Update README.md

README.md

@@ -1,108 +1,136 @@
-# Kalimat Arabic Text Corpus (Cleaned Edition)
-
-This repository provides a cleaned and consolidated version of the **Kalimat Arabic Text Corpus**, containing **18,256 Arabic news articles** collected from a diverse range of domains. The original material consisted of thousands of individual `.txt` files organised across multiple category folders. These have been reconstructed, normalised, and compiled into modern machine-learning-friendly formats.
-
----
-
-## 📚 Corpus Overview
-
-The corpus includes **20k+** articles covering a wide selection of news categories:
-
-- **Politics**
-- **Economy**
-- **Culture**
-- **Religion**
-- **Sport**
-- **Social / Society-related topics**
-- **Other sub-domains depending on the original folder structure**
-
-Each article was originally stored as *one word per line*. In this cleaned edition, all documents have been reconstructed into natural text format with proper spacing, UTF-8 encoding, and consistent metadata extraction.
-
-Although the original filenames varied widely, each document is now associated with the following fields:
-
-- **id** – numeric identifier extracted from the filename (or `-1` where none existed)
-- **filename** – original filename exactly as it appeared
-- **category** – derived from directory structure or filename
-- **year_month** – extracted from filename where possible, otherwise `"unknown"`
-- **text** – reconstructed, cleaned article text
-
----
-
-## 📦 Provided Formats
-
-The cleaned dataset is released in the following forms:
-
-### **1. CSV File**
-`kalimat.csv`
-
-A single UTF-8 CSV containing all metadata and article texts.
-
-### **2. JSONL File**
-`kalimat.jsonl`
-
-One JSON object per line, suitable for training modern NLP models (e.g. HuggingFace Transformers).
-
-### **3. TXT Version (Zipped)**
-`kalimat_txt.zip`
-
-All reconstructed `.txt` documents are included in a single compressed archive to avoid storing thousands of individual files in the repository. Each `.txt` file uses the original filename for easy reference.
-
----
-
-## 🔀 Train / Validation / Test Splits
-
-The dataset has been randomly split (using a fixed seed for reproducibility) into:
-
-- **Training set** – 80%
-- **Validation set** – 10%
-- **Test set** – 10%
-
-These splits are provided as:
-
-- `kalimat_train.csv`
-- `kalimat_val.csv`
-- `kalimat_test.csv`
-
-All CSVs preserve the same column structure as the main file.
-
-### Code used for splitting (for reference)
-
-```
-python
-import pandas as pd
-from sklearn.model_selection import train_test_split
-
-df = pd.read_csv("kalimat.csv", encoding="utf-8")
-
-train_df, temp_df = train_test_split(
-    df, test_size=0.20, random_state=42, shuffle=True
-)
-
-val_df, test_df = train_test_split(
-    temp_df, test_size=0.50, random_state=42, shuffle=True
-)
-
-train_df.to_csv("kalimat_train.csv", index=False, encoding="utf-8")
-val_df.to_csv("kalimat_val.csv", index=False, encoding="utf-8")
-test_df.to_csv("kalimat_test.csv", index=False, encoding="utf-8")
-```
-
-### 📁 Repository Structure
-```
-kalimat.csv
-kalimat.jsonl
-kalimat_train.csv
-kalimat_val.csv
-kalimat_test.csv
-kalimat_txt.zip
-README.md
-```
-
-## 📄 Citation
-
-If you use this dataset in your work, please cite the original Kalimat paper:
-
-El-Haj, M., & Koulali, R. (2013). _Kalimat: a multipurpose Arabic corpus_. In Second Workshop on Arabic Corpus Linguistics (WACL-2), pp. 22–25.  
-[PDF available here](https://elhaj.uk/docs/KALIMAT_ELHAJ_KOULALI.pdf)  
-
+---
+dataset_name: "KALIMAT"
+dataset_summary: "Kalimat - a multipurpose Arabic Corpus containing 18k+ news articles across multiple categories, provided in CSV, JSONL, and zipped TXT formats."
+language:
+  - ar
+license: "cc-by-4.0"
+task_categories:
+  - text-classification
+  - text-generation
+  - language-modeling
+pretty_name: "Kalimat - a multipurpose Arabic Corpus"
+size_categories:
+  - 10K<n<100K
+tags:
+  - arabic
+  - news
+  - corpus
+  - nlp
+  - low-resource
+configs:
+  - config_name: default
+    data_files:
+      - kalimat.csv
+      - kalimat.jsonl
+---
+
+
+
+# Kalimat - a multipurpose Arabic Corpus
+
+This repository provides a cleaned and consolidated version of the **Kalimat - a multipurpose Arabic Corpus**, containing **18,256 Arabic news articles** collected from a diverse range of domains. The original material consisted of thousands of individual `.txt` files organised across multiple category folders. These have been reconstructed, normalised, and compiled into modern machine-learning-friendly formats.
+
+---
+
+## 📚 Corpus Overview
+
+The corpus includes **20k+** articles covering a wide selection of news categories:
+
+- **Politics**
+- **Economy**
+- **Culture**
+- **Religion**
+- **Sport**
+- **Social / Society-related topics**
+- **Other sub-domains depending on the original folder structure**
+
+Each article was originally stored as *one word per line*. In this cleaned edition, all documents have been reconstructed into natural text format with proper spacing, UTF-8 encoding, and consistent metadata extraction.
+
+Although the original filenames varied widely, each document is now associated with the following fields:
+
+- **id** – numeric identifier extracted from the filename (or `-1` where none existed)
+- **filename** – original filename exactly as it appeared
+- **category** – derived from directory structure or filename
+- **year_month** – extracted from filename where possible, otherwise `"unknown"`
+- **text** – reconstructed, cleaned article text
+
+---
+
+## 📦 Provided Formats
+
+The cleaned dataset is released in the following forms:
+
+### **1. CSV File**
+`kalimat.csv`
+
+A single UTF-8 CSV containing all metadata and article texts.
+
+### **2. JSONL File**
+`kalimat.jsonl`
+
+One JSON object per line, suitable for training modern NLP models (e.g. HuggingFace Transformers).
+
+### **3. TXT Version (Zipped)**
+`kalimat_txt.zip`
+
+All reconstructed `.txt` documents are included in a single compressed archive to avoid storing thousands of individual files in the repository. Each `.txt` file uses the original filename for easy reference.
+
+---
+
+## 🔀 Train / Validation / Test Splits
+
+The dataset has been randomly split (using a fixed seed for reproducibility) into:
+
+- **Training set** – 80%
+- **Validation set** – 10%
+- **Test set** – 10%
+
+These splits are provided as:
+
+- `kalimat_train.csv`
+- `kalimat_val.csv`
+- `kalimat_test.csv`
+
+All CSVs preserve the same column structure as the main file.
+
+### Code used for splitting (for reference)
+
+```
+python
+import pandas as pd
+from sklearn.model_selection import train_test_split
+
+df = pd.read_csv("kalimat.csv", encoding="utf-8")
+
+train_df, temp_df = train_test_split(
+    df, test_size=0.20, random_state=42, shuffle=True
+)
+
+val_df, test_df = train_test_split(
+    temp_df, test_size=0.50, random_state=42, shuffle=True
+)
+
+train_df.to_csv("kalimat_train.csv", index=False, encoding="utf-8")
+val_df.to_csv("kalimat_val.csv", index=False, encoding="utf-8")
+test_df.to_csv("kalimat_test.csv", index=False, encoding="utf-8")
+```
+
+### 📁 Repository Structure
+```
+kalimat.csv
+kalimat.jsonl
+kalimat_train.csv
+kalimat_val.csv
+kalimat_test.csv
+kalimat_txt.zip
+README.md
+```
+
+## 📄 Citation
+
+If you use this dataset in your work, please cite the original Kalimat paper:
+
+El-Haj, M., & Koulali, R. (2013). _Kalimat: a multipurpose Arabic corpus_. In Second Workshop on Arabic Corpus Linguistics (WACL-2), pp. 22–25.  
+[PDF available here](https://elhaj.uk/docs/KALIMAT_ELHAJ_KOULALI.pdf)  
+
 ---