From Instructions to ODRL Usage Policies: An Ontology Guided Approach
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Abstract (arXiv)
This study presents an approach that uses large language models such as GPT-4 to generate usage policies in the W3C Open Digital Rights Language ODRL automatically from natural language instructions. Our approach uses the ODRL ontology and its documentation as a central part of the prompt. Our research hypothesis is that a curated version of existing ontology documentation will better guide policy generation. We present various heuristics for adapting the ODRL ontology and its documentation to guide an end-to-end KG construction process. We evaluate our approach in the context of dataspaces, i.e., distributed infrastructures for trustworthy data exchange between multiple participating organizations for the cultural domain. We created a benchmark consisting of 12 use cases of varying complexity. Our evaluation shows excellent results with up to 91.95% accuracy in the resulting knowledge graph.
Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 9 of its 17 references that are in the map. First posted on arXiv 3 Jun 2025.
Builds on
9 of 17 references.
References · 9
- 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
- 2021On the Opportunities and Risks of Foundation Modelscited by 3,961
- 2020KG-BART: Knowledge Graph-Augmented BART for Generative Commonsense Reasoningcited by 106
- 2023LLMs for Knowledge Graph Construction and Reasoning: Recent Capabilities and Future Opportunitiescited by 97
- 2022Generative Knowledge Graph Construction: A Reviewcited by 49
- 2020Neural Entity Linking: A Survey of Models Based on Deep Learningcited by 46
- 2023PiVe: Prompting with Iterative Verification Improving Graph-based Generative Capability of LLMscited by 44
- 2023Construction of Knowledge Graphs: State and Challengescited by 12
- 2023Policy Patterns for Usage Control in Data Spacescited by 4
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Citing papers per year: 2025: 1; 2026: 1.
2 papers.