Akin to stemming in natural language processing, lemmatizing reduces words to their base form. Unlike stemming, which may produce non-existent words, lemmatization ensures outcomes are actual dictionary words. It involves contextual and morphological analysis to accurately strip inflections, returning the root word, or lemma. This distinction is crucial for semantic processing, as lemmatization preserves the word’s original meaning, making it more suitable for tasks requiring precise language understanding.
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