Following standard practices for applying neural architectures to NLP tasks, we initialize our network with word embeddings trained on orders of magnitude more data than is available for our task (SRL).
we use publicly available GloVe 100-dimensional vectors trained on 6 billion words from Wikipedia and Gigaword (Pennington et al., 2014).