Learning Dynamic Context Augmentation for Global Entity Linking
Xiyuan Yang, Xiaotao Gu, Sheng Lin, Siliang Tang, Yueting Zhuang, Fei Wu, Zhigang Chen, Guoping Hu, Xiang Ren
Abstract
Despite of the recent success of collective entity linking (EL) methods, these “global” inference methods may yield sub-optimal results when the “all-mention coherence” assumption breaks, and often suffer from high computational cost at the inference stage, due to the complex search space. In this paper, we propose a simple yet effective solution, called Dynamic Context Augmentation (DCA), for collective EL, which requires only one pass through the mentions in a document. DCA sequentially accumulates context information to make efficient, collective inference, and can cope with different local EL models as a plug-and-enhance module. We explore both supervised and reinforcement learning strategies for learning the DCA model. Extensive experiments show the effectiveness of our model with different learning settings, base models, decision orders and attention mechanisms.- Anthology ID:
- D19-1026
- 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
- Editors:
- Kentaro Inui, Jing Jiang, Vincent Ng, Xiaojun Wan
- Venues:
- EMNLP | IJCNLP
- SIG:
- SIGDAT
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 271–281
- Language:
- URL:
- https://aclanthology.org/D19-1026
- DOI:
- 10.18653/v1/D19-1026
- Cite (ACL):
- Xiyuan Yang, Xiaotao Gu, Sheng Lin, Siliang Tang, Yueting Zhuang, Fei Wu, Zhigang Chen, Guoping Hu, and Xiang Ren. 2019. Learning Dynamic Context Augmentation for Global Entity Linking. 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 271–281, Hong Kong, China. Association for Computational Linguistics.
- Cite (Informal):
- Learning Dynamic Context Augmentation for Global Entity Linking (Yang et al., EMNLP-IJCNLP 2019)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-5/D19-1026.pdf
- Code
- YoungXiyuan/DCA + additional community code
- Data
- AIDA CoNLL-YAGO, CoNLL