DSTI at LLMs4OL 2024 Task A: Intrinsic Versus Extrinsic Knowledge for Type Classification
Applications on WordNet and GeoNames Datasets
DOI:
https://doi.org/10.52825/ocp.v4i.2492Keywords:
Large Language Models, Ontology Learning, Semantic Web, Knowledge Representation, Semantic PrimesAbstract
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's intrinsic knowledge. We report our findings on the Large Language Models for Ontology Learning (LLMs4OL) 2024 challenge.
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Copyright (c) 2024 Hanna Abi Akl
This work is licensed under a Creative Commons Attribution 4.0 International License.
