In addition,<cite> (Wieting et al. 2016)</cite> found that the sum of character n-gram embeddings also outperformed word embeddings constructed from character embeddings with CNN and LSTM. As an encoder, previous studies argued that additive composition, which computes the (weighted) sum of embeddings, is a suitable method theoretically (Tian, Okazaki, and Inui 2016) and empirically (Muraoka et al. 2014; . In this paper, we used multidimensional self-attention to construct word embeddings because it can be interpreted as an element-wise weighted sum.