Triple

T1781293
Position Surface form Disambiguated ID Type / Status
Subject Eurostar E39296 entity
Predicate connectsCity P4245 FINISHED
Object Brussels Airport E36797 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: Brussels Airport | Statement: [Eurostar, connectsCity, Brussels Airport]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Brussels Airport
Context triple: [Eurostar, connectsCity, Brussels Airport]
  • A. Brussels Airport chosen
    Brussels Airport is the main international airport serving Brussels and one of Belgium’s busiest air transport hubs for passengers and cargo.
  • B. Brussels South Charleroi Airport
    Brussels South Charleroi Airport is a major low-cost international airport in Belgium, widely used by budget airlines and serving as an alternative to Brussels Airport.
  • C. Antwerp International Airport
    Antwerp International Airport is a small regional airport in Antwerp, Belgium, primarily serving short-haul European flights and general aviation.
  • D. Zaventem
    Zaventem is a municipality in the Flemish Brabant province of Belgium, best known internationally as the site of Brussels Airport.
  • E. 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.
  • 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_69a88630519c8190a17addd83c4a3ef4 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69aa64e22d6881909ba6ec120b320918 completed March 6, 2026, 5:23 a.m.
NED1 Entity disambiguation (via context triple) batch_69adc9a4ee9c8190a6cdb5df16a48711 completed March 8, 2026, 7:10 p.m.
Created at: March 4, 2026, 7:31 p.m.