---
configs:
- config_name: engineering_human_factor
  data_files:
  - split: train
    path: data/engineering_human_factor.json
- config_name: material_science_additive_manufacturing
  data_files:
  - split: train
    path: data/material_science_additive_manufacturing.json
- config_name: physics_surface_enhanced_raman_spectroscopy
  data_files:
  - split: train
    path: data/physics_surface_enhanced_raman_spectroscopy.json
- config_name: public_health_infectious_disease_modeling
  data_files:
  - split: train
    path: data/public_health_infectious_disease_modeling.json
- config_name: earth_science_remote_sensing
  data_files:
  - split: train
    path: data/earth_science_remote_sensing.json
pretty_name: Intrabench
task_categories:
- question-answering
- text-classification
size_categories:
- n<1K
license: mit
language:
- en
---

# IntraBench Spaceholding

This dataset is a five-domain benchmark of multiple-choice research questions derived from scientific literature.
Each example represents one question-paper pair with a gold letter answer and supporting metadata.

## Subsets
- `engineering_human_factor`: Engineering - Human Factor
- `material_science_additive_manufacturing`: Material Science - Additive Manufacturing
- `physics_surface_enhanced_raman_spectroscopy`: Physics - Surface Enhanced Raman Spectroscopy
- `public_health_infectious_disease_modeling`: Public Health - Infectious-disease Modeling
- `earth_science_remote_sensing`: Earth Science - Remote Sensing

## Data Schema

Each record contains:

- `subject`: human-readable subject name
- `paper_id`: paper index within the subject subset
- `paper_title`: canonical benchmark paper title
- `question_id`: question identifier
- `question`: canonical benchmark question wording
- `choices`: answer choice dictionary keyed by `A`-`F`
- `answer`: gold answer letter
- `metadata`: extra metadata with:
  - `Task-oriented Category`
  - `question_key_term`
  - `term_explanation`

## Notes

- The published dataset excludes source PDFs, markdown paper extracts, and internal evaluation outputs.
- The benchmark uses canonical paper titles and normalized question wording across all five domains.
- Data files are stored as JSON arrays and exposed as separate Hugging Face configs.

## Citation

If you publish this dataset, add the benchmark paper citation here.