{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,4]],"date-time":"2025-12-04T12:10:24Z","timestamp":1764850224039,"version":"3.46.0"},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"value":"9781643686387","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,12,2]],"date-time":"2025-12-02T00:00:00Z","timestamp":1764633600000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,12,2]]},"abstract":"<jats:p>This paper proposes and evaluates a method for interpreting hierarchical graph neural network (GNN) nodes created from criminal law texts. We optimise a hierarchical GNN with extra loss functions to generate coherent abstract nodes from Brazilian habeas corpus data. Four concept grounding (CG) methods (utilising semantic similarity and large language models (LLMs)) are evaluated for giving names to these nodes. Quantitative results demonstrate that optimisation improves the quality of abstractions and predictive performance. Qualitative expert evaluation favoured labels based on LLMs. This dual approach (optimisation and grounding) provides a framework towards more trustworthy and explainable legal AI systems.<\/jats:p>","DOI":"10.3233\/faia251617","type":"book-chapter","created":{"date-parts":[[2025,12,4]],"date-time":"2025-12-04T12:05:39Z","timestamp":1764849939000},"source":"Crossref","is-referenced-by-count":0,"title":["Towards Interpretable Hierarchical Graph Neural Networks in Criminal Law"],"prefix":"10.3233","author":[{"given":"Thiago","family":"Dal Pont","sequence":"first","affiliation":[{"name":"Automation and Systems Department, Federal University of Santa Catarina, Brazil"},{"name":"AlmaAI Research Centre, University of Bologna, Italy"}]},{"given":"Isabela","family":"Sabo","sequence":"additional","affiliation":[{"name":"Department of Law, Federal University of Santa Catarina, Brazil"}]},{"given":"Maite","family":"Vieira","sequence":"additional","affiliation":[{"name":"Department of Law, Federal University of Santa Catarina, Brazil"}]},{"given":"Jomi","family":"H\u00fcbner","sequence":"additional","affiliation":[{"name":"Automation and Systems Department, Federal University of Santa Catarina, Brazil"}]},{"given":"Aires","family":"Rover","sequence":"additional","affiliation":[{"name":"Department of Law, Federal University of Santa Catarina, Brazil"}]}],"member":"7437","container-title":["Frontiers in Artificial Intelligence and Applications","Legal Knowledge and Information Systems"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/FAIA251617","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,12,4]],"date-time":"2025-12-04T12:05:40Z","timestamp":1764849940000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/FAIA251617"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,12,2]]},"ISBN":["9781643686387"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/faia251617","relation":{},"ISSN":["0922-6389","1879-8314"],"issn-type":[{"value":"0922-6389","type":"print"},{"value":"1879-8314","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,12,2]]}}}