Datasets:
Tasks:
Sentence Similarity
Modalities:
Text
Formats:
csv
Languages:
Arabic
Size:
100K - 1M
ArXiv:
Tags:
sentence-transformers
License:
license: apache-2.0 | |
task_categories: | |
- sentence-similarity | |
language: | |
- ar | |
size_categories: | |
- 10K<n<100K | |
tags: | |
- sentence-transformers | |
# Arabic NLI Triplet | |
## Dataset Summary | |
1. The Arabic Version of SNLI and MultiNLI datasets. (Triplet Subset) | |
2. Originally used for Natural Language Inference (NLI), | |
3. Dataset may be used for training/finetuning an embedding model for semantic textual similarity. | |
## Triplet Subset | |
- Columns: "anchor", "positive", "negative" | |
- Column types: str, str, str | |
Examples: | |
```python | |
{ | |
"anchor": "شخص على حصان يقفز فوق طائرة معطلة", | |
"positive": "شخص في الهواء الطلق، على حصان.", | |
"negative": "شخص في مطعم، يطلب عجة." | |
} | |
``` | |
## 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}, | |
} |