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Table 7 
Results using the best neural model with and without induced covering grammars. “+ CG decoding”: covering grammar used during decoding; “+ CG training”: covering grammar used during training and decoding. *: difference is statistically significant (p < .05 on the McNemar test) in comparison with the baseline model without CG.
 Accuracy (Error)
AllSemiotic classSentence
English (Standard): 
 Best model 99.84% (0.16%) 98.30% (1.70%) 98.20% (1.80%) 
 + CG decoding 99.84% (0.16%) 98.36% (1.64%) 98.24% (1.76%) 
 + CG training 99.84% (0.16%) 98.56% (1.44%)98.17% (1.83%) 
  
English (Kaggle): 
 Best model 99.17% (0.83%) 90.08% (9.92%) 89.58% (10.42%) 
 + CG decoding 99.22% (0.78%)90.69% (9.31%)* 90.09% (9.91%) 
 + CG training 99.20% (0.80%)* 90.71% (9.29%)89.87% (10.13%) 
  
Russian (Standard): 
 Best model 99.65% (0.35%) 97.17% (2.83%) 95.62% (4.38%) 
 + CG decoding 99.64% (0.36%) 97.19% (2.81%) 95.58% (4.42%) 
 + CG training 99.62% (0.38%) 97.01% (2.99%) 95.26% (4.74) 
  
Russian (Kaggle): 
 Best model 99.01% (0.99%) 94.09% (5.91%) 89.02% (10.98%) 
 + CG decoding 99.01% (0.99%)94.12% (5.88%)* 89.03% (10.97%) 
 + CG training 98.94% (1.06%)* 94.17% (5.83%)88.13% (11.87%) 
 Accuracy (Error)
AllSemiotic classSentence
English (Standard): 
 Best model 99.84% (0.16%) 98.30% (1.70%) 98.20% (1.80%) 
 + CG decoding 99.84% (0.16%) 98.36% (1.64%) 98.24% (1.76%) 
 + CG training 99.84% (0.16%) 98.56% (1.44%)98.17% (1.83%) 
  
English (Kaggle): 
 Best model 99.17% (0.83%) 90.08% (9.92%) 89.58% (10.42%) 
 + CG decoding 99.22% (0.78%)90.69% (9.31%)* 90.09% (9.91%) 
 + CG training 99.20% (0.80%)* 90.71% (9.29%)89.87% (10.13%) 
  
Russian (Standard): 
 Best model 99.65% (0.35%) 97.17% (2.83%) 95.62% (4.38%) 
 + CG decoding 99.64% (0.36%) 97.19% (2.81%) 95.58% (4.42%) 
 + CG training 99.62% (0.38%) 97.01% (2.99%) 95.26% (4.74) 
  
Russian (Kaggle): 
 Best model 99.01% (0.99%) 94.09% (5.91%) 89.02% (10.98%) 
 + CG decoding 99.01% (0.99%)94.12% (5.88%)* 89.03% (10.97%) 
 + CG training 98.94% (1.06%)* 94.17% (5.83%)88.13% (11.87%) 
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