Learning a Lexical Simplifier Using Wikipedia

Colby Horn, Cathryn Manduca, David Kauchak

Abstract: In this paper we introduce a new lexical simplification approach. We extract over 30K candidate lexical simplifications by identifying aligned words in a sentencealigned corpus of English Wikipedia with Simple English Wikipedia. To apply these rules, we learn a feature-based ranker using SVMrank trained on a set of labeled simplifications collected using Amazon’s Mechanical Turk. Using human simplifications for evaluation, we achieve a precision of 76% with changes in 86% of the examples.