2015 | OriginalPaper | Chapter
Mining RDF from Tables in Chinese Encyclopedias
Authors : Weiming Lu, Zhenyu Zhang, Renjie Lou, Hao Dai, Shansong Yang, Baogang Wei
Published in: Natural Language Processing and Chinese Computing
Publisher: Springer International Publishing
Activate our intelligent search to find suitable subject content or patents.
Select sections of text to find matching patents with Artificial Intelligence. powered by
Select sections of text to find additional relevant content using AI-assisted search. powered by
Web tables understanding has recently attracted a number of studies. However, many works focus on the tables in English, because they usually need the help of knowledge bases, while the existing knowledge bases such as DBpedia, YAGO, Freebase and Probase mainly contain knowledge in English.
In this paper, we focus on the RDF triples extraction from tables in Chinese encyclopedias. Firstly, we constructed a Chinese knowledge base through taxonomy mining and class attribute mining. Then, with the help of our knowledge base, we extracted triples from tables through column scoring, table classification and RDF extraction. In our experiments, we practically implemented our approach in 6,618,544 articles from
Hudong Baike
with 764,292 tables, and extracted about 1,053,407 unique and new RDF triples with an estimated accuracy of
$$90.2\%$$
, which outperforms other similar works.