> Is there much in the way of datasets of things that are recognizable but triggering incorrect something-or-other (what is it exactly? Semantic sensations?)

There are some datasets which collect 'hard' examples. One I love for the title alone is "When does dough become a bagel? Analyzing the remaining mistakes on ImageNet" https://arxiv.org/abs/2205.04596#google , Vasudevan et al 2022. The errors can be pretty interesting: https://arxiv.org/pdf/2205.04596#page=18 You can often see why a model might make a mistake and that you would too. (Like that first one of a swing - I would think it's some sort of large "tripod" too because I have no idea if I've ever seen a swing like that.)