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README.md

@@ -1,25 +1,171 @@
 ---
-dataset_info:
-  features:
-  - name: sentence1
-    dtype: string
-  - name: sentence2
-    dtype: string
-  - name: lang
-    dtype: string
-  - name: source_dataset
-    dtype: string
-  - name: split
-    dtype: string
-  splits:
-  - name: train
-    num_bytes: 21967159
-    num_examples: 139457
-  download_size: 10476154
-  dataset_size: 21967159
-configs:
-- config_name: default
-  data_files:
-  - split: train
-    path: data/train-*
+language:
+- multilingual
+license: apache-2.0
+tags:
+- bitext-mining
+- sentence-embeddings
+- mteb
+- multilingual
+task_categories:
+- sentence-similarity
+pretty_name: "MTEB Bit TextMining Aggregated Dataset"
+size_categories:
+- 100K<n<1M
 ---
+
+# MTEB BitextMining Aggregated Dataset
+
+This dataset aggregates 8 BitextMining datasets from the MTEB (Massive Text Embedding Benchmark) Multilingual v2 benchmark into a single, unified dataset for easy access and evaluation.
+
+## Dataset Summary
+
+- **Total Examples**: 139,457 sentence pairs
+- **Source Datasets**: 8 MTEB BitextMining tasks
+- **Languages**: 117+ unique language codes
+- **Task**: Bitext Mining (parallel sentence retrieval)
+- **Format**: Standardized schema across all sources
+
+## Schema
+
+Each example contains:
+- `sentence1` (string): First sentence of the pair
+- `sentence2` (string): Second sentence of the pair (translation/parallel text)
+- `lang` (string): Language pair code (e.g., "eng-fra", "de-en")
+- `source_dataset` (string): Original MTEB dataset name
+- `split` (string): Original split (train/validation/test)
+
+## Source Datasets
+
+| Dataset | Examples | Languages | Splits |
+|---------|----------|-----------|--------|
+| **Tatoeba** | 88,877 | 112 | test |
+| **BUCC.v2** | 35,000 | 4 | test |
+| **BornholmBitextMining** | 6,785 | 1 | train, validation, test |
+| **DiaBlaBitextMining** | 5,748 | 1 | test |
+| **NorwegianCourtsBitextMining** | 1,137 | 1 | train, test |
+| **NusaTranslationBitextMining** | 1,000 | 1 | train |
+| **NusaXBitextMining** | 500 | 1 | train |
+| **NollySentiBitextMining** | 410 | 1 | train |
+
+**Note**: Some datasets mark language as "unknown" in the lang field but contain multilingual data.
+
+## Excluded Datasets
+
+The following MTEB BitextMining datasets were excluded due to incompatible schemas:
+
+- **BibleNLPBitextMining**: Uses language codes as column names (828 configs with 900+ languages)
+- **FloresBitextMining**: Missing sentence1/sentence2 fields
+- **IN22GenBitextMining**: Schema incompatibility  
+- **IndicGenBenchFloresBitextMining**: Schema incompatibility
+- **NTREXBitextMining**: Schema incompatibility
+
+## Usage
+
+```python
+from datasets import load_dataset
+
+# Load the entire dataset
+dataset = load_dataset("SaylorTwift/mteb-bitext-mining-aggregated")
+
+# Access examples
+for example in dataset['train']:
+    print(f"Sentence 1: {example['sentence1']}")
+    print(f"Sentence 2: {example['sentence2']}")
+    print(f"Language: {example['lang']}")
+    print(f"Source: {example['source_dataset']}")
+    print(f"Split: {example['split']}")
+    print()
+```
+
+### Filter by Source Dataset
+
+```python
+# Get only Tatoeba examples
+tatoeba_data = dataset['train'].filter(lambda x: x['source_dataset'] == 'Tatoeba')
+
+# Get only BUCC examples
+bucc_data = dataset['train'].filter(lambda x: x['source_dataset'] == 'BUCC.v2')
+```
+
+### Filter by Language
+
+```python
+# Get German-English pairs from BUCC
+de_en = dataset['train'].filter(lambda x: x['lang'] == 'de-en')
+
+# Get specific language pairs from Tatoeba
+fra_eng = dataset['train'].filter(lambda x: x['lang'] == 'fra-eng')
+```
+
+## Citation
+
+If you use this dataset, please cite the MTEB benchmark:
+
+```bibtex
+@article{muennighoff2022mteb,
+  title={MTEB: Massive Text Embedding Benchmark},
+  author={Muennighoff, Niklas and Tazi, Nouamane and Magne, Lo{\"\i}c and Reimers, Nils},
+  journal={arXiv preprint arXiv:2210.07316},
+  year={2022}
+}
+```
+
+## Individual Dataset Citations
+
+Please also cite the individual datasets you use:
+
+### Tatoeba
+```bibtex
+@inproceedings{artetxe2019massively,
+  title={Massively multilingual sentence embeddings for zero-shot cross-lingual transfer and beyond},
+  author={Artetxe, Mikel and Schwenk, Holger},
+  booktitle={Transactions of the Association for Computational Linguistics},
+  year={2019}
+}
+```
+
+### BUCC
+```bibtex
+@inproceedings{zweigenbaum2017overview,
+  title={Overview of the second BUCC shared task: Spotting parallel sentences in comparable corpora},
+  author={Zweigenbaum, Pierre and Sharoff, Serge and Rapp, Reinhard},
+  booktitle={Proceedings of the 10th workshop on building and using comparable corpora},
+  year={2017}
+}
+```
+
+*Additional citations available in the original MTEB task metadata.*
+
+## Dataset Statistics
+
+### Language Coverage
+- **Total unique language codes**: 117
+- **Most represented**: English (eng) appears in most pairs
+- **Coverage**: Includes high-resource, mid-resource, and low-resource languages
+
+### Split Distribution
+- **test**: 136,548 examples (primarily from Tatoeba and BUCC)
+- **train**: 9,480 examples
+- **validation**: 500 examples
+
+## License
+
+This aggregated dataset inherits the licenses from its source datasets. Most MTEB datasets are released under permissive licenses (Apache 2.0, MIT, CC-BY, etc.). Please refer to the original dataset pages for specific licensing information.
+
+## Acknowledgments
+
+- **MTEB Team**: For creating and maintaining the benchmark
+- **Original Dataset Creators**: For providing high-quality bitext mining datasets
+- **Hugging Face**: For dataset hosting and infrastructure
+
+## Version History
+
+- **v1.0 (2026-04-02)**: Initial release
+  - 8 source datasets aggregated
+  - 139,457 sentence pairs
+  - 117 language codes
+
+## Contact
+
+For questions or issues with this aggregated dataset, please open an issue on the repository or contact the dataset creator.