K-Best A* Parsing

Adam Pauls,D. Klein

Published 2009 in Annual Meeting of the Association for Computational Linguistics

ABSTRACT

A* parsing makes 1-best search efficient by suppressing unlikely 1-best items. Existing k-best extraction methods can efficiently search for top derivations, but only after an exhaustive 1-best pass. We present a unified algorithm for k-best A* parsing which preserves the efficiency of k-best extraction while giving the speed-ups of A* methods. Our algorithm produces optimal k-best parses under the same conditions required for optimality in a 1-best A* parser. Empirically, optimal k-best lists can be extracted significantly faster than with other approaches, over a range of grammar types.

PUBLICATION RECORD

  • Publication year

    2009

  • Venue

    Annual Meeting of the Association for Computational Linguistics

  • Publication date

    2009-08-02

  • Fields of study

    Computer Science

  • Identifiers
  • External record

    Open on Semantic Scholar

  • Source metadata

    Semantic Scholar

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