Part-of-speech tagging

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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.

Lexical ambiguity

After morphological analysis of a sentence, a not insignificant amount of words will have more than one analysis. For example in the following sentence:

Vino (noun or verb) a ( la playa

Hidden Markov models

A hidden Markov model is a statistical model which consists of a number of hidden states, and a number of observable states.

Ambiguity classes


Expectation-Maximisation (EM)




See also


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