Datasets:
Tasks:
Text Generation
Modalities:
Text
Sub-tasks:
language-modeling
Languages:
Korean
Size:
10K - 100K
ArXiv:
Tags:
question-generation
License:
File size: 2,576 Bytes
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""" python -c "from datasets import load_dataset;load_dataset('.')" """
import json
from itertools import chain
import datasets
logger = datasets.logging.get_logger(__name__)
_DESCRIPTION = """[KorQuAD](https://huggingface.co/datasets/squad_kor_v1) dataset for question generation (QG) task."""
_URL = 'https://huggingface.co/datasets/asahi417/qg_koquad/raw/main/data/processed'
_URLS = {
str(datasets.Split.TEST): [f'{_URL}/test{i:02d}.jsonl' for i in range(9)],
str(datasets.Split.TRAIN): [f'{_URL}/train{i:02d}.jsonl' for i in range(78)],
str(datasets.Split.VALIDATION): [f'{_URL}/validation{i:02d}.jsonl' for i in range(9)],
}
class QGKoQuADConfig(datasets.BuilderConfig):
"""BuilderConfig for SquadQG"""
def __init__(self, **kwargs):
"""BuilderConfig for SquadQG.
Args:
**kwargs: keyword arguments forwarded to super.
"""
super(QGKoQuADConfig, self).__init__(**kwargs)
class QGKoQuAD(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"),
"paragraph_id": 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=i, gen_kwargs={"filepaths": downloaded_file[str(i)]})
for i in [datasets.Split.TRAIN, datasets.Split.VALIDATION, datasets.Split.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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