JSPM – compromise@10.6.1

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

_{by
Spencer Kelly and

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 }]

210k

one javascript file

86%

on the Penn treebank

🙏

npm install compromise

IE9+

caniuse, youbetcha

_{with deliberate, rule-based nlp,}
compromise makes working with text easy

no jargon, | no config, | no training

_{🙌 you can do it!}

Part-of-Speech tags	_{nouns, verbs, adjectives..}	Verb conjugation	_{change tense of a verb or sentence}
Number parsing	_{'seven hundred and fifty' -> 750}	Named-entities	_{the people, places, orgs..}
Template-matches	_{match natural-language forms}	Text cleanup	_{contractions, hyphenation, punctuation}

API docs | Demos

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'

Grab some words,

you can use pre-defined selections (like .nouns()) or grab any pattern with .match()

doc = nlp('Ludwig van Beethoven wrote to Josephine Brunsvik')

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

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

doc.match('#PastTense to').hyphenate().out()
// 'wrote-to'

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:

all your base are belong:

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', ...
// }]

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)
doc.match('#MusicalGroup').length
// 1

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

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>
*/