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

The study compares semantic towers, an extrinsic knowledge representation method, to intrinsic knowledge in large language models for ontology learning, highlighting performance trade-offs and semantic grounding.

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Year
2024
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arXiv 2024
ArXiv
arxiv.org/abs/2408.14236
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arxiv.org/abs/2408.14236
Authors
1
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arxiv.org/abs/2408.14236ARXIV-DEFAULT
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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.

Authors

1
Hanna Abi Akl