Transformer-based model knowledge graph link prediction

Abstract

A system, product, and method are provided for improving knowledge graph (KG) link prediction using transformer-based artificial neural networks. A first topic model is leveraged against a first dataset derived from a KG containing a plurality of first triples. The first triples include first entities and first edges connecting the first entities to represent relationships between the first connected entities. A first similarity function is applied to the first connected entities of the first triples to provide respective first similarity scores. A first subset of one of more first triples is selected from the plurality of first triples based upon the first similarity scores. An artificial neural network is trained using the selected first subset of one or more first triples.