mirror of
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94 lines
2.8 KiB
Python
94 lines
2.8 KiB
Python
# coding: utf-8
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from __future__ import unicode_literals
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import pytest
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from spacy.pipeline import EntityRecognizer
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from spacy.vocab import Vocab
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from spacy.syntax.ner import BiluoPushDown
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from spacy.gold import GoldParse
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from spacy.tokens import Doc
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@pytest.fixture
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def vocab():
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return Vocab()
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@pytest.fixture
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def doc(vocab):
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return Doc(vocab, words=["Casey", "went", "to", "New", "York", "."])
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@pytest.fixture
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def entity_annots(doc):
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casey = doc[0:1]
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ny = doc[3:5]
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return [
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(casey.start_char, casey.end_char, "PERSON"),
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(ny.start_char, ny.end_char, "GPE"),
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]
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@pytest.fixture
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def entity_types(entity_annots):
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return sorted(set([label for (s, e, label) in entity_annots]))
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@pytest.fixture
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def tsys(vocab, entity_types):
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actions = BiluoPushDown.get_actions(entity_types=entity_types)
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return BiluoPushDown(vocab.strings, actions)
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def test_get_oracle_moves(tsys, doc, entity_annots):
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gold = GoldParse(doc, entities=entity_annots)
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tsys.preprocess_gold(gold)
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act_classes = tsys.get_oracle_sequence(doc, gold)
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names = [tsys.get_class_name(act) for act in act_classes]
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assert names == ["U-PERSON", "O", "O", "B-GPE", "L-GPE", "O"]
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def test_get_oracle_moves_negative_entities(tsys, doc, entity_annots):
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entity_annots = [(s, e, "!" + label) for s, e, label in entity_annots]
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gold = GoldParse(doc, entities=entity_annots)
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for i, tag in enumerate(gold.ner):
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if tag == "L-!GPE":
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gold.ner[i] = "-"
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tsys.preprocess_gold(gold)
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act_classes = tsys.get_oracle_sequence(doc, gold)
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names = [tsys.get_class_name(act) for act in act_classes]
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assert names
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def test_get_oracle_moves_negative_entities2(tsys, vocab):
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doc = Doc(vocab, words=["A", "B", "C", "D"])
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gold = GoldParse(doc, entities=[])
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gold.ner = ["B-!PERSON", "L-!PERSON", "B-!PERSON", "L-!PERSON"]
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tsys.preprocess_gold(gold)
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act_classes = tsys.get_oracle_sequence(doc, gold)
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names = [tsys.get_class_name(act) for act in act_classes]
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assert names
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def test_get_oracle_moves_negative_O(tsys, vocab):
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doc = Doc(vocab, words=["A", "B", "C", "D"])
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gold = GoldParse(doc, entities=[])
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gold.ner = ["O", "!O", "O", "!O"]
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tsys.preprocess_gold(gold)
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act_classes = tsys.get_oracle_sequence(doc, gold)
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names = [tsys.get_class_name(act) for act in act_classes]
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assert names
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def test_doc_add_entities_set_ents_iob(en_vocab):
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doc = Doc(en_vocab, words=["This", "is", "a", "lion"])
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ner = EntityRecognizer(en_vocab)
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ner.begin_training([])
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ner(doc)
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assert len(list(doc.ents)) == 0
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assert [w.ent_iob_ for w in doc] == (["O"] * len(doc))
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doc.ents = [(doc.vocab.strings["ANIMAL"], 3, 4)]
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assert [w.ent_iob_ for w in doc] == ["", "", "", "B"]
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doc.ents = [(doc.vocab.strings["WORD"], 0, 2)]
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assert [w.ent_iob_ for w in doc] == ["B", "I", "", ""]
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