Machine Reading Comprehension Using Structural Knowledge Graph-aware Network

Delai Qiu, Yuanzhe Zhang, Xinwei Feng, Xiangwen Liao, Wenbin Jiang, Yajuan Lyu, Kang Liu, Jun Zhao


Abstract
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.
Anthology ID:
D19-1602
Volume:
Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)
Month:
November
Year:
2019
Address:
Hong Kong, China
Venues:
EMNLP | IJCNLP
SIG:
SIGDAT
Publisher:
Association for Computational Linguistics
Note:
Pages:
5896–5901
Language:
URL:
https://aclanthology.org/D19-1602
DOI:
10.18653/v1/D19-1602
Bibkey:
Cite (ACL):
Delai Qiu, Yuanzhe Zhang, Xinwei Feng, Xiangwen Liao, Wenbin Jiang, Yajuan Lyu, Kang Liu, and Jun Zhao. 2019. Machine Reading Comprehension Using Structural Knowledge Graph-aware Network. In Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP), pages 5896–5901, Hong Kong, China. Association for Computational Linguistics.
Cite (Informal):
Machine Reading Comprehension Using Structural Knowledge Graph-aware Network (Qiu et al., EMNLP 2019)
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PDF:
https://aclanthology.org/D19-1602.pdf