UD Portuguese GSD
Language: Portuguese (code: pt)
Family: Indo-European, Romance
This treebank has been part of Universal Dependencies since the UD v1.3 release.
The following people have contributed to making this treebank part of UD: Ryan McDonald, Joakim Nivre, Daniel Zeman, Alexandre Rademaker, Fabricio Chalub, Carlos Ramisch.
Repository: UD_Portuguese-GSD
Search this treebank on-line: PML-TQ
Download all treebanks: UD 2.2
License: CC BY-NC-SA 3.0 US
Genre: blog, news
Questions, comments? General annotation questions (either Portuguese-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 [arademaker (æt) gmail • com]. Development of the treebank happens directly in the UD repository, so you may submit bug fixes as pull requests against the dev branch.
| Annotation | Source |
|---|---|
| Lemmas | assigned by a program, not checked manually |
| UPOS | annotated manually in non-UD style, automatically converted to UD |
| XPOS | annotated manually |
| Features | not available |
| Relations | annotated manually in non-UD style, automatically converted to UD |
Description
The Brazilian Portuguese UD is converted from the Google Universal Dependency Treebank v2.0 (legacy).
Acknowledgments
Statistics of UD Portuguese GSD
POS Tags
ADJ – ADP – ADV – AUX – CCONJ – DET – NOUN – NUM – PART – PRON – PROPN – PUNCT – SYM – VERB – X
Features
Definite – Gender – Number – NumType – Polarity – PronType
Relations
acl:inf – acl:part – acl:relcl – advcl – advmod – amod – appos – aux – aux:pass – case – cc – ccomp – conj – cop – csubj – csubj:pass – dep – det – det:poss – expl:pv – fixed – flat – iobj – mark – nmod – nsubj – nsubj:pass – nummod – obj – parataxis – punct – root – xcomp – xcomp:adj
Tokenization and Word Segmentation
- This corpus contains 12078 sentences, 297478 tokens and 319380 syntactic words.
- This corpus contains 38132 tokens (13%) that are not followed by a space.
- This corpus does not contain words with spaces.
- This corpus contains 181 types of words that contain both letters and punctuation. Examples: &, 's, D., d', c., S., B., a.C., Yahoo!, J., r., Sr., A., Sul., W., Amazon.com, Av., Don't, Dr., E., S.Paulo, art., Bahá'í, F., I., Min., a_0, a_n, d.C., dez/12, didn't, http://m.goal.com, i.e., 11/jul, 1940.http, 19h.A, 2/jan, 2003.Com, 32/2012/CM, A.D., Amém., Anéis., Atenas/2004, B06/42-Acura, Bay., Belém., Brasília.Nos, Bucci-11.fev.2012/AP, C'rculo, Cerro-Corá/RN
- This corpus contains 21902 multi-word tokens. On average, one multi-word token consists of 2.00 syntactic words.
- There are 38 types of multi-word tokens. Examples: do, da, no, na, dos, ao, das, à, pelo, pela, nos, aos, nas, às, dum, duma, pelos, num, numa, pelas, doutros, nalguns, dalguns, noutras, dalgumas, doutra, noutros, nalgumas, doutras, noutro, donde, doutro, noutra, dalguma, dalgum, dalguém, dali, dele.
Morphology
Tags
- This corpus uses 15 UPOS tags out of 17 possible: ADJ, ADP, ADV, AUX, CCONJ, DET, NOUN, NUM, PART, PRON, PROPN, PUNCT, SYM, VERB, X
- This corpus does not use the following tags: SCONJ, INTJ
- This corpus contains 74 word types tagged as particles (PART): 's, Agora, Avante, Cara, Desculpe, Nè, Ok, Olá, Oxalá, Sucesso, afro, ai, alvi, ante, anti, ar, arqui, atenção, auto, aí, bem, claro, co, contra, cyber, eba, então, ex, extra, foi, franco, germano, greco, grão, hein, hélio, in, infanto, infra, inter, intra, ir, latino, lá, mamilo, micro, multi, on, pan, para, pois, prático, pré, pró, pós, pô, público, recém, rs, s, se, su, sub, supra, tele, to, tá, ultra, utz, vice, viu, á, ão, é
- This corpus contains 1 lemmas tagged as pronouns (PRON): _
- This corpus contains 2 lemmas tagged as determiners (DET): _, o
- Out of the above, 1 lemmas occurred sometimes as PRON and sometimes as DET: _
- This corpus contains 62 lemmas tagged as auxiliaries (AUX): _, acabar, andar, apelidar, arar, botar, cansar, chamar, chegar, começar, configurar, conseguir, considerar, constituir, continuar, costumar, deixar, demonstrar, denominar, designar, dever, dizer, eleger, encontrar, entrar, estar, fazer, ficar, haver, iniciar, instituir, intitular, ir, morrer, mostrar, nascer, nomear, ordenar, parar, parecer, passar, permanecer, persistir, poder, precisar, pretender, proclamar, representar, sagrar, seguir, sentir, ser, significar, tentar, ter, terminar, tocar, tornar, vencer, vir, virar, voltar
- Out of the above, 58 lemmas occurred sometimes as AUX and sometimes as VERB: _, acabar, andar, apelidar, botar, chamar, chegar, começar, configurar, conseguir, considerar, constituir, continuar, costumar, deixar, demonstrar, denominar, designar, dever, dizer, eleger, encontrar, entrar, estar, fazer, ficar, haver, iniciar, instituir, ir, morrer, mostrar, nascer, nomear, ordenar, parar, parecer, passar, permanecer, persistir, poder, precisar, pretender, proclamar, representar, seguir, sentir, ser, significar, tentar, ter, terminar, tocar, tornar, vencer, vir, virar, voltar
- This corpus does not use the VerbForm feature.
Nominal Features
- Fem
- DET: a, as
- Masc
- DET: o, os
- Plur
- DET: os, as
- Sing
- DET: o, a
- Def
- DET: o, a, os, as
Degree and Polarity
- Neg
- ADV: não
- NOUN: não
- PROPN: Não
Verbal Features
Pronouns, Determiners, Quantifiers
- Art
- DET: o, a, os, as
- Card
- NUM: dois, três, mil, duas, milhões, 1, 2012, quatro, 2, bilhões
Other Features
Syntax
Auxiliary Verbs and Copula
- This corpus uses 36 lemmas as copulas (cop). Examples: ser, _, tornar, considerar, chamar, virar, denominar, eleger, estar, intitular, nomear, designar, representar, sagrar, dizer, fazer, morrer, ordenar, parecer, significar, apelidar, configurar, constituir, demonstrar, encontrar, entrar, ferido, instituir, menino, mostrar, motivo, nascer, permanecer, proclamar, sentir, vencer.
- This corpus uses 33 lemmas as auxiliaries (aux). Examples: _, ter, ir, estar, dever, poder, haver, vir, acabar, passar, começar, continuar, voltar, chegar, deixar, costumar, ficar, ser, seguir, parar, precisar, cansar, conseguir, tentar, terminar, andar, botar, encontrar, iniciar, parecer, persistir, tocar, tornar.
- This corpus uses 6 lemmas as passive auxiliaries (aux:pass). Examples: ser, _, ficar, arar, poder, ter.
Core Arguments, Oblique Arguments and Adjuncts
Here we consider only relations between verbs (parent) and nouns or pronouns (child).
- nsubj
- VERB--NOUN (6583)
- VERB--NOUN-ADP(_) (20)
- VERB--NOUN-ADP(de) (3)
- VERB--PRON (3594)
- obj
- VERB--NOUN (8839)
- VERB--NOUN-ADP(_) (41)
- VERB--NOUN-ADP(_)-ADP(_) (1)
- VERB--NOUN-ADP(a) (1)
- VERB--NOUN-ADP(de) (2)
- VERB--NOUN-ADP(rede) (1)
- VERB--PRON (1307)
- VERB--PRON-ADP(_) (3)
- iobj
- VERB--NOUN-ADP(_) (32)
- VERB--NOUN-ADP(a) (242)
- VERB--PRON (85)
- VERB--PRON-ADP(_) (24)
- VERB--PRON-ADP(a) (3)
Reflexive Verbs
- This corpus contains 304 lemmas that occur at least once with an expl:pv child. Examples: _ se, tornar se, encontrar se, estender se, referir se, tratar se, destacar se, localizar se, manter se, fazer se, dizer se, passar se, recusar se, ver se, dar se, comunicar se, dever se, realizar se, situar se, ter se, aplicar se, dedicar se, desenvolver se, espalhar se, esperar se, mudar se, saber se, transformar se, aproveitar se, arrepender se, classificar se, formar se, lembrar se, manifestar se, mostrar se, recuperar se, repetir se, sentir se, apropriar se, assemelhar se, campeão se, comportar se, concentrar se, conhecer se, converter se, deparar se, distinguir se, instalar se, limitar se, negar se
Relations Overview
- This corpus uses 9 relation subtypes: acl:inf, acl:part, acl:relcl, aux:pass, csubj:pass, det:poss, expl:pv, nsubj:pass, xcomp:adj
- The following 2 main types are not used alone, they are always subtyped: acl, expl
- The following 10 relation types are not used in this corpus at all: obl, vocative, dislocated, discourse, clf, compound, list, orphan, goeswith, reparandum