import pytest from spacy.tokens import Doc def test_noun_chunks_is_parsed(da_tokenizer): """Test that noun_chunks raises Value Error for 'da' 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 = da_tokenizer("Det er en sætning") with pytest.raises(ValueError): list(doc.noun_chunks) DA_NP_TEST_EXAMPLES = [ ( "Hun elsker at plukker frugt.", ["PRON", "VERB", "PART", "VERB", "NOUN", "PUNCT"], ["nsubj", "ROOT", "mark", "obj", "obj", "punct"], [1, 0, 1, -2, -1, -4], ["Hun", "frugt"], ), ( "Påfugle er de smukkeste fugle.", ["NOUN", "AUX", "DET", "ADJ", "NOUN", "PUNCT"], ["nsubj", "cop", "det", "amod", "ROOT", "punct"], [4, 3, 2, 1, 0, -1], ["Påfugle", "de smukkeste fugle"], ), ( "Rikke og Jacob Jensen glæder sig til en hyggelig skovtur", [ "PROPN", "CCONJ", "PROPN", "PROPN", "VERB", "PRON", "ADP", "DET", "ADJ", "NOUN", ], ["nsubj", "cc", "conj", "flat", "ROOT", "obj", "case", "det", "amod", "obl"], [4, 1, -2, -1, 0, -1, 3, 2, 1, -5], ["Rikke", "Jacob Jensen", "sig", "en hyggelig skovtur"], ), ] @pytest.mark.parametrize( "text,pos,deps,heads,expected_noun_chunks", DA_NP_TEST_EXAMPLES ) def test_da_noun_chunks(da_tokenizer, text, pos, deps, heads, expected_noun_chunks): tokens = da_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]