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usc-ur OP t1_jc9ss05 wrote

Reply to comment by gargolito in Pyplexity: Useful tool to clean scraped text (better than BS4!) by usc-ur

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

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Aphix t1_jca204m wrote

Mind elaborating?

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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

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