We present MMKG , a collection of three knowledge graphs that contain both numerical features and images for all entities as well as entity alignments between pairs of KGs, to benchmark multi-relational link prediction and entity matching approaches. We believe this data set has the potential to facilitate the development of novel multimodal learning approaches for knowledge graphs. We validate the utility of MMKG in the sameAs link prediction task with
an extensive set of experiments.