Triple

T9667803
Position Surface form Disambiguated ID Type / Status
Subject Haikou Meilan International Airport E233748 entity
Predicate hasHubAirline P423 FINISHED
Object Lucky Air E637091 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: Lucky Air | Statement: [Haikou Meilan International Airport, hasHubAirline, Lucky Air]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lucky Air
Context triple: [Haikou Meilan International Airport, hasHubAirline, Lucky Air]
  • A. Lucky Air chosen
    Lucky Air is a Chinese low-cost airline based in Yunnan Province that operates domestic and regional flights across China and nearby countries.
  • B. Buddha Air
    Buddha Air is a prominent Nepalese domestic airline known for operating scheduled flights and mountain sightseeing tours, particularly around the Himalayas.
  • C. Loong Air
    Loong Air is a Chinese passenger and cargo airline based in Hangzhou that operates domestic and regional routes across Asia.
  • D. Malindo Air
    Malindo Air is a Malaysian hybrid full-service and low-cost airline that became the first operator of the Boeing 737 MAX 8.
  • E. Akasa Air
    Akasa Air is an Indian low-cost airline that began operations in 2022, offering domestic flights with a focus on affordable fares and a modern fleet.
  • 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_69ca848d3b6c8190ae98ea554dea58df completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd9c3c06e4819080c1b8e66faa482f completed April 1, 2026, 10:29 p.m.
NED1 Entity disambiguation (via context triple) batch_69d18a208798819088db055e44d288e3 completed April 4, 2026, 10:01 p.m.
Created at: March 30, 2026, 8:15 p.m.