MIT Press

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)
	All	Semiotic class	Sentence
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)
	All	Semiotic class	Sentence
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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