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language:
- en
configs:
- config_name: dataset
data_files:
- split: train
path: data/train-00001-of-00001.jsonl
- split: validation
path: data/dev-00001-of-00001.jsonl
default: true
- config_name: dictionary
data_files:
- split: kb
path: dictionary/dictionary-00001-of-00001.jsonl
size_categories:
- 100K<n<1M
---
# Dataset Card for ZELDA
ZELDA is a benchmark for Entity Disambiguation.
As there is no development split in ZELDA, we split the dataset using the first 90% for training and the remaining 10% for development.
For the entity dictionary, we use Wikipedia page ids and Wikidata descriptions processed by [Rücker and Akbik, 2025](https://github.com/flairNLP/VerbalizED).
## Dataset Description
- **Repository:** [https://github.com/flairNLP/zelda](https://github.com/flairNLP/zelda)
- **Public:** True
- **Source:** [Kensho Derived Wikimedia Dataset](https://www.kaggle.com/datasets/kenshoresearch/kensho-derived-wikimedia-data)
- **Paper:** [ZELDA: A Comprehensive Benchmark for Supervised Entity Disambiguation](https://aclanthology.org/2023.eacl-main.151/)
- **Number of Entities** 821401
### Citation Information
```
@inproceedings{milich2023zelda,
title={{ZELDA}: A Comprehensive Benchmark for Supervised Entity Disambiguation},
author={Milich, Marcel and Akbik, Alan},
booktitle={{EACL} 2023, The 17th Conference of the European Chapter of the Association for Computational Linguistics},
year={2023}
}
``` |