Triple
T18044138
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fama–French three-factor model |
E431728
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | asset pricing 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: asset pricing model Context triple: [Fama–French three-factor model, instanceOf, asset pricing model]
-
A.
option pricing model
An option pricing model is a mathematical framework used to estimate the fair value of options by quantifying how factors like underlying asset price, volatility, time to expiration, interest rates, and dividends affect their expected payoff.
-
B.
price determination model
A price determination model is a conceptual framework that explains how the interaction of supply, demand, and market conditions leads to the establishment of prices for goods or services.
-
C.
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.
-
D.
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.
-
E.
financial forecasting model
A financial forecasting model is a computational framework that uses historical and current financial data, along with statistical or machine learning techniques, to predict future financial outcomes such as revenues, expenses, cash flows, or asset prices.
- 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_69d8b906482481908183315b9ecf9994 |
completed | April 10, 2026, 8:47 a.m. |
Created at: April 10, 2026, 10:25 a.m.