Mulwad, VarishFinin, TimSyed, ZareenJoshi, Anupam2018-11-202018-11-202010-11-08http://hdl.handle.net/11603/12070Proceedings of the the First International Workshop on Consuming Linked DataVast amounts of information is available in structured forms like spreadsheets, database relations, and tables found in documents and on the Web. We describe an approach that uses linked data to interpret such tables and associate their components with nodes in a reference linked data collection. Our proposed framework assigns a class (i.e. type) to table columns, links table cells to entities, and inferred relations between columns to properties. The resulting interpretation can be used to annotate tables, con firm existing facts in the linked data collection, and propose new facts to be added. Our implemented prototype uses DBpedia as the linked data collection and Wikitology for background knowledge. We evaluated its performance using a collection of tables from Google Squared, Wikipedia and the Web.12 pagesen-USThis item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author.Semantic Weblinked datahuman language technologyentity linkinginformation retrievalUMBC Ebiquity Research GroupText