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XLink: An Unsupervised Bilingual Entity Linking System

机译:XLink:无监督的双语实体链接系统

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Entity linking is a task of linking mentions in text to the corresponding entities in a knowledge base. Recently, entity linking has received considerable attention and several online entity linking systems have been published. In this paper, we build an online bilingual entity linking system XLink, which is based on Wikipeida and Baidu Baike. XLink conducts two steps to link the mentions in the input document to entities in knowledge base, namely mention parsing and entity disambiguation. To eliminate dependency of language, we conduct mention parsing without any named entity recognition tools. To ensure the correctness of linking results, we propose an unsupervised generative probabilistic method and utilize text and knowledge joint representations to perform entity disambiguation. Experiments show that our system gets a state-of-the-art performance and a high time efficiency.
机译:实体链接是一个任务,可以将文本中的提到与知识库中的相应实体链接。最近,实体链接已接受了相当大的关注,并且已发布了几个在线实体链接系统。在本文中,我们构建了一个在线双语实体链接系统XLink,其基于WikiSeida和Baidu Baike。 XLink进行两个步骤,将输入文档中的提到链接到知识库中的实体,即提及解析和实体消歧。为了消除语言的依赖,我们在没有任何命名实体识别工具的情况下提到解析。为确保连接结果的正确性,我们提出了无监督的生成概率方法,并利用文本和知识联合陈述来执行实体歧义。实验表明,我们的系统获得了最先进的性能和高时间效率。

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