gated: auto
extra_gated_fields:
Email: text
First Name: text
Last Name: text
Affiliation: text
What do you plan to use this resource for?: text
I agree to use the data in accordance with the license specified in the dataset card: checkbox
license: cc-by-sa-4.0
language:
- ar
pretty_name: BAREC-LexRank
size_categories:
- 10K<n<100K
BAREC-LexRank: A Ranked Arabic Readability Lexicon
Summary
BAREC-LexRank is a ranked readability lexicon of 40K Arabic open-class lemmas (adjectives, nouns, proper nouns, and verbs), ordered from easiest to hardest to read and understand. Instead of assigning lemmas to a small number of coarse levels, it provides a continuous ordering that captures fine-grained readability differences between lemmas.
The lexicon was built using BAREC-LexBench, a benchmark of 36K expert-annotated lemma pairs, and is released together with two variants:
| Config | Coverage | Ordering |
|---|---|---|
lexrank (default) |
Open-class lemmas | Fully model-ranked |
lexcomplete |
All lemmas, open- and closed-class | Fully model-ranked |
lexsamer |
Open-class lemmas | SAMER level order preserved; ranking only within each SAMER level |
Languages
- Arabic (Modern Standard Arabic)
Structure
The structure of this repository is as follows:
.
├── Data/
│ ├── BAREC-LexRank.xlsx
│ ├── BAREC-LexComplete.xlsx
│ ├── BAREC-LexSAMER.xlsx
└── README.md
Metadata
Each file contains the following fields:
- Sort ID: Unique lemma identifier reflecting its rank (lower is easer).
- Lex: The lemma, with diacritics.
- POS: The part of speech of the lemma.
All Lex-POS pairs match the SAMA S31 analyzer.
Usage
You can download the files manually using the Hub’s user interface, or use snapshot_download to download all files at once.
from huggingface_hub import snapshot_download
snapshot_download(
repo_id="CAMeL-Lab/BAREC-LexRank",
repo_type="dataset",
local_dir="path/to/local/dir",
allow_patterns=["Data/*"]
)
Citation
If you use BAREC-LexBench in your work, please cite the following paper:
@inproceedings{elmadani-etal-2026-barec-lex,
title = "A Benchmark for Arabic Lemma-Level Readability Assessment",
author = "Elmadani, Khalid N. and Saeed, Mostafa and Taha-Thomure, Hanada and Habash, Nizar",
booktitle = "Proceedings of the 2026 Conference on Empirical Methods in Natural Language Processing",
month = oct,
year = "2026",
address = "Budapest, Hungary",
publisher = "Association for Computational Linguistics"
}