This paper presents a method for constructing deterministic, context-sensitive, Prolog parsers from corpora of parsed sentences. Our approach uses recent machine learning methods for inducing Prolog rules from examples (inductive logic programming). We discuss several advantages of this method compared to recent statistical methods and present results on learning complete parsers from portions of the ATIS corpus.

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Proceedings of the Twelfth National Conference on Artificial Intelligence (AAAI-94) (1994), pp. 748--753.

@article{zelle:aaai94, title={Inducing Deterministic Prolog Parsers From Treebanks: A Machine Learning Approach}, author={John M. Zelle and Raymond J. Mooney}, booktitle={Proceedings of the Twelfth National Conference on Artificial Intelligence (AAAI-94)}, month={July}, address={Seattle, WA}, pages={748--753}, url="http://www.cs.utexas.edu/users/ai-lab?zelle:aaai94", year={1994} }