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        <title>Towards Automated Extraction of Business Constraints from Unstructured Regulatory Text</title>
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        <namePart type="given">Rahul</namePart>
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    <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.</abstract>
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%0 Conference Proceedings
%T Towards Automated Extraction of Business Constraints from Unstructured Regulatory Text
%A Nair, Rahul
%A Levacher, Killian
%A Stephenson, Martin
%Y Zhao, Dongyan
%S Proceedings of the 27th International Conference on Computational Linguistics: System Demonstrations
%D 2018
%8 August
%I Association for Computational Linguistics
%C Santa Fe, New Mexico
%F nair-etal-2018-towards
%X 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.
%U https://aclanthology.org/C18-2034
%P 157-160

Markdown (Informal)

[Towards Automated Extraction of Business Constraints from Unstructured Regulatory Text](https://aclanthology.org/C18-2034) (Nair et al., COLING 2018)

• Towards Automated Extraction of Business Constraints from Unstructured Regulatory Text (Nair et al., COLING 2018)

ACL

• Rahul Nair, Killian Levacher, and Martin Stephenson. 2018. Towards Automated Extraction of Business Constraints from Unstructured Regulatory Text. In Proceedings of the 27th International Conference on Computational Linguistics: System Demonstrations, pages 157–160, Santa Fe, New Mexico. Association for Computational Linguistics.