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

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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.

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MacAvaney, S., Cohan, A., & Goharian, N. (2017). GUIR at SemEval-2017 Task 12: A Framework for Cross-Domain Clinical Temporal Information Extraction. In Proceedings of the Annual Meeting of the Association for Computational Linguistics (pp. 1024–1029). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/S17-2180

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