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[5:]:
            words= nltk.word_tokenize(i)
            tagged = nltk.pos_tag(words)
            named_et = nltk.ne_chunk(tagged)
            #named_et = nltk.ne_chunk(tagged,binary=True)
            #binary is to just identify tha as ne 
            named_et.draw()
    except Exception as e:
        print(str(e))


process_content()
