OLAC Record
oai:www.ldc.upenn.edu:LDC2014T10

Metadata
Title:GALE Arabic-English Word Alignment Training Part 2 -- Newswire
Access Rights:Licensing Instructions for Subscription & Standard Members, and Non-Members: http://www.ldc.upenn.edu/language-resources/data/obtaining
Bibliographic Citation:Li, Xuansong, et al. GALE Arabic-English Word Alignment Training Part 2 -- Newswire LDC2014T10. Web Download. Philadelphia: Linguistic Data Consortium, 2014
Contributor:Li, Xuansong
Grimes, Stephen
Ismael, Safa
Strassel, Stephanie
Date (W3CDTF):2014
Date Issued (W3CDTF):2014-05-15
Description:*Introduction* GALE Arabic-English Word Alignment Training Part 2 -- Newswire was developed by the Linguistic Data Consortium (LDC) and contains 162,359 tokens of word aligned Arabic and English parallel text enriched with linguistic tags. This material was used as training data in the DARPA GALE (Global Autonomous Language Exploitation) program. Some approaches to statistical machine translation include the incorporation of linguistic knowledge in word aligned text as a means to improve automatic word alignment and machine translation quality. This is accomplished with two annotation schemes: alignment and tagging. Alignment identifies minimum translation units and translation relations by using minimum-match and attachment annotation approaches. A set of word tags and alignment link tags are designed in the tagging scheme to describe these translation units and relations. Tagging adds contextual, syntactic and language-specific features to the alignment annotation. Other releases available in this series are: * GALE Chinese-English Word Alignment and Tagging Training Part 1 -- Newswire and Web (LDC2012T16) * GALE Chinese-English Word Alignment and Tagging Training Part 2 -- Newswire (LDC2012T20) * GALE Chinese-English Word Alignment and Tagging Training Part 3 -- Web (LDC2012T24) * GALE Chinese-English Word Alignment and Tagging Training Part 4 -- Web (LDC2013T05) * GALE Chinese-English Word Alignment and Tagging -- Broadcast Training Part 1 (LDC2013T23) * GALE Arabic-English Word Alignment Training Part 1 -- Newswire and Web (LDC2014T05) *Data* This release consists of Arabic source newswire collected by LDC in 2004 - 2006 and 2008. The distribution by genre, words, character tokens and segments appears below: Language Genre Files Words CharTokens Segments Arabic NW 1,126 112,318 162,359 5,349 Note that word count is based on the untokenized Arabic source, and token count is based on the tokenized Arabic source. The Arabic word alignment tasks consisted of the following components: * Identifying and correcting incorrectly tokenized tokens * Identifying different types of links * Identifying sentence segments not suitable for annotation, such as those that were blank, incorrectly-segmented or containing other languages * Tagging unmatched words attached to other words or phrases *Samples* Please view the following samples: * English Raw * English Token * Arabic Raw * Arabic Token * Word Alignment *Sponsorship* This work was supported in part by the Defense Advanced Research Projects Agency, GALE Program Grant No. HR0011-06-1-0003. The content of this publication does not necessarily reflect the position or the policy of the Government, and no official endorsement should be inferred. *Updates* None at this time.
Extent:Corpus size: 12098 KB
Identifier:LDC2014T10
https://catalog.ldc.upenn.edu/LDC2014T10
ISBN: 1-58563-677-0
ISLRN: 019-953-960-209-5
DOI: 10.35111/1m2h-yb05
Language:English
Standard Arabic
Arabic
Language (ISO639):eng
arb
ara
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
Rights Holder: Portions © 2004-2006, 2008 Agence France Presse, © 2008 Al-Ahram, © 2008 Al Hayat, © 2008 Al-Quds Al-Arabi, © 2008 An Nahar, © 2008 Asharq Al-Awsat, © 2006, 2008 Assabah, © 2004-2006 Xinhua News Agency, © 2004-2006, 2008, 2014 Trustees of the University of Pennsylvania
Type (DCMI):Text
Type (OLAC):primary_text

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Archive:  The LDC Corpus Catalog
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OaiIdentifier:  oai:www.ldc.upenn.edu:LDC2014T10
DateStamp:  2020-11-30
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Search Info

Citation: Li, Xuansong; Grimes, Stephen; Ismael, Safa; Strassel, Stephanie. 2014. Linguistic Data Consortium.
Terms: area_Asia area_Europe country_GB country_SA dcmi_Text iso639_ara iso639_arb iso639_eng olac_primary_text


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