| --- |
| language: |
| - en |
| license: apache-2.0 |
| task_categories: |
| - text-generation |
| tags: |
| - sql |
| - text-to-sql |
| - enterprise |
| - unsloth |
| - chatml |
| - chain-of-thought |
| - postgresql |
| - snowflake |
| - clickhouse |
| - bigquery |
| - mysql |
| size_categories: |
| - n<1K |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: data/train-* |
| - split: test |
| path: data/test-* |
| - split: regression |
| path: data/regression-* |
| --- |
| |
| # 🚀 Enterprise Text-to-SQL & Analytical BI (Verbose CoT Reasoning) |
|
|
| This dataset contains **600 curated training records with in-depth, verbose 4-phase `<Thinking>` Chain-of-Thought reasoning**, **100 frozen evaluation benchmark samples**, and **50 frozen regression verification samples** formatted in standard **ChatML (`messages`)** and Prompt-Target pairs, strictly following the **Pioneer / Prometheus research paper** 3-slice curriculum design. |
|
|
| --- |
|
|
| ## 📊 Dataset Composition & 3-Slice Breakdown |
|
|
| | Split | Rows | Proportion | Paper Design & Purpose | |
| | :--- | :---: | :---: | :--- | |
| | **`train` (Slice 1: Gold CoT)** | **360** | **60.0%** | Full domain context + verbose 4-phase `<Thinking>` Chain-of-Thought reasoning (Constraint Analysis, Formal Derivation, Numerical Gating, Implementation). | |
| | **`train` (Slice 2: Hard Negatives)** | **180** | **30.0%** | Contrastive edge-case disambiguation & boundary refutations (e.g. Non-existent columns, TLE quadratic overhead, Regulation E APP fraud boundaries). | |
| | **`train` (Slice 3: Replay Buffer)** | **60** | **10.0%** | Domain primitives & optimization anchors to prevent catastrophic forgetting. | |
| | **Total `train` Split** | **600** | **100%** | Compact, high-signal, dense curated dataset for fine-tuning. | |
| | **`test` (Frozen Eval)** | **100** | — | Held-out benchmark with zero training contamination (`eval_leakage = 0`). | |
| | **`regression` (Baseline)** | **50** | — | Baseline regression validation set. | |
|
|
| --- |
|
|
| ## 🛡️ 5-Point Quality Audit (100% Passed) |
|
|
| * **Uniqueness**: `100.0%` unique prompts (600 / 600). |
| * **Zero Eval Leakage**: `0` prompt overlaps across train, test, and regression splits. |
| * **Replay Fraction**: `10.0%` dedicated to optimization and schema resilience. |
|
|
| --- |
|
|
| ## 🚀 Usage with Unsloth / Hugging Face |
|
|
| ```python |
| from datasets import load_dataset |
| |
| dataset = load_dataset("StarsMakeGalaxy/enterprise-text2sql-curated-600") |
| print(dataset) |
| ``` |
|
|
