Triple
T24816851
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | rhombicosidodecahedron |
E620946
|
entity |
| Predicate | hasNumberOfSquareFaces |
P25755
|
FINISHED |
| Object | 30 |
—
|
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: 30 | Statement: [rhombicosidodecahedron, hasNumberOfSquareFaces, 30]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfSquareFaces Context triple: [rhombicosidodecahedron, hasNumberOfSquareFaces, 30]
-
A.
numberOfSides
Indicates the relationship that specifies how many sides a given object or shape has.
-
B.
hasNumberOfSquares
chosen
Indicates that an entity is associated with a specific count of squares it contains or comprises.
-
C.
hasSquareShape
Indicates that an entity possesses a square geometric shape, typically having four equal sides and four right angles.
-
D.
isFaceTransitive
Indicates that a face-to-face relation between entities is transitive, so if one entity is face-related to a second, and the second is face-related to a third, then the first is also face-related to the third.
-
E.
haveRegularFaces
Indicates that the entity possesses faces that are all regular polygons, typically congruent and evenly shaped.
- 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_69e2fabfd4648190bd0e5c7f4dbb6cab |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f55e519978819087a1676564a74630 |
completed | May 2, 2026, 2:15 a.m. |
| PD | Predicate disambiguation | batch_69f4a0edd10c81908a052ab864d57c54 |
completed | May 1, 2026, 12:47 p.m. |
Created at: April 18, 2026, 5:03 a.m.