Triple
T8505598
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rubik's Cube |
E201324
|
entity |
| Predicate | numberOfCornerCubiesOnStandardCube |
P82877
|
FINISHED |
| Object | 8 |
—
|
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: 8 | Statement: [Rubik's Cube, numberOfCornerCubiesOnStandardCube, 8]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfCornerCubiesOnStandardCube Context triple: [Rubik's Cube, numberOfCornerCubiesOnStandardCube, 8]
-
A.
numberOfSides
Indicates the relationship that specifies how many sides a given object or shape has.
-
B.
numberOfSpiredTetrahedrons
Indicates the count of spired tetrahedron structures associated with a given subject.
-
C.
fourCornerCode
Indicates a standardized four-character code used to classify or identify something based on its four key components or positions.
-
D.
numberOfColumnsOnFlanks
Indicates the count of columns located on the flanking sides of a structure or object.
-
E.
hasNumberOfSquares
Indicates that an entity is associated with a specific count of squares it contains or comprises.
- 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_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. |
| PDg | Predicate description generation | batch_69cbe12dd0b88190a38ec4d15dcc870b |
completed | March 31, 2026, 2:58 p.m. |
Created at: March 30, 2026, 6:14 p.m.