---
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
  - split: validation
    path: data/validation-*
  - split: test
    path: data/test-*
dataset_info:
  features:
  - name: text
    dtype: string
  - name: label
    dtype: string
  splits:
  - name: train
    num_bytes: 80400
    num_examples: 945
  - name: validation
    num_bytes: 18084
    num_examples: 203
  - name: test
    num_bytes: 17764
    num_examples: 202
  download_size: 57751
  dataset_size: 116248
license: cc-by-nc-sa-4.0
language:
- nl
---

Iconclass is a hierarchical system for classifying the subjects and content of artworks. Each artwork can be annotated with one or more Iconclass codes, where each code represents a specific concept depicted in the work. The dataset is sourced from the Netherlands Institute for Art History and includes annotations linked to artwork titles.
## Citation Information

If you find our paper, benchmark or models helpful, please consider cite as follows:
```latex
@misc{banar2025mtebnle5nlembeddingbenchmark,
      title={MTEB-NL and E5-NL: Embedding Benchmark and Models for Dutch}, 
      author={Nikolay Banar and Ehsan Lotfi and Jens Van Nooten and Cristina Arhiliuc and Marija Kliocaite and Walter Daelemans},
      year={2025},
      eprint={2509.12340},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2509.12340}, 
}
```
[//]: # (https://arxiv.org/abs/2509.12340)

The data source:

```latex
@article{banar2023transfer,
  title={Transfer learning for the visual arts: The multi-modal retrieval of iconclass codes},
  author={Banar, Nikolay and Daelemans, Walter and Kestemont, Mike},
  journal={ACM Journal on Computing and Cultural Heritage},
  volume={16},
  number={2},
  pages={1--16},
  year={2023},
  publisher={ACM New York, NY}
}

```