---
configs:
  - config_name: default
    data_files:
      - split: train
        path: qrels/train.jsonl
      - 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

**SciFact-Fa** is a Persian (Farsi) dataset designed for the **Retrieval** task, with a focus on **scientific fact verification**. It is a translated version of the original English **SciFact** dataset used in the **BEIR benchmark** and is part of the **FaMTEB** (Farsi Massive Text Embedding Benchmark) under the BEIR-Fa collection.

- **Language(s):** Persian (Farsi)  
- **Task(s):** Retrieval (Scientific Fact Verification, Evidence Retrieval)  
- **Source:** Translated from the English SciFact dataset using Google Translate  
- **Part of FaMTEB:** Yes — part of the BEIR-Fa collection

## Supported Tasks and Leaderboards

This dataset evaluates models' ability to **retrieve supporting evidence** from scientific literature abstracts that either **support or refute** given scientific claims. Evaluation results can be compared on the **Persian MTEB Leaderboard** (filter by language: Persian).

## Construction

- Translated from the **SciFact** dataset using the **Google Translate API**  
- The original dataset targets **scientific claim verification** and **evidence-based reasoning**

Translation quality was validated using:

- BM25 score comparisons  
- **LLM-based assessment (GEMBA-DA framework)**

## Data Splits

As reported in the FaMTEB paper (Table 5):

- **Train:** 6,102 samples  
- **Dev:** 0 samples  
- **Test:** 5,522 samples  

> Approximate total dataset size: **7.55k examples** (user-provided figure)