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The CACAPO Dataset: A Multilingual, Multi-Domain Dataset for Neural Pipeline and End-to-End Data-to-Text Generation

Authors :
van der Lee, Chris
Emmery, Chris
Wubben, Sander
Krahmer, Emiel
Language, Communication and Cognition
Cognitive Science & AI
Source :
Proceedings of The 13th International Conference on Natural Language Generation, 68-79, STARTPAGE=68;ENDPAGE=79;TITLE=Proceedings of The 13th International Conference on Natural Language Generation
Publication Year :
2020

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.

Details

Language :
English
Database :
OpenAIRE
Journal :
Proceedings of The 13th International Conference on Natural Language Generation, 68-79, STARTPAGE=68;ENDPAGE=79;TITLE=Proceedings of The 13th International Conference on Natural Language Generation
Accession number :
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