It’s the consequence of translation engines being trained on a corpus that is mainly Spanish and English. Meaning, that most txt in other languages have been translated to either Spanish or english, and those translations are what is used to train contextual inference for translations. It needs a corpus of text of two languages to even attempt translation from A to B. If it doesn’t have enough, it will use bridge languages.

How many texts are there both in Ukrainian and Japanese? Effectively none, so it makes perfect sense to use a bridge language. The issue here is that the context wasn’t properly kept in the bridging, and they should theoretically be able to do that. A buddy I shared my master’s with was Iranian and he explained the semantic context issue to me, he was working on exactly this issue.