Automatic extraction and collection of legal principles from CJEU decisions on Fiscal State Aid

Legal principles stated in judicial decisions are a key reference for judges and legal professionals. However, typically, decisions are long and complex documents. The automatic extraction of legal principles therein may thus be beneficial to many. Unfortunately, this is an under-investigated task for which few resources and implementations exist, especially with regard to EU law. To promote research in this domain, we develop a novel corpus of 64 judicial decisions on Fiscal State Aid by the CJEU (the Court of Justice of the European Union), in which legal principles are identified and tagged. With this new resource, we conduct extensive experimentation to identify the best combinations of representation methods, classifiers and data augmentation methods for the task at hand, obtaining an F1 score of 0.72. Additionally, we consider the collections of legal principles obtained by running the extractive task and collating the output paragraphs together. We show, through the use of lexical metrics and human evaluation, that the quality of generated collections is comparable to that of expert-made ones.