Identity and Granularity of Events in Text

In this paper we describe a method to detect event descriptions in different news articles and to model the semantics of events and their components using RDF representations. We compare these descriptions to solve a cross-document event coreference task. Our component approach to event semantics defines identity and granularity of events at different levels. It performs close to state-of-the-art approaches on the cross-document event coreference task, while outperforming other works when assuming similar quality of event detection. We demonstrate how granularity and identity are interconnected and we discuss how semantic anomaly could be used to define differences between coreference, subevent and topical relations.