Incremental Global Event Extraction
Event extraction is a difficult information extraction task. Li et al. (2014) explore the benefits of modeling event extraction and two related tasks, entity mention and relation extraction, jointly. This joint system achieves state of the art performance in all tasks. However, as a system operating only at the sentence level, it misses valuable information from other parts of the document. In this paper, we present an incremental easy first approach to make the global context of the entire document available to the intra sentential, state of the art event extractor. We show that our method robustly increases performance on two datasets, namely ACE 2005 and TAC 2015.
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