Incremental Global Event Extraction

Alex Judea, Michael Strube


Abstract
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.
Anthology ID:
C16-1215
Volume:
Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers
Month:
December
Year:
2016
Address:
Osaka, Japan
Editors:
Yuji Matsumoto, Rashmi Prasad
Venue:
COLING
SIG:
Publisher:
The COLING 2016 Organizing Committee
Note:
Pages:
2279–2289
Language:
URL:
https://aclanthology.org/C16-1215
DOI:
Bibkey:
Cite (ACL):
Alex Judea and Michael Strube. 2016. Incremental Global Event Extraction. In Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers, pages 2279–2289, Osaka, Japan. The COLING 2016 Organizing Committee.
Cite (Informal):
Incremental Global Event Extraction (Judea & Strube, COLING 2016)
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PDF:
https://aclanthology.org/C16-1215.pdf