Ontolearn-A Framework for Large-scale OWL Class Expression Learning in Python
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| Main Authors: | , , , , , , , , |
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| Format: | Preprint |
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2025
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| _version_ | 1866914090500227072 |
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| author | Demir, Caglar Baci, Alkid Kouagou, N'Dah Jean Sieger, Leonie Nora Heindorf, Stefan Bin, Simon Blübaum, Lukas Bigerl, Alexander Ngomo, Axel-Cyrille Ngonga |
| author_facet | Demir, Caglar Baci, Alkid Kouagou, N'Dah Jean Sieger, Leonie Nora Heindorf, Stefan Bin, Simon Blübaum, Lukas Bigerl, Alexander Ngomo, Axel-Cyrille Ngonga |
| contents | In this paper, we present Ontolearn-a framework for learning OWL class expressions over large knowledge graphs. Ontolearn contains efficient implementations of recent stateof-the-art symbolic and neuro-symbolic class expression learners including EvoLearner and DRILL. A learned OWL class expression can be used to classify instances in the knowledge graph. Furthermore, Ontolearn integrates a verbalization module based on an LLM to translate complex OWL class expressions into natural language sentences. By mapping OWL class expressions into respective SPARQL queries, Ontolearn can be easily used to operate over a remote triplestore. The source code of Ontolearn is available at https://github.com/dice-group/Ontolearn. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2510_11561 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Ontolearn-A Framework for Large-scale OWL Class Expression Learning in Python Demir, Caglar Baci, Alkid Kouagou, N'Dah Jean Sieger, Leonie Nora Heindorf, Stefan Bin, Simon Blübaum, Lukas Bigerl, Alexander Ngomo, Axel-Cyrille Ngonga Machine Learning Symbolic Computation In this paper, we present Ontolearn-a framework for learning OWL class expressions over large knowledge graphs. Ontolearn contains efficient implementations of recent stateof-the-art symbolic and neuro-symbolic class expression learners including EvoLearner and DRILL. A learned OWL class expression can be used to classify instances in the knowledge graph. Furthermore, Ontolearn integrates a verbalization module based on an LLM to translate complex OWL class expressions into natural language sentences. By mapping OWL class expressions into respective SPARQL queries, Ontolearn can be easily used to operate over a remote triplestore. The source code of Ontolearn is available at https://github.com/dice-group/Ontolearn. |
| title | Ontolearn-A Framework for Large-scale OWL Class Expression Learning in Python |
| topic | Machine Learning Symbolic Computation |
| url | https://arxiv.org/abs/2510.11561 |