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 }]
with deliberate, rule-based nlp,
compromise makes working with text easy
compromise makes working with text easy
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nouns! verbs! adjectives!
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people, places, organizations
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seven hundred and fifty == 750
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like a regex for a sentence
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all your base are belong
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contractions, style, mood..
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<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>var nlp = require('compromise')
var doc = nlp('London is calling')
doc.sentences().toNegative()
// 'London is not calling'even if it's just one word:
-
use built-in methods like .nouns(), or .people() - or query 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: - 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', ...
// }]- 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> </span>
<span class="nl-Person nl-LastName">Hawk</span>
</span>
*/and yes, ofcourse, there's a lot more stuff.
Join in - we're fun, using semver, and moving fast. get involved
Twitter
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Slack group
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Mailing-list
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Projects
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Pull-requests
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🌎 Other Languages?
☂️ Isn't javascript too...
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yeah..
it wasn't built to compete with the stanford tagger, and may not fit every project.
all string stuff is synchronous too, and parallelizing is weird.
See here for information about speed & performance.
💃 Can it run on my arduino-watch?
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Only if it's water-proof!
See quickStart for all sorts of funny environments.
✨ Partial builds?
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compromise can't really be tree-shaken, because it's one function.
.. and the tagging methods are competitive, so it's not recommended to pull things out.
It's best to load the library fully, given it's smaller than this gif.
A plug-in scheme is in the works.
- naturalNode - decidedly fancier, statistical nlp in javascript
- superScript - clever conversation engine in js
- nodeBox Linguistics - conjugation, inflection in javascript
- reText - very impressive text utilities in javascript
- jsPos - javascript build of the time-tested Brill-tagger
- spaCy - speedy, multilingual tagger in C/python
For the former promise-library, see jnewman/compromise (Thanks Joshua!)