Triple
T461809
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | de Sitter spacetime |
E7354
|
entity |
| Predicate | hasNumberOfKillingVectors |
P14256
|
FINISHED |
| Object | 10 |
—
|
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: 10 | Statement: [de Sitter spacetime, hasNumberOfKillingVectors, 10]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfKillingVectors Context triple: [de Sitter spacetime, hasNumberOfKillingVectors, 10]
-
A.
hasVector
Indicates that an entity is associated with, or can be represented by, a specific vector in some vector space.
-
B.
numberOfIndependentEquations
Indicates the count of distinct, non-redundant equations that independently constrain or relate the variables in a system.
-
C.
numberOfConflicts
Indicates the count of distinct conflicts associated with or involving a given entity or situation.
-
D.
hasNumberOfDivisions
Indicates the relationship that specifies how many divisions or subunits an entity possesses.
-
E.
dimensionCount
Indicates the number of distinct dimensions or axes associated with an entity or data structure.
- 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_69a2e7e5c5bc8190a1dc8178218fba40 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2efbed5b88190a45716812eb4cfdf |
completed | Feb. 28, 2026, 1:38 p.m. |
| PD | Predicate disambiguation | batch_69a2ede8eac081908dffade6a5e7950b |
completed | Feb. 28, 2026, 1:30 p.m. |
| PDg | Predicate description generation | batch_69a2ef06d2fc8190b379d575215a8518 |
completed | Feb. 28, 2026, 1:35 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.