Triple

T13381966
Position Surface form Disambiguated ID Type / Status
Subject Education City Stadium E319338 entity
Predicate seatsDonationPurpose P109703 FINISHED
Object stadiums in developing countries 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: stadiums in developing countries | Statement: [Education City Stadium, seatsDonationPurpose, stadiums in developing countries]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: seatsDonationPurpose
Context triple: [Education City Stadium, seatsDonationPurpose, stadiums in developing countries]
  • A. VoxSeats
    Indicates a relationship where specific seats are associated with or designated for vocal performers or voice-related roles within a venue or arrangement.
  • B. seatOrDomain
    Indicates a relationship where something serves as, or is associated with, the primary location, base, or jurisdictional area (seat or domain) of an entity.
  • C. seatIs
    Indicates that one entity functions as the seat or seating position of another entity.
  • D. otherSeat
    Indicates that one entity is the alternative or different seat relative to another seat in a given context.
  • E. individualSeats
    Indicates that an entity provides or consists of separate, single-person seating positions rather than shared or bench-style seating.
  • 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_69d806b886bc8190b676e7768b8e01c5 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69dadce694788190881d1feac5b75720 completed April 11, 2026, 11:44 p.m.
PD Predicate disambiguation batch_69d9a03189908190a784a2755f8d81e1 completed April 11, 2026, 1:13 a.m.
PDg Predicate description generation batch_69dadcce5a808190847f2a7833b67a5a completed April 11, 2026, 11:44 p.m.
Created at: April 9, 2026, 9:33 p.m.