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"""PAUQ: Text-to-SQL in Russian""" |
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import json |
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import os |
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import datasets |
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logger = datasets.logging.get_logger(__name__) |
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_CITATION = """\ |
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@inproceedings{bakshandaeva-etal-2022-pauq, |
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title = "{PAUQ}: Text-to-{SQL} in {R}ussian", |
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author = "Bakshandaeva, Daria and |
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Somov, Oleg and |
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Dmitrieva, Ekaterina and |
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Davydova, Vera and |
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Tutubalina, Elena", |
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booktitle = "Findings of the Association for Computational Linguistics: EMNLP 2022", |
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month = dec, |
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year = "2022", |
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address = "Abu Dhabi, United Arab Emirates", |
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publisher = "Association for Computational Linguistics", |
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url = "https://aclanthology.org/2022.findings-emnlp.175", |
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""" |
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_DESCRIPTION = """\ |
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Pauq is a first Russian text-to-SQL dataset translated from original Spider dataset |
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with corrections and refinements of question, queries and databases. |
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""" |
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_LICENSE = "CC BY-SA 4.0" |
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_HOMEPAGE = "https://github.com/ai-spiderweb/pauq" |
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_URL = "https://huggingface.co/datasets/composite/pauq/resolve/main/formatted_pauq.zip" |
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RUSSIAN_PAUQ_TL_DESCRIPTION = "Russian PAUQ train/test split based on target length of SQL query. Long queries in train, short queries in test." |
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ENGLISH_PAUQ_TL_DESCRIPTION = "English PAUQ train/test split based on target length of SQL query. Long queries in train, short queries in test." |
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RUSSIAN_PAUQ_IID_DESCRIPTION = "Independent and identical Russian PAUQ train/test split. Сorresponds to original Spider splitting." |
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ENGLISH_PAUQ_IID_DESCRIPTION = "Independent and identical English PAUQ train/test split. Сorresponds to original Spider splitting." |
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class Pauq(datasets.GeneratorBasedBuilder): |
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VERSION = datasets.Version("1.0.0") |
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BUILDER_CONFIGS = [ |
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datasets.BuilderConfig( |
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name="ru_pauq_tl", |
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version=VERSION, |
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description=RUSSIAN_PAUQ_TL_DESCRIPTION, |
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), |
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datasets.BuilderConfig( |
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name="en_pauq_tl", |
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version=VERSION, |
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description=ENGLISH_PAUQ_TL_DESCRIPTION, |
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), |
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datasets.BuilderConfig( |
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name="ru_pauq_iid", |
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version=VERSION, |
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description=RUSSIAN_PAUQ_IID_DESCRIPTION, |
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), |
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datasets.BuilderConfig( |
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name="en_pauq_iid", |
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version=VERSION, |
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description=ENGLISH_PAUQ_IID_DESCRIPTION, |
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), |
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] |
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def _info(self): |
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features = datasets.Features( |
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{ |
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"id": datasets.Value("string"), |
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"db_id": datasets.Value("string"), |
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"source": datasets.Value("string"), |
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"type": datasets.Value("string"), |
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"question": datasets.Value("string"), |
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"query": datasets.Value("string"), |
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"sql": datasets.features.Sequence(datasets.Value("string")), |
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"question_toks": datasets.features.Sequence(datasets.Value("string")), |
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"query_toks": datasets.features.Sequence(datasets.Value("string")), |
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"query_toks_no_values": datasets.features.Sequence(datasets.Value("string")), |
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"masked_query": datasets.Value("string") |
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} |
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) |
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dataset_info = None |
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if self.config.name == 'ru_pauq_tl': |
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dataset_info = datasets.DatasetInfo( |
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description=RUSSIAN_PAUQ_TL_DESCRIPTION, |
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features=features, |
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supervised_keys=None, |
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homepage=_HOMEPAGE, |
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license=_LICENSE, |
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citation=_CITATION, |
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config_name="ru_pauq_tl") |
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elif self.config.name == "en_pauq_tl": |
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dataset_info = datasets.DatasetInfo( |
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description=ENGLISH_PAUQ_TL_DESCRIPTION, |
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features=features, |
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supervised_keys=None, |
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homepage=_HOMEPAGE, |
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license=_LICENSE, |
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citation=_CITATION, |
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config_name="en_pauq_tl") |
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elif self.config.name == 'ru_pauq_iid': |
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dataset_info = datasets.DatasetInfo( |
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description=RUSSIAN_PAUQ_IID_DESCRIPTION, |
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features=features, |
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supervised_keys=None, |
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homepage=_HOMEPAGE, |
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license=_LICENSE, |
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citation=_CITATION, |
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config_name="ru_pauq_iid") |
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elif self.config.name == 'en_pauq_iid': |
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dataset_info = datasets.DatasetInfo( |
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description=ENGLISH_PAUQ_IID_DESCRIPTION, |
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features=features, |
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supervised_keys=None, |
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homepage=_HOMEPAGE, |
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license=_LICENSE, |
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citation=_CITATION, |
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config_name="en_pauq_iid") |
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return dataset_info |
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def _split_generators(self, dl_manager): |
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downloaded_filepath = dl_manager.download_and_extract(_URL) |
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dataset_name = self.config.name |
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splits = [] |
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if dataset_name == 'ru_pauq_tl': |
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splits = [ |
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datasets.SplitGenerator( |
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name=datasets.Split.TRAIN, |
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gen_kwargs={ |
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"data_filepath": os.path.join(downloaded_filepath, "formatted_pauq/splits/ru_tl_train.json"), |
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}, |
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), |
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datasets.SplitGenerator( |
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name=datasets.Split.TEST, |
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gen_kwargs={ |
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"data_filepath": os.path.join(downloaded_filepath, "formatted_pauq/splits/ru_tl_test.json"), |
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}, |
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) |
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] |
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elif dataset_name == 'en_pauq_tl': |
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splits = [ |
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datasets.SplitGenerator( |
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name=datasets.Split.TRAIN, |
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gen_kwargs={ |
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"data_filepath": os.path.join(downloaded_filepath, "formatted_pauq/splits/en_tl_train.json"), |
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}, |
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), |
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datasets.SplitGenerator( |
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name=datasets.Split.TEST, |
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gen_kwargs={ |
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"data_filepath": os.path.join(downloaded_filepath, "formatted_pauq/splits/en_tl_test.json"), |
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}, |
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)] |
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elif dataset_name == 'ru_pauq_iid': |
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splits = [ |
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datasets.SplitGenerator( |
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name=datasets.Split.TRAIN, |
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gen_kwargs={ |
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"data_filepath": os.path.join(downloaded_filepath, "formatted_pauq/splits/ru_iid_train.json"), |
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}, |
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), |
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datasets.SplitGenerator( |
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name=datasets.Split.TEST, |
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gen_kwargs={ |
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"data_filepath": os.path.join(downloaded_filepath, "formatted_pauq/splits/ru_iid_test.json"), |
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}, |
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) |
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] |
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elif dataset_name == 'en_pauq_iid': |
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splits = [ |
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datasets.SplitGenerator( |
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name=datasets.Split.TRAIN, |
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gen_kwargs={ |
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"data_filepath": os.path.join(downloaded_filepath, "formatted_pauq/splits/en_iid_train.json"), |
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}, |
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), |
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datasets.SplitGenerator( |
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name=datasets.Split.TEST, |
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gen_kwargs={ |
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"data_filepath": os.path.join(downloaded_filepath, "formatted_pauq/splits/en_iid_test.json"), |
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}, |
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) |
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] |
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return splits |
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def _generate_examples(self, data_filepath): |
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"""This function returns the examples in the raw (text) form.""" |
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logger.info("generating examples from = %s", data_filepath) |
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with open(data_filepath, encoding="utf-8") as f: |
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pauq = json.load(f) |
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for idx, sample in enumerate(pauq): |
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yield idx, { |
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"id": sample["id"], |
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"db_id": sample["db_id"], |
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"source": sample["source"], |
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"type": sample["type"], |
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"query": sample["query"], |
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"sql": sample['sql'], |
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"question": sample["question"], |
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"question_toks": sample["question_toks"], |
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"query_toks": sample["query_toks"], |
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"query_toks_no_values": sample["query_toks_no_values"], |
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"masked_query": sample["masked_query"] |
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} |