Datasets:
license: cc-by-4.0
task_categories:
- text-classification
language:
- lb
size_categories:
- 10K<n<100K
configs:
- config_name: LETZ-SYN
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
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 Luxembourgish Entailment-based Topic classification via Zero-shot learning (LETZ) can be used to adapt language models to zero-shot classification in Luxembourgish. It leverages data from the Luxembourg Online Dictionary 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
- Paper: Forget NLI, Use a Dictionary: Zero-Shot Topic Classification for Low-Resource Languages with Application to Luxembourgish (Philippy et al., 2024)
- Source Data Luxembourg Online Dictionary
Source Data
The original Luxembourg Online Dictionary (LOD) data can be downloaded from the Luxembourgish Open Data Platform or can be accessed via their API. All of their data is available under a Creative Commons Zero (CC0) 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"
}