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Using narrative functions as a heuristic for relevance in story understanding

Authors:

Ken ForbusAuthors Info & Claims

INT3 '10: Proceedings of the Intelligent Narrative Technologies III Workshop

Article No.: 9, Pages 1 - 8

https://doi.org/10.1145/1822309.1822318

Published: 18 June 2010 Publication History

Abstract

Story understanding requires a degree of knowledge and expressiveness beyond the current state of natural language understanding. We present an approach that addresses these needs, using a large-scale knowledge base, simplified English grammar and a combination of compositional frame semantics and abductive reasoning. This in turn raises a significant challenge disambiguating complex semantic structures, which requires a pragmatics of narrative for constraint and guidance. We present a theory of narrative functions that serve as a heuristic for relevance in narrative, and provide evidence that this heuristic is effective for disambiguation that leads to consistent understanding.

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Cited By

Goh HSoon LHaw S(2013)Automatic dominant character identification in fables based on verb analysis - Empirical study on the impact of anaphora resolutionKnowledge-Based Systems10.5555/2770961.277110954:C(147-162)Online publication date: 1-Dec-2013
https://dl.acm.org/doi/10.5555/2770961.2771109
Goh HSoon LHaw S(2013)Automatic dominant character identification in fables based on verb analysis – Empirical study on the impact of anaphora resolutionKnowledge-Based Systems10.1016/j.knosys.2013.09.00954(147-162)Online publication date: Dec-2013
https://doi.org/10.1016/j.knosys.2013.09.009

Index Terms

Using narrative functions as a heuristic for relevance in story understanding
1. Computing methodologies
  1. Artificial intelligence
    1. Natural language processing
      1. Discourse, dialogue and pragmatics
      2. Language resources

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Published In

cover image ACM Other conferences

INT3 '10: Proceedings of the Intelligent Narrative Technologies III Workshop

June 2010

128 pages

ISBN:9781450300223

DOI:10.1145/1822309

Co-chair:
Arnav Jhala
University of California Santa Cruz
,
Conference Chairs:
Mark Riedl
Georgia Institute of Technology
,
David Roberts
Georgia Institute of Technology

Copyright © 2010 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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SASDG: Society for the Advancement of the Science of Digital Games
Microsoft Research: Microsoft Research

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 18 June 2010

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Microsoft Research

FDG '10: International Conference on the Foundations of Digital Games

June 18, 2010

California, Monterey

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Cited By

Goh HSoon LHaw S(2013)Automatic dominant character identification in fables based on verb analysis - Empirical study on the impact of anaphora resolutionKnowledge-Based Systems10.5555/2770961.277110954:C(147-162)Online publication date: 1-Dec-2013
https://dl.acm.org/doi/10.5555/2770961.2771109
Goh HSoon LHaw S(2013)Automatic dominant character identification in fables based on verb analysis – Empirical study on the impact of anaphora resolutionKnowledge-Based Systems10.1016/j.knosys.2013.09.00954(147-162)Online publication date: Dec-2013
https://doi.org/10.1016/j.knosys.2013.09.009

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