Triple

T718026
Position Surface form Disambiguated ID Type / Status
Subject Fiji Airways E14352 entity
Predicate hub P423 FINISHED
Object Nadi International Airport E69389 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: Nadi International Airport | Statement: [Fiji Airways, hub, Nadi International Airport]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nadi International Airport
Context triple: [Fiji Airways, hub, Nadi International Airport]
  • A. Nadi International Airport chosen
    Nadi International Airport is Fiji’s main international gateway and busiest airport, serving as the primary hub for international flights to and from the country.
  • B. Suvarnabhumi Airport
    Suvarnabhumi Airport is Bangkok’s main international airport and one of Southeast Asia’s busiest aviation hubs.
  • C. Don Mueang International Airport
    Don Mueang International Airport is one of Bangkok’s main airports and a major hub for low-cost carriers serving domestic and regional flights in Thailand and Southeast Asia.
  • D. Juanda International Airport
    Juanda International Airport is a major international airport serving the city of Surabaya and the surrounding East Java region in Indonesia.
  • E. Mitiga International Airport
    Mitiga International Airport is a major airport serving Tripoli, Libya, handling both domestic and international flights.
  • 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_69a4934a36e081909e7abef98b898a4e completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4a577658881909c12951d63d96377 completed March 1, 2026, 8:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69a66d936bbc81908708ee5d0fc82100 completed March 3, 2026, 5:11 a.m.
Created at: March 1, 2026, 7:37 p.m.