Automatically processing amendments to legislation
ICAIL '95 Proceedings of the 5th international conference on Artificial intelligence and law
Automatic generation of amendment legislation
Proceedings of the 6th international conference on Artificial intelligence and law
An extensive empirical study of feature selection metrics for text classification
The Journal of Machine Learning Research
Processing Normative References on the Basis of Natural Language Questions
DEXA '04 Proceedings of the Database and Expert Systems Applications, 15th International Workshop
Automatic semantics extraction in law documents
ICAIL '05 Proceedings of the 10th international conference on Artificial intelligence and law
Automatic classification of provisions in legislative texts
Artificial Intelligence and Law - AI & law in eGovernment and eDemocracy part II
Automated Detection of Reference Structures in Law
Proceedings of the 2006 conference on Legal Knowledge and Information Systems: JURIX 2006: The Nineteenth Annual Conference
NLP-based metadata extraction for legal text consolidation
Proceedings of the 12th International Conference on Artificial Intelligence and Law
NLP-based extraction of modificatory provisions semantics
Proceedings of the 12th International Conference on Artificial Intelligence and Law
Automatic consolidation of Japanese statutes based on formalization of amendment sentences
JSAI'07 Proceedings of the 2007 conference on New frontiers in artificial intelligence
Model regularity of legal language in active modifications
AICOL-I/IVR-XXIV'09 Proceedings of the 2009 international conference on AI approaches to the complexity of legal systems: complex systems, the semantic web, ontologies, argumentation, and dialogue
Time model for managing the dynamic of normative system
EGOV'06 Proceedings of the 5th international conference on Electronic Government
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In the last few years University of Turin and CIRSFID University of Bologna collaborated to pair NLP techniques and legal knowledge to detect modificatory provisions in normative texts. Annotating these modifications is a relevant and interesting problem, in that modifications affect the whole normative system; and legal language, though more regular than unrestricted language, is sometimes particularly convoluted, and poses specific linguistic issues. This paper focuses on two major aspects. First, we explore a combination between parsing and regular expressions; to the best of our knowledge, such hybrid strategy has never been proposed before to tackle the problem at hand. Secondly, we significantly extend past works coverage (basically focussed on substitution, integration and repeal modifications) in order to account for further twelve modification kinds. For the sake of conciseness, we fully illustrate and discuss only few modification types that are more relevant and interesting: suspension, prorogation of efficacy, postponement of efficacy and exception/derogation. These sorts of modifications appear particularly challenging, in that modifications in these categories make use of similar linguistic speech acts and verbs, and exhibit strong similarities in the linguistic syntactical patterns, to such an extent that to discern them is difficult for the legal expert, too. We describe the implemented system and report about an extensive experimentation on the new modificatory provisions. Results are discussed in order to improve both system's accuracy and annotation practice.