| --- |
| license: apache-2.0 |
| task_categories: |
| - question-answering |
| language: |
| - el |
| tags: |
| - question |
| - answering |
| - greek |
| - nlp |
| - social |
| - media |
| - evaluation |
| - LLMs |
| - Reddit |
| pretty_name: DemosQA |
| size_categories: |
| - n<1K |
| configs: |
| - config_name: default |
| data_files: |
| - split: test |
| path: "DemosQA.csv" |
| --- |
| |
| # DemosQA |
|
|
| We introduce DemosQA (δῆμος), a novel Greek QA dataset, which is constructed using social media user questions and community-reviewed answers to better capture the Greek social and cultural zeitgeist. |
| It comprises questions extracted from the “r/greece” subreddit, each accompanied by four candidate answers, the selected best answer and its index, the date of posting, and the corresponding Reddit post ID. |
| Candidate answers are ranked based on community voting, with the highest-upvoted response designated as the reference answer. |
| This community-driven ranking mechanism not only ensures that the dataset captures genuine user preferences but also establishes a meaningful benchmark for assessing how closely large language models align with human judgments of response quality. |
| For information about dataset creation, limitations etc. see the [arxiv preprint](https://arxiv.org/abs/2602.16811). |
|
|
| <img src="demosqa.png" width="400"/> |
|
|
| ### Supported Task |
|
|
| This dataset supports evaluation of LLMs for **Question Answering**. |
|
|
| ### Language |
|
|
| All dataset samples are written in Greek. |
|
|
| ## Dataset Structure |
|
|
| The dataset is structured as a `.csv` file of 600 rows. |
| The following data fields are provided: |
|
|
| `id`: (**str**) The post id. |
| `question`: (**str**) The post question and its context. |
| `answers`: (**str**): The string containing the four candidate answers. |
| `best_answer`: (**str**) The best answer text selected by the community. |
| `best_answer_index`: (**str**) The letter index of the best answer. |
| `date`: (**str**) The post publication date. |
|
|
| ### Example code |
| ```python |
| from datasets import load_dataset |
| |
| # Load the dataset. |
| test_split = load_dataset('IMISLab/DemosQA', split = 'test') |
| print(test_split[0]) |
| ``` |
| ## Contact |
|
|
| If you have any questions/feedback about the dataset please e-mail one of the following authors: |
| ``` |
| giarelis@ceid.upatras.gr |
| cmastrokostas@ac.upatras.gr |
| karacap@upatras.gr |
| ``` |
| ## Citation |
|
|
| ``` |
| @misc{ |
| mastrokostas2026evaluatingmonolingualmultilinguallarge, |
| title = {Evaluating Monolingual and Multilingual Large Language Models for Greek Question Answering: The DemosQA Benchmark}, |
| author = {Charalampos Mastrokostas and Nikolaos Giarelis and Nikos Karacapilidis}, |
| year = {2026}, |
| eprint = {2602.16811}, |
| archivePrefix = {arXiv}, |
| primaryClass = {cs.CL}, |
| url = {https://arxiv.org/abs/2602.16811}, |
| } |
| ``` |
