Following the experimental settings and evaluation metrics in Bai and Zhao (2018), we use two most-used splitting methods of PDTB data, denoted as PDTB-Lin (Lin et al., 2009), which uses sections 2-21, 22, 23 as training, validation and test sets, and PDTB-Ji (Ji and Eisenstein, 2015), which uses 2-20, 0-1, 21-22 as training, validation and test sets and report the overall accuracy score.
these models typically use pre-trained semantic embeddings generated from language modeling tasks, like Word2Vec (Mikolov et al., 2013), GloVe (Pennington et al., 2014) and ELMo (Peters et al., 2018).