| 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
| |
| 2017 | |
| 会议名称 | The 55th annual meeting of the Association for Computational Linguistics (ACL) |
| 会议日期 | 2017-07-30 |
| 会议地点 | 加拿大温哥华 |
| 所属项目编号 | 2015AA015402 ; 61602479 |
| 摘要 | 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. |
| 收录类别 | EI |
| 资助项目 | National High Technology Research and Development Program of China (863 Program) |
| 文献类型 | 会议论文 |
| 条目标识符 | http://ir.ia.ac.cn/handle/173211/14344 |
| 专题 | 数字内容技术与服务研究中心_听觉模型与认知计算 |
| 作者单位 | Institute of Automation, Chinese Academy of Sciences |
| 推荐引用方式 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. |
| 条目包含的文件 | 下载所有文件 | |||||
| 文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
| [17-ACL] Joint Extra（1235KB） | 会议论文 | 开放获取 | CC BY-NC-SA | 浏览 下载 | ||
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