Update README.md

README.md

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----
-license: cc-by-sa-4.0
----
+---
+license: cc-by-sa-4.0
+task_categories:
+- text-classification
+language:
+- ar
+tags:
+- readability
+size_categories:
+- 10K<n<100K
+pretty_name: BAREC Corpus v1.0
+---
+
+# BAREC Corpus v1.0
+
+## Dataset Summary
+
+**BAREC** (the Balanced Arabic Readability Evaluation Corpus) is a large-scale dataset for **fine-grained Arabic readability assessment**.
+The dataset includes over **1M words**, annotated at the **sentence level** across **19 readability levels**, with additional mappings to coarser 7, 5, and 3 level schemes.
+
+---
+
+## Supported Tasks
+
+The dataset supports **multi-class readability classification** in the following formats:
+
+- **19 levels** (default)
+- **7 levels**
+- **5 levels**
+- **3 levels**
+
+---
+
+### Languages
+
+- **Arabic** (Modern Standard Arabic)
+
+---
+
+## Dataset Structure
+
+### Data Instances
+
+`{'ID': 10100010008, 'Sentence': 'عيد سعيد', 'Word_Count': 2, 'Word': 'عيد سعيد', 'Lex': 'عيد سعيد', 'D3Tok': 'عيد سعيد', 'D3Lex': 'عيد سعيد', 'Readability_Level': '2-ba', 'Readability_Level_19': 2, 'Readability_Level_7': 1, 'Readability_Level_5': 1, 'Readability_Level_3': 1, 'Annotator': 'A4', 'Document': 'BAREC_Majed_0229_1983_001.txt', 'Source': 'Majed', 'Book': 'Edition: 229', 'Author': '#', 'Domain': 'Arts & Humanities', 'Text_Class': 'Foundational'}`
+
+### Data Fields
+
+- **ID**: Unique sentence identifier.
+- **Sentence**: The sentence text.
+- **Word_Count**: Number of words in the sentence.
+- **Word**: Simply tokenized and dediacritized sentences.
+- **Lex**: Each word is replaced by its predicited lemma (dediacritized).
+- **D3Tok**: We tokenize words into their base and clitics forms.
+- **D3Lex**: We replace the base forms in **D3Tok** with the predicited lemmas.
+- **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`.
+- **Annotator**: The annotator ID (`A1-A5` or `IAA`).
+- **Document**: Source document file name.
+- **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).
+
+---
+
+## 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"
+}
+```