HLT '91 Proceedings of the workshop on Speech and Natural Language
HLT '91 Proceedings of the workshop on Speech and Natural Language
Statistical parsing of messages
HLT '90 Proceedings of the workshop on Speech and Natural Language
Generating a grammar for statistical training
HLT '90 Proceedings of the workshop on Speech and Natural Language
Poor estimates of context are worse than none
HLT '90 Proceedings of the workshop on Speech and Natural Language
An efficient context-free parsing algorithm
Communications of the ACM
A stochastic parts program and noun phrase parser for unrestricted text
ANLC '88 Proceedings of the second conference on Applied natural language processing
Pearl: a probabilistic chart parser
EACL '91 Proceedings of the fifth conference on European chapter of the Association for Computational Linguistics
Efficiency, robustness and accuracy in Picky chart parsing
ACL '92 Proceedings of the 30th annual meeting on Association for Computational Linguistics
An information-theory-based feature type analysis for the modelling of statistical parsing
ACL '00 Proceedings of the 38th Annual Meeting on Association for Computational Linguistics
Introduction to information extraction
AI Communications
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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. In tests on randomly selected test data, Picky generates fewer edges on average than other CKY-like algorithms, while achieving 89% first parse accuracy and also enabling the parser to process sentences with false starts and other minor disfluencies. Further, sentences which are parsed completely by the probabilistic prediction technique have a 97% first parse accuracy.