Triple

T10181192
Position Surface form Disambiguated ID Type / Status
Subject Bournemouth Airport E236784 entity
Predicate operator P179 FINISHED
Object Regional & City Airports E787199 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: Regional & City Airports | Statement: [Bournemouth Airport, operator, Regional & City Airports]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Regional & City Airports
Context triple: [Bournemouth Airport, operator, Regional & City Airports]
  • A. Regional & City Airports chosen
    Regional & City Airports is a UK-based airport management company that owns and operates a portfolio of regional airports and related aviation services.
  • B. Airports of Regions
    Airports of Regions is a Russian airport management company that operates and develops several regional airports across Russia.
  • C. Range Regional Airport
    Range Regional Airport is a public airport serving the city of Hibbing and the surrounding Iron Range region in northern Minnesota.
  • D. Metropolitan Airport
    Metropolitan Airport was the former name of Van Nuys Airport, a major general aviation airport in the Los Angeles area.
  • E. RegionsAir
    RegionsAir was a small U.S. regional airline that operated feeder and commuter flights under codeshare agreements with major carriers.
  • 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_69ca84d7260c8190bfbec36762943f37 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cded315f14819085727bd9b4363d10 completed April 2, 2026, 4:14 a.m.
NED1 Entity disambiguation (via context triple) batch_69d301373a008190b8d39a8db4167e4f completed April 6, 2026, 12:41 a.m.
Created at: March 30, 2026, 9:11 p.m.