Datasets:
Tasks:
Question Answering
Languages:
Thai
Multilinguality:
monolingual
Size Categories:
1K<n<10K
Language Creators:
found
Annotations Creators:
expert-generated
Source Datasets:
extended|other-thaiqa
License:
File size: 4,271 Bytes
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"""TODO(squad_v2): Add a description here."""
import json
import os
import datasets
_CITATION = """\
No clear citation guidelines from source:
https://aiforthai.in.th/corpus.php
SQuAD version:
https://github.com/PyThaiNLP/thaiqa_squad
"""
_DESCRIPTION = """\
`thaiqa_squad` is an open-domain, extractive question answering dataset (4,000 questions in `train` and 74 questions in `dev`) in
[SQuAD](https://rajpurkar.github.io/SQuAD-explorer/) format, originally created by [NECTEC](https://www.nectec.or.th/en/) from
Wikipedia articles and adapted to [SQuAD](https://rajpurkar.github.io/SQuAD-explorer/) format by [PyThaiNLP](https://github.com/PyThaiNLP/).
"""
class ThaiQaSquadConfig(datasets.BuilderConfig):
def __init__(self, **kwargs):
"""BuilderConfig
Args:
**kwargs: keyword arguments forwarded to super.
"""
super(ThaiQaSquadConfig, self).__init__(**kwargs)
class ThaiqaSquad(datasets.GeneratorBasedBuilder):
_DOWNLOAD_URL = "https://github.com/PyThaiNLP/thaiqa_squad/raw/main/data.zip"
_TRAIN_FILE = "train.jsonl"
_VAL_FILE = "dev.jsonl"
BUILDER_CONFIGS = [
ThaiQaSquadConfig(
name="thaiqa_squad",
version=datasets.Version("1.0.0"),
description="`thaiqa_squad` is an open-domain, extractive question answering dataset (4,000 questions in `train` and 74 questions in `dev`) in [SQuAD](https://rajpurkar.github.io/SQuAD-explorer/) format",
),
]
def _info(self):
return datasets.DatasetInfo(
# This is the description that will appear on the datasets page.
description=_DESCRIPTION,
# datasets.features.FeatureConnectors
features=datasets.Features(
{
"question_id": datasets.Value("int32"),
"article_id": datasets.Value("int32"),
"context": datasets.Value("string"),
"question": datasets.Value("string"),
"answers": datasets.features.Sequence(
{
"answer": datasets.Value("string"),
"answer_begin_position": datasets.Value("int32"),
"answer_end_position": datasets.Value("int32"),
}
),
}
),
# 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://github.com/PyThaiNLP/thaiqa_squad",
citation=_CITATION,
)
def _split_generators(self, dl_manager):
arch_path = dl_manager.download_and_extract(self._DOWNLOAD_URL)
data_dir = os.path.join(arch_path, "data")
return [
datasets.SplitGenerator(
name=datasets.Split.TRAIN,
gen_kwargs={"filepath": os.path.join(data_dir, self._TRAIN_FILE)},
),
datasets.SplitGenerator(
name=datasets.Split.VALIDATION,
gen_kwargs={"filepath": os.path.join(data_dir, self._VAL_FILE)},
),
]
def _generate_examples(self, filepath):
"""Yields examples."""
with open(filepath, encoding="utf-8") as f:
for id_, row in enumerate(f):
data = json.loads(row)
if not isinstance(data["answer"], list):
answer = [data["answer"]]
answer_begin_position = [data["answer_begin_position"]]
answer_end_position = [data["answer_end_position"]]
yield id_, {
"question_id": data["question_id"],
"article_id": data["article_id"],
"context": data["context"],
"question": data["question"],
"answers": {
"answer": answer,
"answer_begin_position": answer_begin_position,
"answer_end_position": answer_end_position,
},
}
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