@inproceedings{bollmann-sogaard-2021-error,
title = "Error Analysis and the Role of Morphology",
author = "Bollmann, Marcel and
S{\o}gaard, Anders",
editor = "Merlo, Paola and
Tiedemann, Jorg and
Tsarfaty, Reut",
booktitle = "Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume",
month = apr,
year = "2021",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2021.eacl-main.162",
doi = "10.18653/v1/2021.eacl-main.162",
pages = "1887--1900",
abstract = "We evaluate two common conjectures in error analysis of NLP models: (i) Morphology is predictive of errors; and (ii) the importance of morphology increases with the morphological complexity of a language. We show across four different tasks and up to 57 languages that of these conjectures, somewhat surprisingly, only (i) is true. Using morphological features does improve error prediction across tasks; however, this effect is less pronounced with morphologically complex languages. We speculate this is because morphology is more discriminative in morphologically simple languages. Across all four tasks, case and gender are the morphological features most predictive of error.",
}
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%0 Conference Proceedings
%T Error Analysis and the Role of Morphology
%A Bollmann, Marcel
%A Søgaard, Anders
%Y Merlo, Paola
%Y Tiedemann, Jorg
%Y Tsarfaty, Reut
%S Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume
%D 2021
%8 April
%I Association for Computational Linguistics
%C Online
%F bollmann-sogaard-2021-error
%X We evaluate two common conjectures in error analysis of NLP models: (i) Morphology is predictive of errors; and (ii) the importance of morphology increases with the morphological complexity of a language. We show across four different tasks and up to 57 languages that of these conjectures, somewhat surprisingly, only (i) is true. Using morphological features does improve error prediction across tasks; however, this effect is less pronounced with morphologically complex languages. We speculate this is because morphology is more discriminative in morphologically simple languages. Across all four tasks, case and gender are the morphological features most predictive of error.
%R 10.18653/v1/2021.eacl-main.162
%U https://aclanthology.org/2021.eacl-main.162
%U https://doi.org/10.18653/v1/2021.eacl-main.162
%P 1887-1900
Markdown (Informal)
[Error Analysis and the Role of Morphology](https://aclanthology.org/2021.eacl-main.162) (Bollmann & Søgaard, EACL 2021)
ACL
- Marcel Bollmann and Anders Søgaard. 2021. Error Analysis and the Role of Morphology. In Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume, pages 1887–1900, Online. Association for Computational Linguistics.