Moving forward to Chapter 5 although Exercise of Chap 4 is still remaining.
>>> text = nltk.word_tokenize("And now for somthing completely different") >>> nltk.pos_tag(text) [('And', 'CC'), ('now', 'RB'), ('for', 'IN'), ('somthing', 'VBG'), ('completely', 'RB'), ('different', 'JJ')] >>> nltk.help.upenn_tagset('RB') RB: adverb occasionally unabatingly maddeningly adventurously professedly stirringly prominently technologically magisterially predominately swiftly fiscally pitilessly ...
>>> text = nltk.word_tokenize("They refuse to permit us to obtain the refuse permit") >>> nltk.pos_tag(text) [('They', 'PRP'), ('refuse', 'VBP'), ('to', 'TO'), ('permit', 'VB'), ('us', 'PRP'), ('to', 'TO'), ('obtain', 'VB'), ('the', 'DT'), ('refuse', 'NN'), ('permit', 'NN')] >>>
So far I just understand different POS was displayed even for the same words like 'refuse' and 'permit'.
>>> text = nltk.Text(word.lower() for word in nltk.corpus.brown.words()) >>> text.similar('woman') Building word-context index... man day time year car moment world family house boy child country job state girl place war way case question >>> text.similar('bought') made done put said found had seen given left heard been brought got set was called felt in that told >>> text.similar('over') in on to of and for with from at by that into as up out down through about all is >>> text.similar('the') a his this their its her an that our any all one these my in your no some other and
text.similar() is to search words which are used at same situation.