Part-of-speech tagging
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
orverb
) a (preposition
) la (determiner
orpronoun
) playa (noun
)
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
Training
Expectation-Maximisation (EM)
Baum-Welch
Tagging
Viterbi
See also
Notes
- ↑ Also referred to as "parts-of-speech", e.g. Noun, Verb, Adjective, Adverb, Conjunction, etc.