fotisz/compromise

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>
*/