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  # KnowGL: Knowledge Generation and Linking from Text
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- The `knowgl-large` model is trained by combining Wikidata with an extended version of the training data [REBEL](https://huggingface.co/datasets/Babelscape/rebel-dataset) dataset. Given a sentence, it generates triple(s) in the following format -
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  ```
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  [(subject mention # subject label # subject type) | relation label | (object mention # object label # object type)]
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  ```
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  If there is more than one triple generated, they are separated by `$` in the output.
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- The model achieves state-of-the-art results for relation extraction on the REBEL dataset. See results in [Mihindukulasooriya et al (ISWC 2022)](https://arxiv.org/pdf/2207.05188.pdf).
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  The generated labels (for the subject, relation, and object) and their types can be directly mapped to Wikidata IDs associated with them.
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  # KnowGL: Knowledge Generation and Linking from Text
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+ The `knowgl-large` model [Rossiello et al. (AAAI 2023)](https://arxiv.org/pdf/2210.13952.pdf) is trained by combining Wikidata with an extended version of the training data [REBEL](https://huggingface.co/datasets/Babelscape/rebel-dataset) dataset. Given a sentence, it generates triple(s) in the following format -
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  ```
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  [(subject mention # subject label # subject type) | relation label | (object mention # object label # object type)]
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  ```
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  If there is more than one triple generated, they are separated by `$` in the output.
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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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