Abstract
The multiple relation extraction task tries to extract all relational facts from a sentence. Existing works didn't consider the extraction order of relational facts in a sentence. In this paper we argue that the extraction order is important in this task. To take the extraction order into consideration, we apply the reinforcement learning into a sequence-to-sequence model. The proposed model could generate relational facts freely. Widely conducted experiments on two public datasets demonstrate the efficacy of the proposed method.
Cite
CITATION STYLE
Zeng, X., He, S., Zeng, D., Liu, K., & Zhao, J. (2019). Learning the extraction order of multiple relational facts in a sentence with reinforcement learning. In EMNLP-IJCNLP 2019 - 2019 Conference on Empirical Methods in Natural Language Processing and 9th International Joint Conference on Natural Language Processing, Proceedings of the Conference (pp. 367–377). Association for Computational Linguistics. https://doi.org/10.18653/v1/D19-1035
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