Triple

T4287544
Position Surface form Disambiguated ID Type / Status
Subject ATR 72 E97304 entity
Predicate operator P179 FINISHED
Object Bangkok Airways E298802 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: Bangkok Airways | Statement: [ATR 72, operator, Bangkok Airways]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bangkok Airways
Context triple: [ATR 72, operator, Bangkok Airways]
  • A. Bangkok Airways chosen
    Bangkok Airways is a regional airline based in Thailand that operates scheduled services across Asia, often marketing itself as a boutique carrier with full-service amenities.
  • B. Nok Air
    Nok Air is a Thai low-cost airline based in Bangkok that primarily operates domestic flights and is known for its brightly painted, bird-themed aircraft.
  • C. Thai AirAsia
    Thai AirAsia is a Thai low-cost airline operating domestic and international flights, and is part of the wider AirAsia group based in Southeast Asia.
  • D. Thai Airways International
    Thai Airways International is the flag carrier airline of Thailand, operating an extensive network of domestic and international flights from its main hub in Bangkok.
  • E. EVA Air
    EVA Air is a major Taiwanese international airline known for its extensive global route network, high service standards, and innovative themed flights such as its Hello Kitty jets.
  • 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_69b3454595848190a0e6bbb6a2bea040 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b3505ef9fc81909c73e64bf77052ce completed March 12, 2026, 11:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5c72bec388190b03048507e2e6858 completed March 14, 2026, 8:38 p.m.
Created at: March 12, 2026, 11:08 p.m.