Triple
T32043786
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Milne universe model |
E818283
|
entity |
| Predicate | hasSpatialGeometry |
P25627
|
FINISHED |
| Object | hyperbolic |
—
|
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: hyperbolic | Statement: [Milne universe model, hasSpatialGeometry, hyperbolic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSpatialGeometry Context triple: [Milne universe model, hasSpatialGeometry, hyperbolic]
-
A.
hasGeometry
chosen
Indicates that an entity is associated with a specific geometric representation or spatial form.
-
B.
hasSpatialReferenceType
Indicates that one entity specifies the kind or category of spatial reference system used to define the location or geometry of another entity.
-
C.
hasSpatialComponent
Indicates that one entity includes, consists of, or is associated with another entity that represents a spatial part, region, or aspect of it.
-
D.
supportsSpatialQueries
Indicates that the subject system or component is capable of performing spatial (location- or geometry-based) queries on data.
-
E.
hasSpatialConcept
Indicates a relationship where one entity is associated with, defined by, or characterized through a particular spatial concept or spatial configuration.
- F. None of above.
Provenance (3 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_69f348fcfb648190859f6be5e04b7cfe |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69fd474b7e788190a9bb9b542d878f60 |
completed | May 8, 2026, 2:15 a.m. |
| PD | Predicate disambiguation | batch_69fd46d8b2f0819099d92d72c902f60e |
completed | May 8, 2026, 2:13 a.m. |
Created at: May 1, 2026, 12:19 a.m.