What is lemmatization in NLP?

Lemmatization in natural language processing (NLP) is the process of reducing words to their base or canonical form, known as the lemma. The lemma is the dictionary form of a word, which represents its morphological root and typically corresponds to the headword entry in a dictionary.

Unlike stemming, which simply removes affixes from words to produce their root forms, lemmatization considers the context and grammatical structure of the word to determine its lemma. This means that lemmatization ensures that the resulting lemma is a valid word found in the language’s vocabulary.

For example, the lemma of the words “am”, “are”, and “is” is “be”, and the lemma of the word “running” is “run”. Lemmatization helps standardize words to their base forms, reducing variant forms and improving text normalization and analysis tasks in NLP, such as text retrieval, information extraction, and sentiment analysis.