Paper: Probabilistic Disambiguation Models For Wide-Coverage HPSG Parsing

ACL ID P05-1011
Title Probabilistic Disambiguation Models For Wide-Coverage HPSG Parsing
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2005
Authors
  • Yusuke Miyao (University of Tokyo, Tokyo Japan)
  • Jun'ichi Tsujii (University of Tokyo, Tokyo Japan; CREST Japan Science and Technology Corporation, Saitama Japan)

This paper reports the development of log- linear models for the disambiguation in wide-coverage HPSG parsing. The esti- mation 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 empiri- cally evaluated the estimation techniques, and also examined the performance of the disambiguation models on the parsing of real-world sentences.