spaCy/spacy/tests/regression/test_issue4849.py

38 lines
1.0 KiB
Python

# coding: utf8
from __future__ import unicode_literals
from spacy.lang.en import English
from spacy.pipeline import EntityRuler
def test_issue4849():
nlp = English()
ruler = EntityRuler(
nlp,
patterns=[
{"label": "PERSON", "pattern": "joe biden", "id": "joe-biden"},
{"label": "PERSON", "pattern": "bernie sanders", "id": "bernie-sanders"},
],
phrase_matcher_attr="LOWER",
)
nlp.add_pipe(ruler)
text = """
The left is starting to take aim at Democratic front-runner Joe Biden.
Sen. Bernie Sanders joined in her criticism: "There is no 'middle ground' when it comes to climate policy."
"""
# USING 1 PROCESS
count_ents = 0
for doc in nlp.pipe([text], n_process=1):
count_ents += len([ent for ent in doc.ents if ent.ent_id > 0])
assert count_ents == 2
# USING 2 PROCESSES
count_ents = 0
for doc in nlp.pipe([text], n_process=2):
count_ents += len([ent for ent in doc.ents if ent.ent_id > 0])
assert count_ents == 2