UD Chinese PUD
Language: Chinese (code: zh
)
Family: Sino-Tibetan
This treebank has been part of Universal Dependencies since the UD v2.1 release.
The following people have contributed to making this treebank part of UD: Hans Uszkoreit, Vivien Macketanz, Aljoscha Burchardt, Kim Harris, Katrin Marheinecke, Slav Petrov, Tolga Kayadelen, Mohammed Attia, Ali Elkahky, Zhuoran Yu, Emily Pitler, Saran Lertpradit, Josie Li, Cheuk Ying Li, Martin Popel, Daniel Zeman, Herman Leung.
Repository: UD_Chinese-PUD
Search this treebank on-line: PML-TQ
Download all treebanks: UD 2.15
License: CC BY-SA 3.0
Genre: news, wiki
Questions, comments? General annotation questions (either Chinese-specific or cross-linguistic) can be raised in the main UD issue tracker. You can report bugs in this treebank in the treebank-specific issue tracker on Github. If you want to collaborate, please contact [zeman (æt) ufal • mff • cuni • cz]. The UD version of this treebank currently does not have a maintainer. If you know the language and want to help, please consider adopting the treebank.
Annotation | Source |
---|---|
Lemmas | assigned by a program, with some manual corrections, but not a full manual verification |
UPOS | annotated manually in non-UD style, automatically converted to UD |
XPOS | not available |
Features | annotated manually in non-UD style, automatically converted to UD, with some manual corrections of the conversion |
Relations | annotated manually in non-UD style, automatically converted to UD |
Description
This is a part of the Parallel Universal Dependencies (PUD) treebanks created for the CoNLL 2017 shared task on Multilingual Parsing from Raw Text to Universal Dependencies.
There are 1000 sentences in each language, always in the same order. (The sentence alignment is 1-1 but occasionally a sentence-level segment actually consists of two real sentences.) The sentences are taken from the news domain (sentence id starts in ‘n’) and from Wikipedia (sentence id starts with ‘w’). There are usually only a few sentences from each document, selected randomly, not necessarily adjacent. The digits on the second and third position in the sentence ids encode the original language of the sentence. The first 750 sentences are originally English (01). The remaining 250 sentences are originally German (02), French (03), Italian (04) or Spanish (05) and they were translated to other languages via English. Translation into German, French, Italian, Spanish, Arabic, Hindi, Chinese, Indonesian, Japanese, Korean, Portuguese, Russian, Thai and Turkish has been provided by DFKI and performed (except for German) by professional translators. Then the data has been annotated morphologically and syntactically by Google according to Google universal annotation guidelines; finally, it has been converted by members of the UD community to UD v2 guidelines.
Additional languages have been provided (both translation and native UD v2 annotation) by other teams: Czech by Charles University, Finnish by University of Turku and Swedish by Uppsala University.
The entire treebank is labeled as test set (and was used for testing in the shared task). If it is used for training in future research, the users should employ ten-fold cross-validation.
Acknowledgments
Statistics of UD Chinese PUD
POS Tags
ADJ – ADP – ADV – AUX – CCONJ – DET – NOUN – NUM – PART – PRON – PROPN – PUNCT – SCONJ – VERB – X
Features
Aspect – Case – Foreign – Mood – Number – NumType – Person – Polarity – Voice
Relations
acl – acl:relcl – advcl – advmod – amod – appos – aux – aux:pass – case – case:loc – cc – ccomp – clf – compound – conj – cop – csubj – dep – det – discourse – discourse:sp – dislocated – fixed – flat – flat:name – iobj – mark – mark:adv – mark:prt – mark:rel – nmod – nsubj – nsubj:pass – nummod – obj – obl – obl:agent – obl:patient – obl:tmod – parataxis – punct – root – vocative – xcomp
Tokenization and Word Segmentation
- This corpus contains 1000 sentences and 21415 tokens.
- This corpus contains 20322 tokens (95%) that are not followed by a space.
- This corpus does not contain words with spaces.
- This corpus contains 10 types of words that contain both letters and punctuation. Examples: B.C., G.D.P, Jr., King,, St., Traum,, Wi-Fi, Z., Zettel's, al-Jadaan
Morphology
Tags
- This corpus uses 15 UPOS tags out of 17 possible: ADJ, ADP, ADV, AUX, CCONJ, DET, NOUN, NUM, PART, PRON, PROPN, PUNCT, SCONJ, VERB, X
- This corpus does not use the following tags: INTJ, SYM
- This corpus contains 26 word types tagged as particles (PART): 之, 了, 人, 區, 呢, 嗎, 地, 家, 得, 河, 法, 的, 緣, 罪, 者, 肺, 舟, 處, 號, 街, 賽, 配, 鎊, 體, 點, 黨
- This corpus contains 33 lemmas tagged as pronouns (PRON): 之, 什麼, 他, 何, 你, 你們, 個人, 其, 哪, 哪兒, 大家, 她, 它, 對方, 怎麼, 您, 我, 此, 牠, 甚麽, 自己, 自身, 誰, 這, 這樣, 這裡, 這麼, 那, 那兒, 那樣, 那裡, 那里, 閣下
- This corpus contains 44 lemmas tagged as determiners (DET): 上, 下, 任, 任何, 全, 全副, 全部, 其他, 其它, 其餘, 前, 另, 另外, 各, 各個, 各天, 各樣, 各種, 同, 後, 所有, 整個, 有的, 本, 某, 某些, 某種, 此, 此次, 每, 每位, 每個, 每天, 每幅, 每年, 每首, 該, 該項, 這, 這些, 那, 那些, 頭, 頭個
- Out of the above, 3 lemmas occurred sometimes as PRON and sometimes as DET: 此, 這, 那
- This corpus contains 22 lemmas tagged as auxiliaries (AUX): 了, 可, 可以, 可能, 得, 必, 必須, 想, 應, 應該, 是, 會, 為, 能, 能夠, 著, 被, 要, 過, 需要, 願, 願意
- Out of the above, 9 lemmas occurred sometimes as AUX and sometimes as VERB: 可能, 得, 必須, 想, 是, 會, 為, 過, 需要
- This corpus does not use the VerbForm feature.
Nominal Features
- Plur
- NOUN: 人們
- PRON: 他們, 我們, 它們, 你們, 她們, 牠們
- Gen
- PART: 的, 之
Degree and Polarity
- Neg
- ADV: 不, 未, 勿
- AUX: 不會, 不能, 不得, 不是, 未能, 不要, 不可, 不想, 不願
- VERB: 沒有, 不是, 不可思議, 不一而足, 不夠, 不慌不忙, 不朽, 不止, 不足為奇, 沒看
Verbal Features
- Perf
- AUX: 了, 過
- Prog
- AUX: 著
- Int
- AUX: 會不會, 要不要
- Cau
- ADP: 把, 將
- VERB: 讓, 使, 令, 導致, 以, 以至, 使得, 將, 把, 任命
- Pass
- ADP: 被
- AUX: 被
Pronouns, Determiners, Quantifiers
- Card
- NUM: 一, 兩, 很多, 三, 許多, 六, 多, 20, 10, 十
- Ord
- ADJ: 第一, 第二, 第三, 第31, 第45, 第96, 第四
- 1
- PRON: 我, 我們
- 2
- PRON: 你, 您, 你們
- 3
- PRON: 他, 她, 其, 他們, 它, 它們, 她們, 牠們
Other Features
- Foreign
- Yes
- X: Anaya, Film, de, the, Amin, Antilles, Atkinson, Avery, Aviva, Bass
- Yes
Syntax
Auxiliary Verbs and Copula
- This corpus uses 2 lemmas as copulas (cop). Examples: 是、 為.
- This corpus uses 19 lemmas as auxiliaries (aux). Examples: 了、 會、 能、 著、 可以、 可能、 要、 可、 過、 能夠、 必須、 想、 應該、 需要、 得、 必、 願意、 應、 願.
- This corpus uses 1 lemmas as passive auxiliaries (aux:pass). Examples: 被.
Core Arguments, Oblique Arguments and Adjuncts
Here we consider only relations between verbs (parent) and nouns or pronouns (child).
- nsubj
- VERB--NOUN (838)
- VERB--PRON (344)
- obj
- VERB--NOUN (1129)
- VERB--PRON (49)
- iobj
- VERB--NOUN (9)
- VERB--PRON (1)
Relations Overview
- This corpus uses 12 relation subtypes: acl:relcl, aux:pass, case:loc, discourse:sp, flat:name, mark:adv, mark:prt, mark:rel, nsubj:pass, obl:agent, obl:patient, obl:tmod
- The following 5 relation types are not used in this corpus at all: expl, list, orphan, goeswith, reparandum