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README.md

@@ -1,25 +1,144 @@
+
 ---
-dataset_info:
-  features:
-  - name: sentences
-    dtype: string
-  - name: tokens
-    sequence: string
-  - name: characters
-    sequence: string
-  - name: pos_labels
-    sequence: string
-  - name: space_labels
-    sequence: int64
-  splits:
-  - name: train
-    num_bytes: 1022649369
-    num_examples: 424181
-  download_size: 151255810
-  dataset_size: 1022649369
-configs:
-- config_name: default
-  data_files:
-  - split: train
-    path: data/train-*
+language:
+  - fa
+license: gpl-3.0
+size_categories:
+  - 100K<n<1M
 ---
+
+# Persian Space and ZWNJ Correction Dataset
+
+## Dataset Description
+
+### Dataset Summary
+
+This dataset contains Persian text annotated for space and Zero-Width Non-Joiner (ZWNJ) correction tasks. It consists of 424,181 examples derived from the Bijankhan and Peykare corpora. Each example includes the original sentence, tokenized text, character-level information, part-of-speech tags, and space labels.
+
+The dataset is designed for training models that can automatically correct spacing and ZWNJ usage in Persian text, addressing common orthographic issues in Persian digital text.
+
+### Languages
+
+The dataset contains text in Persian (Farsi) language.
+
+## Dataset Structure
+
+### Data Instances
+
+Each instance in the dataset contains:
+- `sentences`: The complete Persian text string
+- `tokens`: Tokenized form of the sentence
+- `characters`: Individual non-space characters from the sentence
+- `pos_labels`: Part-of-speech tags for each token
+- `space_labels`: Space and ZWNJ labels for each character
+
+### Data Fields
+
+- `sentences`: string - Full Persian text sentence
+- `tokens`: list of strings - The words/tokens in the sentence
+- `characters`: list of strings - Individual characters (excluding spaces and ZWNJ)
+- `pos_labels`: list of strings - POS tag for each token
+- `space_labels`: list of integers - Labels indicating proper space or ZWNJ placement:
+  - `0`: No space after the character
+  - `1`: Space after the character
+  - `2`: ZWNJ (Zero-Width Non-Joiner) after the character
+
+### Data Splits
+
+While the dataset does not come with predefined splits, in the original research, it was divided as follows:
+- 80% for training
+- 10% for validation
+- 10% for testing
+
+Users can recreate these splits or create custom splits as needed for their specific use cases.
+
+## Dataset Creation
+
+### Source Data
+
+#### Initial Data Collection and Normalization
+
+This dataset was derived from two major Persian corpora:
+
+- **Bijankhan Corpus**: A Persian tagged corpus developed for linguistics research and natural language processing.
+- **Peykare Corpus**: A comprehensive Persian corpus developed for language resources and evaluation.
+
+### Annotations
+
+The annotation process involved:
+
+[PLACEHOLDER: Brief description of the annotation procedure]
+
+For detailed information about the preprocessing, annotation, and labeling procedures, please refer to:
+
+[PAPER CITATION PLACEHOLDER]
+
+## Usage
+
+This dataset is intended for training and evaluating models for Persian space and ZWNJ correction. Several models have been trained using this dataset:
+
+- https://huggingface.co/PerSpaCor/bert-base-multilingual-uncased
+- https://huggingface.co/PerSpaCor/Relu-Norm
+- https://huggingface.co/PerSpaCor/DualStep-DropNet
+- https://huggingface.co/PerSpaCor/SimplexNet
+- https://huggingface.co/PerSpaCor/bert-base-multilingual-cased
+- https://huggingface.co/PerSpaCor/HooshvareLab-bert-base-parsbert-uncased
+- https://huggingface.co/PerSpaCor/HooshvareLab-bert-fa-zwnj-base
+- https://huggingface.co/PerSpaCor/HooshvareLab-roberta-fa-zwnj-base
+- https://huggingface.co/PerSpaCor/imvladikon-charbert-roberta-wiki
+
+### Example Code
+
+```python
+from datasets import load_dataset
+
+# Load the dataset
+dataset = load_dataset("PerSpaCor/bijankhan-peykare-annotated")
+
+# Sample usage
+example = dataset[0]
+print(f"Sentence: {example['sentences']}")
+print(f"Characters: {example['characters']}")
+print(f"POS Labels: {example['pos_labels']}")
+print(f"Space Labels: {example['space_labels']}")
+
+# Create splits if needed
+train_test = dataset.train_test_split(test_size=0.2)
+test_valid = train_test["test"].train_test_split(test_size=0.5)
+
+train_dataset = train_test["train"]
+valid_dataset = test_valid["train"]
+test_dataset = test_valid["test"]
+```
+
+## Citation
+
+If you use this dataset in your research, please cite:
+
+[PAPER CITATION PLACEHOLDER]
+
+And also cite the original corpora:
+
+```bibtex
+@article{bijankhan,
+  author = {Bijankhan, M.},
+  title = {The Role of Linguistic Structures in Writing Grammar: Introduction to a Computer Software},
+  journal = {Journal of Linguistics},
+  volume = {19},
+  number = {2},
+  pages = {48--67},
+  year = {2004}
+}
+
+@article{peykare,
+  author = {Bijankhan, M. and Sheykhzadegan, J. and Bahrani, M. and others},
+  title = {Lessons from building a Persian written corpus: Peykare},
+  journal = {Language Resources and Evaluation},
+  volume = {45},
+  number = {2},
+  pages = {143--164},
+  year = {2011},
+  doi = {10.1007/s10579-010-9132-x},
+  url = {https://doi.org/10.1007/s10579-010-9132-x}
+}
+```