Regular expression matching is used to tag words. Consider the example, numbers can be matched with \d to assign the tag CD (which refers to a Cardinal number). Or one can match the known word patterns, such as the suffix “ing”.
Understanding the concept –
- RegexpTagger is a subclass of SequentialBackoffTagger. It can be positioned before a
DefaultTagger classso as to tag words that the n-gram tagger(s) missed and thus can be a useful part of a backoff chain.
- At initialization, patterns are saved in
choose_tag()is then called, it iterates over the patterns. Then, it returns the first expression tag that can match the current word using re.match().
- So, if the two given expressions get matched, then the tag of the first one will be returned without even trying the second expression.
- If the given pattern is like – (r’.*’, ‘NN’), RegexpTagger class can replace the
Code #1 : Python regular expression module and re syntax
RegexpTagger class expects a list of two tuples
-> first element in the tuple is a regular expression -> second element is the tag
Code #2 : Using RegexpTagger
Accuracy : 0.037470321605870924
What is Affix tagging ?
It is a subclass of ContextTagger. In the case of AffixTagger class, the context is either the suffix or the prefix of a word. So, it clearly indicates that this class can learn tags based on fixed-length substrings of the beginning or end of a word.
It specifies the three-character suffixes. That words must be at least 5 characters long and None is returned as the tag if a word is less than five character.
Code #3 : Understanding AffixTagger.
Train data : [('Mr.', 'NNP'), ('Vinken', 'NNP'), ('is', 'VBZ'), ('chairman', 'NN'), ('of', 'IN'), ('Elsevier', 'NNP'), ('N.V.', 'NNP'), (', ', ', '), ('the', 'DT'), ('Dutch', 'NNP'), ('publishing', 'VBG'), ('group', 'NN'), ('.', '.')] Accuracy : 0.27558817181092166
Code #4 : AffixTagger by specifying 3 character prefixes.
Accuracy : 0.23587308439456076
Code #5 : AffixTagger by specifying 2-character suffixes
Accuracy : 0.31940427368875457
Attention geek! Strengthen your foundations with the Python Programming Foundation Course and learn the basics.
To begin with, your interview preparations Enhance your Data Structures concepts with the Python DS Course. And to begin with your Machine Learning Journey, join the Machine Learning – Basic Level Course