Natural Language Processing: Python and NLTK

Training a unigram part-of-speech tagger

A unigram generally refers to a single token. Therefore, a unigram tagger only uses a single word as its context for determining the part-of-speech tag.

UnigramTagger inherits from NgramTagger, which is a subclass of ContextTagger, which inherits from SequentialBackoffTagger. In other words, UnigramTagger is a context-based tagger whose context is a single word, or unigram.

How to do it...

UnigramTagger can be trained by giving it a list of tagged sentences at initialization.

>>> from nltk.tag import UnigramTagger >>> from nltk.corpus import treebank >>> train_sents = treebank.tagged_sents()[:3000] >>> tagger = UnigramTagger(train_sents) >>> treebank.sents()[0] ['Pierre', 'Vinken', ',', '61', 'years', 'old', ...