README.md

---
annotations_creators:
- expert-generated
extended:
- original
language_creators:
- found
languages:
- en
- bg
- zh
- hr
- da
- nl
- et
- fa
- ja
- ko
- it
- fr
- de
licenses:
- cc-by-nc-4.0
multilinguality:
- multilingual
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- text-classification
task_ids:
- semantic-similarity-classification
---

# XL-WiC
Huggingface dataset for the XL-WiC paper [https://www.aclweb.org/anthology/2020.emnlp-main.584.pdf](https://www.aclweb.org/anthology/2020.emnlp-main.584.pdf).
Please refer to the official [website](https://pilehvar.github.io/xlwic/) for more information.

## Languages
XL-WiC provides training data in:
- en (English)
- fr (French)
- de (German)
- it (Italian)

and dev and test data in:
- fr (French)
- de (German)
- it (Italian)
- bg (Bulgarian)
- zh (Chinese)
- hr (Croatian)
- da (Danish)
- nl (Dutch)
- et (Estonian)
- fa (Farsi)
- ja (Japanesse)
- ko (Korean)

## Configurations
When loading one of the XL-WSD datasets one has to specify the training language and the target language (on which dev and test will be performed).
For example, we can load the dataset having English as training language and Italian as target language as follows:
```python
from datasets import load_dataset
dataset = load_dataset('pasinit/xlwic', 'en_it')
```