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@@ -26,6 +26,11 @@ The CUBBITT model was published as:
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  Popel, M., Tomkova, M., Tomek, J. et al. Transforming machine translation: a deep learning system reaches news translation quality comparable to human professionals. Nat Commun 11, 4381 (2020). https://doi.org/10.1038/s41467-020-18073-9
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  ## Inter-Annotator Agreement
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  Two random annotators obtained the same dataset. The kappa score is 0.67 (substantial agreement).
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  ```
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  ## Dataset Formats
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- Dataset is available as TSV and JSONL. The JSONL version only contains pairs that were *not* annotated as "bad translation".
 
 
 
 
 
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  Popel, M., Tomkova, M., Tomek, J. et al. Transforming machine translation: a deep learning system reaches news translation quality comparable to human professionals. Nat Commun 11, 4381 (2020). https://doi.org/10.1038/s41467-020-18073-9
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+ ## Annotation
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+ From the 165390 pairs, 151470 (91.58%) were considered understandable (i.e., they were not marked as "bad translation" but the translation may not be accurate enough to preserve the entailment).
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  ## Inter-Annotator Agreement
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  Two random annotators obtained the same dataset. The kappa score is 0.67 (substantial agreement).
 
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  ```
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  ## Dataset Formats
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+ Dataset is available as TSV and JSONL.
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+ The JSONL version only contains pairs that were *not* annotated as "bad translation".
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+ In case of multiple annotations, only the *agreed* pairs (where both annotators agreed) are selected.
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+ The JSONL contains 149660 sentence pairs.