Triple
T14928092
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ameris Bank Amphitheatre |
E372183
|
entity |
| Predicate | hasReservedSeatingCapacity |
P2491
|
FINISHED |
| Object | approximately 5000 |
—
|
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: approximately 5000 | Statement: [Ameris Bank Amphitheatre, hasReservedSeatingCapacity, approximately 5000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasReservedSeatingCapacity Context triple: [Ameris Bank Amphitheatre, hasReservedSeatingCapacity, approximately 5000]
-
A.
hasReservedSeats
Indicates that specific seats have been set aside or allocated in advance for a particular entity or purpose.
-
B.
seatingCapacity
chosen
Indicates the maximum number of people that something (typically a venue or vehicle) is designed or allowed to seat.
-
C.
hasSeatingCapacityCategory
Indicates the classification of an entity based on the range or category of how many people it can seat.
-
D.
hasPrioritySeating
Indicates that one entity provides or designates reserved or preferential seating for another entity.
-
E.
individualSeats
Indicates that an entity provides or consists of separate, single-person seating positions rather than shared or bench-style seating.
- 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_69d85cc9da0c81908d583ca3f63a3908 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded634e67881909daec9eaef188d09 |
completed | April 15, 2026, 12:05 a.m. |
| PD | Predicate disambiguation | batch_69de9a52ba988190a26e268b4ea083ea |
completed | April 14, 2026, 7:49 p.m. |
Created at: April 10, 2026, 2:35 a.m.