Clinical TempEval 2016 evaluated temporal information extraction systems on the clinical domain. Nine sub-tasks were included, covering problems in time expression identification, event expression identification and temporal relation identification. Participant systems were trained and evaluated on a corpus of clinical and pathology notes from the Mayo Clinic, annotated with an extension of TimeML for the clinical domain. 14 teams submitted a total of 40 system runs, with the best systems achieving near-human performance on identifying events and times. On identifying temporal relations, there was a gap between the best systems and human performance, but the gap was less than half the gap of Clinical TempEval 2015.
CITATION STYLE
Bethard, S., Chen, W. T., Pustejovsky, J., Savova, G., Derczynski, L., & Verhagen, M. (2016). SemEval-2016 task 12: Clinical TempEval. In SemEval 2016 - 10th International Workshop on Semantic Evaluation, Proceedings (pp. 1052–1062). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/s16-1165
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