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# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import datasets
import json
_CITATION = """
"""
_DESCRIPTION = """
"""
_HOMEPAGE = ""
# TODO: Add the licence for the dataset here if you can find it
_LICENSE = ""
_URLS = {
"train": "https://raw.githubusercontent.com/wicsaax/NCR/main/train_2.json",
"validation": "https://raw.githubusercontent.com/wicsaax/NCR/main/dev_2.json",
"test": "https://raw.githubusercontent.com/wicsaax/NCR/main/test_2.json",
}
class NCR(datasets.GeneratorBasedBuilder):
VERSION = datasets.Version("0.0.1")
BUILDER_CONFIGS = [
datasets.BuilderConfig(
name="NCR", version=VERSION, description="Chinese dataset."
),
]
def _info(self):
features = datasets.Features(
{
"example_id": datasets.Value("string"),
"article": datasets.Value("string"),
"answer": datasets.Value("string"),
"question": datasets.Value("string"),
"options": datasets.features.Sequence(datasets.Value("string"))
}
)
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=features,
homepage=_HOMEPAGE,
license=_LICENSE,
citation=_CITATION,
)
def _split_generators(self, dl_manager):
urls = {
"train": _URLS["train"],
"test": _URLS["test"],
"validation": _URLS["validation"],
}
data_dir = dl_manager.download_and_extract(urls)
return [
datasets.SplitGenerator(
name=datasets.Split.TRAIN,
# These kwargs will be passed to _generate_examples
gen_kwargs={
"filepath": data_dir["train"],
"split": "train",
},
),
datasets.SplitGenerator(
name=datasets.Split.TEST,
# These kwargs will be passed to _generate_examples
gen_kwargs={"filepath": data_dir["test"], "split": "test"},
),
datasets.SplitGenerator(
name=datasets.Split.VALIDATION,
# These kwargs will be passed to _generate_examples
gen_kwargs={
"filepath": data_dir["validation"],
"split": "validation",
},
),
]
# method parameters are unpacked from `gen_kwargs` as given in `_split_generators`
def _generate_examples(self, filepath, split):
def pure(sens):
if sens.startswith('A') or sens.startswith('B') or sens.startswith('C') or sens.startswith('D'):
sens = sens[1:]
if sens.startswith('.') or sens.startswith('．'):
sens = sens[1:]
return sens.strip()
with open(filepath, encoding="utf-8") as f:
data = json.loads(f.read())
for article_idx,single_data in enumerate(data):
questions = single_data["Questions"]
for i in range(len(questions)):
question = questions[i]
options = [pure(i) for i in question["Choices"]]
yield f"{article_idx}_{i}", {
"example_id": single_data["ID"],
"article": single_data["Content"],
"question": question["Question"],
"answer": question["Answer"],
"options": options,
}
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