Combining strategies for tagging and parsing Arabic

M Alabbas, A M Ramsay

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


    We describe a simple method for combiningtaggers which produces substantiallybetter performance than any of thecontributing tools. The method is verysimple, but it leads to considerable improvementsin performance: given threetaggers for Arabic whose individual accuraciesrange from 0.956 to 0.967, thecombined tagger scores 0.995–a sevenfoldreduction in the error rate whencompared to the best of the contributingtools.Given the effectiveness of this approachto combining taggers, we have investigatedits applicability to parsing. Forparsing, it seems better to take pairs ofsimilar parsers and back off to a third ifthey disagree.
    Original languageEnglish
    Title of host publicationhost publication
    PublisherAssociation for Computational Linguistics
    Number of pages5
    Publication statusPublished - 2014
    EventProceedings of the EMNLP 2014 Workshop on Arabic Natural Language Processing - Doha
    Duration: 1 Jan 1824 → …


    ConferenceProceedings of the EMNLP 2014 Workshop on Arabic Natural Language Processing
    Period1/01/24 → …
    Internet address


    • Natural language processing
    • dependency parsing
    • part of speech tagging


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