Triple
T8454675
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Menger sponge |
E199890
|
entity |
| Predicate | numberOfSubcubesAfterNthIteration |
P82725
|
FINISHED |
| Object | 20^n |
—
|
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: 20^n | Statement: [Menger sponge, numberOfSubcubesAfterNthIteration, 20^n]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfSubcubesAfterNthIteration Context triple: [Menger sponge, numberOfSubcubesAfterNthIteration, 20^n]
-
A.
numberOfSpiredTetrahedrons
Indicates the count of spired tetrahedron structures associated with a given subject.
-
B.
numberOfStaircases
Indicates the quantity of distinct staircases associated with or present in a given entity or location.
-
C.
numberOfPaths
Indicates the count of distinct paths or routes that exist between specified points or within a given structure.
-
D.
numberOfPyramids
Indicates the quantity of pyramids associated with a given entity or context.
-
E.
numberOfSpheres
Indicates the quantity of spheres associated with or contained by a given entity.
- 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_69ca8318231881908fd1bc1c4d45d286 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe48ca9988190b60ebd09a135194d |
completed | March 31, 2026, 3:13 p.m. |
| PD | Predicate disambiguation | batch_69cbd0fc634481909842c0a30077bfde |
completed | March 31, 2026, 1:49 p.m. |
| PDg | Predicate description generation | batch_69cbe12dd0b88190a38ec4d15dcc870b |
completed | March 31, 2026, 2:58 p.m. |
Created at: March 30, 2026, 6:10 p.m.