![]() ![]() In this article, we’ll use some more advanced topics, such as Machine Learning algorithms and some stuff about grammar and syntax. The idea is to be able to extract “hidden” information from our text and also enable future use of Lemmatization, a text normalization tool that depends on PoS tags for correction. In this article, following the series on NLP, we’ll understand and create a Part of Speech (PoS) Tagger. unknown word-tag pairs) which were incorrectly tagged by the original Viterbi POS tagger and got corrected after your modifications.Time to dive a little deeper onto grammar. ![]()
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