Triple

T11095489
Position Surface form Disambiguated ID Type / Status
Subject Polonez Lounge E262366 entity
Predicate locatedInTerminal P40 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: [Polonez Lounge, locatedInTerminal, Terminal A]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Terminal A
Context triple: [Polonez Lounge, locatedInTerminal, Terminal A]
  • A. Terminal A
    Terminal A is one of the passenger terminals at Boston Logan International Airport, serving as a hub for several domestic and international airline operations.
  • B. 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.
  • C. 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.
  • D. 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.
  • E. Terminal A
    Terminal A is one of the main passenger terminals at O. R. Tambo International Airport in Johannesburg, serving as a key hub for airline check-in, departures, and arrivals.
  • 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_69d6aa9a40d88190a373e2c7e48285db completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d79a0897188190b6c293b44990b3d4 completed April 9, 2026, 12:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69e3e7e0c7e4819098e690ffebbd8e61 completed April 18, 2026, 8:21 p.m.
Created at: April 8, 2026, 9:27 p.m.