Triple
T30828442
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Quantitative Feedback Theory |
E785142
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | robust control design methodology |
C22748
|
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 control design methodology Context triple: [Quantitative Feedback Theory, instanceOf, robust control design methodology]
-
A.
control theory conference
A control theory conference is a professional gathering where researchers, practitioners, and students present, discuss, and advance methods for analyzing and designing systems that regulate dynamic behavior.
-
B.
control engineering concept
chosen
A control engineering concept is a theoretical or practical principle used to analyze, design, and optimize systems that automatically regulate their behavior to achieve desired performance.
-
C.
export control law
Export control law is the body of legal rules and regulations that govern the transfer of goods, technology, software, and services across national borders to protect national security, foreign policy interests, and international obligations.
-
D.
solution concept in stochastic control
A solution concept in stochastic control is a rigorous mathematical framework that specifies what it means for a control policy or strategy to optimally govern a stochastic dynamical system, typically defining admissible controls, performance criteria, and the form of optimality (e.g., value functions, optimal policies, or equilibria).
-
E.
control systems engineer
A control systems engineer designs, analyzes, and optimizes automated systems that regulate the behavior of dynamic processes using feedback, sensors, and control algorithms.
- 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_69f224b6642481909e8d701de2cd1a53 |
completed | April 29, 2026, 3:33 p.m. |
Created at: April 29, 2026, 8:44 p.m.