CSS: A Large-scale Cross-schema Chinese Text-to-SQL Medical Dataset
Paper
• 2305.15891 • Published
• 1
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YAML Metadata Warning: The task_categories "text2text-generation" is not in the official list: text-classification, token-classification, table-question-answering, question-answering, zero-shot-classification, translation, summarization, feature-extraction, text-generation, fill-mask, sentence-similarity, text-to-speech, text-to-audio, automatic-speech-recognition, audio-to-audio, audio-classification, audio-text-to-text, voice-activity-detection, depth-estimation, image-classification, object-detection, image-segmentation, text-to-image, image-to-text, image-to-image, image-to-video, unconditional-image-generation, video-classification, reinforcement-learning, robotics, tabular-classification, tabular-regression, tabular-to-text, table-to-text, multiple-choice, text-ranking, text-retrieval, time-series-forecasting, text-to-video, image-text-to-text, image-text-to-image, image-text-to-video, visual-question-answering, document-question-answering, zero-shot-image-classification, graph-ml, mask-generation, zero-shot-object-detection, text-to-3d, image-to-3d, image-feature-extraction, video-text-to-text, keypoint-detection, visual-document-retrieval, any-to-any, video-to-video, other
Dataset Summary
CSS is a large-scale cross-schema Chinese text-to-SQL dataset
Dataset Splits
Example-based Split
- train: 3472 question/SQL pairs
- dev: 434 question/SQL pairs
- test: 434 question/SQL pairs
Template-based Split
- train: 3470 question/SQL pairs
- dev: 430 question/SQL pairs
- test: 440 question/SQL pairs
Schema-based Split
- train: 18550 question/SQL pairs
- dev: 8150 question/SQL pairs
- test: 6920 question/SQL pairs
Citation Information
@misc{zhang2023css,
title={CSS: A Large-scale Cross-schema Chinese Text-to-SQL Medical Dataset},
author={Hanchong Zhang and Jieyu Li and Lu Chen and Ruisheng Cao and Yunyan Zhang and Yu Huang and Yefeng Zheng and Kai Yu},
year={2023},
eprint={2305.15891},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
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