Department of Science, Technology and InnovationCLARIN in South Africa
 

South African Multilingual Learner Corpus of Academic Texts (SAMuLCAT)

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dc.contact.emailTobie.vanDyk@nwu.ac.zaen_ZA
dc.contact.nameTobie van Dyken_ZA
dc.contributor.authorVan Dyk, Tobie
dc.date.accessioned2022-04-06T16:21:57Z
dc.date.available2022-04-06T16:21:57Z
dc.date.issued2021
dc.descriptionNOTE: THIS HAS BEEN SUPERSEDED. See https://hdl.handle.net/20.500.12185/585 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 creative commons 4.0 license and is open source. Use of the corpus for research purposes requires permission from SADiLaR, and applications should include evidence of ethical clearance from the research institutions to which staff and students are affiliated to. 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. Annotation Corpora for the indigenous South African languages are automatically annotated for lemmas and part of speech using the available NCHLT Text lemmatisers and part of speech taggers. Information on the accuracy and tag sets for these languages are available here: NCHLT Web Service. 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/en_ZA
dc.formatXML, texten_ZA
dc.identifier.urihttps://hdl.handle.net/20.500.12185/557
dc.languagesAfrikaansen_ZA
dc.languagesEnglishen_ZA
dc.media.typeTexten_ZA
dc.publisherICELDAen_ZA
dc.publisherSADiLaRen_ZA
dc.relation.isreplacedbyhttps://hdl.handle.net/20.500.12185/585
dc.rights.licenseCreative Commons Attribution 4.0 International Public Licenseen_ZA
dc.subjectLearner Corpus, L2, multi-genreen_ZA
dc.titleSouth African Multilingual Learner Corpus of Academic Texts (SAMuLCAT)en_ZA
dc.version1.0en_ZA

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