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Table 7 Efficiency test results. The numbers of parameters and states indicate the model’s size. The elapsed training/inference times indicate the model’s speed. (shaded: pi-CRF)

From: Precursor-induced conditional random fields: connecting separate entities by induction for improved clinical named entity recognition

Data

Model

Parameter

State

Elapsed training time (sec)

Training time per iteration (sec)

Elapsed

inference time (sec)

i2b2

1st-order CRF

442,705

8

1,550

12.5

1.7

2nd-order CRF

581,604

64

6,819

55.4

5.7

pi-CRF

442,768

11

3,751

17.0

2.1

SNUH

1st-order CRF

396,245

12

2,946

19.5

1.9

2nd-order CRF

495,772

144

27,388

139.7

9.3

pi-CRF

396,400

17

6,231

23.6

2.1

CoNLL

1st-order CRF

313,672

10

4,031

19.1

0.6

2nd-order CRF

431,044

100

24,828

173.6

2.6

pi-CRF

313,776

14

13,512

29.4

0.7