| import datasets | |
| import json | |
| _CITATION = """\ | |
| @misc{li2023estimating, | |
| title={Estimating Contamination via Perplexity: Quantifying Memorisation in Language Model Evaluation}, | |
| author={Yucheng Li}, | |
| year={2023}, | |
| eprint={2309.10677}, | |
| archivePrefix={arXiv}, | |
| primaryClass={cs.CL} | |
| } | |
| """ | |
| _DESCRIPTION = """\ | |
| This dataset contains BBC News articles from 2017 to 2022. The articles are arraged by month. Access the specific month by using the format "YYYY-MM" as config. Such as load_dataset("RealTimeData/bbc_alltime", "2021-1"). | |
| """ | |
| _HOMEPAGE = "https://github.com/liyucheng09/Contamination_Detector" | |
| _TIMES = ["2017-10", "2017-11", "2017-12", "2017-1", "2017-2", "2017-3", "2017-4", "2017-5", "2017-6", "2017-7", "2017-8", "2017-9", "2018-10", "2018-11", "2018-12", "2018-1", "2018-2", "2018-3", "2018-4", "2018-5", "2018-6", "2018-7", "2018-8", "2018-9", "2019-10", "2019-11", "2019-12", "2019-1", "2019-2", "2019-3", "2019-4", "2019-5", "2019-6", "2019-7", "2019-8", "2019-9", "2020-10", "2020-11", "2020-12", "2020-1", "2020-2", "2020-3", "2020-4", "2020-5", "2020-6", "2020-7", "2020-8", "2020-9", "2021-10", "2021-11", "2021-12", "2021-1", "2021-2", "2021-3", "2021-4", "2021-5", "2021-6", "2021-7", "2021-8", "2021-9", "2022-10", "2022-11", "2022-12", "2022-1", "2022-2", "2022-3", "2022-4", "2022-5", "2022-6", "2022-7", "2022-8", "2022-9", "all"] | |
| class Bbc_alltimes(datasets.GeneratorBasedBuilder): | |
| BUILDER_CONFIGS = [ | |
| datasets.BuilderConfig( | |
| name=time, version=datasets.Version("1.0.0"), description=f"BBC News articles published in the priod of {time}" | |
| ) | |
| for time in _TIMES | |
| ] | |
| def _info(self): | |
| features = datasets.Features( | |
| { | |
| "title": datasets.Value("string"), | |
| "published_date": datasets.Value("string"), | |
| "authors": datasets.Value("string"), | |
| "description": datasets.Value("string"), | |
| "section": datasets.Value("string"), | |
| "content": datasets.Value("string"), | |
| "link": datasets.Value("string"), | |
| } | |
| ) | |
| return datasets.DatasetInfo( | |
| description=_DESCRIPTION, | |
| features=features, | |
| homepage=_HOMEPAGE, | |
| citation=_CITATION, | |
| ) | |
| def _split_generators(self, dl_manager): | |
| """Returns SplitGenerators.""" | |
| if self.config.name == "all": | |
| times = _TIMES[:-1] | |
| files = dl_manager.download_and_extract('all_articles.zip') | |
| return [ | |
| datasets.SplitGenerator( | |
| name=datasets.Split.TRAIN, | |
| gen_kwargs={"files": files}, | |
| ) | |
| ] | |
| else: | |
| time = self.config.name | |
| _URL = f"articles/{time}.json" | |
| file = dl_manager.download(_URL) | |
| return [ | |
| datasets.SplitGenerator( | |
| name=datasets.Split.TRAIN, | |
| gen_kwargs={"files": file}, | |
| ) | |
| ] | |
| def _generate_examples(self, files): | |
| """Yields examples.""" | |
| if self.config.name == "all": | |
| assert isinstance(files, list) | |
| for file in files: | |
| time = file.strip('.json') | |
| with open(file, encoding="utf-8") as f: | |
| data = json.load(f) | |
| length = len(data['title']) | |
| for i in range(length): | |
| yield f'{time}-{i}', { | |
| "title": data['title'][i], | |
| "published_date": data['published_date'][i], | |
| "authors": data['authors'][i], | |
| "description": data['description'][i], | |
| "section": data['section'][i], | |
| "content": data['content'][i], | |
| "link": data['link'][i], | |
| } | |
| else: | |
| assert isinstance(files, str) | |
| time = self.config.name | |
| with open(files, encoding="utf-8") as f: | |
| data = json.load(f) | |
| length = len(data['title']) | |
| for i in range(length): | |
| yield f'{time}-{i}', { | |
| "title": data['title'][i], | |
| "published_date": data['published_date'][i], | |
| "authors": data['authors'][i], | |
| "description": data['description'][i], | |
| "section": data['section'][i], | |
| "content": data['content'][i], | |
| "link": data['link'][i], | |
| } |