Better together: enhancing generative knowledge graph completion with language models and neighbourhood information
Knowledge graphs are data structures that semantically organise information. They provide a source of verifiable knowledge for deep learning. But such graphs often have gaps due to their scale and complexity. Knowledge graph completion methods exist to fill in these gaps. Inspired by generative language models, we radically improve existing completion methods by including information on a given node's neighbourhood.