- Generating exception structures for legal information serving
- 7th International Conference on Artificial Intelligence and Law: ICAIL-99
- Book/source title
- The seventh International Conference on Artificial Intelligence and Law: ICAIL-99: proceedings of the conference: June 14-18, 1999, the University of Oslo, Norway
- Pages (from-to)
- New York: The Association for Computing Machinery
- Document type
- Conference contribution
- Faculty of Law (FdR)
Faculty of Social and Behavioural Sciences (FMG)
- Psychology Research Institute (PsyRes)
More and more legal information is available in electronic form, but traditional retrieval mechanisms are insufficient to answer questions and legal problems of most users. In the ESPRIT project CLIME we are building a “Legal Information Server” (LIS), that not only retrieves all relevant norms for a user's query, but also applies them, giving the normative consequences of the 'situation' presented in the query. Typically, these queries represent very general and underspecified cases. Underspecification may lead to 'overlooking' of relevant norms, in particular those norms that directly change the legal status of a case: exceptions. Most exceptions in legislation however, are implicit, i.e. will only be detected after trying all norms for a particular case and resolving conflicts between applicable norms. For LISs we suggest to make the exception relations between norms explicit in off-line mode, so that we can use these exception structures to warn users about potential exceptions to their queries.
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