OLAC Record oai:www.ldc.upenn.edu:LDC2023T01

Metadata
Title:		LORELEI Swahili Representative Language Pack
Access Rights:		Licensing Instructions for Subscription & Standard Members, and Non-Members: http://www.ldc.upenn.edu/language-resources/data/obtaining
Bibliographic Citation:		Tracey, Jennifer, et al. LORELEI Swahili Representative Language Pack LDC2023T01. Web Download. Philadelphia: Linguistic Data Consortium, 2023
Contributor:		Tracey, Jennifer
		Strassel, Stephanie
		Graff, David
		Wright, Jonathan
		Chen, Song
		Ryant, Neville
		Kulick, Seth
		Griffitt, Kira
		Delgado, Dana
		Arrigo, Michael
Date (W3CDTF):		2023
Date Issued (W3CDTF):		2023-01-17
Description:		*Introduction* LORELEI Swahili Representative Language Pack consists of Swahili monolingual text, Swahili-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* Swahili is a Bantu language spoken by 100 million people throughout East and Central Africa. Significant populations of Swahili speakers can be found in Tanzania, Kenya, Uganda, and the eastern Democratic Republic of the Congo. 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 4.3 million words of Swahili monolingual text, approximately 409,000 of which were translated into English * 90,000 Swahili words translated from English data * 545,000 words of found Swahili-English parallel text Approximately 100,000 words were annotated for simple named entities, and up to 26,000 words were annotated for full entity (including nominals and pronouns), entity linking, simple semantic annotation, and situation frame annotation. Lexical resources and software tools are also included in this release. The tools recreate original source data from the processed XML material, condition text that data users download from Twitter, apply sentence segmentation to raw text, and support named entity tagging. Monolingual and parallel text are presented in XML with associated dtds. Annotation data is presented as tab delimited files or XML. 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 these samples: * Translation Alignment XML * English LTF XML * English PSM XML * Swahili LTF XML * Swahili PSM XML * Needs Table (TXT) * Entity Table (TXT) * Full Entity Annotation XML * Semantic Annotation XML *Updates* None at this time.
Extent:		Corpus size: 303015 KB
Identifier:		LDC2023T01
		https://catalog.ldc.upenn.edu/LDC2023T01
		ISLRN: 103-399-285-757-9
		DOI: 10.35111/ense-dv79
Language:		English
		Swahili (macrolanguage); Swahili
Language (ISO639):		eng
		swa
License:		LDC User Agreement for Non-Members: https://catalog.ldc.upenn.edu/license/ldc-non-members-agreement.pdf
Medium:		Distribution: Web Download
Publisher:		Linguistic Data Consortium
Publisher (URI):		https://www.ldc.upenn.edu
Relation (URI):		https://catalog.ldc.upenn.edu/docs/LDC2023T01
Rights Holder:		Portions © 2002-2007, 2009-2010 Agence France Presse, © 2000 American Broadcasting Company, © 2011-2017 BBC, © 2000 Cable News Network LP, LLLP, © 2008 Central News Agency (Taiwan), © 2007-2008, 2014-2017 China Radio International.CRI, © 2009, 2015 Dicasterium pro Communicatione, © 1989 Dow Jones & Company, Inc., © 2015-2016 Global Publishers, © 2017 Independent Television Limited, © 2017 Ipsinternational, © 2005 Los Angeles Times - Washington Post News Service, Inc., © 2015 Makuruki.rw, © 2014-2017 Millard Ayo, © 2014-2016 Mtanzania Newspaper, © 2014-2016 Nation Media Group, © 2000 National Broadcasting Company, Inc., © 1999, 2005, 2006, 2010 New York Times, © 2016 Pars Today, © 2000 Public Radio International, © 2015 Radio Rahma, © 2011-2016 RFI, © 2016 Tanzania Standard Newspapers, Ltd., © 2003, 2005-2008, 2010 The Associated Press, © 2015, 2017 TRT, © 2003, 2005-2008 Xinhua News Agency, © 2017 ZanziNews, © 2017, 2022, 2023 Trustees of the University of Pennsylvania
Type (DCMI):		Software
		Text
Type (OLAC):		lexicon
		primary_text
OLAC Info
Archive:		The LDC Corpus Catalog
Description:		http://www.language-archives.org/archive/www.ldc.upenn.edu
GetRecord:		OAI-PMH request for OLAC format
GetRecord:		Pre-generated XML file
OAI Info
OaiIdentifier:		oai:www.ldc.upenn.edu:LDC2023T01
DateStamp:		2024-01-01
GetRecord:		OAI-PMH request for simple DC format
Search Info
Citation:		Tracey, Jennifer; Strassel, Stephanie; Graff, David; Wright, Jonathan; Chen, Song; Ryant, Neville; Kulick, Seth; Griffitt, Kira; Delgado, Dana; Arrigo, Michael. 2023. Linguistic Data Consortium.
Terms:		area_Europe country_GB dcmi_Software dcmi_Text iso639_eng iso639_swa olac_lexicon olac_primary_text