Triple

T9913169
Position Surface form Disambiguated ID Type / Status
Subject Airport 1975 E185797 entity
Predicate follows P134 FINISHED
Object Airport E320881 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: Airport | Statement: [Airport 1975, follows, Airport]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Airport
Context triple: [Airport 1975, follows, Airport]
  • A. Airport chosen
    "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. 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.
  • C. 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.
  • D. Aeroport
    Aeroport is a Moscow Metro station on the Zamoskvoretskaya Line, named after the nearby Khodynka Aerodrome area.
  • E. Airport Department
    The Airport Department is a specialized division within the Civil Aviation Administration of China responsible for overseeing the planning, construction, management, and regulation of civil airports across the country.
  • 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_69ca829b45f481909040f7b99a1976ed completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cdb53a300481909d917e487d8aab56 completed April 2, 2026, 12:15 a.m.
NED1 Entity disambiguation (via context triple) batch_69d20dcbf28c8190aa9f6a8be423670a completed April 5, 2026, 7:22 a.m.
Created at: March 30, 2026, 8:41 p.m.