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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.