Efficient Few-shot Link Prediction on Hyper-relational Knowledge Graphs

This paper introduces a new task called Few-Shot Link Prediction on Hyper-relational Facts (FSLPHFs), which aims to predict a missing entity in a hyper-relational fact with limited support instances. The authors propose MetaRH, a model that learns Meta Relational information in Hyper-relational facts to accurately predict the missing entity.