About 3 months ago, we had a discussion here, with no result To keep it short:
*You need to install the source language spell checker and the word must be inside the dictionary.
Up to now there were no really suitable workarounds presented. Is there any kind of hope that this very basic point will function in the very near future?
Add the apostrophes to the "Do not match" list in Edit > Preferences > Memory tab. No spellchecker dictionary is needed.
It works in the CTE 2018 Akua version during automatic matching, both with single word and multi-word entries.
Here, "accise" is recognized, "autres" not.
Here, "experience" is not recognized.
You mean in the apostrophe characters in the middle of the words - not quotes. In this case, the straight apostrophe works with the "Prefix matching" option for the glossary enabled.
This works sometimes, but not always
There are remaining the same problems as in the first posting, only that no spellchecker is necessary, plus:
If you wish to keep exactness of your glossary terms, that is, no prefix matching, just provide an exact term (with the apostrophe too) in your glossary, as a standalone term or source side synonym.
In the end, we're not talking about an exotic Zulu dialect. French is besides English and German one of the most common working languages in the EU, while another case, Italian, is at least an official language of the EU. Perhaps I have a too naive view on finding a simple string (term) inside another string (the segment) and this point is really hard to fix, but on the other hand side this apostrophe problem is rather unique.
When I provide a prefix matching solution to increase the fuzziness, you complain about the fuzziness. When I suggest keeping the glossary terms exact, you complain about them being just exact.
Perhaps, another solution will be figured out in the future although it might require checking each segment word for all the variants of apostrophes. I am not sure other users might accept the speed penalty for such an complex word analysis. Probably some neural network approaches would solve your problem.
> In the end it is „just“ about separating words with apostrophes between them and counting/considering them as two (CT counts them as one, BTW).
So how would you separate and count the words such as can't, don't, shouldn't etc?