Triple
T14911011
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tukey's biweight |
E371259
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | robust regression estimator |
C25286
|
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: robust regression estimator Context triple: [Tukey's biweight, instanceOf, robust regression estimator]
-
A.
statistical model
A statistical model is a mathematical representation of observed data and underlying random processes, used to describe relationships, make inferences, and generate predictions.
-
B.
adaptive learning rate method
An adaptive learning rate method is an optimization technique that automatically adjusts the step size for each parameter during training based on past gradient information to improve convergence speed and stability.
-
C.
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.
-
D.
statistical procedure
chosen
A statistical procedure is a systematic method or set of steps used to collect, analyze, interpret, and draw conclusions from data based on principles of probability and statistics.
-
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.
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_69d85cc7ea3481908228b5acb7d06f12 |
completed | April 10, 2026, 2:13 a.m. |
Created at: April 10, 2026, 2:26 a.m.