Triple

T11907933
Position Surface form Disambiguated ID Type / Status
Subject Harambe Theatre E283317 entity
Predicate ticketModel P102292 FINISHED
Object included with park admission 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: included with park admission | Statement: [Harambe Theatre, ticketModel, included with park admission]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: ticketModel
Context triple: [Harambe Theatre, ticketModel, included with park admission]
  • A. ticketSystem
    Indicates a relationship where an entity is managed, tracked, or processed through a ticket-based system for handling requests, issues, or tasks.
  • B. ticket
    Indicates that an entity serves as or is associated with a ticket, typically representing authorization, access, or a record for an event, service, or transaction.
  • C. ticketOfTarget
    Indicates that one entity is a ticket associated with, or issued for, a specific target entity.
  • D. ticketRevenueModel
    Indicates the method or structure by which revenue is generated from ticket sales.
  • E. ticketTypeExample
    Indicates that an entity serves as an example or illustrative instance of a particular ticket type.
  • 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_69d6ab2c07e88190ba13b0d21fd6cf33 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d8e5264b2081909bda6c24abb89725 completed April 10, 2026, 11:55 a.m.
PD Predicate disambiguation batch_69d8bb3632ac8190b13e53c2b5db7125 completed April 10, 2026, 8:56 a.m.
PDg Predicate description generation batch_69d8dd0ba0f88190b7d5e358c27ca184 completed April 10, 2026, 11:20 a.m.
Created at: April 8, 2026, 9:44 p.m.