Toward a Computational Theory of Conceptual Metaphor

Toward a Computational Theory of Conceptual Metaphor

Proceedings of the Twenty-Seventh International Florida Artificial Intelligence Research Society Conference Toward a Computational Theory of Conceptual Metaphor Anca Christine Pascua, Tzu-Keng Fub, Jean-Pierre Desclésc a, b b University of Western Britanny, Brest, France, IDA-NTC, University of West Bohemia, Pilsen, Czech Republic, c University of Paris-Sorbonne, Paris, France Abstract Burstall 1999) (Goguen and Burstall, 1992, 1984). In this This paper provides a framework to construct a paper we introduce the Logic of Determination of Objects computational model of conceptual metaphor. We (LDO) (Desclés, Pascu 2011) as an alternative approach first analyze how conceptual metaphor is described to study conceptual metaphor and conceptual blending. by Algebraic Semiotic at linguistic level and by The structure of the paper is as follows: In Section 2, Institutional Theory (an abstract model theory) at a we start our discussion on conceptual metaphor and general logical level. By the Logic of Determination of Objects, which has been used in a system of conceptual blending that our paper has taken as describing semantic annotation and in a building ontologies human’s basic cognitive capacity. Section 3 then system, we further provide a new computational discusses Algebraic Semiotics that moves toward model as a rival approach. Institution Theory that our paper is attempting to take to describe the underlying process of this cognitive capacity Introduction at the general level. In section 4, we start our discussion on LDO based on Combinatory Logic according to Curry George Lakoff and Mark Johnson in their works and Feys (Curry amd Feys, 1958) and then analyze Conceptual Metaphor in Everyday Language (1980) and conceptual metaphor by LDO. Finally, section 5 is the Metaphor We Live By (1980) extensively discussed how conclusion. conceptual metaphor as a basic cognitive capacity of shaping our communication, action and the way we think. Conceptual Metaphor and Conceptual Blending Conceptual metaphor shapes our thought and language in Metaphor shapes our language and thought in the rhetoric a way of viewing one idea as another (from one sense of viewing one unfamiliar and abstract term A by conceptual domain to another). Following this, the idea of means of borrowing some meaning of another term B that conceptual blending has further been introduced by Gilles is more concrete and familiar that intuitively implies the Fauconnier and Mark Turner: it is possible to yield a new understanding of one idea in terms of another. Recently, conceptual space with emergent structure by blending of when we talk about metaphor in cognitive science we two thematically rather different conceptual spaces don’t talk about metaphor in rhetoric sense. Rather, we (Fauconnier and Turner 2003). A classical example for talk about George Lakoff and Mark Johnson’s works conceptual blending is a blend of the conceptual space of ``Metaphors we Live By”. It refers to the understanding house and the conceptual space of boat, yielding the of one idea, or conceptual domain, in terms of another. concept of houseboats and the concept of boathouses as Many abstract concepts can be defined metaphorically in new emergent structures. “Conceptual metaphor with terms of concrete experiences that we can comprehend. In conceptual blending” as a systematic whole, which was the same spirit as metaphor in rhetoric sense, conceptual used to integrate two conceptual spaces, has been studied metaphor in cognitive linguistics intuitively implies the comprehensively by ontologists in computer science for understanding of one idea, may be a coherent organization developing various ontology designs (Kutz et al., 2010). of human experiences, in terms of another. For example, In the literature, Joseph Goguen et. al. extensively “argument is war” is one conceptual metaphor which developed algebraic semiotics methods to describe the understands “argument” as “war”, that is to say that we structure of complex signs and the blend of such structure, understand “argument” which belongs to a target domain so that it is possible to capture the essence of the by another source domain to which “war” belongs. We transformations between two different concept domains at use this “concept of war” to shape the way that “concept the logical level, called Institution Theory (Goguen and of argument” was thought of, and moreover we shape the ways that we go in argument process. Generally speaking, there could be arbitrarily many mappings between the Copyright © 2014, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved. target domain and the source domain. However, only 455 limited numbers of them are commonly used by people to axioms. A semiotic system is a theory, plus a level understand some concepts. This means some properties ordering on sorts and a priority ordering on constitutes at should be preserved from one to another, so that people each level. Sorts classify the parts of signs and the values can understand these concepts properly. of attributes of signs. Signs of a certain sort are Gilles Fauconnier and Mark Turner develop a theory of represented by terms of that sort, including but not limited cognition - conceptual blending - in their work The Way to constants. Constructors build new signs from given We Think Conceptual Blending and the Mind’s Hidden sign parts as inputs. Levels express the whole-part Complexities (2003). According to this theory, some hierarchy of complex signs, while priorities express the elements and vital relations from different conceptual relative importance of constructors and their arguments; spaces are able to be integrated subconsciously, and this social issues play a key role in determining these kind integration is assumed to be ubiquitous to thought orderings. Semiotic systems are formalized as algebraic and language in our daily life. For example, John Searle theories with additional structure and semiotic morphisms in his works has given a general theory of social are formalized as theory morphisms that also preserve institutions (Searle, 1995, 2005) related to the these additional structures: construction of social institutions. In Searle’s works, he – theory morphisms consists of mappings between stated that human have the ability of creating institutional two theories that preserve the basic constituents, facts from brute facts such as money, government, which are sort declarations, and operation marriage, and so on. This creation of institutional facts declarations; could have a general logical form: x counts as y in c, – semiotic morphisms are the mappings between where x refers to brute facts, y refers to brute facts, and c semiotic systems (preserving levels and refers to context. We can find that there is a priorities), which are uniform representations for subconsciously integrations of different conceptual spaces signs in a source space by signs in a target space. in the process of creating social institutions. For example, Institution Theory “a piece of paper” (a brute fact) counts as “100 USD” (an Further, along the development of algebraic semiotics, institutional fact), “a man” (a brute fact) was represented Goguen and Burstall discuss Institution Theory, which as “a president” (an institutional fact), etc. A piece of aims to capture the essence of the concept of “logical paper cannot present the so-called ``state function” of system”. Next paragraph contains technical descriptions being 100 USD only in virtue of the physical structure of on semiotic morphisms. A semiotic morphism consists of the paper. Rather, there should be some collective the following: assignment of a certain status. Similarly, our action of A category Sign of signatures (or grammars) paying a bill by handing over some this 100 USD with a set N of sorts partially ordered by a sub- presupposes the existence of an institutionalized currency sort relation. system. In the same spirit the man cannot present the state For each signature Σ, Sen is a function that function of being a president only in virtue of the physical builds the set of sentences Sen(Σ). structure of the man. A function ρ : Σ1 → Σ2 between such sets as a signature morphism. Algebraic Semiotics and Institution Theory For each signature morphism, the sentence A general logical system of conceptual metaphor and translation map α(ρ) : Sen(Σ1 ) →Sen(Σ2 ). conceptual blending can be described by Goguen and A semiotic morphism from S1 = (Σ1, Sen(Σ1 )) to S2 = (Σ2 , Burstall’s Institution Theory. Institution Theory comes Sen(Σ2)) consists of a theory morphism that partially from a series study on algebraic semiotics in 1980s. preserves the priority and level of orderings. Algebraic semiotics originated from algebraic semantics Following the work of algebraic semiotics, Institution in the mathematics of abstract data types. Some Theory has introduced not only systematically mappings definitions shown in (Goguen and Harrell 2009, pp. 299– but also the underlying logical behaviors between 300) for algebraic semiotics and semiotic morphism will semiotics. The following paragraph contains technical be given as follows1: descriptions on the application to an abstract concept of Algebraic Semiotics logical system. The basic notion of algebraic semiotics is a (loose Given two logics K1 =〈Σ1 , |=1〉 and K2 =〈Σ2 , |=2〉; algebraic) theory, which consists of type and operation K1, K2 have the set Σ1 and Σ2 (of propositional symbols) declarations, possibly with subtype declarations and as signatures, and a function ρ: Σ1 → Σ2 between such sets as a signature morphism. A Σ-model M is a mapping from 1 Σto{true, false}. α(ρ): Sen(Σ1) → Sen(Σ2) from the Σ1- For the additional details omitted here to refer (Goguen and sentence to Σ - sentences. γ is a model translation function Harrell 2009). 2 from K -models to K -models, such that M |= α(ϕ ) if 2 1 2 2 1 456 and only if γ(M2) |=1 ϕ1 holds for any ϕ1∈Sen(Σ) and any In LDO: M2∈K2-model. - All objects are operands of type J; all propositions are of The metaphor can be seen as a model translation type H; function between K2-models and K1-models.

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