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  The original NYT dataset by Riedel et al. (2010) consists of New York Times news articles from 1987-2007 that was distantly annotated with relations using FreeBase. The original dataset consisted of 1.18M sentences. It is available here: https://iesl.cs.umass.edu/riedel/ecml/
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- The version here is mainly based on the work by Zeng et al. (2018) that filtered out sentences with more than 100 words and sentences without an active relation, leaving 66195 sentences.
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  They randomly selected 5000 sentences from it as the test set, 5000 sentences as the validation set and the rest 56195 sentences are used as train set.
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  The resulting dataset called NYT-multi features overlapping entities across three entity types and 24 relation types.
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- The data is available here: https://github.com/xiangrongzeng/copy_re
 
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  The data was further pre-processed with the StanfordCoreNLP by Yu et al. (2020): https://github.com/yubowen-ph/JointER
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- We converted the data into a more readable JSON format. You can access the raw version from Zeng et al. (2018) using `datasets.load_dataset("DFKI-SLT/nyt-multi", config="raw")`.
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  ### Languages
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  The original NYT dataset by Riedel et al. (2010) consists of New York Times news articles from 1987-2007 that was distantly annotated with relations using FreeBase. The original dataset consisted of 1.18M sentences. It is available here: https://iesl.cs.umass.edu/riedel/ecml/
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+ Zeng et al. (2018) that filtered out sentences with more than 100 words and sentences without an active relation, leaving 66195 sentences.
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  They randomly selected 5000 sentences from it as the test set, 5000 sentences as the validation set and the rest 56195 sentences are used as train set.
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  The resulting dataset called NYT-multi features overlapping entities across three entity types and 24 relation types.
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+ You can access the raw version from Zeng et al. (2018) using `datasets.load_dataset("DFKI-SLT/nyt-multi", config="raw")`.
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+ The original data is available here: https://github.com/xiangrongzeng/copy_re
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  The data was further pre-processed with the StanfordCoreNLP by Yu et al. (2020): https://github.com/yubowen-ph/JointER
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+ We converted the data into a more readable JSON format and used it for the default version of the dataset.
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  ### Languages
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