Datasets:
Tasks:
Text Classification
Modalities:
Text
Sub-tasks:
natural-language-inference
Size:
100K - 1M
Tags:
quality-estimation
License:
fix class
Browse files- ik-nlp-22_transqe.py +1 -2
ik-nlp-22_transqe.py
CHANGED
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@@ -71,7 +71,7 @@ class IkNlp22ExpNLIConfig(datasets.GeneratorBasedBuilder):
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"premise_nl": datasets.Value("string"),
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"hypothesis_en": datasets.Value("string"),
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"hypothesis_nl": datasets.Value("string"),
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"label": datasets.
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"explanation_1_en": datasets.Value("string"),
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"explanation_1_nl": datasets.Value("string"),
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"explanation_2_en": datasets.Value("string"),
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@@ -112,7 +112,6 @@ class IkNlp22ExpNLIConfig(datasets.GeneratorBasedBuilder):
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with open(filepath, encoding="utf-8") as f:
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reader = csv.DictReader(f, dialect="tsv")
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for i, row in enumerate(reader):
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-
print(row)
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yield i, {
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"premise_en": row["premise_en"],
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"premise_nl": row["premise_nl"],
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"premise_nl": datasets.Value("string"),
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"hypothesis_en": datasets.Value("string"),
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"hypothesis_nl": datasets.Value("string"),
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+
"label": datasets.features.ClassLabel(names=["entailment", "neutral", "contradiction"]),
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"explanation_1_en": datasets.Value("string"),
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"explanation_1_nl": datasets.Value("string"),
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"explanation_2_en": datasets.Value("string"),
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| 112 |
with open(filepath, encoding="utf-8") as f:
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reader = csv.DictReader(f, dialect="tsv")
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for i, row in enumerate(reader):
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yield i, {
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"premise_en": row["premise_en"],
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| 117 |
"premise_nl": row["premise_nl"],
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