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Table 8 Comparison with previous systems of CDR extraction

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

Method

System

P (%)

R (%)

F (%)

without KBs

Feature-based

Gu et al. [6]

62.00

55.10

58.30

Neural network-based

Nguyen et al. [13]

57.00

68.60

62.30

Le et al. [14]

58.02

76.20

65.88

Verga et al. [15]

55.60

70.80

62.10

with KBs

Feature-based

Pons et al. [9]

73.10

67.60

70.20

Peng et al. [10]

68.15

66.04

67.08

Peng et al. [10]

71.07

72.61

71.83

Neural network-based

Li et al. [16]

59.97

81.49

69.09

Zhou et al. [17]

60.51

80.48

69.08

Ours

69.65

72.98

71.28

Ours

72.12

68.67

70.35

  1. The descriptions and analysis for Table 8 could be found in subsection “Comparison with previous works”. The marker indicates that the system uses additional weakly labeled data for training. The highest F1-score of each subgroup is highlighted in bold