Semantic Norm Recognition and its application to Portuguese Law

TL;DR

This paper presents SNR, an automatic system for extracting semantic legal norms from Portuguese legal texts, improving understanding and retrieval of legal information in the digital age.

Contribution

It introduces SNR, a novel semantic norm recognition system trained on Portuguese legal texts using BERTimbau, enhancing legal text interpretation and retrieval.

Findings

Achieved 81.44% F1-score on legal corpus

Demonstrated usefulness for downstream information retrieval tasks

Validated effectiveness despite noisy data

Abstract

Being able to clearly interpret legal texts and fully understanding our rights, obligations and other legal norms has become progressively more important in the digital society. However, simply giving citizens access to the laws is not enough, as there is a need to provide meaningful information that cater to their specific queries and needs. For this, it is necessary to extract the relevant semantic information present in legal texts. Thus, we introduce the SNR (Semantic Norm Recognition) system, an automatic semantic information extraction system trained on a domain-specific (legal) text corpus taken from Portuguese Consumer Law. The SNR system uses the Portuguese Bert (BERTimbau) and was trained on a legislative Portuguese corpus. We demonstrate how our system achieved good results (81.44\% F1-score) on this domain-specific corpus, despite existing noise, and how it can be used to improve downstream tasks such as information retrieval.