---
language:
- km
license: cc-by-4.0
task_categories:
- text-generation
- fill-mask
- token-classification
pretty_name: Khmer Education PDF - Role-Playing Teaching Methods (Cleaned)
size_categories:
- n<1K
tags:
- khmer
- education
- pedagogy
- unicode-fixed
- cambodia
- southeast-asia
---

# Khmer Education PDF - Role-Playing Teaching Methods (Cleaned)

## Dataset Description

This dataset contains cleaned and Unicode-corrected text extracted from a 48-page Khmer educational PDF about role-playing teaching methods (ការបងៀនតាមវិធីសម្មែងតួ). The text has undergone comprehensive Unicode repair to fix 537 orphaned COENG characters and other extraction artifacts.

### Dataset Summary

- **Language:** Khmer (km)
- **Source:** Educational PDF - "New Generation Pedagogical Research Center"
- **Topic:** Role-playing teaching methods and pedagogical research
- **Pages:** 48
- **Characters:** 40,806 (after cleaning)
- **License:** CC-BY-4.0

### Supported Tasks

- Khmer language modeling
- Text generation
- Educational content analysis
- Tokenization benchmarking
- NLP research

## Dataset Structure

### Data Files

1. **pdf_text_fixed.txt** - Main cleaned text file (40,806 characters)
2. **coeng_repair_comparison.txt** - Before/after repair analysis
3. **pdf_unicode_analysis_report.txt** - Original Unicode analysis
4. **FINAL_PDF_ANALYSIS_REPORT.md** - Comprehensive technical report

### Data Fields

The main text file (`pdf_text_fixed.txt`) contains:
- **Format:** Plain text (UTF-8 encoded)
- **Encoding:** Unicode NFC normalized
- **Structure:** Sequential page extraction with page markers

## Data Cleaning Process

### Unicode Fixes Applied

#### 1. COENG Character Repair (537 fixes)
- Removed 295 COENG before vowels
- Removed 159 COENG before spaces
- Removed 32 COENG before punctuation
- Removed 23 COENG before diacritic signs
- Fixed 19 double COENG patterns
- Removed 8 other orphaned COENG

#### 2. Validation Results
- ✅ All COENG characters now properly formed (1,753 valid clusters)
- ✅ NFC Unicode normalization verified
- ✅ No invisible characters (zero-width spaces, joiners)
- ✅ Khmer text purity: 85.1%

### Quality Metrics

| Metric | Before | After | Improvement |
|--------|--------|-------|-------------|
| Total characters | 41,343 | 40,806 | -537 |
| Token count (km_8k) | 27,249 | 26,556 | -2.5% |
| Broken tokens | 13,698 | 13,030 | -4.9% |
| Tokens per char | 0.659 | 0.651 | -1.2% |
| Avg token length | 1.639 | 1.661 | +1.3% |

## Source Information

### Original PDF Details
- **Title:** អនុគរុសកាសលយជំនាន់ថ្មី (New Generation Pedagogical Research Center)
- **Subject:** ការបងៀនតាមវិធីសម្មែងតួ (Role-playing teaching methods)
- **Author:** Stanislas Kowalski (translated by Khmer educators)
- **Year:** 2025
- **Copyright:** © New Generation Pedagogical Research Center
- **Pages:** 48

### Content Overview
The document covers:
- Student participation and engagement strategies
- Vocabulary and grammar training methods
- Role-playing teaching principles
- Classroom implementation guidelines
- Feedback techniques
- Time management for role-play activities
- Scenario templates (basic, intermediate, advanced levels)
- Assessment frameworks

## Limitations and Known Issues

### Remaining Challenges
1. **Elevated TPC:** 0.651 (target: 0.40-0.45)
   - Indicates remaining text extraction quality issues
   - ~13,000 broken single-character tokens persist

2. **Word Spacing:** Some incorrect word boundaries remain
   - Missing spaces between words
   - Extra spaces within words

3. **OCR Artifacts:** Minor character substitutions may exist

### Recommended Use
- ✅ Educational content analysis
- ✅ Khmer NLP research and development
- ✅ Tokenization benchmarking
- ✅ Language model pre-training (after additional cleaning)
- ⚠️  Requires further word segmentation for production use

## Usage Example

### Load Text
```python
from datasets import load_dataset

# Load the dataset
dataset = load_dataset("khopilot/khmer-education-pdf-cleaned")

# Access the text
text = dataset['train']['text'][0]
print(f"Text length: {len(text):,} characters")
```

### Tokenization Test
```python
import sentencepiece as spm

# Load km_8k_production tokenizer
sp = spm.SentencePieceProcessor()
sp.load("path/to/km_8k_production/tokenizer.model")

# Tokenize
tokens = sp.encode_as_pieces(text)
print(f"Token count: {len(tokens):,}")
print(f"TPC: {len(tokens) / len(text):.3f}")
```

## Citation

If you use this dataset, please cite:

```bibtex
@dataset{khmer_education_pdf_cleaned_2025,
  title={Khmer Education PDF - Role-Playing Teaching Methods (Cleaned)},
  author={Kowalski, Stanislas and Khmer Pedagogical Team},
  year={2025},
  publisher={HuggingFace},
  url={https://huggingface.co/datasets/khopilot/khmer-education-pdf-cleaned},
  note={Unicode-corrected text with 537 COENG repairs}
}
```

## Dataset Creation

### Curation Process
1. PDF text extraction using `pypdf`
2. Unicode analysis with custom tools
3. Automated COENG repair (537 fixes)
4. Validation with km_8k_production tokenizer
5. Quality metrics calculation

### Tools Used
- Python 3.14
- pypdf 6.1.1
- sentencepiece 0.2.1
- khmer-data-curation-toolkit v1.0.0

### Processing Scripts
Available in the repository:
- `analyze_pdf_unicode.py` - Unicode analysis
- `fix_pdf_coeng.py` - COENG repair
- See `FINAL_PDF_ANALYSIS_REPORT.md` for full methodology

## License

**Text Content:** CC-BY-4.0 (attributed to original authors)
**Processing Scripts:** MIT License

Original copyright: © 2025 New Generation Pedagogical Research Center

## Contact

- **Curator:** khopilot
- **Repository:** https://github.com/khopilot/khmer-data-curation-toolkit
- **Issues:** Report data quality issues via HuggingFace discussions

## Changelog

### Version 1.0 (2025-10-13)
- Initial release
- Fixed 537 orphaned COENG characters
- Added comprehensive documentation
- Validated with km_8k_production tokenizer

---

**Last Updated:** October 13, 2025
**Dataset Version:** 1.0
**Status:** Stable