GALE Arabic-English Word Alignment Training Part 1 -- Newswire and Web

Item Name: GALE Arabic-English Word Alignment Training Part 1 -- Newswire and Web
Author(s): Xuansong Li, Stephen Grimes, Safa Ismael, Stephanie Strassel
LDC Catalog No.: LDC2014T05
ISBN: 1-58563-671-1
ISLRN: 642-473-657-451-7
Release Date: March 17, 2014
Member Year(s): 2014
DCMI Type(s): Text
Data Source(s): web collection, newswire
Project(s): GALE
Application(s): automatic content extraction, content-based retrieval, tagging, machine translation
Language(s): English, Standard Arabic, Arabic
Language ID(s): eng, arb, ara
License(s): LDC User Agreement for Non-Members
Online Documentation: LDC2014T05 Documents
Licensing Instructions: Subscription & Standard Members, and Non-Members
Citation: Li, Xuansong, et al. GALE Arabic-English Word Alignment Training Part 1 -- Newswire and Web LDC2014T05. Web Download. Philadelphia: Linguistic Data Consortium, 2014.

Introduction

GALE Arabic-English Word Alignment Training Part 1 -- Newswire and Web was developed by the Linguistic Data Consortium (LDC) and contains 344,680 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)

Data

This release consists of Arabic source newswire and web data collected by LDC in 2006 - 2008. The distribution by genre, words, character tokens and segments appears below:

 

Language</TD> Genre Docs Words CharTokens Segments
Arabic WB 119 59,696 81,620 4,383
Arabic NW 717 198,621 263,060 8,423

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.

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