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Claim Detection in Judgments of the EU Court of Justice

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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))

Abstract

Mining arguments from text has recently become a hot topic in Artificial Intelligence. The legal domain offers an ideal scenario to apply novel techniques coming from machine learning and natural language processing, addressing this challenging task. Following recent approaches to argumentation mining in juridical documents, this paper presents two distinct contributions. The first one is a novel annotated corpus for argumentation mining in the legal domain, together with a set of annotation guidelines. The second one is the empirical evaluation of a recent machine learning method for claim detection in judgments. The method, which is based on Tree Kernels, has been applied to context-independent claim detection in other genres such as Wikipedia articles and essays. Here we show that this method also provides a useful instrument in the legal domain, especially when used in combination with domain-specific information.

This work was done while Marco Lippi was at DISI – University of Bologna and Francesca Lagioia was at CIRSFID – University of Bologna.

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Notes

  1. 1.

    More about IBM Debating Technologies at http://researcher.watson.ibm.com/researcher/view_group.php?id=5443.

  2. 2.

    http://corpora.aifdb.org/.

  3. 3.

    http://nlp.stanford.edu/software/corenlp.shtml.

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Author information

Authors and Affiliations

  1. DISMI, Università degli Studi di Modena e Reggio Emilia, Reggio Emilia, Italy

    Marco Lippi

  2. EUI – European University Institute, Fiesole, Italy

    Francesca Lagioia, Giuseppe Contissa & Giovanni Sartor

  3. CIRSFID, Università degli Studi di Bologna, Bologna, Italy

    Giuseppe Contissa & Giovanni Sartor

  4. DISI, Università degli Studi di Bologna, Bologna, Italy

    Paolo Torroni

Authors
  1. Marco Lippi
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  2. Francesca Lagioia
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  3. Giuseppe Contissa
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  4. Giovanni Sartor
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  5. Paolo Torroni
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Corresponding author

Correspondence to Marco Lippi .

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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Lippi, M., Lagioia, F., Contissa, G., Sartor, G., Torroni, P. (2018). Claim Detection in Judgments of the EU Court of Justice. 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_35

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  • DOI: https://doi.org/10.1007/978-3-030-00178-0_35

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