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.
K-Best A* Parsing
Published 2009 in Annual Meeting of the Association for Computational Linguistics
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- Publication year
2009
- Venue
Annual Meeting of the Association for Computational Linguistics
- Publication date
2009-08-02
- Fields of study
Computer Science
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