Triple
T23772209
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Celine (Las Vegas residency) |
E587563
|
entity |
| Predicate | orchestraSize |
P153890
|
FINISHED |
| Object | 31-piece orchestra |
—
|
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: 31-piece orchestra | Statement: [Celine (Las Vegas residency), orchestraSize, 31-piece orchestra]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: orchestraSize Context triple: [Celine (Las Vegas residency), orchestraSize, 31-piece orchestra]
-
A.
numberOfOrchestras
Indicates the quantity of orchestras associated with a given entity.
-
B.
orchestralForces
Indicates the specific ensemble of instruments and performers required or used to realize a musical work.
-
C.
orchestralRole
Indicates the specific function or position an entity holds within an orchestra (e.g., conductor, principal violin, section player).
-
D.
orchestralExcerpt
Indicates that one entity is an excerpt or short passage taken from an orchestral musical work associated with another entity.
-
E.
hasOrchestraSection
Indicates that something includes or is associated with a particular section of an orchestra.
- 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_69e2490d245881909028226a1393d624 |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1c467e6588190aab28bc5a8e43e80 |
completed | April 29, 2026, 8:42 a.m. |
| PD | Predicate disambiguation | batch_69f155f79e34819080f9ddb972b34deb |
completed | April 29, 2026, 12:51 a.m. |
| PDg | Predicate description generation | batch_69f15ed138f88190a8ae555422978908 |
completed | April 29, 2026, 1:28 a.m. |
Created at: April 17, 2026, 7:15 p.m.