How new is the (RDF) news? Assessing knowledge graph completeness over news feed entities

Abstract

Linked Open Data and the RDF format have become the premier method of publishing structured data representing entities and facts. Specifically, media organizations, such as the New York Times and the BBC, have embraced Linked Open Data as a way of providing structured access to traditional media content, including articles, images, and video. To ground RDF entities and predicates in existing Linked Open Data sources, dataset curators provide links for some entities to existing general purpose repositories, such as YAGO and DBpedia, using entity extraction and linking tools. However, these state-of-the-art tools rely on the entities to exist in the knowledge base. How much of the information is actually new and thus unable to be grounded is unclear. In this work, we empirically investigate the prevalence of new entities in news feeds with respect to both public and commercial knowledge graphs.