We note that our modular framework can easily maintain purely sense-level tokens with an arbitrary representation learning model.
most related work using probabilistic modeling (Tian et al., 2014;Jauhar et al., 2015;Li and Jurafsky, 2015;Bartunov et al., 2016) binded sense representations with the sense selection mechanism, so efficient sense selection by leveraging wordlevel tokens can be achieved only at the cost of mixing word-level and sense-level tokens in their representation learning process.