Publication
Predicting the Law Area and Decisions of French Supreme Court Cases
Marcos Zampieri Octavia-Maria Sulea
In: Proceedings of the INTERNATIONAL CONFERENCE RECENT ADVANCES IN NATURAL LANGUAGE PROCESSING 2017. Recent Advances in Natural Language Processing (RANLP-17), September 2-8, Varna, Bulgaria, INCOMA Ltd, 2017.
Abstract
In this paper, we investigate the application
of text classification methods to predict
the law area and the decision of cases
judged by the French Supreme Court. We
also investigate the influence of the time
period in which a ruling was made over the
textual form of the case description and the
extent to which it is necessary to mask the
judge’s motivation for a ruling to emulate
a real-world test scenario. We report results
of 96% f1 score in predicting a case
ruling, 90% f1 score in predicting the law
area of a case, and 75.9% f1 score in estimating
the time span when a ruling has
been issued using a linear Support Vector
Machine (SVM) classifier trained on lexical
features.