That'll just be a training problem (often translation is driven from example texts that have lots of translations, and we have many of these for multi-national orgs like EU, which necessarily don't include a lot of colloquialisms), and the inconsistency isn't found because the models built don't extend all the way out to real world experiences (training) and recognizing text as a real world experience narrative. I think a much deeper network could do better but we don't know how to train them, we take way too long as it is.

I've seen the evolution of translators and there is a big difference in results. We can try more convoluted examples.

Also do you think that every human can parse that contemporary metaphors better?