README.md

---
task_categories:
- text-retrieval
- sentence-similarity
- text-classification
language:
- vi
- zh
tags:
- IR
- Rerank
- Information Retrival
size_categories:
- 1M<n<10M
configs:
- config_name: qrels.train
  data_files: qrels.train.tsv
- config_name: qrels.dev
  data_files:
  - split: train
    path: data_qrels.dev.tsv
- config_name: qrels.retrieval.train
  data_files:
  - split: train
    path: qrels.retrieval.train.tsv
- config_name: qrels.retrieval.dev
  data_files:
  - split: train
    path: data_qrels.retrieval.dev.tsv
- config_name: collection
  data_files:
  - split: train
    path:
    - collection_json_0_vi.tsv
    - collection_json_1_vi.tsv
    - collection_json_2_vi.tsv
    - collection_json_3_vi.tsv
    - collection_json_4_vi.tsv
    - collection_json_5_vi.tsv
    - collection_json_6_vi.tsv
    - collection_json_7_vi.tsv
    - collection_json_8_vi.tsv
    - collection_json_9_vi.tsv
- config_name: queries.train
  data_files:
  - split: train
    path:
    - data_queries.train_json_vi.tsv
- config_name: queries.dev
  data_files:
  - split: train
    path:
    - data_queries.dev_json_vi.tsv
- config_name: queries.test
  data_files:
  - split: train
    path:
    - data_queries.test_json_vi.tsv
- config_name: train.bm25.tsv
  data_files:
  - split: train
    path:
    - train.bm25.tsv
- config_name: train.mined.tsv
  data_files:
  - split: train
    path:
    - train.mined.tsv
license: apache-2.0
---

# 📚 5CD-AI/Vietnamese-THUIR-T2Ranking-gg-translated  

## 📝 Overview  
**Vietnamese-THUIR-T2Ranking-gg-translated** is a large-scale dataset for *passage ranking* in Vietnamese.  
It is translated from the original [THUIR/T2Ranking](https://huggingface.co/datasets/THUIR/T2Ranking) [1] using Google Translate, inspired by the approach of **mMARCO** [2].  
The dataset aims to provide a large-scale dataset for research and applications in *Information Retrieval (IR)* in Vietnamese.  

In IR, *passage ranking* is an essential and challenging task, typically involving two stages:  

1. 🔍 **Passage retrieval** – retrieving candidate passages.  
2. 📊 **Passage re-ranking** – re-ordering candidates for final ranking.  


## 📥 Data Download  

Data files follow the same structure as the original:  

| 📂 Description              | 🗂️ Filename                 | 🔢 Num Records | 📑 Format                  |
| --------------------------- | --------------------------- | -------------: | -------------------------- |
| Collection                  | collection_json_*_vi.tsv    |   2,303,643    | tsv: pid, text_zh, text_vi |
| Queries Train               | data_queries.train_json_vi.tsv |     258,042 | tsv: qid, text_zh, text_vi |
| Queries Dev                 | data_queries.dev_json_vi.tsv   |      24,832 | tsv: qid, text_zh, text_vi |
| Queries Test                | data_queries.test_json_vi.tsv  |      24,832 | tsv: qid, text_zh, text_vi |
| Qrels Train for re-ranking  | qrels.train.tsv             |   1,613,421    | TREC qrels format          |
| Qrels Dev for re-ranking    | qrels.dev.tsv               |     400,536    | TREC qrels format          |
| Qrels Retrieval Train       | qrels.retrieval.train.tsv   |     744,663    | tsv: qid, pid              |
| Qrels Retrieval Dev         | qrels.retrieval.dev.tsv     |     118,933    | tsv: qid, pid              |
| BM25 Negatives              | train.bm25.tsv              | 200,359,731    | tsv: qid, pid, index       |
| Hard Negatives              | train.mined.tsv             | 200,376,001    | tsv: qid, pid, index, score|


🚀 **How to download**  

```bash
git lfs install
git clone https://huggingface.co/datasets/5CD-AI/Vietnamese-THUIR-T2Ranking-gg-translated
````

📂 **Folder structure:**

```
├── collection_json_*_vi.tsv
├── data_queries.train_json_vi.tsv
├── data_queries.dev_json_vi.tsv
├── data_queries.test_json_vi.tsv
├── qrels.train.tsv
├── qrels.dev.tsv
├── qrels.retrieval.train.tsv
├── qrels.retrieval.dev.tsv
├── train.bm25.tsv
└── train.mined.tsv
```


## 🗒️ Notes

* ⚠️ This dataset was **translated** using Google Translate, so some translations may be imperfect or unnatural.


## 📖 Reference

\[1] X. Xie et al., *T2Ranking: A Large-scale Chinese Benchmark for Passage Ranking*, in **Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR ’23)**, ACM, pp. 2681–2690, 2023. doi: 10.1145/3539618.3591874.

\[2] L. H. Bonifacio et al., *mMARCO: A Multilingual Version of MS MARCO Passage Ranking Dataset*, **arXiv preprint** arXiv:2108.13897, 2021.