We introduce OntoChat, a framework for conversational ontology engineering that supports requirement elicitation, analysis, and testing. By interacting with a conversational agent, users can steer the creation of use cases and the extraction of competency questions, while receiving computational support to analyse the overall requirements and test early versions of the resulting ontologies.
If you would like to deploy this demo locally,
- Create a python environment and install the requirements using
pip install -r requirements.txt. - Run
app.py.
OntoChat has been hosted in HF Spaces at: https://huggingface.co/spaces/b289zhan/OntoChat.
- A first evaluation of the framework was performed to reproduce the engineering efforts behind the Music Meta Ontology.
- Improve the verbaliser (classes, named entities, and relations might be messy in some cases)
- Optimize clustering visualization (maybe only keep LLM lcustering)
- Add flagging, e.g.,
HuggingFaceDatasetSaver
@article{zhang2024ontochat,
title={OntoChat: a Framework for Conversational Ontology Engineering using Language Models},
author={Zhang, Bohui and Carriero, Valentina Anita and Schreiberhuber, Katrin and Tsaneva, Stefani and Gonz{\'a}lez, Luc{\'\i}a S{\'a}nchez and Kim, Jongmo and de Berardinis, Jacopo},
journal={arXiv preprint arXiv:2403.05921},
year={2024}
}
This project acknoledges Polifonia, and has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 101004746. We also thank all the evaluators that contributed feedback on the effectiveness of the tool and provided their experience of use. We also thank all the evaluators for contributing to the project.
Copyright 2024 OntoChat maintainers
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