Triple
T25725435
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kubo-Greenwood formula for conductivity |
E645104
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | transport theory formula |
C38655
|
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: transport theory formula Context triple: [Kubo-Greenwood formula for conductivity, instanceOf, transport theory formula]
-
A.
transport theory
chosen
Transport theory is the conceptual framework that describes how particles, energy, or quantities such as mass and charge move and are distributed within physical systems under the influence of processes like diffusion, convection, and external forces.
-
B.
transport model
A transport model is a conceptual or mathematical representation used to simulate and analyze the movement of people, goods, or resources across a network or spatial system under various conditions and constraints.
-
C.
transport strategy
A transport strategy is a high-level plan that defines how people and goods will be moved efficiently, safely, sustainably, and cost-effectively within and between areas over a given time horizon.
-
D.
tunneling probability factor
The tunneling probability factor is a dimensionless quantity that expresses the likelihood that a particle will quantum mechanically penetrate and pass through a potential barrier it classically could not surmount.
-
E.
optics formula
An optics formula is a mathematical expression that quantitatively relates optical quantities—such as object and image distances, focal length, refractive index, and wavelength—to describe the behavior of light in optical systems.
- 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_69e77e8476fc8190bd5e9d05b89fad0a |
completed | April 21, 2026, 1:41 p.m. |
Created at: April 21, 2026, 10:23 p.m.