Wink Nlp Utils Save
NLP Functions for amplifying negations, managing elisions, creating ngrams, stems, phonetic codes to tokens and more.
wink-nlp-utils
NLP Functions for amplifying negations, managing elisions, creating ngrams, stems, phonetic codes to tokens and more.
Prepare raw text for Natural Language Processing (NLP) using wink-nlp-utils. It offers a set of APIs to work on strings such as names, sentences, paragraphs and tokens represented as an array of strings/words. They perform the required pre-processing for many ML tasks such as semantic search, and classification.
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We recommend using winkNLP for core natural language processing tasks. It performs Tokenization, Sentence Boundary Detection, and Named Entity Recognition at a blazing fast speeds. It supports all your text processing needs starting from Sentiment Analysis, POS Tagging, Lemmatization, Stemming, Stop Word Removal, Negation Handling, Bigrams to Frequency Table Creation and more. WinkNLP features user-friendly declarative APIs for Iteration, Filtering, and Text Visualization, and runs on web browsers. |
Installation
Use npm to install:
npm install wink-nlp-utils --save
Getting Started
The wink-nlp-utils provides over 36 utility functions for Natural Language Processing tasks. Some representative examples are extracting person's name from a string, compose training corpus for a chat bot, sentence boundary detection, tokenization and stop words removal:
// Load wink-nlp-utils
var nlp = require( 'wink-nlp-utils' );
// Extract person's name from a string:
var name = nlp.string.extractPersonsName( 'Dr. Sarah Connor M. Tech., PhD. - AI' );
console.log( name );
// -> 'Sarah Connor'
// Compose all possible sentences from a string:
var str = '[I] [am having|have] [a] [problem|question]';
console.log( nlp.string.composeCorpus( str ) );
// -> [ 'I am having a problem',
// -> 'I am having a question',
// -> 'I have a problem',
// -> 'I have a question' ]
// Sentence Boundary Detection.
var para = 'AI Inc. is focussing on AI. I work for AI Inc. My mail is [email protected]';
console.log( nlp.string.sentences( para ) );
// -> [ 'AI Inc. is focussing on AI.',
// 'I work for AI Inc.',
// 'My mail is [email protected]' ]
// Tokenize a sentence.
var s = 'For details on wink, check out http://winkjs.org/ URL!';
console.log( nlp.string.tokenize( s, true ) );
// -> [ { value: 'For', tag: 'word' },
// { value: 'details', tag: 'word' },
// { value: 'on', tag: 'word' },
// { value: 'wink', tag: 'word' },
// { value: ',', tag: 'punctuation' },
// { value: 'check', tag: 'word' },
// { value: 'out', tag: 'word' },
// { value: 'http://winkjs.org/', tag: 'url' },
// { value: 'URL', tag: 'word' },
// { value: '!', tag: 'punctuation' } ]
// Remove stop words:
var t = nlp.tokens.removeWords( [ 'mary', 'had', 'a', 'little', 'lamb' ] );
console.log( t );
// -> [ 'mary', 'little', 'lamb' ]
Try experimenting with these examples on Runkit in the browser.
Documentation
Check out the wink NLP utilities API documentation to learn more.
Need Help?
If you spot a bug and the same has not yet been reported, raise a new issue or consider fixing it and sending a pull request.
About wink
Wink 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-nlp-utils is copyright 2017-22 GRAYPE Systems Private Limited.
It is licensed under the terms of the MIT License.
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