Bitte benutzen Sie diese Referenz, um auf diese Ressource zu verweisen: doi:10.22028/D291-25042
Titel: Linking flat predicate argument structures
Verfasser: Xu, Feiyu
Sprache: Englisch
Erscheinungsjahr: 2004
Quelle: Kaiserslautern ; Saarbrücken : DFKI, 2004
SWD-Schlagwörter: Künstliche Intelligenz
DDC-Sachgruppe: 004 Informatik
Dokumentart : Report (Bericht)
Kurzfassung: 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 zu diesem Datensatz: urn:nbn:de:bsz:291-scidok-38861
hdl:20.500.11880/25098
http://dx.doi.org/10.22028/D291-25042
Schriftenreihe: Research report / Deutsches Forschungszentrum für Künstliche Intelligenz [ISSN 0946-008x]
Band: 04-04
SciDok-Publikation: 7-Jul-2011
Fakultät: Sonstige Einrichtungen
Fachrichtung: SE - DFKI Deutsches Forschungszentrum für Künstliche Intelligenz
Fakultät / Institution:SE - Sonstige Einrichtungen

Dateien zu dieser Ressource:
Datei Beschreibung GrößeFormat 
RR_04_04.pdf6,36 MBAdobe PDFÖffnen/Anzeigen


Alle Ressourcen in diesem Repository sind urheberrechtlich geschützt.