I don't say it's easy, at least from organizational/product-development perspective. But that's basically how every translation website before GT worked: type a word in language A, select language B, get the result(s) from a dictionary, done. In the nineties I had this pocket device: https://i.imgur.com/Yp9yTRL.png which would look up and translate words in 8 languages. Today I have a smartphone which can connect to a datacenter with enormous computing power, but a dictionary lookup is a hard problem?
I think the problem is cultural, not one of engineering.
I can't say I can point to any sort of evidence of this, so take it with a pinch of salt, but my gut feeling is that the people in Google who are responsible for GT are somewhat fanatical about making purely statistical machine translation (and, in particular, deep-learning machine translation, a.k.a. neural machine translation) work. They are most probably perfectly well aware that it is possible to improve their system by using some rule-based fall-backs, or some background knowledge, but they have decided that they dont' want to use those and instead want to do machine translation from scratch and from data only, without any expert input.
As a developer I kind of get it: "we have all this machinery so we won't compromise to use the simple route even if it makes sense short-term; let's improve our product instead". But as a user I'd expect Google to be at least as good as dictionary lookup from two decades ago, and do PL -> RU or PL -> DE instead of PL -> EN -> RU, PL -> EN -> DE when I type in a single word.
Google Translate simply isn’t meant to be used for dictionary lookup, though. If you use it for that then you’re using the wrong tool.
This is like complaining that Word isn’t as good as vi, which is decades old, for text editing. Sure they could bolt a text editor onto Word if they wanted to, but why bother? That’s not what people are looking for when they use the product. And if that’s what you want, there are many other choices that are much better.
