@inproceedings{wan-badillo-urquiola-2023-dragonfly,
title = "Dragonfly{\_}captain at {S}em{E}val-2023 Task 11: Unpacking Disagreement with Investigation of Annotator Demographics and Task Difficulty",
author = "Wan, Ruyuan and
Badillo-Urquiola, Karla",
editor = {Ojha, Atul Kr. and
Do{\u{g}}ru{\"o}z, A. Seza and
Da San Martino, Giovanni and
Tayyar Madabushi, Harish and
Kumar, Ritesh and
Sartori, Elisa},
booktitle = "Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023)",
month = jul,
year = "2023",
address = "Toronto, Canada",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2023.semeval-1.272",
doi = "10.18653/v1/2023.semeval-1.272",
pages = "1978--1982",
abstract = "This study investigates learning with disagreement in NLP tasks and evaluates its performance on four datasets. The results suggest that the model performs best on the experimental dataset and faces challenges in minority languages. Furthermore, the analysis indicates that annotator demographics play a significant role in the interpretation of such tasks. This study suggests the need for greater consideration of demographic differences in annotators and more comprehensive evaluation metrics for NLP models.",
}
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<abstract>This study investigates learning with disagreement in NLP tasks and evaluates its performance on four datasets. The results suggest that the model performs best on the experimental dataset and faces challenges in minority languages. Furthermore, the analysis indicates that annotator demographics play a significant role in the interpretation of such tasks. This study suggests the need for greater consideration of demographic differences in annotators and more comprehensive evaluation metrics for NLP models.</abstract>
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%0 Conference Proceedings
%T Dragonfly_captain at SemEval-2023 Task 11: Unpacking Disagreement with Investigation of Annotator Demographics and Task Difficulty
%A Wan, Ruyuan
%A Badillo-Urquiola, Karla
%Y Ojha, Atul Kr.
%Y Doğruöz, A. Seza
%Y Da San Martino, Giovanni
%Y Tayyar Madabushi, Harish
%Y Kumar, Ritesh
%Y Sartori, Elisa
%S Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023)
%D 2023
%8 July
%I Association for Computational Linguistics
%C Toronto, Canada
%F wan-badillo-urquiola-2023-dragonfly
%X This study investigates learning with disagreement in NLP tasks and evaluates its performance on four datasets. The results suggest that the model performs best on the experimental dataset and faces challenges in minority languages. Furthermore, the analysis indicates that annotator demographics play a significant role in the interpretation of such tasks. This study suggests the need for greater consideration of demographic differences in annotators and more comprehensive evaluation metrics for NLP models.
%R 10.18653/v1/2023.semeval-1.272
%U https://aclanthology.org/2023.semeval-1.272
%U https://doi.org/10.18653/v1/2023.semeval-1.272
%P 1978-1982
Markdown (Informal)
[Dragonfly_captain at SemEval-2023 Task 11: Unpacking Disagreement with Investigation of Annotator Demographics and Task Difficulty](https://aclanthology.org/2023.semeval-1.272) (Wan & Badillo-Urquiola, SemEval 2023)
ACL