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https://github.com/winkjs/wink-ner
Language agnostic named entity recognizer
https://github.com/winkjs/wink-ner
ner recognize-named-entities wink
Last synced: 2 months ago
JSON representation
Language agnostic named entity recognizer
- Host: GitHub
- URL: https://github.com/winkjs/wink-ner
- Owner: winkjs
- License: mit
- Created: 2018-01-04T13:57:55.000Z (about 7 years ago)
- Default Branch: master
- Last Pushed: 2023-02-27T18:49:38.000Z (almost 2 years ago)
- Last Synced: 2024-09-19T05:44:55.780Z (4 months ago)
- Topics: ner, recognize-named-entities, wink
- Language: JavaScript
- Homepage: http://winkjs.org/wink-ner/
- Size: 1.66 MB
- Stars: 39
- Watchers: 5
- Forks: 10
- Open Issues: 3
-
Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
- Code of conduct: CODE_OF_CONDUCT.md
Awesome Lists containing this project
README
# wink-ner
Language agnostic named entity recognizer
### [](https://travis-ci.org/winkjs/wink-ner) [](https://coveralls.io/github/winkjs/wink-ner?branch=master) [](http://inch-ci.org/github/winkjs/wink-ner) [](https://david-dm.org/winkjs/wink-ner) [](https://david-dm.org/winkjs/wink-ner?type=dev) [](https://gitter.im/winkjs/Lobby)
[
](http://winkjs.org/)
Recognize named entities in a sentence using **`wink-ner`**. It is a smart Gazetteer-based Named Entity Recognizer (NER), which can be easily trained to suite specific needs. For example, the wink-ner can differentiate between `Manchester United` & `Manchester` in a single sentence and tag them as a club and city respectively.
### Installation
Use [npm](https://www.npmjs.com/package/wink-ner) to install:
npm install wink-ner --save
### Getting Started
#### Named Entity Recognition
```javascript
// Load wink ner.
var ner = require( 'wink-ner' );
// Create your instance of wink ner & use default config.
var myNER = ner();
// Define training data.
var trainingData = [
{ text: 'manchester united', entityType: 'club', uid: 'manu' },
{ text: 'manchester', entityType: 'city' },
{ text: 'U K', entityType: 'country', uid: 'uk' }
];
// Learn from the training data.
myNER.learn( trainingData );
// Since recognize() requires tokens, use wink-tokenizer.
var winkTokenizer = require( 'wink-tokenizer' );
// Instantiate it and extract tokenize() api.
var tokenize = winkTokenizer().tokenize;
// Tokenize the sentence.
var tokens = tokenize( 'Manchester United is a football club based in Manchester, U. K.' );
// Simply Detect entities!
tokens = myNER.recognize( tokens );
console.log( tokens );
// -> [
// { entityType: 'club', uid: 'manu', originalSeq: [ 'Manchester', 'United' ],
// value: 'manchester united', tag: 'word' },
// { value: 'is', tag: 'word' },
// { value: 'a', tag: 'word' },
// { value: 'football', tag: 'word' },
// { value: 'club', tag: 'word' },
// { value: 'based', tag: 'word' },
// { value: 'in', tag: 'word' },
// { entityType: 'city', value: 'Manchester', tag: 'word',
// originalSeq: [ 'Manchester' ], uid: 'manchester' },
// { value: ',', tag: 'punctuation' },
// { entityType: 'country', uid: 'uk', originalSeq: [ 'U', '.', 'K' ],
// value: 'u k', tag: 'word' },
// { value: '.', tag: 'punctuation' }
// ]
```
#### Integration with POS Tagging
The `tokens` returned from `recognize()` may be further passed down to `tag()` api of [**`wink-pos-tagger`**](https://www.npmjs.com/package/wink-pos-tagger) for pos tagging.
Just in case you need to assign a specific pos tag to an entity, the same can be achieved by including a property `pos` in the entity definition and assigning it the desired pos tag (e.g. `'NNP'`); the wink-pos-tagger will automatically do the needful. For details please refer to [`learn()`](#learn) api of wink-ner.
```javascript
// Load pos tagger.
var tagger = require( 'wink-pos-tagger' );
// Instantiate it and extract tag api.
var tag = tagger().tag;
tokens = tag( tokens );
console.log( tokens );
// -> [ { entityType: 'club', uid: 'manu', originalSeq: [ 'Manchester', 'United' ],
// value: 'manchester united', tag: 'word', normal: 'manchester united', pos: 'NNP' },
// { value: 'is', tag: 'word', normal: 'is', pos: 'VBZ', lemma: 'be' },
// { value: 'a', tag: 'word', normal: 'a', pos: 'DT' },
// { value: 'football', tag: 'word', normal: 'football', pos: 'NN', lemma: 'football' },
// { value: 'club', tag: 'word', normal: 'club', pos: 'NN', lemma: 'club' },
// { value: 'based', tag: 'word', normal: 'based', pos: 'VBN', lemma: 'base' },
// { value: 'in', tag: 'word', normal: 'in', pos: 'IN' },
// { value: 'Manchester', tag: 'word', originalSeq: [ 'Manchester' ],
// uid: 'manchester', entityType: 'city', normal: 'manchester', pos: 'NNP' },
// { value: ',', tag: 'punctuation', normal: ',', pos: ',' },
// { entityType: 'country', uid: 'uk', originalSeq: [ 'U', '.', 'K' ],
// value: 'u k', tag: 'word', normal: 'u k', pos: 'NNP' },
// { value: '.', tag: 'punctuation', normal: '.', pos: '.' }
// ]
```
### Documentation
Check out the [named entity recognizer API documentation](http://winkjs.org/wink-ner/) to learn more.
### Need Help?
If you spot a bug and the same has not yet been reported, raise a new [issue](https://github.com/winkjs/wink-ner/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-ner** is copyright 2017-20 [GRAYPE Systems Private Limited](http://graype.in/).
It is licensed under the terms of the MIT License.