TR: direct inferences and figurative adjective-noun combinations

[Susan Weber]

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	A Structured Connectionist Approach to Direct Inferences
	and Figurative Adjective-Noun Combinations

	Susan Hollbach Weber

	University of Rochester
	Computer Science Department TR 289

Categories have internal structure sufficiently sophisticated to
capture a variety of effects, ranging from the direct inferences
arising from adjectival modification of nouns to the ability to
comprehend figurative usages.  The design of the internal structure
of category representation is constrained  by the model requirements
of the connectionist implementation and by the observable behaviors
exhibited in direct inferences.  The former dictates the use of a
spreading activation format, and the latter indicates some to the
topology and connectivity of the resultant semantic network.

The connectionist knowledge representation and inferencing scheme
described in this report is based on the idea that categories and
concepts are context sensitive and functionally structured.  Each
functional property value of a category motivates a distinct aspect
of that category's internal structure.  This model of cognition, as
implemented in a structured connectionist knowledge representation
system, permits the system to draw immediate inferences, and, when
augmented with property inheritance mechanisms, mediated inferences
about the full meaning of adjective-noun combinations.  These
inferences are used not only to understand the implicit references to
correlated properties (a green peach is unripe) but also to make sense
of figurative adjective uses, by drawing on the connotations of the
adjective in literal contexts.