Trained Knowledge Graph Embeddings for LP-DIXIT Experiments

Barile, Roberto

doi:10.6084/m9.figshare.28424246.v1

Trained Knowledge Graph Embeddings for LP-DIXIT Experiments

conference contribution

posted on 2025-02-15, 16:35 authored by Roberto BarileRoberto Barile

This resource contains the Knowledge Graph Embeddings used in the experiments of the following publication:

Roberto Barile, Claudia d’Amato, and Nicola Fanizzi. 2025. LP-DIXIT: Evaluating Explanations of Link Predictions on Knowledge Graphs using Large Language Models. In Proceedings of the ACM Web Conference 2025 (WWW’25), April 28–May 2, 2025, Sydney, NSW, Australia. ACM, New York, NY, USA, 9 pages. https://doi.org/10.1145/3696410.3714667

Funding

FAIR - Future AI Research (PE00000013), spoke 6 - Symbiotic AI (https://future-ai-research.it/) under the PNRR MUR program funded by the European Union - NextGenerationEU

PRIN project HypeKG - Hybrid Prediction and Explanation with Knowledge Graphs (Prot. 2022Y34XNM, CUP H53D23003700006) under the PNRR MUR program funded by the European Union - NextGenerationEU

Trained Knowledge Graph Embeddings for LP-DIXIT Experiments

Funding

FAIR - Future AI Research (PE00000013), spoke 6 - Symbiotic AI (https://future-ai-research.it/) under the PNRR MUR program funded by the European Union - NextGenerationEU

PRIN project HypeKG - Hybrid Prediction and Explanation with Knowledge Graphs (Prot. 2022Y34XNM, CUP H53D23003700006) under the PNRR MUR program funded by the European Union - NextGenerationEU

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