CoPEP: Corpus of Portuguese from Academic Journals
The CoPEP Corpus (Corpus de Português Escrito em Periódicos) is a synchronic corpus of Portuguese made up of around 10.000 texts collected from academic journals from Brazil and Portugal. The corpus was prepared especially for a lexicographic project focussed on designing an online corpus-driven dictionary of Portuguese for university students (Kuhn, 2017). The corpus contains approximately 40 million words, which are distributed among three Schools of Knowledge, and further divided into six Great Areas (according to CAPES classification).
The subcorpora for each language variety are of almost the same size and consist of a similar number of words per both Great Areas and Schools, making the corpus evenly balanced. Metadata on the texts have been carefully recorded in order to allow advanced corpus search options, e.g. year of publication, Great Area of Knowledge and ISSN number.
This study was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior -Brasil (CAPES) -Finance Code 001 and in part by the Fundação para a Ciência e a Tecnologia de Portugal, through the Strategic Project of CELGA-ILTEC at University of Coimbra (POCI-01-0145-FEDER-006986 – UID/LIN/04887/2013).
Authors of corpus
The Corpus of Portuguese from Academic Journals was created by Tanara Zingano Kuhn and José Pedro Ferreira in 2018. For more information about the corpus, please contact Tanara Zingano Kuhn at tanarazingano(a)outlook.com
Copyright & financing
Texts in the corpus are provided under Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0).
The Portuguese CoPEP corpus was tagged by FreeLing using EAGLES PoS tags.
Corpus metadata - categories and names of attributes
Texts are distributed into three Schools of Knowledge, and further divided into six Great Areas (according to CAPES classification).
|Colégios||Colégio de Humanidades (HU)||Colégio de Ciências da Vida (CV)||Colégio de Ciências Exatas, da Terra e Multidisciplinar (CE)|
|Grandes áreas||Ciências Humanas (Hu)||Ciências Socias Aplicadas (Ap)||Ciências da Saúde (He)||Ciências Agrícolas (Ag)||Engenharia (En)||Ciências Exatas e da Terra (Ex)|
Name of attributes
|Attributes in English||Attributes in Portuguese|
|issn||issn (no change)|
Names of attribute values
|Attributes||Values in English||Values in Portuguese|
|great_area||Exact-Earth Sciences||Exatas e da Terra|
|school||Ex-Tech-Multi Sciences||Ciencias da Terra, Exatas e Multidisciplinar|
|great_area||Health Sciences||Ciencias da Saude|
|great_area||Agricultural Sciences||Ciencias Agricolas|
|school||Life Sciences||Ciencias da Vida|
|great_area||Applied Social Sciences||Ciencias Socias Aplicadas|
|great_area||Human Sciences||Ciencias Humanas|
Tools to work with the CoPEP corpus
A complete set of tools is available to work with this academic Portuguese corpus to generate:
- word sketch – Portuguese collocations categorized by grammatical relations
- thesaurus – synonyms and similar words for every word
- word lists – lists of Portuguese nouns, verbs, adjectives etc. organized by frequency
- n-grams – frequency list of multi-word units
- concordance – examples in context
- keywords– terminology extraction of one-word units
- text type analysis – statistics of metadata in the corpus
Bibliography & how to cite this corpus
How to cite
- Tanara Zingano Kuhn & José Pedro Ferreira (2018). CoPEP – Corpus de Português Escrito em Periódicos (v.1.4)
- Kuhn, Tanara Zingano; Ferreira, José Pedro (2018). Introducing CoPEP, the Corpus de Português Escrito em Periódicos (Corpus of Portuguese from Academic Journals). In: 14th American Association for Corpus Linguistics (AACL) Conference, p. 61.
- Kuhn, Tanara Zingano (2017). A design proposal of an online corpus-driven dictionary of Portuguese for university students. Tese de Doutoramento em Linguística Aplicada. Lisboa: Universidade de Lisboa.
Search the CoPEP corpus
Sketch Engine offers a range of tools to work with this Portuguese corpus from Portuguese academic journals.
Use Sketch Engine in minutes
Generate collocations, frequency lists, examples in contexts, n-grams or extract terms. Use our Quick Start Guide to learn it in minutes.