Datasets:
Languages:
Indonesian
Tags:
question-answering
File size: 7,019 Bytes
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# coding=utf-8
# Copyright 2022 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.
from pathlib import Path
from typing import List
import datasets
import json
from nusacrowd.utils import schemas
from nusacrowd.utils.configs import NusantaraConfig
from nusacrowd.utils.constants import Tasks
_CITATION = """\
@article{clark-etal-2020-tydi,
title = "{T}y{D}i {QA}: A Benchmark for Information-Seeking Question Answering in Typologically Diverse Languages",
author = "Clark, Jonathan H. and
Choi, Eunsol and
Collins, Michael and
Garrette, Dan and
Kwiatkowski, Tom and
Nikolaev, Vitaly and
Palomaki, Jennimaria",
journal = "Transactions of the Association for Computational Linguistics",
volume = "8",
year = "2020",
address = "Cambridge, MA",
publisher = "MIT Press",
url = "https://aclanthology.org/2020.tacl-1.30",
doi = "10.1162/tacl_a_00317",
pages = "454--470",
}
@inproceedings{cahyawijaya-etal-2021-indonlg,
title = "{I}ndo{NLG}: Benchmark and Resources for Evaluating {I}ndonesian Natural Language Generation",
author = "Cahyawijaya, Samuel and
Winata, Genta Indra and
Wilie, Bryan and
Vincentio, Karissa and
Li, Xiaohong and
Kuncoro, Adhiguna and
Ruder, Sebastian and
Lim, Zhi Yuan and
Bahar, Syafri and
Khodra, Masayu and
Purwarianti, Ayu and
Fung, Pascale",
booktitle = "Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing",
month = nov,
year = "2021",
address = "Online and Punta Cana, Dominican Republic",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2021.emnlp-main.699",
doi = "10.18653/v1/2021.emnlp-main.699",
pages = "8875--8898"
}
"""
_LANGUAGES = ["ind"] # We follow ISO639-3 language code (https://iso639-3.sil.org/code_tables/639/data)
_LOCAL = False
_DATASETNAME = "tydiqa_id"
_DESCRIPTION = """\
TyDiQA dataset is collected from Wikipedia articles with human-annotated question and answer pairs covering 11 languages.
The question-answer pairs are collected for each language without using translation services.
IndoNLG uses the Indonesian data from the secondary Gold passage task of the original TyDiQA dataset and
randomly split off 15% of the training data and use it as the test set.
"""
_HOMEPAGE = "https://github.com/IndoNLP/indonlg"
_LICENSE = "Creative Common Attribution Share-Alike 4.0 International"
# For publicly available datasets you will most likely end up passing these URLs to dl_manager in _split_generators.
# In most cases the URLs will be the same for the source and nusantara config.
# However, if you need to access different files for each config you can have multiple entries in this dict.
# This can be an arbitrarily nested dict/list of URLs (see below in `_split_generators` method)
_URLS = {
_DATASETNAME: "https://storage.googleapis.com/babert-pretraining/IndoNLG_finals/downstream_task/downstream_task_datasets.zip"
}
_SUPPORTED_TASKS = [Tasks.QUESTION_ANSWERING]
_SOURCE_VERSION = "1.0.0"
_NUSANTARA_VERSION = "1.0.0"
class TyDiQAIdDataset(datasets.GeneratorBasedBuilder):
SOURCE_VERSION = datasets.Version(_SOURCE_VERSION)
NUSANTARA_VERSION = datasets.Version(_NUSANTARA_VERSION)
BUILDER_CONFIGS = [
NusantaraConfig(
name="tydiqa_id_source",
version=SOURCE_VERSION,
description="TyDiQA Id source schema",
schema="source",
subset_id="tydiqa_id",
),
NusantaraConfig(
name="tydiqa_id_nusantara_qa",
version=NUSANTARA_VERSION,
description="TyDiQA Id Nusantara schema",
schema="nusantara_qa",
subset_id="tydiqa_id",
),
]
DEFAULT_CONFIG_NAME = "tydiqa_id_source"
def _info(self) -> datasets.DatasetInfo:
if self.config.schema == "source":
features = datasets.Features(
{
"id": datasets.Value("string"),
"context": datasets.Value("string"),
"question": datasets.Value("string"),
"label": datasets.Value("string")
}
)
elif self.config.schema == "nusantara_qa":
features = schemas.qa_features
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=features,
homepage=_HOMEPAGE,
license=_LICENSE,
citation=_CITATION,
)
def _split_generators(self, dl_manager: datasets.DownloadManager) -> List[datasets.SplitGenerator]:
url = _URLS[_DATASETNAME]
base_path = Path(dl_manager.download_and_extract(url))
train_data_path = base_path / "IndoNLG_downstream_tasks" / "question_answering" / "train_preprocess.json"
valid_data_path = base_path / "IndoNLG_downstream_tasks" / "question_answering" / "valid_preprocess.json"
test_data_path = base_path / "IndoNLG_downstream_tasks" / "question_answering" / "test_preprocess.json"
return [
datasets.SplitGenerator(
name=datasets.Split.TRAIN,
gen_kwargs={"filepath": train_data_path},
),
datasets.SplitGenerator(
name=datasets.Split.VALIDATION,
gen_kwargs={"filepath": valid_data_path},
),
datasets.SplitGenerator(
name=datasets.Split.TEST,
gen_kwargs={"filepath": test_data_path},
)
]
def _generate_examples(self, filepath: Path):
if self.config.schema == "source":
for example in json.load(open(filepath, 'r')):
yield example["id"], example
elif self.config.schema == "nusantara_qa":
for example in json.load(open(filepath, 'r')):
yield example["id"], {
"id": example['id'],
"question_id": example['id'],
"document_id": example['id'],
"question": example['question'],
"type": 'abstractive',
"choices": [],
"context": example['context'],
"answer": [example['label']]
}
else:
raise ValueError(f"Invalid config: {self.config.name}")
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