HyperKG: Hyperbolic Knowledge Graph Embeddings for Knowledge Base Completion
Table 3: Experimental results on WD and WD++ test sets. MRR and H@10 denote the mean reciprocal rank and Hits@10 (in %), respectively.
['[BOLD] Method', '[BOLD] WD MRR', '[BOLD] WD H@10', '[BOLD] WD++ MRR', '[BOLD] WD++ H@10']
We compare HyperKG performance against TransE and ComplEx. It can be observed that neither of the models manages to totally capture the statistical regularities of these datasets. All the models present similar behaviour in terms of Hits@10. HyperKG and TransE , that both have convex relation spaces, outperform ComplEx on both datasets. HyperKG shows the best performance on WD, and demonstrates almost the same performance with TransE on WD++.