A Practical part-of-speech tagger

by: Doug Cutting, Julian Kupiec, Jan Pedersen, Penelope Sibun

(1992)

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Abstract

We present an implementation of a part-of-speech tagger based on a hidden Markov model. The methodology enables robust and accurate tagging with few resource requirements. Only a lexicon and some unlabeled training text are required. Accuracy exceeds 96%. We describe implementation strategies and optimizations which result in high-speed operation. Three applications for tagging are described: phrase recognition; word sense disambiguation; and grammatical function assignment.

@inproceedings{citeulike:346154, abstract = {We present an implementation of a part-of-speech tagger based on a hidden Markov model. The methodology enables robust and accurate tagging with few resource requirements. Only a lexicon and some unlabeled training text are required. Accuracy exceeds 96\%. We describe implementation strategies and optimizations which result in high-speed operation. Three applications for tagging are described: phrase recognition; word sense disambiguation; and grammatical function assignment.}, author = {Cutting, Doug and Kupiec, Julian and Pedersen, Jan and Sibun, Penelope }, booktitle = {Proceedings of the Third Conference on Applied Natural Language Processing}, citeulike-article-id = {346154}, keywords = {hmm, pos}, posted-at = {2005-10-09 10:40:18}, priority = {2}, title = {A Practical part-of-speech tagger}, url = {http://citeseer.ist.psu.edu/cutting92practical.html}, year = {1992} }

RIS record

TY - CONF ID - citeulike:346154 L3 - citeulike-article-id:346154 TI - A Practical part-of-speech tagger T2 - Proceedings of the Third Conference on Applied Natural Language Processing N2 - We present an implementation of a part-of-speech tagger based on a hidden Markov model. The methodology enables robust and accurate tagging with few resource requirements. Only a lexicon and some unlabeled training text are required. Accuracy exceeds 96%. We describe implementation strategies and optimizations which result in high-speed operation. Three applications for tagging are described: phrase recognition; word sense disambiguation; and grammatical function assignment. KW - hmm KW - pos AU - Cutting, Doug AU - Kupiec, Julian AU - Pedersen, Jan AU - Sibun, Penelope PY - 1992/// UR - http://citeseer.ist.psu.edu/cutting92practical.html ER -

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