---
title: Which of the following statements most accurately characterises the… — How a language model learns: guessing… · tree and pragmatics
description: Which of the following statements most accurately characterises the term "large language model"? Exam question 1 of lesson 2 «How a language model learns: guessing the next word» of the AI course of Mova's primary school, with the dependency tree and pragmatics of the question and of each option; Mo
---

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# Exam question 1 · How a language model learns: guessing the next word

<!-- .ven lang=en -->
Which of the following statements most accurately characterises the term "large language model"?

<!-- .vintro -->
**Mova's choice:** option 1 · **The right answer:** option 1 · right ✓ · **What happens:** follow, characteris · **To what, where:** term

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This is exam question 1 of lesson 2 «How a language model learns: guessing the next word» of the AI 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/ai/2-guessing-the-next-word/#e1).

## The question {#question}

```conllu
# sent_id = question:ai:2-guessing-the-next-word:e1:1
# text = Which of the following statements most accurately characterises the term "large language model"?
1	Which	which	PRON	WDT	PronType=Rel	8	nsubj	_	_
2	of	of	ADP	IN	_	5	case	_	_
3	the	the	DET	DT	Definite=Def|PronType=Art	5	det	_	_
4	following	follow	VERB	VBG	VerbForm=Ger	5	amod	_	_
5	statements	statement	NOUN	NNS	Number=Plur	8	obl	_	_
6	most	most	ADV	RBS	Degree=Sup	7	advmod	_	_
7	accurately	accurately	ADV	RB	_	8	advmod	_	_
8	characterises	characteris	VERB	VBZ	Mood=Ind|Number=Sing|Person=3|Tense=Pres|VerbForm=Fin	0	root	_	_
9	the	the	DET	DT	Definite=Def|PronType=Art	10	det	_	_
10	term	term	NOUN	NN	Number=Sing	8	obj	_	_
11	"	"	PUNCT	``	_	14	punct	_	SpaceAfter=No
12	large	large	ADJ	JJ	Degree=Pos	14	amod	_	_
13	language	language	NOUN	NN	Number=Sing	14	compound	_	_
14	model	model	NOUN	NN	Number=Sing	10	appos	_	SpaceAfter=No
15	"	"	PUNCT	''	_	14	punct	_	SpaceAfter=No
16	?	?	PUNCT	.	_	8	punct	_	_
```

<!-- .fr -->
| # | verb | tense, mood | who | what, whom | to whom | where | when | other | roles by |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 1 | **follow** | gerund |  |  |  |  |  |  | vn occur-48.3-1 «NP V»: agent=Theme |
| 2 | **characteris** | present |  | the term |  |  |  | of the following statements; accurately *property* | 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.

## The options {#options}

### Option 1 · ← Mova's choice · ✓ the right answer {#o1}

<!-- .ven lang=en -->
A very extensive program that has acquired the patterns of written language

```conllu
# sent_id = question:ai:2-guessing-the-next-word:e1:o1:1
# text = A very extensive program that has acquired the patterns of written language
1	A	a	DET	DT	Definite=Ind|PronType=Art	4	det	_	_
2	very	very	ADV	RB	_	3	advmod	_	_
3	extensive	extensive	ADJ	JJ	Degree=Pos	4	amod	_	_
4	program	program	NOUN	NN	Number=Sing	0	root	_	_
5	that	that	PRON	WDT	PronType=Rel	7	nsubj:pass	_	_
6	has	have	AUX	VBZ	Mood=Ind|Number=Sing|Person=3|Tense=Pres|VerbForm=Fin	7	aux	_	_
7	acquired	acquire	VERB	VBN	Tense=Past|VerbForm=Part|Voice=Pass	4	acl:relcl	_	_
8	the	the	DET	DT	Definite=Def|PronType=Art	9	det	_	_
9	patterns	pattern	NOUN	NNS	Number=Plur	7	obj	_	_
10	of	of	ADP	IN	_	12	case	_	_
11	written	write	VERB	VBN	Tense=Past|VerbForm=Part|Voice=Pass	12	amod	_	_
12	language	language	NOUN	NN	Number=Sing	9	nmod	_	_
```

<!-- .fr -->
| # | verb | tense, mood | who | what, whom | to whom | where | when | other | roles by |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 1 | **acquire** | present · perfect · passive |  | a extensive program |  |  |  |  | tree rules |
| 2 | **write** | participle |  |  |  |  |  |  | vn scribble-25.2-1 «NP V»: agent=Agent |
| 3 | **pattern** |  | written language |  |  |  |  |  | nom pattern «cognition intransitive»: of=agent |

### Option 2 {#o2}

<!-- .ven lang=en -->
A dictionary of exceptional size printed upon paper

```conllu
# sent_id = question:ai:2-guessing-the-next-word:e1:o2:1
# text = A dictionary of exceptional size printed upon paper
1	A	a	DET	DT	Definite=Ind|PronType=Art	2	det	_	_
2	dictionary	dictionary	NOUN	NN	Number=Sing	0	root	_	_
3	of	of	ADP	IN	_	5	case	_	_
4	exceptional	exceptional	ADJ	JJ	Degree=Pos	5	amod	_	_
5	size	size	NOUN	NN	Number=Sing	2	nmod	_	_
6	printed	print	VERB	VBN	Tense=Past|VerbForm=Part|Voice=Pass	2	acl	_	_
7	upon	upon	ADP	IN	_	8	case	_	_
8	paper	paper	NOUN	NN	Number=Sing	6	obl	_	_
```

<!-- .fr -->
| # | verb | tense, mood | who | what, whom | to whom | where | when | other | roles by |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 1 | **print** | participle |  | a dictionary of exceptional size *not said here* |  |  |  | upon paper | vn scribble-25.2-1 «NP V»: agent=Agent |

### Option 3 {#o3}

<!-- .ven lang=en -->
A physical model of the human organs of speech

```conllu
# sent_id = question:ai:2-guessing-the-next-word:e1:o3:1
# text = A physical model of the human organs of speech
1	A	a	DET	DT	Definite=Ind|PronType=Art	3	det	_	_
2	physical	physical	ADJ	JJ	Degree=Pos	3	amod	_	_
3	model	model	NOUN	NN	Number=Sing	0	root	_	_
4	of	of	ADP	IN	_	7	case	_	_
5	the	the	DET	DT	Definite=Def|PronType=Art	7	det	_	_
6	human	human	ADJ	JJ	Degree=Pos	7	amod	_	_
7	organs	organ	NOUN	NNS	Number=Plur	3	nmod	_	_
8	of	of	ADP	IN	_	9	case	_	_
9	speech	speech	NOUN	NN	Number=Sing	7	nmod	_	_
```

<!-- .fr -->
| # | verb | tense, mood | who | what, whom | to whom | where | when | other | roles by |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 1 | **model** |  |  | the human organs of speech |  |  |  |  | nom model «cognition transitive»: of=patient |

### Option 4 {#o4}

<!-- .ven lang=en -->
A person of great stature who is fluent in many languages

```conllu
# sent_id = question:ai:2-guessing-the-next-word:e1:o4:1
# text = A person of great stature who is fluent in many languages
1	A	a	DET	DT	Definite=Ind|PronType=Art	2	det	_	_
2	person	person	NOUN	NN	Number=Sing	8	nsubj	_	_
3	of	of	ADP	IN	_	5	case	_	_
4	great	great	ADJ	JJ	Degree=Pos	5	amod	_	_
5	stature	stature	NOUN	NN	Number=Sing	2	nmod	_	_
6	who	who	PRON	WP	PronType=Rel	8	nsubj	_	_
7	is	be	AUX	VBZ	Mood=Ind|Number=Sing|Person=3|Tense=Pres|VerbForm=Fin	8	cop	_	_
8	fluent	fluent	ADJ	JJ	Degree=Pos	0	root	_	_
9	in	in	ADP	IN	_	11	case	_	_
10	many	many	ADJ	JJ	Degree=Pos	11	amod	_	_
11	languages	language	NOUN	NNS	Number=Plur	8	obl	_	_
```

<!-- .fr -->
| # | verb | tense, mood | who | what, whom | to whom | where | when | other | roles by |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 1 | **is** | present | a person of great stature |  |  | many languages |  | fluent *property* | tree rules |

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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.

<!-- /div -->

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- ← previous: [How a language model learns: guessing…, test 10](https://md.mova.elamur.ai/free/en/corpora/questions/ai/2-guessing-the-next-word/t10/)
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