Datasets:
Languages:
Indonesian
Tags:
question-answering
Commit
·
fd0a1f0
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Parent(s):
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Upload tydiqa_id.py with huggingface_hub
Browse files- tydiqa_id.py +186 -0
tydiqa_id.py
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# coding=utf-8
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# Copyright 2022 The HuggingFace Datasets Authors and the current dataset script contributor.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from pathlib import Path
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from typing import List
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import datasets
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import json
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from nusacrowd.utils import schemas
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from nusacrowd.utils.configs import NusantaraConfig
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from nusacrowd.utils.constants import Tasks
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_CITATION = """\
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@article{clark-etal-2020-tydi,
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title = "{T}y{D}i {QA}: A Benchmark for Information-Seeking Question Answering in Typologically Diverse Languages",
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author = "Clark, Jonathan H. and
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Choi, Eunsol and
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Collins, Michael and
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Garrette, Dan and
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Kwiatkowski, Tom and
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Nikolaev, Vitaly and
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Palomaki, Jennimaria",
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journal = "Transactions of the Association for Computational Linguistics",
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volume = "8",
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year = "2020",
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address = "Cambridge, MA",
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publisher = "MIT Press",
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url = "https://aclanthology.org/2020.tacl-1.30",
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doi = "10.1162/tacl_a_00317",
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pages = "454--470",
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}
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@inproceedings{cahyawijaya-etal-2021-indonlg,
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title = "{I}ndo{NLG}: Benchmark and Resources for Evaluating {I}ndonesian Natural Language Generation",
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author = "Cahyawijaya, Samuel and
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Winata, Genta Indra and
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Wilie, Bryan and
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Vincentio, Karissa and
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Li, Xiaohong and
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Kuncoro, Adhiguna and
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Ruder, Sebastian and
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Lim, Zhi Yuan and
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Bahar, Syafri and
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Khodra, Masayu and
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Purwarianti, Ayu and
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Fung, Pascale",
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booktitle = "Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing",
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month = nov,
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year = "2021",
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address = "Online and Punta Cana, Dominican Republic",
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publisher = "Association for Computational Linguistics",
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url = "https://aclanthology.org/2021.emnlp-main.699",
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doi = "10.18653/v1/2021.emnlp-main.699",
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pages = "8875--8898"
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}
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"""
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_LANGUAGES = ["ind"] # We follow ISO639-3 language code (https://iso639-3.sil.org/code_tables/639/data)
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_LOCAL = False
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_DATASETNAME = "tydiqa_id"
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_DESCRIPTION = """\
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TyDiQA dataset is collected from Wikipedia articles with human-annotated question and answer pairs covering 11 languages.
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The question-answer pairs are collected for each language without using translation services.
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IndoNLG uses the Indonesian data from the secondary Gold passage task of the original TyDiQA dataset and
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randomly split off 15% of the training data and use it as the test set.
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"""
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_HOMEPAGE = "https://github.com/IndoNLP/indonlg"
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_LICENSE = "Creative Common Attribution Share-Alike 4.0 International"
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# For publicly available datasets you will most likely end up passing these URLs to dl_manager in _split_generators.
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# In most cases the URLs will be the same for the source and nusantara config.
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# However, if you need to access different files for each config you can have multiple entries in this dict.
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# This can be an arbitrarily nested dict/list of URLs (see below in `_split_generators` method)
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_URLS = {
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_DATASETNAME: "https://storage.googleapis.com/babert-pretraining/IndoNLG_finals/downstream_task/downstream_task_datasets.zip"
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}
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_SUPPORTED_TASKS = [Tasks.QUESTION_ANSWERING]
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_SOURCE_VERSION = "1.0.0"
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_NUSANTARA_VERSION = "1.0.0"
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class TyDiQAIdDataset(datasets.GeneratorBasedBuilder):
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SOURCE_VERSION = datasets.Version(_SOURCE_VERSION)
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NUSANTARA_VERSION = datasets.Version(_NUSANTARA_VERSION)
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BUILDER_CONFIGS = [
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NusantaraConfig(
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name="tydiqa_id_source",
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version=SOURCE_VERSION,
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description="TyDiQA Id source schema",
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schema="source",
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subset_id="tydiqa_id",
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),
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NusantaraConfig(
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name="tydiqa_id_nusantara_qa",
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version=NUSANTARA_VERSION,
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description="TyDiQA Id Nusantara schema",
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schema="nusantara_qa",
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subset_id="tydiqa_id",
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),
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]
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DEFAULT_CONFIG_NAME = "tydiqa_id_source"
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def _info(self) -> datasets.DatasetInfo:
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if self.config.schema == "source":
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features = datasets.Features(
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{
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"id": datasets.Value("string"),
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"context": datasets.Value("string"),
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"question": datasets.Value("string"),
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"label": datasets.Value("string")
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}
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)
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elif self.config.schema == "nusantara_qa":
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features = schemas.qa_features
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return datasets.DatasetInfo(
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description=_DESCRIPTION,
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features=features,
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homepage=_HOMEPAGE,
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license=_LICENSE,
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citation=_CITATION,
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)
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def _split_generators(self, dl_manager: datasets.DownloadManager) -> List[datasets.SplitGenerator]:
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url = _URLS[_DATASETNAME]
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base_path = Path(dl_manager.download_and_extract(url))
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train_data_path = base_path / "IndoNLG_downstream_tasks" / "question_answering" / "train_preprocess.json"
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valid_data_path = base_path / "IndoNLG_downstream_tasks" / "question_answering" / "valid_preprocess.json"
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test_data_path = base_path / "IndoNLG_downstream_tasks" / "question_answering" / "test_preprocess.json"
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return [
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datasets.SplitGenerator(
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name=datasets.Split.TRAIN,
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gen_kwargs={"filepath": train_data_path},
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),
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datasets.SplitGenerator(
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name=datasets.Split.VALIDATION,
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gen_kwargs={"filepath": valid_data_path},
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),
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datasets.SplitGenerator(
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name=datasets.Split.TEST,
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gen_kwargs={"filepath": test_data_path},
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)
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]
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def _generate_examples(self, filepath: Path):
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if self.config.schema == "source":
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for example in json.load(open(filepath, 'r')):
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yield example["id"], example
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elif self.config.schema == "nusantara_qa":
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for example in json.load(open(filepath, 'r')):
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yield example["id"], {
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"id": example['id'],
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"question_id": example['id'],
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"document_id": example['id'],
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"question": example['question'],
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"type": 'abstractive',
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"choices": [],
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"context": example['context'],
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"answer": [example['label']]
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}
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else:
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raise ValueError(f"Invalid config: {self.config.name}")
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