RegExp and classfier used in part-of-speech(POS) tagging

1. regular expression in pos
     judge the characteristic of a certain word by suffix pattern matching

>>> import nltk
>>> from nltk.corpus import brown
>>> brown_tagged_sents = brown.tagged_sents(categories='news')
>>> brown_sents = brown.sents(categories='news')
>>> patterns = [
... (r'.*ing$', 'VBG'),
... (r'.*ed$', 'VBD'),
... (r'.*es$', 'VBZ'),
... (r'.*ould$','MD'),
... (r'.*\'s$', 'NN$'),
...     (r'.*s$',   'NNS'),
...     (r'^-?[0-9]+(.[0-9]+)?$', 'CD'),
...     (r'.*',     'NN')
... ]
>>> regexp_tagger = nltk.RegexpTagger(patterns)
>>> regexp_tagger.tag(brown_sents[3])[:10]
[(u'``', 'NN'), (u'Only', 'NN'), (u'a', 'NN'), (u'relative', 'NN'), (u'handful', 'NN'), (u'of', 'NN'), (u'such', 'NN'), (u'reports', 'NNS'), (u'was', 'NNS'), (u'received', 'VBD

2. classfier in pos
    judge the characteristic of a certain word by suffix classfier