Our approach for word sense disambiguation measures the appropriateness of a word sense in a word context through a unified neural network that uses the same set of parameters for all the words and senses.
as shown in Figure 1, like the previous neural network-based methods (Raganato et al., 2017a; Luo et al., 2018b; Luo et al., 2018a), we use bidirectional LSTMs (bi-LSTMs) (Hochreiter and Schmidhuber, 1997) for encoding a word context, sense definitions and a prototype example sentence for each sense.