English

DSTI at LLMs4OL 2024 Task A: Intrinsic versus extrinsic knowledge for type classification

Computation and Language 2024-08-27 v1 Artificial Intelligence Machine Learning

Abstract

We introduce semantic towers, an extrinsic knowledge representation method, and compare it to intrinsic knowledge in large language models for ontology learning. Our experiments show a trade-off between performance and semantic grounding for extrinsic knowledge compared to a fine-tuned model intrinsic knowledge. We report our findings on the Large Language Models for Ontology Learning (LLMs4OL) 2024 challenge.

Keywords

Cite

@article{arxiv.2408.14236,
  title  = {DSTI at LLMs4OL 2024 Task A: Intrinsic versus extrinsic knowledge for type classification},
  author = {Hanna Abi Akl},
  journal= {arXiv preprint arXiv:2408.14236},
  year   = {2024}
}

Comments

8 pages, 4 figures, accepted for the LLMs4OL challenge at the International Semantic Web Conference (ISWC) 2024

R2 v1 2026-06-28T18:23:55.170Z