## 4 Experiments and Analysis
### Main Results
\begin{table}
\begin{tabular}{c c c c c c c c c c c c c} \hline \hline  & \multicolumn{3}{c}{**14 res**} & \multicolumn{3}{c}{**14 lap**} & \multicolumn{3}{c}{**15 res**} & \multicolumn{3}{c}{**16 res**} \\  & \multicolumn{1}{c}{\(P\)} & \multicolumn{1}{c}{\(R\)} & \multicolumn{1}{c}{\(F1\)} & \multicolumn{1}{c}{\(P\)} & \multicolumn{1}{c}{\(R\)} & \multicolumn{1}{c}{\(F1\)} & \multicolumn{1}{c}{\(P\)} & \multicolumn{1}{c}{\(R\)} & \multicolumn{1}{c}{\(F1\)} & \multicolumn{1}{c}{\(P\)} & \multicolumn{1}{c}{\(R\)} & \multicolumn{1}{c}{\(F1\)} \\ \hline \multirow{8}{*}{\(D_{1}\)} & Peng-two-stage + IOG & 58.89 & 60.41 & 59.64 & 48.62 & 45.52 & 47.02 & 51.70 & 46.04 & 48.71 & 59.25 & 58.09 & 58.67 \\  & GTS-CNN & 70.79 & 61.71 & 65.94 & 55.93 & 47.52 & 51.38 & 60.09 & 53.57 & 56.64 & 62.63 & 66.98 & 64.73 \\  & GTS-BiLSTM & 67.28 & 61.91 & 64.49 & 59.42 & 45.13 & 51.30 & 63.26 & 50.71 & 56.29 & 66.07 & 65.05 & 65.56 \\  & Dual-MRC & 71.55 & 69.14 & 70.32 & 57.39 & 53.88 & 55.58 & 63.78 & 51.87 & 57.21 & 68.60 & 66.24 & 67.40 \\  & IMN + IOG & 59.57 & 63.88 & 61.65 & 49.21 & 46.23 & 47.68 & 55.24 & 52.33 & 53.75 & - & - & - \\  & EMC-GCN & 71.15 & 72.29 & 71.71 & 56.55 & 57.06 & 56.80 & 59.21 & 58.01 & 58.61 & 67.98 & 69.41 & 68.69 \\ \cline{2-11}  & BiLSTM-BGAT-GCN & 73.70 & 73.02 & **73.36** & 62.26 & 54.38 & **58.05** & 52.98 & 65.57 & **58.61** & 66.85 & 71.60 & **69.14** \\ \hline \multirow{8}{*}{\(D_{2}\)} & CMLA & 39.18 & 47.13 & 42.79 & 30.09 & 36.92 & 33.16 & 34.56 & 39.84 & 37.01 & 41.34 & 42.10 & 41.72 \\  & RINANTE & 31.42 & 39.38 & 34.95 & 21.71 & 18.66 & 20.07 & 29.88 & 30.06 & 29.97 & 25.68 & 22.30 & 23.87 \\  & Li-unified-R & 41.04 & 67.35 & 51.00 & 40.56 & 44.28 & 42.34 & 44.72 & 51.39 & 47.82 & 37.33 & 54.51 & 44.31 \\  & Peng-two-stage & 43.24 & 63.66 & 51.46 & 37.38 & 50.38 & 42.87 & 48.07 & 57.51 & 52.32 & 46.96 & 64.24 & 54.21 \\  & OTE-MTL & 62.00 & 55.97 & 58.71 & 49.53 & 39.22 & 43.42 & 56.37 & 40.94 & 47.13 & 62.88 & 52.10 & 56.96 \\  & JET-BERT & 70.56 & 55.94 & 62.40 & 55.39 & 47.33 & 51.04 & 64.45 & 51.96 & 57.53 & 70.42 & 58.37 & 63.83 \\  & BMRC & 75.61 & 61.77 & 67.99 & 70.55 & 48.98 & 57.82 & 68.51 & 53.40 & 60.02 & 71.20 & 61.08 & 65.75 \\  & EMC-GCN & 67.40 & 72.33 & 69.77 & 57.00 & 54.90 & 55.60 & 64.01 & 61.24 & **62.59** & 63.93 & 68.42 & 66.10 \\ \cline{2-11}  & BiLSTM-BGAT-GCN & 73.00 & 70.15 & **71.55** & 61.36 & 60.31 & **60.83** & 55.52 & 62.53 & 58.81 & 61.29 & 71.91 & **66.18** \\ \hline \multirow{8}{*}{\(D_{2}\)} & BGAT-GCN & 66.64 & 73.96 & 70.11 & 61.67 & 58.60 & 60.10 & 51.76 & 66.60 & 58.25 & 63.71 & 71.54 & 67.40 \\  & BiLSTM-BGAT-GCN & 73.00 & 70.15 & **71.55** & 61.36 & 60.31 & **60.83** & 55.52 & 62.53 & **58.81** & 61.29 & 71.91 & **66.18** \\ \cline{1-1} \cline{2-11}  & **Model** & \multicolumn{1}{c}{**14 res**} & \multicolumn{1}{c}{**14 lap**} & \multicolumn{3}{c}{**15 res**} & \multicolumn{3}{c}{**16 res**} \\  & \multicolumn{1}{c}{\(P\)} & \multicolumn{1}{c}{\(R\)} & \multicolumn{1}{c}{\(F1\)} & \multicolumn{1}{c}{\(P\)} & \multicolumn{1}{c}{\(R\)} & \multicolumn{1}{c}{\(F1\)} & \multicolumn{1}{c}{\(P\)} & \multicolumn{1}{c}{\(R\)} & \multicolumn{1}{c}{\(F1\)} & \multicolumn{1}{c}{\(P\)} & \multicolumn{1}{c}{\(R\)} & \multicolumn{1}{c}{\(F1\)} \\ \hline \multirow{2}{*}{\(D_{1}\)} & BGAT-GCN & 72.11 & 72.70 & 72.40 & 56.96 & 57.80 & 57.38 & 55.74 & 61.06 & 58.28 & 65.05 & 71.89 & 68.30 \\  & BiLSTM-BGAT-GCN & 73.70 & 73.02 & **73.36** & 62.26 & 54.38 & **58.05** & 52.98 & 65.57 & **58.61** & 66.85 & 71.60 & **69.14** \\ \hline \multirow{2}{*}{\(D_{2}\)} & BGAT-GCN & 66.64 & 73.96 & 70.11 & 61.67 & 58.60 & 60.10 & 51.76 & 66.60 & 58.25 &To delve deeper into the influence of each linguistic feature on our task, we carefully selected a sentence sample and depicted the distribution of attention weights across each word, as exemplified in Figure 11. This figure intricately displays each row as the visualization derived from the GCN for every distinct linguistic feature, while every column unravels the intricacies of how a word is interpreted across the four linguistic features.