A Measure of Semantic Complexity for Natural Language Systems

Abstract

This paper will describe a way to organize the salient objects, their attributes, and relationships between the objects in a given domain. This organization allows us to assign an information value to each collection, and to the domain as a whole, which corresponds to the number of things to "talk about" ill the domain. This number gives a measure of semantic complexity; that is it will correspond to the number of objects, attributes, and relationships in the domain, but not to the level of syntactic diversity allowed when conveying these meanings. Defining a measure of semantic complexity for a dialog system domain will give an insight towards making a complexity measurement standard. With such a standard, natural language programmers can measure the feasibility of making a natural language interface, compare different language processors ability to handle more and more complex do mains, and quantify the abilities of the current state of the art in natural language processors.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2000
Accession Number
ADA460905

Entities

People

  • Alan W. Biermann
  • Shannon Pollard

Organizations

  • Duke University

Tags

Communities of Interest

  • C4I

DTIC Thesaurus Topics

  • Accuracy
  • Artificial Intelligence
  • Computational Linguistics
  • Computer Languages
  • Computer Science
  • Dialogue Systems
  • Grammars
  • Language
  • Linguistics
  • Measurement
  • Natural Language Processing
  • Natural Languages
  • Probability
  • Random Variables
  • Reliability
  • Specifications
  • Standards

Fields of Study

  • Computer science

Readers

  • Computational Linguistics
  • Systems Analysis and Design