[1] https://voidfarer.livejournal.com/623.html
You can label it "bad idea" but you can't bring LLMs back in time.
However I think they have a good excuse for 'Why didn't it ever have the impact that LLMs are having now?': lack of data and lack of compute.
And it's the same excuse that neural networks themselves have: back in those days, we just didn't have enough data, and we didn't have enough compute, even if we had the data.
(Of course, we learned in the meantime that neural networks benefit a lot from extra data and extra compute. Whether that can be brought to bear on Cyc-style symbolic approaches is another question.)
Cyc was able to produce an impact, I keep pointing to MathCraft [1] which, at 2017, did not have a rival in the neural AI.
[1] https://www.width.ai/post/what-is-beam-search
It is possible to even have 3-gram model to output better text predictions if you combine it with the beam search.
Google has its own Knowledge Graph, with billions of daily views, which is wider but more shallow version of Cyc. It is unclear if LLM user facing impact surpassed that project.