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Table 2 Performance of SSVMs and CRFs based NER systems when different features and tag representations were used.

From: Recognizing clinical entities in hospital discharge summaries using Structural Support Vector Machines with word representation features

Tags Features SSVMs - F(R/P)(%) CRFs - F(R/P)(%)
BIO Base 84.89(83.39/86.44) 84.62 (82.35/87.01)
  Base + Clustering 85.22(84.05/86.43) 85.16 (82.94/87.50)
  Base + Distributional 85.19(84.00/86.42) 85.12(82.80/87.58)
  Base + Clustering + Distributional 85.45(84.30/86.63) 85.31(83.19/87.54)
BIESO Base 85.42(83.60/87.31) 85.04(82.31/87.97)
  Base + Clustering 85.74(84.15/87.40) 85.59(83.16/88.16)
  Base + Distributional 85.74(84.16/87.38) 85.35(82.82/88.05)
  Base + Clustering + Distributional 85.82(84.31/87.38) 85.68(83.30/88.20)