Cross-lingual type inference

Bo Xu, Yi Zhang, Jiaqing Liang, Yanghua Xiao, Seung Won Hwang, Wei Wang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

20 Citations (Scopus)


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.

Original languageEnglish
Title of host publicationDatabase Systems for Advanced Applications - 21st International Conference, DASFAA 2016, Proceedings
EditorsShamkant B. Navathe, Weili Wu, Shashi Shekhar, Xiaoyong Du, Hui Xiong, X. Sean Wang
PublisherSpringer Verlag
Number of pages16
ISBN (Print)9783319320243
Publication statusPublished - 2016
Event21st International Conference on Database Systems for Advanced Applications, DASFAA 2016 - Dallas, United States
Duration: 2016 Apr 162016 Apr 19

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other21st International Conference on Database Systems for Advanced Applications, DASFAA 2016
Country/TerritoryUnited States

Bibliographical note

Funding Information:
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.

Publisher Copyright:
© Springer International Publishing Switzerland 2016.

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)


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