nach oben

Erschienen in:

2018 | OriginalPaper | Buchkapitel

Claim Detection in Judgments of the EU Court of Justice

verfasst von : Marco Lippi, Francesca Lagioia, Giuseppe Contissa, Giovanni Sartor, Paolo Torroni

Erschienen in: AI Approaches to the Complexity of Legal Systems

Verlag: Springer International Publishing

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config

KI-gestützte Suche

Aus

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.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

über 102.000 Bücher
über 537 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Finance + Banking
Management + Führung
Marketing + Vertrieb
Maschinenbau + Werkstoffe
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 390 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Maschinenbau + Werkstoffe

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 340 Zeitschriften

aus folgenden Fachgebieten:

Bauwesen + Immobilien
Business IT + Informatik
Finance + Banking
Management + Führung
Marketing + Vertrieb
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Vorheriges Kapitel Dynamics of the Judicial Process by Defeater Activation

Nächstes Kapitel A Non-intrusive Approach to Measuring Trust in Opponents in a Negotiation Scenario

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

http://corpora.aifdb.org/.

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

Aleven, V.: Using background knowledge in case-based legal reasoning: a computational model and an intelligent learning environment. Artif. Intell. 150(1), 183–237 (2003)CrossRef

Alexander, B.: LKIF core: principled ontology development for the legal domain. In: Law, Ontologies and the Semantic Web: Channelling the Legal Information Flood, vol. 188, p. 21 (2009)

Ashley, K.D., Desai, R., Levine, J.M.: Teaching case-based argumentation concepts using dialectic arguments vs. didactic explanations. In: Cerri, S.A., Gouardères, G., Paraguaçu, F. (eds.) ITS 2002. LNCS, vol. 2363, pp. 585–595. Springer, Heidelberg (2002). https://doi.org/10.1007/3-540-47987-2_60CrossRef

Ashley, K.D., Walker, V.R.: Toward constructing evidence-based legal arguments using legal decision documents and machine learning. In: Francesconi, E., Verheij, B. (eds.) ICAIL 2012, Rome, Italy, pp. 176–180. ACM (2013)

Bench-Capon, T., Freeman, J.B., Hohmann, H., Prakken, H.: Computational models, argumentation theories and legal practice. In: Machines, A. (ed.) Reed C, Norman TJ. Argumentation Library, vol. 9, pp. 85–120. Springer, Dordrecht (2003). https://doi.org/10.1007/978-94-017-0431-1_4CrossRef

Bench-Capon, T., Prakken, H., Sartor, G.: Argumentation in legal reasoning. In: Simari, G., Rahwan, I. (eds.) Argumentation in Artificial Intelligence, pp. 363–382. Springer, Boston (2009). https://doi.org/10.1007/978-0-387-98197-0_18CrossRef

Bench-Capon, T., Sartor, G.: A model of legal reasoning with cases incorporating theories and values. Artif. Intell. 150(1), 97–143 (2003)CrossRef

Brighi, R., Lesmo, L., Mazzei, A., Palmirani, M., Radicioni, D.P.: Towards semantic interpretation of legal modifications through deep syntactic analysis. In: Proceedings of the 2008 conference on Legal Knowledge and Information Systems: JURIX 2008: The Twenty-First Annual Conference, pp. 202–206. IOS Press (2008)

Cabrio, E., Villata, S.: A natural language bipolar argumentation approach to support users in online debate interactions. Argum. Comput. 4(3), 209–230 (2013)CrossRef

10.

Carr, C.S.: Using computer supported argument visualization to teach legal argumentation. In: Kirschner, P.A., Buckingham Shum, S.J., Carr, C.S. (eds.) Visualizing Argumentation. Computer Supported Cooperative Work, pp. 75–96. Springer, London (2003). https://doi.org/10.1007/978-1-4471-0037-9_4CrossRef

11.

Chesñevar, C.I., et al.: Towards an argument interchange format. Knowl. Eng. Rev. 21(4), 293–316 (2006)CrossRef

12.

Copi, I.M., Cohen, C., McMahon, K.: Introduction to Logic: Pearson New International Edition. Pearson Higher Education (2013)

13.

Feng, V.W., Hirst, G.: Classifying arguments by scheme. In: Lin, D., Matsumoto, Y., Mihalcea, R. (eds.) The 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies, Proceedings of the Conference, Portland, Oregon, USA, 19–24 June 2011, pp. 987–996. ACL (2011)

14.

Freeman, J.B.: Dialectics and the Macrostructure of Arguments: A Theory of Argument Structure, vol. 10. Walter de Gruyter (1991)

15.

Habernal, I., Eckle-Kohler, J., Gurevych, I.: Argumentation mining on the web from information seeking perspective. In: Cabrio, E., Villata, S., Wyner, A. (eds.) Proceedings of the Workshop on Frontiers and Connections Between Argumentation Theory and Natural Language Processing. Forlì-Cesena, Italy, 21–25 July 2014. CEUR Workshop Proceedings, vol. 1341. CEUR-WS.org (2014)

16.

Hachey, B., Grover, C.: Extractive summarisation of legal texts. Artif. Intell. Law 14(4), 305–345 (2006)CrossRef

17.

Levy, R., Bilu, Y., Hershcovich, D., Aharoni, E., Slonim, N.: Context dependent claim detection. In: Hajic, J., Tsujii, J. (eds.) COLING 2014, Dublin, Ireland, pp. 1489–1500. ACL (2014)

18.

Lippi, M., Torroni, P.: Context-independent claim detection for argument mining. In: Yang, Q., Wooldridge, M. (eds.) Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, IJCAI 2015, Buenos Aires, Argentina, 25–31 July 2015, pp. 185–191. AAAI Press (2015)

19.

Lippi, M., Torroni, P.: Argumentation mining: state of the art and emerging trends. ACM Trans. Internet Technol. 16(2), 10:1–10:25 (2016)CrossRef

20.

McCarty, L.T.: Deep semantic interpretations of legal texts. In: Proceedings of the 11th International Conference on Artificial Intelligence and Law, pp. 217–224. ACM (2007)

21.

Mochales Palau, R., Ieven, A.: Creating an argumentation corpus: do theories apply to real arguments? A case study on the legal argumentation of the ECHR. In: Proceedings of the Twelfth International Conference on Artificial Intelligence and Law (ICAIL 2009), Barcelona, Spain, 8–12 June 2009, pp. 21–30. ACM (2009)

22.

Mochales Palau, R., Moens, M.F.: Argumentation mining. Artif. Intell. Law 19(1), 1–22 (2011)CrossRef

23.

Moschitti, A.: Efficient convolution kernels for dependency and constituent syntactic trees. In: Fürnkranz, J., Scheffer, T., Spiliopoulou, M. (eds.) ECML 2006. LNCS (LNAI), vol. 4212, pp. 318–329. Springer, Heidelberg (2006). https://doi.org/10.1007/11871842_32CrossRef

24.

Moschitti, A.: State-of-the-art kernels for natural language processing. In: Tutorial Abstracts of ACL 2012, ACL 2012, p. 2. Association for Computational Linguistics, Stroudsburg (2012)

25.

Peldszus, A., Stede, M.: From argument diagrams to argumentation mining in texts: a survey. Int. J. Cogn. Inf. Nat. Intell. (IJCINI) 7(1), 1–31 (2013)CrossRef

26.

Prakken, H., Sartor, G.: A dialectical model of assessing conflicting arguments in legal reasoning. In: Prakken, H., Sartor, G. (eds.) Logical Models of Legal Argumentation, pp. 175–211. Springer, Dordrecht (1997). https://doi.org/10.1007/978-94-011-5668-4_6CrossRef

27.

Prakken, H., Sartor, G.: The role of logic in computational models of legal argument: a critical survey. In: Kakas, A.C., Sadri, F. (eds.) Computational Logic: Logic Programming and Beyond. LNCS (LNAI), vol. 2408, pp. 342–381. Springer, Heidelberg (2002). https://doi.org/10.1007/3-540-45632-5_14CrossRefMATH

28.

Rinott, R., Dankin, L., Perez, C.A., Khapra, M.M., Aharoni, E., Slonim, N.: Show me your evidence - an automatic method for context dependent evidence detection. In: Màrquez, L., Callison-Burch, C., Su, J., Pighin, D., Marton, Y. (eds.) Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing, EMNLP 2015, Lisbon, Portugal, 17–21 September 2015, pp. 440–450. The Association for Computational Linguistics (2015)

29.

Stab, C., Gurevych, I.: Identifying argumentative discourse structures in persuasive essays. In: Moschitti, A., Pang, B., Daelemans, W. (eds.) EMNLP 2014, Doha, Qatar, pp. 46–56. ACL (2014)

30.

Teufel, S.: Argumentative zoning. Ph.D. Thesis, University of Edinburgh (1999)

31.

Toulmin, S.E.: The Uses of Argument. Cambridge University Press, Cambridge (1958)

32.

Walton, D.: Fundamentals of Critical Argumentation. Critical Reasoning and Argumentation. Cambridge University Press, Cambridge (2006)

33.

Walton, D.: Argumentation theory: a very short introduction. In: Simari, G., Rahwan, I. (eds.) Argumentation in Artificial Intelligence, pp. 1–22. Springer, Boston (2009). https://doi.org/10.1007/978-0-387-98197-0_1CrossRef

34.

Walton, D., Reed, C., Macagno, F.: Argumentation Schemes. Cambridge University Press, Cambridge (2008)CrossRef

35.

Wilcoxon, F.: Individual comparisons by ranking methods. Biom. Bull. 1(6), 80–83 (1945)CrossRef

36.

Wyner, A., van Engers, T.: From argument in natural language to formalised argumentation: components, prospects and problems. In: Proceedings of the Worskhop on Natural Language Engineering of Legal Argumentation, Barcelona, Spain (2009)

Titel: Claim Detection in Judgments of the EU Court of Justice
verfasst von: Marco Lippi
Francesca Lagioia
Giuseppe Contissa
Giovanni Sartor
Paolo Torroni
Verlag: Springer International Publishing
Buch: AI Approaches to the Complexity of Legal Systems
Print ISBN: 978-3-030-00177-3

Electronic ISBN: 978-3-030-00178-0

Copyright-Jahr: 2018
DOI: https://doi.org/10.1007/978-3-030-00178-0_35

Springer Professional

Abstract

Bitte loggen Sie sich ein, um Zugang zu Ihrer Lizenz zu erhalten.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Springer Professional "Technik"

Springer Professional "Wirtschaft"