Triple
T24806898
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | rhombicuboctahedron |
E620678
|
entity |
| Predicate | hasDihedralAngle |
P160884
|
FINISHED |
| Object | between square and triangle faces |
—
|
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: between square and triangle faces | Statement: [rhombicuboctahedron, hasDihedralAngle, between square and triangle faces]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDihedralAngle Context triple: [rhombicuboctahedron, hasDihedralAngle, between square and triangle faces]
-
A.
hasTorsion
Indicates that an object or structure possesses torsion, meaning it is subject to or characterized by twisting about an axis.
-
B.
hasTriangleAngle
Indicates that a triangle possesses a specific angle as one of its interior angles.
-
C.
hasTypicalAngle
Indicates that there is a characteristic or commonly occurring angle associated with the relationship between the entities.
-
D.
hasRightAngleIntersections
Indicates that the entities intersect each other at right (90-degree) angles.
-
E.
hasDegreeOfFreedom
Indicates that one entity possesses a specific independent parameter or mode in which it can vary or move relative to another entity or within a system.
- 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_69e2fabf26bc8190b191faac8f67065b |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f60cd7b3e88190a1206958c0f0b225 |
completed | May 2, 2026, 2:40 p.m. |
| PD | Predicate disambiguation | batch_69f60b8461ac81908c5bd3d73eed59f4 |
completed | May 2, 2026, 2:34 p.m. |
| PDg | Predicate description generation | batch_69f60c32ce088190a620eb59d2499fa9 |
completed | May 2, 2026, 2:37 p.m. |
Created at: April 18, 2026, 4:50 a.m.