Donald Bren School of Information and Computer Sciences

In the course of understanding a text, a succession of decision points arise at which readers are faced with the task of choosing among alternative possible interpretations of what they're reading. Careful analysis of a wide range of sample texts reveals that such decisions are often based on complex evaluations of the interpretation being constructed, and sometimes cause the reader to construct and discard a number of intermediate inferences before settling on a final interpretation for a text.

This paper introduces Judgmental Inference theory as a proposed scheme of evaluation metrics and mechanisms, derived from examination of inference decisions arising during text understanding. A series of programs, ARTHUR, MACARTHUR and JUDGE are described, which incorporate some of the metrics and mechanisms of Judgmental Inference, enabling them to understand texts more complex than those that can be handled by other understanding systems.