| dataset_info: | |
| features: | |
| - name: id | |
| dtype: string | |
| - name: table_type | |
| dtype: string | |
| - name: domain | |
| dtype: string | |
| - name: difficulty | |
| dtype: string | |
| - name: sample_index | |
| dtype: int32 | |
| - name: query | |
| dtype: string | |
| - name: answer | |
| dtype: string | |
| - name: positive_image | |
| dtype: image | |
| - name: negative_image | |
| dtype: image | |
| - name: target_cell | |
| dtype: string | |
| - name: negative_type | |
| dtype: string | |
| splits: | |
| - name: train | |
| num_bytes: 430733374.0 | |
| num_examples: 2000 | |
| download_size: 427805046 | |
| dataset_size: 430733374.0 | |
| configs: | |
| - config_name: default | |
| data_files: | |
| - split: train | |
| path: data/train-* | |
| # Table retrieval training data | |
| 2,000 synthetic hard table retrieval pairs generated with GPT-6 Luna: 500 each of Vertical, Matrix, Hierarchy, and Nested. | |
| Each train row contains a query, its answer, a positive image, a style-matched hard negative image, the table type and domain, target cell metadata (JSON string), and negative transformation type. Both image columns embed PNG bytes in Parquet shards. | |
| Negative rules: Vertical swaps distinct values in one column; Matrix moves the queried entities onto the same row or column axis; Hierarchy swaps parent groups; Nested swaps outer groups. Rendering uses randomized Matplotlib, HTML/CSS, and LaTeX styles, preserved between each positive and negative. | |
| `metadata/` preserves source table specifications, query templates and answers, original render styles, and hard-negative records. Paths inside these original records describe the source layout; use the embedded image columns when loading the dataset. | |
| ```python | |
| from datasets import load_dataset | |
| ds = load_dataset("NLPRETGOOD/table_train", split="train") | |
| ``` | |