  Controllable text simplification is a crucial assistive technique for
language learning and teaching. One of the primary factors hindering its
advancement is the lack of a corpus annotated with sentence difficulty levels
based on language ability descriptions. To address this problem, we created the
CEFR-based Sentence Profile (CEFR-SP) corpus, containing 17k English sentences
annotated with the levels based on the Common European Framework of Reference
for Languages assigned by English-education professionals. In addition, we
propose a sentence-level assessment model to handle unbalanced level
distribution because the most basic and highly proficient sentences are
naturally scarce. In the experiments in this study, our method achieved a
macro-F1 score of 84.5% in the level assessment, thus outperforming strong
baselines employed in readability assessment.

Computation and Language