Joint Extraction of Events and Entities within a Document Context Joint Extraction of Events and Entities within a Document Context
Paper summary They propose a joint model for 1) identifying event keywords in a text, 2) identifying entities, and 3) identifying the connections between these events and entities. They also do this across different sentences, jointly for the whole text. https://i.imgur.com/ETKZL7V.png Example of the entity and event annotation that the system is modelling. The entity detection part is done with a CRF; the structure of an event is learned with a probabilistic graphical model; information is integrated from surrounding sentences using a Stanford coreference system; and these are all tied together across the whole document using Integer Linear Programming.
arxiv.org
scholar.google.com
Joint Extraction of Events and Entities within a Document Context
Yang, Bishan and Mitchell, Tom M.
arXiv e-Print archive - 2016 via Local Bibsonomy
Keywords: dblp


Summary by Marek Rei 6 months ago
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