Web: http://arxiv.org/abs/2209.09430

Sept. 21, 2022, 1:14 a.m. | Xiaolei Lu, Tommy W.S.Chow

cs.CL updates on arXiv.org arxiv.org

Crowd sequential annotations can be an efficient and cost-effective way to
build large datasets for sequence labeling. Different from tagging independent
instances, for crowd sequential annotations the quality of label sequence
relies on the expertise level of annotators in capturing internal dependencies
for each token in the sequence. In this paper, we propose Modeling sequential
annotation for sequence labeling with crowds (SA-SLC). First, a conditional
probabilistic model is developed to jointly model sequential data and
annotators' expertise, in which categorical …

annotations arxiv labeling modeling

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