Package: python-mecab-ner
mecab_nerTable of ContentsFeaturesInstallationQuick startSimple ExamplePractical ExampleFeaturesPython library to get NER using MecabInfer NER from Data dictionaryInstallationDownload using pip via pypi.$pipinstall'python-mecab-ner'--upgrade(Mac/homebrew users may need to usepip3)Simple Examplefrompython_mecab_ner.mecab_nerimportMecabNermecab_ner=MecabNer()test_sentence="아이유의 금요일에 만나요를 들으면서 신촌 딸기를 먹을래"mecab_ner.parse(test_sentence)# [('아이유', NerFeature(word='아이유', pos='ner', category=Category(large='ner_example_music_singer', small='가수'))), ('의', NerFeature(word='의', pos='JKG', category=None)), ('금요일에 만나요', NerFeature(word='금요일에 만나요', pos='ner', category=Category(large='ner_example_music_song', small='노래'))), ('를', NerFeature(word='를', pos='JKO', category=None)), ('듣', NerFeature(word='듣', pos='VV+EC', category=None)), ('으면서', NerFeature(word='으면서', pos='VV+EC', category=None)), ('신촌 딸기', NerFeature(word='신촌 딸기', pos='ner', category=Category(large='ner_example_fruit', small='과일'))), ('를', NerFeature(word='를', pos='JKO', category=None)), ('먹', NerFeature(word='먹', pos='VV', category=None)), ('을래', NerFeature(word='을래', pos='EC', category=None))]mecab_ner.morphs(test_sentence)# ['아이유', '의', '금요일에 만나요', '를', '듣', '으면서', '신촌 딸기', '를', '먹', '을래']mecab_ner.ners(test_sentence)# [('아이유', 'ner_example_music_singer', '가수'), ('금요일에 만나요', 'ner_example_music_song', '노래'), ('신촌 딸기', 'ner_example_fruit', '과일')]Practical ExampleSetdata pathfor your workFile namewill become entity setcategory largeData Directory# Directory
root/
    word_dir.py
    data/
        programming.txt
        public.txtData FileData file must betxtformat and first line should start your small categoryFirst linewill become entity setcategory small- data/programming.txt
#인공지능
파이썬
딥러닝
머신 러닝
자연어 처리
버트
#백엔드
로그
http통신

- data/place.txt
#hospital
병원Resultson example code 1('자연어 로그', 'programming', '백엔드')is infered ner from vocab로그in data file.on example code 2('서울대병원', 'place', 'hospital')is infered ner from vocab병원in data file.if you don't want, setMecabNer(infer=False)# example code 1frompython_mecab_ner.mecab_nerimportMecabNermecab_ner=MecabNer(ner_path="./data")test_sentence="자연어 처리를 위해 인공지능을 위한 파이썬을 공부하여 자연어와 관련된 일을 하고 있습니다. http 요청시 자연어 로그를 쌓는 것이 중요합니다."mecab_ner.parse(test_sentence)# [('자연어 처리', NerFeature(word='자연어 처리', pos='ner', category=Category(large='programming', small='인공지능'))), ('를', NerFeature(word='를', pos='JKO', category=None)), ('위하', NerFeature(word='위하', pos='VV+EC', category=None)), ('아', NerFeature(word='아', pos='VV+EC', category=None)), ('인공', NerFeature(word='인공', pos='NNP', category=None)), ('지능', NerFeature(word='지능', pos='NNP', category=None)), ('을', NerFeature(word='을', pos='JKO', category=None)), ('위하', NerFeature(word='위하', pos='VV+ETM', category=None)), ('ᆫ', NerFeature(word='ᆫ', pos='VV+ETM', category=None)), ('파이썬', NerFeature(word='파이썬', pos='ner', category=Category(large='programming', small='인공지능'))), ('을', NerFeature(word='을', pos='JKO', category=None)), ('공부', NerFeature(word='공부', pos='NNG', category=None)), ('하', NerFeature(word='하', pos='XSV', category=None)), ('여', NerFeature(word='여', pos='EC', category=None)), ('자연', NerFeature(word='자연', pos='NNG', category=None)), ('어', NerFeature(word='어', pos='NNG', category=None)), ('와', NerFeature(word='와', pos='JC', category=None)), ('관련', NerFeature(word='관련', pos='NNG', category=None)), ('되', NerFeature(word='되', pos='XSV+ETM', category=None)), ('ᆫ', NerFeature(word='ᆫ', pos='XSV+ETM', category=None)), ('일', NerFeature(word='일', pos='NNG', category=None)), ('을', NerFeature(word='을', pos='JKO', category=None)), ('하', NerFeature(word='하', pos='VV', category=None)), ('고', NerFeature(word='고', pos='EC', category=None)), ('있', NerFeature(word='있', pos='VX', category=None)), ('습니다', NerFeature(word='습니다', pos='EF', category=None)), ('.', NerFeature(word='.', pos='SF', category=None)), ('http', NerFeature(word='http', pos='SL', category=None)), ('요청', NerFeature(word='요청', pos='NNG', category=None)), ('시', NerFeature(word='시', pos='NNB', category=None)), ('자연어 로그', NerFeature(word='자연어 로그', pos='ner', category=Category(large='programming', small='백엔드'))), ('를', NerFeature(word='를', pos='JKO', category=None)), ('쌓', NerFeature(word='쌓', pos='VV', category=None)), ('는', NerFeature(word='는', pos='ETM', category=None)), ('것', NerFeature(word='것', pos='NNB', category=None)), ('이', NerFeature(word='이', pos='JKS', category=None)), ('중요', NerFeature(word='중요', pos='NNG', category=None)), ('하', NerFeature(word='하', pos='XSV+EF', category=None)), ('ᄇ니다', NerFeature(word='ᄇ니다', pos='XSV+EF', category=None)), ('.', NerFeature(word='.', pos='SF', category=None))]mecab_ner.morphs(test_sentence)# ['자연어 처리', '를', '위하', '아', '인공', '지능', '을', '위하', 'ᆫ', '파이썬', '을', '공부', '하', '여', '자연', '어', '와', '관련', '되', 'ᆫ', '일', '을', '하', '고', '있', '습니다', '.', 'http', '요청', '시', '자연어 로그', '를', '쌓', '는', '것', '이', '중요', '하', 'ᄇ니다', '.']mecab_ner.ners(test_sentence)# [('자연어 처리', 'programming', '인공지능'), ('파이썬', 'programming', '인공지능'), ('자연어 로그', 'programming', '백엔드')]test_sentence2="나는 서울대병원에 갈려고 합니다."mecab_ner.parse(test_sentence2)# [('나', NerFeature(word='나', pos='NP', category=None)), ('는', NerFeature(word='는', pos='JX', category=None)), ('서울대병원', NerFeature(word='서울대병원', pos='ner', category=Category(large='place', small='hospital'))), ('에', NerFeature(word='에', pos='JKB', category=None)), ('가', NerFeature(word='가', pos='VV+EC', category=None)), ('ᆯ려고', NerFeature(word='ᆯ려고', pos='VV+EC', category=None)), ('하', NerFeature(word='하', pos='VX+EF', category=None)), ('ᄇ니다', NerFeature(word='ᄇ니다', pos='VX+EF', category=None)), ('.', NerFeature(word='.', pos='SF', category=None))]mecab_ner.morphs(test_sentence2)# ['나', '는', '서울대병원', '에', '가', 'ᆯ려고', '하', 'ᄇ니다', '.']mecab_ner.ners(test_sentence2)# [('서울대병원', 'place', 'hospital')]