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  ### Dataset Summary
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- [DEplain-APA](https://zenodo.com) [(Stodden et al., 2022)]() is a dataset for the training and evaluation of sentence and document simplification in German. All texts of this dataset are provided by the Austrian Press Agency. The simple-complex sentence pairs are manually aligned.
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  ### Supported Tasks and Leaderboards
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  | Document Pairs | | | |
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  | Sentence Pairs | | | |
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- The test and validation sets are the same as those of TurkCorpus. The split was random.
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  Here, more information on simplification operations will follow soon.
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  #### Who are the annotators?
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  The annotators are two German native speakers, who are trained in linguistics. Both were at least compensated with the minimum wage of their country of residence.
 
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  ### Personal and Sensitive Information
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- [More Information Needed]
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  ## Considerations for Using the Data
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  ### Social Impact of Dataset
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- [More Information Needed]
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  ### Discussion of Biases
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- [More Information Needed]
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  ### Other Known Limitations
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  ### Dataset Curators
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- ASSET was developed by researchers at the Heinrich-Heine-University Düsseldorf, Germany. This research is part of the PhD-program ``Online Participation'', supported by the North Rhine-Westphalian (German) funding scheme ``Forschungskolleg''.
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  ### Licensing Information
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  ### Dataset Summary
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+ [DEplain-APA](https://zenodo.com) [(Stodden et al., 2023)]() is a dataset for the training and evaluation of sentence and document simplification in German. All texts of this dataset are provided by the Austrian Press Agency. The simple-complex sentence pairs are manually aligned.
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  ### Supported Tasks and Leaderboards
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  | Document Pairs | | | |
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  | Sentence Pairs | | | |
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  Here, more information on simplification operations will follow soon.
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  #### Who are the annotators?
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  The annotators are two German native speakers, who are trained in linguistics. Both were at least compensated with the minimum wage of their country of residence.
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+ They are not part of any target group of text simplification.
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  ### Personal and Sensitive Information
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+ No sensitive data.
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  ## Considerations for Using the Data
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  ### Social Impact of Dataset
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+ Many people do not understand texts due to their complexity. With automatic text simplification methods, the texts can be simplified for them. Our new training data can benefit in training a TS model.
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  ### Discussion of Biases
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+ No bias is known.
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  ### Other Known Limitations
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  ### Dataset Curators
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+ Researchers at the Heinrich-Heine-University Düsseldorf, Germany, developed DEplain-APA. This research is part of the PhD-program `Online Participation` supported by the North Rhine-Westphalian (German) funding scheme `Forschungskolleg`.
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  ### Licensing Information
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