---
title: Select the response consistent with the established facts concerning… — Animals in the news: true stories, fak… · tree and pragmatics
description: Select the response consistent with the established facts concerning photographs of sharks in flooded streets. Exam question 2 of lesson 296 «Animals in the news: true stories, fakes and how to read them» of the biology course of Mova's primary school, with the dependency tree and pragmatics of the 
---

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# Exam question 2 · Animals in the news: true stories, fakes and how to read t…

<!-- .ven lang=en -->
Select the response consistent with the established facts concerning photographs of sharks in flooded streets.

<!-- .vintro -->
**Mova's choice:** option 2 · **The right answer:** option 4 · wrong ✗ · **Who acts:** you · **What happens:** select, establish, flood · **To what, where:** response

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This is exam question 2 of lesson 296 «Animals in the news: true stories, fakes and how to read them» of the biology 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](https://md.mova.elamur.ai/free/en/school-run/biology/296-animals-in-the-news-true-stories-fakes-and-how-to-read-them/#e2).

## The question {#question}

```conllu
# sent_id = question:biology:296-animals-in-the-news-true-stories-fakes-and-how-to-read-them:e2:1
# text = Select the response consistent with the established facts concerning photographs of sharks in flooded streets.
1	Select	select	VERB	VB	Mood=Imp|VerbForm=Fin	0	root	_	_
2	the	the	DET	DT	Definite=Def|PronType=Art	3	det	_	_
3	response	response	NOUN	NN	Number=Sing	1	obj	_	_
4	consistent	consistent	ADJ	JJ	Degree=Pos	1	xcomp	_	_
5	with	with	ADP	IN	_	8	case	_	_
6	the	the	DET	DT	Definite=Def|PronType=Art	8	det	_	_
7	established	establish	VERB	VBN	Tense=Past|VerbForm=Part|Voice=Pass	8	amod	_	_
8	facts	fact	NOUN	NNS	Number=Plur	4	obl	_	_
9	concerning	concerning	ADJ	JJ	Degree=Pos	10	amod	_	_
10	photographs	photograph	NOUN	NNS	Number=Plur	8	conj	_	_
11	of	of	ADP	IN	_	12	case	_	_
12	sharks	shark	NOUN	NNS	Number=Plur	10	nmod	_	_
13	in	in	ADP	IN	_	15	case	_	_
14	flooded	flood	VERB	VBN	Tense=Past|VerbForm=Part|Voice=Pass	15	amod	_	_
15	streets	street	NOUN	NNS	Number=Plur	12	nmod	_	SpaceAfter=No
16	.	.	PUNCT	.	_	1	punct	_	_
```

<!-- .fr -->
| # | verb | tense, mood | who | what, whom | to whom | where | when | other | roles by |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 1 | **select** | imperative | you *not said here* | the response |  |  |  | consistent *property* | vn obtain-13.5.2 «NP V NP»: agent=Agent response=Theme |
| 2 | **establish** | participle |  |  |  |  |  |  | vn indicate-78-1-1 «NP V NP to be NP»: agent=Pivot |
| 3 | **flood** | participle |  |  |  |  |  |  | vn other\_cos-45.4 «NP.patient V»: agent=Patient |

<!-- .note -->
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 {#options}

### Option 1 {#o1}

<!-- .ven lang=en -->
Such images are produced by the sharks' own cameras

```conllu
# sent_id = question:biology:296-animals-in-the-news-true-stories-fakes-and-how-to-read-them:e2:o1:1
# text = Such images are produced by the sharks' own cameras
1	Such	such	ADJ	JJ	Degree=Pos	2	amod	_	_
2	images	image	NOUN	NNS	Number=Plur	4	nsubj:pass	_	_
3	are	be	AUX	VBP	Mood=Ind|Number=Plur|Person=3|Tense=Pres|VerbForm=Fin	4	aux:pass	_	_
4	produced	produce	VERB	VBN	Tense=Past|VerbForm=Part|Voice=Pass	0	root	_	_
5	by	by	ADP	IN	_	10	case	_	_
6	the	the	DET	DT	Definite=Def|PronType=Art	7	det	_	_
7	sharks	shark	NOUN	NNS	Number=Plur	10	nmod:poss	_	SpaceAfter=No
8	'	's	PART	POS	_	7	case	_	_
9	own	own	ADJ	JJ	Degree=Pos	10	amod	_	_
10	cameras	camera	NOUN	NNS	Number=Plur	4	obl	_	_
```

<!-- .fr -->
| # | verb | tense, mood | who | what, whom | to whom | where | when | other | roles by |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 1 | **produce** | present · passive | the sharks's own cameras | Such images |  |  |  |  | vn create-26.4 «NP V NP»: agent=Agent subject=Result |

### Option 2 · ← Mova's choice {#o2}

<!-- .ven lang=en -->
Such images depict dolphins mistaken for sharks

```conllu
# sent_id = question:biology:296-animals-in-the-news-true-stories-fakes-and-how-to-read-them:e2:o2:1
# text = Such images depict dolphins mistaken for sharks
1	Such	such	ADJ	JJ	Degree=Pos	2	amod	_	_
2	images	image	NOUN	NNS	Number=Plur	3	nsubj	_	_
3	depict	depict	VERB	VBP	Mood=Ind|Number=Plur|Person=3|Tense=Pres|VerbForm=Fin	0	root	_	_
4	dolphins	dolphin	NOUN	NNS	Number=Plur	3	obj	_	_
5	mistaken	mistake	VERB	VBN	Tense=Past|VerbForm=Part|Voice=Pass	4	acl	_	_
6	for	for	ADP	IN	_	7	case	_	_
7	sharks	shark	NOUN	NNS	Number=Plur	5	obl	_	_
```

<!-- .fr -->
| # | verb | tense, mood | who | what, whom | to whom | where | when | other | roles by |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 1 | **depict** | present | Such images | dolphins |  |  |  |  | vn characterize-29.2 «NP V NP S\_ING»: agent=Agent dolphin=Theme |
| 2 | **mistake** | participle |  | dolphins *not said here* |  |  |  | for sharks | tree rules |

### Option 3 {#o3}

<!-- .ven lang=en -->
Such images invariably record genuine incursions of marine animals into towns

```conllu
# sent_id = question:biology:296-animals-in-the-news-true-stories-fakes-and-how-to-read-them:e2:o3:1
# text = Such images invariably record genuine incursions of marine animals into towns
1	Such	such	ADJ	JJ	Degree=Pos	2	amod	_	_
2	images	image	NOUN	NNS	Number=Plur	4	nsubj	_	_
3	invariably	invariably	ADV	RB	_	4	advmod	_	_
4	record	record	VERB	VBP	Mood=Ind|Number=Plur|Person=3|Tense=Pres|VerbForm=Fin	0	root	_	_
5	genuine	genuine	ADJ	JJ	Degree=Pos	6	amod	_	_
6	incursions	incursion	NOUN	NNS	Number=Plur	4	obj	_	_
7	of	of	ADP	IN	_	9	case	_	_
8	marine	marine	ADJ	JJ	Degree=Pos	9	amod	_	_
9	animals	animal	NOUN	NNS	Number=Plur	6	nmod	_	_
10	into	into	ADP	IN	_	11	case	_	_
11	towns	town	NOUN	NNS	Number=Plur	4	obl	_	_
```

<!-- .fr -->
| # | verb | tense, mood | who | what, whom | to whom | where | when | other | roles by |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 1 | **record** | present | Such images | genuine incursions of marine animals |  | towns |  | invariably *property* | vn transcribe-25.4 «NP V NP PP.destination»: agent=Agent incursion=Theme into town=Destination |
| 2 | **incur** |  |  | marine animals |  |  |  |  | nom incursion «act transitive»: of=patient |

### Option 4 · ✓ the right answer {#o4}

<!-- .ven lang=en -->
Such images are customarily edited pictures recirculated after successive floods

```conllu
# sent_id = question:biology:296-animals-in-the-news-true-stories-fakes-and-how-to-read-them:e2:o4:1
# text = Such images are customarily edited pictures recirculated after successive floods
1	Such	such	ADJ	JJ	Degree=Pos	2	amod	_	_
2	images	image	NOUN	NNS	Number=Plur	6	nsubj	_	_
3	are	be	AUX	VBP	Mood=Ind|Number=Plur|Person=3|Tense=Pres|VerbForm=Fin	6	cop	_	_
4	customarily	customarily	ADV	RB	_	6	advmod	_	_
5	edited	edit	VERB	VBN	Tense=Past|VerbForm=Part|Voice=Pass	6	amod	_	_
6	pictures	picture	NOUN	NNS	Number=Plur	0	root	_	_
7	recirculated	recirculate	VERB	VBN	Tense=Past|VerbForm=Part|Voice=Pass	6	acl	_	_
8	after	after	ADP	IN	_	10	case	_	_
9	successive	successive	ADJ	JJ	Degree=Pos	10	amod	_	_
10	floods	flood	NOUN	NNS	Number=Plur	7	obl:agent	_	_
```

<!-- .fr -->
| # | verb | tense, mood | who | what, whom | to whom | where | when | other | roles by |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 1 | **edit** | participle |  |  |  |  |  |  | tree rules |
| 2 | **is a** | present | Such images | edited pictures |  |  |  | customarily *property* | tree rules |
| 3 | **recirculate** | participle |  | edited pictures *not said here* |  |  |  |  | vn modes\_of\_being\_with\_motion-47.3 «NP V»: agent=Theme |

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**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.

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- ← previous: [Animals in the news: true stories, fak…, exam 1](https://md.mova.elamur.ai/free/en/corpora/questions/biology/296-animals-in-the-news-true-stories-fakes-and-how-to-read-them/e1/)
- next →: [Animals in the news: true stories, fak…, exam 3](https://md.mova.elamur.ai/free/en/corpora/questions/biology/296-animals-in-the-news-true-stories-fakes-and-how-to-read-them/e3/)
- ↑ back to [Animals in the news: true stories, fakes and how to read them](https://md.mova.elamur.ai/free/en/corpora/questions/biology/296-animals-in-the-news-true-stories-fakes-and-how-to-read-them/)