使用WordNet查找同义词，定义和例句

Question

我需要用一个单词输入文本文件。然后我需要找到使用wordnet的单词的词组名称，定义和例子。我已经阅读了这本书：“使用NLTK 2.0 Cookbook进行Python文本处理”以及“使用NLTK进行自然语言处理”来帮助我实现这一目标。虽然我已经理解了如何使用终端来完成此任务，但我无法使用文本编辑器进行同样的操作。

例如，如果输入的文本具有单词“大吃一惊”时，输出必须以这种方式：

大吃一惊 （动词）惊奇，惊奇，碗过度 - 惊奇地克服; “这让人难以置信！” （形容词）目瞪口呆，模糊不清，惊呆了，惊呆了，惊呆了，哑口无言 - 好像惊呆了一样惊呆了; “一个警察的圈子因为拒绝看到这次事故而感到羞愧”; “令人fla目结舌的议员无言以对”; “被他的宣传消息吓坏了”

synsets，定义和例句是从WordNet直接获得的！

我有下面的代码：

from __future__ import division 
import nltk 
from nltk.corpus import wordnet as wn 


tokenizer = nltk.data.load('tokenizers/punkt/english.pickle') 
fp = open("inpsyn.txt") 
data = fp.read() 

#to tokenize input text into sentences 

print '\n-----\n'.join(tokenizer.tokenize(data))# splits text into sentences 

#to tokenize the tokenized sentences into words 

tokens = nltk.wordpunct_tokenize(data) 
text = nltk.Text(tokens) 
words = [w.lower() for w in text] 
print words  #to print the tokens 

for a in words: 
    print a 

syns = wn.synsets(a) 
print "synsets:", syns 

for s in syns: 
    for l in s.lemmas: 
     print l.name 
    print s.definition 
    print s.examples 

我得到以下输出：

flabbergasted 

['flabbergasted'] 
flabbergasted 
synsets: [Synset('flabbergast.v.01'), Synset('dumbfounded.s.01')] 
flabbergast 
boggle 
bowl_over 
overcome with amazement 
['This boggles the mind!'] 
dumbfounded 
dumfounded 
flabbergasted 
stupefied 
thunderstruck 
dumbstruck 
dumbstricken 
as if struck dumb with astonishment and surprise 
['a circle of policement stood dumbfounded by her denial of having seen the accident', 'the flabbergasted aldermen were speechless', 'was thunderstruck by the news of his promotion'] 

有没有办法跟团引理的名字一起检索讲话的一部分？

Answer 1

def synset(word): 
    wn.synsets(word) 

所以默认你None

不返回任何东西，你应该写

def synset(word): 
    return wn.synsets(word) 

提取引理名称：

from nltk.corpus import wordnet 
syns = wordnet.synsets('car') 
syns[0].lemmas[0].name 
>>> 'car' 
[s.lemmas[0].name for s in syns] 
>>> ['car', 'car', 'car', 'car', 'cable_car'] 


[l.name for s in syns for l in s.lemmas] 
>>>['car', 'auto', 'automobile', 'machine', 'motorcar', 'car', 'railcar', 'railway_car', 'railroad_car', 'car', 'gondola', 'car', 'elevator_car', 'cable_car', 'car'] 

Answer 2

在这里，我已经创建了一个模块，可以很容易地使用（导入），并且在传递给它的字符串时，将返回所有的词条单词的字符串。

模块：

#!/usr/bin/python2.7 
''' pass a string to this funciton (eg 'car') and it will give you a list of 
words which is related to cat, called lemma of CAT. ''' 
from nltk.corpus import wordnet as wn 
import sys 
#print all the synset element of an element 
def lemmalist(str): 
    syn_set = [] 
    for synset in wn.synsets(str): 
     for item in synset.lemma_names: 
      syn_set.append(item) 
    return syn_set 

用法：

注：模块名称是lemma.py因此 “从引理进口lemmalist”

>>> from lemma import lemmalist 
>>> lemmalist('car') 
['car', 'auto', 'automobile', 'machine', 'motorcar', 'car', 'railcar', 'railway_car', 'railroad_car', 'car', 'gondola', 'car', 'elevator_car', 'cable_car', 'car'] 

干杯！

Answer 3

synonyms = [] 
for syn in wordnet.synsets("car"): 
    for l in syn.lemmas(): 
     synonyms.append(l.name()) 
print synonyms 

Answer 4

在NLTK 3.0，lemma_names已从属性改变为方法。因此，如果你得到一个错误说：

TypeError: 'method' object is not iterable 

您可以使用修复：

>>> from nltk.corpus import wordnet as wn 
>>> [item for sysnet in wn.synsets('car') for item in sysnet.lemma_names()] 

这将输出：

>>> [ 
     'car', 'auto', 'automobile', 'machine', 'motorcar', 'car', 
     'railcar', 'railway_car', 'railroad_car', 'car', 'gondola', 
     'car', 'elevator_car', 'cable_car', 'car' 
    ]