Inducing Deterministic Prolog Parsers from Treebanks: A Machine Learning Approach

John M. Zelle, Raymond J. Mooney

This paper presents a method for constructing deterministic 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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