Triple

T1419219
Position Surface form Disambiguated ID Type / Status
Subject KLM E31984 entity
Predicate hasFocusCity P1295 FINISHED
Object Eindhoven Airport E71255 NE 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: Eindhoven Airport | Statement: [KLM, hasFocusCity, Eindhoven Airport]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Eindhoven Airport
Context triple: [KLM, hasFocusCity, Eindhoven Airport]
  • A. Eindhoven Airport chosen
    Eindhoven Airport is a major regional airport in the Netherlands that serves as a key hub for low-cost and European short-haul flights.
  • B. Rotterdam The Hague Airport
    Rotterdam The Hague Airport is a regional international airport in the Netherlands serving the cities of Rotterdam and The Hague with mainly European and holiday destinations.
  • C. Amsterdam Airport Schiphol
    Amsterdam Airport Schiphol is the main international airport of the Netherlands and one of Europe’s busiest aviation hubs for passenger and cargo traffic.
  • D. Maastricht Aachen Airport
    Maastricht Aachen Airport is a regional international airport in the southeastern Netherlands serving the cities of Maastricht and Aachen and the surrounding Limburg region.
  • E. Brussels Airport
    Brussels Airport is the main international airport serving Brussels and one of Belgium’s busiest air transport hubs for passengers and cargo.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69a49919a994819086528951bc224775 completed March 1, 2026, 7:52 p.m.
NER Named-entity recognition batch_69a4c40631e881909ddf81a2eb84af1c completed March 1, 2026, 10:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad0e6a09bc8190a9c67ec42c187340 completed March 8, 2026, 5:51 a.m.
Created at: March 1, 2026, 7:59 p.m.