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

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:

    @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

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/).
task_categories:token-classification size_categories:10K<n<100K language:ar language:de language:en language:es language:it language:fr language:zh license:cc-by-sa-4.0 arxiv:2306.09802 region:us
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"16": "follows", "17": "headquarters location", "18": "cast member", "19": "manufacturer", "20": "located in or next to body of water", "21": "location", "22": "part of", "23": "mouth of the watercourse", "24": "member of", "25": "sport", "26": "characters", "27": "participant", "28": "notable work", "29": "replaces", "30": "sibling", "31": "inception"}}}}, {"name": "object", "struct": [{"name": "uri", "dtype": "string"}, {"name": "surfaceform", "dtype": "string"}, {"name": "type", "dtype": "string"}, {"name": "start", "dtype": "int32"}, {"name": "end", "dtype": "int32"}]}]}], "splits": [{"name": "train", "num_bytes": 2455615, "num_examples": 2071}, {"name": "test", "num_bytes": 334212, "num_examples": 285}, {"name": "validation", "num_bytes": 310862, "num_examples": 252}], "download_size": 8072481, "dataset_size": 3100689}, {"config_name": "en", "features": [{"name": "docid", "dtype": "string"}, {"name": "title", "dtype": "string"}, {"name": "uri", "dtype": "string"}, {"name": "text", 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"type", "dtype": "string"}, {"name": "start", "dtype": "int32"}, {"name": "end", "dtype": "int32"}]}, {"name": "relations", "list": [{"name": "subject", "struct": [{"name": "uri", "dtype": "string"}, {"name": "surfaceform", "dtype": "string"}, {"name": "type", "dtype": "string"}, {"name": "start", "dtype": "int32"}, {"name": "end", "dtype": "int32"}]}, {"name": "predicate", "dtype": {"class_label": {"names": {"0": "country", "1": "place of birth", "2": "spouse", "3": "country of citizenship", "4": "instance of", "5": "capital", "6": "child", "7": "shares border with", "8": "author", "9": "director", "10": "occupation", "11": "founded by", "12": "league", "13": "owned by", "14": "genre", "15": "named after", "16": "follows", "17": "headquarters location", "18": "cast member", "19": "manufacturer", "20": "located in or next to body of water", "21": "location", "22": "part of", "23": "mouth of the watercourse", "24": "member of", "25": "sport", "26": "characters", "27": "participant", "28": "notable work", "29": "replaces", "30": "sibling", "31": "inception"}}}}, {"name": "object", "struct": [{"name": "uri", "dtype": "string"}, {"name": "surfaceform", "dtype": "string"}, {"name": "type", "dtype": "string"}, {"name": "start", "dtype": "int32"}, {"name": "end", "dtype": "int32"}]}]}], "splits": [{"name": "train", "num_bytes": 2452744, "num_examples": 1866}, {"name": "test", "num_bytes": 345782, "num_examples": 281}, {"name": "validation", "num_bytes": 299692, "num_examples": 228}], "download_size": 7825400, "dataset_size": 3098218}, {"config_name": "fr", "features": [{"name": "docid", "dtype": "string"}, {"name": "title", "dtype": "string"}, {"name": "uri", "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": 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"string"}, {"name": "surfaceform", "dtype": "string"}, {"name": "type", "dtype": "string"}, {"name": "start", "dtype": "int32"}, {"name": "end", "dtype": "int32"}]}]}], "splits": [{"name": "train", "num_bytes": 2280992, "num_examples": 1865}, {"name": "test", "num_bytes": 427990, "num_examples": 415}, {"name": "validation", "num_bytes": 429165, "num_examples": 416}], "download_size": 8257363, "dataset_size": 3138147}, {"config_name": "it", "features": [{"name": "docid", "dtype": "string"}, {"name": "title", "dtype": "string"}, {"name": "uri", "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", "struct": [{"name": "uri", "dtype": "string"}, {"name": "surfaceform", "dtype": "string"}, {"name": "type", "dtype": "string"}, {"name": "start", "dtype": "int32"}, {"name": "end", "dtype": "int32"}]}, {"name": "predicate", "dtype": {"class_label": {"names": {"0": "country", "1": "place of birth", "2": "spouse", "3": "country of citizenship", "4": "instance of", "5": "capital", "6": "child", "7": "shares border with", "8": "author", "9": "director", "10": "occupation", "11": "founded by", "12": "league", "13": "owned by", "14": "genre", "15": "named after", "16": "follows", "17": "headquarters location", "18": "cast member", "19": "manufacturer", "20": "located in or next to body of water", "21": "location", "22": "part of", "23": "mouth of the watercourse", "24": "member of", "25": "sport", "26": "characters", "27": "participant", "28": "notable work", "29": "replaces", "30": "sibling", "31": "inception"}}}}, {"name": "object", "struct": [{"name": "uri", "dtype": "string"}, {"name": "surfaceform", "dtype": "string"}, {"name": "type", "dtype": "string"}, {"name": "start", "dtype": "int32"}, {"name": "end", "dtype": "int32"}]}]}], "splits": [{"name": "train", "num_bytes": 1918310, "num_examples": 1657}, {"name": "test", "num_bytes": 489445, "num_examples": 509}, {"name": "validation", "num_bytes": 485557, "num_examples": 521}], "download_size": 7537265, "dataset_size": 2893312}, {"config_name": "zh", "features": [{"name": "docid", "dtype": "string"}, {"name": "title", "dtype": "string"}, {"name": "uri", "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", "struct": [{"name": "uri", "dtype": "string"}, {"name": "surfaceform", "dtype": "string"}, {"name": "type", "dtype": "string"}, {"name": "start", "dtype": "int32"}, {"name": "end", "dtype": "int32"}]}, {"name": "predicate", "dtype": {"class_label": {"names": {"0": "country", "1": "place of birth", "2": "spouse", "3": "country of citizenship", "4": "instance of", "5": "capital", "6": "child", "7": "shares border with", "8": "author", "9": "director", "10": "occupation", "11": "founded by", "12": "league", "13": "owned by", "14": "genre", "15": "named after", "16": "follows", "17": "headquarters location", "18": "cast member", "19": "manufacturer", "20": "located in or next to body of water", "21": "location", "22": "part of", "23": "mouth of the watercourse", "24": "member of", "25": "sport", "26": "characters", "27": "participant", "28": "notable work", "29": "replaces", "30": "sibling", "31": "inception"}}}}, {"name": "object", "struct": [{"name": "uri", "dtype": "string"}, {"name": "surfaceform", "dtype": "string"}, {"name": "type", "dtype": "string"}, {"name": "start", "dtype": "int32"}, {"name": "end", "dtype": "int32"}]}]}], "splits": [{"name": "test", "num_bytes": 311905, "num_examples": 270}, {"name": "validation", "num_bytes": 364077, "num_examples": 307}], "download_size": 1952982, "dataset_size": 675982}, {"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", "struct": [{"name": "uri", "dtype": "string"}, {"name": "surfaceform", "dtype": "string"}, {"name": "type", "dtype": "string"}, {"name": "start", "dtype": "int32"}, {"name": "end", "dtype": "int32"}]}, {"name": "predicate", "dtype": {"class_label": {"names": {"0": "country", "1": "place of birth", "2": "spouse", "3": "country of citizenship", "4": "instance of", "5": "capital", "6": "child", "7": "shares border with", "8": "author", "9": "director", "10": "occupation", "11": "founded by", "12": "league", "13": "owned by", "14": "genre", "15": "named after", "16": "follows", "17": "headquarters location", "18": "cast member", "19": "manufacturer", "20": "located in or next to body of water", "21": "location", "22": "part of", "23": "mouth of the watercourse", "24": "member of", "25": "sport", "26": "characters", "27": "participant", "28": "notable work", "29": "replaces", "30": "sibling", "31": "inception"}}}}, {"name": "object", "struct": [{"name": "uri", "dtype": "string"}, {"name": "surfaceform", "dtype": "string"}, {"name": "type", "dtype": "string"}, {"name": "start", "dtype": "int32"}, {"name": "end", "dtype": "int32"}]}]}], "splits": [{"name": "train", "num_bytes": 13557340, "num_examples": 10337}, {"name": "test", "num_bytes": 3100822, "num_examples": 2551}, {"name": "validation", "num_bytes": 3099341, "num_examples": 2558}], "download_size": 50720746, "dataset_size": 19757503}]}
TAGS
#task_categories-token-classification #size_categories-10K<n<100K #language-Arabic #language-German #language-English #language-Spanish #language-Italian #language-French #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 human-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

RED<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 human-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

RED<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-10K<n<100K #language-Arabic #language-German #language-English #language-Spanish #language-Italian #language-French #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 human-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

RED<sup>FM</sup> is licensed under the CC BY-SA 4.0 license. The text of the license can be found here.
passage: TAGS
#task_categories-token-classification #size_categories-10K<n<100K #language-Arabic #language-German #language-English #language-Spanish #language-Italian #language-French #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 human-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

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