Probabilistic disambiguation models for wide-coverage HPSG parsing

Authors:
Yusuke Miyao;Jun'ichi Tsujii
Affiliations:
University of Tokyo, Hongo, Bunkyo-ku, Tokyo, Japan;University of Tokyo, Hongo, Bunkyo-ku, Tokyo, Japan
Venue:
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Year:
2005

Citing 18
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Abstract

This paper reports the development of log-linear models for the disambiguation in wide-coverage HPSG parsing. The estimation of log-linear models requires high computational cost, especially with wide-coverage grammars. Using techniques to reduce the estimation cost, we trained the models using 20 sections of Penn Tree-bank. A series of experiments empirically evaluated the estimation techniques, and also examined the performance of the disambiguation models on the parsing of real-world sentences.