用AI结构化提示框架，让人身伤害赔偿更公平透明
Soppia: A Structured Prompting Framework for the Proportional Assessment of Non-Pecuniary Damages in Personal Injury Cases
- 构建结构化提示系统，按法定12项标准逐项评估
- 确保补偿与伤情程度成比例，提升判决一致性
- 适合法律AI、司法辅助系统开发者参考
在人身伤害案件中，非财产损害赔偿的量化面临多重异质权重标准的复杂性，常导致判决不一致。本文提出Soppia（System for Ordered Proportional and Pondered Intelligent Assessment），一个基于先进AI的结构化提示框架，旨在协助法律从业者系统化处理此类复杂性。以巴西《劳动法典》（CLT）第223-G条规定的12项非财产损害评估标准为案例，Soppia将模糊的法律指令转化为可复制、可解释且透明的分析流程，实现对各因素的全面平衡考量，确保赔偿金额真实反映立法意图。该框架显著提升了判决的可预测性与一致性，适用于多准则法律场景，推动规范解释与计算推理的融合，助力可审计法律AI的发展。
原文摘要 · Abstract (English)
Applying complex legal rules characterized by multiple, heterogeneously weighted criteria presents a fundamental challenge in judicial decision-making, often hindering the consistent realization of legislative intent. This challenge is particularly evident in the quantification of non-pecuniary damages in personal injury cases. This paper introduces Soppia, a structured prompting framework designed to assist legal professionals in navigating this complexity. By leveraging advanced AI, the system ensures a comprehensive and balanced analysis of all stipulated criteria, fulfilling the legislator's intent that compensation be determined through a holistic assessment of each case. Using the twelve criteria for non-pecuniary damages established in the Brazilian CLT (Art. 223-G) as a case study, we demonstrate how Soppia (System for Ordered Proportional and Pondered Intelligent Assessment) operationalizes nuanced legal commands into a practical, replicable, and transparent methodology. The framework enhances consistency and predictability while providing a versatile and explainable tool adaptable across multi-criteria legal contexts, bridging normative interpretation and computational reasoning toward auditable legal AI.
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