Modificatory Provision Detection: a Hybrid NLP Apprach

In the last few years University of Turin and CIRSFID University of Bologna collaborated to pair NLP techniques and legal knowledge to detect modicatory provisions in normative texts. Annotating these modications is a relevant interesting problem, in that modications aect the whole normative system; and legal language, though more regular than unrestricted language, is sometimes particularly convoluted, and poses specic linguistic issues. This paper focuses on two major aspects. First, we explore a combination between parsing and regular expressions; to the best of our knowledge, such hybrid strategy has never been proposed before to tackle the problem at hand. Secondly, we signicantly extend past works coverage (basically focussed on substitution, integration and repeal modications) in order to account for further twelve modication kinds. For the sake of conciseness, we fully illustrate and discuss only few modication types that are more relevant and interesting: suspension, prorogation of ecacy, postponement of ecacy and exception/derogation. These sorts of modi- cations appear particularly challenging, in that modications in these categories make use of similar linguistic speech acts and verbs, and exhibit strong similarities in the linguistic syntactical patterns, to such an extent that to discern them is dicult for the legal expert, too. We describe the implemented system and report about an extensive experimentation on the new modicatory provisions. Results are discussed in order to improve both system's accuracy and annotation practice.