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nusa-crowd's Introduction

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Contributors

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Forkers

gentaiscool algonacci ilhamfp setyanp bagasstrongman faridlazuarda surfacedata ikhlasulhanif devsalman zikranazir fatyanosa atoxcode kaustubhdhole madenindya roannarum dataodyssy nadyadtm fhudi rayendito tysonyu angelica-inc bryanwilie samuelcahyawijaya vpsea ryanignatius wenliangdai yana-xuyan rifkiaputri acul3 jen-santoso aliakbars vanillamacchiato budikurniawan-github iamfinethanksu christianwbsn ivanhalimp cahya-wirawan rizkyramadhana26 ziweiji yasirabd zaklabs pro-coder04 ranggakd riagusmita asep-fajar-firmansyah dindapusparahmi haryoa eltociear rizquuula emmanueldavee shadieqq catlaughing zaenalium javis16 isa96 seacrowd mutiarais

nusa-crowd's Issues

How to contribute rubric

From earlier discussion

== Rarity ==
Rare / No resource: No public dataset
Uncommon: There are some resources on this language, but very hard to find.
Common: At least there are 3 datasets publicly available
Very common: At least there are 5 datasets publicly available

== Scoring ==
To determine the point I would like to suggest the following point system:
Size: (S: 1, M: 2, L: 3, XL: 4)
Rarity: (Common: 2, Uncommon: 3, Rare: 4)
Quality: (Not qualified: 0, Poor: 0.5, Good: 1, Excellent: 1.5)

  • labeled and verified by human -> Excellent
  • generated/scraped by machine, verified by human -> Good
  • labeled by human, but no verification -> Good
  • generated/scraped by machine, no verification -> Poor

Minimal point: 3

Final point = (size + rarity) * quality * license

We only accept publicly available datasets!

test

Adding a Dataset

  • Name: name of the dataset
  • Dataset Description: short description of the dataset (or link to social media or blog post)
  • Dataset URL: original URL of the dataset
  • Dataset Publication: link to the dataset publication if available
  • Task: The task(s) covered on the dataset
  • Languages: list of languages included in the dataset. Put 3-digit ISO 639-3 code. (i.e. ind, sun, min, ...)
  • Dialect/Style (optional): the dialect of the dataset (eg. Jawa ngapak, Bali dataran rendah, etc) if available
  • Domain: the domain/source of the dataset? (eg. News, law, reviews, social media, etc) if available
  • Dataset Size: the size of the dataset in terms of number of samples. If the dataset has pre-existing split, please report them individualy. (eg. 2000 train, 500 dev, 1000 test).
  • Is Synthetic: Yes/No. Put yes if the dataset is generated synthetically somehow, for example by translating from other languages, or by generating from language models, or CFG, etc2.
  • License: Type of license; please provide public for new datasets
  • Motivation: what are some good reasons to have this dataset

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