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XJNLP at SemEval-2017 Task 12: Clinical temporal information extraction with a Hybrid Model

  • Yu Long
  • , Zhijing Li
  • , Xuan Wang
  • , Chen Li
  • Xi'an Jiaotong University

科研成果: 书/报告/会议事项章节会议稿件同行评审

8 引用 (Scopus)

摘要

Temporality is crucial in understanding the course of clinical events from a patient's electronic health records and temporal processing is becoming more and more important for improving access to content. SemEval 2017 Task 12 (Clinical TempEval) addressed this challenge using the THYME corpus, a corpus of clinical narratives annotated with a schema based on TimeML2 guidelines. We developed and evaluated approaches for: extraction of temporal expressions (TIMEX3) and EVENTs; EVENT attributes; document-time relations. Our approach is a hybrid model which is based on rule based methods, semi-supervised learning, and semantic features with addition of manually crafted rules.

源语言英语
主期刊名ACL 2017 - 11th International Workshop on Semantic Evaluations, SemEval 2017, Proceedings of the Workshop
出版商Association for Computational Linguistics (ACL)
1014-1018
页数5
ISBN(电子版)9781945626555
DOI
出版状态已出版 - 2017
活动11th International Workshop on Semantic Evaluations, SemEval 2017, co-located with the 55th Annual Meeting of the Association for Computational Linguistics, ACL 2017 - Vancouver, 加拿大
期限: 3 8月 20174 8月 2017

出版系列

姓名Proceedings of the Annual Meeting of the Association for Computational Linguistics
ISSN(印刷版)0736-587X

会议

会议11th International Workshop on Semantic Evaluations, SemEval 2017, co-located with the 55th Annual Meeting of the Association for Computational Linguistics, ACL 2017
国家/地区加拿大
Vancouver
时期3/08/174/08/17

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