DaNewsroom: A Large-scale Danish Summarisation Dataset

Daniel Varab, Natalie Schluter

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Dataset development for automatic summarisation systems is notoriously English-oriented. In this paper we present the first large-scale non-English language dataset specifically curated for automatic summarisation. The document-summary pairs are news articles and manually written summaries in the Danish language. There has previously been no work done to establish a Danish summarisation dataset, nor any published work on the automatic summarisation of Danish. We provide therefore the first automatic summarisation dataset for the Danish language (large-scale or otherwise). To support the comparison of future automatic summarisation systems for Danish, we include system performance on this dataset of strong well-established unsupervised baseline systems, together with an oracle extractive summariser, which is the first account of automatic summarisation system performance for Danish. Finally, we make all code for automatically acquiring the data freely available and make explicit how this technology can easily be adapted in order to acquire automatic summarisation datasets for further languages.
TitelProceedings of the 12th Conference on Language Resources and Evaluation (LREC 2020)
ForlagEuropean Language Resources Association
Publikationsdatoapr. 2020
StatusUdgivet - apr. 2020
BegivenhedLREC 2020 - Marseille, Frankrig
Varighed: 17 maj 202022 maj 2020


KonferenceLREC 2020


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