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Results.txt
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Results.txt
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CRF_baseline.py classifier performance on CONLL data with 40000 sentences as training, rest as testing (26787)
precision recall f1-score support
B-geo 0.86 0.90 0.88 6194
B-gpe 0.96 0.95 0.95 2756
B-per 0.84 0.79 0.82 2784
I-geo 0.81 0.80 0.81 1142
B-org 0.78 0.73 0.75 3400
I-org 0.81 0.80 0.80 2880
B-tim 0.93 0.87 0.90 3431
B-art 0.21 0.08 0.12 75
I-art 0.21 0.15 0.17 41
I-per 0.86 0.88 0.87 2820
I-gpe 0.85 0.70 0.77 40
I-tim 0.85 0.76 0.80 1102
B-nat 0.63 0.47 0.54 36
B-eve 0.48 0.37 0.42 41
I-eve 0.18 0.11 0.14 35
I-nat 0.67 0.40 0.50 10
avg / total 0.85 0.84 0.85 26787
CRF_baseline.py classifier performance on CONLL data with 45000 sentences as training, rest as testing (9985)
precision recall f1-score support
B-geo 0.85 0.90 0.87 2255
B-gpe 0.95 0.94 0.95 998
B-per 0.83 0.80 0.82 1053
I-geo 0.79 0.78 0.79 417
B-org 0.79 0.71 0.75 1332
I-org 0.80 0.77 0.78 1065
B-tim 0.92 0.87 0.90 1290
B-art 0.21 0.09 0.12 34
I-art 0.07 0.05 0.06 21
I-per 0.85 0.90 0.87 1033
I-gpe 0.64 0.60 0.62 15
I-tim 0.84 0.78 0.81 420
B-nat 0.50 0.25 0.33 12
B-eve 0.40 0.33 0.36 18
I-eve 0.25 0.11 0.15 19
I-nat 0.00 0.00 0.00 3
avg / total 0.84 0.83 0.84 9985