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              <p>After a brief introduction of the Knowledge Graph (KG) technology, a subfield of symbolic AI used to represent and manage semantic information, this article is devoted to quality assessment, emphasizing the importance of developing trustworthy AI in such knowledge-based systems, particularly in safety-critical applications. In this context, we remind several metrics or methods that can be applied to KGs, along with examples of their implementation in the context of digital NOTAMs (Notice To AirMen) illustrated by the HLIF2024 Hackathon.</p>
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