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
npm install compromise
let r = nlp('I look just like buddy holly.')
r.sentences().toPastTense()
r.out('text')
// "I looked just like buddy holly."demos | quickStart | docs | accuracy
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 Tagging | Named-Entity Recognition | 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="Person Noun MalePerson">Tony Hawk</span>
<span> </span>
<span class="Verb 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 💃
Twitter
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Slack group
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Mailing-list
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Pull-requests
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###Don't forget about:
- naturalNode - decidedly fancier, statistical nlp in javascript, too
- SuperScript - clever conversation engine in js
- NodeBox Linguistics - conjugation, inflection in javascript
- reText - very impressive text utilities in javascript
- jsPos - js-build of the time-tested Brill-tagger
- spaCy - speedy, multilingual tagger in C/python
For the former promise-library, see jnewman/compromise (Thanks Joshua!)