Specifically, we use the following features: 1) the stack embedding d t which encodes the stack of the decoder and is obtained with a stack-LSTM (Dyer et al., 2015 <cite>(Dyer et al., , 2016</cite> ; 2) the output buffer embedding o t ; we use a standard LSTM to compose the output buffer and o t is represented as the most recent state of the LSTM; and 3) the parent non-terminal embedding n t which is accessible in the generative model because the RNNG employs a depth-first generation order.