Triple

T6686464
Position Surface form Disambiguated ID Type / Status
Subject Sonohyan-utaki Ishimon E152109 entity
Predicate locatedIn P40 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: [Sonohyan-utaki Ishimon, locatedIn, Naha]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Naha
Context triple: [Sonohyan-utaki Ishimon, locatedIn, 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_69c687f9977c819097e7f5ada4fe522e completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c6b14cd6748190aad4badd5f253478 completed March 27, 2026, 4:33 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7007ad59c8190a752d9b1152c3435 completed March 27, 2026, 10:11 p.m.
Created at: March 27, 2026, 2:04 p.m.