中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
首页 机构 成果 学者
  
  1. CAS IR Grid
  2. 计算技术研究所
  3. 中国科学院计算技术研究所
  4. 中国科学院计算技术研究所期刊论文
  5. 英文
Nested relation extraction with iterative neural network

文献类型：期刊论文

作者Cao, Yixuan1,2; Chen, Dian1,2; Xu, Zhengqi1,2; Li, Hongwei1,2; Luo, Ping1,2
刊名FRONTIERS OF COMPUTER SCIENCE
出版日期2021-01-16
卷号15期号:3页码:14
关键词nested relation extraction mention insensitive relation iterative neural network
ISSN号2095-2228
DOI10.1007/s11704-020-9420-6
英文摘要Most existing researches on relation extraction focus on binary flat relations like BornIn relation between a Person and a Location. But a large portion of objective facts described in natural language are complex, especially in professional documents in fields such as finance and biomedicine that require precise expressions. For example, "the GDP of the United States in 2018 grew 2.9% compared with 2017" describes a growth rate relation between two other relations about the economic index, which is beyond the expressive power of binary flat relations. Thus, we propose the nested relation extraction problem and formulate it as a directed acyclic graph (DAG) structure extraction problem. Then, we propose a solution using the Iterative Neural Network which extracts relations layer by layer. The proposed solution achieves 78.98 and 97.89 F1 scores on two nested relation extraction tasks, namely semantic cause-and-effect relation extraction and formula extraction. Furthermore, we observe that nested relations are usually expressed in long sentences where entities are mentioned repetitively, which makes the annotation difficult and error-prone. Hence, we extend our model to incorporate a mention-insensitive mode that only requires annotations of relations on entity concepts (instead of exact mentions) while preserving most of its performance. Our mention-insensitive model performs better than the mention sensitive model when the random level in mention selection is higher than 0.3.
资助项目National Key Research and Development Program of China[2017YFB1002104] ; National Natural Science Foundation of China[U1811461] ; Innovation Program of Institute of Computing Technology, CAS
WOS研究方向Computer Science
语种英语
WOS记录号WOS:000610455900003
出版者HIGHER EDUCATION PRESS
源URL[http://119.78.100.204/handle/2XEOYT63/16330]  
专题中国科学院计算技术研究所期刊论文_英文
通讯作者Luo, Ping
作者单位1.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
2.Chinese Acad Sci, Inst Comp Technol, Key Lab Intelligent Informat Proc, Beijing 100190, Peoples R China
推荐引用方式
GB/T 7714		 Cao, Yixuan,Chen, Dian,Xu, Zhengqi,et al. Nested relation extraction with iterative neural network[J]. FRONTIERS OF COMPUTER SCIENCE,2021,15(3):14.
APA Cao, Yixuan,Chen, Dian,Xu, Zhengqi,Li, Hongwei,&Luo, Ping.(2021).Nested relation extraction with iterative neural network.FRONTIERS OF COMPUTER SCIENCE,15(3),14.
MLA Cao, Yixuan,et al."Nested relation extraction with iterative neural network".FRONTIERS OF COMPUTER SCIENCE 15.3(2021):14.

入库方式： OAI收割

来源：计算技术研究所

浏览0
下载0
收藏0
其他版本

除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。