Events and entities are closely related; entities are often actors or participants in events and events without entities are uncommon. The interpretation of events and entities is highly contextually dependent. Existing work in information extraction typically models events separately from entities, and performs inference at the sentence level, ignoring the rest of the document. In this paper, we propose a novel approach that models the dependencies among variables of events, entities, and their relations, and performs joint inference of these variables across a document. The goal is to enable access to document-level contextual information and facilitate contextaware predictions. We demonstrate that our approach substantially outperforms the stateof-the-art methods for event extraction as well as a strong baseline for entity extraction.
REF proposed joint extraction of entities and events with the document context, improving on the event extraction.
Joint Extraction of Events and Entities within a Document Context
Proceedings of NAACL-HLT 2016, pages 289-299
Computer Science