Triple
T6833392
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gaussian rationals ℚ(i) |
E157390
|
entity |
| Predicate | hasRealEmbeddings |
P72965
|
FINISHED |
| Object | 0 |
—
|
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: 0 | Statement: [Gaussian rationals ℚ(i), hasRealEmbeddings, 0]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRealEmbeddings Context triple: [Gaussian rationals ℚ(i), hasRealEmbeddings, 0]
-
A.
isRealValued
Indicates that the value or function in question takes values exclusively from the set of real numbers.
-
B.
isImaginary
Indicates that something exists only in the mind or imagination and does not have a corresponding real-world or physical existence.
-
C.
hasCanonicalBasis
Indicates that there exists a standard or preferred basis associated with an entity, typically used as the reference basis in its context.
-
D.
hasComplexPoints
Indicates that something possesses or includes points that are intricate, detailed, or composed of multiple interconnected parts.
-
E.
hasIntegralRepresentation
Indicates that one entity can be expressed or represented as an integral involving the other entity.
- 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_69c6882c53608190b99aebef079b23bd |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d62b1e8c8190a81d91191a54b073 |
completed | March 27, 2026, 7:10 p.m. |
| PD | Predicate disambiguation | batch_69c6d09d95f0819091ca7f897dc21efe |
completed | March 27, 2026, 6:46 p.m. |
| PDg | Predicate description generation | batch_69c6d11fab808190b18160ff3829fcc6 |
completed | March 27, 2026, 6:49 p.m. |
Created at: March 27, 2026, 2:18 p.m.