Abstract not found

Events and their coreference offer use-ful semantic and discourse resources. We show that the semantic and dis-course aspects of events interact with each other. However, traditional approaches ad-dressed event extraction and event coref-erence resolution either separately or se-quentially, which limits their interactions. This paper proposes a document-level structured learning model that simultane-ously identifies event triggers and resolves event coreference. We demonstrate that the joint model outperforms a pipelined model by 6.9 BLANC F1 and 1.8 CoNLL F1 points in event coreference resolution using a corpus in the biology domain. 1