Datasets:
Add note on data schemata
Browse files
README.md
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@@ -2632,16 +2632,106 @@ translations into 221 Low-Resource Languages, for the purpose of training
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translation models, and otherwise increasing the representations of said
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languages in NLP and technology.
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Please read the [SMOL Paper](
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There are three resources in this directory:
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* **GATITOS:** token-level translations into 172 languages
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* **SmolSent:** sentence-level translations into 81 languages
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* **SmolDoc:** document-level translations into 100 languages
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* **SmolDoc-factuality-annotations:** factuality annotations and rationales
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for 661 documents from `SmolDoc`
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## Notes on the GATITOS multilingual Lexicon
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The GATITOS (Google's Additional Translations Into Tail-languages: Often Short)
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@@ -2649,11 +2739,12 @@ dataset is a high-quality, multi-way parallel dataset of tokens and short
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phrases, intended for training and improving machine translation models.
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Experiments on this dataset and Panlex focusing on unsupervised translation in
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a 208-language model can be found in
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-
[
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This dataset consists in 4,000 English segments (4,500 tokens) that have been
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translated into each of 173 languages,
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-
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directly from English, with the exception of Aymara, which was translated from
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the Spanish.
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translation models, and otherwise increasing the representations of said
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languages in NLP and technology.
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+
Please read the [SMOL Paper](https://arxiv.org/abs/2502.12301) and the
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[GATITOS Paper](https://arxiv.org/abs/2303.15265) for a much more
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thorough description!
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There are three resources in this directory:
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* **SmolDoc:** document-level translations into 100 languages
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+
* **SmolSent:** sentence-level translations into 81 languages
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+
* **GATITOS:** token-level translations into 172 languages
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* **SmolDoc-factuality-annotations:** factuality annotations and rationales
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for 661 documents from `SmolDoc`
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+
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## Data schemata
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The schemata are pretty straightforward. Source and Target languge are
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provided in `sl` and `tl` fields. The `is_src_orig` field has a value
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of `true` if the source text was the original text, and the target field
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was translated, and avalue of `false` if the data is back-translated.
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### SmolDoc
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SmolDoc provides sentence-split and aligned translations through the `srcs` and `trgs` fields. These will always have the same length.
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```
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{
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'id': 'topic_587__weyiwiniwaaotiwenwy',
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'sl': 'en',
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'tl': 'pcm',
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'is_src_orig': True,
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'factuality': 'ok', # this is a story so there is no factual claim that could be wrong
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'srcs': ['"What the hell are you doing, you idiot?!"',
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'"Excuse me?"',
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'"You cut me off! You almost made me crash!"',
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'"I\'m sorry, I didn\'t mean to. I was just trying to get around that slow-moving truck."',
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'"Well, you could have at least used your turn signal!"',
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'"I did use my turn signal!"',
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'"No, you didn\'t! You just pulled right out in front of me!"',
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'"I\'m telling you, I used my turn signal!"',
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'"Whatever. You\'re still a terrible driver."',
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'"And you\'re a jerk!"',
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'"At least I know how to drive!"',
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'"Oh, yeah? Well, I\'m a better writer than you are!"',
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'"That\'s debatable."',
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'"It\'s not debatable! I\'m Ernest Hemingway!"',
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'"Who?"',
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'"Ernest Hemingway! The greatest writer of all time!"',
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'"Never heard of him."',
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'"Well, you\'ve heard of me now!"',
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'"Yeah, I heard of you."'],
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'trgs': ['"Wetin di hell dey do, yu idiot?!"',
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'"Ekskuse mi?"',
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'"Yu komot mi! Yu almost make mi krash!"',
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'"I dey sorry, I nor wont do am. I just dey try get around dat truk wey slow."',
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'"Well, yu for don yus yor turn sign!"',
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'"I yus mai turn sign!"',
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'"No, yu nor turn am! Yu just turn rite in front of mi!"',
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'"I dey tell yu, I yus mai turn sign!"',
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'"Wateva. Yu still bi one tribol driva."',
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'"And yu bi jerk!"',
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'"At least I sabi hau to drive!"',
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'"Oh, yeah? Well, I bi ogbonge writa pass yu!"',
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'"Wi fit dibate dat."',
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'"nortin to dibate! I bi Ernest Hemingway!"',
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'"Who?"',
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'"Ernest Hemingway! De writa of all taim wey grate pass!"',
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'"Neva hear am."',
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'"Well, yu don hear mi nau!"',
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'"Na so, I don hear yu."']
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}
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```
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### SmolSent
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SmolSent's schema differs from SmolDoc's only in that `src` and `trg` are single strings, not lists:
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```
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{'id': 381,
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'sl': 'en',
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'tl': 'ber',
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'is_src_orig': True,
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'src': 'Rih, a deaf former soldier, plots rebellion while married to a queer, teenage god.',
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'trg': 'ⵔⵉⵀ, ⴷ ⴰⴷⴻⴼⵔⵉⵔ ⴰⵇⴱⵓⵔ ⴰⴻⵎⴻⵙⵍⵉ, ⵢⴻⵜⵜⵀⴻⴳⴳⵉ ⵜⴰⴴⴻⵡⵡⴰⵜ-ⵉⵙ, ⴴⴰⵙ ⴰⴽⴽⴻⵏ ⵢⴻⵣⵡⴻⴵ ⴷ ⵢⵉⵡⴻⵏ ⵢⵉⵍⵓ ⵉⵍⴻⵎⵥⵉ ⵉⵁⴻⵎⵎⵍⴻⵏ ⴰⵔⵔⴰⵛ.'
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}
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```
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### GATITOS
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GATITOS has a one-to-many schema, with each source mapping to one or more targets:
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```
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{
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'sl': 'en',
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'tl': 'aa',
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'is_source_orig': True,
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'src': 'how are you',
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'trgs': ['mannah taniih?', 'anninnaay?']
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}
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```
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## Notes on the GATITOS multilingual Lexicon
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The GATITOS (Google's Additional Translations Into Tail-languages: Often Short)
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phrases, intended for training and improving machine translation models.
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Experiments on this dataset and Panlex focusing on unsupervised translation in
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a 208-language model can be found in
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+
the [GATITOS paper](https://arxiv.org/abs/2303.15265).
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This dataset consists in 4,000 English segments (4,500 tokens) that have been
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translated into each of 173 languages, and as a 4001st token, the endonym.
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Of these, 170 are low-resource, and three
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are mid-high resource (es, fr, hi). All translations were made
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directly from English, with the exception of Aymara, which was translated from
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the Spanish.
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