GUIR at SemEval-2017 Task 12: A Framework for Clinical Temporal Information Extraction Domain Adaptation

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Authors: Sean MacAvaney, Arman Cohan, Nazli Goharian

Appeared in: Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval @ ACL 2017)

Abstract:

Clinical TempEval 2017 (SemEval 2017 Task 12) addresses the task of cross-domain temporal extraction from clinical text. We present a system for this task that uses supervised learning for the extraction of temporal expression and event spans with corresponding attributes and narrative container relations. Approaches include conditional random fields and decision tree ensembles, using lexical, syntactic, semantic, distributional, and rule-based features. Our system received best or second best scores in TIMEX3 span, EVENT span, and CONTAINS relation extraction.

BibTeX @inproceedings{macavaney:semeval2017-clinicaltempeval, author = {MacAvaney, Sean and Cohan, Arman and Goharian, Nazli}, title = {GUIR at SemEval-2017 Task 12: A Framework for Clinical Temporal Information Extraction Domain Adaptation}, booktitle = {Proceedings of the 11th International Workshop on Semantic Evaluation}, year = {2017}, doi = {10.18653/v1/S17-2180}, pages = {1024--1029} }