# wink-lexicon

English lexicon useful in NLP/NLU

### [![Build Status](https://api.travis-ci.com/winkjs/wink-lexicon.svg?branch=master)](https://travis-ci.org/winkjs/wink-lexicon) [![Coverage Status](https://coveralls.io/repos/github/winkjs/wink-lexicon/badge.svg?branch=master)](https://coveralls.io/github/winkjs/wink-lexicon?branch=master) [![Gitter](https://img.shields.io/gitter/room/nwjs/nw.js.svg)](https://gitter.im/winkjs/Lobby)

[<img align="right" src="https://decisively.github.io/wink-logos/logo-title.png" width="100px" >](http://winkjs.org/)

The **`wink-lexicon`** is useful in NLP and NLU. It is an internal package of [wink](http://winkjs.org/) and is being used by the following wink packages:

1. [**`wink-ner`**](http://winkjs.org/wink-ner/) — Language agnostic named entity recognizer
2. [**`wink-pos-tagger`**](http://winkjs.org/wink-pos-tagger/) — English Part-of-speech (POS) tagger

<table><tr><td>
    <h3>Use <a href="https://github.com/winkjs/wink-nlp">wink-nlp</a> if your are looking for an integrated NLP package✨</h5>
    <a href="https://github.com/winkjs/wink-nlp">WinkNLP</a> is a <b>developer friendly</b> JavaScript library for Natural Language Processing. Designed specifically to make development of NLP solutions <b>easier</b> and <b>faster</b>, winkNLP is optimized for the right balance of performance and accuracy. The package can handle large amount of raw text at speeds <b>over 525,000 tokens/second</b> for the <b>entire NLP pipeline</b>.
</td></tr></table>

### Installation

Use [npm](https://www.npmjs.com/package/wink-lexicon) to install:

    npm install wink-lexicon --save


### Documentation
Work-in-progress, please stand by!

### Need Help?

If you spot a bug and the same has not yet been reported, raise a new [issue](https://github.com/winkjs/wink-lexicon/issues) or consider fixing it and sending a pull request.

### About wink
[Wink](http://winkjs.org/) is a family of open source packages for **Statistical Analysis**, **Natural Language Processing** and **Machine Learning** in NodeJS. The code is **thoroughly documented** for easy human comprehension and has a **test coverage of ~100%** for reliability to build production grade solutions.

### Copyright & License

**wink-lexicon** is copyright 2017-23 [GRAYPE Systems Private Limited](http://graype.in/).

It is licensed under the terms of the MIT License.

#### Acknowledgement
This also includes **data derived** from [WordNet](http://wordnet.princeton.edu/wordnet/license/) &#169; Princeton University and [fnTBL](http://www.cs.jhu.edu/~rflorian/fntbl/license.html) &#169; Johns Hopkins Whiting School of Engineering.
