Building a large-scale cross-lingual knowledge base from heterogeneous online wikis

Abstract

Cross-Lingual Knowledge Bases are very important for global knowledge sharing. However, there are few Chinese-English knowledge bases due to the following reasons: 1) the scarcity of Chinese knowledge in existing cross-lingual knowledge bases; 2) the limited number of cross-lingual links; 3) the incorrect relationships in semantic taxonomy. In this paper, a large-scale Cross-Lingual Knowledge Base(named XLORE) is built to address the above problems. Particularly, XLORE integrates four online wikis including English Wikipedia, ChineseWikipedia, Baidu Baike and Hudong Baike to balance the knowledge volume in different languages, employs a link-discovery method to augment the cross-lingual links, and introduces a pruning approach to refine taxonomy. Totally, XLORE harvests 663,740 classes, 56,449 properties, and 10,856,042 instances, among of which, 507,042 entities are cross-lingually linked. At last, we provide an online cross-lingual knowledge base system supporting two ways to access established XLORE, namely a search engine and a SPARQL endpoint.