dualfroz
5424b39d8d
mainClause() dropped any clause merely containing 'that', 'before', 'who' etc, so a main clause with a nested relative clause lost to a comma-list fragment and the wrong verb was reported. Only drop a clause when the word comes before the clause's own verb, and parse the pattern once per call rather than once per clause. Fixes #1035
65 lines
3.1 KiB
JavaScript
65 lines
3.1 KiB
JavaScript
import test from 'tape'
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import nlp from '../_lib.js'
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const here = '[three/svo] '
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test('svo parser', function (t) {
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const arr = [
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['My dog loves pizza crusts.', 'my dog', 'loves'],
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['My grey dog loves pizza crusts.', 'my grey dog', 'loves'],
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['if i can recall, my grey dog loves pizza crusts.', 'my grey dog', 'loves'],
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['I remember what you said yesterday.', 'i', 'remember'],
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['i had suddenly and quickly arrived in Kyiev', 'i', 'had suddenly and quickly arrived'],
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['I eat bananas in the kitchen.', 'i', 'eat'],
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['I thought what she wore was so chic.', 'i', 'thought'],
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['In the kitchen, I eat', 'i', 'eat'],
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['smoked poutine is delicious', 'smoked poutine', 'is'],
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[`by chance, the tape was discovered in the room`, `the tape`, `was discovered`],
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[`every year, we gather in Baltimore`, `we`, `gather`],
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[`if only i was awake, we could have eaten the breakfast`, `we`, `could have eaten`],
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['Every night before I go to bed, I eat bananas.', 'i', 'eat'],
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[
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'Diane decided to plant tomatoes in the back of the yard, where the sun blazed the longest during the day.',
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'diane',
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'decided to plant',
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],
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['Once Adam smashed the spider, he ran into the bathroom', 'he', 'ran into'],
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[`We are introducing ourselves to the class.`, 'we', 'are introducing ourselves'],
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[
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'Throughout the day, as the sun gradually set, the temperature dropped significantly, creating a chilly evening.',
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'the temperature',
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'dropped significantly',
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],
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[
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'He collaborated with the university to develop comprehensive academic proposals throughout the entire campus, encompassing academic priorities in every department at the university and course structure typologies for each academic program.',
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'he',
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'collaborated',
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],
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['Despite Susan walking the dog, she was not wearing a coat.', 'she', 'was not wearing'],
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[
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'Taking diligent notes throughout the entire class, the students remained focused during the lecture.',
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'the students',
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'remained',
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],
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[
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'She led a diverse advisory committee throughout the process that included membership from schools, city planning departments, state engineering departments, transit agencies, and AARP.',
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'she',
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'led',
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],
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['He bought the car that the dealer, the bank, and the broker all recommended.', 'he', 'bought'],
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['I ate dinner before I went to bed.', 'i', 'ate'],
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// ['every day the kitten tries to eat the mouse', 'the kitten', 'tries to eat'],
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// ['The boy who you saw at the store committed a robbery.', 'the boy', 'committed'],
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// ['After dripping mustard all over his chest, the man who was wearing a red shirt wished that he had instead chosen ketchup for his hotdog.', 'the man', 'wished'],
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// ["please tell me you'll address the issue", 'you', 'will address'],
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// ['The store that the boy robbed is on the corner.', 'the store', 'is'],
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]
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arr.forEach(a => {
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const doc = nlp(a[0])
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const obj = doc.sentences().json()[0]
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t.equal(obj.sentence.subject, a[1], here + 'subject: ' + a[1])
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t.equal(obj.sentence.verb, a[2], here + 'verb: ' + a[2])
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})
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t.end()
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})
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