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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 (English)In: Proceedings of the Workshop on Prospects and Advances in the Syntax/Semantics Interface / [ed] Denys Duchier and Geert-Jan Kruijff, 2003, 85-89 p.Conference paper, Published paper (Refereed)
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.

Place, publisher, year, edition, pages
2003. 85-89 p.
National Category
Language Technology (Computational Linguistics)
Identifiers
URN: urn:nbn:se:liu:diva-102426OAI: oai:DiVA.org:liu-102426DiVA: diva2:677535
Conference
Workshop on Prospects and Advances in the Syntax/Semantics Interface, 20-21 October 2003, Nancy, France
Available from: 2013-12-09 Created: 2013-12-09 Last updated: 2014-01-16

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Kuhlmann, Marco

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Citation style
  • apa
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  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
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