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  [![PWC](https://img.shields.io/endpoint.svg?url=https://paperswithcode.com/badge/rebel-relation-extraction-by-end-to-end/joint-entity-and-relation-extraction-on-3)](https://paperswithcode.com/sota/joint-entity-and-relation-extraction-on-3?p=rebel-relation-extraction-by-end-to-end)
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  [![PWC](https://img.shields.io/endpoint.svg?url=https://paperswithcode.com/badge/rebel-relation-extraction-by-end-to-end/relation-extraction-on-ade-corpus)](https://paperswithcode.com/sota/relation-extraction-on-ade-corpus?p=rebel-relation-extraction-by-end-to-end)
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  [![PWC](https://img.shields.io/endpoint.svg?url=https://paperswithcode.com/badge/rebel-relation-extraction-by-end-to-end/relation-extraction-on-re-tacred)](https://paperswithcode.com/sota/relation-extraction-on-re-tacred?p=rebel-relation-extraction-by-end-to-end)
 
 
 
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  # REBEL <img src="https://i.ibb.co/qsLzNqS/hf-rebel.png" width="30" alt="hf-rebel" border="0" style="display:inline; white-space:nowrap;">: Relation Extraction By End-to-end Language generation
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  This is the model card for the Findings of EMNLP 2021 paper [REBEL: Relation Extraction By End-to-end Language generation](https://github.com/Babelscape/rebel/blob/main/docs/EMNLP_2021_REBEL__Camera_Ready_.pdf). We present a new linearization approach and a reframing of Relation Extraction as a seq2seq task. The paper can be found [here](https://github.com/Babelscape/rebel/blob/main/docs/EMNLP_2021_REBEL__Camera_Ready_.pdf). If you use the code, please reference this work in your paper:
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  [![PWC](https://img.shields.io/endpoint.svg?url=https://paperswithcode.com/badge/rebel-relation-extraction-by-end-to-end/joint-entity-and-relation-extraction-on-3)](https://paperswithcode.com/sota/joint-entity-and-relation-extraction-on-3?p=rebel-relation-extraction-by-end-to-end)
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  [![PWC](https://img.shields.io/endpoint.svg?url=https://paperswithcode.com/badge/rebel-relation-extraction-by-end-to-end/relation-extraction-on-ade-corpus)](https://paperswithcode.com/sota/relation-extraction-on-ade-corpus?p=rebel-relation-extraction-by-end-to-end)
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  [![PWC](https://img.shields.io/endpoint.svg?url=https://paperswithcode.com/badge/rebel-relation-extraction-by-end-to-end/relation-extraction-on-re-tacred)](https://paperswithcode.com/sota/relation-extraction-on-re-tacred?p=rebel-relation-extraction-by-end-to-end)
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+ ## Multilingual update! Check [mREBEL](https://huggingface.co/Babelscape/mrebel-large), a multilingual version covering more relation types, languages and including entity types.
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  # REBEL <img src="https://i.ibb.co/qsLzNqS/hf-rebel.png" width="30" alt="hf-rebel" border="0" style="display:inline; white-space:nowrap;">: Relation Extraction By End-to-end Language generation
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  This is the model card for the Findings of EMNLP 2021 paper [REBEL: Relation Extraction By End-to-end Language generation](https://github.com/Babelscape/rebel/blob/main/docs/EMNLP_2021_REBEL__Camera_Ready_.pdf). We present a new linearization approach and a reframing of Relation Extraction as a seq2seq task. The paper can be found [here](https://github.com/Babelscape/rebel/blob/main/docs/EMNLP_2021_REBEL__Camera_Ready_.pdf). If you use the code, please reference this work in your paper:
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