Name Entity Resolution NLTK

[Richard Parker]

Dear Group,

NLTK has a good solution for Name Entity Recognition. We can also do by using PoS Tagger.
I am trying to solve name entity resolution. May I use NLTK for the same?

Please suggest.

Regards,
Richard Parker

[14250...@qq.com]

#here is an example:

sent="Deletion of the ADH6 gene has no significant effect on the expression of the ADH7 gene."

words=nltk.word_tokenize(sent)

tags=nltk.pos_tag(words)

chunks=nltk.ne_chunk(tags,binary=True)

NE=[]

for a in chunks.subtrees():
    if a.label()=="NE":
        NE.append(a[0][0])

print(NE)

#we can get three named entity:['Deletion', 'ADH6', 'ADH7']

I hope this can help you.

在 2016年3月4日星期五 UTC+8上午1:55:46，Richard Parker写道：

[Alexis]

Note that named entities can consist of more than one word, but this command will extract only the first one:

    if a.label()=="NE":
        NE.append(a[0][0])

To make a "flat" list of the named entities, it is better to use join() to make a single string from the words of each NE (also works for one-word NEs)

 

    if a.label()=="NE":
        NE.append(" ".join(wrd for wrd, tag in a))

Alexis

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