Please use this identifier to cite or link to this item: doi:10.22028/D291-25042
Title: Linking flat predicate argument structures
Author(s): Xu, Feiyu
Language: English
Year of Publication: 2004
OPUS Source: Kaiserslautern ; Saarbrücken : DFKI, 2004
SWD key words: Künstliche Intelligenz
DDC notations: 004 Computer science, internet
Publikation type: Report
Abstract: This report presents an approach to enriching flat and robust predicate argument structures with more fine-grained semantic information, extracted from underspecified semantic representations and encoded in Minimal Recursion Semantics (MRS). Such representations are provided by a hand-built HPSG grammar with a wide linguistic coverage. A specific semantic representation, called linked predicate argument structure (LPAS), has been worked out, which describes the explicit embedding relationships among predicate argument structures. LPAS can be used as a generic interface language for integrating semantic representations with different granularities. Some initial experiments have been conducted to convert MRS expressions into LPASs. A simple constraint solver is developed to resolve the underspecified dominance relations between the predicates and their arguments in MRS expressions. LPASs are useful for high-precision information extraction and question answering tasks because of their fine-grained semantic structures. In addition, I have attempted to extend the lexicon of the HPSG English Resource Grammar (ERG) exploiting WordNet and to disambiguate the readings of HPSG parsing with the help of a probabilistic parser, in order to process texts from application domains. Following the presented approach, the HPSG ERG grammar can be used for annotating some standard treebank, e.g., the Penn Treebank, with its fine-grained semantics. In this vein, I point out opportunities for a fruitful cooperation of the HPSG annotated Redwood Treebank and the Penn PropBank. In my current work, I exploit HPSG as an additional knowledge resource for the automatic learning of LPASs from dependency structures.
Link to this record: urn:nbn:de:bsz:291-scidok-38861
Series name: Research report / Deutsches Forschungszentrum für Künstliche Intelligenz [ISSN 0946-008x]
Series volume: 04-04
Date of registration: 7-Jul-2011
Faculty: SE - Sonstige Einrichtungen
Department: SE - DFKI Deutsches Forschungszentrum für Künstliche Intelligenz
Collections:SciDok - Der Wissenschaftsserver der Universität des Saarlandes

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