Triple
T23372383
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SU(n) |
E593508
|
entity |
| Predicate | dimensionOverℝ |
P152464
|
FINISHED |
| Object | n² − 1 |
—
|
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: n² − 1 | Statement: [SU(n), dimensionOverℝ, n² − 1]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: dimensionOverℝ Context triple: [SU(n), dimensionOverℝ, n² − 1]
-
A.
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.
-
B.
dimension
Indicates that one entity specifies a measurable extent or size attribute (such as length, width, height, or similar quantitative property) of another entity.
-
C.
dimensionCount
Indicates the number of distinct dimensions or axes associated with an entity or data structure.
-
D.
dimensionVector
Indicates a vector that specifies the magnitudes or extents of an entity along multiple dimensions or measurement axes.
-
E.
dimensionOfAmbientSpace
Indicates the dimensionality of the surrounding or embedding space in which an object or structure exists.
- 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_69e25d2593c88190bcdf4a716a94ccb2 |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1a3af45ec8190a32aa4e5f04f6756 |
completed | April 29, 2026, 6:22 a.m. |
| PD | Predicate disambiguation | batch_69f061c7aaa48190a58ce93f87155ffc |
completed | April 28, 2026, 7:29 a.m. |
| PDg | Predicate description generation | batch_69f0bd4a0e408190ad8916faf23562d9 |
completed | April 28, 2026, 1:59 p.m. |
Created at: April 17, 2026, 5:32 p.m.