DDisCo: A Discourse Coherence Dataset for Danish
Linea Flansmose Mikkelsen, Oliver Kinch, Anders Jess Pedersen, Ophélie Lacroix
Abstract
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.- Anthology ID:
- 2022.lrec-1.260
- Volume:
- Proceedings of the Thirteenth Language Resources and Evaluation Conference
- Month:
- June
- Year:
- 2022
- Address:
- Marseille, France
- Editors:
- Nicoletta Calzolari, Frédéric Béchet, Philippe Blache, Khalid Choukri, Christopher Cieri, Thierry Declerck, Sara Goggi, Hitoshi Isahara, Bente Maegaard, Joseph Mariani, Hélène Mazo, Jan Odijk, Stelios Piperidis
- Venue:
- LREC
- SIG:
- Publisher:
- European Language Resources Association
- Note:
- Pages:
- 2440–2445
- Language:
- URL:
- https://aclanthology.org/2022.lrec-1.260
- DOI:
- Cite (ACL):
- Linea Flansmose Mikkelsen, Oliver Kinch, Anders Jess Pedersen, and Ophélie Lacroix. 2022. DDisCo: A Discourse Coherence Dataset for Danish. In Proceedings of the Thirteenth Language Resources and Evaluation Conference, pages 2440–2445, Marseille, France. European Language Resources Association.
- Cite (Informal):
- DDisCo: A Discourse Coherence Dataset for Danish (Flansmose Mikkelsen et al., LREC 2022)
- PDF:
- https://preview.aclanthology.org/emnlp-22-attachments/2022.lrec-1.260.pdf