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Dataset Alignment and Lexicalization to Support Multilingual Analysis of Legal Documents

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AI Approaches to the Complexity of Legal Systems (AICOL 2015, AICOL 2016, AICOL 2016, AICOL 2017, AICOL 2017)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10791))

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Abstract

The result of the EU is a complex, multilingual, multicultural and yet united environment, requiring solid integration policies and actions targeted at simplifying cross-language and cross-cultural knowledge access. The legal domain is a typical case in which both the linguistic and the conceptual aspects mutually interweave into a knowledge barrier that is hard to break. In the context of the ISA2 funded project “Public Multilingual Knowledge Infrastructure” (PMKI) we are addressing Semantic Interoperability at both the conceptual and lexical level, by developing a set of coordinated instruments for advanced lexicalization of RDF resources (be them ontologies, thesauri and datasets in general) and for alignment of their content. In this paper, we describe the objectives of the project and the concrete actions, specifically in the legal domain, that will create a platform for multilingual cross-jurisdiction accessibility to legal content in the EU.

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Notes

  1. 1.

    https://ec.europa.eu/isa2/

  2. 2.

    https://www.senato.it/3235?testo_generico=745

  3. 3.

    http://eurovoc.europa.eu/

  4. 4.

    It would be more appropriate to adopt the term “reference dataset” (including thus also SKOS thesauri and datasets in general), to express data containing the logical symbols for describing a certain domain. In line with the traditional name OntoLex (and thus the ontology-lexicon dualism), we will however often refer to them with the term ontology.

  5. 5.

    http://www.w3.org/community/ontolex/

  6. 6.

    http://linguistics.okfn.org/

  7. 7.

    http://linguistic-lod.org/llod-cloud

  8. 8.

    http://ec.europa.eu/isa/documents/isa_annex_i_eis_en.pdf

  9. 9.

    http://ec.europa.eu/isa/documents/isa_annex_ii_eif_en.pdf

  10. 10.

    http://termcoord.eu/iate/

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Author information

Authors and Affiliations

  1. ART Group, Department of Enterprise Engineering, University of Rome Tor Vergata, Via del Politecnico 1, 00133, Rome, Italy

    Armando Stellato, Manuel Fiorelli, Andrea Turbati & Tiziano Lorenzetti

  2. Publications Office of the European Union, Luxembourg City, Luxembourg

    Peter Schmitz, Enrico Francesconi, Najeh Hajlaoui & Brahim Batouche

  3. Institute of Legal Information Theory and Techniques (ITTIG), Consiglio Nazionale delle Ricerche (CNR), Via dei Barucci 20, 50127, Florence, Italy

    Enrico Francesconi

Authors
  1. Armando Stellato
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  2. Manuel Fiorelli
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  4. Tiziano Lorenzetti
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  6. Enrico Francesconi
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  7. Najeh Hajlaoui
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  8. Brahim Batouche
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Corresponding authors

Correspondence to Armando Stellato or Enrico Francesconi .

Editor information

Editors and Affiliations

  1. University of Turin, Turin, Italy

    Ugo Pagallo

  2. University of Bologna, Bologna, Italy

    Monica Palmirani

  3. La Trobe University, Melbourne, VIC, Australia

    Pompeu Casanovas

  4. University of Bologna, Bologna, Italy

    Giovanni Sartor

  5. Inria - Sophia Antipolis-Méditerranée, Sophia Antipolis, France

    Serena Villata

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Stellato, A. et al. (2018). Dataset Alignment and Lexicalization to Support Multilingual Analysis of Legal Documents. In: Pagallo, U., Palmirani, M., Casanovas, P., Sartor, G., Villata, S. (eds) AI Approaches to the Complexity of Legal Systems. AICOL AICOL AICOL AICOL AICOL 2015 2016 2016 2017 2017. Lecture Notes in Computer Science(), vol 10791. Springer, Cham. https://doi.org/10.1007/978-3-030-00178-0_17

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