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Analysing Data-To-Text Generation Benchmarks
Abstract : A generation system can only be as good as the data it is trained on. In this short paper , we propose a methodology for analysing data-to-text corpora used for training micro-planner i.e., systems which given some input must produce a text verbalising exactly this input. We apply this methodology to three existing benchmarks and we elicite a set of criteria for the creation of a data-to-text benchmark which could help better support the development , evaluation and comparison of linguistically sophisticated data-to-text generators.
Cited literature [14 references]
https://hal.inria.fr/hal-01623832
Contributor : Claire Gardent <>
Submitted on : Wednesday, October 25, 2017 - 5:01:35 PM
Last modification on : Tuesday, December 18, 2018 - 4:38:02 PM
Document(s) archivé(s) le : Friday, January 26, 2018 - 3:13:02 PM
Contributor : Claire Gardent <>
Submitted on : Wednesday, October 25, 2017 - 5:01:35 PM
Last modification on : Tuesday, December 18, 2018 - 4:38:02 PM
Document(s) archivé(s) le : Friday, January 26, 2018 - 3:13:02 PM
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d2tDatasetAnalysis.pdf
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