A Computational Theory of Metaphor

James H. Martin

EECS Department
University of California, Berkeley
Technical Report No. UCB/CSD-88-465
November 1988

http://www2.eecs.berkeley.edu/Pubs/TechRpts/1988/CSD-88-465.pdf

Metaphor is a conventional and ordinary part of language. A theory attempting to explain metaphor must account for the ease with which conventional metaphors are understood, and with the ability to understand novel metaphors as they are encountered. An approach to metaphor, based on the explicit representation of knowledge about metaphors, has been developed to address these issues. This approach asserts that the interpretation of conventional metaphoric language should proceed through the direct application of specific knowledge about the metaphors in the language. Correspondingly, the interpretation of novel metaphors can be accomplished through the systematic extension, elaboration, and combination of knowledge about already well-understood metaphors.

MIDAS (Metaphor Interpretation, Denotation and Acquisition System) is a computer program that embodies this approach. MIDAS can be used to perform the following tasks: represent knowledge about conventional metaphors, interpret metaphoric language by applying this knowledge, and dynamically learn new metaphors as they are encountered during normal processing.

Knowledge about conventional metaphors is represented in the form of coherent sets of associations between disparate conceptual domains. The representation captures both the details of individual metaphors, and the systematicities exhibited by the set of metaphors in the language as a whole. These systematic sets of associations were implemented using the KODIAK knowledge representation language.

MIDAS is capable of using this metaphoric knowledge to interpret conventional metaphoric language. The main thrust of this approach is that normal processing of metaphoric language proceeds through the direct application of specific knowledge about the metaphors in the language. This approach gives equal status to all conventional metaphoric and literal interpretations. Moreover, the mechanisms used to arrive at metaphoric and literal interpretations are fundamentally the same.

When a metaphor is encountered for which MIDAS has no applicable knowledge, MIDAS calls upon its learning component - the Metaphor Extension System (MES). The approach embodied in the MES asserts that a novel metaphor can best be understood through the systematic extension of an already well-understood metaphor.

MIDAS has been integrated as a part of the UNIX Consultant system. UC is a natural language consultant system that provides naive computer users with advice on how to use the UNIX operating system. By calling upon MIDAS, UC can successfully interpret and learn conventional UNIX domain metaphors, as they are encountered during the course of UC's normal processing.

Advisor: Robert Wilensky


BibTeX citation:

@phdthesis{Martin:CSD-88-465,
    Author = {Martin, James H.},
    Title = {A Computational Theory of Metaphor},
    School = {EECS Department, University of California, Berkeley},
    Year = {1988},
    Month = {Nov},
    URL = {http://www2.eecs.berkeley.edu/Pubs/TechRpts/1988/6068.html},
    Number = {UCB/CSD-88-465},
    Abstract = {Metaphor is a conventional and ordinary part of language. A theory attempting to explain metaphor must account for the ease with which conventional metaphors are understood, and with the ability to understand novel metaphors as they are encountered. An approach to metaphor, based on the explicit representation of knowledge about metaphors, has been developed to address these issues. This approach asserts that the interpretation of conventional metaphoric language should proceed through the direct application of specific knowledge about the metaphors in the language.  Correspondingly, the interpretation of novel metaphors can be accomplished through the systematic extension, elaboration, and combination of knowledge about already well-understood metaphors.  <p>MIDAS (Metaphor Interpretation, Denotation and Acquisition System) is a computer program that embodies this approach. MIDAS can be used to perform the following tasks: represent knowledge about conventional metaphors, interpret metaphoric language by applying this knowledge, and dynamically learn new metaphors as they are encountered during normal processing.   <p>Knowledge about conventional metaphors is represented in the form of coherent sets of associations between disparate conceptual domains. The representation captures both the details of individual metaphors, and the systematicities exhibited by the set of metaphors in the language as a whole. These systematic sets of associations were implemented using the KODIAK knowledge representation language.   <p>MIDAS is capable of using this metaphoric knowledge to interpret conventional metaphoric language. The main thrust of this approach is that normal processing of metaphoric language proceeds through the direct application of specific knowledge about the metaphors in the language. This approach gives equal status to all conventional metaphoric and literal interpretations. Moreover, the mechanisms used to arrive at metaphoric and literal interpretations are fundamentally the same.   <p>When a metaphor is encountered for which MIDAS has no applicable knowledge, MIDAS calls upon its learning component - the Metaphor Extension System (MES). The approach embodied in the MES asserts that a novel metaphor can best be understood through the systematic extension of an already well-understood metaphor.   <p>MIDAS has been integrated as a part of the UNIX Consultant system. UC is a natural language consultant system that provides naive computer users with advice on how to use the UNIX operating system. By calling upon MIDAS, UC can successfully interpret and learn conventional UNIX domain metaphors, as they are encountered during the course of UC's normal processing.}
}

EndNote citation:

%0 Thesis
%A Martin, James H.
%T A Computational Theory of Metaphor
%I EECS Department, University of California, Berkeley
%D 1988
%@ UCB/CSD-88-465
%U http://www2.eecs.berkeley.edu/Pubs/TechRpts/1988/6068.html
%F Martin:CSD-88-465