Triple

T3854445
Position Surface form Disambiguated ID Type / Status
Subject Tabua Club E85377 entity
Predicate hasTier P2393 FINISHED
Object Tabua Club Corporate E85377 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: Tabua Club Corporate | Statement: [Tabua Club, hasTier, Tabua Club Corporate]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tabua Club Corporate
Context triple: [Tabua Club, hasTier, Tabua Club Corporate]
  • A. Tabua Club chosen
    Tabua Club is Fiji Airways’ frequent flyer program offering members benefits such as mileage accrual, flight rewards, and travel privileges.
  • B. United Club
    United Club is United Airlines’ network of airport lounges offering travelers comfortable seating, complimentary snacks and drinks, workspaces, and other amenities in airports worldwide.
  • C. Asiana Club
    Asiana Club is the loyalty program of Asiana Airlines that rewards members with mileage points and tier benefits for flying and partner activities.
  • D. Hatta Club
    Hatta Club is a professional football club based in Hatta, United Arab Emirates, competing in the country’s top-tier league system.
  • E. Abha Club
    Abha Club is a professional football team based in Abha, Saudi Arabia, that competes in the country’s top-tier league system.
  • 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_69aed936de1c81908f91bed80f70abb2 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aeec0438308190865ff74bee5a1cf2 completed March 9, 2026, 3:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5041c7250819093b2743afeb6e36c completed March 14, 2026, 6:45 a.m.
Created at: March 9, 2026, 3:19 p.m.