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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