Triple

T2366884
Position Surface form Disambiguated ID Type / Status
Subject Peach Aviation E46001 entity
Predicate focusCity P164 FINISHED
Object Naha E13218 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: Naha | Statement: [Peach Aviation, focusCity, Naha]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Naha
Context triple: [Peach Aviation, focusCity, Naha]
  • A. Naha chosen
    Naha is the capital and largest city of Okinawa Prefecture in Japan, known as a major political, economic, and cultural center of the Ryukyu Islands.
  • B. Nago
    Nago is a coastal city in northern Okinawa, Japan, known for its beaches, subtropical climate, and role as a regional commercial and cultural center.
  • C. Hanam
    Hanam is a city in South Korea known for its rapid urban development and large shopping and residential complexes, located just east of Seoul in Gyeonggi Province.
  • D. Hatta
    Hatta is an Indonesian surname most prominently associated with Mohammad Hatta, the country’s first vice president and a leading figure in the struggle for independence.
  • E. Nambui
    Nambui was a Mongol empress consort of the Yuan dynasty and a prominent wife of Kublai Khan, influential in the imperial court after the death of his first empress.
  • 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_69a88a145268819083e2736cb835c696 completed March 4, 2026, 7:37 p.m.
NER Named-entity recognition batch_69abc74b6bdc8190a12b2bcaa2dd7616 completed March 7, 2026, 6:35 a.m.
NED1 Entity disambiguation (via context triple) batch_69aea89ae4688190be2e0825f0875ed3 completed March 9, 2026, 11:01 a.m.
Created at: March 4, 2026, 7:56 p.m.