Shift-of-Perspective Identification Within Legal Cases

TL;DR

This paper presents a method for automatically identifying sentences in legal texts that express different perspectives, aiding legal information extraction and analysis of opposing viewpoints in court cases.

Contribution

The study introduces a combined semantic, open information extraction, and sentiment analysis approach for perspective detection in legal opinions, validated with human judges.

Findings

Successfully detects sentences with differing opinions on the same topic.

System demonstrates effectiveness in identifying opposing perspectives in legal texts.

Method can be applied to automate detection of counterarguments and opponent parties.

Abstract

Arguments, counter-arguments, facts, and evidence obtained via documents related to previous court cases are of essential need for legal professionals. Therefore, the process of automatic information extraction from documents containing legal opinions related to court cases can be considered to be of significant importance. This study is focused on the identification of sentences in legal opinion texts which convey different perspectives on a certain topic or entity. We combined several approaches based on semantic analysis, open information extraction, and sentiment analysis to achieve our objective. Then, our methodology was evaluated with the help of human judges. The outcomes of the evaluation demonstrate that our system is successful in detecting situations where two sentences deliver different opinions on the same topic or entity. The proposed methodology can be used to facilitate other information extraction tasks related to the legal domain. One such task is the automated detection of counter arguments for a given argument. Another is the identification of opponent parties in a court case.