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

registration: 2016/01/17 10:21:31, last modified: 2016/01/17 10:21:31
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  • GALE Arabic-English Word Alignment Training Part 1 -- Newswire and Web
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  • *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

    * 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.
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  • 2014-03-17
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  • Text
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  • primary_text
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  • Corpus size: 38824 KB
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  • Web Download
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  • 642-473-657-451-7
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  • English
  • Standard Arabic
  • Arabic
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