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LORELEI Wolof Representative Language Pack
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Tracey, Jennifer; Strassel, Stephanie; Graff, David; Wright, Jonathan; Chen, Song; Ryant, Neville; Griffitt, Kira; Delgado, Dana; Arrigo, Michael. - : Linguistic Data Consortium, 2022. : https://www.ldc.upenn.edu, 2022
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Abstract:
*Introduction* LORELEI Wolof Representative Language Pack consists of Wolof monolingual text, Wolof-English parallel text, annotations, supplemental resources and related software tools developed by the Linguistic Data Consortium for the DARPA LORELEI program. The LORELEI (Low Resource Languages for Emergent Incidents) program was concerned with building human language technology for low resource languages in the context of emergent situations like natural disasters or disease outbreaks. Linguistic resources for LORELEI include Representative Language Packs and Incident Language Packs for over two dozen low resource languages, comprising data, annotations, basic natural language processing tools, lexicons and grammatical resources. Representative languages were selected to provide broad typological coverage, while incident languages were selected to evaluate system performance on a language whose identity was disclosed at the start of the evaluation. *Data* Wolof is spoken mainly in Senegal, the Gambia and Mauritania. Data was collected in the following genres: discussion forum, news, reference, social network, and weblogs. Both monolingual text collection and parallel text creation involved a combination of manual and automatic methods. Data volumes are as follows: * Over 225,000 words of Wolof monolingual text, all of which were translated into English * 115,000 Wolof words translated from English data Approximately 15,000 words were annotated for named entities and 5,000 to 8,000 words contain additional annotation, including situation frames (identifying entities, needs and issues) and entity linking and detection. Lexical resources and software tools are also included in this release. The tools recreate original source data from the processed XML material, condition text data users download from Twitter, apply sentence segmentation to raw text, and support named entity tagging in Wolof. Monolingual and parallel text are presented in XML with associated dtds. Annotation data is presented as tab delimited or XML files. All text is UTF-8 encoded. The knowledge base for entity linking annotation for this corpus and all LORELEI Representative Language and Incident Language Packs is available separately as LORELEI Entity Detection and Linking Knowledge Base (LDC2020T10). *Sponsorship* This material is based upon work supported by the Defense Advanced Research Projects Agency (DARPA) under Contract No. HR0011-15-C-0123. Any opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of DARPA. *Samples* Please view the following samples: * Wolof LTF XML * Wolof PSM XML * English LTF XML * English PSM XML * Simple Name Entity Annotation (XML) * Full Name Entity Annotation (XML) * Semantic Annotation (XML) *Updates* None at this time.
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URL: https://catalog.ldc.upenn.edu/LDC2022T03
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