Comment by schoen
2 years ago
I think there's some hallucination creeping in here!
(1) This HN discussion is the only Google search result for each of these syllabics strings.
(2) I tried using https://syllabics.atlas-ling.ca/ to transliterate these to Roman letters, and none of these was transliterated in the same way as the GPT-4 output (although the third one is somewhat close).
(3) I searched and found that "hello" in Cree is likely written ᑖᓂᓯ (not ᑌᔭᔭᑎ), while correctly romanized as "tān[i]si".
Your approach is clever, but I think the language model is still ultimately overconfident (and confused) here somehow.
Yeah, for Cree it is definitely more suspect than trustworthy. Another thing I noticed was that on another attempt I actually received different translations, so.. it's hard to say how this is going to be refined to be usable, or if it indeed is at all.
And wow, yes we are all alone on google results for those strings.
EDIT 1: Another thought occurs to me, if it's getting the transliteration right, and not the syllabics, maybe I seperate the tasks and go english -> transliteration -> syllabic. I will have to see if that approach works better.
Another idea might be to use that syllabics site to bring it from transliteration -> syllabic. I noticed that they were correct if translated there.
EDIT 2: By updating the system prompt I was able to get it to translate properly. I had to remind it to be correct!
> I had to remind it to be correct!
It's so funny to encounter the effects of language models producing the highest-probability completions of a prompt, and how those aren't necessarily the same as the most correct completions.
I also saw something like this with people asking GPT models to write poetry, and they wrote mediocre poetry. But then when asked to write good poetry, they wrote better poetry!
Yeah, I found that for that kind of use case you really wanted to remind it. You could even say things like,
If you're in the chat interface you could even do: