MAUD (Merger Agreement Dataset)
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A MAUD (Merger Agreement Dataset) is a annotated legal dataset that consists of a collection of merger agreements with detailed expert annotations.
- Context:
- It can (typically) provide over 47,000 labels across 152 merger agreements.
- It can (typically) be utilized to identify 92 questions in each agreement, which are aligned with the standards of the 2021 American Bar Association (ABA) Public Target Deal Points Study.
- It can (often) support Natural Language Processing (NLP) research and development focused on legal contract review, by providing a rich corpus for the training and evaluation of Machine Learning models.
- It can be curated and maintained by The Atticus Project, Inc. (demonstrating an initiative to bridge the gap between legal expertise and AI tech).
- ...
- Example(s):
- MAUD v1 with 47,000+ labels in 152 merger agreements.
- ...
- Counter-Example(s):
- CUAD (Contract Understanding Atticus Dataset), which focuses on commercial legal contracts.
- Legal Judgment Prediction Dataset, which is aimed at predicting the outcome of legal cases based on the facts and legal arguments presented.
- See: Dataset, Natural Language Processing, Machine Learning in Legal Tech, Legal Document Analysis.
References
2024
- https://github.com/TheAtticusProject/maud
- QUOTE: This repository contains code for the Merger Agreement Understanding Dataset (MAUD), a dataset for merger agreement review curated by the Atticus Project and used in the 2021 American Bar Association Public Target Deal Points Study.
2023
- (Savelka, 2023) ⇒ Jaromir Savelka. (2023). “Unlocking Practical Applications in Legal Domain: Evaluation of Gpt for Zero-shot Semantic Annotation of Legal Texts.” In: Proceedings of the Nineteenth International Conference on Artificial Intelligence and Law. DOI:10.1145/3594536.3595161
- QUOTE: ... … selected semantic types from the Contract Understanding Atticus Dataset (CUAD) [16]. Wang et al. assembled and released the Merger Agreement Understanding Dataset (MAUD) [37]. …
2023
- (The Atticus Project et al., 2023) ⇒ The Atticus Project, Inc. (2023). “Merger Agreement Understanding Dataset (MAUD): An Expert-Annotated Legal NLP Dataset for Merger Agreement Understanding.” In: [1](https://www.atticusprojectai.org/maud)
- QUOTE: "Merger Agreement Understanding Dataset (MAUD) v1 is a corpus of 47,000+ labels in 152 merger agreements that have been manually labeled under the supervision of experienced lawyers to identify 92 questions in each agreement used by the 2021 American Bar Association (ABA) Public Target Deal Points Study."
2023
- (Wang, Scardigli et al., 2023) ⇒ Steven H. Wang, Antoine Scardigli, Leonard Tang, Wei Chen, Dimitry Levkin, Anya Chen, Spencer Ball, Thomas Woodside, Oliver Zhang, and Dan Hendrycks. (2023). “Maud: An Expert-annotated Legal Nlp Dataset for Merger Agreement Understanding.” arXiv preprint arXiv:2301.00876