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Statistical A-Star Dependency Parsing
Saarland University, Saarbrücken, Germany.
Saarland University, Saarbrücken, Germany.
Saarland University, Saarbrücken, Germany.ORCID-id: 0000-0002-2492-9872
2003 (engelsk)Inngår i: Proceedings of the Workshop on Prospects and Advances in the Syntax/Semantics Interface / [ed] Denys Duchier and Geert-Jan Kruijff, 2003, s. 85-89Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]

Extensible Dependency Grammar (XDG; Duchier and Debusmann (2001)) is a recently developed dependency grammar formalism that allows the characterization of linguistic structures along multiple dimensions of description. It can be implemented efficiently using constraint programming (CP; Koller and Niehren 2002). In the CP context, parsing is cast as a search problem: The states of the search are partial parse trees, successful end states are complete and valid parses. In this paper, we propose a probability model for XDG dependency trees and an A-Star search control regime for the XDG parsing algorithm that guarantees the best parse to be found first. Extending XDG with a statistical component has the benefit of bringing the formalism further into the grammatical mainstream; it also enables XDG to efficiently deal with large, corpus-induced grammars that come with a high degree of ambiguity.

sted, utgiver, år, opplag, sider
2003. s. 85-89
HSV kategori
Identifikatorer
URN: urn:nbn:se:liu:diva-102426OAI: oai:DiVA.org:liu-102426DiVA, id: diva2:677535
Konferanse
Workshop on Prospects and Advances in the Syntax/Semantics Interface, 20-21 October 2003, Nancy, France
Tilgjengelig fra: 2013-12-09 Laget: 2013-12-09 Sist oppdatert: 2018-01-11

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