E2E Refined Dataset
This work addresses data quality issues for researchers in natural language generation, but it is incremental as it focuses on error correction rather than new methods.
The researchers tackled the problem of errors in the MR-to-text E2E dataset by developing a refined version and tools to convert the original dataset, aiming to improve the quality of MR-to-text systems.
Although the well-known MR-to-text E2E dataset has been used by many researchers, its MR-text pairs include many deletion/insertion/substitution errors. Since such errors affect the quality of MR-to-text systems, they must be fixed as much as possible. Therefore, we developed a refined dataset and some python programs that convert the original E2E dataset into a refined dataset.