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LitWay, Discriminative Extraction for Different Bio-Events

  • Chen Li
  • , Zhiqiang Rao
  • , Xiangrong Zhang
  • Massachusetts Institute of Technology
  • Xidian University

科研成果: 书/报告/会议事项章节会议稿件同行评审

9 引用 (Scopus)

摘要

Even a simple biological phenomenon may introduce a complex network of molecular interactions. Scientific literature is one of the trustful resources delivering knowledge of these networks. We propose LitWay, a system for extracting semantic relations from texts. Lit- Way utilizes a hybrid method that combines both a rule-based method and a machine learning-based method. It is tested on the SeeDev task of BioNLP-ST 2016, achieves the state-of-the-art performance with the F-score of 43.2%, ranking first of all participating teams. To further reveal the linguistic characteristics of each event, we test the system solely with syntactic rules or machine learning, and different combinations of two methods. We find that it is difficult for one method to achieve good performance for all semantic relation types due to the complication of bio-events in the literatures.

源语言英语
主期刊名ACL 2016 - Proceedings of the 4th BioNLP Shared Task Workshop
编辑Claire Nedellec, Robert Bossy, Jin-Dong Kim
出版商Association for Computational Linguistics (ACL)
32-41
页数10
ISBN(电子版)9781945626210
出版状态已出版 - 2016
活动ACL 2016 4th BioNLP Shared Task Workshop 2016 - Berlin, 德国
期限: 13 8月 201613 8月 2016

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ACL 2016 4th BioNLP Shared Task Workshop 2016
国家/地区德国
Berlin
时期13/08/1613/08/16

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