TL;DR
JUDGEBERT is a new evaluation metric for assessing legal meaning preservation in French legal text simplification, demonstrating high correlation with human judgment and passing key sanity checks.
Contribution
The paper introduces JUDGEBERT, a novel metric specifically designed for legal text simplification, along with the FrJUDGE dataset for evaluation.
Findings
JUDGEBERT correlates better with human judgments than existing metrics.
It passes sanity checks for identical and unrelated sentence pairs.
Potential to improve legal NLP applications for accuracy and accessibility.
Abstract
Simplifying text while preserving its meaning is a complex yet essential task, especially in sensitive domain applications like legal texts. When applied to a specialized field, like the legal domain, preservation differs significantly from its role in regular texts. This paper introduces FrJUDGE, a new dataset to assess legal meaning preservation between two legal texts. It also introduces JUDGEBERT, a novel evaluation metric designed to assess legal meaning preservation in French legal text simplification. JUDGEBERT demonstrates a superior correlation with human judgment compared to existing metrics. It also passes two crucial sanity checks, while other metrics did not: For two identical sentences, it always returns a score of 100%; on the other hand, it returns 0% for two unrelated sentences. Our findings highlight its potential to transform legal NLP applications, ensuring accuracy…
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