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Author Simmons, Robert F.
Source ACM Digital Library
Content type Text
Publisher Association for Computing Machinery (ACM)
File Format PDF
Language English
Subject Keyword Language processing ♦ Question-answering system ♦ Semantics ♦ Natural language ♦ Artificial intelligence ♦ Fact retrieval
Abstract Recent experiments in programming natural language question-answering systems are reviewed to summarize the methods that have been developed for syntactic, semantic, and logical analysis of English strings. It is concluded that at least minimally effective techniques have been devised for answering questions from natural language subsets in small scale experimental systems and that a useful paradigm has evolved to guide research efforts in the field. Current approaches to semantic analysis and logical inference are seen to be effective beginnings but of questionable generality with respect either to subtle aspects of meaning or to applications over large subsets of English. Generalizing from current small-scale experiments to language-processing systems based on dictionaries with thousands of entries—with correspondingly large grammars and semantic systems—may entail a new order of complexity and require the invention and development of entirely different approaches to semantic analysis and question answering.
Description Affiliation: Univ. of Texas at Austin, Austin (Simmons, Robert F.)
Age Range 18 to 22 years ♦ above 22 year
Educational Use Research
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2005-08-01
Publisher Place New York
Journal Communications of the ACM (CACM)
Volume Number 13
Issue Number 1
Page Count 16
Starting Page 15
Ending Page 30


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Source: ACM Digital Library