Yes, extractive QA is one of the improvements beyond the "minimalist implementation" from the article. In our lingo, we'd say that's another way to create a deterministic quotation.

So far, we haven't found extractive QA (or any other technique) to significantly improve overall answer quality when compared to matching sub-string similarity. (I'd be interested to hear if you have different experience!)

There aren't a lot of applications can purely be solved with substrings of source documentation, so having both LLM prose and quotations in the answer provides benefit (eg ability to quote multiple passages). Now, we can modify the constrained generation side of things to allow for these but that gets complicated. Or, it can be done with recursive calls to the LLM, but that again requires some kind of DQ check on top.

Ultimately, both styles seem to perform similarly - and suffer from the same downsides (choosing the wrong quote and occasionally omitting useful quotes).

(Good writeup by the way, I've forwarded it to my team, thanks!)