gsarti/qe4pe
Quality Estimation for Post-Editing (QE4PE) For more details on QE4PE, see our paper and our Github repository Gabriele Sarti • Vilém Zouhar • Grzegorz Chrupała • Ana Guerberof Arenas • Malvina Nissim • Arianna Bisazza Word-level quality estimation (QE) detects erroneous spans in machine translations, which can direct and facilitate human post-editing. While the accuracy of word-level QE systems has been assessed extensively, their usability and downstream influence on… See the full description on the dataset page: https://huggingface.co/datasets/gsarti/qe4pe.
Add has_issue column
Add oracle pe dataframe
Minimal fixes to mt_text
Update README.md
Update README.md
Link paper to HF papers URL (#3)
Update README.md
Added WMT preprocessing and raw highlight outputs
Update questionnaires order
Fix readme
Remove old files
Add QA setup folder
Corrected MQM annotations
Added MQM fields
Fix critical tags
Add critical error tags and highlight proportions
Tag entries with issues from config
Added posttask
Fix oracle_t4 -> no_highlight_t4 for t13 nld
Added processing config
Add readme example
Add questionnaires configs
Added processed dataframes
Added metrics output files
Added oracle_t4, minor formatting fixes
Fix readme
Add t13 and readme draft
Added questionnaires data
Main task outputs complete
Main task almost finished
Add main task inputs and logs
Add WMT23 files
Fix tables
Add pretask files
Add task example
initial commit