GALE Arabic-English Word Alignment -- Broadcast Training Part 2

Item Name: GALE Arabic-English Word Alignment -- Broadcast Training Part 2
Author(s): Xuansong Li, Stephen Grimes, Safa Ismael, Stephanie Strassel
LDC Catalog No.: LDC2014T22
ISBN: 1-58563-691-6
ISLRN: 901-500-716-588-1
DOI: https://doi.org/10.35111/2aaj-dj35
Release Date: October 15, 2014
Member Year(s): 2014
DCMI Type(s): Text
Data Source(s): broadcast conversation, broadcast news
Project(s): GALE
Application(s): automatic content extraction, content-based retrieval, machine translation, tagging
Language(s): Standard Arabic, Arabic, English
Language ID(s): arb, ara, eng
License(s): LDC User Agreement for Non-Members
Online Documentation: LDC2014T22 Documents
Licensing Instructions: Subscription & Standard Members, and Non-Members
Citation: Li, Xuansong, et al. GALE Arabic-English Word Alignment -- Broadcast Training Part 2 LDC2014T22. Web Download. Philadelphia: Linguistic Data Consortium, 2014.
Related Works: View

Introduction

GALE Arabic-English Word Alignment -- Broadcast Training Part 2 was developed by the Linguistic Data Consortium (LDC) and contains 215,923 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)
  • GALE Arabic-English Word Alignment Training Part 2 -- Newswire (LDC2014T10)
  • GALE Arabic-English Word Alignment Training Part 3 -- Web (LDC2014T14)
  • GALE Arabic-English Word Alignment -- Broadcast Training Part 1 (LDC2014T19)

Data

This release consists of Arabic source broadcast news and broadcast conversation data collected by LDC from 2007-2009. The distribution by genre, words, tokens and segments appears below:

LanguageGenreFilesWordsTokensSegments
Arabic BC 369 97,514 129,233 7,941
Arabic BN 40 70,635 86,400 3,752
Totals   409 168,149 215,923 11,693

 

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:

  • Normalizing tokenized tokens as needed
  • Identifying different types of links
  • Identifying sentence segments not suitable for annotation
  • Tagging unmatched words attached to other words or phrases

Samples

Please view the following samples:

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.

Available Media

View Fees





Login for the applicable fee