Computational Models of Events
Course Description: The notion of event has long been central for both modeling the semantics of natural language as well as reasoning in goal-driven tasks in artificial intelligence. This course examines developments in computational models for events, bringing together recent work from the areas of semantics, logic, computer science, and computational linguistics. The goal of this course is to look at event structure from a unifying perspective, enabled by a new synthesis of how these disciplines have approached the problem. This entails examining the structure of events at all levels impacted by linguistic expressions: (a) predicate decomposition and subatomic event structure; (b) atomic events and the mapping to syntax; (c) events in discourse structure; and (d) causation in the macro-event structure of narratives and scripts.
This course outlines a unified theory of event structure. The demands on such a theory require it to both facilitate the systematic mapping from semantic forms to syntactic representations and support event-based inferences in texts. What emerges is a framework that represents a situation and its participants in terms of subevents, modeled dynamically through time and space. In addition, the theory must identify events as part of larger scenarios and scripts. The course covers recent work in this direction and models unifying these representational levels for event-based reasoning.
In the first lecture we focus on the general role of events in linguistics, philosophy, AI, and NLP, examining what questions have been solved and what issues are still outstanding. Common to all traditions is the view that events are the means by which we model situations and changes in our world. For lecture two, we examine the subatomic structure of events from the perspective of hybrid modal logic, using dynamic and linear temporal logics as our means of encoding change. Lecture three focuses first on the properties of atomic event structure. This involves examining the formal characteristics of tense and aspect encodings of events within a temporal logic. We then study the effects of discourse relations on temporal inferencing. Lecture four examines the problem of identifying where events happens, which is critical for any deep causal reasoning involving events and their participants. We develop a procedure for "event localization", which is the process of identifying the spatial extent of an event, activity, or situation. Finally, in lecture five, we look at events above the level of the sentence and local discourse. That is, we examine how events are structured within larger narratives and scripts, reflecting conventionalized patterns of behavior and causal and coherence relations within texts and discourse.
Schedule of all courses