Learning the extraction order of multiple relational facts in a sentence with reinforcement learning

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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.

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APA

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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