Natural Language Inference
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 analytic(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.
Document Details
- Document Type
- Technical Report
- Publication Date
- Aug 01, 1973
- Accession Number
- AD0769673
Entities
People
- Yorick Wilks
Organizations
- Stanford University