Datasets:

masakhane
/

afriqa-gold-passages

	"""AfriQA GOLD Passages dataset."""


	import json
	import os
	from textwrap import dedent

	import datasets


	_HOMEPAGE = "https://github.com/masakhane-io/afriqa"

	_DESCRIPTION = """\
	AfriQA: Cross-lingual Open-Retrieval Question Answering for African Languages
	AfriQA is the first cross-lingual question-answering (QA) dataset with a focus on African languages.
	The dataset includes over 12,000 XOR QA examples across 10 African languages, making it an invaluable resource for developing more equitable QA technology.
	"""

	_CITATION = """\
	"""

	_URL = "https://github.com/masakhane-io/afriqa/raw/main/data/gold_passages/"

	_LANG_2_PIVOT = {
	"bem": "en",
	"fon": "fr",
	"hau": "en",
	"ibo": "en",
	"kin": "en",
	"swa": "en",
	"twi": "en",
	"wol": "fr",
	"yor": "en",
	"zul": "en",
	}

	class AfriQAConfig(datasets.BuilderConfig):
	"""BuilderConfig for AfriQA"""

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


	class AfriQA(datasets.GeneratorBasedBuilder):
	"""AfriQA dataset."""

	VERSION = datasets.Version("1.0.0")

	BUILDER_CONFIGS = [
	AfriQAConfig(name="bem", version=datasets.Version("1.0.0"), description="AfriQA Gold Passages Bemba dataset"),
	AfriQAConfig(name="fon", version=datasets.Version("1.0.0"), description="AfriQA Gold Passages Fon dataset"),
	AfriQAConfig(name="hau", version=datasets.Version("1.0.0"), description="AfriQA Gold Passages Hausa dataset"),
	AfriQAConfig(name="ibo", version=datasets.Version("1.0.0"), description="AfriQA Gold Passages Igbo dataset"),
	AfriQAConfig(name="kin", version=datasets.Version("1.0.0"), description="AfriQA Gold Passages Kinyarwanda dataset"),
	AfriQAConfig(name="swa", version=datasets.Version("1.0.0"), description="AfriQA Gold Passages Swahili dataset"),
	AfriQAConfig(name="twi", version=datasets.Version("1.0.0"), description="AfriQA Gold Passages Twi dataset"),
	AfriQAConfig(name="wol", version=datasets.Version("1.0.0"), description="AfriQA Gold Passages Wolof dataset"),
	AfriQAConfig(name="yor", version=datasets.Version("1.0.0"), description="AfriQA Gold Passages Yoruba dataset"),
	AfriQAConfig(name="zul", version=datasets.Version("1.0.0"), description="AfriQA Gold Passages Zulu dataset"),
	]

	def _info(self):
	return datasets.DatasetInfo(
	description=_DESCRIPTION,
	features=datasets.Features(
	{
	"question_lang": datasets.Value("string"),
	"question_translated": datasets.Value("string"),
	"context": datasets.Value("string"),
	"title": datasets.Value("string"),
	"answer_pivot": datasets.Value("string"),
	"answer_start": datasets.Value("string"),
	"answer_lang": datasets.Value("string"),
	}
	),
	homepage=_HOMEPAGE,
	citation=_CITATION,
	)

	def _split_generators(self, dl_manager):
	"""Returns SplitGenerators."""
	urls_to_download = {
	"train": f"{_URL}{self.config.name}/gold_span_passages.afriqa.{self.config.name}.{_LANG_2_PIVOT[self.config.name]}.train.json",
	"dev": f"{_URL}{self.config.name}/gold_span_passages.afriqa.{self.config.name}.{_LANG_2_PIVOT[self.config.name]}.dev.json",
	"test": f"{_URL}{self.config.name}/gold_span_passages.afriqa.{self.config.name}.{_LANG_2_PIVOT[self.config.name]}.test.json",
	}
	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"]}),
	datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": downloaded_files["test"]}),
	]

	def _generate_examples(self, filepath):
	"""Yields examples."""
	with open(filepath, encoding="utf-8-sig") as f:
	for _, row in enumerate(f):
	example = json.loads(row)
	_id = example["id"]

	yield _id, {
	"question_lang": example["question_lang"],
	"question_translated": example["question_translated"],
	"context": example["context"],
	"title": example["title"],
	"answer_pivot": example["answer_pivot"]["text"][0],
	"answer_start": example["answer_pivot"]["answer_start"][0],
	"answer_lang": example["answer_lang"],
	}