Exploiting Semantic Information for HPSG Parse Selection

Authors:
Sanae Fujita;Francis Bond;Stephan Oepen;Takaaki Tanaka
Affiliations:
NTT Communication Science Laboratories, Nippon Telegraph and Telephone Corporation, Kyoto, Japan;Division of Linguistics and Multilingual Studies, Nanyang Technological University, Singapore, Singapore;Department of Informatics, University of Oslo, Oslo, Norway;NTT West, Osaka, Japan
Venue:
Research on Language and Computation
Year:
2010

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Abstract

In this article, we investigate the use of semantic information in parse selection. We show that fully disambiguated sense-based semantic features smoothed using ontological information are effective for parse selection. Training and testing was undertaken using definition and example sentences taken from a Japanese dictionary corpus (Hinoki), which is manually annotated with senses. A model employing both syntactic and semantic information provides better parse selection accuracy than a model using only syntactic features.