TY - JOUR
T1 - An automated framework for detection and resolution of cross references in legal texts
AU - Sannier, Nicolas
AU - Adedjouma, Morayo
AU - Sabetzadeh, Mehrdad
AU - Briand, Lionel
N1 - Publisher Copyright:
© 2015, Springer-Verlag London.
PY - 2017/6/1
Y1 - 2017/6/1
N2 - When identifying and elaborating compliance requirements, analysts need to follow the cross references in legal texts and consider the additional information in the cited provisions. Enabling easier navigation and handling of cross references requires automated support for the detection of the natural language expressions used in cross references, the interpretation of cross references in their context, and the linkage of cross references to the targeted provisions. In this article, we propose an approach and tool support for automated detection and resolution of cross references. The approach leverages the structure of legal texts, formalized into a schema, and a set of natural language patterns for legal cross reference expressions. These patterns were developed based on an investigation of Luxembourg’s legislation, written in French. To build confidence about their applicability beyond the context where they were observed, these patterns were validated against the Personal Health Information Protection Act (PHIPA) by the Government of Ontario, Canada, written in both French and English. We report on an empirical evaluation where we assess the accuracy and scalability of our framework over several Luxembourgish legislative texts as well as PHIPA.
AB - When identifying and elaborating compliance requirements, analysts need to follow the cross references in legal texts and consider the additional information in the cited provisions. Enabling easier navigation and handling of cross references requires automated support for the detection of the natural language expressions used in cross references, the interpretation of cross references in their context, and the linkage of cross references to the targeted provisions. In this article, we propose an approach and tool support for automated detection and resolution of cross references. The approach leverages the structure of legal texts, formalized into a schema, and a set of natural language patterns for legal cross reference expressions. These patterns were developed based on an investigation of Luxembourg’s legislation, written in French. To build confidence about their applicability beyond the context where they were observed, these patterns were validated against the Personal Health Information Protection Act (PHIPA) by the Government of Ontario, Canada, written in both French and English. We report on an empirical evaluation where we assess the accuracy and scalability of our framework over several Luxembourgish legislative texts as well as PHIPA.
KW - Conceptual modeling
KW - Cross references
KW - Legal compliance
KW - Natural language processing (NLP)
UR - http://www.scopus.com/inward/record.url?scp=84947427095&partnerID=8YFLogxK
U2 - 10.1007/s00766-015-0241-3
DO - 10.1007/s00766-015-0241-3
M3 - Article
AN - SCOPUS:84947427095
SN - 0947-3602
VL - 22
SP - 215
EP - 237
JO - Requirements Engineering
JF - Requirements Engineering
IS - 2
ER -