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ACL Findings2022

Towards Responsible Natural Language Annotation for the Varieties of Arabic

A. Stevie Bergman, Mona T. Diab

Abstract

When building NLP models, there is a tendency to aim for broader coverage, often overlooking cultural and (socio)linguistic nuance. In this position paper, we make the case for care and attention to such nuances, particularly in dataset annotation, as well as the inclusion of cultural and linguistic expertise in the process. We present a playbook for responsible dataset creation for polyglossic, multidialectal languages. This work is informed by a study on Arabic annotation of social media content.

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Cited by top-tier papers3

  1. ALDi: Quantifying the Arabic Level of Dialectness of TextAmr Keleg, Sharon Goldwater, Walid MagdyEMNLP 2023 · 4 citations
  2. DialUp! Modeling the Language Continuum by Adapting Models to Dialects and Dialects to ModelsNiyati Bafna, Emily Chang, Nathaniel Romney Robinson, David R. Mortensen et al.ACL 2025
  3. Revisiting Common Assumptions about Arabic Dialects in NLPAmr Keleg, Sharon Goldwater, Walid MagdyACL 2025

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