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propensity

Who acts: natural habit, propensity, dog, She, metals, made people · What happens: behave, tell, get, lose, have, chew · To what, where: certain way, jokes, propensity, socks, trouble, sunny spots · Speech: someone speaks here

«propensity» in the school dictionary: its meaning for a pupil and its 6 examples, every sentence parsed by Mova itself — its syntax tree, a dependency tree in the style of Universal Dependencies, and its pragmatics clause by clause. The word in the dictionary, with its sense in the lessons: propensity in the school dictionary.

Meaning 1

Usage: formal — kept apart, not parsed.

A natural habit of behaving in a certain way, a tendency: «a propensity to tell jokes», «a propensity for getting lost».

The tree, 21 words

The words, one row each (CoNLL-U)

#	word	lemma	UPOS	features	head	relation
1	A	a	DET	Definite=Ind PronType=Art	3 habit	det
2	natural	natural	ADJ	Degree=Pos	3 habit	amod
3	habit	habit	NOUN	Number=Sing	root	root
4	of	of	SCONJ	_	5 behaving	mark
5	behaving	behave	VERB	VerbForm=Ger	3 habit	acl
6	in	in	ADP	_	9 way	case
7	a	a	DET	Definite=Ind PronType=Art	9 way	det
8	certain	certain	ADJ	Degree=Pos	9 way	amod
9	way	way	NOUN	Number=Sing	5 behaving	obl
10	,	,	PUNCT	_	12 tendency	punct
11	a	a	DET	Definite=Ind PronType=Art	12 tendency	det
12	tendency	tendency	NOUN	Number=Sing	9 way	conj
13	:	:	PUNCT	_	16 propensity	punct
14	«	«	PUNCT	_	16 propensity	punct
15	a	a	DET	Definite=Ind PronType=Art	16 propensity	det
16	propensity	propensity	NOUN	Number=Sing	3 habit	conj
17	to	to	PART	_	18 tell	mark
18	tell	tell	VERB	VerbForm=Inf	16 propensity	acl
19	jokes	joke	NOUN	Number=Plur	18 tell	obj
20	»	»	PUNCT	_	16 propensity	punct
21	,	,	PUNCT	_	24 propensity	punct
22	«	«	PUNCT	_	24 propensity	punct
23	a	a	DET	Definite=Ind PronType=Art	24 propensity	det
24	propensity	propensity	NOUN	Number=Sing	16 propensity	conj
25	for	for	SCONJ	_	26 getting	mark
26	getting	get	VERB	VerbForm=Ger	24 propensity	acl
27	lost	lose	VERB	Tense=Past VerbForm=Part Voice=Pass	26 getting	xcomp
28	»	»	PUNCT	_	27 lost	punct
29	.	.	PUNCT	_	3 habit	punct

#	verb	tense, mood	who	what, whom	to whom	where	when	other	roles by
1	behave	gerund	a natural habit and a propensity and a propensity not said here			a certain way and a tendency			vn masquerade-29.6-1 «NP V PP.attribute»: agent=Agent
2	tell speech: assert in a quote	to-infinitive		jokes					vn transfer_mesg-37.1.1-1-1 «NP V NP.recipient»: agent=Agent joke=Recipient
3	get in a quote	gerund	a propensity not said here						vn comprehend-87.2-1 «NP V S_ING»: agent=Experiencer clause=Stimulus
4	lose in a quote	participle	a propensity not said here						vn succeed-74-3-1 «NP V»: agent=Agent

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.

Example 1

My dog has a propensity to chew socks.

The words, one row each (CoNLL-U)

#	word	lemma	UPOS	features	head	relation
1	My	my	PRON	Case=Gen Number=Sing Person=1 Poss=Yes PronType=Prs	2 dog	nmod:poss
2	dog	dog	NOUN	Number=Sing	3 has	nsubj
3	has	have	VERB	Mood=Ind Number=Sing Person=3 Tense=Pres VerbForm=Fin	root	root
4	a	a	DET	Definite=Ind PronType=Art	5 propensity	det
5	propensity	propensity	NOUN	Number=Sing	3 has	obj
6	to	to	PART	_	7 chew	mark
7	chew	chew	VERB	VerbForm=Inf	5 propensity	acl
8	socks	sock	NOUN	Number=Plur	7 chew	obj
9	.	.	PUNCT	_	3 has	punct

#	verb	tense, mood	who	what, whom	to whom	where	when	other	roles by
1	have	present	My dog	a propensity					vn birth-28.2-1 «NP V NP»: agent=Agent propensity=Patient
2	chew	to-infinitive	My dog not said here	socks					vn chew-39.2 «NP V NP»: agent=Agent sock=Patient

Example 2

She has a propensity for getting into trouble.

The words, one row each (CoNLL-U)

#	word	lemma	UPOS	features	head	relation
1	She	she	PRON	Case=Nom Gender=Fem Number=Sing Person=3 PronType=Prs	2 has	nsubj
2	has	have	VERB	Mood=Ind Number=Sing Person=3 Tense=Pres VerbForm=Fin	root	root
3	a	a	DET	Definite=Ind PronType=Art	4 propensity	det
4	propensity	propensity	NOUN	Number=Sing	2 has	obj
5	for	for	SCONJ	_	6 getting	mark
6	getting	get	VERB	VerbForm=Ger	4 propensity	acl
7	into	into	ADP	_	8 trouble	case
8	trouble	trouble	NOUN	Number=Sing	6 getting	obl
9	.	.	PUNCT	_	2 has	punct

#	verb	tense, mood	who	what, whom	to whom	where	when	other	roles by
1	have	present	She	a propensity					vn birth-28.2-1 «NP V NP»: agent=Agent propensity=Patient
2	get	gerund	a propensity not said here			trouble			vn escape-51.1 «NP V PP.destination»: agent=Theme into trouble=Destination

Example 3

Some metals have a propensity to rust.

The words, one row each (CoNLL-U)

#	word	lemma	UPOS	features	head	relation
1	Some	some	DET	PronType=Ind	2 metals	det
2	metals	metal	NOUN	Number=Plur	3 have	nsubj
3	have	have	VERB	Mood=Ind Number=Plur Person=3 Tense=Pres VerbForm=Fin	root	root
4	a	a	DET	Definite=Ind PronType=Art	5 propensity	det
5	propensity	propensity	NOUN	Number=Sing	3 have	obj
6	to	to	PART	_	7 rust	mark
7	rust	rust	VERB	VerbForm=Inf	5 propensity	acl
8	.	.	PUNCT	_	3 have	punct

#	verb	tense, mood	who	what, whom	to whom	where	when	other	roles by
1	have	present	some metals	a propensity					vn birth-28.2-1 «NP V NP»: agent=Agent propensity=Patient
2	rust	to-infinitive	some metals not said here	a propensity not said here					vn entity_specific_cos-45.5 «NP.patient V»: agent=Patient

Example 4

His propensity to exaggerate made people doubt him.

The words, one row each (CoNLL-U)

#	word	lemma	UPOS	features	head	relation
1	His	his	PRON	Case=Gen Gender=Masc Number=Sing Person=3 Poss=Yes PronType=Prs	2 propensity	nmod:poss
2	propensity	propensity	NOUN	Number=Sing	4 exaggerate	nsubj
3	to	to	PART	_	4 exaggerate	mark
4	exaggerate	exaggerate	VERB	VerbForm=Inf	root	root
5	made	make	VERB	Tense=Past VerbForm=Part Voice=Pass	6 people	amod
6	people	people	NOUN	Number=Plur	7 doubt	nsubj
7	doubt	doubt	VERB	Mood=Ind Number=Plur Person=3 Tense=Pres VerbForm=Fin	4 exaggerate	ccomp
8	him	he	PRON	Case=Acc Gender=Masc Number=Sing Person=3 PronType=Prs	7 doubt	obj
9	.	.	PUNCT	_	4 exaggerate	punct

#	verb	tense, mood	who	what, whom	to whom	where	when	other	roles by
1	exaggerate	to-infinitive	His propensity						tree rules
2	make	participle							vn build-26.1-1 «NP.asset V NP»: agent=Asset
3	doubt	present	made people	propensity					vn judgment-33.1-1-1 «NP V NP»: agent=Agent he=Theme

Example 5

Cats have a propensity for sleeping in sunny spots.

The words, one row each (CoNLL-U)

#	word	lemma	UPOS	features	head	relation
1	Cats	cat	NOUN	Number=Plur	2 have	nsubj
2	have	have	VERB	Mood=Ind Number=Plur Person=3 Tense=Pres VerbForm=Fin	root	root
3	a	a	DET	Definite=Ind PronType=Art	4 propensity	det
4	propensity	propensity	NOUN	Number=Sing	2 have	obj
5	for	for	SCONJ	_	6 sleeping	mark
6	sleeping	sleep	VERB	Tense=Pres VerbForm=Part	2 have	advcl
7	in	in	ADP	_	9 spots	case
8	sunny	sunny	ADJ	Degree=Pos	9 spots	amod
9	spots	spot	NOUN	Number=Plur	6 sleeping	obl
10	.	.	PUNCT	_	2 have	punct

#	verb	tense, mood	who	what, whom	to whom	where	when	other	roles by
1	have	present	Cats	a propensity					vn birth-28.2-1 «NP V NP»: agent=Agent propensity=Patient
2	sleep	gerund	Cats not said here			sunny spots			vn fit-54.3 «NP V NP PP.location»: agent=Agent in spot=Location

Example 6

This rope has a propensity to tangle.

The words, one row each (CoNLL-U)

#	word	lemma	UPOS	features	head	relation
1	This	this	DET	Number=Sing PronType=Dem	2 rope	det
2	rope	rope	NOUN	Number=Sing	3 has	nsubj
3	has	have	VERB	Mood=Ind Number=Sing Person=3 Tense=Pres VerbForm=Fin	root	root
4	a	a	DET	Definite=Ind PronType=Art	5 propensity	det
5	propensity	propensity	NOUN	Number=Sing	3 has	obj
6	to	to	PART	_	7 tangle	mark
7	tangle	tangle	VERB	VerbForm=Inf	5 propensity	acl
8	.	.	PUNCT	_	3 has	punct

#	verb	tense, mood	who	what, whom	to whom	where	when	other	roles by
1	have	present	this rope	a propensity					vn birth-28.2-1 «NP V NP»: agent=Agent propensity=Patient
2	tangle	to-infinitive	this rope not said here	a propensity not said here					tree rules

Text: the school dictionary of Mova's schools (world/data/dictionary-schools/), written for Mova. 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 meaning and example read on its own. Elamur Cosmic License.

This page in Markdown → https://md.mova.elamur.ai/free/en/corpora/dictionaries/school/P/propensity/