What are some popular use cases for the NLTK toolkit in text processing applications?
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Another popular use case is named entity recognition, where the toolkit is utilized to identify and classify named entities such as persons, organizations, and locations in text.
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Other use cases include text classification, machine translation, text summarization, and topic modeling.
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One popular use case for the NLTK toolkit is sentiment analysis, where the toolkit is used to analyze text and determine the sentiment or emotion expressed in it.
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NLTK can also be used for part-of-speech tagging, which involves labeling words in a text with their corresponding part of speech categories, such as nouns, verbs, adjectives, etc.
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