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925a852bb6
* Improve NER per type scoring * include all gold labels in per type scoring, not only when recall > 0 * improve efficiency of per type scoring * Create Scorer tests, initially with NER tests * move regression test #3968 (per type NER scoring) to Scorer tests * add new test for per type NER scoring with imperfect P/R/F and per type P/R/F including a case where R == 0.0
74 lines
2.4 KiB
Python
74 lines
2.4 KiB
Python
# coding: utf-8
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from __future__ import unicode_literals
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from pytest import approx
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from spacy.gold import GoldParse
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from spacy.scorer import Scorer
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from .util import get_doc
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test_ner_cardinal = [
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[
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"100 - 200",
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{
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"entities": [
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[0, 3, "CARDINAL"],
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[6, 9, "CARDINAL"]
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]
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}
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]
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]
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test_ner_apple = [
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[
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"Apple is looking at buying U.K. startup for $1 billion",
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{
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"entities": [
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(0, 5, "ORG"),
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(27, 31, "GPE"),
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(44, 54, "MONEY"),
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]
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}
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]
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]
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def test_ner_per_type(en_vocab):
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# Gold and Doc are identical
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scorer = Scorer()
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for input_, annot in test_ner_cardinal:
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doc = get_doc(en_vocab, words = input_.split(' '), ents = [[0, 1, 'CARDINAL'], [2, 3, 'CARDINAL']])
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gold = GoldParse(doc, entities = annot['entities'])
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scorer.score(doc, gold)
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results = scorer.scores
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assert results['ents_p'] == 100
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assert results['ents_f'] == 100
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assert results['ents_r'] == 100
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assert results['ents_per_type']['CARDINAL']['p'] == 100
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assert results['ents_per_type']['CARDINAL']['f'] == 100
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assert results['ents_per_type']['CARDINAL']['r'] == 100
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# Doc has one missing and one extra entity
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# Entity type MONEY is not present in Doc
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scorer = Scorer()
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for input_, annot in test_ner_apple:
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doc = get_doc(en_vocab, words = input_.split(' '), ents = [[0, 1, 'ORG'], [5, 6, 'GPE'], [6, 7, 'ORG']])
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gold = GoldParse(doc, entities = annot['entities'])
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scorer.score(doc, gold)
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results = scorer.scores
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assert results['ents_p'] == approx(66.66666)
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assert results['ents_r'] == approx(66.66666)
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assert results['ents_f'] == approx(66.66666)
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assert 'GPE' in results['ents_per_type']
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assert 'MONEY' in results['ents_per_type']
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assert 'ORG' in results['ents_per_type']
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assert results['ents_per_type']['GPE']['p'] == 100
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assert results['ents_per_type']['GPE']['r'] == 100
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assert results['ents_per_type']['GPE']['f'] == 100
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assert results['ents_per_type']['MONEY']['p'] == 0
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assert results['ents_per_type']['MONEY']['r'] == 0
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assert results['ents_per_type']['MONEY']['f'] == 0
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assert results['ents_per_type']['ORG']['p'] == 50
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assert results['ents_per_type']['ORG']['r'] == 100
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assert results['ents_per_type']['ORG']['f'] == approx(66.66666)
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