import pytest
from spacy.pipeline.functions import merge_subtokens
from spacy.language import Language
from spacy.tokens import Span
from ..util import get_doc
@pytest.fixture
def doc(en_tokenizer):
# fmt: off
text = "This is a sentence. This is another sentence. And a third."
heads = [1, 0, 1, -2, -3, 1, 0, 1, -2, -3, 1, 1, 1, 0]
deps = ["nsubj", "ROOT", "subtok", "attr", "punct", "nsubj", "ROOT",
"subtok", "attr", "punct", "subtok", "subtok", "subtok", "ROOT"]
# fmt: on
tokens = en_tokenizer(text)
return get_doc(tokens.vocab, words=[t.text for t in tokens], heads=heads, deps=deps)
def doc2(en_tokenizer):
text = "I like New York in Autumn."
heads = [1, 0, 1, -2, -3, -1, -5]
tags = ["PRP", "IN", "NNP", "NNP", "IN", "NNP", "."]
pos = ["PRON", "VERB", "PROPN", "PROPN", "ADP", "PROPN", "PUNCT"]
deps = ["ROOT", "prep", "compound", "pobj", "prep", "pobj", "punct"]
doc = get_doc(
tokens.vocab,
words=[t.text for t in tokens],
heads=heads,
tags=tags,
pos=pos,
deps=deps,
)
doc.ents = [Span(doc, 2, 4, doc.vocab.strings["GPE"])]
return doc
def test_merge_subtokens(doc):
doc = merge_subtokens(doc)
# get_doc() doesn't set spaces, so the result is "And a third ."
assert [t.text for t in doc] == [
"This",
"is",
"a sentence",
".",
"another sentence",
"And a third .",
]
def test_factories_merge_noun_chunks(doc2):
assert len(doc2) == 7
nlp = Language()
merge_noun_chunks = nlp.create_pipe("merge_noun_chunks")
merge_noun_chunks(doc2)
assert len(doc2) == 6
assert doc2[2].text == "New York"
def test_factories_merge_ents(doc2):
assert len(list(doc2.ents)) == 1
merge_entities = nlp.create_pipe("merge_entities")
merge_entities(doc2)