Triple
T6385271
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Statistical Confluence Analysis by Means of Complete Regression Systems |
E143684
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | econometrics book |
C3065
|
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: econometrics book Context triple: [Statistical Confluence Analysis by Means of Complete Regression Systems, instanceOf, econometrics book]
-
A.
econometrics lecture
An econometrics lecture is a structured instructional session that teaches how to apply statistical and mathematical methods to analyze economic data and test economic theories.
-
B.
economics book
chosen
An economics book is a written work that explains, analyzes, or applies economic principles, theories, and data to help readers understand how individuals, markets, and governments make decisions about scarce resources.
-
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.
economic treatise
An economic treatise is a systematic, often theoretical written work that analyzes, explains, and argues about economic principles, policies, and their implications for society.
-
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_69c008dac1ec81909cef8157ccd69962 |
completed | March 22, 2026, 3:20 p.m. |
Created at: March 22, 2026, 4:34 p.m.