---
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