Test legat de ghid · Mediu Nivel

Test de traducere automată

Verificați alinierea datelor de traducere, tokenizarea, limitele BLEU, evaluarea perechilor de limbi și erorile semantice, cum ar fi numerele modificate sau negația.

Căi de ghidare aferenteTraducere automată
Întrebare 1 de 8

What does parallel training data contain?

Previzualizează fiecare întrebare8 întrebări

Răspunsurile și explicațiile apar pe măsură ce susțineți testul.

  1. What does parallel training data contain?
    • Source passages paired with corresponding translations
    • Unrelated documents grouped by font
    • Only target-language references
    • A list of model predictions without sources
  2. What can mismatched source-target alignment teach a translation model?
    • A guaranteed improvement in fluency
    • The wrong relationship between passages
    • A correct translation for every language
    • A better BLEU reference
  3. Why keep related documents together when splitting evaluation data?
    • To remove the need for references
    • To make tokenization identical
    • To reduce near-duplicate leakage across splits
    • To increase sentence length
  4. A tokenizer splits one writing system into many more units. What should evaluators check?
    • Whether source and target use the same alphabet
    • Only the model’s name
    • Whether BLEU is always high
    • Length limits and whether either passage is truncated
  5. What does BLEU compare?
    • Whether a translation is legally valid
    • Patterns of word sequences with reference translations
    • The full meaning and readability of a passage
    • The number of languages in a model
  6. A candidate translation changes “did not arrive” to “did arrive.” What error should reviewers flag?
    • An insertion that cannot matter
    • A casing normalization choice
    • Incorrect negation that reverses meaning
    • A target-language tokenization win
  7. A model has a strong average score across several well-resourced languages. What could that conceal?
    • Poor performance in a less-represented language or specialized domain
    • That all language pairs are equally reliable
    • That there are no terminology errors
    • That the test set has no duplicates
  8. What should accompany an automatic metric in translation evaluation?
    • A single score without settings
    • Only a larger reference corpus
    • An assumption that meaning is preserved
    • A documented setup and bilingual review of specific errors