Tagset reduction without information loss

Authors:
Thorsten Brants
Affiliations:
Universität des Saarlandes, Saarbrücken, Germany
Venue:
ACL '95 Proceedings of the 33rd annual meeting on Association for Computational Linguistics
Year:
1995

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Abstract

A technique for reducing a tagset used for n-gram part-of-speech disambiguation is introduced and evaluated in an experiment. The technique ensures that all information that is provided by the original tagset can be restored from the reduced one. This is crucial, since we are interested in the linguistically motivated tags for part-of-speech disambiguation. The reduced tagset needs fewer parameters for its statistical model and allows more accurate parameter estimation. Additionally, there is a slight but not significant improvement of tagging accuracy.