Knowledge Commons of Institute of Automation,CAS
Joint Learning of Entity Semantics and Relation Pattern for R elation Extraction | |
Suncong Zheng; Jiaming Xu; Hongyun Bao; Zhenyu Qi; Jie Zhang; Hongwei Hao; Bo Xu | |
2016 | |
会议名称 | ECML |
会议日期 | 2016 |
会议地点 | Europe |
出版地 | Berlin |
出版者 | Springer |
摘要 | Relation extraction is identifying the relationship of two given entities in the text. It is an important step in the task of knowledge extraction, which plays a vital role in automatic construction of knowl-edge base. When extracting entities’ relations from sentences, some key-words can reflect the relation pattern, besides, the semantic properties of given entities can also help to distinguish some confusing relations. Based on the above observations, we propose a mixture convolutional neural network for the task of relation extraction, which can simultaneously learn the semantic properties of entities and the keyword information related to the relation. We conduct experiments on the SemEval-2010 Task 8 dataset. The method we propose achieves the state-of-the-art result without using any external information. Additionally, the experi-mental results also show that our approach can learn the semantic rela-tionship of the given entities effectively. |
语种 | 英语 |
文献类型 | 会议论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/40647 |
专题 | 复杂系统认知与决策实验室_听觉模型与认知计算 |
作者单位 | CASIA |
第一作者单位 | 中国科学院自动化研究所 |
推荐引用方式 GB/T 7714 | Suncong Zheng,Jiaming Xu,Hongyun Bao,et al. Joint Learning of Entity Semantics and Relation Pattern for R elation Extraction[C]. Berlin:Springer,2016. |
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 | ||
2016 ECML zheng.pdf(1519KB) | 会议论文 | 开放获取 | CC BY-NC-SA | 浏览 |
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