wehub-resource-sync
45 lines
1.4 KiB
JavaScript
45 lines
1.4 KiB
JavaScript
import test from 'tape'
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import nlp from '../_lib.js'
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const here = '[two/out] '
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test('out-tags', function (t) {
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const out = nlp(`he's cool.`).out('tags')
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t.equal(out.length, 1, 'one sentence')
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t.equal(out[0].he.indexOf('Pronoun') !== -1, true, here + 'has he:Pronoun')
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t.equal(out[0].is.indexOf('Copula') !== -1, true, here + 'has is:Copula')
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t.equal(out[0].cool.indexOf('Adjective') !== -1, true, here + 'has cool:Adjective')
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t.end()
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})
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test('out-topk', function (t) {
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const doc = nlp(`What'd I say? Monorail. and it called? Monorail.`)
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const out = doc.out('freq')
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// t.equal(out.length, 3, here + 'three results')
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t.equal(out[0].normal, 'monorail.', here + 'top-result is most-frequent')
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t.equal(out[0].count, 2, here + 'got count')
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t.end()
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})
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test('out-array', function (t) {
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const arr = nlp('1-2').terms().out('array')
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t.equal(arr.length, 1, here + 'one result')
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t.equal(arr[0], '1-2', here + 'got contraction text')
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t.end()
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})
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test('out-wrap', function (t) {
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let doc = nlp("soft and yielding like a nerf ball")
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let out = doc.out({
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'#Adjective': (m) => `[${m.text()}]`
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})
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t.equal(out, `[soft] and [yielding] like a nerf ball`, here + 'two matches')
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// pre-post
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doc = nlp("before (match) after")
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out = doc.wrap({
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'match': () => `few more words`,
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})
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t.equal(out, `before (few more words) after`, here + 'pre+post')
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t.end()
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})
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