Triple
T29076532
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sierpiński carpet |
E735955
|
entity |
| Predicate | HausdorffDimension |
P73728
|
FINISHED |
| Object | log(8)/log(3) |
—
|
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: log(8)/log(3) | Statement: [Sierpiński carpet, HausdorffDimension, log(8)/log(3)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: HausdorffDimension Context triple: [Sierpiński carpet, HausdorffDimension, log(8)/log(3)]
-
A.
hasHausdorffDimension
chosen
Indicates that a mathematical object is associated with a specific Hausdorff dimension value, expressing the fractal or geometric complexity of the object.
-
B.
isSelfSimilar
Indicates that an entity exhibits similarity to itself across different scales, parts, or transformations, often implying a recursive or fractal-like structure.
-
C.
formationDimension
Indicates the dimensional characteristics (such as size, scale, or extent) associated with the formation of something.
-
D.
EulerCharacteristic
Indicates the topological invariant of a space that equals, in a suitable decomposition, the alternating sum of the counts of its cells (e.g., vertices − edges + faces).
-
E.
dimensionAsVectorSpaceOverℚ
Indicates that the dimension of a given vector space is being considered specifically as a vector space over the field of rational numbers ℚ.
- 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_69f077e9b0a48190bb79548279cb7f64 |
completed | April 28, 2026, 9:03 a.m. |
| NER | Named-entity recognition | batch_69f660fdf5f08190b36e506672b64683 |
completed | May 2, 2026, 8:39 p.m. |
| PD | Predicate disambiguation | batch_69f659d297cc8190b2b962ba30a1edb3 |
completed | May 2, 2026, 8:08 p.m. |
Created at: April 28, 2026, 10:23 a.m.