Triple

T4046290
Position Surface form Disambiguated ID Type / Status
Subject Fukuoka Airport E84073 entity
Predicate servesAirlineHub P4364 FINISHED
Object StarFlyer E186918 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: StarFlyer | Statement: [Fukuoka Airport, servesAirlineHub, StarFlyer]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: StarFlyer
Context triple: [Fukuoka Airport, servesAirlineHub, StarFlyer]
  • A. StarFlyer chosen
    StarFlyer is a Japanese airline known for its stylish black-themed aircraft and service-focused operations on domestic routes.
  • B. Fauske
    Fauske is a small Norwegian town and municipality known for its marble quarries and location in the inland part of Nordland county.
  • C. Nordwind Airlines
    Nordwind Airlines is a Russian leisure and charter airline that primarily operates holiday and tourist flights from major hubs such as Moscow.
  • D. Sky Mart
    Sky Mart is an elevated sidewalk and pedestrian walkway system in downtown Morristown, Tennessee, that connects buildings above street level.
  • E. Star Market
    Star Market is a regional supermarket chain in New England offering groceries, fresh produce, and household goods.
  • 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_69aed930bd5c819083e7dcc14fc44f69 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aefb6135b481909d2be890a2140ff9 completed March 9, 2026, 4:54 p.m.
NED1 Entity disambiguation (via context triple) batch_69b55652228c8190a9f301676deb0055 completed March 14, 2026, 12:36 p.m.
Created at: March 9, 2026, 3:37 p.m.