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Table 5 Effects of different parameter settings of word embedding dimensions

From: SBLC: a hybrid model for disease named entity recognition based on semantic bidirectional LSTMs and conditional random fields

 

Dimensions

Precision

Recall

F1

Word embeddings

50

0.816

0.737

0.774

100

0.834

0.750

0.790

150

0.859

0.686

0.763

200

0.866

0.858

0.862

  1. The highest values are denoted in bold type