The Regular Expression Tagger

The regular expression tagger assigns tags to tokens on the basis of matching patterns. For instance, we might guess that any word ending in ed is the past participle of a verb, and any word ending with 's is a possessive noun. We can express these as a list of regular expressions:

>>> patterns = [ (r'.*ing$' (r'.*ed$' (r'.*es$'

(r'.*ould$', 'MD'), (r'.*\'s$', 'NN$'), (r'.*s$', 'NNS'), (r'A-?[0-9]+(.[0-9]+)?$' (r'.*', 'NN')

# gerunds

# simple past

# 3rd singular present

# modals

# possessive nouns

# plural nouns

# cardinal numbers

# nouns (default)

Note that these are processed in order, and the first one that matches is applied. Now we can set up a tagger and use it to tag a sentence. After this step, it is correct about a fifth of the time.

>>> regexp_tagger = nltk.RegexpTagger(patterns) >>> regexp_tagger.tag(brown_sents[3])

[('"', 'NN'), ('Only', 'NN'), ('a', 'NN'), ('relative', 'NN'), ('handful', 'NN'), ('of', 'NN'), ('such', 'NN'), ('reports', 'NNS'), ('was', 'NNS'), ('received', 'VBD'),

( , 'NN'), (',', 'NN'), ('the', 'NN'), ('jury', 'NN'), ('said', 'NN'), (',', 'NN'),

('"', 'NN'), ('considering', 'VBG'), ('the', 'NN'), ('widespread', 'NN'), ...]

>>> regexp_tagger.evaluate(brown_tagged_sents)


The final regular expression «.*» is a catch-all that tags everything as a noun. This is equivalent to the default tagger (only much less efficient). Instead of respecifying this as part of the regular expression tagger, is there a way to combine this tagger with the default tagger? We will see how to do this shortly.

Your Turn: See if you can come up with patterns to improve the performance of the regular expression tagger just shown. (Note that Section 6.1 describes a way to partially automate such work.)

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