Datasets:
Tasks:
Text Classification
Modalities:
Text
Sub-tasks:
fact-checking
Languages:
English
Size:
1K - 10K
ArXiv:
Tags:
stance-detection
License:
test done
Browse files- rumoureval2019_test.csv +0 -0
- rumoureval_2019.py +15 -17
rumoureval2019_test.csv
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rumoureval_2019.py
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@@ -51,12 +51,12 @@ class RumourEval2019Config(datasets.BuilderConfig):
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super(RumourEval2019Config, self).__init__(**kwargs)
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class RumourEval2019(datasets.GeneratorBasedBuilder):
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"""
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VERSION = datasets.Version("0.9.0")
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BUILDER_CONFIGS = [
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RumourEval2019Config(name="RumourEval2019", version=VERSION, description="Stance Detection
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]
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def _info(self):
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@@ -87,23 +87,21 @@ class RumourEval2019(datasets.GeneratorBasedBuilder):
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def _split_generators(self, dl_manager):
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train_text = dl_manager.download_and_extract("rumoureval2019_train.csv")
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validation_text = dl_manager.download_and_extract("rumoureval2019_val.csv")
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return [
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datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": train_text, "split": "train"}),
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datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": validation_text, "split": "validation"})
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]
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# method parameters are unpacked from `gen_kwargs` as given in `_split_generators`
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def _generate_examples(self, filepath, split):
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instance['id'] = str(guid)
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yield guid, instance
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guid += 1
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super(RumourEval2019Config, self).__init__(**kwargs)
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class RumourEval2019(datasets.GeneratorBasedBuilder):
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"""RumourEval2019 Stance Detection Dataset formatted in triples of (source_text, reply_text, label)"""
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VERSION = datasets.Version("0.9.0")
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BUILDER_CONFIGS = [
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RumourEval2019Config(name="RumourEval2019", version=VERSION, description="Stance Detection Dataset"),
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]
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def _info(self):
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def _split_generators(self, dl_manager):
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train_text = dl_manager.download_and_extract("rumoureval2019_train.csv")
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validation_text = dl_manager.download_and_extract("rumoureval2019_val.csv")
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test_text = dl_manager.download_and_extract("rumoureval2019_test.csv")
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return [
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datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": train_text, "split": "train"}),
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datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": validation_text, "split": "validation"}),
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datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": test_text, "split": "test"}),
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]
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def _generate_examples(self, filepath, split):
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with open(filepath, encoding="utf-8") as f:
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reader = csv.DictReader(f, delimiter=",")
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guid = 0
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for instance in reader:
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instance["source_text"] = instance.pop("source_text")
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instance["reply_text"] = instance.pop("reply_text")
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instance["label"] = instance.pop("label")
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instance['id'] = str(guid)
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yield guid, instance
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guid += 1
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