# RED<sup>FM</sup>: a Filtered and Multilingual Relation Extraction Dataset

This is the automatically-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:

    @inproceedings{huguet-cabot-et-al-2023-redfm-dataset,
        title = "RED$^{\rm FM}$: a Filtered and Multilingual Relation Extraction Dataset",
        author = "Huguet Cabot, Pere-Llu{\'\i}s  and Tedeschi, Simone and Ngonga Ngomo, Axel-Cyrille and
          Navigli, Roberto",
        booktitle = "Proc. of the 61st Annual Meeting of the Association for Computational Linguistics: ACL 2023",
        month = jul,
        year = "2023",
        address = "Toronto, Canada",
        publisher = "Association for Computational Linguistics",
        url = "https://arxiv.org/abs/2306.09802",
    }


## License

SRED<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/).
task_categories:token-classification size_categories:10M<n<100M language:ar language:ca language:de language:el language:en language:es language:fr language:hi language:it language:ja language:ko language:nl language:pl language:pt language:ru language:sv language:vi language:zh license:cc-by-sa-4.0 arxiv:2306.09802 region:us
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"num_examples": 2667}, {"name": "validation", "num_bytes": 3511103, "num_examples": 1816}], "download_size": 2440525684, "dataset_size": 457857773}, {"config_name": "all_languages", "features": [{"name": "docid", "dtype": "string"}, {"name": "title", "dtype": "string"}, {"name": "uri", "dtype": "string"}, {"name": "lan", "dtype": "string"}, {"name": "text", "dtype": "string"}, {"name": "entities", "list": [{"name": "uri", "dtype": "string"}, {"name": "surfaceform", "dtype": "string"}, {"name": "type", "dtype": "string"}, {"name": "start", "dtype": "int32"}, {"name": "end", "dtype": "int32"}]}, {"name": "relations", "list": [{"name": "subject", "dtype": "int32"}, {"name": "predicate", "dtype": "string"}, {"name": "object", "dtype": "int32"}]}], "splits": [{"name": "train", "num_bytes": 14615645332, "num_examples": 11865756}, {"name": "test", "num_bytes": 131636046, "num_examples": 67033}, {"name": "validation", "num_bytes": 103507688, "num_examples": 51181}], "download_size": 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TAGS
#task_categories-token-classification #size_categories-10M<n<100M #language-Arabic #language-Catalan #language-German #language-Modern Greek (1453-) #language-English #language-Spanish #language-French #language-Hindi #language-Italian #language-Japanese #language-Korean #language-Dutch #language-Polish #language-Portuguese #language-Russian #language-Swedish #language-Vietnamese #language-Chinese #license-cc-by-sa-4.0 #arxiv-2306.09802 #region-us 

# RED<sup>FM</sup>: a Filtered and Multilingual Relation Extraction Dataset

This is the automatically-filtered dataset from the 2023 ACL paper RED^{FM}: a Filtered and Multilingual Relation Extraction Dataset. If you use the model, please reference this work in your paper:

    @inproceedings{huguet-cabot-et-al-2023-redfm-dataset,
        title = "RED$^{\rm FM}$: a Filtered and Multilingual Relation Extraction Dataset",
        author = "Huguet Cabot, Pere-Llu{\'\i}s  and Tedeschi, Simone and Ngonga Ngomo, Axel-Cyrille and
          Navigli, Roberto",
        booktitle = "Proc. of the 61st Annual Meeting of the Association for Computational Linguistics: ACL 2023",
        month = jul,
        year = "2023",
        address = "Toronto, Canada",
        publisher = "Association for Computational Linguistics",
        url = "URL
    }


## License

SRED<sup>FM</sup> is licensed under the CC BY-SA 4.0 license. The text of the license can be found here.
# RED<sup>FM</sup>: a Filtered and Multilingual Relation Extraction Dataset

This is the automatically-filtered dataset from the 2023 ACL paper RED^{FM}: a Filtered and Multilingual Relation Extraction Dataset. If you use the model, please reference this work in your paper:

    @inproceedings{huguet-cabot-et-al-2023-redfm-dataset,
        title = "RED$^{\rm FM}$: a Filtered and Multilingual Relation Extraction Dataset",
        author = "Huguet Cabot, Pere-Llu{\'\i}s  and Tedeschi, Simone and Ngonga Ngomo, Axel-Cyrille and
          Navigli, Roberto",
        booktitle = "Proc. of the 61st Annual Meeting of the Association for Computational Linguistics: ACL 2023",
        month = jul,
        year = "2023",
        address = "Toronto, Canada",
        publisher = "Association for Computational Linguistics",
        url = "URL
    } ## License

SRED<sup>FM</sup> is licensed under the CC BY-SA 4.0 license. The text of the license can be found here.
TAGS
#task_categories-token-classification #size_categories-10M<n<100M #language-Arabic #language-Catalan #language-German #language-Modern Greek (1453-) #language-English #language-Spanish #language-French #language-Hindi #language-Italian #language-Japanese #language-Korean #language-Dutch #language-Polish #language-Portuguese #language-Russian #language-Swedish #language-Vietnamese #language-Chinese #license-cc-by-sa-4.0 #arxiv-2306.09802 #region-us 
 # RED<sup>FM</sup>: a Filtered and Multilingual Relation Extraction Dataset

This is the automatically-filtered dataset from the 2023 ACL paper RED^{FM}: a Filtered and Multilingual Relation Extraction Dataset. If you use the model, please reference this work in your paper:

    @inproceedings{huguet-cabot-et-al-2023-redfm-dataset,
        title = "RED$^{\rm FM}$: a Filtered and Multilingual Relation Extraction Dataset",
        author = "Huguet Cabot, Pere-Llu{\'\i}s  and Tedeschi, Simone and Ngonga Ngomo, Axel-Cyrille and
          Navigli, Roberto",
        booktitle = "Proc. of the 61st Annual Meeting of the Association for Computational Linguistics: ACL 2023",
        month = jul,
        year = "2023",
        address = "Toronto, Canada",
        publisher = "Association for Computational Linguistics",
        url = "URL
    } ## License

SRED<sup>FM</sup> is licensed under the CC BY-SA 4.0 license. The text of the license can be found here.