Datasets:
Tasks:
Text Generation
Sub-tasks:
language-modeling
Languages:
Japanese
Multilinguality:
monolingual
Size Categories:
10K<n<100K
Source Datasets:
SkelterLabsInc/JaQuAD
ArXiv:
License:
File size: 2,694 Bytes
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import json
import datasets
logger = datasets.logging.get_logger(__name__)
_DESCRIPTION = """
[JaQuAD](https://github.com/SkelterLabsInc/JaQuAD) dataset for question generation (QG) task. The test set of the original
data is not publicly released, so we randomly sampled test questions from the training set.
"""
_URL = 'https://huggingface.co/datasets/asahi417/qg_jaquad/raw/main/data/processed'
_URLS = {
'train': ['{}/train{:02d}.jsonl'.format(_URL, i) for i in range(28)],
'test': ['{}/test{:02d}.jsonl'.format(_URL, i) for i in range(4)],
'validation': ['{}/validation{:02d}.jsonl'.format(_URL, i) for i in range(4)]
}
class QGJaquadConfig(datasets.BuilderConfig):
"""BuilderConfig for SquadQG"""
def __init__(self, **kwargs):
"""BuilderConfig for SquadQG.
Args:
**kwargs: keyword arguments forwarded to super.
"""
super(QGJaquadConfig, self).__init__(**kwargs)
class QGJaquad(datasets.GeneratorBasedBuilder):
def _info(self):
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=datasets.Features(
{
"answer": datasets.Value("string"),
"question": datasets.Value("string"),
"sentence": datasets.Value("string"),
"paragraph": datasets.Value("string"),
"sentence_answer": datasets.Value("string"),
"paragraph_answer": datasets.Value("string"),
"paragraph_sentence": datasets.Value("string")
}
),
supervised_keys=None,
homepage="https://github.com/asahi417/lm-question-generation"
)
def _split_generators(self, dl_manager):
downloaded_file = dl_manager.download_and_extract(_URLS)
return [
datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepaths": downloaded_file["train"]}),
datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepaths": downloaded_file["validation"]}),
datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepaths": downloaded_file["test"]}),
]
def _generate_examples(self, filepaths):
_key = 0
for filepath in filepaths:
logger.info("generating examples from = %s", filepath)
with open(filepath, encoding="utf-8") as f:
_list = f.read().split('\n')
if _list[-1] == '':
_list = _list[:-1]
for i in _list:
data = json.loads(i)
yield _key, data
_key += 1
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