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test for split sentences with various alignment issues, works

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svlandeg 2020-06-18 20:01:02 +02:00
parent 1951921230
commit 6ca6d7d6b4
1 changed files with 28 additions and 1 deletions
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29
spacy/tests/test_gold.py
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@ -90,6 +90,7 @@ def merged_dict():
return { return {
"ids": [1, 2, 3, 4, 5, 6, 7], "ids": [1, 2, 3, 4, 5, 6, 7],
"words": ["Hi", "there", "everyone", "It", "is", "just", "me"], "words": ["Hi", "there", "everyone", "It", "is", "just", "me"],
"spaces": [True, True, True, True, True, True, False],
"tags": ["INTJ", "ADV", "PRON", "PRON", "AUX", "ADV", "PRON"], "tags": ["INTJ", "ADV", "PRON", "PRON", "AUX", "ADV", "PRON"],
"sent_starts": [1, 0, 0, 1, 0, 0, 0], "sent_starts": [1, 0, 0, 1, 0, 0, 0],
} }
@ -150,6 +151,30 @@ def test_gold_biluo_misalign(en_vocab):
assert tags == ["O", "O", "O", "-", "-", "-"] assert tags == ["O", "O", "O", "-", "-", "-"]
def test_split_sentences(en_vocab):
words = ["I", "flew", "to", "San Francisco Valley", "had", "loads of fun"]
doc = Doc(en_vocab, words=words)
gold_words = ["I", "flew", "to", "San", "Francisco", "Valley", "had", "loads", "of", "fun"]
sent_starts = [True, False, False, False, False, False, True, False, False, False]
example = Example.from_dict(doc, {"words": gold_words, "sent_starts": sent_starts})
assert example.text == "I flew to San Francisco Valley had loads of fun "
split_examples = example.split_sents()
assert len(split_examples) == 2
assert split_examples[0].text == "I flew to San Francisco Valley "
assert split_examples[1].text == "had loads of fun "
words = ["I", "flew", "to", "San", "Francisco", "Valley", "had", "loads", "of fun"]
doc = Doc(en_vocab, words=words)
gold_words = ["I", "flew", "to", "San Francisco", "Valley", "had", "loads of", "fun"]
sent_starts = [True, False, False, False, False, True, False, False]
example = Example.from_dict(doc, {"words": gold_words, "sent_starts": sent_starts})
assert example.text == "I flew to San Francisco Valley had loads of fun "
split_examples = example.split_sents()
assert len(split_examples) == 2
assert split_examples[0].text == "I flew to San Francisco Valley "
assert split_examples[1].text == "had loads of fun "
def test_gold_biluo_different_tokenization(en_vocab, en_tokenizer): def test_gold_biluo_different_tokenization(en_vocab, en_tokenizer):
# one-to-many # one-to-many
words = ["I", "flew to", "San Francisco Valley", "."] words = ["I", "flew to", "San Francisco Valley", "."]
@ -466,7 +491,7 @@ def _train(train_data):
def test_split_sents(merged_dict): def test_split_sents(merged_dict):
nlp = English() nlp = English()
example = Example.from_dict( example = Example.from_dict(
Doc(nlp.vocab, words=merged_dict["words"]), Doc(nlp.vocab, words=merged_dict["words"], spaces=merged_dict["spaces"]),
merged_dict merged_dict
) )
assert len(get_parses_from_example( assert len(get_parses_from_example(
@ -484,6 +509,8 @@ def test_split_sents(merged_dict):
split_examples = example.split_sents() split_examples = example.split_sents()
assert len(split_examples) == 2 assert len(split_examples) == 2
assert split_examples[0].text == "Hi there everyone "
assert split_examples[1].text == "It is just me"
token_annotation_1 = split_examples[0].to_dict()["token_annotation"] token_annotation_1 = split_examples[0].to_dict()["token_annotation"]
assert token_annotation_1["words"] == ["Hi", "there", "everyone"] assert token_annotation_1["words"] == ["Hi", "there", "everyone"]