Part of Speech Tagging using TextBlobTextBlob module is utilized for creating programs to analyse text. One of the most powerful features that are included in the TextBlob module can be its Part of Speech tagging. First, we will install TextBlob and run these commands: It will then run TextBlob in addition to downloading the needed NLTK corpora. The installation process above can take a long time because of the huge number of chunkers, tokenizers, other algorithms, as well as all of the corpora that need to be downloaded. In corpus linguistics, part-of-speech tag (POS tagging, also known as PoS tagging or POST) is also known as Grammatical Tagging or Disambiguation of the word category. Here’s a list of the tags, with their meaning, and some examples: CC : it is a coordinating conjunction CD : it is a cardinal digit DT : it is the determiner EX : it is existential there (For example: “there is” … think of it like “there exists”) FW : it is a foreign word IN : it is a preposition/subordinating conjunction JJ : this is an adjective for example: ‘big’ JJR : this is an adjective, for example: comparative ‘bigger’ JJS : this is an adjective, for example: superlative ‘biggest’ LS : it is a list marker for example: 1) 2) MD : it is a modal for example: could, will NN : it is a noun, for example: singular ‘desk’ NNS : it is a noun, for example: plural ‘desks’ NNP : it is a proper noun, for example: singular ‘Harrison’ NNPS : it is a proper noun, for example: plural ‘Americans’ PDT : it is a predeterminer for example: ‘all the kids’ POS : it is a possessive ending parent’s PRP : it is a personal pronoun, for example: I, he, she PRP$ : it is a possessive pronoun, for example: my, his, hers RB : it is a adverb for example: very, silently, RBR : it is a adverb, for example: comparative better RBS : it is a adverb, for example: superlative best RP : it is a particle give up TO : to go, for example: ‘to’ the store. UH : it is a interjection for example: errrrrrrrm VB : it is a verb, for example: base form take VBD : it is a verb, for example: past tense took VBG : it is a verb, for example: gerund/present participle taking VBN : it is a verb, for example: past participle taken VBP : it is a verb, for example: sing. present, non-3d take VBZ : it is a verb, for example: 3rd person sing. present takes WDT : it is a wh-determiner for example: which WP : it is a wh-pronoun, for example: who, what WP$ : it is a possessive wh-pronoun for example: whose WRB : it is a wh-adverb for example: where, when Code: Output: [('Jack', 'NNP'), ('Jill', 'NNP'), ('and', 'CC'), ('Bill', 'NNP'), ('are', 'VBP'), ('living', 'VBG'), ('in', 'IN'), ('America', 'NNP'), ('Jack', 'NNP'), ('use', 'NN'), ('to', 'TO'), ('go', 'VB'), ('for', 'IN'), ('running', 'VBG'), ('every', 'DT'), ('morning', 'NN'), ('but', 'CC'), ('he', 'PRP'), ('got', 'VBD'), ('fever', 'RB'), ('last', 'JJ'), ('night', 'NN'), ('therefore', 'VBD'), ('her', 'PRP$'), ('will', 'MD'), ('not', 'RB'), ('be', 'VB'), ('going', 'VBG'), ('for', 'IN'), ('running', 'VBG'), ('tomorrow', 'NN'), ('this', 'DT'), ('would', 'MD'), ('be', 'VB'), ('his', 'PRP$'), ('first', 'JJ'), ('time', 'NN'), ('of', 'IN'), ('breaking', 'VBG'), ('his', 'PRP$'), ('running', 'VBG'), ('streak', 'NN'), ('jill', 'NN'), ('is', 'VBZ'), ('a', 'DT'), ('school', 'NN'), ('teacher.he', 'NN'), ('believes', 'VBZ'), ('in', 'IN'), ('meditation', 'NN'), ('he', 'PRP'), ('practice', 'NN'), ('mediating', 'VBG'), ('daily', 'RB'), ('for', 'IN'), ('an', 'DT'), ('hour', 'NN'), ('bill', 'NN'), ('is', 'VBZ'), ('a', 'DT'), ('fun', 'NN'), ('guy', 'NN'), ('for', 'IN'), ('him', 'PRP'), ('laughing', 'VBG'), ('is', 'VBZ'), ('the', 'DT'), ('best', 'JJS'), ('medicine', 'NN')] In essence, the purpose of the POS tagger is to assign the linguistic (mostly grammar-related) details to the sub-sentential unit. They are also known as tokens, and, the majority of times, they correspond to symbols and words (e.g., punctuation). |
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