Triple
T5213936
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Blum complexity measures |
E117702
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | complexity measure |
C17828
|
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: complexity measure Context triple: [Blum complexity measures, instanceOf, complexity measure]
-
A.
entropy measure
An entropy measure is a quantitative metric that captures the amount of uncertainty, randomness, or information content in a system, distribution, or process.
-
B.
model of computation
A model of computation is an abstract mathematical framework that defines how algorithms are represented and executed, specifying the rules, operations, and resources available for performing computations.
-
C.
set of axioms in information theory
A set of axioms in information theory is a foundational collection of formal assumptions that precisely define and constrain measures of information, uncertainty, and related concepts so that theorems and results can be derived consistently.
-
D.
set of axioms in information theory
A set of axioms in information theory is a foundational collection of formal principles that precisely define and constrain measures of information, uncertainty, and related concepts so that consistent theorems and results can be derived.
-
E.
model of irreversibility
A model of irreversibility is a conceptual framework that represents processes or systems whose evolution cannot be exactly reversed, typically due to entropy increase, information loss, or path-dependent dynamics.
- 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_69bd4464ba3c8190bc16b2ebbe42ddb0 |
completed | March 20, 2026, 12:58 p.m. |
Created at: March 20, 2026, 1:47 p.m.