Triple
T24806907
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | rhombicuboctahedron |
E620678
|
entity |
| Predicate | hasFaceCountByType |
P159038
|
FINISHED |
| Object | {triangle:8, square:18} |
—
|
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: {triangle:8, square:18} | Statement: [rhombicuboctahedron, hasFaceCountByType, {triangle:8, square:18}]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFaceCountByType
Context triple: [rhombicuboctahedron, hasFaceCountByType, {triangle:8, square:18}]
-
A.
numberOfFaces
Indicates the relationship that specifies how many faces a given object or entity has.
-
B.
hasFaceTransitivityType
Indicates the type of transitivity relationship that holds between faces in a geometric or topological structure.
-
C.
hasNumberOfTriangles
Indicates that an entity is associated with a specific count of triangles it contains or involves.
-
D.
hasNumberOfTypes
Indicates that an entity is associated with a specific count of distinct types or categories it possesses or includes.
-
E.
haveRegularFaces
Indicates that the entity possesses faces that are all regular polygons, typically congruent and evenly shaped.
- 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_69f497bc12b881908fe3386c66252bf6 |
completed | May 1, 2026, 12:08 p.m. |
| PD | Predicate disambiguation | batch_69f49366e8d08190adb4b71fe3a14683 |
completed | May 1, 2026, 11:49 a.m. |
| PDg | Predicate description generation | batch_69f497b8abb88190bb672cf6907c4b8d |
completed | May 1, 2026, 12:08 p.m. |
Created at: April 18, 2026, 4:50 a.m.