Triple
T15661754
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Minkowski metric η_{μν} |
E376582
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | pseudo-Riemannian metric |
C3971
|
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: pseudo-Riemannian metric
Context triple: [Minkowski metric η_{μν}, instanceOf, pseudo-Riemannian metric]
-
A.
pseudo-Riemannian manifold
chosen
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.
-
B.
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.
-
C.
pseudometric
A pseudometric is a function that assigns a nonnegative real number as a "distance" between any two points in a set, satisfying all the axioms of a metric except that distinct points are allowed to have zero distance.
-
D.
curvature tensor
A curvature tensor is a multilinear mathematical object in differential geometry that measures how much a space (or manifold) deviates from being flat by quantifying the failure of vectors to return to their original direction after parallel transport around infinitesimal loops.
-
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_69d85cd1564c8190991adda63bfab4b0 |
completed | April 10, 2026, 2:13 a.m. |
Created at: April 10, 2026, 4:15 a.m.