Triple

T2521663
Position Surface form Disambiguated ID Type / Status
Subject The Big House E55535 entity
Predicate seatingCapacityRank P31373 FINISHED
Object one of the largest stadiums in the world 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: one of the largest stadiums in the world | Statement: [The Big House, seatingCapacityRank, one of the largest stadiums in the world]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: seatingCapacityRank
Context triple: [The Big House, seatingCapacityRank, one of the largest stadiums in the world]
  • A. seatingCapacity
    Indicates the maximum number of people that something (typically a venue or vehicle) is designed or allowed to seat.
  • B. capacityRank chosen
    Indicates the relative ordering of entities based on how much capacity (e.g., volume, throughput, or capability) they possess compared to others.
  • C. audienceCapacityType
    Indicates the classification or type of capacity used to describe how many audience members a venue or event space can accommodate.
  • D. hasSeating
    Indicates that one entity provides or contains seating capacity or seating arrangements for another entity.
  • E. seatCategory
    Indicates the classification or type of a seat (e.g., by comfort level, price tier, or section) assigned to an entity.
  • 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_69ab49e4749c8190813311efd1630f1b completed March 6, 2026, 9:40 p.m.
NER Named-entity recognition batch_69abd23895348190bb4dad6d7174893a completed March 7, 2026, 7:22 a.m.
PD Predicate disambiguation batch_69abd0c144b0819092f32a13c1d127e5 completed March 7, 2026, 7:16 a.m.
Created at: March 6, 2026, 9:46 p.m.