Triple

T6368013
Position Surface form Disambiguated ID Type / Status
Subject St. John’s International Airport E143274 entity
Predicate hasHubAirline P423 FINISHED
Object PAL Airlines E514851 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: PAL Airlines | Statement: [St. John’s International Airport, hasHubAirline, PAL Airlines]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: PAL Airlines
Context triple: [St. John’s International Airport, hasHubAirline, PAL Airlines]
  • A. PAL Airlines chosen
    PAL Airlines is a Canadian regional airline that operates passenger and cargo flights primarily throughout Newfoundland and Labrador and other parts of eastern Canada.
  • B. Sky Airline
    Sky Airline is a Chilean low-cost carrier that operates domestic and regional flights across South America.
  • C. Mango Airlines
    Mango Airlines is a South African low-cost airline that operated domestic and regional flights as a budget subsidiary of South African Airways.
  • D. Rex Airlines
    Rex Airlines is an Australian regional airline that operates domestic passenger services across multiple states, connecting major cities with regional and remote communities.
  • E. Philippine Airlines
    Philippine Airlines is the flag carrier of the Philippines, operating a wide network of domestic and international flights across Asia, North America, Oceania, and beyond.
  • 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_69c008d8c61081908bcaf61510d881ed completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c068251ae48190af8201d5f9ad35b6 completed March 22, 2026, 10:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69c62d8689408190b334928df870ed29 completed March 27, 2026, 7:11 a.m.
Created at: March 22, 2026, 4:32 p.m.