Computational Consequences of Agreement and Ambiguity in Natural Language

Abstract

We argue that the modern computer science technique of computational complexity analysis can provide powerful insights into the algorithm-neutral analysis of information-processing tasks. In particular, we show that a simple, theory-neutral linguistic model of syntactic agreement and lexical ambiguity demonstrates that natural language parsing may be computationally intractable, extending the classic work of Chomsky and Miller (1963). Significantly, we show that it may be syntactic features rather than complex rules that can cause this difficulty. Informally, human languages and the computationally intractable satisfiability problem (SAT) share two costly computational mechanisms: both enforce agreement among terminal symbols across unbounded distances and both allow terminal symbol ambiguity. In natural languages, lexical elements may be required to agree (or disagree) on such features as person, number and gender (e.g., subject/verb agreement in English); in SAT, agreement ensures the consistency of variable truth assignments. (kr)

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Document Details

Document Type
Technical Report
Publication Date
Nov 01, 1988
Accession Number
ADA225794

Entities

People

  • Eric S. Ristad
  • Robert C. Berwick

Organizations

  • Massachusetts Institute of Technology

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Artificial Intelligence
  • Artificial Intelligence Software
  • Automata Theory
  • Classification
  • Communication Systems
  • Computational Complexity
  • Computer Languages
  • Computer Science
  • Computers
  • Grammars
  • Information Processing
  • Information Systems
  • Language
  • Machines
  • Natural Language Processing
  • Natural Languages
  • Recognition

Fields of Study

  • Linguistics

Readers

  • Applied Combinatorial Optimization and Logic Circuit Design.
  • Artificial Intelligence
  • Computational Linguistics