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"""BANKING77 dataset.""" |
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import csv |
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import datasets |
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from datasets.tasks import TextClassification |
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_CITATION = """\ |
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@inproceedings{Casanueva2020, |
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author = {I{\~{n}}igo Casanueva and Tadas Temcinas and Daniela Gerz and Matthew Henderson and Ivan Vulic}, |
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title = {Efficient Intent Detection with Dual Sentence Encoders}, |
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year = {2020}, |
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month = {mar}, |
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note = {Data available at https://github.com/PolyAI-LDN/task-specific-datasets}, |
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url = {https://arxiv.org/abs/2003.04807}, |
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booktitle = {Proceedings of the 2nd Workshop on NLP for ConvAI - ACL 2020} |
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} |
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""" |
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_DESCRIPTION = """\ |
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BANKING77 dataset provides a very fine-grained set of intents in a banking domain. |
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It comprises 13,083 customer service queries labeled with 77 intents. |
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It focuses on fine-grained single-domain intent detection. |
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""" |
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_HOMEPAGE = "https://github.com/PolyAI-LDN/task-specific-datasets" |
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_LICENSE = "Creative Commons Attribution 4.0 International" |
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_TRAIN_DOWNLOAD_URL = ( |
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"https://raw.githubusercontent.com/PolyAI-LDN/task-specific-datasets/master/banking_data/train.csv" |
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) |
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_TEST_DOWNLOAD_URL = "https://raw.githubusercontent.com/PolyAI-LDN/task-specific-datasets/master/banking_data/test.csv" |
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class Banking77(datasets.GeneratorBasedBuilder): |
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"""BANKING77 dataset.""" |
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VERSION = datasets.Version("1.1.0") |
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def _info(self): |
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features = datasets.Features( |
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{ |
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"text": datasets.Value("string"), |
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"label": datasets.features.ClassLabel( |
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names=[ |
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"activate_my_card", |
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"age_limit", |
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"apple_pay_or_google_pay", |
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"atm_support", |
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"automatic_top_up", |
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"balance_not_updated_after_bank_transfer", |
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"balance_not_updated_after_cheque_or_cash_deposit", |
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"beneficiary_not_allowed", |
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"cancel_transfer", |
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"card_about_to_expire", |
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"card_acceptance", |
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"card_arrival", |
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"card_delivery_estimate", |
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"card_linking", |
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"card_not_working", |
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"card_payment_fee_charged", |
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"card_payment_not_recognised", |
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"card_payment_wrong_exchange_rate", |
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"card_swallowed", |
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"cash_withdrawal_charge", |
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"cash_withdrawal_not_recognised", |
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"change_pin", |
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"compromised_card", |
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"contactless_not_working", |
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"country_support", |
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"declined_card_payment", |
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"declined_cash_withdrawal", |
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"declined_transfer", |
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"direct_debit_payment_not_recognised", |
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"disposable_card_limits", |
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"edit_personal_details", |
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"exchange_charge", |
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"exchange_rate", |
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"exchange_via_app", |
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"extra_charge_on_statement", |
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"failed_transfer", |
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"fiat_currency_support", |
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"get_disposable_virtual_card", |
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"get_physical_card", |
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"getting_spare_card", |
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"getting_virtual_card", |
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"lost_or_stolen_card", |
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"lost_or_stolen_phone", |
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"order_physical_card", |
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"passcode_forgotten", |
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"pending_card_payment", |
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"pending_cash_withdrawal", |
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"pending_top_up", |
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"pending_transfer", |
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"pin_blocked", |
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"receiving_money", |
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"Refund_not_showing_up", |
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"request_refund", |
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"reverted_card_payment?", |
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"supported_cards_and_currencies", |
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"terminate_account", |
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"top_up_by_bank_transfer_charge", |
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"top_up_by_card_charge", |
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"top_up_by_cash_or_cheque", |
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"top_up_failed", |
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"top_up_limits", |
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"top_up_reverted", |
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"topping_up_by_card", |
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"transaction_charged_twice", |
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"transfer_fee_charged", |
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"transfer_into_account", |
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"transfer_not_received_by_recipient", |
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"transfer_timing", |
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"unable_to_verify_identity", |
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"verify_my_identity", |
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"verify_source_of_funds", |
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"verify_top_up", |
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"virtual_card_not_working", |
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"visa_or_mastercard", |
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"why_verify_identity", |
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"wrong_amount_of_cash_received", |
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"wrong_exchange_rate_for_cash_withdrawal", |
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] |
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), |
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} |
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) |
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return datasets.DatasetInfo( |
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description=_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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task_templates=[TextClassification(text_column="text", label_column="label")], |
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) |
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def _split_generators(self, dl_manager): |
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"""Returns SplitGenerators.""" |
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train_path = dl_manager.download_and_extract(_TRAIN_DOWNLOAD_URL) |
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test_path = dl_manager.download_and_extract(_TEST_DOWNLOAD_URL) |
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return [ |
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datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": train_path}), |
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datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": test_path}), |
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] |
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def _generate_examples(self, filepath): |
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"""Yields examples as (key, example) tuples.""" |
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with open(filepath, encoding="utf-8") as f: |
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csv_reader = csv.reader(f, quotechar='"', delimiter=",", quoting=csv.QUOTE_ALL, skipinitialspace=True) |
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next(csv_reader) |
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for id_, row in enumerate(csv_reader): |
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text, label = row |
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yield id_, {"text": text, "label": label} |
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