BAREC-10M / README.md
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---
license: cc-by-sa-4.0
task_categories:
- text-classification
language:
- ar
tags:
- readability
pretty_name: BAREC-10M Corpus v1.0
size_categories:
- 1M<n<10M
---
# BAREC-10M Corpus v1.0
## Corpus Summary
**BAREC-10M** is an expanded version of the [Balanced Arabic Readability Evaluation Corpus (BAREC)](https://huggingface.co/datasets/CAMeL-Lab/BAREC-Corpus-v1.0),
scaling from 1 million to 10 million words and broadening its scope to include balanced, multi-domain coverage.
Each text is labeled by **domain**, **genre**, and **readership level**,
and enriched with automatic **morphological**, **syntactic**, and **readability** analysis using state-of-the-art tools.
---
## Available Annotations
The corpus includes both document-level and sentence-level annotations.
**Document-level annotations** (manually labeled):
- **Domain**: `Arts & Humanities`, `Social Sciences`, or `STEM`
- **Readership Group**: `Foundational`, `Advanced`, or `Specialized`
- **Text Category**: `Educational Materials`, `Literature, Art & Music`, `Media & Culture`, `Academic`, `Encyclopedic`, or `Religion & Philosophy`
**Sentence-level annotations** (automatically generated):
- **Morphological analysis**
- **Syntactic parsing**
- **Readability leveling**
---
## Languages
- **Arabic** (Modern Standard Arabic)
---
## Corpus Details
The structure of the dataset directory is as follows:
```
.
├── Data/
│ ├── Metadata.xlsx
│ ├── Raw.zip
│ ├── Morphology_and_Readability.zip
│ ├── Syntax_CATiB.zip
│ └── Syntax_UD.zip
└── README.md
```
### Metadata
The metadata file contains the following fields:
- **Document**: Document file name (without extension)
- **Directory**: Document directory
- **Source**: Document source
- **Book**: Book title
- **Author**: Author name
- **Domain**
- **Readership Level**
- **Text Category**
- **Word Count**: Number of words in the document
- **Sentence Count**: Number of sentences in the document
- **In BAREC Corpus?**: Indicates whether the document originates from the original BAREC corpus (`Yes` or `No`)
### Raw Sentences
The corpus includes 20,535 `.txt` files containing raw sentences, organized into multiple directories according to the metadata.
### Morphology and Readability
The corpus includes 20,535 `.json` files containing morphological and readability annotations, organized into multiple directories according to the metadata.
Each JSON file represents a document and contains the following key-value pairs:
**Sentence-level features:**
- `raw_sents`: Raw sentences (list of strings)
- `sents_word_count`: Number of words per sentence (list of integers)
- `sents_RL`: Sentence-level readability scores (list of integers from 1 to 19). The value `###` indicates problematic sentences in documents originating from the BAREC corpus.
**Word-level features:**
- `word`: Tokenized words for all sentences (list of lists of strings)
- `lex`: Lemmas of all words (list of lists of strings)
- `pos`: Part-of-speech tags (list of lists of strings)
- `RL`: Readability levels of lemmas (list of lists of integers)
- `num`, `gen`, `mod`, etc.: Additional [CAMeL Morph](https://github.com/CAMeL-Lab/camel_morph) features of all words (list of lists of strings)
### Syntax
We provide syntactic annotations in both the [Columbia Arabic Treebank (CATiB)](https://aclanthology.org/P09-2056/) and [Universal Dependencies (UD)](https://aclanthology.org/W17-1320/) schemes.
The corpus includes 20,535 `.conllx` files per annotation scheme, each containing syntactic annotations and organized into multiple directories according to the metadata.
We recommend using the [Palmyra tool](https://camel-lab.github.io/palmyra/index.html) for visualization and analysis of these files.
---
## Usage
You can download the files manually using the Hub’s user interface, or use `snapshot_download` to download all files at once.
```python
from huggingface_hub import snapshot_download
snapshot_download(
repo_id="CAMeL-Lab/BAREC-10M",
repo_type="dataset",
local_dir="path/to/local/dir",
allow_patterns=["Data/*"]
)
```
---
## Citation
If you use BAREC-10M in your work, please cite the following paper:
```
@inproceedings{elmadani2026large,
author = {Elmadani, Khalid N. and Wizani, Adel Mahmoud and Taha-Thomure, Hanada and Habash, Nizar},
title = {A Large and Balanced Multi-Domain Arabic Corpus Annotated for Morphology, Syntax, and Readability},
booktitle = {Proceedings of the International Conference on Language Resources and Evaluation (LREC 2026)},
year = {2026},
address = {Palma, Mallorca, Spain}
}
```