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  5. Who knows what? : perspective-enabled story understanding

Who knows what? : perspective-enabled story understanding

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Author(s)
Noss, Jessica Marie.
Advisor(s)
Patrick H. Winston.
Alternative Title
Perspective-enabled story understanding
Date Issued
2017
Publisher
Massachusetts Institute of Technology
Abstract
Stories are essential to human communication, thus understanding stories is critical to modeling human intelligence. In order to understand a story from multiple characters' perspectives, a reader must form mental models representing each character's knowledge and beliefs. Building on the Genesis story-understanding system, I developed the Perspectives Expert, which enables Genesis to form detailed mental models of characters in a story. I started by annotating stories with characters' entrances and exits, treating stories as theatrical plays. I assumed that characters observe events only while onstage, and I used their observations to populate mental models. Then, inspired by human reasoning, I eliminated explicit stage directions and enabled Genesis to keep track of characters' locations and levels of consciousness. Equipped with this mental-modeling ability, Genesis can retell stories from different characters' perspectives, answer reading-comprehension questions to demonstrate understanding, and perform the first steps of conflict reconciliation by detecting and explaining opposing viewpoints.
Description
Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2017
Cataloged from PDF version of thesis.
Includes bibliographical references (page 63).
Subjects
Electrical Engineering and Computer Science.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.
http://dspace.mit.edu/handle/1721.1/7582
Persistent DSpace Link
http://hdl.handle.net/1721.1/113174
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