2024 TextSimplificationSystemforLega
- (Justo & Recario, 2024) ⇒ Jenel M Justo, and Reginald Neil C Recario. (2024). “Text Simplification System for Legal Contract Review.” In: Future of Information and Communication Conference. doi:10.1007/978-3-031-53960-2_8
Subject Headings: Text Simplification, Legal-Domain Fine-Tuned LLM, Legal-Domain LLM, LEGAL-BERT, LEGAL-BERT-Contracts.
Notes
- The paper explores the integration of automated contract review with text simplification to improve the readability of legal contracts and make them more accessible to non-experts. This process involves NLP techniques and machine learning models specifically tuned for the legal domain.
- The paper leverages a language model fine-tuned on legal data to extract salient clauses from contracts. These clauses are then simplified using language models trained on legal documents, highlighting the use of deep learning in legal tech.
- The paper aims to make the complex language of contracts understandable to individuals with a tenth-grade education level, moving away from the traditional requirement of a postgraduate level of comprehension. This goal addresses the widespread issue of legal jargon that can obfuscate the meaning of contracts for the layperson.
- The paper evaluates the performance of the proposed system using various readability metrics, including FKGL, FRE, SMOG, and DC. These metrics help demonstrate improvements in text readability post-simplification, making use of established linguistics and psycholinguistics methods to assess text clarity.
- The paper conducts a human evaluation through a survey with undergraduate students to assess the system's effectiveness in simplifying text in terms of lexical simplicity, syntactic simplicity, grammaticality, and meaning preservation. This approach incorporates qualitative analysis to gauge user perception and satisfaction with the simplified texts.
- The paper finds that the system notably improves the readability of contracts, making them suitable for readers at a ninth to tenth-grade reading level, indicating a significant reduction in text complexity. This outcome highlights the potential for text simplification technologies in broadening access to legal information.
- The paper reports generally positive feedback from human evaluators, suggesting that the system successfully simplifies text while maintaining its grammaticality and meaning to a satisfactory degree. This feedback points to the effectiveness of the system in achieving semantic integrity alongside readability improvement.
- The paper identifies areas for further research and improvement, including the need for algorithmic optimizations and the creation of parallel datasets for supervised learning approaches. This direction suggests future avenues for enhancing the accuracy and efficiency of NLP applications in legal text processing.
- The paper concludes that integrating text simplification with automated contract review has the potential to enhance contract readability, but more research is necessary to refine the simplification process and improve the quality of the output. This conclusion emphasizes the ongoing need for innovation and development in the field of legal informatics and access to justice.
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Abstract
People tend to avoid reading contracts due to their complexity. As such, this research tackles the challenge of improving the accessibility and readability of contracts, which are often lengthy and difficult to understand. This study proposes a system that integrates automated contract review with text simplification. The system leverages a language model fine-tuned on legal data to extract salient clauses from contracts. Complex words are then replaced with simpler alternatives generated by language models trained on legal documents. Moreover, the simplified output is further refined by breaking down the text into shorter sentences based on their semantic hierarchy. Initial results show that the readability of the simplified contracts improved, making them understandable for 10th graders instead of requiring a postgraduate level of education. Human evaluations were generally positive, although the observed improvements were relatively minor. The research concludes that integrating text simplification with automated contract review has the potential to enhance contract readability, but more research is necessary to improve the quality of simplification further.
1 Introduction
2 Review of Related Literature
5 Conclusion and Future Work
References
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| Author | volume | Date Value | title | type | journal | titleUrl | doi | note | year | |
|---|---|---|---|---|---|---|---|---|---|---|
| 2024 TextSimplificationSystemforLega | Jenel M Justo Reginald Neil C Recario | Text Simplification System for Legal Contract Review | 10.1007/978-3-031-53960-2_8 | 2024 |