README.md

---
license: apache-2.0
task_categories:
- sentence-similarity
language:
- ar
size_categories:
- 100K<n<1M
tags:
- sentence-transformers
dataset_info:
    features:
      - name: premise
        dtype: string
      - name: hypothesis
        dtype: string
      - name: label
        dtype:
          class_label:
            names:
              '0': entailment
              '1': neutral
              '2': contradiction
---


# Arabic NLI Pair-Class

## Dataset Summary

- The Arabic Version of SNLI and MultiNLI datasets. (Pair-Class Subset)
- Originally used for Natural Language Inference (NLI),
- Dataset may be used for training/finetuning an embedding model for semantic textual similarity.

## Pair-Class Subset

- Columns: "premise", "hypothesis", "label"
- Column types: str, str, class with {"0": "entailment", "1": "neutral", "2": "contradiction"}

## Arabic Examples:

```python
{
  "premise": "شخص على حصان يقفز فوق طائرة معطلة",
  "hypothesis": "شخص يقوم بتدريب حصانه للمنافسة",
  "label": 1,
},
{
  "premise": "شخص على حصان يقفز فوق طائرة معطلة",
  "hypothesis": "شخص في مطعم، يطلب عجة.",
  "label": 2,
},
{
  "premise": "شخص على حصان يقفز فوق طائرة معطلة",
  "hypothesis": "شخص في الهواء الطلق، على حصان.",
  "label": 0,
}
```


## Disclaimer

Please note that the translated sentences are generated using neural machine translation and may not always convey the intended meaning accurately.


## Contact
[Contact Me](https://www.omarai.co) if you have any questions or you want to use thid dataset 


## Note

Original work done by [SentenceTransformers](https://www.sbert.net)



## Citation

If you use the Arabic Matryoshka Embeddings Dataset, please cite it as follows:

```bibtex
@misc{nacar2024enhancingsemanticsimilarityunderstanding,
      title={Enhancing Semantic Similarity Understanding in Arabic NLP with Nested Embedding Learning}, 
      author={Omer Nacar and Anis Koubaa},
      year={2024},
      eprint={2407.21139},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2407.21139}, 
}