My guess is that it's aimed more at the humanities. Hence the GUI. My experience: in the world of humanities text analysis, there are just a ton of Java programs which were funded by some academic grant. Mostly they are closed source, not updated, might have a horrible GUI, and the website is always written in 8 point font.... Don't hate them for what they are....
reminds me a bit of klogg https://github.com/variar/klogg which is more for log files and based off glogg which went dead. it has nice filtering and highlighting type stuff. It's great for live views of log files.
Marginally related, but this is one of the things I'm bullish on ChatGPT for. Too frequently, I've gotten hundreds of lines of malformed textual data that I need to standardize. This is like impossible with REGEX but I can drop it into GPT and it does this wonderfully.
I have no idea how Regex became the standard. The syntax is impossible to remember unless you write regex expressions daily. Most people only rarely need regex so it needs to be relearned every time. It is also incredibly unsatisfying to write (and read).
I tried using ChatGPT (4) for format conversion.
I had a draft yaml file and needed some differently structured json.
Mainly with the same content.
If you just want to change the format it works. If you need more than programming skills it seems too fail duo to the amount of text.
E.g. if you have a list of items and want ChatGPT to generate a meta field which it cannot generate using simple python code it stops after 10 to 20 elements.
Thus at least the cloud version doesn't work so well here.
I also wanted it to help me fill out my i18n file with translations and plural forms. Even thought he got every word correct i needed to split it into multiple requests. Not sure if the api would have worked better (used the web frontend).
For the plural forms I finally added them myself as it was way faster for my natural language than copy pasting all the small chunks. Really hoped for more help there.
Agreed. It works especially well for formatting where semantics matter, such as separating the term and definitions of flashcards. Hard to do with code, but easy with GPT.
The MIT license just gives you permission to use the work as published. Normally that work would be in source form, but there is nothing in the MIT license requiring that. In this case, it seems that the authors chose to release the binaries under the MIT license.
totetsu|2 years ago
Is a good Linux command line tool in the same genre
AdieuToLogic|2 years ago
It is also a good OS-X/FreeBSD command line tool as well.
akoboldfrying|2 years ago
dash2|2 years ago
My guess is that it's aimed more at the humanities. Hence the GUI. My experience: in the world of humanities text analysis, there are just a ton of Java programs which were funded by some academic grant. Mostly they are closed source, not updated, might have a horrible GUI, and the website is always written in 8 point font.... Don't hate them for what they are....
keithnz|2 years ago
neilpa|2 years ago
https://superuser.com/questions/706761/textanalysistool-net-...
internetter|2 years ago
BurnerBotje|2 years ago
osigurdson|2 years ago
dextro42|2 years ago
If you just want to change the format it works. If you need more than programming skills it seems too fail duo to the amount of text.
E.g. if you have a list of items and want ChatGPT to generate a meta field which it cannot generate using simple python code it stops after 10 to 20 elements.
Thus at least the cloud version doesn't work so well here.
I also wanted it to help me fill out my i18n file with translations and plural forms. Even thought he got every word correct i needed to split it into multiple requests. Not sure if the api would have worked better (used the web frontend).
For the plural forms I finally added them myself as it was way faster for my natural language than copy pasting all the small chunks. Really hoped for more help there.
Liftyee|2 years ago
atesti|2 years ago
bramblerose|2 years ago
brchn|2 years ago
sebazzz|2 years ago
andix|2 years ago