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@@ -6,10 +6,15 @@ license: cc-by-nc-sa-4.0
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  # Dataset Description
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  This dataset contains parallel documents (i.e., titles & abstracts) extracted from academic theses, dissertations, and other scientific texts.
 
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  In the original [paper](https://aclanthology.org/2022.lrec-1.284.pdf), we've extracted 9.17M sentence pairs in 31 language pairs from 86 repositories.
 
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  This version has been created through further processing and filtering to extract parallel **documents** instead of parallel **sentences**.
 
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  To do this, we kept only the parallel titles and abstracts of academic records with high (mean) alignment scores by also using other filters (e.g., word ratio, non-empty abstracts, etc.).
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  <br/>
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  Table 1: Number of parallel documents per language pair
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  <br/>
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- Please note that this dataset will keep getting updated to include more language pairs, per the original paper.
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-
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  # Related Datasets
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  The original datasets can be found in ELRC-SHARE:
@@ -36,10 +39,12 @@ The original datasets can be found in ELRC-SHARE:
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  # Citation
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  @inproceedings{roussis2022scipar,
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  title={SciPar: A collection of parallel corpora from scientific abstracts},
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  author={Roussis, Dimitrios and Papavassiliou, Vassilis and Prokopidis, Prokopis and Piperidis, Stelios and Katsouros, Vassilis},
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  booktitle={Proceedings of the Thirteenth Language Resources and Evaluation Conference},
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  pages={2652--2657},
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  year={2022}
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- }
 
 
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  # Dataset Description
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  This dataset contains parallel documents (i.e., titles & abstracts) extracted from academic theses, dissertations, and other scientific texts.
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+
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  In the original [paper](https://aclanthology.org/2022.lrec-1.284.pdf), we've extracted 9.17M sentence pairs in 31 language pairs from 86 repositories.
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+
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  This version has been created through further processing and filtering to extract parallel **documents** instead of parallel **sentences**.
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+
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  To do this, we kept only the parallel titles and abstracts of academic records with high (mean) alignment scores by also using other filters (e.g., word ratio, non-empty abstracts, etc.).
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+ Please note that this dataset will keep getting updated to include *more language pairs*, per the original paper.
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+
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  <br/>
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  Table 1: Number of parallel documents per language pair
 
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  <br/>
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  # Related Datasets
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  The original datasets can be found in ELRC-SHARE:
 
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  # Citation
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+ ```
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  @inproceedings{roussis2022scipar,
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  title={SciPar: A collection of parallel corpora from scientific abstracts},
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  author={Roussis, Dimitrios and Papavassiliou, Vassilis and Prokopidis, Prokopis and Piperidis, Stelios and Katsouros, Vassilis},
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  booktitle={Proceedings of the Thirteenth Language Resources and Evaluation Conference},
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  pages={2652--2657},
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  year={2022}
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+ }
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+ ```