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Effectiveness in Retrieving Legal Precedents
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Orientador(es)
Resumo(s)
Automating the retrieval of legal precedents is crucial for streamlining legal research and upholding the principle of stare decisis. With the exponential growth of legal data, traditional methods fail to cope with the demands for efficiency and accuracy. Recent advancements in Artificial Intelligence (AI), particularly in Natural Language Processing (NLP) and Machine Learning (ML), offer promising solutions. However, challenges remain, such as the need for high computational power, costs, scalability, and the lack of universally applicable methodologies across various jurisdictions. This study explores the potential of combining legal text summarization techniques with cutting-edge language models, such as OpenAI's ADA, to develop an efficient and scalable system for legal precedent retrieval. The focus is on balancing performance and resource consumption, addressing the ongoing need for cost-effective yet reliable AI-driven solutions in the legal domain. We assessed different methods for summarizing legal text by extracting parts such as person, organization, place, time, statutes, and jurisprudence. The study also compared summaries based on concepts (nouns) and relations (verbs). Additionally, this research compared the performance of text embeddings created from models trained with general-purpose text and legal documents.
Descrição
Mentzingen, H., António, N., & Bação, F. (2024). Effectiveness in Retrieving Legal Precedents: Exploring Text Summarization and Cutting-Edge Language Models Toward a Cost-Efficient Approach [poster]. 1. Poster session presented at Data Research Meetup by MagIC, Lisbon, Portugal. --- The study utilized data from the Superintendency of Private Insurance (SUSEP), an autonomous entity within the Ministry of Finance of Brazil that regulates and oversees insurance brokers and companies. The authors acknowledge SUSEP for supporting and providing data for this work.
This work was supported by national funds through FCT (Fundação para a Ciência
e a Tecnologia), under the project - UIDB/04152/2020 (DOI:
10.54499/UIDB/04152/2020) - Centro de Investigação em Gestão de Informação
(MagIC)/NOVA IMS).
Palavras-chave
SDG 16 - Peace, Justice and Strong Institutions