从NLP中的名词阶段提取名词 [英] Extracting nouns from Noun Phase in NLP

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问题描述

任何人都可以告诉我如何从以下输出中只提取名词:



我已经进行了标记和解析字符串给我电影评论在给定的语法上使用以下过程: -

  sent = nltk.word_tokenize(msg)
parser = nltk.ChartParser (语法)
trees = parser.nbest_parse(发送)
树中的树:
打印树
tokens = find_all_NP(树)
tokens1 = nltk.word_tokenize令牌[0])
打印tokens1

并获得以下输出:

 >>> 
(VP(V Give)(Det me))
(NP(Det the)(N review)(PP(P of)(N movie))))
(S
(VP(V Give)(Det me))
(NP(Det the)(N review)(NP(PP(P of)(N movie))))
['the','review','of','movie']
>>>

现在我只想获得名词。我该怎么做?

解决方案

你不需要使用完整的解析器来获取名词。你可以简单地使用标签器。您可以使用的一个功能是nltk.tag.pos_tag()。这将返回一个包含单词和词组的元组列表。您可以遍历元组,找到标有NN或NNS的单词用于名词或复数名词。



NLTK有一个如何记录如何使用他们的标签。可以在这里找到: https://nltk.googlecode.com/svn/trunk/doc/ howto / tag.html ,这里是NLTK书中有关使用标记的章节的链接: https://nltk.googlecode.com/svn/trunk/doc/book/ch05.html



每个都有很多代码示例那些地方。


Could anyone please tell me how to extract only the nouns from the following output:

I have tokenized and parsed the string "Give me the review of movie" based on a given grammar using following procedure:-

sent=nltk.word_tokenize(msg)
parser=nltk.ChartParser(grammar)
trees=parser.nbest_parse(sent)
for tree in trees:
    print tree
tokens=find_all_NP(tree)
tokens1=nltk.word_tokenize(tokens[0])
print tokens1

and obtained the following output:

>>> 
(S
  (VP (V Give) (Det me))
  (NP (Det the) (N review) (PP (P of) (N movie))))
(S
  (VP (V Give) (Det me))
  (NP (Det the) (N review) (NP (PP (P of) (N movie)))))
['the', 'review', 'of', 'movie']
>>> 

Now I would like to only obtain the nouns. How do I do that?

解决方案

You don't need to use a full parser to get nouns. You can simply use a tagger. One function you can use is nltk.tag.pos_tag(). This will return a list of tuples with the word and part of speech. You'll be able to iterate over the tuples and find words tagged with 'NN' or 'NNS' for noun or plural noun.

NLTK has a how to document for how to use their taggers. It can be found here: https://nltk.googlecode.com/svn/trunk/doc/howto/tag.html and here is a link to the chapter in the NLTK book about using taggers: https://nltk.googlecode.com/svn/trunk/doc/book/ch05.html

There are many code examples in each of those places.

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