chunking.py

import nltk
from nltk.corpus import state_union
from nltk.tokenize import PunktSentenceTokenizer

train_text= state_union.raw("2005-GWBush.txt")
sample_text= state_union.raw("2006-GWBush.txt")

custom_sent_tokenizer= PunktSentenceTokenizer(train_text)

tokenized= custom_sent_tokenizer.tokenize(sample_text)

def process_content():
    try:
        for i in tokenized:
            words= nltk.word_tokenize(i)
            tagged= nltk.pos_tag(words)

            ## Chunking

            chunck_gram= r"""Chunk: {<RB.?>*<VB.?>*<NNP>+<NN>?}"""

            chunk_parser= nltk.RegexpParser(chunck_gram)
            chunked= chunk_parser.parse(tagged)

            chunked.draw()

    except Exception as e:
        print(str(e))

process_content()