NLP | Training Unigram Tagger
A single token is referred to as a Unigram, for example – hello; movie; coding. This article is focussed on unigram tagger.
Unigram Tagger: For determining the Part of Speech tag, it only uses a single word.
UnigramTagger inherits from NgramTagger, which is a subclass of
ContextTagger, which inherits from
UnigramTagger is a single word context-based tagger.
Code #1 : Training UnigramTagger.
Code #2 : Training using first 1000 tagged sentences of the treebank corpus as data.
['Pierre', 'Vinken', ', ', '61', 'years', 'old', ', ', 'will', 'join', 'the', 'board', 'as', 'a', 'nonexecutive', 'director', 'Nov.', '29', '.']
Code #3 : Finding the tagged results after training.
[('Pierre', 'NNP'), ('Vinken', 'NNP'), (', ', ', '), ('61', 'CD'), ('years', 'NNS'), ('old', 'JJ'), (', ', ', '), ('will', 'MD'), ('join', 'VB'), ('the', 'DT'), ('board', 'NN'), ('as', 'IN'), ('a', 'DT'), ('nonexecutive', 'JJ'), ('director', 'NN'), ('Nov.', 'NNP'), ('29', 'CD'), ('.', '.')]
How does the code work?
UnigramTagger builds a context model from the list of tagged sentences. Because UnigramTagger inherits from
ContextTagger, instead of providing a
choose_tag() method, it must implement a
context() method, which takes the same three arguments a
choose_tag(). The context token is used to create the model, and also to look up the best tag once the model is created. This is explained graphically in the above diagram also.
Overriding the context model –
All taggers, inherited from
ContextTagger instead of training their own model can take a pre-built model. This model is simply a Python dictionary mapping a context key to a tag. The context keys (individual words in case of UnigramTagger) will depend on what the
ContextTagger subclass returns from its
Code #4 : Overriding the context model
[('Pierre', 'NN'), ('Vinken', None), (', ', None), ('61', None), ('years', None), ('old', None), (', ', None), ('will', None), ('join', None), ('the', None), ('board', None), ('as', None), ('a', None), ('nonexecutive', None), ('director', None), ('Nov.', None), ('29', None), ('.', None)]