mirror of https://github.com/explosion/spaCy.git
48 lines
1.6 KiB
Python
48 lines
1.6 KiB
Python
# coding: utf-8
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from __future__ import unicode_literals
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import pytest
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from ...util import get_doc
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SV_NP_TEST_EXAMPLES = [
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(
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"En student läste en bok", # A student read a book
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["DET", "NOUN", "VERB", "DET", "NOUN"],
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["det", "nsubj", "ROOT", "det", "dobj"],
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[1, 1, 0, 1, -2],
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["En student", "en bok"],
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),
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(
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"Studenten läste den bästa boken.", # The student read the best book
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["NOUN", "VERB", "DET", "ADJ", "NOUN", "PUNCT"],
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["nsubj", "ROOT", "det", "amod", "dobj", "punct"],
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[1, 0, 2, 1, -3, -4],
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["Studenten", "den bästa boken"],
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),
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(
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"De samvetslösa skurkarna hade stulit de största juvelerna på söndagen", # The remorseless crooks had stolen the largest jewels that sunday
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["DET", "ADJ", "NOUN", "VERB", "VERB", "DET", "ADJ", "NOUN", "ADP", "NOUN"],
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["det", "amod", "nsubj", "aux", "root", "det", "amod", "dobj", "case", "nmod"],
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[2, 1, 2, 1, 0, 2, 1, -3, 1, -5],
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["De samvetslösa skurkarna", "de största juvelerna", "på söndagen"],
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),
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]
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@pytest.mark.parametrize(
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"text,pos,deps,heads,expected_noun_chunks", SV_NP_TEST_EXAMPLES
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)
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def test_sv_noun_chunks(sv_tokenizer, text, pos, deps, heads, expected_noun_chunks):
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tokens = sv_tokenizer(text)
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assert len(heads) == len(pos)
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doc = get_doc(
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tokens.vocab, words=[t.text for t in tokens], heads=heads, deps=deps, pos=pos
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)
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noun_chunks = list(doc.noun_chunks)
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assert len(noun_chunks) == len(expected_noun_chunks)
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for i, np in enumerate(noun_chunks):
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assert np.text == expected_noun_chunks[i]
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