Furthermore, the gain brought by PAS DM (T.PARSER+features, this paper) 92.11 89.70 (Du et al., 2014) 92.04 89.40 (Martins andAlmeida, 2014) 91.76 89.16 (DSR, this paper) 90.13 85.66    the second-order features is reduced by half when used jointly with our feature set (+1.09 vs +0.57 with them).
although we could assess that the need of second order models is thus alleviated, the conjunction of both types of features still improves the parser performance by an overall gain of 1.62 points on DM (1.18 on PAS), suggesting that both feature sets contribute to different types of "structures".