Triple
T17197858
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zilker Hillside Theater |
E417398
|
entity |
| Predicate | audienceSeatingType |
P2608
|
FINISHED |
| Object | bring-your-own-blanket 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: bring-your-own-blanket seating | Statement: [Zilker Hillside Theater, audienceSeatingType, bring-your-own-blanket seating]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: audienceSeatingType Context triple: [Zilker Hillside Theater, audienceSeatingType, bring-your-own-blanket seating]
-
A.
hasBoxSeating
Indicates that an entity provides or includes box seating as a type of seating arrangement.
-
B.
hasSeating
chosen
Indicates that one entity provides or contains seating capacity or seating arrangements for another entity.
-
C.
audienceCapacityType
Indicates the classification or type of capacity used to describe how many audience members a venue or event space can accommodate.
-
D.
seatCategory
Indicates the classification or type of a seat (e.g., by comfort level, price tier, or section) assigned to an entity.
-
E.
seatingCapacity
Indicates the maximum number of people that something (typically a venue or vehicle) is designed or allowed to seat.
- 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_69d886d6ba8c819093215917b3d01689 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e42dab718c8190b6f5b08189cf2eb2 |
completed | April 19, 2026, 1:19 a.m. |
| PD | Predicate disambiguation | batch_69e383141ae0819096acd71683637cbc |
completed | April 18, 2026, 1:11 p.m. |
Created at: April 10, 2026, 5:38 a.m.