README.md

---
configs:
  - config_name: default
    data_files:
      - split: test
        path: qrels/test.jsonl
  - config_name: corpus
    data_files:
      - split: corpus
        path: corpus.jsonl
  - config_name: queries
    data_files:
      - split: queries
        path: queries.jsonl
---
## Dataset Summary

**CQADupstack-programmers-Fa** is a Persian (Farsi) dataset developed for the **Retrieval** task, with a focus on **duplicate question detection** in community question-answering (CQA) platforms. This dataset is a translated version of the **"Programmers" (Software Engineering)** StackExchange subforum from the English **CQADupstack** collection and is part of the **FaMTEB** benchmark under the **BEIR-Fa** suite.

- **Language(s):** Persian (Farsi)  
- **Task(s):** Retrieval (Duplicate Question Retrieval)  
- **Source:** Translated from English using Google Translate  
- **Part of FaMTEB:** Yes — under BEIR-Fa

## Supported Tasks and Leaderboards

This dataset evaluates **text embedding models** on their ability to retrieve **semantically equivalent or duplicate questions** in specialized domains like **software engineering**. Results can be viewed on the **Persian MTEB Leaderboard** (filter by language: Persian).

## Construction

The dataset was created by:

- Translating the "programmers" subforum from the English CQADupstack dataset using the **Google Translate API**
- Preserving the CQA structure for evaluating **duplicate retrieval** tasks

According to the FaMTEB paper, the BEIR-Fa datasets underwent translation quality evaluation using:

- **BM25 retrieval performance comparisons** (English vs Persian)  
- **GEMBA-DA evaluation**, leveraging LLMs for quality control

## Data Splits

As per the FaMTEB paper (Table 5), all **CQADupstack-Fa** sub-datasets share a pooled evaluation set:

- **Train:** 0 samples  
- **Dev:** 0 samples  
- **Test:** 480,902 samples (aggregate)

The `cqadupstack-programmers-fa` subset contains approximately **34.7k examples** (user-provided figure). For more granular splits, consult the dataset provider or FaMTEB documentation.