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SloppyCalculator/SinFoS

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The declared licence (apache-2.0) is classified as permissive.

Declared licence: apache-2.0, from the tagEvidence: README.md at b0232d6
Licence files: No licence file at the top level of the repositoryEvidence: file list at b0232d6
Declared sources: None listed in the card metadata
Access gated on Hugging Face: No

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Citation text from the card

```python
@inproceedings{sofalas-etal-2026-sinfos,
    title = "{S}in{F}o{S}: A Parallel Dataset for Translating {S}inhala Figures of Speech",
    author = "Sofalas, Johan Nevin  and
      Pavithra, Dilushri  and
      Jayatilleke, Nevidu  and
      Weerasinghe, Ruvan",
    editor = {Ojha, Atul Kr.  and
      Mititelu, Verginica Barbu  and
      Constant, Mathieu  and
      Stoyanova, Ivelina  and
      Do{\u{g}}ru{\"o}z, A. Seza  and
      Rademaker, Alexandre},
    booktitle = "Proceedings of the 22nd Workshop on Multiword Expressions ({MWE} 2026)",
    month = mar,
    year = "2026",
    address = "Rabat, Marocco",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2026.mwe-1.2/",
    pages = "8--26",
    ISBN = "979-8-89176-363-0",
    abstract = "Figures of Speech (FOS) consist of multi-word phrases that are deeply intertwined with culture. While Neural Machine Translation (NMT) performs relatively well with the figurative expressions of high-resource languages, it often faces challenges when dealing with low-resource languages like Sinhala due to limited available data. To address this limitation, we introduce a corpus of 2,344 Sinhala figures of speech with cultural and cross-lingual annotations. We examine this dataset to classify the cultural origins of the figures of speech and to identify their cross-lingual equivalents. Additionally, we have developed a binary classifier to differentiate between two types of FOS in the

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dataset_licence({ "id": "SloppyCalculator/SinFoS" })
signal: "permissive"
stated_licence: "apache-2.0"
sources: 0