Automated Extraction of Semantic Legal Metadata using Natural Language Processing

Abstract

Context] Semantic legal metadata provides information that helps with understanding and interpreting the meaning of legal provisions. Such metadata is important for the systematic analysis of legal requirements.[Objectives] Our work is motivated by two observations: (1) The existing requirements engineering (RE) literature does not provide a harmonized view on the semantic metadata types that are useful for legal requirements analysis.(2) Automated support for the extraction of semantic legal metadata is scarce, and further does not exploit the full potential of natural language processing (NLP). Our objective is to take steps toward addressing these limitations.[Methods] We review and reconcile the semantic legal metadata types proposed in RE. Subsequently, we conduct a qualitative study aimed at investigating how the identified metadata types can be extracted automatically.[Results and Conclusions] We propose (1) a harmonized conceptual model for the semantic metadata types pertinent to legal requirements analysis, and (2) automated extraction rules for these metadata types based on NLP. We evaluate the extraction rules through a case study. Our results indicate that the rules generate metadata annotations with high accuracy.

Using Models to Enable Compliance Checking Against the GDPR: An Experience Report

“…The controller shall make reasonable efforts to verify in such cases that consent is given or authorised by the holder of parental responsibility over the child, taking into consideration available technology. [21]. Nevertheless, we opted for a manual strategy to avoid overlooking any important information while deepening our understanding of the GDPR.…”

“…These metadata items have to be identified in legal and technical documents such as privacy policies, consent statements, records of processing activities and exemptions, and data protection impact assessments. Natural Language Processing (NLP) [30] and Machine Learning (ML) [31] provide a useful technical platform for metadata extraction [21]. The metadata identified will be the basis for the model-based representation of the legal and technical documents to be checked.…”

A Query System for Extracting Requirements-Related Information from Legal Texts

“…Each statement is subsequently processed in order to automatically extract semantic metadata for the statement itself as well as the phrases contained therein. The metadata annotations produced in this step follow the conceptual model developed in our previous work [3] and shown in Fig. 2.…”

“…In a previous collaboration with the Government of Luxembourg [3], we proposed a conceptual model of semantic legal metadata for requirements engineering (RE). Our set of metadata provides information about the statements and the phrases contained in legal provisions.…”

Requirements Engineering for Global Systems: Cultural, Regulatory and Technical Aspects

“…Sleimi et al [20] proposed a conceptual model for extraction of semantic metadata using natural language processing, to provide a basis for the analysis of legal requirements. In our future work, we would like to investigate these approaches more deeply, to identify which of them can be incorporated or reused in the proposed framework within the step of analysis RL i wrt.…”