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Test 1 · ★ · Tales of Adventure, Walter and the Wolf: Walter flees a "w…

So who was the big bad wolf, like, really?

Mova's choice: option 2 · The right answer: option 3 · wrong ✗ · What happens: be · To what, where: big bad wolf

This is test 1 · ★ of lesson 1288 «Tales of Adventure, Walter and the Wolf: Walter flees a "wolf" that turns out to be his dog Caro» of the books course of Mova's primary school. The page gives the question's syntax tree — a dependency tree in the style of Universal Dependencies — and its pragmatics clause by clause, then the 4 options as the student saw them, each with its tree and pragmatics. Every text is parsed by Mova itself. How the student answered it, with the score of every option and why: the test at school.

The question

advmodnsubjcopdetamodamodpunctdiscoursepunctadvmodpunctrootSoADVwhoPRONwasAUXtheDETbigADJbadADJwolfNOUN,PUNCTlikeINTJ,PUNCTreallyADV?PUNCT
The words, one row each (CoNLL-U)
#wordlemmaUPOSfeaturesheadrelation
1SosoADV_7 wolfadvmod
2whowhoPRONPronType=Rel7 wolfnsubj
3wasbeAUXMood=Ind Number=Sing Person=3 Tense=Past VerbForm=Fin7 wolfcop
4thetheDETDefinite=Def PronType=Art7 wolfdet
5bigbigADJDegree=Pos7 wolfamod
6badbadADJDegree=Pos7 wolfamod
7wolfwolfNOUNNumber=Singrootroot
8,,PUNCT_7 wolfpunct
9likelikeINTJ_7 wolfdiscourse
10,,PUNCT_9 likepunct
11reallyreallyADV_7 wolfadvmod
12??PUNCT_7 wolfpunct
#verbtense, moodwhowhat, whomto whomwherewhenotherroles by
1is apastthe big bad wolftree rules

One row per clause the reader finds. «not said here»: a role filled from the clause above. «roles by»: a VerbNet class and frame when one fits the verb, else the reader's rules on the tree.

The options

Option 1

The neighbour's gray hound that chased sheep

detnmod:posscaseamodnsubjacl:relclobjrootTheDETneighbourNOUN'sPARTgrayADJhoundNOUNthatPRONchasedVERBsheepNOUN
The words, one row each (CoNLL-U)
#wordlemmaUPOSfeaturesheadrelation
1ThetheDETDefinite=Def PronType=Art2 neighbourdet
2neighbourneighbourNOUNNumber=Sing5 houndnmod:poss
3's'sPART_2 neighbourcase
4graygrayADJDegree=Pos5 houndamod
5houndhoundNOUNNumber=Singrootroot
6thatthatPRONPronType=Rel7 chasednsubj
7chasedchaseVERBMood=Ind Number=Sing Person=3 Tense=Past VerbForm=Fin5 houndacl:relcl
8sheepsheepNOUNNumber=Plur7 chasedobj
#verbtense, moodwhowhat, whomto whomwherewhenotherroles by
1chasepastthe neighbour's gray houndsheepvn chase-51.6 «NP V NP»: agent=Agent sheep=Theme

Option 2 · ← Mova's choice

A large wolf that ate the ram in the kiln

detamodnsubjnsubjdetobjcasedetoblrootADETlargeADJwolfNOUNthatPRONateVERBtheDETramNOUNinADPtheDETkilnNOUN
The words, one row each (CoNLL-U)
#wordlemmaUPOSfeaturesheadrelation
1AaDETDefinite=Ind PronType=Art3 wolfdet
2largelargeADJDegree=Pos3 wolfamod
3wolfwolfNOUNNumber=Sing5 atensubj
4thatthatPRONPronType=Rel5 atensubj
5ateeatVERBMood=Ind Number=Sing Person=3 Tense=Past VerbForm=Finrootroot
6thetheDETDefinite=Def PronType=Art7 ramdet
7ramramNOUNNumber=Sing5 ateobj
8ininADP_10 kilncase
9thetheDETDefinite=Def PronType=Art10 kilndet
10kilnkilnNOUNNumber=Sing5 ateobl
#verbtense, moodwhowhat, whomto whomwherewhenotherroles by
1eatpasta large wolfthe ramthe kilnvn eat-39.1-1 «NP V NP»: agent=Agent ram=Patient

Option 3 · ✓ the right answer

Caro, Walter's dog

punctnmod:posscaseapposrootCaroPROPN,PUNCTWalterPROPN'sPARTdogNOUN
The words, one row each (CoNLL-U)
#wordlemmaUPOSfeaturesheadrelation
1CaroCaroPROPNNumber=Singrootroot
2,,PUNCT_5 dogpunct
3WalterWalterPROPNNumber=Sing5 dognmod:poss
4's'sPART_3 Waltercase
5dogdogNOUNNumber=Sing1 Caroappos

The frames reader finds no event or fact in this sentence.

Option 4

Walter's big dog

nmod:posscaseamodrootWalterPROPN'sPARTbigADJdogNOUN
The words, one row each (CoNLL-U)
#wordlemmaUPOSfeaturesheadrelation
1WalterWalterPROPNNumber=Sing4 dognmod:poss
2's'sPART_1 Waltercase
3bigbigADJDegree=Pos4 dogamod
4dogdogNOUNNumber=Singrootroot

The frames reader finds no event or fact in this sentence.

Text: the tests of Mova's primary school, written for Mova (world/data/school/), as the course runner gave them to the student. Trees: Mova's own parse — the en model on the CPU, when the site is built — not checked by a teacher; they may be wrong. Frames: Mova's frames reader (prag), each text read on its own. Elamur Cosmic License.

This page in Markdown → https://md.mova.elamur.ai/free/en/corpora/questions/books/1288-pg3454-part13/t1/