§3 · Lane 1 — Rules-as-Code / Law-as-Code
Transforming Legal Texts into Computational Logic the 2026 frontier, validated in a ministry deployment
Bertl, Price, Draheim (2026) · IJCCE 7
Bibliographic data
- Title
- Transforming legal texts into computational logic: Enhancing next generation public sector automation through explainable AI decision support (2026)
- Authors / Issuing body
- Markus Bertl (Unisys / WU Vienna), Simon Price (Bristol), Dirk Draheim (Tallinn University of Technology)
- Venue / Publisher
- International Journal of Cognitive Computing in Engineering 7 (2026) 40-57
- Year
- 2026
- Designation
- Academic
- Licence
- Refer to publisher for full licence terms.
- Canonical link
- https://doi.org/10.1016/j.ijcce.2025.07.003
How to cite
Bertl, Price, Draheim (2026). Transforming legal texts into computational logic: Enhancing next generation public sector automation through explainable AI decision support (2026). International Journal of Cognitive Computing in Engineering 7 (2026) 40-57. https://doi.org/10.1016/j.ijcce.2025.07.003.
Prolog + NLP + XAI pipeline for extracting executable rules from legal text, validated on the Austrian Study Funding Act at the Austrian Ministry of Finance; outlines a path to integrating LLMs into the rule-extraction pipeline while preserving traceability and explainability.
Why it matters for NETEVO
The 2026 frontier. Bertl, Price and Draheim present a peer-reviewed Prolog + NLP + XAI pipeline for extracting executable rules from legal text, validated on the Austrian Study Funding Act in a real deployment at the Austrian Ministry of Finance — demonstrated practice, not vendor speculation. The paper outlines a path to integrating LLMs into the rule-extraction pipeline while preserving traceability and explainability, and quotes the OECD's five benefits of coded rules — Consistency, Agility, Improved Policy Outcomes, Digital Optimisation, Scrutiny of Rules — a concise framework for assessing what an organisation gains when its rules are expressed as executable logic.
Where NETEVO applies this
- Agent Infrastructure Whitepaper — agent-readable policy citation extension
- Architectural AI Leverage Insight — 2026 frontier evidence of architectural AI in public-sector deployment
Who acts on this
Reading this usually means something has forced the question — a listing, an audit finding, a procurement questionnaire, a regulator's letter. The role pages below set out what NETEVO does about it, including where we would tell you not to engage.