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Cross-Lingual Type Inference

机译:跨语言类型推断

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摘要

Entity typing is an essential task for constructing a knowledge base. However, many non-English knowledge bases fail to type their entities due to the absence of a reasonable local hierarchical taxonomy. Since constructing a widely accepted taxonomy is a hard problem, we propose to type these non-English entities with some widely accepted taxonomies in English, such as DBpedia, Yago and Freebase. We define this problem as cross-lingual type inference. In this paper, we present CUTE to type Chinese entities with DBpedia types. First we exploit the cross-lingual entity linking between Chinese and English entities to construct the training data. Then we propose a multi-label hierarchical classification algorithm to type these Chinese entities. Experimental results show the effectiveness and efficiency of our method.
机译:实体键入是构建知识库的重要任务。然而,由于没有合理的局部分类分类,许多非英语知识库未能键入其实体。由于构建广泛接受的分类是一个难以解决的问题,我们建议用一些广泛接受的英语分类,如DBPedia,Yago和FreeBase。我们将此问题定义为交叉语言类型推断。在本文中,我们展示了可爱的键入中国实体的DBPedia类型。首先,我们利用汉语和英语实体之间的跨语言实体来构建培训数据。然后我们提出了一种多标签分层分类算法来键入这些中国实体。实验结果表明了我们方法的有效性和效率。

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