Skip to main content

Advertisement

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.