Menu-based natural language understanding

Authors:
Harry R. Tennant;Kenneth M. Ross;Richard M. Saenz;Craig W. Thompson;James R. Miller
Affiliations:
Central Research Laboratories, Texas Instruments Incorporated, Dallas, Texas;Central Research Laboratories, Texas Instruments Incorporated, Dallas, Texas;Central Research Laboratories, Texas Instruments Incorporated, Dallas, Texas;Central Research Laboratories, Texas Instruments Incorporated, Dallas, Texas;Central Research Laboratories, Texas Instruments Incorporated, Dallas, Texas
Venue:
ACL '83 Proceedings of the 21st annual meeting on Association for Computational Linguistics
Year:
1983

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Abstract

This paper describes the NLMenu System, a menu-based natural language understanding system. Rather than requiring the user to type his input to the system, input to NLMenu is made by selecting items from a set of dynamically changing menus. Active menus and items are determined by a predictive left-corner parser that accesses a semantic grammar and lexicon. The advantage of this approach is that all inputs to the NLMenu System can be understood thus giving a 0% failure rate. A companion system that can automatically generate interfaces to relational databases is also discussed.