Triplifying Wikipedia's Tables

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Triplifying Wikipedia's Tables - scientific work related to Wikipedia quality published in 2013, written by Emir Muñoz, Aidan Hogan and Alessandra Mileo.

Overview

Authors are currently investigating methods to triplify the content of Wikipedia's tables. Authors propose that existing knowledge-bases can be leveraged to semi-automatically extract high-quality facts (in the form of RDF triples) from tables embedded in Wikipedia articles (henceforth called "Wikitables"). Authors present a survey of Wikitables and their content in a recent dump of Wikipedia. Authors then discuss some ongoing work on using DBpedia to mine novel RDF triples from these tables: authors present methods that automatically extract 24.4 million raw triples from the Wikitables at an estimated precision of 52.2%. Authors believe this precision can be (greatly) improved through machine learning methods and sketch ideas for features that should help classify (in)correct triples.

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