OLAC Record

Title:GALE Chinese-English Word Alignment and Tagging 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, Stephen Grimes, and Stephanie Strassel. GALE Chinese-English Word Alignment and Tagging Training Part 2 -- Newswire LDC2012T20. Web Download. Philadelphia: Linguistic Data Consortium, 2012
Contributor:Li, Xuansong
Grimes, Stephen
Strassel, Stephanie
Date (W3CDTF):2012
Date Issued (W3CDTF):2012-10-16
Description:*Introduction* GALE Chinese-English Word Alignment and Tagging Training Part 2 -- Newswire was developed by the Linguistic Data Consortium (LDC) and contains 169,080 tokens of word aligned Chinese 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. GALE Chinese-English Word Alignment and Tagging Training Part 1 -- Newswire and Web (LDC2012T16) is also available through LDC. *Data* This release consists of Chinese source newswire collected by LDC in 2008. The distribution by genre, words, character tokens and segments appears below: Language Genre Files Words CharTokens Segments Chinese nw 1982 112720 169080 4239 Note that all token counts are based on the Chinese data only. One token is equivalent to one character and one word is equivalent to 1.5 characters. The Chinese word alignment tasks consisted of the following components: * Identifying, aligning, and tagging 8 different types of links * Identifying, attaching, and tagging local-level unmatched words * Identifying and tagging sentence/discourse-level unmatched words * Identifying and tagging all instances of Chinese 的 (DE) except when they were a part of a semantic link The file names indicate the source provider, the story date and the language. For example, AFP_CMN_20080406 refers to the source Agence France Presse (AFP), the story date is April 6, 2008 and the language is Chinese (CMN). *Samples* Please follow these links for samples: Chinese, English, 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: 15601 KB
ISBN: 1-58563-628-2
ISLRN: 685-457-689-684-9
DOI: 10.35111/7r7v-ng50
Mandarin Chinese
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/LDC2012T20
Rights Holder: Portions © 2008 Agence France Presse, China Military Online, Chinanews.com, Guangming Daily, Peoples Daily Online, Xinhua News Agency, © 2008, 2012 Trustees of the University of Pennsylvania
Type (DCMI):Text
Type (OLAC):primary_text


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Citation: Li, Xuansong; Grimes, Stephen; Strassel, Stephanie. 2012. Linguistic Data Consortium.
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