Tasks and difficulties inherent in the largely open problem of temporal information extraction from legal text are outlined. We demonstrate the efficacy of tools and concepts available "off-the-shelf" and suggest refinements for such applications. In particular, the frequent references between regulatory texts have to be addressed as a separate named entity recognition task that bears relevance to an analysis of the temporal ordering of legislation. A regular expression-based approach as a robust first step towards addressing this problem is tested. © 2013 Springer-Verlag.
CITATION STYLE
Isemann, D., Ahmad, K., Fernando, T., & Vogel, C. (2013). Temporal dependence in legal documents. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8206 LNCS, pp. 497–504). https://doi.org/10.1007/978-3-642-41278-3_60
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