Affiliations: [a] Department of Computer Science, Aalborg University, Denmark. E-mails: [email protected], [email protected] | [b] Department of Computer Science, Rutgers, The State University of New Jersey, USA. E-mail: [email protected] | [c] Språkbanken, Department of Swedish, University of Gothenburg, Sweden. E-mail: [email protected]
Abstract: Large-scale knowledge graphs such as those in the Linked Open Data cloud are typically stored as subject-predicate-object 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 multiple levels of granularity connected via logical entailment. Overall, this provides a means for semantic integration from heterogeneous sources under a single schema and opens up possibilities to draw on natural language processing techniques for querying and data mining.