---
title: A doctor trains for 5 or 6 years at university and more after, and f… — Why some jobs pay more · tree and pragmatics
description: A doctor trains for 5 or 6 years at university and more after, and few people can do the work, so doctors earn more; lots of people can learn to clean in a few weeks, so cleaning pays less, though it matters just as much. Who acts: doctor, few people, doctors, lots. A sentence of the lesson «Why som
---

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# Why some jobs pay more, sentence 1

<!-- .ven lang=en -->
A doctor trains for 5 or 6 years at university and more after, and few people can do the work, so doctors earn more; lots of people can learn to clean in a few weeks, so cleaning pays less, though it matters just as much.

<!-- .vintro -->
**Who acts:** doctor, few people, doctors, lots, cleaning, it · **What happens:** train, do, earn, learn, clean, pay · **To what, where:** university, work, more, much

<!-- .vabout -->
This is a sentence of the lesson «Why some jobs pay more» of the money course of Mova's primary school. The page gives its syntax tree — a dependency tree in the style of Universal Dependencies — and its pragmatics clause by clause: who acts (doctor, few people, doctors, lots), what happens, when and where, as Mova's frames read it from the tree.

## The tree {#tree}

```conllu
# sent_id = school:money:030-why-some-jobs-pay-more.lesson:1
# text = A doctor trains for 5 or 6 years at university and more after, and few people can do the work, so doctors earn more; lots of people can learn to clean in a few weeks, so cleaning pays less, though it matters just as much.
# source = school lesson (ours)
# course = money
# lesson = 030-why-some-jobs-pay-more.lesson
# annotation = Mova annot: Rust (en) → Haiku 5.5 (medium, Batches API) patches; gates UD 2.18; agreed by treeagree rules (Stanza, Trankit, spaCy trf): R5-strong ×3, R7-rel-agree ×1
1	A	a	DET	DT	Definite=Ind|PronType=Art	2	det	_	Agree=R5-strong|Haiku=3:det
2	doctor	doctor	NOUN	NN	Number=Sing	3	nsubj	_	_
3	trains	train	VERB	VBZ	Mood=Ind|Number=Sing|Person=3|Tense=Pres|VerbForm=Fin	0	root	_	_
4	for	for	ADP	IN	_	8	case	_	_
5	5	5	NUM	CD	NumForm=Digit|NumType=Card	8	nummod	_	_
6	or	or	CCONJ	CC	_	7	cc	_	_
7	6	6	NUM	CD	NumForm=Digit|NumType=Card	5	conj	_	_
8	years	year	NOUN	NNS	Number=Plur	3	obl	_	_
9	at	at	ADP	IN	_	10	case	_	_
10	university	university	NOUN	NN	Number=Sing	3	obl	_	Agree=R5-strong|Haiku=8:nmod
11	and	and	CCONJ	CC	_	13	cc	_	_
12	more	more	ADV	RBR	Degree=Cmp	13	advmod	_	_
13	after	after	ADP	IN	_	10	nmod	_	_
14	,	,	PUNCT	,	_	19	punct	_	_
15	and	and	CCONJ	CC	_	19	cc	_	_
16	few	few	ADJ	JJ	Degree=Pos	17	amod	_	_
17	people	people	NOUN	NNS	Number=Plur	19	nsubj	_	_
18	can	can	AUX	MD	VerbForm=Fin	19	aux	_	_
19	do	do	VERB	VB	VerbForm=Inf	3	conj	_	_
20	the	the	DET	DT	Definite=Def|PronType=Art	21	det	_	_
21	work	work	NOUN	NN	Number=Sing	19	obj	_	_
22	,	,	PUNCT	,	_	25	punct	_	_
23	so	so	ADV	RB	_	25	advmod	_	_
24	doctors	doctor	NOUN	NNS	Number=Plur	25	nsubj	_	_
25	earn	earn	VERB	VBP	Mood=Ind|Number=Plur|Person=3|Tense=Pres|VerbForm=Fin	19	parataxis	_	_
26	more	more	ADJ	JJR	Degree=Cmp	25	obj	_	Agree=R7-rel-agree|Haiku=25:advmod|HaikuPos=ADV:RBR:Degree=Cmp
27	;	;	PUNCT	:	_	28	punct	_	_
28	lots	lot	NOUN	NNS	Number=Plur	32	nsubj	_	Agree=R5-strong|Haiku=3:conj
29	of	of	ADP	IN	_	30	case	_	_
30	people	people	NOUN	NNS	Number=Plur	28	nmod	_	_
31	can	can	AUX	MD	VerbForm=Fin	32	aux	_	_
32	learn	learn	VERB	VB	VerbForm=Inf	3	conj	_	_
33	to	to	PART	TO	_	34	mark	_	_
34	clean	clean	VERB	VB	VerbForm=Inf	32	xcomp	_	_
35	in	in	ADP	IN	_	38	case	_	_
36	a	a	DET	DT	Definite=Ind|PronType=Art	38	det	_	_
37	few	few	ADJ	JJ	Degree=Pos	38	amod	_	_
38	weeks	week	NOUN	NNS	Number=Plur	34	obl	_	_
39	,	,	PUNCT	,	_	42	punct	_	_
40	so	so	ADV	RB	_	42	advmod	_	_
41	cleaning	clean	NOUN	NN	Number=Sing	42	nsubj	_	_
42	pays	pay	VERB	VBZ	Mood=Ind|Number=Sing|Person=3|Tense=Pres|VerbForm=Fin	34	parataxis	_	_
43	less	less	ADV	RBR	Degree=Cmp	42	advmod	_	_
44	,	,	PUNCT	,	_	47	punct	_	_
45	though	though	SCONJ	IN	_	47	mark	_	_
46	it	it	PRON	PRP	Case=Nom|Gender=Neut|Number=Sing|Person=3|PronType=Prs	47	nsubj	_	_
47	matters	matter	VERB	VBZ	Mood=Ind|Number=Sing|Person=3|Tense=Pres|VerbForm=Fin	42	advcl	_	_
48	just	just	ADV	RB	_	50	advmod	_	_
49	as	as	ADV	RB	_	50	advmod	_	_
50	much	much	ADJ	JJ	Degree=Pos	47	obj	_	_
51	.	.	PUNCT	.	_	3	punct	_	_
```

## Pragmatics {#pragmatics}

<!-- .note -->
No stored speech act for this sentence.

<!-- .fr -->
| # | verb | tense, mood | who | what, whom | to whom | where | when | other | roles by |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 1 | **train** | present | a doctor |  |  | university | year |  | vn hire-13.5.3 «NP V NP»: agent=Agent |
| 2 | **do** | can | few people | the work |  |  |  |  | vn act-114-1 «NP V NP»: agent=Agent work=Eventuality |
| 3 | **earn** | present | doctors | more |  |  |  |  | vn get-13.5.1-1 «NP V NP»: agent=Agent more=Theme |
| 4 | **learn** | can | lots of people |  |  |  |  |  | vn learn-14-2-1 «NP V that S»: agent=Agent clause=Topic |
| 5 | **clean** | to-infinitive | lots of people *not said here* |  |  |  | week |  | vn other\_cos-45.4 «NP.patient V»: agent=Patient |
| 6 | **pay** | present | cleaning |  |  |  |  | less *property* | vn pay-68-1 «NP V NP»: agent=Agent |
| 7 | **matter** | present | it | much |  |  |  |  | tree rules |

<!-- .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.

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**Licence: [CC BY-SA 4.0](https://creativecommons.org/licenses/by-sa/4.0/)**, as the whole of Mova corpus 0.4, of which this treebank (the agreed school, `mova-school-agreed-en.conllu`) is part. The lessons were written for Mova's primary school. Sentence `school:money:030-why-some-jobs-pay-more.lesson:1`.

**The tree:** Mova annot: Rust (en) → Haiku 5.5 (medium, Batches API) patches; gates UD 2.18; agreed by treeagree rules (Stanza, Trankit, spaCy trf): R5-strong ×3, R7-rel-agree ×1. **The frames** are read from the tree by Mova's frames reader (`prag`) when this page is built, the lesson read in order, so a pronoun may be resolved from an earlier sentence.

See the [release 0.4](https://md.mova.elamur.ai/free/en/releases/0.4/).

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