PROBE is a generalized rank-based KGC evaluation framework with adjustable sharpness and bias-robustness components that satisfies six claimed key properties where prior metrics fall short.
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Entity representations learned from text via link prediction generalize to unseen entities and transfer to classification and retrieval with reported gains of 22% MRR, 16% accuracy, and 8.8% NDCG@10.
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Generalized Rank-based Evaluation for Knowledge Graph Completion: Perspectives, Framework, and Analyses
PROBE is a generalized rank-based KGC evaluation framework with adjustable sharpness and bias-robustness components that satisfies six claimed key properties where prior metrics fall short.
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Inductive Entity Representations from Text via Link Prediction
Entity representations learned from text via link prediction generalize to unseen entities and transfer to classification and retrieval with reported gains of 22% MRR, 16% accuracy, and 8.8% NDCG@10.