Developer friendly
Natural Language Processing

The right balance of performance and accuracy in Node.js



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Build amazing applications quickly

Multiple Models

We have a light model for English with many more on the way! Looking for something domain specific, or for a particular language? Feel free to get in touch!







All the NLP you’ll need

Powerful NLP functions and helpers to get you directly what you need. Whether its POS tags , sentiment analysis, custom entities, or getting a list of frequent words, it’s all right here!







Easy to use API

An intuitive API lets you get started quick and get the results you’re looking for.

const winkNLP = require('wink-nlp');
const its = require('wink-nlp/src/its.js');
const as = require('wink-nlp/src/as.js');
const model = require('wink-eng-lite-model');
const nlp = winkNLP(model);





const doc = nlp.readDoc(text);
// This runs all core NLP tasks like
// tokenization, sentence boundary
// detection, negation handling, sentiment
// analysis, part-of-speech tagging, and
// named and custom entitiy extraction.





var timeline = [];
doc
  .entities()
  .filter( e => e.out( its.type ) === 'DATE')
  .each( e => {
    timeline.push({
      sentence: e
        .parentSentence()
        .out( its.markedUpText ),
      date: e.out(),
      unixTime: new Date(e.out()).getTime()
    })
  });

timeline.sort( (a, b) => {
  return a.unixTime - b.unixTime
});

Text to Timeline

The above code takes text input and generates a timeline.
The following is from the NASA Wikipedia Article.



See Demo Get started
sample of a timeline output

+500,000 tokens/second

Full NLP pipeline - tokenization, SBD, sentiment analysis, POS and more

94.7% accuracy

PoS tagging on a subset of the WSJ corpus, including tokenization of raw text

80MB peak memory

When processing a 350 page book with over 125,000 tokens.

Open Source packages for NLP, ML and Statistics in Node JS to build production grade solutions

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