Triple

T7856455
Position Surface form Disambiguated ID Type / Status
Subject Benazir Bhutto International Airport E182386 entity
Predicate associatedWithAirline P41156 FINISHED
Object Airblue E276920 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: Airblue | Statement: [Benazir Bhutto International Airport, associatedWithAirline, Airblue]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Airblue
Context triple: [Benazir Bhutto International Airport, associatedWithAirline, Airblue]
  • A. Airblue chosen
    Airblue is a Pakistani low-cost airline that operates domestic and international flights, with a primary base at Jinnah International Airport in Karachi.
  • B. Blue Air
    Blue Air is a Romanian low-cost airline that operated scheduled passenger flights across Europe.
  • C. SkyUp Airlines
    SkyUp Airlines is a Ukrainian low-cost carrier known for operating domestic and international flights across Europe, the Middle East, and other regions.
  • D. West Air
    West Air is a Chinese low-cost airline based in Chongqing that operates domestic and regional passenger services.
  • E. Spring Airlines
    Spring Airlines is a Chinese low-cost carrier headquartered in Shanghai, known for operating budget-friendly domestic and regional flights, particularly within East Asia.
  • 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_69ca82887fd48190975896bf38c4596b completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cb1a75de548190af5653409a3b3881 completed March 31, 2026, 12:51 a.m.
NED1 Entity disambiguation (via context triple) batch_69cb5b2e2980819083369668938bae9c completed March 31, 2026, 5:27 a.m.
Created at: March 30, 2026, 4:52 p.m.