Datasets:

mhardalov
/

exams

	# coding=utf-8
	# 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.
	"""EXAMS: a benchmark dataset for multilingual and cross-lingual question answering"""

	from __future__ import absolute_import, division, print_function

	import json
	import os

	import datasets


	_CITATION = """\
	@article{hardalov2020exams,
	title={EXAMS: A Multi-subject High School Examinations Dataset for Cross-lingual and Multilingual Question Answering},
	author={Hardalov, Momchil and Mihaylov, Todor and Dimitrina Zlatkova and Yoan Dinkov and Ivan Koychev and Preslav Nvakov},
	journal={arXiv preprint arXiv:2011.03080},
	year={2020}
	}
	"""

	_DESCRIPTION = """\
	EXAMS is a benchmark dataset for multilingual and cross-lingual question answering from high school examinations.
	It consists of more than 24,000 high-quality high school exam questions in 16 languages,
	covering 8 language families and 24 school subjects from Natural Sciences and Social Sciences, among others.
	"""

	_HOMEPAGE = "https://github.com/mhardalov/exams-qa"

	_LICENSE = "CC-BY-SA-4.0"

	_URLS_LIST = [
	("alignments", "https://github.com/mhardalov/exams-qa/raw/main/data/exams/parallel_questions.jsonl"),
	]
	_URLS_LIST += [
	(
	"multilingual_train",
	"https://github.com/mhardalov/exams-qa/raw/main/data/exams/multilingual/train.jsonl.tar.gz",
	),
	("multilingual_dev", "https://github.com/mhardalov/exams-qa/raw/main/data/exams/multilingual/dev.jsonl.tar.gz"),
	("multilingual_test", "https://github.com/mhardalov/exams-qa/raw/main/data/exams/multilingual/test.jsonl.tar.gz"),
	(
	"multilingual_with_para_train",
	"https://github.com/mhardalov/exams-qa/raw/main/data/exams/multilingual/with_paragraphs/train_with_para.jsonl.tar.gz",
	),
	(
	"multilingual_with_para_dev",
	"https://github.com/mhardalov/exams-qa/raw/main/data/exams/multilingual/with_paragraphs/dev_with_para.jsonl.tar.gz",
	),
	(
	"multilingual_with_para_test",
	"https://github.com/mhardalov/exams-qa/raw/main/data/exams/multilingual/with_paragraphs/test_with_para.jsonl.tar.gz",
	),
	]

	_CROSS_LANGUAGES = ["bg", "hr", "hu", "it", "mk", "pl", "pt", "sq", "sr", "tr", "vi"]
	_URLS_LIST += [
	("crosslingual_test", "https://github.com/mhardalov/exams-qa/raw/main/data/exams/cross-lingual/test.jsonl.tar.gz"),
	(
	"crosslingual_with_para_test",
	"https://github.com/mhardalov/exams-qa/raw/main/data/exams/cross-lingual/with_paragraphs/test_with_para.jsonl.tar.gz",
	),
	]
	for ln in _CROSS_LANGUAGES:
	_URLS_LIST += [
	(
	f"crosslingual_{ln}_train",
	f"https://github.com/mhardalov/exams-qa/raw/main/data/exams/cross-lingual/train_{ln}.jsonl.tar.gz",
	),
	(
	f"crosslingual_with_para_{ln}_train",
	f"https://github.com/mhardalov/exams-qa/raw/main/data/exams/cross-lingual/with_paragraphs/train_{ln}_with_para.jsonl.tar.gz",
	),
	(
	f"crosslingual_{ln}_dev",
	f"https://github.com/mhardalov/exams-qa/raw/main/data/exams/cross-lingual/dev_{ln}.jsonl.tar.gz",
	),
	(
	f"crosslingual_with_para_{ln}_dev",
	f"https://github.com/mhardalov/exams-qa/raw/main/data/exams/cross-lingual/with_paragraphs/dev_{ln}_with_para.jsonl.tar.gz",
	),
	]
	_URLs = dict(_URLS_LIST)


	class ExamsConfig(datasets.BuilderConfig):
	def __init__(self, lang, with_para, **kwargs):
	super(ExamsConfig, self).__init__(version=datasets.Version("1.0.0", ""), **kwargs)
	self.lang = lang
	self.with_para = "_with_para" if with_para else ""


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

	VERSION = datasets.Version("1.0.0")
	BUILDER_CONFIG_CLASS = ExamsConfig
	BUILDER_CONFIGS = [
	ExamsConfig(
	lang="",
	with_para=False,
	name="alignments",
	description="loads the alignment between question IDs across languages",
	),
	ExamsConfig(
	lang="all",
	with_para=False,
	name="multilingual",
	description="Loads the unified multilingual train/dev/test split",
	),
	ExamsConfig(
	lang="all",
	with_para=True,
	name="multilingual_with_para",
	description="Loads the unified multilingual train/dev/test split with Wikipedia support paragraphs",
	),
	ExamsConfig(
	lang="all", with_para=False, name="crosslingual_test", description="Loads crosslingual test set only"
	),
	ExamsConfig(
	lang="all",
	with_para=True,
	name="crosslingual_with_para_test",
	description="Loads crosslingual test set only with Wikipedia support paragraphs",
	),
	]
	for ln in _CROSS_LANGUAGES:
	BUILDER_CONFIGS += [
	ExamsConfig(
	lang=ln,
	with_para=False,
	name=f"crosslingual_{ln}",
	description=f"Loads crosslingual train and dev set for {ln}",
	),
	ExamsConfig(
	lang=ln,
	with_para=True,
	name=f"crosslingual_with_para_{ln}",
	description=f"Loads crosslingual train and dev set for {ln} with Wikipedia support paragraphs",
	),
	]

	DEFAULT_CONFIG_NAME = (
	"multilingual_with_para" # It's not mandatory to have a default configuration. Just use one if it make sense.
	)

	def _info(self):
	if self.config.name == "alignments": # This is the name of the configuration selected in BUILDER_CONFIGS above
	features = datasets.Features(
	{
	"source_id": datasets.Value("string"),
	"target_id_list": datasets.Sequence(datasets.Value("string")),
	}
	)
	else: # This is an example to show how to have different features for "first_domain" and "second_domain"
	features = datasets.Features(
	{
	"id": datasets.Value("string"),
	"question": {
	"stem": datasets.Value("string"),
	"choices": datasets.Sequence(
	{
	"text": datasets.Value("string"),
	"label": datasets.Value("string"),
	"para": datasets.Value("string"),
	}
	),
	},
	"answerKey": datasets.Value("string"),
	"info": {
	"grade": datasets.Value("int32"),
	"subject": datasets.Value("string"),
	"language": datasets.Value("string"),
	},
	}
	)
	return datasets.DatasetInfo(
	description=_DESCRIPTION,
	features=features, # Here we define them above because they are different between the two configurations
	supervised_keys=None,
	homepage=_HOMEPAGE,
	license=_LICENSE,
	citation=_CITATION,
	)

	def _split_generators(self, dl_manager):
	"""Returns SplitGenerators."""
	data_dir = dl_manager.download_and_extract(_URLs)
	if self.config.name == "alignments":
	return [
	datasets.SplitGenerator(
	name="full",
	gen_kwargs={
	"filepath": data_dir["alignments"],
	},
	),
	]
	elif self.config.name in ["multilingual", "multilingual_with_para"]:
	return [
	datasets.SplitGenerator(
	name=spl_enum,
	gen_kwargs={
	"filepath": os.path.join(
	data_dir[f"{self.config.name}_{spl}"], f"{spl}{self.config.with_para}.jsonl"
	),
	},
	)
	for spl, spl_enum in [
	("train", datasets.Split.TRAIN),
	("dev", datasets.Split.VALIDATION),
	("test", datasets.Split.TEST),
	]
	]
	elif self.config.name in ["crosslingual_test", "crosslingual_with_para_test"]:
	return [
	datasets.SplitGenerator(
	name=datasets.Split.TEST,
	gen_kwargs={
	"filepath": os.path.join(
	data_dir[f"{self.config.name}"], f"test{self.config.with_para}.jsonl"
	),
	},
	),
	]
	else:
	return [
	datasets.SplitGenerator(
	name=spl_enum,
	gen_kwargs={
	"filepath": os.path.join(
	data_dir[f"{self.config.name}_{spl}"],
	f"{spl}_{self.config.lang}{self.config.with_para}.jsonl",
	)
	},
	)
	for spl, spl_enum in [
	("train", datasets.Split.TRAIN),
	("dev", datasets.Split.VALIDATION),
	]
	]

	def _generate_examples(self, filepath):
	f = open(filepath, encoding="utf-8")
	if self.config.name == "alignments":
	for id_, line in enumerate(f):
	line_dict = json.loads(line.strip())
	in_id, out_list = list(line_dict.items())[0]
	yield id_, {"source_id": in_id, "target_id_list": out_list}
	else:
	for id_, line in enumerate(f):
	line_dict = json.loads(line.strip())
	for choice in line_dict["question"]["choices"]:
	choice["para"] = choice.get("para", "")
	yield id_, line_dict