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DDisCo: A Discourse Coherence Dataset for Danish

2022-06-01 · LREC 2022 6 · Linea Flansmose Mikkelsen, Oliver Kinch, Anders Jess Pedersen, Ophélie Lacroix

To date, there has been no resource for studying discourse coherence on real-world Danish texts. Discourse coherence has mostly been approached with the assumption that incoherent texts can be represented by coherent texts in which sentences have been shuffled. However, incoherent real-world texts rarely resemble that. We thus present DDisCo, a dataset including text from the Danish Wikipedia and Reddit annotated for discourse coherence. We choose to annotate real-world texts instead of relying on artificially incoherent text for training and testing models. Then, we evaluate the performance of several methods, including neural networks, on the dataset.

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