Describing Wikimedia Commons images using Wikidata’s structured data enables a wide range of automation tasks, such as search and organization, as well as downstream tasks, such as labeling images or training machine learning models. However, there is currently a lack of structured data-labelled images on Wikimedia Commons.To close this gap, we propose the task of Visual Entity Linking (VEL) for Wikimedia Commons, in which we create new labels for Wikimedia Commons images from Wikidata items. VEL is a crucial tool for improving information retrieval, search, content understanding, cross-modal applications, and various machine-learning tasks. In this paper, we propose a method to create new labels for Wikimedia Commons images from Wikidata items. To this end, we create a novel dataset leveraging community-created structured data on Wikimedia Commons and fine-tuning pre-trained models based on the CLIP architecture. Although the best-performing models show promising results, the study also identifies key challenges of the data and the task.