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download_size: 50720746 |
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dataset_size: 19757503 |
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task_categories: |
|
- token-classification |
|
language: |
|
- ar |
|
- de |
|
- en |
|
- es |
|
- it |
|
- fr |
|
- zh |
|
size_categories: |
|
- 10K<n<100K |
|
license: cc-by-sa-4.0 |
|
--- |
|
# RED<sup>FM</sup>: a Filtered and Multilingual Relation Extraction Dataset |
|
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This is the human-filtered dataset from the 2023 ACL paper [RED^{FM}: a Filtered and Multilingual Relation Extraction Dataset](https://arxiv.org/abs/2306.09802). If you use the model, please reference this work in your paper: |
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@inproceedings{huguet-cabot-et-al-2023-redfm-dataset, |
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title = "RED$^{\rm FM}$: a Filtered and Multilingual Relation Extraction Dataset", |
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author = "Huguet Cabot, Pere-Llu{\'\i}s and Tedeschi, Simone and Ngonga Ngomo, Axel-Cyrille and |
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Navigli, Roberto", |
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booktitle = "Proc. of the 61st Annual Meeting of the Association for Computational Linguistics: ACL 2023", |
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month = jul, |
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year = "2023", |
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address = "Toronto, Canada", |
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publisher = "Association for Computational Linguistics", |
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url = "https://arxiv.org/abs/2306.09802", |
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} |
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## License |
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RED<sup>FM</sup> is licensed under the CC BY-SA 4.0 license. The text of the license can be found [here](https://creativecommons.org/licenses/by-sa/4.0/). |