Knowledge Representation for Commonsense Reasoning with Text

The reader of a text actively constructs a rich picture of the objects, events, and situation described. The text is a vague, insufficient, and ambiguous indicator of the world that the writer intends to depict. The reader draws upon world knowledge to disambiguate and clarify the text, selecting the most plausible interpretation from among the (infinitely) many possible ones. In principle, any world knowledge whatsoever in the reader's mind can affect the choice of an interpretation. Is there a level of knowledge that is general and common to many speakers of a natural language? Can this level be the basis of an explanation of text interpretation? Can it be identified in a principled, projectable way? Can this level be represented for use in computational text understanding? We claim that there is such a level, called naive semantics (NS), which is commonsense knowledge associated with words. Naive semantics identifies words with concepts, which vary in type. Nominal concepts are categorizations of objects based upon naive theories concerning the nature and typical description of conceptualized objects. Verbal concepts are naive theories of the implications of conceptualized events and states. 2 Concepts are considered naive because they are not always objectively true, and bear only a distant relation to scientific theories. An informal example of a naive nominal concept is the following description of the typical lawyer.