Neural Architecture for Temporal Relation Extraction: A Bi-LSTM Approach for Detecting Narrative Containers

Julien Tourille, Olivier Ferret, Aurélie Névéol, Xavier Tannier


Abstract
We present a neural architecture for containment relation identification between medical events and/or temporal expressions. We experiment on a corpus of de-identified clinical notes in English from the Mayo Clinic, namely the THYME corpus. Our model achieves an F-measure of 0.613 and outperforms the best result reported on this corpus to date.
Anthology ID:
P17-2035
Volume:
Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)
Month:
July
Year:
2017
Address:
Vancouver, Canada
Venue:
ACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
224–230
Language:
URL:
https://www.aclweb.org/anthology/P17-2035
DOI:
10.18653/v1/P17-2035
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PDF:
http://aclanthology.lst.uni-saarland.de/P17-2035.pdf