Triple
T12220474
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Plücker coordinates |
E291200
|
entity |
| Predicate | dimensionOfCoordinateSpace |
P53031
|
FINISHED |
| Object | C(n,k) |
—
|
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: C(n,k) | Statement: [Plücker coordinates, dimensionOfCoordinateSpace, C(n,k)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: dimensionOfCoordinateSpace Context triple: [Plücker coordinates, dimensionOfCoordinateSpace, C(n,k)]
-
A.
dimensionCount
Indicates the number of distinct dimensions or axes associated with an entity or data structure.
-
B.
dimensionOfConfigurationSpace
Indicates the number of independent parameters or degrees of freedom that define the configuration space of a system.
-
C.
hasDimensionality
chosen
Indicates that an entity possesses a specific number of dimensions or a particular dimensional structure.
-
D.
basisVectorsCount
Indicates the number of basis vectors associated with a given vector space or basis.
-
E.
formationDimension
Indicates the dimensional characteristics (such as size, scale, or extent) associated with the formation of something.
- 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_69d6ab668acc8190963ba424049d6aee |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d920e312708190b4aede2e21f5f697 |
completed | April 10, 2026, 4:10 p.m. |
| PD | Predicate disambiguation | batch_69d91c3d669c81908eea7ad61122d275 |
completed | April 10, 2026, 3:50 p.m. |
Created at: April 8, 2026, 9:51 p.m.