Babaei GiglouH.D’SouzaJ.AuerS. (2023). LLMs4OL: Large language models for ontology learning. In PayneT. R. (Ed.), The semantic web – ISWC 2023. ISWC 2023. Lecture Notes in Computer Science, vol 14265. Springer.
2.
CascellaM.MontomoliJ.BelliniV.BignamiE. (2023). Evaluating the feasibility of ChatGPT in healthcare: An analysis of multiple clinical and research scenarios. Journal of Medical Systems.
3.
HoferM.ObraczkaD.SaeediA.KöpckeH.RahmE. (2024). Construction of knowledge graphs: Current state and challenges. Information, 15(8), 509.
4.
MihindukulasooriyaN.TiwariS.EnguixC.F.LataK. (2023). Text2KGBench: A benchmark for ontology-driven knowledge graph generation from text. International Workshop on the Semantic Web.
5.
NeuhausF. (2023). Ontologies in the era of large language models – a perspective. Applied Ontology, 18(4), 399–407.
6.
PanS.LuoL.WangY.ChenC.WangJ.WuX. (2024). Unifying large language models and knowledge graphs: A roadmap. IEEE Transactions on Knowledge and Data Engineering, 36, 3580–3599.
7.
RussellS. J. (2020). Artificial Intelligence: A Modern Approach (4th ed.). Prentice Hall.
8.
ShimizuC.HitzlerP. (2024). “Accelerating knowledge graph and ontology engineering with large language models.”