Few-shot Link Prediction on N-ary Facts

arXiv:2305.06104v3 Announce Type: replace-cross
Abstract: Hyper-relational facts, which consist of a primary triple (head entity, relation, tail entity) and auxiliary attribute-value pairs, are widely present in real-world Knowledge Graphs (KGs). Link Prediction on Hyper-relational Facts (LPHFs) is to predict a missing element in a hyper-relational fact, which helps populate and enrich KGs. However, existing LPHFs studies usually require an amount of high-quality data. They overlook few-shot relations, which have limited instances, yet are common in real-world scenarios. Thus, we introduce …

abstract arxiv cs.ai cs.ir cs.lg element facts few-shot graphs head however knowledge knowledge graphs link prediction prediction relational type value world