Unsupervised Extraction of Workplace Rights and Duties from Collective Bargaining Agreements

Elliott Ash, Jeff Jacobs, Bentley MacLeod, Suresh Naidu, Dominik Stammbach

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Scopus citations

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.

Original languageEnglish (US)
Title of host publicationProceedings - 20th IEEE International Conference on Data Mining Workshops, ICDMW 2020
EditorsGiuseppe Di Fatta, Victor Sheng, Alfredo Cuzzocrea, Carlo Zaniolo, Xindong Wu
PublisherIEEE Computer Society
Pages766-774
Number of pages9
ISBN (Electronic)9781728190129
DOIs
StatePublished - Nov 2020
Externally publishedYes
Event20th IEEE International Conference on Data Mining Workshops, ICDMW 2020 - Virtual, Sorrento, Italy
Duration: Nov 17 2020Nov 20 2020

Publication series

NameIEEE International Conference on Data Mining Workshops, ICDMW
Volume2020-November
ISSN (Print)2375-9232
ISSN (Electronic)2375-9259

Conference

Conference20th IEEE International Conference on Data Mining Workshops, ICDMW 2020
Country/TerritoryItaly
CityVirtual, Sorrento
Period11/17/2011/20/20

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Software

Keywords

  • Information Mining
  • Legal Corpus Analysis
  • Unsupervised Extraction

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