Treebank Statistics: UD_German-PUD: Features: Gender
This feature is universal.
It occurs with 3 different values: Fem, Masc, Neut.
This is a layered feature with the following layers: Gender, Gender[psor].
9608 tokens (45%) have a non-empty value of Gender.
4430 types (68%) occur at least once with a non-empty value of Gender.
3775 lemmas (71%) occur at least once with a non-empty value of Gender.
The feature is used with 6 part-of-speech tags: NOUN (4080; 19% instances), DET (2642; 12% instances), ADJ (1187; 6% instances), PROPN (1116; 5% instances), PRON (579; 3% instances), NUM (4; 0% instances).
NOUN
4080 NOUN tokens (97% 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 (2896; 71%).
NOUN tokens may have the following values of Gender:
Fem(1693; 41% of non-emptyGender): Zeit, Regierung, Stadt, Geschichte, Welt, Armee, Frau, Millionen, Region, ReiheMasc(1463; 36% of non-emptyGender): Menschen, Oktober, Teil, Film, Kaiser, April, Fall, Krieg, Präsident, TagNeut(924; 23% of non-emptyGender): Jahr, Jahre, Jahren, Jahrhundert, Mal, Land, Leben, Meer, Ende, ReichEMPTY(110): Leute, Kosten, anderen, Investors, Konservativen, North, Roma, Strategy, Target, 1350ern
| Paradigm ander | Masc | Fem | Neut |
|---|---|---|---|
| Case=Acc|Number=Plur | andere | ||
| Case=Dat|Number=Sing | anderem | ||
| Case=Nom|Number=Sing | andere | ||
| Case=Nom|Number=Plur | andere |
Gender seems to be lexical feature of NOUN. 99% lemmas (2316) occur only with one value of Gender.
DET
2642 DET tokens (85% of all DET tokens) have a non-empty value of Gender.
The most frequent other feature values with which DET and Gender co-occurred: Number=Sing (2452; 93%), NumType=EMPTY (2199; 83%), PronType=Art (2132; 81%), Definite=Def (1700; 64%).
DET tokens may have the following values of Gender:
Fem(1130; 43% of non-emptyGender): der, die, eine, einer, seine, diese, ihre, seiner, ihrer, dieserMasc(853; 32% of non-emptyGender): dem, der, den, des, ein, einen, einem, dieser, seinen, diesemNeut(659; 25% of non-emptyGender): das, dem, ein, des, einem, eines, ihr, dies, dieses, seinEMPTY(453): die, den, der, the, a, alle, Diese, meisten, viele, That
| Paradigm der | Masc | Fem | Neut |
|---|---|---|---|
| Case=Acc | den | die | das |
| Case=Dat | dem | der | dem |
| Case=Gen | des | der | des |
| Case=Nom | der | die | das |
ADJ
1187 ADJ tokens (84% of all ADJ tokens) have a non-empty value of Gender.
The most frequent other feature values with which ADJ and Gender co-occurred: Degree=Pos (1112; 94%), Number=Sing (815; 69%).
ADJ tokens may have the following values of Gender:
Fem(519; 44% of non-emptyGender): neue, eigene, ersten, große, öffentliche, amerikanischen, guten, kleine, neuen, verschiedenenMasc(376; 32% of non-emptyGender): ersten, Vereinigten, letzten, neue, 1., besten, gesamten, große, großer, neuenNeut(292; 25% of non-emptyGender): letzten, ersten, Olympischen, eigenen, 8., drittes, karibische, neuen, 13., 1960erEMPTY(226): bekannt, möglich, groß, klar, paar, sicher, unglaublich, verheiratet, alt, ausgerichtet
| Paradigm neu | Masc | Fem | Neut |
|---|---|---|---|
| Case=Acc|Degree=Pos|Number=Sing | neuen | neue | neues |
| Case=Acc|Degree=Pos|Number=Plur | neue, neuen | neue, neuen | neue |
| Case=Dat|Degree=Pos|Number=Sing | neuen | ||
| Case=Dat|Degree=Pos|Number=Plur | neuen | ||
| Case=Gen|Degree=Pos|Number=Sing | neuen | neuen | |
| Case=Gen|Degree=Pos|Number=Plur | neuer | neuer | |
| Case=Nom|Degree=Pos|Number=Sing | neue | ||
| Case=Nom|Degree=Pos|Number=Plur | neue | neue, neuen | neue |
| Case=Nom|Degree=Sup|Number=Sing | neuestes | ||
| Case=Nom|Degree=Sup|Number=Plur | neuesten |
PROPN
1116 PROPN tokens (92% 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 (1084; 97%).
PROPN tokens may have the following values of Gender:
Fem(221; 20% of non-emptyGender): Qing, US, BBC, Clinton, Kesha, Mongolei, Alpen, Blunt, Erde, JasmineMasc(511; 46% of non-emptyGender): Chr., Trump, Joseph, USA, Donald, Martin, Richard, Bogd, Christopher, ColumbusNeut(384; 34% of non-emptyGender): China, Frankreich, Hong, Paris, Russland, Asien, Danewerk, Deutschland, England, GriechenlandEMPTY(102): Tarlo, Uber, Anden, Aviva, Maya, Spotify, USA, VW, Agora, Amazon
| Paradigm Trump | Masc | Fem |
|---|---|---|
| Case=Acc | Trump | |
| Case=Dat | Trump | |
| Case=Nom | Trump | Trump |
Gender seems to be lexical feature of PROPN. 97% lemmas (762) occur only with one value of Gender.
PRON
579 PRON tokens (59% of all PRON tokens) have a non-empty value of Gender.
The most frequent other feature values with which PRON and Gender co-occurred: Reflex=EMPTY (579; 100%), Number=Sing (550; 95%), Case=Nom (459; 79%), Person=3 (403; 70%), PronType=Prs (403; 70%).
PRON tokens may have the following values of Gender:
Fem(136; 23% of non-emptyGender): sie, die, der, ihr, HerMasc(241; 42% of non-emptyGender): er, der, sie, ihm, ihn, dem, dessen, ihnen, denNeut(202; 35% of non-emptyGender): es, was, das, etwas, nichts, sie, dem, alldemEMPTY(401): sich, die, ich, sie, wir, man, denen, mich, uns, deren
| Paradigm der | Masc | Fem | Neut |
|---|---|---|---|
| Case=Acc | den | die | das |
| Case=Dat | dem | der | dem |
| Case=Gen | dessen | ||
| Case=Nom | der | die | das |
NUM
4 NUM tokens (1% 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 (3; 75%).
NUM tokens may have the following values of Gender:
Fem(1; 25% of non-emptyGender): zweierMasc(3; 75% of non-emptyGender): 24, hunderte, zweierEMPTY(352): zwei, drei, vier, 3, sechs, zehn, 1, 10, 50, 100
Relations with Agreement in Gender
The 10 most frequent relations where parent and child node agree in Gender:
NOUN –[det]–> DET (2207; 86%),
NOUN –[amod]–> ADJ (1051; 100%),
NOUN –[det:poss]–> DET (220; 100%),
PROPN –[flat:name]–> PROPN (158; 100%),
ADJ –[conj]–> ADJ (93; 100%),
NOUN –[appos]–> PROPN (90; 67%),
PROPN –[det]–> DET (87; 83%),
NOUN –[compound]–> NOUN (82; 91%),
NOUN –[compound]–> PROPN (73; 100%),
PROPN –[conj]–> PROPN (41; 77%).