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Table 2 CDI subtask evaluation results of different runs with varied features.

From: Incorporating domain knowledge in chemical and biomedical named entity recognition with word representations

 

Development set

Testing set

Features

Pre

Rec

F-scr

Pre

Rec

F-scr

BANNER setup

82.83

78.71

80.72

85.36

85.29

85.32

Baseline

81.71

82.3

82

75.87

70.55

73.11

Baseline + Brown 300

82.2

82.96

82.58

86.03

85.45

85.74

Baseline + Brown 1000

81.96

83.24

82.59

86.04

85.60

85.82

Baseline + Brown 1000 + WVC 1000

82.73

83.89

83.31

86.23

85.37

85.8

Baseline + Brown 1000 + Brown 300

82.1

83.42

82.76

86.46

85.63

86.04

Baseline + Brown 1000 + WVC 300

82.43

83.82

83.12

86.06

86.06

86.06

Baseline + Brown 1000 + WVC 500

82.78

83.56

83.17

86.12

86.2

86.16

Baseline + Brown 1000 + WVC 500 + WVC 300

83.1

83.78

83.44

86.10

86.31

86.2

Baseline + Brown 1000 + WVC 500 + WVC 1000

82.78

83.76

83.27

86.19

86.4

86.28

Baseline + Brown 1000 + WVC 500 + WVC 300 + WVC 1000

82.3

84.05

83.16

86.47

86.47

86.47

  1. Feature groups are separated by (+). The parameters followed Brown and WVC are the number of classes induced in each model. Pre: Precision, Rec: Recall, F-scr: F-score.