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Integrating Heterogeneous Knowledge with FrameBase

Large-scale knowledge graphs such as those in the Linked Data cloud are typically represented as subject-predicateobject triples. However, many facts about the world involve more than two entities. While n-ary relations can be converted to triples in a number of ways, unfortunately, the structurally different choices made in different knowledge sources significantly impede our ability to connect them. They also increase semantic heterogeneity, making it impossible to query the data concisely and without prior knowledge of each individual source. This article presents FrameBase, a wide-coverage knowledge-base schema that uses linguistic frames to represent and query n-ary relations from other knowledge bases, providing also different levels of granularity connected by logical entailment. This altogether provides for flexible and expressive seamless semantic integration from heterogeneous sources. It also opens possibilities to draw on natural language processing techniques for querying and data mining.