Extract comparable claims, observations, methods, and limits from several documents while preserving source lineage. 제공할 내용: Research or decision question, Labeled source materials, Evidence and table rules. 예상 결과: A traceable evidence table with source inventory, claim clusters, conflicts, and synthesis limits.
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맥락 추가
텍스트는 이 브라우저에 유지됩니다. AILesson Prompts는 이를 모델이나 서버로 보내지 않습니다.
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프롬프트
채워지지 않은 필드는 플레이스홀더로 표시되므로 프롬프트를 복사하고 편집할 수 있습니다
Organize the supplied documents into a traceable evidence table for the exact question.
Question, definitions, population, period, alternatives, decision, and claim threshold:
[question]
Sources with IDs, metadata, methods, locators, and relevant text:
[sources]
Eligibility, extraction unit, quality, independence, applicability, quotation, privacy, unknowns, and schema:
[rules]
Inventory sources before extraction and identify duplicate versions, citations that reuse the same underlying dataset, missing pages, and inaccessible attachments. Use one row per smallest evidence unit that can support a distinct claim; a source may create several rows, while a repeated claim without new data is not new evidence. Separate reported observation, author interpretation, recommendation, and analyst inference. Preserve population, sample, denominator, measure, comparison, period, effect/value, uncertainty, method, limitations, and exact locator. Classify relevance and direction only against the stated question. Do not harmonize incompatible metrics, count dependent sources as independent, repair missing values, or treat absence of mention as evidence of absence. Return: source inventory; evidence table; claim-to-source matrix; dependency map; conflict table; evidence gaps; synthesis weighted by directness, quality, independence, and applicability; and rows needing human verification.
기본적으로 비공개프롬프트 구성은 브라우저에서 로컬로 이루어집니다. 조직에서 허용하지 않는 한 기밀 정보를 AI 서비스에 입력하지 마세요.
입력에서 결과까지
적용 예시
구체적인 맥락이 이 레시피를 바로 사용할 수 있는 결과로 바꾸는 방법을 확인하세요
실제 입력
Research or decision question
Should a 12-week pilot of optional four-day workweeks be approved for the 46-person product department? Decision concerns delivery reliability and employee strain, not permanent adoption. Compare evidence from January–June 2026; 'delivery reliability' means committed milestone met by date; strain means reported workload or overtime. No success threshold has been approved.
Labeled source materials
S1 Delivery report v2, Ops, 8 Jul 2026, pp.3–5: product teams met 38/45 milestones Jan–Mar and 31/39 Apr–Jun. April introduced a planning-system migration; seven delayed milestones were tagged migration-related. No workweek change occurred. S2 Staff pulse, People, 30 Jun, sec.2: 37/46 responded; 21 report frequent overtime, 10 occasional, 6 none; question does not define hours. 28/37 favor trying an optional four-day week. S3 Union memo, 2 Jul, p.1: cites S2's 28/37 and recommends a trial with no pay reduction; no new survey. S4 Vendor case study, rev May, pp.2,7: another 120-person software company reports on-time projects 74%→81% during a six-month four-day pilot; project definition changed in month three and no comparison group. S5 Finance note, 10 Jul, p.2: pilot analysis estimates USD 18,000 temporary coverage, based on two contractors for 12 weeks; rates listed, procurement not confirmed.
Evidence and table rules
Eligible: internal operational records, surveys with denominator, comparable external cases, and cost evidence. One row per measure/claim. Quality fields directness, method, independence, applicability, limitations. Short excerpts max 15 words. Unknown='Not reported'. S3 depends on S2. Do not compare milestone and project rates as identical. No personal data.
예시 출력
Source inventory: five current labeled sources; S3 is analytically dependent on S2, not corroboration. No missing pages are stated. S4 is external and its metric definition changed.
Evidence rows: E1/S1 p.3–5—delivery observation, Jan–Mar 38/45=84.4% milestones met; direct internal baseline, no pilot exposure. E2/S1—Apr–Jun 31/39=79.5%; seven delays tagged migration-related, but the tag does not prove all difference was caused by migration. E3/S2 sec.2—21/37 frequent, 10/37 occasional, 6/37 no overtime; direct self-report among respondents, undefined hours and 9 nonrespondents. E4/S2—28/37 respondents favor an optional trial; preference, not expected delivery effect. E5/S3 p.1—trial recommendation using E4; no independent observation. E6/S4 p.2,7—reported projects 74%→81%; indirect, changed definition, no comparison group, not numerically comparable with S1 milestones. E7/S5 p.2—estimated USD 18,000 coverage based on stated rates/two contractors/12 weeks; planning estimate, procurement unconfirmed.
Conflict/gaps: no source observes this department under a four-day schedule; no approved thresholds, overtime hours, workload baseline, eligibility/take-up estimate, customer impact, or pilot measurement plan. Weighted synthesis: internal evidence establishes current delivery and respondent strain but cannot predict treatment effect. External evidence suggests feasibility only weakly. Cost is estimable but not approved. The table supports designing a controlled, reversible pilot with preregistered milestone, overtime, workload, coverage, and stop criteria; it does not by itself support declaring the policy beneficial. Human verification: check S1 migration tagging and S5 rate arithmetic.
효과가 있는 이유
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Evidence-unit rows keep a document's data separate from its interpretation and recommendation.
2
A dependency map prevents several retellings of one dataset from appearing to be corroboration.
결과 확인
Can every row be traced to a stable source, version, page/section, and exact evidence unit?
Are observations, author conclusions, recommendations, and analyst inferences distinct?
Are shared data, incompatible measures, conflicts, missing material, and applicability limits visible?
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What should I prepare before using “Organize multiple sources into an evidence table”?
For “Organize multiple sources into an evidence table,” prepare Research or decision question, Labeled source materials, and Evidence and table rules. Replace placeholders only with information you can verify. If a detail is unknown, preserve that uncertainty explicitly instead of asking the model to infer it.
When is the “Organize multiple sources into an evidence table” result not ready to use?
The result is not ready if it does not yet deliver the stated outcome—A traceable evidence table with source inventory, claim clusters, conflicts, and synthesis limits—from the supplied evidence, or if it relies on unresolved assumptions, missing approvals, or invented details. Use the checks as release gates: revise the source inputs or assign a named, authorized reviewer instead of polishing an unsupported output.
Which AI tools have recorded tests for “Organize multiple sources into an evidence table”?
The published test record for “Organize multiple sources into an evidence table” lists ChatGPT as of 2026-08-28. This confirms recorded runs, not guaranteed compatibility or identical results in later product versions. For another tool or version, keep every constraint visible and repeat the result checks before use.
ChatGPT
