The rule-based systems typically apply a workflow of binarisation, vectorisation, the detection of specific structural elements like dashed lines and wedges, optical character recognition (OCR), graph compilation and additional post-processing steps. Every single step in these workflows can be fine-tuned to achieve optimal results. In 2021, Clevert et al. have shown that the openly available rule-based systems surprisingly fail on the common benchmark datasets when slight image perturbations like rotation and shearing are introduced . This lack of robustness is a clear indication that these systems have been overfitted to the benchmark datasets and that there is a need for more diverse benchmark data.