Automating the construction of semantic grammars is a difficult and interesting problem for machine learning. This paper shows how the semantic-grammar acquisition problem can be viewed as the learning of search-control heuristics in a logic program. Appropriate control rules are learned using a new first-order induction algorithm that automatically invents useful syntactic and semantic categories. Empirical results show that the learned parsers generalize well to novel sentences and out-perform previous approaches based on connectionist techniques.

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In Proceedings of the 11th National Conference on Artificial Intelligence, pp. 817-822 1993. Menlo Park, CA: AAAI Press.

@InProceedings{zelle:constructive, title={Learning Semantic Grammars With Constructive Inductive Logic Programming}, author={John M. Zelle and Raymond J. Mooney}, booktitle={Proceedings of the 11th National Conference on Artificial Intelligence}, publisher={Menlo Park, CA: AAAI Press}, key={AAAI}, pages={817-822}, url="http://www.cs.utexas.edu/users/ai-lab?zelle:constructive", year={1993} }