An Architecture for Extracting Key Elements from Legal Permits

In many countries worldwide, including Austria, the environmental impact of production facilities is strongly regulated leading to authorities issuing a large number of legal permits on this topic. The access of interested parties to these permits is typically supported by search systems that present a structured view of the permits along their key elements, such as issuing authority or their legal basis. In this paper, we present a real-life use case from Austria's Environment Agency, where the extraction of such key elements represents a non-trivial task for laypersons with limited legal knowledge: the heterogeneity of data, complex language, and implicit information hinder the manual data extraction process and can lead to poor quality in data management. Based on an analysis of the use case's main requirements, we propose an architecture for a system to support the extraction of key elements from legal permits by laypersons. The system combines methods and techniques based on Knowledge Graphs / Semantic Web and Machine Learning technologies and aims to be auditable in terms of its operation.