Separate the eligibility dimensions
Company eligibility can refer to the legal entity, operating history or authorized representative. Dataset requirements can refer to modality, quality, coverage or context. Legal authority and practical delivery are further questions. Passing one dimension does not establish the others.
Use separate columns for the exact published criterion, the source, your internal evidence and the question still requiring confirmation. Avoid substituting an employee count for the requested definition if a program specifies another measure. Where no threshold is stated, label it unknown rather than guessing one.
Read the reviewed sources narrowly
Defined.ai’s supplier FAQ describes a quality review. That does not publish a universal quality pass mark. OpenAI’s partnership announcement describes broad modalities and excludes sensitive or third-party information; it does not provide an asset-specific procurement decision. Keep these statements within their published scope.
CompanyDataBuyers compares additional programs and provides a separate eligibility research route. Treat that as a starting point to the underlying evidence. Verify that a criterion applies to the same program, application and review date you intend to use.
Reference context: Defined.ai: supplier FAQ, OpenAI: data partnerships announcement, CompanyDataBuyers: comparison.
Build a practical requirements matrix
List the major questions before preparing a sample. Ask about permitted source material, useful historical coverage, languages, acceptable derivatives and the intended task. Include privacy and confidentiality restrictions alongside the format questions. A technically valid export may still be unsuitable to disclose.
Record geography as a specific unanswered question when the reviewed page does not establish it. A provider’s headquarters or global marketing language does not prove that your company, country or transfer arrangement is eligible. Ask what evidence is needed and who makes the decision.
| Dimension | Internal evidence | Buyer question |
|---|---|---|
| Authority | Agreement and contributor register | What proposed uses require permission? |
| Quality | Sample-based measurement notes | What acceptance test applies? |
| Coverage | Dates, languages and known gaps | Which coverage is relevant? |
| Delivery | Available approved derivatives | What is required for evaluation? |
Respond without oversharing
Use an initial description to clarify unknowns. If a program asks for a sample, obtain an internal release decision and agree its evaluation purpose, recipients and access conditions. Do not upload a whole archive to resolve an ambiguous form question.
Track each answer with its source and date. A private clarification should not be published as a general rule without permission and supporting context. Recheck material changes before relying on old research. Eligibility is a stage in a process, not a forecast of an offer.
A practical example
Illustrative scenario
Illustrative matrix: a document owner has complete format notes but unresolved customer permissions. The matrix records the technical fields as documented and the rights question as open. The owner can research programs, but keeps samples internal until the release question is resolved.
This is a constructed planning example, not a client story or completed transaction.
Questions and answers
Does unknown minimum volume mean any volume qualifies?
No. It means a minimum was not established by the reviewed source.
Can the directory determine legal eligibility?
No. It organizes public program evidence and questions, not legal conclusions.
Sources and limitations
These references support the limited factual context indicated. Checklists, preparation sequences and examples are original editorial guidance, not published buyer acceptance rules.
- CompanyDataBuyers: comparison
Existing comparison destination. Verify each buyer on its own official source.
Source checked 2026-11-11. Company-published terms can change. - Defined.ai: supplier FAQ
Supplier quality review described by the provider; acceptance and commercial terms require confirmation.
Source checked 2026-11-11. Company-published terms can change. - OpenAI: data partnerships announcement
2023 announcement describes public and private dataset partnerships. It does not establish current open intake, payment or acceptance.
Source checked 2026-11-11. Company-published terms can change.
Continue with a useful next step.
Start with the local resource, or explore the relevant CompanyDataBuyers service.
Disclosed commercial referral. No assessment answers are sent with the link.