Eventually, CL-NLP will provide a comprehensive and extensible set of tools to solve natural language processing problems in Common Lisp.

The goals of the project include the following:

• support for constructing arbitrary NLP pipelines on top of it
• support for easy and fast experimentation and development of new models and approaches
• serve as a good framework for teaching NLP concepts

It comprises of a number of utility/horizontal and end-user/vertical modules that implement the basic functions and provide a way to add own extensions and models.

The utility layer includes:

• tools for transforming raw natural language text, as well as various corpora into a form suitable for further processing
• basic support for language modelling
• support for a number of linguistic concepts
• support for working with machine learning models and a number of training algorithms

The end-user layer will provide:

• POS taggers
• constituency parsers
• dependency parsers
• other stuff (will be added step-by-step, suggestions are welcome)

The project has already reached a stage of usefulness for the primary author: for instance, it supports my current language modelling experiments by providing easy access to treebanks and other utilities.

Yet, it is far from being production-ready. So, if you want to use it for production tasks, expect to bleed on the bleeding edge.

Otherwise, if you want to contribute to developing the toolkit, you're very welcome. Here are a few write-ups to give you the sense of the project and to help get started:

• Writing a POS tagger with CL-NLP
• NLTK series - to be continued, by the way...
• CL-NLP Style Guide

You'll also, probably, need to track the latest version of RUTILS from git.

For CL-NLP to reach v.0.1 that may be considered suitable for limited use by non-contributors, the following things should be finished (work-in-progress):

• implement a comprehensive test-suite and fix all bugs encountered in the process
• describe available models and their quality metrics

• RUTILS
• Closure XML
• DRAKMA
• ZIP
• USERIAL

For development:

• SHOULD-TEST

The license of CL-NLP is Apache 2.0.

Specific models may have different license due to the limitations of the dataset they are built with. Please see a <model>.license file accompanying each model for details.

(c) 2013-2014, Vsevolod Dyomkin [email protected]