Datasets:
Tasks:
Text Classification
Modalities:
Text
Sub-tasks:
semantic-similarity-classification
Size:
100K<n<1M
Tags:
License:
| 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. | |
| ## 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). | |
| Please refer to [Languages](#languages) section to see in which languages training data is available. | |
| 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') | |
| ``` | |
| ## Languages | |
| Training data | |
| - en (English) | |
| - fr (French) | |
| - de (German) | |
| - it (Italian) | |
| **Dev & Test data** | |
| - fr (French) | |
| - de (German) | |
| - it (Italian) | |
| - bg (Bulgarian) | |
| - zh (Chinese) | |
| - hr (Croatian) | |
| - da (Danish) | |
| - nl (Dutch) | |
| - et (Estonian) | |
| - fa (Farsi) | |
| - ja (Japanesse) | |
| - ko (Korean) | |