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Treebank Statistics: UD_Turkish_German-SAGT: POS Tags: NUM

There are 70 NUM lemmas (2%), 76 NUM types (1%) and 313 NUM tokens (1%). Out of 17 observed tags, the rank of NUM is: 9 in number of lemmas, 9 in number of types and 15 in number of tokens.

The 10 most frequent NUM lemmas: bir, iki, zwei, üç, altı, dört, yirmi, ein, kaç, 3

The 10 most frequent NUM types: bir, iki, zwei, üç, altı, dört, kaç, yirmi, 4, drei

The 10 most frequent ambiguous lemmas: bir (DET 270, ADV 59, CCONJ 48, NUM 47, ADJ 2, NOUN 2), iki (NUM 40, ADJ 5, NOUN 4), zwei (NUM 31, ADJ 1, NOUN 1), üç (NUM 21, NOUN 3), altı (NUM 12, ADJ 3), dört (NUM 10, ADJ 2), ein (DET 247, PRON 10, NUM 8), kaç (NUM 8, NOUN 2), 1 (NUM 5, NOUN 1), beş (NUM 5, ADJ 1)

The 10 most frequent ambiguous types: bir (DET 261, ADV 45, NUM 44, CCONJ 39), altı (NUM 12, NOUN 1), ein (DET 105, NUM 5, PRON 1), bin (AUX 44, NUM 4, VERB 2), yarım (NUM 4, ADJ 1), eine (DET 77, PRON 5, NUM 2), Acht (NOUN 1, NUM 1), dritten (ADJ 1, NUM 1)

• bir
  • DET 261: Ama tabii böyle bir tahminim var zu dem Beispiel Englisch oder Deutsch .
  • ADV 45: Ya değil mi bir de işte Hausarbeit yazmıştım für Sprache Gehirn .
  • NUM 44: Wie wie trommelt er diese ganzen Lieder bir Playliste zusammen so ?
  • CCONJ 39: Ondan sonra bir de hani öyle bir şey veriyor ki bana Gefühl veriyor ki .
• altı
  • NUM 12: Tatile gidiyoruz altı hafta aber das ist dann auch zu kurz .
  • NOUN 1: Also ähm die Preise sind das kommt jetzt auch noch auf das Alter an , weil es ist dann so ähm ähm so gegliedert zu dem Beispiel Sprachreise für Erwachsene und danach dann noch ähm öğrenciler için ama mesela onsekiz yaşında altı olanlar için tabii ki burada da fiyat farklı lığı var ama ehm ja biraz pahalı ehm çünkü yani bir öğrenci olarak biraz pahalı ama yani bir yerde de değiyor yapmak .
• ein
  • DET 105: Ya bunun hikayesi ist halt ein Krimibuch ja .
  • NUM 5: En son sinemaya belki eh vor ein zwei Monaten gittim .
  • PRON 1: Ich finde er sieht aus wie ein , so Çinli’ye benziyor bence ya da Koreli’ye oder ich weiß es nicht .
• bin
  • AUX 44: Ja ja biz hep burada ydık also ich bin in Bondorf aufgewachsen .
  • NUM 4: Bir de so etwas haben sie einfach mal iki bin ikide falan yapmışlar böyle bir şeyi .
  • VERB 2: Duruma bağlı hangi ülkede ysem oder wo ich jetzt auch bin .
• yarım
  • NUM 4: Ondan sonra Abiturdan sonra aslında yarım sene liğine falan Fransa’ya gitmek istedim .
  • ADJ 1: Linguistik als Hauptfach und Germanistik als Nebenfach ama önceden burada ydım , eh yarım sene burada ydım ama irgendwie yapamadım deswegen .
• eine
  • DET 77: Okay Äh hangi derslerde äh hast du da eine Prüfung .
  • PRON 5: Sie hat des eine çıkardı und des Nächste die so , ich krieg des nicht rein .
  • NUM 2: Benim şimdi üç sınavım var yani üç yazılı sınavım var und eine ehm Praktikumsbericht halt .
• Acht
  • NOUN 1: Ähm ich lasse mal jetzt so so außer Acht dass ich da groß geworden bin und Familie und so , also ich rede jetzt nur von der Mentalität von den Menschen hier und da çok çok farklı orada ki insanlar çok böyle açıksözlü bir de çok cana yakın lar böyle sehr sympathisch sehr offen .
  • NUM 1: Du hast vollkommen Recht ama daha okumadığın kitapları yok muydu “ Acht Nacht “ falan ?
• dritten
  • ADJ 1: Sende de az kaldı du bist ja jetzt dann in dem dritten Semester .
  • NUM 1: In dem dritten Semesterda Java gelecek .

Morphology

The form / lemma ratio of NUM is 1.085714 (the average of all parts of speech is 1.678698).

The 1st highest number of forms (3) was observed with the lemma “iki”: iki, ikincisi, İki.

The 2nd highest number of forms (2) was observed with the lemma “3”: 3, 3’ün.

The 3rd highest number of forms (2) was observed with the lemma “bir”: Birincisi, bir.

NUM occurs with 6 features: NumType (256; 82% instances), Case (36; 12% instances), Number (36; 12% instances), Number[psor] (4; 1% instances), Person[psor] (4; 1% instances), Foreign (2; 1% instances)

NUM occurs with 9 feature-value pairs: Case=Acc, Case=Nom, Foreign=Yes, NumType=Card, NumType=Dist, NumType=Ord, Number=Sing, Number[psor]=Sing, Person[psor]=3

NUM occurs with 9 feature combinations. The most frequent feature combination is NumType=Card (249 tokens). Examples: bir, iki, zwei, üç, dört, altı, kaç, drei, ein, yirmi

Relations

NUM nodes are attached to their parents using 14 different relations: nummod (236; 75% instances), compound (33; 11% instances), conj (11; 4% instances), obj (10; 3% instances), reparandum (7; 2% instances), obl (4; 1% instances), parataxis (3; 1% instances), compound:redup (2; 1% instances), fixed (2; 1% instances), ccomp (1; 0% instances), csubj (1; 0% instances), nmod (1; 0% instances), nsubj (1; 0% instances), root (1; 0% instances)

Parents of NUM nodes belong to 9 different parts of speech: NOUN (218; 70% instances), NUM (44; 14% instances), VERB (19; 6% instances), PROPN (14; 4% instances), ADJ (7; 2% instances), ADV (4; 1% instances), DET (3; 1% instances), PRON (3; 1% instances), (1; 0% instances)

235 (75%) NUM nodes are leaves.

61 (19%) NUM nodes have one child.

8 (3%) NUM nodes have two children.

9 (3%) NUM nodes have three or more children.

The highest child degree of a NUM node is 11.

Children of NUM nodes are attached using 20 different relations: compound (30; 25% instances), advmod (15; 13% instances), conj (14; 12% instances), case (9; 8% instances), punct (9; 8% instances), cc (8; 7% instances), nmod (6; 5% instances), reparandum (5; 4% instances), advmod:emph (3; 3% instances), det (3; 3% instances), amod (2; 2% instances), compound:redup (2; 2% instances), cop (2; 2% instances), discourse (2; 2% instances), nsubj (2; 2% instances), nummod (2; 2% instances), parataxis (2; 2% instances), parataxis:discourse (2; 2% instances), appos:trans (1; 1% instances), obl (1; 1% instances)

Children of NUM nodes belong to 14 different parts of speech: NUM (44; 37% instances), ADV (17; 14% instances), NOUN (12; 10% instances), ADP (9; 8% instances), PUNCT (9; 8% instances), CCONJ (8; 7% instances), ADJ (7; 6% instances), DET (5; 4% instances), AUX (2; 2% instances), PRON (2; 2% instances), X (2; 2% instances), INTJ (1; 1% instances), PROPN (1; 1% instances), VERB (1; 1% instances)

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