Benchmark and Best Practices for Biomedical Knowledge Graph Embeddings

Test set accuracy for entity semantic type (STY) and semantic group (SG) classification are reported in Table 3. In accordance with the visualizations of semantic clusters (Figures 1 and 2), the KGE and NE methods perform significantly better than the corpus-based method (Cui2Vec). Notably, TransE and RotatE attain near-perfect accuracy for the broader semantic group classification (4 classes). ComplEx, DistMult, and SimplE perform slighty worse, Snomed2Vec slightly below them, and Cui2Vec falls behind by a significant margin. We see a greater discrepancy in relative performance by model type in semantic type classification (32 classes), in which more fine-grained semantic information is required.