SemEval-2015 Task 6: Clinical TempEval


Clinical TempEval 2015 brought the temporal information extraction tasks of past TempEval campaigns to 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 notes and pathology reports from the Mayo Clinic, annotated with an extension of TimeML for the clinical domain. Three teams submitted a total of 13 system runs, with the best systems achieving near-human performance on identifying events and times, but with a large performance gap still remaining for temporal relations.

Proceedings of the workshop on Semantic Evaluation (SemEval)
Leon Derczynski
Leon Derczynski
Associate professor

My research interests include NLP for misinformation detection and verification, clinical record processing, online harms, and efficient AI.