Korean morphological analyzer and tagger.
Project description
KUKoLex
KUKoLex is a Korean morphological analyzer and tagger made by NLP&AI LAB at Korea University. Main functions are as follows.
Requirements
Python 3
Install
From PyPi:
pip install kukolex
From GitHub:
pip install git+https://github.com/nlpai-lab/KU_KoLex.git
Usage
- pos_tagging(input)
It takes "sentences" as an input and gives a list of morphemes and their POS tags as an output
- morphs(input)
It takes "sentences" as an input and gives a list of morphemes.
- pos(input)
It takes "sentences" as an input and gives a list of POS tags.
- nouns(input)
It takes "sentences" as an input and gives a list of nouns.
from KUKoLex import kukolex
kukolex.pos_tagging('안녕하세요. 저의 이름은 홍길동입니다.')
# [('안녕', 'NNG'), ('하', 'XSA'), ('시', 'EP'), ('어요', 'EM'), ('.', 'SF'), ('저', 'NP'), ('의', 'JKG'), ('이름', 'NNG'), ('은', 'JX'), ('홍길동', 'NNP'), ('이', 'VCP'), ('ㅂ니다', 'EM'), ('.', 'SF')]
kukolex.morphs('안녕하세요. 저의 이름은 홍길동입니다.')
# ['안녕', '하', '시', '어요', '.', '저', '의', '이름', '은', '홍길동', '이', 'ㅂ니다', '.']
kukolex.pos('안녕하세요. 저의 이름은 홍길동입니다.')
# ['NNG', 'XSA', 'EP', 'EM', 'SF', 'NP', 'JKG', 'NNG', 'JX', 'NNP', 'VCP', 'EM', 'SF']
kukolex.nouns('안녕하세요. 저의 이름은 홍길동입니다.')
# ['안녕', '저', '이름', '홍길동']
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