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Table 5 The effectiveness of domain-specific contextual word representation according to the mean F1 scores of 30 different random seeds

From: Relation extraction between bacteria and biotopes from biomedical texts with attention mechanisms and domain-specific contextual representations

Pre-trained word model

F1 score

 

Mean

SD

Min

Max

PubMed word2vec

53.42

2.51

46.67

56.70

general-purpose ELMo

54.30

3.61

42.76

56.51

random-PubMed ELMo

53.81

3.65

38.89

57.01

specific-PubMed ELMo

55.91

1.49

51.24

57.48

  1. All of the highest scores are highlighted in bold except for the SD. The first-row results derive from the best results of previous experiments (i.e., the last row in Table 4). Note: “PubMed word2vec” denotes the context-free word model, “general-purpose ELMo” denotes the general-purpose contextual word model, “random-PubMed ELMo” denotes the domain-general contextual word model based on 118 million randomly selected tokens abstracts from PubMed, and “specific-PubMed ELMo” denotes the domain-specific contextual word model based on 118 million bacterial-relevant abstracts from PubMed