Question

我需要输入一个单词的输入文本文件。然后我需要使用wordnet找到lemma_names，定义和单词的synset的例子。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。虽然我已经理解如何使用终端完成这项工作，但我无法使用文本编辑器执行相同操作。

例如，如果输入文本中包含单词“flabbergasted”，则输出必须采用这种方式：

大吃一惊（动词）flabbergast，boggle，bowl over - 惊奇地克服; “这令人难以置信！” （形容词）目瞪口呆，笨拙，大吃一惊，恍恍惚惚，雷鸣般的，笨拙的，笨拙的 - 好像被惊讶和惊讶地打了个傻瓜; “她拒绝看到这起事故，一群警察傻眼了”; “这些惊讶的市议员说不出话来”; “被他晋升的消息震惊了”

直接从WordNet获取同义词，定义和例句！

我有以下代码：


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']

有没有办法检索词性以及引理名称组？

Answer 1

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

不会返回任何内容，因此默认情况下会获得None

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

这里我创建了一个可以轻松使用（导入）的模块，并且传递给它的字符串将返回字符串的所有引理词。

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：

注意：模块名称是lemma.py因此“来自引理导入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中，lemma_names已从属性更改为方法。因此，如果您收到错误消息：

TypeError: 'method' object is not iterable

您可以使用以下方法修复它：

>>> 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'
    ]

使用WordNet查找同义词，定义和例句

4 个答案: