Triple

T34398645
Position Surface form Disambiguated ID Type / Status
Subject Oncenter E882906 entity
Predicate hasMultipleVenues P68646 FINISHED
Object true 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: true | Statement: [Oncenter, hasMultipleVenues, true]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasMultipleVenues
Context triple: [Oncenter, hasMultipleVenues, true]
  • A. usesMultipleVenuesIn chosen
    Indicates that an entity conducts its activities or events across more than one venue within a specified location or context.
  • B. hasVenueIn
    Indicates that an event, activity, or occurrence takes place at a specific venue located within a particular geographic area or location.
  • C. numberOfVenues
    Indicates the total count of venues associated with a given entity or context.
  • D. hasVenueFor
    Indicates that one entity provides or serves as the location or setting where an event, activity, or function takes place for another entity.
  • E. usesVenues
    Indicates that one entity makes use of or operates within specific venues or locations to carry out its activities or services.
  • 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_69f349c1304081909331872829e38106 completed April 30, 2026, 12:23 p.m.
NER Named-entity recognition batch_69fdf5d05cc481909ec9e1b1f0784279 completed May 8, 2026, 2:40 p.m.
PD Predicate disambiguation batch_69fdf0cdd6948190838864ab3120dfa6 completed May 8, 2026, 2:18 p.m.
Created at: May 1, 2026, 1:59 a.m.