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license: cc-by-sa-4.0 |
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task_categories: |
|
- text-generation |
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language: |
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- sv |
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tags: |
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- newspapers |
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- historical |
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size_categories: |
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- 1B<n<10B |
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--- |
|
|
|
# kubhist2 |
|
|
|
## Dataset Description |
|
|
|
- **Homepage: https://changeiskey.org** |
|
- **Repository: https://github.com/ChangeIsKey/kubhist2** |
|
- **Point of Contact: Simon Hengchen / iguanodon.ai** |
|
|
|
|
|
### Dataset Summary |
|
|
|
This is a version of the Kubhist 2 dataset originally created, curated and made available by Språkbanken Text (SBX) at the University of Gothenburg (Sweden) under the CC BY 4.0 license. |
|
This is a corpus of OCRed newspapers from Sweden spanning the 1640s to the 1900s. |
|
The original data is available with many types of annotation in XML at https://spraakbanken.gu.se/en/resources/kubhist2. |
|
A good description of the original data is available in this blog entry by Dana Dannélls: https://spraakbanken.gu.se/blogg/index.php/2019/09/15/the-kubhist-corpus-of-swedish-newspapers/. |
|
|
|
If you use this dataset for academic research, cite it using the provided citation information at the bottom of this page. |
|
|
|
In a nutshell, this huggingface dataset version offers: |
|
- only the OCRed text |
|
- available in decadal subsets |
|
- one line per sentence, sentences shorter than 4 words were discarded |
|
|
|
In total this dataset contains 2,819,065,590 tokens. A distribution of tokens per decade is available below. |
|
|
|
License is CC BY 4.0 ShareAlike. |
|
|
|
```bash |
|
(env) simon@terminus:/mnt/user/cik/kubhist2 wc -w text/*/*.txt |
|
39348 text/1640/1640.txt |
|
4700 text/1650/1650.txt |
|
8524 text/1660/1660.txt |
|
2396 text/1670/1670.txt |
|
199670 text/1680/1680.txt |
|
487943 text/1690/1690.txt |
|
619884 text/1700/1700.txt |
|
265930 text/1710/1710.txt |
|
355759 text/1720/1720.txt |
|
856218 text/1730/1730.txt |
|
1589508 text/1740/1740.txt |
|
2211316 text/1750/1750.txt |
|
5496545 text/1760/1760.txt |
|
14434932 text/1770/1770.txt |
|
22366170 text/1780/1780.txt |
|
26768856 text/1790/1790.txt |
|
36225842 text/1800/1800.txt |
|
44510588 text/1810/1810.txt |
|
65571094 text/1820/1820.txt |
|
95359730 text/1830/1830.txt |
|
143992956 text/1840/1840.txt |
|
214538699 text/1850/1850.txt |
|
392672066 text/1860/1860.txt |
|
524802728 text/1870/1870.txt |
|
695859650 text/1880/1880.txt |
|
498244203 text/1890/1890.txt |
|
31580335 text/1900/1900.txt |
|
2819065590 total |
|
|
|
``` |
|
|
|
|
|
### Languages |
|
|
|
Swedish (nysvenska) |
|
|
|
## Dataset Structure |
|
|
|
One feature: `text`. |
|
|
|
|
|
Load the whole corpus using |
|
```python |
|
dataset = load_dataset("ChangeIsKey/kubhist2") |
|
``` |
|
or a decadal subset using |
|
```python |
|
dataset = load_dataset("ChangeIsKey/kubhist2", "decade") |
|
``` |
|
The `decade` must be a string, valid values are within `range(1640, 1910, 10)`. |
|
|
|
You can combine several decades using `concatenate_datasets` like this: |
|
|
|
```python |
|
from datasets import load_dataset, concatenate_datasets |
|
|
|
ds_1800 = load_dataset("ChangeIsKey/kubhist2", "1800") |
|
ds_1810 = load_dataset("ChangeIsKey/kubhist2", "1810") |
|
ds_1820 = load_dataset("ChangeIsKey/kubhist2", "1820") |
|
|
|
ds_1800_1820 = concatenate_datasets([ |
|
ds_1800["train"], |
|
ds_1810["train"], |
|
ds_1820["train"] |
|
]) |
|
``` |
|
|
|
Despite what the huggingface dataset viewer states the `all` config has 285.4M (285,384,149 to be precise) rows, not 77.9M. |
|
|
|
### Data Splits |
|
|
|
The dataset has only one split, `train`. |
|
|
|
## Dataset Creation |
|
|
|
### Curation Rationale |
|
|
|
The original data is in a highly-annotated XML format not ideally suited for basic NLP tasks such as unsupervised language modeling: information such as page numbers, fonts, etc. is less relevant and has thus been discarded. |
|
Keeping only the running text of the newspaper and removing sentences shorter than 4 words further allows a 150x data size reduction (2.4TB --> 16GB). |
|
|
|
### Source Data |
|
|
|
The original data is available with many types of annotation in XML at https://spraakbanken.gu.se/en/resources/kubhist2. |
|
|
|
#### Initial Data Collection and Normalization |
|
|
|
See on Språkbanken Text's website. |
|
|
|
#### Who are the source language producers? |
|
|
|
Språkbanken Text: https://spraakbanken.gu.se/en/ |
|
|
|
### Personal and Sensitive Information |
|
|
|
This is historical newspaper data, with the latest data published in 1909. Everyone mentioned in this dataset was probably already a public figure, and has been dead for a while. |
|
|
|
## Considerations for Using the Data |
|
|
|
### Discussion of Biases |
|
|
|
This is historical data. As such, outdated views might be present in the data. |
|
|
|
### Other Known Limitations |
|
|
|
The data comes from an OCR process. The text is thus not perfect, especially so in the earlier decades. |
|
|
|
## Additional Information |
|
|
|
### Dataset Curators |
|
|
|
This huggingface version of the data has been created by Simon Hengchen. |
|
|
|
### Licensing Information |
|
|
|
Creative Commons Attribution Share Alike 4.0: https://creativecommons.org/licenses/by-sa/4.0/ |
|
|
|
### Citation Information |
|
|
|
You should always cite the original kubhist2 release, provided below as bibtex. If you want to additionally refer to this specific version, please also add a link to the huggingface page: https://huggingface.co/datasets/ChangeIsKey/kubhist2. |
|
|
|
```bibtex |
|
@misc{Kubhist2, |
|
title = {The Kubhist Corpus, v2}, |
|
url = {https://spraakbanken.gu.se/korp/?mode=kubhist}, |
|
author = {Spr{\aa}kbanken}, |
|
year = {Downloaded in 2019}, |
|
organization = {Department of Swedish, University of Gothenburg} |
|
} |
|
|
|
``` |
|
|
|
### Acknowledgments |
|
|
|
This dataset has been created in the context of the [ChangeIsKey!](https://www.changeiskey.org/) project funded by Riksbankens Jubileumsfond under reference number M21-0021, Change is Key! program. |
|
The compute dedicated to the creation of the dataset has been provided by [iguanodon.ai](https://iguanodon.ai). |
|
|
|
Many thanks got to Språkbanken Text for creating and curating this resource. |
