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metrics.txt
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metrics.txt
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NER FINAL MODEL
> Nov_20_examples.txt
=============== Class: Person ===============
tp, fp, fn counts: [87, 13, 6]
Precision: 0.87
Recall: 0.9354838709677419
F1 score: 0.9015544041450777
=============== Class: Rank ===============
tp, fp, fn counts: [80, 14, 11]
Precision: 0.851063829787234
Recall: 0.8791208791208791
F1 score: 0.8648648648648649
=============== Class: Organization ===============
tp, fp, fn counts: [103, 33, 31]
Precision: 0.7573529411764706
Recall: 0.7686567164179104
F1 score: 0.762962962962963
=============== Class: Title_Role ===============
tp, fp, fn counts: [85, 20, 23]
Precision: 0.8095238095238095
Recall: 0.7870370370370371
F1 score: 0.7981220657276995
=============== All classes ===============
Precision: 0.8160919540229885
Recall: 0.8333333333333334
F1 score: 0.8246225319396051
RE: nearest person
Precision: 0.5667808219178082
993 / 1752
Recall: 0.701271186440678
993 / 1416
F1 score: 0.6268939393939393
RE: shortest path in dep parse tree
Precision: 0.6245674740484429
1083 / 1734
Recall: 0.7648305084745762
1083 / 1416
RE: shortest path in dep parse tree w/ constraint
Precision: 0.6785508913168488
1180 / 1739
Recall: 0.8333333333333334
1180 / 1416
F1 score: 0.7480190174326466
RE: neural networks
Precision: 0.6195094124358242
1086 / 1753
Recall: 0.7669491525423728
1086 / 1416
F1 score: 0.6853897128431682
RE: neural networks w/ constraint
Precision: 0.7102382485511912
1103 / 1553
Recall: 0.778954802259887
1103 / 1416
F1 score: 0.743011114853486