Shared task on quality assessment for text simplification
Sanja Štajner, Maja Popović, Horacio Saggion, Lucia Specia, Mark Fishel · 2016
This paper presents the results of the shared task of the Workshop on Quality Assessment for Text Simplification (QATS), which consisted in automatically assigning one of the three labels (good, ok, and bad) for each of the four aspects of automatically simplified English sentences, i.e. their grammaticality, meaning preservation, simplicity, and overall quality. We asked participants to submit a maximum of three systems (raw metrics and/or classifiers) for each aspect. We received a total of 10 raw metrics and 16 classifiers for each of the four aspects. In addition to that, we computed correlations for four standard MT metrics (BLEU, METEOR, TER and WER) as baselines. The collected scores were evaluated by Pearson correlation (how well each score metric correlates with the manually assigned values) and the classifiers were evaluated in terms of their accuracy, mean average error, root squared mean error and weighted F-scores.