OLAC Record: LORELEI Hungarian Representative Language Pack

OLAC Record
oai:www.ldc.upenn.edu:LDC2025T01

Metadata

Title: LORELEI Hungarian 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 Hungarian Representative Language Pack LDC2025T01. Web Download. Philadelphia: Linguistic Data Consortium, 2025

Contributor: Tracey, Jennifer

Strassel, Stephanie

Graff, David

Wright, Jonathan

Chen, Song

Ryant, Neville

Kulick, Seth

Griffitt, Kira

Delgado, Dana

Arrigo, Michael

Date (W3CDTF): 2025

Date Issued (W3CDTF): 2025-01-15

Description: *Introduction* LORELEI Hungarian Representative Language Pack consists of Hungarian monolingual text, Hungarian-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* Hungarian is spoken mainly in Hungary, where it is an official language, as well as in neighboring countries such as Romania, Slovakia, and Serbia. 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: * 686 million words of Hungarian monolingual text, 165,000 words of which were translated into English * 2.3 million words of found Hungarian-English parallel text * 87,000 Hungarian words translated from English data Approximately 72,500 words were annotated for named entities; about 25,000 words were annotated for full entity (including nominals and pronouns), entity linking and situation frames; over 17,000 words have simple semantic annotation; and close to 10,000 words were annotated for noun phrase chunking. 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. 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: * English LTF XML * English PSM XML * Hungarian LTF XML * Hungarian PSM XML * Full Entity Annotation XML * Semantic Annotation XML * Twitter Tokenization XML * Noun Phrase Chunking XML *Updates* None at this time.

Extent: Corpus size: 16147384 KB

Identifier: LDC2025T01

https://catalog.ldc.upenn.edu/LDC2025T01

ISLRN: 081-777-192-058-6

DOI: 10.35111/8bfb-pj11

Language: Hungarian

English

Language (ISO639): hun

eng

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/LDC2025T01

Rights Holder: Portions © 2002-2007, 2009-2010 Agence France Presse, © 2016 Agrotrend Média Kft., © 2000 American Broadcasting Company, © 2014 ATV, © 2009, 2011, 2013, 2015 blikk.hu, © 2000 Cable News Network, LP, LLLP, © 2010-2011, 2014-2015 Central Media Group Ltd., © 2008 Central News Agency (Taiwan), © 2016 DEHIR, © 1989 Dow Jones & Company, Inc., © 2016 DUEL-PRESS, sro, © 2014-2016 estihirlap.hu, © 2014-2015 euronews, © 2014-2015 GloboPort Media, © 2010 Greenfo, © 2016 HIR.MA, © 2008 HM Zrínyi Nonprofit Ltd., © 2015 http://168ora.hu/, © 2004-2016 HVG Kiadó Zrt., © 2010-2012 ICI Interaktiv Zrt., © 2009, 2011, 2015 Index.hu Zrt., © 2013 Krónika Online, © 2005 Los Angeles Times – Washington Post News Service, Inc., © 2012, 2014 magyarhirlap.hu, © 2009, 2016 Media Index Association,© 2006, 2008-2010, 2012-2016 Mediaworks Hungary Zrt., © 2014 MetNet Hungary Kft., © 2009, 2016 MON, © 2015 MSH Media Ltd., © 2015-2016 MTVA, © 2012, 2014-2016 Napi.hu, © 2000 National Broadcasting Company, Inc., © 2011-2012, 2016 National Meteorological Service, © 2005, 2008-2014, 2016 New Wave Media Group Kft., © 1999, 2005-2006, 2010 New York Times, © 2015-2016 News TV ZRL,© 2014 NLC - Central Medial Group Ltd., © 2015 Nouvelle Media Kft., © 2016 Power Online Kft., © 2016 Professional Publishing Hungary Kft., © 2000 Public Radio International, © 2006 RTL Hungary, © 2015 Stylemagazin.hu, © 2003, 2005-2008, 2010 The Associated Press, © 2011 Transcarpathia.ma, © 2016 VITAL MEDIA, © 2016 Watch Tower Bible and Tract Society of Pennsylvania, © 2008 Webbeteg Kft., © 2009 World News Inc., © 2003, 2005-2008 Xinhua News Agency, © 2016, 2022, 2025 Trustees of the University of Pennsylvania

Type (DCMI): Software

Text

Type (OLAC): 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:LDC2025T01

DateStamp: 2025-01-15

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. 2025. Linguistic Data Consortium.
Terms: area_Europe country_GB country_HU dcmi_Software dcmi_Text iso639_eng iso639_hun olac_primary_text

http://www.language-archives.org/item.php/oai:www.ldc.upenn.edu:LDC2025T01
Up-to-date as of: Thu Jan 16 8:07:48 EST 2025

Metadata
Title:		LORELEI Hungarian 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 Hungarian Representative Language Pack LDC2025T01. Web Download. Philadelphia: Linguistic Data Consortium, 2025
Contributor:		Tracey, Jennifer
		Strassel, Stephanie
		Graff, David
		Wright, Jonathan
		Chen, Song
		Ryant, Neville
		Kulick, Seth
		Griffitt, Kira
		Delgado, Dana
		Arrigo, Michael
Date (W3CDTF):		2025
Date Issued (W3CDTF):		2025-01-15
Description:		Introduction LORELEI Hungarian Representative Language Pack consists of Hungarian monolingual text, Hungarian-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 Hungarian is spoken mainly in Hungary, where it is an official language, as well as in neighboring countries such as Romania, Slovakia, and Serbia. 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: * 686 million words of Hungarian monolingual text, 165,000 words of which were translated into English * 2.3 million words of found Hungarian-English parallel text * 87,000 Hungarian words translated from English data Approximately 72,500 words were annotated for named entities; about 25,000 words were annotated for full entity (including nominals and pronouns), entity linking and situation frames; over 17,000 words have simple semantic annotation; and close to 10,000 words were annotated for noun phrase chunking. 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. 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: * English LTF XML * English PSM XML * Hungarian LTF XML * Hungarian PSM XML * Full Entity Annotation XML * Semantic Annotation XML * Twitter Tokenization XML * Noun Phrase Chunking XML Updates None at this time.
Extent:		Corpus size: 16147384 KB
Identifier:		LDC2025T01
		https://catalog.ldc.upenn.edu/LDC2025T01
		ISLRN: 081-777-192-058-6
		DOI: 10.35111/8bfb-pj11
Language:		Hungarian
Language:		English
Language (ISO639):		hun
Language (ISO639):		eng
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/LDC2025T01
Rights Holder:		Portions © 2002-2007, 2009-2010 Agence France Presse, © 2016 Agrotrend Média Kft., © 2000 American Broadcasting Company, © 2014 ATV, © 2009, 2011, 2013, 2015 blikk.hu, © 2000 Cable News Network, LP, LLLP, © 2010-2011, 2014-2015 Central Media Group Ltd., © 2008 Central News Agency (Taiwan), © 2016 DEHIR, © 1989 Dow Jones & Company, Inc., © 2016 DUEL-PRESS, sro, © 2014-2016 estihirlap.hu, © 2014-2015 euronews, © 2014-2015 GloboPort Media, © 2010 Greenfo, © 2016 HIR.MA, © 2008 HM Zrínyi Nonprofit Ltd., © 2015 http://168ora.hu/, © 2004-2016 HVG Kiadó Zrt., © 2010-2012 ICI Interaktiv Zrt., © 2009, 2011, 2015 Index.hu Zrt., © 2013 Krónika Online, © 2005 Los Angeles Times – Washington Post News Service, Inc., © 2012, 2014 magyarhirlap.hu, © 2009, 2016 Media Index Association,© 2006, 2008-2010, 2012-2016 Mediaworks Hungary Zrt., © 2014 MetNet Hungary Kft., © 2009, 2016 MON, © 2015 MSH Media Ltd., © 2015-2016 MTVA, © 2012, 2014-2016 Napi.hu, © 2000 National Broadcasting Company, Inc., © 2011-2012, 2016 National Meteorological Service, © 2005, 2008-2014, 2016 New Wave Media Group Kft., © 1999, 2005-2006, 2010 New York Times, © 2015-2016 News TV ZRL,© 2014 NLC - Central Medial Group Ltd., © 2015 Nouvelle Media Kft., © 2016 Power Online Kft., © 2016 Professional Publishing Hungary Kft., © 2000 Public Radio International, © 2006 RTL Hungary, © 2015 Stylemagazin.hu, © 2003, 2005-2008, 2010 The Associated Press, © 2011 Transcarpathia.ma, © 2016 VITAL MEDIA, © 2016 Watch Tower Bible and Tract Society of Pennsylvania, © 2008 Webbeteg Kft., © 2009 World News Inc., © 2003, 2005-2008 Xinhua News Agency, © 2016, 2022, 2025 Trustees of the University of Pennsylvania
Type (DCMI):		Software
Type (DCMI):		Text
Type (OLAC):		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:LDC2025T01
DateStamp:		2025-01-15
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. 2025. Linguistic Data Consortium.
Terms:		area_Europe country_GB country_HU dcmi_Software dcmi_Text iso639_eng iso639_hun olac_primary_text