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Table 13 Performance of models learned from the CHEMDNER training set when evaluated on the development set.

From: Optimising chemical named entity recognition with pre-processing analytics, knowledge-rich features and heuristics

 

Macro

Micro

 

P

R

F1

P

R

F1

Default features

86.66

79.01

80.89

88.55

76.82

82.27

Enriched features

88.26

81.11

82.86

89.87

78.99

84.07

Margin

+1.6

+2.1

+1.97

+1.32

+2.17

+1.8