmultron", + "mink", + "jordekorre", + "vattenpipl\u00e4rka", + "fasansporrg\u00f6k", + "savannelefant", + "huvudlus", + "rankfotingar", + "artropod", + "mandarinand", + "\u00f6rons\u00e4l", + "stenh\u00f6na", + "davidshjort", + "strumpebandssnok", + "sandhajar", + "jordekorrar", + "gerbillus_jamesi", + "skorpiongift\u00f6dla", + "granj\u00e4rpe", + "the_crow", + "mantisr\u00e4kor", + "aldabrask\u00f6ldpadda", + "flygfiskar", + "visent", + "tornuggla", + "trumpetartrana", + "gr\u00e4vling", + "ledarhund", + "\u00e4ngsh\u00f6k", + "broklorikit", + "stor_sk\u00e5lsn\u00e4cka", + "rapph\u00f6n\u00e4", + "namaquaspett", + "tobaksmosaikvirus", + "gummiboa", + "indisk_pansarnosh\u00f6rning", + "myskanka", + "spatserk\u00e4pp", + "sott\u00e4rna", + "mj\u00f6lkboskap", + "humlesuga", + "bengalisk_tiger", + "tennesseeskogss\u00e5ngare", + "gr\u00e5hakedopping", + "\u00e4ngspipl\u00e4rka", + "marter", + "paradisparakit", + "lastdjur", + "skratth\u00e4rf\u00e5glar", + "saguarospett", + "trastar", + "kanadasik", + "stillahavstorsk", + "sanktpersfisk", + "sillval", + "kortvingar", + "kejsarpingvin", + "kejsarg\u00e5s", + "kamskrake", + "chacmababian", + "assapan", + "pallasskarv", + "blindhund", + "kronhjort", + "mess\u00e5ngare", + "roskarl", + "taggmakrill", + "gr\u00f6nlandsval", + "stenm\u00e5rd", + "str\u00e5lsk\u00f6ldpadda", + "honkatt", + "banteng", + "sparvfalk", + "nunneastrild", + "faraokatt", + "vargspindlar", + "cockerspaniel", + "rubinkolibri", + "n\u00e4sselfj\u00e4ril", + "bananfluga", + "lilla_hunden", + "helveteseld", + "svang\u00e5s", + "stor_hammarhaj", + "douglasekorre", + "pinctada_margaritifera", + "saltvattenskrokodil", + "rosenstare", + "silverapa", + "eubakterie", + "punaflamingo", + "fenknot", + "gyllingar", + "deltakrokodil", + "dolksvans", + "vattenrall", + "virginiauv", + "fj\u00e4llr\u00f6ding", + "sumpn\u00e4bbmus", + "sandloppa", + "baltimoretrupial", + "skogssork", + "brunalger", + "iller", + "alligatorsk\u00f6ldpadda", + "sj\u00f6borrar", + "kardinaltetra", + "halsbandsparakit", + "polarhare", + "afrikansk_klogroda", + "sillgrissla", + "lappuggla", + "stormsvalor", + "islandsknipa", + "gonokocker", + "beckasin", + "drottningmoder", + "berner_sennenhund", + "brock", + "\u00e5kersparv", + "darr\u00e5l", + "hjorthane", + "sj\u00f6gurkor", + "eskim\u00e5spov", + "hjort", + "skorstensseglare", + "trubbnosh\u00f6rning", + "corallium_rubrum", + "trumpetarsvan", + "gamar", + "skogsm\u00e5rd", + "vildh\u00e4st", + "sj\u00f6gurka", + "skogsh\u00f6ns", + "kedjepickerell", + "dragh\u00e4st", + "piparsn\u00e4ppa", + "korpgam", + "hornlunne", + "komodovaran", + "kongop\u00e5f\u00e5gel", + "bj\u00f6rnspinnarlarv", + "ammospermophilus", + "ictiobus_niger", + "schabraktapir", + "backsvala", + "borneoguldkatt", + "wilsonbeckasin", + "bredn\u00e4sor", + "sj\u00f6h\u00e4st", + "vildg\u00e5s", + "hussvala", + "bj\u00f6rnunge", + "palmduva", + "rosenskedstork", + "bergsgorilla", + "sabelantilop", + "groda", + "bisamand", + "styltsn\u00e4ppa", + "eremitkr\u00e4fta", + "skrikuvar", + "mullvadssyrsa", + "rundbladloppor", + "r\u00f6dbraxen", + "storharkrankar", + "gr\u00f6nlandss\u00e4l", + "steglits", + "kvinnotjusare", + "berguv", + "prutg\u00e5s", + "marsvin", + "svinmakak", + "dragdjur", + "sj\u00f6borre", + "ringsvanslemur", + "hjortdjur", + "stora_leverflundran", + "sk\u00f6ldl\u00f6ss", + "citronhaj", + "\u00e5kerh\u00f6na", + "geting", + "amazonklippf\u00e5gel", + "hasselmus", + "kafferbuffel", + "tapetmal", + "vandringstrast", + "bandstyltl\u00f6pare", + "glas\u00f6rtskaktus", + "huskatt", + "stubbkv\u00e4kare", + "r\u00f6dalger", + "skogsn\u00e4tfj\u00e4ril", + "mantis", + "h\u00e4stmyror", + "b\u00e4lteskungsfiskare", + "koppar\u00f6dla", + "beringtejst", + "grindval", + "vessla", + "amiralfj\u00e4ril", + "polarvarg", + "bardval", + "gr\u00e4ssnok", + "javanosh\u00f6rning", + "wilsonsimsn\u00e4ppa", + "\u00e4ngsp\u00e4rlemorfj\u00e4ril", + "murarbi", + "tornugglor", + "hornpelikan", + "polishund", + "bergzebra", + "gules\u00e4ck", + "maraboustork", + "barramundi", + "cooperh\u00f6k", + "amhaj", + "f\u00e4lthare", + "s\u00e4lgskimmerfj\u00e4ril", + "gr\u00f6ns\u00e5ngare", + "ljungpipare", + "eagle", + "vildget", + "dubbelbeckasin", + "bonit", + "p\u00e5skehare", + "t\u00f6rnastrild", + "kamr\u00e5ttor", + "myskand", + "husarapa", + "gyllensparv", + "stj\u00e4rnmullvad", + "brunand", + "storlabb", + "f\u00e5gelhund", + "vattenmockasin", + "sandkrypare", + "borneoorangutang", + "kondor", + "n\u00e4sapa", + "silverm\u00e5s", + "hammarhajar", + "vakthund", + "sv\u00e4rdst\u00f6r", + "skogsmus", + "strandpadda", + "pansarkrokodil", + "hattapa", + "gumsill", + "peristediidae", + "mississippialligator", + "eider", + "sandkatt", + "gouldsamadin", + "borstb\u00e4lta", + "elfenbensn\u00e4bb", + "vandrarmussla", + "pilgrimsfalk", + "brunr\u00e5tta", + "kapspringare" + ], + "PUBLIC_FIGURE": [ + "lawrence_durrell", + "henry_cavendish", + "matthew_arnold", + "tanasj\u00f6n", + "lev_ivanov", + "benjamin_franklin", + "martin_buber", + "akira_kurosawa", + "frances_wright", + "maria_tallchief", + "noah_webster", + "jean_genet", + "john_knox", + "heinrich_hertz", + "roger_williams", + "giovanni_boccaccio", + "cornelius_vanderbilt", + "rudolf_steiner", + "thomas_wolfe", + "thomas_bayes", + "ben_hogan", + "johann_bernoulli", + "max_bruch", + "charles_best", + "leonard_bernstein", + "mj\u00f6lnare", + "och_s\u00e5_vidare", + "che_guevara", + "georges_simenon", + "c", + "thomas_hodgkin", + "riket", + "john_barth", + "edward_albee", + "dorothy_parker", + "maria_callas", + "william_walton", + "henrik_ibsen", + "morgan", + "sergej_rachmaninov", + "mary_shelley", + "franz_werfel", + "marcello_malpighi", + "peter_lorre", + "karl_baedeker", + "linbana", + "david_livingstone", + "eduard_buchner", + "david_smith", + "john_herschel", + "henry_villard", + "andrzej_wajda", + "jan_van_eyck", + "carl_rogers", + "george_balanchine", + "georg_wilhelm_steller", + "richard_burton", + "bergkolibri", + "douglas_macarthur", + "james_michener", + "mary_wollstonecraft", + "j_edgar_hoover", + "maria_magdalena", + "thomas_reid", + "john_jacob_astor", + "anna_pavlova", + "winston_churchill", + "gustav", + "johannes_diderik_van_der_waals", + "giambattista_marini", + "longinos", + "s\u00f6dra_fisken", + "b", + "conrad_aiken", + "karl_landsteiner", + "ivan_pavlov", + "paul_mccartney", + "tr\u00e4sked", + "richard_smalley", + "skogsvetare", + "andrew_marvell", + "terry_pratchett", + "k", + "stephen_king", + "francis_crick", + "john_trumbull", + "sherry", + "joseph_greenberg", + "isaac_newton", + "victor_hugo", + "joseph_smith", + "edwin_hubble", + "dr\u00f6mprins", + "milton_friedman", + "inge", + "amy_lowell", + "edward_gibbon", + "jefferson_davis", + "saint_louis", + "cass_gilbert", + "george_stephenson", + "john_glenn", + "john_webster", + "john_davis", + "george_burns", + "george_harrison", + "peter_minuit", + "halmt\u00e4ckare", + "george_orwell", + "ronald_norrish", + "georg_meissner", + "arthur_koestler", + "richard_wagner", + "williams", + "storvesir", + "bengt", + "g\u00e4rdsmygar", + "thornton_wilder", + "pancho_villa", + "leopold_stokowski", + "michail_barysjnikov", + "marie_curie", + "francis_galton", + "mary_martin", + "michael_jackson", + "carl_sandburg", + "aristarchos", + "thomas_hobbes", + "charles_louis_de_secondat_montesquieu", + "f\u00f6redetting", + "el_greco", + "samuel_beckett", + "robert_a_millikan", + "david", + "galileo_galilei", + "ernest_bevin", + "lejonkula", + "jane_goodall", + "john_donne", + "chaim_weizmann", + "andrea_guarneri", + "robert_koch", + "joseph_goebbels", + "george_eastman", + "john_steinbeck", + "erich_mendelsohn", + "catherine", + "petrus", + "c_northcote_parkinson", + "edmund_hillary", + "vincent_van_gogh", + "richard_hooker", + "william_hazlitt", + "marie_stopes", + "anne_boleyn", + "josef_stalin", + "john_ruskin", + "robert_burns", + "john_henry", + "carl_anderson", + "skogsbrukare", + "thomas_paine", + "bari", + "1st_armoured_division", + "francis_beaumont", + "edvard", + "steven_weinberg", + "mary_pickford", + "hans_fischer", + "emiliano_zapata", + "elisabet", + "karl_barth", + "willem_einthoven", + "thomas_willis", + "bernard_malamud", + "samuel_johnson", + "jesus", + "allen_iverson", + "marie_antoinette", + "lennart", + "giuseppe_verdi", + "walter_lippmann", + "e", + "karl_jaspers", + "beethoven", + "jamesbukten", + "hideki_yukawa", + "konrad_adenauer", + "antoni", + "john_l_lewis", + "bush", + "norbert_wiener", + "john_masefield", + "miguel_cervantes", + "mark_rothko", + "maurice_chevalier", + "gottlieb_daimler", + "jakobsbrevet", + "von_willebrands_faktor", + "frank_sinatra", + "abel_tasman", + "katharine_hepburn", + "henri_becquerel", + "henri_matisse", + "louis_pasteur", + "ta_sitt_liv", + "richard_strauss", + "leslie_howard", + "theodosius_i", + "hugo_grotius", + "mahalia_jackson", + "ben_shahn", + "john_ford", + "stephen_foster", + "alphonse_bertillon", + "laurits", + "katherine_mansfield", + "gertrude_stein", + "saladin", + "sarah_bernhardt", + "philip_marlowe", + "luigi_pirandello", + "marc_blitzstein", + "hank_williams", + "rube_goldberg", + "dorothea_lange", + "james_thurber", + "charles_de_gaulle", + "paul_von_hindenburg", + "y", + "henry_moore", + "\u00f6rnen", + "holden", + "mary_mallon", + "ralph_bunche", + "rudolf_bultmann", + "charles_lindbergh", + "vincenzo_bellini", + "samuel_barber", + "tobias_smollett", + "f", + "john_jay", + "ludwig_wittgenstein", + "august_strindberg", + "thomas_mann", + "william_ockham", + "alla_nazimova", + "charles_goodyear", + "dante_alighieri", + "margot_fonteyn", + "peter_pan", + "james_tobin", + "john_irving", + "samuel_de_champlain", + "giacomo_puccini", + "edward_fitzgerald", + "fridtjof_nansen", + "louis_braille", + "herbert_marcuse", + "mungo_park", + "benedict_arnold", + "m\u00e4nniskor", + "paul_verlaine", + "q", + "robert_johnson", + "james_dean", + "robert", + "roger_bannister", + "theodor_schwann", + "max_beerbohm", + "alessandro_manzoni", + "henrik", + "donald_budge", + "joseph_priestley", + "hal", + "nicolas_poussin", + "andrea_mantegna", + "sotare", + "joseph_pulitzer", + "ring_lardner", + "george_huntington", + "jim_corbett", + "james_naismith", + "oscar_wilde", + "philip_roth", + "henry", + "lawrence", + "kuria", + "skogsm\u00e4stare", + "richard_trevithick", + "william_bradford", + "heinrich_schliemann", + "eli_whitney", + "milit\u00e4rm\u00e4stare", + "glenn_curtiss", + "don_quijote", + "tandfe", + "laurence_olivier", + "georg", + "pierre_larousse", + "christiaan_eijkman", + "andrej_sacharov", + "adolf_eichmann", + "marilyn_horne", + "francis_bacon", + "pete_seeger", + "walter_hess", + "john_wycliffe", + "joseph_heller", + "a", + "morris", + "norman_rockwell", + "james_brown", + "william_hogarth", + "charles_baudelaire", + "luigi_cherubini", + "david_ricardo", + "g\u00f6ran", + "henri_labrouste", + "mary_leakey", + "hoppas", + "aleksandr_protjorov", + "charlie_parker", + "immanuel_kant", + "richard_gatling", + "brigadgeneral", + "james_franck", + "william_crookes", + "james_meredith", + "samuel_gompers", + "nellie_bly", + "weber", + "alexandre_yersin", + "octavius", + "stephen_leacock", + "albert_schweitzer", + "johann_friedrich_herbart", + "giulio_natta", + "saint_martin", + "titus", + "johannes_kepler", + "william_s_burroughs", + "david_hartley", + "max_planck", + "william_blake", + "julio_iglesias", + "john_bardeen", + "arthur", + "sarah_vaughan", + "john_wilkes", + "praktejder", + "william_byrd", + "christopher_fry", + "scott_joplin", + "carl_lewis", + "sarah_siddons", + "george_vancouver", + "canberra", + "michail_kalinin", + "elias_canetti", + "edward_jenner", + "john_mercer", + "oscar_robertson", + "oliver_hardy", + "cole_porter", + "benjamin_west", + "jean_luc_godard", + "konstantin", + "graham_greene", + "frans_hals", + "edward", + "lars_onsager", + "margaret_mitchell", + "stuart_davis", + "lola_montez", + "jan_swammerdam", + "mary_mccarthy", + "john_walker", + "william_herschel", + "joseph_black", + "arthur_rubinstein", + "arthur_compton", + "niels_bohr", + "kenneth_grahame", + "henry_fielding", + "bertrand_russell", + "katherine_anne_porter", + "michael_faraday", + "john_d_rockefeller", + "anthony_burgess", + "jan_tinbergen", + "robert_venturi", + "greg", + "irving_berlin", + "bernard_baruch", + "rudolf_diesel", + "walt_disney", + "ben_jonson", + "peter", + "h_l_mencken", + "joseph_schumpeter", + "gabriel_lippmann", + "steve_reich", + "lee", + "benny_goodman", + "ted_williams", + "friedrich_engels", + "jane_austen", + "charles_laughton", + "gustav_mahler", + "ed_sullivan", + "phil_collins", + "alice_paul", + "robert_redford", + "jean_giraudoux", + "jack_dempsey", + "ian_fleming", + "richard_feynman", + "wolfgang_pauli", + "theodore_dreiser", + "theodor_mommsen", + "marcel_proust", + "jessica_mitford", + "thomas_more", + "homo_heidelbergensis", + "paul_hindemith", + "elizabeth_taylor", + "thomas_chippendale", + "anne_sullivan", + "paul_robeson", + "arnold", + "thomas_middleton", + "a_till_\u00f6", + "john_dowland", + "greger", + "hans_krebs", + "daniel_jones", + "william_golding", + "robert_motherwell", + "jesus_kristus", + "william_caxton", + "john_milton", + "peter_stuyvesant", + "ethel_merman", + "frank_baum", + "samuel_adams", + "albert_speer", + "james_baldwin", + "valentina_teresjkova", + "john_vanbrugh", + "indira_gandhi", + "jane_seymour", + "george_gershwin", + "alberto_giacometti", + "frank_whittle", + "alfred_nobel", + "jesse_owens", + "stripp", + "marco_polo", + "john_fletcher", + "caravaggio", + "charlie_watts", + "john_northrop", + "m", + "charlotte_corday", + "marcel_marceau", + "allen_ginsberg", + "fred_zinnemann", + "daniel_bernoulli", + "guillaume_apollinaire", + "antoine_watteau", + "brandt", + "pablo_casals", + "joseph_henry", + "henri_bergson", + "antonius", + "edward_macdowell", + "josef_hoffmann", + "sinnessvag", + "boris_karloff", + "pierre_corneille", + "phillis_wheatley", + "patrick_white", + "saul_steinberg", + "bartholomew_roberts", + "peter_cooper", + "william_morris", + "cary_grant", + "hideyo_noguchi", + "thomas", + "friedrich_hegel", + "isaac_watts", + "pieter_zeeman", + "glenn_miller", + "pablo_picasso", + "marian_anderson", + "natalie_wood", + "l_ron_hubbard", + "thomas_moore", + "osman_i", + "kurt_weill", + "otto_hahn", + "lester_young", + "otto_meyerhof", + "john_marshall", + "christiaan_huygens", + "hector_berlioz", + "svinmakak", + "lucille_ball", + "paul_simon", + "claudio_monteverdi", + "benjamin_jowett", + "robert_scott", + "john_galsworthy", + "robert_robinson", + "o", + "adam_smith", + "william_james", + "u", + "jean_harlow", + "henry_miller", + "karl_marx", + "paul_bunyan", + "friedrich_nietzsche", + "i", + "robert_indiana", + "jimmy_durante", + "john_wesley", + "sandro_botticelli", + "carson_mccullers", + "seiji_ozawa", + "nikola_tesla", + "al_capone", + "charles_barkley", + "billy_graham", + "robert_schumann", + "mel_gibson", + "le_corbusier", + "statschef", + "carlo_goldoni", + "lankes", + "john_locke", + "alexis_carrel", + "joseph_marie_jacquard", + "henry_james", + "stephen_sondheim", + "r\u00f6dluvan", + "oscar_hammerstein", + "lorenz_hart", + "christofer_columbus", + "helen_keller", + "paul_dukas", + "ingrid_bergman", + "anna_kurnikova", + "leonard_bloomfield", + "jane_jacobs", + "jean_piaget", + "william_congreve", + "j\u00f6rgen", + "franz_kline", + "henri_rousseau", + "paul_tillich", + "hilaire_belloc", + "konsthandlare", + "gustaf", + "frank_norris", + "frank_stella", + "robert_southey", + "walt_whitman", + "william_wyler", + "john_osborne", + "colin_powell", + "ludwig_boltzmann", + "carl_nielsen", + "chopin", + "leopold_kronecker", + "richard_wright", + "benjamin_thompson", + "adolf_hitler", + "maria_mitchell", + "fritz_haber", + "archibald_macleish", + "peter_behrens", + "alfred_stieglitz", + "joseph_haydn", + "stephen_spender", + "george_boole", + "hans_reiter", + "paul_revere", + "lewiskulspruta", + "inte_till\u00e4mpbar", + "daniel_boone", + "buffalo_bill", + "edvard_grieg", + "robert_boyle", + "arthur_laffer", + "edith_cavell", + "alan_paton", + "ralph_richardson", + "1", + "cordell_hull", + "james_wilson", + "rosa_parks", + "tomas", + "norman_jewison", + "samuel_goldwyn", + "x", + "ernest_walton", + "vladimir_putin", + "giuseppe_mazzini", + "jim_thorpe", + "hertz", + "h", + "randall_jarrell", + "andersson", + "arnold_sch\u00f6nberg", + "laurence_sterne", + "jacqueline_cochran", + "george_fox", + "ben_hecht", + "christopher_isherwood", + "fritz_kreisler", + "anne_hathaway", + "katarina", + "david_garrick", + "bill_russell", + "william_thackeray", + "baldwin", + "jeannette_rankin", + "nyman", + "charles_lamb", + "harry", + "g", + "anthony_comstock", + "arthur_schopenhauer", + "thomas_dekker", + "james_cagney", + "john_keble", + "henri_pitot", + "wanda_landowska", + "martin_heidegger", + "hans_eysenck", + "marinera", + "h.c_andersen", + "muller", + "r", + "george_lucas", + "andrew_jackson", + "edith_wharton", + "louis_armstrong", + "antony_tudor", + "steven_spielberg", + "jean_monnet", + "leonard", + "robert_fulton", + "thomas_hardy", + "eddie_rickenbacker", + "thomas_gainsborough", + "giuseppe_garibaldi", + "robert_brown", + "thomas_carlyle", + "donald_barthelme", + "william_tyndale", + "tamara_karsavina", + "bobby_fischer", + "johannes_gutenberg", + "d", + "james_bowie", + "gaetano_donizetti", + "william_faulkner", + "johannes_eckhart", + "andre", + "amerigo_vespucci", + "arthur_holmes", + "pierre_boulez", + "lars", + "girolamo_savonarola", + "emma_goldman", + "robert_gray", + "francis_poulenc", + "james_ussher", + "john_barrymore", + "john_constable", + "james_mill", + "putin", + "matthew_flinders", + "robert_herrick", + "joseph_campbell", + "jean_de_la_fontaine", + "robert_hooke", + "o_henry", + "karl_popper", + "alfred", + "coleman_hawkins", + "george_sand", + "peter_sellers", + "charles_fourier", + "john_mcgraw", + "henry_clay", + "marcus_aurelius", + "peter_o'toole", + "joseph_conrad", + "kenneth_roberts", + "peter_paul_rubens", + "mahatma_gandhi", + "jim_morrison", + "jules_verne", + "paul_newman", + "george_meredith", + "robert_morris", + "woody_herman", + "philip_w_anderson", + "josef_albers", + "jackson_pollock", + "minustecken", + "john_lennon", + "andrea_palladio", + "bob_woodward", + "charlie_chaplin", + "lillian_russell", + "robert_woodward", + "thomas_malory", + "lea", + "john_brown", + "al_jolson", + "elizabeth_gaskell", + "john_mill", + "hugo_junkers", + "norman_thomas", + "lillian_hellman", + "john_macleod", + "thomas_merton", + "asa_gray", + "hannah_arendt", + "antonio_stradivari", + "reklamformgivare", + "maximianus", + "robinson_jeffers", + "alice_walker", + "miles_davis", + "edmund_cartwright", + "wilhelm_tell", + "harold_nicolson", + "jesse_jackson", + "willa_cather", + "stanley_kubrick", + "edvard_martyren", + "john_deere", + "john_huston", + "william_gilbert", + "james_watt", + "stats\u00f6verhuvud", + "jonathan_edwards", + "ronald_reagan", + "helmut_schmidt", + "jenny_lind", + "homo", + "frederick_douglass", + "david_hilbert", + "wilhelm_reich", + "roman_jakobson", + "oliver_cromwell", + "lionel_hampton", + "martin_luther_king", + "james_hargreaves", + "frank_capra", + "william_wordsworth", + "rex_harrison", + "s", + "william_clark", + "woodrow_wilson", + "william_wycherley", + "margaret_sanger", + "gustav_hertz", + "george_mason", + "george_wallace", + "el_cid", + "marcus_antonius", + "agrippina", + "richard_rodgers", + "don_quixote", + "anne_sexton", + "edvard_bek\u00e4nnaren", + "john_dryden", + "jim_henson", + "frank", + "ernest_hemingway", + "john_eccles", + "george_westinghouse", + "aquila", + "jacques_charles", + "eero_saarinen", + "arthur_miller", + "john_cheever", + "gracie_allen", + "nelson_mandela", + "heinrich_himmler", + "al_gore", + "john_rutledge", + "hans_bethe", + "hans_geiger", + "nicklaus", + "cesare_borgia", + "roald_amundsen", + "sherwood_anderson", + "richard_leakey", + "alfred_korzybski", + "seglare", + "anton", + "charles_dickens", + "k\u00f6rkarl", + "samuel_huntington", + "ella_fitzgerald", + "fats_waller", + "thomas_sydenham", + "jack_robinson", + "alois_senefelder", + "george_enescu", + "wallace_carothers", + "jacques_offenbach", + "joseph_paxton", + "josefus", + "william_curtis", + "william_chambers", + "den_flygande_holl\u00e4ndaren", + "george_stevens", + "federico_fellini", + "bessie_smith", + "patrick_henry", + "willy_brandt", + "charles_wilkes", + "francisco_pizarro", + "francisco_franco", + "jackie_robinson", + "purpurblad", + "bernardo_bertolucci", + "king_oliver", + "jan_steen", + "frank_harris", + "john_ross", + "powell", + "philibert_delorme", + "andrew_carnegie", + "pontius_pilatus", + "gr\u00e4s\u00e4nkling", + "franz_schubert", + "regementsf\u00f6rvaltare", + "johnny_cash", + "joseph_mccarthy", + "alfred_kastler", + "balettdansare", + "dawid", + "peter_den_store", + "mick_jagger", + "otto_loewi", + "georges_cuvier", + "william_harvey", + "walter_scott", + "peter_medawar", + "vladimir_lenin", + "sam_houston", + "robert_browning", + "alessandro_farnese", + "ralph_ellison", + "john_bunyan", + "jonathan_swift", + "m\u00f6ller", + "gr\u00e4s\u00e4nkeman", + "ta_livet_av_sig", + "walter_gropius", + "albert_einstein", + "l", + "henry_sweet", + "fritz_lipmann", + "aletta_jacobs", + "thomas_edison", + "chiang_kai_shek", + "claude_bernard", + "raymond_chandler", + "henry_purcell", + "skorstensfejare", + "t", + "wilhelm_ostwald" + ], + "PLANT": [ + "s\u00e4venbom", + "kanadal\u00e4rk", + "cucurbita_ficifolia", + "acanthocereus_tetragonus", + "\u00e4delcypress", + "baldersbr\u00e5", + "kustgran", + "strandglim", + "trumpetlilja", + "acer_rubrum", + "mahonia", + "svartbr\u00e4ken", + "trift", + "pipkrage", + "leverbalsam", + "videsl\u00e4ktet", + "passionsfrukt", + "plommonsl\u00e4ktet", + "safsa", + "pine", + "balsamgran", + "judaspenningar", + "parnassia", + "sallat", + "korallrot", + "salvia_leucophylla", + "myrlilja", + "krikon", + "tulpantr\u00e4d", + "atlascedertr\u00e4d", + "lagerh\u00e4gg", + "febertr\u00e4d", + "servera", + "melissa", + "dioscorea_bulbifera", + "r\u00f6nnsumak", + "erythronium_albidum", + "bosyska", + "sapindus", + "cellv\u00e4gg", + "porslinsblomma", + "lundgamander", + "salig", + "potatiskr\u00e4fta", + "honungsfacelia", + "bergmynta", + "liguster", + "the_joshua_tree", + "r\u00e5dhusvin", + "paradisf\u00e5glar", + "kvastm\u00e5lla", + "gudatr\u00e4dssl\u00e4ktet", + "johannes\u00f6rt", + "hampflockel", + "nattskatta", + "kungs\u00e4ngslilja", + "lappa", + "pitanga", + "dv\u00e4rgvide", + "mariatistel", + "tomtskr\u00e4ppa", + "gullusern", + "gr\u00e5vide", + "rosenrips", + "sn\u00f6bollschampinjon", + "brysselk\u00e5l", + "ladanumcistros", + "tranb\u00e4r", + "blodkl\u00f6ver", + "madonnalilja", + "silverarv", + "rosenrobinia", + "kardborre", + "smalfr\u00e4ken", + "r\u00f6nn", + "frukttr\u00e4d", + "tr\u00e4dg\u00e5rdsnejlika", + "sparris\u00e4rt", + "mj\u00f6lon", + "purpurbr\u00e4cka", + "r\u00f6d_skogslilja", + "palmyrapalm", + "glansliguster", + "kambr\u00e4ken", + "quercus_kelloggii", + "k\u00e4llfr\u00e4nen", + "klematissl\u00e4ktet", + "amelanchier_bartramiana", + "stens\u00f6ta", + "sankta_maria", + "furu", + "profetsalvia", + "enoki", + "cyclamen_purpurascens", + "drottninglilja", + "kornvallmo", + "vaktelb\u00e4r", + "banksianatall", + "praktportlak", + "br\u00e4nn\u00e4ssla", + "sensitiva", + "backtrav", + "balsampoppel", + "guldgrenadill", + "morell", + "sandnarv", + "curuba", + "palasatr\u00e4d", + "kattfot", + "klibbal", + "h\u00e4ngpelargon", + "adenium_obesum", + "bergsyra", + "halmslidskivling", + "berggran", + "arundo", + "brokiris", + "kolvhirs", + "artist", + "svartpoppel", + "sommarfl\u00e4der", + "svart\u00f6ga", + "harsyra", + "pelargonium_odoratissimum", + "sprutgurka", + "j\u00e4rn\u00f6rt", + "drakmynta", + "notblomster", + "bergek", + "strandvallmo", + "ostronmussling", + "stenek", + "brunsk\u00e4ra", + "chionanthus_virginicus", + "glasbj\u00f6rk", + "papaver_alpinum", + "hydrangea_petiolaris", + "kors\u00f6rt", + "pachysandra_procumbens", + "silverpoppel", + "hornviol", + "glansbr\u00e4ken", + "svinm\u00e5lla", + "fingerborgsblomma", + "leucaena_leucocephala", + "lilium_michiganense", + "penningblad", + "tallkottk\u00f6rteln", + "svarttall", + "berberis_nervosa", + "bletilla_striata", + "bondb\u00f6na", + "krusb\u00e4rsaktinidia", + "cocustr\u00e4", + "fiskstj\u00e4rtsmagnolia", + "tuvvaktelb\u00e4r", + "virginiatobak", + "loblollytall", + "sandstarr", + "svartvinb\u00e4rsbuske", + "havss\u00e4lting", + "acacia_pycnantha", + "soda\u00f6rt", + "dv\u00e4rgfackelblomster", + "actinidia_chinensis", + "liberiakaffe", + "alpstormhatt", + "sakura", + "amerikansk_stj\u00e4rnanis", + "rosenv\u00e4ppling", + "periploca_graeca", + "engelmannsgran", + "kungsljus", + "rosling", + "nattljus", + "bj\u00f6rnloka", + "candida_albicans", + "gr\u00e5mynta", + "senna_alata", + "amaryllis_belladonna", + "lingonoxb\u00e4r", + "smalkaveldun", + "betlehemsstj\u00e4rnan", + "calophyllum_inophyllum", + "p\u00e4rlhirs", + "toppklocka", + "vallmosl\u00e4ktet", + "r\u00f6dlomme", + "taggsallat", + "lundviol", + "sockerannona", + "bj\u00f6rnb\u00e4r", + "asclepias_purpurascens", + "gullupin", + "besks\u00f6ta", + "stinksyska", + "peppar", + "larix_occidentalis", + "klockgentiana", + "svartk\u00e4mpar", + "sandvita", + "pappersmullb\u00e4rstr\u00e4d", + "almsl\u00e4ktet", + "andropogon_virginicus", + "backnejlika", + "munkh\u00e4ttesl\u00e4ktet", + "xanthosoma_sagittifolium", + "acer_palmatum", + "martorn", + "pilgrimsveronika", + "hypericum_androsaemum", + "bl\u00e5hallon", + "flugsvamp", + "blodamarant", + "fikonl\u00f6v", + "strandklo", + "j\u00e4ttekn\u00f6lkalla", + "prakthyperikum", + "kinarosor", + "alstonia_scholaris", + "senap", + "cassia_fistula", + "pterospermum_acerifolium", + "platanus_occidentalis", + "clusia", + "blodek", + "ishavsvide", + "quercus_ellipsoidalis", + "bl\u00e5s\u00e4rt", + "blodhirs", + "ardisia_crenata", + "fraxinus_quadrangulata", + "skruvax", + "naverl\u00f6nn", + "lundviva", + "sockerr\u00f6r", + "nagel\u00f6rt", + "tangerin", + "rundhagtorn", + "osmanthus_americanus", + "bi_ofrys", + "bl\u00e5suga", + "platanus_orientalis", + "gossypium_hirsutum", + "holm", + "vitgran", + "castanea_dentata", + "islandslav", + "liquidambar", + "annueller", + "korst\u00f6rel", + "sk\u00e4rmtry", + "pr\u00e4stkrage", + "j\u00e4ttemalva", + "spikvallmo", + "\u00e4ppelr\u00f6nn", + "bergamott", + "tropaeolum_minus", + "blomk\u00e5l", + "borstnejlika", + "korsandmat", + "cucurbita_argyrosperma", + "revormst\u00f6rel", + "praktmalva", + "olivgr\u00f6n", + "odon", + "pterocarpus_indicus", + "corylus_americana", + "acer_japonicum", + "carissa_macrocarpa", + "pomerans", + "jolster", + "glansh\u00e4gg", + "gullgentiana", + "asclepias_verticillata", + "phyllostachys_nigra", + "stor_vattenpest", + "quercus_variabilis", + "ulmus_americana", + "vindesl\u00e4ktet", + "lindmalva", + "taggbr\u00e4ken", + "smultron", + "klockfacelia", + "slingertry", + "bl\u00e5musseron", + "kinak\u00e5l", + "bomullshibiskus", + "calochortus_amabilis", + "krustistel", + "melastoma_malabathricum", + "tazett", + "silverlind", + "tallsl\u00e4ktet", + "klotgr\u00e4s", + "flugblomster", + "k\u00f6rvel", + "krusnate", + "sommarkyndel", + "silvergran", + "blomsterkornell", + "gullranka", + "frilandshibiskus", + "brudsporre", + "hj\u00e4rtansfr\u00f6jd", + "plym\u00f6rt", + "penning\u00f6rt", + "krikontr\u00e4d", + "scharlakanssmultron", + "rosenhibiskus", + "platanus_hybrida", + "dendrocalamus_giganteus", + "tandt\u00f6rel", + "kaprifol", + "segelbuske", + "rosenhallon", + "l\u00f6nn", + "chlorophyllum_molybdites", + "buskstj\u00e4rnblomma", + "h\u00f6stadonis", + "prosopis_juliflora", + "perukbuske", + "viburnum_prunifolium", + "siden\u00f6rtssl\u00e4ktet", + "paradiskorn", + "h\u00e5rs\u00e4rv", + "l\u00f6nnsl\u00e4ktet", + "mursenap", + "sommarkungsljus", + "lagertibast", + "rosendun\u00f6rt", + "labruskavin", + "drakblommor", + "paran\u00f6tstr\u00e4d", + "ljungvicker", + "svartkummin", + "blackberry", + "gr\u00e5spr\u00e4ngd", + "berghemlock", + "brunkr\u00f6s", + "kitulpalm", + "h\u00e4gg", + "tibast", + "hjortsk\u00f6lding", + "gulltratt", + "sommargyllen", + "sareptasenap", + "j\u00e4ttesmultron", + "brachychiton_acerifolius", + "l\u00f6nnaftonfly", + "mariaklocka", + "ekorrkorn", + "indiankrasse", + "svartpeppar", + "poppig", + "glas\u00f6rt", + "jord\u00e4rtskocka", + "hultbr\u00e4ken", + "muskatellsalvia", + "buskt\u00f6rne", + "uddbr\u00e4ken", + "gulyxne", + "korallbuske", + "cytisus_multiflorus", + "sommarnejlika", + "rosenb\u00f6na", + "talipotpalm", + "gymnocladus_dioica", + "portlak", + "fraxinus_velutina", + "anagallis_tenella", + "knapps\u00e4v", + "kardv\u00e4dd", + "kransborre", + "acrocarpus_fraxinifolius", + "marviol", + "rosensk\u00e4rm", + "parkaralia", + "drosophyllum_lusitanicum", + "stenros", + "silverbuske", + "bergtall", + "contortatall", + "sabina", + "bockt\u00f6rne", + "saccharomyces_cerevisiae", + "robustakaffe", + "orange_siden\u00f6rt", + "fortplantningssystemet", + "flugsvampar", + "sommarbinka", + "krollilja", + "fingerhirs", + "trattfacelia", + "bj\u00f6rnbrodd", + "daphne_cneorum", + "gr\u00e4svial", + "taklosta", + "juglans_californica", + "karpaterklocka", + "phytolacca_dioica", + "brandmusseron", + "coloradogran", + "kanadabinka", + "grenbingel", + "jordr\u00f6k", + "potatissl\u00e4ktet", + "slokstarr", + "gullbr\u00e4cka", + "marathi", + "silverakacia", + "backsippa", + "tr\u00e4dkaktus", + "lent\u00e5tel", + "b\u00e4ckveronika", + "namekotofsskivling", + "jordviva", + "liljekonvalj", + "backvial", + "trumpetranka", + "rosengeranium", + "senna_alexandrina", + "rosenvial", + "haricots_verts", + "palmaralia", + "crataegus_aestivalis", + "drimys_winteri", + "potatisbladm\u00f6gel", + "skatn\u00e4va", + "mannaask", + "flyghavre", + "jobs_t\u00e5rar", + "mastix", + "calla", + "indianrissl\u00e4ktet", + "erythronium_montanum", + "j\u00e4tter\u00f6ksvamp", + "stenfr\u00f6", + "stenbr\u00e4ken", + "aralia_stipulata", + "cycas_circinalis", + "bisuga", + "gudatr\u00e4d", + "vargt\u00f6rel", + "plommon", + "sockerl\u00f6nn", + "kabomba", + "mastixbuske", + "kritsuga", + "hassel\u00f6rt", + "backtimjan", + "edelweiss", + "damascenerrosor", + "piper_betle", + "guckusko", + "brun\u00f6rt", + "l\u00e5ngpeppar", + "sandsenap", + "vitm\u00e5ra", + "hartsvinda", + "solfj\u00e4dertall", + "kauritr\u00e4d", + "bresilja", + "sv\u00e4rdslilja", + "olivf\u00e4rgad", + "montereytall", + "r\u00f6dvide", + "bredkaveldun", + "plattvial", + "lungmossa", + "cypripedium_montanum", + "erodium_texanum", + "annona_reticulata", + "pinus_muricata", + "p\u00e4ronr\u00f6nn", + "judek\u00f6rs", + "druvfl\u00e4der", + "brushane", + "belladonna", + "lingon", + "sporrhagtorn", + "mj\u00f6ldryga", + "vallmo", + "cinnamomum_cassia", + "grekamarant", + "paraplymagnolia", + "smilax_aspera", + "buketthirs", + "mahoniasl\u00e4ktet", + "catharanthus_roseus", + "dunlykt\u00f6rt", + "paran\u00f6t", + "s\u00f6tvedel", + "br\u00f6dgran", + "corylus_cornuta", + "jamsb\u00f6nrot", + "stor_blomstertobak", + "idegran", + "mussepiggbuske", + "parkolvon", + "butternutpumpa", + "hj\u00e4rtstilla", + "gullbandslilja", + "rockentrav", + "gr\u00f6nknavel", + "polejmynta", + "tr\u00e4dg\u00e5rdsm\u00e5lla", + "pappersbj\u00f6rk", + "teveronika", + "svartsenap", + "oliv", + "vallisneria", + "erythrina_variegata", + "rosa_banksiae", + "acer_glabrum", + "begonia_tuberhybrida", + "fross\u00f6rt", + "tjockhorn", + "alder", + "jungfrulin", + "toppamarant", + "rundmynta", + "jamsb\u00f6na", + "underblomma", + "silverl\u00f6nn", + "orientvallmo", + "savoyk\u00e5l", + "papegojblomma", + "kirimoja", + "pampasgr\u00e4s", + "olivtr\u00e4d", + "nattviol", + "oxalisar", + "klockjulros", + "brunven", + "svartgran", + "svartvedsakacia", + "trubbhagtorn", + "mattram", + "paradisf\u00e5gel", + "dv\u00e4rgmandel", + "ligustersl\u00e4ktet", + "missne", + "drakkalla", + "lundgr\u00f6e", + "podocarpus_latifolius", + "dicksonia_antarctica", + "potatisv\u00e4xt", + "rosenk\u00e5l", + "strandvial", + "magnolia", + "j\u00e4ttetuja", + "kungsmagnolia", + "kurrajongtr\u00e4d", + "ulmus_hollandica", + "dadelpalm", + "nephrolepis_exaltata", + "asclepias_meadii", + "pterocarpus_macrocarpus", + "cherimoya", + "stenmurkla", + "phellodendron_amurense", + "kampeschtr\u00e4d", + "pinus_palustris", + "magnoliasl\u00e4ktet", + "cypripedium_reginae", + "strandlysing", + "stinkn\u00e4va", + "rosentry", + "veket\u00e5g", + "j\u00e4ttel\u00f6nn", + "lejongap", + "tritoma", + "stenmurklor", + "silveriris", + "r\u00f6dek" + ], + "PERSON_PRONOUN": [ + "v\u00e5rt", + "i", + "he", + "mig_sj\u00e4lv", + "oss_sj\u00e4lva", + "our", + "hennes", + "my", + "sig_sj\u00e4lv", + "v\u00e5ra", + "ditt" + ], + "ORG": [ + "solarplexus", + "dominion", + "ida", + "shinto", + "bataljon", + "statskapitalism", + "fondb\u00f6rs", + "nazityskland", + "n\u00e4r_jag_h\u00f6r_din_r\u00f6st", + "krambj\u00f6rnarna", + "de_misst\u00e4nkta", + "songdynastin", + "musikh\u00f6gskola", + "jag_heter", + "fruktsallad", + "t\u00f6rnrosa", + "str\u00e5kkvartett", + "hemma", + "kungahus", + "wicca", + "an_education", + "statskupp", + "massmedier", + "lokaltrafik", + "koncilium", + "personalavdelning", + "jan_mayen", + "upp_med_h\u00e4nderna", + "polisstat", + "forskningsinstitut", + "yuandynastin", + "aa", + "r\u00e4ddningsk\u00e5r", + "nasa", + "bloomsburygruppen", + "massmedium", + "arda", + "radiogalax", + "bollywood", + "qingdynastin", + "internationell_organisation", + "grundskola", + "milj\u00f6partiet", + "europol", + "schutzstaffel", + "synnerv", + "stadsstat", + "normalskola", + "the_who", + "representanthuset", + "marink\u00e5r", + "reklambyr\u00e5", + "nym\u00e5ne", + "bleckbl\u00e5sorkester", + "stj\u00e4rnhop", + "sparbank", + "utvecklingsland", + "non_plus_ultra", + "haganah", + "\u00e5ldersgrupp", + "f\u00f6rbundsr\u00e5det", + "fackf\u00f6rening", + "vem_\u00e4r_du", + "samh\u00e4llsklass", + "f\u00f6rs\u00e4kringsbolag", + "stora_bj\u00f6rnen", + "stora_bj\u00f6rn", + "medlemsbank", + "college", + "polens_nationalf\u00f6rsamling", + "frankrikes_nationalf\u00f6rsamling", + "mellanstadie", + "skal\u00e4rf\u00e4lt", + "san_francisco", + "kvinnof\u00f6rf\u00f6rare", + "f\u00f6rresten", + "kristdemokraterna", + "the_national_academy_of_sciences", + "jesuitorden", + "social_democratic_party", + "a_chorus_line", + "nordcypern", + "musikskola", + "kristen_vetenskap", + "aff\u00e4rscenter", + "storbritanniens_flygvapen", + "andromedagalaxen", + "l\u00e4rarkollegium", + "popkonst", + "va", + "konstmuseum", + "f\u00f6rs\u00e4kringskassan", + "bl\u00e5tira", + "gemensamt", + "inte_r\u00f6ra", + "vattenknop", + "frimureri", + "zhoudynastin", + "qindynastin", + "baskien", + "olivberget", + "underr\u00e4ttelsetj\u00e4nst", + "utbildning", + "\u00e5_nyo", + "storband", + "prohibition_party", + "kassationsdomstol", + "soppk\u00f6k", + "med_flera", + "fabianerna", + "mahayana", + "holdingbolag", + "icke_linj\u00e4r", + "man_\u00f6ver_bord", + "liaodynastin", + "saint_vincent", + "skalf\u00f6retag", + "sankta_helena", + "sunt_f\u00f6rnuft", + "can_tho", + "djurr\u00e4tt", + "don_juan", + "planekonomi", + "skattkammare", + "valdistrikt", + "alliansfri", + "the_new_school", + "ai", + "garden_party", + "dominikanorden", + "musikbranschen", + "romersk_r\u00e4tt", + "the_football_league", + "chiang_mai", + "landgericht", + "tummeliten", + "direktdemokrati", + "ole_dole_doff", + "et_al", + "akademi", + "vaggan", + "kyrkan", + "dia", + "marknadsekonomi", + "indiepop", + "med_fingrarna_i_syltburken", + "f\u00f6r_tidig_utl\u00f6sning", + "gatt", + "baktanke", + "konserveringslag", + "in_flagranti", + "kulturministerium", + "golfklubba", + "centralmakterna", + "parasport", + "studentk\u00e5r", + "albertsj\u00f6n", + "le_mans", + "s\u00f6ndagsskola", + "caf\u00e9_au_lait", + "en_vit_l\u00f6gn", + "shia", + "arabf\u00f6rbundet", + "blankvapen", + "hemmavid", + "natriumsilikat", + "skurkstat", + "rabindranath_tagore", + "de_fyra_stora", + "gestapo", + "postkontor", + "privatskola", + "nordatlantiska_f\u00f6rdragsorganisationen", + "ungerns_parlament", + "bilbomb", + "lillpolen", + "hasidism", + "\u00e5terigen", + "andra_person", + "mandelbrotm\u00e4ngd", + "h\u00f6gsta_domstol", + "sockerfri", + "kontinentalarm\u00e9n", + "centralbank", + "frankrikes_generalst\u00e4nder", + "k\u00f6pcentrum", + "pensionsfond", + "brassband", + "tra_vinh", + "al_jazira", + "varf\u00f6r_inte", + "nollpunktsanalys", + "kejsard\u00f6met_tyskland", + "shangdynastin", + "f\u00e4rgstege", + "who_are_you", + "i_ching", + "babyboom", + "kungafamilje", + "chiang_rai", + "milit\u00e4rh\u00f6gskola", + "disa", + "jakobinm\u00f6ssa", + "tjurmarknad", + "dimokratik\u00f3_k\u00f3mma", + "po", + "sjukv\u00e5rd", + "mossad", + "hare_krishna", + "nym\u00e5nad", + "ferdinand_magellan", + "filallokeringstabell", + "\u00f6vernattning", + "nautilus_pompilius", + "polens_nationella_parti", + "tillr\u00e4knelig", + "nationalsocialistiska_tyska_arbetarepartiet", + "f\u00e4rskvatten", + "porten", + "trafikstockning", + "saint_barth\u00e9lemy", + "stadshus", + "en_andra_chans", + "sturmabteilung", + "vaishnavism", + "resebyr\u00e5", + "usa:s_arm\u00e9", + "mitt_namn_\u00e4r", + "los_angeles", + "nato", + "fruntimmerskarl", + "handelskammare", + "karmelberget", + "bl\u00e5sorkester", + "baltimore_orioles", + "flygvapen", + "k\u00f6pcenter", + "i_mitt_tycke", + "\u00e4n_en_g\u00e5ng", + "babyboomare", + "ad_hoc", + "fredsk\u00e5ren", + "efter_kristus", + "homo\u00e4ktenskap", + "fattiga_riddare", + "s\u00f6tvatten", + "mi", + "by_the_way", + "capetinger", + "v\u00e4stl\u00e4nderna", + "gammelstad", + "tankesmedja", + "josef_fr\u00e5n_nasaret", + "ordenss\u00e4llskap", + "in_situ", + "mellaneuropa", + "blodsbr\u00f6der", + "tangdynastin", + "kontinentalkongressen", + "ny\u00e5rsafton", + "guld\u00e5lder", + "f\u00f6rsvar", + "doc", + "den_olympiska_elden", + "totalf\u00f6rsvarsplikt", + "hansan", + "berlinmuren", + "aff\u00e4rsbank", + "allt_eller_inget", + "islamologi", + "var_och_en_f\u00f6r_sig", + "blomsterspr\u00e5k", + "al_ain", + "underhus", + "br\u00e4nd_jord", + "masugn", + "tappkota", + "talionprincipen", + "f\u00f6rsamlingskyrka", + "knownothings", + "femtekolonn", + "taoism", + "tuggummi", + "morgonstj\u00e4rna", + "kammarorkester", + "polisskolan", + "milit\u00e4rpolis", + "svensexa", + "eu", + "r\u00e4ttvisa", + "jehovas_vittnen", + "medelklass", + "centraleuropa", + "olympisk_by", + "bildning", + "lite_i_taget", + "\u00f6verhus", + "handynastin", + "manhattanprojektet", + "mecklenburg_vorpommern", + "d\u00f6dspatrull", + "internationella_teleunionen", + "gula_floden", + "brandk\u00e5r", + "mingdynastin", + "utan_krusiduller", + "s\u00e3o_tom\u00e9", + "hedgefond", + "\u00f6verhuvudtaget", + "konstgalleri", + "nordv\u00e4stpassagen", + "weimarrepubliken", + "till\u00e4ggs", + "f\u00f6rsvarsindustri" + ], + "JOB": [ + "skogsm\u00e4stare", + "kroppsarbetare", + "borgm\u00e4starinna", + "persona_grata", + "konditor", + "guru", + "lockespindel", + "vinkypare", + "l\u00e4derlappen", + "the_nanny", + "sj\u00e4lvst\u00e4ndig", + "lantm\u00e4tare", + "f\u00f6nsterputsare", + "k\u00f6ksm\u00e4stare", + "tulltj\u00e4nsteman", + "brigadgeneral", + "biskop", + "assistent", + "faktotum", + "s\u00e4kerhetsvakt", + "skyddshj\u00e4lm", + "internera", + "maskiningenj\u00f6r", + "potter", + "kaparskepp", + "mikrobiolog", + "borgen\u00e4r", + "make", + "underlydande", + "helare", + "rockvaktm\u00e4stare", + "kirurg", + "brandman", + "dietist", + "besiktningsman", + "salter", + "koordinator", + "hand", + "brigad\u00f6r", + "purser", + "blockfl\u00f6jt", + "oberoende", + "barnvakt", + "strippteasedans\u00f6s", + "sexton", + "industrialist", + "internist", + "vandringsges\u00e4ll", + "don", + "kopparsmed", + "skogsbrukare", + "barberare", + "sergeant", + "kostr\u00e5dgivare", + "\u00f6gonl\u00e4kare", + "coyote", + "kansler", + "dermatolog", + "sk\u00e4rare", + "hush\u00e5llsarbetare", + "blekare", + "timmerman", + "the_police", + "intern", + "pretor", + "sommelier", + "springpojke", + "bager", + "processor", + "skiljedomare", + "koherde", + "doge", + "gentleman", + "allm\u00e4nl\u00e4kare", + "tunnbindare", + "bekant", + "d\u00f6rrvakt", + "kalligraf", + "fris\u00f6rska", + "f\u00f6rs\u00e4ljare", + "f\u00e5ngvaktare", + "grip", + "para", + "krukmakare", + "bagare", + "taleskvinna", + "tandtekniker", + "harpunerare", + "underofficer", + "maskinskrivare", + "mastermind", + "tapper", + "barnpassare", + "partifunktion\u00e4r", + "h\u00f6gl\u00e4saren", + "tr\u00e4snidare", + "land", + "baksm\u00e4llan", + "boss", + "skogsvetare", + "medlare", + "djurl\u00e4kare", + "barnflicka", + "kronist", + "l\u00e4kare", + "tandl\u00e4karen", + "statistiker", + "butler", + "livsmedelshandlare", + "grenadier", + "handlare", + "m\u00f6ller", + "planteringsl\u00e5da", + "barnmorska", + "hush\u00e5llerska", + "brandsoldat", + "fiolbyggare", + "handl\u00e4ggare", + "kurator", + "scientist", + "socialassistent", + "kamikaze", + "halmt\u00e4ckare", + "brevb\u00e4rare", + "the_advocate", + "kopparslagare", + "tjockhuvuden", + "arbetare", + "page", + "sj\u00f6kapten", + "stridsman", + "hantverkare", + "slavinna", + "ritare", + "baksm\u00e4lla", + "sjukgymnast", + "ledare", + "statstj\u00e4nsteman", + "freelancer", + "grenadj\u00e4r", + "hamnarbetare", + "the_professor", + "krigare", + "finansdirekt\u00f6r", + "tecknare", + "diskplockare", + "mont\u00f6r", + "master", + "the_guardian", + "stroke", + "m\u00e5lare", + "f\u00f6rtennare", + "vesir", + "tr\u00e4dg\u00e5rdsm\u00e4stare", + "president", + "kapare", + "agenten", + "chauff\u00f6r", + "minister", + "\u00e5terf\u00f6rs\u00e4ljerska", + "mandarin", + "strippa", + "flikfly", + "ingenj\u00f6r", + "slaganfall", + "tr\u00e4dg\u00e5rdsodlare", + "mate", + "fickminne", + "borgm\u00e4stare", + "guide", + "specerihandlare", + "terapeut", + "angler", + "sotare", + "designer", + "the_babysitter", + "f\u00e4ltmarskalk", + "pastor", + "formgivare", + "fallsk\u00e4rmsj\u00e4gare", + "skiljeman", + "balkongl\u00e5da", + "sheriff", + "hj\u00e4lparbetare", + "pr\u00e4rievarg", + "tandl\u00e4kare", + "f\u00f6rl\u00e4ggare", + "kurir", + "gaucho", + "v\u00e4rldshusv\u00e4rd", + "kliniker", + "kvartersm\u00e4stare", + "baster", + "stallm\u00e4stare", + "kemist", + "intendent", + "logistiker", + "kock", + "the_economist", + "kantra", + "manager", + "kr\u00f6nikeskrivare", + "glasm\u00e4stare", + "h\u00e4rskarinna", + "wetter", + "skogshuggare", + "svartjobbare", + "rammakare", + "infanterist", + "hands\u00e4ttare", + "barista", + "kr\u00f6nikef\u00f6rfattare", + "patolog", + "hjulmakaren", + "svinaherde", + "the_pilot", + "man", + "doc", + "deltidsanst\u00e4lld", + "a_dur", + "regent", + "kriminalv\u00e5rdare", + "f\u00f6rs\u00e4ljerska", + "djurfoder", + "talesperson", + "the_boxer", + "skolflygplan", + "stopperska", + "underh\u00e5llare", + "arbetsterapeut", + "diskmaskin", + "tr\u00e4dg\u00e5rds\u00e4gare", + "tusenkonstn\u00e4r", + "skorstensfejare", + "neurolog", + "munsk\u00e4nk", + "barnl\u00e4kare", + "the_machinist", + "sockerbagare", + "usher", + "messenger", + "statssekreterare", + "tullare", + "kartograf", + "au_pair", + "v\u00e4g_och_vattenbyggnadsingenj\u00f6r", + "proconsul", + "h\u00e4rold", + "marschall", + "trier", + "vagnsmakare", + "lagstiftare", + "bakrus", + "socialarbetare", + "anst\u00e4llningsbar", + "prisj\u00e4gare", + "helbr\u00e4gdag\u00f6rare", + "croupier", + "lakej", + "novellist", + "extern", + "portvakt", + "livgivare", + "sportdomare", + "obstetriker", + "blomsterflickan", + "sub", + "tendera", + "kammarjungfru", + "the_independent", + "konnetabel", + "statsr\u00e5d", + "kass\u00f6rska", + "affisch", + "chambermaid", + "cookie", + "andrepilot", + "kabinpersonal", + "familjef\u00f6rs\u00f6rjare", + "vikarie", + "marinera", + "esquire", + "r\u00f6stsk\u00e5despelare", + "kass\u00f6r", + "maskinskriverska", + "svartjobberska", + "kittelflickare", + "j\u00e4gm\u00e4stare", + "kardiolog", + "lockf\u00e5gel", + "inkastare", + "preceptor" + ], + "LAW": [ + "kronjurist", + "h\u00f6gsta_domstolen", + "civilr\u00e4tt", + "krigslagar", + "justitieminister", + "husrannsakningsorder", + "pressfrihet", + "religionsfrihet", + "handelsr\u00e4tt", + "domstolsbeslut", + "f\u00f6rvaltningslag", + "tryckfrihet", + "advokatbyr\u00e5", + "r\u00e4ttsstat", + "ne_bis_in_idem", + "trosfrihet", + "straffr\u00e4tt", + "yttrandefrihet", + "d\u00f6dsdom", + "skatter\u00e4tt", + "f\u00f6rvaltningsr\u00e4tt", + "undantagstillst\u00e5nd", + "valsystem", + "korsf\u00f6rh\u00f6r", + "krigstillst\u00e5nd", + "federal_bureau_of_investigation" + ], + "DISEASE": [ + "sars", + "stelkramp", + "araknofobi", + "panik\u00e5ngest", + "bieffekt", + "filovirus", + "acanthosis_nigricans", + "dammlunga", + "abrasion", + "f\u00f6rmaksflimmer", + "dubbelseende", + "klaustrofobi", + "sickelcellanemi", + "fettsvulst", + "mastoidit", + "polio", + "humant_papillomavirus", + "ha_ont", + "karpaltunnelsyndrom", + "rage", + "granulom", + "strypning", + "luftv\u00e4gsinfektion", + "flunsa", + "masspsykos", + "br\u00e4nnskada", + "als", + "whiplash", + "strabism", + "rabies", + "tungom\u00e5lstalande", + "br\u00e4cklighet", + "misslyckande", + "gumma", + "stamma", + "dv\u00e4rgv\u00e4xt", + "vinterdvala", + "katarr", + "bornholmssjukan", + "polyarteritis_nodosa", + "inversion", + "poison_ivy", + "progeri", + "presbyopi", + "graviditetskramp", + "smittkoppor", + "furunkel", + "f\u00f6rstoppning", + "kl\u00e4ttersumak", + "kopp\u00e4rr", + "sekvele", + "minamatasjukan", + "zikavirus", + "kycklingbr\u00f6st", + "lump", + "k\u00f6ldskada", + "talassemi", + "nacksp\u00e4rr", + "indigestion", + "kolmonoxidf\u00f6rgiftning", + "sicklecellanemi", + "kallbrand", + "anestesi", + "muskeldystrofi", + "albuminuri", + "kattkl\u00f6ssjuka", + "l\u00e5ngsynthet", + "skotom", + "beriberi", + "funktionsneds\u00e4ttning", + "k\u00e4rlkramp", + "gall", + "gangr\u00e4n", + "the_bends", + "katalepsi", + "stroke", + "utomkvedshavandeskap", + "pang", + "picornavirus", + "seminom", + "liktorn", + "struma", + "papill\u00f6dem", + "boskapspest", + "br\u00e4nnm\u00e4rke", + "matthet", + "f\u00f6rlamning", + "mjukhet", + "bunt", + "trigeminusneuralgi", + "lidande", + "paralys", + "epstein_barr_virus", + "kransk\u00e4rlssjukdomar", + "personlighetsst\u00f6rning", + "intertrigo", + "hermafrodism", + "rust", + "druvhinneinflammation", + "scharlakansfeber", + "hydrocefalus", + "masshysteri", + "galaktosemi", + "fruktsamhet", + "st\u00f6rning", + "f\u00e5gelinfluensa", + "stukning", + "missbildning", + "vaccination", + "bucklig", + "kondition", + "materialism", + "harpest", + "ursinne", + "rosacea", + "para", + "bindhinneinflammation", + "antisocial_personlighetsst\u00f6rning", + "gulsot", + "hunger", + "levercancer", + "skator", + "papegojsjuka", + "hamartom", + "skelning", + "dekubitus", + "portahypertension", + "eltortyr", + "silikos", + "muskelbristning", + "wale", + "lassafeber", + "bl\u00e5m\u00e4rke", + "mollusker", + "autoimmunitet", + "vattenskalle", + "miliaria", + "m\u00f6rkr\u00e4dsla", + "aura_\u00e5", + "sj\u00f6sjuka", + "elektrochock", + "undern\u00e4ring", + "kastanjesl\u00e4ktet", + "poliomyelit", + "kantra", + "vakenhet", + "klagom\u00e5l", + "kakeksi", + "f\u00f6rtviningssjuka", + "duodenals\u00e5r", + "sedering", + "kryptorkism", + "prodrom", + "chi", + "f\u00e4rgblind", + "delirium", + "kobenthet", + "kvarka", + "rosfeber", + "appendicit", + "kammarflimmer", + "pisksn\u00e4rt", + "transposition", + "qi", + "halvsidesf\u00f6rlamning", + "vattkoppor", + "utvecklingsst\u00f6rning", + "helveteseld", + "giftstruma", + "tryckfallssjuka", + "tungotal", + "oordning", + "rakitis", + "puckelrygg", + "stenos", + "tredagarsfeber", + "antoniuseld", + "passion", + "raseri", + "gimp", + "hydronefros", + "rosett", + "frenzy", + "alexia", + "kretinism", + "ledinflammation", + "hermafroditism", + "leversteatos", + "stressfraktur", + "bindhinnekatarr", + "stigande", + "\u00f6verviktig", + "smart", + "amelia", + "stridsutmattning", + "brunst", + "tyreoidit", + "testikelcancer", + "ed", + "blister", + "pica", + "benv\u00e4vsuppmjukning", + "tandlossning", + "miliartuberkulos", + "sk\u00e5lla", + "solbr\u00e4nna", + "sk\u00f6ldk\u00f6rtelinflammation", + "tunnelseene", + "k\u00e4rlinflammation", + "lordos", + "ledg\u00e5ngsreumatism", + "kallus", + "datormus", + "sensation", + "fettlever", + "tanatofobi", + "rubella", + "epidermolysis_bullosa", + "pain", + "tandv\u00e4rk", + "gallbl\u00e5seinflammation", + "till\u00e4gga", + "teratom", + "ansiktsneuralgi", + "rodnande", + "ventrikelflimmer", + "fladdra", + "dilatation", + "f\u00f6rgiftning", + "the_passion_of_the_christ", + "purpura", + "tennisarmb\u00e5ge", + "cirkulationssvikt", + "ventrikels\u00e5r", + "spindelfobi", + "f\u00f6rveckling", + "elst\u00f6t", + "graviditetstoxikos", + "trycks\u00e5r", + "ill", + "chalazion", + "denguefeber", + "bradykardi", + "skotofobi", + "m\u00f6ss", + "puls\u00e5derbr\u00e5ck", + "sammanhopning", + "f\u00f6rfrysning", + "vitaminbrist", + "parestesi", + "vanf\u00f6rest\u00e4llningssyndrom", + "digerd\u00f6den", + "tobaksmosaikvirus", + "pellagra", + "spet\u00e4lska", + "n\u00e4ringsbrist", + "j\u00e4rnbristanemi", + "paraplegi", + "druvb\u00f6rd", + "mi", + "v\u00e5rta", + "almsjuka", + "komplikation", + "friskhet", + "aura", + "arousal", + "f\u00e4rgblindhet", + "potatisbladm\u00f6gel", + "bl\u00e5sningen", + "sting", + "hickning", + "nattblindhet", + "bukhinneinflammation", + "the_bleeding", + "skrumplever", + "paritet", + "indisposition", + "marasm", + "solsting", + "bensk\u00f6rhet", + "kuru", + "burn", + "flexion", + "svampf\u00f6rgiftning", + "kontaktallergi", + "fr\u00e4mlingsfientlighet", + "vissna", + "vargen", + "noma", + "the_hives", + "tilltagande", + "dengue", + "mouches_volantes", + "preeklampsi", + "klippt", + "ont_i_halsen", + "newcastlesjuka", + "ormbett", + "le", + "harm", + "berusning", + "vaccinering", + "gynekomasti", + "hydrofobi", + "cellskr\u00e4ck", + "salmonella", + "\u00f6versynthet", + "\u00e5lderssynthet", + "graviditet", + "magont", + "temporallobsepilepsi", + "h\u00e5rs\u00e4cksinflammation", + "abasi", + "malaria" + ], + "POLITICAL_PARTY_MEMBER": [ + "kommunistisk", + "kommunist", + "kommunistiskt" + ], + "QUANTITY": [ + "primtal", + "rupee", + "primfaktor", + "fransk_franc", + "parkeringsgarage", + "basketkorg", + "de_tre_kungad\u00f6mena", + "metersystemet", + "d_mark", + "kubikcentimeter", + "tv\u00e5siffrig", + "imagin\u00e4rdel", + "parkeringshus", + "krona", + "ton", + "distansminut", + "dollar", + "riyal", + "ordinaltal", + "en_i_taget", + "sj\u00f6mil", + "belopp", + "g", + "elektronvolt", + "rial", + "trinidaddollar", + "en_\u00e5t_g\u00e5ngen", + "schweizerfranc", + "kubikrot", + "inte_alls", + "tre_systrar", + "parkeringsbot", + "hongkongdollar", + "storspigg", + "\u00f6sterrikisk_schilling", + "masstal", + "helpension", + "anders_celsius", + "friktionskoefficient", + "all_inclusive" + ], + "DATE": [ + "palms\u00f6ndag", + "harlemren\u00e4ssansen", + "alla_helgons_dag", + "d\u00e4r_borta", + "askonsdagen", + "menstruationscykeln", + "skottsekund", + "bankfridag", + "indiansommar", + "budget\u00e5r", + "medeltiden", + "sjukpenning", + "exekverings", + "trettondagsafton", + "halvtimme", + "stillest\u00e5ndsdagen", + "fettisdag", + "halvtimma", + "askonsdag", + "happy_hour", + "menstruationscykel", + "nattskift", + "the_day_after_tomorrow", + "arbetstid", + "v\u00e5r_tider\u00e4kning", + "i_l\u00e4ngden", + "n\u00e4r_jag_h\u00f6r_din_r\u00f6st", + "trefaldighet", + "alla_sj\u00e4lars_dag", + "medel\u00e5lder", + "kanadadagen", + "valdag", + "istid", + "in_time", + "l\u00e5ngfredagen", + "trinitatis", + "lunisolarkalender", + "skottdag", + "finans\u00e5r", + "brittsommar", + "halveringstid", + "v\u00e4rldsklass", + "nationaldag", + "adventss\u00f6ndag", + "vintersolst\u00e5ndet", + "skott\u00e5r", + "efter_kristus", + "palms\u00f6ndagen", + "mantimme", + "natalitet", + "regntid", + "hj\u00e4rtminutvolym", + "\u00f6vermorgon", + "hyeonchungil", + "segerdagen", + "br\u00f6llopsnatt", + "fullm\u00e5ne", + "radialhastighet", + "guld\u00e5lder", + "regnperiod", + "nativitet", + "mortalitet", + "nattvakt", + "kalender\u00e5r", + "l\u00e5ngfredag", + "gregoriansk_kalender", + "solarkonstant", + "h\u00e4r_och_nu", + "normaltid", + "sj\u00e4lvst\u00e4ndighetsdag", + "i_l\u00e5nga_loppet", + "h\u00f6stdagj\u00e4mning", + "r\u00e4kenskaps\u00e5r", + "fritid", + "annandag", + "corpus_christi", + "jungfru_marie_himmelsf\u00e4rd", + "sjukskrivning", + "a_och_o", + "sp\u00e4dbarnsd\u00f6dlighet", + "myndighets\u00e5lder", + "kalenderm\u00e5nad", + "torrperiod", + "nattvakten", + "d\u00f6dsb\u00e4dden" + ], + "FOOD": [ + "skuta", + "mj\u00f6lkpulver", + "bakelse", + "svartabborre", + "mousse", + "t_benstek", + "fiskpinne", + "golden_delicious", + "r\u00f6dvin", + "currypulver", + "bechamel", + "christmas_pudding", + "blodpudding", + "pulverkaffe", + "grodl\u00e5r", + "kanelsn\u00e4cka", + "lagerblad", + "tigerkaka", + "granny_smith", + "kycklingssoppa", + "tuggummi", + "lemonad", + "l\u00e4ttmj\u00f6lk", + "vitvin", + "mj\u00f6lkchoklad", + "polkagris", + "bordsalt", + "bordsvatten", + "kranvatten", + "kattmat", + "chilipeppar", + "f\u00f6delsedagst\u00e5rta", + "alkoholdryck", + "lyckokaka", + "hollandaises\u00e5s", + "pinot_noir", + "sidfl\u00e4sk", + "ingef\u00e4rs\u00f6l", + "caesarsallad", + "olivolja", + "matbit", + "bambuskott", + "k\u00f6ttgrotta", + "sockervadd", + "pepparkaksgumma", + "potatischips", + "potatissallad", + "br\u00f6llopst\u00e5rta", + "str\u00f6br\u00f6d", + "fullkornsbr\u00f6d", + "bl\u00e5m\u00f6gelost", + "pepparkaksgubbe", + "gelato", + "chili", + "bordssalt", + "gr\u00e4ddfil", + "florsocker", + "lunch", + "l\u00f6nnsirap", + "chile", + "vitl\u00f6ksbr\u00f6d", + "antipasto", + "chesterost", + "pudding", + "mejeriprodukt", + "bomullsfr\u00f6olja", + "ros\u00e9vin", + "getost", + "apelsinjuice", + "dessert", + "blodkorv", + "iskaffe", + "volauvent", + "tartars\u00e5s", + "djupfrysning", + "rullt\u00e5rta", + "strips", + "k\u00f6ttf\u00e4rslimpa", + "entr\u00e9r\u00e4tt", + "kandisocker", + "yorkshirepudding", + "pinjen\u00f6t", + "citronsaft", + "tranb\u00e4rsjuice", + "pulpet", + "flankstek", + "pot_au_feu", + "mellanm\u00e5l", + "kakaosm\u00f6r", + "grynost", + "schweizerost", + "pannbiff", + "starkvin", + "rotsak", + "pinjek\u00e4rna", + "dricksvatten", + "palmolja", + "vetemj\u00f6l", + "standardmj\u00f6lk", + "waldorfsallad", + "cayennepeppar", + "glasstrut", + "kakaopulver", + "rolad", + "p\u00e5sk\u00e4gg", + "r\u00f6dk\u00e5l", + "marmeladkonfekt", + "jordn\u00f6tssm\u00f6r", + "farinsocker" + ], + "BIO_CHEM_ENTITY": [ + "sm\u00f6rsyra", + "bensalkoniumklorid", + "dietyleter", + "tranexamsyra", + "magnesiumklorid", + "silveroxid", + "gallsalt", + "koniferylalkohol", + "kaliumjodid", + "butansyra", + "polyvinylklorid", + "c_reaktivt_protein", + "mj\u00f6lksyra", + "gammaaminobutansyra", + "adenosindifosfat", + "kiseldioxid", + "nervtillv\u00e4xtfaktor", + "alfasynuklein", + "kaprinsyra", + "zinkklorid", + "retinoblastomprotein", + "metanhydrat", + "kiselnitrid", + "fettsyra", + "laurinsyra", + "polylaktid", + "klortrifluorid", + "mineralolja", + "guanosindifosfat", + "monoaminoxidas", + "kaliumantimontartrat", + "citronsyra", + "salicylsyra", + "magnesiumcitrat", + "d_vitamin", + "karminsyra", + "m\u00e5lmedveten" + ], + "LOCATION": [ + "hai_duong", + "korsv\u00e4g", + "f\u00f6retagspark", + "the_good_night", + "t\u00f6rnrosa", + "so_what", + "drakfrukt", + "tanasj\u00f6n", + "olivberget", + "ha_long_bukten", + "svalbon", + "saltsj\u00f6", + "park", + "non_plus_ultra", + "bruksort", + "qingmingfestivalen", + "tennisbana", + "vintergatan", + "musikh\u00f6gskola", + "corpus_christi", + "michigansj\u00f6n", + "\u00e5lderdomshem", + "kap_verde", + "bow_wow", + "mentalsjukhus", + "k\u00f6rsb\u00e4rstr\u00e4dg\u00e5rden", + "piet_mondrian", + "ha_long", + "milit\u00e4rh\u00f6gskola", + "jultomten", + "sint_maarten", + "det_svarta_h\u00e5let", + "doi_moi", + "mellan\u00f6stern", + "al_jazira", + "f\u00e4rskvatten", + "man_o_war", + "kryvyj_rih", + "chatham\u00f6arna", + "ringv\u00e4g", + "ingen_orsak", + "falklands\u00f6arna", + "trois_rivi\u00e8res", + "p\u00e5_vippen", + "sockerkaka", + "musikskola", + "vars\u00e5god", + "r\u00e5bandsknop", + "\u00e5terv\u00e4ndsgr\u00e4nd", + "selvagens\u00f6arna", + "land", + "heliga_stolen", + "\u00e5ker", + "azerbajdzjans_nationalf\u00f6rsamling", + "nord\u00f6n", + "\u00e4n_sen", + "saint_vincent", + "tempelberget", + "frankrikes_nationalf\u00f6rsamling", + "franska_rivieran", + "blue_mountains", + "biscayabukten", + "ju\u00e1rez", + "natti", + "lilla_bj\u00f6rnen", + "flygvapen", + "sankt_patrik", + "skogsvisslare", + "saltvatten", + "fredsdomare", + "kanal\u00f6arna", + "ringled", + "i_h\u00e4ndelse", + "k\u00f6rsb\u00e4rsfuks", + "\u00e4ngssmygare", + "edwardsj\u00f6n", + "lake_of_the_woods", + "telefoncenral", + "tv\u00e5_tigerbr\u00f6der", + "usa", + "st_albans", + "berlinerbl\u00e5tt", + "saint_lucia", + "kap_horn", + "hat_yai", + "almaaz", + "arena", + "i_det_fall", + "olympen", + "sri_lanka", + "m\u00e5rtensafton", + "drabantstad", + "f\u00e4lt", + "p\u00e5sk\u00f6n", + "viskleken", + "lake_st_clair", + "teknikpark", + "het_k\u00e4lla", + "nordsj\u00f6n", + "l\u00e4ngesen", + "innerstad", + "the_rolling_stones", + "cordon_bleu", + "s\u00e4des\u00e4rla", + "kraftverk", + "\u00f6vre_sj\u00f6n", + "gr\u00f6nsaksland", + "det_finns", + "riksbank", + "br\u00e4nda_jordens_taktik", + "pensionsfond", + "sydkoreas_nationalf\u00f6rsamling", + "heitor_villa_lobos", + "louis_joseph_gay_lussac", + "sl\u00e5ttergr\u00e4sfj\u00e4ril", + "al_ain", + "pterocarpus_indicus", + "varuhus", + "maria_fr\u00e5n_magdala", + "ny_v\u00e4rld" + ], + "RELIGION_MEMBER": [ + "anabaptist", + "guru", + "protestant", + "christin", + "parsism", + "mulla", + "shiitisk", + "gammalkatolsk", + "mormon", + "jihadist", + "muselman", + "saracen", + "baptist", + "mohammedan", + "puritan", + "sunni", + "satanist", + "presbyteriansk", + "franciskanorden", + "mon" + ], + "PRODUCT": [ + "kaffekopp", + "balkanbergen", + "deja_vu", + "justin_bieber", + "sportbil", + "vinkelj\u00e4rn", + "de_fyra_\u00e5rstiderna", + "helsk\u00e4rmsl\u00e4ge", + "effektbrytare", + "kejsarsnitt", + "rymdf\u00e4rja", + "vattenflaska", + "diego_garcia", + "bli_vuxen", + "signalbehandling", + "echinopsis_pachanoi", + "tomten", + "luftv\u00e4rns", + "norrsken", + "helsk\u00e4rm", + "k\u00e4rleksbrevet", + "ett_dockhem", + "tidsmaskin", + "terr\u00e4ngg\u00e5ende", + "k\u00f6penhamns_s_t\u00e5g", + "tredimensionell", + "den_eldr\u00f6da_bokstaven", + "kaffekanna", + "annandag", + "in_memoriam", + "allordbok", + "av_guds_n\u00e5de", + "det_ljuva_livet", + "kullager", + "flaskpost", + "duglig", + "julius_caesar", + "saint_vincent", + "tennisboll", + "julgran", + "diskett", + "pianoexpressen", + "stridsflygplan", + "the_star_spangled_banner", + "stilleben", + "den_gudomliga_komedin", + "skaplig", + "don_quixote", + "hungerspelen", + "som_om", + "monte_cristo", + "stj\u00e4rnbaneret", + "h\u00e5rdkokt", + "trettondagsafton", + "speldosa", + "dv\u00e4rgbrytare", + "sachsen_anhalt", + "die_hard", + "med_bakomliggande_tillg\u00e5ngar", + "dansgolv", + "kortslutning", + "after_burner", + "johannes_d\u00f6paren", + "s\u00e3o_tom\u00e9_och_pr\u00edncipe", + "pappersflygplan", + "polstj\u00e4rna", + "de_tre_kungad\u00f6mena", + "boxing_day", + "k\u00e4rleksbrev", + "startramp", + "d\u00f6dspolarna", + "pansarbil", + "storbritannien", + "deutsche_welle", + "m\u00e4nskliga_r\u00e4ttigheter", + "nya_testamentet", + "hjul\u00e5ngare", + "stridsyxa", + "ferdinand_magellan", + "i_grevens_tid", + "naturhistoria", + "f\u00f6rg\u00e4tmigej", + "mario_andretti", + "halfpipe", + "de_vises_sten", + "l\u00e4nstol", + "vattenbrunn", + "jag_ber_om_urs\u00e4kt", + "de_facto", + "plattformsoberoende", + "karlavagnen", + "i_sista_stund", + "den_helige_ande", + "jag_\u00e4r_ledsen", + "nordrhein_westfalen", + "segelfartyg", + "i_elfte_timmen", + "guldkompassen", + "rosettastenen", + "rosettestenen", + "mycket_v\u00e4sen_f\u00f6r_ingenting", + "badbyxa", + "bergspr\u00e4ngare", + "cook\u00f6arna", + "i_sista_\u00f6gonblicket", + "novo_mesto", + "till_minne_av", + "stj\u00e4rnfall", + "rymdstation" + ], + "LANGUAGE": [ + "panjabi", + "portugisisk", + "polsk", + "persisk", + "walesisk", + "bengali", + "rundi", + "vitrysk", + "venda", + "kashmiri", + "kongo", + "ungersk", + "akan", + "norsk", + "putsmedel", + "ungerska", + "the_haitian", + "spanska", + "norrman", + "pali", + "navajo", + "ryss", + "aymara", + "manx", + "keltisk", + "polermedel", + "malayalam", + "betoning", + "norska", + "polityr", + "hindi", + "nordsamiska", + "malajisk", + "spansk", + "portugisiska", + "guarani", + "herero", + "ryska", + "divehi", + "bengalisk", + "esperanto", + "finl\u00e4ndsk", + "komi", + "lingala", + "katalan", + "georgiska", + "hausa", + "cree", + "franska", + "georgisk", + "kikuyu", + "persiska", + "tagalog", + "marshalliska", + "arabiska", + "ido", + "marathi", + "japansk", + "quechua", + "samoan", + "tonga", + "kannada" + ], + "POLITICAL_PARTY": [ + "nationalistpartiet", + "konservativa_partiet", + "partidul_conservator", + "partit_laburista", + "republikanska_partiet", + "f\u00f3lkaflokkurin", + "united_kingdom_independence_party", + "labour", + "kommunistiska_partiet", + "kuomintang", + "comhaontas_glas", + "demokratiska_partiet", + "liberal_party", + "socialdemokratiska_partiet", + "strana_zelen\u00fdch", + "partido_popular", + "partido_democr\u00e1tico", + "demokratisk_republikanska_partiet", + "milj\u00f6partiet", + "politiskt_parti", + "folkets_parti", + "socialistiska_partiet", + "socialistpartiet", + "javna\u00f0arflokkurin", + "australiens_arbetarparti", + "opposition", + "arbeiderpartiet", + "arbetarpartiet", + "parti_populaire" + ], + "FAC": [ + "vindtunnel", + "nattvarden", + "t_cell", + "konsertsal", + "p\u00e5_jour", + "konstskola", + "porten", + "skidanl\u00e4ggning", + "underhus", + "georgskors", + "k\u00e4rnkraftverk", + "konstgalleri", + "klagomuren", + "arnold_sch\u00f6nberg", + "tr\u00e4dg\u00e5rdsstad", + "aff\u00e4rscenter", + "universitetsstad", + "skjutbana", + "konserthus", + "mall", + "kom_v\u00e4l_hem", + "h\u00f6ga_porten", + "bergtagen", + "kallmur", + "polisstation", + "godahoppsudden", + "saint_lucia", + "den_sista_m\u00e5ltiden", + "peter_den_store", + "nalle_puh", + "kvarndamm", + "trettiotre", + "de_fyra_\u00e5rstiderna", + "j\u00e4rnkorset", + "titus_livius", + "tullstation", + "xixia", + "simbass\u00e4ng", + "grundskola", + "p\u00f6_om_p\u00f6", + "triumfb\u00e5ge", + "stenmur", + "postkontor", + "l\u00e5gstadie", + "bit_f\u00f6r_bit", + "friedrichshain_kreuzberg", + "romersk_katolska_kyrkan", + "katolska_kyrkan" + ], + "SOC_ECO_CLASS": [ + "kvinnlighet", + "broderskap", + "arbetarklass", + "\u00f6verklass", + "center", + "n\u00e5gra", + "prolet\u00e4riat", + "svart_b\u00f6rs", + "samuraj", + "medelklass", + "svart_marknad", + "bourgeoisie" + ], + "RACE": [ + "the_european", + "nordkorean", + "fransm\u00e4n", + "indian_airlines", + "latino", + "turk", + "latin", + "afrikan", + "latinamerikanska", + "filippinsk", + "fransyska", + "sydamerikansk", + "korean", + "the_mexican", + "afrikansk", + "fransman", + "ostasiatisk", + "filippinska", + "judisk", + "latinamerikan", + "engelsm\u00e4n", + "fransos", + "nordeuropeisk" + ], + "RELIGION": [ + "zen", + "shinto", + "puritanism", + "adventism", + "presbyterianism", + "buddhism", + "jainism", + "manikeism", + "salafism", + "islam", + "hinduism", + "wicca", + "anabaptism", + "donatism" + ], + "GPE": [ + "guldgruva", + "saint_lawrencefloden", + "stortorg", + "centralamerika", + "saint_domingue", + "mellanamerika", + "\u0111ur\u0111evdan", + "xihu", + "kotte", + "dar_es_salaam", + "vitguld", + "sri_jayawardenapura", + "tyska_riket", + "sint_maarten", + "pandanus_tectorius", + "sj\u00f6folken", + "den_helige_ande", + "gammelstad", + "alla_hj\u00e4rtans_dag", + "helige_ande", + "gamla_stad", + "industriomr\u00e5de", + "s\u00e3o_tom\u00e9", + "hagia_sofia", + "gran_canaria", + "gamlestad", + "r\u00f6da_havet", + "sankta_barbara", + "r\u00f6da_korset", + "al_andalus", + "bergspass", + "ha_tinh", + "la_rochelle", + "kronkoloni", + "taishan", + "charlottenburg_wilmersdorf", + "vita_huset", + "vinh_long", + "la_gomera", + "tra_vinh", + "helige_anden", + "sankt_g\u00f6ran", + "v\u00e5r_fru" + ], + "UNION": [ + "itu", + "studentk\u00e5r", + "v\u00e4rldspostf\u00f6reningen", + "fackf\u00f6rening" + ], + "PERSON": [ + "prince_albert", + "julius_caesar", + "al_gore", + "saint_vincent", + "i_ching", + "don_delillo", + "jag_ocks\u00e5", + "t_benstek", + "pansarskyttefordon", + "de_witt", + "al_amin", + "igor_sikorsky", + "sankt_pers_fisk", + "maxwell_anderson", + "rudolf_hess", + "jag_med", + "cha_cha" + ], + "GENDER": [ + "miss", + "mademoiselle", + "gentleman", + "k\u00f6ns\u00f6verskridande", + "men", + "jeppe", + "boy", + "male", + "det_svaga_k\u00f6net", + "guido", + "det_t\u00e4cka_k\u00f6net", + "mina_damer_och_herrar", + "grabb", + "transgender", + "putta", + "lass", + "lilla_gumman", + "man", + "gal", + "lady" + ], + "EVENT": [ + "d\u00f6dsdans", + "filmfestival", + "v\u00e4rldsutst\u00e4llning", + "skrytr\u00e4ttigheter", + "sing_sing", + "kuwaitkriget", + "stavhopp" + ], + "ANAT": [ + "nackkota", + "cervikalkota", + "\u00f6verarm", + "willis_ring" + ], + "MEDICAL_THERAPY": [ + "blodtryck" + ], + "ner_regexes": [ + [ + "PERSON", + "\\D+ \\D+|\\D+ \\D+", + false, + [] + ] + ], + "FIRST_NAME_FEMALE": [ + "ingeg\u00e4rd", + "gabriella", + "astrid", + "eivor", + "solveig", + "charlotta", + "ir\u00e9ne", + "ann_marie", + "sara", + "carina", + "camilla", + "valborg", + "ann", + "rebecca", + "rebecka", + "josefin", + "ingegerd", + "carin", + "inga", + "marita", + "karin", + "alexandra", + "ann_charlotte", + "marie", + "sylvia", + "m\u00e4rta", + "\u00e5sa", + "elise", + "anneli", + "felicia", + "olivia", + "signe", + "linn\u00e9a", + "greta", + "kristina", + "margit", + "pia", + "sofie", + "gunnel", + "pernilla", + "inga_lill", + "maria", + "birgit", + "catharina", + "kristin", + "annette", + "lilian", + "sandra", + "ulrika", + "siv", + "maj_britt", + "kerstin", + "helene", + "viola", + "martina", + "angelica", + "ingrid", + "anna", + "helena", + "elsie", + "svea", + "kajsa", + "lilly", + "ylva", + "anne", + "victoria", + "katarina", + "maud", + "veronica", + "ingeborg", + "eva", + "dagny", + "lisa", + "susanna", + "linnea", + "emelie", + "asta", + "anita", + "gudrun", + "lisbeth", + "susanne", + "gunborg", + "anette", + "elvira", + "carolina", + "gunvor", + "inger", + "mikaela", + "hanna", + "marina", + "ther\u00e9se", + "vilhelmina", + "ruth", + "doris", + "ann_mari", + "gunilla", + "monika", + "petra", + "ragnhild", + "agnes", + "lena", + "charlotte", + "linda", + "catarina", + "ann_christin", + "dagmar", + "helen", + "ella", + "annika", + "josefine", + "britt", + "eleonora", + "evelina", + "jeanette", + "ida", + "viktoria", + "malin", + "teresia", + "ellinor", + "ester", + "jessica", + "margaretha", + "anna_karin", + "jenny", + "nina", + "elsa", + "julia", + "sonja", + "johanna", + "elisabeth", + "britta", + "marie_louise", + "stina", + "elisabet", + "caroline", + "sigrid", + "matilda", + "erika", + "lovisa", + "gunhild", + "ingela", + "margareta", + "mary", + "mona", + "amanda", + "maja", + "irene", + "annelie", + "lillemor", + "christine", + "ellen", + "laila", + "emma", + "gerd", + "britt_marie", + "marianne", + "irma", + "magdalena", + "therese", + "iris", + "alice", + "anne_marie", + "elin", + "harriet", + "mari", + "edit", + "aina", + "yvonne", + "frida", + "birgitta", + "jennie", + "berit", + "annie", + "cecilia", + "vera", + "ebba", + "gun", + "anna_lena", + "hillevi", + "rut", + "barbro", + "emilia", + "brita", + "ulla_britt", + "agneta", + "louise", + "karolina", + "lina", + "madeleine", + "josefina", + "evy", + "christina", + "gertrud", + "ulla", + "rose_marie", + "sofia", + "linn", + "maj", + "monica", + "hel\u00e9n" + ], + "FIRST_NAME_MALE": [ + "emanuel", + "valdemar", + "kenneth", + "roger", + "jacob", + "valter", + "artur", + "\u00e5ke", + "gustaf", + "fredrik", + "conny", + "sture", + "edvin", + "bengt", + "christoffer", + "ingemar", + "dennis", + "joakim", + "ragnar", + "torsten", + "mats", + "rikard", + "jesper", + "jonathan", + "georg", + "rasmus", + "edvard", + "peter", + "arnold", + "ingmar", + "jens", + "kjell", + "s\u00f6ren", + "ingvar", + "anders", + "bert", + "daniel", + "tore", + "josef", + "niclas", + "kristoffer", + "johannes", + "carl", + "g\u00f6te", + "tobias", + "alexander", + "linus", + "niklas", + "oscar", + "alf", + "pontus", + "nicklas", + "ove", + "inge", + "magnus", + "kristian", + "olof", + "einar", + "ivar", + "ola", + "max", + "knut", + "patrik", + "bror", + "hugo", + "andreas", + "henry", + "mikael", + "john", + "jakob", + "kim", + "ludvig", + "tage", + "ulf", + "kurt", + "hans", + "herbert", + "sigurd", + "helge", + "emil", + "p\u00e4r", + "b\u00f6rje", + "juhani", + "krister", + "johnny", + "elias", + "ture", + "sven", + "egon", + "anton", + "albin", + "h\u00e5kan", + "klas", + "sixten", + "axel", + "lars", + "gert", + "bernt", + "henning", + "bj\u00f6rn", + "joel", + "jimmy", + "roland", + "claes", + "tord", + "bo", + "ronny", + "allan", + "jan", + "urban", + "vilhelm", + "christian", + "arne", + "morgan", + "verner", + "folke", + "leif", + "paul", + "mattias", + "marcus", + "tony", + "sten", + "uno", + "stig", + "nils", + "william", + "markus", + "otto", + "johan", + "benny", + "per", + "martin", + "olov", + "philip", + "oskar", + "gustav", + "pierre", + "tommy", + "g\u00f6sta", + "rickard", + "gerhard", + "henrik", + "hjalmar", + "eric", + "olle", + "evert", + "viktor", + "andr\u00e9", + "adam", + "alvar", + "arvid", + "robin", + "holger", + "simon", + "harald", + "rolf", + "richard", + "alfred", + "sebastian", + "ernst", + "samuel", + "sigvard", + "bertil", + "mathias", + "gunnar", + "david", + "sune", + "reinhold", + "filip", + "birger", + "wilhelm", + "stefan", + "jan_erik", + "robert", + "thomas", + "petter", + "tomas", + "dan", + "harry", + "ivan", + "erik", + "rune", + "j\u00f6rgen", + "erling", + "jonas", + "jonny", + "yngve", + "christer", + "lennart", + "lars_erik", + "tom", + "albert", + "staffan", + "erland", + "michael", + "victor", + "torbj\u00f6rn", + "g\u00f6ran", + "kent", + "karl" + ], + "FIRST_NAME": [ + "emanuel", + "valdemar", + "ingeg\u00e4rd", + "eivor", + "solveig", + "charlotta", + "gustaf", + "fredrik", + "sture", + "valborg", + "torsten", + "ingegerd", + "inga", + "edvard", + "peter", + "ingmar", + "karin", + "kjell", + "anders", + "tore", + "gunnel", + "maria", + "g\u00f6te", + "catharina", + "annette", + "tobias", + "sandra", + "siv", + "helene", + "ingrid", + "ivar", + "elsie", + "ola", + "helena", + "anne", + "henry", + "eva", + "dagny", + "tage", + "lisbeth", + "gunborg", + "elvira", + "gunvor", + "marina", + "petra", + "ragnhild", + "gert", + "jimmy", + "charlotte", + "catarina", + "jan", + "annika", + "britt", + "verner", + "leif", + "nina", + "per", + "julia", + "sonja", + "tommy", + "elisabet", + "g\u00f6sta", + "caroline", + "erika", + "lovisa", + "adam", + "holger", + "simon", + "alfred", + "christine", + "ellen", + "irma", + "therese", + "alice", + "anne_marie", + "birger", + "aina", + "mari", + "stefan", + "jennie", + "berit", + "petter", + "anna_lena", + "brita", + "agneta", + "karolina", + "madeleine", + "evy", + "rose_marie", + "torbj\u00f6rn", + "tom", + "lars_erik", + "linn", + "g\u00f6ran", + "\u00e5ke", + "astrid", + "edvin", + "conny", + "ir\u00e9ne", + "carina", + "christoffer", + "camilla", + "dennis", + "rebecca", + "rebecka", + "mats", + "rikard", + "carin", + "jonathan", + "georg", + "rasmus", + "alexandra", + "\u00e5sa", + "m\u00e4rta", + "ingvar", + "bert", + "daniel", + "birgit", + "lilian", + "oscar", + "maj_britt", + "alf", + "nicklas", + "martina", + "angelica", + "olof", + "einar", + "svea", + "kajsa", + "lilly", + "knut", + "patrik", + "victoria", + "mikael", + "john", + "lisa", + "emelie", + "hans", + "herbert", + "gudrun", + "susanne", + "anette", + "p\u00e4r", + "b\u00f6rje", + "krister", + "egon", + "mikaela", + "h\u00e5kan", + "sixten", + "ann_mari", + "axel", + "monika", + "bj\u00f6rn", + "roland", + "tord", + "bo", + "ella", + "christian", + "arne", + "morgan", + "viktoria", + "mattias", + "tony", + "sten", + "uno", + "otto", + "johan", + "elisabeth", + "olov", + "gustav", + "pierre", + "rickard", + "matilda", + "evert", + "ingela", + "viktor", + "mary", + "alvar", + "arvid", + "rolf", + "richard", + "sebastian", + "lillemor", + "sigvard", + "gunnar", + "gerd", + "britt_marie", + "marianne", + "sune", + "magdalena", + "reinhold", + "filip", + "frida", + "annie", + "thomas", + "vera", + "tomas", + "harry", + "gun", + "rune", + "erling", + "ulla_britt", + "josefina", + "christina", + "christer", + "lennart", + "gertrud", + "ulla", + "sofia", + "michael", + "monica", + "rut", + "karl", + "roger", + "kenneth", + "jacob", + "valter", + "gabriella", + "ann_marie", + "bengt", + "sara", + "ingemar", + "joakim", + "ragnar", + "jesper", + "arnold", + "ann_charlotte", + "sylvia", + "anneli", + "olivia", + "signe", + "linn\u00e9a", + "s\u00f6ren", + "josef", + "kristoffer", + "johannes", + "carl", + "alexander", + "linus", + "viola", + "inge", + "anna", + "ylva", + "hugo", + "andreas", + "ludvig", + "asta", + "sigurd", + "emil", + "johnny", + "carolina", + "sven", + "hanna", + "ruth", + "lars", + "gunilla", + "henning", + "joel", + "linda", + "dagmar", + "helen", + "ronny", + "josefine", + "eleonora", + "evelina", + "paul", + "malin", + "ellinor", + "ester", + "anna_karin", + "jenny", + "elsa", + "johanna", + "philip", + "oskar", + "britta", + "marie_louise", + "sigrid", + "hjalmar", + "eric", + "gunhild", + "mona", + "irene", + "bertil", + "mathias", + "emma", + "david", + "iris", + "edit", + "jan_erik", + "ebba", + "ivan", + "erik", + "hillevi", + "emilia", + "jonas", + "jonny", + "victor", + "lina", + "hel\u00e9n", + "artur", + "ann", + "josefin", + "marita", + "marie", + "jens", + "felicia", + "elise", + "greta", + "kristina", + "margit", + "sofie", + "pia", + "pernilla", + "inga_lill", + "niclas", + "kristin", + "niklas", + "pontus", + "kerstin", + "ove", + "kristian", + "magnus", + "max", + "katarina", + "veronica", + "bror", + "maud", + "ingeborg", + "jakob", + "kim", + "susanna", + "linnea", + "ulf", + "kurt", + "anita", + "helge", + "juhani", + "elias", + "ture", + "inger", + "anton", + "ther\u00e9se", + "albin", + "klas", + "vilhelmina", + "doris", + "bernt", + "agnes", + "lena", + "ann_christin", + "claes", + "allan", + "urban", + "vilhelm", + "folke", + "jeanette", + "ida", + "marcus", + "teresia", + "stig", + "markus", + "margaretha", + "nils", + "jessica", + "william", + "benny", + "martin", + "stina", + "gerhard", + "henrik", + "olle", + "margareta", + "andr\u00e9", + "robin", + "maja", + "amanda", + "harald", + "annelie", + "ernst", + "samuel", + "laila", + "elin", + "harriet", + "wilhelm", + "yvonne", + "birgitta", + "robert", + "cecilia", + "dan", + "j\u00f6rgen", + "barbro", + "louise", + "yngve", + "albert", + "staffan", + "erland", + "maj", + "kent", + "ulrika" + ], + "LAST_NAME": [ + "olsson", + "sj\u00f6gren", + "ottosson", + "bergqvist", + "berg", + "\u00e5kesson", + "isaksson", + "b\u00e4ckstr\u00f6m", + "bergman", + "ljung", + "augustsson", + "ros\u00e9n", + "klasson", + "nilsson", + "holmgren", + "holmstr\u00f6m", + "ek", + "knutsson", + "oskarsson", + "sj\u00f6str\u00f6m", + "hellberg", + "malm", + "hagstr\u00f6m", + "s\u00f6derstr\u00f6m", + "pettersson", + "m\u00e5rtensson", + "viklund", + "johnsson", + "lilja", + "carlsson", + "ekberg", + "palm", + "h\u00f6glund", + "lindgren", + "lindstr\u00f6m", + "borg", + "molin", + "andersson", + "bostr\u00f6m", + "sundqvist", + "berglund", + "eliasson", + "hansson", + "s\u00f6derlund", + "martinsson", + "blomberg", + "lundstr\u00f6m", + "s\u00f6derberg", + "norberg", + "blom", + "dahlberg", + "str\u00f6m", + "englund", + "jakobsson", + "berggren", + "lundin", + "sj\u00f6berg", + "hedman", + "larsson", + "\u00f6berg", + "\u00f6hman", + "magnusson", + "hedlund", + "ekman", + "jensen", + "lund", + "engstr\u00f6m", + "sk\u00f6ld", + "lundmark", + "lind", + "hedstr\u00f6m", + "jansson", + "forslund", + "dahl", + "str\u00f6mberg", + "gustavsson", + "forsberg", + "bj\u00f6rklund", + "holm", + "lundberg", + "bengtsson", + "h\u00e5kansson", + "berntsson", + "gustafsson", + "t\u00f6rnqvist", + "wahlstr\u00f6m", + "\u00f6stlund", + "eriksson", + "lindblom", + "hjalmarsson", + "erlandsson", + "lindblad", + "dahlgren", + "m\u00e5nsson", + "malmberg", + "b\u00f6rjesson", + "nyberg", + "st\u00e5hl", + "nygren", + "bj\u00f6rk", + "lundgren", + "nordstr\u00f6m", + "m\u00f6ller", + "\u00e5gren", + "nielsen", + "lindahl", + "svensson", + "vikstr\u00f6m", + "kristiansson", + "karlsson", + "sv\u00e4rd", + "lundqvist", + "lundkvist", + "sj\u00f6din", + "strand", + "petersson", + "p\u00e5lsson", + "linder", + "andreasson", + "adolfsson", + "blomqvist", + "lindqvist", + "nyman", + "edlund", + "fredriksson", + "paulsson", + "sundberg", + "h\u00e4gglund", + "nordin", + "lind\u00e9n", + "samuelsson", + "l\u00f6fgren", + "davidsson", + "sandstr\u00f6m", + "gunnarsson", + "nord", + "stenberg", + "norman", + "eklund", + "josefsson", + "roos", + "moberg", + "ljungberg", + "g\u00f6ransson", + "n\u00e4slund", + "sundin", + "lindholm", + "falk", + "\u00e5berg", + "alm", + "claesson", + "boman", + "aronsson", + "sundstr\u00f6m", + "hedberg", + "h\u00f6gberg", + "lindell", + "lindkvist", + "ohlsson", + "skoglund", + "hallberg", + "ericsson", + "melin", + "holmberg", + "lindberg", + "holmqvist", + "henriksson", + "ivarsson", + "fransson", + "hellstr\u00f6m", + "strandberg", + "\u00e5str\u00f6m", + "abrahamsson", + "sandberg", + "hansen", + "bergstr\u00f6m", + "persson", + "franz\u00e9n", + "nor\u00e9n", + "haglund", + "friberg", + "johannesson", + "ekstr\u00f6m", + "jonasson", + "axelsson", + "mattsson", + "wallin", + "danielsson", + "olofsson", + "j\u00f6nsson", + "bj\u00f6rkman", + "hermansson", + "arvidsson", + "olausson", + "jonsson", + "nystr\u00f6m", + "dahlstr\u00f6m", + "johansson", + "wikstr\u00f6m", + "pedersen" + ], + "OTHER_PRONOUN": [ + "it" + ], + "LAST_NAME_MALE": [], + "LAST_NAME_FEMALE": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "abbedissa": "pater", + "abbesses": "abbots", + "aktris": "sk\u00e5despelare", + "baronessa": "baron", + "aff\u00e4rskvinna": "aff\u00e4rsman", + "working_girl": "aff\u00e4rsman", + "f\u00e5gelunge": "gaur", + "panik": "son", + "dotter": "son", + "hertiginna": "hertig", + "kejsarinna": "kejsare", + "femme_fatale": "besv\u00e4rjare", + "trollkvinna": "magiker", + "delila": "besv\u00e4rjare", + "hunn": "he", + "kvinnlig": "male", + "feminin": "maskulin", + "gal": "kolli", + "t\u00f6s": "guido", + "flicka": "guido", + "j\u00e4nta": "guido", + "tjej": "gille", + "adolescens": "kolli", + "guvernant": "guvern\u00f6r", + "sondotter": "sonson", + "dotterdotter": "sonson", + "farmor": "farfar", + "mormor": "farfar", + "hennes": "deras", + "henne": "lia", + "heroin": "heros", + "hj\u00e4ltinna": "heros", + "sitt": "deras", + "v\u00e4rdinna": "genom_dina_\u00f6gon", + "lady": "lort", + "fru": "human", + "hyresv\u00e4rdinna": "hyresv\u00e4rd", + "putta": "pojke", + "lass": "pojke", + "mass\u00f6s": "mass\u00f6r", + "h\u00e4rskarinna": "master", + "m\u00e4tress": "master", + "moder": "pater", + "mutter": "sira", + "matrix": "fader", + "nunna": "munk", + "sista": "munk", + "nun": "munk", + "poliskvinna": "polisman", + "pr\u00e4stinna": "spiritual", + "desiree_heslop": "pr\u00edncipe", + "pr\u00edncipe": "regulus", + "prinsessa": "regulus", + "princessa": "prince", + "danaus_gilippus": "konung", + "reg": "konung", + "drottning": "drott", + "hetman": "konung", + "queens": "andra_kungaboken", + "h\u00e4n": "hy", + "hona": "hy", + "syster": "bror", + "naja": "brorsa", + "fr\u00f6ken": "bachelor", + "ogift_kvinna": "ungkarl", + "gammal_ungm\u00f6": "bachelor", + "taleskvinna": "talesperson", + "styvdotter": "styvson", + "fostermor": "styvfar", + "plastmamma": "styvfar", + "styvmor": "styvfader", + "flygv\u00e4rdinna": "f\u00f6rvaltare", + "servitris": "servit\u00f6r", + "\u00e4nka": "\u00e4nkling", + "marita": "\u00e4r", + "hustru": "marit", + "h\u00e4xa": "magiker", + "hex": "magiker", + "striga": "magiker", + "r\u00f6dtunga": "magiker", + "wicca": "magiker", + "norn": "magiker", + "arnoglossus_scapha": "magiker", + "trollpacka": "magiker", + "kvinna": "din\u00e9", + "domna": "human", + "kvinnor": "men", + "boy": "tjej", + "gille": "t\u00f6s", + "dr\u00e4ng": "adolescens", + "pojke": "tjej" + }, + "other_gender_swap": { + "spindlarna": "hennes", + "deras": "sitt", + "sitt": "deras", + "lia": "deras", + "h\u00f6": "hona", + "ofs": "hunn", + "h\u00e4n": "h\u00f6", + "he": "ofs", + "hy": "ofs", + "seine": "deras", + "hunn": "h\u00f6", + "hona": "ofs", + "hennes": "deras", + "henne": "deras" + }, + "en_pronoun2gender": { + "they": [ + "transperson", + "homosexuell", + "transgender", + "queer", + "k\u00f6ns\u00f6verskridande" + ], + "he": [ + "dandy", + "maskulin", + "boy", + "isle_of_man", + "guido", + "k\u00e4ft", + "snubbe", + "jalu", + "individ", + "human", + "kolli", + "gentleman", + "man", + "m\u00e4nniska", + "little_boy", + "adelsman", + "bemanna", + "pojke", + "jeppe", + "male", + "gaur", + "din\u00e9", + "dr\u00e4ng", + "grabb", + "gille" + ], + "she": [ + "miss", + "flicka", + "kvinna", + "lesbisk", + "brasa", + "missa", + "tjej", + "fru", + "jungfru", + "gal", + "m\u00f6", + "misse", + "adolescens", + "feminin", + "lesbian", + "flickebarn", + "lady", + "j\u00e4nta", + "bomma", + "t\u00f6s", + "mademoiselle", + "fr\u00f6ken", + "det_t\u00e4cka_k\u00f6net", + "det_svaga_k\u00f6net", + "kvinnlig", + "miss_a", + "hunn", + "madam", + "domna" + ] + }, + "en_pronoun2pronoun": { + "he": [ + "he", + "lia", + "seine", + "hy", + "h\u00e4n" + ], + "she": [ + "hona", + "henne", + "sitt", + "hunn", + "hennes", + "h\u00e4n" + ], + "they": [ + "spindlarna", + "ofs", + "sitt", + "lia", + "deras", + "h\u00f6" + ], + "it": [ + "dom_h\u00e4r", + "det_d\u00e4r", + "den_d\u00e4r", + "bt", + "den_h\u00e4r", + "per_se", + "denna", + "hetta", + "det_h\u00e4r", + "dess", + "it", + "denne", + "dessa", + "de_h\u00e4r", + "dass", + "essa", + "de_d\u00e4r", + "dom_d\u00e4r" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/sw.json b/data_tooling/pii_processing/ontology/data/sw.json new file mode 100644 index 0000000..f2be391 --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/sw.json @@ -0,0 +1,637 @@ +{ + "LANGUAGE": [ + "kisomali", + "kicheki", + "ingereza", + "kijapani", + "kongo", + "kiyoruba", + "kilatini", + "kiarabu", + "mkazaki", + "kisantalusia", + "kisanskrit", + "ganda", + "kiositani", + "kiamhari", + "hindi", + "kilingala", + "ya_korea", + "kihindi", + "kibengali", + "kiholanzi", + "lafudhi", + "kingala", + "kiswidi", + "kifaransa", + "kiurdu", + "wanavaho", + "kiesperanto", + "kiamhara", + "mnavaho", + "kishona", + "zunguka", + "tonga" + ], + "PLANT": [ + "cheri", + "karoti", + "popoo", + "mkranberi", + "mwanasanaa", + "maharagwe", + "koliflawa", + "mchengele", + "mierebi", + "kibibimlima", + "mchikichi", + "yungiyungi", + "alizeti", + "beri_ya_mreteni", + "chenza", + "mwanzi" + ], + "PUBLIC_FIGURE": [ + "krushchov", + "akira_kurosawa", + "che_guevara", + "edward_albee", + "henrik_ibsen", + "david_livingstone", + "eduard_buchner", + "james_michener", + "maria_magdalena", + "winston_churchill", + "conrad_aiken", + "karl_landsteiner", + "ivan_pavlov", + "paul_mccartney", + "richard_smalley", + "francis_crick", + "isaac_newton", + "victor_hugo", + "joseph_smith", + "daudi", + "yaakub", + "george_harrison", + "kutumaini", + "ronald_norrish", + "richard_wagner", + "thornton_wilder", + "marie_curie", + "michael_jackson", + "carl_sandburg", + "thomas_hobbes", + "samuel_beckett", + "galileo_galilei", + "robert_koch", + "john_steinbeck", + "edmund_hillary", + "vincent_van_gogh", + "anne_boleyn", + 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"\u0b87\u0ba8\u0bcd\u0ba4\u0bc1\u0bae\u0bc1\u0b95\u0bbf", + "\u0bb7\u0baa\u0bb0\u0bbf", + "\u0ba4\u0b99\u0bcd\u0b95\u0bae\u0ba4\u0bbf", + "\u0baa\u0bb0\u0bbf\u0bae\u0bb3\u0bbe", + "\u0b87\u0b9a\u0bc8\u0bae\u0bc1\u0bb0\u0b9a\u0bc1", + "\u0b8e\u0bb4\u0bbf\u0bb2\u0bbf\u0b9a\u0bc8" + ], + "FIRST_NAME_MALE": [ + "\u0bb0\u0bbe\u0b9c\u0b9a\u0bc7\u0b95\u0bb0\u0bcd", + "\u0bae\u0b95\u0bbf\u0bb4\u0bcd\u0ba8\u0ba9\u0bcd", + "\u0b89\u0ba4\u0bcd\u0ba4\u0bae\u0bcd", + "\u0b86\u0ba4\u0bbf\u0b9a\u0b99\u0bcd\u0b95\u0bb0\u0bbe", + "\u0b8e\u0bb4\u0bbf\u0bb1\u0bcd\u0baa\u0bbe\u0bb5\u0bbf\u0baf\u0ba9\u0bcd", + "\u0bb5\u0bbe\u0b9a\u0bc1", + "\u0bb5\u0bb7\u0bbf\u0bb7\u0bcd\u0b9f\u0bb0\u0bcd", + "\u0b85\u0b95\u0bbe\u0ba4\u0bcd", + "\u0b9a\u0ba4\u0bcd\u0baf\u0bc7\u0ba8\u0bcd\u0ba4\u0bbf\u0bb0\u0bbe", + "\u0bae\u0ba3\u0bbf\u0bae\u0bb2\u0bc8", + "\u0b8e\u0bb4\u0bbf\u0bb2\u0bcd\u0bae\u0bb2\u0bc8", + "\u0ba4\u0b99\u0bcd\u0b95\u0b95\u0bcd\u0b95\u0ba4\u0bbf\u0bb0\u0bcd", + "\u0ba4\u0b9a\u0bb0\u0ba4\u0ba9\u0bcd", + "\u0baf\u0bc7\u0bb5\u0bbe\u0ba9\u0bcd", + "\u0b87\u0b9a\u0bc8\u0b95\u0bcd\u0b95\u0bb2\u0bc8\u0bb5\u0bbe\u0ba3\u0ba9\u0bcd", + "\u0b9a\u0b9e\u0bcd\u0b9c\u0bcb\u0b95\u0bcd", + "\u0ba4\u0b95\u0bcd\u0bb7\u0bc7\u0bb7\u0bcd", + "\u0b8f\u0bb4\u0bbf\u0b9a\u0bc8", + "\u0b85\u0b95\u0bb0\u0ba9\u0bcd", + "\u0b86\u0ba4\u0bbf\u0ba4\u0bc7\u0bb5\u0bbe", + "\u0bb0\u0b95\u0bc1\u0baa\u0ba4\u0bbf", + "\u0ba8\u0bae\u0bcd\u0baa\u0bbf", + "\u0bb5\u0ba3\u0bcd\u0ba3\u0ba9\u0bcd", + "\u0ba8\u0ba9\u0bcd\u0ba9\u0bc2\u0bb2\u0ba9\u0bcd", + "\u0bb5\u0bb0\u0bc1\u0ba3\u0bcd\u0b95\u0bc1\u0bae\u0bbeh", + "\u0bb0\u0bbe\u0b9c\u0bbe", + "\u0ba4\u0b99\u0bcd\u0b95\u0bb0\u0bbe\u0b90;", + "\u0bb5\u0bbe\u0ba9\u0bae\u0bbe\u0bae\u0bb2\u0bc8", + "\u0b85\u0b95\u0bcb\u0bb0\u0bbe", + "\u0b86\u0b95\u0bb0\u0bcd\u0ba3\u0bbe,", + "\u0ba8\u0ba9\u0bcd\u0bae\u0ba3\u0bbf", + "\u0ba8\u0ba9\u0bcd\u0ba9\u0bbe\u0baf\u0b95\u0bae\u0bcd", + "\u0b90\u0baf\u0bbe", + "\u0bb9\u0bb7\u0bcd\u0bb5\u0bbf\u0ba8\u0bcd\u0bb0\u0ba9\u0bcd", + "\u0b95\u0b99\u0bcd\u0b95\u0bc8\u0b95\u0bc6\u0bbe\u0ba3\u0bcd\u0b9f\u0bbe\u0ba9\u0bcd", + "\u0ba4\u0b99\u0bcd\u0b95\u0ba4\u0bcd\u0ba4\u0bae\u0bbf\u0bb4\u0bcd", + "\u0b9a\u0ba8\u0bcd\u0ba4\u0bbe\u0ba9\u0bae\u0bcd", + "\u0b87\u0ba8\u0bcd\u0ba4\u0bbf\u0bb0\u0b95\u0bc1\u0bae\u0bbe\u0bb0\u0bcd", + "\u0baa\u0b95\u0bc1\u0baa\u0bc1\u0ba4\u0bcd\u0bb0\u0ba9\u0bcd", + "\u0baa\u0b95\u0bcd\u0ba4\u0bb5\u0b9a\u0bcd\u0b9a\u0bb2\u0bae\u0bcd", + "\u0baa\u0ba4\u0bcd\u0bb0\u0bbf\u0ba8\u0bbe\u0ba4\u0ba9\u0bcd", + "\u0bb5\u0bb0\u0ba4\u0bb0\u0bbe\u0b9c\u0bcd", + "\u0b86\u0ba3\u0bcd\u0b9f\u0bb0\u0bcd\u0bb8\u0ba9\u0bcd", + "\u0b95\u0b9f\u0bb0\u0bcd", + "\u0b85\u0b95\u0bb2\u0bcd", + "\u0b9a\u0b9a\u0bcd\u0b9a\u0bbf\u0ba4\u0bbe\u0ba8\u0ba8\u0bcd\u0ba4\u0bae\u0bcd", + "\u0b85\u0b9c\u0baf\u0bcd", + "\u0b9a\u0b99\u0bcd\u0b95\u0ba9\u0bcd", + "\u0b87\u0ba8\u0bcd\u0ba4\u0bbf\u0bb5\u0bbe\u0bb0\u0bcd", + "\u0bb8\u0bcd\u0bb0\u0bc0\u0bb0\u0bbe\u0bae\u0bcd", + "\u0b87\u0b9f\u0bc8\u0b95\u0bcd\u0b95\u0bbe\u0b9f\u0ba9\u0bcd", + "\u0baf\u0bbe\u0bb4\u0bb0\u0b9a\u0ba9\u0bcd", + "\u0baa\u0ba4\u0bcd\u0bb0\u0bc1\u0bb9\u0bb0\u0bbf", + "\u0bb5\u0bb2\u0bcd\u0bb2\u0bb0\u0b9a\u0bc1", + "\u0b86\u0ba4\u0bbf", + "\u0baa\u0b95\u0bc1\u0baa\u0bb2\u0bbf", + "\u0baf\u0bc2\u0bb5\u0bb0\u0bbe\u0b9c\u0bcd", + "\u0ba8\u0bae\u0bcd\u0baa\u0bc6\u0bb0\u0bc1\u0bae\u0bbe\u0ba9\u0bcd", + "\u0b87\u0b9a\u0bc8\u0b9a\u0bcd\u0b9a\u0bc6\u0bb2\u0bcd\u0bb5\u0ba9\u0bcd", + "\u0bb0\u0bbe\u0b9c\u0bc0\u0bb5\u0bcd", + "\u0b89\u0b9c\u0bc7\u0bb7\u0bcd", + "\u0b86\u0ba4\u0bbf\u0ba4\u0bcd\u0baf\u0bbe", + "\u0b86\u0ba9\u0ba8\u0bcd\u0ba4", + "\u0b8e\u0bb4\u0bbf\u0bb2\u0bb0\u0b9a\u0ba9\u0bcd", + "\u0ba8\u0b9f\u0bcd\u0baa\u0bc1\u0b9a\u0bcd\u0b9a\u0bc6\u0bb2\u0bcd\u0bb5\u0ba9\u0bcd", + "\u0bb0\u0bae\u0ba3\u0ba9\u0bcd", + "\u0b8a\u0bb0\u0bcd\u0b9c\u0bbf\u0ba4\u0bcd", + "\u0ba8\u0b9f\u0bc7\u0bb7\u0bcd", + "\u0bae\u0ba3\u0bbf\u0bae\u0bbe\u0bb0\u0bcd\u0baa\u0ba9\u0bcd", + "\u0ba4\u0b99\u0bcd\u0b95\u0bb5\u0bc7\u0bb2\u0bcd", + 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"terry_pratchett", + "stephen_king", + "francis_crick", + "alfred_eisenstaedt", + "victor_hugo", + "edwin_hubble", + "colette", + "milton_friedman", + "edward_gibbon", + "\u0131_robert", + "mary_stuart", + "jefferson_davis", + "george_stephenson", + "george_burns", + "george_harrison", + "george_orwell", + "arthur_koestler", + "richard_wagner", + "williams", + "pancho_villa", + "marie_curie", + "\u0131_william", + "francis_galton", + "mary_martin", + "michael_jackson", + "louis_jolliet", + "thomas_hobbes", + "ve_benzeri", + "edward_weston", + "el_greco", + "samuel_beckett", + "maximian", + "robert_a_millikan", + "aram_ha\u00e7aturyan", + "galileo_galilei", + "ernest_bevin", + "jane_goodall", + "john_donne", + "robert_koch", + "joseph_goebbels", + "george_eastman", + "john_steinbeck", + "petrus", + "edmund_hillary", + "vincent_van_gogh", + "martina_navr\u00e1tilov\u00e1", + "anne_boleyn", + "josef_stalin", + "john_ruskin", + "robert_burns", + "thomas_paine", + "liliuokalani", + "steven_weinberg", + "mary_pickford", + "hans_fischer", + "emiliano_zapata", + "karl_barth", + "yuri_gagarin", + "willem_einthoven", + "samuel_johnson", + "marie_antoinette", + "frenk", + "giuseppe_verdi", + "e", + "karl_jaspers", + "konrad_adenauer", + "norbert_wiener", + "maurice_chevalier", + "gottlieb_daimler", + "\u0131_serhas", + "frank_sinatra", + "abel_tasman", + "katharine_hepburn", + "henri_becquerel", + "henri_matisse", + "louis_pasteur", + "richard_strauss", + "leslie_howard", + "hugo_grotius", + "mahalia_jackson", + "ben_shahn", + "john_ford", + "stephen_foster", + "gertrude_stein", + "sarah_bernhardt", + "v", + "philip_marlowe", + "akira_kurosava", + "luigi_pirandello", + "t_s_eliot", + "dorothea_lange", + "charles_de_gaulle", + "paul_von_hindenburg", + "ilk", + "y", + "henry_moore", + "holden", + "mary_mallon", + "ralph_bunche", + "charles_lindbergh", + "vincenzo_bellini", + "orman_m\u00fchendisi", + "samuel_barber", + "f", + "ludwig_wittgenstein", + "august_strindberg", + "thomas_mann", + "charles_goodyear", + "dante_alighieri", + "margot_fonteyn", + "peter_pan", + "james_tobin", + "dr_john_watson", + "giacomo_puccini", + "fridtjof_nansen", + "louis_braille", + "herbert_marcuse", + "mungo_park", + "benedict_arnold", + "paul_verlaine", + "q", + "robert_johnson", + "james_dean", + "kumanda", + "mason", + "marie_tussaud", + "roger_bannister", + "alessandro_manzoni", + "joseph_priestley", + "hal", + "nicolas_poussin", + "andrea_mantegna", + "joseph_pulitzer", + "james_naismith", + "oscar_wilde", + "philip_roth", + "j_d_salinger", + "richard_trevithick", + "heinrich_schliemann", + "eli_whitney", + "laurence_olivier", + "pierre_larousse", + "christiaan_eijkman", + "adolf_eichmann", + "francis_bacon", + "pete_seeger", + "konstantin_stanislavski", + "john_wycliffe", + "a", + "morris", + "norman_rockwell", + "boris_spassky", + "james_brown", + "william_hogarth", + "charles_baudelaire", + "luigi_cherubini", + "david_ricardo", + "henri_labrouste", + "mary_leakey", + "charlie_parker", + "james_franck", + "william_crookes", + "nellie_bly", + "weber", + "warburg", + "yakup", + "albert_schweitzer", + "giulio_natta", + "saint_martin", + "johannes_kepler", + "william_s_burroughs", + "max_planck", + "osman_gazi", + "william_blake", + "t_e_lawrence", + "john_bardeen", + "sarah_vaughan", + "scott_joplin", + "carl_lewis", + "george_vancouver", + "canberra", + "elias_canetti", + "edward_jenner", + "oscar_robertson", + "cole_porter", + "benjamin_west", + "jean_luc_godard", + "konstantin", + "graham_greene", + "frans_hals", + "lars_onsager", + "margaret_mitchell", + "william_herschel", + "mikhail_baryshnikov", + "montesquieu", + "arthur_rubinstein", + "arthur_compton", + "niels_bohr", + "bertrand_russell", + "michael_faraday", + "john_d_rockefeller", + "anthony_burgess", + "jan_tinbergen", + "robert_venturi", + "bernard_baruch", + "rudolf_diesel", + "walt_disney", + "ben_jonson", + "h_l_mencken", + "gabriel_lippmann", + "benny_goodman", + "friedrich_engels", + "jane_austen", + "charles_laughton", + "gustav_mahler", + "ed_sullivan", + "phil_collins", + "robert_redford", + "jack_dempsey", + "richard_feynman", + "wolfgang_pauli", + "v_george", + "theodore_dreiser", + "tu\u011fgeneral", + "theodor_mommsen", + "andrew_huxley", + "marcel_proust", + "magdalal\u0131_meryem", + "thomas_more", + "homo_heidelbergensis", + "paul_hindemith", + "elizabeth_taylor", + "anne_sullivan", + "sergey_rahmaninov", + "paul_robeson", + "daniel_jones", + "william_golding", + "william_caxton", + "john_milton", + "peter_stuyvesant", + "ethel_merman", + "don_ki\u015fot", + "samuel_adams", + "albert_speer", + "james_baldwin", + "indira_gandhi", + "jane_seymour", + "george_gershwin", + "alberto_giacometti", + "e_t_a_hoffmann", + "frank_whittle", + "alfred_nobel", + "jesse_owens", + "daniel_rutherford", + "marco_polo", + "caravaggio", + "m", + "marcel_marceau", + "allen_ginsberg", + "fred_zinnemann", + "daniel_bernoulli", + "guillaume_apollinaire", + "antoine_watteau", + "joseph_henry", + "henri_bergson", + "boris_karloff", + "gottfried_leibniz", + "pierre_corneille", + "patrick_white", + "saul_steinberg", + "catherine_howard", + "hans_christian_andersen", + "reich", + "william_morris", + "cary_grant", + "pieter_zeeman", + "glenn_miller", + "pablo_picasso", + "marian_anderson", + "natalie_wood", + "l_ron_hubbard", + "thomas_moore", + "kurt_weill", + "otto_hahn", + "christiaan_huygens", + "hector_berlioz", + "lucille_ball", + "paul_simon", + "claudio_monteverdi", + "john_galsworthy", + "henrik_\u0131bsen", + "robert_robinson", + "o", + "adam_smith", + "william_james", + "u", + "jean_harlow", + "henry_miller", + "karl_marx", + "friedrich_nietzsche", + "i", + "jimmy_durante", + "john_wesley", + "\u0131_selevkos_nikator", + "sandro_botticelli", + "carson_mccullers", + "nikola_tesla", + "al_capone", + "charles_barkley", + "billy_graham", + "robert_schumann", + "mel_gibson", + "le_corbusier", + "carlo_goldoni", + "john_locke", + "alexis_carrel", + "joseph_marie_jacquard", + "henry_james", + "helen_keller", + "paul_dukas", + "leonard_bloomfield", + "jean_piaget", + "franz_kline", + "henri_rousseau", + "\u0131_clovis", + "frank_stella", + "sa\u011fangiller", + "h_g_wells", + "walt_whitman", + "william_wyler", + "john_osborne", + "colin_powell", + "ludwig_boltzmann", + "carl_nielsen", + "leopold_kronecker", + "richard_wright", + "adolf_hitler", + "maria_mitchell", + "fritz_haber", + "peter_behrens", + "alfred_stieglitz", + "joseph_haydn", + "garfield", + "george_boole", + "buffalo_bill", + "edvard_grieg", + "robert_boyle", + "ralph_richardson", + "1", + "j_willard_gibbs", + "cordell_hull", + "rosa_parks", + "samuel_goldwyn", + "vladimir_putin", + "giuseppe_mazzini", + "\u0131_darius", + "jim_thorpe", + "arnold_sch\u00f6nberg", + "laurence_sterne", + "ben_hecht", + "anne_hathaway", + "david_garrick", + "bill_russell", + "jeannette_rankin", + "clarence_darrow", + "charles_lamb", + "g", + "arthur_schopenhauer", + "thomas_dekker", + "james_cagney", + "martin_heidegger", + "r", + "george_lucas", + "andrew_jackson", + "edith_wharton", + "louis_armstrong", + "steven_spielberg", + "robert_fulton", + "thomas_hardy", + "thomas_gainsborough", + "giuseppe_garibaldi", + "philip_warren_anderson", + "alexandre_dumas", + "robert_brown", + "thomas_carlyle", + "mecdelli_meryem", + "allen_tate", + "donald_barthelme", + "tamara_karsavina", + "bobby_fischer", + "johannes_gutenberg", + "d", + "gaetano_donizetti", + "william_faulkner", + "allen_\u0131verson", + "andre", + "titus_flavius_vespasianus", + "amerigo_vespucci", + "pierre_boulez", + "hans_adolf_krebs", + "girolamo_savonarola", + "emma_goldman", + "anna_kournikova", + "francis_poulenc", + "james_mill", + "putin", + "joseph_campbell", + "jean_de_la_fontaine", + "robert_hooke", + "o_henry", + "karl_popper", + "george_sand", + "peter_sellers", + "homo_rhodesiensis", + "charles_fourier", + "henry_clay", + "marcus_aurelius", + "peter_o'toole", + "joseph_conrad", + "william_shockley", + "peter_paul_rubens", + "jim_morrison", + "jules_verne", + "paul_newman", + "robert_morris", + "josef_albers", + "jackson_pollock", + "john_lennon", + "andrea_palladio", + "bob_woodward", + "charlie_chaplin", + "d_h_lawrence", + "lea", + "john_brown", + "elizabeth_gaskell", + "hugo_junkers", + "piscis_austrinus", + "brescia", + "hannah_arendt", + "antonio_stradivari", + "alice_walker", + "miles_davis", + "jesse_jackson", + "bozen", + "stanley_kubrick", + "\u0131_justinianos", + "john_huston", + "william_gilbert", + "james_watt", + "zambak", + "ronald_reagan", + "helmut_schmidt", + "homo", + "frederick_douglass", + "david_hilbert", + "wilhelm_reich", + "roman_jakobson", + "oliver_cromwell", + "martin_luther_king", + "v_henry", + "frank_capra", + "william_wordsworth", + "rex_harrison", + "william_clark", + "woodrow_wilson", + "margaret_sanger", + "georges_balanchine", + "marcus_antonius", + "lake_powell", + "\u0131_konstantin", + "agrippina", + "st_louis", + "richard_rodgers", + "anne_sexton", + "musalar", + "john_dryden", + "jim_henson", + "frank", + "b\u00e9la_lugosi", + "ernest_hemingway", + "george_westinghouse", + "kara_borsac\u0131", + "aquila", + "jacques_charles", + "arthur_miller", + "john_cheever", + "nelson_mandela", + "heinrich_himmler", + "al_gore", + "hans_bethe", + "hans_geiger", + "masun", + "cesare_borgia", + "roald_amundsen", + "sherwood_anderson", + "alfred_korzybski", + "c_a", + "charles_dickens", + "ella_fitzgerald", + "george_enescu", + "jacques_offenbach", + "\u0131_a_richards", + "pavlus", + "george_stevens", + "federico_fellini", + "the_one", + "willy_brandt", + "charles_wilkes", + "francisco_pizarro", + "francisco_franco", + "bernardo_bertolucci", + "jan_steen", + "\u0131_edmund", + "e_e_cummings", + "john_ross", + "ali_baba", + "andrew_carnegie", + "pontius_pilatus", + "franz_schubert", + "johnny_cash", + "alfred_kastler", + "mick_jagger", + "\u0131_theodosius", + "otto_loewi", + "georges_cuvier", + "william_harvey", + "walter_scott", + "peter_medawar", + "vladimir_lenin", + "saint_lawrence_nehri", + "\u00e7it_ku\u015fugiller", + "ralph_ellison", + "jonathan_swift", + "walter_gropius", + "albert_einstein", + "thomas_edison", + "raymond_chandler", + "henry_purcell", + "t", + "wilhelm_ostwald" + ], + "PLANT": [ + "gazelboynuzu", + "bergamot", + "semizotu", + "g\u00fcnd\u00f6nd\u00fc", + "k\u0131z\u0131la\u011fa\u00e7", + "pine", + "lycium_barbarum", + "akdeniz_servisi", + "melissa", + "kara\u00e7am", + "dulavratot", + "the_joshua_tree", + "at_kestanesi", + "karaa\u011fa\u00e7", + "menek\u015fe", + "hazambel", + "kiraz", + "marul", + "somon\u00e7ile\u011fi", + "amanita", + "arabidopsis_thaliana", + "sekoya", + "artist", + "cam_g\u00fczeli", + "karnabahar", + "amelanchier_alnifolia", + "passiflora_ligularis", + "g\u00fcnebakan", + "kestane", + "hint_keneviri", + "saat_d\u00f6rt", + "candida_albicans", + "turuncan", + "anadolu_kestanesi", + "dar_yaprakl\u0131_sinirli_ot", + "passiflora_incarnata", + "kraltac\u0131", + "cortinarius_violaceus", + "melezi", + "macadamia_tetraphylla", + "acemotu", + "menengi\u00e7", + "akasma", + "hazanbel", + "manolya", + "kurtba\u011fr\u0131", + "lepista_nuda", + "unutmabeni", + "phytophthora_infestans", + "lahana", + "karabiber", + "albal\u0131", + "solanum", + "sultank\u00fcpesi", + "rubus_spectabilis", + "gilaburu", + "su_atkuyru\u011fu", + "saccharomyces_cerevisiae", + "\u00e7oban\u00e7antas\u0131", + "tabasco_biberi", + "\u00e7oban\u00fcz\u00fcm\u00fc", + "\u00e7obang\u00fcl\u00fc", + "g\u00fclibri\u015fim", + "deliboynuz", + "hasekik\u00fcpesi", + "sar\u0131\u00e7am", + "bald\u0131ran", + "gazelotu", + "karayemi\u015f", + "yuka", + "s\u00f6\u011f\u00fct", + "edelweiss", + "kar_\u00e7i\u00e7e\u011fi", + "g\u00fcvem", + "\u00e7\u00f6rek_mantar\u0131", + "paris_quadrifolia", + "belladonna", + "manyok", + "arctostaphylos_uva_ursi", + "kurtluca", + "vallisneria", + "dulavratotu", + "erguvan", + "rubus_odoratus", + "sanat\u00e7\u0131", + "hevea_brasiliensis", + "hardal", + "turun\u00e7", + "pancar" + ], + "RACE": [ + "t\u00fcrkler", + "hollandal\u0131lar", + "kafkas", + "frans\u0131zlar", + "siyahiler", + "latin", + "adal\u0131", + "japonlar", + "frans\u0131z", + "galliler", + "ingilizler", + "amerikal\u0131lar", + "avrupal\u0131" + ], + "LOCATION": [ + "al_jazeera", + "sina_da\u011f\u0131", + "erkecel", + "bir_\u015fey_de\u011fil", + "samanyolu", + "park", + "abd", + "frans\u0131z_rivieras\u0131", + "kap_verde", + "bow_wow", + "delihane", + "piet_mondrian", + "sint_maarten", + "ben_te\u015fekk\u00fcr_ederim", + "n_olmu\u015f", + "man_o_war", + "felemenk", + "saat_biri_\u00e7eyrek_ge\u00e7iyor", + "oram", + "paskalya_adas\u0131", + "karadeniz", + "tatl\u0131_su", + "como_g\u00f6l\u00fc", + "kristof_kolomb", + "idare_i_\u00f6rf\u00ee", + "\u00fc\u00e7\u00fcnc\u00fc_ki\u015fi", + "vaccinium_oxycoccos", + "in\u015faat_m\u00fchendisli\u011fi", + "superior_g\u00f6l\u00fc", + "ali_veli", + "sar\u0131deniz", + "saint_lucia", + "hava_kuvetleri", + "hat_yai", + "arena", + "saksonya_anhalt", + "s\u0131rbistan_ulusal_meclisi", + "sri_lanka", + "erkecey", + "uyuyan_g\u00fczel", + "ernek", + "merkez_bankas\u0131", + "ha_long_koyu", + "\u00f6rf\u00ee_idare", + "ne_olmu\u015f", + "the_rolling_stones", + "cordon_bleu", + "zeytinda\u011f\u0131", + "ana_sokak", + "ye\u015fil_burun_adalar\u0131", + "fransa_ulusal_meclisi", + "kryvyi_rih", + "botanik_bah\u00e7esi", + "konservatuvar", + "birle\u015fik_devletler", + "heitor_villa_lobos", + "louis_joseph_gay_lussac", + "erkenek", + "noel_baba", + "yeni_d\u00fcnya", + "pandispanya" + ], + "JOB": [ + "lalalar", + "astsubay", + "guru", + "\u00e7oban", + "haberci", + "saniye", + "damgac\u0131", + "sayfa", + "ressam", + "bakan", + "karava\u015f", + "kad\u0131", + "itfaiyeci", + "make", + "sava\u015f\u00e7\u0131", + "the_\u0131ndependent", + "zabit", + "kral", + "luthier", + "serdar", + "sexton", + "don", + "sagan", + "bakkal", + "besteci", + "makinist", + "the_police", + "krupiye", + "yatak\u00e7\u0131", + "grip", + "para", + "kopya", + "lostromo", + "piyon", + "gardiyanl\u0131k", + "subay", + "yolda\u015f", + "sahife", + "koramiral", + "hakim", + "y\u00f6netici", + "albay", + "stenograf", + "savc\u0131", + "koruyan", + "aste\u011fmen", + "piskopos", + "radyolog", + "kitap\u00e7\u0131", + "sabanc\u0131", + "ziraat\u00e7\u0131", + "printer", + "yazar", + "b\u00fcy\u00fckel\u00e7i", + "freelance", + "kamikaze", + "bayraktar", + "haham", + "the_advocate", + "menajer", + "tanner", + "hekim", + "sculptor", + "hukuk\u015finas", + "n\u00f6rolog", + "terapist", + "idareci", + "the_guardian", + "denizci", + "zango\u00e7", + "mandarin", + "giri\u015fimci", + "seylani", + "hostes", + "mason", + "mate", + "u\u00e7arman", + "bankac\u0131", + "iktisat\u00e7\u0131", + "dizaync\u0131", + "simsar", + "kalayc\u0131", + "marangoz", + "tacir", + "mellah", + "gaucho", + "striptizci", + "blokfl\u00fct", + "hakem", + "the_economist", + "de\u011firmenci", + "broker", + "wetter", + "biyokimyac\u0131", + "m\u00fczisyen", + "cop", + "m\u00fcte\u015febbis", + "yarbay", + "metres", + "asistan", + "korucu", + "oramiral", + "haritac\u0131", + "kaz\u0131bilimci", + "mezarc\u0131", + "k\u00fct\u00fcphaneci", + "gardiyan", + "kalyoncu", + "geli\u015ftirici", + "kalfa", + "usher", + "messenger", + "baytar", + "mucit", + "korgeneral", + "sabunlamak", + "kartograf", + "nedime", + "takip\u00e7i", + "cerrah", + "zanaatkar", + "tasar\u0131mc\u0131", + "s\u0131vazlamak", + "kurye", + "kaleci", + "the_floorwalker", + "ayak\u00e7\u0131", + "ormanc\u0131", + "esquire", + "tellal", + "bahriyeli", + "suret", + "g\u00f6revli", + "banker" + ], + "LANGUAGE": [ + "madagaskarl\u0131", + "ruandaca", + "ermeni", + "k\u00fcrt\u00e7e", + "katalonyal\u0131", + "tagalogca", + "arnavut", + "frans\u0131zca", + "kongo", + "hint\u00e7e", + "samoal\u0131", + "kriler", + "fars\u00e7a", + "tacikistanl\u0131", + "pali", + "altayca", + "ibrani", + "danca", + "t\u00fcrkmen", + "hindi", + "tacik", + "litvan", + "zent\u00e7e", + "esperanto", + "arap\u00e7a", + "katalan", + "savahili", + "kazakistanl\u0131", + "ido", + "yunanistanl\u0131", + "yunanl\u0131", + "tonga", + "kannada" + ], + "FOOD": [ + "barbunya", + "mousse", + "meyve_salatas\u0131", + "roma_dondurmas\u0131", + "s\u00fctl\u00fc_kahve", + "t_kemikli_biftek", + "zeytinya\u011f\u0131", + "ciklet", + "gelato", + "dondurma" + ], + "PRODUCT": [ + "sanal_makine", + "justin_bieber", + "dijitalle\u015ftirme", + "enstr\u00fcman", + "\u00fc\u00e7_imparatorluk", + "al_jazeera", + "sezaryen", + "de\u011fi\u015fme", + "solaryum", + "son_anda", + "dans_pisti", + "yeti\u015fmek", + "julius_caesar", + "the_star_spangled_banner", + "\u00fc\u00e7_boyutlu", + "the_end_of_the_world", + "the_kid_brother", + "st_helens_yanarda\u011f\u0131", + "d\u00f6rt_mevsim", + "g\u00fcnayd\u0131n", + "kobay", + "horn_burnu", + "onikinci_gece", + "deutsche_welle", + "bir_bebek_evi", + "gong", + "mario_andretti", + 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"don_juan", + "sendika", + "kudurmak", + "han_hanedan\u0131", + "ai", + "the_football_league", + "chiang_mai", + "soya\u011fac\u0131", + "birle\u015fmi\u015f_milletler", + "akademi", + "dia", + "macaristan_ulusal_meclisi", + "ay\u00e7a", + "y\u0131lba\u015f\u0131_gecesi", + "la_bemol_maj\u00f6r", + "bir_kez_daha", + "erkenek", + "ernek", + "ak\u0131l_hastanesi", + "ekincilik", + "the_breakfast_club", + "rabindranath_tagore", + "taoizm", + "gestapo", + "\u00f6z_\u00e7\u0131kar", + "b\u00e2b_\u0131_\u00e2li", + "din_bilimleri", + "h\u0131ristiyan_bilim", + "winnie_the_pooh", + "postane", + "ulusal_meclis", + "roma_hukuku", + "kapamak", + "the_young_turks", + "cizvitler", + "mektep", + "al_jazeera", + "askeriye", + "i\u015f\u00e7i_s\u0131n\u0131f\u0131", + "ciklet", + "s\u00e3o_paulo", + "po", + "addis_ababa", + "\u00e7ok_ya\u015fa", + "mossad", + "japon_sosyal_demokrat_parti", + "kanka", + "bizim_ev", + "yeniay", + "kulumak", + "kara_piyasa", + "kamu_y\u00f6netimi", + "ursa_major", + "erkecey", + "konservatuvar", + "g\u00fcmr\u00fck", + "saint_barth\u00e9lemy", + "sturmabteilung", + "insan_kaynaklar\u0131", + "k\u0131z\u0131ldeniz", + "\u00fc\u00e7\u00fcnc\u00fc_\u015fah\u0131s", + "los_angeles", + "nato", + "baltimore_orioles", + "hava_kuvvetleri", + "kalo\u015fvar", + "ad_hoc", + "roma_katolik_kilisesi", + "sar\u0131_\u0131rmak", + "mi", + "andromeda_galaksisi", + "zeytinda\u011f\u0131", + "alman_imparatorlu\u011fu", + "avustralya_i\u015f\u00e7i_partisi", + "in_situ", + "sa", + "azerbaycan_mill\u00ee_meclisi", + "katolik_kilisesi", + "g\u00fcndeg\u00fcn", + "dominyon", + "az_az", + "sosyal_demokrat_parti", + "yak\u0131p_y\u0131kma_takti\u011fi", + "bir_daha", + "streptococcus_pyogenes", + "ruh_ve_sinir_hastal\u0131klar\u0131_hastanesi", + "irkenek", + "i\u015f\u00e7i_partisi", + "fb\u0131", + "saint_kitts_ve_nevis_millet_meclisi", + "akt\u00fcel", + "s\u00e3o_tom\u00e9", + "sosyoekonomik", + "irkeyel" + ], + "DISEASE": [ + "anestezi", + "miyopi", + "araknofobi", + "blastom", + "prostat_kanseri", + "ki", + "jinekomasti", + "polidaktili", + "ele_ge\u00e7irme", + "bruselloz", + "progeria", + "listeriosis", + "miyoklonus", + "gebelik", + "basur", + "travma", + "vajinit", + "polimiyozit", + "pepelemek", + "beriberi", + "friedreich_ataksisi", + "the_bends", + "denksizlik", + "hastal\u0131k", + "phytophthora_infestans", + "bir_hiz\u00e2da", + "parestezi", + "tahrik", + "kretinizm", + "rust", + "sakatl\u0131k", + "romatizma", + "poliovir\u00fcs", + "sivilce", + "farenjit", + "su_\u00e7i\u00e7e\u011fi", + "para", + "papa\u011fan_hastal\u0131\u011f\u0131", + "vitaminsizlik", + "presbiyopi", + "deliriyum", + "hamartom", + "frengi", + "zenofobi", + "apandisit", + "wale", + "salmonelloz", + "kangren", + "pellegra", + "yanmak", + "demans", + "poliomyelit", + "diki\u015f", + "likenler", + "g\u00fcne\u015f_\u00e7arpmas\u0131", + "zehirli_sarma\u015f\u0131k", + "cerahatlenmek", + "malta_hummas\u0131", + "menenjit", + "u\u00e7uk", + "mastit", + "dikme", + "spina_bifida", + "su_saka\u011f\u0131s\u0131", + "meme_kanseri", + "radyasyon", + "alexia", + "salg\u0131n", + "kabakulak", + "vurgun", + "kloroz", + "smart", + "glokom", + "pica", + "tazelik", + "sarho\u015fluk", + "\u00f6zba\u011f\u0131\u015f\u0131kl\u0131k", + "sertle\u015fme", + "saka\u011f\u0131", + "kolit", + "hamilelik", + "tanatofobi", + "sitomegalovir\u00fcs", + "susuzluk", + "kanl\u0131l\u0131k", + "sendrom", + "teratom", + "purpura", + "karsinom", + "siroz", + "boyunburan", + "down_sendromu", + "belal\u0131lar", + "engellilik", + "an_qi", + "silikozis", + "stigmata", + "t\u00fct\u00fcn_mozaik_vir\u00fcs\u00fc", + "havale", + "materyalizm", + "yorguntu", + "arpac\u0131k", + "k\u0131z\u0131\u015fma", + "mi", + "aura", + "topak", + "tan", + "sting", + "kestane", + "uyar\u0131m", + "sayr\u0131l\u0131k", + "break", + "kuduz", + "kernikterus", + "kuru", + "burn", + "diyabet", + "hem_y\u00fcz", + "belso\u011fuklu\u011fu", + "preeklampsi", + "kanama", + "klostrofobi", + "kanser", + "ziyan", + "do\u011furganl\u0131k", + "le", + "kolaps", + "kesik", + "salmonella", + "krup", + "ok\u015famak", + "ishal", + "\u0131s\u0131rmak", + "irkilme", + "iskorb\u00fct" + ], + "GPE": [ + "tai_da\u011f\u0131", + "\u0111ur\u0111evdan", + "kotte", + "sint_maarten", + "g\u00fcney_b\u00f6lgesi", + "aya_sofya", + "k\u0131z\u0131l_ha\u00e7", + "s\u00e3o_tom\u00e9", + "gran_canaria", + "beyaz_saray", + "yorgi", + "ayasofya", + "kuzey_b\u00f6lgesi", + "yeni_ahit", + "la_gomera", + "insan_haklar\u0131", + "st_louis", + "k\u0131z\u0131ldeniz" + ], + "RELIGION_MEMBER": [ + "anabaptist", + "guru", + "parsiler", + "fransiskanlar", + "hristiyan", + "s\u00fcnni", + "birader", + "mormon", + "tanr\u0131tan\u0131maz", + "p\u00fcritan", + "satanist", + "havaryun", + "sufi", + "budist" + ], + "QUANTITY": [ + "en_b\u00fcy\u00fck_ortak_b\u00f6len", + "y\u00fcz_bin", + "durguluk", + "metrek\u00fcp", + "\u00fc\u00e7_k\u0131zkarde\u015f", + "otuz_y\u0131l_sava\u015f\u0131", + "santimetrek\u00fcp", + "\u00fc\u00e7_imparatorluk", + "dinar", + "ton", + "frans\u0131z_frang\u0131", + "yetmi\u015f_sekiz", + "be\u015f_y\u00fcz", + "g", + "on_bin", + "\u00fc\u00e7_kabaday\u0131", + "on_milyon", + "parkmetre", + "metrekare", + "mauritius_rupisi", + "\u00fc\u00e7_boyutlu", + "karek\u00f6k", + "sterlin", + "anders_celsius" + ], + "RELIGION": [ + "presbiteryenlik", + "zen", + "katharizm", + "\u015finto", + "islam", + "selefilik", + "triniteryanizm", + "tasavvuf", + "mitraizm" + ], + "DATE": [ + "dikeyh\u0131z", + "y\u00fcr\u00fct\u00fcm_s\u00fcresi", + "alt\u0131n\u00e7a\u011f", + "dolunay", + "yeniay", + "milat", + "salise", + "yar\u0131lanma_s\u00fcresi", + "yeni_ay", + "y\u00fcr\u00fctme_s\u00fcresi", + "meryem_in_g\u00f6\u011fe_kabul\u00fc" + ], + "ANIMAL": [ + "dere_alabal\u0131\u011f\u0131", + "iskete", + "ebola_vir\u00fcs\u00fc_hastal\u0131\u011f\u0131", + "tarakdi\u015f", + "musur", + "su_kurba\u011fas\u0131giller", + "karatavukgiller", + "mercan", + "alt\u0131ng\u00f6z", + "argonot", + "kobay", + "de\u011fin", + "billy_elliot", + "kunduz", + "ala_s\u0131\u011f\u0131rc\u0131k", + "denizkestanesi", + "epstein_barr_vir\u00fcs", + "canis_minor", + "alageyik", + "ay_ay", + "g\u00f6kkuzgun", + "kocag\u00f6zgiller", + "carduelis", + "pisces", + "iki_parmakl\u0131_tembel_hayvanlar", + "sar\u0131asmagiller", + "\u00e7ekelez", + "varisella_zoster_vir\u00fcs", + "kar_pars\u0131", + "bozay\u0131", + "kar_kiraz_ku\u015fu", + "kar_kaz\u0131", + "vibe", + "ketta", + "sar\u0131ca", + "sincap", + "zendost", + "karadul", + "su_k\u0131lavuzu", + "su_k\u00f6pe\u011fi", + "notilus", + "denizh\u0131yar\u0131", + "do\u011fan", + "bahri", + "pili\u00e7", + "the_crow", + "dall_yaban_koyunu", + "susamuru", + "dere_kaya_bal\u0131\u011f\u0131", + "kambur_balina", + "su_samuru", + "karatavuk", + "av_k\u00f6pe\u011fi", + "porsuk", + "kad\u0131nc\u0131l", + "zampara", + "feret", + "\u015fahin", + "makasl\u0131b\u00f6cek", + "donald_duck", + "\u00fc\u00e7_parmakl\u0131_tembel_hayvanlar", + "g\u00fcney_domuz_kuyruklu_\u015febe\u011fi", + "mart\u0131", + "sinekkapangiller", + "musurgiller", + "yeleli_denizaslan\u0131", + "karaca", + "yediuyuklayangiller", + "baya\u011f\u0131_yediuyur", + "sable", + "akbaba", + "su_\u00e7ullu\u011fu", + "su_mokaseni", + "bayku\u015f", + "bat\u0131_nil_vir\u00fcs\u00fc", + "firavunfaresi", + "sansar", + "dubar", + "atmaca", + "atmacalar", + "lemming", + "and_kondoru", + "kaya_g\u00fcvercini", + "f\u0131nd\u0131k_faresi", + "k\u0131z\u0131lgerdan", + "kolyoz" + ], + "FAC": [ + "postane", + "otuz_\u00fc\u00e7", + "arnold_sch\u00f6nberg", + "saint_lucia", + "t_h\u00fccresi", + "azar_azar", + "son_ak\u015fam_yeme\u011fi", + "titus_livius", + "az_az", + "\u0131_petro" + ], + "SOC_ECO_CLASS": [ + "kara_pazar", + "samuray", + "alts\u0131n\u0131f", + "biraderlik", + "kad\u0131nl\u0131k", + "karde\u015flik", + "yeralt\u0131_ekonomisi", + "kara_borsa", + "tar\u0131m", + "ekincilik" + ], + "PERSON": [ + "julius_caesar", + "al_gore", + "t_kemikli_biftek", + "tai_da\u011f\u0131", + "c_vitamini", + "h_g_wells", + "don_delillo", + "e_e_cummings", + "d\u00fclger_bal\u0131\u011f\u0131", + "ben_de", + "otuz_iki", + "carl_david_anderson", + "gaius_julius_caesar", + "yo_yo", + "rudolf_hess", + "arac\u0131l\u0131\u011f\u0131yla" + ], + "PERSON_PRONOUN": [ + "i", + "he", + "mine", + "bizim", + "his", + "m\u0131", + "her", + "\u00f6z_ba\u015f\u0131na", + "me", + "kendim", + "our_nehri", + "us" + ], + "POLITICAL_PARTY": [ + "muhalefet", + "demokrat_parti", + "kuomintang", + "sosyalist_parti", + "demokratik_parti", + "cumhuriyet\u00e7i_parti", + "whig_partisi", + "nasyonal_sosyalist_alman_i\u015f\u00e7i_partisi", + "halk_partisi", + "muhafazak\u00e2r_parti", + "kom\u00fcnist_parti" + ], + "BIO_CHEM_ENTITY": [ + "d_vitamini" + ], + "TITLE": [ + "beyefendi" + ], + "LAW": [ + "din_\u00f6zg\u00fcrl\u00fc\u011f\u00fc", + "kamu_hukuku" + ], + "GENDER": [ + "men", + "boy", + "leydi", + "transgender", + "erkek" + ], + "ANAT": [ + "iki_ba\u015fl\u0131_uyluk_kas\u0131" + ], + "UNION": [ + "uluslararas\u0131_telekom\u00fcnikasyon_birli\u011fi", + "sendika" + ], + "MEDICAL_THERAPY": [ + "kan_bas\u0131nc\u0131" + ], + "EVENT": [ + "grand_prix", + "olur_b\u00f6yle_\u015feyler", + "en_iyi_film_akademi_\u00f6d\u00fcl\u00fc" + ], + "ner_regexes": [ + [ + "PERSON", + "\\D+ \\D+|\\D+ \\D+ \\D+|\\D+ \\D+|\\D+ \\D+ \\D+ \\D+|\\D+ \\D+|\\D+ \\D+ \\D+|\\D+ \\D+|\\D+ \\D+ \\D+ \\D+|\\D+ \\D+|\\D+ \\D+ \\D+|\\D+ \\D+|\\D+ \\D+ \\D+ \\D+|\\D+ \\D+ \\D+|\\D+ \\D+ \\D+ \\D+|\\D+ \\D+ \\D+ \\D+ \\D+|\\D+ \\D+ \\D+ \\D+", + false, + [] + ] + ], + "FIRST_NAME_FEMALE": [ + "ruhide", + "rezin", + "\u015f\u00fck\u00fcfe", + "mahnaz", + "a\u015fhan", + "fatig\u00fcl", + "\u015fad\u0131man", + "elvan", + "\u015fazime", + "yosma", + "m\u00fc\u011fber", + "fad\u0131la", + "t\u00fclin", + "umu\u015fan", + "koncag\u00fcl", + "bu\u015fra", + "muhiye", + "evrim", + "fatinur", + "elamiye", + "feyzin", + "afife", + "d\u00f6ner", + "sevim", + "g\u00fclseren", + "ufukay", + "cuheyna", + "g\u00fclfeza", + "yepelek", + "g\u00f6kperi", + "\u00fcmray", + "mehdiye", + "s\u00fczer", + "dil\u015fat", + "sirap", + "peren", + "h\u00fcrmet", + "selmin", + "badeg\u00fcl", + "ar\u0131p\u0131nar", + "ezgin", + "nurmelek", + "\u00e7ilga", + "\u00f6zpetek", + "elifnur", + "h\u00fcda", + "beyhatun", + "semat", + "canur", + "m\u00fcbetcel", + "aylil", + "g\u00f6k\u00e7e", + "deha", + "sehel", + "henife", + "d\u00fcrr\u00fc\u015fehvar", + "semine", + "menfeat", + "sevsevil", + "tasvir", + "ball\u0131", + "\u00fcmm\u00fchan", + "sayg\u0131n", + "\u00f6zay", + "cemiyle", + "egenur", + "ye\u015fil", + "varl\u0131k", + "habibe", + "sefer", + "t\u00fczenur", + "i\u0307lper", + "ruhug\u00fcl", + "ir\u0131s", + "alsoy", + "g\u00fcver\u00e7in", + "zeyno", + "nebiha", + "almast", + "nurser", + "\u015firivan", + "nurgil", + "g\u00fclhisar", + "\u00e7isem", + "hanim", + "a\u00e7\u0131lay", + "nefaret", + "ho\u015fkadem", + "haliye", + "aynilhayat", + "\u015fehza", + "kader", + "begim", + "m\u00fcret", + "yazg\u00fcl", + "efil", + "\u00fcnal", + "hekime", + "yurtseven", + "ogu\u015f", + "adviye", + "maynur", + "g\u00fcler", + "yasemen", + "mehrig\u00fcl", + "dilcan", + "paksu", + "s\u00f6yler", + "g\u00fcls\u00fc", + "g\u00fcnebakan", + "i\u0307mge", + "anarg\u00fcl", + "hayr\u00fcnnisa", + "esna", + "binay", + "rahiye", + "subutiye", + "meryeme", + "i\u0307klim", + "kutun", + "g\u00fclder", + "refet", + "beste", + "z\u00fcmre", + "zevl\u00fcde", + "paye", + "z\u00fclbiye", + "bidayet", + "sahil", + "muarra", + "nurveren", + "kefser", + "f\u00fcgen", + "mel\u00fbl", + "hatin", + "belkize", + "tanyu", + "\u015fel\u00e2le", + "laze", + "firdevis", + "havali", + "bit\u00fcl", + "hasg\u00fcl", + "ferahdiba", + "rojnu", + "i\u0307nsaf", + "i\u0307rfan", + "mesude", + "miyesser", + "mevl\u00fcdiye", + "hamiyet", + "u\u011fur", + "nurbanu", + "safura", + "servinaz", + "m\u00fcveddet", + "masume", + "sanavber", + "akise", + "sadeti", + "nazimet", + "g\u00fclnaziye", + "atanur", + "\u00e7evreg\u00fcl", + "s\u00fcner", + "neslinur", + "ay\u015fenur", + "zaliha", + "aksoy", + "h\u00fcr\u00fcyet", + "azade", + "g\u00fclinaz", + "g\u00fcng\u00f6ren", + "or\u00e7in", + "selvi", + "g\u00fclmisal", + "ayten", + "i\u0307lklima", + "behiza", + "necva", + "perinur", + "b\u00fc\u015franur", + "rakide", + "vezrife", + "kandef", + "adila", + "tanses", + "enfes", + "s\u00fcsen", + "\u015fennur", + "erg\u00fcl", + "a\u011fbegim", + "sejda", + "faize", + "nurseda", + "seniha", + "nazende", + "sevican", + "\u015fahnuray", + "mihrab", + "rehime", + "sel\u00e7uk", + "kifaye", + "elgin", + "i\u0307mrihan", + "\u00fcnsever", + "\u015filan", + "aykut", + "zahfer", + "ay\u015feana", + "ni\u011fmet", + "hadrey", + "m\u00fckr\u00fcme", + "g\u00fcl\u00e7e", + "selime", + "birben", + "g\u00fclgen", + "macide", + "aky\u0131ld\u0131z", + "olu\u015f", + "dilfeza", + "hilayda", + "atiyye", + "\u00f6zge", + "miray", + "g\u00fcld\u00fcnya", + "\u00f6ncel", + "\u00f6zde\u015f", + "\u00fc\u00e7g\u00fcl", + "benek", + "nurhayet", + "i\u0307\u00e7imbike", + "deniz", + "merva", + "basriye", + "hacile", + "deryanur", + "bediriye", + "berrin", + "serfinaz", + "selcen", + "seyhan", + "nur\u015fan", + "birg\u00fcl", + "mujde", + "nuriyet", + "i\u0307ncifir", + "sevgen", + "kerime", + "safinaz", + "nevise", + "simten", + "m\u00fc\u015f\u00fcre", + "rumeysa", + "sezen", + "neriban", + "melikkan", + "\u00f6zyurt", + "feden", + "sab\u0131r", + "g\u00fcnver", + "mecide", + "siti", + "leyli", + "cedide", + "fatmanur", + "erbay", + "kad\u0131nana", + "pembesin", + "revza", + "tayyibe", + "necilal", + "nihan", + "asu", + "sa\u00e7\u0131", + "eseng\u00fcn", + "emi\u015f", + "arziye", + "m\u00fccevher", + "piran", + "n\u00fcdret", + "g\u00fcnsel", + "g\u00fcrten", + "y\u00fccel", + "talibe", + "bilay", + "mefharet", + "hur\u015fide", + "mahter", + "nejdet", + "zubeyde", + "ganiye", + "merim", + "hazine", + "i\u0307lde\u015f", + "g\u00fclper", + "nazi", + "ban\u00fc", + "hinet", + "z\u00fclf\u00fcye", + "sat\u0131a", + "m\u00fcjde", + "g\u00fcl", + "s\u00fcmerya", + "sultane", + "reng\u00fcl", + "maks\u00fcde", + "rebihat", + "g\u00fclg\u00fczel", + "azize", + "ticen", + "neval", + "laika", + "nesfe", + "bergen", + "g\u00fclay", + "saire", + "ceyhun", + "g\u00fclfari", + "b\u00fcreyre", + "i\u015f\u0131n", + "ayyaruk", + "soykan", + "ne\u015frin", + "nili", + "rabbiye", + "nurey", + "turcein", + "fayize", + "k\u00e2zime", + "\u00e2lem\u015fah", + "belgizar", + "hansultan", + "h\u00fcsn\u00fch\u00e2l", + "l\u00e2le", + "teybet", + "risalet", + "melaha", + "i\u0307slime", + "z\u00fcheyla", + "g\u00fclev", + "cannur", + "aysevim", + "nurda", + "\u015ferman", + "samahat", + "serda", + "kaver", + "\u015feref", + "\u015fayan", + "kumral", + "ayt\u00f6z", + "t\u00fcrcan", + "rana", + "do\u011fannur", + "acarkan", + "s\u00fcheyda", + "fehmiye", + "zemzem", + "gilman", + "g\u00fclselin", + "g\u00fclbeyan", + "kezban", + "durgadin", + "i\u0307zel", + "burcuhan", + "nurdeniz", + "cevale", + "g\u00fclzadiye", + "tutkucan", + "s\u00fcleyla", + "aybet", + "meleknur", + "uyanser", + "esmanperi", + "\u00e7al\u0131m", + "fidaye", + "susam", + "alize", + "g\u00fclsal\u0131n", + "nal\u00e2n", + "e\u015fim", + "zehranur", + "r\u0131fk\u0131ye", + "g\u00fcldam", + "salimet", + "eri\u015f", + "akmaral", + "g\u00fczey", + "sabihe", + "zelha", + "naide", + "tan", + "sevcan", + "ahter", + "tercan", + "g\u00fclceg\u00fcn", + "nept\u00fcn", + "akg\u00fcne\u015f", + "g\u00fcnar", + "aysuna", + "\u00f6mriye", + "ta\u00e7nur", + "asiman", + "duha", + "limon", + "birsan", + "adal", + "ild\u0131z", + "alabezek", + "ya\u015far", + "dilhu\u015f", + "g\u00fcrc\u00fcye", + "tu\u011f\u00e7e", + "g\u00f6k", + "nurta\u00e7", + "akay", + "ba\u011fdat", + "gabel", + "divan", + "hayel", + "rafia", + "\u00fclke", + "fermuta", + "ayn\u0131mah", + "temime", + "vefia", + "nursim", + "\u00e7a\u011flar", + "alg\u0131\u015f", + "\u00f6zlem", + "tule", + "ayduru", + "kutg\u00fcn", + "meyhanim", + "ervaniye", + "canseven", + "havse", + "permun", + "hanbiken", + "natalia", + "g\u00fclenay", + "r\u00fcmeysa", + "g\u00fcll\u00fchan", + "pesent", + "\u015feyda", + "alt\u0131nbike", + "g\u00fclsevil", + "anka", + "beray", + "halenur", + "mukbile", + "m\u00fcsemma", + "m\u00fcferrih", + "silanur", + "simber", + "sanur", + "evde", + "sebl\u00e2", + "merba", + "nasiba", + "zebirce", + "mahig\u00fcl", + "g\u00f6li", + "\u015fahdiye", + "harbinaz", + "nezeng\u00fcl", + "\u015fah\u0131g\u00fcl", + "yah\u015fi", + "y\u0131ld\u0131z", + "emal", + "rayla", + "k\u0131smet", + "seyyide", + "pekkan", + "balca", + "de\u011fer", + "i\u0307de", + "sevdinar", + "vacibe", + "\u00fcge", + "\u015fefiye", + "aydar", + "al\u0131\u015f\u0131k", + "canfeza", + "eceg\u00fcl", + "\u00fcrper", + "ay\u00e7an", + "g\u00fclkad\u0131n", + "\u00e7olpan", + "mihriye", + "lezize", + "g\u00f6rsev", + "sevginur", + "\u015fehreban", + "sidar", + "g\u00fcl\u00f6zge", + "armahan", + "g\u00fcl\u015feref", + "g\u00fcl\u00fcs", + "ummahani", + "sonnur", + "\u00f6rfiye", + "i\u0307sra", + "hezniye", + "nevsale", + "besey", + "abiye", + "sernur", + "feyha", + "minibe", + "haf\u0131za", + "nafile", + "emine", + "bilginur", + "nirg\u00fcl", + "serma", + "heva", + "i\u0307lkbahar", + "sevla", + "zerafet", + "tagang\u00fcl", + "kardelen", + "\u00fclk\u00fcm", + "feryas", + "fitnat", + "k\u00fcbran", + "s\u0131rriye", + "nefiye", + "nezize", + "\u015femsinisa", + "sunay", + "tomurcuk", + "ma\u015fide", + "t\u00fcrknur", + "bilkay", + "teknaz", + "yekbun", + "kitan", + "meni\u015fan", + "huban", + "beriye", + "nades", + "erem", + "geleng\u00fcl", + "nilcan", + "zilfa", + "yurdaser", + "verde", + "amre", + "fadile", + "tang\u00fcl", + "vildane", + "ay\u00fclker", + "aycag\u00fcl", + "solma", + "h\u00fcmeyra", + "avun\u00e7", + "nevgin", + "semrin", + "l\u00fcfen", + "\u015f\u00f6hret", + "alaz", + "sarya", + "se\u00e7g\u00fcl", + "musaffa", + "g\u00f6zem", + "neyran", + "p\u00fcr\u00e7ek", + "\u00fcmmahan", + "zinnure", + "g\u00fclbani", + "misra", + "g\u00fclter", + "asliye", + "bahtinur", + "canan", + "\u00f6zg\u00fcn", + "damlanur", + "hasret", + "mezide", + "jaruthip", + "feraye", + "ayhan", + "naz", + "nura", + "meveddet", + "muvahhide", + "dilsitan", + "aral", + "\u015famiha", + "dilara", + "sadiye", + "i\u0307hsan", + "fildan", + "ferhan", + "g\u00fclbiye", + "sebig\u00fcl", + "sedife", + "g\u00fcl\u015fa", + "z\u00f6hrehan", + "duyguhan", + "cihan", + "m\u00fcmtaze", + "n\u00fcrice", + "hurican", + "\u015fendo\u011fan", + "\u00f6v\u00fcn", + "yal\u0131n", + "ayasun", + "alt\u0131n\u00e7i\u00e7ek", + "g\u00fclsiye", + "m\u00fcnezzer", + "mufide", + "\u015fahinder", + "\u00f6zbilge", + "ayg\u00f6nen\u00e7", + "dursadiye", + "narhanim", + "bezek", + "ferinaz", + "goncafer", + "nazlihan", + "naz\u0131dil", + "vecide", + "benice", + "lerze", + "zeride", + "\u015fevketfeza", + "i\u015fin", + "aysema", + "edaviye" + ], + "FIRST_NAME_MALE": [ + "zennun", + "heyvetullah", + "\u00e7opur", + "kete", + "tu\u011frulhan", + "s\u0131yl\u0131han", + "\u00f6zerdin\u00e7", + "abd\u00fclhadi", + "filit", + "t\u00fcrabi", + "g\u00f6rg\u00fcnay", + "refik", + "nehip", + "hekmet", + "dirlik", + "ero\u011ful", + "hidir", + "pehlil", + "muhyettin", + "oganer", + "erenalp", + "s\u00f6zer", + "g\u00f6kbudun", + "onuker", + "sezal", + "nihai", + "barsen", + "maksur", + "\u015ferafeddin", + "abd\u00fclahat", + "dalk\u0131l\u0131\u00e7", + "i\u0307sak", + "ufukay", + "hariz", + "torhan", + "elhan", + "tungu\u00e7", + "galip", + "seyithan", + "feza", + "rasul", + "mecit", + "dalan", + "t\u00fcrkalp", + "derkay", + "kavurt", + "ar\u0131el", + "karakucak", + "\u015fekim", + "ezg\u00fctekin", + "haluk", + "buyrukhan", + "k\u00e2mil", + "yunt", + "ak\u0131nal", + "tongu\u00e7", + "i\u0307lbek", + "teber", + "o\u011fulba\u015f", + "bengibay", + "h\u00fcrya\u015far", + "sunel", + "g\u00f6k\u00e7il", + "din\u00e7kol", + "hunalp", + "sarpk\u0131n", + "velitdin", + "ba\u015fay", + "kel\u00e2mi", + "tayayd\u0131n", + "sarg\u0131n", + "i\u0307zg\u00fc", + "\u015fahat", + "fami", + "denkel", + "\u00e7a\u011fveren", + "mefarettin", + "sa\u011fcan", + "atat\u00f6re", + "nevsal", + "mishat", + "alparslan", + "r\u00fc\u015fen", + "aybora", + "i\u015f\u0131kay", + "h\u00fcrdo\u011fan", + "serol", + "pirahmet", + "us", + "savni", + "satrettin", + "sevindik", + "enginiz", + "to\u011fan", + "bedi", + "g\u00f6ksev", + "i\u0307lim", + "mahsun", + "\u00e7a\u011fa", + "u\u00e7beyi", + "duracan", + "alsoy", + "seracettin", + "ulakbey", + "zihni", + "demiriz", + "\u00f6ztek", + "vedat", + "bari\u015f", + "balta\u015f", + "u\u00e7an", + "borata\u015f", + "bozerk", + "soysel\u00e7uk", + "i\u0307lgi", + "burakhan", + "ert\u00fcn", + "\u00e7elem", + "korkmazalp", + "a\u011faki\u015fi", + "cebesoy", + "yolal", + "s\u00fcvari", + "mutluhan", + "hi\u00e7s\u00f6nmez", + "\u00e7er\u00e7i", + "k\u0131v\u0131lc\u0131m", + "kader", + "dorukhan", + "\u00f6rik", + "vaysal", + "k\u00f6ker", + "ak\u00e7abay", + "uzbay", + "mertel", + "aydin\u00e7", + "\u015favki", + "ahat", + "arpa\u011f", + "ertuncay", + "sami", + "nuyan", + "\u00fcbeydullah", + "yoru\u00e7", + "merdi", + "i\u0307\u015fcan", + "v\u00e2l\u00e2", + "oranl\u0131", + "okseven", + "buhari", + "tok\u00f6z", + "geray", + "odkanl\u0131", + "alaeddin", + "\u00f6zdil", + "bozba\u011f", + "\u00f6zdo\u011fdu", + "tatu", + "g\u00fcla\u011fa", + "adlan", + "efser", + "u\u011furkan", + "ak\u00e7asu", + "kotuz", + "aygutalp", + "sidki", + "\u00f6kt\u00fcrk", + "y\u00f6netmen", + "yeti\u015fal", + "atag\u00fcn", + "almus", + "abdulgazi", + "dirican", + "hakikat", + "zoral", + "emrullah", + "aksay", + "\u00e7okan", + "\u00f6z\u00fcdo\u011fru", + "omaca", + "a\u00e7\u0131kel", + "mestur", + "otay", + "evrimer", + "sar\u0131cabay", + "\u015fabettin", + "bozta\u015f", + "salk\u0131n", + "alpin", + "b\u00fcget", + "ecemi\u015f", + "d\u00fcndaralp", + "i\u0307mam", + "ko\u015fukhan", + "k\u00fcr\u015fad", + "kamar", + "aliabbas", + "g\u00fcnden", + "\u00fclfet", + "aslanhan", + "\u015femsettin", + "akalan", + "de\u011fmeer", + "beyda", + "cihandide", + "birsen", + "duruk", + "bat\u0131rhan", + "ozans\u00fc", + "zeynelabidin", + "\u00e7ak\u0131rca", + "bilta\u015f", + "tali", + "tolonbay", + "mirbadin", + "nas", + "ulu", + "yelesen", + "\u00fcrfettin", + "\u00e7evik\u00f6z", + "akatay", + "abdulmenaf", + "\u00fczer", + "karanbay", + "bekta\u015fi", + "bayruhan", + "nasuf", + "\u00fclk\u00fcde\u015f", + "seda", + "sulhi", + "i\u0307mren", + "erk\u0131l\u0131\u00e7", + "se\u00e7me", + "e\u015fref", + "oymak", + "\u00fcnlen", + "atilhan", + "toker", + "m\u00fcslum", + "g\u00f6nen", + "serezli", + "s\u00fcmeyye", + "n\u02dczamett\u02dcn", + "i\u0307ldem", + "safet", + "melihcan", + "tansev", + "selvi", + "ermutlu", + "\u00f6zkent", + "eraycan", + "haciali", + "beren", + "yigit", + "hayali", + "h\u00fck\u00fcmdar", + "muhip", + "g\u00fcm\u00fc\u015ftekin", + "ayd\u0131nbey", + "ulu\u011fbey", + "delil", + "\u00f6zinal", + "mihin", + "m\u00fcfit", + "birgit", + "cabir", + "berksay", + "m\u00fccellib", + "cezayir", + "\u015fahinbey", + "kay\u0131t", + "nural", + "ery\u0131ld\u0131z", + "aytek", + "yamin", + "do\u011fan\u015fah", + "onursu", + "canberk", + "erdemer", + "benol", + "tekbay", + "salami", + "\u00fcnek", + "san\u00e7ar", + "tekiner", + "\u00f6zger", + "ka\u015fif", + "nurullah", + "i\u0307brahim", + "do\u011fuhan", + "g\u00f6kay", + "m\u00fcnif", + "cevheri", + "y\u0131ld\u0131r", + "sonad", + "m\u00f6hsim", + "bur\u00e7", + "koray", + "emin", + "i\u0307lalm\u0131\u015f", + "baytal", + "\u00fcnsever", + "durdali", + "g\u00fcnser", + "abd\u00fclsamed", + "saba", + "talayer", + "oliver", + "tan\u0131r", + "sayin", + "bin\u0131\u015f\u0131k", + "\u00e7inerk", + "sakip", + "muktedir", + "fuzuli", + "jankat", + "recepali", + "alcan", + "arkut", + "atasagun", + "vezat", + "\u00e7avuldur", + "erksoy", + "temizkal", + "ensari", + "lutfi", + "veis", + "ercihan", + "karaer", + "t\u00fczeer", + "seler", + "yarg\u0131", + "\u00f6ncel", + "barak", + "yadigar", + "k\u0131rat", + "m\u00fckramin", + "semender", + "kahir", + "z\u00fcfer", + "mevl\u00fct", + "atnan", + "metinkaya", + "erin\u00e7er", + "g\u00f6k\u00e7ebalan", + "fazul", + "terlan", + "taylak", + "ba\u015fhan", + "gen\u00e7ay", + "k\u0131rg\u0131z", + "bahaddin", + "kocaba\u015f", + "gencaslan", + "dan\u0131\u015f", + "sittik", + "tanyola\u00e7", + "okt\u00fcremi\u015f", + "ya\u011f\u0131n", + "olca", + "mutas\u0131m", + "samurtay", + "g\u00fcnver", + "\u015fehamet", + "\u00e7o\u011fay", + "evcimen", + "eyy\u00fcp", + "sezginba\u015f", + "tart\u0131\u015f", + "yertan", + "\u00e7akar", + "karata\u015f", + "\u00f6m\u00fcr", + "akver", + "yurtta\u015f", + "deviner", + "\u00f6zkutlu", + "\u00f6\u011fet", + "g\u00fccal", + "aclan", + "\u00e7eliky\u00fcrek", + "alexandru", + "erginel", + "tun\u00e7k\u0131l\u0131\u00e7", + "esenbay", + "\u015fefi", + "sahir", + "binba\u015far", + "g\u00fc\u00e7al", + "\u011fanim", + "\u00f6zs\u00f6zl\u00fc", + "erten", + "bedri", + "ziyaettin", + "nayil", + "karcan", + "rafih", + "tanhan", + "erse\u00e7", + "t\u00fcmkurt", + "yekda", + "g\u00fc\u00e7l\u00fcer", + "akg\u00f6l", + "kopan", + "muratcan", + "telim", + "yah\u015fikan", + "t\u00fcmer", + "s\u00fcha", + "artan", + "\u00f6zbay", + "berran", + "yavuz", + "turgut", + "\u00e7a\u011flas\u0131n", + "erdursun", + "konguralp", + "fenni", + "kiramettin", + "i\u0307smet", + "edg\u00fcbay", + "b\u00fcnyam\u00fcn", + "selatin", + "el\u00f6ve", + "\u00f6z\u00e7am", + "g\u00fcneri", + "aliihsan", + "efe", + "\u00f6ge", + "tanbay", + "g\u00f6ken", + "okg\u00fc\u00e7l\u00fc", + "g\u00fcn\u015fen", + "erg\u00f6n\u00fcl", + "toy", + "kerman", + "nezihi", + "varg\u0131n", + "kiyasi", + "\u00f6zertem", + "halidun", + "c\u00fcneyit", + "nebih", + "esent\u00fcrk", + "\u015f\u00fckri", + "masar", + "oru\u00e7", + "t\u0131nal", + "demirok", + "nurcan", + "tecimer", + "umman", + "soykut", + "kalgay", + "akbo\u011fa", + "av\u015fin", + "ya\u015fattin", + "ginyas", + "risalet", + "koldan", + "ar\u0131kol", + "adasal", + "ertan", + "cannur", + "yazganalp", + "cantez", + "azettin", + "bas\u0131m", + "serda", + "aykutalp", + "g\u00fclel", + "\u00f6zg\u00fcr", + "g\u00fcnaydin", + "say\u0131n", + "efl\u00e2tun", + "paker", + "a\u011fmur", + "demirb\u00fcken", + "k\u0131nel", + "ekber", + "g\u00f6knur", + "tun\u00e7bo\u011fa", + "\u00fcn\u00fcbol", + "ba\u011fda\u015f", + "s\u0131la", + "tulun", + "salurbay", + "sevdi", + "aru", + "g\u00fcrsal", + "aytuna", + "zekayi", + "er\u015fat", + "temu\u00e7in", + "id\u0131k", + "tezol", + "dincer", + "cindoruk", + "rohat", + "hayret", + "aliseydi", + "ushan", + "fehim", + "durmu\u015fali", + "seyfullah", + "akdora", + "denizalp", + "korugan", + "ayayd\u0131n", + "\u015fafii", + "acar", + "tamayd\u0131n", + "\u015fuayp", + "eral", + "sel\u00e2tin", + "u\u011fan", + "\u00e7\u0131dal", + "ayvas", + "m\u00fcl\u00e2yim", + "akkerman", + "ko\u00e7ak", + "tutkun", + "nesip", + "uluda\u011f", + "baturay", + "g\u00fcle\u011fen", + "i\u0307kiz", + "d\u00f6lensoy", + "dilder", + "candeniz", + "erdibay", + "alkor", + "yalg\u0131n", + "yalazabay", + "yurdanur", + "seha", + "k\u0131z\u0131ltun\u00e7", + "ya\u011f\u0131zkurt", + "\u00e7amok", + "selaheddin", + "altu\u011f", + "muhammet", + "dayar", + "cansin", + "kenter", + "\u00e7apkan", + "raz\u0131", + "ko\u00e7kan", + "sa\u011f\u0131t", + "abuzar", + "temirhan", + "ta\u015fkan", + "i\u0307lteri\u015f", + "dolun", + "l\u00fctfi", + "k\u0131z\u0131l", + "erbil", + "ba\u015fok", + "bellisan", + "fetullah", + "abd\u00fcrre\u015fit", + "sudi", + "bar\u0131\u015fcan", + "baba", + "ak\u00f6z", + "abid", + "uluman", + "meng\u00fc\u00e7", + "asalet", + "\u00f6zaslan", + "okyalaz", + "ar\u0131soy", + "canal", + "i\u015f\u0131man", + "apayd\u0131n", + "g\u00fcrelcem", + "\u00f6zel", + "\u00e2dem", + "led\u00fcn", + "abdulsemet", + "necmettin", + "erkan", + "sadat", + "t\u00f6rel", + "m\u00fcrit", + "beyler", + "yilmaz", + "ongay", + "bican", + "abdurrahman", + "musafet", + "\u00f6zbilek", + "\u00f6zakan", + "hudavent", + "nafii", + "ilg\u0131", + "\u00fcsame", + "mucahit", + "aktem\u00fcr", + "\u00f6ver", + "i\u0307lkim", + "berkal", + "tu\u011fta\u015f", + "balatekin", + "k\u00f6semen", + "uraltay", + "at\u0131lgan", + "bi\u015far", + "\u00f6ngen", + "fahrullah", + "i\u0307diris", + "hanedan", + "cemalettin", + "verim", + "alattin", + "yurtg\u00fcven", + "okanay", + "nakip", + "giz", + "bayzettin", + "o\u011furata", + "\u00f6kka\u015f", + "eskinalp", + "ahsen", + "sayrak", + "kasim", + "\u00f6nsal", + "g\u00fcl\u015fahin", + "huzuri", + "\u00f6zp\u0131nar", + "aypar", + "yeneral", + "onat", + "saydam", + "necdat", + "z\u00fclgarni", + "din\u00e7s\u00fc", + "ay\u015fan", + "monis", + "timurta\u015f", + "rezzak", + "erik", + "memili", + "\u00e7a\u011fdan", + "t\u00fckelalp", + "yasan", + "g\u00f6kten", + "tanak", + "hazrat", + "ulutay", + "ti\u011fin", + "suphi", + "\u015fahmettin", + "akba\u015f", + "abd\u00fclcemal", + "g\u00fcrarda", + "cang\u00fcr", + "\u015fenkal", + "ergener", + "i\u0307ntihap", + "tu\u011fcan", + "cenan", + "kutay", + "\u00f6zdal", + "kibar", + "tans\u0131\u011f", + "utkucan", + "a\u015fir", + "tayyip", + "kaygusuz", + "atgun", + "tando\u011fdu", + "resulcan", + "duru\u00f6z", + "i\u0307lsu", + "h\u0131fzullah", + "karaca", + "nabil", + "i\u0307nan\u00e7l\u0131", + "bilg\u00fctay", + "soydaner", + "tuyu\u011f", + "yayak", + "\u00e7elikkan", + "m\u00fczekker", + "\u00f6zt\u00fcrk", + "eba", + "noman", + "\u00fcst\u00fcn", + "zahid", + "g\u00f6rkl\u00fc", + "abdulkadir", + "mazlum", + "sencar", + "erdogan", + "abdulbekir", + "taciddin", + "aran", + "kuddusi", + "rahmet", + "\u015fali", + "i\u0307lmafer", + "baki", + "sebattin", + "diken", + "erensoy", + "tunahan", + "arifcan", + "cavit", + "g\u00fcnkurt", + "toktu\u011f", + "berki", + "abdi\u015f", + "tekecan", + "rabih", + "\u00e7alt\u0131", + "alto\u011fan", + "as\u0131m", + "behrem", + "cercis", + "ortak", + "ekmel", + "mehmed", + "alpcan", + "er\u00f6z", + "ama\u00e7", + "\u015fevket", + "t\u00fcrkmen", + "yank\u0131", + "urhan", + "mehmetzahir", + "nazlim", + "erkinel", + "ebuakil", + "milay", + "\u00f6nel", + "mansurali", + "\u00f6zok\u00e7u", + "ersel", + "bilender", + "nurkan", + "boynak", + "kayrabay", + "i\u0307vecen", + "muvaffak", + "b\u00f6rte\u00e7in", + "feremez", + "baydu", + "bayman", + "cuman", + "seydo", + "turabi", + "g\u00fcnd\u00fczalp", + "tevs", + "k\u00f6kta\u015f", + "g\u00f6zel", + "akar", + "songurkan", + "s\u00fccaettin", + "hami", + "topuz", + "baykan", + "y\u00fccelen", + "okbay", + "mahir", + "besin", + "ism\u0131k", + "karaba\u015f", + "tanp\u0131nar", + "enes", + "atalay", + "akif", + "sancak", + "vahittin", + "hindal", + "uygun", + "kapagan", + "\u00f6ry\u00fcrek", + "ferat", + "\u00e7\u0131vg\u0131n", + "ramadan", + "gazel", + "\u015finasi", + "nerim", + "g\u00fcng\u00f6rd\u00fc", + "olda\u011f", + "bilgen", + "feyruz", + "andi\u00e7", + "taranc\u0131", + "do\u011fanalp", + "\u00f6zl\u00fc", + "me\u015fhur", + "argu", + "annak", + "tenvir", + "\u015fide", + "r\u00fcknettin", + "\u015fanl\u0131", + "siper", + "alaaddin", + "kanak", + "akdurmu\u015f", + "ta\u015far", + "da\u011fistan", + "g\u00fc\u00e7yeter", + "hatem", + "emir\u015fan", + "ferzi", + "hasbek", + "fersan", + "arcan", + "u\u011furtan", + "tezcan", + "alanalp", + "alt\u0131n\u0131\u015f\u0131n", + "ad\u0131g\u00fcn", + "fatih", + "aysoy", + "teksoy", + "nuretdin", + "demiry\u00fcrek", + "kanpulat", + "server", + "suat", + "karlukhan", + "erg\u00fcn", + "elnur", + "bo\u011fatimur", + "y\u00fcmun", + "afer", + "\u015fendo\u011fan", + "yal\u0131n", + "ruhsat", + "aks\u00f6\u011f\u00fct", + "umutcan", + "yalt\u0131rak", + "\u00f6zalpsan", + "ferihan", + "bekbay", + "\u00e7etinsu", + "kayag\u00fcn", + "akmaner", + "niyazi", + "sadittin", + "tahir", + "bulun\u00e7", + "serhatmehmet", + "alt\u0131nkaya", + "taygan", + "co\u015fkun", + "h\u00fcsmen", + "s\u00f6kmen", + "remazan", + "y\u0131lma", + "bali", + "bahittin", + "borahan", + "sabih", + "merzuk", + "savak", + "org\u00fcn", + "k\u0131l\u0131\u00e7bay", + "o\u011fuzman", + "uzsoy", + "akcivan", + "adak", + "i\u0307yiy\u00fcrek", + "beyzade", + "vafir", + "celilay", + "\u00fcmmet", + "onurcan", + "abd\u00fclkerim", + "alps\u00fc", + "zamir", + "mengi" + ], + "PREFIX_FEMALE": [ + "dr", + "bayan" + ], + "PREFIX_MALE": [ + "dr", + "bay" + ], + "FIRST_NAME": [ + "fatig\u00fcl", + "elvan", + "yosma", + "s\u0131yl\u0131han", + "abd\u00fclhadi", + "t\u00fclin", + "dirlik", + "hidir", + "muhyettin", + "onuker", + "nihai", + "afife", + "sevim", + "g\u00fclseren", + "torhan", + "elhan", + "tungu\u00e7", + "galip", + "dalan", + "derkay", + "selmin", + "ar\u0131el", + "nurmelek", + "ezg\u00fctekin", + "haluk", + "buyrukhan", + "k\u00e2mil", + "h\u00fcda", + "tongu\u00e7", + "i\u0307lbek", + "canur", + "o\u011fulba\u015f", + "h\u00fcrya\u015far", + "sunel", + "hunalp", + "\u015fahat", + "d\u00fcrr\u00fc\u015fehvar", + "mefarettin", + "alparslan", + "ball\u0131", + "\u00f6zay", + "aybora", + "serol", + "ye\u015fil", + "sevindik", + "i\u0307lper", + "i\u0307lim", + "ir\u0131s", + "zihni", + "vedat", + "bari\u015f", + "balta\u015f", + "nebiha", + "burakhan", + "\u00e7elem", + "korkmazalp", + "yolal", + "s\u00fcvari", + "a\u011faki\u015fi", + "nurgil", + "hi\u00e7s\u00f6nmez", + "hanim", + "g\u00fclhisar", + "haliye", + "\u015fehza", + "yazg\u00fcl", + "uzbay", + "mertel", + "aydin\u00e7", + "yurtseven", + "ertuncay", + "yasemen", + "oranl\u0131", + "okseven", + "tok\u00f6z", + "dilcan", + "odkanl\u0131", + "paksu", + "bozba\u011f", + "g\u00fcls\u00fc", + "g\u00fcla\u011fa", + "kotuz", + "binay", + "i\u0307klim", + "\u00f6kt\u00fcrk", + "abdulgazi", + "hakikat", + "beste", + "z\u00fcmre", + "paye", + "z\u00fclbiye", + "bidayet", + "aksay", + "sar\u0131cabay", + "\u015fabettin", + "salk\u0131n", + "nurveren", + "ecemi\u015f", + "tanyu", + "\u015femsettin", + "aslanhan", + "havali", + "bit\u00fcl", + "hasg\u00fcl", + "ferahdiba", + "duruk", + "i\u0307nsaf", + "mevl\u00fcdiye", + "tali", + "nas", + "servinaz", + "akatay", + "akise", + "karanbay", + "g\u00fclnaziye", + "atanur", + "se\u00e7me", + "erk\u0131l\u0131\u00e7", + "atilhan", + "s\u00fcmeyye", + "safet", + "g\u00fcng\u00f6ren", + "tansev", + "i\u0307lklima", + "\u00f6zkent", + "haciali", + "b\u00fc\u015franur", + "hayali", + "adila", + "ulu\u011fbey", + "delil", + "cabir", + "a\u011fbegim", + "nural", + "ery\u0131ld\u0131z", + "faize", + "salami", + "tekiner", + "san\u00e7ar", + "ka\u015fif", + "nurullah", + "do\u011fuhan", + "m\u00f6hsim", + "bur\u00e7", + "rehime", + "i\u0307lalm\u0131\u015f", + "\u00fcnsever", + "i\u0307mrihan", + "durdali", + "abd\u00fclsamed", + "aykut", + "zahfer", + "muktedir", + "jankat", + "hadrey", + "m\u00fckr\u00fcme", + "alcan", + "g\u00fcl\u00e7e", + "atasagun", + "birben", + "erksoy", + "aky\u0131ld\u0131z", + "olu\u015f", + "lutfi", + "karaer", + "seler", + "miray", + "nurhayet", + "deniz", + "m\u00fckramin", + "semender", + "kahir", + "fazul", + "selcen", + "seyhan", + "i\u0307ncifir", + "sezen", + "tanyola\u00e7", + "\u00f6zyurt", + "evcimen", + "cedide", + "tun\u00e7k\u0131l\u0131\u00e7", + "y\u00fccel", + "g\u00fcrten", + "mefharet", + "hur\u015fide", + "g\u00fc\u00e7al", + "binba\u015far", + "zubeyde", + "ganiye", + "ziyaettin", + "i\u0307lde\u015f", + "tanhan", + "yekda", + "akg\u00f6l", + "t\u00fcmer", + "erdursun", + "fenni", + "reng\u00fcl", + "rebihat", + "el\u00f6ve", + "efe", + "laika", + "okg\u00fc\u00e7l\u00fc", + "nili", + "rabbiye", + "kiyasi", + "esent\u00fcrk", + "fayize", + "h\u00fcsn\u00fch\u00e2l", + "umman", + "akbo\u011fa", + "ya\u015fattin", + "adasal", + "cannur", + "\u015ferman", + "serda", + "\u00f6zg\u00fcr", + "say\u0131n", + "efl\u00e2tun", + "\u015feref", + "ayt\u00f6z", + "t\u00fcrcan", + "acarkan", + "fehmiye", + "g\u00fclselin", + "er\u015fat", + "temu\u00e7in", + "dincer", + "uyanser", + "hayret", + "ushan", + "seyfullah", + "susam", + "sel\u00e2tin", + "\u015fuayp", + "salimet", + "m\u00fcl\u00e2yim", + "naide", + "tan", + "sevcan", + "g\u00fcle\u011fen", + "nept\u00fcn", + "akg\u00fcne\u015f", + "ya\u011f\u0131zkurt", + "dayar", + "birsan", + "abuzar", + "g\u00fcrc\u00fcye", + "fetullah", + "baba", + "gabel", + "sadat", + "yilmaz", + "ongay", + "ayn\u0131mah", + "musafet", + "ilg\u0131", + "nafii", + "\u00e7a\u011flar", + "alg\u0131\u015f", + "\u00f6zlem", + "aktem\u00fcr", + "tu\u011fta\u015f", + "canseven", + "havse", + "bi\u015far", + "natalia", + "fahrullah", + "pesent", + "yurtg\u00fcven", + "giz", + "anka", + "mukbile", + "silanur", + "kasim", + "sanur", + "sebl\u00e2", + "huzuri", + "yeneral", + "necdat", + "nezeng\u00fcl", + "\u00e7a\u011fdan", + "vacibe", + "ulutay", + "\u015fefiye", + "aydar", + "ti\u011fin", + "cang\u00fcr", + "tu\u011fcan", + "utkucan", + "kaygusuz", + "tayyip", + "duru\u00f6z", + "sonnur", + "karaca", + "tuyu\u011f", + "nevsale", + "\u00e7elikkan", + "sernur", + "feyha", + "minibe", + "\u00fcst\u00fcn", + "erdogan", + "mazlum", + "serma", + "i\u0307lkbahar", + "sevla", + "kardelen", + "s\u0131rriye", + "nefiye", + "tomurcuk", + "\u00e7alt\u0131", + "alto\u011fan", + "as\u0131m", + "behrem", + "bilkay", + "teknaz", + "ama\u00e7", + "kitan", + "yank\u0131", + "\u00f6nel", + "erem", + "kayrabay", + "muvaffak", + "cuman", + "aycag\u00fcl", + "tevs", + "hami", + "ism\u0131k", + "karaba\u015f", + "sancak", + "gazel", + "bahtinur", + "olda\u011f", + "bilgen", + "\u00f6zg\u00fcn", + "hasret", + "do\u011fanalp", + "mezide", + "annak", + "meveddet", + "nura", + "akdurmu\u015f", + "ta\u015far", + "aral", + "fildan", + "ferhan", + "g\u00fclbiye", + "z\u00f6hrehan", + "teksoy", + "demiry\u00fcrek", + "suat", + "erg\u00fcn", + "afer", + "alt\u0131n\u00e7i\u00e7ek", + "ferihan", + "g\u00fclsiye", + "m\u00fcnezzer", + "mufide", + "co\u015fkun", + "ferinaz", + "borahan", + "sabih", + "savak", + "akcivan", + "i\u0307yiy\u00fcrek", + "celilay", + "\u00fcmmet", + "onurcan", + "i\u015fin", + "abd\u00fclkerim", + "edaviye", + "zennun", + "rezin", + "heyvetullah", + "umu\u015fan", + "filit", + "nehip", + "ero\u011ful", + "s\u00f6zer", + "feyzin", + "maksur", + "\u015ferafeddin", + "d\u00f6ner", + "dalk\u0131l\u0131\u00e7", + "i\u0307sak", + "hariz", + "cuheyna", + "rasul", + "dil\u015fat", + "mecit", + "peren", + "ar\u0131p\u0131nar", + "ezgin", + "\u00e7ilga", + "elifnur", + "m\u00fcbetcel", + "aylil", + "g\u00f6k\u00e7e", + "sehel", + "sarpk\u0131n", + "kel\u00e2mi", + "tayayd\u0131n", + "henife", + "denkel", + "sa\u011fcan", + "sevsevil", + "tasvir", + "\u00fcmm\u00fchan", + "sayg\u0131n", + "h\u00fcrdo\u011fan", + "egenur", + "pirahmet", + "us", + "satrettin", + "sefer", + "to\u011fan", + "g\u00f6ksev", + "mahsun", + "ruhug\u00fcl", + "demiriz", + "u\u00e7an", + "ert\u00fcn", + "almast", + "mutluhan", + "nefaret", + "\u00e7er\u00e7i", + "ho\u015fkadem", + "aynilhayat", + "k\u0131v\u0131lc\u0131m", + "vaysal", + "\u00fcnal", + "hekime", + "\u015favki", + "ahat", + "ogu\u015f", + "yoru\u00e7", + "nuyan", + "\u00fcbeydullah", + "v\u00e2l\u00e2", + "buhari", + "geray", + "\u00f6zdil", + "adlan", + "u\u011furkan", + "rahiye", + "zoral", + "refet", + "zevl\u00fcde", + "evrimer", + "b\u00fcget", + "i\u0307mam", + "akalan", + "firdevis", + "zeynelabidin", + "bat\u0131rhan", + "mesude", + "i\u0307rfan", + "miyesser", + "mirbadin", + "tolonbay", + "abdulmenaf", + "sanavber", + "bekta\u015fi", + "nasuf", + "seda", + "ay\u015fenur", + "e\u015fref", + "m\u00fcslum", + "n\u02dczamett\u02dcn", + "behiza", + "necva", + "beren", + "kandef", + "g\u00fcm\u00fc\u015ftekin", + "tanses", + "enfes", + "s\u00fcsen", + "kay\u0131t", + "m\u00fccellib", + "canberk", + "onursu", + "erdemer", + "tekbay", + "\u00f6zger", + "cevheri", + "y\u0131ld\u0131r", + "sel\u00e7uk", + "emin", + "\u015filan", + "oliver", + "\u00e7inerk", + "recepali", + "selime", + "vezat", + "g\u00fclgen", + "macide", + "hilayda", + "ercihan", + "t\u00fczeer", + "yarg\u0131", + "\u00f6zge", + "barak", + "\u00fc\u00e7g\u00fcl", + "k\u0131rat", + "merva", + "z\u00fcfer", + "hacile", + "deryanur", + "g\u00f6k\u00e7ebalan", + "taylak", + "ba\u015fhan", + "gen\u00e7ay", + "bahaddin", + "nur\u015fan", + "birg\u00fcl", + "mujde", + "nuriyet", + "sevgen", + "safinaz", + "m\u00fc\u015f\u00fcre", + "simten", + "sittik", + "rumeysa", + "okt\u00fcremi\u015f", + "melikkan", + "samurtay", + "g\u00fcnver", + "\u00e7o\u011fay", + "eyy\u00fcp", + "leyli", + "kad\u0131nana", + "tayyibe", + "nihan", + "deviner", + "sa\u00e7\u0131", + "aclan", + "arziye", + "m\u00fccevher", + "piran", + "n\u00fcdret", + "esenbay", + "mahter", + "nejdet", + "\u00f6zs\u00f6zl\u00fc", + "erten", + "bedri", + "merim", + "t\u00fcmkurt", + "g\u00fc\u00e7l\u00fcer", + "nazi", + "muratcan", + "yah\u015fikan", + "m\u00fcjde", + "g\u00fcl", + "berran", + "turgut", + "edg\u00fcbay", + "selatin", + "ticen", + "tanbay", + "g\u00f6ken", + "nesfe", + "bergen", + "g\u00fclfari", + "i\u015f\u0131n", + "\u00f6zertem", + "c\u00fcneyit", + "nurey", + "masar", + "\u00e2lem\u015fah", + "k\u00e2zime", + "oru\u00e7", + "t\u0131nal", + "av\u015fin", + "teybet", + "risalet", + "koldan", + "melaha", + "ertan", + "g\u00fclev", + "nurda", + "paker", + "g\u00f6knur", + "\u00fcn\u00fcbol", + "ba\u011fda\u015f", + "s\u00fcheyda", + "salurbay", + "gilman", + "sevdi", + "zekayi", + "tezol", + "cindoruk", + "durmu\u015fali", + "denizalp", + "u\u011fan", + "eri\u015f", + "akkerman", + "i\u0307kiz", + "d\u00f6lensoy", + "alkor", + "erdibay", + "yalg\u0131n", + "ta\u00e7nur", + "muhammet", + "cansin", + "\u00e7apkan", + "raz\u0131", + "ko\u00e7kan", + "adal", + "temirhan", + "ta\u015fkan", + "dolun", + "dilhu\u015f", + "bellisan", + "abd\u00fcrre\u015fit", + "sudi", + "asalet", + "canal", + "g\u00f6k", + "apayd\u0131n", + "nurta\u00e7", + "led\u00fcn", + "divan", + "hayel", + "rafia", + "bican", + "vefia", + "abdurrahman", + "\u00f6zakan", + "hudavent", + "\u00fcsame", + "ayduru", + "mucahit", + "kutg\u00fcn", + "balatekin", + "permun", + "i\u0307diris", + "g\u00fclenay", + "r\u00fcmeysa", + "g\u00fcll\u00fchan", + "nakip", + "bayzettin", + "beray", + "\u00f6kka\u015f", + "eskinalp", + "m\u00fcsemma", + "m\u00fcferrih", + "simber", + "g\u00fcl\u015fahin", + "\u00f6zp\u0131nar", + "mahig\u00fcl", + "harbinaz", + "monis", + "y\u0131ld\u0131z", + "\u015fah\u0131g\u00fcl", + "rezzak", + "erik", + "pekkan", + "t\u00fckelalp", + "balca", + "yasan", + "sevdinar", + "\u00fcge", + "suphi", + "eceg\u00fcl", + "\u00fcrper", + "ay\u00e7an", + "\u00e7olpan", + "mihriye", + "i\u0307ntihap", + "g\u00f6rsev", + "kutay", + "\u015fehreban", + "g\u00fcl\u00f6zge", + "atgun", + "armahan", + "i\u0307lsu", + "nabil", + "hezniye", + "yayak", + "soydaner", + "abiye", + "m\u00fczekker", + "\u00f6zt\u00fcrk", + "noman", + "g\u00f6rkl\u00fc", + "emine", + "abdulkadir", + "i\u0307lmafer", + "tagang\u00fcl", + "fitnat", + "toktu\u011f", + "abdi\u015f", + "nezize", + "\u015femsinisa", + "tekecan", + "ma\u015fide", + "t\u00fcrknur", + "er\u00f6z", + "\u015fevket", + "urhan", + "mehmetzahir", + "huban", + "nazlim", + "erkinel", + "milay", + "\u00f6zok\u00e7u", + "ersel", + "bilender", + "nurkan", + "boynak", + "zilfa", + "feremez", + "yurdaser", + "verde", + "tang\u00fcl", + "fadile", + "ay\u00fclker", + "k\u00f6kta\u015f", + "avun\u00e7", + "songurkan", + "topuz", + "se\u00e7g\u00fcl", + "musaffa", + "p\u00fcr\u00e7ek", + "kapagan", + "ferat", + "misra", + "g\u00fclter", + "feyruz", + "damlanur", + "feraye", + "ayhan", + "kanak", + "i\u0307hsan", + "ferzi", + "alt\u0131n\u0131\u015f\u0131n", + "duyguhan", + "nuretdin", + "kanpulat", + "server", + "karlukhan", + "y\u00fcmun", + "\u015fendo\u011fan", + "aks\u00f6\u011f\u00fct", + "kayag\u00fcn", + "niyazi", + "sadittin", + "tahir", + "serhatmehmet", + "h\u00fcsmen", + "y\u0131lma", + "bali", + "bezek", + "goncafer", + "merzuk", + "org\u00fcn", + "uzsoy", + "adak", + "vafir", + "zeride", + "alps\u00fc", + "mengi", + "ruhide", + "a\u015fhan", + "kete", + "\u015fad\u0131man", + "tu\u011frulhan", + "m\u00fc\u011fber", + "\u00f6zerdin\u00e7", + "fad\u0131la", + "koncag\u00fcl", + "t\u00fcrabi", + "g\u00f6rg\u00fcnay", + "pehlil", + "fatinur", + "g\u00fclfeza", + "yepelek", + "mehdiye", + "s\u00fczer", + "kavurt", + "h\u00fcrmet", + "\u015fekim", + "yunt", + "beyhatun", + "semat", + "ak\u0131nal", + "deha", + "din\u00e7kol", + "g\u00f6k\u00e7il", + "sarg\u0131n", + "i\u0307zg\u00fc", + "nevsal", + "mishat", + "i\u015f\u0131kay", + "savni", + "habibe", + "enginiz", + "\u00e7a\u011fa", + "seracettin", + "ulakbey", + "\u00f6ztek", + "g\u00fcver\u00e7in", + "borata\u015f", + "i\u0307lgi", + "soysel\u00e7uk", + "cebesoy", + "nurser", + "\u00e7isem", + "kader", + "dorukhan", + "begim", + "k\u00f6ker", + "m\u00fcret", + "sami", + "merdi", + "g\u00fcler", + "i\u0307\u015fcan", + "alaeddin", + "s\u00f6yler", + "\u00f6zdo\u011fdu", + "g\u00fcnebakan", + "efser", + "i\u0307mge", + "anarg\u00fcl", + "ak\u00e7asu", + "esna", + "subutiye", + "sidki", + "meryeme", + "y\u00f6netmen", + "yeti\u015fal", + "g\u00fclder", + "dirican", + "emrullah", + "\u00f6z\u00fcdo\u011fru", + "mestur", + "sahil", + "kefser", + "mel\u00fbl", + "k\u00fcr\u015fad", + "aliabbas", + "g\u00fcnden", + "laze", + "beyda", + "cihandide", + "ozans\u00fc", + "rojnu", + "yelesen", + "m\u00fcveddet", + "\u00fczer", + "sadeti", + "\u00fclk\u00fcde\u015f", + "i\u0307mren", + "\u00e7evreg\u00fcl", + "s\u00fcner", + "aksoy", + "\u00fcnlen", + "h\u00fcr\u00fcyet", + "g\u00f6nen", + "g\u00fclinaz", + "i\u0307ldem", + "melihcan", + "g\u00fclmisal", + "rakide", + "h\u00fck\u00fcmdar", + "m\u00fcfit", + "mihin", + "\u015fennur", + "erg\u00fcl", + "berksay", + "\u015fahinbey", + "do\u011fan\u015fah", + "sejda", + "nurseda", + "benol", + "sevican", + "\u015fahnuray", + "sonad", + "mihrab", + "kifaye", + "elgin", + "g\u00fcnser", + "talayer", + "sayin", + "ay\u015feana", + "arkut", + "\u00e7avuldur", + "temizkal", + "veis", + "benek", + "i\u0307\u00e7imbike", + "mevl\u00fct", + "atnan", + "bediriye", + "terlan", + "berrin", + "serfinaz", + "k\u0131rg\u0131z", + "kocaba\u015f", + "gencaslan", + "dan\u0131\u015f", + "nevise", + "feden", + "ya\u011f\u0131n", + "\u015fehamet", + "fatmanur", + "erbay", + "tart\u0131\u015f", + "yertan", + "karata\u015f", + "pembesin", + "revza", + "akver", + "yurtta\u015f", + "\u00f6\u011fet", + "emi\u015f", + "g\u00fccal", + "\u00e7eliky\u00fcrek", + "alexandru", + "bilay", + "\u011fanim", + "nayil", + "erse\u00e7", + "rafih", + "ban\u00fc", + "hinet", + "z\u00fclf\u00fcye", + "sat\u0131a", + "\u00e7a\u011flas\u0131n", + "sultane", + "b\u00fcnyam\u00fcn", + "g\u00fclg\u00fczel", + "g\u00fcneri", + "\u00f6ge", + "neval", + "saire", + "erg\u00f6n\u00fcl", + "b\u00fcreyre", + "ayyaruk", + "nezihi", + "ne\u015frin", + "halidun", + "hansultan", + "nurcan", + "tecimer", + "l\u00e2le", + "soykut", + "ginyas", + "ar\u0131kol", + "cantez", + "aysevim", + "\u015fayan", + "demirb\u00fcken", + "k\u0131nel", + "tun\u00e7bo\u011fa", + "rana", + "tulun", + "g\u00fcrsal", + "kezban", + "aytuna", + "durgadin", + "burcuhan", + "nurdeniz", + "cevale", + "g\u00fclzadiye", + "tutkucan", + "s\u00fcleyla", + "rohat", + "aliseydi", + "esmanperi", + "akdora", + "alize", + "g\u00fclsal\u0131n", + "ayayd\u0131n", + "e\u015fim", + "r\u0131fk\u0131ye", + "tamayd\u0131n", + "eral", + "g\u00fcldam", + "akmaral", + "g\u00fczey", + "tutkun", + "ko\u00e7ak", + "ahter", + "nesip", + "tercan", + "dilder", + "candeniz", + "g\u00fcnar", + "aysuna", + "seha", + "k\u0131z\u0131ltun\u00e7", + "\u00e7amok", + "altu\u011f", + "i\u0307lteri\u015f", + "ya\u015far", + "l\u00fctfi", + "k\u0131z\u0131l", + "erbil", + "bar\u0131\u015fcan", + "ak\u00f6z", + "uluman", + "meng\u00fc\u00e7", + "okyalaz", + "\u00f6zaslan", + "i\u015f\u0131man", + "akay", + "g\u00fcrelcem", + "ba\u011fdat", + "\u00e2dem", + "t\u00f6rel", + "abdulsemet", + "beyler", + "fermuta", + "\u00f6zbilek", + "meyhanim", + "ervaniye", + "k\u00f6semen", + "hanedan", + "verim", + "alattin", + "\u015feyda", + "g\u00fclsevil", + "o\u011furata", + "halenur", + "ahsen", + "sayrak", + "evde", + "aypar", + "merba", + "nasiba", + "zebirce", + "saydam", + "onat", + "z\u00fclgarni", + "ay\u015fan", + "timurta\u015f", + "emal", + "k\u0131smet", + "memili", + "de\u011fer", + "akba\u015f", + "abd\u00fclcemal", + "g\u00fclkad\u0131n", + "ergener", + "lezize", + "cenan", + "kibar", + "sevginur", + "sidar", + "tando\u011fdu", + "resulcan", + "g\u00fcl\u00fcs", + "ummahani", + "h\u0131fzullah", + "i\u0307sra", + "eba", + "nafile", + "zahid", + "nirg\u00fcl", + "sencar", + "abdulbekir", + "rahmet", + "heva", + "\u015fali", + "sebattin", + "diken", + "tunahan", + "k\u00fcbran", + "feryas", + "berki", + "ekmel", + "mehmed", + "beriye", + "ebuakil", + "mansurali", + "nilcan", + "i\u0307vecen", + "seydo", + "turabi", + "g\u00fcnd\u00fczalp", + "g\u00f6zel", + "s\u00fccaettin", + "mahir", + "l\u00fcfen", + "besin", + "\u015f\u00f6hret", + "alaz", + "sarya", + "tanp\u0131nar", + "enes", + "vahittin", + "zinnure", + "uygun", + "\u00f6ry\u00fcrek", + "\u00e7\u0131vg\u0131n", + "g\u00fclbani", + "\u015finasi", + "asliye", + "nerim", + "g\u00fcng\u00f6rd\u00fc", + "taranc\u0131", + "\u00f6zl\u00fc", + "me\u015fhur", + "argu", + "jaruthip", + "r\u00fcknettin", + "muvahhide", + "\u015fanl\u0131", + "dilsitan", + "siper", + "da\u011fistan", + "\u015famiha", + "dilara", + "emir\u015fan", + "sebig\u00fcl", + "u\u011furtan", + "g\u00fcl\u015fa", + "aysoy", + "cihan", + "m\u00fcmtaze", + "elnur", + "ruhsat", + "umutcan", + "yalt\u0131rak", + "akmaner", + "\u015fahinder", + "taygan", + "dursadiye", + "narhanim", + "nazlihan", + "naz\u0131dil", + "k\u0131l\u0131\u00e7bay", + "vecide", + "benice", + "\u015fevketfeza", + "zamir", + "\u015f\u00fck\u00fcfe", + "mahnaz", + "\u00e7opur", + "\u015fazime", + "refik", + "bu\u015fra", + "hekmet", + "muhiye", + "oganer", + "erenalp", + "g\u00f6kbudun", + "evrim", + "sezal", + "elamiye", + "barsen", + "abd\u00fclahat", + "ufukay", + "g\u00f6kperi", + "\u00fcmray", + "seyithan", + "feza", + "sirap", + "t\u00fcrkalp", + "badeg\u00fcl", + "karakucak", + "\u00f6zpetek", + "teber", + "bengibay", + "velitdin", + "ba\u015fay", + "\u00e7a\u011fveren", + "fami", + "semine", + "menfeat", + "atat\u00f6re", + "r\u00fc\u015fen", + "cemiyle", + "varl\u0131k", + "t\u00fczenur", + "bedi", + "u\u00e7beyi", + "duracan", + "alsoy", + "zeyno", + "bozerk", + "\u015firivan", + "a\u00e7\u0131lay", + "\u00f6rik", + "ak\u00e7abay", + "efil", + "arpa\u011f", + "adviye", + "maynur", + "mehrig\u00fcl", + "tatu", + "hayr\u00fcnnisa", + "aygutalp", + "kutun", + "atag\u00fcn", + "almus", + "a\u00e7\u0131kel", + "\u00e7okan", + "omaca", + "otay", + "muarra", + "bozta\u015f", + "alpin", + "d\u00fcndaralp", + "f\u00fcgen", + "ko\u015fukhan", + "hatin", + "kamar", + "belkize", + "\u015fel\u00e2le", + "\u00fclfet", + "de\u011fmeer", + "birsen", + "\u00e7ak\u0131rca", + "bilta\u015f", + "hamiyet", + "ulu", + "\u00fcrfettin", + "nurbanu", + "safura", + "u\u011fur", + "\u00e7evik\u00f6z", + "masume", + "bayruhan", + "nazimet", + "sulhi", + "neslinur", + "zaliha", + "oymak", + "toker", + "serezli", + "azade", + "or\u00e7in", + "selvi", + "ayten", + "perinur", + "ermutlu", + "eraycan", + "yigit", + "vezrife", + "ayd\u0131nbey", + "muhip", + "\u00f6zinal", + "birgit", + "aytek", + "cezayir", + "yamin", + "seniha", + "nazende", + "\u00fcnek", + "i\u0307brahim", + "g\u00f6kay", + "m\u00fcnif", + "koray", + "baytal", + "saba", + "tan\u0131r", + "bin\u0131\u015f\u0131k", + "sakip", + "ni\u011fmet", + "fuzuli", + "ensari", + "dilfeza", + "atiyye", + "\u00f6ncel", + "g\u00fcld\u00fcnya", + "\u00f6zde\u015f", + "yadigar", + "basriye", + "metinkaya", + "erin\u00e7er", + "kerime", + "neriban", + "olca", + "mutas\u0131m", + "sab\u0131r", + "mecide", + "siti", + "sezginba\u015f", + "\u00e7akar", + "\u00f6m\u00fcr", + "necilal", + "asu", + "\u00f6zkutlu", + "eseng\u00fcn", + "erginel", + "g\u00fcnsel", + "talibe", + "\u015fefi", + "sahir", + "hazine", + "karcan", + "g\u00fclper", + "kopan", + "telim", + "s\u00fcha", + "artan", + "\u00f6zbay", + "s\u00fcmerya", + "yavuz", + "konguralp", + "kiramettin", + "maks\u00fcde", + "i\u0307smet", + "azize", + "\u00f6z\u00e7am", + "aliihsan", + "g\u00fclay", + "g\u00fcn\u015fen", + "ceyhun", + "toy", + "kerman", + "soykan", + "varg\u0131n", + "nebih", + "turcein", + "\u015f\u00fckri", + "belgizar", + "demirok", + "kalgay", + "i\u0307slime", + "z\u00fcheyla", + "yazganalp", + "azettin", + "bas\u0131m", + "samahat", + "aykutalp", + "g\u00fclel", + "g\u00fcnaydin", + "kaver", + "ekber", + "a\u011fmur", + "kumral", + "do\u011fannur", + "s\u0131la", + "zemzem", + "g\u00fclbeyan", + "aru", + "i\u0307zel", + "id\u0131k", + "aybet", + "meleknur", + "fehim", + "\u00e7al\u0131m", + "fidaye", + "korugan", + "acar", + "nal\u00e2n", + "zehranur", + "\u015fafii", + "\u00e7\u0131dal", + "ayvas", + "sabihe", + "zelha", + "uluda\u011f", + "baturay", + "g\u00fclceg\u00fcn", + "yalazabay", + "yurdanur", + "\u00f6mriye", + "kenter", + "selaheddin", + "asiman", + "duha", + "limon", + "sa\u011f\u0131t", + "ild\u0131z", + "alabezek", + "ba\u015fok", + "tu\u011f\u00e7e", + "abid", + "ar\u0131soy", + "\u00f6zel", + "erkan", + "necmettin", + "m\u00fcrit", + "\u00fclke", + "temime", + "nursim", + "tule", + "\u00f6ver", + "i\u0307lkim", + "berkal", + "uraltay", + "at\u0131lgan", + "hanbiken", + "\u00f6ngen", + "cemalettin", + "okanay", + "alt\u0131nbike", + "\u00f6nsal", + "g\u00f6li", + "\u015fahdiye", + "din\u00e7s\u00fc", + "yah\u015fi", + "rayla", + "seyyide", + "i\u0307de", + "g\u00f6kten", + "tanak", + "hazrat", + "al\u0131\u015f\u0131k", + "canfeza", + "\u015fahmettin", + "g\u00fcrarda", + "\u015fenkal", + "\u00f6zdal", + "tans\u0131\u011f", + "a\u015fir", + "g\u00fcl\u015feref", + "\u00f6rfiye", + "i\u0307nan\u00e7l\u0131", + "bilg\u00fctay", + "besey", + "haf\u0131za", + "bilginur", + "taciddin", + "aran", + "kuddusi", + "baki", + "zerafet", + "erensoy", + "arifcan", + "cavit", + "g\u00fcnkurt", + "\u00fclk\u00fcm", + "sunay", + "rabih", + "cercis", + "ortak", + "alpcan", + "yekbun", + "meni\u015fan", + "t\u00fcrkmen", + "nades", + "geleng\u00fcl", + "b\u00f6rte\u00e7in", + "baydu", + "bayman", + "amre", + "vildane", + "solma", + "h\u00fcmeyra", + "akar", + "nevgin", + "semrin", + "okbay", + "y\u00fccelen", + "baykan", + "atalay", + "akif", + "g\u00f6zem", + "neyran", + "\u00fcmmahan", + "hindal", + "ramadan", + "canan", + "andi\u00e7", + "tenvir", + "\u015fide", + "naz", + "alaaddin", + "hatem", + "g\u00fc\u00e7yeter", + "sadiye", + "hasbek", + "fersan", + "arcan", + "sedife", + "tezcan", + "alanalp", + "ad\u0131g\u00fcn", + "fatih", + "n\u00fcrice", + "hurican", + "bo\u011fatimur", + "\u00f6v\u00fcn", + "yal\u0131n", + "ayasun", + "\u00f6zalpsan", + "bekbay", + "\u00e7etinsu", + "\u00f6zbilge", + "ayg\u00f6nen\u00e7", + "bulun\u00e7", + "alt\u0131nkaya", + "s\u00f6kmen", + "remazan", + "bahittin", + "o\u011fuzman", + "lerze", + "beyzade", + "aysema" + ], + "LAST_NAME": [ + "\u015fensoy", + "\u00e7orlu", + "\u00f6calan", + "y\u0131ld\u0131r\u0131m", + "i\u0307hsano\u011flu", + "i\u0307n\u00f6n\u00fc", + "hayrio\u011flu", + "tarhan", + "\u015fener", + "han\u00e7er", + "g\u00fc\u00e7l\u00fc", + "bilir", + "alemdar", + "man\u00e7o", + "g\u00fclen", + "y\u0131lmaz", + "arslan", + "yaman", + "k\u0131sak\u00fcrek", + "durdu", + "g\u00fcl", + "\u00fclker", + "demirel", + "\u015fama", + "teveto\u011flu", + "\u015fafak", + "erta\u015f", + "erdo\u011fan", + "ak\u00e7a", + "\u00e7etin", + "dumanl\u0131", + "mans\u0131z", + "bilge", + "f\u0131rat", + "t\u00fcrk", + "bilgin", + "soylu", + "arsoy", + "durmu\u015f", + "duran", + "demir", + "sakarya", + "erg\u00fcl", + "ak\u00e7ay", + "korut\u00fcrk", + "aslan", + "y\u00fcksel", + "seven", + "akdeniz", + "yorulmaz", + "karadeniz", + "akar", + "zengin", + "sezgin", + "zorlu", + "akg\u00fcnd\u00fcz", + "\u00e7amurcuo\u011flu", + "sezer", + "aksu", + "eraslan" + ], + "OTHER_PRONOUN": [ + "it" + ], + "LAST_NAME_MALE": [], + "LAST_NAME_FEMALE": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "aktris": "oyuncu", + "bibi": "dede", + "teyze": "eni\u015fte", + "gelin": "seyis", + "i\u015f_kad\u0131n\u0131": "i\u015f_adam\u0131", + "civciv": "gaur", + "panik": "son", + "k\u0131z_evlat": "son", + "k\u0131z": "son", + "d\u00fc\u015fes": "d\u00fck", + "imparatori\u00e7e": "anax_imperator", + "torun": "erkek_torun", + "k\u0131z_torun": "torun", + "nine": "b\u00fcy\u00fckbaba", + "b\u00fcy\u00fckana": "dede", + "b\u00fcy\u00fckanne": "dede", + "her": "his", + "onun": "his", + "kahraman": "yi\u011fit", + "leydi": "erk", + "cik": "efendim", + "\u0131skalamak": "efendim", + "metres": "efendi", + "matrix": "peder", + "rahibe": "imam", + "soru": "birader", + "prenses": 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"homoseks\u00fcel", + "e\u015f_cinsel" + ], + "he": [ + "erkek", + "ki\u015fi", + "gaur", + "o\u011flan", + "little_boy", + "boy", + "garson" + ], + "she": [ + "m\u00f6", + "lezbiyen", + "gac\u0131", + "hatun", + "kar\u0131", + "cik", + "di\u015filer", + "abla", + "kad\u0131nlar", + "k\u0131z", + "kad\u0131n", + "di\u015fi", + "madam", + "leydi", + "c\u0131v\u0131r", + "\u0131skalamak" + ] + }, + "en_pronoun2pronoun": { + "he": [ + "he", + "sini", + "elli", + "onun", + "his" + ], + "she": [ + "onun", + "her" + ], + "they": [ + "onlar\u0131n", + "onlar", + "has", + "jale", + "onlar\u0131nki" + ], + "it": [ + "bt", + "bunlar", + "onlar", + "acele", + "esas", + "it", + "onun", + "ova" + ] + }, + "en_pronoun2title": {}, + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/tt.json b/data_tooling/pii_processing/ontology/data/tt.json new file mode 100644 index 0000000..6c2e5fd --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/tt.json @@ -0,0 +1,155 @@ +{ + "GPE": [ + "\u043a\u044b\u0437\u044b\u043b_\u0434\u0438\u04a3\u0433\u0435\u0437", + "curcevdan", + "\u0430\u043a_\u0439\u043e\u0440\u0442", + "\u043a\u0435\u0448\u0435_\u0445\u043e\u043a\u0443\u043a\u043b\u0430\u0440\u044b", + "\u0430\u043b\u043c\u0430\u043d_\u0438\u043c\u043f\u0435\u0440\u0438\u044f\u0441\u0435", + "\u043a\u044b\u0437\u044b\u043b_\u0445\u0430\u0447", + "\u0430\u0439\u044f_\u0441\u0443\u0444\u0438\u044f" + ], + "BIO_CHEM_ENTITY": [ + "polivinilxlorid", + "d_\u0432\u0438\u0442\u0430\u043c\u0438\u043d\u044b" + ], + "PUBLIC_FIGURE": [ + "federiko_fellini", + "\u0430\u043f\u043e\u0441\u0442\u043e\u043b_\u043f\u0435\u0442\u0440", + "\u043f\u0451\u0442\u0440_i", + "y", + "f", + "\u0445\u0440\u0438\u0441\u0442\u043e\u0444\u043e\u0440_\u043a\u043e\u043b\u0443\u043c\u0431", + "con_lennon", + "gustav_maler", + "frants_\u015fubert", + "le_korb\u00fczie", + "weber", + "nikola_tesla", + 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"\u0430\u043b\u0430\u0440" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/tw.json b/data_tooling/pii_processing/ontology/data/tw.json new file mode 100644 index 0000000..0a4a989 --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/tw.json @@ -0,0 +1,873 @@ +{ + "ner_regexes": [ + [ + "PERSON", + "\\D+ \\D+|\\D+ \\D+|\\D+ \\D+|\\D+ \\D+|\\D+ \\D+-\\D+|\\D+ \\D+|\\D+ \\D+|\\D+ \\D+|\\D+ \\D+|\\D+ \\D+-\\D+|\\D+ \\D+ \\D+|\\D+ \\D+ \\D+|\\D+ \\D+ \\D+|\\D+ \\D+ \\D+", + false, + [] + ] + ], + "FIRST_NAME_FEMALE": [ + "susan", + "nicola", + "stephanie", + "salomey", + "priscilla", + "hannah", + "gifty", + "natasha", + "janice", + "janet", + "ann", + "lorraine", + "millicent", + "rebecca", + "emily", + "akumaa", + "sylvia", + "afia", + "felicia", + "olivia", + "akos", + "esi", + "danielle", + "francesca", + "maria", + "rosemary", + "roselyn", + "lawrencia", + "ama", + "naomi", + "annette", + "marian", + "sandra", + "mandy", + "marilyn", + "yaa", + "georgia", + "jennifer", + "vida", + "victoria", + "amber", + "joyce", + "veronica", + "rachel", + "tracy", + "lisa", + "wendy", + "catherine", + "rachael", + "jill", + "akosua", + "awesi", + "shirley", + "julie", + "denise", + "eunice", + "dorcas", + "akua", + "maureen", + "angela", + "ruth", + "katy", + "lydia", + "barbara", + "charlotte", + "linda", + "helen", + "debra", + "jasmine", + "vanessa", + "ernestina", + "amelia", + "juliana", + "deborah", + "nana_ama", + "jessica", + "afua", + "josephine", + "michelle", + "julia", + "sarah", + "teresa", + "hannabel", + "caroline", + "lucy", + "rita", + "pamela", + "joanna", + "mary", + "sharon", + "adwoa", + "amanda", + "nimakoah", + "dorothy", + "georgina", + "irene", + "margaret", + "constance", + "emma", + "aba", + "judith", + "alice", + "harriet", + "katherine", + "regina", + "yvonne", + "abigail", + "comfort", + "dora", + "eliabeth", + "tina", + "sheila", + "karen", + "paula", + "baaba", + "patricia", + "kate", + "christina", + "samantha", + "elizabeth", + "natalie", + "beatrice", + "gemma", + "abena", + "grace" + ], + "FIRST_NAME_MALE": [ + "shaun", + "kenneth", + "roger", + "jacob", + "graham", + "raymond", + "justin", + "matthew", + "kweku", + "andrew", + "anthony", + "nigel", + "dennis", + "abeiku", + "benjamin", + "kojo", + "jonathan", + "josh", + "elliott", + "peter", + "terence", + "daniel", + "kujoe", + "kyle", + "carl", + "mathew", + "alexander", + "donald", + "jeffrey", + "fiifi", + "isaac", + "antony", + "leslie", + "alex", + "max", + "jason", + "nathan", + "henry", + "luke", + "john", + "oliver", + "vincent", + "kwamena", + "howard", + "stephen", + "joe", + "julian", + "joshua", + "kwabena", + "clifford", + "george", + "duncan", + "ekow", + "james", + "kwaku", + "douglas", + "denis", + "louis", + "colins", + "russell", + "lawrence", + "bernard", + "mark", + "jack", + "joseph", + "joel", + "malcolm", + "christian", + "kwadwo", + "jake", + "josiah", + "paul", + "marcus", + "tony", + "kevin", + "william", + "gerald", + "gordon", + "kwasi", + "martin", + "philip", + "edward", + "frederick", + "phillip", + "eric", + "steven", + "yaw", + "kofi", + "ronald", + "adam", + "simon", + "richard", + "stanley", + "samuel", + "adrian", + "david", + "derrick", + "akwesi", + "jeremy", + "arthur", + "akwasi", + "robert", + "thomas", + "harry", + "aaron", + "frank", + "nicholas", + "danny", + "dominic", + "sam", + "bruce", + "charles", + "kwame", + "francis", + "tom", + "albert", + "victor", + "michael", + "joojo", + "elliot", + "patrick", + "ben", + "kwesi", + "timothy", + "gregory", + "karl" + ], + "LAST_NAMES_FEMALE": [ + "Adu", + "Agyeiwaa", + "Asenso", + "Ak\u0254maa", + "Ampoma", + "Fosu", + "Akyeampong", + "Mensah", + "Akyer\u03b5ko", + "Tweneboa", + "Akyeampomaa", + "Asamoah", + "Gyasi", + "Amoanimaa", + "Ofori", + "Takyi", + "Boadi", + "Amoako", + "Wiafe", + "Tiwaa", + "Kwarteng", + "Adwubi", + "Ataa", + "Agyapong", + "Adomako", + "Akowua", + "Darko", + "Adoma", + "Omani", + "Okyere", + "Adusei", + "Kwaakye", + "Kyei", + "Agyei", + "Sarpong", + "Amo", + "Baah", + "Badu", + "Kusi", + "Tawia", + "Danso", + "Asiama", + "Boahen", + "Akoto", + "Safo", + "Agyapomaa", + "Boakye", + "Baawia", + "Fofie", + "Prempeh", + "Nyaako", + "Afirifa", + "Kwartemaa", + "Oppong", + "Amoakowaa", + "Ansa", + "Twumasi", + "Yeboa", + "Asamoa", + "Kyeiwaa", + "Asantewaa", + "Ansomah", + "Appiah", + "Quartey", + "Ampofo", + "Amponsa", + "Appia", + "Gyasiwaa", + "Kumi", + "Karikari", + "Adutwumwaa", + "Ansomaa", + "Nkansa", + "Dufie", + "Bonsu", + "Boatemaah", + "Serwaa", + "Pokuaa", + "Abrafi", + "Gyamfiaa", + "Ntiamoa", + "Antwi", + "Ankra", + "Asante", + "Otuo", + "Donkor", + "Ata", + "Gyamfi", + "Andorful", + "Akyer\u03b5", + "Acheampong", + "Owusuwaa", + "Kusiwaa", + "Obeng", + "Baa", + "Aboraa", + "Akyeamfu\u0254", + "Yawson", + "Ampofowaa", + "Nyame", + "Frema", + "Asieduwaa", + "Yirenkyi", + "Ahortor", + "Bona", + "Yaamoa", + "Ampadu", + "Asiedu", + "Asare", + "Amoa", + "Anokye", + "Bonsra", + "Akoaa", + "Nkrumah", + "Boatemaa", + "Owusu", + "Agyare", + "Nti", + "Nsia", + "Duah", + "Opuku", + "Awuah", + "Boaten", + "Pomaa", + "Afrakomaa", + "Fosua", + "Foriwaa", + "Ofosu", + "Frimpomaa", + "Boakyewaa", + "Akyena", + "Kyerewaa", + "Opoku", + "Agyemang", + "Otiwa", + "Koomson", + "Kwaakyewaa", + "Ntim", + "Mensa", + "Tutu", + "Mansa", + "Daakoaa", + "Antwiwaa", + "Boateng", + "Adutwum", + "Safoaa", + "Dwamena", + "Adomah", + "Amoasi", + "Baafi", + "Yeboah", + "Nyaakoaa", + "Boadu", + "Nyantakyi", + "Osei", + "Nkansah", + "Daako", + "Afoakwa", + "Anima", + "Oti", + "Akyaa" + ], + "PREFIX_FEMALE": [ + "osofo_maame", + "mama", + "maame", + "ms", + "mrs", + "dr", + "miss", + "sista", + "awura" + ], + "PREFIX_MALE": [ + "owura", + "mr", + "osofo", + "dr", + "agya" + ], + "FIRST_NAME": [ + "shaun", + "susan", + "kenneth", + "roger", + "jacob", + "graham", + "nicola", + "raymond", + "justin", + "matthew", + "stephanie", + "kweku", + "salomey", + "andrew", + "priscilla", + "hannah", + "anthony", + "gifty", + "nigel", + "natasha", + "janice", + "janet", + "dennis", + "ann", + "lorraine", + "millicent", + "abeiku", + "emily", + "rebecca", + "benjamin", + "akumaa", + "kojo", + "jonathan", + "josh", + "elliott", + "peter", + "sylvia", + "afia", + "terence", + "felicia", + "olivia", + "akos", + "esi", + "danielle", + "francesca", + "daniel", + "kujoe", + "maria", + "rosemary", + "roselyn", + "lawrencia", + "kyle", + "ama", + "carl", + "naomi", + "mathew", + "annette", + "marian", + "alexander", + "donald", + "jeffrey", + "sandra", + "fiifi", + "mandy", + "yaa", + "isaac", + "antony", + "marilyn", + "georgia", + "leslie", + "alex", + "max", + "jennifer", + "jason", + "vida", + "victoria", + "amber", + "joyce", + "veronica", + "nathan", + "henry", + "rachel", + "luke", + "tracy", + "john", + "oliver", + "vincent", + "lisa", + "wendy", + "catherine", + "rachael", + "kwamena", + "jill", + "howard", + "akosua", + "stephen", + "joe", + "julian", + "joshua", + "kwabena", + "clifford", + "george", + "duncan", + "ekow", + "awesi", + "shirley", + "james", + "kwaku", + "douglas", + "denis", + "louis", + "colins", + "julie", + "denise", + "eunice", + "dorcas", + "akua", + "maureen", + "russell", + "angela", + "ruth", + "katy", + "lydia", + "bernard", + "lawrence", + "mark", + "barbara", + "joseph", + "jack", + "joel", + "charlotte", + "linda", + "helen", + "debra", + "malcolm", + "christian", + "kwadwo", + "jasmine", + "jake", + "josiah", + "paul", + "vanessa", + "marcus", + "tony", + "kevin", + "ernestina", + "amelia", + "juliana", + "deborah", + "nana_ama", + "william", + "jessica", + "afua", + "josephine", + "gerald", + "gordon", + "kwasi", + "michelle", + "julia", + "martin", + "sarah", + "philip", + "edward", + "teresa", + "frederick", + "hannabel", + "caroline", + "lucy", + "phillip", + "rita", + "pamela", + "joanna", + "eric", + "steven", + "yaw", + "kofi", + "ronald", + "adam", + "mary", + "sharon", + "adwoa", + "amanda", + "simon", + "nimakoah", + "dorothy", + "georgina", + "richard", + "stanley", + "irene", + "samuel", + "margaret", + "constance", + "emma", + "adrian", + "aba", + "david", + "derrick", + "akwesi", + "judith", + "jeremy", + "alice", + "arthur", + "harriet", + "katherine", + "regina", + "akwasi", + "yvonne", + "abigail", + "comfort", + "dora", + "robert", + "thomas", + "eliabeth", + "tina", + "harry", + "aaron", + "sheila", + "frank", + "nicholas", + "danny", + "dominic", + "karen", + "paula", + "baaba", + "sam", + "bruce", + "patricia", + "charles", + "kate", + "christina", + "samantha", + "kwame", + "francis", + "elizabeth", + "tom", + "albert", + "victor", + "michael", + "natalie", + "beatrice", + "elliot", + "joojo", + "gemma", + "abena", + "patrick", + "ben", + "kwesi", + "grace", + "timothy", + "gregory", + "karl" + ], + "LAST_NAME": [ + "anima", + "twumasi", + "akyena", + "mensa", + "ampadu", + "ansomaa", + "ofosu", + "boadi", + "nyantakyi", + "amoasi", + "safo", + "frimpomaa", + "adusei", + "bonsu", + "afirifa", + "ntiamoa", + "ofori", + "ankra", + "appiah", + "safoaa", + "obeng", + "owusu", + "agyapong", + "kyeiwaa", + "osei", + "adomah", + "danso", + "boatemaa", + "ampofo", + "akyeampong", + "agyei", + "boakyewaa", + "boaten", + "bonsra", + "asiama", + "akyeampomaa", + "kusi", + "asamoa", + "nkansa", + "frema", + "boakye", + "asare", + "afrakomaa", + "okyere", + "fosu", + "akyer\u03b5ko", + "fosua", + "awuah", + "koomson", + "gyasi", + "tutu", + "darko", + "ansa", + "agyapomaa", + "gyasiwaa", + "kyei", + "akowua", + "aboraa", + "adu", + "yawson", + "tweneboa", + "asamoah", + "nyame", + "asieduwaa", + "nyaako", + "boateng", + "yirenkyi", + "adutwum", + "amoakowaa", + "serwaa", + "agyemang", + "appia", + "baah", + "fofie", + "baawia", + "oppong", + "andorful", + "akyeamfu\u0254", + "asiedu", + "anokye", + "asante", + "quartey", + "mensah", + "oti", + "baa", + "nkrumah", + "daakoaa", + "antwiwaa", + "kwaakye", + "owusuwaa", + "ampofowaa", + "kwarteng", + "ahortor", + "amponsah", + "nkansah", + "amo", + "afoakwa", + "adomako", + "baafi", + "ampoma", + "ntim", + "amoanimaa", + "bona", + "agyare", + "omani", + "pomaa", + "dufie", + "yaamoa", + "ak\u0254maa", + "nyaakoaa", + "opuku", + "asantewaa", + "donkor", + "akoaa", + "otuo", + "daako", + "kwaakyewaa", + "amoako", + "nti", + "dwamena", + "adwubi", + "asenso", + "prempeh", + "sarpong", + "boatemaah", + "boahen", + "amponsa", + "mansa", + "pokuaa", + "abrafi", + "adoma", + "boadu", + "gyamfi", + "ataa", + "akoto", + "akyer\u03b5", + "tawia", + "yeboah", + "ansomah", + "kwartemaa", + "takyi", + "amoa", + "gyamfiaa", + "otiwa", + "acheampong", + "agyeiwaa", + "nsia", + "yeboa", + "kusiwaa", + "duah", + "tiwaa", + "akyaa", + "kyerewaa", + "badu", + "foriwaa", + "kumi", + "wiafe", + "ata", + "karikari", + "adutwumwaa", + "opoku", + "antwi" + ], + "LAST_NAME_MALE": [], + "LAST_NAME_FEMALE": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": {}, + "other_gender_swap": {}, + "en_pronoun2gender": {}, + "en_pronoun2pronoun": {}, + "en_pronoun2title": {}, + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/twf.json b/data_tooling/pii_processing/ontology/data/twf.json new file mode 100644 index 0000000..dab74f3 --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/twf.json @@ -0,0 +1,49 @@ +{ + "LOCATION": [ + "h\u01eb\u0301lp\u2019\u020dno" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "p\u2019_\u00e0yu\u2019_\u00fana": "p\u00f2p\u00f3na", + "t\u00f9t\u00fana": "p\u00f2p\u00f3na", + "\u0142\u0209w\u00e9na": "s\u0259\u0301onena", + "\u0259\u0300wyu\u2019_\u00fana": "up\u0119\u0300yu\u2019_\u00fana" + }, + "other_gender_swap": {}, + "en_pronoun2gender": { + "he": [ + "\u0259\u0300wyu\u2019_\u00fana" + ], + "she": [ + "up\u0119\u0300yu\u2019_\u00fana", + "t\u00f9t\u00fana", + "kw\u0259\u0301lena", + "\u0142\u0209w\u00e9na" + ] + }, + "en_pronoun2pronoun": { + "he": [ + "\u0105\u0301w\u0105n\u0105" + ], + "she": [ + "\u0105\u0301w\u0105n\u0105" + ], + "they": [ + "\u0105\u0301w\u0105n\u0105" + ], + "it": [ + "\u0105\u0301w\u0105n\u0105" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/txb.json b/data_tooling/pii_processing/ontology/data/txb.json new file mode 100644 index 0000000..1f8ab40 --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/txb.json @@ -0,0 +1,30 @@ +{ + "RELIGION_MEMBER": [ + "procer" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "\u1e63er": "procer" + }, + "other_gender_swap": {}, + "en_pronoun2gender": { + "he": [ + "trai" + ], + "she": [ + "\u015bana" + ] + }, + "en_pronoun2pronoun": {}, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/ty.json b/data_tooling/pii_processing/ontology/data/ty.json new file mode 100644 index 0000000..34547bd --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/ty.json @@ -0,0 +1,49 @@ +{ + "PRODUCT": [ + "varua_maitai" + ], + "LOCATION": [ + "ia_ora_na_i_te_matahiti_api" + ], + "PERSON_PRONOUN": [ + "i" + ], + "PUBLIC_FIGURE": [ + "one", + "i", + "to_opiti" + ], + "GENDER": [ + "vahine" + ], + "ORG": [ + "te_ekalesia_a_iesu_mesia_i_te_feia_mo\u2018a_i_te_hau_mahana_hopea_nei" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": {}, + "other_gender_swap": {}, + "en_pronoun2gender": { + "he": [ + "fiu" + ], + "she": [ + "vahine" + ] + }, + "en_pronoun2pronoun": { + "they": [ + "one" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/tyv.json b/data_tooling/pii_processing/ontology/data/tyv.json new file mode 100644 index 0000000..8bb2c01 --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/tyv.json @@ -0,0 +1,63 @@ +{ + "JOB": [ + "\u044d\u0440\u0442\u0435\u043c\u0434\u0435\u043d", + "\u0431\u0435\u043b\u0435\u0442\u043a\u044d\u044d\u0440" + ], + "PERSON_PRONOUN": [ + "\u043e\u043b" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "\u0443\u0440\u0443\u0433": "\u043e\u043e\u043b", + "\u043a\u044b\u0441": "\u043e\u043e\u043b", + "\u0430\u0432\u0430": "\u0430\u0447\u0430", + "\u0430\u0432\u0430\u043c": "\u0430\u0434\u0430", + "\u0430\u0432\u0430\u0439": "\u0430\u0447\u0430", + "\u0430\u043d\u0430\u0439": "\u0430\u0434\u0430", + "\u0438\u0439\u0435": "\u0430\u0434\u0430", + "\u0443\u0433\u0431\u0430": "\u0434\u0443\u04a3\u043c\u0430", + "\u043e\u043e\u043b": "\u043a\u044b\u0441", + "\u043e\u043e\u043b_\u043e\u0433\u043b\u0443": "\u043a\u044b\u0441", + "\u0430\u0447\u0430": "\u043a\u044b\u0441" + }, + "other_gender_swap": { + "\u043e\u043b\u0430\u0440": "\u043e\u043b", + "\u043e\u043b": "\u043e\u043b\u0430\u0440" + }, + "en_pronoun2gender": { + "he": [ + "\u0430\u0447\u0430", + "\u043e\u043e\u043b", + "\u043e\u043e\u043b_\u043e\u0433\u043b\u0443" + ], + "she": [ + "\u0443\u0440\u0443\u0433", + "\u043a\u044b\u0441", + "\u043a\u0430\u0434\u0430\u0439", + 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of file diff --git a/data_tooling/pii_processing/ontology/data/uga.json b/data_tooling/pii_processing/ontology/data/uga.json new file mode 100644 index 0000000..a40bcab --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/uga.json @@ -0,0 +1,24 @@ +{ + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "\ud800\udf80\ud800\udf83\ud800\udf9a": "\ud800\udf80\ud800\udf83" + }, + "other_gender_swap": {}, + "en_pronoun2gender": {}, + "en_pronoun2pronoun": { + "she": [ + "\ud800\udf85\ud800\udf8a" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/uk.json b/data_tooling/pii_processing/ontology/data/uk.json new file mode 100644 index 0000000..a71153b --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/uk.json @@ -0,0 +1,1529 @@ +{ + "ANIMAL": [ + "\u0432\u043e\u043b\u043e\u0432\u043e\u043e\u0447\u043a\u043e\u0432\u0456", + "\u0441\u043e\u0431\u043e\u043b\u044c", + "\u043c\u0430\u043d\u0434\u0430\u0440\u0438\u043d\u043a\u0430", + "desmodontinae", + "\u043f\u0456\u0442\u0435\u043a\u0430\u043d\u0442\u0440\u043e\u043f", + "\u0433\u043e\u043b\u043e\u0432\u0435\u043d\u044c_\u0454\u0432\u0440\u043e\u043f\u0435\u0439\u0441\u044c\u043a\u0438\u0439", + "\u043f\u043e\u043f\u0435\u043b\u044e\u0445", + "\u0431\u0443\u0444\u0430\u043b\u043e_\u0447\u043e\u0440\u043d\u0438\u0439", + "\u0442\u0435\u043b\u0435\u0434\u0443", + "\u043a\u0430\u0448\u0430\u043b\u043e\u0442", + "\u043a\u0430\u0432\u0456\u044f_\u0441\u0432\u0456\u0439\u0441\u044c\u043a\u0430", + "\u0430\u0440\u0445\u0456\u0442\u0435\u0443\u0442\u0438\u0441", + "\u0432\u0456\u0440\u0443\u0441_\u0442\u044e\u0442\u044e\u043d\u043e\u0432\u043e\u0457_\u043c\u043e\u0437\u0430\u0457\u043a\u0438", + "\u0433\u043e\u0440\u0431\u0430\u0447", + "\u0430\u0440\u0442\u0435\u043c\u0456\u044f", + "lactobacillus_acidophilus", + "\u043c\u0443\u0445\u043e\u043b\u043e\u0432\u043a\u043e\u0432\u0456", + "gerbillus_jamesi", + "\u0441\u043e\u043d\u0446\u0435\u0432\u0438\u043a", + "\u0433\u043e\u043b\u043a\u043e\u0448\u0435\u0440\u0441\u0442\u043e\u0432\u0456", + "\u043a\u0432\u0430\u043a\u0432\u0430", + "megascops", + "\u043a\u0438\u0442\u043e\u0432\u0438\u0434\u0456", + "\u043f\u0435\u0440\u0435\u043f\u0435\u043b\u044f\u0442\u043d\u0438\u043a", + "\u043f\u0430\u0434\u0430\u043b\u044c\u043d\u0438\u043a", + "\u043c\u043e\u0440\u044f\u043d\u043a\u0430", + "\u043b\u0430\u0441\u0442\u0456\u0432\u043a\u0430_\u0441\u0456\u043b\u044c\u0441\u044c\u043a\u0430", + "\u043a\u043e\u0440\u043e\u043f_\u0437\u0432\u0438\u0447\u0430\u0439\u043d\u0438\u0439", + "\u0432\u043e\u0434\u043e\u043c\u043e\u0440\u043e\u0437", + "\u0430\u0439_\u0430\u0439", + "\u0437\u0435\u043c\u043b\u0435\u0434\u0443\u0445" + ], + "ORG": [ + "\u0432\u0456\u0439\u0441\u044c\u043a\u043e", + "\u0431\u0430\u0441\u043a\u043e\u043d\u0456\u044f", + "tom_thumb", + "\u0441\u0456\u043b\u044c\u0441\u044c\u043a\u0435_\u0433\u043e\u0441\u043f\u043e\u0434\u0430\u0440\u0441\u0442\u0432\u043e", + "\u043f\u0440\u043e\u0441\u0432\u0456\u0442\u043d\u0438\u0446\u0442\u0432\u043e", + "\u0442\u043e\u0440\u0433\u043e\u0432\u0438\u0439_\u0446\u0435\u043d\u0442\u0440", + "\u043a\u0430\u043d\u0442\u0445\u043e", + "\u043c\u043e\u043b\u043e\u0434\u0438\u0439_\u043c\u0456\u0441\u044f\u0446\u044c", + "\u0434\u0435\u043c\u043e\u043a\u0440\u0430\u0442\u0438\u0447\u043d\u0430_\u043f\u0430\u0440\u0442\u0456\u044f", + "\u043c\u043e\u0434\u0435\u0440\u043d", + "\u044f_\u0442\u0435\u0431\u0435_\u043a\u043e\u0445\u0430\u044e", + "the_who", + "\u0440\u0438\u043c\u043e_\u043a\u0430\u0442\u043e\u043b\u0438\u0446\u044c\u043a\u0430_\u0446\u0435\u0440\u043a\u0432\u0430", + 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"\u0491\u043e\u043c\u0456\u043d\u044c\u0434\u0430\u043d", + "\u043d\u0430\u0446\u0456\u043e\u043d\u0430\u043b\u044c\u043d\u0430_\u0430\u0441\u0430\u043c\u0431\u043b\u0435\u044f_\u0444\u0440\u0430\u043d\u0446\u0456\u0457", + "\u043d\u0456\u0432", + "\u0432\u0456\u043a\u043a\u0430", + "\u043f\u0430\u0440\u0442\u0456\u044f", + "\u0431\u043e\u0442\u0430\u043d\u0456\u0447\u043d\u0438\u0439_\u0441\u0430\u0434", + "\u0432\u0430\u0439\u0448\u043d\u0430\u0432\u0456\u0437\u043c", + "\u0445\u0443\u0430\u043d\u0445\u0435", + "\u0434\u043e_\u0440\u0435\u0447\u0456", + "\u0436\u0443\u0432\u0430\u043b\u044c\u043d\u0430_\u0433\u0443\u043c\u043a\u0430", + "\u0441\u0438\u043d\u0442\u043e", + "\u043c\u0430\u043b\u043e\u043f\u043e\u043b\u044c\u0449\u0430", + "\u0434\u0435\u043c\u043e\u043a\u0440\u0430\u0442\u0438\u0447\u043d\u043e_\u0440\u0435\u0441\u043f\u0443\u0431\u043b\u0456\u043a\u0430\u043d\u0441\u044c\u043a\u0430_\u043f\u0430\u0440\u0442\u0456\u044f", + 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"\u043b\u0456\u0441\u043e\u0432\u0435_\u043e\u0437\u0435\u0440\u043e", + "\u0441\u0438\u043d\u0442\u043e\u0456\u0437\u043c", + "\u043b\u0456\u0431\u0435\u0440\u0430\u043b\u044c\u043d\u0430_\u043f\u0430\u0440\u0442\u0456\u044f", + "\u0437\u0430\u043a\u043e\u0440\u0434\u043e\u043d", + "\u0430\u043b\u044c_\u0434\u0436\u0430\u0437\u0456\u0440\u0430", + "\u0434\u0435\u043c\u043e\u043a\u0440\u0430\u0442\u0438\u0447\u043d\u0430_\u043f\u0430\u0440\u0442\u0456\u044f_\u0441\u0448\u0430" + ], + "DATE": [ + "\u0441\u0435\u0440\u0435\u0434\u043d\u044c\u043e\u0432\u0456\u0447\u0447\u044f", + "\u043d\u043e\u0432\u0438\u0439_\u043c\u0456\u0441\u044f\u0446\u044c", + "\u0441\u0442\u0430\u0440\u0456\u0441\u0442\u044c", + "happy_hour", + "\u043d\u0430\u0440\u043e\u0434\u0436\u0443\u0432\u0430\u043d\u0456\u0441\u0442\u044c", + "\u043f\u0435\u0440\u0435\u0434\u0443\u0441\u0456\u043c", + "the_golden_years", + "\u043e\u043d_\u0442\u0430\u043c", + "\u0432\u043e\u0437\u043d\u0435\u0441\u0456\u043d\u043d\u044f_\u0434\u0456\u0432\u0438_\u043c\u0430\u0440\u0456\u0457", + "\u043c\u043e\u043b\u043e\u0434\u0438\u043a", + "\u0434\u0432\u0430\u043d\u0430\u0434\u0446\u044f\u0442\u0430_\u043d\u0456\u0447_\u0430\u0431\u043e_\u044f\u043a_\u0432\u0430\u043c_\u0437\u0430\u0432\u0433\u043e\u0434\u043d\u043e" + ], + "GPE": [ + "\u0434\u0430\u0440_\u0435\u0441_\u0441\u0430\u043b\u0430\u043c", + "\u0441\u0432\u044f\u0442\u0438\u0439_\u0445\u0440\u0438\u0441\u0442\u043e\u0444\u043e\u0440", + "\u0441\u0432\u044f\u0442\u0438\u0439_\u043c\u0438\u043a\u043e\u043b\u0430\u0439", + "\u043c\u0438\u043a\u043e\u043b\u0430_\u0447\u0443\u0434\u043e\u0442\u0432\u043e\u0440\u0435\u0446\u044c", + "\u0441\u0432\u044f\u0442\u0438\u0439_\u044e\u0440\u0456\u0439", + "\u0431\u0456\u043b\u0438\u0439_\u0434\u0456\u043c", + "\u043d\u0456\u043c\u0435\u0446\u044c\u043a\u0430_\u0456\u043c\u043f\u0435\u0440\u0456\u044f", + "\u0442\u0430\u0439\u0448\u0430\u043d\u044c", + "\u0435\u0448_\u0441\u044e\u0440_\u0430\u043b\u044c\u0437\u0435\u0442\u0442", + "\u0441\u0430\u043d_\u0442\u043e\u043c\u0435", + "\u0441\u0435\u043d\u0442_\u043b\u0443\u0457\u0441", + "\u0441\u0432\u044f\u0442\u0438\u0439_\u0434\u0443\u0445" + ], + "JOB": [ + "\u043a\u043e\u0440\u0430\u0431\u0435\u043b", + "guru", + "\u0441\u0430\u043c\u043e\u0441\u0442\u0456\u0439\u043d\u0438\u0439", + "\u043d\u0430_\u0432\u0435\u0441\u0456\u043b\u043b\u0456", + "\u043f\u043e\u043b\u0456\u0446i\u044f", + "\u0437\u0430\u0440\u044f\u0434\u0436\u0430\u044e\u0447\u0438\u0439", + "\u0432\u0430\u043d\u0442\u0430\u0436\u043d\u0438\u043a", + "\u0432\u043e\u0440\u043e\u0442\u0430\u0440", + "make", + "\u043a\u0456\u043d\u043e\u0440\u0435\u0436\u0438\u0441\u0435\u0440", + "the_police", + "\u0431\u043b\u043e\u043a\u0444\u043b\u0435\u0439\u0442\u0430", + "\u0434\u0440\u0443\u0433\u0438\u0439", + "\u043b\u0438\u0441\u0442\u043e\u043d\u043e\u0448\u0430", + "\u0433\u0430\u0441\u0442\u0430\u0440\u0431\u0430\u0439\u0442\u0435\u0440", + "\u043a\u0443\u0440\u0430\u0442\u043e\u0440", + "\u043f\u0440\u043e\u0444\u0435\u0441\u043e\u0440", + "\u043a\u043e\u0441\u0442\u044e\u043c\u0435\u0440", + "\u043f\u0430\u0440\u0430\u043b\u0435\u0433\u0430\u043b", + "mate", + "\u0430\u043a\u0430\u0434\u0435\u043c\u0456\u043a", + "\u0444\u043e\u0442\u043e\u0433\u0440\u0430\u0444", + "\u043f\u043e\u043b\u0456\u0446\u0456\u044f", + "the_economist", + "warrior", + "\u043c\u043b\u0438\u043d\u0430\u0440", + "man", + "doc", + "\u0456\u043d\u0434\u0435\u043f\u0435\u043d\u0434\u0435\u043d\u0442", + "messenger", + "\u043a\u043e\u0441\u0430\u0440\u0438\u043a", + "\u043f\u043e\u043b\u0456\u0446\u0435\u0439\u0441\u044c\u043a\u0438\u0439", + "\u0431\u0430\u0440\u0438\u0441\u0442\u0430", + "\u043f\u043e\u043b\u0456\u0446\u0456\u044f\u043d\u0442", + "\u043c\u0435\u043b\u044c\u043d\u0438\u043a", + "\u0430\u043d\u0435\u0441\u0442\u0435\u0437\u0456\u043e\u043b\u043e\u0433", + "\u043f\u0440\u0435\u0437\u0438\u0434\u0435\u043d\u0442", + "esquire", + "\u043a\u0435\u0440\u043c\u0430\u043d\u0438\u0447" + ], + "LANGUAGE": [ + "\u043f\u0430\u043b\u0456", + "\u043f\u043e\u0440\u0442\u0443\u0433\u0430\u043b\u044c\u0441\u044c\u043a\u0438\u0439", + "\u044f\u043f\u043e\u043d\u0441\u044c\u043a\u0438\u0439", + "\u0431\u0456\u043b\u043e\u0440\u0443\u0441\u044c\u043a\u0438\u0439", + "\u0456\u0441\u043b\u0430\u043d\u0434\u0441\u044c\u043a\u0438\u0439" + ], + "PUBLIC_FIGURE": [ + "sibelius", + "c", + "\u043a\u0430\u0440\u0442\u0435\u0440", + "b", + "\u0432\u043e\u0432\u0447\u043e\u043a_\u0441\u0456\u0440\u0438\u0439", + "\u0431\u043e\u043b\u044c\u0446\u0430\u043d\u043e", + "j", + "y", + "holden", + "f", + "\u0445\u0440\u0438\u0441\u0442\u043e\u0444\u043e\u0440_\u043a\u043e\u043b\u0443\u043c\u0431", + "\u043e_\u0433\u0435\u043d\u0440\u0456", + "q", + "hal", + "a_e", + "\u0433\u0430\u043d\u0434\u0456", + "\u043c\u0443\u043d\u0433\u043e_\u043f\u0430\u0440\u043a", + "lewis", + "\u0432\u043e\u043b\u043e\u0432\u043e\u043e\u0447\u043a\u043e\u0432\u0456", + "\u0441\u0432\u044f\u0442\u0438\u0439_\u0433\u0435\u043e\u0440\u0433\u0456\u0439", + "macaca_nemestrina", + "m", + "\u043c\u0456\u0440\u043e\u0448\u043d\u0438\u043a", + "o", + "i", + "\u0432\u0456\u043b\u044c\u044f\u043c\u0441", + "1", + "\u0434\u0432\u0430", + "g", + "\u0441\u0430\u0436\u043e\u0442\u0440\u0443\u0441", + "r", + "\u0431\u0440\u0438\u0433\u0430\u0434\u043d\u0438\u0439_\u0433\u0435\u043d\u0435\u0440\u0430\u043b", + "\u043f\u0456\u0442_\u043c\u043e\u043d\u0434\u0440\u0456\u0430\u043d", + "\u0441\u043c\u0456\u0442", + "d", + "\u043f\u0435\u0442\u0440\u043e_i_\u043e\u043b\u0435\u043a\u0441\u0456\u0439\u043e\u0432\u0438\u0447", + "\u0441\u0435\u0440\u043f\u043e\u043a\u0440\u0438\u043b\u044c\u0446\u0435\u0432\u0456", + "\u0442\u0435\u0442\u0447\u0435\u0440", + "\u0430\u0440\u043d\u043e\u043b\u044c\u0434_\u0448\u0435\u043d\u0431\u0435\u0440\u0491", + 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"\u0440\u0438\u043c\u0441\u044c\u043a\u0435_\u043f\u0440\u0430\u0432\u043e" + ], + "POLITICAL_PARTY": [ + "\u043d\u043e\u0440\u0432\u0435\u0437\u044c\u043a\u0430_\u0440\u043e\u0431\u0456\u0442\u043d\u0438\u0447\u0430_\u043f\u0430\u0440\u0442\u0456\u044f", + "\u043d\u0430\u0440\u043e\u0434\u043d\u0430_\u043f\u0430\u0440\u0442\u0456\u044f", + "\u0441\u043e\u0446\u0456\u0430\u043b_\u0434\u0435\u043c\u043e\u043a\u0440\u0430\u0442\u0438\u0447\u043d\u0430_\u043f\u0430\u0440\u0442\u0456\u044f", + "\u043f\u0430\u0440\u0442\u0456\u044f_\u0432\u0456\u0433\u0456\u0432", + "\u043d\u0430\u0446\u0456\u043e\u043d\u0430\u043b_\u0441\u043e\u0446\u0456\u0430\u043b\u0456\u0441\u0442\u0438\u0447\u043d\u0430_\u0440\u043e\u0431\u0456\u0442\u043d\u0438\u0447\u0430_\u043f\u0430\u0440\u0442\u0456\u044f_\u043d\u0456\u043c\u0435\u0447\u0447\u0438\u043d\u0438", + "\u043f\u0430\u0440\u0442\u0456\u044f_\u0437\u0435\u043b\u0435\u043d\u0438\u0445", + 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"castagner", + "olivaro" + ], + "DISEASE": [ + "starnudar", + "sangiot", + "pesse", + "mouse", + "morsegar", + "rebego\u0142o", + "pelagra", + "sangiut", + "ruxiol", + "sangioto", + "gratoxa", + "toser", + "orbego\u0142o", + "mi", + "sangiuto", + "tosir" + ], + "JOB": [ + "medego", + "idrau\u0142ico", + "forner", + "siensiato", + "miedego", + "sciavo", + "tisler", + "ingegnere", + "artexan", + "arador", + "boschier", + "marangon", + "pent\u00f3r", + "prefeto", + "broxa", + "carpenter", + "boaro", + "caor\u00e8ro", + "pastor", + "barbier", + "man", + "trevere", + "buschier", + "pit\u00f3r" + ], + "LOCATION": [ + "mar_n\u00e9ro", + "mar_del_nord", + "sassonia_anhalt", + "mar_negro", + "sri_lanka", + "mar_tiren", + "stati_unii_de_\u0142a_m\u00e8rica", + "maria_mada\u0142ena", + "santa_maria_mada\u0142ena", + "fiume_xa\u0142o", + "santa_lena" + ], + "ANIMAL": [ + "gravar\u00f3n", + "bissa", + "brespa", + "lenze", + "fista", + "schirato", + "avoltogio", + "homo_sapiens", + "osela\u017e", + "corn\u00e0cia", + "colonp", + "petare\u0142o", + "crossnobel", + "schirat", + "caori\u00f3l", + "cocal", + "voltor", + "garde\u0142\u00ecn", + "cava\u019aar\u00f3n", + "sengia\u0142e" + ], + "FOOD": [ + "fritata", + "fortaja", + "zenz\u00ecva" + ], + "ORG": [ + "guerno", + "san_francisco", + "un", + "partito_republic\u00e0n", + "academia_mi\u0142itar", + "goerno", + "masoneria", + "ciunga", + "po", + "mar_roso", + "los_angeles", + "nato", + "mi", + "scola", + "s\u00e3o_tom\u00e9" + ], + "PERSON": [ + "al_gore", + "san_francesco_de_sisa" + ], + "GPE": [ + "san_zorzi", + "dar_es_salaam", + "san_piero", + "san_nico\u0142a_de_bari", + "san_crist\u00f2fo\u019ao", + "s\u00e3o_tom\u00e9", + "franca_contea", + "piaza", + "mar_roso", + "san_\u0142orenso" + ], + "RELIGION_MEMBER": [ + "fradel", + "cristcian", + "fradelo", + "crestian" + ], + "LANGUAGE": [ + "olandexe", + "arbanexe", + "fransexe", + "german", + "portoghexe", + "esperanto", + "ido" + ], + "QUANTITY": [ + "ton" + ], + "PRODUCT": [ + "union_sovietica", + "prima_guera_mondia\u0142e", + "mario_andretti" + ], + "DATE": [ + "medioevo", + "asunsion_de_maria" + ], + "RELIGION": [ + "islam" + ], + "FAC": [ + "\u0142e_quatro_stazon", + "cexa_cat\u00f2\u0142ica" + ], + "RACE": [ + "american", + "negro" + ], + "GENDER": [ + "man" + ], + "POLITICAL_PARTY": [ + "partito_democratego", + "partito_pu\u0142itego" + ], + "PERSON_PRONOUN": [ + "nualtri" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "e\u0142a": "e\u0142o", + "sorela": "fradel", + "sore\u0142a": "fradel", + "suster": "german", + "v\u00e9doa": "v\u00e9doo", + "mojer": "cristian", + "mojere": "cristian", + "f\u00e9mena": "man", + "siora": "man" + }, + "other_gender_swap": { + "\u0142ore": "e\u0142a", + "\u0142uri": "e\u0142a", + "\u0142ori": "e\u0142a", + "e\u0142o": "\u0142ore", + "\u00f2n": "\u0142uri", + "e\u0142a": "\u0142ore" + }, + "en_pronoun2gender": { + "he": [ + "toxo", + "toxeto", + "t\u00f3xo", + "man", + "but\u00e8l", + "toxat", + "pria", + "mas_cio", + "b\u00f2cia" + ], + "she": [ + "f\u00e9mena", + "siora" + ] + }, + "en_pronoun2pronoun": { + "he": [ + "\u00f2n", + "e\u0142o" + ], + "she": [ + "e\u0142a" + ], + "they": [ + "\u0142ore", + "\u0142uri", + "\u0142ori" + ], + "it": [ + "cuesto", + "tento" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/vep.json b/data_tooling/pii_processing/ontology/data/vep.json new file mode 100644 index 0000000..95e4d92 --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/vep.json @@ -0,0 +1,51 @@ +{ + "FOOD": [ + "munari\u010d" + ], + "JOB": [ + "maid", + "kunigaz" + ], + "ANIMAL": [ + "vari\u0161" + ], + "GENDER": [ + "maid" + ], + "DISEASE": [ + "s\u00e4dai", + "mi" + ], + "PUBLIC_FIGURE": [ + "bethoven", + "putin" + ], + "ORG": [ + "mi" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": {}, + "other_gender_swap": {}, + "en_pronoun2gender": { + "she": [ + "naine", + "maid" + ] + }, + "en_pronoun2pronoun": { + "they": [ + "h\u00f6" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/vi.json b/data_tooling/pii_processing/ontology/data/vi.json new file mode 100644 index 0000000..d85ca10 --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/vi.json @@ -0,0 +1,1377 @@ +{ + "PLANT": [ + "acer_negundo", + "cucurbita_ficifolia", + "hibiscus_syriacus", + "acanthocereus_tetragonus", + "brachychiton_populneus", + "glaucium_flavum", + "senecio_vulgaris", + "robinia_hispida", + "lilium_martagon", + "lupinus_luteus", + "pyracantha", + "n\u1ea5m_th\u00f4ng", + "campanula_persicifolia", + "diospyros_virginiana", + "verbascum_thapsus", + "lycium_barbarum", + "carduus_crispus", + "mai_\u0111\u1ecba_th\u1ea3o", + "salvia_leucophylla", + "chi_t\u1ed1ng_qu\u00e1n_s\u1ee7", + "iris_germanica", + "lilium_philadelphicum", + "sorghum_halepense", + "rubus_saxatilis", + "veronica_beccabunga", + "liriodendron_tulipifera", + "quercus_coccinea", + "melissa", + "triglochin_maritima", + "geranium_molle", + "erythronium_albidum", + "viola_arvensis", + "scutellaria_galericulata", + "viola_reichenbachiana", + "chimaphila_umbellata", + "the_joshua_tree", + "philadelphus_coronarius", + "aralia_elata", + "brassica_nigra", + "bromus_tectorum", + "helleborus_niger", + "lathyrus_latifolius", + "scorzonera_hispanica", + "monarda_citriodora", + "anthriscus_cerefolium", + "eupatorium_perfoliatum", + "campanula_medium", + "caryota_urens", + "quercus_kelloggii", + "juncus_articulatus", + "eryngium_maritimum", + "schefflera_actinophylla", + "amelanchier_bartramiana", + "salix_babylonica", + "chi_phong", + "cyclamen_purpurascens", + "anthyllis_vulneraria", + "abies_grandis", + "lathyrus_odoratus", + "sen_h\u1ed3ng", + "amanita", + "arabidopsis_thaliana", + "arundo", + "monarda", + "chi_ch\u00e2n_b\u00ea", + "sorbus_torminalis", + "magnolia_grandiflora", + "berteroa_incana", + "pelargonium_odoratissimum", + "colutea_arborescens", + "liparis_loeselii", + "papaver_alpinum", + "hydrangea_petiolaris", + "bidens_tripartita", + "sinapis", + "prunus_laurocerasus", + "pennisetum_glaucum", + "passiflora_ligularis", + "salix_triandra", + "silene_virginica", + "lilium_michiganense", + "cercidiphyllum_japonicum", + "atriplex_hortensis", + "vaccinium_corymbosum", + "teucrium_scorodonia", + "acer_campestre", + "ca_r\u1ed1t", + "laurocerasus_caroliniana", + "carex_pseudocyperus", + "bunya", + "su_l\u01a1", + "mercurialis_perennis", + "matthiola_incana", + "actinidia_chinensis", + "saxifraga_granulata", + "valerianella_locusta", + "rhus_typhina", + "nymphaea_alba", + "silene_dioica", + "sa_l\u00ea", + "phaseolus_coccineus", + "diplotaxis_tenuifolia", + "euphorbia_dentata", + "pulicaria_dysenterica", + "malope_trifida", + "amaryllis_belladonna", + "veronica_officinalis", + "phegopteris_connectilis", + "illicium_floridanum", + "pontederia_cordata", + "aconitum_lycoctonum", + "anthemis_arvensis", + "kim_ng\u00e2n_nh\u1eadt", + "acer_macrophyllum", + "asclepias_purpurascens", + "capsicum_baccatum", + "kim_t\u01b0\u1edbc", + "agrimonia_eupatoria", + "larix_occidentalis", + "plantago_lanceolata", + "polystichum_lonchitis", + "ononis_spinosa", + "andropogon_virginicus", + "thlaspi_arvense", + "agrostemma_githago", + "geranium_pratense", + "chi_h\u01b0\u1edbng_d\u01b0\u01a1ng", + "chi_kim_ng\u00e2n", + "salix_viminalis", + "juniperus_virginiana", + "eriophorum_angustifolium", + "veronica_serpyllifolia", + "eucalyptus_globulus", + "pterospermum_acerifolium", + "passiflora_incarnata", + "festuca_ovina", + "quercus_ellipsoidalis", + "bromus_arvensis", + "polygala_vulgaris", + "chi_m\u1ed9c_lan", + "veronica_peregrina", + "chaenomeles_speciosa", + "selenicereus_grandiflorus", + "pelargonium_peltatum", + "barbarea_vulgaris", + "annona_cherimola", + "helleborus_orientalis", + "gossypium_hirsutum", + "castanea_dentata", + "nymphaea_odorata", + "petasites_hybridus", + "urtica", + "potamogeton_crispus", + "parthenocissus_tricuspidata", + "artemisia_cana", + "paspalum_distichum", + "tropaeolum_minus", + "kim_t\u01b0\u1edbc_chi", + "chi_b\u00f4ng_tai", + "ageratum_mexicanum", + "cucurbita_argyrosperma", + "salix_fragilis", + "amanita_muscaria", + "corylus_americana", + "leonurus_cardiaca", + "spergula_arvensis", + "physostegia_virginiana", + "asplenium_trichomanes", + "acer_japonicum", + "arrhenatherum_elatius", + "nicotiana_alata", + "dracocephalum", + "carissa_macrocarpa", + "populus_balsamifera", + "chi_sau_sau", + "myosotis_sylvatica", + "asclepias_verticillata", + "astragalus_alpinus", + "quercus_variabilis", + "ulmus_americana", + "carex_arenaria", + "erigeron_annuus", + "acanthus_mollis", + "stellaria_media", + "calochortus_amabilis", + "abies_lasiocarpa", + "campanula_rapunculus", + "cystopteris_montana", + "diplotaxis_muralis", + "geranium_robertianum", + "anthemis_tinctoria", + "parthenium_argentatum", + "hedysarum_coronarium", + "hippocrepis_comosa", + "verbena_officinalis", + "dendrocalamus_giganteus", + "cam_bergamot", + "phytophthora_infestans", + "centaurea_americana", + "muscicapa_striata", + "prosopis_juliflora", + "cotoneaster_horizontalis", + "gossypium_barbadense", + "schinus_terebinthifolia", + "euphorbia_cyparissias", + "salvia_pratensis", + "centaurea_cyanus", + "chi_c\u1ecf_thi", + "gymnadenia_conopsea", + "eugenia_uniflora", + "blackberry", + "cortaderia_selloana", + "gentianella_amarella", + "ballota_nigra", + "campanula_carpatica", + "sisymbrium_officinale", + "chi_m\u1eadn_m\u01a1", + "angelica_archangelica", + "campsis_radicans", + "cirsium_vulgare", + "echinocactus_grusonii", + "medinilla_magnifica", + "corypha_umbraculifera", + "brachychiton_acerifolius", + "caragana_arborescens", + "mai_t\u1ee9_qu\u00fd", + "acer_pseudoplatanus", + "aristolochia_macrophylla", + "lotus_corniculatus", + "gymnadenia_odoratissima", + "bo_bo", + "hydrangea_arborescens", + "chi_th\u00f4ng", + "polyporus_squamosus", + "raphanus_raphanistrum", + "cornus_florida", + "cytisus_multiflorus", + "silene_latifolia", + "gymnocladus_dioica", + "saxifraga_stellaris", + "botrychium_lunaria", + "anagallis_tenella", + "tetragonia_tetragonioides", + "scleranthus_annuus", + "acrocarpus_fraxinifolius", + "salix_pentandra", + "cerastium_tomentosum", + "crataegus_laevigata", + "sinapis_arvensis", + "silene_uniflora", + "dracunculus_vulgaris", + "acacia_melanoxylon", + "agrostis_canina", + "saccharomyces_cerevisiae", + "hypochoeris_radicata", + "hydrangea_paniculata", + "campanula_trachelium", + "ranunculus_bulbosus", + "chi_d\u00e2m_b\u1ee5t", + "chi_long_nha_th\u1ea3o", + "erythronium_americanum", + "arenaria_serpyllifolia", + "lysimachia_vulgaris", + "campanula_rotundifolia", + "cam_chua", + "chi_cau", + "chi_li\u1ec5u", + "campanula_glomerata", + "lonicera_tatarica", + "actinidia_deliciosa", + "dalbergia_latifolia", + "polystichum_aculeatum", + "gaultheria_procumbens", + "anemone_pulsatilla", + "cerastium_alpinum", + "pseudotsuga_menziesii", + "tanacetum_parthenium", + "senna_alexandrina", + "heracleum_sphondylium", + "crataegus_aestivalis", + "chi_c\u00e0", + "lathyrus_sylvestris", + "chi_d\u1ebb_tr\u00f9ng_kh\u00e1nh", + "rosa_moschata", + "viola_tricolor", + "so_\u0111\u0169a", + "gentiana_acaulis", + "c\u00e2y_gi\u00e1ng_sinh", + "salvia_farinacea", + "elaeis_guineensis", + "calla", + "erythronium_montanum", + "galium_verum", + "acronicta_aceris", + "aralia_stipulata", + "cycas_circinalis", + "populus_nigra", + "mentha_longifolia", + "nasturtium", + "artemisia_filifolia", + "ranunculus_repens", + "stellaria_holostea", + "agathis_australis", + "lemna_minor", + "larix_laricina", + "pyrola_rotundifolia", + "colocasia_esculenta", + "erica_herbacea", + "inga_edulis", + "spiranthes_spiralis", + "cardamine_pratensis", + "salix_arctica", + "conyza_canadensis", + "amaranthus_hypochondriacus", + "alnus_glutinosa", + "cypripedium_montanum", + "erodium_texanum", + "arctium_minus", + "arrhenatherum", + "pinus_muricata", + "paris_quadrifolia", + "reseda_odorata", + "lathyrus_sativus", + "veronica_arvensis", + "anthriscus_sylvestris", + "pteridium_aquilinum", + "cinnamomum_cassia", + "panicum_capillare", + "smilax_aspera", + "salvia_sclarea", + "aristolochia_clematitis", + "cephalanthera_rubra", + "cypripedium_calceolus", + "viola_odorata", + "poa_nemoralis", + "corylus_cornuta", + "amaranthus_albus", + "lotus_tetragonolobus", + "arctostaphylos_uva_ursi", + "hieracium_aurantiacum", + "chrysanthemum", + "cerasus_vulgaris", + "myrica_gale", + "vallisneria", + "holcus_mollis", + "crambe_maritima", + "erythrina_variegata", + "platanthera_chlorantha", + "rosa_banksiae", + "chi_hoa_t\u00edm", + "platanus_acerifolia", + "physalis_peruviana", + "hamamelis_virginiana", + "calystegia_sepium", + "podocarpus_latifolius", + "dicksonia_antarctica", + "galium_boreale", + "ulmus_hollandica", + "nephrolepis_exaltata", + "asclepias_meadii", + "ranunculus_aquatilis", + "polypodium_vulgare", + "bromus_secalinus", + "pinus_palustris", + "conium_maculatum", + "plantago_media", + "ranunculus_acris", + "cirsium_arvense", + "cypripedium_reginae", + "andromeda_polifolia", + "chi_ni\u1ec5ng", + "betula_papyrifera", + "rosa_damascena", + "platanthera_bifolia", + "solanum_quitoense", + "tritoma" + ], + "PUBLIC_FIGURE": [ + "henry_cavendish", + "benjamin_franklin", + "noah_webster", + "john_knox", + "heinrich_hertz", + "giovanni_boccaccio", + "rudolf_steiner", + "thomas_bayes", + "johann_bernoulli", + "max_bruch", + "leonard_bernstein", + "che_guevara", + "c", + "maria_callas", + "william_walton", + "henrik_ibsen", + "mary_shelley", + "marcello_malpighi", + "david_livingstone", + "eduard_buchner", + "john_herschel", + "jan_van_eyck", + "carl_rogers", + "richard_burton", + "douglas_macarthur", + "mary_wollstonecraft", + "j_edgar_hoover", + "thomas_reid", + "otto_frisch", + "winston_churchill", + "johannes_diderik_van_der_waals", + "karl_landsteiner", + "paul_mccartney", + "andrew_marvell", + "terry_pratchett", + "stephen_king", + "francis_crick", + "isaac_newton", + "victor_hugo", + "joseph_smith", + "edwin_hubble", + "colette", + "milton_friedman", + "edward_gibbon", + "mary_stuart", + "jefferson_davis", + "john_glenn", + "george_harrison", + "george_orwell", + "richard_wagner", + "williams", + "e_l_doctorow", + "marie_curie", + "francis_galton", + "nam_ng\u01b0", + "michael_jackson", + "carl_sandburg", + "thomas_hobbes", + "el_greco", + "samuel_beckett", + "david", + "galileo_galilei", + "jane_goodall", + "john_donne", + "chaim_weizmann", + "robert_koch", + "george_eastman", + "john_steinbeck", + "edmund_hillary", + "vincent_van_gogh", + "anne_boleyn", + "robert_burns", + "thomas_paine", + "bari", + "steven_weinberg", + "mary_pickford", + "hans_fischer", + "emiliano_zapata", + "nam_t\u01b0\u1edbc_m\u00fcnchhausen", + "willem_einthoven", + "samuel_johnson", + "jesus", + "marie_antoinette", + "giuseppe_verdi", + "e", + "karl_jaspers", + "konrad_adenauer", + "norbert_wiener", + "john_masefield", + "gottlieb_daimler", + "catarina", + "frank_sinatra", + "abel_tasman", + "katharine_hepburn", + "henri_becquerel", + "henri_matisse", + "bertram_brockhouse", + "louis_pasteur", + "richard_strauss", + "theodosius_i", + "hugo_grotius", + "mahalia_jackson", + "john_ford", + "gertrude_stein", + "sarah_bernhardt", + "luigi_pirandello", + "t_s_eliot", + "robert_millikan", + "an_t\u00f4n", + "charles_de_gaulle", + "paul_von_hindenburg", + "y", + "mary_mallon", + "ralph_bunche", + "charles_lindbergh", + "vincenzo_bellini", + "samuel_barber", + "f", + "ludwig_wittgenstein", + "august_strindberg", + "stalin", + "thomas_mann", + "dante_alighieri", + "peter_pan", + "james_tobin", + "giacomo_puccini", + "edward_fitzgerald", + "fridtjof_nansen", + "louis_braille", + "herbert_marcuse", + "paul_verlaine", + "robert_johnson", + "james_dean", + "theodor_schwann", + "alessandro_manzoni", + "joseph_priestley", + "nicolas_poussin", + "joseph_pulitzer", + "jim_corbett", + "oscar_wilde", + "philip_roth", + "j_d_salinger", + "henry", + "richard_trevithick", + "jackson", + "laurence_olivier", + "adolf_eichmann", + "francis_bacon", + "pete_seeger", + "john_wycliffe", + "a", + "morris", + "james_brown", + "william_hogarth", + "charles_baudelaire", + "luigi_cherubini", + "david_ricardo", + "henri_labrouste", + "mary_leakey", + "immanuel_kant", + "james_franck", + "weber", + "alexandre_yersin", + "albert_schweitzer", + "john_harvard", + "giulio_natta", + "saint_martin", + "titus", + "johannes_kepler", + "max_planck", + "william_blake", + "t_e_lawrence", + "julio_iglesias", + "john_bardeen", + "nietzsche", + "william_byrd", + "scott_joplin", + "carl_lewis", + "canberra", + "elias_canetti", + "edward_jenner", + "oreonympha_nobilis", + "cole_porter", + "jean_luc_godard", + "graham_greene", + "edward", + "lars_onsager", + "margaret_mitchell", + "igor_stravinsky", + "henri", + "lola_montez", + "jan_swammerdam", + "i_ng\u1eafn", + "john_walker", + "william_herschel", + "joseph_black", + "montesquieu", + "arthur_rubinstein", + "arthur_compton", + "niels_bohr", + "henry_fielding", + "bertrand_russell", + "michael_faraday", + "john_d_rockefeller", + "jan_tinbergen", + "robert_venturi", + "ono_y\u014dko", + "rudolf_diesel", + "walt_disney", + "ben_jonson", + "gabriel_lippmann", + "lee", + "friedrich_engels", + "jane_austen", + "moses", + "gustav_mahler", + "phil_collins", + "robert_redford", + "ian_fleming", + "richard_feynman", + "theodor_mommsen", + "marcel_proust", + "thomas_more", + "homo_heidelbergensis", + "paul_hindemith", + "elizabeth_taylor", + "anne_sullivan", + "paul_robeson", + "kh\u1ec9_\u0111u\u00f4i_l\u1ee3n", + "john_dowland", + "william_golding", + "john_milton", + "indira_gandhi", + "george_gershwin", + "alberto_giacometti", + "alfred_nobel", + "jesse_owens", + "marco_polo", + "caravaggio", + "marcel_marceau", + "allen_ginsberg", + "daniel_bernoulli", + "guillaume_apollinaire", + "joseph_henry", + "henri_bergson", + "edward_macdowell", + "gottfried_leibniz", + "pierre_corneille", + "patrick_white", + "hans_christian_andersen", + "cary_grant", + "thomas", + "pieter_zeeman", + "glenn_miller", + "pablo_picasso", + "natalie_wood", + "thomas_moore", + "osman_i", + "otto_hahn", + "christiaan_huygens", + "hector_berlioz", + "paul_simon", + "claudio_monteverdi", + "john_galsworthy", + "linh_d\u01b0\u01a1ng_ho\u1eb5ng_th\u00f4ng_th\u01b0\u1eddng", + "o", + "adam_smith", + "william_james", + "u", + "jean_harlow", + "karl_marx", + "friedrich_nietzsche", + "i", + "da_t\u00f4", + "john_wesley", + "sandro_botticelli", + "nikola_tesla", + "al_capone", + "billy_graham", + "robert_schumann", + "mel_gibson", + "le_corbusier", + "john_locke", + "th\u00e1nh_ph\u00ear\u00f4", + "alexis_carrel", + "joseph_marie_jacquard", + "henry_james", + "helen_keller", + "paul_dukas", + "ingrid_bergman", + "jean_piaget", + "h_g_wells", + "walt_whitman", + "william_wyler", + "colin_powell", + "ludwig_boltzmann", + "carl_nielsen", + "carl_jung", + "leopold_kronecker", + "adolf_hitler", + "maria_mitchell", + "james_d_watson", + "fritz_haber", + "peter_behrens", + "john_h_watson", + "joseph_haydn", + "garfield", + "george_boole", + "edvard_grieg", + "robert_boyle", + "ralph_richardson", + "chi_ng\u01b0\u1eddi", + "1", + "rosa_parks", + "tchaikovsky", + "ernest_walton", + "jacob", + "hertz", + "fritz_kreisler", + "anne_hathaway", + "don_budge", + "margaret_court", + "g", + "arthur_schopenhauer", + "james_cagney", + "johns_hopkins", + "martin_heidegger", + "arnold_schoenberg", + "r", + "george_lucas", + "andrew_jackson", + "louis_armstrong", + "steven_spielberg", + "st_louis_missouri", + "robert_fulton", + "thomas_hardy", + "giuseppe_garibaldi", + "philip_warren_anderson", + "alexandre_dumas", + "bobby_fischer", + "johannes_gutenberg", + "thomas_malthus", + "gaetano_donizetti", + "william_faulkner", + "amerigo_vespucci", + "arthur_holmes", + "pierre_boulez", + "hans_adolf_krebs", + "emma_goldman", + "francis_poulenc", + "putin", + "matthew_flinders", + "robert_herrick", + "jean_de_la_fontaine", + "robert_hooke", + "o_henry", + "karl_popper", + "george_sand", + "peter_sellers", + "homo_rhodesiensis", + "charles_fourier", + "henry_clay", + "marcus_aurelius", + "peter_o'toole", + "joseph_conrad", + "edmund_halley", + "william_shockley", + "peter_paul_rubens", + "mahatma_gandhi", + "jim_morrison", + "jules_verne", + "paul_newman", + "jackson_pollock", + "john_lennon", + "andrea_palladio", + "bob_woodward", + "charlie_chaplin", + "d_h_lawrence", + "constantin\u00f4", + "hannah_arendt", + "antonio_stradivari", + "maximianus", + "miles_davis", + "h\u1ecd_ti\u00eau_li\u00eau", + "george_marshall", + "stanley_kubrick", + "william_gilbert", + "james_watt", + "jonathan_edwards", + "ronald_reagan", + "helmut_schmidt", + "frederick_douglass", + "david_hilbert", + "wilhelm_reich", + "oliver_cromwell", + "martin_luther_king", + "james_hargreaves", + "william_wordsworth", + "woodrow_wilson", + "el_cid", + "marcus_antonius", + "don_quixote", + "jim_henson", + "ernest_hemingway", + "george_westinghouse", + "aquila", + "jacques_charles", + "arthur_miller", + "cristoforo_colombo", + "nelson_mandela", + "heinrich_himmler", + "al_gore", + "hans_bethe", + "hans_geiger", + "cesare_borgia", + "j_p_morgan", + "roald_amundsen", + "charles_dickens", + "ella_fitzgerald", + "jack_robinson", + "george_enescu", + "jacques_offenbach", + "joseph_paxton", + "federico_fellini", + "the_one", + "bradley", + "willy_brandt", + "francisco_pizarro", + "francisco_franco", + "jackie_robinson", + "e_e_cummings", + "andrew_carnegie", + "pontius_pilatus", + "franz_schubert", + "johnny_cash", + "joseph_mccarthy", + "alfred_kastler", + "mick_jagger", + "william_harvey", + "walter_scott", + "kahlil_gibran", + "th\u00e1nh_george", + "jonathan_swift", + "walter_gropius", + "albert_einstein", + "thomas_edison", + "claude_bernard", + "henry_purcell", + "t", + "wilhelm_ostwald" + ], + "LOCATION": [ + "al_jazeera", + "plantago_lanceolata", + "trifolium_pratense", + "s\u00f4ng_san_joaquin", + "\u0111\u1ea1i_h\u00f9ng", + "dryocopus_martius", + "eryngium_maritimum", + "nam_\u0111\u00f4ng", + "bow_wow", + "piet_mondrian", + "n\u00fai_\u00f4liu", + "sint_maarten", + "petasites_hybridus", + "h\u1ea3i_\u0111\u01b0\u1eddng", + "nam_\u00fac", + "c\u00e1p_ve", + "t\u00f2a_th\u1ecb_s\u1ea3nh", + "iris_pseudacorus", + "nam_th\u1eadp", + "pieris_rapae", + "sa_m\u1ea1c_black_rock", + "mau_l\u00ean", + "joseph_louis_gay_lussac", + "nuphar_lutea", + "ga_\u0111\u01b0\u1eddng_s\u1eaft", + "vaccinium_oxycoccos", + "t\u00f2a_th\u1ecb_ch\u00e1nh", + "plantago_media", + "alnus_glutinosa", + "nam_t\u00e0o", + "t\u00f2a_th\u1ecb_ch\u00ednh", + "saint_lucia", + "th\u00e1nh_patrici\u00f4", + "hat_yai", + "sri_lanka", + "\u00f4ng_gi\u00e0_noel", + "\u00f4ng_gi\u00e0_n\u00f4_en", + "scutellaria_galericulata", + "the_rolling_stones", + "h\u1ed3_th\u01b0\u1ee3ng", + "kryvyi_rih", + "n\u01b0\u1edbc_nh\u1ea1t", + "n\u00fai_st_helens", + "tr\u01b0\u1eddng_nh\u1ea1c", + "heitor_villa_lobos", + "trifolium_dubium", + "1_th\u00e1ng_1" + ], + "ANIMAL": [ + "terenura_sharpei", + "apodemus", + "buteo", + "epidalea", + "vi_khu\u1ea9n_than", + "chi_s\u00f3c", + "lemmus_lemmus", + "chi_linh_mi\u00eau", + "mirounga_leonina", + "voi_r\u1eebng_ch\u00e2u_phi", + "chi_chu\u1ed9t_hai_ch\u00e2n", + "carduelis", + "chi_c\u00e1_voi_hoa_ti\u00eau", + "lactobacillus_acidophilus", + "te_m\u00e0o", + "brachypteraciidae", + "th\u01b0\u1ee3ng_s\u0129", + "raven", + "con_g\u1ea5u_con", + "voi_b\u1ee5i_r\u1eadm_ch\u00e2u_phi", + "chu\u1ed9t_lang", + "chi_tr\u00e2u", + "ai_ai", + "chi_ch\u1ed3n_mactet", + "chi_c\u00e1_heo_m\u1ecf", + "accipiter", + "sa_gi\u00f4ng_b\u1ee5ng_\u0111\u1ecf_trung_qu\u1ed1c", + "voi_ch\u00e2u_phi", + "le_h\u00f4i", + "corallium_rubrum", + "chi_d\u00f9_d\u00ec", + "branta_bernicla", + "chi_ch\u1ed3n", + "le_h\u00f4i_c\u1ed5_\u0111en", + "h\u00e0", + "chi_c\u00fa_m\u00e8o_ch\u00e2u_m\u1ef9", + "h\u1ecd_y\u1ebfn", + "alle_alle", + "ba_toong", + "chi_c\u00fa_m\u00e8o", + "chi_h\u1ea3i_t\u01b0\u1ee3ng", + "voi_ch\u00e2u_\u00e1", + "huy\u1ec1n_v\u0169", + "chu\u1ed9t_lang_nh\u00e0", + "c\u00e1_d\u00e2y_nh\u1eadt_b\u1ea3n", + "chi_c\u1eaft", + "sa_gi\u00f4ng_s\u1edf_h\u00f9ng", + "chi_c\u00fa_l\u1ee3n", + "an_ca_l\u1edbn", + "peristediidae", + "nh\u1ea1n_b\u1ee5ng_tr\u1eafng", + "arvicola", + "b\u1ec7nh_do_vi_r\u00fat_ebola", + "ngan" + ], + "ORG": [ + "con_th\u01b0\u01a1ng_b\u1ed1", + "ma_tr\u1eadn_k\u00ec_\u1ea3o", + "la_gi\u00e1ng_tr\u01b0\u1edfng", + "wicca", + "an_education", + "\u00e0_n\u00e0y", + "jan_mayen", + "the_usual_suspects", + "aa", + "nasa", + "bollywood", + "schutzstaffel", + "the_who", + "haganah", + "san_francisco", + "trung_qu\u1ed1c_qu\u1ed1c_d\u00e2n_\u0111\u1ea3ng", + "v\u0129nh_long", + "h\u1ea1_vi\u1ec7n_ph\u00e1p", + "ti\u1ebfng_\u0111\u1ee9c", + "gao", + "\u0111\u1ea3ng", + "th\u00e1nh_gia_th\u1ea5t", + "an_sinh_x\u00e3_h\u1ed9i", + "saint_helena", + "d\u1ea7n_d\u1ea7n", + "don_juan", + "\u6240\u90f5\u96fb", + "ai", + "lu\u1eadt_la_m\u00e3", + "the_football_league", + "dia", + "h\u1ea1_vi\u1ec7n", + "gi\u00e1o_h\u1ed9i_c\u00f4ng_gi\u00e1o", + "v\u01b0\u1eddn_b\u00e1ch_th\u1ea3o", + "caf\u00e9_au_lait", + "nha_trang", + "\u653f\u9ee8", + "bi\u1ec3n_\u0111\u1ecf", + "\u623f\u90f5\u96fb", + "\u0111\u1ea3ng_c\u1ed9ng_h\u00f2a", + "rabindranath_tagore", + "c\u00f4ng_\u0111\u1ea3ng", + "gestapo", + "winnie_the_pooh", + "ch\u1eef_th\u1eadp_\u0111\u1ecf", + "ph\u00f2ng_b\u01b0u_\u0111i\u1ec7n", + "con_ng\u1ef1a_th\u00e0nh_troia", + "l\u1ee5c_qu\u00e2n_hoa_k\u1ef3", + "y_t\u1ebf", + "\u0111\u1ea3ng_nh\u00e2n_d\u00e2n_t\u00e2y_ban_nha", + "n\u00fai_carmel", + "al_jazeera", + "kim_tr\u01b0\u1edbng_h\u00e3n_qu\u1ed1c", + "b\u1ea1ch_\u1ed1c", + "disa", + "addis_ababa", + "qu\u1ed1c_h\u1ed9i_h\u00e0n_qu\u1ed1c", + "th\u00e1nh_gia", + "t\u00f2a_b\u1ea1ch_cung", + "mossad", + "ba_ch\u1ecb_em", + "th\u1ebf_gi\u1edbi_m\u1edbi", + "h\u1ed3ng_h\u1ea3i", + "ho\u00e0ng_h\u00e0", + "saint_barth\u00e9lemy", + "los_angeles", + "nato", + "\u0111\u1ea3ng_x\u00e3_h\u1ed9i", + "\u0111\u1ea3ng_c\u00f4ng_nh\u00e2n_\u0111\u1ee9c_qu\u1ed1c_gia_x\u00e3_h\u1ed9i_ch\u1ee7_ngh\u0129a", + "mi", + "ng\u00e2n_h\u00e0ng_trung_\u01b0\u01a1ng", + "sa", + "b\u1ea1ch_cung", + "\u1ed1c_anh_v\u0169", + "li\u00ean_minh_vi\u1ec5n_th\u00f4ng_qu\u1ed1c_t\u1ebf", + "\u0111\u1ea3ng_ru\u1ed9ng_\u0111\u1ea5t_belarus", + "l\u1ec5_\u0111\u1ee9c_m\u1eb9_l\u00ean_tr\u1eddi", + "giao_th\u1eeba", + "con_th\u01b0\u01a1ng_m\u1eb9", + "ng\u01b0\u1eddi_\u0111\u1eb9p_ng\u1ee7_trong_r\u1eebng", + "nh\u00e0_tr\u1eafng", + "kh\u00f4ng_qu\u00e2n", + "ti\u00eau_th\u1ed5", + "h\u1ea3i_quan", + "khu_c\u00f4ng_nghi\u1ec7p", + "t\u00f2a_b\u1ea1ch_\u1ed1c", + "s\u00e3o_tom\u00e9", + "an_ninh_qu\u1ed1c_gia" + ], + "FAC": [ + "trung_t\u00e2m_mua_s\u1eafm", + "arnold_schoenberg", + "pyotr_i_c\u1ee7a_nga", + "b\u1ed1n_m\u00f9a", + "gi\u00e1o_h\u1ed9i_c\u00f4ng_gi\u00e1o_r\u00f4ma", + "saint_lucia", + "th\u00e1nh_giuse", + "b\u01b0u_c\u1ee5c", + "b\u01b0u_\u0111i\u1ec7n", + "titus_livius", + "xanh_lu_xi_a", + "trung_t\u00e2m_th\u01b0\u01a1ng_m\u1ea1i", + "s\u1edf_b\u01b0u_\u0111i\u1ec7n" + ], + "RELIGION_MEMBER": [ + "anabaptist", + "moor", + "augustin\u00f4", + "mormon", + "em_trai" + ], + "POLITICAL_PARTY": [ + "c\u00f4ng_\u0111\u1ea3ng_\u00fac", + "\u0111\u1ea3ng_whig", + "ch\u00e1nh_\u0111\u1ea3ng", + "c\u00f4ng_\u0111\u1ea3ng_anh", + "lao_\u0111\u1ed9ng", + "qu\u1ed1c_d\u00e2n_\u0111\u1ea3ng", + "\u0111\u1ea3ng_ph\u00e1i_ch\u00ednh_tr\u1ecb", + "\u0111\u1ea3ng_x\u00e3_h\u1ed9i_d\u00e2n_ch\u1ee7", + "\u0111\u1ea3ng_b\u1ea3o_th\u1ee7", + "\u0111\u1ea3ng_d\u00e2n_ch\u1ee7", + "\u0111\u1ea3ng_c\u1ed9ng_s\u1ea3n" + ], + "FOOD": [ + "mousse", + "k\u1eb9o_cao_su", + "sa_m\u1ea1c", + "nem_r\u00e1n", + "si_r\u00f4_c\u00e2y_th\u00edch", + "chile", + "sonchus_oleraceus", + "omelette" + ], + "PRODUCT": [ + "justin_bieber", + "new_zealand", + "bo_bo", + "al_jazeera", + "diego_garcia", + "c\u01b0\u1eddm_th\u1ea3o", + "echinopsis_pachanoi", + "bi_b\u00f4", + "cape_horn", + "\u0111\u01b0\u1eddng_c\u1ee5t", + "julius_caesar", + "ng\u00f5_c\u1ee5t", + "the_star_spangled_banner", + "don_quixote", + "sachsen_anhalt", + "\u4eba\u6b0a", + "s\u00e3o_tom\u00e9_v\u00e0_pr\u00edncipe", + "deutsche_welle", + "tam_qu\u1ed1c", + "ng\u00e0y_t\u1eb7ng_qu\u00e0", + "ch\u00faa_th\u00e1nh_th\u1ea7n", + "\u00fd_d\u0129", + "th\u00e1nh_th\u1ea7n", + "t\u00e2n_\u01b0\u1edbc_hi_v\u0103n", + "nordrhein_westfalen", + "bi_c\u00e1i", + "\u00f4ng_gi\u00e0_santa", + "c\u00e2y_n\u00f4_en", + "novo_mesto" + ], + "DISEASE": [ + "ki", + "tra_t\u1ea5n", + "als", + "progeria", + "u_nang_bu\u1ed3ng_tr\u1ee9ng", + "poison_ivy", + "listeriosis", + "chi_d\u1ebb_tr\u00f9ng_kh\u00e1nh", + "the_bends", + "phytophthora_infestans", + "virus_kh\u1ea3m_thu\u1ed1c_l\u00e1", + "cam_t\u1ea9u_m\u00e3", + "chi", + "va_ch\u1ea1m_\u0111i\u1ec7n", + "gimp", + "tai_bi\u1ebfn_m\u1ea1ch_m\u00e1u_n\u00e3o", + "ho_g\u00e0", + "nghi\u1ec7n", + "u_m\u1ec1m_l\u00e2y", + "thalassemia", + "purpura", + "vi\u00eam", + "mi", + "u_x\u01a1_ti\u1ec1n_li\u1ec7t_tuy\u1ebfn", + "tan", + "sting", + "n\u00e3o_\u00fang_th\u1ee7y", + "u_m\u00e1u", + "chi_\u00e1c_l\u00e0", + "salmonella" + ], + "JOB": [ + "cu_li", + "the_police", + "ga_l\u0103ng", + "freelancer", + "the_guardian", + "regidor", + "tri_s\u1ef1", + "the_economist", + "tai_bi\u1ebfn_m\u1ea1ch_m\u00e1u_n\u00e3o", + "the_hangover", + "man", + "usher", + "messenger", + "phu", + "proconsul", + "chu\u1ea9n_t\u01b0\u1edbng", + "the_independent", + "bishop", + "cookie" + ], + "POLITICAL_PARTY_MEMBER": [ + "menshevik" + ], + "PERSON": [ + "julius_caesar", + "ha_ha", + "al_gore", + "h_g_wells", + "v_v", + "kim_yoo_jin", + "e_e_cummings", + "th\u00e1i_s\u01a1n", + "carl_david_anderson", + "gaius_julius_caesar" + ], + "QUANTITY": [ + "hai_m\u01b0\u01a1i_m\u1ed1t", + "won_h\u00e0n_qu\u1ed1c", + "ba_ch\u1ecb_em", + "hai_m\u01b0\u01a1i_hai", + "g", + "won_c\u1ed9ng_h\u00f2a_d\u00e2n_ch\u1ee7_nh\u00e2n_d\u00e2n_tri\u1ec1u_ti\u00ean", + "pound", + "gasterosteus_aculeatus", + "anders_celsius" + ], + "DATE": [ + "dog_days", + "in_time", + "tr\u0103ng_non" + ], + "GPE": [ + "dar_es_salaam", + "sint_maarten", + "nam_m\u1ef9", + "b\u1ea3y_s\u1ef1_th\u01b0\u01a1ng_kho_c\u1ee7a_\u0111\u1ee9c_m\u1eb9", + "t\u00e2n_\u01b0\u1edbc", + "nam_\u0111\u1ecbnh", + "hagia_sophia", + "kinh_th\u00e1nh_hi_v\u0103n", + "s\u00e3o_tom\u00e9", + "nic\u00f4la_th\u00e0nh_myra", + "gran_canaria", + "x\u00edch_h\u1ea3i", + "\u0111\u1ebf_qu\u1ed1c_\u0111\u1ee9c", + "al_andalus", + "v\u00e0ng_tr\u1eafng", + "s\u00f4ng_saint_lawrence", + "th\u00e0nh_ph\u1ed1_chiang_rai", + "la_gomera", + "tr\u00e0_vinh" + ], + "PERSON_PRONOUN": [ + "i", + "i_ng\u1eafn", + "m\u00ea", + "me" + ], + "LANGUAGE": [ + "na_u_ru", + "a_r\u1eadp", + "th\u00e1i", + "esperanto", + "lao", + "tonga" + ], + "SOC_ECO_CLASS": [ + "samurai", + "giai_c\u1ea5p_c\u00f4ng_nh\u00e2n", + "kinh_t\u1ebf_ng\u1ea7m", + "ch\u1ee3_\u0111en", + "n\u00f4ng_nghi\u1ec7p" + ], + "UNION": [ + "c\u00f4ng_\u0111o\u00e0n" + ], + "GENDER": [ + "men", + "boys", + "nam_gi\u1edbi", + "man", + "gal" + ], + "LAW": [ + "t\u1ef1_do_b\u00e1o_ch\u00ed", + "lu\u1eadt_d\u00e2n_s\u1ef1", + "c\u1ee5c_\u0111i\u1ec1u_tra_li\u00ean_bang" + ], + "RELIGION": [ + "wicca" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "ch\u00e1u": "ch\u00e1u_n\u1ed9i", + "m\u1eb9": "th\u1ea7y", + "b\u00e0_x\u01a1": "\u50e7\u4f3d", + "n\u1eef_tu_s\u0129": "\u50e7\u4f3d", + "x\u01a1": "th\u1ea7y_tu", + "n\u1eef_tu": "\u50e7\u4f3d", + "pr\u00edncipe": "prince", + "b\u00e0_ch\u00faa": "key", + "c\u00f4ng_ch\u00faa": "prince", + "danaus_gilippus": "vua", + "r\u00e8n": "\u570b\u738b", + "n\u1eef_ho\u00e0ng": "indra", + "n\u1eef_v\u01b0\u01a1ng": "indra", + "b\u00e0_ho\u00e0ng": "\u570b\u738b", + "b\u00e0_\u1ea5y": "\u1ea3nh", + "c\u00f4_\u1ea5y": "h\u1eafn", + "heo": "\u1ed5ng", + "ch\u1ecb_\u1ea5y": "h\u1eafn", + "t\u1ec1_x\u00e1": "anh_\u1ea5y", + "ch\u1ecb_g\u00e1i": "em_trai", + "em_g\u00e1i": "anh_trai", + "con_g\u00e1i_ri\u00eang": "con_trai_ri\u00eang", + "m\u1eb9_gh\u1ebb": "b\u1ed1_d\u01b0\u1ee3ng", + "m\u1eb9_k\u1ebf": "b\u1ed1_d\u01b0\u1ee3ng", + "ch\u1ecb_h\u1ea7u_b\u00e0n": "b\u1ed3i", + "qu\u1ea3_ph\u1ee5": "ng\u01b0\u1eddi_g\u00f3a_v\u1ee3", + "\u5be1\u5a66": "ng\u01b0\u1eddi_g\u00f3a_v\u1ee3", + "ng\u01b0\u1eddi_v\u1ee3": "ch\u1ed3ng", + "phu_nh\u00e2n": "ch\u1ed3ng", + "v\u1ee3": "ch\u1ed3ng", + "\u0111\u00e0n_b\u00e0": "man", + "\u5a66\u5973": "nam_gi\u1edbi", + "ph\u1ee5_n\u1eef": "man", + "con_trai": "con_g\u00e1i", + "trai": "c\u00f4_g\u00e1i" + }, + "other_gender_swap": { + "thay": "b\u00e0_\u1ea5y", + "h\u1ecd": "b\u00e0_\u1ea5y", + "\u1ea3nh": "h\u1ecd", + "anh_\u1ea5y": "h\u1ecd", + "h\u1eafn": "thay", + "\u00f4ng_\u1ea5y": "thay", + "\u1ed5ng": "thay", + "c\u1ee7a_n\u00f3": "c\u1ee7a_h\u1ecd", + "c\u1ee7a_anh_\u1ea5y": "c\u1ee7a_h\u1ecd", + "c\u1ee7a_h\u1eafn": "c\u1ee7a_h\u1ecd", + "lia": "c\u1ee7a_h\u1ecd", + "b\u00e0_\u1ea5y": "thay", + "c\u00f4_\u1ea5y": "h\u1ecd", + "heo": "thay", + "ch\u1ecb_\u1ea5y": "h\u1ecd", + "t\u1ec1_x\u00e1": "h\u1ecd" + }, + "en_pronoun2gender": { + "they": [ + "\u0111\u1ed3ng_t\u00ednh", + "\u0111\u1ed3ng_t\u00ednh_luy\u1ebfn_\u00e1i", + "ng\u01b0\u1eddi_chuy\u1ec3n_gi\u1edbi" + ], + "he": [ + "nam_gi\u1edbi", + "man", + "con_trai", + "little_boy", + "trai" + ], + "she": [ + "c\u00f4_g\u00e1i", + "ph\u1ee5_n\u1eef", + "h\u1ee5t", + "m\u00e1i", + "tr\u1eadt", + "\u5a66\u5973", + "con_g\u00e1i", + "\u0111\u1ed3ng_t\u00ednh", + "g\u00e1i", + "tr\u01b0\u1ee3t", + "thi\u1ebfu_n\u1eef", + "\u0111\u00e0n_b\u00e0", + "miss_a", + "c\u00e1i", + "n\u1eef", + "gal" + ] + }, + "en_pronoun2pronoun": { + "he": [ + "h\u1eafn", + "anh_\u1ea5y", + "c\u1ee7a_anh_\u1ea5y", + "lia", + "c\u1ee7a_h\u1eafn", + "\u00f4ng_\u1ea5y", + "\u1ed5ng", + "c\u1ee7a_n\u00f3", + "\u1ea3nh" + ], + "she": [ + "ch\u1ecb_\u1ea5y", + "b\u00e0_\u1ea5y", + "c\u00f4_\u1ea5y", + "heo", + "t\u1ec1_x\u00e1" + ], + "they": [ + "lia", + "c\u1ee7a_h\u1ecd", + "thay", + "h\u1ecd" + ], + "it": [ + "kia", + "n\u00e0y", + "\u1ea5y" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/vo.json b/data_tooling/pii_processing/ontology/data/vo.json new file mode 100644 index 0000000..92cf620 --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/vo.json @@ -0,0 +1,610 @@ +{ + "JOB": [ + "jileb\u00f6tan", + "jepan", + "cimijiklin\u00fckan", + "hiprokonsulan", + "cilik\u00e4l\u00e4dan", + "sifanakomipan", + "bakan", + "selid\u00f6pilaban", + "galedanahipul", + "krolig\u00fcl", + "hidatuvan", + "hidan\u00fcdan", + "jifarman", + "namajipl\u00e4gan", + "kral", + "hikonletan", + "zeilihigaledan", + "futak\u00e4lan", + "jim\u00fclan", + "pold", + "plaudan", + "nolavan", + "jikrolig\u00fcl", + "bumavan", + "hisanan", + "hibijop", + "jidatuvan", + "hikrolig\u00fcl", + "hifarman", + "vitidajiklopan", + "hitradutan", + "cimihiklin\u00fckan", + "datuvan", + "himetalavan", + "lemekal", + "jisoldat", + "geredavan", + "jiyurinavan", + "hijafan", + "hibakan", + "skalel", + "jibakan", + "cilijik\u00e4l\u00e4dan", + "jigadan", + "hitidan", + "kaligrafan", + "hiselan", + "kvisinan", + "poldan", + "b\u00fcsidan", + "zeilijigaledan", + "jilavogan", + "jidan\u00fcdan", + "lavogan", + "vitidahiklopan", + "jikaligrafan", + "jafan", + "geidan", + "jilulautan", + "hidrogan", + "vitidaklopan", + "jikonletan", + "jipigaledan", + "vomasanan", + "safaferan", + "sifal", + "sanan", + "hidr\u00e4gun", + "galedanapul", + "hilulautan", + "jafel", + "selid\u00f6pijilaban", + "jiheran", + "jijafan", + "konletan", + "nimasanel", + "wetter", + "cimiklin\u00fckan", + "drogan", + "selid\u00f6pihilaban", + "hiyurinavan", + "jafal", + "zeiligaledan", + "namahipl\u00e4gan", + "plovinik", + "hilavogan", + "yurinavan", + "hisafaferan", + "hikaligrafan", + "tidan", + "klavan", + "hipoldan", + "kvisinal", + "cubanaf", + "higadan", + "jikapenan", + "valemik", + "jibijop", + "sanel", + "klin\u00fckan", + "namapl\u00e4gan", + "jislafan", + "galedanajipul", + "litamagel", + "hikapenan", + "stelavan", + "s\u00fcgan", + "lulautan", + "jisifal", + "jimetalavan", + "hileb\u00f6tan" + ], + "PUBLIC_FIGURE": [ + "akira_kurosawa", + "henrik_ibsen", + "troglod\u00fct", + "terry_pratchett", + "isaac_newton", + "victor_hugo", + "sted\u00e4lik", + "saint_louis", + "richard_wagner", + "williams", + "marie_curie", + "michael_jackson", + "samuel_beckett", + "galileo_galilei", + "vincent_van_gogh", + "allen_iverson", + "giuseppe_verdi", + "e", + "igor_stravinskiy", + "ji_flan\u00e4nan", + "henri_matisse", + "louis_pasteur", + "sarah_bernhardt", + "y", + "f", + "ludwig_wittgenstein", + "dante_alighieri", + "giacomo_puccini", + "oscar_wilde", + "lawrence", + "morris", + "immanuel_kant", + "warburg", + "johannes_kepler", + "max_planck", + "spidik", + "canberra", + "oscar_robertson", + "yuriy_gagarin", + "michael_faraday", + "walt_disney", + "lee", + "gustav_mahler", + "marcel_proust", + "john_milton", + "marco_polo", + "henri_bergson", + "gottfried_leibniz", + "hans_christian_andersen", + "thomas", + "pablo_picasso", + "hector_berlioz", + "u", + "friedrich_nietzsche", + "i", + "sandro_botticelli", + "nikola_tesla", + "charles_barkley", + "robert_schumann", + "le_corbusier", + "perry", + "flan\u00e4nan", + "joseph_haydn", + "vladimir_putin", + "bill_russell", + "baldwin", + "m\u00fclan", + "g", + "r", + "george_lucas", + "louis_armstrong", + "steven_spielberg", + "johannes_gutenberg", + "him\u00fclan", + "peter_o'toole", + "peter_paul_rubens", + "jim_morrison", + "jackson_pollock", + "charlie_chaplin", + "lelaplan", + "stanley_kubrick", + "james_watt", + "ronald_reagan", + "william_wordsworth", + "jean_auguste_ingres", + "cristoforo_colombo", + "roald_amundsen", + "charles_dickens", + "jacques_offenbach", + "federico_fellini", + "powell", + "franz_schubert", + "albert_einstein", + "thomas_edison", + "t" + ], + "ANIMAL": [ + "redap\u00e4drit", + "musigasvan", + "regatigrid", + "musigaturd", + "saglied\u00fcl", + "lunag\u00f6bamanit", + "leon\u00fcl", + "busar", + "domakat", + "hiokamp", + "vesep", + "gr\u00fcnapikit", + "halajijevod", + "gianajak", + "halajojevod", + "bienajireg", + "gianatortug", + "vesepan\u00e4st", + "goldac\u00e4f", + "goldafasan", + "jileon\u00fcl", + "st\u00fctastaf", + "potapijun", + "kavead", + "frog", + "penepejin", + "saglied", + "lievadog", + "fotapijun", + "hisaglied\u00fcl", + "fitavesid", + "skaraf", + "bomafit", + "gretaturd", + "turb", + "galedajidog", + "ridakraozef", + "hisaglied", + "halahijevod", + "bomb\u00fczil", + "vanul", + "jisaglied\u00fcl", + "melasval", + "lilal\u00fcl", + "galedahidog", + "jisaglied", + "galedadog", + "gladab\u00f6d", + "halajevod", + "visaf", + "rosip", + "halahojevod", + "ridaberit" + ], + "PLANT": [ + "jilekanan", + "brasid", + "magnol", + "redabetad", + "skapular", + "salig", + "kokotapam", + "vietasalig", + "kokotep", + "paradit", + "hilekanan", + "florabrasid", + "padudep", + "lerid", + "koegakv\u00e4rabim", + "sprotianabrasid", + "lekanan", + "buckeye", + "flukabim", + "dogarosadabim\u00fcl", + "kaor", + "latrop", + "padudabim", + "felapop" + ], + "RACE": [ + "larab\u00e4n", + "ji_laustral\u00e4nan", + "siyopan", + "latin", + "l\u00e4skiomans", + "leskimanef", + "frans\u00e4nan", + "jinisulan", + "l\u00e4skiomanef", + "leskimans", + "laustral\u00e4nan", + "yuropik", + "viet", + "hinisulan", + "frikopik", + "yudanik", + "jiyudanik", + "ji_frans\u00e4nan" + ], + "FOOD": [ + "koled", + "kunamilig", + "maskagumod", + "salodabubamit", + "flapilakrem", + "p\u00e4rlatahod", + "moel\u00e4t", + "gingif", + "glutavin", + "redabrasid", + "bludasosit" + ], + "SOC_ECO_CLASS": [ + "donaklad", + "filist", + "lesog\u00e4d", + "miligapin" + ], + "POLITICAL_PARTY_MEMBER": [ + "rep\u00fcblikimik" + ], + "RELIGION_MEMBER": [ + "jikoptan", + "slamik", + "yudan", + "slaman", + "hikoptan", + "hislaman", + "jain", + "kritan" + ], + "DISEASE": [ + "kekunaflamat", + "fijesiped", + "peil\u00e4pik", + "letod", + "peil\u00e4p", + "materim", + "k\u00e4sem", + "futagig", + "ragit", + "bubap\u00e4st", + "honaskin", + "h\u00e4rmafrodit", + "kanseraluuk", + "mudekluvamal\u00e4d", + "jotagig", + "planaglof", + "silefog", + "larinaflamat", + "lelax\u00fcd", + "bienasteg\u00fcl", + "bomabrek", + "filist", + "tutadol" + ], + "ORG": [ + "germav", + "benodug\u00e4l", + "zifatat", + "sankt_andreasberg", + "redakrod", + "yurop", + "san_francisco", + "yulopayum", + "un", + "sanlusiy\u00e4n", + "kons\u00e4l\u00f6p", + "benodug\u00e4lam", + "dot", + "redamel", + "gl\u00fcg_romakatulik", + "ai", + "planavagad", + "redakrodast\u00e4n", + "sigretaber", + "cilasnab\u00e4dajuk", + "jodem", + "reiganef", + "deut\u00e4nap\u00fck", + "donajul", + "po", + "snab\u00e4dajuk", + "los_angeles", + "maskagumod", + "gl\u00fcg_katulik", + "kabov\u00e4rdu\u00e4ns" + ], + "PRODUCT": [ + "justin_bieber", + "kafaken", + "komipac\u00fcd", + "svimablitil", + "kavead", + "kafaskal", + "julius_caesar", + "pardol\u00f6s", + "the_star_spangled_banner", + "stelastejen", + "sax\u00e4n_lanhalt\u00e4n", + "sakalus\u00fct", + "musig\u00f6m", + "fat\u00fcl_kritid", + "yelas\u00e4suns_fol", + "sesamas\u00fct", + "novo_mesto" + ], + "LANGUAGE": [ + "lingl\u00e4nik", + "ji_rus\u00e4nan", + "ji_macar\u00e4nanik", + "hindiy", + "lislade\u00e4nap\u00fck", + "macar\u00e4nap\u00fckik", + "sperantap\u00fck", + "ji_tahite\u00e4nan", + "macar\u00e4nanik", + "macar\u00e4nik", + "lurduv", + "galegik", + "sved\u00e4nap\u00fck", + "tongu\u00e4ns", + "larab\u00e4nap\u00fck", + "flentap\u00fck", + "frikop\u00e4nap\u00fck", + "portug\u00e4nik", + "spany\u00e4nik", + "ji_norg\u00e4nan", + "jijip", + "ido", + "norg\u00e4nan", + "frans\u00e4nap\u00fck" + ], + "RELIGION": [ + "manig" + ], + "PERSON": [ + "julius_caesar", + "de_witt" + ], + "GPE": [ + "diatek_nulik", + "redakrod", + "goldinamein\u00e4d", + "redamel", + "redakrodast\u00e4n" + ], + "LOCATION": [ + "sri_lank\u00e4n", + "lusogem", + "trois_rivi\u00e8res", + "sibl\u00e4gahog", + "sigretaber", + "rosadagad", + "melop", + "lamerik\u00e4n", + "st_albans", + "sakalus\u00fct", + "the_rolling_stones", + "minavat", + "lindean", + "meropan", + "kr\u00fcv\u00fcy_rih", + "merop", + "lamerik\u00e4nik" + ], + "PERSON_PRONOUN": [ + "i", + "oki", + "her", + "us" + ], + "MEDICAL_THERAPY": [ + "bludiped" + ], + "GENDER": [ + "men", + "bub", + "hipul", + "jimenik", + "himenik" + ], + "FAC": [ + "pot\u00f6p", + "kildegkil", + "j\u00f6navalekans", + "nimagad", + "p\u00f6pajul", + "kilsekil", + "sanlusiy\u00e4n" + ], + "QUANTITY": [ + "ton", + "g" + ], + "DATE": [ + "fulamun", + "el_walpurgisnacht", + "jimagivanaz\u00e4laneit" + ], + "ANAT": [ + "l\u00f6pabrad" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "jilep\u00e4dan": "hilep\u00e4dan", + "bibik": "hiter", + "jibaonan": "baonan", + "daut": "son", + "jid\u00fck": "hid\u00fck", + "d\u00fck": "jid\u00fck", + "hid\u00fck": "jid\u00fck", + "vomik": "manik", + "jimenik": "manik", + "her": "omik", + "ofik": "omik", + "jimasetan": "himasetan", + "jikleudan": "kleudan", + "kleudan": "hikleudan", + "poldan": "hipoldan", + "jipoldan": "hipoldan", + "ledaut": "plin", + "jiplin": "plin", + "reg": "hireg", + "jireg": "kral", + "jigem": "blod", + "s\u00f6r": "higem", + "jiblod": "blod", + "ludaut": "luson", + "jilucil": "hilucil", + "jilupal": "lupal", + "lumot": "lupal", + "jib\u00f6tan": "hib\u00f6tan", + "jiviudan": "hiviudan", + "jimatan": "himatan", + "magivan": "jimagival", + "jimagivan": "himagival", + "himagivan": "magival", + "hicil": "jicil", + "hipul": "jicil" + }, + "other_gender_swap": { + "omsik": "ofik", + "onsik": "her", + "ofsik": "her", + "her": "omsik", + "ofik": "onsik" + }, + "en_pronoun2gender": { + "he": [ + "hipul", + "himenik", + "manik", + "hicil", + "bub" + ], + "she": [ + "vomik", + "jimenik", + "jimen", + "jicil" + ] + }, + "en_pronoun2pronoun": { + "he": [ + "oki", + "omik" + ], + "she": [ + "oki", + "ofik", + "her" + ], + "they": [ + "omsik", + "ofs", + "onsik", + "ofsik", + "oms" + ], + "it": [ + "hasin", + "onik" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/wa.json b/data_tooling/pii_processing/ontology/data/wa.json new file mode 100644 index 0000000..93baac1 --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/wa.json @@ -0,0 +1,307 @@ +{ + "PLANT": [ + "feve", + "schitro\u00fble", + "cabu", + "cascagn\u00ee", + "grande_vintche", + "carote", + "cierfouy", + "harloucrale", + "amanites", + "tchers\u00ee", + "tchene", + "betr\u00e5le", + "magriyete", + "waisse", + "bicoine", + "coltchike", + "pronne", + "most\u00e5de", + "rabrouxhe", + "pavoe", + "caroub\u00ee" + ], + "ANIMAL": [ + "tcherdon\u00ee", + "cat", + "tchivro\u00fb", + "sodoirmant_ordinaire", + "tchawe", + "sprewe", + "tchet", + "sodoirmant", + "fawene", + "spirou", + "colibacile", + "to\u00fbtrale", + "passer", + "tchivene", + "linet", + "brotchet", + "graev\u00ee", + "cressale", + "skiron", + "marcote", + "ritch\u00e5d", + "singl\u00e9", + "wesse", + "ecefalite_do_n\u00eel_co\u00fbtchantrece", + "cast\u00f4r", + "bascolete", + "coirnaye", + "houprale", + "taesson" + ], + "PRODUCT": [ + "abondroets_des_djins", + "li_tchet_\u00e5s_botes", + "sint_esprit", + "abondroets_del_djin", + "grande_burtaegne" + ], + "PUBLIC_FIGURE": [ + "akira_kurosawa", + "georges_simenon", + "sint_p\u00e5", + "isaac_newton", + "michael_jackson", + "m\u00f4n\u00ee", + "vincent_van_gogh", + "si_distrure", + "e", + "paul_verlaine", + "hinri", + "don_quijote", + "pete_seeger", + "a", + "walt_disney", + "peter", + "hanscroufe", + "jesse_owens", + "guillaume_apollinaire", + "karl_marx", + "friedrich_nietzsche", + "john_locke", + "adolf_hitler", + "si_mete_a_f\u00e9n", + "r", + "steven_spielberg", + "johannes_gutenberg", + "jean_de_la_fontaine", + "peter_o'toole", + "charlie_chaplin", + "telecmande", + "ronald_reagan", + "martin_luther_king", + "nelson_mandela", + "roald_amundsen", + "johnny_cash", + "albert_einstein" + ], + "ORG": [ + "e_s_m\u00e5jhone", + "scole", + "end_aw\u00e8_s_s\u00f4", + "cap_vert", + "tawoyisse", + "sint_impire_romin_djermanike", + "sint_ogustin", + "tch\u00e5r_p\u00f4cet", + "divintrin", + "sinte_b\u00e5re", + "e_s_m\u00e5jhon", + "po", + "almand", + "urope", + "zonigne", + "novele_lune", + "nicolai_d_mira", + "al_djazira" + ], + "JOB": [ + "boledj\u00ee", + "scoleu", + "pretcheu", + "roy", + "don", + "valet", + "pondeu", + "boledjresse", + "bokion", + "moult\u00ee", + "boskiyon", + "messaedj\u00ee", + "acontance", + "mandarin", + "mayeur", + "bierdj\u00ee", + "fonccionaire", + "abateu" + ], + "DISEASE": [ + "maladeye", + "essoctaedje", + "pesse", + "five_ebola", + "stiernixhaedje", + "rodjetes", + "toss\u00ee", + "efouwaedje", + "rovio\u00fbles", + "waerb\u00e5d", + "fornourixhaedje", + "froedeur", + "listeri\u00f4ze", + "udinme", + "otisse", + "raedje", + "soumey", + "peumoneye", + "sprogn\u00ee", + "screper", + "greter", + "friskete", + "crantche", + "grangrin", + "tosse", + "poirt\u00eaye", + "waerbea", + "stiernouwer", + "cingues", + "tanfla" + ], + "PERSON_PRONOUN": [ + "vosse", + "mine", + "our", + "leye" + ], + "LOCATION": [ + "si_stamper", + "i_n_f\u00e5t_r\u00e9n_po_\u00e7oula", + "po_si_e_cas", + "si_e_cas", + "grand_tch\u00e5r", + "s_astamper", + "estats_unis", + "si_lever", + "al_djazira", + "the_rolling_stones", + "court" + ], + "GPE": [ + "sint_esprit", + "pass\u00e5jhe" + ], + "FOOD": [ + "stof\u00e9", + "marinde" + ], + "RACE": [ + "turk" + ], + "DATE": [ + "djonne_lune", + "ladr\u00ee", + "tossint", + "grande_notru_dame", + "tinre_lune" + ], + "QUANTITY": [ + "ton", + "spinoke" + ], + "RELIGION_MEMBER": [ + "crustin" + ], + "GENDER": [ + "male", + "kimere", + "frumele" + ], + "LANGUAGE": [ + "malayalam", + "hindi", + "daenw\u00e8s", + "esperanto", + "lingala" + ], + "RELIGION": [ + "islam" + ], + "FAC": [ + "sint_dj\u00e5ke_el_galice" + ], + "SOC_ECO_CLASS": [ + "agrico\u00fbteure", + "crinme" + ], + "PERSON": [ + "magn\u00e5ve_bolet" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "femrin": "male", + "frumele": "male", + "princesse": "prince", + "royinne": "roy", + "frut": "feye", + "gam\u00e9n": "feye" + }, + "other_gender_swap": { + "leus": "s\u00f4", + "s\u00f4": "leus" + }, + "en_pronoun2gender": { + "he": [ + "male", + "frut", + "gam\u00e9n" + ], + "she": [ + "b\u00e5shele", + "feye", + "kimere", + "frumele", + "femrin", + "feme" + ] + }, + "en_pronoun2pronoun": { + "he": [ + "lyi", + "s\u00f4" + ], + "she": [ + "leye", + "s\u00f4" + ], + "they": [ + "leus" + ], + "it": [ + "cisse", + "ces", + "cisse_lale", + "ci_la", + "cesses_lale", + "ces_ci", + "ces_la", + "\u00e8\u00e7_n", + "oyi", + "\u00e8\u00e7" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/war.json b/data_tooling/pii_processing/ontology/data/war.json new file mode 100644 index 0000000..cec85bc --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/war.json @@ -0,0 +1,1097 @@ +{ + "PLANT": [ + "acer_negundo", + "cucurbita_ficifolia", + "hibiscus_syriacus", + "acanthocereus_tetragonus", + "hibiscus_mutabilis", + "brachychiton_populneus", + "primula_auricula", + "robinia_hispida", + "lilium_martagon", + "lupinus_luteus", + "pyracantha", + "acer_rubrum", + "campanula_persicifolia", + "diospyros_virginiana", + "verbascum_thapsus", + "lycium_barbarum", + "parnassia", + "salvia_leucophylla", + "iris_germanica", + "lilium_philadelphicum", + "lilium_longiflorum", + "sorghum_halepense", + "veronica_beccabunga", + "liriodendron_tulipifera", + "quercus_coccinea", + "cladonia_rangiferina", + "triglochin_maritima", + "impatiens_walleriana", + "geranium_molle", + "dioscorea_bulbifera", + "hoya_carnosa", + "erythronium_albidum", + "viola_arvensis", + "sapindus", + "scutellaria_galericulata", + "claviceps_purpurea", + "viola_reichenbachiana", + "chimaphila_umbellata", + "sarcoscypha_coccinea", + "philadelphus_coronarius", + "aralia_elata", + "brassica_nigra", + "eleocharis_dulcis", + "bromus_tectorum", + "helianthus", + "rosa_chinensis", + "lathyrus_latifolius", + "ripolyu", + "cucurbita_moschata", + "monarda_citriodora", + "solanaceae", + "anthriscus_cerefolium", + "campanula_medium", + "caryota_urens", + "quercus_kelloggii", + "viola_cornuta", + "juncus_articulatus", + "eryngium_maritimum", + "schefflera_actinophylla", + "amelanchier_bartramiana", + "pachysandra_terminalis", + "salix_babylonica", + "cyclamen_purpurascens", + "anthyllis_vulneraria", + "arctostaphylos_alpinus", + "abies_grandis", + "laurus_nobilis", + "lathyrus_odoratus", + "amanita", + "vespula_vulgaris", + "arabidopsis_thaliana", + "pilularia_globulifera", + "bertholletia_excelsa", + "adenium_obesum", + "epipremnum_aureum", + "arundo", + "sorbus_torminalis", + "achillea", + "magnolia_grandiflora", + "solanum_quito\u00ebnse", + "berteroa_incana", + "pelargonium_odoratissimum", + "colutea_arborescens", + "liparis_loeselii", + "chionanthus_virginicus", + "coprinus_comatus", + "sinapis", + "prunus_laurocerasus", + "pachysandra_procumbens", + "allium_tuberosum", + "pennisetum_glaucum", + "amelanchier_alnifolia", + "passiflora_ligularis", + "salix_triandra", + "leucaena_leucocephala", + "silene_virginica", + "lilium_michiganense", + "cercidiphyllum_japonicum", + "atriplex_hortensis", + "vaccinium_corymbosum", + "teucrium_scorodonia", + "acer_campestre", + "bletilla_striata", + "mimosa_pudica", + "singkamas", + "mariguso", + "convolvulus", + "carex_pseudocyperus", + "gentiana_lutea", + "mercurialis_perennis", + "matthiola_incana", + "acacia_pycnantha", + "actinidia_chinensis", + "taxus_baccata", + "saxifraga_granulata", + "valerianella_locusta", + "periploca_graeca", + "rhus_typhina", + "nymphaea_alba", + "silene_dioica", + "euphorbia_esula", + "phaseolus_coccineus", + "diplotaxis_tenuifolia", + "euphorbia_dentata", + "candida_albicans", + "ranunculus_ficaria", + "malope_trifida", + "senna_alata", + "schinus_terebinthifolius", + "amaryllis_belladonna", + "veronica_officinalis", + "phegopteris_connectilis", + "illicium_floridanum", + "pontederia_cordata", + "calophyllum_inophyllum", + "rosa_multiflora", + "prunus_cerasus", + "acer_macrophyllum", + "asclepias_purpurascens", + "acacia_dealbata", + "capsicum_baccatum", + "dianthus_caryophyllus", + "agrimonia_eupatoria", + "larix_occidentalis", + "plantago_lanceolata", + "polystichum_lonchitis", + "ononis_spinosa", + "andropogon_virginicus", + "xanthosoma_sagittifolium", + "acer_palmatum", + "thlaspi_arvense", + "agrostemma_githago", + "geranium_pratense", + "hypericum_androsaemum", + "salix_viminalis", + "calvatia_gigantea", + "juniperus_virginiana", + "eriophorum_angustifolium", + "veronica_serpyllifolia", + "alstonia_scholaris", + "eucalyptus_globulus", + "cassia_fistula", + "pterospermum_acerifolium", + "platanus_occidentalis", + "passiflora_incarnata", + "clusia", + "festuca_ovina", + "quercus_ellipsoidalis", + "bromus_arvensis", + "polygala_vulgaris", + "ardisia_crenata", + "fraxinus_quadrangulata", + "lagikway", + "veronica_peregrina", + "chaenomeles_speciosa", + "selenicereus_grandiflorus", + "citrus_aurantium", + "pelargonium_peltatum", + "reseda", + "barbarea_vulgaris", + "osmanthus_americanus", + "annona_cherimola", + "cortinarius_violaceus", + "platanus_orientalis", + "karot", + "piper_longum", + "gossypium_hirsutum", + "prunus_armeniaca", + "castanea_dentata", + "liquidambar", + "nymphaea_odorata", + "urtica", + "potamogeton_crispus", + "parthenocissus_tricuspidata", + "paspalum_distichum", + "tropaeolum_minus", + "macadamia_tetraphylla", + "cucurbita_argyrosperma", + "kawayan", + "salix_fragilis", + "amanita_muscaria", + "pterocarpus_indicus", + "corylus_americana", + "calla_palustris", + "leonurus_cardiaca", + "spergula_arvensis", + "physostegia_virginiana", + "asplenium_trichomanes", + "acer_japonicum", + "arrhenatherum_elatius", + "nicotiana_alata", + "dracocephalum", + "carissa_macrocarpa", + "populus_balsamifera", + "armeria_maritima", + "nicotiana_tabacum", + "myosotis_sylvatica", + "asclepias_verticillata", + "phyllostachys_nigra", + "astragalus_alpinus", + "quercus_variabilis", + "ulmus_americana", + "primula_acaulis", + "carex_arenaria", + "acanthus_mollis", + "stellaria_media", + "solanum_nigrum", + "calochortus_amabilis", + "abies_lasiocarpa", + "campanula_rapunculus", + "melastoma_malabathricum", + "cystopteris_montana", + "diplotaxis_muralis", + "sciadopitys_verticillata", + "geranium_robertianum", + "hedysarum_coronarium", + "lepista_nuda", + "hippocrepis_comosa", + "verbena_officinalis", + "sigidilyas", + "prunus_domestica", + "platanus_hybrida", + "draba_verna", + "dendrocalamus_giganteus", + "tricholoma_aurantium", + "portulaca_grandiflora", + "chlorophyllum_molybdites", + "muscicapa_striata", + "prosopis_juliflora", + "acer_platanoides", + "cotoneaster_horizontalis", + "viburnum_prunifolium", + "gossypium_barbadense", + "erica_carnea", + "euphorbia_cyparissias", + "salvia_pratensis", + "delonix_regia", + "urtica_dioica", + "gymnadenia_conopsea", + "trifolium_repens", + "eugenia_uniflora", + "cortaderia_selloana", + "solanum", + "gentianella_amarella", + "ballota_nigra", + "campanula_carpatica", + "sisymbrium_officinale", + "angelica_archangelica", + "campsis_radicans", + "echinocactus_grusonii", + "medinilla_magnifica", + "corypha_umbraculifera", + "brachychiton_acerifolius", + "caragana_arborescens", + "sorbus_aucuparia", + "dianthus_chinensis", + "acer_pseudoplatanus", + "aristolochia_macrophylla", + "lotus_corniculatus", + "gymnadenia_odoratissima", + "polyporus_squamosus", + "raphanus_raphanistrum", + "cornus_florida", + "cytisus_multiflorus", + "amaranthus_caudatus", + "silene_latifolia", + "gymnocladus_dioica", + "botrychium_lunaria", + "fraxinus_velutina", + "anagallis_tenella", + "fagus_sylvatica", + "scleranthus_annuus", + "acrocarpus_fraxinifolius", + "salix_pentandra", + "rubus_spectabilis", + "drosophyllum_lusitanicum", + "crataegus_laevigata", + "sinapis_arvensis", + "acer_circinatum", + "arum", + "silene_uniflora", + "dracunculus_vulgaris", + "acacia_melanoxylon", + "cyperus_papyrus", + "agrostis_canina", + "saccharomyces_cerevisiae", + "boletus_edulis", + "kuliplor", + "campanula_trachelium", + "ranunculus_bulbosus", + "tetragonia_tetragonoides", + "erythronium_americanum", + "arenaria_serpyllifolia", + "lysimachia_vulgaris", + "daphne_cneorum", + "fraxinus_pennsylvanica", + "juglans_californica", + "campanula_rotundifolia", + "phytolacca_dioica", + "campanula_glomerata", + "lonicera_tatarica", + "dalbergia_latifolia", + "polystichum_aculeatum", + "gaultheria_procumbens", + "beta_vulgaris", + "cerastium_alpinum", + "pleurotus_ostreatus", + "pseudotsuga_menziesii", + "lithospermum_officinale", + "senna_alexandrina", + "heracleum_sphondylium", + "crataegus_aestivalis", + "drimys_winteri", + "lathyrus_sylvestris", + "marasmius_oreades", + "symphytum_officinale", + "rosa_moschata", + "viola_tricolor", + "viburnum_opulus", + "gentiana_acaulis", + "salvia_farinacea", + "elaeis_guineensis", + "coix_lacryma_jobi", + "erythronium_montanum", + "prunus_serrulata", + "galium_verum", + "acronicta_aceris", + "aralia_stipulata", + "cycas_circinalis", + "populus_nigra", + "nasturtium", + "ranunculus_repens", + "stellaria_holostea", + "strelitzia_reginae", + "agathis_australis", + "lemna_minor", + "larix_laricina", + "pyrola_rotundifolia", + "colocasia_esculenta", + "inga_edulis", + "spiranthes_spiralis", + "cardamine_pratensis", + "hypericum_calycinum", + "piper_betle", + "hypericum_maculatum", + "hypericum_perforatum", + "allium_fistulosum", + "salix_arctica", + "phacelia_campanularia", + "alnus_glutinosa", + "cypripedium_montanum", + "erodium_texanum", + "arrhenatherum", + "annona_reticulata", + "pinus_muricata", + "paris_quadrifolia", + "phytolacca_americana", + "nicotiana_rustica", + "reseda_odorata", + "lathyrus_sativus", + "oxalis", + "veronica_arvensis", + "anthriscus_sylvestris", + "pteridium_aquilinum", + "cinnamomum_cassia", + "panicum_capillare", + "smilax_aspera", + "salvia_sclarea", + "aristolochia_clematitis", + "catharanthus_roseus", + "cephalanthera_rubra", + "cypripedium_calceolus", + "viola_odorata", + "poa_nemoralis", + "corylus_cornuta", + "amaranthus_albus", + "lotus_tetragonolobus", + "arctostaphylos_uva_ursi", + "chrysanthemum", + "agrimonia", + "myrica_gale", + "vallisneria", + "holcus_mollis", + "crambe_maritima", + "erythrina_variegata", + "platanthera_chlorantha", + "rosa_banksiae", + "acer_glabrum", + "euphorbia_milii", + "begonia_tuberhybrida", + "castanea", + "physalis_peruviana", + "bilanghoy", + "sambucus_ebulus", + "rubus_odoratus", + "hamamelis_virginiana", + "calystegia_sepium", + "podocarpus_latifolius", + "dicksonia_antarctica", + "magnolia", + "galium_boreale", + "ulmus_hollandica", + "nephrolepis_exaltata", + "asclepias_meadii", + "pterocarpus_macrocarpus", + "phellodendron_amurense", + "hevea_brasiliensis", + "ranunculus_aquatilis", + "polypodium_vulgare", + "bromus_secalinus", + "pinus_palustris", + "conium_maculatum", + "plantago_media", + "ranunculus_acris", + "cypripedium_reginae", + "andromeda_polifolia", + "betula_papyrifera", + "rosa_damascena", + "platanthera_bifolia", + "camellia_japonica", + "tritoma" + ], + "PUBLIC_FIGURE": [ + "henry_cavendish", + "benjamin_franklin", + "martin_buber", + "akira_kurosawa", + "maria_tallchief", + "giovanni_boccaccio", + "cornelius_vanderbilt", + "ben_hogan", + "leonard_bernstein", + "che_guevara", + "c", + "henrik_ibsen", + "mary_shelley", + "jesucristo", + "david_livingstone", + "andrzej_wajda", + "jan_van_eyck", + "carl_rogers", + "richard_burton", + "douglas_macarthur", + "mary_wollstonecraft", + "john_jacob_astor", + "anna_pavlova", + "winston_churchill", + "u_sa", + "ivan_pavlov", + "dmitri_shostakovich", + "paul_mccartney", + "francis_crick", + "isaac_newton", + "victor_hugo", + "joseph_smith", + "edwin_hubble", + "milton_friedman", + "edward_gibbon", + "john_glenn", + "george_harrison", + "george_orwell", + "richard_wagner", + "pancho_villa", + "marie_curie", + "mary_martin", + "michael_jackson", + "carl_sandburg", + "thomas_hobbes", + "sa_yu", + "el_greco", + "david", + "galileo_galilei", + "jane_goodall", + "robert_koch", + "i_m_pei", + "george_eastman", + "john_steinbeck", + "erich_mendelsohn", + "edmund_hillary", + "vincent_van_gogh", + "anne_boleyn", + "thomas_paine", + "mary_pickford", + "emiliano_zapata", + "yuri_gagarin", + "giuseppe_verdi", + "karl_jaspers", + "konrad_adenauer", + "dahum", + "mark_rothko", + "gottlieb_daimler", + "frank_sinatra", + "abel_tasman", + "katharine_hepburn", + "henri_becquerel", + "henri_matisse", + "louis_pasteur", + "somateria_spectabilis", + "theodosius_i", + "hugo_grotius", + "john_ford", + "saladin", + "sarah_bernhardt", + "luigi_pirandello", + "hank_williams", + "charles_de_gaulle", + "y", + "ralph_bunche", + "charles_lindbergh", + "joseph_stalin", + "f", + "john_jay", + "ludwig_wittgenstein", + "thomas_mann", + "dante_alighieri", + "margot_fonteyn", + "peter_pan", + "giacomo_puccini", + "fridtjof_nansen", + "louis_braille", + "james_dean", + "roger_bannister", + "joseph_priestley", + "nicolas_poussin", + "andrea_mantegna", + "james_naismith", + "oscar_wilde", + "eli_whitney", + "laurence_olivier", + "francis_bacon", + "pete_seeger", + "william_hogarth", + "charles_baudelaire", + "david_ricardo", + "immanuel_kant", + "james_franck", + "warburg", + "saint_martin", + "titus", + "johannes_kepler", + "max_planck", + "william_blake", + "john_bardeen", + "carl_lewis", + "canberra", + "edward_jenner", + "oscar_robertson", + "oreonympha_nobilis", + "moises", + "cole_porter", + "jean_luc_godard", + "igor_stravinsky", + "patricio_han_irlanda", + "william_herschel", + "mikhail_baryshnikov", + "montesquieu", + "niels_bohr", + "bertrand_russell", + "michael_faraday", + "john_d_rockefeller", + "irving_berlin", + "rudolf_diesel", + "walt_disney", + "ted_williams", + "friedrich_engels", + "jane_austen", + "gustav_mahler", + "ed_sullivan", + "phil_collins", + "robert_redford", + "jack_dempsey", + "ian_fleming", + "richard_feynman", + "wolfgang_pauli", + "theodor_mommsen", + "marcel_proust", + "thomas_more", + "elizabeth_taylor", + "john_milton", + "ethel_merman", + "samuel_adams", + "indira_gandhi", + "myoxus_glis", + "george_gershwin", + "alfred_nobel", + "jesse_owens", + "marco_polo", + "macaca_nemestrina", + "caravaggio", + "allen_ginsberg", + "daniel_bernoulli", + "henri_bergson", + "hans_christian_andersen", + "cary_grant", + "pieter_zeeman", + "glenn_miller", + "pablo_picasso", + "marian_anderson", + "john_marshall", + "christiaan_huygens", + "hector_berlioz", + "lucille_ball", + "paul_simon", + "claudio_monteverdi", + "adam_smith", + "william_james", + "jean_harlow", + "henry_miller", + "karl_marx", + "paul_bunyan", + "friedrich_nietzsche", + "i", + "pedro", + "e_o_wilson", + "sandro_botticelli", + "nikola_tesla", + "al_capone", + "billy_graham", + "robert_schumann", + "mel_gibson", + "le_corbusier", + "john_locke", + "joseph_marie_jacquard", + "henry_james", + "helen_keller", + "ingrid_bergman", + "jean_piaget", + "henri_rousseau", + "h_g_wells", + "walt_whitman", + "william_wyler", + "ludwig_boltzmann", + "carl_jung", + "adolf_hitler", + "james_d_watson", + "peter_behrens", + "joseph_haydn", + "george_boole", + "edvard_grieg", + "robert_boyle", + "1", + "rosa_parks", + "samuel_goldwyn", + "ernest_walton", + "vladimir_putin", + "giuseppe_mazzini", + "jim_thorpe", + "don_budge", + "bill_russell", + "g", + "arthur_schopenhauer", + "james_cagney", + "johns_hopkins", + "martin_heidegger", + "hans_eysenck", + "arnold_schoenberg", + "r", + "george_lucas", + "andrew_jackson", + "louis_armstrong", + "steven_spielberg", + "st_louis_missouri", + "jean_monnet", + "d_w_griffith", + "robert_fulton", + "thomas_hardy", + "thomas_gainsborough", + "giuseppe_garibaldi", + "tamara_karsavina", + "johannes_gutenberg", + "amerigo_vespucci", + "emma_goldman", + "putin", + "robert_hooke", + "o_henry", + "karl_popper", + "john_calvin", + "peter_sellers", + "henry_clay", + "marcus_aurelius", + "peter_o'toole", + "william_shockley", + "peter_paul_rubens", + "mahatma_gandhi", + "jim_morrison", + "jules_verne", + "paul_newman", + "fyodor_dostoyevsky", + "john_roebling", + "jackson_pollock", + "john_lennon", + "andrea_palladio", + "bob_woodward", + "charlie_chaplin", + "piscis_austrinus", + "alice_walker", + "andrei_sakharov", + "george_marshall", + "bungol", + "stanley_kubrick", + "john_huston", + "william_gilbert", + "james_watt", + "ronald_reagan", + "jenny_lind", + "frederick_douglass", + "david_hilbert", + "oliver_cromwell", + "frank_capra", + "woodrow_wilson", + "margaret_sanger", + "richard_rodgers", + "don_quixote", + "jim_henson", + "ernest_hemingway", + "george_westinghouse", + "aquila", + "arthur_miller", + "nelson_mandela", + "al_gore", + "j_p_morgan", + "roald_amundsen", + "richard_leakey", + "charles_dickens", + "wallace_carothers", + "federico_fellini", + "willy_brandt", + "francisco_pizarro", + "francisco_franco", + "jackie_robinson", + "bernardo_bertolucci", + "andrew_carnegie", + "franz_schubert", + "johnny_cash", + "alfred_kastler", + "mick_jagger", + "georges_cuvier", + "william_harvey", + "vladimir_lenin", + "jonathan_swift", + "walter_gropius", + "albert_einstein", + "robert_joffrey", + "thomas_edison", + "chiang_kai_shek", + "marie_antoniette", + "raymond_chandler", + "t" + ], + "ANIMAL": [ + "terenura_sharpei", + "acherontia", + "apodemus", + "monachus_schauinslandi", + "buteo", + "mamalya", + "lumuan", + "lemmus_lemmus", + "sitta_europaea", + "mirounga_leonina", + "kunduz", + "canis_minor", + "hippotragus_niger", + "sitta_carolinensis", + "carduelis", + "pisces", + "mantodea", + "pieris_brassicae", + "brachypteraciidae", + "bangk\u00e2", + "micropterus", + "perca_flavescens", + "bukaw", + "karabaw", + "gerbillus_jamesi", + "prunus_tenella", + "accipiter", + "manaol", + "pinctada_margaritifera", + "balanak", + "donald_duck", + "takray", + "salmo_salar", + "sanicula_europaea", + "corallium_rubrum", + "martes_foina", + "ammospermophilus", + "ictiobus_niger", + "megascops", + "capreolus_capreolus", + "branta_bernicla", + "arthropoda", + "sarcophagidae", + "bulgan", + "alle_alle", + "sitta_canadensis", + "mantis", + "zeus_faber", + "salvelinus_fontinalis", + "gorilla_gorilla", + "martes_zibellina", + "peristediidae", + "pedunculata", + "arvicola" + ], + "ORG": [ + "pula_nga_dagat", + "shinto", + "inaleman", + "jan_mayen", + "aa", + "nasa", + "bollywood", + "germanistika", + "san_francisco", + "gao", + "kolehiyo", + "can_tho", + "saint_helena", + "pag_uma", + "bangko_sentral", + "chiang_mai", + "taoismo", + "iskwilahan", + "rabindranath_tagore", + "al_a\u00efn", + "gestapo", + "bisperas_han_bag_o_nga_tuig", + "winnie_the_pooh", + "hin_o", + "tra_vinh", + "sao_tome", + "i_ching", + "chiang_rai", + "panmilitar_nga_akademya", + "disa", + "addis_ababa", + "nautilus_pompilius", + "ursa_major", + "saint_barth\u00e9lemy", + "imperyo_han_alemanya", + "los_angeles", + "pakiana", + "partido_politikal", + "kasundalohan", + "balaud_sibil", + "kolehiyo_elektoral", + "partido_demokrata", + "hirundo_rustica", + "hardin_botaniko", + "partido_republicano" + ], + "LOCATION": [ + "danaw_superior", + "hai_duong", + "plantago_lanceolata", + "estados_unidos", + "trifolium_pratense", + "dryocopus_martius", + "eryngium_maritimum", + "piet_mondrian", + "ha_long", + "trifolium_repens", + "sint_maarten", + "trois_rivi\u00e8res", + "crist\u00f3bal_col\u00f3n", + "iris_pseudacorus", + "pieris_rapae", + "plantago_major", + "darag_nga_salog", + "vaccinium_oxycoccos", + "plantago_media", + "alnus_glutinosa", + "hat_yai", + "sri_lanka", + "bukid_santa_helena", + "scutellaria_galericulata", + "the_rolling_stones", + "kryvyi_rih", + "pieris_brassicae", + "al_a\u00efn", + "trifolium_dubium", + "pterocarpus_indicus", + "santa_claus", + "kus\u00f3g_pan_igbaw", + "delonix_regia", + "prunus_avium" + ], + "FAC": [ + "arnold_schoenberg", + "singbahan_katoliko", + "pedro_nga_harangdon", + "an_urhi_nga_pangiklop", + "the_four_seasons", + "santa_lucia" + ], + "QUANTITY": [ + "rupee", + "g" + ], + "FOOD": [ + "citrus_aurantiifolia", + "sopdrink", + "hatok", + "symphytum_officinale", + "daucus_carota", + "vigna_unguiculata", + "capsicum", + "pamahaw", + "sodium_chloride", + "sorbetes", + "bunay", + "chile", + "nasasamsam_nga_goma", + "desyerto", + "juglans_regia" + ], + "DATE": [ + "pamur\u00edng", + "kadayaw" + ], + "BIO_CHEM_ENTITY": [ + "betsin" + ], + "PRODUCT": [ + "justin_bieber", + "fyodor_dostoyevsky", + "diego_garcia", + "echinopsis_pachanoi", + "julius_caesar", + "the_four_seasons", + "don_quixote", + "sachsen_anhalt", + "the_lord_of_the_rings", + "s\u00e3o_tom\u00e9_ngan_pr\u00edncipe", + "mario_andretti", + "katungod_pantawo", + "reino_unido", + "nordrhein_westfalen" + ], + "RELIGION": [ + "zen", + "shinto", + "presbiterianismo", + "islam", + "calvinismo", + "sunni_islam" + ], + "JOB": [ + "alkalde", + "inhenyero", + "yatot", + "sayantista", + "paralegal", + "mangulo", + "sculptor", + "comersyante", + "stroke", + "manunurat", + "rabino", + "wetter" + ], + "GENDER": [ + "babaye", + "lalaki" + ], + "DISEASE": [ + "anthrax", + "sipilis", + "rabies", + "trangkaso", + "stroke", + "ul_ul", + "punggod", + "hangga", + "maws", + "sakit_nga_ebola", + "katurog", + "pica", + "ul_ol", + "altapresyon", + "arkoholismo", + "poliomyelitis", + "malarya", + "kanser", + "materyalismo", + "su_ol" + ], + "POLITICAL_PARTY_MEMBER": [ + "menshevik" + ], + "PERSON": [ + "julius_caesar", + "al_gore", + "h_g_wells", + "i_ching", + "e_o_wilson", + "boletus_edulis" + ], + "LANGUAGE": [ + "inesperanto", + "sinanskrit", + "linatin", + "hindi", + "tonga" + ], + "GPE": [ + "dar_es_salaam", + "sint_maarten", + "pandanus_tectorius", + "hagia_sophia", + "ha_tinh", + "pula_nga_dagat", + "borassus_flabellifer", + "hibiscus_rosa_sinensis", + "vinh_long", + "tra_vinh", + "parke_industriyal", + "salog_san_lorenzo", + "busag_nga_balay" + ], + "PERSON_PRONOUN": [ + "i" + ], + "SOC_ECO_CLASS": [ + "samurai", + "katiringban" + ], + "RACE": [ + "busag" + ], + "POLITICAL_PARTY": [ + "kuomintang" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "heroina": "heros", + "sista": "monachus", + "queens": "mga_hadi", + "babaye": "lalaki", + "lalaki": "babaye" + }, + "other_gender_swap": {}, + "en_pronoun2gender": { + "he": [ + "lalaki" + ], + "she": [ + "babaye" + ] + }, + "en_pronoun2pronoun": { + "he": [ + "iya" + ], + "she": [ + "iya" + ], + "it": [ + "i_ni", + "tyto" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/wau.json b/data_tooling/pii_processing/ontology/data/wau.json new file mode 100644 index 0000000..8556834 --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/wau.json @@ -0,0 +1,25 @@ +{ + "GENDER": [ + "toneju" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": {}, + "other_gender_swap": {}, + "en_pronoun2gender": { + "she": [ + "toneju" + ] + }, + "en_pronoun2pronoun": {}, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/wo.json b/data_tooling/pii_processing/ontology/data/wo.json new file mode 100644 index 0000000..06e78de --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/wo.json @@ -0,0 +1,79 @@ +{ + "PLANT": [ + "lepp", + "dugoor", + "pulloox", + "karoot", + "ariko" + ], + "GENDER": [ + "guy" + ], + "ANIMAL": [ + "wundu", + "looy", + "saafaandu", + "warapul\u00f3", + "ganaar" + ], + "PUBLIC_FIGURE": [ + "piyeer" + ], + "DISEASE": [ + "bunt", + "suba", + "janax" + ], + "FOOD": [ + "tiga_dege" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "buumi": "b\u00fbr", + "mag_ju_jig\u00e9en": "r\u00e0kk_ju_g\u00f3or", + "rakk_ju_jig\u00e9en": "dimas" + }, + "other_gender_swap": { + "wao": "moom", + "\u00f1oom": "moom", + "tey": "moom", + "moom": "wao" + }, + "en_pronoun2gender": { + "he": [ + "guy" + ], + "she": [ + "jig\u00e9en" + ] + }, + "en_pronoun2pronoun": { + "he": [ + "siin", + "moom" + ], + "she": [ + "moom" + ], + "they": [ + "wao", + "leen", + "tey", + "\u00f1oom" + ], + "it": [ + "moom" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/wym.json b/data_tooling/pii_processing/ontology/data/wym.json new file mode 100644 index 0000000..1344c19 --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/wym.json @@ -0,0 +1,49 @@ +{ + "PUBLIC_FIGURE": [ + "e" + ], + "JOB": [ + "bisk\u00fcp", + "rodmaher", + "katachet" + ], + "ORG": [ + "baon", + "draowa" + ], + "FOOD": [ + "faonk\u00fcch" + ], + "DISEASE": [ + "maojs" + ], + "PLANT": [ + "wajd" + ], + "DATE": [ + "nomastaog" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "kazeryn": "kazer" + }, + "other_gender_swap": {}, + "en_pronoun2gender": { + "she": [ + "b\u014dw", + "fraoj" + ] + }, + "en_pronoun2pronoun": {}, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/xcl.json b/data_tooling/pii_processing/ontology/data/xcl.json new file mode 100644 index 0000000..1ee519c --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/xcl.json @@ -0,0 +1,64 @@ +{ + "ORG": [ + "\u056c\u0565\u0561\u057c\u0576_\u0571\u056b\u0569\u0565\u0576\u0565\u0561\u0581" + ], + "JOB": [ + "\u0578\u0582\u057d\u0578\u0582\u0581\u056b\u0579", + 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new file mode 100644 index 0000000..ca42744 --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/za.json @@ -0,0 +1,91 @@ +{ + "ORG": [ + "hagdangz", + "dahvangzhoz", + "va", + "sawfuengz", + "gozminzdangj", + "sa" + ], + "PLANT": [ + "maenzfaex", + "lauxbaeghoengz", + "goliux", + "moegsawz", + "maklangz", + "makmaenj" + ], + "FOOD": [ + "ciengqyouz" + ], + "PUBLIC_FIGURE": [ + "a" + ], + "SOC_ECO_CLASS": [ + "sevei" + ], + "FAC": [ + "guengjciengz" + ], + "JOB": [ + "lauxsae", + "canghyw", + "gingjcaz" + ], + "DISEASE": [ + "bingh", + "haeb" + ], + "LOCATION": [ + "meijgoz", + "meijcouh" + ], + "EVENT": [ + "singj" + ], + "RELIGION_MEMBER": [ + "beixneungx" + ], + "OTHER_PRONOUN": [ + "it" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "beixmbwk": "nuengx", + "dahnuengx": "beix", + "nuengx": "beix", + 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"\u7687", + "\u6b63\u5bae\u5a18\u5a18": "\u8056\u4e0a", + "\u7687\u540e": "\u541b\u738b", + "\u5973\u540c\u80de": "\u7537\u58eb", + "\u96cc\u6027": "\u7537\u4eba", + "\u8a31\u5ac1": "\u8a31\u5a5a", + "\u7ae5\u5973": "\u7537\u5a03", + "\u5c0f\u59b9": "\u963f\u5144", + "\u4e2b\u982d": "\u7537\u5a03", + "\u4e2b": "\u7537\u5a03", + "\u599e": "\u7537\u5a03", + "\u5973\u5b69": "\u5c0f\u4f19\u5b50", + "\u59b9\u5b50": "\u7537\u5a03", + "\u4e2b\u5934": "\u7537\u5a03", + "\u59ae": "\u7537\u5a03", + "\u5973\u5a03": "\u7537\u5a03", + "\u5973\u5b69\u5b50": "\u7537\u5a03", + "\u59c9": "\u7537\u5a03", + "\u5aac": "\u7701\u957f", + "\u59e5": "\u5dde\u9577", + "\u5916\u5b59\u5973\u513f": "\u5b59", + "\u5b59\u5973\u513f": "\u5916\u5b59\u5b50", + "\u5916\u5b6b\u5973": "\u5b59", + "\u5b6b\u5973\u5152": "\u5916\u5b59\u5b50", + "\u5916\u5b59\u5973": "\u5b59", + "\u5b59\u5973": "\u5916\u5b6b\u5b50", + "\u5916\u5b6b\u5973\u5152": "\u5916\u5b59\u5b50", + "\u5b6b\u5973": "\u5916\u5b59", + "\u7956\u6bcd": 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+ "\u8131\u9776", + "\u4e2b\u982d\u7247\u5b50", + "\u59b9\u5b50", + "\u59ae\u5b50", + "\u59ec\u4f6c", + "\u5dfe\u5e3c", + "\u9ec4\u82b1\u95fa\u5973", + "\u59c9", + "\u6dd1\u5973", + "\u95ab", + "\u599e", + "\u9ec3\u82b1\u59d1\u5a18", + "\u4f8d\u5973", + "\u4e2b\u5934\u7247\u5b50", + "\u5973\u540c\u80de", + "\u59ae", + "\u8aa4\u8eca", + "\u5973\u4f63", + "\u7737\u604b", + "\u7ae5\u5973", + "\u95fa\u5973", + "\u4e2b\u73af", + "\u6b27\u5c3c", + "\u5aad", + "\u7d05\u7c89", + "\u5931\u6389", + "\u9519\u8fc7", + "\u8d35\u5987", + "\u857e\u4e1d\u8fb9", + "\u604b\u5ff5", + "\u857e\u7d72\u908a", + "\u5987", + "\u9ec4\u82b1\u59d1\u5a18", + "\u8655\u5973", + "\u5973\u7684", + "\u9b42\u7275\u68a6\u8426", + "\u957f\u59ca", + "\u8e49", + "\u9057\u6f0f", + "\u59ec", + "\u7737\u6200", + "\u5973\u5b69", + "\u9ec4\u82b1\u5e7c\u5973", + "\u5e7c\u5973", + "\u5973\u7ae5" + ] + }, + "en_pronoun2pronoun": { + "he": [ + "\u6039", + "lia", + "\u4f62", + "\u3078", + "\u53f0\u4e0b" + ], + "she": [ + "\u5979", + "\u4f62", + "\u6039", + "\u4f0a\u4eba" + ], + "they": [ + "\u4ed6\u4eec", + "\u5b83\u5011", + "lia", + "\u4ed6\u5011", + "\u5979\u4eec", + "\u5979\u5011", + "uk", + "\u5b83\u4eec" + ], + "it": [ + "\u60c5\u5831\u6280\u8853", + "\u65af", + "\u7260", + "\u8fd9\u4e9b", + "\u9019\u4f4d", + "\u90a3\u4e9b", + "\u9019\u7a2e", + "\u672c\u8eab", + "\u9019\u4e9b", + "\u8fd9\u4e2a", + "\u8fd9\u4f4d", + "\u90a3\u79cd", + "\u90a3\u7a2e", + "\u6041", + "\u4e2a", + "\u8fd9\u4e9b\u4e2a", + "\u5b83\u672c\u8eab", + "\u8fd9\u79cd", + "\u9019\u4e9b\u500b", + "\u4fe1\u606f\u6280\u8853", + "\u4fe1\u606f\u6280\u672f", + "\u5b83", + "\u8fd9", + "\u9019\u500b", + "\u55f0", + "\u6b64", + "\u963f\u5835" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/zu.json b/data_tooling/pii_processing/ontology/data/zu.json new file mode 100644 index 0000000..8b7b0e6 --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/zu.json @@ -0,0 +1,86 @@ +{ + "LANGUAGE": [ + "shona", + "isafrikansi" + ], + "ANIMAL": [ + "inkentshane", + "ingobe", + "isikhova", + "iselesele", + "impangele", + "impalampala" + ], + "PRODUCT": [ + "inyuzilandi", + "isihlahla_sikakhisimuzi" + ], + "PERSON_PRONOUN": [ + "thina" + ], + "PLANT": [ + "jova", + "ikhalothi" + ], + "PUBLIC_FIGURE": [ + "u" + ], + "JOB": [ + "umelaphi", + "inkosi" + ], + "FOOD": [ + "u_ayisikhilimu" + ], + "DISEASE": [ + "mi", + "noma" + ], + "ORG": [ + "mi" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "unyoko": "ubaba", + "umama": "uyihlo", + "unina": "ubaba", + "indlovukazi": "inkosi", + "usisi": "ubhuti", + "udade": "ubhuti", + "unkosikazi": "indoda", + "inkosikazi": "umkhwenyana", + "umka": "umkhwenyana" + }, + "other_gender_swap": {}, + "en_pronoun2gender": { + "he": [ + "umfana" + ], + "she": [ + "inkosikazi", + "umfazi" + ] + }, + "en_pronoun2pronoun": { + "he": [ + "khe" + ], + "she": [ + "khe" + ], + "it": [ + "khe" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/data/zza.json b/data_tooling/pii_processing/ontology/data/zza.json new file mode 100644 index 0000000..f26c07d --- /dev/null +++ b/data_tooling/pii_processing/ontology/data/zza.json @@ -0,0 +1,98 @@ +{ + "PLANT": [ + "pine" + ], + "GENDER": [ + "ceni", + "boy" + ], + "PUBLIC_FIGURE": [ + "bari", + "e", + "a", + "most", + "o" + ], + "ORG": [ + "nara", + "va", + "ez_to_sinena", + "mektev", + "mi", + "sa", + "cond" + ], + "TITLE": [ + "sir" + ], + "PERSON_PRONOUN": [ + "emara", + "m\u0131", + "her" + ], + "ANIMAL": [ + "hermu\u015f\u0131k" + ], + "DISEASE": [ + "gharm", + "surani", + "zerdani", + "gherm", + "mi", + "cengar", + "helpeze", + "merre" + ], + "LANGUAGE": [ + "franski" + ], + "JOB": [ + "degme", + "ma'lim", + "resber" + ], + "FIRST_NAME_MALE": [], + "LAST_NAME_MALE": [], + "FIRST_NAME_FEMALE": [], + "LAST_NAME_FEMALE": [], + "FIRST_NAME": [], + "LAST_NAME": [], + "SUFIX_MALE": [], + "SUFIX_FEMALE": [], + "binary_gender_swap": { + "c\u0131n\u00e9k": "m\u00ear", + "khatun": "m\u00earde", + "xatun": "m\u00earde", + "cen\u00ee": "m\u00ear", + "c\u0131ni": "m\u00ear", + "ceni": "m\u00ear" + }, + "other_gender_swap": {}, + "en_pronoun2gender": { + "he": [ + "m\u00ear", + "boy" + ], + "she": [ + "cen\u00ee", + "ceni", + "c\u0131ni" + ] + }, + "en_pronoun2pronoun": { + "he": [ + "eyr\u00ea", + "siya", + "eyeri", + "ayr\u00ea" + ], + "she": [ + "siya", + "her" + ] + }, + "en_pronoun2title": {}, + "PREFIX_MALE": [], + "PREFIX_FEMALE": [], + "person2religion": {} +} \ No newline at end of file diff --git a/data_tooling/pii_processing/ontology/ontology_buider.py b/data_tooling/pii_processing/ontology/ontology_buider.py new file mode 100644 index 0000000..84cc76c --- /dev/null +++ b/data_tooling/pii_processing/ontology/ontology_buider.py @@ -0,0 +1,1217 @@ +# coding=utf-8 +# Copyright, 2021 Ontocord, LLC, All rights reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +from random import sample +import glob, os, re +import multiprocessing + +import gzip +import os, argparse +import itertools +from collections import Counter, OrderedDict +import os +import json +import threading +import numpy as np +import os +import time +import json +import copy +#from sklearn.cluster import AgglomerativeClustering +from time import time +import numpy as np +from nltk.corpus import wordnet as wn +from collections import Counter +from itertools import chain +import os +#from joblib import dump, load +#from joblib import Parallel, delayed +import glob +import os +import json +import math, os +import random +import transformers +mt5_underscore= "▁" +trannum = str.maketrans("0123456789", "1111111111") +import sys, os +import json +import faker + +from faker.providers import person, job + +from collections import Counter +import re +import gzip +import urllib +import re +from nltk.corpus import wordnet as wn +import transformers + +sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), + os.path.pardir, os.path.pardir, os.path.pardir))) +from data_tooling.pii_processing.ontology.ontology_manager import OntologyManager +from data_tooling.pii_processing.ontology.ontology_builder_data import OntologyBuilderData + +class OntologyBuilder (OntologyManager, OntologyBuilderData): + + def __init__(self, data_dir=None, tmp_dir=None): + OntologyManager.__init__(self, data_dir=data_dir, tmp_dir=tmp_dir) + + self.word2en = {} + + def load_cn_data(self): + tmp_dir = self.tmp_dir + data_dir = self.data_dir + if not os.path.exists(f"{tmp_dir}/conceptnet-assertions-5.7.0.csv"): + if not os.path.exists(f"{tmp_dir}/conceptnet-assertions-5.7.0.csv.gz"): + os.system(f"wget https://s3.amazonaws.com/conceptnet/downloads/2019/edges/conceptnet-assertions-5.7.0.csv.gz") + os.system(f"mv ./conceptnet-assertions-5.7.0.csv.gz {tmp_dir}") + os.system(f"gzip -d {tmp_dir}/conceptnet-assertions-5.7.0.csv.gz") + + def create_wn_cat(self, keep_percentage=.01): + """ + extract linkage from conceptnet words and wordnet category words + """ + self.load_cn_data() + tmp_dir = self.tmp_dir + data_dir = self.data_dir + if not os.path.exists(f"{tmp_dir}/wn.csv"): + os.system(f"grep '\/wn\/' {tmp_dir}/conceptnet-assertions-5.7.0.csv > {tmp_dir}/wn.csv") + wn = open(f"{tmp_dir}/wn.csv", "rb").read().decode().split('\n') + wn = [s.split('\t')[0] for s in wn] + wn = [s.strip(']').split(',/c/')[1:] for s in wn] + + wn_list = itertools.chain(*[[w.split("/")[1] if w.split("/")[-2] == "wn" else w.split("/")[-2] for w in awn if "_" in w] for awn in wn]) + items = list(Counter([w for w in wn_list if w[0] not in "0123456789"]).items()) + items.sort(key=lambda a:a[1], reverse=True) + items = [i for i in items if i[1] != 1] + typeHash = dict( items[:int(len(items)*keep_percentage)]) + wn_list2 = itertools.chain(*[[w for w in awn if (w.split("/")[2] == 'n') and (w.split("/")[0] != 'en') and ("_" in w.split("/")[1]) and (w.split("/")[-2] in typeHash)] for awn in wn]) + items2 = list(Counter([w for w in wn_list2 if w[0] not in "0123456789"]).items()) + items2.sort(key=lambda a:a[1], reverse=True) + return items2, typeHash + + def create_rel(self): + """ + extract words that are related to each other based on conceptnet. + We need to expand the connections between words to find more related nouns. + Conceptnet maps words too broadly so we need to restrict the relationships. + It's unclear if we should expand this much though. + """ + self.load_cn_data() + tmp_dir = self.tmp_dir + data_dir = self.data_dir + if not os.path.exists(f"{tmp_dir}/syn.csv"): + os.system(f"grep '\/r\/Synonym\/' {tmp_dir}/conceptnet-assertions-5.7.0.csv > {tmp_dir}/syn.csv") + if not os.path.exists(f"{tmp_dir}/sim.csv"): + os.system(f"grep 'SimilarTo\/' {tmp_dir}/conceptnet-assertions-5.7.0.csv > {tmp_dir}/sim.csv") + if not os.path.exists(f"{tmp_dir}/deri.csv"): + os.system(f"grep 'DerivedFrom\/' {tmp_dir}/conceptnet-assertions-5.7.0.csv > {tmp_dir}/deri.csv") + if not os.path.exists(f"{tmp_dir}/erel.csv"): + os.system(f"grep 'EtymologicallyRelatedTo\/' {tmp_dir}/conceptnet-assertions-5.7.0.csv > {tmp_dir}/erel.csv") + if not os.path.exists(f"{tmp_dir}/ederi.csv"): + os.system(f"grep 'EtymologicallyDerivedFrom\/' {tmp_dir}/conceptnet-assertions-5.7.0.csv > {tmp_dir}/ederi.csv") + if not os.path.exists(f"{tmp_dir}/rel.csv"): + os.system(f"grep 'RelatedTo\/' {tmp_dir}/conceptnet-assertions-5.7.0.csv > {tmp_dir}/rel.csv") + if not os.path.exists(f"{tmp_dir}/formof.csv"): + os.system(f"grep 'FormOf\/' {tmp_dir}/conceptnet-assertions-5.7.0.csv > {tmp_dir}/formof.csv") + if not os.path.exists(f"{tmp_dir}/isa.csv"): + os.system(f"grep 'IsA\/' {tmp_dir}/conceptnet-assertions-5.7.0.csv > {tmp_dir}/isa.csv") + rel2 = OrderedDict() + for rel_type in ('syn', 'sim', 'deri', 'erel', 'ederi', 'rel', 'formof','isa') : #'dest', 'anti', 'manner', + i = 0 + with open(f"{tmp_dir}/{rel_type}.csv", "rb") as f: + while True: + rel = f.readline() + if not rel: break + rel = rel.decode() + rel = rel.split('\t')[0] + rel = rel.strip(']').split(',/c/')[1:] + if not rel: + continue + else: + if len(rel) < 2: + continue + a = rel[0] + b = rel[1] + a = a.split('/') + lang1 = a[0] + a = a[1] + b = b.split('/') + lang2 = b[0] + b = b[1] + if a == b: + continue + val = [a,b] + if len(a) > len(b): + if a in rel2: + val = rel2[a] + [a,b] + del rel2[a] + rel2[b] = rel2.get(b, []) + val + else: + if b in rel2: + val = rel2[b] + [a,b] + del rel2[b] + rel2[a] = rel2.get(a, []) + val + #i+= 1 + #if i > 10000: + # break + for key in list(rel2.keys()): + rel2[key] = list(set(rel2[key])) + + return rel2 + + def create_cn_ontology(self): + tmp_dir = self.tmp_dir + data_dir = self.data_dir + if os.path.exists(f"{tmp_dir}/conceptnet_ontology.json"): + return json.load(open(f"{tmp_dir}/conceptnet_ontology.json", "rb")), json.load(open(f"{tmp_dir}/conceptnet_ontology_cat2word.json", "rb")) + categories, typeHash = self.create_wn_cat(1.0) + rel = self.create_rel() + word2wncat = OrderedDict() + #get a word to category mapping + for concept, ct in categories: + conceptArr = concept.split("/") + word, wncat = conceptArr[1], conceptArr[-2] + if wncat == 'linkdef': + continue + if word in word2wncat: + if wncat != word2wncat[word]: + word2wncat[word]='*' + else: + word2wncat[word] = wncat + + rel2=OrderedDict() + rel3=OrderedDict() + #group by categories, while expanding the categories + for key, val in rel.items(): + if len(val) < 6: + val2 = [(word2wncat[v] if v in word2wncat else (word2wncat[v.split("_")[0]] if v.split("_")[0] in word2wncat else word2wncat[v.split("_")[-1]]),v) for v in val if (v in word2wncat) or (v.split("_")[0] in word2wncat) or (v.split("_")[-1] in word2wncat)] + if val2: + val3 = [v for v in val if v not in val2] + itr = itertools.groupby(val2, lambda x : x[0]) + groups = [(key, list(group)) for key, group in itr] + groups.sort(key=lambda a: len(a[1])) + max_cat = groups[-1][0] + + if max_cat != '*': + # infer category of other words in this group if majority of labels is max_cat + if len(groups[-1][1])*2 >= len(val): + for word in val3: + if word in word2wncat: + if wncat != word2wncat[word]: + word2wncat[word]='*' + else: + groups[-1][1].append((max_cat, word)) + else: + word2wncat[word] = max_cat + groups[-1][1].append((max_cat, word)) + all = {} + for key, group in groups: + if key == '*': continue + group= list(group) + if len(group) == 1: + continue + group = [g[1] for g in group] + group.sort(key=lambda s: len(s)) + rel2[group[0]] = list(set(rel2.get(group[0],[]) + group)) + for g in group: + all[g]=1 + val = [v for v in val if v not in all] + if val: + val.sort(key=lambda a: len(a)) + rel3[val[0]] = list(set(rel3.get(val[0],[])+val)) + + #group by common prefix, infix, or suffix + + for key, val in rel3.items(): + val.sort(key=lambda a: len(a)) + len_val = len(val) + for rng in range(0, len_val, 5): + all = {} + max_rng = min(rng+5, len_val) + val2 = val[rng:max_rng] + len_val2=len(val2) + val2 = copy.deepcopy(val2) + copy_val2 = copy.deepcopy(val2) + for idx2, word in enumerate(copy_val2): + if len(word) <= 4: + continue + for idx in range(idx2+1, len_val2): + if type(val2[idx]) is tuple: + continue + if type(val2[idx]) is str and (word in val2[idx] or val2[idx].startswith(word[:-1]) or val2[idx].startswith(word[:-2]) or val2[idx].startswith(word[:-3]) or val2[idx].endswith(word[1:]) or val2[idx].endswith(word[2:]) or val2[idx].endswith(word[2:])): + val2[idx] = (word, val2[idx]) + val2 = [v for v in val2 if type(v) is tuple] + itr = itertools.groupby(val2, lambda x : x[0]) + for key, group in itr: + rel2[key] = list(set(rel2.get(key,[key]) + [v[1] for v in group])) + all[key] = 1 + for v in group: + all[v[1]] = 1 + #val3 = [v for v in val[rng:max_rng] if v not in all] + #if val3: + # rel2[val3[0]] = val3 + + print ('rel', len(rel), 'rel2', len(rel2), 'word2wncat', len(word2wncat)) + cat2word={} + for key, value in word2wncat.items(): + cat2word[value]=cat2word.get(value,[])+[key] + json.dump(rel2, open(f"{tmp_dir}/conceptnet_ontology.json", "w", encoding="utf8"), indent=1) + json.dump(cat2word, open(f"{tmp_dir}/conceptnet_ontology_cat2word.json", "w", encoding="utf8"), indent=1) + return rel2, cat2word + + def create_eng2multilang_dict(self): + tmp_dir = self.tmp_dir + if hasattr(self, 'word2lang') and self.word2lang: return + if os.path.exists(f"{tmp_dir}/conceptnet_en.json"): + self.en = json.load(open(f"{tmp_dir}/conceptnet_en.json", "rb")) + self.word2en = json.load(open(f"{tmp_dir}/conceptnet_word2en.json", "rb")) + self.word2lang= json.load(open(f"{tmp_dir}/conceptnet_word2lang.json", "rb")) + return + self.load_cn_data() + if not os.path.exists(f"{tmp_dir}/syn.csv"): + os.system(f"grep '\/r\/Synonym\/' {tmp_dir}/conceptnet-assertions-5.7.0.csv > {tmp_dir}/syn.csv") + mt5_tok = transformers.AutoTokenizer.from_pretrained("google/mt5-small") + rel2 = OrderedDict() + word2lang = {} + for rel_type in ('syn', ) : + i = 0 + rel = open(f"{tmp_dir}/{rel_type}.csv", "rb").read().decode().split('\n') + rel = [s.split('\t')[0] for s in rel] + rel = [s.strip(']').split(',/c/')[1:] for s in rel] + for s in rel: + if len(s) < 2: + continue + a = s[0] + b = s[1] + a = a.split('/') + lang1 = a[0] + + a = a[1] + b = b.split('/') + lang2 = b[0] + b = b[1] + word2lang[a.replace(" ", "_").replace("-", "_").lower().strip(".")] = list(set(word2lang.get(a.replace(" ", "_").replace("-", "_").lower().strip("."), [])+[lang1])) + word2lang[b.replace(" ", "_").replace("-", "_").lower().strip(".")] = list(set(word2lang.get(b.replace(" ", "_").replace("-", "_").lower().strip("."), [])+[lang2])) + if a == b: + continue + if lang2 == 'en': + tmp = b + b = a + a = tmp + if lang1 in ('zh', 'ja', 'ko') and self.cjk_detect(a): + a = "_".join(mt5_tok.tokenize(a)).replace(mt5_underscore,"_").replace("__", "_").replace("__", "_").strip("_") + #print (a) + if lang2 in ('zh', 'ja', 'ko') and self.cjk_detect(b): + b = "_".join(mt5_tok.tokenize(b)).replace(mt5_underscore,"_").replace("__", "_").replace("__", "_").strip("_") + val = [a,b] + if lang1 != 'en' and lang2 != 'en': continue + if lang1 == 'en' and lang2 == 'en': continue + if True: + #if b in rel2: + # val = rel2[b] + [a,b] + # del rel2[b] + rel2[a] = rel2.get(a, []) + val + i+= 1 + #if i > 10000: + # break + + for key in list(rel2.keys()): + rel2[key] = list(set(rel2[key])) + self.en = rel2 + word2en = {} + for r, words in rel2.items(): + for word in words: + word2en[word] = set(list(word2en.get(word, []))+ [r]) + self.word2en = word2en + self.word2lang = word2lang + for key in list(self.word2en.keys()): + self.word2en[key] = dict([(a,1) for a in self.word2en[key]]) + json.dump(self.en, open(f"{tmp_dir}/conceptnet_en.json", "w", encoding="utf8"), indent=1) + json.dump(self.word2en, open(f"{tmp_dir}/conceptnet_word2en.json", "w", encoding="utf8"), indent=1) + json.dump(self.word2lang, open(f"{tmp_dir}/conceptnet_word2lang.json", "w", encoding="utf8"), indent=1) + + + def cjk_detect(self, texts): + # korean + if re.search("[\uac00-\ud7a3]", texts): + return "ko" + # japanese + if re.search("[\u3040-\u30ff]", texts): + return "ja" + # chinese + if re.search("[\u4e00-\u9FFF]", texts): + return "zh" + return None + + def yago_step0(self): + tmp_dir = self.tmp_dir + data_dir = self.data_dir + aHash = {} + onto = {} + catAll = {} + if os.path.exists(f"{tmp_dir}/yago0.tsv"): + return + if not os.path.exists(f"{tmp_dir}/yago-wd-simple-types.nt.gz"): + os.system("wget https://yago-knowledge.org/data/yago4/full/2020-02-24/yago-wd-simple-types.nt.gz") + os.system(f"mv ./yago-wd-simple-types.nt.gz {tmp_dir}") + with gzip.open(f"{tmp_dir}/yago-wd-simple-types.nt.gz") as f: #gzip. + with open(f"{tmp_dir}/yago0.tsv", "w", encoding="utf8") as o: + while True: + line = f.readline() + if not line: break + line = line.decode() + entity, rel, cat, _ = [l.split("/")[-1].strip(" .>") for l in line.split(">")] + if "_" in entity: + entityArr = entity.split("_") + _id = entityArr[-1] + entity = aHash[_id]= urllib.parse.unquote("_".join(entityArr[:-1]).split("(")[0].lower().replace("-","_").replace("__","_").strip("_")).strip(self.strip_chars) + else: + entity = aHash.get(entity, urllib.parse.unquote(entity.split("(")[0].lower().replace("-","_").replace("__","_").strip("_")).strip(self.strip_chars)) + if rel=="22-rdf-syntax-ns#type": + if entity: + cat=re.sub(r'(? 2: + #print (entityArr) + entity=entity.strip(".") + entityArr = entity.split("_") + if entityArr[-1] in {"a", "and", "the", "or", "the", "of", "to", "in", "on", "from"}: + entity = "_".join(entityArr[:-1]) + word2en[entity] = en + if prev_entity and entity != prev_entity: + if ('DOMAIN_NAME' in cats and not prev_entity.endswith(".com")) or ('WORK_OF_ART' in cats and not (prev_entity.count("_") <= 4 and (":" in prev_entity or prev_entity[-1] == "1"))): + a.write (prev_entity.translate(trannum)+"\n") + else: + cats = [a for a in Counter(cats).most_common() if a[0] !='THING'] + if cats and prev_entity.count("_") <= 4: + o.write (prev_entity.translate(trannum) +"\t" +cats[0][0]+"\n") + else: + p.write (prev_entity.translate(trannum)+"\n") + cats = [cat] + prev_entity = entity + else: + cats.append(cat) + prev_entity = entity + if cats: + if ('DOMAIN_NAME' in cats and not prev_entity.endswith(".com")) or ('WORK_OF_ART' in cats and not (prev_entity.count("_") <= 4 and (":" in prev_entity or prev_entity[-1] == "1"))): + a.write (prev_entity.translate(trannum)+"\n") + else: + cats = [a for a in Counter(cats).most_common() if a[0] !='THING'] + if cats and prev_entity.count("_") <= 4: + o.write (prev_entity.translate(trannum) +"\t" +cats[0][0]+"\n") + else: + p.write (prev_entity.translate(trannum)+"\n") + os.system(f"sort --parallel=32 {tmp_dir}/yago{_idx}.tsv --o {tmp_dir}/yago{_idx}.tsv") + + os.system(f"cp {tmp_dir}/yago{_idx}.tsv {tmp_dir}/yago_ontology.tsv") + + def yago_step2(self): + tmp_dir = self.tmp_dir + data_dir = self.data_dir + if os.path.exists(f"{tmp_dir}/yago_ontology.json"): + return json.load(open(f"{tmp_dir}/yago_ontology.json")) + + if not os.path.exists(f"{tmp_dir}/yago_ontology.tsv"): + self.yago_step1() + + Synset = wn.synset + person = Synset('person.n.01') #person or job + commodity = Synset('commodity.n.01') #product + vehicle = Synset('conveyance.n.03') #product + artifact = Synset('artifact.n.01') + plant = Synset('plant.n.02') + molecule = Synset('molecule.n.01') #substance + compound = Synset('compound.n.02')#substance + scientist = Synset('scientist.n.01') + leader = Synset('leader.n.01') + capitalist = Synset('capitalist.n.02') # job + event = Synset('event.n.01') + animal = Synset('biological_group.n.01') #animal + structure = Synset('structure.n.01') + fac = Synset('facility.n.01') + group = Synset('group.n.01') + symptom = Synset('symptom.n.01') + location = Synset('location.n.01') + condition = Synset('condition.n.01') # disease + body_part = Synset('body_part.n.01') #anat + substance = Synset('substance.n.07')#sub, BIO_CHEM_ENTITY + food = Synset('food.n.01') #product + act = Synset('act.n.02') #medical_therapy + process = Synset('process.n.06') + + new_yago_ontology = {} + mt5_tok = transformers.AutoTokenizer.from_pretrained("google/mt5-small") + yago_dict = dict([a.split("\t") for a in open(f"{tmp_dir}/yago_ontology.tsv", "rb").read().decode().split("\n") if len(a.split("\t"))== 2 ]) + for word, label in yago_dict.items(): + if self.cjk_detect(word): + word = word.replace("_","") + word = "_".join(mt5_tok.tokenize(word)).replace(mt5_underscore,"_").replace("__", "_").replace("__", "_").strip("_") + if label == 'MEDICAL_CONDITION': + label='DISEASE' + if label in ('WORK_OF_ART',): + if ":" in word or word.count("_") > 1: + new_yago_ontology[word] = label + continue + if self.cjk_detect(word): + if len(word) > 1: + new_yago_ontology[word] = label + continue + elif "_" not in word: + continue + + synset= None + try: + synset= wn.synset(word+'.n.01') + except: + if label != 'PERSON': + try: + synset = wn.synset(word.split("_")[-1]+'.n.01') + except: + synset = None + if synset is not None: + hype = (list(synset.closure(lambda a: a.hypernyms()))) + if label in ('MEDICAL_THERAPY', ): + if act in hype or process in hype: + new_yago_ontology[word] = label + continue + elif label in ('DISEASE', ): + if condition in hype: + new_yago_ontology[word] = label + continue + elif label in ('ANAT',): + if body_part in hype: + new_yago_ontology[word] = label + continue + elif label in ('PRODUCT',): + if fac in hype or structure in hype: + label = 'FAC' + new_yago_ontology[word] = label + continue + elif food in hype: + label = 'FOOD' + new_yago_ontology[word] = label + continue + elif commodity in hype or vehicle in hype or artifact in hype: + new_yago_ontology[word] = label + elif label in ('ANIMAL',): + if plant in hype: + label = 'PLANT' + new_yago_ontology[word] = label + continue + elif animal in hype: + new_yago_ontology[word] = label + continue + elif label in ('ORG',): + if group in hype: + new_yago_ontology[word] = label + continue + elif label in ('PERSON', 'JOB', ): + if label == 'JOB' and (scientist in hype or leader in hype or capitalist in hype): + new_yago_ontology[word] = label + continue + if person in hype: + new_yago_ontology[word] = label + continue + elif label in ('SUBSTANCE', 'BIO_CHEM_ENTITY'): + if substance in hype or molecule in hype or compound in hype: + new_yago_ontology[word] = label + continue + elif label in ('GPE', 'LOCATION'): + if location in hype: + new_yago_ontology[word] = label + continue + elif fac in hype or structure in hype: + label = 'FAC' + new_yago_ontology[word] = label + continue + elif label in ('FAC',): + if location in hype and fac not in hype: + label = 'LOCATION' + new_yago_ontology[word] = label + continue + elif label in ('EVENT',): + if event in hype: + new_yago_ontology[word] = label + continue + if commodity in hype or vehicle in hype or artifact in hype or \ + plant in hype or molecule in hype or compound in hype or event in hype or \ + animal in hype or fac in hype or group in hype or symptom in hype or location in hype or \ + condition in hype or body_part in hype or substance in hype or food in hype or act in hype or \ + process in hype: + continue + + if label in ('PERSON',) or synset is None: + new_yago_ontology[word] = label + + lst = list(new_yago_ontology.items()) + json.dump(lst, open(f"{tmp_dir}/yago_ontology.json", "w", encoding="utf8"), indent=1) + os.system(f"cp {tmp_dir}/yago_ontology.json {tmp_dir}") + return lst + + def create_yago_ontology(self): + return self.yago_step2() + + + def create_combined_cn_yago(self): + self.create_cn_ontology() + self.create_eng2multilang_dict() + tmp_dir = self.tmp_dir + if hasattr(self, 'ner2word') and self.ner2word: return + if os.path.exists(f"{tmp_dir}/conceptnet_yago_combined.json"): + self.ner2word = json.load(open(f"{tmp_dir}/conceptnet_yago_combined.json", "rb")) + self.yago2ner = [tuple(a) for a in json.load(open(f"{tmp_dir}/yago2ner.json", "rb"))] + return + + mt5_tok = transformers.AutoTokenizer.from_pretrained("google/mt5-small") + + cat2word_list = list(json.load(open(f"{tmp_dir}/conceptnet_ontology_cat2word.json")).items()) + word2ner = {} + ner2word = {} + #cat2ner_map = dict([ ('person', 'PUBLIC_FIGURE'), ('body', 'ANAT'), ('artifact', 'PRODUCT'), ('medicine', 'MEDICAL_THERAPY',), ('plant', 'PLANT'), ('animal', 'ANIMAL'), ('location', 'LOCATION'), ('language', 'LANGUAGE'), ('substance', 'SUBSTANCE'), ('state', 'DISEASE'), ('group', 'ORG'), ('time', 'DATE'), ('law', 'LAW'), ('food', 'FOOD'), ('quantity', 'QUANTITY')]) + cat2ner_map = dict([ ('person', 'PUBLIC_FIGURE'), ('medicine', 'MEDICAL_THERAPY',), ('plant', 'PLANT'), ('animal', 'ANIMAL'), ('language', 'LANGUAGE'), ('substance', 'SUBSTANCE'), ('group', 'ORG'), ('time', 'DATE'), ('law', 'LAW'), ('food', 'FOOD'), ('quantity', 'QUANTITY')]) + + for cat, words in cat2word_list: + label = cat2ner_map.get(cat) + if label: + for word in words: + if self.cjk_detect(word): + word = "_".join(mt5_tok.tokenize(word.replace("_", ""))).replace(mt5_underscore,"_").replace("__", "_").replace("__", "_").strip("_") + #if len(word) <= 1: + # continue + if word in self.word2en: + word2ner[word]= label + + yago0 = self.create_yago_ontology() + yago2ner = [] + for word, label in yago0: + if word in word2ner or word in self.word2en: + if label == 'PERSON' and word in word2ner and word2ner[word] == 'PUBLIC_FIGURE': continue + word2ner[word] = label + else: + yago2ner.append((word, label)) + yago0 = None + for word, label in word2ner.items(): + ner2word[label] = ner2word.get(label,[])+list(self.word2en[word]) + word2ner=None + json.dump(ner2word, open(f"{tmp_dir}/conceptnet_yago_combined.json", "w", encoding="utf8"), indent=1) + json.dump(yago2ner, open(f"{tmp_dir}/yago2ner.json", "w", encoding="utf8"), indent=1) + self.ner2word = ner2word + self.yago2ner = yago2ner + + def save_cross_lingual_ontology(self, word2ner_file = "word2ner.json", do_small_set=True): + tmp_dir=self.tmp_dir + data_dir=self.data_dir + self.create_eng2multilang_dict() + self.create_combined_cn_yago() + ner2word = self.ner2word + if do_small_set: + ignore_ner_labels = set(['LANGUAGE', 'FOOD', 'LAW', 'DATE', 'EVENT', 'FAC', 'ANIMAL', 'PLANT', \ + 'ANAT', 'BIO_CHEM_ENTITY', 'QUANITY', 'DOMAIN_NAME','WORK_OF_ART', 'PRODUCT']) + else: + ignore_ner_labels = set(['WORK_OF_ART']) + yago2ner = [a for a in self.yago2ner if a[1] not in ignore_ner_labels] + mt5_tok = transformers.AutoTokenizer.from_pretrained("google/mt5-small") + + # except for domain names, anat/body part and language we want to only consider compound words + anat_en = list(set(ner2word['ANAT'])) + product_en = list(set(a for a in ner2word['PRODUCT'] if a.count("_") > 0)) + medical_therapy_en = list(set(a for a in ner2word['MEDICAL_THERAPY']if a.count("_") > 0)) + plant_en = list(set(a for a in ner2word['PLANT'] if a.count("_") > 0)) + animal_en = list(set(a for a in ner2word['ANIMAL'] if a.count("_") > 0)) + work_of_art_en = [] # list(set(a for a in ner2word['WORK_OF_ART'] if a.split("_")[0].lower() not in self.stopwords and a.count("_") > 0 and a.count("_") < 5)) + gpe_en = list(set(a for a in ner2word['GPE'] if a.count("_") > 0)) + event_en = list(set(a for a in ner2word['EVENT'] if a.count("_") > 0)) + language_en = list(set(ner2word['LANGUAGE'])) + disease_en = list(set(a for a in ner2word['DISEASE'] if a.count("_") > 0)) + org_en = list(set(a for a in ner2word['ORG'] if a.count("_") > 0)) + date_en = list(set(a for a in ner2word['DATE'] if a.count("_") > 0)) + law_en = list(set(a for a in ner2word['LAW'] if a.count("_") > 0)) + food_en = list(set(a for a in ner2word['FOOD'] if a.count("_") > 0)) + domain_name_en = list(set(a for a in ner2word.get('DOMAIN_NAME',[]) if a.count("_"))) + quantity_en = list(set(a for a in ner2word['QUANTITY'] if a.count("_") > 0)) + union_en = list(set(a for a in ner2word.get('UNION',[]) if a.count("_") > 0)) + fac_en = list(set(a for a in ner2word['FAC'] if a.count("_") > 0)) + location_en = list(set(a for a in ner2word['LOCATION'] if a.count("_") > 0)) + bio_chem_en = list(set(a for a in ner2word['BIO_CHEM_ENTITY'] if a.count("_") > 0)) + + # handle public figure and person specially + block_list = set(['handyman', 'redeemer', 'attorney', 'kroeber', 'anthropologist', 'harte', 'bartholin', 'eames', 'snow', 'crocetti', 'dissident', 'donor', 'adrian', 'otis', 'arouet', 'lachaise', 'danton', 'casanova', 'mantell', 'bernini', 'dame', 'duchess', 'fechner', 'hovick', 'oersted', 'heinz', 'laurens', 'historian', 'didion', 'pro', 'ernst', 'positivist', 'rembrandt', 'clive', 'island', 'crouse', 'dali', 'arrhenius', 'bowdler', 'domitian', 'trader', 'nernst', 'blok', 'markov', 'bontemps', 'berliner', 'gilman', 'geologist', 'hirschsprung', 'bridges', 'lauder', 'hoagland', 'marcher', 'boundaries', 'giver', 'trilling', 'livermore', 'romancer', 'gardiner', 'benet', 'shawn', 'weld', 'brooks', 'enlai', 'apparent', 'samaritan', 'charmer', 'sukarno', 'hirschfeld', 'apes', 'dodger', 'avila', 'eustachio', 'rabbit', 'bullfinch', 'talleyrand', 'bakey', 'broglie', 'bardi', 'pitar', 'egypt', 'culbertson', 'haeckel', 'schrödinger', 'townsend', 'jacob', 'vinson', 'fahrenheit', 'arbiter', 'pickett', 'guess', 'vargas', 'piper', 'gram', 'heart', 'hoffmannsthal', 'robusti', 'purkinje', 'gris', 'millet', 'garnier', 'miro', 'schiller', 'carrere', 'feifer', 'maccabaeus', 'berzelius', 'jacobi', 'wolff', 'parr', 'muck', 'neel', 'xi', 'xii', 'xiii', 'xv', 'xvi', 'argote', 'beyle', 'african', 'lobachevsky', 'jumper', 'glendower', 'vernier', 'broca', 'hoax', 'ovid', 'terence', 'dolby', 'cavelier', 'lion', 'raskolnikov', 'laban', 'trooper', 'bolivar', 'mackenzie', 'wilkinson', 'bessemer', 'maxim', 'dewar', 'paget', 'reynolds', 'khama', 'haworth', 'girard', 'carew', 'vespasianus', 'susumu', 'christian', 'havel', 'balboa', 'columnist', 'ang', 'heisenberg', 'micawber', 'architect', 'cow', 'diver', 'banker', 'loci', 'clothing', 'bleu', 'bearer', 'journalist', 'gillette', 'government', 'widow', 'manufacturer', 'miró', 'hokusai', 'felix', 'weight', 'expert', 'mata', 'kaer', 'mariner', 'trajan', 'leather', 'vinci', 'communicator', 'type', 'toast', 'stockholder', 'shrine', 'salad', 'korea', 'acquaintance', 'montgomerie', 'dosè', 'machinis', 'european', 'hell', 'china', 'inflection', 'islands', 'admirals', 'good', 'fatales', 'monkey', 'university', 'chiannoort', 'bishop', 'puta', 'rivers', 'philosophers', 'dragons', 'colleges', 'grandparents', 'linguists', 'aunts', 'firsts', 'technicians', 'committees', 'eggs', 'test', 'guns', 'pornography', 'nests', 'associations', 'association', 'companions', 'sons', 'homme', 'intellectuals', 'market', 'cell', 'dating', 'composer', 'data', 'colors', 'request', 'pollutant', 'ibt', 'status', 'mexico', 'predicate', 'vulnerability', 'loire', 'today', 'weapons', 'series', 'analysis', 'sector', 'tract', 'game', 'creation', 'missile', 'odor', 'pea', 'district', 'sandwich', 'trades', 'realm', 'worshiper', 'eiffel', 'tzu', 'builder', 'buster', 'marshal', 'cohn', 'hueffer', 'ohm', 'alger', 'hogg', 'jensen', 'drew', 'po', 'langtry', 'flory', 'senator', 'pamby', 'fan', 'hakim', 'robber', 'devi', 'digger', 'chaser', 'holley', 'jerk', 'fallot', 'coca', 'tenens', 'kahn', 'niner', 'fly', 'dipper', 'relation', 'recruit', 'duddy', 'domo', 'witch', 'banneret', 'masoud', 'alexander', 'omikami', 'correggio', 'laurel', 'claudius', 'brinton', 'juvenalis', 'sider', 'know', 'lil', 'baptist', 'julian', 'bodoni', 'houghton', 'devries', 'alhazen', 'gloriosus', 'worcester', 'billings', 'middleweight', 'libertarian', 'din', 'depressive', 'madonna', 'ciccone', 'hershey', 'moto', 'source', 'thumb', 'presumptive', 'hohenheim', 'blonde', 'dakotan', 'hadrianus', 'virgil', 'quarters', 'tertullian', 'rolfe', 'winkle', 'goodfellow', 'langley', 'falstaff', 'sidney', 'daula', 'catcher', 'sepulcher', 'hastings', 'lucretius', 'voter', 'turk', 'kettle', 'protestant', 'resistant', 'anatomist', 'mitty', 'opel', 'speaker', 'bojaxhiu', 'corporal', 'cimabue', 'brontë', 'tussauds', 'nostradamus', 'ship', 'thales', 'climber', 'mercenary', 'xiaoping', 'dostoevsky', 'blimp', 'style', 'saxon', 'leonean', 'snowman', 'ruler', 'velazquez', 'wrestler', 'shaker', 'panther', 'sanzio', 'symbol', 'turkish', 'vecellio', 'petrarca', 'livius', 'hawk', 'nothing', 'phrase', 'accelerator', 'multiplier', 'potyokin', 'half', 'tom', 'bridge', 'priest', 'grandniece', 'financiers', 'эне', 'kozh', 'orchestra', 'centre', 'eminence', 'mauldin', 'donatello', 'steuben', 'compatible', 'dialogue', 'reference', 'subtree', 'investor', 'schüler', 'undertaking', 'fossil', 'shopkeeper', 'benefactor', 'calligrapher', 'storyteller', 'fireman', 'sized', 'ape', 'cobra', 'kong', 'jiom', 'xuan', 'mu', 'shang', 'soong', 'sasser', 'herod', 'freeman', 'japan', 'jin', 'mushroom', 'jeffords', 'jie', 'arabia', 'andronicus', 'compatriot', 'wang', 'legge', 'incompetent', 'qin', 'cake', 'beloved', 'cheerful', 'seal', 'diamond', 'force', 'bastard', 'ina', 'diamonds', 'voting', 'sinister', 'bar', 'mouse', 'blue', 'villains', 'points', 'point', 'professors', 'sib', 'maps', 'machine', 'integrity', 'galaxy', 'store', 'slavic', 'saladine', 'comedy', 'policemen', 'spuriae', 'women', 'five', 'goods', 'part', 'mayores', 'sauce', 'renaissance', 'nièces', 'interviewai', 'interviewée', 'aventure', 'saladines', 'employa', 'highness', 'negócios', 'couple', 'monarch', 'grade', 'pairs', 'effects', 'files', 'eigne', 'neighbor', 'relative', 'relatives', 'caesars', 'objects', 'things', 'bastards', 'administrators', 'brethren', 'wives', 'bulb', 'religionist', 'religionists', 'scholars', 'farmers', 'gab', 'granddaughters', 'porn', 'politicians', 'heads', 'cheetahs', 'emperors', 'grandchildren', 'riches', 'like', 'interest', 'swear', 'structures', 'ideals', 'ideal', 'chancellors', 'address', 'complement', 'complements', 'water', 'error', 'citizens', 'partners', 'dress', 'familiares', 'hommes', 'pères', 'maître', 'maternels', 'filles', 'sparrow', 'généraux', 'série', 'arricchiti', 'corte', 'lavoro', 'uranium', 'cinema', 'quadrinhos', 'бабушки', 'variante', 'competition', 'players', 'sex', 'w', 'living', 'love', 'pawn', 'queen', 'rook', 'newspaper', '1', '3', '4', '5', 'feature', 'check', 'news', 'computers', 'night', 'set', 'roads', 'locations', 'film', 'murder', 'spindle', 'else', 'shop', 'attack', 'oil', 'torino', 'designing', 'performer', 'village', 'expression', 'assignment', 'classical', 'weapon', 'human', 'category', '240', 'tool', 'minor', 'buoy', 'plants', 'murders', 'industry', 'care', 'gene', 'bible', 'movement', 'wisconsin', 'gynecologist', 'environment', 'habakkuk', 'noise', 'dc', 'cousin', 'book', 'shoe', 'vector', 'procedure', 'coat', 'molecule', 'material', 'statement', 'site', 'literature', 'rescue', 'negro', 'warbler', 'cartoon', 'skiing', 'pooh', 'duke', 'investigator', 'hays', 'dick', 'welterweight', 'thanh', 'laureate', 'order', 'kin', 'grise', 'borbon', 'handy', 'sugar', 's', 'city', 'holly', 'cher', 'rule', 'rules', 'musics', 'commissioners', 'secretaries', 'languages', 'tests', 'lights', 'residence', 'schools', 'fair', 'bank', 'tea', 'guy', 'dad', 'bomber', 'foyer', 'nageurs', 'telephone', 'brand', 'crimes', 'compound', 'region', 'composition', 'job', 'name', 'penn', 'bone', 'cars', 'jokes', 'place', 'song', 'report', 'artaxerxes', 'negroid', 'busybody', 'none', 'washer', 'cleaner', 'conservative', 'adviser', 'alene', 'enemy', 'x', 'ballerina', 'lord', 'abed', 'slaver', 'timer', 'stapler', 'buyer', 'slave', 'schoolman', 'saki', 'tripa', 'fellow', 'follower', 'may', 'pachanoi', 'treasurer', 'vespasian', 'thumper', 'nude', 'jaybird', 'betrothed', 'lifer', 'nester', 'saxophonist', 'freak', 'dvořák', 'fool', 'spouse', 'socratic', 'fröbel', 'illiterate', 'germans', 'giotto', 'hawaiian', 'dropper', 'kite', 'hyde', 'disorderly', 'savant', 'carlos', 'poster', 'featherweight', 'impressionist', 'grandmaster', 'ringer', 'watcher', 'hog', 'neuroscientist', 'rater', 'kluxer', 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'p.d.g', 'orthant', 'résédacées', 'impure', 'rams', 'csapat', 'buccaneers', 'titans', 'redskins', 'cardinals', 'falcons', 'colts', 'raiders', 'afabarn', 'ash', 'informática', 'surrogate', 'russian', 'military', 'commissaire', 'poet', 'persona', 'organ', 'left', 'anti', 'nouveau', 'in', 'average', 'eager','u.s', 'green', 'new', 'top', 'house', 'lightweight', 'sea', 'drug', 'hat', 'shade','sol', 'package', 'package', 'spots', 'spiders', 'rooms', 'steads', 'product', 'outages', 'gear', 'beetle', 'bitterns', 'command', 'judge', 'objector', 'suspect', 'mayor', 'goddess', 'politique', 'center', 'intellectual', 'silent', 'rights', 'fruit', 'life', 'grandmothers', 'ministers', 'office', 'activity', 'task', 'user', 'authority', 'arab', 'provocateur', 'machina', 'all','out','ego','infant','arms','guest', 'breaker', 'town', 'smoker', 'policeman', 'politics', 'time', 'animal', 'group', 'turtle', 'first', 'level', 'hunter', 'nephew', 'britain', 'first', 'level', 'consultant', 'beater', 'surgeon', 'assistant', 'egg', 'goose', 'fodder', 'liberator', 'granddaughter', 'jewel', 'hitter', 'statesman', 'boys', 'palace', 'cipher', 'removed', 'politiques', 'card', 'brothers', 'students', 'organization', 'software', 'orange', 'means', 'niece', 'principle', 'duck', 'rider', 'mate' 'dealer', 'sprite', 'captain', 'wise', 'traveler', 'link', 'cause', 'link', 'cause', 'street', 'down', 'up', 'world', 'plant', 'country', 'elimination', 'call', 'unconscious', 'area', 'school', 'room', 'unit', 'commission', 'siblings', 'vehicle', 'doves', 'sun', 'equipment', 'fact', 'aborigine', 'attache', 'pair', 'beauty', 'scout', 'errant', 'worth', 'almighty', 'guard', 'announcer', 'boss', 'baker', 'pilot', 'cop', 'gatherer', 'piston', 'board', 'unionist', 'reporter', 'bachelor', 'cyclops', 'guest', 'infant', 'breaker', 'arms', 'demon', 'coward', 'boomer', 'household', 'gun', 'korean', 'eater', 'department', 'figure', 'bag', 'conjunction', 'numbers', 'paper','ambassador', 'system', 'gods', 'sibling', 'politician', 'duckling', 'correspondent','syndrome', 'wife', 'male', 'waiting','driver', 'governor', 'german', 'lieutenant', 'writer', 'painter', 'critic', 'citizen', 'program', 'clause', 'process', 'parent', 'fathers', 'reds', 'day', 'representative', 'advocate', 'cheese','grandson', 'collector', 'professional', 'musician', 'shot', 'indian', 'men','miner', 'canadian', 'number', 'sisters', 'gentleman', 'grandmother', 'tops', 'husband', 'scientist', 'accountant', 'official', 'clerk', 'heavyweight', 'party', 'bird', 'partner', 'working', 'kings', 'hand', 'princess', 'detective', 'witness', 'twin','agreement', 'property', 'accessory', 'companion','accountant', 'official', 'clerk', 'dog', 'bachelor, ''car', 'parents', 'seconds', 'mothers', 'children', 'parliament', 'coach', 'affaires', 'grandfather', 'solider', 'woman', 'line', 'county', 'effect', 'dove', 'law', 'person', 'house', 'people', 'man', 'houses','player','brother', 'student', 'officer', 'green', 'agent', 'child', 'president', 'minister', 'mother', 'music', 'information', 'uncle', 'leader', 'war', 'uncle', 'secretary', 'engineer', 'second','jockey', 'friend', 'chief', 'being', 'boy', 'live', 'professor', 'american', 'dragon', 'college', 'girl', 'catholic', 'states','grandchild','sister', 'father','prisoner','worker', 'top', 'committee', 'administrator', 'thing', 'god', 'class','automobile','spirit', 'admiral', 'ceremonies', 'russia', 'songwriter', 'executive', 'commissioner', 'technician', 'doctrine', 'therapist', 'operator', 'old', 'greens', 'deity', 'aunt', 'language', 'nest', 'red', 'cat', 'consort', 'member', 'lady', 'killer', 'baby', 'manager', 'disease', 'specialist', 'friends', 'son', 'practitioner', 'event', 'designer', 'you', 'trinity', 'doctor', 'attaché', 'servant', 'designer', 'nurse']) + block_list2 = set(['walk', 'commercial','deems', 'puerto', 'french', 'r', 'recruiting', 'plautus', 'lighthorse', 'kay', 'confederate', 'angus', 'anicius', 'barthold', "frankenstein's", 'honoré', 'front', 'keystone', 'cold', 'talking', 'knight', 'broker', 'financial', 'cy', 'gypsy', 'ostrich', 'knee', 'subordinate', 'lead', 'key', 'real', 'his', 'surname', 'instrumental', 'criminal', 'dual', 'philosopher', 'write', 'milne', 'tap', 'security', 'constant', 'costa', 'research', 'opera', 'riding', 'unknown', "printer's", 'kitchen', 'belt', "photographer's", 'gandy', 'solicitor', 'bay', 'zoo', 'granite', 'garden', 'major', 'rhodes', 'senior', 'quartermaster', 'desert', 'iron', 'barrel', 'dark', 'running', 'granville', 'big', 'faisal', 'soldier', 'render', 'vice', 'melchior', 'illegal', 'crafty', 'last', 'death', 'your', 'dodge', 'yellow', 'tribes', 'general', 'biological', 'topological', 'barracks', 'virgin', 'bright', 'chinese', 'cognitive', 'developmental', 'differential', 'economic', 'euro', 'false', 'fore', 'ground', 'jungle', "li'l", 'natural', 'river', 'some', 'squaw', 'titan', 'undocumented', 'role', 'males', 'at', 'chevrolet', 'making', 'existentialist', 'for', 'state', 'vanuatuan', 'langue', 'piano', 'opium', 'acid', 'lieder', 'coureur', 'saloon', 'edsel', 'desk', 'past', 'hablot', 'grey', 'hooray', 'ivy', 'caffeine', 'cocaine', "king's", 'pledge', 'morris', 'latter', 'hired', 'federal', "artist's", 'odds', 'addle', 'profit', 'lighthouse', 'able', 'mixed', 'rhode', 'credit', 'staff', 'confessor', 'mae', 'amen', 'breughel', 'fetid', 'sparring', 'imaginary', 'seneca', 'repas', 'creditor', 'devoted', 'diocletian','sailing', 'lasso', 'wet', 'musical', 'chandler', 'comics', 'popper', 'firth', 'hertz', 'biographic', 'armchair', 'ögey', 'quantitativer', 'agony', 'april', 'bond', 'cylinder', 'analytic', 'future', 'hiv', 'deer', 'revlon', 'caesar', 'wild', 'youthful', 'aires', 'architecture', 'architectures', 'colleville', 'entre', 'faire', 'grosses', 'les', 'orteil', 'orteils', 'petites', 'fiscal', 'monetary', 'primary', 'imperial', 'нағашы', 'қайын', 'къарт', 'уллу', 'fait', 'mestresses', 'alta', 'assigned', 'bloody', 'comparative', "could've", 'could', 'cunning', 'dead', 'domestic', 'feistel', 'indentured', 'independent', 'internally', 'liquor', 'low', 'maid', 'massage', 'missionary', 'passes', 'passed', 'passing', 'pass', 'pinky', 'playfair', 'potentially', 'preferred', 'princes', 'purple', 'puss', 're', 'reasonable', 'rice', 'she', 'snail', 'sneaker', 'submarine', 'substitution', 'shooting', 'suppressive', 'taxi', 'temporary', 'those', 'trailing', 'vigenère', 'wardrobe', 'flamenco', 'flamencos', 'chevaliers', 'her', 'lupi', 'padroni', 'tasmanian', 'donas', 'gêngis', 'abe', 'bistrița', 'full', 'bqdp', 'bqnd', 'bronco', 'buck', 'bypass', 'mid', 'character', 'chase', 'closing', 'compact', 'luxury', 'premium', 'conditioning', 'important', 'cosmetics', 'cuban', 'determining', 'duplex', 'dutch', 'econoline', 'electoral', 'elton', 'female', 'flight', 'females', 'chin', 'named', 'suwannee', 'ford', 'free', 'grammy', 'guyanese', 'hainan', 'hip', 'immigrants', 'inanimate', 'indus', 'israeli', 'iteration', 'jazz', 'jews', 'jordanian', 'kazakh', 'lebanese', 'ficticious', 'lisa', 'literary', 'luxemburgian', 'more', 'marathon', 'mariachi', 'measuring', 'milk', 'passenger', 'motorcycle', 'road', 'move', 'movie', 'sports', 'entertainment', 'narrative', 'neck', 'political', 'norfolk', 'north', 'orderly', 'parabolic', 'path', 'knows', 'one', 'playstation', 'polish', 'prescription', 'presidential', 'prester', 'pristine', 'radio', 'ally', 'editing', 'trying', 'retail', 'ros', 'saudi', 'seventh', 'shannon', 'sierra', 'sinhalese', 'sneak', 'soeren', 'speed', 'stones', 'sturdy', 'non', 'mainstream', 'surinamese', 'japanese', 'tajik', 'teen', 'bidirectional', 'thai', 'tour', 'trajectory', 'treasure', 'trivial', 'cord', 'elected', 'uruguayan', 'venezuelan', 'video', 'vegetation', 'voice', 'waist', 'while', 'bébé', 'second', 'first','mazda', 'mitsubishi',]) + lst = [(word, (1.0+ sum([a.count('_') for a in self.word2en.get(word, [])]))/(1.0 + len(self.word2en.get(word, []))) - 1.0) for word in ner2word['PUBLIC_FIGURE']] + lst = [l for l in lst if (l[1] >= 0.0) and (l[0].count("_") < 5) and not [a for a in self.word2en.get(l[0], {l[0]}) if a.split("_")[-1] in block_list] and not [a for a in self.word2en.get(l[0], {l[0]}) if a.split("_")[0] in set(list(block_list)+list(block_list2))]] + lst = lst + [a for a in itertools.chain(*[[str(a.name()) for a in d.lemmas()] for d in wn.synset('person.n.01').closure(lambda s: s.hyponyms()) if not d.hyponyms()]) if a[0] == a[0].upper()] + public_figure_en = list(set(OntologyBuilder.public_figure_list + list(itertools.chain(*[self.word2en.get(l[0], {l[0]}) for l in lst])))) + lst = [(word, (1.0+ sum([a.count('_') for a in self.word2en.get(word, [])]))/(1.0 + len(self.word2en.get(word, []))) - 1.0) for word in ner2word['PERSON']] + lst = [l for l in lst if (l[1] >= 0.0) and (l[0].count("_") < 5) and not [a for a in self.word2en.get(l[0], {l[0]}) if a.split("_")[-1] in block_list] and not [a for a in self.word2en.get(l[0], {l[0]}) if a.split("_")[0] in set(list(block_list)+list(block_list2))]] + person_en = list(itertools.chain(*[self.word2en.get(l[0], {l[0]}) for l in lst])) + + union_en = union_en + [word.replace(" ", "_").replace("-", "_").lower().strip(".") for word in OntologyBuilder.union_list] + [a for a in itertools.chain(*[[str(a.name()) for a in d.lemmas()] for d in wn.synset('union.n.01').closure(lambda s: s.hyponyms()) if not d.hyponyms()]) ] + social_economic_class_en = OntologyBuilder.soc_eco_class_list + [a for a in itertools.chain(*[[str(a.name()) for a in d.lemmas()] for d in wn.synset('class.n.03').closure(lambda s: s.hyponyms()) if not d.hyponyms()]) ] + professional_en = [a for a in itertools.chain(*[[str(a.name()) for a in d.lemmas()] for d in wn.synset('professional.n.01').closure(lambda s: s.hyponyms()) if not d.hyponyms()]) if a[0] == a[0].lower()] + worker_en = [a for a in itertools.chain(*[[str(a.name()) for a in d.lemmas()] for d in wn.synset('worker.n.01').closure(lambda s: s.hyponyms()) if not d.hyponyms() if not d.hyponyms()]) if a[0] == a[0].lower()] + poltical_party_member_en = self.political_party_member_list + [a for a in itertools.chain(*[[str(a.name()) for a in d.lemmas()] for d in wn.synset('politician.n.02').closure(lambda s: s.hyponyms()) if not d.hyponyms()]) if a[0] == a[0].upper() and "_" not in a] + politcal_party_en = OntologyBuilder.political_party_list + [a for a in itertools.chain(*[[str(a.name()) for a in d.lemmas()] for d in wn.synset('party.n.01').closure(lambda s: s.hyponyms()) if not d.hyponyms()]) if a[0] == a[0].upper()] + organization_en = org_en + OntologyBuilder.org_list + [a for a in itertools.chain(*[[str(a.name()) for a in d.lemmas()] for d in wn.synset('organization.n.01').closure(lambda s: s.hyponyms()) if not d.hyponyms()]) if a[0] == a[0].upper()] + religion_list_en = [word.replace(" ", "_").replace("-", "_").lower().strip(".") for word in OntologyBuilder.person2religion.values()] + [a for a in itertools.chain(*[[str(a.name()) for a in d.lemmas()] for d in wn.synset('religion.n.01').closure(lambda s: s.hyponyms()) if not d.hyponyms()]) if a[0] == a[0].upper()] + religion_list_en = religion_list_en + OntologyBuilder.religion_list + gender_person_en = OntologyBuilder.gender_list + [word.replace(" ", "_").replace("-", "_").lower().strip(".") for word in itertools.chain(*OntologyBuilder.pronoun2gender.values())] + + language_list_en = list(set(language_en + [word.replace(" ", "_").replace("-", "_").lower().strip(".") for word in person.Provider.language_names])) + language_list_en.remove('interlingua') + race_list_en = list(set([word.replace(" ", "_").replace("-", "_").lower().strip(".") for word in OntologyBuilder.race_list])) + race_list2 = [] + + for word in race_list_en + language_list_en: + for gender in ['person', 'people', 'females', 'women', 'ladies', 'gays', 'males', 'men', 'lesbians', 'boys', 'girls', 'adults', 'female', 'woman', 'lady', 'gay', 'male', 'man', 'lesbian', 'boy', 'girl', ]: + for word2 in [gender+"_"+word, word+"_"+gender, "older_"+gender+"_"+word, "old_"+word+"_"+gender, "younger_"+gender+"_"+word, "young_"+word+"_"+gender, "adult_"+word+"_"+gender, "senior_"+word+"_"+gender,]: + if word2 in self.en: + race_list2.append(word2) + + religious_person_en = list(set(OntologyBuilder.religious_member_list + [word.replace(" ", "_").replace("-", "_").lower().strip(".") for word in [word.split(",")[0].strip() for word in OntologyBuilder.person2religion.keys()]])) + religious_person_en = religious_person_en + [a for a in itertools.chain(*[[str(a.name()) for a in d.lemmas()] for d in wn.synset('religious_person.n.01').closure(lambda s: s.hyponyms())]) if a[0] == a[0].upper() and a not in ('WASP',)] + religious_person2 = [] + for word in religious_person_en: + for gender in ['person', 'people', 'females', 'women', 'ladies', 'gays', 'males', 'men', 'lesbians', 'boys', 'girls', 'adults', 'female', 'woman', 'lady', 'gay', 'male', 'man', 'lesbian', 'boy', 'girl', ]: + for word2 in [gender+"_"+word, word+"_"+gender, "older_"+gender+"_"+word, "old_"+word+"_"+gender, "younger_"+gender+"_"+word, "young_"+word+"_"+gender, "adult_"+word+"_"+gender, "senior_"+word+"_"+gender,]: + if word2 in self.en: + religious_person2.append(word2) + religious_person_en = list(set(religious_person_en + religious_person2)) + + jobs_en = professional_en + worker_en + OntologyBuilder.jobs + list(set([word.replace(" ", "_").replace("-", "_").lower().strip(".") for word in [word.split(",")[0].strip() for word in job.Provider.jobs]])) + jobs_list2 = [] + for word in jobs_en : + for gender in ['female', 'woman', 'lady', 'gay', 'male', 'man', 'lesbian', 'boy', 'girl', ]: + for word2 in [gender+"_"+word, word+"_"+gender]: + if word2 in self.en: + jobs_list2.append(word2) + jobs_en = list(set(jobs_en + jobs_list2)) + jobs_en = list(set(jobs_en + jobs_list2)) + + gender_list2 = [] + for word in gender_person_en : + for age in ['old', 'older', 'young', 'younger', 'adult', 'senior',]: + for word2 in [age+"_"+word, word+"_"+gender]: + if word2 in self.en: + gender_list2.append(word2) + gender_person_en = list(set(gender_person_en+gender_list2)) + + race_list_en = list(set(self.race_list + race_list2)) + disease_list_en = disease_en + self.disease_list + list(itertools.chain(*[[str(a.name()) for a in d.lemmas()] for d in wn.synset('physical_condition.n.01').closure(lambda s: s.hyponyms())])) + disease_list_en = disease_list_en + list(itertools.chain(*[[str(a.name()) for a in d.lemmas()] for d in wn.synset('infectious_agent.n.01').closure(lambda s: s.hyponyms())])) + disease_list_en = disease_list_en + list(itertools.chain(*[[str(a.name()) for a in d.lemmas()] for d in wn.synset('symptom.n.01').closure(lambda s: s.hyponyms())])) + + #now create the x-lingual word2ner mapping + # TODO: need to do LANGUAGE, GPE (country, city) and block lists + block_list= [] + word2ner = yago2ner + print ('num of items', len(word2ner)) + if 'GENDER' not in ignore_ner_labels: + gender_person_list, word2ner, block_list = self.create_multilingual_examples(gender_person_en , 'GENDER', word2ner, block_list= block_list + ['maidservant', 'slip', 'kiddo', 'alma', 'heiress', 'pussy', 'pucelle', 'miss', \ + 'handmaid', 'doll', 'noblewoman', 'damselfly', "lady's_maid", 'ponce', 'bachelorette', 'lesser_black_backed_gull', 'leopardess', \ + 'housemaid', 'zygoptera', 'damselfish', 'demoiselle', 'zygopteran', 'silver_perch', 'sister', 'maiden_over', 'brevier', 'big_sister', 'spinster', 'brat', \ + 'shojo', 'girlfriend', 'wench', 'daughterling', 'petite', 'girlish', 'wife', 'daughter', 'chinese_girl', 'paternal_aunt', 'son', 'spouse', 'husband', 'fellow', 'bloke', 'covey', 'stud', 'cove', 'youngster', 'cub', 'sex', 'madam', 'rocky', 'youth', 'stripling', 'knave', 'child', 'ferrule', 'groom', 'lord', 'master', 'edging', 'person', \ + 'casanova', 'missus', 'grandpa', 'geezer', 'boyfriend','adulteress', 'foot', 'leg', 'mutually', 'with_one_another', 'lazy', 'from', 'jack', 'cock', 'crevice', 'messiah', 'slit', 'fissure', 'young_buck','pair', 'young', 'virgin', 'motel', 'bread', 'dam', 'dam', 'isle_of_man','virgo', 'i_translations', 'prostitute', 'broad', 'man_translations', 'retroflex_final', 'son_translations', 'virile', 'waiter', 'ready', 'vagina', 'wow', 'dungeon', 'wow', 'guild', 'servant' ]) + print ('num of items', len(word2ner)) + title_list, word2ner, block_list = self.create_multilingual_examples(self.title_list , 'TITLE', word2ner, cut_off_per=0.2, block_list= block_list+ ['possessor', 'virgin', 'girl', 'neglect', 'overlook','fail', 'fail_to_catch', 'lose', 'want']) + person_pronoun_list, word2ner, block_list = self.create_multilingual_examples(self.person_pronoun_list, 'PERSON_PRONOUN', word2ner, cut_off_per=0.2, block_list= block_list + ['interjection_expressing_anger_or_chagrin', 'i_translations', 'information_technology', 'here']+self.other_pronoun_list) + other_pronoun_list, word2ner, block_list = self.create_multilingual_examples( self.other_pronoun_list, 'OTHER_PRONOUN', word2ner, cut_off_per=0.2, block_list= block_list+ ['interjection_expressing_anger_or_chagrin', 'i_translations', 'information_technology', 'here']+self.person_pronoun_list ) + domain_name_list, word2ner, block_list = self.create_multilingual_examples(domain_name_en , 'DOMAIN_NAME', word2ner, block_list=block_list) + quantity_list, word2ner, block_list = self.create_multilingual_examples(quantity_en , 'QUANTITY', word2ner, block_list=block_list + ['mimosa', 'attic', 'hay', 'flytrap', 'rudd', 'hop', 'ginger', 'sunray', 'lupine', 'draughts','angelica', 'orange', 'daisy', 'buoy', 'parking_space', 'bin', 'standard', 'long_weekend','rubber', 'won', 'real', 'shield', 'parking', 'short_for', 'snot', 'compositeness', 'mark','decimal', '3d', 'irl', 'three_mountains', 'si', 'tithe', 'solid']) + bio_chem_list, word2ner, block_list = self.create_multilingual_examples(bio_chem_en , 'BIO_CHEM_ENTITY', word2ner, block_list=block_list) + anat_list, word2ner, block_list = self.create_multilingual_examples(anat_en , 'ANAT', word2ner, block_list=block_list) + medical_therapy_list, word2ner, block_list = self.create_multilingual_examples(medical_therapy_en , 'MEDICAL_THERAPY', word2ner, block_list=block_list) + plant_list, word2ner, block_list = self.create_multilingual_examples(plant_en , 'PLANT', word2ner, block_list=block_list+['vanilla', 'face', 'surname_lin', 'iris', 'flag', 'arabica', 'lifeline', 'aspen', 'robust', 'blue_bugle', 'thrift', 'maria','broom','cos','althea','see', 'flamboyant', 'black_eye', 'purplish', 'purple', 'wickerworker', 'wicker', 'plane', 'bay', 'bittersweet', 'litmus', 'fire_opal', 'oliva', 'i_live_in_melbourne', 'absinth', 'cunt', 'prune', 'ricin', 'naked_lady', 'absinthe', 'mugwort', 'camomile_tea', 'mandarin_chinese', 'nonce', 'blond', 'over_embellished', 'mauve', 'bray', 'nincompoop', 'crucible', 'quack', 'oca', 'cherry_red', 'absent', ]) + print ('num of items', len(word2ner)) + animal_list, word2ner, block_list = self.create_multilingual_examples(animal_en , 'ANIMAL', word2ner, block_list=block_list + [ 'sidewinder', 'tuberculosis_germ', 'bug', 'ridley', 'neanderthal','ridley', 'neanderthal', 'pain', 'dipper', 'vampire', 'flicker', 'hsv', 'air_bladder_of_fish', 'sole', 'sultan', 'leatherback','moby_dick', 'mew', 'cramp', 'cough', 'idiot', 'fool', 'rot', 'alcedo', 'cast_net', 'ass', 'jackass', 'mustela', 'pica', 'grampus', 'ailuro', 'brown', 'defensive_opening_for_shogi', 'möwe', 'chump', 'rook', 'night_person', 'hart', 'buck', 'foolish', 'coward', 'simpleton', 'ignoramus', 'folly', 'stupidity', '900', 'hack', 'dunce', 'blockhead', 'nonsense', 'something_strange_or_suspicious', 'ester', 'who', 'ase', 'moke', 'æsir', 'tetrao', ]) + gpe_list, word2ner, block_list = self.create_multilingual_examples(gpe_en , 'GPE', word2ner, block_list=block_list +['christopher', 'sugarloaf', 'elysium', 'peter', 'echinopsis_pachanoi', 'civil_rights', 'valentine']) + fac_list, word2ner, block_list = self.create_multilingual_examples(fac_en , 'FAC', word2ner, block_list=block_list + ['gradually', 'bit_by_bit', 'by_small_degrees', 'junior_school', 'lodging_together', 'center', 'aspirin']) + location_list, word2ner, block_list = self.create_multilingual_examples(location_en , 'LOCATION', word2ner, block_list=block_list + ['helena', 'tram', "new_year's", 'year_end', 'hello', 'good_morning', 'how_do_you_do', 'have_nice_day', 'bat', 'here_you_are', 'no_thanks', 'sure_thing', 'no', 'please', 'excuse_me', 'pardon_me', 'you_are_welcome', 'heartily', 'gladly', 'union', 'eve', 'circumcision', 'daylight', 'daybreak', 'sleep_tight', 'nest', 'social_democrats', 'nothing', "it_doesn't_matter", 'big_dipper', 'spa']) + event_list, word2ner, block_list = self.create_multilingual_examples(event_en , 'EVENT', word2ner, block_list=block_list) + date_list, word2ner, block_list = self.create_multilingual_examples(date_en , 'DATE', word2ner, block_list=block_list+ ['latent_period', 'summer', 'mortality', 'deathrate', 'included', 'within_that', 'even_now', 'over_time','allhallowtide', 'western_calendar', 'deadline', 'in_end', 'around_clock', 'cold_snap', 'night_guard', 'holiday', 'workday', 'leisure', 'interim', 'ad', 'jubilee', 'moment', '4_4', 'instantaneously', 'vacation', 'nonprofessional', 'leisure_time', 'shift', 'month', 'bright_moon', 'refers_to', 'year_of_our_lord', 'phases_of_moon', 'class', 'time_at_leisure', 'off_time', 'work_shift', 'respite', 'infant_mortality_rate']) + law_list, word2ner, block_list = self.create_multilingual_examples(law_en , 'LAW', word2ner, block_list=block_list + ['freedom_of_opinion', 'jurisdiction', 'civil_marriage', 'capital_punishment', 'constitutional_state', 'trustee_beneficiary_relation', 'sexual_exploitation', ]) + food_list, word2ner, block_list = self.create_multilingual_examples(food_en , 'FOOD', word2ner, block_list=block_list+ ['tomato', 'chip', 'baseball_fan', 'patty', 'tisane', 'infusion', 'brackish', 'pop', 'tonic', 'rump', 'buttocks', 'formula', 'blanc', 'oil', 'table_talk', 'zwart', 'starter', 'testicle', 'ovum']) + print ('num of items', len(word2ner)) + language_list, word2ner, block_list = self.create_multilingual_examples(language_list_en , 'LANGUAGE', word2ner, block_list=block_list+['ironworker', 'erse',]) + job_list, word2ner, block_list = self.create_multilingual_examples(jobs_en , 'JOB', word2ner, block_list= block_list + [ 'guarda_portão', 'door', 'root', 'landed', 'give', 'button', 'occupant', 'haughty', 'commender', 'head', 'command', 'lead', 'leveret', 'shop', 'superuser', 'legal_guardian', 'kanji_legs_radical', 'pedestrian_traffic', 'angel', 'clever', 'cast', 'bower_bird', 'calculator', 'catchword', 'generator', 'perpetrator', 'god_almighty', 'southeast', 'aesthetics', 'animated', 'email', 'wearer', 'girder', 'holder', 'luggage_carrier', 'carrying_bag', 'poster_child', 'bleaching_agent', 'utterer', 'falsifier', 'employee', 'curate', 'qualifier', 'gambler', 'playful', 'prayer', 'escort', 'reeve', 'superman', 'dignitary', 'leadership', 'first_place', 'seat_of_honor', 'jobholder', 'redact', 'pacer', 'marcher', 'drive_around', 'motorist', 'scout', 'conductive', 'dribbler', 'hauler', 'conveyor', 'tutorial', 'burn_down', "nobleman's_residence", 'digger', 'teller', 'accounts_office', 'wright', 'artisanal', 'attorney_at_law', 'jurist', 'judge', 'centerfold', 'compiler', 'curtain', 'portiere', 'savior', 'mentor', 'restrainer', 'wing', 'scepter', 'armed', 'seating', 'uncle', 'adjutant', 'egeria', 'consultative', 'consult', 'government', 'taker', 'harbinger', 'dispatch_rider', 'lion', 'steed', 'conveyance', 'sent', 'all_rounder', 'famous_and_virtuous_ancestors', 'pioneer', 'sawbones', 'supervisory_program', 'upper_part_of_flag', 'tour_guide','discussion', 'creative', 'maker', 'praeses', 'chairmanship', 'landowner', 'kitchen_manager', 'interior_decoration', 'regency', 'spin_doctor', 'event_companion', 'baton_twirler', 'puppeteer', 'augustin_eugene_scribe', 'nib', 'claimant', 'contact', 'helper', 'tosser', 'deputation', 'arousing', 'sir_isaac_pitman', 'pilot_light', 'dragoman','defamer', 'translation', 'regulation', 'ordinance', 'fixer', 'stakeholder', 'pictorial', 'woodsman', 'leshy', 'utility', 'recruit', 'person_with_whom_to_speak', 'someone_to_talk_to', 'comrade', 'friend', 'sputnik', 'forced_laborer', 'anesthesiology', 'hellhound', 'raider', 'nerd', 'national_park_service', 'road_map', 'leading', 'managerial', 'reigning', 'peasant', 'burglar', "manage_one's_household", 'thrall', 'addict', 'nief', 'worshipper', 'mammy', 'manny', 'stonemasonry', 'moor', 'bobby', 'man_of_letters', 'literacy', 'connector', 'super', 'speller', 'oceanic', 'ocean', 'showman', 'general_business', 'general_affairs', 'manage', 'preside', 'apprentice', 'tray', 'special_duty', 'lens', 'rule', 'directing', 'do_it_yourselfer', 'rider', 'cleansing_agent', 'optional', 'artillery', 'artillerist', 'witch_doctor', 'person_who_gives_treatment', 'person_who_reads_cards', 'copper', 'bull', 'führer', 'sophisticate', 'dog', 'alfalfa', 'asia', 'nester', 'underling', 'copartner', 'rear_up', 'piper', 'supt', 'blunder', 'captive', 'optics', 'auriga', 'kolar', 'guidance', 'steering', 'drafter', 'frontbencher', 'ministerial', 'young_male_servant', 'stockbreeder', 'conciliatory', 'guide_book', 'kitchenhand', 'carder', 'dominee', 'inhabitant', 'concertante', 'mouthpiece', 'drugstore', 'agent', 'temporary_work', 'fipple_flute', 'chamberlain', 'thrifty', 'sensory', 'department_of_commerce', 'jackhammer', 'herd', 'chair', 'prime', 'fighter', 'army', 'officiate', 'dean', 'practitioner', 'modiste', 'hatter', 'sewer','plotting', 'planning', 'fuzz', 'first_proponent', 'initiator', 'bluejacket', 'fierce_man', 'vet', 'participation_in_government', "grocer's", 'trading', 'chapman', 'commercialize', 'deal', 'trade', 'firm', 'merchandise', 'peddler', 'business_is_business', 'supplier', 'bender', 'autotroph', 'pastoral', 'grazier', 'bucolic', 'johann_gottfried_von_herder', 'ward', 'vigil', 'supervise', 'checker', 'standing_watch', 'prefect', 'scheme', 'plot', 'bring_about', 'commerce', 'commercial_enterprise','huckster', 'juggler', 'commodify', 'market', 'barter', 'negociate', 'industrial', 'enterprising_man', 'child_trafficking', 'trafficker', 'agency', 'retail_outlet', 'franchise', 'provider', \ + 'pedestrian', 'ecclesiastical', 'decigram', 'rancher', 'crimp', 'goon', 'blood_sausage', 'gizzard', 'cattle_dog', 'boötes', \ + 'cattle_droving', 'bull_run', 'purifier', 'vs', 'kosher', 'donor', 'issuer', 'windshield_wiper', 'scanner', 'literary_person', \ + 'skilled', 'pictor', 'writing_desk', 'write_for_someone_else', 'victor', 'aye_aye_sir', 'main', 'shooter', 'whittler', \ + 'pharmacy', 'downloader', 'lower_position', 'negroid', 'black_person', 'sorb', 'serve',\ + 'album', 'vendémiaire','bookcase', 'bunting', 'clop', 'storage_battery', 'gardening', \ + 'staff', 'otto_wagner', 'wagner', 'wilhelm_richard_wagner', 'conservative', 'military', 'edger', 'secant', 'sanitary', 'aesculapian', 'medical', 'factor', 'elizabeth_cochrane_seaman', 'getting_on_board', 'seafaring', 'nautical', 'oceangoing', 'marinate', 'marinade', 'crew', 'galoot', "ship's_company", 'jacob', 'passenger', 'ship', 'military_rank', 'misprint', 'chaser', 'exchange_traded_fund', 'orion', 'guided_tour', 'drawing_card',\ + 'mop', 'national_flag', 'double_crosser', 'device_driver', 'residency', 'systematic', 'favourite', 'enclosed', 'aid', 'adjunct', 'adjoint', 'adjutant_bird', 'concubine', 'shower', 'obstetric', 'mechanized_cavalry', 'cavalry', 'minion', 'intendant', 'sycophant', 'boyfriend', 'pattern', 'friseur', 'samuel_barber', 'barbershop', 'villus', 'apus', 'henchman', \ + 'man_of_war', 'rank_and_file', 'take_care', 'remedy', 'attorneyship', 'litigant', 'moan', 'lament', 'milling_machine', 'jellyfish', 'problem_solver', 'representative', 'betrayer', 'match', 'hunt', 'combatant', 'bold', 'troop', 'terminable', 'impermanent', 'pilot_program', 'squeegee', 'juror', 'gavel', 'pedicure', 'tool', 'mechanical', 'guerrilla', \ + 'controller', 'control', 'pro', 'oar', 'gift', 'teaching', 'professorship', 'magister', 'aio', 'chaperone', 'maestro', 'surname_fu', 'helpmeet', 'bark_beetle', 'hardworking', 'proletarian', 'overall', 'maiden', 'wench', 'bondwoman', 'women', 'majordomo', 'employer', 'proficient', 'male', 'lord', 'cap', 'foster_parent', 'champion', 'skip', \ + 'trust_busting', 'authority', 'craft', 'colleague', 'inn', 'commoner', 'web_server', 'household', 'home', 'pet', 'mechano', 'arm_wrestling', 'troops', 'voyager', 'earthwork', 'earthworks', 'seasonally', 'power_shovel', 'backhoe', 'rod', 'washing_machine', 'sir', 'sidekick', 'helpmate', 'flatterer', 'salary', 'wage', 'seiner', 'peterman', 'schemer', 'conspirator', 'hanging_strap', 'otter_civet', \ + 'seeker', 'alumnus', 'son_translations', 'boy', 'columnist', 'correspond', 'write', 'clerkship', 'moonshee', 'gynecology', 'sales', 'apologist', 'good', 'contributor', 'benefactor', 'subscriber', 'suite', 'requisition', 'support', 'godparent', 'godfather', 'backer', 'dock', 'arranger', 'charger', 'magazine', 'piscatory', 'pescatore', 'kingfisher', \ + 'writing', 'secretary_bird', 'homemade', 'attendee', 'post_carrier', 'postie', 'msw', 'readership', 'reviewer', 'attorney_in_fact', 'proxy', 'bushman', 'blackcoat', 'agriculturist', 'countryman', 'yokel', 'bathyergus', 'mud_dredger', \ + 'flight_simulator', 'useful_person', 'manage_people', 'bantu', 'serf', 'stewardship', 'retinue', 'nigger', 'low_rank_person', 'employment', 'employ', 'service', 'partner', 'fellow', 'kill', 'employed', 'dogsbody', 'follower', 'satellite', 'used', 'abdi', \ + 'ministry', 'vassal', 'stooge', 'abigail', 'assistance', 'subordinate_work', 'avocado', 'preach', 'proponent', 'defense', 'advocaat', 'disciple', 'defender', 'patron', 'promotor', 'seconder', 'eggnog', 'on_sale', \ + 'kitchen', 'coccus', 'coccal', 'editor_program', 'publishing_house', 'copywriting', 'correspondent', 'lookout','cadre', 'raising_cattle', 'unai', 'keeper', 'watchdog', 'protection', 'train', 'security', \ + 'card', 'junior','strikebreaking', 'violator', 'callee', 'selectee', 'new_recruit', 'novice', 'rookie', 'barrater', 'destructor', 'subject', 'performer_of_action', \ + 'pollyannaish', 'milking_machine','guy', 'casanova', 'mobilize', 'dummy', 'exemplar', 'blueprint', 'host', 'toilet_bag', 'burner',]) + race_list, word2ner, block_list = self.create_multilingual_examples(race_list_en, 'RACE', word2ner, block_list= block_list + ['oar', 'iris', 'france', 'français', 'frenchy', 'daniel_chester_french', 'frenchie', \ + 'franco', 'potato_chip', 'francia', 'turki', 'francis', 'yankee_doodle', 'francium', 'dharma',\ + 'dwarf','foreigner', 'double_dutch', 'araba','press_gang', 'romance', 'indigenous', 'countryfolk', 'indus', 'italy', 'specialization', 'painter', 'achromatic', 'arabian_horse', 'arabian_peninsula', 'roundoff', 'jewess', 'jews', 'hebrew', 'commonwealth_of_australia', 'white_translations', 'china', 'japan', 'native', 'chinese_language']) + religious_member_list, word2ner, block_list = self.create_multilingual_examples(religious_person_en , 'RELIGION_MEMBER', word2ner, block_list= block_list + religion_list_en + ['duster', 'girlfriend', 'indian', 'roman', 'parse', 'cousin', 'jewry', 'christendom', 'christianity', ]) + religion_list, word2ner, block_list = self.create_multilingual_examples(religion_list_en , 'RELIGION', word2ner, block_list= block_list + religious_person_en + ['acid', 'duster', 'girlfriend', 'indian', 'roman', 'parse', 'cousin', 'jewry', 'jewess', 'ghetto', 'priesthood', 'church', 'sacred_teachings', 'christendom', 'portuguese_jesuits', 'person', 'mohammedan', 'moslem']) + union_list, word2ner, block_list = self.create_multilingual_examples(union_en , 'UNION', word2ner, block_list= block_list + ['union', 'syndicate',]) + social_economic_class_list, word2ner, block_list = self.create_multilingual_examples(social_economic_class_en , 'SOC_ECO_CLASS', word2ner, block_list= block_list + ['brotherliness', 'freemasonry', 'fraternization', 'clan', 'fellowship', 'handicraft', 'commerce', 'commercialize', 'adele',\ + 'edwin_herbert_land', 'work', 'press', 'time', 'service', 'wife', 'mother', 'female', 'times', 'anthology', 'better', 'breeding', 'choose', 'chivalry', 'noble', 'jue', 'set']) + political_party_list, word2ner, block_list =self.create_multilingual_examples(politcal_party_en , 'POLITICAL_PARTY', word2ner, block_list= block_list +['ungradable_opposition', 'work', 'time', 'service']) + political_party_member_list, word2ner, block_list = self.create_multilingual_examples(poltical_party_member_en , 'POLITICAL_PARTY_MEMBER', word2ner, block_list= ['red', 'rouge','communistically' ]) + public_figure_list, word2ner, block_list = self.create_multilingual_examples(public_figure_en , 'PUBLIC_FIGURE', word2ner, block_list= block_list+ ['gulf_of_saint_lawrence', 'allene', 'james', 'maldives', 'borgia', 'person_of_promise', 'zeeman', 'director', 'they', 'bi', 'kid', 'surname_franklin', 'will', 'edison', 'ego', 'me', "i'm", 'genus_of_humans', 'king', 'neumann', 'augustus', 'couple', 'norman', 'rus', 'foil', 'joule', 'an', 'majority', 'christopher', 'larry', 'wolf', 'swallow', 'ouch', 'elder', 'single', "o'clock", 'ptarmigan', \ + 'forth', 'boast', 'fist', 'zen', 'bunch', 'ostrich', 'spouse', 'woman', 'goatfish', 'wife', 'chaise_longue', 'outer_wall', 'butene', 'paralysis_agitans', 'shrub', 'weaver', 'plough', 'rich', 'algeria', 'cockchafer', \ + 'bumblebee', 'alaska', 'heart', 'flemish', 'schmidt_island', 'petro', 'herz_or_cycles_per_second', 'limb', \ + 'everyone', 'everybody', 'yes', 'logos', 'messiah', 'turner', 'gymnast', 'return', 'gy', 'freemason', 'mason', 'lake_edward', 'alabama', 'los_angeles', 'loss', 'losings', 'passing', 'steed', 'ross_island', \ + 'horse', 'rice', 'young', 'jr', 'japan_railways', 'jnr', 'gilbert_islands', 'slate', 'show', 'stone', 'stoned', 'nub', 'earthen', 'benedictine', 'fuse', 'oxford_shoe', 'dino_paul_crocetti', 'orphan_drug', \ + 'leninist','ash', 'hunt', 'brown', 'brown_university', 'breezy', 'fresh', 'normans', 'grant', 'grunt', 'moses_basket', 'musa', 'burton', 'marx', \ + 'negroid', 'gray', 'grey', 'why', 'wood', 'man', 'beeper', 'hong_kong', 'never', 'vomit', 'puke', "st_george's", 'massachuset', 'massachusetts', 'track_clearing_vehicle', \ + 'snowplow', 'word', 'ward', 'care', 'anger', 'grim', 'midnight', 'houston', 'farmer', 'post', 'morgan_horse', 'moody', \ + 'life_annuity', 'hooker', 'leaky', 'jogging', 'cooper', 'white', 'white_person', \ + 'russia', 'echinopsis_pachanoi', 'touché', 'cytisus_scoparius', \ + 'white_island', 'bark', 'hi_hat', 'troglodytidae', 'key', \ + 'shop_assistant', 'clerk', 'kulak', 'crane', 'grus', \ + 'new_jersey', 'mayor', 'baltic', 'marsh', 'gardener', 'toasting', 'fry', 'gold_translations', "poor_person's_house", 'isochrone', 'tacit', \ + 'too', 'missouri', 'father_christmas', 'duce', 'stalinist']) + person_list, word2ner, block_list = self.create_multilingual_examples(person_en , 'PERSON', word2ner, block_list= block_list+ ['para_rubber', 'cosmic_dual_forces', 'book_of_changes', 'forth', 'boast', 'fist', 'zen', 'bunch', 'ostrich', 'spouse', 'woman', 'goatfish', 'wife', 'chaise_longue', 'outer_wall', 'butene', 'paralysis_agitans', 'shrub', 'weaver', 'plough', 'rich', 'algeria', 'cockchafer', \ + 'bumblebee', 'alaska', 'heart', 'flemish', 'schmidt_island', 'petro', 'herz_or_cycles_per_second', 'limb', \ + 'everyone', 'everybody', 'yes', 'logos', 'messiah', 'turner', 'gymnast', 'return', 'gy', 'freemason', 'mason', 'lake_edward', 'alabama', 'los_angeles', 'loss', 'losings', 'passing', 'steed', 'ross_island', \ + 'horse', 'rice', 'young', 'jr', 'japan_railways', 'jnr', 'gilbert_islands', 'slate', 'show', 'stone', 'stoned', 'nub', 'earthen', 'benedictine', 'fuse', 'oxford_shoe', 'dino_paul_crocetti', 'orphan_drug', \ + 'leninist','ash', 'hunt', 'brown', 'brown_university', 'breezy', 'fresh', 'normans', 'grant', 'grunt', 'moses_basket', 'musa', 'burton', 'marx', \ + 'negroid', 'gray', 'grey', 'why', 'wood', 'man', 'beeper', 'hong_kong', 'never', 'vomit', 'puke', "st_george's", 'massachuset', 'massachusetts', 'track_clearing_vehicle', \ + 'snowplow', 'word', 'ward', 'care', 'anger', 'grim', 'midnight', 'houston', 'farmer', 'post', 'morgan_horse', 'moody', \ + 'life_annuity', 'hooker', 'leaky', 'jogging', 'cooper', 'white', 'white_person', \ + 'russia', 'echinopsis_pachanoi', 'touché', 'cytisus_scoparius', \ + 'white_island', 'bark', 'hi_hat', 'troglodytidae', 'key', \ + 'shop_assistant', 'clerk', 'kulak', 'crane', 'grus', \ + 'new_jersey', 'mayor', 'baltic', 'marsh', 'gardener', 'toasting', 'fry', 'gold_translations', "poor_person's_house", 'isochrone', 'tacit', \ + 'too', 'missouri', 'father_christmas', 'duce', 'stalinist']) + + org_list, word2ner, block_list = self.create_multilingual_examples(organization_en, 'ORG', word2ner, block_list= block_list + ['u.s.a', 'axle', 'heart', 'pit', 'sister', 'ivy', 'stone', 'europa', 'octane', 'tripoli', 'eleven', 'uno', 'epi', 'fn', 'protester', 'work', 'time', 'service', 'commonwealth', 'acid', 'church', 'protestantism', 'quaker', 'sunni_muslim', 'anglicanism', 'baptist', 'united_states_of_america', 'eve', 'us', 'americas', 'normalized_projection_coordinates', 'non_player_character', 'aviation', 'dark_blue', 'personal_handyphone_system', 'iaca', 'which', 'identity', 'mu', 'storm_troopers', 'kingdom', 'might', 'orthodoxy', 'western_christianity', 'hassidism', 'jesuits','eicosapentaenoic_acid', 'woman', 'mail', 'bebop', 'computer_integrated_manufacturing', 'intersymbol_interference', 'ice', 'weak', 'doctor', 'first_lord_of_treasury', 'sixth_form', 'peddlers_and_carriers', 'utility', 'gallery', 'fiction', 'st', 'fantasy_fiction', 'workforce', 'working_force', 'manpower', 'criminal_law', 'proletariat', 'ourselves', 'overtake', 'trojan', 'have_good_meal', 'talk_of_town', 'royalty', 'armada', 'minority_peoples', 'enlightenment', 'almighty', 'high_society', 'showbusiness', 'every_so_often', 'occasionally', 'sometimes', 'once_in_while', 'nicaea', 'istanbul', 'constantinople', 'bridal_shower', 'nazism', 'bank', 'deposit', 'passkey', 'loper', 'ticket', 'amis', 'date', 'market', 'exchange','cdu', 'national_insurance', 'jobcentre', 'constitutional_nationalist_party', 'guomindang_or_kuomintang', 'plaza', 'shopping_center', 'center', 'forefront', 'vanguard', 'bigger_than', 'unknown', 'latte', 'qin', 'supply_network', 'coup', 'putsch', 'overthrow', 'dance_studio', 'yellow_river_or_huang_he', 'huang_ho', 'china’s_sorrow','band', 'syndicate', 'union', 'stag_do', 'greenhorn', 'municipality', 'prefecture', 'royal', 'hiring_hall', 'downtown', 'high_street', 'rainforest', 'group_sounds', "worker's_party", 'indus', 'step_by_step', 'gradually', 'one_by_one', 'by_degrees', 'mincing', 'another_name_for', 'institute', 'bliss', 'on_cloud_nine', 'intelligence', 'antigua_and_barbuda', 'icu', 'fisc', 'estate', 'someone_else', 'firefighter', 'civic_center', 'gum', 'think_factory', 'soldier', 'fdp', 'ldp', 'tropical_forest', 'refrain', 'customs', 'videoconferencing', 'house', 'interest', 'lobby', 'st_john’s', 'civil_right', 'schoolmate', 'academic', 'flock', 'handiwork', 'handicraft', 'wake', 'omnipotent', 'on_and_off', 'occasional', 'season', 'at_times', 'ever_and_anon', 'intermittently', 'frequently', 'often', 'amongst', 'incidentally', 'finn', 'every_now_and_then', 'seldom', 'at_long_intervals', 'downpour', 'byzantium', 'trade', 'mall', 'centre','bustling_street', 'shopping_district', 'kernel', 'midst', 'middle', 'inner_city', 'frontline', 'underground', 'avantgarde', 'head', 'salient', 'forward', 'senate', 'insurgency', 'subversion', 'horizontal_union', 'orchestra', 'ensemble', 'crying', 'weeping', 'gradual', 'stepwise', 'by_small_degrees', 'drop', 'slowly', 'incrementally', 'tardily', 'gently', 'little_for_each', 'in_course_of_time', 'military_personnel', 'fighter', 'serviceman', 'collegiate', 'initiation', 'homemade', 'craft', 'omnipotence', 'constantly', 'more_often_than_not', 'oftentimes', 'unexpectedness', 'emergency', 'thick', 'great_deal', 'commonly', 'oft', 'repeatedly', 'inula', 'frequent', 'btw', 'rarely', 'commercialize', 'marketing', 'shop', 'store', 'midfielder', 'mid_way', 'nucleus', 'center_field', 'cell_nucleus', 'hub', 'midpoint', 'central', 'centrum', 'heartland', 'centrism', 'hit', 'right_in_midst_of', 'right_at_height_of', 'intermediate', 'midplane', 'about_middle', 'advanced_guard', 'rebellion', 'lamenting', 'quietly', 'soon', 'steadily', 'progressively', 'oozing_out', 'slowly_permeating', 'slowly_soaking_in', 'seeping_out', 'slow', 'deliberately', 'suddenly', 'abruptly', 'whisper', 'leisurely', 'surname_xu', 'behind', 'sailor', 'warrior', 'military_strength', 'soldiers', 'legion', 'host', 'private']) + print ('num of items', len(word2ner)) + disease_list, word2ner, block_list = self.create_multilingual_examples(disease_list_en , 'DISEASE', word2ner, block_list=block_list + ['fume', 'shakes', 'see', 'pumpkinseed', 'calenture', 'insulation', 'heliotherapy', 'bleb', 'vesicle', 'hangnail', 'bubble', 'become_bruised', 'bluish_black', 'effort', 'judder', 'bowel', 'stooping', 'hungry', 'crossed_eyes', 'wound_suffered_in_fight', 'external_wound', 'purple_spot', 'hymen', 'kokborok', 'bow_leggedness', 'deuteranopic', 'concentration', 'vaccine', 'shin_splint', 'nasal_vowel', 'fistule', 'aphthous_fever', 'chimney', 'snake', 'ornitosis', 'steppe_murrain', 'vampirism', 'pustulate', 'blackhead', 'comedo', 'bread_mold', 'brand', 'mildew', 'oak_blight', "sow_one's_oats", 'skin', 'limp', 'hitch', 'polyopia', 'hindquarters', 'honeycomb', 'year', 'shawl', 'balance','shine', 'fan', 'rosaceae', 'rose_window', 'mound', 'comforter', 'strawberry', 'lollipop', 'croupy', 'useless', 'superfluous', 'clairvoyance', 'pesto', 'pain_in_ass', 'zostera', 'raft','germ', 'virus_that_infects_bacteria', 'amenorrheic', 'dizzy', 'dazzled', 'dazzle', 'giddy', 'feeling_of_swaying', 'fainting', 'dizzyness', 'dust_devil', 'blinding', 'probably', 'reeling', 'labored_breathing', 'panting', 'pant', 'abbot', 'volcanic_eruption', 'shrew', 'hiccups', 'abnormally_high_blood_sugar_level', 'weak_digestion', 'mule', 'bitterness', 'ketose', 'scruple', 'tingling', 'plight', 'miserable', 'asperity', 'harassment', 'dolor', 'tartar', 'dregs', 'sadness', 'whale', 'kipu', 'unpleasantness', 'quipu', 'pulse', 'extract_and_use', 'hamper', 'jerk', 'cramps', 'clamp', 'knock_on_effect', 'beech', 'wild_cherry', 'callous', 'rennet', 'curd', 'martyr', 'woe', 'flatulent', 'poignance', 'birth_pains', 'contractions', 'twinge', 'afflict', 'harass', 'cut_to_pieces', 'rack', 'persecute', 'crucifixion', 'agonize', 'painfully', 'convulsively', 'wince', 'convex', 'free_alongside_ship', 'beam', 'stage_fright', 'white_coloured_skin', 'hectic', \ + 'disinclination', 'morbidity', 'sob_convulsively', 'stranglehold', 'blockade', \ + 'suffocate', 'stifle', 'gag', 'house_mouse', 'sick', 'ailing', 'drowning', 'strangling',\ + 'deterioration', 'default_option', 'faint', 'mental_case', 'interruption', \ + 'nuisance', 'thirsty', 'famine', 'appetite', 'crave', 'drought', 'gose', \ + 'redden', 'turn_red', 'feel_hot', 'cauterize', 'red', 'turn_pink', 'repair',\ + 'form', 'state', 'mental_determination', 'exuberance', 'viability', 'vigour',\ + 'liveliness', 'coolness', 'emanation', 'shining', 'ray', 'tanned', 'sun_tanning', \ + 'darken', 'burn_off', 'sear', 'char', 'erupt', 'kindle', 'wrath', 'irritability', \ + 'burn_hole', 'set_afire', 'pique', 'luminous', 'prickling', 'blanch', \ + 'hanker', 'hydrogen', 'gravy', 'break_out', 'bleaching', 'difficulty', 'adversity', \ + 'sorrow', 'worry', 'powerlessness', 'inability', 'languor', 'dysgenics', 'grogginess', 'despondency', \ + 'tiredness', 'diffraction_grating', 'misrepresent', 'freak', 'plant_process', 'enlargement', 'hunch', \ + 'binge', 'rabia', 'choler', 'ire', 'bile', 'ferocity', 'furor', 'captivation', 'furious',\ + 'insanity', 'bluster', 'hot_anger', 'violent_rage', 'angry', 'resentment', 'swell', 'talisman', 'amulet', 'ignition', \ + 'node', 'bulge', 'self_conceited', 'torridity', 'hot_weather', 'carsickness', 'tide', 'korea', 'anxiety', 'delusion', \ + 'raving', 'nightmare', 'lettuce', 'babble', 'stuttering', 'bumble', 'gluttony', 'destitution', \ + 'what', 'ch_i', 'whether', 'flag', 'hangar', 'ordeal', 'sufferance', 'pain_and_difficulties', 'concern', 'distress_signal', 'grief', \ + 'attachment', 'pathological', 'disgust', 'nature_of_disease', 'demon_of_ill_health', 'fatigue', 'taint', 'catching', \ + 'spread', 'daze', 'misfortune', 'scathe', 'traumatism', 'score', 'infringement', 'violation', 'frisson', 'damage', 'impediment', 'traumatize', \ + 'tingle', 'prick', 'chagrin', 'be_sick', 'rankle', 'love_dearly', 'hurts', 'ail', 'simmer', 'if', 'fence', 'blemish', 'damnification', \ + 'nullity', 'cajolement', 'boiling_point', 'anginal', 'sharp_pain', 'griping_pain', 'sweetheart', 'melancholy', 'low', 'crisis', \ + 'craziness', 'morbid_fear', 'fissionable', 'cholesterol', 'suidae', 'cold_and_heat', 'malarial', 'tension', 'cave_in', 'crash', 'old',\ + 'fail', 'crumble', 'also', 'blunder', 'arrogance', 'amour_propre', 'greenery', 'tumo_u_r', 'plant', 'outgrowth', 'mass', 'tax', 'gavel', \ + 'able_man', 'fine_man', 'painful', 'raw', 'painfulness', 'bleed', 'bloodloss', 'resentful', 'suggillation', 'claw', 'architect', \ + 'hump', 'bozzo', 'hunk', 'dent', 'impact', 'protuberance', 'suspension', 'jolt', 'break_in', 'break_apart', 'fault', 'schism', 'breakage', 'tea', \ + 'break_off_relations_with', 'burst_open', 'obstruct', 'burstenness', 'severance', 'strut', 'stalemate', 'stab', 'bug_bite', 'compunction', 'resent', \ + 'encourage', 'stretch', 'dislocate', 'streak', 'linear_mark', 'mosquito', 'infestation', 'district', 'heatwave', 'tyrannize', 'screw', 'distort', 'twine', \ + 'tortuosity', 'quarrel', 'torsion', 'cistus', 'dartos', 'driveway', 'cigarette', 'contraction', 'incapacity', 'advantage', 'drawback', 'indolence', \ + 'fragility', 'palpitate', 'crown_shaped', 'hysterical', 'mishegoss', 'rampage', 'anomie', 'alarm', 'monkey', 'knob_on_tree', 'craw', 'neoplasia', 'spit', \ + 'skewer', 'swollen', 'gland', 'pick', 'pickaxe', 'fumigate', 'bay', 'tuberosity', 'nodule', 'large_breasts', 'reverse', 'brown', 'abrade', 'incision', 'nick',\ + 'attrition', 'rift', 'stria', 'paw', 'rub', 'stub', 'brush_against', 'scuff_mark', 'hack', 'chop', 'scarred_skin', 'insult', 'machine', 'cockroach', 'notch', 'slit', \ + 'brush', 'deletion', 'giulio_natta', 'be_paralyzed', 'standstill', 'paralytic', 'every_second_solar_term', \ + 'hindrance', 'flow', 'help', 'fuss', 'annoyance', 'scab', 'ringworm', 'fire_salamander', 'leper', 'rowan', 'nip', \ + 'shot', 'unevenness', 'lopsided', 'dissimilarity', 'unsoundness', 'deviation', 'falsehood', 'divergence', 'dependent', \ + 'outbuilding', 'reliance', 'relation', 'anesthetization', 'local_anesthetic', 'general_anesthetic', 'anesthesiologist', \ + 'bang', 'suppression', 'unrest', 'confusion', 'swage', 'sufferer', 'patient', 'irritate', 'eagerness', 'hankering', \ + 'willpower', 'warmheartedness', 'warmth', 'ardor', 'hot', 'bear', 'berry', 'hole', 'puberty', 'ardour', 'pulsation', 'vibe', 'love',\ + 'lecherousness', 'zeal', 'enthusiasm', 'violent_emotion', 'strong_emotion', 'temperature', 'displeasure', \ + 'burning_sensation', 'sultriness', 'blaze', 'passion_play', 'flame', 'shave', 'ferociousness', 'reproductive_procreative_power', \ + 'fruitfulness', 'fertility_rate', 'bloating', 'meteorism', 'fart', 'novelty', 'aplomb', 'carbon_oxide', 'high_fever', 'pyro', \ + 'filibuster', 'traffic_jam', 'brainwashing', 'drink', 'consequence', 'perplexity', 'parturiency', 'motherhood', \ + 'rest', 'deep_sleep', 'death', 'gound', 'quiescence', 'fruitlessness', 'unproductiveness', 'apparent_death', 'listlessness', 'stupor', 'apathy', \ + 'sleeplessness', 'eve', 'grinding', 'distortion', 'block', 'degeneration', 'regression_analysis', 'rancor', 'huff', 'sequence', \ + 'cross_eyed', 'sidelong', 'walleyes', 'stiff_neck', 'rearrangement', 'excited', 'longing', 'craving', 'wish', 'want', 'foreplay', \ + 'weakness', 'mischief', 'tribulation', 'health', 'discomfort', 'suffer', 'distressed', 'anguish', 'agonised', 'affect', 'have', \ + 'affection', 'misery', 'bout', 'sicken', 'menstruation', 'injured', 'wounded', 'injure', 'hardship', 'tin', 'skinny', + 'preponderance', 'fatness', 'silk', 'eunuch', 'side', 'seize', 'apprehend', 'take', 'more_commonly_known_as', 'goose_pimple', 'see_also', \ + 'gasp', 'clap', 'lobster', 'hit', 'trait', 'touch', 'ironing', 'fondle', 'fit', 'throw', 'chuck', 'terabyte', 'crayfish', 'consumption', \ + 'thickness', 'cold', 'fleshiness', 'caress', 'itch', 'blow', 'stoutness', 'crab']) + product_list, word2ner, block_list = self.create_multilingual_examples(product_en , 'PRODUCT', word2ner, block_list=block_list + ['promnesia', 'nude_body', 'celestial_object', 'moon', 'undoubtedly', 'jump_up', "leap_to_one's_feet", 'day_of_wren', "friar's_lantern", 'orb', 'dead_end_street', 'no_through_road', 'closure', 'cul', 'deadlock', 'catch_22', 'england', 'britain', 'kingdom_of_great_britain', 'britannia']) + #work_of_art_list, word2ner, block_list = self.create_multilingual_examples(work_of_art_en , 'WORK_OF_ART', word2ner, block_list=block_list) + word2ner = [(a,b) for a, b in word2ner if b not in ignore_ner_labels] + print ('num of items', len(word2ner)) + block_list = None + langs =[] + nerbylangs = {} + self.ontology = {} + self.ontology_compound_word_start = {} + word2ner = list(set(word2ner)) + for word,label in word2ner: + langs.extend(list(self.word2lang.get(word,[]))) + for lang in self.word2lang.get(word,[]): + nerbylangs[lang] = nerbylangs.get(lang, [])+ [label] + self.word2ner = word2ner = list(set([(word.translate(trannum), label) for word, label in word2ner])) + print ('num of items', len(word2ner)) + os.system(f"mkdir -p {tmp_dir}") + json.dump(word2ner, open(f"{tmp_dir}/{word2ner_file}", "w", encoding="utf8"), indent=1) + self.add_to_ontology(word2ner) + for lang in list(nerbylangs.keys()): + nerbylangs[lang]= Counter(nerbylangs[lang]).most_common() + for lang, cnt in Counter(langs).most_common(): + print ((lang, cnt)) + print (" "+ str(nerbylangs[lang])) + male_to_female_gender_swap = copy.copy(OntologyBuilder.male_to_female_gender_swap) + binary_gender_swap = copy.copy(OntologyBuilder.female_to_male_gender_swap) + other_gender_swap = copy.copy(OntologyBuilder.other_gender_swap) + + for a, b in male_to_female_gender_swap.items(): + binary_gender_swap[b] = a + + for word in language_list_en + race_list_en + jobs_en + religion_list_en: + word = word.replace(" ", "_").replace("-", "_").lower().strip(".") + for gender in ['female', 'woman', 'lady', 'gay', 'lesbian']: + for word2 in [gender+"_"+word, word+"_"+gender]: + if word2 in self.en: + for gender2 in ['male', 'man', 'person']: + for word3 in [gender2+"_"+word, word+"_"+gender2]: + if word3 in self.en: + if word2 not in binary_gender_swap: + binary_gender_swap[word2] = word3 + if word3 not in binary_gender_swap: + binary_gender_swap[word3] = word2 + word3 = word + if word3 in self.en: + if word3 not in ('white', 'black', 'brown') and word2 not in ('white', 'black', 'brown') : + if word2 not in binary_gender_swap: + binary_gender_swap[word2] = word3 + if word3 not in binary_gender_swap: + binary_gender_swap[word3] = word2 + + binary_gender_swap= self.create_multilingual_map(binary_gender_swap) + other_gender_swap= self.create_multilingual_map(other_gender_swap) + en_pronoun2gender= self.create_multilingual_map(self.pronoun2gender) + en_pronoun2pronoun= self.create_multilingual_map(self.pronoun2pronoun) + en_pronoun2title= self.create_multilingual_map(self.pronoun2title) + person2religion= self.create_multilingual_map(self.person2religion) + + #export formats and words from faker + lang2person = {} + for lang in OntologyBuilder.faker_list: + lang2 = lang.split("_")[0] + aHash = lang2person.get(lang2, {}) + if not hasattr(faker.providers.person, lang): + exec(f"import faker.providers.person.{lang}") + provider = getattr(faker.providers.person, lang) + if hasattr(provider.Provider, 'formats'): + ner_regexes = aHash.get('ner_regexes',[]) + if not type(provider.Provider.formats) is dict: + ner_regexes += [("PERSON", "|".join([a.replace("{{","<").replace("}}",">\d+").upper() for a in provider.Provider.formats]), False, ())] + else: + ner_regexes += [("PERSON", "|".join([a.replace("{{","<").replace("}}",">\d+").upper() for a in provider.Provider.formats.keys()]), False, ())] + aHash['ner_regexes'] = ner_regexes + if hasattr(provider.Provider, 'first_names_female'): + if not type(provider.Provider.first_names_female) is dict: + aHash['FIRST_NAME_FEMALE'] = list(set(aHash.get('FIRST_NAME_FEMALE', []) + list(provider.Provider.first_names_female))) + else: + aHash['FIRST_NAME_FEMALE'] = list(set(aHash.get('FIRST_NAME_FEMALE', []) + list(provider.Provider.first_names_female.keys()))) + if hasattr(provider.Provider, 'first_names_male'): + if not type(provider.Provider.first_names_female) is dict: + aHash['FIRST_NAME_MALE'] = list(set(aHash.get('FIRST_NAME_MALE', []) + list(provider.Provider.first_names_male))) + else: + aHash['FIRST_NAME_MALE'] = list(set(aHash.get('FIRST_NAME_MALE', []) + list(provider.Provider.first_names_male.keys()))) + if hasattr(provider.Provider, 'last_names_female'): + if not type(provider.Provider.last_names_female) is dict: + aHash['LAST_NAMES_FEMALE'] = list(set(aHash.get('LAST_NAMES_FEMALE', []) + list(provider.Provider.last_names_female))) + else: + aHash['LAST_NAMES_FEMALE'] = list(set(aHash.get('LAST_NAMES_FEMALE', []) + list(provider.Provider.last_names_female.keys()))) + if hasattr(provider.Provider, 'LAST_NAMES_MALE'): + if not type(provider.Provider.last_names_male) is dict: + aHash['LAST_NAMES_MALE'] = list(set(aHash.get('LAST_NAMES_MALE', []) + list(provider.Provider.last_names_male))) + else: + aHash['LAST_NAMES_MALE'] = list(set(aHash.get('LAST_NAMES_MALE', []) + list(provider.Provider.last_names_male.keys()))) + if hasattr(provider.Provider, 'prefixes_female'): + if not type(provider.Provider.prefixes_male) is dict: + aHash['PREFIX_FEMALE'] = list(set(aHash.get('PREFIX_FEMALE', []) + list(provider.Provider.prefixes_female))) + else: + aHash['PREFIX_FEMALE'] = list(set(aHash.get('PREFIX_FEMALE', []) + list(provider.Provider.prefixes_female.keys()))) + if hasattr(provider.Provider, 'prefixes_male'): + if not type(provider.Provider.prefixes_male) is dict: + aHash['PREFIX_MALE'] = list(set(aHash.get('PREFIX_MALE', []) + list(provider.Provider.prefixes_male))) + else: + aHash['PREFIX_MALE'] = list(set(aHash.get('PREFIX_MALE', []) + list(provider.Provider.prefixes_male.keys()))) + + if hasattr(provider.Provider, 'sufixes_female'): + if not type(provider.Provider.sufixes_male) is dict: + aHash['SUFIX_FEMALE'] = list(set(aHash.get('SUFIX_FEMALE', []) + list(provider.Provider.sufixes_female))) + else: + aHash['SUFIX_FEMALE'] = list(set(aHash.get('SUFIX_FEMALE', []) + list(provider.Provider.sufixes_female.keys()))) + if hasattr(provider.Provider, 'sufixes_male'): + if not type(provider.Provider.sufixes_male) is dict: + aHash['SUFIX_MALE'] = list(set(aHash.get('SUFIX_MALE', []) + list(provider.Provider.sufixes_male))) + else: + aHash['SUFIX_MALE'] = list(set(aHash.get('SUFIX_MALE', []) + list(provider.Provider.sufixes_male.keys()))) + + + if hasattr(provider.Provider, 'first_names'): + if not type(provider.Provider.first_names) is dict: + aHash['FIRST_NAME'] = list(set(aHash.get('FIRST_NAME', []) + list(provider.Provider.first_names))) + else: + aHash['FIRST_NAME'] = list(set(aHash.get('FIRST_NAME', []) + list(provider.Provider.first_names.keys()))) + if hasattr(provider.Provider, 'last_names'): + if not type(provider.Provider.last_names) is dict: + aHash['LAST_NAME'] = list(set(aHash.get('LAST_NAME', []) + list(provider.Provider.last_names))) + else: + aHash['LAST_NAME'] = list(set(aHash.get('LAST_NAME', []) + list(provider.Provider.last_names.keys()))) + lang2person[lang2] = aHash + + lang2extra = {} + for word, label in word2ner: + if word in self.word2lang: + if label == "OTHER_PRONOUN": + for lang in self.word2lang.get(word, []): + aHash = lang2person.get(lang, {}) + aHash[label] = aHash.get(label, []) + [word] + lang2person[lang] = aHash + else: + _, label2 = self.in_ontology(word) + if label2 != label: + for lang in self.word2lang.get(word,[]): + aHash = lang2extra.get(lang, {}) + aHash[label] = aHash.get(label, []) + [word] + lang2extra[lang] = aHash + + langs = list(set(list(lang2person.keys()) + list(binary_gender_swap.keys()) + list(other_gender_swap.keys()) + list(en_pronoun2gender.keys()) + list(en_pronoun2pronoun.keys()) + list(person2religion.keys()))) + for lang in langs: + if lang in ('sw',): + ret['LAST_NAME'] = list(set(ret.get('LAST_NAME', []) + [word.replace(" ", "_").replace("-", "_").lower().strip(".") for word in OntologyBuilder.bantu_surnames])) + + ret = lang2extra.get(lang, {}) + personHash = lang2person.get(lang, {}) + for key, val in personHash.items(): + #assume lang2exra are just lable => lists + if key in ret: + ret[key] = ret[key] + val + else: + ret[key] = val + ret['FIRST_NAME_MALE'] = list(set([word.replace(" ", "_").replace("-", "_").lower().strip(".") for word in ret.get('FIRST_NAME_MALE', [])])) + ret['LAST_NAME_MALE'] = list(set([word.replace(" ", "_").replace("-", "_").lower().strip(".") for word in ret.get('LAST_NAME_MALE', [])])) + ret['FIRST_NAME_FEMALE'] = list(set([word.replace(" ", "_").replace("-", "_").lower().strip(".") for word in ret.get('FIRST_NAME_FEMALE', [])])) + ret['LAST_NAME_FEMALE'] = list(set([word.replace(" ", "_").replace("-", "_").lower().strip(".") for word in ret.get('LAST_NAME_FEMALE', [])])) + ret['FIRST_NAME'] = list(set([word.replace(" ", "_").replace("-", "_").lower().strip(".") for word in ret.get('FIRST_NAME', [])])) + ret['LAST_NAME'] = list(set([word.replace(" ", "_").replace("-", "_").lower().strip(".") for word in ret.get('LAST_NAME', [])])) + ret['SUFIX_MALE'] = list(set([word.replace(" ", "_").replace("-", "_").lower().strip(".") for word in ret.get('SUFIX_MALE', [])])) + ret['SUFIX_FEMALE'] = list(set([word.replace(" ", "_").replace("-", "_").lower().strip(".") for word in ret.get('SUFIX_FEMALE', [])])) + + ret['binary_gender_swap'] = binary_gender_swap.get(lang, {}) + ret['other_gender_swap'] = other_gender_swap.get(lang, {}) + ret['en_pronoun2gender'] = en_pronoun2gender.get(lang, {}) + ret['en_pronoun2pronoun'] = en_pronoun2pronoun.get(lang, {}) + ret['en_pronoun2title'] = en_pronoun2title.get(lang, {}) + en_pronoun2title = ret['en_pronoun2title'] + ret['PREFIX_MALE'] = list(set([word.replace(" ", "_").replace("-", "_").lower().strip(".") for word in en_pronoun2title.get('he',[])+ret.get('PREFIX_MALE', [])])) + ret['PREFIX_FEMALE'] = list(set([word.replace(" ", "_").replace("-", "_").lower().strip(".") for word in en_pronoun2title.get('she',[])+ret.get('PREFIX_FEMALE', [])])) + ret['person2religion'] = person2religion.get(lang, {}) + if lang == 'en': + ret['ner_regexes'] = ret.get('ner_regexes',[]) + OntologyBuilder.default_ner_regexes + json.dump(ret, open(f"{data_dir}/{lang}.json", "w", encoding="utf8"), indent=1) + self.save_x_lingual_lexicon_prefix_file() + + def load_ontology(self, word2ner_file=None): + data_dir = self.data_dir + tmp_dir = self.tmp_dir + if not os.path.exists(word2ner_file): + word2ner_file = f"{tmp_dir}/{word2ner_file}" + return json.load(open(word2ner_file, "rb").decode()) + + def word2cat(self): + tmp_dir = self.tmp_dir + cat2word = json.load(open(f"{tmp_dir}/conceptnet_ontology_cat2word.json", "rb").decode()) + from collections import Counter + lst = list(cat2word.items()) + lst.sort(key=lambda a: a[1], reverse=True) + print (lst[:10]) + word2cat= {} + for cat, words in cat2word.items(): + for word in words: + word2cat[word] = cat + return word2cat + + def create_multilingual_map(self, en_examples, allow_list=None, cut_off_abs=4, ): + en = self.en + word2en = self.word2en + word2lang = self.word2lang + keys = list(en_examples.keys()) + allow_list = dict([(a, 1) for a in allow_list or []]) + ret_hash = {} + print (keys) + if not keys: return ret_hash + if type(en_examples[keys[0]]) is dict: + for item in keys: + mapHash = en_examples[item] + for key in mapHash.keys(): + words = [word.replace(" ", "_").replace("-", "_").lower().strip(".") for word in mapHash[key]] + for word in words: + if word not in en: + continue + words2 = [word2 for word2 in en[word] if len(word2en[word2]) <= cut_off_abs] + if not words2: + continue + words2.sort(key=lambda a: len(a)) + word2 = words2[0] + for lang in word2lang.get(word2,[]): + aHash = ret_hash.get(lang, {}) + if allow_list is not None and word2 not in allow_list: continue + aHash[item] = list(set(list(aHash.get(item, [])) + [word2])) + ret_hash[lang] = aHash + elif type(en_examples[keys[0]]) is list: + for item, words in en_examples.items(): + lang2words = {} + for key2 in words: + key2 = key2.replace(" ", "_").replace("-", "_").lower().strip(".") + lang2words_list = itertools.chain(*[[(lang, word2) for lang in word2lang.get(word2, ['en'] if word2 == key2 else [])] \ + for word2 in en.get(key2, []) + [key2] if word2 == key2 or (word2 in word2en and len(word2en[word2])) <= cut_off_abs]) + + for lang, word2 in lang2words_list: + lang2words[lang] = lang2words.get(lang, []) + [word2] + lang2words['en'] = words + for lang, words2 in lang2words.items(): + aHash = ret_hash.get(lang, {}) + for word in words2: + if allow_list and word not in allow_list: continue + aHash[item] = list(set(aHash.get(item, []) + [word])) + ret_hash[lang] = aHash + else: + for key in en_examples: + key2 = en_examples[key] + key = key.replace(" ", "_").replace("-", "_").lower().strip(".") + if key not in en: + continue + lang2words_list = itertools.chain(*[[(lang, word) for lang in word2lang.get(word, ['en'] if word == key else [])] \ + for word in en.get(key, []) + [key] if word == key or (word in word2en and len(word2en[word])) <= cut_off_abs]) + lang2words = {} + for lang, word in lang2words_list: + lang2words[lang] = lang2words.get(lang, []) + [word] + lang2words['en'] = [key] + key2 = key2.replace(" ", "_").replace("-", "_").lower().strip(".") + lang2words2_list = itertools.chain(*[[(lang, word2) for lang in word2lang.get(word2, ['en'] if word2 == key2 else [])] \ + for word2 in en.get(key2, []) + [key2] if word2 == key2 or (word2 in word2en and len(word2en[word2])) <= cut_off_abs]) + lang2words2 = {} + for lang, word2 in lang2words2_list: + lang2words2[lang] = lang2words2.get(lang, []) + [word2] + lang2words2['en'] = [key2] + for lang in lang2words.keys(): + for word in lang2words[lang]: + if allow_list and word not in allow_list: continue + if lang not in lang2words2: continue + word2 = random.choice(lang2words2[lang]) + if word2 == word: + word2 = random.choice(lang2words2[lang]) + if word2 == word: continue + if allow_list and word2 not in allow_list: continue + aHash = ret_hash.get(lang, {}) + aHash[word] = word2 + ret_hash[lang] = aHash + return ret_hash + + def create_multilingual_examples(self, en_examples, ner_label, word2ner, block_list=[], cut_off_abs=5, cut_off_per=0.5): + def has_any(words, aSet): + for w in words: + if w in aSet: return True + return False + block_list = set(block_list) + en = self.en + word2en = self.word2en + ret_list = [] + ret_hash = dict([(word.replace(" ", "_").replace("-", "_").lower().strip("."), 1) for word in en_examples]) + added = list(ret_hash.keys()) + for i in range(3): + added2 = [] + for word in added: + if word not in en: continue + found = [(w, word2en[w]) for w in en[word]] + found = [(w, [w2 for w2 in word2en[w] if w2 not in ret_hash], len([w2 for w2 in word2en[w] if w2 not in ret_hash])/len(word2en[w])) for w in en[word] if not has_any(word2en[w], block_list)] + found = [a for a in found if len(a[1]) < cut_off_abs and a[2] < cut_off_per] + unk = list(itertools.chain(*[a[1] for a in found])) + if found: + #print (word, found) + added2.extend(unk) + ret_list.extend([a[0] for a in found]) + if not added: + break + else: + #print (ner_label, Counter(added2)) + added = [a[0] for a in Counter(added2).items () if a[1] > 1] + #print (ner_label, added) + if not added: + break + for word in added: + ret_hash[word] = 1 + block_list = list(set(list(block_list) + (ret_list + list(ret_hash.keys())))) + ret = [(a, ner_label) for a in list(set(ret_list + list(ret_hash.keys())))] + return ret, word2ner + ret, block_list + + +if __name__ == "__main__": + data_dir = tmp_dir = None + if "-s" in sys.argv: + tmp_dir = sys.argv[sys.argv.index("-s")+1] + if "-c" in sys.argv: + builder = OntologyBuilder(tmp_dir=tmp_dir, data_dir=data_dir) + rel2 = builder.save_cross_lingual_ontology() + diff --git a/data_tooling/pii_processing/ontology/ontology_builder_data.py b/data_tooling/pii_processing/ontology/ontology_builder_data.py new file mode 100644 index 0000000..d6c38a2 --- /dev/null +++ b/data_tooling/pii_processing/ontology/ontology_builder_data.py @@ -0,0 +1,1362 @@ +# coding=utf-8 +# Copyright, 2021 Ontocord, LLC, All rights reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +class OntologyBuilderData: + + """ Predefined preliminary labels """ + + #from https://github.com/madisonmay/CommonRegex/blob/master/commonregex.py which is under the MIT License + # see also for ICD https://stackoverflow.com/questions/5590862/icd9-regex-pattern - but this could be totally wrong! + # we do regex in this order in order to not capture ner inside domain names and email addresses. + default_ner_regexes = [ + ("DOMAIN_NAME" , '(?i)((?:https?://|www\d{0,3}[.])?[a-z0-9.\-]+[.](?:(?:international)|(?:construction)|(?:contractors)|(?:enterprises)|(?:photography)|(?:immobilien)|(?:management)|(?:technology)|(?:directory)|(?:education)|(?:equipment)|(?:institute)|(?:marketing)|(?:solutions)|(?:builders)|(?:clothing)|(?:computer)|(?:democrat)|(?:diamonds)|(?:graphics)|(?:holdings)|(?:lighting)|(?:plumbing)|(?:training)|(?:ventures)|(?:academy)|(?:careers)|(?:company)|(?:domains)|(?:florist)|(?:gallery)|(?:guitars)|(?:holiday)|(?:kitchen)|(?:recipes)|(?:shiksha)|(?:singles)|(?:support)|(?:systems)|(?:agency)|(?:berlin)|(?:camera)|(?:center)|(?:coffee)|(?:estate)|(?:kaufen)|(?:luxury)|(?:monash)|(?:museum)|(?:photos)|(?:repair)|(?:social)|(?:tattoo)|(?:travel)|(?:viajes)|(?:voyage)|(?:build)|(?:cheap)|(?:codes)|(?:dance)|(?:email)|(?:glass)|(?:house)|(?:ninja)|(?:photo)|(?:shoes)|(?:solar)|(?:today)|(?:aero)|(?:arpa)|(?:asia)|(?:bike)|(?:buzz)|(?:camp)|(?:club)|(?:coop)|(?:farm)|(?:gift)|(?:guru)|(?:info)|(?:jobs)|(?:kiwi)|(?:land)|(?:limo)|(?:link)|(?:menu)|(?:mobi)|(?:moda)|(?:name)|(?:pics)|(?:pink)|(?:post)|(?:rich)|(?:ruhr)|(?:sexy)|(?:tips)|(?:wang)|(?:wien)|(?:zone)|(?:biz)|(?:cab)|(?:cat)|(?:ceo)|(?:com)|(?:edu)|(?:gov)|(?:int)|(?:mil)|(?:net)|(?:onl)|(?:org)|(?:pro)|(?:red)|(?:tel)|(?:uno)|(?:xxx)|(?:ac)|(?:ad)|(?:ae)|(?:af)|(?:ag)|(?:ai)|(?:al)|(?:am)|(?:an)|(?:ao)|(?:aq)|(?:ar)|(?:as)|(?:at)|(?:au)|(?:aw)|(?:ax)|(?:az)|(?:ba)|(?:bb)|(?:bd)|(?:be)|(?:bf)|(?:bg)|(?:bh)|(?:bi)|(?:bj)|(?:bm)|(?:bn)|(?:bo)|(?:br)|(?:bs)|(?:bt)|(?:bv)|(?:bw)|(?:by)|(?:bz)|(?:ca)|(?:cc)|(?:cd)|(?:cf)|(?:cg)|(?:ch)|(?:ci)|(?:ck)|(?:cl)|(?:cm)|(?:cn)|(?:co)|(?:cr)|(?:cu)|(?:cv)|(?:cw)|(?:cx)|(?:cy)|(?:cz)|(?:de)|(?:dj)|(?:dk)|(?:dm)|(?:do)|(?:dz)|(?:ec)|(?:ee)|(?:eg)|(?:er)|(?:es)|(?:et)|(?:eu)|(?:fi)|(?:fj)|(?:fk)|(?:fm)|(?:fo)|(?:fr)|(?:ga)|(?:gb)|(?:gd)|(?:ge)|(?:gf)|(?:gg)|(?:gh)|(?:gi)|(?:gl)|(?:gm)|(?:gn)|(?:gp)|(?:gq)|(?:gr)|(?:gs)|(?:gt)|(?:gu)|(?:gw)|(?:gy)|(?:hk)|(?:hm)|(?:hn)|(?:hr)|(?:ht)|(?:hu)|(?:id)|(?:ie)|(?:il)|(?:im)|(?:in)|(?:io)|(?:iq)|(?:ir)|(?:is)|(?:it)|(?:je)|(?:jm)|(?:jo)|(?:jp)|(?:ke)|(?:kg)|(?:kh)|(?:ki)|(?:km)|(?:kn)|(?:kp)|(?:kr)|(?:kw)|(?:ky)|(?:kz)|(?:la)|(?:lb)|(?:lc)|(?:li)|(?:lk)|(?:lr)|(?:ls)|(?:lt)|(?:lu)|(?:lv)|(?:ly)|(?:ma)|(?:mc)|(?:md)|(?:me)|(?:mg)|(?:mh)|(?:mk)|(?:ml)|(?:mm)|(?:mn)|(?:mo)|(?:mp)|(?:mq)|(?:mr)|(?:ms)|(?:mt)|(?:mu)|(?:mv)|(?:mw)|(?:mx)|(?:my)|(?:mz)|(?:na)|(?:nc)|(?:ne)|(?:nf)|(?:ng)|(?:ni)|(?:nl)|(?:no)|(?:np)|(?:nr)|(?:nu)|(?:nz)|(?:om)|(?:pa)|(?:pe)|(?:pf)|(?:pg)|(?:ph)|(?:pk)|(?:pl)|(?:pm)|(?:pn)|(?:pr)|(?:ps)|(?:pt)|(?:pw)|(?:py)|(?:qa)|(?:re)|(?:ro)|(?:rs)|(?:ru)|(?:rw)|(?:sa)|(?:sb)|(?:sc)|(?:sd)|(?:se)|(?:sg)|(?:sh)|(?:si)|(?:sj)|(?:sk)|(?:sl)|(?:sm)|(?:sn)|(?:so)|(?:sr)|(?:st)|(?:su)|(?:sv)|(?:sx)|(?:sy)|(?:sz)|(?:tc)|(?:td)|(?:tf)|(?:tg)|(?:th)|(?:tj)|(?:tk)|(?:tl)|(?:tm)|(?:tn)|(?:to)|(?:tp)|(?:tr)|(?:tt)|(?:tv)|(?:tw)|(?:tz)|(?:ua)|(?:ug)|(?:uk)|(?:us)|(?:uy)|(?:uz)|(?:va)|(?:vc)|(?:ve)|(?:vg)|(?:vi)|(?:vn)|(?:vu)|(?:wf)|(?:ws)|(?:ye)|(?:yt)|(?:za)|(?:zm)|(?:zw))(?:/[^\s()<>]+[^\s`!()\[\]{};:\'".,<>?\xab\xbb\u201c\u201d\u2018\u2019])?)', True, ()), + ("EMAIL_ADDRESS" , "([a-z0-9!#$%&'*+\/=?^_`{|.}~-]+@(?:[a-z0-9](?:[a-z0-9-]*[a-z0-9])?\.)+[a-z0-9](?:[a-z0-9-]*[a-z0-9])?)", False, ()), #should be first or second + ("USER_NAME" , "^[a-z0-9](@[a-z0-9!#$%&'*+\/=?^_`{|.}~-]+)", True, ()), + ("DATE" , '(?:(?;:'\"" + + yago_upper_ontology = { + 'ACCOMMODATION': 'FAC', + 'ADMINISTRATIVE_AREA': 'GPE', + 'AIRLINE': 'ORG', + 'AIRPORT': 'FAC', + 'AMUSEMENT_PARK': 'FAC', + 'ANATOMICAL_STRUCTURE': 'ANAT', + 'ANIMAL_SHELTER': 'FAC', + 'APARTMENT': 'FAC', + 'AQUARIUM': 'FAC', + 'ARCHIVE_ORGANIZATION': 'ORG', + 'ARTERY': 'ANAT', + 'ARTICLE': 'WORK_OF_ART', + 'ART_GALLERY': 'FAC', + 'ATLAS': 'WORK_OF_ART', + 'AUTOMOTIVE_BUSINESS': 'ORG', + 'AUTO_RENTAL': 'FAC', + 'BAKERY': 'FAC', + 'BANK_OR_CREDIT_UNION': 'ORG', + 'BAR_OR_PUB': 'FAC', + 'BEACH': 'LOCATION', + 'BEAUTY_SALON': 'FAC', + 'BED_AND_BREAKFAST': 'FAC', + 'BLOG': 'WORK_OF_ART', + 'BLOG_POSTING': 'WORK_OF_ART', + 'MEDICAL_PROCEDURE': 'MEDICAL_THERAPY', + 'BLOOD_TEST': 'MEDICAL_THERAPY', + 'BODY_OF_WATER': 'LOCATION', + 'BONE': 'ANAT', + 'BOOK': 'WORK_OF_ART', + 'BOOK_SERIES': 'WORK_OF_ART', + 'BOOK_STORE': 'FAC', + 'BOWLING_ALLEY': 'FAC', + 'BRAND': 'ORG', + 'BREWERY': 'FAC', + 'BRIDGE': 'FAC', + 'BROADCAST_CHANNEL': 'ORG', + 'BROADCAST_SERVICE': 'PRODUCT', + 'BUDDHIST_TEMPLE': 'FAC', + 'BUS_OR_COACH':'PRODUCT', + 'BUS_STATION': 'FAC', + 'BUS_STOP': 'FAC', + 'CAFE_OR_COFFEE_SHOP': 'FAC', + 'CAMPGROUND': 'FAC', + 'CANAL': 'LOCATION', + 'CAR': 'PRODUCT', + 'CASINO': 'FAC', + 'CATHOLIC_CHURCH': 'FAC', + 'CEMETERY': 'FAC', + 'CHAPTER': 'WORK_OF_ART', + 'CHILD_CARE':'PRODUCT', + 'CHURCH': 'FAC', + 'CITY': 'GPE', + 'CITY_HALL': 'FAC', + 'CIVIC_STRUCTURE': 'FAC', + 'COLLECTION': 'WORK_OF_ART', + 'COLLEGE_OR_UNIVERSITY': 'ORG', + 'COMEDY_CLUB': 'FAC', + 'COMIC_SERIES': 'WORK_OF_ART', + 'COMIC_STORY': 'WORK_OF_ART', + 'COMPUTER_LANGUAGE': 'LANGUAGE', + 'CONTINENT': 'LOCATION', + 'CORPORATION': 'ORG', + 'COUNTRY': 'GPE', + 'COURSE': 'EVENT', + 'COURTHOUSE': 'FAC', + 'CREATIVE_WORK': 'WORK_OF_ART', + 'CREATIVE_WORK_SEASON': 'WORK_OF_ART', + 'CREATIVE_WORK_SERIES': 'WORK_OF_ART', + 'CREMATORIUM': 'FAC', + 'DANCE_GROUP': 'ORG', + 'DATASET': 'WORK_OF_ART', + 'DATA_CATALOG': 'WORK_OF_ART', + 'DAY_SPA': 'FAC', + 'DEFENCE_ESTABLISHMENT': 'ORG', + 'DIAGNOSTIC_PROCEDURE': 'MEDICAL_THERAPY', + 'DISTILLERY': 'FAC', + 'DRAWING': 'WORK_OF_ART', + 'DRUG': 'PRODUCT', + 'DRUG_LEGAL_STATUS': 'LAW', + 'EDUCATIONAL_ORGANIZATION': 'ORG', + 'ELEMENTARY_SCHOOL': 'FAC', + 'EMBASSY': 'FAC', + 'EMERGENCY_SERVICE': 'PRODUCT', + 'EMPLOYMENT_AGENCY': 'ORG', + 'ENTERTAINMENT_BUSINESS': 'ORG', + 'EPISODE': 'WORK_OF_ART', + 'EVENT_SERIES': 'EVENT', + 'EVENT_VENUE': 'FAC', + 'FESTIVAL': 'EVENT', + 'FINANCIAL_PRODUCT': 'PRODUCT', + 'FINANCIAL_SERVICE': 'PRODUCT', + 'FIRE_STATION': 'FAC', + 'FOOD_ESTABLISHMENT': 'FAC', + 'GAME': 'PRODUCT', + 'GAS_STATION': 'FAC', + 'GENE': 'BIO_CHEM_ENTITY', + 'GOLF_COURSE': 'FAC', + 'GOVERNMENT_BUILDING': 'FAC', + 'GOVERNMENT_OFFICE': 'FAC', + 'GOVERNMENT_ORGANIZATION': 'ORG', + 'GROCERY_STORE': 'FAC', + 'HEALTH_AND_BEAUTY_BUSINESS': 'ORG', + 'HEALTH_CLUB': 'FAC', + 'HINDU_TEMPLE': 'FAC', + 'HOSPITAL': 'FAC', + 'HOSTEL': 'FAC', + 'HOTEL': 'FAC', + 'HOUSE': 'FAC', + 'ICE_CREAM_SHOP':'FAC', + 'INFECTIOUS_DISEASE': 'DISEASE', + 'JOINT': 'ANAT', + 'LAKE_BODY_OF_WATER': 'LOCATION', + 'LANDFORM': 'LOCATION', + 'LANDMARKS_OR_HISTORICAL_BUILDINGS': 'FAC', + 'LEGISLATION': 'LAW', + 'LIBRARY':'FAC', + 'LIGAMENT': 'ANAT', + 'LIQUOR_STORE':'FAC', + 'LOCAL_BUSINESS': 'ORG', + 'LODGING_BUSINESS': 'ORG', + 'MANUSCRIPT': 'WORK_OF_ART', + 'MAP': 'WORK_OF_ART', + 'MEDICAL_BUSINESS': 'ORG', + 'MEDICAL_CLINIC': 'FAC', + 'MEDICAL_DEVICE': 'PRODUCT', + 'MEDICAL_ENTITY': 'THING', + 'MEDICAL_GUIDELINE': 'WORK_OF_ART', + 'MEDICAL_ORGANIZATION': 'ORG', + 'MEDICAL_SIGN': 'MEDICAL_SYMPTOM', + 'MEDICAL_SIGN_OR_SYMPTOM': 'MEDICAL_SYMPTOM', + 'MEDICAL_SPECIALTY': 'JOB', + 'MEDICAL_TEST': 'MEDICAL_THERAPY', + 'MIDDLE_SCHOOL': 'FAC', + 'MOBILE_APPLICATION': 'WORK_OF_ART', + 'MOLECULAR_ENTITY': 'BIO_CHEM_ENTITY', + 'MOSQUE': 'FAC', + 'MOTEL': 'FAC', + 'MOTORCYCLE': 'PRODUCT', + 'MOUNTAIN': 'LOCATION', + 'MOVIE': 'WORK_OF_ART', + 'MOVIE_THEATER': 'FAC', + 'MUSCLE': 'ANAT', + 'MUSEUM':'FAC', + 'MUSIC_ALBUM': 'WORK_OF_ART', + 'MUSIC_COMPOSITION': 'WORK_OF_ART', + 'MUSIC_GROUP': 'ORG', + 'MUSIC_PLAYLIST': 'WORK_OF_ART', + 'MUSIC_VENUE': 'FAC', + 'NAIL_SALON': 'FAC', + 'NERVE': 'ANAT', + 'NEWSPAPER': 'ORG', + 'NEWS_ARTICLE': 'WORK_OF_ART', + 'NIGHT_CLUB': 'FAC', + 'N_G_O': 'ORG', + 'OCCUPATION': 'JOB', + 'OCEAN_BODY_OF_WATER': 'LOCATION', + 'OPTICIAN': 'JOB', + 'ORGANIZATION': 'ORG', + 'OUTLET_STORE': 'FAC', + 'PAINTING': 'WORK_OF_ART', + 'PARK': 'LOC', + 'PARKING_FACILITY': 'FAC', + 'PAWN_SHOP': 'FAC', + 'PERFORMING_ARTS_THEATER': 'FAC', + 'PERFORMING_GROUP': 'ORG', + 'PERIODICAL': 'WORK_OF_ART', + 'PERSON': 'PERSON', + 'PET_STORE': 'FAC', + 'PHARMACY': 'FAC', + 'PHOTOGRAPH': 'WORK_OF_ART', + 'PHYSICAL_EXAM': 'MEDICAL_THERAPY', + 'PLACE': 'LOCATION', + 'PLACE_OF_WORSHIP': 'FAC', + 'PLAY': 'WORK_OF_ART', + 'PLAYGROUND': 'FAC', + 'PODCAST_SERIES': 'WORK_OF_ART', + 'POLICE_STATION': 'FAC', + 'POND': 'LOCATION', + 'POSTER': 'WORK_OF_ART', + 'POST_OFFICE': 'FAC', + 'PRESCHOOL': 'FAC', + 'PROTEIN': 'BIO_CHEM_ENTITY', + 'PUBLICATION_ISSUE': 'WORK_OF_ART', + 'PUBLICATION_VOLUME': 'WORK_OF_ART', + 'PUBLIC_SWIMMING_POOL': 'FAC', + 'PUBLIC_TOILET': 'FAC', + 'RADIATION_THERAPY': 'MEDICAL_THERAPY', + 'RADIO_CHANNEL': 'ORG', + 'RADIO_SERIES': 'WORK_OF_ART', + 'RADIO_STATION': 'FAC', + 'RATING': 'QUANTITY', + 'RECYCLING_CENTER': 'FAC', + 'REPORT': 'WORK_OF_ART', + 'RESERVOIR': 'LOCATION', + 'RESORT': 'FAC', + 'RESTAURANT': 'FAC', + 'RIVER_BODY_OF_WATER': 'LOCATION', + 'SCHOLARLY_ARTICLE': 'WORK_OF_ART', + 'SCHOOL': 'FAC', + 'SCULPTURE': 'WORK_OF_ART', + 'SEA_BODY_OF_WATER': 'LOCATION', + 'SELF_STORAGE': 'PRODUCT', + 'SERVICE':'PRODUCT', + 'SHEET_MUSIC': 'WORK_OF_ART', + 'SHOE_STORE': 'FAC', + 'SHOPPING_CENTER': 'FAC', + 'SKI_RESORT': 'FAC', + 'SOCIAL_MEDIA_POSTING': 'WORK_OF_ART', + 'SOFTWARE_APPLICATION': 'WORK_OF_ART', + 'SPORTS_ACTIVITY_LOCATION': 'FAC', + 'SPORTS_EVENT': 'EVENT', + 'SPORTS_ORGANIZATION': 'ORG', + 'SPORTS_TEAM': 'ORG', + 'STADIUM_OR_ARENA': 'FAC', + 'STATE': 'GPE', + 'STORE': 'FAC', + 'SUBWAY_STATION': 'FAC', + 'SURGICAL_PROCEDURE': 'MEDICAL_THERAPY', + 'SYNAGOGUE': 'FAC', + 'TATTOO_PARLOR': 'FAC', + 'TAXON': 'ANIMAL', + 'TELEVISION_CHANNEL': 'ORG', + 'TELEVISION_STATION': 'FAC', + 'TENNIS_COMPLEX': 'FAC', + 'THEATER_GROUP': 'ORG', + 'THERAPEUTIC_PROCEDURE': 'MEDICAL_THERAPY', + 'THESIS': 'WORK_OF_ART', + 'TOURIST_ATTRACTION': 'FAC', + 'TOURIST_INFORMATION_CENTER': 'FAC', + 'TOY_STORE': 'FAC', + 'TRAIN_STATION': 'FAC', + 'TRAVEL_AGENCY': 'ORG', + 'T_V_EPISODE': 'WORK_OF_ART', + 'T_V_SEASON': 'WORK_OF_ART', + 'T_V_SERIES': 'WORK_OF_ART', + 'VEHICLE': 'PRODUCT', + 'VEIN': 'ANAT', + 'VIDEO_GAME': 'PRODUCT', + 'VIDEO_GAME_SERIES': 'EVENT', + 'VISUAL_ARTWORK': 'WORK_OF_ART', + 'VOLCANO': 'LOCATION', + 'WATERFALL': 'LOCATION', + 'WEB_PAGE': 'WORK_OF_ART', + 'WEB_SITE': 'DOMAIN_NAME', + 'WINERY': 'FAC', + 'WORKERS_UNION': 'UNION', + 'ZOO': 'FAC'} diff --git a/data_tooling/pii_processing/ontology/ontology_manager.py b/data_tooling/pii_processing/ontology/ontology_manager.py new file mode 100644 index 0000000..52195dd --- /dev/null +++ b/data_tooling/pii_processing/ontology/ontology_manager.py @@ -0,0 +1,552 @@ +# coding=utf-8 +# Copyright, 2021 Ontocord, LLC, All rights reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +from random import sample +import glob, os, re +import multiprocessing + +import gzip +import os, argparse +import itertools +from collections import Counter, OrderedDict +import os +import json +import threading +import numpy as np +import os +import time +import json +import copy + +from time import time +import numpy as np +from collections import Counter +from itertools import chain +import glob +import json +import math, os +import random +import transformers +import sys, os +import json +import faker +import gzip +from faker.providers import person, job + +from collections import Counter +import re +import gzip +import urllib +import re +from transformers import AutoTokenizer +from nltk.corpus import stopwords + +sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), + os.path.pardir, os.path.pardir, os.path.pardir))) +from data_tooling.pii_processing.ontology.stopwords import stopwords as stopwords_ac_dc +mt5_underscore= "▁" +trannum = str.maketrans("0123456789", "1111111111") + +class OntologyManager: + """ + Basic ontology manager. Stores the upper ontology and lexicon that + maps to the leaves of the ontology. Has functions to determine + whether a word is in the ontology, and to tokenize a sentence with + words from the ontology. + """ + + default_strip_chars="-,~`.?!@#$%^&*(){}[]|\\/-_+=<>;'\"" + stopwords_wn = set(stopwords.words()) + x_lingual_onto_name = "yago_cn_wn" + default_data_dir = os.path.abspath(os.path.join(os.path.dirname(__file__), "data")) + + default_label2label = {'SOC_ECO_CLASS':'NORP', + 'RACE':'NORP', + 'POLITICAL_PARTY':'NORP', + 'UNION':'NORP', + 'RELIGION':'NORP', + 'RELIGION_MEMBER': 'NORP', + 'POLITICAL_PARTY_MEMBER': 'NORP', + 'UNION_MEMBER': 'NORP' + } + + default_upper_ontology = { + 'PERSON': ['PERSON'], + 'PUBLIC_FIGURE': ['PUBLIC_FIGURE', 'PERSON'], + 'ORG': ['ORG'], + 'NORP': ['NORP', 'ORG'], + 'AGE': ['AGE'], + 'DISEASE': ['DISEASE'], + 'STREET_ADDRESS': ['STREET_ADDRESS', 'LOC'], + 'GPE': ['GPE', 'LOC'], + 'CREDIT_CARD': ['CREDIT_CARD', 'CARDINAL'], + 'EMAIL_ADDRESS': ['EMAIL_ADDRESS', 'ELECTRONIC_ADDRESS'], + 'GOVT_ID': ['GOVT_ID', 'CARDINAL'], + } + def __init__(self, target_lang="", data_dir=None, tmp_dir=None, max_word_len=4, compound_word_step =3, strip_chars=None, \ + upper_ontology=None, x_lingual_lexicon_by_prefix_file="lexicon_by_prefix.json.gz", target_lang_data_file=None, x_lingual2ner_file=None, \ + connector = "_", label2label=None, min_word_len=5): + self.mt5_tokenizer = AutoTokenizer.from_pretrained("google/mt5-small") + self.target_lang_lexicon = {} + self.x_lingual_lexicon_by_prefix = {} + self.target_lang = target_lang + self.stopwords = set(stopwords_ac_dc.get(target_lang,[])+ list(self.stopwords_wn)) + self._max_lexicon = 0 + if data_dir is None: data_dir = self.default_data_dir + if tmp_dir is None: tmp_dir = "/tmp/pii_processing/" + os.system(f"mkdir -p {data_dir}") + os.system(f"mkdir -p {tmp_dir}") + self.tmp_dir = tmp_dir + self.data_dir = data_dir + if strip_chars is None: + strip_chars = self.default_strip_chars + self.strip_chars_set = set(strip_chars) + self.strip_chars = strip_chars + self.connector = connector + self.max_word_len = max_word_len + self.min_word_len = min_word_len + self.compound_word_step = compound_word_step + if label2label is None: + label2label = self.default_label2label + self.label2label=label2label + if upper_ontology is None: + upper_ontology = self.default_upper_ontology + self.ontology = OrderedDict() + self.load_upper_ontology(upper_ontology) + self.load_x_lingual_lexicon_from_prefix_file(x_lingual_lexicon_by_prefix_file) + if x_lingual2ner_file is not None: + self.load_x_lingual_lexicon_from_x_lingual2ner_file(x_lingual2ner_file) + if target_lang_data_file is None and target_lang: + target_lang_data_file = f"{data_dir}/{target_lang}.json" + if target_lang_data_file is not None: + self.load_target_lang_data(target_lang_data_file, target_lang=target_lang) + #used for cjk processing + + def load_upper_ontology(self, upper_ontology): + # TODO: load and save from json file + if upper_ontology is None: upper_ontology = {} + + self.upper_ontology = {} + + for key, val in upper_ontology.items(): + key = key.upper() + if key not in self.upper_ontology: + self.upper_ontology[key] = [val, len(self.upper_ontology)] + else: + self.upper_ontology[key] = [val, self.upper_ontology[key][1]] + + def load_x_lingual_lexicon_from_x_lingual2ner_file(self, x_lingual2ner_file): + data_dir = self.data_dir + tmp_dir = self.tmp_dir + if x_lingual2ner_file is None: return + if os.path.exists(x_lingual2ner_file): + word2ner = json.load(open(x_lingual2ner_file, "rb")) + self.add_to_ontology(word2ner, onto_name="yago_cn_wn") + elif os.path.exists(os.path.join(data_dir, x_lingual2ner_file)): + word2ner = json.load(open(os.path.join(data_dir, x_lingual2ner_file), "rb")) + self.add_to_ontology(word2ner, onto_name=self.x_lingual_onto_name) + else: + print ("warning: could not find x_lingual2ner_file") + + def load_x_lingual_lexicon_from_prefix_file(self, x_lingual_lexicon_by_prefix_file="lexicon_by_prefix.json.gz"): + data_dir = self.data_dir + tmp_dir = self.tmp_dir + if x_lingual_lexicon_by_prefix_file is not None: + if not os.path.exists(x_lingual_lexicon_by_prefix_file): + x_lingual_lexicon_by_prefix_file = f"{data_dir}/{x_lingual_lexicon_by_prefix_file}" + if not os.path.exists(x_lingual_lexicon_by_prefix_file): + self.x_lingual_lexicon_by_prefix = {} + self.ontology[self.x_lingual_onto_name] = self.x_lingual_lexicon_by_prefix + return + if x_lingual_lexicon_by_prefix_file.endswith(".gz"): + with gzip.open(x_lingual_lexicon_by_prefix_file, 'r') as fin: + json_bytes = fin.read() + json_str = json_bytes.decode('utf-8') + self.x_lingual_lexicon_by_prefix = json.loads(json_str) + else: + self.x_lingual_lexicon_by_prefix = json.load(open(x_lingual_lexicon_by_prefix_file, "rb")) + for lexicon in self.x_lingual_lexicon_by_prefix.values(): + for val in lexicon[-1].values(): + label = val[0][0] + if label in self.upper_ontology: + val[0] = self.upper_ontology[label][0] + self._max_lexicon = max(self._max_lexicon, val[1]) + else: + self.x_lingual_lexicon_by_prefix = {} + self.ontology[self.x_lingual_onto_name] = self.x_lingual_lexicon_by_prefix + + def save_x_lingual_lexicon_prefix_file(self, x_lingual_lexicon_by_prefix_file="lexicon_by_prefix.json.gz"): + """ saves the base cross lingual leixcon """ + data_dir = self.data_dir + tmp_dir = self.tmp_dir + #print (data_dir, x_lingual_lexicon_by_prefix_file) + x_lingual_lexicon_by_prefix_file = x_lingual_lexicon_by_prefix_file.replace(".gz", "") + if not x_lingual_lexicon_by_prefix_file.startswith(data_dir): + x_lingual_lexicon_by_prefix_file=f"{data_dir}/{x_lingual_lexicon_by_prefix_file}" + json.dump(self.x_lingual_lexicon_by_prefix,open(x_lingual_lexicon_by_prefix_file, "w", encoding="utf8"), indent=1) + os.system(f"gzip {x_lingual_lexicon_by_prefix_file}") + os.system(f"rm {x_lingual_lexicon_by_prefix_file}") + + def load_target_lang_data(self, target_lang_data_file=None, target_lang=None): + data_dir = self.data_dir + tmp_dir = self.tmp_dir + if target_lang_data_file is None: + if os.path.exists(os.path.join(data_dir, f'{target_lang}.json')): + target_lang_data_file= os.path.join(data_dir, f'{target_lang}.json') + if target_lang_data_file is None: return + if os.path.exists(target_lang_data_file): + self.target_lang_data = json.load(open(target_lang_data_file, "rb")) + else: + self.target_lang_data = {} + ner_regexes = [] + if 'ner_regexes' in self.target_lang_data: + # for now we are going to ignore the PERSON rules, becaues the rules don't work yet + # change this for Module 2 of the Hackathon. + ner_regexes = [regex for regex in self.target_lang_data['ner_regexes'] if regex[0] != "PERSON" and regex[0] in self.upper_ontology] + for regex in ner_regexes: + if regex[1]: + regex[1] = re.compile(regex[1], re.IGNORECASE) + else: + regex[1] = re.compile(regex[1]) + self.ner_regexes = ner_regexes + + #pronouns used for basic coref + self.other_pronouns = set(self.target_lang_data.get('OTHER_PRONOUNS',[])) + self.person_pronouns = set(self.target_lang_data.get('PERSON_PRONOUNS',[])) + self.pronouns = set(list(self.other_pronouns) + list(self.person_pronouns)) + + #these are used for aonymizing and de-biasing swapping. + #TODO: consider whether we want to create shorter/stemmed versions of these. + self.binary_gender_swap = self.target_lang_data.get('binary_gender_swap', {}) + self.other_gender_swap = self.target_lang_data.get('other_gender_swap', {}) + self.en_pronoun2gender = self.target_lang_data.get('en_pronoun2gender', {}) + self.en_pronoun2pronoun = self.target_lang_data.get('en_pronoun2pronoun', {}) + self.en_pronoun2title = self.target_lang_data.get('en_pronoun2title', {}) + self.person2religion = self.target_lang_data.get('person2religion', {}) + self.gender2en_pronoun = dict(itertools.chain(*[[(b,a) for b in lst] for a, lst in self.en_pronoun2gender.items()])) + self.pronoun2en_pronoun = dict(itertools.chain(*[[(b,a) for b in lst] for a, lst in self.en_pronoun2pronoun.items()])) + self.title2en_pronoun = dict(itertools.chain(*[[(b,a) for b in lst] for a, lst in self.en_pronoun2title.items()])) + self.religion2person = dict(itertools.chain(*[[(b,a) for b in lst] for a, lst in self.person2religion.items()])) + self.coref_window = self.target_lang_data.get('coref_window', [-1, -2, 1, 2]) #maybe this should be a parameter and not in the ontology + + #now specialize the ontology for target_lang and have no limit on the size of the words + target_lang_lexicon = {} + for label, words in self.target_lang_data if type(self.target_lang_data) is list else self.target_lang_data.items(): + if label in self.upper_ontology: + for word in words: + if word not in self.stopwords and (not self.cjk_detect(word) or len(word) > 1): + target_lang_lexicon[word] = label + #print (target_lang_lexicon) + self.add_to_ontology(target_lang_lexicon, max_word_len=100000, onto_name=os.path.split(target_lang_data_file)[-1].split(".")[0]) + self.target_lang_lexicon = {} # target_lang_lexicon # save away the target lang ontology as a lexicon + + def save_target_lang_data(self, target_lang_data_file): + if target_lang_data_file is None: return + data_dir = self.data_dir + tmp_dir = self.tmp_dir + json.dump(self.target_lang_data,open(f"{data_dir}/{target_lang_data_file}", "w", encoding="utf8"), indent=1) + #os.system(f"gzip {data_dir}/{target_lang_data_file}") + + def _has_nonstopword(self, wordArr): + for word in wordArr: + if word.strip(self.strip_chars) not in self.stopwords: + return True + return False + + def _get_all_word_shingles(self, wordArr, max_word_len=None, create_suffix_end=True): + """ create patterned variations (prefix and suffix based shingles) """ + lenWordArr = len(wordArr) + wordArr = [w.lower() for w in wordArr] + if max_word_len is None: max_word_len =self.max_word_len + compound_word_step = self.compound_word_step + wordArr1 = wordArr2 = wordArr3 = wordArr4 = None + ret = [] + if lenWordArr > compound_word_step: + # we add some randomness in how we create patterns + wordArr1 = wordArr[:compound_word_step-1] + [wordArr[-1]] + wordArr2 = [wordArr[0]] + wordArr[1-compound_word_step:] + wordArr1 = [w if len(w) <=max_word_len else w[:max_word_len] for w in wordArr1] + wordArr2 = [w if len(w) <=max_word_len else w[:max_word_len] for w in wordArr2] + ret.extend([tuple(wordArr1),tuple(wordArr2)]) + if create_suffix_end: + wordArr3 = copy.copy(wordArr1) + wordArr3[-1] = wordArr3[-1] if len(wordArr3[-1]) <=max_word_len else '*'+wordArr3[-1][len(wordArr3[-1])-max_word_len+1:] + wordArr4 = copy.copy(wordArr2) + wordArr4[-1] = wordArr4[-1] if len(wordArr4[-1]) <=max_word_len else '*'+wordArr4[-1][len(wordArr4[-1])-max_word_len+1:] + wordArr3 = [w if len(w) <=max_word_len else w[:max_word_len] for w in wordArr3] + wordArr4 = [w if len(w) <=max_word_len else w[:max_word_len] for w in wordArr4] + ret.extend([tuple(wordArr3),tuple(wordArr4)]) + else: # lenWordArr <= compound_word_step + wordArr1 = [w if len(w) <=max_word_len else w[:max_word_len] for w in wordArr] + ret.append(tuple(wordArr1)) + if lenWordArr > 1 and create_suffix_end: + wordArr2 = copy.copy(wordArr) + wordArr2[-1] = wordArr2[-1] if len(wordArr2[-1]) <=max_word_len else '*'+wordArr2[-1][len(wordArr2[-1])-max_word_len+1:] + wordArr2 = [w if len(w) <=max_word_len else w[:max_word_len] for w in wordArr2] + ret.append(tuple(wordArr2)) + return [list(a) for a in set(ret)] + + def add_to_ontology(self, word2ner, max_word_len=None, onto_name=None): + """ + Add words to the ontology. The ontology is stored in compressed + form, using an upper ontology and several subsuming prefix based lexicon + mappings. We try to generalize the lexicon by using subsequences of + the words and compound words. Each word is shortened to + max_word_len. Compound words are connected by a connector. + Compound words longer than compound_word_step are shortened to + that length for storage purposes. All words except upper ontology + labels are lower cased. + """ + if onto_name is None: + onto_name = self.x_lingual_onto_name + if onto_name == self.x_lingual_onto_name: + self.x_lingual_lexicon_by_prefix = ontology = self.ontology[onto_name] = self.ontology.get(onto_name, self.x_lingual_lexicon_by_prefix) + else: + ontology = self.ontology[onto_name] = self.ontology.get(onto_name, {}) + if max_word_len is None: max_word_len =self.max_word_len + compound_word_step = self.compound_word_step + connector = self.connector + if type(word2ner) is dict: + word2ner = list(word2ner.items()) + lexicon = {} + _max_lexicon = self._max_lexicon + for _idx, word_label in enumerate(word2ner): + _idx += _max_lexicon + word, label = word_label + #if word.startswith('geor'): print (word, label) + label = label.upper() + is_cjk = self.cjk_detect(word) + if is_cjk: + word = "_".join(self.mt5_tokenizer.tokenize(word)).replace(mt5_underscore,"_").replace("__", "_").replace("__", "_").strip("_") + word = word.strip().lower().translate(trannum).strip(self.strip_chars).replace(" ",connector) + wordArr = word.split(connector) + orig_lens = len(word) + len(wordArr) + #wordArr = [w2.strip(self.strip_chars) for w2 in wordArr if w2.strip(self.strip_chars)] + #print (word) + # some proper nouns start with stop words like determiners. let's strip those. + while wordArr: + if wordArr[0] in self.stopwords: + wordArr= wordArr[1:] + else: + break + if not wordArr: + continue + word = connector.join(wordArr) + #we don't have an actual count of the word in the corpus, so we create a weight based + #on the length, assuming shorter words with less compound parts are more frequent + weight = 1/(1.0+math.sqrt(orig_lens)) + lenWordArr = len(wordArr) + if lenWordArr == 0: + continue + # add some randomness and only do suffix ends in some cases. TODO: we can use a config var. + for wordArr in self._get_all_word_shingles(wordArr, max_word_len=max_word_len, create_suffix_end = _idx % 5 == 0): + if not wordArr: continue + word = connector.join(wordArr) + key = (word, lenWordArr//(compound_word_step+1)) + #print (word0, word, weight) + if type(label) in (list, tuple, set): + if type(label) != list: + label = list(label) + _label, _idx, _cnt = lexicon.get(key, [label, _idx, {}]) + if _cnt is None: _cnt = {} + _cnt[label[0]] = _cnt.get(label[0], 0.0) + weight + lexicon[key] = [_label, _idx, _cnt] + else: + _label, _idx, _cnt = lexicon.get(key, [[label], _idx, {}]) + if _cnt is None: _cnt = {} + _cnt[label] = _cnt.get(label, 0.0) + weight + lexicon[key] = [_label, _idx, _cnt] + prev_val= ontology.get(wordArr[0], [1, 100]) + ontology[wordArr[0]] = [max(lenWordArr, prev_val[0]), 2 if lenWordArr == 2 else min(max(lenWordArr-1,1), prev_val[1])] + for key in lexicon: + _cnt = lexicon[key][2] + if _cnt: + label = Counter(_cnt).most_common(1)[0][0] + lexicon[key][0] = lexicon.get(label, [[label]])[0] + lexicon[key] = lexicon[key][:-1] + for word, slot in lexicon: + prefix = word.split(connector,1)[0] + if prefix in ontology: + rec = ontology[prefix] + if len(rec) == 2: + rec.append({}) + rec.append({}) + rec.append({}) + rec.append({}) + lexicon2 = rec[2+min(3,slot)] + if connector in word: + word2 = '*'+connector+word.split(connector,1)[1] + else: + word2 = word + lexicon2[word2] = lexicon[(word, slot)] + self._max_lexicon += len(word2ner) + + def cjk_pre_tokenize(self, text, connector=None): + """ tokenize using mt5. meant for cjk languages""" + if connector is None: + connector = self.connector + if self.mt5_tokenizer is None: + self.mt5_tokenizer = AutoTokenizer.from_pretrained("google/mt5-small") + words = self.mt5_tokenizer.tokenize(text.replace("_", " ").strip()) + words2 = [] + for word in words: + if not words2: + words2.append(word) + continue + if not self.cjk_detect(word): + if not self.cjk_detect(words2[-1]): + if words2[-1] in self.strip_chars_set: + words2[-1] += " "+word + else: + words2[-1] += word + continue + words2.append(word) + text = " ".join(words2).replace(mt5_underscore," ").replace(" ", " ").replace(" ", " ").strip() + return text + + def in_ontology(self, word, connector=None, supress_cjk_tokenize=False, check_person_org_gpe_caps=True): + """ find whether a word is in the ontology. """ + orig_word = word + + max_word_len =self.max_word_len + min_word_len =self.min_word_len + compound_word_step = self.compound_word_step + if connector is None: + connector = self.connector + is_cjk = self.cjk_detect(word) + if not is_cjk and len(word) < min_word_len: + return word, None + if not supress_cjk_tokenize and is_cjk: + word = self.cjk_pre_tokenize(word, connector) + + word = word.strip().translate(trannum).strip(self.strip_chars+connector).replace(" ",connector) + wordArr = word.split(connector) + if word in self.target_lang_lexicon: + return orig_word, self.target_lang_lexicon[word] + if is_cjk: + word = word.replace(connector,"") + if word in self.target_lang_lexicon: + return orig_word, self.target_lang_lexicon[word] + #wordArr = [w2.strip(self.strip_chars) for w2 in wordArr if w2.strip(self.strip_chars)] + if not wordArr or not wordArr[0] or not wordArr[-1]: + return word, None + lenWordArr = len(wordArr) + all_shingles = self._get_all_word_shingles(wordArr, max_word_len=max_word_len, create_suffix_end=not is_cjk) + long_shingles= [] if is_cjk else self._get_all_word_shingles(wordArr, max_word_len=100000, create_suffix_end=False) + for ontology in reversed(list(self.ontology.values())): + #find patterned variations (shingles) + for shingleArr in long_shingles + all_shingles: # we can probably dedup to make it faster + if shingleArr and shingleArr[0] in ontology: + lexicon2 = ontology[shingleArr[0]][2+min(3,lenWordArr//(compound_word_step+1))] + if len(shingleArr) > 1: + shingle = '*'+connector+connector.join((shingleArr[1:])) + else: + shingle = shingleArr[0] + label, _ = lexicon2.get(shingle, (None, None)) + #let's return only labels that are in the upper_ontology + if label is not None and (label[0] in self.upper_ontology or self.label2label.get(label[0]) in self.upper_ontology): + if check_person_org_gpe_caps and ("PUBLIC_FIGURE" in label or "PERSON" in label or "ORG" in label or "GPE" in label): + #ideally we would keep patterns like AaA as part of the shingle to match. This is a hack. + if wordArr[0][0] != wordArr[0][0].upper() or wordArr[-1][0] != wordArr[-1][0].upper(): continue + label = label[0] + label = self.label2label.get(label, label) + return word, label + return orig_word, None + + def _get_ngram_start_end(self, start_word): + """ find the possible range of a compound word that starts with start_word """ + ngram_start = -1 + ngram_end = 100000 + for ontology in self.ontology.values(): + rec = ontology.get(start_word, [ngram_start, ngram_end]) + ngram_start, ngram_end = max(ngram_start,rec[0]), min(ngram_end,rec[1]) + return ngram_start, ngram_end + + + def tokenize(self, text, connector=None, supress_cjk_tokenize=False, return_dict=True, row_id=0, doc_id=0): + """ + Parse text for words in the ontology. For compound words, + transform into single word sequence, with a word potentially + having a connector seperator. Optionally, use the mt5 tokenizer + to separate the words into subtokens first, and then do multi-word + parsing. Used for mapping a word back to an item in an ontology. + Returns the tokenized text along with word to ner label mapping + for words in this text. + """ + max_word_len =self.max_word_len + compound_word_step = self.compound_word_step + labels = [] + if connector is None: + connector = self.connector + if not supress_cjk_tokenize and self.cjk_detect(text): + text = self.cjk_pre_tokenize(text, connector) + sent = text.strip().split() + len_sent = len(sent) + pos = 0 + for i in range(len_sent-1): + if sent[i] is None: continue + start_word = sent[i].lower() #.strip(self.strip_chars) + if start_word in self.stopwords: + pos += len(sent[i])+1 + continue + start_word = start_word.translate(trannum).split(connector)[0] + start_word = start_word if len(start_word) <= max_word_len else start_word[:max_word_len] + ngram_start, ngram_end = self._get_ngram_start_end(start_word) + #print (start_word, ngram_start, ngram_end) + if ngram_start > 0: + for j in range(ngram_start-1, ngram_end-2, -1): + if len_sent - i > j: + wordArr = sent[i:i+1+j] + new_word = " ".join(wordArr) + if not self._has_nonstopword(wordArr): break + # we don't match sequences that start and end with stopwords + if wordArr[-1].lower() in self.stopwords: continue + _, label = self.in_ontology(new_word, connector=connector, supress_cjk_tokenize=True) + if label is not None: + new_word = new_word.replace(" ", connector) + new_word = new_word.lstrip(",") + if new_word not in self.stopwords: + #print ('found', new_word) + sent[i] = new_word + labels.append(((new_word, pos, pos + len(new_word), row_id, doc_id), label)) + for k in range(i+1, i+j+1): + sent[k] = None + break + pos += len(sent[i])+1 + if return_dict: + return {'text': " ".join([s for s in sent if s]), 'chunk2ner': dict(labels)} + else: + return " ".join([s for s in sent if s]) + + def cjk_detect(self, texts): + # korean + if re.search("[\uac00-\ud7a3]", texts): + return "ko" + # japanese + if re.search("[\u3040-\u30ff]", texts): + return "ja" + # chinese + if re.search("[\u4e00-\u9FFF]", texts): + return "zh" + return None + +if __name__ == "__main__": + data_dir = tmp_dir = None + if "-s" in sys.argv: + tmp_dir = sys.argv[sys.argv.index("-s")+1] + if "-t" in sys.argv: + sentence = sys.argv[sys.argv.index("-t")+1] + manager = OntologyManager(data_dir=data_dir, tmp_dir=tmp_dir) + txt = manager.tokenize(sentence) + print(txt) diff --git a/data_tooling/pii_processing/ontology/stopwords.py b/data_tooling/pii_processing/ontology/stopwords.py new file mode 100644 index 0000000..21ce717 --- /dev/null +++ b/data_tooling/pii_processing/ontology/stopwords.py @@ -0,0 +1,14340 @@ +# From https://github.com/6/stopwords-json +# From https://github.com/stopwords-iso/stopwords-iso for Urdu and Vietnamese + +stopwords = { + "af": [ + "'n", + "aan", + "af", + "al", + "as", + "baie", + "by", + "daar", + "dag", + "dat", + "die", + "dit", + "een", + "ek", + "en", + "gaan", + "ges\u00ea", + "haar", + "het", + "hom", + "hulle", + "hy", + "in", + "is", + "jou", + "jy", + "kan", + "kom", + "ma", + "maar", + "met", + "my", + "na", + "nie", + "om", + "ons", + "op", + "saam", + "sal", + "se", + "sien", + "so", + "sy", + "te", + "toe", + "uit", + "van", + "vir", + "was", + "wat", + "\u0149", + ], + "ar": [ + "\u060c", + "\u0623", + "\u0627", + "\u0627\u062b\u0631", + "\u0627\u062c\u0644", + "\u0627\u062d\u062f", + "\u0627\u062e\u0631\u0649", + "\u0627\u0630\u0627", + "\u0627\u0631\u0628\u0639\u0629", + "\u0627\u0637\u0627\u0631", + "\u0627\u0639\u0627\u062f\u0629", + "\u0627\u0639\u0644\u0646\u062a", + "\u0627\u0641", + "\u0627\u0643\u062b\u0631", + "\u0627\u0643\u062f", + "\u0627\u0644\u0627", + "\u0627\u0644\u0627\u062e\u064a\u0631\u0629", + "\u0627\u0644\u0627\u0646", + "\u0627\u0644\u0627\u0648\u0644", + "\u0627\u0644\u0627\u0648\u0644\u0649", + "\u0627\u0644\u062a\u0649", + "\u0627\u0644\u062a\u064a", + "\u0627\u0644\u062b\u0627\u0646\u064a", + "\u0627\u0644\u062b\u0627\u0646\u064a\u0629", + 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+ "ambas", + "ambos", + "antes", + "ao", + "aonde", + "aos", + "apos", + "aquele", + "aqueles", + "as", + "assim", + "com", + "como", + "contra", + "contudo", + "cuja", + "cujas", + "cujo", + "cujos", + "da", + "das", + "de", + "dela", + "dele", + "deles", + "demais", + "depois", + "desde", + "desta", + "deste", + "dispoe", + "dispoem", + "diversa", + "diversas", + "diversos", + "do", + "dos", + "durante", + "e", + "ela", + "elas", + "ele", + "eles", + "em", + "entao", + "entre", + "essa", + "essas", + "esse", + "esses", + "esta", + "estas", + "este", + "estes", + "ha", + "isso", + "isto", + "logo", + "mais", + "mas", + "mediante", + "menos", + "mesma", + "mesmas", + "mesmo", + "mesmos", + "na", + "nao", + "nas", + "nem", + "nesse", + "neste", + "nos", + "o", + "os", + "ou", + "outra", + "outras", + "outro", + "outros", + "pelas", + "pelo", + "pelos", + "perante", + "pois", + "por", + "porque", + "portanto", + "propios", + "proprio", + "quais", + "qual", + "qualquer", + "quando", + "quanto", + "que", + "quem", + "quer", + "se", + "seja", + "sem", + "sendo", + "seu", + "seus", + "sob", + "sobre", + "sua", + "suas", + "tal", + "tambem", + "teu", + "teus", + "toda", + "todas", + "todo", + "todos", + "tua", + "tuas", + "tudo", + "um", + "uma", + "umas", + "uns", + ], + "ca": [ + "a", + "abans", + "ac\u00ed", + "ah", + "aix\u00ed", + "aix\u00f2", + "al", + "aleshores", + "algun", + "alguna", + "algunes", + "alguns", + "alhora", + "all\u00e0", + "all\u00ed", + "all\u00f2", + "als", + "altra", + "altre", + "altres", + "amb", + "ambdues", + "ambd\u00f3s", + "apa", + "aquell", + "aquella", + "aquelles", + "aquells", + "aquest", + "aquesta", + "aquestes", + "aquests", + "aqu\u00ed", + "baix", + "cada", + "cadascuna", + "cadascunes", + "cadascuns", + "cadasc\u00fa", + "com", + "contra", + "d'un", + "d'una", + "d'unes", + "d'uns", + "dalt", + "de", + "del", + "dels", + "des", + "despr\u00e9s", + "dins", + "dintre", + "donat", + "doncs", + "durant", + "e", + "eh", + "el", + "els", + "em", + "en", + "encara", + "ens", + "entre", + "eren", + "es", + "esta", + "estaven", + "esteu", + "est\u00e0", + "est\u00e0vem", + "est\u00e0veu", + "et", + "etc", + "ets", + "fins", + "fora", + "gaireb\u00e9", + "ha", + "han", + "has", + "havia", + "he", + "hem", + "heu", + "hi", + "ho", + "i", + "igual", + "iguals", + "ja", + "l'hi", + "la", + "les", + "li", + "li'n", + "llavors", + "m'he", + "ma", + "mal", + "malgrat", + "mateix", + "mateixa", + "mateixes", + "mateixos", + "me", + "mentre", + "meu", + "meus", + "meva", + "meves", + "molt", + "molta", + "moltes", + "molts", + "mon", + "mons", + "m\u00e9s", + "n'he", + "n'hi", + "ne", + "ni", + "no", + "nogensmenys", + "nom\u00e9s", + "nosaltres", + "nostra", + "nostre", + "nostres", + "o", + "oh", + "oi", + "on", + "pas", + "pel", + "pels", + "per", + "perqu\u00e8", + "per\u00f2", + "poc", + "poca", + "pocs", + "poques", + "potser", + "propi", + "qual", + "quals", + "quan", + "quant", + "que", + "quelcom", + "qui", + "quin", + "quina", + "quines", + "quins", + "qu\u00e8", + "s'ha", + "s'han", + "sa", + "semblant", + "semblants", + "ses", + "seu", + "seus", + "seva", + "seves", + "si", + "sobre", + "sobretot", + "solament", + "sols", + "son", + "sons", + "sota", + "sou", + "s\u00f3c", + "s\u00f3n", + "t'ha", + "t'han", + "t'he", + "ta", + "tal", + "tamb\u00e9", + "tampoc", + "tan", + "tant", + "tanta", + "tantes", + "teu", + "teus", + "teva", + "teves", + "ton", + "tons", + "tot", + "tota", + "totes", + "tots", + "un", + "una", + "unes", + "uns", + "us", + "va", + "vaig", + "vam", + "van", + "vas", + "veu", + "vosaltres", + "vostra", + "vostre", + "vostres", + "\u00e9rem", + "\u00e9reu", + "\u00e9s", + ], + "cs": [ + "a", + "aby", + "ahoj", + "aj", + "ale", + "anebo", + "ani", + "ano", + "asi", + "aspo\u0148", + "atd", + "atp", + "a\u010dkoli", + "a\u017e", + "bez", + "beze", + "bl\u00edzko", + "bohu\u017eel", + "brzo", + "bude", + "budem", + "budeme", + "budete", + "bude\u0161", + "budou", + "budu", + "by", + "byl", + "byla", + "byli", + "bylo", + "byly", + "bys", + "b\u00fdt", + "b\u011bhem", + "chce", + "chceme", + "chcete", + "chce\u0161", + "chci", + "cht\u00edt", + "cht\u011bj\u00ed", + "chut'", + "chuti", + "co", + "co\u017e", + "cz", + "daleko", + "dal\u0161\u00ed", + "den", + "deset", + "devaten\u00e1ct", + "dev\u011bt", + "dnes", + "do", + "dobr\u00fd", + "docela", + "dva", + "dvacet", + "dvan\u00e1ct", + "dv\u011b", + "d\u00e1l", + "d\u00e1le", + "d\u011bkovat", + "d\u011bkujeme", + "d\u011bkuji", + "ho", + "hodn\u011b", + "i", + "jak", + "jakmile", + "jako", + "jako\u017e", + "jde", + "je", + "jeden", + "jeden\u00e1ct", + "jedna", + "jedno", + "jednou", + "jedou", + "jeho", + "jeho\u017e", + "jej", + "jejich", + "jej\u00ed", + "jeliko\u017e", + "jemu", + "jen", + "jenom", + "jestli", + "jestli\u017ee", + "je\u0161t\u011b", + "je\u017e", + "ji", + "jich", + "jimi", + "jinak", + "jin\u00e9", + "ji\u017e", + "jsem", + "jse\u0161", + "jsi", + "jsme", + "jsou", + "jste", + "j\u00e1", + "j\u00ed", + "j\u00edm", + "j\u00ed\u017e", + "k", + "kam", + "kde", + "kdo", + "kdy", + "kdy\u017e", + "ke", + "kolik", + "krom\u011b", + "kterou", + "kter\u00e1", + "kter\u00e9", + "kter\u00fd", + "kte\u0159\u00ed", + "kv\u016fli", + "maj\u00ed", + "mezi", + "mi", + "mne", + "mnou", + "mn\u011b", + "moc", + "mohl", + "mohou", + "moje", + "moji", + "mo\u017en\u00e1", + "mus\u00ed", + "my", + "m\u00e1", + "m\u00e1lo", + "m\u00e1m", + "m\u00e1me", + "m\u00e1te", + "m\u00e1\u0161", + "m\u00e9", + "m\u00ed", + "m\u00edt", + "m\u011b", + "m\u016fj", + "m\u016f\u017ee", + "na", + "nad", + "nade", + "napi\u0161te", + "naproti", + "na\u010de\u017e", + "na\u0161e", + "na\u0161i", + "ne", + "nebo", + "nebyl", + "nebyla", + "nebyli", + "nebyly", + "ned\u011blaj\u00ed", + "ned\u011bl\u00e1", + "ned\u011bl\u00e1m", + "ned\u011bl\u00e1me", + "ned\u011bl\u00e1te", + "ned\u011bl\u00e1\u0161", + "neg", + "nejsi", + "nejsou", + "nemaj\u00ed", + "nem\u00e1me", + "nem\u00e1te", + "nem\u011bl", + "nen\u00ed", + "nesta\u010d\u00ed", + "nevad\u00ed", + "ne\u017e", + "nic", + "nich", + "nimi", + "nov\u00e9", + "nov\u00fd", + "nula", + "n\u00e1m", + "n\u00e1mi", + "n\u00e1s", + "n\u00e1\u0161", + "n\u00edm", + "n\u011b", + "n\u011bco", + "n\u011bjak", + "n\u011bkde", + "n\u011bkdo", + "n\u011bmu", + "n\u011bmu\u017e", + "o", + "od", + "ode", + "on", + "ona", + "oni", + "ono", + "ony", + "osm", + "osmn\u00e1ct", + "pak", + "patn\u00e1ct", + "po", + "pod", + "podle", + "pokud", + "potom", + "pouze", + "pozd\u011b", + "po\u0159\u00e1d", + "prav\u00e9", + "pro", + "prost\u011b", + "pros\u00edm", + "proti", + "proto", + "proto\u017ee", + "pro\u010d", + "prvn\u00ed", + "pta", + "p\u011bt", + "p\u0159ed", + "p\u0159es", + "p\u0159ese", + "p\u0159i", + "p\u0159i\u010dem\u017e", + "re", + "rovn\u011b", + "s", + "se", + "sedm", + "sedmn\u00e1ct", + "si", + "skoro", + "sm\u00ed", + "sm\u011bj\u00ed", + "snad", + "spolu", + "sta", + "sto", + "strana", + "st\u00e9", + "sv\u00e9", + "sv\u00fdch", + "sv\u00fdm", + "sv\u00fdmi", + "ta", + "tady", + "tak", + "takhle", + "taky", + "tak\u00e9", + "tak\u017ee", + "tam", + "tamhle", + "tamhleto", + "tamto", + "tato", + "tebe", + "tebou", + "ted'", + "tedy", + "ten", + "tento", + "teto", + "ti", + "tipy", + "tis\u00edc", + "tis\u00edce", + "to", + "tob\u011b", + "tohle", + "toho", + "tohoto", + "tom", + "tomto", + "tomu", + "tomuto", + "toto", + "tro\u0161ku", + "tu", + "tuto", + "tvoje", + "tv\u00e1", + "tv\u00e9", + "tv\u016fj", + "ty", + "tyto", + "t\u00e9ma", + "t\u00edm", + "t\u00edmto", + "t\u011b", + "t\u011bm", + "t\u011bmu", + "t\u0159eba", + "t\u0159i", + "t\u0159in\u00e1ct", + "u", + "ur\u010dit\u011b", + "u\u017e", + "v", + "va\u0161e", + "va\u0161i", + "ve", + "vedle", + "ve\u010der", + "vlastn\u011b", + "vy", + "v\u00e1m", + "v\u00e1mi", + "v\u00e1s", + "v\u00e1\u0161", + "v\u00edce", + "v\u0161ak", + "v\u0161echno", + "v\u0161ichni", + "v\u016fbec", + "v\u017edy", + "z", + "za", + "zat\u00edmco", + "za\u010d", + "zda", + "zde", + "ze", + "zpr\u00e1vy", + "zp\u011bt", + "\u010dau", + "\u010di", + "\u010dl\u00e1nku", + "\u010dl\u00e1nky", + "\u010dtrn\u00e1ct", + "\u010dty\u0159i", + "\u0161est", + "\u0161estn\u00e1ct", + "\u017ee", + ], + "da": [ + "af", + "alle", + "andet", + "andre", + "at", + "begge", + "da", + "de", + "den", + "denne", + "der", + "deres", + "det", + "dette", + "dig", + "din", + "dog", + "du", + "ej", + "eller", + "en", + "end", + "ene", + "eneste", + "enhver", + "et", + "fem", + "fire", + "flere", + "fleste", + "for", + "fordi", + "forrige", + "fra", + "f\u00e5", + "f\u00f8r", + "god", + "han", + "hans", + "har", + "hendes", + "her", + "hun", + "hvad", + "hvem", + "hver", + "hvilken", + "hvis", + "hvor", + "hvordan", + "hvorfor", + "hvorn\u00e5r", + "i", + "ikke", + "ind", + "ingen", + "intet", + "jeg", + "jeres", + "kan", + "kom", + "kommer", + "lav", + "lidt", + "lille", + "man", + "mand", + "mange", + "med", + "meget", + "men", + "mens", + "mere", + "mig", + "ned", + "ni", + "nogen", + "noget", + "ny", + "nyt", + "n\u00e6r", + "n\u00e6ste", + "n\u00e6sten", + "og", + "op", + "otte", + "over", + "p\u00e5", + "se", + "seks", + "ses", + "som", + "stor", + "store", + "syv", + "ti", + "til", + "to", + "tre", + "ud", + "var", + ], + "de": [ + "Ernst", + "Ordnung", + "Schluss", + "a", + "ab", + "aber", + "ach", + "acht", + "achte", + "achten", + "achter", + "achtes", + "ag", + "alle", + "allein", + "allem", + "allen", + "aller", + "allerdings", + "alles", + "allgemeinen", + "als", + "also", + "am", + "an", + "andere", + "anderen", + "andern", + "anders", + "au", + "auch", + "auf", + "aus", + "ausser", + "ausserdem", + "au\u00dfer", + "au\u00dferdem", + "b", + "bald", + "bei", + "beide", + "beiden", + "beim", + "beispiel", + "bekannt", + "bereits", + "besonders", + "besser", + "besten", + "bin", + "bis", + "bisher", + "bist", + "c", + "d", + "d.h", + "da", + "dabei", + "dadurch", + "daf\u00fcr", + "dagegen", + "daher", + "dahin", + "dahinter", + "damals", + "damit", + "danach", + "daneben", + "dank", + "dann", + "daran", + "darauf", + "daraus", + "darf", + "darfst", + "darin", + "darum", + "darunter", + "dar\u00fcber", + "das", + "dasein", + "daselbst", + "dass", + "dasselbe", + "davon", + "davor", + "dazu", + "dazwischen", + "da\u00df", + "dein", + "deine", + "deinem", + "deiner", + "dem", + "dementsprechend", + "demgegen\u00fcber", + "demgem\u00e4ss", + "demgem\u00e4\u00df", + "demselben", + "demzufolge", + "den", + "denen", + "denn", + "denselben", + "der", + "deren", + "derjenige", + "derjenigen", + "dermassen", + "derma\u00dfen", + "derselbe", + "derselben", + "des", + "deshalb", + "desselben", + "dessen", + "deswegen", + "dich", + "die", + "diejenige", + "diejenigen", + "dies", + "diese", + "dieselbe", + "dieselben", + "diesem", + "diesen", + "dieser", + "dieses", + "dir", + "doch", + "dort", + "drei", + "drin", + "dritte", + "dritten", + "dritter", + "drittes", + "du", + "durch", + "durchaus", + "durfte", + "durften", + "d\u00fcrfen", + "d\u00fcrft", + "e", + "eben", + "ebenso", + "ehrlich", + "ei", + "ei,", + "eigen", + "eigene", + "eigenen", + "eigener", + "eigenes", + "ein", + "einander", + "eine", + "einem", + "einen", + "einer", + "eines", + "einige", + "einigen", + "einiger", + "einiges", + "einmal", + "eins", + "elf", + "en", + "ende", + "endlich", + "entweder", + "er", + "erst", + "erste", + "ersten", + "erster", + "erstes", + "es", + "etwa", + "etwas", + "euch", + "euer", + "eure", + "f", + "folgende", + "fr\u00fcher", + "f\u00fcnf", + "f\u00fcnfte", + "f\u00fcnften", + "f\u00fcnfter", + "f\u00fcnftes", + "f\u00fcr", + "g", + "gab", + "ganz", + "ganze", + "ganzen", + "ganzer", + "ganzes", + "gar", + "gedurft", + "gegen", + "gegen\u00fcber", + "gehabt", + "gehen", + "geht", + "gekannt", + "gekonnt", + "gemacht", + "gemocht", + "gemusst", + "genug", + "gerade", + "gern", + "gesagt", + "geschweige", + "gewesen", + "gewollt", + "geworden", + "gibt", + "ging", + "gleich", + "gott", + "gross", + "grosse", + "grossen", + "grosser", + "grosses", + "gro\u00df", + "gro\u00dfe", + "gro\u00dfen", + "gro\u00dfer", + "gro\u00dfes", + "gut", + "gute", + "guter", + "gutes", + "h", + "habe", + "haben", + "habt", + "hast", + "hat", + "hatte", + "hatten", + "hattest", + "hattet", + "heisst", + "her", + "heute", + "hier", + "hin", + "hinter", + "hoch", + "h\u00e4tte", + "h\u00e4tten", + "i", + "ich", + "ihm", + "ihn", + "ihnen", + "ihr", + "ihre", + "ihrem", + "ihren", + "ihrer", + "ihres", + "im", + "immer", + "in", + "indem", + "infolgedessen", + "ins", + "irgend", + "ist", + "j", + "ja", + "jahr", + "jahre", + "jahren", + "je", + "jede", + "jedem", + "jeden", + "jeder", + "jedermann", + "jedermanns", + "jedes", + "jedoch", + "jemand", + "jemandem", + "jemanden", + "jene", + "jenem", + "jenen", + "jener", + "jenes", + "jetzt", + "k", + "kam", + "kann", + "kannst", + "kaum", + "kein", + "keine", + "keinem", + "keinen", + "keiner", + "kleine", + "kleinen", + "kleiner", + "kleines", + "kommen", + "kommt", + "konnte", + "konnten", + "kurz", + "k\u00f6nnen", + "k\u00f6nnt", + "k\u00f6nnte", + "l", + "lang", + "lange", + "leicht", + "leide", + "lieber", + "los", + "m", + "machen", + "macht", + "machte", + "mag", + "magst", + "mahn", + "mal", + "man", + "manche", + "manchem", + "manchen", + "mancher", + "manches", + "mann", + "mehr", + "mein", + "meine", + "meinem", + "meinen", + "meiner", + "meines", + "mensch", + "menschen", + "mich", + "mir", + "mit", + "mittel", + "mochte", + "mochten", + "morgen", + "muss", + "musst", + "musste", + "mussten", + "mu\u00df", + "mu\u00dft", + "m\u00f6chte", + "m\u00f6gen", + "m\u00f6glich", + "m\u00f6gt", + "m\u00fcssen", + "m\u00fcsst", + "m\u00fc\u00dft", + "n", + "na", + "nach", + "nachdem", + "nahm", + "nat\u00fcrlich", + "neben", + "nein", + "neue", + "neuen", + "neun", + "neunte", + "neunten", + "neunter", + "neuntes", + "nicht", + "nichts", + "nie", + "niemand", + "niemandem", + "niemanden", + "noch", + "nun", + "nur", + "o", + "ob", + "oben", + "oder", + "offen", + "oft", + "ohne", + "p", + "q", + "r", + "recht", + "rechte", + "rechten", + "rechter", + "rechtes", + "richtig", + "rund", + "s", + "sa", + "sache", + "sagt", + "sagte", + "sah", + "satt", + "schlecht", + "schon", + "sechs", + "sechste", + "sechsten", + "sechster", + "sechstes", + "sehr", + "sei", + "seid", + "seien", + "sein", + "seine", + "seinem", + "seinen", + "seiner", + "seines", + "seit", + "seitdem", + "selbst", + "sich", + "sie", + "sieben", + "siebente", + "siebenten", + "siebenter", + "siebentes", + "sind", + "so", + "solang", + "solche", + "solchem", + "solchen", + "solcher", + "solches", + "soll", + "sollen", + "sollst", + "sollt", + "sollte", + "sollten", + "sondern", + "sonst", + "soweit", + "sowie", + "sp\u00e4ter", + "startseite", + "statt", + "steht", + "suche", + "t", + "tag", + "tage", + "tagen", + "tat", + "teil", + "tel", + "tritt", + "trotzdem", + "tun", + "u", + "uhr", + "um", + "und", + "und?", + "uns", + "unser", + "unsere", + "unserer", + "unter", + "v", + "vergangenen", + "viel", + "viele", + "vielem", + "vielen", + "vielleicht", + "vier", + "vierte", + "vierten", + "vierter", + "viertes", + "vom", + "von", + "vor", + "w", + "wahr?", + "wann", + "war", + "waren", + "wart", + "warum", + "was", + "wegen", + "weil", + "weit", + "weiter", + "weitere", + "weiteren", + "weiteres", + "welche", + "welchem", + "welchen", + "welcher", + "welches", + "wem", + "wen", + "wenig", + "wenige", + "weniger", + "weniges", + "wenigstens", + "wenn", + "wer", + "werde", + "werden", + "werdet", + "weshalb", + "wessen", + "wie", + "wieder", + "wieso", + "will", + "willst", + "wir", + "wird", + "wirklich", + "wirst", + "wissen", + "wo", + "wohl", + "wollen", + "wollt", + "wollte", + "wollten", + "worden", + "wurde", + "wurden", + "w\u00e4hrend", + "w\u00e4hrenddem", + "w\u00e4hrenddessen", + "w\u00e4re", + "w\u00fcrde", + "w\u00fcrden", + "x", + "y", + "z", + "z.b", + "zehn", + "zehnte", + "zehnten", + "zehnter", + "zehntes", + "zeit", + "zu", + "zuerst", + "zugleich", + "zum", + "zun\u00e4chst", + "zur", + "zur\u00fcck", + "zusammen", + "zwanzig", + "zwar", + "zwei", + "zweite", + "zweiten", + "zweiter", + "zweites", + "zwischen", + "zw\u00f6lf", + "\u00fcber", + "\u00fcberhaupt", + "\u00fcbrigens", + ], + "el": [ + "\u03b1\u03bb\u03bb\u03b1", + "\u03b1\u03bd", + "\u03b1\u03bd\u03c4\u03b9", + "\u03b1\u03c0\u03bf", + "\u03b1\u03c5\u03c4\u03b1", + "\u03b1\u03c5\u03c4\u03b5\u03c3", + "\u03b1\u03c5\u03c4\u03b7", + "\u03b1\u03c5\u03c4\u03bf", + "\u03b1\u03c5\u03c4\u03bf\u03b9", + "\u03b1\u03c5\u03c4\u03bf\u03c3", + "\u03b1\u03c5\u03c4\u03bf\u03c5\u03c3", + "\u03b1\u03c5\u03c4\u03c9\u03bd", + "\u03b3\u03b9\u03b1", + "\u03b4\u03b5", + "\u03b4\u03b5\u03bd", + "\u03b5\u03b1\u03bd", + "\u03b5\u03b9\u03bc\u03b1\u03b9", + "\u03b5\u03b9\u03bc\u03b1\u03c3\u03c4\u03b5", + "\u03b5\u03b9\u03bd\u03b1\u03b9", + "\u03b5\u03b9\u03c3\u03b1\u03b9", + "\u03b5\u03b9\u03c3\u03c4\u03b5", + "\u03b5\u03ba\u03b5\u03b9\u03bd\u03b1", + "\u03b5\u03ba\u03b5\u03b9\u03bd\u03b5\u03c3", + "\u03b5\u03ba\u03b5\u03b9\u03bd\u03b7", + "\u03b5\u03ba\u03b5\u03b9\u03bd\u03bf", + "\u03b5\u03ba\u03b5\u03b9\u03bd\u03bf\u03b9", + "\u03b5\u03ba\u03b5\u03b9\u03bd\u03bf\u03c3", + "\u03b5\u03ba\u03b5\u03b9\u03bd\u03bf\u03c5\u03c3", + "\u03b5\u03ba\u03b5\u03b9\u03bd\u03c9\u03bd", + "\u03b5\u03bd\u03c9", + "\u03b5\u03c0\u03b9", + "\u03b7", + "\u03b8\u03b1", + "\u03b9\u03c3\u03c9\u03c3", + "\u03ba", + "\u03ba\u03b1\u03b9", + "\u03ba\u03b1\u03c4\u03b1", + "\u03ba\u03b9", + "\u03bc\u03b1", + "\u03bc\u03b5", + "\u03bc\u03b5\u03c4\u03b1", + "\u03bc\u03b7", + "\u03bc\u03b7\u03bd", + "\u03bd\u03b1", + "\u03bf", + "\u03bf\u03b9", + "\u03bf\u03bc\u03c9\u03c3", + "\u03bf\u03c0\u03c9\u03c3", + "\u03bf\u03c3\u03bf", + "\u03bf\u03c4\u03b9", + "\u03c0\u03b1\u03c1\u03b1", + "\u03c0\u03bf\u03b9\u03b1", + "\u03c0\u03bf\u03b9\u03b5\u03c3", + "\u03c0\u03bf\u03b9\u03bf", + "\u03c0\u03bf\u03b9\u03bf\u03b9", + "\u03c0\u03bf\u03b9\u03bf\u03c3", + "\u03c0\u03bf\u03b9\u03bf\u03c5\u03c3", + "\u03c0\u03bf\u03b9\u03c9\u03bd", + "\u03c0\u03bf\u03c5", + "\u03c0\u03c1\u03bf\u03c3", + "\u03c0\u03c9\u03c3", + "\u03c3\u03b5", + "\u03c3\u03c4\u03b7", + "\u03c3\u03c4\u03b7\u03bd", + "\u03c3\u03c4\u03bf", + "\u03c3\u03c4\u03bf\u03bd", + "\u03c4\u03b1", + "\u03c4\u03b7\u03bd", + "\u03c4\u03b7\u03c3", + "\u03c4\u03bf", + "\u03c4\u03bf\u03bd", + "\u03c4\u03bf\u03c4\u03b5", + "\u03c4\u03bf\u03c5", + "\u03c4\u03c9\u03bd", + "\u03c9\u03c3", + ], + "en": [ + "a", + "a's", + "able", + "about", + "above", + "according", + "accordingly", + "across", + "actually", + "after", + "afterwards", + "again", + "against", + "ain't", + "all", + "allow", + "allows", + "almost", + "alone", + "along", + "already", + "also", + "although", + "always", + "am", + "among", + "amongst", + "an", + "and", + "another", + "any", + "anybody", + "anyhow", + "anyone", + "anything", + "anyway", + "anyways", + "anywhere", + "apart", + "appear", + "appreciate", + "appropriate", + "are", + "aren't", + "around", + "as", + "aside", + "ask", + "asking", + "associated", + "at", + "available", + "away", + "awfully", + "b", + "be", + "became", + "because", + "become", + "becomes", + "becoming", + "been", + "before", + "beforehand", + "behind", + "being", + "believe", + "below", + "beside", + "besides", + "best", + "better", + "between", + "beyond", + "both", + "brief", + "but", + "by", + "c", + "c'mon", + "c's", + "came", + "can", + "can't", + "cannot", + "cant", + "cause", + "causes", + "certain", + "certainly", + "changes", + "clearly", + "co", + "com", + "come", + "comes", + "concerning", + "consequently", + "consider", + "considering", + "contain", + "containing", + "contains", + "corresponding", + "could", + "couldn't", + "course", + "currently", + "d", + "definitely", + "described", + "despite", + "did", + "didn't", + "different", + "do", + "does", + "doesn't", + "doing", + "don't", + "done", + "down", + "downwards", + "during", + "e", + "each", + "edu", + "eg", + "eight", + "either", + "else", + "elsewhere", + "enough", + "entirely", + "especially", + "et", + "etc", + "even", + "ever", + "every", + "everybody", + "everyone", + "everything", + "everywhere", + "ex", + "exactly", + "example", + "except", + "f", + "far", + "few", + "fifth", + "first", + "five", + "followed", + "following", + "follows", + "for", + "former", + "formerly", + "forth", + "four", + "from", + "further", + "furthermore", + "g", + "get", + "gets", + "getting", + "given", + "gives", + "go", + "goes", + "going", + "gone", + "got", + "gotten", + "greetings", + "h", + "had", + "hadn't", + "happens", + "hardly", + "has", + "hasn't", + "have", + "haven't", + "having", + "he", + "he's", + "hello", + "help", + "hence", + "her", + "here", + "here's", + "hereafter", + "hereby", + "herein", + "hereupon", + "hers", + "herself", + "hi", + "him", + "himself", + "his", + "hither", + "hopefully", + "how", + "howbeit", + "however", + "i", + "i'd", + "i'll", + "i'm", + "i've", + "ie", + "if", + "ignored", + "immediate", + "in", + "inasmuch", + "inc", + "indeed", + "indicate", + "indicated", + "indicates", + "inner", + "insofar", + "instead", + "into", + "inward", + "is", + "isn't", + "it", + "it'd", + "it'll", + "it's", + "its", + "itself", + "j", + "just", + "k", + "keep", + "keeps", + "kept", + "know", + "known", + "knows", + "l", + "last", + "lately", + "later", + "latter", + "latterly", + "least", + "less", + "lest", + "let", + "let's", + "like", + "liked", + "likely", + "little", + "look", + "looking", + "looks", + "ltd", + "m", + "mainly", + "many", + "may", + "maybe", + "me", + "mean", + "meanwhile", + "merely", + "might", + "more", + "moreover", + "most", + "mostly", + "much", + "must", + "my", + "myself", + "n", + "name", + "namely", + "nd", + "near", + "nearly", + "necessary", + "need", + "needs", + "neither", + "never", + "nevertheless", + "new", + "next", + "nine", + "no", + "nobody", + "non", + "none", + 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+ "ahora", + "ah\u00ed", + "al", + "algo", + "alguna", + "algunas", + "alguno", + "algunos", + "alg\u00fan", + "alli", + "all\u00ed", + "alrededor", + "ambos", + "ampleamos", + "antano", + "anta\u00f1o", + "ante", + "anterior", + "antes", + "apenas", + "aproximadamente", + "aquel", + "aquella", + "aquellas", + "aquello", + "aquellos", + "aqui", + "aqu\u00e9l", + "aqu\u00e9lla", + "aqu\u00e9llas", + "aqu\u00e9llos", + "aqu\u00ed", + "arriba", + "arribaabajo", + "asegur\u00f3", + "asi", + "as\u00ed", + "atras", + "aun", + "aunque", + "ayer", + "a\u00f1adi\u00f3", + "a\u00fan", + "b", + "bajo", + "bastante", + "bien", + "breve", + "buen", + "buena", + "buenas", + "bueno", + "buenos", + "c", + "cada", + "casi", + "cerca", + "cierta", + "ciertas", + "cierto", + "ciertos", + "cinco", + "claro", + "coment\u00f3", + "como", + "con", + "conmigo", + "conocer", + "conseguimos", + "conseguir", + "considera", + "consider\u00f3", + "consigo", + "consigue", + "consiguen", + "consigues", + "contigo", + "contra", + "cosas", + "creo", + "cual", + "cuales", + "cualquier", + "cuando", + "cuanta", + "cuantas", + "cuanto", + "cuantos", + "cuatro", + "cuenta", + "cu\u00e1l", + "cu\u00e1les", + "cu\u00e1ndo", + "cu\u00e1nta", + "cu\u00e1ntas", + "cu\u00e1nto", + "cu\u00e1ntos", + "c\u00f3mo", + "d", + "da", + "dado", + "dan", + "dar", + "de", + "debajo", + "debe", + "deben", + "debido", + "decir", + "dej\u00f3", + "del", + "delante", + "demasiado", + "dem\u00e1s", + "dentro", + "deprisa", + "desde", + "despacio", + "despues", + "despu\u00e9s", + "detras", + "detr\u00e1s", + "dia", + "dias", + "dice", + "dicen", + "dicho", + "dieron", + "diferente", + "diferentes", + "dijeron", + "dijo", + "dio", + "donde", + "dos", + "durante", + "d\u00eda", + "d\u00edas", + "d\u00f3nde", + "e", + "ejemplo", + "el", + "ella", + "ellas", + "ello", + "ellos", + "embargo", + "empleais", + "emplean", + "emplear", + "empleas", + "empleo", + "en", + "encima", + "encuentra", + "enfrente", + "enseguida", + "entonces", + "entre", + "era", + "eramos", + "eran", + "eras", + "eres", + "es", + "esa", + "esas", + "ese", + "eso", + "esos", + "esta", + "estaba", + "estaban", + "estado", + "estados", + "estais", + "estamos", + "estan", + "estar", + "estar\u00e1", + "estas", + "este", + "esto", + "estos", + "estoy", + "estuvo", + "est\u00e1", + "est\u00e1n", + "ex", + "excepto", + "existe", + "existen", + "explic\u00f3", + "expres\u00f3", + "f", + "fin", + "final", + "fue", + "fuera", + "fueron", + "fui", + "fuimos", + "g", + "general", + "gran", + "grandes", + "gueno", + "h", + "ha", + "haber", + "habia", + "habla", + "hablan", + "habr\u00e1", + "hab\u00eda", + "hab\u00edan", + "hace", + "haceis", + "hacemos", + "hacen", + "hacer", + "hacerlo", + "haces", + "hacia", + "haciendo", + "hago", + "han", + "hasta", + "hay", + "haya", + "he", + "hecho", + "hemos", + "hicieron", + "hizo", + "horas", + "hoy", + "hubo", + "i", + "igual", + "incluso", + "indic\u00f3", + "informo", + "inform\u00f3", + "intenta", + "intentais", + "intentamos", + "intentan", + "intentar", + "intentas", + "intento", + "ir", + "j", + "junto", + "k", + "l", + "la", + "lado", + "largo", + "las", + "le", + "lejos", + "les", + "lleg\u00f3", + "lleva", + "llevar", + "lo", + "los", + "luego", + "lugar", + "m", + "mal", + "manera", + "manifest\u00f3", + "mas", + "mayor", + "me", + "mediante", + "medio", + "mejor", + "mencion\u00f3", + "menos", + "menudo", + "mi", + "mia", + "mias", + "mientras", + "mio", + "mios", + "mis", + "misma", + "mismas", + "mismo", + "mismos", + "modo", + "momento", + "mucha", + "muchas", + "mucho", + "muchos", + "muy", + "m\u00e1s", + "m\u00ed", + "m\u00eda", + "m\u00edas", + "m\u00edo", + "m\u00edos", + "n", + "nada", + "nadie", + "ni", + "ninguna", + "ningunas", + "ninguno", + "ningunos", + "ning\u00fan", + "no", + "nos", + "nosotras", + "nosotros", + "nuestra", + "nuestras", + "nuestro", + "nuestros", + "nueva", + "nuevas", + "nuevo", + "nuevos", + "nunca", + "o", + "ocho", + "os", 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"asiasta", + "asiat", + "asioiden", + "asioihin", + "asioita", + "asti", + "avuksi", + "avulla", + "avun", + "avutta", + "edelle", + "edelleen", + "edell\u00e4", + "edelt\u00e4", + "edemm\u00e4s", + "edes", + "edess\u00e4", + "edest\u00e4", + "ehk\u00e4", + "ei", + "eik\u00e4", + "eilen", + "eiv\u00e4t", + "eli", + "ellei", + "elleiv\u00e4t", + "ellemme", + "ellen", + "ellet", + "ellette", + "emme", + "en", + "enemm\u00e4n", + "eniten", + "ennen", + "ensi", + "ensimm\u00e4inen", + "ensimm\u00e4iseksi", + "ensimm\u00e4isen", + "ensimm\u00e4isen\u00e4", + "ensimm\u00e4iset", + "ensimm\u00e4isiksi", + "ensimm\u00e4isin\u00e4", + "ensimm\u00e4isi\u00e4", + "ensimm\u00e4ist\u00e4", + "ensin", + "entinen", + "entisen", + "entisi\u00e4", + "entisten", + "entist\u00e4", + "en\u00e4\u00e4", + "eri", + "eritt\u00e4in", + "erityisesti", + "er\u00e4iden", + "er\u00e4s", + "er\u00e4\u00e4t", + "esi", + "esiin", + "esill\u00e4", + "esimerkiksi", + "et", + "eteen", + "etenkin", + "etessa", + "ette", + "ettei", + "ett\u00e4", + "haikki", + "halua", + "haluaa", + "haluamatta", + "haluamme", + "haluan", + "haluat", + "haluatte", + "haluavat", + "halunnut", + "halusi", + "halusimme", + "halusin", + "halusit", + "halusitte", + "halusivat", + "halutessa", + "haluton", + "he", + "hei", + "heid\u00e4n", + "heihin", + "heille", + "heilt\u00e4", + "heiss\u00e4", + "heist\u00e4", + "heit\u00e4", + "helposti", + "heti", + "hetkell\u00e4", + "hieman", + "hitaasti", + "hoikein", + "huolimatta", + "huomenna", + "hyvien", + "hyviin", + "hyviksi", + "hyville", + "hyvilt\u00e4", + "hyvin", + "hyvin\u00e4", + "hyviss\u00e4", + "hyvist\u00e4", + "hyvi\u00e4", + "hyv\u00e4", + "hyv\u00e4t", + "hyv\u00e4\u00e4", + "h\u00e4n", + "h\u00e4neen", + "h\u00e4nelle", + "h\u00e4nell\u00e4", + "h\u00e4nelt\u00e4", + "h\u00e4nen", + "h\u00e4ness\u00e4", + "h\u00e4nest\u00e4", + "h\u00e4net", + "ihan", + "ilman", + "ilmeisesti", + "itse", + "itsens\u00e4", + "itse\u00e4\u00e4n", + "ja", + "jo", + "johon", + "joiden", + "joihin", + "joiksi", + "joilla", + "joille", + "joilta", + "joissa", + "joista", + "joita", + "joka", + "jokainen", + "jokin", + "joko", + "joku", + "jolla", + "jolle", + "jolloin", + "jolta", + "jompikumpi", + "jonka", + "jonkin", + "jonne", + "joo", + "jopa", + "jos", + "joskus", + "jossa", + "josta", + "jota", + "jotain", + "joten", + "jotenkin", + "jotenkuten", + "jotka", + "jotta", + "jouduimme", + "jouduin", + "jouduit", + "jouduitte", + "joudumme", + "joudun", + "joudutte", + "joukkoon", + "joukossa", + "joukosta", + "joutua", + "joutui", + "joutuivat", + "joutumaan", + "joutuu", + "joutuvat", + "juuri", + "j\u00e4lkeen", + "j\u00e4lleen", + "j\u00e4\u00e4", + "kahdeksan", + "kahdeksannen", + "kahdella", + "kahdelle", + "kahdelta", + "kahden", + "kahdessa", + "kahdesta", + "kahta", + "kahteen", + "kai", + "kaiken", + "kaikille", + "kaikilta", + "kaikkea", + "kaikki", + "kaikkia", + "kaikkiaan", + "kaikkialla", + "kaikkialle", + "kaikkialta", + "kaikkien", + "kaikkin", + "kaksi", + "kannalta", + "kannattaa", + "kanssa", + "kanssaan", + "kanssamme", + "kanssani", + "kanssanne", + "kanssasi", + "kauan", + "kauemmas", + "kaukana", + "kautta", + "kehen", + "keiden", + "keihin", + "keiksi", + "keille", + "keill\u00e4", + "keilt\u00e4", + "kein\u00e4", + "keiss\u00e4", + "keist\u00e4", + "keitten", + "keitt\u00e4", + "keit\u00e4", + "keneen", + "keneksi", + "kenelle", + "kenell\u00e4", + "kenelt\u00e4", + "kenen", + "kenen\u00e4", + "keness\u00e4", + "kenest\u00e4", + "kenet", + "kenett\u00e4", + "kenness\u00e4st\u00e4", + "kenties", + "kerran", + "kerta", + "kertaa", + "keskell\u00e4", + "kesken", + "keskim\u00e4\u00e4rin", + "ketk\u00e4", + "ket\u00e4", + "kiitos", + "kohti", + "koko", + "kokonaan", + "kolmas", + "kolme", + "kolmen", + "kolmesti", + "koska", + "koskaan", + "kovin", + "kuin", + "kuinka", + "kuinkan", + "kuitenkaan", + "kuitenkin", + "kuka", + "kukaan", + "kukin", + "kukka", + "kumpainen", + "kumpainenkaan", + "kumpi", + "kumpikaan", + "kumpikin", + "kun", + "kuten", + "kuuden", + "kuusi", + "kuutta", + "kylliksi", + "kyll\u00e4", + "kymmenen", + "kyse", + "liian", + "liki", + "lis\u00e4ksi", + "lis\u00e4\u00e4", + "lla", + "luo", + "luona", + "l\u00e4hekk\u00e4in", + "l\u00e4helle", + "l\u00e4hell\u00e4", + "l\u00e4helt\u00e4", + "l\u00e4hemm\u00e4s", + "l\u00e4hes", + "l\u00e4hinn\u00e4", + "l\u00e4htien", + "l\u00e4pi", + "mahdollisimman", + "mahdollista", + "me", + "meid\u00e4n", + "meille", + "meill\u00e4", + "melkein", + "melko", + "menee", + "meneet", + "menemme", + "menen", + "menet", + "menette", + "menev\u00e4t", + "meni", + "menimme", + "menin", + "menit", + "meniv\u00e4t", + "menness\u00e4", + "mennyt", + "menossa", + "mihin", + "mikin", + "miksi", + "mik\u00e4", + "mik\u00e4li", + "mik\u00e4\u00e4n", + "milloin", + "milloinkan", + "minne", + "minun", + "minut", + "min\u00e4", + "miss\u00e4", + "mist\u00e4", + "miten", + "mit\u00e4", + "mit\u00e4\u00e4n", + "moi", + "molemmat", + "mones", + "monesti", + "monet", + "moni", + "moniaalla", + "moniaalle", + "moniaalta", + "monta", + "muassa", + "muiden", + "muita", + "muka", + "mukaan", + "mukaansa", + "mukana", + "mutta", + "muu", + "muualla", + "muualle", + "muualta", + "muuanne", + "muulloin", + "muun", + "muut", + "muuta", + "muutama", + "muutaman", + "muuten", + "my\u00f6hemmin", + "my\u00f6s", + "my\u00f6skin", + "my\u00f6sk\u00e4\u00e4n", + "my\u00f6t\u00e4", + "ne", + "nelj\u00e4", + "nelj\u00e4n", + "nelj\u00e4\u00e4", + "niiden", + "niin", + "niist\u00e4", + "niit\u00e4", + "noin", + "nopeammin", + "nopeasti", + "nopeiten", + "nro", + "nuo", + "nyt", + "n\u00e4iden", + "n\u00e4in", + "n\u00e4iss\u00e4", + "n\u00e4iss\u00e4hin", + "n\u00e4iss\u00e4lle", + "n\u00e4iss\u00e4lt\u00e4", + "n\u00e4iss\u00e4st\u00e4", + "n\u00e4it\u00e4", + "n\u00e4m\u00e4", + "ohi", + "oikea", + "oikealla", + "oikein", + "ole", + "olemme", + "olen", + "olet", + "olette", + "oleva", + "olevan", + "olevat", + "oli", + "olimme", + "olin", + "olisi", + "olisimme", + "olisin", + "olisit", + "olisitte", + "olisivat", + "olit", + "olitte", + "olivat", + "olla", + "olleet", + "olli", + "ollut", + "oma", + "omaa", + "omaan", + "omaksi", + "omalle", + "omalta", + "oman", + "omassa", + "omat", + "omia", + "omien", + "omiin", + "omiksi", + "omille", + "omilta", + "omissa", + "omista", + "on", + "onkin", + "onko", + "ovat", + "paikoittain", + "paitsi", + "pakosti", + "paljon", + "paremmin", + "parempi", + "parhaillaan", + "parhaiten", + "perusteella", + "per\u00e4ti", + "pian", + "pieneen", + "pieneksi", + "pienelle", + "pienell\u00e4", + "pienelt\u00e4", + "pienempi", + "pienest\u00e4", + "pieni", + "pienin", + "puolesta", + "puolestaan", + "p\u00e4\u00e4lle", + "runsaasti", + "saakka", + "sadam", + "sama", + "samaa", + "samaan", + "samalla", + "samallalta", + "samallassa", + "samallasta", + "saman", + "samat", + "samoin", + "sata", + "sataa", + "satojen", + "se", + "seitsem\u00e4n", + "sek\u00e4", + "sen", + "seuraavat", + "siell\u00e4", + "sielt\u00e4", + "siihen", + "siin\u00e4", + "siis", + "siit\u00e4", + "sijaan", + "siksi", + "silloin", + "sill\u00e4", + "silti", + "sinne", + "sinua", + "sinulle", + "sinulta", + "sinun", + "sinussa", + "sinusta", + "sinut", + "sin\u00e4", + "sis\u00e4kk\u00e4in", + "sis\u00e4ll\u00e4", + "siten", + "sitten", + "sit\u00e4", + "ssa", + "sta", + "suoraan", + "suuntaan", + "suuren", + "suuret", + "suuri", + "suuria", + "suurin", + "suurten", + "taa", + "taas", + "taemmas", + "tahansa", + "tai", + "takaa", + "takaisin", + "takana", + "takia", + "tapauksessa", + "tarpeeksi", + "tavalla", + "tavoitteena", + "te", + "tietysti", + "todella", + "toinen", + "toisaalla", + "toisaalle", + "toisaalta", + "toiseen", + "toiseksi", + "toisella", + "toiselle", + "toiselta", + "toisemme", + "toisen", + "toisensa", + "toisessa", + "toisesta", + "toista", + "toistaiseksi", + "toki", + "tosin", + "tuhannen", + "tuhat", + "tule", + "tulee", + "tulemme", + "tulen", + "tulet", + "tulette", + "tulevat", + "tulimme", + "tulin", + "tulisi", + "tulisimme", + "tulisin", + "tulisit", + "tulisitte", + "tulisivat", + "tulit", + "tulitte", + "tulivat", + "tulla", + "tulleet", + "tullut", + "tuntuu", + "tuo", + "tuolla", + "tuolloin", + "tuolta", + "tuonne", + "tuskin", + "tyk\u00f6", + "t\u00e4h\u00e4n", + "t\u00e4ll\u00e4", + "t\u00e4ll\u00f6in", + "t\u00e4m\u00e4", + "t\u00e4m\u00e4n", + "t\u00e4nne", + "t\u00e4n\u00e4", + "t\u00e4n\u00e4\u00e4n", + "t\u00e4ss\u00e4", + "t\u00e4st\u00e4", + "t\u00e4ten", + "t\u00e4t\u00e4", + "t\u00e4ysin", + "t\u00e4ytyv\u00e4t", + "t\u00e4ytyy", + "t\u00e4\u00e4ll\u00e4", + "t\u00e4\u00e4lt\u00e4", + "ulkopuolella", + "usea", + "useasti", + "useimmiten", + "usein", + "useita", + "uudeksi", + "uudelleen", + "uuden", + "uudet", + "uusi", + "uusia", + "uusien", + "uusinta", + "uuteen", + "uutta", + "vaan", + "vahemm\u00e4n", + "vai", + "vaiheessa", + "vaikea", + "vaikean", + "vaikeat", + "vaikeilla", + "vaikeille", + "vaikeilta", + "vaikeissa", + "vaikeista", + "vaikka", + "vain", + "varmasti", + "varsin", + "varsinkin", + "varten", + "vasen", + "vasenmalla", + "vasta", + "vastaan", + "vastakkain", + "vastan", + "verran", + "viel\u00e4", + "vierekk\u00e4in", + "vieress\u00e4", + "vieri", + "viiden", + "viime", + "viimeinen", + "viimeisen", + "viimeksi", + "viisi", + "voi", + "voidaan", + "voimme", + "voin", + "voisi", + "voit", + "voitte", + "voivat", + "vuoden", + "vuoksi", + "vuosi", + "vuosien", + "vuosina", + "vuotta", + "v\u00e4hemm\u00e4n", + "v\u00e4hint\u00e4\u00e4n", + "v\u00e4hiten", + "v\u00e4h\u00e4n", + "v\u00e4lill\u00e4", + "yhdeks\u00e4n", + "yhden", + "yhdess\u00e4", + "yhteen", + "yhteens\u00e4", + "yhteydess\u00e4", + "yhteyteen", + "yht\u00e4", + "yht\u00e4\u00e4lle", + "yht\u00e4\u00e4ll\u00e4", + "yht\u00e4\u00e4lt\u00e4", + "yht\u00e4\u00e4n", + "yh\u00e4", + "yksi", + "yksin", + "yksitt\u00e4in", + "yleens\u00e4", + "ylemm\u00e4s", + "yli", + "yl\u00f6s", + "ymp\u00e4ri", + "\u00e4lk\u00f6\u00f6n", + "\u00e4l\u00e4", + ], + "fr": [ + "a", + "abord", + "absolument", + "afin", + "ah", + "ai", + "aie", + "ailleurs", + "ainsi", + "ait", + "allaient", + "allo", + "allons", + "all\u00f4", + "alors", + "anterieur", + "anterieure", + "anterieures", + "apres", + "apr\u00e8s", + "as", + "assez", + "attendu", + "au", + "aucun", + "aucune", + "aujourd", + "aujourd'hui", + "aupres", + "auquel", + "aura", + "auraient", + "aurait", + "auront", + "aussi", + "autre", + "autrefois", + "autrement", + "autres", + "autrui", + "aux", + "auxquelles", + "auxquels", + "avaient", + "avais", + "avait", + "avant", + "avec", + "avoir", + "avons", + "ayant", + "b", + "bah", + "bas", + "basee", + "bat", + "beau", + "beaucoup", + "bien", + "bigre", + "boum", + "bravo", + "brrr", + "c", + "car", + "ce", + "ceci", + "cela", + "celle", + "celle-ci", + "celle-l\u00e0", + "celles", + "celles-ci", + "celles-l\u00e0", + "celui", + "celui-ci", + "celui-l\u00e0", + "cent", + "cependant", + "certain", + "certaine", + "certaines", + "certains", + "certes", + "ces", + "cet", + "cette", + "ceux", + "ceux-ci", + "ceux-l\u00e0", + "chacun", + "chacune", + "chaque", + "cher", + "chers", + "chez", + "chiche", + "chut", + "ch\u00e8re", + "ch\u00e8res", + "ci", + "cinq", + "cinquantaine", + "cinquante", + "cinquanti\u00e8me", + "cinqui\u00e8me", + "clac", + "clic", + "combien", + "comme", + "comment", + "comparable", + "comparables", + "compris", + "concernant", + "contre", + "couic", + "crac", + "d", + "da", + "dans", + "de", + "debout", + "dedans", + "dehors", + "deja", + "del\u00e0", + "depuis", + "dernier", + "derniere", + "derriere", + "derri\u00e8re", + "des", + "desormais", + "desquelles", + "desquels", + "dessous", + "dessus", + "deux", + "deuxi\u00e8me", + "deuxi\u00e8mement", + "devant", + "devers", + "devra", + "different", + "differentes", + "differents", + "diff\u00e9rent", + "diff\u00e9rente", + "diff\u00e9rentes", + "diff\u00e9rents", + "dire", + "directe", + "directement", + "dit", + "dite", + "dits", + "divers", + "diverse", + "diverses", + "dix", + "dix-huit", + "dix-neuf", + "dix-sept", + "dixi\u00e8me", + "doit", + "doivent", + "donc", + "dont", + "douze", + "douzi\u00e8me", + "dring", + "du", + "duquel", + "durant", + "d\u00e8s", + "d\u00e9sormais", + "e", + "effet", + "egale", + "egalement", + "egales", + "eh", + "elle", + "elle-m\u00eame", + "elles", + "elles-m\u00eames", + "en", + "encore", + "enfin", + "entre", + "envers", + "environ", + "es", + "est", + "et", + "etant", + "etc", + "etre", + "eu", + "euh", + "eux", + "eux-m\u00eames", + "exactement", + "except\u00e9", + "extenso", + "exterieur", + "f", + "fais", + "faisaient", + "faisant", + "fait", + "fa\u00e7on", + "feront", + "fi", + "flac", + "floc", + "font", + "g", + "gens", + "h", + "ha", + "hein", + "hem", + "hep", + "hi", + "ho", + "hol\u00e0", + "hop", + "hormis", + "hors", + "hou", + "houp", + "hue", + "hui", + "huit", + "huiti\u00e8me", + "hum", + "hurrah", + "h\u00e9", + "h\u00e9las", + "i", + "il", + "ils", + "importe", + "j", + "je", + "jusqu", + "jusque", + "juste", + "k", + "l", + "la", + "laisser", + "laquelle", + "las", + "le", + "lequel", + "les", + "lesquelles", + "lesquels", + "leur", + "leurs", + "longtemps", + "lors", + "lorsque", + "lui", + "lui-meme", + "lui-m\u00eame", + "l\u00e0", + "l\u00e8s", + "m", + "ma", + "maint", + "maintenant", + "mais", + "malgre", + "malgr\u00e9", + "maximale", + "me", + "meme", + "memes", + "merci", + "mes", + "mien", + "mienne", + "miennes", + "miens", + "mille", + "mince", + "minimale", + "moi", + "moi-meme", + "moi-m\u00eame", + "moindres", + "moins", + "mon", + "moyennant", + "multiple", + "multiples", + "m\u00eame", + "m\u00eames", + "n", + "na", + "naturel", + "naturelle", + "naturelles", + "ne", + "neanmoins", + "necessaire", + "necessairement", + "neuf", + "neuvi\u00e8me", + "ni", + "nombreuses", + "nombreux", + "non", + "nos", + "notamment", + "notre", + "nous", + "nous-m\u00eames", + "nouveau", + "nul", + "n\u00e9anmoins", + "n\u00f4tre", + "n\u00f4tres", + "o", + "oh", + "oh\u00e9", + "oll\u00e9", + "ol\u00e9", + "on", + "ont", + "onze", + "onzi\u00e8me", + "ore", + "ou", + "ouf", + "ouias", + "oust", + "ouste", + "outre", + "ouvert", + "ouverte", + "ouverts", + "o|", + "o\u00f9", + "p", + "paf", + "pan", + "par", + "parce", + "parfois", + "parle", + "parlent", + "parler", + "parmi", + "parseme", + "partant", + "particulier", + "particuli\u00e8re", + "particuli\u00e8rement", + "pas", + "pass\u00e9", + "pendant", + "pense", + "permet", + "personne", + "peu", + "peut", + "peuvent", + "peux", + "pff", + "pfft", + "pfut", + "pif", + "pire", + "plein", + "plouf", + "plus", + "plusieurs", + "plut\u00f4t", + "possessif", + "possessifs", + "possible", + "possibles", + "pouah", + "pour", + "pourquoi", + "pourrais", + "pourrait", + "pouvait", + "prealable", + "precisement", + "premier", + "premi\u00e8re", + "premi\u00e8rement", + "pres", + "probable", + "probante", + "procedant", + "proche", + "pr\u00e8s", + "psitt", + "pu", + "puis", + "puisque", + "pur", + "pure", + "q", + "qu", + "quand", + "quant", + "quant-\u00e0-soi", + "quanta", + "quarante", + "quatorze", + "quatre", + "quatre-vingt", + "quatri\u00e8me", + "quatri\u00e8mement", + "que", + "quel", + "quelconque", + "quelle", + "quelles", + "quelqu'un", + "quelque", + "quelques", + "quels", + "qui", + "quiconque", + "quinze", + "quoi", + "quoique", + "r", + "rare", + "rarement", + "rares", + "relative", + "relativement", + "remarquable", + "rend", + "rendre", + "restant", + "reste", + "restent", + "restrictif", + "retour", + "revoici", + "revoil\u00e0", + "rien", + "s", + "sa", + "sacrebleu", + "sait", + "sans", + "sapristi", + "sauf", + "se", + "sein", + "seize", + "selon", + "semblable", + "semblaient", + "semble", + "semblent", + "sent", + "sept", + "septi\u00e8me", + "sera", + "seraient", + "serait", + "seront", + "ses", + "seul", + "seule", + "seulement", + "si", + "sien", + "sienne", + "siennes", + "siens", + "sinon", + "six", + "sixi\u00e8me", + "soi", + "soi-m\u00eame", + "soit", + "soixante", + "son", + "sont", + "sous", + "souvent", + "specifique", + "specifiques", + "speculatif", + "stop", + "strictement", + "subtiles", + "suffisant", + "suffisante", + "suffit", + "suis", + "suit", + "suivant", + "suivante", + "suivantes", + "suivants", + "suivre", + "superpose", + "sur", + "surtout", + "t", + "ta", + "tac", + "tant", + "tardive", + "te", + "tel", + "telle", + "tellement", + "telles", + "tels", + "tenant", + "tend", + "tenir", + "tente", + "tes", + "tic", + "tien", + "tienne", + "tiennes", + "tiens", + "toc", + "toi", + "toi-m\u00eame", + "ton", + "touchant", + "toujours", + "tous", + "tout", + "toute", + "toutefois", + "toutes", + "treize", + "trente", + "tres", + "trois", + "troisi\u00e8me", + "troisi\u00e8mement", + "trop", + "tr\u00e8s", + "tsoin", + "tsouin", + "tu", + "t\u00e9", + "u", + "un", + "une", + "unes", + "uniformement", + "unique", + "uniques", + "uns", + "v", + "va", + "vais", + "vas", + "vers", + "via", + "vif", + "vifs", + "vingt", + "vivat", + "vive", + "vives", + "vlan", + "voici", + "voil\u00e0", + "vont", + "vos", + "votre", + "vous", + "vous-m\u00eames", + "vu", + "v\u00e9", + "v\u00f4tre", + "v\u00f4tres", + "w", + "x", + "y", + "z", + "zut", + "\u00e0", + "\u00e2", + "\u00e7a", + "\u00e8s", + "\u00e9taient", + "\u00e9tais", + "\u00e9tait", + "\u00e9tant", + "\u00e9t\u00e9", + "\u00eatre", + "\u00f4", + ], + "ga": [ + "a", + "ach", + "ag", + "agus", + "an", + "aon", + "ar", + "arna", + "as", + "b'", + "ba", + "beirt", + "bh\u00far", + "caoga", + "ceathair", + "ceathrar", + "chomh", + "cht\u00f3", + "chuig", + "chun", + "cois", + "c\u00e9ad", + "c\u00faig", + "c\u00faigear", + "d'", + "daichead", + "dar", + "de", + "deich", + "deichni\u00far", + "den", + "dh\u00e1", + "do", + "don", + "dt\u00ed", + "d\u00e1", + "d\u00e1r", + "d\u00f3", + "faoi", + "faoin", + "faoina", + "faoin\u00e1r", + "fara", + "fiche", + "gach", + "gan", + "go", + "gur", + "haon", + "hocht", + "i", + "iad", + "idir", + "in", + "ina", + "ins", + "in\u00e1r", + "is", + "le", + "leis", + "lena", + "len\u00e1r", + "m'", + "mar", + "mo", + "m\u00e9", + "na", + "nach", + "naoi", + "naon\u00far", + "n\u00e1", + "n\u00ed", + "n\u00edor", + "n\u00f3", + "n\u00f3cha", + "ocht", + "ochtar", + "os", + "roimh", + "sa", + "seacht", + "seachtar", + "seacht\u00f3", + "seasca", + "seisear", + "siad", + "sibh", + "sinn", + "sna", + "s\u00e9", + "s\u00ed", + "tar", + "thar", + "th\u00fa", + "tri\u00far", + "tr\u00ed", + "tr\u00edna", + "tr\u00edn\u00e1r", + "tr\u00edocha", + "t\u00fa", + "um", + "\u00e1r", + "\u00e9", + "\u00e9is", + "\u00ed", + "\u00f3", + "\u00f3n", + "\u00f3na", + "\u00f3n\u00e1r", + ], + "gl": [ + "a", + "al\u00ed", + "ao", + "aos", + "aquel", + "aquela", + "aquelas", + "aqueles", + "aquilo", + "aqu\u00ed", + "as", + "as\u00ed", + "a\u00ednda", + "ben", + "cando", + "che", + "co", + "coa", + "coas", + "comigo", + "con", + "connosco", + "contigo", + "convosco", + "cos", + "cun", + "cunha", + "cunhas", + "cuns", + "da", + "dalgunha", + "dalgunhas", + "dalg\u00fan", + "dalg\u00fans", + "das", + "de", + "del", + "dela", + "delas", + "deles", + "desde", + "deste", + "do", + "dos", + "dun", + "dunha", + "dunhas", + "duns", + "e", + "el", + "ela", + "elas", + "eles", + "en", + "era", + "eran", + "esa", + "esas", + "ese", + "eses", + "esta", + "estaba", + "estar", + "este", + "estes", + "estiven", + "estou", + "est\u00e1", + "est\u00e1n", + "eu", + "facer", + "foi", + "foron", + "fun", + "hab\u00eda", + "hai", + "iso", + "isto", + "la", + "las", + "lle", + "lles", + "lo", + "los", + "mais", + "me", + "meu", + "meus", + "min", + "mi\u00f1a", + "mi\u00f1as", + "moi", + "na", + "nas", + "neste", + "nin", + "no", + "non", + "nos", + "nosa", + "nosas", + "noso", + "nosos", + "nun", + "nunha", + "nunhas", + "nuns", + "n\u00f3s", + "o", + "os", + "ou", + "para", + "pero", + "pode", + "pois", + "pola", + "polas", + "polo", + "polos", + "por", + "que", + "se", 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"\u0915\u094b\u0928\u0938\u093e", + "\u0915\u094c\u0928", + "\u0915\u094c\u0928\u0938\u093e", + "\u0917\u092f\u093e", + "\u0918\u0930", + "\u091c\u092c", + "\u091c\u0939\u093e\u0901", + "\u091c\u0939\u093e\u0902", + "\u091c\u093e", + "\u091c\u093f\u0902\u0939\u0947\u0902", + "\u091c\u093f\u0902\u0939\u094b\u0902", + "\u091c\u093f\u0924\u0928\u093e", + "\u091c\u093f\u0927\u0930", + "\u091c\u093f\u0928", + "\u091c\u093f\u0928\u094d\u0939\u0947\u0902", + "\u091c\u093f\u0928\u094d\u0939\u094b\u0902", + "\u091c\u093f\u0938", + "\u091c\u093f\u0938\u0947", + "\u091c\u0940\u0927\u0930", + "\u091c\u0947\u0938\u093e", + "\u091c\u0947\u0938\u0947", + "\u091c\u0948\u0938\u093e", + "\u091c\u0948\u0938\u0947", + "\u091c\u094b", + "\u0924\u0915", + "\u0924\u092c", + "\u0924\u0930\u0939", + "\u0924\u093f\u0902\u0939\u0947\u0902", + "\u0924\u093f\u0902\u0939\u094b\u0902", + "\u0924\u093f\u0928", + "\u0924\u093f\u0928\u094d\u0939\u0947\u0902", + "\u0924\u093f\u0928\u094d\u0939\u094b\u0902", + "\u0924\u093f\u0938", + "\u0924\u093f\u0938\u0947", + "\u0924\u094b", + "\u0925\u093e", + "\u0925\u093f", + "\u0925\u0940", + "\u0925\u0947", + "\u0926\u092c\u093e\u0930\u093e", + "\u0926\u0935\u093e\u0930\u093e", + "\u0926\u093f\u092f\u093e", + "\u0926\u0941\u0938\u0930\u093e", + "\u0926\u0941\u0938\u0930\u0947", + "\u0926\u0942\u0938\u0930\u0947", + "\u0926\u094b", + "\u0926\u094d\u0935\u093e\u0930\u093e", + "\u0928", + "\u0928\u0939\u093f\u0902", + "\u0928\u0939\u0940\u0902", + "\u0928\u093e", + "\u0928\u093f\u091a\u0947", + "\u0928\u093f\u0939\u093e\u092f\u0924", + "\u0928\u0940\u091a\u0947", + "\u0928\u0947", + "\u092a\u0930", + "\u092a\u0939\u0932\u0947", + "\u092a\u0941\u0930\u093e", + "\u092a\u0942\u0930\u093e", + "\u092a\u0947", + "\u092b\u093f\u0930", + "\u092c\u0928\u093f", + "\u092c\u0928\u0940", + "\u092c\u0939\u093f", + "\u092c\u0939\u0940", + "\u092c\u0939\u0941\u0924", + "\u092c\u093e\u0926", + "\u092c\u093e\u0932\u093e", + "\u092c\u093f\u0932\u0915\u0941\u0932", + "\u092d\u093f", + "\u092d\u093f\u0924\u0930", + "\u092d\u0940", + "\u092d\u0940\u0924\u0930", + "\u092e\u0917\u0930", + "\u092e\u093e\u0928\u094b", + "\u092e\u0947", + "\u092e\u0947\u0902", + "\u092f\u0926\u093f", + "\u092f\u0939", + "\u092f\u0939\u093e\u0901", + "\u092f\u0939\u093e\u0902", + "\u092f\u0939\u093f", + "\u092f\u0939\u0940", + "\u092f\u093e", + "\u092f\u093f\u0939", + "\u092f\u0947", + "\u0930\u0916\u0947\u0902", + "\u0930\u0935\u093e\u0938\u093e", + "\u0930\u0939\u093e", + "\u0930\u0939\u0947", + "\u0931\u094d\u0935\u093e\u0938\u093e", + "\u0932\u093f\u090f", + "\u0932\u093f\u092f\u0947", + "\u0932\u0947\u0915\u093f\u0928", + "\u0935", + "\u0935\u0917\u0947\u0930\u0939", + "\u0935\u0930\u0917", + "\u0935\u0930\u094d\u0917", + "\u0935\u0939", + "\u0935\u0939\u093e\u0901", + "\u0935\u0939\u093e\u0902", + "\u0935\u0939\u093f\u0902", + "\u0935\u0939\u0940\u0902", + "\u0935\u093e\u0932\u0947", + "\u0935\u0941\u0939", + "\u0935\u0947", + "\u0935\u095a\u0948\u0930\u0939", + "\u0938\u0902\u0917", + "\u0938\u0915\u0924\u093e", + "\u0938\u0915\u0924\u0947", + "\u0938\u092c\u0938\u0947", + "\u0938\u092d\u093f", + "\u0938\u092d\u0940", + "\u0938\u093e\u0925", + "\u0938\u093e\u092c\u0941\u0924", + "\u0938\u093e\u092d", + "\u0938\u093e\u0930\u093e", + "\u0938\u0947", + "\u0938\u094b", + "\u0939\u093f", + "\u0939\u0940", + "\u0939\u0941\u0905", + "\u0939\u0941\u0906", + "\u0939\u0941\u0907", + "\u0939\u0941\u0908", + "\u0939\u0941\u090f", + "\u0939\u0947", + "\u0939\u0947\u0902", + "\u0939\u0948", + "\u0939\u0948\u0902", + "\u0939\u094b", + "\u0939\u094b\u0924\u093e", + "\u0939\u094b\u0924\u093f", + "\u0939\u094b\u0924\u0940", + "\u0939\u094b\u0924\u0947", + "\u0939\u094b\u0928\u093e", + "\u0939\u094b\u0928\u0947", + ], + "hr": [ + "a", + "ako", + "ali", + "bi", + "bih", + "bila", + "bili", + "bilo", + "bio", + "bismo", + "biste", + "biti", + "bumo", + "da", + "do", + "du\u017e", + "ga", + "ho\u0107e", + "ho\u0107emo", + "ho\u0107ete", + "ho\u0107e\u0161", + "ho\u0107u", + "i", + "iako", + "ih", + "ili", + "iz", + "ja", + "je", + "jedna", + "jedne", + "jedno", + "jer", + "jesam", + "jesi", + "jesmo", + "jest", + "jeste", + "jesu", + "jim", + "joj", + "jo\u0161", + "ju", + "kada", + "kako", + "kao", + "koja", + "koje", + "koji", + "kojima", + "koju", + "kroz", + "li", + "me", + "mene", + "meni", + "mi", + "mimo", + "moj", + "moja", + "moje", + "mu", + "na", + "nad", + "nakon", + "nam", + "nama", + "nas", + "na\u0161", + "na\u0161a", + "na\u0161e", + "na\u0161eg", + "ne", + "nego", + "neka", + "neki", + "nekog", + "neku", + "nema", + "netko", + "ne\u0107e", + "ne\u0107emo", + "ne\u0107ete", + "ne\u0107e\u0161", + "ne\u0107u", + "ne\u0161to", + "ni", + "nije", + "nikoga", + "nikoje", + "nikoju", + "nisam", + "nisi", + "nismo", + "niste", + "nisu", + "njega", + "njegov", + "njegova", + "njegovo", + "njemu", + "njezin", + "njezina", + "njezino", + "njih", + "njihov", + "njihova", + "njihovo", + "njim", + "njima", + "njoj", + "nju", + "no", + "o", + "od", + "odmah", + "on", + "ona", + "oni", + "ono", + "ova", + "pa", + "pak", + "po", + "pod", + "pored", + "prije", + "s", + "sa", + "sam", + "samo", + "se", + "sebe", + "sebi", + "si", + "smo", + "ste", + "su", + "sve", + "svi", + "svog", + "svoj", + "svoja", + "svoje", + "svom", + "ta", + "tada", + "taj", + "tako", + "te", + "tebe", + "tebi", + "ti", + "to", + "toj", + "tome", + "tu", + "tvoj", + "tvoja", + "tvoje", + "u", + "uz", + "vam", + "vama", + "vas", + "va\u0161", + "va\u0161a", + "va\u0161e", + "ve\u0107", + "vi", + "vrlo", + "za", + "zar", + "\u0107e", + "\u0107emo", + "\u0107ete", + "\u0107e\u0161", + "\u0107u", + "\u0161to", + ], + "hu": [ + "a", + "abba", + "abban", + "abb\u00f3l", + "addig", + "ahhoz", + "ahogy", + "ahol", + "aki", + "akik", + "akkor", + "ak\u00e1r", + "alapj\u00e1n", + "alatt", + "alatta", + "alattad", + "alattam", + "alattatok", + "alattuk", + "alattunk", + "al\u00e1", + "al\u00e1d", + "al\u00e1juk", + "al\u00e1m", + "al\u00e1nk", + "al\u00e1tok", + "al\u00f3l", + "al\u00f3la", + "al\u00f3lad", + "al\u00f3lam", + "al\u00f3latok", + "al\u00f3luk", + "al\u00f3lunk", + "amely", + "amelybol", + "amelyek", + "amelyekben", + "amelyeket", + "amelyet", + "amelyik", + "amelynek", + "ami", + "amikor", + "amit", + "amolyan", + "amott", + "am\u00edg", + "annak", + "ann\u00e1l", + "arra", + "arr\u00f3l", + "att\u00f3l", + "az", + "aznap", + "azok", + "azokat", + "azokba", + "azokban", + "azokb\u00f3l", + "azokhoz", + "azokig", + "azokkal", + "azokk\u00e1", + "azoknak", + "azokn\u00e1l", + "azokon", + "azokra", + "azokr\u00f3l", + "azokt\u00f3l", + "azok\u00e9rt", + "azon", + "azonban", + "azonnal", + "azt", + "azt\u00e1n", + "azut\u00e1n", + "azzal", + "azz\u00e1", + "az\u00e9rt", + "bal", + "balra", + "ban", + "be", + "bel\u00e9", + "bel\u00e9d", + "bel\u00e9j\u00fck", + "bel\u00e9m", + "bel\u00e9nk", + "bel\u00e9tek", + "bel\u00fcl", + "bel\u0151le", + "bel\u0151led", + "bel\u0151lem", + "bel\u0151letek", + "bel\u0151l\u00fck", + "bel\u0151l\u00fcnk", + "ben", + "benne", + "benned", + "bennem", + "bennetek", + "benn\u00fck", + "benn\u00fcnk", + "b\u00e1r", + "b\u00e1rcsak", + "b\u00e1rmilyen", + "b\u00facs\u00fa", + "cikk", + "cikkek", + "cikkeket", + "csak", + "csakhogy", + "csup\u00e1n", + "de", + "dehogy", + "e", + "ebbe", + "ebben", + "ebb\u0151l", + "eddig", + "egy", + "egyebek", + "egyebet", + "egyed\u00fcl", + "egyel\u0151re", + "egyes", + "egyet", + "egyetlen", + "egyik", + "egym\u00e1s", + "egyre", + "egyszerre", + "egy\u00e9b", + "egy\u00fctt", + "eg\u00e9sz", + "eg\u00e9szen", + "ehhez", + "ekkor", + "el", + "eleinte", + "ellen", + "ellenes", + "elleni", + "ellen\u00e9re", + "elmondta", + "els\u0151", + "els\u0151k", + "els\u0151sorban", + "els\u0151t", + "el\u00e9", + "el\u00e9d", + "el\u00e9g", + "el\u00e9j\u00fck", + "el\u00e9m", + "el\u00e9nk", + "el\u00e9tek", + "el\u0151", + "el\u0151bb", + "el\u0151l", + "el\u0151le", + "el\u0151led", + "el\u0151lem", + "el\u0151letek", + "el\u0151l\u00fck", + "el\u0151l\u00fcnk", + "el\u0151sz\u00f6r", + "el\u0151tt", + "el\u0151tte", + "el\u0151tted", + "el\u0151ttem", + "el\u0151ttetek", + "el\u0151tt\u00fck", + "el\u0151tt\u00fcnk", + "el\u0151z\u0151", + "emilyen", + "engem", + "ennek", + "ennyi", + "enn\u00e9l", + "eny\u00e9m", + "erre", + "err\u0151l", + "esetben", + "ett\u0151l", + "ez", + "ezek", + "ezekbe", + "ezekben", + "ezekb\u0151l", + "ezeken", + "ezeket", + "ezekhez", + "ezekig", + "ezekkel", + "ezekk\u00e9", + "ezeknek", + "ezekn\u00e9l", + "ezekre", + "ezekr\u0151l", + "ezekt\u0151l", + "ezek\u00e9rt", + "ezen", + "ezent\u00fal", + "ezer", + "ezret", + "ezt", + "ezut\u00e1n", + "ezzel", + "ezz\u00e9", + "ez\u00e9rt", + "fel", + "fele", + "felek", + "felet", + "felett", + "fel\u00e9", + "fent", + "fenti", + "f\u00e9l", + "f\u00f6l\u00e9", + "gyakran", + "ha", + "hall\u00f3", + "hamar", + "hanem", + "harmadik", + "harmadikat", + "harminc", + "hat", + "hatodik", + "hatodikat", + "hatot", + "hatvan", + "helyett", + "hetedik", + "hetediket", + "hetet", + "hetven", + "hirtelen", + "hiszen", + "hi\u00e1ba", + "hogy", + "hogyan", + "hol", + "holnap", + "holnapot", + "honnan", + "hova", + "hozz\u00e1", + "hozz\u00e1d", + "hozz\u00e1juk", + "hozz\u00e1m", + "hozz\u00e1nk", + "hozz\u00e1tok", + "hurr\u00e1", + "huszadik", + "h\u00e1ny", + "h\u00e1nyszor", + "h\u00e1rmat", + "h\u00e1rom", + "h\u00e1t", + "h\u00e1tha", + "h\u00e1tuls\u00f3", + "h\u00e9t", + "h\u00fasz", + "ide", + "ide-\u043eda", + "id\u00e9n", + "igaz\u00e1n", + "igen", + "ill", + "illetve", + "ilyen", + "ilyenkor", + "imm\u00e1r", + "ink\u00e1bb", + "is", + "ism\u00e9t", + "ison", + "itt", + "jelenleg", + "jobban", + "jobbra", + "j\u00f3", + "j\u00f3l", + "j\u00f3lesik", + "j\u00f3val", + "j\u00f6v\u0151re", + "kell", + "kellene", + "kellett", + "kelljen", + "keress\u00fcnk", + "kereszt\u00fcl", + "ketten", + "kett\u0151", + "kett\u0151t", + "kev\u00e9s", + "ki", + "kiben", + "kib\u0151l", + "kicsit", + "kicsoda", + "kihez", + "kik", + "kikbe", + "kikben", + "kikb\u0151l", + "kiken", + "kiket", + "kikhez", + "kikkel", + "kikk\u00e9", + "kiknek", + "kikn\u00e9l", + "kikre", + "kikr\u0151l", + "kikt\u0151l", + "kik\u00e9rt", + "kilenc", + "kilencedik", + "kilencediket", + "kilencet", + "kilencven", + "kin", + "kinek", + "kin\u00e9l", + "kire", + "kir\u0151l", + "kit", + "kit\u0151l", + "kivel", + "kiv\u00e9", + "ki\u00e9", + "ki\u00e9rt", + "kor\u00e1bban", + "k\u00e9pest", + "k\u00e9rem", + "k\u00e9rlek", + "k\u00e9sz", + "k\u00e9s\u0151", + "k\u00e9s\u0151bb", + "k\u00e9s\u0151n", + "k\u00e9t", + "k\u00e9tszer", + "k\u00edv\u00fcl", + "k\u00f6r\u00fcl", + "k\u00f6sz\u00f6nhet\u0151en", + "k\u00f6sz\u00f6n\u00f6m", + "k\u00f6zben", + "k\u00f6zel", + "k\u00f6zepesen", + "k\u00f6zep\u00e9n", + "k\u00f6z\u00e9", + "k\u00f6z\u00f6tt", + "k\u00f6z\u00fcl", + "k\u00fcl\u00f6n", + "k\u00fcl\u00f6nben", + "k\u00fcl\u00f6nb\u00f6z\u0151", + "k\u00fcl\u00f6nb\u00f6z\u0151bb", + "k\u00fcl\u00f6nb\u00f6z\u0151ek", + "lassan", + "le", + "legal\u00e1bb", + "legyen", + "lehet", + "lehetetlen", + "lehetett", + "lehet\u0151leg", + "lehet\u0151s\u00e9g", + "lenne", + "lenni", + "lenn\u00e9k", + "lenn\u00e9nek", + "lesz", + "leszek", + "lesznek", + "lesz\u00fcnk", + "lett", + "lettek", + "lettem", + "lett\u00fcnk", + "l\u00e9v\u0151", + "ma", + "maga", + "magad", + "magam", + "magatokat", + "magukat", + "magunkat", + "mag\u00e1t", + "mai", + "majd", + "majdnem", + "manaps\u00e1g", + "meg", + "megcsin\u00e1l", + "megcsin\u00e1lnak", + "megint", + "megvan", + "mellett", + "mellette", + "melletted", + "mellettem", + "mellettetek", + "mellett\u00fck", + "mellett\u00fcnk", + "mell\u00e9", + "mell\u00e9d", + "mell\u00e9j\u00fck", + "mell\u00e9m", + "mell\u00e9nk", + "mell\u00e9tek", + "mell\u0151l", + "mell\u0151le", + "mell\u0151led", + "mell\u0151lem", + "mell\u0151letek", + "mell\u0151l\u00fck", + "mell\u0151l\u00fcnk", + "mely", + "melyek", + "melyik", + "mennyi", + "mert", + "mi", + "miatt", + "miatta", + "miattad", + "miattam", + "miattatok", + "miattuk", + "miattunk", + "mibe", + "miben", + "mib\u0151l", + "mihez", + "mik", + "mikbe", + "mikben", + "mikb\u0151l", + "miken", + "miket", + "mikhez", + "mikkel", + "mikk\u00e9", + "miknek", + "mikn\u00e9l", + "mikor", + "mikre", + "mikr\u0151l", + "mikt\u0151l", + "mik\u00e9rt", + "milyen", + "min", + "mind", + "mindegyik", + "mindegyiket", + "minden", + "mindenesetre", + "mindenki", + "mindent", + "minden\u00fctt", + "mindig", + "mindketten", + "minek", + "minket", + "mint", + "mintha", + "min\u00e9l", + "mire", + "mir\u0151l", + "mit", + "mit\u0151l", + "mivel", + "miv\u00e9", + "mi\u00e9rt", + "mondta", + "most", + "mostan\u00e1ig", + "m\u00e1r", + "m\u00e1s", + "m\u00e1sik", + "m\u00e1sikat", + "m\u00e1snap", + "m\u00e1sodik", + "m\u00e1sodszor", + "m\u00e1sok", + "m\u00e1sokat", + "m\u00e1st", + "m\u00e9g", + "m\u00e9gis", + "m\u00edg", + "m\u00f6g\u00e9", + "m\u00f6g\u00e9d", + "m\u00f6g\u00e9j\u00fck", + "m\u00f6g\u00e9m", + "m\u00f6g\u00e9nk", + "m\u00f6g\u00e9tek", + "m\u00f6g\u00f6tt", + "m\u00f6g\u00f6tte", + "m\u00f6g\u00f6tted", + "m\u00f6g\u00f6ttem", + "m\u00f6g\u00f6ttetek", + "m\u00f6g\u00f6tt\u00fck", + "m\u00f6g\u00f6tt\u00fcnk", + "m\u00f6g\u00fcl", + "m\u00f6g\u00fcle", + "m\u00f6g\u00fcled", + "m\u00f6g\u00fclem", + "m\u00f6g\u00fcletek", + "m\u00f6g\u00fcl\u00fck", + "m\u00f6g\u00fcl\u00fcnk", + "m\u00faltkor", + "m\u00falva", + "na", + "nagy", + "nagyobb", + "nagyon", + "naponta", + "napot", + "ne", + "negyedik", + "negyediket", + "negyven", + "neked", + "nekem", + "neki", + "nekik", + "nektek", + "nek\u00fcnk", + "nem", + "nemcsak", + "nemr\u00e9g", + "nincs", + "nyolc", + "nyolcadik", + "nyolcadikat", + "nyolcat", + "nyolcvan", + "n\u00e1la", + "n\u00e1lad", + "n\u00e1lam", + "n\u00e1latok", + "n\u00e1luk", + "n\u00e1lunk", + "n\u00e9gy", + "n\u00e9gyet", + "n\u00e9ha", + "n\u00e9h\u00e1ny", + "n\u00e9lk\u00fcl", + "o", + "oda", + "ok", + "olyan", + "onnan", + "ott", + "pedig", + "persze", + "p\u00e1r", + "p\u00e9ld\u00e1ul", + "rajta", + "rajtad", + "rajtam", + "rajtatok", + "rajtuk", + "rajtunk", + "rendben", + "rosszul", + "r\u00e1", + "r\u00e1d", + "r\u00e1juk", + "r\u00e1m", + "r\u00e1nk", + "r\u00e1tok", + "r\u00e9gen", + "r\u00e9g\u00f3ta", + "r\u00e9sz\u00e9re", + "r\u00f3la", + "r\u00f3lad", + "r\u00f3lam", + "r\u00f3latok", + "r\u00f3luk", + "r\u00f3lunk", + "r\u00f6gt\u00f6n", + "s", + "saj\u00e1t", + "se", + "sem", + "semmi", + "semmilyen", + "semmis\u00e9g", + "senki", + "soha", + "sok", + "sokan", + "sokat", + "sokkal", + "sokszor", + "sok\u00e1ig", + "sor\u00e1n", + "stb.", + "szemben", + "szerbusz", + "szerint", + "szerinte", + "szerinted", + "szerintem", + "szerintetek", + "szerint\u00fck", + "szerint\u00fcnk", + "szervusz", + "szinte", + "sz\u00e1m\u00e1ra", + "sz\u00e1z", + "sz\u00e1zadik", + "sz\u00e1zat", + "sz\u00e9pen", + "sz\u00e9t", + "sz\u00edves", + "sz\u00edvesen", + "sz\u00edveskedj\u00e9k", + "s\u0151t", + "tal\u00e1n", + "tavaly", + "te", + "tegnap", + "tegnapel\u0151tt", + "teh\u00e1t", + "tele", + "teljes", + "tess\u00e9k", + "ti", + "tied", + "titeket", + "tizedik", + "tizediket", + "tizenegy", + "tizenegyedik", + "tizenhat", + "tizenh\u00e1rom", + "tizenh\u00e9t", + "tizenkettedik", + "tizenkett\u0151", + "tizenkilenc", + "tizenk\u00e9t", + "tizennyolc", + "tizenn\u00e9gy", + "tizen\u00f6t", + "tizet", + "tov\u00e1bb", + "tov\u00e1bbi", + "tov\u00e1bb\u00e1", + "t\u00e1vol", + "t\u00e9ged", + "t\u00e9nyleg", + "t\u00edz", + "t\u00f6bb", + "t\u00f6bbi", + "t\u00f6bbsz\u00f6r", + "t\u00fal", + "t\u0151le", + "t\u0151led", + "t\u0151lem", + "t\u0151letek", + "t\u0151l\u00fck", + "t\u0151l\u00fcnk", + "ugyanakkor", + "ugyanez", + "ugyanis", + "ugye", + "urak", + "uram", + "urat", + "utolj\u00e1ra", + "utols\u00f3", + "ut\u00e1n", + "ut\u00e1na", + "vagy", + "vagyis", + "vagyok", + "vagytok", + "vagyunk", + "vajon", + "valahol", + "valaki", + "valakit", + "valamelyik", + "valami", + "valamint", + "val\u00f3", + "van", + "vannak", + "vele", + "veled", + "velem", + "veletek", + "vel\u00fck", + "vel\u00fcnk", + "vissza", + "viszl\u00e1t", + "viszont", + "viszontl\u00e1t\u00e1sra", + "volna", + "voln\u00e1nak", + "voln\u00e9k", + "volt", + "voltak", + "voltam", + "voltunk", + "v\u00e9gre", + "v\u00e9g\u00e9n", + "v\u00e9g\u00fcl", + "\u00e1ltal", + "\u00e1ltal\u00e1ban", + "\u00e1m", + "\u00e1t", + "\u00e9ljen", + "\u00e9n", + "\u00e9ppen", + "\u00e9rte", + "\u00e9rted", + "\u00e9rtem", + "\u00e9rtetek", + "\u00e9rt\u00fck", + "\u00e9rt\u00fcnk", + "\u00e9s", + "\u00e9v", + "\u00e9vben", + "\u00e9ve", + "\u00e9vek", + "\u00e9ves", + "\u00e9vi", + "\u00e9vvel", + "\u00edgy", + "\u00f3ta", + "\u00f6n", + "\u00f6nbe", + "\u00f6nben", + "\u00f6nb\u0151l", + "\u00f6nh\u00f6z", + "\u00f6nnek", + "\u00f6nnel", + "\u00f6nn\u00e9l", + "\u00f6nre", + "\u00f6nr\u0151l", + "\u00f6nt", + "\u00f6nt\u0151l", + "\u00f6n\u00e9rt", + "\u00f6n\u00f6k", + "\u00f6n\u00f6kbe", + "\u00f6n\u00f6kben", + "\u00f6n\u00f6kb\u0151l", + "\u00f6n\u00f6ket", + "\u00f6n\u00f6kh\u00f6z", + "\u00f6n\u00f6kkel", + "\u00f6n\u00f6knek", + "\u00f6n\u00f6kn\u00e9l", + "\u00f6n\u00f6kre", + "\u00f6n\u00f6kr\u0151l", + "\u00f6n\u00f6kt\u0151l", + "\u00f6n\u00f6k\u00e9rt", + "\u00f6n\u00f6k\u00f6n", + "\u00f6n\u00f6n", + "\u00f6ssze", + "\u00f6t", + "\u00f6tven", + "\u00f6t\u00f6dik", + "\u00f6t\u00f6diket", + "\u00f6t\u00f6t", + "\u00fagy", + "\u00fagyis", + "\u00fagynevezett", + "\u00faj", + "\u00fajabb", + "\u00fajra", + "\u00far", + "\u0151", + "\u0151k", + "\u0151ket", + "\u0151t", + ], + "hy": [ + "\u0561\u0575\u0564", + "\u0561\u0575\u056c", + "\u0561\u0575\u0576", + "\u0561\u0575\u057d", + "\u0564\u0578\u0582", + "\u0564\u0578\u0582\u0584", + "\u0565\u0574", + "\u0565\u0576", + "\u0565\u0576\u0584", + "\u0565\u057d", + "\u0565\u0584", + "\u0567", + "\u0567\u056b", + "\u0567\u056b\u0576", + "\u0567\u056b\u0576\u0584", + "\u0567\u056b\u0580", + "\u0567\u056b\u0584", + "\u0567\u0580", + "\u0568\u057d\u057f", + "\u0569", + "\u056b", + "\u056b\u0576", + "\u056b\u057d\u056f", + "\u056b\u0580", + "\u056f\u0561\u0574", + "\u0570\u0561\u0574\u0561\u0580", + "\u0570\u0565\u057f", + "\u0570\u0565\u057f\u0578", + "\u0574\u0565\u0576\u0584", + "\u0574\u0565\u057b", + "\u0574\u056b", + "\u0576", + "\u0576\u0561", + "\u0576\u0561\u0587", + "\u0576\u0580\u0561", + "\u0576\u0580\u0561\u0576\u0584", + "\u0578\u0580", + "\u0578\u0580\u0568", + "\u0578\u0580\u0578\u0576\u0584", + "\u0578\u0580\u057a\u0565\u057d", + "\u0578\u0582", + "\u0578\u0582\u0574", + "\u057a\u056b\u057f\u056b", + "\u057e\u0580\u0561", + "\u0587", + ], + "id": [ + "ada", + "adalah", + "adanya", + "adapun", + "agak", + "agaknya", + "agar", + "akan", + "akankah", + "akhirnya", + "aku", + "akulah", + "amat", + "amatlah", + "anda", + "andalah", + "antar", + "antara", + "antaranya", + "apa", + "apaan", + "apabila", + "apakah", + "apalagi", + "apatah", + "atau", + "ataukah", + "ataupun", + "bagai", + "bagaikan", + "bagaimana", + "bagaimanakah", + "bagaimanapun", + "bagi", + "bahkan", + "bahwa", + "bahwasanya", + "banyak", + "beberapa", + "begini", + "beginian", + "beginikah", + "beginilah", + "begitu", + "begitukah", + "begitulah", + "begitupun", + "belum", + "belumlah", + "berapa", + "berapakah", + "berapalah", + "berapapun", + "bermacam", + "bersama", + "betulkah", + "biasa", + "biasanya", + "bila", + "bilakah", + "bisa", + "bisakah", + "boleh", + "bolehkah", + "bolehlah", + "buat", + "bukan", + "bukankah", + "bukanlah", + "bukannya", + "cuma", + "dahulu", + "dalam", + "dan", + "dapat", + "dari", + "daripada", + "dekat", + "demi", + "demikian", + "demikianlah", + "dengan", + "depan", + "di", + "dia", + "dialah", + "diantara", + "diantaranya", + "dikarenakan", + "dini", + "diri", + "dirinya", + "disini", + "disinilah", + "dong", + "dulu", + "enggak", + "enggaknya", + "entah", + "entahlah", + "hal", + "hampir", + "hanya", + "hanyalah", + "harus", + "haruslah", + "harusnya", + "hendak", + "hendaklah", + "hendaknya", + "hingga", + "ia", + "ialah", + "ibarat", + "ingin", + "inginkah", + "inginkan", + "ini", + "inikah", + "inilah", + "itu", + "itukah", + "itulah", + "jangan", + "jangankan", + "janganlah", + "jika", + "jikalau", + "juga", + "justru", + "kala", + "kalau", + "kalaulah", + "kalaupun", + "kalian", + "kami", + "kamilah", + "kamu", + "kamulah", + "kan", + "kapan", + "kapankah", + "kapanpun", + "karena", + "karenanya", + "ke", + "kecil", + "kemudian", + "kenapa", + "kepada", + "kepadanya", + "ketika", + "khususnya", + "kini", + "kinilah", + "kiranya", + "kita", + "kitalah", + "kok", + "lagi", + "lagian", + "lah", + "lain", + "lainnya", + "lalu", + "lama", + "lamanya", + "lebih", + "macam", + "maka", + "makanya", + "makin", + "malah", + "malahan", + "mampu", + "mampukah", + "mana", + "manakala", + "manalagi", + "masih", + "masihkah", + "masing", + "mau", + "maupun", + "melainkan", + "melalui", + "memang", + "mengapa", + "mereka", + "merekalah", + "merupakan", + "meski", + "meskipun", + "mungkin", + "mungkinkah", + "nah", + "namun", + "nanti", + "nantinya", + "nyaris", + "oleh", + "olehnya", + "pada", + "padahal", + "padanya", + "paling", + "pantas", + "para", + "pasti", + "pastilah", + "per", + "percuma", + "pernah", + "pula", + "pun", + "rupanya", + "saat", + "saatnya", + "saja", + "sajalah", + "saling", + "sama", + "sambil", + "sampai", + "sana", + "sangat", + "sangatlah", + "saya", + "sayalah", + "se", + "sebab", + "sebabnya", + "sebagai", + "sebagaimana", + "sebagainya", + "sebaliknya", + "sebanyak", + "sebegini", + "sebegitu", + "sebelum", + "sebelumnya", + "sebenarnya", + "seberapa", + "sebetulnya", + "sebisanya", + "sebuah", + "sedang", + "sedangkan", + "sedemikian", + "sedikit", + "sedikitnya", + "segala", + "segalanya", + "segera", + "seharusnya", + "sehingga", + "sejak", + "sejenak", + "sekali", + "sekalian", + "sekaligus", + "sekalipun", + "sekarang", + "seketika", + "sekiranya", + "sekitar", + "sekitarnya", + "sela", + "selagi", + "selain", + "selaku", + "selalu", + "selama", + "selamanya", + "seluruh", + "seluruhnya", + "semacam", + "semakin", + "semasih", + "semaunya", + "sementara", + "sempat", + "semua", + "semuanya", + "semula", + "sendiri", + "sendirinya", + "seolah", + "seorang", + "sepanjang", + "sepantasnya", + "sepantasnyalah", + "seperti", + "sepertinya", + "sering", + "seringnya", + "serta", + "serupa", + "sesaat", + "sesama", + "sesegera", + "sesekali", + "seseorang", + "sesuatu", + "sesuatunya", + "sesudah", + "sesudahnya", + "setelah", + "seterusnya", + "setiap", + "setidaknya", + "sewaktu", + "siapa", + "siapakah", + "siapapun", + "sini", + "sinilah", + "suatu", + "sudah", + "sudahkah", + "sudahlah", + "supaya", + "tadi", + "tadinya", + "tak", + "tanpa", + "tapi", + "telah", + "tentang", + "tentu", + "tentulah", + "tentunya", + "terdiri", + "terhadap", + "terhadapnya", + "terlalu", + "terlebih", + "tersebut", + "tersebutlah", + "tertentu", + "tetapi", + "tiap", + "tidak", + "tidakkah", + "tidaklah", + "toh", + "waduh", + "wah", + "wahai", + "walau", + "walaupun", + "wong", + "yaitu", + "yakni", + "yang", + ], + "it": [ + "IE", + "a", + "abbastanza", + "abbia", + "abbiamo", + "abbiano", + "abbiate", + "accidenti", + "ad", + "adesso", + "affinche", + "agl", + "agli", + "ahime", + "ahim\u00e8", + "ai", + "al", + "alcuna", + "alcuni", + "alcuno", + "all", + "alla", + "alle", + "allo", + "allora", + "altri", + "altrimenti", + "altro", + "altrove", + "altrui", + "anche", + "ancora", + "anni", + "anno", + "ansa", + "anticipo", + "assai", + "attesa", + "attraverso", + "avanti", + "avemmo", + "avendo", + "avente", + "aver", + "avere", + "averlo", + "avesse", + "avessero", + "avessi", + "avessimo", + "aveste", + "avesti", + "avete", + "aveva", + "avevamo", + "avevano", + "avevate", + "avevi", + "avevo", + "avrai", + "avranno", + "avrebbe", + "avrebbero", + "avrei", + "avremmo", + "avremo", + "avreste", + "avresti", + "avrete", + "avr\u00e0", + "avr\u00f2", + "avuta", + "avute", + "avuti", + "avuto", + "basta", + "bene", + "benissimo", + "berlusconi", + "brava", + "bravo", + "c", + "casa", + "caso", + "cento", + "certa", + "certe", + "certi", + "certo", + "che", + "chi", + "chicchessia", + "chiunque", + "ci", + "ciascuna", + "ciascuno", + "cima", + "cio", + "cioe", + "cio\u00e8", + "circa", + "citta", + "citt\u00e0", + "ci\u00f2", + "co", + "codesta", + "codesti", + "codesto", + "cogli", + "coi", + "col", + "colei", + "coll", + "coloro", + "colui", + "come", + "cominci", + "comunque", + "con", + "concernente", + "conciliarsi", + "conclusione", + "consiglio", + "contro", + "cortesia", + "cos", + "cosa", + "cosi", + "cos\u00ec", + "cui", + "d", + "da", + "dagl", + "dagli", + "dai", + "dal", + "dall", + "dalla", + "dalle", + "dallo", + "dappertutto", + "davanti", + "degl", + "degli", + "dei", + "del", + "dell", + "della", + "delle", + "dello", + "dentro", + "detto", + "deve", + "di", + "dice", + "dietro", + "dire", + "dirimpetto", + "diventa", + "diventare", + "diventato", + "dopo", + "dov", + "dove", + "dovra", + "dovr\u00e0", + "dovunque", + "due", + "dunque", + "durante", + "e", + "ebbe", + "ebbero", + "ebbi", + "ecc", + "ecco", + "ed", + "effettivamente", + "egli", + "ella", + "entrambi", + "eppure", + "era", + "erano", + "eravamo", + "eravate", + "eri", + "ero", + "esempio", + "esse", + "essendo", + "esser", + "essere", + "essi", + "ex", + "fa", + "faccia", + "facciamo", + "facciano", + "facciate", + "faccio", + "facemmo", + "facendo", + "facesse", + "facessero", + "facessi", + "facessimo", + "faceste", + "facesti", + "faceva", + "facevamo", + "facevano", + "facevate", + "facevi", + "facevo", + "fai", + "fanno", + "farai", + "faranno", + "fare", + "farebbe", + "farebbero", + "farei", + "faremmo", + "faremo", + "fareste", + "faresti", + "farete", + "far\u00e0", + "far\u00f2", + "fatto", + "favore", + "fece", + "fecero", + "feci", + "fin", + "finalmente", + "finche", + "fine", + "fino", + "forse", + "forza", + "fosse", + "fossero", + "fossi", + "fossimo", + "foste", + "fosti", + "fra", + "frattempo", + "fu", + "fui", + "fummo", + "fuori", + "furono", + "futuro", + "generale", + "gia", + "giacche", + "giorni", + "giorno", + "gi\u00e0", + "gli", + "gliela", + "gliele", + "glieli", + "glielo", + "gliene", + "governo", + "grande", + "grazie", + "gruppo", + "ha", + "haha", + "hai", + "hanno", + "ho", + "i", + "ieri", + "il", + "improvviso", + "in", + "inc", + "infatti", + "inoltre", + "insieme", + "intanto", + "intorno", + "invece", + "io", + "l", + "la", + "lasciato", + "lato", + "lavoro", + "le", + "lei", + "li", + "lo", + "lontano", + "loro", + "lui", + "lungo", + "luogo", + "l\u00e0", + "ma", + "macche", + "magari", + "maggior", + "mai", + "male", + "malgrado", + "malissimo", + "mancanza", + "marche", + "me", + "medesimo", + "mediante", + "meglio", + "meno", + "mentre", + "mesi", + "mezzo", + "mi", + "mia", + "mie", + "miei", + "mila", + "miliardi", + "milioni", + "minimi", + "ministro", + "mio", + "modo", + "molti", + "moltissimo", + "molto", + "momento", + "mondo", + "mosto", + "nazionale", + "ne", + "negl", + "negli", + "nei", + "nel", + "nell", + "nella", + "nelle", + "nello", + "nemmeno", + "neppure", + "nessun", + "nessuna", + "nessuno", + "niente", + "no", + "noi", + "non", + "nondimeno", + "nonostante", + "nonsia", + "nostra", + "nostre", + "nostri", + "nostro", + "novanta", + "nove", + "nulla", + "nuovo", + "o", + "od", + "oggi", + "ogni", + "ognuna", + "ognuno", + "oltre", + "oppure", + "ora", + "ore", + "osi", + "ossia", + "ottanta", + "otto", + "paese", + "parecchi", + "parecchie", + "parecchio", + "parte", + "partendo", + "peccato", + "peggio", + "per", + "perche", + "perch\u00e8", + "perch\u00e9", + "percio", + "perci\u00f2", + "perfino", + "pero", + "persino", + "persone", + "per\u00f2", + "piedi", + "pieno", + "piglia", + "piu", + "piuttosto", + "pi\u00f9", + "po", + "pochissimo", + "poco", + "poi", + "poiche", + "possa", + "possedere", + "posteriore", + "posto", + "potrebbe", + "preferibilmente", + "presa", + "press", + "prima", + "primo", + "principalmente", + "probabilmente", + "proprio", + "puo", + "pure", + "purtroppo", + "pu\u00f2", + "qualche", + "qualcosa", + "qualcuna", + "qualcuno", + "quale", + "quali", + "qualunque", + "quando", + "quanta", + "quante", + "quanti", + "quanto", + "quantunque", + "quasi", + "quattro", + "quel", + "quella", + "quelle", + "quelli", + "quello", + "quest", + "questa", + "queste", + "questi", + "questo", + "qui", + "quindi", + "realmente", + "recente", + "recentemente", + "registrazione", + "relativo", + "riecco", + "salvo", + "sara", + "sarai", + "saranno", + "sarebbe", + "sarebbero", + "sarei", + "saremmo", + "saremo", + "sareste", + "saresti", + "sarete", + "sar\u00e0", + "sar\u00f2", + "scola", + "scopo", + "scorso", + "se", + "secondo", + "seguente", + "seguito", + "sei", + "sembra", + "sembrare", + "sembrato", + "sembri", + "sempre", + "senza", + "sette", + "si", + "sia", + "siamo", + "siano", + "siate", + "siete", + "sig", + "solito", + "solo", + "soltanto", + "sono", + "sopra", + "sotto", + "spesso", + "srl", + "sta", + "stai", + "stando", + "stanno", + "starai", + "staranno", + "starebbe", + "starebbero", + "starei", + "staremmo", + "staremo", + "stareste", + "staresti", + "starete", + "star\u00e0", + "star\u00f2", + "stata", + "state", + "stati", + "stato", + "stava", + "stavamo", + "stavano", + "stavate", + "stavi", + "stavo", + "stemmo", + "stessa", + "stesse", + "stessero", + "stessi", + "stessimo", + "stesso", + "steste", + "stesti", + "stette", + "stettero", + "stetti", + "stia", + "stiamo", + "stiano", + "stiate", + "sto", + "su", + "sua", + "subito", + "successivamente", + "successivo", + "sue", + "sugl", + "sugli", + "sui", + "sul", + "sull", + "sulla", + "sulle", + "sullo", + "suo", + "suoi", + "tale", + "tali", + "talvolta", + "tanto", + "te", + "tempo", + "ti", + "titolo", + "torino", + "tra", + "tranne", + "tre", + "trenta", + "troppo", + "trovato", + "tu", + "tua", + "tue", + "tuo", + "tuoi", + "tutta", + "tuttavia", + "tutte", + "tutti", + "tutto", + "uguali", + "ulteriore", + "ultimo", + "un", + "una", + "uno", + "uomo", + "va", + "vale", + "vari", + "varia", + "varie", + "vario", + "verso", + "vi", + "via", + "vicino", + "visto", + "vita", + "voi", + "volta", + "volte", + "vostra", + "vostre", + "vostri", + "vostro", + "\u00e8", + ], + "ja": [ + "\u3042\u3063", + "\u3042\u308a", + "\u3042\u308b", + "\u3044", + "\u3044\u3046", + "\u3044\u308b", + "\u3046", + "\u3046\u3061", + "\u304a", + "\u304a\u3088\u3073", + "\u304a\u308a", + "\u304b", + "\u304b\u3064\u3066", + "\u304b\u3089", + "\u304c", + "\u304d", + "\u3053\u3053", + "\u3053\u3068", + "\u3053\u306e", + "\u3053\u308c", + "\u3053\u308c\u3089", + "\u3055", + "\u3055\u3089\u306b", + "\u3057", + "\u3057\u304b\u3057", + "\u3059\u308b", + "\u305a", + "\u305b", + "\u305b\u308b", + "\u305d\u3057\u3066", + "\u305d\u306e", + "\u305d\u306e\u4ed6", + "\u305d\u306e\u5f8c", + "\u305d\u308c", + 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"\uadf8\ub7ec\ub098", + "\uadf8\ub7ec\ub2c8", + "\uadf8\ub7ec\ub2c8\uae4c", + "\uadf8\ub7ec\uba74", + "\uadf8\ub7ec\ubbc0\ub85c", + "\uadf8\ub7ec\ud55c\uc989", + "\uadf8\ub7f0 \uae4c\ub2ed\uc5d0", + "\uadf8\ub7f0\ub370", + "\uadf8\ub7f0\uc989", + "\uadf8\ub7fc", + "\uadf8\ub7fc\uc5d0\ub3c4 \ubd88\uad6c\ud558\uace0", + "\uadf8\ub807\uac8c \ud568\uc73c\ub85c\uc368", + "\uadf8\ub807\uc9c0", + "\uadf8\ub807\uc9c0 \uc54a\ub2e4\uba74", + "\uadf8\ub807\uc9c0 \uc54a\uc73c\uba74", + "\uadf8\ub807\uc9c0\ub9cc", + "\uadf8\ub807\uc9c0\uc54a\uc73c\uba74", + "\uadf8\ub9ac\uace0", + "\uadf8\ub9ac\ud558\uc5ec", + "\uadf8\ub9cc\uc774\ub2e4", + "\uadf8\uc5d0 \ub530\ub974\ub294", + "\uadf8\uc704\uc5d0", + "\uadf8\uc800", + "\uadf8\uc911\uc5d0\uc11c", + "\uadf8\uce58\uc9c0 \uc54a\ub2e4", + "\uadfc\uac70\ub85c", + "\uadfc\uac70\ud558\uc5ec", + "\uae30\ub300\uc5ec", + "\uae30\uc810\uc73c\ub85c", + "\uae30\uc900\uc73c\ub85c", + "\uae30\ud0c0", + "\uae4c\ub2ed\uc73c\ub85c", + "\uae4c\uc545", + "\uae4c\uc9c0", 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"\ub354\ub77c\ub3c4", + "\ub354\ubd88\uc5b4", + "\ub354\uc6b1\ub354", + "\ub354\uc6b1\uc774\ub294", + "\ub3c4\ub2ec\ud558\ub2e4", + "\ub3c4\ucc29\ud558\ub2e4", + "\ub3d9\uc2dc\uc5d0", + "\ub3d9\uc548", + "\ub41c\ubc14\uc5d0\uc57c", + "\ub41c\uc774\uc0c1", + "\ub450\ubc88\uc9f8\ub85c", + "\ub458", + "\ub465\ub465", + "\ub4a4\ub530\ub77c", + "\ub4a4\uc774\uc5b4", + "\ub4e0\uac04\uc5d0", + "\ub4e4", + "\ub4f1", + "\ub4f1\ub4f1", + "\ub529\ub3d9", + "\ub530\ub77c", + "\ub530\ub77c\uc11c", + "\ub530\uc704", + "\ub530\uc9c0\uc9c0 \uc54a\ub2e4", + "\ub531", + "\ub54c", + "\ub54c\uac00 \ub418\uc5b4", + "\ub54c\ubb38\uc5d0", + "\ub610", + "\ub610\ud55c", + "\ub69d\ub69d", + "\ub77c \ud574\ub3c4", + "\ub839", + "\ub85c", + "\ub85c \uc778\ud558\uc5ec", + "\ub85c\ubd80\ud130", + "\ub85c\uc368", + "\ub959", + "\ub97c", + "\ub9c8\uc74c\ub300\ub85c", + "\ub9c8\uc800", + "\ub9c8\uc800\ub3c4", + "\ub9c8\uce58", + "\ub9c9\ub860\ud558\uace0", + "\ub9cc \ubabb\ud558\ub2e4", + "\ub9cc\uc57d", + "\ub9cc\uc57d\uc5d0", + "\ub9cc\uc740 \uc544\ub2c8\ub2e4", + "\ub9cc\uc774 \uc544\ub2c8\ub2e4", + "\ub9cc\uc77c", + "\ub9cc\ud07c", + "\ub9d0\ud558\uc790\uba74", + "\ub9d0\ud560\uac83\ub3c4 \uc5c6\uace0", + "\ub9e4", + "\ub9e4\ubc88", + "\uba54\uc4f0\uac81\ub2e4", + "\uba87", + "\ubaa8", + "\ubaa8\ub450", + "\ubb34\ub835", + "\ubb34\ub98e\uc4f0\uace0", + "\ubb34\uc2a8", + "\ubb34\uc5c7", + "\ubb34\uc5c7\ub54c\ubb38\uc5d0", + "\ubb3c\ub860", + "\ubc0f", + "\ubc14\uafb8\uc5b4\ub9d0\ud558\uba74", + "\ubc14\uafb8\uc5b4\ub9d0\ud558\uc790\uba74", + "\ubc14\uafb8\uc5b4\uc11c \ub9d0\ud558\uba74", + "\ubc14\uafb8\uc5b4\uc11c \ud55c\ub2e4\uba74", + "\ubc14\uafd4 \ub9d0\ud558\uba74", + "\ubc14\ub85c", + "\ubc14\uc640\uac19\uc774", + "\ubc16\uc5d0 \uc548\ub41c\ub2e4", + "\ubc18\ub300\ub85c", + "\ubc18\ub300\ub85c \ub9d0\ud558\uc790\uba74", + "\ubc18\ub4dc\uc2dc", + "\ubc84\uae08", + "\ubcf4\ub294\ub370\uc11c", + "\ubcf4\ub2e4\ub354", + "\ubcf4\ub4dc\ub4dd", + "\ubcf8\ub300\ub85c", + "\ubd10", + "\ubd10\ub77c", + "\ubd80\ub958\uc758 \uc0ac\ub78c\ub4e4", + "\ubd80\ud130", + "\ubd88\uad6c\ud558\uace0", + "\ubd88\ubb38\ud558\uace0", + "\ubd95\ubd95", + "\ube44\uac71\uac70\ub9ac\ub2e4", + "\ube44\uad50\uc801", + "\ube44\uae38\uc218 \uc5c6\ub2e4", + "\ube44\ub85c\uc18c", + "\ube44\ub85d", + "\ube44\uc2b7\ud558\ub2e4", + "\ube44\ucd94\uc5b4 \ubcf4\uc544", + "\ube44\ud558\uba74", + "\ubfd0\ub9cc \uc544\ub2c8\ub77c", + "\ubfd0\ub9cc\uc544\ub2c8\ub77c", + "\ubfd0\uc774\ub2e4", + "\uc090\uac71", + "\uc090\uac71\uac70\ub9ac\ub2e4", + "\uc0ac", + "\uc0bc", + "\uc0c1\ub300\uc801\uc73c\ub85c \ub9d0\ud558\uc790\uba74", + "\uc0dd\uac01\ud55c\ub300\ub85c", + "\uc124\ub839", + "\uc124\ub9c8", + "\uc124\uc0ac", + "\uc14b", + "\uc18c\uc0dd", + "\uc18c\uc778", + "\uc1a8", + "\uc27f", + "\uc2b5\ub2c8\uae4c", + "\uc2b5\ub2c8\ub2e4", + "\uc2dc\uac01", + "\uc2dc\uac04", + "\uc2dc\uc791\ud558\uc5ec", + "\uc2dc\ucd08\uc5d0", + "\uc2dc\ud0a4\ub2e4", + "\uc2e4\ub85c", + "\uc2ec\uc9c0\uc5b4", + "\uc544", + "\uc544\ub2c8", + "\uc544\ub2c8\ub098\ub2e4\ub97c\uac00", + "\uc544\ub2c8\ub77c\uba74", + "\uc544\ub2c8\uba74", + "\uc544\ub2c8\uc5c8\ub2e4\uba74", + "\uc544\ub798\uc717", + "\uc544\ubb34\uac70\ub098", + "\uc544\ubb34\ub3c4", + "\uc544\uc57c", + "\uc544\uc6b8\ub7ec", + "\uc544\uc774", + "\uc544\uc774\uace0", + "\uc544\uc774\uad6c", + "\uc544\uc774\uc57c", + "\uc544\uc774\ucfe0", + "\uc544\ud558", + "\uc544\ud649", + "\uc548 \uadf8\ub7ec\uba74", + "\uc54a\uae30 \uc704\ud558\uc5ec", + "\uc54a\uae30 \uc704\ud574\uc11c", + "\uc54c \uc218 \uc788\ub2e4", + "\uc54c\uc558\uc5b4", + "\uc557", + "\uc55e\uc5d0\uc11c", + "\uc55e\uc758\uac83", + "\uc57c", + "\uc57d\uac04", + "\uc591\uc790", + "\uc5b4", + "\uc5b4\uae30\uc5ec\ucc28", + "\uc5b4\ub290", + "\uc5b4\ub290 \ub144\ub3c4", + "\uc5b4\ub290\uac83", + "\uc5b4\ub290\uacf3", + "\uc5b4\ub290\ub54c", + "\uc5b4\ub290\ucabd", + "\uc5b4\ub290\ud574", + "\uc5b4\ub514", + "\uc5b4\ub54c", + "\uc5b4\ub5a0\ud55c", + "\uc5b4\ub5a4", + "\uc5b4\ub5a4\uac83", + "\uc5b4\ub5a4\uac83\ub4e4", + "\uc5b4\ub5bb\uac8c", + "\uc5b4\ub5bb\ud574", + "\uc5b4\uc774", + "\uc5b4\uc9f8\uc11c", + "\uc5b4\uca0b\ub4e0", + "\uc5b4\uca54\uc218 \uc5c6\ub2e4", + "\uc5b4\ucc0c", + "\uc5b4\ucc0c\ub40f\ub4e0", + "\uc5b4\ucc0c\ub40f\uc5b4", + "\uc5b4\ucc0c\ud558\ub4e0\uc9c0", + "\uc5b4\ucc0c\ud558\uc5ec", + "\uc5b8\uc81c", + "\uc5b8\uc820\uac00", + "\uc5bc\ub9c8", + "\uc5bc\ub9c8 \uc548 \ub418\ub294 \uac83", + "\uc5bc\ub9c8\uac04", + "\uc5bc\ub9c8\ub098", + "\uc5bc\ub9c8\ub4e0\uc9c0", + "\uc5bc\ub9c8\ub9cc\ud07c", + "\uc5bc\ub9c8\ud07c", + "\uc5c9\uc5c9", + "\uc5d0", + "\uc5d0 \uac00\uc11c", + "\uc5d0 \ub2ec\ub824 \uc788\ub2e4", + "\uc5d0 \ub300\ud574", + "\uc5d0 \uc788\ub2e4", + "\uc5d0 \ud55c\ud558\ub2e4", + "\uc5d0\uac8c", + "\uc5d0\uc11c", + "\uc5ec", + "\uc5ec\uae30", + "\uc5ec\ub35f", + "\uc5ec\ub7ec\ubd84", + "\uc5ec\ubcf4\uc2dc\uc624", + "\uc5ec\ubd80", + "\uc5ec\uc12f", + "\uc5ec\uc804\ud788", + "\uc5ec\ucc28", + "\uc5f0\uad00\ub418\ub2e4", + "\uc5f0\uc774\uc11c", + "\uc601", + "\uc601\ucc28", + "\uc606\uc0ac\ub78c", + "\uc608", + "\uc608\ub97c \ub4e4\uba74", + "\uc608\ub97c \ub4e4\uc790\uba74", + "\uc608\ucee8\ub300", + "\uc608\ud558\uba74", + "\uc624", + "\uc624\ub85c\uc9c0", + "\uc624\ub974\ub2e4", + "\uc624\uc790\ub9c8\uc790", + "\uc624\uc9c1", + "\uc624\ud638", + "\uc624\ud788\ub824", + "\uc640", + "\uc640 \uac19\uc740 \uc0ac\ub78c\ub4e4", + "\uc640\ub974\ub974", + "\uc640\uc544", + "\uc65c", + "\uc65c\ub0d0\ud558\uba74", + "\uc678\uc5d0\ub3c4", + "\uc694\ub9cc\ud07c", + "\uc694\ub9cc\ud55c \uac83", + "\uc694\ub9cc\ud55c\uac78", + "\uc694\ucee8\ub300", + "\uc6b0\ub974\ub974", + "\uc6b0\ub9ac", + "\uc6b0\ub9ac\ub4e4", + "\uc6b0\uc120", + "\uc6b0\uc5d0 \uc885\ud569\ud55c\uac83\uacfc\uac19\uc774", + "\uc6b4\uc6b4", + "\uc6d4", + "\uc704\uc5d0\uc11c \uc11c\uc220\ud55c\ubc14\uc640\uac19\uc774", + "\uc704\ud558\uc5ec", + "\uc704\ud574\uc11c", + "\uc719\uc719", + "\uc721", + "\uc73c\ub85c", + "\uc73c\ub85c \uc778\ud558\uc5ec", + "\uc73c\ub85c\uc11c", + "\uc73c\ub85c\uc368", + "\uc744", + "\uc751", + "\uc751\ub2f9", + "\uc758", + "\uc758\uac70\ud558\uc5ec", + "\uc758\uc9c0\ud558\uc5ec", + "\uc758\ud574", + "\uc758\ud574\ub418\ub2e4", + "\uc758\ud574\uc11c", + "\uc774", + "\uc774 \ub418\ub2e4", + "\uc774 \ub54c\ubb38\uc5d0", + "\uc774 \ubc16\uc5d0", + "\uc774 \uc678\uc5d0", + "\uc774 \uc815\ub3c4\uc758", + "\uc774\uac83", + "\uc774\uacf3", + "\uc774\ub54c", + "\uc774\ub77c\uba74", + "\uc774\ub798", + "\uc774\ub7ec\uc774\ub7ec\ud558\ub2e4", + "\uc774\ub7ec\ud55c", + "\uc774\ub7f0", + "\uc774\ub7f4\uc815\ub3c4\ub85c", + "\uc774\ub807\uac8c \ub9ce\uc740 \uac83", + "\uc774\ub807\uac8c\ub418\uba74", + "\uc774\ub807\uac8c\ub9d0\ud558\uc790\uba74", + "\uc774\ub807\uad6c\ub098", + "\uc774\ub85c \uc778\ud558\uc5ec", + "\uc774\ub974\uae30\uae4c\uc9c0", + "\uc774\ub9ac\ud558\uc5ec", + "\uc774\ub9cc\ud07c", + "\uc774\ubc88", + "\uc774\ubd10", + "\uc774\uc0c1", + "\uc774\uc5b4\uc11c", + "\uc774\uc5c8\ub2e4", + "\uc774\uc640 \uac19\ub2e4", + "\uc774\uc640 \uac19\uc740", + "\uc774\uc640 \ubc18\ub300\ub85c", + "\uc774\uc640\uac19\ub2e4\uba74", + "\uc774\uc678\uc5d0\ub3c4", + "\uc774\uc6a9\ud558\uc5ec", + "\uc774\uc720\ub9cc\uc73c\ub85c", + "\uc774\uc820", + "\uc774\uc9c0\ub9cc", + "\uc774\ucabd", + "\uc774\ucc9c\uad6c", + "\uc774\ucc9c\uc721", + "\uc774\ucc9c\uce60", + "\uc774\ucc9c\ud314", + "\uc778 \ub4ef\ud558\ub2e4", + "\uc778\uc820", + "\uc77c", + "\uc77c\uac83\uc774\ub2e4", + "\uc77c\uacf1", + "\uc77c\ub2e8", + "\uc77c\ub54c", + "\uc77c\ubc18\uc801\uc73c\ub85c", + "\uc77c\uc9c0\ub77c\ub3c4", + "\uc784\uc5d0 \ud2c0\ub9bc\uc5c6\ub2e4", + "\uc785\uac01\ud558\uc5ec", + "\uc785\uc7a5\uc5d0\uc11c", + "\uc787\ub530\ub77c", + "\uc788\ub2e4", + "\uc790", + "\uc790\uae30", + "\uc790\uae30\uc9d1", + "\uc790\ub9c8\uc790", + "\uc790\uc2e0", + "\uc7a0\uae50", + "\uc7a0\uc2dc", + "\uc800", + "\uc800\uac83", + "\uc800\uac83\ub9cc\ud07c", + "\uc800\uae30", + "\uc800\ucabd", + "\uc800\ud76c", + "\uc804\ubd80", + "\uc804\uc790", + "\uc804\ud6c4", + "\uc810\uc5d0\uc11c \ubcf4\uc544", + "\uc815\ub3c4\uc5d0 \uc774\ub974\ub2e4", + "\uc81c", + "\uc81c\uac01\uae30", + "\uc81c\uc678\ud558\uace0", + "\uc870\uae08", + "\uc870\ucc28", + "\uc870\ucc28\ub3c4", + "\uc878\uc878", + "\uc880", + "\uc88b\uc544", + "\uc88d\uc88d", + "\uc8fc\ub8e9\uc8fc\ub8e9", + "\uc8fc\uc800\ud558\uc9c0 \uc54a\uace0", + "\uc904\uc740 \ubab0\ub78f\ub2e4", + "\uc904\uc740\ubaa8\ub978\ub2e4", + "\uc911\uc5d0\uc11c", + "\uc911\uc758\ud558\ub098", + "\uc988\uc74c\ud558\uc5ec", + "\uc989", + "\uc989\uc2dc", + "\uc9c0\ub4e0\uc9c0", + "\uc9c0\ub9cc", + "\uc9c0\ub9d0\uace0", + "\uc9c4\uc9dc\ub85c", + "\ucabd\uc73c\ub85c", + "\ucc28\ub77c\ub9ac", + "\ucc38", + "\ucc38\ub098", + "\uccab\ubc88\uc9f8\ub85c", + "\uccc7", + "\ucd1d\uc801\uc73c\ub85c", + "\ucd1d\uc801\uc73c\ub85c \ub9d0\ud558\uba74", + "\ucd1d\uc801\uc73c\ub85c \ubcf4\uba74", + "\uce60", + "\ucf78\ucf78", + "\ucf85\ucf85", + "\ucff5", + "\ud0c0\ub2e4", + "\ud0c0\uc778", + "\ud0d5\ud0d5", + "\ud1a0\ud558\ub2e4", + "\ud1b5\ud558\uc5ec", + "\ud22d", + "\ud264", + "\ud2c8\ud0c0", + "\ud30d", + "\ud314", + "\ud37d", + "\ud384\ub801", + "\ud558", + "\ud558\uac8c\ub420\uac83\uc774\ub2e4", + "\ud558\uac8c\ud558\ub2e4", + "\ud558\uaca0\ub294\uac00", + "\ud558\uace0 \uc788\ub2e4", + "\ud558\uace0\uc788\uc5c8\ub2e4", + "\ud558\uace4\ud558\uc600\ub2e4", + "\ud558\uad6c\ub098", + "\ud558\uae30 \ub54c\ubb38\uc5d0", + "\ud558\uae30 \uc704\ud558\uc5ec", + "\ud558\uae30\ub294\ud55c\ub370", + "\ud558\uae30\ub9cc \ud558\uba74", + "\ud558\uae30\ubcf4\ub2e4\ub294", + "\ud558\uae30\uc5d0", + "\ud558\ub098", + "\ud558\ub290\ub2c8", + "\ud558\ub294 \uae40\uc5d0", + "\ud558\ub294 \ud3b8\uc774 \ub0ab\ub2e4", + "\ud558\ub294\uac83\ub3c4", + "\ud558\ub294\uac83\ub9cc \ubabb\ud558\ub2e4", + "\ud558\ub294\uac83\uc774 \ub0ab\ub2e4", + "\ud558\ub294\ubc14", + "\ud558\ub354\ub77c\ub3c4", + "\ud558\ub3c4\ub2e4", + "\ud558\ub3c4\ub85d\uc2dc\ud0a4\ub2e4", + "\ud558\ub3c4\ub85d\ud558\ub2e4", + "\ud558\ub4e0\uc9c0", + "\ud558\ub824\uace0\ud558\ub2e4", + "\ud558\ub9c8\ud130\uba74", + "\ud558\uba74 \ud560\uc218\ub85d", + "\ud558\uba74\ub41c\ub2e4", + "\ud558\uba74\uc11c", + "\ud558\ubb3c\uba70", + "\ud558\uc5ec\uae08", + "\ud558\uc5ec\uc57c", + "\ud558\uc790\ub9c8\uc790", + "\ud558\uc9c0 \uc54a\ub294\ub2e4\uba74", + "\ud558\uc9c0 \uc54a\ub3c4\ub85d", + "\ud558\uc9c0\ub9c8", + "\ud558\uc9c0\ub9c8\ub77c", + "\ud558\uc9c0\ub9cc", + "\ud558\ud558", + "\ud55c \uae4c\ub2ed\uc5d0", + "\ud55c \uc774\uc720\ub294", + "\ud55c \ud6c4", + "\ud55c\ub2e4\uba74", + "\ud55c\ub2e4\uba74 \ubab0\ub77c\ub3c4", + "\ud55c\ub370", + "\ud55c\ub9c8\ub514", + "\ud55c\uc801\uc774\uc788\ub2e4", + "\ud55c\ucf20\uc73c\ub85c\ub294", + "\ud55c\ud56d\ubaa9", + "\ud560 \ub530\ub984\uc774\ub2e4", + "\ud560 \uc0dd\uac01\uc774\ub2e4", + "\ud560 \uc904 \uc548\ub2e4", + "\ud560 \uc9c0\uacbd\uc774\ub2e4", + "\ud560 \ud798\uc774 \uc788\ub2e4", + "\ud560\ub54c", + "\ud560\ub9cc\ud558\ub2e4", + "\ud560\ub9dd\uc815", + "\ud560\ubfd0", + "\ud560\uc218\uc788\ub2e4", + "\ud560\uc218\uc788\uc5b4", + "\ud560\uc904\uc54c\ub2e4", + "\ud560\uc9c0\ub77c\ub3c4", + "\ud560\uc9c0\uc5b8\uc815", + "\ud568\uaed8", + "\ud574\ub3c4\ub41c\ub2e4", + "\ud574\ub3c4\uc88b\ub2e4", + "\ud574\ubd10\uc694", + "\ud574\uc11c\ub294 \uc548\ub41c\ub2e4", + "\ud574\uc57c\ud55c\ub2e4", + "\ud574\uc694", + "\ud588\uc5b4\uc694", + "\ud5a5\ud558\ub2e4", + "\ud5a5\ud558\uc5ec", + "\ud5a5\ud574\uc11c", + "\ud5c8", + "\ud5c8\uac71", + "\ud5c8\ud5c8", + "\ud5c9", + "\ud5c9\ud5c9", + "\ud5d0\ub5a1\ud5d0\ub5a1", + "\ud615\uc2dd\uc73c\ub85c \uc4f0\uc5ec", + "\ud639\uc2dc", + "\ud639\uc740", + "\ud63c\uc790", + "\ud6e8\uc52c", + "\ud718\uc775", + "\ud734", + "\ud750\ud750", + "\ud765", + "\ud798\uc785\uc5b4", + "\ufe3f", + "\uff01", + "\uff03", + "\uff04", + "\uff05", + "\uff06", + "\uff08", + "\uff09", + "\uff0a", + "\uff0b", + "\uff0c", + "\uff10", + "\uff11", + "\uff12", + "\uff13", + "\uff14", + "\uff15", + "\uff16", + "\uff17", + "\uff18", + "\uff19", + "\uff1a", + "\uff1b", + "\uff1c", + "\uff1e", + "\uff1f", + "\uff20", + "\uff3b", + "\uff3d", + "\uff5b", + "\uff5c", + "\uff5d", + "\uff5e", + "\uffe5", + ], + "la": [ + "a", + "ab", + "ac", + "ad", + "at", + "atque", + "aut", + "autem", + "cum", + "de", + "dum", + "e", + "erant", + "erat", + "est", + "et", + "etiam", + "ex", + "haec", + "hic", + "hoc", + "in", + "ita", + "me", + "nec", + "neque", + "non", + "per", + "qua", + "quae", + "quam", + "qui", + "quibus", + "quidem", + "quo", + "quod", + "re", + "rebus", + "rem", + "res", + "sed", + "si", + "sic", + "sunt", + "tamen", + "tandem", + "te", + "ut", + "vel", + ], + "lv": [ + "aiz", + "ap", + "apak\u0161", + "apak\u0161pus", + "ar", + "ar\u012b", + "aug\u0161pus", + "bet", + "bez", + "bija", + "biji", + "biju", + "bij\u0101m", + "bij\u0101t", + "b\u016bs", + "b\u016bsi", + "b\u016bsiet", + "b\u016bsim", + "b\u016bt", + "b\u016b\u0161u", + "caur", + "diem\u017e\u0113l", + "diezin", + "dro\u0161i", + "d\u0113\u013c", + "esam", + "esat", + "esi", + "esmu", + "gan", + "gar", + "iekam", + "iekams", + "iek\u0101m", + "iek\u0101ms", + "iek\u0161", + "iek\u0161pus", + "ik", + "ir", + "it", + "itin", + "iz", + "ja", + "jau", + "jeb", + "jeb\u0161u", + "jel", + "jo", + "j\u0101", + "ka", + "kam\u0113r", + "kaut", + "kol\u012bdz", + "kop\u0161", + "k\u0101", + "k\u013cuva", + "k\u013cuvi", + "k\u013cuvu", + "k\u013cuv\u0101m", + "k\u013cuv\u0101t", + "k\u013c\u016bs", + "k\u013c\u016bsi", + "k\u013c\u016bsiet", + "k\u013c\u016bsim", + "k\u013c\u016bst", + "k\u013c\u016bstam", + "k\u013c\u016bstat", + "k\u013c\u016bsti", + "k\u013c\u016bstu", + "k\u013c\u016bt", + "k\u013c\u016b\u0161u", + "labad", + "lai", + "lejpus", + "l\u012bdz", + "l\u012bdzko", + "ne", + "neb\u016bt", + "nedz", + "nek\u0101", + "nevis", + "nezin", + "no", + "nu", + "n\u0113", + "otrpus", + "pa", + "par", + "pat", + "pie", + "pirms", + 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"inderdaad", + "intussen", + "is", + "ja", + "je", + "jij", + "jijzelf", + "jou", + "jouw", + "jullie", + "kan", + "kon", + "konden", + "kun", + "kunnen", + "kunt", + "laatst", + "later", + "lijken", + "lijkt", + "maak", + "maakt", + "maakte", + "maakten", + "maar", + "mag", + "maken", + "me", + "meer", + "meest", + "meestal", + "men", + "met", + "mevr", + "mij", + "mijn", + "minder", + "miss", + "misschien", + "missen", + "mits", + "mocht", + "mochten", + "moest", + "moesten", + "moet", + "moeten", + "mogen", + "mr", + "mrs", + "mw", + "na", + "naar", + "nam", + "namelijk", + "nee", + "neem", + "negen", + "nemen", + "nergens", + "niemand", + "niet", + "niets", + "niks", + "noch", + "nochtans", + "nog", + "nooit", + "nu", + "nv", + "of", + "om", + "omdat", + "ondanks", + "onder", + "ondertussen", + "ons", + "onze", + "onzeker", + "ooit", + "ook", + "op", + "over", + "overal", + "overige", + "paar", + "per", + "recent", + "redelijk", + "samen", + "sinds", + "steeds", + "te", + "tegen", 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"blitt", + "b\u00e5de", + "b\u00e5e", + "da", + "de", + "deg", + "dei", + "deim", + "deira", + "deires", + "dem", + "den", + "denne", + "der", + "dere", + "deres", + "det", + "dette", + "di", + "din", + "disse", + "ditt", + "du", + "dykk", + "dykkar", + "d\u00e5", + "eg", + "ein", + "eit", + "eitt", + "eller", + "elles", + "en", + "enn", + "er", + "et", + "ett", + "etter", + "for", + "fordi", + "fra", + "f\u00f8r", + "ha", + "hadde", + "han", + "hans", + "har", + "hennar", + "henne", + "hennes", + "her", + "hj\u00e5", + "ho", + "hoe", + "honom", + "hoss", + "hossen", + "hun", + "hva", + "hvem", + "hver", + "hvilke", + "hvilken", + "hvis", + "hvor", + "hvordan", + "hvorfor", + "i", + "ikke", + "ikkje", + "ingen", + "ingi", + "inkje", + "inn", + "inni", + "ja", + "jeg", + "kan", + "kom", + "korleis", + "korso", + "kun", + "kunne", + "kva", + "kvar", + "kvarhelst", + "kven", + "kvi", + "kvifor", + "man", + "mange", + "me", + "med", + "medan", + "meg", + "meget", + "mellom", + "men", + "mi", + "min", + "mine", + "mitt", + "mot", + "mykje", + "ned", + "no", + "noe", + "noen", + "noka", + "noko", + "nokon", + "nokor", + "nokre", + "n\u00e5", + "n\u00e5r", + "og", + "ogs\u00e5", + "om", + "opp", + "oss", + "over", + "p\u00e5", + "samme", + "seg", + "selv", + "si", + "sia", + "sidan", + "siden", + "sin", + "sine", + "sitt", + "sj\u00f8l", + "skal", + "skulle", + "slik", + "so", + "som", + "somme", + "somt", + "s\u00e5", + "s\u00e5nn", + "til", + "um", + "upp", + "ut", + "uten", + "var", + "vart", + "varte", + "ved", + "vere", + "verte", + "vi", + "vil", + "ville", + "vore", + "vors", + "vort", + "v\u00e5r", + "v\u00e6re", + "v\u00e6rt", + "\u00e5", + ], + "pl": [ + "aby", + "ach", + "aj", + "albo", + "ale", + "ani", + "a\u017c", + "bardzo", + "bez", + "bo", + "bowiem", + "by", + "byli", + "bym", + "by\u0107", + "by\u0142", + "by\u0142a", + "by\u0142o", + "by\u0142y", + "b\u0119dzie", + "b\u0119d\u0105", + "chce", + "cho\u0107", + "ci", + "ciebie", + "ci\u0119", + "co", + "coraz", + "co\u015b", + "czy", + "czyli", + "cz\u0119sto", + "daleko", + "dla", + "dlaczego", + "dlatego", + "do", + "dobrze", + "dok\u0105d", + "do\u015b\u0107", + "dr", + "du\u017co", + "dwa", + "dwaj", + "dwie", + "dwoje", + "dzisiaj", + "dzi\u015b", + "gdy", + "gdyby", + "gdy\u017c", + "gdzie", + "go", + "godz", + "hab", + "i", + "ich", + "ii", + "iii", + "ile", + "im", + "inne", + "inny", + "in\u017c", + "iv", + "ix", + "i\u017c", + "ja", + "jak", + "jakby", + "jaki", + "jakie", + "jako", + "je", + "jeden", + "jedna", + "jednak", + "jedno", + "jednym", + "jedynie", + "jego", + "jej", + "jemu", + "jest", + "jestem", + "jeszcze", + "je\u015bli", + "je\u017celi", + "ju\u017c", + "j\u0105", + "ka\u017cdy", + "kiedy", + "kierunku", + "kilku", + "kto", + "kt\u00f3ra", + "kt\u00f3re", + "kt\u00f3rego", + "kt\u00f3rej", + "kt\u00f3ry", + "kt\u00f3rych", + "kt\u00f3rym", + "kt\u00f3rzy", + "ku", + "lat", + "lecz", + "lub", + "ma", + "maj\u0105", + "mam", + "mamy", + "mgr", + "mi", + "mia\u0142", + "mimo", + "mnie", + "mn\u0105", + "mog\u0105", + "moi", + "moja", + "moje", + "mo\u017ce", + "mo\u017cna", + "mu", + "musi", + "my", + "m\u00f3j", + "na", + "nad", + "nam", + "nami", + "nas", + "nasi", + "nasz", + "nasza", + "nasze", + "natychmiast", + "nawet", + "nic", + "nich", + "nie", + "niego", + "niej", + "niemu", + "nigdy", + "nim", + "nimi", + "ni\u0105", + "ni\u017c", + "no", + "nowe", + "np", + "nr", + "o", + "o.o.", + "obok", + "od", + "ok", + "oko\u0142o", + "on", + "ona", + "one", + "oni", + "ono", + "oraz", + "owszem", + "pan", + "pl", + "po", + "pod", + "ponad", + "poniewa\u017c", + "poza", + "prof", + "przed", + "przede", + "przedtem", + "przez", + "przy", + "raz", + "razie", + "roku", + "r\u00f3wnie\u017c", + "sam", + "sama", + "si\u0119", + "sk\u0105d", + "sobie", + "spos\u00f3b", + "swoje", + "s\u0105", + "ta", + "tak", + "taki", + "takich", + "takie", + "tak\u017ce", + "tam", + "te", + "tego", + "tej", + "tel", + "temu", + "ten", + "teraz", + "te\u017c", + "to", + "tobie", + "tob\u0105", + "trzeba", + "tu", + "tutaj", + "twoi", + "twoja", + "twoje", + "tw\u00f3j", + "ty", + "tych", + "tylko", + "tym", + "tys", + "tzw", + "t\u0119", + "u", + "ul", + "vi", + "vii", + "viii", + "vol", + "w", + "wam", + "wami", + "was", + "wasi", + "wasz", + "wasza", + "wasze", + "we", + "wie", + "wi\u0119c", + "wszystko", + "wtedy", + "www", + "wy", + "w\u0142a\u015bnie", + "w\u015br\u00f3d", + "xi", + "xii", + "xiii", + "xiv", + "xv", + "z", + "za", + "zawsze", + "za\u015b", + "ze", + "z\u0142", + "\u017caden", + "\u017ce", + "\u017ceby", + ], + "pt": [ + "a", + "acerca", + "adeus", + "agora", + "ainda", + "algmas", + "algo", + "algumas", + "alguns", + "ali", + "al\u00e9m", + "ambos", + "ano", + "anos", + "antes", + "ao", + "aos", + "apenas", + "apoio", + "apontar", + "ap\u00f3s", + "aquela", + "aquelas", + "aquele", + "aqueles", + "aqui", + "aquilo", + "as", + "assim", + "atrav\u00e9s", + "atr\u00e1s", + "at\u00e9", + "a\u00ed", + "baixo", + "bastante", + "bem", + "bom", + "breve", + "cada", + "caminho", + "catorze", + "cedo", + "cento", + "certamente", + "certeza", + "cima", + "cinco", + "coisa", + "com", + "como", + "comprido", + "conhecido", + "conselho", + "contra", + "corrente", + "custa", + "c\u00e1", + "da", + "daquela", + "daquele", + "dar", + "das", + "de", + "debaixo", + "demais", + "dentro", + "depois", + "desde", + "desligado", + "dessa", + "desse", + "desta", + "deste", + "deve", + "devem", + "dever\u00e1", + "dez", + "dezanove", + "dezasseis", + "dezassete", + "dezoito", + "dia", + "diante", + "direita", + "diz", + "dizem", + "dizer", + "do", + "dois", + "dos", + "doze", + "duas", + "d\u00e1", + "d\u00e3o", + "d\u00favida", + "e", + "ela", + "elas", + "ele", + "eles", + "em", + "embora", + "enquanto", + "entre", + "ent\u00e3o", + "era", + "essa", + "essas", + "esse", + "esses", + "esta", + "estado", + "estar", + "estar\u00e1", + "estas", + "estava", + "este", + "estes", + "esteve", + "estive", + "estivemos", + "estiveram", + "estiveste", + "estivestes", + "estou", + "est\u00e1", + "est\u00e1s", + "est\u00e3o", + "eu", + "exemplo", + "falta", + "far\u00e1", + "favor", + "faz", + "fazeis", + "fazem", + "fazemos", + "fazer", + "fazes", + "fazia", + "fa\u00e7o", + "fez", + "fim", + "final", + "foi", + "fomos", + "for", + "fora", + "foram", + "forma", + "foste", + "fostes", + "fui", + "geral", + "grande", + "grandes", + "grupo", + "hoje", + "horas", + "h\u00e1", + "iniciar", + "inicio", + "ir", + "ir\u00e1", + "isso", + "ista", + "iste", + "isto", + "j\u00e1", + "lado", + "ligado", + "local", + "logo", + "longe", + "lugar", + "l\u00e1", + "maior", + "maioria", + "maiorias", + "mais", + "mal", + "mas", + "me", + "meio", + "menor", + "menos", + "meses", + "mesmo", + "meu", + "meus", + "mil", + "minha", + "minhas", + "momento", + "muito", + "muitos", + "m\u00e1ximo", + "m\u00eas", + "na", + "nada", + "naquela", + "naquele", + "nas", + "nem", + "nenhuma", + "nessa", + "nesse", + "nesta", + "neste", + "no", + "noite", + "nome", + "nos", + "nossa", + "nossas", + "nosso", + "nossos", + "nova", + "nove", + "novo", + "novos", + "num", + "numa", + "nunca", + "n\u00e3o", + "n\u00edvel", + "n\u00f3s", + "n\u00famero", + "o", + "obra", + "obrigada", + "obrigado", + "oitava", + "oitavo", + "oito", + "onde", + "ontem", + "onze", + "os", + "ou", + "outra", + "outras", + "outro", + "outros", + "para", + "parece", + "parte", + "partir", + "pegar", + "pela", + "pelas", + "pelo", + "pelos", + "perto", + "pessoas", + "pode", + "podem", + "poder", + "poder\u00e1", + "podia", + "ponto", + "pontos", + "por", + "porque", + "porqu\u00ea", + "posi\u00e7\u00e3o", + "possivelmente", + "posso", + "poss\u00edvel", + "pouca", + "pouco", + "povo", + "primeira", + "primeiro", + "promeiro", + "pr\u00f3prio", + "pr\u00f3ximo", + "puderam", + "p\u00f4de", + "p\u00f5e", + "p\u00f5em", + "qual", + "qualquer", + "quando", + "quanto", + "quarta", + "quarto", + "quatro", + "que", + "quem", + "quer", + "quero", + "quest\u00e3o", + "quieto", + "quinta", + "quinto", + "quinze", + "qu\u00ea", + "rela\u00e7\u00e3o", + "sabe", + "saber", + "se", + "segunda", + "segundo", + "sei", + "seis", + "sem", + "sempre", + "ser", + "seria", + "sete", + "seu", + "seus", + "sexta", + "sexto", + "sim", + "sistema", + "sob", + "sobre", + "sois", + "somente", + "somos", + "sou", + "sua", + "suas", + "s\u00e3o", + "s\u00e9tima", + "s\u00e9timo", + "tal", + "talvez", + "tamb\u00e9m", + "tanto", + "tarde", + "te", + "tem", + "temos", + "tempo", + "tendes", + "tenho", + "tens", + "tentar", + "tentaram", + "tente", + "tentei", + "ter", + "terceira", + "terceiro", + "teu", + "teus", + "teve", + "tipo", + "tive", + "tivemos", + "tiveram", + "tiveste", + "tivestes", + "toda", + "todas", + "todo", + "todos", + "trabalhar", + "trabalho", + "treze", + "tr\u00eas", + "tu", + "tua", + "tuas", + "tudo", + "t\u00e3o", + "t\u00eam", + "um", + "uma", + "umas", + "uns", + "usa", + "usar", + "vai", + "vais", + "valor", + "veja", + "vem", + "vens", + "ver", + "verdade", + "verdadeiro", + "vez", + "vezes", + "viagem", + "vindo", + "vinte", + "voc\u00ea", + "voc\u00eas", + "vos", + "vossa", + "vossas", + "vosso", + "vossos", + "v\u00e1rios", + "v\u00e3o", + "v\u00eam", + "v\u00f3s", + "zero", + "\u00e0", + "\u00e0s", + "\u00e1rea", + "\u00e9", + "\u00e9s", + "\u00faltimo", + ], + "ro": [ + "acea", + "aceasta", + "aceast\u0103", + "aceea", + "acei", + "aceia", + "acel", + "acela", + "acele", + "acelea", + "acest", + "acesta", + "aceste", + "acestea", + "ace\u015fti", + "ace\u015ftia", + "acolo", + "acord", + "acum", + "ai", + "aia", + "aib\u0103", + "aici", + "al", + "ale", + "alea", + "altceva", + "altcineva", + "am", + "ar", + "are", + "asemenea", + "asta", + "astea", + "ast\u0103zi", + "asupra", + "au", + "avea", + "avem", + "ave\u0163i", + "azi", + "a\u015f", + "a\u015fadar", + "a\u0163i", + "bine", + "bucur", + "bun\u0103", + "ca", + "care", + "caut", + "ce", + "cel", + "ceva", + "chiar", + "cinci", + "cine", + "cineva", + "contra", + "cu", + "cum", + "cumva", + "cur\u00e2nd", + "cur\u00eend", + "c\u00e2nd", + "c\u00e2t", + "c\u00e2te", + "c\u00e2tva", + "c\u00e2\u0163i", + "c\u00eend", + "c\u00eet", + "c\u00eete", + "c\u00eetva", + "c\u00ee\u0163i", + "c\u0103", + "c\u0103ci", + "c\u0103rei", + "c\u0103ror", + "c\u0103rui", + "c\u0103tre", + "da", + "dac\u0103", + "dar", + "datorit\u0103", + "dat\u0103", + "dau", + "de", + "deci", + "deja", + "deoarece", + "departe", + "de\u015fi", + "din", + "dinaintea", + "dintr-", + "dintre", + "doi", + "doilea", + "dou\u0103", + "drept", + "dup\u0103", + "d\u0103", + "ea", + "ei", + "el", + "ele", + "eram", + "este", + "eu", + "e\u015fti", + "face", + "fata", + "fi", + "fie", + "fiecare", + "fii", + "fim", + "fiu", + "fi\u0163i", + "frumos", + "f\u0103r\u0103", + "gra\u0163ie", + "halb\u0103", + "iar", + "ieri", + "la", + "le", + "li", + "lor", + "lui", + "l\u00e2ng\u0103", + "l\u00eeng\u0103", + "mai", + "mea", + "mei", + "mele", + "mereu", + "meu", + "mi", + "mie", + "mine", + "mult", + "mult\u0103", + "mul\u0163i", + "mul\u0163umesc", + "m\u00e2ine", + "m\u00eeine", + "m\u0103", + "ne", + "nevoie", + "nici", + "nic\u0103ieri", + "nimeni", + "nimeri", + "nimic", + "ni\u015fte", + "noastre", + "noastr\u0103", + "noi", + "noroc", + "nostru", + "nou\u0103", + "no\u015ftri", + "nu", + "opt", + "ori", + "oricare", + "orice", + "oricine", + "oricum", + "oric\u00e2nd", + "oric\u00e2t", + "oric\u00eend", + "oric\u00eet", + "oriunde", + "patra", + "patru", + "patrulea", + "pe", + "pentru", + "peste", + "pic", + "poate", + "pot", + "prea", + "prima", + "primul", + "prin", + "printr-", + "pu\u0163in", + "pu\u0163ina", + "pu\u0163in\u0103", + "p\u00e2n\u0103", + "p\u00een\u0103", + "rog", + "sa", + "sale", + "sau", + "se", + "spate", + "spre", + "sub", + "sunt", + "suntem", + "sunte\u0163i", + "sut\u0103", + "s\u00eent", + "s\u00eentem", + "s\u00eente\u0163i", + "s\u0103", + "s\u0103i", + "s\u0103u", + "ta", + "tale", + "te", + "timp", + "tine", + "toate", + "toat\u0103", + "tot", + "totu\u015fi", + "to\u0163i", + "trei", + "treia", + "treilea", + "tu", + "t\u0103i", + "t\u0103u", + "un", + "una", + "unde", + "undeva", + "unei", + "uneia", + "unele", + "uneori", + "unii", + "unor", + "unora", + "unu", + "unui", + "unuia", + "unul", + "vi", + "voastre", + "voastr\u0103", + "voi", + "vostru", + "vou\u0103", + "vo\u015ftri", + "vreme", + "vreo", + "vreun", + "v\u0103", + "zece", + "zero", + "zi", + "zice", + "\u00eei", + "\u00eel", + "\u00eemi", + "\u00eempotriva", + "\u00een", + "\u00eenainte", + "\u00eenaintea", + "\u00eencotro", + "\u00eenc\u00e2t", + "\u00eenc\u00eet", + "\u00eentre", + "\u00eentruc\u00e2t", + "\u00eentruc\u00eet", + "\u00ee\u0163i", + "\u0103la", + "\u0103lea", + "\u0103sta", + "\u0103stea", + "\u0103\u015ftia", + "\u015fapte", + "\u015fase", + "\u015fi", + "\u015ftiu", + "\u0163i", + "\u0163ie", + ], + "ru": [ + "\u0430", + "\u0430\u043b\u043b\u043e", + "\u0431\u0435\u0437", + "\u0431\u0435\u043b\u044b\u0439", + "\u0431\u043b\u0438\u0437\u043a\u043e", + "\u0431\u043e\u043b\u0435\u0435", + "\u0431\u043e\u043b\u044c\u0448\u0435", + "\u0431\u043e\u043b\u044c\u0448\u043e\u0439", + "\u0431\u0443\u0434\u0435\u043c", + "\u0431\u0443\u0434\u0435\u0442", + "\u0431\u0443\u0434\u0435\u0442\u0435", + "\u0431\u0443\u0434\u0435\u0448\u044c", + "\u0431\u0443\u0434\u0442\u043e", + "\u0431\u0443\u0434\u0443", + "\u0431\u0443\u0434\u0443\u0442", + "\u0431\u0443\u0434\u044c", + "\u0431\u044b", + "\u0431\u044b\u0432\u0430\u0435\u0442", + "\u0431\u044b\u0432\u044c", + "\u0431\u044b\u043b", + "\u0431\u044b\u043b\u0430", + "\u0431\u044b\u043b\u0438", + "\u0431\u044b\u043b\u043e", + "\u0431\u044b\u0442\u044c", + "\u0432", + "\u0432\u0430\u0436\u043d\u0430\u044f", + "\u0432\u0430\u0436\u043d\u043e\u0435", + "\u0432\u0430\u0436\u043d\u044b\u0435", + "\u0432\u0430\u0436\u043d\u044b\u0439", + "\u0432\u0430\u043c", + "\u0432\u0430\u043c\u0438", + "\u0432\u0430\u0441", + "\u0432\u0430\u0448", + "\u0432\u0430\u0448\u0430", + "\u0432\u0430\u0448\u0435", + "\u0432\u0430\u0448\u0438", + "\u0432\u0432\u0435\u0440\u0445", + "\u0432\u0434\u0430\u043b\u0438", + "\u0432\u0434\u0440\u0443\u0433", + "\u0432\u0435\u0434\u044c", + "\u0432\u0435\u0437\u0434\u0435", + "\u0432\u0435\u0440\u043d\u0443\u0442\u044c\u0441\u044f", + "\u0432\u0435\u0441\u044c", + "\u0432\u0435\u0447\u0435\u0440", + "\u0432\u0437\u0433\u043b\u044f\u0434", + "\u0432\u0437\u044f\u0442\u044c", + "\u0432\u0438\u0434", + "\u0432\u0438\u0434\u0435\u0442\u044c", + "\u0432\u043c\u0435\u0441\u0442\u0435", + "\u0432\u043d\u0438\u0437", + "\u0432\u043d\u0438\u0437\u0443", + "\u0432\u043e", + "\u0432\u043e\u0434\u0430", + "\u0432\u043e\u0439\u043d\u0430", + "\u0432\u043e\u043a\u0440\u0443\u0433", + "\u0432\u043e\u043d", + "\u0432\u043e\u043e\u0431\u0449\u0435", + "\u0432\u043e\u043f\u0440\u043e\u0441", + "\u0432\u043e\u0441\u0435\u043c\u043d\u0430\u0434\u0446\u0430\u0442\u044b\u0439", + "\u0432\u043e\u0441\u0435\u043c\u043d\u0430\u0434\u0446\u0430\u0442\u044c", + "\u0432\u043e\u0441\u0435\u043c\u044c", + "\u0432\u043e\u0441\u044c\u043c\u043e\u0439", + "\u0432\u043e\u0442", + "\u0432\u043f\u0440\u043e\u0447\u0435\u043c", + "\u0432\u0440\u0435\u043c\u0435\u043d\u0438", + "\u0432\u0440\u0435\u043c\u044f", + "\u0432\u0441\u0435", + "\u0432\u0441\u0435\u0433\u0434\u0430", + "\u0432\u0441\u0435\u0433\u043e", + "\u0432\u0441\u0435\u043c", + "\u0432\u0441\u0435\u043c\u0438", + "\u0432\u0441\u0435\u043c\u0443", + "\u0432\u0441\u0435\u0445", + "\u0432\u0441\u0435\u044e", + "\u0432\u0441\u044e", + "\u0432\u0441\u044e\u0434\u0443", + "\u0432\u0441\u044f", + "\u0432\u0441\u0451", + "\u0432\u0442\u043e\u0440\u043e\u0439", + "\u0432\u044b", + "\u0432\u044b\u0439\u0442\u0438", + "\u0433", + "\u0433\u0434\u0435", + "\u0433\u043b\u0430\u0432\u043d\u044b\u0439", + "\u0433\u043b\u0430\u0437", + "\u0433\u043e\u0432\u043e\u0440\u0438\u043b", + "\u0433\u043e\u0432\u043e\u0440\u0438\u0442", + "\u0433\u043e\u0432\u043e\u0440\u0438\u0442\u044c", + "\u0433\u043e\u0434", + "\u0433\u043e\u0434\u0430", + "\u0433\u043e\u0434\u0443", + "\u0433\u043e\u043b\u043e\u0432\u0430", + "\u0433\u043e\u043b\u043e\u0441", + "\u0433\u043e\u0440\u043e\u0434", + "\u0434\u0430", + "\u0434\u0430\u0432\u0430\u0442\u044c", + "\u0434\u0430\u0432\u043d\u043e", + "\u0434\u0430\u0436\u0435", + "\u0434\u0430\u043b\u0435\u043a\u0438\u0439", + "\u0434\u0430\u043b\u0435\u043a\u043e", + "\u0434\u0430\u043b\u044c\u0448\u0435", + "\u0434\u0430\u0440\u043e\u043c", + "\u0434\u0430\u0442\u044c", + "\u0434\u0432\u0430", + "\u0434\u0432\u0430\u0434\u0446\u0430\u0442\u044b\u0439", + "\u0434\u0432\u0430\u0434\u0446\u0430\u0442\u044c", + "\u0434\u0432\u0435", + "\u0434\u0432\u0435\u043d\u0430\u0434\u0446\u0430\u0442\u044b\u0439", + "\u0434\u0432\u0435\u043d\u0430\u0434\u0446\u0430\u0442\u044c", + "\u0434\u0432\u0435\u0440\u044c", + "\u0434\u0432\u0443\u0445", + 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"\u0441\u0432\u043e\u0435\u0433\u043e", + "\u0441\u0432\u043e\u0435\u0439", + "\u0441\u0432\u043e\u0438", + "\u0441\u0432\u043e\u0438\u0445", + "\u0441\u0432\u043e\u0439", + "\u0441\u0432\u043e\u044e", + "\u0441\u0434\u0435\u043b\u0430\u0442\u044c", + "\u0441\u0435\u0430\u043e\u0439", + "\u0441\u0435\u0431\u0435", + "\u0441\u0435\u0431\u044f", + "\u0441\u0435\u0433\u043e\u0434\u043d\u044f", + "\u0441\u0435\u0434\u044c\u043c\u043e\u0439", + "\u0441\u0435\u0439\u0447\u0430\u0441", + "\u0441\u0435\u043c\u043d\u0430\u0434\u0446\u0430\u0442\u044b\u0439", + "\u0441\u0435\u043c\u043d\u0430\u0434\u0446\u0430\u0442\u044c", + "\u0441\u0435\u043c\u044c", + "\u0441\u0438\u0434\u0435\u0442\u044c", + "\u0441\u0438\u043b\u0430", + "\u0441\u0438\u0445", + "\u0441\u043a\u0430\u0437\u0430\u043b", + "\u0441\u043a\u0430\u0437\u0430\u043b\u0430", + "\u0441\u043a\u0430\u0437\u0430\u0442\u044c", + "\u0441\u043a\u043e\u043b\u044c\u043a\u043e", + "\u0441\u043b\u0438\u0448\u043a\u043e\u043c", + "\u0441\u043b\u043e\u0432\u043e", + "\u0441\u043b\u0443\u0447\u0430\u0439", + "\u0441\u043c\u043e\u0442\u0440\u0435\u0442\u044c", + "\u0441\u043d\u0430\u0447\u0430\u043b\u0430", + "\u0441\u043d\u043e\u0432\u0430", + "\u0441\u043e", + "\u0441\u043e\u0431\u043e\u0439", + "\u0441\u043e\u0431\u043e\u044e", + "\u0441\u043e\u0432\u0435\u0442\u0441\u043a\u0438\u0439", + "\u0441\u043e\u0432\u0441\u0435\u043c", + "\u0441\u043f\u0430\u0441\u0438\u0431\u043e", + "\u0441\u043f\u0440\u043e\u0441\u0438\u0442\u044c", + "\u0441\u0440\u0430\u0437\u0443", + "\u0441\u0442\u0430\u043b", + "\u0441\u0442\u0430\u0440\u044b\u0439", + "\u0441\u0442\u0430\u0442\u044c", + "\u0441\u0442\u043e\u043b", + "\u0441\u0442\u043e\u0440\u043e\u043d\u0430", + "\u0441\u0442\u043e\u044f\u0442\u044c", + "\u0441\u0442\u0440\u0430\u043d\u0430", + "\u0441\u0443\u0442\u044c", + "\u0441\u0447\u0438\u0442\u0430\u0442\u044c", + "\u0442", + "\u0442\u0430", + "\u0442\u0430\u043a", + "\u0442\u0430\u043a\u0430\u044f", + "\u0442\u0430\u043a\u0436\u0435", + "\u0442\u0430\u043a\u0438", + "\u0442\u0430\u043a\u0438\u0435", + "\u0442\u0430\u043a\u043e\u0435", + "\u0442\u0430\u043a\u043e\u0439", + "\u0442\u0430\u043c", + "\u0442\u0432\u043e\u0439", + "\u0442\u0432\u043e\u044f", + "\u0442\u0432\u043e\u0451", + "\u0442\u0435", + "\u0442\u0435\u0431\u0435", + "\u0442\u0435\u0431\u044f", + "\u0442\u0435\u043c", + "\u0442\u0435\u043c\u0438", + "\u0442\u0435\u043f\u0435\u0440\u044c", + "\u0442\u0435\u0445", + "\u0442\u043e", + "\u0442\u043e\u0431\u043e\u0439", + "\u0442\u043e\u0431\u043e\u044e", + "\u0442\u043e\u0432\u0430\u0440\u0438\u0449", + "\u0442\u043e\u0433\u0434\u0430", + "\u0442\u043e\u0433\u043e", + "\u0442\u043e\u0436\u0435", + "\u0442\u043e\u043b\u044c\u043a\u043e", + "\u0442\u043e\u043c", + "\u0442\u043e\u043c\u0443", + "\u0442\u043e\u0442", + "\u0442\u043e\u044e", + "\u0442\u0440\u0435\u0442\u0438\u0439", + "\u0442\u0440\u0438", + "\u0442\u0440\u0438\u043d\u0430\u0434\u0446\u0430\u0442\u044b\u0439", + "\u0442\u0440\u0438\u043d\u0430\u0434\u0446\u0430\u0442\u044c", + "\u0442\u0443", + "\u0442\u0443\u0434\u0430", + "\u0442\u0443\u0442", + "\u0442\u044b", + "\u0442\u044b\u0441\u044f\u0447", + "\u0443", + "\u0443\u0432\u0438\u0434\u0435\u0442\u044c", + "\u0443\u0436", + "\u0443\u0436\u0435", + "\u0443\u043b\u0438\u0446\u0430", + "\u0443\u043c\u0435\u0442\u044c", + "\u0443\u0442\u0440\u043e", + "\u0445\u043e\u0440\u043e\u0448\u0438\u0439", + "\u0445\u043e\u0440\u043e\u0448\u043e", + "\u0445\u043e\u0442\u0435\u0442\u044c", + "\u0445\u043e\u0442\u044c", + "\u0445\u043e\u0442\u044f", + "\u0445\u043e\u0447\u0435\u0448\u044c", + "\u0447\u0430\u0441", + "\u0447\u0430\u0441\u0442\u043e", + "\u0447\u0430\u0441\u0442\u044c", + "\u0447\u0430\u0449\u0435", + "\u0447\u0435\u0433\u043e", + "\u0447\u0435\u043b\u043e\u0432\u0435\u043a", + "\u0447\u0435\u043c", + "\u0447\u0435\u043c\u0443", + "\u0447\u0435\u0440\u0435\u0437", + "\u0447\u0435\u0442\u0432\u0435\u0440\u0442\u044b\u0439", + "\u0447\u0435\u0442\u044b\u0440\u0435", + "\u0447\u0435\u0442\u044b\u0440\u043d\u0430\u0434\u0446\u0430\u0442\u044b\u0439", + "\u0447\u0435\u0442\u044b\u0440\u043d\u0430\u0434\u0446\u0430\u0442\u044c", + "\u0447\u0442\u043e", + "\u0447\u0442\u043e\u0431", + "\u0447\u0442\u043e\u0431\u044b", + "\u0447\u0443\u0442\u044c", + "\u0448\u0435\u0441\u0442\u043d\u0430\u0434\u0446\u0430\u0442\u044b\u0439", + "\u0448\u0435\u0441\u0442\u043d\u0430\u0434\u0446\u0430\u0442\u044c", + "\u0448\u0435\u0441\u0442\u043e\u0439", + "\u0448\u0435\u0441\u0442\u044c", + "\u044d\u0442\u0430", + "\u044d\u0442\u0438", + "\u044d\u0442\u0438\u043c", + "\u044d\u0442\u0438\u043c\u0438", + "\u044d\u0442\u0438\u0445", + "\u044d\u0442\u043e", + "\u044d\u0442\u043e\u0433\u043e", + "\u044d\u0442\u043e\u0439", + "\u044d\u0442\u043e\u043c", + "\u044d\u0442\u043e\u043c\u0443", + "\u044d\u0442\u043e\u0442", + "\u044d\u0442\u0443", + "\u044f", + ], + "sk": [ + "a", + "aby", + "aj", + "ako", + "ak\u00fd", + "ale", + "alebo", + "ani", + "av\u0161ak", + "ba", + "bez", + "bu\u00ef", + "cez", + "do", + "ho", + "hoci", + "i", + "ich", + "im", + "ja", + "jeho", + "jej", + "jemu", + "ju", + "k", + "kam", + "kde", + "ked\u017ee", + "ke\u00ef", + "kto", + "ktor\u00fd", + "ku", + "lebo", + "ma", + "mi", + "mne", + "mnou", + "mu", + "my", + "m\u00f2a", + "m\u00f4j", + "na", + "nad", + "nami", + "neho", + "nej", + "nemu", + "nich", + "nielen", + "nim", + "no", + "n\u00e1m", + "n\u00e1s", + "n\u00e1\u0161", + "n\u00edm", + "o", + "od", + "on", + "ona", + "oni", + "ono", + "ony", + "po", + "pod", + "pre", + "pred", + "pri", + "s", + "sa", + "seba", + "sem", + "so", + "svoj", + "tak\u00fd", + "tam", + "teba", + "tebe", + "tebou", + "tej", + "ten", + "ti", + "tie", + "to", + "toho", + "tomu", + "tou", + "tvoj", + "ty", + "t\u00e1", + "t\u00fdm", + "v", + "vami", + "ve\u00ef", + "vo", + "vy", + "v\u00e1m", + "v\u00e1s", + "v\u00e1\u0161", + "v\u0161ak", + "z", + "za", + "zo", + "\u009da", + "\u00e8i", + "\u00e8o", + "\u00e8\u00ed", + "\u00f2om", + "\u00f2ou", + "\u00f2u", + "\u017ee", + ], + "sl": [ + "a", + "ali", + "april", + "avgust", + "b", + "bi", + "bil", + "bila", + "bile", + "bili", + "bilo", + "biti", + "blizu", + "bo", + "bodo", + "bojo", + "bolj", + "bom", + "bomo", + "boste", + "bova", + "bo\u0161", + "brez", + "c", + "cel", + "cela", + "celi", + "celo", + "d", + "da", + "dale\u010d", + "dan", + "danes", + "datum", + "december", + "deset", + "deseta", + "deseti", + "deseto", + "devet", + "deveta", + "deveti", + "deveto", + "do", + "dober", + "dobra", + "dobri", + "dobro", + "dokler", + "dol", + "dolg", + "dolga", + "dolgi", + "dovolj", + "drug", + "druga", + "drugi", + "drugo", + "dva", + "dve", + "e", + "eden", + "en", + "ena", + "ene", + "eni", + "enkrat", + "eno", + "etc.", + "f", + "februar", + "g", + "g.", + "ga", + "ga.", + "gor", + "gospa", + "gospod", + "h", + "halo", + "i", + "idr.", + "ii", + "iii", + "in", + "iv", + "ix", + "iz", + "j", + "januar", + "jaz", + "je", + "ji", + "jih", + "jim", + "jo", + "julij", + "junij", + "jutri", + "k", + "kadarkoli", + "kaj", + "kajti", + "kako", + "kakor", + "kamor", + "kamorkoli", + "kar", + "karkoli", + "katerikoli", + "kdaj", + "kdo", + "kdorkoli", + "ker", + "ki", + "kje", + "kjer", + "kjerkoli", + "ko", + "koder", + "koderkoli", + "koga", + "komu", + "kot", + "kratek", + "kratka", + "kratke", + "kratki", + "l", + "lahka", + "lahke", + "lahki", + "lahko", + "le", + "lep", + "lepa", + "lepe", + "lepi", + "lepo", + "leto", + "m", + "maj", + "majhen", + "majhna", + "majhni", + "malce", + "malo", + "manj", + "marec", + "me", + "med", + "medtem", + "mene", + "mesec", + "mi", + "midva", + "midve", + "mnogo", + "moj", + "moja", + "moje", + "mora", + "morajo", + "moram", + "moramo", + "morate", + "mora\u0161", + "morem", + "mu", + "n", + "na", + "nad", + "naj", + "najina", + "najino", + "najmanj", + "naju", + "najve\u010d", + "nam", + "narobe", + "nas", + "nato", + "nazaj", + "na\u0161", + "na\u0161a", + "na\u0161e", + "ne", + "nedavno", + "nedelja", + "nek", + "neka", + "nekaj", + "nekatere", + "nekateri", + "nekatero", + "nekdo", + "neke", + "nekega", + "neki", + "nekje", + "neko", + "nekoga", + "neko\u010d", + "ni", + "nikamor", + "nikdar", + "nikjer", + "nikoli", + "ni\u010d", + "nje", + "njega", + "njegov", + "njegova", + "njegovo", + "njej", + "njemu", + "njen", + "njena", + "njeno", + "nji", + "njih", + "njihov", + "njihova", + "njihovo", + "njiju", + "njim", + "njo", + "njun", + "njuna", + "njuno", + "no", + "nocoj", + "november", + "npr.", + "o", + "ob", + "oba", + "obe", + "oboje", + "od", + "odprt", + "odprta", + "odprti", + "okoli", + "oktober", + "on", + "onadva", + "one", + "oni", + "onidve", + "osem", + "osma", + "osmi", + "osmo", + "oz.", + "p", + "pa", + "pet", + "peta", + "petek", + "peti", + "peto", + "po", + "pod", + "pogosto", + "poleg", + "poln", + "polna", + "polni", + "polno", + "ponavadi", + "ponedeljek", + "ponovno", + "potem", + "povsod", + "pozdravljen", + "pozdravljeni", + "prav", + "prava", + "prave", + "pravi", + "pravo", + "prazen", + "prazna", + "prazno", + "prbl.", + "precej", + "pred", + "prej", + "preko", + "pri", + "pribl.", + "pribli\u017eno", + "primer", + "pripravljen", + "pripravljena", + "pripravljeni", + "proti", + "prva", + "prvi", + "prvo", + "r", + "ravno", + "redko", + "res", + "re\u010d", + "s", + "saj", + "sam", + "sama", + "same", + "sami", + "samo", + "se", + "sebe", + "sebi", + "sedaj", + "sedem", + "sedma", + "sedmi", + "sedmo", + "sem", + "september", + "seveda", + "si", + "sicer", + "skoraj", + "skozi", + "slab", + "smo", + "so", + "sobota", + "spet", + "sreda", + "srednja", + "srednji", + "sta", + "ste", + "stran", + "stvar", + "sva", + "t", + "ta", + "tak", + "taka", + "take", + "taki", + "tako", + "takoj", + "tam", + "te", + "tebe", + "tebi", + "tega", + "te\u017eak", + "te\u017eka", + "te\u017eki", + "te\u017eko", + "ti", + "tista", + "tiste", + "tisti", + "tisto", + "tj.", + "tja", + "to", + "toda", + "torek", + "tretja", + "tretje", + "tretji", + "tri", + "tu", + "tudi", + "tukaj", + "tvoj", + "tvoja", + "tvoje", + "u", + "v", + "vaju", + "vam", + "vas", + "va\u0161", + "va\u0161a", + "va\u0161e", + "ve", + "vedno", + "velik", + "velika", + "veliki", + "veliko", + "vendar", + "ves", + "ve\u010d", + "vi", + "vidva", + "vii", + "viii", + "visok", + "visoka", + "visoke", + "visoki", + "vsa", + "vsaj", + "vsak", + "vsaka", + "vsakdo", + "vsake", + "vsaki", + "vsakomur", + "vse", + "vsega", + "vsi", + "vso", + "v\u010dasih", + "v\u010deraj", + "x", + "z", + "za", + "zadaj", + "zadnji", + "zakaj", + "zaprta", + "zaprti", + "zaprto", + "zdaj", + "zelo", + "zunaj", + "\u010d", + "\u010de", + "\u010desto", + "\u010detrta", + "\u010detrtek", + "\u010detrti", + "\u010detrto", + "\u010dez", + "\u010digav", + "\u0161", + "\u0161est", + "\u0161esta", + "\u0161esti", + "\u0161esto", + "\u0161tiri", + "\u017e", + "\u017ee", + ], + "so": [ + "aad", + "albaabkii", + "atabo", + "ay", + "ayaa", + "ayee", + "ayuu", + "dhan", + "hadana", + "in", + "inuu", + "isku", + "jiray", + "jirtay", + "ka", + "kale", + "kasoo", + "ku", + "kuu", + "lakin", + "markii", + "oo", + "si", + "soo", + "uga", + "ugu", + "uu", + "waa", + "waxa", + "waxuu", + ], + "st": [ + "a", + "ba", + "bane", + "bona", + "e", + "ea", + "eaba", + "empa", + "ena", + "ha", + "hae", + "hape", + "ho", + "hore", + "ka", + "ke", + "la", + "le", + "li", + "me", + "mo", + "moo", + "ne", + "o", + "oa", + "re", + "sa", + "se", + "tloha", + "tsa", + "tse", + ], + "sv": [ + "aderton", + "adertonde", + "adj\u00f6", + "aldrig", + "alla", + "allas", + "allt", + "alltid", + "allts\u00e5", + "andra", + "andras", + "annan", + "annat", + "artonde", + "artonn", + "att", + "av", + "bakom", + "bara", + "beh\u00f6va", + "beh\u00f6vas", + "beh\u00f6vde", + "beh\u00f6vt", + "beslut", + "beslutat", + "beslutit", + "bland", + "blev", + "bli", + "blir", + "blivit", + "bort", + "borta", + "bra", + "b\u00e4st", + "b\u00e4ttre", + "b\u00e5da", + "b\u00e5das", + "dag", + "dagar", + "dagarna", + "dagen", + "de", + "del", + "delen", + "dem", + "den", + "denna", + "deras", + "dess", + "dessa", + "det", + "detta", + "dig", + "din", + "dina", + "dit", + "ditt", + "dock", + "du", + "d\u00e4r", + "d\u00e4rf\u00f6r", + "d\u00e5", + "efter", + "eftersom", + "ej", + "elfte", + "eller", + "elva", + "en", + "enkel", + "enkelt", + "enkla", + "enligt", + "er", + "era", + "ert", + "ett", + "ettusen", + "fanns", + "fem", + "femte", + "femtio", + "femtionde", + "femton", + "femtonde", + "fick", + "fin", + "finnas", + "finns", + "fjorton", + "fjortonde", + "fj\u00e4rde", + "fler", + "flera", + "flesta", + "fram", + "framf\u00f6r", + "fr\u00e5n", + "fyra", + "fyrtio", + "fyrtionde", + "f\u00e5", + "f\u00e5r", + "f\u00e5tt", + "f\u00f6ljande", + "f\u00f6r", + "f\u00f6re", + "f\u00f6rl\u00e5t", + "f\u00f6rra", + "f\u00f6rsta", + "genast", + "genom", + "gick", + "gjorde", + "gjort", + "god", + "goda", + "godare", + "godast", + "gott", + "g\u00e4lla", + "g\u00e4ller", + "g\u00e4llt", + "g\u00e4rna", + "g\u00e5", + "g\u00e5r", + "g\u00e5tt", + "g\u00f6r", + "g\u00f6ra", + "ha", + "hade", + "haft", + "han", + "hans", + "har", + "heller", + "hellre", + "helst", + "helt", + "henne", + "hennes", + "hit", + "hon", + "honom", + "hundra", + "hundraen", + "hundraett", + "hur", + "h\u00e4r", + "h\u00f6g", + "h\u00f6ger", + "h\u00f6gre", + "h\u00f6gst", + "i", + "ibland", + "icke", + "idag", + "igen", + "ig\u00e5r", + "imorgon", + "in", + "inf\u00f6r", + "inga", + "ingen", + "ingenting", + "inget", + "innan", + "inne", + "inom", + "inte", + "inuti", + "ja", + "jag", + "ju", + "j\u00e4mf\u00f6rt", + "kan", + "kanske", + "knappast", + "kom", + "komma", + "kommer", + "kommit", + "kr", + "kunde", + "kunna", + "kunnat", + "kvar", + "legat", + "ligga", + "ligger", + "lika", + "likst\u00e4lld", + "likst\u00e4llda", + "lilla", + "lite", + "liten", + "litet", + "l\u00e4nge", + "l\u00e4ngre", + "l\u00e4ngst", + "l\u00e4tt", + "l\u00e4ttare", + "l\u00e4ttast", + "l\u00e5ngsam", + "l\u00e5ngsammare", + "l\u00e5ngsammast", + "l\u00e5ngsamt", + "l\u00e5ngt", + "man", + "med", + "mellan", + "men", + "mer", + "mera", + "mest", + "mig", + "min", + "mina", + "mindre", + "minst", + "mitt", + "mittemot", + "mot", + "mycket", + "m\u00e5nga", + "m\u00e5ste", + "m\u00f6jlig", + "m\u00f6jligen", + "m\u00f6jligt", + "m\u00f6jligtvis", + "ned", + "nederst", + "nedersta", + "nedre", + "nej", + "ner", + "ni", + "nio", + "nionde", + "nittio", + "nittionde", + "nitton", + "nittonde", + "nog", + "noll", + "nr", + "nu", + "nummer", + "n\u00e4r", + "n\u00e4sta", + "n\u00e5gon", + "n\u00e5gonting", + "n\u00e5got", + "n\u00e5gra", + "n\u00f6dv\u00e4ndig", + "n\u00f6dv\u00e4ndiga", + "n\u00f6dv\u00e4ndigt", + "n\u00f6dv\u00e4ndigtvis", + "och", + "ocks\u00e5", + "ofta", + "oftast", + "olika", + "olikt", + "om", + "oss", + "p\u00e5", + "rakt", + "redan", + "r\u00e4tt", + "sade", + "sagt", + "samma", + "sedan", + "senare", + "senast", + "sent", + "sex", + "sextio", + "sextionde", + "sexton", + "sextonde", + "sig", + "sin", + "sina", + "sist", + "sista", + "siste", + "sitt", + "sitta", + "sju", + "sjunde", + "sjuttio", + "sjuttionde", + "sjutton", + "sjuttonde", + "sj\u00e4lv", + "sj\u00e4tte", + "ska", + "skall", + "skulle", + "slutligen", + "sm\u00e5", + "sm\u00e5tt", + "snart", + "som", + "stor", + "stora", + "stort", + "st\u00f6rre", + "st\u00f6rst", + "s\u00e4ga", + "s\u00e4ger", + "s\u00e4mre", + "s\u00e4mst", + "s\u00e5", + "s\u00e5dan", + "s\u00e5dana", + "s\u00e5dant", + "tack", + "tidig", + "tidigare", + "tidigast", + "tidigt", + "till", + "tills", + "tillsammans", + "tio", + "tionde", + "tjugo", + "tjugoen", + "tjugoett", + "tjugonde", + "tjugotre", + "tjugotv\u00e5", + "tjungo", + "tolfte", + "tolv", + "tre", + "tredje", + "trettio", + "trettionde", + "tretton", + "trettonde", + "tv\u00e5", + "tv\u00e5hundra", + "under", + "upp", + "ur", + "urs\u00e4kt", + "ut", + "utan", + "utanf\u00f6r", + "ute", + "vad", + "var", + "vara", + "varf\u00f6r", + "varifr\u00e5n", + "varit", + "varje", + "varken", + "vars", + "vars\u00e5god", + "vart", + "vem", + "vems", + "verkligen", + "vi", + "vid", + "vidare", + "viktig", + "viktigare", + "viktigast", + "viktigt", + "vilka", + "vilkas", + "vilken", + "vilket", + "vill", + "v\u00e4nster", + "v\u00e4nstra", + "v\u00e4rre", + "v\u00e5r", + "v\u00e5ra", + "v\u00e5rt", + "\u00e4n", + "\u00e4nnu", + "\u00e4r", + "\u00e4ven", + "\u00e5t", + "\u00e5tminstone", + "\u00e5tta", + "\u00e5ttio", + "\u00e5ttionde", + "\u00e5ttonde", + "\u00f6ver", + "\u00f6vermorgon", + "\u00f6verst", + "\u00f6vre", + ], + "sw": [ + "akasema", + "alikuwa", + "alisema", + "baada", + "basi", + "bila", + "cha", + "chini", + "hadi", + "hapo", + "hata", + "hivyo", + "hiyo", + "huku", + "huo", + "ili", + "ilikuwa", + "juu", + "kama", + "karibu", + "katika", + "kila", + "kima", + "kisha", + "kubwa", + "kutoka", + "kuwa", + "kwa", + "kwamba", + "kwenda", + "kwenye", + "la", + "lakini", + "mara", + "mdogo", + "mimi", + "mkubwa", + "mmoja", + "moja", + "muda", + "mwenye", + "na", + "naye", + "ndani", + "ng", + "ni", + "nini", + "nonkungu", + "pamoja", + "pia", + "sana", + "sasa", + "sauti", + "tafadhali", + "tena", + "tu", + "vile", + "wa", + "wakati", + "wake", + "walikuwa", + "wao", + "watu", + "wengine", + "wote", + "ya", + "yake", + "yangu", + "yao", + "yeye", + "yule", + "za", + "zaidi", + "zake", + ], + "th": [ + "\u0e01\u0e25\u0e48\u0e32\u0e27", + "\u0e01\u0e27\u0e48\u0e32", + "\u0e01\u0e31\u0e19", + "\u0e01\u0e31\u0e1a", + "\u0e01\u0e32\u0e23", + "\u0e01\u0e47", + "\u0e01\u0e48\u0e2d\u0e19", + "\u0e02\u0e13\u0e30", + "\u0e02\u0e2d", + "\u0e02\u0e2d\u0e07", + "\u0e02\u0e36\u0e49\u0e19", + "\u0e04\u0e07", + "\u0e04\u0e23\u0e31\u0e49\u0e07", + "\u0e04\u0e27\u0e32\u0e21", + "\u0e04\u0e37\u0e2d", + "\u0e08\u0e30", + "\u0e08\u0e31\u0e14", + "\u0e08\u0e32\u0e01", + "\u0e08\u0e36\u0e07", + "\u0e0a\u0e48\u0e27\u0e07", + "\u0e0b\u0e36\u0e48\u0e07", + "\u0e14\u0e31\u0e07", + 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"bana", + "bari", + "bazen", + "baz\u00fd", + "baz\u0131", + "ba\u0163ka", + "belki", + "ben", + "benden", + "beni", + "benim", + "beri", + "be\u00fe", + "be\u015f", + "be\u0163", + "bile", + "bin", + "bir", + "biraz", + "biri", + "birka\u00e7", + "birkez", + "bir\u00e7ok", + "bir\u00feey", + "bir\u00feeyi", + "bir\u015fey", + "bir\u015feyi", + "bir\u0163ey", + "biz", + "bizden", + "bize", + "bizi", + "bizim", + "bu", + "buna", + "bunda", + "bundan", + "bunlar", + "bunlar\u0131", + "bunlar\u0131n", + "bunu", + "bunun", + "burada", + "b\u00f6yle", + "b\u00f6ylece", + "b\u00fct\u00fcn", + "da", + "daha", + "dahi", + "dahil", + "daima", + "dair", + "dayanarak", + "de", + "defa", + "de\u0111il", + "de\u011fil", + "diye", + "di\u0111er", + "di\u011fer", + "doksan", + "dokuz", + "dolay\u0131", + "dolay\u0131s\u0131yla", + "d\u00f6rt", + "edecek", + "eden", + "ederek", + "edilecek", + "ediliyor", + "edilmesi", + "ediyor", + "elli", + "en", + "etmesi", + "etti", + "etti\u011fi", + "etti\u011fini", + "e\u0111er", + "e\u011fer", + "fakat", + "gibi", + "g\u00f6re", + "halbuki", + "halen", + "hangi", + "hani", + "hari\u00e7", + "hatta", + "hele", + "hem", + "hen\u00fcz", + "hep", + "hepsi", + "her", + "herhangi", + "herkes", + "herkesin", + "hi\u00e7", + "hi\u00e7bir", + "iken", + "iki", + "ila", + "ile", + "ilgili", + "ilk", + "illa", + "ise", + "itibaren", + "itibariyle", + "iyi", + "iyice", + "i\u00e7in", + "i\u015fte", + "i\u0163te", + "kadar", + "kan\u00fdmca", + "kar\u015f\u0131n", + "katrilyon", + "kendi", + "kendilerine", + "kendini", + "kendisi", + "kendisine", + "kendisini", + "kere", + "kez", + "ke\u0163ke", + "ki", + "kim", + "kimden", + "kime", + "kimi", + "kimse", + "k\u00fdrk", + "k\u00fdsaca", + "k\u0131rk", + "lakin", + "madem", + "me\u0111er", + "milyar", + "milyon", + "mu", + "m\u00fc", + "m\u00fd", + "m\u0131", + "nas\u00fdl", + "nas\u0131l", + "ne", + "neden", + "nedenle", + "nerde", + "nere", + "nerede", + "nereye", + "nitekim", + "niye", + "ni\u00e7in", + "o", + "olan", + "olarak", + "oldu", + "olduklar\u0131n\u0131", + "oldu\u011fu", + "oldu\u011funu", + "olmad\u0131", + "olmad\u0131\u011f\u0131", + "olmak", + "olmas\u0131", + "olmayan", + "olmaz", + "olsa", + "olsun", + "olup", + "olur", + "olursa", + "oluyor", + "on", + "ona", + "ondan", + "onlar", + "onlardan", + "onlari", + "onlar\u00fdn", + "onlar\u0131", + "onlar\u0131n", + "onu", + "onun", + "otuz", + "oysa", + "pek", + "ra\u011fmen", + "sadece", + "sanki", + "sekiz", + "seksen", + "sen", + "senden", + "seni", + "senin", + "siz", + "sizden", + "sizi", + "sizin", + "sonra", + "taraf\u0131ndan", + "trilyon", + "t\u00fcm", + "var", + "vard\u0131", + "ve", + "veya", + "veyahut", + "ya", + "yahut", + "yani", + "yapacak", + "yapmak", + "yapt\u0131", + "yapt\u0131klar\u0131", + "yapt\u0131\u011f\u0131", + "yapt\u0131\u011f\u0131n\u0131", + "yap\u0131lan", + "yap\u0131lmas\u0131", + "yap\u0131yor", + "yedi", + "yerine", + "yetmi\u00fe", + "yetmi\u015f", + "yetmi\u0163", + "yine", + "yirmi", + "yoksa", + "y\u00fcz", + "zaten", + "\u00e7ok", + "\u00e7\u00fcnk\u00fc", + "\u00f6yle", + "\u00fczere", + "\u00fc\u00e7", + "\u00feey", + "\u00feeyden", + "\u00feeyi", + "\u00feeyler", + "\u00feu", + "\u00feuna", + "\u00feunda", + "\u00feundan", + "\u00feunu", + "\u015fey", + "\u015feyden", + "\u015feyi", + "\u015feyler", + "\u015fu", + "\u015funa", + "\u015funda", + "\u015fundan", + "\u015funlar\u0131", + "\u015funu", + "\u015f\u00f6yle", + "\u0163ayet", + "\u0163imdi", + "\u0163u", + "\u0163\u00f6yle", + ], + "ur": [ + "آئی", + "آئے", + "آج", + "آخر", + "آخرکبر", + "آدهی", + "آًب", + "آٹھ", + "آیب", + "اة", + "اخبزت", + "اختتبم", + "ادھر", + "ارد", + "اردگرد", + "ارکبى", + "اش", + "اضتعوبل", + "اضتعوبلات", + "اضطرذ", + "اضکب", + "اضکی", + "اضکے", + "اطراف", + "اغیب", + "افراد", + "الگ", + "اور", + "اوًچب", + "اوًچبئی", + "اوًچی", + "اوًچے", + "اى", + "اً", + "اًذر", + "اًہیں", + "اٹھبًب", + "اپٌب", + "اپٌے", + "اچھب", + "اچھی", + "اچھے", + "اکثر", + "اکٹھب", + "اکٹھی", + "اکٹھے", + "اکیلا", + "اکیلی", + "اکیلے", + "اگرچہ", + "اہن", + "ایطے", + "ایک", + "ب", + "ت", + "تبزٍ", + "تت", + "تر", + "ترتیت", + "تریي", + "تعذاد", + "تن", + "تو", + "توبم", + "توہی", + "توہیں", + "تٌہب", + "تک", + "تھب", + "تھوڑا", + "تھوڑی", + "تھوڑے", + "تھی", + "تھے", + "تیي", + "ثب", + "ثبئیں", + "ثبترتیت", + "ثبری", + "ثبرے", + "ثبعث", + "ثبلا", + "ثبلترتیت", + "ثبہر", + "ثدبئے", + "ثرآں", + "ثراں", + "ثرش", + "ثعذ", + "ثغیر", + "ثلٌذ", + "ثلٌذوثبلا", + "ثلکہ", + "ثي", + "ثٌب", + "ثٌبرہب", + "ثٌبرہی", + "ثٌبرہے", + "ثٌبًب", + "ثٌذ", + "ثٌذکرو", + "ثٌذکرًب", + "ثٌذی", + "ثڑا", + "ثڑوں", + "ثڑی", + "ثڑے", + "ثھر", + "ثھرا", + "ثھراہوا", + "ثھرپور", + "ثھی", + "ثہت", + "ثہتر", + "ثہتری", + "ثہتریي", + "ثیچ", + "ج", + "خب", + "خبرہب", + "خبرہی", + "خبرہے", + "خبهوظ", + "خبًب", + "خبًتب", + "خبًتی", + "خبًتے", + "خبًٌب", + "خت", + "ختن", + "خجکہ", + "خص", + "خططرذ", + "خلذی", + "خو", + "خواى", + "خوًہی", + "خوکہ", + "خٌبة", + "خگہ", + "خگہوں", + "خگہیں", + "خیطب", + "خیطبکہ", + "در", + "درخبت", + "درخہ", + "درخے", + "درزقیقت", + "درضت", + "دش", + "دفعہ", + "دلچطپ", + "دلچطپی", + "دلچطپیبں", + "دو", + "دور", + "دوراى", + "دوضرا", + "دوضروں", + "دوضری", + "دوضرے", + "دوًوں", + "دکھبئیں", + "دکھبتب", + "دکھبتی", + "دکھبتے", + "دکھبو", + "دکھبًب", + "دکھبیب", + "دی", + "دیب", + "دیتب", + "دیتی", + "دیتے", + "دیر", + "دیٌب", + "دیکھو", + "دیکھٌب", + "دیکھی", + "دیکھیں", + "دے", + "ر", + "راضتوں", + "راضتہ", + "راضتے", + "رریعہ", + "رریعے", + "رکي", + "رکھ", + "رکھب", + "رکھتب", + "رکھتبہوں", + "رکھتی", + "رکھتے", + "رکھی", + "رکھے", + "رہب", + "رہی", + "رہے", + "ز", + "زبصل", + "زبضر", + "زبل", + "زبلات", + "زبلیہ", + "زصوں", + "زصہ", + "زصے", + "زقبئق", + "زقیتیں", + "زقیقت", + "زکن", + "زکویہ", + "زیبدٍ", + "صبف", + "صسیر", + "صفر", + "صورت", + "صورتسبل", + "صورتوں", + "صورتیں", + "ض", + "ضبت", + "ضبتھ", + "ضبدٍ", + "ضبرا", + "ضبرے", + "ضبل", + "ضبلوں", + "ضت", + "ضرور", + "ضرورت", + "ضروری", + "ضلطلہ", + "ضوچ", + "ضوچب", + "ضوچتب", + "ضوچتی", + "ضوچتے", + "ضوچو", + "ضوچٌب", + "ضوچی", + "ضوچیں", + "ضکب", + "ضکتب", + "ضکتی", + "ضکتے", + "ضکٌب", + "ضکی", + "ضکے", + "ضیذھب", + "ضیذھی", + "ضیذھے", + "ضیکٌڈ", + "ضے", + "طرف", + "طریق", + "طریقوں", + "طریقہ", + "طریقے", + "طور", + "طورپر", + "ظبہر", + "ع", + "عذد", + "عظین", + "علاقوں", + "علاقہ", + "علاقے", + "علاوٍ", + "عووهی", + "غبیذ", + "غخص", + "غذ", + "غروع", + "غروعبت", + "غے", + "فرد", + "فی", + "ق", + "قجل", + "قجیلہ", + "قطن", + "لئے", + "لا", + "لازهی", + "لو", + "لوجب", + "لوجی", + "لوجے", + "لوسبت", + "لوسہ", + "لوگ", + "لوگوں", + "لڑکپي", + "لگتب", + "لگتی", + "لگتے", + "لگٌب", + "لگی", + "لگیں", + "لگے", + "لی", + "لیب", + "لیٌب", + "لیں", + "لے", + "ه", + "هتعلق", + "هختلف", + "هسترم", + "هسترهہ", + "هسطوش", + "هسیذ", + "هطئلہ", + "هطئلے", + "هطبئل", + "هطتعول", + "هطلق", + "هعلوم", + "هػتول", + "هلا", + "هوکي", + "هوکٌبت", + "هوکٌہ", + "هٌبضت", + "هڑا", + "هڑًب", + "هڑے", + "هکول", + "هگر", + "هہرثبى", + "هیرا", + "هیری", + "هیرے", + "هیں", + "و", + "وار", + "والے", + "وٍ", + "ًئی", + "ًئے", + "ًب", + "ًبپطٌذ", + "ًبگسیر", + "ًطجت", + "ًقطہ", + "ًو", + "ًوخواى", + "ًکبلٌب", + "ًکتہ", + "ًہ", + "ًہیں", + "ًیب", + "ًے", + "ٓ آش", + "ٹھیک", + "پبئے", + "پبش", + "پبًب", + "پبًچ", + "پر", + "پراًب", + "پطٌذ", + "پل", + "پورا", + "پوچھب", + "پوچھتب", + "پوچھتی", + "پوچھتے", + "پوچھو", + "پوچھوں", + "پوچھٌب", + "پوچھیں", + "پچھلا", + "پھر", + "پہلا", + "پہلی", + "پہلےضی", + "پہلےضے", + "پہلےضےہی", + "پیع", + "چبر", + "چبہب", + "چبہٌب", + "چبہے", + "چلا", + "چلو", + "چلیں", + "چلے", + "چکب", + "چکی", + "چکیں", + "چکے", + "چھوٹب", + "چھوٹوں", + "چھوٹی", + "چھوٹے", + "چھہ", + "چیسیں", + "ڈھوًڈا", + "ڈھوًڈلیب", + "ڈھوًڈو", + "ڈھوًڈًب", + "ڈھوًڈی", + "ڈھوًڈیں", + "ک", + "کئی", + "کئے", + "کب", + "کبفی", + "کبم", + "کت", + "کجھی", + "کرا", + "کرتب", + "کرتبہوں", + "کرتی", + "کرتے", + "کرتےہو", + "کررہب", + "کررہی", + "کررہے", + "کرو", + "کرًب", + "کریں", + "کرے", + "کطی", + "کل", + "کن", + "کوئی", + "کوتر", + "کورا", + "کوروں", + "کورٍ", + "کورے", + "کوطي", + "کوى", + "کوًطب", + "کوًطی", + "کوًطے", + "کھولا", + "کھولو", + "کھولٌب", + "کھولی", + "کھولیں", + "کھولے", + "کہ", + "کہب", + "کہتب", + "کہتی", + "کہتے", + "کہو", + "کہوں", + "کہٌب", + "کہی", + "کہیں", + "کہے", + "کی", + "کیب", + "کیطب", + "کیطرف", + "کیطے", + "کیلئے", + "کیوًکہ", + "کیوں", + "کیے", + "کے", + "کےثعذ", + "کےرریعے", + "گئی", + "گئے", + "گب", + "گرد", + "گروٍ", + "گروپ", + "گروہوں", + "گٌتی", + "گی", + "گیب", + "گے", + "ہر", + "ہن", + "ہو", + "ہوئی", + "ہوئے", + "ہوا", + "ہوبرا", + "ہوبری", + "ہوبرے", + "ہوتب", + "ہوتی", + "ہوتے", + "ہورہب", + "ہورہی", + "ہورہے", + "ہوضکتب", + "ہوضکتی", + "ہوضکتے", + "ہوًب", + "ہوًی", + "ہوًے", + "ہوچکب", + "ہوچکی", + "ہوچکے", + "ہوگئی", + "ہوگئے", + "ہوگیب", + "ہوں", + "ہی", + "ہیں", + "ہے", + "ی", + "یقیٌی", + "یہ", + "یہبں", + ], + "vi": [ + "a ha", + "a-lô", + "ai", + "ai ai", + "ai nấy", + "alô", + "amen", + "anh", + "bao giờ", + "bao lâu", + "bao nhiêu", + "bao nả", + "bay biến", + "biết", + "biết bao", + "biết bao nhiêu", + "biết chừng nào", + "biết mấy", + "biết đâu", + "biết đâu chừng", + "biết đâu đấy", + "bà", + "bài", + "bác", + "bây bẩy", + "bây chừ", + "bây giờ", + "bây nhiêu", + "bèn", + "béng", + "bông", + "bạn", + "bản", + "bất chợt", + "bất cứ", + "bất giác", + "bất kì", + "bất kể", + "bất kỳ", + "bất luận", + "bất nhược", + "bất quá", + "bất thình lình", + "bất tử", + "bất đồ", + "bấy", + "bấy chầy", + "bấy chừ", + "bấy giờ", + "bấy lâu", + "bấy lâu nay", + "bấy nay", + "bấy nhiêu", + "bập bà bập bõm", + "bập bõm", + "bắt đầu từ", + "bằng", + "bằng không", + "bằng nấy", + "bằng ấy", + "bển", + "bệt", + "bị", + "bỏ mẹ", + "bỗng", + "bỗng chốc", + "bỗng dưng", + "bỗng không", + "bỗng nhiên", + "bỗng đâu", + "bộ", + "bội phần", + "bớ", + "bởi", + "bởi chưng", + "bởi nhưng", + "bởi thế", + "bởi vì", + "bởi vậy", + "bức", + "cao", + "cha", + "cha chả", + "chao ôi", + "chiếc", + "cho", + "cho nên", + "cho tới", + "cho tới khi", + "cho đến", + "cho đến khi", + "choa", + "chu cha", + "chui cha", + "chung cục", + "chung qui", + "chung quy", + "chung quy lại", + "chuyện", + "chành chạnh", + "chí chết", + "chính", + "chính là", + "chính thị", + "chùn chùn", + "chùn chũn", + "chú", + "chú mày", + "chú mình", + "chúng mình", + "chúng ta", + "chúng tôi", + "chăn chắn", + "chăng", + "chưa", + "chầm chập", + "chậc", + "chắc", + "chắc hẳn", + "chẳng lẽ", + "chẳng những", + "chẳng nữa", + "chẳng phải", + "chết nỗi", + "chết thật", + "chết tiệt", + "chỉ", + "chỉn", + "chốc chốc", + "chớ", + "chớ chi", + "chợt", + "chủn", + "chứ", + "chứ lị", + "coi bộ", + "coi mòi", + "con", + "cu cậu", + "cuốn", + "cuộc", + "càng", + "các", + "cái", + "cây", + "còn", + "có", + "có chăng là", + "có dễ", + "có thể", + "có vẻ", + "cóc khô", + "cô", + "cô mình", + "công nhiên", + "cùng", + "cùng cực", + "cùng nhau", + "cùng với", + "căn", + "căn cắt", + "cũng", + "cũng như", + "cũng vậy", + "cũng vậy thôi", + "cơ", + "cơ chừng", + "cơ hồ", + "cơ mà", + "cơn", + "cả", + "cả thảy", + "cả thể", + "cảm ơn", + "cần", + "cật lực", + "cật sức", + "cậu", + "cổ lai", + "của", + "cứ", + "cứ việc", + "cực lực", + "do", + "do vì", + "do vậy", + "do đó", + "duy", + "dào", + "dì", + "dù cho", + "dù rằng", + "dưới", + "dạ", + "dần dà", + "dần dần", + "dầu sao", + "dẫu", + "dẫu sao", + "dễ sợ", + "dễ thường", + "dở chừng", + "dữ", + "em", + "giữa", + "gì", + "hay", + "hoàn toàn", + "hoặc", + "hơn", + "hầu hết", + "họ", + "hỏi", + "khi", + "khác", + "không", + "luôn", + "là", + "làm", + "lên", + "lúc", + "lại", + "lần", + "lớn", + "muốn", + "mà", + "mình", + "mỗi", + "một", + "một cách", + "mới", + "mợ", + "ngay", + "ngay cả", + "ngay khi", + "ngay lúc", + "ngay lập tức", + "ngay tức khắc", + "ngay từ", + "nghe chừng", + "nghe đâu", + "nghen", + "nghiễm nhiên", + "nghỉm", + "ngoài", + "ngoài ra", + "ngoải", + "ngày", + "ngày càng", + "ngày ngày", + "ngày xưa", + "ngày xửa", + "ngôi", + "ngõ hầu", + "ngăn ngắt", + "ngươi", + "người", + "ngọn", + "ngọt", + "ngộ nhỡ", + "nh", + "nhau", + "nhiên hậu", + "nhiều", + "nhiệt liệt", + "nhung nhăng", + "nhà", + "nhân dịp", + "nhân tiện", + "nhé", + "nhón nhén", + "như", + "như chơi", + "như không", + "như quả", + "như thể", + "như tuồng", + "như vậy", + "nhưng", + "nhưng mà", + "nhược bằng", + "nhất", + "nhất loạt", + "nhất luật", + "nhất mực", + "nhất nhất", + "nhất quyết", + "nhất sinh", + "nhất thiết", + "nhất tâm", + "nhất tề", + "nhất đán", + "nhất định", + "nhận", + "nhỉ", + "nhỡ ra", + "những", + "những ai", + "những như", + "nào", + "này", + "nên", + "nên chi", + "nó", + "nóc", + "nói", + "năm", + "nơi", + "nấy", + "nếu", + "nếu như", + "nền", + "nọ", + "nớ", + "nức nở", + "nữa", + "oai oái", + "oái", + "pho", + "phè", + "phóc", + "phót", + "phăn phắt", + "phương chi", + "phải", + "phải chi", + "phải chăng", + "phắt", + "phỉ phui", + "phỏng", + "phỏng như", + "phốc", + "phụt", + "phứt", + "qua", + "qua quít", + "qua quýt", + "quyết", + "quyết nhiên", + "quyển", + "quá", + "quá chừng", + "quá lắm", + "quá sá", + "quá thể", + "quá trời", + "quá xá", + "quá đỗi", + "quá độ", + "quá ư", + "quý hồ", + "quả", + "quả là", + "quả tang", + "quả thật", + "quả tình", + "quả vậy", + "quả đúng", + "ra", + "ra phết", + "ra sao", + "ra trò", + "ren rén", + "riu ríu", + "riêng", + "riệt", + "rày", + "ráo", + "ráo trọi", + "rén", + "rích", + "rón rén", + "rút cục", + "răng", + "rất", + "rằng", + "rằng là", + "rốt cuộc", + "rốt cục", + "rồi", + "rứa", + "sa sả", + "sao", + "sau", + "sau chót", + "sau cuối", + "sau cùng", + "sau đó", + "so", + "song le", + "suýt", + "sì", + "sạch", + "sất", + "sắp", + "sẽ", + "số", + "số là", + "sốt sột", + "sở dĩ", + "sự", + "tanh", + "tha hồ", + "than ôi", + "thanh", + "theo", + "thi thoảng", + "thoạt", + "thoạt nhiên", + "thoắt", + "thuần", + "thà", + "thà là", + "thà rằng", + "thành ra", + "thành thử", + "thái quá", + "tháng", + "thì", + "thì thôi", + "thình lình", + "thím", + "thôi", + "thúng thắng", + "thương ôi", + "thường", + "thảo hèn", + "thảo nào", + "thấy", + "thẩy", + "thậm", + "thậm chí", + "thật lực", + "thật ra", + "thật vậy", + "thế", + "thế là", + "thế mà", + "thế nào", + "thế nên", + "thế ra", + "thế thì", + "thế à", + "thếch", + "thỉnh thoảng", + "thỏm", + "thốc", + "thốc tháo", + "thốt", + "thốt nhiên", + "thộc", + "thời gian", + "thục mạng", + "thửa", + "thực ra", + "thực sự", + "thực vậy", + "tiếp theo", + "tiếp đó", + "tiện thể", + "toà", + "toé khói", + "toẹt", + "trong", + "trên", + "trước", + "trước kia", + "trước nay", + "trước tiên", + "trước đây", + "trước đó", + "trếu tráo", + "trển", + "trệt", + "trệu trạo", + "trỏng", + "trời đất ơi", + "trừ phi", + "tuy", + "tuy nhiên", + "tuy rằng", + "tuy thế", + "tuy vậy", + "tuyệt nhiên", + "tuần tự", + "tuốt luốt", + "tuốt tuồn tuột", + "tuốt tuột", + "tà tà", + "tênh", + "tít mù", + "tò te", + "tôi", + "tông tốc", + "tù tì", + "tăm tắp", + "tại", + "tại vì", + "tấm", + "tấn", + "tất cả", + "tất thảy", + "tất tần tật", + "tất tật", + "tắp", + "tắp lự", + "tọt", + "tỏ ra", + "tỏ vẻ", + "tốc tả", + "tối ư", + "tột", + "tớ", + "tới", + "tức thì", + "tức tốc", + "từ", + "từng", + "tự vì", + "tựu trung", + "veo", + "veo veo", + "việc", + "vung thiên địa", + "vung tàn tán", + "vung tán tàn", + "và", + "vào", + "vâng", + "vèo", + "vì", + "vì chưng", + "vì thế", + "vì vậy", + "ví bằng", + "ví dù", + "ví phỏng", + "ví thử", + "vô hình trung", + "vô kể", + "vô luận", + "vô vàn", + "văng tê", + "vạn nhất", + "vả chăng", + "vả lại", + "vẫn", + "vậy", + "vậy là", + "vậy thì", + "về", + "vị tất", + "vốn dĩ", + "với", + "với lại", + "vở", + "vụt", + "vừa", + "vừa mới", + "xa xả", + "xiết bao", + "xon xón", + "xoành xoạch", + "xoét", + "xoẳn", + "xoẹt", + "xuất kì bất ý", + "xuất kỳ bất ý", + "xuể", + "xuống", + "xăm xúi", + "xăm xăm", + "xăm xắm", + "xềnh xệch", + "xệp", + "à", + "à ơi", + "ào", + "á", + "á à", + "ái", + "ái chà", + "ái dà", + "áng", + "âu là", + "ô hay", + "ô hô", + "ô kê", + "ô kìa", + "ôi chao", + "ôi thôi", + "ông", + "úi", + "úi chà", + "úi dào", + "ý", + "ý chừng", + "ý da", + "đang", + "đi", + "điều", + "đành đạch", + "đáng lí", + "đáng lý", + "đáng lẽ", + "đánh đùng", + "đáo để", + "đây", + "đã", + "đó", + "được", + "đại loại", + "đại nhân", + "đại phàm", + "đại để", + "đến", + "đến nỗi", + "đều", + "để", + "ơ", + "ơ hay", + "ơ kìa", + "ơi", + "ư", + "ạ", + "ạ ơi", + "ấy", + "ầu ơ", + "ắt", + "ắt hẳn", + "ắt là", + "ối dào", + "ối giời", + "ối giời ơi", + "ồ", + "ổng", + "ớ", + "ờ", + "ở", + "ở trên", + "ủa", + "ứ hự", + "ứ ừ", + "ừ", + "ử", + ], + "yo": [ + "a", + "an", + "b\u00e1", + "b\u00ed", + "b\u1eb9\u0300r\u1eb9\u0300", + "f\u00fan", + "f\u1eb9\u0301", + "gbogbo", + "in\u00fa", + "j\u00f9", + "j\u1eb9", + "j\u1eb9\u0301", + "kan", + "k\u00ec", + "k\u00ed", + "k\u00f2", + "l\u00e1ti", + "l\u00e8", + "l\u1ecd", + "mi", + "mo", + "m\u00e1a", + "m\u1ecd\u0300", + "ni", + "n\u00e1\u00e0", + "n\u00ed", + "n\u00edgb\u00e0", + "n\u00edtor\u00ed", + "n\u01f9kan", + "o", + "pad\u00e0", + "p\u00e9", + "p\u00fap\u1ecd\u0300", + "p\u1eb9\u0300l\u00fa", + "r\u1eb9\u0300", + "s\u00ec", + "s\u00ed", + "s\u00edn\u00fa", + "s\u0323", + "ti", + "t\u00ed", + "w\u00e0", + "w\u00e1", + "w\u1ecdn", + "w\u1ecd\u0301n", + "y\u00ec\u00ed", + "\u00e0ti", + "\u00e0w\u1ecdn", + "\u00e9", + "\u00ed", + "\u00f2un", + "\u00f3", + "\u0144", + "\u0144l\u00e1", + "\u1e63e", + "\u1e63\u00e9", + "\u1e63\u00f9gb\u1ecd\u0301n", + "\u1eb9m\u1ecd\u0301", + "\u1ecdj\u1ecd\u0301", + "\u1ecd\u0300p\u1ecd\u0300l\u1ecdp\u1ecd\u0300", + ], + "zh": [ + "\u3001", + "\u3002", + "\u3008", + "\u3009", + "\u300a", + "\u300b", + "\u4e00", + "\u4e00\u5207", + "\u4e00\u5219", + "\u4e00\u65b9\u9762", + "\u4e00\u65e6", + "\u4e00\u6765", + "\u4e00\u6837", + "\u4e00\u822c", + "\u4e03", + "\u4e07\u4e00", + "\u4e09", + "\u4e0a\u4e0b", + "\u4e0d\u4ec5", + "\u4e0d\u4f46", + "\u4e0d\u5149", + "\u4e0d\u5355", + "\u4e0d\u53ea", + "\u4e0d\u5982", + "\u4e0d\u6015", + "\u4e0d\u60df", + "\u4e0d\u6210", + "\u4e0d\u62d8", + "\u4e0d\u6bd4", + "\u4e0d\u7136", + "\u4e0d\u7279", + "\u4e0d\u72ec", + "\u4e0d\u7ba1", + "\u4e0d\u8bba", + "\u4e0d\u8fc7", + "\u4e0d\u95ee", + "\u4e0e", + "\u4e0e\u5176", + "\u4e0e\u5426", + "\u4e0e\u6b64\u540c\u65f6", + "\u4e14", + "\u4e24\u8005", + "\u4e2a", + "\u4e34", + "\u4e3a", + "\u4e3a\u4e86", + "\u4e3a\u4ec0\u4e48", + "\u4e3a\u4f55", + "\u4e3a\u7740", + "\u4e43", + "\u4e43\u81f3", + "\u4e48", + "\u4e4b", + "\u4e4b\u4e00", + "\u4e4b\u6240\u4ee5", + "\u4e4b\u7c7b", + "\u4e4c\u4e4e", + "\u4e4e", + "\u4e58", + "\u4e5d", + "\u4e5f", + "\u4e5f\u597d", + "\u4e5f\u7f62", + "\u4e86", + "\u4e8c", + "\u4e8e", + "\u4e8e\u662f", + "\u4e8e\u662f\u4e4e", + "\u4e91\u4e91", + "\u4e94", + "\u4eba\u5bb6", + "\u4ec0\u4e48", + "\u4ec0\u4e48\u6837", + "\u4ece", + "\u4ece\u800c", + "\u4ed6", + "\u4ed6\u4eba", + "\u4ed6\u4eec", + "\u4ee5", + "\u4ee5\u4fbf", + "\u4ee5\u514d", + "\u4ee5\u53ca", + "\u4ee5\u81f3", + "\u4ee5\u81f3\u4e8e", + "\u4ee5\u81f4", + "\u4eec", + "\u4efb", + "\u4efb\u4f55", + "\u4efb\u51ed", + "\u4f3c\u7684", + "\u4f46", + "\u4f46\u662f", + "\u4f55", + "\u4f55\u51b5", + "\u4f55\u5904", + "\u4f55\u65f6", + "\u4f5c\u4e3a", + "\u4f60", + "\u4f60\u4eec", + "\u4f7f\u5f97", + "\u4f8b\u5982", + "\u4f9d", + "\u4f9d\u7167", + "\u4ffa", + "\u4ffa\u4eec", + "\u5018", + "\u5018\u4f7f", + "\u5018\u6216", + "\u5018\u7136", + "\u5018\u82e5", + "\u501f", + "\u5047\u4f7f", + "\u5047\u5982", + "\u5047\u82e5", + "\u50cf", + "\u516b", + "\u516d", + "\u516e", + "\u5173\u4e8e", + "\u5176", + "\u5176\u4e00", + "\u5176\u4e2d", + "\u5176\u4e8c", + "\u5176\u4ed6", + "\u5176\u4f59", + "\u5176\u5b83", + "\u5176\u6b21", + "\u5177\u4f53\u5730\u8bf4", + "\u5177\u4f53\u8bf4\u6765", + "\u518d\u8005", + "\u518d\u8bf4", + "\u5192", + "\u51b2", + "\u51b5\u4e14", + "\u51e0", + "\u51e0\u65f6", + "\u51ed", + "\u51ed\u501f", + "\u5219", + "\u522b", + "\u522b\u7684", + "\u522b\u8bf4", + "\u5230", + "\u524d\u540e", + "\u524d\u8005", + "\u52a0\u4e4b", + "\u5373", + "\u5373\u4ee4", + "\u5373\u4f7f", + "\u5373\u4fbf", + "\u5373\u6216", + "\u5373\u82e5", + "\u53c8", + "\u53ca", + "\u53ca\u5176", + "\u53ca\u81f3", + "\u53cd\u4e4b", + "\u53cd\u8fc7\u6765", + "\u53cd\u8fc7\u6765\u8bf4", + "\u53e6", + "\u53e6\u4e00\u65b9\u9762", + "\u53e6\u5916", + "\u53ea\u662f", + "\u53ea\u6709", + "\u53ea\u8981", + "\u53ea\u9650", + "\u53eb", + "\u53ee\u549a", + "\u53ef", + "\u53ef\u4ee5", + "\u53ef\u662f", + "\u53ef\u89c1", + "\u5404", + "\u5404\u4e2a", + "\u5404\u4f4d", + "\u5404\u79cd", + "\u5404\u81ea", + "\u540c", + "\u540c\u65f6", + "\u5411", + "\u5411\u7740", + "\u5413", + "\u5417", + "\u5426\u5219", + "\u5427", + "\u5427\u54d2", + "\u5431", + "\u5440", + "\u5443", + "\u5455", + "\u5457", + "\u545c", + "\u545c\u547c", + "\u5462", + "\u5475", + "\u5478", + "\u547c\u54e7", + "\u548b", + "\u548c", + "\u549a", + "\u54a6", + "\u54b1", + "\u54b1\u4eec", + "\u54b3", + "\u54c7", + "\u54c8", + "\u54c8\u54c8", + "\u54c9", + "\u54ce", + "\u54ce\u5440", + "\u54ce\u54df", + "\u54d7", + "\u54df", + "\u54e6", + "\u54e9", + "\u54ea", + "\u54ea\u4e2a", + "\u54ea\u4e9b", + "\u54ea\u513f", + "\u54ea\u5929", + "\u54ea\u5e74", + "\u54ea\u6015", + "\u54ea\u6837", + "\u54ea\u8fb9", + "\u54ea\u91cc", + "\u54fc", + "\u54fc\u5537", + "\u5509", + "\u554a", + "\u5550", + "\u5565", + "\u5566", + "\u556a\u8fbe", + "\u5582", + "\u558f", + "\u5594\u5537", + "\u55e1\u55e1", + "\u55ec", + "\u55ef", + "\u55f3", + "\u560e", + "\u560e\u767b", + "\u5618", + "\u561b", + "\u563b", + "\u563f", + "\u56db", + "\u56e0", + "\u56e0\u4e3a", + "\u56e0\u6b64", + "\u56e0\u800c", + "\u56fa\u7136", + "\u5728", + "\u5728\u4e0b", + "\u5730", + "\u591a", + "\u591a\u5c11", + "\u5979", + "\u5979\u4eec", + "\u5982", + "\u5982\u4e0a\u6240\u8ff0", + "\u5982\u4f55", + "\u5982\u5176", + "\u5982\u679c", + "\u5982\u6b64", + "\u5982\u82e5", + "\u5b81", + "\u5b81\u53ef", + "\u5b81\u613f", + "\u5b81\u80af", + "\u5b83", + "\u5b83\u4eec", + "\u5bf9", + "\u5bf9\u4e8e", + "\u5c06", + "\u5c14\u540e", + "\u5c1a\u4e14", + "\u5c31", + "\u5c31\u662f", + "\u5c31\u662f\u8bf4", + "\u5c3d", + "\u5c3d\u7ba1", + "\u5c82\u4f46", + "\u5df1", + "\u5e76", + "\u5e76\u4e14", + "\u5f00\u5916", + "\u5f00\u59cb", + "\u5f52", + "\u5f53", + "\u5f53\u7740", + "\u5f7c", + "\u5f7c\u6b64", + "\u5f80", + "\u5f85", + "\u5f97", + "\u600e", + "\u600e\u4e48", + "\u600e\u4e48\u529e", + "\u600e\u4e48\u6837", + "\u600e\u6837", + "\u603b\u4e4b", + "\u603b\u7684\u6765\u770b", + "\u603b\u7684\u6765\u8bf4", + "\u603b\u7684\u8bf4\u6765", + "\u603b\u800c\u8a00\u4e4b", + "\u6070\u6070\u76f8\u53cd", + "\u60a8", + "\u6162\u8bf4", + "\u6211", + "\u6211\u4eec", + "\u6216", + "\u6216\u662f", + "\u6216\u8005", + "\u6240", + "\u6240\u4ee5", + "\u6253", + "\u628a", + "\u6291\u6216", + "\u62ff", + "\u6309", + "\u6309\u7167", + "\u6362\u53e5\u8bdd\u8bf4", + "\u6362\u8a00\u4e4b", + "\u636e", + "\u63a5\u7740", + "\u6545", + "\u6545\u6b64", + "\u65c1\u4eba", + "\u65e0\u5b81", + "\u65e0\u8bba", + "\u65e2", + "\u65e2\u662f", + "\u65e2\u7136", + "\u65f6\u5019", + "\u662f", + "\u662f\u7684", + "\u66ff", + "\u6709", + "\u6709\u4e9b", + "\u6709\u5173", + "\u6709\u7684", + "\u671b", + "\u671d", + "\u671d\u7740", + "\u672c", + "\u672c\u7740", + "\u6765", + "\u6765\u7740", + "\u6781\u4e86", + "\u679c\u7136", + "\u679c\u771f", + "\u67d0", + "\u67d0\u4e2a", + "\u67d0\u4e9b", + "\u6839\u636e", + "\u6b63\u5982", + "\u6b64", + "\u6b64\u5916", + "\u6b64\u95f4", + "\u6bcb\u5b81", + "\u6bcf", + "\u6bcf\u5f53", + "\u6bd4", + "\u6bd4\u5982", + "\u6bd4\u65b9", + "\u6cbf", + "\u6cbf\u7740", + "\u6f2b\u8bf4", + "\u7109", + "\u7136\u5219", + "\u7136\u540e", + "\u7136\u800c", + "\u7167", + "\u7167\u7740", + "\u751a\u4e48", + "\u751a\u800c", + "\u751a\u81f3", + "\u7528", + "\u7531", + "\u7531\u4e8e", + "\u7531\u6b64\u53ef\u89c1", + "\u7684", + "\u7684\u8bdd", + "\u76f8\u5bf9\u800c\u8a00", + "\u7701\u5f97", + "\u7740", + "\u7740\u5462", + "\u77e3", + "\u79bb", + "\u7b2c", + "\u7b49", + "\u7b49\u7b49", + "\u7ba1", + "\u7d27\u63a5\u7740", + "\u7eb5", + "\u7eb5\u4ee4", + "\u7eb5\u4f7f", + "\u7eb5\u7136", + "\u7ecf", + "\u7ecf\u8fc7", + "\u7ed3\u679c", + "\u7ed9", + "\u7ee7\u800c", + "\u7efc\u4e0a\u6240\u8ff0", + "\u7f62\u4e86", + "\u8005", + "\u800c", + "\u800c\u4e14", + "\u800c\u51b5", + "\u800c\u5916", + "\u800c\u5df2", + "\u800c\u662f", + "\u800c\u8a00", + "\u80fd", + "\u817e", + "\u81ea", + "\u81ea\u4e2a\u513f", + "\u81ea\u4ece", + "\u81ea\u5404\u513f", + "\u81ea\u5bb6", + "\u81ea\u5df1", + "\u81ea\u8eab", + "\u81f3", + "\u81f3\u4e8e", + "\u82e5", + "\u82e5\u662f", + "\u82e5\u975e", + "\u83ab\u82e5", + "\u867d", + "\u867d\u5219", + "\u867d\u7136", + "\u867d\u8bf4", + "\u88ab", + "\u8981", + "\u8981\u4e0d", + "\u8981\u4e0d\u662f", + "\u8981\u4e0d\u7136", + "\u8981\u4e48", + "\u8981\u662f", + "\u8ba9", + "\u8bba", + "\u8bbe\u4f7f", + "\u8bbe\u82e5", + "\u8be5", + "\u8bf8\u4f4d", + "\u8c01", + "\u8c01\u77e5", + "\u8d76", + "\u8d77", + "\u8d77\u89c1", + "\u8d81", + "\u8d81\u7740", + "\u8d8a\u662f", + "\u8ddf", + "\u8f83", + "\u8f83\u4e4b", + "\u8fb9", + "\u8fc7", + "\u8fd8\u662f", + "\u8fd8\u6709", + "\u8fd9", + "\u8fd9\u4e2a", + "\u8fd9\u4e48", + "\u8fd9\u4e48\u4e9b", + "\u8fd9\u4e48\u6837", + "\u8fd9\u4e48\u70b9\u513f", + "\u8fd9\u4e9b", + "\u8fd9\u4f1a\u513f", + "\u8fd9\u513f", + "\u8fd9\u5c31\u662f\u8bf4", + "\u8fd9\u65f6", + "\u8fd9\u6837", + "\u8fd9\u8fb9", + "\u8fd9\u91cc", + "\u8fdb\u800c", + "\u8fde", + "\u8fde\u540c", + "\u901a\u8fc7", + "\u9075\u7167", + "\u90a3", + "\u90a3\u4e2a", + "\u90a3\u4e48", + "\u90a3\u4e48\u4e9b", + "\u90a3\u4e48\u6837", + "\u90a3\u4e9b", + "\u90a3\u4f1a\u513f", + "\u90a3\u513f", + "\u90a3\u65f6", + "\u90a3\u6837", + "\u90a3\u8fb9", + "\u90a3\u91cc", + "\u9119\u4eba", + "\u9274\u4e8e", + "\u963f", + "\u9664", + "\u9664\u4e86", + "\u9664\u6b64\u4e4b\u5916", + "\u9664\u975e", + "\u968f", + "\u968f\u7740", + "\u96f6", + "\u975e\u4f46", + "\u975e\u5f92", + "\u9760", + "\u987a", + "\u987a\u7740", + "\u9996\u5148", + "\ufe3f", + "\uff01", + "\uff03", + "\uff04", + "\uff05", + "\uff06", + "\uff08", + "\uff09", + "\uff0a", + "\uff0b", + "\uff0c", + "\uff10", + "\uff11", + "\uff12", + "\uff13", + "\uff14", + "\uff15", + "\uff16", + "\uff17", + "\uff18", + "\uff19", + "\uff1a", + "\uff1b", + "\uff1c", + "\uff1e", + "\uff1f", + "\uff20", + "\uff3b", + "\uff3d", + "\uff5b", + "\uff5c", + "\uff5d", + "\uff5e", + "\uffe5", + ], + "zu": [ + "futhi", + "kahle", + "kakhulu", + "kanye", + "khona", + "kodwa", + "kungani", + "kusho", + "la", + "lakhe", + "lapho", + "mina", + "ngesikhathi", + "nje", + "phansi", + "phezulu", + "u", + "ukuba", + "ukuthi", + "ukuze", + "uma", + "wahamba", + "wakhe", + "wami", + "wase", + "wathi", + "yakhe", + "zakhe", + "zonke", + ], +} diff --git a/data_tooling/pii_processing/regex/README.md b/data_tooling/pii_processing/regex/README.md new file mode 100644 index 0000000..43318ad --- /dev/null +++ b/data_tooling/pii_processing/regex/README.md @@ -0,0 +1,9 @@ + +A rulebase is an ordered list of rule groups and the number of times to apply the rule groups. +A rule group is on oredered list of rules of the form (new_label, regex, old_label, before text, after text) +A rule will match if all of regex, old_label, before text and after text matches. + - new_label is the label to tag the matching text + - regex is the regex to use + - old label is the label that this text was previously tagged as. None means to ignore the test. + - before text is some text before the matching pattern. None means to ignore the test. + - after text is some text after the matching pattern. None means to ignore the test. diff --git a/data_tooling/pii_processing/regex/hhn_en.py b/data_tooling/pii_processing/regex/hhn_en.py new file mode 100644 index 0000000..a4c026e --- /dev/null +++ b/data_tooling/pii_processing/regex/hhn_en.py @@ -0,0 +1,18 @@ +# some of the below are from https://github.com/madisonmay/CommonRegex/blob/master/commonregex.py which is under the MIT License +rulebase = [([ + ("AGE", re.compile("\S+ years old|\S+\-years\-old|\S+ year old|\S+\-year\-old"), None, None, None), + ("STREET_ADDRESS", re.compile( + '\d{1,4} [\w\s]{1,20} (?:street|st|avenue|ave|road|rd|highway|hwy|square|sq|trail|trl|drive|dr|court|ct|park|parkway|pkwy|circle|cir|boulevard|blvd)\W?(?=\s|$)', re.IGNORECASE), None, None, None), + ("STREET_ADDRESS", re.compile('P\.? ?O\.? Box \d+', re.IGNORECASE), None, None, None), + ("GOVT_ID", re.compile( + '(?!000|666|333)0*(?:[0-6][0-9][0-9]|[0-7][0-6][0-9]|[0-7][0-7][0-2])[- ](?!00)[0-9]{2}[- ](?!0000)[0-9]{4}'), None, None, None), + ("DISEASE", re.compile("diabetes|cancer|HIV|AIDS|Alzheimer's|Alzheimer|heart disease", re.IGNORECASE), None, None, None), + ("NORP", re.compile("upper class|middle class|working class|lower class", re.IGNORECASE), None, None, None), + ("BIRTH_DEATH_DATE", re.compile('born (?:(?=0.25 +faker +pytest +sentencepiece +spacy +transformers diff --git a/data_tooling/pii_processing/setup.py b/data_tooling/pii_processing/setup.py new file mode 100644 index 0000000..585dd75 --- /dev/null +++ b/data_tooling/pii_processing/setup.py @@ -0,0 +1,239 @@ +#!/usr/bin/env python +""" +Simple check list from AllenNLP repo: https://github.com/allenai/allennlp/blob/master/setup.py + +To create the package for pypi. + +1. Change the version in __init__.py and setup.py. + +2. Commit these changes with the message: "Release: VERSION" + +3. Add a tag in git to mark the release: "git tag VERSION -m'Adds tag VERSION for pypi' " + Push the tag to git: git push --tags origin master + +4. Build both the sources and the wheel. Do not change anything in setup.py between + creating the wheel and the source distribution (obviously). + + For the wheel, run: "python setup.py bdist_wheel" in the top level allennlp directory. + (this will build a wheel for the python version you use to build it - make sure you use python 3.x). + + For the sources, run: "python setup.py sdist" + You should now have a /dist directory with both .whl and .tar.gz source versions of allennlp. + +5. Check that everything looks correct by uploading the package to the pypi test server: + + twine upload dist/* -r pypitest + (pypi suggest using twine as other methods upload files via plaintext.) + + Check that you can install it in a virtualenv by running: + pip install -i https://testpypi.python.org/pypi neuralcoref + +6. Upload the final version to actual pypi: + twine upload dist/* -r pypi + +7. Copy the release notes from RELEASE.md to the tag in github once everything is looking hunky-dory. + +""" +import os +import subprocess +import sys +import contextlib +from distutils.command.build_ext import build_ext +from distutils.sysconfig import get_python_inc +import distutils.util +from distutils import ccompiler, msvccompiler +from setuptools import Extension, setup, find_packages + +def is_new_osx(): + """Check whether we're on OSX >= 10.10""" + name = distutils.util.get_platform() + if sys.platform != "darwin": + return False + elif name.startswith("macosx-10"): + minor_version = int(name.split("-")[1].split(".")[1]) + if minor_version >= 7: + return True + else: + return False + else: + return False + + +PACKAGE_DATA = {'': ['*.pyx', '*.pxd'], + '': ['*.h'],} + + +PACKAGES = find_packages() + + +MOD_NAMES = ['neuralcoref.neuralcoref'] + + + +COMPILE_OPTIONS = { + "msvc": ["/Ox", "/EHsc"], + "mingw32": ["-O2", "-Wno-strict-prototypes", "-Wno-unused-function"], + "other": ["-O2", "-Wno-strict-prototypes", "-Wno-unused-function"], +} + + +LINK_OPTIONS = {"msvc": [], "mingw32": [], "other": []} + + +if is_new_osx(): + # On Mac, use libc++ because Apple deprecated use of + # libstdc + COMPILE_OPTIONS["other"].append("-stdlib=libc++") + LINK_OPTIONS["other"].append("-lc++") + # g++ (used by unix compiler on mac) links to libstdc++ as a default lib. + # See: https://stackoverflow.com/questions/1653047/avoid-linking-to-libstdc + LINK_OPTIONS["other"].append("-nodefaultlibs") + + +USE_OPENMP_DEFAULT = "0" if sys.platform != "darwin" else None +if os.environ.get("USE_OPENMP", USE_OPENMP_DEFAULT) == "1": + if sys.platform == "darwin": + COMPILE_OPTIONS["other"].append("-fopenmp") + LINK_OPTIONS["other"].append("-fopenmp") + PACKAGE_DATA["spacy.platform.darwin.lib"] = ["*.dylib"] + PACKAGES.append("spacy.platform.darwin.lib") + + elif sys.platform == "win32": + COMPILE_OPTIONS["msvc"].append("/openmp") + + else: + COMPILE_OPTIONS["other"].append("-fopenmp") + LINK_OPTIONS["other"].append("-fopenmp") + + +# By subclassing build_extensions we have the actual compiler that will be used which is really known only after finalize_options +# http://stackoverflow.com/questions/724664/python-distutils-how-to-get-a-compiler-that-is-going-to-be-used +class build_ext_options: + def build_options(self): + for e in self.extensions: + e.extra_compile_args += COMPILE_OPTIONS.get( + self.compiler.compiler_type, COMPILE_OPTIONS["other"] + ) + for e in self.extensions: + e.extra_link_args += LINK_OPTIONS.get( + self.compiler.compiler_type, LINK_OPTIONS["other"] + ) + + +class build_ext_subclass(build_ext, build_ext_options): + def build_extensions(self): + build_ext_options.build_options(self) + build_ext.build_extensions(self) + + +# def is_installed(requirement): +# try: +# pkg_resources.require(requirement) +# except pkg_resources.ResolutionError: +# return False +# else: +# return True + +# if not is_installed('numpy>=1.11.0') or not is_installed('spacy>=2.1.0'): +# print(textwrap.dedent(""" +# Error: requirements needs to be installed first. +# You can install them via: +# $ pip install -r requirements.txt +# """), file=sys.stderr) +# exit(1) + +@contextlib.contextmanager +def chdir(new_dir): + old_dir = os.getcwd() + try: + os.chdir(new_dir) + sys.path.insert(0, new_dir) + yield + finally: + del sys.path[0] + os.chdir(old_dir) + + +def generate_cython(root, source): + print('Cythonizing sources') + p = subprocess.call([sys.executable, + os.path.join(root, 'bin', 'cythonize.py'), + source], env=os.environ) + if p != 0: + raise RuntimeError('Running cythonize failed') + + +def is_source_release(path): + return os.path.exists(os.path.join(path, 'PKG-INFO')) + + +def setup_package(): + root = os.path.abspath(os.path.dirname(__file__)) + with chdir(root): + if not is_source_release(root): + generate_cython(root, 'neuralcoref') + + include_dirs = [ + get_python_inc(plat_specific=True), + os.path.join(root, 'include')] + + if (ccompiler.new_compiler().compiler_type == 'msvc' + and msvccompiler.get_build_version() == 9): + include_dirs.append(os.path.join(root, 'include', 'msvc9')) + + ext_modules = [] + for mod_name in MOD_NAMES: + mod_path = mod_name.replace('.', '/') + '.cpp' + extra_link_args = [] + # ??? + # Imported from patch from @mikepb + # See Issue #267. Running blind here... + if sys.platform == 'darwin': + dylib_path = ['..' for _ in range(mod_name.count('.'))] + dylib_path = '/'.join(dylib_path) + dylib_path = '@loader_path/%s/neuralcoref/platform/darwin/lib' % dylib_path + extra_link_args.append('-Wl,-rpath,%s' % dylib_path) + ext_modules.append( + Extension(mod_name, [mod_path], + language='c++', include_dirs=include_dirs, + extra_link_args=extra_link_args)) + + setup(name='neuralcoref', + version='4.0', + description="Coreference Resolution in spaCy with Neural Networks", + url='https://github.com/huggingface/neuralcoref', + author='Thomas Wolf', + author_email='thomwolf@gmail.com', + ext_modules=ext_modules, + classifiers=[ + 'Development Status :: 3 - Alpha', + 'Environment :: Console', + 'Intended Audience :: Developers', + "Intended Audience :: Science/Research", + "License :: OSI Approved :: MIT License", + "Operating System :: POSIX :: Linux", + "Operating System :: MacOS :: MacOS X", + "Operating System :: Microsoft :: Windows", + "Programming Language :: Cython", + "Programming Language :: Python :: 3.6", + "Programming Language :: Python :: 3.7", + "Programming Language :: Python :: 3.8", + "Topic :: Scientific/Engineering", + ], + install_requires=[ + "numpy>=1.15.0", + "boto3", + "requests>=2.13.0,<3.0.0", + "spacy>=2.1.0,<3.0.0"], + setup_requires=['wheel', 'spacy>=2.1.0,<3.0.0'], + python_requires=">=3.6", + packages=PACKAGES, + package_data=PACKAGE_DATA, + keywords='NLP chatbots coreference resolution', + license='MIT', + zip_safe=False, + platforms='any', + cmdclass={"build_ext": build_ext_subclass}) + +if __name__ == '__main__': + setup_package() diff --git a/data_tooling/pii_processing/wip/brill_ner_tagger.py b/data_tooling/pii_processing/wip/brill_ner_tagger.py new file mode 100644 index 0000000..a24b63b --- /dev/null +++ b/data_tooling/pii_processing/wip/brill_ner_tagger.py @@ -0,0 +1,71 @@ + +def learn_brill_transformation_base_tagger(dat, regexs, target_lang, pattern_search_window = 3, ntimes=4): + """ + Input: + dat: the corpus plus init ner tagging in list of dict. Assumes a basic lexcion or other process performed an init NER tag on dat. + regexes: Regexs used to detect and re-tag to reduce the error. + target_lang: used for shingling, conversion, etc. + pattern_search_window: number of words or tags before and after regex matched pattern used to create rules + ntimes: the maximum number of iterations through the alogirthm. + + Output: + rules: ordered list of (regex, matching nearby shingles and tag patterns, tag_wrong => tag_right, score) + + Side effect: dat['predicted_ner'] will be changed to the prediction applied by the returned rules + + Naive algortihm (very memory inefficient) + TODO for participants is to find a faster algortihm, including out of core or dynamic programming (caching ngram). + + loop ntimes or there are no more improvements + given a set of sentences with predict_ner and actual ner, + - find which regex that will match an item that is wrongly tagged by predict_ner, + - find nearby word shingles + - find nearby tag patterns + - add candidate (regex, ngram pattern before, ngram pattern after, tag_wrong => tag_right, number of wrong matches, number of right matches) + find the top n rules that do not have overlapping patterns or shingles, and maximizes the score with number of right > X + apply the top n rules to create a new predict_ner, and continue loop + + """ + ontology_manager = OntologyManager(target_lang=target_lang) + tag2regex = {} + regex_id = 0 + for tag, regex in regexes: + tag2regex[tag] = tag2regex.get(tag, []) + [(regex_id, regex)] + regex_id += 1 + + for times in range(ntimes): + candidates = {} + for d in dat: + text = d['text'] + ner = d['ner'] # the human tagged data + predicted_ner = d['predicted_ner'] + + #find tagging that are wrong + for ent, tag in ner.items(): # sort by sentence order + if tag not in tag2regex: continue + if ent not in predicted_ner predicted_ner[ent] != tag: + regex_id, regex = tag2regex[tag] + match = regex.findall(ent) + if not match: continue + before, after = find_before_after_words(text, ent, pattern_search_window) + before_shingles = ontology_manager._get_shingles(before) + after_shingles = ontology_manager._get_shingles(after) + # before, after correct tags + for before, after in all_combos(before_shingles, after_shingles): + candidates[(before, after, predicted_ner.get(ent), tag, regex_id)] = 0 + + # find tagging that shouldn't be done at all + for ent, tag in predicted_ner.items(): + # do a case where there are no regexes + if tag not in tag2regex: continue + if ent not in ner: + regex_id, regex = tag2regex[tag] + match = regex.findall(ent) + if not match: continue + before, after = find_before_after_words(text, ent, pattern_search_window) + before_shingles = ontology_manager._get_shingles(before) + after_shingles = ontology_manager._get_shingles(after) + # before, after correct tags + for before, after in all_combos(before_shingles, after_shingles): + candidates[(before, after, tag, None, regex_id)] = 0 + diff --git a/data_tooling/pii_processing/wip/processor.py b/data_tooling/pii_processing/wip/processor.py new file mode 100644 index 0000000..416d5fe --- /dev/null +++ b/data_tooling/pii_processing/wip/processor.py @@ -0,0 +1,702 @@ +# coding=utf-8 +# Copyright, 2021 Ontocord, LLC, All rights reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +import copy +from time import time +import numpy as np +from collections import Counter +from itertools import chain +import os +import re +import glob +import math +import difflib +import random +import nltk +from random import choice +import spacy, itertools +from collections import Counter, OrderedDict +trannum = str.maketrans("0123456789", "1111111111") +import torch +from transformers import pipeline, XLMRobertaForTokenClassification, BertForTokenClassification, AutoTokenizer +import sys, os +sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), + os.path.pardir, os.path.pardir))) +from pii_processing.pii.round_trip_trans import RoundTripTranslate +from pii_processing.ontology.ontology_manager import OntologyManager +from pii_processing import neuralcoref + +class Processor (OntologyManager): + """ + A multi-lingual PII/NER processor. + + Pre-processes text into chunks of NER/PII words and coreference tagged words. + + Uses a multilingual ontology and regex rules to obtain PII/NER labels and coreference labels. + + Note that Spacy parsing (and Neuralcoref https://github.com/huggingface/neuralcoref) are performed in English. + We use round-trip translation to perform NER in English, and then translate back to target lang. + + Provides basic multi-lingual functionality using a multilingual ontology and regex rules, round-trip-translation and HF ner transformer pipelines. + + See OntologyManager for the defintion of the upper_ontology. + + """ + # base en spacy models + nlp = None + + + model_loaded = {} + en_basic_person_pronouns = ["you", "your", "yours", "yourself", "we", 'us', "our", "ours", "ourself", "ourselves", 'i', 'my' , 'mine', 'me', 'he', "she", "his", "her", "him", "hers", "himself", "herself"] + + #there are a few multi-lingual ner transfomers. + #which one to use? we could experiment. + #jplu/tf-xlm-r-ner-40-lang + #gunghio/distilbert-base-multilingual-cased-finetuned-conll2003-ner + default_ner_model = ("wietsedv/bert-base-multilingual-cased-finetuned-conll2002-ner", BertForTokenClassification) + + lang2ner_model = { + "sw": ("Davlan/xlm-roberta-large-masakhaner", XLMRobertaForTokenClassification ), # consider using one of the smaller models + "yo": ("Davlan/xlm-roberta-large-masakhaner", XLMRobertaForTokenClassification ), + "ar": ("Davlan/xlm-roberta-base-ner-hrl", XLMRobertaForTokenClassification ), + "de": ("Davlan/xlm-roberta-base-ner-hrl", XLMRobertaForTokenClassification ), + "en": ("Davlan/xlm-roberta-base-ner-hrl", XLMRobertaForTokenClassification ), + "es": ("Davlan/xlm-roberta-base-ner-hrl", XLMRobertaForTokenClassification ), + "it": ("Davlan/xlm-roberta-base-ner-hrl", XLMRobertaForTokenClassification ), + "nl": ("Davlan/xlm-roberta-base-ner-hrl", XLMRobertaForTokenClassification ), + "la": ("Davlan/xlm-roberta-base-ner-hrl", XLMRobertaForTokenClassification ), + "pt": ("Davlan/xlm-roberta-base-ner-hrl", XLMRobertaForTokenClassification ), + "fr": ("Davlan/xlm-roberta-base-ner-hrl", XLMRobertaForTokenClassification ), + "zh": ("Davlan/xlm-roberta-base-ner-hrl", XLMRobertaForTokenClassification ), + } + + def __init__(self, target_lang="en", data_dir=None, tmp_dir=None, max_word_len=4, compound_word_step =3, strip_chars=None, \ + upper_ontology=None, x_lingual_lexicon_by_prefix_file="lexicon_by_prefix.json.gz", target_lang_config_file=None, x_lingual2ner_file=None, \ + connector = "_", en_spacy_models=[], label2label=None): + super().__init__(target_lang=target_lang, data_dir=data_dir, tmp_dir=tmp_dir, max_word_len=max_word_len, compound_word_step = compound_word_step, strip_chars=strip_chars, \ + upper_ontology=upper_ontology, x_lingual_lexicon_by_prefix_file=x_lingual_lexicon_by_prefix_file, target_lang_config_file=target_lang_config_file, x_lingual2ner_file=x_lingual2ner_file, \ + connector = connector, label2label=label2label) + + if True: + #hf stuff. we assume we are working only in CPU mode. + if target_lang in self.lang2ner_model: + model_name, cls = self.lang2ner_model[target_lang] + if model_name in self.model_loaded: + model = self.model_loaded[model_name] + else: + model = cls.from_pretrained(model_name) + model = torch.quantization.quantize_dynamic(model, {torch.nn.Linear}, dtype=torch.qint8) + self.model_loaded[model_name] = model + self.ner_model_pipeline = pipeline("ner", model=model, tokenizer=AutoTokenizer.from_pretrained(model_name)) + else: + model_name, cls = self.default_ner_model + if model_name in self.model_loaded: + model = self.model_loaded[model_name] + else: + model = cls.from_pretrained(model_name) + model = torch.quantization.quantize_dynamic(model, {torch.nn.Linear}, dtype=torch.qint8) + self.ner_model_pipeline = pipeline("ner", model=model, tokenizer=AutoTokenizer.from_pretrained(model_name)) + + #spacy stuff + if en_spacy_models: + self.en_spacy_models = en_spacy_models + else: + self.en_spacy_models = [] + #we are storing the nlp object as a class variable to save on loading time if we create processor objects over and over. + if Processor.nlp is None: + Processor.nlp = spacy.load('en_core_web_lg') + #TODO: we could increase the ontology by adding more words here. + #e.g., conv_dict={"Angela": ["woman", "girl"]} + coref = neuralcoref.NeuralCoref(Processor.nlp.vocab) #, conv_dict + Processor.nlp.add_pipe(coref, name='neuralcoref') + self.en_spacy_models.append(Processor.nlp) + + + def add_chunks_span(self, chunks, new_mention, old_mention, label, coref, chunk2ner, chunk2ref, ref2chunk): + """ add a span to the chunks sequence and update the various ref and NER hashes """ + if old_mention in chunk2ner: + del chunk2ner[old_mention] + if label: + chunk2ner[new_mention] = label + if old_mention in chunk2ref: + old_ref = chunk2ref[old_mention] + ref2chunk[old_ref].remove(old_mention) + if not ref2chunk[old_ref]: + del ref2chunk[old_ref] + del chunk2ref[old_mention] + if new_mention in chunk2ref and coref != chunk2ref[new_mention]: + old_ref = chunk2ref[new_mention] + ref2chunk[old_ref].remove(new_mention) + if not ref2chunk[old_ref]: + del ref2chunk[old_ref] + del chunk2ref[new_mention] + if coref: + chunk2ref[new_mention] = coref + lst = ref2chunk.get(coref, []) + if new_mention not in lst: + ref2chunk[coref] = lst + [new_mention] + chunks.append(new_mention) + + def del_ner_coref(self, old_mention, chunk2ner, chunk2ref, ref2chunk): + """ remove an old_mention from the various NER and ref hashes """ + if old_mention in chunk2ner: + del chunk2ner[old_mention] + if old_mention in chunk2ref: + old_ref = chunk2ref[old_mention] + ref2chunk[old_ref].remove(old_mention) + if not ref2chunk[old_ref]: + del ref2chunk[old_ref] + del chunk2ref[old_mention] + + def _spacy_ner_coref(self, text, nlp, chunk2ner, chunk2ref, ref2chunk, row_id=0, doc_id=0): + """ + Use the spacy English models to create chunks for English text + and gather NER and coreference information. + Note: Spacy's span start and end does NOT correspond to text position in a sentence. + """ + connector = self.connector + pronouns = self.pronouns + person_pronouns = self.person_pronouns + other_pronouns = self.other_pronouns + # Spacy is not as high accuracy as transformers, but we use the spacey neuralcoref model so we can get pronoun coreference groups + # to be able to decide if a name is assocaited with a gender, race, job, etc. this allows us to decide in downstream modules that + # the mentions refer to PII. + doc = nlp(text) + + #store away NOUNs for potential label and coref reference + #rule for promotig a noun span into one considered for further processing: + # - length of the number of words > 2 or length of span > 2 and the span is all uppercase (for abbreviations) + # coref candidates: + # - create an abbreviation from noun phrases as a candidate coref. + # - use either the last two words a span as a candidate coref. + # - use the abbreviation as a candidate coref + for entity in list(doc.noun_chunks) + list(doc.ents) : + chunk2ner[(entity.text, entity.start, entity.end, row_id, doc_id)]= "NOUN" + mention_lower = entity.text.lower() + textArr = mention_lower.split() + if len(textArr) > 2: + short_span = " ".join(textArr[-2:]) + ref2chunk[short_span] = ref2chunk.get(short_span, []) + [(entity.text, entity.start, entity.end, row_id, doc_id)] + non_stopwords = [a for a in textArr if a not in self.stopwords] + if len(non_stopwords) > 2: + abrev = "".join([a[0] for a in non_stopwords]) + ref2chunk[abrev] = ref2chunk.get(abrev, []) + [(entity.text, entity.start, entity.end, row_id, doc_id)] + elif (len(entity.text) >=2 and entity.text == entity.text.upper()): + ref2chunk[entity.text.lower()] = ref2chunk.get(entity.text.lower(), []) + [(entity.text, entity.start, entity.end, row_id, doc_id)] + + #store away coref NOUNs for potential label and coref reference + #same rule as above for promoting a noun span into one considered for further processing. + for cl in list(doc._.coref_clusters) : + mentions = [(entity.text, entity.start, entity.end, row_id, doc_id) for entity in cl.mentions] + mentions.sort(key=lambda e: len(e[0]), reverse=True) + textArr = mentions[0][0].lower().split() + for key in mentions: + chunk2ner[key]= "NOUN" + for mention in mentions: + mention_lower = mention[0].lower() + textArr = mention_lower.split() + if mention_lower not in self.stopwords: + if len(textArr) > 1: + short_span = " ".join(textArr[-2:]) + else: + short_span = textArr[0] + ref2chunk[short_span] = ref2chunk.get(short_span, []) + mentions + non_stopwords = [a for a in textArr if a not in self.stopwords] + if len(non_stopwords) > 2: + abrev = "".join([a[0] for a in non_stopwords]) + ref2chunk[abrev] = ref2chunk.get(abrev, []) + mentions + + #cleanup the chunk2ref, favoring large clusters with coref labels that are longer + seen = {} + corefs = [(a, list(set(b))) for a, b in ref2chunk.items()] + corefs.sort(key=lambda a: a[0].count(" ")+len(a[1]), reverse=True) + for coref, spans in corefs: + new_spans = [] + spans = list(set(spans)) + spans.sort(key=lambda a: a[1]+(1.0/(1.0+a[2]-a[1]))) + spans2 = [] + for span in spans: + if spans2 and spans2[-1][1] >= span[1]: + continue + spans2.append(span) + for span in spans2: + if span in seen: continue + seen[span] = 1 + new_spans.append(span) + del ref2chunk[coref] + if new_spans: + new_coref = [s[0] for s in new_spans] + new_coref.sort(key=lambda a: len(a), reverse=True) + ref2chunk[new_coref[0].lower()] = list(set(list(ref2chunk.get(new_coref[0].lower(), [])) + new_spans)) + + chunk2ref.clear() + for a, b1 in ref2chunk.items(): + for b in b1: + chunk2ref[b] = a + + # expand coref information by using the most common coref label in a cluster + if True: + for cl in list(doc._.coref_clusters) : + mentions = [(entity.text, entity.start, entity.end, row_id, doc_id) for entity in cl.mentions] + all_mentions = list(set(itertools.chain(*[ref2chunk[chunk2ref[mention]] for mention in mentions if mention in chunk2ref]))) + corefs = [chunk2ref[mention] for mention in mentions if mention in chunk2ref] + if corefs: + coref = Counter(corefs).most_common()[0][0] + else: + coref = cl.main.text.lower() + for mention in all_mentions: + if mention not in chunk2ner: + chunk2ner[mention] = 'NOUN' + old_ref = chunk2ref.get(mention) + if old_ref and mention in ref2chunk[old_ref]: + ref2chunk[old_ref].remove(mention) + if not ref2chunk[old_ref]: + del ref2chunk[old_ref] + chunk2ref[mention] = coref + if mention not in ref2chunk[coref]: + ref2chunk[coref].append(mention) + + #expand ner labels based on coref matches + for entity in list(doc.ents) : + mention = (entity.text, entity.start, entity.end, row_id, doc_id) + chunk2ner[mention]= entity.label_ + if mention in chunk2ref: + coref = chunk2ref[mention] + for mention in ref2chunk[coref]: + chunk2ner[mention] = entity.label_ + + # overwrite all ner labels in the coref cluster to PERSON if there is a person pronoun + if True: + for cl in list(doc._.coref_clusters): + cluster_text_list = set([m.text.lower() for m in cl.mentions if m.text != 'US']) + found=False + # since we are doing English, we can do basic person pronoun matching + for pr in self.en_basic_person_pronouns: + if pr in cluster_text_list: + found = True + break + if found: + label = "PERSON" + for m in cl.mentions: + chunk2ner[(m.text, m.start, m.end, row_id, doc_id)] = label + return self._cleanup_chunks(text, chunk2ner, chunk2ref, ref2chunk, row_id, doc_id, doc, mention_access_fn=lambda a: a.text) + + def _hf_ner(self, text, chunk2ner, chunk2ref, ref2chunk, row_id=0, doc_id=0): + """ + run the text through a Huggingface ner pipeline for the target_lang text. + any tags found by this method that contradicts what was already tagged will take precedence. + For example, if we previously had categorized a noun as an ORG (which spacy sometimes does), but + the HF ner pipeline categorized it as a PERSON, then the tag will be changed to PERSON. + """ + connector = self.connector + pronouns = self.pronouns + person_pronouns = self.person_pronouns + other_pronouns = self.other_pronouns + results = self.ner_model_pipeline(text) + results.sort(lambda a: a['start']) + prev_word = [] + prev_label = None + prev_start = None + for ner_result in results: + if ner_result['entity'].startswith('I-'): + if prev_label and ner_result['entity'].split("-")[-1].upper() != prev_label: + start = ner_result['start'] + if not is_cjk and text[start] != ' ': + for j in range(1, start): + if start - j == -1 or text[start-j] == ' ': + start = max(start -j, 0) + break + if text[start] == ' ': start += 1 + prev_word.append(text[start:].strip().split(" ",1)[0]) + if ner_result['entity'].startswith('B-'): + start = ner_result['start'] + if not is_cjk and text[start] != ' ': + for j in range(1, start): + if start - j == -1 or text[start-j] == ' ': + start = max(start -j, 0) + break + if text[start] == ' ': start += 1 + if prev_word: + ner_word = " ".join(prev_word) + mention = (ner_word, prev_start, prev_start+len(ner_word), row_id, doc_id) + if mention not in chunk2ner or prev_label not in chunk2ner[mention]: + if prev_label == 'PER': prev_label = 'PERSON' + chunk2ner[mention] = prev_label + prev_word = [] + prev_label = None + prev_start = None + prev_word.append(text[start:].strip().split(" ",1)[0]) + prev_label = ner_result['entity'].split("-")[-1].upper() + if prev_label == "MISC": + prev_label = "NOUN" + + prev_start = ner_result['start'] + if prev_word: + ner_word = " ".join(prev_word) + mention = (ner_word, prev_start, prev_start+len(ner_word), row_id, doc_id) + if mention not in chunk2ner or prev_label not in chunk2ner[mention]: + if prev_label == 'PER': prev_label = 'PERSON' + chunk2ner[mention] = prev_label + + return self._cleanup_chunks(text, chunk2ner, chunk2ref, ref2chunk, row_id, doc_id) + + def _rule_based_ner_coref(self, text, chunks2, chunk2ner, chunk2ref, ref2chunk, row_id, doc_id, number_regex_cycle=1, do_ontology=True): + """ + do rule based ner and coref using regex, ontology and connect coreference using pronouns around a noun. + regex matches can be word based or rule based. + regex matching prefers patterns that also matches surronding contexts: [regex for street address], surronding words: ['live', 'at'] + rule based matching. e.g., rule chaining: + (Rd.|Street|Ave.) => + President => + *the numbers after the NER labels represents a unique id for the tag in the document. + + NOTE: We may want to refactor this code to use Spacy's rule based processing and regex processing. But it may not be possible + to do so for multiple languages at the same time, as here. + """ + connector = self.connector + pronouns = self.pronouns + person_pronouns = self.person_pronouns + other_pronouns = self.other_pronouns + ner_regexes = self.ner_regexes + # first do matching to the lexicon/ontology + idx = 0 + label2word = {} + if do_ontology: + dat = self.tokenize(text) + word2label = dict([(a[0].replace(connector, " "),b) for a, b in dat['chunk2ner'].items()]) + for x, label2 in word2label.items(): + text = text.replace(x.strip(), "<"+label2.upper()+str(idx)+">") + if "<" in x and ">" in x: + x = ' '.join([a if a not in label2word else label2word[a] for a in x.strip().split()]) + label2word["<"+label2.upper()+str(idx)+">"] = (x.strip(), label2) + idx += 1 + else: + word2label = {} + if not chunks2: + chunks2 = [(None, [text,])] + print (text) + print (word2label) + print (label2word) + # now do regex for number_regex_cycle times + for rng in range(number_regex_cycle): + chunks = [] + len_chunks2 = len(chunks2) + print (chunks2) + for spanIdx, mention in enumerate(chunks2): + label = chunk2ner.get(mention) + coref = chunk2ref.get(mention) + self.del_ner_coref(mention, chunk2ner, chunk2ref, ref2chunk) + span_str = mention[0] + prev_words = [] + #regex matching and + #check surronding words for additional contexts when doing regexes. + #prioritize those rules first that matching surronding words. + #Presidio does weighting, but this is too complicated for our needs + wordsDict = dict([(s.strip(self.strip_chars),1) for s in span_str.lower().split()]) #TODO, we can stem the surrounding word and wordsDict + ner_regex_list1 = [] + ner_regex_list2 = [] + print (ner_regexes) + for label2, regex0, _, surronding in ner_regexes: + found=False + for surronding_word in surronding: + if surronding_word in wordsDict: + ner_regex_list1.append((label2, regex0)) + found=True + break + if not found: + ner_regex_list2.append((label2, regex0)) + for label2, regex0 in ner_regex_list1 + ner_regex_list2: + for x in regex0.findall(span_str): + if type(x) != str: continue + span_str = span_str.replace(x.strip(), "<"+label2.upper()+str(idx)+">") + if "<" in x and ">" in x: + # expand out embedded tags. => will associated the word corresponding to first and last name to person. + x = ' '.join([a if a not in label2word else label2word[a] for a in x.strip().split()]) + label2word["<"+label2.upper()+str(idx)+">"] = (x.strip(), label2) + idx += 1 + + wordArr = [w2.strip(self.strip_chars) for w2 in span_str.split()] + for word in wordArr: + #first do poor man's coref + #let's look at the previous nouns/ner we found + found_chunks = [] + if not coref and word in pronouns: + for idx in [i for i in self.coref_window if i <0]: + if chunk2ner.get(chunks[idx]) and chunks[idx][0].lower() not in pronouns: + if word in person_pronouns and 'PERSON' not in self.ontology.get(chunk2ner.get(chunks[idx]), []): + continue + coref = chunk2ref.get(chunks[idx]) + found_chunks.append(chunks) + break + #now do the window between spans both prior and next + if not coref and word in pronouns: + for idx in [spanIdx + i for i in self.coref_window]: + if idx >= 0 and idx < len_chunks2 and chunk2ner.get(chunks2[idx]) and chunks2[idx][0].lower() not in pronouns: + if word in person_pronouns and 'PERSON' not in self.ontology.get(chunk2ner.get(chunks2[idx]), []): + continue + coref = chunk2ref.get(chunks2[idx]) + found_chunks.append(chunks) + break + #create a new coref group if there isn't one + if not coref and found_chunks: + coref = found_chunks[0][0].lower() + + #now see if the word is already regex labeled or is in the ontology and label accordingly + if word in label2word or word in word2label: + if prev_words: + new_word = " ".join(prev_words) + len_new_word = len(new_word) + self.add_chunks_span(chunks, (new_word, 0 if not chunks else chunks[-1][2]+1, len_new_word if not chunks else chunks[-1][2]+1+len_new_word, row_id, doc_id), None, label, coref, chunk2ner, chunk2ref, ref2chunk) + new_word = label2word[word][0] if word in label2word else word.replace(connector, " ") + len_new_word = len(new_word) + new_label = label2word[word][1] if word in label2word else (word2label[word] if word in word2label else label) + self.add_chunks_span(chunks, (word, 0 if not chunks else chunks[-1][2]+1, len_new_word if not chunks else chunks[-1][2]+1+len_new_word, row_id, doc_id), None, new_label, coref, chunk2ner, chunk2ref, ref2chunk) + prev_words = [] + continue + prev_words.append(word) + + if prev_words: + new_word = " ".join(prev_words) + len_new_word = len(new_word) + self.add_chunks_span(chunks, (new_word, 0 if not chunks else chunks[-1][2]+1, len_new_word if not chunks else chunks[-1][2]+1+len_new_word, row_id, doc_id), None, label, coref, chunk2ner, chunk2ref, ref2chunk) + + #let's prepare for the next loop + chunks2 = chunks + + text = " ".join([c[0] for c in chunks]) + print ("basic parse returns", text) + return self._cleanup_chunks(text, chunk2ner, chunk2ref, ref2chunk, row_id, doc_id) + + + def _cleanup_chunks(self, text, chunk2ner, chunk2ref, ref2chunk, row_id=0, doc_id=0, doc=None, mention_access_fn=None): + """ + cleanup the chunks and references by tagging nouns in the same group the same or similar ner label. + flatten mention sequences to remove embedded mentions. + """ + connector = self.connector + pronouns = self.pronouns + person_pronouns = self.person_pronouns + other_pronouns = self.other_pronouns + if doc is None: doc = text + if mention_access_fn is None: + mention_access_fn = lambda a: a + + # propogate the ner label to everything in the same coref group + for coref, seq in ref2chunk.items(): + labels = [chunk2ner[mention] for mention in seq if mention in chunk2ner and chunk2ner[mention] != 'NOUN'] + if labels: + label = Counter(labels).most_common()[0][0] + for mention in seq: + if mention in chunk2ner and label not in self.upper_ontology.get(chunk2ner[mention], []): chunk2ner[mention] = label + + #add other words from the document into a sequence of the form (word, start_idx, end_idx, row_id, doc_id) + chunks = [a for a in chunk2ner.items() if a[0][-2] == row_id and a[0][-1] == doc_id] + chunks.sort(key=lambda a: a[0][1]+(1.0/(1.0+a[0][2]-a[0][1]))) + chunks2 = [] + + # there may be overlapping mentions of noun phrases or ner labeled phrases. + # we clear duplicates and subsumed mentions + for mention, label in chunks: + if not chunks2 or (chunks2[-1][2] <= mention[1]): + if not chunks2 or chunks2[-1][2] < mention[1]: + self.add_chunks_span(chunks2, (mention_access_fn(doc[0 if not chunks2 else chunks2[-1][2]: mention[1]]), 0 if not chunks2 else chunks2[-1][2], mention[1], row_id, doc_id), None, None, None, chunk2ner, chunk2ref, ref2chunk) + self.add_chunks_span(chunks2, mention, None, label, chunk2ref.get(mention), chunk2ner, chunk2ref, ref2chunk) + elif chunks2[-1][2] > mention[1] and chunks2[-1][1] <= mention[1]: + if chunk2ner.get(chunks2[-1]) not in (None, '', 'NOUN'): + self.del_ner_coref(mention, chunk2ner, chunk2ref, ref2chunk) + continue + elif label in (None, '', 'NOUN'): + self.del_ner_coref(mention, chunk2ner, chunk2ref, ref2chunk) + continue + old_mention = chunks2.pop() + oldSpan = old_mention[0] + oldLabel = chunk2ner.get(old_mention) + oldAnaphore = chunk2ref.get(old_mention) + sArr = oldSpan.split(mention[0], 1) + self.del_ner_coref(old_mention, chunk2ner, chunk2ref, ref2chunk) + s0 = sArr[0].strip() + if s0: + self.add_chunks_span(chunks2, (s0, old_mention[1], mention[1], row_id, doc_id), None, oldLabel if s0 in pronouns or (len(s0) > 1 and s0 not in self.stopwords) else None, oldAnaphore if s0 in pronouns or (len(s0) > 1 and s0 not in self.stopwords) else None, chunk2ner, chunk2ref, ref2chunk) + self.add_chunks_span(chunks2, mention, None, label, oldAnaphore if not chunk2ref.get(mention) else chunk2ref.get(mention), chunk2ner, chunk2ref, ref2chunk) + if len(sArr) > 1: + s1 = sArr[1].strip() + if s1: + self.add_chunks_span(chunks2, (s1, mention[2], old_mention[2], row_id, doc_id), None, oldLabel if s1 in pronouns or (len(s1) > 1 and s1 not in self.stopwords) else None, oldAnaphore if s1 in pronouns or (len(s1) > 1 and s1 not in self.stopwords) else None, chunk2ner, chunk2ref, ref2chunk) + len_doc = len(doc) + print (chunks2) + if chunks2[-1][2] < len_doc: + self.add_chunks_span(chunks2, (mention_access_fn(doc[chunks2[-1][2]:]), chunks2[-1][2], len_doc, row_id, doc_id), None, None, None, chunk2ner, chunk2ref, ref2chunk) + + #chunks2 now has non overlapping mentions. + #reset the indexes for chunks to be per character index. + chunks = [] + len_chunks2 = len(chunks2) + for spanIdx, mention in enumerate(chunks2): + label = chunk2ner.get(mention) + coref = chunk2ref.get(mention) + self.del_ner_coref(mention, chunk2ner, chunk2ref, ref2chunk) + new_word = mention[0] + len_new_word = len(new_word) + self.add_chunks_span(chunks, (new_word, 0 if not chunks else chunks[-1][2]+1, len_new_word if not chunks else chunks[-1][2]+1+len_new_word, row_id, doc_id), None, label, coref, chunk2ner, chunk2ref, ref2chunk) + text = " ".join([c[0] for c in chunks]) + + # propogate the ner label to everything in the same coref group + for coref, seq in ref2chunk.items(): + labels = [chunk2ner[mention] for mention in seq if mention in chunk2ner and chunk2ner[mention] != 'NOUN'] + if labels: + label = Counter(labels).most_common()[0][0] + for mention in seq: + if mention in chunk2ner and label not in self.upper_ontology.get(chunk2ner[mention], []): chunk2ner[mention] = label + + return text, chunks, chunk2ner, chunk2ref, ref2chunk + + def analyze_with_ner_coref(self, text, target_lang=None, row_id=0, doc_id=0, chunk2ner=None, ref2chunk=None, chunk2ref=None, do_preprocess_basic=False, do_post_process_regex=False, do_spacy=True, do_transformer=False): + """ + Process multilingual NER on spans/chunks of text. Perform some coreference + matching (anaphoric matching). Use rules to expand and cleanup the coref and ner + labeling. + + :arg text: The plaint text input or a JSON representation or a dict. + If in JSON or dict form, the data will include row_id, doc_id, chunk2ner, ref2chunk and chunk2ref as described below. + :arg row_id: Some unique id representing the sentence in a document or dataset. + :arg doc_id: some unique document or dataset # + :arg chunk2ner: a dict that maps the chunk to an ner label, such as PERSON, ORG, etc. + :arg ref2chunk: a coreference group label that maps to the applicable chunk or chunks + :arg chunk2ref: a dict that maps a chunk to a coreference group. + + Return a dict of form: + {'text': text, + 'chunks':chunks, + 'chunk2ner': chunk2ner, + 'ref2chunk': ref2chunk, + 'chunk2ref': chunk2ref}. + + Each chunks (aka spans) is in the form of a list of tuples: + [(text_span, start_id, end_id, doc_id, row_id), ...]. + + A note on terminology: A span or a chunk is a segment of text of one or more words. + A mention is a chunk that is recognized by some processor. + """ + connector = self.connector + pronouns = self.pronouns + person_pronouns = self.person_pronouns + other_pronouns = self.other_pronouns + ret={} + if ref2chunk is None: + ref2chunk = {} + if chunk2ref is None: + chunk2ref = {} + if chunk2ner is None: + chunk2ner = {} + if not text: return ret + if type(text) is dict: + ret = text + elif text[0] == '{' and text[-1] == '}': + ret = json.loads(text) + if ret: + text = ret['text'] + doc_id = ret.get('doc_id', doc_id) + row_id = ret.get('id', row_id) + chunk2ner = ret.get('chunk2ner', chunk2ner) + chunk2ref = ret.get('chunk2ref', chunk2ref) + ref2chunk = ret.get('ref2chunk', ref2chunk) + text = text.strip() + if target_lang is None: + target_lang = self.target_lang + assert target_lang == self.target_lang or target_lang == 'en', "Can only processes in English or the target_lang" + is_cjk = target_lang in ("zh", "ja", "ko") + #we need to be able to find potential words broken on spaces for cjk langauges so we tokenize using mt5 + if is_cjk and self.t5_tokenizer is not None and self.detect_cjk(text): + text = " ".join(self.mt5_tokenize(text)).replace(self.mt5_underscore+" ", self.mt5_underscore).strip() + chunks = [] + chunks2 = [] + chunks3 = [] + #currently the ordering of the processing will determine precedence. So, for example, a transformer model's prediction + #will take precedence over thhe basic process or spacy process + #TODO: We could rank decisions by the spacy model, HF ner pipeline and the regex, ontology matcher and choose the max scoring decision. + + if do_preprocess_basic: + #first do rule based ner and coref processing using regex, ontology/lexicon, etc. on the whole text + text, chunks, chunk2ner, chunk2ref, ref2chunk = self._rule_based_ner_coref(text, [(text, 0, len(text), row_id, doc_id)], chunk2ner, chunk2ref, ref2chunk, row_id, doc_id, do_ontology=True) + + #run the spacy model if this is English to get coreference and NER info. + if target_lang == "en" and do_spacy: + for nlp in self.en_spacy_models: + text, chunks2, chunk2ner, chunk2ref, ref2chunk = self._spacy_ner_coref(text, nlp, chunk2ner, chunk2ref, ref2chunk, row_id=row_id, doc_id=doc_id) + + #now let's run a HF transformer ner pipeline model to refine the tags + if do_transformer and self.ner_model_pipeline is not None: + text, chunks3, chunk2ner, chunk2ref, ref2chunk = self._hf_ner(text, chunk2ner, chunk2ref, ref2chunk) + + if do_post_process_regex: + #do fnal rule based ner without ontology/lexicon matching. this will permit us to do patterns + #based on prior matches. + text, chunks, chunk2ner, chunk2ref, ref2chunk = self._rule_based_ner_coref(text, [(text, 0, len(text), row_id, doc_id)], chunk2ner, chunk2ref, ref2chunk, row_id, doc_id, do_ontology=False) + + # do one final cleanup and resolve any conflicts + else: + text, chunks, chunk2ner, chunk2ref, ref2chunk = self._cleanup_chunks(text, chunk2ner, chunk2ref, ref2chunk, row_id, doc_id) + + ret['doc_id'] = doc_id + ret['id'] = row_id + ret['text'] = " ".join([c[0] for c in chunks]) + ret['chunks'] = chunks + ret['chunk2ner'] = chunk2ner + ret['chunk2ref'] = chunk2ref + ret['ref2chunk'] = ref2chunk + return ret + + def process(self, text="", batch=None, *args, **argv): + """ + Process a single row of text or a batch. Performs basic chunking into roughly ner and non-ner phrases, and corefrence identification. + The ner and coref information is used by downstream modules for PII detection. + """ + row_id=argv.get('row_id',0) + doc_id=argv.get('doc_id',0) + chunk2ner=argv.get('chunk2ner') + ref2chunk=argv.get('ref2chunk') + chunk2ref=argv.get('chunk2ref') + target_lang = argv.get('target_lang', self.target_lang) + if batch is None: + return_single = True + batch = [text] + else: + return_single = False + ret = None + if type(batch[0]) is str: + if batch[0][0] == '{' and batch[0][-1] == '}': + batch = [json.loads(text) for text in batch] + else: + batch = [{'id': _id+row_id, 'doc_id': doc_id, 'text': text} for _id, text in enumerate(batch)] + if 'do_round_trip_trans' in argv and target_lang != 'en': + if not hasattr(self, 'trans'): + self.trans = Translate(target_lang=target_lang) + batch_en = [self.trans.translate(text, target_lang='en') for text in batch] + batch_en = [self.analyze_with_ner_coref(text, target_lang='en') for text in batch_en] + batch_trans = [self.trans.translate(text, target_lang=target_lang) for text in batch_en] + batch= [self.analyze_with_ner_coref(text, target_lang=target_lang, chunk2ner=chunk2ner, ref2chunk=ref2chunk, chunk2ref=chunk2ref, do_preprocess_basic=argv.get('do_preprocess_basic',False), do_post_process_regex=argv.get('do_post_process_regex',False), do_spacy=argv.get('do_spacy',True), do_transformer=argv.get('do_transformer',False)) for text in batch] + ret = self.merge_ner_coref_predictions([batch, batch_trans]) #TODO + if ret is None: + ret = [self.analyze_with_ner_coref(text, target_lang=target_lang, chunk2ner=chunk2ner, ref2chunk=ref2chunk, chunk2ref=chunk2ref, do_preprocess_basic=argv.get('do_preprocess_basic',False), do_post_process_regex=argv.get('do_post_process_regex',False), do_spacy=argv.get('do_spacy',True), do_transformer=argv.get('do_transformer',False) ) for text in batch] + if return_single: + return ret[0] + else: + return ret + +if __name__ == "__main__": + if "-t" in sys.argv: + target_lang = sys.argv[sys.argv.index("-t")+1] + sentence = sys.argv[sys.argv.index("-t")+2] + pii_processor = Processor(target_lang=target_lang) + print (pii_processor.process(sentence)) diff --git a/data_tooling/pii_processing/wip/round_trip_trans.py b/data_tooling/pii_processing/wip/round_trip_trans.py new file mode 100644 index 0000000..cb0ef3c --- /dev/null +++ b/data_tooling/pii_processing/wip/round_trip_trans.py @@ -0,0 +1,108 @@ +# coding=utf-8 +# Copyright, 2021 Ontocord, LLC, All rights reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +import copy +from time import time +import numpy as np +from collections import Counter +from itertools import chain +import os +import re +import glob +import math +from transformers import M2M100ForConditionalGeneration, M2M100Tokenizer +import random +import torch +from collections import Counter, OrderedDict +trannum = str.maketrans("0123456789", "1111111111") +import sys, os +sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), + os.path.pardir, os.path.pardir, os.path.pardir))) + +class RoundTripTranslate: + """ + A class for translating text from English to another language, and vice versa. Uses M2M100. + Can be used to create paraphrases in various languages, and manipulating the text in English and then back to the target langauge + to provide multi-lingual capabilities to English only text processing. + """ + + def __init__(self, target_lang='fr'): + """ + Create a translation engine from English to the target_lang, and + vice versa. Useful for round trip translation, paraphrase + generation and manipulation and extraction in English and + translation back to target_lang. + """ + self.target_lang = target_lang + self.model = M2M100ForConditionalGeneration.from_pretrained("facebook/m2m100_418M") + # we assume we are working only in CPU mode + self.model = torch.quantization.quantize_dynamic(self.model, {torch.nn.Linear}, dtype=torch.qint8) + self.tokenizer = M2M100Tokenizer.from_pretrained("facebook/m2m100_418M") + #todo, check if target_lang in the 100 lang list + + #TODO: We can vary the probabilties and sampling used to generate in order to get multiple paraphrases + def translate_to_en(self, text): + self.tokenizer.src_lang = self.target_lang + encoded = self.tokenizer(text, return_tensors="pt") + generated_tokens = self.model.generate(**encoded, forced_bos_token_id=self.tokenizer.get_lang_id("en")) + return self.tokenizer.batch_decode(generated_tokens, skip_special_tokens=True) + + def translate_from_en(self, text): + self.tokenizer.src_lang = "en" + encoded = self.tokenizer(text, return_tensors="pt") + generated_tokens = self.model.generate(**encoded, forced_bos_token_id=self.tokenizer.get_lang_id(self.target_lang)) + return self.tokenizer.batch_decode(generated_tokens, skip_special_tokens=True) + + def translate(self, sentence, fr='en', to=None): + if fr == self.target_lang: + to = 'en' + if to == self.target_lang: + fr = 'en' + if fr == 'en': + if to == None: + to = self.target_lang + if to != self.target_lang: + raise RuntimeError("one of 'from' or 'to' must be in the target lang") + if to == 'en': + if fr == None: + fr = self.target_lang + if fr != self.target_lang: + raise RuntimeError("one of 'from' or 'to' must be in the target lang") + if fr != "en" and to != "en": + raise RuntimeError("one of 'from' or 'to' must be in english") + if fr == to: + return sentence + if fr == "en": + return self.translate_from_en(sentence)[0] + return self.translate_to_en(sentence)[0] + + def round_trip_translate(self, sentence, lang='en'): + if lang not in ('en', self.target_lang): + raise RuntimeError("lang must be in english or the target_lang") + if lang == self.target_lang: + return self.translate(self.translate(sentence, fr=lang, to='en'), fr='en', to=lang) + return self.translate(self.translate(sentence, fr=lang, to=self.target_lang), fr=self.target_lang, to=lang) + +if __name__ == "__main__": + if "-t" in sys.argv: + target_lang = sys.argv[sys.argv.index("-t")+1] + sentence = sys.argv[sys.argv.index("-t")+2] + rt = RoundTripTranslate(target_lang=target_lang) + print (rt.translate(sentence, fr="en", to=target_lang)) + elif "-f" in sys.argv: + target_lang = sys.argv[sys.argv.index("-f")+1] + sentence = sys.argv[sys.argv.index("-f")+2] + rt = RoundTripTranslate(target_lang=target_lang) + print (rt.translate(sentence, fr=target_lang, to="en")) + diff --git a/data_tooling/poetry.lock b/data_tooling/poetry.lock new file mode 100644 index 0000000..85df239 --- /dev/null +++ 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= "^3.7.10" + +datasets = "^1.12.1" +transformers = "^4.12.3" +nltk = "^3.6.5" +scikit-learn = "^1.0.1" +fsspec = "^2021.11.0" +kenlm = {url = "https://github.com/kpu/kenlm/archive/master.zip", optional = true} +networkx = "^2.6.3" +typer = "^0.4.0" +simhash = "^2.0.0" +mpire = "^2.3.2" +annoy = "^1.17.0" + +[tool.poetry.dev-dependencies] +pdbpp = "^0.10.2" +isort = "^5.6.4" +flake8 = "^3.8.4" +black = "^21.7b0" +pytest = "^6.2.4" +jupyterlab = "^3.0.16" + +[tool.poetry.extras] +kenlm = ["kenlm"] + +[tool.isort] +profile = 'black' +treat_comments_as_code = "# %%" diff --git a/data_tooling/requirements.txt b/data_tooling/requirements.txt new file mode 100644 index 0000000..24e425c --- /dev/null +++ b/data_tooling/requirements.txt @@ -0,0 +1,14 @@ +dataset>=1.5.0 +datasets>=1.8.0 +fasttext>=0.9.2 +fsspec +ftfy +indexed_gzip>=1.6.1 +indexed_gzip>=1.6.1 +langid>=1.1.6 +nltk +scikit-learn +sentencepiece +sqlalchemy>=1.4.20 +transformers +wordfreq diff --git a/requirements.txt b/requirements.txt new file mode 100644 index 0000000..837876c --- /dev/null +++ b/requirements.txt @@ -0,0 +1,18 @@ +fsspec +langid +dataset>=1.5.0 +datasets>=1.8.0 +fasttext>=0.9.2 +ftfy +indexed_gzip>=1.6.1 +indexed_gzip>=1.6.1 +langid>=1.1.6 +nltk +scikit-learn +sentencepiece +sqlalchemy>=1.4.20 +transformers +wordfreq +sentence-transformers +faker + diff --git a/test.py b/test.py new file mode 100644 index 0000000..77a84de --- /dev/null +++ b/test.py @@ -0,0 +1,6 @@ +import nltk +from TextAugment import TextAugment + +processor = TextAugment() +docs, chunks = processor.process_ner(src_lang="vi", do_ontology=False, do_backtrans=False, cutoff=30) +print(docs) \ No newline at end of file diff --git a/utils/CharManager.py b/utils/CharManager.py new file mode 100644 index 0000000..10b9562 --- /dev/null +++ b/utils/CharManager.py @@ -0,0 +1,10 @@ +class CharManager: + strip_chars = " ,،、{}[]|()\"'“”《》«»" + punc_char = ".?!:;?。…" + special_char = ",{}[]()|\\\"'“”《》«»~!@#$%^&*{}[]()_+=-0987654321`<>," \ + "、،./?':;“”\"\t\n\\πه☆●¦″．۩۱（☛₨➩°・■↑☻、๑º‹€σ٪’Ø·−♥ıॽ،٥《‘©。¨﴿！★×✱´٬→±x" \ + "：¹？£―▷ф¡Г♫∟™ª₪®▬「—¯；¼❖․ø•�」٣，٢◦‑←§١ー٤）˚›٩▼٠«¢¸٨³½˜٭ˈ¿¬ι۞⌐¥►†ƒ∙²»¤…﴾⠀》′ا✓→¶' " + junk = set( + ",{}[]()|\\\"'“”《》«»~!@#$%^&*{}[]()_+=-0987654321`<>," + "、،./?':;“”\"\t\n\\πه☆●¦″．۩۱（☛₨➩°・■↑☻、๑º‹€σ٪’Ø·−♥ıॽ،٥《‘©。¨﴿！★×✱´٬→±x" + "：¹？£―▷ф¡Г♫∟™ª₪®▬「—¯；¼❖․ø•�」٣，٢◦‑←§١ー٤）˚›٩▼٠«¢¸٨³½˜٭ˈ¿¬ι۞⌐¥►†ƒ∙²»¤…﴾⠀》′ا✓→¶'") \ No newline at end of file diff --git a/utils/LogingHandler.py b/utils/LogingHandler.py new file mode 100644 index 0000000..8e6fa63 --- /dev/null +++ b/utils/LogingHandler.py @@ -0,0 +1,57 @@ +import logging +import tqdm + + +class LoggingHandler(logging.Handler): + def __init__(self, level=logging.NOTSET): + super().__init__(level) + + def emit(self, record): + try: + msg = self.format(record) + tqdm.tqdm.write(msg) + self.flush() + except (KeyboardInterrupt, SystemExit): + raise + except: + self.handleError(record) + + +def install_logger( + given_logger, level=logging.WARNING, fmt="%(levelname)s:%(name)s:%(message)s" +): + """ Configures the given logger; format, logging level, style, etc """ + import coloredlogs + + def add_notice_log_level(): + """ Creates a new 'notice' logging level """ + # inspired by: + # https://stackoverflow.com/questions/2183233/how-to-add-a-custom-loglevel-to-pythons-logging-facility + NOTICE_LEVEL_NUM = 25 + logging.addLevelName(NOTICE_LEVEL_NUM, "NOTICE") + + def notice(self, message, *args, **kws): + if self.isEnabledFor(NOTICE_LEVEL_NUM): + self._log(NOTICE_LEVEL_NUM, message, args, **kws) + + logging.Logger.notice = notice + + # Add an extra logging level above INFO and below WARNING + add_notice_log_level() + + # More style info at: + # https://coloredlogs.readthedocs.io/en/latest/api.html + field_styles = coloredlogs.DEFAULT_FIELD_STYLES.copy() + field_styles["asctime"] = {} + level_styles = coloredlogs.DEFAULT_LEVEL_STYLES.copy() + level_styles["debug"] = {"color": "white", "faint": True} + level_styles["notice"] = {"color": "cyan", "bold": True} + + coloredlogs.install( + logger=given_logger, + level=level, + use_chroot=False, + fmt=fmt, + level_styles=level_styles, + field_styles=field_styles, + ) diff --git a/utils/__init__.py b/utils/__init__.py new file mode 100644 index 0000000..11f2476 --- /dev/null +++ b/utils/__init__.py @@ -0,0 +1,7 @@ +from .banned_words import banned_words +from .datasets import download_urls, get_oscar_urls, get_docs +from .hf_ner_models import hf_ner_model_map +from .LogingHandler import LoggingHandler +from .mariam_mt import mariam_mt +from .regex_rules import rulebase +from .CharManager import CharManager diff --git a/utils/banned_words.py b/utils/banned_words.py new file mode 100644 index 0000000..ec6b08e --- /dev/null +++ b/utils/banned_words.py @@ -0,0 +1,35 @@ +# see https://www.researchgate.net/publication/259179064_Comparing_Methods_for_Detecting_Child_Exploitation_Content_Online for common CSAM words +# http://antipaedo.lip6.fr/T12/keywords_cnrs.pdf - for top 20 from table 7 and 8 of the paper, plus other , ignoring stopwords like "tuesday" +# WARNING: Translations are probably not accurate. TODO to fix. +# we are only doing our current covered langauges. TODO, do for all languages. +banned_words = { + 'ar': {"فتاة صغيرة", "فتاة صغيرة", "فتى صغير", "مراهق", "لولي", "لولا", "لوليتا", "لولي", "لولي", "لوليتاغوي", + "فتاة", "صبي", "طفل", "حمام"}, + 'bn': {'ছোট মেয়ে', 'ছোট মেয়ে', 'ছোট ছেলে', 'কিশোর', 'ললি', 'লোলা', 'ললিতা', 'ললি', 'লোলি', 'ললিটাগুই', 'মেয়ে', + 'ছেলে', 'শিশু', 'স্নান', }, + 'hi': {'युवा लड़की', 'छोटी लड़की', 'छोटा लड़का', 'किशोर', 'लॉली', 'लोला', 'लोलिता', 'लल्ली', 'लोली', 'लोलितागुय', + 'लड़की', 'लड़का', 'बच्चा', 'स्नान', }, + 'eu': {'neska gaztea', 'neska txikia', 'mutil txikia', 'nerabea', 'neska', 'mutil', 'haurra', 'bainua', }, + 'ca': {'noia', 'nena', 'nen petit', 'nen', 'nen', 'banyer', }, + 'vi': {'thiếu niên', 'cậu nhỏ', 'cậu bé', 'cô gái trẻ', 'cô bé', 'cậu bé', 'trẻ em', 'tắm', }, + 'zh': {'儿童', '女孩', '孩子', '小女孩', '小姑娘', '小男孩', '年輕女孩', '年轻女孩', '年轻的女孩', '洗澡', '洛丽塔', '洛麗塔', '浴', '男孩', '萝拉', '萝莉', + '萝莉塔吉', '蘿拉', '蘿莉', '蘿莉塔', '青少年'}, + 'fr': {'jeune fille', 'petite fille', 'petit garçon', 'ado', 'fille', 'garçon', 'enfant', 'bain', }, + 'id': {'gadis muda', 'gadis kecil', 'anak laki-laki kecil', 'remaja', 'perempuan', 'laki-laki', 'anak', 'mandi', }, + 'fa': {'دختر جوان', 'دختر کوچولو', 'پسر کوچولو', 'نوجوان', 'لولی', 'لولا', 'لولیتا', 'لولی', 'لولی', 'لولیتاگو', + 'دختر', 'پسر', 'کودک', 'حمام', }, + 'ur': {'نوجوان لڑکی', 'چھوٹی لڑکی', 'چھوٹا لڑکا', 'نوعمر', 'لولی', 'لولا', 'لولیتا', 'لولی', 'لولی', 'لولیتاگوئے', + 'لڑکی', 'لڑکا', 'بچہ', 'غسل', }, + 'es': {'niña', 'niño', 'adolescente', 'baño', }, + 'pt': {'menina', 'menino', 'adolescente', 'pirulito', 'criança', 'banho', }, + 'ig': {'nwa agbọghọ', 'nwa agbọghọ', 'nwa agbọghọ', ' iri na ụma', 'nwa agbọghọ', 'nwoke', 'nwa', }, + 'sw': {'msichana mdogo', 'msichana mdogo', 'kijana mdogo', 'mtoto', 'kuoga', }, + 'yo': {'kekere', 'omobinrin', 'omokunrin', 'ọmọ', 'wẹwẹ', }, + 'xh': {'intombazana encinci', 'intsha', 'umntwana', 'hlamba', 'inkwenkwe', }, + 'zu': {'intombazane', 'intsha', 'intombazane encane', 'umfana omncane', 'geza', 'ingane', 'yomfana'}, + 'default': {'young girl', 'little girl', 'little boy', 'young boy', 'teen', 'lolli', 'lola', 'lolita', 'lolly', + 'loli', 'lolitaguy', 'girl', 'boy', 'child', 'kid', 'bath', 'baths', 'bathing', "pedo", 'nymphet', 'nimphet', 'babyj', 'voglia', 'eurololita', '349', + 'hussyfan', 'kidzilla', 'raygold', 'ygold', 'qwerty', 'qqaazz', 'ptsc', 'pthc', 'nn', 'tanta', 'mylola', 'arina', 'newstar', 'playtoy', 'imouto', 'lourinha', 'amateurz', + 'kacy', 'vicky', 'lsm', 'sandra', 'babyshivid', 'shiori', 'tvg', 'chiharu', 'kidzilla', 'izzy', 'rika', 'kdquality', 'cbaby', 'nablot', + 'lso', 'kinderficker', 'yo', 'yr', } +} \ No newline at end of file diff --git a/utils/datasets.py b/utils/datasets.py new file mode 100644 index 0000000..6aa02c6 --- /dev/null +++ b/utils/datasets.py @@ -0,0 +1,58 @@ +import os +from typing import List + +import fsspec +from datasets import load_dataset +import logging + +from .LogingHandler import LoggingHandler + +logging.basicConfig(format='%(asctime)s - %(message)s', + datefmt='%Y-%m-%d %H:%M:%S', + level=logging.INFO, + handlers=[LoggingHandler()]) + + +def get_oscar_urls(language, shuffled="unshuffled", deduplicated="deduplicated"): + _BASE_DATA_URL_FORMAT_STR = ( + "https://s3.amazonaws.com/datasets.huggingface.co/oscar/1.0/{shuffled}/{deduplicated}/{language}/") + _BASE_CHECKSUM_FILE_NAME = "{language}_sha256.txt" + base_data_url = _BASE_DATA_URL_FORMAT_STR.format( + shuffled=shuffled, language=language, deduplicated=deduplicated + ) + checksum_url = base_data_url + _BASE_CHECKSUM_FILE_NAME.format(language=language) + with fsspec.open(checksum_url, encoding="utf-8") as f: + data_filenames = [line.decode().split("\t")[0] for line in f if line] + return [base_data_url + data_filename for data_filename in data_filenames] + + +def download_urls(urls): + for url in urls: + if not os.path.exists(url.split("/")[-1]): + os.system(f"wget {url}") + + +def get_docs(src_lang: str = None) -> List[str]: + logging.info("Docs is None so trying to load dataset") + + docs = None + domain = None + try: + domain = 'oscar_registry' + d = load_dataset("TurkuNLP/register_oscar", data_files=f"{src_lang}/{src_lang}_00000*") + docs = [doc for doc in d['train'] if 'labels' not in doc or doc['labels'] != []] + except: + try: + logging.info("Failed to load oscar_registry") + domain = 'mc4_registry' + d = load_dataset("TurkuNLP/register_mc4", data_files=f"{src_lang}/{src_lang}_00000*") + docs = [doc for doc in d['train'] if 'labels' not in doc or doc['labels'] != []] + except: + logging.info("Failed to load mc4_registry") + domain = 'oscar' + url = get_oscar_urls(src_lang)[0] + download_urls([url]) + docs = [{f'{src_lang}_text': line.decode()} for line in open(url.split("/")[-1], "rb").readlines()] + finally: + logging.info(f"Loaded Documents in domain: {domain}") + return docs, domain diff --git a/utils/hf_ner_models.py b/utils/hf_ner_models.py new file mode 100644 index 0000000..24d6f68 --- /dev/null +++ b/utils/hf_ner_models.py @@ -0,0 +1,49 @@ +from transformers import XLMRobertaForTokenClassification, BertForTokenClassification, ElectraForTokenClassification, RobertaForTokenClassification + +# note that we do not have a transformer model for catalan, but spacy covers catalan and we use transfer learning from Davlan/xlm-roberta-base-ner-hrl + + +hf_ner_model_map = { + "sn": [["Davlan/xlm-roberta-large-masakhaner", XLMRobertaForTokenClassification, 1.0]], + # consider using one of the smaller models + "st": [["Davlan/xlm-roberta-large-masakhaner", XLMRobertaForTokenClassification, 1.0]], + # consider using one of the smaller models + "ny": [["Davlan/xlm-roberta-large-masakhaner", XLMRobertaForTokenClassification, 1.0]], + # consider using one of the smaller models + "xh": [["Davlan/xlm-roberta-large-masakhaner", XLMRobertaForTokenClassification, 1.0]], + # consider using one of the smaller models + "zu": [["Davlan/xlm-roberta-large-masakhaner", XLMRobertaForTokenClassification, 1.0]], + # consider using one of the smaller models + "sw": [["Davlan/xlm-roberta-large-masakhaner", XLMRobertaForTokenClassification, 1.0]], + # consider using one of the smaller models + "yo": [["Davlan/xlm-roberta-large-masakhaner", XLMRobertaForTokenClassification, 1.0]], + "ig": [["Davlan/xlm-roberta-large-masakhaner", XLMRobertaForTokenClassification, 1.0]], + "ar": [["Davlan/xlm-roberta-base-ner-hrl", XLMRobertaForTokenClassification, 1.0]], + "en": [["Davlan/xlm-roberta-base-ner-hrl", XLMRobertaForTokenClassification, 1.0], + ["bioformers/bioformer-cased-v1.0-ncbi-disease", BertForTokenClassification, 1.0]], + # ["jplu/tf-xlm-r-ner-40-lang", None ], + "es": [["Davlan/xlm-roberta-base-ner-hrl", XLMRobertaForTokenClassification, 1.0]], + "eu": [["Davlan/xlm-roberta-base-ner-hrl", XLMRobertaForTokenClassification, 0.8]], + "ca": [["Davlan/xlm-roberta-base-ner-hrl", XLMRobertaForTokenClassification, 0.8]], + "pt": [["Davlan/xlm-roberta-base-ner-hrl", XLMRobertaForTokenClassification, 1.0]], # there is a + "fr": [["Davlan/xlm-roberta-base-ner-hrl", XLMRobertaForTokenClassification, 1.0]], + "zh": [["Davlan/xlm-roberta-base-ner-hrl", XLMRobertaForTokenClassification, 1.0]], + 'vi': [["lhkhiem28/COVID-19-Named-Entity-Recognition-for-Vietnamese", RobertaForTokenClassification, 1.0]], + # ["jplu/tf-xlm-r-ner-40-lang", None ], + 'hi': [["jplu/tf-xlm-r-ner-40-lang", None, 1.0]], + 'ur': [["jplu/tf-xlm-r-ner-40-lang", None, 1.0]], + 'id': [["cahya/bert-base-indonesian-NER", BertForTokenClassification, 1.0]], + 'bn': [["sagorsarker/mbert-bengali-ner", BertForTokenClassification, 1.0]], + 'hr': [["classla/bcms-bertic-ner", ElectraForTokenClassification, 1.0]], + 'bs': [["classla/bcms-bertic-ner", ElectraForTokenClassification, 1.0]], + 'sr': [["classla/bcms-bertic-ner", ElectraForTokenClassification, 1.0]], + 'cnr': [["classla/bcms-bertic-ner", ElectraForTokenClassification, 1.0]], + 'hbs': [["classla/bcms-bertic-ner", ElectraForTokenClassification, 1.0]], + 'da': [["saattrupdan/nbailab-base-ner-scandi", BertForTokenClassification, 1.0]], + 'no': [["saattrupdan/nbailab-base-ner-scandi", BertForTokenClassification, 1.0]], + 'nb': [["saattrupdan/nbailab-base-ner-scandi", BertForTokenClassification, 1.0]], + 'nn': [["saattrupdan/nbailab-base-ner-scandi", BertForTokenClassification, 1.0]], + 'sv': [["saattrupdan/nbailab-base-ner-scandi", BertForTokenClassification, 1.0]], + 'fo': [["saattrupdan/nbailab-base-ner-scandi", BertForTokenClassification, 1.0]], + 'is': [["saattrupdan/nbailab-base-ner-scandi", BertForTokenClassification, 1.0]], +} \ No newline at end of file diff --git a/utils/mariam_mt.py b/utils/mariam_mt.py new file mode 100644 index 0000000..16e8f08 --- /dev/null +++ b/utils/mariam_mt.py @@ -0,0 +1,663 @@ +mariam_mt = {('aav', 'en'): 'Helsinki-NLP/opus-mt-aav-en', ('aed', 'es'): 'Helsinki-NLP/opus-mt-aed-es', + ('af', 'de'): 'Helsinki-NLP/opus-mt-af-de', ('af', 'en'): 'Helsinki-NLP/opus-mt-af-en', + ('af', 'eo'): 'Helsinki-NLP/opus-mt-af-eo', ('af', 'es'): 'Helsinki-NLP/opus-mt-af-es', + ('af', 'fi'): 'Helsinki-NLP/opus-mt-af-fi', ('af', 'fr'): 'Helsinki-NLP/opus-mt-af-fr', + ('af', 'nl'): 'Helsinki-NLP/opus-mt-af-nl', ('af', 'ru'): 'Helsinki-NLP/opus-mt-af-ru', + ('af', 'sv'): 'Helsinki-NLP/opus-mt-af-sv', ('afa', 'afa'): 'Helsinki-NLP/opus-mt-afa-afa', + ('afa', 'en'): 'Helsinki-NLP/opus-mt-afa-en', ('alv', 'en'): 'Helsinki-NLP/opus-mt-alv-en', + ('am', 'sv'): 'Helsinki-NLP/opus-mt-am-sv', ('ar', 'de'): 'Helsinki-NLP/opus-mt-ar-de', + ('ar', 'el'): 'Helsinki-NLP/opus-mt-ar-el', ('ar', 'en'): 'Helsinki-NLP/opus-mt-ar-en', + ('ar', 'eo'): 'Helsinki-NLP/opus-mt-ar-eo', ('ar', 'es'): 'Helsinki-NLP/opus-mt-ar-es', + ('ar', 'fr'): 'Helsinki-NLP/opus-mt-ar-fr', ('ar', 'he'): 'Helsinki-NLP/opus-mt-ar-he', + ('ar', 'it'): 'Helsinki-NLP/opus-mt-ar-it', ('ar', 'pl'): 'Helsinki-NLP/opus-mt-ar-pl', + ('ar', 'ru'): 'Helsinki-NLP/opus-mt-ar-ru', ('ar', 'tr'): 'Helsinki-NLP/opus-mt-ar-tr', + ('art', 'en'): 'Helsinki-NLP/opus-mt-art-en', ('ase', 'de'): 'Helsinki-NLP/opus-mt-ase-de', + ('ase', 'en'): 'Helsinki-NLP/opus-mt-ase-en', ('ase', 'es'): 'Helsinki-NLP/opus-mt-ase-es', + ('ase', 'fr'): 'Helsinki-NLP/opus-mt-ase-fr', ('ase', 'sv'): 'Helsinki-NLP/opus-mt-ase-sv', + ('az', 'en'): 'Helsinki-NLP/opus-mt-az-en', ('az', 'es'): 'Helsinki-NLP/opus-mt-az-es', + ('az', 'tr'): 'Helsinki-NLP/opus-mt-az-tr', ('bat', 'en'): 'Helsinki-NLP/opus-mt-bat-en', + ('bcl', 'de'): 'Helsinki-NLP/opus-mt-bcl-de', ('bcl', 'en'): 'Helsinki-NLP/opus-mt-bcl-en', + ('bcl', 'es'): 'Helsinki-NLP/opus-mt-bcl-es', ('bcl', 'fi'): 'Helsinki-NLP/opus-mt-bcl-fi', + ('bcl', 'fr'): 'Helsinki-NLP/opus-mt-bcl-fr', ('bcl', 'sv'): 'Helsinki-NLP/opus-mt-bcl-sv', + ('be', 'es'): 'Helsinki-NLP/opus-mt-be-es', ('bem', 'en'): 'Helsinki-NLP/opus-mt-bem-en', + ('bem', 'es'): 'Helsinki-NLP/opus-mt-bem-es', ('bem', 'fi'): 'Helsinki-NLP/opus-mt-bem-fi', + ('bem', 'fr'): 'Helsinki-NLP/opus-mt-bem-fr', ('bem', 'sv'): 'Helsinki-NLP/opus-mt-bem-sv', + ('ber', 'en'): 'Helsinki-NLP/opus-mt-ber-en', ('ber', 'es'): 'Helsinki-NLP/opus-mt-ber-es', + ('ber', 'fr'): 'Helsinki-NLP/opus-mt-ber-fr', ('bg', 'de'): 'Helsinki-NLP/opus-mt-bg-de', + ('bg', 'en'): 'Helsinki-NLP/opus-mt-bg-en', ('bg', 'eo'): 'Helsinki-NLP/opus-mt-bg-eo', + ('bg', 'es'): 'Helsinki-NLP/opus-mt-bg-es', ('bg', 'fi'): 'Helsinki-NLP/opus-mt-bg-fi', + ('bg', 'fr'): 'Helsinki-NLP/opus-mt-bg-fr', ('bg', 'it'): 'Helsinki-NLP/opus-mt-bg-it', + ('bg', 'ru'): 'Helsinki-NLP/opus-mt-bg-ru', ('bg', 'sv'): 'Helsinki-NLP/opus-mt-bg-sv', + ('bg', 'tr'): 'Helsinki-NLP/opus-mt-bg-tr', ('bg', 'uk'): 'Helsinki-NLP/opus-mt-bg-uk', + ('bi', 'en'): 'Helsinki-NLP/opus-mt-bi-en', ('bi', 'es'): 'Helsinki-NLP/opus-mt-bi-es', + ('bi', 'fr'): 'Helsinki-NLP/opus-mt-bi-fr', ('bi', 'sv'): 'Helsinki-NLP/opus-mt-bi-sv', + ('bn', 'en'): 'Helsinki-NLP/opus-mt-bn-en', ('bnt', 'en'): 'Helsinki-NLP/opus-mt-bnt-en', + ('bzs', 'en'): 'Helsinki-NLP/opus-mt-bzs-en', ('bzs', 'es'): 'Helsinki-NLP/opus-mt-bzs-es', + ('bzs', 'fi'): 'Helsinki-NLP/opus-mt-bzs-fi', ('bzs', 'fr'): 'Helsinki-NLP/opus-mt-bzs-fr', + ('bzs', 'sv'): 'Helsinki-NLP/opus-mt-bzs-sv', ('ca', 'de'): 'Helsinki-NLP/opus-mt-ca-de', + ('ca', 'en'): 'Helsinki-NLP/opus-mt-ca-en', ('ca', 'es'): 'Helsinki-NLP/opus-mt-ca-es', + ('ca', 'fr'): 'Helsinki-NLP/opus-mt-ca-fr', ('ca', 'it'): 'Helsinki-NLP/opus-mt-ca-it', + ('ca', 'nl'): 'Helsinki-NLP/opus-mt-ca-nl', ('ca', 'pt'): 'Helsinki-NLP/opus-mt-ca-pt', + ('ca', 'uk'): 'Helsinki-NLP/opus-mt-ca-uk', ('cau', 'en'): 'Helsinki-NLP/opus-mt-cau-en', + ('ccs', 'en'): 'Helsinki-NLP/opus-mt-ccs-en', ('ceb', 'en'): 'Helsinki-NLP/opus-mt-ceb-en', + ('ceb', 'es'): 'Helsinki-NLP/opus-mt-ceb-es', ('ceb', 'fi'): 'Helsinki-NLP/opus-mt-ceb-fi', + ('ceb', 'fr'): 'Helsinki-NLP/opus-mt-ceb-fr', ('ceb', 'sv'): 'Helsinki-NLP/opus-mt-ceb-sv', + ('cel', 'en'): 'Helsinki-NLP/opus-mt-cel-en', ('chk', 'en'): 'Helsinki-NLP/opus-mt-chk-en', + ('chk', 'es'): 'Helsinki-NLP/opus-mt-chk-es', ('chk', 'fr'): 'Helsinki-NLP/opus-mt-chk-fr', + ('chk', 'sv'): 'Helsinki-NLP/opus-mt-chk-sv', ('cpf', 'en'): 'Helsinki-NLP/opus-mt-cpf-en', + ('cpp', 'cpp'): 'Helsinki-NLP/opus-mt-cpp-cpp', ('cpp', 'en'): 'Helsinki-NLP/opus-mt-cpp-en', + ('crs', 'de'): 'Helsinki-NLP/opus-mt-crs-de', ('crs', 'en'): 'Helsinki-NLP/opus-mt-crs-en', + ('crs', 'es'): 'Helsinki-NLP/opus-mt-crs-es', ('crs', 'fi'): 'Helsinki-NLP/opus-mt-crs-fi', + ('crs', 'fr'): 'Helsinki-NLP/opus-mt-crs-fr', ('crs', 'sv'): 'Helsinki-NLP/opus-mt-crs-sv', + ('cs', 'de'): 'Helsinki-NLP/opus-mt-cs-de', ('cs', 'en'): 'Helsinki-NLP/opus-mt-cs-en', + ('cs', 'eo'): 'Helsinki-NLP/opus-mt-cs-eo', ('cs', 'fi'): 'Helsinki-NLP/opus-mt-cs-fi', + ('cs', 'fr'): 'Helsinki-NLP/opus-mt-cs-fr', ('cs', 'sv'): 'Helsinki-NLP/opus-mt-cs-sv', + ('cs', 'uk'): 'Helsinki-NLP/opus-mt-cs-uk', ('csg', 'es'): 'Helsinki-NLP/opus-mt-csg-es', + ('csn', 'es'): 'Helsinki-NLP/opus-mt-csn-es', ('cus', 'en'): 'Helsinki-NLP/opus-mt-cus-en', + ('cy', 'en'): 'Helsinki-NLP/opus-mt-cy-en', ('da', 'de'): 'Helsinki-NLP/opus-mt-da-de', + ('da', 'en'): 'Helsinki-NLP/opus-mt-da-en', ('da', 'eo'): 'Helsinki-NLP/opus-mt-da-eo', + ('da', 'es'): 'Helsinki-NLP/opus-mt-da-es', ('da', 'fi'): 'Helsinki-NLP/opus-mt-da-fi', + ('da', 'fr'): 'Helsinki-NLP/opus-mt-da-fr', ('da', 'no'): 'Helsinki-NLP/opus-mt-da-no', + ('da', 'ru'): 'Helsinki-NLP/opus-mt-da-ru', ('de', 'ZH'): 'Helsinki-NLP/opus-mt-de-ZH', + ('de', 'af'): 'Helsinki-NLP/opus-mt-de-af', ('de', 'ar'): 'Helsinki-NLP/opus-mt-de-ar', + ('de', 'ase'): 'Helsinki-NLP/opus-mt-de-ase', ('de', 'bcl'): 'Helsinki-NLP/opus-mt-de-bcl', + ('de', 'bg'): 'Helsinki-NLP/opus-mt-de-bg', ('de', 'bi'): 'Helsinki-NLP/opus-mt-de-bi', + ('de', 'bzs'): 'Helsinki-NLP/opus-mt-de-bzs', ('de', 'ca'): 'Helsinki-NLP/opus-mt-de-ca', + ('de', 'crs'): 'Helsinki-NLP/opus-mt-de-crs', ('de', 'cs'): 'Helsinki-NLP/opus-mt-de-cs', + ('de', 'da'): 'Helsinki-NLP/opus-mt-de-da', ('de', 'de'): 'Helsinki-NLP/opus-mt-de-de', + ('de', 'ee'): 'Helsinki-NLP/opus-mt-de-ee', ('de', 'efi'): 'Helsinki-NLP/opus-mt-de-efi', + ('de', 'el'): 'Helsinki-NLP/opus-mt-de-el', ('de', 'en'): 'Helsinki-NLP/opus-mt-de-en', + ('de', 'eo'): 'Helsinki-NLP/opus-mt-de-eo', ('de', 'es'): 'Helsinki-NLP/opus-mt-de-es', + ('de', 'et'): 'Helsinki-NLP/opus-mt-de-et', ('de', 'eu'): 'Helsinki-NLP/opus-mt-de-eu', + ('de', 'fi'): 'Helsinki-NLP/opus-mt-de-fi', ('de', 'fj'): 'Helsinki-NLP/opus-mt-de-fj', + ('de', 'fr'): 'Helsinki-NLP/opus-mt-de-fr', ('de', 'gaa'): 'Helsinki-NLP/opus-mt-de-gaa', + ('de', 'gil'): 'Helsinki-NLP/opus-mt-de-gil', ('de', 'guw'): 'Helsinki-NLP/opus-mt-de-guw', + ('de', 'ha'): 'Helsinki-NLP/opus-mt-de-ha', ('de', 'he'): 'Helsinki-NLP/opus-mt-de-he', + ('de', 'hil'): 'Helsinki-NLP/opus-mt-de-hil', ('de', 'ho'): 'Helsinki-NLP/opus-mt-de-ho', + ('de', 'hr'): 'Helsinki-NLP/opus-mt-de-hr', ('de', 'ht'): 'Helsinki-NLP/opus-mt-de-ht', + ('de', 'hu'): 'Helsinki-NLP/opus-mt-de-hu', ('de', 'ig'): 'Helsinki-NLP/opus-mt-de-ig', + ('de', 'ilo'): 'Helsinki-NLP/opus-mt-de-ilo', ('de', 'is'): 'Helsinki-NLP/opus-mt-de-is', + ('de', 'iso'): 'Helsinki-NLP/opus-mt-de-iso', ('de', 'it'): 'Helsinki-NLP/opus-mt-de-it', + ('de', 'kg'): 'Helsinki-NLP/opus-mt-de-kg', ('de', 'ln'): 'Helsinki-NLP/opus-mt-de-ln', + ('de', 'loz'): 'Helsinki-NLP/opus-mt-de-loz', ('de', 'lt'): 'Helsinki-NLP/opus-mt-de-lt', + ('de', 'lua'): 'Helsinki-NLP/opus-mt-de-lua', ('de', 'ms'): 'Helsinki-NLP/opus-mt-de-ms', + ('de', 'mt'): 'Helsinki-NLP/opus-mt-de-mt', ('de', 'niu'): 'Helsinki-NLP/opus-mt-de-niu', + ('de', 'nl'): 'Helsinki-NLP/opus-mt-de-nl', ('de', 'no'): 'Helsinki-NLP/opus-mt-de-no', + ('de', 'nso'): 'Helsinki-NLP/opus-mt-de-nso', ('de', 'ny'): 'Helsinki-NLP/opus-mt-de-ny', + ('de', 'pag'): 'Helsinki-NLP/opus-mt-de-pag', ('de', 'pap'): 'Helsinki-NLP/opus-mt-de-pap', + ('de', 'pis'): 'Helsinki-NLP/opus-mt-de-pis', ('de', 'pl'): 'Helsinki-NLP/opus-mt-de-pl', + ('de', 'pon'): 'Helsinki-NLP/opus-mt-de-pon', ('de', 'tl'): 'Helsinki-NLP/opus-mt-de-tl', + ('de', 'uk'): 'Helsinki-NLP/opus-mt-de-uk', ('de', 'vi'): 'Helsinki-NLP/opus-mt-de-vi', + ('dra', 'en'): 'Helsinki-NLP/opus-mt-dra-en', ('ee', 'de'): 'Helsinki-NLP/opus-mt-ee-de', + ('ee', 'en'): 'Helsinki-NLP/opus-mt-ee-en', ('ee', 'es'): 'Helsinki-NLP/opus-mt-ee-es', + ('ee', 'fi'): 'Helsinki-NLP/opus-mt-ee-fi', ('ee', 'fr'): 'Helsinki-NLP/opus-mt-ee-fr', + ('ee', 'sv'): 'Helsinki-NLP/opus-mt-ee-sv', ('efi', 'de'): 'Helsinki-NLP/opus-mt-efi-de', + ('efi', 'en'): 'Helsinki-NLP/opus-mt-efi-en', ('efi', 'fi'): 'Helsinki-NLP/opus-mt-efi-fi', + ('efi', 'fr'): 'Helsinki-NLP/opus-mt-efi-fr', ('efi', 'sv'): 'Helsinki-NLP/opus-mt-efi-sv', + ('el', 'ar'): 'Helsinki-NLP/opus-mt-el-ar', ('el', 'eo'): 'Helsinki-NLP/opus-mt-el-eo', + ('el', 'fi'): 'Helsinki-NLP/opus-mt-el-fi', ('el', 'fr'): 'Helsinki-NLP/opus-mt-el-fr', + ('el', 'sv'): 'Helsinki-NLP/opus-mt-el-sv', ('en', 'aav'): 'Helsinki-NLP/opus-mt-en-aav', + ('en', 'af'): 'Helsinki-NLP/opus-mt-en-af', ('en', 'afa'): 'Helsinki-NLP/opus-mt-en-afa', + ('en', 'alv'): 'Helsinki-NLP/opus-mt-en-alv', ('en', 'ar'): 'Helsinki-NLP/opus-mt-en-ar', + ('en', 'az'): 'Helsinki-NLP/opus-mt-en-az', ('en', 'bat'): 'Helsinki-NLP/opus-mt-en-bat', + ('en', 'bcl'): 'Helsinki-NLP/opus-mt-en-bcl', ('en', 'bem'): 'Helsinki-NLP/opus-mt-en-bem', + ('en', 'ber'): 'Helsinki-NLP/opus-mt-en-ber', ('en', 'bg'): 'Helsinki-NLP/opus-mt-en-bg', + ('en', 'bi'): 'Helsinki-NLP/opus-mt-en-bi', ('en', 'bnt'): 'Helsinki-NLP/opus-mt-en-bnt', + ('en', 'bzs'): 'Helsinki-NLP/opus-mt-en-bzs', ('en', 'ca'): 'Helsinki-NLP/opus-mt-en-ca', + ('en', 'ceb'): 'Helsinki-NLP/opus-mt-en-ceb', ('en', 'cel'): 'Helsinki-NLP/opus-mt-en-cel', + ('en', 'chk'): 'Helsinki-NLP/opus-mt-en-chk', ('en', 'cpf'): 'Helsinki-NLP/opus-mt-en-cpf', + ('en', 'cpp'): 'Helsinki-NLP/opus-mt-en-cpp', ('en', 'crs'): 'Helsinki-NLP/opus-mt-en-crs', + ('en', 'cs'): 'Helsinki-NLP/opus-mt-en-cs', ('en', 'cus'): 'Helsinki-NLP/opus-mt-en-cus', + ('en', 'cy'): 'Helsinki-NLP/opus-mt-en-cy', ('en', 'da'): 'Helsinki-NLP/opus-mt-en-da', + ('en', 'de'): 'Helsinki-NLP/opus-mt-en-de', ('en', 'dra'): 'Helsinki-NLP/opus-mt-en-dra', + ('en', 'ee'): 'Helsinki-NLP/opus-mt-en-ee', ('en', 'efi'): 'Helsinki-NLP/opus-mt-en-efi', + ('en', 'el'): 'Helsinki-NLP/opus-mt-en-el', ('en', 'eo'): 'Helsinki-NLP/opus-mt-en-eo', + ('en', 'es'): 'Helsinki-NLP/opus-mt-en-es', ('en', 'et'): 'Helsinki-NLP/opus-mt-en-et', + ('en', 'eu'): 'Helsinki-NLP/opus-mt-en-eu', ('en', 'euq'): 'Helsinki-NLP/opus-mt-en-euq', + ('en', 'fi'): 'Helsinki-NLP/opus-mt-en-fi', ('en', 'fiu'): 'Helsinki-NLP/opus-mt-en-fiu', + ('en', 'fj'): 'Helsinki-NLP/opus-mt-en-fj', ('en', 'fr'): 'Helsinki-NLP/opus-mt-en-fr', + ('en', 'ga'): 'Helsinki-NLP/opus-mt-en-ga', ('en', 'gaa'): 'Helsinki-NLP/opus-mt-en-gaa', + ('en', 'gem'): 'Helsinki-NLP/opus-mt-en-gem', ('en', 'gil'): 'Helsinki-NLP/opus-mt-en-gil', + ('en', 'gl'): 'Helsinki-NLP/opus-mt-en-gl', ('en', 'gmq'): 'Helsinki-NLP/opus-mt-en-gmq', + ('en', 'gmw'): 'Helsinki-NLP/opus-mt-en-gmw', ('en', 'grk'): 'Helsinki-NLP/opus-mt-en-grk', + ('en', 'guw'): 'Helsinki-NLP/opus-mt-en-guw', ('en', 'gv'): 'Helsinki-NLP/opus-mt-en-gv', + ('en', 'ha'): 'Helsinki-NLP/opus-mt-en-ha', ('en', 'he'): 'Helsinki-NLP/opus-mt-en-he', + ('en', 'hi'): 'Helsinki-NLP/opus-mt-en-hi', ('en', 'hil'): 'Helsinki-NLP/opus-mt-en-hil', + ('en', 'ho'): 'Helsinki-NLP/opus-mt-en-ho', ('en', 'ht'): 'Helsinki-NLP/opus-mt-en-ht', + ('en', 'hu'): 'Helsinki-NLP/opus-mt-en-hu', ('en', 'hy'): 'Helsinki-NLP/opus-mt-en-hy', + ('en', 'id'): 'Helsinki-NLP/opus-mt-en-id', ('en', 'ig'): 'Helsinki-NLP/opus-mt-en-ig', + ('en', 'iir'): 'Helsinki-NLP/opus-mt-en-iir', ('en', 'ilo'): 'Helsinki-NLP/opus-mt-en-ilo', + ('en', 'inc'): 'Helsinki-NLP/opus-mt-en-inc', ('en', 'ine'): 'Helsinki-NLP/opus-mt-en-ine', + ('en', 'is'): 'Helsinki-NLP/opus-mt-en-is', ('en', 'iso'): 'Helsinki-NLP/opus-mt-en-iso', + ('en', 'it'): 'Helsinki-NLP/opus-mt-en-it', ('en', 'itc'): 'Helsinki-NLP/opus-mt-en-itc', + ('en', 'jap'): 'Helsinki-NLP/opus-mt-en-jap', ('en', 'kg'): 'Helsinki-NLP/opus-mt-en-kg', + ('en', 'kj'): 'Helsinki-NLP/opus-mt-en-kj', ('en', 'kqn'): 'Helsinki-NLP/opus-mt-en-kqn', + ('en', 'kwn'): 'Helsinki-NLP/opus-mt-en-kwn', ('en', 'kwy'): 'Helsinki-NLP/opus-mt-en-kwy', + ('en', 'lg'): 'Helsinki-NLP/opus-mt-en-lg', ('en', 'ln'): 'Helsinki-NLP/opus-mt-en-ln', + ('en', 'loz'): 'Helsinki-NLP/opus-mt-en-loz', ('en', 'lu'): 'Helsinki-NLP/opus-mt-en-lu', + ('en', 'lua'): 'Helsinki-NLP/opus-mt-en-lua', ('en', 'lue'): 'Helsinki-NLP/opus-mt-en-lue', + ('en', 'lun'): 'Helsinki-NLP/opus-mt-en-lun', ('en', 'luo'): 'Helsinki-NLP/opus-mt-en-luo', + ('en', 'lus'): 'Helsinki-NLP/opus-mt-en-lus', ('en', 'map'): 'Helsinki-NLP/opus-mt-en-map', + ('en', 'mfe'): 'Helsinki-NLP/opus-mt-en-mfe', ('en', 'mg'): 'Helsinki-NLP/opus-mt-en-mg', + ('en', 'mh'): 'Helsinki-NLP/opus-mt-en-mh', ('en', 'mk'): 'Helsinki-NLP/opus-mt-en-mk', + ('en', 'mkh'): 'Helsinki-NLP/opus-mt-en-mkh', ('en', 'ml'): 'Helsinki-NLP/opus-mt-en-ml', + ('en', 'mos'): 'Helsinki-NLP/opus-mt-en-mos', ('en', 'mr'): 'Helsinki-NLP/opus-mt-en-mr', + ('en', 'mt'): 'Helsinki-NLP/opus-mt-en-mt', ('en', 'mul'): 'Helsinki-NLP/opus-mt-en-mul', + ('en', 'ng'): 'Helsinki-NLP/opus-mt-en-ng', ('en', 'nic'): 'Helsinki-NLP/opus-mt-en-nic', + ('en', 'niu'): 'Helsinki-NLP/opus-mt-en-niu', ('en', 'nl'): 'Helsinki-NLP/opus-mt-en-nl', + ('en', 'nso'): 'Helsinki-NLP/opus-mt-en-nso', ('en', 'ny'): 'Helsinki-NLP/opus-mt-en-ny', + ('en', 'nyk'): 'Helsinki-NLP/opus-mt-en-nyk', ('en', 'om'): 'Helsinki-NLP/opus-mt-en-om', + ('en', 'pag'): 'Helsinki-NLP/opus-mt-en-pag', ('en', 'pap'): 'Helsinki-NLP/opus-mt-en-pap', + ('en', 'phi'): 'Helsinki-NLP/opus-mt-en-phi', ('en', 'pis'): 'Helsinki-NLP/opus-mt-en-pis', + ('en', 'pon'): 'Helsinki-NLP/opus-mt-en-pon', ('en', 'poz'): 'Helsinki-NLP/opus-mt-en-poz', + ('en', 'pqe'): 'Helsinki-NLP/opus-mt-en-pqe', ('en', 'pqw'): 'Helsinki-NLP/opus-mt-en-pqw', + ('en', 'rn'): 'Helsinki-NLP/opus-mt-en-rn', ('en', 'rnd'): 'Helsinki-NLP/opus-mt-en-rnd', + ('en', 'ro'): 'Helsinki-NLP/opus-mt-en-ro', ('en', 'roa'): 'Helsinki-NLP/opus-mt-en-roa', + ('en', 'ru'): 'Helsinki-NLP/opus-mt-en-ru', ('en', 'run'): 'Helsinki-NLP/opus-mt-en-run', + ('en', 'rw'): 'Helsinki-NLP/opus-mt-en-rw', ('en', 'sal'): 'Helsinki-NLP/opus-mt-en-sal', + ('en', 'sem'): 'Helsinki-NLP/opus-mt-en-sem', ('en', 'sg'): 'Helsinki-NLP/opus-mt-en-sg', + ('en', 'sit'): 'Helsinki-NLP/opus-mt-en-sit', ('en', 'sk'): 'Helsinki-NLP/opus-mt-en-sk', + ('en', 'sla'): 'Helsinki-NLP/opus-mt-en-sla', ('en', 'sm'): 'Helsinki-NLP/opus-mt-en-sm', + ('en', 'sn'): 'Helsinki-NLP/opus-mt-en-sn', ('en', 'sq'): 'Helsinki-NLP/opus-mt-en-sq', + ('en', 'ss'): 'Helsinki-NLP/opus-mt-en-ss', ('en', 'st'): 'Helsinki-NLP/opus-mt-en-st', + ('en', 'sv'): 'Helsinki-NLP/opus-mt-en-sv', ('en', 'sw'): 'Helsinki-NLP/opus-mt-en-sw', + ('en', 'swc'): 'Helsinki-NLP/opus-mt-en-swc', ('en', 'tdt'): 'Helsinki-NLP/opus-mt-en-tdt', + ('en', 'ti'): 'Helsinki-NLP/opus-mt-en-ti', ('en', 'tiv'): 'Helsinki-NLP/opus-mt-en-tiv', + ('en', 'tl'): 'Helsinki-NLP/opus-mt-en-tl', ('en', 'tll'): 'Helsinki-NLP/opus-mt-en-tll', + ('en', 'tn'): 'Helsinki-NLP/opus-mt-en-tn', ('en', 'to'): 'Helsinki-NLP/opus-mt-en-to', + ('en', 'toi'): 'Helsinki-NLP/opus-mt-en-toi', ('en', 'tpi'): 'Helsinki-NLP/opus-mt-en-tpi', + ('en', 'trk'): 'Helsinki-NLP/opus-mt-en-trk', ('en', 'ts'): 'Helsinki-NLP/opus-mt-en-ts', + ('en', 'tut'): 'Helsinki-NLP/opus-mt-en-tut', ('en', 'tvl'): 'Helsinki-NLP/opus-mt-en-tvl', + ('en', 'tw'): 'Helsinki-NLP/opus-mt-en-tw', ('en', 'ty'): 'Helsinki-NLP/opus-mt-en-ty', + ('en', 'uk'): 'Helsinki-NLP/opus-mt-en-uk', ('en', 'umb'): 'Helsinki-NLP/opus-mt-en-umb', + ('en', 'ur'): 'Helsinki-NLP/opus-mt-en-ur', ('en', 'urj'): 'Helsinki-NLP/opus-mt-en-urj', + ('en', 'vi'): 'Helsinki-NLP/opus-mt-en-vi', ('en', 'xh'): 'Helsinki-NLP/opus-mt-en-xh', + ('en', 'zh'): 'Helsinki-NLP/opus-mt-en-zh', ('en', 'zle'): 'Helsinki-NLP/opus-mt-en-zle', + ('en', 'zls'): 'Helsinki-NLP/opus-mt-en-zls', ('en', 'zlw'): 'Helsinki-NLP/opus-mt-en-zlw', + ('en_el_es_fi', 'en_el_es_fi'): 'Helsinki-NLP/opus-mt-en_el_es_fi-en_el_es_fi', + ('eo', 'af'): 'Helsinki-NLP/opus-mt-eo-af', ('eo', 'bg'): 'Helsinki-NLP/opus-mt-eo-bg', + ('eo', 'cs'): 'Helsinki-NLP/opus-mt-eo-cs', ('eo', 'da'): 'Helsinki-NLP/opus-mt-eo-da', + ('eo', 'de'): 'Helsinki-NLP/opus-mt-eo-de', ('eo', 'el'): 'Helsinki-NLP/opus-mt-eo-el', + ('eo', 'en'): 'Helsinki-NLP/opus-mt-eo-en', ('eo', 'es'): 'Helsinki-NLP/opus-mt-eo-es', + ('eo', 'fi'): 'Helsinki-NLP/opus-mt-eo-fi', ('eo', 'fr'): 'Helsinki-NLP/opus-mt-eo-fr', + ('eo', 'he'): 'Helsinki-NLP/opus-mt-eo-he', ('eo', 'hu'): 'Helsinki-NLP/opus-mt-eo-hu', + ('eo', 'it'): 'Helsinki-NLP/opus-mt-eo-it', ('eo', 'nl'): 'Helsinki-NLP/opus-mt-eo-nl', + ('eo', 'pl'): 'Helsinki-NLP/opus-mt-eo-pl', ('eo', 'pt'): 'Helsinki-NLP/opus-mt-eo-pt', + ('eo', 'ro'): 'Helsinki-NLP/opus-mt-eo-ro', ('eo', 'ru'): 'Helsinki-NLP/opus-mt-eo-ru', + ('eo', 'sh'): 'Helsinki-NLP/opus-mt-eo-sh', ('eo', 'sv'): 'Helsinki-NLP/opus-mt-eo-sv', + ('es', 'NORWAY'): 'Helsinki-NLP/opus-mt-es-NORWAY', ('es', 'aed'): 'Helsinki-NLP/opus-mt-es-aed', + ('es', 'af'): 'Helsinki-NLP/opus-mt-es-af', ('es', 'ar'): 'Helsinki-NLP/opus-mt-es-ar', + ('es', 'ase'): 'Helsinki-NLP/opus-mt-es-ase', ('es', 'bcl'): 'Helsinki-NLP/opus-mt-es-bcl', + ('es', 'ber'): 'Helsinki-NLP/opus-mt-es-ber', ('es', 'bg'): 'Helsinki-NLP/opus-mt-es-bg', + ('es', 'bi'): 'Helsinki-NLP/opus-mt-es-bi', ('es', 'bzs'): 'Helsinki-NLP/opus-mt-es-bzs', + ('es', 'ca'): 'Helsinki-NLP/opus-mt-es-ca', ('es', 'ceb'): 'Helsinki-NLP/opus-mt-es-ceb', + ('es', 'crs'): 'Helsinki-NLP/opus-mt-es-crs', ('es', 'cs'): 'Helsinki-NLP/opus-mt-es-cs', + ('es', 'csg'): 'Helsinki-NLP/opus-mt-es-csg', ('es', 'csn'): 'Helsinki-NLP/opus-mt-es-csn', + ('es', 'da'): 'Helsinki-NLP/opus-mt-es-da', ('es', 'de'): 'Helsinki-NLP/opus-mt-es-de', + ('es', 'ee'): 'Helsinki-NLP/opus-mt-es-ee', ('es', 'efi'): 'Helsinki-NLP/opus-mt-es-efi', + ('es', 'el'): 'Helsinki-NLP/opus-mt-es-el', ('es', 'en'): 'Helsinki-NLP/opus-mt-es-en', + ('es', 'eo'): 'Helsinki-NLP/opus-mt-es-eo', ('es', 'es'): 'Helsinki-NLP/opus-mt-es-es', + ('es', 'et'): 'Helsinki-NLP/opus-mt-es-et', ('es', 'eu'): 'Helsinki-NLP/opus-mt-es-eu', + ('es', 'fi'): 'Helsinki-NLP/opus-mt-es-fi', ('es', 'fj'): 'Helsinki-NLP/opus-mt-es-fj', + ('es', 'fr'): 'Helsinki-NLP/opus-mt-es-fr', ('es', 'gaa'): 'Helsinki-NLP/opus-mt-es-gaa', + ('es', 'gil'): 'Helsinki-NLP/opus-mt-es-gil', ('es', 'gl'): 'Helsinki-NLP/opus-mt-es-gl', + ('es', 'guw'): 'Helsinki-NLP/opus-mt-es-guw', ('es', 'ha'): 'Helsinki-NLP/opus-mt-es-ha', + ('es', 'he'): 'Helsinki-NLP/opus-mt-es-he', ('es', 'hil'): 'Helsinki-NLP/opus-mt-es-hil', + ('es', 'ho'): 'Helsinki-NLP/opus-mt-es-ho', ('es', 'hr'): 'Helsinki-NLP/opus-mt-es-hr', + ('es', 'ht'): 'Helsinki-NLP/opus-mt-es-ht', ('es', 'id'): 'Helsinki-NLP/opus-mt-es-id', + ('es', 'ig'): 'Helsinki-NLP/opus-mt-es-ig', ('es', 'ilo'): 'Helsinki-NLP/opus-mt-es-ilo', + ('es', 'is'): 'Helsinki-NLP/opus-mt-es-is', ('es', 'iso'): 'Helsinki-NLP/opus-mt-es-iso', + ('es', 'it'): 'Helsinki-NLP/opus-mt-es-it', ('es', 'kg'): 'Helsinki-NLP/opus-mt-es-kg', + ('es', 'ln'): 'Helsinki-NLP/opus-mt-es-ln', ('es', 'loz'): 'Helsinki-NLP/opus-mt-es-loz', + ('es', 'lt'): 'Helsinki-NLP/opus-mt-es-lt', ('es', 'lua'): 'Helsinki-NLP/opus-mt-es-lua', + ('es', 'lus'): 'Helsinki-NLP/opus-mt-es-lus', ('es', 'mfs'): 'Helsinki-NLP/opus-mt-es-mfs', + ('es', 'mk'): 'Helsinki-NLP/opus-mt-es-mk', ('es', 'mt'): 'Helsinki-NLP/opus-mt-es-mt', + ('es', 'niu'): 'Helsinki-NLP/opus-mt-es-niu', ('es', 'nl'): 'Helsinki-NLP/opus-mt-es-nl', + ('es', 'no'): 'Helsinki-NLP/opus-mt-es-no', ('es', 'nso'): 'Helsinki-NLP/opus-mt-es-nso', + ('es', 'ny'): 'Helsinki-NLP/opus-mt-es-ny', ('es', 'pag'): 'Helsinki-NLP/opus-mt-es-pag', + ('es', 'pap'): 'Helsinki-NLP/opus-mt-es-pap', ('es', 'pis'): 'Helsinki-NLP/opus-mt-es-pis', + ('es', 'pl'): 'Helsinki-NLP/opus-mt-es-pl', ('es', 'pon'): 'Helsinki-NLP/opus-mt-es-pon', + ('es', 'prl'): 'Helsinki-NLP/opus-mt-es-prl', ('es', 'rn'): 'Helsinki-NLP/opus-mt-es-rn', + ('es', 'ro'): 'Helsinki-NLP/opus-mt-es-ro', ('es', 'ru'): 'Helsinki-NLP/opus-mt-es-ru', + ('es', 'rw'): 'Helsinki-NLP/opus-mt-es-rw', ('es', 'sg'): 'Helsinki-NLP/opus-mt-es-sg', + ('es', 'sl'): 'Helsinki-NLP/opus-mt-es-sl', ('es', 'sm'): 'Helsinki-NLP/opus-mt-es-sm', + ('es', 'sn'): 'Helsinki-NLP/opus-mt-es-sn', ('es', 'srn'): 'Helsinki-NLP/opus-mt-es-srn', + ('es', 'st'): 'Helsinki-NLP/opus-mt-es-st', ('es', 'swc'): 'Helsinki-NLP/opus-mt-es-swc', + ('es', 'tl'): 'Helsinki-NLP/opus-mt-es-tl', ('es', 'tll'): 'Helsinki-NLP/opus-mt-es-tll', + ('es', 'tn'): 'Helsinki-NLP/opus-mt-es-tn', ('es', 'to'): 'Helsinki-NLP/opus-mt-es-to', + ('es', 'tpi'): 'Helsinki-NLP/opus-mt-es-tpi', ('es', 'tvl'): 'Helsinki-NLP/opus-mt-es-tvl', + ('es', 'tw'): 'Helsinki-NLP/opus-mt-es-tw', ('es', 'ty'): 'Helsinki-NLP/opus-mt-es-ty', + ('es', 'tzo'): 'Helsinki-NLP/opus-mt-es-tzo', ('es', 'uk'): 'Helsinki-NLP/opus-mt-es-uk', + ('es', 've'): 'Helsinki-NLP/opus-mt-es-ve', ('es', 'vi'): 'Helsinki-NLP/opus-mt-es-vi', + ('es', 'war'): 'Helsinki-NLP/opus-mt-es-war', ('es', 'wls'): 'Helsinki-NLP/opus-mt-es-wls', + ('es', 'xh'): 'Helsinki-NLP/opus-mt-es-xh', ('es', 'yo'): 'Helsinki-NLP/opus-mt-es-yo', + ('es', 'yua'): 'Helsinki-NLP/opus-mt-es-yua', ('es', 'zai'): 'Helsinki-NLP/opus-mt-es-zai', + ('et', 'de'): 'Helsinki-NLP/opus-mt-et-de', ('et', 'en'): 'Helsinki-NLP/opus-mt-et-en', + ('et', 'es'): 'Helsinki-NLP/opus-mt-et-es', ('et', 'fi'): 'Helsinki-NLP/opus-mt-et-fi', + ('et', 'fr'): 'Helsinki-NLP/opus-mt-et-fr', ('et', 'ru'): 'Helsinki-NLP/opus-mt-et-ru', + ('et', 'sv'): 'Helsinki-NLP/opus-mt-et-sv', ('eu', 'de'): 'Helsinki-NLP/opus-mt-eu-de', + ('eu', 'en'): 'Helsinki-NLP/opus-mt-eu-en', ('eu', 'es'): 'Helsinki-NLP/opus-mt-eu-es', + ('eu', 'ru'): 'Helsinki-NLP/opus-mt-eu-ru', ('euq', 'en'): 'Helsinki-NLP/opus-mt-euq-en', + ('fi', 'NORWAY'): 'Helsinki-NLP/opus-mt-fi-NORWAY', ('fi', 'ZH'): 'Helsinki-NLP/opus-mt-fi-ZH', + ('fi', 'af'): 'Helsinki-NLP/opus-mt-fi-af', ('fi', 'bcl'): 'Helsinki-NLP/opus-mt-fi-bcl', + ('fi', 'bem'): 'Helsinki-NLP/opus-mt-fi-bem', ('fi', 'bg'): 'Helsinki-NLP/opus-mt-fi-bg', + ('fi', 'bzs'): 'Helsinki-NLP/opus-mt-fi-bzs', ('fi', 'ceb'): 'Helsinki-NLP/opus-mt-fi-ceb', + ('fi', 'crs'): 'Helsinki-NLP/opus-mt-fi-crs', ('fi', 'cs'): 'Helsinki-NLP/opus-mt-fi-cs', + ('fi', 'de'): 'Helsinki-NLP/opus-mt-fi-de', ('fi', 'ee'): 'Helsinki-NLP/opus-mt-fi-ee', + ('fi', 'efi'): 'Helsinki-NLP/opus-mt-fi-efi', ('fi', 'el'): 'Helsinki-NLP/opus-mt-fi-el', + ('fi', 'en'): 'Helsinki-NLP/opus-mt-fi-en', ('fi', 'eo'): 'Helsinki-NLP/opus-mt-fi-eo', + ('fi', 'es'): 'Helsinki-NLP/opus-mt-fi-es', ('fi', 'et'): 'Helsinki-NLP/opus-mt-fi-et', + ('fi', 'fi'): 'Helsinki-NLP/opus-mt-fi-fi', ('fi', 'fj'): 'Helsinki-NLP/opus-mt-fi-fj', + ('fi', 'fr'): 'Helsinki-NLP/opus-mt-fi-fr', ('fi', 'fse'): 'Helsinki-NLP/opus-mt-fi-fse', + ('fi', 'gaa'): 'Helsinki-NLP/opus-mt-fi-gaa', ('fi', 'gil'): 'Helsinki-NLP/opus-mt-fi-gil', + ('fi', 'guw'): 'Helsinki-NLP/opus-mt-fi-guw', ('fi', 'ha'): 'Helsinki-NLP/opus-mt-fi-ha', + ('fi', 'he'): 'Helsinki-NLP/opus-mt-fi-he', ('fi', 'hil'): 'Helsinki-NLP/opus-mt-fi-hil', + ('fi', 'ho'): 'Helsinki-NLP/opus-mt-fi-ho', ('fi', 'hr'): 'Helsinki-NLP/opus-mt-fi-hr', + ('fi', 'ht'): 'Helsinki-NLP/opus-mt-fi-ht', ('fi', 'hu'): 'Helsinki-NLP/opus-mt-fi-hu', + ('fi', 'id'): 'Helsinki-NLP/opus-mt-fi-id', ('fi', 'ig'): 'Helsinki-NLP/opus-mt-fi-ig', + ('fi', 'ilo'): 'Helsinki-NLP/opus-mt-fi-ilo', ('fi', 'is'): 'Helsinki-NLP/opus-mt-fi-is', + ('fi', 'iso'): 'Helsinki-NLP/opus-mt-fi-iso', ('fi', 'it'): 'Helsinki-NLP/opus-mt-fi-it', + ('fi', 'kg'): 'Helsinki-NLP/opus-mt-fi-kg', ('fi', 'kqn'): 'Helsinki-NLP/opus-mt-fi-kqn', + ('fi', 'lg'): 'Helsinki-NLP/opus-mt-fi-lg', ('fi', 'ln'): 'Helsinki-NLP/opus-mt-fi-ln', + ('fi', 'lu'): 'Helsinki-NLP/opus-mt-fi-lu', ('fi', 'lua'): 'Helsinki-NLP/opus-mt-fi-lua', + ('fi', 'lue'): 'Helsinki-NLP/opus-mt-fi-lue', ('fi', 'lus'): 'Helsinki-NLP/opus-mt-fi-lus', + ('fi', 'lv'): 'Helsinki-NLP/opus-mt-fi-lv', ('fi', 'mfe'): 'Helsinki-NLP/opus-mt-fi-mfe', + ('fi', 'mg'): 'Helsinki-NLP/opus-mt-fi-mg', ('fi', 'mh'): 'Helsinki-NLP/opus-mt-fi-mh', + ('fi', 'mk'): 'Helsinki-NLP/opus-mt-fi-mk', ('fi', 'mos'): 'Helsinki-NLP/opus-mt-fi-mos', + ('fi', 'mt'): 'Helsinki-NLP/opus-mt-fi-mt', ('fi', 'niu'): 'Helsinki-NLP/opus-mt-fi-niu', + ('fi', 'nl'): 'Helsinki-NLP/opus-mt-fi-nl', ('fi', 'no'): 'Helsinki-NLP/opus-mt-fi-no', + ('fi', 'nso'): 'Helsinki-NLP/opus-mt-fi-nso', ('fi', 'ny'): 'Helsinki-NLP/opus-mt-fi-ny', + ('fi', 'pag'): 'Helsinki-NLP/opus-mt-fi-pag', ('fi', 'pap'): 'Helsinki-NLP/opus-mt-fi-pap', + ('fi', 'pis'): 'Helsinki-NLP/opus-mt-fi-pis', ('fi', 'pon'): 'Helsinki-NLP/opus-mt-fi-pon', + ('fi', 'ro'): 'Helsinki-NLP/opus-mt-fi-ro', ('fi', 'ru'): 'Helsinki-NLP/opus-mt-fi-ru', + ('fi', 'run'): 'Helsinki-NLP/opus-mt-fi-run', ('fi', 'rw'): 'Helsinki-NLP/opus-mt-fi-rw', + ('fi', 'sg'): 'Helsinki-NLP/opus-mt-fi-sg', ('fi', 'sk'): 'Helsinki-NLP/opus-mt-fi-sk', + ('fi', 'sl'): 'Helsinki-NLP/opus-mt-fi-sl', ('fi', 'sm'): 'Helsinki-NLP/opus-mt-fi-sm', + ('fi', 'sn'): 'Helsinki-NLP/opus-mt-fi-sn', ('fi', 'sq'): 'Helsinki-NLP/opus-mt-fi-sq', + ('fi', 'srn'): 'Helsinki-NLP/opus-mt-fi-srn', ('fi', 'st'): 'Helsinki-NLP/opus-mt-fi-st', + ('fi', 'sv'): 'Helsinki-NLP/opus-mt-fi-sv', ('fi', 'sw'): 'Helsinki-NLP/opus-mt-fi-sw', + ('fi', 'swc'): 'Helsinki-NLP/opus-mt-fi-swc', ('fi', 'tiv'): 'Helsinki-NLP/opus-mt-fi-tiv', + ('fi', 'tll'): 'Helsinki-NLP/opus-mt-fi-tll', ('fi', 'tn'): 'Helsinki-NLP/opus-mt-fi-tn', + ('fi', 'to'): 'Helsinki-NLP/opus-mt-fi-to', ('fi', 'toi'): 'Helsinki-NLP/opus-mt-fi-toi', + ('fi', 'tpi'): 'Helsinki-NLP/opus-mt-fi-tpi', ('fi', 'tr'): 'Helsinki-NLP/opus-mt-fi-tr', + ('fi', 'ts'): 'Helsinki-NLP/opus-mt-fi-ts', ('fi', 'tvl'): 'Helsinki-NLP/opus-mt-fi-tvl', + ('fi', 'tw'): 'Helsinki-NLP/opus-mt-fi-tw', ('fi', 'ty'): 'Helsinki-NLP/opus-mt-fi-ty', + ('fi', 'uk'): 'Helsinki-NLP/opus-mt-fi-uk', ('fi', 've'): 'Helsinki-NLP/opus-mt-fi-ve', + ('fi', 'war'): 'Helsinki-NLP/opus-mt-fi-war', ('fi', 'wls'): 'Helsinki-NLP/opus-mt-fi-wls', + ('fi', 'xh'): 'Helsinki-NLP/opus-mt-fi-xh', ('fi', 'yap'): 'Helsinki-NLP/opus-mt-fi-yap', + ('fi', 'yo'): 'Helsinki-NLP/opus-mt-fi-yo', ('fi', 'zne'): 'Helsinki-NLP/opus-mt-fi-zne', + ('fi_nb_no_nn_ru_sv_en', 'SAMI'): 'Helsinki-NLP/opus-mt-fi_nb_no_nn_ru_sv_en-SAMI', + ('fiu', 'en'): 'Helsinki-NLP/opus-mt-fiu-en', ('fiu', 'fiu'): 'Helsinki-NLP/opus-mt-fiu-fiu', + ('fj', 'en'): 'Helsinki-NLP/opus-mt-fj-en', ('fj', 'fr'): 'Helsinki-NLP/opus-mt-fj-fr', + ('fr', 'af'): 'Helsinki-NLP/opus-mt-fr-af', ('fr', 'ar'): 'Helsinki-NLP/opus-mt-fr-ar', + ('fr', 'ase'): 'Helsinki-NLP/opus-mt-fr-ase', ('fr', 'bcl'): 'Helsinki-NLP/opus-mt-fr-bcl', + ('fr', 'bem'): 'Helsinki-NLP/opus-mt-fr-bem', ('fr', 'ber'): 'Helsinki-NLP/opus-mt-fr-ber', + ('fr', 'bg'): 'Helsinki-NLP/opus-mt-fr-bg', ('fr', 'bi'): 'Helsinki-NLP/opus-mt-fr-bi', + ('fr', 'bzs'): 'Helsinki-NLP/opus-mt-fr-bzs', ('fr', 'ca'): 'Helsinki-NLP/opus-mt-fr-ca', + ('fr', 'ceb'): 'Helsinki-NLP/opus-mt-fr-ceb', ('fr', 'crs'): 'Helsinki-NLP/opus-mt-fr-crs', + ('fr', 'de'): 'Helsinki-NLP/opus-mt-fr-de', ('fr', 'ee'): 'Helsinki-NLP/opus-mt-fr-ee', + ('fr', 'efi'): 'Helsinki-NLP/opus-mt-fr-efi', ('fr', 'el'): 'Helsinki-NLP/opus-mt-fr-el', + ('fr', 'en'): 'Helsinki-NLP/opus-mt-fr-en', ('fr', 'eo'): 'Helsinki-NLP/opus-mt-fr-eo', + ('fr', 'es'): 'Helsinki-NLP/opus-mt-fr-es', ('fr', 'fj'): 'Helsinki-NLP/opus-mt-fr-fj', + ('fr', 'gaa'): 'Helsinki-NLP/opus-mt-fr-gaa', ('fr', 'gil'): 'Helsinki-NLP/opus-mt-fr-gil', + ('fr', 'guw'): 'Helsinki-NLP/opus-mt-fr-guw', ('fr', 'ha'): 'Helsinki-NLP/opus-mt-fr-ha', + ('fr', 'he'): 'Helsinki-NLP/opus-mt-fr-he', ('fr', 'hil'): 'Helsinki-NLP/opus-mt-fr-hil', + ('fr', 'ho'): 'Helsinki-NLP/opus-mt-fr-ho', ('fr', 'hr'): 'Helsinki-NLP/opus-mt-fr-hr', + ('fr', 'ht'): 'Helsinki-NLP/opus-mt-fr-ht', ('fr', 'hu'): 'Helsinki-NLP/opus-mt-fr-hu', + ('fr', 'id'): 'Helsinki-NLP/opus-mt-fr-id', ('fr', 'ig'): 'Helsinki-NLP/opus-mt-fr-ig', + ('fr', 'ilo'): 'Helsinki-NLP/opus-mt-fr-ilo', ('fr', 'iso'): 'Helsinki-NLP/opus-mt-fr-iso', + ('fr', 'kg'): 'Helsinki-NLP/opus-mt-fr-kg', ('fr', 'kqn'): 'Helsinki-NLP/opus-mt-fr-kqn', + ('fr', 'kwy'): 'Helsinki-NLP/opus-mt-fr-kwy', ('fr', 'lg'): 'Helsinki-NLP/opus-mt-fr-lg', + ('fr', 'ln'): 'Helsinki-NLP/opus-mt-fr-ln', ('fr', 'loz'): 'Helsinki-NLP/opus-mt-fr-loz', + ('fr', 'lu'): 'Helsinki-NLP/opus-mt-fr-lu', ('fr', 'lua'): 'Helsinki-NLP/opus-mt-fr-lua', + ('fr', 'lue'): 'Helsinki-NLP/opus-mt-fr-lue', ('fr', 'lus'): 'Helsinki-NLP/opus-mt-fr-lus', + ('fr', 'mfe'): 'Helsinki-NLP/opus-mt-fr-mfe', ('fr', 'mh'): 'Helsinki-NLP/opus-mt-fr-mh', + ('fr', 'mos'): 'Helsinki-NLP/opus-mt-fr-mos', ('fr', 'ms'): 'Helsinki-NLP/opus-mt-fr-ms', + ('fr', 'mt'): 'Helsinki-NLP/opus-mt-fr-mt', ('fr', 'niu'): 'Helsinki-NLP/opus-mt-fr-niu', + ('fr', 'no'): 'Helsinki-NLP/opus-mt-fr-no', ('fr', 'nso'): 'Helsinki-NLP/opus-mt-fr-nso', + ('fr', 'ny'): 'Helsinki-NLP/opus-mt-fr-ny', ('fr', 'pag'): 'Helsinki-NLP/opus-mt-fr-pag', + ('fr', 'pap'): 'Helsinki-NLP/opus-mt-fr-pap', ('fr', 'pis'): 'Helsinki-NLP/opus-mt-fr-pis', + ('fr', 'pl'): 'Helsinki-NLP/opus-mt-fr-pl', ('fr', 'pon'): 'Helsinki-NLP/opus-mt-fr-pon', + ('fr', 'rnd'): 'Helsinki-NLP/opus-mt-fr-rnd', ('fr', 'ro'): 'Helsinki-NLP/opus-mt-fr-ro', + ('fr', 'ru'): 'Helsinki-NLP/opus-mt-fr-ru', ('fr', 'run'): 'Helsinki-NLP/opus-mt-fr-run', + ('fr', 'rw'): 'Helsinki-NLP/opus-mt-fr-rw', ('fr', 'sg'): 'Helsinki-NLP/opus-mt-fr-sg', + ('fr', 'sk'): 'Helsinki-NLP/opus-mt-fr-sk', ('fr', 'sl'): 'Helsinki-NLP/opus-mt-fr-sl', + ('fr', 'sm'): 'Helsinki-NLP/opus-mt-fr-sm', ('fr', 'sn'): 'Helsinki-NLP/opus-mt-fr-sn', + ('fr', 'srn'): 'Helsinki-NLP/opus-mt-fr-srn', ('fr', 'st'): 'Helsinki-NLP/opus-mt-fr-st', + ('fr', 'sv'): 'Helsinki-NLP/opus-mt-fr-sv', ('fr', 'swc'): 'Helsinki-NLP/opus-mt-fr-swc', + ('fr', 'tiv'): 'Helsinki-NLP/opus-mt-fr-tiv', ('fr', 'tl'): 'Helsinki-NLP/opus-mt-fr-tl', + ('fr', 'tll'): 'Helsinki-NLP/opus-mt-fr-tll', ('fr', 'tn'): 'Helsinki-NLP/opus-mt-fr-tn', + ('fr', 'to'): 'Helsinki-NLP/opus-mt-fr-to', ('fr', 'tpi'): 'Helsinki-NLP/opus-mt-fr-tpi', + ('fr', 'ts'): 'Helsinki-NLP/opus-mt-fr-ts', ('fr', 'tum'): 'Helsinki-NLP/opus-mt-fr-tum', + ('fr', 'tvl'): 'Helsinki-NLP/opus-mt-fr-tvl', ('fr', 'tw'): 'Helsinki-NLP/opus-mt-fr-tw', + ('fr', 'ty'): 'Helsinki-NLP/opus-mt-fr-ty', ('fr', 'uk'): 'Helsinki-NLP/opus-mt-fr-uk', + ('fr', 've'): 'Helsinki-NLP/opus-mt-fr-ve', ('fr', 'vi'): 'Helsinki-NLP/opus-mt-fr-vi', + ('fr', 'war'): 'Helsinki-NLP/opus-mt-fr-war', ('fr', 'wls'): 'Helsinki-NLP/opus-mt-fr-wls', + ('fr', 'xh'): 'Helsinki-NLP/opus-mt-fr-xh', ('fr', 'yap'): 'Helsinki-NLP/opus-mt-fr-yap', + ('fr', 'yo'): 'Helsinki-NLP/opus-mt-fr-yo', ('fr', 'zne'): 'Helsinki-NLP/opus-mt-fr-zne', + ('fse', 'fi'): 'Helsinki-NLP/opus-mt-fse-fi', ('ga', 'en'): 'Helsinki-NLP/opus-mt-ga-en', + ('gaa', 'de'): 'Helsinki-NLP/opus-mt-gaa-de', ('gaa', 'en'): 'Helsinki-NLP/opus-mt-gaa-en', + ('gaa', 'es'): 'Helsinki-NLP/opus-mt-gaa-es', ('gaa', 'fi'): 'Helsinki-NLP/opus-mt-gaa-fi', + ('gaa', 'fr'): 'Helsinki-NLP/opus-mt-gaa-fr', ('gaa', 'sv'): 'Helsinki-NLP/opus-mt-gaa-sv', + ('gem', 'en'): 'Helsinki-NLP/opus-mt-gem-en', ('gem', 'gem'): 'Helsinki-NLP/opus-mt-gem-gem', + ('gil', 'en'): 'Helsinki-NLP/opus-mt-gil-en', ('gil', 'es'): 'Helsinki-NLP/opus-mt-gil-es', + ('gil', 'fi'): 'Helsinki-NLP/opus-mt-gil-fi', ('gil', 'fr'): 'Helsinki-NLP/opus-mt-gil-fr', + ('gil', 'sv'): 'Helsinki-NLP/opus-mt-gil-sv', ('gl', 'en'): 'Helsinki-NLP/opus-mt-gl-en', + ('gl', 'es'): 'Helsinki-NLP/opus-mt-gl-es', ('gl', 'pt'): 'Helsinki-NLP/opus-mt-gl-pt', + ('gmq', 'en'): 'Helsinki-NLP/opus-mt-gmq-en', ('gmq', 'gmq'): 'Helsinki-NLP/opus-mt-gmq-gmq', + ('gmw', 'en'): 'Helsinki-NLP/opus-mt-gmw-en', ('gmw', 'gmw'): 'Helsinki-NLP/opus-mt-gmw-gmw', + ('grk', 'en'): 'Helsinki-NLP/opus-mt-grk-en', ('guw', 'de'): 'Helsinki-NLP/opus-mt-guw-de', + ('guw', 'en'): 'Helsinki-NLP/opus-mt-guw-en', ('guw', 'es'): 'Helsinki-NLP/opus-mt-guw-es', + ('guw', 'fi'): 'Helsinki-NLP/opus-mt-guw-fi', ('guw', 'fr'): 'Helsinki-NLP/opus-mt-guw-fr', + ('guw', 'sv'): 'Helsinki-NLP/opus-mt-guw-sv', ('gv', 'en'): 'Helsinki-NLP/opus-mt-gv-en', + ('ha', 'en'): 'Helsinki-NLP/opus-mt-ha-en', ('ha', 'es'): 'Helsinki-NLP/opus-mt-ha-es', + ('ha', 'fi'): 'Helsinki-NLP/opus-mt-ha-fi', ('ha', 'fr'): 'Helsinki-NLP/opus-mt-ha-fr', + ('ha', 'sv'): 'Helsinki-NLP/opus-mt-ha-sv', ('he', 'ar'): 'Helsinki-NLP/opus-mt-he-ar', + ('he', 'de'): 'Helsinki-NLP/opus-mt-he-de', ('he', 'eo'): 'Helsinki-NLP/opus-mt-he-eo', + ('he', 'es'): 'Helsinki-NLP/opus-mt-he-es', ('he', 'fi'): 'Helsinki-NLP/opus-mt-he-fi', + ('he', 'fr'): 'Helsinki-NLP/opus-mt-he-fr', ('he', 'it'): 'Helsinki-NLP/opus-mt-he-it', + ('he', 'ru'): 'Helsinki-NLP/opus-mt-he-ru', ('he', 'sv'): 'Helsinki-NLP/opus-mt-he-sv', + ('he', 'uk'): 'Helsinki-NLP/opus-mt-he-uk', ('hi', 'en'): 'Helsinki-NLP/opus-mt-hi-en', + ('hi', 'ur'): 'Helsinki-NLP/opus-mt-hi-ur', ('hil', 'de'): 'Helsinki-NLP/opus-mt-hil-de', + ('hil', 'en'): 'Helsinki-NLP/opus-mt-hil-en', ('hil', 'fi'): 'Helsinki-NLP/opus-mt-hil-fi', + ('ho', 'en'): 'Helsinki-NLP/opus-mt-ho-en', ('hr', 'es'): 'Helsinki-NLP/opus-mt-hr-es', + ('hr', 'fi'): 'Helsinki-NLP/opus-mt-hr-fi', ('hr', 'fr'): 'Helsinki-NLP/opus-mt-hr-fr', + ('hr', 'sv'): 'Helsinki-NLP/opus-mt-hr-sv', ('ht', 'en'): 'Helsinki-NLP/opus-mt-ht-en', + ('ht', 'es'): 'Helsinki-NLP/opus-mt-ht-es', ('ht', 'fi'): 'Helsinki-NLP/opus-mt-ht-fi', + ('ht', 'fr'): 'Helsinki-NLP/opus-mt-ht-fr', ('ht', 'sv'): 'Helsinki-NLP/opus-mt-ht-sv', + ('hu', 'de'): 'Helsinki-NLP/opus-mt-hu-de', ('hu', 'en'): 'Helsinki-NLP/opus-mt-hu-en', + ('hu', 'eo'): 'Helsinki-NLP/opus-mt-hu-eo', ('hu', 'fi'): 'Helsinki-NLP/opus-mt-hu-fi', + ('hu', 'fr'): 'Helsinki-NLP/opus-mt-hu-fr', ('hu', 'sv'): 'Helsinki-NLP/opus-mt-hu-sv', + ('hu', 'uk'): 'Helsinki-NLP/opus-mt-hu-uk', ('hy', 'en'): 'Helsinki-NLP/opus-mt-hy-en', + ('hy', 'ru'): 'Helsinki-NLP/opus-mt-hy-ru', ('id', 'en'): 'Helsinki-NLP/opus-mt-id-en', + ('id', 'es'): 'Helsinki-NLP/opus-mt-id-es', ('id', 'fi'): 'Helsinki-NLP/opus-mt-id-fi', + ('id', 'fr'): 'Helsinki-NLP/opus-mt-id-fr', ('id', 'sv'): 'Helsinki-NLP/opus-mt-id-sv', + ('ig', 'de'): 'Helsinki-NLP/opus-mt-ig-de', ('ig', 'en'): 'Helsinki-NLP/opus-mt-ig-en', + ('ig', 'es'): 'Helsinki-NLP/opus-mt-ig-es', ('ig', 'fi'): 'Helsinki-NLP/opus-mt-ig-fi', + ('ig', 'fr'): 'Helsinki-NLP/opus-mt-ig-fr', ('ig', 'sv'): 'Helsinki-NLP/opus-mt-ig-sv', + ('iir', 'en'): 'Helsinki-NLP/opus-mt-iir-en', ('iir', 'iir'): 'Helsinki-NLP/opus-mt-iir-iir', + ('ilo', 'de'): 'Helsinki-NLP/opus-mt-ilo-de', ('ilo', 'en'): 'Helsinki-NLP/opus-mt-ilo-en', + ('ilo', 'es'): 'Helsinki-NLP/opus-mt-ilo-es', ('ilo', 'fi'): 'Helsinki-NLP/opus-mt-ilo-fi', + ('ilo', 'sv'): 'Helsinki-NLP/opus-mt-ilo-sv', ('inc', 'en'): 'Helsinki-NLP/opus-mt-inc-en', + ('inc', 'inc'): 'Helsinki-NLP/opus-mt-inc-inc', ('ine', 'en'): 'Helsinki-NLP/opus-mt-ine-en', + ('ine', 'ine'): 'Helsinki-NLP/opus-mt-ine-ine', ('is', 'de'): 'Helsinki-NLP/opus-mt-is-de', + ('is', 'en'): 'Helsinki-NLP/opus-mt-is-en', ('is', 'eo'): 'Helsinki-NLP/opus-mt-is-eo', + ('is', 'es'): 'Helsinki-NLP/opus-mt-is-es', ('is', 'fi'): 'Helsinki-NLP/opus-mt-is-fi', + ('is', 'fr'): 'Helsinki-NLP/opus-mt-is-fr', ('is', 'it'): 'Helsinki-NLP/opus-mt-is-it', + ('is', 'sv'): 'Helsinki-NLP/opus-mt-is-sv', ('iso', 'en'): 'Helsinki-NLP/opus-mt-iso-en', + ('iso', 'es'): 'Helsinki-NLP/opus-mt-iso-es', ('iso', 'fi'): 'Helsinki-NLP/opus-mt-iso-fi', + ('iso', 'fr'): 'Helsinki-NLP/opus-mt-iso-fr', ('iso', 'sv'): 'Helsinki-NLP/opus-mt-iso-sv', + ('it', 'ar'): 'Helsinki-NLP/opus-mt-it-ar', ('it', 'bg'): 'Helsinki-NLP/opus-mt-it-bg', + ('it', 'ca'): 'Helsinki-NLP/opus-mt-it-ca', ('it', 'de'): 'Helsinki-NLP/opus-mt-it-de', + ('it', 'en'): 'Helsinki-NLP/opus-mt-it-en', ('it', 'eo'): 'Helsinki-NLP/opus-mt-it-eo', + ('it', 'es'): 'Helsinki-NLP/opus-mt-it-es', ('it', 'fr'): 'Helsinki-NLP/opus-mt-it-fr', + ('it', 'is'): 'Helsinki-NLP/opus-mt-it-is', ('it', 'lt'): 'Helsinki-NLP/opus-mt-it-lt', + ('it', 'ms'): 'Helsinki-NLP/opus-mt-it-ms', ('it', 'sv'): 'Helsinki-NLP/opus-mt-it-sv', + ('it', 'uk'): 'Helsinki-NLP/opus-mt-it-uk', ('it', 'vi'): 'Helsinki-NLP/opus-mt-it-vi', + ('itc', 'en'): 'Helsinki-NLP/opus-mt-itc-en', ('itc', 'itc'): 'Helsinki-NLP/opus-mt-itc-itc', + ('ja', 'ar'): 'Helsinki-NLP/opus-mt-ja-ar', ('ja', 'bg'): 'Helsinki-NLP/opus-mt-ja-bg', + ('ja', 'da'): 'Helsinki-NLP/opus-mt-ja-da', ('ja', 'de'): 'Helsinki-NLP/opus-mt-ja-de', + ('ja', 'en'): 'Helsinki-NLP/opus-mt-ja-en', ('ja', 'es'): 'Helsinki-NLP/opus-mt-ja-es', + ('ja', 'fi'): 'Helsinki-NLP/opus-mt-ja-fi', ('ja', 'fr'): 'Helsinki-NLP/opus-mt-ja-fr', + ('ja', 'he'): 'Helsinki-NLP/opus-mt-ja-he', ('ja', 'hu'): 'Helsinki-NLP/opus-mt-ja-hu', + ('ja', 'it'): 'Helsinki-NLP/opus-mt-ja-it', ('ja', 'ms'): 'Helsinki-NLP/opus-mt-ja-ms', + ('ja', 'nl'): 'Helsinki-NLP/opus-mt-ja-nl', ('ja', 'pl'): 'Helsinki-NLP/opus-mt-ja-pl', + ('ja', 'pt'): 'Helsinki-NLP/opus-mt-ja-pt', ('ja', 'ru'): 'Helsinki-NLP/opus-mt-ja-ru', + ('ja', 'sh'): 'Helsinki-NLP/opus-mt-ja-sh', ('ja', 'sv'): 'Helsinki-NLP/opus-mt-ja-sv', + ('ja', 'tr'): 'Helsinki-NLP/opus-mt-ja-tr', ('ja', 'vi'): 'Helsinki-NLP/opus-mt-ja-vi', + ('jap', 'en'): 'Helsinki-NLP/opus-mt-jap-en', ('ka', 'en'): 'Helsinki-NLP/opus-mt-ka-en', + ('ka', 'ru'): 'Helsinki-NLP/opus-mt-ka-ru', ('kab', 'en'): 'Helsinki-NLP/opus-mt-kab-en', + ('kg', 'en'): 'Helsinki-NLP/opus-mt-kg-en', ('kg', 'es'): 'Helsinki-NLP/opus-mt-kg-es', + ('kg', 'fr'): 'Helsinki-NLP/opus-mt-kg-fr', ('kg', 'sv'): 'Helsinki-NLP/opus-mt-kg-sv', + ('kj', 'en'): 'Helsinki-NLP/opus-mt-kj-en', ('kl', 'en'): 'Helsinki-NLP/opus-mt-kl-en', + ('ko', 'de'): 'Helsinki-NLP/opus-mt-ko-de', ('ko', 'en'): 'Helsinki-NLP/opus-mt-ko-en', + ('ko', 'es'): 'Helsinki-NLP/opus-mt-ko-es', ('ko', 'fi'): 'Helsinki-NLP/opus-mt-ko-fi', + ('ko', 'fr'): 'Helsinki-NLP/opus-mt-ko-fr', ('ko', 'hu'): 'Helsinki-NLP/opus-mt-ko-hu', + ('ko', 'ru'): 'Helsinki-NLP/opus-mt-ko-ru', ('ko', 'sv'): 'Helsinki-NLP/opus-mt-ko-sv', + ('kqn', 'en'): 'Helsinki-NLP/opus-mt-kqn-en', ('kqn', 'es'): 'Helsinki-NLP/opus-mt-kqn-es', + ('kqn', 'fr'): 'Helsinki-NLP/opus-mt-kqn-fr', ('kqn', 'sv'): 'Helsinki-NLP/opus-mt-kqn-sv', + ('kwn', 'en'): 'Helsinki-NLP/opus-mt-kwn-en', ('kwy', 'en'): 'Helsinki-NLP/opus-mt-kwy-en', + ('kwy', 'fr'): 'Helsinki-NLP/opus-mt-kwy-fr', ('kwy', 'sv'): 'Helsinki-NLP/opus-mt-kwy-sv', + ('lg', 'en'): 'Helsinki-NLP/opus-mt-lg-en', ('lg', 'es'): 'Helsinki-NLP/opus-mt-lg-es', + ('lg', 'fi'): 'Helsinki-NLP/opus-mt-lg-fi', ('lg', 'fr'): 'Helsinki-NLP/opus-mt-lg-fr', + ('lg', 'sv'): 'Helsinki-NLP/opus-mt-lg-sv', ('ln', 'de'): 'Helsinki-NLP/opus-mt-ln-de', + ('ln', 'en'): 'Helsinki-NLP/opus-mt-ln-en', ('ln', 'es'): 'Helsinki-NLP/opus-mt-ln-es', + ('ln', 'fr'): 'Helsinki-NLP/opus-mt-ln-fr', ('loz', 'de'): 'Helsinki-NLP/opus-mt-loz-de', + ('loz', 'en'): 'Helsinki-NLP/opus-mt-loz-en', ('loz', 'es'): 'Helsinki-NLP/opus-mt-loz-es', + ('loz', 'fi'): 'Helsinki-NLP/opus-mt-loz-fi', ('loz', 'fr'): 'Helsinki-NLP/opus-mt-loz-fr', + ('loz', 'sv'): 'Helsinki-NLP/opus-mt-loz-sv', ('lt', 'de'): 'Helsinki-NLP/opus-mt-lt-de', + ('lt', 'eo'): 'Helsinki-NLP/opus-mt-lt-eo', ('lt', 'es'): 'Helsinki-NLP/opus-mt-lt-es', + ('lt', 'fr'): 'Helsinki-NLP/opus-mt-lt-fr', ('lt', 'it'): 'Helsinki-NLP/opus-mt-lt-it', + ('lt', 'pl'): 'Helsinki-NLP/opus-mt-lt-pl', ('lt', 'ru'): 'Helsinki-NLP/opus-mt-lt-ru', + ('lt', 'sv'): 'Helsinki-NLP/opus-mt-lt-sv', ('lt', 'tr'): 'Helsinki-NLP/opus-mt-lt-tr', + ('lu', 'en'): 'Helsinki-NLP/opus-mt-lu-en', ('lu', 'es'): 'Helsinki-NLP/opus-mt-lu-es', + ('lu', 'fi'): 'Helsinki-NLP/opus-mt-lu-fi', ('lu', 'fr'): 'Helsinki-NLP/opus-mt-lu-fr', + ('lu', 'sv'): 'Helsinki-NLP/opus-mt-lu-sv', ('lua', 'en'): 'Helsinki-NLP/opus-mt-lua-en', + ('lua', 'es'): 'Helsinki-NLP/opus-mt-lua-es', ('lua', 'fi'): 'Helsinki-NLP/opus-mt-lua-fi', + ('lua', 'fr'): 'Helsinki-NLP/opus-mt-lua-fr', ('lua', 'sv'): 'Helsinki-NLP/opus-mt-lua-sv', + ('lue', 'en'): 'Helsinki-NLP/opus-mt-lue-en', ('lue', 'es'): 'Helsinki-NLP/opus-mt-lue-es', + ('lue', 'fi'): 'Helsinki-NLP/opus-mt-lue-fi', ('lue', 'fr'): 'Helsinki-NLP/opus-mt-lue-fr', + ('lue', 'sv'): 'Helsinki-NLP/opus-mt-lue-sv', ('lun', 'en'): 'Helsinki-NLP/opus-mt-lun-en', + ('luo', 'en'): 'Helsinki-NLP/opus-mt-luo-en', ('lus', 'en'): 'Helsinki-NLP/opus-mt-lus-en', + ('lus', 'es'): 'Helsinki-NLP/opus-mt-lus-es', ('lus', 'fi'): 'Helsinki-NLP/opus-mt-lus-fi', + ('lus', 'fr'): 'Helsinki-NLP/opus-mt-lus-fr', ('lus', 'sv'): 'Helsinki-NLP/opus-mt-lus-sv', + ('lv', 'en'): 'Helsinki-NLP/opus-mt-lv-en', ('lv', 'es'): 'Helsinki-NLP/opus-mt-lv-es', + ('lv', 'fi'): 'Helsinki-NLP/opus-mt-lv-fi', ('lv', 'fr'): 'Helsinki-NLP/opus-mt-lv-fr', + ('lv', 'ru'): 'Helsinki-NLP/opus-mt-lv-ru', ('lv', 'sv'): 'Helsinki-NLP/opus-mt-lv-sv', + ('mfe', 'en'): 'Helsinki-NLP/opus-mt-mfe-en', ('mfe', 'es'): 'Helsinki-NLP/opus-mt-mfe-es', + ('mfs', 'es'): 'Helsinki-NLP/opus-mt-mfs-es', ('mg', 'en'): 'Helsinki-NLP/opus-mt-mg-en', + ('mg', 'es'): 'Helsinki-NLP/opus-mt-mg-es', ('mh', 'en'): 'Helsinki-NLP/opus-mt-mh-en', + ('mh', 'es'): 'Helsinki-NLP/opus-mt-mh-es', ('mh', 'fi'): 'Helsinki-NLP/opus-mt-mh-fi', + ('mk', 'en'): 'Helsinki-NLP/opus-mt-mk-en', ('mk', 'es'): 'Helsinki-NLP/opus-mt-mk-es', + ('mk', 'fi'): 'Helsinki-NLP/opus-mt-mk-fi', ('mk', 'fr'): 'Helsinki-NLP/opus-mt-mk-fr', + ('mkh', 'en'): 'Helsinki-NLP/opus-mt-mkh-en', ('ml', 'en'): 'Helsinki-NLP/opus-mt-ml-en', + ('mos', 'en'): 'Helsinki-NLP/opus-mt-mos-en', ('mr', 'en'): 'Helsinki-NLP/opus-mt-mr-en', + ('ms', 'de'): 'Helsinki-NLP/opus-mt-ms-de', ('ms', 'fr'): 'Helsinki-NLP/opus-mt-ms-fr', + ('ms', 'it'): 'Helsinki-NLP/opus-mt-ms-it', ('ms', 'ms'): 'Helsinki-NLP/opus-mt-ms-ms', + ('mt', 'en'): 'Helsinki-NLP/opus-mt-mt-en', ('mt', 'es'): 'Helsinki-NLP/opus-mt-mt-es', + ('mt', 'fi'): 'Helsinki-NLP/opus-mt-mt-fi', ('mt', 'fr'): 'Helsinki-NLP/opus-mt-mt-fr', + ('mt', 'sv'): 'Helsinki-NLP/opus-mt-mt-sv', ('mul', 'en'): 'Helsinki-NLP/opus-mt-mul-en', + ('ng', 'en'): 'Helsinki-NLP/opus-mt-ng-en', ('nic', 'en'): 'Helsinki-NLP/opus-mt-nic-en', + ('niu', 'de'): 'Helsinki-NLP/opus-mt-niu-de', ('niu', 'en'): 'Helsinki-NLP/opus-mt-niu-en', + ('niu', 'es'): 'Helsinki-NLP/opus-mt-niu-es', ('niu', 'fi'): 'Helsinki-NLP/opus-mt-niu-fi', + ('niu', 'fr'): 'Helsinki-NLP/opus-mt-niu-fr', ('niu', 'sv'): 'Helsinki-NLP/opus-mt-niu-sv', + ('nl', 'af'): 'Helsinki-NLP/opus-mt-nl-af', ('nl', 'ca'): 'Helsinki-NLP/opus-mt-nl-ca', + ('nl', 'en'): 'Helsinki-NLP/opus-mt-nl-en', ('nl', 'eo'): 'Helsinki-NLP/opus-mt-nl-eo', + ('nl', 'es'): 'Helsinki-NLP/opus-mt-nl-es', ('nl', 'fi'): 'Helsinki-NLP/opus-mt-nl-fi', + ('nl', 'fr'): 'Helsinki-NLP/opus-mt-nl-fr', ('nl', 'no'): 'Helsinki-NLP/opus-mt-nl-no', + ('nl', 'sv'): 'Helsinki-NLP/opus-mt-nl-sv', ('nl', 'uk'): 'Helsinki-NLP/opus-mt-nl-uk', + ('no', 'da'): 'Helsinki-NLP/opus-mt-no-da', ('no', 'de'): 'Helsinki-NLP/opus-mt-no-de', + ('no', 'es'): 'Helsinki-NLP/opus-mt-no-es', ('no', 'fi'): 'Helsinki-NLP/opus-mt-no-fi', + ('no', 'fr'): 'Helsinki-NLP/opus-mt-no-fr', ('no', 'nl'): 'Helsinki-NLP/opus-mt-no-nl', + ('no', 'no'): 'Helsinki-NLP/opus-mt-no-no', ('no', 'pl'): 'Helsinki-NLP/opus-mt-no-pl', + ('no', 'ru'): 'Helsinki-NLP/opus-mt-no-ru', ('no', 'sv'): 'Helsinki-NLP/opus-mt-no-sv', + ('no', 'uk'): 'Helsinki-NLP/opus-mt-no-uk', ('nso', 'de'): 'Helsinki-NLP/opus-mt-nso-de', + ('nso', 'en'): 'Helsinki-NLP/opus-mt-nso-en', ('nso', 'es'): 'Helsinki-NLP/opus-mt-nso-es', + ('nso', 'fi'): 'Helsinki-NLP/opus-mt-nso-fi', ('nso', 'fr'): 'Helsinki-NLP/opus-mt-nso-fr', + ('nso', 'sv'): 'Helsinki-NLP/opus-mt-nso-sv', ('ny', 'de'): 'Helsinki-NLP/opus-mt-ny-de', + ('ny', 'en'): 'Helsinki-NLP/opus-mt-ny-en', ('ny', 'es'): 'Helsinki-NLP/opus-mt-ny-es', + ('nyk', 'en'): 'Helsinki-NLP/opus-mt-nyk-en', ('om', 'en'): 'Helsinki-NLP/opus-mt-om-en', + ('pa', 'en'): 'Helsinki-NLP/opus-mt-pa-en', ('pag', 'de'): 'Helsinki-NLP/opus-mt-pag-de', + ('pag', 'en'): 'Helsinki-NLP/opus-mt-pag-en', ('pag', 'es'): 'Helsinki-NLP/opus-mt-pag-es', + ('pag', 'fi'): 'Helsinki-NLP/opus-mt-pag-fi', ('pag', 'sv'): 'Helsinki-NLP/opus-mt-pag-sv', + ('pap', 'de'): 'Helsinki-NLP/opus-mt-pap-de', ('pap', 'en'): 'Helsinki-NLP/opus-mt-pap-en', + ('pap', 'es'): 'Helsinki-NLP/opus-mt-pap-es', ('pap', 'fi'): 'Helsinki-NLP/opus-mt-pap-fi', + ('pap', 'fr'): 'Helsinki-NLP/opus-mt-pap-fr', ('phi', 'en'): 'Helsinki-NLP/opus-mt-phi-en', + ('pis', 'en'): 'Helsinki-NLP/opus-mt-pis-en', ('pis', 'es'): 'Helsinki-NLP/opus-mt-pis-es', + ('pis', 'fi'): 'Helsinki-NLP/opus-mt-pis-fi', ('pis', 'fr'): 'Helsinki-NLP/opus-mt-pis-fr', + ('pis', 'sv'): 'Helsinki-NLP/opus-mt-pis-sv', ('pl', 'ar'): 'Helsinki-NLP/opus-mt-pl-ar', + ('pl', 'de'): 'Helsinki-NLP/opus-mt-pl-de', ('pl', 'en'): 'Helsinki-NLP/opus-mt-pl-en', + ('pl', 'eo'): 'Helsinki-NLP/opus-mt-pl-eo', ('pl', 'es'): 'Helsinki-NLP/opus-mt-pl-es', + ('pl', 'fr'): 'Helsinki-NLP/opus-mt-pl-fr', ('pl', 'lt'): 'Helsinki-NLP/opus-mt-pl-lt', + ('pl', 'no'): 'Helsinki-NLP/opus-mt-pl-no', ('pl', 'sv'): 'Helsinki-NLP/opus-mt-pl-sv', + ('pl', 'uk'): 'Helsinki-NLP/opus-mt-pl-uk', ('pon', 'en'): 'Helsinki-NLP/opus-mt-pon-en', + ('pon', 'es'): 'Helsinki-NLP/opus-mt-pon-es', ('pon', 'fi'): 'Helsinki-NLP/opus-mt-pon-fi', + ('pon', 'fr'): 'Helsinki-NLP/opus-mt-pon-fr', ('pon', 'sv'): 'Helsinki-NLP/opus-mt-pon-sv', + ('pqe', 'en'): 'Helsinki-NLP/opus-mt-pqe-en', ('prl', 'es'): 'Helsinki-NLP/opus-mt-prl-es', + ('pt', 'ca'): 'Helsinki-NLP/opus-mt-pt-ca', ('pt', 'eo'): 'Helsinki-NLP/opus-mt-pt-eo', + ('pt', 'gl'): 'Helsinki-NLP/opus-mt-pt-gl', ('pt', 'tl'): 'Helsinki-NLP/opus-mt-pt-tl', + ('pt', 'uk'): 'Helsinki-NLP/opus-mt-pt-uk', ('rn', 'de'): 'Helsinki-NLP/opus-mt-rn-de', + ('rn', 'en'): 'Helsinki-NLP/opus-mt-rn-en', ('rn', 'es'): 'Helsinki-NLP/opus-mt-rn-es', + ('rn', 'fr'): 'Helsinki-NLP/opus-mt-rn-fr', ('rn', 'ru'): 'Helsinki-NLP/opus-mt-rn-ru', + ('rnd', 'en'): 'Helsinki-NLP/opus-mt-rnd-en', ('rnd', 'fr'): 'Helsinki-NLP/opus-mt-rnd-fr', + ('rnd', 'sv'): 'Helsinki-NLP/opus-mt-rnd-sv', ('ro', 'eo'): 'Helsinki-NLP/opus-mt-ro-eo', + ('ro', 'fi'): 'Helsinki-NLP/opus-mt-ro-fi', ('ro', 'fr'): 'Helsinki-NLP/opus-mt-ro-fr', + ('ro', 'sv'): 'Helsinki-NLP/opus-mt-ro-sv', ('roa', 'en'): 'Helsinki-NLP/opus-mt-roa-en', + ('ru', 'af'): 'Helsinki-NLP/opus-mt-ru-af', ('ru', 'ar'): 'Helsinki-NLP/opus-mt-ru-ar', + ('ru', 'bg'): 'Helsinki-NLP/opus-mt-ru-bg', ('ru', 'da'): 'Helsinki-NLP/opus-mt-ru-da', + ('ru', 'en'): 'Helsinki-NLP/opus-mt-ru-en', ('ru', 'eo'): 'Helsinki-NLP/opus-mt-ru-eo', + ('ru', 'es'): 'Helsinki-NLP/opus-mt-ru-es', ('ru', 'et'): 'Helsinki-NLP/opus-mt-ru-et', + ('ru', 'eu'): 'Helsinki-NLP/opus-mt-ru-eu', ('ru', 'fi'): 'Helsinki-NLP/opus-mt-ru-fi', + ('ru', 'fr'): 'Helsinki-NLP/opus-mt-ru-fr', ('ru', 'he'): 'Helsinki-NLP/opus-mt-ru-he', + ('ru', 'hy'): 'Helsinki-NLP/opus-mt-ru-hy', ('ru', 'lt'): 'Helsinki-NLP/opus-mt-ru-lt', + ('ru', 'lv'): 'Helsinki-NLP/opus-mt-ru-lv', ('ru', 'no'): 'Helsinki-NLP/opus-mt-ru-no', + ('ru', 'sl'): 'Helsinki-NLP/opus-mt-ru-sl', ('ru', 'sv'): 'Helsinki-NLP/opus-mt-ru-sv', + ('ru', 'uk'): 'Helsinki-NLP/opus-mt-ru-uk', ('ru', 'vi'): 'Helsinki-NLP/opus-mt-ru-vi', + ('run', 'en'): 'Helsinki-NLP/opus-mt-run-en', ('run', 'es'): 'Helsinki-NLP/opus-mt-run-es', + ('run', 'sv'): 'Helsinki-NLP/opus-mt-run-sv', ('rw', 'en'): 'Helsinki-NLP/opus-mt-rw-en', + ('rw', 'es'): 'Helsinki-NLP/opus-mt-rw-es', ('rw', 'fr'): 'Helsinki-NLP/opus-mt-rw-fr', + ('rw', 'sv'): 'Helsinki-NLP/opus-mt-rw-sv', ('sal', 'en'): 'Helsinki-NLP/opus-mt-sal-en', + ('sem', 'en'): 'Helsinki-NLP/opus-mt-sem-en', ('sem', 'sem'): 'Helsinki-NLP/opus-mt-sem-sem', + ('sg', 'en'): 'Helsinki-NLP/opus-mt-sg-en', ('sg', 'es'): 'Helsinki-NLP/opus-mt-sg-es', + ('sg', 'fi'): 'Helsinki-NLP/opus-mt-sg-fi', ('sg', 'fr'): 'Helsinki-NLP/opus-mt-sg-fr', + ('sg', 'sv'): 'Helsinki-NLP/opus-mt-sg-sv', ('sh', 'eo'): 'Helsinki-NLP/opus-mt-sh-eo', + ('sh', 'uk'): 'Helsinki-NLP/opus-mt-sh-uk', ('sk', 'en'): 'Helsinki-NLP/opus-mt-sk-en', + ('sk', 'es'): 'Helsinki-NLP/opus-mt-sk-es', ('sk', 'fi'): 'Helsinki-NLP/opus-mt-sk-fi', + ('sk', 'fr'): 'Helsinki-NLP/opus-mt-sk-fr', ('sk', 'sv'): 'Helsinki-NLP/opus-mt-sk-sv', + ('sl', 'es'): 'Helsinki-NLP/opus-mt-sl-es', ('sl', 'fi'): 'Helsinki-NLP/opus-mt-sl-fi', + ('sl', 'fr'): 'Helsinki-NLP/opus-mt-sl-fr', ('sl', 'ru'): 'Helsinki-NLP/opus-mt-sl-ru', + ('sl', 'sv'): 'Helsinki-NLP/opus-mt-sl-sv', ('sl', 'uk'): 'Helsinki-NLP/opus-mt-sl-uk', + ('sla', 'en'): 'Helsinki-NLP/opus-mt-sla-en', ('sla', 'sla'): 'Helsinki-NLP/opus-mt-sla-sla', + ('sm', 'en'): 'Helsinki-NLP/opus-mt-sm-en', ('sm', 'es'): 'Helsinki-NLP/opus-mt-sm-es', + ('sm', 'fr'): 'Helsinki-NLP/opus-mt-sm-fr', ('sn', 'en'): 'Helsinki-NLP/opus-mt-sn-en', + ('sn', 'es'): 'Helsinki-NLP/opus-mt-sn-es', ('sn', 'fr'): 'Helsinki-NLP/opus-mt-sn-fr', + ('sn', 'sv'): 'Helsinki-NLP/opus-mt-sn-sv', ('sq', 'en'): 'Helsinki-NLP/opus-mt-sq-en', + ('sq', 'es'): 'Helsinki-NLP/opus-mt-sq-es', ('sq', 'sv'): 'Helsinki-NLP/opus-mt-sq-sv', + ('srn', 'en'): 'Helsinki-NLP/opus-mt-srn-en', ('srn', 'es'): 'Helsinki-NLP/opus-mt-srn-es', + ('srn', 'fr'): 'Helsinki-NLP/opus-mt-srn-fr', ('srn', 'sv'): 'Helsinki-NLP/opus-mt-srn-sv', + ('ss', 'en'): 'Helsinki-NLP/opus-mt-ss-en', ('ssp', 'es'): 'Helsinki-NLP/opus-mt-ssp-es', + ('st', 'en'): 'Helsinki-NLP/opus-mt-st-en', ('st', 'es'): 'Helsinki-NLP/opus-mt-st-es', + ('st', 'fi'): 'Helsinki-NLP/opus-mt-st-fi', ('st', 'fr'): 'Helsinki-NLP/opus-mt-st-fr', + ('st', 'sv'): 'Helsinki-NLP/opus-mt-st-sv', ('sv', 'NORWAY'): 'Helsinki-NLP/opus-mt-sv-NORWAY', + ('sv', 'ZH'): 'Helsinki-NLP/opus-mt-sv-ZH', ('sv', 'af'): 'Helsinki-NLP/opus-mt-sv-af', + ('sv', 'ase'): 'Helsinki-NLP/opus-mt-sv-ase', ('sv', 'bcl'): 'Helsinki-NLP/opus-mt-sv-bcl', + ('sv', 'bem'): 'Helsinki-NLP/opus-mt-sv-bem', ('sv', 'bg'): 'Helsinki-NLP/opus-mt-sv-bg', + ('sv', 'bi'): 'Helsinki-NLP/opus-mt-sv-bi', ('sv', 'bzs'): 'Helsinki-NLP/opus-mt-sv-bzs', + ('sv', 'ceb'): 'Helsinki-NLP/opus-mt-sv-ceb', ('sv', 'chk'): 'Helsinki-NLP/opus-mt-sv-chk', + ('sv', 'crs'): 'Helsinki-NLP/opus-mt-sv-crs', ('sv', 'cs'): 'Helsinki-NLP/opus-mt-sv-cs', + ('sv', 'ee'): 'Helsinki-NLP/opus-mt-sv-ee', ('sv', 'efi'): 'Helsinki-NLP/opus-mt-sv-efi', + ('sv', 'el'): 'Helsinki-NLP/opus-mt-sv-el', ('sv', 'en'): 'Helsinki-NLP/opus-mt-sv-en', + ('sv', 'eo'): 'Helsinki-NLP/opus-mt-sv-eo', ('sv', 'es'): 'Helsinki-NLP/opus-mt-sv-es', + ('sv', 'et'): 'Helsinki-NLP/opus-mt-sv-et', ('sv', 'fi'): 'Helsinki-NLP/opus-mt-sv-fi', + ('sv', 'fj'): 'Helsinki-NLP/opus-mt-sv-fj', ('sv', 'fr'): 'Helsinki-NLP/opus-mt-sv-fr', + ('sv', 'gaa'): 'Helsinki-NLP/opus-mt-sv-gaa', ('sv', 'gil'): 'Helsinki-NLP/opus-mt-sv-gil', + ('sv', 'guw'): 'Helsinki-NLP/opus-mt-sv-guw', ('sv', 'ha'): 'Helsinki-NLP/opus-mt-sv-ha', + ('sv', 'he'): 'Helsinki-NLP/opus-mt-sv-he', ('sv', 'hil'): 'Helsinki-NLP/opus-mt-sv-hil', + ('sv', 'ho'): 'Helsinki-NLP/opus-mt-sv-ho', ('sv', 'hr'): 'Helsinki-NLP/opus-mt-sv-hr', + ('sv', 'ht'): 'Helsinki-NLP/opus-mt-sv-ht', ('sv', 'hu'): 'Helsinki-NLP/opus-mt-sv-hu', + ('sv', 'id'): 'Helsinki-NLP/opus-mt-sv-id', ('sv', 'ig'): 'Helsinki-NLP/opus-mt-sv-ig', + ('sv', 'ilo'): 'Helsinki-NLP/opus-mt-sv-ilo', ('sv', 'is'): 'Helsinki-NLP/opus-mt-sv-is', + ('sv', 'iso'): 'Helsinki-NLP/opus-mt-sv-iso', ('sv', 'kg'): 'Helsinki-NLP/opus-mt-sv-kg', + ('sv', 'kqn'): 'Helsinki-NLP/opus-mt-sv-kqn', ('sv', 'kwy'): 'Helsinki-NLP/opus-mt-sv-kwy', + ('sv', 'lg'): 'Helsinki-NLP/opus-mt-sv-lg', ('sv', 'ln'): 'Helsinki-NLP/opus-mt-sv-ln', + ('sv', 'lu'): 'Helsinki-NLP/opus-mt-sv-lu', ('sv', 'lua'): 'Helsinki-NLP/opus-mt-sv-lua', + ('sv', 'lue'): 'Helsinki-NLP/opus-mt-sv-lue', ('sv', 'lus'): 'Helsinki-NLP/opus-mt-sv-lus', + ('sv', 'lv'): 'Helsinki-NLP/opus-mt-sv-lv', ('sv', 'mfe'): 'Helsinki-NLP/opus-mt-sv-mfe', + ('sv', 'mh'): 'Helsinki-NLP/opus-mt-sv-mh', ('sv', 'mos'): 'Helsinki-NLP/opus-mt-sv-mos', + ('sv', 'mt'): 'Helsinki-NLP/opus-mt-sv-mt', ('sv', 'niu'): 'Helsinki-NLP/opus-mt-sv-niu', + ('sv', 'nl'): 'Helsinki-NLP/opus-mt-sv-nl', ('sv', 'no'): 'Helsinki-NLP/opus-mt-sv-no', + ('sv', 'nso'): 'Helsinki-NLP/opus-mt-sv-nso', ('sv', 'ny'): 'Helsinki-NLP/opus-mt-sv-ny', + ('sv', 'pag'): 'Helsinki-NLP/opus-mt-sv-pag', ('sv', 'pap'): 'Helsinki-NLP/opus-mt-sv-pap', + ('sv', 'pis'): 'Helsinki-NLP/opus-mt-sv-pis', ('sv', 'pon'): 'Helsinki-NLP/opus-mt-sv-pon', + ('sv', 'rnd'): 'Helsinki-NLP/opus-mt-sv-rnd', ('sv', 'ro'): 'Helsinki-NLP/opus-mt-sv-ro', + ('sv', 'ru'): 'Helsinki-NLP/opus-mt-sv-ru', ('sv', 'run'): 'Helsinki-NLP/opus-mt-sv-run', + ('sv', 'rw'): 'Helsinki-NLP/opus-mt-sv-rw', ('sv', 'sg'): 'Helsinki-NLP/opus-mt-sv-sg', + ('sv', 'sk'): 'Helsinki-NLP/opus-mt-sv-sk', ('sv', 'sl'): 'Helsinki-NLP/opus-mt-sv-sl', + ('sv', 'sm'): 'Helsinki-NLP/opus-mt-sv-sm', ('sv', 'sn'): 'Helsinki-NLP/opus-mt-sv-sn', + ('sv', 'sq'): 'Helsinki-NLP/opus-mt-sv-sq', ('sv', 'srn'): 'Helsinki-NLP/opus-mt-sv-srn', + ('sv', 'st'): 'Helsinki-NLP/opus-mt-sv-st', ('sv', 'sv'): 'Helsinki-NLP/opus-mt-sv-sv', + ('sv', 'swc'): 'Helsinki-NLP/opus-mt-sv-swc', ('sv', 'th'): 'Helsinki-NLP/opus-mt-sv-th', + ('sv', 'tiv'): 'Helsinki-NLP/opus-mt-sv-tiv', ('sv', 'tll'): 'Helsinki-NLP/opus-mt-sv-tll', + ('sv', 'tn'): 'Helsinki-NLP/opus-mt-sv-tn', ('sv', 'to'): 'Helsinki-NLP/opus-mt-sv-to', + ('sv', 'toi'): 'Helsinki-NLP/opus-mt-sv-toi', ('sv', 'tpi'): 'Helsinki-NLP/opus-mt-sv-tpi', + ('sv', 'ts'): 'Helsinki-NLP/opus-mt-sv-ts', ('sv', 'tum'): 'Helsinki-NLP/opus-mt-sv-tum', + ('sv', 'tvl'): 'Helsinki-NLP/opus-mt-sv-tvl', ('sv', 'tw'): 'Helsinki-NLP/opus-mt-sv-tw', + ('sv', 'ty'): 'Helsinki-NLP/opus-mt-sv-ty', ('sv', 'uk'): 'Helsinki-NLP/opus-mt-sv-uk', + ('sv', 'umb'): 'Helsinki-NLP/opus-mt-sv-umb', ('sv', 've'): 'Helsinki-NLP/opus-mt-sv-ve', + ('sv', 'war'): 'Helsinki-NLP/opus-mt-sv-war', ('sv', 'wls'): 'Helsinki-NLP/opus-mt-sv-wls', + ('sv', 'xh'): 'Helsinki-NLP/opus-mt-sv-xh', ('sv', 'yap'): 'Helsinki-NLP/opus-mt-sv-yap', + ('sv', 'yo'): 'Helsinki-NLP/opus-mt-sv-yo', ('sv', 'zne'): 'Helsinki-NLP/opus-mt-sv-zne', + ('swc', 'en'): 'Helsinki-NLP/opus-mt-swc-en', ('swc', 'es'): 'Helsinki-NLP/opus-mt-swc-es', + ('swc', 'fi'): 'Helsinki-NLP/opus-mt-swc-fi', ('swc', 'fr'): 'Helsinki-NLP/opus-mt-swc-fr', + ('swc', 'sv'): 'Helsinki-NLP/opus-mt-swc-sv', ('taw', 'en'): 'Helsinki-NLP/opus-mt-taw-en', + ('th', 'en'): 'Helsinki-NLP/opus-mt-th-en', ('th', 'fr'): 'Helsinki-NLP/opus-mt-th-fr', + ('ti', 'en'): 'Helsinki-NLP/opus-mt-ti-en', ('tiv', 'en'): 'Helsinki-NLP/opus-mt-tiv-en', + ('tiv', 'fr'): 'Helsinki-NLP/opus-mt-tiv-fr', ('tiv', 'sv'): 'Helsinki-NLP/opus-mt-tiv-sv', + ('tl', 'de'): 'Helsinki-NLP/opus-mt-tl-de', ('tl', 'en'): 'Helsinki-NLP/opus-mt-tl-en', + ('tl', 'es'): 'Helsinki-NLP/opus-mt-tl-es', ('tl', 'pt'): 'Helsinki-NLP/opus-mt-tl-pt', + ('tll', 'en'): 'Helsinki-NLP/opus-mt-tll-en', ('tll', 'es'): 'Helsinki-NLP/opus-mt-tll-es', + ('tll', 'fi'): 'Helsinki-NLP/opus-mt-tll-fi', ('tll', 'fr'): 'Helsinki-NLP/opus-mt-tll-fr', + ('tll', 'sv'): 'Helsinki-NLP/opus-mt-tll-sv', ('tn', 'en'): 'Helsinki-NLP/opus-mt-tn-en', + ('tn', 'es'): 'Helsinki-NLP/opus-mt-tn-es', ('tn', 'fr'): 'Helsinki-NLP/opus-mt-tn-fr', + ('tn', 'sv'): 'Helsinki-NLP/opus-mt-tn-sv', ('to', 'en'): 'Helsinki-NLP/opus-mt-to-en', + ('to', 'es'): 'Helsinki-NLP/opus-mt-to-es', ('to', 'fr'): 'Helsinki-NLP/opus-mt-to-fr', + ('to', 'sv'): 'Helsinki-NLP/opus-mt-to-sv', ('toi', 'en'): 'Helsinki-NLP/opus-mt-toi-en', + ('toi', 'es'): 'Helsinki-NLP/opus-mt-toi-es', ('toi', 'fi'): 'Helsinki-NLP/opus-mt-toi-fi', + ('toi', 'fr'): 'Helsinki-NLP/opus-mt-toi-fr', ('toi', 'sv'): 'Helsinki-NLP/opus-mt-toi-sv', + ('tpi', 'en'): 'Helsinki-NLP/opus-mt-tpi-en', ('tpi', 'sv'): 'Helsinki-NLP/opus-mt-tpi-sv', + ('tr', 'ar'): 'Helsinki-NLP/opus-mt-tr-ar', ('tr', 'az'): 'Helsinki-NLP/opus-mt-tr-az', + ('tr', 'en'): 'Helsinki-NLP/opus-mt-tr-en', ('tr', 'eo'): 'Helsinki-NLP/opus-mt-tr-eo', + ('tr', 'es'): 'Helsinki-NLP/opus-mt-tr-es', ('tr', 'fr'): 'Helsinki-NLP/opus-mt-tr-fr', + ('tr', 'lt'): 'Helsinki-NLP/opus-mt-tr-lt', ('tr', 'sv'): 'Helsinki-NLP/opus-mt-tr-sv', + ('tr', 'uk'): 'Helsinki-NLP/opus-mt-tr-uk', ('trk', 'en'): 'Helsinki-NLP/opus-mt-trk-en', + ('ts', 'en'): 'Helsinki-NLP/opus-mt-ts-en', ('ts', 'es'): 'Helsinki-NLP/opus-mt-ts-es', + ('ts', 'fi'): 'Helsinki-NLP/opus-mt-ts-fi', ('ts', 'fr'): 'Helsinki-NLP/opus-mt-ts-fr', + ('ts', 'sv'): 'Helsinki-NLP/opus-mt-ts-sv', ('tum', 'en'): 'Helsinki-NLP/opus-mt-tum-en', + ('tum', 'es'): 'Helsinki-NLP/opus-mt-tum-es', ('tum', 'fr'): 'Helsinki-NLP/opus-mt-tum-fr', + ('tum', 'sv'): 'Helsinki-NLP/opus-mt-tum-sv', ('tvl', 'en'): 'Helsinki-NLP/opus-mt-tvl-en', + ('tvl', 'es'): 'Helsinki-NLP/opus-mt-tvl-es', ('tvl', 'fi'): 'Helsinki-NLP/opus-mt-tvl-fi', + ('tvl', 'fr'): 'Helsinki-NLP/opus-mt-tvl-fr', ('tvl', 'sv'): 'Helsinki-NLP/opus-mt-tvl-sv', + ('tw', 'es'): 'Helsinki-NLP/opus-mt-tw-es', ('tw', 'fi'): 'Helsinki-NLP/opus-mt-tw-fi', + ('tw', 'fr'): 'Helsinki-NLP/opus-mt-tw-fr', ('tw', 'sv'): 'Helsinki-NLP/opus-mt-tw-sv', + ('ty', 'es'): 'Helsinki-NLP/opus-mt-ty-es', ('ty', 'fi'): 'Helsinki-NLP/opus-mt-ty-fi', + ('ty', 'fr'): 'Helsinki-NLP/opus-mt-ty-fr', ('ty', 'sv'): 'Helsinki-NLP/opus-mt-ty-sv', + ('tzo', 'es'): 'Helsinki-NLP/opus-mt-tzo-es', ('uk', 'bg'): 'Helsinki-NLP/opus-mt-uk-bg', + ('uk', 'ca'): 'Helsinki-NLP/opus-mt-uk-ca', ('uk', 'cs'): 'Helsinki-NLP/opus-mt-uk-cs', + ('uk', 'de'): 'Helsinki-NLP/opus-mt-uk-de', ('uk', 'en'): 'Helsinki-NLP/opus-mt-uk-en', + ('uk', 'es'): 'Helsinki-NLP/opus-mt-uk-es', ('uk', 'fi'): 'Helsinki-NLP/opus-mt-uk-fi', + ('uk', 'fr'): 'Helsinki-NLP/opus-mt-uk-fr', ('uk', 'he'): 'Helsinki-NLP/opus-mt-uk-he', + ('uk', 'hu'): 'Helsinki-NLP/opus-mt-uk-hu', ('uk', 'it'): 'Helsinki-NLP/opus-mt-uk-it', + ('uk', 'nl'): 'Helsinki-NLP/opus-mt-uk-nl', ('uk', 'no'): 'Helsinki-NLP/opus-mt-uk-no', + ('uk', 'pl'): 'Helsinki-NLP/opus-mt-uk-pl', ('uk', 'pt'): 'Helsinki-NLP/opus-mt-uk-pt', + ('uk', 'ru'): 'Helsinki-NLP/opus-mt-uk-ru', ('uk', 'sh'): 'Helsinki-NLP/opus-mt-uk-sh', + ('uk', 'sl'): 'Helsinki-NLP/opus-mt-uk-sl', ('uk', 'sv'): 'Helsinki-NLP/opus-mt-uk-sv', + ('uk', 'tr'): 'Helsinki-NLP/opus-mt-uk-tr', ('umb', 'en'): 'Helsinki-NLP/opus-mt-umb-en', + ('ur', 'en'): 'Helsinki-NLP/opus-mt-ur-en', ('urj', 'en'): 'Helsinki-NLP/opus-mt-urj-en', + ('urj', 'urj'): 'Helsinki-NLP/opus-mt-urj-urj', ('ve', 'en'): 'Helsinki-NLP/opus-mt-ve-en', + ('ve', 'es'): 'Helsinki-NLP/opus-mt-ve-es', ('vi', 'de'): 'Helsinki-NLP/opus-mt-vi-de', + ('vi', 'en'): 'Helsinki-NLP/opus-mt-vi-en', ('vi', 'eo'): 'Helsinki-NLP/opus-mt-vi-eo', + ('vi', 'es'): 'Helsinki-NLP/opus-mt-vi-es', ('vi', 'fr'): 'Helsinki-NLP/opus-mt-vi-fr', + ('vi', 'it'): 'Helsinki-NLP/opus-mt-vi-it', ('vi', 'ru'): 'Helsinki-NLP/opus-mt-vi-ru', + ('vsl', 'es'): 'Helsinki-NLP/opus-mt-vsl-es', ('wa', 'en'): 'Helsinki-NLP/opus-mt-wa-en', + ('wal', 'en'): 'Helsinki-NLP/opus-mt-wal-en', ('war', 'en'): 'Helsinki-NLP/opus-mt-war-en', + ('war', 'es'): 'Helsinki-NLP/opus-mt-war-es', ('war', 'fi'): 'Helsinki-NLP/opus-mt-war-fi', + ('war', 'fr'): 'Helsinki-NLP/opus-mt-war-fr', ('war', 'sv'): 'Helsinki-NLP/opus-mt-war-sv', + ('wls', 'en'): 'Helsinki-NLP/opus-mt-wls-en', ('wls', 'fr'): 'Helsinki-NLP/opus-mt-wls-fr', + ('wls', 'sv'): 'Helsinki-NLP/opus-mt-wls-sv', ('xh', 'en'): 'Helsinki-NLP/opus-mt-xh-en', + ('xh', 'es'): 'Helsinki-NLP/opus-mt-xh-es', ('xh', 'fr'): 'Helsinki-NLP/opus-mt-xh-fr', + ('xh', 'sv'): 'Helsinki-NLP/opus-mt-xh-sv', ('yap', 'en'): 'Helsinki-NLP/opus-mt-yap-en', + ('yap', 'fr'): 'Helsinki-NLP/opus-mt-yap-fr', ('yap', 'sv'): 'Helsinki-NLP/opus-mt-yap-sv', + ('yo', 'en'): 'Helsinki-NLP/opus-mt-yo-en', ('yo', 'es'): 'Helsinki-NLP/opus-mt-yo-es', + ('yo', 'fi'): 'Helsinki-NLP/opus-mt-yo-fi', ('yo', 'fr'): 'Helsinki-NLP/opus-mt-yo-fr', + ('yo', 'sv'): 'Helsinki-NLP/opus-mt-yo-sv', ('zai', 'es'): 'Helsinki-NLP/opus-mt-zai-es', + ('zh', 'bg'): 'Helsinki-NLP/opus-mt-zh-bg', ('zh', 'de'): 'Helsinki-NLP/opus-mt-zh-de', + ('zh', 'en'): 'Helsinki-NLP/opus-mt-zh-en', ('zh', 'fi'): 'Helsinki-NLP/opus-mt-zh-fi', + ('zh', 'he'): 'Helsinki-NLP/opus-mt-zh-he', ('zh', 'it'): 'Helsinki-NLP/opus-mt-zh-it', + ('zh', 'ms'): 'Helsinki-NLP/opus-mt-zh-ms', ('zh', 'nl'): 'Helsinki-NLP/opus-mt-zh-nl', + ('zh', 'sv'): 'Helsinki-NLP/opus-mt-zh-sv', ('zh', 'uk'): 'Helsinki-NLP/opus-mt-zh-uk', + ('zh', 'vi'): 'Helsinki-NLP/opus-mt-zh-vi', ('zle', 'en'): 'Helsinki-NLP/opus-mt-zle-en', + ('zle', 'zle'): 'Helsinki-NLP/opus-mt-zle-zle', ('zls', 'en'): 'Helsinki-NLP/opus-mt-zls-en', + ('zls', 'zls'): 'Helsinki-NLP/opus-mt-zls-zls', ('zlw', 'en'): 'Helsinki-NLP/opus-mt-zlw-en', + ('zlw', 'fiu'): 'Helsinki-NLP/opus-mt-zlw-fiu', ('zlw', 'zlw'): 'Helsinki-NLP/opus-mt-zlw-zlw', + ('zne', 'es'): 'Helsinki-NLP/opus-mt-zne-es', ('zne', 'fi'): 'Helsinki-NLP/opus-mt-zne-fi', + ('zne', 'fr'): 'Helsinki-NLP/opus-mt-zne-fr', ('zne', 'sv'): 'Helsinki-NLP/opus-mt-zne-sv'} \ No newline at end of file diff --git a/utils/regex_rules.py b/utils/regex_rules.py new file mode 100644 index 0000000..2632397 --- /dev/null +++ b/utils/regex_rules.py @@ -0,0 +1,23 @@ +import re +# TODO, copy in the code from https://github.com/bigscience-workshop/data_tooling/blob/master/ac_dc/anonymization.py +rulebase = {"en": [([ + ("AGE", re.compile("\S+ years old|\S+\-years\-old|\S+ year old|\S+\-year\-old"), None, None, + None), + ("STREET_ADDRESS", re.compile( + '\d{1,4} [\w\s]{1,20} (?:street|st|avenue|ave|road|rd|highway|hwy|square|sq|trail|trl|drive|dr|court|ct|park|parkway|pkwy|circle|cir|boulevard|blvd)\W?(?=\s|$)'), + None, None, None), + ("STREET_ADDRESS", re.compile('P\.? ?O\.? Box \d+'), None, None, None), + ("GOVT_ID", re.compile( + '(?!000|666|333)0*(?:[0-6][0-9][0-9]|[0-7][0-6][0-9]|[0-7][0-7][0-2])[- ](?!00)[0-9]{2}[- ](?!0000)[0-9]{4}'), + None, None, None), + ("DISEASE", re.compile("diabetes|cancer|HIV|AIDS|Alzheimer's|Alzheimer|heart disease"), None, + None, None), + ("NORP", re.compile("upper class|middle class|working class|lower class"), None, None, None), + ], 1), +], + "vi": [] +} + + + +