# Lisan: Yemeni, Iraqi, Libyan, and Sudanese Arabic Dialect Copora with Morphological Annotations

arXiv: https://arxiv.org/abs/2212.06468 · HTML: https://mlsanity.com/paper/2212.06468/

## Key facts

- Cited by 9 papers in the map (data through 14 Oct 2026).
- Builds on 10 of its 35 references that are in the map.
- First posted on arXiv 13 Dec 2022.

## Builds on (most cited first, 10 of 10)

- [NADI 2020: The First Nuanced Arabic Dialect Identification Shared Task](https://mlsanity.com/paper/2010.11334/) (2020)
- [A Panoramic Survey of Natural Language Processing in the Arab World](https://mlsanity.com/paper/2011.12631/) (2020)
- [Wojood: Nested Arabic Named Entity Corpus and Recognition using BERT](https://mlsanity.com/paper/2205.09651/) (2022)
- [NADI 2021: The Second Nuanced Arabic Dialect Identification Shared Task](https://mlsanity.com/paper/2103.08466/) (2021)
- [Curras + Baladi: Towards a Levantine Corpus](https://mlsanity.com/paper/2205.09692/) (2022)
- [The Arabic Ontology -- An Arabic Wordnet with Ontologically Clean Content](https://mlsanity.com/paper/2205.09664/) (2022)
- [ArabGlossBERT: Fine-Tuning BERT on Context-Gloss Pairs for WSD](https://mlsanity.com/paper/2205.09685/) (2022)
- [Extracting Synonyms from Bilingual Dictionaries](https://mlsanity.com/paper/2012.00600/) (2020)
- [LU-BZU at SemEval-2021 Task 2: Word2Vec and Lemma2Vec performance in Arabic Word-in-Context disambiguation](https://mlsanity.com/paper/2104.08110/) (2021)
- [TArC: Tunisian Arabish Corpus First complete release](https://mlsanity.com/paper/2207.04796/) (2022)

## Built on by (most cited first, 9 of 9)

- [A Benchmark and Scoring Algorithm for Enriching Arabic Synonyms](https://mlsanity.com/paper/2302.02232/) (2023)
- [SALMA: Arabic Sense-Annotated Corpus and WSD Benchmarks](https://mlsanity.com/paper/2310.19029/) (2023)
- [ArBanking77: Intent Detection Neural Model and a New Dataset in Modern and Dialectical Arabic](https://mlsanity.com/paper/2310.19034/) (2023)
- [Arabic Fine-Grained Entity Recognition](https://mlsanity.com/paper/2310.17333/) (2023)
- [WojoodNER 2023: The First Arabic Named Entity Recognition Shared Task](https://mlsanity.com/paper/2310.16153/) (2023)
- [From English-Centric to Effective Bilingual: LLMs with Custom Tokenizers for Underrepresented Languages](https://mlsanity.com/paper/2410.18836/) (2024)
- [Doing More with Less: Data Augmentation for Sudanese Dialect Automatic Speech Recognition](https://mlsanity.com/paper/2601.06802/) (2026)
- [Computational Linguistics Meets Libyan Dialect: A Study on Dialect Identification](https://mlsanity.com/paper/2512.04257/) (2025)
- [Ramsa: A Large Sociolinguistically Rich Emirati Arabic Speech Corpus for ASR and TTS](https://mlsanity.com/paper/2603.08125/) (2026)

## Abstract (arXiv)

This article presents morphologically-annotated Yemeni, Sudanese, Iraqi, and Libyan Arabic dialects Lisan corpora. Lisan features around 1.2 million tokens. We collected the content of the corpora from several social media platforms. The Yemeni corpus (~ 1.05M tokens) was collected automatically from Twitter. The corpora of the other three dialects (~ 50K tokens each) came manually from Facebook and YouTube posts and comments. Thirty five (35) annotators who are native speakers of the target dialects carried out the annotations. The annotators segemented all words in the four corpora into prefixes, stems and suffixes and labeled each with different morphological features such as part of speech, lemma, and a gloss in English. An Arabic Dialect Annotation Toolkit ADAT was developped for the purpose of the annation. The annotators were trained on a set of guidelines and on how to use ADAT. We developed ADAT to assist the annotators and to ensure compatibility with SAMA and Curras tagsets. The tool is open source, and the four corpora are also available online.