The process of transforming a word to its base or dictionary form, known as its lemma, to ensure the result is valid.
Lemmatization uses linguistic rules and context to ensure the result is a valid word. For instance, “was” would be lemmatized to “be,” and “better” to “good,” reflecting accurate grammatical relationships.
In localization workflows, lemmatization helps standardize vocabulary across different languages and dialects. By converting various inflected forms of a word to a common base, it enhances translation consistency and improves the performance of tools like translation memory systems and machine translation engines.
Lemmatization relies on Part-Of-Speech tagging and morphological analysis to determine the correct base form of a word. This approach is particularly beneficial in languages with rich inflectional morphology, where words can have numerous forms depending on tense, number, or case.
In the end, this process helps reduce redundancy and ambiguity in translated content, as well as to keep translations clear and consistent.