Named Entity Recognition for NLTK in Python. Identifying the NE

Question

I need to classify words into their parts of speech. Like a verb, a noun, an adverb etc.. I used the

nltk.word_tokenize() #to identify word in a sentence 
nltk.         


        

Answer 1

This will work

for sent in chunked_sentences:
  for chunk in sent:
    if hasattr(chunk, "label"):
        print(chunk.label())

Answer 2

Below is my code:

chunks = ne_chunk(postags, binary=True)
for c in chunks:
  if hasattr(c, 'node'):
    myNE.append(' '.join(i[0] for i in c.leaves()))

Answer 3

I agree with bdk

sent3[2].node

O/P - 'NE'

I think there is no function in nltk to do it.Above solution will work but for reference you can check here

for looping problem you can do :-

 for i in range(len(sent3)):
     if "NE" in str(sent3[i]):
          print sent3[i].node

I have executed this in nltk and it works fine..

Answer 4

This answer may be off base, and in which case I'll delete it, as I don't have NLTK installed here to try it, but I think you can just do:

   >>> sent3[2].node
   'NE'

sent3[2][0] returns the first child of the tree, not the node itself

Edit: I tried this when I got home, and it does indeed work.

Answer 5

Now sent3[2].node is outdated.

use sent3[2].label() instead