Learning Semantic Parsers: An Important but Under-Studied Problem

Raymond J. Mooney

Computational systems that learn to transform naturallanguage sentences into semantic representations have important practical applications in building naturallanguage interfaces. They can also provide insight into important issues in human language acquisition. However, within AI, computational linguistics, and machine learning, there has been relatively little research on developing systems that learn such semantic parsers. This paper briefly reviews our own work in this area and presents semantic-parser acquistion as an important challenge problem for AI.

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