| --- |
| license: cc-by-sa-4.0 |
| task_categories: |
| - text-classification |
| language: |
| - ar |
| tags: |
| - readability |
| size_categories: |
| - 1K<n<10K |
| pretty_name: 'BAREC 2025: Readability Assessment Shared Task' |
| --- |
| |
| # BAREC Shared Task 2025 |
|
|
| ## Dataset Summary |
|
|
| **BAREC** (the Balanced Arabic Readability Evaluation Corpus) is a large-scale dataset developed for the **BAREC Shared Task 2025**, focused on **fine-grained Arabic readability assessment**. The dataset includes over **1M words**, annotated across **19 readability levels**, with additional mappings to coarser 7, 5, and 3 level schemes. |
|
|
| The dataset is **annotated at the sentence level**. Document-level readability scores are derived by assigning each document the readability level of its **most difficult sentence**, based on the 19-level scheme. This provides both **sentence-level** and **document-level** readability information. |
|
|
| --- |
|
|
| ## Supported Tasks and Leaderboards |
|
|
| The dataset supports **multi-class readability classification** in the following formats: |
|
|
| - **19 levels** (default) |
| - **7 levels** |
| - **5 levels** |
| - **3 levels** |
|
|
| For details on the shared task, evaluation setup, and leaderboards, visit the [Shared Task Website](https://barec.camel-lab.com/sharedtask2025). |
|
|
| --- |
|
|
| ### Languages |
|
|
| - **Arabic** (Modern Standard Arabic) |
|
|
| --- |
|
|
| ## Dataset Structure |
|
|
| ### Data Instances |
|
|
| `{'ID': 1010219, 'Document': 'BAREC_Majed_1481_2007_038.txt', 'Sentences': '"موزة الحبوبة وشقيقها رشود\nآيس كريم بالكريمة..\nأم كريمة بالآيس كريم؟!"', 'Sentence_Count': 3, 'Word_Count': 15, 'Readability_Level': '8-Ha', 'Readability_Level_19': 8, 'Readability_Level_7': 3, 'Readability_Level_5': 2, 'Readability_Level_3': 1, 'Source': 'Majed', 'Book': 'Edition: 1481', 'Author': '#', 'Domain': 'Arts & Humanities', 'Text_Class': 'Foundational'}` |
|
|
| ### Data Fields |
|
|
| - **ID**: Unique document identifier. |
| - **Document**: Document file name. |
| - **Sentences**: Full text of the document. |
| - **Sentence_Count**: Number of sentences. |
| - **Word_Count**: Total word count. |
| - **Readability_Level**: The readability level in `19-levels` scheme, ranging from `1-alif` to `19-qaf`. |
| - **Readability_Level_19**: The readability level in `19-levels` scheme, ranging from `1` to `19`. |
| - **Readability_Level_7**: The readability level in `7-levels` scheme, ranging from `1` to `7`. |
| - **Readability_Level_5**: The readability level in `5-levels` scheme, ranging from `1` to `5`. |
| - **Readability_Level_3**: The readability level in `3-levels` scheme, ranging from `1` to `3`. |
| - **Source**: Document source. |
| - **Book**: Book name. |
| - **Author**: Author name. |
| - **Domain**: Domain (`Arts & Humanities`, `STEM` or `Social Sciences`). |
| - **Text_Class**: Readership group (`Foundational`, `Advanced` or `Specialized`). |
|
|
| ### Data Splits |
|
|
| - The BAREC dataset has three splits: *Train* (80%), *Dev* (10%), and *Test* (10%). |
| - The splits are in the document level. |
| - The splits are balanced accross *Readability Levels*, *Domains*, and *Text Classes*. |
|
|
| --- |
|
|
| ## Evaluation |
|
|
| We define the Readability Assessment task as an ordinal classification task. The following metrics are used for evaluation: |
|
|
| - **Accuracy (Acc<sup>19</sup>):** The percentage of cases where reference and prediction classes match in the 19-level scheme. |
| - **Accuracy (Acc<sup>7</sup>, Acc<sup>5</sup>, Acc<sup>3</sup>):** The percentage of cases where reference and prediction classes match after collapsing the 19 levels into 7, 5, or 3 levels, respectively. |
| - **Adjacent Accuracy (±1 Acc<sup>19</sup>):** Also known as off-by-1 accuracy. The proportion of predictions that are either exactly correct or off by at most one level in the 19-level scheme. |
| - **Average Distance (Dist):** Also known as Mean Absolute Error (MAE). Measures the average absolute difference between predicted and true labels. |
| - **Quadratic Weighted Kappa (QWK):** An extension of Cohen’s Kappa that measures the agreement between predicted and true labels, applying a quadratic penalty to larger misclassifications (i.e., predictions farther from the true label are penalized more heavily). |
|
|
| We provide evaluation scripts [here](https://github.com/CAMeL-Lab/barec-shared-task-2025). |
|
|
| --- |
|
|
| ## Citation |
|
|
| If you use BAREC in your work, please cite the following papers: |
|
|
| ``` |
| @inproceedings{elmadani-etal-2025-readability, |
| title = "A Large and Balanced Corpus for Fine-grained Arabic Readability Assessment", |
| author = "Elmadani, Khalid N. and |
| Habash, Nizar and |
| Taha-Thomure, Hanada", |
| booktitle = "Findings of the Association for Computational Linguistics: ACL 2025", |
| year = "2025", |
| address = "Vienna, Austria", |
| publisher = "Association for Computational Linguistics" |
| } |
| |
| @inproceedings{habash-etal-2025-guidelines, |
| title = "Guidelines for Fine-grained Sentence-level Arabic Readability Annotation", |
| author = "Habash, Nizar and |
| Taha-Thomure, Hanada and |
| Elmadani, Khalid N. and |
| Zeino, Zeina and |
| Abushmaes, Abdallah", |
| booktitle = "Proceedings of the 19th Linguistic Annotation Workshop (LAW-XIX)", |
| year = "2025", |
| address = "Vienna, Austria", |
| publisher = "Association for Computational Linguistics" |
| } |
| ``` |
