South African Multilingual Learner Corpus of Academic Texts (SAMuLCAT) version 2023-03
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By downloading this resource I accept and agree to the terms of use and the associated license conditions under which the resource is distributed.
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Author(s)
Van Dyk, Tobie
Metadata
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The South African Multilingual Learner Corpus of Academic Texts (SAMuLCAT) is a multi-genre, multi-level learner corpus developed by the Inter-institutional Centre for Language Development and Assessment (ICELDA) in collaboration with the South African Centre for Digital Language Resources (SADiLaR). This corpus includes shorter and longer pieces of texts, from an array of genres, different fields of study, and at all levels of study. The corpus was, and continues to be, contributed to by several institutions of higher education that are part of the ICELDA network. Ethical clearance has been granted at all partnering institutions to collect data; this includes informed consent by all students who contributed to SAMULCAT. The corpus is augmented by two sets of metadata. The first set includes mainly biographical detail about students (completed by students themselves); the second set includes more information on different task types and texts included in the corpus (completed by e.g. lecturers, writing centre staff, etc.). Data can be filtered through the metadata filters available in the search functionality of the corpus. The corpus is available under the Attribution 4.0 International (CC BY 4.0) license and is open source.
More information about the design of the corpus and metadata available in the corpus can be found in the following article: Carstens, A. and Eiselen, R., 2019. Designing a South African multilingual learner corpus of academic texts (SAMuLCAT). Language Matters, 50(1), pp.64-83. The Afrikaans part of the corpus is automatically annotated for lemmas and part of speech using the available NCHLT Text lemmatisers and part of speech taggers. Additional information is available here:
https://hlt.nwu.ac.za/about
No quality control of the automatic annotations was performed. The English data is annotated using the open-source NLP4J library available here: https://emorynlp.github.io/nlp4j/
DISCLAIMER: For a description of SADiLaR's privacy stance and practices, please see the privacy statement:
https://sadilar.org/index.php/en/394-privacy-statement
Contact person
Tobie van DykContact person's e-mail address
Tobie.vanDyk@nwu.ac.zaPublisher(s)
ICELDA
SADiLaR