Efficiency, robustness and accuracy in Picky chart parsing

Authors:
David M. Magerman;Carl Weir
Affiliations:
Stanford University, Stanford, CA;Paramax Systems, Paoli, PA
Venue:
ACL '92 Proceedings of the 30th annual meeting on Association for Computational Linguistics
Year:
1992

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Abstract

This paper describes Picky, a probabilistic agenda-based chart parsing algorithm which uses a technique called probabilistic prediction to predict which grammar rules are likely to lead to an acceptable parse of the input. Using a suboptimal search method, Picky significantly reduces the number of edges produced by CKY-like chart parsing algorithms, while maintaining the robustness of pure bottom-up parsers and the accuracy of existing probabilistic parsers. Experiments using Picky demonstrate how probabilistic modelling can impact upon the efficiency, robustness and accuracy of a parser.