Datasets:
Tasks:
Text Classification
Modalities:
Text
Formats:
json
Languages:
Luxembourgish
Size:
10K - 100K
License:
| license: cc-by-4.0 | |
| task_categories: | |
| - text-classification | |
| language: | |
| - lb | |
| size_categories: | |
| - 10K<n<100K | |
| #source_datasets: | |
| #- Luxembourg Online Dictionary (LOD) | |
| configs: # Optional. This can be used to pass additional parameters to the dataset loader, such as `data_files`, `data_dir`, and any builder-specific parameters | |
| - config_name: LETZ-SYN # Example: default | |
| data_files: | |
| - split: train | |
| path: LETZ-SYN/train.json | |
| - split: validation | |
| path: LETZ-SYN/val.json | |
| - split: test | |
| path: LETZ-SYN/test.json | |
| - config_name: LETZ-WoT # Example: default | |
| data_files: | |
| - split: train | |
| path: LETZ-WoT/train.json | |
| - split: validation | |
| path: LETZ-WoT/val.json | |
| - split: test | |
| path: LETZ-WoT/test.json | |
| # Dataset Card for Luxembourgish Entailment-based Topic classification via Zero-shot learning (LETZ) | |
| ## Dataset Summary | |
| The datasets for **L**uxembourgish **E**ntailment-based **T**opic classification via **Z**ero-shot learning (**LETZ**) can be used to adapt language models to zero-shot classification in Luxembourgish. It leverages data from the [*Luxembourg Online Dictionary*](https://lod.lu) to provide relevant topic classification examples in Luxembourgish. The LETZ datasets were created to address the limitations of using Natural Language Inference (NLI) datasets for zero-shot classification in low-resource languages. Specifically, they aim to improve topic classification performance by providing more relevant and accessible data through dictionary entries. | |
| ## Columns in the Dataset | |
| Each dataset includes the following columns: | |
| * **Text**: The Luxembourgish sentence or phrase. | |
| * **Label**: The potentially associated topic label. | |
| * **Class**: A binary indicator where “1” denotes relevance (entailment) and “0” denotes irrelevance (non-entailment). | |
| ## Dataset Description | |
| - **Repository:** [fredxlpy/LETZ](https://github.com/fredxlpy/LETZ) | |
| - **Paper:** [Forget NLI, Use a Dictionary: Zero-Shot Topic Classification for Low-Resource Languages with Application to Luxembourgish (Philippy et al., 2024)](https://aclanthology.org/2024.sigul-1.13/) | |
| - **Source Data** [Luxembourg Online Dictionary](https://data.public.lu/en/datasets/letzebuerger-online-dictionnaire-lod-linguistesch-daten/) | |
| ## Source Data | |
| The original [Luxembourg Online Dictionary](https://lod.lu) (LOD) data can be downloaded from the [Luxembourgish Open Data Platform](https://data.public.lu/fr/datasets/letzebuerger-online-dictionnaire-lod-linguistesch-daten/) or can be accessed via their [API](https://data.public.lu/fr/datasets/letzebuerger-online-dictionnaire-lod-public-api/). All of their data is available under a [Creative Commons Zero (CC0)](https://creativecommons.org/publicdomain/zero/1.0/) license. | |
| ## Citation Information | |
| ``` | |
| @inproceedings{philippy-etal-2024-forget, | |
| title = "Forget {NLI}, Use a Dictionary: Zero-Shot Topic Classification for Low-Resource Languages with Application to {L}uxembourgish", | |
| author = "Philippy, Fred and | |
| Haddadan, Shohreh and | |
| Guo, Siwen", | |
| editor = "Melero, Maite and | |
| Sakti, Sakriani and | |
| Soria, Claudia", | |
| booktitle = "Proceedings of the 3rd Annual Meeting of the Special Interest Group on Under-resourced Languages @ LREC-COLING 2024", | |
| month = may, | |
| year = "2024", | |
| address = "Torino, Italia", | |
| publisher = "ELRA and ICCL", | |
| url = "https://aclanthology.org/2024.sigul-1.13", | |
| pages = "97--104" | |
| } | |
| ``` | |