GALE Chinese-English Word Alignment and Tagging Training Part 1 -- Newswire and Web
| Item Name: | GALE Chinese-English Word Alignment and Tagging Training Part 1 -- Newswire and Web |
| Author(s): | Xuansong Li, Stephen Grimes, Stephanie Strassel |
| LDC Catalog No.: | LDC2012T16 |
| ISBN: | 1-58563-624-X |
| ISLRN: | 582-702-931-027-0 |
| DOI: | https://doi.org/10.35111/t2mj-v058 |
| Release Date: | September 17, 2012 |
| Member Year(s): | 2012 |
| DCMI Type(s): | Text |
| Data Source(s): | weblogs, newswire |
| Project(s): | GALE |
| Application(s): | machine translation, content-based retrieval, automatic content extraction, tagging |
| Language(s): | English, Mandarin Chinese, Chinese |
| Language ID(s): | eng, cmn, zho |
| License(s): |
LDC User Agreement for Non-Members |
| Online Documentation: | LDC2012T16 Documents |
| Licensing Instructions: | Subscription & Standard Members, and Non-Members |
| Citation: | Li, Xuansong, Stephen Grimes, and Stephanie Strassel. GALE Chinese-English Word Alignment and Tagging Training Part 1 -- Newswire and Web LDC2012T16. Web Download. Philadelphia: Linguistic Data Consortium, 2012. |
| Related Works: | View |
Introduction
GALE Chinese-English Word Alignment and Tagging Training Part 1 -- Newswire and Web was developed by the Linguistic Data Consortium (LDC) and contains 150,068 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.
Data
This release consists of Chinese source newswire and web data (newsgroup, weblog) collected by LDC in 2008. The distribution by genre, words, character tokens and segments appears below:
| Language | Genre | Files | Words | CharTokens | Segments |
| Chinese | nw | 193 | 53279 | 79919 | 2016 |
| Chinese | wb | 87 | 46766 | 70149 | 2357 |
| Total | 280 | 100045 | 150068 | 4373 |
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 the links for the source, translation, and word alignment files.
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.