Detecting Subevent Structure for Event Coreference Resolution

Jun Araki, Zhengzhong Liu, Eduard H Hovy, Teruko Mitamura

Abstract:

In the task of event coreference resolution, recent work has shown the need to perform not only full coreference but also partial
coreference of events. We show that subevents can form a particular hierarchical event structure. This paper examines a novel two-stage
approach to finding and improving subevent structures. First, we introduce a multiclass logistic regression model that can detect
subevent relations in addition to full coreference. Second, we propose a method to improve subevent structure based on subevent clusters
detected by the model. Using a corpus in the Intelligence Community domain, we show that the method achieves over 3.2 BLANC F1
gain in detecting subevent relations against the logistic regression model.