Natural Language Toolkit (NLTK)

Language is a key component of our ability to understand each other’s views and this capability is being given to machines today. One way of doing this is through natural language processing (NLP), a branch of artificial intelligence (AI) used widely in AI development services, for instance.

NLP enables machines to understand and respond to text or voice data. AI development services will use NLP in speech recognition, word sense disambiguation, sentiment analysis, and natural language generation. 

These NLP tasks require the use of a wide range of tools and libraries, which are provided by the Python programming language. These tools and libraries can be found in the Natural Language Toolkit.

The Natural Language Toolkit or NLTK is a leading platform for building Python programmes to work with human language data. It is a free, open source and community-driven project and is suitable for linguists, engineers, students, educators, researchers and industry users like a natural language processing company.

The platform provides interfaces that are easy to use to over 50 corpora and lexical resources as well as a suite of text processing libraries. The latter is used for classification, tokenisation, stemming, tagging, parsing and semantic reasoning.

NLTK also provides wrappers for industrial-strength NLP libraries and has an active discussion forum and a hands-on guide for the introduction of programming fundamentals.

There are several things a Natural Language Processing company can do with NLTK. The programme can be used to tokenise and tag text, identify named entities, and display a parse tree.

Widely used today, the beginning of NLTK can be traced back to 2001. Back then, Steven Bird was teaching CIS-530 at the University of Pennsylvania and hired Edward Loper, his start student from the previous offering of the course, as his teaching assistant.

Bird and Loper worked on a plan for developing software infrastructure for NLP teaching that could be easily maintained over time. Loper wrote up the plan and they started working on it immediately. Version 0.2 was released in September 2001.

In 2005, the developers created NLTK-Lite, which was a lightweight version of NLTK. It was simpler and faster than the Natural Language Toolkit. Version 0.9 of NLTK-Lite provided the same functionality of NLTK, but did not impose a heavy burden on the programmer like older versions of NLTK did.

Standard Python objects were adopted instead of custom NLP versions wherever possible so that students learning to programme for the first time would be learning to do so in Python with some useful libraries as opposed to learning to programme in NLTK.

When NLTK-Lite reached version 1.0 in mid-2009, it took over the original NLTK name and became NLTK 2.0

At present, the NLTK project is led by Steven Bird and Lilian Tan, while Dan Garrette maintains semantics, Peter Ljunglöf maintains parsing, Joel Nothman maintains metrics, Mikhail Korobov maintains Python 3, Steven Bird maintains releases, and Alexis Dimitriadis maintains NLTK-users.

Natural Language Processing with Python is a valuable book written by Steven Bird, Ewan Klein and Edward Loper, the creators of NLTK and any Natural Language Processing company will find great use of it.

It is a practical introduction to programming for language processing and guides the readers through the fundamentals of writing Python programmes, working with corpora, categorising text, and analysing linguistic structure.

While the NLTK developers originally planned to produce a second edition, they decided against it.

According to the creators, NLTK will be supported for as long as possible. The toolkit will be supported while the NLTK book, which was published in 2009, is still in active use and the developers are employed in NLP research and teaching.

AI development services as well as a natural language processing company can thus rely on NLTK for short-term as well as long-term projects.

NLTK is an open source project, which means it depends on the efforts of volunteers. Students and teachers donate code and volunteers are encouraged to get involved. Anyone interested in contributing can consult the NLTK list of development priorities and submit a pull request.

Since it is an open source software, the source code is distributed under the terms of the Apache License Version 2.0 and documentation is distributed under the terms of the Creative Commons Attribution-Noncommercial-No Derivs Works 3.0 United States license.

NLTK corpora are distributed under various licenses, which are documented under the respective README files.

In terms of further development, the platform is undergoing continual development, with new models added to the platform and existing modules improved.