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.