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 weremanually annotated with tags for Person, Location, and Organisation. Subsequently, they applied each NER toolto both the raw and corrected OCR outputs, evaluating their performance by comparing the precision, recall, andF1 scores against the manually annotated data.
Institutions
- Karlsruhe Institute of Technology (DE)
- FIZ Karlsruhe – Leibniz Institute for Information Infrastructure (DE)
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2024-12-12
- DOI
- https://doi.org/10.5281/zenodo.14419993
- Primary Topic
- Handwritten Text Recognition Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00