Triple

T7721242
Position Surface form Disambiguated ID Type / Status
Subject Miyako Airport E175015 entity
Predicate connectsTo P845 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: [Miyako Airport, connectsTo, Naha]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Naha
Context triple: [Miyako Airport, connectsTo, 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. Naha Port
    Naha Port is a major seaport in Naha, Okinawa, serving as a key hub for passenger ferries, cargo shipping, and cruise ships in Japan’s Ryukyu Islands.
  • 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_69c6995d541c81909eaa646b1a8369a9 completed March 27, 2026, 2:51 p.m.
NER Named-entity recognition batch_69c702f0366c8190a78f0b03f090fc2c completed March 27, 2026, 10:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8b517c64881908d24e8613dc33bf4 completed March 29, 2026, 5:13 a.m.
Created at: March 27, 2026, 4:05 p.m.