Triple

T1479249
Position Surface form Disambiguated ID Type / Status
Subject Hollywood Burbank Airport E30913 entity
Predicate servesAirline P12356 FINISHED
Object Alaska Airlines E20454 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: Alaska Airlines | Statement: [Hollywood Burbank Airport, servesAirline, Alaska Airlines]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Alaska Airlines
Context triple: [Hollywood Burbank Airport, servesAirline, Alaska Airlines]
  • A. Alaska Airlines chosen
    Alaska Airlines is a major American airline based in Seattle, known for its extensive route network along the West Coast and to Alaska, Hawaii, and beyond.
  • B. Horizon Air
    Horizon Air is a regional airline in the United States that operates short-haul flights, primarily in the Pacific Northwest, as a subsidiary of Alaska Airlines.
  • C. Virgin America
    Virgin America was a U.S.-based low-cost airline known for its stylish, tech-friendly in-flight experience and West Coast–focused route network.
  • D. Alaska Air Group
    Alaska Air Group is an American airline holding company best known for owning and operating Alaska Airlines and its regional affiliates.
  • E. Frontier Airlines
    Frontier Airlines is a U.S. ultra-low-cost carrier known for its point-to-point route network, animal-themed aircraft tails, and extensive domestic service.
  • 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_69a498fe55a88190ab7f9e40ace88e49 completed March 1, 2026, 7:52 p.m.
NER Named-entity recognition batch_69a4c6739d2481909ea8d8e075f62cf3 completed March 1, 2026, 11:06 p.m.
NED1 Entity disambiguation (via context triple) batch_69aebeee5a808190981c06b78d30f004 completed March 9, 2026, 12:37 p.m.
Created at: March 1, 2026, 8:11 p.m.