When Machine Translation Goes Wrong...

Hallucinations and made-up content

What goes wrong:

• The model invents facts, terms, or completions that were not in the source.
• It “fills gaps” with plausible-sounding but false fragments.

Why it matters:

This is the most dangerous failure mode. A single invented clause in a contract, a regulatory note, or a technical instruction can change obligations or safety conditions.

How Verosetta fixes it:

• Purpose-built prompts for translation: We instruct LLMs to translate, not to elaborate, and to preserve structure and content rigorously.
• Optimal segmentation (chunking): We split texts into fragments sized and shaped to carry enough context for accuracy, while avoiding the drift that long, unconstrained spans can introduce.
• Multi-level quality checks:
  • Text-based alignment: We compare source and target to detect additions, omissions, and changes to numbers, entities, or critical phrases.
  • Cross-model verification: We use separate language models to re-check meaning from another angle and highlight inconsistencies.
  • Human-in-the-loop by design: Our workflow flags suspected hallucinations and routes them to a verifier with clear, focused context. Verification is comfortable, fast, and effective.

Negation, modality, idioms, and inter-sentence context

What goes wrong:

• Misreading modality and conditions: shall vs. may; unless; only; not only… but also.
• In Polish, mishandling double negation can invert meaning.
• Literal translations of idioms; wrong senses for polysemous words, phrasal verbs, and collocations.
• False friends (for example: English “eventually” vs. Polish “ewentualnie”).
• Lost references between sentences: it/they/this; drift in gender and number agreement in Polish; discourse coherence falls apart.

Why it matters:

These are subtle but common. A flipped modal (shall/may) or a misplaced unless can create legal or compliance exposure. Idioms and collocations affect credibility and clarity.

How Verosetta fixes it:

• Context-aware translation: We provide LLMs with the right surrounding context — not just a sentence in isolation — to keep references and conditions intact.
• Multi-layer quality review for nuance: We run targeted checks for negation, modality, idiomatic expressions, and likely polysemy hotspots. When a choice is genuinely ambiguous, we surface it to the verifier with alternatives.
• Cross-sentence coherence checks: We examine pronoun chains and agreement patterns across sentence boundaries. In Polish, we specifically review gender and number consistency.

Terminology and consistency within and across documents

What goes wrong:

• Wrong term choices or mixing several variants.
• Inconsistent terminology across the same document or across documents in the same domain.

Why it matters:

In specialized content (legal, medical, technical), inconsistent terms reduce precision and can mislead readers.

How Verosetta fixes it:

• Termbases from your actual work: We build dictionaries from historical translations to reflect your organization’s preferred equivalents.
• Consistency enforcement: We apply the chosen term consistently throughout a document and across related documents, while still allowing a verifier to approve or override when needed.

Word order and information focus (especially for Polish)

What goes wrong:

• English calques distort Polish theme–rheme (what the sentence is about vs. what is being said about it), creating odd emphasis.
• Struggles with particles like “już/jeszcze” and “to”, which steer nuance and flow.
• Result: text that may be technically correct but reads as foreign or stiff.

Why it matters:

Readers notice fluency. Natural information structure improves comprehension and trust, especially in public-facing materials and editorial content.

How Verosetta fixes it:

• Training on Polish editorial corpora: Our models internalize natural Polish sentence flow beyond literal mappings.
• Penalization of syntactic calques: We actively discourage unnatural English-like structures.
• Fluency pass with a strong Polish LM/LLM: We polish style while safeguarding key content. Terms and numbers are protected (“locked”) so that readability never alters facts.
• Post-edit checklists: Editors get a practical checklist to catch the last traces of calque and awkward emphasis.

Localization details: units, formats, names, and punctuation (Polish specifics)

What goes wrong:

• Decimal comma vs. point; date formats; currencies and units.
• Exonyms and inflection of proper names (e.g., w Google’u).
• Polish typographic quotes („…”) and spacing; commas before że/który; consistent handling of placeholders and tags.
• “Do not translate” items (product names, codes, tags) accidentally changed.

Why it matters:

These details communicate professionalism, prevent number misreading, and avoid functional breakage in templates or code.

How Verosetta fixes it:

• Post-processing and normalization:
  • Numbers, dates, and currencies are converted and formatted according to Polish conventions (decimal comma, thousand spaces) or English, depending on direction.
  • Formats are guarded so models do not corrupt tags or placeholders.
• Built-in Polish punctuation and style rules: Proper quotes, commas before że/który where needed, and other typographic norms are enforced.
• Do-not-translate lists: Product names, codes, and other protected strings are preserved reliably.

What this adds up to

• High-quality first pass from LLMs, because we set them up with the right constraints and context.
• Several lines of defense that catch additions, omissions, negation and modality slip-ups, idioms gone literal, and context breakage.
• Terminology that stays consistent within and across your materials, learned from your own translation history.
• Polish that reads like Polish, not English in disguise.
• A verifier workflow designed for speed and certainty — because human judgment is the final guarantee of quality.