Triple
T24036505
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | GL(n,ℂ) |
E595246
|
entity |
| Predicate | dimensionAsRealManifold |
P63678
|
FINISHED |
| Object | 2n² |
—
|
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: 2n² | Statement: [GL(n,ℂ), dimensionAsRealManifold, 2n²]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: dimensionAsRealManifold Context triple: [GL(n,ℂ), dimensionAsRealManifold, 2n²]
-
A.
dimensionOverℝ
Indicates that the dimension of a given mathematical structure is being considered or measured as a vector space over the field of real numbers ℝ.
-
B.
dimensionOfAmbientSpace
Indicates the dimensionality of the surrounding or embedding space in which an object or structure exists.
-
C.
dimensionAsLieGroup
chosen
Indicates the dimension of an entity when it is considered as a Lie group, i.e., the number of independent parameters defining the group manifold.
-
D.
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.
-
E.
dimensionCount
Indicates the number of distinct dimensions or axes associated with an entity or data structure.
- 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_69e288bf45f08190a1b6ed8cd0b9e86b |
completed | April 17, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69f1d8d43884819093e9207a99ae2a70 |
completed | April 29, 2026, 10:09 a.m. |
| PD | Predicate disambiguation | batch_69f1764345388190a3102b62ddb729b4 |
completed | April 29, 2026, 3:08 a.m. |
Created at: April 17, 2026, 9:56 p.m.