| Challenge: | Using a reading corpus in Modern Standard Arabic, we explore the lexical coverage of textbooks and unabridged works of fiction. |
| Approach: | They propose to use textbooks from the United Arab Emirates curriculum and a reading corpus in Modern Standard Arabic to enrich the sparse collection of resources available for educational applications. |
| Outcome: | The corpus spans all 12 grades and contains 129 unabridged works of fiction spanning grades 1-12 . lexical coverage is compared to other genres, and the results show that the two sub-corpora are similar to each other to measure their genres. |
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A Morphologically Annotated Corpus of Emirati Arabic (L18-1)
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| Challenge: | Emirati Arabic corpus is first large-scale morphologically manually annotated corpus . resources for dialectal Arabic NLP tasks are still lacking compared to those for modern standard Arabic (MSA). |
| Approach: | They propose to annotate a large-scale corpus of Emirati Arabic using a morphologically manually annotated corpus from eight Gumar novels . they discuss the guidelines for each part of the annotation components, and the annotation interface they use. |
| Outcome: | The annotated corpus includes about 200,000 words from eight Gumar novels in the Emirati Arabic variety. |
The SAMER Arabic Text Simplification Corpus (2024.lrec-main)
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| Challenge: | Our corpus includes 159K words selected from 15 publicly available Arabic fiction novels . text simplification aims to reduce the complexity of a text while maintaining the overall grammaticality and core content. |
| Approach: | They propose to annotate Arabic parallel corpus for text simplification targeting school-aged learners. |
| Outcome: | The SAMER Corpus includes readability level annotations at both the document and word levels, as well as two simplified parallel versions for each text targeting learners at two different readability levels. |
A Large and Balanced Corpus for Fine-grained Arabic Readability Assessment (2025.findings-acl)
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| Challenge: | Texts above a student's readability level can lead to disengagement and disengagement . Developing readability models is crucial for improving literacy, language learning, and academic performance. |
| Approach: | They introduce the Balanced Arabic Readability Evaluation Corpus (BAREC) a large-scale, fine-grained dataset for Arabic readability assessment. |
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The Bahrain Corpus: A Multi-genre Corpus of Bahraini Arabic (2022.lrec-1)
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| Challenge: | Various corpora of various sizes and representing different genres, have been created for various Arabic dialects. |
| Approach: | They propose to create a specialized corpus of Bahraini Arabic dialect, which includes written texts as well as transcripts of audio files. |
| Outcome: | The proposed corpus includes 620K words representing the Bahraini Arabic dialect . the annotated corpus is available to support researchers interested in Arabic NLP . |
A Large-Scale Leveled Readability Lexicon for Standard Arabic (2020.lrec-1)
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| Challenge: | a large-scale leveled readability lexicon for Modern Standard Arabic is not available in many other languages. |
| Approach: | They propose a large-scale leveled readability lexicon for Arabic with 26,000 lemmas . they manually annotate a lexico from three different regions in the arab world . |
| Outcome: | The proposed lexicon is publicly available for Arabic readability tasks. |
An Online Readability Leveled Arabic Thesaurus (2020.coling-demos)
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| Challenge: | a small minority of dictionaries specify the readability level of their words, let alone their lexical relations with other words. |
| Approach: | They propose to use Arabic lemmas, roots, English glosses, related Arabic words and phrases to provide a readability leveled Arabic thesaurus interface. |
| Outcome: | The proposed system provides the user with lemmas, roots, English glosses, related Arabic words and phrases, and readability on a five-level readability scale. |
Camel Treebank: An Open Multi-genre Arabic Dependency Treebank (2022.lrec-1)
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| Challenge: | CAMELTB is an open-source dependency treebank of Arabic with 13 sub-corpora . texts are publicly available (out of copyright, creative commons, or under open licenses) |
| Approach: | They present the Camel Treebank, a 188K word open-source dependency treebank of Arabic. |
| Outcome: | The CAMELTB is a 188K word open-source dependency treebank of Arabic . the texts are publicly available (out of copyright, creative commons, or under open licenses) |
The DReaM Corpus: A Multilingual Annotated Corpus of Grammars for the World’s Languages (2020.lrec-1)
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| Challenge: | Until recently, language descriptions were available in paper form only, with indexes as the only search aid. |
| Approach: | They propose to digitize a multilingual corpus of language descriptions and annotate it with various meta, word, and text attributes to make searching and analysis easier and more useful. |
| Outcome: | The proposed corpus is searchable through a couple of well-established corpus infrastructures. |
Annotating Verbal Multiword Expressions in Arabic: Assessing the Validity of a Multilingual Annotation Procedure (2022.lrec-1)
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Najet Hadj Mohamed, Cherifa Ben Khelil, Agata Savary, Iskandar Keskes, Jean-Yves Antoine, Lamia Hadrich-Belguith
| Challenge: | a subset of 1,062 sentences from the Prague Arabic Dependency Treebank PADT were selected and annotated by two Arabic native speakers independently. |
| Approach: | They propose to use Arabic as an annotation framework to extend PARSEME to modern standard Arabic by measuring inter-annotator agreement. |
| Outcome: | The proposed framework is based on a subset of 1,062 sentences from the Prague Arabic Dependency Treebank PADT and is already exceeding the smallest corpus of the PARSEME suite. |
The WAW Corpus: The First Corpus of Interpreted Speeches and their Translations for English and Arabic (L18-1)
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| Challenge: | Using the corpus, we study the characteristics of interpreters' work and train machine translation systems. |
| Approach: | They propose to build an interpreting corpus for Arabic and an Arabic corpus to study interpreters' work. |
| Outcome: | The proposed corpus can be used for teaching interpreters and to train machine translation systems. |