@inproceedings{b81289a014024f1fa1b9067112fad6be,
title = "Unsupervised Extraction of Workplace Rights and Duties from Collective Bargaining Agreements",
abstract = "This paper describes an unsupervised legal document parser which performs a decomposition of labor union contracts into discrete assignments of rights and duties among agents of interest. We use insights from deontic logic applied to modal categories and other linguistic patterns to generate topic-specific measures of relative legal authority. We illustrate the consistency and efficiency of the pipeline by applying it to a large corpus of 35K contracts and validating the resulting outputs.",
keywords = "Information Mining, Legal Corpus Analysis, Unsupervised Extraction",
author = "Elliott Ash and Jeff Jacobs and Bentley MacLeod and Suresh Naidu and Dominik Stammbach",
note = "Publisher Copyright: {\textcopyright} 2020 IEEE.; 20th IEEE International Conference on Data Mining Workshops, ICDMW 2020 ; Conference date: 17-11-2020 Through 20-11-2020",
year = "2020",
month = nov,
doi = "10.1109/ICDMW51313.2020.00112",
language = "English (US)",
series = "IEEE International Conference on Data Mining Workshops, ICDMW",
publisher = "IEEE Computer Society",
pages = "766--774",
editor = "{Di Fatta}, Giuseppe and Victor Sheng and Alfredo Cuzzocrea and Carlo Zaniolo and Xindong Wu",
booktitle = "Proceedings - 20th IEEE International Conference on Data Mining Workshops, ICDMW 2020",
address = "United States",
}