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  1. README.md +3 -3
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@@ -25,9 +25,9 @@ model-index:
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  name: Babelscape/rebel-dataset
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  type: REBEL
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  metrics:
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- - type: re+ macro f1
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  value: 70.74
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- name: RE+ Macro F1
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  ---
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  # KnowGL: Knowledge Generation and Linking from Text
@@ -38,7 +38,7 @@ The `knowgl-large` model is trained by combining Wikidata with an extended versi
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  ```
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  If there are more than one triples generated, they are separated by `$` in the output. More details in [Rossiello et al. (AAAI 2023)](https://arxiv.org/pdf/2210.13952.pdf).
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- The model achieves state-of-the-art results for relation extraction on the REBEL dataset. See results in [Mihindukulasooriya et al. (ISWC 2022)](https://arxiv.org/pdf/2207.05188.pdf).
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  The generated labels (for the subject, relation, and object) and their types can be directly mapped to Wikidata IDs associated with them.
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  name: Babelscape/rebel-dataset
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  type: REBEL
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  metrics:
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+ - type: re+ micro f1
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  value: 70.74
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+ name: RE+ Micro F1
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  ---
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  # KnowGL: Knowledge Generation and Linking from Text
 
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  ```
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  If there are more than one triples generated, they are separated by `$` in the output. More details in [Rossiello et al. (AAAI 2023)](https://arxiv.org/pdf/2210.13952.pdf).
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+ The model achieves good results for relation extraction on the REBEL dataset. See results in [Mihindukulasooriya et al. (ISWC 2022)](https://arxiv.org/pdf/2207.05188.pdf).
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  The generated labels (for the subject, relation, and object) and their types can be directly mapped to Wikidata IDs associated with them.
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