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We propose a new method for evaluating the readability of simplifiedsentences through pair-wise ranking. The validity of the method is establishedthrough in-corpus and cross-corpus evaluation experiments. The approachcorrectly identifies the ranking of simplified and unsimplified sentences interms of their reading level with an accuracy of over 80%, significantlyoutperforming previous results. To gain qualitative insights into the nature ofsimplification at the sentence level, we studied the impact of specificlinguistic features. We empirically confirm that both word-level and syntacticfeatures play a role in comparing the degree of simplification of authenticdata. To carry out this research, we created a new sentence-aligned corpus fromprofessionally simplified news articles. The new corpus resource enriches theempirical basis of sentence-level simplification research, which so far reliedon a single resource. Most importantly, it facilitates cross-corpus evaluationfor simplification, a key step towards generalizable results.

Readability-based Sentence Ranking for Evaluating Text Simplification