2 https://github.com/wanghm92/Sing_Par Neural networks have led to significant advance in the performance for dependency parsing, including transition-based parsing (Chen and Manning, 2014;Zhou et al., 2015;Weiss et al., 2015;Andor et al., 2016), and graph-based parsing (Kiperwasser and Goldberg, 2016;Dozat and Manning, 2017).
the biaffine attention method of Dozat and Manning (2017) uses deep bi-directional long short-term memory (bi-LSTM) networks for highorder non-linear feature extraction, producing the highest-performing graph-based English dependency parser.