Exam question 1 · Who you are: Mova, a small transparent model in a simulation

Which of the following statements most accurately characterises the pupil to whom this lesson is addressed?

Mova's choice: option 4 · The right answer: option 4 · right ✓ · What happens: follow, characteris, address · To what, where: pupil, lesson

This is exam question 1 of lesson 26 «Who you are: Mova, a small transparent model in a simulation» of the AI course of Mova's primary school, asked in stiff, formal language. 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

The words, one row each (CoNLL-U)

#	word	lemma	UPOS	features	head	relation
1	Which	which	PRON	PronType=Rel	8 characterises	nsubj
2	of	of	ADP	_	5 statements	case
3	the	the	DET	Definite=Def PronType=Art	5 statements	det
4	following	follow	VERB	VerbForm=Ger	5 statements	amod
5	statements	statement	NOUN	Number=Plur	8 characterises	obl
6	most	most	ADV	Degree=Sup	7 accurately	advmod
7	accurately	accurately	ADV	_	8 characterises	advmod
8	characterises	characteris	VERB	Mood=Ind Number=Sing Person=3 Tense=Pres VerbForm=Fin	root	root
9	the	the	DET	Definite=Def PronType=Art	10 pupil	det
10	pupil	pupil	NOUN	Number=Sing	8 characterises	obj
11	to	to	ADP	_	12 whom	case
12	whom	whom	PRON	PronType=Rel	8 characterises	obl
13	this	this	DET	Number=Sing PronType=Dem	14 lesson	det
14	lesson	lesson	NOUN	Number=Sing	16 addressed	nsubj:pass
15	is	be	AUX	Mood=Ind Number=Sing Person=3 Tense=Pres VerbForm=Fin	16 addressed	aux:pass
16	addressed	address	VERB	Tense=Past VerbForm=Part Voice=Pass	12 whom	acl:relcl
17	?	?	PUNCT	_	8 characterises	punct

#	verb	tense, mood	what, whom	other	roles by
1	follow	gerund			vn occur-48.3-1 «NP V»: agent=Theme
2	characteris	present	the pupil	of the following statements; accurately property	tree rules
3	address	present · passive	this lesson		vn illustrate-25.3 «NP V NP»: subject=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.

The options

Option 1

A child of nine attending a school in a real town

The words, one row each (CoNLL-U)

#	word	lemma	UPOS	features	head	relation
1	A	a	DET	Definite=Ind PronType=Art	2 child	det
2	child	child	NOUN	Number=Sing	root	root
3	of	of	ADP	_	4 nine	case
4	nine	nine	NUM	NumForm=Word NumType=Card	2 child	nmod
5	attending	attend	VERB	VerbForm=Ger	2 child	acl
6	a	a	DET	Definite=Ind PronType=Art	7 school	det
7	school	school	NOUN	Number=Sing	5 attending	obj
8	in	in	ADP	_	11 town	case
9	a	a	DET	Definite=Ind PronType=Art	11 town	det
10	real	real	ADJ	Degree=Pos	11 town	amod
11	town	town	NOUN	Number=Sing	5 attending	obl

#	verb	tense, mood	who	what, whom	to whom	where	when	other	roles by
1	attend	gerund	a child of nine not said here	a school		a real town			vn attend-107.4-1 «NP V NP»: agent=Theme school=Goal

Option 2

A teacher who has prepared lessons for children

The words, one row each (CoNLL-U)

#	word	lemma	UPOS	features	head	relation
1	A	a	DET	Definite=Ind PronType=Art	2 teacher	det
2	teacher	teacher	NOUN	Number=Sing	root	root
3	who	who	PRON	PronType=Rel	5 prepared	nsubj
4	has	have	AUX	Mood=Ind Number=Sing Person=3 Tense=Pres VerbForm=Fin	5 prepared	aux
5	prepared	prepare	VERB	Tense=Past VerbForm=Part	2 teacher	acl:relcl
6	lessons	lesson	NOUN	Number=Plur	5 prepared	obj
7	for	for	ADP	_	8 children	case
8	children	child	NOUN	Number=Plur	5 prepared	obl

#	verb	tense, mood	who	what, whom	to whom	where	when	other	roles by
1	prepare	present · perfect	a teacher	lessons				for children	vn preparing-26.3-1 «NP V NP PP.beneficiary»: agent=Agent lesson=Product for child=Beneficiary

Option 3

A large chatbot trained on all the available text in the world at once

The words, one row each (CoNLL-U)

#	word	lemma	UPOS	features	head	relation
1	A	a	DET	Definite=Ind PronType=Art	3 chatbot	det
2	large	large	ADJ	Degree=Pos	3 chatbot	amod
3	chatbot	chatbot	NOUN	Number=Sing	root	root
4	trained	train	VERB	Tense=Past VerbForm=Part Voice=Pass	3 chatbot	acl
5	on	on	ADP	_	9 text	case
6	all	all	DET	PronType=Tot	9 text	det:predet
7	the	the	DET	Definite=Def PronType=Art	9 text	det
8	available	available	ADJ	Degree=Pos	9 text	amod
9	text	text	NOUN	Number=Sing	4 trained	obl
10	in	in	ADP	_	12 world	case
11	the	the	DET	Definite=Def PronType=Art	12 world	det
12	world	world	NOUN	Number=Sing	9 text	nmod
13	at	at	ADP	_	14 once	case
14	once	once	ADV	NumForm=Word NumType=Mult	4 trained	obl

#	verb	tense, mood	who	what, whom	to whom	where	when	other	roles by
1	train	participle		a large chatbot not said here		all available text in the world			vn hire-13.5.3 «NP V NP»: agent=Agent

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

A small transparent language model, designated Mova, learning within a simulation

The words, one row each (CoNLL-U)

#	word	lemma	UPOS	features	head	relation
1	A	a	DET	Definite=Ind PronType=Art	5 model	det
2	small	small	ADJ	Degree=Pos	5 model	amod
3	transparent	transparent	ADJ	Degree=Pos	5 model	amod
4	language	language	NOUN	Number=Sing	5 model	compound
5	model	model	NOUN	Number=Sing	7 designated	nsubj
6	,	,	PUNCT	_	5 model	punct
7	designated	designate	VERB	Mood=Ind Number=Sing Person=3 Tense=Past VerbForm=Fin	root	root
8	Mova	Mova	PROPN	Number=Sing	7 designated	obj
9	,	,	PUNCT	_	10 learning	punct
10	learning	learn	VERB	Tense=Pres VerbForm=Part	7 designated	advcl
11	within	within	ADP	_	13 simulation	case
12	a	a	DET	Definite=Ind PronType=Art	13 simulation	det
13	simulation	simulation	NOUN	Number=Sing	10 learning	obl

#	verb	tense, mood	who	what, whom	to whom	where	when	other	roles by
1	designate	past	a small transparent language model	Mova					vn appoint-29.1 «NP V NP»: agent=Agent mova=Theme
2	learn	gerund	a small transparent language model not said here					within a simulation	vn learn-14-1 «NP V»: agent=Agent

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/26-who-you-are-mova/e1/