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View in-depth performance of a single language model on a single test suite.

Region-by-region surprisal
Sample item for Cleft Structure
Item
Condition
intro subj verb passive verb.1 matrix_v
Item Condition intro subj verb passive verb.1 matrix_v
1 np_mismatch What he did was the meal
1 np_match What he ate was the meal
1 vp_match What he did was prepare the meal
1 vp_mismatch What he ate was prepare the meal
Prediction performance for Vanilla LSTM on Cleft Structure
Accuracy
Formula
Description
AccuracyPredictionDescription
67.50% ((547,np_mismatch/6,matrix_v)-(545,np_match/6,matrix_v))+(((546,vp_mismatch/5,verb.1)+(546,vp_mismatch/6,matrix_v))-((548,vp_match/5,verb.1)+(548,vp_match/6,matrix_v)))>0 We expect that the Matrix Verb has lower surprisal in the NP Match condition, where we have a lexicalized verb (“ate” instead of “did”). In addition, we expect that the sum of the Verb 1 + Matrix Verb has lower surprisal in the VP Match condition, where it cannot be the object of a lexicalized verb such as “ate.” Together, the differences between these sums should be greater than zero.