---
dataset_info:
- config_name: default
  features:
  - name: question
    dtype: string
  - name: index
    dtype: int64
  - name: option-A
    dtype: string
  - name: option-B
    dtype: string
  - name: option-C
    dtype: string
  - name: correct
    dtype: string
  - name: origin
    dtype: string
  splits:
  - name: train
    num_bytes: 103251
    num_examples: 605
  download_size: 43667
  dataset_size: 103251
- config_name: raw
  features:
  - name: question
    dtype: string
  - name: index
    dtype: int64
  - name: option-A
    dtype: string
  - name: option-B
    dtype: string
  - name: option-C
    dtype: string
  - name: correct
    dtype: string
  - name: origin
    dtype: string
  splits:
  - name: train
    num_bytes: 103906
    num_examples: 605
  download_size: 45297
  dataset_size: 103906
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
- config_name: raw
  data_files:
  - split: train
    path: raw/train-*
task_categories:
- question-answering
language:
- da
pretty_name: Citizenship Tests Da.
size_categories:
- n<1K
---
# Dataset Card for "citizenship-test-da"

This dataset contains scraped questions and answers from Danish citizen tests (Danish: *indfødsretsprøver* og *medborgerskabsprøver*) from Juni 2019 to May 2023 from PDF's produced by ''Styrelsen for International Rekruttering og Integration'' (SIRI).

The dataset is released as an appendix to the thesis [''Are GLLMs Danoliterate? Benchmarking Generative NLP in Danish''](https://sorenmulli.github.io/thesis/thesis.pdf) and permission by SIRI for this specific purpose.


The PDF's are available on [SIRI's website](https://siri.dk/nyheder/?categorizations=9115).
The `default` configuration has been semi-automatically cleaned to remove PDF artifacts using the [Alvenir 3gram DSL language model](https://github.com/danspeech/danspeech/releases/tag/v0.02-alpha).
The examples were not deduplicated.

Further details can be found in Section 4.2.1 in the [thesis](https://sorenmulli.github.io/thesis/thesis.pdf).

- Produced by: Søren Vejlgaard Holm under supervision of Lars Kai Hansen and Martin Carsten Nielsen.
- Usable for: Question Answering Evaluation.
- Contact: Søren Vejlgaard Holm at swiho@dtu.dk or swh@alvenir.ai.