MMKG: Multi-Modal Knowledge Graphs
This provides a new dataset for the multi-modal learning and knowledge graph communities, facilitating development in these areas.
The authors introduced MMKG, a collection of three knowledge graphs with numerical features and images for entities, along with entity alignments, to support multi-relational link prediction and entity matching. They validated its utility in the sameAs link prediction task, showing that learning from multiple feature types improves performance.
We present MMKG, a collection of three knowledge graphs that contain both numerical features and (links to) images for all entities as well as entity alignments between pairs of KGs. Therefore, multi-relational link prediction and entity matching communities can benefit from this resource. We believe this data set has the potential to facilitate the development of novel multi-modal learning approaches for knowledge graphs.We validate the utility ofMMKG in the sameAs link prediction task with an extensive set of experiments. These experiments show that the task at hand benefits from learning of multiple feature types.