Machine Reading Comprehension Using Structural Knowledge Graph-aware Network
Delai Qiu1; Yuanzhe Zhang2; Xinwei Feng4; Xiangwen Liao1; Wenbin Jiang4; Yajuan Lyu4; Kang Liu2,3; Jun Zhao2,3
2019-11
会议名称Conference on Empirical Methods in Natural Language Processing (EMNLP 2019)
会议日期Nov 3, 2019 - Nov 7, 2019
会议地点Hong Kong, China
摘要

Leveraging external knowledge is an emerging trend in machine comprehension task. Previous work usually utilizes knowledge graphs such as ConceptNet as external knowledge, and extracts triples from them to enhance the initial representation of the machine comprehension context. However, such method cannot capture the structural information in the knowledge graph. To this end, we propose a Structural Knowledge Graph-aware Network(SKG) model, constructing sub-graphs for entities in the machine comprehension context. Our method dynamically updates the representation of the knowledge according to the structural information of the constructed sub-graph. Experiments show that SKG achieves state-of-the-art performance on the ReCoRD dataset.

收录类别EI
语种英语
文献类型会议论文
条目标识符http://ir.ia.ac.cn/handle/173211/40583
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.College of Mathematics and Computer Science, Fuzhou University
2.Institute of Automation, Chinese Academy of Sciences
3.University of Chinese Academy of Sciences
4.Baidu Inc.,
推荐引用方式
GB/T 7714
Delai Qiu,Yuanzhe Zhang,Xinwei Feng,et al. Machine Reading Comprehension Using Structural Knowledge Graph-aware Network[C],2019.
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