Also, "acquired" could simply mean that the museum paid money to a third party to, well, acquire the piece(s) in question while not inquiring too deeply into how said third party came into possession of the objects that they sold.
They got photos to the leading professor in Ogham who translated it for them.
I happened to mention this on HN a few months ago in relation to something or other, and a commenter replied to me to explain that that translation was no longer sound, and the current understanding was that the tablet said something completely different instead!
(Found the link they gave! https://www.babelstone.co.uk/Blog/2008/05/throng-of-fifty-wa...)
So the done thing in translation is to choose some existing translation as a "gold standard" and use that one, without any assumptions of how good or bad it is. Sometimes there's an attempt to rate translations by polling humans but that can not be easily done at scale and certainly not at web-scale, as in LLMs (the modern de facto standard for automatic translation as far as I can tell; I haven't been watching the field closely lately).
The same logic is applied to metrics like BLEU and ROUGE scores, used to measure the goodness of a translation. The general idea is that you choose a translation to be the "gold standard" and then compare the n-grams in the gold standard, and the automatic translation, for overlap.
It's a very crude and imperfect measure and it's one reason why, in practice, we have no idea how good automatic translations are especially now that automatic translation systems are deployed and working every day with millions of input and output texts that nobody can reasonably be expected to evaluate.
In any case just because there's no fixed opinion on what is a good translation, doesn't mean an LLM can't be used to produce one. It probably will. Assuming I understand your point better now, I agree that this is going to cause trouble down the line.
(I think I just said "triage" in a lot more words, to be honest).
No problem marking them as machine translated and keeping track of which have been spot-checked by experts either.
Indeed, one of the thing you'd probably like the translators to do is identify rare or unique words that can be added to our existing knowledge of these languages.
It would be really neat to set up something like a wiki populated with the existing translations and machine translations done via LLM, and to periodically re-train the LLM on all the newly manually verified translations and automatically re-run the machine translations after. The whole thing could move incrementally toward high quality output.