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Table 3 CEM 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

85.59

72.74

78.64

88.2

80.74

84.31

Baseline

84.40

77.34

80.71

79.81

63.16

70.51

Baseline + Brown 300

84.6

78.47

81.42

88.67

81.17

84.75

Baseline + Brown 1000

84.6

79.34

81.89

88.71

81.39

84.89

Baseline + Brown 1000 + WVC 1000

85.25

80.3

82.7

88.79

81.45

84.96

Baseline + Brown 1000 + Brown 300

84.76

79.46

82.03

89.1

81.54

85.2

Baseline + Brown 1000 + WVC 300

84.98

80.07

82.45

88.65

82.13

85.26

Baseline + Brown 1000 + WVC 500

85.32

79.92

82.53

88.77

82.42

85.48

Baseline + Brown 1000 + WVC 500 + WVC 300

85.58

80.1

82.75

88.57

82.6

85.48

Baseline + Brown 1000 + WVC 500 + WVC 1000

85.28

80.28

82.7

88.8

82.6

85.59

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

84.89

80.35

82.56

88.9

82.68

85.68

  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.