Triple
T17752814
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gaussian orthogonal ensemble |
E443153
|
entity |
| Predicate | symmetryClass |
P60479
|
FINISHED |
| Object | orthogonal symmetry |
—
|
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: orthogonal symmetry | Statement: [Gaussian orthogonal ensemble, symmetryClass, orthogonal symmetry]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: symmetryClass Context triple: [Gaussian orthogonal ensemble, symmetryClass, orthogonal symmetry]
-
A.
symmetryInvolved
Indicates that a relationship or action inherently involves symmetry, such as invariance under certain transformations or the presence of symmetric structure or behavior.
-
B.
usesSymmetryGroup
Indicates that one entity employs or is based on a particular symmetry group in its structure, behavior, or formulation.
-
C.
hasSymmetryType
chosen
Indicates that one entity possesses a specific kind or pattern of symmetry characterized or classified by the other entity.
-
D.
testsSymmetry
Indicates that one entity evaluates or verifies whether a relationship or property holds identically in both directions between two entities.
-
E.
localSymmetry
Indicates that an entity exhibits symmetry within a localized region or subset of its structure, rather than across its entire extent.
- 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_69d8b9edf16c8190a59ebd245d378f4f |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e4841c0540819093a32d759775c61f |
completed | April 19, 2026, 7:28 a.m. |
| PD | Predicate disambiguation | batch_69e3cde9dc288190af0e2198487f2051 |
completed | April 18, 2026, 6:31 p.m. |
Created at: April 10, 2026, 10:10 a.m.