| dataset_info: | |
| features: | |
| - name: messages | |
| list: | |
| - name: content | |
| dtype: string | |
| - name: role | |
| dtype: string | |
| - name: source | |
| dtype: string | |
| - name: ref_count | |
| dtype: int64 | |
| - name: languages | |
| list: string | |
| splits: | |
| - name: train_single | |
| num_bytes: 37115180 | |
| num_examples: 25772 | |
| - name: valid_single | |
| num_bytes: 1861539 | |
| num_examples: 1235 | |
| - name: train_group | |
| num_bytes: 12511678 | |
| num_examples: 725 | |
| - name: valid_group | |
| num_bytes: 987781 | |
| num_examples: 31 | |
| download_size: 11510722 | |
| dataset_size: 52476178 | |
| configs: | |
| - config_name: default | |
| data_files: | |
| - split: train_single | |
| path: data/train_single-* | |
| - split: valid_single | |
| path: data/valid_single-* | |
| - split: train_group | |
| path: data/train_group-* | |
| - split: valid_group | |
| path: data/valid_group-* | |
| # Reference Parsing Dataset for LoRA Training | |
| This dataset contains structured reference parsing examples for fine-tuning language models with LoRA. | |
| ## Dataset Description | |
| Two complementary datasets for training reference parsing models: | |
| - **Single**: Parse individual bibliographic references (25,772 train / 1,235 valid) | |
| - **Group**: Extract and parse references from documents (725 train / 31 valid) | |
| ## Data Sources | |
| - **LinkedBook**: 24,615 train / 1,055 valid tagged references (multilingual: Italian, English, French, German, Spanish) | |
| - **CEX**: 16 academic papers from 27 categories (96 reserved for testing) | |
| - **EXCITE**: 35 papers from 3 reference location classes (316 reserved for testing) | |
| ## Format | |
| Conversation-style JSON with system, user, and assistant messages. The assistant outputs structured JSON with reference fields including authors, title, journal, volume, pages, date, publisher, etc. | |
| ## Citation | |