Artificial Intelligence and Law

, Volume 21, Issue 2, pp 139–172 | Cite as

TULSI: an NLP system for extracting legal modificatory provisions

  • Leonardo Lesmo
  • Alessandro Mazzei
  • Monica Palmirani
  • Daniele P. Radicioni
Article

Abstract

In this work we present the TULSI system (so named after Turin University Legal Semantic Interpreter), a system to produce automatic annotations of normative documents through the extraction of modificatory provisions. TULSI relies on a deep syntactic analysis and a shallow semantic interpreter that are illustrated in detail. We report the results of an experimental evaluation of the system and discuss them, also suggesting future directions for further improvement.

Keywords

Natural language processing Information extraction Law Semantic interpretation 

References

  1. Abney SP (1991) Principle-based parsing: computation and psycholinguistics. In: Berwick RC, Abney SP, Tenny C (eds) Parsing by Chunks. Kluwer, DordrechtGoogle Scholar
  2. AIPA (2002) Formato per la rappresentazione elettronica dei provvedimenti normativi tramite il linguaggio di marcatura XML. Circolare n. AIPA/CR/40, 22 aprileGoogle Scholar
  3. Alchourròn CE, Bulygin E (1971) Normativity and norms: critical perspectives on Kelsenian themes. In: Paulson SL, Litschewski-Paulson B (eds) The expressive conception of norms. Clarendon Press, OxfordGoogle Scholar
  4. Alicante A, Bosco C, Corazza A, Lavelli A (2012) A treebank-based study on the influence of Italian word order on parsing performance. In: Calzolari N (Conference Chair), Choukri K, Declerck T, Uğur Doğan M, Maegaard B, Mariani J, Odijk J, Piperidis S (eds) Proceedings of the eight international conference on language resources and evaluation (LREC’12), Istanbul, Turkey, May 2012. European Language Resources Association (ELRA)Google Scholar
  5. Appelt DE, Israel D (1999) Introduction to information extraction technology. In Proceedings of 16th international joint conference on artificial intelligence IJCAI-99, TutorialGoogle Scholar
  6. Arnold-Moore T (1995) Automatically processing amendments to legislation. In: ICAIL, pp 297–306Google Scholar
  7. Arnold-Moore T (1997) Automatic generation of amendment legislation. In: Proceedings of the international conference on artificial intelligence and law (ICAIL), pp 56–62Google Scholar
  8. Bartolini R, Lenci A, Montemagni S, Pirrelli V, Soria C (2004) Semantic mark-up of italian legal texts through nlp-based techniques. In: Proceedings of LREC 2004, pp 795–798Google Scholar
  9. Biagioli C, Francesconi E, Spinosa P, Taddei M (2003) The NIR project: standards and tools for legislative drafting and legal document web publication. In: Proceedings of ICAIL workshop on e-government: modelling norms and concepts as key issues, pp 69–78Google Scholar
  10. Biagioli C, Francesconi E, Passerini A, Montemagni S, Soria C (2005) Automatic semantics extraction in law documents. In: ICAIL ’05: Proceedings of the 10th international conference on artificial intelligence and law. New York, NY, USA. ACM, pp 133–140Google Scholar
  11. Bolioli A, Dini L, Mercatali P, Romano F (2002) For the automated mark-up of italian legislative texts in XML. In: Bench-Capon T, Daskalopulu A, Winkels R (eds) Legal knowledge and information systems. Proceedings of Jurix 2002: the fifteenth annual conference. IOS PressGoogle Scholar
  12. Bosco C, Montemagni S, Mazzei A, Lombardo V, Dell’Orletta F, Lenci A (2009) Evalita’09 parsing task: comparing dependency parsers and treebanks. In: Proceedings of Evalita’09. Reggio Emilia, ItalyGoogle Scholar
  13. Brighi R, Palmirani M (2009) Legal text analysis of the modification provisions: a pattern oriented approach. In: Proceedings of the international conference on artificial intelligence and law (ICAIL)Google Scholar
  14. Cherubini M, Giardiello G, Marchi S, Montemagni S, Spinosa PL, Venturi G (2008) NLP-based metadata annotation of textual amendments. In: Proceedings of workshop on legislative XML 2008, JurixGoogle Scholar
  15. Collins M (1997) Three generative, lexicalised models for statistical parsing. In: Proceedings of the 35th annual meeting of the association for computational linguistics, pp 16–23Google Scholar
  16. de Maat E, Winkels R, van Engers TM (2006) Automated detection of reference structures in law. In: van Engers TM (ed) Proceedings of the JURIX 2006 on legal knowledge and information systems: the nineteenth annual conference. IOS Press, Amsterdam, pp 41–50Google Scholar
  17. de Maat E, Krabben K, Winkels R (2010) Machine learning versus knowledge based classification of legal texts. In: IOS Press, (ed) Proceedings of the 2010 conference on legal knowledge and information systems: JURIX 2010: the twenty-third annual conference, Amsterdam, pp 87–96Google Scholar
  18. De Salvo Braz R, Girju R, Punyakanok V, Dan R, Sammons M (2005) An inference model for semantic entailment in natural language. In: AAAI’05: Proceedings of the 20th national conference on artificial intelligence. AAAI Press, pp 1043–1049Google Scholar
  19. Domingos P (1999) The role of Occam’s razor in knowledge discovery. Data Min Knowl Discov 3:409–425CrossRefGoogle Scholar
  20. Haghighi AD, Ng AY, Manning CD (2005) Robust textual inference via graph matching. In: HLT ’05: Proceedings of the conference on human language technology and empirical methods in NLP, Morristown, NJ, USA, 2005. ACL, pp 387–394Google Scholar
  21. Jackson P, Moulinier I (2002) Natural language processing for online applications. Text retrieval, extraction and categorization, vol 5 of natural language processing. Benjamins, Amsterdam, PhiladelphiaGoogle Scholar
  22. Lesmo L (2007) The rule-based parser of the nlp group of the university of torino. Intell Artif 2(4):46–47Google Scholar
  23. Lesmo L, Lombardo V (2002) Transformed subcategorization frames in chunk parsing. In: Proceedings of the 3rd international conference on language resources and evaluation (LREC 2002), Las Palmas, pp 512–519Google Scholar
  24. Lupo C, Vitali F, Francesconi E, Palmirani M, Winkels R, de Maat E, Boer A, Mascellani P (2007) General XML format(s) for legal Sources—ESTRELLA European project. Deliverable 3.1, Faculty of Law, University of Amsterdam, AmsterdamGoogle Scholar
  25. McCarty LT (2007) Deep semantic interpretations of legal texts. In: ICAIL ’07: Proceedings of the 11th international conference on Artificial intelligence and law. New York, NY, USA, ACM, pp 217–224Google Scholar
  26. Ogawa Y, Inagaki S, Toyama K (2008) Automatic consolidation of Japanese statutes based on formalization of amendment sentences. In: Proceedings of the 2007 conference on New frontiers in artificial intelligence, JSAI’07, Berlin, Heidelberg, 2008. Springer, pp 363–376Google Scholar
  27. Palmirani M (2011) Legislative change management with Akoma-Ntoso. In: Sartor G, Palmirani M, Francesconi E, Angela Biasiotti MA (eds) Legislative XML for the Semantic Web. Springer, BerlinGoogle Scholar
  28. Palmirani M, Benigni F (2007) Norma-system: a legal information system for managing time. In: Biagioli C, Francesconi E, Sartor G (eds) Proceedings of the V legislative XML workshop. European Press Academic Publishing, Feb 2007, pp 205–223Google Scholar
  29. Palmirani M, Brighi R (2003) An XML editor for legal information management. In: Traunmüller R (ed) Electronic government, vol 2739 of LNCS. Springer, Berlin, pp 421–429Google Scholar
  30. Palmirani M, Brighi R (2006) Time model for managing the dynamic of normative system. Electron Gov. Lecture notes in computer science, vol 4084. Springer, pp 207–218Google Scholar
  31. Palmirani M, Brighi R (2010) Model regularity of legal language in active modifications. In: Biasiotti M et al (eds) AICOL workshops 2009. Springer, Berlin, pp 54–73Google Scholar
  32. Palmirani M, Brighi R, Massini M (2004) Processing normative references on the basis of natural language questions. In: DEXA ’04 Proceedings of the database and expert systems applications, 15th international workshop. IEEE Computer Society, pp 9–12Google Scholar
  33. Rodotà S (1998) La tecnica legislativa per clausole generali in Italia. In: Cabella Pisu L, Nanni L (eds) Clausole e principi generali nell’argomentazione giurisprudenziale degli anni novanta. Cedam, PadovaGoogle Scholar
  34. Sacco R (2000) Lingua e diritto. Ars Interpretandi. Annuario di ermeneutica giuridica. Traduzione e diritto 5:117–134Google Scholar
  35. Sagri MT, Tiscornia D (2009) Le peculiarità del linguaggio giuridico. Problemi e prospettive nel contesto multilingue Europeo. MediAzioni 7. http://mediazioni.sitlec.unibo.it. ISSN 1974-4382
  36. Saias J, Quaresma P (2004) A methodology to create legal ontologies in a logic programming based web information retrieval system. Artif Intell Law 12(4):397–417CrossRefGoogle Scholar
  37. Sartor G (1996) Riferimenti normativi e dinamica dei nessi normativi. In: Il procedimento normativo regionale. Cedam, Padova, pp 151–164Google Scholar
  38. Soria C, Bartolini R, Lenci A, Montemagni S, Pirrelli V (2007) Automatic extraction of semantics in law documents. In: Biagioli C, Francesconi E, Sartor G (eds) Proceedings of the V legislative XML workshop. European Press Academic Publishing, pp 253–266Google Scholar
  39. Spinosa PL, Giardiello G, Cherubini M, Marchi S, Venturi G, Montemagni S (2009) Nlp-based metadata extraction for legal text consolidation. In: Proceedings of the 12th international conference on artificial intelligence and law, ICAIL ’09. New York, NY, USA, 2009. ACM, pp 40–49Google Scholar
  40. Wyner A (2011) Towards annotating and extracting textual legal case elements. In: Francesconi E (ed) Informatica e Diritto: special issue on legal ontologies and artificial intelligent techniques 19(1–2):9–18 ESIGoogle Scholar
  41. Zanchetta E, Baroni M (2005) Morph-it! A free corpus-based morphological resource for the Italian language. Corpus Linguistics 2005 1(1). http://www.corpus.bham.ac.uk/PCLC/

Copyright information

© Springer Science+Business Media B.V. 2012

Authors and Affiliations

  • Leonardo Lesmo
    • 1
  • Alessandro Mazzei
    • 1
  • Monica Palmirani
    • 2
  • Daniele P. Radicioni
    • 1
  1. 1.Dipartimento di InformaticaUniversità di TorinoTorinoItaly
  2. 2.CIRSFIDUniversità di BolognaBolognaItaly

Personalised recommendations