Afrikaans text unit identification data
| Title | Afrikaans text unit identification data |
| Description | This dataset was developed during a masters degree and used in the development of a text unit identifier capable of tagging sentences, named-entities, words, abbreviations and punctuation in Afrikaans text. The dataset consists of 39,762 tokens, containing 3,294 named entities in 1,581 sentences. The data was manually annotated by the author and verified by an independent linguist according to the tagset developed during the same study. Details on the annotation and tagset used are available in the publication mentioned above in (2). The data is also presented in CoNNL-2002 format (Sang, E. F., & De Meulder, F. (2003). Introduction to the CoNLL-2003 shared task: Language-independent named entity recognition. Available at: https://www.aclweb.org/anthology/W02-2024). |
| Contact name | Martin Puttkammer |
| Contact email | martin.puttkammer@nwu.ac.za |
| Publisher(s) | Centre for Text Technology, North-West University |
| License | Creative Commons Attribution 4.0 International: https://creativecommons.org/licenses/by/4.0/ |
| Language(s) | Afrikaans |
| Author(s) | Puttkammer, Martin |
| Subject | Afrikaans, Tokenisation, Sentence recognition, Named-entity recognition, sentence, named-entity, word, token |
| Citation | Puttkammer, M.J. 2006. Outomatiese Afrikaanse tekseenheididentifisering. Potchefstroom: North-West University. (Dissertation - MA). |
| URI | https://hdl.handle.net/20.500.12185/507 |
| Media type | Text |
| Media category | Monolingual text corpus: annotated |
| Format extent | 39,762 tokens |
| Version | 1.0 |
| Format size | 195,324 bytes (zipped) |
| Format medium | N/A |
| Primary collection | Resource Catalogue |
| Secondary collection | Resource Index |
| ISO639 code | afr |
| Submit date | 2019-04-15T14:05:43Z |
| Date available | 2019-04-15T14:05:43Z |
| Date created | 2006 |
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Resource Catalogue [350]
A collection of language resources available for download from the RMA of SADiLaR. The collection mostly consists of resources developed with funding from the Department of Arts and Culture. -
Resource Index [412]
A collection of language resource metadata mostly collected during the NHN funded technology audit of 2009, as well as the SADiLaR technology audit of 2018. Not all resources in this collection are available for download.