Abstract
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.
We gratefully acknowledge Enterprise Ireland’s Governance Risk and Compliance Technology Centre Initial Grant CC-2011-2601-B.
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Isemann, D., Ahmad, K., Fernando, T., Vogel, C. (2013). Temporal Dependence in Legal Documents. In: Yin, H., et al. Intelligent Data Engineering and Automated Learning – IDEAL 2013. IDEAL 2013. Lecture Notes in Computer Science, vol 8206. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-41278-3_60
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DOI: https://doi.org/10.1007/978-3-642-41278-3_60
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