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  ---
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  task_categories:
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  - text2text-generation
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- task_ids:
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- - text-simplification
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  language:
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  - de
 
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  size_categories:
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  - 10K<n<100K
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- pretty_name: DEplain-APA
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- configs:
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- - simplification
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  ---
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  # Dataset Card for DEplain-APA
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  ## Dataset Description
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- - **Repository:** [DEplain-APA zenodo repository](https://zenodo.com/)
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- - **Paper:** [DEplain: ]()
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  - **Point of Contact:** [Regina Stodden](regina.stodden@hhu.de)
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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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  ### Data Access
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- - The dataset is licensed with restricted access for only academic purposes. To download the dataset, please request access on [zenodo]().
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  ### Data Instances
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  - `document-simplification` configuration: an instance consists of an original document and one reference simplification.
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  | | Train | Dev | Test | Total |
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  | ----- | ------ | ------ | ---- | ----- |
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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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  #### Initial Data Collection and Normalization
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  The original news texts (in CEFR level C2) were manually simplified by professional translators, i.e. capito – CFS GmbH, and provided to us by the Austrian Press Agency.
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- All documents date back to 2019 to 2021 (?).
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  Two German native speakers have manually aligned the sentence pairs by using the text simplification annotation tool TS-ANNO. The data was split into sentences using a German model of SpaCy.
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  #### Who are the source language producers?
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  [More Information Needed]
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- This dataset card uses material written by [Juan Diego Rodriguez](https://github.com/juand-r) and [Yacine Jernite](https://github.com/yjernite).
 
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  ---
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  task_categories:
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  - text2text-generation
 
 
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  language:
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  - de
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+ pretty_name: DEplain-APA
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  size_categories:
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  - 10K<n<100K
 
 
 
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  ---
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  # Dataset Card for DEplain-APA
 
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  ## Dataset Description
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+ - **Repository:** [DEplain-APA zenodo repository](https://zenodo.org/record/7674560)
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+ - **Paper:** Regina Stodden, Momen Omar, and Laura Kallmeyer. 2023. ["DEplain: A German Parallel Corpus with Intralingual Translations into Plain Language for Sentence and Document Simplification."](https://arxiv.org/abs/2305.18939). In Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), Toronto, Canada. Association for Computational Linguistics.
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  - **Point of Contact:** [Regina Stodden](regina.stodden@hhu.de)
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  ### Dataset Summary
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+ [DEplain-APA](https://zenodo.org/record/7674560) [(Stodden et al., 2023)](https://arxiv.org/abs/2305.18939) 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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  ### Data Access
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+ - The dataset is licensed with restricted access for only academic purposes. To download the dataset, please request access on [zenodo](https://zenodo.org/record/7674560).
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  ### Data Instances
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  - `document-simplification` configuration: an instance consists of an original document and one reference simplification.
 
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  | | Train | Dev | Test | Total |
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  | ----- | ------ | ------ | ---- | ----- |
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+ | Document Pairs | 387 | 48 | 48 | 483
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+ | Sentence Pairs | 10660 | 1231 | 1231 | 13122
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  Here, more information on simplification operations will follow soon.
 
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  #### Initial Data Collection and Normalization
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  The original news texts (in CEFR level C2) were manually simplified by professional translators, i.e. capito – CFS GmbH, and provided to us by the Austrian Press Agency.
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+ All documents date back to 2019 to 2021.
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  Two German native speakers have manually aligned the sentence pairs by using the text simplification annotation tool TS-ANNO. The data was split into sentences using a German model of SpaCy.
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  #### Who are the source language producers?
 
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  [More Information Needed]
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+ This dataset card uses material written by [Juan Diego Rodriguez](https://github.com/juand-r) and [Yacine Jernite](https://github.com/yjernite).