| Joint Extraction of Entities and Relations Based on a Novel Tagging Scheme | |
Zheng SC(郑孙聪); Feng Wang ; Hongyun Bao; Yuexing Hao; Peng Zhou; Bo Xu
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| 2017 | |
| Conference Name | The 55th annual meeting of the Association for Computational Linguistics (ACL) |
| Conference Date | 2017-07-30 |
| Conference Place | 加拿大温哥华 |
| Project Number | 2015AA015402 ; 61602479 |
| Abstract | Joint extraction of entities and relations is an important task in information extraction. To tackle this problem, we firstly propose a novel tagging scheme that can convert the joint extraction task to a tagging problem. Then, based on our tagging scheme, we study different end-toend models to extract entities and their relations directly, without identifying entities and relations separately. We conduct experiments on a public dataset produced by distant supervision method and the experimental results show that the tagging based methods are better than most of the existing pipelined and joint learning methods. What’s more, the end-to-end model proposed in this paper, achieves the best results on the public dataset. |
| Indexed By | EI |
| Funding Project | National High Technology Research and Development Program of China (863 Program) |
| Document Type | 会议论文 |
| Identifier | http://ir.ia.ac.cn/handle/173211/14344 |
| Collection | 数字内容技术与服务研究中心_听觉模型与认知计算 |
| Affiliation | Institute of Automation, Chinese Academy of Sciences |
| Recommended Citation GB/T 7714 | Zheng SC,Feng Wang,Hongyun Bao,et al. Joint Extraction of Entities and Relations Based on a Novel Tagging Scheme[C],2017. |
| Files in This Item: | Download All | |||||
| File Name/Size | DocType | Version | Access | License | ||
| [17-ACL] Joint Extra（1235KB） | 会议论文 | 开放获取 | CC BY-NC-SA | View Application Full Text | ||
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