Triple
T16402916
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Smale’s paradox |
E398343
|
entity |
| Predicate | dimensionOfAmbientSpace |
P123289
|
FINISHED |
| Object | 3 |
—
|
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: 3 | Statement: [Smale’s paradox, dimensionOfAmbientSpace, 3]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: dimensionOfAmbientSpace Context triple: [Smale’s paradox, dimensionOfAmbientSpace, 3]
-
A.
dimensionCount
Indicates the number of distinct dimensions or axes associated with an entity or data structure.
-
B.
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.
-
C.
dimensionOfAssociatedLattice
Indicates the dimensionality (number of independent directions) of the lattice that is associated with a given object or structure.
-
D.
dimensionOfConfigurationSpace
Indicates the number of independent parameters or degrees of freedom that define the configuration space of a system.
-
E.
basisVectorsCount
Indicates the number of basis vectors associated with a given vector space or basis.
- 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_69d87f2950248190bc8ad9b9bebdc8c8 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e327d0652081908f42f78b156f3ae7 |
completed | April 18, 2026, 6:42 a.m. |
| PD | Predicate disambiguation | batch_69e226fe1dd08190865c181721f8c348 |
completed | April 17, 2026, 12:26 p.m. |
| PDg | Predicate description generation | batch_69e24555bb6c8190977cf5c5f9149056 |
completed | April 17, 2026, 2:36 p.m. |
Created at: April 10, 2026, 5:09 a.m.