Treebank Statistics: UD_Hindi-PUD: Features: Gender
This feature is universal.
It occurs with 2 different values: Fem
, Masc
.
This is a layered feature with the following layers: Gender, Gender[psor].
11116 tokens (47%) have a non-empty value of Gender
.
3503 types (68%) occur at least once with a non-empty value of Gender
.
1 lemmas (0) occur at least once with a non-empty value of Gender
.
The feature is used with 8 part-of-speech tags: NOUN (4997; 21% instances), AUX (1522; 6% instances), PROPN (1338; 6% instances), ADP (1285; 5% instances), VERB (1254; 5% instances), PRON (408; 2% instances), ADJ (273; 1% instances), DET (39; 0% instances).
NOUN
4997 NOUN tokens (89% of all NOUN
tokens) have a non-empty value of Gender
.
The most frequent other feature values with which NOUN
and Gender
co-occurred: Animacy=Inan (4558; 91%), Number=Sing (4463; 89%), Case=Acc (2505; 50%).
NOUN
tokens may have the following values of Gender
:
Fem
(1654; 33% of non-emptyGender
): तरह, बार, दुनिया, बात, सरकार, शताब्दी, फिल्म, संभावना, सेना, वृद्धिMasc
(3343; 67% of non-emptyGender
): रूप, वर्ष, समय, क्षेत्र, शुरू, काम, साल, युद्ध, उपयोग, दिनEMPTY
(600): लोगों, वहां, लोग, अभी, पहले, बाद, अब, राष्ट्रपति, आगे, आज
AUX
1522 AUX tokens (86% of all AUX
tokens) have a non-empty value of Gender
.
The most frequent other feature values with which AUX
and Gender
co-occurred: Person=3 (1501; 99%), Number=Sing (1293; 85%), Mood=Ind (768; 50%).
AUX
tokens may have the following values of Gender
:
Fem
(330; 22% of non-emptyGender
): है, गयी, थी, हैं, रही, सकती, थीं, दी, गई, जातीMasc
(1192; 78% of non-emptyGender
): है, था, गया, हैं, दिया, हुए, जाता, सकता, गए, थेEMPTY
(254): हैं, हो, जा, रहे, थे, कर, जाने, होने, सकते, गए
PROPN
1338 PROPN tokens (99% 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 (1337; 100%), Animacy=Inan (745; 56%), Case=Acc (712; 53%).
PROPN
tokens may have the following values of Gender
:
Fem
(189; 14% of non-emptyGender
): इटली, स्पेनिश, क्लिंटन, रोना, केशा, क्यूरी, गिनी, जर्मनी, जैस्मिन, ब्लंटMasc
(1149; 86% of non-emptyGender
): अमेरिका, चीन, ब्रिटेन, ट्रम्प, फ्रांस, यूरोप, मिस्र, रूस, हांगकांग, अफ्रीकाEMPTY
(20): VW, 2C, Aoun, Emicro, ExxonMobil, GEMA, GOP, Hariri, Huawei, IRENA
ADP
1285 ADP tokens (27% of all ADP
tokens) have a non-empty value of Gender
.
The most frequent other feature values with which ADP
and Gender
co-occurred: Case=Gen (1200; 93%), Number=Sing (758; 59%).
ADP
tokens may have the following values of Gender
:
Fem
(444; 35% of non-emptyGender
): की, वाली, संबंधीMasc
(841; 65% of non-emptyGender
): के, का, वाले, वाला, योग्य, स्थित, आधारित, केन्द्रित, प्राप्त, लायकEMPTY
(3564): में, के, से, को, ने, पर, लिए, तक, साथ, बाद
VERB
1254 VERB tokens (61% of all VERB
tokens) have a non-empty value of Gender
.
The most frequent other feature values with which VERB
and Gender
co-occurred: VerbForm=EMPTY (1238; 99%), Person=3 (1205; 96%), Number=Sing (1107; 88%), Mood=Ind (874; 70%), Tense=EMPTY (629; 50%).
VERB
tokens may have the following values of Gender
:
Fem
(313; 25% of non-emptyGender
): की, है, थी, हुई, दी, होती, करती, हैं, आती, होगीMasc
(941; 75% of non-emptyGender
): किया, है, कहा, था, हुआ, करता, करते, दिया, किए, बतायाEMPTY
(804): करने, कर, हो, होने, करना, रहने, बन, बनाने, करते, रखने
PRON
408 PRON tokens (36% 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 (365; 89%), Gender[psor]=EMPTY (309; 76%), Number[psor]=EMPTY (300; 74%), PronType=EMPTY (297; 73%), Case=Nom (246; 60%), Person=3 (240; 59%).
PRON
tokens may have the following values of Gender
:
Fem
(135; 33% of non-emptyGender
): अपनी, उसकी, उनकी, वह, जिसकी, उसे, जिनकी, हमारी, इसने, उन्हेंMasc
(273; 67% of non-emptyGender
): अपने, वह, उसका, उसके, उसे, इसका, अपना, उसने, मैं, वेEMPTY
(720): जो, यह, उसने, उसके, इसके, जिसमें, उसे, इसे, उन्होंने, वे
ADJ
273 ADJ tokens (14% of all ADJ
tokens) have a non-empty value of Gender
.
ADJ
tokens may have the following values of Gender
:
Fem
(91; 33% of non-emptyGender
): पहली, अच्छी, दूसरी, नयी, बड़ी, पुरानी, ऊंची, पिछली, पूरी, बुरीMasc
(182; 67% of non-emptyGender
): नये, पहले, पिछले, नया, दूसरे, पुराने, पूरा, बड़ा, छोटे, तीसरेEMPTY
(1722): सबसे, शामिल, प्राप्त, स्थापित, अन्य, अमेरिकी, अलग, महत्वपूर्ण, विशेष, कम
DET
39 DET tokens (4% of all DET
tokens) have a non-empty value of Gender
.
The most frequent other feature values with which DET
and Gender
co-occurred: Definite=EMPTY (39; 100%), Number=Sing (23; 59%).
DET
tokens may have the following values of Gender
:
Fem
(18; 46% of non-emptyGender
): पूरी, थोड़ी, इतनी, कितनी, सारीMasc
(21; 54% of non-emptyGender
): थोड़ा, पूरे, कितने, जिस, समूचे, सारे, इतना, जितना, जोEMPTY
(837): एक, इस, कई, बहुत, ज्यादा, यह, लगभग, कम, उस, केवल
Relations with Agreement in Gender
The 10 most frequent relations where parent and child node agree in Gender
:
VERB –[aux]–> AUX (554; 59%),
NOUN –[compound]–> NOUN (220; 56%),
NOUN –[nmod:poss]–> PRON (213; 70%),
PROPN –[flat:name]–> PROPN (194; 94%),
VERB –[aux:pass]–> AUX (147; 79%),
VERB –[nsubj]–> PROPN (140; 65%),
NOUN –[compound]–> PROPN (122; 73%),
NOUN –[conj]–> NOUN (121; 58%),
NOUN –[nmod:poss]–> PROPN (109; 51%),
VERB –[nsubj:pass]–> NOUN (90; 81%).