Triple
T1389343
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gauss–Bonnet theorem (early form) |
E29918
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | theorem about curvature |
C716
|
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: theorem about curvature Context triple: [Gauss–Bonnet theorem (early form), instanceOf, theorem about curvature]
-
A.
mathematical theorem
chosen
A mathematical theorem is a rigorously proven statement derived from axioms and previously established results, expressing a fundamental truth within a formal mathematical system.
-
B.
pseudo-Riemannian manifold
A pseudo-Riemannian manifold is a smooth manifold equipped with a nondegenerate, symmetric metric tensor of arbitrary signature that allows measurement of lengths and angles, including those with indefinite sign as in spacetime geometry.
-
C.
geometric structure
A geometric structure is an abstract mathematical entity defined by sets of points and the relationships between them (such as distances, angles, or incidences) that determine its shape and spatial properties.
-
D.
Lorentzian manifold
A Lorentzian manifold is a smooth manifold equipped with a metric tensor of signature \((-+\cdots+)\) (or its variants) that models spacetime in general relativity by distinguishing timelike, spacelike, and null directions.
-
E.
differential geometric object
A differential geometric object is a mathematical entity, such as a manifold, tensor, or connection, defined on smooth spaces and characterized by properties that are invariant under smooth coordinate transformations.
- 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_69a498dc92f8819094a1108f8ac90f43 |
completed | March 1, 2026, 7:51 p.m. |
Created at: March 1, 2026, 7:59 p.m.