Translation that scales · Lesson 4
The human in the loop.
A human checks it is not a workflow. This lesson gives review its structure: the machine translates first, a reviewer walks the segments with clear statuses, automated QA catches the mechanical errors, and the depth of editing is declared before anyone starts.
Lesson one ended with a rule: machine first pass, human judgment on top. This lesson is about what that judgment looks like in practice, because "a human checks it" is not a workflow. Who checks what, in what order, with what tools, and how does anyone know when a 348-segment document is actually done? The industry's answer is called post-editing, and it has more structure than most people expect.
The shape of the work
The machine translates the whole document first. Then the document is presented as segments: source on one side, machine translation on the other, one sentence or heading or table cell per row. The reviewer walks the segments in order, and for each one makes a small decision: the translation is right (accept it), nearly right (edit it), or wrong enough to redo. This sounds tedious and is actually the efficient part: the machine has done the typing, terminology has been pre-applied from the glossary, and memory matches arrive already locked. The human is doing pure judgment, at reading speed, not writing speed.
Statuses make the process visible. In TranslateX the segment states are machine, edited, accepted, rejected, and locked, and the pattern generalizes to any serious tool:
- Machine. Untouched first-pass output. The starting state of every segment no memory match covered.
- Edited. A human changed it. The tool keeps a track-changes diff against the original MT, which is how you later see what kinds of errors the machine actually makes.
- Accepted. A human read it and signed off. This is the state that feeds the translation memory.
- Locked. Settled language, usually an exact memory match or a legally fixed clause, protected from accidental change.
Progress is not a feeling, it is a count: 212 of 348 segments reviewed, one QA warning open. A document is done when every segment carries a human-approved status and the QA list is empty.
QA checks: machines catching machine errors
Some errors need a human ear. Others are mechanical, and mechanical errors deserve mechanical detection. Automated QA runs across all segments and flags the failure modes machines are bad at noticing in themselves: numbers that differ between source and target (the most dangerous error in institutional work, because a wrong number reads perfectly), untranslated segments that slipped through, doubled spaces, missing or mismatched punctuation, and suspicious length ratios, where a target segment far shorter than its source usually means something was dropped.
The point is division of labor. QA checks will never tell you a sentence sounds bureaucratic; a human will rarely spot that ٨٫٢ became 8.4 on page 61 at four in the afternoon. Run both, and each covers the other's blind spot. The one discipline QA demands: warnings get resolved, not dismissed by habit. A QA report that everyone ignores is a smoke alarm with the battery out.
Light or full: declare the depth before you start
Not every document deserves the same effort, and pretending otherwise just means the effort gets allocated by accident. The industry distinguishes two levels of post-editing. Light post-editing fixes errors of meaning and nothing else: wrong numbers, dropped negations, mistranslations. Awkward-but-accurate phrasing is left alone. The output is correct, not beautiful, and for internal working documents that is exactly right. Full post-editing brings the text to publication standard: meaning, terminology, style, and tone, indistinguishable from human translation. It costs several times the effort, which is why you reserve it for documents that earn it.
The triage at Al Dana Holdings
A competitor's Arabic press release, translated for the strategy team to skim: raw MT, no review, labeled as machine output. The quarterly supplier performance memo: light post-editing by one reviewer, an hour of work. The Annual Report 2025 and anything Khalid Mansour's legal team signs: full post-editing, every segment human-approved, QA list at zero, no exceptions. Three depths, chosen on purpose.
When is skipping review entirely legitimate? When the reader knows it is machine output, the stakes of an error are near zero, and the alternative is not translating at all: gisting foreign news, skimming an inbound document to decide if it matters, internal lookups. When is it never legitimate? Anything legally binding, anything published under your name, anything where a wrong number or a dropped "not" has consequences. The test from lesson one still governs: who reads the output, and what happens if a sentence is wrong?
Closing the loop
Review is also where the whole system from lesson three gets fed. Every accepted segment enters the translation memory; every term a reviewer fixes twice is a glossary proposal waiting to be made. A team that reviews without capturing is doing the same work annually. A team that captures finds its second year materially easier than its first, because the machine now starts from the organization's own approved language.
And when the last segment is approved, the document leaves the segment grid: the tool merges the edits back into the original layout, so what ships is not a spreadsheet of sentences but the finished, formatted document from lesson two. In TranslateX this whole loop is the review editor: side-by-side segments, statuses, per-segment glossary and memory lookups, bulk accept for the clean stretches, reviewer notes, automated QA including Arabic-specific checks, and a regenerated final document at the end. One craft remains for this course: the typography and direction of Arabic itself, which is lesson five.
The segment walk
Judgment at reading speed.
Four segments from the annual report: a locked memory match, an accepted segment, one being edited, and a machine segment wearing the QA flag that justifies the whole system, a wrong number inside a perfectly fluent sentence.
- Machine, edited, accepted, rejected, locked: the status vocabulary
- Accepted segments feed the translation memory
- QA warnings are resolved, never waved through
يخضع هذا الاتفاق لقوانين إمارة دبي.
This Agreement shall be governed by the laws of the Emirate of Dubai.
حقق صافي الربح نمواً بنسبة ١٤٪ مقارنة بالعام السابق.
Net profit grew 14% compared with the previous year.
وافق مجلس الإدارة على توزيعات أرباح نقدية.
The Board of Directors approved a cash dividend.
بلغ إجمالي الأصول ٨٫٢ مليار درهم.
Total assets reached AED 8.4 billion.
Layla walks the segments: TM lock, accept, edit, and one QA flag doing exactly what QA is for, catching a wrong number in fluent prose.
Depth of review
Three depths, chosen on purpose.
Gist, light, and full post-editing are all legitimate. What is not legitimate is deciding by accident. Declare the depth when the job starts, match it to the consequences of an error, and never publish or sign raw machine output.
Decide the depth per document, before review starts, and tell the reviewer. Undeclared expectations produce full effort on gist jobs and gist effort on contracts.
Frequently asked questions
What is post-editing?
The workflow where a machine translates the whole document first and a human reviewer then walks the output segment by segment, accepting, editing, or rejecting each one. The machine does the typing and the human does the judgment, which is faster than human translation and safer than raw machine output.
What do automated QA checks catch?
The mechanical failure modes: numbers that differ between source and target, untranslated segments, doubled spaces, missing or mismatched punctuation, and length ratios that suggest dropped content. They exist because these errors hide inside fluent prose where human eyes skip past them.
What is the difference between light and full post-editing?
Light post-editing fixes only errors of meaning: wrong numbers, dropped negations, mistranslations, leaving awkward but accurate phrasing alone. Full post-editing also fixes terminology, style, and tone to publication standard. Light suits internal working documents; full is for anything that ships under your name.
When is it acceptable to skip human review entirely?
When the reader knows the text is machine output, an error costs nearly nothing, and the alternative is no translation at all: gisting foreign news, triaging inbound documents, internal lookups. It is never acceptable for legal instruments, published material, or any document where a wrong number or dropped negation has consequences.
Translate the document. Keep the design.
Right-click a file, work inside Office, or press F6 on anything on screen. TranslateX returns the same document in the other language: fonts, tables, and layout intact, terminology on brand.
Arabic, English & more · Layout preserved · On-premises available