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Joint Extraction of Entities and Relations Based on a Novel

发布于44个月以前

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发布于44个月以前

Joint Extraction of Entities and Relations Based on a Novel Tagging Scheme

Joint extraction of entities and relations is an important task in information extraction. To tackle this problem, we firstly propose a novel tagging scheme that can convert the joint extraction task to a tagging problem. Then, based on our tagging scheme, we study different end-toend models to extract entities and their relations directly, without identifying entities and relations separately. We conduct experiments on a public dataset produced by distant supervision method and the experimental results show that the tagging based methods are better than most of the existing pipelined and joint learning methods. What’s more, the end-to-end model proposed in this paper, achieves the best results on the public dataset.

论文下载

论文地址:https://aclanthology.org/P17-1113.pdf

算法链接

算法https://marketplace.huaweicloud.com/markets/aihub/modelhub/detail/?id=039c08e1-b619-4d28-b9fa-857a0ad1536a

算法指南

算法指南https://bbs.huaweicloud.com/forum/thread-98843-1-1.html

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