Triple

T6938262
Position Surface form Disambiguated ID Type / Status
Subject Henri Coandă International Airport E160605 entity
Predicate focusCityFor P164 FINISHED
Object Blue Air E317407 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: Blue Air | Statement: [Henri Coandă International Airport, focusCityFor, Blue Air]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Blue Air
Context triple: [Henri Coandă International Airport, focusCityFor, Blue Air]
  • A. Blue Air chosen
    Blue Air is a Romanian low-cost airline that operated scheduled passenger flights across Europe.
  • B. Flying Blue
    Flying Blue is the joint frequent flyer loyalty program of Air France–KLM and partner airlines, offering members miles, elite status levels, and travel-related rewards.
  • C. Airblue
    Airblue is a Pakistani low-cost airline that operates domestic and international flights, with a primary base at Jinnah International Airport in Karachi.
  • D. Edelweiss Air
    Edelweiss Air is a Swiss leisure airline based in Zurich that operates holiday and charter flights to vacation destinations worldwide.
  • E. Flair Airlines
    Flair Airlines is a Canadian ultra-low-cost carrier that operates domestic and select international flights, emphasizing budget-friendly travel options.
  • 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_69c6884f3db4819080ad65da69386206 completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6da62d2f88190968d3fea538a95c9 completed March 27, 2026, 7:28 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7515509148190b5739cdf8cd7a28a completed March 28, 2026, 3:56 a.m.
Created at: March 27, 2026, 2:28 p.m.