Datasets:
Tasks:
Text Generation
Modalities:
Text
Formats:
parquet
Sub-tasks:
language-modeling
Languages:
Danish
Size:
1M - 10M
License:
KennethEnevoldsen
commited on
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Parent(s):
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Update README.md
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README.md
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- da-synnejyl
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# Danish Gigaword
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*Version*:
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*License*: See the respective dataset
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## Dataset Description
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https://gigaword.dk
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- **Paper:**
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http://www.derczynski.com/papers/dagw.pdf
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### Dataset Summary
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The Danish Gigaword Corpus contains text spanning several domains and forms.
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### Loading the dataset
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### Citation Information
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In a press release:
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> Modellen er præ-trænet på et datasæt fra The Danish Gigaword Project (https://gigaword.dk), der er udviklet af forskere fra IT-Universitetet i København
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> The model is pre-trained using the Danish Gigaword Corpus (https://gigaword.dk), developed at the IT University of Copenhagen
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In academic writing:
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> Derczynski, L., Ciosici, M. R., et al. (2021). The Danish Gigaword Corpus. In Proceedings of the 23rd Nordic Conference on Computational Linguistics (NoDaLiDa 2021).
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publisher = {NEALT}
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}
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```
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In a software product, tool, or service:
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> Denne service er lavet med data fra The Danish Gigaword Corpus
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### Contributions
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Dataset created by Derczynski et al. (2021). Thanks to [@HLasse](https://github.com/HLasse), [@KennethEnevoldsen](https://github.com/kennethenevoldsen), and [Jan Kostkan](https://github.com/jankounchained) for adding this dataset to the Hugging Face Hub.
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# Danish Gigaword 2
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*Version*: 2.0.0
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*License*: See the respective dataset
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## Dataset Description
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This is intended as a second version of the Danish Gigaword corpus. It is intended to be continually updated with new data sources. This is currently a work in progress.
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### Dataset Summary
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The Danish Gigaword Corpus contains text spanning several domains and forms.
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### Loading the dataset
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### Citation Information
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The original version of Danish Gigawords was created as a part of the following publication.
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> Derczynski, L., Ciosici, M. R., et al. (2021). The Danish Gigaword Corpus. In Proceedings of the 23rd Nordic Conference on Computational Linguistics (NoDaLiDa 2021).
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publisher = {NEALT}
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}
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```
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