Datasets:
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---
dataset_info:
features:
- name: case_id
dtype: string
- name: Overskrift
dtype: string
- name: Afgørelsesstatus
dtype: string
- name: Faggruppe
dtype: string
- name: Ret
dtype: string
- name: Rettens sagsnummer
dtype: string
- name: Sagstype
dtype: string
- name: Instans
dtype: string
- name: Domsdatabasens sagsnummer
dtype: string
- name: Sagsemner
dtype: string
- name: Særlige retsskridt
dtype: string
- name: Sagsdeltagere
dtype: string
- name: Dørlukning
dtype: string
- name: Løftet ud af småsagsprocessen
dtype: string
- name: Anerkendelsespåstand
dtype: string
- name: Politiets journalnummer
dtype: string
- name: Påstandsbeløb
dtype: string
- name: Sagskomplekser
dtype: string
- name: text
dtype: string
- name: text_anonymized
dtype: string
- name: text_len
dtype: int64
- name: text_anon_len
dtype: int64
splits:
- name: train
num_bytes: 193593176
num_examples: 3917
download_size: 96435472
dataset_size: 193593176
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
language:
- da
task_categories:
- text-generation
size_categories:
- 1K<n<10K
---
# Dataset Card for "domsdatabasen"
## Dataset Description
- **Point of Contact:** [Oliver Kinch](mailto:[email protected])
- **Size of dataset:** 199 MB
### Dataset Summary
[Domsdatabasen](https://domsdatabasen.dk/) is a database where you can find and read selected judgments delivered by the Danish Courts.
Each judgment/case consists of tabular data and a case-descriptive PDF. This dataset collects all these cases, with each sample describing a specific judgment/case.
The PDFs are anonymized to protect sensitive information. Therefore, each sample includes two text versions:
- `text_anon` (with anonymization tags: \<anonym\>"Some sensitive text"\</anonym\>).
- `text` (without anonymization tags).
`text_anon` is read with [Easyocr](https://github.com/JaidedAI/EasyOCR).
`text` is read with [Easyocr](https://github.com/JaidedAI/EasyOCR) or [Tika-python](https://github.com/chrismattmann/tika-python)
depending on the PDF and the anonymization method used.
`text_anon` will be empty if no anonymization is detected in the PDF.
### Languages
The dataset is available in Danish (`da`).
## Dataset Structure
An example from the dataset looks as follows.
```
{
"case_id": "id of case/judgment",
... The tabualar string data ...,
"text": "pdf text",
"text_anon": "anonymized pdf text"
"text_len": <number of chars in text>,
"text_anon_len": <number of chars in anonymized text>
}
```
### Data Fields
- `case_id`: a `string` feature.
- `text`: a `string` feature.
- `text_anon`: a `string` feature.
- `text_len`: an `int` feature.
- `text_anon_len`: an `int` feature.
### Dataset Statistics
#### Size of dataset
With the PDF texts being provided in two versions, `text` and `text_anon`, the total size of all PDF texts is approximately ~199//2 MB.
#### Number of samples
- 3919
#### PDF Text Length Distribution
Statistics based on `text`.
- Minimum length: 192
- Maximum length: 2101736
## Potential Dataset Issues
See [open issues](https://github.com/oliverkinch/doms_databasen/issues).
## Dataset Creation
### Curation Rationale
There are not many large-scale law datasets in Danish.
### Source Data
The dataset has been scraped from [Domsdatabasen](https://domsdatabasen.dk/).
## Additional Information
### Dataset Curators
[Oliver Kinch](https://huggingface.co/oliverkinch) from the [The Alexandra
Institute](https://alexandra.dk/) |