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GaiusT: supporting the extraction of rights and obligations for regulatory compliance
<span title="2013-09-20">2013</span>
<i title="Springer Nature">
<a target="_blank" rel="noopener" href="https://fatcat.wiki/container/ksueo6d4evgydaetaqy5yhvtfq" style="color: black;">Requirements Engineering</a>
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This work examines the challenge of developing tool support for extracting such requirements from legal documents. To address this challenge, we have developed a tool called GaiusT 1 . ...
Generally speaking, solutions to the problem first identify rights and obligations defined in the law and then treat these as requirements for the system under design. ...
Breaux, Vail and Antón [13] propose a systematic manual process for extracting rights and obligations from legal text. ...
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<a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/s00766-013-0181-8">doi:10.1007/s00766-013-0181-8</a>
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Automated Extraction of Semantic Legal Metadata using Natural Language Processing
<span title="">2018</span>
<i title="IEEE">
<a target="_blank" rel="noopener" href="https://fatcat.wiki/container/35k6qz2nqrfkziwp6ui5gszhbi" style="color: black;">2018 IEEE 26th International Requirements Engineering Conference (RE)</a>
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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). ...
[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 ...
At a statement level, LKIF supports the following deontic concepts: rights, permissions, obligations, and prohibitions. ...
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An Automated Framework for the Extraction of Semantic Legal Metadata from Legal Texts
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<span title="2020-01-30">2020</span>
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arXiv
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<span class="release-stage" >pre-print</span>
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analysis; (2) automated support for the extraction of semantic legal metadata is scarce, and it does not exploit the full potential of artificial intelligence technologies, notably natural language processing ...
Subsequently, we devise an automated extraction approach for the identified metadata types using NLP and ML. We evaluate our approach through two case studies over the Luxembourgish legislation. ...
At statement level, LKIF supports the following deontic concepts: right, permission, obligation, and prohibition. ...
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Modular norm models: practical representation and analysis of contractual rights and obligations
<span title="2019-08-05">2019</span>
<i title="Springer Science and Business Media LLC">
<a target="_blank" rel="noopener" href="https://fatcat.wiki/container/ksueo6d4evgydaetaqy5yhvtfq" style="color: black;">Requirements Engineering</a>
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We outline a practical modeling process for norms in legally binding agreements that include contractual rights and obligations. ...
For norm extraction, using the theory of frame semantics, we construct two foundational norm templates for linguistic guidance. ...
It has a graphical notation and provides extended tool support for compliance analysis. ...
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A Query System for Extracting Requirements-Related Information from Legal Texts
<span title="">2019</span>
<i title="IEEE">
<a target="_blank" rel="noopener" href="https://fatcat.wiki/container/35k6qz2nqrfkziwp6ui5gszhbi" style="color: black;">2019 IEEE 27th International Requirements Engineering Conference (RE)</a>
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These solutions are not adequate for requirements analysts whose objective is to extract domain knowledge including stakeholders, rights and duties, and business processes that are relevant to legal requirements ...
In this paper, we investigate the use of our metadata extraction framework as an enabler for smart legal search with a focus on requirements engineering activities. ...
Apart from GaiusT and NomosT, none of these contributions provide tool support for automatically extracting semantic information. ...
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<a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/re.2019.00041">doi:10.1109/re.2019.00041</a>
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Defining and retrieving themes in nuclear regulations
<span title="">2012</span>
<i title="IEEE">
<a target="_blank" rel="noopener" href="https://fatcat.wiki/container/35k6qz2nqrfkziwp6ui5gszhbi" style="color: black;">2012 Fifth IEEE International Workshop on Requirements Engineering and Law (RELAW)</a>
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This paper presents the regulatory landscape in the context of digital Instrumentation and Command systems in nuclear power plants. ...
Consequently, when licensees want to extract the set of regulations related to a specific concern, they lack explicit traces between all regulation documents and mostly get lost while attempting to compare ...
[15] use GaiusT to extract rights, obligations, on both HIPAA (Health Insurance Portability and Accountability Act) and equivalent Italian regulations. ...
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<a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/relaw.2012.6347797">doi:10.1109/relaw.2012.6347797</a>
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Requirement mining for model-based product design
<span title="">2016</span>
<i title="Inderscience Publishers">
<a target="_blank" rel="noopener" href="https://fatcat.wiki/container/xuan4sq6mjhddfnkf5riefgehy" style="color: black;">International Journal of Product Lifecycle Management</a>
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However, PLM activities of the beginning-of-life and end-of-life of a product mainly deal with a fastidious document-based approach. ...
The NLP experiment shows an average precision of 0.86 and an average recall of 0.95, whereas the SVM requirements classifier outperforms that of naive Bayes with a 76% accuracy rate. ...
More recently, Zeni et al. (2015) have proposed GaiuST, a framework that extracts legal requirements for ensuring regulatory compliance. ...
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<a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1504/ijplm.2016.080983">doi:10.1504/ijplm.2016.080983</a>
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