Shift-of-Perspective Identification Within Legal Cases 
Proceedings of the 3rd Workshop on Automated Detection, Extraction and Analysis of Semantic Information in Legal Texts
Arguments, counter-arguments, facts, and evidence obtained via previous court case transcripts are of essential need for individuals handling legal scenarios. Therefore, the process of automatic information extraction from court case transcripts can be considered to be of significant importance. This study is focused on the identification of sentences in court case transcripts which convey different perspectives on the same 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 such as the detection of counter arguments and identification of opponent parties in a court case.
Keywords: Natural Language Processing | Machine Learning / Deep Learning | Semantic Similarity | Semantic Analysis | Sentiment Analysis | Information Extraction |