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"""FROM SQUAD_V2""" |
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import json |
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import datasets |
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from datasets.tasks import QuestionAnsweringExtractive |
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_CITATION = """\ |
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Tuora, R., Zawadzka-Paluektau, N., Klamra, C., Zwierzchowska, A., Kobyliński, Ł. (2022). |
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Towards a Polish Question Answering Dataset (PoQuAD). |
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In: Tseng, YH., Katsurai, M., Nguyen, H.N. (eds) From Born-Physical to Born-Virtual: Augmenting Intelligence in Digital Libraries. ICADL 2022. |
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Lecture Notes in Computer Science, vol 13636. Springer, Cham. |
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https://doi.org/10.1007/978-3-031-21756-2_16 |
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""" |
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_DESCRIPTION = """\ |
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PoQuaD description |
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""" |
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_URLS = { |
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"train": "https://huggingface.co/datasets/clarin-pl/poquad/blob/main/poquad-dev.json", |
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"dev": "https://huggingface.co/datasets/clarin-pl/poquad/blob/main/poquad-train.json, |
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} |
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class SquadV2Config(datasets.BuilderConfig): |
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"""BuilderConfig for SQUAD.""" |
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def __init__(self, **kwargs): |
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"""BuilderConfig for SQUADV2. |
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Args: |
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**kwargs: keyword arguments forwarded to super. |
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""" |
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super(SquadV2Config, self).__init__(**kwargs) |
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class SquadV2(datasets.GeneratorBasedBuilder): |
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"""TODO(squad_v2): Short description of my dataset.""" |
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# TODO(squad_v2): Set up version. |
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BUILDER_CONFIGS = [ |
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SquadV2Config(name="poquad", version=datasets.Version("1.0.0"), description="PoQuaD plaint text"), |
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] |
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def _info(self): |
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# TODO(squad_v2): Specifies the datasets.DatasetInfo object |
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return datasets.DatasetInfo( |
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# This is the description that will appear on the datasets page. |
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description=_DESCRIPTION, |
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# datasets.features.FeatureConnectors |
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features=datasets.Features( |
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{ |
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"id": datasets.Value("string"), |
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"title": datasets.Value("string"), |
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"context": datasets.Value("string"), |
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"question": datasets.Value("string"), |
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"answers": datasets.features.Sequence( |
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{ |
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"text": datasets.Value("string"), |
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"answer_start": datasets.Value("int32"), |
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} |
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), |
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# These are the features of your dataset like images, labels ... |
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} |
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), |
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# If there's a common (input, target) tuple from the features, |
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# specify them here. They'll be used if as_supervised=True in |
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# builder.as_dataset. |
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supervised_keys=None, |
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# Homepage of the dataset for documentation |
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homepage="https://rajpurkar.github.io/SQuAD-explorer/", |
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citation=_CITATION, |
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task_templates=[ |
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QuestionAnsweringExtractive( |
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question_column="question", context_column="context", answers_column="answers" |
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) |
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], |
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) |
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def _split_generators(self, dl_manager): |
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"""Returns SplitGenerators.""" |
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# TODO(squad_v2): Downloads the data and defines the splits |
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# dl_manager is a datasets.download.DownloadManager that can be used to |
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# download and extract URLs |
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urls_to_download = _URLS |
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downloaded_files = dl_manager.download_and_extract(urls_to_download) |
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return [ |
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datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_files["train"]}), |
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datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": downloaded_files["dev"]}), |
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] |
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def _generate_examples(self, filepath): |
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"""Yields examples.""" |
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# TODO(squad_v2): Yields (key, example) tuples from the dataset |
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with open(filepath, encoding="utf-8") as f: |
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squad = json.load(f) |
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for example in squad["data"]: |
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title = example.get("title", "") |
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for paragraph in example["paragraphs"]: |
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context = paragraph["context"] # do not strip leading blank spaces GH-2585 |
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for qa in paragraph["qas"]: |
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question = qa["question"] |
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id_ = qa["id"] |
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answer_starts = [answer["answer_start"] for answer in qa["answers"]] |
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answers = [answer["text"] for answer in qa["answers"]] |
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# Features currently used are "context", "question", and "answers". |
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# Others are extracted here for the ease of future expansions. |
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yield id_, { |
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"title": title, |
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"context": context, |
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"question": question, |
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"id": id_, |
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"answers": { |
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"answer_start": answer_starts, |
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"text": answers, |
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}, |
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} |
