Catriple: Extracting Triples from Wikipedia Categories

As an important step towards bootstrapping the Semantic Web, many efforts have been made to extract triples from Wikipedia because of its wide coverage, good organization and rich knowledge. One kind of important triples is about Wikipedia articles and their non-isa properties, e.g. (Beijing, country, China). Previous work has tried to extract such triples from Wikipedia infoboxes, article text and categories. The infobox-based and text-based extraction methods depend on the infoboxes and suffer from a low article coverage. In contrast, the categorybased extraction methods exploit the widespread categories. However, they rely on predefined properties, which is too effort-consuming and explores only very limited knowledge in the categories. This paper automatically extracts properties and triples from the less explored Wikipedia categories so as to achieve a wider article coverage with less manual effort. We manage to realize this goal by utilizing the syntax and semantics brought by su...

• Type: Conference
• Year: 2008
• Where: ASWC
• Authors: Qiaoling Liu, Kaifeng Xu, Lei Zhang, Haofen Wang, Yong Yu, Yue Pan
• Keywords: ASWC 2008, Internet Technology, Triples, Wikipedia, Wikipedia Articles