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).

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"
}