Guidelines for the Annotation and Visualization of Legal Argumentation Structures in Chinese Judicial Decisions
arXiv:2603.05171v2 Announce Type: replace Abstract: This Guideline presents a systematic and operationalizable annotation framework for representing legal argumentation structures in judicial decisions. Grounded in theories of legal reasoning and argumentation, the framework aims to reveal the logical organization of judicial reasoning and provide a reliable foundation for computational analysis. At the element level, the Guideline distinguishes between the non-propositional layer and the propositional layer. The non-propositional layer consists of two elements: Issue and Non-argumentative Com
The increasing sophistication of AI models and the critical need for explainable AI in legal domains are driving the development of structured argumentation frameworks.
This development is crucial for leveraging AI in high-stakes legal contexts, enabling better judicial decision-making transparency and computational analysis of legal reasoning.
The ability to systematically annotate and visualize legal arguments in judicial decisions will accelerate the application of AI in legal tech, potentially transforming legal research and dispute resolution processes.
- · Legal tech companies
- · Judiciaries in common law systems
- · AI researchers in NLP
- · Legal practitioners
- · Legal research services reliant on manual review
- · Jurisdictions resistant to AI integration
Improved efficiency and accuracy in legal document analysis and research.
Enhanced public trust in judicial systems due to greater transparency and consistency in legal reasoning.
The development of AI systems capable of predicting judicial outcomes or drafting legal arguments with high precision, fundamentally reshaping the legal profession.
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Read at arXiv cs.CL