Trigram tagger
In computational linguistics, a trigram tagger is a statistical method for automatically identifying words as being nouns, verbs, adjectives, adverbs, etc. based on second order Markov models that consider triples of consecutive words. It is trained on a text corpus as a method to predict the next word, taking the product of the probabilities of unigram, bigram and trigram. In speech recognition, algorithms utilizing trigram-tagger score better than those algorithms utilizing IIMM tagger but less well than Net tagger.
The description of the trigram tagger is provided by Brants (2000).
References
- Kempe Andre (1993). "A stochastic Tagger and an Analysis of Tagging Errors". Internal paper. Institute for Computational Linguistics, Universität Stuttgart.
- Brants, T. (2000) TnT - A Statistical Part-of-Speech Tagger, Proc 6th Applied Natural Language Processing Conference, ANLP-200
External links
- TnT -- Statistical Part-of-Speech Tagging by Thorsten Brants
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