A Bootstrapping Approach for Semi-Automated Legal Knowledge Extraction and Enrichment

In this paper, we propose a bootstrapping approach for semiautomated legal knowledge extraction. The approach is characterized by the use of a reference legal ontology that is progressively enriched with relevant concepts and related terms extracted from a corpus of legal documents (i.e., Court Decision documents). Supervised, multi-label classification techniques and black-box model explanation techniques are the core components of the bootstrapping approach i) to associate CD documents with appropriate concepts in the ontology and ii) to choose the terms that are decisive for determining the association between a document and a certain ontology concept, respectively. The goal of the proposed approach is to reduce the manual involvement of legal experts as much as possible and to improve the accuracy of document classification, by progressively enriching the term sets associated with ontology concepts. Preliminary experimental results are finally provided to show the contribution of the proposed approach on a corpus of real Court Decision documents.