Triple

T11055348
Position Surface form Disambiguated ID Type / Status
Subject MMMY E261359 entity
Predicate hasPassengerTerminal P1297 FINISHED
Object Terminal A unclear NED1 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: Terminal A | Statement: [MMMY, hasPassengerTerminal, Terminal A]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Terminal A
Context triple: [MMMY, hasPassengerTerminal, Terminal A]
  • A. Terminal A
    Terminal A was one of the original passenger terminals at Shenzhen Bao’an International Airport, later decommissioned and demolished as the airport expanded and modernized its facilities.
  • B. Terminal A
    Terminal A is one of the passenger terminals at Hannover Airport in Germany, serving airline check-in, departures, and arrivals operations.
  • C. Terminal A
    Terminal A is one of the main passenger terminals at Newark Liberty International Airport, serving as a hub for various domestic and regional airline operations.
  • D. Terminal A
    Terminal A is one of the passenger terminals at Hollywood Burbank Airport, serving as a primary facility for airline check-in, security screening, and boarding.
  • E. Terminal A
    Terminal A is a passenger terminal at Volgograd International Airport in Russia, serving as one of the airport’s main facilities for handling flights and travelers.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide. chosen

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_69d6aa98650481908609c7c56bfa7902 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d798a152b4819095b74a8996346077 completed April 9, 2026, 12:16 p.m.
NED1 Entity disambiguation (via context triple) batch_69e3c86e0e6481908f091497313132c1 completed April 18, 2026, 6:07 p.m.
Created at: April 8, 2026, 9:26 p.m.