Referencias:
Texto sin formato
Utilice el siguiente comando para cargar este conjunto de datos en TFDS:
ds = tfds.load('huggingface:wmt20_mlqe_task3/plain_text')
- Descripción :
This shared task (part of WMT20) will build on its previous editions
to further examine automatic methods for estimating the quality
of neural machine translation output at run-time, without relying
on reference translations. As in previous years, we cover estimation
at various levels. Important elements introduced this year include: a new
task where sentences are annotated with Direct Assessment (DA)
scores instead of labels based on post-editing; a new multilingual
sentence-level dataset mainly from Wikipedia articles, where the
source articles can be retrieved for document-wide context; the
availability of NMT models to explore system-internal information for the task.
The goal of this task 3 is to predict document-level quality scores as well as fine-grained annotations.
- Licencia : Desconocido
- Versión : 1.1.0
- Divisiones :
| Separar | Ejemplos |
|---|---|
'test' | 180 |
'train' | 1448 |
'validation' | 200 |
- Características :
{
"document_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"source_segments": {
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"dtype": "string",
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"_type": "Value"
},
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},
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"mt_segments": {
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},
"mt_tokenized": {
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},
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},
"annotations": {
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"severity": {
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"names": [
"minor",
"major",
"critical"
],
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},
"severity_weight": {
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},
"category": {
"num_classes": 45,
"names": [
"Addition",
"Agreement",
"Ambiguous Translation",
"Capitalization",
"Character Encoding",
"Company Terminology",
"Date/Time",
"Diacritics",
"Duplication",
"False Friend",
"Grammatical Register",
"Hyphenation",
"Inconsistency",
"Lexical Register",
"Lexical Selection",
"Named Entity",
"Number",
"Omitted Auxiliary Verb",
"Omitted Conjunction",
"Omitted Determiner",
"Omitted Preposition",
"Omitted Pronoun",
"Orthography",
"Other POS Omitted",
"Over-translation",
"Overly Literal",
"POS",
"Punctuation",
"Shouldn't Have Been Translated",
"Shouldn't have been translated",
"Spelling",
"Tense/Mood/Aspect",
"Under-translation",
"Unidiomatic",
"Unintelligible",
"Unit Conversion",
"Untranslated",
"Whitespace",
"Word Order",
"Wrong Auxiliary Verb",
"Wrong Conjunction",
"Wrong Determiner",
"Wrong Language Variety",
"Wrong Preposition",
"Wrong Pronoun"
],
"names_file": null,
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}
},
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"token_annotations": {
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"major",
"critical"
],
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},
"category": {
"num_classes": 45,
"names": [
"Addition",
"Agreement",
"Ambiguous Translation",
"Capitalization",
"Character Encoding",
"Company Terminology",
"Date/Time",
"Diacritics",
"Duplication",
"False Friend",
"Grammatical Register",
"Hyphenation",
"Inconsistency",
"Lexical Register",
"Lexical Selection",
"Named Entity",
"Number",
"Omitted Auxiliary Verb",
"Omitted Conjunction",
"Omitted Determiner",
"Omitted Preposition",
"Omitted Pronoun",
"Orthography",
"Other POS Omitted",
"Over-translation",
"Overly Literal",
"POS",
"Punctuation",
"Shouldn't Have Been Translated",
"Shouldn't have been translated",
"Spelling",
"Tense/Mood/Aspect",
"Under-translation",
"Unidiomatic",
"Unintelligible",
"Unit Conversion",
"Untranslated",
"Whitespace",
"Word Order",
"Wrong Auxiliary Verb",
"Wrong Conjunction",
"Wrong Determiner",
"Wrong Language Variety",
"Wrong Preposition",
"Wrong Pronoun"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
}
},
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"token_index": {
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"total_words": {
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}