NCR.py

# 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,
                    }