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thesis-split: 784/196 partition stratified by tier, spatial function and territorial division

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  1. README.md +20 -2
  2. split_manifest.json +68 -0
  3. train.parquet +2 -2
  4. validation.parquet +2 -2
README.md CHANGED
@@ -46,10 +46,28 @@ The dataset comprises manually annotated question-SQL pairs classified into four
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  ## 📁 Files and Reproducibility
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- The dataset is divided into standard `train.parquet` and `validation.parquet` splits.
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  **⚠️ Important Note on Reproducibility:**
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- The baseline experiments documented in the original paper were conducted **exclusively** on the original 980 question-SQL pairs. The dataset files available here also include additional data generated through data augmentation techniques.
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  To exactly replicate the experiments and results from the original paper, you **must**:
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  1. Use the dataset version associated with the **`paper-released`** tag.
 
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  ## 📁 Files and Reproducibility
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+ The dataset is divided into standard `train.parquet` and `validation.parquet` splits. Two tagged snapshots are preserved so that published results remain reproducible:
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+
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+ | Tag | Content | Used in |
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+ | :--- | :--- | :--- |
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+ | `paper-released` | 980 curated pairs (`source = base_dataset`) plus five augmented partitions in `train.parquet`; a separate 196-pair `validation.parquet` | SBBD 2026 paper (first execution of the experiments) |
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+ | `thesis-split` (current `main`) | The 980 curated pairs partitioned into 784 training and 196 validation pairs, stratified by complexity tier, spatial function and territorial division (one validation pair per tier × function × division cell, seed 42); `split_manifest.json` records the counts and checksums | Master's thesis (second execution of the experiments) |
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+
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+ ### Loading the thesis split (Python)
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+
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+ ```python
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+ from datasets import load_dataset
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+
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+ dataset = load_dataset("datafromlopes/atlas-sql-br", revision="thesis-split")
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+ print(len(dataset["train"]), len(dataset["validation"])) # 784 196
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+ ```
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+
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+ The thesis split is generated by `core/make_paper_split.py` in the [code repository](https://github.com/datafromlopes/atlas-sql-br), which also holds the training, generation and evaluation pipeline and the results of the thesis run. The fine-tuned adapter is published as [`datafromlopes/llama-3.1-8b-atlassql-br`](https://huggingface.co/datafromlopes/llama-3.1-8b-atlassql-br).
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+
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+ ### Reproducing the paper
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  **⚠️ Important Note on Reproducibility:**
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+ The baseline experiments documented in the original paper were conducted **exclusively** on the original 980 question-SQL pairs. The `paper-released` snapshot also includes additional data generated through data augmentation techniques.
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  To exactly replicate the experiments and results from the original paper, you **must**:
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  1. Use the dataset version associated with the **`paper-released`** tag.
split_manifest.json ADDED
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+ {
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+ "source_file": "/Users/diegolopes/repositories/atlas_sql_br/data/paper_released/train.parquet",
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+ "source_md5": "bd62f326098f882009ca72b7f26c5c97",
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+ "source_partition": "base_dataset",
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+ "seed": 42,
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+ "val_fraction": 0.2,
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+ "stratified_by": [
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+ "level",
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+ "geospatial_functions",
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+ "territorial_division"
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+ ],
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+ "train": {
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+ "rows": 784,
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+ "by_tier": {
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+ "Difícil": 196,
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+ "Fácil": 196,
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+ "Muito Difícil": 196,
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+ "Médio": 196
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+ },
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+ "by_function": {
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+ "País": 112,
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+ "Rua": 112
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+ }
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+ },
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+ "validation": {
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+ "rows": 196,
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+ "by_tier": {
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+ "País": 28,
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+ "Região": 28,
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+ }
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+ "train_md5": "c759e6c383ed39459ea9622dc1160911",
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+ "validation_md5": "645ff583d3deb55dbbe02807d6e0ecaf"
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+ }
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