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    Automated annotation of learner English

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    Name:
    IJLCR_2021_20003R3_RR_MP_libra ...
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    Description:
    Final Accepted Manuscript
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    Author
    Picoral, Adriana
    Staples, Shelley
    Reppen, Randi
    Affiliation
    University of Arizona
    Issue Date
    2021-03-01
    Keywords
    Automated annotation
    Learner English
    learner NLP
    Writing research
    
    Metadata
    Show full item record
    Publisher
    John Benjamins Publishing Company
    Citation
    Picoral, A., Staples, S., & Reppen, R. (2021). Automated annotation of learner English. International Journal of Learner Corpus Research, 7(1), 17–52.
    Journal
    International Journal of Learner Corpus Research
    Rights
    © John Benjamins Publishing Company.
    Collection Information
    This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.
    Abstract
    This paper explores the use of natural language processing (NLP) tools and their utility for learner language analyses through a comparison of automatic linguistic annotation against a gold standard produced by humans. While there are a number of automated annotation tools for English currently available, little research is available on the accuracy of these tools when annotating learner data. We compare the performance of three linguistic annotation tools (a tagger and two parsers) on academic writing in English produced by learners (both L1 and L2 English speakers). We focus on lexico-grammatical patterns, including both phrasal and clausal features, since these are frequently investigated in applied linguistics studies. Our results report both precision and recall of annotation output for argumentative texts in English across four L1s: Arabic, Chinese, English, and Korean. We close with a discussion of the benefits and drawbacks of using automatic tools to annotate learner language.
    Note
    Immediate access
    ISSN
    2215-1478
    EISSN
    2215-1486
    DOI
    10.1075/ijlcr.20003.pic
    Version
    Final accepted manuscript
    ae974a485f413a2113503eed53cd6c53
    10.1075/ijlcr.20003.pic
    Scopus Count
    Collections
    UA Faculty Publications

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