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Treebank Statistics: UD_Portuguese-CINTIL: Features: Gender

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

200191 tokens (42%) have a non-empty value of Gender. 18595 types (54%) occur at least once with a non-empty value of Gender. 11518 lemmas (46%) occur at least once with a non-empty value of Gender. The feature is used with 7 part-of-speech tags: NOUN (86397; 18% instances), DET (77510; 16% instances), ADJ (21937; 5% instances), VERB (7554; 2% instances), PRON (4854; 1% instances), NUM (1938; 0% instances), PROPN (1; 0% instances).

NOUN

86397 NOUN tokens (99% 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 (61066; 71%).

NOUN tokens may have the following values of Gender:

• Fem (40592; 47% of non-empty Gender): pessoas, empresa, vida, situação, parte, vez, questão, casa, acções, história
• Masc (45805; 53% of non-empty Gender): anos, ano, dia, presidente, mercado, caso, lado, país, fim, tempo
• EMPTY (826): segurança, razão, líder, jovens, capital, razões, capitais, final, analistas, estudantes

Paradigm presidente	Masc	Fem
Number=Sing	presidente	presidente
Number=Plur	presidentes

Gender seems to be lexical feature of NOUN. 96% lemmas (7369) occur only with one value of Gender.

DET

77510 DET tokens (99% 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 (70597; 91%), Definite=Def (61198; 79%), Number=Sing (60959; 79%).

DET tokens may have the following values of Gender:

• Fem (35910; 46% of non-empty Gender): a, as, uma, esta, essa, toda, todas, estas, algumas, muitas
• Masc (41600; 54% of non-empty Gender): o, os, um, este, isso, todos, esse, alguns, estes, isto
• EMPTY (555): qualquer, cada, tal, isso, quaisquer, isto, tais, aquilo, bastantes

Paradigm qualquer	Masc	Fem
	qualquer	qualquer

Gender seems to be lexical feature of DET. 92% lemmas (69) occur only with one value of Gender.

ADJ

21937 ADJ tokens (88% 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 (15527; 71%).

ADJ tokens may have the following values of Gender:

• Fem (10193; 46% of non-empty Gender): nova, primeira, outra, outras, grande, segunda, portuguesa, mesma, novas, boa
• Masc (11744; 54% of non-empty Gender): novo, outro, outros, primeiro, novos, mesmo, grande, últimos, último, português
• EMPTY (3132): grande, grandes, diferente, importante, bom, maior, diferentes, difícil, nacional, forte

Paradigm outro	Masc	Fem
Number=Sing	outro	outra, outro
Number=Plur	outros	outras

VERB

7554 VERB tokens (18% 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 (7554; 100%), Person=EMPTY (7554; 100%), Tense=EMPTY (7554; 100%), VerbForm=Part (7554; 100%), Number=Sing (4948; 66%).

VERB tokens may have the following values of Gender:

• Fem (3295; 44% of non-empty Gender): feita, feitas, marcada, passada, apresentada, sediada, prevista, anunciada, dada, tomada
• Masc (4259; 56% of non-empty Gender): passado, feito, divulgados, apresentado, aprovado, preso, divulgado, apresentados, dado, feitos
• EMPTY (35067): há, tem, vai, pode, disse, é, ter, diz, quer, têm

Paradigm fazer,feito	Masc	Fem
Number=Sing	feito, feitinho	feita
Number=Plur	feitos	feitas

PRON

4854 PRON tokens (40% of all PRON tokens) have a non-empty value of Gender.

The most frequent other feature values with which PRON and Gender co-occurred: PronType=Prs (4130; 85%), Number=Sing (3630; 75%), Person=EMPTY (3367; 69%).

PRON tokens may have the following values of Gender:

• Fem (1804; 37% of non-empty Gender): sua, suas, minha, ela, nossa, elas, -a, a, cuja, minhas
• Masc (3050; 63% of non-empty Gender): seu, ele, tudo, seus, eles, meu, o, nosso, meus, nada
• EMPTY (7407): que, -se, se, quem, onde, eu, nós, -me, me, -lhe

Paradigm -se	Masc	Fem
	-se	-se

NUM

1938 NUM tokens (28% of all NUM tokens) have a non-empty value of Gender.

The most frequent other feature values with which NUM and Gender co-occurred: NumType=Card (1476; 76%), Number=Plur (1473; 76%).

NUM tokens may have the following values of Gender:

• Fem (387; 20% of non-empty Gender): duas, três, cinco, mil, quatro, Ambas, meia, seis, sete, vinte
• Masc (1551; 80% of non-empty Gender): dois, cento, duzentos, milhões, três, mil, quatro, cinco, sete, dez
• EMPTY (5088): mil, três, quatro, vinte, cinco, seis, dez, sete, 30, 20

Paradigm mil	Masc	Fem
	mil	mil

PROPN

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

PROPN tokens may have the following values of Gender:

• Masc (1; 100% of non-empty Gender): Presidente
• EMPTY (45817): Portugal, Lisboa, Porto, Pedro, José, Governo, João, Câmara, Manuel, PSD

Relations with Agreement in Gender

The 10 most frequent relations where parent and child node agree in Gender: NOUN –[det]–> DET (59170; 99%), NOUN –[amod]–> ADJ (17898; 91%), NOUN –[amod]–> VERB (2954; 56%), NOUN –[amod]–> PRON (1414; 99%), NOUN –[det:poss]–> PRON (1124; 100%), ADJ –[nsubj]–> NOUN (977; 58%), ADJ –[det]–> DET (887; 94%), NOUN –[parataxis]–> NOUN (575; 59%), NOUN –[conj]–> NOUN (544; 55%), NOUN –[nsubj]–> DET (368; 80%).

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