Triple

T769062
Position Surface form Disambiguated ID Type / Status
Subject KSFO E16239 entity
Predicate hasTerminal P182 FINISHED
Object Terminal 2 E19268 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 2 | Statement: [KSFO, hasTerminal, Terminal 2]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Terminal 2
Context triple: [KSFO, hasTerminal, Terminal 2]
  • A. Terminal 2
    Terminal 2 is a major passenger terminal at Ronald Reagan Washington National Airport serving numerous domestic airline operations and traveler amenities.
  • B. Terminal 2
    Terminal 2 is one of the main passenger terminals at Manchester Airport, handling a large share of the airport’s international and domestic flights.
  • C. Terminal 2
    Terminal 2 is one of the main passenger terminals at Ontario International Airport in Southern California, serving domestic airline operations and traveler services.
  • D. Terminal 2
    Terminal 2 is one of the passenger terminals at Chicago O'Hare International Airport, serving various domestic and regional flights with multiple concourses and airline operations.
  • E. Terminal 2 chosen
    Terminal 2 is a modern, sustainably designed passenger terminal at San Francisco International Airport known for its upgraded amenities, art installations, and improved traveler experience.
  • 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_69a49369a0848190af883934cee3db4c completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4a70376988190be2826259f5281ab completed March 1, 2026, 8:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69a7a3adf1d88190acec593f0aca1ec0 completed March 4, 2026, 3:14 a.m.
Created at: March 1, 2026, 7:37 p.m.