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Henok/age_dataset

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The checks could not identify a recognised licence ID in the dataset's metadata.

Declared licence: cc, from the tagEvidence: README.md at b7a3fe4
Licence files: No licence file at the top level of the repositoryEvidence: file list at b7a3fe4
Declared sources: None listed in the card metadata
Access gated on Hugging Face: No

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translation

Citation text from the card

@inproceedings{ademtew-birbo-2024-age,
    title = "{AGE}: {A}mharic, {G}e{'}ez and {E}nglish Parallel Dataset",
    author = "Ademtew, Henok  and
      Birbo, Mikiyas",
    editor = "Ojha, Atul Kr.  and
      Liu, Chao-hong  and
      Vylomova, Ekaterina  and
      Pirinen, Flammie  and
      Abbott, Jade  and
      Washington, Jonathan  and
      Oco, Nathaniel  and
      Malykh, Valentin  and
      Logacheva, Varvara  and
      Zhao, Xiaobing",
    booktitle = "Proceedings of the Seventh Workshop on Technologies for Machine Translation of Low-Resource Languages (LoResMT 2024)",
    month = aug,
    year = "2024",
    address = "Bangkok, Thailand",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2024.loresmt-1.14",
    doi = "10.18653/v1/2024.loresmt-1.14",
    pages = "139--145",
    abstract = "African languages are not well-represented in Natural Language Processing (NLP). The main reason is a lack of resources for training models. Low-resource languages, such as Amharic and Ge{'}ez, cannot benefit from modern NLP methods because of the lack of high-quality datasets. This paper presents AGE, an open-source tripartite alignment of Amharic, Ge{'}ez, and English parallel dataset. Additionally, we introduced a novel, 1,000 Ge{'}ez-centered sentences sourced from areas such as news and novels. Furthermore, we developed a model from a multilingual pre-trained language model, which brings 12.29 and 30.66 for English-Ge{'}ez and G

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dataset_licence({ "id": "Henok/age_dataset" })
signal: "unclear"
stated_licence: "cc"
sources: 0