Test 7 · ★ · Japanese Fairy Tales, The Dog Shiro, part 29: the greedy n…

yo what did the old man say to make Shiro beg?

Mova's choice: option 2 · The right answer: option 4 · wrong ✗ · Who acts: old man, Shiro · What happens: say, make, beg · Speech: someone speaks here

This is test 7 · ★ of lesson 1369 «Japanese Fairy Tales, The Dog Shiro, part 29: the greedy neighbour borrows the magic mortar and breaks it» 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

The words, one row each (CoNLL-U)

#	word	lemma	UPOS	features	head	relation
1	yo	yo	INTJ	_	7 say	discourse
2	what	what	PRON	PronType=Int	7 say	obj
3	did	do	AUX	Mood=Ind Number=Sing Person=3 Tense=Past VerbForm=Fin	7 say	aux
4	the	the	DET	Definite=Def PronType=Art	6 man	det
5	old	old	ADJ	Degree=Pos	6 man	amod
6	man	man	NOUN	Number=Sing	7 say	nsubj
7	say	say	VERB	VerbForm=Inf	root	root
8	to	to	PART	_	9 make	mark
9	make	make	VERB	VerbForm=Inf	7 say	xcomp
10	Shiro	Shiro	PROPN	Number=Sing	11 beg	nsubj
11	beg	beg	VERB	VerbForm=Inf	9 make	xcomp
12	?	?	PUNCT	_	7 say	punct

#	verb	tense, mood	who	roles by
1	say speech: assert	past · do-support	the old man	tree rules
2	make	to-infinitive	the old man not said here	tree rules
3	beg speech: request	infinitive	Shiro	vn beg-58.2-1-1 «NP V PP.Topic»: 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.

The options

Option 1

Good dog, sit!

The words, one row each (CoNLL-U)

#	word	lemma	UPOS	features	head	relation
1	Good	good	ADJ	Degree=Pos	2 dog	amod
2	dog	dog	NOUN	Number=Sing	4 sit	nsubj
3	,	,	PUNCT	_	2 dog	punct
4	sit	sit	VERB	VerbForm=Inf	root	root
5	!	!	PUNCT	_	4 sit	punct

#	verb	tense, mood	who	what, whom	to whom	where	when	other	roles by
1	sit	infinitive	Good dog						vn assuming_position-50 «NP V»: agent=Agent

Option 2 · ← Mova's choice

Chin, chin, Shiro, beg for food now!

The words, one row each (CoNLL-U)

#	word	lemma	UPOS	features	head	relation
1	Chin	chin	NOUN	Number=Sing	5 Shiro	nsubj
2	,	,	PUNCT	_	3 chin	punct
3	chin	chin	NOUN	Number=Sing	1 Chin	conj
4	,	,	PUNCT	_	5 Shiro	punct
5	Shiro	Shiro	PROPN	Number=Sing	root	root
6	,	,	PUNCT	_	7 beg	punct
7	beg	beg	NOUN	Number=Sing	5 Shiro	appos
8	for	for	ADP	_	9 food	case
9	food	food	NOUN	Number=Sing	7 beg	nmod
10	now	now	ADV	PronType=Dem	7 beg	advmod
11	!	!	PUNCT	_	5 Shiro	punct

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

Option 3

Shiro, speak!

The words, one row each (CoNLL-U)

#	word	lemma	UPOS	features	head	relation
1	Shiro	Shiro	PROPN	Number=Sing	3 speak	nsubj
2	,	,	PUNCT	_	1 Shiro	punct
3	speak	speak	VERB	Mood=Imp VerbForm=Fin	root	root
4	!	!	PUNCT	_	3 speak	punct

#	verb	tense, mood	who	what, whom	to whom	where	when	other	roles by
1	speak speech: other	infinitive	Shiro						vn talk-37.5 «NP V»: agent=Agent

Option 4 · ✓ the right answer

Chin, chin!

The words, one row each (CoNLL-U)

#	word	lemma	UPOS	features	head	relation
1	Chin	chin	NOUN	Number=Sing	root	root
2	,	,	PUNCT	_	3 chin	punct
3	chin	chin	NOUN	Number=Sing	1 Chin	conj
4	!	!	PUNCT	_	1 Chin	punct

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/1369-pg4018-part29/t7/