---
title: Horses carried soldiers for thousands of years, millions died in the… — Horses, cattle, camels and chickens: how people… · tree and pragmatics
description: Horses carried soldiers for thousands of years, millions died in the First World War, and a memorial in London remembers animals in war, including dogs and pigeons that carried messages. Who acts: Horses, millions, memorial, dogs. A sentence of the lesson «Horses, cattle, camels and chickens: how pe
---

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# Horses, cattle, camels and chickens: how people tamed animals, sentence 18

<!-- .ven lang=en -->
Horses carried soldiers for thousands of years, millions died in the First World War, and a memorial in London remembers animals in war, including dogs and pigeons that carried messages.

<!-- .vintro -->
**Who acts:** Horses, millions, memorial, dogs · **What happens:** carry, die, remember · **To what, where:** soldiers, animals, war, messages

<!-- .vabout -->
This is a sentence of the lesson «Horses, cattle, camels and chickens: how people tamed animals» of the biology 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 (Horses, millions, memorial, dogs), what happens, when and where, as Mova's frames read it from the tree.

## The tree {#tree}

```conllu
# sent_id = school:biology:293-horses-cattle-camels-and-chickens-how-people-tamed-animals.lesson:18
# text = Horses carried soldiers for thousands of years, millions died in the First World War, and a memorial in London remembers animals in war, including dogs and pigeons that carried messages.
# source = school lesson (ours)
# course = biology
# lesson = 293-horses-cattle-camels-and-chickens-how-people-tamed-animals.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): R1-cc-next ×2, R5-strong ×1, R6-punct-agree ×3
1	Horses	horse	NOUN	NNS	Number=Plur	2	nsubj	_	_
2	carried	carry	VERB	VBD	Mood=Ind|Number=Plur|Person=3|Tense=Past|VerbForm=Fin	10	conj	_	_
3	soldiers	soldier	NOUN	NNS	Number=Plur	2	obj	_	_
4	for	for	ADP	IN	_	5	case	_	_
5	thousands	thousand	NOUN	NNS	Number=Plur	2	obl	_	_
6	of	of	ADP	IN	_	7	case	_	_
7	years	year	NOUN	NNS	Number=Plur	5	nmod	_	_
8	,	,	PUNCT	,	_	10	punct	_	Agree=R6-punct-agree|Haiku=3:punct
9	millions	million	NOUN	NNS	Number=Plur	10	nsubj	_	_
10	died	die	VERB	VBD	Mood=Ind|Number=Plur|Person=3|Tense=Past|VerbForm=Fin	0	root	_	_
11	in	in	ADP	IN	_	15	case	_	_
12	the	the	DET	DT	Definite=Def|PronType=Art	15	det	_	_
13	First	First	PROPN	NNP	Number=Sing|NumForm=Word	15	amod	_	_
14	World	World	PROPN	NNP	Number=Sing	15	compound	_	_
15	War	War	PROPN	NNP	Number=Sing	10	obl	_	_
16	,	,	PUNCT	,	_	22	punct	_	Agree=R6-punct-agree|Haiku=19:punct
17	and	and	CCONJ	CC	_	22	cc	_	Agree=R1-cc-next|Haiku=10:cc
18	a	a	DET	DT	Definite=Ind|PronType=Art	19	det	_	_
19	memorial	memorial	NOUN	NN	Number=Sing	22	nsubj	_	_
20	in	in	ADP	IN	_	21	case	_	_
21	London	London	PROPN	NNP	Number=Sing	19	nmod	_	_
22	remembers	remember	VERB	VBZ	Mood=Ind|Number=Sing|Person=3|Tense=Pres|VerbForm=Fin	10	conj	_	_
23	animals	animal	NOUN	NNS	Number=Plur	22	obj	_	_
24	in	in	ADP	IN	_	25	case	_	_
25	war	war	NOUN	NN	Number=Sing	23	nmod	_	_
26	,	,	PUNCT	,	_	28	punct	_	_
27	including	include	ADP	IN	_	28	case	_	_
28	dogs	dog	NOUN	NNS	Number=Plur	23	conj	_	_
29	and	and	CCONJ	CC	_	30	cc	_	Agree=R1-cc-next|Haiku=28:cc
30	pigeons	pigeon	NOUN	NNS	Number=Plur	28	conj	_	_
31	that	that	PRON	WDT	PronType=Rel	32	nsubj	_	_
32	carried	carry	VERB	VBD	Mood=Ind|Number=Plur|Person=3|Tense=Past|VerbForm=Fin	28	acl:relcl	_	Agree=R5-strong|Haiku=30:acl:relcl
33	messages	message	NOUN	NNS	Number=Plur	32	obj	_	_
34	.	.	PUNCT	.	_	2	punct	_	Agree=R6-punct-agree|Haiku=10:punct
```

## Pragmatics {#pragmatics}

<!-- sa -->
- form: statement
- act: assert
- voice: narrator
- polarity: none
- teacher: changed polarity=none

<!-- .fr -->
| # | verb | tense, mood | who | what, whom | to whom | where | when | other | roles by |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 1 | **carry** | past | Horses | soldiers |  |  |  | for thousands of years | vn carry-11.4 «NP V NP»: agent=Agent soldier=Theme |
| 2 | **die** | past | millions |  |  |  |  | in the First World War | vn calibratable\_cos-45.6.1 «NP.patient V PP.attribute»: agent=Patient in war=Attribute |
| 3 | **remember** | present | a memorial in London | animals and dogs and pigeons |  | war |  |  | vn characterize-29.2-1-1 «NP V NP S\_ING»: agent=Agent animal=Theme |
| 4 | **carry** | past | dogs and pigeons | messages |  |  |  |  | vn carry-11.4 «NP V NP»: agent=Agent message=Theme |

<!-- .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:biology:293-horses-cattle-camels-and-chickens-how-people-tamed-animals.lesson:18`.

**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): R1-cc-next ×2, R5-strong ×1, R6-punct-agree ×3. **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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