| --- |
| language: |
| - en |
| - it |
| - fr |
| - de |
| - es |
| license: cc-by-4.0 |
| task_categories: |
| - visual-question-answering |
| - question-answering |
| tags: |
| - chart-qa |
| - plot-qa |
| - multilingual |
| configs: |
| - config_name: en |
| default: true |
| data_files: |
| - split: train |
| path: en/train-*.parquet |
| - config_name: it |
| data_files: |
| - split: train |
| path: it/train-*.parquet |
| - config_name: fr |
| data_files: |
| - split: train |
| path: fr/train-*.parquet |
| - config_name: de |
| data_files: |
| - split: train |
| path: de/train-*.parquet |
| - config_name: es |
| data_files: |
| - split: train |
| path: es/train-*.parquet |
| --- |
| |
| # Multi-PlotQA |
|
|
| Multilingual chart question answering dataset. Each language is a separate config (subset). |
|
|
| ## Description |
|
|
| This dataset is a multilingual translation of [PlotQA](https://github.com/NiteshMethani/PlotQA), a large-scale chart question answering benchmark built on synthetically generated bar, line and pie charts. PlotQA pairs rendered charts with template-based questions and answers about values, comparisons, trends and chart structure, and was originally released in English only. |
|
|
| Here, the questions and answers of PlotQA have been translated into Italian, French, German and Spanish using the large language model [Qwen/Qwen3.5-122B-A10B](https://huggingface.co/Qwen/Qwen3.5-122B-A10B). The charts were not simply reused: they were re-rendered in each of the four languages, translating the text embedded in the images as well (axis labels, tick labels, legends, titles and other in-chart text), so that the visual content is fully localized and consistent with the translated questions and answers. The English config (`en`) contains the original, untranslated data. |
|
|
| Qwen3.5-122B-A10B was chosen because it is a permissive model that does not impose restrictions on the use of the data it generates, which makes the resulting translations safe to redistribute under this dataset's license. |
|
|
| **This is not a parallel dataset:** the same entries are not present in every language. About 40% of the original PlotQA data is kept in English, while the remaining 60% is split across the other four languages. Each config is therefore a distinct subset of the source data, and the configs should not be aligned row by row. |
|
|
| ## Configs |
|
|
| | config | language | rows | size | share of total | |
| |--------|----------|------|------|----------------| |
| | `en` | English | 8,109,641 | 2.6 GB | ~40% | |
| | `it` | Italian | 3,031,539 | 998.4 MB | ~15% | |
| | `fr` | French | 3,057,816 | 1.1 GB | ~15% | |
| | `de` | German | 3,010,298 | 1.1 GB | ~15% | |
| | `es` | Spanish | 3,040,185 | 1.1 GB | ~15% | |
|
|
| ## Schema |
|
|
| | column | type | description | |
| |------------|-------------------------------|-------------| |
| | `images` | `Image` | the rendered chart (PNG) | |
| | `messages` | `list[{role, content}]` | chat-format conversation: user turn holds the image + question, assistant turn holds the answer | |
| | `question` | `string` | the question in the config's language | |
| | `answer` | `string` | the answer (numeric answers are stored as strings) | |
|
|
| ## Usage |
|
|
| ```python |
| from datasets import load_dataset |
| |
| ds = load_dataset("VillanovaAI/Multi-PlotQA", "en", split="train") |
| print(ds[0]["question"]) |
| print(ds[0]["answer"]) |
| ds[0]["images"][0].show() |
| ``` |
|
|
| ## Notes |
|
|
| * `images` is a single-element list containing the chart image. |
| * `messages` follows the chat format used by vision-language models. |
