DaSeLab at LLMs4OL 2024 Task A: Towards Term Typing in Ontology Learning

Authors

DOI:

https://doi.org/10.52825/ocp.v4i.2489

Keywords:

LLM, Term Typing, Ontology Learning

Abstract

The report presents the evaluation results of our approach in the LLM4OL Challenge, where we fine-tuned GPT-3.5 for Task A (Term Typing) across three different datasets. Our approach demonstrated consistent and robust performance during few- shot testing, achieving top rankings in several datasets and sub-datasets, proving the potential of fine-tuning LLMs for ontology creation tasks.

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References

[1] H. B. Giglou, J. D’Souza, and S. Auer, “LLMs4OL: Large language models for ontology learning,” in The Semantic Web – ISWC 2023 – 22nd International Semantic Web Conference, Athens, Greece, November 6-10, 2023, Proceedings, Part I, T. R. Payne, V. Presutti, G. Qi, et al., Eds., ser. Lecture Notes in Computer Science, vol. 14265, Springer, 2023, pp. 408–427.

[2] P. Buitelaar, P. Cimiano, and B. Magnini, Ontology Learning from Text: Methods, Evaluation and Applications (Frontiers in Artificial Intelligence and Applications). IOS Press, Amsterdam, 2005, vol. 123.

[3] H. Babaei Giglou, J. D’Souza, and S. Auer, “Llms4ol 2024 overview: The 1st large language models for ontology learning challenge,” Open Conference Proceedings, vol. 4, Oct. 2024.

[4] H. Babaei Giglou, J. D’Souza, S. Sadruddin, and S. Auer, “Llms4ol 2024 datasets: Toward ontology learning with large language models,” Open Conference Proceedings, vol. 4, Oct. 2024.

[5] G. A. Miller, “WordNet: A lexical database for english,” Communications of the ACM, vol. 38, no. 11, pp. 39–41, 1995.

[6] GeoNames, Geonames geographical database, http://www.geonames.org/, 2024.

[7] O. Bodenreider, “The Unified Medical Language System (UMLS): Integrating biomedical terminology,” Nucleic acids research, vol. 32, no. suppl 1, pp. D267–D270, 2004.

[8] J. Wei, M. Bosma, V. Y. Zhao, et al., “Finetuned language models are zero-shot learners,” in The Tenth International Conference on Learning Representations, ICLR 2022, Virtual Event, April 25-29, 2022, OpenReview.net, 2022. [Online]. Available: https://openreview.net/forum?id=gEZrGCozdqR.

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Published

2024-10-02

How to Cite

Barua, A., Saki Norouzi, S., & Hitzler, P. (2024). DaSeLab at LLMs4OL 2024 Task A: Towards Term Typing in Ontology Learning. Open Conference Proceedings, 4, 77–84. https://doi.org/10.52825/ocp.v4i.2489

Conference Proceedings Volume

Section

LLMs4OL 2024 Task Participant Papers

Funding data