PoEM : a parser of emotion metaphors

Although metaphor is generally recognized as an integral component of everyday language, very few computational systems capable of understanding metaphoric utterances exist today. This thesis describes one approach to the problem and presents PoEM, a prototype system which recognizes and interprets metaphoric descriptions of emotions and mental states in single-sentence input. Building upon previous work in knowledge-based metaphor comprehension, this research adopts a goal-driven approach which assumes each metaphor is selected by a speaker for its aptness at serving a particular communicative goal. To identify these goals, an empirical analysis of metaphor distribution in song lyrics was performed, and typical communicative intentions and surface patterns were identified for the top five most frequently occurring metaphor groups. These intentions and surface patterns have been implemented as a set of metaphor templates and interpretation rules in PoEM, using the WordNet lexical database for supplemental semantic information. Evaluation of PoEM demonstrates fairly high accuracy but low recall.

Department dc:contributor.department

Program in Media Arts and Sciences (Massachusetts Institute of Technology)

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

1999

Author dc:creator

• Hiyakumoto, Laurie Satsue, 1969-

Advisor dc:contributor.advisor

• Brian K. Smith.

• Architecture. Program in Media Arts and Sciences

Statement dc:rights

• M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/1721.1/61537

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/61537