Knowledge Commons of Institute of Automation,CAS
Unsupervised Joint Entity Linking over Question Answering Pair with Global Knowledge | |
Liu, Cao1,2; He, Shizhu1; Yang, Hang1; Liu, Kang1; Zhao, Jun1,2 | |
2017-10 | |
会议名称 | The 16th China National Conference on Computational Linguistics (CCL) |
会议日期 | 13-15 October 2017 |
会议地点 | Nanjing, China |
摘要 | We consider the task of entity linking over question answering pair (QA-pair). In conventional approaches of entity linking, all the entities whether in one sentence or not are considered the same. We focus on entity linking over QA-pair, in which question entity and answer entity are no longer fully equivalent and they are with the explicit semantic relation. We propose an unsupervised method which utilizes global knowledge of QA-pair in the knowledge base(KB). Firstly, we collect large-scale Chinese QA-pairs and their corresponding triples in the knowledge base. Then mining global knowledge such as the probability of relation and linking similarity between question entity and answer entity. Finally integrating global knowledge and other basic features as well as constraints by integral linear programming (ILP) with an unsupervised method. The experimental results show that each proposed global knowledge improves performance. Our best F-measure on QA-pairs is 53.7%, significantly increased 6.5% comparing with the competitive baseline. |
语种 | 英语 |
文献类型 | 会议论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/39194 |
专题 | 多模态人工智能系统全国重点实验室_自然语言处理 |
作者单位 | 1.National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences 2.University of Chinese Academy of Sciences |
第一作者单位 | 模式识别国家重点实验室 |
推荐引用方式 GB/T 7714 | Liu, Cao,He, Shizhu,Yang, Hang,et al. Unsupervised Joint Entity Linking over Question Answering Pair with Global Knowledge[C],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 | ||
CCL2017-Cao Liu.pdf(885KB) | 会议论文 | 开放获取 | CC BY-NC-SA | 浏览 |
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