The DAPRECO Knowledge Base: Representing the GDPR in LegalRuleML

14142

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nan

Abstract

AbstractThe DAPRECO knowledge base (D-KB) is a repository of rules written in LegalRuleML, an XML formalism designed to represent the logical content of legal documents. The rules represent the provisions of the General Data Protection Regulation (GDPR). The D-KB builds upon the Privacy Ontology (PrOnto) (Palmirani et al., 2018), which provides a model for the legal concepts involved in the GDPR, by adding a further layer of constraints in the form of if-then rules, referring either to standard first order logic implications or to deontic statements. If-then rules are formalized in reified I/O logic (Robaldo and Sun, 2017) and then codified in (LegalRuleML, 2019). To date, the D-KB is the biggest knowledge base in LegalRuleML freely available online at (Robaldo et al., 2019).

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Proceedings of the 12th Conference on Language Resources and Evaluation (LREC 2020), pages 549–558 Marseille, 11–16 May 2020 c⃝ European Language Resources Association (ELRA), licensed under CC-BY-NC 549 The ISO Standard for Dialogue Act Annotation, Second Edition Harry Bunt1, Volha Petukhova2, Emer Gilmartin3, Catherine Pelachaud4, Alex Fang5, Simon Keizer6, and Laurent Pr´evot7 1Tilburg University, 2Saarland University, Saarbr¨ucken 3Trinity College, Dublin, 4CNRS-ISIR, Sorbonne University, Paris 5City University, Hong Kong 6Toshiba Research Erope Ltd., Cambridge 7Universit´e Aix-Marseille bunt@uvt.nl, v.v.petukhova@gmail.com, gilmare@tcd.ie, catherine.pelachaud@upmc.fr, alex.fang@cityu.edu.hk, keizer.simon@gmail.com, laurent.prevot@lpl-aix.fr Abstract ISO standard 24617-2 for dialogue act annotation, established in 2012, has in the past few years been used both in corpus annotation and in the design and implementation of components of spoken and multimodal dialogue systems. This has brought some inaccuracies and undesirable limitations of the standard to light, which are addressed in the second edition. This second edition allows a more accurate annotation of dependence relations and rhetorical relations in dialogue. Moreover, a triple-layered plug-in mechanism is introduced which allows dialogue act descriptions to be enriched with information about their semantic content and other information, such as accompanying emotions, and which allows the annotation scheme to be customised by adding application-specific dialogue act types. Keywords: dialogue annotation, dialogue acts, ISO standards, plug-ins, semantic annotation 1. Introduction The first edition of ISO standard 24617-2 for dialogue act annotation, published in 2012 (Bunt et al 2010; 2012), has been applied in corpus annotation1 and in the design of components for language understanding, dialogue man- agement, and output generation in spoken and multimodal interactive systems.2. These applications have brought some inaccuracies of the standard to light and some undesirable limitations, both of which are addressed in the second edition. The design of the standard has also contributed to the specification of a framework for defining other standards for semantic annotation. This framework was in turn established as an ISO standard in 2016 (ISO 24617-6, Principles of semantic annotation). In its specification the second edition of ISO 24617-2 closely follows the requirements and recommendations of this framework. When revising an annotation standard, an important issue concerns the compatibility between annotations according to the original and the revised version. It is desirable that ‘old’ annotations do not require re-annotation or conver- sion, for being valid according to the revised version, ex- cept where the revision concerns the correction of errors in the original version.The revised standard should thus preferably be ‘downward compatible’ with the original ver- sion. The second edition of ISO 24617-2 is indeed down- ward compatible with its first edition, which was made pos- sible by the fact that the ISO scheme is extensible in the following respects: Dimensions: Due to the orthogonality of the set of di- mensions, additional dimensions may be introduced 1See e.g. Fang et al., 2012; Chowdhury et al. (2014); Petukhova et al. (2014), Gilmartin et al., 2018; Ngo et al. (2018); Bunt et al. (2019); Mezza et al. (2019). 2See e.g. Keizer and Rieser (2018); Keizer et al. (2019), Malchanau (2019), Malchanau et al. …

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Labeled Text

AbstractThe DAPRECO knowledge base (D-KB) is a repository of rules written in LegalRuleML, an XML formalism designed to represent the logical content of legal documents. The rules represent the provisions of the General Data Protection Regulation (GDPR). The D-KB builds upon the Privacy Ontology (PrOnto) (Palmirani et al., 2018), which provides a model for the legal concepts involved in the GDPR, by adding a further layer of constraints in the form of if-then rules, referring either to standard first order logic implications or to deontic statements. If-then rules are formalized in reified I/O logic (Robaldo and Sun, 2017) and then codified in (LegalRuleML, 2019). To date, the D-KB is the biggest knowledge base in LegalRuleML freely available online at (Robaldo et al., 2019).

Publication Details

Paper ID:
14142
Year:
2020
Publication:
TIPSTER
Publication Type:
conf
DOI:
nan