Following Marcheggiani and Titov (2017), we focus on argument labeling and formulate SRL as sequence labeling problem.
we differ by (1) leveraging enhanced word representation, (2) applying recent advances in recurrent neural networks (RNNs), such as highway connections (Srivastava et al., 2015), (3) using deep encoder with residual connections (He et al., 2016), (4) further extending Syntax Aware Long Short-Term Memory (SA-LSTM) (Qian et al., 2017) for SRL, and 5introducing the Tree-Structured Long Short-Term Memory (Tree-LSTM) (Tai et al., 2015) to model syntactic information for SRL.