Difference between revisions of "Part-of-speech tagging"

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==Hidden Markov models==
==Hidden Markov models==
===Ambiguity classes===

Revision as of 09:35, 3 September 2008

Part-of-speech tagging is the process of assigning unambiguous grammatical categories[1] to words in context. The crux of the problem is that surface forms of words can often be assigned more than one part-of-speech by morphological analysis. For example in English, the word "trap" can be both a singular noun ("a trap") or a verb ("I'll trap it").

This page intends to give an overview of how part-of-speech tagging works in Apertium, primarily within the apertium-tagger, but giving a short overview of constraints (as in constraint grammar) and restrictions (as in apertium-tagger) as well.

Hidden Markov models

Ambiguity classes


Expectation-Maximisation (EM)





  1. Also referred to as "parts-of-speech", e.g. Noun, Verb, Adjective, Adverb, Conjunction, etc.