---
title: Weather forecasts use computer models and AI to make good guesses, b… — Counting the AI in one ordinary day · tree and pragmatics
description: Weather forecasts use computer models and AI to make good guesses, but weather is hard to predict, so forecasts are not promises. Who acts: Weather forecasts, weather, forecasts. A sentence of the lesson «Counting the AI in one ordinary day» of the ai course of Mova's primary school with its depende
---

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# Counting the AI in one ordinary day, sentence 9

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Weather forecasts use computer models and AI to make good guesses, but weather is hard to predict, so forecasts are not promises.

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**Who acts:** Weather forecasts, weather, forecasts · **What happens:** use, make, be, predict, not be · **To what, where:** computer models, good guesses, promises

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This is a sentence of the lesson «Counting the AI in one ordinary day» of the ai 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 (Weather forecasts, weather, forecasts), what happens, when and where, as Mova's frames read it from the tree.

## The tree {#tree}

```conllu
# sent_id = school:ai:019-ai-in-one-ordinary-day.lesson:9
# text = Weather forecasts use computer models and AI to make good guesses, but weather is hard to predict, so forecasts are not promises.
# source = school lesson (ours)
# course = ai
# lesson = 019-ai-in-one-ordinary-day.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 ×2
1	Weather	weather	NOUN	NN	Number=Sing	2	compound	_	_
2	forecasts	forecast	NOUN	NNS	Number=Plur	3	nsubj	_	_
3	use	use	VERB	VBP	Mood=Ind|Number=Plur|Person=3|Tense=Pres|VerbForm=Fin	0	root	_	_
4	computer	computer	NOUN	NN	Number=Sing	5	compound	_	_
5	models	model	NOUN	NNS	Number=Plur	3	obj	_	_
6	and	and	CCONJ	CC	_	7	cc	_	_
7	AI	ai	NOUN	NN	Number=Sing	5	conj	_	_
8	to	to	PART	TO	_	9	mark	_	_
9	make	make	VERB	VB	VerbForm=Inf	3	advcl	_	_
10	good	good	ADJ	JJ	Degree=Pos	11	amod	_	_
11	guesses	guess	NOUN	NNS	Number=Plur	9	obj	_	_
12	,	,	PUNCT	,	_	16	punct	_	_
13	but	but	CCONJ	CC	_	16	cc	_	_
14	weather	weather	NOUN	NN	Number=Sing	16	nsubj	_	_
15	is	be	AUX	VBZ	Mood=Ind|Number=Sing|Person=3|Tense=Pres|VerbForm=Fin	16	cop	_	_
16	hard	hard	ADJ	JJ	Degree=Pos	3	conj	_	_
17	to	to	PART	TO	_	18	mark	_	_
18	predict	predict	VERB	VB	VerbForm=Inf	16	ccomp	_	Agree=R7-rel-agree|Haiku=16:xcomp
19	,	,	PUNCT	,	_	24	punct	_	_
20	so	so	ADV	RB	_	24	advmod	_	Agree=R7-rel-agree|Haiku=24:cc|HaikuPos=CCONJ:CC:_
21	forecasts	forecast	NOUN	NNS	Number=Plur	24	nsubj	_	_
22	are	be	AUX	VBP	Mood=Ind|Number=Plur|Person=3|Tense=Pres|VerbForm=Fin	24	cop	_	_
23	not	not	PART	RB	Polarity=Neg	24	advmod	_	_
24	promises	promise	NOUN	NNS	Number=Plur	3	conj	_	_
25	.	.	PUNCT	.	_	3	punct	_	_
```

## Pragmatics {#pragmatics}

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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 | **use** | present | Weather forecasts | computer models and AI |  |  |  |  | vn eat-39.1 «NP V NP»: agent=Agent model=Patient |
| 2 | **make** | to-infinitive | Weather forecasts *not said here* | good guesses |  |  |  |  | vn build-26.1-1 «NP.asset V NP»: agent=Asset guess=Product |
| 3 | **is** | present | weather |  |  |  |  | hard *property* | tree rules |
| 4 | **predict** | to-infinitive | weather *not said here* |  |  |  |  |  | vn indicate-78 «NP V how S»: agent=Pivot |
| 5 | **not** **is a** | present | forecasts | promises |  |  |  |  | tree rules |

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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:ai:019-ai-in-one-ordinary-day.lesson:9`.

**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 ×2. **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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