What is lemmatization in NLP? Define lemmatization, Lemmatization example
Lemmatization
In a language, usually a word is inflected to form new words, especially to mark the distinctions such as tense, person, number, gender, mood, voice, and case. In linguistics, lemmatization is the process of removing those inflections from a word in order to identify the lemma (dictionary form/word). A dictionary word (lemma / root word) is inflected into various words having same base meaning or different meanings by adding one or more morphemes (both free and bound). Through lemmatization, we remove the bound morphemes.
Lemmatization refers to doing things algorithmically with the use of a vocabulary and morphological analysis of words, aiming to remove inflections only and to return the base or dictionary form of a word, which is known as the lemma.
Inflected word → Removal of morphemes → Lemma
Example:
|
Inflected word |
Morphemes |
Lemma |
|
Runs |
‘s’ |
Run |
|
Studies |
‘ies’ |
Study |
|
Opened |
‘ed’ |
Open |
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