Abstract
This paper describes the system developed for the task of temporal information extraction from clinical narratives in the context of the 2017 Clinical TempEval challenge. Clinical TempEval 2017 addressed the problem of temporal reasoning in the clinical domain by providing annotated clinical notes, pathology and radiology reports in line with Clinical TempEval challenges 2015/16, across two different evaluation phases focusing on cross domain adaptation. Our team focused on subtasks involving extractions of temporal spans and relations for which the developed systems showed average F-score of 0.45 and 0.47 across the two phases of evaluations.
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CITATION STYLE
Sarath, P. R., Manikandan, R., & Niwa, Y. (2017). Hitachi at SemEval-2017 Task 12: System for temporal information extraction from clinical notes. In Proceedings of the Annual Meeting of the Association for Computational Linguistics (pp. 1005–1009). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/S17-2176
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