NLTK

NLTK, the Natural Language Toolkit, is a widely used open-source Python library and collection of linguistic resources for building natural language processing (NLP) applications. It provides easy-to-use interfaces to over 50 corpora and lexical resources, along with a comprehensive suite of text processing libraries for classification, tokenization, stemming, tagging, parsing, and semantic reasoning. The project also includes helpers for accessing corpus data, a rich API for linguistic annotations, and educational tutorials and examples.

NLTK's core components cover core NLP tasks: tokenization, stemming and lemmatization, part-of-speech tagging, chunking, parsing (including constituency and dependency parsing), and named entity recognition. It also provides interfaces to comprehensive lexical databases such as WordNet, and tools for exploring corpora, building frequency distributions, concordances, and simple visualization of parse trees. It ships with command-line and programmatic data download via nltk.download() so users can obtain datasets such as the Brown, Gutenberg, Reuters, and Inaugural Address corpora, plus WordNet, stopword lists, and more.

NLTK originated at the University of Pennsylvania, developed by Steven Bird, Ewan Klein, and Edward Loper, and first released in 2001. It has become a staple in NLP education and research thanks to extensive documentation and an accompanying book, Natural Language Processing with Python. While suitable for teaching and prototyping, NLTK is generally not optimized for production-scale NLP and is often complemented by faster libraries in real-world deployments.