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cs.AI2026
PyKEEN-NSX: A Modular Framework for Static, Dynamic and Schema-Aware Negative Sampling in PyKEEN
Ivan Diliso, Nicola Fanizzi, Claudia d'Amato
Embedding methods have become popular due to their scalability on link prediction and/or triple classification tasks on Knowledge Graphs (KGs). Embedding models are trained relying…
cs.AI2026
Return of the Schema: Building Complete Datasets for Machine Learning and Reasoning on Knowledge Graphs
Ivan Diliso, Roberto Barile, Claudia d'Amato +1
Datasets for the experimental evaluation of knowledge graph refinement algorithms typically contain only ground facts, retaining very limited schema level knowledge even when such…