{"id":2249,"date":"2026-11-05T11:28:25","date_gmt":"2026-11-05T11:28:25","guid":{"rendered":"https:\/\/www.oursglobal.com\/blog\/?p=2249"},"modified":"2026-11-05T11:28:25","modified_gmt":"2026-11-05T11:28:25","slug":"data-annotation-services-is-99-accuracy-enough","status":"publish","type":"post","link":"https:\/\/www.oursglobal.com\/blog\/data-annotation-services-is-99-accuracy-enough\/","title":{"rendered":"Data Annotation Services: Is 99% Accuracy Enough?"},"content":{"rendered":"<div id=\"ez-toc-container\" class=\"ez-toc-v2_0_88 counter-hierarchy ez-toc-counter ez-toc-grey ez-toc-container-direction\">\n<div class=\"ez-toc-title-container\">\n<label class=\"ez-toc-title\" style=\"cursor:inherit\">In this article<\/label>\n<span class=\"ez-toc-title-toggle\"><a href=\"#\" class=\"ez-toc-pull-right ez-toc-btn ez-toc-btn-xs ez-toc-btn-default ez-toc-toggle\" aria-label=\"Toggle Table of Content\"><span class=\"ez-toc-js-icon-con\"><span class=\"\"><span class=\"eztoc-hide\" style=\"display:none;\">Toggle<\/span><span class=\"ez-toc-icon-toggle-span\"><svg style=\"fill: #0a0a0a;color:#0a0a0a\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" class=\"list-377408\" width=\"20px\" height=\"20px\" viewBox=\"0 0 24 24\" fill=\"none\"><path d=\"M6 6H4v2h2V6zm14 0H8v2h12V6zM4 11h2v2H4v-2zm16 0H8v2h12v-2zM4 16h2v2H4v-2zm16 0H8v2h12v-2z\" fill=\"currentColor\"><\/path><\/svg><svg style=\"fill: #0a0a0a;color:#0a0a0a\" class=\"arrow-unsorted-368013\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"10px\" height=\"10px\" viewBox=\"0 0 24 24\" version=\"1.2\" baseProfile=\"tiny\"><path d=\"M18.2 9.3l-6.2-6.3-6.2 6.3c-.2.2-.3.4-.3.7s.1.5.3.7c.2.2.4.3.7.3h11c.3 0 .5-.1.7-.3.2-.2.3-.5.3-.7s-.1-.5-.3-.7zM5.8 14.7l6.2 6.3 6.2-6.3c.2-.2.3-.5.3-.7s-.1-.5-.3-.7c-.2-.2-.4-.3-.7-.3h-11c-.3 0-.5.1-.7.3-.2.2-.3.5-.3.7s.1.5.3.7z\"\/><\/svg><\/span><\/span><\/span><\/a><\/span><\/div>\n<nav><ul class='ez-toc-list ez-toc-list-level-1 ' ><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-1\" href=\"https:\/\/www.oursglobal.com\/blog\/data-annotation-services-is-99-accuracy-enough\/#1_Ask_What_%E2%80%9C99_Accuracy%E2%80%9D_Actually_Measures\" >1. Ask What \u201c99% Accuracy\u201d Actually Measures<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-2\" href=\"https:\/\/www.oursglobal.com\/blog\/data-annotation-services-is-99-accuracy-enough\/#2_Define_the_Task_Before_Negotiating_the_Volume\" >2. Define the Task Before Negotiating the Volume<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-3\" href=\"https:\/\/www.oursglobal.com\/blog\/data-annotation-services-is-99-accuracy-enough\/#3_Treat_Annotation_Guidelines_as_Part_of_the_Deliverable\" >3. Treat Annotation Guidelines as Part of the Deliverable<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-4\" href=\"https:\/\/www.oursglobal.com\/blog\/data-annotation-services-is-99-accuracy-enough\/#4_Agreement_Between_Annotators_Is_Useful%E2%80%94but_It_Is_Not_Proof_of_Truth\" >4. Agreement Between Annotators Is Useful\u2014but It Is Not Proof of Truth<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-5\" href=\"https:\/\/www.oursglobal.com\/blog\/data-annotation-services-is-99-accuracy-enough\/#5_Make_the_Pilot_Representative_of_the_Difficult_Work\" >5. Make the Pilot Representative of the Difficult Work<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-6\" href=\"https:\/\/www.oursglobal.com\/blog\/data-annotation-services-is-99-accuracy-enough\/#6_Review_Rare_Cases_Separately_From_Overall_Quality\" >6. Review Rare Cases Separately From Overall Quality<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-7\" href=\"https:\/\/www.oursglobal.com\/blog\/data-annotation-services-is-99-accuracy-enough\/#7_Define_How_Incorrect_Labels_Will_Be_Corrected\" >7. Define How Incorrect Labels Will Be Corrected<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-8\" href=\"https:\/\/www.oursglobal.com\/blog\/data-annotation-services-is-99-accuracy-enough\/#8_AI-Assisted_Labelling_Still_Needs_a_Review_Plan\" >8. AI-Assisted Labelling Still Needs a Review Plan<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-9\" href=\"https:\/\/www.oursglobal.com\/blog\/data-annotation-services-is-99-accuracy-enough\/#9_Validate_the_Export_Before_Approving_the_Dataset\" >9. Validate the Export Before Approving the Dataset<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-10\" href=\"https:\/\/www.oursglobal.com\/blog\/data-annotation-services-is-99-accuracy-enough\/#10_Compare_Cost_Per_Accepted_Deliverable\" >10. Compare Cost Per Accepted Deliverable<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-11\" href=\"https:\/\/www.oursglobal.com\/blog\/data-annotation-services-is-99-accuracy-enough\/#What_to_Send_a_Data_Annotation_Provider\" >What to Send a Data Annotation Provider<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-12\" href=\"https:\/\/www.oursglobal.com\/blog\/data-annotation-services-is-99-accuracy-enough\/#Frequently_Asked_Questions\" >Frequently Asked Questions<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-13\" href=\"https:\/\/www.oursglobal.com\/blog\/data-annotation-services-is-99-accuracy-enough\/#Is_99_annotation_accuracy_always_good\" >Is 99% annotation accuracy always good?<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-14\" href=\"https:\/\/www.oursglobal.com\/blog\/data-annotation-services-is-99-accuracy-enough\/#What_is_the_difference_between_annotation_quality_and_model_accuracy\" >What is the difference between annotation quality and model accuracy?<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-15\" href=\"https:\/\/www.oursglobal.com\/blog\/data-annotation-services-is-99-accuracy-enough\/#Should_every_item_be_reviewed_by_multiple_people\" >Should every item be reviewed by multiple people?<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-16\" href=\"https:\/\/www.oursglobal.com\/blog\/data-annotation-services-is-99-accuracy-enough\/#Can_we_change_label_definitions_after_the_project_begins\" >Can we change label definitions after the project begins?<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-17\" href=\"https:\/\/www.oursglobal.com\/blog\/data-annotation-services-is-99-accuracy-enough\/#What_is_the_best_way_to_begin_outsourcing_data_annotation\" >What is the best way to begin outsourcing data annotation?<\/a><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-18\" href=\"https:\/\/www.oursglobal.com\/blog\/data-annotation-services-is-99-accuracy-enough\/#Discuss_Your_Data_Annotation_Project_With_OURS_GLOBAL\" >Discuss Your Data Annotation Project With OURS GLOBAL<\/a><\/li><\/ul><\/nav><\/div>\n<p style=\"text-align: justify;\"><span style=\"font-size: 12pt; font-family: verdana, geneva, sans-serif;\"><strong>A dataset can pass an impressive quality score and still contain problems that matter to your AI project.<\/strong><\/span><\/p>\n<p style=\"text-align: justify;\"><span style=\"font-size: 12pt; font-family: verdana, geneva, sans-serif;\">Perhaps the common examples are labelled correctly while rare cases are repeatedly missed. Perhaps reviewers agree with one another because they are following the same unclear instruction. Or perhaps the labels look correct in the annotation tool but arrive in a format your team cannot use.<\/span><\/p>\n<p style=\"text-align: justify;\"><span style=\"font-size: 12pt; font-family: verdana, geneva, sans-serif;\">This is why choosing data annotation services requires more than comparing an accuracy percentage, delivery schedule and price.<\/span><\/p>\n<p style=\"text-align: justify;\">The important question is:<\/p>\n<p style=\"text-align: justify;\"><span style=\"font-size: 12pt; font-family: verdana, geneva, sans-serif;\"><strong>\u201cWhat was measured, against which standard, and what did the review miss?\u201d<\/strong><\/span><\/p>\n<p style=\"text-align: justify;\"><span style=\"font-size: 12pt; font-family: verdana, geneva, sans-serif;\">Before outsourcing your next dataset, use this guide to evaluate whether the proposed quality process matches the work your model needs to learn.<\/span><\/p>\n<h2 style=\"text-align: justify;\"><span class=\"ez-toc-section\" id=\"1_Ask_What_%E2%80%9C99_Accuracy%E2%80%9D_Actually_Measures\"><\/span><span style=\"font-size: 12pt; font-family: verdana, geneva, sans-serif;\">1. Ask What \u201c99% Accuracy\u201d Actually Measures<\/span><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p style=\"text-align: justify;\">An accuracy claim is incomplete without a definition.<\/p>\n<p style=\"text-align: justify;\"><span style=\"font-size: 12pt; font-family: verdana, geneva, sans-serif;\">Does it describe correct image categories? Accepted bounding boxes? Individual attributes? Reviewed records? Agreement between annotators?<\/span><\/p>\n<p style=\"text-align: justify;\">Those are different measurements.<\/p>\n<p style=\"text-align: justify;\">Consider a hypothetical dataset containing 1,000 items:<\/p>\n<ul style=\"text-align: justify;\">\n<li>990 items belong to a common category.<\/li>\n<li>10 items belong to an important rare category.<\/li>\n<li>Every common item is labelled correctly.<\/li>\n<li>Every rare item is labelled incorrectly.<\/li>\n<\/ul>\n<p style=\"text-align: justify;\"><span style=\"font-size: 12pt; font-family: verdana, geneva, sans-serif;\">The overall item-level accuracy is 99%. Accuracy on the rare category is 0%.<\/span><\/p>\n<p style=\"text-align: justify;\"><span style=\"font-size: 12pt; font-family: verdana, geneva, sans-serif;\">This arithmetic example is not a provider\u2019s performance result. It demonstrates why an overall score can conceal a concentrated problem.<\/span><\/p>\n<p style=\"text-align: justify;\"><span style=\"font-size: 12pt; font-family: verdana, geneva, sans-serif;\">Before accepting a quality target, ask the provider to explain:<\/span><\/p>\n<ul style=\"text-align: justify;\">\n<li>The unit being scored.<\/li>\n<li>The reference used to judge correctness.<\/li>\n<li>The sample size and selection method.<\/li>\n<li>Results by category or relevant subgroup.<\/li>\n<li>How missing annotations are counted.<\/li>\n<li>How ambiguous cases are handled.<\/li>\n<\/ul>\n<p style=\"text-align: justify;\"><span style=\"font-size: 12pt; font-family: verdana, geneva, sans-serif;\">A percentage becomes useful when you understand what sits behind it.<\/span><\/p>\n<h2 style=\"text-align: justify;\"><span class=\"ez-toc-section\" id=\"2_Define_the_Task_Before_Negotiating_the_Volume\"><\/span><span style=\"font-size: 12pt; font-family: verdana, geneva, sans-serif;\">2. Define the Task Before Negotiating the Volume<\/span><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p style=\"text-align: justify;\"><span style=\"font-size: 12pt; font-family: verdana, geneva, sans-serif;\">\u201cLabel 50,000 images\u201d describes a quantity. It does not define the job.<\/span><\/p>\n<p style=\"text-align: justify;\"><span style=\"font-size: 12pt; font-family: verdana, geneva, sans-serif;\">The same images might require classification, object detection, segmentation or several attributes per object. Each requires different instructions and review criteria.<\/span><\/p>\n<p style=\"text-align: justify;\">Start with the intended use.<\/p>\n<p style=\"text-align: justify;\"><span style=\"font-size: 12pt; font-family: verdana, geneva, sans-serif;\">What should the model distinguish? Which mistakes matter most? What information must the annotator record?<\/span><\/p>\n<p style=\"text-align: justify;\"><span style=\"font-size: 12pt; font-family: verdana, geneva, sans-serif;\">For example, a product-image project may require category labels, visible packaging attributes or object boundaries. Those tasks should not be treated as interchangeable.<\/span><\/p>\n<p style=\"text-align: justify;\">Write down:<\/p>\n<table>\n<tbody>\n<tr>\n<th><\/th>\n<\/tr>\n<tr>\n<th><\/th>\n<\/tr>\n<tr>\n<th><span style=\"font-size: 12pt; font-family: verdana, geneva, sans-serif;\">Brief component<\/span><\/th>\n<th><span style=\"font-size: 12pt; font-family: verdana, geneva, sans-serif;\">What to specify<\/span><\/th>\n<\/tr>\n<tr>\n<td><span style=\"font-size: 12pt; font-family: verdana, geneva, sans-serif;\">Data type<\/span><\/td>\n<td><span style=\"font-size: 12pt; font-family: verdana, geneva, sans-serif;\">Images, text, audio, video or another format<\/span><\/td>\n<\/tr>\n<tr>\n<td><span style=\"font-size: 12pt; font-family: verdana, geneva, sans-serif;\">Annotation task<\/span><\/td>\n<td><span style=\"font-size: 12pt; font-family: verdana, geneva, sans-serif;\">What the worker must identify or mark<\/span><\/td>\n<\/tr>\n<tr>\n<td><span style=\"font-size: 12pt; font-family: verdana, geneva, sans-serif;\">Label definitions<\/span><\/td>\n<td><span style=\"font-size: 12pt; font-family: verdana, geneva, sans-serif;\">Meaning of each category and attribute<\/span><\/td>\n<\/tr>\n<tr>\n<td><span style=\"font-size: 12pt; font-family: verdana, geneva, sans-serif;\">Inclusion rules<\/span><\/td>\n<td><span style=\"font-size: 12pt; font-family: verdana, geneva, sans-serif;\">What should receive an annotation<\/span><\/td>\n<\/tr>\n<tr>\n<td><span style=\"font-size: 12pt; font-family: verdana, geneva, sans-serif;\">Exclusion rules<\/span><\/td>\n<td><span style=\"font-size: 12pt; font-family: verdana, geneva, sans-serif;\">What should be ignored<\/span><\/td>\n<\/tr>\n<tr>\n<td><span style=\"font-size: 12pt; font-family: verdana, geneva, sans-serif;\">Uncertain cases<\/span><\/td>\n<td><span style=\"font-size: 12pt; font-family: verdana, geneva, sans-serif;\">When to flag, skip or request a decision<\/span><\/td>\n<\/tr>\n<tr>\n<td><span style=\"font-size: 12pt; font-family: verdana, geneva, sans-serif;\">Delivery requirements<\/span><\/td>\n<td><span style=\"font-size: 12pt; font-family: verdana, geneva, sans-serif;\">File structure, identifiers and required fields<\/span><\/td>\n<\/tr>\n<tr>\n<td><\/td>\n<\/tr>\n<tr>\n<td><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p style=\"text-align: justify;\"><span style=\"font-size: 12pt; font-family: verdana, geneva, sans-serif;\">OURS GLOBAL lists image, text, video, audio, 3D\/LiDAR and custom annotation services. Match your enquiry to the actual task rather than requesting a generic rate for \u201cAI data.\u201d<\/span><\/p>\n<h2 style=\"text-align: justify;\"><span class=\"ez-toc-section\" id=\"3_Treat_Annotation_Guidelines_as_Part_of_the_Deliverable\"><\/span><span style=\"font-size: 12pt; font-family: verdana, geneva, sans-serif;\">3. Treat Annotation Guidelines as Part of the Deliverable<\/span><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p style=\"text-align: justify;\"><span style=\"font-size: 12pt; font-family: verdana, geneva, sans-serif;\">Instructions should do more than list category names.<\/span><\/p>\n<p style=\"text-align: justify;\"><span style=\"font-size: 12pt; font-family: verdana, geneva, sans-serif;\">They should explain how to make decisions when examples are incomplete, overlapping or ambiguous.<\/span><\/p>\n<p style=\"text-align: justify;\"><span style=\"font-size: 12pt; font-family: verdana, geneva, sans-serif;\">Suppose an object is partly hidden. Should the annotator mark only the visible area or estimate the full object boundary?<\/span><\/p>\n<p style=\"text-align: justify;\"><span style=\"font-size: 12pt; font-family: verdana, geneva, sans-serif;\">Either approach may be appropriate for a particular task. Mixing them without a rule creates inconsistency.<\/span><\/p>\n<p style=\"text-align: justify;\"><span style=\"font-size: 12pt; font-family: verdana, geneva, sans-serif;\">For text, define how to handle abbreviations, overlapping entities and uncertain sentiment. For audio, clarify how to represent unintelligible speech or overlapping speakers. For video, explain when an object identity should continue across frames.<\/span><\/p>\n<p style=\"text-align: justify;\">Include examples showing:<\/p>\n<ul style=\"text-align: justify;\">\n<li>A clear positive case.<\/li>\n<li>A clear negative case.<\/li>\n<li>A difficult boundary case.<\/li>\n<li>A common mistake.<\/li>\n<li>A situation requiring escalation.<\/li>\n<\/ul>\n<p style=\"text-align: justify;\"><span style=\"font-size: 12pt; font-family: verdana, geneva, sans-serif;\">Then test whether different annotators interpret the instructions consistently.<\/span><\/p>\n<p style=\"text-align: justify;\"><span style=\"font-size: 12pt; font-family: verdana, geneva, sans-serif;\">If repeated questions appear, improve the guideline before increasing production volume.<\/span><\/p>\n<h2 style=\"text-align: justify;\"><span class=\"ez-toc-section\" id=\"4_Agreement_Between_Annotators_Is_Useful%E2%80%94but_It_Is_Not_Proof_of_Truth\"><\/span><span style=\"font-size: 12pt; font-family: verdana, geneva, sans-serif;\">4. Agreement Between Annotators Is Useful\u2014but It Is Not Proof of Truth<\/span><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p style=\"text-align: justify;\">Having several people review the same item can reveal disagreement and support quality control.<\/p>\n<p style=\"text-align: justify;\"><span style=\"font-size: 12pt; font-family: verdana, geneva, sans-serif;\">AWS documentation describes annotation consolidation as a way to combine multiple worker responses, with methods varying by task. This is a concrete example of using multiple annotations rather than relying solely on one worker\u2019s answer.<\/span><\/p>\n<p style=\"text-align: justify;\"><span style=\"font-size: 12pt; font-family: verdana, geneva, sans-serif;\">However, agreement and correctness are different questions.<\/span><\/p>\n<p style=\"text-align: justify;\"><span style=\"font-size: 12pt; font-family: verdana, geneva, sans-serif;\">If everyone follows an incorrect definition, they may agree on the wrong label. If a task is subjective, disagreement may reflect genuine ambiguity rather than careless work.<\/span><\/p>\n<p style=\"text-align: justify;\">Ask how the provider separates:<\/p>\n<ul style=\"text-align: justify;\">\n<li>Annotator consistency.<\/li>\n<li>Agreement with approved reference labels.<\/li>\n<li>Unclear instructions.<\/li>\n<li>Legitimately ambiguous examples.<\/li>\n<\/ul>\n<p style=\"text-align: justify;\"><span style=\"font-size: 12pt; font-family: verdana, geneva, sans-serif;\">Define who makes the final decision when reviewers disagree. For specialised work, that decision may require a qualified subject-matter expert from your organisation or an agreed review team.<\/span><\/p>\n<p style=\"text-align: justify;\">Do not let unresolved decisions disappear into a majority vote without considering the task.<\/p>\n<h2 style=\"text-align: justify;\"><span class=\"ez-toc-section\" id=\"5_Make_the_Pilot_Representative_of_the_Difficult_Work\"><\/span><span style=\"font-size: 12pt; font-family: verdana, geneva, sans-serif;\">5. Make the Pilot Representative of the Difficult Work<\/span><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p style=\"text-align: justify;\">A pilot containing only straightforward examples gives limited evidence about production quality.<\/p>\n<p style=\"text-align: justify;\">Include the conditions your team expects to encounter:<\/p>\n<ul style=\"text-align: justify;\">\n<li>Rare categories.<\/li>\n<li>Low-quality source material.<\/li>\n<li>Partially visible objects.<\/li>\n<li>Similar-looking classes.<\/li>\n<li>Unusual phrasing.<\/li>\n<li>Background noise.<\/li>\n<li>Missing context.<\/li>\n<li>Examples that challenge the current instructions.<\/li>\n<\/ul>\n<p style=\"text-align: justify;\">Keep the pilot manageable enough to inspect carefully.<\/p>\n<p style=\"text-align: justify;\"><span style=\"font-size: 12pt; font-family: verdana, geneva, sans-serif;\">Review both the labels and the questions raised during annotation. A thoughtful clarification request can reveal an issue in the brief before it spreads across thousands of records.<\/span><\/p>\n<p style=\"text-align: justify;\">Agree on what must be resolved before scaling:<\/p>\n<ol style=\"text-align: justify;\" start=\"1\">\n<li>Label definitions are understood.<\/li>\n<li>Difficult cases have a decision process.<\/li>\n<li>Quality checks are measurable.<\/li>\n<li>Output files pass your import checks.<\/li>\n<li>Rework responsibilities are clear.<\/li>\n<\/ol>\n<p style=\"text-align: justify;\">A pilot should test the workflow, not simply produce a polished demonstration.<\/p>\n<h2 style=\"text-align: justify;\"><span class=\"ez-toc-section\" id=\"6_Review_Rare_Cases_Separately_From_Overall_Quality\"><\/span><span style=\"font-size: 12pt; font-family: verdana, geneva, sans-serif;\">6. Review Rare Cases Separately From Overall Quality<\/span><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p style=\"text-align: justify;\"><span style=\"font-size: 12pt; font-family: verdana, geneva, sans-serif;\">Random sampling can provide useful information about a batch, but important low-frequency cases may receive little attention in a small sample.<\/span><\/p>\n<p style=\"text-align: justify;\">Ask for a review plan that reflects the dataset\u2019s risks and composition.<\/p>\n<p style=\"text-align: justify;\"><span style=\"font-size: 12pt; font-family: verdana, geneva, sans-serif;\">For example, consider separately reviewing:<\/span><\/p>\n<ul style=\"text-align: justify;\">\n<li>Classes with few examples.<\/li>\n<li><span style=\"font-size: 12pt; font-family: verdana, geneva, sans-serif;\">Categories frequently confused with one another.<\/span><\/li>\n<li>Items flagged as uncertain.<\/li>\n<li>Work completed under a new guideline version.<\/li>\n<li>Batches where error rates changed.<\/li>\n<li>Data from a new source or capture environment.<\/li>\n<\/ul>\n<p style=\"text-align: justify;\"><span style=\"font-size: 12pt; font-family: verdana, geneva, sans-serif;\">Keep targeted review results distinct from an overall estimate. A deliberately difficult review sample should not be presented as though it represents the whole dataset without explanation.<\/span><\/p>\n<p style=\"text-align: justify;\">The goal is to understand where quality is strong and where further work is needed.<\/p>\n<h2 style=\"text-align: justify;\"><span class=\"ez-toc-section\" id=\"7_Define_How_Incorrect_Labels_Will_Be_Corrected\"><\/span><span style=\"font-size: 12pt; font-family: verdana, geneva, sans-serif;\">7. Define How Incorrect Labels Will Be Corrected<\/span><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p style=\"text-align: justify;\"><span style=\"font-size: 12pt; font-family: verdana, geneva, sans-serif;\">Quality review is incomplete if it identifies problems without specifying what happens next.<\/span><\/p>\n<p style=\"text-align: justify;\">Ask the provider how corrections move through the workflow.<\/p>\n<p style=\"text-align: justify;\"><span style=\"font-size: 12pt; font-family: verdana, geneva, sans-serif;\">Will rejected items return to the original annotator? Will another reviewer adjust them? Who checks the corrected version?<\/span><\/p>\n<p style=\"text-align: justify;\"><span style=\"font-size: 12pt; font-family: verdana, geneva, sans-serif;\">AWS documentation distinguishes label verification from label adjustment: one evaluates existing annotations, while the other supports correcting them. That distinction is useful when specifying an outsourced review process.<\/span><\/p>\n<p style=\"text-align: justify;\">Your agreement should cover:<\/p>\n<ul style=\"text-align: justify;\">\n<li>What qualifies as a rejected item.<\/li>\n<li>How feedback is recorded.<\/li>\n<li>Which corrections are included.<\/li>\n<li>Expected rework timing.<\/li>\n<li>How recurring errors are investigated.<\/li>\n<li><span style=\"font-size: 12pt; font-family: verdana, geneva, sans-serif;\">Whether a guideline change requires relabelling earlier batches.<\/span><\/li>\n<\/ul>\n<p style=\"text-align: justify;\"><span style=\"font-size: 12pt; font-family: verdana, geneva, sans-serif;\">Also distinguish a provider error from a change in your requirements. Both may require work, but they should not be confused.<\/span><\/p>\n<h2 style=\"text-align: justify;\"><span class=\"ez-toc-section\" id=\"8_AI-Assisted_Labelling_Still_Needs_a_Review_Plan\"><\/span><span style=\"font-size: 12pt; font-family: verdana, geneva, sans-serif;\">8. AI-Assisted Labelling Still Needs a Review Plan<\/span><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p style=\"text-align: justify;\"><span style=\"font-size: 12pt; font-family: verdana, geneva, sans-serif;\">If a provider uses model-generated labels as a starting point, ask how people review those suggestions.<\/span><\/p>\n<p style=\"text-align: justify;\">Clarify which items receive human attention and how accepted labels are checked.<\/p>\n<p style=\"text-align: justify;\">Useful questions include:<\/p>\n<ul style=\"text-align: justify;\">\n<li>Are all suggested labels reviewed or only a selection?<\/li>\n<li>Can reviewers reject or replace a suggestion?<\/li>\n<li>Are difficult examples routed differently?<\/li>\n<li>How are repeated model errors detected?<\/li>\n<li>Are manually created and automatically suggested labels distinguishable where needed?<\/li>\n<\/ul>\n<p style=\"text-align: justify;\">Do not assume a human-in-the-loop label means every item received the same depth of review.<\/p>\n<p style=\"text-align: justify;\"><span style=\"font-size: 12pt; font-family: verdana, geneva, sans-serif;\">Equally, do not assume manual work is automatically error-free. Evaluate the process and its evidence rather than choosing by label alone.<\/span><\/p>\n<h2 style=\"text-align: justify;\"><span class=\"ez-toc-section\" id=\"9_Validate_the_Export_Before_Approving_the_Dataset\"><\/span><span style=\"font-size: 12pt; font-family: verdana, geneva, sans-serif;\">9. Validate the Export Before Approving the Dataset<\/span><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p style=\"text-align: justify;\"><span style=\"font-size: 12pt; font-family: verdana, geneva, sans-serif;\">A correctly annotated example is not useful if its identifier points to the wrong source file.<\/span><\/p>\n<p style=\"text-align: justify;\">Test an early export using the workflow that will consume the production data.<\/p>\n<p style=\"text-align: justify;\">Check:<\/p>\n<ul style=\"text-align: justify;\">\n<li>File and record identifiers.<\/li>\n<li>Category names and IDs.<\/li>\n<li>Coordinate conventions where applicable.<\/li>\n<li>Required attributes.<\/li>\n<li>Missing values.<\/li>\n<li>Duplicate records.<\/li>\n<li>Text encoding.<\/li>\n<li>Version information.<\/li>\n<li>Compatibility with your expected schema.<\/li>\n<\/ul>\n<p style=\"text-align: justify;\"><span style=\"font-size: 12pt; font-family: verdana, geneva, sans-serif;\">For geometry-based tasks, inspect imported examples visually as well as checking file structure.<\/span><\/p>\n<p style=\"text-align: justify;\"><span style=\"font-size: 12pt; font-family: verdana, geneva, sans-serif;\">Do this during the pilot. Discovering an incompatible convention after final delivery can create avoidable rework.<\/span><\/p>\n<p style=\"text-align: justify;\">Ask the provider to preserve traceability between the source item, annotation and review status.<\/p>\n<h2 style=\"text-align: justify;\"><span class=\"ez-toc-section\" id=\"10_Compare_Cost_Per_Accepted_Deliverable\"><\/span><span style=\"font-size: 12pt; font-family: verdana, geneva, sans-serif;\">10. Compare Cost Per Accepted Deliverable<\/span><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p style=\"text-align: justify;\">A low rate per item may exclude review, adjudication, corrections or export preparation.<\/p>\n<p style=\"text-align: justify;\">Compare providers using the same task definition and acceptance standard.<\/p>\n<p style=\"text-align: justify;\">A useful cost discussion should address:<\/p>\n<table>\n<tbody>\n<tr>\n<th><\/th>\n<\/tr>\n<tr>\n<th><\/th>\n<\/tr>\n<tr>\n<th><\/th>\n<\/tr>\n<tr>\n<th><\/th>\n<\/tr>\n<tr>\n<th>Cost component<\/th>\n<th>Question to ask<\/th>\n<\/tr>\n<tr>\n<td>Initial labelling<\/td>\n<td>What counts as one billable unit?<\/td>\n<\/tr>\n<tr>\n<td>Complexity<\/td>\n<td>Do objects, attributes or duration affect the rate?<\/td>\n<\/tr>\n<tr>\n<td>Quality review<\/td>\n<td>What review is included?<\/td>\n<\/tr>\n<tr>\n<td>Disagreement resolution<\/td>\n<td>Who handles difficult decisions?<\/td>\n<\/tr>\n<tr>\n<td>Corrections<\/td>\n<td>Which rework is included?<\/td>\n<\/tr>\n<tr>\n<td>Guideline updates<\/td>\n<td>How are scope changes priced?<\/td>\n<\/tr>\n<tr>\n<td>Export<\/td>\n<td>Are validation and custom formatting included?<\/td>\n<\/tr>\n<tr>\n<td><\/td>\n<\/tr>\n<tr>\n<td><\/td>\n<\/tr>\n<tr>\n<td><\/td>\n<\/tr>\n<tr>\n<td><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p style=\"text-align: justify;\"><span style=\"font-size: 12pt; font-family: verdana, geneva, sans-serif;\">Also consider your internal review time. A cheaper batch that requires extensive correction may not be the most useful purchase.<\/span><\/p>\n<p style=\"text-align: justify;\"><span style=\"font-size: 12pt; font-family: verdana, geneva, sans-serif;\">Avoid assuming a higher price guarantees better quality. Use the pilot and documented acceptance criteria to compare the actual work.<\/span><\/p>\n<h2 style=\"text-align: justify;\"><span class=\"ez-toc-section\" id=\"What_to_Send_a_Data_Annotation_Provider\"><\/span><span style=\"font-size: 12pt; font-family: verdana, geneva, sans-serif;\">What to Send a Data Annotation Provider<\/span><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p style=\"text-align: justify;\">Prepare an initial project brief containing:<\/p>\n<ol style=\"text-align: justify;\" start=\"1\">\n<li>The model\u2019s intended task.<\/li>\n<li>Data types and estimated volume.<\/li>\n<li>A representative, appropriately shareable sample.<\/li>\n<li>Draft label definitions.<\/li>\n<li>Known difficult cases.<\/li>\n<li>Required output format.<\/li>\n<li>Quality and acceptance criteria.<\/li>\n<li>Review responsibilities.<\/li>\n<li>Delivery milestones.<\/li>\n<li>Access and data-handling requirements.<\/li>\n<\/ol>\n<p style=\"text-align: justify;\"><span style=\"font-size: 12pt; font-family: verdana, geneva, sans-serif;\">Before transferring sensitive or confidential data, agree on authorised access, approved tools, storage locations, retention and deletion arrangements. Confirm whether subcontractors or external AI tools will be involved.<\/span><\/p>\n<p style=\"text-align: justify;\"><span style=\"font-size: 12pt; font-family: verdana, geneva, sans-serif;\">These decisions belong in the project setup, not as assumptions discovered during production.<\/span><\/p>\n<h2 style=\"text-align: justify;\"><span class=\"ez-toc-section\" id=\"Frequently_Asked_Questions\"><\/span><span style=\"font-size: 12pt; font-family: verdana, geneva, sans-serif;\">Frequently Asked Questions<\/span><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<h3 style=\"text-align: justify;\"><span class=\"ez-toc-section\" id=\"Is_99_annotation_accuracy_always_good\"><\/span><span style=\"font-size: 12pt; font-family: verdana, geneva, sans-serif;\">Is 99% annotation accuracy always good?<\/span><span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p style=\"text-align: justify;\"><span style=\"font-size: 12pt; font-family: verdana, geneva, sans-serif;\">It depends on how the score is calculated and where the remaining errors occur. Review the metric definition, reference standard, sample design and category-level results.<\/span><\/p>\n<h3 style=\"text-align: justify;\"><span class=\"ez-toc-section\" id=\"What_is_the_difference_between_annotation_quality_and_model_accuracy\"><\/span><span style=\"font-size: 12pt; font-family: verdana, geneva, sans-serif;\">What is the difference between annotation quality and model accuracy?<\/span><span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p style=\"text-align: justify;\"><span style=\"font-size: 12pt; font-family: verdana, geneva, sans-serif;\">Annotation quality concerns how well labels meet the agreed standard. Model performance depends on additional factors, including data coverage, training choices and evaluation design. A high annotation score does not guarantee a particular model result.<\/span><\/p>\n<h3 style=\"text-align: justify;\"><span class=\"ez-toc-section\" id=\"Should_every_item_be_reviewed_by_multiple_people\"><\/span>Should every item be reviewed by multiple people?<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p style=\"text-align: justify;\"><span style=\"font-size: 12pt; font-family: verdana, geneva, sans-serif;\">Not necessarily. The appropriate process depends on ambiguity, task complexity, risk and budget. Agree on where multiple reviews or expert decisions add value.<\/span><\/p>\n<h3 style=\"text-align: justify;\"><span class=\"ez-toc-section\" id=\"Can_we_change_label_definitions_after_the_project_begins\"><\/span><span style=\"font-size: 12pt; font-family: verdana, geneva, sans-serif;\">Can we change label definitions after the project begins?<\/span><span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p style=\"text-align: justify;\"><span style=\"font-size: 12pt; font-family: verdana, geneva, sans-serif;\">Yes, but changes should be documented and versioned. Determine which earlier annotations are affected and whether they need correction before combining batches.<\/span><\/p>\n<h3 style=\"text-align: justify;\"><span class=\"ez-toc-section\" id=\"What_is_the_best_way_to_begin_outsourcing_data_annotation\"><\/span><span style=\"font-size: 12pt; font-family: verdana, geneva, sans-serif;\">What is the best way to begin outsourcing data annotation?<\/span><span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p style=\"text-align: justify;\"><span style=\"font-size: 12pt; font-family: verdana, geneva, sans-serif;\">Start with a representative pilot, clear guidelines and an export test. Resolve recurring questions before expanding the workload.<\/span><\/p>\n<h2 style=\"text-align: justify;\"><span class=\"ez-toc-section\" id=\"Discuss_Your_Data_Annotation_Project_With_OURS_GLOBAL\"><\/span><span style=\"font-size: 12pt; font-family: verdana, geneva, sans-serif;\">Discuss Your Data Annotation Project With OURS GLOBAL<\/span><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p style=\"text-align: justify;\">A strong annotation project starts with a definition of quality that both teams can apply.<\/p>\n<p style=\"text-align: justify;\">You need clear labels, representative examples, a process for disagreement and a delivery format your team can use.<\/p>\n<p style=\"text-align: justify;\">Explore <a href=\"https:\/\/www.oursglobal.com\/outsource-data-annotation-labelling-services\">OURS GLOBAL\u2019s data annotation and labelling services<\/a> and share your task, data type, expected volume and quality requirements.<\/p>\n<p style=\"text-align: justify;\"><span style=\"font-size: 12pt; font-family: verdana, geneva, sans-serif;\">Ask the team to propose a pilot covering annotation, review, corrections and export validation before agreeing on larger production volumes.<\/span><\/p>\n<p style=\"text-align: justify;\"><span style=\"font-size: 12pt; font-family: verdana, geneva, sans-serif;\"><strong>Request a project quotation through the service page or email <\/strong><a href=\"mailto:info@oursglobal.com\"><strong>info@oursglobal.com<\/strong><\/a><strong>.<\/strong><\/span><\/p>\n<p style=\"text-align: justify;\"><span style=\"font-size: 12pt; font-family: verdana, geneva, sans-serif;\"><strong>Before accepting \u201c99% accurate,\u201d ask what the remaining 1% contains.<\/strong><\/span><\/p>\n","protected":false},"excerpt":{"rendered":"<p>A dataset can pass an impressive quality score and still contain problems that matter to your AI project. Perhaps the<\/p>\n","protected":false},"author":1,"featured_media":2250,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"colormag_page_container_layout":"default_layout","colormag_page_sidebar_layout":"default_layout","footnotes":""},"categories":[41],"tags":[],"class_list":["post-2249","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-ai-updates"],"aioseo_notices":[],"aioseo_head":"\n\t\t<!-- All in One SEO 5.0.2 - aioseo.com -->\n\t<meta name=\"description\" content=\"Is 99% annotation accuracy enough? 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