Viewing test suite Cleft Structure
Reference
No reference provided.
Number of items
40
Models evaluated
88% (8/9)
Description
The pseudo-cleft construction involves (i) an extraction of a targeted constituent from a sentence and (ii) a constituent that provides the semantic contents of the targeted constituent and must match it in syntactic category, where (i) and (ii) are linked by the copula. The pseudo-cleft construction can target both NPs and VPs; in the latter case, the VP of the free relative becomes an inflected form of "do". This means that a free relative plus the copula can set up a requirement for the syntactic category that comes next. If the free relative clause has a "do" VP without a direct object, then the main-clause postcopular predicate can be a VP. Otherwise, the postcopular predicate must be an NP.
Items for cleft
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 |
2 | np_mismatch | What | the young man | did | was | the crops | |
2 | np_match | What | the young man | planted | was | the crops | |
2 | vp_match | What | the young man | did | was | plant | the crops |
2 | vp_mismatch | What | the young man | planted | was | plant | the crops |
3 | np_mismatch | What | the worker | did | was | the plane | |
3 | np_match | What | the worker | repaired | was | the plane | |
3 | vp_match | What | the worker | did | was | board | the plane |
3 | vp_mismatch | What | the worker | repaired | was | board | the plane |
4 | np_mismatch | What | the fan | did | was | the tickets | |
4 | np_match | What | the fan | sold | was | the tickets | |
4 | vp_match | What | the fan | did | was | buy | the tickets |
4 | vp_mismatch | What | the fan | sold | was | buy | the tickets |
5 | np_mismatch | What | the young woman | did | was | the toilet | |
5 | np_match | What | the young woman | wiped | was | the toilet | |
5 | vp_match | What | the young woman | did | was | flush | the toilet |
5 | vp_mismatch | What | the young woman | wiped | was | flush | the toilet |
6 | np_mismatch | What | the fans | did | was | the game | |
6 | np_match | What | the fans | watched | was | the game | |
6 | vp_match | What | the fans | did | was | lose | the game |
6 | vp_mismatch | What | the fans | watched | was | lose | the game |
7 | np_mismatch | What | the gardener | did | was | the tree | |
7 | np_match | What | the gardener | trimmed | was | the tree | |
7 | vp_match | What | the gardener | did | was | plant | the tree |
7 | vp_mismatch | What | the gardener | trimmed | was | plant | the tree |
8 | np_mismatch | What | the old man | did | was | the flag | |
8 | np_match | What | the old man | bought | was | the flag | |
8 | vp_match | What | the old man | did | was | raise | the flag |
8 | vp_mismatch | What | the old man | bought | was | raise | the flag |
9 | np_mismatch | What | the old man | did | was | the chicken | |
9 | np_match | What | the old man | cooked | was | the chicken | |
9 | vp_match | What | the old man | did | was | hunt | the chicken |
9 | vp_mismatch | What | the old man | cooked | was | hunt | the chicken |
10 | np_mismatch | What | the workers | did | was | the sidewalk | |
10 | np_match | What | the workers | walked down | was | the sidewalk | |
10 | vp_match | What | the workers | did | was | pave | the sidewalk |
10 | vp_mismatch | What | the workers | walked down | was | pave | the sidewalk |
11 | np_mismatch | Who | the mother | did | was | the baby | |
11 | np_match | Who | the mother | fed | was | the baby | |
11 | vp_match | Who | the mother | did | was | hug | the baby |
11 | vp_mismatch | Who | the mother | fed | was | hug | the baby |
12 | np_mismatch | What | the old woman | did | was | the apartment | |
12 | np_match | What | the old woman | bought | was | the apartment | |
12 | vp_match | What | the old woman | did | was | furnish | the apartment |
12 | vp_mismatch | What | the old woman | bought | was | furnish | the apartment |
13 | np_mismatch | What | the guards | did | was | the plot | |
13 | np_match | What | the guards | concocted | was | the plot | |
13 | vp_match | What | the guards | did | was | thwart | the plot |
13 | vp_mismatch | What | the guards | concocted | was | thwart | the plot |
14 | np_mismatch | What | the senator | did | was | the bill | |
14 | np_match | What | the senator | sponsored | was | the bill | |
14 | vp_match | What | the senator | did | was | veto | the bill |
14 | vp_mismatch | What | the senator | sponsored | was | veto | the bill |
15 | np_mismatch | What | the representatives | did | was | the law | |
15 | np_match | What | the representatives | wrote | was | the law | |
15 | vp_match | What | the representatives | did | was | repeal | the law |
15 | vp_mismatch | What | the representatives | wrote | was | repeal | the law |
16 | np_mismatch | What | the old woman | did | was | the cats | |
16 | np_match | What | the old woman | fed | was | the cats | |
16 | vp_match | What | the old woman | did | was | stroke | the cats |
16 | vp_mismatch | What | the old woman | fed | was | stroke | the cats |
17 | np_mismatch | What | the army | did | was | the country | |
17 | np_match | What | the army | loved | was | the country | |
17 | vp_match | What | the army | did | was | invade | the country |
17 | vp_mismatch | What | the army | loved | was | invade | the country |
18 | np_mismatch | Who | the soldier | did | was | the enemy | |
18 | np_match | Who | the soldier | battled | was | the enemy | |
18 | vp_match | Who | the soldier | did | was | attack | the enemy |
18 | vp_mismatch | Who | the soldier | battled | was | attack | the enemy |
19 | np_mismatch | What | the novelist | did | was | the book | |
19 | np_match | What | the novelist | wrote | was | the book | |
19 | vp_match | What | the novelist | did | was | borrow | the book |
19 | vp_mismatch | What | the novelist | wrote | was | borrow | the book |
20 | np_mismatch | What | the worker | did | was | the door | |
20 | np_match | What | the worker | installed | was | the door | |
20 | vp_match | What | the worker | did | was | lock | the door |
20 | vp_mismatch | What | the worker | installed | was | lock | the door |
21 | np_mismatch | What | the workers | did | was | the wall | |
21 | np_match | What | the workers | painted | was | the wall | |
21 | vp_match | What | the workers | did | was | reinforce | the wall |
21 | vp_mismatch | What | the workers | painted | was | reinforce | the wall |
22 | np_mismatch | What | the actor | did | was | the story | |
22 | np_match | What | the actor | wrote | was | the story | |
22 | vp_match | What | the actor | did | was | tell | the story |
22 | vp_mismatch | What | the actor | wrote | was | tell | the story |
23 | np_mismatch | What | the tourists | did | was | the destination | |
23 | np_match | What | the tourists | traveled towards | was | the destination | |
23 | vp_match | What | the tourists | did | was | reach | the destination |
23 | vp_mismatch | What | the tourists | traveled towards | was | reach | the destination |
24 | np_mismatch | What | the men | did | was | the city | |
24 | np_match | What | the men | repaired | was | the city | |
24 | vp_match | What | the men | did | was | defend | the city |
24 | vp_mismatch | What | the men | repaired | was | defend | the city |
25 | np_mismatch | What | he | did | was | the package | |
25 | np_match | What | he | sent | was | the package | |
25 | vp_match | What | he | did | was | deliver | the package |
25 | vp_mismatch | What | he | sent | was | deliver | the package |
26 | np_mismatch | What | she | did | was | the contract | |
26 | np_match | What | she | wrote | was | the contract | |
26 | vp_match | What | she | did | was | renew | the contract |
26 | vp_mismatch | What | she | wrote | was | renew | the contract |
27 | np_mismatch | What | he | did | was | the rumor | |
27 | np_match | What | he | spread | was | the rumor | |
27 | vp_match | What | he | did | was | confirm | the rumor |
27 | vp_mismatch | What | he | spread | was | confirm | the rumor |
28 | np_mismatch | Who | they | did | was | the politician | |
28 | np_match | Who | they | rebuked | was | the politician | |
28 | vp_match | Who | they | did | was | murder | the politician |
28 | vp_mismatch | Who | they | rebuked | was | murder | the politician |
29 | np_mismatch | Who | the police | did | was | the suspect | |
29 | np_match | Who | the police | caught | was | the suspect | |
29 | vp_match | Who | the police | did | was | monitor | the suspect |
29 | vp_mismatch | Who | the police | caught | was | monitor | the suspect |
30 | np_mismatch | What | the people | did | was | the trash | |
30 | np_match | What | the people | collected | was | the trash | |
30 | vp_match | What | the people | did | was | remove | the trash |
30 | vp_mismatch | What | the people | collected | was | remove | the trash |
31 | np_mismatch | What | the teacher | did | was | the subject | |
31 | np_match | What | the teacher | taught | was | the subject | |
31 | vp_match | What | the teacher | did | was | write about | the subject |
31 | vp_mismatch | What | the teacher | taught | was | write about | the subject |
32 | np_mismatch | What | they | did | was | the drugs | |
32 | np_match | What | they | bought | was | the drugs | |
32 | vp_match | What | they | did | was | transport | the drugs |
32 | vp_mismatch | What | they | bought | was | transport | the drugs |
33 | np_mismatch | Who | he | did | was | his friend | |
33 | np_match | Who | he | called | was | his friend | |
33 | vp_match | Who | he | did | was | hug | his friend |
33 | vp_mismatch | Who | he | called | was | hug | his friend |
34 | np_mismatch | What | she | did | was | the shipment | |
34 | np_match | What | she | bought | was | the shipment | |
34 | vp_match | What | she | did | was | transport | the shipment |
34 | vp_mismatch | What | she | bought | was | transport | the shipment |
35 | np_mismatch | What | we | did | was | the argument | |
35 | np_match | What | we | won | was | the argument | |
35 | vp_match | What | we | did | was | make | the argument |
35 | vp_mismatch | What | we | won | was | make | the argument |
36 | np_mismatch | Who | you | did | was | the worker | |
36 | np_match | Who | you | contracted | was | the worker | |
36 | vp_match | Who | you | did | was | hire | the worker |
36 | vp_mismatch | Who | you | contracted | was | hire | the worker |
37 | np_mismatch | What | he | did | was | a painting | |
37 | np_match | What | he | created | was | a painting | |
37 | vp_match | What | he | did | was | paint | a painting |
37 | vp_mismatch | What | he | created | was | paint | a painting |
38 | np_mismatch | What | the woman | did | was | the letter | |
38 | np_match | What | the woman | wrote | was | the letter | |
38 | vp_match | What | the woman | did | was | the letter | |
38 | vp_mismatch | What | the woman | wrote | was | the letter | |
39 | np_mismatch | What | the maid | did | was | the glass | |
39 | np_match | What | the maid | broke | was | the glass | |
39 | vp_match | What | the maid | did | was | empty | the glass |
39 | vp_mismatch | What | the maid | broke | was | empty | the glass |
40 | np_mismatch | Who | the judge | did | was | the criminal | |
40 | np_match | Who | the judge | accused | was | the criminal | |
40 | vp_match | Who | the judge | did | was | sentence | the criminal |
40 | vp_mismatch | Who | the judge | accused | was | sentence | the criminal |
Predictions for cleft
Formula
|
Description |
---|---|
Formula | Description |
((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. |
Results for cleft
Model | Prediction 1 accuracy | |
---|---|---|
Model | Prediction 1 accuracy | |
TinyLSTM | 67.50% | Visualize results |
GPT-2 | 100.00% | Visualize results |
GPT-2 XL | 100.00% | Visualize results |
JRNN | 100.00% | Visualize results |
Ordered Neurons | 100.00% | Visualize results |
RNNG | 85.00% | Visualize results |
Transformer XL | 95.00% | Visualize results |
Vanilla LSTM | 67.50% | Visualize results |