Triple
T24816852
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | rhombicosidodecahedron |
E620946
|
entity |
| Predicate | hasNumberOfPentagonalFaces |
P159692
|
FINISHED |
| Object | 12 |
—
|
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: 12 | Statement: [rhombicosidodecahedron, hasNumberOfPentagonalFaces, 12]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfPentagonalFaces Context triple: [rhombicosidodecahedron, hasNumberOfPentagonalFaces, 12]
-
A.
hasPentagons
Indicates that an entity possesses or contains one or more pentagon-shaped components or regions.
-
B.
numberOfSides
Indicates the relationship that specifies how many sides a given object or shape has.
-
C.
hasFaceTransitivityCount
Indicates the number of times a face-related relation or transformation is applied or propagated through connected entities.
-
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.
hasFaceTransitivityType
Indicates the type of transitivity relationship that holds between faces in a geometric or topological structure.
- 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_69e2fabfd4648190bd0e5c7f4dbb6cab |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f5f7a205688190b8f36bff5013247c |
completed | May 2, 2026, 1:09 p.m. |
| PD | Predicate disambiguation | batch_69f5afd5baac8190bb8ed576813c8591 |
completed | May 2, 2026, 8:03 a.m. |
| PDg | Predicate description generation | batch_69f5f6b32a8881909baa0db57b80d56a |
completed | May 2, 2026, 1:05 p.m. |
Created at: April 18, 2026, 5:03 a.m.