datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
wmt-da-human-evaluation
Dataset Summary
This dataset contains all DA human annotations from previous WMT News Translation shared tasks.
The data is organised into 8 columns:
lp: language pair
src: input text
mt: translation
ref: reference translation
score: z score
raw: direct assessment
annotators: number of annotators
domain: domain of the input text (e.g. news)
year: collection year
You can also find the original data for each year in the results section https://www.statmt.org/wmt{YEAR}/results.html… See the full description on the dataset page: https://huggingface.co/datasets/RicardoRei/wmt-da-human-evaluation.wmt-mqm-human-evaluation
Dataset Summary
This dataset contains all MQM human annotations from previous WMT Metrics shared tasks and the MQM annotations from Experts, Errors, and Context.
The data is organised into 8 columns:
lp: language pair
src: input text
mt: translation
ref: reference translation
score: MQM score
system: MT Engine that produced the translation
annotators: number of annotators
domain: domain of the input text (e.g. news)
year: collection year
You can also find the original data here.… See the full description on the dataset page: https://huggingface.co/datasets/RicardoRei/wmt-mqm-human-evaluation.wmt-sqm-human-evaluation
Dataset Summary
In 2022, several changes were made to the annotation procedure used in the WMT Translation task. In contrast to the standard DA (sliding scale from 0-100) used in previous years, in 2022 annotators performed DA+SQM (Direct Assessment + Scalar Quality Metric). In DA+SQM, the annotators still provide a raw score between 0 and 100, but also are presented with seven labeled tick marks. DA+SQM helps to stabilize scores across annotators (as compared to DA).
The data is… See the full description on the dataset page: https://huggingface.co/datasets/RicardoRei/wmt-sqm-human-evaluation.