Semantics, Dialogue, and Reference Resolution

Abstract

Most pronoun resolution research has focused on written corpora while using syntactical and surface cues. Though big gains have been made in this domain with those methods, it is difficult to do better than the 80% coverage in these domains without some world or semantic knowledge. We investigate this issue by incorporating rich semantic information into a proven reference resolution model over a very difficult domain of human-human task-oriented dialogues. Our results show that semantic information greatly improves performance and can even be viewed as a substitution for the usual syntactic filters.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2006
Accession Number
ADA454766

Entities

People

  • James F. Allen
  • Joel Tetreault

Organizations

  • University of Rochester

Tags

Communities of Interest

  • Biomedical

DTIC Thesaurus Topics

  • Abstracts
  • Algorithms
  • Ambulances
  • Computational Linguistics
  • Computer Science
  • Computers
  • Context Free Grammars
  • Dialogue Systems
  • Error Analysis
  • Errors
  • Language
  • Linguistics
  • Natural Language Processing
  • Natural Languages
  • Semantics
  • Syntax
  • Test And Evaluation

Fields of Study

  • Computer science

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Computational Linguistics