Underreporting of errors in NLG output, and what to do about it

Research Output

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.

Date:

31 December 2021
Publication Status:

Published
Funders:

EPSRC Engineering and Physical Sciences Research Council

http://researchrepository.napier.ac.uk/output/2791216 <p>van Miltenburg, E., Clinciu, M., Dušek, O., Gkatzia, D., Inglis, S., Leppänen, L., …Wen, L. (2021). Underreporting of errors in NLG output, and what to do about it. In <i>Proceedings of the 14th International Conference on Natural Language Generation</i> (140-153)</p>

Citation

van Miltenburg, E., Clinciu, M., Dušek, O., Gkatzia, D., Inglis, S., Leppänen, L., …Wen, L. (2021). Underreporting of errors in NLG output, and what to do about it. In Proceedings of the 14th International Conference on Natural Language Generation (140-153)