Datasets:

clarin-pl
/

poquad

	"""FROM SQUAD_V2"""


	import json

	import datasets
	from datasets.tasks import QuestionAnsweringExtractive


	# TODO(squad_v2): BibTeX citation
	_CITATION = """\
	Tuora, R., Zawadzka-Paluektau, N., Klamra, C., Zwierzchowska, A., Kobyliński, Ł. (2022).
	Towards a Polish Question Answering Dataset (PoQuAD).
	In: Tseng, YH., Katsurai, M., Nguyen, H.N. (eds) From Born-Physical to Born-Virtual: Augmenting Intelligence in Digital Libraries. ICADL 2022.
	Lecture Notes in Computer Science, vol 13636. Springer, Cham.
	https://doi.org/10.1007/978-3-031-21756-2_16
	"""

	_DESCRIPTION = """\
	PoQuaD description
	"""


	_URLS = {
	"train": "poquad-train.json",
	"dev": "poquad-dev.json",
	}


	class SquadV2Config(datasets.BuilderConfig):
	"""BuilderConfig for SQUAD."""

	def __init__(self, **kwargs):
	"""BuilderConfig for SQUADV2.
	Args:
	**kwargs: keyword arguments forwarded to super.
	"""
	super(SquadV2Config, self).__init__(**kwargs)


	class SquadV2(datasets.GeneratorBasedBuilder):
	"""TODO(squad_v2): Short description of my dataset."""

	# TODO(squad_v2): Set up version.
	BUILDER_CONFIGS = [
	SquadV2Config(name="poquad", version=datasets.Version("1.0.0"), description="PoQuaD plaint text"),
	]

	def _info(self):
	# TODO(squad_v2): Specifies the datasets.DatasetInfo object
	return datasets.DatasetInfo(
	# This is the description that will appear on the datasets page.
	description=_DESCRIPTION,
	# datasets.features.FeatureConnectors
	features=datasets.Features(
	{
	"id": datasets.Value("string"),
	"title": datasets.Value("string"),
	"context": datasets.Value("string"),
	"question": datasets.Value("string"),
	"answers": datasets.features.Sequence(
	{
	"text": datasets.Value("string"),
	"answer_start": datasets.Value("int32"),
	}
	),
	# These are the features of your dataset like images, labels ...
	}
	),
	# If there's a common (input, target) tuple from the features,
	# specify them here. They'll be used if as_supervised=True in
	# builder.as_dataset.
	supervised_keys=None,
	# Homepage of the dataset for documentation
	homepage="https://rajpurkar.github.io/SQuAD-explorer/",
	citation=_CITATION,
	task_templates=[
	QuestionAnsweringExtractive(
	question_column="question", context_column="context", answers_column="answers"
	)
	],
	)

	def _split_generators(self, dl_manager):
	"""Returns SplitGenerators."""
	# TODO(squad_v2): Downloads the data and defines the splits
	# dl_manager is a datasets.download.DownloadManager that can be used to
	# download and extract URLs
	urls_to_download = _URLS
	downloaded_files = dl_manager.download_and_extract(urls_to_download)

	return [
	datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_files["train"]}),
	datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": downloaded_files["dev"]}),
	]

	def _generate_examples(self, filepath):
	"""Yields examples."""
	# TODO(squad_v2): Yields (key, example) tuples from the dataset
	with open(filepath, encoding="utf-8") as f:
	squad = json.load(f)
	id_ = 0
	for example in squad["data"]:
	title = example.get("title", "")
	# paragraph_id = example["id"]
	for paragraph in example["paragraphs"]:
	context = paragraph["context"] # do not strip leading blank spaces GH-2585
	for qa in paragraph["qas"]:
	question = qa["question"]

	if "answers" not in qa:
	continue
	answer_starts = [answer["answer_start"] for answer in qa["answers"]]
	#answer_ends = [answer["answer_end"] for answer in qa["answers"]]
	answers = [answer["text"] for answer in qa["answers"]]
	# is_impossible = qa["is_impossible"]
	# Features currently used are "context", "question", and "answers".
	# Others are extracted here for the ease of future expansions.
	id_ += 1
	yield str(id_), {
	"id": str(id_),
	"title": title,
	"context": context,
	"question": question,
	#"is_impossible" : is_impossible,
	# "paragraph_id": paragraph_id,
	"answers": {
	"answer_start": answer_starts,
	#"answer_end": answer_ends,
	"text": answers,
	},
	}