Abstract
In this paper we introduce a new lexical simplification approach. We extract over 30K candidate lexical simplifications by identifying aligned words in a sentence-aligned corpus of English Wikipedia with Simple English Wikipedia. To apply these rules, we learn a feature-based ranker using SVM rank 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. © 2014 Association for Computational Linguistics.
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CITATION STYLE
Horn, C., Manduca, C., & Kauchak, D. (2014). Learning a lexical simplifier using Wikipedia. In 52nd Annual Meeting of the Association for Computational Linguistics, ACL 2014 - Proceedings of the Conference (Vol. 2, pp. 458–463). Association for Computational Linguistics (ACL). https://doi.org/10.3115/v1/p14-2075
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