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A survey on neural relation extraction | |
Liu Kang1,2 | |
发表期刊 | SCIENCE CHINA-TECHNOLOGICAL SCIENCES |
ISSN | 1674-7321 |
2020-09-15 | |
页码 | 19 |
通讯作者 | Liu Kang(kliu@nlpr.ia.ac.cn) |
摘要 | Relation extraction is a key task for knowledge graph construction and natural language processing, which aims to extract meaningful relational information between entities from plain texts. With the development of deep learning, many neural relation extraction models were proposed recently. This paper introduces a survey on the task of neural relation extraction, including task description, widely used evaluation datasets, metrics, typical methods, challenges and recent research progresses. We mainly focus on four recent research problems: (1) how to learn the semantic representations from the given sentences for the target relation, (2) how to train a neural relation extraction model based on insufficient labeled instances, (3) how to extract relations across sentences or in a document and (4) how to jointly extract relations and corresponding entities? Finally, we give out our conclusion and future research issues. |
关键词 | knowledge graph relation extraction event extraction and information extraction |
DOI | 10.1007/s11431-020-1673-6 |
收录类别 | SCI |
语种 | 英语 |
资助项目 | National Natural Science Foundation of China[61922085] ; National Natural Science Foundation of China[61533018] ; Natural Key R&D Program of China[2018YFC0830101] ; Key Research Program of the Chinese Academy of Sciences[ZDBS-SSW-JSC006] ; Beijing Academy of Artificial Intelligence[BAAI2019QN0301] ; Open Project of Beijing Key Laboratory of Mental Disorders[2019JSJB06] ; independent research project of National Laboratory of Pattern Recognition |
项目资助者 | National Natural Science Foundation of China ; Natural Key R&D Program of China ; Key Research Program of the Chinese Academy of Sciences ; Beijing Academy of Artificial Intelligence ; Open Project of Beijing Key Laboratory of Mental Disorders ; independent research project of National Laboratory of Pattern Recognition |
WOS研究方向 | Engineering ; Materials Science |
WOS类目 | Engineering, Multidisciplinary ; Materials Science, Multidisciplinary |
WOS记录号 | WOS:000571751900001 |
出版者 | SCIENCE PRESS |
七大方向——子方向分类 | 自然语言处理 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/42003 |
专题 | 多模态人工智能系统全国重点实验室_自然语言处理 |
通讯作者 | Liu Kang |
作者单位 | 1.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China 2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China |
第一作者单位 | 模式识别国家重点实验室 |
通讯作者单位 | 模式识别国家重点实验室 |
推荐引用方式 GB/T 7714 | Liu Kang. A survey on neural relation extraction[J]. SCIENCE CHINA-TECHNOLOGICAL SCIENCES,2020:19. |
APA | Liu Kang.(2020).A survey on neural relation extraction.SCIENCE CHINA-TECHNOLOGICAL SCIENCES,19. |
MLA | Liu Kang."A survey on neural relation extraction".SCIENCE CHINA-TECHNOLOGICAL SCIENCES (2020):19. |
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