Triple
T173550
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Feynman checkerboard model |
E3528
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | quantum mechanical model |
C324
|
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: quantum mechanical model Context triple: [Feynman checkerboard model, instanceOf, quantum mechanical model]
-
A.
molecular quantum mechanics method
A molecular quantum mechanics method is a theoretical and computational approach that applies quantum mechanical principles to describe and predict the electronic structure, properties, and behavior of molecules.
-
B.
theoretical model
chosen
A theoretical model is an abstract, simplified representation of a system or phenomenon used to explain, predict, or understand its behavior based on underlying principles and assumptions.
-
C.
nuclear reaction mechanism
A nuclear reaction mechanism is the detailed sequence of interactions and intermediate steps by which incident particles induce changes in a nucleus, leading to specific reaction products and energy release.
-
D.
gravitational collapse model
A gravitational collapse model is a theoretical framework that describes how matter in astrophysical systems contracts under its own gravity, potentially leading to the formation of dense objects such as stars, black holes, or compact stellar remnants.
-
E.
automobile model
An automobile model is a specific version of a vehicle produced by a manufacturer, defined by a distinct combination of design, features, and specifications that differentiates it from other vehicles in the product lineup.
- 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_69a25374990081909766d30c79a18e0e |
completed | Feb. 28, 2026, 2:31 a.m. |
Created at: Feb. 28, 2026, 2:39 a.m.