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Treebank Statistics: UD_Italian-KIParlaForest: Features: Gender

This feature is universal. It occurs with 2 different values: Fem, Masc.

6263 tokens (34%) have a non-empty value of Gender. 1546 types (53%) occur at least once with a non-empty value of Gender. 1271 lemmas (60%) occur at least once with a non-empty value of Gender. The feature is used with 13 part-of-speech tags: NOUN (2495; 13% instances), DET (1812; 10% instances), ADJ (665; 4% instances), PRON (650; 3% instances), VERB (389; 2% instances), PROPN (111; 1% instances), AUX (35; 0% instances), INTJ (34; 0% instances), NUM (34; 0% instances), ADV (33; 0% instances), ADP (2; 0% instances), CCONJ (2; 0% instances), X (1; 0% instances).

NOUN

2495 NOUN tokens (94% of all NOUN tokens) have a non-empty value of Gender.

The most frequent other feature values with which NOUN and Gender co-occurred: Number=Sing (1699; 68%).

NOUN tokens may have the following values of Gender:

• Fem (1179; 47% of non-empty Gender): città, realtà, casa, lingua, cosa, parte, università, cose, persone, storia
• Masc (1316; 53% of non-empty Gender): tipo, arabo, centro, anni, dialetti, alfabeto, sud, sacco, senso, periodo
• EMPTY (173): po’, nord, lingue, cazzo, femminile, okay, chewing, grazie, gum, ics

Paradigm lingua	Masc	Fem
Number=Sing	lingue	lingua
Number=Plur		lingue

Gender seems to be lexical feature of NOUN. 97% lemmas (755) occur only with one value of Gender.

DET

1812 DET tokens (83% of all DET tokens) have a non-empty value of Gender.

The most frequent other feature values with which DET and Gender co-occurred: PronType=Art (1555; 86%), Number=Sing (1335; 74%), Definite=Def (1167; 64%).

DET tokens may have the following values of Gender:

• Fem (853; 47% of non-empty Gender): la, le, una, questa, un’, queste, delle, mia, quella, tutte
• Masc (959; 53% of non-empty Gender): il, un, i, gli, questo, lo, questi, dei, uno, tutti
• EMPTY (382): l’, che, tutto, loro, tutti, il, qualche, alcuni, la, tutta

Paradigm il	Masc	Fem
Definite=Def|Number=Sing|PronType=Art	il, lo, l	la, le
Definite=Def|Number=Plur|PronType=Art	i, gli, il	le, lo
Number=Sing|Person=3|PronType=Prs	lo, l'	la
Number=Sing|PronType=Art		la
Number=Plur|PronType=Art		i

ADJ

665 ADJ tokens (70% of all ADJ tokens) have a non-empty value of Gender.

The most frequent other feature values with which ADJ and Gender co-occurred: Number=Sing (511; 77%).

ADJ tokens may have the following values of Gender:

• Fem (295; 44% of non-empty Gender): araba, mia, piccola, prima, semitica, bella, buona, tua, mezza, altra
• Masc (370; 56% of non-empty Gender): esatto, arabo, miei, proto, stesso, strano, antico, bel, islamico, perfetto
• EMPTY (282): grande, difficile, stessa, comune, standard, udenti, altra, certo, enorme, facile

Paradigm arabo	Masc	Fem
Number=Sing	arabo	araba
Number=Plur	arabi

PRON

650 PRON tokens (35% of all PRON tokens) have a non-empty value of Gender.

The most frequent other feature values with which PRON and Gender co-occurred: Number=Sing (510; 78%), Person=EMPTY (383; 59%).

PRON tokens may have the following values of Gender:

• Fem (180; 28% of non-empty Gender): questa, le, la, lei, quella, una, altra, queste, alcune, quelle
• Masc (470; 72% of non-empty Gender): lo, quello, questo, l’, tutti, li, qualcuno, uno, questi, tutto
• EMPTY (1232): c’, io, si, ci, mi, che, me, ti, cui, ne

Paradigm lo	Masc	Fem
Definite=Def|Number=Sing|PronType=Art	lo
Definite=Def|Number=Plur|PronType=Prs		l'
Number=Sing|Person=3|PronType=Prs	lo, l', qual

VERB

389 VERB tokens (16% of all VERB tokens) have a non-empty value of Gender.

The most frequent other feature values with which VERB and Gender co-occurred: Mood=EMPTY (389; 100%), Person=EMPTY (389; 100%), Number=Sing (336; 86%), Tense=Past (334; 86%), VerbForm=Part (334; 86%).

VERB tokens may have the following values of Gender:

• Fem (102; 26% of non-empty Gender): fatta, trovata, datata, morte, scritte, andata, andate, basta, chiusa, coperta
• Masc (287; 74% of non-empty Gender): detto, fatto, scritto, sentito, visto, imparato, parlato, trovato, usato, vissuto
• EMPTY (1995): è, so, sono, abbiamo, fa, fare, era, ha, dire, va

Paradigm essere	Masc	Fem
Number=Sing	stato	stata
Number=Plur	stati

PROPN

111 PROPN tokens (26% of all PROPN tokens) have a non-empty value of Gender.

The most frequent other feature values with which PROPN and Gender co-occurred: Number=Sing (81; 73%).

PROPN tokens may have the following values of Gender:

• Fem (59; 53% of non-empty Gender): arabia, siria, giordania, saudita, saba, turchia, arancioni, marina, palestina, palmira
• Masc (52; 47% of non-empty Gender): rossi, oman, kitab, nabatei, qays, erodoto, sinai, arab, egitto, fermo
• EMPTY (313): [TOWN_NAME], ancona, bologna, pesaro, cristo, [PLACE_NAME], fermo, gialli, imola, marche

Gender seems to be lexical feature of PROPN. 100% lemmas (56) occur only with one value of Gender.

AUX

35 AUX tokens (3% of all AUX tokens) have a non-empty value of Gender.

The most frequent other feature values with which AUX and Gender co-occurred: Mood=EMPTY (35; 100%), Person=EMPTY (35; 100%), Tense=Past (27; 77%), VerbForm=Part (27; 77%), Number=Sing (26; 74%).

AUX tokens may have the following values of Gender:

• Fem (18; 51% of non-empty Gender): stata, state, son, esser
• Masc (17; 49% of non-empty Gender): stato, son, stati, abbiamo, avevo, ero, stavo
• EMPTY (1009): è, sono, ho, ha, era, devi, hanno, possiamo, abbiamo, son

Paradigm essere	Masc	Fem
_	son	son
Number=Sing	ero
Number=Sing|Tense=Past|VerbForm=Part	stato	stata
Number=Plur		esser
Number=Plur|Tense=Past|VerbForm=Part	stati	state

INTJ

34 INTJ tokens (4% of all INTJ tokens) have a non-empty value of Gender.

INTJ tokens may have the following values of Gender:

• Masc (34; 100% of non-empty Gender): mh, eh
• EMPTY (757): eh, mh, okay, ah, no, sì, vabbè, mhmh, beh, ehm

NUM

34 NUM tokens (20% of all NUM tokens) have a non-empty value of Gender.

The most frequent other feature values with which NUM and Gender co-occurred: Number=Sing (25; 74%), NumType=Ord (19; 56%).

NUM tokens may have the following values of Gender:

• Fem (10; 29% of non-empty Gender): prima, seconda, sedicimila, terza
• Masc (24; 71% of non-empty Gender): primi, primo, seicento, trecentoventotto, duecento, duemiladiciotto, milleseicento, ottocento, secondo, sedici
• EMPTY (138): due, quattro, tre, cinque, quattordici, sette, dieci, mille, undici, cinquanta

Paradigm primo	Masc	Fem
_	primi
Number=Sing|NumType=Ord	primo	prima
Number=Plur|NumType=Ord	primi

ADV

33 ADV tokens (1% of all ADV tokens) have a non-empty value of Gender.

The most frequent other feature values with which ADV and Gender co-occurred: PronType=EMPTY (29; 88%).

ADV tokens may have the following values of Gender:

• Fem (12; 36% of non-empty Gender): cosa, etcetera, lì, più, invece, molte, quali, tutta, tutte, vicina
• Masc (21; 64% of non-empty Gender): quanto, giusto, lì, meno, almeno, bene, esatto, fino, lontano, manco
• EMPTY (2179): non, sì, no, anche, più, poi, molto, così, bene, adesso

Paradigm lì	Masc	Fem
	lì	lì

ADP

2 ADP tokens (0% of all ADP tokens) have a non-empty value of Gender.

ADP tokens may have the following values of Gender:

• Fem (1; 50% of non-empty Gender): a
• Masc (1; 50% of non-empty Gender): in
• EMPTY (1901): di, in, a, per, da, con, su, come, secondo, tra

CCONJ

2 CCONJ tokens (0% of all CCONJ tokens) have a non-empty value of Gender.

CCONJ tokens may have the following values of Gender:

• Fem (2; 100% of non-empty Gender): oppure
• EMPTY (1000): e, cioè, ma, quindi, però, o, comunque, sia, che, infatti

X

1 X tokens (0% of all X tokens) have a non-empty value of Gender.

X tokens may have the following values of Gender:

• Fem (1; 100% of non-empty Gender): s~
• EMPTY (353): x, s~, no~, a~, day, di~, may, n~, p~, ti~

Relations with Agreement in Gender

The 10 most frequent relations where parent and child node agree in Gender: NOUN –[det]–> DET (1388; 81%), NOUN –[amod]–> ADJ (341; 69%), NOUN –[conj]–> NOUN (46; 56%), PROPN –[det]–> DET (34; 51%), ADJ –[det]–> DET (24; 59%), NOUN –[det:poss]–> DET (23; 66%), ADJ –[nsubj]–> NOUN (22; 76%), DET –[reparandum]–> DET (16; 57%), NOUN –[parataxis]–> NOUN (15; 63%), INTJ –[discourse]–> INTJ (13; 100%).

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