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ShanghaiTech University Knowledge Management System
An Empirical Study of Pipeline vs. Joint Approaches to Entity and Relation Extraction | |
2022-11-20 | |
会议录名称 | THE 2ND CONFERENCE OF THE ASIA-PACIFIC CHAPTER OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS AND THE 12TH INTERNATIONAL JOINT CONFERENCE ON NATURAL LANGUAGE PROCESSING (AACL-IJCNLP 2022)
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发表状态 | 已发表 |
摘要 | The Entity and Relation Extraction (ERE) task includes two basic sub-tasks: Named Entity Recognition and Relation Extraction. In the last several years, much work focused on joint approaches for the common perception that the pipeline approach suffers from the error propagation problem. Recent work reconsiders the pipeline scheme and shows that it can produce comparable results. To systematically study the pros and cons of these two schemes. We design and test eight pipeline and joint approaches to the ERE task. We find that with the same span representation methods, the best joint approach still outperforms the best pipeline model, but improperly designed joint approaches may have poor performance. We hope our work could shed some light on the pipeline-vs-joint debate of the ERE task and inspire further research |
会议名称 | the 2nd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 12th International Joint Conference on Natural Language Processing (AACL-IJCNLP 2022) |
会议日期 | 2022-11 |
文献类型 | 会议论文 |
条目标识符 | https://kms.shanghaitech.edu.cn/handle/2MSLDSTB/284202 |
专题 | 信息科学与技术学院_博士生 信息科学与技术学院_PI研究组_屠可伟组 |
共同第一作者 | Jia, Zixia |
通讯作者 | Tu, Kewei |
作者单位 | 1.School of Information Science and Technology, ShanghaiTech University, Shanghai, China 2.Shanghai Engineering Research Center of Intelligent Vision and Imaging |
第一作者单位 | 信息科学与技术学院 |
通讯作者单位 | 信息科学与技术学院 |
第一作者的第一单位 | 信息科学与技术学院 |
推荐引用方式 GB/T 7714 | Yan, Zhaohui,Jia, Zixia,Tu, Kewei. An Empirical Study of Pipeline vs. Joint Approaches to Entity and Relation Extraction[C],2022. |
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