@inproceedings{ma-etal-2025-taxi1500,
    title = "Taxi1500: A Dataset for Multilingual Text Classification in 1500 Languages",
    author = "Ma, Chunlan  and
      Imani, Ayyoob  and
      Ye, Haotian  and
      Pei, Renhao  and
      Asgari, Ehsaneddin  and
      Schuetze, Hinrich",
    editor = "Chiruzzo, Luis  and
      Ritter, Alan  and
      Wang, Lu",
    booktitle = "Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 2: Short Papers)",
    month = apr,
    year = "2025",
    address = "Albuquerque, New Mexico",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/Author-Pages-WenzhengZhang-ZhengyanShi-ShuYang/2025.naacl-short.36/",
    doi = "10.18653/v1/2025.naacl-short.36",
    pages = "414--439",
    ISBN = "979-8-89176-190-2",
    abstract = "While broad-coverage multilingual natural language processing tools have been developed, a significant portion of the world{'}s over 7000 languages are still neglected. One reason is the lack of evaluation datasets that cover a diverse range of languages, particularly those that are low-resource or endangered. To address this gap, we present a large-scale text classification dataset encompassing 1504 languages many of which have otherwise limited or no annotated data. This dataset is constructed using parallel translations of the Bible. We develop relevant topics, annotate the English data through crowdsourcing and project these annotations onto other languages via aligned verses. We benchmark a range of existing multilingual models on this dataset. We make our dataset and code available to the public."
}