nltk를 사용하는 Nominalisation

Question

나의 임무는 동사를 적절한 명사 형태로 변환하는 것이다.

예 : 개선 - 개선 인식 - 인식을 나는이 시도

등

이 ...하지만 난 점점 오전 오류

내 코드 :

import nltk.app.wordnet_app as nwapp 
from nltk.corpus import wordnet as wn 

word = "recognize" 
print("Nominalizing " + word) 
verb_synsets = wn.synsets(word, pos=wn.VERB) 
print nwapp.get_relations_data(word,verb_synsets) 

내 오류 :

Nominalizing recognize 
Traceback (most recent call last): 
    File "nominalizeme.py", line 8, in <module> 
    print nwapp.get_relations_data(word, 
verb_synsets) 
    File "/usr/lib/python2.7/dist-packages/nltk/app/wordnet_app.py", line 412, in get_relations_data 
    if synset.pos == wn.NOUN: 
AttributeError: 'list' object has no attribute 'pos' 

Answer 1

get_relations_data()은 한 번에 하나의 synset을 사용합니다. 당신은 synset을 목록의 항목을 통해 루프 필요 http://www.nltk.org/_modules/nltk/app/wordnet_app.html

>>> import nltk.app.wordnet_app as wnapp 
>>> from nltk.corpus import wordnet as wn 
>>> word = "recognize" 
>>> verb_synsets = wn.synsets(word, pos=wn.VERB) 
>>> verb_synsets 
[Synset('acknowledge.v.06'), Synset('recognize.v.02'), Synset('spot.v.02'), Synset('recognize.v.04'), Synset('accredit.v.01'), Synset('greet.v.01'), Synset('acknowledge.v.04'), Synset('recognize.v.08'), Synset('recognize.v.09')] 
>>> print wnapp.get_relations_data(word, verb_synsets[0]) 
((18, 'Antonym', []), (0, 'Hyponym', []), (1, 'Direct hypernyms', [Synset('accept.v.01')]), (26, 'Indirect hypernyms', [(Synset('accept.v.01'), [(Synset('evaluate.v.02'), [(Synset('think.v.03'), [])])])]), (17, 'Entailments', []), (14, 'Causes', []), (15, 'Also see', []), (10, 'Verb Groups', []), (25, 'Derivationally related form', []))