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An automated framework for detection and resolution of cross references in legal texts

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Abstract

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.

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Notes

  1. http://www.legilux.public.lu.

  2. http://www.legifrance.gouv.fr.

  3. http://www.e-laws.gov.on.ca.

  4. http://www.belgielex.be/en/index.html.

  5. The discrepancy between the number of CREs in the French and English editions of PHIPA is due to differences in the wording of the provisions. For example, the statement “(3) Despite clause (1) (b), the person described in that clause...” from the English edition of PHIPA contains two CREs, namely “clause (1) (b)” and “that clause,” whereas the corresponding statement in the French edition, “(3) Malgr l’alin a (1) b), la personne qui y est vis e,” contains only one CRE.

  6. https://lexum.com/en/resources/lexhub.

  7. https://addons.mozilla.org/En-uS/firefox/addon/jureeka-6636/.

  8. http://www.lexisnexis.ca/.

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Acknowledgments

Financial support for this work was provided by Luxembourg’s National Centre of Information Technologies (CTIE) and Luxembourg’s National Research Fund (FNR) under grant number FNR/P10/03. We are grateful to members of Luxembourg Inland Revenue Office (ACD) and CTIE, particularly, Thierry Prommenschenkel, Ludwig Balmer, Marc Blau, and Michael Masseroni for sharing their valuable knowledge and insights with us. We thank the anonymous reviewers of the RE Journal and the RE’14 conference for their insightful comments which helped us improve this article.

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  1. Interdisciplinary Centre for Security, Reliability and Trust (SnT), University of Luxembourg, 4 rue Alphonse Weicker, 2721, Luxembourg, Luxembourg

    Nicolas Sannier, Morayo Adedjouma, Mehrdad Sabetzadeh & Lionel Briand

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  1. Nicolas Sannier
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  2. Morayo Adedjouma
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  3. Mehrdad Sabetzadeh
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  4. Lionel Briand
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Correspondence to Mehrdad Sabetzadeh.

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Sannier, N., Adedjouma, M., Sabetzadeh, M. et al. An automated framework for detection and resolution of cross references in legal texts. Requirements Eng 22, 215–237 (2017). https://doi.org/10.1007/s00766-015-0241-3

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