Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
From the project website: https://www.atticusprojectai.org/cuad
Contract Understanding Atticus Dataset (CUAD) v1 is a corpus of more than 13,000 labels in 510 commercial legal contracts that have been manually labeled by The Atticus Project to identify 41 categories of important clauses that lawyers look for when reviewing contracts. We tested CUAD v1 against ten pretrained AI models and published the results on arXiv here.
ReadMe and Datasheet are published here. Code for replicating the results, together with the model trained on CUAD, is published on Github here.
Atticus Open Contract Dataset (AOK)(beta) is a corpus of 5,000+ labels in 200 commercial legal contracts that have been manually labeled by legal experts to identify 40 types of clauses that are important during contract review in connection with corporate transactions, such as mergers and acquisitions, IPO, and corporate financing. AOK Dataset is curated and maintained by The Atticus Project, Inc., a non-profit organization, to support NLP research and development in legal contract review. If you download this dataset, we'd love to know more about you and your project! Please fill out this short form: https://forms.gle/h47GUENTTbBqH39m7. Check out our website at atticusprojectai.org. Update: The expanded 1.0 version of the dataset is available here https://zenodo.org/record/4595826
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Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
From the project website: https://www.atticusprojectai.org/cuad
Contract Understanding Atticus Dataset (CUAD) v1 is a corpus of more than 13,000 labels in 510 commercial legal contracts that have been manually labeled by The Atticus Project to identify 41 categories of important clauses that lawyers look for when reviewing contracts. We tested CUAD v1 against ten pretrained AI models and published the results on arXiv here.
ReadMe and Datasheet are published here. Code for replicating the results, together with the model trained on CUAD, is published on Github here.