Triple

T411669
Position Surface form Disambiguated ID Type / Status
Subject El Dorado International Airport E9501 entity
Predicate passengerTrafficRanking P8174 FINISHED
Object one of the busiest airports in Latin America 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 busiest airports in Latin America | Statement: [El Dorado International Airport, passengerTrafficRanking, one of the busiest airports in Latin America]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: passengerTrafficRanking
Context triple: [El Dorado International Airport, passengerTrafficRanking, one of the busiest airports in Latin America]
  • A. peakPassengerTrafficRank
    Indicates the relative position of an entity in an ordered list based on the amount of passenger traffic it experiences at its peak.
  • B. passengerTrafficRankUS
    Indicates the relative ranking of a location or facility within the United States based on the volume of passenger traffic it handles.
  • C. peakFreightTrafficRank
    Indicates the relative ranking position of an entity based on the highest level of freight traffic it experiences or handles compared to others.
  • D. hasApproxAnnualPassengerUsageRank chosen
    Indicates the approximate position or ranking of an entity based on its annual passenger usage compared to similar entities.
  • E. airportRankInFranceByTraffic
    Indicates the relative position of an airport in France when airports are ordered by the volume of passenger or cargo traffic they handle.
  • 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_69a2e80111fc8190961d5b7c6154123f completed Feb. 28, 2026, 1:05 p.m.
NER Named-entity recognition batch_69a2ed31681c8190ac32334562fb17fd completed Feb. 28, 2026, 1:27 p.m.
PD Predicate disambiguation batch_69a2e9737694819080fde9adcc1aa4d4 completed Feb. 28, 2026, 1:11 p.m.
Created at: Feb. 28, 2026, 1:09 p.m.