- cross-posted to:
- [email protected]
- [email protected]
- cross-posted to:
- [email protected]
- [email protected]
Source: https://front-end.social/@fox/110846484782705013
Text in the screenshot from Grammarly says:
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To develop these data sets, we sample snippets of text at random, disassociate them from a user’s account, and then use a variety of different methods to strip the text of identifying information (such as identifiers, contact details, addresses, etc.). Only then do we use the snippets to train our algorithms-and the original text is deleted. In other words, we don’t store any text in a manner that can be associated with your account or used to identify you or anyone else.
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should’ve used grammarly
They’d’ve gotten it wrong too. Prepositions and postpositions are their own category of linguistic hell, especially in idioms and phrasal verbs.
They’dn’t’ve necessarily gotten it wrong. With a big enough dataset, an ML tool should be pretty accurate, at least in that it will make the same choices as most people have made in their writing.
Apostrophe mistakes aside, no native speaker would stack contractions like this. There’s an upper limit of three words in a single contracted form. It would be “They wouldn’t’ve gotten” or “They’d not’ve gotten.”
ML tools don’t write grammatically correct complex sentences precisely because their training sets contain too many discrepancies. They may learn how to apply prescriptive rules consistently one day, perhaps even one day soon, but this is not that day.
Who says there’s an upper limit? You might not be one of those people, but I’m.
Also, that’ll teach me to try to write tricky comments while also doing other things. Fixed.
Muphry’s Law strikes again.
LOL! How did I not know about this? Thanks!
Well, linguists say it. But you do you, friend.
LOL! Right there with you. If I had a dollar for every time this happens to me…. 😄