Abstract This study uses an error-annotated, mass-media subset of a sentence-aligned, multi-parallel learner translator corpus to reveal source-language items that are challenging in English–Russian translation. Our data includes multiple translations the most source sentences, drawn from large collection student on basis error statistics. sample was subjected manual contrastive-comparative ana...