Triple
T7943575
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Knebworth Park 1996 |
E184445
|
entity |
| Predicate | ticketsSold |
P79948
|
FINISHED |
| Object | approximately 250000 |
—
|
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 250000 | Statement: [Knebworth Park 1996, ticketsSold, approximately 250000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ticketsSold Context triple: [Knebworth Park 1996, ticketsSold, approximately 250000]
-
A.
ticketDemand
Indicates that there is a level of desire or need among potential buyers for tickets to an event, service, or offering.
-
B.
sellsTicketsUnder
Indicates that one entity sells tickets at a price lower than or under the pricing of another entity.
-
C.
ticketRevenueModel
Indicates the method or structure by which revenue is generated from ticket sales.
-
D.
ticketingProduct
Indicates a relationship where an entity is associated with, or offered as, a ticketing-related product (such as a service or item used for issuing, managing, or selling tickets).
-
E.
ticketFormat
Indicates the specific structure, layout, or template in which a ticket is represented or issued.
- 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_69ca8291c2008190b1b8832c87814bcf |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb3b0d31548190af54a2f3bbb8cad3 |
completed | March 31, 2026, 3:10 a.m. |
| PD | Predicate disambiguation | batch_69cae93526d081909303265bf60419fd |
completed | March 30, 2026, 9:20 p.m. |
| PDg | Predicate description generation | batch_69caf788db1c8190839523e7777961d6 |
completed | March 30, 2026, 10:22 p.m. |
Created at: March 30, 2026, 5:09 p.m.