Triple
T16111208
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Downtown Cabaret Theatre |
E390880
|
entity |
| Predicate | seatingStyle |
P16826
|
FINISHED |
| Object | cabaret seating |
—
|
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: cabaret seating | Statement: [Downtown Cabaret Theatre, seatingStyle, cabaret seating]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: seatingStyle Context triple: [Downtown Cabaret Theatre, seatingStyle, cabaret seating]
-
A.
architecturalStyleOfSeat
Indicates the architectural style that characterizes a particular seat or seating structure.
-
B.
seatingConfiguration
chosen
Indicates how seats are arranged or organized relative to each other in a given context.
-
C.
hasSeating
Indicates that one entity provides or contains seating capacity or seating arrangements for another entity.
-
D.
seatStructure
Indicates that one entity serves as the structural or physical seating component or arrangement associated with another entity.
-
E.
seatingPosition
Indicates the relative location or arrangement of an entity’s seat with respect to other seats or a reference point in a seating layout.
- 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_69d87f1a8dd881909f1de6ef78849874 |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e2016718ec8190a6c8284c7f612ea8 |
completed | April 17, 2026, 9:46 a.m. |
| PD | Predicate disambiguation | batch_69e1828518c48190a8ef3aaa46a1f639 |
completed | April 17, 2026, 12:44 a.m. |
Created at: April 10, 2026, 5 a.m.