Triple
T6397017
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AdS isometry group SO(2,d) |
E143965
|
entity |
| Predicate | hasNumberOfGenerators |
P26394
|
FINISHED |
| Object | (d+2)(d+1)/2 |
—
|
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: (d+2)(d+1)/2 | Statement: [AdS isometry group SO(2,d), hasNumberOfGenerators, (d+2)(d+1)/2]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfGenerators Context triple: [AdS isometry group SO(2,d), hasNumberOfGenerators, (d+2)(d+1)/2]
-
A.
hasGenerations
Indicates a relationship where an entity is associated with one or more successive generational levels or cohorts derived from it.
-
B.
hasGeneratingFunction
Indicates that one entity serves as the generating function associated with, or defining, another entity.
-
C.
hasNumberOfKillingVectors
Indicates the relationship that specifies how many Killing vector fields (symmetries of the metric) a given geometric or physical system possesses.
-
D.
generators
chosen
Indicates that one entity produces, creates, or brings about another entity or outcome, typically as its source or origin.
-
E.
hasNumberOfDaughters
Indicates the specific count of daughters associated with a given entity.
- 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_69c008db906c819096f3597d55d95432 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c068953968819083a94f5de3e11819 |
completed | March 22, 2026, 10:09 p.m. |
| PD | Predicate disambiguation | batch_69c060f25c088190b433f78553ff1d84 |
completed | March 22, 2026, 9:36 p.m. |
Created at: March 22, 2026, 4:35 p.m.