---
license: cc0-1.0
task_categories:
- summarization
language:
- nb
- nn
- 'no'
size_categories:
- n<1K
dataset_info:
- config_name: nb
  features:
  - name: id
    dtype: string
  - name: article
    dtype: string
  - name: summaries
    sequence: string
  splits:
  - name: validation
    num_bytes: 165830
    num_examples: 30
  - name: test
    num_bytes: 217351
    num_examples: 33
  download_size: 247097
  dataset_size: 383181
- config_name: nn
  features:
  - name: id
    dtype: string
  - name: article
    dtype: string
  - name: summaries
    sequence: string
  splits:
  - name: validation
    num_bytes: 165879
    num_examples: 30
  - name: test
    num_bytes: 219189
    num_examples: 33
  download_size: 249301
  dataset_size: 385068
configs:
- config_name: nb
  data_files:
  - split: validation
    path: nb/validation-*
  - split: test
    path: nb/test-*
- config_name: nn
  data_files:
  - split: validation
    path: nn/validation-*
  - split: test
    path: nn/test-*
---
configs:
- config_name: default
  data_files:
  - split: dev
    path: "NorSumm_dev.json"
  - split: test
    path: "NorSumm_test.json"
---
---
# Dataset Card for Dataset Name

<!-- Provide a quick summary of the dataset. -->

This repository contains the Norwegian Summarisation Benchmark Dataset, which consists of 378 human-authored summaries from prominent Norwegian news sources across various domains. The dataset is designed to benchmark the abstractive summarisation capabilities of generative language models. NorSumm is the first manually created Norwegian news summarization datasat, created from scratch in Norwegian. The dataset consists of 378 manually generated summaries for 63 new articles. Each news article has been summarised by three native Norwegian speakers, and each generated summary has been translated to either Norwegian written form (Bokmål or Nynorsk) depending on which language the original summary has been written in.

The accompanying paper by [Touileb et al. (2025)](https://arxiv.org/pdf/2501.07718) provides a comprehensive account of the data creation process and evaluates the performance of existing open large language models for Norwegian on this dataset. Additionally, it offers insights from a manual human evaluation, comparing human-authored summaries to those generated by models. The findings suggest that the dataset presents a challenging benchmark for assessing the summarisation capabilities of LLMs in Norwegian.

## Source data

We used a subset of news articles from the Norwegian event extraction dataset EDEN [(Touileb et al., 2024)](https://aclanthology.org/2024.lrec-main.488/), as the source for summarisation. Due to the time-intensive nature of creating summaries, we only created summaries for the development and test splits of EDEN, comprising 30 and 33 news articles, respectively.

### Dataset Description

<!-- Provide a longer summary of what this dataset is. -->

The dataset contains pairs of articles and six generated summaries (generetaed by three individual people, in both Bokmål and Nynorsk). The news articles represen the Bokmål portion of the Norwegian Dependency treebank data [NDT](https://www.nb.no/sprakbanken/en/resource-catalogue/oai-nb-no-sbr-10/).

- **Curated by:** Human annotators.
- **Funded by:** [MediaFutures: Research Centre for Responsible Media Technology & Innovation](https://mediafutures.no/), University of Bergen.
- **Shared by:** [WP5 -- Norwegian language technology](https://mediafutures.no/norwegian-language-technologies/), at MediaFutures
- **Language(s) (NLP):** Norwegian Bokmål and Nynorsk.
- **License:** CC0-1.0

### Dataset Sources [optional]

<!-- Provide the basic links for the dataset. -->

- **Repository:** [https://github.com/SamiaTouileb/NorSumm](https://github.com/SamiaTouileb/NorSumm)
- **Paper [optional]:** [Touileb et al. (2025)](https://arxiv.org/pdf/2501.07718). Benchmarking Abstractive Summarisation: A Dataset of Human-authored Summaries of Norwegian News Articles. Accepted at NoDaLiDa2025.

## Uses

<!-- Address questions around how the dataset is intended to be used. -->
The dataset is intended to be used for NLP model benchmarking.

## Terms of use
The license is the same as the underlying Norwegian Dependency Treebank and is Creative Commons (CC) Licence Name: Creative_Commons-ZERO (CC-ZERO).

#### Who are the annotators?

We hired three annotators with strong academic backgrounds related to journalism, all Norwegian native speakers. They were fairly compensated following an hourly contract, and were hired for a period of 6 months. All annotators have a background in media science or journalism. 

## Citation [optional]

<!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. -->

**BibTeX:**

``
@article{touileb2025benchmarking,
  title={Benchmarking Abstractive Summarisation: A Dataset of Human-authored Summaries of Norwegian News Articles},
  author={Touileb, Samia and Mikhailov, Vladislav and Kroka, Marie and {\O}vrelid, Lilja and Velldal, Erik},
  journal={arXiv preprint arXiv:2501.07718},
  year={2025}
}
``

**APA:**

Touileb, S., Mikhailov, V., Kroka, M., Øvrelid, L., & Velldal, E. (2025). Benchmarking Abstractive Summarisation: A Dataset of Human-authored Summaries of Norwegian News Articles. arXiv preprint arXiv:2501.07718.

## Dataset Card Authors

Samia Touileb

## Dataset Card Contact

Samia Touileb