---
title: AI helped scientists predict the shapes of proteins, the tiny buildi… — Worries and hopes: climate, the UN, space, AI, a… · tree and pragmatics
description: AI helped scientists predict the shapes of proteins, the tiny building parts of every living thing, work that won a Nobel Prize in 2024; people also worry about jobs, fake videos and safety. Who acts: AI, scientists, work, people. A sentence of the lesson «Worries and hopes: climate, the UN, space, 
---

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# Worries and hopes: climate, the UN, space, AI, and is the world getting better?, sentence 12

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AI helped scientists predict the shapes of proteins, the tiny building parts of every living thing, work that won a Nobel Prize in 2024; people also worry about jobs, fake videos and safety.

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**Who acts:** AI, scientists, work, people · **What happens:** help, predict, win, worry · **To what, where:** scientists, shapes, Nobel Prize, 2024

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This is a sentence of the lesson «Worries and hopes: climate, the UN, space, AI, and is the world getting better?» of the history 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 (AI, scientists, work, people), what happens, when and where, as Mova's frames read it from the tree.

## The tree {#tree}

```conllu
# sent_id = school:history:079-worries-and-hopes-is-the-world-getting-better.lesson:12
# text = AI helped scientists predict the shapes of proteins, the tiny building parts of every living thing, work that won a Nobel Prize in 2024; people also worry about jobs, fake videos and safety.
# source = school lesson (ours)
# course = history
# lesson = 079-worries-and-hopes-is-the-world-getting-better.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): R7-rel-agree ×1, R8-pos-agree ×1
1	AI	ai	NOUN	NN	Number=Sing	2	nsubj	_	Agree=R8-pos-agree|Haiku=2:nsubj|HaikuPos=PROPN:NNP:Number=Sing
2	helped	help	VERB	VBD	Tense=Past|VerbForm=Fin	0	root	_	_
3	scientists	scientist	NOUN	NNS	Number=Plur	2	obj	_	_
4	predict	predict	VERB	VB	VerbForm=Inf	2	xcomp	_	_
5	the	the	DET	DT	Definite=Def|PronType=Art	6	det	_	_
6	shapes	shape	NOUN	NNS	Number=Plur	4	obj	_	_
7	of	of	ADP	IN	_	8	case	_	_
8	proteins	protein	NOUN	NNS	Number=Plur	6	nmod	_	_
9	,	,	PUNCT	,	_	13	punct	_	_
10	the	the	DET	DT	Definite=Def|PronType=Art	13	det	_	_
11	tiny	tiny	ADJ	JJ	Degree=Pos	13	amod	_	_
12	building	building	NOUN	NN	Number=Sing	13	compound	_	_
13	parts	part	NOUN	NNS	Number=Plur	8	appos	_	_
14	of	of	ADP	IN	_	17	case	_	_
15	every	every	DET	DT	PronType=Tot	17	det	_	_
16	living	living	NOUN	NN	Number=Sing	17	compound	_	_
17	thing	thing	NOUN	NN	Number=Sing	13	nmod	_	_
18	,	,	PUNCT	,	_	19	punct	_	_
19	work	work	NOUN	NN	Number=Sing	17	nmod	_	_
20	that	that	PRON	WDT	PronType=Rel	21	nsubj	_	_
21	won	win	VERB	VBD	Mood=Ind|Number=Sing|Person=3|Tense=Past|VerbForm=Fin	19	acl:relcl	_	_
22	a	a	DET	DT	Definite=Ind|PronType=Art	24	det	_	_
23	Nobel	Nobel	PROPN	NNP	Number=Sing	24	compound	_	_
24	Prize	Prize	PROPN	NNP	Number=Sing	21	obj	_	_
25	in	in	ADP	IN	_	26	case	_	_
26	2024	2024	NUM	CD	NumForm=Digit|NumType=Card	21	obl	_	_
27	;	;	PUNCT	:	_	30	punct	_	_
28	people	people	NOUN	NNS	Number=Plur	30	nsubj	_	_
29	also	also	ADV	RB	_	30	advmod	_	_
30	worry	worry	VERB	VBP	Mood=Ind|Number=Plur|Person=3|Tense=Pres|VerbForm=Fin	2	parataxis	_	Agree=R7-rel-agree|Haiku=2:conj
31	about	about	ADP	IN	_	32	case	_	_
32	jobs	job	NOUN	NNS	Number=Plur	30	obl	_	_
33	,	,	PUNCT	,	_	35	punct	_	_
34	fake	fake	ADJ	JJ	Degree=Pos	35	amod	_	_
35	videos	video	NOUN	NNS	Number=Plur	32	conj	_	_
36	and	and	CCONJ	CC	_	37	cc	_	_
37	safety	safety	NOUN	NN	Number=Sing	32	conj	_	_
38	.	.	PUNCT	.	_	2	punct	_	_
```

## Pragmatics {#pragmatics}

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

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| # | verb | tense, mood | who | what, whom | to whom | where | when | other | roles by |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 1 | **help** | past | AI | scientists |  |  |  |  | vn help-72.1-1-1 «NP V NP S\_INF»: agent=Agent scientist=Beneficiary clause=Theme |
| 2 | **predict** | infinitive | scientists *not said here* | the shapes of proteins |  |  |  |  | vn indicate-78 «NP V NP»: agent=Pivot shape=Topic |
| 3 | **win** | past | work | a Nobel Prize |  | 2024 |  |  | vn succeed-74-2 «NP V NP»: agent=Agent prize=Eventuality |
| 4 | **worry** | present | people |  |  |  |  | about jobs and fake videos and safety | vn care-88.1-1 «NP V PP.stimulus what S»: agent=Experiencer about job=Stimulus |

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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:history:079-worries-and-hopes-is-the-world-getting-better.lesson:12`.

**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): R7-rel-agree ×1, R8-pos-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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- next →: [Worries and hopes: climate, the UN, sp…, 13](https://md.mova.elamur.ai/free/en/corpora/school/history/79-worries-and-hopes-is-the-world-getting-better/13/)
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