The failure analysis (FA) of microelectronics is a complex endeavor that extends across electronics, device physics, and material science. As such, the jargon of this field is a rich nomenclature capturing a lot of information and final failure analysis reports are written in this spirit. Therefore, knowledge extraction from a corpus of FA documents needs to take into account the field-specific terms and associations and moreover, their relationships. This is most effectively done by constructing an FA ontology which can be efficiently represented as a knowledge graph. This Master student internship deals with all aspects of the above as well as with modern machine learning methods with the ultimate goal to unlock the knowledge from FA documents with applications in report search and generation.
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