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| CHIP 2020评测任务2概述:中文医学文本实体关系抽取 | |
| 引用本文： | 甘子发,昝红英,关同峰,李雯昕,张欢,朱田恬,穗志方,陈清财.CHIP 2020评测任务2概述:中文医学文本实体关系抽取[J].中文信息学报,2022,36(6):101-108. |
| 作者姓名： | 甘子发 昝红英 关同峰 李雯昕 张欢 朱田恬 穗志方 陈清财 |
| 作者单位： | 1.郑州大学 信息工程学院,河南 郑州 450001; 2.北京大学 计算语言学教育部重点实验室,北京 100871; 3.哈尔滨工业大学(深圳),广东 深圳 518000; 4.鹏城实验室,广东 深圳 518052 |
| 基金项目： | 河南省医学科技攻关计划省部共建项目(SB201901021);郑州市协同创新重大专项科技攻关项目(20XTZX1120) |
| 摘 要： | 第六届中国健康信息处理会议(China conference on Health Information Processing,CHIP 2020)组织了中文医疗信息处理方面的6个评测任务,其中任务2为中文医学文本实体关系抽取任务,该任务的主要目标为自动抽取中文医学文本中的实体关系三元组。共有174支队伍参加了评测任务,最终17支队伍提交了42组结果,该任务以微平均F1值为最终评估标准,提交结果中F1最高值达0.648 6。 |
| 关 键 词： | 实体关系抽取 中文医学文本处理 信息抽取 |
Overview of CHIP 2020 Shared Task 2: Entity and Relation Extraction in Chinese Medical Text |
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| GAN Zifa,ZAN Hongying,GUAN Tongfeng,LI Wenxin,ZHANG Huan,ZHU Tiantian,SUI Zhifang,CHEN Qingcai.Overview of CHIP 2020 Shared Task 2: Entity and Relation Extraction in Chinese Medical Text[J].Journal of Chinese Information Processing,2022,36(6):101-108. | |
| Authors: | GAN Zifa ZAN Hongying GUAN Tongfeng LI Wenxin ZHANG Huan ZHU Tiantian SUI Zhifang CHEN Qingcai |
| Affiliation: | 1.School of Information Engineering, Zhengzhou University, Zhengzhou, Henan 450001, China; 2.Key Laboratory of Computational Linguistics, Ministry of Education, Peking University, Beijing 100871, China; 3.Harbin Institute of Technology (Shenzhen), Shenzhen, Guangdong 518000, China; 4.Peng Cheng Laboratory, Shenzhen, Guangdong 518052, China |
| Abstract: | The 6th China conference on Health Information Processing (CHIP 2020) organized six shared tasks in Chinese medical information processing. The second task was entity and relation extraction that automatically extracts the triples consist of entities and relations from Chinese medical texts. A total of 174 teams signed up for the task, and eventually 17 teams submitted 42 system runs. According to micro-average F1 which was the key evaluation criterion in the task, the top performance of the submitted results reaches 0.648 6. |
| Keywords: | entity and relation extraction Chinese medical text processing information extraction |
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