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

53 lines
1.6 KiB
Python

import pytest
from spacy.tokens import Doc
def test_noun_chunks_is_parsed(la_tokenizer):
"""Test that noun_chunks raises Value Error for 'la' language if Doc is not parsed.
To check this test, we're constructing a Doc
with a new Vocab here and forcing is_parsed to 'False'
to make sure the noun chunks don't run.
"""
doc = la_tokenizer("Haec est sententia.")
with pytest.raises(ValueError):
list(doc.noun_chunks)
LA_NP_TEST_EXAMPLES = [
(
"Haec narrantur a poetis de Perseo.",
["DET", "VERB", "ADP", "NOUN", "ADP", "PROPN", "PUNCT"],
["nsubj:pass", "ROOT", "case", "obl", "case", "obl", "punct"],
[1, 0, -1, -1, -3, -1, -5],
["poetis", "Perseo"],
),
(
"Perseus autem in sinu matris dormiebat.",
["NOUN", "ADV", "ADP", "NOUN", "NOUN", "VERB", "PUNCT"],
["nsubj", "discourse", "case", "obl", "nmod", "ROOT", "punct"],
[5, 4, 3, -1, -1, 0, -1],
["Perseus", "sinu matris"],
),
]
@pytest.mark.parametrize(
"text,pos,deps,heads,expected_noun_chunks", LA_NP_TEST_EXAMPLES
)
def test_la_noun_chunks(la_tokenizer, text, pos, deps, heads, expected_noun_chunks):
tokens = la_tokenizer(text)
assert len(heads) == len(pos)
doc = Doc(
tokens.vocab,
words=[t.text for t in tokens],
heads=[head + i for i, head in enumerate(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]