i think you are assuming that what is happening under the hood is that a human-inputted sentence is being parsed into a grammar. it is not.
"I took the water bottle out of the backpack so that it would be [lighter/handy]"
What is lighter and what is handy? No amount of stochastic language manipulation gets you the answer, you need to understand some rudimentary physics to answer the question, and as a precondition, you need a grammar or ontology.
It sounds like you're saying "It doesn't work because it can't work", but you haven't actually shown that it doesn't work.
In the example above it guesses wrongly, but again this is not surprising because it can't possibly get the right answer (other than by chance). The solution here cannot be found by correlating syntax, you can only answer the question if you understand the meaning of the sentence. That's what these schemas are constructed for.
edit: Retracted a test where it seemed to know which to select, because further tries revealed it was random.
edit: I did some more tries, and it does seem to be somewhat random, but the way it continues the sentence does seem to indicate that it has some form of operational model. It's just hard to prompt it in a way that it is "forced" to reveal which of the two it's talking about. Also, it seems to me its coherence range is too short in GPT-2. I would love to try this with GPT-3.