|
|
--- |
|
|
configs: |
|
|
- config_name: default |
|
|
data_files: |
|
|
- split: train |
|
|
path: qrels/train.jsonl |
|
|
- split: dev |
|
|
path: qrels/dev.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 |
|
|
|
|
|
**MSMARCO-Fa** is a Persian (Farsi) dataset created for the **Retrieval** task, particularly focusing on **web search** and **document ranking**. It is a translated version of the original English **MS MARCO (Microsoft MAchine Reading COmprehension)** dataset and is a key part of the [FaMTEB (Farsi Massive Text Embedding Benchmark)](https://huggingface.co/spaces/mteb/leaderboard), under the **BEIR-Fa** collection. |
|
|
|
|
|
- **Language(s):** Persian (Farsi) |
|
|
- **Task(s):** Retrieval (Web Search, Document Ranking) |
|
|
- **Source:** Translated from the English MS MARCO dataset |
|
|
- **Part of FaMTEB:** Yes — under BEIR-Fa |
|
|
|
|
|
## Supported Tasks and Leaderboards |
|
|
|
|
|
This dataset is used to evaluate the effectiveness of **text embedding models** in **ranking web documents** based on relevance to user queries, simulating real-world search engine applications. Benchmarking is available via the **Persian MTEB Leaderboard** (language: Persian). |
|
|
|
|
|
## Construction |
|
|
|
|
|
The dataset was built by: |
|
|
|
|
|
- **Translating** the original English MS MARCO dataset to Persian using the **Google Translate API** |
|
|
- Preserving original relevance annotations, where some passages are **human-judged** as relevant to each query |
|
|
|
|
|
As described in the *FaMTEB* paper: |
|
|
|
|
|
- Translation quality was evaluated by **BM25 retrieval score comparison** with the English dataset |
|
|
- Further validation was done using **LLM-based assessments (GEMBA-DA framework)** |
|
|
- This dataset is similar in structure to mMARCO, but focused solely on the **Persian language** |
|
|
|
|
|
## Data Splits |
|
|
|
|
|
Based on FaMTEB paper (Table 5): |
|
|
|
|
|
- **Train:** 9,374,574 samples |
|
|
- **Dev:** 0 samples |
|
|
- **Test:** 8,845,925 samples |
|
|
|
|
|
**Total:** ~9.9 million examples |
|
|
|
