Must agree with suggestion that "make my code better" isn't well suited for this site, but I can give you some way where you can try to dig in.
Take a look at Stanford Named Entity Recognizer (NER). Its binding has been included into NLTK v 2.0, but you must download some core files. Here is script which can do all of that for you.
I wrote this script:
import nltk
from nltk.tag.stanford import NERTagger
st = NERTagger('stanford-ner/all.3class.distsim.crf.ser.gz', 'stanford-ner/stanford-ner.jar')
text = """YOUR TEXT GOES HERE"""
for sent in nltk.sent_tokenize(text):
tokens = nltk.tokenize.word_tokenize(sent)
tags = st.tag(tokens)
for tag in tags:
if tag[1]=='PERSON': print tag
and got not so bad output:
('Francois', 'PERSON')
('R.', 'PERSON')
('Velde', 'PERSON')
('Richard', 'PERSON')
('Branson', 'PERSON')
('Virgin', 'PERSON')
('Galactic', 'PERSON')
('Bitcoin', 'PERSON')
('Bitcoin', 'PERSON')
('Paul', 'PERSON')
('Krugman', 'PERSON')
('Larry', 'PERSON')
('Summers', 'PERSON')
('Bitcoin', 'PERSON')
('Nick', 'PERSON')
('Colas', 'PERSON')
Hope this is helpful.
