@inproceedings{nair-etal-2018-towards,
    title = "Towards Automated Extraction of Business Constraints from Unstructured Regulatory Text",
    author = "Nair, Rahul  and
      Levacher, Killian  and
      Stephenson, Martin",
    editor = "Zhao, Dongyan",
    booktitle = "Proceedings of the 27th International Conference on Computational Linguistics: System Demonstrations",
    month = aug,
    year = "2018",
    address = "Santa Fe, New Mexico",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/jlcl-multiple-ingestion/C18-2034/",
    pages = "157--160",
    abstract = "Large organizations spend considerable resources in reviewing regulations and ensuring that their business processes are compliant with the law. To make compliance workflows more efficient and responsive, we present a system for machine-driven annotations of legal documents. A set of natural language processing pipelines are designed and aimed at addressing some key questions in this domain: (a) is this (new) regulation relevant for me? (b) what set of requirements does this law impose?, and (c) what is the regulatory intent of a law? The system is currently undergoing user trials within our organization."
}