A Prolog-based media search engine

I am currently carrying out an internship project consisting in a visual search engine. This made me think of how Google handled its image searches using the names and the descriptions of images on the web to match with the queried words. Here, images are only associated with clouds of words. So I thought, wouldn't it be better if they were associated with meaningful sentences that describe their content?

Prolog is in my opinion the perfect way to do this. We would create a knowledge base in the form of Prolog statements like height(img.jpg, 500). , shows(tree.png, tree). , uniform_background(tree.png). , background_color(tree.png, white). , etc. The downside is this would be a huge amount of work to do, so this task would probably have to be done collaboratively by the community of users (or Santa's dwarves). Then a query could be for example: shows(X, tree), background_color(X, white). and Prolog would answer that X is tree.jpg. The name of the images would in fact be their URL on the web and of course the search engine would be provided some rules to make deductions on statements.

Associated with a very good language analysis AI, this could allow users to make a search in the form of real sentences like "photo of a tree in northern England and a sunset in the background" and get very accurate results − better than if that sentence had been queried in a Google Image search. This could also help machine learning: bots would be able to make the text search they want, and use the results to learn how to associate an image with a statement regarding this image. In turn they would be able to generate statements on new images.