Triple

T20757084
Position Surface form Disambiguated ID Type / Status
Subject EuroAirport Basel–Mulhouse–Freiburg E510876 entity
Predicate hasPassengerTerminalSector P141382 FINISHED
Object French sector 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: French sector | Statement: [EuroAirport Basel–Mulhouse–Freiburg, hasPassengerTerminalSector, French sector]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasPassengerTerminalSector
Context triple: [EuroAirport Basel–Mulhouse–Freiburg, hasPassengerTerminalSector, French sector]
  • A. hasPassengerTerminal
    Indicates that one entity possesses or is equipped with a passenger terminal used for boarding, alighting, or handling passengers.
  • B. hasPassengerTerminalFunction
    Indicates that something serves the role or performs the function of a passenger terminal, supporting the handling and movement of passengers.
  • C. hasPassengerTerminalFacilities
    Indicates that an entity provides facilities or infrastructure specifically intended for handling and serving passengers.
  • D. hasPassengerTerminalDesign
    Indicates a design relationship in which one entity specifies or defines the passenger terminal layout, structure, or configuration of another entity.
  • E. hasNumberOfPassengerTerminalsAtAirport
    Indicates the relationship that specifies how many passenger terminals are present at a given airport.
  • 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_69e0b4c909ec8190b05987f1639513f6 completed April 16, 2026, 10:07 a.m.
NER Named-entity recognition batch_69e6c23113c88190a567c3a098cf7552 completed April 21, 2026, 12:17 a.m.
PD Predicate disambiguation batch_69e5c0509608819080cdbf47fcddfe36 completed April 20, 2026, 5:57 a.m.
PDg Predicate description generation batch_69e5c3cbe5788190b7ace43bfdac2ef6 completed April 20, 2026, 6:12 a.m.
Created at: April 16, 2026, 12:35 p.m.