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Sparse Probability of Agreement

2022-08-12 08:15:34
Jeppe Nørregaard, Leon Derczynski
arXiv_CL
   
Abstract

Measuring inter-annotator agreement is important for annotation tasks, but many metrics require a fully-annotated dataset (or subset), where all annotators annotate all samples. We define Sparse Probability of Agreement, SPA, which estimates the probability of agreement when no all annotator-item-pairs are available. We show that SPA, with some assumptions, is an unbiased estimator and provide multiple different weighing schemes for handling samples with different numbers of annotation, evaluated over a range of datasets.

Abstract (translated)

URL

https://arxiv.org/abs/2208.06161

PDF

https://arxiv.org/pdf/2208.06161.pdf

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