1. Ali, M., et al.: Bringing light into the dark: a large-scale evaluation of knowledge graph embedding models under a unified framework. IEEE Trans. Pattern Anal. Mach. Intell., 1–1 (2021). https://doi.org/10.1109/TPAMI.2021.3124805
2. Belleau, F., Nolin, M.A., Tourigny, N., Rigault, P., Morissette, J.: Bio2RDF: towards a mashup to build bioinformatics knowledge systems. J. Biomed. Inform. 41(5), 706–716 (2008)
3. Betz, P., Niepert, M., Minervini, P., Stuckenschmidt, H.: Backpropagating through Markov logic networks. In: Proceedings of 15th International Workshop on Neural-Symbolic Learning and Reasoning, vol. 2986, pp. 67–81. CEUR (2021)
4. Bordes, A., Usunier, N., Garcia-Duran, A., Weston, J., Yakhnenko, O.: Translating embeddings for modeling multi-relational data. In: Neural Information Processing Systems (NIPS), pp. 1–9 (2013)
5. Broscheit, S., Ruffinelli, D., Kochsiek, A., Betz, P., Gemulla, R.: LibKGE-a knowledge graph embedding library for reproducible research. In: Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing: System Demonstrations, pp. 165–174 (2020)