Lemmatization reduces words to their base or dictionary form (lemma). For example, "running", "ran", and "runs" all become "run". This groups related word forms together for more meaningful analysis.
Apply lemmatization after tokenization to consolidate word variants. Particularly useful for topic modeling and keyword extraction where grouping related forms improves interpretability.
Learn More: spaCy Lemmatization Guide