Named Entity Recognition for digitised archival documents in German

This paper presents an experiment that evaluates the effectiveness of two different Named Entity Recognition (NER) tools at extracting entities directly from the output of an Optical Character Recognition (OCR) workflow. The authors initially developed a test dataset comprising both raw and corrected OCR outputs, which were manually annotated with tags for Person, Location, and Organisation. Subsequently, they applied each NER tool to both the raw and corrected OCR outputs, evaluating their performance by comparing the precision, recall, and F1 scores against the manually annotated data.