Triple

T3356713
Position Surface form Disambiguated ID Type / Status
Subject Zurich Airport E70621 entity
Predicate passengerTrafficRankInSwitzerland P47447 FINISHED
Object 1 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: 1 | Statement: [Zurich Airport, passengerTrafficRankInSwitzerland, 1]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: passengerTrafficRankInSwitzerland
Context triple: [Zurich Airport, passengerTrafficRankInSwitzerland, 1]
  • A. passengerTrafficRankInEurope
    Indicates the relative position of an entity in Europe based on the volume of passenger traffic it handles.
  • B. passengerTrafficRankingWorld
    Indicates the relative position of an entity in a global ranking based on the volume of passenger traffic it handles.
  • C. peakPassengerTrafficRank
    Indicates the relative position of an entity in an ordered list based on the amount of passenger traffic it experiences at its peak.
  • D. chartPositionSwitzerland
    Indicates the position or ranking that something holds on a music or sales chart specifically in Switzerland.
  • E. passengerTraffic
    Indicates the flow or volume of passengers moving through or using a particular transport service, route, or facility.
  • 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_69ad85a660c48190998489309a3b4869 completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb242d4988190bbac993df587936d completed March 8, 2026, 5:30 p.m.
PD Predicate disambiguation batch_69ada42fbe7c8190b9f185b5ab985f17 completed March 8, 2026, 4:30 p.m.
PDg Predicate description generation batch_69ada52716ec81908e89688a81039394 completed March 8, 2026, 4:34 p.m.
Created at: March 8, 2026, 3:13 p.m.