Submitted by usc-ur t3_11r45r8 in coolgithubprojects
Comments
usc-ur OP t1_jc9ss05 wrote
A perplexity filter allows to remove sentences by likelihood to a given language model. In there you need to "play" with the parameter or threshold
Aphix t1_jca204m wrote
Mind elaborating?
usc-ur OP t1_jca4ot7 wrote
Sure! The idea is that you create a language model from a given corpus (let's say BNC) and then you use a similarity measure, in this case, perplexity, but can be another one to test how well your sample (sentence) "fits" into the model distribution. Since we assume the distribution is correct, this allows us to identified malformed sentences. You can also check the paper here: https://www.cambridge.org/core/journals/natural-language-engineering/article/an-unsupervised-perplexitybased-method-for-boilerplate-removal/5E589D838F1D1E0736B4F52001150339#article
Aphix t1_jc739fl wrote
Link to GitHub?
usc-ur OP t1_jc73mgl wrote
https://github.com/citiususc/pyplexity . My bad :)
Aphix t1_jc799qb wrote
All good, might want to link the other ones you posted in those other post comments, too (Smarty-GPT, etc) -- most of the time you can just link the GitHub directly from the post here.
usc-ur OP t1_jc7guwj wrote
>All good, might want to link the other ones you posted in those other post comments, too (Smarty-GPT, etc) -- most of the time you can just link the GitHub directly from the post here.
My bad, quite a newbie: https://github.com/citiususc/Smarty-GPT
gargolito t1_jc889m6 wrote
so... what are perplexity filters ?