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Table 3 Performance comparison of the different pruning approaches and the baseline methods (TEES/EVEX) on the official BioNLP Shared Task GE data sets

From: Filtering large-scale event collections using a combination of supervised and unsupervised learning for event trigger classification

 

Predictions

Precision

Recall

F1-score

TEES-2011 (Shared Task 2011)

Original TEES

61.76

48.78

54.51

 

Pruned-TEES (Unsupervised Method)

62.39

48.75

54.74

 

Pruned-TEES (Manual Annotation Method)

62.04

48.78

54.62

 

Pruned-TEES (Aggregation Method)

62.26

48.78

54.70

 

Pruned-TEES (Aggregation Method + SVM)

62.27

48.78

54.71

TEES-2013 (Shared Task 2013)

Original TEES

56.32

46.17

50.74

 

Pruned-TEES (Unsupervised Method)

57.13

46.02

50.97

 

Pruned-TEES (Manual Annotation Method)

56.63

46.17

50.87

 

Pruned-TEES (Aggregation Method)

56.97

46.17

51.00

 

Pruned-TEES (Aggregation Method + SVM)

57.01

46.17

51.02

EVEX-2013 (Shared Task 2013)

Original EVEX

58.03

45.44

50.97

 

Pruned-EVEX (Unsupervised Method)

58.77

45.29

51.15

 

Pruned-EVEX (Manual Annotation Method)

58.32

45.44

51.08

 

Pruned-EVEX (Aggregation Method)

58.66

45.44

51.21

 

Pruned-EVEX (Aggregation Method + SVM)

58.71

45.44

51.23