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Test 5 · ★★ · In the news: tricked bots, real discoveries, careful words

In a cartoon a star actor finds a film using her face that she never made. Why did real actors worry about this?

Mova's choice: option 3 · The right answer: option 3 · right ✓ · Who acts: star actor, film, actor, real actors · What happens: find, use, not make, do, worry · To what, where: film, cartoon, face

This is test 5 · ★★ of lesson 23 «In the news: tricked bots, real discoveries, careful words» of the AI 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 a cartoon a star actor finds a film using her face that she never made.

The words, one row each (CoNLL-U)

#	word	lemma	UPOS	features	head	relation
1	In	in	ADP	_	3 cartoon	case
2	a	a	DET	Definite=Ind PronType=Art	3 cartoon	det
3	cartoon	cartoon	NOUN	Number=Sing	7 finds	obl
4	a	a	DET	Definite=Ind PronType=Art	6 actor	det
5	star	star	NOUN	Number=Sing	6 actor	compound
6	actor	actor	NOUN	Number=Sing	7 finds	nsubj
7	finds	find	VERB	Mood=Ind Number=Sing Person=3 Tense=Pres VerbForm=Fin	root	root
8	a	a	DET	Definite=Ind PronType=Art	9 film	det
9	film	film	NOUN	Number=Sing	7 finds	obj
10	using	use	VERB	VerbForm=Ger	7 finds	xcomp
11	her	her	PRON	Case=Gen Gender=Fem Number=Sing Person=3 Poss=Yes PronType=Prs	12 face	nmod:poss
12	face	face	NOUN	Number=Sing	10 using	obj
13	that	that	SCONJ	_	16 made	mark
14	she	she	PRON	Case=Nom Gender=Fem Number=Sing Person=3 PronType=Prs	16 made	nsubj
15	never	never	ADV	PronType=Neg	16 made	advmod
16	made	make	VERB	Mood=Ind Number=Sing Person=3 Tense=Past VerbForm=Fin	10 using	advcl
17	.	.	PUNCT	_	7 finds	punct

#	verb	tense, mood	who	what, whom	to whom	where	when	other	roles by
1	find	present	a star actor	a film		a cartoon			vn declare-29.4-1-1 «NP V NP ADJ»: agent=Agent film=Attribute clause=Theme
2	use	gerund	a film not said here	actor's face					vn eat-39.1 «NP V NP»: agent=Agent face=Patient
3	not make	past	actor						vn build-26.1-1 «NP V NP»: agent=Agent

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: Why did real actors worry about this?

The words, one row each (CoNLL-U)

#	word	lemma	UPOS	features	head	relation
1	Why	why	ADV	PronType=Int	2 did	advmod
2	did	do	VERB	Mood=Ind Number=Sing Person=1 Tense=Past VerbForm=Fin	root	root
3	real	real	ADJ	Degree=Pos	4 actors	amod
4	actors	actor	NOUN	Number=Plur	5 worry	nsubj
5	worry	worry	VERB	Mood=Ind Number=Plur Person=3 Tense=Pres VerbForm=Fin	2 did	parataxis
6	about	about	ADP	_	7 this	case
7	this	this	PRON	Number=Sing PronType=Dem	5 worry	obl
8	?	?	PUNCT	_	2 did	punct

#	verb	tense, mood	who	what, whom	to whom	where	when	other	roles by
1	do	past							vn act-114-1 «NP V»: agent=Agent
2	worry	present	real actors					about this	vn care-88.1-1 «NP V PP.stimulus what S»: agent=Experiencer about this=Stimulus

The options

Option 1

They wanted to act alongside robots

The words, one row each (CoNLL-U)

#	word	lemma	UPOS	features	head	relation
1	They	they	PRON	Case=Nom Number=Plur Person=3 PronType=Prs	2 wanted	nsubj
2	wanted	want	VERB	Mood=Ind Number=Plur Person=3 Tense=Past VerbForm=Fin	root	root
3	to	to	PART	_	4 act	mark
4	act	act	VERB	VerbForm=Inf	2 wanted	xcomp
5	alongside	alongside	ADP	_	6 robots	case
6	robots	robot	NOUN	Number=Plur	4 act	obl

#	verb	tense, mood	who	what, whom	to whom	where	when	other	roles by
1	want	past	They						vn want-32.1-1-1 «NP V NP S_INF»: agent=Pivot clause=Theme
2	act not said to happen	to-infinitive	They not said here					alongside robots	vn act-114-1-1 «NP V»: agent=Agent

Option 2

They wanted much more money for each photo of their faces

The words, one row each (CoNLL-U)

#	word	lemma	UPOS	features	head	relation
1	They	they	PRON	Case=Nom Number=Plur Person=3 PronType=Prs	2 wanted	nsubj
2	wanted	want	VERB	Mood=Ind Number=Plur Person=3 Tense=Past VerbForm=Fin	root	root
3	much	much	ADV	_	4 more	advmod
4	more	more	ADJ	Degree=Cmp	5 money	amod
5	money	money	NOUN	Number=Sing	2 wanted	obj
6	for	for	ADP	_	8 photo	case
7	each	each	DET	PronType=Tot	8 photo	det
8	photo	photo	NOUN	Number=Sing	2 wanted	obl
9	of	of	ADP	_	11 faces	case
10	their	their	PRON	Case=Gen Number=Plur Person=3 Poss=Yes PronType=Prs	11 faces	nmod:poss
11	faces	face	NOUN	Number=Plur	8 photo	nmod

#	verb	tense, mood	who	what, whom	to whom	where	when	other	roles by
1	want	past	They	more money				for each photo of their faces	vn want-32.1-1-1 «NP V NP ADV»: agent=Pivot money=Theme

Option 3 · ← Mova's choice · ✓ the right answer

They want control over their own face and voice

The words, one row each (CoNLL-U)

#	word	lemma	UPOS	features	head	relation
1	They	they	PRON	Case=Nom Number=Plur Person=3 PronType=Prs	2 want	nsubj
2	want	want	VERB	Mood=Ind Number=Plur Person=3 Tense=Pres VerbForm=Fin	root	root
3	control	control	NOUN	Number=Sing	2 want	obj
4	over	over	ADP	_	7 face	case
5	their	their	PRON	Case=Gen Number=Plur Person=3 Poss=Yes PronType=Prs	7 face	nmod:poss
6	own	own	ADJ	Degree=Pos	7 face	amod
7	face	face	NOUN	Number=Sing	2 want	obl
8	and	and	CCONJ	_	9 voice	cc
9	voice	voice	NOUN	Number=Sing	7 face	conj

#	verb	tense, mood	who	what, whom	to whom	where	when	other	roles by
1	want	present	They	control		their own face and voice			vn want-32.1-1-1 «NP V NP ADV»: agent=Pivot control=Theme

Option 4

They were afraid of cameras

The words, one row each (CoNLL-U)

#	word	lemma	UPOS	features	head	relation
1	They	they	PRON	Case=Nom Number=Plur Person=3 PronType=Prs	3 afraid	nsubj
2	were	be	AUX	Mood=Ind Number=Plur Person=3 Tense=Past VerbForm=Fin	3 afraid	cop
3	afraid	afraid	ADJ	Degree=Pos	root	root
4	of	of	ADP	_	5 cameras	case
5	cameras	camera	NOUN	Number=Plur	3 afraid	obl

#	verb	tense, mood	who	what, whom	to whom	where	when	other	roles by
1	is	past	They					of cameras; afraid property	tree rules

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/ai/23-news-tricked-bots-discoveries/t5/