We audited 14,512 heritage-site photos with a vision model. The "trustworthy" sources were the dirtiest.

We run Kahve Tabela, an open atlas of 32,000+ registered heritage sites in Türkiye — castles, ancient cities, mosques, museums. Like everyone building a dataset on a budget, we filled the photo gaps from the usual open sources: Wikipedia article images, Wikimedia Commons geosearch, Google Places, Mapillary, the national heritage inventory.

Then a reader reported that a photo on one of our pages showed the wrong building. We checked. They were right. So we asked the obvious question nobody budgets for: how many of our 14,512 photos actually show the place they claim to show?

We put every single one through a local vision model (Qwen3-VL 30B, MLX, one Mac Studio, no API bill). Two findings — one about the sources, one about the audit itself — and the second one is the reason to read this.

Finding 1: error rate is a property of the SOURCE

First pass: show the model the photo, the place name, the province, and ask "could this photo belong to this place?"