I find it interesting that the prior probability example always happens to be the one where the prior is correct, while the opposite direction is never given more than half a line. You can very easily turn it around so that an unreasonably large amount of evidence is needed to move a strongly believed wrong prior.

My favourite example is to do that with normal distributions and the posterior ends up as "let's meet in the middle and agree that we both were wrong" -a very low variance posterior with mean right in the middle between prior and data.