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  - **Size of the generated dataset:** 139.2 MB
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  - **Total amount of disk used:** 201.5 MB
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  ### Dataset Summary
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- The TAC Relation Extraction Dataset (TACRED) is a large-scale relation extraction dataset with 106,264 examples built over newswire and web text from the corpus used in the yearly TAC Knowledge
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- Base Population (TAC KBP) challenges. Examples in TACRED cover 41 relation types as used in the TAC KBP challenges (e.g., per:schools_attended
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- and org:members) or are labeled as no_relation if no defined relation is held. These examples are created by combining available human annotations from the TAC
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- KBP challenges and crowdsourcing. Please see our EMNLP paper, or our EMNLP slides for full details.
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- Note: There is currently a label-corrected version of the TACRED dataset, which you should consider using instead of
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- the original version released in 2017. For more details on this new version, see the [TACRED Revisited paper](https://aclanthology.org/2020.acl-main.142/)
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  published at ACL 2020.
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  ### Supported Tasks and Leaderboards
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  - **Tasks:** Relation Classification
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  - **Leaderboards:** [https://paperswithcode.com/sota/relation-extraction-on-tacred](https://paperswithcode.com/sota/relation-extraction-on-tacred)
 
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  - **Size of the generated dataset:** 139.2 MB
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  - **Total amount of disk used:** 201.5 MB
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  ### Dataset Summary
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+ The TAC Relation Extraction Dataset (TACRED) is a large-scale relation extraction dataset with 106,264 examples built over newswire and web text from the corpus used in the yearly TAC Knowledge Base Population (TAC KBP) challenges. Examples in TACRED cover 41 relation types as used in the TAC KBP challenges (e.g., per:schools_attended
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+ and org:members) or are labeled as no_relation if no defined relation is held. These examples are created by combining available human annotations from the TAC
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+ KBP challenges and crowdsourcing. Please see [Stanford's EMNLP paper](https://nlp.stanford.edu/pubs/zhang2017tacred.pdf), or their [EMNLP slides](https://nlp.stanford.edu/projects/tacred/files/position-emnlp2017.pdf) for full details.
 
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+ Note: There is currently a [label-corrected version](https://github.com/DFKI-NLP/tacrev) of the TACRED dataset, which you should consider using instead of
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+ the original version released in 2017. For more details on this new version, see the [TACRED Revisited paper](https://aclanthology.org/2020.acl-main.142/)
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  published at ACL 2020.
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+
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+
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  ### Supported Tasks and Leaderboards
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  - **Tasks:** Relation Classification
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  - **Leaderboards:** [https://paperswithcode.com/sota/relation-extraction-on-tacred](https://paperswithcode.com/sota/relation-extraction-on-tacred)