Ontology Matching with Knowledge Retrieval and Large Language Models (ISWC 2025)
We provide the minimum environment requirements to support the running of our project. This means there can be a slight difference depending on the actual automatic dependency-solving result of different systems.
Should one be interested in reproducing a certain method, please look up the corresponding requirement file and install listed packages accordingly.
pip install --upgrade pip
pip install -r requirements.txt
Currently, our method features 6 datasets (Mouse-Human, NCIT-DOID, Nell-DBpedia, YAGO-Wikidata, ENVO-SWEET, MI-MatOnto). Please provide the downloaded datasets in experiments/dataset/.
Our paper features models provided by TogetherAI's API. So please supply your TogetherAI access token in the .env file.
We supply a sample script to run an experiment on ENVO-SWEET track with Llama-3.3-70B in the scripts/run_envo_sweet.sh. We provided a dynamic results saving to the script so that the results files will be automatically updated with the newest predicted pairs.
The final results can be find under 2 folders. For example, after running the ENVO-SWEET experiment, you can find the results under results/baseline/envo_sweet for accepted alignments and reviews/baseline/envo_sweet for reviews needed by experts
Should you want to add a new evaluation, you may consider adding an experiments/configs/method/<llm> folder for the LLMs you want to evaluated on, and supply corresponding .jsonl for the dataset and the configurations you want to evaluate on. For a new dataset, add a folder experiments/configs/dataset/<dataset>.json to point towards the dataset you wish to add.
The OAEI datasets will be stored at experiments/datasets/OAEI/<track>/<dataset>. If you want to test multiple times, we advised to cache the query results and provide a path to it at experiments/configs/dictionary.json.
KROMA is currently undergoing maintenance to resolve dependency issues and ensure a seamless release. The final version will be available soon.
Should you need to refer to this work or find our codebase useful, please consider citing our work as:
@inproceedings{nguyen_2025_kroma,
title={KROMA: Knowledge Retrieval Ontology Matching using Large Language Models},
author={Lam Nguyen and Erika Barcelos and Roger French and Yinghui Wu},
journal={Proceedings of the 24th International Semantic Web Conference Research Track},
year={2025},
}