Triple

T6422688
Position Surface form Disambiguated ID Type / Status
Subject KPHL E127981 entity
Predicate hasTerminal P182 FINISHED
Object Terminal F E134081 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 F | Statement: [KPHL, hasTerminal, Terminal F]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Terminal F
Context triple: [KPHL, hasTerminal, Terminal F]
  • A. Terminal F
    Terminal F is one of the passenger terminals at Sheremetyevo International Airport in Moscow, primarily serving international flights and offering a range of traveler services and facilities.
  • B. Terminal F chosen
    Terminal F is a regional commuter terminal at Philadelphia International Airport primarily serving short-haul and domestic flights.
  • C. Terminal F
    Terminal F is a passenger terminal at Boryspil International Airport in Ukraine, primarily used for handling charter and low-cost airline flights.
  • D. Terminal E
    Terminal E is one of the passenger terminals at Sheremetyevo International Airport in Moscow, serving international flights with modern facilities and connections to adjacent terminals.
  • E. Terminal E
    Terminal E is the international terminal at Boston Logan International Airport, serving most of the airport’s overseas flights and customs operations.
  • 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_69c00838de888190af2eec0b80495efa completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c0690576c48190b5db5464eacc9de3 completed March 22, 2026, 10:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69c640dc01188190b67290801aae0d6c completed March 27, 2026, 8:33 a.m.
Created at: March 22, 2026, 4:43 p.m.