Creating a Large Multi-Layered Representational Repository of Linguistic Code Switched Arabic Data

Abdelati Hawwari; Fahad AlGhamdi; Mahmoud Ghoneim; Mohamed Al-Badrashiny; Mona Diab; Nada AlMarwani

Creating a Large Multi-Layered Representational Repository of Linguistic Code Switched Arabic Data

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arxiv 1909.13009 v1 pith:BWYZ7SO7 submitted 2019-09-28 cs.CL

Mona Diab , Mahmoud Ghoneim , Abdelati Hawwari , Fahad AlGhamdi , Nada AlMarwani , Mohamed Al-Badrashiny This is my paper · ORCID

classification cs.CL

keywords annotationarabicdataprocessrepositoryannotationscodelarge

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We present our effort to create a large Multi-Layered representational repository of Linguistic Code-Switched Arabic data. The process involves developing clear annotation standards and Guidelines, streamlining the annotation process, and implementing quality control measures. We used two main protocols for annotation: in-lab gold annotations and crowd sourcing annotations. We developed a web-based annotation tool to facilitate the management of the annotation process. The current version of the repository contains a total of 886,252 tokens that are tagged into one of sixteen code-switching tags. The data exhibits code switching between Modern Standard Arabic and Egyptian Dialectal Arabic representing three data genres: Tweets, commentaries, and discussion fora. The overall Inter-Annotator Agreement is 93.1%.

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A Survey of Code-switched Arabic NLP: Progress, Challenges, and Future Directions
cs.CL 2025-01 conditional novelty 5.0 of 10

A structured survey of code-switched Arabic NLP, categorizing the literature, quantifying task and corpus coverage, and listing research gaps and recommendations.

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