TDG-Bench Leaderboard

A dual-purpose benchmark for text-derived knowledge graphs and GNN evaluation in the biomedical domain. Semi-supervised node classification on 8 semantic types across 3 graph variants derived from MedMentions + UMLS-NCI.

Biomedical NLP Node Classification KG Construction
# Model Accuracy Macro F1
TaskSemi-supervised node classification
Classes8 semantic types — 1,032 annotated nodes
Data split10 / 10 / 80 — train / val / test, stratified
Seeds42, 123, 456, 789, 1000 — mean ± std reported
Node initializationall-MiniLM-L6-v2 (sentence-transformers)
OptimizerAdam, lr=0.01, weight_decay=5×10−&sup4;
RegularizationDropout 0.5, early stopping (patience=20)
Hidden dimsTuned over {64, 128, 256}