Abstract
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.
Y. Xiao—This paper was supported by the National NSFC (No. 61472085, 61171132, 61033010, U1509213), by National Key Basic Research Program of China under No. 2015CB358800, by Shanghai Municipal Science and Technology Commission foundation key project under No. 15JC1400900. Seung-won Hwang was supported by Microsoft.
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Notes
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In this paper, we strictly differentiate “category” from “type”. “Category” always refer to the part of the knowledge base such as Baidu Baike and Wikipedia named as “category”. Most of these categories actually are only tags of an entity. Instead “type” always refer to the class that an entity can be classified into.
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Xu, B., Zhang, Y., Liang, J., Xiao, Y., Hwang, Sw., Wang, W. (2016). Cross-Lingual Type Inference. In: Navathe, S., Wu, W., Shekhar, S., Du, X., Wang, X., Xiong, H. (eds) Database Systems for Advanced Applications. DASFAA 2016. Lecture Notes in Computer Science(), vol 9642. Springer, Cham. https://doi.org/10.1007/978-3-319-32025-0_28
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