mirror of
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66 lines
2.0 KiB
Python
66 lines
2.0 KiB
Python
# coding: utf-8
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from __future__ import unicode_literals
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from spacy.lang.en import English
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from spacy.pipeline import EntityRuler
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from ..util import make_tempdir
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def test_issue4651_with_phrase_matcher_attr():
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"""Test that the EntityRuler PhraseMatcher is deserialize correctly using
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the method from_disk when the EntityRuler argument phrase_matcher_attr is
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specified.
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"""
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text = "Spacy is a python library for nlp"
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nlp = English()
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ruler = EntityRuler(nlp, phrase_matcher_attr="LOWER")
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patterns = [{"label": "PYTHON_LIB", "pattern": "spacy", "id": "spaCy"}]
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ruler.add_patterns(patterns)
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nlp.add_pipe(ruler)
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doc = nlp(text)
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res = [(ent.text, ent.label_, ent.ent_id_) for ent in doc.ents]
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nlp_reloaded = English()
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with make_tempdir() as d:
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file_path = d / "entityruler"
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ruler.to_disk(file_path)
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ruler_reloaded = EntityRuler(nlp_reloaded).from_disk(file_path)
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nlp_reloaded.add_pipe(ruler_reloaded)
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doc_reloaded = nlp_reloaded(text)
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res_reloaded = [(ent.text, ent.label_, ent.ent_id_) for ent in doc_reloaded.ents]
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assert res == res_reloaded
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def test_issue4651_without_phrase_matcher_attr():
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"""Test that the EntityRuler PhraseMatcher is deserialize correctly using
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the method from_disk when the EntityRuler argument phrase_matcher_attr is
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not specified.
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"""
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text = "Spacy is a python library for nlp"
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nlp = English()
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ruler = EntityRuler(nlp)
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patterns = [{"label": "PYTHON_LIB", "pattern": "spacy", "id": "spaCy"}]
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ruler.add_patterns(patterns)
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nlp.add_pipe(ruler)
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doc = nlp(text)
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res = [(ent.text, ent.label_, ent.ent_id_) for ent in doc.ents]
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nlp_reloaded = English()
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with make_tempdir() as d:
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file_path = d / "entityruler"
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ruler.to_disk(file_path)
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ruler_reloaded = EntityRuler(nlp_reloaded).from_disk(file_path)
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nlp_reloaded.add_pipe(ruler_reloaded)
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doc_reloaded = nlp_reloaded(text)
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res_reloaded = [(ent.text, ent.label_, ent.ent_id_) for ent in doc_reloaded.ents]
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assert res == res_reloaded
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