Triple

T9381102
Position Surface form Disambiguated ID Type / Status
Subject GLA E225784 entity
Predicate operatedBy P86 FINISHED
Object AGS Airports E225786 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: AGS Airports | Statement: [GLA, operatedBy, AGS Airports]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: AGS Airports
Context triple: [GLA, operatedBy, AGS Airports]
  • A. AGS Airports chosen
    AGS Airports is a UK-based airport management company that owns and operates several regional airports in Scotland and England.
  • B. Aeroport
    Aeroport is a Moscow Metro station on the Zamoskvoretskaya Line, named after the nearby Khodynka Aerodrome area.
  • C. Airport
    "Airport" is the musical score composed by Alfred Newman for the 1970 disaster film of the same name, noted for its dramatic orchestral themes that underscore the movie’s tension and romance.
  • D. Airports of Regions
    Airports of Regions is a Russian airport management company that operates and develops several regional airports across Russia.
  • E. Flughafen
    Flughafen is the Nuremberg U-Bahn station that serves Nuremberg Airport, providing direct metro access between the airport and the city.
  • 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_69ca842e9dcc8190a264119e683cfe04 completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd50be52248190bc7cd9deb95a1ef8 completed April 1, 2026, 5:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69d0f4311a548190885d82167199221b completed April 4, 2026, 11:21 a.m.
Created at: March 30, 2026, 7:44 p.m.