Triple

T21355167
Position Surface form Disambiguated ID Type / Status
Subject Stuart Gilmore E526600 entity
Predicate notableWork P4 FINISHED
Object Airport NE NERFINISHED

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: Airport | Statement: [Stuart Gilmore, notableWork, Airport]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Airport
Context triple: [Stuart Gilmore, notableWork, Airport]
  • A. 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.
  • B. Airport chosen
    "Airport" is a 1970 American disaster-drama film, based on Arthur Hailey's novel, that helped launch the popular 1970s disaster movie genre.
  • C. Terminal Aérea
    Terminal Aérea is a Mexico City Metro station that serves the area around the Mexico City International Airport, providing convenient transit access for air travelers.
  • D. Airport Sector
    Airport Sector is a specialized unit of the Central Industrial Security Force (CISF) responsible for providing security and protection at airports across India.
  • E. Aeroport
    Aeroport is a Moscow Metro station on the Zamoskvoretskaya Line, named after the nearby Khodynka Aerodrome area.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b51cd5cc81909ac1187971e8a8ad completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e8af9be3a48190aa8e6e9a5b812981 completed April 22, 2026, 11:23 a.m.
Created at: April 16, 2026, 5:06 p.m.