Triple
T92275
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Annenberg Center for the Performing Arts |
E1853
|
entity |
| Predicate | hasSeatingType |
P2608
|
FINISHED |
| Object | indoor 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: indoor seating | Statement: [Annenberg Center for the Performing Arts, hasSeatingType, indoor seating]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSeatingType Context triple: [Annenberg Center for the Performing Arts, hasSeatingType, indoor seating]
-
A.
hasSeating
chosen
Indicates that one entity provides or contains seating capacity or seating arrangements for another entity.
-
B.
seatingCapacity
Indicates the maximum number of people that something (typically a venue or vehicle) is designed or allowed to seat.
-
C.
hasCabinClass
Indicates that an entity (such as a booking, ticket, or seat) is associated with a specific cabin class (e.g., economy, business, first).
-
D.
seatingAddedYear
Indicates the year in which additional seating was installed or added to a venue or location.
-
E.
hasLiftType
Indicates the specific type or category of lift associated with an 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_69a24d1a97dc819094e6c021fe9b05a7 |
completed | Feb. 28, 2026, 2:04 a.m. |
| NER | Named-entity recognition | batch_69a2512ef600819084d3c627f0d534f4 |
completed | Feb. 28, 2026, 2:21 a.m. |
| PD | Predicate disambiguation | batch_69a24eb9a5ac8190b1d1300e8c4e3606 |
completed | Feb. 28, 2026, 2:11 a.m. |
Created at: Feb. 28, 2026, 2:07 a.m.