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Research project

ADELE - Analytics for DEcision of LEgal cases

Project ADELE was premised on the ongoing paradigm shift towards cognitive computing and human-centered AI which is transforming many socio-economic activities, including justice.

This project was funded by the European Union’s Justice Programme (2014-2020).

The project applied legal analytics (LA) – a blend of data science, machine learning and natural language processing techniques – to judicial decisions.

ADELE had to main goals: (1) develop methods to extract knowledge and engage in outcome predictions, and therefrom (2) build a pilot tool to support legal research and decision-making processes in the judiciary.

The project analysed four datasets of judgments respectively of Italian and Bulgarian case law in the fields of Intellectual Property, and Unfair Commercial Practices (WP2). Annotation guidelines were developed and used to tag the datasets. Domain-specific ontologies and citation networks were built. In WP3 tagged documents were processed with machine learning algorithms to extract legal arguments and predict possible outcome of new cases.

Two German datasets were collected and used as a language transferability test. WP4 developed a pilot tool embedding knowledge extraction and outcome prediction functionalities. 

Check out the pilot tool to support activities of justices in the Italian and Bulgarian courts.

These novel solutions have a strong impact on the efficacy and transparency of judicial decision-making by developing automated means that enhance the understanding of the law, facilitate judicial tasks and reduce the courts’ workload. The outcomes of ADELE are expected to contribute to developing a trustworthy AI by producing ethical and robust LA methods for the judiciary and will foster scientific debate on the use of AI technologies in the legal field.

More scientific publications of the project.

The team

Group members

External Partners

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