Triple
T23801704
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Agmon–Douglis–Nirenberg estimates |
E588690
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | a priori estimate |
C15244
|
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: a priori estimate Context triple: [Agmon–Douglis–Nirenberg estimates, instanceOf, a priori estimate]
-
A.
approximation
An approximation is a value, representation, or solution that is close to, but not exactly equal to, a true or ideal quantity, used when exactness is unnecessary or unattainable.
-
B.
composite estimator
A composite estimator is a statistical estimator formed by combining two or more individual estimators, often through weighted averaging, to improve overall accuracy, stability, or robustness of parameter estimates.
-
C.
equation in the calculus of variations
An equation in the calculus of variations is a mathematical relation, typically an Euler–Lagrange equation, that characterizes the functions making a given functional stationary (usually minimizing or maximizing its value).
-
D.
norm inequality
chosen
A norm inequality is a mathematical statement that compares the sizes (norms) of vectors or functions, often establishing bounds or relationships between different norms in a vector space.
-
E.
seminorm
A seminorm is a function from a vector space to the nonnegative real numbers that is subadditive and absolutely homogeneous but may assign zero to nonzero vectors.
- 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_69e25d15db58819092ac1e6791696fd9 |
completed | April 17, 2026, 4:17 p.m. |
Created at: April 17, 2026, 7:53 p.m.