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Automatic semantics extraction in law documents
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Source International Conference on Artificial Intelligence and Law archive
Proceedings of the 10th international conference on Artificial intelligence and law table of contents
Bologna, Italy
SESSION: Legal knowledge bases 2: legislation table of contents
Pages: 133 - 140  
Year of Publication: 2005
ISBN:1-59593-081-7
Authors
C. Biagioli  ITTIG - CNR, Firenze - Italy
E. Francesconi  ITTIG - CNR, Firenze - Italy
A. Passerini  DSI - Univ. Firenze, Firenze - Italy
S. Montemagni  ILC-CNR, Pisa-Italy
C. Soria  ILC-CNR, Pisa-Italy
Sponsors
: The International Association for Artificial Intelligence and Law
: CIRSFID
Publisher
ACM  New York, NY, USA
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Downloads (6 Weeks): 8,   Downloads (12 Months): 63,   Citation Count: 14
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ABSTRACT

Normative texts can be viewed as composed by formal partitions (articles, paragraphs, etc.) or by semantic units containing fragments of a regulation (provisions). Provisions can be described according to a metadata scheme which consists of provision types and their arguments. This semantic annotation of a normative text can make the retrieval of norms easier. The detection and description of the provisions according to the established metadata scheme is an analytic intellectual activity aiming at classifying portions of a normative text into provision types and to extract their arguments. Automatic facilities supporting this intellectual activity are desirable. Particularly, in this paper, two modules able to qualify fragments of a normative text in terms of provision types and to extract their arguments are presented.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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CITED BY  14
Collaborative Colleagues:
C. Biagioli: colleagues
E. Francesconi: colleagues
A. Passerini: colleagues
S. Montemagni: colleagues
C. Soria: colleagues