A knowledge of intensions, which are used to designate concepts of objects, is important for natural language processing systems. Certain linguistic phrases can refer either to the concept of an entity or to the entity itself. To properly understand a phrase and to prevent invalid inferences from being drawn, the system must determine the type of reference being asserted. We identify a set of ``opaque'' constructs and suggest that a common mechanism be developed to handle them.
To account for the ambiguities of opaque contexts, noun phrases are translated into descriptors. It must be made explicit to whom the descriptor is ascribed and whether its referent is non-specific or specific. Similarly, sentential constituents should be treated as propositions and evaluated relative to conjectured states of affairs. As a testbed for these ideas we define a Montague-style meaning representation and implement the syntactic and semantic components of a moderate-size NLP system in a logic programming environment.
One must also consider how to disambiguate and interpret such a representation with respect to a knowledge base. Much contextual and world knowledge is required. We characterize what facilities are necessary for an accurate semantic interpretation, considering what is and is not available in current knowledge representation systems.
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