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Test 10 · ★ · Wolves and dogs

A dog has been trained to find people buried in snow after an avalanche. Which sense does it use most?

Mova's choice: option 2 · The right answer: option 1 · wrong ✗ · Who acts: dog, sense · What happens: train, find, bury, use · To what, where: dog, people, snow, most

This is test 10 · ★ of lesson 24 «Wolves and dogs» of the biology 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

Sentence 1: A dog has been trained to find people buried in snow after an avalanche.

detnsubj:passauxaux:passmarkxcompobjaclcaseoblcasedetoblpunctrootADETdogNOUNhasAUXbeenAUXtrainedVERBtoPARTfindVERBpeopleNOUNburiedVERBinADPsnowNOUNafterADPanDETavalancheNOUN.PUNCT
The words, one row each (CoNLL-U)
#wordlemmaUPOSfeaturesheadrelation
1AaDETDefinite=Ind PronType=Art2 dogdet
2dogdogNOUNNumber=Sing5 trainednsubj:pass
3hashaveAUXMood=Ind Number=Sing Person=3 Tense=Pres VerbForm=Fin5 trainedaux
4beenbeAUXTense=Past VerbForm=Part5 trainedaux:pass
5trainedtrainVERBTense=Past VerbForm=Part Voice=Passrootroot
6totoPART_7 findmark
7findfindVERBVerbForm=Inf5 trainedxcomp
8peoplepeopleNOUNNumber=Plur7 findobj
9buriedburyVERBTense=Past VerbForm=Part Voice=Pass8 peopleacl
10ininADP_11 snowcase
11snowsnowNOUNNumber=Sing9 buriedobl
12afterafterADP_14 avalanchecase
13anaDETDefinite=Ind PronType=Art14 avalanchedet
14avalancheavalancheNOUNNumber=Sing9 buriedobl
15..PUNCT_5 trainedpunct
#verbtense, moodwhowhat, whomto whomwherewhenotherroles by
1trainpresent · perfect · passivea dogvn hire-13.5.3 «NP V NP to be NP»: subject=Theme clause=Attribute
2findto-infinitivea dog not said herepeoplevn discover-84 «NP V NP»: agent=Agent people=Topic
3buryparticiplepeople not said heresnowafter a avalanchevn put-9.1-1 «NP V NP PP.destination»: agent=Agent in snow=Destination

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.

Sentence 2: Which sense does it use most?

detnsubjauxnsubjobjpunctrootWhichDETsenseNOUNdoesAUXitPRONuseVERBmostADJ?PUNCT
The words, one row each (CoNLL-U)
#wordlemmaUPOSfeaturesheadrelation
1WhichwhichDETPronType=Int2 sensedet
2sensesenseNOUNNumber=Sing5 usensubj
3doesdoAUXMood=Ind Number=Sing Person=3 Tense=Pres VerbForm=Fin5 useaux
4ititPRONCase=Nom Gender=Neut Number=Sing Person=3 PronType=Prs5 usensubj
5useuseVERBVerbForm=Infrootroot
6mostmostADJDegree=Sup5 useobj
7??PUNCT_5 usepunct
#verbtense, moodwhowhat, whomto whomwherewhenotherroles by
1usepresent · do-supportwhich sensemostvn eat-39.1 «NP V NP»: agent=Agent most=Patient

The options

Option 1 · ✓ the right answer

Smell

rootSmellNOUN
The words, one row each (CoNLL-U)
#wordlemmaUPOSfeaturesheadrelation
1SmellsmellNOUNNumber=Singrootroot

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

Option 2 · ← Mova's choice

Hearing only

advmodrootHearingVERBonlyADV
The words, one row each (CoNLL-U)
#wordlemmaUPOSfeaturesheadrelation
1HearinghearVERBTense=Pres VerbForm=Partrootroot
2onlyonlyADV_1 Hearingadvmod
#verbtense, moodwhowhat, whomto whomwherewhenotherroles by
1heargerundvn see-30.1-1-1 «NP V PP.stimulus»: agent=Experiencer

Option 3

Sight

rootSightNOUN
The words, one row each (CoNLL-U)
#wordlemmaUPOSfeaturesheadrelation
1SightsightNOUNNumber=Singrootroot

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

Option 4

Taste

rootTasteNOUN
The words, one row each (CoNLL-U)
#wordlemmaUPOSfeaturesheadrelation
1TastetasteNOUNNumber=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/biology/24-wolves-and-dogs/t10/