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README.md

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-license: apache-2.0
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+This dataset is a merged collection of multiple text-to-SQL datasets, designed to provide a comprehensive resource for training and evaluating text-to-SQL models. It combines data from several popular benchmarks, including Spider, CoSQL, SparC, and others, to create a diverse and robust dataset for natural language to SQL query generation tasks.
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+Dataset Details
+Dataset Description
+Curated by: Mudasir Ahmad Mir
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+Language(s) (NLP): English
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+License: Apache 2.0
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+This dataset is ideal for researchers and developers working on natural language processing (NLP), semantic parsing, and database query generation. It supports a wide range of SQL complexities, from simple queries to nested and multi-turn interactions, making it suitable for both beginner and advanced text-to-SQL tasks.
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+Dataset Sources [optional]
+Repository: Hugging Face Dataset Link
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+Original Datasets:
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+Spider: Yale-LILY Lab
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+CoSQL: Yale-LILY Lab
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+SparC: Yale-LILY Lab
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+Uses
+Direct Use
+This dataset is intended for:
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+Training Text-to-SQL Models: Use this dataset to train models for converting natural language questions into SQL queries.
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+Benchmarking: Evaluate the performance of text-to-SQL models across diverse queries and domains.
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+Research: Study the challenges of semantic parsing, cross-domain generalization, and conversational SQL generation.
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+Out-of-Scope Use
+This dataset is not suitable for:
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+Tasks requiring domain-specific knowledge beyond the included datasets.
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+Applications requiring real-time or low-latency SQL generation without further fine-tuning.
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+Dataset Structure
+The dataset contains the following columns:
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+sentence: A natural language question or query.
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+sql: The corresponding SQL query for the given sentence.
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+Dataset Composition
+The dataset is created by merging the following sources:
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+Spider Dataset: A cross-domain text-to-SQL dataset with complex SQL queries.
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+CoSQL Dataset: A conversational text-to-SQL dataset with multi-turn interactions.
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+SparC Dataset: A context-dependent text-to-SQL dataset for cross-domain tasks.
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+Custom Text-to-SQL Dataset: A dataset containing additional sentence-SQL pairs.
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+Train Dataset: A dataset with context-question-answer pairs, adapted for text-to-SQL tasks.
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+Dataset Statistics
+Total Rows: [Insert total number of rows]
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+Unique SQL Patterns: [Insert number of unique SQL patterns]
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+Domains Covered: Academia, geography, conversational systems, and more.
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+Dataset Creation
+Curation Rationale
+This dataset was created to provide a unified and diverse resource for text-to-SQL tasks, combining high-quality datasets from multiple domains and use cases. The goal is to support research and development in natural language understanding and database query generation.
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+Source Data
+Data Collection and Processing
+The dataset was created by merging publicly available text-to-SQL datasets, including Spider, CoSQL, and SparC. The data was cleaned and standardized to ensure consistency in column names and formats.
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+Who are the source data producers?
+Spider: Yale-LILY Lab
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+CoSQL: Yale-LILY Lab
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+SparC: Yale-LILY Lab
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+Custom Dataset: Mudasir Ahmad Mir
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+Annotations [optional]
+The SQL queries in this dataset are manually curated and validated by the original dataset creators.
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+Annotation process
+Annotations were created as part of the original datasets. For example:
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+Spider: Annotators were provided with database schemas and asked to write SQL queries for given natural language questions.
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+CoSQL: Annotators engaged in multi-turn conversations to generate context-dependent SQL queries.
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+Who are the annotators?
+The annotators include researchers and contributors from Yale-LILY Lab and other organizations involved in the original datasets.
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+Personal and Sensitive Information
+This dataset does not contain personal, sensitive, or private information.
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+Bias, Risks, and Limitations
+Recommendations
+Users should be aware of the following:
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+The dataset may contain biases inherent in the original datasets, such as domain-specific language or query complexity.
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+The dataset is not designed for real-time applications without further fine-tuning or optimization.
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+Citation [optional]
+If you use this dataset in your research, please cite the original datasets (Spider, CoSQL, SparC, etc.) along with this merged version.
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+BibTeX:
+
+bibtex
+Copy
+@misc{text-to-sql,
+  author = {Mudasir Ahmad Mir},
+  title = {Text-to-SQL Dataset},
+  year = {2023},
+  publisher = {Hugging Face},
+  howpublished = {\url{https://huggingface.co/datasets/Mudasir692/text-to-sql}}
+}
+APA:
+Mudasir Ahmad Mir. (2023). Merged Text-to-SQL Dataset. Hugging Face. https://huggingface.co/datasets/Mudasir692/text-to-sql
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+Glossary [optional]
+Text-to-SQL: The task of converting natural language questions into SQL queries.
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+Cross-Domain: Refers to datasets that cover multiple domains or topics.
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+Multi-Turn Interactions: Conversations where SQL queries depend on previous interactions.
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+More Information [optional]
+For more information, visit the Hugging Face dataset page: Merged Text-to-SQL Dataset.
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+Dataset Card Authors [optional]
+Mudasir Ahmad Mir
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+Dataset Card Contact
+For questions or feedback, please contact Mudasir Ahmad Mir.