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Table 3 Impact of Unary-Network and Pairwise-Network in terms of the F1-score (%)

From: DTranNER: biomedical named entity recognition with deep learning-based label-label transition model

SettingsBC5CDR-ChemicalBC5CDR-DiseaseNCBI-Disease
Unary-CRF93.0186.1486.94
Pairwise-CRF93.2786.0586.71
Unary+Pairwise ensemble93.2586.7887.09
DTranNER94.1687.2288.62
  1. Note: “Unary-CRF” denotes a variant model excluding Pairwise-Network from DTranNER, “Pairwise-CRF” denotes a variant model excluding Unary-Network from DTranNER, and “Unary+Pairwise ensemble” is an ensemble model of “Unary-CRF” and “Pairwise-CRF.” In the ensemble model, “Unary-CRF” and “Pairwise-CRF” were independently trained, and they voted over the sequence predictions by their prediction scores