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Test 3 · Mountains of the world: snow leopards, high-flying geese,…

In The Emperor's New Groove the emperor is turned into a llama. If a real llama spat, who would it most likely spit at?

Mova's choice: option 4 · The right answer: option 4 · right ✓ · Who acts: real llama spat · What happens: turn, spit · To what, where: emperor

This is test 3 of lesson 183 «Mountains of the world: snow leopards, high-flying geese, condors and Everest spiders» 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: In The Emperor's New Groove the emperor is turned into a llama.

The words, one row each (CoNLL-U)

#	word	lemma	UPOS	features	head	relation
1	In	in	ADP	_	6 Groove	case
2	The	the	DET	Definite=Def PronType=Art	3 Emperor	det
3	Emperor	Emperor	PROPN	Number=Sing	6 Groove	nmod:poss
4	's	's	PART	_	3 Emperor	case
5	New	New	ADJ	Degree=Pos	6 Groove	amod
6	Groove	Groove	PROPN	Number=Sing	10 turned	obl
7	the	the	DET	Definite=Def PronType=Art	8 emperor	det
8	emperor	emperor	NOUN	Number=Sing	10 turned	nsubj:pass
9	is	be	AUX	Mood=Ind Number=Sing Person=3 Tense=Pres VerbForm=Fin	10 turned	aux:pass
10	turned	turn	VERB	Tense=Past VerbForm=Part Voice=Pass	root	root
11	into	into	ADP	_	13 llama	case
12	a	a	DET	Definite=Ind PronType=Art	13 llama	det
13	llama	llama	NOUN	Number=Sing	10 turned	obl
14	.	.	PUNCT	_	10 turned	punct

#	verb	tense, mood	who	what, whom	to whom	where	when	other	roles by
1	turn	present · passive		the emperor				into a llama; in the Emperor's New Groove	vn crane-40.3.2 «NP V NP PP.recipient PP.theme»: subject=Patient in groove=Topic into llama=Recipient

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: If a real llama spat, who would it most likely spit at?

The words, one row each (CoNLL-U)

#	word	lemma	UPOS	features	head	relation
1	If	if	SCONJ	_	5 spat	mark
2	a	a	DET	Definite=Ind PronType=Art	5 spat	det
3	real	real	ADJ	Degree=Pos	5 spat	amod
4	llama	llama	NOUN	Number=Sing	5 spat	compound
5	spat	spat	NOUN	Number=Sing	root	root
6	,	,	PUNCT	_	12 spit	punct
7	who	who	PRON	PronType=Rel	12 spit	nsubj
8	would	would	AUX	VerbForm=Fin	12 spit	aux
9	it	it	PRON	Case=Nom Gender=Neut Number=Sing Person=3 PronType=Prs	12 spit	nsubj
10	most	most	ADV	Degree=Sup	11 likely	advmod
11	likely	likely	ADJ	Degree=Pos	12 spit	amod
12	spit	spit	NOUN	Number=Sing	5 spat	acl:relcl
13	at	at	ADP	_	12 spit	nmod
14	?	?	PUNCT	_	5 spat	punct

#	verb	tense, mood	who	what, whom	to whom	where	when	other	roles by
1	spit	would	a real llama spat						tree rules

The options

Option 1

Only at the moon, when it is full and bright

The words, one row each (CoNLL-U)

#	word	lemma	UPOS	features	head	relation
1	Only	only	ADV	_	4 moon	advmod
2	at	at	ADP	_	4 moon	case
3	the	the	DET	Definite=Def PronType=Art	4 moon	det
4	moon	moon	NOUN	Number=Sing	root	root
5	,	,	PUNCT	_	4 moon	punct
6	when	when	SCONJ	_	9 full	mark
7	it	it	PRON	Case=Nom Gender=Neut Number=Sing Person=3 PronType=Prs	9 full	nsubj
8	is	be	AUX	Mood=Ind Number=Sing Person=3 Tense=Pres VerbForm=Fin	9 full	cop
9	full	full	ADJ	Degree=Pos	4 moon	advcl
10	and	and	CCONJ	_	11 bright	cc
11	bright	bright	ADJ	Degree=Pos	9 full	conj

#	verb	tense, mood	who	what, whom	to whom	where	when	other	roles by
1	is	present	moon					full property	tree rules
2	be		moon not said here						tree rules

Option 2

Any person at all who comes close to it

The words, one row each (CoNLL-U)

#	word	lemma	UPOS	features	head	relation
1	Any	any	DET	PronType=Ind	2 person	det
2	person	person	NOUN	Number=Sing	6 comes	nsubj
3	at	at	ADP	_	4 all	case
4	all	all	DET	PronType=Tot	2 person	nmod
5	who	who	PRON	PronType=Rel	6 comes	nsubj
6	comes	come	VERB	Mood=Ind Number=Sing Person=3 Tense=Pres VerbForm=Fin	root	root
7	close	close	ADV	Degree=Pos	6 comes	advmod
8	to	to	ADP	_	9 it	case
9	it	it	PRON	Case=Acc Gender=Neut Number=Sing Person=3 PronType=Prs	6 comes	obl

#	verb	tense, mood	who	what, whom	to whom	where	when	other	roles by
1	come	present	any person at all			it		close property	vn escape-51.1-1 «NP V PP.initial_location»: agent=Theme to it=Initial_Location

Option 3

At its own food, to make it soft to chew

The words, one row each (CoNLL-U)

#	word	lemma	UPOS	features	head	relation
1	At	at	ADP	_	4 food	case
2	its	its	PRON	Case=Gen Gender=Neut Number=Sing Person=3 Poss=Yes PronType=Prs	4 food	nmod:poss
3	own	own	ADJ	Degree=Pos	4 food	amod
4	food	food	NOUN	Number=Sing	7 make	obl
5	,	,	PUNCT	_	7 make	punct
6	to	to	PART	_	7 make	mark
7	make	make	VERB	Mood=Imp VerbForm=Fin	root	root
8	it	it	PRON	Case=Acc Gender=Neut Number=Sing Person=3 PronType=Prs	7 make	obj
9	soft	soft	ADJ	Degree=Pos	7 make	xcomp
10	to	to	PART	_	11 chew	mark
11	chew	chew	VERB	VerbForm=Inf	9 soft	xcomp

#	verb	tense, mood	who	what, whom	to whom	where	when	other	roles by
1	make	to-infinitive		food		its own food		soft property	vn build-26.1-1 «NP.asset V NP»: agent=Asset it=Product
2	chew	to-infinitive	food not said here						vn chew-39.2 «NP V»: agent=Agent

Option 4 · ← Mova's choice · ✓ the right answer

Another llama, to settle an argument

The words, one row each (CoNLL-U)

#	word	lemma	UPOS	features	head	relation
1	Another	another	DET	PronType=Ind	2 llama	det
2	llama	llama	NOUN	Number=Sing	5 settle	nsubj
3	,	,	PUNCT	_	5 settle	punct
4	to	to	PART	_	5 settle	mark
5	settle	settle	VERB	VerbForm=Inf	root	root
6	an	a	DET	Definite=Ind PronType=Art	7 argument	det
7	argument	argument	NOUN	Number=Sing	5 settle	obj

#	verb	tense, mood	who	what, whom	to whom	where	when	other	roles by
1	settle	to-infinitive	another llama	a argument					vn odge-46-1 «NP V ADV»: agent=Theme argument=Location

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/183-mountains-of-the-world-snow-leopards-high-flying-geese-condors-and-everest-spiders/t3/