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   Populating legal ontologies using semantic role labeling; ; van der Torre, Leon  et alin Artificial Intelligence and Law (2020) This paper is concerned with the goal of maintaining legal information and compliance systems: the ‘resource consumption bottleneck’ of creating semantic technologies manually. The use of automated ... [more ▼] This paper is concerned with the goal of maintaining legal information and compliance systems: the ‘resource consumption bottleneck’ of creating semantic technologies manually. The use of automated information extraction techniques could significantly reduce this bottleneck. The research question of this paper is: How to address the resource bottleneck problem of creating specialist knowledge management systems? In particular, how to semi-automate the extraction of norms and their elements to populate legal ontologies? This paper shows that the acquisition paradox can be addressed by combining state-of-the-art general-purpose NLP modules with pre- and post-processing using rules based on domain knowledge. It describes a Semantic Role Labeling based information extraction system to extract norms from legislation and represent them as structured norms in legal ontologies. The output is intended to help make laws more accessible, understandable, and searchable in legal document management systems such as Eunomos (Boella et al., 2016). [less ▲] Detailed reference viewed: 65 (1 UL) Argumentation-based Methodology for Goal-oriented Requirements Language (GRL); Van Zee, Marc ; in Proceedings of the 10th International i* Workshop co-located with the 29th International Conference on Advanced Information Systems Engineering (CAiSE 2017), Essen, Germany, June 12-13, 2017. (2017) Goal-oriented Requirements Language (GRL) aims to capture goals and non-functional requirements of stakeholders and analyzing alternative solutions for realizing these goals. GRL also documents the ... [more ▼] Goal-oriented Requirements Language (GRL) aims to capture goals and non-functional requirements of stakeholders and analyzing alternative solutions for realizing these goals. GRL also documents the rationale behind selecting certain goals or alternatives. However, it does not have any means to document and trace back all of the arguments that occur during the stakeholder’s discussion process. To address this, we have developed the RationalGRL framework. RationalGRL combines techniques for formal argumentation from artificial intelligence with goal modeling in GRL. However, we did not specify how practitioners can actually use this framework. In this paper we discuss the methodology for RationalGRL, which consists of two processes, goal modeling and argumentation, that can be done interchangeably. We motivate our approach with an example. [less ▲] Detailed reference viewed: 57 (1 UL)Formalizing and Modeling Enterprise Architecture (EA) Principles with Goal-oriented Requirements Language (GRL); Van Zee, Marc ; in Proceedings of the 28th International Conference on Advanced Information System Engineering (CAiSE16) (2016) Detailed reference viewed: 127 (0 UL)The RationalGRL toolset for Goal Models and Argument DiagramsVan Zee, Marc ; ; et alin Proceedings of the 6th International Conference on Computational Models of Argument (COMMA'16) (2016) Detailed reference viewed: 64 (4 UL)RationalGRL: A Framework for Rationalizing Goal Models Using Argument DiagramsVan Zee, Marc ; ; in 35th International Conference on Conceptual Modeling (ER'2016) (2016) Detailed reference viewed: 100 (0 UL)Classifying and Extracting Elements of Norms for Ontology Population using Semantic Role LabellingHumphreys, Llio ; ; Robaldo, Livio et alin The 15th International Conference on Artificial Intelligence & Law — San Diego, June 8-12, 2015 (2015) Detailed reference viewed: 282 (23 UL)Rationalization of Goal Models in GRL using Formal ArgumentationVan Zee, Marc ; ; in In Proceedings of RE: Next! track at the Requirements Engineering Conference 2015 (RE'15) (2015) Detailed reference viewed: 97 (1 UL)Capturing Evidence and Rationales with Requirements Engineering and Argumentation-Based TechniquesVan Zee, Marc ; Scientific Conference (2014, September) Detailed reference viewed: 49 (4 UL)Compliance with Multiple Regulations; Humphreys, Llio ; et alin Conceptual Modeling, Lecture Notes in Computer Science 8824 (2014) Detailed reference viewed: 104 (1 UL)Integrating Legal-URN and Eunomos: Towards a Comprehensive Compliance Management Solution; ; et al in AICOL (2013) Business process compliance with regulations has been a topic of many research areas in Computer Science such as Requirements Engineering (RE), Artificial Intelligence (AI), Logic and Natural Language ... [more ▼] Business process compliance with regulations has been a topic of many research areas in Computer Science such as Requirements Engineering (RE), Artificial Intelligence (AI), Logic and Natural Language Processing (NLP). This work aims to provide a systematic way of establishing and managing compliance to assist decision-making and reporting. Despite many notable advances, few systems deal adequately with legal interpretation and modeling norms in an expressive way that is well-integrated with business modeling practices. In this paper, we bring together two leading systems, Legal-URN and Eunomos, for a comprehensive compliance management solution. [less ▲] Detailed reference viewed: 132 (0 UL) |
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