Corpus with tags (5.2-5.2.2)

Tagged token is expressed as tuple.

>>> tagged_token = nltk.tag.str2tuple('fly/NN')
>>> tagged_token
('fly', 'NN')
>>> tagged_token[0]
>>> tagged_token[1]

Longer sample is here.

>>> sent = '''
... The/AT grand/JJ jury/NN commented/VBD on/IN a/AT number/NN of/IN
... other/AP topics/NNS ,/, AMONG/IN them/PPO the/AT Atlanta/NP and/CC
... Fulton/NP-tl Country/NN-tl purchasing/VBG departments/NNS which/WDT it/PPS
... said/VBD ``/`` ARE/BER well/QL operated/VBN and/CC follow/VB generally/RB
... accepted/VBN practices/NNS which/WDT inure/VB to/IN the/AT best/JJT
... interest/NN of/IN both/ABX governments/NNS ''/'' ./.
... '''
>>> [nltk.tag.str2tuple(t) for t in sent.split()]
[('The', 'AT'), ('grand', 'JJ'), ('jury', 'NN'), ('commented', 'VBD'), ('on', 'IN'), ('a', 'AT'), ('number', 'NN'), ('of', 'IN'), ('other', 'AP'), ('topics', 'NNS'), (',', ','), ('AMONG', 'IN'), ('them', 'PPO'), ('the', 'AT'), ('Atlanta', 'NP'), ('and', 'CC'), ('Fulton', 'NP-TL'), ('Country', 'NN-TL'), ('purchasing', 'VBG'), ('departments', 'NNS'), ('which', 'WDT'), ('it', 'PPS'), ('said', 'VBD'), ('``', '``'), ('ARE', 'BER'), ('well', 'QL'), ('operated', 'VBN'), ('and', 'CC'), ('follow', 'VB'), ('generally', 'RB'), ('accepted', 'VBN'), ('practices', 'NNS'), ('which', 'WDT'), ('inure', 'VB'), ('to', 'IN'), ('the', 'AT'), ('best', 'JJT'), ('interest', 'NN'), ('of', 'IN'), ('both', 'ABX'), ('governments', 'NNS'), ("''", "''"), ('.', '.')]

Reading tagged corpus.

>>> nltk.corpus.brown.tagged_words()
[('The', 'AT'), ('Fulton', 'NP-TL'), ...]
>>> nltk.corpus.brown.tagged_words(simplify_tags=True)
[('The', 'DET'), ('Fulton', 'NP'), ('County', 'N'), ...]
>>> print nltk.corpus.nps_chat.tagged_words()
[('now', 'RB'), ('im', 'PRP'), ('left', 'VBD'), ...]
>>> nltk.corpus.con112000.tagged_words()
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
AttributeError: 'module' object has no attribute 'con112000'
>>> nltk.corpus.treebank.tagged_words()
[('Pierre', 'NNP'), ('Vinken', 'NNP'), (',', ','), ...]

simplify_tags is to map the original (corpus specific) complicated tags to simplified "common" tags.

>>> nltk.corpus.brown.tagged_words(simplify_tags=True)
[('The', 'DET'), ('Fulton', 'NP'), ('County', 'N'), ...]
>>> nltk.corpus.treebank.tagged_words(simplify_tags=True)
[('Pierre', 'NP'), ('Vinken', 'NP'), (',', ','), ...]

Compare with the original one.

>>> nltk.corpus.treebank.tagged_words()
[('Pierre', 'NNP'), ('Vinken', 'NNP'), (',', ','), ...]
>>> nltk.corpus.brown.tagged_words()
[('The', 'AT'), ('Fulton', 'NP-TL'), ...]

Non-ASCII character sets.

>>> nltk.corpus.sinica_treebank.tagged_words()
[('\xe4\xb8\x80', 'Neu'), ('\xe5\x8f\x8b\xe6\x83\x85', 'Nad'), ...]
>>> nltk.corpus.indian.tagged_words()
[('\xe0\xa6\xae\xe0\xa6\xb9\xe0\xa6\xbf\xe0\xa6\xb7\xe0\xa7\x87\xe0\xa6\xb0', 'NN'), ('\xe0\xa6\xb8\xe0\xa6\xa8\xe0\xa7\x8d\xe0\xa6\xa4\xe0\xa6\xbe\xe0\xa6\xa8', 'NN'), ...]
>>> nltk.corpus.mac_morpho.tagged_words()
[(u'Jersei', u'N'), (u'atinge', u'V'), ...]
>>> nltk.corpus.cess_cat.tagged_words()
[('El', 'da0ms0'), ('Tribunal_Suprem', 'np0000o'), ...]

I expected Chinese should be displayed in my environment...