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Joint Extraction of Events and Entities within a Document Context

2016-09-12 · NAACL 2016 6 · Bishan Yang, Tom Mitchell

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 context-aware predictions. We demonstrate that our approach substantially outperforms the state-of-the-art methods for event extraction as well as a strong baseline for entity extraction.

📄 PDF Abstract BibTeX arXiv:1609.03632

Code (1)

bishanyang/EventEntityExtractor 공식 구현

Tasks

Entity Extraction using GANEvent ExtractionSentence

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