https://github.com/dsfsi/embedding-eval-data
Embedding Evaluation Data for South African Languages
https://github.com/dsfsi/embedding-eval-data
africa dsfsi-datasets low-resource-languages machine-learning nlp nlproc south-africa
Last synced: about 15 hours ago
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Embedding Evaluation Data for South African Languages
- Host: GitHub
- URL: https://github.com/dsfsi/embedding-eval-data
- Owner: dsfsi
- Created: 2021-09-30T07:54:33.000Z (about 4 years ago)
- Default Branch: main
- Last Pushed: 2023-10-26T07:24:15.000Z (almost 2 years ago)
- Last Synced: 2025-03-14T18:20:53.926Z (7 months ago)
- Topics: africa, dsfsi-datasets, low-resource-languages, machine-learning, nlp, nlproc, south-africa
- Homepage: https://zenodo.org/record/5673974
- Size: 8.79 KB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Embedding Evaluation Data for South African Languages
[](https://arxiv.org/abs/2111.06230)
Give Feedback 📑: [DSFSI Resource Feedback Form](https://docs.google.com/forms/d/e/1FAIpQLSf7S36dyAUPx2egmXbFpnTBuzoRulhL5Elu-N1eoMhaO7v10w/formResponse)
## Dataset Information
The datasets(Simlex and WordSim) contain pairs of Setswana and Sepedi words that have been assigned similarity ratings by humans to measure semantic relatedness. The word-pairs(Simlex and WordSim) are manually translated from English to Setswana and Sepedi. The evaluation task aims to find the degree of correlation between the scores provided by the model and the human rating, the score of the model is collected by computing the cosine similarity of corresponding vectors for word pairs.
## Online Repository link
* [Zenodo Data Repository](https://zenodo.org/record/5673974) - Link to the data repository.
## Authors
* **Vukosi Marivate** - [@vukosi](https://twitter.com/vukosi)
* **Valencia Wagner**
* **Mack Makgatho**
* **Tshephisho Sefara**
See also the list of [contributors](https://github.com/dsfsi/embedding-eval-data//contributors) who participated in this project.
## Citing the dataset
To appear in conference proceedings
>@article{Makgatho_Marivate_Sefara_Wagner_2022, title={Training Cross-Lingual embeddings for Setswana and Sepedi},
volume={3},
url={https://upjournals.up.ac.za/index.php/dhasa/article/view/3822},
DOI={10.55492/dhasa.v3i03.3822},
number={03},
journal={Journal of the Digital Humanities Association of Southern Africa },
author={Makgatho, Mack and Marivate, Vukosi and Sefara, Tshephisho and Wagner, Valencia},
year={2022},
month={Feb.}}
## License
Dataset is licensed under CC-BY-4.0
This project is licensed under the MIT License - see the [LICENSE.md](LICENSE.md) file for details