Validity, Agreement, Consensuality and Annotated Data Quality

Anaëlle Baledent, Yann Mathet, Antoine Widlöcher, Christophe Couronne, Jean-Luc Manguin


Abstract
Reference annotated (or gold-standard) datasets are required for various common tasks such as training for machine learning systems or system validation. They are necessary to analyse or compare occurrences or items annotated by experts, or to compare objects resulting from any computational process to objects annotated by experts. But, even if reference annotated gold-standard corpora are required, their production is known as a difficult problem, from both a theoretical and practical point of view. Many studies devoted to theses issues conclude that multi-annotation is most of the time a necessity. That inter-annotator agreement measure, which is required to check the reliability of data and the reproducibility of an annotation task, and thus to establish a gold standard, is another thorny problem. Fine analysis of available metrics for this specific task then becomes essential. Our work is part of this effort and more precisely focuses on several problems, which are rarely discussed, although they are intrinsically linked with the interpretation of metrics. In particular, we focus here on the complex relations between agreement and reference (of which agreement among annotators is supposed to be an indicator), and the emergence of consensus. We also introduce the notion of consensuality as another relevant indicator.
Anthology ID:
2022.lrec-1.315
Volume:
Proceedings of the Thirteenth Language Resources and Evaluation Conference
Month:
June
Year:
2022
Address:
Marseille, France
Editors:
Nicoletta Calzolari, Frédéric Béchet, Philippe Blache, Khalid Choukri, Christopher Cieri, Thierry Declerck, Sara Goggi, Hitoshi Isahara, Bente Maegaard, Joseph Mariani, Hélène Mazo, Jan Odijk, Stelios Piperidis
Venue:
LREC
SIG:
Publisher:
European Language Resources Association
Note:
Pages:
2940–2948
Language:
URL:
https://aclanthology.org/2022.lrec-1.315
DOI:
Bibkey:
Cite (ACL):
Anaëlle Baledent, Yann Mathet, Antoine Widlöcher, Christophe Couronne, and Jean-Luc Manguin. 2022. Validity, Agreement, Consensuality and Annotated Data Quality. In Proceedings of the Thirteenth Language Resources and Evaluation Conference, pages 2940–2948, Marseille, France. European Language Resources Association.
Cite (Informal):
Validity, Agreement, Consensuality and Annotated Data Quality (Baledent et al., LREC 2022)
Copy Citation:
PDF:
https://aclanthology.org/2022.lrec-1.315.pdf