使用NLTK WordNet查找专有名词 [英] Finding Proper Nouns using NLTK WordNet

问题描述

是否可以使用NLTK WordNet查找专有名词?即，我可以使用nltk Wordnet标记所有名词吗?

Is there any way to find proper nouns using NLTK WordNet?Ie., Can i tag Possessive nouns using nltk Wordnet ?

推荐答案

我认为您不需要WordNet来查找专有名词，我建议使用词性标记器pos_tag.

I don't think you need WordNet to find proper nouns, I suggest using the Part-Of-Speech tagger pos_tag.

要查找专有名词，请查找NNP标记:

To find Proper Nouns, look for the NNP tag:

from nltk.tag import pos_tag

sentence = "Michael Jackson likes to eat at McDonalds"
tagged_sent = pos_tag(sentence.split())
# [('Michael', 'NNP'), ('Jackson', 'NNP'), ('likes', 'VBZ'), ('to', 'TO'), ('eat', 'VB'), ('at', 'IN'), ('McDonalds', 'NNP')]

propernouns = [word for word,pos in tagged_sent if pos == 'NNP']
# ['Michael','Jackson', 'McDonalds']

由于Michael和Jackson被分为2个标记，您可能会不太满意，那么您可能需要诸如名称实体标记器之类的更复杂的东西.

You may not be very satisfied since Michael and Jackson is split into 2 tokens, then you might need something more complex such as Name Entity tagger.

如penntreebank标签集所述，对于所有格名词，您只需查找POS标签

By right, as documented by the penntreebank tagset, for possessive nouns, you can simply look for the POS tag, http://www.mozart-oz.org/mogul/doc/lager/brill-tagger/penn.html. But often the tagger doesn't tag POS when it's an NNP.

要查找所有名词，请查找str.endswith('s")或str.endswith("s'"):

from nltk.tag import pos_tag

sentence = "Michael Jackson took Daniel Jackson's hamburger and Agnes' fries"
tagged_sent = pos_tag(sentence.split())
# [('Michael', 'NNP'), ('Jackson', 'NNP'), ('took', 'VBD'), ('Daniel', 'NNP'), ("Jackson's", 'NNP'), ('hamburger', 'NN'), ('and', 'CC'), ("Agnes'", 'NNP'), ('fries', 'NNS')]

possessives = [word for word in sentence if word.endswith("'s") or word.endswith("s'")]
# ["Jackson's", "Agnes'"]

或者，您可以使用NLTK ne_chunk，但是除非您担心从句子中获得什么样的专有名词，否则它似乎没有其他作用:

Alternatively, you can use NLTK ne_chunk but it doesn't seem to do much other unless you are concerned about what kind of Proper Noun you get from the sentence:

>>> from nltk.tree import Tree; from nltk.chunk import ne_chunk
>>> [chunk for chunk in ne_chunk(tagged_sent) if isinstance(chunk, Tree)]
[Tree('PERSON', [('Michael', 'NNP')]), Tree('PERSON', [('Jackson', 'NNP')]), Tree('PERSON', [('Daniel', 'NNP')])]
>>> [i[0] for i in list(chain(*[chunk.leaves() for chunk in ne_chunk(tagged_sent) if isinstance(chunk, Tree)]))]
['Michael', 'Jackson', 'Daniel']

使用ne_chunk有点冗长，并且不能使您拥有所有格.

Using ne_chunk is a little verbose and it doesn't get you the possessives.

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