Temporal Dependence in Legal Documents

Abstract

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.

TempCourt: evaluation of temporal taggers on a new corpus of court decisions

“…While the first two types of documents received dedicated attention, narratives in case law were assimilated to narratives present in news. An alternative approach proposed by Isemann et al (2013) used both Named Entity Recognition (NER) and temporal processing to extract temporal dependencies from regulations with no narrative-structure. The authors also described some of the recurrent pitfalls temporal taggers have to deal with, such as the confusion between legal references (e.g., ‘Directive 2009 /28/EC’) and actual dates, as shown in Table 2, or the distinction between episodic and generic events—the former referring to a specific moment (e.g., ‘the rescission of the contract was done on 7 December 2017’) and the latter referring to an event in general truths, laws, rules, or expectations (e.g., ‘Every rescission implies the following actions’).…”