| --- |
| dataset_info: |
| features: |
| - name: example_id |
| dtype: string |
| - name: task |
| dtype: |
| class_label: |
| names: |
| '0': col_type |
| '1': ent_link |
| '2': fetaqa |
| '3': hitab |
| '4': hybridqa |
| '5': infotabs |
| '6': merged_cell_detection |
| '7': rel_extraction |
| '8': row_column_extraction |
| '9': struct_aware_parse |
| '10': tabfact |
| '11': table_cell_extraction |
| '12': table_cell_location |
| '13': table_instruction |
| '14': table_recognition |
| '15': table_size_detection |
| '16': tabmwp |
| '17': tat-qa |
| '18': totto |
| '19': wikibio |
| '20': wikitq |
| - name: src_example_ids |
| dtype: string |
| - name: table_id |
| dtype: string |
| - name: table_seed_id |
| dtype: string |
| - name: table_seed_dataset |
| dtype: string |
| - name: table_page_title |
| dtype: string |
| - name: table_section_title |
| dtype: string |
| - name: table_variant |
| dtype: string |
| - name: img_source |
| dtype: |
| class_label: |
| names: |
| '0': PubTabNet |
| '1': TABMWP |
| '2': seed_render |
| '3': wikipedia |
| - name: input |
| dtype: large_string |
| - name: output |
| dtype: string |
| - name: split |
| dtype: |
| class_label: |
| names: |
| '0': dev |
| '1': test |
| '2': train |
| - name: metadata |
| dtype: string |
| - name: table_wiki_page_id |
| dtype: string |
| - name: table_wiki_old_id |
| dtype: string |
| - name: table_html |
| dtype: large_string |
| - name: table_img |
| dtype: image |
| splits: |
| - name: wikibio_train |
| num_bytes: 11073920562 |
| num_examples: 140000 |
| - name: rel_extraction_train |
| num_bytes: 14264320579 |
| num_examples: 60615 |
| - name: col_type_train |
| num_bytes: 27297001896 |
| num_examples: 140000 |
| - name: tatqa_train |
| num_bytes: 114858299 |
| num_examples: 2201 |
| - name: hybridqa_train |
| num_bytes: 14932215002 |
| num_examples: 62670 |
| - name: table_instruction_train |
| num_bytes: 12180312819 |
| num_examples: 136944 |
| - name: tabmwp_train |
| num_bytes: 326184930 |
| num_examples: 23059 |
| - name: hitab_train |
| num_bytes: 1026591527 |
| num_examples: 7417 |
| - name: table_recognition_train |
| num_bytes: 788489258 |
| num_examples: 6927 |
| - name: table_cell_extraction_train |
| num_bytes: 2102295132 |
| num_examples: 7727 |
| - name: table_size_detection_train |
| num_bytes: 1695496703 |
| num_examples: 7800 |
| - name: merged_cell_detection_train |
| num_bytes: 993975274 |
| num_examples: 7500 |
| - name: table_cell_location_train |
| num_bytes: 1227016660 |
| num_examples: 7708 |
| - name: tabfact_train |
| num_bytes: 10356555069 |
| num_examples: 87717 |
| - name: totto_train |
| num_bytes: 36076773336 |
| num_examples: 110934 |
| - name: ent_link_train |
| num_bytes: 339639370460 |
| num_examples: 140000 |
| - name: row_column_extraction_train |
| num_bytes: 2261383511 |
| num_examples: 7721 |
| - name: infotabs_train |
| num_bytes: 1486818337 |
| num_examples: 16538 |
| - name: wikitq_train |
| num_bytes: 3661437306 |
| num_examples: 14152 |
| - name: struct_aware_parse_train |
| num_bytes: 2711049786 |
| num_examples: 126581 |
| - name: fetaqa_train |
| num_bytes: 366072076 |
| num_examples: 3006 |
| download_size: 242660503785 |
| dataset_size: 484582138522 |
| configs: |
| - config_name: default |
| data_files: |
| - split: wikibio_train |
| path: data/wikibio_train-* |
| - split: rel_extraction_train |
| path: data/rel_extraction_train-* |
| - split: col_type_train |
| path: data/col_type_train-* |
| - split: tatqa_train |
| path: data/tatqa_train-* |
| - split: hybridqa_train |
| path: data/hybridqa_train-* |
| - split: table_instruction_train |
| path: data/table_instruction_train-* |
| - split: tabmwp_train |
| path: data/tabmwp_train-* |
| - split: hitab_train |
| path: data/hitab_train-* |
| - split: fetaqa_train |
| path: data/fetaqa_train-* |
| - split: table_recognition_train |
| path: data/table_recognition_train-* |
| - split: table_cell_extraction_train |
| path: data/table_cell_extraction_train-* |
| - split: table_size_detection_train |
| path: data/table_size_detection_train-* |
| - split: merged_cell_detection_train |
| path: data/merged_cell_detection_train-* |
| - split: table_cell_location_train |
| path: data/table_cell_location_train-* |
| - split: tabfact_train |
| path: data/tabfact_train-* |
| - split: totto_train |
| path: data/totto_train-* |
| - split: ent_link_train |
| path: data/ent_link_train-* |
| - split: row_column_extraction_train |
| path: data/row_column_extraction_train-* |
| - split: infotabs_train |
| path: data/infotabs_train-* |
| - split: wikitq_train |
| path: data/wikitq_train-* |
| - split: struct_aware_parse_train |
| path: data/struct_aware_parse_train-* |
| --- |
| ### TABLET-Medium |
|
|
| This is the _Medium_ sized **train set** of the **TABLET** dataset. It contains the train examples for all **TABLET** tasks. |
| Each task is capped at **140,000 examples**, resulting in a total of **1,117,217 training examples** across **17 tasks**. |
| This dataset is self-contained, each example includes a table image, its HTML representation, and the associated task data. |
| However, if you're interested in downloading just the TABLET tables, check out [TABLET-tables](https://huggingface.co/datasets/alonsoapp/TABLET-tables). |
|
|
| All TABLET Subsets: |
| - _(train)_ [**TABLET-Small**](https://huggingface.co/datasets/alonsoapp/TABLET-Small): The smallest TABLET subset, including **776,602 examples** across **14 tasks**. |
| - _(train)_ [**TABLET-Medium**](https://huggingface.co/datasets/alonsoapp/TABLET-Medium): Includes all examples from _TABLET-Small_, plus **Column Type Annotation**, **Entity Linking**, and **Relation Extraction** tasks. Each task is capped at **140,000 examples**, resulting in a total of **1,117,217 training examples** across **17 tasks**. |
| - _(train)_ [**TABLET-Large**](https://huggingface.co/datasets/alonsoapp/TABLET-Large): Includes all examples from _TABLET-Medium_ with **no cap** on task size, resulting in a total of **3,505,311 training examples** across **17 tasks**. |
| - _(dev)_ [**TABLET-dev**](https://huggingface.co/datasets/alonsoapp/TABLET-dev): The **development** set of TABLET. |
| - _(test)_ [**TABLET-test**](https://huggingface.co/datasets/alonsoapp/TABLET-test): The **test** set of TABLET. |
|
|
| For more information, see our [paper](https://arxiv.org/pdf/2509.21205), [website](https://precious-panda-5ce815.netlify.app/tablet/), and [GitHub repository](https://github.com/AlonsoApp/TABLET). |
|
|
| #### Using the Dataset |
|
|
| Given its size, we recommend [streaming](https://huggingface.co/docs/datasets/stream) the dataset instead of downloading it entirely to disk: |
|
|
| ```python |
| from datasets import load_dataset |
| dataset = load_dataset('alonsoapp/TABLET-Medium', split='fetaqa_train', streaming=True) |
| print(next(iter(dataset))) |
| ``` |
|
|
| #### Data Fields |
|
|
| Each sample within the dataset is structured with the following fields: |
|
|
| * **`example_id`**: Unique identifier for the example. |
| * **`task`**: The name of the task this example belongs to. |
| * **`src_example_ids`**: IDs of the original examples from the source dataset, formatted as `{"Dataset name": "id"}`. Use the `get_original_example` helper function from [our published code](https://github.com/AlonsoApp/TABLET) to easily retrieve the source example. |
| * **`table_id`**: Unique identifier for the table. |
| * **`table_seed_id`**: ID referencing the table in its original (seed) dataset. |
| * **`table_seed_dataset`**: Name of the dataset where the table originated, typically matching the source dataset of the example. |
| * **`table_page_title`**: For tables sourced from Wikipedia, the corresponding page title. |
| * **`table_section_title`**: For Wikipedia tables, the title of the section where the table appears. |
| * **`table_variant`**: Either "raw" or "highlighted". Some examples visually highlight specific cells and this field indicates whether the table is unmodified (raw) or includes highlights (highlighted). |
| * **`img_source`**: Source of the table image. That is, whether the image comes from the Wikipedia visualization (wikipedia), a synthetic renderization from the data in the soruce dataset (seed_render), or directly copied from the original visualization of the table of the source dataset (PubTabNet, TabMWP). |
| * **`input`**: The _instructified_ input used for training and evaluation (see [paper](https://arxiv.org/pdf/2509.21205)). The input can be rephrased using information in `metadata`. |
| * **`output`**: The expected model output for the given `input`. |
| * **`split`**: Dataset split: `train`, `dev`, or `test`. |
| * **`metadata`**: Atomic data for the example to enable reconstruction or rephrasing of the instruction. Each key indicates a data element, the value can be obtained from either the _'input'_ or the _'output'_ strings using the substring defined by the character indexes in 'idx'. Use the get_metadata helper function from [our published code](https://github.com/AlonsoApp/TABLET) to retrieve these values. |
| * **`table_wiki_page_id`**: For Wikipedia tables, the page ID corresponding to the article containing the table (useful for Wikipedia API queries). |
| * **`table_wiki_old_id`**: For Wikipedia tables, the “old ID” identifying the article version at the crawl time. |
| * **`table_html`**: HTML representation of the table. Use the `render_table` helper function from [our code](https://github.com/AlonsoApp/TABLET) to render it in its original style. For highlighted variants, highlighted cells use the CSS class `demeter_highlighted_cell`. Remove any decorators for this class in the CSS to render identically to the raw version. |
| * **`table_img`**: The image representation of the table. |
| |
| #### Citation |
| |
| If you find **TABLET** useful in your research, please consider citing it by the following BibTeX entry. |
| |
| ```bibtex |
| @misc{alonso2025tabletlargescaledatasetrobust, |
| title={TABLET: A Large-Scale Dataset for Robust Visual Table Understanding}, |
| author={Iñigo Alonso and Imanol Miranda and Eneko Agirre and Mirella Lapata}, |
| year={2025}, |
| eprint={2509.21205}, |
| archivePrefix={arXiv}, |
| primaryClass={cs.CV}, |
| url={https://arxiv.org/abs/2509.21205}, |
| } |
| ``` |
