Natural Language, Knowledge Representation, and Logical Form

Abstract

Current natural language understanding systems generally maintain a strict division between the parsing processes and the representation that supports general reasoning about the world. This paper examines why these two forms of processing are separated, determines the current advantages and limitations of this approach, and identifies the inherent limitations of the approach. I will point out some fundamental problems with the models as they are defined today and suggest some important directions of research in natural language and knowledge representation. In particular, I will argue that one of the crucial issues facing future natural language systems is the development of knowledge representation formalisms that can effectively handle ambiguity.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1991
Accession Number
ADA247389

Entities

People

  • James F. Allen

Organizations

  • University of Rochester

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Communities of Interest

  • Air Platforms
  • Energy and Power Technologies
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Abstracts
  • Algorithms
  • Artificial Intelligence
  • Computational Complexity
  • Computational Linguistics
  • Computational Science
  • Computer Science
  • Computers
  • Databases
  • Grammars
  • Language
  • Linguistics
  • Natural Language Processing
  • Natural Language Understanding
  • Natural Languages
  • Recognition
  • Three Dimensional

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  • Computational Linguistics
  • Systems Analysis and Design