We observe a severe under-reporting of the different kinds of errors that Natural Language Generation systems make. This is a problem, because mistakes are an important indicator of where systems should still be improved. If authors only report overall performance metrics, the research community is left in the dark about the specific weaknesses that are exhibited by `state-of-the-art' research. Next to quantifying the extent of error under-reporting, this position paper provides recommendations for error identification, analysis and reporting.
|Title of host publication||Proceedings of the 14th International Conference on Natural Language Generation|
|Place of Publication||Aberdeen, Scotland, UK|
|Publisher||Association for Computational Linguistics|
|Number of pages||14|
|Publication status||Published - 1 Aug 2021|