Triple

T37196859
Position Surface form Disambiguated ID Type / Status
Subject Cheeger–Simons differential characters E921617 entity
Predicate instanceOf P0 FINISHED
Object differential cohomology theory C22356 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: differential cohomology theory
Context triple: [Cheeger–Simons differential characters, instanceOf, differential cohomology theory]
  • A. cohomology theory chosen
    A cohomology theory is a functorial assignment of graded algebraic invariants to topological spaces (or other mathematical objects) that encodes global structural and obstruction information via axioms such as exactness and homotopy invariance.
  • B. theory in differential topology
    A theory in differential topology is a coherent framework of concepts, theorems, and techniques that studies the properties of smooth manifolds and smooth maps between them that are invariant under smooth deformations.
  • C. cohomological invariant
    A cohomological invariant is a rule that assigns to each object in a given class (such as algebraic varieties, groups, or topological spaces) an element of a cohomology group in a way that is functorial and captures structural or classification information about those objects.
  • D. cohomological method
    A cohomological method is a technique in mathematics that uses cohomology theories to translate geometric, topological, or algebraic problems into computations with cohomology groups, enabling the extraction of structural and invariant information.
  • E. homological invariant
    A homological invariant is a quantity or structure derived from homology theory that remains unchanged under specified transformations, used to distinguish and classify mathematical objects up to an appropriate notion of equivalence.
  • 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_69f76ea313a08190a54404cd1e47da90 completed May 3, 2026, 3:49 p.m.
Created at: May 3, 2026, 4:15 p.m.