Triple
T27130714
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wharton econometric forecasting model |
E681555
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | macroeconometric model |
C39392
|
CONCEPT FINISHED |
How this triple was built (1 step)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
CD
Concept disambiguation
gpt-5-mini-2025-08-07
Target class: macroeconometric model Context triple: [Wharton econometric forecasting model, instanceOf, macroeconometric model]
-
A.
econometric model
chosen
An econometric model is a quantitative representation of economic relationships that uses statistical methods and real-world data to estimate, test, and forecast economic behavior.
-
B.
macroeconomic theory
Macroeconomic theory is the branch of economics that studies the behavior, performance, and structure of an economy as a whole, focusing on aggregate measures like output, inflation, unemployment, and economic growth, and the policies that influence them.
-
C.
economic forecasting model
An economic forecasting model is a structured analytical framework that uses historical data, statistical methods, and assumptions about future conditions to predict key economic variables such as growth, inflation, and employment.
-
D.
macroeconomic aggregate
A macroeconomic aggregate is a broad measure that summarizes the overall level or performance of key economic variables—such as output, income, prices, or employment—across an entire economy.
-
E.
system of macroeconomic statistics
A system of macroeconomic statistics is an integrated framework of concepts, classifications, and standardized measures used to collect, organize, and present data on the overall performance, structure, and dynamics of an economy.
- F. None of above.
Provenance (1 batch)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69eefacbcc2081909ebf00daa23f1981 |
completed | April 27, 2026, 5:57 a.m. |
Created at: April 27, 2026, 9:04 a.m.