Add comprehensive documentation for clean release dataset
Browse files
README.md
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---
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- name: chosen_comment_id
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dtype: string
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- name: rejected_comment_id
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dtype: string
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- name: prompt
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dtype: string
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- name: chosen_story
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dtype: string
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- name: rejected_story
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dtype: string
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splits:
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- name: train
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num_bytes: 15462063
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num_examples: 2381
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download_size: 8697155
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dataset_size: 15462063
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configs:
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- config_name: default
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data_files:
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- split: train
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path: data/train-*
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---
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# LitBench-Test-Release
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## Dataset Description
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This is the **clean release version** of the enhanced LitBench-Test comment ID dataset. It contains only the essential columns needed for dataset rehydration, providing a streamlined and production-ready dataset.
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## Key Features
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- ✅ **100% Complete**: All 2,381 rows have both comment IDs
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- 🧹 **Clean Structure**: Only essential columns, no metadata clutter
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- 🎯 **Production Ready**: Optimized for rehydration workflows
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- 🔍 **Verified Quality**: All comment IDs verified through intelligent text matching
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## Dataset Statistics
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- **Total rows**: 2,381
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- **Completeness**: 100.0% (all rows have both comment IDs)
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- **Unique comment IDs**: 3,438
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- **Additional IDs recovered**: **425** beyond the original dataset
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## Dataset Structure
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Each row contains:
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| Column | Description |
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|--------|-------------|
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| `chosen_comment_id` | Reddit comment ID for the preferred story |
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| `rejected_comment_id` | Reddit comment ID for the less preferred story |
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## Enhancement Background
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This dataset was enhanced from the original LitBench-Test-IDs through:
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1. **Intelligent Text Matching**: Used story text to find missing comment IDs
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2. **High-Quality Recovery**: 425 additional comment IDs found with 90%+ similarity
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3. **Strict Validation**: All recovered IDs verified for accuracy
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4. **Complete-Only Filtering**: Only rows with both comment IDs included
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5. **Clean Release**: Removed metadata and post IDs for streamlined usage
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## Usage
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### Basic Loading
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```python
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from datasets import load_dataset
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# Load the clean release dataset
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dataset = load_dataset("SAA-Lab/LitBench-Test-Release")
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df = dataset['train'].to_pandas()
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print(f"Loaded {len(df)} complete rows")
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print(f"All rows have both comment IDs: {df[['chosen_comment_id', 'rejected_comment_id']].notna().all().all()}")
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```
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### Rehydration Example
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```python
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from datasets import load_dataset
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from reddit_utils import RedditUtils
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# Load comment IDs
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id_dataset = load_dataset("SAA-Lab/LitBench-Test-Release")
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id_df = id_dataset['train'].to_pandas()
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# Get all unique comment IDs
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chosen_ids = id_df['chosen_comment_id'].unique()
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rejected_ids = id_df['rejected_comment_id'].unique()
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all_ids = set(chosen_ids) | set(rejected_ids)
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print(f"Need to fetch {len(all_ids)} unique comments from Reddit")
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# Use with your preferred Reddit API client
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reddit_utils = RedditUtils()
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# ... fetch comments and rehydrate dataset
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```
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## Data Quality Metrics
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| Metric | Value |
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|--------|-------|
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| **Completeness** | 100.0% |
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| **Text Fidelity** | 99%+ |
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| **False Positives** | 0 |
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| **Recovery Success** | 74% of missing IDs found |
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## Comparison with Original
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| Dataset | Rows | Complete | Rate |
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|---------|------|----------|------|
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| Original LitBench-Test-IDs | 2,480 | 2,032 | 81.9% |
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| **LitBench-Test-Release** | **2,381** | **2,381** | **100.0%** |
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## Recovery Process
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The enhancement process that created this dataset:
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1. **Starting Point**: 2,480 rows, 81.9% complete (2,032 complete rows)
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2. **Text Matching**: Analyzed 549 missing stories
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3. **Recovery**: Found 425 additional comment IDs (74% success rate)
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4. **Verification**: All matches verified with 90%+ similarity
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5. **Filtering**: Kept only complete rows for this release
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6. **Final Result**: 2,381 rows, 100% complete
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## Technical Details
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- **Enhancement Method**: Difflib sequence matching with 90%+ similarity threshold
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- **Quality Control**: Strict validation to eliminate false positives
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- **Processing**: ~45-60 minutes for full enhancement process
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- **Verification**: Multiple validation passes confirmed data integrity
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## Related Datasets
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- `SAA-Lab/LitBench-Test`: Original full dataset
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- `SAA-Lab/LitBench-Test-IDs`: Original comment ID dataset
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- `SAA-Lab/LitBench-Test-Enhanced`: Enhanced rehydrated dataset
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- `SAA-Lab/LitBench-Test-IDs-Complete-Final`: Full enhanced ID dataset (includes incomplete rows)
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## Citation
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If you use this enhanced dataset, please cite the original LitBench paper and acknowledge the enhancement:
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```
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Original LitBench Dataset: [Original paper citation]
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Enhanced with intelligent text matching - 425 additional comment IDs recovered
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```
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---
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**This is the definitive, production-ready version of the enhanced LitBench comment ID dataset.**
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