# Generating Intelligible Plumitifs Descriptions: Use Case Application with Ethical Considerations

arXiv: https://arxiv.org/abs/2011.12183 · HTML: https://mlsanity.com/paper/2011.12183/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 24 Nov 2020.

## Built on by (most cited first, 5 of 5)

- [Underreporting of errors in NLG output, and what to do about it](https://mlsanity.com/paper/2108.01182/) (2021)
- [Quebec Automobile Insurance Question-Answering With Retrieval-Augmented Generation](https://mlsanity.com/paper/2410.09623/) (2024)
- [RISC: Generating Realistic Synthetic Bilingual Insurance Contract](https://mlsanity.com/paper/2304.04212/) (2023)
- [Benchmarking Large Language Models for Quebec Insurance: From Closed-Book to Retrieval-Augmented Generation](https://mlsanity.com/paper/2603.07825/) (2026)
- [A Human-Centric Evaluation of a Retrieval-Augmented Generation System for Explaining Quebec Insurance Contracts](https://mlsanity.com/paper/2607.15963/) (2026)

## Abstract (arXiv)

Plumitifs (dockets) were initially a tool for law clerks. Nowadays, they are used as summaries presenting all the steps of a judicial case. Information concerning parties' identity, jurisdiction in charge of administering the case, and some information relating to the nature and the course of the preceding are available through plumitifs. They are publicly accessible but barely understandable; they are written using abbreviations and referring to provisions from the Criminal Code of Canada, which makes them hard to reason about. In this paper, we propose a simple yet efficient multi-source language generation architecture that leverages both the plumitif and the Criminal Code's content to generate intelligible plumitifs descriptions. It goes without saying that ethical considerations rise with these sensitive documents made readable and available at scale, legitimate concerns that we address in this paper.