Update README.md

README.md

@@ -1,3 +1,78 @@
----
-license: apache-2.0
----
+---
+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
+---
+
+# DemosQA
+
+We introduce DemosQA, 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 cited preprint below.
+
+<img src="DemosQA.svg" width="200"/>
+
+### Supported Tasks and Leaderboards
+
+This dataset supports:
+
+**Question Answering:** A text generation model can be evaluated for QA.  
+
+### Languages
+
+All dataset samples are written in Greek.
+
+## Dataset Structure
+
+### Data Instances
+
+The dataset is structured as a `.csv` file of 600 rows.
+
+### Data Fields
+
+The following data fields are provided for each split:
+
+`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. 
+
+### Example code
+```python
+from datasets import load_dataset
+
+# Load the dataset.
+test_split = load_dataset('IMISLab/DemosQA', split = 'all')
+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
+
+```
+TBA
+```