{"uid":"cap_YY4gr3HRAX-GxrhWr4CXq","slug":"language-routing-training-evaluation-text-overlap-dace4201","name":"Language Routing – Training/Evaluation Text Overlap","description":"Language routing - Training evaluation text overlap: Training evaluation text overlap for Language routing. Up to 200 supplied labelled text records. Local dataset tools, evaluation and small naive-Bayes baselines; no hosted model or foundation-model training. One of 25 profiles or calculations across 20 shared operations in this sector. 0.01 USDC includes one bounded training evaluation text overlap deliverable.","url":"https://market.datapackvibe.com/x402/assistant-sector-ml-language-routing-leakage?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"records":{"type":"array","items":{"type":"object","required":["id","text","actual"],"properties":{"id":{"type":"string","default":"","maxLength":80,"minLength":1},"text":{"type":"string","default":"","maxLength":1000},"actual":{"enum":["english","french","spanish","other"],"type":"string"}},"additionalProperties":false},"default":[{"id":"example-0-0","text":"english sample document number 0 for this supplied dataset.","actual":"english"},{"id":"example-0-1","text":"english sample document number 1 for this supplied dataset.","actual":"english"},{"id":"example-0-2","text":"english sample document number 2 for this supplied dataset.","actual":"english"},{"id":"example-1-0","text":"french sample document number 0 for this supplied dataset.","actual":"french"},{"id":"example-1-1","text":"french sample document number 1 for this supplied dataset.","actual":"french"},{"id":"example-1-2","text":"french sample document number 2 for this supplied dataset.","actual":"french"},{"id":"example-2-0","text":"spanish sample document number 0 for this supplied dataset.","actual":"spanish"},{"id":"example-2-1","text":"spanish sample document number 1 for this supplied dataset.","actual":"spanish"},{"id":"example-2-2","text":"spanish sample document number 2 for this supplied dataset.","actual":"spanish"},{"id":"example-3-0","text":"other sample document number 0 for this supplied dataset.","actual":"other"},{"id":"example-3-1","text":"other sample document number 1 for this supplied dataset.","actual":"other"},{"id":"example-3-2","text":"other sample document number 2 for this supplied dataset.","actual":"other"}],"maxItems":200,"minItems":2},"evaluation_texts":{"type":"array","items":{"type":"string","default":"","maxLength":1000},"default":["english sample document number 0 for this supplied dataset.","A separate supplied document."],"maxItems":200,"minItems":1}}},"responseSchema":null,"example":null,"exampleRequest":null,"tags":["x402"],"displayCostAmount":"0.01","displayCostAsset":"USDC","priceDynamic":false,"priceHint":null,"priceStatus":"priced","priceSource":"probe","requiresHandshake":false,"reviewCount":0,"rating":{"score":"0.00","successRate":"0.00","reviews":0,"stars":null,"state":"unrated"},"availabilityStatus":"unknown","priceObserved":null,"sessionDeposit":null,"pricing":{"kind":"static","summary":"$0.01/call","primary":{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.01","per":"call","confidence":"exact"},"accepted":[{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.01","per":"call","confidence":"exact"}]},"paymentMethods":[{"uid":"pm_Nsn8Nbrz-HvGTUFTaSCBq","protocol":"x402","methodType":"crypto","chain":"base","mode":"charge","costAmount":"0.01","costPer":"request","priority":0,"asset":"0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913","unit":"request","depositMicros":null,"planRef":null}],"brandName":null,"brandSlug":null,"brandBaseUrl":null,"brandDocsUrl":null,"whatItDoes":"Checks whether evaluation texts appear verbatim or near-verbatim in a labelled training set, detecting data leakage for a language-routing (English/French/Spanish/other) classifier.","exampleAgentPrompt":"Can you check whether any of my evaluation texts overlap with my labelled training records? I have up to 200 training examples tagged as english, french, spanish, or other, and I want to know if any evaluation documents leaked into the training set.","exampleUseCases":[{"title":"Pre-training dataset integrity check","prompt":"Before I train my language router, check these 150 labelled training records (english, french, spanish, other) against my 50 evaluation texts and tell me if any eval examples appear in the training data — I need to know if my benchmark is contaminated."},{"title":"Audit crowdsourced annotation batch","prompt":"I just received a batch of crowd-annotated language samples. Can you compare the evaluation texts I plan to use against this set of up to 200 labelled records to flag any exact or near-exact overlaps before I lock in the eval split?"},{"title":"Validate held-out test set cleanliness","prompt":"I'm finalising a held-out test set for my English/French/Spanish/other classifier — please run an overlap check against my 180 labelled training records to confirm none of my test sentences snuck into training."}],"resultDescription":"A report identifying which evaluation texts (if any) overlap with records in the supplied labelled training set, including match details and an overall leakage/overlap assessment, helping determine whether the evaluation set is contaminated by training data.","failureModes":["Fewer than 2 training records supplied — rejected with validation error","More than 200 records or evaluation texts supplied — rejected with limit error","Missing required fields (id, text, actual) on any record — schema validation failure","Invalid language label outside allowed enum — rejected","Empty evaluation_texts array — rejected","Timeout if texts are unusually long or numerous near the 200-item limit"],"whenToPreferThis":"Use this endpoint when you need to audit a labelled language-classification dataset for train/eval data leakage before model training or benchmarking. Prefer it over generic deduplication tools when your records carry language class labels (english, french, spanish, other) and you need a domain-specific overlap report tied to that classification context. It is especially useful for small dataset validation workflows where a naive-Bayes or local baseline is sufficient and no hosted model is needed.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-15T18:47:40.225Z","isFirstParty":false,"canonicalSlug":"language-routing-training-evaluation-text-overlap-dace4201"}