Towards Grammatical Tagging for the Legal Language of Cybersecurity
This work addresses the interpretative complexities of legal language for cybersecurity professionals, but it is incremental as it applies existing NLP tools with minor tailoring.
The paper tackled the challenge of interpreting legal language in cybersecurity documents by developing an automated methodology for Part-of-Speech tagging, leveraging NLP tools and manual validation, and demonstrated it on the EU NIS 2 directive to produce the first structured interpretation.
Legal language can be understood as the language typically used by those engaged in the legal profession and, as such, it may come both in spoken or written form. Recent legislation on cybersecurity obviously uses legal language in writing, thus inheriting all its interpretative complications due to the typical abundance of cases and sub-cases as well as to the general richness in detail. This paper faces the challenge of the essential interpretation of the legal language of cybersecurity, namely of the extraction of the essential Parts of Speech (POS) from the legal documents concerning cybersecurity. The challenge is overcome by our methodology for POS tagging of legal language. It leverages state-of-the-art open-source tools for Natural Language Processing (NLP) as well as manual analysis to validate the outcomes of the tools. As a result, the methodology is automated and, arguably, general for any legal language following minor tailoring of the preprocessing step. It is demonstrated over the most relevant EU legislation on cybersecurity, namely on the NIS 2 directive, producing the first, albeit essential, structured interpretation of such a relevant document. Moreover, our findings indicate that tools such as SpaCy and ClausIE reach their limits over the legal language of the NIS 2.