---
configs:
  - config_name: '1640'
    data_files:
      - split: train
        path: data/1640/train/*.parquet
  - config_name: '1650'
    data_files:
      - split: train
        path: data/1650/train/*.parquet
  - config_name: '1660'
    data_files:
      - split: train
        path: data/1660/train/*.parquet
  - config_name: '1670'
    data_files:
      - split: train
        path: data/1670/train/*.parquet
  - config_name: '1680'
    data_files:
      - split: train
        path: data/1680/train/*.parquet
  - config_name: '1690'
    data_files:
      - split: train
        path: data/1690/train/*.parquet
  - config_name: '1700'
    data_files:
      - split: train
        path: data/1700/train/*.parquet
  - config_name: '1710'
    data_files:
      - split: train
        path: data/1710/train/*.parquet
  - config_name: '1720'
    data_files:
      - split: train
        path: data/1720/train/*.parquet
  - config_name: '1730'
    data_files:
      - split: train
        path: data/1730/train/*.parquet
  - config_name: '1740'
    data_files:
      - split: train
        path: data/1740/train/*.parquet
  - config_name: '1750'
    data_files:
      - split: train
        path: data/1750/train/*.parquet
  - config_name: '1760'
    data_files:
      - split: train
        path: data/1760/train/*.parquet
  - config_name: '1770'
    data_files:
      - split: train
        path: data/1770/train/*.parquet
  - config_name: '1780'
    data_files:
      - split: train
        path: data/1780/train/*.parquet
  - config_name: '1790'
    data_files:
      - split: train
        path: data/1790/train/*.parquet
  - config_name: '1800'
    data_files:
      - split: train
        path: data/1800/train/*.parquet
  - config_name: '1810'
    data_files:
      - split: train
        path: data/1810/train/*.parquet
  - config_name: '1820'
    data_files:
      - split: train
        path: data/1820/train/*.parquet
  - config_name: '1830'
    data_files:
      - split: train
        path: data/1830/train/*.parquet
  - config_name: '1840'
    data_files:
      - split: train
        path: data/1840/train/*.parquet
  - config_name: '1850'
    data_files:
      - split: train
        path: data/1850/train/*.parquet
  - config_name: '1860'
    data_files:
      - split: train
        path: data/1860/train/*.parquet
  - config_name: '1870'
    data_files:
      - split: train
        path: data/1870/train/*.parquet
  - config_name: '1880'
    data_files:
      - split: train
        path: data/1880/train/*.parquet
  - config_name: '1890'
    data_files:
      - split: train
        path: data/1890/train/*.parquet
  - config_name: '1900'
    data_files:
      - split: train
        path: data/1900/train/*.parquet
  - config_name: 'all'
    default: true
    data_files:
      - split: train
        path: data/all/train/*.parquet

license: cc-by-sa-4.0
task_categories:
- text-generation
language:
- sv
tags:
- newspapers
- historical
size_categories:
- 1B<n<10B
---

# kubhist2

## Dataset Description

- **Repository: https://github.com/iguanodon-ai/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:/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("iguanodon-ai/kubhist2")
```
or a decadal subset using 
```python
dataset = load_dataset("iguanodon-ai/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("iguanodon-ai/kubhist2", "1800")
ds_1810 = load_dataset("iguanodon-ai/kubhist2", "1810")
ds_1820 = load_dataset("iguanodon-ai/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/iguanodon-ai/kubhist2) as well as the second bibtex. 

```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}
}

```

```bibtex
@techreport{hengchen2025kubhist,
  author      = {Hengchen, Simon},
  title       = {A Huggingface Version of the Kubhist Newspaper Archive},
  year        = {2025},
  institution = {Université de Genève/\texttt{iguanodon.ai}},
  type        = {Technical Report},
  url         = {https://archive-ouverte.unige.ch/unige:187998},
  note        = {Published: 2025-10-02}
}
```

### Acknowledgments

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.