We introduce a computational method for identifying delegating and constraining provisions in European Union (EU) laws. Leveraging the syntactic structures employed by legislators, we developed a set of extraction rules applied through a custom-built computational linguistics pipeline. We run through the pipeline more than 600,000 legal sentences that we extracted from 9319 laws adopted between 1958 and 2019. The application performs very well vis-á-vis human annotation and outperforms transformer models. The produced patterns of authority delegation and constraint resonate with our knowledge of the policymaking and history of the EU. Our approach provides valuable insights for designing transparent and adaptable rule-based computational linguistic methods of legal text analysis. We also release the comprehensively annotated dataset and the fine-tuned transformer models developed for this task.
Identifying delegation and constraints in legislative texts: A computational method applied to the European Union / F. Franchino, M. Migliorati, G. Pagano, V. Vignoli. - In: EUROPEAN UNION POLITICS. - ISSN 1465-1165. - (2026). [Epub ahead of print] [10.1177/14651165261423778]
Identifying delegation and constraints in legislative texts: A computational method applied to the European Union
F. Franchino
Primo
;M. Migliorati;G. Pagano;V. VignoliUltimo
2026
Abstract
We introduce a computational method for identifying delegating and constraining provisions in European Union (EU) laws. Leveraging the syntactic structures employed by legislators, we developed a set of extraction rules applied through a custom-built computational linguistics pipeline. We run through the pipeline more than 600,000 legal sentences that we extracted from 9319 laws adopted between 1958 and 2019. The application performs very well vis-á-vis human annotation and outperforms transformer models. The produced patterns of authority delegation and constraint resonate with our knowledge of the policymaking and history of the EU. Our approach provides valuable insights for designing transparent and adaptable rule-based computational linguistic methods of legal text analysis. We also release the comprehensively annotated dataset and the fine-tuned transformer models developed for this task.| File | Dimensione | Formato | |
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