Events Matter: Extraction of Events from Court Decisions

Erwin Filtz, María Navas-Loro, Cristiana Santos, Axel Polleres, Sabrina Kirrane

Publication: Chapter in book/Conference proceedingContribution to conference proceedings

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The analysis of court decisions and associated events is part of the daily life of many legal practitioners. Unfortunately, since court decision texts can often be long and complex, bringing all events relating to a case in order, to understand their connections and durations is a time-consuming task. Automated court decision timeline generation could provide a visual overview of what happened throughout a case by representing the main legal events, together with relevant temporal information. Tools and technologies to extract events from court decisions however are still underdeveloped. To this end, in the current paper we compare the effectiveness of three different extraction mechanisms, namely deep learning, conditional random fields, and rule-based method, to facilitate automated extraction of events and their components (i.e., the event type, who was involved, and when it happened). In addition, we provide a corpus of manually annotated decisions of the European Court of Human Rights, which shall serve as a gold standard not only for our own evaluation, but also for the research community for comparison and further experiments.
Original languageEnglish
Title of host publicationLegal Knowledge and Information Systems
Editors Serena Villata, Jakub Harašta, Petr Křemen
Place of PublicationOnline Event
Pages33 - 42
Publication statusPublished - 2020

Austrian Classification of Fields of Science and Technology (ÖFOS)

  • 102
  • 102001 Artificial intelligence
  • 102015 Information systems
  • 502050 Business informatics
  • 505002 Data protection

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