Triple

T9435575
Position Surface form Disambiguated ID Type / Status
Subject Louis Armstrong Stadium E227495 entity
Predicate seatingCapacityNightSessions P88896 FINISHED
Object approximately 10000 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 10000 | Statement: [Louis Armstrong Stadium, seatingCapacityNightSessions, approximately 10000]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: seatingCapacityNightSessions
Context triple: [Louis Armstrong Stadium, seatingCapacityNightSessions, approximately 10000]
  • A. numberOfSittings
    Indicates the total count of distinct sittings or sessions associated with an entity or event.
  • B. audienceCapacityType
    Indicates the classification or type of capacity used to describe how many audience members a venue or event space can accommodate.
  • C. seatingCapacity
    Indicates the maximum number of people that something (typically a venue or vehicle) is designed or allowed to seat.
  • D. typicalSeatingCapacityUpperBound
    Indicates the maximum number of seats that a venue or vehicle is typically designed or allowed to accommodate under normal conditions.
  • E. typicalSeatingCapacityLowerBound
    Indicates the minimum number of seats that an entity is typically designed or expected to provide.
  • 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_69ca8437a7ac81908651de48f2d2141d completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd7e64109081908222f590928bc572 completed April 1, 2026, 8:21 p.m.
PD Predicate disambiguation batch_69cca55548488190b171ae695a3212de completed April 1, 2026, 4:55 a.m.
PDg Predicate description generation batch_69cca89b3368819087a3d69270c1f185 completed April 1, 2026, 5:09 a.m.
Created at: March 30, 2026, 7:50 p.m.