Triple
T8505596
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rubik's Cube |
E201324
|
entity |
| Predicate | numberOfCenterCubiesOnStandardCube |
P63968
|
FINISHED |
| Object | 6 |
—
|
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: 6 | Statement: [Rubik's Cube, numberOfCenterCubiesOnStandardCube, 6]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfCenterCubiesOnStandardCube Context triple: [Rubik's Cube, numberOfCenterCubiesOnStandardCube, 6]
-
A.
numberOfSpiredTetrahedrons
Indicates the count of spired tetrahedron structures associated with a given subject.
-
B.
hasNumberOfCentres
chosen
Indicates the relationship specifying how many centers (or central units/locations) are associated with a given entity.
-
C.
numberOfSides
Indicates the relationship that specifies how many sides a given object or shape has.
-
D.
numberOfCounts
Indicates the total quantity or tally of discrete occurrences, items, or instances associated with an entity or event.
-
E.
numberOfCentralStars
Indicates the quantity of central stars associated with or contained within a given entity or system.
- 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_69ca831fe47c8190b5c57b456d2aefa0 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe5d8b7208190b199c56bf366c692 |
completed | March 31, 2026, 3:18 p.m. |
| PD | Predicate disambiguation | batch_69cbd10cfd208190a519049fad32c508 |
completed | March 31, 2026, 1:50 p.m. |
Created at: March 30, 2026, 6:14 p.m.