Triple
T21046355
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thurston norm |
E518459
|
entity |
| Predicate | relatedInvariant |
P37
|
FINISHED |
| Object | Gromov norm |
—
|
NE NERFINISHED |
How this triple was built (3 steps)
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.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Gromov norm | Statement: [Thurston norm, relatedInvariant, Gromov norm]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gromov norm Context triple: [Thurston norm, relatedInvariant, Gromov norm]
-
A.
Thurston norm
The Thurston norm is a topological invariant on the second homology of a 3-manifold that measures the minimal complexity (via Euler characteristic) of embedded surfaces representing a given homology class.
-
B.
Gromov’s systolic inequality
Gromov’s systolic inequality is a fundamental result in Riemannian geometry that bounds the volume of a manifold from below in terms of the length of its shortest non-contractible loop (the systole).
-
C.
Gromov compactness theorem
The Gromov compactness theorem is a fundamental result in symplectic geometry and geometric analysis that provides compactness for families of pseudoholomorphic curves (or Riemannian manifolds with bounded geometry) up to bubbling and degeneration.
-
D.
Cheeger–Gromov compactness theorem
The Cheeger–Gromov compactness theorem is a fundamental result in Riemannian geometry that gives conditions under which a sequence of Riemannian manifolds has a subsequence converging (in the Gromov–Hausdorff or smooth sense) to a limit space.
-
E.
Dehn function
The Dehn function is a mathematical tool in geometric group theory that measures the complexity of filling loops with discs in a space or group, quantifying the difficulty of solving the word problem.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Gromov norm Target entity description: The Gromov norm is a topological invariant of manifolds that measures the “size” of their fundamental class via the minimal ℓ¹-norm of singular chains representing it, closely linked to simplicial volume and geometric structures.
-
A.
Thurston norm
The Thurston norm is a topological invariant on the second homology of a 3-manifold that measures the minimal complexity (via Euler characteristic) of embedded surfaces representing a given homology class.
-
B.
Gromov’s systolic inequality
Gromov’s systolic inequality is a fundamental result in Riemannian geometry that bounds the volume of a manifold from below in terms of the length of its shortest non-contractible loop (the systole).
-
C.
Gromov compactness theorem
The Gromov compactness theorem is a fundamental result in symplectic geometry and geometric analysis that provides compactness for families of pseudoholomorphic curves (or Riemannian manifolds with bounded geometry) up to bubbling and degeneration.
-
D.
Cheeger–Gromov compactness theorem
The Cheeger–Gromov compactness theorem is a fundamental result in Riemannian geometry that gives conditions under which a sequence of Riemannian manifolds has a subsequence converging (in the Gromov–Hausdorff or smooth sense) to a limit space.
-
E.
Dehn function
The Dehn function is a mathematical tool in geometric group theory that measures the complexity of filling loops with discs in a space or group, quantifying the difficulty of solving the word problem.
- F. None of above. chosen
Provenance (2 batches)
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_69e0b50438e08190917e2538bb8bc034 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e6fcf3cac081909915a440fbb5c084 |
completed | April 21, 2026, 4:28 a.m. |
Created at: April 16, 2026, 2:34 p.m.