raoanmol/ViTaB-A

---
language:
- en
license: apache-2.0
pretty_name: ViTaB-A
task_categories:
- question-answering
tags:
- table-question-answering
configs:
- config_name: hitab
data_files:
- split: train
path: hitab/train.jsonl
- split: validation
path: hitab/validation.jsonl
- split: test
path: hitab/test.jsonl
- config_name: fetaqa
data_files:
- split: train
path: fetaqa/train.jsonl
- split: validation
path: fetaqa/validation.jsonl
- split: test
path: fetaqa/test.jsonl
---

# ViTaB-A Dataset

A normalized table question answering dataset for the ViTaB-A research project.

## Configs

- **hitab**: Derived from [HiTab](https://huggingface.co/datasets/kasnerz/hitab) (10,670 samples)
- **fetaqa**: Derived from [FeTaQA](https://huggingface.co/datasets/DongfuJiang/FeTaQA) (10,330 samples)

## Usage

```python
from datasets import load_dataset

hitab = load_dataset("raoanmol/ViTaB-A", "hitab")
fetaqa = load_dataset("raoanmol/ViTaB-A", "fetaqa")
```

## Schema

Each sample contains:

| Field | Type | Description |
|---|---|---|
| `id` | string | Unique identifier (e.g. `vitaba_000001_hitab`) |
| `split` | string | Dataset split (train/validation/test) |
| `question` | string | Natural language question about the table |
| `answer` | list or string | Answer (list for HiTab, string for FeTaQA) |
| `citation` | list[str] | Excel-style cell references (e.g. `["=E7"]`) |
| `table_json` | dict | Simplified table with keys: `title` (string), `header` (list of header rows), `rows` (list of data rows) |
| `table_md` | string | Markdown representation of the table with Excel-style row/column labels |
| `table_images` | dict | Table images as base64 PNGs. Keys: `arial`, `times_new_roman`, `red`, `blue`, `green`. Unrendered variants are empty strings. |
| `source` | string | Source dataset and split (e.g. `hitab_train`) |
| `source_id` | string | Original ID from source dataset |