Abstract: Provided is an incorrect triple detection system including a triple selector configured to select a target triple (subject, type, object) in a knowledge base, a sampler configured to create a sentence model by connecting object triples sharing entities included in the target triple, a model builder configured to embed the sentence model into a vector space to create a training entity vector and build an embedding model, and an incorrect triple detector configured to detect an incorrect triple by inputting a test triple into the embedding model.

Abstract: Provided is an incorrect triple detection system including a triple selector configured to select a target triple (subject, type, object) in a knowledge base, a sampler configured to create a sentence model by connecting object triples sharing entities included in the target triple, a model builder configured to embed the sentence model into a vector space to create a training entity vector and build an embedding model, and an incorrect triple detector configured to detect an incorrect triple by inputting a test triple into the embedding model.

Abstract: Disclosed are a method of operating a knowledgebase and a server using the same. The method of operating a knowledgebase may include: (a) receiving triple data sets as input; (b) forming at least one data cluster set by classifying the triple data sets according to relation based on semantic information of the knowledgebase; and (c) learning each relation model by inputting the data cluster set into a neural tensor network.