Datasets:
Tasks:
Sentence Similarity
Modalities:
Text
Formats:
csv
Languages:
Arabic
Size:
100K - 1M
ArXiv:
Tags:
sentence-transformers
License:
File size: 1,864 Bytes
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---
license: apache-2.0
task_categories:
- sentence-similarity
language:
- ar
size_categories:
- 100K<n<1M
tags:
- sentence-transformers
---
# Arabic NLI Pair-Score
## Dataset Summary
- The Arabic Version of SNLI and MultiNLI datasets. (Pair-Score 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: "sentence1", "sentence2", "score"
- Column types: str, str, float
## Arabic Examples:
```python
{
"sentence1": "شخص على حصان يقفز فوق طائرة معطلة",
"sentence2": "شخص يقوم بتدريب حصانه للمنافسة",
"score": 0.5,
},
{
"sentence1": "شخص على حصان يقفز فوق طائرة معطلة",
"sentence2": "شخص في مطعم، يطلب عجة.",
"score": 0,
},
{
"sentence1": "شخص على حصان يقفز فوق طائرة معطلة",
"sentence2": "شخص في الهواء الطلق، على حصان.",
"score": 1,
}
```
## 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},
} |