Update readme.md

README.md

@@ -18,4 +18,84 @@ configs:
   data_files:
   - split: train
     path: data/train-*
+license: apache-2.0
+task_categories:
+- sentence-similarity
+- feature-extraction
+language:
+- ar
+size_categories:
+- 100K<n<1M
 ---
+
+# Arabic Mr. TyDi in Triplet Format
+
+## Dataset Summary
+
+This dataset is a transformed version of the Arabic subset of the [Mr. TyDi dataset](https://huggingface.co/datasets/castorini/mr-tydi), designed specifically for training retrieval and re-ranking models. Each query is paired with a positive passage and one of the multiple negative passages in a triplet format: `(query, positive, negative)`. This restructuring resulted in a total of 362,000 rows, making it ideal for pairwise ranking tasks and contrastive learning approaches.
+
+The dataset maintains the original purpose of Mr. TyDi for monolingual retrieval, while offering a simplified and scalable format for learning-to-rank tasks.
+
+## Dataset Structure
+
+The dataset includes a train split, presented in the triplet format with the following fields:
+
+- `query`: The query string.
+- `positive`: The relevant passage for the query.
+- `negative`: A non-relevant passage for the query.
+
+### Example Data
+
+#### Triplet Format
+
+```json
+{
+  "query": "متى تم تطوير نظرية الحقل الكمي؟", 
+  "positive": {
+    "text": "بدأت نظرية الحقل الكمي بشكل طبيعي بدراسة التفاعلات الكهرومغناطيسية ..."
+  },
+  "negative": {
+    "text": "تم تنفيذ النهج مؤخرًا ليشمل نسخة جبرية من الحقل الكمي ..."
+  }
+}
+```
+
+### Language Coverage
+The dataset focuses exclusively on the **Arabic** subset of Mr. TyDi.
+
+### Loading the Dataset
+
+You can load the dataset using the **datasets** library from Hugging Face:
+
+```python 
+from datasets import load_dataset
+
+dataset = load_dataset('NAMAA-Space/Ara-TyDi-Triplet')
+dataset 
+```
+
+
+### Dataset Usage
+
+The new format facilitates training retrieval and re-ranking models by providing explicit negative passage fields. This structure simplifies the handling of negative examples during model training and evaluation.
+
+### Citation Information
+
+If you use this dataset in your research, please cite the original Mr. TyDi paper and this dataset as follows:
+
+```
+@article{mrtydi,
+      title={{Mr. TyDi}: A Multi-lingual Benchmark for Dense Retrieval}, 
+      author={Xinyu Zhang and Xueguang Ma and Peng Shi and Jimmy Lin},
+      year={2021},
+      journal={arXiv:2108.08787},
+}
+
+@dataset{Namaa,
+      title={Ara TyDi Triplet},
+      author={Omer Nacar},
+      year={2024},
+      note={Hugging Face Dataset Repository}
+}
+```
+