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An HPSG parser with CFG filtering

Published online by Cambridge University Press:  02 November 2000

KENTARO TORISAWA
Affiliation:
Department of Information Science, Graduate School of Science, University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-0033, Japan; Information and Human Behavior, PRESTO, Japan Science and Technology Corporation, 4-1-8 Kawaguchi Hon-cho, Kawaguchi-shi, Saitama, 332-0012, Japan; e-mail: torisawa@is.s.u-tokyo.ac.jp
KENJI NISHIDA
Affiliation:
Department of Information Science, Graduate School of Science, University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-0033, Japan; e-mail: {nishiken | yusuke}g@is.s.u-tokyo.ac.jp
YUSUKE MIYAO
Affiliation:
Department of Information Science, Graduate School of Science, University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-0033, Japan; e-mail: {nishiken | yusuke}g@is.s.u-tokyo.ac.jp
JUN-ICHI TSUJII
Affiliation:
Department of Information Science, Graduate School of Science, University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-0033, Japan; CCL, UMIST, P.O.Box 88, Manchester, M60 1QD, England; e-mail: tsujii@is.s.u-tokyo.ac.jp

Abstract

This article presents an HPSG parser using a technique called CFG filtering. The parser predicts possible parse trees using a CFG generated automatically from a given HPSG-based grammar. Parsing costs are reduced because unification is applied only to the predicted parse trees. In other words, parsing is speeded up because the parser avoids unnecessary unification by eliminating impossible parse trees. We show the method for generating a CFG from an HPSG-based grammar and outline a parsing scheme using the CFG. The effectiveness of the parsing scheme is shown through experimental results obtained by using several HPSG-based grammars, including the LinGO grammar.

Type
Research Article
Copyright
2000 Cambridge University Press

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