JSPM – compromise@11.2.3

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, in javascript

_{by
Spencer Kelly and

many contributors}

var nlp = require('compromise')

nlp('Wee-ooh, I look just like buddy holly.').sentences().toPastTense()
// 'Wee-ooh, I looked just like buddy holly.'

nlp('..then consider me Miles Davis!').people().out('freq')
// [{ text:'Miles Davis', count:1 }]

210kb

one javascript file

86%

on the Penn treebank

🙏

npm install compromise

IE9+

caniuse, youbetcha

_{a
least-fancy way to handle text,}

Text in → data out.

_{without training, jargon or config}

Demos Usage API WTF

⚡️ on the Client-side

<script src="https://unpkg.com/compromise@latest/builds/compromise.min.js"></script>
<script>
  var doc = nlp('dinosaur')

  var str = doc.nouns().toPlural().out('text')
  console.log(str)
  // 'dinosaurs'
</script>

🌋 Server-side!

var nlp = require('compromise')

var doc = nlp('London is calling')
doc.sentences().toNegative()
// 'London is not calling'

Part-of-Speech tagging _{nouns! verbs! adjectives!}	Named-entities _{people, places, organizations}	Number parsing _{seven hundred and fifty == 750}
Template-matches _{like a regex for a sentence}	Verb conjugation _{all your base are belong}	Transformations _{contractions, style, mood..}

pop right in:

var doc= nlp(myNovel) //whoosh
doc.match('the #Superlative of times').length

API is bearable:

doc.contractions().expand()
doc.people().lastNames()

loosely-held opinions..

var ayeRight= require('nlp-scottish-slang')
nlp.plugin(ayeRight)

nlp('Taps aff, high doh!')

no foolin,

6 years, 150 PRs, 60 devs

_{in production in the United Nations🎈}

Throw in text,

even if it's just one word:

var doc = nlp('Ludwig van Beethoven')

Grab a part:

.match()

built-in methods

.nouns()

.people()

doc.match('#TitleCase van #LastName').out()
// 'Ludwig van Beethoven'

doc.people().out('list')
// ['ludwig van beethoven']

Move stuff around:

Plural/singular: - grab the noun-phrases, make em plural:

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

Number parsing: - parse written-out numbers, and change their form:

doc = nlp('ninety five thousand and fifty two')
doc.values().toNumber().out('text')
// '95052'

doc = nlp('the 23rd of December')
doc.values().add(2).toText()
doc.out('text')
// 'the twenty fifth of December'

Normalization: - handle the craziness:

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

Tense: - switch between conjugations of any verb

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

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

Contractions: - grab, expand and contract them:

doc = nlp("we're not gonna take it, no we ain't gonna take it.")
doc.has('going') // true
doc.match('are not').length // == 2
doc.contractions().expand().out()
//'we are not going to take it, no we are not going to take it'

Named-entities: - get the people, places, organizations:

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

Error correction: - make it say what you'd like:

var lexicon={
  'boston': 'MusicalGroup'
}
doc = nlp('i heard Boston\'s set in Chicago', lexicon)

//alternatively, fix it all 'in-post':
doc.match('heard #Possessive set').terms(1).tag('MusicalGroup')

Handy outputs: - get sensible data:

doc = nlp('We like Roy! We like Roy!').sentences().out('array')
// ['We like Roy!', 'We like Roy!']

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