---
title: Identify the proportion of young academy footballers frequently cite… — Famous athletes and what being a profe… · tree and pragmatics
description: Identify the proportion of young academy footballers frequently cited as attaining professional status. Exam question 1 of lesson 63 «Famous athletes and what being a professional takes» of the medicine course of Mova's primary school, with the dependency tree and pragmatics of the question and of e
---

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# Exam question 1 · Famous athletes and what being a professional takes

<!-- .ven lang=en -->
Identify the proportion of young academy footballers frequently cited as attaining professional status.

<!-- .vintro -->
**Mova's choice:** option 1 · **The right answer:** option 3 · wrong ✗ · **Who acts:** you, proportion · **What happens:** identify, cite, attain · **To what, where:** professional status

<!-- .vabout -->
This is exam question 1 of lesson 63 «Famous athletes and what being a professional takes» of the medicine 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/medicine/63-famous-athletes-and-what-being-a-professional-takes/#e1).

## The question {#question}

```conllu
# sent_id = question:medicine:63-famous-athletes-and-what-being-a-professional-takes:e1:1
# text = Identify the proportion of young academy footballers frequently cited as attaining professional status.
1	Identify	identify	VERB	VB	Mood=Imp|VerbForm=Fin	0	root	_	_
2	the	the	DET	DT	Definite=Def|PronType=Art	3	det	_	_
3	proportion	proportion	NOUN	NN	Number=Sing	9	nsubj	_	_
4	of	of	ADP	IN	_	7	case	_	_
5	young	young	ADJ	JJ	Degree=Pos	7	amod	_	_
6	academy	academy	NOUN	NN	Number=Sing	7	compound	_	_
7	footballers	footballer	NOUN	NNS	Number=Plur	3	nmod	_	_
8	frequently	frequently	ADV	RB	_	9	advmod	_	_
9	cited	cite	VERB	VBD	Mood=Ind|Number=Sing|Person=3|Tense=Past|VerbForm=Fin	1	parataxis	_	_
10	as	as	SCONJ	IN	_	11	mark	_	_
11	attaining	attain	VERB	VBG	Tense=Pres|VerbForm=Part	9	advcl	_	_
12	professional	professional	ADJ	JJ	Degree=Pos	13	amod	_	_
13	status	status	NOUN	NN	Number=Sing	11	obj	_	SpaceAfter=No
14	.	.	PUNCT	.	_	1	punct	_	_
```

<!-- .fr -->
| # | verb | tense, mood | who | what, whom | to whom | where | when | other | roles by |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 1 | **identify** | imperative | you *not said here* |  |  |  |  |  | vn empathize-88.2 «NP V»: agent=Experiencer |
| 2 | **cite** | past | the proportion of young academy footballers |  |  |  |  | frequently *property* | vn judgment-33.1-1 «NP V NP»: agent=Agent |
| 3 | **attain** | gerund | the proportion of young academy footballers *not said here* | professional status |  |  |  |  | vn get-13.5.1 «NP V NP»: agent=Agent status=Theme |

<!-- .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 · ← Mova's choice {#o1}

<!-- .ven lang=en -->
Every participant without exception

```conllu
# sent_id = question:medicine:63-famous-athletes-and-what-being-a-professional-takes:e1:o1:1
# text = Every participant without exception
1	Every	every	DET	DT	PronType=Tot	2	det	_	_
2	participant	participant	NOUN	NN	Number=Sing	0	root	_	_
3	without	without	ADP	IN	_	4	case	_	_
4	exception	exception	NOUN	NN	Number=Sing	2	nmod	_	_
```

<!-- .note -->
The frames reader finds no event or fact in this sentence.

### Option 2 {#o2}

<!-- .ven lang=en -->
Approximately nine in ten

```conllu
# sent_id = question:medicine:63-famous-athletes-and-what-being-a-professional-takes:e1:o2:1
# text = Approximately nine in ten
1	Approximately	approximately	ADV	RB	_	2	advmod	_	_
2	nine	nine	NUM	CD	NumForm=Word|NumType=Card	0	root	_	_
3	in	in	ADP	IN	_	4	case	_	_
4	ten	ten	NUM	CD	NumForm=Word|NumType=Card	2	nmod	_	_
```

<!-- .note -->
The frames reader finds no event or fact in this sentence.

### Option 3 · ✓ the right answer {#o3}

<!-- .ven lang=en -->
Fewer than one in one hundred

```conllu
# sent_id = question:medicine:63-famous-athletes-and-what-being-a-professional-takes:e1:o3:1
# text = Fewer than one in one hundred
1	Fewer	few	ADJ	JJR	Degree=Cmp	3	advmod	_	_
2	than	than	ADP	IN	_	1	fixed	_	_
3	one	one	NUM	CD	NumForm=Word|NumType=Card	0	root	_	_
4	in	in	ADP	IN	_	6	case	_	_
5	one	one	NUM	CD	NumForm=Word|NumType=Card	6	compound	_	_
6	hundred	hundred	NUM	CD	NumForm=Word|NumType=Card	3	nmod	_	_
```

<!-- .note -->
The frames reader finds no event or fact in this sentence.

### Option 4 {#o4}

<!-- .ven lang=en -->
Approximately one half

```conllu
# sent_id = question:medicine:63-famous-athletes-and-what-being-a-professional-takes:e1:o4:1
# text = Approximately one half
1	Approximately	approximately	ADV	RB	_	2	advmod	_	_
2	one	one	NUM	CD	NumForm=Word|NumType=Card	3	nummod	_	_
3	half	half	NOUN	NN	Number=Sing|NumForm=Word|NumType=Frac	0	root	_	_
```

<!-- .note -->
The frames reader finds no event or fact in this sentence.

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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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- next →: [Famous athletes and what being a profe…, exam 2](https://md.mova.elamur.ai/free/en/corpora/questions/medicine/63-famous-athletes-and-what-being-a-professional-takes/e2/)
- ↑ back to [Famous athletes and what being a professional takes](https://md.mova.elamur.ai/free/en/corpora/questions/medicine/63-famous-athletes-and-what-being-a-professional-takes/)