python – 使用nltk和wordnet对多数名词进行解释

我想用lemmatize

from nltk import word_tokenize, sent_tokenize, pos_tag
from nltk.stem.wordnet import WordNetLemmatizer
from nltk.corpus import wordnet
lmtzr = WordNetLemmatizer()
POS = pos_tag(text)

def get_wordnet_pos(treebank_tag):
        #maps pos tag so lemmatizer understands
        from nltk.corpus import wordnet
        if treebank_tag.startswith('J'):
            return wordnet.ADJ
        elif treebank_tag.startswith('V'):
            return wordnet.VERB
        elif treebank_tag.startswith('N'):
            return wordnet.NOUN
        elif treebank_tag.startswith('R'):
            return wordnet.ADV
        else:
            return wordnet.NOUN
 lmtzr.lemmatize(text[i], get_wordnet_pos(POS[i][1]))

问题是POS标记器得到“procaspases”是’NNS’,但是如何将NNS转换为wordnet,因为即使在词形变换器之后“procaspases”仍然是“procaspaseS”.

解决方法:

NLTK负责大多数复数,而不仅仅是删除一个结尾.

import nltk
from nltk.stem.wordnet import WordNetLemmatizer

Lem = WordNetLemmatizer()

phrase = 'cobblers ants women boys needs finds binaries hobbies busses wolves'

words = phrase.split()
for word in words :
  lemword = Lem.lemmatize(word)
  print(lemword)

输出：
补鞋匠蚂蚁女人男孩需要找到二元爱好公共汽车狼

标签：wordnet,python,nltk,lemmatization
来源： https://codeday.me/bug/20190722/1504611.html