spaCy/spacy/tests/lang/sv/test_noun_chunks.py

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# coding: utf-8
from __future__ import unicode_literals
import pytest
from ...util import get_doc
2019-10-24 14:20:48 +00:00
SV_NP_TEST_EXAMPLES = [
(
"En student läste en bok", # A student read a book
["DET", "NOUN", "VERB", "DET", "NOUN"],
["det", "nsubj", "ROOT", "det", "dobj"],
[1, 1, 0, 1, -2],
["En student", "en bok"],
),
(
"Studenten läste den bästa boken.", # The student read the best book
["NOUN", "VERB", "DET", "ADJ", "NOUN", "PUNCT"],
["nsubj", "ROOT", "det", "amod", "dobj", "punct"],
[1, 0, 2, 1, -3, -4],
["Studenten", "den bästa boken"],
),
(
"De samvetslösa skurkarna hade stulit de största juvelerna på söndagen", # The remorseless crooks had stolen the largest jewels that sunday
["DET", "ADJ", "NOUN", "VERB", "VERB", "DET", "ADJ", "NOUN", "ADP", "NOUN"],
["det", "amod", "nsubj", "aux", "root", "det", "amod", "dobj", "case", "nmod"],
[2, 1, 2, 1, 0, 2, 1, -3, 1, -5],
["De samvetslösa skurkarna", "de största juvelerna", "på söndagen"],
),
]
@pytest.mark.parametrize(
"text,pos,deps,heads,expected_noun_chunks", SV_NP_TEST_EXAMPLES
)
def test_sv_noun_chunks(sv_tokenizer, text, pos, deps, heads, expected_noun_chunks):
tokens = sv_tokenizer(text)
assert len(heads) == len(pos)
doc = get_doc(
tokens.vocab, words=[t.text for t in tokens], heads=heads, deps=deps, pos=pos
)
noun_chunks = list(doc.noun_chunks)
assert len(noun_chunks) == len(expected_noun_chunks)
for i, np in enumerate(noun_chunks):
assert np.text == expected_noun_chunks[i]