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