Triple
T36870521
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 4-sphere S^4 |
E911210
|
entity |
| Predicate | isModelSpaceFor |
P186616
|
FINISHED |
| Object | constant positive curvature geometry in dimension 4 |
—
|
LITERAL FINISHED |
How this triple was built (2 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: constant positive curvature geometry in dimension 4 | Statement: [4-sphere S^4, isModelSpaceFor, constant positive curvature geometry in dimension 4]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isModelSpaceFor Context triple: [4-sphere S^4, isModelSpaceFor, constant positive curvature geometry in dimension 4]
-
A.
isModelOf
Indicates that one entity serves as a representation or abstraction that captures the structure or behavior of another entity.
-
B.
scopeModelUsed
Indicates that a particular model is employed or applied within a specified scope or context.
-
C.
requiresModelingOf
Indicates that one entity depends on another entity being represented or simulated in a model in order for it to be properly defined, analyzed, or executed.
-
D.
isNamedPublicSpaceOf
Indicates that a public space (such as a park, square, or street) bears the name associated with a particular entity (such as a person, event, or organization).
-
E.
definedInModel
Indicates that an element or concept is specified, structured, or formally represented within a particular model.
- F. None of above. chosen
Provenance (4 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_69f76e80f6f0819091cba8e19b269615 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69f9fe1a1ca4819084c196f0041f0be2 |
completed | May 5, 2026, 2:26 p.m. |
| PD | Predicate disambiguation | batch_69f7cf7890008190a8bc355ff2d61c86 |
completed | May 3, 2026, 10:43 p.m. |
| PDg | Predicate description generation | batch_69f9fd66eed48190bdc26a8def328c2d |
completed | May 5, 2026, 2:23 p.m. |
Created at: May 3, 2026, 4:13 p.m.