Table 1.
BL |
VD |
||||
---|---|---|---|---|---|
Entity | Corpus | Average | σ | Average | σ |
Chemicals | BC4CHEMD | 88.46 | 0.61 | 88.71 | 0.76 |
BC5CDR | 92.82 | 0.80 | 93.08 | 0.82 | |
CRAFT | 84.98 | 1.98 | 85.22 | 1.37 | |
Disease | BC5CDR | 84.49 | 0.33 | 85.10 | 0.56 |
NCBI-disease | 87.01 | 1.17 | 87.60 | 1.50 | |
Variome | 85.75 | 2.83 | 85.69 | 3.81 | |
Species | CRAFT | 96.28 | 2.21 | 96.38 | 2.26 |
Linnaeus | 89.44 | 3.91 | 89.66 | 7.47 | |
S800 | 72.75 | 2.42 | 77.39 | 4.17 | |
Genes/proteins | BC2GM | 81.48 | 0.48 | 83.10 ** | 0.50 |
CRAFT | 84.46 | 6.08 | 86.09 | 5.19 | |
JNLPBA | 80.92 | 2.50 | 81.95 | 2.62 |
Note: In the BL model, dropout is applied only to the character-enhanced word embeddings. In the VD model, dropout is additionally applied to the input, recurrent and output connections of all LSTM layers. IC performance is derived from 5-fold cross-validation, using exact matching criteria. Statistical significance is measured through a two-tailed t-test. Bold, best scores, σ, standard deviation.
Significantly different than the BL (P ≤ 0.01).