metadata

dataset_info:
  - config_name: nb
    features:
      - name: id
        dtype: string
      - name: question
        dtype: string
      - name: choices
        struct:
          - name: label
            sequence: string
          - name: text
            sequence: string
      - name: answer
        dtype: string
      - name: quiz
        dtype: string
      - name: curated
        dtype: bool
    splits:
      - name: test
        num_bytes: 922278
        num_examples: 3600
    download_size: 492918
    dataset_size: 922278
  - config_name: nn
    features:
      - name: id
        dtype: string
      - name: question
        dtype: string
      - name: choices
        struct:
          - name: label
            sequence: string
          - name: text
            sequence: string
      - name: answer
        dtype: string
      - name: quiz
        dtype: string
      - name: curated
        dtype: bool
    splits:
      - name: test
        num_bytes: 340107
        num_examples: 1330
    download_size: 175131
    dataset_size: 340107
configs:
  - config_name: nb
    data_files:
      - split: test
        path: nb/test-*
  - config_name: nn
    data_files:
      - split: test
        path: nn/test-*
license: mit
task_categories:
  - question-answering
language:
  - nb
  - nn
pretty_name: NRK-Quiz-QA
size_categories:
  - 1K<n<10K

Dataset Card for NRK-Quiz-QA

Dataset Details

Dataset Description

NRK-Quiz-QA is a multiple-choice question answering (QA) dataset designed for zero-shot evaluation of language models' Norwegian-specific and world knowledge. It comprises 4.9k examples from over 500 quizzes on Norwegian language and culture, spanning both written standards of Norwegian: Bokmål and Nynorsk (the minority variant). These quizzes are sourced from NRK, the national public broadcaster in Norway. Each example includes a question and 2 to 5 answer choices.

NRK-Quiz-QA is part of the collection of Norwegian QA datasets, which also includes: NorOpenBookQA, NorCommonSenseQA, NorTruthfulQA (Multiple Choice), and NorTruthfulQA (Generation). We describe our high-level dataset creation approach here and provide more details, general statistics, and model evaluation results in our paper.

Curated by: The Language Technology Group (LTG) at the University of Oslo
Shared by: NRK through initial contact by Språkbanken.
Language: Norwegian (Bokmål and Nynorsk)
Repository: github.com/ltgoslo/norqa
Paper: aclanthology.org/2025.nodalida-1.43 (NoDaLiDa/Baltic-HLT 2025)
License: MIT

Citation

@inproceedings{mikhailov-etal-2025-collection,
    title = "A Collection of Question Answering Datasets for {Norwegian}",
    author = "Mikhailov, Vladislav  and
      M{\ae}hlum, Petter  and
      Lang{\o}, Victoria Ovedie Chruickshank  and
      Velldal, Erik  and
      {\O}vrelid, Lilja",
    editor = "Johansson, Richard  and
      Stymne, Sara",
    booktitle = "Proceedings of the Joint 25th Nordic Conference on Computational Linguistics and 11th Baltic Conference on Human Language Technologies (NoDaLiDa/Baltic-HLT 2025)",
    month = mar,
    year = "2025",
    address = "Tallinn, Estonia",
    publisher = "University of Tartu Library",
    url = "https://aclanthology.org/2025.nodalida-1.43/",
    pages = "397--407",
    ISBN = "978-9908-53-109-0",
    abstract = "This paper introduces a new suite of question answering datasets for Norwegian; NorOpenBookQA, NorCommonSenseQA, NorTruthfulQA, and NRK-Quiz-QA. The data covers a wide range of skills and knowledge domains, including world knowledge, commonsense reasoning, truthfulness, and knowledge about Norway. Covering both of the written standards of Norwegian {--} Bokm{\r{a}}l and Nynorsk {--} our datasets comprise over 10k question-answer pairs, created by native speakers. We detail our dataset creation approach and present the results of evaluating 11 language models (LMs) in zero- and few-shot regimes. Most LMs perform better in Bokm{\r{a}}l than Nynorsk, struggle most with commonsense reasoning, and are often untruthful in generating answers to questions. All our datasets and annotation materials are publicly available."
}

Uses

NRK-Quiz-QA is intended to be used for zero-shot evaluation of language models for Norwegian.

Dataset Creation

NRK-Quiz-QA is based on a collection of quizzes from between the years of 2017 and 2024, provided by NRK. The quiz data is of high quality, but we perform a targeted adaptation to ensure correct time references. This annotation stage is performed by three students in linguistics and computer science, all native Norwegian speakers. Two annotators work on Bokmål, and one annotator works on Nynorsk. There are three main curation aspects:

Temporal adjustment: The annotators adjust temporal references to fit the current time.
Content filtering: The annotators discard examples requiring images or sounds for answering.
Data cleaning: The annotators remove unnecessary text segments (e.g., web page artifacts), and irrelevant content in the questions (e.g., comments that guide the user through the quiz).

Personal and Sensitive Information

The data does not contain information considered personal or sensitive.

Dataset Structure

Dataset Instances

Each dataset instance looks as follows:

Bokmål

{
    'id': '1.16235578-6',
    'question': 'Juletrefester er moro for kidsa. I sin tid bidro festene også til å spre den juletreskikken vi kjenner i dag. Vet du i hvilket århundre juletreet meldte sin ankomst i Norge?',
    'choices': {
        'label': ['A', 'B', 'C'],
        'text': ['1900-tallet', '1800-tallet', '1700-tallet']
    },
    'answer': 'B',
    'quiz': 'Romjulsquiz',
    'curated': True
}

Nynorsk

{
    'id': '1.14319825-6b',
    'question': 'Sogndal spelte i førstedivisjon i 2019, etter at dei tapte 3–1 borte mot Aalesund i kvalifiseringskampen. Men kven scora Sogndal sitt mål?',
    'choices': {
        'label': ['A', 'B', 'C', 'D'],
        'text': [
            'Ulrik Flo',
            'Sigurd Haugen',
            'Ulrik Fredriksen',
            'Eirik Birkelund'
        ]
    },
    'answer': 'C',
    'quiz': 'Helgequiz frå NRK Sogn og Fjordane',
    'curated': True
}

Dataset Fields

id: an example id
question: a quiz question
choices: answer choices (label: a list of labels; text: a list of possible answers)
answer: the correct answer from the list of labels (A/B/C/D/E)
quiz: a quiz name
curated: an indicator of whether an example has been curated or not

Dataset Card Contact

Vladislav Mikhailov ([email protected])
Lilja Øvrelid ([email protected])