<hi xmlns="http://www.tei-c.org/ns/1.0" style="font-size:11pt">To evaluate segmentation, we developed a methodology that examines text presence in non-intersecting areas of predicted regions and their ground truth, rather than focusing solely on their intersection. Using the model described in (Venglarova, Adam, Balasubramanian, et al. 2024), we compared segmentation results from the Eynollah model (Rezanezhad et al. 2023), the default ANNO corpus segments (Österreichische Nationalbibliothek 2021), and Tesseract (Smith 2009). The comparison was based on a random sample of 250 manually annotated segments. The Eynollah model achieved the highest accuracy (Tab. 1) and we adopt this model for further work. However, the solutions for layout analysis tailored for historical newspapers are quickly evolving at the time of writing this article, and we expect even better results in the near future (Sun et al. 2024; Girdhar, Coustaty, and Doucet 2023).</hi>