Report Number: CS-TR-73-383
Institution: Stanford University, Department of Computer Science
Title: Natural language inference.
Author: Wilks, Yorick A.
Date: August 1973
Abstract: The paper describes the way in which a Preference Semantics system for natural language analysis and generation tackles a difficult class of anaphoric inference problems (finding the correct referent for an English pronoun in context): those requiring either analysis (conceptual) knowledge of a complex sort, or requiring weak inductive knowledge of the course of events in the real world. The method employed converts all available knowledge to a canonical template form and endeavors to create chains of non-deductive inferences from the unknowns to the possible referents. Its method of selecting among possible chains of inferences is consistent with the overall principle of "semantic preference" used to set up the original meaning representation, of which these anaphoric inference procedures are a manipulation.