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From Case Law to Ratio Decidendi

Research output: Chapter in Book/Report/Conference proceedingChapter in a book

Original languageEnglish
Title of host publicationLecture Notes in Artificial Intelligence
Subtitle of host publicationNew Frontiers in Artificial Intelligence
EditorsSachiyo Arai, Kazuhiro Kojima, Koji Mineshima, Daisuke Bekki, Ken Satoh, Yuiko Ohta
Publisher or commissioning bodySpringer
Pages20-34
Volume10838
ISBN (Electronic)978-3-319-93794-6
ISBN (Print)978-3-319-93793-9
DOIs
DatePublished - 2018

Abstract

This paper is concerned with the task of automatically identifying legally binding principles, known as ratio decidendi or just ratio, from transcripts of court judgements, also called case law or just cases. After briefly reviewing the relevant definitions and previous work in the area, we present a novel system for automatically extracting ratio from cases using a combination of natural language processing and machine learning. Our approach is based on the hypothesis that the ratio of a given case can be reliably obtained by identifying statements of legal principles in paragraphs that are cited by subsequent cases. Our method differs from related recent work by extracting principles from the text of the cited paragraphs (in the given case) as opposed to the text of the citing paragraphs (in a subsequent case). We conduct our own independent small-scale annotation study which reveals that this seemingly subtle shift of focus substantially increases reliability of finding the ratio. Then, by building on previous work in the automatic detection of legal principles and cross citations, we present a fully automated system that successfully identifies the ratio (in our study) with an accuracy of 72%.

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