We don't disagree. A look up table with exact rules is a rules system to me from an NLP/GOFAI perspective. I was aware of how the libraries tend to work because I had often used things like looking up lemmas/word sense/pos in NLTK and Spacy in the past, and I know the libraries code fairly well.

Context today may mean more (e.g. the whole sentence, or string, or the prompt context for an LLM), and obviously context has a meaning in computational linguistics (e.g. "context free grammar"), but the point here is stemmers arbitrary follow the same process without a second stage. If a stemmer encounters "best" and "good" it by definition does not have a stage to use the same lemma for them. Context is just one of those overloaded terms unfortunately.

Lemmatizing, in terms of how it works on simple scenarios (lets imagine reviews) helps to lump those words together and correctly identify the proportion of term frequencies for words we might be interested in more consistently than stemming can. It's still limited by using word breaks like spaces or punctuation ofcourse.