Update README.md

README.md

@@ -1,5 +1,86 @@
+# 🧠 PerCQA: A Persian Community Question Answering Dataset
+
+**PerCQA** is the first large-scale dataset for Community Question Answering (CQA) in the Persian language. It was created to support research in question retrieval, answer selection, and overall QA system development for low-resource languages, particularly Persian.
+
+This dataset was introduced in the paper:
+
+> Naghmeh Jamali, Yadollah Yaghoobzadeh, and Heshaam Faili. (2022). [**PerCQA: A Persian Community Question Answering Dataset**](https://aclanthology.org/2022.lrec-1.654/). In *Proceedings of the 13th Language Resources and Evaluation Conference (LREC 2022)*.
+
 ---
-license: mit
-language:
-- fa
----
+
+## 📦 Dataset Structure
+
+Each question thread in PerCQA includes:
+- A **question** post
+- A list of **answers** (comments)
+- Annotations indicating the **quality** of each answer (Good / Bad)
+
+### Data Fields
+| Field        | Description                                   |
+|--------------|-----------------------------------------------|
+| `qid`        | Unique ID of the question                     |
+| `question`   | The text of the original question             |
+| `answers`    | A list of answer texts                        |
+| `labels`     | Corresponding quality labels for each answer  |
+
+---
+
+## 📊 Statistics
+
+- **Number of questions**: ~6,000  
+- **Total answer instances**: ~25,000  
+- **Language**: Persian (Farsi)  
+- **Annotation**: Manual, using quality standards adapted from SemEval CQA tasks  
+
+---
+
+## 🔍 Intended Use
+
+PerCQA is useful for tasks including:
+- Answer selection and ranking
+- Question classification
+- Multilingual and cross-lingual QA research
+- Low-resource NLP
+
+---
+
+## 💬 Languages
+
+- **Primary**: Persian (Farsi)
+- The dataset includes questions and answers written in colloquial Persian, often with informal expressions typical of online communities.
+
+---
+
+## 📚 Citation
+
+Please cite the following paper if you use this dataset:
+
+```bibtex
+@inproceedings{jamali-etal-2022-percqa,
+    title = "{P}er{CQA}: {P}ersian Community Question Answering Dataset",
+    author = "Jamali, Naghme  and
+      Yaghoobzadeh, Yadollah  and
+      Faili, Heshaam",
+    editor = "Calzolari, Nicoletta  and
+      B{\'e}chet, Fr{\'e}d{\'e}ric  and
+      Blache, Philippe  and
+      Choukri, Khalid  and
+      Cieri, Christopher  and
+      Declerck, Thierry  and
+      Goggi, Sara  and
+      Isahara, Hitoshi  and
+      Maegaard, Bente  and
+      Mariani, Joseph  and
+      Mazo, H{\'e}l{\`e}ne  and
+      Odijk, Jan  and
+      Piperidis, Stelios",
+    booktitle = "Proceedings of the Thirteenth Language Resources and Evaluation Conference",
+    month = jun,
+    year = "2022",
+    address = "Marseille, France",
+    publisher = "European Language Resources Association",
+    url = "https://aclanthology.org/2022.lrec-1.654/",
+    pages = "6083--6092",
+    abstract = "Community Question Answering (CQA) forums provide answers to many real-life questions. These forums are trendy among machine learning researchers due to their large size. Automatic answer selection, answer ranking, question retrieval, expert finding, and fact-checking are example learning tasks performed using CQA data. This paper presents PerCQA, the first Persian dataset for CQA. This dataset contains the questions and answers crawled from the most well-known Persian forum. After data acquisition, we provide rigorous annotation guidelines in an iterative process and then the annotation of question-answer pairs in SemEvalCQA format. PerCQA contains 989 questions and 21,915 annotated answers. We make PerCQA publicly available to encourage more research in Persian CQA. We also build strong benchmarks for the task of answer selection in PerCQA by using mono- and multi-lingual pre-trained language models."
+}
+}