Add BAREC-X data and dataset card

README.md

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+---
+license: cc-by-sa-4.0
+language:
+- ar
+pretty_name: BAREC-X
+task_categories:
+- text-classification
+size_categories:
+- 1K<n<10K
+tags:
+- readability
+- arabic
+- explanations
+configs:
+- config_name: annotations
+  default: true
+  data_files: annotations.parquet
+- config_name: gpt
+  data_files: gpt.parquet
+- config_name: gemini
+  data_files: gemini.parquet
+- config_name: rule_based
+  data_files: rule_based.parquet
+- config_name: labels
+  data_files: labels.parquet
+source_datasets:
+- CAMeL-Lab/BAREC-Corpus-v1.0
+---
+
+# BAREC-X
+
+BAREC-X is the first explanation-annotated Arabic readability dataset. It contains 1,793 sentences from the [Balanced Arabic Readability Evaluation Corpus (BAREC)](https://huggingface.co/datasets/CAMeL-Lab/BAREC-Corpus-v1.0), each with its BAREC readability level (1–19, from early literacy to postgraduate comprehension) and the linguistic reasons that justify that level, 
+selected by expert annotators from the BAREC annotation guidelines along six dimensions: spelling, word count, morphology, syntax, vocabulary and content.
+
+The sentences come from the inter-annotator agreement portion of BAREC and were annotated by three native Arabic-speaking educators.
+About 300 sentences were labelled by all three; 
+for those, the released labels are the reasons at least two annotators agreed on.
+
+The release also includes the labels predicted for the same sentences by GPT-5.5 and Gemini-3-Flash (four-shot prompting) and by a training-free rule-based system, plus the full label inventory.
+
+BAREC-X was introduced in *Benchmarking Fine-Grained Readability Explanations for Arabic* (Rabih, Elmadani, Taha-Thomure and Habash). Project page: https://barec.camel-lab.com/
+
+
+## Content
+
+| Config | Rows | What it holds |
+|---|---|---|
+| `annotations` (default) | 1,793 | Human annotations: sentence, readability level, labels. |
+| `gpt` | 1,793 | Labels predicted by GPT-5.5 with four-shot prompting. |
+| `gemini` | 1,793 | Labels predicted by Gemini-3-Flash with four-shot prompting. |
+| `rule_based` | 1,793 | Labels predicted by the training-free rule-based system. |
+| `labels` | 148 | The label inventory: code, dimension, level, Arabic description. |
+
+
+The four sentence tables have the same 1,793 rows in the same order and share the `id` column, so they can be joined on `id` or compared row by row.
+
+All three systems receive the sentence and its gold readability level and return the reasons that justify that level.
+The LLM prompts contain a task description, the BAREC guideline excerpt for the sentence's level, and four example sentences with their gold reasons.
+The rule-based system extracts its features with CAMeL Tools 1.5.6 and CamelParser 2.0 and returns the activated reasons whose guideline level matches the given level.
+
+
+## Loading
+
+```python
+from datasets import load_dataset
+
+repo = "CAMeL-Lab/BAREC-X"
+gold = load_dataset(repo)                 # human annotations
+gpt = load_dataset(repo, "gpt")           # also "gemini", "rule_based"
+labels = load_dataset(repo, "labels")     # code -> Arabic description
+```
+
+## `annotations`
+
+| Column | Type | Description |
+|---|---|---|
+| `id` | string | Unique 11-digit sentence identifier. |
+| `sentence` | string | The Arabic sentence. |
+| `readability_level` | int | Readability level, 1–19. |
+| `spelling` | list of string | Spelling label codes (prefix `O`). |
+| `word_count` | list of string | Word-count label codes (prefix `W`). |
+| `morphology` | list of string | Morphology label codes (prefix `M`). |
+| `syntax` | list of string | Syntax label codes (prefix `S`). |
+| `vocabulary` | list of string | Vocabulary label codes (prefix `V`). |
+| `content` | list of string | Content label codes (prefix `C`). |
+
+A dimension with no label is an empty list. A sentence can carry more than one label, in the same dimension or across dimensions.
+
+Example row:
+
+```json
+{"id": "10600010006", "sentence": "عالم غريب المعالم", "readability_level": 11, "spelling": [], "word_count": [], "morphology": [], "syntax": ["S11-2"], "vocabulary": [], "content": []}
+```
+
+## `gpt`, `gemini`, `rule_based`
+
+These are the outputs of the systems. They contain the same columns as `annotations` without `readability_level`: `id`, `sentence`, and the six label lists holding that system's predictions. The `sentence` text is identical to `annotations`.
+
+## `labels`
+
+| Column | Type | Description |
+|---|---|---|
+| `code` | string | Label code, e.g. `S10-2`. |
+| `dimension` | string | One of `spelling`, `word_count`, `morphology`, `syntax`, `vocabulary`, `content`. |
+| `level` | int or null | The BAREC readability level the label belongs to. Null for the "other" codes. |
+| `description_ar` | string | The label's description in Arabic. |
+| `num_sentences` | int | Number of sentences carrying this label in the human annotations. |
+
+A code has the form `<dimension letter><level>-<index>`: `S10-2` is the second syntax label of level 10. Codes ending in `-O` (`M-O`, `S-O`, `V-O`, `C-O`) mean "other" and have no level.
+
+Sentences per readability level:
+
+| Level | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | 14 | 15 | 16 | 17 | 18 | 19 |
+|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
+| Sentences | 4 | 12 | 34 | 10 | 49 | 55 | 134 | 130 | 61 | 209 | 89 | 423 | 93 | 337 | 75 | 47 | 23 | 3 | 5 |
+
+
+## Citation
+
+```bibtex
+TODO
+```

annotations.parquet

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+size 163610

gemini.parquet

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gpt.parquet

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+size 162280

labels.parquet

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+size 7474

rule_based.parquet

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