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. 2019 Jun 20;36(1):280–286. doi: 10.1093/bioinformatics/btz504

Table 1.

In-corpus (IC) performance, measured by F1-score, of the baseline (BL) BiLSTM-CRF compared to a BiLSTM-CRF with variational dropout (VD)

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).