JSPM

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  • License MIT

natural language processing in the browser

Package Exports

  • compromise

This package does not declare an exports field, so the exports above have been automatically detected and optimized by JSPM instead. If any package subpath is missing, it is recommended to post an issue to the original package (compromise) to support the "exports" field. If that is not possible, create a JSPM override to customize the exports field for this package.

Readme

natural language processing, actually in the browser
(formerly nlp_compromise)
inspect and play with english text.

📯 Welcome to v7 📯
a lot has changed!
let r = nlp('I look just like buddy holly.')
r.sentences().toPastTense()
r.out('text')
// "I looked just like buddy holly."
220k
  one javascript file  
86%
  on the Penn treebank  
🙏
  npm install compromise  
IE9+
    caniuse, youbetcha    

demos   |   quickStart   |   docs

no training, configuration, or prolog

the idea is, reach-in to a part of the text, and change it:

r = nlp('john is really nice. sara sings loudly.')

r.match('#Person').toUpperCase()
//JOHN is really nice. SARA sings loudly.

or pluck-out some parts,

r.remove('#Adverb')
// "JOHN is nice. SARA sings."

//replacements,
r.replace('is nice', 'is bad')
// "JOHN is bad. SARA sings."

or just be downright fancy

r.sentences().toNegative()
// "JOHN is not bad. SARA doesn't sing."

or grab specific parts, and analyze-the-heck out of them:

r = nlp(chomskyFanFic)
r.places().sort('freq').unique().data()
/*[
  {text: 'MIT lecture hall'},
  {text: '23 Desperado dr.'},
  {text: 'desert island'},
]*/
Part-of-Speech Tagging️ Named-Entity Recognition️ 🍾Verb Conjugation ✨Inflection/Pluralization

###Client-side:

<script src="https://unpkg.com/compromise@latest/builds/compromise.min.js"></script>
<script>
  var r = nlp('dinosaur').nouns().toPlural()
  console.log(r.out('text'))
  //dinosaurs
</script>

###Tense:

let r = nlp('she sells seashells by the seashore.')
r.sentences().toFutureTense().out('text')
//'she will sell seashells...'

r.verbs().conjugate()
// [{ PastTense: 'sold',
//    Infinitive: 'sell',
//    Gerund: 'selling', ...
// }]

###Plural/singular:

r = nlp('a bottle of beer on the wall.')
r.nouns().first().toPlural()
r.out('text')
//'The bottles of beer on the wall.'

###Negation:

r = nlp('london is calling')
r.sentences().toNegative()
// 'london is not calling'

###Number interpretation:

r = nlp('fifth of december')

r.values().toCardinal().out('text')
// 'five of december'

r.values().toNumber().out('text')
// '5 of december'

###Normalization:

r = nlp("the guest-singer's björk at seven thirty.").normalize().out('text')
// 'The guest singer is Bjork at 7:30.'

###Named-entity recognition:

r = nlp('the opera about richard nixon visiting china')
r.topics().data()
// [
//   { text: 'richard nixon' },
//   { text: 'china' }
// ]

###Fancy outputs:

r = nlp('Tony Hawk won').out('html')
/*
<span>
  <span class="nl-Person nl-Noun nl-FirstName">Tony</span>
  <span class="nl-Person nl-Noun nl-LastName">Hawk</span>
  <span>&nbsp;</span>
  <span class="nl-Verb nl-PastTense">won</span>
</span>
*/

and yes, ofcourse, there's a lot more stuff.

Join in! we're fun, we're using semver, and moving fast. get involved

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      Pull-requests      

###Don't forget about:

For the former promise-library, see jnewman/compromise (Thanks Joshua!)

(also don't forget NLTK, GATE, Stanford, and Illinois toolkit ) ❤️️

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