Triple
T23812433
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Merkaba |
E589892
|
entity |
| Predicate | associatedShape |
P136254
|
FINISHED |
| Object | interlocking tetrahedra (star tetrahedron) |
—
|
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: interlocking tetrahedra (star tetrahedron) | Statement: [Merkaba, associatedShape, interlocking tetrahedra (star tetrahedron)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedShape Context triple: [Merkaba, associatedShape, interlocking tetrahedra (star tetrahedron)]
-
A.
shapeAssociation
chosen
Indicates a relationship where one entity is associated with, characterized by, or linked to a particular shape of another entity.
-
B.
shapeInfluencedBy
Indicates that the form or outline of one entity is affected, determined, or modified by another entity or factor.
-
C.
hasShapeRelation
Indicates that one entity is related to another through a specific geometric or spatial shape relationship (such as similarity, congruence, or containment of shape).
-
D.
secondaryShape
Indicates that one entity serves as a secondary or subordinate shape in relation to another primary shape.
-
E.
facesAssociatedWith
Indicates that there is a connection or linkage between certain faces (e.g., facial instances or representations) and related entities, contexts, or records.
- 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_69e25d19fecc8190a5cf39bbb18d5d7f |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1c75715d48190ac55713de9d5ba4f |
completed | April 29, 2026, 8:54 a.m. |
| PD | Predicate disambiguation | batch_69f155fe300481909bd617443228df65 |
completed | April 29, 2026, 12:51 a.m. |
Created at: April 17, 2026, 7:57 p.m.