Improving Distant Supervised Relation Extraction by Dynamic Neural Network
Table 4: P@N comparison of proposed models with other methods. The best results are in bold font.
['P@N', 'PCNN+MIL', 'PCNN+ATT', 'RESIDE', 'PCNNs+WN', 'DNNRE']
The precision value of DNNRE outperforms others under almost all recall values. Especially, when recall ranges from 0.10 to 0.40, there is a consistent margin between DNNRE and other methods.