Unlocking Legal Litigation Analysis with chatGPT

A Step-by-Step Tutorial

Walid Amamou

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The legal field is notorious for its vast amounts of complex and unstructured textual data. Legal professionals spend countless hours poring over legal documents, searching for relevant information, and extracting key insights to build persuasive arguments. However, this traditional approach to legal analysis is time-consuming, labor-intensive, and often prone to human error. Law firms typically employs junior analysts to sift through relevant and irrelevant documents, annotate relevant sections and information. A process that can take months, significantly delaying the completion of the case.

In recent years, the rapid advancement of NLP techniques, combined with the recent advent of large language models such as OpenAI’s GPT-4, has paved the way for more efficient and accurate legal analysis. These sophisticated models can not only extract named entities, such as people, organizations, locations, events, laws, etc. but also generate concise summaries and identify critical facts buried within extensive legal documents. By automating these time-consuming tasks, legal professionals can now focus on higher-level strategic analysis and decision-making.

Moreover, by embedding the enriched legal documents into a high-dimensional vector space, additional analysis can be performed. Similarity analysis allows for the comparison of multiple cases based on their facts, revealing patterns and relationships that might otherwise be missed. Clustering techniques can group similar cases together, aiding in the identification of precedents or relevant legal arguments. Last but not least, one can apply predictive analytics to predict the outcome of the case based on its facts and entities. The possibilities are limitless.

In this tutorial, we are going to extract relevant information from environmental litigation cases such as named entities, facts presented and summarization using the LLM GPT-3.5-Tubo.

Dataset

During the litigation process, an enormous amount of effort is put into analyzing previous cases searching for evidence that will support the current case. Traditional keyword search with Ctrl + F is not enough to yield accurate and complete results since it requires knowing the…

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Walid Amamou

Founder of UBIAI, annotation tool for NLP applications| PhD in Physics.