The automatic interpretation of natural language (in this work, English), database questions formulated by a user untrained in the technical aspects of database querying is an established problem in the field of artificial intelligence. State-of-the-art approaches involve the analysis of queries with syntactic and semantic grammars expressed in phrase structure grammar or transition network formalisms. With such method difficulties exist with the detection and resolution of ambiguity, with the misinterpretation possibilities inherent with finite length look-ahead, and with the modification and extension of a mechanism for other sources of semantic knowledge. This work examines the potential of optimization techniques tomore » solve these problems and interpret natural language, database queries. The proposed method involves developing a 0-1 integer programming problem for each query.

TINLAP-2, 25-32.

Cognitive Science 1:3-46

Artificial Intelligence 8:155-173

This paper describes a computer system for understanding English. The system answers questions, executes commands, and accepts information in an interactive English dialog. It is based on the belief that in modeling language understanding, we must deal in an integrated way with all of the aspects of language—syntax, semantics, and inference. The system contains a parser, a recognition grammar of English, programs for semantic analysis, and a general problem solving system. We assume that a computer cannot deal reasonably with language unless it can understand the subject it is discussing. Therefore, the program is given a detailed model of a particular domain.

In Computer Models of Thought and Language, R. C. Schank and K. M. Colby, eds. San Francisco: W. H. Freeman, pp. 114–151.