---
title: A language model learned by predicting missing or next words in enor… — How a language model learns: guessing the next w… · tree and pragmatics
description: A language model learned by predicting missing or next words in enormous amounts of text. A sentence of the lesson «How a language model learns: guessing the next word» of the ai course of Mova's primary school with its dependency tree and the pragmatics of every clause.
---

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# How a language model learns: guessing the next word, sentence 7

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A language model learned by predicting missing or next words in enormous amounts of text.

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**What happens:** learn, predict, amount · **To what, where:** language model, missing words, enormous amounts, text

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This is a sentence of the lesson «How a language model learns: guessing the next word» 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: what happens, when and where, as Mova's frames read it from the tree.

## The tree {#tree}

```conllu
# sent_id = school:ai:002-guessing-the-next-word.lesson:7
# text = A language model learned by predicting missing or next words in enormous amounts of text.
# source = school lesson (ours)
# course = ai
# lesson = 002-guessing-the-next-word.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 ×1
1	A	a	DET	DT	Definite=Ind|PronType=Art	3	det	_	_
2	language	language	NOUN	NN	Number=Sing	3	compound	_	_
3	model	model	NOUN	NN	Number=Sing	4	nsubj:pass	_	_
4	learned	learn	VERB	VBN	Tense=Past|VerbForm=Part|Voice=Pass	0	root	_	_
5	by	by	SCONJ	IN	_	6	mark	_	_
6	predicting	predict	VERB	VBG	Tense=Pres|VerbForm=Part	4	advcl	_	_
7	missing	missing	ADJ	JJ	Degree=Pos	10	amod	_	_
8	or	or	CCONJ	CC	_	9	cc	_	_
9	next	next	ADJ	JJ	Degree=Pos	7	conj	_	_
10	words	word	NOUN	NNS	Number=Plur	6	obj	_	_
11	in	in	ADP	IN	_	13	case	_	_
12	enormous	enormous	ADJ	JJ	Degree=Pos	13	amod	_	_
13	amounts	amount	NOUN	NNS	Number=Plur	6	obl	_	Agree=R5-strong|Haiku=10:nmod
14	of	of	ADP	IN	_	15	case	_	_
15	text	text	NOUN	NN	Number=Sing	13	nmod	_	_
16	.	.	PUNCT	.	_	4	punct	_	_
```

## Pragmatics {#pragmatics}

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No stored speech act for this sentence.

<!-- .fr -->
| # | verb | tense, mood | who | what, whom | to whom | where | when | other | roles by |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 1 | **learn** | participle · passive |  | a language model |  |  |  |  | vn learn-14-2-1 «NP V NP»: subject=Topic |
| 2 | **predict** | gerund |  | missing words |  | enormous amounts of text |  |  | vn indicate-78 «NP V NP»: agent=Pivot word=Topic |
| 3 | **amount** |  |  | text |  |  |  |  | nom amount «possession transitive»: of=patient |

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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:002-guessing-the-next-word.lesson:7`.

**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 ×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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