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Related Experiment Videos

Coherence-driven resolution of referential ambiguity: a computational model.

Stefan L Frank1, Mathieu Koppen, Leo G M Noordman

  • 1Tilburg University, Tilburg, The Netherlands. s.frank@nici.ru.nl

Memory & Cognition
|November 24, 2007
PubMed
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This study introduces a computational model for text comprehension, explaining how coherence resolves ambiguity. It predicts that insufficient information can leave ambiguities unresolved, impacting reading.

Area of Science:

  • Computational linguistics
  • Cognitive science
  • Natural language processing

Background:

  • Text comprehension involves resolving ambiguities.
  • Coherence and world knowledge are crucial for interpretation.
  • Previous models lack a unified account of these processes.

Purpose of the Study:

  • To present a unified computational model for inference, coherence, and disambiguation.
  • To simulate how text coherence leads to knowledge-based resolution of referential ambiguity.
  • To account for experimental data on ambiguous pronoun resolution.

Main Methods:

  • Developed a computational model representing interpretations as "centers of gravity" in a high-dimensional space.
  • Modeled unresolved ambiguity as a vector influenced by context and world knowledge.

Related Experiment Videos

  • Simulated the process of ambiguity resolution as the vector reaching a "center of gravity".

    • Main Results:

    • The model successfully accounts for reading time and error rate data in ambiguous pronoun resolution.
    • It explains the influence of context informativeness, anaphor type, and processing depth.
    • Demonstrated that implicit causality can affect reading early in the process.

    Conclusions:

    • The model provides a unified framework for understanding text comprehension mechanisms.
    • It highlights the dynamic interplay between coherence, context, and world knowledge.
    • A novel prediction is that ambiguities may persist if disambiguating information is insufficient.