What Computers Should Know, Shouldn't Know, and Shouldn't Believe.

Automatically constructed knowledge bases (KB's) are a powerful asset for search, analytics, recommendations and data integration, with intensive use at big industrial stake-holders. Examples are the knowledge graphs for search engines (e.g., Google, Bing, Baidu) and social networks (e.g., Facebook), as well as domain-specific KB's (e.g., Bloomberg, Walmart). These achievements are rooted in academic research and community projects. The largest general-purpose KB's with publicly accessible contents are BabelNet, DBpedia, Wikidata, and Yago. They contain millions of entities, organized in hundreds to hundred thousands of semantic classes, and billions of relational facts on entities. These and other knowledge and data resources are interlinked at the entity level, forming the Web of Linked Open Data.