NLTK (Natural Language Toolkit) is a leading platform for building Python programs to work with human language data. It provides easy-to-use interfaces to over 50 corpora and lexical resources such as WordNet, and a suite of text processing libraries for various tasks in Natural Language Processing (NLP).

Features

• Text processing libraries for classification, tokenization, stemming, tagging, parsing, and semantic reasoning.
• Wrappers for industrial-strength NLP libraries.
• An active discussion forum for users to discuss and resolve issues.
• A hands-on guide introducing programming fundamentals alongside topics in computational linguistics, plus comprehensive API documentation.

Use Cases

NLTK is suitable for a wide range of users including linguists, engineers, students, educators, researchers, and industry users. Some of the things you can do with NLTK include:

• Tokenize and tag text: Break down text into words, phrases, symbols, or other meaningful elements (tokens) and assign parts of speech to each token (tagging).
• Identify named entities: Recognize and categorize words that represent proper nouns (named entities) such as person names, organization names, locations etc.
• Display a parse tree: Visualize the grammatical structure of a sentence.

Additional Information

NLTK has been praised as a wonderful tool for teaching and working in computational linguistics using Python, and an amazing library to play with natural language. The creators of NLTK have also written a book titled “Natural Language Processing with Python” which provides a practical introduction to programming for language processing. The online version of the book has been updated for Python 3 and NLTK 3.