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IBM/limit

438 downloads in 30 days11 likesLast modified 18 Jan 2024View on Hugging Face

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The checks could not identify a recognised licence ID for at least one declared source dataset.

Declared licence: cc-by-sa-4.0, from the tagEvidence: README.md at f2b5b14
Licence files: No licence file at the top level of the repositoryEvidence: file list at f2b5b14
Declared sources: 1
Access gated on Hugging Face: No

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net-activities-captionsnot foundUnclearEvidence: Hub page

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Citation text from the card

@inproceedings{manotas-etal-2020-limit,
    title = "{L}i{M}i{T}: The Literal Motion in Text Dataset",
    author = "Manotas, Irene  and
      Vo, Ngoc Phuoc An  and
      Sheinin, Vadim",
    booktitle = "Findings of the Association for Computational Linguistics: EMNLP 2020",
    month = nov,
    year = "2020",
    address = "Online",
    publisher = "Association for Computational Linguistics",
    url = "https://www.aclweb.org/anthology/2020.findings-emnlp.88",
    doi = "10.18653/v1/2020.findings-emnlp.88",
    pages = "991--1000",
    abstract = "Motion recognition is one of the basic cognitive capabilities of many life forms, yet identifying motion of physical entities in natural language have not been explored extensively and empirically. We present the Literal-Motion-in-Text (LiMiT) dataset, a large human-annotated collection of English text sentences describing physical occurrence of motion, with annotated physical entities in motion. We describe the annotation process for the dataset, analyze its scale and diversity, and report results of several baseline models. We also present future research directions and applications of the LiMiT dataset and share it publicly as a new resource for the research community.",
}

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dataset_licence({ "id": "IBM/limit" })
signal: "unclear"
stated_licence: "cc-by-sa-4.0"
sources: 1