# Legal Requirements Analysis

arXiv: https://arxiv.org/abs/2311.13871 · HTML: https://mlsanity.com/paper/2311.13871/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 7 of its 65 references that are in the map.
- First posted on arXiv 23 Nov 2023.

## Builds on (most cited first, 7 of 7)

- [Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks](https://mlsanity.com/paper/1908.10084/) (2019)
- [Stanza: A Python Natural Language Processing Toolkit for Many Human Languages](https://mlsanity.com/paper/2003.07082/) (2020)
- [Multimodal Trajectory Predictions for Autonomous Driving using Deep Convolutional Networks](https://mlsanity.com/paper/1809.10732/) (2018)
- [NLP-based Automated Compliance Checking of Data Processing Agreements against GDPR](https://mlsanity.com/paper/2209.09722/) (2022)
- [An Automated Framework for the Extraction of Semantic Legal Metadata from Legal Texts](https://mlsanity.com/paper/2001.11245/) (2020)
- [AI-enabled Automation for Completeness Checking of Privacy Policies](https://mlsanity.com/paper/2106.05688/) (2021)
- [COREQQA -- A COmpliance REQuirements Understanding using Question Answering Tool](https://mlsanity.com/paper/2206.10233/) (2022)

## Built on by (most cited first, 2 of 2)

- [Engineering the Law-Machine Learning Translation Problem: Developing Legally Aligned Models](https://mlsanity.com/paper/2504.16969/) (2025)
- [Generative Language Models Potential for Requirement Engineering Applications: Insights into Current Strengths and Limitations](https://mlsanity.com/paper/2412.00959/) (2024)

## Abstract (arXiv)

Modern software has been an integral part of everyday activities in many disciplines and application contexts. Introducing intelligent automation by leveraging artificial intelligence (AI) led to break-throughs in many fields. The effectiveness of AI can be attributed to several factors, among which is the increasing availability of data. Regulations such as the general data protection regulation (GDPR) in the European Union (EU) are introduced to ensure the protection of personal data. Software systems that collect, process, or share personal data are subject to compliance with such regulations. Developing compliant software depends heavily on addressing legal requirements stipulated in applicable regulations, a central activity in the requirements engineering (RE) phase of the software development process. RE is concerned with specifying and maintaining requirements of a system-to-be, including legal requirements. Legal agreements which describe the policies organizations implement for processing personal data can provide an additional source to regulations for eliciting legal requirements. In this chapter, we explore a variety of methods for analyzing legal requirements and exemplify them on GDPR. Specifically, we describe possible alternatives for creating machine-analyzable representations from regulations, survey the existing automated means for enabling compliance verification against regulations, and further reflect on the current challenges of legal requirements analysis.