Generalizing Explanations of Narratives into Schemata (1985)
This paper describes a natural language system which improves its performance through learning. The system processes short English narratives and from a single narrative acquires a new schema for a stereotypical set of actions. During the understanding process, the system constructs explanations for characters' actions in terms of the goals they were meant to achieve. If a character achieves a common goal in a novel way, it generalizes the set of actions used to achieve this goal into a new schema. The generalization process is a knowledge-based analysis of the narrative's causal structure which removes unnecessary details while maintaining the validity of the explanation. The resulting generalized set of actions is then stored as a new schema and used by the system to process narratives which were previously beyond its capabilities.
In Proceedings of the Third International Machine Learning Workshop, pp. 126--128, New Brunswick, New Jersey 1985.

Raymond J. Mooney Faculty mooney [at] cs utexas edu