Abstract
This paper describes the CACAPO dataset, built for training both neural pipeline and end-to-end data-to-text language generation systems. The dataset is multilingual (Dutch and English), and contains almost 10,000 sentences from human-written news texts in the sports, weather, stocks, and incidents domain, together with aligned attribute-value paired data. The dataset is unique in that the linguistic variation and indirect ways of expressing data in these texts reflect the challenges of real world NLG tasks.
Original language | English |
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Title of host publication | Proceedings of The 13th International Conference on Natural Language Generation |
Place of Publication | Dublin, Ireland |
Pages | 68-79 |
Number of pages | 15 |
Publication status | Published - 1 Dec 2020 |
Event | International Conference on Natural Language Generation - online, Dublin , Ireland Duration: 15 Dec 2020 → 18 Dec 2020 Conference number: 13 https://www.inlg2020.org/ |
Conference
Conference | International Conference on Natural Language Generation |
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Abbreviated title | INLG 2020 |
Country/Territory | Ireland |
City | Dublin |
Period | 15/12/20 → 18/12/20 |
Internet address |
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CACAPO dataset
van der Lee, C. (Creator), Emmery, C. (Creator), Wubben, S. (Creator) & Krahmer, E. (Creator), DataverseNL, 2 Aug 2022
DOI: 10.34894/libyhp, https://dataverse.nl/citation?persistentId=doi:10.34894/LIBYHP
Dataset