Knowledge Commons of Institute of Automation,CAS
Joint Extraction of Multiple Relations and Entities by using a Hybrid Neural Network | |
Peng Zhou1,2; Suncong Zheng1,2; Jiaming Xu1; Zhenyu Qi1; Hongyun Bao1; Bo Xu1,2 | |
2017 | |
会议名称 | The Sixteenth China National Conference on Computational Linguistics |
会议日期 | 2017 |
会议地点 | Nanjing, China |
出版地 | Nanjing |
出版者 | Springer |
摘要 | This paper proposes a novel end-to-end neural model to jointly extract entities and relations in a sentence. Unlike most existing approaches, the proposed model uses a hybrid neural network to automatically learn sentence features and does not rely on any Natural Language Processing (NLP) tools, such as dependency parser. Our model is further capable of modeling multiple relations and their corresponding entity pairs simultaneously. Experiments on the CoNLL04 dataset demonstrate that our model using only word embeddings as input features achieves state-of-the-art performance. |
语种 | 英语 |
文献类型 | 会议论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/40653 |
专题 | 复杂系统认知与决策实验室_听觉模型与认知计算 |
通讯作者 | Zhenyu Qi |
作者单位 | 1.CASIA 2.University of Chinese Academy of Sciences |
第一作者单位 | 中国科学院自动化研究所 |
通讯作者单位 | 中国科学院自动化研究所 |
推荐引用方式 GB/T 7714 | Peng Zhou,Suncong Zheng,Jiaming Xu,et al. Joint Extraction of Multiple Relations and Entities by using a Hybrid Neural Network[C]. Nanjing:Springer,2017. |
条目包含的文件 | ||||||
文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
2017 CCL zhou.pdf(247KB) | 会议论文 | 开放获取 | CC BY-NC-SA | 浏览 |
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