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Quality and Efficiency of Manual Annotation: Pre-annotation Bias

Proceedings of the Thirteenth International Conference on Language Resources and Evaluation (LREC 2022)

DOI:10.63317/5p9o4xvssfuh

Abstract

This paper presents an analysis of annotation using an automatic pre-annotation for a mid-level annotation complexity task - dependency syntax annotation. It compares the annotation efforts made by annotators using a pre-annotated version (with a high-accuracy parser) and those made by fully manual annotation. The aim of the experiment is to judge the final annotation quality when pre-annotation is used. In addition, it evaluates the effect of automatic linguistically-based (rule-formulated) checks and another annotation on the same data available to the annotators, and their influence on annotation quality and efficiency. The experiment confirmed that the pre-annotation is an efficient tool for faster manual syntactic annotation which increases the consistency of the resulting annotation without reducing its quality.

Details

Paper ID
lrec2022-main-312
Pages
pp. 2909-2918
BibKey
mikulova-etal-2022-quality
Editor
N/A
Publisher
European Language Resources Association (ELRA)
ISSN
2522-2686
ISBN
79-10-95546-38-2
Conference
Thirteenth Language Resources and Evaluation Conference
Location
Marseille, France
Date
20 June 2022 25 June 2022

Authors

  • MM

    Marie Mikulová

  • MS

    Milan Straka

  • Jan Štěpánek

  • Barbora Štěpánková

  • JH

    Jan Hajic

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