Triple

T1996154
Position Surface form Disambiguated ID Type / Status
Subject Mexico City International Airport E43362 entity
Predicate hasApproximateAnnualPassengerTrafficCategory P25278 FINISHED
Object tens of millions of passengers per year 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: tens of millions of passengers per year | Statement: [Mexico City International Airport, hasApproximateAnnualPassengerTrafficCategory, tens of millions of passengers per year]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasApproximateAnnualPassengerTrafficCategory
Context triple: [Mexico City International Airport, hasApproximateAnnualPassengerTrafficCategory, tens of millions of passengers per year]
  • A. hasAnnualPassengerTrafficOver chosen
    Indicates that the subject location or transport facility experiences an annual passenger volume exceeding a specified threshold.
  • B. hasApproxAnnualPassengerUsageRank
    Indicates the approximate position or ranking of an entity based on its annual passenger usage compared to similar entities.
  • C. hasPassengerTrafficRank
    Indicates the relative position or ranking of an entity based on the volume of passenger traffic it handles compared to others.
  • D. servesPassengerTrafficType
    Indicates that a transportation facility or service accommodates a specified type or category of passenger traffic.
  • E. passengerTraffic
    Indicates the flow or volume of passengers moving through or using a particular transport service, route, or facility.
  • 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_69a88714cf2c819081644be450b8356e completed March 4, 2026, 7:25 p.m.
NER Named-entity recognition batch_69abb91055d88190a980e7b42e5895d4 completed March 7, 2026, 5:35 a.m.
PD Predicate disambiguation batch_69abb79c97d48190b3147430ed39faa9 completed March 7, 2026, 5:29 a.m.
Created at: March 4, 2026, 7:37 p.m.