Proceedings of the Eleventh National Conference of the American Association for Artificial Intelligence (AAAI-93), pp. 817-822, Washington, D.C. July 1993.
Paper ID: 25
Category: Inductive Logic Programming, Natural Language Learning, Learning for Semantic Parsing
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.
