Following previous works that used supervised machine learning for ranking in lexical simplification<cite> (Horn et al., 2014</cite>; Paetzold and Specia, 2017) , we train the DSSM using the LexMTurk dataset<cite> (Horn et al., 2014)</cite> , which contains 500 instances composed of a sentence, a target word and substitution candidates ranked by simplicity (Paetzold and Specia, 2017) .