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Increased Recall in Annotation Variance Detection in Treebanks

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Text, Speech, and Dialogue (TSD 2015)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9302))

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Abstract

Automatic inconsistency detection in parsed corpora is significantly helpful for building more and larger corpora of annotated texts. Inconsistencies are inevitable and originate from variance in annotation caused by different factors as, for instance, the lack of attention or the absence of clear annotation guidelines. In this paper, some results involving the automatic detection of annotation variance in parsed corpora are presented. In particular, it is shown that a generalization procedure substantially increases the recall of the variant detection algorithm proposed in [1].

This research is funded by Sao Paulo Research Foundation – FAPESP – through grants no. 13/18090-6 and 14/17172-1.

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Authors and Affiliations

  1. University of Campinas, Language Studies Institute, Campinas, Brazil

    Pablo Faria

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  1. Pablo Faria
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Correspondence to Pablo Faria .

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Editors and Affiliations

  1. University of West Bohemia, Pilsen, Czech Republic

    Pavel Král

  2. University of West Bohemia, Pilsen, Czech Republic

    Václav Matoušek

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Faria, P. (2015). Increased Recall in Annotation Variance Detection in Treebanks. In: Král, P., Matoušek, V. (eds) Text, Speech, and Dialogue. TSD 2015. Lecture Notes in Computer Science(), vol 9302. Springer, Cham. https://doi.org/10.1007/978-3-319-24033-6_65

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  • DOI: https://doi.org/10.1007/978-3-319-24033-6_65

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-24032-9

  • Online ISBN: 978-3-319-24033-6

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