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2026-07-13 12:48:55 +08:00

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import test from 'tape'
import nlp from '../_lib.js'
const here = '[one/hyphen-matrix] '
test('hyphen-input', (t) => {
const doc = nlp(`before follow-up after`)
t.equal(doc.has('follow-up'), true, here + 'hyphen -> follow-up')
t.equal(doc.has('follow up'), true, here + 'hyphen -> follow up')
t.equal(doc.has('followup'), false, here + 'hyphen -> followup')//would be nice
t.end()
})
test('no-hyphen-input', (t) => {
const doc = nlp(`before follow up after`)
t.equal(doc.has('follow-up'), true, here + 'no-hyphen -> follow-up')
t.equal(doc.has('follow up'), true, here + 'no-hyphen ->follow up')
t.equal(doc.has('followup'), false, here + 'no-hyphen ->followup')
t.end()
})
test('compound-hyphen-input', (t) => {
const doc = nlp(`before followup after`)
t.equal(doc.has('follow-up'), false, here + 'compound -> follow-up')//maybe?
t.equal(doc.has('follow up'), false, here + 'compound -> follow up')
t.equal(doc.has('followup'), true, here + 'compound -> followup')
t.end()
})
// ==================
test('hyphen-skipping', (t) => {
const doc = nlp(`before super-cool after`)
t.equal(doc.has('before super'), true, here + '[hyphen] before')
t.equal(doc.has('before super cool'), true, here + '[hyphen] before-mid')
t.equal(doc.has('cool after'), true, here + '[hyphen] after')
t.equal(doc.has('super cool after'), true, here + '[hyphen] after-mid')
//
t.equal(doc.has('before after'), false, here + '[hyphen] no-jump')
t.equal(doc.has('before super after'), false, here + '[hyphen] no-mid-jump')
t.equal(doc.has('before cool after'), false, here + '[hyphen] no-mid-2-jump')
t.end()
})
test('match-dash', function (t) {
const arr = [
're-purpose',
'co-opting',
'mis-information',
'proto-plasmic',
'counter-argument',
'soft-sell',
'big-news',
'do-over',
'over-the-top',
'larger-than-life',
're-zoning-laws',
'inter-sectional',
'counter-argument',
're-purpose itself',
'full-enough tank',
'the size-difference',
'counter-balance',
'score was 10-2',
'Nobel Prizewinning',
'take-down ',
'the non-player-character',
'load-bearing walls',
'this clearly-impossible story',
'beautiful-looking flowers ',
'community-based education',
'Mother-in-law',
'Master-at-arms',
'Editor-in-chief',
'Ten-year-old',
'Factory-made',
'Twelve-pack',
'fifty-six bottles',
'a 10-minute speech',
'self-serve',
'non-sequitur'
]
arr.forEach(str => {
t.equal(nlp(str).has(str), true, here + '[dash] ' + str)
})
t.end()
})