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Table 5 Effects of each component of architecture on performance on the CDR dataset

From: Knowledge-guided convolutional networks for chemical-disease relation extraction

Method

Intra-sentence level

Inter-sentence level

Document level

P (%)

R (%)

F (%)

P (%)

R (%)

F (%)

P (%)

R (%)

F (%)

KCN

70.61

60.41

65.12

65.37

12.57

21.09

69.65

72.98

71.28

w/o GTRU

67.71

60.60

63.96

60.95

9.66

16.68††

66.70

70.26

68.43††

w/o Att

63.37

52.25

57.28††

42.55

9.38

15.37††

58.98

61.63

60.28††

  1. The descriptions and analysis for Table 5 could be found in subsection “Effects of architecture”. The marker and †† represent P-value < 0.05 and P-value < 0.01, respectively, using pairwise t-test against KCN. The highest scores are highlighted in bold