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7 décembre 2023
- handle: 10670/1.j5o5s0
- hal: hal-04516129
- doi: 10.3233/FAIA230972
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info:eu-repo/semantics/altIdentifier/doi/10.3233/FAIA230972
info:eu-repo/semantics/OpenAccess
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Language (New words, slang, etc.) Skills training Authorities (Persons) Experts Freshwater turtles Testudinata Terrapins Tortoises Testudines Pleurodira Cryptodira Fresh-water turtles Chelonia (Order) Marine birds Ocean birds Seabirds Papers Article Frenchmen (French people) Pattern Model Environment law Environmental protection--Law and legislation Environmental control Environmental quality--Law and legislation Intellectronics AI (Artificial intelligence) Artificial thinking Electronic brains Intelligent machines Intelligence, Artificial Machine intelligence Thinking, Artificial IACiter ce document
Youssef Al Mouatamid et al., « Assessing Ocean’s Legal Protection Using AI: A New Dataset and a BERT-Based Classifier », HAL-SHS : droit et gestion, ID : 10.3233/FAIA230972
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This paper aims to address the challenge of using artificial intelligence for empirical legal studies. We introduce a new annotated dataset on French marine environmental law dealing with definitions, bans, sanctions, and controls on living (turtles and seabirds) and non-living (plastic bags and straws) subjects. The annotation has been produced by law students and validated by a legal expert. Based on the developed dataset, we train a CamemBERT-based classifier which accurately predicts the class of a given legal article according to the pre-defined classes within the dataset we have created. The proposed training set and the resulting trained model provide a better interpretation and accessibility of legal texts to specialists and the general public, based on findings from legal studies and on natural language processing techniques.