research-article

Extracting semantic annotations from legal texts

Authors:

Leonardo Lesmo,

Alessandro Mazzei,

Daniele P. RadicioniAuthors Info & Claims

HT '09: Proceedings of the 20th ACM conference on Hypertext and hypermedia

Pages 167 - 172

https://doi.org/10.1145/1557914.1557944

Published: 29 June 2009 Publication History

Abstract

This paper illustrates a system designed to automatically extract semantic annotations of the normative modifications present in legal texts. The work relies on a deep parsing approach. The problem of semantically annotating legal texts is cast to the problem of mapping parse trees to semantic frames representing such modifications. We report a preliminary experimentation along with the dataset employed, and discuss the results to point out future improvements.

References

[1]

D.E. Appelt and D.J. Israel. Introduction to information extraction technology. Tutorial at IJCAI-99, 1999.

[2]

Timothy Arnold-Moore. Automatic generation of amendment legislation. In Proceedings of the International Conference on Artificial Intelligence and Law (ICAIL), pages 56--62, 1997.

Digital Library

[3]

T. Berners-Lee. Linked Data, http://www.w3.org/designissues/linkeddata.html, 2006.

[4]

C. Biagioli, E. Francesconi, P. Spinosa, and M. Taddei. 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, pages 69--78, 2003.

[5]

Raffaella Brighi. I fondamenti cognitivi del diritto, volume 1, chapter Analisi Linguistica delle Modificazioni Normative: Metodologia e Sperimentazione, pages 51--63. GEDIT Edizioni, Bologna, 2008.

[6]

Raffaella Brighi, Leonardo Lesmo, Alessandro Mazzei, Monica Palmirani, and Daniele P. Radicioni. Towards Semantic Interpretation of Legal Modifications through Deep Syntactic Analysis. In Jurix 2008: The 21st Annual Conference, Frontiers in Artificial Intelligence and Applications. IOS Press, 2008.

Digital Library

[7]

M. Cherubini, G. Giardiello, S. Marchi, S. Montemagni, P. Spinosa, and G. Venturi. NLP-based metadata annotation of textual amendments. In Proc. of WORKSHOP ON LEGISLATIVE XML 2008, JURIX 2008, 2008.

[8]

H. Cui. Unsupervised Semantic Markup of Literature for Biodiversity Digital Libraries. In Proceedings of the 19th ACM Conference on Hypertext and Hypermedia, pages 25--28, 2008.

Digital Library

[9]

E. Hetzner. A Simple Method for Citation Metadata Extraction using Hidden Markov Models. In Proceedings of the 19th ACM Conference on Hypertext and Hypermedia, pages 280--283, 2008.

Digital Library

[10]

J. Klavans, J. Sheffield, J. Lin, and T. Sidhu. Computational Linguistics for Metadata Building. In Proceedings of the 19th ACM Conference on Hypertext and Hypermedia, page 427, 2008.

Digital Library

[11]

L. Lesmo. The rule-based parser of the nlp group of the university of torino. Intelligenza Artificiale, 2(4):46--47, June 2007.

[12]

C. Lupo, F. Vitali, E. Francesconi, M. Palmirani, R. Winkels, E. de Maat, A. Boer, and P. Mascellani. General XML format(s) for legal Sources - ESTRELLA European Project. Deliverable 3.1, Faculty of Law, University of Amsterdam, Amsterdam, The Netherlands, 2007.

[13]

L. T. McCarty. Deep semantic interpretations of legal texts. In ICAIL '07: Proceedings of the 11th International Conference on Artificial Intelligence and Law, pages 217--224, New York, NY, USA, 2007. ACM.

Digital Library

[14]

M. Palmirani and R. Brighi. An XML Editor for Legal Information Management. In R. Traunmüller, editor, Electronic Government, volume 2739 of LNCS, pages 421--429, Berlin / Heidelberg, 2003. Springer-Verlag.

[15]

J. Saias and P. Quaresma. A Methodology to Create Legal Ontologies in a Logic Programming Based Web Information Retrieval System. Artificial Intelligence and Law, 12(4):397--417, 2004.

Digital Library

[16]

C. Soria, R. Bartolini, A. Lenci, S. Montemagni, and V. Pirrelli. Automatic Extraction of Semantics in Law Documents. In C. Biagioli, E. Francesconi, and G. Sartor, editors, Proceedings of the V Legislative XML Workshop, pages 253--266. European Press Academic Publishing, 2007.

Cited By

Soavi MZeni NMylopoulos JMich L(2022)From Legal Contracts to Formal Specifications: A Systematic Literature ReviewSN Computer Science10.1007/s42979-022-01228-43:5Online publication date: 21-Jun-2022
https://doi.org/10.1007/s42979-022-01228-4
Mensa EMarino GColla DDelsanto MRadicioni D(2021)A Resource for Detecting Misspellings and Denoising Medical Text DataProceedings of the Seventh Italian Conference on Computational Linguistics CLiC-it 202010.4000/books.aaccademia.8728(296-302)Online publication date: 3-Sep-2021
https://doi.org/10.4000/books.aaccademia.8728
Boella GCaro LHumphreys LRobaldo LRossi PTorre L(2018)Eunomos, a legal document and knowledge management system for the Web to provide relevant, reliable and up-to-date information on the lawArtificial Intelligence and Law10.1007/s10506-016-9184-324:3(245-283)Online publication date: 26-Dec-2018
https://dl.acm.org/doi/10.1007/s10506-016-9184-3
Show More Cited By

Index Terms

Extracting semantic annotations from legal texts
1. Applied computing
  1. Document management and text processing
    1. Document management

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Published In

cover image ACM Conferences

HT '09: Proceedings of the 20th ACM conference on Hypertext and hypermedia

June 2009

410 pages

ISBN:9781605584867

DOI:10.1145/1557914

General Chairs:
Ciro Cattuto
Institute for Scientific Interchange Foundation, Italy
,
Giancarlo Ruffo
University of Torino, Italy
,
Program Chair:
Filippo Menczer
Indiana University, USA

Copyright © 2009 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 29 June 2009

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HT '09

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HT '09: 20th ACM Conference on Hypertext and Hypermedia

June 29 - July 1, 2009

Torino, Italy

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Overall Acceptance Rate 378 of 1,158 submissions, 33%

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Cited By

Soavi MZeni NMylopoulos JMich L(2022)From Legal Contracts to Formal Specifications: A Systematic Literature ReviewSN Computer Science10.1007/s42979-022-01228-43:5Online publication date: 21-Jun-2022
https://doi.org/10.1007/s42979-022-01228-4
Mensa EMarino GColla DDelsanto MRadicioni D(2021)A Resource for Detecting Misspellings and Denoising Medical Text DataProceedings of the Seventh Italian Conference on Computational Linguistics CLiC-it 202010.4000/books.aaccademia.8728(296-302)Online publication date: 3-Sep-2021
https://doi.org/10.4000/books.aaccademia.8728
Boella GCaro LHumphreys LRobaldo LRossi PTorre L(2018)Eunomos, a legal document and knowledge management system for the Web to provide relevant, reliable and up-to-date information on the lawArtificial Intelligence and Law10.1007/s10506-016-9184-324:3(245-283)Online publication date: 26-Dec-2018
https://dl.acm.org/doi/10.1007/s10506-016-9184-3
Zahoor FBajwa I(2014)Automatic Extraction of Catchphrases from Software License AgreementProceedings of the 2014 Sixth International Conference on Intelligent Human-Machine Systems and Cybernetics - Volume 0210.1109/IHMSC.2014.148(189-193)Online publication date: 26-Aug-2014
https://dl.acm.org/doi/10.1109/IHMSC.2014.148
Palmirani MCeci MRadicioni DMazzei AAshley Kvan Engers T(2011)FrameNet model of the suspension of normsProceedings of the 13th International Conference on Artificial Intelligence and Law10.1145/2018358.2018385(189-193)Online publication date: 6-Jun-2011
https://dl.acm.org/doi/10.1145/2018358.2018385

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