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.
CITATION STYLE
van der Lee, C., Emmery, C., Wubben, S., & Krahmer, E. (2020). The CACAPO Dataset: A Multilingual, Multi-Domain Dataset for Neural Pipeline and End-to-End Data-to-Text Generation. In INLG 2020 - 13th International Conference on Natural Language Generation, Proceedings (pp. 68–79). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/2020.inlg-1.10
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