Aim: to perform Parts of speech identification and Synonym using Natural Language Processing (NLP) techniques.
Step 1: Import the nltk library.
Step 2: Download the 'punkt', 'wordnet', and 'averaged_perceptron_tagger' resources.
Step 3:Accept user input for the text.
Step 4:Tokenize the input text into words using the word_tokenize function.
Step 5:Iterate through each word in the tokenized text.
• Perform part-of-speech tagging on the tokenized words using nltk.pos_tag.
• Print each word along with its corresponding part-of-speech tag.
• For each verb , iterate through its synsets (sets of synonyms) using wordnet.synsets(word).
• Extract synonyms and antonyms using lemma.name() and lemma.antonyms()[0].name() respectively.
• Print the unique sets of synonyms and antonyms.
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Thus ,the program to perform the Parts of Speech identification and Synonymis executed sucessfully.
React
Typescript
Django
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