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arnaudmiribel

35 karma · joined February 21, 2019

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arnaudmiribel··on Structuring Legal Documents with Deep Learning
That's totally right. In our original dataset, 45% of decisions have no explicit titles splitting categories, so it's quite difficult to read them.

We classify each paragraph as one of "facts", "pleas", "grounds", etc. in order to generate a table of contents and help users read a court decision more easily. For example, one may want to directly jump to the operative part of the judgement: he just has to click on the "Operative part" of the table of contents, instead of having to read all the decision and guess when that part actually starts.

It's indeed intended to improve our users experience on Doctrine's website https://www.doctrine.fr (legal search engine).

arnaudmiribel··on Structuring Legal Documents with Deep Learning
Good point! Some French jurisdictions are working on it: see "Towards more understandable decisions from the Court of Cassation (finally)" published last week https://bit.ly/2Ivhcgf
arnaudmiribel··on Structuring Legal Documents with Deep Learning
Currently, not all this data is freely available on the net. Doctrine has actually established partnerships with many French jurisdictions to collect court decisions and publishes them on https://www.doctrine.fr :)