Triple
T26254245
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Griess algebra |
E656676
|
entity |
| Predicate | basisDimension |
P77161
|
FINISHED |
| Object | 196884 |
—
|
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: 196884 | Statement: [Griess algebra, basisDimension, 196884]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: basisDimension Context triple: [Griess algebra, basisDimension, 196884]
-
A.
boundaryDimension
Indicates the dimensionality of the boundary of an entity, such as whether its boundary is a point, line, surface, or higher-dimensional analogue.
-
B.
formationDimension
Indicates the dimensional characteristics (such as size, scale, or extent) associated with the formation of something.
-
C.
dimension
Indicates that one entity specifies a measurable extent or size attribute (such as length, width, height, or similar quantitative property) of another entity.
-
D.
basisVectorsCount
chosen
Indicates the number of basis vectors associated with a given vector space or basis.
-
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_69ee5b4d25ac819086acb51184602576 |
completed | April 26, 2026, 6:37 p.m. |
| NER | Named-entity recognition | batch_69f60dcc29cc81908880bd825cb12141 |
completed | May 2, 2026, 2:44 p.m. |
| PD | Predicate disambiguation | batch_69f5f7ff548c8190a23e98c5e66e0bc7 |
completed | May 2, 2026, 1:11 p.m. |
Created at: April 26, 2026, 9:08 p.m.