Metaphoric Generalization Through Sort Coercion

METAPHORIC GENERALIZATION THROUGH SORT COERCION Ellen Hays 10 Pine Avenue Arlington, MA 02174 hays@linc.cis.upenn.edu Samuel Bayer The MITRE Corporation, A040 Burlington Rd. Bedford, MA 01730 sam@mitre.org Abstract This paper presents a method for interpret- ing metaphoric language in the context of a portable natural language interface. The method licenses metaphoric uses via coercions between incompatible ontological sorts. The machinery allows both previously-known and unexpected metaphoric uses to be correctly interpreted and evaluated with respect to the backend expert sys- tem. 1 Introduction One of the central issues in AI systems has been how to model the domain: what are the primitives of the ontological language, how are the ontolog- ical sorts organized, and so on. AI researchers have explored a wide range of object-centered and relation-centered representations (for exam- ple, Brachman and Schmolze (1985) and Minsky (1975)). When setting up the domain model for a natural language interface, though, one must also keep the lexicon in mind, so that words can be defined and processed efficiently; if possible, the hierarchical organization of the domain model should minimize sense ambiguity, by allowing lex- ical items to point to classes that dominate the objects that reflect each item's range of meanings. However, a growing body of literature argues that the generalizations about the world im- plied by the lexicon do not correspond exactly to standard computational notions of fine-grained ontological structure. Rather, the mapping is mediated by pervasive low-level metaphoric and metonymic processes (as pointed out by Lakoff (1987) and others) that make for a mismatch be- tween the desired world model and the lexicon. At the MITRE Corporation, we are developing an interface architecture to support King Kong, our portable natural language interface for ex- pert systems, and AIMI, our multimedia interface for the same class of systems) Portable inter- faces provide an additional set of problems be- yond simple domain modeling. In particular, in our case, the structure the knowledge represen- tation imposes on the backend domain model is hierarchical and relation-based, and its form must be consistent across system ports; thus the knowl- edge representation may structure domain-specific information in a way that is fundamentally differ- ent from the way it is organized in the backend. In this context, one needs to develop a computational account of the low-level metaphor that creates the mismatch between the domain model and the lex- icon. In this paper, we will discuss a mechanism implemented in King Kong that we call "sort co- ercion" that is intended to address that mismatch. 2 Refinement in the King Kong domain model In the King Kong knowledge representation, both concepts and relations are organized hierarchi- cally. King Kong exploits this hierarchy in a num- ber of ways, of which the most relevant to this discussion occurs in the process of refinement. When King Kong interprets a sentence, it builds an interpretation corresponding to the input. In- terpretations represent a point in the semantic 1 The AIMI system is, in fact, one of the domains to which …

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