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test_gold_biluo_different_tokenization works

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svlandeg 2020-06-16 15:21:20 +02:00
parent 1c35b8efcd
commit 44a0f9c2c8
2 changed files with 23 additions and 26 deletions
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15
spacy/gold/example.pyx
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@ -85,17 +85,17 @@ cdef class Example:
vocab = self.reference.vocab
gold_values = self.reference.to_array([field])
output = []
output = [None] * len(self.predicted)
for i, gold_i in enumerate(cand_to_gold):
if self.predicted[i].text.isspace():
output.append(None)
elif gold_i is None:
output[i] = None
if gold_i is None:
if i in i2j_multi:
output.append(gold_values[i2j_multi[i]])
output[i] = gold_values[i2j_multi[i]]
else:
output.append(None)
output[i] = None
else:
output.append(gold_values[gold_i])
output[i] = gold_values[gold_i]
if field in ["ENT_IOB"]:
# Fix many-to-one IOB codes
@ -117,7 +117,8 @@ cdef class Example:
if cand_j is None:
if j in j2i_multi:
i = j2i_multi[j]
output[i] = gold_values[j]
if output[i] is None:
output[i] = gold_values[j]
if as_string:
output = [vocab.strings[o] if o is not None else o for o in output]

34
spacy/tests/test_gold.py
View File

@ -158,7 +158,7 @@ def test_gold_biluo_different_tokenization(en_vocab, en_tokenizer):
entities = [(len("I flew to "), len("I flew to San Francisco Valley"), "LOC")]
gold_words = ["I", "flew", "to", "San", "Francisco", "Valley", "."]
example = Example.from_dict(doc, {"words": gold_words, "entities": entities})
assert example.get_aligned("ENT_IOB") == [2, 2, 1, 2]
assert example.get_aligned("ENT_IOB") == [2, 2, 3, 2]
assert example.get_aligned("ENT_TYPE", as_string=True) == ["", "", "LOC", ""]
# many-to-one
@ -195,25 +195,21 @@ def test_gold_biluo_different_tokenization(en_vocab, en_tokenizer):
assert example.get_aligned("ENT_TYPE", as_string=True) == ["", "", "", "", "LOC", "LOC", ""]
# from issue #4791
data = (
"I'll return the ₹54 amount",
{
"words": ["I", "'ll", "return", "the", "₹", "54", "amount"],
"entities": [(16, 19, "MONEY")],
},
)
gp = GoldParse(en_tokenizer(data[0]), **data[1])
assert gp.ner == ["O", "O", "O", "O", "U-MONEY", "O"]
doc = en_tokenizer("I'll return the ₹54 amount")
gold_words = ["I", "'ll", "return", "the", "₹", "54", "amount"]
gold_spaces = [False, True, True, True, False, True, False]
entities = [(16, 19, "MONEY")]
example = Example.from_dict(doc, {"words": gold_words, "spaces": gold_spaces, "entities": entities})
assert example.get_aligned("ENT_IOB") == [2, 2, 2, 2, 3, 2]
assert example.get_aligned("ENT_TYPE", as_string=True) == ["", "", "", "", "MONEY", ""]
data = (
"I'll return the $54 amount",
{
"words": ["I", "'ll", "return", "the", "$", "54", "amount"],
"entities": [(16, 19, "MONEY")],
},
)
gp = GoldParse(en_tokenizer(data[0]), **data[1])
assert gp.ner == ["O", "O", "O", "O", "B-MONEY", "L-MONEY", "O"]
doc = en_tokenizer("I'll return the $54 amount")
gold_words = ["I", "'ll", "return", "the", "$", "54", "amount"]
gold_spaces = [False, True, True, True, False, True, False]
entities = [(16, 19, "MONEY")]
example = Example.from_dict(doc, {"words": gold_words, "spaces": gold_spaces, "entities": entities})
assert example.get_aligned("ENT_IOB") == [2, 2, 2, 2, 3, 1, 2]
assert example.get_aligned("ENT_TYPE", as_string=True) == ["", "", "", "", "MONEY", "MONEY", ""]
def test_roundtrip_offsets_biluo_conversion(en_tokenizer):