NLTK is a Rule-based/Statistical Models library and open-source NLP solution. It includes tools for analyzing text, such as tokenization, stemming, lemmatization, and removing stop words, which are all crucial steps in preprocessing for traditional topic modeling like LDA.
NLTK is also noted for having entity extraction models and supports various NLP functions like Part-of-Speech (POS) Tagging and sentence tokenization. It is cited as a Python library used in conjunction with LDA for Long-Form Topic Modeling and in fuzzy matching tasks like Hashtag Normalization.