mlsanityData to 7 Oct 2026

Camelira: An Arabic Multi-Dialect Morphological Disambiguator

arXiv 2211.16807 ↗First posted 30 Nov 2022cs.CLcited by 10

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Abstract (arXiv)

We present Camelira, a web-based Arabic multi-dialect morphological disambiguation tool that covers four major variants of Arabic: Modern Standard Arabic, Egyptian, Gulf, and Levantine. Camelira offers a user-friendly web interface that allows researchers and language learners to explore various linguistic information, such as part-of-speech, morphological features, and lemmas. Our system also provides an option to automatically choose an appropriate dialect-specific disambiguator based on the prediction of a dialect identification component. Camelira is publicly accessible at http://camelira.camel-lab.com.

Key facts. Cited by 10 papers in the map (data through 7 Oct 2026). Builds on 10 of its 48 references that are in the map. First posted on arXiv 30 Nov 2022.

Builds on

10 of 48 references.

References · 10

  1. 2020Stanza: A Python Natural Language Processing Toolkit for Many Human Languagescited by 719
  2. 2020NADI 2020: The First Nuanced Arabic Dialect Identification Shared Taskcited by 47
  3. 2020A Panoramic Survey of Natural Language Processing in the Arab Worldcited by 45
  4. 2021NADI 2021: The Second Nuanced Arabic Dialect Identification Shared Taskcited by 32
  5. 2018Arap-Tweet: A Large Multi-Dialect Twitter Corpus for Gender, Age and Language Variety Identificationcited by 23
  6. 2022NADI 2022: The Third Nuanced Arabic Dialect Identification Shared Taskcited by 23
  7. 2019AraNet: A Deep Learning Toolkit for Arabic Social Mediacited by 14
  8. 2021Morphosyntactic Tagging with Pre-trained Language Models for Arabic and its Dialectscited by 14
  9. 2019Joint Diacritization, Lemmatization, Normalization, and Fine-Grained Morphological Taggingcited by 12
  10. 2019An Arabic Dependency Treebank in the Travel Domaincited by 3

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Citing papers per year: 2023: 1; 2024: 5; 2025: 3; 2026: 1.

10 papers.