Triple
T18723616
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | extended Kalman filter |
E457842
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | recursive estimator |
C40683
|
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: recursive estimator Context triple: [extended Kalman filter, instanceOf, recursive estimator]
-
A.
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.
-
B.
redescending M-estimator
A redescending M-estimator is a robust statistical estimator whose influence function decreases back toward zero for large residuals, thereby downweighting extreme outliers more strongly than standard M-estimators.
-
C.
meta-estimator
A meta-estimator is a higher-level model that wraps or combines one or more base estimators to extend, modify, or coordinate their behavior for tasks like ensembling, preprocessing, or model selection.
-
D.
recursive function
A recursive function is a function that solves a problem by calling itself with modified arguments until reaching a base case that stops the recursion.
-
E.
recurrent artificial neural network
A recurrent artificial neural network is a type of neural network where connections form directed cycles, allowing information to persist over time and enabling the modeling of sequential or temporal data.
- F. None of above. chosen
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_69d8d393ba9c8190a8b03b04ddbb0a09 |
completed | April 10, 2026, 10:40 a.m. |
Created at: April 10, 2026, 11:50 a.m.