Abstract
Legal Judgement Prediction (LJP) is the task of automatically predicting the outcome of a court case given only the case document. During the last five years researchers have successfully attempted this task for the supreme courts of three jurisdictions: the European Union, France, and China. Motivation includes the many real world applications including: a prediction system that can be used at the judgement drafting stage, and the identification of the most important words and phrases within a judgement. The aim of our research was to build, for the first time, an LJP model for UK court cases. This required the creation of a labelled data set of UK court judgements and the subsequent application of machine learning models. We evaluated different feature representations and different algorithms.
Our best performing model achieved: 69.05% accuracy and 69.02 F1 score. We demonstrate that LJP is a promising area of further research for UK courts by achieving high model performance and the ability to easily extract useful features.
Our best performing model achieved: 69.05% accuracy and 69.02 F1 score. We demonstrate that LJP is a promising area of further research for UK courts by achieving high model performance and the ability to easily extract useful features.
Original language | English |
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Pages | 204-209 |
Number of pages | 6 |
DOIs | |
Publication status | Published - 20 Apr 2020 |
Keywords
- Legal judgement prediction
- feature extraction
- legal calculus
Profiles
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Beatriz De La Iglesia
- School of Computing Sciences - Professor & Head of School
- Norwich Institute for Healthy Aging - Member
- Norwich Epidemiology Centre - Member
- Data Science and AI - Member
Person: Research Group Member, Research Centre Member, Academic, Teaching & Research