All datasets / uctnlp

uctnlp/t2x

48 downloads in 30 days0 likesLast modified 18 Aug 2026View on Hugging Face

Use restrictions

The declared licence (cc-by-nc-sa-4.0) is classified as having use restrictions.

Declared licence: cc-by-nc-sa-4.0, from the tagEvidence: README.md at d4d06e4
Licence files: No licence file at the top level of the repositoryEvidence: file list at d4d06e4
Declared sources: None listed in the card metadata
Access gated on Hugging Face: No

Each cell links to what was checked: a file, a file list or a Hub record.

Tasks

text-generation

Citation text from the card

@inproceedings{meyer-buys-2024-triples,
    title = "Triples-to-isi{X}hosa ({T}2{X}): Addressing the Challenges of Low-Resource Agglutinative Data-to-Text Generation",
    author = "Meyer, Francois  and
      Buys, Jan",
    editor = "Calzolari, Nicoletta  and
      Kan, Min-Yen  and
      Hoste, Veronique  and
      Lenci, Alessandro  and
      Sakti, Sakriani  and
      Xue, Nianwen",
    booktitle = "Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)",
    month = may,
    year = "2024",
    address = "Torino, Italia",
    publisher = "ELRA and ICCL",
    url = "https://aclanthology.org/2024.lrec-main.1464/",
    pages = "16841--16854",
    abstract = "Most data-to-text datasets are for English, so the difficulties of modelling data-to-text for low-resource languages are largely unexplored. In this paper we tackle data-to-text for isiXhosa, which is low-resource and agglutinative. We introduce Triples-to-isiXhosa (T2X), a new dataset based on a subset of WebNLG, which presents a new linguistic context that shifts modelling demands to subword-driven techniques. We also develop an evaluation framework for T2X that measures how accurately generated text describes the data. This enables future users of T2X to go beyond surface-level metrics in evaluation. On the modelling side we explore two classes of methods - dedicated data-to-text models trained from scratch and pretrained language model

All datasets marked Use restrictions | JSON

The same facts for your agent

A free MCP server at mcp.datalicense.uk/mcp. Connect it from an MCP client such as Claude or Cursor.

dataset_licence({ "id": "uctnlp/t2x" })
signal: "restrictive"
stated_licence: "cc-by-nc-sa-4.0"
sources: 0