Paper: New Models For Improving Supertag Disambiguation

ACL ID E99-1025
Title New Models For Improving Supertag Disambiguation
Venue Annual Meeting of The European Chapter of The Association of Computational Linguistics
Session Main Conference
Year 1999
Authors

In previous work, supertag disambigua- tion has been presented as a robust, par- tial parsing technique. In this paper we present two approaches: contextual models, which exploit a variety of fea- tures in order to improve supertag per- formance, and class-based models, which assign sets of supertags to words in order to substantially improve accuracy with only a slight increase in ambiguity.